plenum_time_evolution.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "from matplotlib import rc\n",
    "rc('font', **{'family': 'serif', 'serif': ['Computer Modern']})\n",
    "rc('text', usetex=True)\n",
    "\n",
    "from tqdm import tqdm, trange, tqdm_notebook\n",
    "\n",
    "from matplotlib.pylab import get_cmap\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "\n",
    "import numpy as np\n",
    "import scipy as sp\n",
    "import sys, os\n",
    "import cPickle as pickle\n",
    "from glob import glob\n",
    "\n",
    "fs=20\n",
    "fs_ticks = 16\n",
    "#sys.path.append('/Users/mhuber/PointSource/skylab/')\n",
    "#from SkyMap import SkyMap\n",
    "\n",
    "from scipy.stats import norm\n",
    "\n",
    "# define sfb colors\n",
    "colors = ['#3850A1', '#F79645', '#993A91']\n",
    "#new trial\n",
    "colors = ['#0D589A', '#5DB5D0', '#A9DBB7','blue']\n",
    "\n",
    "from matplotlib.ticker import (AutoMinorLocator, FixedLocator, FuncFormatter,\n",
    "                               MultipleLocator, NullLocator, LogLocator)\n",
    "import healpy as hp\n",
    "\n",
    "from scipy.interpolate import UnivariateSpline\n",
    "from matplotlib.lines import Line2D\n",
    "from copy import deepcopy\n",
    "\n",
    "from scipy.interpolate import splrep, splev\n",
    "from copy import deepcopy "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tools import *\n",
    "from tools import _trans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from mpl_toolkits.basemap import Basemap\n",
    "from matplotlib.colors import LogNorm\n",
    "from PyAstronomy import pyasl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get the detection efficiency "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + 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=\"700\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = \"/Users/mhuber/StackingSkylab/MultiYearPointSourceData/\"\n",
    "mc = np.load(os.path.join(path,'IC86-2012_MC.npy'))\n",
    "\n",
    "ang=4\n",
    "decs = np.linspace(-np.pi/2+np.radians(0.1), np.pi/2-np.radians(0.1), 50)\n",
    "xvals = np.linspace(-np.pi/2, np.pi/2, 1000)\n",
    "\n",
    "fig,ax=plt.subplots(figsize=(7,5))\n",
    "tcks = dict()\n",
    "gammas = [2.5]\n",
    "for gamma in gammas:\n",
    "    \n",
    "    Res = np.zeros_like(decs)\n",
    "    for i, deci in enumerate(decs):\n",
    "    \n",
    "        if deci > np.radians(30): ang=10\n",
    "        dec_min, dec_max = np.sin(deci-np.radians(ang)), np.sin(deci+np.radians(ang))\n",
    "        Omega = 2 * np.pi * (dec_max - dec_min)\n",
    "        dec_mask = (np.sin(mc['trueDec']) > dec_min)&(np.sin(mc['trueDec']) < dec_max)\n",
    "\n",
    "        DetEff = np.sum(mc['ow'][dec_mask] * mc['trueE'][dec_mask]**(-gamma)) / Omega \n",
    "        \n",
    "        \n",
    "\n",
    "\n",
    "        \n",
    "        Res[i] = DetEff\n",
    "    \n",
    "    Res_max = np.max(Res)\n",
    "    Res /= np.max(Res)\n",
    "    \n",
    "    \n",
    "    tck = splrep(decs, Res, s=1.e-4)\n",
    "    spl_val = splev(xvals, tck)\n",
    "    \n",
    "    tcks[gamma] = tck\n",
    "    p=ax.plot(np.degrees(decs), Res, label=r'$\\gamma$={0:.1f}'.format(gamma))\n",
    "    ax.plot(np.degrees(xvals), spl_val, ls='dashed', color=p[0].get_color())\n",
    "    \n",
    "fig.legend(loc='upper center', mode='expand', fontsize=fs, ncol=3)\n",
    "ax.set_xlabel(r'$\\delta$ [deg]',fontsize=fs)\n",
    "ax.set_ylabel(r'relative detection efficiency [a.u.]',fontsize=fs)\n",
    "ax.set_yscale('log')\n",
    "fig.tight_layout()\n",
    "\n",
    "plt.subplots_adjust(top = 0.82)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get the plenum improvements by averaging over the earth rotation in right ascension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "49152\n",
      "0.000255663464648\n",
      "(12.566370614359172, 12.566370614359172)\n"
     ]
    }
   ],
   "source": [
    "NSIDE = 2**6\n",
    "npix = hp.nside2npix(NSIDE)\n",
    "\n",
    "# this gives the pixel size in sterradian (also called square radian)\n",
    "psize = hp.nside2pixarea(NSIDE)\n",
    "print(npix*psize, 4*np.pi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 24/24 [00:22<00:00,  1.08it/s]\n",
      "100%|██████████| 24/24 [00:21<00:00,  1.11it/s]\n",
      "100%|██████████| 24/24 [00:21<00:00,  1.13it/s]\n",
      "100%|██████████| 24/24 [00:21<00:00,  1.13it/s]\n",
      "100%|██████████| 24/24 [00:29<00:00,  1.22s/it]\n"
     ]
    }
   ],
   "source": [
    "NSIDE = 2**6\n",
    "npix = hp.nside2npix(NSIDE)\n",
    "\n",
    "fact = 1.\n",
    "poles = {'IceCube':(np.radians(0), np.radians(-90.)),\n",
    "         'Gen2':(np.radians(0), np.radians(-90.)),\n",
    "         'P-ONE':(-np.radians(123.3656), np.radians(48.4284)),\n",
    "         'KM3NeT':(np.radians(16.1), np.radians(36.27)) ,\n",
    "         'Baikal-GVD':(np.radians(108.1650), np.radians(53.5587)),\n",
    "         #'X, China':(np.radians(111.918), np.radians(8.640)),\n",
    "         #'SA, Cape Town ':(np.radians(18.4241), np.radians(-33.9249)),\n",
    "        #'hypothetical':(np.radians(0.2093), np.radians(-0.8688)),\n",
    "        }\n",
    "      \n",
    "comb_values = dict()\n",
    "\n",
    "    \n",
    "for i,(name, new_pole) in enumerate(sorted(poles.iteritems())):    \n",
    "    \n",
    "    vals = np.zeros(npix)    \n",
    "    rot_angles = np.arange(0.,360., 15.) #15.\n",
    "    for rot_ra in tqdm(rot_angles):\n",
    "        vals2 = np.zeros(npix)\n",
    "        new_ra = new_pole[0] + np.radians(rot_ra)\n",
    "        \n",
    "        x = np.linspace(0,2*np.pi, 1.e3)\n",
    "        y = np.linspace(-np.pi/2,np.pi/2 ,500)\n",
    "    \n",
    "        xx, yy = np.meshgrid(x,y,indexing='ij')\n",
    "        \n",
    "        ra2 , dec2 = rotate(0, -np.pi/2, new_ra, new_pole[1],xx.ravel(),yy.ravel())\n",
    "        \n",
    "        \n",
    "        lat2 = np.pi/2 + dec2\n",
    "        lat2 = lat2\n",
    "        lon2, lat2 = _trans(ra2, lat2)\n",
    "        \n",
    "        p = hp.ang2pix(NSIDE, lat2, lon2)\n",
    "        \n",
    "        if name == 'IceCube' or 'Gen2' in name:\n",
    "            vals2[p] = splev(yy.ravel(), tck)\n",
    "        else:\n",
    "            vals2[p] = splev(yy.ravel(), tck) \n",
    "        \n",
    "        if name == 'Gen2':\n",
    "            vals2 *= 7.5\n",
    "    \n",
    "        vals = vals + vals2 * (1. / len(rot_angles))\n",
    "    \n",
    "    comb_values[name] = vals\n",
    "    \n",
    "blub = 5000"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get the values for the 1d (right ascension information is irrelevant due to the earth rotation) discovery potential improvemt with and without Gen2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "first get the current values for sens and disc pot\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "    } 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",
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       "            fig.send_message(\"refresh\", {});\n",
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       "\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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + 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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/p/FV+nyLlMhAgLACnlQ1VbN+XP+pfBv9+7d1dZE7SFAgAABAgQIECBAgAABAmUlMP/P4mVVMZVZcwFDgNec2A0IECBAgAABAgQIECBAgAABAgQIbJyAAHDj7N2ZAAECBAgQIECAAAECBAgQIECAwJoLCADXnNgNCBAgQIAAAQIECBAgQIAAAQIECGycgABw4+zdmQABAgQIECBAgAABAgQIECBAgMCaCwgA15zYDQgQIECAAAECBAgQIECAAAECBAhsnIBVgDfOvqbuPDg4uKC9U1NTC777QoAAAQIECBAgQIAAAQIECBAgsDYCegCujaurEiBAgAABAgQIECBAgAABAgQIECgLAT0Ay+IxVH8ljh07tqCRQ0NDMTAwsGCfLwQIECBAgAABAgQIECBAgAABAqsvoAfg6pu6IgECBAgQIECAAAECBAgQIECAAIGyERAAls2jUBECBAgQIECAAAECBAgQIECAAAECqy8gAFx9U1ckQIAAAQIECBAgQIAAAQIECBAgUDYCAsCyeRQqQoAAAQIECBAgQIAAAQIECBAgQGD1BQSAq2/qigQIECBAgAABAgQIECBAgAABAgTKRkAAWDaPQkUIECBAgAABAgQIECBAgAABAgQIrL6AAHD1TV2RAAECBAgQIECAAAECBAgQIECAQNkICADL5lGoCAECBAgQIECAAAECBAgQIECAAIHVFxAArr6pKxIgQIAAAQIECBAgQIAAAQIECBAoGwEBYNk8ChUhQIAAAQIECBAgQIAAAQIECBAgsPoCAsDVN3VFAgQIECBAgAABAgQIECBAgAABAmUj0Fg2NVGRqhYYHBxc0L6pqakF330hQIAAAQIECBAgQIAAAQIECBBYGwE9ANfG1VUJECBAgAABAgQIECBAgAABAgQIlIWAHoBl8RiqvxLHjh1b0MihoaEYGBhYsM8XAgQIECBAgAABAgQIECBAgACB1RfQA3D1TV2RAAECBAgQIECAAAECBAgQIECAQNkICADL5lGoCAECBAgQIECAAAECBAgQIECAAIHVFxAArr6pKxIgQIAAAQIECBAgQIAAAQIECBAoGwEBYNk8ChUhQIAAAQIECBAgQIAAAQIECBAgsPoCFgFZfVNXJFBzApMzUzE2NRHj0zdjdm426uvqc6+GqLvzOe1rSK/6hmiqb8xeTdmxupqz0mACBAgQIECAAAECBAgQILDeAgLA9RZ3PwIVKJBCvZvTt2MiC/hS0Df/NT51MyZnp1bUqhQENmdBYFNDU/Y+//Pn3z/fn33OHc/KZWVaGppz31d0QycRIECAAAECBAgQIECAAIEaFBAA1uBD12QCiwlMzU7H8K2RXLiXgr6J6VuRwr30OYV/c9k/q72le6ZXZPdYztbW0BI9LV3Za1P0NG+K7uy9s6lDj8LlICpLgAABAgQIECBAgAABAjUjIACsmUetoQS+LJCG7p4bvxRDYxfiws2rueG7Xy5VfntuztyOmxOX43z2ym8NdQ3R3dyZCwW7svf0Ob23ZmFhnaHGeSbvBAgQIECAAAECBAgQIFCDAgLAGnzomlzbArdnJuPsF6HfpYks9FuDnn0bITwzNxPDt0dyr/n3T8OGUxCYe2W9BNN7b9Z7sLWxZX4xnwkQIECAAAECBAgQIECAQNUKCACr9tFqGIHfCaRhtmeyXn5nRs/HpZvDazKc93d3K69Pqe1Xb13PvebXrL2xNfpae6KvpTt7dUVva3dujsH5ZXwmQIAAAQIECBAgQIAAAQLVICAArIanqA0EFhGYm5uLa7dvxIkbZ+J0FvxNZz3kbL8TSHMcTmShaBr+nN9S78BcIJiFgek9zS2YVi62ESBAgAABAgQIECBAgACBShYQAFby01N3AosIpHn9To+djxMjZ+L65OgiJexaSuDG5Fik16nRs7ki9VGXW2yk74tAML1vyoYRm1NwKUH7CRAgQIAAAQIECBAgQKAcBQSA5fhU1InACgTSMNfjWeh3Jgv/ZuZmV3CF1TmlLgvN1mLF4NWp3fKukuZHvHtewcZssZHNbb2xra0/trVvzi02IhBcnqvSBAgQIECAAAECBAgQILC+AgLA9fV2NwKrLnAzG8r65uUPYmj84qpfe6kLppV1O5vas1db9urIvXfkvrdHS0NzpOHHKYScnffKf09z8qXX5OxUpN6KCz9/vm8yV+bzz+U2dDnV58LEldwrrn6Ua+/Wtr5cGLgte08ONgIECBAgQIAAAQIECBAgUE4CAsByehrqQmAZAilkO3FjKN7JQqgUoq3m1pYtkNGRvdob26I9C/nynzuyz2lfY31DwdulHnGpp1xE4XIFL/LFwRQi5kLCLCxMKxiPZMOar9/OXtn7SPa+0QFhqlNugZUv5hJMwWg+EEzvKRC1ESBAgAABAgQIECBAgACBjRQQAG6kfg3de3BwcEFrp6amFnz3ZXkCaZ66o5eOxeVb15Z3YoHSW1p7Y3fn9tjVuS0L+VoLlFzfQ/XZIhwpREuvTdGRG36br0EKQcemJnJhYAoFUziYbMazfXP5Quv8nuqTXimcTVtPtsLw58OF+2NzZlwsPF3n6rodAQIECBAgQIAAAQIECNSAgACwBh6yJlaPQBpG+9G1k/H+teO54bX30rI0V1/qobY7C/x2dWyL1saWe7nchpybehpuau7IvQay8DK/zczOxGgWwuUX9ci/p33rPT/h9Wwl5vT66PrJSIuK9GfzB27P5g/cns0fmMJB8wfmn5p3AgQIECBAgAABAgQIEFgrAQHgWsm67gKBY8eOLfg+NDQUAwMDC/b5UlggLfLx+qX3sl5uY4ULFjna19Id+7p254K/ah2e2pANUe5p2ZR7zeeYzoLBFMblFva4NZJ7T7311mtLi4pcvjmce707/EmuV2MKAtMrLSjSarjwej0K9yFAgAABAgQIECBAgEBNCQgAa+pxa2wlCsxmw1yPZWHRB9dOrLj6TfWNsXfTztjfNfClUGzFF63AE9Pw27SCb3rlt7QQybXbI3E1CwTT+3D2fnPmdv7wmr6n+QM/Gz2Xe6Ub9WY9AlMYuLNja6SgVu/ANeV3cQIECBAgQIAAAQIECNSMgACwZh61hlaiQOqx9urFd+LsClf4TXPO7c/19ttu7rklfgDNDU2fr+CbBW/5La2snILA+T0FV3uhlfy95r9fy3onplcKe9M8jGlY80DnjlwwKAycL+UzAQIECBAgQIAAAQIECCxHQAC4HC1lCayjwM3p2/HL82/kQqjl3jYFR4N990dXc+dyT1U+E0irIO/qTK9tOY/8YiNp0ZVLE1fj4s2ruRWJ1xJrIgshP7p+KvfqyFZeTgu0pOeaegkKA9dS3rUJECBAgAABAgQIECBQfQICwOp7plpUBQIj2Yq2/+780Ugh0HK2FFwd3vJwbgjpcs5TtrBACtzyi42kHpUpEExzMaYgMAWCaV6/6bmZwhe5h6Pj0zdzi4ikhURSGPh5z8DtFhG5B1OnEiBAgAABAgQIECBAoJYEBIC19LS1tSIELk5ciV9deCuWO+T0/u498Wj/A5Hm+7OtrUAKBPOLjDzYc1+k1ZnTkOFLWSB4MQsE04Ita7XacAoDP8yCwPTqbGq/0zOwp3mTnoFr+9hdnQABAgQIECBAgAABAhUrICmo2Een4tUocOLGUBy9dGxZ4VFXU0cc2frIgoUtqtGmnNvUUFcfW7KFRdIrDb1O4e2Vm9eyMPBKrpfgva7cvFTb0wrGH2bzBaZXCgPzPQO7hYFLkdlPgAABAgQIECBAgACBmhQQANbkY9fochNIQ0rfzVb6TUFOqVt91MWhvgPxUO/+SAGUrXwEUi/MHR1bcq9Uq1vZfI5puHDqHXghCwVvrcEqwykMTIuHpNemLBROqz6nV0dTW/nAqAkBAgQIECBAgAABAgQIbIiAAHBD2N2UwO8EZrPho7+9+G6cHjv/u51FPrU2tMQ3djwVva3dRUo6XA4CrY0tdwK5z+cPHM0FgSkMTD0FZ7M+n6u5jU6Nx3tZoJxeW9r64r4sCEyLiBgevprKrkWAAAECBAgQIECAAIHKERAAVs6zUtMqFEhh0GuX3ltW+JeGd6bwr13Pror8RXw+f2BXbgGP1HszDRdOi4icH78cZ8cvrXrvwHTt9Hrj8vu5xWHu27QrtrX3R71eoxX5+1FpAgQIECBAgAABAgQIrERAALgSNecQWCWBd65+FJ+Nniv5atvbN8dXtz+hJ1fJYuVfMPXK29mxNfd6cu7hbAGRa3Fm7EIMZa9bM5Or1oC0UEm6bnqlHqSpV+C+bEXjtLqxjQABAgQIECBAgAABAgSqW0AAWN3PV+vKWODDayfjo+unSq7hga6BeHLLIT23SharvIL12erCachuej2x+VA2PHj48zBw/GLcXsUwMM1BmF9JeHNrbxYE7sotINJoBenK+9GoMQECBAgQIECAAAECBEoQEACWgKQIgdUWOHXjbKTef6Vuj/c/GA/03Bdp+KitNgRSGLg1G6qbXk/OHcqG8V7L9QocWuUw8ErW4zC93rz8QQxs2hH7s16BfS3dfmu18TPTSgIECBAgQIAAAQIEakRAAFgjD1ozy0fgXDbPW5r3r5Qtre777LbHcgs4lFJemeoUSPP1pXn70isfBp7JFo0ZGrsYk7NTq9Lo6bmZOHljKPfqbu6M+7v35hYuaaxvWJXruwgBAgQIECBAgAABAgQIbJyAAHDj7N25BgXSiq+/vvBWtuZr8VVfm+ub4hs7D0d/a08NSmnyUgLzw8Cntjwcl7Jhwmm+wNUMA0cmx+Lo5WPx7tWPcz0C7+/eY9GZpR6I/QQIECBAgAABAgQIEKgAAQFgBTwkVawOgZHbo/Hvzh+NtBhDsa2hrkH4VwzJ8dx8kGlhmPR6MgsDL0xcic+y4eWpl+lsCSFzMcLUuzDNFZjmqtzVuS0eyHoFpkDaUPRico4TIECAAAECBAgQIECgvAQEgOX1PNSmSgXGp27G3557PaZmp4u2sC7q4mvZSr96/hWlUmCeQBouvitbTTi9JmemcouHfDZ6Npvf7/q8Uiv7mHqsft7L8EL0tnTFwSwITPMFpnvaCBAgQIAAAQIECBAgQKD8BQSA5f+M1LDCBebm5uLVi+/EzWzl1VK2Z7Y9Gjs6tpRSVBkCiwo0NzTFge6B3GtsaiI+Gz2Xe6XP97pdu30jfnvp3dwiNgeyocH7s9Wp2xpb7vWyzidAgAABAgQIECBAgACBNRQQAK4hrksTSAJns1Vb0yqrpWxptd+9m3aWUlQZAiUJdDa1x2Df/fFw74G4nP0O00IfqTdfKUPRC93g1sxkHBv+ND4YPp7rDZh6Bfa1dhc6xTECBAgQIECAAAECBAgQ2CABAeAGwbttbQjMZr3/3rv6SUmNfahnXzzYu6+ksgoRWK5Amrdva1tf7vXk5kPZEOHzWRh4NoZvjyz3UgvKp7kG8z0MN2fzAx7suS83DDktVmIjQIAAAQIECBAgQIAAgfIQEACWx3NQiyoVOJ0NvbwxNV60dfdt2hWP9j9QtJwCBFZD4PMhwnuyIcJ74nq2OE3qFZhCvLTox71sab7BK9kq1+2NrfFQ7/7Yl/2uG+ob7uWSziVAgAABAgQIECBAgACBVRAQAK4CoksQWEwgDbFMQySLbTvbt8SRrYNWVi0G5fiaCPS0bMpWED6UC6BTYP3JyGcxMjl2T/eamL4Vb1x+P97PhgenXq0HunZHY73/d3NPqE4mQIAAAQIECBAgQIDAPQj4E9k94DmVQCGB1KtqfPpmoSLRXN8Uz2x7LAyXLMjk4DoINGY99fZnC4fsy8K6yzeH4+MsCDw3fume7nwrW/jm7SsfxodZEPhANjT4/p690SQIvCdTJxMgQIAAAQIECBAgQGAlAgLAlag5h0ARgenZmdziCEWK5XpHpeGYNgLlIpCbK7C9P7Zmr7Rq8KfXP4uTo2djanZ6xVW8nQ0tfnf4k/jw+slIi4UczILAlobmFV/PiQQIECBAgAABAgQIECCwPAEB4PK8lF6hwODg4IIzp6buba6xBRcrwy/HR07Hzaz3U6GtNQtADmZzsNkIlKtAWkH4iWx48GD/wTiVLRiShgenUHClWwoR3792PD6+fioXAqZegYLAlWo6jwABAgQIECBAgAABAqULCABLt1KSQEkCKeT48NqJomXTIgnmRSvKpEAZCKRhu6nX3v1ZYH1h4kouCEzvK92m57Iestm/I59mQXnqEZiCQD1hV6rpPAIECBAgQIAAAQIECBQXEAAWN1JiFQSOHTu24CpDQ0MxMDCwYF+1fEm9m9KQx0JbWiU1rcBqI1BJAml48I6OLbnXjWyhkE+y4cGnsoVDZrJAbyVbvkdg6lkoCFyJoHMIECBAgAABAgQIECBQmoAAsDQnpQiUJHB7ZjI3vLFY4Yd7D0RDXX2xYo4TKFuBrubOOJytXv1o/wNxIlvwJoV4N7PVf1eyCQJXouYcAgQIECBAgAABAgQIlC4gACzdSkkCRQU+unay6GIJaV61+7p2Fb2WAgQqQSAN3X2od19uiHCaJzANfy+2+vVS7ZofBB7KQvI07FhQvpSW/QQIECBAgAABAgQIEChdQABYupWSBAoKpN5/aU6zYtsjffdHvd5/xZgcrzCBFNQd6B6IfVm4fXr0fG6Ov9Gp8RW1IgWB71z9KOtZeCYey3oY7urYFmn4sY0AAQIECBAgQIAAAQIEViYgAFyZm7MIfEkgzYeWFjcotHVnwyYHOncUKuIYgYoWSOF26uG6Z9POODt2Ibfq70g2X+BKtrTi8K8uvBVbWnvj8c0PRV9r90ou4xwCBAgQIECAAAECBAjUvIAAsOZ/AgBWQyD1WCqt999BPZlWA9w1yl6gPuuxN7BpR+zu3B7nxi/FsWvH4/rtGyuq9+Vb1+LloV/HfVmo+EjWIzAtomMjQIAAAQIECBAgQIAAgdIFBIClWylJYEmB4yNnYrLIyr99Ld2xs2PrktdwgEA1CqShu7s6t+V++7kgcPjTuD45uqKmphWHz4xdzM05+GDPvmisb1jRdZxEgAABAgQIECBAgACBWhMQANbaE9feVReYmZ3JVv49WfS6h/oO6P1XVEmBahVYrSBwJhtmfywLEdOCI09sOZTNDyhUr9bfjHYRIECAAAECBAgQILB6AgLA1bN0pRoVODl6Nm5lC4AU2tLcfzvbtxQq4hiBmhCYHwSeTUODszBvZAU9AtNKw788/0bsyP69ejILAtPq2jYCBAgQIECAAAECBAgQWFxAALi4i70EShKYnZuND6+dKFr2UO9+vf+KKilQSwIpCNydDQ1OPfjOjl+Md69+EitZNfj8xOW4ePpqpH/HDAuupV+QthIgQIAAAQIECBAgsBwBAeBytJQlcJfA6dHzMTF96669C7+mnkm7rfy7EMU3Al8IfB4Ebs/NEZgW0nl/+HjR+TTvxktBfH5YcOoNaK7Nu4V8J0CAAAECBAgQIECg1gXqax1A+wmsVGBubi4+KKH330PZYgVpRVQbAQJLC9TX1ccDPffF3937jTjYvTfqsn+Wu6Vhwb/IhgWn1/jUzeWerjwBAgQIECBAgAABAgSqVkAAWLWPVsPWWiANWyw2ZLGtoSX2du1a66q4PoGqEWhpaM7N6fd39vzeinvypdWG/7/Tv4iPrp2M1DvQRoAAAQIECBAgQIAAgVoXEADW+i9A+1ckkHr/vV9C778He/dFQ9azyUaAwPIENjV3xO/teCp+f+fT0dO8aXknZ6XTasFvX/0oXhn6TQzfGln2+U4gQIAAAQIECBAgQIBANQlIJqrpaWrLugmkHkbXb98oeL+W+qbY37W7YBkHCRAoLLCtvT+eH/haPLXl4WiqX/60tdeyf09fGfp1vHn5g5ianS58M0cJECBAgAABAgQIECBQpQICwCp9sJq1dgKp9997w58WvcHBbD6zxhUEFkUvrACBGhNIc2je370n/u6eb8R9m5Y/pH4u8/pk5LP4i2xY8NksvLcRIECAAAECBAgQIECg1gQEgLX2xLX3ngWGsrn/RiZHC14n9VRKgYWNAIHVE2htbIlntj0af7jr2RUNC04rdv8yWyDkl+ffjJvTt1evYq5EgAABAgQIECBAgACBMhcQAJb5A1K98hJIvf+OldD77/5sFdPmhqbyqrzaEKgSgc1tvdmw4K/Gk5sPrWhYcFrA5y/P/DLSUH4bAQIECBAgQIAAAQIEakFAAFgLT1kbV03gzNiFuDE5VvB6qfffg9nwXxsBAmsnUJ8trnOwZ29uWPDeTTuXfaPbM5Pxi6w3YJobcGZ2ZtnnO4EAAQIECBAgQIAAAQKVJCAArKSnpa4bKjBbYu+/B7LwT++/DX1Ubl5DAmlY8LPbHsutFtzZ1L7slqe5AV/OVgoeKRLsL/vCTiBAgAABAgQIECBAgEAZCQgAy+hhqEp5C5wZOx+jU+MFK5l6/x3Mhv/aCBBYX4G0WvC/N/D1ONR7IOqjblk3T3N6vnzmV3F85HSkYf42AgQIECBAgAABAgQIVJuAALDanqj2rInA7NxsvF/C3H8P9uzT+29NnoCLEigu0FDfEI/2H4wXBr4Wm1t7ip8wr8RM9u/40cvvx68uvBVpeLCNAAECBAgQIECAAAEC1SQgAKymp6ktayZwejT1/psoeP3m+qbcnGQFCzlIgMCaC3S3bIpvZSsFH94yuOxFQnILhJz+ZVyauLrm9XQDAgQIECBAgAABAgQIrJeAAHC9pN2nYgVyvf+uHS9a/wd79y07bCh6UQUIEFiRQF1dXRzoHoi/s+cbsbtj27KucXPmdvz1udfi3asfR/r330aAAAECBAgQIECAAIFKFxAAVvoTVP81F/hs9FyMFen915L1/ru/e8+a18UNCBBYnkBbtkjIV7c/EUe2PhINdQ3LOvmDayfir4ZeLfrv/7IuqjABAgQIECBAgAABAgQ2QEAAuAHoblk5Ap/P/VdK77/9ev9VzmNV0xoTSL0B93ftzuYG/Gr0tnQtq/XDt0fiL7MhwekvAmwECBAgQIAAAQIECBCoVAEBYKU+OfVeF4GTN87G+PTNgvdqbWjW+6+gkIMEykOgq7kz/nD3V+KBnvuWVaHpuZl49eI7udfU7PSyzlWYAAECBAgQIECAAAEC5SAgACyHp6AOZSmQVgX9oIS5/x7q3R+N2eqjNgIEyl+goa4+ntj8UHxz55FI4f1yttQLMPUGvHrr+nJOU5YAAQIECBAgQIAAAQIbLtC44TVQgbIR+MlPfhJHjx7N1Wd4eDj2798fP/rRj8qmfutdkYsTV2Ji+lbB27Y2tGRDCwcKlnGQAIHyE9jevjm+PfD1eO3Se3F+4nLJFUw9gtO8gI9tfjAe6N4baXixjQABAgQIECBAgAABAuUuoAdguT+hdarf9773vThy5Ei8+OKLudfPf/7zOHDgQBw+fHidalB+t9nZsTWey4YLpqBgqe2Q3n9L0dhPoOwFWrMFQn5vx1O5HoH1UXqQNxdz8faVD+Po5WNWCS77p6yCBAgQIECAAAECBAgkAQGg30GcOHEiXn/99XjqqacWaPzJn/xJ7vsbb7yxYH8tfelv7ckNFfzDXc/G1rb+BU1vy/X+271gny8ECFSWQOrBl+YEfD5bIKSrqWNZlT9xYyj+9tzrMTkztazzFCZAgAABAgQIECBAgMB6CwgA11u8DO+XAsAU8l2//uV5rdK+NBy41rfNbb3xB7uejm/teia2tPbmOA71HYgGc//V+k9D+6tEoCdbHfj5ga8te0j/pZvD8crQr2N0crxKJDSDAAECBAgQIECAAIFqFBAAluFT/bM/+7N44YUX4rvf/e6d97XshZfm+kvbvn37It07v7388su5j88//3x+V82/b2nri2/tfjb+YOfTsa9L77+a/0EAqCqBtJjPka2D8bXtT0RzfVPJbRudmshCwN9ECgNtBAgQIECAAAECBAgQKEcBi4Csw1NJvej++I//OH76059GT09PwTv+4Ac/yIVwaTGOfNkU/j333HO587/zne8UPH8lB/OLfaR7p9AxBX4pgHzppZfuLAqykutW8zlb2xcOB67mtmobgVoT2N25Pfqy4f+vXng7Lt+6VlLzJ2en4m/PvhaHswDRXw6URKYQAQIECBAgQIAAAQLrKKAH4Bpip6G1P/7xj+/0rCs2lDb1uEvl0wIc+fAvVS/Nzfenf/qnuXBusWG6q9GE73//+7nFP9K1Uj3yYeD8eqzGfVyDAAEClSDQ3tgav58N+X+k72C2PEhpC4TMZouDpFWF37nyUczNzVVCM9WRAAECBAgQIECAAIEaERAArsGDTiFeb29vLkRLAVqpoV1aiTeVv3sxjlTF/IIcqSfhWmxp6O+PfvSjXPiYH/Kb6pN6BNoIECBQiwL12QIhD2dzfX5z55Foqi+9w/yH10/Gry68GVOz07XIps0ECBAgQIAAAQIECJShQF3WS0E3hTV+MCkMTCHg8ePHIz/f3t23TL0FDxw4kAv6XnzxxbsP576n46ncYo+s1JAxf+H5PftSj78U9J08efJOz8P8vnTd1DswhYOruQ0NDcXAwEDukmfOnIndu82nt5q+rkWAwOoK3Jgci1+cfyPGsvn+St26mjvj93Y8FZ1N7aWeohwBAgQIECBAgACBVRfw5+9VJ63IC5bepaEim1c5lU6BW9rmB3N31z6FhykATGXzvfRSmRTeLXeRkBRG5rcU7qXX/Hun66dAMM09mO8dmC/vnQABArUmkMK853Z/JX51/s2S5wVMoeHLZ34dX80WFdlm3tBa+8loLwECBAgQIECAAIGyEhAAlsnjSAtuFNvyAV0K++YHgGnOwHvZXn/99dxw5buvke6XgsE0FNhGgACBWhdoaWiOb+56Oo5eOhanRs+WxJFbHOTc6/H45gfjYPfeqMuGFdsIECBAgAABAgQIECCw3gLmAFxv8SXul3r2pa2/f+nVZfv6+nJl5vfey+24x/9z5MiRJXsQpnrNDxvv8VZOJ0CAQEULNNTVx9NbH4lH+x8ouR1z2eIgb135MLdAyMzsTMnnKUiAAAECBAgQIECAAIHVEtADcLUk7/E6+Tn88r387vFyyzo9zTl4+PDh3OIj88O+1NMwHXvllVeWdb1UOM0xUGg7f/58ocOOESBAoGwFUi++Q737Y1M2t9+rF9+JmbnZkuqaeg2mYcFf3/FktGWrDNsIECBAgAABAgQIECCwXgICwPWSLnKf4eHhIiV+d3g5ZX931tKf0tyCR48ezQ33zS9AknobpjAy7V/Jll/gYyXnOocAAQKVILC7c3u0N7bFL7PFQW7O3C6pysO3R+KlbF7AFAL2t/aUdI5CBAgQIECAAAECBAgQuFcBAeC9Cm7A+fnegqt56xQC5sO/1byuaxEgQKCaBfpau+P5ga/mFge5moV7pWy3srDwr8++lgsBt7dvLuUUZQgQIECAAAECBAgQIHBPAgLAe+JbvZNTj7tSg72NGCa83JaeOXOm4ClpCPAzzzxTsIyDBAgQqASBNJz3D3Y/u6zFQWbmZuIX547GV7Y/HqknoY0AAQIECBAgQIAAAQJrKSAAXEvdZVx7OaFefjGQZVx+3Yvu3r173e/phgQIENgogfziID0tm+LtKx9ly37MFa3KbFbm1xfeiiPZoiL7uvxvZlEwBQgQIECAAAECBAgQWLGAVYBXTLc2JxbqBZif+285YeHa1NJVCRAgQOBugbQ4yAM998U3dx6J5vqmuw8v+j3FhK9dei8+vn5q0eN2EiBAgAABAgQIECBAYDUEBICrobgK1zhy5EjuKlevXl3yavlw8Omnn16yjAMECBAgsLEC29r7c/MCdjd3llyRt658GO9d/STm5or3HCz5ogoSIECAAAECBAgQIEDgCwEBYJn8FA4fPpyrST7kW6xaJ06cyO1+/vnnFztsHwECBAiUiUBnU3v84e6vxK6ObSXX6P1rxyMFgULAkskUJECAAAECBAgQIECgRAFzAJYItdbF/uiP/ii+973vxeuvv77krVIAmFbrrcQhwIODgwvaNTU1teC7LwQIEKg2gab6xvja9idyod4nI5+V1LxUbmp2KjcvYH2dv6MrCU0hAgQIECBAgAABAgSKCvjTRVGi9SmQQr3vfOc78cYbbyy6GvDLL7+cq8gPfvCD9amQuxAgQIDAPQukeQGf2PxQDPbdX/K1To2eyxYHeTtm52ZLPkdBAgQIECBAgAABAgQIFBKoy4YamXCokNA9Hku99g4cOJC7yksvvRSFhu+m4b/79u2L1BvwxRdfXHDn/BDho0ePLthfqV+GhoZiYGAgV/0zZ86EVYMr9UmqNwECpQqkhT7SEN9St92d2+Mr2x4LPQFLFVOOAAECBAgQIEBgMQF//l5Mpfb26QG4Bs889dZLoV/q+ZEP/9JtXnjhhTv7fvzjH3/pzqkXYAr40vlpOHDqDZg+p/P6+vrilVde+dI5dhAgQIBAZQikFYKf2fpo1JVY3aGxC/Hbi+9mPQH9PV2JZIoRIECAAAECBAgQILCEgB6AS8Dc6+7Um2+pufoKHcvfNwV/KQBM10grBD/11FP5Q1Xx7m8gquIxagQBAisQGBq7GL+58FbMRmnB3n2bdsbTKTjM/lLJRoAAAQIECBAgQGC5Av78vVyx6ixvEZA1eq5LhX/pdoWO5auThgoXGi6cL+edAAECBCpLYHfntvjGzsPxy/NvxvTcTNHKpzkB0zDgw1sGhYBFtRQgQIAAAQIECBAgQGAxAUOAF1OxjwABAgQIrKHAtvbN8fu7no60UnAp24kbQ/HmlQ/CtL2laClDgAABAgQIECBAgMDdAqX9yePus3wnsEyBwcHBBWdMTU0t+O4LAQIEak2gv7UnvrXr2fjrs7+Nydni/5v46cjpbP7Az1cVNhy41n4t2kuAAAECBAgQIEDg3gT0ALw3P2cTIECAAIEVC/S0bMr1BGyubyrpGp+MfBbvXP1YT8CStBQiQIAAAQIECBAgQCAvoAdgXsL7mgocO3ZswfXnT0K64IAvBAgQqDGB3pau+ObOI/E3516Lqdnpoq3/6PrJaMjmBHyk/2DRsgoQIECAAAECBAgQIEAgCegB6HdAgAABAgQ2WKCvtTsXAjbWNZRUk/evHY8Pr50sqaxCBAgQIECAAAECBAgQEAD6DRAgQIAAgTIQSHMCfiPrCdhQYgj4ztWP4vjImTKouSoQIECAAAECBAgQIFDuAgLAcn9C6keAAAECNSOwpa03vrHjqdwQ31IaffTysTg9er6UosoQIECAAAECBAgQIFDDAgLAGn74mk6AAAEC5Sewtb0/vp6FgPXZPH+lbK9efCfOj18upagyBAgQIECAAAECBAjUqEBpf7qoURzNJkCAAAECGyGwvX1zfH37k9lEvXVFbz8Xc/GrC2/G5ZvDRcsqQIAAAQIECBAgQIBAbQoIAGvzuWs1AQIECJS5wI6OLfHV7U9kEWDxEHBmbjb+3bmjMXxrpMxbpXoECBAgQIAAAQIECGyEQONG3NQ9a09gcHBwQaOnpqYWfPeFAAECBL4ssKtzWzyz7dFIw3yLbdNzM/G3516PP9z9bHQ1dxYr7jgBAgQIECBAgAABAjUkoAdgDT1sTSVAgACByhPYu2lnPLXl4ZIqPjk7FX9z9rUYn5ooqbxCBAgQIECAAAECBAjUhoAegLXxnDe8lceOHVtQh6GhoRgYGFiwzxcCBAgQWFzg/u49MTUzFe8Of7J4gXl7b87cjr/JegI+t/sr0dLQPO+IjwQIECBAgAABAgQI1KqAHoC1+uS1mwABAgQqSuCh3v3xYM++kuo8lvUA/NX5NyPNDWgjQIAAAQIECBAgQICAANBvgAABAgQIVIBAXV1dPNb/QOzv2l1SbS/fuhZvXH4/5ubmSiqvEAECBAgQIECAAAEC1SsgAKzeZ6tlBAgQIFBlAikEfGrLYAx0bi+pZSdvDMUnI5+VVFYhAgQIECBAgAABAgSqV0AAWL3PVssIECBAoAoF6rMQ8Nltj8WO9i0lte7tKx/G+fHLJZVViAABAgQIECBAgACB6hQQAFbnc9UqAgQIEKhigfq6+vjq9idiS2tv0VamAcC/ufh2jEyOFS2rAAECBAgQIECAAAEC1SkgAKzO56pVBAgQIFDlAo31DfH1HU/Fpqb2oi2dmp2OX5w7GrdnJouWVYAAAQIECBAgQIAAgeoTaKy+JmlROQoMDg4uqNbU1NSC774QIECAwPIFmhua4vd2HI6Xh34dKeQrtI1P38ytDPzNXU9HQ9aD0EaAAAECBAgQIECAQO0I+BNA7TxrLSVAgACBKhTY1NwRX8uGA9dl/xTbrAxcTMhxAgQIECBAgAABAtUpoAdgdT7XsmvVsWPHFtRpaGgoBgYGFuzzhQABAgRWJrCtfXM8ueVQvHH5/aIXSCsDdzd3xgM99xUtqwABAgQIECBAgAABAtUhoAdgdTxHrSBAgACBGhe4v3tPpFcpW1oZ+MLElVKKKkOAAAECBAgQIECAQBUICACr4CFqAgECBAgQSAJPbH4otrX1F8XIrQx84e0Ym5ooWlYBAgQIECBAgAABAgQqX0AAWPnPUAsIECBAgEBOoD5b3OOr2XyApawMPDk7Fb84/0bRxUPQEiBAgAABAgQIECBQ+QICwMp/hlpAgAABAgTuCORXBm6ub7qzb6kPNybH4rcX3425udQn0EaAAAECBAgQIECAQLUKCACr9clqFwECBAjUrEBaGTj1BCxlZeCz4xfjg2snatZKwwkQIECAAAECBAjUgoAAsBaesjYSIECAQM0JbGvvz60MXErD3xv+JM6NXyqlqDIECBAgQIAAAQIECFSggACwAh+aKhMgQIAAgVIEDnQNxL6u3aUUjd9ki4KkIcE2AgQIECBAgAABAgSqT0AAWH3PVIsIECBAgEBOoK6uLp7a8nD0t/YUFZmem4lfZouCTM5MFS2rAAECBAgQIECAAAEClSUgAKys56W2BAgQIEBgWQIN2crAX8vmA2xtaCl63ujURLx68Z2YtShIUSsFCBAgQIAAAQIECFSSQGMlVVZdK1dgcHBwQeWnpvQwWQDiCwECBNZQoK2xNb6+48n4t0OvxmwUXvH3/MTlOJbNCfho/wNrWCOXJkCAAAECBAgQIEBgPQX0AFxPbfciQIAAAQIbJJCGAR/euvAvY5aqSloV+MLElaUO20+AAAECBAgQIECAQIUJ6AFYYQ+sUqt77NixBVUfGhqKgYGBBft8IUCAAIG1FUgLgly7fSM+HTld9Ea/zYYCf3vg69HaWHzocNGLKUCAAAECBAgQIECAwIYK6AG4ofxuToAAAQIE1lfgic0PxZbW3qI3vTUzGb+99G7MmQ+wqJUCBAgQIECAAAECBMpdQABY7k9I/QgQIECAwCoK1GeLgnw1mw+wPZsXsNiWhgF/dP1UsWKOEyBAgAABAgQIECBQ5gICwDJ/QKpHgAABAgRWW6C1oTm+vv3JSCsEF9vevfpxDN8aKVbMcQIECBAgQIAAAQIEylig+H/5l3HlVY0AAQIECBBYmUBva3c8ng0HLrbNZasG//rCWzE1O12sqOMECBAgQIAAAQIECJSpgACwTB+MahEgQIAAgbUWONA1ELs6thW9zfj0zTh66Zj5AItKKUCAAAECBAgQIECgPAUEgOX5XNSKAAECBAisuUBdXV0c2TpY0nyAp8fOx6nRs2teJzcgQIAAAQIECBAgQGD1BQSAq2/qigQIECBAoGIEWrL5AJ/d9njUlVDjNy5/EDcmx0ooqQgBAgQIECBAgAABAuUkIAAsp6ehLgQIECBAYAMEtrT1xmDfwaJ3npmbid9ceDtmZmeKllWAAAECBAgQIECAAIHyERAAls+zUBMCBAgQILBhAg/17o8tbX1F7399cjTSysA2AgQIECBAgAABAgQqR0AAWDnPSk0JECBAgMCaCdRn8wE+u+2xaK5vKnqPj0c+iwsTV4qWU4AAAQIECBAgQIAAgfIQEACWx3NQCwIECBAgsOEC7Y2t8cy2R0uqx28vvhu3ZiZLKqsQAQIECBAgQIAAAQIbK9C4sbd391oRGBwcXNDUqampBd99IUCAAIHyENjZsTUOdu+NT7JefoW2WzO347UsBPy9HU9FWk3YRoAAAQIECBAgQIBA+QroAVi+z0bNCBAgQIDAhgg8tvnB6GneVPTe5ycux/EbZ4qWU4AAAQIECBAgQIAAgY0V0ANwY/1r5u7Hjh1b0NahoaEYGBhYsM8XAgQIECgPgYa6+vjK9sfjpTO/ipm52YKVevvKh7nFQ7qbOwuWc5AAAQIECBAgQIAAgY0T0ANw4+zdmQABAgQIlK1AVxboPbH5oaL1SwHhqxfeLhoUFr2QAgQIECBAgAABAgQIrJmAAHDNaF2YAAECBAhUtsD+roFIcwIW265Pjsa7Vz4qVsxxAgQIECBAgAABAgQ2SEAAuEHwbkuAAAECBMpdIC3u8fTWR6K1oaVoVT/OFg25MHGlaDkFCBAgQIAAAQIECBBYfwEB4PqbuyMBAgQIEKgYgZaG5nh226Ml1fe32arAt2YmSyqrEAECBAgQIECAAAEC6ycgAFw/a3ciQIAAAQIVKbCtfXM80HNf0brfmrkdb1xauOhT0ZMUIECAAAECBAgQIEBgzQUEgGtO7AYECBAgQKDyBR7tfyB6mjcVbcjQ+MU4M3ahaDkFCBAgQIAAAQIECBBYPwEB4PpZuxMBAgQIEKhYgYa6+vjK9scjvRfbUi9AQ4GLKTlOgAABAgQIECBAYP0Eiv9X/PrVxZ0IECBAgACBMhboau6MJzY/VLSGt2en4s3L7xctpwABAgQIECBAgAABAusjIABcH2d3IUCAAAECVSGwv2sgdnZsLdqWNAzYUOCiTAoQIECAAAECBAgQWBcBAeC6MLsJAQIECBCoDoG6uro4vGUwmuubijbojawX4G2rAhd1UoAAAQIECBAgQIDAWgsIANda2PUJEOj4GZAAAEAASURBVCBAgECVCbQ1tsSTWw4VbVUK/1IIaCNAgAABAgQIECBAYGMFBIAb6+/uBAgQIECgIgX2dO4oeSjwkFWBK/IZqzQBAgQIECBAgED1CAgAq+dZagkBAgQIEFg3gc+HAj9c0lDgo4YCr9tzcSMCBAgQIECAAAECiwkIABdTsY8AAQIECBAoKtDW2FryUOA3L39Q9HoKECBAgAABAgQIECCwNgICwLVxdVUCBAgQIFATArmhwO1birb19Nj5ODt+qWg5BQgQIECAAAECBAgQWH2BxtW/pCsS+LLA4ODggp1TU1MLvvtCgAABApUpkBsKvHUwLp/+RUzNThdsxBuXjsXWvX3RVO8/PwpCOUiAAAECBAgQIEBglQX0AFxlUJcjQIAAAQK1JpAbCry5+KrAN2dux7tXP641Hu0lQIAAAQIECBAgsOEC/gp+wx9BbVTg2LFjCxo6NDQUAwMDC/b5QoAAAQKVK7B30844k632e37icsFGfDpyOlLZ/taeguUcJECAAAECBAgQIEBg9QT0AFw9S1ciQIAAAQI1K5AfClzK8N7XL70Xs3OzNWul4QQIECBAgAABAgTWW0AAuN7i7keAAAECBKpUoD1bFfjx/geLtm5kciw+unayaDkFCBAgQIAAAQIECBBYHQEB4Oo4ugoBAgQIECCQCezr2h1bWnuLWhy7djxGJ8eLllOAAAECBAgQIECAAIF7FxAA3ruhKxAgQIAAAQJfCOSHAtdHXUGTNAT46OVjMTc3V7CcgwQIECBAgAABAgQI3LuAAPDeDV2BAAECBAgQmCfQ1dwZh/oOzNuz+MdLN4fj1OjZxQ/aS4AAAQIECBAgQIDAqgkIAFeN0oUIECBAgACBvMBDvfujq6kj/3XJ97evfBS3pm8vedwBAgQIECBAgAABAgTuXUAAeO+GrkCAAAECBAjcJdBQVx+Htz5y194vf52cnYq3rnz45QP2ECBAgAABAgQIECCwagICwFWjdCECBAgQIEBgvsCWtt440DUwf9ein0+PnY8L45cXPWYnAQIECBAgQIAAAQL3LiAAvHdDVyBAgAABAgSWEHi0/4FobWhZ4ujvdh+9/H5Mz07/bodPBAgQIECAAAECBAismoAAcNUoXYgAAQIECBC4W6C5oSme2nLo7t1f+j4+fTOODR//0n47CBAgQIAAAQIECBC4dwEB4L0bugIBAgQIECBQQGBXx7bY2bG1QInPD318/VRcu32jaDkFCBAgQIAAAQIECBBYnoAAcHleShMgQIAAAQLLFKirq4unNh+KxrqGgmfOxVy8fum9mJ2bLVjOQQIECBAgQIAAAQIElicgAFyel9IECBAgQIDACgTam9oizQdYbEs9AD8ZOV2smOMECBAgQIAAAQIECCxDQAC4DCxFCRAgQIAAgZULHOjeE30t3UUv8N7VT2J8aqJoOQUIECBAgAABAgQIEChNQABYmpNSBAgQIECAwD0K1GdDgY9sfSTqsn8KbTNzM5FWBZ6bmytUzDECBAgQIECAAAECBEoUEACWCKUYAQIECBAgcO8CPS2b4sHefUUvdGHiSpwZu1C0nAIECBAgQIAAAQIECBQXaCxeZHVLnDp1anUvuIKr3XfffSs4yykECBAgQIDAagg83HsghrJwb6zIMN83r3wQ29r7o6WheTVu6xoECBAgQIAAAQIEalZg3QPA/fv3R1oNcKOG9dTX18frr78eTzzxRM0+dA0nQIAAAQIbKdBY3xCHtwzG35x7rWA1bs9MxjtXP46ns2HDNgIECBAgQIAAAQIEVi6w7gFgqupLL70Uhw8fXnmtV3hmCh37+vpWeLbTCBAgQIAAgdUSSD377tu0K06Nni14yZM3hmJv547YmpW3ESBAgAABAgQIECCwMoENCQBTCNfdXXwVwJU1yVkECBAgQIBAJQg8vvnBOD9+KW7PThWs7tHLx+LbA1+PhqznoI0AAQIECBAgQIAAgeULWARk+WbOIECAAAECBFZBIM3t98SWQ0WvNJrNFfjBtRNFyylAgAABAgQIECBAgMDiAuseAKbhv2kewI3aNvr+G9Vu9yVAgAABAuUosCcb3rutrfjw3g+zAHDk9mg5NkGdCBAgQIAAAQIECJS9wLoPAX7uuec2FGWj77+hjd/Amw8ODi64+9RU4eFeCwr7QoAAAQJVK5AWBju8dTD+4vQvYmZudsl2zsZcvJ4NBf7DXc/mFhNbsqADBAgQIECAAAECBAh8SWDdewB+qQZ2ECBAgAABAjUt0NnUHoN9B4saXL11PY7fOFO0nAIECBAgQIAAAQIECCwUWPcegAtv71utCBw7dmxBU4eGhmJgYGDBPl8IECBAoHYFHujZG6dHz8X1ycLDfN+9+nHs7Nga7Y2ttYul5QQIECBAgAABAgSWKVD2PQD/wT/4B8tskuIECBAgQIBApQnU19XHka2PRF2Rik/NTseblz8oUsphAgQIECBAgAABAgTmC5R9APj666/Pr6/PBAgQIECAQJUK9LV2x8HuvUVbd3b8YlyYuFK0nAIECBAgQIAAAQIECHwuUPYB4IkTJzwrAgQIECBAoEYEBvsPljS8960rH8ZsgUVDaoRLMwkQIECAAAECBAiUJLBuAWBfX180NDQs+3X9+vWSGqIQAQIECBAgUPkCTfWNcXjLwpXjF2vVjcmxOD5iQZDFbOwjQIAAAQIECBAgcLfAui0C8t3vfjdeeeWV6OnpubsOS36/du1anDp1asnjDhAgQIAAAQLVJ7CjY0sMdG6PM2MXCjbuveFPYs+mHdHS0FywnIMECBAgQIAAAQIEal1g3QLAH/7wh3Hw4MH4h//wHy7LPPUctBEgQIAAAQK1JfDE5ofi/PjlmJ6bWbLhaUGQ94Y/zXoMPrxkGQcIECBAgAABAgQIEIhYtyHA+/bti5deemnZ5keOHFn2OU4gQIAAAQIEKlugrbE1DvUdKNqIEyOn4/rt0aLlFCBAgAABAgQIECBQywLrFgAm5O7u7mVbv/DCC8s+xwkECBAgQIBA5Qs80HNfdDa1F2zIXHb0rSsfxNxc+mQjQIAAAQIECBAgQGAxgXUNAH/2s58tVoeC+/7RP/pHBY87SIAAAQIECFSnQENdfTze/2DRxl26ORxnxy8WLacAAQIECBAgQIAAgVoVWNcAsFaRtZsAAQIECBBYmcDOjq2xra2/6MlvX/koZmaXni+w6AUUIECAAAECBAgQIFDFAgLAKn64mkaAAAECBCpdoK6uLtKCIHXZP4W28emb8dH1U4WKOEaAAAECBAgQIECgZgXKKgA8depUzT4IDSdAgAABAgQWF+hu2RQHugcWPzhv74fXTsTE9K15e3wkQIAAAQIECBAgQCAJlFUAeOBA8dX+PDYCBAgQIECg9gQG++6P5vqmgg2fnpuJd69+XLCMgwQIECBAgAABAgRqUaCsAkAr+NXiT1CbCRAgQIBAcYGWhuZ4pP9g0YKfjZ6Lq7euFy2nAAECBAgQIECAAIFaEiirADDN82MjQIAAAQIECCwmsL9rd3Q3dy52aMG+Ny9/EP5ScQGJLwQIECBAgAABAjUuUFYBYI0/C80nQIAAAQIECgjU19VnC4IcKlDi80PDt0ci9QS0ESBAgAABAgQIECDwuYAA0C+BAAECBAgQqBiBbe39satjW9H6vpPNBTg1O120nAIECBAgQIAAAQIEakFAAFgLT1kbCRAgQIBAFQk8vvnBbBWzwtOG3Jq5HR8MH6+iVmsKAQIECBAgQIAAgZULCABXbudMAgQIECBAYAMEOpva44HefUXv/PH1UzE2NVG0nAIECBAgQIAAAQIEql1AAFjtT1j7CBAgQIBAFQoc6t0frQ0tBVs2G3Px1pUPC5ZxkAABAgQIECBAgEAtCAgAa+EpayMBAgQIEKgygab6xnis/4GirTo3fikuTFwpWk4BAgQIECBAgAABAtUsIACs5qerbQQIECBAoIoF9m7aGX0t3UVb+N7VT2Jubq5oOQUIECBAgAABAgQIVKuAALBan6x2ESBAgACBKheoq6uLJ7ccKtrK4dsjcfXW9aLlFCBAgAABAgQIECBQrQICwGp9stpFgAABAgRqQKC/tSdST8Bi20fZgiA2AgQIECBAgAABArUqIACs1Sev3QQIECBAoEoE0lyAjXUNBVtzbvyiFYELCjlIgAABAgQIECBQzQJlFQDu27evmq21jQABAgQIEFgDgbbG1tjftbvgldMMgJ9c/6xgGQcJECBAgAABAgQIVKtAWQWAn376abU6axcBAgQIECCwhgIHe/ZGXZHrn7wxFJMzU0VKOUyAAAECBAgQIECg+gTKKgCsPl4tIkCAAAECBNZDoKOpPXZ1bCt4q+m5mUghoI0AAQIECBAgQIBArQk01lqDtXdpgR//+Mfx0ksvxf79+2N4eDheeOGF+JM/+ZOlT3CEAAECBAiUkcADPffFUDbXX6Htk5HPIvUWrK/zd6CFnBwjQIAAAQIECBCoLoGKDQBv3LgRP/nJT+K1117LBVbf/va341vf+lZ1PZ11bE0K+3p6enIBYP62hw8fjuvXr8f3v//9/C7vBAgQIECgbAU2t/VGX0t3DN8eWbKOE9O3YmjsYuzZtGPJMg4QIECAAAECBAgQqDaBsv3r71deeSX6+/vvvJ5++uk4depUzv/NN9+MtGDID37wg/j5z3+eez333HPxj//xP66257Mu7UmOL7/8cvzoRz9acL/0PR1LIaCNAAECBAhUgsCDWS/AYtvH10/F3FxaFsRGgAABAgQIECBAoDYEyjYATIFe6oGW3l9//fVcT7/77rsv91T++I//OK5du5Y7lt7T4iFpyGoq91d/9Ve18eRWsZV/9md/lrtaGvo7f3v++edzX1NPSxsBAgQIEKgEgV2d26I9WxW40JZ6CF695S+3Chk5RoAAAQIECBAgUF0CZRsAJuYUSP3sZz/L9fbLs//5n/95vPHGG1FXVxcpuOru7s4dSsNX/+W//Jfx4osv5otW7HtqVxqS+93vfvfOe2rzWm0pPE1+S21pmLWNAAECBAhUgkCa2+9g996iVT1+40zRMgoQIECAAAECBAgQqBaBsg0A/9W/+le5AOxu6LRIRdrS4hRdXV0LDqfAsByHq6Y6pTCvlLqlIbfzhzan9v7pn/5prrdjvqfegkavwpcjR44sWrd8fU+cOLEKd3EJAgQIECCwPgL7unZHY11DwZudzeYBnJmdKVjGQQIECBAgQIAAAQLVIlC2i4AcP3580QAwDfNNvf/S8OBy31JwlkK7f/pP/2kuYEtz6hXqaZfm4Usr8R49enRBuaeeeioXAqYQMQ15LnSNlZik66Z7p/rOHwac9qVNALgS1do6Z3pmNk4Pj8UH50fi00ujcfryWJy5OhYXr03ElZGJuDE2GbOzswVRmpoaoruzJXo3tcXm7tbY1t0eu/raY6C/M/Zu7oz7t2yK7V2tUV9ftn9vUbB9DhIgsH4CzQ1NkULAtOLvUtv03Eycn7gcuzu3L1XEfgIECBAgQIAAAQJVI1C2AWAKufI90PLaIyMjd4b/5uenyx8rp/cU4qXQL9UxDeW9ux1L1fV73/teLtxLgd/dW+rxmHoGpvkP08Inq7mla6eehun++R6WKfTLB399fX2reTvXqkCBFN6duDIW7529Fh+cG4kTF2/EmcujcSEL+K5en4jR0dtZwHfvE+oPD0/Eybi2pFBDY310djRH96bW6O9qi609bbGzryP2fBES7si+7+7tiJ3Ze1ND4d4/S97EAQIEqkLgQPdAwQAwNfL02AUBYFU8bY0gQIAAAQIECBAoJlC2AWAalpp6+z3xxBN32pDvkZbCwfyCIHcOZh9Onjy5YL7A+cfW8/P3v//9SK/8VspKuvnALYVxi22pzal33lLDgEsNGfPXvrsXYQoV07VTCJi2AwcO5IZZp7rP7xWYP9979QoMj92Kf/vRhfjVJ5fivc+uxoks8LsyPB4z00v34JuLLPyrH4/Zxhsx1zgScw1jMVd/O9t3a+F7ZMPt6lLp7FrZe2Sfmq5/Mxpv3r8o6NSmrMfvXPY/UzPtUTfbHrPZ+/UbnTEycitOR+EJ/JuaG6KttSna25qis605Nmeh4KHdvfH0/i3xjQe3xd6+zkXvaScBAtUh0NXcGT3Nm+L65OiSDTo/fimmZqejqb5s/3Noybo7QIAAAQIECBAgQGA5AmX7X7xPPvlkLoD6e3/v791pTwqj0vDfxUKy1Dvw7//9v7/qvePu3HyNP8wPN5e6VQriUlCYys7vAZmG8C53kZA0xPru7Tvf+U6kV37LX3OxHon5Mt4rW2BqZib+zZtn4qX3zsb7nw3HZxdGsh6rN7/UqBTZ1WX/LLbNtJ6Iib3/XRborWwurcaxxxa7bG7frR3/UxYiZkHi3dtMW9RPd0fdvFf9dE/UTfVH/dTm3Gtqsj2mJmfixo1bubM/zf7vb94aiv/hi2u1tzfHjq2b4v6d3fH4fZvjq/dvia8e2BLtzU133813AgQqVGBg0464fnXpAHBmbjbOZSHg3k07K7SFqk2AAAECBAgQIECgNIGyDQBT9dNw1/7+/lzYlUKvNP9db29vbj68fPNu3LgRP/nJT3JDblNAlgLCStzyQ28L1T3fay8Fc/MDwNUYEpx6/80P/1I9Ug/MtOV7Bea++D8VL3AzC8X+j9+eiJ/9+ni88cGFuHlzakGbUu+82ebzMdt6OmZah2K25Uz2Ohsdx/9J1huvZUHZ9KVupmPF4V/uYqmH3yLbXEwvHv6lsg03YzZ7RcuFRc78fFfzlX8/Wq78B0sen5iYjOOnruZef/Grzxe6Sf/70Zv1FBzY1hUP7O6JJ+7rj6/fvzUe290XjQ3mHlwS0wECZSqwJ5vf792rHxes3enR8wLAgkIOEiBAgAABAgQIVIPA4n/yLpOWpZ5+af65f/bP/lku+Hvuuefipz/96Z3Vf3/4wx/mwr98dVOvthRi/cVf/EV+V8W85+fbS4HnUlt+Lr7Feu8tdU4p+1P4l3oRpiBxfgiYFi1Jz8AQ4FIUy7vMjZuT8T//6nj861dPxNsfX4rJ21m49sU2VzeVBX2nYqbt02yk7SfZe9Y7NIVrd22zLeei4da+u/am7K/7S/uWsyM3xHeRE+YWqcMixZbcVTfVs+SxiT1Zj8WsV2P95I6sg+H27D173d6d9SjsieFsXsP0evvDC5GfbbMxm3twS39H7N3RHQ/t6o0j+zbHNx7YHvu2GEa8JLIDBMpAoKOpPfpbe+LqraWnDLg4cSVuz0xGS0NzGdRYFQgQIECAAAECBAisjUBZB4CpySmQmh9KzWdIwWB6VcOWn8Mv38tvPduUAr503/m9ClOvv7Q/hYAr2YaGhgqedv78+YLHHbx3gbQy7//2mxPx01c+iGPZfH7T8+bwm20cjumO92Km893s/YOsp91k0RvOtAwtGgBm3QMj6zL4u2tkPQLrp7NgbLYtm7evNXul41+853r7pV66WW+6uTSouD679dbF7103nU0hOJDNITiRzSmYBZL12Ss3b+Dixe/em4YCL7alnoUzbVmPv2zI8kx7Ghg8b8vq3nBrdy4MbLg9kN0/+5yFhNPTTXH+4mjulYYR/49fnNKazS+4PVuheH82jPjRPf3xHx3eE0/tXfy+8+7iIwEC6ygwkPUCLBQAzmZ/GXA2Gwa8P1s12EaAAAECBAgQIECgWgXKPgCsVvi72zU8PHz3riW/L6fskheZdyDN8ZeCvtQLMB9APv300/Hiiy/OK7W8jwMDA8s7QelVEzh5eSx+9P++Hf9PNqw1P/9duvhc/VhM9v5NTG86muVxhQPaxSoz23omYuTLR1KM1/7ZD7M8LVuoY2ZTltGtzhx69dO90XHqv7xzw9zCIWlRkWyhkdncQiPZYiPZe+5z+t40HLNNV7J9WU+fLChcMgBsvpIL/+5ceP6Hhmyxk46Pcq87A6PnspAy9RLMAsGGW3sjzVlYP/V5aHkrGz596sy13OuvXj0V//3Pj8amTS3xSDaX4Lce2RX/yTP79RKc7+szgQ0QSAHg21c+zGK+pbc0DFgAuLSPIwQIECBAgAABApUvIACswGeY7y24mlVPQ30XW1xlNe/hWmsnMDub9fZ79WS8+Jfvx7sfX4zZ2S//UXeubjYmN/9fJfeiq5vqywKvrBdcridcCr/uW7IBDdnw2flbfUNddHa0RG9Xa/R3t8f23vboyhbdWGpL9U2rD1+5cTOujd6OG9nn8fHJmMzmK8xvqbdgZCsB12WLe6Qhu0ttaUjzXNbDMS0Istg207z0vIGLlc+6MGaB6bnca7r71SzkzHo4fhEALlZ+NKv/r7Negun1T/7XV2Pz5o54MptH8NuPD8R/fHhvbNnUuthp9hEgsEYCbY2tsaWtLy7dXPov2i7fvBo3p29HW+OX5zldo2q5LAECBAgQIECAAIF1FRAAriv30jdL8/uVGuzle+ktfbWNP3LmTNZbrMCWhgA/88wzBUo4VIrAlSwo+6//9Zvxb355PEZGvjxv3/xr1M90RcP4oWzY7/vzd3/+ORuOm+bAa5g4mE3/d3/2OpAN4+39crkv9jQ3N0R3V1tsyYK9nWluvC2b4kC2cMbB7V3x0PbuGMj219ff+6IZY7em4vjl0dzr5KXROH11LM4Nj8elbKXiq1lYODJ6K8ayoHBm3vDm1AOxbmrbknVPbWsb+s9jJi10koWBuVc2v2GWcC55zvwDi82DmI7PZb0Tb+7+55nd/i8cD2TZYUdcuTIeL105GS/95mR8Pxv9vDWzemz/5viDR3bGf/jk3hjoyxZRsREgsKYCA507CgaA6a9MhsYuxMGevWtaDxcnQIAAAQIECBAgsFECAsCNkr/rvssJ9fKLgdx1ibL6unv3wh5hZVW5KqnMP3/l/fhv//fXYiILwNI2FzO54b1p3r3G8ccWbWXT6DO/CwCzIbuN44PZkNZHs2BwMOqz4bt3bx0dzbE7hXoDffHE3v54ZKA3Hs9WxN3e3XZ30TX53tnaFI9n906vpbbU+/FS1utu6Pp4nLt2My6MTMSlG7fichYQDmf7r41nn7PA8GwWIKYh0amd9WOPR2M8fueSc5neXNPVmMmteJytfJwNkU6f59Jw4fnbTDav4RJzFs60fPb5IirZQirRny1ElAtVd2aBYBaqTqRQ9WAuVL2Y1eOl9MoCwf8ifhn9WQA4uL8/fv/hnfGfPrtfIDjf22cCqySwu3NbvHH5/fRv+pJXPDN2XgC4pI4DBAgQIECAAAEClS4gACyzJ1ioF2B+7r/lhIVl1jzVWQWBjy+OxH/2L/4m3vvoYu5qacjrVPcvY7LvL3OBVZqvruHkI7kFNu6+XePoE9HU+gfReONwFkjdn5VpuFMkhX0PZCHfw3v64tn7sznsDu2IvX3lv8pt6mmYAslcKFmk807qMfmLTy7Gq59ejndPD8fJ89fjQjZn4lQ21LguWzQkN2/g2JN3TOayhUfS4iez6dV6Ogv1GhZ1TSfMtp26c17uQzYP4Wzr2dxrqvevP981uTkXBDZOPJCFrg9lgWB/XM16NP5ter1+Ov6b/+U3sSsLXL8+uCv+6Cv74/lD2dyDq9CTcmHFfCNQewJphd/t7Zvj/MTlJRt/JVspeHzqZnQ0rc9fcCxZEQcIECBAgAABAgQIrIGAAHANUFdyySNHjsQbb7wRV69eXfL0fDiYFuiw1Z5A6un2X/2fb8a/+Ddv5wKrXI+/7l/H7c3/d9Z77dodkNn/n737gI+izP8H/tma3SSkJ0BIgARQBBvNBhYgCKJio6jnWe5o3k/PswBy9nIiiGe5JqB/vfPulCJnwQrE3iA0FRuQAAklkB6S7bv/55mYkEm2JJBkZ5PP+FozM88zM8/znojkm+d5vlEHxSi/b8TIvtMbztXv6MQaepbia+sPES8CZyNP6YVfjeqPi8XXzh5sSom1KNNu5dTb+k26bj9Qic/F2olb9pTip6Jy7C2uQllZrVhL0QqjGLkH+QmxeSwFIWqI+KEYUeiWH/He5CZHExrFtGw5NVsmF9GJLMn7DlRhhfys+wHRIih72oA0TBzaB786Oxuy/dwoQIFjE+jdrWfQAKC8a6GYBjwwMevYHsCrKEABClCAAhSgAAUooGEBBgA18nKGDRumtKQ+yOevWfn5+crpnJwcf8U814kFvso/jBn/+Ah7iiqUKWzu2C1wpr4uRqb5T2jhSHrfbwBQEqWINfvOOy0DN5x3As4XwaXOHvQL9W0h+39Kr0Tl07iuw+XBxt0l+HLnIWwTgcEd+yuxTwQGG2dWblzfVDFaSU7iEVOAlWCg3t242O++z3wILvmJ24jYHX9uVkdO765PKPLAS18gS4zOHD+0N6affwL6p8U1q88TFKBAYIH0mDQYdHp4fN6AleQ0YAYAA/KwgAIUoAAFKEABClAgggUYANTIy5s6dSpmzZqFvLy8gC2SAcDs7GxE4hTgwYMHq/rlcrlUxzzwL2ATU1N//+8vsTL3R3g9YsyfSFzh6P4KPDE/+r9AnNXb+sBcnqMECnViwqrcrFYTxg7vgz9MOBlnZKcq5/iv4AJRJgNGDeiufBrXlNmKPxNTiDeKoOx3e0uRL0YPFooRe6g9EUbxkZucli2nDLutIhgoA4LWXSLJSG3j26j25XVKlmPV2boDr0lM9faJzKTuBOzaXYq/y8/qLchIj8dokVn4t+cPwNA+KX6u5CkKUKCxgElvRM/oVBTV1C2f0Lisfr/cUYVqZw26mZmcp96EXylAAQpQgAIUoAAFOocAA4AaeY8yqDd58mSsWrVKyQbcNMi3bt06paXz5s3TSIvZjPYW2CACTNc+vQ6HxBp1Pp0djtQ1cCWJ7wOd/9ErBrGunLnkEhFnksGkusBfdp8kXD/mRNx8wUmwisy93I5fIElMw510eqbyqb+bDNS+/U0h1mzei40/H0SRCAjqRLZhmXEYZRNEMNYrRmvuF4HAnSIg+CPcMT+JgGBN/eXKFOCGgyY7DjHS0x23CXp7ppKwRSZt0duzUCRGJL4sP+9+p4zqHHVqL9xw7gCMPpHrBjYh5CEFGgTkNOBgAUBZca8YBTg4qX/DNdyhAAUoQAEKUIACFKBAZxDQ+cTWGTqi1T7IUXv9+okggNjWrl2LYNN35fTfrKwsyNGAS5YsUXWpforwpk2bVOcj9aCoqAiZmZlK8wsLC8Gsweo3+fjb32DR8jy4xTRUtwgY2Xv+U8lSq65Vd6S390bU4StEEGmQEviziNF+Y4b1wV2XnILhHBnmj6zdz8lRgqs27cH7WwuxRUwhLik5GuyTD68LCBaKQOAPSkDQUnyNSEDSvVm7fHDjyIA7RLDQrirTuWNFMFBkMq4eIgK+J4m1A00N5fHxFpx9ci9cN2oALhFBwa4+xbsBhjsUEAJurwdvFuTC7fME9OhmisGE3qOg09X9IiVgRRZQgAIUoAAFKECBCBHgz98R8qLauZkMALYDsBytJ6fz1q/Z1/QRchqvLJ87d27TIuWacePGKYFCWUdm/l24cKFSb+XKlRE5/bdZJ8UJ/gHkTwWotDkx7S+5+GJLoRj154Aj7TXUZ5BteoXOlYioQ1eJINBwEfjTwyRG+E2/+BQ8cPnpiDYfDQg1vY7HHS9QKLL8vrFlLz7cvh/fipGdxYeq0ZJfvbitP8HW58ngDfZEiUQiJyvBQGPNKWKA6NEMpjKz8xmD0zHtnH6YIqaAmwwcBRock6VdQeDr4m+wp3p/0K5emDkSCVHdgtZhIQUoQAEKUIACFIgUAf78HSlvqn3byQBgO/nK0XxNp/HWPypYWX0dGUSUWYHlPWSG4KFDh9YXdYqv/AOo+Wv8fGcxrnt6vcgEXTdazGs6jJqsh8Wifg51ZZ8B5rJxYrrvxWLkl1gbTmyDT0jDSzdfgBN7xKvr8kiTAoer7UpAMPe7fcoIwf0Hq/wGBF1xX8Eu1nwUc4lb1g+vUYwIHKgEA01idKDOG9twncViwhkn98T0MQMxSawdyJGBDTTc6WIC+2sO4bMDm4P2emBCFk5NqVvTM2hFFlKAAhSgAAUoQIEIEODP3xHwkjqgiQwAdgAyH9FcgH8AqU0eeXMrnlq5CW63en0/Z8JHcPT4b0Nluc6f5eB1SrZZeTI62oz5V4/AbeMGNdThTuQJ7K+oxX++3IV3xRqC34kEI3b70SQ5chqwTCLiif0O7thvlbUEW9RDnx7WvXfBaGu+lll8vBU5YkTg7y8cjCEiszA3CnQlAZkF+K2CD+H0Hv3vrGn/Y4xWTOxzHqcBN4XhMQUoQAEKUIACESnAn78j8rW1eaMZAGxzUt6wJQL8A6hOSa4VN0VM+d34zT6/bHKtOFvm00oAKOrwlTCVj1am+8rKI4dm4sWZ56OHCOZw6zwCbo8X73y7D6s25OOr7w/gYHG1qnNeU4kIBG6Bu9uWuuzCugDLuHosiN35pGp9QNWNfjmQ2YQvPzsbt+QMQnpCtL8qPEeBTieQd+g75FcVBe3X2IyzkGxJCFqHhRSgAAUoQAEKUCASBPjzdyS8pfZvY4cHAKuqqiCnt27cuFFJjiETXsTFxal6+sQTTyhlctpr3759VWU8iEyBwYMHqxrucrmwY8cO5VxXTQLy44FKXPTo2ygV68MF27zGUpH5192QJCIhwYpFN52Dq8/IDnYZyzqJwM5DVXjh45/xvhgduGtvGXzeowE/r6FKBAO3iWDgZnhifhTfJ0cTGxgrz4b1wE1+FTyW3fDpa+oSiIj1I+Wm1+twygndMSPnJFx7VjaMhrrzfm/AkxSIcIHi2lJ8vH9j0F4MiO+DIaknBa3DQgpQgAIUoAAFKBAJAgwARsJbav82dmgAcPXq1ZgyZYqqV4mJiZDJLUaPHt1wfv369UrGXBkIlFn43G53Qxl3IlOAAUD1e9tTdgTn3fsGystr4TEfgM9cLLK6nq6u5Odo1NDeeOWW0Yi3mv2U8lRnFzhYacP/+/RnrMnbgx93HVZNGffpa0VWYTFNOE5MJRdfrftmi+Qgp/glsaU/J+pths6VAJMIFJqqzm6YVi4viIuzYKIIAs4VSWX6p6l/QeP3hjxJgQgT8IosPGt2fwS7p8kaq436YTFE4ZK+F0DPbMCNVLhLAQpQgAIUoEAkCjAAGIlvre3b3GEBwIKCAmVUn+zC5MmTkZSUpGS8laMBZZBv1apVuOKKK1Q9lIvUyzKP5+ioFlUFHkSsQFf+A6hETPs9597Xlamdnqi9qO39lBi55YC18A6/67XJl2wyGTDvmhGYe5H/gE7EfiOw4ccsUCUyRr/8ZT5Wf52Pb34qhsNx9BclPr1IGuI1i+nizbP++vR2HOl/pxjyp17/TG/L/iUYKLJKe2OUdsk/fwcNSMVvxg7ETSMHcFTgMb8tXqhFgS2Hf8COyj1Bm3ZB+gikRScHrcNCClCAAhSgAAUooHWBrvzzt9bfTUe2r8MCgHKqr8x+K0f7xccfzVRaWVmJuXPn4vnnn28WBOzfvz9k4JABwI78luiYZ3XVP4COiOQO59z/BnYXlsMTtacu+GeoVdB17hhE75kv4jJpqpeQlhqL/94+DmdkpajO84AC9QIOlwfLNxRguUgkkvfDAdhq1cG9+nryqyvua9jTX2h8Sr0vMgnL0aimilFKRmHdL1OEY2OjcNFZWbhn0mnITuWoQDUajyJRoMRWjtx9XwdtenZcJoanqZewCHoBCylAAQpQgAIUoIAGBbrqz98afBVhbZKxo56+efNmyE/T9f5kMHDJkiUYNmyYMjJQ1jnttNM6qll8DgU6TEAGaXIee6cu+CfWYKsVyT1EhKXh+T5jDRwpb4p126Y3nBt9Rl/85+YLEGsxNZzjDgWaCkSJEaLXj+yvfGQSkde37MUrn+/El9v340i1eoqjzmuB3p4Jr6Ww6W3qjvVuMT04T/nonCkiEHieGBl4Do4cicPKdT/itdyfcPpJPXHHJadi0umZ/u/BsxSIAAGZ4CPaaEGt2x6wtUVHDmKoWAdQr+OamAGRWEABClCAAhSgAAUoEBECHRYAzM7Obhb8ayw0c+ZMyDpjxoxRAoV9+vRpXMx9CkS0gNfrxcTF7+P7HYfgNR2CLeNZVfBPds5QcyIsB3+t9NNkNuD+687CbeMGRXS/2fiOF5DJOyYP76t85Pfd2yKj8PO5P+KLb4rgsLvF6L7TlI8nqgiu+C9FoO8r+IzqTMP1rfaZS+BMWw1n6hswVstRgeeJmPWJ2CwCi9eJT4/u3XDdmBNxx4UnM0hdj8avESMgp7j3ju2JHysKArbZ6XVBJgzpGZMasA4LKEABClCAAhSgAAUoEAkCHfYr7YSEhJAeOTk5SvIPuUagzBbMjQKdQUAGYSb/JRcbv9kHr6FajPx7RgRcjqi6Zqg5CdaiW6DzRSE1JRbrHrmcwT+VEA+ORUCuo3rpaZl4Q0wh37vkeiyceS5OHdgDeoNYHdCRAcuhKYjZuVCsP3kLjFVDxbqBAX4nJLILy+Qitl7/EOtVOhuacrC4GotfyUPWzf/GtX//ENv3lTeUcYcCkSCQ2a1nyGbuPXIgZB1WoAAFKEABClCAAhSggNYFOiwAOGLECMgswHLbunVrw35ToKFDh2L58uXKdOCysrKmxTymQMQJzHjxc6z7qgA+kejDlvEXkfH3sKoPdcG//1OCf0mJ0ch96FIM6Z2kqsMDChyvgFWMKr159EB89sCl+PFvv8Ktk4cis1eCSBQi1vyrORXW/bMRu3MRooqvFlOE0/0+zlR1pvg+tTQrkyML13y6E+fMeQ3nPvwW3toWYHpxsyt5ggLhFUgwd0M3U13Sm0At2XekGB4vk5EF8uF5ClCAAhSgAAUoQIHIEOiwJCCSQyYCufDCC5WkHzL5x9q1a5Upv/6oZMIQuS7g7t27mQTEH1CEnRs8WL2Iusvlwo4dO5ReFBYWIiMjI8J61LLmzlm+AUte3waf+Mfe8wW44zeoLpRrsUXvnSOyrloQ2y1KBP8uw8CeR5PkqCrzgALtIJC3pwRPvv0tcvP2wGarSx4iv1+9lnw4Ez+Bu1teQ8bg6IL7xMhB/+v+ySnFeke6CCjW/V4pIz0eM8YPxi0ig7DJ0DwbcTt0hbekwDEJfFe6A9+X7wp67Tk9hiAjtnvQOiykAAUoQAEKUIACWhVgEhCtvpmObVeHjQCU3VqxYgV8Ph+GDx+OsWPHKl8DdVdOGd60aZNSL1AdnqeAlgX++1U+lryxTWmiK+HjZsE/nStZTL28VQn+WawmvH73RQz+afmFdtK2De+Tgld+Nxq7n/s1HvnNSPTvmyyCeGKKsL2fSEhzU8OoQGPlWQGDfz59rchovRA1/e6BM+kD+PQ1KNpfiQde/AJ9f/df3Pafr3C4OnCihU5Ky25FiEBvTgOOkDfFZlKAAhSgAAUoQAEKHI9Ah44APJ6G8trOJdDZfwNRXuvEKbcvF2tZ2uGxFKC2zyKxdlqjKWQeC6L3zIfB2RMy4cer8yZg3CD/0y4715tnbyJBYFthGRaLUYFr80S26pqja/4FarszcR0c3VccLfaaRebgs2EuGwe9K005L7/Pxwzvg0enDMeJPTjK9SgW97Qg8MHez1Hh9J8MR7bPILIAT8oaA5M+wDqZWugE20ABClCAAhSgAAUCCHT2n78DdJunmwh06AjAJs/mIQU6rcDMFz5Vgn9yJJSt1xJ18E/02iJGVsngn0FkbF1y6xgG/zrtd0Jkduy0zCS8PPt87PnHdXjktyOR1TsxYEfEZGExVThXXa53wpX4MWqy74MtfSk8UXvgcnrw/hf5OPPOlZj4xPvYLKYec6OAVgRCJQPx+LzYX3NIK81lOyhAAQpQgAIUoAAFKNBqAU0FAOV6f9woEOkC73xbhA++zFe6YU9bCZ9JnczGVHohTEeGQKfXYdHMUZg8vG+kd5nt76QCUSYDbssZhG0LJ2PNw5NwnhjBZzSq/7fhM1aJwa0BkijofCJ7cB5qs/4ksl//Ge7o7SKZghefbd6L0fP/hwsefRsf/3Swk+qxW5Ek0Du2R8jm7q1mNuCQSKxAAQpQgAIUoAAFKKBZAU3NZenXrx8Tfmj2W4UNa4mAw+XBrUs/FWtdQqyDJqb/WtULyxtqByDq8BXKre657kzMOO/EltyWdSgQdoHzBnTHeXdeiENVNiwU04NXfvIzKips0LsTxHT2P9YlDUnKFUlDNokRr95m7fXE/Aib+OjtGWJq8HgYq4Zj8/b9uFR8TuqfinuuGoZJp/tPMNLsZjxBgTYWiDFFI9mSgFJ7RcA7F9eWwOFxIspgDliHBRSgAAUoQAEKUIACFNCqgKbWANTr9fCK0SHcOr9AZ12DYNZLn+OV979veIE+nROOlDfhSloLeKMQU/CgCJgk4Zrxg7DkxpEN9bhDgUgTkH9W//OLXfj7u9/hp/yj03m9xnIxJXg9XAmfiIXTAif+0DmTYS69SKwVeI5IOVL3uyg51fiBaSNw5dA+kcbB9nYCgZ8rdmNryY9BezI87WRkx3XOrPVBO85CClCAAhSgAAUiWqCz/vwd0S8lDI3XVADQYDBwBGAYvgnC8cjO+AfQV/mHMeH+N+D1iOF/TTaPZTe8plKYqoehe1o3fP/nKTCJ73duFOgMAp/vLMaf/rcVX24rEn+G1/0SR2YGdoogoCtpHeQ04UCbde9tMNYOVhUPyErGw1ePwMWnckSgCoYH7Spgc9uxZvdHaP4n+NHHdrcm4/xeI46e4B4FKEABClCAAhSIAIHO+PN3BLBrronqxZw01zw2iAKRISBHQ03/x0d+g3+yBwZ7XyX4p9Pp8LeZ5zH4Fxmvla1socDI/t3xzpzx2PrsNEzNOQnR0WYxCzgaUWUTELNrAaIO/Bo6R/dmd9Pb+sJQO6jZ+R0FpbhmwXs4877Xsf6H/c3KeYIC7SFgNVqQak0KeutDtlLY3I6gdVhIAQpQgAIUoAAFKEABLQowAKjFt8I2RZzAff/bgr1FgdeOqu/QxFH9cOHg9PpDfqVApxLokxSL5387Cvn/uBZzrhmB1JRY6HwmmCvPFdPfH4Kl6GbobVkNfY4quURM/9U1HDfd+WHnYVzx8NsY9dBb+GxHcdNiHlOgzQUyY3sGvaccHVh0hIlrgiKxkAIUoAAFKEABClBAkwKcAqzJ19L5GjV4sHqKn8vlwo4dO5SOFhYWIiMjctdU+ulgJc6Z9xpcTo+YOuYLGNCIj7di+1NTEWflAvKd7zucPfInUL9O4J/f2Io9vwTI5X8jnugfRbKQPEQVX+f3vxdZx56+BAbbCTBVnKsEEWWccJgInj99w9k4LSP4KC1/beE5CrREQCb5eLPgQ+XP8kD1U0SykDEZZwUq5nkKUIACFKAABSigOQFOAdbcKwlLgzgCMCzsfGhnErhRTP2VwT+PZRdsvReLtf78j1RaeNM5DP51phfPvoQUkImdbho1AN8+MQUv3jUOJ2anKAE/Y+1JsBSLacEyqudn80T/BHfcZji6v4qa7Pvhiv9CZNb2YNN3+3H+vNWY8pf12F9R6+dKnqLA8QnIDL89olOC3qREZAqucdmC1mEhBShAAQpQgAIUoAAFtCbAEYBaeyNdpD2d5TcQi979Fo/+6yv4dC7U9n1EJPoVU8O8JkSVTIKpLEeEN+oSfYwcmol350zoIm+X3aRAYAG5pt9DqzZh6w/iv5UA2RZqRSDdE/2z6iZ6Rw+YSy6DsXqI+O9KD3OUEdfkDMTCqcMRbTap6vKAAscjsKd6P74u/iboLU5NPhEDE49OZw9amYUUoAAFKEABClAgzAKd5efvMDNG/OM5AjDiXyE7EC6B7fvKsejVjcrjnclr6oJ/8kjvgiPtNbjjv1LKZEKEF2eer+zzXxTo6gJjT0rHJ/ddinV/ugLnnJ4BnV49CtATVdgs+CfNZHDd3muJCLQ/BnfMdjgcLvzz7e8w4NZX8fjb30BON+ZGgbYQSI9Jg0EX/K9HhUcOtMWjeA8KUIACFKAABShAAQp0mEDwv+F2WDP4IApEloDb48U1z6yHU079jdoDZ/L7qg7I7KbGyro1ou65dgR6iPX/uFGAAkcFzshKwXvzLsJHC67EGaf2gkiQrWwGRyase+aI7MADjlZutOe17IUt8xllur3HUoDqKjse+/fXGHjHCry6Ib9RTe5S4NgETHojekanBr243FGFamdN0DospAAFKEABClCAAhSggJYEGADU0ttgWyJG4PZXvsbuwnIxg9ENe89/ArpGo498BlgO3KBM/z35xO64deygiOkXG0qBjhYY0jsJ6+ZPxNpHL8fQwXUZWI22AbDuvQvWwt9Db8/02yRP9A4xGnABbOnLxKz7EhwsrsbMp9ZjxL3/Y8Zgv2I82RqBzG7BswHLe+3lKMDWkLIuBShAAQpQgAIUoECYBRgADPML4OMjT0CuYfbyu9uVhjtT3oHXUqTqhLnkYhicvWAyG/DSzZz6q8LhAQUCCJyRnYqP7r0Eax6ehFNE4FwmCDHWnIzo3ffAsm8W5BqA/jZ33EbUZN0Pe+oq+PS1+GlXCS5+4E1c9MR7+Lm40t8lPEeBkAJyBKBRV7eGa6DKhdUHRHKaAAtZBrqI5ylAAQpQgAIUoAAFKBAmAQYAwwTPx0amQJXNiel//UisN+b7ZervO6qO6O0ZMJfWJfuYI5ITnNA