Training_Spark_ML/4.0c-Training-HLF_LightGBM.ipynb

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   "source": [
    "# LightGBM Classifier\n",
    "**Example 4.0c, LightGBM classifier:** This trains a particle classifier using Random Forest distributed using PySpark ML APIs.\n",
    "\n",
    "The High-Level Features classifier is built with labeled data\n",
    " - input: 14 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",
    " - output: 3 classes, \"W + jet\", \"QCD\", \"t tbar\", see also [Machine Learning Pipelines with Modern Big Data Tools for High Energy Physics Comput Softw Big Sci 4, 8 (2020)](https://rdcu.be/b4Wk9)  \n",
    " - Open dataset: [download data](https://github.com/cerndb/SparkDLTrigger/tree/master/Data)\n",
    "![Physics use case for the particle classifier](../Docs/Physics_use_case.png)\n",
    "\n",
    "To run this notebook we used the following configuration:\n",
    "\n",
    "The notebook has been tested using the following configuration:\n",
    "* *Software stack*: Spark 3.5.1, LightGBM and synapseml 1.0.4\n",
    "* *Platform*: CentOS 7, Python 3.11\n",
    "* *Spark cluster*: Analytix"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
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   "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 \n",
    "# or use your favorite way to set Spark Home, here we use findspark\n",
    "import findspark\n",
    "findspark.init('/home/luca/Spark/spark-3.4.1-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 = ( SparkSession.builder\n",
    "          .appName(\"Training-LightGBM\")\n",
    "          .master(\"yarn\")\n",
    "          .config(\"spark.driver.memory\",\"4g\")\n",
    "          .config(\"spark.executor.memory\",\"32g\")\n",
    "          .config(\"spark.executor.cores\",\"10\")\n",
    "          .config(\"spark.executor.instances\",\"1\")\n",
    "          .config(\"spark.dynamicAllocation.enabled\",\"false\")\n",
    "          .config(\"spark.sql.execution.arrow.pyspark.enabled\", \"true\")\n",
    "          .config(\"spark.ui.showConsoleProgress\", \"false\")\n",
    "          .config(\"spark.jars.packages\", \"com.microsoft.azure:synapseml_2.12:1.0.4\")\n",
    "          .getOrCreate()\n",
    "        )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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       "\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://pcitdbgpu1.dyndns.cern.ch:4040\">Spark UI</a></p>\n",
       "\n",
       "            <dl>\n",
       "              <dt>Version</dt>\n",
       "                <dd><code>v3.4.1</code></dd>\n",
       "              <dt>Master</dt>\n",
       "                <dd><code>yarn</code></dd>\n",
       "              <dt>AppName</dt>\n",
       "                <dd><code>Training-LightGBM</code></dd>\n",
       "            </dl>\n",
       "        </div>\n",
       "        \n",
       "            </div>\n",
       "        "
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       "<pyspark.sql.session.SparkSession at 0x7efcef44f890>"
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     "execution_count": 6,
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   "source": [
    "spark"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load train and test dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For CERN users, data is already available in the Analytix cluster\n",
    "\n",
    "# Open data: download the test and training data sets as described at\n",
    "# https://github.com/cerndb/SparkDLTrigger/tree/master/Data\n",
    "# DATASET_NAME=\"trainUndersampled.parquet\"\n",
    "# wget -r -np -R \"index.html*\" -e robots=off http://sparkdltrigger.web.cern.ch/sparkdltrigger/$DATASET_NAME\n",
    "# \n",
    "\n",
    "# PATH = \"./\" # use the path where you downloaded the data\n",
    "# For CERN users, data is already available on the Analytix Hadoop cluster\n",
    "PATH = \"hdfs://analytix/Training/Spark/TopologyClassifier/\"\n",
    "\n",
    "trainDF = ( spark.read.format('parquet')\n",
    "              .load(PATH + 'trainUndersampled.parquet')\n",
    "              .selectExpr('hfeatures as features', 'label')\n",
    "          )\n",
    "        \n",
    "testDF = ( spark.read.format('parquet')\n",
    "             .load(PATH + 'testUndersampled.parquet')\n",
    "             .selectExpr('hfeatures as features', 'label', 'encoded_label')\n",
    "         )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 3426083 training events\n",
      "There are 856090 test events\n"
     ]
    }
   ],
   "source": [
    "# Optionally count the number of events in the training and test datasets\n",
    "print('There are', trainDF.count(), 'training events')\n",
    "print('There are', testDF.count(), 'test events')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "root\n",
      " |-- features: vector (nullable = true)\n",
      " |-- label: long (nullable = true)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# There are 14 High Level Features for this classifier, \n",
    "# packed into a vector in the \"features\" column\n",
    "# The label can take 3 possible values. Details at:\n",
    "# https://github.com/cerndb/SparkDLTrigger/tree/master/Data\n",
    "\n",
    "trainDF.printSchema()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+-----+-------------+\n",
      "|            features|label|encoded_label|\n",
      "+--------------------+-----+-------------+\n",
      "|[0.0,0.0,0.0,0.0,...|    0|(3,[0],[0.0])|\n",
      "|[0.0,0.0,0.0,0.0,...|    0|(3,[0],[0.0])|\n",
      "|[0.0,0.0,0.0,0.0,...|    0|(3,[0],[0.0])|\n",
      "+--------------------+-----+-------------+\n",
      "only showing top 3 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "testDF.show(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train the classifier using LightGBM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# requires lightGBM\n",
    "# !pip install lightgbm\n",
    "from synapse.ml.lightgbm import LightGBMClassifier\n",
    "\n",
    "model = LightGBMClassifier(objective='multiclass')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "%time gbm_model = model.fit(trainDF)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save the model to the local filesystem\n",
    "gbm_model.save(path='file:/tmp/models/GBM/gbm_model')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = gbm_model.transform(testDF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/02/24 15:53:52 WARN DAGScheduler: Broadcasting large task binary with size 1099.4 KiB\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------------------+-----+-------------+--------------------+--------------------+----------+\n",
      "|            features|label|encoded_label|       rawPrediction|         probability|prediction|\n",
      "+--------------------+-----+-------------+--------------------+--------------------+----------+\n",
      "|[74.9491729736328...|    0|(3,[0],[1.0])|[1.80693299538203...|[0.99104608682686...|       0.0|\n",
      "|[0.0,27.335390090...|    0|(3,[0],[1.0])|[0.55580234897910...|[0.88318448913853...|       0.0|\n",
      "|[47.6835403442382...|    0|(3,[0],[1.0])|[1.16190661904102...|[0.96812987091222...|       0.0|\n",
      "|[80.9036312103271...|    0|(3,[0],[1.0])|[1.22871101434430...|[0.92824126453611...|       0.0|\n",
      "|[95.2762756347656...|    0|(3,[0],[1.0])|[-0.0258602123350...|[0.88969609154375...|       0.0|\n",
      "+--------------------+-----+-------------+--------------------+--------------------+----------+\n",
      "only showing top 5 rows\n",
      "\n"
     ]
    }
   ],
   "source": [
    "pred.show(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute the AUC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyspark.sql.types import ArrayType, DoubleType\n",
    "from pyspark.sql.functions import udf\n",
    "    \n",
    "vector_udf = udf(lambda vector: vector.toArray().tolist(),ArrayType(DoubleType()))\n",
    "pred = pred.select([vector_udf('encoded_label').alias('encoded_label'),\n",
    "                    vector_udf('probability').alias('probability')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "23/02/24 15:53:54 WARN DAGScheduler: Broadcasting large task binary with size 1086.8 KiB\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 776 ms, sys: 294 ms, total: 1.07 s\n",
      "Wall time: 59.3 s\n"
     ]
    }
   ],
   "source": [
    "%time pred_pd = pred.select(['encoded_label', 'probability']).toPandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>encoded_label</th>\n",
       "      <th>probability</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[1.0, 0.0, 0.0]</td>\n",
       "      <td>[0.9910460868268698, 0.0023829251567053502, 0....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[1.0, 0.0, 0.0]</td>\n",
       "      <td>[0.8831844891385315, 0.005853727003600766, 0.1...</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[1.0, 0.0, 0.0]</td>\n",
       "      <td>[0.9681298709122245, 0.008860690795284882, 0.0...</td>\n",
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       "     encoded_label                                        probability\n",
       "0  [1.0, 0.0, 0.0]  [0.9910460868268698, 0.0023829251567053502, 0....\n",
       "1  [1.0, 0.0, 0.0]  [0.8831844891385315, 0.005853727003600766, 0.1...\n",
