docs/tutorials/continuous_learning_for_existing_model.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f5d135e6",
   "metadata": {},
   "source": [
    "# Continuous learning from a trained hyperbox-based model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34fa93b3",
   "metadata": {},
   "source": [
    "This example shows how to perform a continuous learning ability for a trained hyperbox-based model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "523546f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d6d638e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fc9d837",
   "metadata": {},
   "source": [
    "### Load training and testing datasets "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ddb6fa1",
   "metadata": {},
   "source": [
    "In this example, we create two training datasets. One data set is used to trained a model and store it to the data storage. The other data set is used to continously train the stored model after reloading that trained model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "325ffe0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import StratifiedKFold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6a24b338",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\hyperbox-brain\\\\examples\\\\other_learning_ability_gfmm'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the path to the this jupyter notebook file\n",
    "this_notebook_dir = os.path.dirname(os.path.abspath(\"__file__\"))\n",
    "this_notebook_dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "38415257",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WindowsPath('C:/hyperbox-brain')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the home folder of the hyperbox-brain toolbox\n",
    "from pathlib import Path\n",
    "project_dir = Path(this_notebook_dir).parent.parent\n",
    "project_dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6b22ac91",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the path to the training and testing files\n",
    "training_file = os.path.join(project_dir, Path(\"dataset/syn_num_train.csv\"))\n",
    "testing_file = os.path.join(project_dir, Path(\"dataset/syn_num_test.csv\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "95f89af9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create training and testing data sets\n",
    "df_train = pd.read_csv(training_file, header=None)\n",
    "df_test = pd.read_csv(testing_file, header=None)\n",
    "\n",
    "Xy_train = df_train.to_numpy()\n",
    "Xy_test = df_test.to_numpy()\n",
    "\n",
    "Xtr = Xy_train[:, :-1]\n",
    "ytr = Xy_train[:, -1]\n",
    "\n",
    "Xtest = Xy_test[:, :-1]\n",
    "ytest = Xy_test[:, -1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6c308ab9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split the existing training set into two training sets\n",
    "skf = StratifiedKFold(n_splits=2)\n",
    "for train1_index, train2_index in skf.split(Xtr, ytr):\n",
    "    X_tr1, X_tr2 = Xtr[train1_index], Xtr[train2_index]\n",
    "    y_tr1, y_tr2 = ytr[train1_index], ytr[train2_index]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e081ac71",
   "metadata": {},
   "source": [
    "This example shows how to continue to train a deployed model. This example will use an incremental learning algorithm and an agglomerative learning algorithm without retraining from scratch for demonstration."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eaa9cb0e",
   "metadata": {},
   "source": [
    "### 1. Training a General fuzzy min-max neural network model using an incremental learning algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4cec0801",
   "metadata": {},
   "outputs": [],
   "source": [
    "from hbbrain.numerical_data.incremental_learner.onln_gfmm import OnlineGFMM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "df994d67",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initializing parameters\n",
    "theta = 0.1\n",
    "theta_min = 0.1\n",
    "gamma = 1\n",
    "is_draw = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "71b2062d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OnlineGFMM(C=array([1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1,\n",
       "       1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2]),\n",
       "           V=array([[0.42413   , 0.53516   ],\n",
       "       [0.70577   , 0.39146   ],\n",
       "       [0.82785   , 0.78025   ],\n",
       "       [0.6416    , 0.4824875 ],\n",
       "       [0.48794   , 0.672     ],\n",
       "       [0.26651   , 0.18424   ],\n",
       "       [0.32527   , 0.60393   ],\n",
       "       [0.19944   , 0.03      ],\n",
       "       [0.29343   , 0.28975   ],\n",
       "       [0.63683   , 0.6936    ],\n",
       "       [0.32782   , 0.55997   ],\n",
       "       [0.03      , 0.47757   ],\n",
       "       [0.54181   , 0.43986   ],\n",
       "       [0.73368   , 0.2170...\n",
       "       [0.49255   , 0.43164   ],\n",
       "       [0.81877   , 0.51294   ],\n",
       "       [0.4713    , 0.77996   ],\n",
       "       [0.25281   , 0.41059   ],\n",
       "       [0.25858   , 0.30637   ],\n",
       "       [0.3378    , 0.451095  ],\n",
       "       [0.68354   , 0.41653   ],\n",
       "       [0.34544   , 0.85954   ],\n",
       "       [0.59061   , 0.62471   ],\n",
       "       [0.68628   , 0.65662   ],\n",
       "       [0.14324   , 0.47785   ],\n",
       "       [0.41517   , 0.51424   ],\n",
       "       [0.83355   , 0.5761    ],\n",
       "       [0.15331   , 0.13567   ],\n",
       "       [0.25929   , 0.81558   ],\n",
       "       [0.815     , 0.35526   ],\n",
       "       [0.67625   , 0.80457   ],\n",
       "       [0.37033   , 0.26124   ],\n",
       "       [0.67914   , 0.48785   ]]),\n",
       "           theta=0.1, theta_min=0.1)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "onln_gfmm_clf = OnlineGFMM(theta=theta, theta_min=theta_min, gamma=gamma, is_draw=is_draw)\n",
    "onln_gfmm_clf.fit(X_tr1, y_tr1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "247ff915",
   "metadata": {},
   "source": [
    "#### Display decision boundaries among classes if input data are 2-dimensional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "eb587589",
   "metadata": {},
   "outputs": [
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       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // 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=\"526.6666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "onln_gfmm_clf.draw_hyperbox_and_boundary(\"The trained GFMM classifier and its decision boundaries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c6bfe948",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of hyperboxes =  39\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of hyperboxes = \", onln_gfmm_clf.get_n_hyperboxes())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9dfdb006",
   "metadata": {},
   "source": [
    "#### Make prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b0dd872a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "834f4d88",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy =  86.40%\n"
     ]
    }
   ],
   "source": [
    "y_pred = onln_gfmm_clf.predict(Xtest)\n",
    "acc = accuracy_score(ytest, y_pred)\n",
    "print(f'Accuracy = {acc * 100: .2f}%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46f76ddc",
   "metadata": {},
   "source": [
    "#### Store the trained model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "070e65aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "from hbbrain.utils.model_storage import store_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "bfb75fd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "store_model(onln_gfmm_clf, \"store_cont_model.dummy\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "101b4de7",
   "metadata": {},
   "source": [
    "#### Reload the trained model and make prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f570b847",
   "metadata": {},
   "outputs": [],
   "source": [
    "from hbbrain.utils.model_storage import load_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b0d6094b",
   "metadata": {},
   "outputs": [],
   "source": [
    "trained_onln_gfmm_clf = load_model(\"store_cont_model.dummy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "95459b86",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy =  86.40%\n"
     ]
    }
   ],
   "source": [
    "y_pred_trained_model = trained_onln_gfmm_clf.predict(Xtest)\n",
    "acc = accuracy_score(ytest, y_pred_trained_model)\n",
    "print(f'Accuracy = {acc * 100: .2f}%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f88d455",
   "metadata": {},
   "source": [
    "#### Continue to train the deployed model using another training set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e29db85d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OnlineGFMM(C=array([1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1,\n",
       "       1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1, 1,\n",
       "       2, 2, 1, 2, 2, 2, 2, 2, 1]),\n",
       "           V=array([[0.42413   , 0.53516   ],\n",
       "       [0.70577   , 0.397105  ],\n",
       "       [0.82785   , 0.78025   ],\n",
       "       [0.66038   , 0.51128   ],\n",
       "       [0.48794   , 0.672     ],\n",
       "       [0.26651   , 0.18424   ],\n",
       "       [0.32289   , 0.60194   ],\n",
       "       [0.19944   , 0.03      ],\n",
       "       [0.29343   , 0.28975   ],\n",
       "       [0.63683   , 0.6936    ],\n",
       "       [0.32906   , 0.55512   ],\n",
       "       [0.03      , 0.47757   ],\n",
       "       [0.54...\n",
       "       [0.25929   , 0.81558   ],\n",
       "       [0.815     , 0.397095  ],\n",
       "       [0.67906   , 0.83605   ],\n",
       "       [0.37033   , 0.26124   ],\n",
       "       [0.66037   , 0.57837   ],\n",
       "       [0.52197   , 0.91371   ],\n",
       "       [0.52621   , 0.66846   ],\n",
       "       [0.80583   , 0.43242   ],\n",
       "       [0.79935   , 0.7757    ],\n",
       "       [0.35813   , 0.58772   ],\n",
       "       [0.79516   , 0.32629   ],\n",
       "       [0.70743   , 0.50325   ],\n",
       "       [0.36057   , 0.71561   ],\n",
       "       [0.72496   , 0.38674   ],\n",
       "       [0.28822   , 0.62174   ],\n",
       "       [0.14737   , 0.28498   ],\n",
       "       [0.56487   , 0.17003   ],\n",
       "       [0.68469   , 0.2221    ],\n",
       "       [0.55763   , 0.43813   ]]),\n",
       "           theta=0.1, theta_min=0.1)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trained_onln_gfmm_clf.fit(X_tr2, y_tr2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "013e3948",
   "metadata": {},
   "source": [
    "#### Display decision boundaries among classes if input data are 2-dimensional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f7f510c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // 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=\"548\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trained_onln_gfmm_clf.draw_hyperbox_and_boundary(\"The trained GFMM classifier and its decision boundaries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "fbd78ab7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of hyperboxes =  53\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of hyperboxes = \", trained_onln_gfmm_clf.get_n_hyperboxes())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02a9a7ad",
   "metadata": {},
   "source": [
    "#### Make prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "4bb97721",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy =  84.50%\n"
     ]
    }
   ],
   "source": [
    "y_pred = trained_onln_gfmm_clf.predict(Xtest)\n",
    "acc = accuracy_score(ytest, y_pred)\n",
    "print(f'Accuracy = {acc * 100: .2f}%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d851a0d4",
   "metadata": {},
   "source": [