9XlXOAwpQILjAeQO64/MHJ2HVvRfjxH4ya7AepuphiC54QIysvRE6V1LzG+jdcCV/IAKBDymjcmVM5vPNhTjrrlW4ceknKDtib34Nz1AgiIBRb0Cv2O5BagBVrhpUOo8ErcNCClCAAhSgAAUoQAEKaEVAUwHArCxm1NPKNwbb4V/gJhFMKC2rUbL+2tNfbDL1V//L1F+jMpXx7otP9X8TnqUABUIKXDg4HRsfvQLLbs9Bzx5xIhBogKnyHMTkP4Ko4ikQmUKa3UOWi3GDDefdbi9Wf/gTTvr9q5i/Mg8Ol6ehjDsUCCWQGet/1Gnj6zgNuLEG9ylAAQpQgAIUoAAFtCygqQDgzp07tWzFtnVxgX99vhNrvypQFOqy/u5XiZhLJ8Lg6IOY2Ci8eutYVRkPKECBYxOYdkYWfnhyCu6/4WzExVmg85lgLh+H2F2PwlQm/jvz1f1vTOeOg7lsvN+H2Gwu/G31Fpx426v495e7/NbhSQo0FegenQKz3tT0tOqY04BVHDygAAUoQAEKUIACFNCwgKYCgBp2YtO6uMC+ihrMe/FzRcEd/ZPI+vueSkQmKjCXTFTOPTl9FLP+qnR4QIHjE9Dr9bhrwsn4+S9X4zeXnoKoKKPIuxMLy6FpYkTgQzBWD4H58CRxzuL3QT6dU1kfsKy8Fr97NhcXPLqG6wP6leLJxgIGnR4ZIaYB17htKHNwrcnGbtynAAUoQAEKUIACFNCmQKcLAObm5mpTmq2KaIGrn8lFTY0TXkMV7CLrqBiGdLQ/Stbfm5SphxNG9sO1Z2YfLeMeBSjQZgLRZhOevvYsfPvM1bhI/LemN4gVAl3dYd13s5gefG7A5ziT3kdN9n1wxX8m1gj0YvP2Azh7zmu4/b9fw+XhtOCAcCxAZmwLsgGLZCDcKEABClCAAhSgAAUooHWBo4slab2lLWzfuHHj4OEPdC3U6rhqgwcPVj3M5XKpjrV88Ke3tmHbjweVwIE9/QX4jFWq5sqRRwZHBlJSYvDSzMBBCNVFPKAABY5ZoEe8FctvGYNvrxiC2176Annf7RcBeJ3f+3lNJXUjdvUu2Hv+C/qET2ApvgawZ+GFt77Bm1/m48nfnIPLh/Txez1Pdm2BVGsSLIYo2D2OgBCFRw7itJSB0Ov8fw8GvJAFFKAABShAAQpQgAIU6ECBTjUCsLKyEj6Z/pEbBdpIYFthGf68apNyN0/Md/DE/KC6s+HIYGXdMTkS6UURkJAjlLhRgAIdI3BKr0Tk3nOxkjE4q3ei34c60lZCDBNsKPNad6O27wLYe/xTjOitxuGSI7h+0QeYsPBd7CljRtcGKO4oAjKoFyoZiAwOVjjUvxgiHwUoQAEKUIACFKAABbQmoBMBM01HzFavXo3ly5ejoqICZWVlip/c97fJclnGEYD+dLR1rqioCJmZmUqjCgsLkZGRoa0GitbIqYGnz1uNwn1Hv99ccV+LwMG/RUDBAZ0rAdG774Pe001Zl0xOTeRGAQqET+D5T37Gn1bkobS0RmmETydG/aUvhbvbNv+N8sSIdQSvgrFypDKCUK4tOGvSqXjwsiEwGjrV78f8959nWyRQYitH7r6vg9Y9XYwAPCGhb9A6LKQABShAAQpQgALhEoiEn7/DZdOVnqvpKcDz58/HokWLWjWqT8cpOF3p+7dd+3r7fzeogn/yYaaqM2Gw94FNrAMYVXy1Evzr1ycJi6ed0a5t4c0pQIHQAtPPOwE3iLUBHxVTe5eu+Uas2wmxPuD/wS1G79rTlsMXVay+iaFGmRZsiP8SUQevg8PRE8+u3IzXPtuJv844F2NPSlfX51GXFEi2JIScBlxqP/qLoi6JxE5TgAIUoAAFKEABCmheQLMjAAsKCtCvXz8MHToU06ZNQ0JCApKSkoKCbtiwAYsXL+YIwKBK2iiMhN9A/HSwElc/vQ679tSNPG0sJxMJiPQDMIsRQ58tuBIDe8Y3LuY+BSgQZoFKmxN3/OdrrP7oZ/H/BK9Yw9MNZ9I6sR7g2xCLdjZvnUjmYy6dID4TRY4fE+TvknLOysaS34xESqz/7MLNb8IznVXgi4NbUSTW+gu0WcU6gZf0vUB833AdwEBGPE8BClCAAhSgQPgEIuHn7/DpdJ0nazYA+NprrylTf1esWNGqt2EwGBgAbJVYeCpHyh9AXq8Xd766ES++8y28nuaz5R+86WzcceHJ4UHkUylAgZACW/aWYdayT/DjzsNKXa+xAo60FXDH5fm9VudMg+XgtTDWDlLKY2LMmDt1OG7LOQl6PacF+0XrAid/rtiNrSU/Bu3pxX3OR4zJGrQOCylAAQpQgAIUoEA4BCLl5+9w2HSlZ2r2p5n8/HzMnj271e8iKyur1dfwAgoEEpA/8D917Zl4475LlCy/jeuNOLUXg3+NQbhPAQ0KDOmdhA2PXI4FYkpvbLco6N0JsO6fCWvhrdA5k5u12Gc+BFvvp2HrKTJ+izUEa2qceODFLzDi3texeU9Js/o80TUEUiz+k8w07n2JvbzxIfcpQAEKUIACFKAABSigKQHNBgCzs7OVhB6t1dq5c2drL2F9CoQUOP/EHvjuySm4SKwvJrducRa8KrL+cqMABSJD4P/GDMQPz1yNSecPECP5dDDWnIKYggeVab/wNf9foc8gMgL7ji6Tu6OgFGPveQO3/ecruMWUYm5dSyAhqhsMOkPQTstkIdwoQAEKUIACFKAABSigVYHmP/VopKU5OTlYu3Ztq1uTm5vb6mt4AQVaIhBtNmG5CPo994ex+Mus85DajeuCtcSNdSigFYF4qxn/nn0B3nvkMmSL5D06XxSiDl8psnnfC31t9tFmek2wFF+rZAY+ehLKWoIvrvkWQ+avxrai5muDNq7L/c4loNfpkWwJvtZrCROBdK6Xzt5QgAIUoAAFKECBTiag2QBgfHw85Gf16tWtIh83blyr6rMyBVorcO2Z2bhyaJ/WXsb6FKCARgTOyk7F5seuwH3Xn4XoaLPICZKB6L1zRSbgX4konxXmkkugd6UGbO2ewnKM+ePreOj1LZDrhHLrGgKhpgFXOqvh9Li6BgZ7SQEKUIACFKAABSgQcQKaDQBKyccffxwys+/NN9+M3bt3h8StrKyEz9c8UUPIC1mBAhSgAAW6lIBc33PORafgm6emYsyZfUX2VpHVu0Ikcch/GOaywL9I8kTthddYBpfLgyeX5+HsB99CwWExXZhbpxdIsSQxOtdrAABAAElEQVSE7GMZRwGGNGIFClCAAhSgAAUoQIHwCBxd4Cg8zw/51GnTpmHevHno169u7bWhQ4cGvEYmDtHpdAHLWUABClCAAhRoLJAWZ8XrfxiH97fvw++f/wwHDjYuVe/7dA7Yei2Bz1CNqENTYKochR92HMIZc1fi3l+dKTIF12UOVl/Fo84ikNSCAKCcBtwjJvDo0c5iwX5QgAIUoAAFKEABCkSegKYDgIsXL1aCf5K1fmTfpk2bgiozABiUh4UUoAAFKOBHYPzgXti+eAruW70Zy9Z8A6fT06yWI/V1+MyHlfOOni/DHZcHy4Eb4bAn4r4XPsebGwrwilgnVAYVuXU+AbPBhHhzN8ipvoE2ZgIOJMPzFKAABShAAQpQgALhFtCJwJom58zK6byJiYmQI/5kQpD6EYDBwPLy8vD888+Lhdqb/+AW7DqWdbxAUVERMjMzlQcXFhYiIyOj4xvBJ1KAAhTwIyCn9E5f9jE2fru/odRj3YXa3osgMoc0nFN2PNGwiLUDTdUjlMPYblF4avq5mHZGlroejzqFwKbD32NX5d6AfZGZgq/IHguZNIQbBShAAQpQgAIU0IoAf/7WypsIbzs0GwBctmyZkgV4xYoVrRIyGAwMALZKrGMqDx48WPUgl8uFHTt2KOcYAFTR8IACFNCIwL8+34l5L32BmiMO+PQ1sHdfAXf8l35bZ6w8Q2QOvgY6b4wIEgIXj+qPF6aPgswezq3zCOyp3o+vi78J2qGcjLORFCJjcNAbsJACFKAABShAAQq0sQADgG0MGqG30+yvqCsqKjB79uxWs2ZlcdRFq9F4AQUoQAEKNBO4fmR/bBHTgkeckq4E9qwHboK18FboXM2TQbjjN6Am62G4o38Qa1YAb3+6E6fetQqf7Shudl+eiFyBUJmAZc84DThy3y9bTgEKUIACFKAABTqzgGYDgNnZ2cfkvnPnzmO6jhe1r8D27dvR+JObm9u+D+TdKUABCrSBQI94K9b/8WI88puRiLIYYaw5BTEFD8BYNbzZ3X2mcth6PwV72nL4dE4cElOJL31oDe58dQO8Xm+z+jwReQLRRgushqigDZeJQLhRgAIUoAAFKEABClBAawKaDQDKdf9WrlzZaq+tW7e2+hpeQAEKUIACFAgmcNu4Qfh60VU4qX9q3WjA/TNh2TcdEGsANt1cSetR2/dP8EQViSUpvFj2xjYMv+d1/Fxc2bQqjyNMQCYaS7EmBm11qa28IXFZ0IospAAFKEABClCAAhSgQAcKaDYAGB8fDzkKsLUjxYYNG9aBfHwUBShAAQp0FYHs1Dh8+dAk3DltOEwmg0j8cYYYDXg/DDUDmxF4ow6gts9jcCZ8JGYE+7BzdylG3r0az334Y7O6PBFZAqGmAds8DtS4bZHVKbaWAhSgAAUoQAEKUKDTC2g2ACjl58yZgw8++ADz589HVVVVyJchMwdrNKlxyLazAgUoQAEKaF9Ar9fjgcuHIPexy9EnIwF6d5JYF/APiCqeBnibJPzQu+Ho8V94YrYrHXPY3Zi79FNM+2suHC5mq9f+2/bfwhRL8zUgm9Ys5TTgpiQ8pgAFKEABClCAAhQIs4AxzM8P+Pj169dj1apVSnleXh4WLVqEhIQEZVRgoIvy8/Mhp+dwowAFKEABCrSnwGkZSdjy+FX4/X++wn/f/x668rFiJOBJsKe/AK+lsOHRxqph4rw6C/q7n+/C0N0leO3O8RjYM76hLnciQyA+qhuMOgPcvsBB3BIxDbhPt/TI6BBbSQEKUIACFKAABSjQJQQ0GwCUwbwlS5YoAb36UX3l5eXYtGlT0BfDAGBQHhZSgAIUoEAbCRgNevz9+nNw+bC+mPm3D1FWno7oPXfDkfo/uJLWiWzBybAc/DV04p+mW+G+Spz7x9VY+JtR+M25A5oW81jDAnqdHkliFOAhW2nAVjITcEAaFlCAAhSgAAUoQAEKhElAswHApKQkheSqq67CuHHjWsQjRwo+//zzLarLShSgAAUoQIG2ELhwcDq+eXIKrl/yMXK/3g3LoakiW/BJ0IkEITpv8yQh9c+UU4L/8PeP8OH2/fh/M0bBZDDUF/GrxgXkNOBgAcBK5xE4PS6YDU2mhWu8X2weBShAAQpQgAIUoEDnFdCJ0XU+LXZvy5YtGD58uMigGHiKjb92G8QPUK29xt99eK59BYqKipCZmak8pLCwEBkZGe37QN6dAhSgQAcIvPjZDsx/8QvU1jqDPs1t3QExRBDG2kFKvb6ZiVh914XonxYX9DoWakPgYG0JPtmfF7Qx5/Ychp4xqUHrsJACFKAABShAAQp0hAB//u4IZe0/Q7NJQOR6f0OGDGm1oMwezI0CFKAABSgQDoGbRg3Axicm4+QT0gI+3muoEmsFLoUt8xk4kt8SOYK92F1YrmQJfnVDfsDrWKAdgWQxArD5xG51+zgNWO3BIwpQgAIUoAAFKECB8ApoNgCYlZUFOaW3tVtZWVlrL2F9ClCAAhSgQJsJZCbF4LMHLsUtVw2B3qAOE8lgnz19GXymSjEC0Adn6luwZTwLr6EaNpsLs57OxZ2vboDX622z9vBGbS9g0hsRb+4W9MaHRSIQbhSgAAUoQAEKUIACFNCKgGYDgI2BqqqqGh+q9mW24K1bt6rO8YACFKAABSgQTgG9Xo/HJg/HivkTER9vaWiKO+5reGJ+ajiWO57Y71Hb91F4LLsgV+VY9sY2jF/0Po7YXap6PNCWQIo1MWiDyuwV8Hhbt4xJ0BuykAIUoAAFKEABClCAAschoPkA4NSpU5GYmIgJEyb47WZ2djaee+45TJs2DcEChX4v5kkKUIACFKBAOwrIBCGbFk3GqQN7KE8xVp2FqENXAT71/359pnLU9nkCzsT1YkqwD19vK8Kwu1/D9wcq2rF1vPXxCKRa65KVBbqHV7zHMocY6cmNAhSgAAUoQAEKUIACGhBQ/wSigQY1bsLNN9+MiooKZUTExo0bGxc17MupwjIAuGDBAkyZMqXhPHcoQAEKUIACWhBIi7Pik/suxozLToNBjAw0l42Hde8dIgdIkzVrdV44ui+vmyKsc+BAcTVG3/M6VuXt1kI32IYmAqmW4CMAZXVOA26CxkMKUIACFKAABShAgbAJaDYAWFlZqQT+lixZgrlz52LdunVBkeRIwJkzZ2Lx4sVB67GQAhSgAAUo0NECckrwk1efgf/MG49ucRYYbScgevd9MNSc2Kwp7rg8MRrwcXhNh5V1AX/71DrcvbL1a+I2uzFPtKmAxRiFbqbooPc8bOO6xEGBWEgBClCAAhSgAAUo0GECmg0AyoDf8OHDIUf4Pf744y3KCHzVVVdh7dq1HYbHB1GAAhSgAAVaI3DxqZnYuPAqnDQgDXpPHKyFt8NcMrHZLbyWfajp+ye4o7fD5/Xh76u3YMLCd1Hr5LqAzbDCeCIlxDTgUrEOoNfHhC5hfEV8NAUoQAEKUIACFKDALwKaDQDm5+dDjupr7cYswK0VY30KUIACFOhIgfSEaHz54KW4dsIg6HR6RJVcLgKBt4psIE1GkxlqYct8Fo6k95R1Ab/YWoTh8/+HgsNHOrK5fFYQgVDTgN0+Dyoc1UHuwCIKUIACFKAABShAAQp0jIBmA4AJCQmQQcDWbsdyTWufwfqtFxg8eDAaf8aMGdP6m/AKClCAAp1EQE4Jfu6Gkfjz7PNhNhtgrDkFMbv/CL0jXd1DnQ/OtNV16wLCg6L9lRh5z2p8+OMBdT0ehUUgNUQmYNkoTgMOy6vhQylAAQpQgAIUoAAFmghoNgAoR/+tXLmySXODH7722mvHNGow+F1ZSgEKUIACFGgfgennnYB3HpyEpKRo6F1piN5zN4zVQ5o9TOeOgw4G5fyRageueuxdPPfhj83q8UTHCkQbrbAaLUEfetheHrSchRSgAAUoQAEKUIACFOgIAc0GAMeOHQuZ+ffJJ59skUNBQYGSBGTatGktqs9KHSuwfft2NP7k5uZ2bAP4NApQgAIaFTgjKwV5Yl3Ak09Ig85rgWXfbJgPXw74dEqLDbUnIOrQZFXr3S4P5i77FLe8/CW8Xq4xp8LpwAOdTodQ04BLbOVKUrMObBYfRQEKUIACFKAABShAgWYCmg0AypbK5B9z5szB1Vdfja1btzZrvDxRVVWF+fPno3///kr5XXfd5bceT1KAAhSgAAW0KpASa8FnD1yKqTkniZF+OkSVToS16Bbo7b1EQHCmOGNs3nQf8K93vsP4Re8zOUhznQ47E2oasNPrQpWT6zZ22AvhgyhAAQpQgAIUoAAF/Ar4+YnCb72wnJw5cyY2bdqEZcuWKdOB5bqAcmpwUlKS0h653l/9mn8+nw/r168PSzv5UApQgAIUoMDxCsh1AZ//7SgMz07BPS99AYh1AQ01g0XwL/jv6r7eVoQRf/wf3pk/EX2SY4+3Gby+lQKhMgHL28lpwPFR3Vp5Z1anAAUoQAEKUIACFKBA2wkE/6mi7Z5zzHdasmSJMhJQBvjKy8uVgOC6desgP7t27VKm1WRlZSnnTz/99GN+Di+kAAUoQAEKaEFg9uiBeOu+S5GQYA0a/POaDsPW80X49HYU7qvEOSII+MmOYi10oUu1Ic4Ugyi9KWifS+0VQctZSAEKUIACFKAABShAgfYW0HwAUALMnTtXCf4tXLgQOTk5kAG/IUOGYPLkycrIwJ07dyrH7Y3F+1OAAhSgAAU6QuCc/qn4asGVyOqd6PdxPn0tbBl/hTv+S9T2XgSvsRTVVXZc+ejbWLFxt99reLJ9BOQ6gCkhsgGX2Svb5+G8KwUoQAEKUIACFKAABVoooBMj68QqQtwo0LECRUVFyMzMVB5aWFiIjIyMjm0An0YBClAgAgQcItnHVc+uxyd5expa64NHCf55Yrc3nNO5u4k1A38Hg70f9AYdHrrxHNyWM6ihnDvtK/BDeT6+Lf056EMuzxoLsyH4SMGgN2AhBShAAQpQgAIUOEYB/vx9jHCd7LKIGAHYyczZHQpQgAIUoECLBKJMBqy580LMvvx0iIFmyuYzH4bHult1vc9YLUYCPglXtzx4PT7c9/8+x90r81R1eNB+AslR8SFvXubgKMCQSKxAAQpQgAIUoAAFKNBuAgwAthstb0wBClCAAhRoG4FF00bgmf+7ACazAXpnD8Tsng+9o4f65no37OnL4Excq6yP+/fVW3D90o/h9XrV9XjU5gKJltABQK4D2ObsvCEFKEABClCAAhSgQCsEGABsBRarUoACFKAABcIlcOPIAUpykPh4K/SuNETvuRuGI02m+ep8cHRfCUfacvjgxesf/oyJiz+Ay+MJV7O7xHNNeiPizcEzMHMdwC7xrcBOUoACFKAABShAAc0KMACo2VfDhlGAAhSgAAXUAkpykMevUJKD6LzRYt2/W2EqP09dSRy5knJh77UEPp0DX2wpxKgH30KlzdmsHk+0nUCSJSHozcpEJmAuuxyUiIUUoAAFKEABClCAAu0owABgO+Ly1hSgAAUoQIG2FuiVEIOvHrkCI05Jhw4GRBX/CuZDVzR7jLvbFrEu4FPwGqrxw87DOOue/6GwrKZZPZ5oG4GkEOsAOrwu1LhtbfMw3oUCFKAABShAAQpQgAKtFGAAsJVgrE4BClCAAhQIt4BVrAW49u6LcPG5/UUQUIeosotg2f9bwGdQNc1rzUdtn4Xwmg5h34EqnHvv6/j+QIWqDg/aRiA5xAhA+RQ5CpAbBShAAQpQgAIUoAAFwiHAAGA41PlMClCAAhSgwHEK6PV6vPK70fjtpacqdzJVnQlr4R8gUgSr7uwzHxJBwMfhsRSgrLwWOQ+8ia/yD6vq8OD4BeLEGoBGnToA2/SupXZmAm5qwmMKUIACFKAABShAgY4RYACwY5z5FApQgAIUoEC7CDx17Zm4/4azodfrYKw9USQHmQedK0n1LJ/xCBwpbynnjlQ7MOmRt/H+9n2qOjw4PgG9TofEqLigN+EIwKA8LKQABShAAQpQgAIUaEcBBgDbEZe3pgAFKEABCnSEwF0TTsZfbxkNk8kAgzNdyRCst2c2PFpvz4B1//SGY7vdhWsXvo9XN+Q3nOPO8QuESgRS7qyGx+c9/gfxDhSgAAUoQAEKUIACFGilAAOArQRjdQpQgAIUoIAWBa47ux9evXsCoqPN0LsTEL13DgxHBkHnTBVTg2+DzBrceHO5PJj9bC7+lvtj49PcPw6BZEt80Ku9IvhX6agOWoeFFKAABShAAQpQgAIUaA8BBgDbQ5X3pAAFKEABCoRBYNygdLz/4KVISLCKgJ8F1qJbRCDwLug9/gNTXo8Pf3z+Uzzy5tYwtLbzPTLUCEDZ41ImAul8L549ogAFKEABClCAAhEgwABgBLwkNpECFKAABSjQUoHTMpPw6Z8uR4/u3UR+YKMYDZgY8FKfzgE5Ku2JVzbitv98FbAeC1omEG0UQVdDVNDKDAAG5WEhBShAAQpQgAIUoEA7CYQtADh+/Ph26hJvSwEKUIACFOjaAn2SYvHFo5ejb2aw4J8Ltoy/wZ7+Anxw48U13+LXSz6G18s16o7nuyfUKEAGAI9Hl9dSgAIUoAAFKEABChyrQNgCgGvXrsWePXuOtd28jgIUoAAFKECBIAIpsRZ88fBlGHxCWrNaPnhh7/kCPDE/wh23UQQC/w6fzok3PvoZk/+SyyBgM7GWn0ixJAStXOO2wea2B63DQgpQgAIUoAAFKEABCrS1QNgCgLIj8+bNa+v+8H4UoAAFKEABCvwiEGsx4ZP7L8FZp2eoTBxpK0Tgb3PDOU/sdyII+Cx8ejvWfVWAiYs/gNvDkYANQK3YSbEGHnVZf5sSrgNYT8GvFKAABShAAQpQgAIdJBDWAODKlSsxbdo0bN3Kxcc76H3zMRSgAAUo0MUETAYD3pszHhNG9mvoufHIqYBXvVadJ+Zn1GY+LYKAtfhiSyHGPvYOHCJTMLfWCSRExUGvC/7Xq1JbeetuytoUoAAFKEABClCAAhQ4ToHgf0M9zpuHujw+Ph6JiYmYPn06BgwYgMWLF6OqqirUZSynAAUoQAEKUKAVAnq9HituGYNrJwxSrjLWDhLZgW8HPNGqu3it+ajt/SS8hmps+f4Aznv4LRyxu1R1eBBcwCCCf0kiCBhs4wjAYDosowAFKEABClCAAhRoD4GwBgBXrVqF5557Dnl5efjggw9QUlKCoUOHQiYIyc3NbY/+8p5hEhg8eDAaf8aMGROmlvCxFKAABbquwHM3jMTvpwyFSA8Mgz1bBAHvgM4dqwLxWgph671YBAEr8MPOwxj14Jsor3Wq6vAguECyJfg04ApHFdxejq4MrshSClCAAhSgAAUoQIG2FAhbADAnJweNg0BZWVl4/PHHsXPnTsydO1cJDCYnJ2P+/PnYvXt3W/aZ96IABShAAQp0WYFHrxyGB288G3q9DgZHb1j33gWdK17l4Y06gNo+T8BrLEX+njKMvO91HKqyqerwILBAqEQgXpF3udxRGfgGLKEABShAAQpQgAIUoEAbC+h8Ymvje7bZ7SorK7FixQosWbIEOp0Os2bNwtSpUxEXF3xqTZs1gDdqN4GioiJkZmYq9y8sLERGhnqB+nZ7MG9MAQpQgAKKwLJPfsLcpZ/BI5J9eE2HxNTfp+Azlap0dK5EZZSg3tUd3dO6Yd0Dl6BPknrEoOoCHigCdrcDb+7+MKjGKckn4KTE7KB1WEgBClCAAhSgAAXaQoA/f7eFYuTfI2wjAFtCJ9cInDFjhjJFWAYC5ejAvn37KolDOEW4JYKsQwEKUIACFPAvMOO8E/G3W0fDaDJA70pD9B4xEtCZpqrsM5UrIwE95v0oPlSNC+5/EwWHj6jq8KC5gMUYhViTen3FprVKmQm4KQmPKUABClCAAhSgAAXaUUDTAcDG/a6fIlxWVoaZM2cqU4Rl4hBOEW6sxH0KUIACFKBAywWuPTMbL90xDmazCAK6k0UQcA709nTVDXzGKrEm4JPwRBWhtLQGox94AzsPMWGXCsnPQbIlwc/Zo6dkJmANT8I42lDuUYACFKAABShAAQp0CoGICQA21h47dqwyNVgmD8nOzsa4ceMwYsQIvPDCC42rcZ8CFKAABShAgRACk07PxPK7J8BiNUHviRdTfu+C3tZHdZXPWA17+lKxcp0XZeW1GCsSg/x0kGvYqZCaHIRaB9DhdeGIq7bJVTykAAUoQAEKUIACFKBA+whEZACwnqKgoACbNm3Crl27sHnzZmVkoMFgwOrVq+ur8CsFKEABClCAAiEExp6Ujtf/eDFiYszQeWMRXXg79LX9jl7liYFl/wyRPLjurw3l5TbkPPgWvj9QcbQO91QCoTIBy8ol9nLVNTygAAUoQAEKUIACFKBAewlEXACwqqoKixcvhpz+O2zYMCxbtkxJECKn0cjPVVddhaFDh7aXF+9LAQpQgAIU6JQC5/RPxXsPXCoSbVlEEDAa0UW3wVA7APCI/b23i4zBdYmb6jtfWWnDhSII+O0+BrHqTRp/jTfHwqQ3Nj7VbL/MzlGUzVB4ggIUoAAFKEABClCgXQQiJgAoR/WNHz8eiYmJmDdvHvLz85WAnwz6yfUBFy5ciPLycmVqsEwUwo0CFKAABShAgdYJnJaZhPUPTUJSYrQIAlpgLbxVrAs4VwT/evu9UVWVHRMeegvbCsv8lnflkzqdDklR8UEJyhwMAAYFYiEFKEABClCAAhSgQJsJaDoAuHXrVtx8881ITk7GlClTsG7duoagn8wQLJOByCnAMjvwnDlzIM9xowAFKEABClDg2AVO7BGPjx+5DCnJMdD5LDA41UlBmt65utqBix5eg817SpoWdfnjpBCJQCoc1XB7PV3eiQAUoAAFKEABClCAAu0vELYAoJzC629rOsV36dKlysi++im+OTk5WLlyJWQ24Oeeew5DhgzxdxueowAFKEABClDgGAX6JMfiw4cnITUlNugdnIlr4bHsxpEjDlz8yNvYUMAgYGOwZEvwX0yKxUtQ4WBG5cZm3KcABShAAQpQgAIUaB+BsAUAZeKO6urqhl4Fm+IrM/3WT/H94IMPlHX+Gi7kDgUoQAEKUIACbS7QJykWnzwyCd3Tuvm9tyPpXTi6r0Rt5tNKELCmxonL/vQ2tuzldOB6sFBTgGW9Uk4DrufiVwpQgAIUoAAFKECBdhQIWwBQ9mnGjBkBp/jKEX+c4tuOb563pgAFKEABCoQQ6JUQg4/FmoA9u6uDgI6k9+BM+1/d1YbauiBg1B7IIOAlj65hYpBfXC3GKMQYrUGVy+zMpBwUiIUUoAAFKEABClCAAm0iENYAoJzKG2iKr9fr5RTfNnnFvAkFKEABClDg2AXSE6Lx6cOXIb1nnHITH7zwxPygvqEMAvYWIwGjisTofgcmPrIGPx1kgguJlBRiGjAzAau/lXhEAQpQgAIUoAAFKNA+AmENAMouyZF+nOLbPi+Xd6UABShAAQq0hUBanBWfPnQZMtLjoYMe1qL/g+HIIPWtDTWwZT4Fj/kAKivtuPDht5B/mOvbhUoEUuO2we52qC15RAEKUIACFKAABShAgTYWCGsAcOjQoVi7di2z+LbxS+XtKEABClCAAm0tkNrNgs/EdODeGQkiO7AZ1n2/g6FmoOoxPmO1CAL+GV5TsUjgZcPYB9dgT9kRVZ2udpAcFTwRiPQo4zqAXe3bgv2lAAUoQAEKUIACHS4Q1gCgnAI8duzYDu80H0gBClCAAhSgQOsFkmItykjArN6JdUFAORKwdoDqRj5TpZgOLIOAJSgtqxFBwLewv6JWVacrHSRExYlRk7qgXS61c7p0UCAWUoACFKAABShAAQoct0BYA4B9+/Y97g7wBhSgAAUoQAEKdJxAYrQZHz0wCZm95EjAKDEd+FbobdmqBvhM5SIxyJPwGktx6PARjH7wTRyqsqnqdJUDo96AhCh1EpWmfWcikKYiPKYABShAAQpQgAIUaGuBsAUAlyxZ0tZ94f0oQAEKUIACFOgAARkE/PjBS5XEIDqvBdGFvxdBwD6qJ/vMpXUjAY0VOFBcjQseegslR+yqOl3lICnENGA5Bdgr1kTmRgEKUIACFKAABShAgfYSCFsAcMaMGa3q09atW/H8889j9erVquvWr18PWcaNAhSgAAUoQIGOE0gR04HlSMDuad2g80aLIOAfoLdnqBrgMx+uWxPQUIWi/ZUYLYKAlTanqk5XOAiVCdjldaPCwYQpXeF7gX2kAAUoQAEKUIAC4RIIWwCwpR3Ozc3FgAEDMGzYMMyaNQsLFixQXSozCD/22GOYNm2a6jwPKEABClCAAhRoX4Ee8VZ89NClSEmJEUHAGFgLb4feka56qDfq4C9BwGrsKapQRgIesbtUdTr7QbIlIWQXi22lIeuwAgUoQAEKUIACFKAABY5VQNMBQDm6LycnB7t27cKQIUMgRw0mJSWp+pqVlYUVK1YoZQwCqmh4QAEKUIACFGh3gV4JMfjwwUlISoyG3tMN1r23Q+fornqu17IfnugflHO79pRh9CNrUOvsOkHAbiYRHDVEqUyaHhTXMgDY1ITHFKAABShAAQpQgAJtJ6DpAOCUKVMwefJklJeXIy8vD8899xwSEvz/Fl0GCuVHThPmRgEKUIACFKBAxwn0SY7FOrEmYEKCVQQB48V04Dugc6bWNcCng2X/TTBVn9HQoJ/ySzD2T+/A4fI0nOvMOzqdDt2jk4N2scReDre3a3gEhWAhBShAAQpQgAIUoEC7CGg2AChH/w0fPlwZ3RcfH9+izssRgitXrmxRXVaiAAUoQAEKUKDtBPqnxeG9+y9BXJwFencioveKIKAYCWjZNxumqrObPWj7z4eQs+AduDxdI+jVPTqlmUHjE16fF6UiCMiNAhSgAAUoQAEKUIAC7SGg2QBgfn4+5s2b1x595j0pQAEKUIACFGgHgUE9E/D2fRcjNjZKBAGTEVPwAExHhgR80rYfDmLCwvfg9ngD1uksBWlW9RIm/vrFacD+VHiOAhSgAAUoQAEKUKAtBDQbAKyoqEBycvDpMv4AZOCQGwUoQAEKUIAC4RE4LSMJb947EdExZuhgDNmIjd/uxyVPfgCvt3MHAa1GC+LMsUE9mAgkKA8LKUABClCAAhSgAAWOQ0CzAUCZ3Veu+9eaTU4bDrRGYGvuw7oUoAAFKEABChy7wPA+KVh990RYrKaAN3Fbd8CR+hp84p8vthTi8mfWd/ogYHdr8F9sljuq4PA4A5qxgAIUoAAFKEABClCAAscqoNkAoEzoIacAV1dXq/rm8/lUx/UHlZWVmD17NpgJuF6EXylAAQpQgALhEzinfyqWz5uAKEvzUYDumO2wZT4NZ/L7cKa8rjTyow27cfXfPwpfgzvgyaESgcgmHLaVdUBL+AgKUIACFKAABShAga4moNkAoEz8ITMA9+3bF9u2bWt4LzKTXtMtNzdXSRhSVlaGu+66q2kxjylAAQpQgAIUCIPA6BN74D93jYfZbGh4uqvbJtgy/groXco5Z8q7cCS9p+y/9/kuzHzx84a6nW0nVawDqBP/BNu4DmAwHZZRgAIUoAAFKEABChyrQPNfyx/rndrhuiVLlmDdunUYOnQo+vXrhyFDhmDz5s2YP38+5BqBcr0/OU1Y7suRgbKMGwUoQAEKUIAC2hG4cHA6XrxjHG58ci1cLpnxV47kV6/350xbDZ3XAnPFBXj1g++RLJKILJgyXDudaKOWmPRGJFviUWKvCHhHrgMYkIYFFKAABShAAQpQgALHIaDpAKDslwzqzZ07F8uWLcOuXbuUri5atKihyzLwJ9f9k+v/nX766Q3nuUMBClCAAhSggDYELj0tE8v+MBbTn1oHVA+H76Adjp7/UjXO0f0VJQhoqjoLf1u9BUkiCDjnolNUdTrDQZpYBzBYAPCIqxY14hNjiu4M3WUfKEABClCAAhSgAAU0IqCpKcBVVVXYunUrdu/e3cAjpwLLkYBypN+VV14JeSyDfvKrHBG4cOFCyKm/cp9bYAG5nmLjwKm/mrJ83LhxmDVrlvJ16dKl/qrxHAUoQAEKUKDVAlcO7YO/3zoaBqMe5spRiCqeor6Hzgd7z5fgit2qnH/031/j+U9+VtfpBEfdo1NC9qKY6wCGNGIFClCAAhSgAAUoQIHWCYRtBOD48eOVwJ2cxiun8Mqsv/WfKVOmKGv/Ne6KnAa8cuXKxqe43wIBabtgwQIl+CeDpYE2GfSTgdS1a9c2VJHvQY66DHZdQ2XuUIACFKAABUIIXH1GNuyzPfjDPz6GuXwcfHo7nKlvHb1K54U9fSl0hbfBaDsRc5Z9isQYM64a1vdonQjfk1OAjToD3D45Hdr/Vlxbguy4DP+FPEsBClCAAhSgAAUoQIFjEAhbAFAGmmRCjzlz5ihr+skRfdzaVkAG8GQAUI7qC7bJadZytF/9FOv6unLadWJiojIiUAZnuVGAAhSgAAWOV+DGkQNgd3owb9lnMJdeAp/BBleSmBpcv+ndIknI3xC9dw7gyMSsZ3ORcPcEjD0pvb5GRH/V6/SQyUAO1B4O2I9DYgSgnO3gL/FZwItYQAEKUIACFKAABShAgSACYZ0CLLP8Pv7448p03iBtZNExCsgRkzLQOnPmzKB3WL58uVLeNMgn11aUm5yCzY0CFKAABSjQVgKzRw/EvGtHKBlxow5NgalilPrWBjtsmc/AazoEpwgWXvvEB8jbU6KuE8FH3aOTg7be4XGi0lkdtA4LKUABClCAAhSgAAUo0BqBsAYA5bTTrrKtWrVKGYknR+XJEXnyq1ayFstMy02Df/XvRZ6X5dwoQAEKUIACbSnwx0tOw4zLTqsLAh78FYzV6rV8fcYq1GY+Da+hAjabC5c99i5+OljZlk0I2726i0Qgobbi2tJQVVhOAQpQgAIUoAAFKECBFguENQAYKOjU4tb7qTh//nw/Z9v+lJxaWz/FNtTdZQIO+ZEj8upH5cl2jh07FjIwGO5NrsNYP9qvaVvkedlXbhSgAAUoQIG2Fnjy6jNw1diBIghogGX/dBhqT1A9wmcuESMBnxVrBdaiusqOCY+8jf0Vtao6kXgQZ46FxWAO2vRiGwOAQYFYSAEKUIACFKAABSjQKoGwBQDlujZ9+/ZtVWNbUjlUptuW3CNYHRksk8/IyspSgncycUawTY6ek/Vl4K9xkE0mNZFBwJYGEYM943jLQgX4ZJ+5UYACFKAABdpD4IXfjMSYM/tC5zPBWvQ76O2Zqsd4LUVwJn6onCstq8G4R9egyuZU1Ym0A/l3oLQQowAP28rh8XkjrWtsLwUoQAEKUIACFKCARgXCFgBsLw+5aHZ7bDKIJxNiyJF8rRkVJ6c5y/oy4Nd0q1+bb8aMGU2LeEwBClCAAhToEgJ6vR6rbh2L4SenQ+eNhlVkANY5Uxv6biofLZKFXNRwXLivEuMWvAuXJ3AW3YbKGt4JtQ6gR2QJLrVzBL6GXyGbRgEKUIACFKAABSJKoNMFANsrY97cuXNRXl6ujOSTgbvGo/kCvXE5ck5+pk6d6reKvIecBh1oGrAcmdeaj9+HtMHJlvS1DR7DW1CAAhSgQBcVMBr0eHfuBAzsnwq9Jw7RhX+Azh0H8+FJiCq+WkwRVv915Ycdh3Dp4g/g9UbuCDmuA9hFv9nZbQpQgAIUoAAFKBAmAWOYngs5Uu/DDz/EsGHD2qwJWstWW588I1gATQYAZZBQ1s3JyWmwOJYkIbt27Wq4vjU7cnRioGnA8nx7rNXYmvaxLgUoQAEKdH6BKJMB6/44ESPvfwN7ioCY/IfEiMCYgB3/YmsRblj2KV6edX7AOlouiDZZ0c0Ug2pXTcBmHqoVmY+TBwQsZwEFKEABClCAAhSgAAVaKhC2AKBsYOOAV0sbHEn11q5dG7K59cFBmRG4sYdcM7CjtuHDh2Pp0qV+HyeDk3L0IzcKUIACFKBAewvEWc3Ivf9SnHPv6yg+FPppb3z0M+YmRGPRtBGhK2uwhpwGXF0ZOABY5qiE0+OC2WDSYOvZJApQgAIUoAAFKECBSBJQz6np4JbLUYBt/engLgR9nAyeyS05OTlgvaSkJKXsWEfvBbxxKwrkOoVyq29v/aX1x9OmTas/xa8UoAAFKECBdhVI7WbB+/dORHy8JeBzvIYKuGK3KOXPvb4VT773XcC6Wi4INQ1Yrmp82BY82ZiW+8e2UYACFKAABShAAQpoRyCsIwDl1FM5+qwtNpmNV46iKygoaIvbtck96qfV1o/ya5ObHsdNSktL/V4t38PkyZOVBCeNRx7KwKBc79BfAhO/N2p0sqhIzN8Ksh04cCBIKYsoQAEKUKArC2SnxuGN+RfhoofWwGZzqSi8pkOozXwKPlM5dPtuhvHIaXjk5a/QPd6K687up6qr9YNUa5JY3xAIlr5MBgB7xXbXelfYPgpQgAIUoAAFKEABjQuENQCYm5uLuLi4NiOSI9YGDNDOWjkyKNnSrTV1W3pPmbFYBkXz8vKUS2QmY7nWoFzTb9myZapEJjLwJ8vl2oNyVKJsz7hx4455+m9mZmZLm8l6FKAABShAgWYCQ/uk4OU7L8Q1C9+Dy1WX8dcTtRe2zGfgM1Yr9W3pSxG9907Ano3b/vEx0uKsuHBwerN7afWEnNqbGBUPOdU30HbYXh6oiOcpQAEKUIACFKAABSjQYoGwBQBltt62DP7JHkdysor60YItfnMtqLhw4cIW1DpahWv9HbXgHgUoQAEKhF9ABvP+8rsL8Lu/5IqMvz64u21pCP4prdO7YMv4C6L33C2ChN1x/Z/XIvfRyzCoZ0L4G9/CFshRgMECgBWOKri8bpj0YfsrWwt7wmoUoAAFKEABClCAAloWCOsagFqGaYu21a/v15J7aWWacEva2pI6hYWFCPbZsGFDS27DOhSgAAUo0MUFrj0rG/f9+ixFwVwyCcbKs1UiPmONmBL8DLyGStTWOjFpwbsoF18jZUu1JgZtqpweXGqvCFqHhRSgAAUoQAEKUIACFAglELZfJ8vkH1VVVW0+ClDeVytba4J6rQkWaqV/wdqRkZERrJhlFKAABShAgRYL3DnhZBRX2iATflgO/Bo2QxU8sdsbrveZS8TUYDEScO9dOHQYmLjwXXwqsgkbDdr/PWeKJXgAUHZSrgPYIzqlob/coQAFKEABClCAAhSgQGsFwvo34/oss61tdLD6Xq83WHFYyoJN761f+681wcKwdIIPpQAFKEABCoRRYNG0EbjsghNE0gwjrPtmQW/ro2qN1yLWB0x/TiTUcGP7z4fw6yUfq8q1eiDXAYw3dwvavBIb1wEMCsRCClCAAhSgAAUoQIGQAmENAG7atClkAyO5Qn2G40DZd2Xf6oODI0aMiOSusu0UoAAFKECBdhf454xzcc6QTOh8FliLboXOqR4V54n9HvaeL4sgoA9vf7oTD7+5pd3b1BYPCDUNuFQkCfH4tPcLzrboO+9BAQpQgAIUoAAFKNAxAmENAMokFdXVdZn8Oqa7HfuUYcOGKQ+sD/L5e3r9KMicnBx/xZ3m3ODBg9H4M2bMmE7TN3aEAhSgAAU6RkCv1+OtO8dhYP9U6D1xiC68DTp3rOrh7vgv4Ux5XTn35+WbsHxDgapciwepIaYBe0Xwr8weOFOwFvvENlGAAhSgAAUoQAEKaEsgrAHAnTt3om/fvpg/fz5yc3Oxe/dubekcZ2umTp2q3CEvLy/gnWQAUGYv5hTggEQsoAAFKEABCjQImAwGvDdvAlJTYqEXmX+tRbcAXlNDudxxprwLV9yXSubgW/7xEfL2lKjKtXaQEiIRiGyvXAeQGwUoQAEKUIACFKAABY5VIGxJQNauXatMf5UBMDlFdsWKFZDr4RUUFGDWrFmYPn36sfZJM9fJoN7kyZOxatUqpa9Ng3zr1q1T2jpv3jzNtLm9GrJ9+9HF2uUzioqKkJmZ2V6P430pQAEKUKATCyTFWvDm3RMw5v43YKvNVtYEtGX8DWJucEOv7T1eht7ZHQ57Nq5a+D6+XnAlesRbG8q1tGM1WhBrisYRV23AZpXYuQ5gQBwWUIACFKAABShAAQqEFNCJrLlH/7YcsjorSAEZtOzXr5+CIQOZwabvyum/WVlZkKMBlyxZogKsnyLc2ddCVHX6l4PGAcDCwkIwa7A/JZ6jAAUoQIFgAm9tK8T1T3wAj8cLZ/wncPT8t6q6zi2mCe++B3p3Ivr1TcZXD1+GKJNBVUcrBxuLv0VB9b6AzTHqDLg8eyz0urBO3gjYPhZQgAIUoAAFKKBdAf78rd1305Et6/C/RcqpvlVVVR3ZR9WzjvX5crSeDPrpdLqG4J+88bhx4xrOLVq0SPUseSBH/ckAn7xejmzcvHmzsi+vS0pKwvr165tdwxMUoAAFKEABCoQWuPS0TNxz3ZlKRXPleTCVqdeX1bkSG26ya3cpblz2ScOx1nZCTQN2+zwotVdordlsDwUoQAEKUIACFKBAhAh0+AhAg1i7RwbETj/99LAQHc/z5Wi+ptN46zsRrKy+jgwCygCgvIfMEDx06ND6oi73lb+B6HKvnB2mAAUo0G4Cv33+U6xc/6PI/euBLfNZeGJ+gLFqOCwHbhCzgqManit+h4dV916McYPSG85pZUdO/31nT/AA5cDEbJyafIJWmsx2UIACFKAABSgQIQL8+TtCXlQ7N7PD1wAM94zj43l+oOCffEfByurfoZwqHGy6cH09fqUABShAAQpQoOUCy34zErsOVmLz9gNiPcCZcMV/DVP5aOjEP403uejJrcs+xXeLp8Bo6PBJEI2b0mxfrgEYah3Ag7UlDAA2k+MJClCAAhSgAAUoQIGWCHR4AFA2qry8PCzTgGXwT07h5UYBClCAAhSgQOcR0Ov1ePPOC3HGPf/D/gOAuVw9FbhxT/cfrMK9qzfj8SnDG5/WxH6P6BTsrNwbsC0VjirY3A5YjUdHNQaszAIKUIACFKAABShAAQo0EghLADBco+COZ/RfIzPuHoPA4MGDVVe5XC7VMQ8oQAEKUIACxyMQZzXjnfkXYdQ9r+NItSPorZat+QbTzz8B/dPigtbr6MKe0alBA4CyPcViFGDfuF4d3TQ+jwIUoAAFKEABClAgwgU6PAC4a9eusJPJrLzcKEABClCAAhToXALZqXF44dYxuHrBu5DTfZtuPrFKoM90CC5nd0xf+gk+uveSplXCepxqTVKy/Hp93oDtOFB7mAHAgDosoAAFKEABClCAAhQIJNDhAUAG3wK9is59fvv27aoONl6EVFXAAwpQgAIUoMBxCFx0SgbGnpmFdV8VqO7iNZbC3uNleKz5iCl4SKwXCLz0+Q7cOHKAql44D4x6A1ItiSi2lQZsRnFtKbwiuqnnkiYBjVhAAQpQgAIUoAAFKNBcQFsrYDdvH89QgAIUoAAFKECBVgks/e0oxMSYG65xJnyMmqwH4Yn9HjDYlUCgHA1438tfocrmbKinhZ0eMalBm+H0ulDuqAxah4UUoAAFKEABClCAAhRoKsAAYFMRHlOAAhSgAAUoENECKbEW3D1tREMf5Kg/GI6uC+iJ/Q7ubptQWWnHLS9/2VBPCzs9RSKQUNuBmsOhqrCcAhSgAAUoQAEKUIACKgEGAFUcPKAABShAAQpQoDMI3DZuEE7sVxdMsxRPhc6tTvjhSFsJn86BNz/egS92aieg1s0Ug2ijJegrOCgSgXCjAAUoQAEKUIACFKBAawQYAGyNFutSgAIUoAAFKBAxAs/PPh9Gox46bwyiiq9RtdtnKocz+T14vT7MXvr/2TsPwLiqM22/U9V7t+UqF8C424BNt40hlBAwxkB6wcBms9ksxECym/InwWDIsimbQEw2bZMsYBsIIQluYKrBHdxt2bIlW733afq/70ojaaTRaNRH0nuSwy3n3HvPee54NPe9X9khy64Tb/gcOMAbJontly7ZgAMVdQF2uJ2BurCNBEiABEiABEiABEiABHwIUAD0wcENEiABEiABEiCBkUJgdmYi7rruQmM61up5sNRe4DM1R+Lr8FjLkJNbjl+/c8KnbSg3unMD1gTHRfVlQzlEXpsESIAESIAESIAESGCYEaAAOMxu2HAd7owZM9C+LlmyZLhOheMmARIgARIYRgSevvtSJCdFwST/Cyu8C2hq99PH7IIj+a/GbJ7YsBcud2hYAaZEJBrjDYQ5UKbgQMexjQRIgARIgARIgARIYHQSaPcreHQC4KxJgARIgARIgARGLoEwmwVPfelyY4IWxxjYKq7ymawz7l247fkoKq7Bf22RLMEhUOwWGxLD4wKOpJBxAAPyYSMJkAAJkAAJkAAJkIAvAQqAvjy4NUAEDh06hPZ1+/btA3QlnpYESIAESIAEfAncPm8CLp83zthpL7kZ8NjbOpiaxArwFWP7p6/sR6PT3dY2hGtpEUkBr17jrEOtsz5gHzaSAAmQAAmQAAmQAAmQgJcABUAvCS5JgARIgARIgARGLIFffOEKIyGI2R0Le9lSn3m6YvfCHZ6Diop6/PDVAz5tQ7WRFhlYANRx0Q14qO4Or0sCJEACJEACJEACw48ABcDhd884YhIgARIgARIggR4SmJQSjRsvzzKOspddD7gjfc7QmPKSsf3c3w+ipmHoM+wmhsfDarL4jLHjRlFdacdd3CYBEiABEiABEiABEiABvwQoAPrFwp0kQAIkQAIkQAIjjcBTkhDEHmaFyRMJe+kNPtNzRx2BK+IYamsa8e+b9vi0DcWGxWSGJgMJVNQCsKlJcwKzkAAJkAAJkAAJkAAJkEBgAhQAA/NhKwmQAAmQAAmQwAghkB4XgTuunWbMxl5+LUxO30QbjpSX0ST/+9OWoyipaRjyWad24wbc6Hag0lE95OPkAEiABEiABEiABEiABEKfAAXA0L9HHCEJkAAJkAAJkEA/EVi7ciEiIm0wNYWJFeBNbWdtssDcKIlCTC40iAvww8/vamsborXuEoHosArpBjxEd4eXJQESIAESIAESIIHhRYAC4PC6XxwtCZAACZAACZBAHwgkRNrxueUXGWewVVwBkyMF1orFiDr1A4QX3iPCoM1oe/mtE8gtq+3Dlfp+aJw9GmGWdhmL/ZyyoK7Ez17uIgESIAESIAESIAESIAFfAiEtAG7fvt13tB22li9fjuuvv96ojz76KHJycjr04CYJkAAJkAAJkAAJ+BL4/m1zERMbDhOsiDr9XUQUfAFmZ7JPJ6fDjW/8cafPvsHeMJlM6M4KsLi+DE6Pa7CHxuuRAAmQAAmQAAmQAAkMMwLWUB7vddddB7fb3eUQN2/e3Nq2b98+rF69GuvWrcOcOXNa93MlNAjMmDHDZyBO59BnWPQZEDdIgARIgARGDYFIuw333zQTT/55l1j8dW1ht3Xnaey7tQxzxwdOxjGQ4NIkDuDZmvwuL+GRmIXqBpwZndZlHzaQAAmQAAmQAAmQAAmQQEhbAPYks93cuXOhguDDDz/Mu0oCJEACJEACJEACAQk8IgJgYmJkwD4eTxP+5TfvBuwz0I3pkb6Wif6ud762yN9u7iMBEiABEiABEiABEiCBVgIhLQCq60tPS1lZWU8PYf9BIHDo0CG0r925dw/CkHgJEiABEiCBUUzAZrHgG+IK3F05cLQAL+870123AWuPsIYjMcw3W3HHi+XXFaMnL007Hs9tEiABEiABEiABEiCBkU8gpAXAnuLfuHEjKioqenoY+5MACZAACZAACYxCAl9bcgHGZMR2mnmTqRGNiX+HM/Z9o+3RP+yEx+Pp1G+wdmREpQS8VKPbgbLGyoB92EgCJEACJEACJEACJDC6CQx5DMD7778fgSz9HnjggW7vkFr97d27F6dOncITTzzRbX92IAESIAESIAESIAGz2YzHPnMZvvBkc0zhJpMTzvi34Ej6G5qs1TA542Gtno9z+VV4evNhPHjDxUMCbUxUKg6VnQx4bXUDTgqPD9iHjSRAAiRAAiRAAiRAAqOXwJALgPfddx9UwFPx7sUXX8TWrVtbBUF1Z3n22WeDvjvLli3DQw89FHR/diQBEiABEiABEhjdBG6fNwE/np6Gj48Vwh1xCo1pz7cCabJViCC4A/by6/D0S/vwwJLp0AQig13i7TGIFFfgOldDl5dWAXBm0rQu29lAAiRAAiRAAiRAAiQwugkMuQCoyTu0LF26FPfee6/hwqtLdedVy0Bd765kZWVBxT/vubrrz3YSIAESIAESIAES8BL42RcXY8m3Xoa1bjostRfAHXXU22RYA9oqr0BVFfDwC7vxs88sam0brBX9PZQRmYLsqtwuL1npqEGtsx5Rtogu+7CBBEiABEiABEiABEhg9BIwiZVdUyhOf+XKldi0aRPcbncoDo9j6iOBvLw8jBs3zjhLbm4uMjMz+3hGHk4CJEACJEACvSew4idbsWXnabjDT6Fu4uM+J7IX34Kw0ltgt1uw7+lVGJcY5dM+GBv5tcV4O39PwEvNTb4QU+MnBOzDRhIgARIgARIggdFHgM/fo++e+5txyCYB0Vh+IapN+uPIfSRAAiRAAiRAAsOYwE8/vwj2MCssDZMl7t9sn5k4ErfAY6mGw+HG1//QnBjEp8MgbKRGJMJqsgS8kroBs5AACZAACZAACZAACZCAPwIhKwBOnjy5R/H//E2O+0iABEiABEiABEggGAJj46Pw6esuNLraS24Fmkxth1ka4Eh83dje/mEOjhUMfsZdi9mCtMiktjH5WSuuL0ONs85PC3eRAAmQAAmQAAmQAAmMdgIhKwDqjfEX/69KgvDs378fOTk5o/3ecf4kQAIkQAIkQAL9SGDtyvmIjQ2HpTET1qpLfM7sTHgDHms5PJ4mfHfjXp+2wdrIkGzAgYoHTXjr/G40uB2BurGNBEiABEiABEiABEhgFBIIaQGw/f147rnnMHXqVCQkJGD+/PnQxB8WiwU33HADDhw40L4r10OQwIwZM9C+LlmyJARHySGRAAmQAAmMZgKa4ffBFfMMBGElt4gVYLufSWanJAR5zWjb8uFpFFd3nZF3oBiOkUQg3RW1AHzn/B64PIyh3B0rtpMACZAACZAACZDAaCLQ7pdtaE5bLf4WLlyI++67D9nZ2UZcQI0N6K2bN2/GvHnz8K1vfSs0J8BRkQAJkAAJkAAJDBsCX192ITLHxMHsTIWt4kqfcTvj3xUrwDI4JRbg91/e59M2GBvh1jAkhcd3e6myxkrsLNgPT5On277sQAIkQAIkQAIkQAIkMDoIWEN9mirunTp1CnfccQeuu+46JCYmIj4+HhUVFSgrKzNEwRdffBGaNCQpKQkPPvhgqE9pVI7v0KFDPvNun4XIp4EbJEACJEACJDCEBMxmMx761Fz86y/ehL30Jjjj3oOogc0jMrklFuBmhBfdhY07juPJVZcgQjIDD2a5KCGr22zAOp7zdcXYW3wE81MugsnULp7hYA6W1yIBEiABEiABEiABEggZAiEtAD7wwAPQZCB79uxBXFxcl9Aef/xxrFu3DmvWrDGEwgkTJnTZlw0kQAIkQAIkQAIkEIjAFy7Pwg9f2IWSEsBWeQU0/p+3OOPfFmHwRtTWxuKpf3yM//jkHG/ToCzTI5MxPjoDZ2vyu73eqapc1IpL8MVJU4OyHOz2hOxAAiRAAiRAAiRAAiQwbAmErAtwZWUltmzZAnXxDST+ecmr+PfQQw9BxUAWEiABEiABEiABEugtAbUC/PLyGcbh9tLlnWIBOhO3GG3/s/mwJAUZXDdbteZbmDYTKRGJQU2vsL4U2/J24m2JC1jWMPjZi4MaJDuRAAmQAAmQAAmQAAkMOIGQFQC3bt1qxP3rCQGNA6jHsZAACZAACZAACZBAXwj82/UXIyo6DGZXklgBLvY5lSP+TckPUovS0lr8+p0TPm2DsWExmXF5+lzE2aODvly+uARvzXsf7+TvRXljrlqQWwAAQABJREFUVdDHsSMJkAAJkAAJkAAJkMDIIBCyAqDG/dNsvz0paikYjLVgT87JviRAAiRAAiRAAqOPgMb2W3n1NGPi9tIbxAqwOY6euX4CwvO/DHgijLaf/fXjIYFjt9hwZcZ8RFjCenT987VF2JL7niEEFtaVGEnVenQCdiYBEiABEiABEiABEhiWBEJWAPQm+ugpVXUdZiEBEiABEiABEiCBvhL4zqfmwC5CoGYEthd/ChFnv47IM9+CrWYOTGj+CZWTW46/fZzX10v16vhIWwSuHLMANnPPQzqrELjj/G784+w7OF6RA4e7JdFJr0bCg0iABEiABEiABEiABEKdQMgKgJr8Y9euXT3id/r0aVoA9ogYO5MACZAACZAACXRFIDk6HMsvnWQ0h5V9Ata6GSL8dc6ou3bTvq5OMeD748NiDHdgs59xBXPxamct9pccxas5b2J30UFUNFYHcxj7kAAJkAAJkAAJkAAJDDMCpiYpoTrmxMRE7Nu3D8Fm9V21ahUWLlxoJAMJ1TlxXM0E8vLyMG7cOGMjNzcXmZmZREMCJEACJEACIUfgZFEVFnzjBUn2EeDnkmiCb669DfMmJA/Z+PNri/FB4UdwePpuyZcUFocYiS8YJm7GYRY77FJ1GWZu3g63hvXK6nDI4PDCJEACJEACJDDKCfD5e5R/AFqm33OfkUHkphl9582bhw0bNuDaa6/t8so5OTlGwpDdu3dj/fr1XfZjAwmQAAmQAAmQAAn0hMCU1FhcNmss3tsfwM1XtMHvbNiDvz54fU9O3a99M6JSsHz85ThcdhKnq86hSf7X21LaWAmtgYq6HUdYwxEpVZcai1BdkiNlGSYCoV3abSIYaj/NXMxCAiRAAiRAAiRAAiQwtARCWgBcvXo1tmzZgmXLlkFdglUMVKtAb3zAsrIyaLKQvXv3GhQ3b96M2NjYoSXKq5MACZAACZAACYwoAt9ZsQA3BBIAZbbv7MvFqeIqTE4Zut8hKsYtSL0YFyRMxpHyU8jpoxAY6CY6PS44HTWoktpdURHQ3iIG2sSq0LtuiISy7W3XxCZtwmIEzBQOu0PLdhIgARIgARIgARIImkBIC4A6ixdffNGw7lPLvuzs7E5vkdWDWQVB7bd06dKgJ86OJEACJEACJEACJBAMgcVTUnDh1FQcOVHU2l0t7NwRx+FI2gJ72RKJD3gR/n3DXvzpgWta+wzVSrQtEgtFCLxQhEC1CDxTfb4P9oB9n4UhFopg2JOiMQ2j7VGIsUmVZWzLUrdVKGQhARIgARIgARIgARLoGYGQjgHYfiqa4ENdgrdt22ZY/WmbWgRq3D+1FIyLi2vfneshToAxCEL8BnF4JEACJEACPgQ27T2DLzy52djnijqIxuRX4Ik4Y2xbai5CZN6/GhmDj/73PdDkIaFUqh21OCRCYG5N/pAKgf3FxGqytMQmbLYmbI5T2LauLsmxIhqqEGo2hWy+u/7CwfOQAAmQAAmQQLcE+PzdLaJR0SHkLQC9d2HSpEl49tlnvZtcDjMCM2bM8Bmx09n3IOU+J+QGCZAACZAACQwggdvnTcB/jI1D7rlKeKxlreKfXtIdfRjusDw4GjPxvZf24eefXTSAI+n5qdWC7rL02ZjlnIbsKnFVrspDo9vR8xOFyBGuJjdcrnrUSg1U1IrQsB6UhCax3ioWhBqrUEVExiYMRI9tJEACJEACJEACI43AsBEARxp4zocESIAESIAESGB4EfjaTbOw5ldvw1Z1GRwpr6DJWt06AUfiFkTkfxEbdxzHulULEGkPPTdVFb5mJk3DRYlTcK6mACcrz6KkoaJ1DiNtxSP2jpUSo1Brx6LiYHPMQbEcbIlL6F2qBWGcCIZxYTFGchMKhR3pcZsESIAESMBLwNPkgcPtRLgkwGIhgVAnQAEw1O/QCBnfoUOHfGbS3gTZp4EbJEACJEACJBCiBFZfPQ1PSJy/0jLAVn6NiICvto7UFfshPMW3obY2Hk/87SC+/6m5rW2htmIRt9jxMWOMWtFYZQiBZ6rz4RbLutFSVBxsECtIrQjglKAJS9R6UMVAQxS0xyBKhFRNYGKhFeFo+bhwniRAAiTgQ0BFv6L6MuTJy7RzNYVICI/DVWMW+PThBgmEIoFhIwDm5OQYLsBbt25FRUWFkfhDMwPff//9uPbaa0ORLcdEAiRAAiRAAiQwggiYzWZ86fqL8OSfd8FWIQJg0j8Ac4t6ZHLDGb8DYSW34rebD+M/bpkNqyX048/Fh8UamYNnJU3H+doilDVWGu7B6iLcKBYNunRIVcFsNBaHxylWkuVG7Th/tSLUrMbeLMbGUrYjLGFGAhNv4pJw2aYVYUd63CYBEiCB4UXAraJfXanE0y0w/l7q3wdv0f1qBcgkVV4iXIYqgWEhAD766KNYt25dK0PN/Ktl79692LBhA+bPn29kAZ4wYUJrH66QAAmQAAmQAAmQQH8TeOiGmfjFqx+hVrxK1RXYGf926yWc8W/BXnojysvr8Mybx/DPSy9sbQv1FX1omRg7FhMxttNQ9XeXxt1TMbDB1Yh6dyPqXA2od9ajTtbrZV23G6SOJplQRdFmoTRwPEWNN6ixCL0ZjVUgtJothgVh29Laui9M7gWTl3T6GHIHCZAACQw6AbfHjYL6UsPST1+SaVZ7f0X/Hmi7/h1lIYFQJhDyAuD1118Ptfrzin5q9ae1rKzMyAas1oC7d+82RMA9e/aAImAof9w4NhIgARIgARIY3gQi7Bbcec00/OavH4sb8LU+AqDGBHTFiHVg1WI884+Dw0oADHRX1HrNZrIalm6aWberoi5RKojpA5JaQhhLsZDotN1FW9MIlQ9VPC0XV2utwRSTWBYqZ63NwqEsJXlJtIiIKh7SmjAYiuxDAiRAAr0j4FLRr65YRL9CQ9TT7/BgiroDUwAMhhT7DCWBkBYAn3rqKWzZsgXz5s2DWgGuWLGiE6vTp09jzZo12LhxI6677jocP368Ux/uIAESIAESIAESIIH+IvDdW+fgT1uOoLExE5baC+COOtp6akfiNlirFuFsXgXeOFaAa6ent7aN9BW1WtMEGhG9mKjXylAtDKudtah2SG23NGL19eK8w/EQFUKNucv88+UhtH3RuIMREmhe3Y21WluWzdvN7shqQahux+EWO8Kkry5pUdieItdJgARIwJeAvqgqqC1Gbm0h8mXZm5i4BXUlxgsv/T5mIYFQJRDSn04V9u677z788pe/7JLfpEmTDPdfdQdesGABfv3rX+PLX/5yl/3ZQAIkQAIkQAIkQAJ9IZAYHY4bFk3GK28eFyvAJT4CoCc8F+6IbFjrp+CpVw+MKgGwL0xbrQztVsPqDVG+Z1OLQhXFasXtWOMuNccmdHZaV3dkjdM0Uos+lNY463o8PU1m4hUEI0WkNSwKW6wM1dKQcat6jJQHkAAJDHMCKvqp265a+qnFX1//dnjdgCdIki0WEghVAiErAKpF37JlywKKf+2hqpXgCy+8gPXr11MAbA+G6yRAAiRAAiRAAv1O4Id3zMerb5+AtWYWTI5kNNlLWq/hTBArQBEA3z+Qh6KqeqTG9sYmrvV0XBECKlAlWeKRFB4fkIdaEta66lHlqJFa27LU9RojjmHAg0dwo4qmRsB6EVH9lTCxEvS6HatYqBaDmi1al83VZGyrBaL2VUtPFRLV0oUuyf6Ich8JkEAoEtCXSc2iX4GIfiX9nuBKxUQKgKF45zkmL4GQFQBPnTplZPj1DjSY5R133IFHHnkkmK7sQwIkQAIkQAIkQAK9JjAhKRoLZozBhx+dg11iATamvdh6LlfMPnisZXC5ErH2rx/h6XsubW3jysASUDHKK2SNaWdFqMKgWgeqOKgPgIYg5l0aMQubYxdqMhN1Px6p8Qi7ou9NZlLaUNFVF7/7NcGJ4fbdIgg2r4cZsQrDW9yP1R3ZIklPWEiABEhgKAjUS2gJDaegMfo0W+9AZrWvkZcs+veGL0aG4k7zmsEQCFkBMD4+8BverianCUJYSIAESIAESIAESGCgCfzbzbNwlwiAtsrL0ZjyCmBuyQZr8sCZ8CbCim/HpndO4Md3LYTZbB7o4fD8AQjow1ikLcKoAboZTeoGpiJgpaMalY1SxXpQ11UcZPEloMHxvfEKfVt8t9RS0IhLKKKgioZtFoamVitDr8WhYWGoMQxFVNR4h3qcZktmIQESIIFgCOjLnuL6chTVl8myzPiOCua43vbRkAqZ0ekYF52GOHsMxb/eguRxg0IgZAVAjeenLr233357v4HIycnBxIkT++18PBEJkAAJkAAJkMDoJXDjzExkpMcivwAiAi4S0W9HKwxH/Nuwl9yM8nLgf98/hc9dPqW1jSuhTUCFqPiwGKMipm2sGi/KG4PQKdaDRnZjda1tWXfKulqaqCBGsbCNm64pK63KpjdFBUTDutAQBtssDDvuo6Vhb+jyGBIY3gT0+1aFPm+t7kWc1J4SiLNHG6JfZlQaYmWdFn89Jcj+Q0UgZAXAuXPnYu3atT3ismnTJiMTcFcHzZ8/H6WlpV01cz8JkAAJkAAJkAAJ9IjAZ66djif/vMtIBtIqALqjYK+4EjC5IMEB8YvXD1EA7BHV0OysIpQKg8EUl0eTdTRnM65qWar4pZYp2qaWcyzBEzAERI3riJqAB+k9UutCk/xPi/Ffsf5s3tJtkxFPUq0MjSrxDlvXvftalnouPtQHxM1GEhgSAl7Bz2vh15vESL0ZeLxY96mlX6ZY+qnox0ICw5FAyAqACvPRRx/FqlWr8Pzzz3fLdv/+/Ua/QH3L9TU8CwmQAAmQAAmQAAn0E4FvLJ+Bn760D40NGSICXgtzQyZsVZfA1BTWeoUjJ4tw6Fw5ZoxNaN3HlZFNQF1W48NijepvphojSl2NNauvVxB0izCosfhUKNQHWnVDpjWhP3pd71OhsLuicSCDKSoj2n1EwTaxUMVBFQ51qUlTNEmNLm2ybJMbO19FhUiKip25cA8JdEVAvyv1e7CsobLZwq+hvFeZ0Ls6f3f7E+R73BD9xNIvxt4usGx3B7KdBEKUQMgKgNu2bcPWrVuRnZ2NqVOnGhmBu2KoCUO0ryYBeeCBBzp1Kysrw969e/kHtxMZ7iABEiABEiABEugLgehwG5YumIi/vXMS4YV3+z2VPL/gR385gD89cI3fdu4cfQRUBNJYeFZoVl3f+WcgxWeHCoS1KgjKQ7BavnjdaVuXrS7IrpbkJg5JYsLSVwKaKKDB3WjUvp6r/fFe8TDcR1zUWIfNVonablQRE73r+lmhcNieItdHIgGPvBTR7O0VjVUob6m6PtgW04lhca2WfppUioUERhKBkBUAVdR74oknjD92qvyrENhd2bBhg5F1p6t+/MPZFRnuJwESIAESIAES6C2BR2+djb+9e1Lcfbs+w7ZdOaj7shORdlvXndhCAn4IqDVhnLgeaw2meOR3s0MsCRukNhoClqxLbELdrhPrN7Uu1BqMtVww12OfnhHwCrc9cVtUy0Fri7Wh12XZm2VZt40EKy0CYqDnHbVO1M+TTawVNdZloL49mxV7k0DwBNT6uabFwlktnb1hEjTZkrYNRUkOjzdEv7Fi6RclCaNYSGCkEghZATAxMdFgvnTpUmhm395mBfbeuD179mD79u3eTS5JgARIgARIgARIoF8IzM5MxAVZKTh6srjL89XXO/HzbUex5hMzu+zDBhLoDwJmsS40xCHJoIv2WUzanVxfrjskaYnX1dgrCmqMQrXCcYuarUtv1YdyXVdrxKZASne7a3C1/wjouwWvcBisC3N3V1cx0GthqK7LreteC0Rj2Xl/oPOqoKhipGZv1liMLKOXgH7HqAWtN5RB87JOLPxqjBcRAd6XDRq0lPCEZtFPYvpFStZxFhIYDQRCVgBUwU//iGzevLnf7oPF0sHHot/OzBORAAmQAAmQAAmMZgL3SyzAfz35ZkAEv99OATAgIDYOGgH9je21JEsSy5dgi1oXqlWhZjtWa0J1SVbR0LvU/frQP1RWPMHOg/3UYLlZBFYhGEHGRQyWm1oshougoqJKc40wlpq1WQXqvhR1h9ZszxZdisioFo3GuiyN9C99PH9fxjZajtV4pQ6Jt6mZz71Z0PVzpFnSNVSBV/QLNStj/XwkRySK6JcGtfRToZqFBEYbgZAVANXqb9KkSf16P/RNBMvQEJgxY4bPhZ1O+bHBQgIkQAIkQAIjhMDnFmfhu3/cicrKBp8ZeSxVcMa9B3vZMpzNq8COYwW4enq6Tx9ukMBwIaDijYo4WhMR53fY+ntbH/yN+Hktrse6ruKguiZrbD2vRaFhbdjO0tAlx2m/wY755Xci3NlrAvrEpcKw1tJen6XnB6pVY0dR0BAMRShU0bBNPJRtERDbi4dW7SP7+lJUWDeu3yJSeq+n7tvedW0f7KL/3jQMgP778vk3J/8W22+rha8h6qm4J7FFVdQzLE+N9RbBr+Ucgz2H3lxPrVCTJJ5fioh+qVIT5WWH3nMWEhjNBEJWAFTx7+RJiafTj8XjGZqYAv04BZ6KBEiABEiABEggBAlYLWZ8cvEU/OHvB43RuSOy4Yh/A67YPZL20w2zMxG26kvw1GsfUQAMwfvHIfUfARVBjKy44lYaa4/u1YkNAVEEi3oRDlW4MMQk77qxVHGJQmGv4I7gg9SqUcVjl9sdsrNUIbD534ckffFmkNb4jZpFWoRC/ffT26ICniG8a/xP+fehcT91O9Qs8Xo7v+6OU3FVLZpV8NOq4p8KvywkQAJtBEJWAGwbItdGAoFDhw75TCMvLw/jxo3z2ccNEiABEiABEhjOBB65eRb+uPkQPG5xk0zZBHfkidbpOBPeMATA9/bnoaymAYnRjDfUCocrJNCBgBGPzm6VCIZRHVp8N32FwgZxT3aKBNTs8WP8t8X7x7tHLaHUZbFRBZIOVS0TWUhgoAkYAqXLbbjND/S1Rvr5mwW/BBH7Elot/IbCwnKkc+b8RhYBCoAj635yNiRAAiRAAiRAAkNEYFxiFOZflIFdH5+HrfwaHwHQHZkNd1gu0DgOT4qV4NqVC4ZolLwsCYwcAsEKhd3N2Ou2rC6PXmGwOYuyr1Co4qH2aY57pmIjCwmQwGARUOvJ9hZ+ieFi4TcELtWDNV9ehwQGggAFwIGgynOSAAmQAAmQAAmMSgL/cuNMfFYEQGv1XJhcsWiyVrVycCa8CUvBZ/H8W8fxoxXzYDYPfiyo1sFwhQRIoJVAe7flaFtk6/5AK+1FQ68wqDHWAhW1QPQKjN5le6FxtLhqBmLENhJQAnZxiU4Ii0W8VF1q1X+bfXGRJlkSIAGAAiA/BSRAAiRAAiRAAiTQTwRumZWJ1JRoFBXXwFZxFRzJf209szP2A4QVrUBJCfDy/lzcPm9CaxtXSIAEhheB9qIhbP0zdk3IoCJgx6rColdkNATDdvHdVEikcNg//HmWwSegiVdi7FGIEXEvxhbVKvhp9miKfYN/P3jFkU+AAuDIv8ecIQmQAAmQAAmQwCARUKu+VVdPw8827G0WAJP+JklAWpKQmeVBXTMCly/Dz8QNmALgIN0UXoYEhgkBzVoapgkhpPakuI3kD90LgSowqpjYUWDUzK8++8TVuf02szL35G6wrz8CKuipwNcs9kVJgiAV/aKMjOIU+vwR4z4SGBgCFAAHhivPSgIkQAIkQAIkMEoJPHj9DDzzlwNwOuINV2AjE3ALC4e4AdvKl2Df4XycKavBhMTeZUkdpWg5bRIgAT8ENNNplDnCT0v/7PJIMhUVDrsTArVPnauhuTrrW9a9ywaoAMkycgloTE510/UKfbEtgl+0LK3MxjtybzxnNqwIUAAcVreLgyUBEiABEiABEgh1Aprh94o54/DGhzlGMpD2AmCTvUiSgxyBqW4G1r56AM98/vJQnw7HRwIkMMoJmE0m2C022IPwdY61+3+poTETNQZiX4pmeFZrR3eTW8RIT9t6yz49v8u7Lkujj/TVY1S8bD5WjtPjvf3aHdNXgVKFUm8W6r7McyiONcFkJNSw6X0WIc8mMfhU0NP7bixbtr3tGqNP171tVumrnxMWEiCB0CZAATC07w9HRwIkQAIkQAIkMAwJfPPmWYYAaKmfBnPjGHjCzrfOQpOBWEUA/Mu72fjZZy6ThyhLaxtXSIAESGAkElA3T83i2teiglMoFxUh2wuOKjwaYmOL63VjSxZph8Ru7Liux/WlKGN1Hw+3hLUsZd0aJtvN++yy1Ky56mruXep6c6V41xf2PJYEhguB0P4GHS4UOU4SIAESIAESIAESaEfgiqlpmJAZjzN5FYYVYGP6n1pbXdEfwWMtRU11Ep558xi+tvSi1jaukAAJkAAJDF8CKqxZLOagrCWH7yw5chIggeFKwDxcB85xkwAJkAAJkAAJkEAoE/j80guN4dmqLgPc4W1DNTXBmbDD2F7/+uG2/VwjARIgARIgARIgARIggQEiQAFwgMDytCRAAiRAAiRAAqObwFeXXIjIKLskAQ6HrWqRDwxn3DtoMjmRk1uOHccKfNq4QQIkQAIkQAIkQAIkQAL9TWBYCIBVVVVdznvbtm3Yv39/l+1sIAESIAESIAESIIGhIBBht+CmRZONS9vKr/EZQpO1Bq6Y3ca+x//C3zE+cLhBAiRAAiRAAiRAAiTQ7wRCXgC88847kZCQgBtuuMHv5CdPnoxnnnkGq1atQiCh0O/B3EkCJEACJEACJEACA0jg3z85F2azZFd0ZMBSe4HPldzhZ4ztnR+dw/mKOp82bpAACZAACZAACZAACZBAfxIIaQHwgQceQEVFBTRt/K5du/zOe9KkSYYAuHbtWqxcudJvH+4kARIgARIgARIggaEgMCklGvNnZBiXVitAkysKttLrEHnq+wgvusvY73Z58KO/HBiK4fGaJEACJEACJEACJEACo4RAyAqAlZWVhvD37LPPYs2aNdi6dWvAW6KWgKtXr8ZTTz0VsB8bSYAESIAESIAESGAwCTx4y2zjctaa2YjKXofw4pWGRWD7Mbz8zgk43e72u7hOAiRAAiRAAiRAAiRAAv1GIGQFQBX8FixYALXwe/zxxzF37txuJ71ixQps2bKl237sQAIkQAIkQAIkQAKDReDGmZkYmxELcQSGqcnm97LV1Y149s3jftu4kwRIgARIgARIgARIgAT6SiBkBcBTp05Brfp6WsrKynp6CPuTAAmQAAmQAAmQwIAS+PzSC7s9//rNh7rtww4kQAIkQAIkQAIkQAIk0BsCISsAxsfHQ0XAnpbeHNPTa7A/CZAACZAACZAACfSEwNevm4HISHvAQ06fLceOYwUB+7CRBEiABEiABEiABEiABHpDwNqbgwbjGLX+W7duHb7yla8EfbmNGzf2ymow6AuwIwmQQCcCDbX1qDqZg+pTZ1B15hyqzhWiuqgMddW1kvGyBtaaathcTljRBJupCdabb4LtnrsRbrMgLTYMKdFhsFpC9l1Ep/lyBwmQAAn0hkCE3YKbFk3Gi9uOdjq8CR7A5BD34HA8IclArv5meqc+3EECJEACJEACJEACJEACfSEQsgLg0qVLjay+P/7xj/Hggw92O8fTp08bSUAeffTRbvuyAwmMdgLuqmoU7z+EspNnmkU6pwP2yAhYoyU7ZWy01BjYJk+EJy0dtY0u1EhtXRaVouYPf0ZNWSWqK2vQWFMPydjTNVJTFNA+5JUzEsgube1vNpmQEhOG9LgwpJ0/g/RxqUicMgEm2c9CAiRAAiOJwLdvnY2NbxyDx9P8nemxVMIZ9x6c8W/Ly5LZkhV4FXZ+fA6V9Q7ERQS2FhxJXDgXEiABEiABEiABEiCBgScQsgKgTl2Tf9x///3YtWsXHnnkEcyZM6cTkaqqKqxdu9awFlS34YceeqhTH+4ggdFOoL6iCvlvvIf89/fi3JFTKCqtgdNsCYzlmmuAq6/u3KehAfjoROf9we6JifHp6RHxsLCqwaj49UYgLw/2lCSMuWASJlwhiYCuWoCEmAifY7hBAiRAAsORwOSUWMy7KAO7D56HM/Z9NGT8Tiz/xPpPijPufYQV3w4xmMYvtx/FIzfNGo5T5JhJgARIgARIgARIgARClEBIC4CrV6/Gnj17sH79erz44otQgU9dgxMTEw2cGu/PG/OvSUSEbdu2hShmDosE+pmAWtzV1gKlYkkXHQ1HXALqHGKl53CjrsVir07Wq//n9yg8fAJlZdVAi8WJMZLuxD/tFBbmf9Dh4YBdLFMcDv/t3e0V60K/pa4OOJdnNDmKS5Gj9e3d2PHTSMRnTcDEeRdh4tLFyByfChtdhv0i5E4SIIHQJ/DgLbNwtwiAlvqsVvHPGLWlDq6YvbBVXYoN72VTAAz9W8kRkgAJkAAJkAAJkMCwIhDSAqCSfPbZZ5GVlWVYAJaXlxuCoNc1UEU/LSoKqkDoz0LQ6MD/kMAwI+AWse78mXycPXAcRbJ0FhShqagQ7pJSuKtr4Kmtg9vtgcdsRuP1n4Djqmv8z/DIGaCkyn9bd3u7EgAhrrnxcUBRsc8ZouXbJDY2CjFJcYhNS0JUegqaxNrPFRkNp8UKp4zX5XDCNX0KnBGRqKhzoLTW0eY9nJ0trsQ+p2zekLlWfHQE+7X+biOs8gJgXFocxmYkICw5CfakeNgiwmG/+irYrWZDHNTvBtU7jWX2KXg+/lhYWdCUlARPUjJiJmUiITmebsZ+cHMXCZDAwBK4adY4pKZEG1+hltoL4Y460npBZ/xbhgB44nQpThfXYJL0YyEBEiABEiABEiABEiCB/iAQ8gKgTnLNmjW477778Ktf/QpbtmwxrP681oCrVq3CihUr+oMFz0ECQ0dAXNkr3tmJM3sOIyf7HPKKquCoqul6PDaJo+eNq9co/mJdFXsXVnzaX2LsJUTZYRYLQqfNBqfTLa5nLlm6gMbGVgtAjdEXFWZBdJhVltbm5RUXI6q+FjETMxE7eQKip2eJMJfQ1Si63N/ocqOoqtFw/83fX4VCSxOq3QFi/4mo5yotw2mth0+3nVfiFyJ6ctt2+7Wdu4HXX2+/R+YOhMfFIj0tHulZmciYcxHSF81DeIIImywkQAIkMMAEblg4Eb//20HYKq70EQDdkSfgtufD4sjAz7cexo/vvmSAR8LTkwAJkAAJkAAJkAAJjBYCJrGQ8WdzM1rmz3kOEoEZM2b4XMnpdOLEieY4crm5ucjMzPRpH+kb+s+ust6J/MoG5OeX4cz9/4oKuyTL6E1ZMB+46Wb/R/7+98DpZqHM1uRBWmocxlyUhYzF85Fx5SWIkIQfHYuOzenW6lGNEBGSrddrdduxb79vuyThyDvv4/w/3kDOroPIqRG3ZlsQ8f+iRBB96Jv+h/Phh8Df/+6/rf1emWxiXATSMtMQL0lIYsamIWZCJmJmX4yYcCszFbdnxXUSIIE+ETheWIkF33hBrJTlO27Kw2iySpiGlmIru06SgaxERnosjj29yrubSxIgARIgARIgARLoNYE8ibM+btw44/jR+Pzda3Aj7MBhYQE4wphzOqOQQENNHYpKqpHvsaJAEl6o8FcvMfpaS+Ykcaktat3s0UpjWyw+dYGNtFsQZW+21oucMQ7x05IxZuEsJF9+CSwxnQW/jtdSsc9u1Wru2DTw21axMLzmSkzTKldrkjifxa++jpy3diHndD7ORyaIl7A/C0F/+1qGqypmMEWEz7KKOqkimB5ssS6MjQW+8Q3jaOUaE24z+FotJlh3fQjbG9ubMydHR8ImbK1iTWmPixFLwliEpaciLCMd4eIKHWa3iWuyafCE1GDmyz4kQAJDRmCahDHIGp+I7DNlsFUuhiOpzUpZswKHFX8K+QVV2HmqGJdNThmycfLCJEACJEACJEACJEACI4fAsBUANfuvugRrhmCNAbh8+XJce+21I+fOjLCZHDp0yGdG7d9A+DSMkA21ois+eBzZW95BtsTxKzlbiKZFiyAfUv8znDDBrwCY2lCF8VFmxIiIZBErSfP4cbCkpxnutmaJhWdJSoBFRKeoCLvhnttJtJt1n//rDZO9Jvm3nfr1B4x6SX09GvYdwJkPP8aZk3moqawx3KSd9Q1wRIfDIZaKarWo8RO1qO6n7svmqAiYkhNhltSa5upqeMS9ucEawDW6PZvwtn6aVEVrazktMRBzJAkLtAYoEqdRE7VYoqMQER2BxPhopIxJRsrKW5GcGINEccO2mIMUKQNchk0kQALDi8Dti7PwpAqAFVf4CICw1MIVvQ+26kvw31sO47L7rh5eE+NoSYAESIAESIAESIAEQpJAyAqAmtH3zjvvbIXmTfQxceJE7Nu3D8uWLUNFRYUR5F/bnnjiCSNRyGOPPdZ6DFdIYDAJeCSe3bk330P2ZhH9Ps5GVXW97+WzTwYWAPfuRWRqEiaMScCECyZi/MKZiBL3U0h8PhYhEBGB8MWXYbrWAEA8IgCq+Nfqtrx0KvD121uPaJLsydUHDqJg7yHkHz2NgjMFKCqXB25/loVhkvG4q9LQ0FWL736PB5AXFm6pGtVR61mrBZh1hQyyzBD/kqLtSI4OQ2pMGMaYHEh21cMyUURhnQgLCZDAiCTwwJIL8J8v7gGcaaL5TZdYgMda5+mMf8cQAN/YexYe+Q4x64sEFhIgARIgARIgARIgARLoA4GQFQCXLl2K+fPnQ5N9qLg3adKk1mnee++90IzAKgJq9t+4uDhDDFTBcPv27ViyZElrX66QwEAScNbV4+w/3kT29p04dfQM6hsCJOQ4fx6oqwUi22L9qVtpelw4xnxiESbccy1SUuLahKuBHPgIPre5G2s6U1QUYhdfalR1M9bilkzDxR/sQ/7egyg7mo3qojJUV9ehWlx+G5u7dP5vsAJg5yOBBEmY0iLuqcWiJkLRelj77t8P20sbkWpyYsyEdKTPnIYxixcg8tIFkrkkgCDp7zrcRwIkELIEksVyeda0NOw7nN+SDKRNAHRHHYXHViTvDlLx8v5c3D5PXgiwkAAJkAAJkAAJkAAJkEAfCISsAKhzUsu+Z555xmd6GzduxF6xlFLrng0bNiBWY3RJUaFQ+z766KMUAH2IcaPfCYgllyaVaHr5Zfw+14MqBPfPyCJWHKkl55F+xUJkSLKJ9NhwxEZYKfj1+w3q+QktkkQkfcnlRvU5Wly5G1we1DS6UN2g1YlG2VZXY9elF8KVKNmTa8R6sLYerro6OOoa0NjgQGO9uBnL0mHu4rMh7ttdlsICOOW4c/K5One2UswFdwGv7UK8sw4ZY5KQcfE0I4lL8tWLYI6U5CcsJEACw5bAp6+aagiA1pq58iZCXg6J+6+3OOPeRVjJbfj19qMUAL1QuCQBEiABEiABEiABEug1gS6eTnt9vn47cNOmTVi5cmWn823ZssXYt3r16lbxz9tJBUN1C2YhgQEj8NJLwF13AQ6H4TCaOfUyHE6d3OXlYm0mTJkyBpMvn4uMTyyFNS21y75sCEEC8qIhXGILalUXXZ+S1UXmZW8nyWjsKSyE41w+GvLy0VhQiKr8YhSfK0Lx1EwUS2ZhFRU7Fennr1TYIlFRXI8jbxwApNoe+7VkdY5HxoWTkX7JbKRfeSmi4mMoKPuDx30kEKIEPr94Cv79d++jQSJG2CovgzNxW+tInfHvwl7ySez86BxKahrkO4gWwK1wuEICJEACJEACJEACJNBjAiErAGZnZ/sVAHfv3m084Kp7MAsJDDqBuWKlIeKft0wpze0kAKaIZV/WnOnIuvFqpCxaAJNF4r2xjD4CktHYPHYswrVe0jz9NFlIRMLW0uB0o7i6EcU1UmVZINmhy6rE6i+I4mwyIa+wUuo+4E2pP/49LFdeicjrlyE6zIpIqdFhLRmh62tg+vVzaCwuhUNrabm4NpvgiIiS8GPpSL54OmZ+7jbETRofxJXZhQRIoL8IhMnLhcWzxmL7BzlGMpD2AmCTtUqSgXwMU80crHvtY6xbtbC/LsvzkAAJkAAJkAAJkAAJjEICISsAqktvR2u+ysrKVvdfjf/HQgKDTkCS0GDOHCNOm157fEUB7G4nUtMTkbXwYmR9chniLr5g0IfFCw5PAmpZOC4x0qjeGdS/+F/IP3QCBR8ewPnD2SjMFSvCEsk03Jzc2Nut81IzIIuo1+yq3MGyUGNPfniq5Rj52g9LaV6X/CTIr8Tp/A+xf8tOLLogA3N/8E2YMzI6n597SIAEBoTAvZIMRAVAi2MszPWT4Ynw/luV/CCaDEQEwBd2HMfjK+czGciA3AGelARIgARIgARIgARGB4GQFQAXLFgAtfabo2JLS9m6dauxpuLgRBViOpTTp0/7JAvp0MxNEugfArfdBhw6BAk2CZus33vTzbBnju2fc/Mso55AhFjuTZ53oVEVhmY1LjlfjPx3diF/z0HkZ+eKK7CEOpD4hJ2KJhfxVyIkVqBmEdWMxF0UJ8x462ghjt7+T1h29w1I++d7m4/poj93kwAJ9A+BT1w8Fqkp0SgqrjGsABtbBEBL7QWGW7Bepay8Dn/84DQ+uyirfy7Ks5AACZAACZAACZAACYw6AqYmKaE664ULF2LXLgmA31KmTJkCFfnWrFmDtWvXencbS7UO1CzAmhXYmxjEpwM3QopAXl4exo0bZ4wpNzcXmZmZITW+gIMpK5NA7eLWK9mnWdoI6FdJZZ0DBfKgWlAhGXTrHdAMt+2rillam/eJxZoc421v3i/7WtpNcup4ibuXKHGvkmLCZRmGJHGv1m11bx3Npa6kHPlvvoeCXR8h/+gpFJZUw2GSz+QXvyhmqeP9o3n6P4Gqav9tHfaaxNxwdnIYFq/7FsKmtXda7tCRmyRAAv1C4Dsv7cV/vbAHTaYGOJL+IcLfYpidvjFjL5qaip3/79Z+uR5PQgIkQAIkQAIkMLoIDOvn79F1qwZ0tiH9FH3vvfciKSkJ6u6r1n/l5eVIEAsXzfTrLVWSkfVXv/qVIQhqEhDNDsxCAgNKIFAG1wG98NCcXIW9iloV9mpF2KtHviwLReDLF6GvUGq+rBuin6xrTLvBKBF2S5swGCMioSEQtgiFsq2CodYxCeJemxKD6HDbYAxr0K4RmZyArDtuMqpe1CPfgzVvvYu6ObNQY49ErWQtrnVIbXS3rmPexbA7HQhLSoA9OQlhEWEIq69F9e79OHzkrPgaOlvH3ySuxPtLHMj+4rdxze3XYso37qM1YCsdrpBA/xN46IaL8ctXDqCxMVwy/37K7wUOnyzCgbwyzM4MkEXc75HcSQIkQAIkQAIkQAIkQAJASFsA6g3asGEDHn/8cSMe4Lx587B+/XoxvGq2vHrkkUcM8a/9jVSrwddff739Lq6HIAG+gQi9m1IuiSj2ny7BvlPF+OhMKc6Vtgl9jYMk7A0UFbUeHC9C4HhxsxuXHN28Lstxyc374qM6ZPgdqIGE6HnPi1vxtqd+i5KPj3YeYZgdWf/xEGbMmIAUEVdjxPqSL1o6Y+IeEugrgVU/346/v5sd8DQ3XTkFf/6nawP2YSMJkAAJkAAJkAAJdCTA5++OREbndsgLgKPztoz8WfMLaGjvcU2DEwdaxL492SL6nS7GqYKqoR3UEF49NsJmiII+4qCIhVnpcZg+Nh5268jP5Kyu13s3bcXO/9kIV3tX4VtuAeTli7eE2cxIEUE1BQ4k11Yg9YLJSEyOg9UiMQZZSIAEek3gQG4Zrnx4Y8CEP2HhVmT/4tOIjbD3+jo8kARIgARIgARIYPQR4PP36Lvn/mYc0i7A/gbMfSRAAj0j0CCuoGrRt+9Us3Xf3uxiHDtf4TeHRM/OPHJ6V9U7cfBsmVE7zspqMWH6mATMGJ+ImRMSW5ZJSI2LGFGWcBazCQvvuA5Tr5qP7T/6Jc7sOQxkTRbxb64PkkanB3nl9cj7+GNg0yajzRYdhbEJERg/dRzGXzITyVctgik21uc4bpAACQQmMHtcIi7MSsGRk8VddmxscOG/thzCdz7p+++yywPYQAIkQAIkQAIkQAIkQAItBEacBaBFkjO43YMTh4yfot4T4BuI3rPr7sjsgkq8dei8Ifip2HdYYka53CGb66e76YRse7IkJJk5PskQBC8WYfBiWVdrwTDb8LcW1LiPx17djh2eONRFdSHk7dgBvPmm3/sT5WrEeHW1vngKxl+1ENFXXwFERfnty50kQAJtBH777gn8y8/fbNsha5I6Ce4oEeRlaa2dhbTUGJz4yV0+fbhBAiRAAiRAAiRAAoEI8Pk7EJ3R0zaiBEDNBKxJQjwez+i5g8N0pvwC6t8bl1tSg03vZ2PDe9k4kFPavyfn2YImoNaC08bEG2LgxWoxODEJC6akIi5yeLrraVKXvWfLDYu/EokRqdZ/reWll4CPPmrdDLSS4KhFRnoCxsychowrFiLp6sUwRUYGOoRtJDAqCejvl0n//CdJelYPj6UCzvi3pb6LJlsZzI0ZiDz9PUnRY8KfH70BN80aNyoZcdIkQAIkQAIkQAI9J8Dn754zG4lHDJkL8P79+43MvcuXL8eXv/xlH7b79u2DJvjoadm9e/eIcsnr6fzZf3QRKJLsuy99cBobRfjbeaxwdE0+RGerlpaHc8uN+sK7zYPUxOQXSdbOS6el4tLp6bJMwySx4BkOiTTCxZpxcVayMRG1CqwS98Pi6kaoGFhcmY/ihhpUhkd3ezfK7VEoL3Pg8I6DgFT7T/4PGT/6HjLiIzAmPhzpcZL5dBTEWewWFDuMegJmsxl3XDUN6yUjsCesEI6UV1uZeMLy4Y7IhrV+Cn7694MUAFvJcIUESIAESIAESIAESCAYAkNmAZiYmAi12NOSnZ2NiRMnGuv6HxUA58+fbzwg60NnT4o+VNMFuCfEhqYv30D0jrtm6v3rrhzD0m+HuPl6evjvo3dX7ftRZvl3qTHm2ld90G2/7V337ne5PSirboDG5xtpReMHqhB4mdRLpM6ZlDw8XYdra9Fw7ARyPzqOMx+fxJkzhagqLgPk3gUsMy4C7ljZ2kU/H6mxYRgrguDY2lKMnZiB8ITmbO+tnbhCAqOEQLF8703/6p/gdLpQO/k/0GQvap25tWIxIgq+AKvVjKP/fY/8u4lobeMKCZAACZAACZAACXRFgM/fXZEZXfuHzAJQBb5t27YZIl978U/xx8fHG3dh7ty5uO+++4K+I2oB+NxzzwXdnx1JYDgQqJWMvX/bc0Ys/U5hy/5cOLsTVwZhUiny0JkuSR/SE6KQLqJN8zISGQmRst5ck2PCYZOHVBV3+mLt5nC5ocKnioGlYn1WVqPLBtlubF56t6WPd39FbeMgUOj9JYoq6/GqCLlatWjcwLmTkw1BUIVBrcnD4cFe4vqFz5uDqVplHvrCprK0Emd2fIAzuw8h99R5OPLFOrVjWIaJk4x5e/+jQnZBZYNR9/zuDzCdyUFyQjTGTsrAmNkXIGXRAsRPmwwzMw17kXE5ggmkyHfn4tlj8dbus7BVXAFHanOyHZ2yK3YXmoruhMsViafECnDdqoUjmASnRgIkQAIkQAIkQAIk0J8EhswCUCexceNGzJs3D5Mm+T4MaptaAe3duxdz5szRzaBKRUUFkpKSaAEYFK2h7cQ3EIH5N0rsta0HcvGixPT7x96zqGt0BT6gH1tFr5Ost/GYLVZp41NiDFFPhb20+GaBLzUu0hD2+vGS/X4qtR5UkU1jI54prkZucQ3OllTjbMtStzW+XSiXrPRYQwi8+uKxWDJzrME/lMfrb2weTxOKC8uQ//aHyN9zEOdP5qKqSCwE/+mfgORm12Kf4zxyTx5/HBDLp47FFhWJ5LEpSJk2ESlzLkLK/FlIToyGjaJgR1TcHgEEth05j9v+32sSB7AStVMeBkxtVrVhBXfBXrFE/glF4aQkA9HfSywkQAIkQAIkQAIkEIgAn78D0Rk9bUMqAAbCvGDBAmzfvh2xsV1koOziYHUtLiuTB0yWkCbALyD/t+fYuXL87LWP8YrE9qusc/jv1M