       "2  [1.0, 0.0, 0.0]  [0.9681298709122245, 0.008860690795284882, 0.0...\n",
       "3  [1.0, 0.0, 0.0]  [0.9282412645361183, 0.015820103532417293, 0.0...\n",
       "4  [1.0, 0.0, 0.0]  [0.8896960915437561, 0.09051627405878927, 0.01..."
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_pd.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "y_true = np.array(pred_pd['encoded_label'].tolist())\n",
    "y_pred = np.array(pred_pd['probability'].tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import roc_curve, auc\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_true[:, i], y_pred[:, i])\n",
    "    roc_auc[i] = auc(fpr[i], tpr[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
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       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; 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",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\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",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.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",
       "    this.rubberband_canvas.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",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.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",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // 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 icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\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=\"697.5833333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "plt.style.use('seaborn-v0_8-darkgrid')\n",
    "\n",
    "plt.style.use('seaborn-darkgrid')\n",
    "plt.figure()\n",
    "plt.plot(fpr[1], tpr[1], color='blue', \n",
    "         lw=2, label='Random Forest classifier (AUC) = %0.4f' % roc_auc[1])\n",
    "plt.plot([0, 1], [0, 1], color='orange', 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.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = 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(\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",
       "    );\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('style', 'box-sizing: content-box;');\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; position: absolute; left: 0; top: 0; 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",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\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",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.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",
       "    this.rubberband_canvas.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",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.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",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // 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 icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\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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       "<img 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AQpQoOIKMOTrjT1DfjFeX3/9NcaPH48LLrgAH3/88QlD/rZt23DFFVdgxIgRuOGGG7B//34MHToUqampeOKJJxjy9a5JlqYABShAAQpQgALHCTDk610UDPnFeL3//vs4++yz8ffff+P2228/Ych/6qmnIO/kf/rpp7m1yTv/999/v/q5vLNf1ME7+XoXK0tTgAIUoAAFKFBxBRjy9caeIb8Er+XLl5cY8m+66SY0bdoUEyZMyK1t37596NatG+bMmYPOnTsz5OtdlyxNgQopEAwC8o/fDwQCxh/5vfxZ6PtAwJb7WqhM/q9G2bwybjfgcBh1hOop/L0sL4/iXzeGQ76enm5DbCxgtwfVeUJ1ya+hMkWdK3+5UFnZ7mCwYB3ytd27bahVK6jqDtWZ/4Io/PNQ3fnLFlUmr315/TW33oKXrWzD9u12VKkShMv1v878z7Go8xbdV6OtoSPUr5P9u5l1nagtZrazsEvJdZ+cmc8H/PabA+eeK/6jO8FR+PxFFS2pTEmvn7AB/3uxNHWYUSZS6rDb/Ph0XnxpaFjmfwIM+SVcCqUJ+T169MCll16KBx54ILe2nJwctG3bFs899xwuv/zyIs/CO/n877CiCoSCrNcLyD8ej019lYHU67WJv4d+XvDv8jUZeo33AHv32nHaaUHIf5zlz+Ufn88oY3yf97Xwz5ctc4j/RkXKFEfhUG0E67x6QkG7YDkjnOb/Wf5gLs8XCuah9hh/N/qXlWVDXJwRZPPCfMFwUlGvD/abAhSgQGGBGf36o//MmYTREGDINynkd+/eXc3JDx2hkD958mT06tWLIV/jomTR8AvIUJmdbYRqt9umvpehU3w2Fd/b1M9zcmzqjmpSknwt73UZUOV7ZFn51fi7EdTzf5//Z/Ln8nX5Mxm8ZUiXIZoHBShAAQpQoDQC9U7bgR0H65emKMv8T4Ah34SQf8stt6BRo0Z4/PHHc2vbu3cvLrzwQrzxxhvo1KkTQz7/kztpARmKMzKMaRJpaTb1NTMT4o9N/dz4arwW+rt8Xf5MBncZ0GVwl0FefpXhXAZuHpEvYLMFxbQYOTXGmHIT+j7vq/G6TQxn4dfy/2zLFjuqVQuo33rIn+f/E3p/qPzxr+e9J1R2wwY7UlKA+vUDx9UXer+cziOPwvXlvZ73WlHlfv/djtatA+K3HcY4SYtQufzl84+irLvwa/l/Vtz7C5cpXK7ovxsuxZXN/9qBAzZVtnr1vCk7oddD7c//9xO9lv98Rb1X9/XC5yr8X8XxbcnrQ0nnCmc/9NtdsGcnatuePTbUqVOwnyW5FPV/E902Fl1H+NtRmv8TltSXoq6FUzWral8LOzw4GGifW9U99xS/YmFp+lHRyjDklzDipZmu8+yzz+L777/HvHnzcmv77LPPMGrUKCxdulTMxXQVeRZO16k4/7nJKRkygMt/7A8dsuHoUeOPDObyz7FjMrwj93tZ5vBho4wM6lY+YmKCao63nLoSEwP1vfHV+Lv843QaZZzOvL/Ln8t/eFatcqBLF58KwfJ1+TX0R74v9LO814yfyT/79tlQu7ZxHoejYKAuHKplOwsHaVnGCMfB40J4XjuM9+VvV15oN9qSv9785y3NP6xWvjbYNwpQoAIKBANI2PEKkv4cj0B8bRzp9COCzmQFwQdv9a4HhvyTCPmrV6/GyJEjMXv2bBEQamPXrl1q3v2wYcNw4403iikOuzF48GB07doVY8eOLfYMDPl6F2uklZZTXg4etKmgKMO7/HPwoF2syGQr8EeWkUE+0u6eyzujchsHeac0Pt74PvQ1ISGofi6D9urVDlx0kQ+Jicbr8ufGn9D3RgAPBXXjq/Hewt8bAT5/eDdCMg8KUIACFKCAPWcvktcNROzhbxWGP74+jrV7H35XS4b8k7g8GPKLQZMP0+7Zs0fMGw6K+cNeEUxiRBixoXfv3mpN/MLLaq5YsQJTpkzBxo0bUblyZfUgrpyjL99X3MGQfxJXbBm9RQZ4Gd537rSreem7dtnFQ55GkJcPe8qfye/lQ5RlccjAnJISRLK4mZGcbKzUIefKy6+JifLvxveyjPx5UpL8mvd9vFiQQAb3UFCXf5eBmwG7LEaP56AABShAgZIEYg98huQ/hsDuPayK5px+PTJaPIdgTN4y5LyTX5JiwdcZ8vW8TC3NkG8qp3Zlct76jh12bN1qF8vc2cRuxXZs22ZXwV7OyTT7zrucDlKtWlDNi5ZL6lWuHBR7KBjBXX4vw3soyMsy8o/8uywjQzkPClCAAhSggOUE/JlwbRyFhN1zVNcCzhQR7ifDXev647rKkK83+gz5el6mlmbIN5WzyMrkPPe//rKrAC8fPpR/ZKjfsUPOjRcTpU/xkHfRa9aUfwKoUSOoHqyTQV5+rVEjoL7KsG6EeGNeNg8KUIACFKAABQyBxC1PI+kvY+ESb+XOSEudgUBCgyJ5GPL1rhqGfD0vU0sz5JvHKR9s3bnTph7CXLXKjvXrHeKPXU2zOdlDTneRq4fIVRbq1DG+yjAvQ33dukHxPEZATY3hlJeTFeb7KEABClCgwgv4c1B5xaXw1OyNrIbDxT+qxd8NY8jXu1oY8vW8TC3NkH/ynHK+/O+/O7BihR0rVzqwbp0DR47ozY+XD57KXTUbNAigYcMgGjcOqD/y7zLQV62at0TeybeU76QABShAAQpQICRgz94BZ/paeGr8Mw8lIDZPsRf/DGOoIEO+3nXEkK/nZWpphvzSccqNlORW40uXOkSwt6vvDxwo3R16GeTr1w+iSZMAmjYNiP0MjCDfsGFALZ0YWoO7dC1hKQpQgAIUoAAFTlYgbu9cuDbcD5sI9Uc6LYE/qZlWVQz5WlxgyNfzMrU0Q37RnHKzJnmXXob6RYvk9BuH2lm1pEPOj2/VKoB27fxITfWjRYsAmjcPqBVleFCAAhSgAAUoUD4CNu8xFe7j972vGhCIqYK01m/Ae9qFWg1iyNfiYsjX4zK3NEO+4Snn0//5px3ffefA1187sWxZyaFeLil55pkBtG/vxznn+NG2rXGXXm4sxIMCFKAABShAgcgQiDnyE5LXDoAjZ4dqkKfqRUhv9arY6KqWdgMZ8vXIeCdfz8vU0hU55IutB7BkibxT78RXXznV0pUnOk4/PYDzzvOjY0e/ulPfsmVArfPOgwIUoAAFKECBCBQQU3ISt0xC4tbJsCGAoC0Wmc0eRXb9e8TDtaWbclu4Vwz5euPMkK/nZWrpihbys7KAH35w4LPPYjB/vlPtAlvcIVez6dzZjy5d/LjwQp9azYYHBShAAQpQgALRIRB74AtUWnWjaqwvqaWYnvMa/Mmpp9R4hnw9PoZ8PS9TS1eEkC93jpV37N97Lwaff+5EVlbRwT4uLoiuXf3o1s2H7t194uFYhnpTLzZWRgEKUIACFChLATEXN3nNXQjEVld38OFIOOWzM+TrETLk63mZWtrKIf/vv214880YvP12DHbvLvrXctWrB3DZZT5cfLER7uWa8zwoQAEKUIACFIg+AZvnEOIOzENO3TvyGh/0n3Dde91eMuTriTHk63mZWtqKIX/tWjtmzIjFRx854fEcf9e+Xr0AevTw4YorfGp+vf3kpuWZOg6sjAIUoAAFKECBkxeIOfQtktcNhMO9F8favivWwO918pWd4J0M+XqsDPl6XqaWtlLI/+03OyZPjsOCBccvb+NyBXHllV5cf70PHTow2Jt6EbEyClCAAhSgQHkJBNxI2vwYErdPUy0I2hOQ3nIK3LVvDkuLGPL1WBny9bxMLW2FkL94sQPPPBOL5cuPD/ctW/oxYIAXV1/tRcKpT8Uz1Z6VUYACFKAABShw8gKOjPVIWdMPzow1qhJv8llIbz1LbHDV/OQrLeGdDPl6tAz5el6mlo7mkL9hgx1jx8Zh8eLjw/2ll/owcKBHPUhrK3kPK1NNWRkFKEABClCAAmEUEA/Uxu+cAdefj4ida3MQFAtkZjcchswmYwB7eNe2ZsjXG1eGfD0vU0tHY8jPzASmTInFSy/Fwu/PS/B2exCXX+7D4MEesY69WFKHBwUoQAEKUIAClhNwZP6JKks7id1UvfDH1UF66gx4q55fJv1kyNdjZsjX8zK1dDSFfLkrrVwCU96937Mn72lZmy2Iq67yYeRIN5e9NPXqYGUUoAAFKECByBRI2PY8nGkrkSHm3wdjqpRZIxny9agZ8vW8TC0dLSH/wAGbCPFx+OKLmAL9lzvPPvVUDs46i3fuTb0wWBkFKEABClAgUgT8WUgQ03Oy6w8W03H+lwPknT95lPGcXIZ8vYuCIV/Py9TS0RDyFyxwYMSIeOzfn3f3vnLlIB56yI0+fbxwHj8l31QjVkYBClCAAhSgQPkIyLv1yWvFw7WZm5DZ+CFkyXn35Xgw5OvhM+TreZlaOpJDvs8HjB8fh5kzCz5EI1fKeewxN2rU4I60pl4MrIwCFKAABSgQKQLBABK2TxXLY05Qc++DNgeyGo8Sf0aWawsZ8vX4GfL1vEwtHakhf/9+m1gdJx4//ph3m75SpSCefz4HvXqJ9M+DAhSgAAUoQAFLCthzdom79wMRe2Sx6p8/oSHSUmfBV7lDufeXIV9vCBjy9bxMLR2JIX/ZMgf69YvHgQN503MuusiHqVNzULMm796begGwMgpQgAIUoEAECcTu/xjJf9wHu++oalVO7VuQccbTCDqTI6KVDPl6w8CQr+dlaulICvnyGZo33ojBmDFx8HrzlsYcMsQtfuaBw2Fq11kZBShAAQpQgAKRJODLQNUf28Ph2YeAszLSz3wBnppXRVILwZCvNxwM+XpeppaOlJAv59/L1XPefjtv/r2cniPv3vfsyek5pg46K6MABShAAQpEqEDMoUVIFMtjprd6BYH4OhHXSoZ8vSFhyNfzMrV0JIT87GzgjjsS8O23efPvmzf34803s7nuvamjzcooQAEKUIACESQQ8ImHa6chp86tCMZWz2uY/NV+GS+NWVoVhvzSShnlGPL1vEwtXd4hX+5ee/vtCfjhh7yA36uXF9Om5cDlMrWrrIwCFKAABShAgQgRsGdtRcra/og59jPc1S5D2lnvRWywz0/GkK93ATHk63mZWro8Q35WFnDbbQUD/t13e/Dvf7s5/97UUWZlFKAABShAgQgREHfp4/a+C9eGB2H3p6tGZdftKx6ufUpsdFVwyewIaXGBZjDk640KQ76el6mlyyvkyzn4corOggV5d/CHDXNj1ChPpP6GzlR3VkYBClCAAhSoaAI27xG41g9H/P6PVNcDMdXE3PuX4KneM2ooGPL1hoohX8/L1NLlEfLlVDv5kO0bb+R9Yr/vPmMFHR4UoAAFKEABClhPIObwD2Lt+wFwuHerzrlPu1Q9XBuMqxFVnWXI1xsuhnw9L1NLl0fInzo1Fo8/Hpfbj379PJg40c07+KaOLCujAAUoQAEKRIiAuLtX6ddeYnOrJQja45HRbAJy6g2Iijn4hQUZ8vWuKYZ8PS9TS5d1yJ8714khQxJy+9CzpxezZ+dwDr6po8rKKEABClCAApElYM/ernaxzWg5GX5Xy8hqnEZrGPI1sERRhnw9L1NLl2XI37TJju7dE5GVZWx0dfbZfnz4YRYSE03tEiujAAUoQAEKUKA8BcSd+/hds+FLaQtfpXPKsyWmn5shX4+UIV/Py9TSZRXy5VKZPXsmYsMGY9vaBg0C4qHbTFSpYmp3WBkFKEABClCAAuUoYPP8jeR1QxB3cD58CY1xpNMSwGmdNbEZ8vUuLoZ8PS9TS5dVyB86NB7/+U+MantsbBDz5mWhXbuAqX1hZRSgAAUoQAEKlJ9A7MEFIuAPgt1zQDXCXeNfSD9zGoIx1rmjx5Cvd30x5Ot5mVq6LEL+woUO3Hxz3pyciRNz0L+/19R+sDIKUIACFKAABcpJwJ+NpD/HIXHndNWAoCNJrHv/NHJq3xqVD9eeSJEhX+8aY8jX8zK1dLhD/pEjwIUXJmHvXrtqt3zQds6cHK6kY+oosjIKUIACFORg/OIAACAASURBVKBA+Qg40tciZU1fODPXqwZ4U85GWutZCCQ2KZ8GhfmsDPl6wAz5el6mlg53yB88OB7vv29M00lJCWLJkkycfrpYKJ8HBShAAQpQgAJRL5C0YaS4g/8qgrAjq9EDyGr8kNi51vh334oHQ77eqDLk63mZWjqcIX/JEgeuvjpvms60adm44Qax1S0PClCAAhSgAAWsISCm6qSsvg1ZDUfAV6WzNfp0gl4w