Workshop 4 - Anomaly Detection.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Anomaly Detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from math import ceil\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.preprocessing import  normalize\n",
    "from sklearn.exceptions import NotFittedError"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Loading\n",
    "\n",
    "For this workshop we'll use the retail dataset, which has spikes during Black Friday and holidays that we could consider anomalous, or at least worth detecting. We'll sum the dataset down into all stores for the purpose of this workshop. Feel free to select a single store or group of stores to experiment with different results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\n",
    "    \"datasets/retail/sales.csv.gz\", \n",
    "    names=['store', 'dept', 'date', 'sales', 'holiday'], \n",
    "    index_col='date', \n",
    "    parse_dates=True, \n",
    "    header=0,\n",
    "    usecols=['date', 'dept', 'store', 'sales'],\n",
    ")\n",
    "\n",
    "sales = df.groupby(['date'])['sales'].sum()\n",
    "sales.index = pd.to_datetime(sales.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
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       "            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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"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\", \"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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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.one(\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",
       "\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",
       "    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": {
      "text/html": [
       "<img src=\"data:,\" width=\"0\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_sales(s):\n",
    "    fig, ax = plt.subplots(figsize=(9,6))\n",
    "    sales.plot(ax=ax)\n",
    "    ax.set_ylabel(\"sales ($)\")\n",
    "    \n",
    "    fig.tight_layout()\n",
    "    return ax\n",
    "\n",
    "\n",
    "_ = plot_sales(sales)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PCA/FFT\n",
    "\n",
    "One of the simplest methods of anomaly detection is to use a discrete FFT to extract features from a fixed-length sliding window and then apply PCA to learn a threshold for the explained variance and robustness to error. Once the thresholds are learned, any window above the threshold is anomalous, and the amount above the threshold is the \"strength\" of the anomaly. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "class FrequencyThresholdAnomalies(object):\n",
    "    \n",
    "    def __init__(self, window=6, stride=1, n_components=None, pca_percentile=99.95):\n",
    "        # Length of the window to detect spikes in, we'll use a 6 week window\n",
    "        self.window = window\n",
    "        \n",
    "        # Amount to move the window over, we'll move one week at a time.\n",
    "        self.stride=stride\n",
    "        \n",
    "        # The threshold for PCA explained variance to accept\n",
    "        self.pca_percentile = pca_percentile\n",
    "        \n",
    "        # Compute the number of components as a majority of the window size\n",
    "        if n_components is None:\n",
    "            n_components = int(ceil(self.window+1.0)/2.0)\n",
    "        \n",
    "        self.n_components = n_components\n",
    "        self.pca = PCA(n_components=n_components)\n",
    "        \n",
    "    def fit(self, series):\n",
    "        # Extract the windowed FFT features\n",
    "        X = self.windowed_instances(series)\n",
    "        X = self.fft_features(X)\n",
    "        \n",
    "        # Fit the PCA model and transform X\n",
    "        X = self.pca.fit_transform(X)\n",
    "        \n",
    "        # Use the thresholds to learn the magnitudes for anomaly detection\n",
    "        self.thresholds_ = np.zeros((self.n_components))\n",
    "        for i in range(self.n_components):\n",
    "            self.thresholds_[i] = np.percentile(X[:,i], self.pca_percentile)\n",
    "        \n",
    "        return self\n",
    "    \n",
    "    def transform(self, series):\n",
    "        X = self.windowed_instances(series)\n",
    "        X = self.fft_features(X)\n",
    "        return self.pca.transform(X)\n",
    "\n",
    "    def predict(self, series, return_strengths=True):\n",
    "        X = self.transform(series)\n",
    "        anomalies = np.array([\n",
    "            self.is_anomaly(Xi) for Xi in X\n",
    "        ])\n",
    "        \n",
    "        # process the array into an array the same sies as the series\n",
    "        tmp = np.zeros_like(series)\n",
    "        tmp[0:(series.shape[0] - self.window):self.stride] = anomalies\n",
    "        anomalies = np.convolve(tmp, np.ones((self.window)))\n",
    "        \n",
    "        return anomalies \n",
    "\n",
    "    def windowed_instances(self, series):\n",
    "        X = [\n",
    "            series.values[i:i+self.window].reshape(-1)\n",
    "            for i in range(0, series.shape[0]-self.window, self.stride)\n",
    "        ]\n",
    "        return np.vstack(X)\n",
    "    \n",
    "    def fft_features(self, X):\n",
    "        Xp = np.abs(np.fft.fft(X))\n",
    "        Xp = Xp[:, 0:int(ceil((self.window+1.0)/2))]\n",
    "        return normalize(Xp)\n",
    "    \n",
    "    def is_anomaly(self, instance):\n",
    "        for val, thr in zip(instance, self.thresholds_):\n",
    "            if val > thr:\n",
    "                return True\n",
    "        return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.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",
       "    // 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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"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\", \"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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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.one(\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",
       "\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",
       "    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=\"899.9999804930258\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_anomalies(s, model):\n",
    "    fig, ax = plt.subplots(figsize=(9,6))\n",
    "    s.plot(ax=ax)\n",
    "    ax.set_ylabel(\"sales ($)\")\n",
    "    \n",
    "    model.fit(s)\n",
    "    y = model.predict(s)\n",
    "    \n",
    "    ax2 = ax.twinx()\n",
    "    pd.Series(y[:-1*model.window+1], index=s.index).plot(ax=ax2, c='C1')\n",
    "    ax2.set_ylabel(\"anomaly strength\")\n",
    "    \n",
    "    return ax\n",
    "\n",
    "\n",
    "model = FrequencyThresholdAnomalies()\n",
    "_ = plot_anomalies(sales, model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Autoencoder/Decoder Anomaly Detection\n",
    "\n",
    "In this section we'll use a Keras convolutional autoencoder/decoder model for anomaly detection. The idea with this model is that we'll train on \"normal data\" and then find anything outside of the normal data to be an anomaly. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_instances(series, window=16):\n",
    "    # Ensure that all data going into a deep neural network is standardized!\n",
    "    mu = series.mean()\n",
    "    std = series.std()\n",
    "    series = (series - mu) / std\n",
    "    \n",
    "    # Create the instances\n",
    "    instances = [\n",
    "        series[i:(i+window)] \n",
    "        for i in range(len(series)-window)\n",
