Training_HLF_Classifier/TensorFlow_Keras_HLF_with_Pandas_Parquet.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Traininig of the High Level Feature classifier with TensorFlow/Keras\n",
    "\n",
    "**Tensorflow/Keras, HLF classifier** This notebooks trains a dense neural network for a particle classifier using High Level Features. It uses TensorFlow/Keras on a single node. Pandas is used to read the data and pass it to TensorFlow via numpy arrays.\n",
    "\n",
    "Credits: this notebook is part of the work: \n",
    "- [Machine Learning Pipelines with Modern Big Data Tools for High Energy Physics Comput Softw Big Sci 4, 8 (2020)](https://rdcu.be/b4Wk9)  \n",
    "- Code and data at:https://github.com/cerndb/SparkDLTrigger\n",
    "- The model is a classifier implemented as a DNN\n",
    "  - Model input: 14 \"high level features\", described in [ Topology classification with deep learning to improve real-time event selection at the LHC](https://link.springer.com/epdf/10.1007/s41781-019-0028-1?author_access_token=eTrqfrCuFIP2vF4nDLnFfPe4RwlQNchNByi7wbcMAY7NPT1w8XxcX1ECT83E92HWx9dJzh9T9_y5Vfi9oc80ZXe7hp7PAj21GjdEF2hlNWXYAkFiNn--k5gFtNRj6avm0UukUt9M9hAH_j4UR7eR-g%3D%3D)\n",
    "  - Model output: 3 classes, \"W + jet\", \"QCD\", \"$t\\bar{t}$\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load train and test datasets via Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Download the datasets from \n",
    "# ** https://github.com/cerndb/SparkDLTrigger/tree/master/Data **\n",
    "#\n",
    "# For CERN users, data is already available on EOS\n",
    "PATH = \"/eos/project/s/sparkdltrigger/public/\"\n",
    "\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "testPDF = pd.read_parquet(path= PATH + 'testUndersampled_HLF_features.parquet', \n",
    "                          columns=['HLF_input', 'encoded_label'])\n",
    "\n",
    "trainPDF = pd.read_parquet(path= PATH + 'trainUndersampled_HLF_features.parquet', \n",
    "                           columns=['HLF_input', 'encoded_label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are HLF_input        856090\n",
      "encoded_label    856090\n",
      "dtype: int64 events in the test dataset\n",
      "There are HLF_input        3426083\n",
      "encoded_label    3426083\n",
      "dtype: int64 events in the train dataset\n"
     ]
    }
   ],
   "source": [
    "# Check the number of events in the train and test datasets\n",
    "\n",
    "num_test = testPDF.count()\n",
    "num_train = trainPDF.count()\n",
    "\n",
    "print('There are {} events in the test dataset'.format(num_test))\n",
    "print('There are {} events in the train dataset'.format(num_train))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>HLF_input</th>\n",
       "      <th>encoded_label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[0.015150733133517018, 0.003511028294205839, 0...</td>\n",
       "      <td>[1.0, 0.0, 0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[0.0, 0.003881822832783805, 0.7166341448458555...</td>\n",
       "      <td>[1.0, 0.0, 0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[0.009639073600865505, 0.0010022659022912096, ...</td>\n",
       "      <td>[1.0, 0.0, 0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[0.016354407625436572, 0.002108937905084598, 0...</td>\n",
       "      <td>[1.0, 0.0, 0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[0.01925979125354152, 0.004603697276827594, 0....</td>\n",
       "      <td>[1.0, 0.0, 0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>856085</th>\n",
       "      <td>[0.020383967386165446, 0.0022348975484913444, ...</td>\n",
       "      <td>[0.0, 1.0, 0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>856086</th>\n",
       "      <td>[0.02475209699743233, 0.00867502196073073, 0.3...</td>\n",
       "      <td>[0.0, 1.0, 0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>856087</th>\n",
       "      <td>[0.03498179428310887, 0.02506331737284528, 0.9...</td>\n",
       "      <td>[0.0, 1.0, 0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>856088</th>\n",
       "      <td>[0.03735147362869153, 0.003645269183639405, 0....</td>\n",
       "      <td>[0.0, 1.0, 0.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>856089</th>\n",
       "      <td>[0.04907273976147946, 0.003058462073646085, 0....</td>\n",
       "      <td>[0.0, 1.0, 0.0]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>856090 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                HLF_input    encoded_label\n",
       "0       [0.015150733133517018, 0.003511028294205839, 0...  [1.0, 0.0, 0.0]\n",
       "1       [0.0, 0.003881822832783805, 0.7166341448458555...  [1.0, 0.0, 0.0]\n",
       "2       [0.009639073600865505, 0.0010022659022912096, ...  [1.0, 0.0, 0.0]\n",
       "3       [0.016354407625436572, 0.002108937905084598, 0...  [1.0, 0.0, 0.0]\n",
       "4       [0.01925979125354152, 0.004603697276827594, 0....  [1.0, 0.0, 0.0]\n",
       "...                                                   ...              ...\n",
       "856085  [0.020383967386165446, 0.0022348975484913444, ...  [0.0, 1.0, 0.0]\n",
       "856086  [0.02475209699743233, 0.00867502196073073, 0.3...  [0.0, 1.0, 0.0]\n",
       "856087  [0.03498179428310887, 0.02506331737284528, 0.9...  [0.0, 1.0, 0.0]\n",
       "856088  [0.03735147362869153, 0.003645269183639405, 0....  [0.0, 1.0, 0.0]\n",
       "856089  [0.04907273976147946, 0.003058462073646085, 0....  [0.0, 1.0, 0.0]\n",
       "\n",
       "[856090 rows x 2 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the schema and a data sample of the test dataset\n",
    "testPDF\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert training and test datasets from Pandas DataFrames to Numpy arrays\n",
    "\n",
    "Now we will collect and convert the Pandas DataFrame into numpy arrays in order to be able to feed them to TensorFlow/Keras.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "X = np.stack(trainPDF[\"HLF_input\"])\n",