5OsNMUO+npeppcMV8t1u4IILkrB1qzFN57LLvGKHW07TMXXwWBkFKEABClCgjAViD8yDzZ8Fd60byvjMkXE6hny9cWDI1/MytXS4Qv7zz8fiiSeMXW0TE4P4/vtMsWwmp+mYOnisjAIUoAAFKFBWAr4MuDaNQsLuN9SDtUc6/gB/UtOyOnvEnIchX28oGPL1vEwtHY6Qv3evDZ07J+VuevXII27ce6/H1HazMgpQgAIUoAAFykbAeewXJK/pB2f2FnVCT+UuSE+diUBCvbJpQASdhSFfbzAY8vW8TC0djpA/cGA8PvrIeOimSZMAFi/ORIx1n8ExdTxYGQUoQAEKUCBiBIJ+JG6djMQtT8Amvg/anMhsMgbZDYeJpTGNzS0r2sGQrzfiDPl6XqaWNjvkb95sw3nnJSEYtKl2vvtuFi6+2G9qm1kZBShAAQpQgALhFbBnb0fK2gGIObpUncgnlsRMT30Nvkrtw3viCK+dIV9vgBjy9bxMLW12yB8wIB6ffGLctu/a1Sfu6Geb2l5WRgEKUIACFKBA+AXidr+NlD8GqRNl17lDbG41CRBz8Sv6wZCvdwUw5Ot5mVrazJC/Zo0dl1ySmHsX/5NPstClC+/imzpgrIwCFKAABShQFgLBIFzrh8FT7VJ4alxeFmeMinMw5OsNE0O+npeppc0M+XfcEY8vvjDu4nfr5hObYPEuvqmDxcooQAEKUIACYRKIOfITYg4vRlaTh8N0BmtUy5CvN44M+XpeppY2K+Rv2mQX03Pyfo03f34mzj47YGpbWRkFKEABClCAAiYLBLziwdpJ6gFbGwI4dtZ78FTvafJJrFMdQ77eWDLk63mZWtqskD9yZBzmzInlXXxTR4eVUYACFKAABcIn4MjcjOS1/RCT9ps6ic91JtLEw7X+5FbhO2mU18yQrzeADPl6XqaWNiPkZ2QAqamu3HXx33knS8zN51x8UweKlVGAAhSgAAXMEhDz7eN3vwnXxodgC2SpWrPq34PMpo+Kh2vjzTqLJethyNcbVoZ8PS9TS5sR8v/v/2IwfLjxP4WGDQNYtiwTdrupzWRlFKAABShAAQqYIGDzHELy+qGIOzBP1eaPrYn0Vq/AW+0SE2q3fhUM+XpjzJCv52VqaTNCfq9eiVixwtgUY9Qotwj83N3W1EFiZRSgAAUoQAGTBJzHfkPlFZeIza18cFfvhfQzpyEYW82k2q1fDUO+3hgz5Ot5mVr6VEO+3PyqSxeXapPNFsTKlZmoVStoahtZGQUoQAEKUIAC5gkkbH8RQYcLOXX6yH+8zau4AtTEkK83yAz5el6mlj7VkD9xYixeeCFOtemii3x47z0um2nqALEyClCAAhSgwCkIODLWI2HHy8hoMQWwO0+hJr5VCjDk610HDPl6XqaWPpWQHxArZJ5zThJ27TIm4E+fno2rrvKZ2j5WRgEKUIACFKDASQjIh2t3Tofrz0fEw7VuZDYZg6zGD51ERXxLfgGGfL3rgSFfz8vU0qcS8pctc+Bf/0pU7XG5glizJgNJ3PHa1PFhZRSgAAUoQAFdAZt7P1LW3YPYQwvVW/3xdcXDtTPgrdpVtyqWLyTAkK93STDk63mZWvpUQv7DD8dh9mxjbfwbbvBi2rQcU9vGyihAAQpQgAIU0BOIPfAFkv8YDLv3kHpjTs2rkdFyCoIxVfQqYukiBRjy9S4Mhnw9L1NLn2zIF78FRNu2Sdi3z5iqw7XxTR0WVkYBClCAAhTQE/BninXvxyBh92z1voAjWczDfxbuWjfy4Vo9yROWZsjXw2TI1/MytfTJhvzff7ejRw9jbo6cqrN+fQbijOdveVCAAhSgAAUoUMYCNs9BVF3aCXbPAXgrdURa65kIJDQs41ZY/3QM+XpjzJCv52Vq6ZMN+RMmxIrpOUaq793bi5kzOVXH1IFhZRSgAAUoQAFNgZiDXyMm7TdkNRzBlXQ07UpbnCG/tFJGOYZ8PS9TS59syO/aNRGbNhkbYM2cmS2CPlfVMXVgWBkFKEABClDgBAL2nF1I2jRWTcnhZlZld6kw5OtZM+TreZla+mRC/o4dNrF0prEBltMZxMaNGUhONrVZrIwCFKAABShAgWIE4vZ9CNf64bD7jqpda9PavsN592V0tTDk60Ez5Ot5mVr6ZEL+nDkxGDkyXrXjvPN8+PhjboBl6qCwMgpQgAIUoEARAjZfGlwbHkT83nfVqwFnZaSfOQ2emr3pVUYCDPl60Az5el6mlj6ZkH/LLQn4+mtj17yxY90YOtRjaptYGQUoQAEKUIACBQWcR5cjZW1/OLK3qRc8VbuJte9fRSC+DqnKUIAhXw+bIV/Py9TSuiHf6wWaNXMhK8um2vHDD5k44wyx9S0PClCAAhSgAAXMFwj4kLj1aSRueRo2BBC0xSCz6b+R3WCwmKJjLGPNo+wEGPL1rBny9bxMLa0b8lessKNXL2PpzBo1AmKX20zYjLzPgwIUoAAFKEABswVEyK/8Sw/EHFsBX9IZYmnM1+BPbmP2WVhfKQUY8ksJ9b9iDPl6XqaW1g35L7wQi4kTjaUzr7rKi+nTuXSmqQPCyihAAQpQgAKFBOxZW5Gwc4a4gz8OcCTQpxwFGPL18Bny9bxMLa0b8m+6KQHffGPMx3/yyRzcdZeYv8ODAhSgAAUoQAFTBGzew+Lh2gfEdJx74UtpZ0qdrMQ8AYZ8PUuGfD0vU0vrhHy/H2je3IX0dGN+zuLFmWjRgvPxTR0QVkYBClCAAhVWIObw90heezcc7j3wJTbDkU5LeOc+wq4Ghny9AWHI1/MytbROyN+40Y7zzzfm41eqZKyPb+czP6aOByujAAUoQIEKKBBwI2nz40jYPlU8XBtE0B6PjOYTkVO3H9e/j7DLgSFfb0AY8vW8TC2tE/LfeisGI0YY6+NfeKEPc+dyfXxTB4OVUYACFKBAhRNwZGwUd+/7IiZ9teq7VzxUm546C35XiwpnEQ0dZsjXGyWGfD0vU0vrhPzBg+Px/vsx6vwPP+zG/fdzfXxTB4OVUYACFKBAhRKI3zkLrk2jYQsYi1hkNRgqHq59BLAbC1zwiDwBhny9MWHI1/MytXRpQ34wCLRvn4Tdu435Of/9bxY6dxaT9HlQgAIUoAAFKHBSAq4/hiFh92z442qrja28p114UvXwTWUnwJCvZ82Qr+dlaunShvw9e2w46yyXOndcXBCbN2eIr6Y2hZVRgAIUoAAFKpaAP1PMxZ+ArMYjEYypWrH6HqW9ZcjXGziGfD0vU0uXNuTPn+9Enz7G2rzt2/vx5ZdZpraDlVGAAhSgAAUsLeDPhuvPsfCmtIe79i2W7qqVO8eQrze6DPkn8MrOzhbr0T+JH374AceOHUPTpk0xdOhQnHfeeUW+a86cOeKB2LnYu3cvkpOTxZSazuJh2RFid9oaRZYvbch/4olYPP+8ceu+Tx8PnnnGrTfKLE0BClCAAhSooAIO8VBtypp+cGZuQMDhwpHOSxFIaFBBNaK72wz5euPHkH8Cr1GjRmHt2rV44YUXUKtWLXzwwQd4+umnMW/ePDRs2LDAOz/88EM89thjeOWVV9CxY0fs379fPBx7P2JjY/Hmm2+eUsi/5poE8UHD2ARr6tRs3HijT2+UWZoCFKAABShQ0QSCAbEs5ktiSs6jsAU9YnFMu5qak9VopHi41vg3lUd0CTDk640XQ34xXvLOvbxjP2XKFFx66aW5pa644gp07doVDz30UIF3jh8/Hn/88YdYAef93J+/9dZbmDx5Mn7//feTDvlyE6wmTVzIyjI2wVq2LAONG4sncXlQgAIUoAAFKFCkgD1nD5LXDUTs4e/U6/6EhkhLnQlf5Y4Ui2IBhny9wWPIL8brp59+wp133il2ll2MmjVr5pYaM2YMtm7dinfeeafAO+WUniFDhog77VPVNJ2///4bDzzwgLrjP2nSpJMO+evW2XHRRcYmWFWrBrB+fSZsRt7nQQEKUIACFKBAIYHYA58h+Y/BsHuPqFdyat2EjBbPIOhMoVWUCzDk6w0gQ34xXp999pmaT7969Wqxkk3eUjbPPPMMFi5ciK+++uq4d7777ruYOHEivF6vek2GfTl9JyHBeGi28FGaOflz5zrFhwfj/f/4hw//+Q83wdK7xFmaAhSgAAUqkkD8rjlIXj8UAWdlZLScAvfp11Sk7lu6rwz5esPLkF+Ml5x3L+/Er1mzRs2rDx0y5H/zzTdihZsvC7xz/vz5GDt2rJqe06lTJzUnf9y4caqMfCD3ZEP+hAmxmDbN+JBxzz0ePPooH7rVu8RZmgIUoAAFKpSA2FwmccuTyKl9q3jAtl6F6rrVO8uQrzfCDPnFeC1duhR33HHHcdN1Ro8ejR07duDtt98u8M7rr78eLVq0UA/fhg75W4DrrrsOX3zxhZhX3+S4M5XmTv711yfgu+/40K3eZc3SFKAABShQIQQCPiRuew427zFknvFEhehyRe4kQ77e6DPkF+OVnp6OLl264Nlnn0WPHj1yS1122WXo3r27Wjkn/3H11VejZcuWarpO6Pjtt99w0003nVLIT01NwoEDxk63336biVatAnojzNIUoAAFKEABCwrYs7chZe0AxBxdpnp3tP2n3LXWguOcv0sM+XoDzJB/Aq9///vf+OWXX8R0mWk4/fTTIVfLkXPsP//8cxw8eBAjR47E7NmzUbt2bcyYMUO99uKLL6olNOXr8q7/4cOH8dFHH8FuN4J6/qOkO/lHjwLNmyertzidQWzbliGmDukNMEtTgAIUoAAFLCUgpuPE7XsPrvUjYPenq65l17kLGWeIm2wOY6EKHtYUYMjXG1eG/BN4eTwetS7+okWLkJaWpqbjyDv47du3x/Lly3H77bdjwYIFaNCgAQKBgJp7L9fL37NHLN0lNsPq0KGDmtcvPyAUdZQU8n//3S5+i2D8D6tRo4A4Z6be6LI0BShAAQpQwEICNu9REe6HI37/h6pXgZjTkH7mi/DU6GWhXrIrxQkw5OtdGwz5el6mli4p5H/wgRODBnFlHVPRWRkFKEABCkSlgPPocrFz7V1w5OxU7fecdjHSW72CQFzRN9KispNs9AkFGPL1LhCGfD0vU0uXFPIffzxWrLtvrKwzcKBHPNTLlXVMHQBWRgEKUIACUSPgPLYClVd0B2xOZDZ7DNn17hbfHz8VNmo6xIZqCzDk65Ex5Ot5mVq6pJB/ww0J4mFbrqxjKjorowAFKECB6BEQ8+/z7wAZv/tNeFPOhj+5VfT0gS01TYAhX4+SIV/Py9TSJYX8s85KEvP7jbsU33yTidatubKOqQPAyihAAQpQIDIFRLiP3/0GYg/MQ1q7uSLoOyKznWxVmQow5OtxM+TreZla+kQhPysLaNjQWFlHHtu2pSMx0dTTszIKUIACFKBAxAnYPIeQ/Me9iPv7M9W2jOZPILvBkIhrJxtU9gIM+XrmDPl6XqaWPlHI37zZJtbpd6nz1agRwNq1XFnHVHxWRgEKUIACEScQc+gbJK+9Bw7PPtU2d40rkN5yKoKxp0VcW9mgshdgyNczZ8jX8zK19IlC/sKFDtx8s3Hr/uyz/Zg/X9za50EBClCAAhSwooA/B0mb/43EHS+r3gXtiWLd+6eQU+f2AnPyrdh19qn0Agz5pbeSJRny9bxMLX2ikD9jRgzGjo1X57vuOi9eeinH1HOzMgpQgAIUoEAkCDgyNyNl9W1wZqxTzfGmtEN66iz4k5pFQvPYhggSYMjXGwyGfD0vU0ufKOSPHh2HWbOM7W1HjnSLTbU8pp6blVGAAhSgAAUiQcDmPoCqSzvB5j2ErEYjkNV4FGCPiYSmsQ0RJsCQrzcgDPl6XqaWPlHIv/HGBLHTrrF85iuvZOOaa3ymnpuVUYACFKAABcpNoNDSmDGHFolgHwdvlfPKrUk8ceQLMOTrjRFDvp6XqaVPFPK7dEnE5s3GkmHz52eKeflcPtNUfFZGAQpQgALlIhB74HMk/fUEjp79KR+oLZcRiN6TMuTrjR1Dvp6XqaWLC/nyBkfDhi5kZ9vU+dasyUDNmuKHPChAAQpQgALRKuDPhGvjaCTsfl31IKfWTWLu/fRo7Q3bXQ4CDPl66Az5el6mli4u5B84YENqqrF8Znx8ENu3Z+Tf8M/UNrAyClCAAhSgQLgFnMd+E0tj9oMza7M6lbdyJ6SlzkQgoUG4T836LSTAkK83mAz5el6mli4u5K9caUf37knqXI0bB7BsGdfINxWelVGAAhSgQNkIBP1I2Pa8mJ4zUSzn50NQ7FwrH6zNani/mINvPHfGgwKlFWDIL62UUY4hX8/L1NLFhfx585zo2zdBnev883348MNsU8/LyihAAQpQgALhFpA716asuhWxR39Up/InNEJa61nwVTo33Kdm/RYVYMjXG1iGfD0vU0sXF/JffTUG48YZa+TffLMHzz/vNvW8rIwCFKAABSgQdoGAF5VXdEdM2q/Irn272NzqScBpTEXlQYGTEWDI11NjyNfzMrV0cSH/kUfiMH26sUb+Aw+4xTr5XCPfVHhWRgEKUIAC4REQ03MgpuSEDnvWX3Cmr4WnZu/wnI+1VigBhny94WbI1/MytXRxIf+OO+LxxRfGRiBTp2bjxhu5Rr6p8KyMAhSgAAVMF3AeXY7kdYOQ1uZ1+JPbmF4/K6QAQ77eNcCQr+dlauniQv5llyXit9+MOyEffJCFCy4Qd0Z4UIACFKAABSJRIOBD4tankLjlGdgQgDe5LY52XCzu6BvLQPOggFkCDPl6kgz5el6mli4u5Ldtm4S9e+3qXEuWZKJ5c26EZSo8K6MABShAAVME7FlbkCKWxow59ouqz5fUUj1c609ubUr9rIQC+QUY8vWuB4Z8PS9TSxcV8n1iZk6dOi4Eg8YdkC1b0uHic0qmurMyClCAAhQ4RQGxa2Pc3nfg2vAg7P4MVVlWvbuR2ewxwGGsDseDAmYLMOTriTLk63mZWrqokL9vnw1t2hip3uUKipBv/M+TBwUoQAEKUCAiBMT0nJQ1dyHuwCeqOYHYGkhv9TI81bpHRPPYCOsKMOTrjS1Dvp6XqaWLCvm//mpHz57GRljNm/vFdJ0sU8/JyihAAQpQgAKnKuD6414k7H4D7mo9RcB/EcHY6qdaJd9PgRIFGPJLJCpQgCFfz8vU0kWF/M8+c+Kuu4xfdV5wgU88eMuNsExFZ2UUoAAFKKAvINa8h91Y9U0dvgxxJ/9TuGvdxAds9TX5jpMUYMjXg2PI1/MytXRRIX/mzBiMGWNshHXjjV6xhGaOqedkZRSgAAUoQAEdAUfGBjE9py+yGg4Vof4GnbeyLAVMFWDI1+NkyNfzMrV0USF/woRYTJsWp84zbJgbo0dzIyxT0VkZBShAAQqUTkA8XBu/ayZcm8bCFshBwFkZh7uuQTCmUunez1IUMFmAIV8PlCFfz8vU0kWF/CFD4jF3rvEr0UmTctC3r/gVKQ8KUIACFKBAGQrY3AeQ/McgxB1coM7qj6uN9NQZ8Fa9oAxbwVNRoKAAQ77eFcGQr+dlaumiQv6VVybgp5+c6jxvvJEtHsLlbremorMyClCAAhQ4oUDs31+qnWvt3oOqXE7Nq5DRcoq4g1+VchQoVwGGfD1+hnw9L1NLFxXyO3VKEstmGhthLVyYKZbT5EZYpqKzMgpQgAIUKFYgSUzNSdw+Vb0ecLiQ0eIZMQ//Zj5cy2smIgQY8vWGgSFfz8vU0kWF/CZNXEhPNzbCWrUqA7VqBU09JyujAAUoQAEKFCcQv/M1JG8YDm+lc5GWOhOBxMbEokDECDDk6w0FQ76el6mlC4f8HLGQTv36ybnn2LUrHbGxpp6SlVGAAhSgAAXyBILit8VBMS3U/r9/bOROtvvmwl3zGvEzY+ooDwpEigBDvt5IMOTreZlaunDI37rVho4djd1uTzstgPXrM009HyujAAUoQAEKhATsOXvE3PuB8LlaIfOMSYShQMQLMOTrDRFDvp6XqaULh/ylSx3o3TtRnaN1az+++Ya73ZoKzsooQAEKUEAJxO7/r1g9517YfUfV3w93Xga/60zqUCCiBRjy9YbHciF/3bp14g74ehw+fFhJVKlSBS1btkRqaqqeTBmULhzy8+92262bD++/z91uy2AYeAoKUIACFUdA7FTr2vgQEva8pfos175PP/MFeMQKOjwoEOkCDPl6I2SJkJ8jJrO/+eab6s/Bgwdht9tRqVIl2Gw2HDt2DH6/H9WqVUOfPn1w2223IT7e2FG2vI/CIX/OnBiMHGm07dprvXj5Ze52W95jxPNTgAIUsIqA89gKsXNtPziyt6oueaqcL9a+n45AfF2rdJH9sLgAQ77eAEd9yP/zzz8xaNAgFeRvvvlmdO3aFWeccYYK+PIIioeINm3ahB9++AHvvvsuHA4HXnrpJTRr1kxPKgylC4f8Z5+NxdNPG7vdDhzowWOPucNwVlZJAQpQgAIVTUCumuPa+ABsQT+CthhkNh2H7Ab3iqUxjSWbeVAgGgQY8vVGKepDfseOHUUgHohbb70VMTHGTrHFHT6fD2+//TZeffVVLFu2TE8qDKULh/yHH47D7NnGCgdjx7oxdKgnDGdllRSgAAUoUNEEnEeXo/KKHvAnNkF669fgSzmrohGwvxYQYMjXG8SoD/lyDn6rVq20ev3HH3/gzDPL/wGjwiG/b994zJtnfFCZOjUbN97I3W61BpaFKUABClDAEBC/xUZALN7gSMoVkTvZeqpeIH5mLPDAgwLRJsCQrzdiUR/yQ92V03L++usvBAIBNG/e/DiFr776Cj169NDTCXPpwiH/6qsTsGSJsS7x//1fFi691B/mFrB6ClCAAhSwmoDNewSu9cNh9/yNY2d/KqbkOKzWRfanggow5OsNvCVC/v79+zFgwAA1914ebdq0waxZs5CcnIysrCxMmDAB//3vfyHv4EfSUTjkX3hhomij8T/jzz7LRIcOYpMSHhSgAAUoQIFSCsQc/kGsfX83HDm71DvSWs+G+/RrS/luFqNAZAsw5OuNjyVC/qhRo7Bnzx6MGDECHo8HzzzzjAr6vXr1woMPPqgeyp04cSI6d+6spxPm0oVDfps2Sdi3z3gIaunSDDRpIn7dyoMCFKAABShQkkDAg6S/nkDCtimwIYigPQ4ZzSYgp97d4k6+sRAFDwpEuwBDvt4IWiLk/+Mf/8Abb7yBevXqqd7LaTvXXnstvF4vrrnmGrEs5UgkJeXNS9QjCl/pwiG/fn0XcnKM/xlv2JCOqlXDd27WTAEKUIAC1hBwZP6J5DV9EZO+UnXI50oVd/BncXMrawwve5FPgCFf73KwRMhv27YtVq1aldtzOT9fbn41c+ZMdOnSRU+kDEvnD/liqX/Ur5+ce/Y9e9LhNKbn86AABShAAQoUKRD