    "### 2. Training a General fuzzy min-max neural network model using an agglomerative learning algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e925d8aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "from hbbrain.numerical_data.batch_learner.agglo_gfmm import AgglomerativeLearningGFMM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "895962a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialise parameters\n",
    "theta = 0.2\n",
    "gamma = 1\n",
    "min_simil = 0\n",
    "simil_measure = 'long'\n",
    "is_draw = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "344d7773",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgglomerativeLearningGFMM(min_simil=0, simil_measure='long', theta=0.2)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agglo_sm_clf = AgglomerativeLearningGFMM(theta=theta, gamma=gamma, min_simil=min_simil, simil_measure=simil_measure, is_draw=is_draw)\n",
    "agglo_sm_clf.fit(X_tr1, y_tr1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba5575ef",
   "metadata": {},
   "source": [
    "#### Display decision boundaries among classes if input data are 2-dimensional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "11f325d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // 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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kyNnKRqJRS7KGdDB9peWo2T2PJSdqXSOMzQsFN17ZmJaUTZGdzUjJyUChqCggJ4HB0cBClCAAhSggGcCXP955tf6bDY5cpaikVjkopwBH+zs+VoMvWs+vtx/yjnWYGMwcvPTMKnEivHdUtE9PRrB3GI64HPJAVKAAhSgAAXcFeD6z125S89jkyNnKRqJRS7KqYpgdfWNmPboYny4/oBzvAaDARnWFIy12zC5lwV9M2MQxp3XVJFPDpICFKAABSjQUQGu/zoqduXj2eTIWYpGYpGLcqomWFNTE2b/+zM89d4Xbcackp6IEUU5mN43DYNs8TCFcYtp1SSVA6UABShAAQq4KMD1n4tQLhzGJscFJH8cwiL3h3rgXPMfH+/ArX9bgaaWjdcQlxiDIYNtuKkgEyU5CYgzhQTOgDkSClCAAhSgAAU8FuD6z2NCZwA2OXKWopFY5KKcqgz2yebDGP/wQtTVNzjHb4qJxMABNswalIFh+ckwx4RCeZgoXxSgAAUoQAEKqF+A6z+5HLLJkbMUjcQiF+VUbbCvDp7BtXPm4WxFjXMOYRFh6NU7EzOLsjGisxnWJG4xrdoEc+AUoAAFKECBVgJc/8mVA5scOUvRSCxyUU5VBys7W4Uhs+dh37FzznkYQ4zI75aBqfZsfKtrKvJTTdx5TdVZ5uApQAEKUIACANd/clXAJkfOUjQSi1yUU/XBlIeFjnnoY6zadtQ5F0OwAdm5qZhgt2Fij1T0zIhGqJEbEqg+2ZwABShAAQroVoDrP7nUs8mRsxSNxCIX5dREsMbGJvzkLyvw4uKvnfNRPo9jzkjCKLsN03qnY6A1FuGhbHQ0kXBOggIUoAAFdCfA9Z9cytnkyFmKRmKRi3JqKtgf3t2Cu/79WZs5JaTEYVhRDmb0S0dxbgJiIoyamjMnQwEKUIACFNCDANd/cllmkyNnKRqJRS7Kqblg767Zh5v+sAQNDY3OuUXHRaFokBUzCzJxXV4ikmPCNDdvTogCFKAABSigZQGu/+SyyyZHzlI0EotclFOTwTbuKsPwez5EZXWdc37hpnD065eNWYOzMDw/GRnx3HlNk8nnpChAAQpQQJMCXP/JpZVNjpylaCQWuSinZoMdPFGBIXe8j2OnKp1zDAkLQdceGZhRbMXorinITTHBwGfpaLYGODEKUIACFNCOANd/crlkkyNnKRqJRS7Kqelg5VW1GH73h9i854RznsHGYOTkWzDJbsW4bqnokREDo4EPDdV0IXByFKAABSigegGu/+RSyCZHzlI0EotclFPzweobGjHzD0vw/pp9zrkGGYKQnp2CsXYbpvSyoF9WLMJCuPOa5ouBE6QABShAAdUKcP0nlzo2OXKWopFY5KKcugjW1NSEe17egMf+s7nNfJMtCRhenIMZfdMw2BYPUzh3XtNFQXCSFKAABSigOgGu/+RSxiZHzlI0EotclFNXwV78ZCd+/KflUJqe5ldsYjRKBtkwc0A6ru2UhHhTqK5MOFkKUIACFKCAGgS4/pPLEpscOUvRSCxyUU7dBVu27SjGPrAAtXUNzrlHRkWgoCAHswrTcX1eMlLjwqA8TJQvClCAAhSgAAUCQ4DrP7k8sMmRsxSNxCIX5dRlsN1Hz6Lkjnk4XV7tnH9oeCh69c7C9KIs3NjFDFtSBBsdXVYHJ00BClCAAoEowPWfXFbY5MhZikZikYty6jbYyfJqXHvnfOw6fMZpYAwxolOXdEwtsWJsVzO6WKIQzJ3XdFsjnDgFKEABCgSOANd/crlgkyNnKRqJRS7Kqetg1bX1GP/bRVi65bDTwRBsQFaOGd+y2zC5hwW9M6MRauTOa7ouFE6eAhSgAAX8LsD1n1wK2OTIWYpGYpGLcuo+WGNjE3727Go8t2C700L5PI45IxEji22Y1icdA61xiAxlo6P7YiEABShAAQr4TYDrPzl6NjlylqKRWOSinAz2jcAf39+GX/9rTRuP+OQ4XFdkw6z+GbDnJiAmgltMs2AoQAEKUIAC/hDg+k9OnU2OnKVoJBa5KCeDtRKY/9kBTH90MZQHiDa/omJNGDzQhlkDM3BtXhJSYkK5IQGrhgIUoAAFKOBjAa7/5MDZ5MhZikZikYtyMthFApv3nsT1d32Aiqpa51fCI8PQp68VMwdnYUTnZGQmhLPRYeVQgAIUoAAFfCjA9Z8cNpscOUvRSCxyUU4Gu4zAkVPnMeSOeTh8osL51ZDQEHTtkYGpxVaM6ZqCTikmGLjzGuuHAhSgAAUo4BMBrv/kmNnkyFmKRmKRi3Iy2BUEKqrqMOK+D7FxZ5nziGBjMKx5Fky0Z2NC91T0SI9BiNFAQwpQgAIUoAAFvCzA9Z8cMJscOUvRSCxyUU4Gu4pAQ0MjvvfUUry1Yo/zKGXntbTsZIyx52BKbwv6Z8UiPIQ7r7GQKEABClCAAt4U4PpPTpdNjpylaCQWuSgng7Uj0NTUhIde34TfvrGpzZFJqQkYVmTFrP7pKLQlIDqcO6+xmChAAQpQgALeEuD6T06WTY6cpWgkFrkoJ4O5KPDast344dNLoTxXp/kVEx8Ne6ENMwvScW2nJCSaQl2MxsMoQAEKUIACFOiIANd/HdG6+rFscuQsRSOxyEU5GawDAqu/KsWo+z5CdW2986yIqAgMGJCNmwZl4fr8ZFjiwrjzWgdMeSgFKEABClDAFQGu/1xRcu0YNjmuOfn8KBa5z8l5wVYCe4+dQ8nseTh5tsr5r6FhoejROwvTi7MwKt8MW0oEDEFBdKMABShAAQpQQEiA6z8hSABscuQsRSOxyEU5GcwNgdMVNRg6Zz6+Onjaebay81pel3RMKc7GuB4WdLVEIZhbTLuhy1MoQAEKUIAClwpw/SdXFWxy5CxFI7HIRTkZzE2B2roGTH5kERZuPOSMYDAYkJFjxrhiKyb1tKBvVgxCjdx5zU1inkYBClCAAhRwCnD9J1cMbHLkLEUjschFORnMAwFl57Vf/nMt/jx/W0uUIMCclogR9hxM75OGQbZ4RIay0fGAmadSgAIUoAAFwPWfXBGwyZGzFI3EIhflZDABgb99tB23PbsKTS0bryEuKRbXOnZey0BJbiLiIrnFtAA1Q1CAAhSggE4FuP6TSzybHDlL0UgsclFOBhMSWLjpECbOXYj6+kZnRFNMJAoLbJhVmImheUlIiQnlzmtC3gxDAQpQgAL6EuD6Ty7fbHLkLEUjschFORlMUODLA6dx7Zx5KD9f64waFhGGPn2zMWNwJkZ2NiMrMZyNjqA5Q1GAAhSggD4EuP6TyzObHDlL0UgsclFOBhMWKD1ThZI73sfB4+XOyMZQI7p0y8RUexbGdElF51QTDNx5TVie4ShAAQpQQMsCXP/JZZdNjpylaCQWuSgng3lBoLKmHqPu/whrvyp1RjcEG2DNs2CC3YoJPVLRKz0GIUaDF67OkBSgAAUoQAHtCXD9J5dTNjlylqKRWOSinAzmJYGGhkb86E/L8eqnu5xXCAoKgiUrGaOKbZjaOw0F1liEh3DnNS+lgGEpQAEKUEBDAlz/ySWTTY6cpWgkFrkoJ4N5WeCRtz/HfS9vaHOVRHMchhXnYEa/dBTnJCA6nDuveTkNDE8BClCAAioX4PpPLoFscuQsRSOxyEU5GcwHAm+v2ovvPL4EjY0te0xHx0XBPsiGWQMzcE1eIpKiw3wwEl6CAhSgAAUooE4Brv/k8sYmR85SNBKLXJSTwXwk8NnO4xhxz4eoqql3XjHCFI7+/ayYOTgTw/OTkR7Pndd8lA5ehgIUoAAFVCbA9Z9cwtjkyFmKRmKRi3IymA8FDhwvR8nseTh+utJ51ZCwEHTvmYXpRdkY1TUFuSmRMAQF+XBUvBQFKEABClAg8AW4/pPLEZscOUvRSCxyUU4G87HA2fO1uP7uD7B130nnlYONwcjNT8OkEivGdTWjR0YMgrnFtI8zw8tRgAIUoEAgC3D9J5cdNjlylqKRWOSinAzmB4G6+kZM//0n+OCz/c6rBxmCkGE141t2Gyb3sqBvZgzCuPOaH7LDS1KAAhSgQCAKcP0nlxU2OXKWopFY5KKcDOYngaamJsz+92d46r0v2owgOS0RI5Sd1/pYMMgWDxN3XvNThnhZClCAAhQIJAGu/+SywSZHzlI0EotclJPB/Czwz0U78L9/WYGmlo3XEJcYg5LBNny7IBP2nATEm0L8PEpengIUoAAFKOBfAa7/5PzZ5MhZikZikYtyMlgACCzZcgTjH/4YtXUNztGYoiNRUGDDTYMyMCw/GeaYUCgPE+WLAhSgAAUooEcBrv/kss4mR85SNBKLXJSTwQJEYMehM7jmznk4W1HjHFFYRBh69s7EzKIsjOxshjUpgo1OgOSLw6AABShAAd8KcP0n580mR85SNBKLXJSTwQJIoOxslaPR2Xv0nHNUxhAj8rumY6rdirHdUtE51eTTndfOnweioi4Mp6ICMJkCCIxDoQAFKEAB3Qhw/SeXajY5cpaikVjkopwMFmACysNCxz70MVZuO+ocmSHYgOwcM8aV5GByj1T0zIhGqDHYJyNnk+MTZl6EAhSgAAXaEeD6T65E2OTIWYpGYpGLcjJYAAo0Njbhp39diRcW7XCOTvk8jjkjCaPsNkzrnY4CaywiQr3f6LDJCcAC4ZAoQAEK6FCA6z+5pLPJkbMUjcQiF+VksAAWeOK9L3DnC+vajDAhJQ7DinIwo186inMTEBNh9OoM2OR4lZfBKUABClDARQGu/1yEcuEwNjkuIPnjEBa5P9R5TX8J/Hftfsx87BM0NDQ6hxAdF4WiQVbMHJCB6zolITkmTGx4SlPT+qX8t9l84V9KSy/9TA4/oyNGz0AUoAAFKHAVAa7/5MqDTY6cpWgkFrkoJ4OpQGDT7hO4/u4PUFld5xxtbGIMhg/phG/3T0NRTgKihB4a2tFdqls/30cFlBwiBShAAQqoVIDrP7nEscmRsxSNxCIX5WQwlQgcPFGBbv/zBuobLjw1NDwyHEVFefhOYQaGdkpGcnSoyEzY5IgwMggFKEABCggLcP0nB8omR85SNBKLXJSTwVQk8MCrGzD3zc+92uTwdjUVFQSHSgEKUEBHAlz/ySWbTY6cpWgkFrkoJ4OpSOCx/2zG3S+t92qTczEHNx5QUYFwqBSgAAU0LMD1n1xy2eTIWYpGYpGLcjKYigTY5KgoWRwqBShAAQqICnD9J8fJJkfOUjQSi1yUk8FUJMAmR0XJ4lApQAEKUEBUgOs/OU42OXKWopFY5KKcDKYiATY5KkoWh0oBClCAAqICXP/JcbLJkbMUjcQiF+VkMBUJ+KPJUREPh0oBClCAAhoW4PpPLrlscuQsRSOxyEU5GUxFAmxyVJQsDpUCFKAABUQFuP6T42STI2cpGolFLsrJYCoSYJOjomRxqBSgAAUoICrA9Z8cJ5scOUvRSCxyUU4GU5EAmxwVJYtDpQAFKEABUQGu/+Q42eTIWYpGYpGLcjKYigTY5KgoWRwqBShAAQqICnD9J8fJJkfOUjQSi1yUk8FUJMAmR0XJ4lApQAEKUEBUgOs/OU42OXKWopFY5KKcDKYiATY5KkoWh0oBClCAAqICXP/JcbLJkbMUjcQiF+VkMBUJsMlRUbI4VApQgAIUEBXg+k+Ok02OnKVoJBa5KCeDqUiATY6KksWhUoACFKCAqADXf3KcbHLkLEUjschFORlMRQJsclSULA6VAhSgAAVEBbj+k+NkkyNnKRqJRS7KyWAqEmCTo6JkcagUoAAFKCAqwPWfHCebHDlL0UgsclFOBlORAJscFSWLQ6UABShAAVEBrv/kONnkyFmKRmKRi3IymIoE2OSoKFkcKgUoQAEKiApw/SfHySZHzlI0EotclJPBBATO4zyiEOWIVIEKmGASiHppCDY5XmFlUApQgAIUUIEA139ySWKTI2cpGolFLsrJYAICbHIEEBmCAhTQjEBTE1BZqZnpqGIikZFAUJAqhur2ILn+c5vukhPZ5MhZikZikYtyMpiAAJscAUSGoAAFNCGgNDh2O7BqlSamo5ovZmIbAAAgAElEQVRJFBcDy5dru9Hh+k+uHNnkyFmKRmKRi3IymIAAmxwBRIagAAU0IXD+PBB14e5dvnwsUFEBmLxzt7SPZ3L5y3H9J5cGNjlylqKRWOSinAzmhoDS1LR+Kf9thtnxT6UoveQzOVKf0eFnctxIFk+hAAV8KtC6ySkt1fai26ewV7iY4m2+8OsHbHICISPqGAObnADNE5ucAE2MjoYVhI7d+NyEJhGd1k2OMcSIrj2yMLk4E6M7p6JrmgkGrd+QLaLIIBSggDcFWjc5Wl90e9PR1dh68ub6z9WqaP84XTU51dXVmDt3Ll599VUcOHAACQkJGDlyJB544AFkZGS0r9XqiI8++ghPPfUUPvvsM5w9exbx8fEYOHAgbrvtNgwbNqxDsS53MIvcY0IG8FDAX03Oa8t24/tPfuocfbAxGLld0jG5OBsTeljQ1RKFYEPHGjAPKXg6BShAgTYCelp0B0Lq9eTN9Z9cxemmyVEaHKX5WLVqFSwWC0pKSrBv3z6sW7cOycnJWL16NXJzc12Sffzxx3H77bcjKCgIxcXFSE9Px549exwNj/L6y1/+gp/85CcuxbrSQSxyj/h4soCAv25Xa2hoxNRHF+ODzw44Z2EwGJBhTcFYuw2Te1nQNzMGYSHBArNkCApQgAIdF9DTorvjOvJn6Mmb6z+5+tFNk3PPPffgwQcfxODBg/Hxxx8j6ptPDDY3LEOGDMHSpUvblS0rK3O+67N48WLYle1Vvnm9/fbbmDJlCiIiIlBaWuq8RrtBL3MAi9wdNZ7jTQFfbTygzKGpqQm/fn4dnnl/a5sppaQnYkRRDmb0S8NAWzxMoWx0vJlzxqYABS4voKdFdyDUgJ68uf6TqzhdNDl1dXVISUnBmTNnsHHjRvTt27eNYO/evbFlyxasX78e/fv3v6ruvHnzMHbsWMdtbh9++OElx/bp0webN2/G2rVrHbevuftikbsrx/O8JeDLJqd5Dn9fsB0///sqKNu1Nr/ikmIxpNCKmwoyUZKTgDhTiLemzLgUoAAFLiugp0V3IJSAnry5/pOrOF00OUuWLMHQoUMdt6Pt2rXrEj3lHR7lnZ57770X991331V1Fy5ciBtuuKHdJmfnzp3Iy8tzO1MscrfpeKKXBPzR5ChTWbz5MCY8vBB19Q3OmZliIjGwwIabBmVgaKdkmGNCHbeP8kUBClxdwF8PsNTaQxz1tOgOhO8pPXlz/SdXcbpocp588knHhgDKrWRvvPHGJXrz58/HmDFjMH78eLzzzjtX1VXeDbJaraiqqsLFt6v95z//weTJkx23xK1cudKjLLHIPeLjyV4Q8FeTo0zlq4NncO2d83D2fI1zZmERYejdJwszirIwIt8Ma1I4Gx0v5J0htSPgzwdYau0hjnpadAfCd4CevLn+k6s4XTQ5v/jFL/DEE084Gh3lMzgXv5Tby5TbzPr164cNGza0q/vWW29h1qxZUG6Da954YO/evY6NB5Tb2J5//nnH7XGevFjknujxXC0KlJ2twpDZ87Dv2Dnn9JQtpvO7Z2BacTbGdk1FfqqJO69pMfmck4iAvx9gqaWtlvW06BYpPg+D6Mmb6z8Pi6XV6bpocm655RY8++yzmDNnDh566KFL9JRb2Dp16oT8/Hzs2LHDJd1PPvkE06ZNw4kTJ5zHm81m/PKXv3Q0U8HBrn0gurmYL77o7t27HbfXbdu2zaXx8CAK6EGgqqYeox9cgNVfHnNO1xBsQHZuKibYbZjYMxU902MQajTogYNzpECHBPzxAEutPsRRT4vuDhWZlw7WkzebHLki0kWT86Mf/QjPPfcc7rrrLscOaxe/lM/PKA2Oq03OH/7wB/z617923N6mfIYnJyfHsYW08rmed999F5MmTYLybo8rLzY5rijxGAq0CDQ2NuHHf16Blz752vmPyudxUjOSMMpuw7Te6SiwxiKcO6+xbCjQRsAfC0V/XNMXadfqvHxh58419OTNJsedCrn8ObpociRvV1O2mb722msdt7Ypt6cpz+9ofjU0NKCgoACbNm3CggULHBsUuPtikbsrx/P0IvD7d7bgnhcvPJuq+ZVojsPQwTmY2T8dRTkJiIkw6oWD86RAuwL+WCj645rtQggcoNV5CdB4JYSevLn+kyshXTQ5khsP/PCHP8Q///lPx21vyu1vF7+Uf7/77rsxe/Zs/Pa3v3U7Uyxyt+l4oo4E3lm9D9/+wydoaGzZYzo6LgpFg2yYVZCBa/MSkRwTpiMRTpUCVxbwx0LRH9f0RQ1odV6+sHPnGnry5vrPnQq5/Dm6aHJc3UJaud3s/vvvv6ruiBEjHA8Tffrpp3Hrrbdecqzy7z/72c/w4x//GH/961/dzhSL3G06nqgzgQ27ynDDPR+isrrOOfMIUzj69svGrMFZGJ6fjIx47ryms7LgdC8j4I+Foj+u6Yvka3VevrBz5xp68ub6z50K0XGTU1tb69jt7OzZs1d9GOi6desct5td7fXd734X//73v/Gd73wHL7zwwiWHfvvb38ZLL72EuXPn4o477nA7Uyxyt+l4og4FDpaVo2T2PJSeqnTOPiQsBN16ZGF6cRZGdzUjNyUSBj5LR4fVwSk3C/hjoeiPa/oi41qdly/s3LmGnry5/nOnQnTc5ChTVzYdePjhh1FUVOR4J8ZkMjlElC2lb7/9dtjtdixfvtyp9Mwzz0D534QJExwNS/NLeY7OxIkTHbunKf9/7Nixzq+99957jq8pry+//BKdO3d2O1MscrfpeKJOBc5V1mL43R9gy96TToFgYzBy8i2YZLdhXDczemTEwGjgQ0N1WiK6n7Y/For+uKYvEq3VefnCzp1r6Mmb6z93KkTnTU51dbVjw4C1a9fCYrGgpKQE+/fvd/x3YmIi1qxZg7y8PKeSsmuacuua8s6N8tyb5ldTU5Nj6+g333zT8U8DBgyAzWaD8pyc9evXO/5NaabuvPNOj7LEIveIjyfrVKCuvhEz//AJ5q3d7xQIMgQhPTsFY+02TOllQb+sWISFuLbFu04ZOW2NCijPqYmOvjC50lLgm7/1eXW23ELaq7y6Cc4mRzepFp2oLj6T0yxWVVXleFfmlVdewcGDBxEfH+94eKeyrXRmZmYb2Cs1OcpBSqPzr3/9y3G72pYtW1BRUYG4uDgMHDjQ8TkdJaanLzY5ngryfL0KKN+fd720Ho+/s6UNQXJaAm4ozsH0PmkYbIuHKZw7r+m1RvQ67+PHAbPZf7Pnw0D9Z6/2K7PJUXsG/TN+XTU5/iF276psctxz41kUaBZ4YfHX+J8/r3D8UaL5FZsYg5JBNswckIZrOyUh3hRKMAroRsCfTU5xMaDcEa6Vj8XpadEdCN8gevLm+k+u4tjkyFmKRmKRi3IymE4Flm49gm89+DFq6xqcApHRkRg4wIZZhekYlpeM1LgwKA8T1etL6QErW/Zr0CtDh+cdGam+BbuS67KyC1P19fh9fb0OJ7SDJ+hp0d1BGq8cridvrv/kSohNjpylaCQWuSgng+lYYNeRsxgyex5Ol1c7FcJN4RhcmIubBmVgWKdkmGP1+SwdZdFrtwOrVum4QNycutbemXCTQben6WnRHQhJ1pM3139yFccmR85SNBKLXJSTwXQucLK8GoN/+R4OllU4JTr3smLGkGx8q0squqZF6VKo9cJBlwAeTlpLnzHxkEJ3p+tp0R0IydWTN9d/chXHJkfOUjQSi1yUk8EogANlFej849edEvk9szFjiNXR5HRLZ5Pjq9221F6KWt0tTO158fX49bTo9rXt5a6nJ2+u/+Qqjk2OnKVoJBa5KCeDUQDzPtuPKXMXsclpVQt6WjhIfQvQTEpS3XFYB77Nn568uf6Tqy02OXKWopFY5KKcDKZzgdeX78YPnlyKxm92WlM2GujWx4YZJdkY08WMzqkXHg6st5eeFg5SuaWZlKS647AOfJs/PXlz/SdXW2xy5CxFI7HIRTkZTMcCv31jEx58bWMbgSRLAkbYczCzTzoG5cTBFKbPZ+boaeEg9S1AMylJdcdhHfg2f3ry5vpPrrbY5MhZikZikYtyMpgOBRoaGvGDp5fhjeW7nbNX3sFJy0rGKLsNU3ulYYA1FuEhwTrUuTBlPS0cpJJMMylJdcdhHfg2f3ry5vpPrrbY5MhZikZikYtyMpjOBM5X1+HG+xfgsx2lzpkHBwfD2smCifZsjO+eip7pMQgxGnQm03a6elo4SCWaZlKS6o7DOvBt/vTkzfWfXG2xyZGzFI3EIhflZDAdCRw7XYkhd8zDwbJy56xDQkPQuXsGphdnY3RXM/LNJhgM+n0AaDOMnhYOUt8CNJOSVHcc1oFv86cnb67/5GqLTY6cpWgkFrkoJ4PpROCL/acwbM58lFfWOmccFhmGvn2zMWNwFkZ2TkFmQjiU29b44u1q7tSAnhZb7vjo5RzWgW8zrSdvrv/kaotNjpylaCQWuSgng+lA4KMNBzHlkUWor290zjYq1oTCAitmDcrEdXlJSIkJZYPTqhb0tHCQ+hagmZSkuuOwDnybPz15c/0nV1tscuQsRSOxyEU5GcxPAgdPVOD7Ty3Fxl0nvDoCZZOB2lbNjXKx+ORYXFeUg5n90lGcm4i4SH3uoHY1eD0tHKQKkGZSkuqOwzrwbf705M31n1xtscmRsxSNxCIX5WQwPwhs3FWG4fd8iMrqOt