    "y = np.stack(trainPDF[\"encoded_label\"])\n",
    "\n",
    "X_test = np.stack(testPDF[\"HLF_input\"])\n",
    "y_test = np.stack(testPDF[\"encoded_label\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create the Keras model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-11 20:18:42.557581: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
      "2024-06-11 20:18:42.762533: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
      "To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2024-06-11 20:18:46.382238: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'2.16.1'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-11 20:18:49.166736: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "2024-06-11 20:18:49.311462: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "2024-06-11 20:18:49.311842: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check that we have a GPU available\n",
    "tf.config.list_physical_devices('GPU')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/cvmfs/sft-nightlies.cern.ch/lcg/views/dev3cuda/Tue/x86_64-centos7-gcc11-opt/lib/python3.9/site-packages/keras/src/layers/core/dense.py:87: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
      "  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n",
      "2024-06-11 20:18:49.372989: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "2024-06-11 20:18:49.373359: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "2024-06-11 20:18:49.373617: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "2024-06-11 20:18:49.460189: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "2024-06-11 20:18:49.460520: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "2024-06-11 20:18:49.460809: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
      "2024-06-11 20:18:49.460982: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1928] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 12958 MB memory:  -> device: 0, name: Tesla T4, pci bus id: 0000:00:07.0, compute capability: 7.5\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, Activation\n",
    "\n",
    "def create_model(nh_1, nh_2, nh_3):\n",
    "    ## Create model\n",
    "    model = Sequential()\n",
    "    model.add(Dense(nh_1, input_shape=(14,), activation='relu'))\n",
    "    model.add(Dense(nh_2, activation='relu'))\n",
    "    model.add(Dense(nh_3, activation='relu'))\n",
    "    model.add(Dense(3, activation='softmax'))\n",
    "    \n",
    "    ## Compile model\n",
    "    optimizer = 'Adam'\n",
    "    loss = 'categorical_crossentropy'\n",
    "    model.compile(loss=loss, optimizer=optimizer, metrics=[\"accuracy\"])\n",
    "    \n",
    "    return model\n",
    "\n",
    "keras_model = create_model(50,20,10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
      "I0000 00:00:1718129932.860451    5556 service.cc:145] XLA service 0x7f8a3c0035e0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:\n",
      "I0000 00:00:1718129932.860521    5556 service.cc:153]   StreamExecutor device (0): Tesla T4, Compute Capability 7.5\n",
      "2024-06-11 20:18:52.903608: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:268] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.\n",
      "2024-06-11 20:18:53.108280: I external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:465] Loaded cuDNN version 8907\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m   82/26767\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m50s\u001b[0m 2ms/step - accuracy: 0.4609 - loss: 1.0649  "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "I0000 00:00:1718129934.985962    5556 device_compiler.h:188] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m26767/26767\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m69s\u001b[0m 2ms/step - accuracy: 0.8757 - loss: 0.3330 - val_accuracy: 0.9063 - val_loss: 0.2548\n",
      "Epoch 2/5\n",
      "\u001b[1m26767/26767\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m62s\u001b[0m 2ms/step - accuracy: 0.9067 - loss: 0.2528 - val_accuracy: 0.9117 - val_loss: 0.2385\n",
      "Epoch 3/5\n",
      "\u001b[1m26767/26767\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m62s\u001b[0m 2ms/step - accuracy: 0.9110 - loss: 0.2394 - val_accuracy: 0.9134 - val_loss: 0.2342\n",
      "Epoch 4/5\n",
      "\u001b[1m26767/26767\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m62s\u001b[0m 2ms/step - accuracy: 0.9131 - loss: 0.2342 - val_accuracy: 0.9144 - val_loss: 0.2324\n",
      "Epoch 5/5\n",
      "\u001b[1m26767/26767\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m62s\u001b[0m 2ms/step - accuracy: 0.9143 - loss: 0.2311 - val_accuracy: 0.9156 - val_loss: 0.2278\n",
      "CPU times: user 6min 9s, sys: 1min 50s, total: 8min\n",
      "Wall time: 5min 17s\n"
     ]
    }
   ],
   "source": [
    "batch_size = 128\n",
    "n_epochs = 5\n",
    "\n",
    "%time history = keras_model.fit(X, y, batch_size=batch_size, epochs=n_epochs, \\\n",
    "                                validation_data=(X_test, y_test))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Performance metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        alert(\n",
       "            '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",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
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       "        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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.canvas_div.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://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",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt \n",
    "plt.style.use('seaborn-v0_8-darkgrid')\n",
    "# Graph with loss vs. epoch\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(history.history['loss'], label='train')\n",
