controller_performance_plotting.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
     ]
    }
   ],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "import sklearn.linear_model\n",
    "import sklearn.preprocessing\n",
    "import sklearn.decomposition\n",
    "import matplotlib.ticker as ticker\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "import math\n",
    "import scipy\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "from cycler import cycler\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0)\n",
    "plt.rcParams[\"axes.prop_cycle\"] = cycler('color', sns.color_palette(\"muted\")) # chooses a nicer default set of colors.\n",
    "sns.set_context(\"poster\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
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       "\n",
       "    this.ws = websocket;\n",
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       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
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       "        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",
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       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
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       "    this.imageObj.onload = function() {\n",
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       "\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",
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       "\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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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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3aPkNYz8V/BKDCDtvtOfvQYcx/lWS0vLNNd1xfubxpj9wuGw/2pedsv0h3ybvbHWeiN5QpS9kTLGPBSPx2W63bbHv94gdAvna2Ox2IT8BvJu5O7TWssrKrnNdV0ZtzIsmUwOyL5qVUjfFHMNAjhQay03jPntyroR8tRhT631C9lJJNq7TtrxKsq/vYsq8/qVjLf6XGstY17W2fI+g7O01hH5YTEBpJTzkdc2Y7GYhKK214c/S1pmooIP8/rzQa21PAXIbR38rtngExClVHvXTLGf80ICSFH9tqHPTTQa/ZUxRr4IkHB2ZSgUenjmzJnvt9fX/DsKUKAwAQaQwpy4FwVyAtFo1H/yYIzZKh6Pyz/WBW+RSOQf8i2a4zi7tbS0vNS2YCQSuUueaOS9/pEdA/IPrbUM7M5tbW/ssz9o78Yl+6qOUuoAGZeRX0/m5kgGgcvNkYwNkE0GhJ5rjJHZd2QwbNvNtBdAZGxGIpGQcLHB44xGo4cbY2QAtnzLKr+HFsv74sYYeUIjNw7+5rquHJejte7WHrLrujIZwBbZG9q8MSDnxGIxGQyf2zp6NaRtva7rynvuMrZGBtHL62LrbK7ryjf+TwF4LPvaRYkB5H6ttbTVtn5pW0LOYVrrR13XlUkO5Ka0o9/X/uxq2f7IO88/aK1/2k797QWQkpwBnK+1lgUY13OWvozH4zIWI/9n7c7A1UHflHQNyrgYrfV/27S7zg2r67rnApAndTKAep3jb8erKP/2rtMxY8Zs3trauqC9pwiy/5577hlesGCBvOIkTx5k3FGxAaTo8+noCxTXdV/MjC3yv9jIuzFfrz87+F2zoQAiTzzbu2aKvf4KCSBF9VsBnxt5qiZPPuV3kXwWZxtj5KnVr/NfQWyv//l3FKDA+gIMILwqKFCkQPZ9YBlUG4/H5Wax4K3tE462BaPR6FRjzNHZJyR5T0ACCSCe5+0vA0Lz2828Iy/fzi7SWsvsLrmVhuWpiAxANcbEHcfxB24bY2SWqk3bCyDt3fx1FJRkRqBevXodIMeklJLXYKRt+Z0k407khkqOQ2YwCmutZRar9TbXdT+UctknJAEFkPWecOQ3HIlEvqOUkkX8ck9ISgwg92qtZeaydba88RB+WMyu26GUkjAk38C2u6VSqScTicSaDd0wZkzbCyCBO9sGkOxq10Fcg22nbXVd9+zM7GCXaK1lRq8Ot2L926uovScc+ftlxj/JLHNLs09IinwCUvT5ZJ9wtHP9TZdX1bJPSIIOIEqp9r4cKPb6KySA+E9ygvrciFOmH2VSA/kySGYkkxkMZRKDw+PxOAehF/wvIXekQMffqNGGAhToQCA7iFq+/YrH4/KPUYebDFI0xjS3tLTIDavcUMt0uD/MfrvdtmA0Gn3SGPPt7JOEoAOIDNrWWsuA39w2evToLWTKWpliV2u9bebbWvnzstbW1tH5A+Uz5+C/x28bQNqcu4pEIjKwX6Zv7aOUGhOLxWLRaFTWWRm6du3aTebOnSuDV/M3GTMjwclkXj/KjgGRWbBKfgISjUb3kvf/286ElG04EonIE6qpAHJPGEoJIO2NP5A28q6BHWTK4Mz0sjLr146xWOzVzj6YpQSQcjjbBJCgr8G2ASQzy5QE6Zu11jKIusOtWP/2KsoEDAnwK/OeMrb3GYxrrWWq6aKegJRyPjI1cnuvPrquG5Pm88Yg+U802uvPUp6AtPfZLOH6KySAyAxngX1u2vZrZq0nmUpdnqTJeDGZtY0bBShQoACfgBQIxd0okBUYM2ZM79bWVnkyIDMhyaBEmUq0vU1Fo9F/GGO+k/mG7GHXdeVm50ZjzNXxeFzWwcjfQq7ryuDn3itWrBiwYMGClWUIIFO01jL9am7LjnnITgOaXYEZwLNaaxkPkb9vdgaddl/BKuQJSFNTU/dQKDRCAkZbNNd15bUsmT73KFnHJDvjGIDvaq1lfExuy1vw7CWt9a7ygyCegGRmGJMnDZ9kbirWWUAyb+YfmYrYX7OklACSqV+e+qxTv+u6cm0NcRxnkMzk5LquzG41Ljv1b1uzaDQ6Mn/tmBIDiD+zW5DONgEk6GuwbQBpamraznEcmWZ6vYHymZ9NNMb8Ix6P/75Y/45+U7quK+FRpste79VN13XF/iFZDyQej8sXFEUFkBLO53Sl1CmxWOy3+cebmYBBJp2Qp6H+DXUlnoAU+Dn/t9Za1h/JTStujNkrO8ub67oyecVcrbWsSyP7BPa5kd8JjuP0za5j1OZ3osygNlrWSspOXdzRNcC/pwAFvhRgAOHVQIESBCKRiAwkl3UGZM0CmZ1onZvjpqamvo7jyPStsl5H/uxSA0Oh0NzM4mjbaq3lSYO/5c0EtN5NCIAgXsGSbzJlrIWs97Eg267ruo/KwF1jzC/khiuzAN/7mXUH5B9zf+rbzBTCsq+MCdnEcZzR2fVK8tYBWe/9+3am4ZWpdrfxPG/7RCIhC+/lNtd1ZfD33p7n7SLraEQikey0tNP79Omzd/6MUXk3LbnZfIIIIHIweVMtr3OTlrGRgbuh7t27b/nOO+/IYmSlBhBjjDk5Ho//Lq8v/BtRWdsjO+lANBrdxhgjCyB+mEqldshfJC4ajR5kjJE+WW8WovYCQOZY13sFqxzONgEk6GuwvZWzI5HIO7KWTtuZjbKvQRpjjozH4w8V67+BAOJ/+SDrouSP/ZGnIytWrHhO1kbJn+2tmFewMr8/ijofY8wsWVsoO5Nd5tq4FoAsUnpFdorsEgKIP4ZKxkbEYjGZvc3fNvTZLOH66/QJSLH91tF5Zr6QkC+GZIFXeQrpr5UkW2bWMJlWvdvgwYMH5M9SWMI/KyxCgS4lwADSpbqbJxukgLz2kHmaITMwyZSi04wxXziOMyqzAJxMN/pwa2vrsbKmRd4/xLJ4odx0ymrDsuaBvNIkq1sfCGBeKBT6pky/KvuX4QmIzMK1n1LqkcwCffIes6x0PnPt2rVjs8eZN8PWS/JNsFJKvqmXGY2uUUptbYz5vrxCBOCWeDz+cDEBJLNYmdw0y3oQ8q1vIjOwU562yGxP/8yfGjU7MD+zCns26MkCivI0Rubfl/ex/acIebNgnV3qIPTMjcXwcDgss0sNlBt8WYcjs/DYYRK+lFLHxWIxCaD5N1cyBfBxWmtZn6TDLa9P5Vy2y6zJIAsRbi71yirnSql986f7zKzwLuszyDVztzFmibyjn5la9mPHcXZtaWmRGaY2+I115uftDgQP2tkmgMhxBnkNthdAmpqadnIcJ7umw5+UUh95nrd3ZkHNx/MXIizGfwNdL4PqnzbGyGrt/1ZKPWuM6Snr1WQWFZWFTXOTHhQbQIo5n2g0eqkx5pzMooOPGmNklXpZFFMmWHhzxYoVu8oT2M6up/aOMXPjL2usyCtnMlucPEk8b0OfTWmnyOuv0wCSOfaLZdC77efGdV0ZPC+f73ky7