9ePQhITU/CSGUHtT5pGGSNR2SofndQY5MjW356WmzJymkrGuvAt/nUkzfXf3K1xSZHzlI0EotclJPBfCzwzup9+PbjS6C8w+LLlyHYgEybGePsNkzuYUHvrGiEGtngXCkHelo4SNUhzaQk1R2HdeDb/OnJm+s/udpikyNnKRqJRS7KyWA+FPj9O1twz4uftbmicutYVEyEV0cRhCCYU6IxorcZ47pb0NUShWDuoHZVcz0tHKSKj2ZSkuqOwzrwbf705M31n1xtscmRsxSNxCIX5WQwHwg0Njbhx39egZc++dp5NWUXs9TMJIwstiE7wftNTmZsOAZlxcOaHAEDd1BrN+t6Wji0i+HiATRzEUrjh7EOfJtgPXlz/SdXW2xy5CxFI7HIRTkZzMsCVTX1GP3gAqz+8pjzSsqtY9m5qZhQYsO3upiREhPu1VEoPU18pBExEUbuoOaitJ4WDi6StHsYzdol0sUBrAPfpllP3lz/ydUWmxw5S9FILHJRTgbzosDxM1W45s552HfsnPMqxlAjOnfLwNTibIztmor8VBNvHfNiDtwNraeFg7tGF59HMylJdcdhHfg2f3ry5vpPrrbY5MhZikZikYtyMpiXBLYfPI1r75yPc+drnFcIiwhD7z5ZmFGUhRH5ZliT+PBNL/F7HFZPCwePsb4JQDMpSXXHYR34Nn968ub6T6622OTIWYpGYpGLcjKYFwQWf34YE367EHX1Dc7opphIDCyw4aZBGRjaKRlmPnzTC/JyIfW0cJBSo5mUpLrjsA58mz89eXP9J1dbbHLkLEUjschFORlMWODvC7bj539fhaamlsBxSbG4ptCGWQUZKMlJQJwpRPiqDCctoKeFg5QdzaQk1R2HdeDb/OnJm+s/udpikyNnKRqJRS7KyWBCAk1NTfj18+vwzPtb20RMSU/EiKIcTO+bhkE58TDx4ZtC4t4No6eFg5QkzaQk1R2HdeDb/OnJm+s/udpikyNnKRqJRS7KyWACArV1DZj66CdYsOGAM5rBYECGNQVjlYdv9rKgb2YMwkL48E0Bbp+E0NPCQQqUZlKS6o7DOvBt/vTkzfWfXG2xyZGzFI3EIhflZDAPBc6cr8HQOR9g+4FTzkjBxmDkdknHlOJsjO/Bh296SOyX0/W0cJACppmUpLrjsA58mz89eXP9J1dbbHLkLEUjschFORnMA4H9peWwz34fJ85UOaOEhoWie69MTC/OxqjOZuSk8OGbHhD77VQ9LRykkGkmJanuOKwD3+ZPT95c/8nVFpscOUvRSCxyUU4Gc1Ng7dfHMfLeD1FdU++MEBEVgf79szFrUCZu6JwMSxy3iHaT1++n6WnhIIVNMylJdcdhHfg2f3ry5vpPrrbY5MhZikZikYtyMpgbAm+s2IPvP/kpGhtbtlCLiY9GcaEVswZk4Jq8RCRFh7kRmacEioCeFg5S5jSTklR3HNaBb/OnJ2+u/+Rqi02OnKVoJBa5KCeDdVBg7puf44FXN7Q5KzE1HtcX2TCjXzqKchIQHW7sYFQeHmgCelo4SNnTTEpS3XFYB77Nn568uf6Tqy02OXKWopFY5KKcDOaiQENDI374x2V4fdlu5xlBQUFIy0rGKLsNU3ulYYA1FuHcQc1F0cA+TE8LB6lM0ExKUt1xWAe+zZ+evLn+k6stNjlylqKRWOSinAzmgsD56jrceP8CfLaj1Hl0cHAwrJ0smGjPxvjuqeiZHoMQo8GFaDxEDQJ6WjhI5YNmUpLqjsM68G3+9OTN9Z9cbbHJkbMUjcQiF+VksHYEjp2uRMkd83CorNx5ZEhoCDp3y8A0ezbGdDUj32yCwRBESw0J6GnhIJU2NZk1NjXhXGW94/s2OjwYyruyfMkIqKkOZGbs3yh68ub6T67W2OTIWYpGYpGLcjLYVQS+2H8Kw+bMR3llrfOosMgw9O2TjRlF2RjZORmZCdxBTYtFpKeFg1T+1GJW39iEL4+UY+uxchgNQeiTFoM85Q8VbHRESkEtdSAy2QAIoidvrv/kCo5NjpylaCQWuSgng11BYMHGQ5j8u4Wor290HhEVa0JhgdWxRfR1eUlIiQnlX4A1WkF6WjhIpVANZjV1Ddh08Cze3HIM63aedDQ5Q7olYUI3C3pkxjj+my/PBNRQB57NMLDO1pM3139ytccmR85SNBKLXJRTV8EOHC/H7f9ai637T1913pU19Th+urLNMfHJsbiuKAcz+6WjODcRcZHcQU3LxaOnhYNUHgPd7Hx1PVbvPY3XPj+Cj1fuxcnS044/UqRmJmGs3YYpvSzonxWLMG4e4lFJBHodeDS5ADxZT95c/8kVIJscOUvRSCxyUU7dBFv3zcM7q1o9vNOlyQcBqelJGKnsoNYnDYOs8YgMDXbpVB6kXgE9LRykshTIZqfP12HprhN4+bPDWL52L86ePNdm2smWBAwvzsGMvmkotMUjitvAu10WgVwHbk8qgE/UkzfXf3KFyCZHzlI0EotclFMXwd5auQfffaLtwztdmbjBYEBmjhnj7DZM7mFB76xohBrZ4Lhip/Zj9LRwkMpVIJo1NTXh2JkaLN5VhpfXHMa69XtRWd72Xdrm+ccmRKOk0IaZA9JxTackJJhCpWh0FScQ60DLCdCTN9d/cpXMJkfOUjQSi1yUU/PB5r71OR54pe3DO2MTYxAWFnLVuQcZgpBmicXo/mkY192CrpYoBPN+fc3XS/ME9bRwkEpqoJkpDc7eE1X46KtSvLr6AL74/ABqqls2EbncvCOjIlAwwIpZhZkY1ikZlrgwfu6ugwUSaHXQweGr7nA9eXP9J1eebHLkLEUjschFOTUbTHl4583PLMdrS3c556jcf2/JSsawQivi2/lMjdFgQOfkSNitibAmR3DnJc1WyuUnpqeFg1RqA8msobEJO45W4L/bS/HGin3Yuf0w6uvqnVPNTYvF0rljcKaiBkNmz8Opc9XOr4WGh6JH7yzMKMrCqM5m2JIj2Oh0oEgCqQ46MGzVHqonb67/5MqUTY6cpWgkFrkopyaDKRsH3Hj/R1j3VcvDOw3BBljzLJhgt2J0lxTER4Zdde7KmzaJUaFIMBm5wNFklVx9UnpaOEilN1DMausbsOVQOd764ijeW7EXB/aUorGhZZfEIT3T8N6c4QgPvbB5yKnyGlw7Zx52HjrjpDCGGNGpSxom2bMxrhvfye1IjQRKHXRkzGo+Vk/eXP/JVSqbHDlL0UgsclFOzQUrPVOFkjvex8HjLQ/vNIYa0aVbJqbZszC6ayo68+Gdmsu79IT0tHCQsgsEs8raBqzfdwavfn4YH63ch9JDJ6Dcttb8+v7wLnjmx0WXPLxX2Vp6/G8X4tPNh53H8jN57lVGINSBeyNX51l68ub6T65G2eTIWYpGYpGLcmoq2Lb9p3DdXfNRfr7VwzsjwtCnr/LwziyMzE9BViIf3qmppHtpMnpaOEgR+tvsXFU9Vuw+hVc2HsaSVXtw6njLOzPKHH/3/UH42dgeV5yu0gz97NnVePaj7S3HtNpdcVqfNAzk7ortlou/66DdAWrsAD15c/0nV7xscuQsRSOxyEU5NRPs442HMOmih3eaYiIxeKCND+/UTJZ9NxE9LRykVP1lpjQnZeW1+HSnskX0Iaxauw8VZyuc0woONuC1Xw/FmIJsl6b6p/lf4lf/WI2W93+A1s/JsucmIpbPybqipb/qwKXkavAgPXlz/SdXwGxy5CxFI7HIRTk1EewvH36J25+9dFFyTaENswZkQFmU8OGdmki1zyahp4WDFKo/zJQG5+DpaizcUYaXVh3A55v2o7qyZRMBU0QIFj80Gr1tiR2a5ocbDmLq7xahvtVneaJiTSgssPKPJu1I+qMOOpRcjR2sJ2+u/+SKl02OnKVoJBa5KKeqgykLnNv+sQZ/++DLlnkEAea0RIyw52C68vBOGx/eqeok+2nwelo4SBH72qyxqQk7S89j3vbjeGPlPmzfegh1tXXO6aQlRWH578YgLcHk1hS37DuFYXfNR0Vly+2v4ZHK7a9WzBychRGdk5GZwNtfL8b1dR24lVwNnaQnb67/5AqXTY6cpWgkFrkop2qDKR8Unvy7RVi06ZBzDsoHhTOUh3cWWzGppwV9s2L48E7VZti/A9fTwkFK2pdmjY1N+FLZIvrLY3hjxX7s2n4IDfUNzqn0zUvGgvtHIjrCswd6Hj1V6djI5PCJltvfQkJD0KV7BqZ9s1NjPjcyaVNCvqwDqdpVcxw9eXP9J1epbHLkLEUjschFOVUZ7HRFDa6bMx87Dp52jj84JBh5XdIxpSgb43pwy1d3EqtsQlV5+YfBuxMuYM6JjASCgjo2HD0tHDomc+WjfWmmbDKwfNcJvLD+CD5Z9jXOnz3vHNjE4hy88PNrYAw2iEytoqrOsSX9+q+Pt/y8CQ6GtZMFE+3ZGN89FT3TYxBilLne5Qatpu9NpQ7M5guzKC0FTO69kSaSO1eDuPMzwtXY3j7Ol9933p5Le/G5/mtPyPWvs8lx3cqnR7LIfcodcBfbe+wcSmbPw8mzVc6xOR7e1ysLM4qzcOM3D+8zdHRVG3Az9e2AlEWU3Q6sWuXb6/riasXFwPLlHWt09LRwkMqBL83OVNZj2a4TeH7dISxdvhOV5Re6805psdj8x0niz7ZSHi78/aeX4c3lu51cysOF07KSMarEhmm90tA/OxbhIcFSnM44Wv7eFMdyM6A7PyPcvJT4ab78vhMffAcDcv3XQbCrHM4mR85SNBKLXJRTVcFWf1WKUfd9hOralieXR0RFoGDAhQ8DX5+fDEtcmPgCR1VIbg629S9KN0ME9GkVFR37i7KeFg5SifOl2ZWanJ+M6oYnbh4sNaVL4jz8xiY89NrGNv+emBqP64tsmNkvHYNzEhAdfuEho1IvrX9vSjl5GqejPyM8vZ7U+b78vpMas7txuP5zV+7S89jkyFmKRmKRi3KqJthry3bjh08vhXIvfvMrJiEa9kE2zCpIxzWdkpBo8uz+e9VgeGGgrX9RquUWk/YYWt8209EFjJ4WDu05uvp1X5r5q8lRLF5fvhs/eOqin0Xx0SgutGJWQQauyU1EUnSYq2ztHqe270013a7myc+IdhPnowN8+X3noyld8TJc/8llgE2OnKVoJBa5KGfAB1N2UHvw9U2Y+8amNmNNSk3A8GIbZvRLR6EtXvyvpwEPIzxALf6i9GROnpwrnBrVhPOlmT+bHCUha3aU4sZ7L31XecCAbMwamInhnVPE3lX2patEsalpvGoa65Vyo4U5uFp3XP+5KtX+cWxy2jfyyxEscr+w++WiyjMqvvfkUry9co/z+o774LNTMMZuw9TeFvTPikWYF+6D98uE/XhRLf6i9GROnpzrxzT69dK+NPN3k6NA7ys9h5I75uFE688HhoWie69MTC/OxqjOZuSkRMDTzwf60lWigNQ0XjWNlU0OwPWfxHfohRhscuQsRSOxyEU5AzaYsqPRiPs+xMadZc4xBhuDYetkwYTibEzsbkH39Giv7mgUsDheGJgWftlfzOLJnDw51wvpUUVIX5oFQpOjJOXM+RoMnfMBth841ebnlLLT4+TibIwX2OnRl64Shaam8apprGxy2ORIfH82x2CTI6kpGItNjiBmgIY6cuq84y+kRy56NkXXHhmYWmzFmK4p6JRigsHQwX2BA3S+gTAsLfyyZ5Pj30ryZQ0FSpOjiNfWNWDKo4vx8YaDzgQ4ntllS8G3im2Y3MuCPpkxbr/j7EtXiQpS03jVNFY2OWxyJL4/2eRIKnohFpscL6AGUMjNe0/ieuUp41UtTy5vfsr4rMFZuIFPGfdKtrTwy55NjldKw+WgvqyhQGpyFCDls4O//Nda/HnethavICAlLREjinIwo18aBtriYQrt+BbTvnR1OdlXOVBN41XTWNnksMmR+P5kkyOp6IVYbHK8gBogIed/dgDTHl0M5ZkUza+oWBOKHDuoZeDavCQkx4Ryi2gv5EsLv+zZ5HihMDoQ0pc1FGhNTjPT3xZsx21/XwXl2TbNr7ikWFxbaMPMggyU5CQgzhTSAVXAl64dGtgVDlbTeNU0VjY5bHIkvj/Z5EgqeiEWmxwvoAZAyOcXf42f/mk5Wq0NEJ8ch6HFOY7nT9hzExATIfv8iQCYdsAMQQu/7Nnk+LecfFlDgdrkKBlYtOkQJs5diLr6lj/WmGIiMajAhpsGZeK6Tkkwd+CPNb50laggNY1XTWNlk8MmR+L7k02OpKIXYrHJ8QJqAIRMnPECKmsuPEhptDgAACAASURBVORT2UHNnJGIkcU2TOuTjoHWOES6cZtHAExLNUPQwi97Njn+LTdf1lAgNzlKFr48cBrXzZmPc+drnEkJiwhD7z5ZmFmUhRGdzchODHfpXWlfukpUkJrGq6axsslhkyPx/ckmR1LRC7HY5HgBNQBCRkz8h3MUqZnJGDskB5N6pGJwbjxCjR2/jz0ApqSqIWjhlz2bHP+WnC9rKNCbHCUTx89UYcjs97G/tNyZGGOoEZ27KRuoZGNs11Tkp5oQ3M4GKr50laggNY1XTWNlk8MmR+L7k02OpKIXYrHJ8QJqAIRs3eRk5aVh4jU2TOyWiv7WWI+fMxEA0wv4IWjhlz2bHP+WmS9rSA1NjpIN5d3p0Q8swJrtx5zJMQQbYM2zYLzdiok9UtErPeaqW+H70lWigioqgOjoC5FKSwGTSSKqd2IotmazOsZ6tSaneQ6KfSB7e5pFrv88FWw5n1tIy1mKRmKRi3IGTLDoKf9EfcOFT+QYQ4zI75qOqfZsjO1mQWcX/toZMBNR6UDUtpByhdmTOalpoeaKhS+Oab1g9PZiSy1NjuLe2NiEW/68HC9/stOZBuWW3NTMJIxWHmrcKx0FtliEX+Ghxp7UsS/yfvE1jh9vaRz8cX09X9Pb33f+tuX6Ty4DbHLkLEUjschFOQMm2Pee/BSvL9vtHI/y187sHDPGldgwqYcFvTKieduaF7OltoWUKxSezIkLNVeEr3yMtxdbampympUefXsz7n15fRu0RHMchhblYGb/dBTbEhB9mc1VPKljz7Lo3tn83nHPzdOziouB5cuVz7R6Gilwz+f6Ty43bHLkLEUjschFOQMmmPLXzp/+dSVeWLSjzV87zRlJGGW3YVrvdBRYYxHBDQi8kjO1LaRcQfBkTlyouSJ8+WN8sdhSY5OjaP1n1V585/ElaGhs2UcyOi4Kxd9sk39NXiKSY8LawHpSx+5n0f0zle2zy8ounB8ZGdiLbi3crtacqUC3dr+iWs7k+k9C8UIMNjlylqKRWOSinAEX7PF3v8Ccf69rM66ElDgMczxQLx3F3EraKzlT20LKFQRP5qSmhZorFr48xheLLbU2OUoe1u88jhvu+RBV3+wmqfxbhCkc/ftlY+bgLFyfn4yM+Jad1zypY1/mXY3Xoq26ssb1n1y+2OTIWYpGYpGLcgZksP+u3Y+Zj33S5qGgyl87Bw+yYtaADMdzJpKi+VBQyeRp8Ze9FuckmXM1x7pSk/PjkV3x5C1FAT+1g2XlKLljHkpPVzrHGhIWgm49szC9KAuju5qRmxLp2HSFdey9dNLWe7beiMz1n5wqmxw5S9FILHJRzoANtmn3CVx/9weorK5zjjE8Mhx9+2VjVlEWbrjor50BOxGVDEyLv+y1OCeVlJPXh3mlJic8NBiHnp8FU3iI18fg6QXOVdZi2N0fYOvek85QwcZg5OSnYVKJFeO6mtEzIwbVVUGIirpwiLc/6+TpnNR2Pn9GqCtjXP/J5YtNjpylaCQWuShnQAc7dKICQ2bPw9GT59v8tbNrjwxML7ZidNcU5KWYuMW0QBa1+Mtei3MSSLUmQlTUNGDlrpN4ceNhLFy6E+dOtTyLJjMlGsvmjkFqfGTAz7WuvhEzHvsE89ftd441yBCEjOwUjLXbMKV3GrokxSA+9sKzwtjkyKaUPyNkPb0djes/OWE2OXKWopFY5KKcAR+svKrWcf/657tPtPlrp62TBZPs2RjfzYIemTEwtvNAvYCfqJ8HqMVf9lqck5/LJGAu39TUhIOnqvHx12V4edUBbNq0DzWVNc7xRUeGYvHDo9EzOyFgxnylgShzueul9Xj8nS1tDklJT8SN9hxM75OGX38vHp+tCWaTI5xN/owQBvVyOK7/5IDZ5MhZikZikYtyqiJYfUMjbnr8U7y3em+bv3amNf+1s5cF/bNiEXaF50yoYpJ+HqQWf9lrcU5+LpOAurzSHBw/V4slu07g5bUHseazfag42/Kur9FowJu/uR4j+2cG1LivNJjnF3+Nn/55OZRNL5SX8o5O9742zLRb0SM8BTcUmtjkCGeSPyOEQb0cjus/OWA2OXKWopFY5KKcqgmmLGjue3UjHn3r8zZjTrYkYHhxDmb0TUOhLR5R4UbVzCmQBqrFX/ZanFMg1UygjEX5fM7K3SfxyobDWLJ6D06XnW35YwiAx24ejJ+O6ubxcJvQhEq0bBTgccDLBHj30yO4+ellzq906W3F9BIrhqSaUdQ9ik2OMDp/RgiDejkc139ywGxy5CxFI7HIRTlVF+ylT3fhx39chsbmP3cCiE2IRkmhDTMHpOOaTklIMIWqbl7+HrAWf9lrcU7+rpNAvX5lbQPW7juNNz4/go9W7MWxwyeAlkfR4JYbu+HJmwsR5OaTEpUGxw47VmGVVwkKTgzHF7dMY5PjVeWW4PwZ4SNooctw/ScEyefkyEFKR2KRS4uqL96KL49hzP0foaauwTn4yKgIFAywYlZhJoZ1SoYlLsztBY36RDwfsRZ/2WtxTp5nWrsRausbsPlAOd7aehTvrtiLQ3tK0djY6JzwsD4ZeHv29W7d1noe5xGFb7Y48ybhiXiE3/J7NjneNG4Vmz8jfAQtdBmu/4Qg2eTIQUpHYpFLi6oz3u6jZx07r506V+2cQGh4KHr2zsKMoizc2MUMW1IEGx0X06vFX/ZanJOL6dTtYQ2NTdh+tALvbTuKt1bux66vjqC+rt7pkZ8RhyUPj0FCdFiHjFo3OaUohQmmDp3f3sFKfDPMAJuc9qhEv86fEaKcXg/G9Z8cMW9Xk7MUjcQiF+VUdbBT5TW45s552HX4jHMexhAjOnVJxyR7FsZ1s6CrJQrB3Hmt3Txr8Ze9FufUbiJ5gONW1n1lVfhgRyleXXkAW7ccQG11rVMmISYcy+eOQY4l1mWt1k1OBSq80uQ43ilik+NyTiQO5M8ICUXfxeD6T86aTY6cpWgkFrkop+qDKbesTfjtQizZfNg5F4PBgMwcM8bZbZjcw4LeWdEINV54zgRflxfQ4i97Lc6J9euagLJRydEzNVi0swwvrzmIz9bvQ1VFlfPksNBgzL9nJIq7pboUkE2OS0yqO4g/I9SVMq7/5PLFJkfOUjQSi1yUUxPBlAXNz55djWc/2t4ynyAgNT0JI+02TO2ThkHWeESGstG5UsKVhwxGR1/4amkpYJK9G8cvdaYsYMzmC5fmQxT9kgK/X/TU+Vos3XkCL68/jOVr9rZ5aKghKAjP/t8QzLwmr91xsslpl0iVB7DJUVfauP6TyxebHDlL0UgsclFOTQX70/wv8at/rG69qRLik2NxXVEOZvZLhz03EbGR3GL6ckk/frylIdBUUXwzGTY5Wsyqa3OqqK7H6r2n8dqmw/h4xV6cOHaqzYm/mdwH987od9XP77HJcc1abUexyVFXxrj+k8sXmxw5S9FILHJRTs0F+2jDQUz53SIoDxBtfkXFmlBYYMWsQZm4Li8JKTGh3JDgosxruckpLgaWLwfc3D1Yc98jepyQclvrhgNn8cbmo5i3Yi+OHDiOpsaWPabHF9nw4m3XwhhsuCwPmxxtVg2bHHXlles/uXyxyZGzFI3EIhfl1GSwL/afwtA581FR2fJh4/DIMPTpa8XMwVkY0TkZmQnhbHRaZV957FBZ2YV/iIzUVkOgtflo8pvWB5Oqb2jC1kPn8M62o/jPyv3Yu/MoGupbtqHvm5eMBfePRHTEpc/ZYpPjgwT54RJscvyA7sEluf7zAO+iU9nkyFmKRmKRi3JqNtjRU5UYMvt9HCqrcM4xJDQEXbpnYJrditFdUpBvNsHAndc0WwOcGAUuFlB2XttZeh7zvzqO11fsw/ath1BXW+c8zJJowrK5Y5CR1PaZOGxytFlLbHLUlVeu/+TyxSZHzlI0EotclFPTwc5X12HkfR9h/dfHnfMMDg6GtZMFE+3ZGN89FT3TYxBivPwtKprG4eQooFMBZaOSg6ersXBHGV5efQCbNu5HdWXL87ZMESFY/OBo9M5JdAop20ZH48LOHHxOjnYKh02OunLJ9Z9cvtjkyFmKRmKRi3JqPlhDQyO+//QyvLl8t3OuQUFBSMtKxuiSHEztZUH/7FiEh3DnNc0XAydIgW8ElEanrLwWnyo7r312CKvW7kPF2ZZ3fZXDss3RCAsJRkSoETfdmI5bhxV43S/oeCLCfvKI8zpdelsxvcSKIalmFHWP4i6BwhlgkyMM6uVwXP/JAbPJkbMUjcQiF+XUTbCHXt+Eh1/f2Ga+ianxuL7I5th5bXBOAqLDufOabgqCE6UAgHNV9Vix+xRe2XgYS1btwanjLQ8Wvhioach61Nz6NyC4ZcMCUcSqMMT/5neoOvTNXu4AlCZn5hAripPNKO7JJkfUGwCbHGlR78bj+k/Ol02OnKVoJBa5KKeugr2+fDd+8NRSNLbaVSkmPhrFhVbMKsjANbmJSIoO05WJvyer/EX9Si/lHTe+KOBtgcraBqzfdwavfX4EH67ci9JDJ3CluuzbOQHv3HsdosJDRId15MR5DJ+9GKUnK51xwyLCMGhQLm4anImja5Pxm1vD+E6OqDqbHGFOr4fj+k+OmE2OnKVoJBa5KKfugq3ZUYob7/0I1bX1zrlHREVgwIBszBqYieGdU2CJC+POa16ujOq6Buw7UYUzVS15aH3J4CAgPS4Cljhu9+3lVDA8gNr6Bmw5VI63tx7FxxuPoKy0HE3KE7eamnDmVDnqW/28yEyOxrLfjUFqfKSI3abdJzD8ng9wvqplA4TwyHD07ZeNWUVZGJqTjDxLOBobg9jkiIi3BOE7OcKgXg7H9Z8cMJscOUvRSCxyUU5dBttXeg4ld8zDibNVzvmHhoWiR69MTCvOxqjOZuSkREB5Ijpf8gLlysMZ95zCsn2ncfxczWUvoDyvpKvZhOvzkpGfakIwd8GTTwQjthFoaGzCjqMVWL7vJPacqkLzG77rd55wbE5QU9VSq9GRoVj88Gj0zE7wSPG/a/dj5mOfQPnsYPMrOi4KRYOsmFmQ4XiuV2RwGKK+2eyND7X1iPuSk9nkyHp6OxrXf3LCbHLkLEUjschFOXUb7Mz5Ggyd8wG2H2h5+nmwMRh5XdIxuTgb43tY0NUSxcW1cIWcKK/B0t0nHR/23vjFUVRWtOxq1fpSQYYgmFPjMLowC5N7pKJnRjRCjdwcQjgdARFOuWOxsuUuLb+OSblN7UxNLc5VX3hXRWl8tpaexSvrDmH1un04f+68c3xGowFv/uZ6jOyf6daYn3jvC9z5wro25yakxGFYUQ5m9EtHcW4CYiKM/NyIW7quncQmxzWnQDmK6z+5TLDJkbMUjcQiF+XUdbDaugZMeWQxPt540OlgMBiQYUvBt4ptmNTLgr6ZMY4dlvjyTEBZPB45U4OFO47jlbUHsX7DflRVtLyTdrnoymdyzBlJGGW3YVrvdAy0xiI8lLnwLBOBdbbS4NjtwKpVgTUuZTTFxcDy5cDZqnqs3H0Sr2w4jCWr9+B02VnnYJX3eh+7eTB+OqqbyxNQPhP407+uxAuLdrTEuajWC6yxiPim1rkQd5m2wwfStsNkfj2B6z85fjY5cpaikVjkopy6D6Ysvn/1/Fr86f1tLRZBQEpaIkY4/qKahkG2eERyce12rSgPYNxzvAof7CjFayv3Y9uWg6itqXU53uX+uu3yyTwwoAVaLzIDcaDNt4cpmxOs3Xcar286go9W7EHpkZNQPrLT/Lrlxm548ubCdj/LV1VTj7EPfYyV2462/GEl2IDsHDPGl+RgYo9U9LroXUsuxL1XGbT1nq03InP9J6fKJkfOUjQSi1yUk8G+Efjbgu247e+rlM8ZO19xSbG4ttDmuDe+JCcBcSbZHZX8ge/tW4MiI4HWH2VSbvfZfrQC72w9irdW7sfurw6job7BOXXlsw3X9UpD608/nSyvwYpWi0DlYOVzCsWDbLhpUCaG5CYgmbvg+aN8xK/ZepFZWgqYTOKX6HBAZUxm84XTWn8GRtmcYPOBcry59Sj+u2IvDu4pRWNjy2dphvZJx39mD7/iO79lZ6twzZ3zsPfoOeeYjCFG5HdNx1S7FWO7paLzZT5/xoV4h1Po8gm0dZkqIA7k+k8uDWxy5CxFI7HIRTkZrJXAok2HMHHuQtTVtyxcTDGRGFRgw6xBmRjWKQkpMerd7csXtwY13+KjNDo1dQ3YdPAc3tpyFO+v2ItD+463WRSO6J+JN349DKGXuR1w464yDL/nQ1R+89kIJU3KrWtjr8nD9N4WDMiO5W2EGvjuDcRF5tXG1Ny0v7ftKN5euR87vzqC+rqWHQLzM+Lw6W/HID6q7Vb0Ow6dcTQ4ZytaNi9Qtoju2TsTM4uyMLKzGdakiMu+ExSIRhooPccUaKuuTHL9J5cvNjlylqKRWOSinAx2kcD2g6dx7Z3zce5828VI7z5ZjsXIiM5mZCeGt3tbSiDC+urWIOWv3whpwLq9p/HqxiNYsGoPjh8+2Ybk1m/1wCPfHXhVx4MnKpB/y+vO8+KS4nDjdXmY1TcdhbY4mML48NZArLOOjCkQF5ntjUm5/XJvWRU+3FGKV1cdwNbNB1Bb3XL7ZUJMOJbPHYMcS6yDYsmWIxj/8MdQPgPY/DJFR6KgQHlnMgNDOyUjNfbKfzxpbzwd8eaxbQVoq66K4PpPLl9scuQsRSOxyEU5GewyAsfPVGHI7HnYX9rqtpJQIzp3y3BsMT2m64XbSgwq29bYm7cGtb7Fp+xMPdYfOolXNh7FohW7cbqs1VPkg4Df3zIA/zuit0u1Z//Nf7FhZ5nj2NZNzuAcfk7KJcAAPygQF5mujEn5LN/RMzVYtLMMr6w5iHXr912ykUbvnCRU1dbj60Ot6h9AbGIMhgy24dsDMmDPTUR8O7fBujKeAE9zwA6PtgGbmssOjOs/uXyxyZGzFI3EIhflZLArCFTW1GP0AwuwZvsx5xGGYAOseRZMsFsxQdnWOD0GoUaDagy9+Qu9dezth89j/teleGX5Pnz5+V7nB7SDgptQM+dJnOuzFia49uGLIXe8j8++Ps4mRzVV1rGBerMmOzaSlqM7MqZT52uxdOcJvLL+MJat2Ytzp8qvetlkZUOT4hzM6GNxbGhiCm//3ciOjMfdOev1PNqqK/Nc/8nlS1dNTnV1NebOnYtXX30VBw4cQEJCAkaOHIkHHngAGRkZHVbdtWsXHnnkESxcuBDHjh1DdHQ0OnXqhAkTJuBXv/pVh+O1PoFF7hEfT+6AgLLV6y1/Wo6Xl+x0nqVsa5yamYTR9hxM7ZWGAlsswlWyxbQ3f6G3jr3tUAXe/+oYXlm2H19/sc9pV3vfY2js9RUqUMEmpwN1qOVDvVmT7rp1dEwVysNt957Ga5sO4+MVe3HiWMuzt5rHoDz3KcOagrH2HEzp4Nb0HR2Pu/PW43m0VVfWuf6Ty5dumhylwRk2bBhWrVoFi8WCkpIS7Nu3D+vWrUNycjJWr16N3Nxcl2XfeecdzJw5EzU1Nejbty/y8/Nx8uRJfPHFFzCZTFAaIE9eLHJP9HiuOwKPvP057nt5Q5tTE81xGFqUg5n901FsS0B0RPt/kXXn2pLnePMXuitNTvVztwMJZ9nkSCZV5bG8WZPu0rgzJmWTjQ0HzuKNzUexeMMhnDyhfDDtwlaNyrO3UtPi8K2BGRjXzYwe6TEdesiwO+Nxd+56O4+26so4139y+dJNk3PPPffgwQcfxODBg/Hxxx8jKirKofj444/j9ttvx5AhQ7B06VKXZDdv3oyBAwc63rl59913YVee8vbNS9lqc+PGjRgwYIBLsa50EIvcIz6e7KbAf1bvw3f+8InjCejNr+ZtjWcVZODavEQkxbTdUcnNS3ntNG/+Qu9Ik1OK0kveybnS7Wu8Xc1r5RAQgb1Zk+5O0N0x1Tc0Yeuhc1i67xT2nKp0bkcfYghC1xQTrslNQm5KJAyt91h3YZDujseF0Lo/hLbqKgGu/+TypYsmp66uDikpKThz5oyjAVHeeWn96t27N7Zs2YL169ejf//+7eoqDdHy5cvx/vvvY8yYMe0e784BLHJ31HiOhMAGZVvjuz+A8kC/5leEKRz9+2Vj5uAsXJ+fjIz4wN15zZu/0DvS5FwuF02tn6zY6gA2ORKVG7gxvFmT7s7akzEpO68pGxKcqKhF899DjEFBMMeGITk6xK1dGT0Zj7sGejmPturKNNd/cvnSRZOzZMkSDB061HE72uVuI1Pe4VHe6bn33ntx3333XVV3+/bt6Natm+P2tB07dshl4qJILHKv0TKwCwIHy8pRcsc8lJ6udB4dEhaCbj2zML0oC6O7mt36a60Ll/b4EG/+QldDk+PtB6F6nCAvBrj4Ia1evFSHQnuzJjs0kFYHB9qYAm087roG4nm0DcSsXHlMXP/J5UsXTc6TTz6J2267DVOmTMEbb7xxid78+fMd78iMHz8eymdtrvZ65plncOutt+L//b//h8ceewyvv/664x0g5YPavXr1wtSpUxETE+NxhljkHhMygIcC5yprMezuD7B1b8uzX4KNwcjNT8PEEivGdTWjZ0bH7rv3cEgune7NX+gdaXL8cbuaLx6E6lIS/HRQ64e0+mkIl72sN2vS3XkG2pgCbTzuugbiebQNxKywyfFFVnTR5PziF7/AE0884Wh0lM/gXPxSPmPTp08f9OvXDxs2tP3g9cXH/s///A/++te/4pe//KXjdrWL381JSkrC22+/7fiMjycvNjme6PFcKYG6+kbMeOwTzF+33xnSsYNSdgrGlig7KKWib2YswgJo5zXlIZ3R0ReGW1oKmFzbxdklMmWxYDZfOPRKu6v5c+OB1osZlyakwYOU/EvmXIIoEBeZgTamQBuPRN4DJQZtAyUTro2D6z/XnFw5ShdNzi233IJnn30Wc+bMwUMPPXSJi3ILm7L1syu3oE2fPt3x7o3RaER8fDz+9re/OW6FKy0txf33349XXnnF8e/btm1z7OLW3qu5mC8+bvfu3Y7b65Q4fFHAnwLKAwHnvLQeT7yzpc0wlGdh3FCcg5kdeBaGL+Zx/HhLI+LN612pyamf+S7qJ8/zy+5qrRcz0g2eNy09jd26+WST45pmoC18A208rimq4yjaqiNPzaNkkyOXL100OT/60Y/w3HPP4a677nLssHbxa+fOnY4Gx5UmR7nl7a233nKEWLBgAf4/e+cBHVd17f2/eu9l1KWRJcu9Si4qLtjYxgVjbFwhkFCSle+RPEISei8mpJFGHgQe8MAGTDHgXrGtYrn3bqsXj3rv5VtnJE1Rm7kzZ+5c6e67VtYK1j37nPPbe6T9n3POPgsWLNAzx6qunThxYkBB1btvEjn8gpksWZbAxweu45fvpoGJnp5Hfav5DCU2xIdiVoy/wVvNLTvCLutiiBy2LeqTbxuw85oKm9JyceF0NjraOzTTa7/7ACoefB/uNl1VHA09vAoPyDWZkfq8pTg+qY1JauMx9JkdSj8ntkPJWwCJHH7+koXI4bld7Wc/+xk++ugjhIaGoqCgoI8n/v3vf+OXv/wlkpKSkJaWZrKnKMhNRkcNLUjg8MUi3P3aXrS0tmt6cfVwxbR4JTbMCMW82AAEeTmZVF2J17CZBist7bJmqYPozG5rezvO5tXg6wvF+D4tBwXZKrAS8j3PnfGh+Ob3C+Bgb2twaiRyDCIa9AWpJ3FSHJ/UxiS18ZgXkdJqTWyl5Q9Do6H8zxAh438uC5HDs/DAq6++qq7ClpiYiPT09D6kd+3ahcWLF6u3v12/ft14T/R6k4LcZHTU0MIErhdWYfaz21FV26zpycnZEeMnRmBdYgTuGqVAlL+LVYWOhRFozLP7hC4X1WHrpWJ8k5aLW9cK0d6mFYBjIn1x4PXF8HYb/G4hEjnmeUzqSZwUxye1MUltPOZFpLRaE1tp+cPQaCj/M0TI+J/LQuQYW0KalZFm52oGe1ixgbvvvhujRo0CKyfd+/nss8/wwAMPqO/iYXfymPpQkJtKjtqJQaCspkktdLKKqjXd2TvYI3Z0KNYkR2HZmCDEBbkJuvFcjHFbog92Z0hWSaN669oXabm4eCEPrc2tmq4CvF2RunEpIhXd1RD6GQSJHPM8I/UkTorjk9qYpDYe8yJSWq2JrbT8YWg0lP8ZImT8z2UhclpaWtSXgVZXVw96Gejx48eRkJAwKL2Ghga1LWaTFQcIDw/Xe/+RRx7Bhx9+iIcfflh9DsjUh4LcVHLUTiwCTS1tuPv1fUi9WKTp0tbOFhHRCtyTosTKccGYEOYBR3s7sYZktX7YOaXCqibsu1aKzZn5OHUqF431jZrxuDjZY/crd2HayMB+x0gixzzXST2Jk+L4pDYmqY3HvIiUVmtiKy1/GBoN5X+GCBn/c1mIHIaDFR1444031NvM9u7dC7fuGqOspPSTTz6J5ORkpKamasix+3DY/1asWIGNGzfqEX3mmWfw1ltvYcmSJepKaz22du/ejWXLlqG9vR2ZmZlgRQhMfSjITSVH7cQk0NHRif96LwMf7buq6ZbdGaUI88ddSVFYOykUCVHecHEc/kKHASirbcbhm+XYdKIA6cdyUFNZqxWAtjb4+Ik5uC8puo+LSOSYF7VST+KkOD6pjUlq4zEvIqXVmthKyx+GRkP5nyFCxv9cNiKnqakJc+bMwbFjx9SlnVNSUpCbm6v+bz8/P7UoiYmJ0ZB7+eWX1VvXHnzwQXz88cd6RJmt+fPnq8/kMFvTp09HSUmJ2gY7eMzE1LPPPmu8F/p5k4LcLHzUWGQC7/xwAc98fFyvV99Ab8xNjMb6KaFIHuELTxd7LqNi52B0CrxxsWnIiJ0tjD5jVNvUhoysCnx+uhD707NRrqrUM//iuql45r5Jev9GIseQBwb/udSTOCmOT2pjktp4zItIabUmttLyh6HRUP5niJDxP5eNyGFIGhsb1asy7C6b/Px89X02ixYtsS6zFgAAIABJREFUUpeV7r3tbDCRw2yx7Wp/+tOfwM7gZGVlwdnZGfHx8eoLR9kKj7kPBbm5BKm92AS2Hc/Fuj8eRLtOKWV3L3ckTo/ChoQwzIn1R4CHo9Fioff4W9ra1WdfSuqbRRc5bg52UAa6ws/N0SisTa3tOJlTjS3ni7AjLRvFeaV6pbfXzIrBh4+nwI6pJwAkcozCOuBLUk/ipDg+qY1JauMxLyKl1ZrYSssfhkZD+Z8hQsb/XFYix3gs1n+Tgtz6PqARCCdwLqsc817YgfpG7cF7Z1dnTJ4SiQ0zI3BnXADCfZwFC52mlnYcz6nG3pulyClrQIf2qh7hgzShBVuFSozyxvzYAAR7G1ciu7WtAxcKa7D10m18m5qDnJvFenfpJMQpsOulhXBzdiCRY4JPdJtIPYmT4vikNiapjcfMkJRUc2IrKXcYHAzlfwYRGf0CiRyjUYn7IgW5uLypN34ECsrqMPuZ7Sgqr9cYdXB0wOhxYerKa0tHBSJG4QZbGxujOq1p7Nr+tflUIVJP5aOmsh6dEFflsPHHxARiTWIEFscpEB3oYtT42Zml66p6bL+iwpdpubh6OR9tLW2aeQf6uOKF1ZPx+HvacvTe/t64a24MNkwOxcxoH7gKOM8k12RG6vOW4vikNiapjceoX05D5CViO0Qc1T1Myv/4+YtEDj+WXC1RkHPFScZEJlDX2IoFL+3CmZvdt3ICsLO3gzI2GPcmRWLF2GCMC/OEvd3gQqe0phk/3izD5hMFyDiWg9qqOpFnou2OjX/EqFDclxSJe8YFY3Swu1ElslnltbzyJuy+XoLPM/Jw9kwumhu1dwz1nhCJHOEulnoSJ8XxSW1MUhuP8CiUbgtiK13f9Dcyyv/4+YtEDj+WXC1RkHPFScasQKCtvQMP/PUQvsvI1vRuY2uDkIhALE1RYvWEYEyN8IKTQ9/Ka0wYFFQ2Ye/1Umw+mofTp3PRVN9khVnod2lra4swZSDuTlJi5YRgTA737Hf8vQfK5lNS06IWbJuO5ePo8RzU12hXunTfDwz1w9LZMVg/MQQJSm842ned2zHmkWsyI/V5S3F8UhuT1MZjzOdtqLxDbIeKp7rGSfkfP3+RyOHHkqslCnKuOMmYlQiw5P6Vz0/jD1+f1RuBf5AvFiRHY+3kEMxU+sDdWVt5jV2ueaukHjuulODz9BxcuVigd7mmu4sDNsyJgbMDn2pthtBkXFXhxPUS7Ws2QGCIHxYmRmPdlBBMU/rAzcgtZVUNbUi7VY5NJwuQeiIXtVX16Ow5YGQDuLq7IGFKOO6fFo65sQEI9DSu0EHP4OSazEh93lIcn9TGJLXxGPq9MJR+TmyHkrdI5PD0FokcnjQ52iKRwxEmmbI6gU2HbuKxfxwBEzA9j6evB1JmKLEhPhSzY/3h6+aIto5OXCyowfeXb+ObtBxkXS9Ge1u7ps3EaH/se+0ueLgIS/7NBfDenit44v0Mvapu3v5emM3GnxCGlGhfeLs5GNVNQ0s7juVUYttlFa4X16GtvYsJO6KkDHTD4lGBSB7hB29X4SJOrsmM1OctxfFJbUxSG49RH+Yh8hKxHSKO6h4m5X/8/EUihx9LrpYoyLniJGMSIJB++TaWvLobzS1a0cJWLuLjo7BhRjjmjPBHYVUjvjpfjG1p2SjMLdGucgBYNiMKm5+cC/vusstiT2n/mQLcu3EfWNW0nsfN0xXTEpR4YHoY7uheeWGXoRp6WDnsK8UNKK5pQI85WxsgwM0JY0M9BBUb0O1LrsmM1OctxfFJbUxSG4+hz/BQ+jmxHUreopUcnt4ikcOTJkdbJHI4wiRTkiGQVVyNlGe2o6JGe77G0dkR4yZE4J5pobiqqse+tCyUFlfojfl3KyfilfVTBZee5j3xK/mVmPPsDtTUawsHOLk4YeKkCKxPjMDCOAUi/Ywrkc228jW3dWpWt5g0cnKwNapq20DzkmsyI/V5S3F8UhuT1MbD+3eHNe0RW2vSF9435X/CmQ3UgkQOP5ZcLVGQc8VJxiREoKK2GXOf247rBVWaUdk72Ksrr5WoqlBdXqv5d7Yq8t7/S8EDd8RKZgYlVY2Y9cw25Kq047R3tEfcmDCsTorEstFBiAtygy1bmhH5kWsyI/V5S3F8UhuT1MYj8kfXot0RW4vi5W6c8j9+SEnk8GPJ1RIFOVecZExiBJpb29Vbvw6eLdSOjGkCnetvHB3ssO3FhZg1Nlhiowcamtuw9NU9OHrltmZstna2iBwRhBUpStw7LgjjQz0FVUbjMUm5JjNSn7cUxye1MUltPDw+j1KxQWyl4gnjxkH5n3GcjHmLRI4xlKzwDgW5FaBTl6ISYNu1/vuDTLy/63Kffn08nJH61lKMCPYSdUxCOmMXfT72bio2HbyhacZWnoLC/bEkmZXIDkWC0gvO/ZTIFtKPkHflmsxIfd5SHJ/UxiS18Qj53En9XWIrdQ/pj4/yP37+IpHDjyVXSxTkXHGSMQkTeHfnZfz2g6OaRZyYUG8cenMJ/DycJTxq7dDe/uYcXtp0Um+sfgpv3JEYjfVTQ5Gk9IWHi/BKaaZMXq7JjNTnLcXxSW1MUhuPKZ8/qbYhtlL1TP/jovyPn79I5PBjydUSBTlXnGRM4gQOXSjCK1+cQXyMP16/P96oCzaNmVInOtGAhn5fdYUrbMDn3My3R3Pwkz8fRHvPnTcAPLzdkTS9q8T0nBg/+Hs6GTNks96RazIj9XlLcXxSG1NdHeDh0RX+KhXg5mbWR4Ea6xBgvlYouv6BcSa20g4Pyv/4+YdEDj+WXC1RkHPFScZkSIAJnGQkIwMZ/c4+CUlIRSo3oXPqZinufGEnGpvbNP25uDlj6pRIrJsZgTtHBiDMx7jKa6a6S2qJq6nzENpO6vOW4vikNqaSEm0iLtT/9L7xBEjkGM/KWm9S/sePPIkcfiy5WqIg54qTjMmQQD3q4Q73QWdehzq4gd9XxvmltUh5ejtUldrVIwcnB4wZH4G1iRFYMlqBEYGuZpWJHmxCUktcxQo7qc9biuOT2phI5Fj+05KUBKSmdl08TI90CVD+x883JHL4seRqiYKcK04yJkMCuiJHBZVGzLB/V6Br7wZvkcNs1jS0YP4LO3Ehu1xD3c7eDjFxoViVEoXlY4MwJtgddhYoMS21xFWssJP6vKU4PqmNqbMTKC3tihhXV0rELfHZIa6WoMrfJuV//JiSyOHHkqslCnKuOMmYDAnoihxdMTPQv/NE1NrWgXV/Oogdx3M1ZtmlodNnjMBPZoZjbow/Qrz5F1aQWuLKk+lgtqQ+bymOT4pjEiteqB8iIGUClP/x8w6JHH4suVqiIOeKk4zJkIA1RQ7DzUpk3/XyLhy+UKymzy4MnRI/AhsSw7EoLhARfi7cvSLXxFXq85bi+KQ4Ju4fCDJIBIYgAcr/+DmNRA4/llwtUZBzxUnGZEjA2iKHIf8+Mwdr3z5AIsfC8Sf1hF2K45PimCwcJmSeCAwJApT/8XMTiRx+LLlaoiDnipOMyZAAiRz5lIqVesIuxfLIVFZYhr8UacpDggDlf/zcRCKHH0uulijIueIkYzIkQCKHRI5Uwl7qlcOorLBUIoXGQQQAyv/4RQGJHH4suVqiIOeKk4xJnMDft13Exq/OqiuT9TzRwV745NezMCUmwKTRk8ghkWNS4FigkZRFDpUVtoDDySQRMIMA5X9mwOvVlEQOP5ZcLVGQc8VJxiRKoKOjE4/9KxWbfrzR7wjt7Gyx6bdzsXx6lOAZkMghkSM4aCzUQMrlkamssIWcTmaJgIkEKP8zEVw/zUjk8GPJ1RIFOVecZEyCBBqa27D01T04euW2wdG98ZNp+M094w2+p/sCiRwSOYIChl4mAkSACEiAAOV//JxAIocfS66WKMi54iRjEiSw5u0D+CEzRzMyewd7BEf4w97ODvV1TSgtrlCXYe55Hpwfh3d/kQRbIy/RJJFDIkeCYU9DIgJEgAgMSoDyP34BQiKHH0uulijIueI0aKwTnWhAg8H36IX+CbjCFTawEYQn6uHPoarsYs4uypw4KQILJ4fA1cEWRdVN2J6eg9wsFTraOzR2k8YGY9vzC+DiZG+wLxI5JHIMBgm9QASIABGQGAHK//g5hEQOP5ZcLVGQc8U5qDEmcJKRjAxkiNfpMOspCUlIRaogoRP5s80oqWpUkwgKD8Cy2SOwcmwQInxdUN3Yhj3XS7AlLQfXrxSirbVNQ0wZ7InDby5FgNfgl2nKUeRIsVSxGKFO5ZDFoEx9EAEiIAYByv/4USaRw48lV0sU5FxxDmpMNxkWr9fh11Md6uAGN6Mn1p/IWTshBAlKL9jb2iCnrBG7r6mwOSMPF87lo7mxWWPby91JLXTiwrwH7E+OIkfKVbyMDgwzX6RyyGYCpOZEgAhYlQDlf/zwk8jhx5KrJQpyrjiNFjkqqAQl6uKNUpo9MSGhgEI9OJ4ix8HOVn0eR1XTggPXS/HZsQKcOJmN+hrtlkIHBzt8/9wCzJ0Q0i8cEjnSjBlLjorKIVuSLtkmAkRADAKU//GjTCKHH0uulijIueI0WuQITdTFG6U0expISBgz2sFWcpjI6Xkq61uRllWBz07k48jRbFSV12h+ZmMD/PMXyfjZnXF9upSjyJFyqWJjYsLcd6gcsrkEqT0RIALWJkD5Hz8PkMjhx5KrJQpyrjhJ5FgIpxgihw29vqkNx7Ir8fnZYuxJz0JpUbnejH69fDw2/iQBNkz1dD9yFDkWcjOZJQJEgAgQAZEIUP7HDzSJHH4suVqiIOeKk0SOhXCKJXLY8Jtb23EmvwZfny/GD2nZKMhRobNDW2J6cUIkvvjdHXCw71oFIpFjIaeTWSJABIgAEbAYAcr/+KElkcOPJVdLFORccZLIsRBOMUUOm0J7RycuFtbg+8sqfJOag1vXi9De1q6Z3dhIXxx4fQm83BxJ5FjI52SWCAxGoLqhDUVVTfB0tkewt5PR91oNd6rsS5qCiibUNGl/X1ljzh7Odgj3dYaTg501uqc+jSBA+Z8RkIx8hUSOkaDEfo2CXDzi5iTq4o1Smj2Zw87YMzm9Z97R2YlbJQ3YeaUEX2bk4uKFPLQ2t2peC/ByRdoflsIv0BbucFf/u+5ZK3PGLNQL32fmYO3bB9TN7B3tMSV+BDYkhmNRXCAi/AYvgS20L3qfCFiTACsUUlzVjMNZ5ThfXAuFuxNmK30wLtRTs7pqzfFZs++e7bYZ+VVQ1bVYcygIcHPEzAhvzFD6wMPZ8H1jVh2sTDun/I+f40nk8GPJ1RIFOVecgxoTM+kVb1bi9GQOO1NFDpsZS6gKK5uw73opNh/Nx6nTuWis77pzhz3sstCtr8zBnJFRJHLECQXqRUIE2Ion+zJArId1lV/RpC75vuVYPnJyK+Dh6YJ5U8OwekIwpkZ6wVmmKwfqwim3yvHpyQKcvnQbDXVNYrml335cXJ0weUwQNiSEYlasP/zcHK06Huq8LwHK//hFBYkcfiy5WqIg54qTRI6FcFpL5PRMp6y2GYdvlmPT8QKkHc9GbWWdZqbsbE7tv38D+FXRSo6F/E9mpUWgR/znVjSipb1DtMG1dXTiREEVvk7LxY2r2st7/YJ8MT8xChumhmKG0ldWKwd9SuCfyEZ9rbYEvmjO6acjF3cXJMRHYcOMcMyPDVBvK9Qt2mLNsVHfAOV//KKARA4/llwtUZBzxUkix0I4rS1y2LRqm9qQdrMCX54txP70bJSrKjWzbfn9v9Ax4wyJHAv5n8xKhwBbubmhqsfuayU4nV+Dxmbxzn4wOXXxugr5WSp09BJXnj4eSJoRhQ0JYZgT4w8/9+G/csAEjv5lxnlobrTuNrXekero7IhxEyKwLikCd8UpoAxwga1OdUrpRLb8RkL5Hz+fk8jhx5KrJQpyrjhJ5FgIp7VETn29/oSKahpxMFuFzzMLcOr4LbS1tKlfaPnVh+hIOIc6txLNJa/mjFkoRjqTI5SYtN9vbe9AU6t4KyQ9NJzsbeHYXTWwP0JsJeVSQS2+vViErUfzUJRfoVeQQwyqzY3N6m2k/T1s5SA+PhL3T4/A/JHDe+WAbRW8drse2y7fxpa0HFy/ol3ZYmyYHydG+0NsPcFccz67XF2lsuexc7BD7KhQrEqKxPKxwRgd7A47W20ZfjHihvroS4DyP35RQSKHH0uulijIueIkkWMhnOYIBnPO5PROED7a0oS2MBU+Y+dzdEXOsTvQUaREXWc9iRwLxYAczLLkvay2BReLaqGqb4Z4p1266Pq7OmBskAeCvZ373VaUV96oXsHZlJGP0yduoa21S+Rb42Ep8q+Wj8emQzdRVq09J+fo1LVysCYpAovjFIgONH7lgCXoDSLu9DL1UtmWtnacL6jFNxeL8V1qNvJ6rWwljwvGtucXwNnROgf+W1rbsfKt/dh/pkATGra2tgiLVmB5shL3jQvGxAgPONpT5TVrfHZ6+qT8jx99Ejn8WHK1REHOFSeJHAvhJJEzOFhaybFQ4Ilolgmcgsom7L1eir2XS6Gq1CbuYg3D18MJc0b5DygOckobsfs6Ezl5OHPiluirOD0c2Dm4L34/D4vjI1BV34w7ntuJK3kVGkx29naI6V45uGeccSsHTOAkJwMZGWLRBpKSgNRUCFptaWxpx4mcKnx5rgg707KhKijTW9l6cH4c3v1FktVLarN4/s2HmfifnZe1QG0ARYgfFqVEY82kEEyP8oGrIwkd8SJOvyfK//iRJ5HDjyVXSxTkXHGSyLEQTmuJnP62q/2YXYLNmb1Wcmi7moU8Lw+z7JzLzZJ6dbnyz9NzcOPqbTQ3NYs+eQdHB0SOUGBlUiTu7UccsG10Z3JrNCsI+dm39S7KZQP+/aqJg255M3dSHs6OWJWsRIivm8YUWzm47w8