    "plt.plot(history.history['val_loss'], label='validation')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(loc='upper right')\n",
    "plt.title(\"HLF classifier loss\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.canvas_div.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://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",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Graph with accuracy vs. epoch\n",
    "%matplotlib notebook\n",
    "plt.figure()\n",
    "plt.plot(history.history['accuracy'], label='train')\n",
    "plt.plot(history.history['val_accuracy'], label='validation')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(loc='lower right')\n",
    "plt.title(\"HLF classifier accuracy\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Confusion Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m26753/26753\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 2ms/step\n"
     ]
    }
   ],
   "source": [
    "y_pred=history.model.predict(X_test)\n",
    "y_true=y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of the HLF classifier: 0.9156\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "print('Accuracy of the HLF classifier: {:.4f}'.format(\n",
    "    accuracy_score(np.argmax(y_true, axis=1),np.argmax(y_pred, axis=1))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.canvas_div.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://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",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "from sklearn.metrics import confusion_matrix\n",
    "labels_name = ['qcd', 'tt', 'wjets']\n",
    "labels = [0,1,2]\n",
    "\n",
    "cm = confusion_matrix(np.argmax(y_true, axis=1), np.argmax(y_pred, axis=1), labels=labels)\n",
    "\n",
    "## Normalize CM\n",
    "cm = cm / cm.astype(float).sum(axis=1)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax = sns.heatmap(cm, annot=True, fmt='g')\n",
    "ax.xaxis.set_ticklabels(labels_name)\n",
    "ax.yaxis.set_ticklabels(labels_name)\n",
    "plt.xlabel('True labels')\n",
    "plt.ylabel('Predicted labels')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ROC and AUC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import roc_curve, auc\n",
    "\n",
    "fpr = dict()\n",
    "tpr = dict()\n",
    "roc_auc = dict()\n",
    "\n",
    "for i in range(3):\n",
    "    fpr[i], tpr[i], _ = roc_curve(y_test[:, i], y_pred[:, i])\n",
    "    roc_auc[i] = auc(fpr[i], tpr[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 0.98740771210857, 1: 0.9854809052110163, 2: 0.9812919906771842}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dictionary containign ROC-AUC for the three classes \n",
    "roc_auc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute('tabindex', '0');\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;' +\n",
       "            'z-index: 2;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: relative;' +\n",
       "            'z-index: 0;'\n",
       "    );\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box;' +\n",
       "            'left: 0;' +\n",
       "            'pointer-events: none;' +\n",
       "            'position: absolute;' +\n",
       "            'top: 0;' +\n",
       "            'z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            /* This rescales the canvas back to display pixels, so that it\n",
       "             * appears correct on HiDPI screens. */\n",
       "            canvas.style.width = width + 'px';\n",
       "            canvas.style.height = height + 'px';\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        /* User Agent sniffing is bad, but WebKit is busted:\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=144526\n",
       "         * https://bugs.webkit.org/show_bug.cgi?id=181818\n",
       "         * The worst that happens here is that they get an extra browser\n",
       "         * selection when dragging, if this check fails to catch them.\n",
       "         */\n",
       "        var UA = navigator.userAgent;\n",
       "        var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n",
       "        if(isWebKit) {\n",
       "            return function (event) {\n",
       "                /* This prevents the web browser from automatically changing to\n",
       "                 * the text insertion cursor when the button is pressed. We\n",
       "                 * want to control all of the cursor setting manually through\n",
       "                 * the 'cursor' event from matplotlib */\n",
       "                event.preventDefault()\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        } else {\n",
       "            return function (event) {\n",
       "                return fig.mouse_event(event, name);\n",
       "            };\n",
       "        }\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    canvas_div.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    canvas_div.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.canvas_div.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://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",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "# Plot roc curve \n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('seaborn-v0_8-darkgrid')\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(fpr[0], tpr[0], lw=2, \\\n",
    "         label='HLF classifier (AUC) = %0.4f' % roc_auc[0])\n",
    "plt.plot([0, 1], [0, 1], linestyle='--')\n",
    "plt.xlim([0.0, 1.0])\n",
    "plt.ylim([0.0, 1.05])\n",
    "plt.xlabel('Background Contamination (FPR)')\n",
    "plt.ylabel('Signal Efficiency (TPR)')\n",
    "plt.title('$tt$ selector')\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "@webio": {
   "lastCommId": null,
   "lastKernelId": null
  },
  "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": "3.9.12"
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 },
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}