97J4vQNHdSCuZLrLe5k1MwSxJXxEQMz6QVwaJRS7ViEQjPikB4VgVCQyiskWWzSKjbNWJ5GUplpmQaXjIzE0tnZxqWguH2ITPg7hOWmqJSFDTZcV4s/vLlHhRWNYrHcEuoh/PngfXrgzu/xAw0jRmDtHFpGD8jC+MXzcWYrEzDrTy4E7AXCYQ2gQu+8TzOF1Shfuwv4YrZ1zpYc2OaJAP5vqQCMeMPD1+PW+eMb23jCgmQAAmQAAmQAAn4I8Dnb39URt++kBUAR9+tGF0z5heQ7/1WMeqxDXvw2+1H28QQ3y79spWZFIV5WSmG4KdLjT2XEB3WL+ceSSdRgTC/vA4Hz5bh4JnS1uWJ/MoBvT/BMoywW3DFRWMMy8BlIghq5uG+uFkHe92B6Kcu7er+mydZT/P+8QYK/rwJLpE2elPsK1cg8+pLMT4x0qiJUfZhy6U38+cxI4vAd1/eh6ef3w1X5FHUj/9Pn8lF5H4d1toZuGTWWGx99EafNm6QAAmQAAmQAAmQQEcCfP7uSGR0bo84AbCqqqrHVoOj89YP7az5BdTMv8Hhwi//cRBPvbwf1f2c7CI63IbLL0zHPLHqU8u+eRJjLlXceFl6T0Dv19FzFTgkwuDHIgx6l2USf3Aoy9jEKCwRIWDprEyoy3CSxBAbrsVVU4PCd3fj3K6PcP5oDorOFaPW2eb+GHBeX/2qj2txTLgVWanRmJYWgzGOaphSUwMezkYSCCUClfUOTL7/f+GQ7526Sd+XrMBiIdtSLDUzEZn3NVgkzuqhn90t2bT53e5lwyUJkAAJkAAJkEBnAnz+7sxkNO4ZUQLg6dOnMWXKFMYAHAaf5NH+BaQWZpt2nsJ3//Sh4YbaX7csXJJJ3DBvPFYsysLyueMQMUzdRPuLx2CcR+9lgVgLfiyi4KGzpSIMNlsNHj9fOSRZmjWGo4q+S0QMXCZ1wZTUkI/ZGPA+Cd/aw8dQ/O6HKN5/GMUnzqC4rAblETFoam8pGCHZUNd8U07lx3pQwkLE/PgJTEmOxNQr5mHMqk/BlJUV8LJsJIFQIPDJp7fgzQ9z4Ijfgcb0P/oMKSr7BzA70/DlW2bh6Xsu9WnjBgmQAAmQAAmQAAm0JzDan7/bsxjN6yNKANSswsuXL6cAOAw+0aP5C+jDE4X41h924sMTRf1yp6wWkxEb7o7FWbhx/gTERo7s+H39Am0QTlIlMRx3nyzCzuOF+ECqrve3lWcw00gUF+9PXjIJty+ajCsvypAYeSMgYUB5ORzvvY/C9/fizKFsnDlfjqIZc4G77/aP5P33gc2bW9tiHHWYkhqDaZ+4Chl33w6TxI5lIYFQJLDjWAFu+d6raDI1okaTgVjqWodpK1uK8KJVSJCM7CfFCtBmsbS2cYUESIAESIAERiMBj8eD0loHTkuM75zSWpwrr0W9WNJrvGlNTueS6pY+xra8ZHa5m4y43/q7XX+n10oMcK11UuslCWOjHivhaqSr1Ka2pZxHI1g3tSzj48Jx5hefCWnko/n5O6RvzCAPbkgEwKeeegrZ2dn9PtUXXngBmgnY7Q7t7J79PvFheMLR+AWkySa+93+7sEEy+/a1qJXXlRdmYIWIfp9cOAlJscPX5bOvLIbL8fpj43BuOXYeaxYEPzheIBmKawZ1+CmxEbj10kliIToZi6anS/ZQP9ZygzqifrqYS1wki0pw1hyJs6V1OFtWh+qGdpmEf/sb4MxZvxeLdTdg+swsTP/sCqRcSSsqv5C4c0gJXPTgC8gTi+KGlA1wJrUJ2XCHIzr7cUkQHIl/un0uHl+5YEjHyYuTAAmQAAmQwEAQaHS6cUa8P860CHrnxfOmoKIeJVX1KK1uQJnUKgnHUy0iXn2d0xDsBmIcgc4ZK89iec9+NlCXIW8bjc/fQw49BAcwJAKgZvjdt685o50q6YGKN7B9oH7t++g6BcBAREOjbTR9Aekbpf98ZT/+++8HoX/A+lLUnVPFm9svm4wMifvGMrwJ5JfV4gOxCFULwQ+OF+HA6RJoUozBKBkJkfjUpfJZks/TJVNTR1SyDP17oW9/TxTW4EReKUp/8ATQ0NAt1uSUeExffjmm33UL4hJiuu3PDiQwGAR+8Jf9ePLPu+CxlaB28rfFy73td5O9+FaEld6EMIl3eeDpVYwFOBg3hNcgARIgARLoMwGnGOwclUz3H+eV45z8HlZBr0gFvaoGlNeIoFcrgp78lqsTqzyHWOL1pIiNH5rUYt7khNnl38vDHZ4NV8wBsbB3AGaHLJ3SX3+DS21ZGjZ+xrr83dVlk1jaN5kl2IwF4ee/KH+O2wwwYmLCcO5Xn+vJMAe972h6/h50uMPogkMiAN55553YsGED7rjjDkyePDkgLu0XHx8PFQ27KqdOncLWrVuxevVqo8szzzzTVVfuDxECo+ELyCVCzu/fOIYfvrhb3lB1Lz50dWsuHp9oxPRToWZSWmxX3bh/BBBQF4V9p4oNK8EdB8/jPXH/66toHAyWccnRuE1EZRWW50qyGO9LlWCOHQ59SkqrcWLruzjx3gGUHjkB+TUZeNjR0chYNA8z774ZF04ZM3IsJQPPmq0hSqBKk4E88EfjAah+zDNwxe5tG6k7SqwA18pzSTiWXDoRL//rdW1tXCMBEiABEiCBISKgz0E5pTU4XliFI5JA76QszxRVI1/2lVTUoaq60XCfDWZ4GgajyVot+lsVPNYqY9mkS++6pcYQ/FT0azKL8Gdpfu4yOZIQfWqt30s44rdLbN3/89sWzM7o4z81/vZ6+0ZJyJ389RQAvTy4DF0C1qEYWqLEW1q5ciWef/75gJfXmH7q0huMoKdC4YsvvtjtOQNekI0k0E8Eth7Ixbf/9wMckbdavS3XSjbX799zCeZMSu7tKXjcMCOgSVsWX5Bh1H+7dQ7q5I3nu0fysf3jPGw7kGdkIB6IKeWW1OCnf/3IqCoyqxCogrOKzyNBDExOikHyqhuwSGqJuJCceG07jr+5C2Unz0BMxjsjlUzE+VveQv5bH2D3LXLc3Z/AVMkmPBJYdJ4s94Q6gdgIO26+PAubth+DXaz92guAZmeCPAyVw+LIwBsfnsFbYlF81dS0UJ8Sx0cCJEACJDDMCahL7gfZJfgotxR54ppb1OKSWy5GD9VivaeuuIE8+HT6EpVPhDsJh2NukKRWqX6JNKZsgiPpH37buttpWAF20cnU1MeY6WIJ6FO68Wr06csNEhhCAkMiAKpFX0JCQrfTXrduHV5//fVu+2kHtSbULMDPPfccvvKVrwR1zGjq9PDDDyMpKQlr1qzpdto96dvtyUZZhyO5Zfj2Hz/AVhFrelumjYnHjz5zKZbPGUfBobcQR8hxkWFWXCefA62QsCLn5K3p9o/OYZsIgm98fE5cJBr7faan5Q3tj8VlXevUMXGG9ek9V03FxNSRYX2anBiN5M9+Epd95hYU55zHsT9swrG39/hP0NLYiLLYJLz2UT5SxLVjcVYSJiVH8d9lv3/qeMLuCDz96cvw+genUVs7Dtbq2SL6VRhioLVmlrgiNT+E6IPW13/9DvY8dptYrXZ4MOnuAmwnARIgARIggQ4EaiQRxvHCSuzOKcVHZ8tw8nwFzooVX7G47Da2j7Xc4TjvprrVaviKJqkeW6ksS42XVk22clmWyXaFuNa6Rf8bi6ic73oP8126I323e7JlqTdERu/fSZ9DPWE+mz3e6CAAeigA9hghDxgaAkPiAhzMVDdt2mS8NVixYkUw3Vv7rFq1ilaArTRgWFCuXbsWKqY+8cQTAQVAtbYMtm+7S/RqdaS5ABdX1uOxDXvwm21H0ds/AEkx4fjWHfPxhSUXwGblw1uvPlij6CBNKrL/dKlYBuaKheA5ySpdaGQyGygEV0kG4c9cM93IKKzC5EgqTU4nzm38K4698BpOiJtKva3lR+H48cAXv+gz1QzJ8nYPf+oAAEAASURBVLY4Kxnjk/rwg9TnjNwggeAIrPv7x/jh73eKe5O4sIvLr0n+56889pUr8M9LL/TXxH0kQAIkQAIkYBDQ8BJ7RNRTYe+seILkS7bcQnmeKZNaIe65NXWNQYl8XpyuiBNwRx02BD+v6Ndkq/Q2B16KyBdz4r/89nHGvoeGMb/12xbMzujjT4urbue46e7wHDgStkocP7EE9NhlaTPi+4k5Yoel/rXVffI3V+IAqtWiipZqkd/+73B4hA1F//OFYIY0ZH1G2vP3kIEc5hcO2ac4zRJ83XWMZdOXz5e6WauoFwzHnvTty5hG2rFqcfGTVz/Cky/v829BFMSE7SL2PXDDxXjwU3MQH9XHt1FBXI9dRgYBi1j4zM9KMeqa2+dBk828ffg8tomFoLqg58gb2v4sbx3Oh9aHfvOukX3601dPw0JJSjMS3GJNNhsy77rNqNfs2oXTTz+LD46cR9Hld3dCmF/ZgI178zCu8AwWJ5gw5sal8kPQvxDT6WDuIIE+EHjo+hn43bYjyD0X+CSPv7AbX7h8CqLD5WGGhQRIgARIYNQSKJffhicKKrFfPJQOSViibFnPVQs+yaJbIyJfd0WTYGjcPcOCz14iv3ecsFVe4fcwd+QxOJJf89vW7U6N3Sdx/kxNnZ+DTO52Higeq2hvsTC5pMrSrEtXjKxrFQ8Nj7ycFTHRpFXWdYkuXH0tDRMRkd9/XoPduTt3y4AdSGCQCISsAKhuwprcY86cOT1CoYIXSzMBjYmoRZmoW2+g0pO+gc4z2tpU/Dgob86qJUNVb4rGWvve3QtHjHtlbxjwmP4hEBtpx00LJhpVf4To53LT+6ew8f3sfhUDq+SzrpauWqePjcdnRAi868qpSIsfGRZxloULMeVPC5F18iSyo1Px3ukylNZIhjif0oTcl/+O5wsKMemZP2PRp29C2p2fkpfGtNz1wcSNfiWgbr3/+cXLsfKHfwt43iqJv7T4O6/gVvn78qUrp2FSSnTA/mwkARIgARIYXgQ84gVySqz29p4pkwQb5cgTl1y13itV6z3NoCshYmolBp/L6SfOcYepNpkaxABOXXTVVbfYcNX12IubRT/ZJ8H5Wo8wuaK7FADNzqTWfj1eEXfaJmul6Iud4wBa6qYgKvsHhsgHT4SP1V3Q11HjPXlm09e1JrMsdd27T5ZWixlhEoc7PNyKyDAbouQFWpRY9MVI1d/XGqPbIsdZ5e+w/tTTl/C6bZaTWHUpNVL6sJDAcCAQsp9Uzfr7yCOP4Pbbbw+ao8YALCsrC7r/YHbUJCXPPvuskdFYBTkVOB999FHMmzdvMIfBaw0Age/etRB/+fA0GoL4I+u9vFpurf3sZbhserp3F5ck0G8E9IfNzAlJRv3OqgWSWbgEm3aewktSNeFHf5Vj4i77H3/6EN/7v11GzMrPXDMN188dD7vV0l+XGLLzmKZMwRS5+uTUGBwrrMb72aWo9Ar9Ig5CxD8tp8sbcPrnGzFl/QtYdNcNSP78PYC9j4GljTPzPyTQmcD1M8Zi8ZxMvLc/r3Oj7HGH5cLcmImc3HL8JHcPfiKhKcZJLM9rZ4/DFySW54IJTCrlFxx3kgAJkECIESgTIe9kcQ1OFVfhsGbRza80sugWithXJgk3ghH3/E3JFXkEzrh3RfRrFvk0u26wpckq2XZFMDQ1hXc6xOTs+u+LySXWedJulmpyJorlniSZc8XLdoIsdV0s+Vri2XY8sV7L5Ox8PZvdgkhJkhUdKSJddDgSJVZzcmwE0uMjkJEQicyEaExMipKXYDFIirIzNm5HsNwetQRCVgCcO3cu1A34W9/6Fh577LGgbtD9998PjQE4GEVFvHvvvRfr1683xLxA11TrOxUA9+zZ09p37969WLp0qXG8JjBhGb4ExiVH459vmomnXt7f7SQy5Q/R9+6+BHcsyjLeFnV7ADuQQB8JqBg4TwRnrf9PPnu7ThYZloEvf3BK4r3U9fHszYe7PU34+96zRk2ODceqK6bgsxIv8KJxif1y/qE8ib7VvTAjFtPSYnD4fBU+kLiL1e+822lIJxstyP7dZkz/zSZcdscyJKz+EhBNy6tOoLijzwR++aUrseChF+B0tFl2qJuWU2IZNaZugK38WoQV3SEPU/ITrwniMlyJ32v920EkJUZh2fzxePATM3FBRlyfx8ITkAAJkAAJ9JxApcTf251TggPimntUvp8LKuoM673y6uYMurW1DrhcEmsuiGJk0rWKm64k1dBEG4Yln4h64UV3+j26STLHu+I+9NsWzE61FrTIi6aOxexIM5JUeYU+tQj0rpskbm13xWpTQU8s78TiLlYEu3gR9TQ+eorEXk6Li8QY8TQZmxiJCZLMTeMwR9oZ5qI7pmwnAX8EQlYA1ME+/vjjuPPOOw1XYLUG7ModWBOGqMim1n/BZg32ByOYfeqWrGKeJstQEVATa6g1X1dl69atRgKO9uKf9lXLP7UA1Nh75eXlAc/R1bm5P3QIfOOTs/H7N46hSEzv/RWNxfRvt87GV2+caZiR++vDfSQw0ARUzLp0WppR1QL1/WMF4iJ8Cq9IdtHiKv+f3Z6OqUTcD/9bhAatcycnG0LgSolHFic/6IZzUVePmZlxuDAtCh/tmYJdZcWoq/YVUJtEcjlqjsHxje9j+h//ijk3X420r90HU3LXb8WHMxOOfWgIqEvvPdddiN+9dtAYQBNcaEz7PxEA3zK2nYnbJQTSUdgqroG1Zo5YWrT9RikVy5HntxzB81uPYOrEJNxz1TQ8sGQ6H6SG5lbyqiRAAsOYgLrhVkiMvVx5marLBpcbjU6P4RHkkHX1DHK6Pah3unBa4u6dKqhCXnE1isrqUCsuusGWJrO46BoZc0Xg8y5tmkHXu10ufq1tL4S85w0rvtV/TL0AlnreYzstmywi5iWJxZ66+cqbJT/FLDH5Is591U9L8y6rxDyPEwu9FBHxxopBxMTUWEyXF1EXZyZgxtgEJAzz34ldTpwNJBBiBEI2C7CXkwp7Tz75pOGrr0JbYmIiJk+ebDSrGKdVi8a8Uqu6rkRCo1Mf/qNZdFX0W7ZsmZFU47777jPOplaK3vH4O31WVpYhTKrI17GogJiQkAC1APTG4OvYpz+2vdfpLguwXqsnffsytpGYheh324/ia+vf9sGisSE+d+10fHvl/BETI81ngtwYEQRc8gP1nSP5hmXgK+LOXt6DH6bBANCswXcszsKXJDOpWiKOhOJocODA/76C3a+9hYbirkNPpDpqMGvxTEz/ly/DPnnSSJg65xACBOrF+m/61/8sf7PFDUzEvvpxT8sDoP+HMpO4WGmwc3P9RFlOMGr7jIhhEvNo8axMfHX5DCyfMSYEZschkAAJkMDAE1ABr7LBhQqxtiuva0CJxPstr200qgp6lVI17rFmy62Q/RXy26hKljUSW69O9tU3OOFx+//eDWb0mvSiOe5dirw+1Oh0vsUVeQj1Y9dLwDnfl42+vbreijz1PVgcnb/TPWIBWDulc2x4k1NdctVFt9lV1+yQcRmin+yTF0lduejqCCJa3HATxAtE3XBTxQ13rFicj5M6SUKpTJU6MSmabrhd365BaRmJz9+DAm6EXSTkBUDlreKbWgB6i7q0afFm21EBbsuWLZg0afAerlS4U7EskACo4qQKgKtXrzbi/3nH336p7drPO5f2bXr+npSuLBF7Iur1pG9Pxtax70j8AnLLD4krHnkJh8ScX8u1M8fisc9chhnjh78bZMf7x+2RS8ApLidvHDyHP711HK/tPiNvszu/Ve7L7OdMSjaEwDsuzxoRWUob5c3+vg2bsecvb8IRID2r3ePCRRdNwMwHPovk+TP7gpDHkoBBYP1bx/DgL1us/mI/QEPGb/1agfjDpWKgtXoebNXz5YGvTZSPl4e2FImdlCKuVukaQ0msNCZImIspYqmhVa3ZxRgWFvkdpoHQ9YFQQ356H171Qbm6UR6oZVkjD8f68Fwr29Wyrt8lenxidBgSJeN9orh4pcREIE4ESE1wwkICA01AhXN1vVRxRz+jul4pYo5+bhuDdLccqDG65Dek/v1VyzEdi7N1KfvcYkkmlmUO2d8o+7VPc9/mfrrfLS/yPGIM4ZGQHPJ/47lC1/X5QvfL/wMWfbayi4WWTdwwNY6vrttlPaxd1X3GtrR794cb7dLXIhZiLc9nAS/URaPOqU6+K2obRVxzuGTdjXpZam2Q+6Y8dM7KySWim7641DnrUrf9PUe1v5T21e8gp1HlGDlfsC627c/T1brhhmuplYy5EiOvZQlZ90hF6/7mNo+l2hD+5G2McbqoEz+GWbLYdiyuiJOon7Cu4+6gtyPyvipW4LM79dexNqZsNMS+NsFP3HW7yJbrPYHe3zhxx82QvwmT0uMkzEs85oxPxiJ5sZsirrosoU9gJD5/hz710BthSLsAe3GtWbMGanH3q1/9yhD6VDBTsUuFP435t2LFCm/XkFqq+6+WroQ5bdM56Hy0r1oXeou6BqtFY0+KipEsQ0dAM0I9Jm6Va373Hn4kwt91szP79GNo6GbCK49mAjb5gb98zjijagDqDe9l449vHse+05IJrh/KfjnPvzz3Nr79x524U1yDv7TsQiNZST+cekhOEWaz4rK7b8ScO67Hnr+9g32vbIfzuCQJ6VAcZiv2Hz2H/VsOYqwnHrPlh/OU1Ggji1yHrtwkgaAI3HvVdOw4nI+/7DgBW9WlkvwjXUTA38ETntft8Z6IHDi0pm6CtfIyROR/yThGLQq1nkBpt+forw6qGWjsJ7tkUAyXGhkhVYTCaAnuHiMuYRo+IF7EwljZViGgRgUCEQq01ms1BAKXIQRotsYUiRWlAeDHJYuLWXIMsiQA/FSJ4cl4Uf11xwbuPCrmFFbX41x5PQolLIVmNS2RmGil8rdIrbRqRUhWQbn13stnoUHuf2OLQGSIXyqAeWuLINYk2xqrVpcsJKAE5BMh2W0dktDCYWS5bV7qtrjm6n6pENdbdb9tMtcbNaz0ZpgkC23H4oo4IULdkx13B72tVoDwIwC2D98Q1Mk8ViOhhlmTbKglnyvO72H64ia8eKVPm8ViRpR+z+oLGrHgSxahT18CjU2Ql0BiuZcl36FzxaCB36M+2LhBAsOSwLAQAJVsXFwcvvnNbxp1uJBWq8TuilccVLGvvQA4kC7B3Y2J7b0noFZ/O9etMNLD9/4sPJIEQoNAogRgXi1ugVoPninF/+44juffOYlSeSDra6kWy6BfSxwyrQunphpWgbf9f/bOAzCKMm/jT9qm9wpJgIRO6NJBEEXsYMHeznre3Wdvd+rZu57l1LP3LoKKgoKIBRGQ3ktIAklI7z27Kd//nRSyySbZTXaT3c3z3o0z8847b/lN2GSe/Zdp8VDuwo5YlBXEzIVzMOG0mdj9+3bs+uJ7lOw9AM0Uo2lBKinIuHE4KgKL2vzF8kkJgWOiA6HuZyEBSwl8cP1svDQkAq98t1MSUw+Ez+H7UOO3AzX+W2S/UyxPOv+36lrdz+Sw9a4VkiUyS36GJQOjCuBe7yEWIspST7bmvfq5VfZ/DZ4ZJjvqpFJZJqmEJmorR7XNpEdP+WxRMahcxIRRhedQMVGbNvUFnhIim4UjJSA1ikdanRz3hHjkKi/h7m4uUC/j7k2bzFkdqy9nNMss+azwVMcilqq9Ek0brLCUBVb7sBVntWnWYCJ/iCGVZjXVUF8vVmZ1msCmLDcrxC2yQvZKXFMiq1721rSWMjVLZaGll58BRygq7qaoK7LVimAkc27aRFTq8Fy1q/WBe+VQk8us9UqRTN5NAr48rGa3fjnWitqrenXSVNeYKEL+jeqKj9datf6P6rfGR34ftVua+mrbQIlFuoJT2l6QGpV1XPuc0a6210eL+ub1NHSnyztdltL2d36dR7Zkqd3Qakzpx6Wuka+wl2dgxFqeR33jM/E+er009W11v9whDCqj/6cJfKZi5rW5oVWFTuKqmhIAXeo8W7W07LTeTQRAxLS5qbWA51LjLy65jRl0NZFPZc9VYp/sVcKNWj/h2b41dZMFX6RyzVVuuSr+niRrO07iwY6IDKAldpsnwAoScE4CbT91nXOdvbIqZdmnSmioCphquqiYhqrQes80H0esVS8SLCTgbARGDwzFk1dMx8OXTMEPkvFXiYGrtqVpL5PdXeumxByo7V8frsdFxw/VxMAREhTaEYuPvIxPOXESJp1wHI7sSsTO95cgZes+1Iu7EaZNE1OnY792S+Ul+/fEPGxMzsdIeVcZP6wfQoOZOdgRn3tvzVm5zt48b5S27TpaiPd+S8Tq7aE4nDZR/m3WioCXiTrvI6j1OqxtdUpccFUvz8eKcgM2VdQ9lQNeMHWpbZ0SBJtFQfU7UKxJkh8St7a2FihKNKiK+kBr4yKB5RvuU3sRsLRzJSqq/hrr0LDX2kmdrnCeLKHt54MSLGv8tzXfJz52LfpzQ43qv1b+/dU0jaX+LTb1ra75mBQjpBFLNwmIfCo9qDRJ6mejbanzyJXHK5ZXng1impGw01pUU6Kbst5qFN2UgO1eMaptp1KjD/4JdZ5HG4Qi7Z62ol3LvlSfTefuFSPglXWFyX6r+r+LmoBNJq91VulaMRjuqW3jr6n7DP6bYQjt3HjA1BhKAGpXAPQ5qFn7mrqv07o6j3YFwDqvNOjDv+m0i/Ya6PJFWJR/p61LnS4H+rDlravNPlfWe6YEQO0zxK3rCc+UJaCpYkoUNNWuvbp6yeBrqrjIly7eqbeJwBcsQp9sHbjoeimr6eCGzLkqDl+4WPFFBUscPrHgGyAWfHFiCT1O/q5SrtssJEACfZtA20/dvs3DqqtviuHXZOVn1c670Fl+vvkuPZa0NTUVFWOgo5KZmdnRZV4jARKwUwLKAmXBlDhty5LMd5+tTcSHvx5AYob6Brt7Rbl4vfbDHm2bMSIKV0nSkIVTBmkWLt3ruefvVpZFceOGIe65f6E4PQt73vwUu2dMEQuntsUg8Yt2vrcEO4+kYtCs4zDh0gUYOECCb3dkztO2G9b0cQJjJIvify6eAsiWUVSBd+Xf5vItR7A/KRY1xTM0OspyqVbEgJoAZSG4TXupdDVEmCSnXN/MLmKZo6xzjItpczTNslBEya4Wj5LpIuK1FQDrxI1OuUB3tXin3mJSSFLzLY+/V7pVYqH82ayERE2cbDhW9c3CpXbtWL1qryucI4aY8W2mpeJw6cO/knrhVK9YNYlj6lwdqzopjccNVpZNbWXU8lES4D+6oU2r/1aH/CC3K6FXWU01iG8NTRqfUWNdvfbMmsQ0sa4SkUwJwu7lpuOUVvZ/XbKQSnxqTXxTfann3mj11nisXWsj2tVBl38qPHPPbTXThtPK6NfE0DTN5LXOKt2LZph8buq+Gt9dqPXb21kXJq/X6Tv4naaef1eLYtduaXzm7V7v6IJ6ziwagXYYu9TpugWoPQFQWUkblVpP+TgUa7wa2Wp9ZVP7lpvUiXuuq2wu8iWJZmFt1MGxEyVENxVvbw/5klBCHEgMvkFiwTeifxDGilvuxAGhjMHXBIl7EiCBTgnIXykstiJQUNCQDMKc/i1pa05/qo3KoKxcizdv3qzdopKpqFiDKu7gm2++aRSb0JK25owfGxtrTjO2IQEScGACKj7MLQvG4eazxuJPseD76JcDWLohGcq9t7vlj/1ZUNvd73vimpNH4e+njkaofKvtiCUwJgozHroVU8WtMCm3DNtTizQX4Oa1qCzxu/fIu3o9Dq/4GYd/Xo+oKeMx/cqzMXAoY4k2c+KB2QT6SxKPe88ap23KpfPt3xPxsVjtHkjKhYtYSymLqXpcIvpUB8nGLBEATcxME8VM1Msbr6la8+vaE19s1K9yK6x3N5buLZFa3MvGmBQAlTinD11p/rpbtfTMvKJdAVAfukIUQgsE3BZ9u+qj2hUAlVVovc78L5NbdKuJiy3PjY7be6ZGjdo56fC5d+c1p/2f03Z/ttuZolF1h/M1amnhiSU/lRZ27WjNNfHbxKQ7sKDTWou1oyYSqnYiFiphrmGTuH8S+0+JeKaKEvl8Uu5vFPlE3BPLPUuKCk0QFOgNZbkXLMk0wuU4UhIyxYT4NWTR1RIx+UsCJcf8G8gSFmxLAiRgewLd+c1o+9n1oRGarAWtueSnnnrK7O4saWt2p2xIAiTQJwgoS7WpwyK1TbkJf/NnCt5bsx8bDmR3e/0FZdV45qtteGXFLlw5dwRuPHOMZCY1/Ud4twezcQduYhU4TAJpqy2ruArbUgtxMFuyBK5fr4l/zcNXViHr1w34at1m9B8/EtOvOgexY4fRIrAZEA8sIaAy7za5CR/MLsbzYmW7YmMKCsWC16Wm/RAlmnWYvBCL/5klw7Vo22TR1qJKHXZTAGlffGlfsGk1A5OnLiZcEbWG3Zyv5spscsTuCjbdvd/kpOT5tLbkbNnORpZvNhIA2/9Zabmmdo47eu6dzVdZdKo2WrtWFqLtJGZQs3AVN17Xyjg5Uvermqb4mk2WgcfqtTaqSaMFqYuJJBLaZdVCEkK4lY1uOm24p/msqW+paPEj1RzXs4O1qnh07qUTmnsyeaBZt5q8IpWmPyOUdZx7yaQWNzXOUQs1oHiq11fFt4Wbv6qTuapnrizvTBXF1/vIXY0i3zGxr0H0k/N25mOqr5Z16j636rYx/IzayO//QBH4VPy9ASr+nljvjRaX3EmDwrS/CZgJvSUtHpMACdiSAAVAG9JV8f3MFfbsxU3YWjjS0tI67Eq5AE+ZIq5KLCRAAk5FwFfEhktmD9O2vWkFeEeSfCg34ZJuWgWqrI+v/rAbb/24V+IEDtEsD4f2C3JYdlGSYe+0Mf0wa4geO1/dhZ011ahybxVIvKYGGZt3YclWyRw8fBBmiBAYM8N0vDaHBcGJ9yiBYZGBePXKGaiTjPXLdqThtR/3YdPuDBgMbcUzXfEsiSk2SzQBEYRUJkzNqka5fDZuUq/FalOqgSaWtKyX43YC47vKi7JXxlUN92r3ydhqL/029NdwrOqa4rE1XG90NTWRhVODKFY3rpUDG/tqbNvcf8uEASoOnMyvTWlH3GrPmqjN/aYr2hcWW6gtpm/tpLaj+00LK5102HjZFJuGSyoJTEejdti/9ixMt5C0JyLeKHFLPQN13EI0a33e2EYT9+TYtdq0G7QaSVlfKpGqub/GvprPW/WlBCXtmrRTCRfaK7q8BRIX79SG+ZqaaxeFJF3RXKjN2kW5dbcX67M7Yyn31JYuqt3pq+W9btUD4J1xfcsqqxyrGHrulUPM7ktZ5nlIzDwtQ7kkEVJZyQN8PRHsp0Oov7fE2fNChFjrKYvrMH9PeHt4SEIeF0nO4wZvnSTr0RL2uEnmXDd4SR1FPrPRsyEJkIANCVAAtCFcS0S9pmQgNpxOj3YdE9PxN2E9OhkORgIk0CsERkl2uWevmomHJCbZ0vXJeOenfdgiLojdKQbJFPnhLwe1JCRnSyzC2xaOx7i4sO502av3+nvrMHPJ25jy+zrsf+kdbBY+RV6tXjzFdfjovhQsvus5DJDYgNMvX4D+p8pLImME9uqzc+TB1Yvo2RMGalthhR6fb0zG5uQ8ZBWVI1cyVBeUVKFUrG8rKiWYvrK6qVMJMqxTVAIPVxXHz8rFTd8fvkfuNavXhqQUTcJjg1joUitufiaKskbyTr1drijhsIWwqAQtdd5Yf0ykbGgnOVI1QdPVEG6iV6kSwcu9eGrjNZHVNFFSyWvquHEvx9pcW5w3XXetaf8LECV8QRIhaKKaNoJ6eo2bZpHV+DSVeKWJYvKMG8UwN80CrXFarXa6vDMlJGFVg6WUaq/d03Bvg7WdOm48V9ldm9rIXrlJtldUooOuWl+116eq9xAB2zJnzI56O3bNtTZAPV6blabs1CortDpW1uMtM0R7qAzRIk41ZYr2EHFJHascdK4uYo0me2WZr92n7pXjzmLK1kpaaH2NbPJlgNqrLwUMkrzKoI5lq6mtlU0kefkdrLa6xmOVJduaRa3LTa1N1qQyX6u1eXg07LX1ynq0tctimxgoHopTR0Wx8BERT22+npIww8tdNg/4S1w9f9kHyO/iUBH3Qvw8ES6utqEi8nm4KUGahQRIgASciwAFwB54nh1ZATbF/rNELOyBKXMIEiABErAaAWUVePnc4dq2IyUP74oQ+MW6JKjYZF0tEi4PX4kbo9rmjYvBHWePx4wR/braXa/f5zFrJsbIlrBnD/Y+/yY27kpFiUdbQSI1NRepj72N+Dc+w/RrFiHijJPVm16vz58TcFwCwWLVcoO412Nu2zVUiwiQlFeKxOwSZIrLsLzzS6hKEQHUP0D5f53s1f9EO9CKt2TB9vV0016otZdrT528YLsjQD4DvMUaRomN+WWylVehSI4LyqtRInt1XCxJgEpEcFTnpbKVy+dDhWyVki27WiyAlRjhJi/6miigrHIaN08Z00ssbJTAUVxWheLSapTL/bUiWrRXGtwblUCltgZprN22ymqoYnh7l7tcLzIGvDOv6fL9Hd1oq349Sm3judGZ+OeuLKlEuNEsqpQ1lRx7yXP3lr3afETQUcKOTn4+1M+Iu5vQFYFIE8rUsVbnqv1cKrFHiT6BSvgR0Uftg+TfgL/056IUtF4qSr9SlmKOJjrVyT/+Kvm3WV0j/5C6UTyUQCfrp5VcNyDyVhIgARIwgwAFQDMgdbXJpEmTtCQcHWXUbRIHJ0+e3NVheB8JkAAJOAwBZa33wrXH45FLp2KxiIDKRXjnka4FlW9a9Ood6VDbtOGRuF0sAuePj+3U2qHpXnvbuyYkYPRbL2CkZATe+9+3sXHDPpS6tLVhSc4tR/KT72PY5oOYfuf1CPHtXnZDe+PA+dgHASW4jBJXe7VZo0QEtBW1rdFv6z6UKJEnFowHRbhMySvDEdlySyo1C6YauVajWTGJ7Z4ca9ZNYsWk7tHEI2VZ1CgguTWKR5qFkWZF1Xok650rMVVZXinRVbPCkjk2WWQp8VM7VtZYpiyzpL5WqbOdlObvChrXor46aLIMUxZUSlRVgpoS2NQXN0pY89OEsgaBTVmS2aqovkMlAUKYWGApt8qoAMl2qvayKXdKFvskoAQ7H53a7HN+nBUJkAAJkIAxAQqAxjysenbccQ2xmppEPlOdJycna9Xz5s0zdZl1JEACJOCUBJTlxdXzRuKqk0ZobsFKCFyyPgmV+q77VamkI+c/vRJjBobg1gXjcc60OHGB6j2Lju48OLeBAzDmPw9hZF4+dr/8Hjb9uh1lhlYWTfLCfnDUJCSuPywCTQCmxodq1izdGZf3koAzEFCihBIb1TZraKQzLIlrIAESIAESIAESIIFuE3ARV47OvzLs9jDO10FwcLCW4CMpKQnx8fEmF6iEP9Vu4sSJ2LJli8k26ptXdb/qx5lLgli1tCwGgwGJiYlalUoYwpiBLenwmAT6JoEicQf8/PdDeFsSfew/WtRtCPFRAbjlzHG4ePZQzXWs2x32YgeG0jLsevMzbFq5HhXiPqmV8eOAhWc3z0rFOBoTHYjJcSHwEwseFhIgARIgARIgARIgARJQBNLT0xEbG6vB4Pt33/2ZcEzTCAd5Xiqu36JFizQ3YFNWgKtXr9ZWcvfddzvIijhNEiABErAdgSAJwP3XUxKw8ZlF+OLOUzSX3u6MlpxVgpveWotxt3yO11fuQZVegvM7aPHw98PE267FVV+9ghkXzIdnoCQKOf54o9XUihvj9rQivPN7Cla9sQT5Xy1XAduM2vCEBEiABEiABEiABEiABEigbxKgBWAXnrty2x08eLB2548//oiO3HeV8BcXF4cLLrgAr7/+utFoTS7C7VkHGjV2shN+A+FkD5TLIQEbEfhjfyae/Xq7FuOvu0NEBfng5rPGitvxSC1gfHf76837q6oN2JJWjG2phTC0jv1VI0Lnf1+EpHFFfJgvJv3tEvSfP6c51ldvzptjkwAJkAAJkAAJkAAJ9DwBvn/3PHN7HJECoJlPRVnr/fWvf0VTzL7Wtyk3XnX9rrvuan1Ju+fkk0/WhELVRmX+feqpp7R2ixcvRl/MAMwPoDY/JqwgARLogIDKHvzcN9vx9Z8p3TZqC5e4YEoIVDEIVaZSRy7lkh31z8MF2JVeDGUBqJU//wS+/95oWf0GRGLSdRcifs4UybJou0D+RoPyhARIgARIgARIgARIwC4I8P3bLh5Dr0+CAqAFj0BZ87Un1nV0rWkIJSJu3bpV60NlCFaxAftq4QdQX33yXDcJdI9AYkYRXvh2Bz5be0gs31olxbCwa5Vx8sYzxuC6+aOgkpI4cimpMmBTSgH2phag5gVl/VdqcjnBw+NxwvXnY9DUsSavs5IESIAESIAESIAESMD5CPD92/meaVdWRAGwK9R4T7cJ8AOo2wjZAQn0aQLp+WV4efkuvLdmPyrECq47JdjPE/84bTT+eupoBPo4thBYXlGNHe8twY5vf0ZVaYVpLJJ8atTYeMy59x/w6s8MqaYhsZYESIAESIAESIAEnIcA37+d51l2ZyUUALtDj/d2mQA/gLqMjjeSAAm0IJBfUoVXV+7GG5Lko6hc3+KK5YdK/LtBRMC/ixioREFHLvqKKux+7SNs/e5XlOpNW0r6utVj7lmzMPSW6wF3Zg125OfNuZMACZAACZAACZBARwT4/t0Rnb5zjQJg33nWvbrShIQEo/ENBgMSExO1OqYhN0LDExIggS4QKKnQ492f9uElsQrMKa7sQg/HbvH39tCyEf/j9DFQbsKOXGolEUjiS29h8/LfketiWtQcGuSBuY/fCd+xxp/Tjrxuzp0ESIAESIAESIAESOAYAQqAx1j05SMKgH356ffg2ikA9iBsDkUCfZhAlb4GH/16EM8v24G0vLJukfD1dNfiA954xliEB3p3q6/evrm+sBB7nn0Nv67dDVMGgV6oxexLTsOov13BbMG9/bA4PgmQAAmQAAmQAAlYmQAFQCsDddDuKAA66INz9GnzA8jRnyDnTwL2TUBfUyuJQhLx7NfbcTjHdEIMc1eghMBbF4zD/4kQ6CPHjlxKU1Kx5vHXkbzvcNtliBvwkPvvwGlzEuDu5tr2OmtIgARIgARIgARIgAQckgDfvx3ysVl90vwL3+pI2SEJkAAJkEBvE9C5u+GKuSOw5T8X4NUb5iA+KqDLUyqXJCOPLt6C4277QhMV6+rqu9xXb9/oHzcAC954FKfdcz28g1sxOessHKr1xLIdGd3OsNzb6+T4JEACJEACJEACJEACJEACxgQoABrz4BkJkAAJkIATEfBwd8Wlc4Zh87Pn481/zMWw/kFdXt3RgnJc/79fMPffX+OP/Zld7qe3b3SRLMAjTp+DKz56BsMnj2qYztSpwNix2vGR/Ap8sz0D+hrTyUN6e/4cnwRIgARIgARIgARIgARIwHICdAG2nBnvsAIBmiBbASK7IAESsJhAbV0dvt6YgqeXbsO+9EKL7295w8IpcXjokimIj2xlSdeykQMcJy39Hj8ExENf72I02+hgbywc3x+eYk3JQgIkQAIkQAIkQAIk4LgE+P7tuM/OmjOnAGhNmuzLbAL8ADIbFRuSAAnYgIBy4/1202E8tXQrdqcWdHkED4mVd8OpCbjznAkI8jWdZbfLnffgjdklVViyNR3VBmOrv/5BXlgY4wmvfpE9OBsORQIkQAIkQAIkQAIkYE0CfP+2Jk3H7YsuwI777DhzEiABEiCBLhJwdXXBwqlx+P2Jc/Hp7SdjfFxYl3oy1NbhpeW7MP6Wz/H6yj0wOKjbbGSAFxZNjIG3ztjaL2PLHiw+5wakv/ouUO+4sQ+79HB5EwmQAAmQAAmQAAmQAAk4EQEKgE70MLkUEiABEiABywgoIfCMSYPw62Nn44s7T8Fxg8Mt66CxdUFZNe587w9Mu/tLfL/1iGhljieWRYgIeJ6IgD5NImB2FrD4C+S5+2Dxx6vx/XX/Qmle99ymuwSXN5EACZAACZAACZAACZAACXSbAF2Au42QHZhDICEhwaiZwWBAYmKiVpeWloaYmBij6zwhARIggd4goIS7H3ek44FP/sSetK67Bp8wuj8eu2waxgwM7Y1ldGvMfBEzl/y6H+UvvwqUlhr1pQsKwJQbr8SEeVPgLu7PLCRAAiRAAiRAAiRAAvZPgC7A9v+MemKG/Ou9JyhzDBIgARIgAYcgoDLkzh8fi9+fPAcvXXc8IgK9uzTvX3ZnYNa/luL/3vgNWYUVXeqjt24K9fPE+bOHIWz0sDZT0BeV4PfH/4ePnv4Qh3PL2lxnBQmQAAmQAAmQAAmQAAmQgH0SoAWgfT4Xp58Vv4Fw+kfMBZKAUxAordTj+WU78LLE+asy1HZpTb6e7rjr3An4+2lj4OlhHGOvSx320E0qUcqOj77G+neWotpUbMMRI3DibVdi3KgBPTQjDkMCJEACJEACJEACJNAVAnz/7go157uHFoDO90y5IhIgARIgASsR8PfW4f4LJ2PLcxfggplDutRreXUNHvh0E6bd9SV+3J7WpT564yYVH3HCFefgL288iNGBbnBBq7iG+/fjl7ueQuq2fb0xPY5JAiRAAiRAAiRAAiRAAiRgAQEKgBbAYlMSIAESIIG+SSA2zA9v/d9crHlkIaYNj+wShKSsEpz31A+46NlVSMku6VIfvXGTz7DBOPnrt3HRjHhEleUbTaGuqAjL73oahZu2GdXzhARIgARIgARIgARIgARIwL4IUAC0r+fB2ZAACZAACdgxgUlDIrDygbPwwS0nYVCEf5dmumLLEUy580s8ungzKsQ60CGKhweinn4UFz1+EyaXphtNuUrcpJfd+gSq1q4zqucJCZAACZAACZAACZAACZCA/RCgAGg/z4IzIQESIAEScAACKlHI2VPjsenZ8/HopVMR6KOzeNbVEk/w6aXbMPmOxfhmYwpU9mFHKC6nn46Zyz/GEH/jPx8K4IEfbnoYdT/84AjL4BxJgARIgARIgARIgARIoM8RMP4Lvs8tnwsmARIgARIgga4RUAk9bjpzLLY/fyGunz8KbhIzz9KSlleGy19YjYWPr8D+9EJLb++V9i4xMTjl4/8irF+o0fgpvmH45NG3ceSosZuwUSOekAAJkAAJkAAJkAAJkAAJ9AoBCoC9gp2DkgAJkAAJOAuB0AAvPHvVTGx4+jycMiG2S8v6ZXcGZvxzCe75cANKKvRd6qMnb9KFBGPB64/AZ0ic0bC551yIpXvzsXRrOnJKq4yu8YQESIAESIAESIAESIAESKD3CLiI25Fj+B31HiOObAUCCQkJRr0YDAYkJiZqdWlpaYgRixIWEiABEnAGAmt2puPuD9bjwNGiLi0nItAbD18yBRfNGgqVideey9HcEiy5/xXU7toNjBkDnHtu83TFUxoj+wVg+uBQBHh5NNfzgARIgARIgARIgARIoGcJpKenIza24Ytqvn/3LHt7Go0WgPb0NDgXEiABEiABhydw4tgY/PHkeXj88mnw97Zc+MoprsQNr/6K+Q8uw/aUPLvmER0egPMeuwlhJx0PnHG60VzV14t7M0rw/rrD2Hy4wGHiHBotgickQAIkQAIkQAIkQAIk4CQEaAHoJA/S0ZbBbyAc7YlxviRAAl0hkF1Ugfs/+ROfrm2weLa0D2VFd9WJI3D/RZMR4udl6e091r6urh57M0uwPikfZW0yG4sS+NXXiB8Qjvk3XwZvb8uTpvTYQjgQCZAACZAACZAACTghAb5/O+FD7cKSaAHYBWi8hQRIgARIgATMIRAZ5IPX/34CfnxoAcbHhZlzi1EbZUX3zk/7MeWOL/HtphSja/Z0olyVR0cH4soZgzBDXH517i3+vNi7D9i5E8nf/YSPr7gLmZt32dPUORcSIAESIAESIAESIAES6BMEWvyF3ifWy0WSAAmQAAmQQI8TmDosEj8/uhAvXDMLwX6eFo+v3IIvfW41/vLiT8iVY3stSvibGh+Kq2YOwrjYQLhUylxXrGiebmlmLhbf9hS2Pfw86vX2n+ykeeI8IAESIAESIAESIAESIAEHJ0AB0MEfIKdPAiRAAiTgGATcXF1x9byR2PrcBbhG9q7Kv9fCsnRDMibfsRiL1x2y65h6Pjp3nDgiEudm74RPUb7RKmvFXfiXVZux/KyrUb5xk9E1npAACZAACZAACZAACZAACdiGAGMA2oYre+2EAGMQdAKIl0mABJyewA5J8HHn+39gw4HsLq319OMG4vmrZ6JfiG+X7u+pm8pW/4wVT7yFo9VtR9TV12Li8eNw3H03Qedn3+toO3vWkAAJkAAJkAAJkIBjEOD7t2M8J1vPkhaAtibM/kmABEiABEjABIFxEhNw5QNn4Q2JERgZ5G2iRcdVK7YcwZQ7v8RHvxywa2tAv3lzsWjZG5g8PQFoZfWod3HDht93470Lb8WOZT9DWQeykAAJkAAJkAAJkAAJkAAJWJ8ALQCtz5Q9mkGA30CYAYlNSIAE+gyBkgo9nv5qG/73/S7U1Fougp04Nhr/vfZ4DAj3t2tmyWvWY+V/P0ZVXqHJeQYfNw6zb7kC8XFRJq+zkgRIgARIgARIgARIwHICfP+2nJkz3kELQGd8qlwTCZAACZCAQxEI8NHh0UunYv1T52Hu6GiL575m51FMu2sJ3vpxL+rs2Iou/sTpuOyDp5Fw0lS4SObg1qVwyw5884+HsOPbX1pf4jkJkAAJkAAJkAAJkAAJkEA3CFAA7AY83koCJEACJEAC1iQwPDoYX99zGl69YQ6CfHUWdV1WZcBt76zDmY8uR1JWsUX39mRj/wAfzH/oJslqfBfiQn3aDl1SgjX/eQe7P1/e9hprSIAESIAESIAESIAESIAEukSAAmCXsPEmEiABEiABErANAReJk3fpnGH485nzccakgRYP8vu+TMy4ewleXrFLYurVWXx/T90QPmkszl76GhadMwOR+lLjYXWeWI0Q7M8qMa7nGQmQAAmQAAmQAAmQAAmQQJcIMAZgl7DxJksJJCRI8PcWxWAwIDExUatJS0tDTExMi6s8JAESIAESUATq6+uxdEMy7nj3D+SXVlkMZfLQCPzvr7OhLAvtudQnJ2PDbQ9hQ14NoBPLxyuvBPr3h6uIoWeMjcKQCPuObWjPbDk3EiABEiABEiABEmAMQP4MKAK0AOTPAQmQAAmQAAnYKQFlDXje9MHY9OwibW/pNDcl5mDmP5fi+WXb7doa0CU+HtO+fBuTjxsCXHihJv6ptdaJALpiVxZS8sotXTrbkwAJkAAJkAAJkAAJkAAJtCBAC8AWMHjYcwT4DUTPseZIJEACzkPgu02Hces7vyO7qNLiRc0cEYXX/36CXWcKVhaPvx7MxbbUIqP1uUvCkLkjIjA6OtConickQAIkQAIkQAIkQAKdE+D7d+eM+kILWgD2hafMNZIACZAACTgFgTMnD9JiA14mMQItLev2Z2mxAT///ZDmWmzp/T3RXlk8zhkWjjGthL4ayWz8494srHrpExiKGRewJ54FxyABEiABEiABEiABEnAuAhQAnet5cjUkQAIkQAJOTiDYzxP/kyzBS/95KmJCfS1abUmlAde98jOuemkNCsuqLbq3pxorEfCkkREY2S