RateRegression.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib.ticker\n",
    "\n",
    "%matplotlib notebook\n",
    "\n",
    "#Linear Regression\n",
    "from sklearn import linear_model\n",
    "\n",
    "#used for 3D plot\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from matplotlib import cm\n",
    "\n",
    "#igore warning\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading data and preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>US0001M</th>\n",
       "      <th>US0002M</th>\n",
       "      <th>US0003M</th>\n",
       "      <th>US0006M</th>\n",
       "      <th>US0012M</th>\n",
       "      <th>USSW2</th>\n",
       "      <th>USSW3</th>\n",
       "      <th>USSW5</th>\n",
       "      <th>USSW7</th>\n",
       "      <th>USSW10</th>\n",
       "      <th>USSW15</th>\n",
       "      <th>USSW30</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-01-02 00:00:00</td>\n",
       "      <td>0.1683</td>\n",
       "      <td>0.21250</td>\n",
       "      <td>0.24285</td>\n",
       "      <td>0.3464</td>\n",
       "      <td>0.5826</td>\n",
       "      <td>0.4903</td>\n",
       "      <td>0.8705</td>\n",
       "      <td>1.7740</td>\n",
       "      <td>2.4540</td>\n",
       "      <td>3.0610</td>\n",
       "      <td>3.5613</td>\n",
       "      <td>3.8950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-01-03 00:00:00</td>\n",
       "      <td>0.1647</td>\n",
       "      <td>0.20995</td>\n",
       "      <td>0.23985</td>\n",
       "      <td>0.3452</td>\n",
       "      <td>0.5846</td>\n",
       "      <td>0.5113</td>\n",
       "      <td>0.9000</td>\n",
       "      <td>1.7920</td>\n",
       "      <td>2.4648</td>\n",
       "      <td>3.0665</td>\n",
       "      <td>3.5635</td>\n",
       "      <td>3.8953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-01-06 00:00:00</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.20825</td>\n",
       "      <td>0.23935</td>\n",
       "      <td>0.3445</td>\n",
       "      <td>0.5854</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>0.8760</td>\n",
       "      <td>1.7468</td>\n",
       "      <td>2.4203</td>\n",
       "      <td>3.0260</td>\n",
       "      <td>3.5315</td>\n",
       "      <td>3.8738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-01-07 00:00:00</td>\n",
       "      <td>0.1615</td>\n",
       "      <td>0.20820</td>\n",
       "      <td>0.24210</td>\n",
       "      <td>0.3447</td>\n",
       "      <td>0.5866</td>\n",
       "      <td>0.4985</td>\n",
       "      <td>0.8735</td>\n",
       "      <td>1.7375</td>\n",
       "      <td>2.4065</td>\n",
       "      <td>3.0098</td>\n",
       "      <td>3.5145</td>\n",
       "      <td>3.8580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-01-08 00:00:00</td>\n",
       "      <td>0.1610</td>\n",
       "      <td>0.20750</td>\n",
       "      <td>0.24040</td>\n",
       "      <td>0.3452</td>\n",
       "      <td>0.5856</td>\n",
       "      <td>0.5350</td>\n",
       "      <td>0.9520</td>\n",
       "      <td>1.8280</td>\n",
       "      <td>2.4835</td>\n",
       "      <td>3.0650</td>\n",
       "      <td>3.5500</td>\n",
       "      <td>3.8703</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Date  US0001M  US0002M  US0003M  US0006M  US0012M   USSW2  \\\n",
       "0  2014-01-02 00:00:00   0.1683  0.21250  0.24285   0.3464   0.5826  0.4903   \n",
       "1  2014-01-03 00:00:00   0.1647  0.20995  0.23985   0.3452   0.5846  0.5113   \n",
       "2  2014-01-06 00:00:00   0.1625  0.20825  0.23935   0.3445   0.5854  0.5000   \n",
       "3  2014-01-07 00:00:00   0.1615  0.20820  0.24210   0.3447   0.5866  0.4985   \n",
       "4  2014-01-08 00:00:00   0.1610  0.20750  0.24040   0.3452   0.5856  0.5350   \n",
       "\n",
       "    USSW3   USSW5   USSW7  USSW10  USSW15  USSW30  \n",
       "0  0.8705  1.7740  2.4540  3.0610  3.5613  3.8950  \n",
       "1  0.9000  1.7920  2.4648  3.0665  3.5635  3.8953  \n",
       "2  0.8760  1.7468  2.4203  3.0260  3.5315  3.8738  \n",
       "3  0.8735  1.7375  2.4065  3.0098  3.5145  3.8580  \n",
       "4  0.9520  1.8280  2.4835  3.0650  3.5500  3.8703  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('swapLiborData.csv')\n",
    "\n",
    "#convert number to datatime format\n",
    "for i in range(df.shape[0]):\n",
    "    df.loc[i,'Date'] = pd.to_datetime('1899-12-30') + pd.to_timedelta(df.loc[i,'Date'],'D')\n",
    "    \n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# regress 5-yr against 2-yr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.8079227] [[-0.2480387]]\n",
      "0.04318013965625678\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "len1 = len(df)\n",
    "\n",
    "t1 = 0\n",
    "t2 = int(np.ceil(len1/2))\n",
    "\n",
    "xX = df.iloc[t1:t2,6:7]\n",
    "yY = df.iloc[t1:t2,8:9]\n",
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(xX, yY)\n",
    "B = regr.coef_\n",
    "b_0 = regr.intercept_\n",
    "rSquared = regr.score(xX, yY)\n",
    "\n",
    "print(b_0, B)\n",
    "print(rSquared)\n",
    "\n",
    "yHat = b_0 + df.iloc[t1:t2,6:7] @ B.T\n",
    "\n",
    "#plot data\n",
    "plt.figure(figsize=(8,5)) # set the figure size\n",
    "\n",
    "plt.plot(df.iloc[t1:t2,0], yHat)\n",
    "plt.plot(df.iloc[t1:t2,0], df.iloc[t1:t2,8:9])\n",
    "\n",
    "#adjust display setting\n",
    "#plt.figure(figsize=(8,5)) # set the figure size\n",
    "plt.autoscale(enable=True, axis='x', tight=True)\n",
    "plt.autoscale(enable=True, axis='y', tight=True)\n",
    "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d/%m/%y'))\n",
    "plt.gca().xaxis.set_major_locator(mdates.MonthLocator(interval=6))\n",
    "plt.xticks(rotation='horizontal',horizontalalignment='center')\n",
    "\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('5-yr swap rate')\n",
    "plt.title('original vs. constructed')\n",
    "plt.legend(labels = ['constructed 5-yr','original 5-yr'], loc='best')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# regress 5-yr against 2-yr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.43706762] [[ 0.90311227]]\n",
      "0.96822828184\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"799.9999682108573\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "len1 = len(df)\n",
    "\n",
    "t1 = int(np.ceil(len1/2))\n",
    "t2 = len1\n",
    "\n",
    "xX = df.iloc[t1:t2,6:7]\n",
    "yY = df.iloc[t1:t2,8:9]\n",
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(xX, yY)\n",
    "B = regr.coef_\n",
    "b_0 = regr.intercept_\n",
    "rSquared = regr.score(xX, yY)\n",
    "\n",
    "print(b_0, B)\n",
    "print(rSquared)\n",
    "\n",
    "yHat = b_0 + df.iloc[t1:t2,6:7] @ B.T\n",
    "\n",
    "#plot data\n",
    "plt.figure(figsize=(8,5)) # set the figure size\n",
    "\n",
    "plt.plot(df.iloc[t1:t2,0], yHat)\n",
    "plt.plot(df.iloc[t1:t2,0], df.iloc[t1:t2,8:9])\n",
    "\n",
    "#adjust display setting\n",
    "plt.autoscale(enable=True, axis='x', tight=True)\n",
    "plt.autoscale(enable=True, axis='y', tight=True)\n",
    "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d/%m/%y'))\n",
    "plt.gca().xaxis.set_major_locator(mdates.MonthLocator(interval=6))\n",
    "plt.xticks(rotation='horizontal',horizontalalignment='center')\n",
    "\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('5-yr swap rate')\n",
    "plt.title('original vs. constructed')\n",
    "plt.legend(labels = ['constructed 5-yr','original 5-yr'], loc='best')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# regress 5-yr against 2-yr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 1.03876557] [[ 0.62619905]]\n",
      "0.768824964502\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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width=\"799.9999682108573\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "len1 = len(df)\n",
    "\n",
    "t1 = 0\n",
    "t2 = len1\n",
    "\n",
    "xX = df.iloc[t1:t2,6:7]\n",
    "yY = df.iloc[t1:t2,8:9]\n",
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(xX, yY)\n",
    "B = regr.coef_\n",
    "b_0 = regr.intercept_\n",
    "rSquared = regr.score(xX, yY)\n",
    "\n",
    "print(b_0, B)\n",
    "print(rSquared)\n",
    "\n",
    "yHat = b_0 + df.iloc[t1:t2,6:7] @ B.T\n",
    "\n",
    "#plot data\n",
    "plt.figure(figsize=(8,5)) # set the figure size\n",
    "\n",
    "plt.plot(df.iloc[t1:t2,0], yHat)\n",
    "plt.plot(df.iloc[t1:t2,0], df.iloc[t1:t2,8:9])\n",
    "\n",
    "#adjust display setting\n",
    "plt.autoscale(enable=True, axis='x', tight=True)\n",
    "plt.autoscale(enable=True, axis='y', tight=True)\n",
    "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d/%m/%y'))\n",
    "plt.gca().xaxis.set_major_locator(mdates.YearLocator(base=1))\n",
    "plt.xticks(rotation='horizontal',horizontalalignment='center')\n",
    "\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('5-yr swap rate')\n",
    "plt.title('original vs. constructed')\n",
    "plt.legend(labels = ['constructed 5-yr','original 5-yr'], loc='best')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# regress 30-yr against 15-yr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.02430841] [[ 1.08162197]]\n",
      "0.994786634158\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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OYL0hAR4M7DTFsXk8+hif52VpY5ixerVZgQAAABAas2vz+dD8guwHuTnRn5+5OcI0hcS4M1AXsBHYwcUqXEdxRPgcB1enQIAAIA4WbvoduPpIcD6kgZYWAOc3vAbbjMxql83day1stVRxEI1ZgQAAAAAABuqpQ7QkB6QAG8mRvQ1CTDFE2AriAQYAAAAAAA2H0iANxMjTQJcTwF1VFABBgAAAEgLd9xxB7355pvmbNN4+OGH6emnnzZnHUsqozfddJM5S032nz7ppJNoyy23pPz8fLWn7rbbbku33Xabui2ZbDl01llnUffu3VXn8l133ZU+++wzcytAakiANxODSnKpb2E2WfxfXms3wgrX6iMAAAAAbFKZngC3RWNjo1o/e+WVV9L//vc/euutt+jYY4+lW265hY466ihzL00aTe23334q4X3ggQfUfXv27EkHH3wwffXVV+ZeAE0hAd5MuN0uevn8XegfJ263rhGWK9z0lTQAAAAASG8NDQ0Z2WipsLCQXn75ZTr//PPpwAMPpP33318lv1dccYVKdOfPn2/uSfTkk0/StGnT6JVXXqFTTz2VDjjgAHrttddo+PDhdNVVV5l7bRzytZf/A+iakABvRvoV5dAhI3uta4TlbnRUgMsXEK2cZk4AAAAAMtPMmTPp5JNPVtXCQCBAAwYMoDPOOCNh6xpJrKTiWFRURFlZWbTddtvRM888Y27VvvzySzWt98UXX6Trr7+e+vTpQwUFBSppmzVrlrmXNnnyZDr88MOpR48e6mPKfQ877DBaunSpul3ej0zxlY8hY4m9995b3SYVWTn/+OOP6ZxzzqHS0lI13Vcer0z/HTRokLqfk0w1lrdxisVi9K9//Ut9LtnZ2SrZ3GWXXejtt99Wt8v7mT59uqqe2o/B+b5lb9s///nPtMUWW6jtfvr27UuXX355k6nJcr8//OEPVFJSQnl5eaoiO3v2bHPr+pHPWXi9XnUUb7zxhpoqLdOebXL7aaedRhMmTKBly5aZq6mde+65VFxcTPX19eZK3L777qumXtvka/HHP/6R/v3vf9PWW2+t/g+Tvx+g60ACvJnxe9xUZxphee0EuL6c6N97cOxGtGq6vgYAAACQYaZMmUI77rgjjR8/XlUWP/jgA7rzzjtVMhkOh9V9JHkdN26cSgb/+c9/0uuvv07bbLONSjbvvvtudR+n6667jhYtWkRPPPEEPfbYYzRnzhw64ogjKBqNqtslQZTq5KpVq+ihhx6iTz75hP7xj3+oxLumRvdj+eGHH1RSeuihh6qxhExHdpLkV/aYffbZZ1WlU8btIY//sssuU5+/VFlfeuklOvLII2nhwoXqdkkoBw8eTGPGjFn3GOSakCRxr732UknfpZdeqr5uV199tUrO5X3Y1Wg5Hn300eox/ulPf1JvL0n2IYccom5vK3k/kUhEJdMffvgh/f3vf1cvWsjXzCYvUowaNcqcxdnX5P+vJfK1qKiooBdeeMFc0WbMmEFffPEFXXzxxeaKJtPTH3nkEfrrX/9KH330Ee2xBz93hi4Jfbozm7x0xb8fpiW8ivXjjeNoZ9d0WpI3ivr/+RuiCY8Tvf9nfeP2ZxEd8YAeAwAAwGbFnmIqiVCym9+ZTjOWV5uzTWubPgV04xHx5zZtJWtGf/75Z1WRtKuKySTRksRNEtn+/fubq6SSU6mOLl++nLp166YqwPvss4+6/t5775l7Eb366qt0wgknqARSkr+ffvqJdthhB5VAJa9jdZJq6XHHHddkDa6cn3322apKnVx1lKRWHoedxNqkAnzzzTevS0y/+eYb2nPPPVWlWhpKNWfEiBGqoZS8T6e77rpLve2PP/6oPhebrNOVx/z++++rJFeSVTnKmlxJlG2yvlne/sYbb2y1EZaQ5Fz+H2zy+cuLC84KsFSh5UUBqco6ydddXsCQxNb5PlKRKntVVZWq0Nsuuugiev7551UFWf5PhFSA5f98wYIFalZAS1r6GRKSmMvXmck/qDxtAqgAb4YaXKYCHDFTVurW6KMI5JsBAAAAQJwkvz8uKE+LWJ9EXKqYksBKctpc8is+//xzlSg7k18hyaa8D0mwnKQC6mRXIKUqLIYOHaqSJqmYSrImFcb1Ic2g1pdUbEVyVbOt3n33XZW0yfRpqczacdBBB6nk0E6YpXIqZE2u0ymnnGJGbSPvd+LEier/4vbbb1eJtnz+Mo3bST52c+zb5G2cj9muzAupAv/yyy/03XffqXOpOEv1+swzz1yX/NpkWnRryS90DUiAN0NBd646+qNmzUPtSn0U7vZNpwEAAIDNg1Rdd96iOC1CHkt7yXRXSX769etnrqS2du1a6t27tzmLk3W7Qm53krWuTrI+VNhNkqRyKIm3JI8yXVpm5cn7kmqodD1uq1SPqa3KysrI4/FQr169zJX2kenbv/76q5p27QzZqkiqzGvW6GKKfG2kSpv8NWnvx5VEUyrNUmGXr5lUf2WtsnR6tsnHSP6/EOXl5eoo63uFPXXcDnlxwyYVeVnnLFPThVTbZcp6qhcKNuTrDwCdR+YGWdOmTePfTXFv3XaiZd1YYNXc3E+dx/5ziDqXaHzzEnUNAAAANj/z5s1TkYnq6+stTgKt8847z1xJrUePHtahhx5qzuJefvllmU9sffjhh+r8iy++UOevvvqqOrctWLBAXX/qqafMlbhYLGb98ssv1uWXX67uc+edd5pbLCs3N9c688wzzVmcvB+578SJE82VuPPPP9/i5NKcxXECp97Gdu2116rz5cuXmyupcXJu7bXXXuYsbpdddrFGjhypHkOqkM9ZXHXVVerjcEKszm3214STfnOlfebPn6/e/q677jJXLOuAAw6wttpqK3MWJ19Tue+yZcvUuXxs52OdOXOmum675557LE6M1ddmyy23tPbff39zS5y8P/matkVrP0PyvFzeH0f75/BDh0AFeDMU9uSoYyCmX5lsXBXvVLiklY55AAAAAF2RNJmSRk6csK6rWKYiFUKZeitrfZ3++9//qu7Lsq53fcm03NGjR9P999+vujDLemSbVI7bu7WOVC9Xr16tKrQ2aeYlTZqc7CZU0sSpJc09BulgzUmdqrpKZTY57G7RUrEVsobWKbnRVHvZU6tlOrntmGOOUR29ZV2yTaY4P/fcc7Tzzjuvq9jLY3M+Vukc7fT73/9erSeWadvSAE26PUNmQwK8GYp49RRoHzUSNVSQPxj/IxCrazqVBAAAACAT3HfffWrasSRIjz/+uEqspOGSrFG1OzLL1GSZKivJnCRysn5WttaRRlfSwEmmNLeHrJ+VRlkyjffTTz9VXaAvvPBCqqysVN2hbSNHjlRrad955x2aNGlSk62UUjnxxBPV1OaTTjpJNaKSjtWyf65znauQjsWnn366aoAle+zKx5Btlf72t7+prZFs8hikU7Z0iZ44cSJNnTpVXZftjiRxlEZa8jWUz0PeXjpfy5pqOwmVjy33kX14pbu2fK7yNZM9e9vi0UcfVV9rebFB/m/kaydrpyUplcZWziZiMrVZppMff/zxKsGWxySPRb5u8nm1lbwQIQ3G5OMNHDhQdfAGgK4r5RTop/5xw7opz9b0t+JjjpV3jjH3AgAAgM1NJk+Bts2YMcPipMkqKSmx/H6/NWDAAOuss86ygsGguYdlceJncSJkcbKr7jN69OgmU5rbOgVaptyefPLJ1pAhQ6zs7Gz1PnfaaSfr6aefVrfbZGr0brvtZuXk5Ki3t6citzQFWnDia2233XbqfQ8ePNh68MEH1VRjeRsnToqt+++/3xoxYoT6nORx7LrrrhYnw+YelrVw4UKLk1grPz9fvT0nhOYWy6qtrbVuuOEGNU3YfnuZFn3FFVdYK1euNPeyLE7sLU5OLU4s1eciU5XlayDvr7Up0N999511+OGHW3369FEfQ95evva33nqrVVdXZ+4VJx+Xk1eruLjYysrKUlO1Oek2t7bdl19+qR6fc4q1k9yGKdCZA9sgZTb5weKfs8RtkK5/8m26fcnp+mTgbkSLdOc7Ue3rTgXXzzNnAAAAsDlpbQsXgEwkexbL9PAlS5Y0aeDVXtgGKf1hCnTbbMchG7wt5pCFEdJeTnrgn8bRGukLb7/SkyqcbfGau++HHB2mNrc//RrbQp84kl+RE6nijygfEgAAAAAgc40fP15Nt3744YfpvPPO2+DkF7oGJMBtU8ixhOM6jkM5zuCQHcef5biBoyUXceyaFNJ/Xfrej+dw7EGkyMtGyfe/nKPDZPs89G40dQMHr8UPK2z2BwYAAAAAyFC77rqrWo8tTb5kfTRsHpAAt41UZi/geI5D2tC9y3Eyh6z4P4+jJbLbuSS6zpCd1WXD3Sc4kkmFOfn+Mzk6TBYnwO81kwArDXr/NAAAAACATGVZltr3VzqD5+XlmauQ6ZAAbxhpnxzRw3Y5l6OW42V11smy/R5aRqU0OTbMXElSu9oMAAAAAAAAMgcS4PaRr5eXo5RDpjYfxNH2PuuaZJ17cLzEIUlwsiEcUoKVxFq6Ud3Okc3RYbK8HnV8x1EFrrEcH2KtowmWrAeOrk+ODwAAAAAAkF6QALfPwxyydldKpPdzXMrxKEd7SPVXpNoQ7VuOKzmO5TiS432OqzikCVZr/1c9OKTVszMkmW4i26/f1XvRnckyjcAnxrakmKXH1tq56kjheqr8+/ZUc/c2ZNVjWjQAAAAAAHRtSIDb5w6OHTkO4/gPx4Mcf+ZoK6ken8khLc9lbW8yaaj1CIesM5bk9xKOazj25Ijv/J2aVKSnJcVbHE30K8pRx1VUTLNKpB8X0UexHWk56c530TKdAC/+9BEqrJ1H+aFVNPuj9ub5AAAAAAAA6QUJcPvINkiTOCQ5vZDjMY47OWRKdFtIB2nZ9ihV86vmSOMt0ULXKkWq07KfmDNSJs3jhpSQ2+wAfX79BbRT8CF6OboPLYjpHZlia+eoqc+1i35R52JJhfTmAgAAAAAA6LqQAG+YCRxS1W3rbvEy/TnMIdsntVfMHJsj07KlsuwMx2LeuMIcP40ZUKTGiyrC/IZ6vMDqrY7+1VOJbimhbVa9rc5FwCefJgAAAAAAQNeFBHjD7MMhians3dsaKa9KBfhNjrVyoY1kyrRINWV6ve01vGnR+mdnV2gragZajlVvRgAAAAAAAF0TEuC2kanO93KcwLEXhzSpki7Op3P8naOMQ0hjK2mZPFCdJZJEVsqozU1/ls7Q0uzqfI4DOI7gkGnNsu74c453ODrM3ls2TYDfjo2ji8KX0ncDLyLa7lRzVXOHa8wIAAAAYPP19NNPk8vlooULF5orbSdvI28r72NjOuuss2jQoEHmrHkvvvgi7bnnntSzZ08KBALUp08fOuKII+j7778390j00ksv0XbbbUdZWVnqvpdffjnV1qba1AQgfSEBbpsfOHbieIjjUw5JYqWiKwmwdGm2yf5CEmaFbYJzOOQ3pbx9Kis4pOz6Fw5Jdl/h2J3jrxxSOW5tCnS7jOjTjUpy/eaMP5mCLOrZLYfej+1Cr2Zznn/UQ/RB7tHmVv6kkAADAAAA0GGHHUY//PAD9e6tl461h7yNvK28j3Swdu1a2m233ejhhx+mjz/+mO677z5atWqVSoq/+uorcy/t+eefp5NPPpl23HFH+uCDD+jGG29Uifzvfvc7cw+AriFVogaZQ7ZCmsZo221lmOiKl3+hNyYvU+OteuVTUY6ffpi/lkb3L6S3Lt6N9r33S3q8+gIa4l5B04v2pW0ve0PdFwAAADLT/Pl6VdfgwW1tb7L5aGhoUJVPqeCmO6kAf/nll+tVpa6qqqLS0lI66aST6L///a+6Fo1GqX///jRy5Ej66KOP1DXxwgsv0Kmnnkrvv/8+HXLIIeZqx6uvr6ecHL2LSbpr7Wdo+vTpNGKE9KpVDWulZw90MlSAN2POadCS/A7qnqvGU5dW0o63f0rz19RRDelfNr7GDagAWxbRxCf5Hb9mLgAAAABsGt9++y3tt99+lJ+fr5KqcePG0XvvvWdu1expzlIVPeecc1RCKPcNhUIpp0Bb/FznjjvuoIEDB6okeYcddqBPPvmE9t57bxW2VFOgb7rpJnVNEiOpsHbr1k1NSZaPK8mo00MPPaSqsz169KDc3FyVkN59993U2Nho7rHh5Osin4PXG2+AOn78eFqxYgWdffbZ5op2/PHHU15eHr3xRstFEvm85f3deadsnpLo66+/Vp//q6++qs7tr8fPP/9Mxx13HBUVFdGQIUPUbQAdAQnwZmyPYaX8C0aPi3P9NLJvNzWOcb5aVhNS42rLJMCRDVjfMZP/qLx3JdH/ziVaPdNcBAAAAOhcMq133333VYnlk08+qdbASsIn615ffvllc684SUJ9Ph89++yz9Nprr6lxKtdff72Kgw8+mN566y264IIL6Pe//z3Nnj3b3KN1xx57LA0fPpz+97//0TXXXKOqq1dccYW5VZs3bx6dcsop6vG8++67dO6559I999xD558vLWTWn1R4JYmWRPXCCy9UCf3FF19sblXTCdVx1KhR6miTr8dWW2217vbmyHrkI488kv7973+rj+X04IMPqvXExxxzjLmiydTqoUOHqsRY3g6go2AKdGZrcQq0+P0zk+jT31bRjUdsQ6fsPICe/WERLa1ooFAkyklwmI6Zey0d5plAy30DqM/1U81btdOrZxNNf12Pj3qIaMxpegwAAABppcXpmx9cQ7RyPZ8LdLReI4kOucuctN2uu+6qPkdJJKVyKSQhk8ZOlZWVtHjx4nUVWql2nnHGGfTMM8+o+9ns2xYsWKASu4qKCrW29+ijj1ZNomxSNZWPt9dee6npyEISzC222IKeeuopNU1ZSMXz5ptvVpXc//u//1PXhCSg//nPf9T0X3lMyWKxmApJ4uXxlJWVqWqpaO8UaEliZ82apcbyuUjSKWuDbVLdlgRfqsC9ekkbnLiDDjpIfRz77Zsjj2efffZR1WL5Wonly5erqvlf/vIX+utfpe1N/Osh53LsajAFOv2hAryZe+jUMfTplXvRWeMGUcDrod/vMZhuOnJbuvN3o+iJM3eg7LxCdb/s6AZUgKOy9bEh06Ft0Uaij64n+ubvRBHHfQAAACD9SPK76Nv0iPVIxOvq6ujHH39U02rt5Fd4PB46/fTTaenSpU2SOKnKtkYSXZkafcIJsllI3C677NKmTsw2qZA6SbU1GAzS6tWrzRWiyZMnq/uVlJSoxy0VWEnSJYlvT7U5mVSd5Wsjie8222yj1vPaSbtTqkRcOK9HIpGEkGqykKngo0ePVtO4bVLZlbc977zzzJW4tnztAdYHEuDNnCS9Q3vkNfsLLezNV8fsWJ06rpdI0AxYXfyXOM36gOiHB4k+u4XoVf0qKAAAAKQpqboO3D09Qh5LO0mlVpKxVN2bZQqukK7ITm3p9Gy/jazbTZbqWnMkqXWSbYmENN8SUp3eY489aNmyZfTAAw/QN998QxMnTlyXUNr3Wx8yU3CnnXZSLw58+OGHqip72WWXmVvjjy356yPKy8upuLhYjaUSLEm5M5zdpC+99FL67LPP1AsNMuX68ccfVx8zuaos2vK1B1gfSIChRRGffoU0i0JEUdnieD3UO35Z1qwyA7Z2rhmwWe8RhdpYZZ7Pv0ifOEAnznVNfxEDAADARiBTjs/mv9fpEOsx/VmmB7vdbjWNN5lMxRXdu3dXR1tzBQInOzmU7YOSrVy50ow23Jtvvqmq2K+//jqddtpptPvuu6tmW35/fFvLjiDNqsaOHZtQUZZmW2Lq1MTKu1R4Z86caU/pVS8kSFLujO23317dJmT9sny9JGmXarN8fZxrjZ3a8rUHWB9IgKFFEZ+uACuhajNop8rFZsBqHX8IqpaagVHT9A9SSt/eR7R0gp46/cAooq/vSZxaDQAAAJBEuibvvPPOKoF0VktlHe1zzz1H/fr1U02o2kvep1Rrk5toydToRYsWmbMNZyeEdmVYSEVbqqgdSaZdy2OXBlQ2+RylIuvsXi2kMVhtbe26vYAlGZek3BnSZMwm3aVlurOsq5Y9h2XttXOtMUBnQAIMLbICBWbE1icBDtclVoBnvEX0/PFETx9ONOlJc9FIToibs8ZROQ7XEn1+m+40DQAAANAC2YZHpvFKMyZJ3t5++2069NBDVRfje++9d72qjjL998orr6RXXnlFdX+WfXKlw7SsCZakUarOHeGAAw5QCaZslfTBBx+oZlLSgEqmdq8v2QLqrrvuUp2rZc2vJLjStEuahEnjK5usN5YmXTI9WjpOy30l8ZaO0fK4pPt1W1100UWqsddPP/1Ef/zjH81VgM6DBBhaFAs4KsDB9UiAq5aZgcOcj4kWfmNOHKr19KMWNTbw/UyivOVhRD6zKfrsD/URAAAAoBmS3H3++eeqGiydkk866SS1JZIkwieeeKK5V/vdfvvtdNttt6n9hKVJ1T//+U965JFH1H69hYW6oeiGkk7N0qxKEl6puF5yySWqgiofa31JAiydq88880yVyF577bXUt29ftTevbA3lJNOuZWsmqQ5L4i1dmqUBl1TU20Pev0zflhcOZEo0QGfD5PrM1uo2SK15/bXn6XfTLlLjyBnvknfwHmrcIunu7PbKXB1OdL8jevpQc4PRrT8n01VNK8r7XM9/ma4yJ81YNYPokV31+JjHiH59mWjeZ0SFA4guT5OtGQAAALqo1rZwgbaTbZIkab3xxhvpuuuuM1dBulpLky1J4KWqnGmwDVL6QwUYWuTOjk+BDteZKTZf/o3opVOJGlJMuSmbRXQ3/8A/vq9uUFW/xtzgcOprRFsdZk4cqlNUi5OV618qSskQ/u2ytx7LOuOKjltnAwAAANBWU6ZMoWuuuUZVkmV68KOPPkr7778/FRQU0LnnnmvutXmTbaaksixfD5kW7uwyDdCZkABDizzZ3cxIlttWEa3+jRPgO4hmvks0/hFzi8NUTm6lsrv8Z6LXzkpY//tJdHv6acxtRD22Iuq3o7nqsOgHvcn+V/foKnIq5fPMgOjhXy2K9R5jzpjjNgAAAIDOIlOqJ02apJI7mUp8/fXX05gxY+jbb79t11ZImeyJJ55QewFLBfT5559XU6EBNgUkwNAiX048AW6sryRa9pM5Y6tSzNpYPcMM2IKviRaPNydEFzdeStNKzXqS7U4h6rsDUfFgov676GtrZhH9yEn1F5wkT39DX0tWuUQdqq0cuvvr1XT7t5yU29qyhhgAAACgg0nH5E8//ZTKysrU/rZr1qxRTba23HJLcw+46aabVMdtmSJ89NFHm6sAnQ8JMLQokFdkRkQRSYBXTjNnrFs/M3CQCrHTNN0YocbKpjD5qLLeVHZ92UR/+Izokp+JxpyqrzmtbaaaW1emDmWWTsyfm+GoFFe3cRslAAAAAADYLCEBhhbl5uZRyPKqcbShmmjZJDVWZIsjp3B94hpdEdMJaoWVp46VDWF1tNU3RunJ+j1oyok/Ev15LlF2sb6hbrU+JjNTqsspX/XYCpGfys37btMaYgAAAAAA2GwhAYYW5QW8VEN6qyFP1SKylk9WYxGqTWqCJVOYydLjAeP00Sgn3UyrylSAg5z4rq4J0tlPTaRb351BZ726mCLZJfwBe6jb7UpvMqtON9UqtwrovD0GU1GOj1ZZJmmuSVEBtvjxSFW6uTXFAAAAAAAdxJLnnpDWkABDi/KzOAG2stW4x/LPyBWLqLGoKE+q0laZ/XnFnn/m7y5dORbllt5PuKw2RE98M592ufMz2un2z+jHBeXqegUnxmtqw0S5peqcalMnwLF1CXA+9SvKpj2GldIKkwBbqfYc/vY+ood3IXrtbHOheYvW1nFCPoFenLDYXAEAANi8uFwuikQieBIPsB7k5yYajaqfI0hfSIChRZIA15JOgD1WPPkV7uR9fB0dn6n7cKKh+5uTeAX4mzlr6Lb3fouvBXZYUdUQT4BTVYBjMXI36IRZpkCX5gdor+GltNLS65SjVUlNsGSv4c9u0ePf3tHHFjzw6Rz6YlYZXfv61HWVagAAgM1JXl6eegK/YsUKlQgDQNvIz4v83MjPj/wcQfrCyxOZbVuOaYy23VaG7ReJxmjCTbvROI+ju7PTyS8RbXmIHn9zHyecN+vxdSuIZn+4rvL6aOQwujOSotmVw79PG0sHL76faMKjRAFOmK/VHZ/Xqefk9+4t1PDWxtPokD/cSm63i7589M90pe81dZ1uWE3kDejxxCeJ3rtSj8VNjo7RKexw26e0pjakxvceP5qO2z5Fky8AAIAMJk/ily1bRvX19erc6/WqPVtR0QJITaq+0t3afsEoJydHbfEkPzupyDZQI0aMkKH8k2JLFdjYUAGGFnk9bqp355oz7fvoNmbEXjyJyExLXlcB9mYR+XNUYhzO1mt6Z8X6q6PYf+seNKpffHsl24qqYLwCLNXlRj638S8WZzK71iqg7nkBKuWoIMerbKEaM+CHtSqpIVe05VeyDyhaRR/6r6ZLPa/Th9PQURoAADY/8qR9wIAB6gl8fn6+OkfyC9A8+fmQnxP5eZGfG/n5aS75hfSA32iZbYMrwOLdm4+iw60v1XhabBB9HtuOLvW+qc6V339G1G8HojcvIvrlear296DPD/mSjh7Tl77+cSL9562P6OvYaIqZ11vuO2E0ffbbanpvamKSef5eg+naHj8SvXOZvnDF9PhWS0smED15gB6zM8JX0yM3XkUet4uuv/E6+rv/3/qGy6YQFQ1Sw1mPnUVbLo/vJxz7v4Xkzo1v65Ts19t2p1GRqWp8dMFL9OaVprINAAAAANABUAHe9FABhlaFvPEK6xvR3ajaSqwIJ1eAlwSz6fKXf1Freld5etGXsTHrkl+x+9Du1Kcwy5zFragM0vJGRzW31tFkqzKxMVWdp5ByA17K8nko5tNdqhXH1kwus17YVludeJ5sSGSOGRENbdCJMAAAAAAAZA4kwNCqel+JOkYtF70THUdVlJQA167UR5MA23v+TlhQTtXB+LTjo7frQ/efOJp6FGRRT45kb09ZThe+5ejknGpbI1uufkzCn607TCuOBNjfmLjmt7UEeJHVy4yIRjf+YkYAAAAAAJApkABDq37sdjAnvrvQ9ZFzaTUVUa4vaeZ8zSp9lCZVrIJ0Qjp+fjlVNcS7Kf/9hO3omDF6SnPAm/pbb5ll1gALZ9W3UTfjEDNj/cnK72vOZLmxMwGuNQOirKQEuL660oyaqg9HKMuKrzkeGZuJLSAAAAAAADIMEmBoVTS3J13SeCm9FN2XCrK81Lt3UnfkpAqwvefvd3PXULVJgPMDXrVe17ZNH70tkjhvz8G0x7DudMToPlTtLaR6y3RxrlikjyIcT4BPDl9P3fPjFeScPEdDLUcFOCuSuE1TQ23zCXB5XZhKXfGEuTuPQ5GYOQMAAAAAgEyABBhaJXsB2/bZqgct7bEnvRUdZ64wqQBLh+WgTjArTQV4cXk9fT1b7+dbkO1TR9v2A4vp6oO3Uo2v5PjsuTvTv04eQz04sV1qddd3qnQkwI4KcD1lcQJskmSWkxdPptclypZFudHEBDhUV2FGTVVUVVG+q8GcERVTDdWFsP8hAAAAAEAmQQIMrcoLxJPXA7bpSblZWXRZ4x/pm6jqYEdRWatrkl9hV4DF/DW6IpucAIsL9x5C1x6ydUJluCQvQEssvXVSQgXYJMAxy0Uh8qntj2z5BfEKcGNDjU6CH92D7xWffi0a65vfB7hu7XIz0nJcIaqvjW+pBAAAAAAAXR8SYGhV7256urGs291reOm6ivBqKlTHaNVKooZ4Alxl5SYktUKmTrdF91w/J8BmHbBUgO11uI26OttAfv7XlVABDuTEK8Dhhmqiqa8QrWzaxTkqtzUjWNG04VZDteluDQAAAAAAGQEJMLTqhB370wV7DaFHThvLya9vXQK8yipWR1/9Ks4W49OL6yiLLttvmDnTUlWAUynJcyTA0tDKNNayK8D1pBPfUr6fzZ8d70odaeC3mfWhOUsUayEBbpQkPkljjZ6+DQAAAAAAmQEJMLSqGyev1xyyFe27VU91nhfQCfC8WB91dFlRopVT1FjUUjb9bmxfKnVUaeV9tIVMgV5qT4EWlQvVIRrSU6mDpkGW831nB/zrGmdZ1cuI5n6qxslc4WrV2fnj6StpypLEhliWc89hAwkwAAAAAEBmQQIM7RYzs5LnWjoBVpb+ZAZEdVYWdedEVpJgW0FWGxPgXD8nwI6tkMw64MoqvX7XrgDL+7fl+D1UZ67nzX+PH2Di2t91gjX06W+r6bxnf6KjHvqOqurj97PsSrNDrE53tQYAAAAAgMyABBjaza7mzrXiCS4tiyfAMV8uZfk8dMIO/c0VouLctiXAUtldNwVamE7QltneSK8BJupTmK2OItvnpXpOuoU3rBtXWYECejW6Jz0YOUrtGyxkG6Rb3p2uxmL26niTK0+waQJMdVgDDAAAAACQSZAAQ7vtu1UPtWdvHWXTMqtEX1wzWx+ZzzSlGlKaR5fvP4x2GVxMR23nSJZbUJIboGrKpSorR1+oXKyPdhMsTnTf+ePu5PPEv3WlAixbIzlFtvkd/V/jBXRv5ESKZevHOJiW0ZLy+FZHdn8t4Q3pKdFlrhLVaVq4GlIkxQAAAAAA0GUhAYZ2kw7PsmfvoJKcdeuAOZ00R+nKHN+W6PL9h9NL5+1K/YtNQtsKe23vuq2QJv2H6LsHyB3RTbCkAiyNspx0AhyfEi0unjLIjPht+u+hjkPdy2mkaz694LuN7vA+TtX1YXVdZDXqKdYNviKq5ARcpKwKAwAAAABAl4UEGNZbUa6f5lj9zFlcdl58H+D26lWgK7lBM9VZ+eSv5A/pLtOSAGf7PGpsy5Y1wGYKtGgIdKdP64eaM6K1/fY3I6J3AjfQOM8MOsX7BVHZDHOVk+ioToDD/m60mnR3696VPyeWiQEAAAAAoEtDAgzrTRpWzXGuA2bSjbkoL74+t70Ksr2U5XPThNhW5oqWF9T79DZQllpf7JTj9yZMgf45dy+KOb61o8XDKdJtoDmLC9fqac/RmEV5sVo9DhTRx+7d1bi0YT7RnE/UGAAAAAAAuj4kwLDeijkBnrtuCrQmewAX5yROUW4Pl8ulqsDPRA6kaTk7m6txDZafAt7Eb1tnF2jxbO32ZqTlZPnIu/Xh5iwuUq8T4Mr6MBW6dEOsWHYRvR84lGosk8R/9w+iRd8T/X1roi/u0NcAAAAAAKBLQgIM6022IkroBM1qrSw1NXpD9OQEeBUV0435NxFtf7a5qoXdWeR26yZVNkmI7b2Dy3x96KPqAWpskwSZtjzEnDnU622OKuqC1I1TaOHOKaEhA/rSC9F91Tkt+o7oKX7bmuVEX/1NXwMAAAAAgC4JCTCst0EluVRJ+VRmxZteSWdoqQxviN7d9HTmlVVBolEnqLEtwglwMqkaP+85iq5vPIfODP0fWUnf1ipdHrArWVmF6tzmDpar6c8vfDWNPC691tebX0IX7z2U/hM5hMJW4lRrJRoxAwAAAAAA6GqQAMN6G1yquyXPjcWrwDIF2t4neH31NAnw6pogxfrtTNQtvp9wxJN6fbHlz6Pno/vTjHBPde73uGlw91zaaYtiGjOgiMjjJdfwg9RtNqu+nC547if6fPJv5gpR/z59aZs+BbT9yG3ozaheC5wgqKdNAwAAAABA14MEGNbb4NI8dXQ2wqq1sikv4DVn68fuBN0YtWhtfYRo5HHqXESbSYDVNGeHo7brQ5/9aS96+bxd1LZNypaH6qNRU76KPpmxinpSPKn153dXR9m+6cWYmQbt1KC7UduCjVH6Zk6ZOgIAAAAAQHpDAgzrTaY6F+X4EhJgqQDnZW1YAtyvKL5n8KK1dUSjTjRn/P59RWaUKHlrpD2Gl6qp0RLryDrgLQ8zJ0RFLun8bNF1uW/pCzJZuvtwNRreM58Gb7uLGieoT9wb+IY3p9HpT06gq1771VwBAAAAAIB0hQQYNohUgZ2NsKQJVv4GVoDtqdXi1UlLqa7bMHqs6Ar6d+QI+jV3V3NLImcFWHLe3YfqSm4Cb4Do5BdoXvYodSoJ8HGer2l0xCSvO57LWf0WesxO2V0nwwmSKsCzV+nu0W9PWU4zllerMQAAAAAApCckwLBBZJ1t4hrg7A2uAA8oziGvmbb88qQl9OdXp9CHvgPorsjJ5PHHq8NOshewbWTfbi024gr7dTOsIa5ldL33eTWmvF5E+/1Vj41hPfMpZCV+LpbpHG1rCEVokGsF/yDF6J+fzTFXAQAAAAAgHSEBhg0iFeAy6kazYv3U+W+xAZSftWFNsHweN/UpjK/1/WDaSlpVHVLjrKSpzrZsRwV4z2GlZpRaJKCnUZe6qs00aHbo3fzO492sRQF/Hq96EtcNB2sSE+BzG56kLwN/ous4kf5w+kpUgQEAAAAA0hgS4LbZjuM9jsUcDRyyEPQHjtM4WnMWh+yxkyp6cSQ7ieMXjiDHco5/cOhuU2lIT1d20cnhG+jY0I30hrUH5TSTpLaHdIB2WlYpX/bERNfJOQV6j2Eppj875BTqPYNtNX33INr6SHOW6L+BU+iZyAHmjChUnZgAj4xMV8czPB9TKVWgCgwAAAAAkMaQALeNzJldwnEdh5QEz+BYyPEsxw0cbXE2hyxgdUZiNkV0KseLHBM5DuG4mUMS6Nc50tIQ0wm6nAroJ2tLyvP7yG13Xd4Ap+w00IwSZXlTf8sW5egpz9KBeuzA1I2ybN0GjjQjzTVkX71wOIWqqI9ujJxN5Zb+PBtr16ijLcvSibrfFaUzvR+rKvBvK1AFBgAAAABIR0iA2+ZLjgs4nuP4guNdjpM5fuQ4j6MtpnGMT4pGDpuUMO/h+JjjDxzycR7luIhDSpCSEKcdWa+7bpshtqHrf20X7D2Yjt9eT6t2aq4CfNouA2n/rXvQ7ceMUFOoW1Ky5Tgz0nIGjDWjpi7db5g6VpoEOFoX7wJtWRZlkZ6aLU7zfErZFEQVGAAAAAAgTSEB3jBSDozo4QaTPXd6czylzuJe5ZCFqseoszTj97pVEmzb0D2AbT3ys+ie40fTPcfpjs225O2ObEN75NETZ+5IR20Xb8jVHFfJUDPS3H0SP4bTCTv0p9/vvgVV2bPQG+IJcDgaoxw1U10rdNXR8Z6v1JplVIEBAAAAANIPEuD2ka+XZHjSZUkqswdx/I2jLaRqHOWQDEqmNI/gcLLPkzeUlSrxTI7k+6cN6QRty++gCrBt7y17JMxObq4JVrvwO2w0naCVnGIzaEqqyZcfMJzWWvnq3BuMJ8DBsCTA8QqwONf7AX+TxOiBT1EFBgAAAABIN0iA2+dhDklIV3Pcz3Eph0xTbslKjts5fs+xD8dfOHbkkCnQozlsJeYYz7Di5Jp9e3Oks9O2STGEY6Nz7tubt4EdoJOV5gdoVL94strcFOj28p3+KtGAcUTHJRfcm8rlj1nu0uuKs4Nl6igaQmEKuPQs9rqsnuo40LWaDnRPoo9nrKTaUEdNDgAAAAAAgI6ABLh97uCQ5PUwjv9wPMjxZ46WfMghjbKkAvw1x0Mce3BIF+hbOJLJ9VSau26TirSsM3bGWxwbnd0IS+R30BRop/22indtbq4JVrv134nonA+IRvzOXGiey+WiWq+uEmdHKomiOrENNtSoo1g06Dh+cDpRP8/7LsX4f2vq0ip1DgAAAAAA6QEJcPvINkiTON7nuJDjMY47OVreeLYp6SD9LYes+7XZHaFTVXol+0pVGXaS6rRMk3bGURwbnewFbOuoNcBO+zoS4ILsjq0wt1V9QP8Xu+V1iHrdCTpcF1/na2Xz7TtKkZ9orHsujXXNpilLOVlmSyvqabe7PqfTnviRGqMxdQ0AAAAAADofEuANM4FDMr7B6qx9ZGWrMxuaao6Je/To978Vh1R0WyLTsmVTWmfM49joEqdAd3wCvG2fArp4nyF0yIhetP82eqpxZ4vkOF7jqJFZ7ZwAN0hvMs2dxV+Dnc4j8ujtmM7zvke/LNYJsHSFln2Mv527hj77Tf6bAAAAAABgU0ACvGFkTa8ksfPVWdttwbEbh6wDtsmWSis4ZN9fp+M4pMSatnsBl+T6aateuknUyL7d1LEjyRTk/ztoK3rktO2poIPXGLeVJ9+ReFcuIvryLir5VSYAaN4A/xfJfUaeoM4PcE+ieUvlv5No1qJl9LjvXrrR+wy9Pam93yoAAAAAANBRkAC3jWQ693JIdrMXx7EcL3GczvF3Drsz0pMcskB0oDrTPuX4K8fRHPtyXMYh059lTa80xLJJh+irOA7mkMZae3PIfsCPcHzCIWuJ05IkqC+dtwu9dfFudNR2fczVzBIokh2qNOvtSzkBvpN6z33RXOEEOMtMA9/6CHXwuCzqXfOrqvzuWvE2HeD5mc72fkSHzr9V7R8MAAAAAACdDwlw2/zAsROHNLCShPYJjl4ckgBL0mqTFsUSjo171NTmEzn+y/ERh9z/c44dOJKnNT/HcQqHrA2W+0qTLHm71js1bWKFOX4a3b9QJcOZKK97fH9hV1BPbXbyZZsEeMDOZJn//h3ds+i/Pyyk3V3xna0Ocf1AVbV15gwAAAAAADoTEuC2kb1y9uSQhaAyB1f2xJEKrSSsTjJ9WbIfaXJlu4JDtiQq4JC3lUxKEufZHKlIWVG2RwpwSNlRKsbxxaawSfQoKqJqK9ucNbUuAc4uolCJLNkm2sk9k176bqZKhG1SGV67vFOWZgMAAAAAQBIkwABt0KtbFv0UG67Gn0S3p7WWXvNs82fHz30DZKcsoi1dS2hMbAYFXIn7AdetbCUBjjYSff8g0QLZNQsAAAAAADoKEmCANujNCfCFjZfTUaFb6LzGK2ielbjWOSvHVICZp/tQdSx01dERnu/V2Cm8ZoEZNeP7fxJ9fD3Ri6cQRcLm4kYQCZkBAAAAAMDmAQkwQBsU5/op5smmKdZQsvjHZpElS8DjAjkyw90oHmIGRMd6pN8ZUV2PsRS2ZHk4kavCOUM+SSxKNElm3LNwDb+h3V+tg/3wMNEdnMR/x8k2AAAAAMBmAgkwQBtIc6+t++gkd7ehJeQq1dOhbW7ZBslWEk+AbTnbHEwrXD3UOFCzWB1TmvsZUdUSc8Lq15pBB/voWk62I0SfOBuRAwAAAABkNiTAAG30jxO3o1uP2pYeO30HCvXb3Vw13Lq6qxRtsa4TtM01dD8q8+qqcV7DcnVMadJ/zMCoX2MGGxGmQgMAAADAZgIJMEAbbdE9l07fdRDlBry0x577m6sp+LLI1a2fOSGK+fKI+oyhuoCuAOdHmqnqVi0lmiO7XznUl5tBBwrXm4EWXT3TjAAAAAAAMhsSYID1MKB7HtUVba3GIX+xOiYYfrAZ8A/ZME6W3R6KZHdX591ilZwVx9Q4wc//JbKSrtdthApw9TIz0NbM/dmMAAAAAAAyGxJggPWUe/YbRLtcTIHTXjJXHA68jWj0yUR5vfg+F6lLrjzZRprIS1GK1leo8TqSEP/8rBouyx5OMUtPoQ5Vr1bHDSIV38U/rku6g2WJTbiqF08xow2wZCLRT88Qlc83FwAAAAAA0g8SYID1VdCb6OA7iAbsbC44+LKIjvk30Z9nrbvdWxDvHF252tHoSqydS1Sj1wY/H9qDKkg31QpXb2AXaJlC/cT+RP85kOjDq9WlmtWJ2zAFy1OsSZZkOVxnTlohU6ifOoTonUuJHt6VP7mkzw0AAAAAIE0gAQboJFmFnDAbVWuSks4lP5oB0ecNw6jCylfjaO0GJsBf3sUJ6nQ9nvAY0YJvKLJimj433KEqMzIk+X3yAKK7hxCtTLxvSl/xx4g16nEkSDT1FT0GAAAAAEgzSIABOkl+9z5mRFRXvsKMjCXj1SHoyaXZVj8qJ50Ab/A2SKtnmIHx6lnUe+Yz5kTzRWrNyJBtmJZN4mS2geiti83FZsSiZP32jjkxpv7PDAAAAAAA0gsSYIBOUtSjrxkRhSqTEuClnHCyX2kYxfjHstzSew67GzYwAQ5Vm4FhtlWqsPL4Y+hp1oFoPAGeu7qWnvrSVIxFhVkv3BjUx2TBKnLJfsJsralaq4rz6t/0GAAAAAAgjSABBugkJd17UtjS+wXHalapoxJt1GuA2c+h/uooCarwhSrVcX1FGmrUcXYsnnwvzdmGDgvdQZ9Fx6rzbEcC/LuHv6N3Jzi2RQrzbROfILqT3/6zW81FB06Abc9H9zMjNvU1MwAAAAAASB9IgAE6ic/rpQpXNzV21znW9lYu5oxYV1HnWXqdcA3lqGOT6cnt1FivE9RJsS3p/PAV9PO219IBldfQcuq+7mPkWvFmV3uEv6X/BW42Z0we10c36GOKtb0RRzfrqbHB9AuHMo0TYMvSYwAAAACANIEEGKAT1XiK1NEfdOzvu2aOGRAtiPWirXrlU9ibq869sRBnmWE1Xh/uRp3c1lI2fRTbkX7300hqiHkp4HVTXrcSdVsuNai1vOIh/z/VMYGsBRbSUTpJsDp+rcrKpXei4/SJTJ1ehv2FAQAAACC9IAEG6ET1fp105jQ61vaa6c9ivtWHDtimJ0V9eg2wEtLTmNstGqGApdfu1lrZ6mj7+wmjqVfPHuZMdjyqolislYqtTIdOWgscqo1/HgP79eEEeNd1exirKjAAAAAAQBpBAgzQicJZ3dWxIOpY27tWV4ArrVzV/XnckO5kBUxDKZG8TVFbheOJc50rm1wmL/3zgcPp8FF9yJ2lp2OLuqo1VNNgtjJqSVJX6nBtfAr0nqOGUpW3hCZbQ/WFpRP1EQAAAAAgTSABBuhEVm6pOhZblRRqNAnnKr1V0XyrN/k8bhozoJBcWY4KcDCpk7P47gGiR/dqeZ/eUHz98BZ9e9JrF+xKT5yxA128j05Qvbl6Oraorymnyqp4Mus00xpgRsx0kbZF6+JToItLetD+2/SklZZ+v7GGDWvgBQAAAADQ0ZAAA3Qid34vdfS6YrS2bCVRJES04hd1bUpsCI3uV0hZPg95suPV2SZToBsbiD75q3679/9sLqbgeDvLl0/bDyxWCarLlIJ9OYXqKBpqKqi2nB9Pkpcje9OdjSebM5ZUAY7W6yS30fJQTm4BHTW6D1Vbev1yuA4JMAAAAACkFyTAAJ0oUNjTjIgqVi8ja8UUziJ1k6vJsWG021A9RdqT40yAkyrAy34yA7b4BzNIwZk4ZzmmVBuB/GIzIsqZ9ToFqxxbMxlXR86jpZZ+TCJc7ehezSxT5a2iXMrP9tFeW5aua+DlTn7cAAAAAACbGBJggE6UW9LHjIi+mTiZPvzv38wZ0c/WMDpitN4Gye2oAFuOvXaVRY6kNz/+/pJZjgTY5VxTbGQXxKdA95n3CuVOeticJaqw4m/bULXajDSXWZ9cbeVQXsBHAa+H8rrphNlvbVgH667mu7lraPaqpGo9AAAAAKQVJMAAnaiwtJ8ZEZ2+9EY6pPFTNZ4X6035PQfT0B462fQ5EuCI2ct3HWfVN9Z846rGhvjbebIda4qNHEcFWGxV8YUZJZK1vXZn51BSAuwO6QpwNeVSXpZXja2As4P15lEF/mZOGZ36xI/0u4e/p8r6zSfpBwAAAOhqkAADdKJu3fuaEVGuK6SOy7OG0Efb3k3/PHmMOhf+vPj6XNmiaB3LWrdmWKkra7bKGq6PJ58eZ1Mto1txD5ocMx2bm7HvVj3omsNGUAXlqfNITWITLF9YfwyZAp3j86hxzJkAJ1evM9TdH86iUv4qScI/YUHT/ZIBAAAAID0gAQboRO6cIgr7dHU36smi2P63UJ//+5EuOvFIGtYzPtU4JzuHQpZPjSOm0ZRa0/vKGU0aUVHNCjNI1OhInH05KSrAAR9NP/gVumbIm/RV9v7matxaK5/+c9aONKh7DpVb+u3dNcvV0eZv1B+jzp1HbreuErucDbw2kwS4V+00+j5wKX0cuIpmLUtcJw0AAAAA6QMJMEBncrnIf+JTRLtdTp4/TiD37pcReXSi65QX8FI1Zatx1J7K/O39RL+9rcdO1YlJqS3aEK8A+1MkwOK0cUPortP3oZ0ueIzWuuJTopfESun3Yd1hujg3QNOsQWpcsmZCvOJsWZQX1sl4tadEHYXHsb9wuC711kqZpDrYSLcG7yKfK0p9XOVUOf9ncwsAAAAApBskwACdbeh+RAfcTFQ00FxoStbT1lo6AY7Ziazs/ZtK9TIzSBQ1+wc3WH7KycpS4+Zkdysh3ynP07LCHejS8B9pj/ADNNkapm7rlu2jL2J6erYvWk+06Fs1lum+fiuohtW+eKdo5/7CodrMTIDHz19L+9/3Fd3+3gyaMHUm9XLFP8/I6tlmBAAAAADpBgkwQBrKD/iohnL0iTSSqi/nTDiqz1nMm01Rl246RVNf1cck/rUz1XGZ1Z1y/Hp9bksKho2jvpd/Rm/Hxqnz4ly/OnrcLvolsCNFLPPrYp5pllUT3ze4zh9PgH258fXLmZoAvzxxCc1dXUuPf7OA3nvrFXNV6xleTI3RmDkDAAAAgHSCBBggDUkFWLYWEi5JgBd8xSNLnVu5PeiM+svp5cY91TnN/jBxb2ARi1Fe2WQ1/Ck2nHIDJllug6sP3oqG9cijp8/e0VwhCuQV0RzLNPCa+R5RxaKEtccNWfH9jeW+ttwpTzfbpKsrq26Id98eRbPMSBviWk41wYg5AwAAAIB0ggQYIA3JGmDprCy84Sqi+V+qMXmzaO0fJtG3sZH0YORoClumsvvFnfpoK5tJvkitGsr+wm2pANsu3HsIfXLlXjSqX7ySu1XvApppDdAn5fOI/rU90S8v6nPWmF1qRkTZjg7W2WunEb1wfEL1OhPUhHSC6/e4aKx7jhrbdALc/PZUAAAAALDpIAEGSEP5WZwAWzoB9jkT4AG70py1OvlaTt3ppei+akxzPyFaMkGPxZIfzUAqwMPaVQFOZZfBxTQzZhJgIfsP//qSOeFfJAW9zYgfe7aeOr2OPPa5nxItnUT0vz8QLXLsY9xFxYLVdKX3Ffo6+/9otHu+uaoNcK2i6nokwAAAAADpCAkwQBoKeN1U49J77+Y0lhNVLFTjT4Jb08NfzlVj8XDkSCKPSTi/dFSBTTJcZeXQPKtPuyrAqew6uIRmWf3NWaJaK4u6FcY7SEvy/lss6b4yZfrtS4imvkL0zOGcDCdN2e5ijq95ji71vkm9Ikv1BbePKvrpraT8rijV1tWoMQAAAACkFyTAAGnI5XJRg6fp1kX/WNCPvpmzxpwRrXKVUGzsWfpk3ufx6upSnQBPjg0ji3/Mc/wbVgHeonsuLcnakhrtKde9R+sjW2UVUfe8gDmTBNhH/9d4Pj0kyblt4TdEq2focSxC9NN/9LiLKo2uUscGdx7RAbcQXfITBQfto66JhupyMwIAAACAdIIEGCBNhbyJCXAl5dMMex2uYVmcV46+SK0NVmSrpLq1RGt1lfhnToCzfG7VyXlDSEJeVNqHLm68lJ7NP5foD1/Qmm3PVrd9EtuBSvPjCbCsX55mDaZ7IidRrd0dWhpnOUlFuB0s/kRjMd0ELB0EYvXquDZ7ENFul6ktrQKOtc/BukozAgAAAIB0ggQYIE1F/IkJ8LfRbVU1N9myaDei4QfrkzWziJZO1GP2kzWMeha0vAdwW0kV+OPYjvSXsv1odlk9TRlxLY0OPkZ3RU6m7nnxdb9+b/wxLgzqadxkJTbBsioWmFHryuvCtPe9X9LBD3xNwcZN30wrEo1RjtWgxlGfXqctshwJcLiuyowAAAAAIJ0gAQZIUxE/J7YOP8a2MqNESys4Gcs1ldYgJ16mAVaMXDQlNiShm/OG2KI0nuwdeP/X9OqkpVRFOsF1VoBFUY5PHVdbzXzsqmVt3h7pno9m0aK19TR7VS19Py8+/XtTqQtH+bPWCXDMZxJ8lpUb3/4pUo8KMAAAAEA6QgIMkKas7HhCJeba+/Ameezr+RSzq8UqAdbrf2fF+lMt5dDofomJ9PraoiSeAIsPp680I0pYAywOHtFLHZMT4Ecjh6mjS/Y0rlqixq35atZqM5Lq66afBl0XilCuSyfAlj+eALuz41/naEO1GQEAAABAOkECDJCmvDmJCfD8WHyrIXHu7luo4/Tl1TRxpZkaLA2mFn2rhrL+V3RUBXhQ98QE2CZdn7N8iV2m7zhmJE28fn9aTfGPPY8f/+fRseaMtWEatEw3Xl4VNGdENUG9BdSmJAlwHpnHFMjXR+EYW/JCBAAAAACkHSTAAGnK65hSK1ZREe0xTE91HlCcQ/930JY02CSl783RTZmcJsa2JOl9NaJv027S62NYjzwa2bebanJ1xOg+5ipRaVL1V0jTLJkWHbSbYLH3YzvTIquHOWNma6eWLKvUlVZbdXDT769bw48h10yBdmc5EuCs+NfZFUIFGAAAACAdIQEGSFPOrsJiZN9C+tfJY+gvh29Dz5yzk6q63vG7keq2tZFsdbTVuvLoo9gONLxn/gZvgWTzetz05sW70eS/HkD/PGk7Om77fur67iYpT6WuQFepxXvRXciVW2rOiEK1rW8VVB+OUgHV0hv+v9Ir/puppq5pot/ZGupryOPSU7E9jqSXAvGxO4R9gAEAAADSERJggDRVmJtYWT1gm55UmONXU5+lI7PYZXAJnbBDP6qmHHVue8Pakxooi0Z10Ppfm2yn5ONEWCq89x4/mr65ah+66Yhtza1NVfTYlW5uPJ0uCf+RZtEAOnfvLSlk6QZZNZWtJ8DS9fka74s0xj2XdnLPouKyeIfrTSXk6PDszXZUgN0eCrp0x+1QfZWaKg0AAAAA6QUJMECa6pbtU02jaqxsOjN8NQ12dGF2uu7QrcmVlZjoTmvUDbM6av1vc/oX55C7hT2G+xbn0lPRQ+id2DjacVAx7cBRQ7pa3VBToY4tCYajdIr3C3NGZNW3njRvbOG6+PRmX07i190yVWBfYy099IXeixkAAAAA0gcSYIA0JQnwnZFTaXTocfoqNpp6d0u9n69Uhbce1N+caSusYnUcvZET4Nb0K4pPzT5iVG91Lgm9CNe33ijKql5mRpovWGZGm06j43H7cxPXV2fl6XXb+a56euKbBbRwTZ06BwAAAID0gAQYIE1JAixi5se0V7fEdb5OruzERHeZ1Z38Xjdt2csxRXcTkCnaXreLinP9dNioPupzqjUVYHe49XWysYbEKnEguOn3Aa6tju/xm5WbWAF2mU7Qsk9wOBqjW96dQcsrGzAdGgAAACBNIAEGSFOFOToBtvXIb9pt2eZNSsRWWCW0Te8ClQRvSkNK8+ibq/ehz67cSyXBsn64zqxX9jTWqmNLosHEplc5jZt2CnQoEqVJsxebMyJ/0hRouxP08Jwa8lKEPp+5msbd9Tkd/MDXaksnAAAAANi0kAADpKkCUwG2SfLYnOzsxCZY9ZRFozu4Adb66t0tm4o4+bU1uPVaZl9j6xXgaChxCnF+ZNMmwN/OWUORBscWR859gEW+3qu5V2ghveC/nXqSfrxLyhtoAaZDAwAAAGxySIDbZjuO9zik9CMbgMqz2h84TuNoze84XuSQjjjytrL56fMcwziSfckh+6skx4ccsJmxp0C3hezNm2zkJl7/25yQRyfA/mjrCWEsnFgBLoryj97U14je+iPRmjnmaudZXhWkPFfQnDF/nhkYe1/L2a/emkq6Vr8buI4KSSf6kZj8KAMAAADApoQEuG0kk1jCcR3HoRxncEgi+yzHDRwtuZpDynO3cxzMIfcfw/EzR6r9Y+Zz7JoUl3PAZibg9ZhR63JTJMDb9kls0JQuwiYBDiQnwNFGohdPIXrhJD1mVmNiAry1i3/s/ncu0WT+0fvv0UR1a80tnaOyLsy/DBxTtwNJCXBhf6JzP+Gf8NPVaamrmi70vk0FVEc1QawDBgAAANjUkAC3jVRmL+B4jkP2ZHmX42SOHznO42jJERxHcTzF8RWHvI/9OWRB5xUcyaRKPD4pZnLAZqggSye2J+6Q2OU5mVSALwtfRNNig+ik8A3k87jU+tt01OjTjysvVsPf7fGGUrGfOamd9R7R7A8oNu11dc0Kt1Alrl5Ktd8/Zk46R331GjrbayZk5PYg8qXYmsqXTXTYfeaE6Hzve/RB4BqqrU9M5gEAAACg8yEB3jDSkra1ss5qc3RazrGUo+WsBjZ7b1y8G9169Ai64fCtzZXUJAF+K7Y7HR6+g8bHtqFhPfI3eQOs5kRMAqw8uAMnwbrT88JpsqpAmz53gR6E5fWgRF9GR6/bSmnFtK/VsbP0KvuOurvMGuADbuHfoM18jb1+qnPFk+O+rrVkrZlnzgAAAABgU0EC3D7y9ZKSXCnHRRwHcfyNo70GcwzkmK7OEg3hkDXGkljLM2aZOt38/jeQ0aSKe/ouAyk/q+X1wHmmUmzbund6Tn8Wls/ROKqujGiSTI4gCtXEpzOvCZlfTRFHArzLxbRq3/vog1EP0KexsepSj+pp/A47b22tt96xDdNw+fFvXp03cQ12Q7BpMg8AAAAAnQsJcPs8zCGLE6Wqez/HpRyPcrSHZCpPcshCQnkfTt9yXMlxLMeRHO9zXMUhcy5b+7/qwSFrip0hyTRsBvICieuFh/RIMTU3TcSSOyf/8rxKYgONVeYCUbalk0W3cw3wgbdRzz3Ppb8dP4YKhuyiLnWzqqli2Ww17gy+kE7So/LjmNVyk7Ggv8iMtMb6+HRvAAAAANg0kAC3zx0cO3IcxvEfjgc5/szRVi4OSX734JBGWtJYy0kaZD3CIeuMJfm9hOMajj05ZB1xS6QiPS0p3uKAzUBeILFC3L8ocVukdOJKbhy1di7Rgq8oqzGeIHrCepqx21SAQ+Tnk/ivq9KtpDectniGLMU3PrmRfzIPJqpeYS50rKywnq5d7+mW8HhSCfoSE+BYfTzBBwAAAIBNAwlw+8g2SJM4JDm9kEM68NzJIVOiWyPJ7xMcsnXSWRxtTU6laZbQJa/mSXV6RFK0ljRDhshNqgD3LUrfWfM5TRtWE018kgrDK80JC5oEOGoSYJf0jIsr7TfUjIjCVWaZfc0qou/+wT+lPxB93Fpz9vWTG9FJeoOv9S2m6pPuYwWRAAMAAABsakiAN8wEDnk6L2t6W2Inv2dz/J7DTmrbI2aOzZEsQNYUOwNddzYTuf7ErLJfGifAa3qMo1VWIVVbOfR1VO+ZS7+9TTmx+PZC7pBOgD12BdiVpY62/CKZ8a9Z9WZacrlpnMVCCx1V4Q4SikSpwNJJbDhQrI4tqfcmVoBdISTAAAAAAJsaEuANsw+HJKayd29zJPl9nEOS3/M5dMeftjvTHGU7JICU3G75NosrzUusmKYTf2432it0P+0UeojuixxvriaSKdCTF1dQVbVOhMNJFeDcnByqs/Q1d1BPS16zJL5b2OqN0G+qsr6RiqlGjaNZrSfAW/VNvI/HJPUAAAAAsOkgAW4bmep8L8cJHHtxSJOqlzhO5/g7RxmHkPW90r1ZOjzb/slxLockvlM5ZCqzHWM4bLIuWJpdSZJ8AIfsHyzTmmXd8ecc73AAtInLlZgQpxNp2BWkgIpfrCE0NTbI3BLnCdfQ1U9/Qod79Os+je7ECrB8ftUu3UzLYxLg+pVz1VGErFTzrDdMeV2Yil06AbZyStSxJcXZidPS164to8VrsRcwAAAAwKaEBLhtZIPSnTge4viUQ6Yz9+KQBFi6NNvkGa+EM/uQRFacwyHvxxlvcNika0+U4y8ckuy+wrE7x185DuVobQo0QJeQkzBd20XPReX1nkRZ4XJ6NBJfxxtOSoBFjVtv9eQP63W50TXxKdDdVJP1jrWqopaKXPr9+gviU7CbVbSFGWgFVEd/evUXcwYAAAAAmwIS4LaR6q10YpZmV9JuVxb37c2RvJZXmltJ8rtQnWlS3pJrqcJZ+pLylXSX7schz/ZlEecoDqkAhzgAWnT1wVtRrt9D/zzZObEg/dSFZJKENm5ICX3p24MqrcRtm4a5l9EW7lXmjCjiaZoA10knZhYw3aP9NYvUURTFyoliHfuaUVlZvElXbnFPM2rB6JOItpbdzLR8VwNNXFihKskAAAAAsGkgAQbIEBfuPYSm3nQQHTm6j7mSnkb1i3dH/sMeg+nSQ7ajU8PX022Np9KLEVlW31S9We/rFPTpBDgnWk209CfqXRdfA+yVyRT1a8xZx6hes8yMOJkt7m1GLfD4iE58lhblyutYugIsvplTRqurg7S2Fq9rAQAAAHQ2JMAAGSS5GVY6Gtojjx46ZSzdd8Jo2merHnTKTgNo9z32pS+KT6CC0r7mXolijUEzigubbYaKouXU+OKp5KNGdb5OTdJewHM+JZopO5itH1/ZDDPir3PJEDNqXWmpni5d4NLrf5//cTHt/rcvaO97vqSqhqTHDAAAAAAbFRJgAOh0h43qTb8bK7P9STW0uvbQremzP+1NvXvE19aGPTlmxMljpGk1N5qltxnKpiD56nSy+3Z0V3UUwbVLzYgtmciZ57FEL51MtCqeyLZHSdU0dQzLKoie26pxW+Tk627QPf06iZ+woJzC0RjVhCL07ZyOrVIDAAAAQMuQAANA2hg8LJ5Yug6+04yI+nn0Ol+nWHbiNkOvR3ent0qk4bpWWx5fsxv76m4zImpc8I0ZtZHsL7zga9oyqBtYLcserqc3t1W2rlSXRlbStq54oy5RkN3x3aoBAAAAoHlIgAEgbRSOPYZo/5uJTnyOfNudZK4S+fvqdbROrpx4AjwtNohqD7iHzjpgR3OFqKHKNNGyLAovnqTHbMai1WbUBpOfJ/rndkTPHEFDrcXqUkXhSHVss22O4n/01PSbfM+ooy0StcwIAAAAADoDEmAASB9uD9HulxNtfQSRL4to7+uI+owh/5H3mzvErSrZWXWPXhwrpXsK/0Jn7LkNlRQWUdDS1dlwtUl0KxepbZVsVvLa4JbMfNcMNNlfuGAH2Q68HQbtTrS9NIgnGuueq5phHeieSHu4f6VQRHY+AwAAAIDOggQYANLX3lcTnfclUfdh5kKcNMzaMfQI7R++lw7ZXbbpJupVmE1rOcUU0ZoydaQlE/TRyGpoewW4dqle9/tddFs6Jvo3Gv+7H2jo9vupa+2y9eHq4KEYXeF9jR7z30/P+u8iNyfnAAAAANB5kAADQJe0/9Y96cCR/enEXYbS8Tv0V9eKcnxUYRJgd8NadaQlP+qj4WuI7y/cosYGyqlboobTPVvRjeedRHuNHq7O223Arpz9+tXwbO9H6igKyn4yIwAAAADoDEiAAaBLyvJ56KFTx9KtR48gj9n+STpK13l10yl/UCfA0UWJCXBuyFSGW9G4ejb/gtRrdAv6j6Dt+sf3L243fy5RP12ldqp155sRAAAAAHQGJMAAkFFCft0cK7uxkrPfRnKV/abObUVRToyt1ptPLZ31sxkR9Rgy2ow2wOC9zSAuGomYEQAAAAB0hkxNgLfieJFDut2EOcZyiBs59tFDAMhE0awSdcyPcQJcsZDclk4yZ8X0vsMB/pVgNVSocUvWLp9vRkRbb9sRCfBeZhAXC9ebEQAAAAB0hkxMgLfjmMghzza/5PBw2PI4LtBDAMhIed3VIYsT3diyyWosvouNMCPOi1ck7sebSjRYrY6Nlod6FifuObxe+owl8idNeY40mAEAAAAAdIZMTIDv4viVYyjH6Rx6caAm7WDjG4UCQMbx55eaEVHdnG/MiGhR0S5mRLRm6Rwzap4rVKuO9ZxKuz0d8KvS49VbIjk1IgEGAAAA6EyZmADvxnE3h8wtTF7oJ+1fe+khAGQif4GuAIvIYr0FUrmVR4NGyq8GrXrFXDNqnruxRh3rXTnq2CGS1wGjAgwAAADQqTIxAZaKr6z7TaWII6SHAJCJfLnx6coF1brSO9/qQzttO5zqrYA6j6xtff9db6OuAAfdHZgAD9nXDLT6ujp69oeFtLQCa4EBAAAAOkMmJsAy/fkYPWziYA5svAmQwQJ58jqX5qGoOkoCPKRHPpV5e6pzX81idUzFsiz6xwtv0ra149V5hybApcOJjnrInBCtWltBf3lrOh3ywDf02W9t3J8YAAAAANZbJibAD3Ccy3E/h926dQDHnznO4ZDbASBDZRfoLtBO5VkD1L7BdVl91HlxwyKaMG22Gif7de5Cunz2meRz6eQ57M1Vxw4z5jSqI51US6MuUROM0LnPTKJ/fDpbJeAAAAAAsHFkYgL8MsdfOC7mkG7Q4n8ct3PINkjvyAUAyEzZ+U0T4EjREHXM7TlYHbdwraCdXtuRyu7enmKf3sp3iK+McC350Yy0iKeDE2AWcuup2Od4P6RrvC9Sjl83q//Hp3PoxwXlagwAAAAAHS8TE2BxB4c80z2P4waOCzmGc0iHaADIYHkFhRSxEn+1+XptqY4D9j6Twl7ZDU0rrZ9L7m/vpcjMD8wVToB92WakRXzx+3eURpdOgMUF3nfo1UNdtK1rARVSDa2qDppbAAAAAKCjZWICvCeHPGNdyvEkhyTDj3FI1xu5LrcDQIbKCXip2kwxFpIMl/TTCbBrwC7kv3ouLTnyZXoxcJy6JmbO+s2MiELBxAQ05t8ICbA7y4y0bT88gd4LXE8/Bi4mqlpirgIAAABAR8vEBPgLjm30sAl5Fiy3A0CGcrlcVOuKT1teZPWkob3jnaHJl039xx5Mh1zyoLnASW/NWjPihDmouz+v4883g44TMVOgkwVcEcovm2zOAAAAAKCjZWICLNsgNcfHEdNDAMhUda540jrf6k1DSpuu4+2Wm0XVlq4UW/UV6iiioaQEOLDxE+DIfreYET+W5I8PAAAAAB0mUxLgAg7p9CwhenHY53ZI9fdMjpUcAJDB6j3xacurfP0pP0te+0qkK8X6fu5QlTqKWFIF2JXV8Qlw2LEG+Lfex5B3hzPMGQsjAQYAAADYWDIlAb6CY4EJ2UPkDce5HTM4zud4hgMAMljYG09ag9105+dU7ETZG44nwBSuMwPNmy2vr3WsBstvRiynmMixztiFBBgAAABgo8mUBPhjjqs4ruaQKdCyuE/OnXEZxz4c0hUaADJYyBtPWt2lw8yoqaC5n7+xRh2FlZSAujxeM+o4VixiRkSe3BL+x0chtUJDEuDEBBwAAAAAOk6mJMA/cPyd416Omzn+Zs6dIUnxVxwAkOEi/ngCnN+vuZ54RGFfN3XMjsYTYFdjYgIaCzeYUcfxxOL7DvvMvsUNLr39kjtSr44AAAAA0PEysQmWJMDL9RAANkeLi3ZW2x9NiG1J/fv2N1ebigV0ApxrxRNgd2NiAlo4eAcz6ji+aHyrJb9JgIMmAfZGUAEGAAAA2FgyMQEWHo7DOf6P469J8RcOAMhgZaW70k6hh+mk8F9oaM/mm1hZWYXqWGDVUiQSVWOPowL77ag7adjIncxZxynwxadA5xSUqmPYrRNgHyrAAAAAABtNJibAUk6ZyvE2x10cN5m40YSMASCD7TGsO9V4utHOg0upJNfRcCqJO0cnwH5XlCqrdSMsX1RPeZ7vG0q7/+4iNe5ofXLju7UVlegEOOTRWzL5Yxs3AQ5xoj9xYTk1RrEjHAAAAGx+MjEBvp1D5hcO5JBnmTtzSBec+zhmc9hbJQFAhho3pDtNuv4Aev73O6vtjprjzS02I6KaijJ19EZ1AtpoEtKNwevLMiPm13sURzy6Auw3CfjGcterX9P/Hr+d7n/ze3MFAAAAYPORiQnwfhyS7NrrgKXMMY9DpkN/yiGNsgAgw3XL8ZHb3XzyK7LN+ltRtma1OgZiOgGNbMQEmI74B//29RL1GskPVL8m1+jRiXDA2rgJ8DG/XUF3+Z6gXX65xlwBgBvfmkYH/+NrWlKOJQgAAJkuExPgfhwLOWRBnyS/+lml9g7HAXoIAJu7Xn3iDbJmz55NtaHIugQ46tUV2Y2i3w5Ef5pF9Icv+Lew/jUc9emEO3sjJ8Cj3LItOtGeHlkpAgBV9Y30zA+LaObKGrrqtV/NVQAAyFSZmACv4dCtXXUVeIQeKjLfseM39QSALqmg/7ZmRLRw5k80+uaPyW/pDs2WSUg3mtzuav9fW8yrX6vLNh9/Y4jFLDMCAFttON6Ubtoy3QsAAAAyVyYmwD9x2M9q3+eQzs+ncZzAcQfHeA4AAKK8HlTt1q+XHev5mray5lM+6Qqs5ctTx85i+fXHy+GPH9lIDarsRl9NrJxG9MKJRLM+MBcANh81wUYzIgqjORwAQMbLxAT4QQ77WZ5sebSS478cL3HItOjLOAAAlDW5Q9Vxa/cSei9wPRW49BrAAb11d+ZO4zNrgF0Rqg9unGnQVWVLzShuWQV/vv/ejWj2hxR7G78eYfNTG4xXgNvbHV1mVUxZUkl1ofj7AACA9JaJCbA0unpUD0nauo7hGM0ximNrjlkcAABK6QD5tdBU8YD49OhOEYi3KwjW1ZhRx6pdk5QAR0JU8dSJ5oT/INStIrIwTRo2LzWO5LW9qwRenrSEjnroOzr9yR/NFQAASHeZlgBL15rvOPZXZ5r8OZNuL9M48BItACTIH3GIOloeP9GR/yI69F6iYx4jGnm8ut5Z3Fn5ZsS/qJb+bEYbqHY10fQ3iEI6oQ5VrFBHW3jqGzSi+mtzZjRUmAFA19TeJQQ1jgpwe308XSaZEU1ZWkUWXjwCAOgSMi0BlnmDIzmQ6AJA22x1GNGJz5PrvC+Jxp5BtNMfiEafmNCgqjPkdetuRkS93jmdKNoBv8Ze5vfz6llE/9qBn6G/TNEqe3c4beUUmTCTKFqdmCQDdCVvTl5GI276iB76Yq650jrnFOj2kIT3lyWVahyNWVQXllVWAACQ7jJxCvQPHDvpIQBAK1wuoq0PJ+rZyVOek2yx82HUQAE1dlv8hHztHDVeb7EoxZZJT0BWu5LojfNo51l363MjZ0XTaZs1ZYvNCKDrufzlXyjYGKN7Pmr7aidnEywRbGxbIru4vJ4q6uNvW9WQ+H4AACA9ZWIC/CeO8znO4OjcNq4AAOvJl1NIDw36lznj/HXFeu7TK5Xjn/9LNO11csf0E/KIlfpXffeQTna/jsrEGa1+zRIzYg2VRJOfJ0JVGDKY7P/tVFEfpgVr6uj+T2bTUmkS1wy7+muT/YQBACD9ZWoFuB/HUxzSDVoWv1U7Apv8AUBa6jt8zLpktW7xL+rYbtNeI3r7EqLXf28uEF3eeLEZpTbeu4MZEYXLl5kRkfXpTURvXUSxF082VwAyT/Ia4PK6MJ3/7CR64LM5dMZ/JpirTU1enJQAowIMANAlZGIC/D+OFzhk6yMJfjaortnxOgcAQNrp272I5ll91Di6vhXgz241g7i8obuaUWquATtThaUnzMSq4+uEXT/J64j8h2LFZHSHhowlCfBxnq/oDu8TVEB1KgGevapW3Ta/rE4dU0muAFcnTaUGAID0lIkJ8FkcZ7cSAABpZ0BxDs20Bqixr2I91wD7ssxAC1k+2nOH7ehOOsdcSdRoeWjItjvTSqtYnfurF3H2zU/kp8jW6XFWJdYGQ3oLR9rX/dnW2FBN9/oepVO8n9O13hdUAuyUvEZYhCJRmrFcJpXFoQIMANA1ZGICDADQJfUpzF6XiAaCa9pWdV05jeiVM4neuIBozqdE9eXmBm2x1YN6dsuhPU+9lq6L/IGubTzX3KLNtvrR9kN60lQaqs57Vv1C9PTh/P6klUJc9WLZSQ4gfVXWJyaubRWTte7G4Z7xVJGUANvVYKffVtRQOGm7pWokwAAAXQISYACANOH3uikU0NsheS1+Mh1MnGKZ0jf3Es14k2jKi0TPH0vUkJgAfxLbnnoWBGi3YT3oymtup5NPPNXcos10Dab+RTk0JbC9OvfFQkRLxquxU8WiKWYEkJ6cHZlFW/cDtoJ6n2wRoDCtbZIAx2+3/bJY75fdm9bSv3z/pMPdP6ACDADQRSABbpvtON7jkDmAstewPMOUZluncbRFD46nOdZwSEtJedv9OFLZn0Nul/vJ/eXt5O0BYDPgynf8uNeWmUELWujQ/Hp0d7ovchz1yNfTorvnBSg/v0CNbeUFW5Pb7aLlRTtR1HKZq01FVv5mRgDpKXnqcnKFtlmh+FRmvytKS8oTOz9PXJD4opKw1/9ekf0uHeEZTzf7nkYCDADQRSABbptCDtkb5DqOQzlki6WFHM9y3MDREtnY8zMOSXgv4ziKYxXHhxx7cTjJ+QcccrvcT+4vCbG8vd4gFAAymq+gtxmxWvlV0IqgaWw/aA+iA2+j+oIhNDE2nLYMPk1XNl5EEfKqyrLNn52YAEd7jlLHYYP600PRo2hBrCddlzRNWriq492hAdKRbF/kFGpsWwLsdiTAYlFSAvz+tBVNkls7Ad7NO1MdS1w1VFvXfMMsAABIH0iA2+ZLjgs4nuP4guNdDtkX5EeO8zhaIs8kR3CcwPE8xyccx3HM5ribw+keDrkut8v95P7ydvL2qTvYAEBG8Rf2NCOiWO1qM2qBPU26cCDRuEvo0ZEv0fHhmyhEfnV5cGmuOtqycvLNiJNfy0XdthijxmMHFNF9kRNon/D99EK06QSV7GAbHgvAJpRcAQ61oSmWZVnkCidOcU6uAAc5kf54+kpzpptdLVxbT4VUQ30bF5mr/PNat9aMAAAgnSEB3jAyRTlxA8GmjuGYxSHTmm3yNpJM78TRVy6Y444cUlV2vs/vOSQplvcDABkuqyheAW4oj29J1Cy7ApwtE1WIVlYF1VEUZHnpnN22MGdaVsBPQcunxnOtvjS8n55yPXagfnvhcTedCt0tIr/uANJXchMs6dTcmnlldZRrJVZu19bqn6EsCqmjmL8mfp+1tfr6Dm750xxnJa2/BwCA9JSpCbCHQyq0j3HI3r9ylHMvx4aQr5e8j1KOizgO4vgbR0ukevurHiawr21rjnI/0dx97dsBIIMVFPegiKV/NTdUNr++V4nwE/5GU63K6qYOy6ukTQHRqH7daMqNB9JpuwxU57Ysn4eqSFeFp1lb0Ja99JRoWSc8bkiJGl998Jbq6JQr7Q9CTZsBAaSL5CZYrW2L9L+fltL+931Feaq1R1wh1dIfPW/Q9MA5dLZHViURLa2I36cupBPrHdzy2nacBwkwAECXkIkJsLRQlanJMn1Y9gQeZ45yLtd1i9X18zCH/IWVuYD3c1zK8ShHS+QZZaq/ivY1/YwzfmzuvvbtzZEyjiTTzhjCAQBdSGl+Nq0hncxmL/iU6N0riCY+kXpLJLv6K7ISK8C9CrLI5WpayZXq7j9iJ9IP0W3onbzjKC8Qf13wqbN3pG+u2ofO23MI3daY2C1ahCqwDhjSV/I2RK1Ngf7Tq7qzeb4rccpziaua/ux7lTwui270PcsJcn3CtOiakP44OyYlwL6Q7gwNAADpLRMTYElMpXwhz96yOWQ+oRylY/MwDrl9fd3BIdOUD+P4D8eDHH/maE1Lm3km39bcfVvbEFQq0rJRpzPe4gCALqQ0P0Bllk6Acyv5CfYk/lXz3p+Ilv2kriVwbJP03JRKKqsJrUuAe3fTnZ9Ted+7P53ceAMF+iROLAl4PdS/OEeNn44eROeHr6D/a4y3Oaib+j7Ry/yr9Ju/mysA6aM6mJwAtz4FWuQnVYBLXY4Xlti0rN9Tbvl0c6YrwLJd0kjXfHNFCzRWqjXFAACQ3jIxAT6CQzozv8hh//WT4wscf+WQ29eXbIM0iYOfBdKFHDK1+k4OmRLdHOmKkap6W2yOdsXX7p7R3H1TVYadpDotz2adIZ2kAaAL6VGQRc9GD6BaK4sibt3ISilfYAYOjgrwZwvDdMgD31BNSLcQ6F0or/uldvC2vVQl+JgxdguCpg4Y0Y8+iu1IP8fkdUOt+LubiX57hz/YrUQNqHZBeqluiNAITkqf9N1De7t/aXMX6ILkCjAldoUWh4Xep4awfkpRxz9j27nmqS2TnApiNdTQ2LakGwAANp1MTIBlzl/8pdpEUhVtfqPL9pvAIfMHB6uz1KZyjNTDBPY1eUzOY3P3tW9vjkzLls/bGfM4AKALyfV76B33/jQi9CQ9MPJNc5WlWl/oqABXWzm0xjTnES1VgO86diRNvelAOniEY8ulJLcdPYLOGjeITjtgZ3PFyeIsIKnj7Ur+FfX04US/yGuNAJ1PujO/G7iB9vNMpqf9d7epC7TIV9vux3VPqgCLLFcjLavU96vlBNi5/jfm0ssIily12AsYAKALyMQE+FMO2Ts3lQM4ZEujjrIPh/yFTZwHlegNjq04nM8i5a+lTMmWNcl2m1dZXCcJtVyXJl62XThkSvfr6gwAMpqs25Vp0PJa3Yu/xitRVqotVhriCbA0tnLu99u7W/MVYPkYOf742t9USvICdNOR29Kx47aheTGdKK+14lsoNdQkPZ5XTida+A3RmzI5BqDzddQU6P6uMjOK684/YUvK9f2kAryTW+//GysaQsFsvXVZkatGVaEBACC9ZWICfCuH7J0re+rKBpfyzE2O93Icz3Ejh0wptqMtZKqzvL283704juV4iYOf8ZEshrP/Wj7JIX/9nG1XZa2wVGNf5TiFQ5LzVzgkqb2aw0nOJVmW+8r95P5yX6n+PsUBAJuBgSV6He6ahhhVWXq8alWKjtC1q8yAaI8RQ+nNi3ajHQcV0d5bltLYAfFtjTZEfsBL13f7G50evoYuCl9urnKyUZG0LVK543XAUK0ZAHSe9jTBisbia3XzkqZAb+Fq+rPW17WGllbo+9UFQzTWPUeNXQN3oWhWkRoXUQ0qwAAAXUAmJsA/cwzi+BOHrNddao5Xcsh16SQjCasdbSF7+MqevQ9xSIX5CY5eHJIAX8Vhk8qthHOatcxJ3I/jC45/cbzDIUn5IRxfcThJdfpQDrld7if3l7eTt4/PbQSAjPaXw7ehE3foT7sNLaEKU3WNJleAy2YRfXSdOeFfPLlFtE2fAnr1gnH09Nk7kdfTMb/epVr8wB8OotNPPZtO3Gs7c5UomFwBdqpaYgYAG9dz4xfRKY+Pp7mra9atf7e1lADXOKrFyRXgQa6VZkRk5enqbh/X2nWdoN01yynfpd/G1W8HohzdukMqwEiAAQDSXyYmwLdw3GxCxnakuibRFlJ93ZNDml35OOTl3r05nuNwku2WJPldqM7ipExzJof8lZR5ibtySCKdyicccrvcT+4vbyfrewFgMzG8Zz797bhRdO/xo6mS8tQ1dzBpDfCMeJN32Tc4O1tXijeGngVZdOC2vWiL/vGmWY21zTfBql/d0qoQgI7z949n0ffz1tIVL0+hLEt3QLe1lABXOvYM7uaqMyNtsDueALt6yo6C/AfZFabKNXrFkuVYekA53cmdoyeTFaMCDADQJWRiAnwTh53stiUAANKS7NFbYekE2BviJ91zPyN64SSieZ8TrZT+etq/o0dQfra8Nrdx5XaLN6mP1DefAJcvm2tGABtXdVBXfacuq6ISV40a20ItdGSuqA+ro5ti1I0SE+AEJgEWkXLZCIIFHV2iswrIm99dDQvRBAsAoEvIxAQYACAj5Pq9VE56CrQ/zAnwx38hmv0B0XPHcRIsqyOIPoluT/dGTuRkeeMnwPn5+RSy9MeJ1TuqYI2Jlbe61Sm2bALoYI3RWMJaXmlU5RRubD4ZrTSJajeqJbfLvA9XiqdEPeN7Zbur9dR+V8iRAAcKyJevd0IscDVQTV3iemIAAEg/mZoAyzrcwzn+j0P2/nUGP4MEAEh/breL6twFapwTXku0xmy9YkX52b2uds2wBqhjflbLXZ07QrdsH1WTmWrt2IKJ6hMbYsUqFpkRwMaTvOduSdL2RdFw860zquobaVf3dJqcdYG5wkq3NgMHRwW4MLxKrR12m589JavbuinQIlLbwtp4AABIC5mYAMscPZkb+DbHXRwyJVpCuj9LyBgAoEto8HZTR58V5syy6RYrv8V00/m8TkiAs30eToBz1dgdciQbdYkJsK8u3p0aYGMJNkmAHZVZVlbRdD9fm0yBftp3tzkzSoebgUPhQIp49Is+uhN0A3kaHQlwoGBdEywRrIr31py9qqbJYwQAgE0vExPg2zlkPp48K5SGVLL/7jCO+zhmc+hyCQBAFxD06QQ4wZH/4ifrW1Ft4Vb0dWyUulTQCQmwdISudZk1yeF4chGtTUyAA5HERARgYwg1xptcFeX4qDslft99OGURfTIj9Ysx5XVhCriSpkjzz5STJU8h/HnUmK+bv/UzCbDfmQBnSQIcrwAvWrqEYjGL7vzgNzrw/q/pgudk4wkAAEgnmZgAy5ZBkuzqdo1E8hdyHodMh5bOy7KfLwBAl1Dv1w12EmxzNNFF4+mzvf5H9ZSlLnXGGmAR9Jg1yY3xZCNYlZhkBCI1dPZTE2htLXZvg43HWV29dL9hNKJQN7ayBVxh+sN/ZRfEptak+t4sle35HQL8ve52k7tIv24uFWDZCsnP39+i0eUn8gYSKsCeYAXd98lsevQr3Qn9x/lJ3dsBAGCTy8QEuB+HbEMkfxkl+dXz9TTZW/cAPQQASH812fIrzSG/j6o6zV9TR5e9PMVc7Jw1wCLo1QnwgNAcouWT1TiUlABLV90vZpXR8z+arrkAG0HQUQHuV5RDhw7VLwbZAqQrvEsrmjamKqtJTJaVpAqwK0vPvvAX62UGfV1lqgKcFdNdo0NePRvCmQAXu2rowS/iXdBlnXJDGNOgAQDSSSYmwDIXz54zKFXgeAtH2aaPqHOeJQIAdICGvP5mZJimPC9OSEwuO2MNsGjwx6d70mN7E/34GFllnAw7yNTSAIVpyhJHoyyADuZsgpXl46cz9YnVVjsBfnuKPSEsbm1digpw8WAzMPJ7qYOrUP8MdnPV0+o1ZZRr6YQ67DEJcHb8Z6KQHNOjjZQfCwAANplMTIBlwY3dtvF9Dun8fBrHCRx3cIznAADoEnzZ+VRtZZszfo5fso06VtQnrl/M83dOAjyp5CiabhpvKYu+I+/ameYk7g3/jbR4yWKyrPg2NQAdyTkFOsvn4Yw4cW9qOwF+a3LTBLiiJsXevzKd2VR9lULTMsQ+smDZAsonnQA3+vRsCPJlcejJZlIBFlv1MrcxWW8MAADpIxMT4Ac57O4ssuXRSo7/crzEIX8tL+MAAOgSZG2v/UReXPVNTDXYWVUd33u3b2G22jKpM4QKh9Jh4TtplVWozq2GSsqplP6CxIm62SKJbeNeRJeFH6OVjscJ0FGqGhrpyW/j+01Lh3JqSKwAn7J9D3WctaqGZq5MbJAVq2tmba6jmrsu8e0Wn4URq1xC+S6TANtToIVphHXQFl66/tCt6aYj49snrUUCDACQVjIxAZZGV4/qIcl+BGM4RnNIq1TZ5M9spAkAkP5kanPAFd/+aIY1UDXYmbgw/gT+4VPHmtHGt/eWpepob79Uv3Qq+SK1ajwhlthE6HDPeJqypPmtaADW13VvTKWvZse3HEo1BXqvwXoPbfGmowpcH45QVmPS9Hy/qdjGHOt1C81MBzMFWkgjrAJTAY7YFWBhkuX+1kr6w56DqWdBfD1yeS0SYACAdJKJCXAymX8n+wJP42i6iSYAQBrLD3jpjsaTzRnRQkuvS7QbAJ2/12Aa3V9XYzvDvlv1oDEDCqmadLU3t3GtOoqJscQmQuLXpVgHDB3vvV9XmJEW8Lj4hyLxe600K0bbDyxS47d/WaaqwA9+PoePNeumKiuSvJ79nh43Ohpm2RXgvF4Uc+klBpIA2xXgmJ00i+6y2yJbM4efdVhUnOvX5wxToAEA0ksmJsDSjvQFjnM4HAvVAAC6