    "    ]\n",
    "    return np.stack([instances], axis=-1)\n",
    "    \n",
    "    \n",
    "X = create_instances(sales)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(127, 16, 1)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Build the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_6\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv1d_12 (Conv1D)           (None, 8, 8)              64        \n",
      "_________________________________________________________________\n",
      "dropout_12 (Dropout)         (None, 8, 8)              0         \n",
      "_________________________________________________________________\n",
      "conv1d_13 (Conv1D)           (None, 4, 4)              228       \n",
      "_________________________________________________________________\n",
      "conv1d_transpose_18 (Conv1DT (None, 8, 4)              116       \n",
      "_________________________________________________________________\n",
      "dropout_13 (Dropout)         (None, 8, 4)              0         \n",
      "_________________________________________________________________\n",
      "conv1d_transpose_19 (Conv1DT (None, 16, 8)             232       \n",
      "_________________________________________________________________\n",
      "conv1d_transpose_20 (Conv1DT (None, 16, 1)             57        \n",
      "=================================================================\n",
      "Total params: 697\n",
      "Trainable params: 697\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "from tensorflow import keras\n",
    "from tensorflow.keras import layers\n",
    "\n",
    "model = keras.Sequential([\n",
    "    # Input layer\n",
    "    layers.Input(shape=(X.shape[1], X.shape[2])),\n",
    "    # An 8 layer convolutional autoencoder\n",
    "    layers.Conv1D(\n",
    "        filters=8, kernel_size=7, padding=\"same\", strides=2, activation=\"relu\"\n",
    "    ),\n",
    "    # Helps prevent overfitting\n",
    "    layers.Dropout(rate=0.2),\n",
    "    # Latent Space Representation\n",
    "    layers.Conv1D(\n",
    "        filters=4, kernel_size=7, padding=\"same\", strides=2, activation=\"relu\"\n",
    "    ),\n",
    "    # Flip latent space for decoding\n",
    "    layers.Conv1DTranspose(\n",
    "        filters=4, kernel_size=7, padding=\"same\", strides=2, activation=\"relu\"\n",
    "    ),\n",
    "    # Helps prevent overfitting\n",
    "    layers.Dropout(rate=0.2),\n",
    "    # An 8 layer convolutional autodecoder\n",
    "    layers.Conv1DTranspose(\n",
    "        filters=8, kernel_size=7, padding=\"same\", strides=2, activation=\"relu\"\n",
    "    ),\n",
    "    # Output layer for anomaly detection\n",
    "    layers.Conv1DTranspose(\n",
    "        filters=1, kernel_size=7, padding=\"same\"\n",
    "    ),\n",
    "])\n",
    "\n",
    "model.compile(optimizer=keras.optimizers.Adam(learning_rate=0.001), loss=\"mse\")\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "4/4 [==============================] - 0s 12ms/step - loss: 1.0133 - val_loss: 0.1314\n",
      "Epoch 2/50\n",
      "4/4 [==============================] - 0s 7ms/step - loss: 0.9752 - val_loss: 0.1288\n",
      "Epoch 3/50\n",
      "4/4 [==============================] - 0s 8ms/step - loss: 0.9685 - val_loss: 0.1261\n",
      "Epoch 4/50\n",
      "4/4 [==============================] - 0s 7ms/step - loss: 0.9655 - val_loss: 0.1237\n",
      "Epoch 5/50\n",
      "4/4 [==============================] - 0s 7ms/step - loss: 0.9302 - val_loss: 0.1215\n",
      "Epoch 6/50\n",
      "4/4 [==============================] - 0s 7ms/step - loss: 0.8853 - val_loss: 0.1201\n",
      "Epoch 7/50\n",
      "4/4 [==============================] - 0s 6ms/step - loss: 0.8852 - val_loss: 0.1189\n",
      "Epoch 8/50\n",
      "4/4 [==============================] - 0s 6ms/step - loss: 0.8792 - val_loss: 0.1177\n",
      "Epoch 9/50\n",
      "4/4 [==============================] - 0s 6ms/step - loss: 0.8615 - val_loss: 0.1170\n",
      "Epoch 10/50\n",
      "4/4 [==============================] - 0s 6ms/step - loss: 0.8376 - val_loss: 0.1178\n",
      "Epoch 11/50\n",
      "4/4 [==============================] - 0s 6ms/step - loss: 0.8446 - val_loss: 0.1196\n",
      "Epoch 12/50\n",
      "4/4 [==============================] - 0s 7ms/step - loss: 0.8406 - val_loss: 0.1213\n",
      "Epoch 13/50\n",
      "4/4 [==============================] - 0s 7ms/step - loss: 0.8232 - val_loss: 0.1221\n",
      "Epoch 14/50\n",
      "4/4 [==============================] - 0s 6ms/step - loss: 0.8033 - val_loss: 0.1217\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(X, X, epochs=50, batch_size=32, validation_split=0.1, callbacks=[\n",
    "    keras.callbacks.EarlyStopping(monitor=\"val_loss\", patience=5, mode=\"min\")\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.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",
       "    // 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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"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\", \"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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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.one(\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",
       "\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",
       "    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=\"899.9999804930258\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_training_loss(history):\n",
    "    fig, ax = plt.subplots(figsize=(9,6))\n",
    "    ax.plot(history.history[\"loss\"], label=\"Training Loss\")\n",
    "    ax.plot(history.history[\"val_loss\"], label=\"Validation Loss\")\n",
    "    ax.legend()\n",
    "    fig.tight_layout()\n",
    "    \n",
    "    return ax\n",
    "\n",
    "\n",
    "_ = plot_training_loss(history)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Detecting Anomalies \n",
    "\n",
    "1. Find MAE loss on training samples\n",
    "2. Find maximum MAE loss value - use this as the threshold for anomaly detection\n",
    "3. If reconstruction loss is greater than threshold, label as anomaly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.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",
       "    // 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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"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\", \"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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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.one(\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",
       "\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",
       "    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>"
      ]
     },
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     "output_type": "display_data"
    },