bBS6mNjzMaZ9ZPkS5r1BtYH+W8N66LAV1GAAeSr2Ks8p4oJNDU1DXUcR77ZlPUz5MlAr8xAYRnI+Zv8GZ3yD6q5uXlfz/PGyyJuAGT61PkypsQYc3kikcgNNM78A/9M5glIbhXnzD/YsnbHbslkclT+qwHZMsaYO9pOwyvf9hpjhiil5N3lZglMAJ5IpVJn5n+znllwT74NlYDSB0BMKXV9LBabmrnBuFcpJeNbZNaq8ZkAIjdW32w7A1H2Z/nHGY1GZSrecUqpXYwxgwDI+iYxY8y93bp1uzG7qnfGTMZ6yGxKx8sxZ/5OVni/c/DgwTfmf+tYwBMQmYb3olgs1uE0vNl+ikajg2VVdZn+NjNAXr75lBWs5fU5WdE6t5X4CtZdoVBoUiqVkjVJ5BWyHgDeMsZcFI/H/cX78rdIJPI9eW0mE1rkmlmolPpHKpW6NJFIyGxg/pZd0bm9NV/yAsgwrXW4TROBOrfXfmYNkvXazluFOtc3QV6D7QUQOffRo0dv5XneRZlQ0M8Y84FSSq5pWRwytx5N5vNWkP+GfvnI64dKKXkFUiaaaJTrXiklr/DcGovFZLXx3Nbe57izX2xFno88xZWV1mXBS5nkQQLsAw0NDVfPmDFjRSHXU0fHGI1GJxljpG65pv+mtT5qQ5/NEj7nHQWQOVprcc1tQX1uotHokcYY+fJoK1ksVRb6lDWIlFK3ZBfP7Kx/+HMKUOBLAQYQXg0U6AICedPwtreQVhcQqJ1TzHsCcpfWWhaH5EYBClCAAhToUgIMIF2qu3myXVWAAaR2ep4BpHb6gkdCAQpQgALVEWAAqY47W6VARQUYQCrKvcHGGEBqpy94JBSgAAUoUB0BBpDquLNVClRUgAGkotwMILXDzSOhAAUoQIEaFGAAqcFO4SFRIGgBBpCgRUuvL29iARkDIlMjc6MABShAAQp0KQEGkC7V3TxZClCAAhSgAAUoQAEKVFeAAaS6/mydAhSgAAUoQAEKUIACXUqAAaRLdTdPlgIUoAAFKEABClCAAtUVYACprj9bpwAFKEABClCAAhSgQJcSYADpUt3Nk6UABShAAQpQgAIUoEB1BRhAquvP1ilAAQpQgAIUoAAFKNClBBhAulR382QpQAEKUIACFKAABShQXQEGkOr6s3UKUIACFKAABShAAQp0KQEGkC7V3TxZClCAAhSgAAUoQAEKVFeAAaS6/mydAhSgAAUoQAEKUIACXUqAAaRLdTdPlgIUoAAFKEABClCAAtUVYACprj9bpwAFKEABClCAAhSgQJcSYADpUt3Nk6UABShAAQpQgAIUoEB1BRhAquvP1ilAAQpQgAIUoAAFKNClBBhAulR382QpQAEKUIACFKAABShQXQEGkOr6s3UKUIACFKAABShAAQp0KQEGkC7V3TxZClCAAhSgAAUoQAEKVFeAAaS6/mydAhSgAAUoQAEKUIACXUqAAaRLdTdPlgIUoAAFKEABClCAAtUVYACprj9bpwAFKEABClCAAhSgQJcSYADpUt3Nk6UABShAAQpQgAIUoEB1BRhAquvP1ilAAQpQgAIUoAAFKNClBBhAulR382QpQAEKUIACFKAABShQXQEGkOr6s3UKUIACFKAABShAAQp0KQEGkC7V3TxZClCAAhSgAAUoQAEKVFeAAaS6/mydAhSgAAUoQAEKUIACXUqAAaRLdTdPlgIUoAAFKEABClCAAtUVYACprj9bpwAFKEABClCAAhSgQJcSYADpUt3Nk6UABShAAQpQgAIUoEB1BRhAquvP1ilAAQpQgAIUoAAFKNClBBhAaqy7Fy363NTYIfFwKEABClCAAhSgAAXyBAYN6st7aIsrgngWeOUoygBSDlXWSQEKUIACFKAABYITYACxs2QAsfMLvDQDSOCkrJACFKAABShAAQoEKsAAYsfJAGLnF3hpBpDASVkhBShAAQpQgAIUCFSAAcSOkwHEzi/w0gwggZOyQgpQgAIUoAAFKBCoAAOIHScDiJ1f4KUZQAInZYUUoAAFKEABClAgUAEGEDtOBhA7v8BLM4AETsoKKUABClCAAhSgQKACDCB2nAwgdn6Bl2YACZyUFVKAAhSgAAUoQIFABRhA7DgZQOz8Ai/NABI4KSukAAUoQAEKUIACgQowgNhxMoDY+QVemgEkcFJWSAEKUIACFKAABQIVYACx42QAsfMLvDQDSOCkrJACFKAABShAAQoEKsAAYsfJAGLnF3hpBpDASVkhBShAAQpQgAIUCFSAAcSOkwHEzi/w0gwggZOyQgpQgAIUoAAFKBCoAAOIHScDiJ1f4KUZQAInZYUUoAAFKEABClAgUAEGEDtOBhA7v8BLM4AETsoKKUABClCAAhSgQKACDCB2nAwgdn6Bl2YACZyUFVKAAhSgAAUoQIFABRhA7DgZQOz8Ai/NABI4KSukAAUoQAEKUIACgQowgNhxMoDY+QVemgEkcFJWSAEKUIACFKAABQIVYACx42QAsfMLvDQDSOCkrJACFKAABShAAQoEKsAAYsfJAGLnF3hpBpDASVkhBShAAQpQgAIUCM0ZDpcAACAASURBVFSAAcSOkwHEzi/w0gwggZOyQgpQgAIUoAAFKBCoAAOIHScDiJ1f4KUZQAInZYUUoAAFKEABClAgUAEGEDtOBhA7v8BLM4AETsoKKUABClCAAhSgQKACDCB2nAwgdn6Bl2YACZyUFVKAAhSgAAUoQIFABRhA7DgZQOz8Ai/NABI4KSukAAUoQAEKUIACgQowgNhxMoDY+QVemgEkcFJWSAEKUIACFKAABQIVYACx42QAsfMLvDQDSOCkrJACFKAABShAAQoEKsAAYsfJAGLnF3hpBpDASVkhBShAAQpQgAIUCFSAAcSOkwHEzi/w0gwggZOyQgpQgAIUoAAFKBCoAAOIHScDiJ1f4KUZQAInZYUUoAAFKEABClAgUAEGEDtOBhA7v8BLM4AETsoKKUABClCAAhSgQKACDCB2nAwgdn6Bl2YACZyUFVKAAhSgAAUoQIFABRhA7DgZQOz8Ai/NABI4KSukAAUoQAEKUIACgQowgNhxMoDY+QVemgEkcFJWSAEKUIACFKAABQIVYACx42QAsfMLvDQDSOCkrJACFKAABShAAQoEKsAAYsfJAGLnF3hpBpDASVkhBShAAQpQgAIUCFSAAcSOkwHEzi/w0gwggZOyQgpQgAIUoAAFKBCoAAOIHScDiJ1f4KUZQAInZYUUoAAFKEABClAgUAEGEDtOBhA7v8BLM4AETsoKKUABClCAAhSgQKACDCB2nAwgdn6Bl2YACZyUFVKAAhSgAAUoQIFABRhA7DgZQOz8Ai/NABI4KSukAAUoQAEKUIACgQowgNhxMoDY+QVemgEkcFJWSAEKUIACFKAABQIVYACx42QAsfMLvDQDSOCkrJACFKAABShAAQoEKsAAYsfJAGLnF3hpBpDASVkhBShAAQpQgAIUCFSAAcSOkwHEzi/w0gwggZOyQgpQgAIUoAAFKBCoAAOIHScDiJ1f4KUZQAInZYUUoAAFKEABClAgUAEGEDtOBhA7v8BLM4AETsoKKUABClCAAhSgQKACDCB2nAwgdn6Bl2YACZyUFVKAAhSgAAUoQIFABRhA7DgZQOz8Ai/NABI4qXWFxhg8/vgjePvtN9GjRw/su+8B2Hrrba3rZQUUoAAFKEABCtSnAAOIXb8xgNj5BV6aASRwUusKEwmN6667MldPv379cPnl10EpfnyscVkBBShAAQpQoA4FGEDsOo13UHZ+gZdmAAmc1LrC6dOfx9Spd6xTz7XX3oSePXta180KKEABClCAAhSoPwEGELs+YwCx8wu8NANI4KTWFf7jH3/DX/7y0Dr1XHTRFRg0aDPrulkBBShAAQpQgAL1J8AAYtdnDCB2foGXZgAJnNS6wvvvn4pp055ep55x485GU5NrXTcroAAFKEABClCg/gQYQOz6jAHEzi/w0gwggZNaV3jLLTfhzTdfW6eeE074GXbY4RvWdbMCClCAAhSgAAXqT4ABxK7PGEDs/AIvzQASOKl1hVddNQnvvz9nnXoOPfRIfOc7+1nXzQooQAEKUIACFKg/AQYQuz5jALHzC7w0A0jgpNYVnnnmaVixYvk69eyxx9446qgfWtfNCihAAQpQgAIUqD8BBhC7PmMAsfMLvDQDSOCkVhWuWrUS48efsl4dX/vaVjjllHFWdbMwBShAAQpQgAL1KcAAYtdvDCB2foGXZgAJnNSqQnn1Sl7BarttssmmmDRpslXdLEwBClCAAhSgQH0KMIDY9RsDSMavubl5rOd59wJoTCaTI2bPnv1BZ7SRSOQHSqkJAJoBrADw99bW1glz5sz5uLOyHf2cAaRUufKUe/nl6fjzn29LVx7qCaRW5RqaMuW36N69e3kaZq0UoAAFKEABCtSsAAOIXdcwgABwXVfepbkcwCIAQ5LJ5MjOAkgkEvm+UmoqgN8qpe72PG8zpdQ1AJYPHjx47LRp05KldA0DSClq5Svz0EP34emnn/QbUP2iMMtnA16r/+cJE87DyJGN5WucNVOAAhSgAAUoUJMCDCB23dLlA0hzc/Oenuc9ppT6CYBtjDHnFhJAXNedDWCu1nrvbBdEo9FdjDEvGGNOjMfjt5fSNQwgpaiVr8z110+G1i1+A85mu8J8noBZ9ZH/56OPPha7775X+RpnzRSgAAUoQAEK1KQAA4hdt3T5ADJ69OiIEM6cOTMejUYnFRJAXNfdFsAbxphfxOPx3+V3geu6HyqlXovFYgeV0jUMIKWolaeM53k444xTsHr1ar+B0JaH+gHEW/KO/+edd94Vxx57QnkaZ60UoAAFKEABCtSsAAOIXdd0+QCSz1dEADkWwB0A9tRav9AmgPwTQERrPaKUrmEAKUWtPGXmz5+Hyy+/MFO5g3D0JzDL5yC1QLoY2GyzzXHhhfLmHjcKUIACFKAABbqSAAOIXW8zgOT5FRFAxgOYbIzZKh6Pz2wTQO5WSh0ci8V6ldI1DCClqJWnzLPP/gsPPHC3X7nqMQjhkYfDtC5HMnFnrsErrpiCfv36lecAWCsFKEABClCAAjUpwABi1y0MICUEkEgkcr5S6mLP89xEIjGrTQD5E4Afaq1DpXQNA0gpauUp87vf/Rpvv/2GX