HqkAPxM9iG5oPJsOC91OsaRf2wOK49OOO4PsBfzY6TskTHe2TUyqAIvFi/R2MAAbU7Z0ZrbiXaGVSIgOGaFfMFpeFaSD//EN3fvxbLrkhclU5GxWddKLRL1lohhrbNBHYVeA3W4K5fZWQ9kLOI/0faLOBLjEJMCShNetUfty+yQpZ5gCDQCQXjIxAX6ZQ/6SPcEhz7ykPekjHMdy6JeCAQC6iMJsH4XIT89FD6Dp1hbq2rAe8bWHW5Q4d3rrHKX5ASoojG/9IsqsAqrKafqao3vFZDTCgo3KRTHKiqSYaRAJqvXxyZZVNiRWgB3bGNG2R5sB6xbfgixWoKvBUgHOJp3QWj7Hi0Ddh5sBWzNbvVBUlKOrwOXoAg0AkFYyMQG+lEO6T/TlOJvjB44jOF7hkAVDEzgAALoESTaT3XfCdnTiDv3plJ0H0C6DExPRztLoj6+vFLNj/Wlw/z7mLG5IZA4tWuuYVgrQgW71/oemBn5POd/caa44REJUktf050d0X9crk5kGVsoBtxCNPpnoqId1d2fDU6wT4IGuleR26Rd0XNI12mZPgRacAAt7GvRarAEGAEgrmbwGWBYISffnCzjO5/iEQz7f7TkAALqEVAnw0B559LfjRtEdx4zstO7PyWLJCbDVj0YPaJqMj3LNpylYBwwbybGebyjPFST3jDfMFYdIkBPg+Fpcpx4u/T1pZRfp7Y9sud2Jjvk30ZhTzQUtUKwbYRW7dMM34fY7qsuyXthrEuYyvS1YvyJ9+zdz19CcVU33BwYAgE0jExNg+Zx24biB4ysOaQv5Pw75S3Qjx+4cAABdQvekClZJrp+y/R5ztunEAk0T4O36F9EXUbOW0hjpXkBTlyABho4nU59zXC1ML5YE2NGMyqnUJMCuPL1GuDWuPL2lkpPbmTi7+Wey1DSBWzVdHS4a15NcLovCkRg9N36RugYAAJteJibA0pL0Ww5Z8zuRQxb0yPymvThu5ZAp0QAAXUJuwEu5joR3QEnnNr1qVlY3M9BmxfrTlr3y6fzGK+mg0F10c+Pp6np3VzUtXyytGAA6lr0WV7HX4BbE1+3KFOiCLB95U8ySsCvAlN9TH1sjleEkbscUaaXnCH1cOZXo3Stp7Auj6ZHcJ9WlNZgGDQCQNjIxAZZnZfKXRjb9W8qxhAML0ACgy+rumAY9vIej8+wm5MpK3HppZWAQdc/z8y9fH82yBhD1ie9N7Fs1hWIxNMKCjpVLQTNiO51HdOVMoovHE3nN1GRORGWJQFGKKrBdAZYtjtokp2kC7PEnJcC9TAIsnaAnceJrxWifyHd8waLaEHZhBABIF5mYAJdynMWxjEMaYskewDJ+huM0jjb+tQMASA/O+tWwnvEO0JuSJyeeAC+zSqhnjx6q8+1rF+xK5+85mC48+eh1WzZtGZtLNUgAoAP5vW7Kdk5/9ucSFfQmCuRzAmwS3tkfEv30jOqknsjiJwrtrQDLU4tEniYVYOm/mShAISqmGiTAAABpJFOnQEvH5/M4BnNIa0aZ+iztSSUJlqowAECXUVHfaEa6AVY68OXEd5WbHetHQ0v149phUDFde+jW1KO4mKrzh6hrI13zqbIeU0Ch43hcLsrh5HId55ZEQUeH53cupboanexe6HmbJgQuoqPc35HfFVXX2lwBTpUAJ1eA+26v35+Ln1oN3sdc5CcfrjVUhwQYACBtZGICbJOXfGXdr1SDz+TYm0MKKdIUCwCgy3A+eR7eMz2mQPvyHAmw1Y+GpEjM60tGqeMo93yqqEMCDB0nHI1xAuyYAu1v/oWhY8Lv8r8WXe17Sa39fcD/sL5BtLUCnF20bkaDrUkCLFXoP07UU7H3+6u5KHsHr6WaIBJgAIB0kYkJ8J84PuCo4PiC4woOeTn4Wg7ZAqlpK0cAgDQm2x2J3t2yVKSD7Jwc+k/kYJoX600vR/ehIaYC7BQt3VIdu7nqqaZStmEH2HARTn6jMYsGuFabK8zffHO4S7Lep6EuWQmVQl4bE2C3m4K+xHXvvoBjGyRbVoFOqrvpbZOEqgCHkQADAKSLTEyA7+KQRlj3ccgcJClTHMxxL8dkDgCALuV3Y/vSU2ftSK9esKtaZ5sO8gJeuiVyBu0X/jvNt/pwApxrbonzF8U78oYrsPoEOkYoEqOTPZ/RP5yVXOcU6GMeI+o9mmjXP6rTrGgtPVfylBo30dYp0Czolw0l4rzOfYCTSddoj25e18e1lmqDEbIsNIIDAEgHmZgAy1+ocRwy/0j2AY4vngMA6IK8Hjfts1UP6leUJlsgMdmeyebzuKh/cdPHll0ST4CjldKYH2DDSQJ8p09vL7SOTD+2jT6R6PyviQ68jajfTupSr9rf1LGJtk6BZo1ZiQmwr6UEWF6o6qa//6UCHIlZ6nEDAMCml4kJcI05OslcJKkCl6gzAADYIFIBtg0syeUkuOmfk9zuA8yIyKpZaUYtk+mt389bgzXD0KxQxDSwcnJWgG2ShG4vLUBSi8nbSNfoNooE4uvehTfQynKEooHqsKVLz35AJ2gAgPSQiQnwbRz366GyP8dsjvfMsek+BQAA0C7OCnCq6c/CI9vSGN66FWbUsrs+mEmnPP4j7XzHZ/ThtLYlzdB1rKwK0pUv/0Lv/dq274dUQo0pKqnNrQFuYYqz1db1v7akZNnlje/PnZKpPg91L6cSqkpoZre0op7embKcgo0pknkAANioMjEBPpZjhh4qkhD/ynEMxyKOGzgAAGADSAXY49brkYf1aKaK5suiStK3BepXqWNrZq7Uk3iky++z4xeqMWSOP736C70+eRld/MLP5kr7pZxK7Ev9Ioxai9sMd37b1/8KlzS4cvK2UgEetJsZEO3onpXQCfrER8fTJS9Opoe/nGeuAABAZ8nEBLgvx1w9VFOed+SQ9cBvc0iDrN05AABgA/i9brp8v2G006BiOnnn+FTnZBUenYDkhhwde1vgnN76y+JKNSUaMsd3c2Wrfi28nmtiU06B9vrNIEmK/XttrnYmwJ6spBd6Wq0A70gxt+zIqBNguwIs39PLKhvU+J+fzVFHAADoPJmYAEtJwv685OVX+Uv5tTojkjlXzb8cDAAAbXYJJ8CvXLAr9S1svhlQtU//ys1vXKOOrXFW9+rC0XUVYej6krsg1wTXr0dlu5pJtVABbvMWSIYnO6kCbLo8N8uXTY158po8Uamrct0a4DW1WN8OALApZWICLPOJDtdDOoljAod+qZVIFqTJ/sAAANAJGgK6Atct2rZfvcnrO39ejF/ZmaAhHKVDHvjGnGnOKcHtkXINcHNaqtK2MwH2JSfArVWAmWXWDedScF0CvKo6qI4AALBpZGIC/CjHZRwyz+pEjsc5bFIRdq4PBgCAjSiapTvnFlpVUgJU45YEk6a3TlqIBDgTvD55qanmWzTGNYcKqG79E2D+HglaemrxBmnnFGhfblIC7PaYQfNcJgHOczUgAQYASBOZmAA/wnEKx/Mcsv/BMxw2maf3tB4CAMDGFsvRU1B9riiF6zkJbkVyde+nRUiAM0F1g07+jvd8RW8EbqRn/XdS9QZMgY5Q68lnq9pZAQ7kdDOjtvOYxln51EA/L6pU41U1IXW0YXskAIDOlYkJsHiJ41KO59RZ3HkcydcAAGAjcefGt1+vKW99W6PkBkfSLGhFlb2KBboqr+kYfo/vMXUc7Z5PtfX1atxe8j2SRR2wjrbdTbCSKsBt4DXTpvOonv7381KatLCcVlUlVoBXOyrCD30xV00Vn7my2lwBAICOlqkJMAAApAFvfrwLb11F61sh2Q2OxgwoVEeBKnDXl6raG6qON0aT29va8TscCpHX1Y51wPnx/agTtLBHcEpJ+wC3ib0G2KWT3I9nrGoyBXq1qQhLk7B7PppFv62opvOf/Uld25SmLq1S+3K/NGFxkwZmAABdGRJgAADYaAIF8WmmDZVtT4B3GFhEfo/+E4UEuOsrr2tasY1U6++HacuqaIdbP6WjH/6OYrHWE61oOGlGwBlvmUEzTnqeqGQo0ZD9zAUm2xPlFJuTNgrkmUE7mAS4wKUf8xczVzeZAm0nwEHH9P9Fa9evOt5R5P/hlMfH07+/mkfXvD6Vxs8vN7cAAHR9SIABAGCjyS6MV4DD1WVmFPfY1/Po2Ee+p3lltdQYjfET7yiNds2lIl+URvTV00eRAHd9FfVhfsKRWLW1avX3w3VvTKUw/99PW1ZNSypaT/wiofh9wgfdTTR4b3PWjL7bE13yE9H+N5oLTNb/uvS07DYLtH8KtJ0A+yhCfmqkOatraepSvRbYtsYkwFUN67cmemOQZnQ1jrXJ9r7FAACZAAkwAABsNPkl8emn0dqmewHf8f5MleBe8OxPqvp7lfdleivwVzpw3m20/UDdQXr68mqqD6NRUFfjnNJcX1NJX/ivNGeaq14nwM4pwRX1rSeBsXA8Afb4c8yoDXy5ZsDyephBO/jXvwIs8syOjMmfo90Ea32bgm0MUo0+3P0D3eV9jI50f08N+PkDgAySaQmwtIUczhFfPAYAAJtMt4JCClleNbbqEhNgqfjapDIWaozShd531PnQVR/SuB46IYjGLJqypPUO0l2ZfC3e+3WFqoRnAtm/ecwtn9DlL01W5ztUfkwD3avV2OZtkN0K9f+vrSxpenAqzgqwxy+bO7SR35EAt7MBltKGfX+bcCTA/XPjSeQB7kl0n+9h6ktl6xLgtKoAh8L0d98jdJL3S/qn/0EqXD3R3AIA0PVlWgIs85lkn99d1RkAAGxSOQEvVZCeOupuSFxH2MAJr5NUgBssvzkj2qnyAzOSadCZvQbxzcnL6OIXfqZTH/8xISHsqs777yQ1hfbNX5brzycsewAnCoT0CyKRdibACWuAfe2oADurxe3cAklp75Rp4UiA9xiQZUZEj/vvo995vqV7fI+u2w+5qg3V784SbKilgCuesGfVLTEjAICuL9MSYPltLftsYGo3AEAacHHSUO3SCXAgmLgGOBhOTICDnBDPsfqaM6LcxZ/TwBKdtGT6OmC76dHK6iAtWFOnxl3Zmtp406u6cIRqw02T+kBIv6jRaBqfiTYlwI4KMPniSWWrZAq019y/cIA+bmyOBHiXvvrFnVwzFVqM88xotgLcloZgG0s4mPQ9GO7635MAALZMTBRlD+Az9BAAADa1pb6B6tizdgZV1ccTnPqkBFgqwAFyJAHLfqJx/fS0U0mAN2VCsLE59z+esSKz9oBdXR2ifGo6tTs3UkEN/D1Q5/g+WF2TuEVQKgkVYG87pkB7vESH3Uc06iSisRv4NKFbGxNoRwI8uodHFZH7uhKXAtSatb/Ja4CdTag6W2NDYsLrCmfG1HwAAJGJCfAvHOM4Puf4I8exHL9LCgAA6CThPjupYxHV0Huff63GItUU6CxybJcTi9CB+QvUsDoYyZj1sanY2z+JGcszKwFeWlFPxfx/n6wgWqkq3iKLQuSiWJsqwFajcwp0OyrAYsyp/CzgUc6+u5sL7fR7fmqx4++JznjTXGiFP54A51MDje5X2CQBrgvpn4PkCvCmnBIdSaoAuxtRAQaAzJGJCfB/OWQOneyL8E+OVzlec4ScAwBAJ9nvoKPMiBOdFT+akU6AJekpNMmRNMEKuBKf9I9u/NWMiCZl8DTokGMP2EyrAMsWOiWupp+T3wrSiqoG2tq1iCYHzqf/+W+iNTWO5LYZCQlweyrAHaHf9kSH/Z2oZIi50ApHBZhWTqGzxg2i/kkJsF3pTU6AKxua7p3cWSKOTtvCE0ECDACZIxMT4H1aiX05AACgk/h6bUv1pCt1JfXz1FHI9NcnfH+nnwIX0N7uXyiYXAFmRavHU36W7iI9aWHmJsCyD64t8yrADVTsaloB9lthWlEZpDt8T1K2K0xj3XPJW7XY3NqCDakAd7Ysx97B3/+Lju5XS3/d05EUs4agroInJ8Bt2RJqY3F22hbexsRzAICuLBMT4K/aEO0lSfN/OGZyyMugyzje4tieozVfcsjCtebCuRdDc/f9kAMAoGtyu6nWpfdQ9TXGpzE3hCK0n2cyeVwWPe2/myrqwolrgJlr5a+0ez+dAMvWOpnKuQZ4TW2oTWthuwqVAFOKCjCF1RToIa7l5gpRXjA+blbE8bXp7Apwe8nWS2NONydswuPkrV5qTjRPUH9fVzckrvmtrA+rde9zV9d2+vr3hEZjzBdFBRgAMkcmJsD/4thSDzvMhRyDOB7gOJTjMg7ZRX88R2sV5Ys4ZFsmZ+zHIc/y5O2la7XTfI7k+1/OAQDQZQXdupuzNxp/Yh0KJSZ5ZZwMSSVQBHuOUUeyYnRIvvxaJNUdOblRUKZwToEWv61oWjHtSnpQBT3oe4BO8Hyh1wCnrAA3qinQzhc9ekRXJrwYkIrLmQCnewVYHPUgP4PYQ4+nvkq0do4eG1lh3Q27OqkCLOf//HwO7X/fV3T9m9PM1c4RS5oC7Xf83AIAdHWZmABLa0fZC/gTDll4th4b9zVxMYckuo9wSAVZ1hIfwCG7+F/H0RJ5LJLoOqM/h4/jCY5kMrcr+f5SeQYA6LLCbl2p8zmeSIeDiU2t1lbHk6TQgD35L5T8miTaLhJfB/xbhk0PtjmbYImuPg36Xt+/6XDPj3S373FaWV5DhS5dQbT2upom9dUdmGW6+8ry6oR13/1dq1tt/uSOOhPgduwDvCntcLY+BiuJVk7VY6PAqlZJf/KLO7WhKH362yo1/rmT17/HnJ22mS/W+tpsAICuIhMT4D4cl3D05niDYyHHNRzr2fJRWW2OTvLMTZJbSWbb61wOefuX1RkAQIYLe3LV0R+NP5FO7jRbVR1P+tw5xUT9dlDj3hUT1VFMy9AEOJycAHfhRliWZdGenniS56lbYUZErtxSssxevJL4xsria8JFf1cZVSZVQpN5zfdQ1OXhd65fJEl7Wx7GGX83c5KoO1VRbTCi9gOWhmBneD6iHAqqNcEy/Vkkd0zf2KykNb9ZMVSAASBzZGICLM+oHuYYwbE/x08ct3Is4XiaQz+j2nDyl2wsx3R11nbDOGQulOxXnFj+0KS1pMyHksVA8szgdo40X+QEANCyiFmr6XwiHQklJcA18Qqw18/332JPNfat+Y2G5OikZ/qyKnXMNMnTfmcs77qfZzBpOnc/Z9fjnBJyOaYtF9bMMiNtgGs1HXj/1zRpoZ4WnCwasygQ0xXgRvOiSpcgn/OI48xJIumQLcmvxAeBa+kW3zP0Z+8r9NuK6nVfy85PgBOXJ2RZqAADQObIxATYSfYCln1/t+D4nkM6UcgeHBJHcGyIhzjkr68kqO0h1V/xpDk6fctxJYfsXXwkx/scV3FIE6zW/q9kTfK2SdHGfRoAADauiElWnE+ko0kV4IUr40mPN5CzLgEWRxfr/YB/WVqpjpkmeQr0/DV1VB9ObIrUVUgi59TPVWZGLLc7J8Dx13S3oMSGUH3NfU95PL5dlpN8TXJJJ2cRTxeZ/mzb7lQzSFTMCXBNMJKwJv4c74c02dH0LRju3ASYkirA2UiAASCDZHoCLH9lf8/xDodsgfQbx80cHg7Zxf4vHOtDKsryl+wKDqkwt5W0Mj2TQ6rGsrY32Q0css74Cw5JfmUqt0zflmeB8Y00U5NmW9IlwxnSqRoAYJOL+nQC7HwiHU1qtBN2dJ71BvjXd78deaCrhXt55dc3J4ZldapbdKaxE+CAV/9ZtiyiWSu7ZiOsupYS4Jzu5HZUgIe7EhPgIjUxykrYFspJts7KcZkE2NvFEuC+Y4lKt9Jjfz6FA8Vq2J2qqZy/p3OjiZPCqjkptnV2Bdjl3GqKZVsmOV/+C9FX9/B/srRAAQDomjI1AZbK530csl3RvznkL+yBHDIt+hYOmQb9Nw5JMNvrRg5JVK/neFAutIN0kJZtj1I1v2rOc+a4izk2x5727YzWkmYAgE4RMwmwVO9kjahI7jTr3ANYVQm9AaL+O6vzoXU/q6OYvCTztkOy1wCP6hdfJ9pV1wEnV4D7UuIUaLdMbzeGJSXAXleM8lUvSKK1tSF1dKrnBDjPVIBjXaUBls3lItrrKn7m5SMaewbFckvVZZkCPXNlNXVzpVoVpUViFjU286JAc/77w0J6+Mu5637e2iWSlAC7wmRFG4leO4foi9uIfmjv0x8AgPSRiQnwBxyyqEimGv+XQ7ZEkunOn3I4SVW4vY2xJPm9ycQdcqGd5DHJM7xn1Vn7tPaXTxp1SWXZGYndRQAANhXZD5VJ46NwWCc2VlICvFWho8olya/YQm8fk1OzgHq59BTpnzq5I25nsNcAD+2RT9k+maTEv8BXJ04R7yqSK8B9E9YAF5PHH68AD3TpLsdOdiKYquGZJMB2BdgyL6p0KSOOJbp+BdHBd5C/QFYu6SnQ38xZQ4Up24LEtacK/OvSSvrrW9Pp7g9n0QfTkndbbJ3budWUEapYRlRunlZUJb5wAQDQlWRiAizVX5ma3JdD9s9tLgmUKcIyLbqtZLq0JL63ccg06vaSyq9UgGXqdXvmDsmUaZFqyjQAQJdg+fPMiChYZxKbpGmWN+7jeE3SNM2iLfbSR3ZEgf51LtOgM429D3CWz02FObqzcU0X3fO4Lmntsj0FOuQtUF2bPY41wB6XmQ1QPFQdhZ4GzX+kUzQ8a2iMrwG2zIsqXY7pXO22K8BUTT8uKKfCFirAoj3rgJ3bJr3763IzaruEraaMyKIJZsTCmfczCACbj0xMgIdz/Iuj5b8k/NyCQ/b0bYs/ccjUaWlG9R6HTEd2hk0aW8lf/oHqLJEksrIGuLnpz1LmkPd/PofsMSxVa5nWLJVmaeYlFWsAgC7JHXAkwPXVtHBNXZMu0PmNjs6/Zu0v9RlDZCp9u3lk5zmi5VVNn5x3daFolMa6ZlORVUm5AflT0XQqcVch+9c62V2gG7P0mlePrO9O4pb1sYadCKZKgOv4fcsWQcIVyFfHLsskwN1d1WoKfKHaxCLOT4kvgKSqADc3vXl1TXz6uDTYssla47mrm64tl7XVv3v4Ozr5sfHqsXhTJMC0dJIZ8PdrfWZ2YweAzUOmrgG2uTj+yiHV1w1hd4w+mOOHFGGTeWsS8nGTncMhexInT8W2yUaJ8tdNKs2S7L7CsTuHPH6pHLdv8Q8AQBpxJisf/DSX9r73S1q6OmkyTK1jOqzdKEmqZQPHqeGoxinquKIysXLc1UkSc0DsB3o9cBOdPuMCyvfrP81dNQGWFzec3KbKG80uUUe1xVUyeaHDOMfzgUpyp6ZIgGUKdK5LJ3eurloBtuXqGQ8FrnqV7Ba6EhPT5CnR8rm/9+sK+mKmrHgiuu+T2bTdLZ+sO3ey9w8WdjM1SWwPeeBr2v++r+n7eY5p6ezVn5bQz4sr6Yf5a+nNycvIE226/tq7LN6Ze0156m2qAAC6gkxPgOXzk3W7fdTZ+tubQ5La5sJ2FoecS6KbTNYiy3ZMzXWjmMtxGEc/DnnmJ88QRnFIBbjpXyIAgC7EkxWvAL87cY46ZjuaXim1jifydgVYmO2QihtXUj/XaiqrDa1rGpUJpAP01u5FalwUXEzDPXrKaldNgKc1s1WVK0cnwL6sFM2rHBXgfTxT6FLvG7S0oqFJx+9V1UHKNU2yfNldvQIcn/JfRDWcACe+cCDNsZxufHs6XfzCz3TOMxNp6tIq+udnc6iqoZHOfnqiuUfcvLJ4AizV4OWVDbSMY1W1fjpx6hOJ20ytdMyqmLemlnxmr2Unf9lUM+InV0nbJKUTqWZLJXvcnZ/Rne//1uQFGQCATE+AhTNBBQCATcDrSFayY7W0m3sq9edkNkGto1lPQgKsG2GJXd0z1BZBkghlCkmAnR2wR8ZmqmNyM6muYvby1NVBT76e8uuTPZ4dYvJUpNdIc6Zd4NWrfqYnNcKaML9sXQU4Lz/eMbtLMlOghUyDTq74SnMspwkL9NdVvv+f+l7vi52KdItetLaeAvw9ZU8X/2TGKqqoj3+PyfsIOqZUO19QKq8Nkzemv8YrSb9oIdxW/P7+aPomwPd9MktVsmWpxKNfz6djHv4uo14wA4ANtzkkwAAAsIk5q3X3+R6h5/130mnez8wVY9H3ZsCcCXCvUURZOtnZ3S39C4lWZNA6YHly7kyAhzfaCXDTNZ/pTtaYVlSlrgDbXY+TK8A1gV7ruoQ7+SiSMA1apopPmS+rhTSXY115l+RIgHu4Kpo0wSqhGirNN93Qk7z1S/ONrWTNb06slr4OXE7jAxdTL1pL701dQZUqAY5PQvtlSfz/aWl5PV3ieZ1+73mPPpy+krNoneBWeFJvlhGIpWcCLJ/Tk98mvjhQUd+YUS+YAcCGy/QEWH7Ty7wyTCEGANiEfNnxal2pq5kGOjFHxdNeAyzcHqLBshKFaH/3T2oK7IqqzFkHLFsgZbniDY+2aJBd7LpmF+jpy6vWdWlO5jMVYH9SAhzM629GiWSPYGcjLFnXGqp3rJN1dBbvkkrina+H8+faLakJlmwHdVbRVPo+8Ec62ZP4YlE0Fk9kk0ll93DPeOrpqqQCVwOd4f2EJi4sp1kraugZ399UUjzEtUy9WCH+/OoUCs78iP7ke41u8D1Po8OTVfVY5JT0o5jVdCJdlsU/f1JGTiPyQtJVr03hx8vfGh4X/W1Pn0r+xZoUe0oDwOYr0xNgmfMi6271swkAANgk/HmFZtRUo5uT3ewic2Y4K8Bi9CnqINNfD+Mn97KeMVMkT4EuDS3iZKiW6sJRVfXsSqYtq163T28TObqamJwAxwpTbZxANMK9gKZxQm0bP39t4vvu6gmwrAHO0z06ZQ14cgU4nxro6OBb1MdVTqd54v0zC7J0l/DmyPfTIFd8OUFPfnv5Nvpywk+0l+dX6uWqoJf9t1JlfSNFojF67aelNMat1+WLS7xv0GC3fvu+ffqSvKSRzCs9O6Px79l08NR3C2j2qlo17fvLkr/RiROOp08CV9Fg13JOgNPrsQLAppWpCbCfoyeHzLeSMQAAbEJZRb3oreg4WhDrSR97dFMrW10WJwH73mDOmNunq75OQ/dfl0CNc0+nFZXpOaVx8uIKeuKb+VSftBduS2QPYLviZpOERKp8QbM/cFchCWtzFWAyTbD8Sdsg+boP1oNAgT4aI1wL1VpWafQkxs8vpzzn++7qXaBFrxHqsK178br9j21FniD1Cuq9r+2v6dAeeXT0mL5q7OR8oURmFIx267cT23j1tPG6yviae1lzHCtfRJXma+tsl7Kze6ZOcN1e8ux4NlXyVz2lNNsLWF4gEXfkvkR9qn9R43xXA13nfZ7WogIMAA6ZlADLX9Y7OWTxlCxOkQUy8ltfxnLtdo54NwcAAOg0pXkBen2Lm+mEwMNUvNNJ5qpmeTkh2v7seCMks943gcfL70Sa6RP1da1J2ynQxzz8Pd323m908fM/05Lytq2TDEcTK8BirKnIdbVO0NOXVVGOaVLVRK7+E+yS/2+H3F5D9ODU14iGy26D2ki3Xssp06olwVMV4ExLgHtuqw5SpUzu+nzm0HryhPU1+2s6qCSHjt++6ZRxmS1gC4YaaaQrvg52GC3mhDZCxUnbLAUqZqou2xd53qTLvK+bqw77/oVcfcdSjTvxhYl1Qk33E96UpPK9r/tnOjr6sbmi7e+ZTNWVids+pROZnt3SlHYA6HiZkgDLNGfZIPJKDtmC6D6O603IWP4S/IljMofcFwAAOpHL5aKnz96RJl6/P23RL2lnOn+Orvge+x+ioQcQHXCzuSFJN/3EXxLg5WlYAZbuu7YvZpXRgfd/nbC9THNCjVEKONYAi7EunQB3pU7Q1cFGWri2voUKsGmo5HZzuh+fxpvdw6yFHbAz0SkvE+10njrd2rWIPBRV64Bl/e9aTtZyM2kKtOipX/TxUKzJCwf+5RPMSPZG1LcNKM6lEX0LaMueiVtA2VVyEa0rT3hfXquR9nT/qrZaSlBfTuW1QbrK94q54CBr7sddqob1nngCXGPFX7ywwokV600tEC6nv/keMyf8mPe/SY9ZY8UyM0ovH09fSTvc9imd8Z/EbakAYOPKlAT4Xo4KjmEc8vLxVRx3mZDxIRzDOaTl4T0cAADQySQJFtkFxepoc/nMmtBS/jV92mtEY07T58kKB6hDL/51X1aZWC1LB85tZUQDnz/9fapt4RMlrwEW27nn8R/oWJeqAM8wWxblq4lXKTj2vQ05VycVDTIDo/d26iCNwYa6ltHUZdU03mwBVOB83xlUAU4pGF//nKMSYIu26pWvfo7uPDZx2yjd4VkLh5vOjrgw8HGTCrCroYJqK8vMmUNBX6JjHlUvVIiQNz4jY0rMTFdnjQ3p9TN4dPULVGpX0Q/lp3r9dtRjFq12bLGWRs579id1/G7u2iZ7XgPAxpMpCfC+HH/hWKzOUpPbbuTYT50BAMAmkZ2f2PDKk7QvbLMKdQXY7bIoK7iKGhzTPtOBJLzJFpe3vk7SmQBbLv1nOc8VpC1dS7pUAmx3bB7uXqqOCXycrPri1cNGl06A61x8PbkBWu/RZqDXAb8zZTn95U29/dVegVnqSB5+e/P90KV1H6Y/l1Z4XTHyU4RG9dfJ6NgBRfTiH3ZRY+GsAEdC8QQ4kqVfbNrR+lXtoe3kCVVQg2NdsCKV34vGE+Xr5lwi7I8nwL9Y8c7Vobr0mgLdJ6K/75b5OUkfdSL/EEkrGM3t3GO8E0gy21oDu+TfX7+tSL8X9QAyVaYkwDKXqi0LwuQ+LbdPBACAjcqVldgR2lXQ24xaYSrAol8argMOhps2rJq5svUk4efFFesS4FBpvLIn64Brg10nAZ5uKsBjfbL7YJKcxKq/Zbp81+dyEmtmBqxTuhX/pda3Sydom1TE93dP0idb7EUUSJwG3CV5fOvWtq/jTv00JZtCNLQ0Pu27Wza/rVHtnALtqABXbHchf331U70DPbraaAuEKylck1QBlp/NrMQ1v5FA/AWK+YGtzYi/V+vTK2HzWXrad4OXH798TzkSYH+w89YAvzl5GY259RP686u/miup2U27bDOQAAN0mkxJgGXxxDUcLc2HktvkPj+oMwAA2DSS1m76iuOJbYvMGmDRz1XGCXB6rQMORppWgOeX1bU4tfHXpZX0+Nfz1+0D7O0zimJSLWUy/beuHd2kNzVdAbZoW0cDpnWqlpiBVtxdVxi7D9JdkBNIwzMzNdhuhCW2c82lblFZ7cS2PlwfM4FZB7xOM9tCyTRoryf+tK3Hqq/pH74HaZBrhdrSyBYJOaaJS3K95aHmJFFWpIoiNUmJ4c4XmEHc4tK9qdzKo4+j21NB//j/V6NzT+Y04LP0z1nUHVBHeYEkLFussexQiqneG8nlL+sO1P/7OcVMCIfPZyZW35EAA3SeTEmAZZ3vWI75HA9xyG/wEziON2O5NpdjDMfVHAAAsKmYtYU2X0kbexN268fpla4WSgU43fYCbm5K9hROclORKZJXvfYrRWLWugqwN5BLlqmQ51EDVXeRCrBs+zSvrFa9MJEXM4nRvrIyyXBMaxauA29V01RdezXzJ9msA97GtUhVfsVNw+VPvODvgWaSui4peR1wUeoE+KaDB3F2F/9+6P7WqXS053t6xPdAYhOscPyFIa+fE8BdLzZniXKi/P9U50iAj3+aaOCu5iQuXLI17RD6N53X+CfaZlC8gV3vLy5Pq62Q/KYCHPOYPcRdLqr36c7j3aLlG9RpWV7c+cN/J9E3c9qWSEvztpbIz35yAjxzRXq9oACQyTIlAf6ZYyeOrzjO4niY4yWOl81Yrsltch/pBA0AAGnC3cwT/ia8Ac4KdeVQbYWUZp2gU60BFlOWxJsZOa2uCa2bIp3jNgmMN4vcAV0hz3EFqYzv0xX8xk/eJb8Y5bKTVDZoD91MSba3cnTkVf6/vfsAj6O6+gZ+Zrt6seXebWzjQjGm924g1ARCC0mAJJQQICQkAZKQwJveCQR4IUAIH28gEDqE3jEdbMDG2Lh3W71t/86Ze0dzd7Wqllar1f/3PIe5M5KltVmt9sy599zJBxGdcqtqfJaJTpilm7FsESSV5WnbX7Sv0fi9+Xkg2/znCb0XcBtjqr/p6BePJ/r9DKJtn3GW5z7XdvasSVkrnoi6Pxd+WV8/gZPatBsQojTZQGFzCrSxBZXpkBkjKBTw035Th9GksWnLFT5L3XJoIAV0BTghrxNaOFRlH0dYtSnTxHvqjP9dSM98spm+crvbmbsjh3vepcXB8+39hyOxzPt4S1dzuYE3gmroL/4b6CTPq7S2pnvbpgHAjsuXBFhIZwyp+srilZkc++uQsVyTjSd19wwAAMgZPWhmZFWo5EBNgc6xCnAHCfAHa/W03TQbdAVbKpyyVY3NX0CW7m5cRGHalKP7HaeTvXpF25RlWXcqie+u/Kv3gleJpkqvyh4YoyrAQhphTbfWUWGj7nOZT9OfxUgzAbb4Hcs4Pc6geRvRfy4gakqtRDYYMwUSRgXYHyywK6G0T/sqcLnFCXCdqkK2WiH7uZfJ3HFl9N6Pj6R7zt+bCguL6JuRy/VHiJIP8ddd8bw+GzhSUQ3qWRRtFWAWK1I3SqqolqqNTtk9Zf77dkYex+2B39s3br7pe7zDbcyc6u+v/P9LJ3jfoD8FbqLW1taUSj4A9J98SoAd8g5kGYes9ZWQcedzUQAAYOAUqSpNtzh7AdM22pBra4A7nAJdl7EjrLNHsPPG3SbNn3QCLBXgXFvn3BGnA/RuPr3tkzSykv2de6tq57buyJJUH+152x7bZh6nB3lCtofSMxsoVEZUYDSJs7x6YFj/Dj95VFdsh5mgJWPuTZNASP8/mH1yW2XZ6TReQY1UobdGCgfSOnGnCfm9nEdbVBT00dOJ+dSYVEmmFW0iupu/tjE1eyBE45IAq+TRabAmkroRVpVVm7JVVG84U/E7quoKcy22MCvz2xrDdMNzn9GnmxrsBNhHMTrMq9YLi+nWWlpbjSowQDbkYwKcThaAyGZwaiEIAAAMOGedqy29C3Bn9Jv40dZ22lzTaI9zhVkBnjaimL5/tOruW90U4Te27Su5TgKfsgewVOF0k7AiarWrxJIox+Idv+nOBSu2ylrQJM11GmDpNby95uPkd8Qse7jA+xZ9M6in2o6YTVTp7kWbN5xp0IX8ViVodGFOnx7teOJ7eqC0tLqJU9KYAm35dTIo/55fe5zotLvb1l0XWBE6ukJtD1RS6XZM7kxRQBJyi9Yn3T2dbQ0b9WBghGNx9+fISIC9ejunUquFaut632TqBM9rtDh4Hn3L+yhtb+p4WcLmhtQbVk2t7vkPH1hMv39mGX3l9jfpndU17bal2sXzOa2rGRwzPgAGu3xKgK/ikFvP0uzqfLnAruCQxUMLOeRV/pccAAAwwKyvPEg09XCiM6RdQw/o6dKyL2q8fmDfdKdrjbpJqkwXlTWTjg8yNMLaqKdAl/qM6plZAeYEWBLLfX75HH39TqMCmoNkqqfdACupb0oYU5h7Ta9bHWttp5KETl52P0sd881+lxANn0G0/3dSt3caJ61LMqhJ7bTtbTamRMeMJMxIBu2bR7NO4Cec28iquF7eMvGbQalCd0Op3nppQzK1ppCoTe3ynW3haNxO6G3G3zlY4f5dW2vW61HP/SVwIxVZYfqR/17aUt9xArypJrUpWEuDm3Q/u2SzfZS1/9KQ6ziPvDV1zbUkAUYFGCAb8iUBlt+I13PIu6ElHNL1+Vscv+a4neM8jns5pFv0GRwAADCQxu5BJEnwjGP0hW4yGgRVRjZSfWvurJkzK8BFm9+hWcnl5Peq6vaHazMkwLoCPL7EqIDbFWC9BpjfcDte+WybXUnOVa38d2+r/oodrQCLlLWxTM73vlCf5JkphxB9+y2iPb5GpKuWton76YE268S2qeGmQIvRzTlmJGhmAuyQDtoT+Oua06vH76MHnZOp0H/68m60ncr0FaVhi9H8bACEw0bl1FjLHKp0E+BYnap276jOGtM1bEtNslub1dIAZ7mDw08xWuBNvaklU/0xBRogO/IlAZbuDpLgSv/+4zmkQ8OfOG7huIjjTo5zOO7n+AYHAAAMRmVuApxrnaAlCRTTrHVUfM9xFLxrAR08Qj2+DzIkwBt0g6uxxUYCbFeAdRdoSv27OY2mcpEk/zKF0+Y0wNpR6d2QpZFW2hZaeWnM7kSHXk102DX8ZDpCX9SmH0O0/6X6xFUQMSrAxhTojAmwVHvPfZLo6o1EF7xGdN4zRAdcpj/YtZN2H0tji1LXtDdvWa1HAyPa4lZeLSMBLqhwu1Yn6vsmAa6uqdYjxdxeKVydWgkPN6kK8Durq8miBM2yVtnJ7/6ej6jc0o9Zpr2zadYGeuDdNfTJBuwHDNDf8uU3iSy0ukcNbfdxSB/8R+0zl1xvvxcAAAAMDmVj9UCtA3aSyFzg7AN8lk93xU3E6PSQ9GJUTaKiaet4neR9jCr4KvLmXW+DVGy12m+aHR/n8BvjZv67z3EqwDvaAMuRngDrBmh5T9bEH3wl0UHfb5sN0EbWPx/w3Xb/NoXh7XrEfzxuJsDulkDtyMdkjfH4vYi8ampzd60rm69HSrRad+geIFGjAuxx1j0zq8RNgL1NagryjmrZvk6P+E3l22tp7rX/pTte08/9OvdjItqifmal8dUF3sfoieBVdIP/BvqCV09/lhsU+33HHsoU7rLIFjr3zrfbVYwBoG/lSwIst/vMhRfOnhOpu4wTyRwh9c4CAAAGH04I4iHVsXacta1tK6FcIFXQC72P0Ne9T+krbnU3HEvYb4Id0tRqi26YM8rMFe0KsJv0nLX7cKosUlNeczkBbo3G3C2Q+mL6s0jfHqsH22XlDU9aF2hJgOXmwlkPEM2TiW1KcczdasuKqym6UfK1//N95PWyY+kfsSP1GX+b+t6vr+0LKQlwwK0AU+Fwiuu3uk3V6+lOTlTfXZ1awe2pWJ20llGufGCRffPnZ4+qhla+ptS+BNEW9TMvHaB/4Ff9DmTq81Ged+wx7cT/hmPnqTGb5tlAm+pb6by73u5wCyUA2HH5kgDL3B+3LED2LXOZ/pyeAEubw/bz0AAAYNDw6OrXGGt7Tk2BbonE2t7kOsZa7tRUcxr05oYwOTMnRxQY00mNNcDi+mOn0G7jVcfsj/VWQ7lGKtsjE1vcKZ190QBLmM2gRFkn++MOFU6zqqrpRCfcQDGPqvAGEs1tncI9TgJs9ayq2xPFhYX0k9jX6Zn4HvZ5oMlNCjsU5mQwkXmrsB0VC7s1kJQE2OOhOo+6YTa8eSU9/tiDdPHfHqNFGZrSdSZmvF1u5UTasbe1hO71X0+HeNR2Rv7WtOnROgFurjPWaLNSS6/1le2ppPmZdtoklcjLza4r7vvQHgNA38uXBHgxxwFqaJN3E9IpI3UuCpG0U5QmWQAAMEhZuhI4RirAOTQFOh5p/1hKGldRSchnj801vJuMx10VMqZGG2uAbZFGmj1GbYuzcntTTlaF+qUBViZDZQp0Z9K2DIt61fSBYmrh54ZKLr1tCXAn05930AWHTKVSfl6v192gS8Mb+Z1X6rrgFJs/JvodJ+23HtIvewbHjAqw10yAma9UNRU70vsu3R/8Ob0SvIw++rBnXdXryL0Z07R9XdtewP8KXkf7ej+hOwO/sc/9YbcSL5KS9LPRte/axxQ+fpw7Hc3/80YQBVVTsWPK19LB09W+6E99vAldoQH6Sb4kwFdz/EsNOyXvIu5QQwAAGJR0JdCuAOfQvpnJcPt9ia3tK2hkiUpE6lrcjtUbjMr12GpjO5QifvNrrvuMNLUlwJJfLNmYe9OgzQZYCXlb0RcNsDIJpXYeHnJKzYluSszvrBdvoYawen55E04C3L5bdF8ZW15Ab119BFn6ZzGU4ESttZMZCs9fzw+IP2fTIo6+r2zGI26i6A2mrj8v3Sm1k7bfilNg5XP6rHvCSXUTSwxLVNPi9XX23sPpCqKpleVkq06Amz+1jymmc/Ir6/3lpsaEve1Lnk/+Qz8Z7/77LNmo/jwA9K18SYDl1eIlNeyUbI10lxoCAMCgpN90S5OohrSphQMpwclqO+E6muhTVSGnQic26grwSKqm8mX/tsc0fQFRycgMCbCb+OXiOmBp/jXbkm34iRpKpvLj74MGWI6Tb1XHXU5vV/0cMr7+pFrv+9X0vp6cYDkJMLVQo54d4Imr7bLinv5LgIVsiRQrNaalpzWAShExbg519nm9ZM6+8AdTK8B0FCffZ/yL6Mv3UINH3UwqrunZZEDp3OyYYG2hN1dup+117W94FcXTbgLo14RSs0u3Q6Y/O475jbSstodTFl5Nu1pqf+ZcvOEFkA/yJQEGAIChwlgLKs13kp1NvcymTAkw24VU9ac54r6JdirAPwze39a0iA6QHfxYyhToJhpXUWBPNxW5uBWSVIArLVWpChe5+672iV2/THTlSk6Eb9YXhiDZC/iEG4iGTdUXXEmjY3hDq3p++ZLq+eSsD+5P3gq3G3WyLnULoBQFlXrAtn2mB33HTIB9aRVgkq7QMxYQ7fwFqind2b40MbqC6pq7t4e4bHNkJsB7e5bQ2yu2Uv2mFfqKIp9XkkhNWLds28b/X6JUmUhrvOUvItrpKH3CKicTnXoXyd7M8npwe/CPNIJqaOkmJMAA/QEJMAAADC7GWtARiS1U3aQqXgNBktqL73mPzrh1IW3ebqz/GzaN38yqX7Fz4kvtY2NaBbiIWugE6xV1YeYXiCbso8YpFeBGsiyLZulp0LlaAS4glXQl5Y19Xyvk5GmoVn+7ohuF2RVgnQD79RToeBYS4OAwNwFu2mKsA0+XcBPI/kiAk1GzAtzJDAQ9PV/23H1/ZWrH5o5Ik7eAkQBLA6vw6repaZOq0jqkq3uFvhHk8Maa6Ozb3qQRVuraYJr7xfYzJaYcTLTgV/ZwOCe/fwv8iZbm8N7fAIMZEmAAABhcjAqwNMLaOIB7Zj6+aCM9vngjvfH5doq1GlMij/8z0Tjpu0g0PfyxfTQrwPKYx1lbyevs82tOh0xLgIUzDXrZ5oa2Bjy5QirAhZZKuqy+nP4MXfKG1I0RuZni3AjyJdQx4e3/BLi8ahxFkmqrpZatq+1jJskmY6nCiueIHr6Y6OXfdThroidiLfVktbgJpj/Y8U2Yqp3U/sWyDvizjzI0pspAtjALUGq1eM/4B7R+Zeo06o3baqmCUhPgImqlD9fV0UidAG+ccALRmfdzovtr+7ydvb5BNO+r9nAPz2c0vr57jxEAegYJMAAADC5FIyih1zdKI6z1A7gXsFl9LvcalWg/J4K6sc3Y8HI7QTHXAMsUaEmA2+itnWxBldTYdGMhpxFWNJ6kz7bkVmMc6QJdyG/0hdVJ8gF9L1ikboxIEyzZP1aWA/iS6nmY9PV/AjyqvJA2JdX05nhNhinQT11F9IdZZK01Gr018fP+/X8SPX+dOu6AhprN1PzrnWn/T3+prxAFCjq+CVMwwd1zt2HVe3rUuWg0Sj4r9abTAd7FVLc+tZJds2kVea3U5RhTSuJ28lxpqRtZyWFTiKYf1b7665CZDkdcSzHdwOxker5teysA6DtIgAEAYHDxeChRotaajpUK8AAmwM62RPK+9cZTZ9pjm1RxJ+xrD/nR0m6e5W0VYKngbmsM24+9jbnFT6icv6CqqpGunOVyI6xmYwq0x6xeQ7/zF+qmTtRKmzkBlv8XQadaKVtq9bPRZQW0Pqm27fE0uPvj2mKciC+8kag+9XpLyWT+r57SXt3JtOluWPr4X6mUUptRBdKbYJmGTaOonhpe0fCpffOmK9Fo+xkmu1vLaUZ8mT5TmjarTuimPVteoVtGu83LSqu6sZVXYSWtqTrEHh7sWZRy4wwA+gYSYAAAGHS8FeqNpL0V0gBOgW7QCXBxwEeeqDGdUyrA41UFWMy3ltnJSSKRtBMV0ZYAewP8BUaqseAE394OSTRtsQ9Tq4oo4FW/spdvad99diC1trZSwFJv0n0hJMBZFVBrgAusCG2uVftEB0lVgK0sJMBVJUHaSGov4FDzBvvYJkNTrD/HTqZHDnrEveFjTF3ujXi4/RRqT2fT8D1eqivZyR7O9qxK2ZqsI9GwurkjNlepLZWkIryXJ3Vro23r3DXBiSL35/nQGt3lnRUP70YCzFpKJ9nHMmqixrAxswQA+gQSYAAAGHQs/QZaksgNA5gAO42HiqVLs+xz6pBKqDRvGj7dPt3Do6pFp9+6kM74XzUdtG0KtKxplqTX1JYAqyTZx8mvJBtia4P7hjwXmGufvborMWSJboIl6uuq7RsyQUsldZ5A/yfAXo9FdQGV7BVH+LkaNxLKGrU1lqk6WUortnLSWlCuLrSkdUfuIem8bEpIZVluKHWisWK2fdzZWkO1TV3/LMUj7uvLthH7Udzj12epktvchNhz2p2qD0CV6jrdpmSUHnTOo/e89lhJam5AIyyAvoYEGAAABh/dCGsE1dLWmnr61ZNLObl8I+vJobP3anGQE2CzoY8zFVhXged5PiMvxemtVdW0rkZN2W6rAJvTnx3FOgFuVBVgMVwnwDJ9OpfEjCqcrwAJcFYZNxwa62vsGzIhXQH2+DuZCtyHWgrVcgSZ6k/1RhW4tn1TrJpkCb23uoa2JdTjTjbvWAKc/uejFv+MdNExPFE5xT6WWC3UWNf1949G3J+3JCem8XHuzA7TUfSWfYzK+t3RuxHt8TWiC15VDa8KhxONmccvWCr57oqnwF3y0NKwY/9GANAeEmAAABh8dAIsFZItG1bRzS+toIWfV9N1j31iX8+WtgTYrADL+l2nCqXXAcs+rTOt1CmhbQlweYYEuGiEOm54j+j3OxM99SOqKs7NCnC81U2AO+vAC/3AqABHmuuptiVqrwcWnpD7sf6UKBmrR6xunR6wmvYJcDWV0DucAL+xUTV2aqo1GsF1w9aNa2jhH8+gtx+7zT73t6T++YaCrveh9hdzMqo113X9/eNR9+fN4p/rwPQj9Fmq8R71tbaP4J95Zxq2l18X9rmA6PvLic5/Tp13g183NxPhJlSAAfoaEmAAABh8jK2QquLum9iP1mf3zWKDMwXarABL9depQjl7+7I9jDWDsk6zytLNrMonqqOpyH2TTg0biBbeRGML1TrbnEuAw8YU6BAqwFml1wCLomQLrdpc0zYF2tkiqb95K9wO5klz3W+GCvDnidH2sTapnife1gxrgD9/keiTh/VJqtX3fIf2qXuC9nznCkrEYlQY2a4/okSGd11hDZbq2RUsXK9vQnUiZjTB8vhDRDufIAN9pb3Q7GP1yCCvB+nLHDrhL6rQI6JoU60eAUBfQQIMAACDj7FtkOwF7Ohi9mOfcyrAJVIBNhNgR+UUigbVNjFzLHdNZMoWSBmnQOsKsGGmRyUX1c0RiubQ1iiRFqMplzT/guwxKsCyFdKbS9foM0mispMAF1S5N3BatxrrfjOsAZbPvevcvajFpyqcwXgDUcJ4LktX6H+cSHTfOZwIv6QvuuY3vqBH/KnbNlJZPHV6cNnkPfSoY4Vl7s2lWJNKoOuao3TazW/Qd+59v922Q3FjCrTHHyQaNpXokneITr6F6k69X3/EVb7r8XrUe8EivUaaxZp3rFEYALSHBBgAAAafUnfapXSCdlhZzIBlC5Xtej2uXQF2pkCbSSA/nmihSmbLLHeqcMoWSBmnQLtVKseU+Ar7mEzym39j/+GBtHp7E72+xE26UpJ/6H9GlbecGmnx524F1m+sI+1PVZWVVJdUz/mWamPLo7Qp0NuSpXT07FF08PQqigV0kyfiJ3OrUeFcaSS9i/6lB67mpFoGIFZ8vpyGU+qMj6Kxs/SoY4Vl7s9WvEkl0He8vtJen//Ihxvoyn8votpm9+crblaAnb2VKyYR7Xo6+Sfsqc61dcFp/INuTAnvpYJitwIcb8mtbc8A8gESYAAAGHwChdTsU1WSsUY11ZOl/LclEqeTb3qdaprVdNPioF8WYdrjtvV/jqBKUkrI7RKdmgC71ew2nvZrBce0fKZHuTMN+pEPNrTtAWxDBTi7jKUAMqugmNw9sYPF2UmAR5WF2qY0R5p0tTLc0K7D8/ei36LyQjV1OBJwK5wpWyGZXaQ9ei9sQ6s0udLeeudNKrTSfg7GzteDjnmK1IwMm36M762p5TfECfJTjB58fz2df9c7lJQ7TSxhrAH2BdzvL0IFqeusa8cdpkc7pqDE/fdJtmANMEBfQwIMAACDUmNIbSky1tpO53kfpz/7/0qlSbfK2p/ueXM1LdmoKjO7WstpSmw5v6vXU4H9qVVQSzcjkimqjrYp0NIwqyRD455pR/C7a05gZI1nxWT7UmWDu4Y4VxLgzQ2tVKSbLtlQAc4umQKtZwtMtLbw/wv3OZatCvBoToDrSd34iDfraq5R/f1L7CQ6J/IDejGxOyfAqjlcLORWOFMSYHMrMVlnK021jCnSYXIT0EO33atHnCTufDzRuf/lfwu1J3GnQm5yuWzlWvrnwtW0be0y+iD4DXokcA3NtNbQXuvuoI+WqRtO8ZhbDfbKFGiDx+dLqUqX7bbj05+Fr9C4QRBGBRigryEBBgCAQam5QDXUmev5nH7sv4dO9L5O57beZV/rb/KmWezr+ZgeDv6Ezv7wK0SrXrGvpSeBTjOijBVgmcqdqTOs7CF86SKi735MNH2BulTzKflIrTnOla2QJBFPqcKhApx9Mh2XTfZuTbnJYhnrg/uT7E9dz6m3rcVJgN31v8/F59HLiV3tcYVOgJNGEkrmVkbGtl/0zu1Ef5xN9MB5+gLngh53b+M5HvU9agsmkPWlO1MaznWKf94aLfV4y61Guuahj+iY6DNUyv92O3vW0FPBH9KV/vso8NA37c9JGhXg9ARYtFjqMW2nMho3e397vMP4NSSm36JbkQb7CAB9BwkwAAAMSrGgehNdyW9iHbvGPtSj/iPrA1dtV8nsjLStjWzpCXChqsSZyUmnWyA5CvjvJ1XgUXPtUysepqmW2mc1HMuNJljbGiOpU6DTp39D/9MJ8DT/NioxKsBmg6z+5Pd6qMWjvpc/ysmarJmtWWmfi7VJt6FbZZHeHqzAmIZsrgFu3KwHho8f5B929RzzJdUNIJN16A8y30TqRD2pKduSAIsJlpF4azNa3qc17z9LCf29hVe6QKfZ7BlpHz8qPYisDNO2e8WyqFlX1b1IgAH6HBJgAAAYnLzt34zyO0d97D/LNrsJd8r03wn7ERUOt5vjmNwKsDkFWifAmTpApxu9ix4QzbJU5TmSIwmwXQFOWQOMKdBZpxPgitiWtoTOlqUEWLT61PcaEV5F9NtpRE9fY583JYP23r+OnUaqxDNQaDw2Z+mAaNikB2k2LrIPhUljijRb759IZfPP0GfdV6sT4ApqpAcu3JeOrUrdTsnR+PQvUhJgf9oaYLH5iD/T3eUX0siTf6mv9I0Wj/pZ8slNBQDoU0iAAQBgcPIX6IErkYUE+NPN7hvSEl3VjXkCROc+SXTlCqKZx9nX2ugmWCErajfZkRhJet1jpgZY6YbP4CxaVc5m62mfubANkjQJkgS4wJkC7eXkoIeVOOgDeo24RUna07vcHtuCKsnLhohOgG1GxVJVf