HsPd0vv7KgTIQdycrsWp8MCaFew56Zwv7rLt3VYIX9amrA9y0Uxm075rGNqTfqsDnpwtxICMLFSVVeu+/+eA0PLF8vKjjN9TZv3ddxpP/Oaq3Kukb6I25idG4f2oIEqP94OlinRUnQ2Mf7j+n/I+fh0nk8GPJ1RIFOVecJHIshNNaIkd3Og0t7ci8VYktF4qwOy0LqsJy9Pzlbvn9u+iYcZoKD1jI/8PZLDvncjG/Bt9fuY2vU3OQfaPYaiskjLN6W1FUIJYxcTAhGJN7iQN2FuRKcR2+u1iMr9NzcfNqod54R0X44Mc3lsDbzUlUt7GVg99+dAzvbr+k7dcGCGQrB8nRWMtWDpQDrxzoihyVynjhYcokWV8KRVdLY0ROzzbGH2+WYdOJAhw9loPaKm2FRzs7W2z+7R24e3qkKcOxeJs9pwuw6q19aGvTnjOLHReJNSmRWD46COPCPCw+BuqgLwHK//hFBYkcfiy5WqIg54qTRI6FcFpb5FQ1sG9Qy7HpZAEOZWajsrRaM1NbWxs0/vMpdAaVkcixkP+Hq1l2OPt0XjW+Ol+MH9KyUZRb0mdlxCpz7xYHCxOjsW5KCKYpfeCms62IrTxllTRi5zUVvkzPxcXz+Whp1lb18vdyQepbSxGl8BR9+O/tuYIn3s+Abm0Cb38vzJmhxPqEMKRE+8LbzaHPuHRFjjHCw5yJCemLCZz87ru6Nh3Nw5lTuWhq0N6B4+rsgP2vLcbkEf7mDMnibS/kVmDaE1s1/USNDMWq2UqsGsvO54gfJxaf8BDogPI/fk4ikcOPJVdLFORccZLIsRBOa4kclmCU1LRA/Q3qsXxknshBXbW25Jq9vS0+fSoZK6aO7PpWFnVUeMDMGGAJtKq6BVX1rRC/vpiZgxfQXH3XTHUjtpwrxr70LJQWa8+UMDMb5sbioXkjBZ3XENB9n1e3Hc/D33+40EcczJoRhfsTwvuIAzb+4qpm7LtWik3H83DyZC4a67TniNih912vLMKMuO4lC3MGJ7AtO/B+78Z9aNVZOXDzdMX0BCXunx6GO2IDEOjpqFdcQYjwEDgckwWVehujqh47rpbgi/QcXLlQgNaWVo29YD83HNm4FGH+VthnJxAC84Xn6o9I5AjkZsnXKf/jR5dEDj+WXC1RkHPFSSLHQjitIXJYEpdX3oQ910vx+dFcnDmdC1a+tudxd3VUb8tRRjrBHV1JBokc8wKAJUKXCmuRlleB3Err3thu3kyMa52tqkPasWxUV9RqGrA7RN57fBbunxNjnBGObx04W4gVbzJxoC3/2yMONnSLA0UvcVBe14JD3duo0jNzUFOpMxdbG/zvr2djTcoIjqM0ztTlvErMfW47auq1K0xOLk6YOCkC6xMjsDBOgUg/bRU5qYmcnm2MWy8X49u03D7bGCeN8MfeV++Ch4v07wOqa2zFwpd34fSNUo3zokeFYdUsJe5lKznhtF3NuKjm+xblf/x4ksjhx5KrJQpyrjhJ5FgIp9gip6OjE9fZN6hXVPgiLRdXL+dr7sRhUwwLcEfqW8sQ5OOKgcZmzpiFYhwO1dXY1q1TedXqlY0fzxahorwOessKQqEMgffr65r0Vj+cHOyw7aWFSBkTbLXRX8mvxJxnd6CmXivoe8TBOiYORioQ5a9fYppdlHs0qwKbTxdif0YOym/rr0o9t2YKnl8zWfQ5qaoaMeuZbchTaYWXvaM94saEYU1yJJaOCkJckJu6EpmURE7PNsYt54uxrZ9tjMtnKvHZb+bA3s5WdKZCOyyqqEfK09tRVKY9Q8QuCJ0Sr8QDiRFYMDIQYb7OQs3S+xwIUP7HAWK3CRI5/FhytURBzhUniRwL4TRHMAi9J4etJlworMHWS7exNS0XOewgeLv2m+2EkYHY9fIiuDl37esnkWO+0+tYkpxdiS/OFGJvWjbKeiXJ5vcgfQu+ns7qrUcjgr2sPtgStTjYjlxVjWYs9g72iBsbhtVJkVg2Oggjg9z0LnRsam3HyZxqfHWhCDtSs1GUV6pX2vi+lBH46FezwA7Ji/k0NLdhyau7kXlFpemWlZgeNzES61IisXikAjEKVzQ02Giqq1nzTA77LGRmV+LzM0X9bmP83cqJeGX91H7vMRKTqzF9ncsux/znd4Ct5PQ8zq5OmDQ5ChtmRmBBXADCffu/k8kY+/SOeQQo/zOPn25rEjn8WHK1REHOFSeJHAvhFEvk9CRqW84XYUdaNop7JWqrZ43A/z6un6iRyDHP6RX1LTh8owybThYiNTMbNTpbt8yzPHRax4R649CbS+DnIZ1vtBuZOHhtD45evq0BaWtni8gRQViRwrYZBWF8mKdeuWj2BcHF7i8I2Bar3l8QTB0ZiD06XxCI5aH29g78/N00bPrxhqbLUKUCK2ZHY/X4EEyJ9EJTo/VFTs9nYXP3Z0Eq2xhN8dOOE7lY8/ZBMPY9j7uXG2ZOV+L+hDDMifFHQK+tj6b0Q21MJ0D5n+nserckkcOPJVdLFORccZLIsRBOMUQO23KTkdV1B8X+jGyU367Um80La6fg2dV9t9yQyDHN6T0H1/ffKMWmzHycOJmjt3WLWWWrGvZ27G774fmwbVKLpoTjpXVTBr3DxVqzZ9s2mTj47OB1zRBsbGwQFO6PxclKrJkQioQoLzjrVl7r6MSNknpsv1KCL9NycPWS/mH5ULbVc+MyBPu6ij4tl3s/1PQZEqXAPd0iJz7KuiLH1bWriMMBnc9Cg04RBydHO2x70brbGIU46+/bLuKpj47pNfEJ8MYdSdFYPyUUySN86W4cIUAt9C7lf/zAksjhx5KrJQpyrjhJ5FgIp6VFTlltMw6zEtHHC5B+rO/h6Y+fmIP7kqL7nR2JHOFOZ1WjsksbseuaCp+n5+Hi+Ty0NGkPiPuxEsQbl0IZRKVlhdPl3+KP357Di5+d1DPsF9idtE4NRaJSP2lVlz2uaMKea6XYfDQXZ8+wssf6RTsOvrEE4yN9+Q92EIuB9/8fahu6tk5JSeS027Yh7VY5Pj1ViANHbqJWp3iDr4czjrwljW2MhpzFRPHj72fgf/de1RPFijB/LEqKwrpJoYiP8oarjig2ZJN+bjkClP/xY0sihx9LrpYoyLniJJFjIZyWEjn2tjYoqmpSl8HdfCy/qwxuvU4ZXCd77H7lLkwfGTjgzEjkCHN6z2WS31/qukzyBrtMslV75mlkGNu6tRQ+7uJeJilsFvJ7e+vRHDzw54Ng/ut5PLzdkThdiQ3q7Ud+CPDU+sxg+XU7W2x5ej7umhouGkypipz69hYcvFGKTzLzkXn0luYeHBcne9x8fy18PaT/WWhqacPyN/bhyIUijT/Z9saIaAWWJyuxcnwwJoZ5wNHeTjR/U0eDE6D8j1+EkMjhx5KrJQpyrjhJ5FgIJ2+Rc9+4YET5u6K2sQ37b5Xii/RcXOp1oWGAt4v6ILihCw2lKnLWJ4Zj0chARPq7WMgrws22tLXjXF4tvrpYjO/TslGQpUJHh3bP/rxJYfjmmfmS3LolfLbDr8Wpm6VY8OIuNDRpD5K7uDljypRIrJ8ZgTtHBiDMR/8geXVD1yoFq7z2Y0aW3kW6bCPiHx+eif+3ZIwosIaayHl5/VQ8tWqSKGzM6aS8tgmzn9mOW0XaS5JZoYrYUaFYnRKFZaMVGBXsrleowpz+qC0fApT/8eHIrJDI4ceSqyUKcq44SeRYCCcvkePi5oL4+EgsmBgEdwc7FFY34YfMfNxiqwk6d4OMifTFgdcXw9vN8DeoUhM57MxEcHgAFqcosWpcMKZHe8PZwfrfnja0tONYTiW+PFuE3alZUBWVA9pFAfxi8Rj85eEZQ6JqlIXCfEiYzS+rQ8rT26CqaNCM18HJAWPGR2BtYgSWjFZgRKAr2H0/PQ/z/fEe36dl43ZhmZ7vH100Gn97dCZgAzRAa9dcIK5whQ0z2v0MNZHz5k+m4Yl7xpuLwaLtbxZVqyvxVdZq77ViJaInTIwAKzm+aJQCSn8X+lxb1AumGaf8zzRu/bUikcOPJVdLFORccZLIsRBOc0TO0ld3g11y2PM4OjmzrM9OAAAgAElEQVQiYoQC9g52qK1uQHFemd5qwsKp4djy+3lwNFIYSEHk3Cquwfj/+krvWhm/IB/MT1Ri3ZRQJEb7wsPZ3kLeMWy2qqEN6ezM08kCHMrM7vNt/p8enYlf3iXOt/mGR0tvGCJQ09CCO1/YifPZ5ZpXWVnm6JEhWJkcheVjFBgX5gm2HbTnUa/i5dfia7aKl5qN/F6reHMmhqDq2TeR6ZBmqHujf56EJKQiVSN0hoPI6USn2UKwt/gzGmivF49cKsayV/egRWe7qauHK6bFK7FhRijmxQQgyNuJBI6pgC3cjvI/foBJ5PBjydUSryA3JwnlOiEJGyNGpjvHHHaVdc2447kduJqvXy2tv9E8fvc4/OHBaYL+KEtB5LC5bEnLwk/fOQR2+Lfn8fb3wh1JI3D/1BAkj/CDh4v4QqeyoRVHbpTj0xMFOHL0FmortZcC2tvb4qun5mORiOcyTI9CaqlLgJWL3vDnH7HtWI7mn21sbRAaGYi7k5W4b2IwJod76W097DmP9cPlYnydlqc+j9XW2qZtH1qGxjdfAzzqucGuQx3c4Ka2N9RFDhM4yUhGBjLM4tNb/Jli7P8OXscv/pWmdxeSl58nUqZHYUN8KGbH+sPHzdEU09RGJAK88j+RhivpbkjkSNQ9vILcnCRUomi4D4sYmY7UXHbsm8aVb+3H/jMF/Q6C7az528+T8OiCUYIHKRWRwwa+/2yB+pvVnoclneOnRGNdUiSWxCkQGyR+2d4rRXXYzqqopebgylltQszGmPrW3YgfGSCYOTWQBgFWXOD5z07iL1vP6w0oIMQXC1i54EkhmK70gZvOKiJro6msl5GHC+f0K+vZejbhx413YWywwuRJss+kAl3th5PIYXPxgIfJXHQb6nIRYtCQz9dOCsHMXj4XYp/eFY8Ar/xPvBFLtycSORL1Da8gNzcJlSgersMiRqbj5MGO/XF+7tOT+NeOS3rbK/y9XPDxr2dj3qRQkwYoFZGTV1KLlGe2o6RSe6bB2dUZM2aOwAPTwzAvNgAKL8NnjEyCMEijwspm7Ltegk8z8nDyRJZeqegIhQeObFwGhbd0iiPwnr8c7H184Dp++W5/3+orsSE+BLNjA+Dj5qBG0dkJ1Nd3oqKxGYdyWInprjuSdO+FYVtFd7y0CMljgkzCN9Bncqiv5JSgRCPeTAKj08gUkcNW79b/+SC2H8vV+yKFrd4tY6t3E4IxJUJ/9c7ccVJ7yxHglf9ZboRDxzKJHIn6ileQ80hCJYqI27CIkekoebJjqzr1zdotMt5ujoK2p/WehRREzokbJVj44i6wW+p7Hlb1amp31av5/VS9Mt0bwloycZlbzu5MUWFzRh7Onc1Dc6P2zhRPNyf8+MYSjInwEWaY3pYUgcMXi3D3a3sHPZ/BRHZKig0yundbPfTzFiz7RRk+P1mI1MxsVFfUaubELkpNf/tuTIr2FzxPEjmDIzNlu9rA57CCsTJZ2e85LMGOowaiEuCV/4k6aIl2RiJHoo4xNcjZHxHdR3d7gAoqzR7onnd69kRLFIMow+KZqIsyYAl1ImV21hY5X6dn4cG/6p/F8fBxR/I0Jdaz+0ti/eBv5Xs2eu5MOXijDJ8dy8exE9mor9GpzmVvi2+fuRPzJ4dJKOpoKEIJ3Ciswuxnd+hV2nJydsT47kpbC2IVGBvpgpYWbUGCufPb8OzfKvH52SLsS89CaXGFptunVk3Ey+vjhQ4Dw1XksDM5pShV8zCneIDQtvmltUh5ejtUOqvE6op648Kxlm2F7aeinmCnUQPRCZia/4k+0CHQIYkciTrJ1CDXLctpzNTYL2e5P1JO1KXuGymzs6bIeevrs3hl8yk99/kpfDAvqauqWpKVq6r1jquq+lakZlVg04kCHM7MRlWZ9l4Ndi7qr48l4ucLR0s9HGl8gxAwdGfKaHsFHlzhjuvXbODWVQ8A5fUtOFpQik0nCpGWfhONdV0X8j65YgJefyBBMO/hKnIEg+DQwJS7kTh0SyZEIGBq/ifC0IZcFyRyJOoyU4OcRI5wh0o5URc+G3FbSJmdtUTOzpN5WPnmPo0j1PfjRARgcVIU1kwMRXyUlyTux+kdKfXszpTsSnxxpgi707NQ0uu+nANvLEXiaNMPnYsbmdRbfwSaWtqw/I19OHKhSPNjdjnkpHgl7k+KhGdZIO6e56IROarKVqTnleGTY/lITSOR09TQdefMqHBvnH7nXrO205oToVuP5uCBPx8Eq4rX83h4uyNxuhIb2CpxjB8CPMU/52fOnKitloCp+R8x7EuARI5Eo8LUIKftasIdKuVEXfhsxG0hZXbWEjkvfHYCf/q2q6qVrZ0tIkcE457kSKwYG4xJ4Z5wsLcV10kCemtubcepvBp8e6EY29KzkZ+tQmd3IvWHn07Hr5aNE2DNuFd53C9iXE/0FiPASpn/4m+Z+DZVe0h95LhIrJkViTsjgjEm1F1SIqexwQYe3YXLVCpoxmYJb9bXA4puHV9XBzSjFYdvMpFXiNS0G2io027lZFs4v3l6vtH3dvEa7x+3nseLn57QM+cX6I07WNW87ru3PK1Qkp7X/MgOYGr+R+xI5AyZGOAV5FJOQqXiDGJkuiekzE4KIsfF3QUpSTHqKmpzY/zh5y79+yluV7fgIKu6drwAR4/eRHNDVzECS4gcXveLmB7BMm1Z4w7nh97RTF7KIqe8zEYjPMT0FhM5Li6duFpch21XVNiSnoNrlwvQrnPBZoC3Cx6YEwt7O+1ZJkuOcf+5Qpy+Wabpgq0SB4X7Y0myEqsnhCKBrRI72llyCGRbBAK88j8Rhir5LmglR6Iu4hXkUk5CpYKeGJnuCSmzk5LIeXB6OObE+sO3u1yv6cQt37KkpgX7r5fi02P5Fhc5uj6y/MyoBw0BEjmDBkNSEpCaCrDzaB269wel5+Hief37g6wVVV2rxEFYkazEveODMD7UA472JHCs5Q+e/fLK/3iOaajaIpEjUc/xCnIpJ6FSQU+MTPeElNmRyDHNr9YSOf1VfzRtBtTKEIHymmbEPbR1SKzk2NrYoLSrcBlcXbuEh6Wf3v2wKoTFVc1q8b/pWNf9QT1FGCw9lv7s2zvaI25MGFYnRWLZ6CCMDHKDna0IYKwxWRn2ySv/kyG6PlMmkSPRKOAV5FJOQqWCnhiZ7gkpsyORY5pfrSVyTLkE0bQZUquymiaEP7RpSIgcKSXvrNrcEVZu/UQhjp8tQH1NI8SuUMpKf8fFKrAuKQILRyoQ5e9stQII9EmyDAFe+Z9lRje0rJLIkai/KMjFc4yUE3XxKJjWk5TZkcgxzackckzjNpRakcgx3Vu1TW3IzK7E3htlKKhohE6BM9ONCmjp6+6AFKUP7ogNgMLTvAuTBXRLr4pIgPI/frBJ5PBjydUSBTlXnIMak3KiLh4F03qSMjsSOab5lESOadyGUisSOeZ5i1UhvKFqQFl9i3mGTGjt7miHmEA3eA+B830mTI+agKqr8QwCEjk8aXK0RSKHI0wDpqScqItHwbSepMyORI5pPiWRYxq3odRKyiInKDwAd8+JwZK4APi4OsAaJ03YOaAADyeEejvBdoCzLuycTlsH87q4F2rb29rQ9rSh9GEzYayU/5kAbYAmJHL4seRqiYKcK05aybEQThI5fcHq3pPTU0Kaqqv1H4BSjh8LfWQkYVZqIif0wc9QUdtVqrynaljy5FDY21nnTinWa7S/K+YqfTEuVNp3W0kioGgQXAlQ/scPJ4kcfiy5WqIg54qTRI6FcEo5SaWVHNOcTis5pnEbSq2kJnJe/eIUNm45q0HI7n9x93YHW1GxxmNjawNffw/Mjw/D6onBmBrhBWcHKs9sDV/IsU/K//h5nUQOP5ZcLVGQc8VJIsdCOEnk0EqOOaEl5fgxZ15Sbys1kcN4/XHrebz46QlJofML8sX8xChsmBqKGUpfeDjbS2p8NJjhSYDyP35+JZHDjyVXSxTkXHGSyLEQTiknqbSSY5rTaSXHNG5DqZUURQ7jt/VoDh7480G0i12ybBDnefp4IGlGFDYkhGFOjD/83B2NdnVnJ9DQYPTrZr0o1h1CZg2SGhtFgPI/ozAZ9RKJHKMwif8SBbl4zKWcqItHwbSepMyORI5pPiWRYxq3odRKqiKHMbySX4m3vz2P25UiqYNejmtsacexqyq9f2Vn6xLio7BhRjjmxwYg2NvJ4OF/JnCSk4GMDHEiIykJSE0V57JUcWYk314o/+PnexI5/FhytURBzhXnoMaknKiLR8G0nqTMjkSOaT4lkWMat6HUSsoiRwocc1Q1SHl6O8qqGzXD8fLzxILZsbh/SgiSRvjBzWnwMzr19YC7u7izqasD3NzE7ZN640+A8j9+TEnk8GPJ1RIFOVecJHIshFPKIqcOdfCAh3rmKqjghq6//mzMCijU/5+90/PvvBBRdTXjSUo5foyfxdB7cziInE50ogHCV3tc4QobIwpTV9U3I+KhzWhtV9eJhquHK2anxOKhaWGYHeMPL9fBz+foihyVynLig/Wj6Pp1BhI5Q++z2N+IKf/j50cSOfxYcrVEQc4VJ4kcC+GUcpJaghKNmBlo+iRy+pKhlRwLfVgkZHaoixwmcJKRjAwI3wuWhCSkItUoofP4e+n4YM9Vs0WOJcWHrpiyZD8SCt9hPxTK//i5mEQOP5ZcLVGQc8VJIsdCOIeyyBGS7AjBJ9ZKjqWSGxI5Qrw9NN8d6iJH9/eOKR4w9suN//5PBt7bdYVEjimQqY3JBCj/Mxldn4Ykcvix5GqJgpwrThI5FsIpZZHDvu0tRWlXgtLPFhVjt60IRUcix3hiUo4f42cx9N4cTiJHdyvqYJ4wZZsqiZyhF9vDYcSU//HzIokcfiy5WqIg54qTRI6FcFKS2hcsiRzjg43ix3hWPN8c6iJnoPN2JHIsd/aHZ/yRrcEJUP7HL0JI5PBjydUSBTlXnCRyLISTklQSOeaEFsWPOfRMbzvURY4x5+0Go0Pb1UyPHWppeQKU//FjTCKHH0uulijIueIkkWMhnJSkiidy2Bkc3Ue3qlJ/1ZtMLSVLZ3Is9GGRkFmpi5z6pla4OtkPeBeNOSJHyFk82q4moaCV0VAo/+PnbBI5/FhytURBzhUniRwL4SSRI57IsbER5kR2GaEpD4kcU6gNrTZSFTmtbR145B9H8HVaFsID3bH9hYWICfHqA9fQebvBvCHkLB6JnKEV18NltJT/8fMkiRx+LLlaoiDnipNEjoVwksghkWNOaJlytsKc/qhtF4HymmbEPbRVg2PkuEismRWJOyOCMSbUXXOhpKqyFel5ZfjkWD5S026isa7rcswnV0zA6w8kCMY52O+LmoYW3PnCTpzPLtfYdXKwww8vLsSsscGC++LRgEQOD4pkQygByv+EEhv4fRI5/FhytURBzhUniRwL4SSRI57IGY7b1czZdmShkJaH2Rp3OD/0Tr8iJ9JbK3Iq6lpxorgMnxy3rMgpKKtH8lM/QFXZ93JPGxsbPLIgDjNHdd94OYCHPFwcMG9iKFycBr+kU4iDSeQIoUXv8iJA+R8vkgCJHH4suVqiIOeKk0SOhXCSyBFP5PTuaTjck0Mix0IfTANm7fbOhsP/PNCvyJkW567+d0fHThw8VY9jZSp8dTQfl87lobWlVf0z3is5M3/7Pc5mlWnG4+jkiJbmFsFwPN0csf/1JRgf6Su4bX8NSORwwUhGBBKg/E8gsEFeJ5HDjyVXSxTkXHGSyLEQThI5JHLMCS1zzlaY06+c2/7lm8t4c9N5DQIbWxuMm6zEuqRIjHMJwoIZrvD06sQn39XhWpsKX6bl4MaVQrS1tmna/P2xRDy6aLRgjAP9vgi8//9Q29AloNy93BA/NRI3s8tRmFuCzg5hh8vs7Wyx5en5uGtquODx9W5AIsdshGTABAKU/5kAbYAmJHL4seRqiYKcK04SORbCSSKHRI6FQovMcibQ3t6Bx/6Vhs2HbmgFjo0NgiMCsDQ5GvdNCEa0pxdcnYGbFbX45lIxvkvNRl6WCh3tHZo2s8eHYNsLC+Fgbyt4hMaInJAoBe6ZHQ03R1t8l56HgtwytLVpBdZAnbY2d4kk9rAaHX98eCb+35Ixgseo24BEjln4qLGJBCj/MxFcP81I5PBjydUSBTlXnCRyLISTRA6JHAuFFpnlSKChuQ1LXt2NzCsqjVVbO1tExQRjRXIUVowLwoRQT7R2dOJkThW+OFuIXek5UBWUoVOnTN8Dd8bgf34+C7a2Akv9dfcqROQsH6XA6eJqHM2uAitKMNjDhnjtugq3C8sAnYUfttr0t0dnDliK2hBiEjmGCNHPLUGA8j9+VEnk8GPJ1RIFOVecJHIshJNEjvVEjoVcCjFLSFtqDmRXS0BV1YhZT29DXkmt5h/tHe0xakwYVidHYumoIMQFuaGuuR1ptyqw+XQhfszIQkVJlR7Gtp9+hapl38ANbibjFSJyVo8PQYC7E3Ir6tHY1j5on20dHUjLrcIPqdnIZytPHdqVp7mTQrH1mTvBKrUJfUjkCCVG7/MgQPkfD4pdNkjk8GPJ1RIFOVecJHIshJNEDokcC4XWkDL78YFr+NsPl1DbqN0yZc4E2ELJoqnh+MOD08yqFnY5rxJzn9uBmvpmzXCcXJwwcVIE1idGYGGcApF+ziitbcGhG2XYdKIAGcdyUFddp3nfzs4Wjb/7BzqmnQEr+S2myBkT6IXRYzoRGdWJ7dsBZ+f+qbJjO9mlDfj+SjG+ScvDjav6Z4hiw7xx6I2l8PVwEuSWe9/ch10n89RtXD1cMTslFg9NC8PsGH94uQ5exc1ShUF6T0CsfgSBo5fNIkD5n1n49BqTyOHHkqslCnKuOEnkWAgniRwSORYKrSFhtqOjE7/4dxo+PXDdIuONCvLE4TeXItDbRbD9/WcKcO/GfWAXbPY8bp6umJGgxIbp4bgj1h+Bno7Ir2zCvmul2HQ0D2dO56KpoUn7vosDtr12BxKjuw7xW0PkeHp0bY2rq4Pm/p7+YHR0diKntBG7rqmwOSMPF8/loaVJu83N19MZRzYuxYjgvpeL9mfvy9RbeOivh3TYuWF2SgweSgjDrFh/eLmQyBEclNTAKAKU/xmFyaiXSOQYhUn8lyjIxWNOibrprIkdiRzTo2dot2xsbsPS1/ci41KxRSfi6eaEQ28uwehwH6P7eW/PFTzxfgZ0jtPA298Lc2YosT4hDCnRfvB0tcNNVT22Xy3Bl+k5uHKhQFMimnUU7OeG1LeWwdsPcEdXWWmxRU6UuxeCFF0iR6XqK3Lceu2cY+eHiquasf9GKTZn5uPEyRw0dF9gymywLWs7XlqEpDFBg7J8c8sZvPbFab13giMDsXxWNNZMCMGUSC84Gii8INYKi1j9GB189KLZBCj/MxuhxgCJHH4suVqiIOeKc1BjlKibzprYkcgxPXqGbsvS6kbMfnY7sotrNJOwd7CHbyBbJTDtUL4ujbqaBjTUai/GdLC3w9bn7lRfdjnYw5L83/7vMby745L2NRtAEeKHBUnRWDc5BNOVPnCwtcGlwlpsvVSMb9NzkX2jGO06516mxARgzyt3wd3FATw/40LP5Cyd4YWy0oF56oo4XS4V9S04fKMMm08WIjUzG9UV2vNItjY2eO/xWbh/TkwflKwC3cP/SMWXR25qk6TuCnRLkpVYPSEE8VFecDbifI9Y4kOsfobup3XojZzyP34+I5HDjyVXSxTkXHGSyLEQTp4JkIWGKLrZFz47gT9923UPiYu7C1KSYvDg9HDMifWHr5uD6OMR2iEVHhic2NX8Ksx5bjuq6/TPuUyYGI6ksQoIL6zct7+bqjocycxBVVm1TrIN/P3nSXhkwah+B9jS2o5VfziAfafzNT+3tbVFmFKBu5OjsGp8MCZHeKpXd07lVWPLuWJsT8tGUZ7+XTQrEpX4vyfmgN03wx6en3GxRA4bd11TGzKzK/H5mSLsS89CaXGFHrffrZyIV9ZP1VReq29qxV2v7MGJa30r0N2bEoUVY4MwPtTT6NLZYokPsfoR+nuE3jedAOV/prPr3VJWIqepqQkbN27E559/jry8PPj6+mLRokV49dVXERYWZjLVGzduYMKECWD2Fy5ciN27d5tsq6chBbnZCI02wLZgeMBD/b4KKrMO1hrd6TB5kSUtCijUszF3K8swQQISOcPFk33ncfBcIe55g51z0Vb7YudcpiUosX5aGCYFe/WbBHd2ALm5XfYiIwGbwZRQJ5Bf1YAtZ4uxJyMLJUXlemWR/2vZOLz90DS9ssiVdc244/kduJpXqRm0nb0dYkaFYlVSJO4ZF4zRwe5obGnH0exKfHGmEPvSslF6Wz/xf2rVJLy0boqebWuKHKHb1Xp7rLm1HaeZoDtfjG1M0PW6XHT5TCU++80clNU0YdYz25HfpwJdONawCnSjFRipcBNUOlss8SFWP8P3Uy29mVH+x88nshE5TIDMmzcPGRkZCA4ORkpKCnJycnD8+HEEBATg6NGjGDFihElk77jjDhw6dEh9nwCJHJMQWrVRCUo0ibpVBzLEOyeR0+VAEjlDPJAHGP4He6/iV++l9znnMmtGFO5PCEdKtC+8B1ipE5qIsuT8TH4Nvu5OzgtySvTKIi+YGo6vfj8Pjg52yFHVIOXp7SirbtSM3NHJEeMmRGBtUgQWxymgDHRBZUMrjrAKat1buGp6beF6//FZ2NDPFi5rihxWXc3YwgMDRV1bRycu5tdg6+VibE3PRdZ1/a15z6+dgm3H83Auq0xjwsnVCZMnRWIdq0A3MhARfs6C79oR6nNTPzVi9WPq+KidcAIkcoQzG6iFbETOiy++iNdeew0zZ87E3r174e7edZDyL3/5C5588knMmjULhw8fFkz2ww8/xCOPPILHHnsM77//PokcwQSt34BEjvk+SEISUpEKGw7nEcwfjXUtkMixLn/evbMvr5765Dj+8cNFPdOBoX5YmBiNtZOCMT3aF25OA9/DYkoi2t7RiSvFdfj2YjG+Sc/FrauFeudmRkf44g8PJmD1Hw6gqaVNMza2RTI+PhL3T4/A/JEBCPZ20hzG35SZj5O9D+M72mHHiwMfxh/qIoeBYZXXrhbXY8fV2/j6aJ5ekYX5k8OQdqkYTS1dq3PqCnTTlFibEIp5sQEI8nISLHCYHVN8bkrsitWPKWOjNqYRIJFjGrf+WslC5LS2tiIwMBBVVVU4ffo0Jk+erMdi4sSJOH/+PE6ePImpU6caTbekpASjRo1St3nuuecwd+5cEjlG05POi53oRClK1QNyhSsl6ia4hrhpofUncn4yPRwTQ7zh4WzaiQ120NnT2c6kZEuoO+lMjpYYKxG9+u0D2HG8e68ZAPU5l6hALEtWYtWEYEwO9+xz0SRLPHUf9t+Krl2dRlUJ62nLkvOskkbsvKbCF+m5uHQ+Hy3N2rLIvX3r6eOBZFZBLT4EE0J84Olih4q6Vhy4VYrPByirnLpxKaIHKatsPZETjDGB3mav5PQwqmtil52WY9OZIuz58TpqK7uKEfQWOWHRQbh39gisGhuEqVFegrao9fZ593epBstfC/2MWqMfc8ZIbYURIJEjjNdgb8tC5Pz4449gW8rYdrSbN7VVU3rAsBUettLz0ksv4eWXXzaa7tq1a/H999/jwoULKCgoIJFjNDl6kQgMXwK6IoedixgRF4LliREI9XIxeZ3L29keYxSe6nMVduymSAs+JHK0cL/LzMG6tw9o/kHtz1GhWJkUiXu7z7n05w8bgS4aqEoY65itJBVVdd1ls/lYPk6eykWjTlnknsH5BfkgZXoUEqK84d5d/asTQFF1I37IzFdfkNneqj1LNDLMGz8acUGm2CJHs5ISH4rZ0QGICGAXeNqYJRSYWLxxuwHbr93G1xn5uHQhD63NXRe39hY57l5uSJwejTXxIZgfG4BAL2EXiPb4Q6wVFrH6seCvHDLdiwCJHH4hIQuR88477+CJJ57Afffdhy1btvSht2PHDixduhT33HMPtm7dahTdnTt3YsmSJeqiBS+88IL6TA6t5BiFjl4iAsOawDfpWbj/zz9q5si++Q+JDICXt6vJ83Z3dcD0kf5YNTYYEyM84Gg/8NYokzvpbkgiR0uQlWJ+8sNM9T8wgTN6fARWJkZgSZwCY0PdwcoR9/fwFDk99osqm3DgRim2nCpCRmaWXolp9g5LziOjAtG7vFt1VaP6wH1Hh/ZS0HmTQvHNM3f2WYHqby5iiJzk3/+AUze7VtPZ4+zqhEmTo7BuZgQWxQUg3Ff4mZgeWz3b/rZeLMbX/Wz7e/q+SeozOZdytUUYnN2cMWVKJDbMjMCdIwMQ5iO8f7HEh1j9mPt7hdobT4BEjvGsDL0pC5Hzm9/8Bn/961/VQoedwen9nDt3DpMmTcKUKVNw6tQpQ8xQX18PFoTOzs7qbW6Ojo4kcgxSoxeIgDwIsG/ef/fxcfxrm/4ZDnNmzxJs/yBvLEqOxppJIZge5QNXR8sIHRI5XZ5ifvz3zssakePk4oTpM0Zgw3R2ViMQoT7OA7qU13Y13Q7qm9uRfqscX567jV2Hb6CypMqkkHrsrjF455EZRm99FEPk3K5sQMrT21BQWqeZk4OjA0aNDcOa5CgsGRUouLoZM8QKOJztLuDwQ3o2CrL1xd7CqRH46ql5UFU1IuXpH3C7QuduIicHjB4XhnVJUVgyOhAjAt0GFLX9isN6gLarmRSism9EIodfCMhC5LCiAP/5z3/U52Zef/31PvTYFrbY2FiMHDkS165dM0iXiSW2OnTw4EH16g17TF3J6Qnm3p3eunVLvb3u0iWdS90MjoxeIAJEQCoE+rt13tyx+QR031ofH4bkEX7wdrU312Sf9iRytEj+vfMSfvNB10oOewKCfXFnUpfQTIz2gbuzcfzN/badVQg7n1+N7y6r8F16jl6FMAd7W7S2aVdpBgoItub0p0dm4jXqy1AAACAASURBVJeLxwiKGTFEDhsQu6dm0cu7cfJ6iWZ8dnZ2iIoNxr3JkbhH6D01Le04zu7JOV1kVCnumoYWLHhxl16VNfblQvTIYKxMjsLyMUEYF+YJeyO3i5rrc2OdJFY/xo6H3jOfAIkc8xn2WJCFyHn00UfxwQcf4Pnnn1dXWOv9sHtumMAxRuSw4gQzZszAhg0b8Mknn2hMkcjhF5RkiQgMFwL7zxTgwXcOo6K2iduU3DzdMHNaFDZMD8fcGH8Eejoa/a28MYMgkaOldK2gClP/+1uwLU89j5dv1+H+DezMiPqCV0eDWM1JRA3d9fLC2ik4eq0EB84W6JW31h2Ut7sTPvr1bCyaGm5wrL1fEEvksH7b2zvw078fwVeptzTDsLGxQUhEAJYkK3HfhBDER3mBFeIY7Kmqb0VqVgU2nSjA4czsPpeqvvNYIh5bOLqPibb2Dmz484/4ITNH27+tDUIjuwpN3DchGFMivIzb5kcrOYJjjRp0ESCRwy8SZCFyeG1Xa2trQ0JCgvoi0atXr6rv1+l5TBU5A7mSgpxfkJMlImBNAqxCV2mN6SLncl4l1rx9ALUN2qpa6ns8JkeqzyyYeo/HQExyyxqx/2YJPj9WgBPHstDS1NXvH346Hb9aNs6aKK3Sd/rl21jy6m40d5cYZoNwdXdBQnwU1s8IVx9OZ2WaWTI+0GOqyKlrakMmW404U4R96VkoLda/vPP3qybh5e7LO9lKBLvss78nwNPZ9CphqIc7uq5cMPcuLGMF0+tfnsEbX57WmworrDA/UYmVE4IR6D7wVkEmR6+X1eKLE4U4fiIb9TU6W9Ds7bD1uTsxb2LogL5i2xRf2nwKf/zmnN47Pat46yaHYKbSB24GVvFM9bnQIBerH6HjovdNJ0D5n+nsereUhcjhVXiAXR6qVCoRFBSEuLg4PZasPDU72+Pj44MJEyao7+HZvn27yZ6iIDcZHTUkAsOOADuzMOvp7cgv7Sp7yx52ZiFuDDuzYNqN7L0hseSOreIcvFGKTccKkNkrQfz7zxPxaD/ffg872P1MKKu4GinPbEeFjlh1dHbEuIkR6gsjF49SQOnvMqDQMSURrahvweEbZdjcfXlnda/LO997fBbu7+fyTt7+YMLGAx5qsyqo4AY3k7tgIkeBrlrahgTTl6m38LO/HQb7kqDnYSWy2SpmoI/LoGO4lluJc2fz0NzYrHnPy80Jh95cilHh3kaN/9ODN/Dzf6Wqz2b1PF5+HkiZzkp0h2JOrD98BlnFM8XnRg2s10ti9WPK2KiNaQQo/zONW3+tZCFyjC0hzcpIv/LKKwPS7RE5xuD38vJS38tj6kNBbio5akcEhicBdmbhrlf24MQ1lWaC7MxCZEwQ7k2JwgqBZxZ0KbFELq+8Cbuvl6jvUzl7JlcvQWTbnc79fSUCvQdPLocn+a5ZVdQ2Y85z23GjQPt73d7BHrGjQrAyORLLxwQjOsBV0OH0gXiV1bbgx1ul2HQ0Hyd6X97pYIdtLy1EyphgUXBb6rJkQyKHTS7zmgp3vbwbTc3ay05ZAQhHJ4dB595Y34S2Vm2bSIUnjmxcKjh+j1wqxrJX96BFp/Q2W8WblqDE+hlhmB8TgKABVvHEEh9i9SNKsFEnagKU//ELBFmInJaWFvVloNXV1YNeBnr8+HH1djRTHtquZgo1akMEiIAQAuzMwsP/SMWXR7T3ffWcWVicrMRqI88s6PbJvim/rqrH9isqfJmWi6uX89HWok0QwwM9kPrWMihkLHB6eLHzMfdu3IeDZws1CFmJ8PBoBe5OVmKW0sfs8t5McF4tq8NXR/Nx4VyeZrsg69DX01mdrI8Y5PJOIfFkzLuWEDlJSEIqUo26eDlHVYOUp7ejrLrRmOH2eSdxTBC2v7AQLk7GFYnobeBmUTVmPbMdlTrn6tgq3oSJEVibGIG7BljFE0t8iNWPSfCpkUkESOSYhK3fRrIQOWzmrOjAG2+8gcTEROzduxdubl1L7qyk9JNPPonk5GSkpqZqIP3zn/8E+9+KFSuwceNGg8RJ5BhERC8QASLAicCbW87gtS/6P7OwbkooEqN94WFE5S9WletCYQ22XrqNb1NzkHOzGB3t2kpd00cpsPOlRXA1MUHkNF1JmWEi5L8/yMT7uy5rx2UDBIX6Y8yoIAi9I6e/yRXersHNq0V6qxExod44/OZS+HqYdjmlqRA70YlSdN1h4wpXo4SJob6E2qmqb8Ydz+3ElTz9M0mG+rn/jpF475fJJp9H6rFfXtuEOc9ux83Cak2XXat4oVidEoVloxUY1euiXrHEh1j9GGJNP+dHgEQOP5ayETlNTU2YM2cOjh07huDgYKSkpCA3N1f9335+fsjMzERMTIyG7Msvv6zeuvbggw/i448/NkicRI5BRPQCESACHAlsScvCT9851OfMQtL0KGyYFobZI/zgP0hC3NTajpM51dhyvgg70rJRnFeqd/5gzawYfPh4CuzsbDmOeviYenfnZfz2g6PQntgA2Df8PB62kqZ7eeecCaH47jnjLu/k0b8UbbAtY//ZcxUHLxQbHJ6jva36vNKShAiD7xr7QlNLG+55cz8On9dZxbOzRUS0AsuTlVg5LhgTw7UX9YolPsTqx1hO9J75BEjkmM+wx4JsRA6bcGNjo3pVZvPmzcjPz1cXCVi0aJG6rHR4uH5pTRI5/IKMLBEBImAZAseul2DRS7v0ziy4uLkgPj4S66eH4864AIR4972tvbapDRlZFfj8dCH2p2ejXFWpN8AX103FM/dNssygh5HV3afycd9b+8FKD1vqeWTRaPz90Zlcy4RbaqzD3S7b2vnr/xzFB3uuaKbKtosqwvywKEmJNZNCMS3KW31Rr1jiQ6x+hrtvpTQ/Ejn8vCErkcMPm+UtUZBbnjH1QASGA4FcVS1SntmG0irtmQVHJ0eMnRCOtUmRWBynQHSgi+ZAfFltMw7fLMem4wVIP56DmkptxTZbWxt88sQcrEqKHg5oRJnDhdwKzH9+B2rqtSW+eXTMtr29/dMZ+K+lY3mYIxscCfxj2yU89VGm3iqeT4A35iYqsWEqu6jXF3Yd9nDvqryNujqge4c8x1F0mSKRwx2p1Q1S/sfPBSRy+LHkaomCnCtOMkYEhjUB9ZmF53fiSq72zAK7rX1EXKi68hcTOn5ujmBb1I7lVairdp06nYvGeq0wYgezd79yF6aNDBzWrCwxOVb5bvfpAm5Cx87WBrPHByMysKt0Mz3SI7DjRB7Wvn1AbxXPw9sdKTOjsSEhDDMj/RDi27V9kUSO9Pwn5RFR/sfPOyRy+LHkaomCnCtOMkYEhj0BdmZh9dsHsOdUvmaurPJXWFQg7kqMQpCXE5paO7D3TBEuns9Da3Or5r0Ab1ekblyKSAUl1cM+UGiC3Aicyy7H/Od3oq5Ru4qnHBWG+2ZFYcXoYCTEeKCtzYZEDjfi8jBE+R8/P5PI4ceSqyUKcq44yRgRkAUBVvnrqU9O4B8/XNCbL7st3tXNCe1tHVAVlqO9rV3z8zGRvjj4+hJ4DXKxoSzg0SSJgAkEiirqMeKRLzQtw0cEY+XsaKwaF4yUsZ5obCCRYwJWWTeh/I+f+0nk8GPJ1RIFOVecXI2xkqoNaOBqU8rGhJZ7lfJc5DK2D/Zexa/eS4fOZe39Tn1RfAS2/H4eHOypgppcYoPmyZ+A5+qPwMqxs4dEDn++crNI+R8/j5PI4ceSqyUKcq44uRljAicZychABjebUjck5OI+qc9FTuM7eK4Q97yxD606qza68//V3ePx1oMJVLWLY1DI7QsQjuiGnCndL39I5Aw590l6wJT/8XMPiRx+LLlaoiDnipObsXrUwx3dJXO4WZW+IRVUcEPXBbr0DExAaqteV/Or8PA/juBKvrZEtK+HM15aNwUPzI0lV3IkIMcvQDjiG3KmdL/8IZEz5Nwn6QFT/sfPPSRy+LHkaomCnCtObsZ0Rc5wTfxZsjYf83EMx7hxk4shWvWSi6f7zlOuX4DI1+NAHerUX/6QyJFzFPCfO+V//JiSyOHHkqslCnKuOLkZ001kev7AcTMuEUOUrJnniOEaF+ZRGf6t5fAFyPD3ouEZMj8roFC/SCLHMC96QzgByv+EMxuoBYkcfiy5WqIg54qTmzG5ipzhumrFKzD6S3x42SY7Q4OAHH43DA1PWHaU/fmZVnIsy1xu1in/4+dxEjn8WHK1REHOFSc3Y3JIZPpbyaHVicFDSA5xwe1DNEwNUQwMU8f2mhaJHHn42ZqzpPyPH30SOfxYcrVEQc4VJzdjckhkSOQIDxc5xIVwKvJqQTEgD3+TyJGHn605S8r/+NEnkcOPJVdLFORccXIzJodEhkSO8HCRQ1wIpyKvFhQD8vA3iRx5+Nmas6T8jx99Ejn8WHK1REHOFSc3Y3JIZEjkCA8XOcSFcCryakExIA9/k8iRh5+tOUvK//jRJ5HDjyVXSxTkXHFyMyaHRIZEjvBwkUNcCKcirxYUA/LwtykiR6UC3Cx0zVh9PaDoKvaGujrL9SMP70pjlpT/8fMDiRx+LLlaoiDnipObMTkkMiRyhIeLHOJCOBV5taAYkIe/TRE5YpEhkSMWacv2Q/kfP74kcvix5GqJgpwrTm7G5JDIkMgRHi5yiAvhVOTVgmJAHv6WqshJSgJSUwEbG3n4YTjPkvI/ft4lkcOPJVdLFORccXIzJodEhkSO8HCRQ1wIpyKvFhQD8vC3EJET5uoJG9jA1dXy4kOMPuThYevPkvI/fj4gkcOPJVdLFORccXIzJodEhkSO8HCRQ1wIpyKvFhQD8vC3EJEzOdITtrS0Io/A4DhLyv/4wSSRw48lV0sU5FxxcjMmh0SGRI7wcJFDXAinIq8WFAPy8DeJHHn42ZqzpPyPH30SOfxYcrVEQc4VJzdjckhkSOQIDxc5xIVwKvJqQTEgD38bK3JWjgvGFFrJkUdQcJ4l5X/8gJLI4ceSqyUKcq44uRmTQyJDIkd4uMghLoRTkVcLigF5+NuQyPEN9MGdydFYPTEYs2L94O5sLw8wNEtuBCj/44YSJHL4seRqiYKcK05uxuSQyJDIER4ucogL4VTk1YJiQB7+7s/PUQ9/DlVlgwaAt58nUmYq8UB8GJJH+MHHzUEecGiWXAhQ/scFo9oIiRx+LLlaoiDnipObMTkkMiRyhIeLHOJCOBV5taAYkIe/+/Nz+uXbWPzKbrS0tmsguHm4IiFBifunh2HeyAAoPB1hQ0UI5BEkZs6S8j8zAeo0J5HDjyVXSxTkXHFyMyaHRIZEjvBwkUNcCKcirxYUA/Lw90B+vlZQhdnPbkd1XbMGhJOLEyZMDMe6xAgsilMgyt+FhI48wsSsWVL+ZxY+vcYkcvix5GqJgpwrTm7G5JDIkMgRHi5yiAvhVOTVgmJAHv4ezM+l1Y1qoZNdXKOBYe9gj5GjQ7E6OQrLxgQhLsgNdrZ0Y6c8osW0WVL+Zxq3/lqRyOHHkqslCnKuOLkZk0MiQyJHeLjIIS6EU5FXC4oBefjbkJ8bm9uw7PW9SL9UrAFia2eLyGgFlqdEY9W4IIwP84CjvZ08gNEsBROg/E8wsgEbkMjhx5KrJQpyrji5GTP0B45bR1Y0RCJHOHw5xIVwKvJqQTEgD38b4+eOjk788n/S8cn+axoo7DyOIswfi5OVWDMxFNOivODsSEJHHlEjbJaU/wnjNdjbJHL4seRqiYKcK05uxoz5A8etMysZIpEjHLwc4kI4FXm1oBiQh7+F+Pkv313Ac/93XA+Mb6A35iVGY92UUCSN8IWnC5WYlkfkGD9Lyv+MZ2XoTRI5hghZ6ecU5FYCb6BbIX/gpDkDw6MikWOYUe835BAXwqnIqwXFgDz8LdTP3x/LwYY//Yj29g4NIA9vdyROj8L6hDDMjfFHgKeTPODRLI0iQPmfUZiMeolEjlGYxH+Jglx85sb0KPQPnDE2pfYOiRzhHpFDXAinIq8WFAPy8Lcpfj5zqwzzX9iJhqZWDSRnN2dMnhKJDTMisCAuAGE+zlR5TR4hZHCWlP8ZRGT0CyRyjEYl7osU5OLyNrY3U/7AGWtbKu+RyBHuCTnEhXAq8mpBMSAPf5vq5/yyOsx6ejtuV9RrQDk4OmD0+DCsS4rC4tGBiAl0gy3dpSOPQBpklpT/8QsBEjn8WHK1REHOFSc3Y6b+geM2ABEMkcgRDlkOcSGcirxaUAzIw9/m+Lm2sQV3vrAL57LKNLDs7O0QPTIYK5OjsHxMEMaFecKeSkzLI5gGmCXlf/zcTyKHH0uulijIueLkZsycP3DcBmFhQyRyhAOWQ1wIpyKvFhQD8vC3uX5ua+/Ahj//iB8yczTAbGxtEBIZiLuTlbhvQjCmRHjByYEqr8kjovrOkvI/fp4nkcOPJVdLFORccXIzZu4fOG4DsaAhEjnC4cohLoRTkVcLigF5+JuHnzs7O/HS5lP44zfn9KAFBPvizqRorJscghlKH7g7U+U1eUSV/iwp/+PndRI5/FhytURBzhUnN2M8/sBxG4yFDJHIEQ5WDnEhnIq8WlAMyMPfPP382aGb+Pk/jqCjs1MDz8vPAynTlVgfH4rZsf7wdXOUB1iapYYA5X/8goFEDj+WXC1RkHPFyc0Yzz9w3AbF2RCJHOFA5RAXwqnIqwXFgDz8zdvPaZdvY+kru9Hc2q4B6OrugoT4KGyYGY55MQEI9naiymvyCC/1LCn/4+dsEjn8WHK1REHOFSc3Y7z/wHEbGEdDJHKEw5RDXAinIq8WFAPy8Lcl/HyruBopT29HZW2TBqKjsyPGT4zAusQI3DVKAaW/CwkdeYQYiRyOfiaRwxEmT1MkcnjS5GfLEn/g+I2OjyUSOcI5yiEuhFORVwuKAXn421J+Lq9twpxnd+BmYZUGpL2DPWJHhWJlcgSWjwnG6GB32FHltWEfaJT/8XMxiRx+LLlaoiDnipObMUv9geM2QA6GSOQIhyiHuBBORV4tKAbk4W9L+pltWbvnzX04dK5QA9PW1hbh0QosT1Fi1bhgTAz3gKM9VV4bztFG+R8/75LI4ceSqyUKcq44uRmz5B84boM00xCJHOEA5RAXwqnIqwXFgDz8bWk/s8prv/rPUXyw+4oGqI2NDRShfliUrMSaSSGYFuUDV0cSOsM14ij/4+dZEjn8WHK1REHOFSc3Y5b+A8dtoGYYIpEjHJ4c4kI4FXm1oBiQh7/F8vM//397ZwJeVXWu/zcjQ5hDEkJCSMLkgMzIkAQVUKlKFScU2qpttbe9ba1y278W64zY3tbZ20Fb9do63Xptb8EqzsUiUufirHXACVEEQWaS/7O2ciCM56zzJVkn+7efx+dpyf6+vdbv/c7Z33v23mvPeV4/+t1CbV13Tepa1FkHja3WtGFlqutbqE7tWGK6NVYd/Z+dqpgcO5ammShyU5xmyZrrBGc2YI9EmJzUocWhLlKnEq8IaiAeejenznc/8bam/vQBuReIbtk6dC7Q6P0rNX3/Xjqob3cVd8pnQYJWVnr0f3aCYnLsWJpmoshNcZola84TnNmgU0yEyUkRmKQ41EXqVOIVQQ3EQ+/m1vm5N5drwsy5Wr12QwJw2/ZtNGRopaaNqdChA4rUq1tbjE4rKj/6PzsxMTl2LE0zUeSmOM2SNfcJzmzgKSTC5KQA64td41AXqVOJVwQ1EA+9W0Ln95evUd1Zf9G7H61OQM7Lz9Ne+5Zram2ljti7WP2KC5TNymutogjp/+xkxOTYsTTNRJGb4jRL1hInOLPBJ5kIk5MkqG12i0NdpE4lXhHUQDz0bimdP1u3UZPOv0dPvPJhAnROTo4q+5Xq6NremrJvDw0s66S83Ox4CNGKZ0n/ZycuJseOpWkmitwUp1myljrBmU0giUSYnCQgbbdLHOoidSrxiqAG4qF3S+q8eXO9Tr7yEf3x0X8lYLuV13pWFOnwuiodP6inhvfurLZ5rLyWydVI/2enHibHjqVpJorcFKdZspY8wZlNYg+JMDmpk45DXaROJV4R1EA89G5pnd0S0xff8bQuuf3pRsC79+imCWMrNX14mUZXdVPHtqy8lqkVSf9npxwmx46laSaK3BSnWbKWPsGZTWQ3iTA5qVOOQ12kTiVeEdRAPPQORefb5r+ub1z5iOrrty4y3alrR9WMrtT0keU6sG93FXbIj4corWyW9H92gmJy7FiaZqLITXGaJQvlBGc2oZ0kwuSkTjcOdZE6lXhFUAPx0DsknR97aakOO/8erduwKQG/XYd2GjGit6bvX6GDBxSptEsbVl7LsNKk/7MTDJNjx9I0E0VuitMsWUgnOLNJbZcIk5M62TjURepU4hVBDcRD79B0fuODTzXu7Dn6aOXahAD5bfI1cFCFptZU6PABJaoqbqfsrKx4CNQKZkn/ZyciJseOpWkmitwUp1my0E5wZhPbJhEmJ3WqcaiL1KnEK4IaiIfeIeq84rP1OmjmXL309icJEXJyc9R3rzIdW9NbRw0s1d6lHZTDEtMZUaT0f3YyYXLsWJpmoshNcZolC/EEZza5LxJhclInGoe6SJ1KvCKogXjoHarOGzZu1rGXPqD7nl6SECI7O1vlVcX6cm2Vjt2vVEMrOik/l5XXQq9U+j87hTA5dixNM1HkpjjNkoV6gjOboCRMTuo041AXqVOJVwQ1EA+9Q9bZrbz2Hzc8rv+a8/xWMbKk4p6FmlRbrROG9NSoqq5qn4/RCbla6f/s1MHk2LE0zUSRm+I0SxbyCc5qkpic1EnGoS5SpxKvCGogHnpngs6/vvdFnfGbBWrYuvCaunTvrANGV0Urr9VVd1OXgrx4CJaBs6T/sxMNk2PH0jQTRW6K0yxZJpzg0p0sJid1gnGoi9SpxCuCGoiH3pmi8/1Pv6OjZ9+njZvqE8IUdGqvUSOrNH1UL03o113FnfJZeS3AsqX/sxMFk2PH0jQTRW6K0yxZppzg0pkwJid1enGoi9SpxCuCGoiH3pmk84tLPtGBP56jTz/bkBCnTbs2GjykQtPGVujQASXqXdgWoxNY6dL/2QmCybFjaZqJIjfFaZYsk05wvpPG5KROLg51kTqVeEVQA/HQO9N0Xrpircad/Re9vXRVQqDc