791dIWX07bAFj88Ss+oPF8pjjxcO1kbEfDIeNAmYKMOTraVoy5EuCwsFfj6VsSucP+fv329C6tUudOCUliM2bM8qmETwLBShAAQpErYDdvQ9VlnZWa9+np74K72n/iNq+sOEUKEmAIb8koYKvM+TreZlaOn/I37TJLjbyMqYU1a0bwG+/ZZp6LlZGAQpQgALWELD50hB0puR2xnn0Z7X+fTD2NGt0kL2gQDECDPl6l4YlQr58yPbzzz8v0HP50G3hn4Xm7OsRha90/pC/fLkDV1xhrF2cmurHokVifWMeFKAABShAgZCAPwdJm8cj7sBnONJpCYIxVWhDgQolwJCvN9yWCPktWrQQiwcUXD1AzssP/Sz0/fr16/V0wlw6f8ifP9+JPn0S1BnPP9+HDz805lfyoAAFKEABCjjS1yFlbV84M4yloDMbPYispo8QhgIVSoAhX2+4LRHyf/7551L1ukOHDqUqV1aF8of8//zHiaFDjZB/xRVevPaaeBKXBwUoQAEKVGyBYAAJO19F0p/jxcO1brE4ph1Zje5HVuNRgN3YIZ0HBSqKAEO+3khbIuTrdTlySucP+dOnx+CRR4zVEG691YPJk92R01C2hAIUoAAFylxAPlSbvG4gYg8tUuf2x9dHWupM+KpE1p4vZQ7DE1ZYAYZ8vaG3TMhfvXo15s+fD4fDgcsvvxxyCk+kH/lD/lNPxeK55+JUk4cMcWPcOE+kN5/towAFKECBMAk4xLScyr/8E3bvYXWGnNOvR0aL58Q8/EphOiOrpUDkCzDk642RJUL+999/j0GDBqFRo0Zqd9tdu3bh9ddfxznnnKOnUcal84f8sWPjMGNGrGrBmDFu3HcfQ34ZDwdPRwEKUCByBMQOtpV/vhSO7L9EuJ8Md63rI6dtbAkFykmAIV8P3hIh/9Zbb0W3bt3Qv39/1fsZM2bgp59+wpw5c/Q0yrh0/pA/dGg8/vMfY37lpEk56NvXW8at4ekoQAEKUKA8BWyeQwWWwbRnbQFsTgQS6pdns3huCkSMAEO+3lBYIuR36tRJLDm5CImJxhKUGRkZ6N69uwr6kXzkD/l33hkvlvw0Qv60adm44QZfJDedbaMABShAAbMEgn4kbpuChK2TcfTcBfAnp5pVM+uhgKUEGPL1htMSIb+o3W2jbcfb669PwHffOdXovf56Nnr1YsjXu5RZmgIUoED0CdizdyB57QDEHjVuSrmr90LaWe9GX0fYYgqUgQBDvh4yQ76el6ml89/J79kzEb/+6lD1f/BBFi64wG/quVgZBShAAQpElkDc3vfh2nA/7L5jqmHZdfogo/kkquEK1AAAIABJREFUwOmKrIayNRSIEAGGfL2BsEzIX7lyJeSmV/KQX9u3b4/8P5M/t9vtejphLp0/5Hfrloj1642Q/+WXmaL9gTCfndVTgAIUoEB5CNi8x0S4H4H4fXPV6QNi59r0M1+Ep8YV5dEcnpMCUSPAkK83VJYI+SXteBsiieQdb885Jwk7dhgfQhYvzhRLgDLk613KLE0BClAg8gVsYknMKssugCNnh2qsp+pFSG/1KgLxtSK/8WwhBcpZgCFfbwAsEfI//vjjUvX6qquuKlW5siqU/05+ixZJOHzYCPm//56BOnWM30rwoAAFKEABawm41g1C/N65yGz2b2TXHyRW0Ims3zJbS5u9sZIAQ77eaFoi5Ot1OXJKh0K+nGVUt64LXq9NNe7PP9NRifudRM5AsSUUoAAFTkHA5j6AYFyN3BpsvnTYs7dzFZ1TMOVbK6YAQ77euFsi5EfDSjpFDUso5GdnAw0aJOcW2bs3XezcqzeQLE0BClCAAhEmIO7gxO95G66NI8Wc+2lwn35thDWQzaFAdAkw5OuNlyVCfps2bbB69Wq9nkdA6VDIP3DAhtRUYzUFlyuILVsyIqB1bAIFKEABCpysgNzYKnn9MMQd+K+qwpfUHEc6LxdTc3gH52RN+T4KMOTrXQOWCPnRfid/yxYbOnUyQv7ppwfEB5ZMvVFkaQpQgAIUiBiBmEPfIXnd3XC496o2uav/U62eE4ytFjFtZEMoEI0CDPl6o2aJkN+qVSsMGjQodwnN4giGDBmipxPm0qE7+WvX2vGPfySpszVuHMCyZQz5YaZn9RSgAAXMFwi4kbT5MSRun6bqDtoTkHHGJOTUuVPcwTeeueJBAQqcvABDvp6dJUK+XEKzZs2aJ+y5TfwP9rvvvtPTCXPpUMj/+Wc7Lr/cCPmpqX4sWpQV5jOzegpQgAIUMFUgGEDlFd0Rc+xnVa03+Sykt54Fv5imw4MCFDBHgCFfz9ESIT/ap+ssWuTAjTcmqpHr1MmHTz8VT+LyoAAFKECBqBKI3zFdPWSb3XA4MpuMFjswxkZV+9lYCkS6AEO+3ggx5Ot5mVo6dCf/00+d6NcvQdV9ySU+vPMOQ76p0KyMAhSgQBgE1NKYMWK9Y3ucUbtYTceZvhq+lLZhOBurpAAFGPL1rgFLhPxoX13n3XeduO8+I+RfeaUXM2bk6I0iS1OAAhSgQJkKxP49XzxcOxg5tW9BZvMJZXpunowCFVWAIV9v5C0R8l955RXcc889ej2PgNKhO/mvvRaDUaPiVYtuvtmD5593R0Dr2AQKUIACFDhOwJ8F16YxSNj1mnop4EzB4fNWcuUcXioUKAMBhnw95KgP+YMHD8ZTTz0l1pc3lqAs6cjIyBCBehSmTTNWPyjPIxTyp06NxeOPG7/u7dvXg0mTGPLLc1x4bgpQgAJFCTjTViJ5bT84Mzepl72VOiAtdSYCiY0IRgEKlIEAQ74ectSHfBnYly1bpu7kX3311XA6nUUK+Hw+fPzxx5B3/Tt37oyJEyfqSYWhdCjkP/lkLCZPNkL+ffe5MWaMJwxnY5UUoAAFKHBSAmLlnITtU8XymBNgC3oRFBtaZTUaKf48KObjF/1vzkmdh2+iAAVOKMCQr3eBRH3Il92dO3cuXnjhBbjdbnTo0AEtW7ZElSpVxLLENhw+fBgbNmzAzz//jNjYWAwbNgzXXXednlKYSodC/iOPxGH6dGMVhlGj3Bg+nCE/TOSslgIUoIC2QPLagYjf+456nz+hobp776vcUbsevoECFDg1AYZ8PT9LhHzZ5ezsbHzyySf44YcfVKiX4V4eVatWxRlnnIFu3bqhd+/eSEgwHnCNhCMU8keMiMNbbxkh//HHczBggDcSmsc2UIACFKCAEIg58hMq/fJPuGvfJDa3ehpBZzJdKECBchBgyNdDt0zI1+t2ZJQOhfyBA+Px0UcxqlGTJ+fg1lsZ8iNjhNgKClCgIgrYfOniidoc8TBt9dzuOzLWw+9qWRE52GcKRIwAQ77eUDDk63mZWjoU8vv0icf8+UbIf+WVbFxzjc/U87AyClCAAhQonYDz6M9IEQ/Xymk5x9p/AtjspXsjS1GAAmEXYMjXI2bIP4GXnAL05JNPqilAx44dQ9OmTTF06FCcd955Rb5r//79YmWcSap8UGyKcvbZZ2PcuHGoV69ekeVDIf+aaxLEe4yHt956Kws9evj1RpGlKUABClDg1AQCPiRufVb8eUo8XOsXD9fG4Oi5X8NXqf2p1ct3U4ACpgkw5OtRMuSfwEuu3LN27Vr1UG+tWrXwwQcf4Omnn8a8efPQsGHDAu/0er1qdZ9WrVph5MiR6rVnnnkGdru92JV8QiH/sssS8dtvDvWejz7KQteuDPl6lzFLU4ACFDh5AXvWVnH3fgBiji1XlfiSzkB66izuXHvypHwnBcIiwJCvx8qQX4yXvHMv79hPmTIFl156aW6pK664QoTwrnjooYcKvPOLL77Ao48+iu+//x7x8cbGViUdoZB/wQWJ4mFhI+R/9VUm2rULlPRWvk4BClCAAqcqIH7jGrf3Xbg2PAi7X8zDF0d23X7IaP444Eg81dr5fgpQwGQBhnw9UEuF/BkzZqi76dWqVdNTKKL0Tz/9hDvvvBOLFy9GzZo1c0uMGTMGW7duxTvvGMuphQ45LWfHjh1o37493n//fch1+bt06SLWvB+jVvgp6giF/HPOSRLvNeZ9/vBDplgNiCH/lAeQFVCAAhQoQSBh6xS4No9XpQIx1ZDe6iV4qvekGwUoEKECDPl6A2OpkH/++efjyJEjuOCCC3D99derr3K6zMkcn332GUaMGIHVq1cjLs7YqEoecgrOwoULxR33rwpU279/f7UWv/xgIL/ft2+fWpO/Ro0aeO01Y/vzwkco5J95ZhIOHjTauWJFBho0CJ5Mk/keClCAAhTQELDn7EGVZZ3FzrXnIv3MlxGMq6HxbhalAAXKWoAhX0/cUiFfPuwqd7+VU2cWLFigwvlVV12Fa6+9ttiHX4vjkvPuH3jgAaxZs0ZtopU/5H/zzTf48ssvC7y1X79+2LRpk7rzHzrkh4HBgwdjyZIlqF49bym20OuhkN+okQuZmTb143XrMkRZhny9y5ilKUABCpRCIOCBPWcnAolNcgvbs7YgkNBIrKJj/D+YBwUoELkCDPl6Y2OpkJ+/6/JBWBmu5QZZcp58u3btcMstt+CSSy4pldDSpUtxxx13HDddZ/To0Wpazttvv12gHvlzeddf/gYgdMjQL+fwy+k7bdq0Oe68oZBfq5YLfr/xD8yWLelwuUrVRBaiAAUoQIFSCjgyNyF5TT/YvYdwpNOPCMZULuU7WYwCFIgUAYZ8vZGwbMj3+/349ttv8emnn6qQ36BBAxw9elTNr586dapaLedER3p6uppT/+yzz4olLXvkFr3sssvQvXt33H///QXe/u6776rlM+UHi5SUFPVa6E6+/MBQ1Lx8GfLFZxHUqZO3e+Lu3emIMZbM50EBClCAAqcqIH7DG79rNlybRsMWyFa1paW+Bnet6061Zr6fAhQoYwGGfD1wy4X8v/76Sy11KcN9VlYWevbsqebnn3XWWfB4PGoFnD179uD1118vUerf//43fvnlF0ybNg2nn366WMP+LbFZ1Sv4/PPPxRz6g2qpzNmzZ6N27dqQa+rLVXg6duyI8ePHq3X1Bw0ahEaNGqkPFUUdMuRnZACNGxsh3+EIYu9e8QMeFKAABShwygI2z99IXjcEcQfnq7r8cbXEw7WvwnvaRadcNyugAAXKXoAhX8/cUiH/hhtuUFNm5KZV8vvevXsjOTnvLrmkkWG8U6dOWLVqVYlS8kOBXBd/0aJFSEtLQ4sWLdQdfLmCzvLly3H77beruf/ytwTykNNzHn/8cdWGGHE7Xn7AkB8EXMXMv5Eh/8ABG1JTjfk5LldQTNdhyC9xYFiAAhSgQAkCsQcXiIA/CHbPAVXSXeNfSG/5AoKxp9GOAhSIUgGGfL2Bs1TIf/jhh1W4l/PvT3TIefOXX365nlQYSsuQv327Deeea4T86tUD4sHbzDCciVVSgAIUqDgCsQc+R6VVN6kOBx1JyDjjaeTUvpUP11acS4A9tagAQ77ewFoq5Muuy7nxrVu3FnfHU5WEXAXn8OHDuPnmm/VkyqC0DPkbNtjFUp9J6mz16wfE9CCG/DKg5ykoQAErCwTcqPzzxSLUxyCt9awCq+lYudvsGwWsLsCQrzfClgr506dPV3PkX3rpJZxzzjlK4rvvvlMbUvXp0wcDBgzQ0wlzaRnyV660iwd5jZDfooVfrOaTFeazsnoKUIACFhMIBuDIWAt/ct4qZnb3PrHBlZiaY+dKBhYbbXanAgsw5OsNvqVC/sUXX6wCvpw7n//YuHGjWq9ernYTSYcM+UuXOsSzA8b26e3a+cUmWwz5kTRGbAsFKBDZAvacvWLu/UDEHP0JRzouht/VMrIbzNZRgAInLcCQr0dnqZAvV9CRq+E4nc4CCvIB2g4dOoi75iv1dMJcWob8hQsdYiqREfK7dPGJdf2NJd54UIACFKDAiQViD8xD8h/3irXvD6uCmY0fRlaT0WSjAAUsKsCQrzewlgr5V199tdrA6l//+lcBBbn0pdyQSi6rGUmHDPnz5jnRt2+CatbFF/vEMwUM+ZE0RmwLBSgQgQK+DLHu/Sgk7H5DNS7grISMFpO59n0EDhWbRAEzBRjy9TQtFfIXL16spuU0a9YM9erVQ1BsgrJ582a1Q+2cOXNy5+nrEYWvtAz577/vFG02Qn6vXl6xfn9O+E7ImilAAQpEuYDz2K9i59q+cGZvUT3xVD4P6anTEUioH+U9Y/MpQIGSBBjySxIq+LqlQr7smlyrXm6GJYO93W5Hw4YN1WZY8mukHTLkv/VWDEaMiFdNu+Yar9hsiyE/0saJ7aEABSJDwJG5CVWWdoIt6EPQ5kRmk7HIbnifWEXHERkNZCsoQIGwCjDk6/FaLuTrdb98S8uQP2tWDEaPNkL+rbd6MHmyu3wbxbNTgAIUiGCB5LUD4Dz2i7h7Pwu+Su0juKVsGgUoYLYAQ76eqKVCvtvtVnfx5RSdnJzj74hPmjRJTyfMpWXIf/HFGDz2mBHy+/b1YNIkhvwws7N6ClAgigScR5fDV7ljbottvnRxF98OiE2ueFCAAhVLgCFfb7wtFfKHDRumlsls2rQpEhONFWtCh81mw//93//p6YS5tAz5zz0Xi6eeilNnuuceDx59lCE/zOysngIUiAIBm/coXBtGIH7f+zjW5k14al4ZBa1mEylAgXAKMOTr6Voq5MsNsOQDtqHdbvUoyr60DPlPPBGL5583Qv7w4W6MGuUp+4bwjBSgAAUiSCDmyE9IXtsfjpydqlU5Na9BepvXI6iFbAoFKFAeAgz5euqWCvldu3bFt99+i5iY6NjhUIb88ePjxMO2sWrUHn7YjfvvZ8jXu4RZmgIUsIxAwIvELZOQuHUybAggaI9DZrNHkV1voHi4VkzR4UEBClRoAYZ8veG3VMifMmUK6tSpo1bTiYZDhvyHH47D7NlGyB83LgdDhnijoelsIwUoQAFTBRyZm8Xd+36ISftN1etznYm01NfgT25l6nlYGQUoEL0CDPl6Y2epkP/kk0+qDa9k0G/QoIFaQjP/8fTTT+vphLm0DPn33x+Ht982Qv7EiTno358hP8zsrJ4CFIg0AbG51WlLUnN3rs2qfw8ymz4qHq41FiXgQQEKUEAKMOTrXQeWCvm33XbbCXsvd76NpEOG/HvuiceHHxrTi559Nge3386QH0ljxLZQgAJlI5Cw/SUkbHse6a1egbfaJWVzUp6FAhSIKgGGfL3hslTI1+t6+ZeWIb9v33jMm2eE/GnTsnHDDb7ybxhbQAEKUCDMAs4jS8U692cDduM3mQgGYPMdRTCmapjPzOopQIFoFWDI1xs5y4X8w4cPqyk7u3fvxpgxY5TGn3/+iWbNmunJlEFpGfJvuy0BX33lVGebOTMbvXsz5JcBPU9BAQqUl4A/B0mbH0XijpeQ1XCEeLB2fHm1hOelAAWiTIAhX2/ALBXyf/nlFzGnvT+qVq2K/fv3Y+3atdi5cyd69eqFl19+GXL1nUg6ZMi//voEfPedEfLnzMnGP//JkB9JY8S2UIAC5gk4MtYjZU1fODPWqkq9Ke1x9NwFeXfzzTsVa6IABSwowJCvN6iWCvk33XQTunXrhoEDB6JNmzZYvXq10vjwww8xd+5cvPfee3o6YS4tQ37v3glYutQI+e++m4WLL/aH+aysngIUoEAZCwSDiN85Ha4/H4Et4EZQLJCZ3fB+ZDYZxYBfxkPB01EgmgUY8vVGz1Ihv127dli+fDliY2PRtm1brFq1Smn4fD506tQJ8k5/JB0y5PfsmYhff3X878NIFs4/nyE/ksaIbaEABU5NwObej5R19yD20EJVkT++rni4dga8VSPrN6un1ku+mwIUKAsBhnw9ZUuFfDkd58svv4TL5SoQ8uXUncsvvxwrVqzQ0wlzaRnyL744EWvWGCF/3rwsdOzIkB9mdlZPAQqUlYC4g195eTfEpK9UZ5Q712a0nCIerq1cVi3geShAAQsJMOTrDaalQv69996L5ORkjB07Fp07d1Z38uWc/HHjxiEpKQkvvviink6YS8uQf/75idi40Qj5CxZk4qyzAmE+K6unAAUoUHYCMYd/QMqqW5DR4mm4T79B7FxrK7uT80wUoIClBBjy9YbTUiF/165duPPOO7F37141RUcG/oyMDDRt2hSvvPIK6tatq6cT5tIy5HfokIRt24xNu77/PhMtWzLkh5md1VOAAmEUcKatRCDudPUndNh8aQg6U8J4VlZNAQpUBAGGfL1RtlTIl133eDxYvHgxtm7divj4eDRq1AhdunQ5bvdbPabwlJYh/6yzkrBnjxHyly7NQJMmwfCcjLVSgAIUCKdA0C82s5qKpL8eF/PtL8Cxdh+Ku/YFdx0P5+lZNwUoYH0Bhny9MbZcyNfrfvmWliH/zDOTcPCg8Q/hr79moF49hvzyHRWenQIU0BWw5+xC8toBiD2yRL3Vn9AIR8/5EoH4WrpVsTwFKECBYgUY8vUujqgP+T169BCbSX2lei2Xz7SdYL7nd999p6cT5tIy5Ddp4kJ6ujFHdc2aDNSsyZAfZnZWTwEKmCgQt+9DuNYPh13sViuP7Nq3IfOMJ8X0nGQTz8KqKEABCgAM+XpXQdSHfDnX/p577lG9njZt2glD/pAhQ/R0wlxahvy6dV1iipER8v/8Mx2VKoX5pKyeAhSggAkCcp69a8ODiN/7rqot4KyM9DOnwVOztwm1swoKUIACxwsw5OtdFVEf8ovqrt/vh8NhrFjjdrsRFxenp1JGpQ8cSBd37vPudm3fno6EhDI6OU9DAQpQ4BQEktcOFAH/HVWDp2o3sfb9q2J6Tp1TqJFvpQAFKHBiAYZ8vSvEUiFfrocvl9Hs378/Lr30UiUxY8YMfP3112r5zJo1a+rphLn0rl3pYg5+Xsjfty9dPCAc5pOyegpQgAImCMh5+FWWX4isBvchu8FgPmRrgimroAAFGPLNvAYsFfJlwA+KzVceeeSR3EC/Z88ePPXUU+rnU6dONdPulOvaujUdjRsbId/pDIpVdjJOuU5WQAEKUCAcAvasLWLefRp8KWflVe/PBBxJ4Tgd66QABShwnADv5OtdFJYK+R07dsSiRYvUxlf5D7lW/iWXXIJly5bp6YS59IYNGWJdfJc6S2JiUKyXz5AfZnJWTwEK6AqIGyRxYlqOnH8fjK2GI52WcM17XUOWpwAFTBFgyNdjtFTIP/fcc/HNN98gJaXgpisHDx6EXIXn119/1dMJc2m5mk6bNkbIr1QpKB68ZcgPMzmrpwAFNARs3sNq5Zz4/R+rdwViq4v17z8Qd/PbadTCohSgAAXMEWDI13O0VMgfPny42gxr2LBhanfbQCCAv/76C8899xyqVaumvkbS8dtvGTj7bCPkV6sWwB9/iF9986AABSgQAQIxhxerte8d7j2qNe5q3cXqOS8jGFcjAlrHJlCAAhVRgCFfb9QtFfIPHTqEwYMHY+XKlQWW0jznnHPw8ssvIzk5stZtXr48A506GSG/Vq0AVq1iyNe7fFmaAhQwXSDgQdLmCUjYPhU2BBG0xyOj+UTk1O0nHq41lvvlQQEKUKA8BBjy9dQtFfJDXd+wYQO2b9+ultFs2LAhmjZtqqdSRqWXLMnE+ecbzw/Urx/AL78w5JcRPU9DAQoUI5CwbSpcf45Vr3qT2yA99TX4XWfQiwIUoEC5CzDk6w1B1Id8uWpOaJdbOT3nRIc9wtanXLQoExdfbIT8Jk0CWLqUIV/v8mVpClDAdAF/DiqvuATeqhchs6kI+/bI3GfE9H6zQgpQIOIFGPL1hijqQ37btm3FNJdVqtctWrQ44Y6369ev19MJc+kvv8xEz55GyG/Z0o/vv88K8xlZPQUoQIGCAjbP34hJ+x0eMec+9wi4Ge55oVCAAhEnwJCvNyRRH/L/+9//ondvYxv1jz82VoAo7rjqqqv0dMJcet68LPzrX4nqLG3b+sWmXQz5YSZn9RSgQD6B2L+/QvIfg2DzZYilMX+AP6k5fShAAQpErABDvt7QRH3If+yxxzBu3DjVa/lV/j1ajg8+yMJ11xkh/9xz/fj8c4b8aBk7tpMCUS3gz1bz7hN2zlTdCDhcYu79LHhq/DOqu8XGU4AC1hZgyNcb36gP+e3bt8eUKVPEzrGN0atXLxGUPy9WoF69eno6YS797rtZuPlmI+R37erDRx9lh/mMrJ4CFKjoAo701UhZ0w/OzA2KwlvpHKSJgB9IbFzRadh/ClAgwgUY8vUGKOpD/siRI/Hpp5+qufj5H8LNzxD6eaTNyX/jjWzccUeCauqFF/owdy5Dvt7ly9IUoECpBYIBsSzmS2J5zEdhC3rE4ph2ZDV+EFmNRor59zGlroYFKUABCpSXAEO+nnzUh3zZ3Y0bN+LYsWO46667MHv27GIFOnTooKcT5tKzZmWjf38j5Hfv7sPbbzPkh5mc1VOgwgrEHFyIyr9frfrvj2+AtNYz4avcqcJ6sOMUoED0CTDk641Z1If8/HPyL7nkEixcuFBPoBxLv/xytti8ywj5vXp58frrOeXYGp6aAhSwukDymrvEhlYxyGjxDILOFKt3l/2jAAUsJsCQrzegUR/yo3lO/tSp2bjvPiPkX3WVF9OnM+TrXb4sTQEKFCsgVsyJO/Ap3LVvzisS8HJqDi8ZClAgagUY8vWGLupDfv45+cV1PVLn5D/7bA4efDBeNfu667x46SWGfL3Ll6UpQIGiBJzHfkGyfLg2ewuOtXkbnpr/IhQFKECBqBdgyNcbwqgP+bK70Tonf9KkHIwebYT8W27xiFWCxAY0PChAAQqcrEDQj8StzyFxyyTxcK0fQZsTGc0nIaf+3SdbI99HAQpQIGIEGPL1hsISIT/U5fwbY+kxlE/pxx7LwfjxRsjv08eDZ55hyC+fkeBZKRD9Avbs7UhZ2x8xR5epzvgSmyK99WvwpbSL/s6xBxSgAAWEAEO+3mVgiZD/ySef4Morrzxhz4cPH67W04+kY9w4NyZMiFNN6tvXg0mTGPIjaXzYFgpEi0Dc3vfg2jACdl+aanJ2nbuQccZEwJEULV1gOylAAQqUKMCQXyJRgQKWCPlt27bFqlWrcjvWtWtXLFmypEBHC5fRYwpP6dGj3SLYGyH/7rs9IvAz5IdHmrVSwLoC8g5+1R/bi+k5XgRiTkP6mS9x51rrDjd7RoEKLcCQrzf8lgj5bdq0werVq3N7Xvjv8oWifqZHZX7pBx9049lnjZA/ZIgb48Z5zD8Ja6QABSwvkLBtGmIPL0Jaq1cRjKtp+f6ygxSgQMUUYMjXG3dLhPzCd+mLumsfiXfy77/fLaYQGSF/+HA3Ro1iyNe7fFmaAhVQQCyDGb9rNnLqijXvQzvVit1s1WGzV0AQdpkCFKgoAgz5eiPNkK/nZWrpIUM8/9/eeYBHVbRt+E0lIQm9gxRBAQFRRIpiQ0FQEcQCNj4QFARFpPcuHZEiKE0UxAJYUJSuSBMRC01QVHoTBNLr7j/P5D8hCSk7eJLsbp65Li81mZ0zc89Jcs973pmjjs0M1G327Rsn/ftT8m0FzMZIwMsI+EX9IWF7u0hA+M8SVaWfRFcb5mUj5HBIgARIIHMClHyzu4OSb8bL1trdusWrF2AlS/6gQXEqmk/JtxUwGyMBbyHgdErQiXcl9OBA8XFE61FFV3pZoq4bq6L3Pt4ySo6DBEiABLIkQMk3u0Eo+Wa8bK3dpUu8LFiQLPnDhsXJyy9T8m0FzMZIwAsI+MSfl7D9L0mBf1bp0SQFlpGI2nMkofi9XjA6DoEESIAEXCdAyXedFWp6heTXqFFDypQpkzLy06dPp/l/fOPMmTPy22+/mdHJ4do4G/+995IlH2fmd+umXjnPQgIkQAL/TyDg/AaVntNN/OLP6K/ElXxInZ4zU5yBxcmIBEiABPIdAUq+2ZR7heTPmjXLpVG/9NJLLtXLrUp4y+3SpcmSj7ffdu5Myc8t9rwOCbg9gaRYdTTmzeIXd0KcvgXVufcTJbZ8B6bnuP3EsYMkQAI5RYCSb0bWKyTfbMjuU/uJJxJk2bIA3aHJk2PVW28p+e4zO+wJCeQ9gYDz30rIoVEqPWeuJIVcl/cdYg9IgARIIA8JUPLN4FPyzXjZWvvRRxPkk0+SJf+NN2LkqacSbW2fjZEACXgQAXUMZtDxBRJXqrU6677U5Y7jeEwejelBE8mukgAJ5BQBSr4ZWUq+GS9ba7dunSArVyZL/syZMdKuHSXfVsBsjAQ8hIBv3GkJ2/eiBKoc/LjizST85uVMy/GQuWM3SYAEco8AJd+MNSXfjJettR96KEFWrUqW/DlzYuTRRyn5tgJmYyTgAQQUVXm8AAAgAElEQVQCz67Sp+f4JpzXvY0t85jaXPumiF+wB/SeXSQBEiCB3CNAyTdjTck342Vr7ZYtE2T16mTJnzs3Rtq0oeTbCpiNkYA7E0iKUufeD5HgEwt1Lx3+hSSyxlSJK9vOnXvNvpEACZBAnhGg5Juh93jJdzj+/3XuLozb19e9XvnerFmirF/vr3u+YEGMtGpFyXdhGlmFBDyegL96Y23Yns7iH31IjyWhSCMJrz1PHMGVPH5sHAAJkAAJ5BQBSr4ZWY+XfJyR7+PiGx/d7Zz8pk0T5ZtvkiV/0aIYeeABSr7Z7cvaJOCZBArvai2B/34jTh8/ib52kERX7i3im/y7gIUESIAESCBjApR8szvD4yX/k08+cVnyH3nkETM6OVz7zjsTZfPm5D/sS5ZES/PmSTl8RTZPAiTgDgR8Y45Jod3PqvScKZJYuL47dIl9IAESIAG3J0DJN5sij5d8V4c7fPhw9VbZ0a5Wz5V6TZokytatyZL/wQfRcu+9lPxcAc+LkEAuEyhweoUkBVdUQn/r5Ss7nTxBJ5fngZcjARLwbAKUfLP58zrJ37lzp/zyyy8SFxeXQuLUqVPy1Vdfyc8//2xGJ4drN2iQJDt3+umrLFsWLXfdRcnPYeRsngRylYBPYriEHugrQac+VJJfRS402iJO/7Bc7QMvRgIkQALeQoCSbzaTXiX577//vowZM0aKFi0qFy9elOLFi8u5c+ekQoUK0qFDB/2PO5V69ZLUwiNZ8j/7LFpuu42S707zw76QwH8h4H/xeym053nxiz2im4kvdreE11kgzsCS/6VZfpYESIAE8i0BSr7Z1HuV5N9///3Sv39/lfZyr9x4442ye/duOX78uIwdO1Z69eol2KTrTqVOnSTZuzdZ8r/8MkoaNHD9pCB3Ggf7QgIkkIqAI0EK/jVRCv49RXzEoTbXBkrUdSMlpmJ3vrmWNwoJkAAJ/AcClHwzeF4l+TfffHNKSo4l+cBx4MABGTVqlMp7/8CMTg7XrlkzSfUtWfLXrImSm2+m5OcwcjZPAjlKwDf6Tym093kJuPSjvk5iSA0dvU8Kq5Oj12XjJEACJJAfCFDyzWbZqyT/7rvvVrnty6RkyZJy++23y0cffaRTdZKSkqR+/fpul5NfrZpD/vwz+ez+DRuipE4dSr7Z7cvaJOBeBEJ+HyoFj8zQnYq55gWJvG4M31zrXlPE3pAACXgwAUq+2eR5leTjBJ0dO3bIihUrZPDgwXLp0iV59tln5ccff1QSvUHWrVtnRieHa1eq5JCjR5Ml/7vvolQ6ESU/h5GzeRLIWQJJMVL4l3YqNaeHxJe8P2evxdZJgARIIJ8RoOSbTbhXSX50dLS8/vrrMnDgQDl9+rR07txZjhw5IqGhoTJhwgS57777zOjkcO3y5R1y8mSy5G/fHilVq6oj9VhIgAQ8hkDAv5vEN+6MxJV9wmP6zI6SAAmQgKcSoOSbzZxXSX76oTvVOdTnz5/Xp+34+SXnvpuUmJgYvTjYvHmzfipQrVo16dmzp04Fyq5ggbFlyxY5ePBgplVLl3bI2bPJkv/DD5FSuTIlPzuu/D4JuAUBR5yEHBqjU3OcvgXV0ZibJSnkOrfoGjtBAiRAAt5KgJJvNrNeJ/mQcUTvU5+TbyG59dZUL6JxgdOgQYPU6Td7Zfr06VK2bFlZvny5TJo0Sb744gsl5JUzbQH7AiZOnCgRERFZSn6JEg61CEmW/J9+ilT7Byj5LkwLq5BAnhLwizwoYXs7S0DEbt2PhLC6ElFnISU/T2eFFycBEsgPBCj5ZrPsVZIPucY5+QkJCYIofuri4+Mjv/32m8t0sFhAxH7atGnSrFmzlM+1atVKmjRpIgMGDMiwLbx4q3Xr1tK1a1e9IMgqkl+kiFM9IfDR7ezeHSllylDyXZ4gViSB3CagfqcEHZ8vob8PER9HrDjVAZkxlV+RqKpDRXwDc7s3vB4JkAAJ5DsClHyzKfcqyb/rrrvkwQcflIcfflgKFix4BYmKFSu6TGfbtm3SqVMntSH2OyldunTK54YMGSJ///23LF26NMO2kKZTs2ZNueOOO/TLt7KS/NBQp0RFJUv+vn2R6lQgSr7LE8SKJJCLBHzizkrY/h5S4NwafdWkAuUkovZcSSh2Zy72gpciARIggfxNgJJvNv9eJfk4Jx8n6VxN/n16bF9++aX06dNHv1CrQIECKd+ePHmyrF+/Xp1rn/zHPnX5+OOPZdGiRerttZ/p4zqzk/zgYKfExiZL/sGDEWrvgNnksTYJkEDuEChw6iN9/j1KbOlHJLLmNHEGFMudi/MqJEACJEACmgAl3+xG8CrJf+655wR59Ndd9983wCHvvm/fvrJnzx4JDLz8KB6Sj+M4V69enYb0yZMnpU2bNjJv3jypW7euPsozO8kPCHBKYmKy5P/5Z4SEhZlNHmuTAAnkEgGVqhP6W09JKNJInaTzlHpzbfLPLQsJkAAJkEDuEaDkm7H2KsnftGmTzJo1S9q2bSuVKlVSf4fT/iFu3Lixy3S2b98uHTt2vCJdB+fvHz16VJYsWZKmLStNBwsDFFckP3X3jhyJkOBgl7vHiiRAAjlIwE9tqi1wbq1EV0n+eWYhARIgARLIewKUfLM58CrJr1GjRqajN914i5NxbrvtNpkyZYrcf//ll9q0aNFCmjdvLr1790651okTJ6Rp06ZSuHDhlIVFYmKiREZGSpEiRaRLly7y/PPJj/pTl9SSf+JEhAQEmE0ea5MACdhMwOmQ4COz1PGYo8THmSCX6n4o8aUesPkibI4ESIAESOBqCFDyzah5leRDtrMq5cuXN6IzcuRIneM/c+ZMdfJNGVm8eLHMmTNHVq1aJefOnZP+/fvLwoUL9cbcf/75J03byMnv1auX4OkCXsaFf7KS/NOnI8Q3+TRNFhIggTwg4Bt7QsL2dZNA9YIrlKTgyhJee54kFmmYB73hJUmABEiABNIToOSb3RNeJflmQ8++dnx8vD4Gc+PGjRIeHi54UoAIfr169VLScdauXatTg9IXk3QdHx+nnDkTmX2HWIMESCBHCASe+UydntNTfBMv6vZjVd59ZI1J4vQvlCPXY6MkQAIkQALmBCj5Zsy8SvKRMpM+D9/C4avC5IjG48z7Z555RkXN8z5sbqXrYAPuiROUfLNbl7VJ4L8T8EmMkJCDAyT4ZPIeG4d/EXVyzhsSV6btf2+cLZAACZAACdhKgJJvhtOrJH/27Nny3nvvqTfHVpA6depokd+3b58S6BPyyCOP6JQaHH2JTbI9evQwI5UDtS3Jx1GaR45Q8nMAMZskgSwJYINt0R336Pz7+KJ3qLPv3xZHUAVSIwESIAEScEMClHyzSfEqyR81apROncGpOKkLTsKB4L/66qv6/Hrk0q9bt86MVA7UtiQfL8X66y9Kfg4gZpMkkC0BbLQVZ6LEVHpZHY3pl219ViABEiABEsgbApR8M+5eJfm33nqrbN26Nc259sCB3Pp77rlHf8+pzrtGTj1kP6+LJfmFCzvljz8o+Xk9H7y+9xPwjTksBY/MlMjrJ4r4+nv/gDlCEiABEvAiApR8s8n0Kslv2LChTJ06VZo0aZKGwq5du6Rnz55a8nFaDl6Y5U6R/BIlHLJ/f5TZzLE2CZCA6wTU4r7AqQ8l9EBf8U2KkKhrB0p01cGuf541SYAESIAE8pwAJd9sCrxK8qdNm6aPtLzjjjt02k6AOnj+2LFj8u233+qc/IEDB0r9+vXllVde0Xn5eV2sSH7p0g71Zl1Kfl7PB6/vnQR8Ei6qt9W+KkFnVugBOgKKS0St2RJfsqV3DpijIgESIAEvJUDJN5tYr5J8DH3FihV6c+2pU6d0ak7JkiX1i6rat2+vpR8RfJyw4w7Fkvzy5R0qfYiS7w5zwj54F4GAf7eos+9fEL/Y43pg8cXvk/Bac8RZoLR3DZSjIQESIIF8QICSbzbJXif5ZsPP29qW5Fes6FBpRJT8vJ0NXt2rCDjiJeTPcRJ8eJr4iFOcvgUk8roxEntNV7W51serhsrBkAAJkEB+IUDJN5tpj5f8N998M+U4zOnTp2c5eqTpuFOxXOPaax3y/feUfHeaG/bFswn4xJ+Xotsbi1/8aUkMrSXhdRZIUugNnj0o9p4ESIAE8jkBSr7ZDeDxkt+iRQtZvXq1HjXScjIreEnWhg0bzOjkcG1L8q+/Pkm2bInO4auxeRLIXwQCzm+UwHNrJaraSBG/oPw1eI6WBEiABLyQACXfbFI9XvLNhutetS3JDwx0yvHjPELTvWaHvfEkAj7x5yTkj+ESdd0ocQaW9KSus68kQAIkQAIuEqDkuwjq/6t5leQ7HA79llur4LjMixcvSqNGjSQ0NNSMTC7UtiTfz8+pNgpT8nMBOS/hhQQCzq1Tm2u7q9ScMxJXoqWE3/Qh8+69cJ45JBIgARKg5JvdA14h+REREdK9e3d59tlnpXnz5prA4MGD5ZNPPtH/XapUKfn444+lTJkyZnRyuLYl+TfdlCRr1zJdJ4dxs3lvI5AUq6P3BY+9pUfm9C0okdUnSmz5DpR8b5trjocESIAEFAFKvtlt4BWSP2bMGNm5c6dg422VKlXkwIED0qZNGxk9erR+0+3YsWOlUKFCgnruVCzJv+WWJPn6a0q+O80N++LeBPwi9kmhvZ3FP3K/7mhCoXoSUXu+JIVUc++Os3ckQAIkQAJXTYCSb4bOKyQfG25nz54tNWrU0KPHiTtfffWVrFq1Sv//4cOH5bnnnpONGzea0cnh2pbk33prkuorJT+HcbN5byDgdEjw0dkqgj9SfJzx6nBMX4mu0luirx0k4hvgDSPkGEiABEiABDIhQMk3uzW8QvJvvPFG+fXXX9Xx18nnX+NttojoDx06VP8/Xop100036TruVCzJb9w4UT7/PMadusa+kIB7EnAkSpFdD0jAxe8lKaiiit7PlYSit7lnX9krEiABEiABWwlQ8s1weoXkN2jQQB1BuUUCAwO10Dds2FCGDx8uDz30kKYRHx8vjRs3ll27dpnRyeHaluQ3aZKo9g9Q8nMYN5v3EgK+MYel4N9T1Uk6Y8UZUNhLRsVhkAAJkAAJZEeAkp8dobTf9wrJb9u2rd5oW79+fdm8ebN07dpVNm3apDZoJB+lt3v3bhkwYIDKe//ajE4O17Yk/847E2X5ckp+DuNm855IIClKQn8fKrHlnpHEwrd44gjYZxIgARIgAZsIUPLNQHqF5M+fP1+WLFki9913n34xVt26dXVePsrp06elV69eOl1n4MCBZnRyuLYl+ffckygffUTJz2HcbN7DCPhf+knC9nYR/+hDkliwqlxouFnE3/2OwvUwrOwuCZAACXgsAUq+2dR5heQjRWfChAk6in/dddfJiBEjpFixYprEqFGjZPv27fLBBx9I0aJFzejkcG1L8osWdcrBgzwnP4dxs3lPIeBMkuDDb0jIn6+pzbWJ4vTxl+iqgyW68qvqaEw/TxkF+0kCJEACJGAzAUq+GVCvkPyshnzy5EkpUaKEztd3t2JJfqNGibJyJSP57jY/7E/uE/CNOaqi910l8OJWfXFE8HE0JlN1cn8ueEUSIAEScDcClHyzGfF6yTfDkbu1Lcl/4IEEWbQoNncvzquRgJsRKHB6uYT+9qr4Jl7SPYsp/z+JvH48U3TcbJ7YHRIgARLIKwKUfDPylHwzXrbWtiS/VasEWbCAkm8rXDbmcQRCf+stwcfniyOgqETcMEviS7XyuDGwwyRAAiRAAjlHgJJvxpaSb8bL1tqW5LdpkyBz51LybYXLxjyPQFK0hB4cpF5sNVAcQWU9r//sMQmQAAmQQI4SoOSb4aXkm/GytbYl+W3bJshbb1HybYXLxtybgCNBCv41QZKCq0hc+Wfcu6/sHQmQAAmQgFsQoOSbTQMl34yXrbUtyX/88QR15Ccl31a4bMxtCfhFHVKba5+XgPBd4vQLkX8bbRVHwWvdtr/sGAmQAAmQgHsQoOSbzQMl34yXrbUtyW/fPkFmzKDk2wqXjbkfAXXUbdDJxSolZ4D4qJdcoURf01W9uXa0iF+w+/WXPSIBEiABEnArApR8s+mg5JvxsrW2JflPPx0v06bF2do2GyMBdyLgE39ewn57RQqcXam75QgsJeG15khCiWbu1E32hQRIgARIwI0JUPLNJoeSb8bL1tqW5D/7bLxMnUrJtxUuG3MbAgHnv5WwfV3FL+6U7lNciZYSUetNcQaWcJs+siMkQAIkQALuT4CSbzZHlHwzXrbWtiS/Y8d4mTSJkm8rXDbmNgSCTiyWsP09xOkbLJHVx0ts+U7qzbU+btM/doQESIAESMAzCFDyzeaJkm/Gy9balud07hwv48dT8m2Fy8bch4DKxS/45xiJK9tekkKud59+sSckQAIkQAIeRYCSbzZdlHwzXrbWtiT/hRfiZexYSr6tcNlY3hDA5tpjc8Uv9qhEXf9a3vSBVyUBEiABEvBKApR8s2ml