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9X3N9SXDNVDXv+1cA1yt6+Uvf/nsPvXTtOvpeA1a9VOsa9hc+zTsrQ3e9fr1T5TVT+Ouoa3+yau6bv3wuPp3xNd/Uvmm1q4nwfWDyeoHyNW/LV3fs1xPwetLq+s/yQ9Xu+Sf0bpkN9f/+bFNBe+6v3rqvKnb+vfvr62xualZ/57+tfvVXw485SlPmb0Xv56w19Pr6vn7v//7cz0ENxW8a5/qB7HVvwleP9G8vhqivh+8vt+8hvx5Xro+VwHuRIAAAQJdCwjeXbdHcQQIECBAgAABAgQIECCw7AKC97J3UP0ECBAgQIAAAQIECBAg0LWA4N11exRHgAABAgQIECBAgAABAssuIHgvewfVT4AAAQIECBAgQIAAAQJdCwjeXbdHcQQIECBAgAABAgQIECCw7AKC97J3UP0ECBAgQIAAAQIECBAg0LWA4N11exRHgAABAgQIECBAgAABAssuIHgvewfVT4AAAQIECBAgQIAAAQJdCwje69pzwQUXlC996Utlhx12KNttt13XjVMcAQIECBAgQIAAAQIECCxe4Je//GU555xzyh577FGudKUrXaYLCt7r2E466aSy9957XyZIX0SAAAECBAgQIECAAAEC0xX49Kc/Xfbaa6/LtEHBex3b6aefXnbbbbdSQXfaaafLBOqLCBAgQIAAAQIECBAgQGA6AmefffbsgPab3/xm2XXXXS/TxgTvdWzf+ta3yg1veMNy1llnlZ133vkygfoiAgQIECBAgAABAgQIEJiOQCInCt6C93QeEXZCgAABAgQIECBAgACBsIDg3SFouCTLESBAgAABAgQIECBAgMCIAoJ3GD8BGi7JcgQIECBAgAABAgQIECAwokAiJ3qp+boGJkBHnAeXJkCAAAECBAgQIECAAIGwQCInCt6Cd3gsLUeAAAECBAgQIECAAIHpCAje4V4mQMMlWY4AAQIECBAgQIAAAQIERhRI5EQn3k68RxxhlyZAgAABAgQIECBAgEDfAoJ3uD8J0HBJliNAgAABAgQIECBAgACBEQUSOdGJtxPvEUfYpQkQIECAAAECBAgQINC3gOAd7k8CNFyS5QgQIECAAAECBAgQIEBgRIFETnTi7cR7xBF2aQIECBAgQIAAAQIECPQtIHiH+5MADZdkOQIECBAgQIAAAQIECBAYUSCRE514O/EecYRdmgABAgQIECBAgAABAn0LCN7h/iRAwyVZjgABAgQIECBAgAABAgRGFEjkRCfeTrxHHGGXJkCAAAECBAgQIECAQN8Cgne4PwnQcEmWI0CAAAECBAgQIECAAIERBRI50Ym3E+8RR9ilCRAgQIAAAQIECBAg0LfASgTvr3/96+V5z3teOfHEE8uXv/zlsvvuu8/+d+123nnnlWOOOaa8973vLaeeemq54hWvWPbee+9y1FFHlT322GOrOpgA3aoLujMBAgQIECBAgAABAgQIdC2QyIndn3i/853vLI9+9KPLPvvsMwvWF1544cWCdw3hd7vb3crDHvawcsc73rFccMEFs6D+mc98ppx88snl5je/+dxNTIDOfTF3JECAAAECBAgQIECAAIHuBRI5sfvgXYP2tttuO2vGQQcdNAvT60+8f/KTn5RtttmmXOUqV9nQsPPPP7/ssssu5QEPeEB58YtfPHcjE6BzX8wdCRAgQIAAAQIECBAgQKB7gURO7D54r+/CxoL3prpUT8h33nnn8o53vGPuRiZA576YOxIgQIAAAQIECBAgQIBA9wKJnDjJ4H3uueeWX/u1XyuHH354edaznjV3IxOgc1/MHQkQIECAAAECBAgQIECge4FETpxk8D7kkEPKG9/4xvK1r31tduq9qVv9YLb6z9rt7LPPnn0w21lnnbXZr+t+MhRIgAABAgQIECBAgAABAhEBwXsjjK961avKwQcfXF796leXhzzkIZuFPuKII8qRRx55qfsI3pH5tMgcArs+8T1z3Gvzdzn96Hs3r2EBAgQIECBAgAABAgQ2LiB4X8Llfe97X/nd3/3d8qQnPak885nP3OLcOPHeIpE7LFhA8F4wsOUJECBAgAABAgQINAoI3usA69/5vstd7lLuf//7l1e+8pWXiTYBepku7ItWVkDwXtnW2zgBAgQIECBAgMCSCCRy4iTe4/3Vr3613OEOdyj77bdfOe6448p22213mVqYAL1MF/ZFKysgeK9s622cAAECBAgQIEBgSQQSObH74P3Tn/60vPe975215CUveUk57bTTyjHHHDP7//fff/9y0UUXlT333HP2v6997Wsv9ve8r371q5db3OIWc7czATr3xdyRQClF8DYGBAgQIECAAAECBPoWSOTE7oP36aefXnbbbbeNduL444+f/fsDDjhgo/+9BvMPf/jDc3cxATr3xdyRgOBtBggQIECAAAECBAh0L5DIid0H7yG7kAAdsl7XWn4BJ97L30M7IECAAAECBAgQmLZAIicK3utmJAE67ZGzu7SA4J0WtR4BAgQIECBAgACBrEAiJwregnd2Kq22VQKC91ZxuTMBAgQIECBAgACBwQUE7zB5AjRckuUmLiB4T7zBtkeAAAECBAgQILD0Aomc6MTbiffSPxCWeQOC9zJ3T+0ECBAgQIAAAQKrICB4h7ucAA2XZLmJCwjeE2+w7REgQIAAAQIECCy9QCInOvF24r30D4Rl3oDgvczdUzsBAgQIECBAgMAqCAje4S4nQMMlWW7iAoL3xBtsewQIECBAgAABAksvkMiJTrydeC/9A2GZNyB4L3P31E6AAAECBAgQILAKAoJ3uMsJ0HBJlpu4gOA98QbbHgECBAgQIECAwNILJHKiE28n3kv/QFjmDQjey9w9tRMgQIAAAQIECKyCgOAd7nICNFyS5SYuIHhPvMG2R4AAAQIECBAgsPQCiZzoxNuJ99I/EJZ5A4L3MndP7QQIECBAgAABAqsgIHiHu5wADZdkuYkLCN4Tb7DtESBAgAABAgQILL1AIic68XbivfQPhGXegOC9zN1TOwECBAgQIECAwCoICN7hLidAwyVZbuICgvfEG2x7BAgQIECAAAECSy+QyIlOvJ14L/0DYZk3IHgvc/fUToAAAQIECBAgsAoCgne4ywnQcEmWm7iA4D3xBtseAQIECBAgQIDA0gskcqITbyfeS/9AWOYNCN7L3D21EyBAgAABAgQIrIKA4B3ucgI0XJLlJi4geE+8wbZHgAABAgQIECCw9AKJnOjE24n30j8QlnkDgvcyd0/tBAgQIECAAAECqyAgeIe7nAANl2S5iQsI3hNvsO0RIECAAAECBAgsvUAiJzrxduK99A+EZd6A4L3M3VM7AQIECBAgQIDAKggI3uEuJ0DDJVlu4gKC98QbbHsECBAgQIAAAQJLL5DIiU68nXgv/QNhmTcgeC9z99ROgAABAgQIECCwCgKCd7jLCdBwSZabuIDgPfEG2x4BAgQIECBAgMDSCyRyohNvJ95L/0BY5g0I3svcPbUTIECAAAECBAisgoDgHe5yAjRckuUmLiB4T7zBtkeAAAECBAgQILD0Aomc6MTbiffSPxCWeQOC9zJ3T+0ECBAgQIAAAQKrICB4h7ucAA2XZLmJCwjeE2+w7REgQIAAAQIECCy9QCInOvF24r30D4Rl3oDgvczdUzsBAgQIECBAgMAqCAje4S4nQMMlWW7iAoL3xBtsewQIECBAgAABAksvkMiJTrydeC/9A2GZNyB4L3P31E6AAAECBAgQILAKAoJ3uMsJ0HBJlpu4gOA98QbbHgECBAgQIECAwNILJHKiE28n3kv/QFjmDQjey9w9tRMgQIAAAQIECKyCgOAd7nICNFyS5SYuIHhPvMG2R4AAAQIECBAgsPQCiZzoxNuJ99I/EJZ5A4L3MndP7QQIECBAgAABAqsgIHiHu5wADZdkuYkLCN4Tb7DtESBAgAABAgQILL1AIic68XbivfQPhGXegOC9zN1TOwECBAgQIECAwCoICN7hLidAwyVZrnOBRHBu3eLpR9+7dQlfT4AAAQIECBAgQIDAJgQSOdGJtxNvD7AGAcG7Ac+XEiBAgAABAgQIEFgCAcE73KQEaLgky3UuIHh33iDlESBAgAABAgQIEGgUSOREJ95OvBvHcLW/XPBe7f7bPQECBAgQIECAwPQFBO9wjxOg4ZIs17mA4N15g5RHgAABAgQIECBAoFEgkROdeDvxbhzD1f5ywXu1+2/3BAgQIECAAAEC0xcQvMM9ToCGS7Jc5wKCd+cNUh4BAgQIECBAgACBRoFETnTi7cS7cQxX+8sF79Xuv90TIECAAAECBAhMX0DwDvc4ARouyXKdCwjenTdIeQQIECBAgAABAgQaBRI50Ym3E+/GMVztLxe8V7v/dk+AAAECBAgQIDB9AcE73OMEaLgky3UuIHh33iDlESBAgAABAgQIEGgUSOREJ95OvBvHcLW/XPBe7f7bPQECBAgQIECAwPQFBO9wjxOg4ZIs17mA4N15g5RHgAABAgQIECBAoFEgkROdeDvxbhzD1f5ywXu1+2/3BAgQIECAAAEC0xcQvMM9ToCGS7Jc5wKCd+cNUh4BAgQIECBAgACBRoFETnTi7cS7cQxX+8sF79Xuv90TIECAAAECBAhMX0DwDvc4ARouyXKdCwjenTdIeQQIECBAgAABAgQaBRI50Ym3E+/GMVztLxe8V7v/dk+AAAECBAgQIDB9AcE73OMEaLgky3UuIHh33iDlESBAgAABAgQIEGgUSOREJ95OvBvHcLW/XPBe7f7bPQECBAgQIECAwPQFBO9wjxOg4ZIs17mA4N15g5RHgAABAgQIECBAoFEgkROdeDvxbhzD1f5ywXu1+2/3BAgQIECAAAEC0xcQvMM9ToCGS7Jc5wKCd+cNUh4BAgQIECBAgACBRoFETnTi7cS7cQxX+8sF79Xuv90TIECAAAECBAhMX0DwDvc4ARouyXKdCwjenTdIeQQIECBAgAABAgQaBRI50Ym3E+/GMVztLxe8V7v/dk+AAAECBAgQIDB9AcE73OMEaLgky3UuIHh33iDlESBAgAABAgQIEGgUSOREJ95OvBvHcLW/XPBe7f7bPQECBAgQIECAwPQFBO9wjxOg4ZIs17mA4N15g5RHgAABAgQIECBAoFEgkROdeDvxbhzD1f5ywXu1+2/3BAgQIECAAAEC0xcQvMM9ToCGS7Jc5wKCd+cNUh4BAgQIECBAgACBRoFETnTi7cS7cQxX+8sF79Xuv90TIECAAAECBAhMX0DwDvc4ARouyXKdCwjenTdIeQQIECBAgAABAgQaBRI50Ym3E+/GMVztLxe8V7v/dk+AAAECBAgQIDB9AcE73OMEaLgky3UuIHh33iDlESBAgAABAgQIEGgUSOREJ95OvBvHcLW/XPBe7f7bPQECBAgQIECAwPQFBO9wjxOg4ZIs17mA4N15g5RHgAABAgQIECBAoFEgkROdeDvxbhzD1f5ywXu1+2/3BAgQIECAAAEC0xdYieD99a9/vTzvec8rJ554Yvnyl79cdt9999n/XvJ27LHHluc85znlzDPPLL/xG79Rnv3sZ5cDDzxwq6YgAbpVF3TnpRcQvJe+hTZAgAABAgQIECBAYLMCiZzY/Yn3O9/5zvLoRz+67LPPPuXUU08tF1544aWC95vf/ObygAc8oDzlKU8pd77znctb3vKWUoP4xz72sXL7299+7jFKgM59MXechIDgPYk22gQBAgQIECBAgACBTQokcmL3wbsG7W233XaGcNBBB5WTTz75UsG7nnDvueee5Y1vfOMGrP32269c85rXLO9973vnHqEE6NwXc8dJCAjek2ijTRAgQIAAAQIECBBY7eC9fvcbC97f+MY3yo1vfONy3HHHlfve974b7v6iF72oPP7xjy/nnXdeueIVrzjXGAneczG50zoBwds4ECBAgAABAgQIEJi2QCIndn/ivaXgXU+0733ve5dTTjll9v7vtdsHP/jBcve73/1S/35zI5EAnfbI2d0lBQRvM0GAAKCAr4sAACAASURBVAECBAgQIEBg2gKJnLj0wfsNb3hDedCDHlTOPvvscv3rX39Dx+tL0vfaa6/y8Y9/vNSXnW/sVk/D6z9rt7rG3nvvXc4666yy8847T3t67C4iIHhHGC1CgAABAgQIECBAoFsBwbuU0hK8jzjiiHLkkUdeqsGCd7czHy+sh+DcuqnTj7530xIJg9YamjbgiwkQIECAAAECBAgsUEDwLmX24Wn1peZf+9rXZn9GbO02z0vNnXgvcDqXZOlE6Bx7q62hN2HQWsPYhq5PgAABAgQIECBAYFMCgncpZe3D1f7pn/6p/N7v/d4Gqxe/+MXlL/7iL8qPf/zjcoUrXGGuKUqAznUhd+pGIBE6x95Ma+hNGLTWMLah6xMgQIAAAQIECBAQvP9HYHN/Tqy+n/v1r3/9Bqvf/u3fLle/+tX9OTGPn80KJELn2MStoTdh0FrD2IauT4AAAQIECBAgQGClg/dPf/rTDeH5JS95STnttNPKMcccMzPZf//9yw477FDe9KY3lQc+8IHlaU97WjnggAPKW97ylvLKV76yfPSjHy377rvv3BPkxHtuqsncMRE6x8ZoDb0Jg9YaxjZ0fQIECBAgQIAAAQIrHbxPP/30sttuu23U4Pjjjy93utOdZv/t2GOPLUcffXQ588wzZ+/1Puqoo8qBBx64VdMjeG8V1yTunAidY0O0ht6EQWsNYxu6PgECBAgQIECAAIGVDt5Dtl/wHlK7j2slQufYO2kNvQmD1hrGNnR9AgQIECBAgAABAoL3QDMgeA8E3dFlEqFz7O20ht6EQWsNYxu6PgECBAgQIECAAAHBe6AZELwHgu7oMonQOfZ2WkNvwqC1hrENXZ8AAQIECBAgQICA4D3QDAjeA0F3dJlE6Bx7O62hN2HQWsPYhq5PgAABAgQIECBAQPAeaAYE74GgO7pMInSOvZ3W0JswaK1hbEPXJ0CAAAECBAgQICB4DzQDgvdA0B1dJhE6x95Oa+hNGLTWMLah6xMgQIAAAQIECBAQvAeaAcF7IOiOLpMInWNvpzX0Jgxaaxjb0PUJECBAgAABAgQICN4DzYDgPRB0R5dJhM6xt9MaehMGrTWMbej6BAgQIECAAAECBATvgWZA8B4IuqPLJELn2NtpDb0Jg9YaxjZ0fQIECBAgQIAAAQKC90AzIHgPBN3RZRKhc+zttIbehEFrDWMbuj4BAgQIECBAgAABwXugGRC8B4Lu6DKJ0Dn2dlpDb8KgtYaxDV2fAAECBAgQIECAgOA90AwI3gNBd3SZROgcezutoTdh0FrD2IauT4AAAQIECBAgQEDwHmgGBO+BoDu6TCJ0jr2d1tCbMGitYWxD1ydAgAABAgQIECAgeA80A4L3QNAdXSYROsfeTmvoTRi01jC2oesTIECAAAECBAgQELwHmgHBeyDoji6TCJ1jb6c19CYMWmsY29D1CRAgQIAAAQIECAjeA82A4D0QdEeXSYTOsbfTGnoTBq01jG3o+gQIECBAgAABAgQE74FmQPAeCLqjyyRC59jbaQ29CYPWGsY2dH0CBAgQIECAAAECgvdAMyB4DwTd0WUSoXPs7bSG3oRBaw1jG7o+AQIECBAgQIAAAcF7oBkQvAeC7ugyidA59nZaQ2/CoLWGsQ1dnwABAgQIECBAgIDgPdAMCN4DQXd0mUToHHs7raE3YdBaw9iGrk+AAAECBAgQIEBA8B5oBgTvgaA7ukwidI69ndbQmzBorWFsQ9cnQIAAAQIECBAgIHgPNAOC90DQHV0mETrH3k5r6E0YtNYwtqHrEyBAgAABAgQIEBC8B5oBwXsg6I4ukwidY2+nNfQmDFprGNvQ9QkQIECAAAECBAgI3gPNgOA9EHRHl0mEzrG30xp6EwatNYxt6PoECBAgQIAAAQIEBO+BZkDwHgi6o8skQufY22kNvQmD1hrGNnR9AgQIECBAgAABAoL3QDMgeA8E3dFlEqFz7O20ht6EQWsNYxu6PgECBAgQIECAAAHBe6AZELwHgu7oMonQOfZ2WkNvwqC1hrENXZ8AAQIECBAgQICA4D3QDAjeA0F3dJlE6Bx7O62hN2HQWsPYhq5PgAABAgQIECBAQPAeaAYE74GgO7pMInSOvZ3W0JswaK1hbEPXJ0CAAAECBAgQICB4DzQDgvdA0B1dJhE6x95Oa+hNGLTWMLah6xMgQIAAAQIECBAQvAeaAcF7IOiOLpMInWNvpzX0Jgxaaxjb0PUJECBAgAABAgQICN4DzYDgPRB0R5dJhM6xt9MaehMGrTWMbej6BAgQIECAAAECBATvgWZA8B4IuqPLJELn2NtpDb0Jg9YaxjZ0fQIECBAgQIAAAQKC90AzIHgPBN3RZRKhc+zttIbehEFrDWMbuj4BAgQIECBAgAABwXugGRC8B4Lu6DKJ0Dn2dlpDb8KgtYaxDV2fAAECBAgQIECAgOA90AwI3gNBd3SZROgcezutoTdh0FrD2IauT4AAAQIECBAgQEDwHmgGBO+BoDu6TCJ0jr2d1tCbMGitYWxD1ydAgAABAgQIECAgeA80A4L3QNAdXSYROsfeTmvoTRi01jC2oesTIECAAAECBAgQELwHmgHBeyDoji6TCJ0dbWe0UgTv0ehdmAABAgQIECBAYMECiZy4zUUXXXTRgutcmuUToEuzWYXOBATvzCAI3hlHqxAgQIAAAQIECPQnkMiJgve6viZA+xsTFW1OQPDOzIfgnXG0CgECBAgQIECAQH8CiZwoeAve/U32gBUJ3hlswTvjaBUCBAgQIECAAIH+BATvcE8SoOGSLLdgAcE7Ayx4ZxytQoAAAQIECBAg0J9AIic68Xbi3d9kD1iR4J3BFrwzjlYhQIAAAQIECBDoT0DwDvckARouyXILFhC8M8CCd8bRKgQIECBAgAABAv0JJHKiE28n3v1N9oAVCd4ZbME742gVAgQIECBAgACB/gQE73BPEqDhkiy3YAHBOwMseGccrUKAAAECBAgQINCfQCInOvF24t3fZA9YkeCdwRa8M45WIUCAAAECBAgQ6E9A8A73JAEaLslyCxYQvDPAgnfG0SoECBAgQIAAAQL9CSRyohNvJ979TfaAFQneGWzBO+NoFQIECBAgQIAAgf4EBO9wTxKg4ZIst2ABwTsDLHhnHK1CgAABAgQIECDQn0AiJzrxduLd32QPWJHgncEWvDOOViFAgAABAgQIEOhPQPAO9yQBGi7JcgsWELwzwIJ3xtEqBAgQIECAAAEC/QkkcqITbyfe/U32gBUJ3hlswTvjaBUCBAgQIECAAIH+BATvcE8SoOGSLLdgAcE7Ayx4ZxytQoAAAQIECBAg0J9AIic68Xbi3d9kD1iR4J3BFrwzjlYhQIAAAQIECBDoT0DwDvckARouyXILFhC8M8CCd8bRKgQIECBAgAABAv0JJHKiE28n3v1N9oAVCd4ZbME742gVAgQIECBAgACB/gQE73BPEqDhkiy3YAHBOwMseGccrUKAAAECBAgQINCfQCInOvF24t3fZA9YkeCdwRa8M45WIUCAAAECBAgQ6E9A8A73JAEaLslyCxYQvDPAgnfG0SoECBAgQIAAAQL9CSRyohNvJ979TfaAFQneGWzBO+NoFQIECBAgQIAAgf4EBO9wTxKg4ZIst2ABwTsDLHhnHK1CgAABAgQIECDQn0AiJzrxduLd32QPWJHgncEWvDOOViFAgAABAgQIEOhPQPAO9yQBGi7JcgsWELwzwIJ3xtEqBAgQIECAAAEC/QkkcqITbyfe/U32gBUJ3hlswTvjaBUCBAgQIECAAIH+BATvcE8SoOGSLLdgAcE7Ayx4ZxytQoAAAQIECBAg0J9AIic68Xbi3d9kD1iR4J3BFrwzjlYhQIAAAQIECBDoT0DwDvckARouyXILFhC8M8CCd8bRKgQIECBAgAABAv0JJHKiE28n3v1N9oAVCd4ZbME742gVAgQIECBAgACB/gQE73BPEqDhkiy3YAHBOwMseGccrUKAAAECBAgQINCfQCInOvF24t3fZA9YkeCdwRa8M45WIUCAAAECBAgQ6E9A8A73JAEaLslyCxYQvDPAgnfG0SoECBAgQIAAAQL9CSRyohNvJ979TfaAFQneGWzBO+NoFQIECBAgQIAAgf4EBO9wTxKg4ZIst2ABwTsDLHhnHK1CgAABAgQIECDQn0AiJzrxduLd32QPWJHgncEWvDOOViFAgAABAgQIEOhPQPBe15N3vetd5dnPfnb56le/WrbffvtyhzvcoRx99NHl13/91+fuXAJ07ou5YxcCgnemDYJ3xtEqBAgQIECAAAEC/QkkcuIkTrw//OEPl7vc5S7lwQ9+cHngAx9Yvv/975enP/3p5Ve/+lX50pe+VK585SvP1b0E6FwXcqduBATvTCsE74yjVQgQIECAAAECBPoTSOTESQTvQw89tHzgAx8op512Wtlmm21mnTr++OPLne985/LRj350dvo9zy0BOs913KcfAcE70wvBO+NoFQIECBAgQIAAgf4EEjlxEsH7YQ97WDn55JPLF77whQ1d+uxnP1v23HPP8pGPfKTc8Y53nKt7CdC5LuRO3QgI3plWCN4ZR6sQIECAAAECBAj0J5DIiZMI3h/72Mdmp9svfOELN7zU/FGPelT57ne/W0466aRyuctdbq7uJUDnupA7dSMgeGdaIXhnHK1CgAABAgQIECDQn0AiJ04ieNfW/PM//3N5wAMeUH784x/POnXrW9+6vP/97y/Xu971Ntm58847r9R/1m5nn3122XvvvctZZ51Vdt555/46rqK4gOCdIRW8M45WIUCAAAECBAgQ6E9A8P6fnnziE58o9773vcvBBx9cDjzwwNmHq/3VX/1VufzlL1/qafimPlztiCOOKEceeeSlOit49zfsG6tIaO6nT4J3P71QCQECBAgQIECAQFZA8P4fz9vd7nZll112Ke94xzs2CFecG93oRuXlL395OeSQQzYq78Q7O5BDryZ4Dy2+6esJ3v30QiUECBAgQIAAAQJZAcH7fzyvcpWrlCc96UnlaU972sWEd9xxx/LQhz60POc5z5lLPgE614XcKSIgeEcYI4sI3hFGixAgQIAAAQIECHQokMiJk3iP981vfvOy++67l+OOO25Dm84444yy2267lZe85CXlkY985FztS4DOdSF3iggI3hHGyCKCd4TRIgQIECBAgAABAh0KJHLiJIJ3/TTzww47rDzmMY8p97nPfWbv8X7Ws55VzjnnnPKVr3ylXOc615mrfQnQuS7kThEBwTvCGFlE8I4wWoQAAQIECBAgQKBDgUROnETwvuiii8rf/d3flZe97GXltNNOK1e72tXKvvvuW4466qjZSfi8twTovNdyv3YBwbvdMLWC4J2StA4BAgQIECBAgEBvAomcOIngnWpMAjRVi3W2LCB4b9loqHsI3kNJuw4BAgQIECBAgMDQAomcKHiv61oCdOghWOXrCd79dF/w7qcXKiFAgAABAgQIEMgKJHKi4C14Z6dywNUE7wGxt3ApwbufXqiEAAECBAgQIEAgKyB4Zz1LAjRckuU2IyB49zMegnc/vVAJAQIECBAgQIBAViCRE514O/HOTuWAqwneA2I78e4HWyUECBAgQIAAAQKDCgjeYe4EaLgkyznxXooZcOK9FG1SJAECBAgQIECAwGUQSOREJ95OvC/D6PXxJU68++hDrULw7qcXKiFAgAABAgQIEMgKCN5ZT+/xDnsuejnBe9HC868veM9v5Z4ECBAgQIAAAQLLJSB4h/uVAA2XZLnNCAje/YyH4N1PL1RCgAABAgQIECCQFUjkRC81X9eTBGi2xVbbnIDg3c98CN799EIlBAgQIECAAAECWYFEThS8Be/sVA64muA9IPYWLiV499MLlRAgQIAAAQIECGQFBO+sp/d4hz0XvZzgvWjh+dcXvOe3ck8CBAgQIECAAIHlEhC8w/1KgIZLstxmBATvfsZD8O6nFyohQIAAAQIECBDICiRyopear+tJAjTbYqttTkDw7mc+BO9+eqESAgQIECBAgACBrEAiJwregnd2KgdcTfAeEHsLlxK8++mFSggQIECAAAECBLICgnfW03u8w56LXk7wXrTw/OsL3vNbuScBAgQIECBAgMByCQje4X4lQMMlWW4zAoJ3P+MhePfTC5UQIECAAAECBAhkBRI50UvN1/UkAZptsdU2JyB49zMfgnc/vVAJAQIECBAgQIBAViCREwVvwTs7lQOuJngPiL2FSwne/fRCJQQIECBAgAABAlkBwTvr6T3eYc9FLyd4L1p4/vUF7/mt3JMAAQIECBAgQGC5BATvcL8SoOGSLLcZAcG7n/EQvPvphUoIECBAgAABAgSyAomc6KXm63qSAM222GqbExC8+5kPwbufXqiEAAECBAgQIEAgK5DIiYK34J2dygFXE7wHxN7CpQTvfnqhEgIECBAgQIAAgayA4J319B7vsOeilxO8Fy08//qC9/xW7kmAAAECBAgQILBcAoJ3uF8J0HBJltuMgODdz3gI3v30QiUECBAgQIAAAQJZgURO9FLzdT1JgGZbbLXNCQje/cyH4N1PL1RCgAABAgQIECCQFUjkRMFb8M5O5YCrCd4DYm/hUoJ3P71QCQECBAgQIECAQFZA8M56eo932HPRywneixaef33Be34r9yRAgAABAgQIEFguAcE73K8EaLgky21GQPDuZzwE7356oRICBAgQIECAAIGsQCIneqn5up4kQLMtttrmBATvfuZD8O6nFyohQIAAAQIECBDICiRyouAteGencsDVBO8BsbdwKcG7n16ohAABAgQIECBAICsgeGc9vcc77Lno5QTvRQvPv77gPb+VexIgQIAAAQIECCyXgOAd7lcCNFyS5TYjIHj3Mx6Cdz+9UAkBAgQIECBAgEBWIJETvdR8XU8SoNkWW21zAoJ3P/MhePfTC5UQIECAAAECBAhkBRI5UfAWvLNTOeBqgveA2Fu4lODdTy9UQoAAAQIECBAgkBUQvLOe3uMd9lz0coL3ooXnX1/wnt/KPQkQIECAAAECBJZLQPAO9ysBGi7JcpsRELz7GQ/Bu59eqIQAAQIECBAgQCArkMiJXmq+ricJ0GyLrbY5AcG7n/kQvPvphUoIECBAgAABAgSyAomcGA/eZ5xxRjnvvPPKHnvsMdvtz3/+8/K85z2vnHLKKeWud71rOeigg7IKwdUSoMFyLLUFAcG7nxERvPvphUoIECBAgAABAgSyAomcGA/ed7/73cutb33r8tznPne228MOO6y89KUvLbe85S3LF7/4xfK3f/u35VGPelRWIrRaAjRUimXmEBC850Aa6C6C90DQLkOAAAECBAgQIDC4QCInxoP3jjvuWI499thyn/vcp/zyl78sO+ywQ3n6059eDj/88HLUUUeVN73pTeVLX/rS4FjzXDABOs913CcjIHhnHBOrCN4JRWsQIECAAAECBAj0KJDIifHgfeUrX7n8y7/8S7njHe9YPv7xj8/+txa60047lY9+9KPlXve6V/nJT37So6dPNe+yK5suSvDup2GCdz+9UAkBAgQIECBAgEBWoMvgfdOb3rQ84hGPKH/5l39ZHve4x5UPfOADG0643/nOd5aHP/zh5ZxzzslKhFZLgIZKscwcAoL3HEgD3UXwHgjaZQgQIECAAAECBAYXSOTE+In30UcfPXtp+a1udavyuc99rrzgBS8of/7nfz7DedKTnjQ7Ba8n3z3eEqA97muqNQne/XRW8O6nFyohQIAAAQIECBDICiRyYjx41y2+9rWvLSeddFK57W1vO/sU82222Wa280MPPbTst99+5cEPfnBWIrRaAjRUimXmEBC850Aa6C6C90DQLkOAAAECBAgQIDC4QCInLiR4Dy4RumACNFSKZeYQELznQBroLoL3QNAuQ4AAAQIECBAgMLhAIicuLHi///3vn516n3XWWeWpT31qudGNbjR7iflNbnKTcoMb3GBwrHkumACd5zrukxEQvDOOiVUE74SiNQgQIECAAAECBHoUSOTEePCuH5x23/vet5x44onlhje84Sx4r3/Z+VWvetXykpe8pEdPn2reZVc2XZTg3U/DBO9+eqESAgQIECBAgACBrECXwfuBD3zgLGjXTzCvn3B+hStcoZx88smz93u//vWvL8961rPK1772taxEaLUEaKgUy8whIHjPgTTQXQTvgaBdhgABAgQIECBAYHCBRE6Mn3hf85rXLK94xSvKH/3RH5Vf/epX5fKXv/yG4P2Rj3yk3Pve9y7nn3/+4FjzXDABOs913CcjIHhnHBOrCN4JRWsQIECAAAECBAj0KJDIifHgvf3225e3vvWt5Xd+53cuFbz/6Z/+qRx88MHlBz/4QY+eXmreZVc2XZTg3U/DBO9+eqESAgQIECBAgACBrECXwfsud7lLuda1rlXe/va3Xyp4/8mf/En5yU9+Ut797ndnJUKrJUBDpVhmDgHBew6kge4ieA8E7TIECBAgQIAAAQKDCyRyYvzE+5Of/GQ54IADyt57713+8A//sBx++OHlKU95SjnllFPKe97znnLCCSfM3u/d4y0B2uO+plqT4N1PZwXvfnqhEgIECBAgQIAAgaxAIifGg3fdYg3fT3ziE8snPvGJ2an3NttsU/bdd9/yN3/zN7P/7fWWAO11b1OsS/Dup6uCdz+9UAkBAgQIECBAgEBWIJETFxK817b5s5/9rPzwhz8s9QPXrnKVq2R3v4DVEqALKMuSmxAQvPsZDcG7n16ohAABAgQIECBAICuQyIkLDd7Z7S5+tQTo4qt0hTUBwbufWRC8++mFSggQIECAAAECBLICiZwYCd6Pecxj5t5Zfdn5C1/4wrnvP+QdE6BD1rvq1xK8+5kAwbufXqiEAAECBAgQIEAgK5DIiZHgvdtuu829sxq8v/GNb8x9/yHvmAAdst5Vv5bg3c8ECN799EIlBAgQIECAAAECWYFETowE7+y2xlstATpe9at3ZcG7n54L3v30QiUECBAgQIAAAQJZgUROFLzX9SQBmm2x1TYnIHj3Mx+Cdz+9UAkBAgQIECBAgEBWIJETFxK8v/e975UXvOAF5VOf+lQ5++yzy0477VRuf/vbl8c+9rFlhx12yCoEV0uABsux1BYEBO9+RkTw7qcXKiFAgAABAgQIEMgKJHJiPHjXsH3Pe96zXHjhheWud71rud71rle+853vlH/913+d7f4DH/hA2WeffbISodUSoKFSLDOHgOA9B9JAdxG8B4J2GQIECBAgQIAAgcEFEjkxHrxvd7vblStd6Urlve99b7n61a++AeVHP/pRude97lV+8YtflJNOOmlwrHkumACd5zrukxEQvDOOiVUE74SiNQgQIECAAAECBHoUSOTEePC+8pWvXN72treVAw888FJm73rXu8of//Efl5/97Gc9epYEaJcbm2hRgnc/jRW8++mFSggQIECAAAECBLICiZwYD9577LFHecITnlAe9KAHXWq3r3vd68rRRx9dvvKVr2QlQqslQEOlWGYOAcF7DqSB7iJ4DwTtMgQIECBAgAABAoMLJHJiPHi///3vL3/2Z39W/uEf/qHsv//+G1A+/OEPl4c97GHl//7f/zt7yXmPtwRoj/uaak2Cdz+dFbz76YVKCBAgQIAAAQIEsgKJnBgP3vXEu36S+Q9/+MNyjWtcY/Yp5uecc06p7/G+1rWuVW5wgxtsUNhmm23KF77whaxKw2oJ0IbL+9KtFBC8txJsgXcXvBeIa2kCBAgQIECAAIFRBRI5MR68DzrooFID9by3V73qVfPedeH3S4AuvEgX2CAgePczDIJ3P71QCQECBAgQIECAQFYgkRPjwTu7xWFXS4AOW/FqX03w7qf/gnc/vVAJAQIECBAgQIBAViCREwXvdT1JgGZbbLXNCQje/cyH4N1PL1RCgAABAgQIECCQFUjkxIUE7xNPPHH2J8XOOuuscsEFF1xs1/Vl6O985zuzEqHVEqChUiwzh4DgPQfSQHcRvAeCdhkCBAgQIECAAIHBBRI5MR68X/jCF5bDDz+87LjjjuXGN75xucIVrnApmOOPP35wrHkumACd5zrukxEQvDOOiVUE74SiNQgQIECAAAECBHoUSOTEePC+4Q1vWO53v/uVv/3bvy3bbrttj