/FwN2Kdcx9f21uS9emhAjwJls/JaMAVM/2cnBSbHjqVpJorcFKdZskw7wflMHJOTOrU41EXqVOIVQQ3EQ+9M1HnN+k06/MJ7tPDFpQmRsnOyVdm3VFNqKzVlYA8NKuukvNzseIgY+Czp/+wEwuTYsTTNRJGb4jRLloknuFQnj8lJlVjjFelWa7UKVJB6EiIymkAcvhsyWiCjwWeqzps31+u0ax/VLQ+/miCRlZWlHr266/DaKh0/qEwjqzqrbR4rrxmVinca+j9vdDsEYnLsWJpmoshNcZoly9QTXCoAMDmp0Pp83zjURepU4hVBDcRD70zX+ad3PqPz//BkI7EKS7po/NhqTRtepprqburYNjceYgY6S/o/O2EwOXYsTTNR5KY4zZJl+gkuGRCYnGQoNd4nDnWROpV4RVAD8dC7Neh854I3dNJlD2lz/dY1pjt26aCaUZ8vMX1g30J179QmHoIGOEv6PztRMDl2LE0zUeSmOM2StYYT3J5gYHL2RGjHv8ehLlKnEq8IaiAeercWnZ98bZkO/sndWrt+U0K4dgVtNXxYb00bU6GJ/YtU3pWV11qiqun/7KhjcuxYmmaiyE1xmiVrLSe43QHB5KReLnGoi9SpxCuCGoiH3q1J5yXLVqnurDla+smahHh5bfK0z34VOmFsbx2+d7H6FLdXdlZWPMQNZJb0f3ZCYHLsWJpmoshNcZola00nuF1BweSkXi5xqIvUqcQrghqIh96tTedP12zQhJ/crcVvfJwQMCc3R33699TRdZU6ap8SDSzrpByWmG62Aqf/s0ONybFjaZqJIjfFaZastZ3gdgYGk5N6ucShLlKnEq8IaiAeerdGnTduqteJP39Qcxe9lRAxKztL5b2LNbmuWscN6qGhvTqrDSuvNUuR0//ZYcbk2LE0zUSRm+I0S9YaT3Dbw3FLIHdUx0b/vFRLWRZ5N1Xk6qJEJdEeLCFt9nHLqERx+G7IKEGaaLCtVeeGhgbN/P0Tuvyu5xqRK+pZqENrqnXikFKNquqqAlZea6LK2pqW/s8OMSbHjqVpJorcFKdZstZ6gtsW0If6MNGwm4GLUSJMTozE3maqcfhuiKeyjWfd2nW+4f6X9e+/fFQNWxdeU+fCTho3ukpfHVmu2j6F6lqQRyk0IQH6Pzu4mBw7lqaZKHJTnGbJWvsJzoHC5PiXS41qNF/zlSUe1PWnmJmRcfhuyExlbEcdB50f/ud7OvLiedqwcXMCXkHH9ho5skrTR5VrQr/u6tG5jdzLRNnsCdD/2THF5NixNM1EkZviNEsWhxNcgxq0TMuiF1xWqzpix+1qyZVQe7XH4CSHqtXtFYfvhlYnmseE4qLzK++u0AFnz9GK1esTlNq0y9d+gys0bWyFJg0oUWX3dhgdjxraUwj9354IJf93TE7yrJp1T4q8WXEnfbC4nOAckDjNNekCYEcI7IIAn5d4lEacdP7o03WR0fnX+ysT4ubm5arf3mWaWlupyfv00IAeBay8Zlz69H92QDE5dixNM1HkpjjNksXpBBenuZoVCIliS4DPSzykj5vO6zZs0pcvnqf5i99PCJydk62K6hIdVVelYwaWalB5R+Xn5sSjAJphlvR/dpAxOXYsTTNR5KY4zZLF6QQXp7maFQiJYkuAz0s8pI+jzvX1DfrurxfohvteSojsnscpKe+uw2qrNHVwT42o7KL2+Rgdi08B/Z8Fxc9zYHLsWJpmoshNcZoli9MJLk5zNSsQEsWWAJ+XeEgfZ52v+L/FOvvGxxsJ3a24i8aPrdaJw8pU26ebOrXLjUchNOEs6f/s4GJy7FiaZqLITXGaJYvTCS5OczUrEBLFlgCfl3hIH3edubybJQAAIABJREFU/7LoLZ34nw9q8+b6hOAdu3TQmFGVmj6iXAf1667uHfNZkCCNjwP9XxrwtgvF5NixNM1EkZviNEsWpxNcnOZqViAkii0BPi/xkB6dpWf+9ZEm/uRufbZ2Y0L0tu3bauiw3po+pkKHDChSede2GB3PjwT9nye4nYRhcuxYmmaiyE1xmiWL0wkuTnM1KxASxZYAn5d4SI/On+v8zkerNe7sOXr/488Swufl52nv/co1taZSR+xVrL4lBcrmXTopfzDo/1JGtssATI4dS9NMFLkpTrNkcTrBxWmuZgVCotgS4PMSD+nReavOq9Zu0KHn3aOnX1uW+Mec3BxV9SvV0TW9NWXfUg3s1Um52bw0NJVPB/1fKrR2vy8mx46laSaK3BSnWbI4neDiNFezAiFRbAnweYmH9OjcWOdNm+v11cse1p8eeyPxh6zsLPWsKNbkuiodN6hUwys6q00eK68l+wmh/0uW1J73w+TsmVGL7EGRtwj2PR40Tie4OM11j8KzAwT2QIDPSzxKBJ131LmhoUHn3/qUfvbHZxr9sai0mw6uqdYJQ3tqTFVXdWjLymvJfEro/5KhlNw+mJzkODX7XhR5syNP6oBxOsHFaa5Jic9OENgNAT4v8SgPdN61zr9/+DV96+q/qb6hIbFT524dVTe6StNGlOmAft3VrSA/HoWSxizp/9KAt10oJseOpWkmitwUp1myOJ3g4jRXswIhUWwJ8HmJh/TovHud//7CBzr8gnu0fuPmxI7tO7TTyBGVmja6lyb2K1JplzasvLYbjPR/dt8lmBw7lqaZKHJTnGbJ4nSCi9NczQqERLElwOclHtKj8551fv39ldHKa8s/XZfYOb9tvgYOrtCJYyt02IASVRa1Y+W1XaCk/9tzjSW7ByYnWVLNvB9F3szAkzxcnE5wcZprkvKzGwR2SYDPSzyKA52T03n5qvU68Mdz9Oq7KxIBuXm56rtXTx1b01tH7luqvUs7KIeV13YASv+XXI0lsxcmJxlKLbAPRd4C0JM4ZJxOcHGaaxLSswsEdkuAz0s8CgSdk9fZ3bI25ZL79NCz7yaCsrOz1au6REfWVunYgaUaXNFR+bmsvLYtVfq/5GtsT3ticvZEqIX+TpG3EPg9HDZOJ7g4zTXMamNUmUSAz0smqeU/VnROjZ1bee0H1y/Ub/76wtbALKlHWXcdWlulqUN6alRlV7XPx+hsAUT/l1qN7W5vTI4dS9NMFLkpTrNkq7VaHdUxyrdUS1WgArPcoSVyJ/MSlUTDcvNuzXMNjT3jyTwCNL+Zp5nPiNHZh5p07dwX9MPfPqat665JXYs666Ax1Zo2vEy1fQrVuT1LTDu69H9+NbazKEyOHUvTTBS5KU6zZB/qw0Tjb5Y0AxJhcjJAJIbYogRoflsUf7MdHJ39Ud/z5BIdd+n9ci8Q3bJ16Fyg0SMrNX1ULx3Ut7uKO+XHfuU1+j//Gts+EpNjx9I0E0VuitMsWRxNTo1qNF/zlaUsM44kgkBrI0Dz29oU3fl80Dk9nf/51nKNnzlXq9dsSCRq276NhgztrRPH9NakAUXq1a1trI0O/V96NbZtNCbHjqVpJorcFKdZsgY1aJmWRfnaq30sGv+4zNOsSEgUSwI0v/GQHZ3T1/mDT9ao7qy/6J1lqxPJ8vLzNGDfcp1Q01uH712i/iUFyo7pymv0f+nX2JYMmBw7lqaZKHJTnCSDAAQg0KQEaH6bFG8wydHZRorP1m3UpPPv0ROvfJhImJOTo8p+pTq6treO2reH9ivrpLzcbJsDZlAW+j87sTA5dixNM1HkpjhJBgEIQKBJCcRpUZImBRl4chZksRNo8+Z6ff2qv+mO+a8nkmZlZalnRZEOq63S8YN6akRlZ7XNi9fKa/R/djWGybFjaZqJIjfFSTIIQAACTUogjs/rNSnQDEjOgiw2Il1yx9O66LanGiUr7NFVE8dW6cRhZRpb3U0d28Zn5TX6P5u6clkwOXYsTTNR5KY4SQYBCECgSQlgcpoUb3DJWZDFVpLb57+ur1/5iOrrty4y3alrR9WMrtT0keU6oE+hundsY3vQQLPR/9kJEyuTs27dOs2ePVu33nqr3n77bXXr1k2TJk3ShRdeqPLy8qSorlixQnfffbfmzJmjZ555Rm+99ZbcG3z32WcfTZs2Td/5zneUl5eXVK7d7USRp42QBBCAAASajUAcFyVpNrgBHogFWexFWfjyUn3p/Hu0bv2mRPJ2HdppxPDemjaqlw4ZUKzSLm1a/cpr9H92tRUbk+MMzoQJE7RgwQKVlpaqrq5Ob775phYtWqSioiI99thj6tOnzx7JnnPOOZo1a1ZkbIYOHaq+fftq2bJl+vvf/67169ertrZW9957r9q3b7/HXJictBA1S7BrXNZoTbMci4M0DwGak+bhzFEgAAEIpErgzaWfqu7sOfpoxdpEaH6bfO07qFe08tphA0pUXdxO2Vmt95UGmJxUq2bX+8fG5Jx77rm66KKLNGbMGM2bN08dOnSIqFx22WWaMWOGxo0bp0ceeWSPZC+99FKtWrUqumJTVlaW2P/VV1/VxIkToytEZ599ti655JI95sLkpIWoyYOdwalVrRZoQZMfiwM0HwFuM2k+1hwJAhCAQKoEVny2XuNn3q0X316eCM3JzVGfvcp0XE1vHTWwVHuXdlBOK11iGpOTasXE3ORs3LhRxcXFcreaPfXUU9EVmG23wYMH67nnntMTTzyh4cOHe9N1t8G5W9YqKyv1xhtveOdxgRR5WvhMgrddKtQkIUmCIcADw8FIwUAgAAEI7EBgw8bNOv5nD+jeJ5ck/ubuoCmvLNbk2iodO6hUQ3t1UptWuPIa/Z/dByIWV3IeeughjR8/Prod7bXXXtuBnrvC4670nHfeeTr//PO96b7wwguROcnPz49uXUtno8jToWcTu63JWaqlKlCBTWKytAgBln5tEewcFAIQgIAXgYaGBv3oxkW65i+Lt8ZnScU9C3Xo2GqdOKyn9q/qqoL81rXENP2fV7nsNCgWJueKK67QGWecoeOOO0533HHHDiDmzp2rI444QkcddZTuuusub7puMYLJkyeroqIiWpAgnY0iT4eeTSwvfbPhGEoW9AxFCcYBAQhAIHkCv7n3Rf3gNwvUsHXhNXXp3lkHjK6KVl6rq+6mLgXpL/iU/Iiadk/6Pzu+sTA5Z555pi6//PLI6LhncLbfnn32WQ0ZMkTDhg3Tk08+6U334IMP1v3336/vfe97uuqqq7zzuECKPC18JsE0xSYYg0mCnsFIwUAgAAEIpETggWfe1ZRL7tPGTZsTcQWd2mv/kVX6yqhyje9XpJJO+a1i5TX6v5RKY7c7x8LknHbaabruuus0c+ZMXXzxxTsAcbew9evXT/3799fLL7/sRfdXv/qVvv3tb6tLly56/vnn1bNnz6TybCnm7Xd+/fXXo9vrXC62liFAU9wy3JvqqOjZVGTJCwEIQKDpCby45BMd+OO5+vSzrY8DtGnXRoMHV+jEmgod2r9Eld3bZrzRweTY1VIsTM6pp56q66+/Xm75Z/f8zfabWxnNGRxfk+NWZTvkkEPkFji48847NWXKlKQVwuQkjarZd6QpbnbkTXpA9GxSvCSHAAQg0OQEPlyxVuPOnqO3ln6aOFZuXq7671uuqTW9NXnvHhrQo0DZGbzyGibHroxiYXKa8nY1tyrbAQccEK3c5m5Rc7eqWWwUuQXF9HLQFKfHL7Ro9AxNEcYDAQhAIHUCa9Zv0hEX3avHXvggEZydk63efXpoSl2Vjh7YQ/uVdVJ+bnbqyQOIoP+zEyEWJqepFh5wt5S5l39+8MEH0apsbnU2q40ityLpn4em2J9diJHoGaIqjAkCEIBA6gTq6xv0rf96VL9/8JVEcFZWlnr06q7Da6t0/KAyjazsrLYZuPIa/V/q9bCriFiYnGSXkHbLSF9wwQVJ0X3vvfcig+Peh3P66afLGSnLjSK3pOmXi6bYj1uoUegZqjKMCwIQgIAfgf/832d17u+faBRcWNJF48dWa9qwMtVUd1PHdrl+yVsoiv7PDnwsTM6GDRuil4GuXLlyty8DXbRokUaOHLlHup988onGjRunxYsX65RTTtFvf/tb8wfdKPI9ytDkO9AUNzniZj0AejYrbg4GAQhAoFkI3PXYm/rqLx7U5vqta0x37NJBNaM+X2L6gL6FKurUplnGYnEQ+j8Lip/niIXJcRN1iw7MmjVLY8eO1bx581RQ8PmLHd2S0jNmzIiuysyfPz9B9pprrpH7zy0iMHv27MS/r1mzRhMmTNDChQt1/PHH65ZbblFOjv2LqChyuyL3zURT7EsuzDj0DFMXRgUBCEAgXQJPvrZMB//kbq1dvymRql1BWw0b1lvTx1RoYv8ilXfNjJXX6P/SrYat8bExOevWrdOBBx6oxx9/XKWlpaqrq4te2On+f2FhYWRa+vbtmyDjnrFxt66ddNJJuvHGGxP/7t61425Nc8Zm6tSpysvb+Quoto3xkYsi96FmG0NTbMuzpbOhZ0srwPEhAAEINB2BJctWqe6sOVr6yZrEQfLa5Gmf/Sp0wtgKHb53ifoUt1d2VlbTDcIgM/2fAcQvUsTG5Lj5rl27Nroq466+LFmyRF27dtWkSZOiZaV79erViOquTM7JJ5+sm266aY8KNGz7at497r3jDhS5BzTjEJpiY6AtnA49W1gADg8BCECgiQl8umZDdEXnuTc+ThwpJzdH1f1LdUxdlY7cu0QDyzspN+Alpun/7IokVibHDlvTZ6LIm57xno5AU7wnQpn1d/TMLL0YLQQgAAEfAhs31WvaLx7UnMffSoRnZWeprHexvlxbpeMGl2por85qk2f/qIHPeLePof+zoPh5DkyOHUvTTBS5KU6vZDTFXtiCDULPYKVhYBCAAARMCbi7ac75/RO67K7nGuUt6tlNh9RU68QhPTW6qqsK2oa38hr9n10pYHLsWJpmoshNcXoloyn2whZsEHoGKw0DgwAEINAkBG584BV9578e1baPEHQu7KQ6t/LaiJ46oF93dS3Ib5Jj+yal//Mlt2McJseOpWkmitwUp1cymmIvbMEGoWew0jAwCEAAAk1G4JHF7+nLF83Tho2bE8do37G99h9RpemjyzShb5F6dGlj/ioQ3wnR//mSw+TYkWviTBR5EwNOIj1NcRKQMmgX9MwgsRgqBCAAAUMCr767QuN+PEcrVq1PZG3TNl/7Da7QiWMr9KW9SlTZvV0QRof+z054ruTYsTTNRJGb4vRKRlPshS3YIPQMVhoGBgEIQKDJCXz06Tod+OM5ev29lYlj5eblqt9eZTq+rlJf3rtEA0o7KKeFV16j/7MrBUyOHUvTTBS5KU6vZDTFXtiCDULPYKVhYBCAAASahcC6DZt05Kz79Ld/vpc4XnZOtiqqS3RkXZWOHViqQeUdlZ/bciuv0f/ZlQImx46laSaK3BSnVzKaYi9swQahZ7DSMDAIQAACzUagvr5B3/31At1w30uJY2ZlZamkvLsm1VTqxCFlGlHZRe3zW8bo0P/ZlQImx46laSaK3BSnVzKaYi9swQahZ7DSMDAIQAACzU7gyv9brLNufLzRcbsVd9FBY6s1bViZavt0U6d2zb/ENP2fXSlgcuxYmmaiyE1xeiWjKfbCFmwQegYrDQODAAQg0CIE5ix6Syf854PavLk+cfwOnQs0xi0xPbJcB/XtrqJO+c26IAH9n10pYHLsWJpmoshNcXoloyn2whZsEHoGKw0DgwAEINBiBJ5942NNOGeuPlu7MTGGtu3bauiw3po2pkKHDChSr65tm83o0P/ZlQImx46laSaK3BSnVzKaYi9swQahZ7DSMDAIQAACLUrgveWfqe6sOXrvo9WJceTl52nvgeU6vqZSk/cuVt+SAmVnZTX5OOn/7BBjcuxYmmaiyE1xeiWjKfbCFmwQegYrDQODAAQg0OIEVq/dqEPP+6ueem1ZYiw5uTmq6leqo2t6a8q+pRpY3km5OU1rdOj/7EoBk2PH0jQTRW6K0ysZTbEXtmCD0DNYaRgYBCAAgSAIbNpcr69e/rD+tOCNxHiysrPUs6JYR9RW6fjBpRpe0Vlt8ppu5TX6P7tSwOTYsTTNRJGb4vRKRlPshS3YIPQMVhoGBgEIQCAYAg0NDbrgtqf00/95ptGYuvfopkNqq3TC0DKNqeqqDm2bZuU1+j+7UsDk2LE0zUSRm+L0SkZT7IUt2CD0DFYaBgYBCEAgOAK3/u01ffPKv6m+oSExtk5dO6p2TJW+MqJMB/Trrm4F+ebjpv+zQ4rJsWNpmokiN8XplYym2AtbsEHoGaw0DAwCEIBAkAQWvLhUh13wV63fsDkxvnYd2mnkiEpNH91LE/sVqbRLG9OV1+j/7EoBk2PH0jQTRW6K0ysZTbEXtmCD0DNYaRgYBCAAgWAJ/Ov9lao7e46Wf7ouMcb8tvkaOKhCJ9ZU6EsDSlRV1M5s5TX6P7tSwOTYsTTNRJGb4vRKRlPshS3YIPQMVhoGBgEIQCBoAstXrddBM+folXdWJMaZm5ervnv11LE1vXXkvqXau7SDcrLTX3mN/s+uFDA5dixNM1Hkpji9ktEUe2ELNgg9g5WGgUEAAhAInsD6jZt1zOz79cAz7yTGmp2drfLqEh1ZW6XjBpZqcEVH5eemt/Ia/Z9dKWBy7FiaZqLITXF6JaMp9sIWbBB6BisNA4MABCCQEQTcymtn/Hahfn33C1vHmyWV9CzUpNpqTR3aU6Mqu6p9vr/Rof+zKwVMjh1L00wUuSlOr2Q0xV7Ygg1Cz2ClYWAQgAAEMorAL//6gmZc95i2rrsmdS3qrANGV2n6iHLV9ilUl/Z+S0zT/9mVAibHjqVpJorcFKdXMppiL2zBBqFnsNIwMAhAAAIZR+Dep97RsZfep02b6hNjL+hUoDH7V2r6qF46qG93FXfKT3nlNfo/u1LA5NixNM1EkZvi9EpGU+yFLdgg9AxWGgYGAQhAICMJLH5rucbPnKtVazYkxt+mXRsNGdpb08ZW6ND+xaoobJuS0aH/sysFTI4dS9NMFLkpTq9kNMVe2IINQs9gpWFgEIAABDKWwAefrNG4s+ZoybJViTnk5udqr316aWptbx2xd4n6lxQoO8mV1+j/7EoBk2PH0jQTRW6K0ysZTbEXtmCD0DNYaRgYBCAAgYwm8Nm6jfrSBffqHy8vTcwjOydblX1LdXRdpabs20P7lXVSXm72HudJ/7dHREnvgMlJGlXz7kiRNy/vnR2NprjlNbAcAXpa0iQXBCAAAQhsS2Dz5np94+r5uv1vryX+OSsrSz0rinRYbZWOH9RTIyo7q23e7ldeo/+zqytMjh1L00wUuSlOr2Q0xV7Ygg1Cz2ClYWAQgAAEWg2BS+54Whfd9lSj+RT26KqJY6t04rAyja3upo5td73yGv2fXSlgcuxYmmaiyE1xeiWjKfbCFmwQegYrDQODAAQg0KoI3PHov3TKFQ+rvn7rItOdunZUzahKTR9ZrgP6Fqp7xzY7nTP9n10pYHLsWJpmoshNcXoloyn2whZsEHoGKw0DgwAEINDqCDz+yof60nl/1dr1mxJza1fQTsOH99b00b108IAi9eyy48pr9H92pYDJsWNpmokiN8XplYym2AtbsEHoGaw0DAwCEIBAqyTw1tJVqjt7jpatWJOYX36bfO07qJdOqOmtwwaUqLq4nbKzshJ/p/+zKwVMjh1L00wUuSlOr2Q0xV7Ygg1Cz2ClYWAQgAAEWi2BlZ9t0Phz5uqFt5Yn5piTm6M+A8p0TG1vTdm3VPv07KCcL5aYpv+zKwVMjh1L00wUuSlOr2Q0xV7Ygg1Cz2ClYWAQgAAEWjWBDRs3a+p/Pqh7nng7Mc/s7GyVVxZrcm2Vjh1UquG9OysvJ1v0f3algMmxY2maiSI3xemVjKbYC1uwQegZrDQMDAIQgECrJ9DQ0KD/d9M/dPX//bPRXIvLCnXo2GpddFh/lXRui8kxrARMjiFMy1SYHEuafrloiv24hRqFnqEqw7ggAAEIxIfA9fNe0vd//Xc1bF14TV0KO+vucyZqaO8umBzDUsDkGMK0TIXJsaTpl4um2I9bqFHoGaoyjAsCEIBAvAg88Oy7mjLrPm3ctDmaeE5Otp6/9lj1Lu6IyTEsBUyOIUzLVJgcS5p+uWiK/biFGoWeoSrDuCAAAQjEj8BLS1bowJlztHL1et1x9kRNHtk7gkD/Z1cLmBw7lqaZKHJTnF7JaIq9sAUbhJ7BSsPAIAABCMSSwLKVa/W3xe/rmJrqxPzp/+xKAZNjx9I0E0VuitMrGU2xF7Zgg9AzWGkYGAQgAAEIfEGA/s+uFDA5dixNM1Hkpji9ktEUe2ELNgg9g5WGgUEAAhCAACbHvAYwOeZIbRJicmw4ppOFpjgdeuHFomd4mjAiCEAAAhBoTID+z64iMDl2LE0zUeSmOL2S0RR7YQs2CD2DlYaBQQACEIAAV3LMawCTY47UJiEmx4ZjOlloitOhF14seoanCSOCAAQgAAGu5DRVDWBymopsmnkxOWkCNAinKTaAGFAK9AxIDIYCAQhAAAI7JUD/Z1cYmBw7lqaZKHJTnF7JaIq9sAUbhJ7BSsPAIAABCEDgCwL0f3algMmxY2maiSI3xemVjKbYC1uwQegZrDQMDAIQgAAEMDnmNYDJMUdqkxCTY8MxnSw0xenQCy8WPcPThBFBAAIQgEBjAvR/dhWBybFjaZqJIjfF6ZWMptgLW7BB6BmsNAwMAhCAAAS4kmNeA5gcc6Q2CTE5NhzTyUJTnA698GLRMzxNGBEEIAABCHAlp6lqAJPTVGTTzIvJSROgQThNsQHEgFKgZ0BiMBQIQAACENgpAfo/u8LA5NixNM1EkZvi9EpGU+yFLdgg9AxWGgYGAQhAAAJfEKD/sysFTI4dS9NMFLkpTq9kNMVe2IINQs9gpWFgEIAABCCAyTGvAUyOOVKbhJgcG47pZKEpTodeeLHoGZ4mjAgCEIAABBoToP+zqwhMjh1L00wUuSlOr2Q0xV7Ygg1Cz2ClYWAQgAAEIMCVHPMawOSYI7VJiMmx4ZhOFpridOiFF4ue4WnCiCAAAQhAgCs5TVUDmJymIptmXkxOmgANwmmKDSAGlAI9AxKDoUAAAhCAwE4J0P/ZFQYmx46laSaK3BSnVzKaYi9swQahZ7DSMDAIQAACEPiCAP2fXSlgcuxYmmaiyE1xeiWjKfbCFmwQegYrDQODAAQgAAFMjnkNYHLMkdokxOTYcEwnC01xOvTCi0XP8DRhRBCAAAQg0JgA/Z9dRWBy7FiaZqLITXF6JaMp9sIWbBB6BisNA4MABCAAAa7kmNcAJsccqU1CTI4Nx3Sy0BSnQy+8WPQMTxNGBAEIQAACXMlpqhrA5DQV2TTzYnLSBGgQTlNsADGgFOgZkBgMBQIQgAAEdkqA/s+uMDA5dixNM1Hkpji9ktEUe2ELNgg9g5WGgUEAAhCAwBcE6P/sSgGTY8fSNBNFborTKxlNsRe2YIPQM1hpGBgEIAABCGByzGsAk2OO1CYhJseGYzpZaIrToRdeLHqGpwkjggAEIACBxgTo/+wqApNjx9I0E0VuitMrGU2xF7Zgg9AzWGkYGAQgAAEIcCXHvAYwOeZIbRJicmw4ppOFpjgdeuHFomd4mjAiCEAAAhDgSk5T1QAmp6nIppkXk5MmQINwmmIDiAGlQM+AxGAoEIAABCCwUwL0f3aFgcmxY2maiSI3xemVjKbYC1uwQegZrDQMDAIQgAAEviBA/2dXCpgcO5ammShyU5xeyWiKvbAFG4SewUrDwCAAAQhAAJNjXgOYHHOkNgkxOTYc08lCU5wOvfBi0TM8TRgRBCAAAQg0JkD/Z1cRmBw7lqaZKHJTnF7JaIq9sAUbhJ7BSsPAIAABCECAKznmNYDJMUdqkxCTY8MxnSw0xenQCy8WPcPThBFBAAIQgABXcpqqBjA5TUU2zbyYnDQBGoTTFBtADCgFegYkBkOBAAQgAIGdEqD/sysMTI4dS9NMFLkpTq9kNMVe2IINQs9gpWFgEIAABCDwBQH6P7tSwOTYsTTNRJGb4vRKRlPshS3YIPQMVhoGBgEIQAACmBzzGsDkmCO1SYjJseGYThaa4nTohReLnuFpwoggAAEIQKAxAfo/u4rA5NixNM1EkZvi9EpGU+