5JvxsrW2JfndusXL6NGUfFvhsrFcJ+ATd1al5XSXAufW6mtfunm5xJdonuv94AVJgARIgAS8kwAl32xeKflmvGytbUl+9+7xMnIkJd9WuGwsVwkE/vO12lzbQ3wTzunrxpZuK5E1p4kzoGiu9oMXIwESIAES8F4ClHyzuaXkm/GytbYl+S+/HCfDhsXb2jYbI4FcIZAULaG/D5Hg4wv05Rx+oRJZY4rKv3+Sm2tzZQJ4ERIgARLIPwQo+WZzTck342VrbUvye/WKk8GDKfm2wmVjOU7AL2KPFNrTSfyjftfXSijcQMJrz1Nvr62S49fmBUiABEiABPIfAUq+2ZxT8s142VrbkvzeveNk4EBKvq1w2ViOE/C/tEuK7MTLrJwSXaW/+qefiK9/jl+XFyABEiABEsifBCj5ZvNOyTfjZWttS/L79YuTfv0o+bbCZWO5QiDo+EJJDK0liUUa5sr1eBESIAESIIH8S4CSbzb3lHwzXrbWtiR/wIA46dOHkm8rXDZmO4HAM59K0MkPJbzu+4zY206XDZIACZAACWRHgJKfHaG036fkm/GytbYl+UOGxMkrr1DybYXLxmwj4JMYIaEH+knQqaW6zchqIyWmSm/b2mdDJEACJEACJOAKAUq+K5Qu16Hkm/GytbYl+UOHxknPnpR8W+GyMVsI+F/cIYX2Pi9+MYd1e/FF75SI2m+JI6iCLe2zERIgARIgARJwlQAl31VSyfUo+Wa8bK1tSf6IEbHSo0eCrW2zMRL4TwQciVLw70nqn8nql0SSOH0CJKracImp9LL6reH7n5rmh0mABEiABEjgaghQ8s2oUfLNeNla25L80aNjpVs3Sr6tcNnYVRPwjTmmj8YMuPSDbiMx5HoVvV8giYXqXnWb/CAJkAAJkAAJ/FcClHwzgpR8M1621rYkf+zYWHnhBUq+rXDZ2FUT8In/R4ptbyy+8WclpkIXibx+rIhfwatujx8kARIgARIgATsIUPLNKFLyzXjZWtuS/PHjY6VzZ0q+rXDZmBkBpzPNG2oDzm8UH0ecxJdsadYOa5MACZAACZBADhGg5JuBpeSb8bK1tiX5EybEynPPUfJthcvGXCYQ8O9mCTk0Qi7dtEycgcVd/hwrkgAJkAAJkEBuEqDkm9Gm5JvxsrW2JfmTJ8fK//5HybcVLhvLnoAjXkL+fE2CD78hPuqttbGl20rEjYuy/xxrkAAJkAAJkEAeEKDkm0Gn5JvxsrW2Jfmvvx4rzzxDybcVLhvLkoBf1O8StqeLBET8ouslhtaR8DoLJCm0BsmRAAmQAAmQgFsSoOSbTQsl34yXrbUtyX/jjRh56qlEW9tmYySQIQGVex90fKGE/j5Y5dzH6CrRlXqq4zGHqbfYFiA0EiABEiABEnBbApR8s6mh5JvxsrW2JfkzZsRI+/aUfFvhsrErCPgkhqvo/fNS4NzX+ntJBcpKRK23JKH4PaRFAiRAAiRAAm5PgJJvNkWUfDNetta2JH/WrBh54glKvq1w2diVBNQLror8eL86/36nxJV6WCJqTudGW94nJEACJEACHkOAkm82VZR8M1621rYkf/bsGHnsMUq+rXDZWDKBdEdj+kb/JYEXtkpsuWfSHJlJXCRAAiRAAiTg7gQo+WYzRMk342VrbUvy3347Rh55hJJvK1w2Jn4ReyRsX3eJvGGmelvtTSRCAiRAAiRAAh5NgJJvNn2UfDNetta2JH/evBhp3ZqSbyvc/NyY0yHBR2dLyB8jxccZL4khNeRC4+0qcu+Xn6lw7CRAAiRAAh5OgJJvNoGUfDNetta2JH/Bghhp1YqSbyvcfNqYb+wpFb3vJoH/fqMJJAVVlPDa8ySxaON8SoTDJgESIAES8BYClHyzmaTkm/GytbYl+e+8EyMPPkjJtxVuPmws8MxKCfvtZfFNuKBHH1u2nURWnyLOgML5kAaHTAIkQAIk4G0EKPlmM0rJN+Nla21L8t97L1patEiytW02lo8IqPSc0P09Jfjke3rQDv/CElnjdYkr+3g+gsChkgAJkAAJeDsBSr7ZDFPyzXjZWtuS/CVLoqV5c0q+rXDzWWOh+3tJ8ImFEl/kdomo/bY4givmMwIcLgmQAAmQgLcToOSbzTAl34yXrbUtyV+6NFruu4+Sbytcb2/MifvF9/IxmElREnTyfYmt0JkbbL197jk+EiABEsinBCj5ZhNPyTfjZWttS/I//DBamjal5NsK14sb8405KmF7X5DY8h0krtxTXjxSDo0ESIAESIAELhOg5JvdDZR8M1621rYk/+OPo+Xuuyn5tsL10sYKnPpYQg/0Ft/EcHH4hcm/TXbzrbVeOtccFgmQAAmQQFoClHyzO4KSb8bL1tqM5NuK06sb80m4pOU+6PQyPU5HQDGJuGGWxJd6yKvHzcGRAAmQAAmQgEWAkm92L1DyzXjZWpuSbytOr20s4MI2nZ7jF3tUjzG+eFMl+HPEEVTWa8fMgZEACZAACZBAegKUfLN7gpJvxsvW2pbkf/55tDRuzHQdW+F6SWMF/54iBQ+NFR9xiNMnUKKuGyUxFV9Um2vVplsWEiABEiABEshHBCj5ZpNNyTfjZWttS/K/+CJaGjak5NsK10saCzr+jnrB1SuSGHqDenPtfEkKq+0lI+MwSIAESIAESMCMACXfjBcl34yXrbUtyV+1KkpuvdVha9tszEMJOJ0iOB7T1z95AOr/g068q99eK37BHjoodpsESIAESIAE/jsBSr4ZQ0q+GS9ba1uS//XXUXLLLZR8W+F6YGM+8edV1L6nJAVVkKjqEz1wBOwyCZAACZAACeQcAUq+GVtKvhkvW2tbkr9mTZTcfDMl31a4HtZYwPmNanNtN/GLP617fqHBN5JY+BYPGwW7SwIkQAIkQAI5R4CSb8aWkm/Gy9baluSvWxcldetS8m2F6ymNJcVKyKFRUvDom7rHTt9giaw+Xr3oqtPlt9l6yljYTxIgARIgARLIQQKUfDO4lHwzXrbWtiR/w4YoqVOHkm8rXA9ozC9yvxTa01n8I/fp3iaE3SwRddTm2pDrPKD37CIJkAAJkAAJ5C4BSr4Zb0q+GS9ba1uS/803UVKrFiXfVrhu3liBUx9K2P6XxccRJ051QGZM5d4SVXWQ2nAb6OY9Z/dIgARIgARIIG8IUPLNuFPyzXjZWtuS/E2boqRmTUq+rXDdvDH/iz9IkR/vF0eBshJRa64kFGvi5j1m90iABEiABEggbwlQ8s34U/LNeNla25L8zZujpHp1Sr6tcN2xMRW1F98CKT0LPPuFJBRtIs6Aou7YW/aJBEiABEiABNyKACXfbDoo+Wa8bK1tSf62bZFSrZo6H53FOwkkRUvo70PEL+qgXLrlC7Wh1s87x8lRkQAJkAAJkEAOEqDkm8Gl5GfBKyYmRiZMmCCbN2+WS5cuKRGvJj179pTbb789w0999dVXMn/+fPn7778lJCRE7rjjDunXr58UK1Ysw/qW5G/fHilVq1LyzW5dz6jtH/6LhGFzbfQfusPhteZIXLmnPaPz7CUJkAAJkAAJuBEBSr7ZZFDys+A1aNAg2bt3r0yfPl3Kli0ry5cvl0mTJskXX3whlStXTvPJTZs2SY8ePWT8+PHSsmVLOXXqlHTv3l0qVaoks2bNylLyd+yIlCpVKPlmt66b11ZvrQ0+MlMdjzlGfJwJ4lTR++hrB0p05T6X32br5kNg90iABEiABEjAnQhQ8s1mg5KfCS9E7hGxnzZtmjRr1iylVqtWraRJkyYyYMCANJ+E+B85ckReeumllK8vWrRIC/6PP/6YpeTv3BmpFgOUfLNb131r+8YeVy+26iqBFzbrTiYFV5Hw2vMksUgD9+00e0YCJEACJEACbk6Akm82QZT8THht27ZNOnXqJN99952ULl06pdaQIUN0Os7SpUuzJT1mzBjZsWOHfPnll1lK/q5dkXLNNZT8bIF6QIWAf7dIoV+fEt/Ei7q3MeWekajqE8XpH+YBvWcXSYAESIAESMB9CVDyzeaGkp8JL4h5nz59ZPfu3VKgwOUTUSZPnizr16+XNWvWZEnaSt+ZOXOm3HPPPVlK/k8/RUqFCpR8s1vXPWv7xJ2VYtsbqVfXJkrEDTMkvnQb9+woe0UCJEACJEACHkaAkm82YZT8THgh/aZv376yZ88eCQy8/IIiSP6GDRtk9erVmZJetmyZjB07VoYNGyaPPfZYpvWsjbe//BIp5cpR8s1uXTeqrU7PEb+CKR3yv7BdHMEVxRFU3o06ya6QAAmQAAmQgGcToOSbzR8lPxNe27dvl44dO16RrjN48GA5evSoLFmy5IpPOp1OLfd4CoBc/ttuuy3L2bAkf/fuSClThpJvduu6QW1HohT8e5IEnXxfLjTarM67z/gUJTfoKbtAAiRAAiRAAh5PgJJvNoWU/Ex4RUREaEmfMmWK3H///Sm1WrRoIc2bN5fevXtf8b2qBWMAACAASURBVMnhw4fL999/r4/RrFixYrYzYUn+nj2RKu+fkp8tMDeq4Bv9lxTa+7wEXNqpexVdsYfKvR/vRj1kV0iABEiABEjAuwhQ8s3mk5KfBa+RI0fqk3GQV1+mTBlZvHixzJkzR1atWiXnzp2T/v37y8KFC1WqTTlZt26dPnEHaT7ly7uWpmFJ/r59kVKyJCXf7NbNo9rqaU2BU0sl9EA/8U2K1J2IqdBFIq8fmyZlJ496x8uSAAmQAAmQgNcSoOSbTS0lPwte8fHx+lz8jRs3Snh4uNSoUUNH8OvVq6dPzenQoYOsXbtWn4WP1B58zd/f/4oWkb+fkfhbkr9/f6SUKEHJN7t1c7+2T8IFCf2tlwSd+VRf3BFYUm2ufVPiS7bI/c7wiiRAAiRAAiSQzwhQ8s0mnJJvxsvW2pbkHzgQod6Ka2vTbMxmAn5Rh6TwrlbiF3dCtxxXorkS/NniLFDK5iuxORIgARIgARIggYwIUPLN7gtKvhkvW2tbkv/77xFSpIitTbMxuwk4EqTIzmbiH7lfpea8JrEqRUesCbT7WmyPBEiABEiABEjgCgKUfLObgpJvxsvW2pYjHjoUIYUK2do0G7OBgE9iRJqXWGGzrY8jXpJCa9jQOpsgARIgARIgARIwIUDJN6GlYpHq2Ecmg5sxs622Jfl//hkhYXwhqm1c/3ND6kci6PgCCTk0Wi7WXyVJYXX+c5NsgARIgARIgARI4L8RoOSb8aPkm/GytbYl+X/9FSGhobY2zcaukoBP/D8Stq+HFDiX/LKz+GL3yKVbPr/K1vgxEiABEiABEiABuwhQ8s1IUvLNeNla25L8w4cjpODlF6baeg025jqBwHNrleC/KL5K9FHiSrVWm2un8yVXriNkTRIgARIgARLIMQKUfDO0lHwzXrbWtiT/yJEICQ62tWk2ZkIgKUZC/xgmwcfm6k85/UIkovpkiSv3NDfXmnBkXRIgARIgARLIQQKUfDO4lHwzXrbWtiT/+PEICQy0tWk25iIBbK4t8sN94h/1m/5EQuH6El57njgKVnWxBVYjARIgARIgARLIDQKUfDPKlHwzXrbWtiT/5MkI9RItW5tmYwYEQve9JEEnl0h0lb4Sfe0AEd8Ag0+zKgmQAAmQAAmQQG4QoOSbUabkm/GytbYl+adORYifn61Ns7EsCPgk/Js2zz4xUp1/v08SizQkNxIgARIgARIgATclQMk3mxhKvhkvW2tbkn/mTATfq2Qr2cwbCzzzuYT91lMiq0+SuLLtcumqvAwJkAAJkAAJkMB/JUDJNyNIyTfjZWttS/LPno2wtV02lgEBFa0PPThAgk8u1t9MCrpG/r39F6bm8GYhARIgARIgAQ8hQMk3myhKvhkvW2tD8n18nHLmTKSt7bKxtAT8L/0oYXu6iH/MX/ob8UVul4jac8URfA1RkQAJkAAJkAAJeAgBSr7ZRFHyzXjZWhuS7+fnlFOnKPm2grUacyZJwb9fl4J/jVOvdk4Sp4+/RFUdKjGVX1GrK26CyBHmbJQESIAESIAEcogAJd8MLCXfjJettSH5/v5OOXmSkm8rWDTmdErhnx+RwPMbddOJBatJRJ0FkljoZtsvxQZJgARIgARIgARyngAl34wxJd+Ml621IfmBgU45fpySbyvY/28s6Nh8CTvQW2LKP6c22r6mHpuE5MRl2CYJkAAJkAAJkEAuEKDkm0Gm5JvxsrU2JD8oyClHj1Ly7QDrk3BJnL4FlMwHJTenovn+l37g0Zh2wGUbJEACJEACJJDHBCj5ZhNAyTfjZWttSH5wsFOOHKHk/1ewARe2StjeFySuVGuJqj7uvzbHz5MACZAACZAACbgZAUq+2YRQ8s142Vobkl+woFMOH6bkXzVYR4LaWDtebbCdKj7iVJH8IHU05q/iCCp71U3ygyRAAiRAAiRAAu5HgJJvNieUfDNettaG5IeGOuWvvyj5VwPWL+oPFb3vIgHhP+uPJ4bWkvDa8yUprNbVNMfPkAAJkAAJkAAJuDEBSr7Z5FDyzXjZWhuSHxbmlD//pOQbgVW59kEn3lUvtxooPo5o/dHoit0lqtrIy/n4Rg2yMgmQAAmQAAmQgLsToOSbzRAl34yXrbUh+YULO+WPPyj5JmBDDvSXgsfe0h9JCiytXmz1liQUv9ekCdYlARIgARIgARLwMAKUfLMJo+Sb8bK1NiS/SBGn/P47Jd8ErP/F76XIzhYSX7KlRNwwS5yBxU0+zrokQAIkQAIkQAIeSICSbzZplHwzXrbWhuQXK+aQAweibG3X6xpLihWfpEgl8yVShuav8vATw25Sb65VEFlIgARIgARIgAS8ngAl32yKKflmvGytDT8tUcIh+/dT8jMD6xexTwqpzbWOgOJy6ZaVSup9bZ0DNkYCJEACJEACJOAZBCj5ZvNEyTfjZWttSn4WOJ0OCVZ59yF/jFCba+PU4Zg+cqn+V5JQ9HZb54CNkQAJkAAJkAAJeAYBSr7ZPFHyzXjZWhuSX6qUQ/buZSQ/NVjfuNMStu9FCTy/QX85KaiCRNSaKwnFmtjKn42RAAmQAAmQAAl4DgFKvtlcUfLNeNlaG5JfurRD9uyh5FtgA89+JWH7e4hvwnn9pdjSj0pkzWniDChiK3s2RgIkQAIkQAIk4FkEKPlm80XJN+Nla21IfpkyDtm9m5IPsEHH5knYgT6ascO/kETWmCJxZdpxc62tdx0bIwESIAESIAHPJEDJN5s3Sr4ZL1trQ/LLlnXIr79S8gEWaTpFtzeSpJDr1Ztr54kjuJKtvNkYCZAACZAACZCA5xKg5JvNHSXfjJettSH55co55Jdf8qnkO5PEN/Z4Gpn3i/pdkoKvVcbvbytrNkYCJEACJEACJODZBCj5ZvNHyTfjZWttSH6FCg756af8J/m+McfU5tqu4hdzWC402qpy7ovaypaNkQAJkAAJkAAJeBcBSr7ZfFLyzXjZWhuSf801Dtm1K39JfoHTKyT0t17im3hJ84yoOUNiK3S0lS0bIwESIAESIAES8C4ClHyz+aTkm/GytTYkv2JFh/z4Y/6QfJ/EcAk90FeCTn2oOTr8i0jEDTMlvnRrW7myMRIgARIgARIgAe8jQMk3m1NKvhkvW2vnJ8n3v/i9enPtCzo9ByW+2N3q7Pu3xBFUzlambIwESIAESIAESMA7CVDyzeaVkm/Gy9bakPzKlR3yww/eHckPOL9RCv/UVr2z1iFOn0CJqjZCYir1UEdj+trKk42RAAmQAAmQAAl4LwFKvtncUvLNeNlaG5JfpYpDduzwbskXR7wU+eE+8XHESHidBZIUdqOtHNkYCZAACZAACZCA9xOg5JvNMSXfjJettSH5117rkO+/9zLJdzpFH4UZWj2Fl2/sCXEEFBPxC7aVIRsjARIgARIgARLIHwQo+WbzTMk342VrbUh+1aoO2b7deyTfJ+FfCdv/igSeWy0XGnyrova1bGXGxkiABEiABEiABPInAUq+2bxT8s142Vobkl+tWpJs2xZta7t51VjAv5skbK86+z7upO5CdMUeElV9fF51h9clARIgARIgARLwIgKUfLPJpOSb8bK1NiT/+uuTZMsWD5d8R5yEHBorwUdmqM21TnH6Bkvk9a+ps+87q821apAsJEACJEACJEACJPAfCVDyzQBS8s142Vob/lu9epJs3uy5ku8XeVBF7ztLQMRuzSYhrK5E1J6fJh/fVmhsjARIgARIgARIIF8SoOSbTTsl34yXrbUh+TVqJMl333mm5PuqM++LbWuoT81xqhh+TOVXJKrqUBHfQFs5sTESIAESIAESIAESoOSb3QOUfDNettaG5NesmSSbNnmm5ANG2N5uglz8iNpvS0KxO23lw8ZIgARIgARIgARIwCJAyTe7Fyj5ZrxsrQ3Jv+GGJPn2W8+RfD+VlpP6nHufxAgRZ4I4cTwmCwmQAAmQAAmQAAnkEAFKvhlYSr4ZL1trQ/Jr1UqSb77xAMlPipHQP4ZK8LF56oVW70hcmUdtZcHGSIAESIAESIAESCArApR8s/uDkm/Gy9bannKEJqL3hfZ0Fv+og3r8ccWbSfjNy3lyjq13AxsjARIgARIgARKg5Nt3D1Dy7WNp3JJ1uuTZsyrlxR2L06GOxZyljsccJT5IyRFfib62v0RX6a821/q7Y4/ZJxIgARIgARIgAS8lwEi+2cRS8s142Vobkn/jjUmyfr37pev4xp6QsH3dJFBtqkVJCq4s4bXnSWKRhrYyYGMkQAIkQAIkQAIk4AoBSr4rlC7XoeSb8bK1NiS/bt0kWbfOzSRf5d8X23qTenPtKT3e2LJPSmSNyeL0L2Tr+NkYCZAACZAACZAACbhKgJLvKqnkepR8M1621nZbyVejDDr6loT8OU4ia07jJltbZ52NkQAJkAAJkAAJXA0BSr4ZNUq+GS9ba0Pyb7opSdauzftIvn/4L5IYWlPl2hdIHqNTvd4q/qw4C5S2dcxsjARIgASulsAXX3wmEyeOlS1bfrzaJvi5/yfw008/Ss+e3eTDDz+VChWuyVEuixbNl6+//lI++ugzfZ3du3+RsWNHyLlz5+SDD1ZIr17dpVmzFvLccy/Y3o+FC+fKtm1bZM6cBRIQEGB7+642uHz5h/LZZ5/I3LmLpGDBgq5+jPXSEaDkm90SlHwzXrbWhuTffHOSrFmTh5LvSJSCf09R/0yUmIovSdT1Y2wdIxsjARLwHgIvvfSCFjR//8sb7/39A+SaayrKE088Kfff/0CODjYvJH/BgrflnXfmSWDglW/yLlmyVIq45ujAM2l8zZqvpHbtG6V8+QrGl89NyU/fucGD+ynB/0dmz56f5l4yHkQ2H9ixY7sMGzZQ3n33Aylbtlya2oMG9ZXNm7+VkSNfk/vuuz/N9zDnX375uXz66VdXXGHnzh3y6qs9ZNmylSltJiQkyPLlH6n9dWvk6NEj+jOlS5eRu+9uKk8//T8JDg7WXxsw4FUpUCBIRo8eb/dQ5cCB39RCZob88cfv+l6tW/dm1c/+UqRIkQyvFR4eLgsXvi1bt26Wf/89L5UqVZYXX+wpt956ed/dxx8vlZUrP5UzZ05LaGiY3HLLrdKt28tSokQJ3ebx48fkrbdmyq+//iLx8XFy7bVV5fnnu0u9evX19+Pj42XevDmyceM6uXTpohQtWlzuuuseVedFxeH/A4qGJCj5ZsAo+Wa8bK0Nya9XL0lWr84byfeNOayOxnxeAi7t0ONKDKkuFxp+J+KX/AuJhQRIgARSE4DklypVWoYPvxwMiIuLVX/E18uECWPU18fKvfc2yzFoeSX5mQlfjg3UhYad6mlrq1bNZMSI19KImQsf1VXyUvJffrmrYIGU+j5ytd+u1nM4HNKx45PSuHETJa8vp/nY6dOnpV271upebS6nT5/Si43UxUTyIbK9e7+k2+nTZ4DUr99QHI4k2bNnt8yYMVV81B96RO8h94cP/y0dOrTT18PizK4SHn5JnnrqUWnZspX873+dJSYmWl57baR6IO+U6dPnZHgZLDhOnjwhY8ZMlHLlyquXcm6USZPGyoIFS7Twr1q1Ul5/faL6uX5dS/s///wjo0YNVk9DAtW43hL83D/99OPqXT911Pj7S1BQkPrs22phtEI/nSlRoqR+6rZ3727Vl0nqaVFFOXjwN+nbt6c89FCbK+bEVRaUfFdJJdej5JvxsrU2JP+WW5LUY8xclnz1g1/g9EcS+lsf8U1KPr4zpkJnibx+rBL8EFvHyMZIgASyJpCUpLPjcr3g94+fn9llM5J8qwX88cYf+rFjJ+kv7d27R95+e5b89dchSVKDvO666io9pLf+Nwraql69hoo6FtBCAWlo0KCxDBkyUreDsmLFxyqd5H25ePFfLRq1a9fVbVrpOogOvvnmdPnxxx9UnYtKJCrIM890kubNW+jPQ3SioqKkZs1agqhkbGysPPhgK3nyyWdl3LhRsn//XilevKT07z84JfqYnkhWwpe67qZNG1XEeKEcO3ZUjSlAj6Vnzz4qellUTp06KY8//rASnIGyePEi3Z+xYydqyZo16w3Zt2+37me1atdr+UEUFuXgwQPq+9N0dBYMq1atJt2799QMH3igqSCCjKcqN998i0yb9uYVk5mYmKjF66uvvpDo6CgVaa0mPXq8ok51u+kKyT9//pySt9fll192qbrROkrdsePz0rTpfbpdsJ42bbLs2rVTSyQWe+DYqlUb/X1EsRcvfkeN6WRKn3r3HqCjvqkZPvlkWx0Bhvyi70uXrtD3QvPmLeWFF7rrtjZsWKtEcYmOigcE+Mvtt9+p6rwqhQoVypRl+sF///02LZSfffa1Fs7UZc4cRJ9/lsGDR2g5XrToA8X+upQqJpKP+cSTHoyjTJkyaa6DdCREujt0eE4qVqykv5f8cxKs5z+jgqcE6FtGBU/KBgwYesW3Vqz4SEXl58rnn69JeTKCe6dz52fkvfc+1POeusTExKinbnfJ0KGjU35W8P2hQzFfJVX6VF+ZMmW8vv/mzXs35aNIOXr77dnqsJDv9L2LNKyuXXuon6HkyD6eDuC+HDduitx5593qRZ/rdSqY9TOPOniCgoXR1KkzMhxjdl+k5GdHKO33KflmvGytnReS75NwUcn9qxJ0ZoUeiyOguETUmi3xJVvaOjY2RgIkkD2BGTMCVbQsUEmVMu5cLgULOlXkMV5efjne5StnJfmvvPKihISEqj/wk/Uf8UceaanyrFtqqYRsIqq3b98eneaAgrYOH/5LunR5UYlBK70Y6Nq1k+rPq/LYY+216PTo8bxOp7j77ntVZPRX9d9DBDJqST7agPwimg2ZRsR92rRJSvznaVGG5G/fvkWJXAcl2U9qEcXXEEXt33+ISnMprxYV/XW6wsKF72fIwRXJ//nnXTq/HQsURIeR3jBs2AAlpUVUJHV2ipjWqXOj6us4lcpRWgv6M888rvv58su9VaQ3UIvtkiWLNKOiRYtpAcXYO3V6XkWHHer7i3X6BL5/9uwZvXCA3KdOsUg9iLffflOnSkye/IaK1lbQn3/vvXfUgucz+fvvv9Lk5Pfv/6qStEsqmjtNz+MnnyzTC4z331+uRW3y5HFa7EaPnqC+H6IXVgMH9lECv1ilcoSqOWulo76NGt2m2xk/frSWWcxfeobp7yN81pL8H374XrXbWwsoUjswztGjh+rFGMTYWjClZokFQ/ryxhtT5Oeff1QLrw/TfCsuLk7atn1Ap6Y89FBrfY8hco37wSomkv+//7VXi9WaesHgSvn44w90msyXX663LVVp9OhhcuHCv2kWerhf7r33dv10AZHz1CUzyZ8yZYIcOvS7WpgsFKQ6DR7cVzPH0wn83I0aNVSn5mU2VqQMdenyrMyf/57UqHFDmmvidwBSndBXLCKuNrWPku/KXXa5DiXfjJettfF7qX79JBVlyb1IfuGdLSTw4jY9jvji90l4rTncXGvrrLIxEnCNAKL3tWqFqNxkX9c+kAO1SpRwKPGOUlFV1xrPSPIRIV679mu1WJmkxG6qirreoRuLjIzUucFWLjs2P/bv30tFG1fryB/aQmQdQmCVjh2fUgJeR0U7B6lI30T1NOBXFSVdmvJ9SMhnny3Xko9FQYcO7bWQpE596NQJbdTVcgOhh1ggtxoiiOvdd18TLc2dO3fV7SbL7BtKhrdmCMEVyR86VL0kUEW/X399VkobyPdG1PKLL9ap68ZoIYfcYAGD8t133+qFwNdfb1QbMS8/QUW9tm2fUFHyZ1SUvLk8+ugTKqLeRX8G6RcoGIslu5lJPuo++OB9eqyPP558TYgWnjgg8o/UkdQbb/EkBQsmqy8QwWbN7kjJWR8+fJB+GoA5tjawQiR9fX11W1iwvPnmfLVouUlfy/oe/ttE8gcN6qPvmVGjLuetI7UIi8iVK9dmyDKjicP9hbz4YcNGp/k2FoJ4YoH7ELny2NeAqPWnn36tFysZ9Td1A+lz8ps2vV2JbTe1IHs2w/sn/RexIES6kp0bnpEuFBYWloYZrov7B3tlnn220xV969fvFZ1ihHQdLOIwLqTcgQn6hoKftenTp+oFKcottzRQi/XXU560pW4UUfwePbpI5crXqjYnpLkeFvjgjrx+PKl6+OFHXGKVUSVKvhk6Sr4ZL1tr4w/rrbcmqUfVuSf5ARe2SuGfHpXI60ZK7DXqj5yrf91tHTkbIwESAIGZMwOVzHpWJD/9xltE7WvWvEGnJNxxx90pE7thwzodOUbKRWJigpY+SKa1YREShtQARHqt8uKLnbVwICKOyDLSOfBkwCqIgiLPGZIPSUakcf36LWmkA9HGyMgIFXmeriUf6TNYCFilSZP6KlI8TEdxUZDKgtSdzE7syWrjbaNGt+v+YXHSoEFDlUrzSsp1cF2kpiDdoUiRolryEVFHjjgKIvZvvTXrig29EO02bR7VmyYhoMiLLly4iBasxo1vlyZN7tRinZ3kI33poYfuU1I2LWXhlfqnLn1O/u+/H9CpGAcO7NMLFiwkMLeI2uJJy6FDf6hFSx+dVoQNmPXrN1CLgPtTFgWQwU8++VinZtSrd4uKwt+rFrG19SVNJP/ppx/T6Tx+6XLJwOXtt9/RLNKzzOi3CRYdDRs21k9JUpfnnntap0v16zdYfxmR/UceeSDNYsgkko9oOdKann22o0u/1P7660+dl59+cerShzOphBSfQoUKK8kfl6ZGsuQ/lWHfLly4oDfq7tixTUl8or5HypQpq1NslixZpvfZTJw4Rv981qt3q94oPWlScvt4OpW64GccT1+wARyRf+w/SF+wUMA9N27cSLVwbad/X1xNoeSbUaPkm/GytTb8ukGDRLXCjbG13dSN+UX9IU6/UHEElU35sk/8eXEGFs+xa7JhEiAB1wl4ck4+osWISiL6B6m2yi+//KS/jqhd69ZtdfoHHv/36fNyGslPv4k3teRDXJAWYuX4o23k6CMdJyvJR0rPxYsX5I03ZmvJhzDi+ESrQPItccXXXJH87DbeZiT5EB+k22CTJTaZpk+tWbbsQ/UUY44S+eS3imdWED1HCgvSYyBeOMEEmymzS9ex8qMnTJiqFgZ3XdF8aslHqtPjj7dWQacGOvcd/YXgN216WxpWEG2kUSHq+803G3Ru/ttvL0rJRYcIbt++Vc/11q3fSfv2z+icbRPJh4TfeOPN+qlHRiW7xY31mWTJv02nf1kFC9Tu3bvok11SH6eJpxYQVKQmYXGDvQXvv/+uOhTj2yu6AAnGiT0rV66RYsWKq2M/n9EpLOkFO7P5RJrUs88+kankX01O/pgxw3U6De55q2CusADBYubBBx926RcSfraOHTumFpYz1f6IjnqfQuo0JuxhwdfBCSlOKDt3fq94DNLXwH6R9Iuz9Bd+772FOi0NT7CuplDyzahR8s142Vobkt+wYaJ6nJsDkq/++AadWCShBwdJQpGGcqmeevzmk3dpAbaCY2MkQAJ5QiCjdJ0TJ46rEz3a6xxnpJagYDPikiXvpBFYbAzEP6kj+VlJPnK6//zzUJp0nokTX1O/Lz/9/3Sd5IgoTi654YbkiDEK+gJJtNJ1ckPysWERKTlTplzeTIi0GHwdMog0ofSSby160qdtgKd1JCairRBwq+B77dq1URyXqPSMQtnm5COS367dMymRXCuvH9IPKbTSdRD179atkz5ZBZuhUay0EmtBFBERoRdz1vGp1p6Ctm0f1/sd8PQE0WSrYGE0c+br+h4wkfwRIwbrBUzqhRkWOnFx8Wk2MWe1FwF9yChdZ8SIQXpjcPojLLGHAvWtNrds+U5HphHRrly5SpqftTfemKyfIq1Y8aVeEHz44RLV15l6826VKtemqQuuSGHp02dgysZui+sHH3yiFwd2FKTVzJ07R99r1vzgVJtu3Z5TG4KXq02/la+4DO4/LL6RHoeCe6N9+0f0ohzHfnbu/Kx6KnO9fuplFeyLwULcknwsFHFKzyuv9E15MmbVxSIR6XQ4LjP1iVtYQH300VIV3Fx3VUOn5Jtho+Sb8bK1dk5Jvk/8OQnb/7IU+GeV7m9SYBm52GCdOIKTd/ezkAAJkMDVEMhs4y1O3YDoQBIhRYg4jxw5WKdXVKlSVUnRN/oEHZzMMmvWXPUSwHpaqrKSfCunHY//IaWQI7xAKfXGW0QVkb89cuQ4nZP8+ecr9Gk7c+e+q2U1tyL5iF5jv8GIEWP1RllEm5GnX778NTqdJ6PoMyKtOOIR0WCkJ+HfVn74/PmLtYC1b99GRUnH6A2oKDh1BvnN2GMAKUM6xksv9VJR1NZ6/OkL5BrHjmIzLU5YwdMD6ySYo0cPp0g+Nsg++uiDepM09gMgYrt06XsqvWKX3huAPQFPPvmoThXq1KmL7hvSe155pbvOeYfgz549Q2+8BXdExnGqzP79+/QizUTycSoTFhw4ienhh9vqpwXImT979qxOfXI1kg8Z//nnn/QZ+Sh4yoANvjidpmXLh65ghSdPyBkfP36KZov5xIZsRMKRgoSFBl7oZY0TqVMoSEFDTjwi9L169dOMUCDE2PyLc+qxV8Pam4I5WLDgLVs33mL/y9NPP6o3umN+8P94olW4cGE9JyhIDcNiBvcoCqL2EH0sbIoVK6Zz7/H0ZfHiZfoUIyzUEXUfN26S2sNRX7PAwhtPyfBzjoUrnpa0a/eU+ufpDH+dYJMt7gH8DGMB9McfB/Vmbfw846SpqymUfDNqlHwzXrbWhuQ3apSoVt/2RfIDzq2TsH3dxS/+jO5rXKlWElFzBtNzbJ05NkYC+ZNAZpJvpe1AhJC+gZxxiBlSG3x9/fRLgSCQ/fr10nII8cDxe1lJPghDNJGig+MbkRfcsGEjfYyjlT8P4YecIA0DkXSIxAsv9NAbS1FyS/JxreQ3ui4VRNuRg3/nnXfpk4MQ/c5MTFEXJ9ggIoo9tUiBwFtfLYHctOkbxWme3leARCpKLwAAHshJREFUCC3G16nTCyrNs5EeHyQKjLGwSr1B2bo7Iat4eoITeSDLWR2h+emny5UQL1A595Eppw+BPfLskT99111NFesp8ttv+7QEY+5at35Ub+zE/EMIEb0/f/68ytMPljp1btJzjj0WJpKPvmMxg/YwbuslTD169NLHcboq+ThCE5tLsaEWn5s//y3138vUeL7K8EVMWJiOGjVEnTz0ud6wi4UKjl1dt26NlmOMqVq16opFp5QjTi3OeKqxbNkHqu5qnR6G+x9PY3CCDPLPU788Dn1CznpmR2he7W8WbESfOXOafikW7jmcuISFEhZkGf0sQNKnTp2gfpa+03tm6tSpqyPyVhoO5hj3MxbnZ86c0vOAn6tu3V7Sc48FKdKEMnpJHO4XLAzB8J135qq6X0tERLg+IQlRfXzPOibXdLyUfDNilHwzXrbWhuQ3bpyook82SH5SrIT8MVwKHntL99HpW1Aiq0+U2PIduLnW1lljYyRAAiRAAu5OwHoZFs7Yx74AdyhHjhzWKWY44tXOl2G5w9hyqw+UfDPSlHwzXrbWhuTfdluiOqbqv0s+zr4PPp68uSyh0M0SUXu+JIVcfrmHrR1nYyRAAiRAAiTg5gSQjjJ8+ED1hOKjK15UlRddx+lEeGNs+j0BedEXT70mJd9s5ij5ZrxsrQ3Jv/32RPUI8b9Lvm/sSSn6/e3qzbWdJPraQSK+Abb2lY2RAAmQAAmQgKcRQLoSXog2e/aCNCfq5PY48FbaTz9dofaLvJPmvQi53Q9Pvx4l32wGKflmvGytDclv0iRR5QiaS75v3GnxiT8rSWE3pvTJJ+GSOAMun25ga2fZGAmQAAmQAAmQAAnkIQFKvhl8Sr4ZL1trQ/LvuCNRbSwzk/zAs6vU6Tk99Pn3FxptpdjbOitsjARIgARIgARIwB0JUPLNZoWSb8bL1trGkp8Upc69HyzBJ97R/XD4F5JLNy2TxKKNbe0XGyMBEiABEiABEiABdyNAyTebEUq+GS9ba0Py77wzUZYvzz6S73/pJwnb20X8ow/pPiQUaSzhtefy7HtbZ4SNkQAJkAAJkAAJuCsBSr7ZzFDyzXjZWtslyXcmSfDhNyTkz9fEx5koTh9/ia46WKIrq1d1+/jZ2h82RgIkQAIkQAIkQALuSoCSbzYzlHwzXrbWhuTfdVeieolG5pH8oGPzJOxAH33dxIJV9dGYiYWTX/TCQgIkQAIkQAIkQAL5hQAl32ymKflmvGytDcm/++5E9Va9LNJ1HHFS5Id7JVGdfR95/XgR/+S317GQAAmQAAmQAAmQQH4iQMk3m21KvhkvW2tD8u+5J1G9Ovqy5OMYTP/wXZJQvOnla6kNt+IXYuu12RgJkAAJkAAJkAAJeBIBSr7ZbFHyzXjZWhuS37Rponz4YbLk+1/YLoX2Pi++6vz7Cw2/k6TQGrZej42RAAmQAAmQAAmQgKcSoOSbzRwlPwteMTExMmHCBNm8ebNcunRJqlWrJj179lRvqb09w09t3bpVZsyYIYcOHZLChQurM/DvkIEDB0pwcHCG9SH5996bKB+8Hy4F/5ogBf+eKj7iUJtrAyWi1psSV7ad2WyyNgmQAAmQAAmQAAl4KQFKvtnEUvKz4DVo0CDZu3evTJ8+XcqWLauOulwukyZNki+++EIqV66c5pOHDx+WVq1aSZ8+faRdu3Zy5swZvSCoXbu2jBs3LlPJ7/DIAZn/3DMSoFJ0UBJDakp4nfnqTbZ1zGaStUmABEiABEiABEjAiwlQ8s0ml5KfCS9E7hGxnzZtmjRr1iylFkS+SZMmMmDAgDSfnDhxoiCSv3LlypSvr127Vnr37q2/jsh++tLprndk9nMvS3CAyrlXJfqarhJ13WiVf59x5N9salmbBEiABEiABEiABLyHACXfbC4p+Znw2rZtm3Tq1Em+++47KV26dEqtIUOGyN9//y1Lly5N88knn3xSp/OMGTMm5eunT59WR2TeJYsWLZLGjTN4K+1Sla+jiiOwlErPmS3xJZqbzR5rkwAJkAAJkAAJkEA+IUDJN5toSn4mvL788kuderN7924pUKBASq3JkyfL+vXrZc2aNWk+ef/99+uIf9++fVO+HhsbK3Xr1pWpU6fKQw89ZDYzrE0CJEACJEACJEACJEACV0mAkp8JOOTdQ9j37NkjgYGBaSR/w4YNsnr16iskv3nz5nphYBVL8l9//XV58MEHr3KK+DESIAESIAESIAESIAESMCNAyc+E1/bt26Vjx45XpOsMHjxYjh49KkuWLEnzyaefflqqVKkiY8eOTfn6qVOn1Muu7pZ3331XGjVqZDYzrE0CJEACJEACJEACJEACV0mAkp8JuIiICLnttttkypQpglQcq7Ro0UIQsceG2tQF9TZt2qRP3rEKUn5wQg8WDKGhfFPtVd6j/BgJkAAJkAAJkAAJkIAhAUp+FsBGjhwpP/74o8ycOVPKlCkjixcvljlz5siqVavk3Llz0r9/f1m4cKGUK1dOjh8/rvPue/XqJe3bt5cTJ05Ijx499Ek8Q4cONZwWVicBEiABEiABEiABEiCBqydAyc+CXXx8vD4Xf+PGjRIeHi41atTQEfx69erJjh07pEOHDoJjMitVqqRb2blzpz5y8+DBg1KkSBG9ERc5+gEBAVc/Q/wkCZAACZAACZAACZAACRgSoOQbAmN1EiABEiABEiABEiABEnB3ApT8HJqhmJgYmTBhgmzevFnwYi2coY834OIFWxkVvDBrxowZcujQIf3irDvuuEMGDhwowcF8MVYOTdFVNWs6r1999ZXMnz9fv1shJCREz2u/fv2kWLFiV3V9fihnCJjOa+pedO7cWbZs2aKf4LG4FwHTecWbysePH69/bzudTrnllltk+PDhcs0117jXwPJ5b0znFe+q+fjjjwWHYYSFhen31uApe6lSpfI5Sfcb/rFjxwQHnPzwww9pMiXoTVc3V5T8q+OW7aew4Xbv3r0yffp0KVu2rCxfvlyn/mBjbuXKldN8/vDhw4I36eKXTrt27QR/aLAgqF27towbNy7ba7FC7hEwmVdsxMa+DEhDy5Yt9R+Y7t276/SuWbNm5V6neaVsCZjMa+rGli1bJnjbNTbqU/KzxZzrFUzmNSEhQdq2bSu1atXS+61Q8F4UX19fee2113K977xg5gRM5nXFihUyevRovZ+uYcOG+u8r0m5xNPZ7771HzG5EYN26dTJixAi588475dNPP81S8ulNrk0cJd81Tka1ELlHxB75+cjLtwpEHhtxBwwYkKY9SAIi+StXrkz5OnL98YsIX0dknyXvCZjOKxZ0R44ckZdeeiml84goQfCxoZvFPQiYzqvVayzaWrduLV27dtULeEq+e8yn1QvTecVTt1GjRulT0oKCgtxrMOxNCgHTeYU07t+/X7AgtwoO0cD7a37++WeSdSMCmCM8Pfvnn3+u2POYvpv0JtcmjpLvGiejWtu2bZNOnTpdccb+kCFDdNrG0qVL07T35JNP6nSeMWPGpHz99OnTctdddwmkEI8WWfKegOm8ZtRjzDE2beN4VRb3IHC184o0nZo1a+oULGzCp+S7x3xavTCdV6Tl4B0oOFgBspGYmKiPUcbvbabXuc/cms4rUq8QaEE6LP6WQiDxoks8UcdTVhb3I5DRwSbpe0lvcm3eKPmucTKqBYFD6s3u3bulQIECKZ/Fo9/169fLmjVr0rSHc/gR8ccvHqtYb8udOnWqPpqTJe8JmM5r+h5b6Ts4kvWee+7J+wGxB5rA1cwr8nuxAP/ss890NJCS7343k+m8Pv/88zoPGAEa/DcCLTgSGXnbCxYscL8B5tMemc4rMH3wwQc65QopWSiQfaTvcM+be95Erkg+vcm1uaPku8bJqBbSNCDse/bs0Xl/VoHkb9iwQVavXn2F5OMFW1gYpJd8PFJ88MEHja7PyjlDwHReU/cCkUG8DXnYsGHy2GOP5UwH2epVETCd15MnT0qbNm1k3rx5Urdu3ZTjdBnJvyr8OfYh03nt0qWL/P777/oJrFUQlMG+GmysLlmyZI71lQ27TsB0Xr/++mv9rhr8LcWb55GTj6c2KFios7gfAVcln96U/dxR8rNnZFwDb7jt2LHjFek62DGOx8FLlixJ0+bTTz8tVapU0RJoFeT73n333fLuu+/qX0wseU/AdF7RY5zQgXlF9Al7NPD4n8W9CJjOq5WmYz15s/4gUfI9e17x+xlPX1On0kH6sZcKi/Qbb7zRvQaYT3tj+vP6xBNP6HfcYPOtVTDPjz/+uGAfRtWqVfMpSfcdtiuST29ybf4o+a5xMqqFkzYgc1OmTBE8UrJKixYtBCtPbKhNXVAPqRyIUFgFf2hwggB+oYWGhhpdn5VzhoDpvKIXiBh9//33+hjNihUr5kzH2Op/ImAyr3iTddOmTfVmeB8fH31d5G5HRkbqF+AhGoxUD5a8J2Ayr+gtUjqQo42ofaFChfQArEg+fg8zLz/v5xQ9MJ1XnJiEvTOpT0j66aefBDndlHz3mNP0vXBF8ulNrs0dJd81Tsa1Ro4cqU9QQf51mTJlBLv5kQO4atUqOXfunD6ibeHChVKuXDk5fvy4zrtH/mf79u0FIoFHxDiJB48ZWdyHgMm84jgwnKSExVv58uXdZxDsyRUEXJ3X0qVL6417qQty8vGzi4U6FuRclLvPDebqvOL3MM5ex94oHLOIE1lwiguOvMVTVmzaZHEfAibzOnfuXP23F6eaYW7x9xdPbf7991/55JNP9BGpLO5FICPJx9MXepP5PFHyzZm59In4+Hh9rN7GjRslPDxcPy5EBB8nN2R0A+/cuVOnc+CRPyKC+GODHP2AgACXrsdKuUPAZF6RsoW59vf3v6Jz2JdB8c+dOXPlKibzmlnUiek6rpDO3Tqm84r0HKTXQSjwuxfvt4BYcOGWu/OW3dVM5tXhcOjce5yXj/00eBlWgwYN9L45BOBY3IcAMh8wR0hzxSZp/AziiSmOKkbaHA44wPHieNcMCr0p+7mj5GfPiDVIgARIgARIgARIgARIwKMIUPI9arrYWRIgARIgARIgARIgARLIngAlP3tGrEECJEACJEACJEACJEACHkWAku9R08XOkgAJkAAJkAAJkAAJkED2BCj52TNiDRIgARIgARIgARIgARLwKAKUfI+aLnaWBEiABEiABEiABEiABLInQMnPnhFrkAAJkAAJkAAJkAAJkIBHEaDke9R0sbMkQAIkQAIkQAIkQAIkkD0BSn72jFiDBEiABEiABEiABEiABDyKACXfo6aLnSUBEkhNoHr16voNpY8//rjHg7nzzjv1OF5++WWPH4srA/jss89k2LBh8ssvv4ifn58rHzGuU6dOHRk1apS0bdvW+LMmH9i+fbu8+uqrsmzZMrnmmmtMPmpLXbwd9Omnn5bbb79dXnnlFVvaZCMkQAKeT4CS7/lzyBGQgNsRePbZZ+XHH38Uf39/3Te8nrxs2bLy4IMPSrdu3cTX19eWPuc3yf/tt99k/vz5smPHDgkPD5dChQoJRLZjx47SsGFDW5iikaioKPn444+lU6dOtrWZGw19/vnnUq9evVwV7bNnz8rDDz+sFxP333+/npsOHTroe97Hx+eKYX/11Ve6f7h38fNh/SxgoYOfkQceeECef/55CQoK0p9t2rSpnD59Os1CKDg4WKpVqyZdu3aVu+66S9c7ceKEtGrVSqZNm5bytdxgzmuQAAm4LwFKvvvODXtGAh5LAJJfunRpmTJlih5DYmKibNu2TUep+/btK/i+HSU/Sf769eulV69eOtqPhVKpUqXkzJkz8sEHH8i8efNk3Lhx0qZNGzuwysaNG2XkyJHy3Xff2dJebjTidDqlcePG8vrrr8ttt92WG5fU1wCn/fv360URiiX5a9eulUqVKmXaj/T3Ln5Gfv31V/1E4N5775URI0akSD7kHV+3SmRkpCxdulTeeOMNef/99+Xmm2/W35o6daps2LBBvvzyS9sW0rkGkhciARKwnQAl33akbJAESCC95FtEkDZx4403ajFC+eeff2T8+PHyww8/6OhxhQoVpHv37tKyZcsUiEjrePvtt+XkyZNSpkwZ6dKlS0p6TnpRmjhxoqxevVoLEKKiixcvlrfeekuio6MF6TCQv+HDh8vBgwd1+/j8gAEDdJpFSEiILF++XC5cuCCTJk0SpGD8+++/WtReeOEFHSVFGThwoBw5ckTLtVVSf82SPMgX2vn999+lZMmSMmjQIB2VRUFkdsiQIfLzzz9LkSJF9OIHEdjM0nXABp9FlNeSv9R32TvvvKMjvYggo+zcuVML36FDhwTye+utt+rrW9KJcYMVZH7Lli06avzUU0/JSy+9pMc1ZswYSUpKksDAQP3fWDxgHhYsWKAjxgUKFNCpIRhD0aJFU1hiofH111/rpzjFihXT0e2IiAgto5jrBg0a6H6FhobKJ598ovu0b98+HdHOqk+4ACQY7SASjnnBddGvnj17SkxMjG4baSuIoOO/Fy5cqNtMnc714Ycfaik+duyY7sN9990n/fv3l4IFC6bIeVbzlv4nG7LdqFEjmTBhgjz00EP621cr+VbbeFKDRRvaQcG8p5d8qy7uB0TycQ+jnDt3Tpo0aaLv+bvvvjt9d/n/JEAC+YwAJT+fTTiHSwK5QSC95MfGxuqoMGR47ty5Ur9+fd0NRKQvXryopSQsLEwLGOQTIgchhYBC+mfNmqUFHfKKVIY333xTy01qiYMcLVq0SLeBz37//ffyv//9T0e4IWCIhL/22mty/vz5NJJftWpVLdjXX3+9Tq9A3yGUkNHixYtr8R89erRuF/12VfIhW5BcS/DxJAMLB1wD/YqLi9PjgEhDRDFmLCYyyslHVBhfh5SXL18+yynEAgTyh9xsjAWSjT5DznENLAbArXLlyprHTTfdpMUefVi5cqX+3syZM/XCx4rk79mzRx577DHNCQswPEHo3LmzThWC4KLgc0ghmTx5slx77bW6v0gvuuOOO3Tu/alTp+SRRx7RT3KwGMlI8rPqE6Qd9wn6ijnDAgkcsWDE4vH48eM6Ao4FjxXJT31/4HqYx+nTp+vv//HHH9KjRw/93+BgyXlW85Ye/Lp16/Q4MbdY1Ngh+fj5wBhwr2Qn+c2aNdOLACyWrIKFD1KWsJhlIQESyN8EKPn5e/45ehLIEQLpc/KtCCuEHXnEVh4y5B9CjagqCiLuSD1AygXy9yFhkGJIvlUgnojSX3fddSmSj+gtngi89957+msokL9du3bJF198kfJZRH3XrFmTRvKRdw4JRkHUHVFTRHytFAh8HeKE/0cU3VXJx9MHK5qKBQbGsnXrVj12pJVA8BFJRsHCA7KJSHpGkg/xmzNnjhbb7AoWSd98841+omGVAwcOSOvWrbW440kKGD333HMpEWDk9yPaD4nHAiG95ONpAJ5wWCKLdtNfB21ikdKnTx99WSyKINUYu7UZFQuFWrVq6cVPRpKfVZ9wnyByjicfVnn00Ud1e7hOdpKPhUDt2rV1Xau8++67+ukAuFqSn9m8lShR4gr0M2bM0OP49ttvU753tZF8/IwgXQcpWbgHreh8RpF8LIzRd0T8Mac1a9ZMuT6E//Dhw2meNGV3z/D7JEAC3kmAku+d88pRkUCeEsgoJx+pIxBvSBoisijIZYbQI1KMlBQIfXx8vBZ2SBki8IgEW8KTflAQS2x2RB4y5Dt1rj8WE5D/1AsESBH2CaRO10HEEyeToFgyjhNfsLnRKhBXRMQh265KPiS7SpUquglEerGYQD8haJBTbBKtUaNGyjUg2YhwZyT56DfGgX5ltJkzNRcspDBuRKytAoGE4EJoEYkHN8huu3btdBUINGTZ4p5e8h0Oh8yePVsvmJBqhP9HOg/Sp/B0ASV9m5bEI5pvLeowP3gSgeh/RpKfVZ/ADQsLPN3Bf6NgXFiAob3sJB9PYZDXbs01Po9FFxYWiJojsg/+mc0bUsnSF9zPEPNPP/005VtZbby10oIsXuk33uIa2MSLewVziJJ+4y0WXBg3FopYFFpPxawOWGlYWMyykAAJ5G8ClPz8Pf8cPQnkCIHMcvIhqRDLVatWaUFEegUi2BBnbNSF4CMFxJJNCA9kJnU6QuoOQyyxaEB+ONJzkDeODakoiCojzx7Raasgpxx58qklP3XOdlaSjzxwpFFkJPn9+vXTkolUkowiuaklH6exPPnkk1qYkSJkFeR2Q0AzknyI9Isvvqjz3ZEKk1XJSPItrkilAdOMNn1mJfkQfCw0wBLzhRQjpDNhHlNLfmqWlsRbrNHn7CQ/9efTLzxwghByzrEoRFoQFg64l7CQckXysYhClDy15GPBgLQjPB1C9BuSn3rDbOp5y0zyd+/erRcsVrnaSH5mc5o+ko+nX3gqg58La29L6s/i/sZikpKfI7/a2CgJeBQBSr5HTRc7SwKeQSAzyf/pp5+04CLFANFgSBoECYKJgg24+Kwl+UivQYQfcm4V5I0jbQS505BVpH5gwyoEDeKHvHzknWNTKAQTOfVW6d27txbTzCQf0Vw8PbDSWqzPIX0CEVOk6+AfPHlILXYYB67tiuSjb0jjSZ0Wghx3bAzOLF0HYocFERYCkOv0Bak86BNkHJHcTZs26fx7q2BzK56MpE7XyUqo00fyIcKILFtPYCxhR55/bkk+Fn+YP+tYT6TuYF8G8tJdkXw8PUEbqcUYizaMFXs9sFnYVPLtTNdxVfJRD2lo+DlBytc999yT5qNYEP/999865YyFBEggfxOg5Ofv+efoSSBHCGQk+TjRZOjQoTrtBbKJPHTILk43QXQVEVHrDHikUEB4kUaB03QQgYbMYZGACD3STiA3qSPSEGVEqbGIQMQW0Uxr0y5kEDIKGcQG0MwkHzCeeOIJHalGxLhw4cJa3BEdRZ+xGEEuNPrz0Ucf6Ug8nh6gLjaNuiL5iAgjxQT7ECCJkH4rdx1jzexlWMj7BhOkJ2F8aAdPBZYsWaL7hD4gxx/59xBapBg988wzOpcejMF9xYoVOt0nu0g+ovYQSDxtwIIKKU6IemPMKFhIIWKNRRG+jjSU9G3aHcnHHg1suEVfkDKEOcAmY5yyg/7gSYv1VAjjxzsEUvcJJy5hHrEgwuk74IT7o0WLFvpJUXZPYDKK5CPqjw3OiPhbpwzldCTf+oHFvYwFL+YIG8Stgs3N2Eyd0SlMOfLDzkZJgATclgAl322nhh0jAc8lkH7jLcQSEgQxR3Te2sAJ8YJ0ISqLja3WKTYQV5y8g82qSFGB1EPOy5Urp9MrrDfcphdLbDjFZyCpED5EaRHJxxGLzZs31znwOEkFgoeS0Tn7OOoRdRAtxeeQGoIIMsQQBZuDkbIDuUV0G31BfjpSkVyVfCx48KQB0XekG4EJ8v2x6TWrN95iDwOeACDqjM2y4HjLLbfoE4dSb75EJB+S/ueff+rFBFggpcjinp3kHz16VC+ucGwp8tjxdAMLBeSfo7+IpmOBhtNtwAgLKvQjJ9N1MGaIK9KicHoS5gALFwh63bp1dSoVTu5BTj3mDIuv1ONELjueCGHxgXsJaV1Ie8GiEbnxVyP51hGaeHqCRQhKbkk+nu5gsQgWuCdQsHBG6hqP0PTc353sOQnYSYCSbydNtkUCJOBWBHBMJc50twqkH5KHxQALCdhBAOk/WDS6Q3oM9kzgWE++DMuOmWUbJOD5BCj5nj+HHAEJkEAGBBAlR5QdaSxIyfjrr790dBopLUgbYiEBOwggZQp7NvAUAylleVXwdAJPXHC/Iz2NhQRIgAQo+bwHSIAEvJYActDxEiVsEEWaCQQf6Sc4dYeFBOwigL0juK+wb8N6J4BdbbvSDk4iwv4LnLiDPQIsJEACJAAClHzeByRAAiRAAiRAAiRAAiTgZQQo+V42oRwOCZAACZAACZAACZAACVDyeQ+QAAmQAAmQAAmQAAmQgJcRoOR72YRyOCRAAiRAAiRAAiRAAiRAyec9QAIkQAIkQAIkQAIkQAJeRoCS72UTyuGQAAmQAAmQAAmQAAmQACWf9wAJkAAJkAAJkAAJkAAJeBkBSr6XTSiHQwIkQAIkQAIkQAIkQAKUfN4DJEACJEACJEACJEACJOBlBCj5XjahHA4JkAAJkAAJkAAJkAAJUPJ5D5AACZAACZAACZAACZCAlxGg5HvZhHI4JEACJEACJEACJEACJEDJ5z1AAiRAAiRAAiRAAiRAAl5GgJLvZRPK4ZAACZAACZAACZAACZAAJZ/3AAmQAAmQAAmQAAmQAAl4GQFKvpdNKIdDAiRAAiRAAiRAAiRAApR83gMkQAIkQAIkQAIkQAIk4GUEKPleNqEcDgmQAAmQAAmQAAmQAAlQ8nkPkAAJkAAJkAAJkAAJkICXEaDke9mEcjgkQAIkQAIkQAIkQAIkQMnnPUACJEACJEACJEACJEACXkaAku9lE8rhkAAJkAAJkAAJkAAJkAAln/cACZAACZAACZAACZAACXgZAR8vGw+HQwIkQAIkQAIkQAIkQAL5nsD/AaCFrqoiZUIjAAAAAElFTkSuQmCC\" width=\"697.5833333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(fpr[2], tpr[2], color='blue', \n",
    "         lw=2, label='Random Forest classifier (AUC) = %0.4f' % roc_auc[2])\n",
    "plt.plot([0, 1], [0, 1], color='orange', 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('$W$ selector')\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Confusion Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of the HLF classifier: 0.9186\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": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/luca/ipykernel_30934/950292951.py:9: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n",
      "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
      "  cm = cm / cm.astype(np.float).sum(axis=1)\n"
     ]
    },
    {
     "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_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = 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(\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",
       "    );\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('style', 'box-sizing: content-box;');\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; position: absolute; left: 0; top: 0; 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",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\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",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.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",
       "    this.rubberband_canvas.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",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.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",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // 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 icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\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=\"697.5833333333334\">"
      ],
      "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(np.float64).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": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "spark.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}