9XPpDRoLw2pJljBQrd7dWL9+0T3nEr07M8omWHvYNu6t+1DegK8ZY/L+Z1sz6uulcPUuulDvB/SHv85hPw1usGc7PH7zRfpjQo+slkt75JnzRv2WPgC7W+6HbrffvSVy35FMyd342ZWDzgJcCBm3CAAgD6BBBgAAAYlK8N0xITu3NqfPjMSYFk3KKzOkg1jq5r/F7ie/uH/FXks/Tg7mwLt8HHyWzXTHs7OoQpwUyRO4WiUzvQ+ry5g+vPAmLgv/0clmcd53GSNAtlLgKPSrC2DtUl3y6FKvf5XhIrcz/e8/w/+oXqa6NU/kFVrbKll4gRYujHLTSTHxzSVZh/+FX3WM6NGud2zSZLupP55mnUi0ZjdaeJJP6VIUt3M2b/mIfso0rtA96eIT/3/80eRAAP0NSTAAAAwKHkyVGMS/Z//0qJ1aluSXcaV0Qk7qzfyzjTnjIypqHt6ltG+3k/0GevOFGihp0HPsivASYrkQAV4W0OYvuh9mUotXZWT9cqQfZVTiGYcaw+9FLePSUl++2o9ajfE9b6+6dYZCfC4CnfGRklBiFqTqhrcLeveoeYGt1v0q/HZtPWU+yng7+WMA5mlIVuNyfTxGTyunEo05dC22RtjJk6j94Z9wR6b/IH2s076Szyk1kmXxbe3bckEAH0DCXD3yMZuf+dYyiF7bMhO7w9z7MHRla9xyCtXplB7eKSSxWMfcMjCMul28ieO7N3GBQAYJKwMU6D7+33im59vpw/WqqY9+0wZxi/Oeg1wZ+stO/tYd6ZAi1Gqi24ZJ5uyfjgXEuCtjWHayZJfh9qhV+sBZN1+l+iBkq0O0I5kMHMCbDbAuu6kOXrECXDIx2+m0m5gTdyf1lcdqE/S1K2h1s3L9AmRb/cz6JBdOGntrTmnEP1wLdGlHxKd8f+IvvMe0TkPpSyrKN/vHD1y+YPZqwBHSyfaxzG0lWobjeZmALDDkAB3z4Uc0mXizxxym/VSDnlVX8jR3V3Pv84h85TMSO+6cBaHbGwni12O4fgZhyTQD3IAAIDBm6EaIxXgWD8mh398Vr0JD/o8dP4Bk4nCejq0XuebUWcfKzOmYnZGd4IWs61VOTEFejsnwFWWuhkQKea/xy6n2WMYALIF0FjjnnwWpz/bOthzeA0nwDedNY9eufJQ2mWcu/VRaYGfmpNpCfBOR9ITc/9Cl0S+rS+kslboqfbMW9DJz1R3dTFlv6RSbbNmsmSde7YMm2IfAlactq5fYY8BoG8gAe6eizkk0f0bx0sc/+Y4kkMS2Ks4uuMjDkmYzXAXs8jMJaLfcjzN8Q2OFzhu4biIQ76XJMQAAKBlSoCTZFFzVE0D7Wuvr9hGCz9Xe5Z+ZZ+JNKKU38CH6+3zThOOjqpxxaOIfN18Qz3KrZ7NtNbkxhrgcJyqSCXAyWK1FQwMEOkwZVaBs1wB9hRU6FEqWQM8a3Qpja9MTTYzVoCHTaPtTRF6MbGbvpAquEbefim+QmMf4X5SXO5Wr9voZnTZUDBymh4RNW7UTboAoE8gAe6e9hvE8esRhyzk6qu2f7KDu9xuvMM+c93PId/rZPsMAABsmRJgH8WomROzviZr8P74jKr+Fvi99K2D9fRLZwuXTqdAd1Ct6u70ZyFfv3CYPZSqay50gW6NxWm4pW8AFGVIFiC7Zh7Pzyk1bZaK3LW32eAvypyQrqcRNKa8/c9pcdBHzZR280cS4MYwNVAhHRL+PT0W34eujp5LnyTU36l4y3v2UQSL+n+9eUlZJcWS7tvkmNQpPNl721w2doYe8cvMVqO7NwDsMCTAvSevvvM4PrbPuvYYh7wrk/KBTGl2b+crzrna7M4lVWJZe5z++QAAQ5ov2H4KY6EVpuZITJ/1nffW1NLbq1QTnnP2nUhVJfrNe9sU6E4S4I4aZHWnA7RJJ8AVVkNOVIBbIvG2KdBUggR4wMkWVF+8jWj2KUSH/EBfzA5fsXpumt5KzKCysgoK+Nq/1Qz5vdScTEuAKyZRdVPEHq5KjqZvR79D98SPoPcTbiXUEewg4e5LHq+H6i13X+tWq30i35+GjZ5MkaRqZGbVqO3PAKBvIAHuvRs55JXxf+yzjsmu7vI553McyvFjjj05ZAq06mqiOL891Py6VHKt/W+XVPLuY3Za7ECHCACA3OYPtn9DWkCSAPd9Bfjzre5WJKftaSSubQlwL6ZAd7cDtEMnwJXUmBNNsCLhMA3jZFz4SjL1dISsG78X0al3pK4HzoJA2Si6I3Y0vZ2YTvNb/0b7tt5AZ0aupglpU58dIR8nwMYU6Ji/mGoiXnsKdLoPkqlvZaR7dLBK2rL0vwbLvXlV68/uTR6vz0ebPep7BhqlJyoA9BUkwL1zHYc0rLqc41250ImnOK7hkArwyxySOEubQ+lV+nOOdB31MO2qt6msFZZ1xmZIp2oAgLyUqQJcRK3UHO77CrCZcMr0TVs8yu/cnS7QnTTlkc6yoQwVq55MgRY5VgG2mrfqEb+ZKMUa4KFM1vT+LPZVOjVyLW2jMtpIwyhGPhpfmblqGvR7UtYArw0X0SG/e5GWb2m/5+17iZ30SPmQE+LhZdlZ49zsdX+uG4PZv8nT5FHfPxDVSw0AoE8gAe65n3JIQiv7PfxVLvSCzGV5lUPW/TqcjtCZKr2yGVymyrDpJg6ZJm3GiRwAAHkpEGqfAHutJG2u0dNy+5CZcAa8/KszzG/UV8nLuNZV0yHZqzVdLxPgSkmA4+3viYZjcbrztZX2Vk3Z4GvepkecDKMJ1pBWEsq8p29HFWDpom5WgCVprmuJUmOGm1crkmNoY1LtiSuWWNPsKdTZ0OJzE+DWwvZdoftbi0+9rgRjSIAB+hIS4J6R5PdaHb+QCzvA4jBv4S/WR3evC0VKDTM5pKLbGWnUJeuRzUDffADIW15/WhdZ7YPl6/So76QkwLKm8R8nEt19kr7CepMA93IKdAVxAhxtnyjc9foquvbRT+jLty7sl3XQ6QJhtwJMxVgDPJRJBTiT9O7PDsuyKGwZCXCy46ZWw4qC9Jvol/UZv7kJZW96d5TcxD5eMkaPsifsU/8uhYkGSsYitPyhX9LmD/5rXwOA3kMC3H2ydlcS3+s5ZH/eHTGZY38OWQfseJNjI4fs+2v6EocsLsNewAAABkumFmfw4YoNdtfmvpSSAEfriNa/o8+0rvZdrdDdeU3d3QPYoRNgvxUnX7T9VNG7Xl+tR0Rb6sN61H+8zhZQItMUbxgyKgszbw/UUQVYRDzux6qTpXTc3NH0pT3a/0wcPKOK/pM4gK6NnkO/iJ5BK8v21h/pf/6k+3Nk9fTntQ/EAqoCXZxopI8f/gNN++BXVPzQORQLt9jXAaB3kAB3zxUcsl5X1vM+ziFTl81w3M4ht93NdzrPcvyEQ0oFspfwpRwyb07enUlS7ZCuLVdyLOCQ/X8P4ZD9gGXv4Wc45HsDAICjgwS4oaGWVm9v1md9I6wTYNlu1bdVdsBL01UFuMCdwmk79U7+M10kzel0AiwKY+2neYf87q/02hZzm/nMPlpfR/v98jm69pHubWaQSKTdVIgab8IDHSc6kP8qigL03SOn01GzUqfCd1QBFgljT11ZDzx3XBn97tRd6fUfHkZlBX4axl/zr2fuTvMmyB7DFt0ZX0C3xo+n4SWZZ370h0BCr/FnwbLsT/OPOwkw/wsVfvaIPZY+B/W17vIDAOg5JMDdc7w+SnL6RoZwyKIUCZne7JCpzTJ35x8cMm9FktznOeZzpE9r/ifHmRySVMvnStItf+4UDgAAMPkyvxGWN4ivLu/bN4hOEyxZ/2ttMRJgaX41fAbRhH31hQ6UGtMn97mYaHYvtnY3EuCCaPsEuCDgrouU/VS78vPHPqENda105+urqK6584RZmhPt9Yvn6Jv/eMetrjsNwIQfCfBQ953Dd6Jbz5lP3ztqur4i05czV4ZFscft+NxCQRpXoW5oyb7Bb151OL119RH0hV3G0G7jU2cXDC/p+Gv2tZU+mbCnJEqyvwY4EZLkX96sJ2lKq3ujqrVJd58HgF5BAtw9Uo2VpLajcMj0ZTk3N2yTTtGyJZHcxpPFJGM5vsKxjCOTezlkeyTZIE9ebaVi3H6uGwDAUNdBAixdkl/r6wRYV4CleQ9t1m9EQ2VEP+CX+4vf7LoCOvM4oqqZqhK837f1xR4yK8DxOj1yFRiNgbZ1IwFeX+NWcBet77xx2C+eWGJ/zac/2dxWXbdiRgW4g/8XMPScf+AU+tUpc+m/lx1kr/XtiJkAy57A4yvcnyFpcuX1qD87Y1RJyl7Cw4vT9g/uR2ULrqFX47Pp77EFNGnn7G4tZSvIvLQg0owEGGBHIAEGAIDBqYOka3/Px/T6iu0UT5+yuwOcKdBBL78pX6Mn/oyYzb9FOens5E1+Gx+/ab+Q/9wVS1OrwT1RqKpBoihDAmx2xt3W2H4/1XRTqmQre+XDtZ0nwGZFeVO9qvx640YFGAkwaPI8PH2vCXbi2pmw133+bU2W0VhdAU7n93po1mi3G3NlJ1XlvnbgLtMpevZDtP+3b+uw03V/8hSmLZ3Qwi1IgAF2BBJgAAAYnDyZf4Ud5nmf6loi9hrXvuJUgA/hr03b9ASe6UerY3fJ45VEuLf8bsLgM5PPDLZ3IwG2t3PSPugiAR5mVN3W6cqxV1eAIxZ/rIP/FwAdeabkZFqbqKJPEhPpscS+VNFBIy1x0E7D9UglxNkiFexDZ4zoMpnvL74i96aXKYYEGGCH4DcWAADkB72udpJnM02xNvbpOmBnDfA58f/YRwqWEc0/V42zxdj2yZton+A2GXuobm/qegq0uefqK59to+qmjpPm8kK3+rW2Wk2B9ukGQREPqr/Qc/FgOR0c+SMdG/kFBUMFbVOeMzn/oCk0aVghjSoN0TFzRumr+S9QnLkCHEUCDLBDkAADAEB+mPdVPVBV4JeXGfvU7qBILE7zraU0N7FEXdjzPKKQOy0zK4xpxr5E+wS3OSKbCSjdqQCbCbBM8b73rTX6rD1zOrmTAHvj6jHEPNlbkwn5Q7qWJ+y3oRaVdjG9WD7+/BWH0Cs/OJTKO6kU55tQmVv5NiXCaA0DsCOQAAMAQH6YdABRxSR7eDgnwG+tqqZ1NX2zHZJMgb7Ip7YhIS8nfPtcqMbZ5A1QUvdd9CUzVIAjbkL7Nv/dD/j187TgTy/T6u1N+moqMwEWd72+KmW/Y5NZXV6r/039ugIcQwUYesFs2lZa0PX6Wo/Hyur051xQWOpWgN+Iz9IjongrEmCAHYEEGAAA8oOX30RPl93qiOZ7PqWSZBM98O56+3xHDW9ZSYd5P1Anu59NVDxCjbPJsjjZVNWvQDLcbl/e5rBbAZaKrqzVXbqpgf724gp9NVVjq0pq7c7WbEtDmJ5YvNEep2syvvYaXQEOJFUCHPciAYaeM5u2lYZ8egSm4uJSejy+FzUlg3Sb5W6dlohkvqkFAN2DBBgAAPKHbkzlt+J0oGcxvbemxj7fURNal+oRy/baX0NcV1uDFG1bl+wwK8AHT6+y10yKxxZtpBZjerSjILyF/ui/kX417WMaXqwS69tfXenu82toDkdprvU5VVEtbeVEORyLU5CTcBFHB2joBTMBLutGBXgoKgn56OLopbRL+DbyTZUdOTUkwAA7BAkwAAAMXsNnqOMIPT1w4v5t3ZKP8r7TaWOnnkjpulxUpQfZF/eqRDVEEXp/jdu5WdbotkZVQnzZETvRXefuRT88ZqZ9LlOd//P++pQkWKY6X0L30cne1+jkVdfRV/ccaV9fvL6O3jO+rmPnlnfo0eA1HFeTNxmzq8sFlvq3Tfoyb18D0Jmg330L2p0p0EORTBOfMbKU4uSlk/cYb1eCbRFMgQbYEUiAAQBg8DrrfqIjfkZ09gPqXLYZmna4PTzR+zrNrnvZHu8op+GTzT9wCV9bBdiK0hn/u5DqWqL2ebNR/S0KqOmk00e6W7dc9Z/FdNwNr1BDq/p8WdN7mPc9eyzOmFivR5n3BP5Gy9/t4yirhiZbG+11xZKEiwQSYOiFkM+tABcHMQU6E9mG6YGL9qOnLjuQFswZTS2W+vn3RPumtwHAUIUEGAAABq+KiUQHXEZUOkZfYIf/hOKWenO9IPJ0xim9PeVs+WMbwAQ4IQ24mJN8vrFCbfUkHaAncWL6UuAyOuzTa+1r6UnF51ub6BdPqKncUhX+POn+mw2rXdy2L/DmeuPvqjUk3WnOVVYtrdrW3PYYCAkw9ILf6257ZE6HhlTyczxzlOo4H9YJsDeKKdAAOwIJMAAA5JfhO9H6in3s4UjaTk1p61+fXLyRrv7PYqpt7v70aGcKtExFtJttDZCkVLiZrAEWb66sto+S0F7nu4MmerbQ1PUPc8a6mYoyVNVkq6PXlm+jhtYY1SXVVHFhrX+PRpSqr50pAa5OFOsR0VhrGz23dDMVWLoqHlBrjQF6IhJ3b0wFdCM26FyrpW42eeMt9hEAegevOAAAkHeixaq6OcKqoWpjT1ypBl94z3t0z5tr6Hv3L9JXu+bTDZ+iA7znbUJ3XHaqry8t22qv/5UO0BOtzfY1W2stFQa8ZLlFtjZX/nuRneQWkZHoLnmEDihYZQ83pSXA0vCqLulWecdZWzmJ3k4F+jEMLy+zjwA9YW655XQih85FPOrn0BfDFGiAHYFXHAAAyDtW6Sj7OMxqoO317vpW2R7I8ewSI2HsQiBH9ryN6wRc1gALmdZ8y8sr7A7QraQaZNmat9vrB531wMJJhtfXttA1D31ERZZRRYq10o/qfk5jaSttqmul99fUtK0XluQ6oCvOYpylpl0XkLopUFDoVocBukturDic6ffQuYhXJcD+BCrAADsCrzgAAJB3/OVj9YioaZu7F3BrNHU6dHfXB/sSKtmLDXAFuCWpEtq29bfsj88so7dXVnM6akzN5gRYSBXYsdv4ctp7cqU9liS4hFLfRJfFa+i2wO9o8/ZqOvmm1+ns29+yr0tyXaSTXSFToC1KUEgn4eTHFGjoObMCjCnQ3RPzqp+16dGlRGvetMcA0HN4xQEAgLwTqhynR5z0VrsJcEtaArylwU3sOuPseRvTU5AHyojKcvsoyeftX51PPo9F0XiSfs9JcEoFuElVac1GWKUhP/36i7tQSG8/U6wrwLHdvkK0z0X2eGfPWlrgedseSzdoe3p1JE6Fljstery1hfYcZyS9A9gUDAavr+8/SY+IjpmrZmxA5+Lm68+D5/MFd2YGAHQfEmAAAMg7xVXj9YjfI9YZCXBaQ6yPN9TpUcdi8QQFdcU1rqcgDpSCAtW4alKZlw7feSRdevhO9rkIJ80KsEqAzUZYxSEfTRpeRN8/Wu0P7KwB9oVKiY64lpKk5kgf511ILwQup8t9/7a3WZItk4qN9cJjrGq6+8uT9RlDBRh6YdqIEnriOwfS81ccTCNKBvbG0mBRXTxNj1jtGqLF/9YnANATSIABACDvFBgVYE+ju9a3XQW4vusKcIQTYKfhU1xvQzRgfCpRcPYlvvCQqVSgt5Dxcgrbpmk7/+WW0BGJV8lHMQpRmEr0dOiv7TeJrjxqGhU7Vd1gCX/dIMUKhtunR3jfp8mezXSp70GqbgrbHaYLzYZZLLjlQz1iqABDL80aU0pTqrCGvLsqDr+cLoxeps/Yqlf0AAB6AgkwAADkn8JhFJUti1hBeKt9FLIG+DDPe3S1759USk12ctcVWasYslQCnBjoPW91AixNq4TP66FhxWrqszlNmVa+RHTLQXRpzS9pYfDb9GHwm3TxyouJwg3k9Vh00X7GlFNJgJmvwr1p4KhpaKb/frwptWGWWHSfHjAkwABZsfe0UVQ274u0NKFmuEQaa+wjAPQMEmAAAMg/lkXNpBIzj7FlSEs4Tn8P/I6+4XuCfu6/w94Ptyt2AqybQCWdBHSg+FMTYFFZpBLglG2NtnxCFNfbFFn1dtfo8U2Lif5zAWfxCTsRbhNUFTir1G0c5li5fhPd/866lCZYtk+f0ANWPlEPAKC/nbDbGKonteygpkYtdQCAnkECDAAAeSmim0Kt2VxN5/z9LfrTs8vopSVr7GviJO/r9vrWrsjWSU7X5cQArwEmpwItyW1CTed2EuCUCnBHlj5G9PJv+S/VqC8wXQGmsvYV4H+9+jFFYzH+2hmmigfL+B/xb0Tj99QXAKC/7TWpklo8qhdArAkVYIDeQAIMAAB5KWyp9bqn+16k01b+mJY8///o0Tc+tq85ujMFWhLgAj0Fuq0CO1B8xhrkmEpKM1aAxW5n6UGaF39BtOj/9AkLlqpj6Rh1NDQ31Kau/y0Zzf+xiKYvILroDf4eZ6rrAJAVsuwh7lc3rQIx40YWAHQbEmAAAMhLUZ0Aiy94F9ItgT/SwtAl+orS0M01wAXOFOCBXu9qfn89DXqYnQAnOVE1qrR7fI3omN/oEyUcKOd3zLra++of1VE4FeAMU6BLqDk1sT74B0RXbyQ6819EZe0/HwD6X1QnwKE4EmCA3kACDAAAeSnqUZXRzkSa1VrYJRvr6cYXllN1k670GqQLdIj0fpsDnQCnVIBVYlpZFKQAxchv6Q7Xh11DdPyfOdktorjxa765aDzRKbfoM0NAd+Edvas6GmSv4JnD1PZINvlcNL0CGFAxnQAXJpuIkkb3dxFpJqrfqE8AIBMkwAAAkJfMCrDY5Hf3BnaUNK+jD9fW0jF/foV++99P6daXP9cfcTW3hu0mUsITGOA9b80u1FHVmVkqwCnTlJ0qr2VRq14rKGI+Hs88juiQq/QVZnn5H0F3hB6+E9FXHyOae5o6Z1IBPnt3tT2STTfMAoCBk9TLFryU4NcBt8kfxSJEN+9P9IediVa/oS8CQDokwAAAkJei3tT1urUFE/TIVRpeTz9/7BN9RvTppno9crW0uG8wfUE3oRwQGdYAFwS8qdOUA+5jjPvdhNVfoNf6HvR9oqOuJ9rly0Sn3EpUZCS4kw9UH9PGFETpsOp/6TNmfG0AGCChMj1grXV6wNa8TlQtN/GSlHj6GnUNANpBAgwAAHkp5kmtAMeKRuqRK9Gwld5d7XZSDfrU3sGmSIu7zs4XHOAKsDn9+P277YPs65vSpdlIUotLy/WIqLy8Ug08/Kt/v0tU8jv3S+qayVkTzL4xdg15P3lQn7GiEXoAAAPFW+AmwNHmWj0ialnytB4RxTcvaT89GgBsSIABACAvxT1pHZvtDsapAvEmPVLCMb2O1hA2KsCBggGugJqdmhfeRPTir2n/pmfpAM9ifZE5a3qZJ6SrvqK705clyfb47GHlmv/aR5tUjqtm6BMAGCj+QvfGVlPddj3i16pPn9Ej/pwYv7bZ1WDWgu2SAExIgAEAIC/FjCnQsaSHAmXtK8AllrF+jknDq3TRVrcCHAgNcAV41Fyik28h8um/24u/oLKnvk0/9atqsM2cpmwkw2Zlt1OW1f5zZbq0NNeSjwHAgPIXV+gRUXM9J7erXqXYX+ZTef0yfVVJLn+O6L9XE/16EtGbGRrgAQxRSIABACAvJbzuFOgWClKB8abRUUqpCXA4mikBNivAOdAEatfT1fRl4++Xwqz0mmuGzWS4K87ewI59LtIDABhooWK3AtzayAnwnceRr/ozfcXVvOQZojf+qk6evFIdAQAJMAAA5KeEUQFuoRCFStonwMX8ESlqzhqtEr5MFeB42K0Aewe6C7Rj1olEP1pH9D1+01usuzg7CofpQZruVoCFmQBPPIBozG76BAAGWkGJXs/PRr37ez1qL7TmBT0CABMSYAAAyEsJY8ugiOWnwtL2CXCJ1UL7Tx1Os0pb6QjPuxSLtN8HONai9gq2OVsM5QJfgJPfEURFVfqCVmh0daa0PXy7y0yW90X1FyCXFFcMp3DSb48LG1fbR9PCxM720ZvQ+5c7oka3eIAhDAkwAADkpaSzTtbmyTgFWva5PXnXkfT9DZfTbYHf06ktxpY/7JdPLKF3lq3VZywX98EtdKtBdpLrT2v+5ehJ9dpptlU5hWj6AjUGgJxQWlJKP4h+g16M78rJ7ix91fVUfE89SlPbPlkGGIqQAAMAQH4yEuCk5SFPgbtuzjEqFKXj6SUaGVVJ7uGxl+yj45aXP6ciq0WfsZ5UUbPF3Me3o+nPth40sDr0KrXu97R/8DuF9ltDAcDAqSgM0NulR9LXoj+g0yPX0FXR8/RHlET5JPo4MVGfGapX6gHA0IYEGAAA8lLS2DM3KQt9zS2BtKklMQosvEGfEa1Ott8qqYiMaYNmh+VcYSa9ZjLcTg/2BB02lWjBL1XXaQDIKbL390MX70+/PGUufX3/SdSYNPYHZzMnjqGXErvqM0PNKj0AGNqQAAMAQF6yjDXASal+Zqreyj6Z293uqclk+yQxJQHuSSOpbDET4FBalXvygXrAKjmpBYC8UFUSpDP2mkA/PX42nXnwbH1VmT5+FP3L+wV95orXGss5AIYwJMAAAJCfAm4CnJBfd93Yw9afdJtgOclwsaUS4KjlJ/KqxjM5xUyArbRf63uer6YyH3U90ehd9EUAyCf+gtTZLQUl5TRp4mQ6Kvxruj92kL5K1FS7VY8AhjYkwAAAkJcsv9v0ya4Ad4OfopRIqMQ3GlfHQl0BDlup0wxzhtkEK50k7DKVeb9L9AUAyDeBotSZHwVFZXTAtOG0LDmevh+7gJYkxtvXW+q22UeAoQ4JMAAA5CXLXAPsJMB7fZP/w+NRqdXQVp+a2hykSNtewFF9dJpgtVg5sgdwOm9QD1g3qtwAkF9CaR3uC4rL6KTdx+ozojpSyz9iTdX2EWCoQwIMAAB5yRswukA7v+6O/S3RD1aqacGOEbNoY8Ve9jBEUQrHVOIb4eMXPS/TF72v2udN/NGcZK5LLp+gBwAwVBQUp1aAC4tK7DXCJ+6mtjOrTaoE2BeptY8AQx0SYAAAyEt+r1sNtbtAOwoqONMt0yds/rltHaOlAhyOxe2xVIB/H7jZHoucTYAnHUg0+WDV5OqQH+mLADBUFJakJsDFIdWr4LqT5tidop0KcChWbx8BhjokwAAAkJfMBDhOPj3SJu1PNHwG0dj5RLue3jaNOGhFKRzVFWA9BdoRKjKS5lzi4V/lX32E6JJ3u9gGCQDyUVFh6s052SZJlHIiLJ2ivYUqQS6IN0h3P6LPXyJq2m5fAxiKkAADAEBeilTNoQ1J1SDqpsIL7WMbqQB/+y2ibzynphD7dAJM0bbEV6ZAmyaMqtKjHIX1vwBDUtDn1aPMwn518y4gXe6fv47oHycQ3X2SfQ1gKEICDAAAeSkQCNLR4d/QAeE/0wr/NH21A21ToN0KcFRPhXb4Qxn2EQYAyHGxgDF75dU/qeO2ZeoI7X32DNGbtxLFY/oC5BskwAAAkJd8Hg81UCGtS1Z1WRz1+NUUwgIrQhFnDXBYbX/UJtKoBwAAg0c8ZHSJTuobezF+fdN7nYOhbh3RPV8ievL7REsf1Rch3yABBgCAvGd1sQ+wpRNg8cLH/AaIxSJq+6M2zdhCBABy0yWRb9NnibF0XuQKfcWVDKU2yWoTC+sBtPn8RT1gi+7TA8g3SIC75zCOv3Ms5WjiWM/xMMceHF05heNejuUc8m5qFcc9HDtxpJOfOrkdlx5PcQAAQA8kjOpGdyvA4u8vLaUP1tZSPJpWAW5BAgwAualy7zPoyMhvadYhX9ZXXJZugtWOVIEh1VZ5q69hW7m8hQS4e6R7yiSOP3Mcy3EpxwiOhRySHHfmBxyFHP/DsYDjGo7dOd7jmM2R7nOOfdPiMg4AAOiBYUWqsZWYN8GYApiBmQDLOuD73llLsUhadWR/vBQDQG766fGz6dnvHkzfPXK6vuLyFrkN/Foto2M0KsDtrXtXD1i0WQ8g3yAB7p6LOSTR/RvHSxz/5jiSQ3rIX8XRmeM5TuS4g0P+7D85juCQd2aXc6STKrEk1mYYt6MAAKA7JgwrpCv4zeAXdhlNVxzV/k2hyROQ+5RKyIrQiJJgSgW4ftwhRHNP1WcAALnF47Fo2ohisjJNdykbR/fFDqa3EjPohsgJ+iKLpS3zGOpkmct6IwHGspe8hQS4e7boo0m6oXzCMd4+61imP7uBQxaZdfVnAQBgB1xy+E701zPnUUnIr69k5guYFeAIlRX4KWEmwDO/TORN20sYAGAQKAn56MrYt+i0yE9pTVImMCqx8AAlwLI85dOniFa/oS/kiPfvJoobVXEkwHkLCXDvSU/5eRwf22c9M4VjIkemPzuVQ37ipPf6Cg6ZOq325wAAgH7hDbgvs/ZewLEExaLuGyFzijQAwGBSHHRv3rVSQI+IoumN/rJl/XtE936Z6M7jiDYu0hcHWCJO9PZt+kRD34e8hQS4927kKOKQBLUn5FXodg6pIP9RLhhe5fguxxc5ZI7KExxXckgTrK7+X8ktPVlTbIYk0wAA0AVfWgLcGk1Q0kiAfX53PTEAwGBizoAJkzuOtg7QGtdqqe8w2ZLpld8RNW0jWv7swO67+9nTRLVr9InWLCsdIR8hAe6d6zjO4pA1vMZigS7JwgxJfg/kOIdjLYdJGmTJOuMXOCT5vYTjhxwHccg64s5cxPFRWkinagAA6IIv6CbAsga4NRbnBNidAu01Pg4AMJjIFGhHOOlWgO0p0FL5jGa3EhxtrtMjzoE/eYToT7sQ/fOLRAtv0lcHwFv/q46BEqK9vqXGMgUaeyXnJSTAPfdTDklUr+b4q1zoJkl+ZW7F2Rxf4+hucipNs8Q++tgRedWYkxZdJc0AAMCCBTKhR7k38D9ktVRTAhVgAMgDZgJMxnKOuCR4N+1L9LsZRNUr9dX+t3rjZj2SN8ecYEZlh1H2zI/VMdu2LSda8Zwa73amu/2RVKhb3WQd8gcS4J6R5PdaHb+QC93kJL9f5zifw0lqeyKhjx2RZluyptgMPccEAAA6401b47vbpgf4vY+bAHuNJlkAAIPJuIpC2mlEMQV8Hjp6V2lBoxR8ch8nf58ShTnJe1c2K8mOSHO9HqWKB6W9zgD4SDZ3URLzz6O7F8kqRQ3ToPMSEuDuk9tSkvhez/EzudBNkvzKvApJfmVORU9fYb6qj7IdEgAA9AdfWoIbj1DS2CPTjwQYAAYpr8eix75zAL3/4yNpxjh3T+CiNS/qEYvoKmw2tKoEOJZMTUPWxTvfr73fbFumjmUT6I36YfT8GmMtMhLgvIQEuHuu4Pg5hzSjepxDpiOb4ZD1vfJT495eI/oLx3kckvgu5jD/3O4cDlkXLF9fkmTZY1j2D5ZpzVJpfp7jUQ4AAOgPvtQpzrVWaUoTLL/RJAsAYLAJ+rxUFPSlNPyzkkai17BJD7IgoiqsW6icHogfYI9FMDpA041rVqlj5SR6b3UNrU8OV+cii1PDIXuQAHePJKNiAYdsWpYeDq8Ocxdy58+ey5H+5/7D4djIEeeQSrMku/dxyKvCTziO5ehqCjQAAPSWPy3BleqvMQXagzXAAJAHzIZ/KWpW60H/8+g1v03JAroy+i16LS4blxANsxpSm04t/BvR7UdxprxEX+gnTpJbMYkWr6+j1cmRFE/qt/JOdRjyChLg7jmEQ34SOgqHNLeSc30ryTaJI/3znZCPOZZzHMcxjkPm2skr1C4cUgF234UBAEDfS6sAe2MtZBlToNtNkQYAGIT8wUI9SiNV0Cx1PPZGVQW4kd/qxslLLyXk7S4/NplEGdbrg6Uz9VM/JFr7pjr2F2lypff7jZdPordXVfOb7gCtTcruomz9u6pTNuQVJMAAAAD+1DeFnji/+YpH9BnzuVuHAAAMVv6OKsCRBk4Ea/RJ//LFVAU45iuiWaNLqZpK7XOb7Aks1r2jjmLtW3rQD4wpzouaKqmmOWqPVyTH2Ef6/AWi//dlToIxETOfIAEGAADw+onOekCf8JvEeGvKFGjyYgo0AAx+wWDaa9lI2TVTq8nOeteAToAj3kK64+t70vakkQA7TafWGCsMR+ysB/3A+Ds/sIp/D2hrnAqwWP4MZ8f/0ieQD5AAAwAAiJ2OoGrfSHvoi7eQZVaAJUEGABjkgn5pVePaXDJLj5jTDKqfBRLN9jHiLaKRpSHaf5cZ9rnNqQCvelUdWU1/LgSUKc4saXnpwdVudfytxEw90p79aVv3ahj8kAADAABoUY+qjvgTrW0JcJg4+bWkbQMAwOAW9KW+9f/jEqP6mqVGWCGdAMf9RfbRKnK7LickAY62UHKNu/vn1q2b9agf6O+zqXA6NdsteIgmDiukJxN70e8KLyOaLz1sWSM/hpd/q8Yw6CEBBgAA0GJeVQEIcALsSaiyQ5Sw/hcA8kN6AixTfauTxeokGxXgZJIKk6kJsKfEnW4c2c6PYfVrZBlLUEo4Ne0XEf66G963h883T7WP8yaU0/yJlTyy6MH4QUTH/YFo3F72x+yu1Ns+U2MY1JAAAwAAaHGdAAeTnADrCnDUwvRnAMgPsh+wqTpZ6q537c8EeOnjRDcfQLT43+TVO3sm/CX2saiolD5PjLLHyY2LiFa8YI8dZaTWDPe5LZ/wg1B7Ib8aVgnwmXtPpJKQzx43tPLHZPbPsb/hMz4moqojdZa6ZUP/QQIMAACgxX26ApwMkyehEuAYEmAAyBN+b+pyjupkCa1zEuDafpoCXbeO6MFvEm1aTPTC/+iLLKgqz8WccH6cVDuD+rbw5yx/zh47Cq0w0TM/7ftOzEbX603JSrs6ftzc0VSqE+DGSIy/JSe7Y3YnmneOfY2WP9s2bRoGLyTAAAAAWkLv91tAnADrCjASYADIF1ZaP4MaKnErwLVrieKqItpnpFr6xPeJImrv32TtGvsorKBafywV148TKgH2N20i2rrEHm8zu0O/9ieiTx/XJ31E9gDW6qmQxlcWUkHAS6UF6jVfHnpDWP97HPQ9dRSSyMOghgQYAABAS/jUfsCSADe36HVqHqwBBoD8FCWfmwAn45wJrlPjvrLkUU5cn9AnnPTK99CsgnL7WBLy00fJyfbY9Fh8Hz1Skh+5W9X1CSMBbkgW0phyNQPImQItGlrVvsBUOo6zJn29fr06wqCFBBgAAEBL+nUCbEXIK+u9WGmxatQCAJBvpo8sTt3zti/XAYcbiZ68Up+0lygdax8l4VyUmEKJpFudrqdiei1h7FHMEkufVF9TvP9Pomd/RhTXCWpvhN1tjRqogMa2JcDurB97HbDwcMpUMkaN6zeoIwxaSIABAAAceg2wVIAD5CTAukMqAEAeeDB+gH18PzGN9phYQWuTVfa5raOtkKT78Tt/dxPQ7lj9OmeQG+1hc+kU+5iizE2A66mIPk2Ot8/Fy/HZVON0p9a88VaiZU8RyTTqhy8mevUPRG/eoj/aC3pf31jSQy0U5ARYLYEp01OgRXWTsR986Wh1RAI86CEBBgAAcARUBbiQE+DJgVp7TD61NzAAQD74cfTrdHHkO/T1yPdp9wkVtDE5zE4CbR1VgP+6J9FjlxM9+1N9oRt08iseakqt5jYng1Rcpvb/LS8IkM9j0dZkmX0u3kzsTHWU4eajTIM2H+MnD+tBL+gKsKz/lS7PzhToCZXq94BYuc3oQF2qK8AN3UyAE3G1ddKSx/QFJguL6zCFeqAhAQYAANDGVA2zjx4rSePiei3cpAPVEQAgDzRRAT2e2IdqqYTmcQIcIx9t4CTYlikBtrf9kWBv36aO3dG4RQ+IFrUa06zZxmQlVRarm4sBn4emjyyhW+JfsM9jVoCejs+nhqRKSE1J6cJsVmCNNcU9pivAsv5XOFOgJRGWxySueegjeuRD/f30lG37+3dnK6TPnlbbJv3rLKKty9Q1qV7/8xQ1hgGDBBgAAEArLja6joqy8UT7flufAADkl/GVBTS8OGB0gs4wBTqqGgJ2m1Q9fz+T6N077dNGq4i2mx2dmZ0AF7kNBncZV0avJebSJckr6ZryX9FmqqRNNIzujh1hT9W+NHKR/XmWdOeXqdgOqbL2lq4AN9gVYKJxuvLr9Vg0eZjb++E7975PWxvCbgU41pqyhVKHpAGYw6lUb3hfHWFAIQEGAABw+NMqDkf/om1aNABAvgn6vDSuopDWOeuAjW2K2nQn2TNJ1VOmP+uO0pviZW1JpkOmXZsJ8Jyxavrzo+Hd6P82jrLHs8eU0o9j59LJkZ/TY4l93W2R1r6pjmJHEmCjAjy6LERjOByyJZLp3rf438VJgEV3OkEXG1Xv9e+o44b31BEGFBJgAAAAR8Do+DzlUKKdj9cnAAD5aVxFAVWTTi4l2U2f3tui+yH00pZkeds0Y8c2b5WdfDvm6gTYdMgMtzlXnLz0RHxvfWboaXJuSOptkKQD9L5Th7XbI9l0z5urKVZoJLSNm/WgE03b9ICtfFn9O6ICnBOQAAMAADjG7E5k8a/GQAnRMb/hccdviAAABqObz97Drnj+8pS59rlUO2uT+uZfIkYUSev0vANJpthK5dRspSXAQbfjs9hpZPuGVwftZHSnZun7AtskEU0k9EnPRJtVYi/V6X2n6DXQ2jn7TtQjZXN9mF7aYKRNDd1IgJu36wGTaeR3fYFojVG9hgGDBBgAAMAxbCrRt98hunghUdV0fREAIH8smDOK3vjR4XTGXhPs8/EVhakdl9Mrvq09qABnmJIs3Z3nz0xNKGsKU7dFKgz42ppQiRElQdprciU/xvE0Z2wpfZUT0reTM2hTskJ/hib7tbdU65Oe8ThdoJOFNHl46n7vB+40nP59wb707HcPoopCtS3SHR8Ya6Efvojov1frkw40bdUDbdNionhYn8BAQgIMAABgkiS4bJw+AQDIbzIFuq0CLNIrvj2pAKdXj1mQojR2xEh9prRk2Bd46gg3CZf9iWVK8i9P2YUeu+RAOpqT9iSnLRmrwFuX6kEHXvsL0b1nEK17l6hRJ6WJBHmj6rHKNkjFIZ89dsj3nj+pkqaNKKHT9Y2CV9e2UtxnVLLfuLHjfZOFMwW6ZAzR6N1UTD2MaFd+LDCgkAADAAAAAAxRMgU6tQKcngCnVYA7azwVbp8Av52YQWOGpXaBLi5J67jPCv3umuDdxpfrkbLruHK7O/Oj8X31FcNj3yWq/lyfpJHH/syPiT59gug2Tj7/Op8fY4OdqFt6aydZn1wcTE2ATWfvM5H4W9tqPGYFmv/8e3fpcQZOAjzrBKJvvWTHphPupW+txNZ6Aw0JMAAAAADAEDWmPET11IMKcIYqbxtJLrVVxbvTLbHj6CXfvjSs2O34LMwO0I7po0r0SDpApzbFKuIEdefRJfRhciot889QF0fMUsdtnxLdfBDRovvUualmpR5oMp1746KU61uSFVQSVNOcM5Gp2UfNUp2pV4dTp0rTe3cTxaP6xBBt5X8n/W9ROFwd2YqtjfQ5BwwsJMAAAAAAAEOUdGP2FRlNoNLX/KafG0luO0Zy/Ez5l+mXsbOouLDIXuN7c+wLFE766YLIZe0SYnHe/pNp9wnldPyuY2i/qalNqcQeE6T6atEpLVfTy8c+T//c9W5K7H2h+qAkmw9+gxPhA4mev56T0pi6Xp2WAAtZM7z5E31CtDQ5nhNst/qcidMUy0qmNdxq2kJ0HSe4tx7C/06qq7St2e0AfceHjdQYVo8HyW9uQAIMAAAAADCElVW4VcouK8CdJcDGx7ZGVVVVqr2SYP4qdibNDt9OTyX2opGl7p67jrJCP/3nov3phjN2J48z59gwb6KaftwY89E5D26iax79lB4dfQnRmferzv1i0yKil39L9ME/1Xl6BVg0bCLa8rE9jCa9tMk3jnzezlOiueNURbqEWuxjO7K90UcP6BNWp/ZAFgs3WfStu9U+wCu2NtlHGFhIgAEAAAAAhrCqykqKcDJo62oNcDcrwFvCKgGu4ARYKsAiRuo4KkMC3BVpjJXuwffWE00/ir/gHH1F+/xFdaxZpY4mSYB1BXhFcgwFQ10/FlkjXOD32nsat5l+jB5oK14galWdpZ3p2PGkRR8mptBry7fTqm1NtJIDBh4SYAAAAACAIWxYSdBthJWe8DrNnBwPnEf0f2cR3X0K0WfP6oua0QTr/c1q2m9lob/dFONMFeCuyFrckaVBfaaUFei1u4VpU6a9/HnJJNG25epcOjE7pGv0+nft4afJ8VTSSQMsh3SFHsHf+/rY2dTiKSKafBDRkT/TH9WWPEJ02+FE0Raixffbl15K7EqbSD223z39KS3dpBNkGFBIgAEAAAAAhjBJJOv0Vkjx5tR9dZP16/VIq11DtPQxohXPEf33Kn1RMyrAjUm1r29lUbCtAuzoTQIsSWh6FTjg06lMYaU6Ohb9H9FN+xKteV2dT9yPaPSuaiyPXa9rfjY+r90WSB2RvYmXJCfSeSPuJTqHk92qGUQLfq0/qm1bxl//cSK9x/ADcU6UtccWbaTN9dgHOBcgAQYAAAAAGMJKOQGu1RXgeJMxBTraQpY0jUpXoBNRWWObSBDFOLGLNKdMj24klQBLcl0USK0AF6Sdd9c8uxGWq6YpogYFaQmw2LpEHX2cbMveu8Wqk7PjncBe9GhiXyrpdgKskvaNjUnJxu0x7XMB0c4nqLHjfbX+OM5p1iuJufZ4dFnPE37oP0iAAQAAAACGMElSnYptwtzLt36DHhhmn0J0yI/UOM4J6PbPiP44m+hPnOytVhXXWNJDYVLTkyVX7KrJVHelV4C3Owlw+hRoxxHXEl3+CdFORxCVjNQXWaicfh+8mAdWp3sAm6pK1PTrLfWt9rFNUZUeaHr98fLgLHt7qbljy+iNHx1Ob111OP39a/PpD6ftZn8cBg4SYAAAAACAIUwqwC2ktiZKSiXXYUx/vjd2KN0YO4HopJs4Yx6nr7Ib9yJq2qq2/ln+jH2piaTiaVFhwEvH7TLavtYX0vcHrm5LgDNUgEP8uQdczgmqTo7LxqujOO73tCZaag+LO9kD2CRrgEVTJE5Nelsjm1S/UyTt/77jm2cfnXXKI0pDdNjMkW0dpWHgIAEGAAAAABjCSkOSAOsGU1EzAXYrwP8bP45+GzudyF+QmkxmINOfZT/fN686nKZW6eZa2i47kADKmt87vr6nPiPa3qiTz0wV4JDRsVns/hWiKYcSHXYN0ZwvUn1r1L7c3SnQI/UUaLGlwUh69zxPD1K9klRrjksLuvf1IXuQAAMAAAAADGFSpWxNqgqwFWshevKHRHefTPT27fY1sSlpVFnLO0+Am5Ih/po+Ti7d6uoDF+5L5+4/mW4+ew99pXcOnTGCvnfUdHss1Vh7a6FMCbCzTpnFE0n6y9uN9H8z/0J00PftGm2jruL2dAq02GomwGPnEZ37X32iFVXRu+EJ9tCpAEPuQAIMAAAAADCESZXSqQCHwtuJ3vwb0Yrnida9ZV+rSxZSsz2tWUuvrgpJOPe/1F7/+2Ri73adn/eYWEk/OX4WjSlXa413xLBiNxk99Hcv0uoW97xNgXqM9729lqZe9QT94Zll9MMHF9v78TZz4iy7JInudoGuLFI3CER1U9q05wn7EJVP1Cds6uFUF47bQ5leDrkFCTAAAAAAwBCmpkC7CV66J+N76ZFsr2t0QTaVjKb44T+jueHb6I+xL1GBv3ednrvDTEbFJQ+v0SMDJ+SyVvfKBxbpC8qa6mbaZDSyqizs+O9tGlbsft6zS7a0TaFuU+w22YpMPowisYQ9ln9byC1IgAEAAAAAhrAQJ6tRK8NWPWc/QDft8Tj9MPYNfYEorBM7OvUudXQES6klGudEWn2domD/JcB7TqpMmVq8eLsemELlKYmuQ6q/y7e4na6njkhdo9wRM+n+97vr6Lw739ZnWvEIPbCodswBeowp0LkICTAAAAAAwFAnza3SBYppY1ymErsVX0kgbbNPIjr5FjUWiRh/zO2OXJA2BbovSTIqDbY+/tnRtGD2KEpySrMg/Ctq9RsNtgoqaHOGBLimOZKSAE/rZgIc9HlT1gu/vaqG1lYbDcMm6aR3+gKqJdVhWiABzj1IgAEAAAAAhjgrkCEB9gXbTfVN2QKoxNjiKBmnZr3uVRT24xRoIVXrIk5If3/arjSiJEhLkxPony376Y+yUFlqsypNtk5yEmD5cz1JUNOnXr/46RY9YntfQHTRQqJT76T1tS36Yvs/AwMPCTAAAAAAwBDnCRTqkcEXovqW1AS4rQIsiqr0gA2fnvIx2QM4GyQJnjhMPXYv6enZwhvIWAHe3hihz7Y02OPuVn8d6cnsC59u1SMm66JH7EzkD9H7a2r1RaI5aXsXw8BDAgwAAAAAMMRZmRJgTiLr2iXARgVYEr45X+LkdwbRET+jlqj7scJubi/UF8p1Iys/GY/N4+MEuH0F+N01NbRko0qAp48ssY/d5femNv96fcU2ao0aNwS09/l7CEmwywoxBTrXIAEGAAAAABjikr5MU6BDtKkutYoq++dK0mcnflL1/NLtRN9+i6h09IBUgEWFTjJTKsAeL23RU6ClQrzLOFWJ/XBtrb0vsDz0L+/Z+X7G6ZqMKd6iNZqg793/Id380gr6ZEO9PV08wV/7A10Bnjchw3ZRMOCQAAMAAAAADHFWhiZYMU+gXSflr9z+Fs388VM0+6f/pRue+0xfVcwEsT+3QUpXoSvAjyf2sY+2yQe1TYGWtb7p05dP3m0s7TzabVbVHSnVb+2xRRvpV08upWP/8gqddONrtGxLAzXoddLzJlTYR8gtSIABAAAAAIY6f/sp0Jubk5RI6pM0UkX9v7fX6jMlZQp0FivAzhToVxNz6DuRb9NtE35Df11EtGidqsSOKA2l7Pcb8Hro8iOn67PuO3Sms9UR0cxR7adPf761iV5Y6q4LnjcRCXAuQgIMAAAAADDEeYPtE+ANjZmz370nV9pH6bKcTLqfY06BluZU2eJMgSay6JHEfnT9snH0u6eX2VOUxXxORM0K8Nn7TKTxlRnWPHfhssOn05f2GEfXnzSHTpk3Vl9N9dySzfaxJOSjaVU9a7IF2YEEGAAAAABgiEtvgpXgNOGhD1UyZ7r62J3pyFkj7XEknqDa5qidBEdiCWoxEuCCbK4B7mCrIZnifNNZ8+hr+02iOWPVGmDZ9ujiQ6fa456Shla/O3VXO4E+dIZbDTa9pxtg7Ta+nDye1KZZkBuQAAMAAAAADHHpFeBw0kf3vOVOcb7/gn3pxjPn0fkHTranFDuO+fMrNPWqJ+iIP7xEyzar7sqiv/cBNjlrgE2yBvmJ7xxAx84dTZZl0fG7jqGbz96DHr54fxpWHNSf1XvS4Vm+ZjpnyjjW/+YuJMAAAAAAAEOcN1ikR0qY3O17pGq656RKOm4XlUxWGQmkNMmSpG9NdTPd9846+1rA5yGfN3tphjsF2kHt8dwAABHRSURBVCVTnuWxOrweixbMGUWThqf+PXtLvvYNZ+xOC2aP0ldSYf1v7kIC3LXDOP7OsZSjiWM9x8Mce3B0h8yPuJNjG0czxxsch3NkcgSHfFw+Tz5f/lzm+RUAAAAAAH3En14B5gTYnsbLOeTJu6eudx1R2nkFNZsNsITTBMtUUTSw++/Kvx3kJiTAXbuQYxLHnzmO5biUQ5LShRySHHdGXh2e45CEV/7ciRyymOIpjoM5THL+JId8XD5PPl8SYvnzOz5PAwAAAACgA8FgkCJJN3GNJP10zXE705LrFtC1J8zWVxXZVqgz2Zz+LMozVIAzTYvuD0fPUeuhTTuNKLar5pCbkAB37WIOSXT/xvESx785juTYznEVR2fO45jDcRrHPRzPcHyJYxnHbzhMv+WQ6/Jx+Tz5fPlz8ufP5QAAAAAA6BchTlpbjZqLVIBlKnPQ1z6ZLe6iw3M2G2AJv9dDfz59N32mZCsBPnHXsXRF2pZKWP+b25AAd22LPpoaOT7hGG+fdexkjk85ZFqzQzZI+yfHXhzOfBI57slxN4e5w/brHJIUy9cBAAAAAOgXkgC3kJs0OglwJubaWsfoshAdM0eth3U6LmfTibuNpfMPmKzP1BrgbJBOz5ccvhPNHlOqr8j6X0x/zmVIgHtHfqrncXxsn3VMqreL1DCFc82ZTyKfJzr6XOfjAAAAAAB9Trom1yfdBlERToAzVX8dZ+49QY8UqbhKU6i7z9uLrjtpYN66Bv1ualOa5SnIZsKNCnBuQwLcOzdyyCvE/9hnHRvGUa2GKZxr8nHz2NHnOh/vjKxLloTajN5tcgYAAAAAQ4pUgGuoWJ91XgEW1584h76+v7TJUTz8qdL5+cCdqqg0NDDrX6NxvQcRC3by2PuD0xm7NOSjqVXuvyPkHiTAPXcdx1kcl3O8Kxe64P4ktpf+sY4+t7Ov4biI46O0kG7VAAAAAACdkgpwTbJEn3ECnJQKcMepgkz9nT+xUp/lhkgsoUfZT4ClIj5zVAl9/+gZ9r8N5C4kwD3zU45rOK7m+Ktc6II0yspUvXVeLZyKr3ye6OhzM1WG093EIfNNzJBu0gAAAAAAnQr5PVRtJMAyBbqzCrAYVuxO+012p1zTz8JGAtzVY+9r8ydV0lOXHURf2detikNuQgLcfZL8XqvjF3KhGxZzzFXDFM41qdKax44+1/l4Z6RZl6xJNmMFBwAAAABAp9QUaKMCTD4KeDtPFaRq7JDpzwPtoJ2G6xHW4ULHkAB3z485JPG9nuNncqGb/sMxk2Nv+0yRvvFnc7zJsUEusPUcb3HIdbPbwD4cMzgetM8AAAAAAPqBnQAn3bWrfop3OY145uiStj2Bf/KFne3jQFowZ5S9d/FvvrTLgHSihsEBCXDXruD4OcdTHI9zSFJqhuN2DtnCaKJ9pvydQyqx93OcyXEEx30cktT+gMMk55Isy+fK58nny+dK9fcODgAAAACAfiF795oV4BKrNeN2RybpEi3Tfp/97kG0Rw6sB5bHe/6BU+i0+V3tVApDGRLgrh2vjws4ZD/f9HBI5VbCfKUIcxzO8QLHDRyPcozmOIbjJQ7TixzHcsjH5fPk8+XPyZ+XrwMAAAAA0C9CvtQ1wEVW995+yvY/00a4fw4g1yEB7tohHJLUdhSOr3HI+Sr7zLWZ46sc0uCqgGNfjmc5MnmGQz4unyefL39O1vYCAAAAAPQbWcPb4DET4FY9AsgvSIABAAAAAIBavO662SJCAgz5CQkwAAAAAABQ2F+qR5wMWzIhESD/IAEGAAAAAACKBirolfgcak4G6Q+Fl+qrAPkFCTAAAAAAAFBZYYC+Ev0R7RH+G60KyaYlAPkHCTAAAAAAAFBpgZ//a1ELhewtjgDyERJgAAAAAACgMjsBVgJepAmQn/DMBgAAAAAAXQFWAj6kCZCf8MwGAAAAAIDUCjASYMhTeGYDAAAAAEBKApxIJPUIIL8gAQYAAAAAgJQEuCUa1yOA/IIEGAAAAAAAUhLgViTAkKeQAAMAAAAAAJWGzApwQo8A8gsSYAAAAAAASKkAh1EBhjyFBBgAAAAAADAFGoYESx8hP+3O8d5DDz1E06ZNU1cAAAAAADKobY7QqTe/YY+rSoL0/76xjz2GvrN8+XI66aSTZDiP430ZQHYhAc5vJ3A8rIYAAAAAAJAjTuR4RA0hm5AA57cyjoM51nJE5EI/mcohibb8IK+QCwD9AM8zyDY85yAb8DyDbMNzbmAFOMZzvMRRJxcAYPCZzSG7pcsRoL/geQbZhuccZAOeZ5BteM7BkIYmWAAAAAAAADAkIAEGAAAAAACAIQEJMAAAAAAAAAwJXn0E2BHSTK2ZQxbzN8kFgH6A5xlkG55zkA14nkG24TkHAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADQHcUcf+LYwNHK8QHH6RymAzhu43iXI8yR5JjE0ZkHOR5WQ9sIjjs5tnFIx8A3OA7nMJVyXM3xIscmjkaOxRw/4AhxdOQ9jj+rIc3muIlDvr50JJTHeghHV0ZybOeQz/+SXIA+lUvPMxHk+D7HRxzy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width=\"799.9999682108573\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "len1 = len(df)\n",