yFLdgg9AxWGgYGAQhAAAJcyTGvAUyOOVKbhJgcG47pZKEpTodeeLHoGZ4mjAgCEIAABLiS01Q1gMlpKrJp5sXkpAnQIJym2ABiQCnQMyAxGAoEIAABCOyUAP2fXWFgcuxYmmaiyE1xeiWjKfbCFmwQegYrDQODAAQgAIEvCND/2ZUCJseOpWkmitwUp1cymmIvbMEGoWew0jAwCEAAAhDA5JjXACbHHKlNQkyODcd0stAUp0MvvFj0DE8TRgQBCEAAAo0J0P/ZVQQmx46laSaK3BSnVzKaYi9swQahZ7DSMDAIQAACEOBKjnkNYHLMkdokxOTYcEwny2qtVkd1jFIs1VIVqCCddMS2MAFnckpUEo3CaYueLSwIh4cABCAAgR0I0P/ZFQUmx46laSaK3BSnV7IP9WGiKfZKQFCwBDA5wUrDwCAAAQjEmgD9n538mBw7lqaZKHJTnF7JMDle2IIPqlGN5mu+spQV/FgZIAQgAAEIxIsA/Z+d3pgcO5ammShyU5xeyRrUoGVaFsW2V3uaYi+K4QWhZXiaMCIIQAACEPicAP2fXSVgcuxYmmaiyE1xkgwCEIAABCAAAQgET4D+z04iTI4dS9NMFLkpTpJBAAIQgAAEIACB4AnQ/9lJhMmxY2maiSI3xUkyCEAAAhCAAAQgEDwB+j87iTA5dixNM1HkpjhJBgEIQAACEIAABIInQP9nJxEmx46laSaK3BQnySAAAQhAAAIQgEDwBOj/7CTC5NhaRZlsAAAWnElEQVSxNM1EkZviJBkEIAABCEAAAhAIngD9n51EmBw7lqaZKHJTnCSDAAQgAAEIQAACwROg/7OTKFYmZ926dZo9e7ZuvfVWvf322+rWrZsmTZqkCy+8UOXl5SlRXbFihc4//3zddddd+uCDD9SjRw8dddRRuuCCC9SlS5eUcu1sZ4o8bYQkgAAEIAABCEAAAhlFgP7PTq7YmBxncCZMmKAFCxaotLRUdXV1evPNN7Vo0SIVFRXpscceU58+fZIi+/HHH2vMmDF69dVXVV1drREjRuj555+P/uvbt68WLlyowsLCpHLtaieKPC18BEMAAhCAAAQgAIGMI0D/ZydZbEzOueeeq4suuigyJ/PmzVOHDh0iipdddplmzJihcePG6ZFHHkmK7Ne+9jXdfPPNOvroo3X77bcrNzc3ivv+97+vq6++Wu7vN910U1K5MDlpYSIYAhCAAAQgAAEItBoCmBw7KWNhcjZu3Kji4mK5W8yeeuopDR06tBHBwYMH67nnntMTTzyh4cOH75auuzWtrKxMOTk5WrJkiUpKShL7r1+/Xr169dLy5cv17rvvNvpbqpJR5KkSY38IQAACEIAABCCQ2QTo/+z0i4XJeeihhzR+/PjodrTXXnttB3ruCo+70nPeeedFz9nsbrvhhhv09a9/Pbr17f77799h12984xv63e9+J7ffySef7K0URe6NjkAIQAACEIAABCCQkQTo/+xki4XJueKKK3TGGWfouOOO0x133LEDvblz5+qII46IFg5wCwnsbvvBD36gK6+8Uj/84Q/1s5/9bIddr732Wn33u9+V2+/yyy/3Vooi90ZHIAQgAAEIQAACEMhIAvR/drLFwuSceeaZkeFwRsc9g7P99uyzz2rIkCEaNmyYnnzyyd3Sdc/hOCPkjI57Bmf77c9//nNkltx+d955p7dSFLk3OgIhAAEIQAACEIBARhKg/7OTLRYm57TTTtN1112nmTNn6uKLL96BnruFrV+/furfv79efvnl3dI95JBDdN9990X5vvnNb+6wr7uF7eCDD5bb7957792jUluKefsdX3rpJeXl5SW94tseD8QOEIAABCAAAQhAAAJBE3j99dej/m/VqlVBjzMTBhcLk3Pqqafq+uuv1znnnBOtsLb95paCdgYnGZPjDIwzMi6fe/5m+80ZIGdw0jU5L7zwgrKzs7XXXntlQh0xRmMC7kvObckua258eNK1MAH0b2EBWvjw6N/CArTw4dG/hQVo4cO7H7mzsrK0adOmFh5J5h8+FiaH29Uyv1DjNgMuV8dN8cbzRX/0dwTcu9fY4keAz3/8NN92xuhvp38sTA4LD9gVDJmahwBfcs3DOdSjoH+oyjTPuNC/eTiHehT0D1WZ5hkX+ttxjoXJSXYJabeM9AUXXLBbuskuIe2WkT7llFO8laLIvdG1ikD0bxUyek8C/b3RtYpA9G8VMnpPAv290bWKQPS3kzEWJmfDhg3Ry0BXrly525eBLlq0SCNHjtwt3ffff1/l5eXKzc2NXgbq8m7ZtrwM9OOPP45eBtqjRw9vpShyb3StIhD9W4WM3pNAf290rSIQ/VuFjN6TQH9vdK0iEP3tZIyFyXG43KIDs2bN0tixYzVv3jwVFBREFN2S0jNmzFBtba3mz5+fIHvNNdfI/TdlyhTNnj27EfGvfOUr+sMf/qBjjjlGt912W2R43Hb66afrqquukvv7zTffnJZKFHla+DI+GP0zXsK0JoD+aeHL+GD0z3gJ05oA+qeFL+OD0d9OwtiYnHXr1unAAw/U448/rtLSUtXV1emtt96K/n9hYaEWLlyovn37Jsief/750a1rJ510km688cZGxD/66CONHj1abgUUt/rViBEjogdEFy9eHP1/l6t79+5pqUSRp4Uv44PRP+MlTGsC6J8WvowPRv+MlzCtCaB/WvgyPhj97SSMjclxyNauXRtdlbnllluiW826du2qSZMmRctK9+rVqxHV3Zkct+Mnn3yi8847T3/605+0dOlSlZSU6Mgjj4yMUbdu3ewUIhMEIAABCEAAAhCAAAQgkBKBWJmclMiwMwQgAAEIQAACEIAABCCQkQQwORkpG4OGAAQgAAEIQAACEIAABHZFAJNDbUAAAhCAAAQgAAEIQAACrYoAJqdVyclkIAABCEAAAhCAAAQgAAFMDjUAAQhAAAIQgAAEIAABCLQqApicViUnk4EABCAAAQhAAAIQgAAEMDnUAAQgAAEIQAACEIAABCDQqghgcppJTvcyUveOnltvvVVvv/129C4d946eCy+8UOXl5SmNYsWKFXLv8bnrrrv0wQcfqEePHjrqqKOid/R06dIlpVzs3DwELPR3ut99992aM2eOnnnmmehlttnZ2dpnn300bdo0fec731FeXl7zTIijpETAQv+dHfDVV1/VoEGD5PIfeuihuueee1IaFzs3DwFr/V977TX99Kc/1X333RedAzp27Kh+/fppypQp+uEPf9g8k+IoSRGw1N59vq+88kr94x//0MqVK6N3/e2///4644wzNGHChKTGw07NR+DJJ5+MPqOLFi2KXjz/3nvvqU2bNtH3tc9G75c6NUxO6sxSjnAF7b6AFixYoNLSUtXV1enNN9+MCr+oqEiPPfaY+vTpk1Tejz/+WGPGjJFrbqqrqzVixAg9//zz0X99+/bVwoULVVhYmFQudmoeAlb6n3POOZo1a1ZkbIYOHRrpvWzZMv3973/X+vXrVVtbq3vvvVft27dvnolxlKQIWOm/s4ONHz9eDz/8sBoaGjA5SanR/DtZ6+9+3HI/arjPvPse6N+/v9x54Z///KcKCgrkDBBbGAQstb/ssss0Y8YMZWVlqaamRmVlZfrXv/4VGR63/fKXv9S//du/hTFxRhERcD8+//nPf25Ew9fk0Pv5FRUmx49bSlHnnnuuLrroosiczJs3Tx06dIjit3xpjRs3To888khSOb/2ta/p5ptv1tFHH63bb79dubm5Udz3v/99XX311XJ/v+mmm5LKxU7NQ8BK/0svvVSrVq2Krti4E9yWzRneiRMnRlcIzz77bF1yySXNMzGOkhQBK/23P9hvf/tbffOb39Rpp52m3/zmN5icpNRo/p0s9X/22WejX+7dlZs//elP0Q8bW7b6+no99dRT0Q9fbGEQsNLe/Zi15Y6PBx54oJHud955p4477ji1a9dOS5cuTfQXYRCI9yjc1dY1a9Zo5MiR0X/urhtfk0Pv51dLmBw/bklHbdy4UcXFxXKXGd0JyP3ytu02ePBgPffcc3riiSc0fPjw3eZ1tyW45jYnJ0dLlixRSUlJYn/3q16vXr20fPlyvfvuu43+lvRg2dGcgKX+uxucuw3S/bpbWVmpN954w3weJPQj0FT6f/jhh9prr72i74yZM2fqoIMOwuT4SdSkUdb6ux/E5s+fr7/85S864ogjmnTsJE+PgKX27hblyZMnR7e4//Wvf91hYEOGDJEzwO6WKGeC2cIk4K7C+Zgcej9/PTE5/uySinzooYfkbilxt6Pt7DYCd4XH/dpz3nnnRc/Z7G674YYb9PWvfz269e3+++/fYddvfOMb+t3vfie338knn5zU+NipaQlY6r+7kb7wwgvad999lZ+fH93GwhYGgabS/4QTTohug3C3KL3zzjuYnDDk3mEUlvq/+OKL0fN37va0l19+OdAZM6wtBCy1d891HHLIIXs0Oe6qvruNmS1MAr4mh97PX09Mjj+7pCKvuOKK6KFAdzn5jjvu2CFm7ty50S9y7t5Nd6/17rYf/OAH0UOH7sHSn/3sZzvseu211+q73/2u3H6XX355UuNjp6YlYKn/7ka65Ze+ioqKaEECtjAINIX+bvGJww8/PFq05Cc/+Un0TA5XcsLQe/tRWOp/zTXX6Hvf+57+/d//XT//+c+j25XdHQCucXKLTxx//PHq1KlTmCBiOCpL7d2dIO4q/dq1a7X97Wr/+7//q2OPPTa6Hd49n8kWLgFfk0Pv568pJsefXVKRZ555ZmQ4nNFxz+Bsv7lLzO5S87Bhw+RW4tjd5p7DcUbIGR33DM72m/tl15klt5+7T5et5QlY6r+72Rx88MHR1T3XBF111VUtP3FGEBGw1v+zzz6Lrti1bds2us3VXbnD5IRbbJb6f/vb39avfvUr/cd//Ed0u9r2V3O6d+8efe+7W9rYWp6ApfZuNn/84x81ffp0udvgtiw84G5NdgsPuNvYbrzxxujWeLZwCfiaHHo/f00xOf7skop0DwVfd9110X3zF1988Q4x7hY2t/RnMrcguMvV7rK1y+ceON5+c02ua3bdfm6VLbaWJ2Cp/65m4xof1wC55cPdKns9e/Zs+YkzgoiAtf7uxxL3C/GDDz4YXb1xGyYn3GKz1N/dorhlsRm3dPCvf/3r6FZo97C5e33ALbfcEi0p7L4D3CqebC1LwFL7LTNxn/upU6fqo48+SkzOPZvrjK/7bnDP67KFS8DX5ND7+WuKyfFnl1Tkqaeequuvv15u+V/3/M32m7uH1hmcZEzOll/rXT73/M3225b7djE5SUnTLDtZ6r+zAbtV+Zze7tc99yuue08GWzgELPV3tyaNHj06+jV32xUUMTnh6L39SCz1d7c8u1/z3eZ+xHKf+20398C5+1V/Vz+ohUupdY7MUntH6Be/+IV+9KMfRXdruOd33Ssk3BLS7plet9LeMccck6iP1kk082fla3Lo/fy1x+T4s0sq0vKSNZcsk0Ie1E6W+m8/MXe70gEHHBCt3OduUXO3qrGFRcBK/02bNkVLkLplwl966aXo/VpbNkxOWJpvOxor/V1Ot+iMewDZrbDpFpvYfnPvSXHLy7tbmR599NFwocRkZJbaux+zDjzwwOi2dmdk3bvStmybN2+OvhuefvrpnZrfmODOiGn6mhx6P395MTn+7JKKtHz4kIfPkkIe1E6W+m87sddffz16V4JbWtL9qudW52MLj4CV/u7lwVVVVdF7FgYMGNBoos7kumf73K1K7gF09x4utxAFW8sTsNLfzcQtNOE+52PHjt3pA+ZuaeHDDjssuv35lVdeafnJx3wEltpvWTnV3fLurtRtv7l/d4uQ8J60sIvO1+TQ+/nrisnxZ5dUZLLLSLpLzu6+6t1tyS4j6JaRPuWUU5IaHzs1LQFL/beM9L333osMjnvo9PTTT4+e0WALk4CV/ltMTjKz7Ny5c3R1j63lCVjp72biFhv48pe/HL0fyS0nvf32+9//Xl/96lejd7G5d7KxtSwBS+0PPfTQ6EXiu7pi7/7dnQu+9a1vRYtTsIVJwNfk0Pv564nJ8WeXVOSGDRuiFU9Wrly525eBLlq0KLrkvLvt/fffj956nJubG70MdNuVVLa8DPTjjz+OXgbqfvFla3kClvq72XzyySfR6kmLFy+OjKx767374mQLk4C1/jubJberham9G5Wl/u7N6e473+V0V3Ldy5+33dxiNO77wP3q757bZGtZApban3TSSfrv//5vubfeb/s83pYZOnPrTO7s2bN11llntezEOfouCfiaHHo//6LC5PizSzrSLTowa9as6DYD92tMQUFBFOuWlJ4xY0b0q7x7i/WWzb0Pwf3nHiJ3X1rbbl/5ylf0hz/8IXrI8LbbbosMj9vcrzju1xz395tvvjnpsbFj0xOw0t81Oe5FsAsXLozeieFWU2I1nabXL90jWOm/q3FgctJVqGnjLfV3tyNdeuml0XuS3EprW84l99xzjyZPniz3fIb7fuCt902rabLZrbR3r45wz2W473v3v53WWzb36gj3N7e5l0JvfztrsmNlv6YnsCeTQ+9nrwEmx57pDhnXrVsXPTT4+OOPR0t71tXVRS9sdP+/sLAwOilt+5Zi94yFu3XN/Xrj1r7fdnNLR7oVltwveX369NGIESOiJUPdL/vu/7tc7n0JbOEQsNJ/y/LB7kTnlhHNy8vb6SS3r5lwSMRzJFb6Y3Iys34s9Xe5Jk6cGD2T484lo0aN0ocffhh979fX10c/pv34xz/OTFCtcNRW2jc0NETf+f/zP/8TUXLnffeMnrtl2a266Da0D6+A3Mvet11V1/V8zuhs+yOEe5bK/WjhNno/ew0xOfZMd5rRvanYXZVxv767W83cQ8LuBV7uA7D9bQe7K3SX3N2y5B5AdctGunckuHXyjzzyyMgYdevWrZlmxGFSIWCh/8knn7zTWxW2H4c7IbKFRcBCf0xOWJqmMhpL/d1tUD//+c+j25PcEsLuxbCu6XU/gmxpllIZG/s2LQEr7d33uns2w92u5lbWXL16dfRuNNcwu5U1XT/BFhYB94Pjnp6Pdpq6c/ueTA69n5+2mBw/bkRBAAIQgAAEIAABCEAAAoESwOQEKgzDggAEIAABCEAAAhCAAAT8CGBy/LgRBQEIQAACEIAABCAAAQgESgCTE6gwDAsCEIAABCAAAQhAAAIQ8COAyfHjRhQEIAABCEAAAhCAAAQgECgBTE6gwjAsCEAAAhCAAAQgAAEIQMCPACbHjxtREIAABCAAAQhAAAIQgECgBDA5gQrDsCAAAQhAAAIQgAAEIAABPwKYHD9uREEAAhCAAAQgAAEIQAACgRLA5AQqDMOCAAQgAAEIQAACEIAABPwIYHL8uBEFAQhAAAIQgAAEIAABCARKAJMTqDAMCwIQgAAEIAABCEAAAhDwI4DJ8eNGFAQgAAEIQAACEIAABCAQKAFMTqDCMCwIQAACEIAABCAAAQhAwI8AJsePG1EQgAAEIAABCEAAAhCAQKAEMDmBCsOwIAABCEAAAhCAAAQgAAE/ApgcP25EQQACEIAABCAAAQhAAAKBEsDkBCoMw4IABCAAAQhAAAIQgAAE/Ahgcvy4EQUBCEAAAhCAAAQgAAEIBEoAkxOoMAwLAhCAAAQgAAEIQAACEPAjgMnx40YUBCAAAQhAAAIQgAAEIBAoAUxOoMIwLAhAAAIQgAAEIAABCEDAjwAmx48bURCAAAQgAAEIQAACEIBAoAQwOYEKw7AgAAEIQAACEIAABCAAAT8CmBw/bkRBAAIQgAAEIAABCEAAAoESwOQEKgzDggAEIAABCEAAAhCAAAT8CGBy/LgRBQEIQAACEIAABCAAAQgESgCTE6gwDAsCEIAABCAAAQhAAAIQ8COAyfHjRhQEIAABCEAAAhCAAAQgECgBTE6gwjAsCEAAAhCAAAQgAAEIQMCPACbHjxtREIAABCAAAQhAAAIQgECgBDA5gQrDsCAAAQhAAAIQgAAEIAABPwKYHD9uREEAAhCAAAQgAAEIQAACgRLA5AQqDMOCAAQgAAEIQAACEIAABPwIYHL8uBEFAQhAAAIQgAAEIAABCARKAJMTqDAMCwIQgAAEIAABCEAAAhDwI4DJ8eNGFAQgAAEIQAACEIAABCAQKAFMTqDCMCwIQAACEIAABCAAAQhAwI8AJsePG1EQgAAEIAABCEAAAhCAQKAEMDmBCsOwIAABCEAAAhCAAAQgAAE/ApgcP25EQQACEIAABCAAAQhAAAKBEsDkBCoMw4IABCAAAQhAAAIQgAAE/Ahgcvy4EQUBCEAAAhCAAAQgAAEIBEoAkxOoMAwLAhCAAAQgAAEIQAACEPAjgMnx40YUBCAAAQhAAAIQgAAEIBAoAUxOoMIwLAhAAAIQgAAEIAABCEDAjwAmx48bURCAAAQgAAEIQAACEIBAoAQwOYEKw7AgAAEIQAACEIAABCAAAT8C/x8icRGfPMGzDgAAAABJRU5ErkJggg==\" width=\"550\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "agglo_sm_clf.draw_hyperbox_and_boundary(\"The trained GFMM classifier and its decision boundaries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b464cb77",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of hyperboxes =  30\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of hyperboxes = \", agglo_sm_clf.get_n_hyperboxes())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32bbd7fa",
   "metadata": {},
   "source": [
    "#### Make prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f6189a08",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy =  84.90%\n"
     ]
    }
   ],
   "source": [
    "y_pred_agglosm = agglo_sm_clf.predict(Xtest)\n",
    "acc = accuracy_score(ytest, y_pred_agglosm)\n",
    "print(f'Accuracy = {acc * 100: .2f}%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6b7314d",
   "metadata": {},
   "source": [
    "#### Store the trained model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b93b238b",
   "metadata": {},
   "outputs": [],
   "source": [
    "store_model(agglo_sm_clf, \"store_agglosm_model.dummy\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b45aad4f",
   "metadata": {},
   "source": [
    "#### Reload the trained model and make prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7d0d115d",
   "metadata": {},
   "outputs": [],
   "source": [
    "trained_agglo_sm_clf = load_model(\"store_agglosm_model.dummy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "068655f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy =  84.90%\n"
     ]
    }
   ],
   "source": [
    "y_pred_trained_agglosm_model = trained_agglo_sm_clf.predict(Xtest)\n",
    "acc = accuracy_score(ytest, y_pred_trained_agglosm_model)\n",
    "print(f'Accuracy = {acc * 100: .2f}%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45e90a42",
   "metadata": {},
   "source": [
    "#### Continue to train the deployed model using another training set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "2978d6c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgglomerativeLearningGFMM(min_simil=0, simil_measure='long', theta=0.2)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trained_agglo_sm_clf.fit(X_tr2, y_tr2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d7da39f",
   "metadata": {},
   "source": [
    "#### Display decision boundaries among classes if input data are 2-dimensional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5b6c7b05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // 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=\"550.6666666666666\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trained_agglo_sm_clf.draw_hyperbox_and_boundary(\"The trained GFMM classifier and its decision boundaries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "cd399498",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of hyperboxes =  51\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of hyperboxes = \", trained_agglo_sm_clf.get_n_hyperboxes())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27a833e5",
   "metadata": {},
   "source": [
    "#### Make prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "aafb569d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy =  87.90%\n"
     ]
    }
   ],
   "source": [
    "y_pred_agglosm = trained_agglo_sm_clf.predict(Xtest)\n",
    "acc = accuracy_score(ytest, y_pred_agglosm)\n",
    "print(f'Accuracy = {acc * 100: .2f}%')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}