26brCkBulQbXvJiBe9+Gih499MLlRAgQIAAAQIECGQFEjkxHryvfe1rz15mfpe73CW72wFWS4AOUKZL/I+A4N3PKAje/fRCJQQIECBAgAABAlmBRE6MB+9HPvKR5apXvWp53vOel93tAKslQAco0yUE7+5mQPDuriUKIkCAAAECBAgQCAkkcmI8eP/85z8vD3/4w8uvfvWrcte73rVc85rXvNR2f//3fz9EkF0mAZqtyGqbE3Di3c98CN799EIlBAgQIECAAAECWYFETowH7y984Quz93iffvrpG91t/VTzGsoXcXvNa14ze2/5KaecUrbffvuy1157lX/8x38sV77ylee6XAJ0rgu5U0RA8I4wRhYRvCOMFiFAgAABAgQIEOhQIJET48F7zz33LL/4xS/KX//1X5eb3exmG/1U81122SXO+exnP7s85znPKU9+8pPLvvvuW773ve+Vf/u3fyvPfe5zZyF8nlsCdJ7ruE9GQPDOOCZWEbwTitYgQIAAAQIECBDoUSCRE+PB+ypXucrslPme97znYGb//u//Xn7rt36rvOtd7yr3ute9LvN1E6CX+eK+cKsFBO+tJlvYFwjeC6O1MAECBAgQIECAwMgCiZwYD9777bdf+dM//dPykIc8ZDCeJz7xibOwf+qppzZdMwHaVIAv3ioBwXuruBZ6Z8F7obwWJ0CAAAECBAgQGFEgkRPjwfvzn/98Oeigg2Yv8b7zne9ctttuu4UT3elOdyrXuc51ym1uc5vyohe9qJx77rmzcsMSVwAAIABJREFU93cfc8wxZZ999pn7+gnQuS/mjs0CgnczYWwBwTtGaSECBAgQIECAAIHOBBI5MR68r3a1q83e413/2XbbbS/1wWb1w9V+9KMfRSl333338u1vf7vstNNO5aijjir15e71f7/0pS+V//iP/yg77rjjRq933nnnlfrP2u3ss88ue++9dznrrLPKzjvvHK3RYnkBwTtvellXFLwvq5yvI0CAAAECBAgQ6F2gy+B9xBFHlBquN3d7xjOeEbWtH+JWA3b9RPVb3vKWs7V/8IMflF133bUcdthh5ZnPfOZGr1drPfLIIy/13wTvaHsWtpjgvTDarV5Y8N5qMl9AgAABAgQIECCwJAJdBu8x7OrLyU877bTZJ5mvv+2///7lute9bnnHO96x0bKceI/Rrdw1Be+cZetKgneroK8nQIAAAQIECBDoVUDw/p/OHHzwwbNPNN9Y8K5/Suw973nPXD1MgM51IXeKCAjeEcbIIoJ3hNEiBAgQIECAAAECHQokcmL8Pd7V6etf/3p59atfPfuU8QsuuOBSdDUkJ2/1E83/4A/+oHzuc58rt771rWdLf//735+91Pzwww/f5EvNL1lDAjS5L2ttXkDw7mdCBO9+eqESAgQIECBAgACBrEAiJ8aD90knnVTqS7x32WWXWfCu77muH6Z2+umnzz6w7CY3uUn50Ic+FJW48MILy+1vf/vZ+7qf/exnzz7Q7a//+q9n7/v+8pe/XK5//evPdb0E6FwXcqeIgOAdYYwsInhHGC1CgAABAgQIECDQoUAiJ8aD9wEHHDAL3ccee2y5/OUvX04++eRy29vetnziE58o97///cvf//3fl3vc4x5xzvoy83q6/e53v7v813/9V7nDHe5QXvCCF5Rb3OIWc18rATr3xdyxWUDwbiaMLSB4xygtRIAAAQIECBAg0JlAIifGg/e1r33t8qY3vanc/e53L5e73OXKCSecUPbbb78Z3ate9arZ39muLwnv8ZYA7XFfU61J8O6ns4J3P71QCQECBAgQIECAQFYgkRPjwfs617lOefvb317qyXd9iXc9da4n3fX2wQ9+sNz3vvctP/nJT7ISodUSoKFSLDOHgOA9B9JAdxG8B4J2GQIECBAgQIAAgcEFEjkxHrzrS7wf8pCHlIc//OHlfve7X6l/E7t+0Fp92fmjHvWocs4555QvfvGLg2PNc8EE6DzXcZ+MgOCdcUysIngnFK1BgAABAgQIECDQo0AiJ8aD9+te97pyxhlnlKc+9anllFNOmb3k/D//8z9nfle96lVnp+H13/V4S4D2uK+p1iR499NZwbufXqiEAAECBAgQIEAgK5DIifHgfcktnn/++bMPVqt/Vqx+8viOO+6YVQiulgANlmOpLQgI3v2MiODdTy9UQoAAAQIECBAgkBVI5MSFB+/slhe7WgJ0sRVafb2A4N3PPAje/fRCJQQIECBAgAABAlmBRE6MBO/6p7zqy8nr3+xef6vv5X7mM585e8n5TjvtVB772MeW+9znPlmF4GoJ0GA5ltqCgODdz4gI3v30QiUECBAgQIAAAQJZgUROjATvRzziEeUzn/lM+exnP7thh/V93jWI//SnPy23utWtZh+y9v3vf7986EMfKne84x2zEqHVEqChUiwzh4DgPQfSQHcRvAeCdhkCBAgQIECAAIHBBRI5MRK8b3GLW5SHPexh5XGPe9wGhMMOO6y8+MUvLu973/tmH6b2s5/9rNztbncr17jGNcp73vOewbHmuWACdJ7ruE9GQPDOOCZWEbwTitYgQIAAAQIECBDoUSCREyPBu4bpt771reUe97jHBqcb3/jG5ZrXvObsJHzt9uY3v7k8/vGPn51+93hLgPa4r6nWJHj301nBu59eqIQAAQIECBAgQCArkMiJkeBdA3YN3mt/Juw73/nO7D3d9dT7mGOO2bDrE044YXbqXU+/e7wlQHvc11RrErz76azg3U8vVEKAAAECBAgQIJAVSOTESPDeZ599yv7771+e+9znznZ47LHHlkMOOWT2kvJ73vOeG3b9tre9bfZy9DPPPDMrEVotARoqxTJzCAjecyANdBfBeyBolyFAgAABAgQIEBhcIJETI8H7DW94Q3nwgx9cDj744HL961+/vOxlLyvXuc51yle+8pWy3XbbbYB5+MMfXs4++2zv8R58VKZ5QcG7n74K3v30QiUECBAgQIAAAQJZgW6Cd91WPe2uH6b2wx/+sOy5557lpS99afnN3/zNDTv+7ne/W/bYY49y5JFHlkMPPTQrEVotARoqxTJzCAjecyANdBfBeyBolyFAgAABAgQIEBhcIJETIyfeg+98QRdMgC6oNMtuREDw7mcsBO9+eqESAgQIECBAgACBrEAiJwre63qSAM222GqbExC8+5kPwbufXqiEAAECBAgQIEAgK5DIiYK34J2dygFXE7wHxN7CpQTvfnqhEgIECBAgQIAAgayA4J31LAnQcEmW24yA4N3PeAje/fRCJQQIECBAgAABAlmBRE504u3EOzuVA64meA+I7cS7H2yVECBAgAABAgQIDCogeIe5E6DhkiznxHspZsCJ91K0SZEECBAgQIAAAQKXQSCRE514O/G+DKPXx5c48e6jD7UKwbufXqiEAAECBAgQIEAgKyB4Zz29xzvsuejlBO9FC8+/vuA9v5V7EiBAgAABAgQILJeA4B3uVwI0XJLlNiMgePczHoJ3P71QCQECBAgQIECAQFYgkRO91HxdTxKg2RZbbXMCgnc/8yF499MLlRAgQIAAAQIECGQFEjlR8Ba8s1M54GqC94DYW7iU4N1PL1RCgAABAgQIECCQFRC8s57e4x32XPRygveihedfX/Ce38o9CRAgQIAAAQIElktA8A73KwEaLslymxEQvPsZD8G7n16ohAABAgQIECBAICuQyIlear6uJwnQbIuttjkBwbuf+RC8++mFSggQIECAAAECBLICiZwoeAve2akccDXBe0DsLVxK8O6nFyohQIAAAQIECBDICgjeWU/v8Q57Lno5wXvRwvOvL3jPb+WeBAgQIECAAAECyyUgeIf7lQANl2S5zQgI3v2Mh+DdTy9UQoAAAQIECBAgkBVI5EQvNV/XkwRotsVW25yA4N3PfAje/fRCJQQIECBAgAABAlmBRE4UvAXv7FQOuJrgPSD2Fi4lePfTC5UQIECAAAECBAhkBQTvrKf3eIc9F72c4L1o4fnXF7znt3JPAgQIECBAgACB5RIQvMP9SoCGS7LcZgQE737GQ/DupxcqIUCAAAECBAgQyAokcqKXmq/rSQI022KrbU5A8O5nPgTvfnqhEgIECBAgQIAAgaxAIicK3oJ3dioHXE3wHhB7C5cSvPvphUoIECBAgAABAgSyAoJ31tN7vMOei15O8F608PzrC97zW7knAQIECBAgQIDAcgkI3uF+JUDDJU16OcF5Ou3tIXi3zlMPe5jORNgJAQIECBAgQGA6Aomc6KXm6+YhATqd8Vr8TlqD0uIrdIV5BXoIra3z1MMe5vV2PwIECBAgQIAAgeEEEjlR8Ba8h5vYS1ypNSiNVrgLX0qgh9DaOk897MFoESBAgAABAgQI9CcgeId7kgANlzTp5VqD0qRxlmxzPYTW1nnqYQ9L1nblEiBAgAABAgRWQiCRE514O/Ee7cHSGpRGK9yFnXibAQIECBAgQIAAgZURELzDrU6Ahkua9HKC93Ta28Npces89bCH6UyEnRAgQIAAAQIEpiOQyIlOvJ14j/aIaA1KoxXuwk68zQABAgQIECBAgMDKCAje4VYnQMMlTXo5wXs67e3htLh1nnrYw3Qmwk4IECBAgAABAtMRSOREJ95OvEd7RLQGpdEKd2En3maAAAECBAgQIEBgZQQE73CrE6Dhkia9nOA9nfb2cFrcOk897GE6E2EnBAgQIECAAIHpCCRyohNvJ96jPSJag9JohbuwE28zQIAAAQIECBAgsDICgne41QnQcEmTXk7wnk57ezgtbp2nHvYwnYmwEwIECBAgQIDAdAQSOdGJtxPv0R4RrUFptMJd2Im3GSBAgAABAgQIEFgZAcE73OoEaLikSS8neE+nvT2cFrfOUw97mM5E2AkBAgQIECBAYDoCiZzoxNuJ92iPiNagNFrhLuzE2wwQIECAAAECBAisjIDgHW51AjRc0qSXE7yn094eTotb56mHPUxnIuyEAAECBAgQIDAdgUROdOLtxHu0R0RrUBqtcBd24m0GCBAgQIAAAQIEVkZA8A63OgEaLmnSywne02lvD6fFrfPUwx6mMxF2QoAAAQIECBCYjkAiJzrxduI92iOiNSiNVrgLO/E2AwQIECBAgAABAisjIHiHW50ADZc06eUE7+m0t4fT4tZ56mEP05kIOyFAgAABAgQITEcgkROdeDvxHu0R0RqURivchZ14mwECBAgQIECAAIGVERC8w61OgIZLmvRygvd02tvDaXHrPPWwh+lMhJ0QIECAAAECBKYjkMiJTrydeI/2iGgNSqMV7sJOvM0AAQIECBAgQIDAyggI3uFWJ0DDJU16OcF7Ou3t4bS4dZ562MN0JsJOCBAgQIAAAQLTEUjkRCfeTrxHe0S0BqXRCndhJ95mgAABAgQIECBAYGUEBO9wqxOg4ZImvZzgPZ329nBa3DpPPexhOhNhJwQIECBAgACB6QgkcqITbyfeoz0iWoPSaIW7sBNvM0CAAAECBAgQILAyAoJ3uNUJ0HBJk15O8J5Oe3s4LW6dpx72MJ2JsBMCBAgQIECAwHQEEjnRibcT79EeEa1BabTCXdiJtxkgQIAAAQIECBBYGQHBO9zqBGi4pEkvJ3hPp709nBa3zlMPe5jORNgJAQIECBAgQGA6Aomc6MTbifdoj4jWoDRa4S7sxNsMECBAgAABAgQIrIyA4B1udQI0XNKklxO8p9PeHk6LW+ephz1MZyLshAABAgQIECAwHYFETnTi7cR7tEdEa1AarXAXduJtBggQIECAAAECBFZGQPAOtzoBGi5p0ssJ3tNpbw+nxa3z1MMepjMRdkKAAAECBAgQmI5AIic68XbiPdojojUojVa4CzvxNgMECBAgQIAAAQIrIyB4h1udAA2XNOnlBO/ptLeH0+LWeephD9OZCDshQIAAAQIECExHIJETnXg78R7tEdEalEYr3IWdeJsBAgQIECBAgACBlREQvMOtToCGS5r0coL3dNrbw2lx6zz1sIfpTISdECBAgAABAgSmI5DIiZM88T7//PPL7rvvXr797W+Xk046qdzudrebq+sJ0Lku5E4zgdaghLEfgR5Ca+s89bCHfjqqEgIECBAgQIAAgTWBRE6cZPB+whOeUF7zmteU73znO4J3x4+X1qDU8dZWrrQeQmvrPPWwh5UbHBsmQIAAAQIECCyBgOC9kSZ97Wtfm51wP//5zy+HHnqo4N3xILcGpY63tnKl9RBaW+ephz2s3ODYMAECBAgQIEBgCQQE74006W53u1u51a1uVQ488MBywAEHCN4dD3JrUOp4aytXWg+htXWeetjDyg2ODRMgQIAAAQIElkBA8L5Ek97+9reXRz/60eXUU08tn/3sZwXvzoe4NSh1vr2VKq+H0No6Tz3sYaWGxmYJECBAgAABAksiIHiva9RPf/rT2QeqHXHEEeXggw8uH/7wh7cYvM8777xS/1m7nX322WXvvfcuZ511Vtl5552XZAyWt8zWoLS8O59e5T2E1tZ56mEP05sMOyJAgAABAgQILL+A4L2uh09+8pPLBz/4wfLpT3+6bLPNNnMF7xrSjzzyyEtNguA9zIOjNSgNU6WrDCGQCL2t85SoYQgr1yBAgAABAmMLtH7PrfX7vjt2F11/awQE7//ROuOMM8rNbnazctxxx5X99ttv9m9POOGEcp/73Kccf/zxsw9b23777S9l68R7a8Ytf9/Ek3a+KiuOIZD45ts6T4kaxrBzTQIECBAgMLRA6/dcwXvojrleq4Dg/T+Cay8r3xToPvvsU0488cQteidAt3gRd9ggkHjSxjkNgUTobZ2nRA3T6IZdECBAgACBzQu0fs8VvE3YsgkkcuIk/o73ueeeWz7/+c9frH/1/z/88MPLy1/+8rLXXnuV2972tlvsbwJ0ixdxB8HbDFxKIBF6W38ISNSgtQQIECBAYBUEWr/nCt6rMCXT2mMiJ04ieG+srfN8uNolvy4BOq0RW+xuEk/ai63Q6kMJJEJv6zwlahjKy3UIECBAgMCYAq3fcwXvMbvn2pdFIJETBe918gnQy9LIVf2axJP2qtpNbd+J0Ns6T4kaptYX+yFAgAABAhsTaP2eK3ibq2UTSOTEyQbvy9LMBOhlue6qfk3iSXtV7aa270TobZ2nRA1T64v9ECBAgAABwdsMECglkRMFbyfeoz2WWoPSaIW7cFwgEXpb5ylRQxzGggQIECBAoEOB1u+5Trw7bKqSNisgeIcHJAEaLmnSyyWetCcNtEKbS4Te1nlK1LBCLbNVAgQIEFhhgdbvuYL3Cg/Pkm49kROdeDvxHm38E0/aoxXvwlGBROhtnadEDVEUixEgQIAAgU4FWr/nCt6dNlZZmxQQvMPDkQANlzTp5RJP2pMGWqHNJUJv6zwlalihltkqAQIECKywQOv3XMF7hYdnSbeeyIlOvJ14jzb+iSft0Yp34ahAIvS2zlOihiiKxQgQIECAQKcCrd9zBe9OG6ssJ95DzUDiNxlD1TqF6ySetKfgYA+lJEJv6zwlatBLAgQIECCwCgKt33MF71WYkmntMZETnXg78R7tUZF40h6teBeOCiRCb+s8JWqIoliMAAECBAh0KtD6PVfw7rSxynLiPdQMJH6TMVStU7hO4kl7Cg724MTbDBAgQIAAgWUSSPwM5xfey9RxtSZyohNvJ96jPZIST9qjFe/CUYHEN9/WeUrUEEWxGAECBAgQ6FSg9XuuE+9OG6ssJ95DzUDiNxlD1TqF6ySetKfgYA9OvM0AAQIECBBYJoHEz3B+4b1MHVdrIic68XbiPdojKfGkPVrxLhwVSHzzbZ2nRA1RFIsRIECAAIFOBVq/5zrx7rSxynLiPdQMJH6TMVStU7hO4kl7Cg724MTbDBAgQIAAgWUSSPwM5xfey9RxtSZyohNvJ96jPZIST9qjFe/CUYHEN9/WeUrUEEWxGAECBAgQ6FSg9XuuE+9OG6ssJ95DzUDiNxlD1TqF6ySetKfgYA9OvM0AAQIECBBYJoHEz3B+4b1MHVdrIic68XbiPdojKfGkPVrxLhwVSHzzbZ2nRA1RFIsRIECAAIFOBVq/5zrx7rSxynLiPdQMJH6TMVStU7hO4kl7Cg724MTbDBAgQIAAgWUSSPwM5xfey9RxtSZyohNvJ96jPZIST9qjFe/CUYHEN9/WeUrUEEWxGAECBAgQ6FSg9XuuE+9OG6ssJ95DzUDiNxlD1TqF6ySetKfgYA9OvM0AAQIECBBYJoHEz3B+4b1MHVdrIic68XbiPdojKfGkPVrxLhwVSHzzbZ2nRA1RFIsRIECAAIFOBVq/5zrx7rSxynLiPdQMJH6TMVStU7hO4kl7Cg724MTbDBAgQIAAgWUSSPwM5xfey9RxtSZyohNvJ96jPZIST9qjFe/CUYHEN9/WeUrUEEWxGAECBAgQ6FSg9XuuE+9OG6ssJ95DzUDiNxlD1TqF6ySetKfgYA9OvM0AAQIECBBYJoHEz3B+4b1MHVdrIic68XbiPdojKfGkPVrxLhwVSHzzbZ2nRA1RFIsRIECAAIFOBVq/5zrx7rSxynLiPdQMJH6TMVStU7hO4kl7Cg724MTbDBAgQIAAgWUSSPwM5xfey9RxtSZyohNvJ96jPZIST9qjFe/CUYHEN9/WeUrUEEWxGAECBAgQ6FSg9XuuE+9OG6ssJ95DzUDiNxlD1TqF6ySetKfgYA9OvM0AAQIECBBYJoHEz3B+4b1MHVdrIic68XbiPdojKfGkPVrxLhwVSHzzbZ2nRA1RFIsRIECAAIFOBVq/5zrx7rSxynLiPdQMJH6TMVStU7hO4kl7Cg724MTbDBAgQIAAgWUSSPwM5xfey9RxtSZyohNvJ96jPZIST9qjFe/CUYHEN9/WeUrUEEWxGAECBAgQ6FSg9XuuE+9OG6ssJ95DzUDiNxlD1TqF6ySetKfgYA9OvM0AAQIECBBYJoHEz3B+4b1MHVdrIic68XbiPdojKfGkPVrxLhwVSHzzbZ2nRA1RFIsRIECAAIFOBVq/5zrx7rSxynLiPdQMJH6TMVStU7hO4kl7Cg724MTbDBAgQIAAgWUSSPwM5xfey9RxtSZyohNvJ96jPZIST9qjFe/CUYHEN9/WeUrUEEWxGAECBAgQ6FSg9XuuE+9OG6ssJ95DzUDiNxlD1TqF6ySetKfgYA9OvM0AAQIECBBYJoHEz3B+4b1MHVdrIic68XbiPdojKfGkPVrxLhwVSHzzbZ2nRA1RFIsRIECAAIFOBVq/5zrx7rSxynLiPdQMJH6TMVStU7hO4kl7Cg724MTbDBAgQIAAgWUSSPwM5xfey9RxtSZyohNvJ96jPZIST9qjFe/CUYHEN9/WeUrUEEWxGAECBAgQ6FSg9XuuE+9OG6ssJ95DzUDiNxlD1dp6ncQTZmsNvp7AmkAi9LbOdKIGHSVAIC/gsZ0xnYJj6x6Evcws1VX0ImdppeUQSOREJ97rep0AXY7RyTxhLste1dm/QCL0tv4QkKihf2kVElg+AY/tTM+m4Ni6B8E7M0uCd87RSssjkMiJgrfgvTwTr9LJCiRCb+sPZIkaJtsgGyMwooDHdgZ/Co6texC8M7MkeOccrbQ8AoJ3uFcJ0HBJC1su8c1rYcVZeOUEEqG3daYTNaxc42yYwAACHtsZ5Ck4tu5B8M7MkuCdc7TS8ggkcqITbyfeyzPxKp2sQCL0tv5Alqhhsg2yMQIjCnhsZ/Cn4Ni6B8E7M0uCd87RSssjIHiHe5UADZe0sOUS37wWVpyFV04gEXpbZzpRw8o1zoYJDCDgsZ1BnoJj6x4E78wsCd45Rystj0AiJzrxduK9PBOv0skKJEJv6w9kiRom2yAbIzCigMd2Bn8Kjq17ELwzsyR45xyttDwCgne4VwnQcEkLWy7xzWthxVl45QQSobd1phM1rFzjbJjAAAIe2xnkKTi27kHwzsyS4J1ztNLyCCRyohNvJ97LM/EqnaxAIvS2/kCWqGGyDbIxAiMKeGxn8Kfg2LoHwTszS4J3ztFKyyMgeId7lQANl7Sw5RLfvBZWnIVXTiAReltnOlHDyjXOhgkMIOCxnUGegmPrHgTvzCwJ3jlHKy2PQCInOvF24r08E6/SyQokQm/rD2SJGibbIBsjMKKAx3YGfwqOrXsQvDOzJHjnHK20PAKCd7hXCdBwSQtbLvHNa2HFWXjlBBKht3WmEzWsXONsmMAAAh7bGeQpOLbuQfDOzJLgnXO00vIIJHKiE28n3ssz8SqdrEAi9Lb+QJaoYbINsjECIwp4bGfwp+DYugfBOzNLgnfO0UrLIyB4h3uVAA2XtLDlEt+8FlachVdOIBF6W2c6UcPKNc6GCQwg4LGdQZ6CY+seBO/MLAneOUcrLY9AIic68XbivTwTr9LJCiRCb+sPZIkaJtsgGyMwooDHdgZ/Co6texC8M7MkeOccrbQ8AoJ3uFcJ0HBJC1su8c1rYcVZeOUEEqG3daYTNaxc42yYwAACHtsZ5Ck4tu5B8M7MkuCdc7TS8ggkcqITbyfeyzPxKp2sQCL0tv5Alqhhsg2yMQIjCnhsZ/Cn4Ni6B8E7M0uCd87RSssjIHiHe5UADZe0sOUS37wWVpyFV04gEXpbZzpRw8o1zoYJDCDgsZ1BnoJj6x4E78wsCd45Rystj0AiJzrxduK9PBOv0skKJEJv6w9kiRom2yAbIzCigMd2Bn8Kjq17ELwzsyR45xyttDwCgne4VwnQcEkLWy7xzWthxVl45QQSobd1phM1rFzjbJjAAAIe2xnkKTi27kHwzsyS4J1ztNLyCCRyohNvJ97LM/EqnaxAIvS2/kCWqGGyDbIxAiMKeGxn8Kfg2LoHwTszS4J3ztFKyyMgeId7lQANl7Sw5RLfvBZWnIVXTiAReltnOlHDyjXOhgkMIOCxnUGegmPrHgTvzCwJ3jlHKy2PQCInOvF24r08E6/SyQokQm/rD2SJGibbIBsjMKKAx3YGfwqOrXsQvDOzJHjnHK20PAKCd7hXCdBwSQtbLvHNa2HFWXjlBBKht3WmEzWsXONsmMAAAh7bGeQpOLbuQfDOzJLgnXO00vIIJHKiE28n3ssz8SqdrEAi9Lb+QJaoYbINsjECIwp4bGfwp+DYugfBOzNLgnfO0UrLIyB4h3uVAA2XtLDlEt+8FlachVdOIBF6W2c6UcPKNc6GCQwg4LGdQZ6CY+seBO/MLAneOUcrLY9AIic68XbivTwTr9LJCiRCb+sPZIkaJtsgGyMwooDHdgZ/Co6texC8M7MkeOccrbQ8AoJ3uFcJ0HBJC1su8c1rYcVZeOUEEqG3daYTNaxc42yYwAACHtsZ5Ck4tu5B8M7MkuCdc7TS8ggkcqITbyfeyzPxKp2sQCL0tv5Alqhhsg2yMQIjCnhsZ/Cn4Ni6B8E7M0uCd87RSssjIHiHe5UADZe0sOUS37wWVpyFV04gEXpbZzpRw8o1zoYJDCDgsZ1BnoJj6x4E78wsCd45Rystj0AiJzrxduK9PBOv0skKJEJv6w9kiRom2yAbIzCigMd2Bn8Kjq17ELwzsyR45xyttDwCgne4VwnQcEkLWy7xzWthxVl45QQSobd1phM1rFzjbJjAAAIe2xnkKTi27kHwzsyS4J1ztNLyCCRyohNvJ97LM/EqnaxAIvS2/kCWqGGyDbIxAiMKeGxn8Kfg2LoHwTszS4J3ztFKyyMgeId7lQANl7Sw5RLfvBZWnIVXTiDZwFKSAAAgAElEQVQReltnOlHDyjXOhgkMIOCxnUGegmPrHgTvzCwJ3jlHKy2PQCInOvF24r08E6/SyQokQm/rD2SJGibbIBsjMKKAx3YGfwqOrXsQvDOzJHjnHK20PAKCd7hXCdBwSQtbLvHNa2HFWXjlBBKht3WmEzWsXONsmMAAAh7bGeQpOLbuQfDOzJLgnXO00vIIJHKiE28n3ssz8SqdrEAi9Lb+QJaoYbINsjECIwp4bGfwp+DYugfBOzNLgnfO0UrLIyB4h3uVAA2XtLDlEt+8FlachVdOIBF6W2c6UcPKNc6GCQwg4LGdQZ6CY+seBO/MLAneOUcrLY9AIidO4sT7bW97W3n9619fPvOZz5Qf/vCH5aY3vWl5zGMeUx760IeWbbbZZu6OJkDnvtjId0x88xp5Cy4/IYFE6G2d6UQNE2qJrRDoRsBjO9OKKTi27kHwzsyS4J1ztNLyCCRy4iSC97777lt23XXXct/73rfssMMO5YMf/GB57nOfW57+9KeXZzzjGXN3NAE698VGvmPim9fIW3D5CQkkQm/rTCdqmFBLbIVANwIe25lWTMGxdQ+Cd2aWBO+co5WWRyCREycRvL/3ve+V6173uhfr3CGHHFLe8pa3zE7At91227m6mgCd60Id3CnxzauDbShhIgKJ0Ns604kaJtIO2yDQlYDHdqYdU3Bs3YPgnZklwTvnaKXlEUjkxEkE74217GUve1l51KMeVc4777xytatdba6uJkDnulAHd0p88+pgG0qYiEAi9LbOdKKGibTDNgh0JeCxnWnHFBxb9yB4Z2ZJ8M45Wml5BBI5cbLB+4EPfGD5yEc+UirSvLcE6LzXGvt+iW9eY+/B9acjkAi9rTOdqGE6HbETAv0IeGxnejEFx9Y9CN6ZWRK8c45WWh6BRE6cZPA+4YQTyv7771+e//znl8MOO2yTHa2n4fWftdvZZ59d9t5773LWWWeVnXfeeXkm4TJUmvjmdRku60sIbFQgEXpbZzpRg/YSIJAX8NjOmE7BsXUPgndmlgTvnKOVlkdA8N5IryrKPvvsU25+85uXD3zgA5t9f/cRRxxRjjzyyEutIngvz4NApQR6EhDe/7sbrT8c9+DYuofEXPbgkNhH6xo99KJ1D4mvb52HHhx72MMUakjMU+saiXlq7UXrHnw9ga0RELwvoXXuueeWO9zhDrM/Ifaxj32sXOMa19ispxPvrRk39yVAYEsCfogQvLc0I1vz381TZp62xrzn+7bOQyIotfr0sIcp1NDah8TXJ+aptReJfViDwLwCgvc6qZ/97Gflbne7WznzzDPLJz/5yfJrv/Zr8zpuuF8CdKsvOtIXJJ4wRyrdZQl0K+CHiExQ6sGxh+fIHhx6eLD10IseHFrnoQfHHvYwhRp6mMfEPLX2ogcHNayOQCInTuI93r/85S/L/e53v/KJT3xidtJ9i1vc4jJNQQL0Ml14hC9KPGGOULZLEuhawA8RgndyQM1TZp6SPRlzrdZ56OH7fg97mEINY87h2rUT89Taix4c1LA6AomcOIngXf9m9yte8YrZh6ntt99+F5uA29zmNuWKV7ziXFORAJ3rQh3cKfGE2cE2lECgKwE/RGSCUg+OPTxH9uDQwwOsh1704NA6Dz049rCHKdTQwzwm5qm1Fz04qGF1BBI5cRLBe9dddy1nnHHGRjv/zW9+s9T/Ps8tATrPdXq4T+IJs4d9qIFATwJ+iBC8k/NonjLzlOzJmGu1zkMP3/d72MMUahhzDteunZin1l704KCG1RFI5MRJBO9UyxOgqVoWvU7iCXPRNVqfwLIJ+CEiE5R6cOzhObIHhx4egz30ogeH1nnowbGHPUyhhh7mMTFPrb3owUENqyOQyImC97p5SYAuy/glnjCXZa/qJDCUgB8iBO/krJmnzDwlezLmWq3z0MP3/R72MIUaxpxDJ9496KthDIFEThS8Be8xZtc1CUxSoPUHuqmgtP6A34Nj6x4SvezBIbGP1jV66EXrHhJf3zoPPTj2sIcp1JCYp9Y1EvPU2ovWPfh6AlsjIHhvjdYc902AznGZLu6SeMLsYiOKINCRgB8i/rsZrc8vPTi27iExlj04JPbRukYPvWjdQ+LrW+ehB8ce9jCFGhLz1LpGYp5ae9G6B19PYGsEEjnRifc68QTo1jRwzPsmnjDHrN+1CfQo4IcIwTs5l+YpM0/Jnoy5Vus89PB9v4c9TKGGMedw7dqJeWrtRQ8OalgdgUROFLwF79V5xNgpgQUL+CEiE5R6cEz8UNk6bj04tO4h8fU99CKxj9Y1WuehB8ce9jCFGlpnKfH1iXlq7UViH9YgMK+A4D2v1Jz3S4DOeanR75Z4whx9Ewog0JmAHyIE7+RImqfMPCV7MuZarfPQw/f9HvYwhRrGnMO1ayfmqbUXPTioYXUEEjnRife6eUmALsv4JZ4wl2Wv6iQwlIAfIjJBqQfHHp4je3AY6rGzuev00IseHFrnoQfHHvYwhRp6mMfEPLX2ogcHNayOQCInCt6C9+o8YuyUwIIF/BAheCdHzDxl5inZkzHXap2HRFBq3X8Pe5hCDa19SHx9Yp5ae5HYhzUIzCsgeM8rNef9EqBzXmr0uyWeMEffhAIIdCbgh4hMUOrBsYfnyB4ceniI9dCLHhxa56EHxx72MIUaepjHxDy19qIHBzWsjkAiJzrxduK9Oo8YOyWwYAE/RAjeyREzT5l5SvZkzLVa5yERlFr338MeplBDax8SX5+Yp9ZeJPZhDQLzCgje80rNeb8E6JyXGv1uiSfM0TehAAKdCfghIhOUenDs4TmyB4ceHmI99KIHh9Z56MGxhz1MoYYe5jExT6296MFBDasjkMiJTrydeK/OI8ZOCSxYwA8RgndyxMxTZp6SPRlzrdZ5SASl1v33sIcp1NDah8TXJ+aptReJfViDwLwCgve8UnPeLwE656VGv1viCXP0TSiAQGcCfojIBKUeHHt4juzBoYeHWA+96MGhdR56cOxhD1OooYd5TMxTay96cFDD6ggkcqITbyfeq/OIsVMCCxbwQ4TgnRwx85SZp2RPxlyrdR4SQal1/z3sYQo1tPYh8fWJeWrtRWIf1iAwr4DgPa/UnPdLgM55qdHvlnjCHH0TCiDQmYAfIjJBqQfHHp4je3Do4SHWQy96cGidhx4ce9jDFGroYR4T89Taix4c1LA6Aomc6MTbiffqPGLslMCCBfwQIXgnR8w8ZeYp2ZMx12qdh0RQat1/D3uYQg2tfUh8fWKeWnuR2Ic1CMwrIHjPKzXn/RKgc15q9LslnjBH34QCCHQm4IeITFDqwbGH58geHHp4iPXQix4cWuehB8ce9jCFGnqYx8Q8tfaiBwc1rI5AIic68XbivTqPGDslsGABP0QI3skRM0+ZeUr2ZMy1WuchEZRa99/DHqZQQ2sfEl+fmKfWXiT2YQ0C8woI3vNKzXm/BOiclxr9boknzNE3oQACnQn4ISITlHpw7OE5sgeHHh5iPfSiB4fWeejBsYc9TKGGHuYxMU+tvejBQQ2rI5DIiU68nXivziPGTgksWMAPEYJ3csTMU2aekj0Zc63WeUgEpdb997CHKdTQ2ofE1yfmqbUXiX1Yg8C8AoL3vFJz3i8BOuelRr9b4glz9E0ogEBnAn6IyASlHhx7eI7swaGHh1gPvejBoXUeenDsYQ9TqKGHeUzMU2svenBQw+oIJHKiE28n3qvziLFTAgsW8EOE4J0cMfOUmadkT8Zcq3UeEkGpdf897