Training_HLF_Classifier/TensorFlow_Keras_HLF_with_PySpark_Parquet.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Traininig of the High Level Feature classifier with TensorFlow/Keras\n",
    "\n",
    "**4.0 Tensorflow/Keras, HLF classifier, PySpark and Keras** This notebooks trains a dense neural network for the particle classifier using High Level Features. It uses TensorFlow/Keras on a single node. Spark is used in local mode just to read the data and pass it to TensorFlow.\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": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Setting default log level to \"WARN\".\n",
      "To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n",
      "24/06/11 17:09:10 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable\n"
     ]
    }
   ],
   "source": [
    "# No need to run this when using CERN SWAN service\n",
    "# Just add the configuration parameters for Spark on the \"star\" button integration\n",
    "\n",
    "# pip install pyspark or use your favorite way to set Spark Home, here we use findspark\n",
    "# import findspark\n",
    "# findspark.init('/home/luca/Spark/spark-3.5.1-bin-hadoop3') #set path to SPARK_HOME\n",
    "\n",
    "# Create Spark session and configure according to your environment\n",
    "from pyspark.sql import SparkSession\n",
    "\n",
    "# Spark is used in local mode for this, just to fork data for HLF classifier (~ 300 MB)\n",
    "spark = ( SparkSession.builder\n",
    "          .appName(\"Training-RandomForestClassifier\")\n",
    "          .master(\"local[*]\")\n",
    "          .config(\"spark.driver.memory\",\"2g\")\n",
    "          .config(\"spark.sql.execution.arrow.pyspark.enabled\", \"true\")\n",
    "          .config(\"spark.dynamicAllocation.enabled\", \"true\")\n",
    "          .config(\"spark.ui.showConsoleProgress\", \"false\")\n",
    "          .getOrCreate()\n",
    "        )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <div>\n",
       "                <p><b>SparkSession - in-memory</b></p>\n",
       "                \n",
       "        <div>\n",
       "            <p><b>SparkContext</b></p>\n",
       "\n",
       "            <p><a href=\"http://jupyter-canali:4040\">Spark UI</a></p>\n",
       "\n",
       "            <dl>\n",
       "              <dt>Version</dt>\n",
       "                <dd><code>v3.5.1</code></dd>\n",
       "              <dt>Master</dt>\n",
       "                <dd><code>local[*]</code></dd>\n",
       "              <dt>AppName</dt>\n",
       "                <dd><code>Training-RandomForestClassifier</code></dd>\n",
       "            </dl>\n",
       "        </div>\n",
       "        \n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "<pyspark.sql.session.SparkSession at 0x7f89a41cf4f0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check if Spark Session has been created correctly\n",
    "spark"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load train and test datasets via Spark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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",
    "# PATH = \"../Data/sparkdltrigger.web.cern.ch/sparkdltrigger/\"\n",
    "\n",
    "trainDF = spark.read.format('parquet')\\\n",
    "        .load(PATH + 'trainUndersampled_HLF_features.parquet')\\\n",
    "        .select(['HLF_input', 'encoded_label'])\n",
    "        \n",
    "testDF = spark.read.format('parquet')\\\n",
    "        .load(PATH + 'testUndersampled_HLF_features.parquet')\\\n",
    "        .select(['HLF_input', 'encoded_label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 856090 events in the test dataset\n",
      "There are 3426083 events in the train dataset\n"
     ]
    }
   ],
   "source": [
    "# Check the number of events in the train and test datasets\n",
    "\n",
    "num_test = testDF.count()\n",
    "num_train = trainDF.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": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- HLF_input: array (nullable = true)\n",
      " |    |-- element: double (containsNull = true)\n",
      " |-- encoded_label: array (nullable = true)\n",
      " |    |-- element: double (containsNull = true)\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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",
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       "    <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",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\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]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the schema and a data sample of the test dataset\n",
    "testDF.printSchema()\n",
    "testDF.limit(5).toPandas()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert training and test datasets from Spark DataFrames to Numpy arrays\n",
    "\n",
    "Now we will collect and convert the Spark DataFrame into numpy arrays in order to be able to feed them to TensorFlow/Keras.\n",
    "We use the \"spark.sql.execution.arrow.pyspark.enabled\" toPandas optimization in Spark to move data faster bewteen JVM and Python.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "trainPDF=trainDF.toPandas()\n",
    "testPDF=testDF.toPandas()\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": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-11 17:09:51.799237: 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 17:09:51.873152: 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 17:09:55.503482: 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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-11 17:09:58.270700: 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": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-11 17:09:58.357877: 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 17:09:58.358239: 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"
     ]
    }
   ],
   "source": [
    "# Check that we have a GPU available\n",
    "tf.config.list_physical_devices('GPU')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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 17:10:02.229178: 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 17:10:02.229625: 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 17:10:02.230050: 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 17:10:02.325012: 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 17:10:02.325390: 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 17:10:02.325656: 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 17:10:02.325865: 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": 10,
   "metadata": {},
   "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 00:00:1718118611.553682    3978 service.cc:145] XLA service 0x7f86f4001d40 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:\n",
      "I0000 00:00:1718118611.553809    3978 service.cc:153]   StreamExecutor device (0): Tesla T4, Compute Capability 7.5\n",
      "2024-06-11 17:10:11.596238: 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 17:10:11.786453: 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   79/26767\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m51s\u001b[0m 2ms/step - accuracy: 0.4685 - loss: 1.0606 "
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "I0000 00:00:1718118613.588401    3978 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[1m68s\u001b[0m 2ms/step - accuracy: 0.8824 - loss: 0.3194 - val_accuracy: 0.9054 - val_loss: 0.2557\n",
      "Epoch 2/5\n",
      "\u001b[1m26767/26767\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m61s\u001b[0m 2ms/step - accuracy: 0.9089 - loss: 0.2462 - val_accuracy: 0.9111 - val_loss: 0.2399\n",
      "Epoch 3/5\n",
      "\u001b[1m26767/26767\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m61s\u001b[0m 2ms/step - accuracy: 0.9118 - loss: 0.2383 - val_accuracy: 0.9136 - val_loss: 0.2338\n",
      "Epoch 4/5\n",
      "\u001b[1m26767/26767\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m61s\u001b[0m 2ms/step - accuracy: 0.9134 - loss: 0.2348 - val_accuracy: 0.9142 - val_loss: 0.2327\n",
      "Epoch 5/5\n",
      "\u001b[1m26767/26767\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m61s\u001b[0m 2ms/step - accuracy: 0.9144 - loss: 0.2313 - val_accuracy: 0.9137 - val_loss: 0.2346\n",
      "CPU times: user 6min 2s, sys: 1min 51s, total: 7min 53s\n",
      "Wall time: 5min 13s\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))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Performance metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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",
    "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": 12,
   "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": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m26753/26753\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m40s\u001b[0m 1ms/step\n"
     ]
    }
   ],
   "source": [
    "y_pred=history.model.predict(X_test)\n",
    "y_true=y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of the HLF classifier: 0.9137\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": 15,
   "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": 16,
   "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": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 0.9870150943414651, 1: 0.9851549630674189, 2: 0.9805511912092388}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dictionary containign ROC-AUC for the three classes \n",
    "roc_auc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "spark.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "@webio": {
   "lastCommId": null,
   "lastKernelId": null
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