    "\n",
    "t1 = 0\n",
    "t2 = int(np.ceil(len1/2))\n",
    "\n",
    "xX = df.iloc[t1:t2,11:12]\n",
    "yY = df.iloc[t1:t2,12:13]\n",
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(xX, yY)\n",
    "B = regr.coef_\n",
    "b_0 = regr.intercept_\n",
    "rSquared = regr.score(xX, yY)\n",
    "\n",
    "print(b_0, B)\n",
    "print(rSquared)\n",
    "\n",
    "yHat = b_0 + df.iloc[t1:t2,11:12] @ B.T\n",
    "\n",
    "#plot data\n",
    "plt.figure(figsize=(8,5)) # set the figure size\n",
    "\n",
    "plt.plot(df.iloc[t1:t2,0], yHat)\n",
    "plt.plot(df.iloc[t1:t2,0], df.iloc[t1:t2,12:13])\n",
    "\n",
    "#adjust display setting\n",
    "plt.autoscale(enable=True, axis='x', tight=True)\n",
    "plt.autoscale(enable=True, axis='y', tight=True)\n",
    "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d/%m/%y'))\n",
    "plt.gca().xaxis.set_major_locator(mdates.MonthLocator(interval=6))\n",
    "plt.xticks(rotation='horizontal',horizontalalignment='center')\n",
    "\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('30-yr swap rate')\n",
    "plt.title('original vs. constructed')\n",
    "plt.legend(labels = ['constructed 30-yr','original 30-yr'], loc='best')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# regress 30-yr against 15-yr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.44771641] [[ 0.85177058]]\n",
      "0.995169312527\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"799.9999682108573\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "len1 = len(df)\n",
    "\n",
    "t1 = int(np.ceil(len1/2))\n",
    "t2 = len1\n",
    "\n",
    "xX = df.iloc[t1:t2,11:12]\n",
    "yY = df.iloc[t1:t2,12:13]\n",
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(xX, yY)\n",
    "B = regr.coef_\n",
    "b_0 = regr.intercept_\n",
    "rSquared = regr.score(xX, yY)\n",
    "\n",
    "print(b_0, B)\n",
    "print(rSquared)\n",
    "\n",
    "yHat = b_0 + df.iloc[t1:t2,11:12] @ B.T\n",
    "\n",
    "#plot data\n",
    "plt.figure(figsize=(8,5)) # set the figure size\n",
    "\n",
    "plt.plot(df.iloc[t1:t2,0], yHat)\n",
    "plt.plot(df.iloc[t1:t2,0], df.iloc[t1:t2,12:13])\n",
    "\n",
    "#adjust display setting\n",
    "plt.autoscale(enable=True, axis='x', tight=True)\n",
    "plt.autoscale(enable=True, axis='y', tight=True)\n",
    "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d/%m/%y'))\n",
    "plt.gca().xaxis.set_major_locator(mdates.MonthLocator(interval=6))\n",
    "plt.xticks(rotation='horizontal',horizontalalignment='center')\n",
    "\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('30-yr swap rate')\n",
    "plt.title('original vs. constructed')\n",
    "plt.legend(labels = ['constructed 30-yr','original 30-yr'], loc='best')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# regress 30-yr against 15-yr "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.1938514] [[ 0.98636103]]\n",
      "0.953895616954\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"799.9999682108573\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "len1 = len(df)\n",
    "\n",
    "t1 = 0\n",
    "t2 = len1\n",
    "\n",
    "xX = df.iloc[t1:t2,11:12]\n",
    "yY = df.iloc[t1:t2,12:13]\n",
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(xX, yY)\n",
    "B = regr.coef_\n",
    "b_0 = regr.intercept_\n",
    "rSquared = regr.score(xX, yY)\n",
    "\n",
    "print(b_0, B)\n",
    "print(rSquared)\n",
    "\n",
    "yHat = b_0 + df.iloc[t1:t2,11:12] @ B.T\n",
    "\n",
    "#plot data\n",
    "plt.figure(figsize=(8,5)) # set the figure size\n",
    "\n",
    "plt.plot(df.iloc[t1:t2,0], yHat)\n",
    "plt.plot(df.iloc[t1:t2,0], df.iloc[t1:t2,12:13])\n",
    "\n",
    "#adjust display setting\n",
    "plt.autoscale(enable=True, axis='x', tight=True)\n",
    "plt.autoscale(enable=True, axis='y', tight=True)\n",
    "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d/%m/%y'))\n",
    "plt.gca().xaxis.set_major_locator(mdates.MonthLocator(interval=6))\n",
    "plt.xticks(rotation='horizontal',horizontalalignment='center')\n",
    "\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('30-yr swap rate')\n",
    "plt.title('original vs. constructed')\n",
    "plt.legend(labels = ['constructed 30-yr','original 30-yr'], loc='best')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# regress 30-yr against 2-yr, 5-yr, and 10-yr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0.35040478] [[ 0.01235598 -0.76618625  1.61493626]]\n",
      "0.993819498302\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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AdpAfm7k50d+jiBxIQHeROSs/YG2d/1pzogKKuqotCpgzgAAAAD0GmC3G08PAdpKGmBhDXBiw2+4TYEnVR3u6P4+/xv5gVxWVGlGAAAAAACwoZrqAA2JAQnwpmDskeqwWcVM+ujgyNrfsuqgGQEAAAAAACQ/JMCbgoknEfky1HDUFyfTc77bKIuqqKIWCTAAAABAIrj11lvpnXfeMWed4+GHH6ZnnnnGnLUvqYxef/315iw+2X/62GOPpREjRlBWVpbaU3f06NF08803q9tiyZZDp556KvXo0UN1Lt9xxx3pyy+/NLcCxIcEeFOQnku0xb7mhGg3z2w62fMZVSIBBgAAAEgIyZ4At0QgEFDrZy+99FJ688036d1336UjjzySbrzxRjrssMPMvTRpNLX33nurhPf//u//1H179+5N+++/P33zzTfmXgANIQHeVAzcwQy0bdzzqbIOCTAAAABAV1NdXZ2UjZZycnLo1VdfpXPOOYf23XdfmjRpkkp+L7nkEpXoLl4c2dbzqaeeojlz5tBrr71GJ5xwAu2zzz70xhtv0BZbbEFXXHGFudfGIV97+T+ArgkJ8KZi0PZmoPV1FWEKNAAAAGxy5s2bR8cdd5yqFvr9fho0aBCdfPLJUVvXSGIlFcfc3FxKTU2lCRMm0LPPPmtu1aZMmaKm9b788st01VVXUb9+/Sg7O1slbfPnzzf30n777Tc6+OCDqVevXupjyn0POuggWrlypbpd3o9M8ZWPIWOJPfbYQ90mFVk5/+yzz+j000+nnj17qum+8nhl+u9mm22m7uckU43lbZzC4TA98MAD6nNJS0tTyeYOO+xA7733nrpd3s/cuXNV9dR+DM73LXvbXnbZZTRkyBC13U///v3p4osvbjA1We531llnUffu3SkzM1NVZBcsWGBubRv5nIXX61VH8fbbb6up0jLt2Sa3n3jiifTTTz/RqlWrzNX4zjjjDMrLy6OqqipzJWKvvfZSU69t8rW48MIL6dFHH6WRI0eq/8PY7wfoOpAAbyp6jyXK0L88xOaulVRXVW7OAAAAAJLf77//Tttuuy1Nnz5dVRY//vhjuu2221QyWVdXp+4jyetOO+2kksH777+f3nrrLRo1apRKNu+88051H6crr7ySli1bRk8++SQ9/vjj9Ndff9EhhxxCoZBuPCoJolQn161bRw899BB9/vnndN9996nEu7xcPxebNm2aSkoPPPBANZaQ6chOkvzKHrPPP/+8qnTKuDXk8V900UXq85cq6yuvvEKHHnooLV26VN0uCeXQoUNp4sSJ9Y9BrglJEnfffXeV9P3jH/9QX7d//etfKjmX92FXo+U4efJk9Rj/+c9/qreXJPuAAw5Qt7eUvJ9gMKiS6U8++YT++9//qhct5Gtmkxcpxo0bZ84i7Gvy/9cU+VoUFxfTSy+9ZK5of/zxB3399dd0wQUXmCuaTE9/5JFH6Nprr6VPP/2Udt11V3MLdDXo053c5KUr/v0wR7+KtWYW0efXEC2eom58bIsn6Zzjj1ZjAAAAAHuKqSRCsW54fy79sbrMnHWuUf2y6bpDIhW6lpI1o7/++quqSNpVxViSaEniJonswIEDzVVSyalUR1evXk3dunVTFeA999xTXf/www/NvYhef/11OuaYY1QCKcnfL7/8Qttss41KoGLXsTpJtfSoo45qsAZXzk877TRVpY6tOkpSK4/DTmJtUgG+4YYb6hPTb7/9lnbbbTdVqZaGUo0ZM2aMaigl79Pp9ttvV2/7448/qs/FJut05TF/9NFHKsmVZFWOsiZXEmWbrG+Wt7/uuuuabYQlJDmX/webfP7y4oKzAixVaHlRQKqyTvJ1lxcwJLF1vo94pMpeWlqqKvS2888/n1588UVVQZb/EyEVYPk/X7JkiZoV0JSmfoaEJObydWbyT9NZOmwUqABvSvqOI9r9X+aEyKpJjD9iAAAAkPgk+f1xSVFCRFsScaliSgIryWljya/46quvVKLsTH6FJJvyPiTBcpIKqJNdgZSqsBg+fLhKmqRiKsmaVBjbQppBtZVUbEVsVbOlPvjgA5W0yfRpqczasd9++6nk0E6YpXIqZE2u0/HHH29GLSPvd8aMGer/4pZbblGJtnz+Mo3bST52Y+zb5G2cj9muzAupAs+cOZO+//57dS4VZ6len3LKKfXJr02mRTeX/ELXgAR4U5Pi+GGuRQIMAAAALSNV1+2H5CVEyGNpLZnuKsnPgAEDzJX4CgsLqW/fvuYsQtbtCrndSda6Osn6UGE3SZLKoSTekjzKdGmZlSfvS6qh0vW4peI9ppZav349eTwe6tOnj7nSOjJ9e9asWWratTNkqyKpMhcUFKj7yddGqrSxX5PWflxJNKXSLBV2+ZpJ9VfWKkunZ5t8jNj/C1FUVKSOsr5X2FPH7ZAXN2xSkZd1zjI1XUi1Xaasx3uhYEO+/gDQcWRukDVnzhz+3WQULrKs67JVPPp/N6pLoVDYOu+Fn60jHv7eKquuU9cAAABg07No0SIVyaiqqsriJNA6++yzzZX4evXqZR144IHmLOLVV1+V+cTWJ598os6//vprdf7666+rc9uSJUvU9aefftpciQiHw9bMmTOtiy++WN3ntttuM7dYVkZGhnXKKaeYswh5P3LfGTNmmCsR55xzjsXJpTmL4AROvY3tP//5jzpfvXq1uRIfJ+fW7rvvbs4idthhB2vs2LHqMcQL+ZzFFVdcoT4OJ8Tq3GZ/TTjpN1daZ/Hixertb7/9dnPFsvbZZx9ryy23NGcR8jWV+65atUqdy8d2PtZ58+ap67a77rrL4sRYfW1GjBhhTZo0ydwSIe9PvqYt0dzPkDwvl/fH0fo5/NAuUAHe1KRkmQGRq0537ftqXj59NHst/bKsmJ6bpqfrAAAAACQTaTIljZw4Ya2vWMYjFUKZeitrfZ2ee+451X1Z1vW2lUzLHT9+PN17772qC7OsR7ZJ5bi1W+tI9TI/P19VaG3SzEuaNDnZTaikiVNTGnsM0sGakzpVdZXKbGzY3aKlYitkDa1TbKOp1rKnVst0ctvhhx+uOnrLumSbTHF+4YUXaPvtt6+v2Mtjcz5W6RztdOaZZ6r1xDJtWxqgSbdnSG5IgDc1/sgUaG+gQh0XrddHsaYUe5oBAABAcrrnnnvUtGNJkJ544gmVWEnDJVmjandklqnJMlVWkjlJ5GT9rGytI42upIGTTGluDVk/K42yZBrvF198obpAn3feeVRSUqK6Q9vGjh2r1tK+//779PPPPzfYSimev/3tb2pq87HHHqsaUUnHatk/17nOVUjH4pNOOkk1wJI9duVjyLZKd9xxh9oaySaPQTplS5foGTNm0OzZs9V12e5IEkdppCVfQ/k85O2l87WsqbaTUPnYch/Zh1e6a8vnKl8z2bO3JR577DH1tZYXG+T/Rr52snZaklJpbOVsIiZTm2U6+dFHH60SbHlM8ljk6yafV0vJCxHSYEw+3uDBg1UHbwDouhpOgQ6HreB1uWoK9DM3nqou3frhH9bgf32g4o6P/1TXAAAAYNOTzFOgbX/88YfFSZPVvXt3KyUlxRo0aJB16qmnWjU1NeYelsWJn8WJkMXJrrrP+PHjG0xpbukUaJlye9xxx1nDhg2z0tLS1PvcbrvtrGeeeUbdbpOp0TvvvLOVnp6u3t6eitzUFGjBia81YcIE9b6HDh1qPfjgg2qqsbyNEyfF1r333muNGTNGfU7yOHbccUeLk2FzD8taunSpxUmslZWVpd6eE0Jzi2VVVFRYV199tZombL+9TIu+5JJLrLVr15p7WRYn9hYnpxYnlupzkanK8jWQ99fcFOjvv//eOvjgg61+/fqpjyFvL1/7m266yaqsrDT3ipCPy8mrlZeXZ6Wmpqqp2px0m1tbbsqUKerxOadYO8ltmAKdPLANUnKTHyz+OTPbIBlVNw2g9FA5vUz70XHXv0bnPP8zfTpXT505ZcfBdMNhqjU7AAAAbGKa28IFIBnJnsUyPXzFihUNGni1FrZBSnyYAr0JCngy1NEfqlKd+xav12uBRVFVy7sRAgAAAAB0VdOnT1fTrR9++GE6++yzNzj5ha4BCfAmKOjVCXA61VBVXYiWFVbRSZ7P6DLvq1RSgTXAAAAAAJD8dtxxR7UeW5p8yfpo2DQgAd4UmUZYGVRN0xcX0pbhv+gm3zN0ofddGlv8hboNAAAAACCZyUxI2fdXOoNnZkYaxUJyQwK8CcrMytFHVw299esq2tYd6TK4eY3u9gcAAAAAAJBskABvgvwZun2/VIA//3Md5bnK1LlYG9TTowEAAAAAAJINEuBNkT9LHTJd1VQXDFN/V2QzeE+4jqrroveOAwAAAAAASAZIgDdFKXqNQybVqOMw12p1FLlUTkVVdeYMAAAAAAAgeSAB3hQ5mmC5KExDXWvUuchxVdD68lpzppsDBENhcwYAAAAAANB1IQHeFJkKsMdlUT8qpAxXJOHN5QR4eVGVGtcEQrTffVNp97umUAmqwgAAAAAA0MUhAd4U5QwyA6IDPD+ZkSZToFeYBFg6RC9YV0GrSqrpxR+Xq2sAAAAAAABdFRLglpnA8SGHZIHVHEUc0zhO5GjOFA6riejDYWvsvp9wtJ/hk4g8KWp4iuczdbTJFOhlhZVqvLJYJ8KiNoDGWAAAAADPPPMMuVwuWrp0qbnScvI28rbyPjamU089lTbbbDNz1riXX36ZdtttN+rduzf5/X7q168fHXLIIfTDDz+Ye0R75ZVXaMKECZSamqrue/HFF1NFRYW5FaBrQALcMrJx7gqOKzkO5DiZQ37rPc9xNUdTzufYMSb25ghwTOdYy+G0mCP2/hdztJ80/nSGyUMgGuher462HKqgFYX6F1lJtTxELcPvNSMAAACATddBBx1E06ZNo759+5orLSdvI28r7yMRFBYW0s4770wPP/wwffbZZ3TPPffQunXrVFL8zTffmHtpL774Ih133HG07bbb0scff0zXXXedSuSPOOIIcw+ArsFljtA2ksD244jMKW6ZUzjkpb8zOZ6SC4ZUgHtwjFFnG240xxxGo0fL0GHWa0RvnWVOou1M/6MDthlJT363xFwh+sdew+nSfUeYMwAAAEhGixfL6/BEQ4cOVUeIqK6uVpVPqeAmOqkAT5kypU1V6tLSUurZsycde+yx9Nxzz6lroVCIBg4cSGPHjqVPP/1UXRMvvfQSnXDCCfTRRx/RAQccYK62v6qqKkpPTzdnia25n6G5c+fSmDHqqb78M1cG0LFQAd4wsoFuUA9b5QwOKbO+qs46wxb7E3n85iSat7YkKvkVZTVt+TQBAAAAEst3331He++9N2VlZamkaqeddqIPP5SVbhH2NGepip5++ukqIZT71tbWxp0CLbtm3HrrrTR48GCVJG+zzTb0+eef0x577KHCFm8K9PXXX6+uSWIkFdZu3bqpKcnycSUZdXrooYdUdbZXr16UkZGhEtI777yTAoHIrL0NJV8X+Ry83sjsv+nTp9OaNWvotNNOM1e0o48+mjIzM+ntt982V+KTz1ve32233WauREydOlV9/q+//ro6t78ev/76Kx111FGUm5tLw4YNU7cBtAckwK0jXy/5bdCTQ6Y278dxB0drbM6xK8crHPEWTchPuKwxloxzEcctHGkc7Ss1mx/JPuYk2lBfMaV4or81yhzToQEAAAC6IpnWu9dee6nE8qmnnlJrYCXhk3Wvr77asC4hSajP56Pnn3+e3njjDTWO56qrrlKx//7707vvvkvnnnsunXnmmbRgwQJzj+YdeeSRtMUWW9Cbb75J//73v1V19ZJLLjG3aosWLaLjjz9ePZ4PPviAzjjjDLrrrrvonHPOMfdoG6nwShItiep5552nEvoLLrjA3KqmE6rjuHHj1NEmX48tt9yy/vbGyHrkQw89lB599FH1sZwefPBBtZ748MMPN1c0mVo9fPhwlRjL2wG0F0yBbh356bN/w8i+QLI29xF11nK3c/yLQ9b2yhRqp5s5VnHM45CkV+aSnMshnQj25GhqQ95eHJKYO0ky/W7cKdBi9htEb0oxmnUbRFRqOj0ffB/N7H04TX7oe9rMtYZ8FKLBW25FT56yrb4dAAAAklKT0zc//jfR2tnmpJP1GcvPkuQpVevsuOOO6nOURFIql0ISMmnsVFJSQsuXL6+v0Eq18+STT6Znn31W3c9m37ZkyRKV2BUXF6u1vZMnT1ZNomxSNZWPt/vuu6vpyEISzCFDhtDTTz+tpikLqXjecMMNqpJ7+eWXq2tCEtD//e9/avqvPKZY4XBYhSTx8njWr1+vqqWitVOgJYmdP3++GsvnIkmnrA22SXVbEnypAvfp4+zfSrTffvupj2O/fWPk8ey5556qWixfK7F69WpVNb/mmmvo2muvVdfsr4ecy7GrwRToxIcKcOvcyiFZoHQu+B/HgxyXcbSUVI9l/a98s8cmv0IaaklC/TXHRxx/5+C/NrQbx2EcTZGKtLz85ox3ORon06C9prg8kD8tt3lVs2gRTRiYQ3fu25M+TvkPfe6/gtLLo6dEAwAAwCZGkt9l3yVGtCERr6yspB9//FFNq7WTX+HxeOikk06ilStXNkjipCrbHEl0ZWr0McccY65oO+ywQ4s6MdukQuok1daamhrKz883V4h+++03db/u3burxy0VWEnSJYlvTbU5llSd5Wsjie+oUaPUel47aXeKl4gL5/VgMBgVUk0WMhV8/Pjxahq3TSq78rZnn322uRLRkq89QFsgAW4dKZH+zCHJ6Xkcj3PIYobYymtjpIO0vGz2pDprmRfMcQdzbMzDHPJKkjOaTpr9/Mt/72v50W/Jaf1ZRHlD9PVCmXlNdIz1KaW5pNDNN5d/pY5t9fW8fPppiczsBgAAgC5Jqq6Dd0mMkMfSSlKplWQsXvdmmYIrpCuyU0s6PdtvI+t2Y8W71hhJap1kWyIhzbeEVKd33XVXWrVqFf3f//0fffvttzRjxoz6hNK+X1vITMHttttOvTjwySefqKrsRRddZG6NPLbYr48oKiqivLw8NZZKsCTlznB2k/7HP/5BX375pXqhQaZcP/HEE+pjxlaVRUu+9gBtgQR4w/zEIVXdlrZKlPnGklHK9kmt1dT0ZyEvD0pl2Rk6k23KjucTXfAj/zHZkX+7DdfX1vGbLpvGb/2lPmf5oQwzaj1JfE97ZgYd89g0WlXS9l/OAAAA0IlkyvFpHyZGtGH6s0wPdrvdahpvLJmKK3r0kM04IhqreDrZyaFsHxRr7drY3S7b7p133lFV7LfeeotOPPFE2mWXXVSzrZSUFHOP9iHNqrbaaquoirI02xKzZ0dX3qXCO2/ePHtKr3ohQZJyZ2y99dbqNiHrl+XrJUm7VJvl6+Nca+zUkq89QFsgAd4w9rpcPdm/afLSllSA3+Fo+PJZ42TKtIg3Zbp95Zk8vmQZ0dP781+D3/Q5C9XVmlHrvTCd358xbVFrPnUAAACA9iFdk7fffnuVQDqrpbKO9oUXXqABAwaoJlStJe9TqrWxTbRkavSyZZHnQBvKTgjtyrCQirZUUduTTLuWxy4NqGzyOUpF1tm9WkhjsIqKivq9gCUZl6TcGdJkzCbdpWW6s6yrlj2HZe21c60xQEdAAtwyMtX5bg5Z3LE7hyxKkC4HJ3H8l2M9h5A9faV782B1Fk0SWakWNzb9WTpDf8IhTbakPfMhHDKtWdYdy/zj9zk2rhEH8G/X+N8S/nAlBUPNFaHjqwtG3s7nwat5AAAA0DlkGx6ZxivNmCR5e++99+jAAw9UXYzvvvvuNlUdZfrvpZdeSq+99prq/iz75EqHaVkTLEmjVJ3bwz777KMSTNkq6eOPP1bNpKQBlUztbivZAur2229Xnatlza8kuNK0S5qESeMrm6w3liZdMj1aOk7LfSXxlo7R8rik+3VLnX/++aqx1y+//EIXXnihuQrQcZAAt8w0ju04ZJHFFxySxEpFVxLgKzhsHhPxfnueziGt+OTt45H5ONIX/hoOSXZf49iFQ1riSeW4bdlna2zGH+7SP4nO+JzosEiDApFFVW3eCzjgSJwra6Nb3wMAAAB0FEnuvvrqK1UNlk7Jxx57rNoSSRLhv/3tb+ZerXfLLbfQzTffrPYTliZV999/Pz3yyCNqv96cnBxzrw0jnZqlWZUkvFJx/fvf/64qqPKx2koSYOlcfcopp6hE9j//+Q/1799f7c0rW0M5ybRr2ZpJqsOSeEuXZmnAJRX11pD3L9O35YUDmRIN0NFQjktusvfRnEa3QWrO3HeIXtczsF8P7kbbXvwKbdaj9WuBT3rqR/r2rwI1vny/EXTBnpEpNQAAAJA4mtvCBVpOtkmSpPW6666jK6+80lwF6WotTbYkgZeqcrLBNkiJDxVgaNzoyVSRrZPVLFc1ldUE1PiezxfQmc/+TCVVukN0c8qq9duJlr4NAAAAQFfx+++/07///W9VSZbpwY899hhNmjSJsrOz6YwzpAcqyDZTUlmWr4dMC3d2mQboSEiAoUmWP1sdM2UKdHWQ5q8tp/u//Iu++HMdPfVdy/YGLiytoP/6HqZrvM9TcWWdatjw8k/L6fr35lJFbdumVQMAAAAkCplS/fPPP6vkTqYSX3XVVTRx4kT67rvvWrUVUjJ78skn1V7AUgF98cUX1VRogM6ABBia5ErVCbBdAf59ZYk6FwvWlZtR48Jhi/ar/oCO9HxHZ3g/ph6FM+iqd+bQf96aTc/8sJTu/GQe/ba8mEJ8PwAAAICuSDomf/HFF7R+/Xq1v21BQYFqsjVixAhzD7j++utVx22ZIjx58mRzFaDjIQGGJnnSuqmjNMEqrQ7QgrWRpHdAbroZNa6wso4muiL7yK1fsZBe+nG5OSN6btoyOvzhH+jUp2VL5ZYp50T83ZmraF1ZjbkCAAAAAADQPCTA0CRvuu5cmOWSKdABmrWyVJ0LZ3fnxqwvr6UUtTOUluKKrAeWpPrVlBvpMd89NO+vhSqxbYlbPvyTLnplJu393284gV6K6jEAAAAAALQIEmBokjdNT4HOpmpaW1ZDs1ZFpkBXtGBbJGl6lUqRxlc9qZS27JNFOw7tTvu4f6bt3fNoP8/P9HLKzbSuNLIpfVNmLC0iF4XV+uFr351Lf3tsGtYSAwAAAECnk143kNiQAEOTXKl6CrTfFaBPf19ONYFI1bc8TtIp06QveOlXGn/DZ3TzB39QcVWAeroiSXMvVzGdvvMQGtk3mwa49NZIYrh7tVo305zaYIi2Kf6Q5vlPo2dTbqetXAvo52XF9OwPssUyAAAAbAiXy0XBYBBP4gHaQH5uQqGQ+jmCxIUEGJpmmmCJmopIIiviVYBlbe6Hs9aoRPjJ75bQwvwK6u9IdPt6SumAsX1oQG4a9XNcF+Xrl5lR45YWVNFR7ikqId/dPYve8l9Pj/jupdd/WqwabgEAAEDbZWZmqifwa9asUYkwALSM/LzIz438/MjPESQuvDyR3EZzzGE0erQM22Dmy0TvnKuGu9feQ8usPmosxvbvRu//fRdzpl337hx6dlokkR2dF6YPq040Z0ZWP6qtqSB/oMxc0N4fcz8dctQp5iy+939fTTu8tT31dEW/7RWBs+iUC66h0f10xRoAAABaT57Er1q1iqqqqtS51+tVe7aiogUQn1R9pbu1/YJRenq62uJJfnbikW2gxowZI0P5Z64MoGOhAgxN82eZgW5apY6p+gc63rrbpYX6PrZg8Uozcihf3SD5FaHSVWbUuGWr19Ynv8Gtz6KgXzfp2tU9m/LLatUYAAAA2kaetA8aNEg9gc/KylLnSH4BGic/H/JzIj8v8nMjPz+NJb+QGPAbLblteAV4yVSiZw9Rw+PqrqI//BNo31G96fVfVlKPzBT6+ep91G22Pe76msJFS6jYyqJySqcd3XPp5ZRbzK3GoJ2ISpYTlUUnx29lHU+9D7uJctJ9jVZy73n2Nbp0yVn65OhnqPLX1ylj0YdUYGXT1wd/R0dvO1jfBgAAAACQYFAB7nyoAEPT/JE1wFIB3p+T39PX3EBfpVxKKRWraeqCSOMq2Rapd8lvNNV/CU1N+ycNda2mPE6DGzjqf0TD9zYnEcHiVXTCkz/SQfd/R9MXF5qr0XylS8yI5Q0j7/A91LCHq4zC6yP7DQMAAAAAAMRCAgxNczTByqJqOq7/WhpZ9CUNda+l87zv0cn/+0ltdSRWl1TTXq6f1TjXKqVHU+6jPOda3d3/RXT6p0TZfYmG7m4uRuzqmU3P+W6j+30P0My/Vpir0TIql5sRyxtCKf3HmROicFHzTbQAAAAAAGDThQQYmuaPTEUenBmksd5IYprjqlDHlcV6/97lRVW0uSuyjncL10ra0z3TnLHdLicatIMej5pMNPFEohEHUWDYJHWpr6uIduMk+FDPNOqz4n11LVZmzVp1rPTw4/JnkSu7nzoX7oo1ZgQAAAAAANAQEmBomqMJ1unbdCfPutnmjGi9pRtQlVQF1LGgopa2cEev693LoxPgag+/H49PjRW3h+iwh4iOe4l8O5xLlMrvKy3P3EjkLV9tRhGVtUHKCpeqca3f3Dcz0pU6pUonxwAAAAAAAPEgAYameVM4UtUw06okWvmLGotM0pXfwkrdfbmspJAGxOzta6tN0clyXJvvQ/SvpRxLqNSt7+etabgGeG1ZDeW59JriUFp3dZTHV+rOVcO0mnx1jBWvWzUAAAAAAGx6kABD8+xGWPl/EjkqwN1cnBCzokq9BthTMF8dhbWl7hxtS8/pbUaNMFssVPt0ZTetrmECvK6UE2DTVMuV0UMdRXlKT3XMDkQacgnZl+2OD2bRP2+8mW5783tzFQAAAAAANlVIgKF5diOsRV/po5Ft9gUurNAJMJVF1uC6drqQyJduzohSsnSS2py6VF3ZzQqVUG0wpMa2z/9cV99Uy5cZSYCr03Ry3T1UQOGwpcbi07lrqe/0G+kx37209+zLzdWmSSMv6WYNAAAAAADJBwkwNK9+K6RIcilyPboCXGgqwOGqInVUcgYRbXmQOWEZZspyM6x0ndj2oFLKL9NTq8WKoip6/ofFlEu68VZGXqSiHEjX64B7u4qovCYy3XnBooV0svdzNd6uBdusfThrDe10+1d08lM/mSsAAAAAAJBMkABD8xyNsJy2pGV0oudzKjJrgD01jgRYGlqNO9acsPSWJcDubFPNdZXRurIaNRYL1pVTtlVBbpdOwr2ZvdRRBDJ0ApzjqqSq6si+w5ut+cSMtJpAdEU51nXvzeUfiDBNW1xIa0r1+mYAAAAAAEgeSICheY69gJURB5oB0c2+p4nK9NZH3toSdax1pRL5OIbuQdRjC3WNBm6vj83wd9MJcIarltYXRRLq6poaejrlTnPGHGuAVQdpo6Zcd4kW/qp1ZqSVlOuKdWNG1c2imf6z6Hbv4zSdk2AAAAAAAEguSICheY69gGnQTkR9xpoTzVuptx9KC+gEuNpn7u/xEp3xOdEFP0VPh25CRl5fMyIqLYisKc5aM53GuxebM5Ye2TLJk5ppRkR1VXqNsPDW6cdjKysrNqP4rvU8S9muajrWO4V+n7/IXAUAAAAAgGSBBBia56wAjzuazx0JMfNWFajpxZlhnXzWpehtiZS0HKKeI8xJ89JzI/v6VhdFEuBwdUzyatYKC29qZIp2rWMKdGogUg0WVaWNJ8DSMbpHONJFOmXlD2YEAAAAAADJAgkwNC/LVGU9fqJRkxskwJmBAlpaWBnZozc1Up1tLVdWJAEOleqp1SIQCJiR4VgD7E1zVIAdCXBaKFINFlUVjSfABRV1tMKKdKoeWTPTjAAAAAAAIFkgAYbmbXUS0U5/JzrmOT31OGS2PTJ6uUro12UllGv26A2nOirArZUz2AyIUipWmBGRVae3XBLW5vtyUh5JlFPSIhXgYFWF2grp32/OoqxwJBkWNeXRU6KdZPsje1snMSIY2dMYAAAAAACSAxJgaF4aJ7T73sxZ4f763JGkip5UTL8tL6Zcl96iqKUdn+Pij1Xj1vsHZ1SvVkdh1UUaWLkOf8yMNH96JAEO1ZTTlAX59MqMFZRjPx4jUBU9JdpJEuAersjtOVaZmhYNAAAAAADJAwkwtN6wvXRF2JAK8KzlBZTt0hVUV0bbp0CTy0Wl/n5q2L1ubSQJDTi2JfLpBNmWmh5ZoxyqraBv5q8nLwUpj6KnQDeVABcUFanO0zZ529pmtk0CAAAAAICuBQkwtB4nqaoiPGxvddrTVUqF6yNbDvkyHVsUtUFNxgB17E/5VFhpplsHdQIckm9Zr1+Nbf6MSAIcrq2kH+cto2/9F5PH7BlsC9VEJ8RONSW6k7Ut1RWgsorGE2YAAAAAAOh6kABD22XqPXulApztikxR9mVswBpg5s7TU6wHuNbTgrU6aXUHdHW5ljj5lQTcwZ8eaYJVWFREO5R9Qn1dkT2EbZZJgGeuKKHlhZH1viJUFp0Ai5riSFdoAAAAAADo+pAAQ9tl66nKvai4vgGWSM2M7hLdWjn9hqtjmquOFi5ZosZuUwGudaeqo5PLl2FGRGsKCmkv92/mLFpdZQn9vLSIJj/0PR30wLdUWRs0t7DySAXbVlOGBBgAAAAAIJkgAYa267GFOshU4zHupWos/I41uW2R1WeYGRG9/dUP9NR3S8gT0glwwBU9/Vlxu6mKdGLc18qnndxz1ThWVXkJXfra72pcXhOkWSsjU5zd1QVmFBEoRwIMAAAAAJBMkABD2/XUCbCY4F5oRkQuf6Qrc5s4ukzLNOj/fjafXKYJViBOBVjUuPT1/dwzyOsKq3GsLFc1LS+Knvps89Q23CIpWNEwKQYAAAAAgK4LCTC0nakAi/GuRWbENjgBHmQGRAM5Aa6qC3ECrBPXoCdNHWPVuPT1TFeNOtaldtedqve9haxeo9S1THJ0kmal1QEzIkqpKzajiDASYAAAAACApIIEGNouJYOom05Wh7odTaRSIk2p2iQ1myzZe5gNdOWrY6pLd4MOeeJXgOtiKsOesUfpTtU7XUiuzF7q2gjXCv430hm6tFq/z7pgmNJDukFWqa8XhSzdZMtV3bCRFgAAAAAAdF1IgGHD9BxhBg7+DUyAmctMgz7O+zVd4n2D0kjv0Rvyxq8AB2Iqw56xR5gRM9s1beZeR9u45tN7KVfR/b4HqLRKJ8DFfMylCjUOpuZRCenH70YCDAAAAACQVJAAw4aJlwA7ujK3mTdS0b3I+xb1cOmGVZY3XR1jBTyR61WpvYkGbGfO2IgDzYDoDf+NNM69hA71TKOUgj/UtcKKOspx6QTYSsujddRdjfuVzCAKh2lFURVd9Mpv9MmchlslAQAAAABA14EEGDZMTAJcK82o3O3wbbXZLmag9TP7+lq++BXgkCMBptGTox9Dj+FE3Tc3JxG1VXra82d/rKUcUwF2Z+TRJ5491LhHzXKiBR+r5Pfdmavo3Bd+UdcBAAAAAKBrQgIMG6ZHdAJc52mH6q/Y/hxOZB3TmG2++BXg3NwcMyJKn3iMGTmMOMAMIsJVJbSmtJoe/WYR5ZoKcE73PvRDtwOp1NIfp+Kr/5J/5fc00382/dv7slovDAAAAAAAXRMSYNgwjq2QRKCRKcqtJo2rjn6aaNuzzAUtKyv+HsMDho1VR0sqvf23VuMojmnQNndNEd31yXyqCwSpG1Xqa+m5dNak8fRCaJI6z8z/hV5OuYVyXJV0rvd9KqzUa5EBAAAAAKDrQQIMG0a6NWf2NidE6ZmRSmy7GHu0GWj9eur1uQ3seCHR5EfJdcLrRC7dxTnKwO34seaZE60gfw299dsqyqIqcrtMd2i+z36j+1D//S6hWsurrzmsL9WVYgAAAAAA6HqQAMOGc6wDTs2IX6FtM0lcTUdopZE1wJSSTjThOKK8IeZCDLeHaIv9zYlmT3vu5dHVXyVdJ8mTd92KFvY7RI2dSgqj9wZ+dcZy2vqmz+m1GbLFEgAAAAAAJDIkwLDhnOuAN3QP4FhSzXVWgRtZA9wiMeuAc6hcHQ925syOKnHP3aOnX4vy4nVmpL3KiW9hZR3d/OEfVFEbNFcBAAAAACARIQGGDefsBN0OewA34EyAZW1wW0kFeNRkc2JXgC2aXPqcvkCcbDvWNHcfupUZRVSVRleAK2tD6lhWE6QXpy9TYwAAAAAASExIgGHDORPg9q4Ai15bEk1+hGjXyxpMY24VbwrRMc9SQZ5ukpXnKqejPd/Q4PLf1DltdzZnxZvpMfOkNJxuXVteaEZaZV2k6vvkd0uoJqATYgAAAAAASDxIgGHDOadA+7PMoJ1NOJ5o72uIfKnmQtu5M3QjraGu1XSV90U1pqx+RHtdrccOsY2wQhXRCXB1bZA2c63hH6QwrS+vpTd/XWluAQAAAACARIMEGDacTEvuOVKP++jtiBJZSlYPdezpKlPbGykH3kmU2rCB1yuu6IpzqKrIjLQLg8/QFP8/6UqTSMuewsEQ9goGAAAAAEhESIBbZgLHhxzLOao5JAuaxnEiR3NO5ZA9duJFH45Yx3LM5KjhWM1xH8dGmFfcjqRR1akfEJ3+GdG4v5mLiSs1p6cZadUDdyPa8mBzFi28+5X0bHAfc8afanWxGfFtYYu2oj/V+GTv59STSmhFUTV9OHuNugYAAAAAAIkFCXDLyOa2ss/NlRwHcpzMsZTjeY6G82bjO41jx5iInk9LdALHyxwzOKRl8Q0ckkC/xZHYMnoQDdo+/h68Ccbby1SrDc/mezf6uE/cbSSFD7iLyl16arevrqS+wlsTDFE61apxCgXp3LQv1fjhrxep5BgAAAAAABILEuCWmcJxLscLHF9zfMBxHMePHGdztMQcjukxEeCweTju4viMQ/bfkY/zGMf5HFKCjN7DB9puwDZmoKX0H29GDfk8bjpt5yFkme2RulEF5ZfrpFc6QKe59Fic4PmC0qiG5q8rp6/m5ZurAAAAAACQKJAAbxjZE6e9Nn/dgaMvx9PqLOJ1Dtmv53B1Bhsub5gZGH0bT4BtVppMApAEuJK++6uADrr/Wzr28WmUrmaqa6nBUjoh9Xs1fuSbReoIAAAAAACJAwlw68jXS9oCyyJSqczux3EHR0tI1Vj2yJH1wzKleQyHk30+yxxtUiWexxF7f2grt5vCvgxzwtJ1dbcpnky9briHq4z+/dYsmru6jBatr6QMMwXadr7/U/4mCdMvy4qpoCL6NgAAAAAA6FxIgFvnYQ5JSGV+670c/+CQacpNWctxC8eZHHtyXMOxLYdMgXaWHvXePDpBjiXX7Nsb04tjdEzElDrB5j7xTaL+2xAd8YS50rSUbrpfWU9XCdnLeyXR9bv0LPbaNPnyE+XVrqRJ7l/U+FdOgoVlWfTOb6tUUgwAAAAAAJ0HCXDr3MohyetBHP/jeJDjMo6mfMIhjbKkAjyV4yGOXTkkjbqRI1Zj3ZOa66okFWlZZ+yMdzkgnsE7Ep31JdG4Y8yFpvlMApxHZSrxFc7pz+s3P5bI302Nz/J+pI6/LNcJ78dz1tLFr86k45+YjqowAAAAAEAnQgLcOrIN0s8ckuGcx/E4x20c0fvqNE86SH/HIet+bXZH6HiVXpmjG68y7CTVaZkm7YzDOKAduLJ0AuxxWXTWVlmU4nFTmmP6syuzN9E20rCbaFv3fBrvWlhfAb7/y7/UsTYYpq/+RHMsAAAAAIDOggR4w/zEIWuCh6qz1pF9d3QpUZttjmPN0Sbvf0sOqeg2RTKruTGBTkztJVNPcRb/2TWP+nRLpXRHB2hvagbRdufwT5T8d+kq8J9rytV2SEWVdeqa+Oav9WYEAAAAAAAdDQnwhpE1vZLELlZnLTeEY2cOWQdsky2V1nDoMmLEURyZHIm/F3AykwqvrXQlneH5iI736H1/hS89i6hbf6IxR6rz/dwzKFxbQd8vKqCK8lK6x/cw/dP7Gk1fsFatCQYAAAAAgI6HBLhlZKrz3RyyYHR3DslyXuE4ieO/HHZZ7ykO2RZpsDrTvuC4lmMyx14cF3HI9GfJgqQhlk06RF/BsT+HNNbag0P2A36E43MOWUsMncVRAab3L6JTyh+nc7wfmgtE/jROgMUoPevc5wrRRPdf9PT3S+k4z1d0hOc7+rv3Hboi+BgVVEQqwgAAAAAA0HGQALfMNI7tOKSBlSS0T3LIolBJgCVptXlMyPRmm0xt/hvHcxyfcsj9v+LYhiN2WvMLHMdzyNpgua80yZK3O4IDOlOGIwGubLiONyVNivRs0I76yLZzz6ev5uXTbu7IzlZHeqbS0vwScwYAAAAAAB0JCXDLPM2xG4c0u/Jx5HJIhVYSVieZvizJrzS5sl3CIVsSZXPI2/bnkMR5AUc8L3PI9kh+jr4cUjGu4IDO5OcEN8UkuXH47ARY9hTuKUu2ibZ1zeP/xDra3v2nOhdeV5jWrVxozgAAAAAAoCMhAQZoqf5b6eNmu1I4VV4DcfBlmAGT/YXZCPcK2sY9n1LNXsG2sjXN9CYLh4lmvky0eqa5AAAAAAAA7QEJMEBLHf0s0YlvcrxF7h6bm4tGiiMB7j5MH1zldJBbeptFCxUuMaNG/PQY0TvnEj0/me8cnTy3KzTjAgAAAIBNDBJggJaS6c3DJxF5U+qT3Hop6WbAHLcd75Xl3pxr9h1PIfPj5iuT7aQbIUnpT0/ocXUxUWWBHre3314gunMI0S+c1AMAAAAAbCKQAAO0RffhZmA4p0DnxSTHzLX5vlSaIn3TiLJrVjW+FdKSqURFjinSVYVm0M7evUAn2O//w1wAAAAAAEh+SIAB2mKzXczA8HjNgOXJNs8xhu1F1RkD1LCftY5KqxuZ2vzLM2ZgVG2kCrDTxpxmDQAAAACQQJAAA7SFaXQVl6wHzpIG3oY3lWjAtmSZaz1dpbSyuFqNo1SsJ/rzfXNibIwKcKDGDIyCv8wAAAAAACC5IQEGaAup+GbIrliNGLK7GbBhe/H9fZTSTU+B7kGcABdVqnGUmS8ShaOrsTWlDfcc3mBlq8zAyP/DDAAAAAAAkhsSYIC2Ov1TotFHEB33qrngcOCdOgn2pBBtc4a6lNldtoAm8ruClL8+JrGVNcG/6oZUS6ifOorqkg1PgPNLq+jzab9QVV1QXyhdqY+GtW6uGW2AosVEC7+QB2wuAAAAAAAkHiTAAG0l3Z6PfppoxP7mgkNqN6KT3yX69wqizSepS2m5ugIsygpiqrDFS3USyV4K7EEllm6qVVe2gQlwoJrWPnQA7fPpXjTjuSv1tZgEuHhNI9sytXSbpJLlRI/uSvTCkUT3T9RTuQEAAAAAEhASYICNxeUi8qWaEz7N7GVGRDUla83IWDnDDIimh0dRoZWtxqHKDVsDHPj6DhpXN1ONd1/5GNGa3ylc6OgyzYqKYhptSeL76klE947hG5vZs1hMvZsz9Qo9ri4imvOmHgMAAAAAJBgkwAAdxZEAe2L3913xozpUWyn0pzWIiilLnbs2cB/g6iX6/drCr59Oru/vM2dGbZkZGLJG+M/3+Liy+W2SwmGiWTFTwOe8YQYAAAAAAIkFCTBAR8mIJMC+mphpwit+UodZ1lAKkpeKLZ0Ae2uL1bGtaiuj1+S6ixaSywpRreUzV4j8wXIzMuocDbrWzjGDRtTx2wZNV2mPXx+lmi1TugEAAAAAEgwSYICOkp5HIfKoYVqdY2qzVFHXz1fD2eEhNLh7OlV6u6lzf92GJcDhGp3crrHy1FFUp/enI+uuozdDu6rz1JCZvmyrKTUDVstvP+9DonvHEs140lx0cDa92lY3+1LmvGUGAAAAAACJAwkwQEdxe6jal6OGmcEizntNk6nSFUShWjVcbPWjQ8f3o5BPV4D9oTjbJbVCSlC//ZTQeLopcCK95j2E7h/+FM2xhlKZla5uSws7PsbS74iePcScMNmW6d0L+DEuJ5r2kLnoUONIgAfvRNRzSz1GAgwAAAAACQgJMEAHqvV3V8fuVEplNWbP38KF+siWWH1odL9uRKm6CZbfquHk2Gxf1Aap4Sp1rKRUeip0IF1RcRw98lORulZGOgFOt/g+UoUWzxwUmdJsqzZV6HgNuZzV4lRO7sccqcfrZtdXtQEAAAAAEgUSYIAOFEzrqY49XKVUVFmnxs4EeFG4Hw3rmUEukwArsU2qWiocojTSyWzP7j1o68G5amwrNxVgN1l6LW9zajnZDZmk3eacAi1bP9kJsEA3aAAAAABIMEiAATqQlaET4J5xEuAKK5UKXDk0qHs6eSSZtLU1Aba3JmKu1Cx687ydaPp/9qZHT9yarjxwSxrQN7IvcVQltylVMVVgxxTognCa3hu5z1h9Ycm3+ggAAAAAkCCQAAN0IE9Wb3XsQZwAV+h1v5T/pzrI9OeBeRnk93rInRZJgEPVcRLgP94leutsopIV5kIctZEE2ErRa4r7dEul/cf0obN3G0a9euhkXASkW3Sg2pzFyO5vBiwmAQ47KsCHP/UHhWRdc+5m+oI9dRoAAAAAIEEgAQboQL4cXXX1u4K0cMVq+uGvdRRc+Yu6Jh2gh/bIUGNPemQKdFW5XrNbT6Yhv3ay3n/382vNxTikg7PNn2kGEe503ZBL1MjHiLfn8MDtifa92ZywmPsEKnWSG7JctLLKTU9+u5g/lkneW1pVBgAAAADoIEiAATpQem5fMyJ6Y+qvdOP/3iJvUDeq+s3anHYe3kONU6KSU8c6W7F2lhmwuY13Ww44Kscuv64AO3nTI1Xm4KrfOLmN2ZuYBU79hKjnCHPGYirAgQq7oVYGWfzr5O7P5lOFWyfxbZ66DQAAAACwkSABBuhAKd30FGgh06D3cf9szojWZY+lE3cYrMb+LEcCXBGTAC+fbgaRNcXx1Mq0ZsPtbKplpGREmmLlfns9BWc3bFr11HdLOGvXSbkSkwCHqvTHKLV00hsIWbSw1PxakTXIG9DBGgAAAACgvSEBBuhIGb3MgOh/3Z+jf/reUOMqXy7dcuYRlOrzqPP0rDx1FHWORFZYy6eZEVFl0GVGDdVWRSqw3rSGCbA/M7ortHf6g2YU8fjUxVTtdTTkikmALbMG2N5SScx23gVVYAAAAABIIEiAATpSZqQCnFmxTA9Scyj96MdpYPfIOt2M7EhyGjRV1pXFVXTs49OodOGP6lyk1hQ0WmUNVEbW4Hoda4pt/uyetCLceAVZSKfqU5/7jUrNlkmNdYGWCvDY/jpRnlNgqaOyKa0DtvjzlgAAAACAhIUEGKAjpecRefzmhI09mujCn4m22Ndc0LIysyhg6Wqw3QX6n6/+SqOXPU85gXx1LryuMFFl5Nwp6FgDnBInAc5M89NRddfRUbXX0vTwSHO1oR+XFFGhZd6+Yp0+Gh7ZG5hJBXjyRN0tuli2Q7JtKhXg4qVE944hevYQtf8yAAAAACQmJMAAHcnNSa10VR62F9GJbxId+SRnog2rsN3SU6icdCJp1egkcuSKV+ka34tq7GSVrTajaM7tk/wZjmnMRlaql9ZRHv1sbUlXBM6mKiuSmEtX53PqLjZnRIusfupoLZvGCR4n3YZfKtBsvZVD+43uTak+Nz/uyHToTaYC/NY5RGUriZZ+S7RurrkIAAAAAIkGCTBAR9v+bKKT3iYaPslcaCgjxVOfSLrqyqiwopYu8sbv+Fy6zkyljhE22yDVWl5KTzOdmR2yU31mRLTc6k3/CZxBZVY63Rc8graufZQ+DW9nbiX6OjxRHV1SbV7zmxpTXSWlBPXHyLdyqWeWn3YZ3oPfh+NjmeQ9qcl+yysijcmo8C8zAAAAAIBEgwQYIAG5XC6qdukE2F1XTjP+WkUZVK3OY9XO+9yMovlLl6jjesqhdL+eTu2Uxkn2DYeOpoPH9aUjJvand8O70PjaxzkBPopKKLJtkqzt/TKkE2Dlry/0sXytPrIidy75vR7ae2RvKjOVa2VTqABL1depAAkwAAAAQKJCAgyQoKrNfrq+QDmtnf01pbgia0uvCZxan5T2WPg6UXFMFdiyKLdophrODA+njBSvGsc6ZafN6MHjt6K7jx5Ph4zvp/bydbr24FF0+X4j1FTpJWHTwGvN77rxliMBLvfpadx7bdkrugK8Rj+GpLbiJzMwChaYAQAAAAAkGiTAAAmqxqsbT/mD5ZS2UlcZZW3uuJrH6fnQvvQIHa2ueawglX52mxrXK1lOabV6fe6v4c3jVoCd3G4X3X/sBHrqlG3MFe30XYZQ7+xUNZ5vDVJHmv8h0QNbES37QZ+z6lSdAMt9B/WNdLqmnx4n+vw6c5KkVs4wAwMVYAAAAICEhQQYIEHV+UwCHCij0TV63e1sayiVkd4u6cqzjqcvQpyIsow/X6NQoZ7yrDiSMpUAm/2FmyLTrnfdvGFDru6ZKeo4zxqojkrJMqKvbzYnRLVpkaS3X15kOyfl+/t0lbRsDSfETxCVR3eS7pJkuyOZCv72eUTLHet/ReEiMwAAAACARIMEGCBBBXy6c3NPKqIx7qVqHNxsdxrVN5tuP2IsbTUol5aM+Ye67qUQLXrzejVWVui9gmstHy30DCWvp2U/6inehvfLTU/h5JgT4LCpAMeQj+FOyzFnurnWeium67R0Rn73fKKPLiN6Yi+i0pXmhi7qhweIXjyS6PeXiMIBfa3POH0MVPJ/VK0eAwAAAEBCQQIMkKBC/oZbF43b7TD66KJd6djtdDJ6wuGH0Lce3a156Kr3aPXiP9TYXpc62xpC3bvFVGSbcepOm1Gm30svnrm9Ove4XZTHSfCf9hToGPlWDmWn6SqxyOIE+KbAifSLtaW5wtbOJlr0lR7LdkHTHtLjrmrVz/ro9hJteTDR0c8STThBXxOmAzcAAAAAJBYkwACJKi06Aa51+Sll8A7mTEtP8VLWfteosdcVpiXv3Ky2J7Ik4WS/hDennYZ1V+OWuv7Q0fT7dfvSzsN7mCtEPTL9tMzqQ+9nH0s04iCify4ga6BOkH+3hlGv7MgewtlpXnovvDMdWXstWWl5+uKs1/TRtn6+GXRRsvWRkKrvsS8SjZ5MlOr4/9pU9j8GAAAA6GKQAAMkKFdarhlpa7tNJPLphlROE7bbjeak6rXAA8tnEq3+jVyW7hgt6393Gd5wXW9zpOrrNKKP3hbphqqjyZKEL6s3FR/1Bp1R90+6MnAG9c+JbH3k3F84nNFLD+piKqKyhrgrqzMJsN9RXU/Va7YVVIABAAAAEhISYIAE5UmPToAr++1oRg1Vpg1Qx3SrMmpbnt+s1leA4xk/UK/xLaiopdWlNWq8usKiL8NbUxllRCXAWamRLZfq0kwCHKtkOWfHkW2duhy7ApwS2S+Z/I5xbZkZAAAAAEAiQQIMkKBSMs30YcPVe7QZNRQ0iVimJMCmA/RKqwf17rcZ5WZE1ue21fgBkem9r/y0nOauLqWVxdXmClE/ZwU4LVIBrvFHplErow/Xx1AdUfkaPe6K7AqvM+n1OyrANUiAAQAAABIREmCABJWaFV25Te87wowaCqfo5CvVFSBrid4z+JfwFlHreDfE6H7d6qdFP/DVQjro/u/ovi8WqHPRPzf+FOiqFMfnkM6PZfzx5oQV687WXZI9pds5BTqqAowp0AAAAACJCAkwQIJKzY5OgHMHbG5GDVmOBkwuk5zJ+t9dN2+fBDgtxUNbDYpsdSTmrdUfR7ZO6u6oMjunQJd5HR9/y4OIug8zJ6wrJ8D1U6Cda4AdTbAwBRoAAAAgISEBBkhQmTnRyWtWWsMGWDaXM/liActDX7m2p60HR68j3hB7j+xtRtFk/a9LNgo2ujmmQJc4E+BRh/In0cecsMoCM2hGOEz01c1EU+7gTN8yFzuR7PFr7/3bWAUYU6ABAAAAEhISYIAElZ0enfA6k8xYrrTo6uxH4e1psyHDKdXnMVc23KSRkYZW5+8xjI7ZZoCaFj15Qn9zVXNOgX5g5VAKb74f0VYnEw3dk0KeNH6w5jG1tEr602NEU+/iBPhWorWzzMVO5JzebNb9Tl9cSM/PWENhj9kOChVgAAAAgISEBBggQUkzqe9DuvHVjYGT1LEx3vToCrDe/7d9pj/bhvfKopsmj6HTdx5CF03anO48ajz9ceN+auyU6ZgC/cPyarqQ/kXhg++nh6cuoeFXf0y1ngx9Y0vXyX5zpxmwwkVm0Imcjzslkxbml9PxT0yna96dS8VB86IFEmAAAACAhIQEGCBB+TxuOjtwKR1Zex09E9rPXI3PmxE91XmN1Z0mmK2L2tNJOwymaw8ZRX6vruLaR6fYPYQ/mr2WPpy9hu78ZL6awZxfZ1dJW5AAVxURVXPYqovNoBPZewCzOYUh+uLPfAqbmdlllp0AtzC5BwAAAIAOhQQYIIH16N6dfrFG0Jm7DTdX4kvJiE52V3MCvEVvx/rUDjYoL92MtDs/nWdGRBVkOka3ZJ1sRb4ZGLHnncFugMXu+GoV3fNZpBt2OZnPG2uAAQAAABISEmCABPbK2TvQ/cdNpEv32cJciS92z+CatL7UPdNUWjvB9YeOokPG9zNnRCuKInsGl9sJcEumCQeqzMCoTIQEOFLdrbDSqC4UNmf8uVkmAcYUaAAAAICEhAQYIIH17ZZGh3Ii2Vwzq4wMRwdi1rN3XzPqHHtt2Zse4MQ9XhdqSRqVlkwTjk2AE6ECbO8BzCx/Jvm9kV+jpWTWN6+cQTT1bt3BGgAAAAASBhLglpnA8SHHcg4pZcmixGkcJ3I05wiOlzkWcsjbyuanL3LE29R1CoesJoyNTzgAGpXujzSeElv00d2JO9vQHiYhZJIo5mWkRKYJt6gCHKkci0DpGqLytUTzPyYKma2IOppjCvRmfXvT9P/sTd9cvgedsuNgeiW0J9VYPv6pla2bbuKf/GP5cQbNvQEAAACgsyEBbhlZYLmC40qOAzlO5pBE9nmOqzma8i8OecZ/C8f+HHL/iRy/cugWv9EWc+wYExdzADQqIyYB3rx3dEW4swzpGUmAZUr0CH5cTVaAf3uRfzLkx8qIrQCvn0f04LY6sXz1RKJwyNzQgRyP2+3PolxO6gd3z6Be2ak0NTyeDq+7kcK5Q/Ud/vqUaN77egwAAAAAnQ4JcMtIZfZcjhc4vub4gOM4jh85zuZoyiEch3E8zfENh7yPSRyyQPMSjlhS8poeE5EOQgBxSHX1heDeanxz4ATaolfnNcByGtU3UomWDtJ9uqU61gDHJMBLviV693yi9y4kWjFDX4upAPuClZHK8YJPiGa9qscdRRLuP3VCW2v5yJMWeaEh22z/9Kc1mAqPdSS9r59K9PZ55gQAAAAAOhMS4A1TwNHc/MZ4ixZXc6zkGKjOADaQy+Wiq4On0441D9CToYNoiwSpAO+2eU+69uBRqpHX+IE51Ds7NVIBDtZwYnhupIprEktl+Q/6WMcJbyy3o9q9WF6b6kCLv+bkXF6TInoptBelp0Yajcm+zbZS6kbkNVsiid9fIipaYk4AAAAAoLMgAW4d+XrJs++eHOdzyOasd3C0lsyPHMwxV51FG8Yha4wlsV7EIVOnTcYA0BQXraHuaiTTchOB2+2i03cZohp5id7Z/sgaYPH7y5z4vqfHzj1+UzmBZKG6yBTo1VYe/ZWzC9FFs4g231dfXPWLPnaUYln5oD0WPDhq6nl2aiQBLq/lH9/0HubMiKlmAwAAAEDHQwLcOg9zSOcdqerey/EPjsc4WkOeMT/FIZ105H04fcdxKceRHIdyfMRxBYc0wWru/6oXh6wpdoYk0wAJo4+zAmz7TVYFMGcCHKxVh/LySKOs3Wrvo0f73UrUrT9R/631xcKF0W+3sVUWmgF/aOoWnQCnRcZlNZwAZ+gXI+phayQAAACATocEuHX42Tdty3EQx/84HuS4jKOlXByS/O7KIY20pLGWkzTIeoRD1hlL8vt3jn9z7MYh64ibIhXpOTHxLgdsIm44dLSqsD5+kkkOE1DvbpwAx05oWPilnh7sTGRrStUhWKunQNdZHgqSlwoqdGJM/bfRR7H6NzNgS78n+vFxfsM6c6GdVcmqB05wrXQK8OPJSIlsT5XlqACXVQcaVoBrkAADAAAAdDYkwK0j2yD9zCHJqXS14WfadBuHTIlujiS/T3LI1kmncrQ0OTXlMdrBHBsj1ekxMdFc0gxJ5JSdNqMfr5xE+47uY64kHqkA+xosm7eIfnmGs0ZZGm+YBNiq1VOga1TPOKLCSpMA9xiuj8J+u9oKomcOJPr4cn5/0nNuI6jUCXChpddYNzYFuqyGE+CM2ARYf04AAAAA0HmQAG+YnzjkGbDZ86RRdvJ7GseZHHZS2xphc2yMTMuWNcXOkDXEAAlD9gGeaTmSV9vP/yMqb5gAh80a4GrSa5oLyk1lNy1PH0WVLJlnxY4mUz88YAbtrEpPgS4i3d06s7Ep0NVx1gDXlJgBAAAAAHQWJMAbZk8OSUxl797GSPL7BIckv+dwtLY0dYo56tazAF2YbNe0zt2LTq27nN7a/A6iI+RHg8Wuj7XPzT7AVVakAmxZFr+jLP7tZRLOajsBXqaPwtmBuT3ZCbCpAKc7EuA0n4e8bvlx51xeKsDyGJ1QAQYAAADodEiAW0amOt/NcQzH7hzSpOoVjpM4/suxnkPI+l6Z3ykdnm33c5zBIYnvbA6ZymzHRA6brAuWZleSJO/DIfsHy7RmWXf8FYdjjxiArkm2a5Kq6ZTwRPolfWeikYdGV3Ntkixyousxya09BToQsuiBrxbKO4q8nUlKoyrAGysBNlOgiyy7AhxZAyyfm70VkpoCbZntnWxoggUAAADQ6ZAAt8w0ju04HuL4gkOmM8tCS0mApUuzTZ4NS+gykCaJrDidQ96PM97msK3hkGfM13BIsvsaxy4c13IcyNHcFGiALsFuFlUhWwX5OFGdKMviY0jDqA//ST3yv1en9hRocc/nC+iRKYuI0k2XZXsKtHOfXdljuL1J5bl+CnTDNcAiK1WfqynQ7siaYAUVYAAAAIBOl6wJ8JYcL3NIUimLBrfiENdxyLTl1pLqrXRilmZX8qw2l2MPjti1vNLcSpLfyGahRJtxyLV4IbfZFnJId+kBHFK+kla54zikAmw6/wB0fXaSWC5bBYmt5ccmRv6fRD/LhApNpkA/f8Z21CNTV4Lv+GQe5YfMfsJ292jHHr1UvtYM2pFUcMOyC5o0wdIV4IyU6ATYboSlKsDyefkcex4jAQYAAADodMmYAE/gmMEhU5WncETmKBJlcpyrhwDQGezGUWqdrOg+jGiPK4l6jyUatJO+FqzWR6Oa/DSqbza9fNb21D1DV4N/LzS/vqQCXFtOtE52/jLq+FyutScz/VkUx+kCLexGWCuLq6nYnUt0MT+mPNMjDwkwAAAAQKdLxgT4do5ZHNJqVqYoS6XVJl2bZR9fAOgk9hTo+gqw2ONfROd9R1W97cka0Sz+MU71eWjz3ll0/3F66XxBSF7PYjIt+d0LiCrW6XNbbBU4HJKNhc1JGzimWK9Vk0AkAXa+vkb1FeqF+RW00+1f0W3f5FM4x0z0wD7AAAAAAJ0uGRPgnTnu5JD2sZZccJBnyIm7SSrAJiA7dgq0kV9WQ4/9GKmyOvVwlaoEWOw8vAcdOr4flagJHawyn+gPva225Vx369xXWKrE943TYU+Zbq1Vv5gB0ZzwEBreK5P83ugE+II9h9Pofnp6dHUgRI9NXUxTlpn1yKgAAwAAAHS6ZEyApeJrNgttQMo2WE8L0IkyTQKsmmA5PP3DUioMydJ3Y8xRZkDU21VCHrPFkDh7t6FUbJkE2LByBtPZLlnmb1TazdnZt//lhHglf9C1RPM+MhdbySTAS8K9qZST7/1G91bnTlv0zqIP/r4LPX1aZKLJ2lpdFbaKFhEFoqd2AwAAAEDHSsYEWKY/H66HDezPESnjAECHs5tgSQKs9vQ11pXV0JTweFpp9aDVedsT7XuzuYUog6K7OvftlkrFphOz4k2jFfs+Qb9U9jAXmGPNLi380gyY2Vu4RfLnET17CNH/jef3IQ3giX63hqnjpJENE2Ah2yHtsUVPSvXpX68LrIHq6LLCRJ9epcYAAAAA0DmSMQH+Pw7Zd/deDn7WqgziuIxDtiKS2wGgk9hrgENhi6rqInvlllYFOPntRbvU3k/vjHuY79iHVqfKUn6i2z1nq6NN9ttdFO5nztih99Mi9xA1LTpsmUpxlUmApRnWek5kbbFrhZvywwNES6bqDtNmX98fwyPVcUiPDHWMR5Lg7hm68vtSaG/6PWwaYc15Q69FDgX1EQAAAAA6VDImwK9yyF66F3BIN2jxJsctHDI/UvbYBYBOYneBFq/MWGFGRKtKItODCyvqJIukBwb9Hx1Qext959/V3KL5PG6a7xtJf6+7kF4afg/RuGNoeVEVhflXWnH92mAzBXrlz/yPox1AueyO1kL5c/Uxuz/RtmfSF4MvpTdCu5PX7arf8qgxPTJ1t+o68tELoUlqrNYBL/qa6L4xRA9tRxTYCPsVAwAAAECjkjEBFrJ3rpRcpGx0Ncd5HFtwSIdoAOhE9hRocdMHf9DMFSWqGrykoNJcJSqq1Mv4S8Jp9Kc1uL4BlpNUgd8P70S/pGyjziUBFvYevZY9BXql/TqY0dI9gsNhovUL9HjEgUQH/Zc+y5pMAfJSXkYKuR1rkuPpbjpCix9Co82IvXikTsILFxIt+MRcBAAAAICOkIwJ8G4cUgJayfEUhyTDj3Ms45DrcjsAdBJnAiwembKQZq8qpdogJ5xGQYXuVVcT0NOE7fW0Tt04ARal1Xo/4WWFOgEuIp0AB8tNBXjFj/poK2thBViaZgVMUt5zhDqoyjRzJreNsSvAYhX1pNI0vRY4irthYg8AAAAAG08yJsBfc4zSwwbkWazcDgCdJM0XnQB/9sc6uudzU2k1JNGsqgvSt3/pKm5qzHZDQirAoqzGToB1slpo6eZYoQp+W2my5di+SGnpFOj1882A9dxSHQpMZdqZ3DYmz6wBti3J1pXqKJ7m3w8AAAAAtJ9kTICbmpcoz5gjZSYA6HBbDc6hMf2z67c1khx16gLHlkVsZXEV7XffVAqG9drdeFOg7QpwWXWA5qwqpb/yK9R5kZkC7a7mBFimQdv7/qZ208fqIqJgC3ZDkynKth6ygkISc/12PVpQAZZ1wk5/pk00IwdsiwQAAADQoZIlAZZnvNLpWUL04bDP7ZDq7ykcLVwACAAbg9/rofcv3IUW3Xog7Tsqeiuh3tk6sSyrCdKKokhy2NwU6Ae/iiSr9hTolLpSovw/1FgZ4lj9ULbaDJpQXWIGLENvr1Q/BTqj+cpt2LHFk5jpGWdGDkE0wQIAAADoSMmSAF/CscSEPOt823FuhzwTPofjWQ4A6ESyTZA4dw+9p65IT/HQcdvZr2FF8zdRAV5TWkOfzNWvax251QAqMQmwsuInM2BD9zQDVhrpPt0o2T5J+DL4N6VHTcmuNmuSW7IGeEQfxz7FbHVdOlGfsebMQAUYAAAAoEMlSwL8GccVHP/ikGfWD5pzZ1zEIc+ApSs0ACSArQbl0l5b9lLjY7YZSDsO7a7GKV437TRMj0Wdo0GWzU6AbTLj+II9h1EoNc9cYSum66PbR1MDeh2vUiw98ZpRZxJgv05k7eqv6N6CNcCHjOtHJ2wfSehLqgJEQ3Y3ZwYSYAAAAIAOlSwJ8DSO/3LczXEDxx3m3BmSFH/DAQAJ5KHjt6KXztqerjpoJG03JI/eu3Bn+vqyPejkHTcz95Aqb8NEMTumm/TBnHAO7ZlJ7oxcc4WZBlhl6QPpjPcKKGyZdbkly/WxKXYF2K/3FV5bFpmu3DOr+QqwbJN0y+Fj6fCJ/dW5dLr+wRqjxvWCSIABAAAAOlKyJMBOkgC3YIEfACSCtBQP7TSsB/k8bjU1etyAHOqfk8bJbIa5ByfAJQ3XynZLj64AX7DncHVMyXBUgE0DrGmleWr/3rVkkuMWJcC6qZZdAV5h9hkWA3PTzKh5zvXCl//cjazejj2BUQEGAAAA6FDJmAALWTB4MMflHNfGxDUcAJDgBndPNyOiiYMcVV1jbP8cTpj5h93toqsOHFm/5jY925EAG4utvuq40uqpjk0mwNK86tUTiRZ+rs9TdAXY2ZRrQG7ksTXnWMe65lUVFv124Af8m9dUr5EAAwAAAHSoZEyAZeHgbI73OG7nuN7EdSZkDAAJTrpFX3fIKNp18x7qGGt4r0z68tLdaeoVe9JZuw01V4kyuumOzU4NEuDVvxG9ewHR768SVeTra7bl04n+fN+cML9uqrXcVIB7ZfnjbsvUGHmcP125tzkjen/WGionU92e9iDROkenagAAAADYqJIxAb6FQ+ZLDuaQBX/bc2zOcQ/HAo74bWYBIOGctvMQev6M7WlgXvyKq6z5lenSTjl5DRPgReF+6vhHWH4tMFl7+9sLRG+fTfR/44ny/9TXRSAy1Vmxp0AX6+uNPZam9MpOpYmDctT46e+XUlnIsX75kR1bti8xAAAAAGywZEyApdQiya69Dljaxy7ikOnQX3BIoywASFLZmelUaUU3qbIrwM+F9qXH0znpHT5Jb28kJOFd9oMeC1f0r8UVlW56dcZyWpSv1wS3Zv2v076jZHtyrcaK6SL94tH84CYTfcS/pkJBcxEAAAAA2lsyJsADOJZyyIadkvxGOukQybzGffQQAJJRVqqXSh0/9kVWJpWQruLWkY8er9uP6MQ3iS6TCSFGTYkZsJgK8PvzK+hfb86mwkq9DVJbKsBi39G9zUimqMQkwEu+4Sz9a6KfHufjFHMRAAAAANpbMibABRzd9FBVgZ37jkh3nOi9UwAgqWSn+qjMiiTAiy09/XmPEXr9b0FFrd5XWLY38phKsekWrdRVmoFWYaWaEVFGiof2Gx2p5LbGsJ6ZHPpxNUiAuw00A1a53gwAAAAAoL0lYwIsG3/a+4x8xCGdn0/kOIbjVo7pHACQpGIrwIvDfcntItp9C9MAi62z9/RN0+tyqdpRAa4z2x8ZFZTGSW9vmvafvejnq/ehMf3t19dab88RvdQxagr0uL8RnfW1OWExHx8AAAAA2k8yJsAPcpTqodryaC3HcxyvcMi06Is4ACBJZakKcGSasqz/3axHBg3hsK21E+BUkwA7p0DHVIArrTQay0lv325pas/iDbH3SD0NutpZAU7Llc2LzQlDAgwAAACw0SRjAiyNrh7TQ5K5hBM5xnOM4xjJMZ8DAJKUVIDLnBVgToBH9c1WCaxtdYnZfzduBTh6DXAlpdLwXnoN8YbaYWgenbzjYAo6V2Kk5RH5+LHZzbdiEnAAAAAAaD/JlgDLM9zvOSapM83ikH2B53CgvSpAkvN53FTpiiTAi6x+NFIS4JzIWt61pU1VgKMrsD7+tbFF70xztmFcLhf954CRnFLrhlqKVID5OqWYj4EEGAAAAGCjSbYEWMo6YzmQ6AJswoq8eq1tleWn5VZvVQHO8ntVEyuxxk6A6yvA9qoJFpOABslDA3Lb1vk5Hr/XTakuRwKcLr35mD0NurZcHwEAAACg3SXjFOhpHNvpIQBsir5O25f+F9yfLgmcTwHyqgqwVF/7dNNV4KYrwJEEeFG4L33v2ZZSOGltL263i9KcCbCdhNsJMCrAAAAAABtNMibA/+Q4h+NkjvaZtwgAXUtaLt0YPJk+DW9Luek+6p2ttzuy1wGvie0CXVtGFJYeecxMgV7rG0j71N1FaWmRtcPtJc0VMCMma4AFpkADAAAAbHTJWgEewPE0h8xrlPmE/Oy2PhxzHQEgGUknaJtd/RV2BXhFURVV1gYjFWBRo381hGp1Ary61k9h/hUp+wq3tzTnGmC/abBVnwCjCzQAAADAxpKMCfCbHC9xyNZHEm+Ya3a8xQEASUw6QdskAbbJWmBRVFlHJzz5I1W6HZNEqovVoaJcXifT64dFdlr7J8DTvNuaEdHlH6+mQCjsmAK9kRPgWa8T3TeOaO7b5gIAAADApiMZE+BTOU5rJgAgiTWWAB+//SDafYueajxzRQndPkW2CTfMVkieoN4GqYp0tTjb8b7ayysZJ9DzwUl0WeAcen1uhUrGi4Im0d7YU6DfOpOoZBnR6/KrEgAAAGDTkowJMABs4pxToO2qr0j1eeiJk7ehQ8f3U+c/lzgqwEWL1MEd0Amo7P8rNkYFOJSSTdcET6c3Qrur85+WFNGnf+mPa5kp2AAAAADQ/pAAA0DS6ZejG1fJtkfDe0X3wpOOzvf9bQKdutNmao/goGV+Da6bqw7ugKkAW3YFuP0T4NSYrtLymOyKc6hmI26DFA6bQQzLIir4K9IIDAAAACBJIQEGgKRz9DYD6MI9h9NDJ2wVdwsj2Yro3wdsSXXkoyVWX33x+/uI3jyTfAHdDCtSAW7/KdBSibZJNfrNc3fij6fXHKsp2JKQbgzVRWYQ49v/Ej24DdFbZ5sLAJuWD2atpps/+IMqpDkeAAAkNSTAAJB0pGp72X4jaI8RvcyVhiQJlbXCUgWuN/t18lj6CXCVSUid06nbS5ojAc7LSKF+OalUaemqtYs4+TVV6HZXsc4MHMpWE311kx7PkZ6BAJuWmkCI/vna7/Tkd0vo7V9XmqsAAJCskAADwCarZ6af5lkDzRlLy6OgK4XyrRz6OLSdurQxpkB73HpbJiEJcIbfW19xVjZWI6xyR9MvUbiI6J6R5sQIOfYoBtgESFf42qBeHrC8aCO9+AQAAAkDCTAAbLJ6ZPnpteAetM7Th2iL/Yn+OY+uHfslbV/7IM23Bqn7ZPgj1dr2Uh2IrLXN5QTY73VTjcuRAH92tRlsoJkvET21L9Evz+r1v7EV4D/eMQOHeFVigCRWWh150aegwrFHdwv8sqyItrvlC7rt4z/NFQAASHTJmgDLM9bjOB7nkL1/5Sjn7b+YDwC6LKkAr6YedFzaY0THv8q/IfxUXhsiy/GrMRRu//W4VXWRdYbdOQF2uVy01jvAXGGz+LGYfYk3yJc3Eq34kej9fxA9uTfRgk/NDcayaWbgULbGDAA2DSVVzgS41oxa5vGpiym/vJae/WGpuQIAAIkuGRPgHhz8jI9e5JCNLncyRzmX63I7AAD1yExRx/X8BNZWURM9BTg9pf1fN6uuc1SA0/VjWJI6ip4J7qvGiulK3WaynVK5I5ld/WvDiq8kxyLLNAIT5avNAGDT0NYKcF0wTN/9VaDGNYGwWksMAACJLxkT4Hs5RnCcwCFdZeSZnRxP5NicQ24HAKCeWbrRVXltsP7Ja3lNpDq7zeBcmjSy8UZabVXpSIBz0vUa40y/lx4PHqzGyto5ZtBKpSuJHt2F6PnJ5gIbvLMZxKgt08ct9tNH4VwnvGQq0eN7EM1GcyxIXqXVkaS3NRXgn5cWRf0sOyvJAACQuJIxAT6EQxbQvcxh/2WS40sc13LI7QAA1CNTJ8DCfuJrJ8D7jupNb5y3E3k97f9rsltapLGWJL5C1hqvpu5U6TL7Fq9rYwL8xQ2cPM8mWjnDXGD7mi7PjRm2N/81MJVu6Qpte/4IotW/Eb15hrkAkNjWldXQg1/9RYvWV5grzZPE1UVhSqca1RAr3MJlD1/PzzcjrcSRSAMAQOJKxgRY2qs2NndQnlFG2q8CwCbNrgCLC178lZ6btpSKq/ST2I2x/ZHt5sljVOK707DuNCBXb38knaDl19Ni7xB13uYEeMV0M3DIG0bUd7w5aejZZblUm9pTnzinTYcdFa1AtRkAJK4zn/2Z7v5sAU1+6HtzpXml/DP/SsrN9Kv/HBplLar/HdCcr+evNyOtuBIVYACAriAZE+AvOCbpYQP7cEzRQwDY1I3ok2VGRL+vLKVr352rGtoI2SN4YxnZN5t+vnoSvXjm9qoBlrA/3lLqr45UvEwfW6KqKLJ1kl3JtaV3J0rLITr4Pgp7/FRhObpNs2pvN7rum1KaWcH3Eap6/LPuHu1UsMAMABLX7FWl6uhcytCcQMV62t49j1JdAbrP91D9OmCpBjdmRVEVLcyPrjI7p1IDAEDiSsYEWOb6HcNxF8dEDlkDLMe7OY7muI4jzxEAsIkakJtOfbKjE0Jb9kZMgEWqz1Of/IoM02xrXShbHamak9qW7Mn70xNEdw4hum0A0SsnEJWsMDcYPaQlAuu/FX106C90VN31+tyYGRzM/7roh9AofSH/D6L/7R9pkGVbP98MAJJLbVW5GfETBleRWg5x5yfzaKubPqcTnpxOJXEqwlMc05+zSRJhC2uAAQC6iGRMgH/l2Izjnxw/c6w0x0s55PovHDJvyY6WmMDxIcdyDpkHyM9MSfYPkcZaLSFddJ7hkHaRssu+vO3eHPFI9Vpul/vJ/eXt2r8LDwAodhMqcdTWA2hE7yxVjd17ZG9ztWPoKdD8S6bOrAEWlbrDbJPmya8mZoV5/EH0tGX2Rubx9M2C9apj7erSOn6qHp3wzwrJr0WiqeFx6qjEvA8lH/ucQnIKVuqqsfBTnUqAv5qnE9zvFxbSXZ82fPHHvv3wtN9opv8cesR3H5U4ukkDAEDiSsYE+EaOG0zI2I541yRaQuYGSlnlSo4DOU7mkE3/nueQhltNkUWGX3JIwnsRx2Ec6zg+4didw0nOP+aQ2+V+cn9JiOXtI4sVAaDdXLDncHXMSPHQ1QeNpE8v2Y1+v3ZfGj/QTAnuIHYzrHXhbuqoVMivgmbURJ68k8fxa2L4JLoi42a67Nc8OuV/P9HWN39Ot340j6pipkDbCfDv1jDKt8znnB5nt7jCv8wAILmEa0rMiH+EXJbaFs25NdoHs9ZQbTDS7Vk6xv+wqFCNz8ycRm5+m0nuX6m4suUdpAEAoPMkYwIs8/vsZLcl0RKybvhcjhc4vub4gOM4DpkjeDZHU6R96hgOmZYtexF/znEUhyyou5PDSaZty3W5Xe4n95e3k7c/nQMA2tnB4/rSQ8dvRa+esyPlmD153e6O75WXaaZcr7ccCXBlCyap2E/eRx9BdMlcov1uJZr8CAWPe53eLB6mb2P2msiqmNfS5lg6AQ7zn4Mz6i6j6j2uIzpfJqHEKHM0xwJIQG3eh7fGbAdmFFbWUbXjfck+wVMXRGZjrC2t4YQ4zCOLhtfoZnU+V4hqKhwvRgEAQMJKxgS4I8lfxOY6bRzOIfOnnM8o5W0kmd6Ow3S8UcdtOaSq7HyfP3BIUizvBwDamazDPYiT4DH9HYlnJ0j16l/HBeSsAEdvsxKXXQGWRleZPYl2vIBowvG0tqyGQmY7l8Mn2r9m+O6UQmFLJ/iVlEbLrcgKi9nWUFo58ix+P3FWXTj3BwZIQGUxU5Atq2XbGbnqImuAhSS4VY79fcUc01xLlNXojzPMtZr8gUj1OFihq8IAAJDYkjUB9nAczHE5h+z964xrONpKvl5SppH9Qs7n2I/jDo6mSPV2lh5Gsa+NNke5n2jsvvbtAJCEKs0T7gJnBbi5KdDyBN9OgFP128laX9nO6Y1fpP2BJgnwpPo1za76KvCc8GCy+Nfa4O7p6lysK2tkGmcFJ8BhqXoBJKbimCZUwRbs5ysvEnkD0d2cl+cX8x/5Yjre8yXlkq4OLy+SthyaPZtiG3d0Z3SrqgVr9gEAoNMlYwLcnWM2x3sct3PIlGgJ6f4sEd0CtXUe5pC/sFKWuZfjHxyPcTRFHo80zYplX5PbncfG7mvf3hgp2Ugy7YzI/EcASGiHjOunjlWUSpWWmabc3BRo2foobCaMpOr1ux/OXq22c7rvi8iaXdlr+JbDx9AeI3rSdpvl0RKrj7o+Law7P+83Wp+L/PIaPTAJdT35OFWocEHiiu3WLC8GNUeqxlmq52REScEautX3lIoHfA+oa0sLzTZjzK40b+uObo7lqi42IwAASGTJmADfwiHP4PTeHkTbc2zOcQ+HvFw7iKOtbuWQacoHcfyP40GOyzia09TL0LG3NXbf5l7Kloq0LEZyxrscANAFDOqeTt9cvocar7ebUc14in+jcWL85D78bD76SbribIBlEtZnfojeP1h2WurPCXDv7FR65rTt6LL9RtB5gYvpn3Xn0qPBQ9R99hsd6XgtFWCZOjpt+0eozEqnIsvRlbp8NX/MspZtzwTQwWK7MOt1uk2TfYOzXbK5Q0RaXSHt45ENJYh28cyloz1TaFVBZJq0PQV6G1d0AuyrQQIMANAVJGMCLN2WJdnlZ2qK/AVcxCHTob/gkP2A20q2QZItlT7iOI/jcY7bOGRKdGOkZBKvemvvQWxXfO3SSmP3jVcZdpLqtEyTdoZ0kgaALmJQXjr5vW5aZpmENFRLFKgkWvkT0ZKp+pqTo3utnQD3z4nu8tw7K5Xfp6wK0dJTPLTS6kVvhnejGvKr7tcTBuZGulCX1dBjUxfTcZ8STah9nM6sc7zG9/l1RHdsRvTEXpgODQmn1EyBziZdrW2uAvzqjOV08v9+osyYCnAPV3RTrLt8j9N2Nd9RuUl8ZQq0TJHezB29RMEXQAIMANAVJGMCPIBDtiiSBXXy1y+Dw/Y+xz562C74WalaEzxUncUn07HH6mEU+5puIRk5NnZf+/bGyLTsuTEhiT8AdBHSkKtXtp9uDp5I3+Ycxj/50gTeiLe+0FkBliZYrKgyehrosF7OX4E6AXaS7Z48bv1xxQ+LCuiez/XaRukMvc7KVWNl8ddEFv9qXTtLrwmOJZ2ikRhDJymuqqMTPZ/TrNSz6N/el5pNgP/1pvx5JsqKqQB3N+t+nQ72TKdlhTpRlinQset/RVa4rO2dqAEAoMMkYwIszxLtxWtSBXY2j5JKqi5ztI89OeQv7GJ1Ft/bHFtyyFRsmzyGEzlkGyW7Ur2KQxJque58hroDxwiOt9QZACS1Xlmp9Jc1gB5KP4/ooP+aq6wqziSQOFOgpYOtTdb7Xnuw3WdPyzCVXtvEQTpxHtE7Sx0XrKuIShzyKbe+a3SUakf1Wcx8iege/lX3xmnmAkDHkinQN/ueVuNzvR9E7d3blNg1wL1cMd/brIZ8kQS4JhhZ/+v2UZ1Hv8iUSxVqyyQAAEhsyZgA/8JhP+OTqcrS+VmSSimlyBre6RytJVOdZeq0vI/dOY7keIXjJA55hmp3qnmKQzrSyPpjm6wVlmrs6xzHc0zieI1Dktp/cTjJuSTLcl+5n9xf7ivVX/1XHQCSWq8sXYnNl27Mfk5K3SZhrY6TADuS0JXVfrV2d41JgM/cZQi9du6ONKKPTmxtsRXgiQN1hTfSJTpagLz0cmgvKndnE42abK4yZ/It3pFVIeyPd0h1pwboYCUxXaBbsgZYZLmiE+DBroazG/q7CmhZkZ5aLWuAt3XPU2PqvxXVpelVULmuclWFBgCAxJaMCbA0prKfmcmWR/KX7DkOSVjl5eCLOFpL9vCVPXsf4pB1xE9ySNtUSYCv4LDJM0sJZ7lE9hSRdclfc0g7SZmG3ZfjAI5vOJymcBzIIbfL/eT+8nby9o3sTQIAyaRfTpo6riypJrWLS5ppFxBbAZYkc+aL5oTokCdn06dz19U/6e9r3k+s9JToCvAEUwHec8s4e/8aVwXPoMPS+dfoztL43nCuP45Vie1goOOVVkcnny1OgCl6CvQQd/wEeLmpANdVldMol2k2N2gHCpufUakAxybhAACQeJIxAZYE1d6aSCqzEznGc4zjGMkR3baxZaT6uhuHvMzr45CSibRrfYHD6VQOSX5lDbKTdMo4hUMaXMmz0h055HHG8zmH3C73k/vL28n6XgDYBNh78so05HWyJVG6SYBjK8DzP+bfNN+aE6JySqdzX5AJMFrfbtHNsGyy3lcabQlputUjU1ec8zJS6NJ9tqAt+2TRW+fvpK45rSypoXCKY2uk2AqwU4n0CwToWCUx69+bWgMcDEVuy4xZAzzEWQHuLptIEPWmYlpRoL/nvZVryeMysxx6jap/kSrPVY4EGACgC0jGBDiW/JWSThcyjdhsmAkAkJgkKbWpNYf1FWDTYdbeDmnZ9/rICqxs/uUWXdkdmBt5P7Gy0+R1vMj6X9s/9t6cPrl4N9pqkKPxlSHJRGHYUVWOXQPsVIoEGDpeoDL6e7LOkeTGcjaLy6EKM9Ki1gD31iuqJOGtLlypxpZsBWZL7UaezB5qmOOSNcCYAg0AkOiSMQGWautLHKdzONfiAgAkvMHdI12b1ZRLZwX4q5uJbutP9NHlRGt+19fZ3wN/p4PG9qX7/jaBjpjYn87ZfSiN6Z9tbm3o4kmbc5KbQ+fsNsxcaWjrwQ2T4OVVKWbEnFOgY9f8ogIMncBbFT1Zqrau8de811foVUUpFKBMV6RxXAO9I300UypWqS7PrlpHAuzPJl+WToDzqJyKY6rQAACQeJIxAX6VQ6Y8yzpd6c78F8cjHNK4quEzOgCABNI/J43cpouAarqTZn5tyRrgmS9zshkm+unx+unPb4Z2pWnh0TS0ZwZN5uT3Hk6C/3PASLWlUmNO2H4wvXX+zjSqX+NJsiTTe2/Zi07beTNzheiFn1ZRndtUlp1ToJ0JgUACDB3kpg/+oK1u+pymLSokb629nb4WCDaejBZU1JGLwrSne6a5wkwn9SimAiz60XpaWVxF7jpnBZgTYFMB9rsCVFlRrsYAAJC4kjEBli4t8herP4fsxyENrA7hkG7KsiZYthoCAEhIKV53fSOsX5eVkGVPgZZ9d8v0FEynP8OD1DE33VGdbQcD89LpqVO3pcv2lYb12tu/raL1If3YgpWONcmxTa+QAEMHeeWn5Wo683XvzaHMYPQU6GBt45XdgvJaOtXzKT2Wcq+5wnrKJgwxeknrEE11gi6sopSgY8q0P5tc9iwNFqywN4UAAIBElcxrgNdwSPfncznO4ZDmUvL5bs0BAJCwtjHTj6ctLqRPFsdpAJ+ht10Rs8ND1VGaWG0Msm/wrpvrCpcos0yTrgqzJllURVfe0AUaOoJs+1UV0Hv9yv7V3V3RMxFCddHNrZwKK2vpOt/z5szosYUZOGT2pnCa/v6XBHjx+krKsBzbJqVmE6VLv0qttFBWYQEAQCJLxgRYPqcdOK7mkG2GpEzxJoeULa7j2IUDACBhXX3wKNq8V6Yaf71CP8GPcsLr/JvsUlo1/h/0o6WrVrkbKQEWz562HX17xZ5079/GUxnpNcphZxOs2AS4qS2SANqJbHPkXH7ewxXdmTwUaKICXBFnenRMBdiSPbh9aeTKHajOJQFesK48et9gvyTAkQpwQf4aCqv9ywAAIFElYwIsz8S+45A1vzM4JnPIX6fdOW7ikCnRAAAJS7YmevGs7WlojwxaY0WqS4o8Ke81mpZPvJx2/lFe69NrffPaeQq0k9vtUlOi++ekU6mlE2CXM8mNrfg21SEaoJ1IQyqnXIpef9tUBVimQDcQOwVakluXi1zddALcz1VIC/Ir6vcNDnjS+YfDE1UBTg2U0pLCSnMGAACJKBkTYOliIS/truaQBXMrOBwv1wIAJL5eWal0/3ETaZnV21wx8oYSeVPoxR+XmQtabobe2mhj6pbmq68AZ5TMJ5pyh052yx37pgppkBXbGRqgnVXHJsCu6O2MrCYqwHYX6Cg9o6dAu+ymWCYBlgrwX+vKOAHWTykCXj1Lo36rMpbjKqdZK/ECEABAIkvGBFgWx53KsYpDGmLJHsAyfpbjRI4+HAAACa9vt1RabXWnoOX4VW22ZSmtDqijbWOtAXaSBHh5uJc5Y1NuJZp6F2cT88wFw+LEpBLNgGDjqq6LJMC9s/0N9vMN1bVyCnR2f856HT9r3QboY45OgFNdAUqvK6ZsMwU64MtSx/pO7SyPE+DXf17JsYLu+Ww+zVkVPS0bAAA6X7JOgZaOz2dzSHeYzTlk6nM/DkmCG7ZRBQBIQJJwhlxeqiK/ucL66AS4vDZ6j9M0n8eMNh55PE+EDqQHg4eZK6x4KVH+n+bE4W7+1bvqV3MC0P6cFeCLJ21BA9OiE14r2HgCXF4es3WXiJnOTDmD9dFUgEV/1/r6CnAoxSTAHm/9FkqShP+wqJAuf2MW3f/VQrrkVcc2SwAAkBCSMQG2yXxAWfcr1eBTOPbgkMVyjr07AAASl9fjVklnBkWeyD+/JJsWra+gtaWRa1cf1PS+v+0l1eemkCed7g7+jVZkyXbrTBpgFSxQw+XhSHdq5Z3zzQCg/TnXAMvWYUPSo6u6jU2BVk2qYhu32fwmqRW5JgE2FWAh06DtJlhhOwEW6bpTdB939PRn+VkNoSkWAEBCScYE+J8cH3PIHh1fc1zCIXOQ/sMhWyA55u8BACQ2aW5Vatbdigf+SKOTnvyRlplGO4dP7E9n7qq3QtrYJMnO5oRcVNiPac0szgT0dOwZVmTPYGV9nMowQDuQ6c9v/iqrm7RULz+dqXZszcW++WOFSkBjlVQHqJsVUwEefbg+Bh1rg3P0HtvRFWBOgE0FOJySrY6KrM1nu3cvozuPGkdn7TpEnUvuK1suAQBA4kjGBPh2DpmLdA/HnhyyOGd/jrs5fuMAAOgyZHuj/wTOUuO5NJTyKYdWl9bUr2Hs0y1VHTtKtzSvOpaR3g+YApGOtz+HYxJgEY5uVATQHm796E966cfl5owozRsmqo1Oav0UoBve/8OcRRRU1Kq1uvW2O5vo4Pv0OKCTW8VOgNNyKezTL/joCrDuAm1Jl2hbD1ltxXctX0rHbNWPtjZ7eYv8MiTAAACJJBkTYGnHuBPHtRyyD3B0pxgAgC4kNz2FPg1vS8ekPExH1MivteipztIoqyPJlGxREjYJsEPcBLhwoRkAtJ/np0d3Qc8MNaz0SgI8dcF6WlOqE9b8shr6YNZqWllcFb1l0rZncuaao8cBx9ZJdgIsWyGZsa4Am/s4p0ubBJhk3XHpCuqZFfm5zC9vfC0yAAB0vGRMgKM3AtRk/pJUgWM21AQASGx5Znujn8pyqJZ0p2ePO5IE98nunAS4KJSmjjZZ/7vWimwHU281mgDBxpNONTTetZDSgg23HvK79OvfL5tK8XFPTKcLX/qNrnlnbnQF2Nn4ap8bzYBl9TUDzoHNOuABnADb79eV4vgZ6G4SYFGwkHplRRrXoQIMAJBYkjEBvpnjXj1UJnFIh5YPzXE0BwBAlyBToGNdf8goyvJ7KZPDOdWyI9QnwMHoxHu+NZAqKE4yvhorT2DjeS7ldnrXfy31+uh0cyVis266M/orM1ZQbTBEi9br6fqrSqqph0tvT2TJtkeObYxo69OIJj9KdO73/AzJ0VndrAPezBXZ89rjc3y/93DsIVwwn3o6E+ByJMAAAIkkGRPgIzmci34kIZ7FIR0uZM7U1RwAAF2CNMGKdcDYvjT1ij1p2n/2ou6Zji2SOoD9xH55dfTjWmANICvenxQkwLARjXUtVkdPsT467ThYr9uVBPSF6ZH1wqIXmYpxRq/oRNfL39cTjqvfbqxetq4Gp7kinabdzgQ4k99PqplGnf8npfo89S8WYQo0AEBiScYEuD+HvehM5jVtyyEL597jkAZZu3AAAHQJsQmubEXUPSNFVYazUvUT7I70t20HUorXTWVW9BrgBeEB6ih7BBdZmWTlDVPntFa6RKMRFrQ/D4XI74reD9tpVE9/fRIqTbOcerp0AuySxLUlzDZHTt4URwIs25D1NhPM1s1V3aQPTJtLuVSGKdAAAAkmGRNgWRxnf147c8gzr6nqjGgNR8O/YgAACWqnYdGtC4b0yOyQPX8bM7xXFv336PGRLtDGAktPEZU9greqfYzqdrxInauuumafYID2lE6OxHKL/Ym6Dyfa8mB+FqCfAvisOjpqa/3CTOxevL1MAkxZffSxORkxe1wzj3MNsLAT4HxOtp/ah26rup6eTPkvzV8XrzUJAAB0lmRMgBdx8F9A5ViOnzjsto4yhyl6o0AAgATWLyeNJo3sbc6IztmtY/b8bcoh4/tRv96RxxTiPyWLrUjDIHkdsiLPMYUU06BhI0iLSoD3I/r7L/xX/0Uir0lMZzxFWw3I1OMY9QlwZuT7uEkZzVSAhZ0AB/kpx5rf1XCcazGtKKygJQWR7cIAAKBzJWMC/BiHlB4KOf7G8QSHTSrCDTcFBABIYP/afwSN7JtNZ+4yhA6b0M9c7Vxue9sYtszqozpU98iMrAt++i8/WV6TICABho0g3eVYW2v26VVMBZhqSmirBf+nx8xNYRrgWq+OeWT2DN6ACrC3QQU4Zt0w87lC1JNKaMr8fHMFAAA6WzImwI9wHM/xIscpHM9y2OSv1TN6CADQNWzeO4s+vmhXuvrgUZ06/dnJ40iA55n1v9sMjmyD9OCUZVSQafYFRgIM7Uy2AstwVoBTHFPy6yJTjvv+8ST1Ua+HE93re5i+819EF3vfII/LTInegAqw2xfTgK7fRKJhexPJ+vcdLjAX9d7Bc1aZhBsAADpdMibA4hWOf3C8oM4izuaIvQYAAK3kzcyhGks3GPojPFgdtx0SvQ/wJ0WmurZ2NlE4rMcA7cDLCXAaOSvA0WvSnf7ufYdcFKbDPD+o83/web2WJsD+bAq7YprOeWMSYOkmfdJb/AF+JZp4grnIebGrkMpr9N7BAADQ+ZI1AQYAgI0oMy2NrgqcQW+EdqMXQpOI8xHaalCkKiz+CpkEOMiJSuV6PQbYQJZlEYVq6BDPNHOFpTimQNsdyI1jPFNoJ/dccxajpVOgXS4KpEU3pCN7in883fSsCNHPVUAVtY13qwYAgI6FBBgAAFpNtmB6M7wbXRY4l0ooi4b2zKQeMVs2rbNyzYiVSxN+gA0XCFl0qed1OsX7ubnCnBXgwx8j2uYMznyfU6eyDvdhX2QtcJSWVoBZOC16hgN5YirATqndVNVY6AowEmAAgESBBBgAAFotO81rRtqWfbI4KY6+ts5yJAxIgKGd1AZDdI73Q3NmOCvAA7clOvgeolGHcUxWl7q5qtSxgVYkwFZ6TCOs2CnQsUwVWNYAowIMAJA4kAADAECrSQXYSbpUZ/ijE+C1zgpw2WozANgwNYE468mdCbCT7AvciLC/G5GviWnMMTwZMRXg5hLgPL1l2Wj3UiqvrlNjAADofMmWAHs4tuCIXogGAADtKjum2juybxb5PNF/UgqoG1lkulaXr9VH2OTll9VQKGy6MLeBVIAbaKwJVpzuzTZXS9f/Gp40PaW5XnMJ8KAd1KGfq4iya6NnQKwpraaPZ6+J/7kAAMBGlWwJsDzTkn1+d1RnAACwUcRWgLfsE5McsCB5qcxjqsDlqAAD0Wdz19J2t35Jpz0zw1xpvdpgKyrAcfbvtbkye5lRy3hTs8zIaGoNsBi8kxkQTQj/QXWOx/23x6bTeS/+So9OWWyuAABAR0m2BFgW2UiZAVO7AQA2om6ONcDd0nzUt5ueSvrUKdvQ5An91JRoscaeBl2GNcBAdPbzv6jj1AXrKdzGKnBtvCnQsgVRPE0kwC3uAG0zTa3qNVcB7jOeAp40NZzoXli/Dlg+7+VFek3yvV8sUEcAAOg4yZgoyh7AJ+shAABsDM4KsDTAcrn0VOe9R/am+46dSPuM0s2FVga6qSOaYEGsyrq2NYZq1bTh9Jiti5xa0QBL8WeagdHUNkjC46WaVP0xcl0V9XsBF1dhPTAAQGdKxgR4JofMO/qK40KOIzmOiAkAANgA2Y4E2K72Oo3kpFjkWyYBxj7AEKO0WieErRW3CVZjOAltVGsrwCkxCbAnxQwaFzZvk0nV9Vshra+oVUcAAOgcyZgAy8Z//Tn24Lif43WONxwh5wAAsAHSUjx04Ng+lOn30uET5VdutBEmAS4ikxxXFcncTz2GTZaf6uhozxQa5lpFZdVtrwBXWc1MP26JVleAY9YAu5t/CmWZt8l0RRLggnJUgAEAOlMyJsB7NhN7cQAAwAZ6+IStaea1+9D4gQ0b7w/unkGpPjcVWyZpsEJENSV6DJusC73v0F2+x+lL/+VtrgDHbYLVFhuaALeAy6wbzqDq+jXA6ytq1NFmWW3viL0xSafuMjNtGwAgmSRjAvxNCwIAANqBN2brI5vH7aIRvbOo0HJMj5YqMGzS/s4JsK28stKMWqc2EKJUaocqaqubYLU+AXabztFZqgKsk8n15dFToNtaCd/YTnzyR5pww2d0xyfzEjZJBwBoi2RMgB/gGKGHAADQWWRrpGJyJA1VBWYAm6KCmLWvtaVt2xu6rraG3C5HQpZq1pk3pv/WZhCjtRXg2DXALeA1ewfLGuAPZ+lGcAUV0cl7QWXk6yJV4tkrSzs94awJhGja4kKSRt2PTFlEU//Czy4AJI9kTIClA7TsBfw5x2EcujUpAAB0qKE9M6jQngItqgrNADY1UvXc5uYvzJkWLMs3o9YJ1ukthOqd+pEZNOKIJ4hGHEi0zRnmApM9fJtLnGPFdoFugZR0/TEyqIa+nLeOfuSkMrYCXOhIiKXqesiD39Gbv64yVzpHdV10p+11ZdHTtgEAurJkTID7cfydoy/H2xxLOf7N0YMDAAA6SO/s1MgaYNGSBLi2gkK/v0YrV67AtMsk8vGcNZRNFeZMsyp0Z/C1pTV0KCd91747R503J1QbSYCr97uLqM8Yc9aI7sOIjnuZE+DTzAWW1ZvIbN3VYrH7ALeAx1SAfa4Q+SnAie3KOAmwPpf9gWeu0OvkL3v9d3XsLFWB6AS40qxfBgBIBsmYAMuiooc55C/iJA7Zdf8mjhUcz3BswwEAABtZr2w/FdpdoEVlC6ZRfn4Ned4+iwofP5Se+m6JuQhdXWqgmL73X2TODLM11i0f/UmzVpbSc9OW0aqSanWtKeG6yH28Kelm1AI+x30zW7n+V7RhCrRz3XAWVdOnc9fRsqLotc8FlboCbHeJTgRSAT7L8wG95LuZLvC8Q1U1qAADQPJIxgTYSfYCln1/h3D8wHESx48mDuEAAICNpFdWKtWQn6ots19qSyrAP/9PHca7F9OLH8mvcEgG/Za8rRpBOXlr9PfD76bqKVYWxUxvjiPkmALt9bciAU7JMAMmFeDW8ja/728DjgQ4gz9/6Xy9oqiaTvB8Qa+nXE8jXMupzHTDbmtX7I2hpraWrvK9RDt5/qDLfa9Rj/xp5hYAgK4v2RPgNI4zOd7nkC2Q/uS4gcPDIa0or+EAAICNoHe23qu1yG6E1YIEuNYX2VLpKM83as9X6Pqqaht2bU4xCbDXE5mKvKwFCXCwNpJIu3zyZ76FnAlwaxtgtZUjAc712FOfLbrF9z/a1r2AHvLdX7/VUCJtOVRTFT1d3Ve1zowAALq+ZE2Ah3HcwyFdJB7lWMmxL4dMi76RQ6ZB38Eha4UBAGAjyPR7Kc3niWyFVLZaH5uwzt3TjIh2d8+iP9eUmzPoyipqG76QkVant8VyO9biLi9sSQXYUUn2pppBC/g4Afabxlfdh+vjxuaYNr3rIF1BzlYrtbTh7tX12yAlUgW4riZ6mrarrm1bVgEAJKJkTIA/5pjPIe0en+OQLZFkunN0+0ldFUZjLACAjcTFiY1UgeeFB+kLq34lCjdd0XWHIg2CRrmW0dxF0scQuhrZzuehrxeqrsfCXd1wD+iMYLE65js6DLekAhx2doFuTQXYzU95jv4f0W6XE0080VxsJUmixcAd9LE5jgrwLoP0Yx3gil4Lb1d+EykBDsQkwIQEGACSSDImwFL9vYSjP8fFHIs44pF2kzItGgAANhJZBzzDMluz15UTrZurx43whiNTZWWv16oFU80ZdCV3fjKP7vp0Pv3t8emqm3dKnU52nbLCJVTOyV9ZTZD6UCGlUi0tK2w+0WpzBVgMn0S019VRiWmrnPst0aTriY6R19dbwNE5enxPN/m9burnil4K0Nga4M7sgh6bALsDSIABIHkkYwK8BccDHNELWBqSeXXf6CEAAGwM0gn657BJgMXy6WZgBDiZWb/AnBD5rOi1orn5MfeHLkE6Ottqg2FKC0QaXdn84VpaU1pDW7vm0/TUv9OHKVfSmqLm/nQz+Z6xtaYC3B5kS6VdLml5Ey1Hop268jvae2Qv6h9TAba7P8cmwFUxe/F2pIBjqynhDSIBBoDkkaxrgG2ysOhajjbsdwAAABtK9gJeYvWhcsskKgWRZFd59lCih7YlmvOWOk2xovdIHVM3iwrMPqnQNRVW1lE3q9ScRfioTm17dKvvKXU+zL2GsmtWqP1wm+RMgFtbAe5oqdn8TMQ81frtBbpu6zrau2/093Nltf58YhPgzpwSHYqpAHuCzU9NBwDoKpI9AZbP7zqOfuqs7fbikL055nHIXwVprvUux9YczZnCIX/NGwtnct7YfT/hAADocnplSSdoF5WSWTtZ56jwyRTPlT/p8RunqUMKRT/p39K9guYuWGzOoCuSxlZ5atJVtBSrjlZzAtzXMSW4HxU0vx9u0LEnbUdXgFtLHt8ul5oTot7zX6DdejkSeOau1tPD2zsBfuybRXT3p/Obf0Ehjqhp5swfQgUYAJJHsifAItJesu3O49iM4/84DuSQ3fx7ccjcPEmOm3I+x44xsTeH/GWTt1/L4STP9GLvL2uZAQC6HKkAi0rLVOqcCXAwprLLCbGf9BTohWnj1VGUzMN+wF3NQNc6eiXlJjrb8z4tL6qkPFfDBNjPfwZXFVero22QK59KqhtumeTkcibAiV4BFntfQzTiID2e+w5RvryWHuGv1S8AtGcCPG1RId328Tx68OuF9NkfsU8zmhfVaIylhB1fcwCALm5TSIDbwwUckug+wiHrht/g2IdD/mpdydGUPzgk0XXGQA4fx5McseRl19j7R/+1BADoInQFmKiKTKJS60iAAzHTKh0J8aqcrTkVll+TRBmrvldH6Dru9z1EO7j/pCt9L9PK9SWU7dL/1+u2vpR+GXiKGsuLHasKSsjvilR8B7rWU0lV04mfs1N4wleAbXbXaXkBqEA2qoiQZmA1gVB9MyybJMAL88vpX2/Mol+XN2wi1pTvFq43I6KflrTubUU4pgKcalW1qZIMAJCIkj0Blt/W0oljQxeQ5ZujkzyLk+RWktnWki2a5O1fVWcAAEmql6kAV9RXgCNTKa0GCXDkSXcwJZuWZ45V46EVv1EoyZ98SwL0wvRlNGtlw2ZRXdFE90IzIipfF2mIlZ7Tm1ymaiuJb3BddDI4wJVPxVVNV4C9If19E3J5iDz6RZKEt/k+/MnH33mxO5Wpad+SAG/jmkcXed6kbH6KIAmwdNJ+9ecVdPtHrXsdfE1JpGIbbks36ZifzXSqoSr+HgUASAbJngCHOYZwNL3vRtvIbvpbcbT2fW/OsSvHKxyOUkg92cZJNkyUl8RlC6dbOLrIS9wAANGkC7SorwA7pkDHbrUSrI0kwJIkVffbSY2HulbTkiV/qXGyeuvXVXT1O3Po1KdnUDAkf7qSR6A4OgF2Vm0zSqMTO6kANzX1V22pFNbfJwGPWVfeFUiiPu4YcxKtu0sS4ID6vN/w30iX+N6ka30vqKR4zqoydZ/WNoKbvSrSdGx5C/ZWjmUFoqc8Z3ACXFnbzNpsAIAuIlkT4BQO2aNA1unKeGN4iEP++kqC2hpS/RW67WW07zikW8aRHIdyfMRxBYc0wWru/0o+19ExIck0AECnyfJ7Kc3noYo4CXBtVfRrgHU1kSfqLl8qdRsl7RK09bO+MKPktLJYf+5FlXW0uCC5Gg55ylaYEY8ze5DLq18UEUPCkdvEAE6A/1itk754agJhSrd0chbwpKtjlzHheDOIJgmw7IVcVRX5/j/KM5XWldWoLtmisq7lyafMJli4PvKz1ZK9leVtTnhyOp3+zAwKhMLkiun6nOGqoQokwACQJJIpAe7OcRuHvJwsv7lXc6wxY7kmiarcpz3cxHECxyUcv8iFFvJyyOInqRrL2t5YV3PIOuOvOST5/TvHvzl24ziMoynSbGtOTEinagCATuNyuVQVuMqeAu1YA1xTHf3E3JkAu1PSaMDonfntdLLkWS6vDyavasf00j/XNJ4AdgV1wegKdvfgOjNiGT34/zaSuA53yaYKETlUQY9PXUjPTVtqrkSr4kQwnZMxEfJ2sQS4z1ii3npaP6V2o0CqnhItU6DXl9eSqzZ6q6hfl0XW7lbVtnz6sVSOnbOeVxRX16/fra4L0drShg2t3vhlJX2/sJC+mpdP781cTa44FeAK6c69bBrRZ/xUpbz1jbUAABJFsiTAMs35dw6pnspfzXs4rjIh4yUc/+T4jUPuuyFkWyVJVOV9PygXWkE6SMu2R/GaXzXmBXPcwRwb8zDHmJhoLmkGANjoBuWlU6W9ksOxBriuOqYCXOtIgH2pHH5amKoThgGlrXmtseuRyqatqQpoVyDTeZ0GuArMiKVzAsz/t7YtXCvNSPO4LMqiarr23firi6o4gcswbT1Cvi40Bdq2Fz91SM3hv+jnkztLJm7pCvDUBespy4rulD3LMY1Z1t/K9O+WkGquk7wgIZVkqewe8H9Tadc7v6IPZkmNIGKFmYEg5q8rJ3coOgFOdQWotLKa6O2ziX54gGiaTIIDAOiakiUBvptDXiqV9bX7c8i04dtNyPgAji04pLvIXRxtJcnv9SZulQutJNOfpbvH8+qsdZpbFCaNuuQZgzNkDTEAQKfaalAuVZpKLkkH35BOkGLXAIcqIvvB2lXCkt7bq2O/8FoqX5e8+wHXOpKWP7p4BTh2H1+Z1lwvLZc8/sgaYFnzG6ubS78wEm8ttCTAdgXY6ooJ8Ah+OvKvpUR7/Js8mT3VJUmAP527VlW/nZyVdGkCVxtTWW9MbbBhtfiLP9epLaeWFlZxImzRhS/9pqbb20odnbdlOn5sAiyCxcv5B5KD1ZVGJ9AAAF1JsiTAskXRNRz6N3N8cpsksJFFZa0j718S35s5bpALrSSVX6kAv8MReZbXPL1fRPwp0wAACW/bzfIiFWBh1gEHa6Kf8IfLIw33vSm6Spi2xR7qKNb89pkZJZ8aR9Ly55qGe+Z2JbFrRfubCnCVJ5vI4yWPowmW26WrmqEeI9RR5JpEcMG66O8PIVOgM8kkwCldMAEWLpc+Zugp0HlURvnltZTjanqtriT/LeGcTWB7//fVVFgZ3Uhr5orIFGvnuvNP566j6sqGX/uUtb+aET+hWh1vcwwAgK4hWRJgWVsbaR/aOLmP3Le1ZPr0jRzSjOpDDpmO7AybNLaSv/yD1Vk0SWTlYzc2/Vk6Q8v7P4dD9hg+hEOmNUul+SuO9zkAALqciYNyqNoVmfZqrwMOOqY8C6syslbU49cV4KHjdqZySydMocVT1TEZ1XJit5N7DvWhQtXxN7+8YQWuqyhrZAp0nT9PHb2OCrDN0182VdByTAV45oqGW0KpCrBJgF1dNQG2ZUQqwML+vG0pFP11lOS/JZwV4NH9stXx1+Ul9PuK6DXGdrdt2X7rpyWy+YQm1eZUV8OtqKwVP5sR38exlh8AoKtJlgT4Rw5pFtXUX0O5Te4zTZ21jiSjQqZXy9vHhs1jwry8G+V0Dlmf3FgrU2nYJX+1pNIsye5rHLtwXMshleOWzX0CAEgwGX4vuf2Z5oyZdcCh2uiKl1UeSYC9KTpJ6p6dQbO90tSeqFfhT3ynNuxp2gVMKP2SXkq5lV5LuZH/MIe7dBU4dgq0LZSqE2CfeXEjSr+JZkB0vvc9yqSqqAqlTa0BNlOgXc7vqa7I7Auc7apWyW63mCnQuRT9PRBbAf5teTHd9vGfqlu0k7MCfNTWA8yIGjQWk2nP0hxLtt9yGtojg0b3bFgryCuKVIB9waar1QAAiSxZEmBZ5ysvH8sCMenMcC6HbLh3tBnLNdmVX/7C/oujtWQOniS1jYXtVA45j9e+UuZ3SQOuxp69yeM7iEP+WkmpRJ79jeOQCnDrNgAEAEgwYZ8zAdZP9MN10RVg5xRon6NKmN99O3XsHlpPVlFyrgPuW6f/bAxyr6fNXSu7dCfo/NJGJmRl6I0Y7Bc3ojgS4B3cf9Kl3jcaVCyFVMbtCrAnNUsduywzBVrINOjYKdB2Zdi2uqSaLnv9d7r+vbmqSnv4wz/QY98spivemGXuoTmbYE0clEtDe+ragKz/dSqpDjSo1r945vb01WV70PBcOwGOPMXZ0pJ+opovFP2+AAC6kmRJgOVlSXmG9A2HJKEydfgVjlfNWK7JbXIf6QQNAAAdyTldtbqEaMFnlFoW/VqhxzEF2ueP3N8zVHaC04rmfGlGycXZdGgr919dOgGevdzR9dnBbvqUkhpdAQ7JxKnesnFBxOneT2hBfnmD9cRf/bGWMlz6NeHs7Bx17LIcCbAku7FNsPJc0RXgU5+eobYreuaHpfTRbJk0pn2zILqRmN0sK41qKD1cQYeM66fOY5VUBajQ0QjrsAn9aKdhZrfIgHkRI7u/PjLp0G3zh1uy6gwAIDElSwIs5nNI1VcWvGzJsbMJGcu1YznkPgAA0MGiGhbJViovHU2br3rbXND6lUSmWKakRqqEg0ZtTyWWfvvqBdISIfl4pTu2sZWrayfAf62MJGdO/m562x/n/62oSO3DFxtOi/ZaQZq1MrIOWJLhXxZGug9HTavvijL010P0dhVTbswa4LyYKdBO93/5lxk1JBXgbE6mp/ovpuEvbEuHD3WuoJIkVieysgY40gnaUlV313f38JBvr0+A4yfPqRYSYADoupIpAbbJ3J8FHPb6XBlHL5wBAIAOFTVdtSp+I3y341d1SlokIRrZL4d+sPR+wL3WfE1U27W7JMfjCTsSYPdftGh9ZYP9XLsCmVKbXxBpqOTkz9YVYF9MBbgua6AZRZM9gp2NsKbMz4+eetvVm2B1H24G/D3uWdVgDXCOq5wm+3+mn/zn04mez81V7a/86Ps6yRrgQz3TqKerjNyBKtps8Us0sq/UASx6wXcrzeD3N5y/tpIAF1boBHhP90waPOdBoi9vJFr0ZSQBzupN4ThPFdOsGp0oJyp5bGvnEJWsMBcAACKSMQGOJfN5tjVHAADoBK5U3Y02HtkjuMiKrub5HY2SUrxu+i1PtnPncZifeM95S42TiVc+L2OYew1lhsvprzjbACW6WStKKc1MUY7lNl2P/akxiWvuZmYQbbR7Cc1cHkmAZXueDJej8pjS1SvA/LQkq68a7pixpkEXaNnu6Rz/Z9TLVULHeZqe+WA5klF54WSwK7KcgMrX0cHj+lJ/KqBdPHM5MS5VzdZKqurqK8AT3IvUUZl6N1GROU/vTlWehl9nnytEtbUJWgWWDtX/24/o0Z0p8MC29Nsv0icVACAimRLgKzlkQZk0kzpTLjDZvkjmS8keums5buMAAIAOZmX0ojdDu9ASfhpO4/5mrmprrTy6Oxi5Vmd5KNWfYs60tJH70npLJ9E1f01Rx2Tis6K3nZnYRdcBS+fmDNOkqgHTBMvtc2yJxfw9h+lBajd9NMa4lqoKsCR3srXP1/Py+X07kuuuXgEWvXWH8wn+VdTdE91YKstVRUNCep28/TUdPzCHtt0sV42dnB2iZQ3wOLejWVzBfLUOONexpjiPk+3UypWcAMd5sWL5NKJwkP+jvERbn0Y13vgvXlWUNdymKiF8yk8HV+ik1xeqppL3/t0lZ1MAwMaTLAnwCRw3c8jCoz85pOuz7Kd7B4fszXsGx8sc0i36OA4AAOhAmX4v/TNwPu0f/C/RqMnmqlZFfnoltCfNDutKYBk/3fd7o/887TqiDy229HrEivxIN9pkIAlebAIs06D/yu96U71nriil9EYqwFJNVLzRCXBGb5MAn/AG0QjZ9U8b615C+eW1tLashn5YVKjWANsdoJWkSIB186/MssXUzxtdAZYp4Kkhfc3+mo7qm0XHbz9IjZ3sqcyitq6OxrocPyPr5tKgHB8dMtxvLmi9qherJljne96hi7xxZlXsfS1RvwlU54vfbKyyvGGX7k43/xOiX581J9qerl+psDDSYR4AIFkS4As4JMHdkUP27L2E4z6OxzjO53iG42SO1znO4gAAgA4kewELqU4FU6K3rwl702jMgFy6KHAhfRWaQHeGjievJ/rP08SBObTOpZsGectXqWOyqAuFyU8xCbDrL9WltyuRRF4qto1WgM2+t+R282cb2WfW0112CGQDtyM6jv+Ub3e2Oh3pWkYeCqlp0J/NlUlcRN08juTa38W3QRJ292srRBSIrgDv4Is0uko1le/xA3LogDF9qVuaT53bCpyV3JqS6BchQvy9tfBLOmfb6ETWV1dCxRU1dIXvNXPFYege/Izq72popen9m0XAG3nRoaoiwWYoVBYQvacfc8CbSbcHpPepVl2AtcAAEJEsCbDssfuiHiry21xe6nxfnUXI9fF6CAAAHcVOgEWVO3pNYciTRo+ftA1VZA6h0wNX0Jf+SeaWCEmIq9J1BTg7sJ4oGJ0wdmXStCg1JgGWNZkV1Y4kpgtYVVJNBRW1lEmNrA21K8CslhxT3GPXAPedoA6prgANc62m6YsL6eM5OgHepk/k+4h8DTtHdzlmCnQ8GeFIRThdJcAW7TisO6X6PPSPvTfXNxjOCnC4Ls4LED8+wj940c3Jsq1ymrtouTlzyOKfs8MfUy9UiF69+6ijqO6p/2/EPR/8QsGQs8N0J5O1y5W60vvvmpNpphVpMlZbEr8zOQBsmpIlAZY9FZw7yBebY+ycF9mcsIt3zQAA6HqyHAlwpSs6cQm6U6lPt1R69vTtaO8te9F/DhxpbolWm6H3JHXLNi5lyVMFlvWJdgJsd9zNdNVQtwppadF12B2bt3CvVMcokqw6tjoKufV03GppsJQWs6a1b+R1apnK++y0ZfXV8AOyzNfE7SPKid89ukvpwYmsJ3q9ezxeV5hSKEiD8vTX8IxdhtDUy/dUY1FYEXmxJGx3cBb213bxFKKl3+qxIdsuhaRq6jRkd6ILpvMPbCTp9WVG9isO9t3KjDifriyjG97/g9aVNVLx72gFsukHf5qezejN4M603oqsKQ+W6hdQAABEsiTAsgt8ZLd2eQ6hpz/HJsC9ORK0awMAQPJyVoCf+TX613CFT1cGZauWp07dlo7aeoA6j2V1cyQ8pckzpdGZAJd0iyT/AyvnmlHX8LtJgMe546zRdlR/RWaGnkrrk+nPLpca1+s5gpNCnSCPcbyvAd38NGi9aYA2lBO1ZJgC7eFEXj5fJ5fHDKIdOCKbv1SRr1Wv7MiaXlnLaws5K8A7/YP/MW8z7wN9NIak11Evj7N2wNJyGjQjI8cUaPfAbcyIf6aphp6fvoyOfnQahcMJsCVSUH/eawNSE3HRVqMjP0tWORJgAIhIlgR4NscueqjIb+LzOGJfht6OQ5pkAQBAB8rwR57UP/5j9GuTZal6K5jmeLtHpsrWFCRmI6y6YJhWFkev5WyOmgLt0hXOitxRVOvSTaL61HatZl+6AmzROI/uXBwl5gULb6ZOiL29tlDHKJIUmqnBo92R93V033xyVZjtfbY8WB+Tgb0O2JbTsMmVuOkg0yzMSF0+le5OeZwGutap/Zdt4YAjAe41KqqxmNNBw/304vHR75O2P9cMHEbsr5Pizfel9P78/owMM9V9eVFV9BrkThKo1T93NVYK9c9Jo8sP3YaqeSxcZmo0AIBIlgT4Ko5X9bBJ0sv/aT0EAICOIl2gbVbMn56adOcEnsZl94okwFXr4iRZCeCEJ6fTLnd8Xd+0qSWcFWBXShpVm21nvKHWJdKdKRAK0+xVpTTAVaDWlip7yp9mQxIxp0nXc3Z7BNFul5sLMfrptaajXUv5u0WvM905KDsaClejSV2XFLsOOHewGUTLcvP3iGO/X3p+Mh3lnkIP+h6g8pqguch3cU6B9vqJdpB6QBzVReThqHfEE0SDdzInDn3GEl2+iL+5X6eUtEh1+J6UR+ubt60u6fxp0EUluit1DaXQDYeOpp5ZqbSedOMvX1UHJ8DhBFobDQANJEsC/DvHN3rYJNkaKbo/PgAAbHTOKdCxAlnxpzzH6pWXTess/YQ2ULRMHROJTAOdsVS3oDj7+V/UsSWqOQG2EwmXL42CHr3O08cJsHRW7goWrCtXlewxzu13huxGdOgDRD1GEO1zo7loDNuL6Oin+T81/npvex1whquWhrh0A6MR/9/efYDHVVx7AP9v16rLttwLLhhjgymmGNMDBAOhBQKEksCDkFASSPIgJCQh/b20l94hJAQSQidAaKETmrEDBhtscMO9yOplV9rdN+fOXN3Z1Upa2dKq/X/fd7hzr7pZrfbcM3Om5nnniIkHq2xQVjQNETlWgPHbI1XWqf69qlQyaiVY+/lXpyXAsCvAsuXUHkeor6GS2EzN6rHaVGVOlK6q6lKVFzJF2nKs/w3nuLG6k8ZneZQyU6DDBYU4fvYYZ7r4Tp9eA13QIivl8uT9fwE/2AN46tvmQhca1Pf1wFXAsgfMBSLKh6GSABMR0QBmV4AzJe21vV0YV1aADalKZ+yrzdK9tp+1tCXMSLvqr0ucKdHdaYnFEfHpBMavEuCE6W4cTbU420YNBm4DrH1VMubwqZcXUjk88BPA1a8Be56gr+fKaoQlVeDpvo0oaTDJ9axT9HGoSEuAfUBnvw9tKsms3ww8qBKmxvSErt6aAo2ENR1ZKsCybjhbFbjJSoAzmpR1Sj7f2X80J8C3Q7fiIN+72FjT/7MVQkn9c/tC3j7TtQG9frmw1Ur0+9rtZ6lf6lrghR+ZC114+Fr1y3M7cPcn1f+3wbXtGdFgxgSYiIj63KjiSHsn6MOmpTdECpXmVs0bU1qAjSndkTbSuMk5DiRSAbU9snQzHnij+27V9Q3edjf+cBSpkG4QJXu52ms7BzLZq1fsHzSV+VEzVULl7RnbYzJlWjo9K/v41+JE/+vO2LG3bPc/hBRXAkV6j2tnrW2BVWWVGwmZPngZ2LbcnGgNdgW4zU6ATTK4j0rKZHsjm0x/dhPgjCZlXZrzUSSDOlmu9NXinsi3sHmnmfbej0IpPYsiFfASYLfBXklvJMC9PRsjof6f2Y3JtrFFDVG+MAEmIqI+Fw0HnA7P3z9rX9x4yt6IpcyUSqWs0Otm2xXZ/7QqqJPl4pYtQDK94trfZCpzpmfe7XrtoeyjeseLK8yZykMKi5EK6936pMtuXbOV2Axgq7ZLEp9yti1ymL18d5lUGs306OP9i3Fx8HFnjMpZwMiMxk1DgbsOuHBEenfr0Z3sE/zol8xAa2r2pj37EtYUaLcaKseLVbJ15u+Bo67X11qbgC3SQ1SRr5srnw/+jC2oGqr6f1uycEon/kk36VeaIvqGWVGqUf28uzFNe/k/gB/NBF5V/3490dVz1Lp/m4Gx6T9mQER9jQkwERHlxSFTR+DcgyejoiiM8+NfwaLkTFwZ/xxKo51Pj87UGNVVrADUC8sBtrVJc7zji90X39vR5TTol1ZVYd1WrxFRaUkJfKZyKl1206a2DmANsTZMgDTAqtMXTBOr3WKmQU/zb8Fon9k6a+65+jjUzL9S/c+fqH5JPp2eAE862Awy7PBumohgi7efrz9bBVjIjYP91L9fqVUJ3vq2PhZ6e/3mpCx93X6yJsvez/mUSrU3krN/5niBXjLhcDuI74q7LlJPPtuARztp2ubKTHjj3uyODpbdbwYGE2CivGECTEREeVVaEMTi1F74WPwb+GdyPsqiXjW4O63F1gvvmoG1Dli6Obtm+tY761brVWK4bJPuTpvN8yu3o8BnXriLUBT+AlMB9sXSmxsNYI2xhDNVuZ21hneXZTaHkmZazr62Q9DMDwNfWKYS4c8AxWY6tJic0ZV5zxORbZ/gaMxKgO0KsJ0Au6SDdmZTrAnzzCBHxenLFoL1/ZwAJ7zfIXsNcMKdWi7qdyMBzlVDxoyPWCcJsEx/fucf5sTYrBuKEVHfYwJMRER5ldkQq7Qg9wTYV2FNvczYW7a/uQnwHr7NeDR8A/4Z/grGYCcWr9OdobN54b0diMCq8qqEJWgS4EK0DJ4EON6mEmC3A7QPGDvXjHdDZjdkaaQVyH22wKAlXa4Puxo4/BqdGNtmn5a1oVVxW5XThdyR2QQrk3TQvuJF4EtrgUseAy68Fzjyi+aNOZKGXJaK1m39O1vBnt4cipqBGpZ5e4zHa3U38d0W62K9c11Gb4J4oxkosoa4Rj1nSQfvtS9466/NkgdsX9n764yJKCsmwERElFeyPYmttAcV4OhILylq3TmwEmB3DfD5gacR8KUQ8bXizMCLWLTW2mvVIg2uVmyt96ZuCkmAo3oKbCFiqG2ykpkBrCmW8Nb/jtoTiJgX9bsjMwHOsVv4oCe/Hyd+V28dZRqitRsxDTjmBpXEeomdqEQNGuJtzprygFUNzVoBdkUrgCmHATOOV1+ni/fLZsJBZqCN91VhY03/bYXUGvO6UPutn6VwhDfdu3FHL61T7qqSXJdRCY9byfKrvwN+ug/wwBXe9Gdp9Hb4tXrcqpLlzASaiPoEE2AiIupXMiU6VyNHjkJNSicFzTsG1l7Asgb4/MBTuDz4iLmicgxfHK+vrc66n+8HVfpFe/oU6AIUFpU5Q79KondUm7WvA5iscY4nZAp0LzXAcmU0WupwPhxkVrwlAZY1wh+/M60b9kjUObMFGtVjMGIeTwmf+lh/x+nSveLgS4F9zjYnkgDv6HIv4C21LVj40+fxxbvezPq7sLuam71Kq3RSd5WOGo9ESt9wa67upQS4oYveA5kJrD0F+jHTuGyp+n/3zkN6POO49HXeGWu7iahvMAEmIqJ+FQzk/qdofFkBNpmtkNqqB9Ya4OZ4G74XusWcaRNUYlDVGMdak+zaNlSbBDitAhxtnwIttlVV4f1t9U6TqYGqSf3c47ATo3y92ABLyJZAtozGS8OSu/ZW/o3PvR0Jf9g5LfHphmmN6nFSYKbUJwO5dVffJTLN+Oxb0DJV7+88oZsK8A8eexcrt9Ti3iUbsGq7NS24l8Savd+vgLWf8ZiyIlTBPI52rlEJ5ntdT2HuhJtEi7ZaK8nduAS4+2Jg3cv6PGN/5vYmWLIvsE22oBJzztRbhrnk+yOiPscEmIiIBo2xKgHemNJ7ewbq+n/rFVs81jEBmOrT6w6zTYNev1O/f8ROgGX6prsmUHl+2Toc/3/P44KbX+2TyllvkOR8X/9qc6b0VgU403CZAt2VjOUDCTNFWncMb3MSYPfxlPT3YQJsREZOcY5OBbiLBLhxy0q8GrkSt4X+B1tqOt4M2l0xqwIctCrAo0sj2J7SCfD4Df8EfnkQ8KO9gGqrYVsOquF15m6qsqY5/+FYPZ351oX63F3X63IrwB+8oo+2QBjvVxyJj/zpfcQDJmnf/KY+ElGfYgJMRER5N2ustdVLD0gCvMkkwAVNA2u9XKKlY8fX6SYBfj1bAmwqwAtCVtUnOkIlwN66T9kLWLy5vgYbuphi2p+a4t7055Q0wBrXCw2wspE1q8NZlvW8qbD+PSr2NaNBJcByM8JtqpbK1gCrl/nKdVW+zNeEqh1eJ+pMFzf/BZW+OhwVeAsN63p/u594i5cAByJeBXhEYRjLU1PNmSFrbVeafaVz1AJdaRctOzt/3onXpVeA21pMtVkqxZlmHI/vPLURb2+qx+ut5nt84689/t6IqOeYABMRUd7d/MmD8Omjp+GRzx1hruSmMBzEzqCeBhpJqIQzc2phP2rLsuVJua/BaVD0epZO0Ot3NqEc9TjH95S+sMeRKpOYkJYASydo1+vrsjfT6m+SdO3j0xW1phL1Qt7ex3Z3nfwjfZx5Uofq57Bx/l3657/sX+aCx2eajRWrx8m2+hZnOyppviZSfTkF2mVV5ePVnTelK095v6dN23tWfc1Fm9UEK2QlwH6/D3+IXorrWi/HHaO/gFSkVL9hy1J9zFEY3hKEVLXpPZDo2PW6pS79JkBrk1kWUN8xaa6acjKeW6kT5m+0fgKJoHzfKeDey3RHaCLqM0yAiYgo7yZWFOLLJ+2NOeMz1nnmoKXQ6oBbO3CmQSesKpTtQP97WL29EVUN6R2d11c345rgfYi6Se4RphusNQW6yOclwIvWdr6dUn+SDtCVPt2sq7U0o3Pz7jpYJQNXLQLO/Yu5MAzNPFElwXcCYzP27lVChfr3pxjNWLOjKa0CbO+H22esddm+2s73Aq5OeY9p/873zaj3xFu82RHhAm8KtIiWjcTdiWNw4wcH4ZVm/f0mNr/lHHMVtrYqK9umHo+ylVGWnzfZmD4FurXFTYAzGmcFIvhz1d7tux6tTE3Cv/f9rj6JqY+58+NA88BvgEc0WDEBJiKiQSVRMsGMlC5edOdbKmYlwEHvRfg8v67m2FVgWc+7o7ra6RrtmHoUMP04PU6rAHtJc7Zp1AOBJF3u9+mzvvdeIVXfypkqYch9q6zhxGeq7UU+SYAbTBMsvQbYZ+2H22esBLioZQtibXorMFd1YxyL1+1E3Lruq3oPF93yKq66Ywm21/fONl92BThc4FWAxfGzRpsRsCyp1yxj2/KsFdzOhH3e91/Qqn6PpYKcZR1xKJb+O5poNlOg69P3IE7sdTJufyP9htaTqUOAo2/QJ1XvA/ddLk8U+pyIehUTYCIiGlQCFVYzpNqBsxdwMm4lwBfcBYw/0BkeZBLgxVYCvL0hhlFtWxHxmamV+1+gkz1hJZFXLhiDzx23pzNeubUBNU1Ww6wBQrpAR306kfFHejkBpq6Z2QK6AtyIRvX/wp0CnZcKcPFYJH16qyVphLW5xpuxID7+h1dw1m9eRrTNq2bOS76FeWt+i9Cyu3HPa1bztF1U2xhDQ4OptCqRqFdtFp9Vvz9PfP4o/Phj+2El9FrbQFL9G+3IfZqxXQF2rH6mYwKsEuqC1vQlGQl3DbBbAZ65EDj153hsynXY2ah/l0MB/Xu/fLP6GY7+EjDrI8453nsc2LhYj4moVzEBJiKiQaVo5ES0pfSfr7Yu1h3mm89OgKU77+T5znBf/xqnM6/dJVc6QE9UCUO7cmvqsLWGdu4oPw6a4jV/spPogUKqjm4FOGBt4UR5YB4rxb4WZ6st6QTtToEO5CMBDgQRL9Rr8mXLr03WY1yqv0dsvxN3h7+BA31eozd53F8bvA8/Df8a49c9YK7umu1VVdj5g/1wxLKbzBWgINrxJszMMSU4a95ENI7Y21xRtuQ4DTqZRBDplW2sypIA121CIOP9UtIXQCrNjfp3/f4to/BY5MO4dYlOlEcUhXHSPnpJh7Mtml89r53yY/VkYvZvXnKbPhJRr2ICTEREg8rY8iJswQhnHKsyDWkGglZrexep4k461BmG0Ia5vtVOcuKSF7uSMLSzt/iRbsc+8+e5aQcOmFwOvykOD8R1wI3xBKImAQ4WsAKcV24CjGbE25J4Y31NewLsD+chARalehr0eF8VNlgJ8OptNfhq6A4c7F+JkDWF2F4eUFa/yox2zdsP/bJ9qzFXpDB9CrSteMJsxFJBZ5zKNQFOdJx1kfrg5Y6NtGo67kteue4R4NXfqZGeyvx6VRifuX1J+3KIcw6ahCkj9fe7rT6G1kQSKBkL7Kn3V8aKf+ojEfUqJsBERDSo6L2ARznjxACqAKcnwOpFrakAC5kGXd/iTaOUDtBuApzyqxfkJVZjL38AKNRbPaFhG0oKQth7nO5eK+spB5qG5ub2qdxB05WY8sQkwIW+mHpBl8STy7c6sw2EL8u2SX0hNELPXpDH80Zrq64t6zsmt2tnXwF8dQu2+yud82C8Z42eZAnAdx9Zjmfe3eacp5o7/j5Es1SAXXtNGIn3Ujphj2/Icc/dhLdO+dXkLOfok6R41dPOuJ2VADemrA7cT9xoBsDWlDebQ1Y8XHDoZOf5TMhy3/Y10WPm6GOT+vm4Dpio1zEBJiKiQWWctRdwsL7/u0AnkimnqZW/zUqAZQq0VHLKddOdef4VaRVgPQVab4HiKx3vTCVNU6QTBHfq5MF76Ir3m+tr0dKaMR2zHy3bVIs/P/uOOVMvKrgGOL+sjuFSBRbuGmC70tqX3DX5Y7ETVfXe70Dtpo7dngvL9XTppoBO3CMZa2a7891H3sEfXliDS/60yPmdi7elJ4fJlA+hcOc/t9xIWm4aYfm3vpVTcpls9SrAzyfmti+/6GCnl/B/rvVq/KLtDDSH9e+ty06Aj55ZiUkjCp3nM9fmWrOG2t2uKaV+1+2lFUTUK5gAExHRoDKuPNqeABc0b1UZqJdY5ps0Hpr3nSex4H+fRn2tVc2SCrAwVeB5/vfQ0OxVktbbU6DLsmwd1J4A60rXQXvoF87xRBJvbxw4ex8/vmxr+/RnR6jz6afUB6z14qMjOvF1u0AjmId9gIXpBB30JeFvUL+PRuuONWbkGVk51jm2BPX2TdE2r3lVLu5e7HV9r21uRbI5fUlA3BfSpdVOzFYJ8Pup8c44JNVn2XKoG/G4V9WuQineTE03Z+mSKx51jq2pAF5L7o0ft52DOw+9H5h/JRIIYKN6zlppqs/iwkN1Ij6m1EuAt9aZBLjAJMAih++RiHqGCTAREQ0qxZEgqgJ6axO/NJ1pyNhjM49efG87appancpNykyBTkK9AHenn046xDlU+BowMuZN1/7AmgKNcmv9r6vYbN2yYRHwp4/gqJ336nPF3k6pv0mjo0Jrr2K7gzXlgTXl/DPz9WOmyN1XOl//L6z165HGTWYEBOo6rokNFOsbO61hnQAXJk2X5BwVoRmfCfwD83wrsKMhjlCznkXhqgnqpRGdKSsMIRU1ywtERgKdTWurd4Mn4QvixWTH/ZiFX7ZWUhYl90I99I2g6qQ6LvwfXD/1Phwf+yFiCDvXJ5RHcazZnmlcmVex7lABFu5ewkTUa5gAExHRoBMr1FUcRz/uBVxnTWt2OyHH/eoFrVuFmuStA56TeMeZLt2WSGJHbQNGw1SM7QZYLrcCLNa+gNIXvoVK8zrZ6RY7QMhWLvZexawA51nYqwCfMbsUM9WDJOozFWA7iepL1l7AhS26IZU8xktbvGS4XYWuerYV6BkNpal6JNXvRJqdq4Etb5uTdF8I3YcbQnfi3sg3sXZ7A0oT6QlsVbFeo9uVshHevsC5JMBtMe8Gz/SxI/FE4iBzlt1TyQPMCGiK6eeHDS0Rlbrrm2IzxxTjO2fug4DpbFehkvJwUL8cf2dznd5LuUDfIHCwAkzU65gAExHRoJMsnWBGikqAZT2gvOjOt7pmPe1UXsCeMksnHGF7H9LReyMe0Of7+1ahQSXMUuUZndoBv8+88M9WAbYTYJGIY16hnl5a1eCtSexvkgCnTYF2p35TflhToINtjbjjE7PNmWK9rU9ZCXBJTD9G11c3YwL09P00I2c4h5RJgMvRgIaY1xxOmj4lf70A+O3hwLZ3nT2mbZcGHjEj4J4X38IopC8HiFdaP38nRo3W65BFvKHKjDrXGvce39PHjcC7vqk4L/5V3BY+B//d+mnzFs/TSb3/t5B9mUW12b/7xDlj8MTnj8axe3lJuM/nw3izDviexRtwwLeexP8+bfU2YAJM1OuYABMR0aATNJ1nRapmPT556yIc/N1/YdX2BnM1P+pMZ+eyaAhjozoB99tTT/0BNEf1uscKX73z/nYHaIe9B7ArMwFW9gvqKaU7GqyEs5/JC3vpQNxOmn9R/thJbnMNKkPWzZF8deQuKEOLX9/4KGvVU5JXq9/DSabJmyslFWkzM8JXqJtDybrhuhqvk3Pdknvhb9Nrbpfe9S3s+40ncOP93nZFLQiZkfoaa1eh0pfeRTo81nRP7kJRuZd8NtWkf4/ZtMW9CnBRYRT7TijDK8nZ+HrdGXg8cbB5i7Y6ORbrMM6p6orGmG5YV92knycqCvUU6EwXHbZHe0W4KZ7A02utZQWcAk3U65gAExHRoFMxYhTqUvpFd93WNXh+5XbnReaX781xb89eUtesKzylBUG0d2vNWHuZNElKCZpw3T1v4vp7l7Z3gHZkmwItWyFl2Nu31jnK2seBoipzCjQrwPlVZs+EWA/ErBtA+aoAKy1BPfshktBretdtqcLojOTUd9zXzUglvkVed+QGKwl9Z5M3JXn5lkZnyYBURZ39cZUWM41YTPZtQ6nPa1Alxs7Sa+67UljmrRNurrVuRHUiYSXAvmAE86d5a4ibkN5o7OnkAZg3paJ9Xe8W6Q2QSjlr5UVFUfYE+NIjpmLJV0/AL88/wKkS15vnNgcrwES9jgkwERENOrJ1iHRVFW07P8Bx/sW4MvAAqmrz2yFZKrplaEBlRCXCbgKcsQ42ZdZpFqsX66+s3okN1bIFkvXC25pC2m7q0erVtkqCZY9g8/FTW/U2KwOlAuy+sE/vAs0KcF5FK7z1otVrVbJkNZWy1gf3tXhIJ8BFKgGWNb01m70tkFKzzwAW/i9w0KXminxrdhJq3Qxq9ZLNNshNoBRibUms2KJ/riZrf90LA/8yI5VEF4zDO/N/hJET9BTrrhSXe7Mr2qdAy1rgm48H/n6RHr/7z/bvpc1qghUIRXDYdC8Blu7OLSmvKv1U8kCnuVVlif4+X1u7E3e9vh5tZp3ziE4qwEIadH1k7nh8/6y5qFe/Ve1YASbqdUyAiYho0Bnr7AWsX0RHdr6LW8I/xvWhu3Bu64POtXwZUb8Cr0Wuwl92nAesf01fzKgA+82WJiVmn1bRPgW6eCyyblcjlb3PvABc/iyw79nOpXEtq+BD0tlPeCDsBVwfa3Ne2KdNgWYFOP8q9tDHzAQ4jxXgNpMAl/ianHWvse3eFki+Qz8NzL9C/SJ4LzkLSr0EOFbvrcP1N3nJ8AmBxXgz8il8IXgX/rO+xqkCN1oJ8DGBN/WgqBLFX1iMvRd+Sp93o6K0GA0pXUlOuAnw4j/rjuvv/AP4vvr3vPPjwEPXOG9KZCTAB02paJ+uLBpNVbo+FcXryb2c9b1XHjMdBSH98375Pm9WSmcVYFu5SpJHjxzp7GnsYAWYqNcxASYiokFHKsBVKf2iu9h0nhULE8+YUX5Ma3oLEV8rQmhVWYBJcDMT4Kj5Pq3pmhPQxRZIrjFzVKa/rw4lnGh0pn0KaT7V39xpnVF32x3BLtD5ZyfA8f5JgBOm43QpmjDvO/9C07bVzrmjXHd+toVLvCnQqSZvDbCv0dtHeIyvBmUqof5c8AG8ua7KaTjnR5ZGd0d8vsPvXFdkHW4N9ProlOkCHdu0zDmmWXonsH1FWgIcVAlwUSSIaMhborA9Ve4cn0vuh1FlxZg1tgSHThuJ3190kJMo202u3bXB3dlv8gg0uNO9WQEm6nVMgImIaNAZVyppV8dqSsqtmuRJoM1acxk1L+qnHaOPRjCqp6imV4BNpStbA6xMY+eaATDbt845DoRp0LL+V6SvAeYU6LxzE+CaDyCNsNrlqwmWkirQSeBU3xbc5f8Kvh36k3Oe8KmEr2ScM7ZFinUXaJFs8X6HIhn7+rpq1y11thyzbyKJVPEY4KD/Mme5KVdJaE1K/9vU7tyG19bsxJZVppqc6YUfI2lXgMM6Kf2Q2cNXfLPtE7iz7Rj8b9vHccxeo52uzuKomZW46dT0rtS5VIDFxIpo+17CyZb8LusgGg6YABMR0aBTGg0i4c/txWRfkTWwoVa97jch63X/+z3giyuBQ9KnYoaKdAIsU4UDSDhVrHE+U/XK1gArk1SCffrP9Ry/2wir/xNgtwLcPgXar5KdQG4VLupFbgKcbAO2WpXMPFaA/WYdssyG2N/vVX9biiaoN3Z8qRkt9L63gsb1wFPfBpbdj+LW7E2pRta+5ex/bd9EEr4jv6h+waz1sjkIBfxo9OsE+MCWV1H1x3MwtkV/zxtSo3Bd6+WITVzgnOOtuxGpUb/XRiCkE+AbTpqFvceV4tyDJuGV1Bzc0Ha5+tjKtMRYfOKwPXDRfF0BD/p9TmKbC5kG7TbCamtmBZiotzEBJiKiQUeqLKGCjtNtrdmGfUq6015/z1IUpJqc81bZ6zcQBEq8PUZdIVMBFjcG78B1wb8j5DNreLuaAu2SdbVm/1S3AjwQ9gKWtchinl8l/YLrf/vHeG/fWSz9uxkoeWyC5S/UFeAOKjpOfxaRQq86Pe+DW4EXfgTcfTGmJvVWX5kO8L2PF1duSV9vXjJeZbCfNCc90xzw/m1OCixyEnfxs7aP4u7EMbim5jznHKkkpi37pR4rwbBegzy+PIpHrzkS3z97LorD6vdeCavEeoHVIMslVeDvnrkPfnvhPIwuMdOau1EeDbU3wko0sQJM1NuYABMR0aAU6ccE+BdPv4e7F29on5LZ1lX3Y6sS91/Bx3BF8CFzppTlMAVamGnQs/06AR4ITbBkv9Jj/P/BIf4V+kI4f1NuyTJ+f2Ci2f7HbZgUVMmT3JDJk2CRN6XZVlA5zYzSyXZC8VTu398B/veweMV6c6aSwnAp8Ml/AKYi21OvtU43I6A2rG9aNYdH4OnEAc74sR2jsH3Ccc7YFjJToG3lRXrWw6HTRjjrgzMFVWJ8waFTcPzsjjfHOlOhPqc7TRuN2aeFE9GuYwKcmw+p+KOKd1XIfLeNKqTV6DwV3blYhbwmyxZjVWSS245vqJCuIptU/FQFX1UQEWUIF3RMOlPo+zXAMvX5lhd0l9ti0wAqEeriabqrqai5VICFaYQ11leNkah1tobpb03xNi/5FftfYAaUdwuuNgMjj9OfRaTYa2plC4ww07OzaPKlJ5NrfRNQH/K6Q9tm+DahYbu++SMaj/kmMGpPc9Zzv4kvxBmxb2F2yx9R9aklwJc3IHrD+3jmGx9DYVg3uPpN8/HO0eZWgG1XHTMD+0woxbXHzzRXdp9MgZYp1SJcrxJ/9ZxDRL2HCXBurlAhz+I/U3GyCumNLws9XlEhyXEuLlFxWEZ4vf81efXwNxWLVJykQj3DOwn0fSqIiMjiy1KNSaoXipKg9qXt9TFnCyBRbNYkJoJdJMBmG6SsclkDLMZZjbD86wZMBbgSuulSSqq/H7rRGVM/mPURby2wyGMDLFFa3nHqr6OTKdAilpEArxpzIkq+vBL/nnmDueLx+1I43O9tJ1RSlj3hztVJ+47HG6kZaEIBpo4q0jcM/AGUFoTa1+w+s7ljj4Fwluec8w6ZjIc/eyTmTcleBd8VMgV6XUpXjAMJ9RzT4HXHJqLdxwQ4N1epkET3NyqeU3GPihNUSAL7FRW5eFuFJMx26EUnmtxy/KGKJ1RIBxXZy+N3Kq5UIV9LEmIiIjL8wY4vRqULdHMfJ4drq/S6X+FOgS4u62QNpDBbxHQgXaNzTVTG6AqwkHXALa0DoQKsEmCfXp/oM2uUqZ+o5A3z5eWCkecKsC/ayeM/yxZIrhZfekOooFR01c9RPPcUcyXdkX55GaX5urqplIOvnLw3Ljh0Mv72qfntXZtdlxw+FaGADzWpjjNMsk2B7guyVdNakwA7dlrbShHRbmMCnBu98WI66du/XEWOt++7NV+F7BVwq3PmuVuFfK0znTMiInL4snR/lQ7LbnOmvrK2Snd+FrMq9IvncKHX6KqDzpKRXKc/i+JKwHTaHevbiVjbQKgAt2GUSYBRnN79lvqBTEE3j5FOb7r0FbMNUgd2VTpDzJ/++1s6cW/nOHfOvlhy5B8Qkw7S8y5GrEQn0Uf5lzpHx27+fBMrCvHdM/fFYVmaVo0tK8Bp+01Abcbqs7aUH+Fwfrqcl0ZDWA87AdZLLoiodzAB3nXyV0ZaL2bZPT2rh1XIKxbZ+0KmNO+jwuaeW8/wDqkSy9rjzPcnIhrWAuGOCXDUF1MJsD25pvetMwlwwO9DOGGS4a4qbp29Ldfpz65C/WJ9hK++0wrwtvoWxPO0PlhXgM2+s0yA+5/MJjjxf3RjtR7ujbvbslVkZY/eaOfTglszEuDxU/WeuVKRPfC4cxC5bjlw6s8QnHywc12mQbfr4wr3p46aiqR6iVxrtiISzYggHMzPy2Z5bqkNj0fS3de8mgkwUW9iArzrfqVC5sd81znr3BYV8j6XqThWxddUyLO5TIHeT4XLvQ1pNodMI9c6WWDTTl59zMkIr80hEdEQky0BLkIL6vq8AqynQI8vL4AvVu+Mu9xyprNqVXmOHaBdJgGugCTAHSvAr6/difnfewqn/fJFJJN93zSnORZXf5hM12FJdqj/HXAB8Pm3gH0+ai7kSekEYKJ6aRNSCePlzwIf+xPwX49JNmveoaN4wEouU2FUjtJNnzIFJpsO14Ykpigdb876xqyxpTh6ZiWqU97v9dZUhbOXb74UFxVik/vSr9prAEZEu48J8K75tgppWPV5FYvlQhfUXwB8VYVUgJ9XIYnzkSrk1cm3VGTq7FVLd69mZPGPLJCxQzpVExENSYFIxwS4EDFs3Omt0e1tb2+sxbPv6lUx00aqr9+aQwU4XKQTg0y7UQHO1gX6aw8ug+S9726px8YavTa5tzTHE/jJkyvxxDK5p6v5W6oR9Jnvo4gV4GFNEt3/ehy4fg0w/gBgzpnqgZp9CyRXQrZqMqp9ZfAHOnlJOuEgM9BiI/fu8wqwuHjBHqixpkFvUclo5nrhvlRWGMZONwFvrtZHIuoVTIB77iYVktBKu0tvd/SeWaviRRWy7tfldoTOVumVdofZKsO2X6uQadJ2nK6CiGhICkY6JpUhXwLPLt9gznrXepVYX3zrIjSqZFBeB196sPV03dULcnnniqnmxNKTNcDCrQA7U6A7VoDbEl5SXNUYN6Ouvb+tHo2mo3VXbnt5LX721Hu4/C+LUW0+d7hlh3N0cAo0SSOuHuzLm7AqwHWBLjooyxZg1iyK6NRDzahvTass8vbiVaqD+X2MjyoKo9ZtxNVilhoQUa9gAtwzkvx+w8T35MJukNuI9i18t7+/1+pTk13VZ6nw2h9mJyUJWY9sxyoVRERDUihLBVi8umJ9r6+DlSTxE398DTsaYs75Y9Puw1H36bWJju66OY/IlgD3dAq03vplhEyBzvLzFRfInwtta53en7grjyzdjOP/73mc+/uXu9066qGlsi29tnKrnvYdjdkJMKdAU88krVkRjcEuEuBgGDjkcnOiTEyfEt1XRhVH0Ahv39+GSH4f47PHl6LWWWkHJJpMBXjTf9Q/lvV7R0S7hAlw7mTtriS+31Eh+/PuDnkldLgKWQfselXFZhWy76/tbBXyyop7ARMRWUKRjtuUiGSsES+t6t0Xic+u2I41O/R056uPnIC9NmU8JXc3JTNbN9xdnAId9cWRinudqF3FkZ4lwN96WPdwfHtjHbZ08/7jy7ybDavNv0O41XSAFiY5J8pVMuT9/rZEsk1+sxz5RWDv04CZC/X06jwoUr9PhX5vdkSsSDbqyJ/9Jpaj1lSgk407gXcfAX5/jIpj1YX+7wJPNJgxAc6NeuZ11uvKel71DORMXbbDdYsKeba0N777l4qvqzhDhewlfI0Kmf4st9slqXbJs9n1KtSzu7P/r3qWc/YDlr2Hn1QhX5uIiIxwQfYKcKGvBY9ba1V7Q22z11n6kpkx9QyeUYHtqgmWKMpo8HPY1T1PGk0CLMLxjlMioyHZTl7bUtt9Amx3tJUkuCsjisJm5FWAfa3WOuNsa5yJumI9ZlLd/f6E1fue+xfg/L/3aJr17ioLWB3li8eaQX7sN0klwKYC7I/XAv+53Rmj9gOgmVOiiXYHE+DcnGqOkpy+nCVc8upDwu6SIFObz1Vxm4rHVUiS+7QK6eqQOa1Znt3OVyFJtbyvJN3ycXlu50hENPBFCrJXgKUT9BPLtiLRi52Qm601t9GdsjOdJRDR6xS7Ym8Hs596mj+xuw0EsrAS4Gi8Y1Mc+3vsrqIrJpZ7CchbG61qbhay5ZHrva2yNb16AZFgAky7Luzs8mhk2dN7IIgFvaUNkZL8znKoLIkgGdH7OgdS6vfvPamFGHH9O0hEu4YJcG6kGitJbWfhkunLci5NrlzSKVq2JJIODrKD+gQVF6lYqSKbv6mQ7ZFk4YnMt5GKMZ/piIgyRKLZE+BiX7PTBEq2BeotdtOp8M539EAS388uUfG6eobvZnrkrI8AQVO5mv8ZfewpOwFu65iw2s2sNte0OJ2bu7oJYL/trQ1dV5Tsz/3eNl0BDiasJHuAJjA0cPlavW7tKWs69EDyl6JL0JiKYHlyCpLjDjBX8ydZUG5GStK6YWD92xFRzzEBJiKiQakgmr3qeKD/fef4+LKtzrE3uAmwbAMa2PKmM0blXsDI6bk1sypSyetn/g1c9jQwzt4CvgesBLiwrWMFuDHmJekvr67C3l9/DPO+8ySWbcpe3bWndT//3g68u6XzadANVgK8tS7mJMShpNVpmgkw9VSbdQNFpjgPQBsDE3BQ7Df4SPy7GFWW/yQ9EdYV4A6y9AAgotwxASYiokEpWuB1aLWdGtVN9R9euilta6DdIdVUMTe0Eb51LzljTD5MH3M1agYwcZ452QVhbzpmyJ5+bDTGvSTVVdPUil8/k31DADsBlmrwTQ8u67QbtJ0Ai/e3NSDq0x2xE76QejXhrT8mysXLlecgmfKhJRXCpkknm6sDi0ySaEYBkurlsr0OPl9SdgXY0lDf9ZIFIuoaE2AiIhqU7KZPomWsTi73bF2BEajDtvoYnlmx3bm2u9z1tZ8KPOQc4VN/Pnd1KvOuCnoJvz+hk0+bO025IOTHDSfNwiFT9ZpFaQjmbt9ksxNg8eqanXh4qWxG0JE9BVpII6wC6ApwIpC/pkQ0dJx5/JE4qe2HON33Eyw8uJs19P3E/R0SlcXZb7j1qWj2BLilkQkw0e5gAkxERINSKGC3YADa9v+Ec/QhhYURXQV+6E1v/9rdIQnwBGzHiSlp4q/MPgMYMU2P88WaZhxMxjpUa90p0J9csAc+c/R0XHv8ns55WzKFg77zL/zm2VXtHyP7JLtJ/WVHTMVIU9363j/f6ZDsiswK8CurdyIKUwEOcvoz9dzEikL85UsX4e/Xn4uyQmmRMvDI79CJc8bgcx+agT1G5X8KtL8w+/7I8Wa9Dp+Idg0TYCIiGpR8vvQEuGCuSkoL9Jq5Uwt1AvzBzo7NYv7yyjpc+qdF2FzbcRpxZ2KtSVwW/CeCMFOqj7hWH/NJmm4ZYcTRmvASYElo42a6d1FY7wc8SSUYtu8/9i5+rZJgYVd/J40oxPUL93LGm2tb8MTyjltIZSbA9y7ZgAKfrgAHBuj6TRr4RpcWoLww/1OLc1VSEMLvLjoIX/iw/v3It1CRV4FenfS2YYo3MQEm2h1MgImIaEgIFpYD049zxvvHlqhktQ1bM7YDSiZT+NoDb+Opd7fh6r/+x1ztXqBlJ84LPKNPpn9o1xtZ7Q6/H21+nSxE0IpYm9f0qsla/1sU0QlwsTnafvj4Cjz4xsa0BLgsGsIZB8gGBdq6qvSbBrKOuqW141rqqJkCHe5kOyoi2j2RojKsS452xn9JnOAcRVsLNwch2h1MgImIaOiYeaJziCYbcJB/pbMO2N7uJ9bmJXKL13XspNyZGQ2vI2oqnljwWX3sB0m/rgLL+ttH3/IqtY3WPr3FEb02urigYwIsrrt7KZ5cvtW5QXCK/xWMbduISDCAUcU6ud5U04zlm+raG3953aXTp1zPHmU+PztAE/WJ0mgYZ8dvwsfjN+K2xIfNVSDRwgow0e5gAkxEREPHjOPVf/TU6GP9/3GSX7sBlLvutaeCrVbFpXKWGeRfwkyDlgrw9fcuxW+f01Oa7XW7hWYKdCjgT2sUVqISYlk3LVOlZTr0OYHn8Kvwz3HIo6dIaRzjynQie9frG3Dyz1/ARbe86pw3xNsw1bcZr0Suxj0jfou9Rhfj22fsg0klZgo6E2CiPlEaDWI7KvBycg4SCCCW0mulkzFug0S0O5gAExHRoHVJ/DosSs50KiSOolHAxIOdoUxZnubbhC213jRodz9fV+Z5Z3wJayp1PyZ8STcBNtXoH6hEdsWW+rQ1uvbUZ7sKPHNMCf73o3PNGXBD8K/O0S/7+Va9rxLg9G7Or6+rdqaMS3L91eDtGOurxkFNz+PxiyfjovlTgFazhjrENcBEfUHWINsaoX//U0yAiXYLE2AiIhq0Lr740/jp5F/g2ssuNVeUBVc7hzJfE64KPoAt1jrgzArwqu25raULtFkNs/qx63HSbDkkFWAhs7u/+dAyJ0ktQjO+HLwDkzY/5rxNSNXXVarGZ82b2N4d+oPUGOfo2LQE48s7/lw1za2ob2lDpa/GXFEatupjewLMCjBRX7B/f0UTzE2qVibARLuDCTAREQ1aR8+sxB2Xzceh00aaK8rs09E6Zn9nOM23Ja0Rlruu1bV6e24vJIOmApyU6dXWfrz55laA3T14xUurqnD36xvw2eD9+HTwEcx47rNAS53zthKrGuxWk645bk98/6x9UTJmqnPu2LikQwVYVDXEnOpyTarYXFFqN+gjE2CiPlVqVYCDfh+aTQLsZwJMtFuYABMR0ZATGKO3LRntq05LgDOnPNc0eYlkVwJJ/TnapAlVxvZL+VRSrBPRcUU+vPaV41Bh9k/9x5ub8JHAK87Y0bjdOdhTKGU9oZDto849eDKmlFovAVY+ikmFXmdoV1VjHO9srkMNrAS4Zp0+tppu0UyAifqEXQGeM74UMb/+XfO7v3tEtEuYABMR0ZDjLx3vHEer1K2pxUvsMqdA29sBdSWY1I202vwdq6T55A/prz+nMuzsoWrvT+o2yHE06ynL9npgu5rkiFmdZGs+wLFLr0PIl/7vU9UQx+trdyJlGos5atbrY5u5scA1wER9Qm5g+c2v3gGTKxA3CXCgjQkw0e5gAkxERENPyTjnIAldsKXKGYvMKdB1LV7zqM5IJ+mwSYDdLsz9xl1/bJLP8w+ZjKKw7vQcg97GyNGkf+ZgwEtcS6MZCXA8ff1zdP3zeHm/x3HzRfPMFTgdtBetrXbWF7dTyTJSKVaAifpYOOjHp4+ejlljS/DJBXug1dyAm97ydvsyByLqOSbAREQ09JSMNQPgpTeW4TsPL3caXmVWgOtyqADLtGl3D+C2QD8ne+764zadkAf8Powxa3dbYCW4TTucg71zb2ZDnfYK8OzTgbG6O/Sod2/HMZF3nbG47eW1TpW8SKXX7SQBTqh/j5TZU5kJMFGf+dLCWXjs2qMwdVQREvbzz32fMgMi6ikmwERENPSU6CnQYoxvJ25+cQ2O+/FzuObON8xVrc6aHt0ZSZojpulUqr8rwG6yaXWlHltqEuCUVQFu1AmwnQHb06EdMVNBKh4DnHeHHivBtc/iywX34iDfu1hlmoSVB+0EeF369Ol+7IpNNJw0hq1mfysfAzYuNidE1BNMgImIaOixKsBjfNVm1FFdc/dToJ0KsKmAJvs72cuoAAs3AXY6VLtkCnQqhYCZui2CfutPvkxhjpkp0JESleFOVsdSff7iT/Bp3It7It9yTqXn15QSK5OW6u/WZeZEYQWYKC9erfwYXk3OMmfKm3eaARH1BBNgIiIaeqSqaYw1CbC7zU8xmjDHt1aNUk4FWKb43vTg2zjrNy9h6QZrv1tDEuACn64Up4L6c/Qb9+u7WxAp7hToQp9Vpd25GrjlBPxg9Zm4LPAIfhL6Faas/pt5oyIfnzLTwSUBFqZxmM2n0urPHD0dhSmvk7Zj/WtmoLAJFlFehCqn4dz417EqqXscoGGbPhJRjzABJiKioScYRrNPJ2YlKuEV+0woc453h7+FRyJfwcn+V501wNfe+R/8+eV1WLyuGn999QPnfWzN8WR7Bbjfkz03Ac5SAS601+m+8w9gwyIUpJrx1dAdODPwb+zzxjeBJbfpt9tTmMNmi6PSCfpomT+xAF84YWaHhll49ntmoBSYyjER9alzDprkzMioV7/toqm+89ktRNQ5JsBERDQkxWXPXqXArN+dUB5FCG3Y26+T3F+Hf44N1c14ZoXeM1fUxzpOiW5Q19zP4TPbEPWb9gRYKrh6WrK7v28RMqq02TzyRWD9ovSE1p36nKUC/Kfz90JI9mHJTIDdBljTjgGmHqXHRNSnpBHWqXPHoy6lE+AdVd5zFxHljgkwERENSa0+nQAv8C/D0f43MbksiMKMJLEtafdJBloytkkSTgJsukD7w0XOsd/YCbisxVUKwzoBLvRlJMCFo8zAIh/z9wvVK+eV5oLiToEum6iPlojsN+pMlzYJr0uqxqf8H3Dh/Wrcz/8mRMPID86ei0Yzu8Vvz+QgopwxASYioiGpzVSA9/BvxZ/D38cF/z4R3w/9wbnWmZa2jglwfUtrewU4GBkgU6CFWQd89MxKjC8rSK8AF48FLn7EnBg+8ye/YQvwt/P0WETcKdAdK8DOVOm47gTtOPoG4NSfAVe+Ahx8qXoVwZcRRPlUEAqgYoS+uVWQSE+AH166CVfdsQTrd5o9uokoK/7lIiKiISkRSJ+uHIlXY2FgkTnT/NI72WdtJdSaUelUpAIcdRPgggGUAJt1wPKC+OkvHNHeqAvj9geueAkYtac+d42ZAxz4CXNicSvA5VP00RarTZ/+XKHeZ97F6n0nmQtElG+hogrnWJRqQrM1a+WmB5fhkbc246SfvYCUWSJBRB0xASYioiEpMwFORHQTLNs4VOGkfcZi9ni9DlY6Pmeqb/YqwOEBlQB7naAL7C7N+56tXhmPVH/hA16DKxFWie7JPwImHmwuGO4a4CmHA/udr8cupwJsJcD25yOiflFYohPgqC+OD7bXOM9bd72+HlWNcVwbvAc/S/4PXlv2nvM+RNQRE2AiIhqSEgGzZ66RHLOfGXn2CGzHlcfMQEFI/znMTIBfW7MTP3/ibfh9upoSjAygNcBWJ2jErSmP9ppcO2GVSq/sI3zu7cCovfS1GccDI6bpcSAInPkb4Nq39bmQBLhatowyuN6XqN8Vl480I+DR11fgoltexfX3LMVU32aVAN+H4wL/QerZ/zXvQUSZmAATEdGQlMqoAAfKzd6Zlu8cW+5sj1QQDDjnmVOgz/ndy4iY6q8jGDWDfmJXgOs2mYFir9PNTHpd7lrfkrHAVa8CX90OXHgvnDngNntbI0l+pWmWy/58RNQvRlR4De7uf+UdLFqrt0M6yr/UOYo5Ox4zIyLKxASYiIiGpGRGsuov6ZgATy3RCW8kpBPgWJYmWO76X0eonxNguwL713OAhm16nDZN2XofO2G1E2NJeoNhc5LBfr9Ft5iBUjIeGLuvOSGi/lJUNsKMvH3OhXS7d0VTzdi6jdskEWXDBJiIiIamzD17i8eYgaWlzjl4U6A7NsFyt0ByhPp5DfDEQ4DJh+mxbGn0oz2B700Afn+0vibSEuBOqsFdsdcOt9ToY+lE4Nql/X8DgIjU77I3S+N3H5uBoydHcHHgMXwo8Ia5CgR9Sax+/VEsfu4feOkHZ+CdN142byEiJsBERDQ0WRXgFoSBaLk5s8TcBNidAu1VgN0uqukV4IykOt/CKgG/5FFgzpnmgmJXf0XISoDtsV3Z7Y71Attx7FeAQMicEFG/KvAa+k0oaMX38HN8I3SbueJJvPc05j1zERY0PYPy+zMa3BENY0yAiYhoaLKS1RafGmcmdcJNgM0a4LZkCm0JXQWOteljFFazqf5eAyxk+vIZvwU+8hO9L6+d5Iqo7hDrsNf39mT9rv2+RZXAPmeZEyLqd/Y6/TXPYcK258xJuik1r5gRMM63k1sjERlMgImIaGiypivHEEl/0egyU6CjYe/PYYtJfOMmES70WVsM2VOK+5Mk9wf9F3Dsl4HS8eaiIVsgZdOT791OgA++LO1mAhH1M/tm3qKbzcBTGxrtHCelNjtH15Zab+s0ouGMCTAREQ1Jfmu9asIXTH/R6JJtfpRD1v0BL0Y+h8P8y9qnQcdNIlwMKwHuyTTifCm0El6/+jkL7KneVgW4J9+7e7MgENaJNhENHDLLY8oR5qSjphknm1G691a9b0ZEwxsTYCIiGpL8YS8BTkoimK0CLFOgt72D/Vf9BhN9O/CpwCPtCbA7BbowLQHOmG48ENgJsIwztzVySXKcK5nyLMnvEV8AinU1iYgGCPkd/+RDwGeXAFe8jIbZ55k3aJVzjkUNOi552LbuXTMiGt6YABMR0ZDkl4ZRRkr+3EW8xjHtZAr0cz8wJ7JOrqpDBbgobQp0D9bR5kuhtyUKCr39QTvqwfq/Ay4Ebtyip1gT0cDjV89pI6cDY2YjMDW9GhyMlmFVycHmzOOrWWtGRMMbE2AiIhqa7IZVUhTNVgGu2wi88w9zAmxIjW7fCqk9AR5MFeDM9b92wu7vYRdn2Q6JiAa8SFHGzT31e9+678fNiaewcYMZEQ1vTICJiGhISgQiZmQqwNm28ZEp0Mk2c6JeNyKepQJsGsf41Ofo732As7ETYOtndnzoRt0lunwysOcJ5iIRDSX+zJt74WIcdNzZ+FmbtV2aEo7tNCOi4Y0JMBERDUllpV71szCSW/Uz4mvF2b99GbVNrYi16US4vQmWNJHqbH1tfyqypj1nfn+S+P73CuDq14FgRnJMREND5tKMSDGCAT/mnP99LIzchjXJMc7lcGutcyQa7pgAExHRkDSi3OuGPKI4t218pAIsbn91XXsFuL0J1kCc/iy6W5csb2fySzR0ZXa4Nx3fj589Bo99+XT1JKb7BETb9LZvRMMdE2AiIhqarDXAfpm+LD79AnDkfwPHWM2dQoVoHL/AGUbQ6hxlGnQskUQpGnBCYLFzbUBugURElHkTLOO5Kh7Sa4SjCb3tG9FwxwSYiIiGJumS6nKnBo+bCxz3NWDUTH0uZMufokpn6CbAFYVhxFqTuDn8Y4z0mReNA7UCPNHq9nrI5WZARMNGZgIcSN/yrC2sE+CSVD2a4wnc/MJqvL2R06Fp+GICTEREQ1PK2vbHrQC7ZPsQh0qMD76sfc9gWQMsWtoSiCeSOMS/wjl3dDfVuL+UjAUueQw45zZgxvHmIhENG90050sW6OUgZWjAjfe/he888g6uvGOJc41oOGICTEREQ1PxaDNQph1jBsa4/YDz/gpcdD8wfn/4Q3qNsFsBliqJuwa43UCeAj3lMGD26QOzSRcR9a3ufu+jFc6hzNeEd954CfeFv44T6+91rhENR0yAiYhoaJIOyAu/D8y7GDj6enPRMusUYPqxzjAY0RUUNwFuUglwrNXbHskxUKdAExF1wV+oE2Dx89AvcaD/fVzlvw+tiYybfKTJ7KFExvM/DSlMgImIaOia/xng1J91m7wGTAW4wHSBlgS4tVWP27G6SkSDULBId4EWe/o3OscitKDZ7HlOFkl8bz0J+PFeQPVac5GGGibAREREQZ0Ah3wJBJBAc7wNiXjMudauaacZEBENMFOP0kdZCpEhXDLSjDzyXNfSkvEcR8Ca54APXlbP9zuAf//cXKShhglwbj6k4o8q3lXRqEJunz2oYp6K7nxUxd9UvK+iWYXcTrpDxZ4qMj2rQrq2ZMZjKoiIqK9Y++SG0epUgBOtZv9fVzMTYCIaoKQJ3sf+DJz+K3PBEy3xKsC2luYmM6J2W5eZgdLGGwRDFRPg3FyhYg8VP1NxsoprVEh3lVdUSHLclS+pkMVl31WxUMVXVRygQtrvzVGRabWKwzLiWhVERNRXTAVYyDpgmRqYaM148VM6wQyIiAYYaXQ154ys3epHjx5nRuliLUyAO9j8phkoEe79PlQxAc7NVSok0f2NiudU3KPiBBVVKr6ioiunqpD5KLeqkI+9XYXsUyHlhs+ryCRVYkms7ZDKMxER9RWzBlhIAiwV4FRmBfjD3zEDIqLBw18xCamQ7oNQXXmIcxRMgDNI86sNr5kThctehiwmwLnZZo62BhXLVUxyzjqX7WM3qdigoruPJSKifLAqwAW+uJMAJ+0K8Fm3ACOmmhMiokEkXATfZU86275V7XWeuQjEmxtx16L1+L8nV7IjtFj3ElDzgTlRmqTORUMRE+BdV6biQBXWYoGcTVMxRUW2j52uQm45Sf/1VSpk6nRUBRER9RVrDbAzBTrehmSbVQEOhM2AiGgQGjNHvcL8EIJh72bfkjVbcP29S/Hzp97Dv5ZvNVfzoKUWuPkE4K8qGc+cadOfFv3BDAz2fRiymADvOukyIPNJJEHtiaCKW1RIBfkncsHyooovqDhLxWkq/qlCNq+UJljd/b+SNcmyptgOSaaJiKg7GWuAO1SArbcTEQ1WoQJvS7h/vL7GjICXV+ex2rn6OT3VeOWjwBuyMnAAqN8CvPOQOTFYAR6ymADvmm+ruECFrOFdLBdyJJtISvJ7pIpPqFivwiYNsmSd8TMqJPn9rIobVEhv+4597dNdqeLtjJBO1URE1J20CnAczbIG2O4AGmQFmIgGv1DEm1To7nsuappazSgPpALsevGnwOu3An/6CLBVVhb2k8V/ApIy+VKZaNZJN1XrIw05TIB77iYVkqjeqOKXciFHkvzerOJCFReryDU5dW+NzTfHzvxaxT4Z0V3STEREwqrwnh54CU2tbekJcMBLkImIBis7AY74WnGifxEuCTyKtdvrzdU8iMskSKN2PfDwtcDaF4DHZOOUfpBQyb8k4WLc/sCe0udWiat/kzbvJgENHUyAe0aS32+Y+J5cyJGb/F6i4jIVuzLfo7vuBNJsS9YU2yFriImIqDtWAnxR8F/YP7UCybi1No0VYCIaAgoKZGdObR/fWvwu/BPcFPoLJlW9iJR0Qc6DVKyTZHvN82aQZ+8+AjRs0eNDPgUUWvsmcx3wkMQEOHdfUyGJr+yD8U25kCNJfmVVvSS/n1ZhbjHl7JPmKNshERFRX8hY43tq4GXUNzWaM4UVYCIaAsJRbw3wWQEv4fxQ8t/Y3pCx93kf2bpjhxllGNFPrWvWSgseJVQI7HMWELUSYK4DHpKYAOfmiyq+pUKaUT2iQqYj2+GS9b2ygEA6PLt+ruJSFZL4vqXC/rgDVLhkXbB8fkmSZe6F7B8s05ql0vy0ioyV+URE1GusNcBiY2oUauqsaXoZbyciGowC1p7nM/yyK6fWmgpizXbrpl8faqyrcY51Ka8a7fBJzagfVK/VR0nAQ1GgqFKfi/rNZkBDCRPg3EgyKhaqeDlLuAIm7N9g92P/S0Xmx92vwiW/YQkVUmmWZPcuFUeo+LqKk1VwgzYior6SUQFOqKfysM80RBHcBomIhoJOOtpP8m3Hmh35SYDdKdDVqWJ8PiQve43GjMpws0qUNy5WH9DHU7OrTTfsClO/GjlDH0UVVxMORUyAc3OMCklqOwuXNLeSc3MrybGHisz3d0Pe5npfxSkqJqqQZyfpUjBXhVSA8zMnhYhouMp4UVjsj2PhXhXmTOnkRSMR0aBiVYBtk33b8pYAu02wGtVL3fvr98aq2Vc752hRCa80pHLdfhbwhw8BS/5sLvSBZAKo+UCPR0x11kH/6KVatPhMs7AdK/WRhhQmwERERBlTnK84fDyO27PcnClsgkVEQ0EnN/PG+aqwbru1PVEfCpgEuMGp9wB/etNabtJkmk7VbgA2vu4MWx/9Ch58Y6Mz7nV1m1TSbTo9V+yBl1ZV4ZfPrsKKxDh9bdHNugpNQwoTYCIionARMPFgcyJTcGLqRRG3QSKiISbjuSwVKXWOQV8SjdvXOeO+FmzTleaGlK6yVqdKnKOjyUyDXuetMNzaGsU1d76BpRv02uFe5a7/FRVTcd8SnWivSY11jo7bzlDfrGy2QkMFE2AiIiJpvnLJo+qvYlCftzYB9j7AbIJFREOBP/2lv2/CPDNSb6pZh0Sy77dCCpkEuNFUgKugk3CH23X5g5f0UVmfHO0cX19b7Rx71Y4VZgC0lEzBv97Z6ozX2glwrA54qicbwNBAxwSYiIhIBEJAmbRhUOJWAuwLqL+W0t+QiGiIsRLgcamt2FTTbM76TiSpE+CCojLnuNOuAJtGWCl3ayIl6tN7sr+zWSWive2DV/UxWoH71wZR26zXID+QOBzN/mJn7PjPHcDGJeaEBjsmwERERK6Q2SNTKsDuujBWf4loqBo3Fym5yadM8m3D6jw0wipImiQ7UorrTtxLJcBWBVgS4Jr18FnNp0qhno+V5X2SAL/iHFKTDsWtL3lTwNemxuH66Q8AV7+usqWQupICHv0SkOSmLEMBE2AiIiKX7AEpWtULNLcCzC2QiGioKh6LROkEZ+h0gt5uNaTqTZI4SjOpeBOi0BVdhItx5THTcf6HDkRTSt9obN26HFj9jDN2lfl0Uv7e1ga0JnoxAa3dqEJ3gF5btB9Wqs9vq2lRX2vUnsBhV+oLG14D3pJdSmmwYwJMRETkak+ApQJsEmBugUREQ1XhSARG6F05+3Qv4Psu01saPXSNuQD4Corh8/kwcUQx3klNdq4lNi4FVj3tjF0jffUIIIG4Sn5X9WaCvnO1GQD3bhrhHAtCfuw/Se8A4E6HxlHXAcVj9PjJm4BYH90koLxhAkxEROSSbtDCaYLlToFmBZiIhqiikfBVuAlwH02Bfudh4O17nWFq1VPOUQQK9Nrf0aUFeDupv4fw9reA99MTYPGfyKcxCrVYvqkXp0G3eNs+PfNBm3P86IETMXlEoTNuT4Aj6vs83jTBatgCvPe4HtOgxQSYiIjI5VaAnSZYZpoet0AioqEqUgaUT3GGUmndst1sQ9RbYvXAo9ebE8DndnlWglG99nd0SQTLUjoB9ifj6mN0Yvqf5AznKEp9TTgz8ELvNsKS7s5GPXTSe8mCPVAWlTW/wPqdTfjl0+9hyQfVwN4fca45avS0aRq8mAATERG52ptgNbMJFhENfbItkqkAi6KmDWbUS575HlCn99bN5C/R04qdBDg51RnbHkkcakbaRwKveI2wUqndb0jVYiXAqSgmlEex55iS9gRYdoT60RMr8ak/v47WoPrbYPZMRt0mfaRBiwkwERGRy14DzCZYRDQcVHjJZ2Xblt5rNCVrbF/9rTnpKDpKr/sdURTGjsLpThLqei85AStSk8yZtp9/NRo2rUQqmQD+fCrwk9lA7W4k7BkV4Ekj9Nd3E2BXVWMcr67eCZSM0xeYAA96TICJiIhcaU2wWAEmoiHozN87HZjx4e/q8wo9BVpIJ+j6Fr0eNs2im4Gbjwe2vG0u5GDTG1DZqjN8IuHtN+wqG6Mrz9IIa+6UUXjXSnifT85FbcrMyLEcHnsBO1e+Aqx9QWWtm3VTql1l1gC3IIw2BNvX/pYVpifA4vFlW4DS8fqECfCgxwSYiIjI5TbBkvW/m5fqcYHuCEpENCTsdy5ww3pgwdX6vHAkWgM6+Zvo2446t/mT7ZEvAhsWAX89x1zIQcM2MwDeypjiXJUqwegRZeYMOGByOVYkvQT41eQsNKJjB/5TA69g/Zbt5kyp8fbu7TFTAa5L6Z+9PQHOqACLJ5dvRaqnCXBjFfC7o4C7PglI1VpIc8XXbtZj6jdMgImIiFxuBViYRiw46BJ9JCIaKmTtr8vnQ0uxTj6lAlzXkpEA22ttO1nPmybeCKx+Dq07dbOotpQfH6RGO2PXVoxEcSRozoADJ1fgN22nOYnxsuQUPJfcDyPGepXp7dDbFO3t/wDxNf92xg5TYd4lZg2wO/V6kkmAK0s6zvrZUteivmf9PaBhK5DIcpMg0+t/BDa/CSx/AHjvCX1t2zJg0R/0mPoNE2AiIiJXSL8AajdzoYoTzQkR0dDUWqrX42adAu3eDMzVvZ8CbjsNodd+5ZxWoRShIpM8GjuDo52pz669x5ViIypxaOxXOCX+PcQQxlmH7Y2Px2/EV1svwatH/cm8JzBrw91mpLiV1V1hKsBuB2i3AjxzjN6eKdMbte7fh5ROgrvTvNMMlDUv6OOm/+gj9SsmwERERC47AZbmVwv/x5wQEQ1hpROcwxhfdccp0M3VZpCjFY+YgbY9VY4Zk00DKaMxkl4RlmnHY0ojzlpcwAe/yo0X7jMW1152KfY5/QtYePSRWBfe03nf0oT1/bi9GnaFqQDLFOhQwIdplcXOuV2ZFm6e/sIWa2p0TtOgvQQfH7ykj0yABwQmwERERK6IfgHkWPA5YMQ0c0JENHQFi3WFVvbbrW82e6AbbY09TIAzbE+VoaKi0pxpzYVmPa1lz9Fe5XXuxHKUF4Zx6LSROO+QyQgG/Fg3ruNsnFQuldhOJJp1ZbseUZw4Z2za2t/CcMCMgONm6WT9zRprTbK1vrlTTdaeypL4blgMbFxiLlB/YgJMRETkmn4cMPEQ9UpMvdA68gvmIhHR0BYuHmlGQEt9esLbVGs1ndoF1f4KFJenT4GOlc8wI49sh+Q6fIb3/biSe59hRh5fU5VuLLUL3AS4LlWEMw/QFXDXYSrxdl1wqF6LLJXsdm/drZtcdaUx49/t5g8BW3vQRZv6DBNgIiIil1SAL3tSveK5y+sITUQ0xIVNBVi0NqQnds113SR6Nnf/dEtTqEI9nVaYMy01aqYZefYa61WAD94jPWEWU/ecjSXJjolzt+txZZ1wrN6cePxxfU3WAI8pTe84/e0z9sEeIwtxytxxOGavSkyvLHLWMreTxlZ/UQl5KmUuZNFoVYBpQGECTEREREQ0jPkLvYQzkTHlOV7fgwQ41mAGnvJQAtEiK3lUCkZPNyPPhfOn4JCpI/DRAyfgqD3Tp0yLSRWFeAILzJnl/X+ZQRaSoN56EvD9PYC7LwGWmgZaiVYEE83OULpAZ259NL48imevOxa/Ov9Ap1mXTJGW9ck7U9YymS1LgbUvmpMs3AR4r5OBE76t4/RfAWf9UV+nfsMEmIiIiIhoOIt603tTGU2vWjPXAGep8rYzVVXbW+XHoTjqTW8Wo8syOu4rkoTe9enD8H/n7A+/dMHKINdWjz4ByVTG2x79ErDo5uzVWNm2af2rQLINWHYfcN9lQO0GoLnGvIOuAJcVdtz713bC7DHOMW0atFh8qxlkkO/FXQM8cgZw+Od0HHAhMHaOvk79hgkwEREREdFwFrWmKFvJoUg2Wdv5iCxV3nbW237pvxCnx76F6pEHpHVW3pga2WHKca7GTJyGn7SdhTeS0/Gt1ouQkFQmoRLyR74I3HVRe2fndtXrzMCyY6XKZN81J8AHGIPicHrn50zTR+vKbw2sCrBY/g9g67KOX0emXLsdqotG6SMNGEyAiYiIiIiGMysBDsTSE+DMhNjdPzeruJcAv9YyAW+mZmBkcQQlBUFcEr8ODyfm46L4lzG6JGLeq2dmjy/FLxIfxRnxb+OPiZPwufA3gRLTUfqdh4D/nQT8aj7gJu3Va/TRJm/b9o45ATaFp2atONtKVAJfEPKjABkNt5KtwG8WAD8/QCXVKrF22Q2wijpO56b+xQSYiIiIiGg4K/Cm9obb0hNcX4vuluxKZFZZbVYFuCEVdY4ji8IoUgnkM8kDcHXr57A6Nb7DXru52ntc+lriJxv3ROozLwJlKvF1bVfJ7Qs/1uPqtfpoq9+sEuBlzrBOfY/N0fQ9irORdcCVKmkvQZO5ogT1z+dIJYB3HzYnilSFXcXpex5T/2MCTEREREQ0nAXDiPn0tORoRgIcjKdXgFsa1HkyCbTqJlJprDXAjdCfb+qoIhSGvH11hSSUu2KvMV6naBFPJLEtUdRxz3ZJcsXOLBXg+i0qQV3uDFemJqGsMH19cmdGlxTg+eRcc6YcdpUZGE9/G1j9rB7/5y/6GFEJ++TD9JgGDCbARERERETDXHNAJ5eFifRGVoWx9O18iv56GvCdSuB744FnvmeuGlYFuBFRnLKvbCM0utspxrmKhgO4fuFe5kw79HtPoSVUZs6MQEQlv6uBzW/o8z2OBMon6/Ga54FNS5zhu0mVAGd0gO6MTNv+adtZeDp4BHDi/wALrlYJrvV1U0ngttOBOpV8u52p9/0Yt9QbgJgAExERERENcy1BncwVJr0EuL45jqLYNnNmka7KkvAtuc1cMKw1wLK90PfO3BeBXkp+XVceMwPP/PcxsIvIT65V34/tzb8CPz8QqHrfOV0fmIjmiFmLK9sXqe9fGmj9LXEcSnNMgGUKdA1KcE3b54DDrtTrpi95xLzVsvTv+t9GWTfuRJz3+5fxm2dXOec0MDABJiIiIiIa5mIhXQEuSXkJ8A8efA2FvizbHk2ar48ynTjRqjK9l1W8lFYBLiwuS9te6KZTZzvToe+83HzsbpDP8+BVh2P/SXrt8uqmbE219LZIi3z74OPLD8Wzm9LTnlt8Z2FZao8eVYBFfUsbWloTzhhj9wXmnqfHrjdU8q2kwsU47cFWvLJ6J37w+LvYVNOMWFsC3/2n14CL+gcTYCIiIiKiYS4R1FN1I6kYkskU6lpa8cbbVjMn470FPwT2P9+cqSTztT8AfzoZuPUkXXlVYqkQpo5J3zP3ksOnOpXb+dNGmiu7Z+7Ectx7xQIsnDMWNamM7YmEL4DNFzyLjzV/BRtSo7HN2sM3NXYufhI7zRnnngB7Wzdtq7NuCoSsZlhixwrnsGnEfNTGdZlatgV+8I1NeGtDLZ59N0tFnfKKCTARERER0TCXCpomWIijuTWBh97chJFJb/3v5+JX46zYTVgzQSWOZRPNVeXxL6sP1lN+nXW3SgMKMK4sIzHsAzK9+qfn7Q8UZkmqoxXYGJpiTnTDK5H0hdB8yq/QnNSNuXJNgCtLvSrztvoWM1Ii6Y25XO+VHmpG2u+eX4U/v5xlX2LKOybARERERETDXMps61PgUwlwvA33vLYWY31mP11lcXJPLE7thUb1tvaGUp1oTBU4e//mQ0EogGhZlr12o+XYXOslqvckjsK3Wy/Eowf/EUtazN7ByqSKQjPqWmWxlwBvr7cqwPOvAEIdG129VTDPjLSaplbnpgL1PybARERERETDXVgnwKWygdEfDsddO87EDcG/OddS8GEbKpzxzsZW9U4TnHE6H1IBvaVQNUpQmqcEWPiLsleAt9Z5CXAMYdySOBnLAzPxtJmGLBXkI2aMcsbdGW1VgK+4Ywn+/b6pjpeqZPpLa9S/n1UJHrUX1rTq72lCeRTfPn2OM6aBgQkwEREREdEw5wvpSmiprxnFde8j5Eug3NfoXEPJWBQX6gT518+8j8/eq9e5plHv0/zRP+OV5N74ZdsZKCnIbWpxb4iUZqkAF6RXgF1rdzThsbf1PsHzJlekNerqysiiCOyG1lf9dQnibWbqd1Alx+rnbzfjeOxojDvDkcVhXHTYHvjBWXPTOldT/2ECTEREREQ0zLkJsG1dcCpQuTd8x34FX/iw3n+3SiV2MpX37eQeznm74jGonnAszot/DU8mD8rbFGiRbQp0UiXAW6wKsOuRtzZjk0mMT9vfmwrdHakWj7KmQcuU5hfe227OFPXzt5txHKoa9DTpkUW6Kn7OwZNw3xULcOPJezvn1H+YABMRERERDXOBSMcEeNVBXwOuegU48BM4/5DJuPKY6Th4jwpUFIZwbeuVaIFVPQ0WoL6l1ZwgrxXg0rIKvJmcZs60v71V195xedbYEuw3Ue9z7FowfaTzM/WE7AVsS1vTW2ISYFlLPeVwlQC7FWDvYw6YXIFjZo02Z9RfmAATEREREQ1z/iwJcFmJt72QVECvXzgLd39mAT511DS8n5qIL8avMG9Vkq3OHrmufFaAK0sK8LH4TXg44XVe3pEoRGNc79e7l0qA50zwEmBJ4H9y7v7w23OacxAN6c7RrieWb0Wz+RrO1lBFlcAR1yIVjGCnNQWaBhYmwEREREREw1ww0rGTcTDs7X1rG1emr29PWVXVZFtGBTh/CbAkmXGEsDU1wlwBWnxRTBlZiBFFYZx78CRMHuEl+D88ez+MKc3+s3WlIeYl+KJJJb8/fmIFnlu53Vn3i+veB465AfXq/eIJvT7YnQJNAwcTYCIiIiKiYS5UkC0Bzr6X79hSfX1Dylp7O3NhRgU4f1Og3bW5AZhqrFIYLcBz1x2LJV87AQumj8J5Kgn+2LyJ+MHZc3H8bGu9bg/E3KZXlptfXINP/vE1vLG+xlxB+/RnIc2zaGBhAkxERERENMztSgV4E0bha60X447EcUguuAZ1zV4FOJ/bILnTjENWAhwJpyee5YVh/PBj++GcgyaZKz33FdPAanRJBKftl95A64xf/Rt3vvaBM35va71zFPb2STQwMAEmIiIiIhrmQtGOCXC4oOO6YDHWJMDiL4kP48bWS3H8LxZh+eY6czW/FeBIMIAvnzQLPngV2oJI7yeex+89Gn+/fD7uu3IBPnpgx72Qb7jvLcTaEs7aYBEJ+jFvit4/mQYOJsBERERERMNcJFsC3EkFuCCjGZRYvaMRf3ttvTMO+n3qffKbZnz66OnYsu9nkEj50JAqwKrRJ5i39B6fz4dDp43ExIpCHD5jlNNdOpNMf37qHZ0AHzWzEoXh/FXCKTdMgImIiIiIhrlsU6BD0exrgEVXDZSlAZYki/kWL90DR8d/gmNjP0a0dJS52jdCAT/uuWIBxlvVcCF7A1c36angJ+ziWmPqW0yAiYiIiIiGu1DH6c6RLFsjue68/DAz6iif059tqVQKG1KjsR0VeelCXRwJ4sCMKc6PvLXFjIAjZvRtEk67hgkwEREREdFwF0yvZLal/IiEO9/C55CpI3DrxQebM83damjSiM4rx33J7tIcDuQnzQkH07/Ov9/f4RynjirC+PL++XegrjEBJiIiIiIa7jIqwDGEnCZOXXG7L4sJKtn72+Xz8bnj9sQ3T5tjruaXu/euyExM+0qsNX1rpEQy5RwXTB/pHGngYQJMRERERDTchdKrlXGEu13HO2Wkt274muP3dJLgL5wwEzNGd2wOlQ9zxpeaEbDn6GIz6lsXHTbFjNLJ3sM0MDEB7t6HVPxRxbsqGlVsVPGginkqcjFaxZ9UyHyIJhUvqzhORTbHq5C3y/vJ+8vHyccTEREREfWdzATY1/0a2rJoCHdePh/fP/ZtICMAAA+uSURBVGtfnH3gRHO1/8gevx8/ZBKuOGY6DstTBfbQqSPw2ws7pgX5+vrUc0yAu3eFij1U/EzFySquUSFJ6SsqJDnuimxA9pQKSXjl405XIX3RH1NxtAqbnD+qQt4u7yfvLwmxfDx30CYiIiKivuMPoBVe86pWdL7+1zZ/2kice/Bk+LtqC50n0pn5fz46F19aOCtvXajl6yzcZyzGWd2gZ48rxYii3P79KP+YAHfvKhWS6P5GxXMq7lEhG4tVqfiKiq5cqmIfFeeouEPFkyrOVrFSxQ9U2H6oQq7L2+X95P3l4+Tj/0sFEREREVGfifu9JK7N1z+dnAer8kIv4eX634GNCXD3tpmjrUHFchWTnLPOnalihQqZ1uxqU3G7ikNUTJAL5iht9P6iQt7uekmFJMXyeYiIiIiI+kxbwEuAW32sYPZERaF3w+Bwbn80oDEB3jVlKg5Uscw565xUb5fqYRr3mtsiT95PdPa+7tuJiIiIiPpELOg1r2rzMwHuiQpTAQ76fTh46ghnTAMTE+Bd8ysV0vbuu85Z52T+w049TONec+dHuMfO3jeXeRSyLlkSajumqyAiIiIi6lYsVGFGMgWaCXBPHL1XpXP8yNxxKI5030CM+g8T4J77tooLVHxexWK50A29GVh2mW/r7H27+hyuK1W8nRHSrZqIiIiIqFutkXIzkm2QuAa4J6QD9etfPR4/OXd/c4UGKibAPXOTiq+quFHFL+VCN6RRVrbqrTsvwq34yvuJzt43W2U4069VyFRpO6SbNBERERFRt9oKvKm7MSbAPTaqOJK37tO065gA506S32+Y+J5cyMFbKvbVwzTuNanS2sfO3td9e1ekWZesSbZjlQoiIiIiom6lol4CHAen8dLQxAQ4N19TIYnvd1R8Uy7k6H4Vs1Qc6pxp8mxyoYpXVWySC8pGFa+pkOsBuWDMV7GXivucMyIiIiKivmIlwKFU3IyIhhYmwN37oopvqXhMxSMqJCm1w3WLCtnCaIpzpv1RhVRi71ZxvorjVdylQpLaL6mwybkky/K+8n7y/vK+Uv29VQURERERUZ/xF3mr8QqSzWZENLQwAe7eqea4UIXs55sZLqncStgT/2MqjlPxjIpfqHhIxTgVJ6l4ToXtWRUnq5C3y/vJ+8vHycfL5yEiIiIi6jOBYm//2oJUixkRDS1MgLt3jApJajsL18Uq5Hytc+bZquKTKuSWWlTFYSr+pSKbJ1XI2+X95P3l42RtLxERERFRnwqVeAlwFKwA09DEBJiIiIiIiBAp9RLgQlaAaYiyK5g09BygYskDDzyAGTNm6CtERERERFnUVe9A6V9PccbvYBr2vupvzph6z/vvv48zzjhDhgeq+I8MKL+YAA9tp6l4UA+JiIiIiGiAOF3FP/SQ8okJ8NBWpuJoFetV9GUv++kqJNGWX2TuPUx9hY8zyjc+5igf+DijfONjrn+FVUxSIQ1xa+UCEQ0+c1SkzJGor/BxRvnGxxzlAx9nlG98zNGwxiZYRERERERENCwwASYiIiIiIqJhgQkwERERERERDQsBcyTaHdJMrUmFLOZvlAtEfYCPM8o3PuYoH/g4o3zjY46IiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiCgXxSp+qmKTihYVb6g4T4XtCBU3q1isIqYipWIPFV25T8WDeugYreJPKnaokI6BL6s4ToWtVMWNKp5VsUVFg4q3VHxJRYGKzixR8TM9xBwVv1Yhn186Esr3eoyK7oxRUaVC3v9suUC9aiA9zkRExXUq3lYhj5OtKh5VsUBFZ/g4G1yG83PbWhXy9sz4rQrqfcP5+Y2Ptfwb7q/bRqmQj5XHnvxs7uN7hAoiopw8oaJaxadVHKviDyrkyed8Fa6bVMgTzf0qnlHR3RNpkQp5svyEc6b/GMsT4noVF6g4QcUDKlpVHK3CtY+K7Sr+T8VpKj6kQr52s4p/qZB2+5mmqpDv5yjnDPikCvmj8IiKf6jo7onUdY+KjSrk/ZmY9L6B9DgTt6lIqPiOCnmcyf/z11XI+x6iIhMfZ4PPcH5uk5/pRRXzM0I+J/W+4fz8xsda/g3n57bxKlapWKHiUhXyOT6q4hcqxqogIurWySrkiebjzplHnlzlRbq7v7PfHMV/q+juifRjKuIqKpwz4EoV8jGHOWdaUMUyFa86Z5o8AUtkcr+m3NHMJHe55e6f+z3a36v80e/qidR1lop6FfLEL+/PxKR3DbTHmfxhb1PxF+fMM06FfLx7V9rGx9ngMtyf2+SF78N6SH1suD+/8bGWX8P9uU2S8A0q3O+TqF/ZD14aPM5UIdNV7nbOPLeqkLtshzpnQNIccyUv9J9WIXcohXwduVsn01tc8gf6dhVyN3qCXFBk6otEptfMcZI52uRryR1O93vs6fcqU2Z+pUKm8HwgF6jXDbTHmXwdiVrnzFOnQq7LlLJMfJwNLnxuo3zh8xvl03B+bpMEXqrMUvF2v0+ifsUEeHCSqSvvqJAnNdtSc5S395Ss+ThFxb3OmSafx/2cNvearP/oikypEXLn0TZRhTwR21+rp36uYo2KXzpn1BcG2uNMpnDJeiOZdnWGClnDJH9Y5Y+qvGiUo42Ps8FnoD3mOtOXz20yNVBmHMjjfbmKL6pwq0PUewbaY60/nt/4WMufgfZ460xfPLcdqUKmVMt06b+pkBsBckNH1h/blWqivGECPDiNVLFTD9O41+TtPXWiiqgKmabi2p2vM1fF9SrkbmHmk7HcRaxRIetbdoU84Z+j4lMqeMe77wzEx9nnVciaJfkjLC8KJTk9XIX80X5fhY2Ps8FnID7mMvXlc5uspbtGhTz2ZEqhNJz5kQppaEO9ayA+1vL5/MbHWn4NxMdbpr56bnOrzvL4ku9XPpese5bp0FK9lq9LlFdMgAcvWWvRma7e1hl5QnpBhTRFsO3K15G71rK2SJowXCYXMsjXko6FmXdCc1Gm4ncqvq9COmVS3xpojzOZiixrlL6hQpqInK5Cpns9qeIAFTY+zgangfaYs/Xlc5u4SoVMiXxehXyeC1XI7AM5Zj6+afcNtMdavp7fBB9r+TfQHm+2vnxuc3MNWQMsn+dxFdK5eqEKubksSTdRXjEBHpxkO5Zsd/HcVvLZ7v51JaTiVBWZU1t25etMUSF3COVJUtruZ76PdPuTO9q7Mo1GfFeFTNeSP9TlJmRrAVGoQs6zdS+knhtoj7O9VXxLhXSq/LYKmT4lnSelgiF3pqVy4uLjbHAazs9tnZG1e0I69FLvGc7Pb53hY63vDOfnNvmehHSXli7nrs0q3lRxoHNGlEdMgAcnaXEvfyyls59tX3PsacXqeBVS8ZJpLzb5Ou7ntHX2deRJVP5oS2Igd6/lbl8madAgjRfkjvaukPUtcqdS9q2TZgoSD6kQf1Yh5/Kz0O4baI+z/VTIY2uRc+aRRFX+iNprqPg4G5yG83NbZ9wbLZyG37uG8/NbZ/hY6zvD+bkt25pkl3xdPt4o75gAD07yhCfVKJlKYnP3ZLNb3edCPs8rKqQVv02+ziwVbndCIU/eMkVKvoZ8LddkFfIkKg00ZL3SOhXZyNeSaTayCfquuFaFPEnbIeumhDttTBos0O4baI8z95hZnZDtQ+QOsv2Hm4+zwWk4P7d1xt3fU34O6j3D+fmtM3ys9Z3h/NwmX1cevx9WYTdZk+7XcuOHjzciypnsHSfTVKRBj7wY/70KWdshG5+7KlVIcwsJqVrJ268w5+6G6PJkJOtHpPtjJvnDK3cLZfsXaVggdxxl3YbckbY3VB+tQjY4l65+8vXlD7gd0j1QyLQc+djMPwBCppW636s0SpDvVaaCyflJKroi+87J+8v7Uu8aSI8zuWEnWzTIRv3fVCFTtWQjfZm6JV9T/sALPs4Gt+H63Cbfxz0qLlEhL0blsS0dU+X9Za0m9b7h+vzGx1r/GM6v2+SaVHolkXYbTEq1Wqb3T1dBRJQTuZMoG+PLGgq5KydTpM5TYXNfsGcLuesn5I+snE91zjoao0KehGUNh/xhlr3l5AnV1tXXkZCKmbhUhUyjkSfNTDLdNNvHSsiG/V1hYtJ3BtLjTMiUr++okC075LEkm/LLC0T7jy0fZ4PbcH1ukxedskZOfu64Cvl8khDJi1/O1uobw/X5jY+1/jHcX7dJUzf3Jo8kvtJUa7YKIqK8k30HF+thn/unit5u2kGDAx9nlG98zFG+8LFG+cTHGxEREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREdEQ9A0VKT3skfNVXKuHRERElCu/ORIREdHgwQSYiIhoFzABJiIiIiIiomGBCTAREVF+nKLiDRUxFWtU/LeKTFepeF7FNhWNKt5Scb2KkArXsyrkc01RIdOn3XCFVXxVxbsq5GttV3GrikoVRERERERERH3qOBVtKl5QcaaKs1W8pmKdCjt5/T8Vn1FxoopjVcg0Z0lg/6jCNVvFiyo2q5hvhZAb24+qaFDxdRXHq7hUxQYVy1REVRARERERERH1mVdUbFRR4JxpJSqqVHTWBEuS2aCKi1RI8lyhwvWwirV6mOY8FfL5PuqceQ5SIdevcM6IiIiIiIiI+kCRioSKXzhn6f6kwk6AD1DxDxVuYmzHoSpcnSXAt6uoViFTpiV5tkMqxn9XQURENGxxDTAREVHfksqt/L3d4pyls69NViFTpCeouEbFkSoOViHrgkUu05fHqChXEVfRmhFjVYxSQURENGwxASYiIupbUpGVCq4koJnsa2eokGqxTF+WSq6s831dhSSzudqhQqrHkjhniytVEBEREREREfWZXNYAf1ZFZqLsU/GqCrl+jFww7lWxVQ/TXKAic7o0ERERGQFzJCIior4j3Z6lu7N0dpaK8BwVv1cRUVGm4psq6lRcrkKSV9kGaV8VP1MxTsVIFX9W4a77lU7QshWSvJ/M5pL32aRiuQqp9H5JhSTbMm1atks6SsXnVUhCLdsjEREREREREfWZU1W8qUL25pWEWJLUb6hwK8DiIypkr+BmFbJ10Q9ULFSRWQGWdcV3q5BkOqnC/hzS8OqLKtzPU6/iHRW/VTFDBREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREQ1cwP8D1C3vaEAyRDQAAAAASUVORK5CYII=\" width=\"799.9999682108573\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "len1 = len(df)\n",
    "\n",
    "t1 = 0\n",
    "t2 = int(np.ceil(len1/2))\n",
    "\n",
    "xX = df.iloc[t1:t2,[6,8,10]]\n",
    "yY = df.iloc[t1:t2,12:13]\n",
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(xX, yY)\n",
    "B = regr.coef_\n",
    "b_0 = regr.intercept_\n",
    "rSquared = regr.score(xX, yY)\n",
    "\n",
    "print(b_0, B)\n",
    "print(rSquared)\n",
    "\n",
    "yHat = b_0 + df.iloc[t1:t2,[6,8,10]] @ B.T\n",
    "\n",
    "#plot data\n",
    "plt.figure(figsize=(8,5)) # set the figure size\n",
    "\n",
    "plt.plot(df.iloc[t1:t2,0], yHat)\n",
    "plt.plot(df.iloc[t1:t2,0], df.iloc[t1:t2,12:13])\n",
    "\n",
    "#adjust display setting\n",
    "plt.autoscale(enable=True, axis='x', tight=True)\n",
    "plt.autoscale(enable=True, axis='y', tight=True)\n",
    "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d/%m/%y'))\n",
    "plt.gca().xaxis.set_major_locator(mdates.MonthLocator(interval=6))\n",
    "plt.xticks(rotation='horizontal',horizontalalignment='center')\n",
    "\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('30-yr swap rate')\n",
    "plt.title('original vs. constructed')\n",
    "plt.legend(labels = ['constructed 30-yr','original 30-yr'], loc='best')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}