7mzyXYIDdrZ/+/WxF1A6+f+fx9//P/h61/fqTwHwFopQAEKUIACFKhJAQYQu25hACkhgLiu6z8B8Txv60Qi8V6bACJT+X5Xa927lK5JJlOmlHIsE6xAa2srTjrpJ1+O/xh2IJzew/xGkgufhVmafvC166674ZRT1l+oMNijYW0UoAAFKEABCtSSQDgc4j20RYcQr4QAEo1GjzHG/NnzvL0TicRz+f6RSORZpdRQrbU/uL3YjQGkWLHy7P/WW2/hiisy4ztUGGH3RCgn/VDLWz4bqfn/8P+7d+/e+P3vb0EoVNIDr/IcPGulAAUoQAEKUKCsAgwgdrwMICUEkKampjGO47xjjDktHo//Or8LXNf9BMDTWuujS+kavoJVilrwZaZOvQPTpz/vV6z6jER46P65RozXiqT+I2BS/t+deup4NDePCf4gWCMFKEABClCAAjUpwFew7LqFAaSEACJFXNd9Tym1NBaLfTNbheu6cpf6N2PM4fF4/OFSuoYBpBS1YMskk0mcc844fPGFLG4PhAZ/B06/dR9oJef9HWbFHP/n3/zmbvjhD48P9iBYGwUoQAEKUIACNSvAAGLXNV0+gLiuu5tSyhVGY8whAP5XKXUOgMXyd7FY7DbXdScCuED2i8Vi/l1nJBL5rlLqUaXUn40xtxtjhimlrgaQ0FrvUWq3MICUKhdcuTfffA233HJTukL/9avjoZyGdRrwPo8j9WF6Ot4ePXrgyiunoFu37sEdBGuiAAUoQAEKUKBmBRhA7LqGAcR1ZcXyH3XAaLTWYdd1ZTGIC+TBh9ZaVkD3t6ampgMdx5FwIu/fLAPwkOd55yYSifQUSSVsDCAloAVc5Oabr8e7776dzh/9XIQHf3u9FoyXRDJ+B+Ct9X/2ox+diJ122iXgI2F1FKAABShAAQrUogADiF2vdPkAYscXfGkGkOBNi6nx008X4cILz5GnYX6x0PCD4fQa0m4VqYXPwVs6w//ZlluOxFlnSUblRgEKUIACFKDAV12AAcSuhxlA7PwCL80AEjhpURXKwoOyAKG/dR+A8MijoFT7HxOzejGSc+7L1T9+/LlobGwqqj3uTAEKUIACFKBA/QkwgNj1GQOInV/gpRlAAictuMIVK5bj/PMnYO3a9GtVzuZ7ILTxhme3Sr7/GMzKD/39t976f/Dzn59acHvckQIUoAAFKECB+hRgALHrNwYQO7/ASzOABE5acIWPPfYQnnzyb+n9Qz0RbjoWyglvsLy34gOk5v01t88551yIYcO2LLhN7kgBClCAAhSgQP0JMIDY9RkDiJ1f4KUZQAInLajC5cs/x8SJZ2HNmjX+/s7AnRDadPtOy8pYkdTcB2FWy/IvwFZbbYNf/OJXnZbjDhSgAAUoQAEK1K8AA4hd3zGA2PkFXpoBJHDSgiq855478cILz6b39Z9+/HC9qXc7qshb8T5S8zJPTgCcdtoERKOjC2qXO1GAAhSgAAUoUH8CDCB2fcYAYucXeGkGkMBJO61wwYL5uOyyC3MzXzmb7YbQgK07LZfdwX8K8v6jMKsW+n81dOgwnH32hXAcp+A6uCMFKEABClCAAvUjwABi11cMIHZ+gZdmAAmcdIMVep6HKVOuwqxZ8fR+3fojPEpmvgoVdSBm1SIk5z6YK3PEET/AXnutv35IUZVyZwpQgAIUoAAFalKAAcSuWxhA7PwCL80AEjjpBiucPv15TJ16R26f0LDvwuk9vKSDSC54BmZZi19WVkefOPEy9O+/cUl1sRAFKEABClCAArUrwABi1zcMIHZ+gZdmAAmctMMKlyz5DJdeegFWrVrl76P6NCI8dN+SD8AkVyE5+x4gtdqvY8wYGZB+WofriJTcEAtSgAIUoAAFKFBVAQYQO34GEDu/wEszgARO2m6FMm7jppum4L333k3/3OmO8KijoRp6WR2At7QFqYXP5Oo45pjjsMsuu1vVycIUoAAFKEABCtSWAAOIXX8wgNj5BV6aASRw0nYrfOaZf+LBB+/J/Sw0+Ftw+kWtG/cHpM9/AmbF+35d3bt39wekb7bZ5tZ1swIKUIACFKAABWpDgAHErh8YQOz8Ai/NABI46XoVfvDB+7jmmsuQTCb9n6neIxEaul9gr0qZ1i+QnHNf7lUsWZjwjDPORUNDQ/lPji1QgAIUoAAFKFB2AQYQO2IGEDu/wEszgAROuk6FK1d+gSuuuBiLF3+a/vtwL4RHHgUV7rHBhlMfT4f32TtwBmyN0Ga7dHqQ3vK5/pOQ7LbrrnviBz/4UafluAMFKEABClCAArUvwABi10cMIHZ+gZdmAAmcNFehTLn7u9/diHfffTvzdwqh4QfB6TVkg40aL4lk7A8AjDwvQTh6EpQT7vRAUx+9AG/JO7n9jj32BOy8866dluMOFKAABShAAQrUtgADiF3/MIDY+QVemgEkcNJchY899hCefPLLFcudQTsjtMl2nTZoUmuR1Lfm9gu7P4EKdeu8nEllFij82N83HA7j9NPPwsiRjZ2W5Q4UoAAFKEABCtSuAAOIXd8wgNj5BV6aASRwUr/CV155GbfffkuuctVnFEJD9i1o3EepAUQaM60rkJzzAJBKT/Xbt28/nHnmBRgwYEB5TpS1UoACFKAABShQdgEGEDtiBhA7v8BLM4AETopEQuPGG6/JDTpH9wEIjzgMyilsULhNAJGz8VYuROr9x+S//JMbMmQoxo8/Bz169Az+ZFkjBShAAQpQgAJlF2AAsSNmALHzC7w0A0iwpB9//BGuueZyfPHFinTFoZ7p8NGtb8EN2QYQP4S0WR/ka1/bCj//+akIhTofS1LwgXJHClCAAhSgAAUqIsAAYsfMAGLnF3hpBpDgSJctW+ZPt5ub8UqFENryYDg9i1uTI4gAImeVWvQyvMWv505wp512gQxMV4ofw+B6nTVRgAIUoAAFyi/AAGJnzDsfO7/ASzOABEO6atUqXH/9VZg374NchTLmw+lb/ADwoAKIv0jhgn/BfB7PHdO++x6Agw8+LJiTZi0UoAAFKEABClREgAHEjpkBxM4v8NIMIPakra2tuOmmKdC6JVeZs9muCA3YpqTKgwog0rjxUkjN+yvMyg9zx3L44Udj7733KenYWIgCFKAABShAgcoLMIDYmTOA2PkFXpoBxI40lUrh1ltvxltvvfFl+NhkO4QG7VxyxUEGED+EpNYg+f6jwJrFuWP68Y9/gh13/GbJx8iCFKAABShAAQpUToABxM6aAcTOL/DSDCClk8orTnfe+Ue8/PL0XCWqXzNCW+xlNc4i6ADih5DkSiTnPgy0fu4fq+M4+L//OxnbbNP5uiSlC7EkBShAAQpQgAJBCDCA2CkygNj5BV6aAaQ0UgkfDz10H5555qkvw0fvkQgNlbU+nNIqzZQqRwDxQ8jaZUjOfQRIrfRbkoUKTz75dESjo62Ol4UpQAEKUIACFCivAAOInS8DiJ1f4KUZQEojfeKJv+Cvf330y/Cx0RCEhh0A5dhPc1uuAOKHkNWL069jeWv8Y+/evTtOO+1MjBgxsjQIlqIABShAAQpQoOwCDCB2xAwgdn6Bl2YAKZ70ueeewX333fVl+OgxCKHhB0GFuhVfWTslyhlApDlv1UdIvf8XeS/Lb71Xr97+QoWbb75FIMfPSihAAQpQgAIUCFaAAcTOkwHEzi/w0gwgxZG++up/cPvtt0BewfK3bhsjvOWhUOEexVW0gb3LHUD8ELJiHlLz/pZbLb1//41xxhnnYsCATQI7D1ZEAQpQgAIUoEAwAgwgdo4MIHZ+gZdmACmctKVlBm666XrIzFf+1tAnHT4aehdeSQF7ViKA+CHk81lIffhk7ojkCYg8CZEnItwoQAEKUIACFKgdAQYQu75gALHzC7w0A0hhpPPmvY/rrrsSa9akx04g1BPhEYdCdetfWAVF7FWpAOKHkCXvIfXRtNzRNTY24Ze/PAPdugXzOlkRp81dKUABClCAAhToQIABxO7SYACx8wu8NANI56RLlnyGyZMvxbJlS9M7qzDCWx4C1XNQ54VL2KOSAUQOL/Xpq/A++W/uSLff/us44YSf+lP1cqMABShAAQpQoPoCDCB2fcAAYucXeGkGkA2Trl692n/yMX/+B5kdHYSG/S+c3sMD74tshZUOIDKexfvoeXhLZ+TOad99D8DBBx9WtnNkxRSgAAUoQAEKFC7AAFK4VXt7MoDY+QVemgGkY1K5Mb/11t/ijTdeze0kiww6/cu7bkalA4icnDEeUvOegPkiG7SAE0/8GcaO/Ubg1xwrpAAFKEABClCgOAEGkOK82u7NAGLnF3hpBpCOSZ966gk8+uiDuR2cTbZDaNDOgfdB2wqrEUD8EJJai+T7jwBrFvuHJONAJkw4H0OGDC37ObMBClCAAhSgAAU6FmAAsbs6GEDs/AIvzQDSPumsWQlMmXIlPM/zd1C9hvuvXtmucl5IB1YrgPghZO3nSM59AEilB9vLzFhnnTXRX7CQGwUoQAEKUIAC1RFgALFzr6sAMmbMmN4zZsxYkT3lESNG9O/evfvuANaGw+FnZsyYsdaOo/qlGUDW74NVq1bisssuxGefpZ8EoKEvwiOPgApV5ia8mgFETje9RsjjOZhddtkdxxxzXPUvVh4BBShAAQpQoIsKMIDYdXxdBJDBgwdv1Lt3b3n3ZrXW+ntyyk1NTds7jvMUgI0zBC2O4+ze0tKSuUu1g6lWaQaQ9eXvvvvPePHF7NS0DkIjDoXTc7OKdVG1A4icaGrRy/AWv54751NPHY/m5jEVM2BDFKAABShAAQp8KcAAYnc11EUAiUQiVymlfqWU+nksFvujnLLruv8BsC2AccaYlUqp64wxf4rH46fbkVS3NAPIuv6JhPZnvcpuzsAdEdp0bEU7qRYCiDEppOY+ArN6kX/um246EOefP4nrg1T0SmBjFKAABShAgbQAA4jdlVAvAUQD+Fs2XLiu2wzgPQBTtNbjM4HkIgA/1Fo32ZFUtzQDyJf+Mt5j8uRJ+OCD99N/2X1ThEceXpFxH9mjMK3LkfrkFZhlLbkDU/2aERr4daiGPhW9WMzqT5GcIw8C0+NgDjnkCOyzz/4VPQY2RgEKUIACFKAAA4jtNVAXAcR13ZXGmJ/E4/G75YSj0ehpxpjrHMfZraWl5SX5u0gk8n2l1