/AeMjf12GPZAb+/LI7UHQw2fgaz0iABEiABEiABEiABEiABDokQAGwQzy8SAIkQAIkQAL2SWDeuFhseHoRrpk30uIJLl2frFkD/rr7qMX39sQNSgScPyoSEwYENQy3ZQvw00/acW5hOT75xyNI+nFdT0yFY5AACZAACZAACZAACZCAUxCgAOgUj5GLIAESIAES6IsEAnx0eP6aWVj+7zMwyMJMuUcLynHWYytw70cbUG2otTt8rhL374ThEThjoC90P640ml91pR7LHnsd6974AnXiHsxCAiRAAiRAAiRAAj1BoLy6BnsSM1B35EhPDMcxSMCqBCgAWhUnOyMBEiABEiCBnidw/Kj+WP/UefjH6aMhxnMWlZeW78Lc+77G3rQCi+7rqcbDhkXjoufvRqi4PhuVmlr8+cE3+O7fL6JGjllIgARIgARIgARIwNoEVIKyrOIqrE/KxycbU/HGb8lY9fFKZJ21yNpDsT8SsDkBCoA2R8wBSIAESIAESMD2BHy9PPDE5dOx6sEFFlsD7k4twJx7v8YrK3bZpUVd6NiRuOijZzC8dVxAwZr06yZ8fcP9qC6rsD1kjkACJEACJEACJOD0BOrLy5GyaTdW7cnCm2uT8emfqdiQnI/skqqGtQcGIsWjVaxip6fCBToDAQqAzvAUuQYSIAESIAESaCQwdVgk1j15Lq6YO9wiJsoN+F8fbsA5T3yPDHEPtreiCwvFaR+/iBMmDIRbfZ3R9NL2H8bSK+5A5dFMo3qekAAJkAAJkAAJkIC5BOrS0nDw9vvx0fy/4Osn38GejGKUV5vwMggIQIpXsLndsh0J2A0BCoB28yg4ERIgARIgARKwDgF/bx1evn42Pr5tHkJau852MsTPkhhk2l1L8PVG+8u066LTYcJLj+Oc8+dAV1djtJKsnGIs/ss/Ubptl1E9T0iABEiABEiABEigIwJ1GRnYe/O9+PC8G7F8YxLyXHRAdjaQlm7yNl1IEIJKClDLOMQm+bDSfgm4iE87o2fb7/Nx2pmlp6cjNjZWW1+afNMSExPjtGvlwkiABEigNwlkFVbgb6/9ip92mv4jtqO5XTJ7KJ6+cgZUshF7Kzlfr8BXz32EijrjoIcBLrU479EbETRnpr1NmfMhARIgARIgARKwIwK1hUXY9/iL2LR2J4rcvdrObMwY4NxztfpgHw/EhfshPswX/QO94GbQA14m7mnbi13U8P3bLh5Dr0+CAmCvP4K+OQF+APXN585VkwAJ9A4B9V3fG6v24t8fb0SVhRl/B8ofu2/+Yy6mDY/qncl3MGrB5h1Yes8LKK2QP8JbFF8RAc+55zqEn3ZSi1oekgAJkAAJkAAJkABQV1uHve9+gQ2frkCpKRffRkihQwZg9IN3ID7CH0F2+GWoJc+S79+W0HLethQAnffZ2vXK+AFk14+HkyMBEnBSAvvTC3Htyz9j55F8i1bo7uaC//11Di46fqhF9/VE45IjR7H01idQmFNoNJyXuysWffIcwvuHG9XzhARIgARIgARIoO8SSNu4A7889y7yjuaahuDmivDxCZh62VkYMmkUXFyMPQ1M32T/tXz/tv9n1BMzpADYE5Q5BhISEowoGAwGJCYmanV0ATZCwxMSIAESsCkBfU0tHlu8BS98uwOWBgF56srp+Nupo206v650XlFchq/+72HkpBxtuN1VQhxfeCF8Ro/E+ZNiEeJrfy7MXVkn7yEBEiABEiABEugagaLcQqx95i0c2rBTTACNk4lpPcrfDlHjRmDKtRcgfuwQpxH+mmhRAGwi0bf3FAD79vPvsdVTAOwx1ByIBEiABMwisG5fJq7/3y9Iyyszq31To7vPnYh7Fk20uz+Mq8orsezGR3A0MRU47zzIN0/alP293HH+cbEIlNg9LCRAAiRAAiRAAn2LQLWhBn9+sAzbvlyJ2lLTf/NED4rClFuvwcCJI+3u7xtrPS0KgNYi6dj9UAB07OfnsLPnB5DDPjpOnARIwIkIFEvsvDveXYfPfz9k0aqumz8Kz0hyEFdX+3KLMVTr8dWXa3E0oiHJVNOiArw9cMGkGPh7UQRsYsI9CZAACZAACTgzgTrJ0LsnowR/bE5ExfMvQlL2tllumJcrZl+3CAPOPwsuynvAiQvfv5344VqwNOf+KbcABJuSAAmQAAmQQF8jECgBrVWCj3duPBFBFrjJvikJRa595Wcod2J7Kh6eOiy88ARESXa+lqWk0oAlW9JRXl3TsprHJEACJEACJEACTkggr6wan29Ow+p92ajwDQCmzzBapXedASfNTsCl37yGgRcudHrxz2jxPOnTBCgA9unHz8WTAAmQAAmQALBoxmD88dR5mD2qn9k4vvwjCRf/50dU2Jmo5unuhnMmRCPM39NoLYUVBiz97k9U5lqWAMWoE56QAAmQAAmQAAnYLQFl9fdnSgE+2ZiKrOKqY/OcfTwQGAi3+jocF+GFv7z5EMY+fg9cfX2PteERCfQBAnQB7gMP2R6XSBNke3wqnBMJkEBfJ6D+cP7PN9vxyBebzUYxdVgkvrjzFAT7GQtuZndgo4YV+hos3pyOgnJ9wwiHxM158WJERgRi0TtPQudjbCVoo2mwWxIgARIgARIggR4gkLt5J36s9EZ2Vb3J0eIzDmG2RxmCLz4fEujPZBtnruT7tzM/XfPXRgtA81mxJQmQAAmQAAk4NQEV0+/Ocybgletnw9XMP443HszG6Q9/h6zCCrti46Nzx7kToxEo8f+wbRvw6SeAXo/s9Fx8f+ujqDMRC8iuFsDJkAAJkAAJkAAJdEqgNr8AG259CJ/e8iSyV/zUpn2IhDhRfw8svPJ0BF9yQZ8U/9pAYUWfJUABsM8+ei6cBEiABEiABEwTuHzucHx460nQuZv3Z8KetALMf3AZUrJLTHfYS7Uq6cd5QwPgv3I5INaNTSV5TwrW/vs/TafckwAJkAAJkAAJOBqBqirkPP0CPltwHdZvOohaiFXfH38AhQXaStT3mJMGBeOSqQMwMJSuvo72eDlf2xAw7y9724zNXkmABEiABEiABOyUwFmT47Dk7lPhZ2bm3MM5pZoIuPuIfcXYC4wMxXmP3Agvl2MCoEK+9bft2PXK+3ZKn9MiARIgARIgARIwSaC2FrnvfIjv5l2Ej5dtQo5Li5Aecg0rVyLUT4cLJ8fi+KHh8HCj5GGSIyv7JAH+a+iTj52LJgESIAESIIHOCcwZHY1v7zsDIWbG98suqsTpj3yHDQeyOu+8B1sEz5iMM2+5FG4wFgHXfLYKqd+s7MGZcCgSIAESIAESIIEuEaivR+5Xy/Hd6Vfio3d+QCLaWvW5iNg3pZ8vLjkuGv0Cvbs0DG8iAWcmQAHQmZ8u10YCJEACJEAC3SRw3OBwrHpwAaJD2v6hbarrIkm6sfDxFVi1Pc3U5V6riz3vDJx0wTyj8ZVX8HfPfYj8jVuN6nlCAiRAAiRAAiRgJwRE+Mv7chmWnyHC338+QWK58Zd5TbMMGzEYF718H2Y+egfcdRL/l4UESKANAQqAbZCwggRIgARIgARIoCWBYdFBWPXQAgztH9iyut3jSn0tLnp2JRavk8y7dlQSbroaU2aNMZpRdW09vrnnBVSkHDGq5wkJkAAJkAAJkEAvEqirQ85nS7H81Mvx0Quf4WCJuPeaKJ4DYjDjnr/j4tcfRNSY4SZasIoESKCJAAXAJhLckwAJkAAJkAAJtEsgNswPKx84CxPiw9pt0/JCjQhr177yM95ctbdlda8fz3jsTgwdHmM0j+LqWnz7fw/BUFhkVM8TEiABEiABEiCBniWgr6nD7tUb8OmZ1+Ljl5fgoFj81asEH62KZ1gwpv/9Elz93mOYevpMuDPWXytCPCWBtgQoALZlwhoSIAESIAESIAETBMICvPGdxAScPaqfiattq8RrB7e/uw5PLtmKenViB8XFzQ2n/PcBREUFG80mo7gaP9xwH+qq9Ub1PCEBEiABEiABErA9gdzSaqzZn4031ybjx1IPZJUbTA7qGRSA6Zeegas/ew7TLjkDXjp3k+2sVan+ftl4MBu5xZXW6pL9kECvEaAA2GvoOTAJkAAJkAAJOB4Bf28dvpTswGdOGmj25B//cgv+8uJPKK6wD3HNw9cHZ710P/wDfIzWcOhoIX699WHUi9sRCwmQAAmQAAmQgG0JVNfUYk9GMT7flIqPNhzBjrRiKAtA+PkDo0cbDe4ZEohpVyzA1V++iGl/uwReXjqj69Y+2ZdWgIc/34SxN3+Gkx9Yhk/XJlp7CPZHAj1OwEUUbfv4Sr7Hl84Be5PIifcsAABAAElEQVRAeno6YmNjtSmkpaUhJsbYHas358axSYAESIAEOidQU1uHm99aiw9/Odh548YWcZEBeP/mkzA+zjw3YrM77mLD3F0H8MWtT0JfZSxMHj9/Mibdf0sXe+VtJEACJEACJEAC7REwyN8Ph/cdxoGlK5Gid0PNnBNMN83MBN54A/4hARi9UP52uHSBzUW/tLwyLPkjCV9IDOPdqQVG8xo3KBRrnzjXqM6RTvj+7UhPy3Zzta29rO3mzZ5JgARIgARIgAR6kYCKtfPy9bMR7OeF/36306yZpGSXYN793+CJy6fj2pNHwsWlbUwfszqyUqNwCRa+4F/X4quHX0OtvJA0lbX5tfDLLMaIfuYlPWm6j3sSIAESIAESIIG2BNSXhkcOpePg8l+QvGUv9KnpkNgggMrWO3267D2NblJ/HsSNHYLR912PuHmz4OruZnTdmif5pVX4ZmOKJvr9sT+r3a53HM7HAfEUGB5tHEKk3Rt4gQTskAAFQDt8KJwSCZAACZAACTgCASXgPXrpVIT6e+KBTzeZNWXl2qPiAq7bl4n/Xnc8Anxs68LT2aRiT5qJU7JyseK1xfIyIq1POgmYNROr9ubAR15MBoQauwl31h+vkwAJkAAJkAAJQHPlTd22D0m/bETSjkRUp6YBda2cD/US52+PJAubMEFD5ufpjoRosfiLDkSAl4iDiLYJyvIqA77fmqqJfqt3pEElLjOnfLEuCf++YJI5TdmGBOySAAVAu3wszjephIQEo0UZDKaDuho14gkJkAAJkIBDELh1wXgE+3rhlrd/l7/tzfsjeumGZGw/nIf3bzoJ43rZJXj4pWejLDMHv7mGAmPGaMxr5SXl250ZuGhyLEL9jC0THOKhcJIkQAIkQAIk0MMEyjKykbJmPZI37UFqUjpqiko6nYHbls0YOH8WEvoHIj7MF66utvEOMMgXkGt2pWOxiHjLNx9GeXVNp3Nr3WCxuAbfd/5xve7B0HpePCcBcwlQADSXFNuRAAmQAAmQAAm0S+AvJ41AkJ8O1778c0MA73ZbHruQnCUuwRJY+8nLp+Hqeb3rEjzx9utQcjAX21OLmieorBW/25mJi6bEwtOG7kfNA/KABEiABEiABByIgIrnlyPZe48++ASS9qciq8w8Iw8XMbmPrSzC8EkjMeSys+E13jaWfk0ZfJXl3lfyxaNy9+1OOZxTik2HcjBlaGR3uuG9JNBrBCgA9hr6vjXwnj17jBbcMgip0QWekAAJkAAJOCyBs6fGizuwl2T8XYPckkqz1lFtqMWt76zDWuUSfG3vuQQrd+Y5Q8M1i4DE7LLmuReU67Fa3IFPHxPFb/ybqfCABEiABEigTxEoKUFdcTHygyKQXVKFrGLZZJ9fpm+w/M8V4c8M8S+6qgjDRg3C0LNOgu+ZpwHe3jbBuFcy+CpLvy//OIQjucd+p1tjMNUvBUBrkGQfvUGAAmBvUOeYJEACJEACJOCkBI4f1R/rnjwX17y8Bmv3SgY/M8vS9cnYkSIuwTfPw1jJtNcbRbkdnZIQheLKNOSUVDdP4eDBdPRbvgQT//V/zXU8IAESIAESIAFnIVAlX8aVlFWhMuUIKg6loEL2lalHUSEuvZXZuaioqEb+xKkwXHyp6SXHDgCOpLa55lpfJ1H8qjFYRL/BJ01HwIIzAB/bxNY9kluqZfBVAt0eEQBtUaKCfBARaBvR0hbzZZ8k0JoABcDWRHhOAiRAAiRAAiTQLQJRwT5Ydu/peHLJNjz91VYt0Z85HSaJS/BJkiX4qSum4ypxKe6NLMEekt34zDH98fGfR1BtkMzAR9OBzz7D2tJSRPYLRfRfLjZnKWxDAiRAAiRAAnZFoE5i2xZXGlCYkYPCA8koTElDwdEcFOUUorywGCgQ0UxcetsUVz/AT7bsnDaXmisGiADYWHSu9YgL90f8xBEYdMoJ8Jo4DhLYr+myVfd54m3w1YYULBZLvw0Hsq3ad1NngZKsbOHUOJw/YzBmjeoHNxutpWk87knAlgQoANqSLvsmARIgARIggT5KQP2BfK8Eyp4+PBLXvvIz8sRVyJyiXIJVMpHfxSX4xWtnwd+757MEB/p44FSxBPzm4x+Br7+CpAdEnYsrVrz1NS4ZPxq+4xsShZizHrYhARIgARIggZ4moGLflVTWIFMEskzlritbrsTqq139E7B2bdemUywJPSorxG3X2IJPImggbGQ8os+ag/gpYxAz4zi4edrud3dppV6SeBwR0S8Ja3ami2ZpXvIxSxbt6eGG0yYOwPkzB2P++AFQ5ywk4AwEKAA6w1PkGkiABEiABEjATgmcODYG655QLsE/a6KeudP8Uv6w35aciw9umYcxA3veJTg+3A9TdZXYKOJfUymDO1bc9TTO+/IVuAYENFVzTwIkQAIkQAI9T0BEPuTlQb9vP0r3JaIk6QhyU7OQCR2y/nYLKvTHfn81Ty4wsPnQ4gOVnTcvHwHDAhEV4IWoQE9Eyj5CYv/q3MXCb+5Ii7s09wa9/C5evT0dX4il3/dbxD3Z1NrM7ayddq4qFvDo/rhg5hCcOXkQlOUfCwk4GwEKgM72RLkeEiABEiABErAzAv1CfDWX4CeWbMWzX2+zzCX439/g6Stn4MoTh/e4S/C0Gy5G1l4JIL79QDPR9Io6bLjtYcx469nmOh6QAAmQAAmQgC0IKLfdsuIylO1PRKnE5itLSUVJehZKsvJQml+MUtH4qtw9jYdWJnmVEsfWzcSrfliYcdsWZyozr7ehGj5i7eYdHgyfyHB4R0fBZ0AMfOIHwm/wIESG+cNHZ6LfFv1Y61Ctfd3+TC2Zx9cbU1BUfiw2r7XGUP0cNzhcLP2G4Lzp8YiUGH8sJODMBHrmX68zE+TaSIAESIAESIAEOiXgLrH1/n3BJMwYEYXrLHAJVoHJb3prLbaKNeB/rpoJD2Vl0ENFJQU57fHb8fGVd6M0t7B51D/3ZyDmoy8x4LJFzXU8IAESIAESIAFLCShX3dLqGhG3DCgS19aiCgNKq2pQumc/yr5doYl/9cr11lRxEeHP1Nu8sgxU8fzCI9reFRaqiXwh+nIEBfkiOCoUwQP6IXjIIASNHAK3ESPEn7d9kbBth9avScwswqe/JWrb0YJy6w8gPQ7pF6hZ+ikX38FR3bCKtMns2CkJ2I6AqY8M243GnkmABEiABEiABPo0gZMaXYKvfmmNfLOfZTaL99bsR3JWMT64dR5C/LzMvq+7Db0DfHHmIzfh85seR53eoHVXDxf8IPEAL501Fb6DYrs7BO8nARIgARJwEgL1dXWoyi+EPiML1VnZMOQVwlAo55JkQ19UDENxKcpKKzShr0hfh6IbbkSNn3/b1ZfJ75vUjLb15taIq64SAH10buKqK+664qrbT7LXhvvp4J3wBBAXJ+Kh/UgBxRV6LF2fhI9/PYg/EztINmLu+k20Uxl8F0kiDyX6jY8L63GvAhNTYhUJ9DgB+/lX3+NL54AkQAIkQAIkQAK9QUC5BH973xl4/Mst4hK83ewp/LY3EyeKS/DiO0/B0P5BZt/X3YZRo4dh1kWn4LcPvmvuqrymHqv++QzO/uQFuDAjYDMXHpAACZCAMxNostgrkWy6KslGya69KP1mOUqy81FSUi7WfLWWJaUoK5MMuyYEwCALrNLEwh4hofAJCUSguO5GxkSg36yR6DcsDgHe7m2FrqFD7eIR1YpY+svuDE30+27TYSiLf2uXIF/J4DslThP+mMHX2nTZnyMSoADoiE+NcyYBEiABEiABByegXILvv3Byo0vwL8gvNS9LcHJWiSYCquQgc8dE9xiFiddeiLQNO5ByMK15zMPp+djy/NuYdPt1zXU8IAESIAEScHwC9TU1Wry9/H1JyE9KRf6805Avgl9BuR76mrpjCzws4SF2Jh87t/SoQrLqmioq0ZSK5afceaW419XCT5JS+IUGwT8yFAESmy8gLhb+Q+PgL/H5/MUy3kMJgQ5QEjOK8Ily8V2biAwbuPh6SQzD048bqFn6zRsXywy+DvAzwSn2HAEKgD3HmiORAAmQAAmQAAm0IqD+OF/35LlQLsF/mOkSrFyFzn3yezzzlxm49uRRrXq0zamy8puv4gFedifKqhpcgdVI65b9hugTpqPfcaNtMzB7JQESIAESsAmBmpJSlKakoUS2YrVPz0Rxlljy5RehoKwaerQQ1PoniJVdSNt5hHYzXl5FpdanyqIb5OOBIG8dAr094OflDv/zjod/eAj8hg+G94hhcPHzazu+g9SoBB5fbUi2mYuvm8TsVV8KqmQeZ04SQVQ4spAACbQl4CJmzA1fK7S9xhoSsBmB9PR0xMY2xE1KS0tDTEyMzcZixyRAAiRAAvZPoKa2Do8t3oL/fGO+S7Ba1fXzR+HJK6ZDWRT2RElbtgpLnn5PciWKZUZjCRBrjMs+fhaeXnzhaGLCPQmQAAn0BgH1alumkmpIMo1yfY24ldahUl+LquwcVH3wMSqLSlBZUobK0kqU1au8t8c+yzuc7yWXAKZcZ9Wr9OOPA2Ix2Lq4eHrCw9sTnrJ5eIuFnq83dL4+8PL3RVCgbKEBCJo0HkHxsfCVWH0uyuLPiYpy8f1511ER/RLx3ebDqLaBi+/UYZGapd85U+MRLjEOWdonwPfv9tn0pSu0AOxLT5trJQESIAESIAE7JaAEvAcumozpkiX4GrEGVFZ+5pQ3Vu3FIUkO8t5NJyHIVzIi2rjELpiPKWv+wMbNic0jqdhPa598DfMevKm5jgckQAIkQAI2IGAQC+zMTFQdEau9IxkozMhGQXYhigpKUFgiyTUWXQx9mInst2Xiars7pcWELPzSKF+SarQQAD3cXCS+ngcCvDzgP2s8AsR6L2BgDPyjI7XNq38U3H28nU7UawGwzaESX9Xv498krt9ve2STuL3mhvdo01kHFSNjgrUMvufNiMegCHGVZiEBEjCbAAVAs1GxIQmQAAmQAAmQgK0JzB8fi58eXogLnl0pWX9LzBpuzc6jmHf/Mnx+53wMjrIgcLpZvbdtNO2xO5F+9l9xtPKYE8WuNZsw5MRNGDR7ctsbWEMCJEACJGAeAbGkq0k8hPKDSShLOoLS1KMozSlAaWEJSiXJhpZ4w9MHejcP0/1JBl6YEgB9fQFxE0Xdsc9t0x0Y1+pE6AsVy7IQf9kPC0eoJJUIlUy6fp4tkmtMuNX4pj50lpZXpol9v+45KvtMm8T0Uzhjw/xwvpbBdwgSBphwxe5DzLlUEugOAQqA3aHHe0mABEiABEiABKxOYFh0kCYCXvHCaqwVCwJzykEJKq4yBH9868lQmf5sWVzlRfKU+/+Bj+5+EXpXt4ahxo/Har0fLhMXJxWAnIUESIAESKAtAc1FV+KoFkoyjQJJqlEqx+WSObdc3HaVy265WPRVPf/ftjeqGhcR8XxMX2quLWnniyMXsfhT2XZNXPeS+HsB4pIbGBqIgH7hCIzth0Bxyw0ZMRj+Mf2Y6b0ZLpBTVIG1+zLxq1j5/SpWfinZ7fBucU9XD31EZFUZfC+dMwyzRvaDqxJwWUiABLpFgAJgt/DxZhIgARIgARIgAVsQCPX3wlf/Og13vPsH3luz36whCiVo+4LHl+OFa2bhirkjzLqnq40Cj5+O4+f+gp+2HAYWLNBcw0rFsOS3g7mYnxDV1W55HwmQAAk4BQEl9Kk4fPmpmSjYexAFh1JRkJ6FwpxC6PPEnfayy4CYhnjgRgv2E5fOLljqNfdRWqodqqQa/pJIQ30h4y2btj9+LLxrDfCMDId3vwhN3AuIi4FXIN1Im/m1OlDJO9YpwU+59Mq2N00sLG1cZkooECX6LZwqGY6ZzMPGtNl9XyNAAbCvPXGulwRIgARIgAQchIDO3Q0vXjsLw8Ui8N6PNornVueuWzW19fi/N9biwNEiPHzJFLhJ9l5blTH334bEDSlI1R8bY09GCYZG+iMuTCxVWEiABEigDxCoE7fagsxc5OzYj5wDychJzUKuEvpyC4AKib1nquTkmhYAlVV1YBBQ2InQ5CEuuP4BCBCX3OAAHwQH+yE4Ihghk8YhSKzGjFx0m8Yf9bemI+7bIaASd2xNzsOqbWn4cUcatsuxOb972+nO7OoB4uJ7iYh+Fx8/FHGRFGTNBseGJGAhAQqAFgJjcxIgARIgARIggZ4joLIi/uP0MRjSLxBXS3KQ0koJAG9GeWn5Lii34Lf/70QJzm6b7Lwqw+O8KYPx0YYj0NfUNc9q9d5sXD59IF2Bm4nwgARIwFkIqIzteWV65BaVI+flN5GbkYvcglLUlJZbtsTcnPbbh0iMN3013IOC4B/sD39xzfUPC4a/ZFwPkCQbAbH9tWM/ScDRUxng25+s41/JL6nC6p3p+HF7GlaL6Fcg1vQ9UZpcfC87YRhmjqCLb08w5xgkQAGQPwMkQAIkQAIkQAJ2T+CUCQOw+qEFuPDZVTic0+Di1dmkV4oFw/wHVXKQUzAwXGI/2aAEShbIORIY/kcR/ZpKmcSy+mlfDk4fE9WnMkA2rZ97EiABxydQX1mJ8t37UOjlj5yAMOSWVstWhYJywzGLsF3JQJmFwl8jGl1WpljueUF9hvp6umkWez46d23vO+ku+Pp5w1PceNWXQCzWJaAsNrel5GmC3yoR/bYk5cAMA3urTYIuvlZDyY5IwGICFAAtRsYbSIAESIAESIAEeoPAyNgQrHlkIS597kesP3BMcOtoLipe0dz7vsZnd8zHlKGRHTXt8rWE/gFIFFHycN4xV7eDu5MwcNdGjL707C73yxtJgARIwNYE9GUVKNq9H4WNcfqK0iRmn2TdLRLBT0tyNHs2MHeu6WlERIgAmGL6WmOtj6EKITWVCAkPQkhsFEKGDERwwjD4jx8Dl5iYDu/lResRyBfxdo2y8hMLv9U70pEnVn89WZSL78WzxcV39lDE08W3J9FzLBIwIkAB0AgHT0iABEiABEiABOyZQFiAN5bdewZufmstPvkt0aypqhedhY+twBd3nYLjR/U36x5LGikLlXkjI8UVOBVVkgUYO3YAy5fjl9oa9B8ep8WksqQ/tiUBEiABaxKorahEyf5EFB5MQWFKOoqOZmvJOIqKyiSsgh4wFV61KcN5rsTqa68oATD5mADob6hERKA3IvqHIWJwLCIShsJ3bAJc4uIAN2ZHbw+jLepVLL8dKfmaS6+y8tt8KPeY5aYtBmzVZ6CE3pg1qh9mJ/THbPm9Oyo2mNacrRjxlAR6gwAFwN6gzjFJgARIgARIgAS6TMBTMjq+esMcjIgOxgOf/WmW61K5uOWe9+QP+OT2kzFvnInMk12eTcON/hKL6uQR4fj28TeArdu0ShWt8Pv7XsCFX/wX7gG2cUHu5rR5OwmQgCMTEJGnrqgI+uxclNe5oDQyGqVVNbIZUKJt6rgGZa++gbojqV1bqYlYfcorN0hcdyPGD0e4ZxUihg9C+NiR8Bk1HNDZJuZq1ybfd+5SWZf3pxc2Z+v9XTL3FpWLuNtDRcXzmz48CnOU4CfbuLhQmybh6qFlcRgScDoCFACd7pFyQSRAAiRAAiTg/ASU1d0tC8ZhaP9AXPvyz1ACX2dFWeddJDEE37/5JJwxaVBnzS2+PiQqAGPrS7GzxZ05Eiz/j1sfwuy3noGYP7S4wkMSIIE+RUBlw83LQ63EX6uI6o9KfS3KZavQ12jHFXJcu3kzag8kos6gR121xNozGFCrV/sa1NbUwCCfYXo5NlRUwVBZBb1cq0FjFvKhQ4FLLjGNNDQU6KIA6FFjQLCfB8LF+jpCYvaF+3sizE8n8fnEom+mWPbhFNNjstamBJTglyKhJ37bndEs+uWWVNp0zJad6yQ+owqrocQ+JfodNyQcOvUzwUICJGDXBCgA2vXjcZ7JJSQkGC3GIH/QsJAACZAACZBAdwkoIW+VSg7yzEqk53cejF5l673s+dV48x9zsWjG4O4O3+b+2U/ejaOX3Ib8/GOJSrYcyMSA517FoNv/3qY9K0iABJyDQH2tiHkHDqFsy3aUJR9BmcTSK8/KRWlBMcrFGq8M7ijXeaEqYQxw0cWmF735APDnJtPXTNY2in/qWkmxyRZaZYgIgB0UF/EB9vfxRHBYIIIly25wfCyCRwxG8JiRWgZeJuLoAF4PXsooKG8W+37bk4G0vLIeG91VvsCaODi82cJv6rBIKKs/FhIgAcciwH+1jvW8OFsSIAESIAESIIFWBMYMDMXPj56Ni//zo8Q5yml1te2pssC55uU1qBLLm8tOEJc1KxYPXx+c+uit+OzmJzTLnaauV3z5Cy4aPhghZ9JapokJ9yTgyAQqyiuR9dtGZP2+CdkHDyMrpxhVtSaC6bkGAD4tVqosAdsr7h7tXem8vqSk/TYhIdo1HwlVEBzki6CwIBH6IhA8KAaBQwchaORQeATKPFnsikCeWPSt3ZsJJfb9KtuhzA5EXhvMPCbUFyePj8XJEjbjeLHyU3H9WEiABBybAAVAx35+DjP7PXv2GM01PT0dsbHWj8FkNAhPSIAESIAE+gyByCAfrPj3Gfj767/hyz+SOl23eE9pbZUb3nXzR3Xa3pIGEWOGY9Zfzsavbyxuvq3azQPfPPUOLo4fCK9RI5rreUACJGD/BJS7Zb7EUzsiVsZZxdXIeusDlOzZD1R3IcZahwJgN17NxDXYG7UICPCFv5d74+aBQG85HheBwMtPgFdwoP3D7qMz1NfUYufhfO1LrE3yRZZK2pGS3YGoawNO7m4umCFx/JToN1+2ETFM3GEDzOySBHqVQDd+y/TqvDk4CZAACZAACZAACRgR8NK54y1x7Q3288Sbq/YaXWvv5PZ312mWgDeeOba9Jl2qn3D5QmQeSsXBNRub7y+qd8d3Nz+Kc754GW7BQc31PCABErA/AnViKZxRXInk3HIk5ZahqKJF+Jo6cb3tivinlllVpS1WuVR661zhI59bPjo3bfMYGALXQbJJIg1XDw+46Tzg4qnT9m5S5yHHHp4e0Mnnhy40GB4hsoWHQhcRBk9/P4nB1sIl2P6QckaNBJSgfCS3VBP5NiWK2JeUo4l/1SqLfA+X/iFi5TcuBvMnxIp7bzQCaOXXw0+Aw5FAzxKgANizvDkaCZAACZAACZCADQm4urrg2b/MkBdrd/z3u5bpONof9N6PN2qB+O86Z4Lk6bBOog7Vz/x//x3F6dmae2DT6GmV9fjl+rtx4scvwYXZMpuwcE8CdkHAUFaOI2v+QPKGnUguq0PlWQtNz2uwxA/dvt3kNVcJA+AbHgK/0CD4RoTCr18E/CJlHxYs+zB4q3oR8bw8XNt+3ow+H/irbCxORaCkQo+tybkN1n1K8BPrvp5M2NESppv8jpwm8fuU4KdcexMGhLT9OWx5A49JgAScigAFQKd6nFwMCZAACZAACZCAEt8euWSKFqD8ySVbzQLy2OItqJRMwg9cNNlqL0MeHu4469m78NnV96Isr7B5HjszyxB6070Y/+rTzAzcTIUHJNCzBFTSjtJ9B5H5505k7ktC1uFM5GQXall6tZmIUIJTTgV0nm0nFh8v/3YBj9oaRIT4ISphKKLGj0Tk5HHwjxsAVzda4rWF1jdqcooqsCetEHvTCrAntQBbknKx/2ghVNiJ3ir9gn0wT6z8lGvvCaOjEeRr4me6tybHcUmABHqUAAXAHsXNwUiABEiABEiABHqCgBIB71l0nFgCuuGBT83Lqvncsh2aJeCTl0+HsiS0RvEPCcRZj9+Kxbc8jpqKBtc/1e+vu9Lh98izGHL/ndYYhn2QAAm0Q6C+vBzViUko3Z+I0kOHUXgkA5nZRcgUoaZMufK2V8QFGEdSgaFDm1uo2HoDJTFCv8BIRN56MUJnTIJrVFTzdR70HQIqs/O+9Cahr3Evol9eybHP+d6iESJhMOZI0o7ZahvdH0OiAq32xVZvrYnjkgAJWIcABUDrcGQvJEACJEACJEACdkjg1gXjNXfgu95fb9bsXvthj2YJ+MK1s+Dm2oE4YFZvDY2iRg3G/DuvxorH3wAkUL8qdS6uWLFyK87s9xHir7usoSH/SwIkYB4BZU5VWor6jAxUH81E2eBhKPcPQmlVDcrEkrdM9qXVBpTml6D03w9CL0l42hYz/n0fPoywiaMxONwXQ8L9EO7veUxIOffMtl2yxukI1NTWITmrRKz6xKJPtr1i1acs/A7nlPSqVV9L0AHeHpg5sp8m+Cnhb1SsxJG00pdYLcfhMQmQgOMToADo+M+QKyABEiABEiABEuiAwA2njtZEwJveWmvWC9v7Px+Ayg782t/mwN1KrnzDT56J/Iw8bHzrC6DRFaxWRMDv0quxIK8cg8J8O1gBL5GAcxNQCTeqJAuqcsOvyC9EdUYW9Nm50OfkwZBXAEN+AaoLCmEoLIahuAQVZZUor3dFmacPDK7yOnO+xM0bZSqbt5u48HoB4u5rbnGVf6D9Q/0weOQgDD59AgKnDTT3VrZzUALq5y9LLEKV0JecXdy4L0FSVjEOZhSjN5JzdIRSWbZPk2y9TVZ+4+PCrPa7qqNxeY0ESMDxCVAAdPxnyBWQAAmQAAmQAAl0QuDKE0dAZQm+4dVfjsX46uCeL9Yd0l763r5xrmTWFBHBCmX6FQtQnp2H3cvWQMwzgIULUTt2LL7dkYGF46MxINTHCqOwCxKwPwK1IrAUFpQgv6IG+fp65JfrNXd7JbRXGupQVV4JvPoqUFYKiBDYcZH4ZV6tYpiJNaDpIq78kh0XRcWmL0utl5cO/SIDERUfg35jRyDyxJnwkgy7LM5FoLauDkfzy0XgE5FPE/rUXsQ+OU+RTf0s2mvxkC+iJg+NaLbwmzQkAp4e1vm9ZK9r5rxIgARsQ4ACoG24slcSIAESIAESIAE7I3DhrCGSedMNV7+0BgZx6+qsfPNnCqqeq8GHt8zTxMPO2nd2XcUlnCeuwHUlJdg7YCQQF6/dUiPiyLIdRzURMDaEImBnHHndTgmIlV1tahqKDyShICkV+WlZyM8uQH5BKQpF8KutqgYuuAAYKT/7rYtOXHTNEv9a39h4XlbWzgWp9vNvEAAD/OEbFAB/ycYb0T9UBL9o9BP33uD4WLhYyd2//Unwiq0JKCu+vJJKpInIl55XJnvZcss0V90kEfyUy66+pvPPfVvP05z+YyTOpBL51DZZtnFi4efjydd2c9ixDQmQQMcE+EnSMR9eJQESIAESIAEScCICC6fG4WOPk3H5C6vNcutauS0NFzyzEp/ePh++XqbiiFkGR4mAJz98C+r3ZmFf5jGrJUNtPb7ZfhRnT4hGjGRsZCEBuyVgMKD6QCIKd+5Fwf4kFB4+Ku7tuSgsqUCRh48W37LduYv4bbqIpZ4m1BWZvtxRraeyBqzXEv74iUjStKmEHf7yb9b/wRsQEBoEX0nIYy2X/o6mw2u2IVAh7uFHlagn4l66thehT/ZNYp+y7rM3V11zSChhb2J8uIh94ZqV36TBEegXwpAQ5rBjGxIgAcsJUAC0nBnvIAESIAESIAEScGACp04cgMV3nYKLnl0F9VLZWflldwbOffJ7uedUBPjoOmve6XUVnH3+qCiIwQoOZLUWAWWsiWKZFOjdaT9sQAK2JFAviTbKxS1SWe8pl121LxA33sLb/4lSt1YuuBCXdp242nZWStsTAOVGzVW3CJ41enjJ5unpAY8AP+jEck8nlnsewYGyBUMnFnyeEWHwi4qAX0wU/ALFss/TrX1xr39AZ7Pi9V4moIS7zMJyzUX3aIHal7U4LtdEv/zS3s+uaw1Mw6ODNKs+zbpP3HpHxgS3/7NrjQHZBwmQAAm0IEABsAUMHpIACZAACZAACfQNAieMjsZX/zwNi57+AaWVhk4Xvf5ANhY+vgJL5Z5gv9biR6e3t2mgRMBTE6K0pCQHs4+JgPqkFHz1/ntY9NTtiIhkHLI24FhhfQISG82QcgQFO/Yid98h5IpFX+7MucgbNFQsqky4TAaHASXHfmYtmZB/UQFCw3wQ6uuJQMlcqpIZeItbvrb3OQdervVw698fiIqCKICWdM22dkqgI3EvQ6z2lOCXUywxIJ2siLE34iMDkDAgBGMGhmqi38TB4QiSn30WEiABEugtAhQAe4s8xyUBEiABEiABEuhVAtNHRGHZvWfgnCe+R1G5xCfrpGxJysVZjy7HN/ecjtAAySzazaKJgKOVJWA9DuVIDLPEROCLL1BdU4Oltz+FRc//E2HhQd0chbeTQCMB+TmrPnwExSL0Fe0/hMLkNBQczUGuitHn6mnsuht2BIgebBpdeETHAqBOB98AXwQH+Wo/v6ExEQgdFI3QwbHwGjhALP0kJp+pMnOaqVrW2SGBKn0NckuqkCvCnRLvVOw9tc9t3OcVV2nnTXV2uASrTikyyBujYkOQINuo2GDteIRY9jFun1UxszMSIAErEHAR835xQGEhgZ4lkJ6ejtjYWG3QtLQ0xMTE9OwEOBoJkAAJkAAJNBLYdSRfs+7Lkxdac4py2Vp27+mIDLJOrD6VIfXbt75BykdLALHGaiq+sf1x/ov3IDiCloBNTLjvmIBKhFAm4kxpVQ1KfvkdJfsSUZSagaLMPBSJ+25FnZglmVNGDAcuvMh0y1WrgPXr4eLnh6DQAARHhSJkYDSChw5C6PB4BMdEWiVpjunBWWsrAuqVsESsoZvdb8U6L0PccpXI1yTsacdyrtr1xeIr8fpGakKfiHxi2dck+IUFMGRDX/x5cLQ18/3b0Z6YbeZLAdA2XNlrJwT4AdQJIF4mARIgARLoUQIHjhZiwWMrJA5VhVnjDukXiG9FBIwONSPumRk9GnbuwjfX3Ys0D2PrKP/+ETj/5X8jMCLEjF7YpC8QUBmsC/OKUHgwBQV6EW2iYjRBRol+alMWpVr54H0g5XDXkISI6HzjTdq9Hm4uCPbVIUTiX6p9aHWZuMF7Iah/OGOXdY1ur9xVXKFHhkqaoYQ9cbtt2B87V0k0yqr6prDX+oH0lyQcyn03PioAcREBGBETpFn1DQz3h7LcZiEBRyTA929HfGrWnzMFQOszZY9mEOAHkBmQ2IQESIAESKBHCSRnl2guvirLpDllUIQ/vr3vDKiXQmsU/abN+Oqmx5DhZmxZGCgWVoteug8B/cT1kqVPEKgTka8sIwvFB5NRnJKO/LQsFGblo6CwDCWSbbe+rPFndNQo4PzzTTP57ltgy1bT10zUukjMvaAQf4RFhiA8Lhrhl1+IUH8vBEg2XZW9msV+CSiXXBVLT2XEVcLesUy5ZZrYpwQ/c2Kd2u8KrTsz9eMcK1/eKIGvQegLbBb8BongR9dd6/Jmb/ZBgO/f9vEcensWFAB7+wn00fH5AdRHHzyXTQIkQAJ2TkC9OJ8pcf5SRAw0p8SE+moi4OCoQHOad9qmaut2LL3pUWTDOFC8b5A/Fjx5O6JGD+20DzZwDALKXbdIXCkLNmxB8a59KD6ajeKcAhQXlkqOjUrUGjrPUK0ly/jrX00veN06YPXqNtdcPHXwDw5AkAh9QbH9ED5kAMJGD0fY4AHQSUIOFvsioFxzVQbcJlEvNVeJfLLlidCn7cucMolGd5+CcteNDfNDjGxxypqv0aJvcGQgBsqXN578We8uYt7vYAT4/u1gD8xG06UAaCOw7LZjAvwA6pgPr5IACZAACfQegUyxljlL3IEPZhSZNYkoiQX47X2nY3i0dWL1VW7fiS9vfhx5tcZijIePN07913UYMneqWfNiI/sgUC9xHUvyi5EPD+SX65FfVo28Mj0K5FjFf8TSpcCuXV2brCTcwL/+KfcaW+gpt13/5EQErFimuY8HShKO4GHxCBo9AgHxA+Dubvyz1bXBeZe1CJRW6nE4p1T74qFpn5JTAk3sky8lqgy11hrKKfpxFRO+/iE+mrgXI5Z86osYJfQpqz61V3VB4q5Oy1WneNxchJUI8P3bSiAdvBsKgA7+AB11+vwActQnx3mTAAmQQN8goILdq5iAe9IKzFpwmGQFXibZgUcPDDWrfWeNynftxRJxB85vHZLLwx3/396dwElx3Qce/w8Mx3AMc3CL4QYJocPhkhLb0QHIqziSvQmHlWS9iWOJdbJZO4kzRE7ijXOxYDvOOnG8gJ04q/gQkHwix1lbAoyiJIojATqRQOIUwyGOObhhgNn3r9Eb9fRUd1dVd3XX8XtS091Vr169+r7q6e5/v1fvfT/3QZn38aV8uS2EWKH1l4+fkOPPbpejL+6WY/sOy7HjbXJl8lSRj+SYVOOZZ0S2bfNd2+GXz0tDTbXUf2mN1I6sM0N1B8hwc6s1y2pM7yaCH75JQ9tAe3seMxNqvBvc6x3s0x5+pHcFGoYNcoJ4401g7wZzPT7bk88G+MbVD+H6k+9y8QgBTwJ8//bElPhM1Yk/Qg4QAQQQQAABBBDwKTBqRI187/c+KD+z6vvywoFTBbfWGYQ/aIYO/8Oj98uPTR1VMH+hDENvvVmW/dWfyPc+8Vk5fC5jKKgZFvqvf/OEtO3eKwtX/Zb0HzigUFGsD1Hg+oUL0v4fO+Xt51+So7sPyNHDJ+W0GdbbldUjT460mFro5By9e+o5VRs5MmcNB5htRphgSH3dMGkYUy/1N4yRxqlNUjdjigycOV2khtlHc+JVYMWVq9dkz5F2efngaXn1rdOy91iH6dV3Vg6dPCuX6cXntIgG927QwJ7ppafBPX2sk25orz291+c1A/mKWoHTl10igEAKBOgBmIJGjuIh8gtEFFuFOiGAAAIIZAu0n78sS1b/QJ5780T2KtfntTUD5O9++365Y+YY1/V+F15rbZMffrxZXj3Rd3biplHD5KfXNMvgGdP8Fkv+AAKXLl2RUy++Jid3vCynXt8npw4dldOt56Szqp+30n79UyK1fa8VObSjVer/ep3UjqqXEWNHyghzXb4RUybICDNkd8jkiVJVTTDEG3B5c+nfhlcPtcrLh07LK3ozQb/XW9pEZ2lOW+pvZsYdVVsjo0YMNjdzbx6Ptvd1Ne8E+roDfEywkbazg+ONigDfv6PSEpWtBwHAyvqndu/8AUpt03PgCCCAQOwE9Ppcy9Y8Kf+2+7inuuvF5zc2/yd5383jPOUvlKnr8mXZ8Ru/L//60qHePcvMddyG/coKueuu22TG6GEM+SwE6WP9ZdOT68SZy3Lc9Ow83nFJ3jb3Z595VuT73/dRSu+sgx9aJo13zJGRwwZK49BB0vjOfc1ArsfXWypaz3QSDp2AQ4N82rPPCfaZx4fMZBxJThrU06G2Y+uHOsE8DejppQ6cwJ55bAN8GvCrN+dzP5OfhAAC0RXg+3d026acNSMAWE5t9tUjwB+gHgoeIIAAAgjEQODC5avy0Befkm2vHPFUWw3qfOs375OFt03wlN9Lpr1f/Yb84FtPSWfXO1+0P/ABkTvvdDad1DhE7r1ptNQNMZNCkHwJ6PXZTh05Iceee1GOv/qmvL3wp6T10lUxcZ/eqcUM4/3613svy/Gsf/9+MnpkrYyfMl7G3zpDxtw5R4bNmCpV/Tz2FsxRLovDE9BA37G2C/KmmfznTTN0VycB2vVWqxPwazcTtiQp2eBe9tDbzKG5Y0zPvf6cr0lqdo4l5QJ8/075CfDO4TOmgPMAAQQQQAABBBAoIKDD1h7/9H3y0f+9VX6w860CuUUuXrkmyz//pDz264vk/jmTCub3kmH6J35Rls6+Sb676utybvRYkTvenQ340OkL8ti/H5J5kxtk/uR6LpCfB7SzrV2O/+gFOfrSbjmyt0WOvW0m6WjreHeLabeLjHEZwj3WmGtAxMzq2yuZGUmHNoyQsTeMlPE3TZFxc2+RMXNvlerBg3pl40k0BM5f6nSuzadBPhvs02v16e2cWZeEpDOTazBPJ8+wQT2dKdcG/LT3XrUJUpMQQAABBNIlQA/AdLV3ZI6WXyAi0xRUBAEEEEDAh4Be5P+X/3ybPPHcAU9bDTBfsv/6f9wrDy6Y4im/l0xnT7XJllePycFO999x6853yD2HX5JJKz4qVQNT3CPQ9Oi6dOSYdLz0mrS/tkdO6CQdLSfl7XNX5Fq+6/Y98IDInDmuTdF/3VppaH1bRjaNlVE3TpGR75ktI+/4MScA6LoBCysiYIftai++7kCfBvjM46MdcqT1fEXqVKqd6o8Rzqy4ZtKM7nszgYYJ9NllGuQbZGaBJiGAAAKZAnz/ztRI72MCgOlt+4oeOX+AKsrPzhFAAAEEihC4ai7yv+KrT8vGf9vnqRQdbrfuV+6Wpe+d7im/l0wa4Nh74pw8veeknDPDk3ulv9sk8uouqR/UT2YtulNm/fJDUju6oVeWpDxRh/Omt2WHmXm3/cIV576jw8zMu+rz0n66Qy6Zdb7TXBP8++kHzPDHKnO9vkEydsQgGaPXPhs+WBqqrkr/YUN9F8kG4QlcMz0ytffeiwf0Gn2n5CUza7dOzBHXYbt6DdHJo2tlypjhzv1EM9nPxJHDnSDfhJFDnevtVZlepyQEEEDAjwDfv/1oJTev+0/HyT1ejgwBBBBAAAEEEChKQIfOaUBvsOll89jTbxQs65q5xtzDX3laRpgL5d/3nqaC+b1k0ADADBMgmGiu/fej/a3y4lvtct0Ew+TYUSf4p2W0Xb4uz/7Ts/Ls5u3SdNNkmfVTd8n0D7zP9A6K+Me/ayZo19Eh10+flsumt+PFU61y0QzRvWRuZzvOS/uZC9JhZmA9M2eBdEy70cy6mn2xPnPwZy+L+Az+1V29KONG1cqYsSbot6BJRpngX99hkgzr9XJ+hpXncuc1Z6ZdDfK9ZCbk0IDfq+Y6fXqNzjglHaJrA3xTxtSaQN9w89wE/cy9TqpBgC9OrUldEUAAgfgIRPwTYHwgqSkCCCCAAAIIpEdAL47/5w//pAw0M/F+fcvrBQ9cg3O/9OWtsvlzD8rNTaXrjTfI7P+umaNk1rjhsm33CTn62Na+dblyRQ6//IZz2/YX35TpM26QG98/Vxrff4cMGzMq1Nk7u0ww7/z5S9JxvZ90XOiUs+Yaaxqwu2p6bV3V+699Ta4dPiJXL1yQaxcuSufFy3Lx6nW5WD1QLptbl+Tp6VRrrtM3eWbf49Ulo0eLnMs9TLvK9O4bpddJmzBKbpg1VcbPv1WGznmPSJqHTLtLVmypXo/vVdOTTwN9Tq8+c/96S5s5f7KuwVixGubfcYMJIN82uVFmjq9zgntT3wn0TTK9+3QYLwkBBBBAAIFyC/DuU25x9ocAAggggAACiRDoZ4JIf/qx90rNwGr5i//3SsFjOmuGqS5b86Rs+6MPO718Cm7gI4MOT102r0l2/ezd8vw3z0r70ZOuW3eeuyCvv/Cmc5Mvf0f6NTbI8LGjnCHCtZMnSO0975fawQNML8F+0t/0MtRhsPbW75oZ/nrxolSZYF3n2XPSeeasdJ48LZ2nTssV00tPJ9fQ2znTS++M6aHXYQI4Zzq7pPPue0Xuvtu1PtLSbnot2gk4zMfSar25Z+2ztK2tz6KeBaNMAHB/dwCwygRJa+trpW7cSBk7faKMf88sGbfgdhk0bEhPdh5UTkAn5dhzpF12H2lz7jXIt9vcDp0823cm5spVM++etffebZMa5dZJDXKrCfrpY70WHz358rKxEgEEEECgzAJeP2KVuVrsrtQCK1eulMbGRmlubs5ZtObZv3+/c9NMK1askEceeSRnflYggAACCCCQdgH9gv/Hv3CHDB7YX77wDy8W5Hjr1Dl56ItPyfd+94Nmm9J+DNO63PKhhTL7wXvl2LZn5bVvbJQ33jwql/sPyFmv66dbpUNvu0yW8eNFJt7snveb3xTZu9d9Xc6lZpZR7cB3Ps+kCzU1ObcuuCIjAFhtApW1NQOkbsgAGaH3998hI+ZPkrpbZ0ntzKnSP+rDngsebPwzaI8+J9D3ToBPA37dgb5zsTk4nVzj5gn1TpDvVhPk00Df7IkNUjskxZPtxKb1qCgCCCCAQGk/eeIZOYH29nZZtWqVrFmzRlavXp2zfnPnzpX169ebSe+6Z73bsmWLLF68WDZu3CibN2/OuR0rEEAAAQQQSLuABt4+u3y+c03AP9q4oyDHc2+ekF9d94x87VfvCaWHkNZn/L3vdW53H26R/Y9tktd/+JwcvNgl1/PNfmt+KMyZrgeYTMMWljcAONjmcr/vb2YzNUHCgYMGyGBzG2J6J9bVVDvXU6y9YYzUzZvgBPyGmSGVetw96UbTA5BUEQGdmGXf8TPy/N4Tsstcn0979O0xNw1+xyXpqTTRzKw7fVydGbJvAn4a7DM9+2aY5wOqTWCbhAACCCCAQAwFCADGsNG8Vnnp0qWiAUAN5OVLGhzU3n42+Kd5Fy1a5AQMtVfgunXr6AmYD5B1CCCAAAIIGIHmn5njXBPws99+rqCHziCswYTf/tnuH94KbhAwQ3XTBJn5mU/JzEfNbLkv75I9//S0vPHCHjn1thmym30ptbwBQJeJNrzW6fw5sT30tHfeYB1ebK6hqMuqf+IW6T+pXqprh0t/cxswolYGm+G6NY31Mnhkg9TUDnUCq30n4/C6c/KFLdBhZl/eYYJ9GvB73gS3t5v71nNmEpYYpBGm5970cSNkxnhzM69Hez91rDkHS9xDNwYcVBEBBBBAIOECBAAT3MDae0+TBgE1kJcraQ+/7du3y7Jly6Surq4nmwYBNel6hgL3sPAAAQQQQACBnAKfevB2aTl9TtY99VrOPHbFn2za4QQflvzENLsovHvTpWno7bfIHL2ZvXRdNpNtvPCynHlup5zZd1DOtByXMzPHyZmRQ52JOq6YCTqum9mLr5neXDqL8fXrV+WamZLDTspRZR4N7LouA4cMlgFDamTAsKEyYPhQGVg7TAaZQN6IxloZMdoMjRw7UkY0jZdhTeN699CzR3rTg/YR9zEQuGYmb9ltrtuogb7n977t3O852h7pa/XpNSz1Gn1OoE+DfT2BvhHMuBuDc44qIoAAAgiUToAAYOks85a0adMmWbt2rRNg04CcBtoeffTRXr3u8hYQ4sqpU6eKDvnNTjYYqPUlIYAAAggggIA3gf/10R93hkBufbml4Aaf+D//LBNHDZMFM8yMtmVMVYMGyZA75zu3sV722/SwdHV2StfQoXJ96DDpbwJ+WgYp2QInOy46Pfps774d+06KXssvqkl79OlQXb3dPnmkuTU6w3gZthvVFqNeCCCAAALlFCAAGFBbg2IPP/ywc908GyjLVZT2vtMA4I4dO3p62O3cuVMWLlzobL9kyZJcm5ZluQYm9ZadtI6aMocGZ+fhOQIIIIAAAgj0FtDhqt/45EJZ/NknzMym+X9Eu9x5TR76wmYzM/CHTCBweO+CovRs+nRnPg+9yh5XQItSw5SmLlevXTdB6w7nen2vHe6enOPFA6fk4ImzpdlBCKWMHlEjt0/pDvJpsE+DfpNHD3fvaRrC/ikSAQQQQACBuAkQAPTZYjpLrgbzdGINDQLqxBr5AoDas06vsZcZ/NNdalBNewDqdfrazCx2+crwWcWSZddj1KT1JCGAAAIIIICAdwHtibSh+QNy7+89IafOXMq74ckzF2X555+Spz73gAyvYTbRvFisLEpAh/BqUE9n39VAn07Q8bq5f/NYu1y5mn1RyKJ2VdKNJ5lesre906NP799jAn9j64eUdB8UhgACCCCAQNIFCAB6bGEN4mlATK+Lp5NqeB0Wq5NraHDPrRedXldPewdqT0J7vT6P1Qk9mx6v9gDMDlyGvmN2gAACCCCAQEIEJo+ulW//5n3ywT/8XsHgyq7DrfKxP/+hfOfT9zkTZCSEgMOokIDOxHvYzLprA3zOvc7Ge6RNLl4pYkbnkI+ncfhgmTWhXm68oU5mmdl3b7qhXm6Z1CANwwrMFh1yvSgeAQQQQACBJAgQAPTYis3NzaI3mzRwVygIqL0F9ZZrAg0NDOr197RHoVsqVH72NqXqRai9FvX4dPIPt8Bl9n55jgACCCCAAALuAnfMHCNfWXGXPPyVbe4ZMpY++cJh+Z2//Q/RawiSEPAioBO1HDppevSZwN4eMzmH3uuw8zfMLcrX6htVWyM3Tagzt+4gnwb99PlIs5yEAAIIIIAAAuEIEAAMx9Up1U6skS8wpwFADRJqXjvrrm6sQ4PtNfi8VnHfvn1es+bMp/vUfWvPP4J/OZlYgQACCCCAgGeB5e+b7gyxXPP3LxTc5i+//6qZpXSE/PLimwvmJUN6BPQafQdOnHk3yGeCfdqb7w0zA2+Ue/QNrxngDNfVAF93kK874NdYS4++9Jy9HCkCCCCAQFQECACG2BLag65QssFBDbxlBgArMSRYA5E2+KeBSZt0OHBm70e7nHsEEEAAAQQQ8CbwmZ+dK3uPdsjf/2h/wQ0+/Y1nZerYEXLPrTcUzEuGZAnopDA6Gcce04NPb7ZnX9Sv0aetUGVmiNEg3/zpo2X+DHMz9zPNUN7+/Zg2JllnKUeDAAIIIBBXAQKAIbacBtQ0NTY25txLQ0ODs64Uvfdy7sTDChv806BlZvBPl1e6bh6qTxYEEEAAAQQiLdCvX5V89RN3OcM1d+w7mbeu18ywzo/+2RbZ8gcPmmuh1efNy8p4CrSdu+z03tOhutqLb4+56f3Bt8/KdXP9vjgkvV6fDfTp/Zypo6TWTH5DQgABBBBAAIFoChAADLFd7DX8bC+/EHflqejTp0+75tN66sQmWk+dtMSm1tZWZ3iyznTsN7W0tOTd5NixY3nXsxIBBBBAAIGkCdQMrHYm+bjnd/9BWk6fz3t4HReuyNI1T8q2P/ywMFwyL1VkV+pEHEdazzs9+TS4p8E+7dWnj090XIxsvd0qVt2/ypmFd960USboN8YJ/E0ZPdz0+jPd/kgIIIAAAgggEAsBAoAhNpMG0LwmP3m9lqkTeejQ4u3btzub6FBevdag9vBbv369E/DTFToLse2t6FZ2Zo9At/Vuy5qamtwWswwBBBBAAIFUC4ypGyIbfusDct/v/2PBSRoOnjgrP/+lzfLEZ35KBg3on2q3KB9867lLZtjuGdl7rMMZvqv3+83zN02g7/zlq1Guumvdhg6qdibn0OG8N09scIby3ja5UTSATUIAAQQQQACB+ArwTh6RtrO9BUtZHa899ypxvcFSHidlIYAAAgggECeBWyY1ytd/7R75yBeekkKjPZ/dfVw++bV/ka/+t7vobVXBRtYZdfeZwN5ec32+nnsT5NPHrWY4bxyTBpVvMtfo05l4b27SWXj1vkGaGoeJDlknIYAAAggggECyBAgAhtieen0/r4G9qAwTLhXH4cOH8xalQ4AXLFiQNw8rEUAAAQQQSKrA/XMmyR//wp3ymcd+VPAQv/XMm1Ldv5/86cfeKwOr6QlYEKzIDNpz76kXD8vulrZ3evWdkePtF4ostXKbDzDnzozxI7oDfCbIN8sE+2ZNaJApY4YzQUflmoU9I4AAAgggUHYBAoAhkvsJ6tnJQEKsTlmLnjBhQln3x84QQAABBBCIm8Cv3n+LmRm4Xf5q6+6CVf+/2/Y4wai//fVFMrK2pmB+MvgTuHTlqjzx3EH5662vi/a6jGMaWG0CfePq5MYJplefmTzmpnfup5kZpQeYdSQEEEAAAQQQSLcAAcAytH++XoD22n9+goVlqDK7QAABBBBAAIGQBXQChc//4ntl/9tn5OlXjxbcmwamdAKRx801BHWoJql4gTePtcs3TAD2m//8RmyG8g42Q3dvNEN3dYZoG+TToN+U0bVOT9HiVSgBAQQQQAABBJIoQAAwxFadN2+eMwlHrtl3ddc2ODh//vwQa0LRCCCAAAIIIBBFAe2Z9TefXCSL/ucTZtKIjoJVPHTynCz67Hfl6//9Hrl/7qSC+cnQV+DK1Wvyj8+b3n5bXpdnXjvWN0NElgwbPMAZuquTcWiPPtuzb+KoYQzdjUgbUQ0EEEAAAQTirckdzwAALC9JREFUJEAAMMTWmjt3rlO6DfK57crOvrto0SK31SxDAAEEEEAAgYQL1A8b5MwMfO/vPSFtHiaU0AkpPvLFp+RzH1kgn3zgNiYH8Xh+aE/Lb5ghvn9revudOnPJ41bhZxtrZoaeaa7RN9ME+fRee/ZpD79x9UNo2/D52QMCCCCAAAKpESAAGGJTL1u2TFasWCHbt2/PuRcNAE6dOlWSPgR49uzZvQw6Ozt7PecJAggggAACaRbQ67R96zcWy4dXfV8ud14rSKGzB3/228/Jay2t8uWPv18GD+QjnRta59Xr8k87tLffbtn26hG3LGVZ1t/MqjtlTK0J8OnQ3Trnfqa5nzFuhNQNHVSWOrATBBBAAAEEEEi3AJ8WQ2x/DeotWbJENm3a5Az1zQ7ybdmyxdn7ypUrQ6wFRSOAAAIIIIBAHATeO2ucbGr+gPyXP9sq7ecve6ryd/5lr+w7fsYJHo4xPcnSnnQyj7fMMOmDJ8/Kj/Ycl8ee3iNvt18sG8vI2sGiwdzpJrA3bWxt96QcJtCnwb9B5tp9JAQQQAABBBBAoFICVV0mVWrncd2v9tqbNm2aU/3NmzdLvuG7Ovx3ypQpor0B165d2+uQ7RDhHTt29FqehictLS3S1NTkHOrhw4eFWYPT0OocIwIIIICAF4G9xzpk+Ree9HRNQFveDQ1D5Tufvk9unzLSLkrk/fXrXSagd0EOnjgrB06ckUPmXh8f1Mcm8He09Xzox11bM0CmOQE+G+iz97X05gtdnx0ggAACCAQR4Pt3ELXkbUMA0GObam89Hc5rr9mXvZkO49X1zc3N2aucbRYvXuwECjWPzvy7evVqJ9/GjRsTP/y3D4hZwB8gNxWWIYAAAggg0C2gPQB/6cs/lK0vt3gmGTKoWtZ+4m750B1TPG+TnVGvL7jrrVZ5+eBp2XOkTS6aHnWDBlSLlj14YH+pMY/1vvt5tdToMjP8WG/OcnM/yCyrMv91mf+c/5277t+b9Wdn/e1Zn+V+3CXXTKDveJsG+s68E+DrDvS9ZXr2XfIwRDr7uII812O797YJcqMZttvdo6870Ke9/HQGZxICCCCAAAJxEeD7d1xaKtx6EgD04au9+bKH8drN862zeTSIuHPnTqcMnSF4zpw5dlXq7vkDlLom54ARQAABBHwKXL12XX73m/8hf/n9V31t+TtL50rzf/6xvEEqDcIdMwE2DfS9cqj79rK5P2AmytDAXJrTTWbI7scWzZLl75shOkELCQEEEEAAgbgL8P077i1YmvoTACyNI6X4FOAPkE8wsiOAAAIIpFbgb364W37jr/5NOk1A0Gv6mR+fKn+54i6np55OhPHG0faeQJ8G/DTw1+phxmGv+4t7Pr0+34dNz8mPLZwld944Jm/wNO7HSv0RQAABBNInwPfv9LW52xEzCYibCssQQAABBBBAAIGICPzXe29yhqD+wpe2yOmzlzzV6u//fb8zlFeH5r52uFWumCAgqa/AjPEj5JdM0O+h98+QxuGD+2ZgCQIIIIAAAgggkBABAoAJacioH8bs2bN7VbGzs7PXc54ggAACCCCAQG4BnSF42x99SJZ//il5vaUtd8aMNXuOtGc846EVGFjdTx5c0N3b772zxtLbz8JwjwACCCCAAAKJFiAAmOjm5eAQQAABBBBAICkCk0fXyubPPSgf/8o2+cHOt5JyWGU7jmlja53efj//kzOl0UzkQUIAAQQQQAABBNIkQAAwTa1dwWPdtWtXr71nXoOg1wqeIIAAAggggEBOgdohA+Xbv7lY/uDx7fKl776UMx8rRAb07ycTRw0z1/QbKx9533T5ydnj6e3HiYEAAggggAACqRUgAJjapufAEUAAAQQQQCCOAv379ZPPPbRAbppQL7+27plUX99vVG2NTB4zXCaP1lutTB5l7p3ntTK+YYioFQkBBBBAAAEEEEBAhAAgZwECCCCAAAIIIBBDAZ24YuqYWvm5L26Wk2culvwImkYOc8rX2YcvXr4qF69clUud1+SCeXzJPL545ZqvmYmDVLBmYH+Z5AT1THAvK8g30SwfNnhAkGLZBgEEEEAAAQQQSJ0AAcDUNTkHjAACCCCAAAJJEbhj5hh5+o8/LA994Sl5+dDpQIelQ2Vnmd6Et0xqkFsnNcptkxtl9sQGaRhW+Dp5VzU4qIFBEwzUe/tYK1JVVWVu5j7jsbM847nJ4eTRTPaxs53JM3RQtYwaUcOwXUUjIYAAAggggAACRQoQACwSkM0RQAABBBBAAIFKCmhPvSd//wFZ8dWn5bvPHcxblbqhg+Q2DfSZIJ8G+/R24w11MrC6f97tcq2sNsHD4TUDzS1XDpYjgAACCCCAAAIIREGAAGAUWoE6IIAAAggggAACRQgMNUNhH/vUIvne9oPy5e+9Im+3XzDXv6uSWyY2Oj37btNgnwn63dAwlB51RTizKQIIIIAAAgggEFcBAoBxbbmY1Xv27Nm9atzZ2dnrOU8QQAABBBBAoDgBHTr7wPwpzq24ktgaAQQQQAABBBBAIGkCTI2WtBbleBBAAAEEEEAAAQQQQAABBBBAAAEEEMgQoAdgBgYPwxPYtWtXr8JbWlqkqamp1zKeIIAAAggggAACCCCAAAIIIIAAAgiUXoAegKU3pUQEEEAAAQQQQAABBBBAAAEEEEAAAQQiI0AAMDJNQUUQQAABBBBAAAEEEEAAAQQQQAABBBAovQABwNKbUiICCCCAAAIIIIAAAggggAACCCCAAAKRESAAGJmmoCIIIIAAAggggAACCCCAAAIIIIAAAgiUXoAAYOlNKREBBBBAAAEEEEAAAQQQQAABBBBAAIHICBAAjExTUBEEEEAAAQQQQAABBBBAAAEEEEAAAQRKL0AAsPSmlIgAAggggAACCCCAAAIIIIAAAggggEBkBKojUxMqkmiB2bNn9zq+zs7OXs95ggACCCCAAAIIIIAAAggggAACCCAQjgA9AMNxpVQEEEAAAQQQQAABBBBAAAEEEEAAAQQiIUAPwEg0Q/IrsWvXrl4H2dLSIk1NTb2W8QQBBBBAAAEEEEAAAQQQQAABBBBAoPQC9AAsvSklIoAAAggggAACCCCAAAIIIIAAAgggEBkBAoCRaQoqggACCCCAAAIIIIAAAggggAACCCCAQOkFCACW3pQSEUAAAQQQQAABBBBAAAEEEEAAAQQQiIwAAcDINAUVQQABBBBAAAEEEEAAAQQQQAABBBBAoPQCBABLb0qJCCCAAAIIIIAAAggggAACCCCAAAIIREaAAGBkmoKKIIAAAggggAACCCCAAAIIIIAAAgggUHoBAoClN6VEBBBAAAEEEEAAAQQQQAABBBBAAAEEIiNAADAyTUFFEEAAAQQQQAABBBBAAAEEEEAAAQQQKL0AAcDSm1IiAggggAACCCCAAAIIIIAAAggggAACkRGojkxNqEiiBWbPnt3r+Do7O3s95wkCCCCAAAIIIIAAAggggAACCCCAQDgC9AAMx5VSEUAAAQQQQAABBBBAAAEEEEAAAQQQiIQAPQAj0QzJr8SuXbt6HWRLS4s0NTX1WsYTBBBAAAEEEEAAAQQQQAABBBBAAIHSC9ADsPSmlIgAAggggAACCCCAAAIIIIAAAggggEBkBAgARqYpqAgCCCCAAAIIIIAAAggggAACCCCAAAKlF2AIcOlNKdGDwNWrV3tyHTt2rOcxDxBAAAEEEEAAAQQQQAABBBBAoHQCmd+5M7+Ll24PlBQHAQKAcWilBNbx5MmTPUe1YMGCnsc8QAABBBBAAAEEEEAAAQQQQACBcAT0u/jkyZPDKZxSIy3AEOBINw+VQwABBBBAAAEEEEAAAQQQQAABBBBAoDiBqi6TiiuCrRHwL3Dp0iV55ZVXnA1HjRol1dXR74yq3aZtb8XnnntOxo0b5//A2aKiArRhRflLsnPasCSMFSuE9qsYfcl2TBuWjLJiBdGGFaMvyY5pv5IwVrQQ2rCi/CXZeRzbUIf92lF4t956qwwePLgkFhQSL4HoR13i5UltPQroH5z58+d7zB29bBr8mzBhQvQqRo08C9CGnqkim5E2jGzTeKoY7eeJKdKZaMNIN4+nytGGnpgim4n2i2zTeK4YbeiZKrIZ49SGDPuN7GlUtooxBLhs1OwIAQQQQAABBBBAAAEEEEAAAQQQQACB8gsQACy/OXtEAAEEEEAAAQQQQAABBBBAAAEEEECgbAIEAMtGzY4QQAABBBBAAAEEEEAAAQQQQAABBBAovwABwPKbs0cEEEAAAQQQQAABBBBAAAEEEEAAAQTKJkAAsGzU7AgBBBBAAAEEEEAAAQQQQAABBBBAAIHyCxAALL85e0QAAQQQQAABBBBAAAEEEEAAAQQQQKBsAgQAy0bNjhBAAAEEEEAAAQQQQAABBBBAAAEEECi/QFWXSeXfLXtEAAEEEEAAAQQQQAABBBBAAAEEEEAAgXII0AOwHMrsAwEEEEAAAQQQQAABBBBAAAEEEEAAgQoJEACsEDy7RQABBBBAAAEEEEAAAQQQQAABBBBAoBwCBADLocw+EEAAAQQQQAABBBBAAAEEEEAAAQQQqJAAAcAKwbNbBBBAAAEEEEAAAQQQQAABBBBAAAEEyiFAALAcyuwDAQQQQAABBBBAAAEEEEAAAQQQQACBCgkQAKwQPLtFAAEEEEAAAQQQQAABBBBAAAEEEECgHAIEAMuhzD4QQAABBBBAAAEEEEAAAQQQQAABBBCokAABwArBs1sEEEAAAQQQQAABBBBAAAEEEEAAAQTKIUAAsBzK7AMBBBBAAAEEEEAAAQQQQAABBBBAAIEKCRAArBA8u0UAAQQQQAABBBBAAAEEEEAAAQQQQKAcAgQAy6HMPhBAAAEEEEAAgQoIbNq0SRYvXixLly7tud+5c2fRNQlabtDtiq5wjAsIy2zNmjUybdo0qa+vd+71HMl3buzfv1/mzp3rmqe9vd05x/JtH+MmKLrqpW7DYtui1PUpGigGBZTaTF9vK1eudF5P+vrxmopte6/7IV9hgaDnRNDtCteIHAh4EOgiIYAAAggggAACCCROoLm5uWvq1KldbW1tPce2Y8eOrrq6uq6NGzf2LPP7IGi5QbfzW78k5Q/LbMmSJV1atj039LzQc8V8dehavXq1K6Hm0fV6W7RokbO95tWy7DLXDVO+MIw2LKYtwqhP0ps4DLM5c+b0vJ7s6yrX/ebNm3uIi2n7nkJS+kD/3unfK/t3rxiGoOdE0O2KqSvbIpApIJlPeIwAAqUV0C9Y+iFZ32zsvb5x50tBtslXXhrWldrMfjHStvL6IWHfvn1d+mHOrX3tBw63dWloHy/HWOo2LKY9Sl0XL8efhDxhuWmAQQMTGrTSe3195notFdPuSWiDzGPQL4z6ZdLNSk11nde/b6UoN6z6ZNYtaY/DMtMvoI888kgfLj0fbABCX8/ZSc8luz77Xj/jkPoKhNWGQdsirPr0PfLkLAnLTN/Tsl9Hbs/1fS8zBW37zDLS9lg/G+j7njXX58WkoOdE0O2KqSvbIpAtQAAwW4TnqRawgZogX4qy4YL8whNkm+z9pu15GGZBfpXN/EBGzwh/Z2EYbRi0PcKoiz+NeOYOy80G4+3fZG3XfL2UgrZ7PNXz19oGTd1y2UCP+vpNQcsNup3f+iUpfxhm2vb6JThX0teyBiHc8ujrS5fre6T9Iq2P3YKFucpP2/Iw2lANg7ZFWPVJcruGYWZfh/ra0aCQ3rRNM2+6TF9nuiwzBW37zDLS8tgG/fS9bu3atT0B12IDgEHPiaDbpaW9OM7yCBAALI8ze4m4QBR+GeJXIf8nSVhm9ouN2y+xmcv0jdwm/UCWuS7zMT0jrFLf+7DaMEh7hFWXvkedrCVhuWkgwm8vpSDtnqzW6D4afU/Tv0FufvZ49e+X5vGTgpYbdDs/dUta3rDMNOCQL/BrX896bmgdMpO+vvJtm5mXx12OXxivQ7UN0hZhnVNJbuuwzLT98v19VlMNXuktOwVp++wy0vrcfr7P/tvmxyPoORF0Oz91Iy8CXgSYBMS8M5PSK6AXwNaLX+tFeM2bgvi5CG8+tRUrVjjlmV/G+2Qzb/jOsocffrjXuiDb9CoghU/CMLPngPmSJOaLkHMzH7Yk86bL9XzRPJlJl2mb670mfWzLyczH43cFwmhDW7rf9gizLrZOSbwPw01fh+vWrRPzi30fMm1XExx0lmf/HdWFftu9zw4SsGDLli3OUdi/RW6HZAKAzmKb1y1P9jKb12+5QbfL3n+anodl9vzzz4tegF4n/3BL9rzQdUzo4SbkfVlYbei9Br1zRq0+vWsXzWdhmelEHjo5U66k6x9//PGe97pc+VhefoGg50TQ7cp/hOwx6QIEAJPewhxfXgH9Emm64TtBGg3M5ftSk7egjJX6pq23ZcuWZSx996HuQz9g6wdwm4JsY7dN631YZrbtTC8HMT33nJsG8jJv+qXo0UcfdZZl+mt+DRTqOWV+gXEeazkkd4Gw2tDuzU97hF0XW6ek3Yflph+Utf1yJfvFSQOFWofM5KfdM7dL0mP9kaJQsu93foI8QcsNul2hY0jy+rDN9HXj1vb2RzC1tedIkp3DPLaw29Bv3aNWH7/1r0T+sMz0s2G+z4c6Q3D2j8yVOH722Vcg6DkRdLu+NWAJAsUJEAAszo+tEegjEOQXniDb9NlxyhaEZaZfimxwwY1U1/OrrJuM/2VhtaH/mohEqS5B6l+pbcJyo5dScS1qg6KNjY05C2poaHDWmWFJOfNkrwhabtDtsvefpudhmS1fvtwJ7GmgXH/Yyk52v7o8szdgZj4NEmrPXw1S6Pul3tyCiZnbpPGxtSz16zDT0k9blKM+mXVLwuNKmOnoJH2d5nr9WVc/bW+34b54gaDnRNDtiq8xJSDQW6C691OeIYBAsQJ+f+HRD+FBtim2nnHfPiyzfL/Iqhm/ypbuzAmrDYPUMEp1CVL/Sm0Ttpt+YNbAQnaggl5K+Vvc+pS6B1fQcoNul/8ok702LDN9LWkv9VzJDrvXfG4BCH096tD79evX9/QQ1B8C5s6d6/RYKvQemmu/SVweVhtaK79tEXZ9bL2SdF9uM92fvgYL/TDjt+2T1CaVPpag50TQ7Sp9vOw/eQL0AExem3JEFRYI8gtPkG0qfJgV330lzLz8Kqtv8PSM8HZ6lKMNvbZHOeriTSVeucJyK7aXktd2j5e299q2trZ6zlyOvGHtw/NBxjBjJcz09Wx79WqAzy1pvTKDf5pHf8jUwJ/+QGb/Jrhtm7ZlYbeh37YIuz5JbN9ym+k1yfUzZKHkt+0Llcd67wJBz4mg23mvGTkR8CZAD0BvTuRCwLNAkF94gmzjuUIJzVhuM91foV9l+UXW38kWdhv6aY+w6+JPJj65w3IrppeSn3aPj3R4NbVtWOo9BC036Halrn+cyiuVmQ08mJlH+/S6VQ99Xep1bt16lmrQXq9trAEMrl3m/+zx24Zht4Xf+vg/4uRtUayZBs918qtCvf/CbvvktUzljijoORF0u8odKXuOkwA9AOPUWtQ1FgJBfuEJsk0sMEKsZLnNvPwqq3WiZ4T3Rg+7Df20R9h18a4Sr5yVcCvUS8lPu8dL23tt7fX9vGzhFszJtV3QcoNul6seaVhebjMNPGjvP50Qzc6y7ebsNixY82lQQpMGAfny6lBI2G3oty3Crk/3USfr33KaaeBdU652zZTNlYfXYaZSOI+DnhNBtwvnKCg1zQIEANPc+hx7xQWCfEgOsk3FD7TCFSjWzP4qm+/aRoV+kVUCDSKSggn4bcMw28NvXYIdcfK2KpVbvl5KYbZ7nFqkHEG9Qh6ZX3bCqk+hOsR5fTnN9D1OX1f6HmevAejXLrO9tTySv1mUM/2KtcssK7MtynlOFXsMUdm+nGYbNmzoCaQHPf5cbR+0PLbrKxD0nAi6Xd8asASB4gQIABbnx9YI9BHIfPPtszJrgX0zCLJNVlGpe1pOM6+/yvKLrL/TMOw29NMeYdfFn0x8cpfbzUsvJT/tHh/pYDXNF3S1vTft+5CfPQQtN+h2fuqWtLzlMNNZfLXnXzFDdzPPo8ygU9LaI8jxlKMNM+tVqC3KXZ/MusX1cdhm2vtW95Hr/curW6G291oO+QoLBD0ngm5XuEbkQMCbANcA9OZErgoL6B9L/UBpv7D4rY5+SbXd4v1u6zd/5ptvoW3tl+cg2xQqO0rrw2i/cpoV+6usbWdtEz2Py3UulvIciHsbZlq4tUc5z6fMupTzcdzbUF87xfRScmv3cvqXc1/z5s1zZk8+ffp0zt3q+aBp/vz5OfNkrwhabtDtsvefpuflMtPgn07iUajnnwYodJIPzesWKLTnU5raqNCxhtWGQdsirPoUcojz+nKZbd682WHKfJ9ycwva9m5lsSyYQNBzIuh2wWrJVgjkFiAAmNuGNRES0F4fhT6cFqpuoYvqFtre7/p8H4ZtIDM76BBkG7/1qkT+MNsvbLNS/Cqb2c5xDQDGuQ2zz/l87RH2+ZRdl3I+j3sb2l5KQd8L8rV7OduhHPuaO3eus5t857P+LdKkAR2vKWi5QbfzWq8k5iuHmV6WQl8Xbq8pvZafrrPnhwb99HzS5W7Jfq7RdXH8kcvtmIpdFlYbBm2LsOpTrFOUty+XmX7W1JT5PuXmErTt3cpiWTCBoOdE0O2C1ZKtEMgj0EVCAIEeAfPG22VeLl0mWNizzO8DM4zGKcNcRDvnpuYDtZPHvJE7eYJsk7PwlKwol5m2o54Tur9cyfxy26Xnjrl+kmuWtrY2pwwtx7a5a8aULQyrDYO0R1h1SXqTlstN/2bmew2qc5B2T2r72L85JhCT8xD175EZbpZzvduKoOUG3c6tDmlZFraZvhfp6ypX0vezzM9CJkjovM/l+myj64OcU7n2n4TlYbVh0LYIqz5JaKtcx1AuM33t6M1cciZXVZzlQds+b6EpWlmK73lBz4mg26WoeTjUMglwDUDz15aEQCkFgvzCE2SbUtY5jmWVy8zLr7L8IhvsDAqrDYO0R1h1CSYTn63K4Vaol5J9jQZp9/hI+6up9iLRCR127tzpOiOrNXObmEh7BmpvSzvZSuaeg5YbdLvMfaftcTFm+dpQHfW80LbXmz7OvOm5ob389D7zemTaE3DZsmVir4mb3R76+tNk77PXp/F5WG0YtC2KqU8a20+PuRizQq9DN1PdX74UtO3zlcm6vgL52i7oORF0u761YwkCRQqUKdDIbhCIhYD54+z8Apf5q7ffigf5hSfINn7rlbT85TIzf2IL/irLL7LBzq6w2jBIe4RVl2Ay8dkqbDcTTPDcSylIu8dH2n9NtW30Pc2t56T2DMzVO9D2eta/fTt27Oiz46DlBt2uTwVStCCoWb42tGXa97Zc9269Q7Vctx5K+trTcnL1DkxRk/U5VOtd6tdh0LYIWp8+B5aiBUHN8r0OM/m0fPs61NdSoRS07QuVm/T1+t3OOuuIgXypUNsFPSeCbpevrqxDwK+A+N2A/AgkWcBrAFDfRHTojNsHOvXRoTP6JqN/6LOTvunouuw3+SDbZJedtudBzQq1X6aj/bCQ3V6ZebS8XOeC5tNzRctx+zKdWU4aH4fRhkHbI2hd0thumccc1K3Q61BfLxqE0L+Z+jjzpss0OKh/s20K2u52+yTeq4ka6t8n9VM3/XukN7f3JzWw7ponVwpSrpYVdLtc9UjD8iBm+dpQzwX7vpbvPlf7awBQg8d6r69BW16+98g0tFO+Yyx1G9p9BW2LIPWx+0zrfRCzfK/DbEf7WtS/0V5S0Lb3UnaS8qinvgda3+x7XaeW2clL2wU5J3Q/QbfLriPPEQgqUKUbmhcDCYHUC2h372nTpjkO5g2j58LXbjA6bGbNmjXOKvMm0eeC13qh7ClTpjjDZcyH4l5F2CFzul1mCrJN5vZpfBzUrFD7WUstv76+3nmq7Wi+6NhVfe61zMbGRjG/GvZapxMv6FA6XW4+ZPRaxxNxhif6fa2oW6E2DNIeQc+ntLdjULd8bWjL1Pt8yXx4F/NhuidLkHbv2TjBD3Q4pw7zNAFT0ZkITQCnJEcbtNyg25Wk0jEtJEpm+rrU+ujnJn0NmmBhwckLYspe0mqH0YbFtEUY9SkpWAQLC8vMvp7yfc7M5iim7bPLSvJzddL3PreUb51bfrdlQc+JoNu51YFlCPgRIADoR4u8iRPQP74anNEPsW5JP9ja4E3mev0itXTpUueDrwYL3ZK9foR+MNYydIY8GwDSa+S4vRkF2cZt32laFsTMS/tZw6qqKudhoaCwZtKg8OOPPy7Lly/vOTfszKt+PtTZfaflPqw2DNIeQeqSlnbKd5xB3PK9DvVvpr52CiX9+5r9NzhIuxfaD+sRQAABBBBAAAEEEIi7AAHAuLcg9S9aIN+vP/nWed1xkF94gmzjtT5JzReWmZarwQ2vATw9Z+w29Izwd7aF0YZB2yOMuvjTiGfuqLgFbfd4qlNrBBBAAAEEEEAAAQQKCxAALGxEDgQQQAABBBBAAAEEEEAAAQQQQAABBGIr0C+2NafiCCCAAAIIIIAAAggggAACCCCAAAIIIFBQgABgQSIyIIAAAggggAACCCCAAAIIIIAAAgggEF8BAoDxbTtqjgACCCCAAAIIIIAAAggggAACCCCAQEEBAoAFiciAAAIIIIAAAggggAACCCCAAAIIIIBAfAUIAMa37ag5AggggAACCCCAAAIIIIAAAggggAACBQUIABYkIgMCCCCAAAIIIIAAAggggAACCCCAAALxFSAAGN+2o+YIIIAAAggggAACCCCAAAIIIIAAAggUFCAAWJCIDAgggAACCCCAAAIIIIAAAggggAACCMRXgABgfNuOmiOAAAIIIIAAAggggAACCCCAAAIIIFBQgABgQSIyIIAAAggggAACCCCAAAIIIIAAAgggEF8BAoDxbTtqjgACCCCAAAIIIIAAAggggAACCCCAQEEBAoAFiciAAAIIIIAAAggggAACCCCAAAIIIIBAfAUIAMa37ag5AggggAACCCCAAAIIIIAAAggggAACBQUIABYkIgMCCCCAAAIIIICAH4EtW7b4ye4pbxhletoxmRBAAAEEEEAAgQQIEABMQCNyCAgggAACCCCAQFQEFi9eHEpVNm7cKOvWrQulbApFAAEEEEAAAQSSLlCd9APk+BBAAAEEEEAAAQTKI6DBvxUrVsiiRYs871Dzb9iwQdrb22Xq1KnObc6cOU45+tymtWvXyrRp05ynjzzyiF3MPQIIIIAAAggggIAHAXoAekAiCwIIIIAAAgggEBcBDcLV19fLzp07y1plDeTV1dXJkiVLPO/XBgwPHDggO3bsEA386VDfNWvWyMqVK/uUs3nzZmd5uY+tT0VYgAACCCCAAAIIxEygqsukmNWZ6iKAAAIIIIAAAgi4CGzatEmWLl3qrNFAnA6bLUfSoJ0G89ra2pwgoJd9ahBPe/XpLTPt379f9Di0l58GFLOTDgNevXq17Nu3L3sVzxFAAAEEEEAAAQRyCNADMAcMixFAAAEEEEAAgbgJaA86mzQgV66kvf+am5tdA3a56tDa2ioa7MtOOuw3X1kaGNRttZcgCQEEEEAAAQQQQMCbAD0AvTmRCwEEEEAAAQQQiI2ABtYyr58XZsW1R54GAP30/tP66DX/dKiy9uTzW1c7RNjvPsN0oGwEEEAAAQQQQCDKAgQAo9w61A0BBBBAAAEEEIi4gE7MoT0Pgww31gDgvHnzRK/t5yfZ4KEOBdbegiQEEEAAAQQQQACB/AIMAc7vw1oEEEAAAQQQQACBHAJ67T/tbag9AIOkZcuWOZN+aC9CP8lONpJ9/UA/ZZAXAQQQQAABBBBIkwABwDS1NseKAAIIIIAAAgiUUMD2+lu0aFGgUrUHnyYNILpdDzBfofPnz3e2YUbgfEqsQwABBBBAAAEEugUIAHImIIAAAggggAACCRLQQJoGxcoRGNuwYYPv6/dlUtuefLrM76QlNuj4+OOPZxbJYwQQQAABBBBAAAEXgWqXZSxCAAEEEEAAAQQQiIiABvK2b9/uTJqhk2UsWbLEqZkOv7VBMF0wd+7cXkE/XZd9bT0NDur18/ReZ9LV8mwZutwO6dXlel2/fJNz2LJ0GG+QpPvTob+6Dw0Eank6uYfXa/rZGY/LEegMcnxsgwACCCCAAAIIREmAHoBRag3qggACCCCAAAIIvCOgwTEN6mnwTyfK0MCfBsp0uKz2llu6dGkvq61bt8qOHTucwF2vFRlPdBstU++1HDuE186qq+VrYE171enkHro8V7KBNy3Pb9q0aZMsXLjQOSYdBvzII484RaxcudLXUGCtqwYtSQgggAACCCCAAAL5BQgA5vdhLQIIIIAAAgggUHYBDZBpMEwDehocs73xtLeeTnyhgbrsZIN3+Sbk0PK6urp6ehFqGbofLV/L1fL1poFBXabrcgXYtMeepny9BJ0MWf9omQ8//LBowNJum1lnPXavqaGhwWtW8iGAAAIIIIAAAqkWIACY6ubn4BFAAAEEEEAgigKrVq3qGZrrVj87eYbbOi/L7PX2tHehJjsMOHNbu8z2Esxcp4/37dvnLPIThNNejdqrUIN/mUFMDQTa/fm5pp8NINpgZHYdeY4AAggggAACCCDQLUAAkDMBAQQQQAABBBCImIC9Hl+uamngywa/cuXxslyH8T766KOuWXUIsKZcwTW9hqCmzECesyDHP3pM2tNPhzJr78LsZJdpPq/J7tvPNl7LJh8CCCCAAAIIIJAkAQKASWpNjgUBBBBAAAEEEiGgwTANamkQTofEugW4cvXM8wOgATQbRPOznea1dfLaA1CH/mrKHO7rLHjnn/nz5zuPbGAxc12ux42Njb63yVUWyxFAAAEEEEAAgSQLEABMcutybAgggAACCCAQS4H169c7gTntfacTdtTX1zuTd2jwzF4jrxQ9AL2U4Scglwtbg4U6/FeTHeqbndcGIr3UKXtbG4zMXs5zBBBAAAEEEEAAgW4BAoCcCQgggAACCCCAQMQENBh24MABaW5u7umhp8N1NYhmZ/K1s/BWuupeAoQbNmxwqqnDf3MlG8TzEwA8ffq0U5wNHuYqm+UIIIAAAggggEDaBQgApv0M4PgRQAABBBBAIJICGtTSyT7a2tqcCTd0ll6dEViTBv8WLlzYMwy3Egdgg242cJevDjr7sCY7zNctr73WYL482dvZfXsdhpy9Pc8RQAABBBBAAIG0CBAATEtLc5wIIIAAAgggEBsBe708W2HtFafBPw0CakBQh9Fq8MsOq7X5ynlve+p56QFo89ht3OppZ/+1QU63PNnLbLk2GJm9nucIIIAAAggggAAC3QIEADkTEEAAAQQQQACBiAloYM/2bsuumga77AQgzz//fPbqsj23swTnqmdmRWyvvlyBOi1DezXqEOFceTLLs4/tvvMFFm1e7hFAAAEEEEAAgTQLEABMc+tz7AgggAACCCAQWYF8vfs0SKZBr0oGvuy+7dDdfJA6q7GmXNcttMf66KOP5iumzzrdt61Hn5UsQAABBBBAAAEEEOgRIADYQ8EDBBBAAAEEEEAgOgKrVq3K2QtQe75p8Gvx4sUVq7CdzXfz5s0F66B5NVDnllePRYc869BfGygsWKDJYA38bOOlXPIggAACCCCAAAJJFCAAmMRW5ZgQQAABBBBAIPYCGjDTGX+ze9jpc12uMwTbIJw9WA2K2Qk3tm/fnjOAaPNoWbqNW/KSR4NvW7Zscdu8zzIdtqx1WrNmTc863bceiw791esb+klalqbly5f72Yy8CCCAAAIIIIBAKgWqU3nUHDQCCCCAAAIIIBBhgXnz5vVc5097x2UGAXX4ry7LDv7V19f3CuZpcE2Xaerq6nLu8+XRgJ8G9PTafpn7yyxHe/Bl7leDbzqsV/MXGoqrZR84cMCpu/Zc1OOwAUA/E384B2L+sb0JM+tj13GPAAIIIIAAAggg0Fugynwg7P5E2Hs5zxBAAAEEEEAAAQQQyCtgg4OrV692eiTmzVzilRqo1KCinRClxMVTHAIIIIAAAgggkCgBAoCJak4OBgEEEEAAAQQQKK+ADuHVXoD79u0r24512LH2IrS9Fsu2Y3aEAAIIIIAAAgjEVIAAYEwbjmojgAACCCCAAAJRENDhv9obT3vi6bX8ypE0+Nfa2tpzvcNy7JN9IIAAAggggAACcRYgABjn1qPuCCCAAAIIIIBABARWrFjhTPBhJw4Js0o24EjvvzCVKRsBBBBAAAEEkiZAADBpLcrxIIAAAggggAACZRbQawFOmTJF1q9fH3ovQO39pxOO+J01uMwk7A4BBBBAAAEEEIiUALMAR6o5qAwCCCCAAAIIIBA/AZ3Rd+vWrbJw4UJnYo5CMwIHPcJ169Y5Q3/tDMBBy2E7BBBAAAEEEEAgbQL0AExbi3O8CCCAAAIIIIBASAKbNm2SVatWhXJtPp1oRCcc0aG/GnAkIYAAAggggAACCHgXIADo3YqcCCCAAAIIIIAAAgUEdIZeDdY1NzcXyOlvtQb/dIgxwT9/buRGAAEEEEAAAQRUgAAg5wECCCCAAAIIIIAAAggggAACCCCAAAIJFuiX4GPj0BBAAAEEEEAAAQQQQAABBBBAAAEEEEi9AAHA1J8CACCAAAIIIIAAAggggAACCCCAAAIIJFmAAGCSW5djQwABBBBAAAEEEEAAAQQQQAABBBBIvQABwNSfAgAggAACCCCAAAIIIIAAAggggAACCCRZgABgkluXY0MAAQQQQAABBBBAAAEEEEAAAQQQSL0AAcDUnwIAIIAAAggggAACCCCAAAIIIIAAAggkWYAAYJJbl2NDAAEEEEAAAQQQQAABBBBAAAEEEEi9AAHA1J8CACCAAAIIIIAAAggggAACCCCAAAIIJFmAAGCSW5djQwABBBBAAAEEEEAAAQQQQAABBBBIvQABwNSfAgAggAACCCCAAAIIIIAAAggggAACCCRZgABgkluXY0MAAQQQQAABBBBAAAEEEEAAAQQQSL0AAcDUnwIAIIAAAggggAACCCCAAAIIIIAAAggkWYAAYJJbl2NDAAEEEEAAAQQQQAABBBBAAAEEEEi9wP8HLtmwjg6m848AAAAASUVORK5CYII=\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2.5, 2.5)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x108a9a5d0>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "disc = np.genfromtxt('resources/PSdiscPot7years.csv', delimiter=',')\n",
    "sdec = disc[:,0]\n",
    "disc = disc[:,1]\n",
    "\n",
    "tck_disc = splrep(sdec, np.log(disc), s=1.e-3)\n",
    "xvals = np.linspace(-1, 1, 1000)\n",
    "spl_disc = splev(xvals, tck_disc)\n",
    "\n",
    "fig,ax=plt.subplots()\n",
    "\n",
    "ax.plot(xvals,np.exp(spl_disc), color='red', ls='dashed')\n",
    "ax.plot(sdec, disc, alpha=0.5)\n",
    "    \n",
    "fig.legend()\n",
    "ax.set_xlabel(r'$\\sin(\\delta)$',fontsize=12)\n",
    "ax.set_ylabel(r'disc pot [TeV cm$^{-2}$ s$^{-1}$]',fontsize=12)\n",
    "ax.set_yscale('log')\n",
    "\n",
    "\n",
    "ps_disc = np.genfromtxt('resources/'+\n",
    "                        'tcarver_10y_disc.csv', delimiter=',')\n",
    "ind_disc = np.argsort(ps_disc[:,0])\n",
    "ax.plot(ps_disc[:,0][ind_disc], ps_disc[:,1][ind_disc], ls='solid', color=colors[0],lw=3,\n",
    "       label='2')\n",
    "\n",
    "\n",
    "ps_disc = np.genfromtxt('resources/'+\n",
    "                        '10yr_ps_dicPot_g25_tessaThesis.csv', delimiter=',')\n",
    "ind_disc = np.argsort(ps_disc[:,0])\n",
    "ax.plot(ps_disc[:,0][ind_disc], ps_disc[:,1][ind_disc], ls='solid', color=colors[1],lw=3,\n",
    "       label='2.5')\n",
    "\n",
    "ps_disc = np.genfromtxt('resources/'+\n",
    "                        '10yr_ps_dicPot_g3_tessaThesis.csv', delimiter=',')\n",
    "ind_disc = np.argsort(ps_disc[:,0])\n",
    "ax.plot(ps_disc[:,0][ind_disc], ps_disc[:,1][ind_disc], ls='solid', color=colors[2], lw=3,\n",