GEKNbT2IfH1iXlq7UViH9YgMK+A4D2v1Jz3S4DOeanR75Z4whx9Ewog0JmAHyIyQakHxx6eI3tw6OEh1kMvenBonYceHHvYwxRq6GEeE/PU2oseHNSwOgKJnOjE24n36jxi7JTAggX8ECF4J0fMPGXmKdmTMddqnYdEUGrdfw97mEINrX1IfH1inlp7kdiHNQjMKyB4zys15/0SoHNeavS7JZ4wR9+EAgh0JuCHiExQ6sGxh+fIHhx6eIj10IseHFrnoQfHHvYwhRp6mMfEPLX2ogcHNayOQCInOvF24r06jxg7JbBgAT9ECN7JETNPmXlK9mTMtVrnIRGUWvffwx6mUENrHxJfn5in1l4k9mENAvMKCN7zSs15vwTonJca/W6JJ8zRN6EAAp0J+CEiE5R6cOzhObIHhx4eYj30ogeH1nnowbGHPUyhhh7mMTFPrb3owUENqyOQyIlOvJ14r84jxk4JLFjADxGCd3LEzFNmnpI9GXOt1nlIBKXW/fewhynU0NqHxNcn5qm1F4l9WIPAvAKC97xSc94vATrnpUa/W+IJc/RNKIBAZwJ+iMgEpR4ce3iO7MGhh4dYD73owaF1Hnpw7GEPU6ihh3lMzFNrL3pwUMPqCCRyohNvJ96r84ixUwILFvBDhOCdHDHzlJmnZE/GXKt1HhJBqXX/PexhCjW09iHx9Yl5au1FYh/WIDCvgOA9r9Sc90uAznmp0e+WeMIcfRMKINCZgB8iMkGpB8ceniN7cOjhIdZDL3pwaJ2HHhx72MMUauhhHhPz1NqLHhzUsDoCiZzoxNuJ9+o8YuyUwIIF/BAheCdHzDxl5inZkzHXap2HRFBq3X8Pe5hCDa19SHx9Yp5ae5HYhzUIzCsgeM8rNef9EqBzXmr0uyWeMEffhAIIdCbgh4hMUOrBsYfnyB4ceniI9dCLHhxa56EHxx72MIUaepjHxDy19qIHBzWsjkAiJzrxduK9Oo8YOyWwYAE/RAjeyREzT5l5SvZkzLVa5yERlFr338MeplBDax8SX5+Yp9ZeJPZhDQLzCgje80rNeb8E6JyXGv1uiSfM0TehAAKdCfghIhOUenDs4TmyB4ceHmI99KIHh9Z56MGxhz1MoYYe5jExT6296MFBDasjkMiJTrydeK/OI8ZOCSxYwA8RgndyxMxTZp6SPRlzrdZ5SASl1v33sIcp1NDah8TXJ+aptReJfViDwLwCgve8UnPeLwE656VGv1viCXP0TSiAQGcCfojIBKUeHHt4juzBoYeHWA+96MGhdR56cOxhD1OooYd5TMxTay96cFDD6ggkcqIT7yU88U482a3Ow8ROCQwn0MMPEVN4fuD43zPb6jCFWRju0etKqyLgceX5JTnrrfOUrGXMtVq/3yyDo+AdnrAEaLikjS7XOtxD1OgaBFZRoIdvHFN4fuDoB+NVfP6w52EEWp9fpvAc6xd7uVlrnadcJeOu1Pq4WAbHRE504u3Ee9xHqqsTmJBAD984Wr/59dAOjoJ3D3OohmkKtD6/TOE5VvDOzXbrPOUqGXel1sfFMjgK3uEZS4CGS3LiPQSoaxAICfTwjaP1m1+IomkZjoJ30wD5YgKbEWh9fpnCc6zgnXuItM5TrpJxV2p9XCyDYyInOvF24j3uI9XVCUxIoIdvHK3f/HpoB0fBu4c5VMM0BVqfX6bwHCt452a7dZ5ylYy7UuvjYhkcBe/wjCVAwyU58R4C1DUIhAR6+MbR+s0vRNG0DEfBu2mAfDEBJ95bnIHW59kpfK/ZItIcd2h1nOMSS3GX1nlYBsdETnTivW6cE6BDPDpah3uIGl2DwCoK9PCNYwrPDxwF71V8/rDnYQRan1+m8BxbpTlk5q3VMVPF+Ku0Pi6WwTGREwVvwXv8R6sKCExEoIdvHK3f/HpoBUfBu4c5VMM0BVqfX/6/9s4EXKui/uM/FQgXkiUxIBU0EQPMMlyoUKOyRDOz0mKRwFJRTLEUIRUEEVzAFDMR155MezKw3DJxKSNCyz1AxQUkF1QWN3L9P9/pee//vfe+l/ved+aeM+ecz3keH/W+58z85jPfmTnfM3Pm5KGPxXiH07avnsJFkm5Kvu0iCxwx3oE1FgJo4JAqJucr7iRiJA8IFJFADANHHvoHOGK8i9h/UOZkCPj2L3noYzHe4bTmq6dwkaSbkm+7yALHED6RGW9mvNNtqeQOgRwRiGHg8B38YqgOOGK8Y9AhMeSTgG//koc+FuMdTtu+egoXSbop+baLLHDEeAfWWAiggUNixjsJoOQBgUAEYhg4fAe/QCi8koEjxttLQFwMgY0Q8O1f8tDHYrzDNRFfPYWLJN2UfNtFFjiG8InMeDPjnW5LJXcI5IhADAOH7+AXQ3XAEeMdgw6JIZ8EfPuXPPSxGO9w2vbVU7hI0k3Jt11kgSPGO7DGQgANHBIz3kkAJQ8IBCIQw8DhO/gFQuGVDBwx3l4C4mIIMOPdrAZ8+9k8jDXNQqriBF+OVWSRiVN89ZAFjiF8IjPeZXIOATSJ1uEr7iRiJA8IFJFADANHHvoHOGK8i9h/UOZkCPj2L3noY0UaDmH05ssxTBTpp+LbLrLAMYRPxHhjvNNvrUQAgZwQiGHg8B38YqgKOGK8Y9AhMeSTgG//koc+FuMdTtu+egoXSbop+baLLHDEeAfWWAiggUOqmJyvuJOIkTwgUEQCMQwceegf4IjxLmL/QZmTIeDbv+Shj8V4h9Oar57CRZJuSr7tIgscQ/hEZryZ8U63pZI7BHJEIIaBw3fwi6E64IjxjkGHxJBPAr79Sx76WIx3OG376ilcJOmm5NsussAR4x1YYyGABg6JGe8kgJIHBAIRiGHg8B38AqHwSgaOGG8vAXExBDZCwLd/yUMfi/EO10R89RQuknRT8m0XWeAYwicy482Md7otldwhkCMCMQwcvoNfDNUBR4x3DDokhnwS8O1f8tDHYrzDadtXT+EiSTcl33aRBY4Y78AaCwE0cEjMeCcBlDwgEIhADAOH7+AXCIVXMnDEeHsJiIshwIx3sxrw7WfzMNY0C6mKE3w5VpFFJk7x1UMWOIbwicx4l8k5BNAkWoevuJOIkTwgUEQCMQwceegf4IjxLmL/QZmTIeDbv+ShjxVpOITRmy/HMFGkn4pvu8gCxxA+EeON8U6/tRIBBHJCIIaBw3fwi6Eq4IjxjkGHxJBPAr79Sx76WIx3OG376ilcJOmm5NsussAR4x1YYyGABg6pYnK+4k4iRvKAQBEJxDBw5KF/gCPGu4j9B2VOhoBv/5KHPhbjHU5rvnoKF0m6Kfm2iyxwDOETmfFmxjvdlkruEMgRgRgGDt/BL4bqgCPGOwYdEkM+Cfj2L3noYzHe4bTtq6dwkaSbkm+7yAJHjHdgjYUAGjgkZryTAEoeEAhEIIaBw3fwC4TCKxk4Yry9BMTFENgIAd/+JQ99LMY7XBPx1VO4SNJNybddZIFjCJ/IjDcz3um2VHKHQI4IxDBw+A5+MVQHHDHeMeiQGPJJwLd/yUMfi/EOp21fPYWLJN2UfNtFFjhivANrLATQwCEx450EUPKAQCACMQwcvoNfIBReycAR4+0lIC6GADPezWrAt5/Nw1jTLKQqTvDlWEUWmTjFVw9Z4BjCJzLjXSbnEECTaB2+4k4iRvKAQBEJxDBw5KF/gCPGu4j9B2VOhoBv/5KHPlak4RBGb74cw0SRfiq+7SILHEP4RIw3xjv91koEEMgJgRgGDt/BL4aqgCPGOwYdEkM+Cfj2L3noYzHe4bTtq6dwkaSbkm+7yAJHjHdgjYUAGjikisn5ijuJGMkDAkUkEMPAkYf+AY4Y7yL2H5Q5GQK+/Use+liMdzit+eopXCTppuTbLrLAMYRPZMabGe90Wyq5QyBHBGIYOHwHvxiqA44Y7xh0SAz5JODbv+Shj8V4h9O2r57CRZJuSr7tIgscMd6BNRYCaOCQmPFOAih5QCAQgRgGDt/BLxAKr2TgiPH2EhAXQ2AjBHz7lzz0sRjvcE3EV0/hIkk3Jd92kQWOIXwiM97MeKfbUskdAjkiEMPA4Tv4xVAdcMR4x6BDYsgnAd/+JQ99LMY7nLZ99RQuknRT8m0XWeCI8Q6ssRBAA4fEjHcSQMkDAoEIxDBw+A5+gVB4JQNHjLeXgLgYAsx4N6sB3342D2NNs5CqOMGXYxVZZOIUXz1kgWMIn8iMd5mcQwBNonX4ijuJGMkDAkUkEMPAkYf+AY4Y7yL2H5Q5GQK+/Use+liRhkMYvflyDBNF+qn4tosscAzhEzHeGO/0WysRQCAnBGIYOHwHvxiqAo4Y7xh0SAz5JODbv+Shj8V4h9O2r57CRZJuSr7tIgscMd6BNRYCaOCQKibnK+4kYiQPCBSRQAwDRx76BzhivIvYf1DmZAj49i956GMx3uG05quncJGkm5Jvu8gCxxA+kRlvZrzTbankDoEcEYhh4PAd/GKoDjhivGPQITHkk4Bv/5KHPhbjHU7bvnoKF0m6Kfm2iyxwxHiXaWzp0qU2duxYW7hwoXXo0MFGjBhhU6dOtXbt2lWtxBBAq87M40RfcXtkzaUQgMBGCMQwcOShf4AjxpuOBgKtRcC3f8lDH4vxDqcuXz2FiyTdlHzbRRY4hvCJuZjxXrNmjfXt29d23nlnmzBhgq1atcrGjRtnw4YNs9mzZ1etxBBAq87M40RfcXtkzaUQgADGu9U1EMMAHEM/68shhjK0uljIAAItJEC74sFeCyWz0dN99RQyljTT8h1vssAxhE/MhfE+55xz7Oyzz7YVK1ZY586dne7mzJljY8aMcX/r3r17VVoMAbSqjDxP8hW3Z/ZcDgEINEEghoEjD/0DHLkxppOBQGsR8O1f8tDHii0cwijMl2OYKNJPxbddZIFjCJ+YC+M9aNAgZ7jnz59fp7y1a9e6v1155ZU2cuTIqhQZAmhVGXme5Ctuz+y5HAIQwHi3qgZiGIBj6Gd9OcRQhlYVColDoAYCtCse7NUgmyYv8dVTyFjSTMt3vMkCxxA+MRfGu2vXrjZq1CibPn16Pc316NHDhg8f3ujvTQkzBNAkRO8r7iRiJA8IFJFADANHHvoHOHJjXMT+gzInQ8C3f8lDHyvScAijN1+OYaJIPxXfdpEFjiF8Yi6Md9u2bW3KlCk2fvz4esrr16+fDRw40C07r3SsX7/e9E/pWLlypTt/8eLF1q1bt/RV3EQEe09bEG1sBAaBIhNYNGFw6sXPQ/8Ax//JyJdDHrSQeoMigNwRoF3Rv4QUta+eQsaSZlq+400WOL7wwgu255572jPPPGM9e/asCXehjfekSZNs8uTJNYHjIghAAAIQgAAEIAABCEAAAhAoDgFN0A4YMKCmAufCeGup+ejRo02brJUfzS01bzjjvWHDBtOsd69evaxNmzY1AeWiMARKT5ViX30QprSkkhQBdJUU6WLlg66KVd9JlRZdJUW6WPmgq2LVd1KlLYKu3nvvPVu9erX179/f2rdvXxPaXBhvba7WpUsXmzdvXh2EdevWWadOnVq0uVpNBLmoVQiEeI+iVQIj0UwTQFeZrr5og0dX0VZNpgNDV5muvmiDR1fRVk2mA0NX1VVfLoy3ZrqnTZvmZqs7duzoSj537lw75phjWvQ5seqQcVYSBGjASVAuXh7oqnh1nkSJ0VUSlIuXB7oqXp0nUWJ0lQTl4uWBrqqr81wY7zVr1ljfvn2td+/eNmHCBFu1apWNGzfOhg4darNnz66OBGdFRYAGHFV15CYYdJWbqoyqIOgqqurITTDoKjdVGVVB0FVU1ZGbYNBVdVWZC+Otoi5ZssTGjh1rCxcutA4dOtiIESPs7LPPtnbt2lVHgrOiIqD372fOnOkeoHz0ox+NKjaCyS4BdJXduos5cnQVc+1kNzZ0ld26izlydBVz7WQ3NnRVXd3lxnhXV1zOggAEIAABCEAAAhCAAAQgAAEIJEsA450sb3KDAAQgAAEIQAACEIAABCAAgYIRwHgXrMIpLgQgAAEIQAACEIAABCAAAQgkSwDjnSxvcoMABCAAAQhAAAIQgAAEIACBghHAeBeswikuBCAAAQhAAAIQgAAEIAABCCRLAOOdLG9yM7OlS5c22oF+6tSpG92B/oUXXrBZs2bZHXfcYcuXL7ett97aBg0aZPqG+w477ABXCNSkq4bYLrzwQjvppJNsyJAhdvPNN0MVAl660qct9YnLW2+91d544w3r2bOn/exnP3OfuuQoNoFaxkERe/XVV23ixIlOU/rvXr162fHHH2/HHHNMsYFSekfgqaeesvPPP98WLVpkjz32mPXp08f9u7njww8/tBkzZtgvfvELW716te2+++7unmvvvfdu7lJ+LwCBWnTFfXtlYWC8C9BgYipi6ZvrO++8c71vrg8bNmyj31yXCTrxxBNt1KhRbiB45ZVXbMqUKfbyyy+7QWWbbbaJqZjEkjCBWnVVHuaLL75ou+66q3sANGDAAIx3wnUYY3Y+utJNx1577WW77LKLjRkzxn0W8fHHH7etttrK9WMcxSXgo6svfelL7mHQtGnTbPvtt3cG/IILLrA5c+bYD3/4w+JCpeSOwE033eQexKjveeKJJ+yDDz6oynhPnz7dzjzzTNO/d9ttN7vkkkvszjvvtIceesh23HFH6BacQC264r4d413wZhNH8TVDre+rr1ixwjp37uyC0g2Dbkz1t+7du1cMdO3ate6GtU2bNnW/P//88+7G47zzzrOTTz45jgISRSoEatVVebAjRoywTTbZxJ577jmnNWa8U6nKqDL10dXw4cPt6aeftr/85S+22WabRVUugkmXQK260sPBbt262VVXXWUjR46sK8S+++7rxsYFCxakWzByT52AjPamm27q4pBGHnjggWaN94YNG2zbbbe14447zj3Q0fHOO+9Y79697cADD3Sz4BzFJlCLrrhvx3gXu9VEUnotD5fhnj9/fl1Eapz625VXXlnvZqKakDVYaLZcT/w5ikvAV1f33Xefu8FYtmyZfe9738N4F1dK9Upeq67Wr1/vVuGoT2NZOWJqSKBWXa1cudI9bP79739vhx56aF2y3/jGN9yrDHfddRewIVBHoFrjLd0MHjzYHnzwQbfEvHSMGzfOae3ZZ5+FKgRarKumkBX9vp2l5jSmRAl07drVLbPUcqbyo0ePHqYZooZ/31hwWkalZZyXX365Hand5VIAABEzSURBVHXUUYmWg8ziIuCjq/fff9/22GMPZ7hPPfVU22+//TDecVVvatHUqqt77rnH9t9/f7vhhhvcks2FCxdaly5d7MgjjzTtZ9G2bdvUykTG6ROoVVeK/IADDrDXXnvNrrnmGttuu+3stttuM63W+fWvf22HHXZY+oUjgmgIVGu8NaOt2e63337b2rdvXxe/7q2OPvpoe/PNN23zzTePplwEki6BanVVKUru280w3unqt3C564ZT72aPHz++Xtn79etnAwcOdMvOqzm0EcjXv/51e/TRR917TFtuuWU1l3FOTgn46Oriiy+2iy66yL1/q/e7Md45FUkNxapVV9dff717kNOhQwf33u1BBx1kixcvtjPOOMM0i6SlxhzFJVCrrkRMJujwww+3W265xQHUawzqw4499tjiAqXkFQlUa5D0+p/uy7TkvPz43e9+Z9/5zndMm0Q29Rog6ItHoFpdNSTDffv/iGC8i9dmUi2xzw1HeeDaBETvIt1+++1uiRRHsQnUqittzqdVE9dee60dfPDBDiLGu9haKi99rbq67rrr3BJzLQfWUs3SoR3NteOwNtdiBqm4OqtVV7pxlel++OGHbdKkSe597z//+c9OU5oBP+KII4oLlZI3IlCtQcJ4I56WEKhWVw3T5L4d490SnXFuIAJaYjd69OhGMz4tWWqu5U8/+tGP7IorrmB34ED1kvVkatWVPsGzZMkStxNs6dDspDZX06xlww39ss6J+FtGoFZdafmv9gzQTKR2GC4dd999t2lX6kceecT69+/fsmA4OzcEatWVNnzUA8KG+tGqCu1urplJDgiUCFRrkFhqjmZaQqBaXZWnyX37/9NgxrslauNcbwLaVEbvOs6bN68urXXr1lmnTp2q2lxN12npk56cnX766d7xkEA+CNSqK81u33vvvU1CkIH62te+lg9IlKLFBGrVlXbG1ze7mzLeWnauT9ZxFJNArbo699xz3Wc43333XfcFhtJRMk5ahr7FFlsUEyqlbkSgWoNU2lxNnw779Kc/XZeOvhZz4403srka2qpHoFpdlS7ivr2+gDDeNKhECejdRi0R1+6sHTt2dHnPnTvXNPO4sc+J6TxtWCQT9IMf/MAuvfTSROMms7gJ1Kor3WhoV/3yQ9+L1zJgpanvmZY+exc3AaJrDQK16kqxSDv6/m35Fxxkmi688EJbvXo1+1K0RoVlJM1adaXN+rScvKFB0ioyzYa/9NJLGSFAmEkQqNYglT4nNnbsWLf5ow493NHnxLSXDp8TS6K2spNHtbrivr1ynWK8s6P1XESqdxv79u3rOnTdhGppnDYb0vuQs2fPriuj3tvWrNFTTz3l/qblwPvss4/bxfWyyy6r+06lftNne3baaadc8KEQtRGoVVeVcuMd79rqII9X+ejqj3/8ox1yyCF2wgkn2JAhQ+z+++937+WecsopdTe3eWRGmZonUKuuXn/9ddNGpNoEUqu+9I73HXfc4d7xnjx5smkPAY5iE3jrrbfcawc69EWF5cuX28yZM93/63vvul9qeH+l3/RFGfVPM2bMcK/ByGxLW3rIoweIHMUmUIuuuG/HeBe71URUejVGPVnVJ3a0668+haLNPXQzUTpkfvTtyNL3I6+++mo3013p0Cd69DtHsQnUoiuMd7E1U03pfXSlGUrtFvzkk086k6RP8+iLDuXLhKuJgXPyR6BWXelh9MSJE+2+++5zq3V69erlds7XXgLa4Zyj2AR0zyRNVDq0x4TurRreX+lcbdwn8y3DrRU5+p73rFmz3IQHBwRq0RX37RhvWg4EIAABCEAAAhCAAAQgAAEIQCBxAiw1Txw5GUIAAhCAAAQgAAEIQAACEIBAkQhgvItU25QVAhCAAAQgAAEIQAACEIAABBIngPFOHDkZQgACEIAABCAAAQhAAAIQgECRCGC8i1TblBUCEIAABCAAAQhAAAIQgAAEEieA8U4cORlCAAIQgAAEIAABCEAAAhCAQJEIYLyLVNuUFQIQgAAEIAABCEAAAhCAAAQSJ4DxThw5GUIAAhCAAAQgAAEIQAACEIBAkQhgvItU25QVAhCAAAQgAAEIQAACEIAABBIngPFOHDkZQgACEIBAjAQ22WSTZsO66qqrbOTIkc2eV+mE/fbbz7baaiu7+eabW3R9z5497aCDDrLZs2e36LpaT77nnnts//33d5cvWbLE+vTpUy+piRMn2rRp02yHHXawZ599tlE2s2bNsnHjxtmoUaPsiiuuaPS7ONx7770Vw/v73/9ue++9d8XfSnHdf//99rnPfa7W4nEdBCAAAQhAIBUCGO9UsJMpBCAAAQjERmDRokX1Qtpnn31s7Nix9v3vf7/u7zvttJNts802NYX+73//2zbbbDPbZZddWnT9gw8+aJ06dTIZ8CSOksHVQ4KTTz7ZJk2aVC9bMXj55ZetS5cuFY23TPE///lP69ixo7344ov2kY98pN71Mt7vvfeenX/++Y2K069fP/dwotKB8U6i9skDAhCAAARaiwDGu7XIki4EIAABCGSagGbAzzvvPPvJT37SZDnefvtt23zzzTNdzobBlwzu0KFDTbPLy5YtqzvlH//4h33+85+37373u7Zw4cJGxvuJJ55wDxa+/OUv25133mk33nijfetb32pkvGuZ+cd450pmFAYCEIBA4QhgvAtX5RQYAhCAAASqIdDQeGvmV7O0d911l/34xz82zURPnTrVGfPx48fbLbfcYs8884xtvfXWNmjQIJs5c6Z169atLquGS81L6Wl59bHHHmv/+te/bMcdd7QLLrjADjjggLrrGi4111L3Bx54wC09P+mkk0xmt2/fvnbppZfaHnvsUXfdunXr7LjjjrObbrrJPRw46qij3Cy14v3www+bRFAyuLru0EMPdeb7s5/9rDtf5V66dKntuuuuNn/+/EbGW2U666yzbPny5aYVAzLpMt/lR61L7qsx3q+99por3x/+8Ad788037TOf+YxNnz7d1Ufp+Nvf/mannXaaPfzww/bBBx+4lQS65sgjj3SnNPd7NdrhHAhAAAIQgEBDAhhvNAEBCEAAAhCoQKCS8da7zdtvv70zvJ/61Keckd1tt93c+8xf+cpXrHv37rZ69Wpnnl999VXT8vI2bdq41CsZ73POOcfNEJ9wwgm23Xbb2YwZM2zx4sX23HPPubR1VDLeek9cecnwy+jLSK5du9YZ3rZt27rrNNOshwTKQ+9jX3755W4J+MqVK6sy3jLcp5xyijPzmvmXSe3Ro4dL76GHHqpovHv37u0eNugdbpVpzpw59tJLL7kYS4c4bLnllu6BQPkh3lqK39TRnPF+//33beDAgfb00087s73tttvaRRdd5GLR7LzKsX79eld/X/jCF2zMmDFuGbzqSGXTQ4XmfqehQAACEIAABGolgPGulRzXQQACEIBArglUMt6TJ0+266+/3g4//PAmyy4DqHebP/GJT9if/vQn++pXv9qk8VZ6mik/8MAD3TnarKxXr172q1/9yoYNG9ak8b722mvt0UcfdTPdOkqm9K9//aszlTKT+k3nDR8+3J0jc6mN0p588smqjbdm9adMmeIeBMjEa5M3GekzzjijkfGWUd9zzz3tl7/8pR199NGmd+Y1660N1vRgotx4V9pcTaZb737Xarw1y33IIYfY7bffXrdi4N1337VPfvKTbjM2zbxrpcCAAQPskUcesf79+zfKqrnfcy14CgcBCEAAAq1KAOPdqnhJHAIQgAAEskqgKeP9+uuvN9oA7LbbbnMG9fHHH3ezpqXj4osvtuOPP75J461r9J54u3bt6q7ZYostnLHVbLaOSjPeen/6+eefr7tGm51phvc3v/mNHXHEEXbNNde43dc1C14+26zN0rQEvpql5jLSWvr+8Y9/3Jnuq6++2tasWeMM7IknntjIeGsVwCWXXOIeOnTu3NnFpo3YFP+CBQvqGW89nNDu5+WHeJcvlW+om+ZmvH/605+6GXYtsS8/FNd1113nHhgofsUj060Zee3eXr5ZXnO/Z1XLxA0BCEAAAukTwHinXwdEAAEIQAACERKoZLy15FrvDpcfMqha4qzZ1hEjRljXrl1N1+qzWOWbszX1jvcbb7xRLz3tBi5jW9pNvKl3vB977LG662SwtfN56XNnWmot8/7OO+/US1tL2WXoqzXemik++OCDnamX4Z47d64ddthhjYx3aRm6DO1vf/vbujz1vvfPf/5zt7xdS+N1tNY73nqHXTPpmtEvP8Ti9NNPN81+69BS/jPPPNM9TNAM+xe/+EXTA5LSDHhzv0coVUKCAAQgAIEMEMB4Z6CSCBECEIAABJIn0NTmag2N8oQJE9xMq2adN910UxeolmbLMKdlvEPNeMt4a7ZYy9W1E7lmjdu3b9/IeGsGXu+4N3XonXd927s1jbfeR7/ssss2OuNdHp9WGtx9991uY7X//ve/7v34lvyevCLJEQIQgAAEskwA453l2iN2CEAAAhBoNQLVGm8tZdZ73//5z3/cTLcObcI2ceLE1Iy3lrzrm9gy4JqF11HLO94y3prhl/Hea6+97NRTT3VpNVxqrne4NdOtDdMabpCmc/U3bezWmsa79I53+Xv1mtHWO95awt5wd/WScDTbrY3V3nrrLfdQoeHR3O+tJkAShgAEIACBXBHAeOeqOikMBCAAAQiEIlCt8b711lttyJAh7tNd+vyWPg+mzdH0ma+0ZrzFoLSruZZaa1dzzcpr87BVq1Y5E97U0dy71A2N94YNG9x74FpqL6Pf8NDO4qXPkGkHdy01lyHWp9kaHjLJH/vYxyqGVopLy+X17nn5oQ3pdt99d7fkX590K+1qLtOsWe3SrubayE6bvametLu53kfXMnQtpdfGdM39HkpbpAMBCEAAAsUjgPEuXp1TYghAAAIQqIJAtcZbSZ177rnuPWF9R1rfrtYmY/q0VprGW+99a2M3fW9bM7n6TrU2btP3v7WJWCjjrZnkb3/726bl5oMHD26U7CuvvFL36TO98y3jXWlXc11Yvpt7w4RKxrtS3KNHj3bvn+sTbuXf8db3x/X5s3333dddtmzZMrcSQe9x69UAfbJNu87rHD08aO73KmTDKRCAAAQgAIGKBDDeCAMCEIAABCBQEAKDBg1yy741C8wBAQhAAAIQgEByBDDeybEmJwhAAAIQgEBiBDQTvWLFCrdbt95f1iZpN9xwg82bN8+++c1vJhYHGUEAAhCAAAQgYIbxRgUQgAAEIACBHBLQJmOnnXaa+7yWPivWp08f087fQ4cOzWFpKRIEIAABCEAgbgIY77jrh+ggAAEIQAACEIAABCAAAQhAIOMEMN4Zr0DChwAEIAABCEAAAhCAAAQgAIG4CWC8464fooMABCAAAQhAAAIQgAAEIACBjBPAeGe8AgkfAhCAAAQgAAEIQAACEIAABOImgPGOu36IDgIQgAAEIAABCEAAAhCAAAQyTgDjnfEKJHwIQAACEIAABCAAAQhAAAIQiJsAxjvu+iE6CEAAAhCAAAQgAAEIQAACEMg4AYx3xiuQ8CEAAQhAAAIQgAAEIAABCEAgbgIY77jrh+ggAAEIQAACEIAABCAAAQhAIOMEMN4Zr0DChwAEIAABCEAAAhCAAAQgAIG4CWC8464fooMABCAAAQhAAAIQgAAEIACBjBPAeGe8AgkfAhCAAAQgAAEIQAACEIAABOImgPGOu36IDgIQgAAEIAABCEAAAhCAAAQyTgDjnfEKJHwIQAACEIAABCAAAQhAAAIQiJsAxjvu+iE6CEAAAhCAAAQgAAEIQAACEMg4AYx3xiuQ8CEAAQhAAAIQgAAEIAABCEAgbgIY77jrh+ggAAEIQAACEIAABCAAAQhAIOME/g9QnaHXFE/PVQAAAABJRU5ErkJggg==\" width=\"899.9999804930258\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_mae_loss_hist(X, model):\n",
    "    fig, ax = plt.subplots(figsize=(9,6))\n",
    "    \n",
    "    Xpred = model.predict(X)\n",
    "    loss = np.mean(np.abs(Xpred-X), axis=1)\n",
    "    \n",
    "    ax.hist(loss, bins=50)\n",
    "    ax.set_xlabel(\"Training MAE Loss\")\n",
    "    ax.set_ylabel(\"Samples\")\n",
    "    \n",
    "    threshold = np.max(loss)\n",
    "    ax.set_title(f\"Threshold={threshold:0.5f}\")\n",
    "    \n",
    "    fig.tight_layout()\n",
    "    return ax, threshold\n",
    "\n",
    "\n",
    "_, threshold = plot_mae_loss_hist(X, model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.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",
       "    // 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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"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\", \"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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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.one(\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",
       "\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",
       "    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=\"899.9999804930258\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11 anomalies\n"
     ]
    }
   ],
   "source": [
    "def plot_anomalies(s, X, model):\n",
    "    fig, ax = plt.subplots(figsize=(9,6))\n",
    "    \n",
    "    Xpred = model.predict(X)\n",
    "    loss = np.mean(np.abs(Xpred-X), axis=1)\n",
    "    threshold = np.max(loss) - np.std(loss)\n",
    "    \n",
    "    anomalies = loss > threshold\n",
    "    print(f\"{np.sum(anomalies)} anomalies\")\n",
    "    \n",
    "    steps = 3\n",
    "    aidx = []\n",
    "    for i in range(steps-1, len(X)-steps+1):\n",
    "        if np.all(anomalies[i-steps+1:i]):\n",
    "            aidx.append(i)\n",
    "    \n",
    "    sales.plot(legend=False, ax=ax, alpha=0.25)\n",
    "    sales.iloc[aidx].plot(legend=False, ax=ax, color='r', label=\"anomalies\")\n",
    "    \n",
    "    ax.legend()\n",
    "    \n",
    "    fig.tight_layout()\n",
    "    return ax\n",
    "\n",
    "\n",
    "_ = plot_anomalies(sales, X, model)"
   ]
  }
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