    "       label='3')\n",
    "\n",
    "if gammas[0] == 2:\n",
    "    print(gammas[0],gamma)\n",
    "    ps_disc = np.genfromtxt('resources/'+\n",
    "                        'tcarver_10y_disc.csv', delimiter=',')\n",
    "\n",
    "elif gammas[0] ==2.5:\n",
    "    print(gammas[0],gamma)\n",
    "    ps_disc = np.genfromtxt('resources/'+\n",
    "                        '10yr_ps_dicPot_g25_tessaThesis.csv', delimiter=',')\n",
    "\n",
    "elif gammas[0] ==3.:\n",
    "    print(gammas[0],gamma)\n",
    "    ps_disc = np.genfromtxt('resources/'+\n",
    "                        '10yr_ps_dicPot_g3_tessaThesis.csv', delimiter=',')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "ind_disc = np.argsort(ps_disc[:,0])\n",
    "ax.plot(ps_disc[:,0][ind_disc], ps_disc[:,1][ind_disc], ls='solid', color=colors[0],lw=3,\n",
    "       label='IceCube PS 5$\\sigma$ Disc. Potential')\n",
    "\n",
    "tck_disc = splrep(ps_disc[:,0][ind_disc], np.log(ps_disc[:,1][ind_disc]), s=1.e-3)\n",
    "xvals = np.linspace(-1, 1, 1000)\n",
    "spl_disc = splev(xvals, tck_disc)\n",
    "\n",
    "ax.plot(xvals,np.exp(spl_disc), color='green', ls='dashed')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#------------------------------------------\n",
    "# cover area at the horizon that is not \n",
    "# plotted nicely\n",
    "#------------------------------------------\n",
    "\n",
    "num = 5000\n",
    "x = np.linspace(0,2*np.pi, num)\n",
    "y = np.linspace(-np.pi/2,np.pi/2 ,500)\n",
    "\n",
    "disc_vals = np.ones(npix)\n",
    "for dec_i in y:\n",
    "    \n",
    "    #get the pixels\n",
    "    p = hp.ang2pix(NSIDE, dec_i+np.pi/2, x)\n",
    "    #fill them \n",
    "    disc_vals[p] = np.exp(splev(np.sin(dec_i), tck_disc))\n",
    "\n",
    "\n",
    "disc_ice = np.min(disc_vals)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + 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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MGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGA0ZW4AAEAASURBVGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYmB06EAAAAAAA8n9thAQHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODA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Dhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDmiHjgUAAAAABvlbT2NHIWTAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGuzSB8AAAXmSURBVGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMHAZCHJmAAGuQb1GAAAAAElFTkSuQmCC\" width=\"1600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2.9393668488168284e-12, 7.224683123974168e-12)\n"
     ]
    }
   ],
   "source": [
    "ngrid=500\n",
    "\n",
    "t_0 = 10. # years\n",
    "t_new = 10. # years\n",
    "\n",
    "vari = 'rrel'\n",
    "used_keys = list()\n",
    "fact = 1.\n",
    "\n",
    "\n",
    "fig =  plt.figure(figsize=(16,6))\n",
    "    \n",
    "bckg_vals2 = deepcopy(comb_values['IceCube'])\n",
    "all_vals = deepcopy(comb_values)\n",
    "\n",
    "#-------------------------------------------    \n",
    "# Show the improvements with Gen2 as well   \n",
    "#-------------------------------------------\n",
    "\n",
    "comb_vals = np.zeros(npix)\n",
    "ax= fig.add_subplot(121, projection='hammer',\n",
    "                                       rasterized=True)\n",
    "    \n",
    "for (name, vali) in sorted(all_vals.iteritems()):\n",
    "    if vari == 'rrel':\n",
    "        mask_bckg = bckg_vals2 > 0.0\n",
    "        vali[mask_bckg] /= bckg_vals2[mask_bckg]\n",
    "        vali[~mask_bckg] = np.max(vali[mask_bckg])\n",
    "\n",
    "\n",
    "    nuse = ['X, China']\n",
    "\n",
    "\n",
    "    if name == 'IceCube' and 'Gen2' in nuse:\n",
    "        comb_vals += (t_0+t_new) * vali\n",
    "    elif name == 'IceCube':\n",
    "        comb_vals += t_0 * vali\n",
    "    elif name in nuse:\n",
    "        continue\n",
    "    else:\n",
    "        comb_vals += t_new * vali * fact\n",
    "\n",
    "    if name not in used_keys:\n",
    "        used_keys.append(name)\n",
    "\n",
    "effA_vals_wGen2 = deepcopy(comb_vals)\n",
    "\n",
    "new_vals = (comb_vals / (t_0+t_new))**(-0.8)\n",
    "mask0 = new_vals > 0.\n",
    "new_vals[mask0] = new_vals[mask0]\n",
    "new_vals[~mask0] = np.min(new_vals[mask0])\n",
    "\n",
    "\n",
    "disci = disc_vals * 1./ ( (t_0+t_new)/ 10.)**0.8\n",
    "new_vals *= disci\n",
    "\n",
    "_min = np.min(new_vals)\n",
    "_max = np.max(new_vals)\n",
    "\n",
    "cax=plot_area(new_vals, ax, npix=ngrid,  alpha=1., vmax=_max,  vmin=_min, #.e14, #vmax=1.,\n",
    "         shading='gouraud', cmap='GnBu_r')#, norm=LogNorm())\n",
    "\n",
    "cax_effA_wGen2 = plot_area(effA_vals_wGen2, ax, npix=ngrid,  alpha=1., vmax=_max,  vmin=_min, #.e14, #vmax=1.,\n",
    "         shading='gouraud', cmap='GnBu_r')\n",
    "\n",
    "\n",
    "#-------------------------------------------    \n",
    "# Show the improvements with Gen2 as well   \n",
    "#-------------------------------------------\n",
    "bckg_vals2 = deepcopy(comb_values['IceCube'])\n",
    "all_vals = deepcopy(comb_values)\n",
    "\n",
    "used_keys2 = list()\n",
    "comb_vals2 = np.zeros(npix)\n",
    "ax= fig.add_subplot(122, projection='hammer',\n",
    "                                       rasterized=True)\n",
    "    \n",
    "for (name, vali) in sorted(all_vals.iteritems()):\n",
    "    if vari == 'rrel':\n",
    "        mask_bckg = bckg_vals2 > 0.0\n",
    "        vali[mask_bckg] /= bckg_vals2[mask_bckg]\n",
    "        vali[~mask_bckg] = np.max(vali[mask_bckg])\n",
    "\n",
    "\n",
    "    nuse = ['X, China', 'Gen2']\n",
    "\n",
    "\n",
    "    if name == 'IceCube' and 'Gen2' in nuse:\n",
    "        comb_vals2 += (t_0+t_new) * vali\n",
    "    elif name == 'IceCube':\n",
    "        comb_vals2 += t_0 * vali\n",
    "    elif name in nuse:\n",
    "        continue\n",
    "    else:\n",
    "        comb_vals2 += t_new * vali * fact\n",
    "\n",
    "    if name not in used_keys2:\n",
    "        used_keys2.append(name)\n",
    "\n",
    "        \n",
    "effA_vals_woGen2 = deepcopy(comb_vals2)\n",
    "new_vals2 = (comb_vals2 / (t_0+t_new))**(-0.8)\n",
    "mask0 = new_vals2 > 0.\n",
    "new_vals2[mask0] = new_vals2[mask0]\n",
    "new_vals2[~mask0] = np.min(new_vals2[mask0])\n",
    "\n",
    "\n",
    "disci = disc_vals * 1./ ( (t_0+t_new)/ 10.)**0.8\n",
    "new_vals2 *= disci\n",
    "\n",
    "\n",
    "rvals = new_vals2\n",
    "\n",
    "_min = np.min(rvals)\n",
    "_max = np.max(rvals)\n",
    "\n",
    "print(_min, _max)\n",
    "cax2=plot_area(rvals, ax, npix=ngrid,  alpha=1., vmax=_max,  vmin=_min, #.e14, #vmax=1.,\n",
    "         shading='gouraud', cmap='GnBu_r')#, norm=LogNorm())\n",
    "\n",
    "cax_effA_woGen2 = plot_area(effA_vals_woGen2, ax, npix=ngrid,  alpha=1., vmax=_max,  vmin=_min, #.e14, #vmax=1.,\n",
    "         shading='gouraud', cmap='GnBu_r')\n",
    "plt.close()\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10.0, 10.0)\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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + 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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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get the results from PLENUM(+Gen2)\n",
    "z = cax.get_array()\n",
    "z2 = cax2.get_array()\n",
    "\n",
    "\n",
    "z_effA1 = cax_effA_woGen2.get_array()\n",
    "\n",
    "# get the icecube results\n",
    "print(t_0, t_new)\n",
    "t_newi = t_new\n",
    "disci = disc_vals * 1./ ( (t_0+t_newi)/ 10)**0.8\n",
    "cax3=plot_area(disci, ax, npix=ngrid,  alpha=1., #vmin=1.e14, #vmax=1.,\n",
    "             shading='gouraud', cmap='GnBu_r', norm=LogNorm())\n",
    "\n",
    "z_icecube = cax3.get_array()\n",
    "\n",
    "# get the cordinates of the skymap entries\n",
    "x = np.linspace(-np.pi, np.pi, ngrid)\n",
    "y = np.linspace( 0, np.pi, ngrid / 2)\n",
    "       \n",
    "lon = np.linspace(-np.pi, np.pi, len(x))\n",
    "lat = np.linspace(-np.pi/2., np.pi/2., len(y))\n",
    "\n",
    "xx,yy = np.meshgrid(lon,lat)\n",
    "\n",
    "bins = np.linspace(-1,1, 50) #50\n",
    "res_wGen2 = np.zeros_like(get_mids(bins))\n",
    "res_woGen2 = np.zeros_like(get_mids(bins))\n",
    "res_ice = np.zeros_like(get_mids(bins))\n",
    "_effA_woGen2 = np.zeros_like(get_mids(bins))\n",
    "\n",
    "\n",
    "inds = np.searchsorted( bins, np.sin(yy.flatten()))\n",
    "\n",
    "\n",
    "\n",
    "for i, indi in enumerate(get_mids(bins)):\n",
    "    m = inds==i\n",
    "    res_wGen2[i] = np.sum(z[m]) / float(np.sum(m))\n",
    "    res_woGen2[i] = np.sum(z2[m]) / float(np.sum(m))\n",
    "    res_ice[i] = np.sum(z_icecube[m]) / float(np.sum(m))\n",
    "    _effA_woGen2[i] = np.sum(z_effA1[m]) / float(np.sum(m))\n",
    "\n",
    "\n",
    "\n",
    "fig,ax = plt.subplots(figsize=(6,4))\n",
    "\n",
    "gcm = get_cmap('GnBu_r')\n",
    "num_c = 2 + 2\n",
    "cgen = [gcm(th/float(num_c)) for th in range(num_c)]\n",
    "\n",
    "\n",
    "# conversion to flux normalisation at 100TeV in 1/GeV /cm2/s\n",
    "const = 10**(-2*gamma) / 1.e3\n",
    "\n",
    "\n",
    "c='#DC6C25'\n",
    "p=ax.plot(get_mids(bins), res_wGen2*const, label=r'IceCube(10yr)+PLE$\\nu$M $\\wedge$ Gen-2(10yr)',\n",
    "       lw=2., color=c)\n",
    "ax.plot(get_mids(bins), res_woGen2*const, label=r'IceCube(10yr)+PLE$\\nu$M(10yr)', lw=2.,\n",
    "       color=p[0].get_color(), ls='dashed')\n",
    "\n",
    "ax.plot(get_mids(bins), res_ice*const, color=cgen[0], label=r'IceCube(20yr)', lw=2.)\n",
    "ax.plot(xvals,np.exp(spl_disc)*const, color=cgen[2], ls='solid', label=r'IceCube(10yr)',\n",
    "       lw=2.)\n",
    "\n",
    "ax.set_yscale('log')\n",
    "\n",
    "ax.set_xlim(-1,1)\n",
    "ax.set_xlabel(r\"$\\sin(\\delta)$\",fontsize=fs-2)\n",
    "\n",
    "fig.legend( fontsize=fs-6, loc='best', mode='expand',\n",
    "            ncol=2, frameon=False)\n",
    "ax.text(0.75,0.8, r'$\\gamma$={0:.1f}'.format(gamma), fontsize=22 ,\n",
    "         transform = ax.transAxes)\n",
    "\n",
    "if gamma==2:\n",
    "    ax.set_ylabel(r\"$\\phi^{\\mathrm{thr}}_{100\\mathrm{TeV}}$  [$\\mathrm{GeV}^{-1} \\mathrm{cm}^{-2} \\mathrm{s}^{-1}$]\",\n",
    "              fontsize=fs-2)\n",
    "    \n",
    "    ax.tick_params(axis='both', which='major', labelsize=fs-4)\n",
    "    ax.set_ylim(5e-21, 1.5e-17) \n",
    "    # add the location of the galactic center and TXS\n",
    "    ax.annotate(\"Galactic Center\", xy=(np.sin(np.radians(-29.)), 5.e-21), xytext=(np.sin(np.radians(-50.)), 15.e-21),\n",
    "            arrowprops=dict(arrowstyle=\"->\"), fontsize=12)\n",
    "\n",
    "    ax.annotate(\"TXS 0506+056\", xy=(np.sin(np.radians(5.7)), 5.e-21), xytext=(np.sin(np.radians(25.7)), 8.e-21),\n",
    "            arrowprops=dict(arrowstyle=\"->\"), fontsize=12)\n",
    "\n",
    "elif gamma==2.5:\n",
    "    ax.set_ylabel(r\"$\\phi^{\\mathrm{thr}}_{100\\mathrm{TeV}}$  [$\\mathrm{GeV}^{-1} \\mathrm{cm}^{-2} \\mathrm{s}^{-1}$]\",\n",
    "              fontsize=fs-2)\n",
    "    \n",
    "    ax.tick_params(axis='both', which='major', labelsize=fs-4)\n",
    "    ax.set_ylim(5e-21, 1.5e-17) \n",
    "    # add the location of the galactic center and TXS\n",
    "    ax.annotate(\"Galactic Center\", xy=(np.sin(np.radians(-29.)), 5.e-21), xytext=(np.sin(np.radians(-50.)), 15.e-21),\n",
    "            arrowprops=dict(arrowstyle=\"->\"), fontsize=12)\n",
    "\n",
    "    ax.annotate(\"TXS 0506+056\", xy=(np.sin(np.radians(5.7)), 5.e-21), xytext=(np.sin(np.radians(25.7)), 8.e-21),\n",
    "            arrowprops=dict(arrowstyle=\"->\"), fontsize=12)\n",
    "\n",
    "    \n",
    "km3net_cas = np.genfromtxt('/Users/mhuber/Documents/Km3NET_cascade_discPot_3years.csv', \n",
    "                           delimiter=',')\n",
    "\n",
    "ax.plot(km3net_cas[:,0], km3net_cas[:,1]*1e-10 * (10/3.)**(-0.8), color='red', lw=2.,\n",
    "       ls='dotted')\n",
    "\n",
    "km3net_cas = np.genfromtxt('/Users/mhuber/Documents/Km3NET_track_discPot_3years.csv', \n",
    "                           delimiter=',')\n",
    "\n",
    "ax.plot(km3net_cas[:,0], km3net_cas[:,1]*1e-10 * (10/3.)**(-0.8), color='red', lw=2.,\n",
    "       ls='dashed')\n",
    "    \n",
    "    \n",
    "fig.tight_layout()\n",
    "\n",
    "plt.subplots_adjust(top = 0.81)\n",
    "#fig.savefig('plots/PLENUM_ps_disc_pot_time_evolution_g2_pCascades.pdf',\n",
    "#               bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Now do a similar plot but with the time on the x-axis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + 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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MGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGA0ZW4AAEAASURBVGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYmB06EAAAAAAA8n9thAQHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODA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Dhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDhw4cODAgQMHDmiHjgUAAAAABvlbT2NHIWTAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGuzSB8AAAXmSURBVGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMGDAgAEDBgwYMHAZCHJmAAGuQb1GAAAAAElFTkSuQmCC\" width=\"1600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t_0 = 10. # years\n",
    "#t_new = 10. # years\n",
    "t_news = np.arange(0,15,.25)\n",
    "\n",
    "vari = 'rrel'\n",
    "used_keys = list()\n",
    "fact = 1.\n",
    "\n",
    "\n",
    "fig =  plt.figure(figsize=(16,6))\n",
    "    \n",
    "results = dict()\n",
    "scenarios = {'p_woGen2':['Gen2'], 'p_wGen2':[] }\n",
    "bins = np.linspace(-1,1, 50) #50 declination bins in sin(dec)\n",
    "\n",
    "for key, sceni in scenarios.items():\n",
    "    if not key in results.keys():\n",
    "        results[key] = dict()\n",
    "        \n",
    "    for t_new in t_news:\n",
    "        bckg_vals2 = deepcopy(comb_values['IceCube'])\n",
    "        all_vals = deepcopy(comb_values)\n",
    "\n",
    "        #-------------------------------------------    \n",
    "        # Show the improvements with Gen2 as well   \n",
    "        #-------------------------------------------\n",
    "\n",
    "        comb_vals = np.zeros(npix)\n",
    "        ax= fig.add_subplot(121, projection='hammer',\n",
    "                                           rasterized=True)\n",
    "\n",
    "        for (name, vali) in sorted(all_vals.iteritems()):\n",
    "            if vari == 'rrel':\n",
    "                mask_bckg = bckg_vals2 > 0.0\n",
    "                vali[mask_bckg] /= bckg_vals2[mask_bckg]\n",
    "                vali[~mask_bckg] = np.max(vali[mask_bckg])\n",
    "\n",
    "\n",
    "            nuse = ['X, China']+sceni\n",
    "\n",
    "\n",
    "            if name == 'IceCube' and 'Gen2' in nuse:\n",
    "                comb_vals += (t_0+t_new) * vali\n",
    "            elif name == 'IceCube':\n",
    "                comb_vals += t_0 * vali\n",
    "            elif name in nuse:\n",
    "                continue\n",
    "            else:\n",
    "                comb_vals += t_new * vali * fact\n",
    "\n",
    "            if name not in used_keys:\n",
    "                used_keys.append(name)\n",
    "\n",
    "\n",
    "\n",
    "        new_vals = (comb_vals / (t_0+t_new))**(-0.8)\n",
    "        mask0 = new_vals > 0.\n",
    "        new_vals[mask0] = new_vals[mask0]\n",
    "        new_vals[~mask0] = np.min(new_vals[mask0])\n",
    "\n",
    "\n",
    "        disci = disc_vals * 1./ ( (t_0+t_new)/ 10.)**0.8\n",
    "        new_vals *= disci\n",
    "\n",
    "        _min = np.min(new_vals)\n",
    "        _max = np.max(new_vals)\n",
    "\n",
    "        cax=plot_area(new_vals, ax, npix=ngrid,  alpha=1., vmax=_max,  vmin=_min, #.e14, #vmax=1.,\n",
    "                 shading='gouraud', cmap='GnBu_r')#, norm=LogNorm())\n",
    "\n",
    "        # get the results from PLENUM(+Gen2)\n",
    "        z = cax.get_array()\n",
    "\n",
    "        # get the cordinates of the skymap entries\n",
    "        x = np.linspace(-np.pi, np.pi, ngrid)\n",
    "        y = np.linspace( 0, np.pi, ngrid / 2)\n",
    "\n",
    "        lon = np.linspace(-np.pi, np.pi, len(x))\n",
    "        lat = np.linspace(-np.pi/2., np.pi/2., len(y))\n",
    "\n",
    "        xx,yy = np.meshgrid(lon,lat)\n",
    "\n",
    "        \n",
    "        res = np.zeros_like(get_mids(bins))\n",
    "        inds = np.searchsorted( bins, np.sin(yy.flatten()))\n",
    "\n",
    "        # get average values at each declination bin\n",
    "        for i, indi in enumerate(get_mids(bins)):\n",
    "            m = inds==i\n",
    "            res[i] = np.sum(z[m]) / float(np.sum(m))\n",
    "\n",
    "        \n",
    "        results[key][t_new] = res\n",
    "    \n",
    "results['icecube'] = dict()\n",
    "for t_new in t_news:        \n",
    "        \n",
    "    disci = disc_vals * 1./ ( (t_0+t_new)/ 10)**0.8\n",
    "    cax=plot_area(disci, ax, npix=ngrid,  alpha=1., #vmin=1.e14, #vmax=1.,\n",
    "             shading='gouraud', cmap='GnBu_r', norm=LogNorm())\n",
    "\n",
    "    z_icecube = cax.get_array()        \n",
    "    \n",
    "    res = np.zeros_like(get_mids(bins))\n",
    "    inds = np.searchsorted( bins, np.sin(yy.flatten()))\n",
    "\n",
    "    # get average values at each declination bin\n",
    "    for i, indi in enumerate(get_mids(bins)):\n",
    "        m = inds==i\n",
    "        res[i] = np.sum(z_icecube[m]) / float(np.sum(m))\n",
    "    \n",
    "    results['icecube'][t_new] = res\n",
    "    \n",
    "plt.close()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "results5_10 = dict()\n",
    "t_old = np.arange(-5,0,0.25)\n",
    "\n",
    "for t_new in t_old:        \n",
    "        \n",
    "    disci = disc_vals * 1./ ( (t_0+t_new)/ 10)**0.8\n",
    "    cax=plot_area(disci, ax, npix=ngrid,  alpha=1., #vmin=1.e14, #vmax=1.,\n",
    "             shading='gouraud', cmap='GnBu_r', norm=LogNorm())\n",
    "\n",
    "    z_icecube = cax.get_array()        \n",
    "    \n",
    "    res = np.zeros_like(get_mids(bins))\n",
    "    inds = np.searchsorted( bins, np.sin(yy.flatten()))\n",
    "\n",
    "    # get average values at each declination bin\n",
    "    for i, indi in enumerate(get_mids(bins)):\n",
    "        m = inds==i\n",
    "        res[i] = np.sum(z_icecube[m]) / float(np.sum(m))\n",
    "    \n",
    "    results5_10[t_new] = res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + 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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\" width=\"700\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(figsize=(7,5))\n",
    "lss = {'icecube':'solid', 'p_woGen2':'dotted', 'p_wGen2':'dashed' }\n",
    "\n",
    "decs = [-40, 0 ,40]\n",
    "gcm = get_cmap('GnBu_r')\n",
    "num_c = 2 + 2\n",
    "cgen = [gcm(th/float(num_c)) for th in range(num_c)]\n",
    "\n",
    "\n",
    "\n",
    "for i,dec in enumerate(decs):\n",
    "    \n",
    "    ind_dec = np.argmin(np.abs(bins-np.sin(np.deg2rad(dec))))\n",
    "    # conversion to flux normalisation at 100TeV in 1/GeV /cm2/s\n",
    "    const = 10**(-2*gamma) / 1.e3\n",
    "\n",
    "\n",
    "    results_time = dict()\n",
    "    for key, resi in results.items():\n",
    "        res_time = np.zeros_like(t_news, dtype=float)\n",
    "        for k, (key1, res1) in enumerate(sorted(resi.items())):\n",
    "            res_time[k] = res1[ind_dec]\n",
    "\n",
    "        results_time[key] = res_time\n",
    "\n",
    "    res_time_old = np.zeros_like(t_old, dtype=float)\n",
    "    for k, (key1, res1) in enumerate(sorted(results5_10.items())):\n",
    "        res_time_old[k] = res1[ind_dec]\n",
    "\n",
    "\n",
    "    #ax.plot(t_old,res_time_old*const , lw=2)  \n",
    "\n",
    "    \n",
    "    for key, resi in results_time.items():\n",
    "\n",
    "        if key == 'icecube': \n",
    "            ax.plot(np.concatenate([t_old,t_news])+10, np.concatenate([res_time_old,resi])*const, \n",
    "                label=r'$\\delta$ = {0:.0f}deg'.format(dec),\n",
    "               lw=2., color=cgen[i] , ls = lss[key])\n",
    "        else:\n",
    "            ax.plot(np.concatenate([t_old,t_news])+10, np.concatenate([res_time_old,resi])*const, \n",
    "               lw=2., color=cgen[i] , ls = lss[key])\n",
    "        \n",
    "        \n",
    "\n",
    "ax.set_yscale('log')\n",
    "ax.set_xlabel(r\"Time [years]\",fontsize=fs-2)\n",
    "ax.set_ylabel(r\"$\\phi^{\\mathrm{thr}}_{100\\mathrm{TeV}}$  [$\\mathrm{GeV}^{-1} \\mathrm{cm}^{-2} \\mathrm{s}^{-1}$]\",\n",
    "              fontsize=fs-2)\n",
    "    \n",
    "ax.tick_params(axis='both', which='major', labelsize=fs-4)\n",
    "\n",
    "fig.legend( fontsize=fs-2, loc='upper center', mode='expand',\n",
    "            ncol=3, frameon=False)\n",
    "\n",
    "ax.set_xlim(5,21)\n",
    "if gammas[0] ==2.:\n",
    "    ax.set_ylim(8e-21,5e-18)\n",
    "elif gammas[0] ==2.:\n",
    "    ax.set_ylim(3e-21,5e-17)\n",
    "#else:\n",
    "#    ax.set_ylim(3e-18,5e-15)\n",
    "\n",
    "fig.tight_layout()\n",
    "\n",
    "plt.subplots_adjust(top = 0.88)\n",
    "fig.savefig('plots/PLENUM_ps_disc_pot_time_evolution_v2_{0:.1f}.pdf'.format(gammas[0]),\n",
    "               bbox_inches=\"tight\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}