O1a6x62KNUszwDypf5rr/0Xt932u9xfhEYcVuFXr1anb/hbP1//kvDHoRwOFars5Zb6+CV4n73pH0/Pnhth0qSrsNFGvap5ybJtClCAAhSgQJcT4BMQuy6vlwCySCl1dt7rV08A2FFrPTD7dXA0Gj3RGHON1jo7JsROpkqlGUDS8LLmx1VXXZJ7+qH6NCI8dN+K9kryw3/CfB7vsE3VN4LwkO9U9JhMajWSiamAl54V69BDj8B3vsOnIBXtBDZGAQpQgAJdXoABxO4SqJcA8jyA5VrrA5qbm8d6nvcygLu01sdnT9913XuUUm4sFqvsAAE7//VKM4CkSWbPTuCaay7P+YRHHQ3VfUDA2h1XJwEoqf+Yu9Fvd0+nO8LuCVCqsh+j1Cf/hfdpejHGAQM2wSWXXAXHcSpmw4YoQAEKUIACXV2AAcTuCqjsnVOJxxqJRA5TSj0AYBkAefF+NYAdtNb+i/mu614LQAapj4vFYjeU2ExNFGMASXfD/fffjWnT/uX/t9poCMJbHlzR/jFrlyE5a2qnbYYbj4Hq1q/T/YLcwbR+gWTiztxYkPHjz0FjYyTIJlgXBShAAQpQgAIbEGAAsbs86iKAZELGIQCOVEp1S6VS1yQSCXkK4m8yI5ZS6vVYLPZzO47ql2YASb9+dcEFZ+bW/QhtsRec/qMr2jlmzWdIzr630zYr/WQme0DJDx6H+WKe/8dvf3s/fO97R3Z6rNyBAhSgAAUoQIFgBBhA7BzrJoBs6DSbmpq6JxKJ9Evxdb4xgABLlnyG8847I9eT4chxUOGNKtqztR5AUp+9A+/jF3yTkSMbMWHCeRX1YWMUoAAFKECBrizAAGLX+zUfQMaOHduwfPlyedVqvNb6UbvTrf3SDCDAO++8hd/+NvMmXUMfNDQdW/GOq/UA4q36GKm5D/ku3bt3x7XX3sRxIBW/StggBShAAQp0VQEGELuer/kAIqfnuu4HAK7UWt9sd7q1X5oBBHj++Wdx770yxgFQvYYhPPzAindcrQeQtosjTp58A3r3ruy6JBXvFDZIAQpQgAIUqBEBBhC7jqiXACLjP67JDDL/G4CU3WnXbmkGEOCpp57Ao4/KgnuA6tuE8JB9Kt5hNR9AZJauFlkjxfg2MhOWrI7OjQIUoAAFKECB8gswgNgZ10sAeVgp1csYsxeANcaYhUqpFW1PXSllOA2v3QVRC6WffPJveOyx9OtFDCDt94g/TXBeALn44isxcOCgWug+HgMFKEABClDgKy/AAGLXxfUSQLwCT9NorUMF7luTu/EJCPDii9Nw991/TgeQXkMRHn5Qxfuq5p+ApNYgqW/LuVxzzW+w0UaVHahf8U5hgxSgAAUoQIEaEWAAseuIugggdqdYX6UZQIB3330bN998fbrjwr3REPlRxTux1gNI20Ho1113c8UXRKx4p7BBClCAAhSgQI0IMIDYdQQDiJ1f4KUZQIBly5binHPG5WyrPQ1vOBzG4MGD0b9/fyxduhQLFixAMplM56MKr9CeRcmfhrepycW4cWcHfi2yQgpQgAIUoAAF2hdgALG7MuopgIQikcixSqk9AAz3PO+MRCLxhpx+JBI5oLW19em5c+fKCul1vTGApLvv/PMn1MRChBI+9tprL5x44okIhUJIpVK47bbb8Oyzz/ohpFoBJPnBX2G+kMnhuBBhXX/gefAUoAAFKFCXAgwgdt1WFwEkGo32Mcb8C8AOMixApv6RAenxePz5MWPGDGhtbV0I4J21a9d+e+7cuUvtSKpbmgEk7X///VMxbdrT/n+rXsMRHv7dinZM9hWs4cOHY/LkyX74yG4SQiZMmIB58+ZVJYCY5Cok438CkB4aJU8/5CkINwpQgAIUoAAFKiPAAGLnXBcBJBKJXKWU+pUx5gxjzBOO48SNMXtKAJHTj0ajPzTG/AHAb7XWX767Y2dTldIMIGn2RELjuuuuzPVBuPEYqG79KtYn2QCyzTbb4IILLliv3UmTJuHtt9+uSgBJLX4D3qJ/+8fUr19/XHbZNVyEsGJXBhuiAAUoQAEKAAwgdldBXQQQ13XjAJ7UWp8yatSofuFweEl+AMmEkBuMMQdprUfakVS3NANI2l+mmb300olYuPBD/8/OxlsjtPluFeucWn0CYrwUkrOmAsn0LNQHHHCw/z9uFKAABShAAQpUToABxM66XgKIjO04SWt95wYCiDwFuU1r3d2OpLqlGUC+9H/hhWm45570dLxQDvynIA2VWe07G0BqbQxI6rN34X3sP/iDHNukSZP9pyDcKEABClCAAhSonAADiJ11vQSQTwFcpLX+TUcBxHVdmQZovNa6rpeDZgD58oJubW3FxRefmxuMrvpFER78LbsrvsDS+dPwyo3+FltsgY033hhLlizBwoULqzILlkmtTT/9SK3yz2LPPb+NI4/8QYFnxN0oQAEKUIACFAhKgAHETrJeAsijAEatWLFipx49ejS0fQWrqalpe8dxngLwgtb6UDuS6pZmAFnXf/r05zF16h25vwyNOAxOz83K3km1uA5I6uOX4H32pn/u3bp1g6x+zqcfZb8U2AAFKEABClBgPQEGELuLoi4CSHNz81jP814EMFcp9VdjzDil1B88z1umlNoZwC5KqdWpVGrX7NS8dizVK80Asq6953m46qpLMG9eespZdN8U4ZGHQanyLnhfawHErP4UyTkP5ma+OvDAQ7H//gdW70JlyxSgAAUoQIEuLMAAYtf5dRFA5BRd190VwM0AtmrnlN9WSp0ci8Wm23FUvzQDyPp9MGtWHNdee0XuB87AnRDadPuydlYtBRBjPKTmPgyzepF/zgMHDsL5509CQ0NDWQ1YOQUoQAEKUIAC7QswgNhdGXUTQLKnGY1GowCaAfQGsDyZTL43a9ashB1D7ZRmAGm/L+6++8948cVp6R+qEMIjj4DqPqBsHVdLAST16evwPnk5d66nnnoGmpu/VrZzZ8UUoAAFKEABCmxYgAHE7gqpuwBid7q1X5oBpP0+WrVqJSZNugBLly5JZ5AeAxEa8b2yvYpVKwHErF6M5NwHAJNedHDnnXfFsceeUPsXMo+QAhSgAAUo8BUWYACx69yaDCCu604s5bSUUiYWi00qpWytlGEA6bgn3nvvXfzmN9fldnA23QGhgd8oS9fVQgAxXhLJuQ8Caz7zz3HAgE1w3nmXoGfPnmU526biSQAAIABJREFUZ1ZKAQpQgAIUoEBhAgwghTl1tFetBpD0173Fb0ZrXd7RycUfU1ElGEA2zHXPPXfihReezeykENryEDgbbVGUcSE710IASX08Hd5nb+UOl69eFdJz3IcCFKAABShQfgEGEDvjmgwgTU1Ne5R6WolE4rlSy9ZCOQaQDffCmjVrcMUVF2HRoo/TOzb0RXjkkVChboF2X7UDiPfFPKQ+eDx3Tt/61j447LCjAz1HVkYBClCAAhSgQGkCDCCluWVL1WQAsTul+i7NANJ5/82dOwfXXHM5PC/l71yOBQqrGUBMajWSs+8Dkl/45zd48FCcddYFnPWq80uDe1CAAhSgAAUqIsAAYsdckwFk1KhRw0s9rdmzZ2cWjCi1huqWYwApzP/vf38cjz/+SG7n0JB94fRtLKxwAXtVK4AYY5D68CmY5bP8o5RV2M86ayKGDBlawFFzFwpQgAIUoAAFKiHAAGKnXJMBxHVdGQNiSjg1GQMSLqFczRRhACmsK2SBwilTrkRuBuZQd4RHHg3V0KuwCjrZq1oBxFumkVrwr9zRyWtX8voVNwpQgAIUoAAFakeAAcSuL2o1gNxRYgCB1vp4O5LqlmYAKdz/008/wWWXTYSMC5FN9R6B0ND9oZT9ZV2NAGJav0By9r2Alz6faHQ0fvnL8XAcp3AU7kkBClCAAhSgQNkFGEDsiO3v1OzaZ+k2AgwgxV0S06c/j6lTJa+mt9Dgb8HpJ2tV2m2VDiD+q1fz/w6zYq5/4D169PRXOx8woHyLLdoJsTQFKEABClCg6wowgNj1fV0GkFGjRvVraPDftVkei8WW2xHUVmkGkOL6Q27cb775esyY8U4mgfRAeNT3ocJ2a2VUOoB4nyf8sR/ZTRYblEUHuVGAAhSgAAUoUHsCDCB2fVI3AcR13VEALgKwv6zJlnfaHwF42PO8SxKJxCd2HNUvzQBSfB8sWfIZJk06H6tXr/YLq34uwoO/XXxFeSUqGUBMag2Ss+4GUqv8I/ja17bCySefHsirZFYILEwBClCAAhSgQLsCDCB2F0ZdBJDm5mbX87x/A9gYwBwAGsAqpVQvY8xoADJF0Hyl1E6xWGyBHUl1SzOAlOb/3HNP4777puYKh7Y81GqBwkoGkNRHL8Jb8rZ/7N26dcMFF1yKTTbZtDQIlqIABShAAQpQoOwCDCB2xHURQFzXvQeAfKX9Pa31C21PORqN7meMuRfAfVrrn9qRVLc0A0hp/jIr1uTJl+KDD9JjKNB9U4RHHlHyU4RKBZB0O/fl5lw45JAjsM8+8pCPGwUoQAEKUIACtSrAAGLXM/USQD5SSt0Ui8UmdXS6ruteBuDHWuu6XjCBAaT0C3rOnFm4+mq5DNKbzYD0SgWQ5LwncgPPBw3azB94Lmt/cKMABShAAQpQoHYFGEDs+qZeAsgapdSJsVjsrg0EkGMB3Kq17l4KSTQa3cEYcwWAHQHIvKcvK6XOjsVir3ZUXzQa7WOMOQ/AwQC2BLASwAuO40xsaWnJjIou7mgYQIrzarv37bffgldeeTn91w19EG78AZQKFV1pJQKIt3IhUu9/uZjiz372S2yzzXZFHysLUIACFKAABShQWQEGEDvvegkgHyqlbo/FYud3dLqRSOQSpdRPtNaDiyVpbGxsCoVCrwN4VUKIUkoWQjxbwojnedslEon0stRttkgk8qxSalsA5yul3gIw2BhzoYxJSaVSW8+aNWtescfCAFKs2Lr7L178KS6++Fwkk0n/B6Et9oLTX4YJFbdVIoAkP3gc5ov0JdLYGMG4cWeX/MpYcWfHvSlAAQpQgAIUsBFgALHRA+olgPxJnjI4jnNUS0vLk+0EgQOUUvJ05NFSFiJ0XVcWkjhEKTUsO63vmDFjere2tn4A4HGt9Y/btum6rgSPN4wxE+Px+KXZn7uuuxuA55RSJ8disd8W2z0MIMWKrb//3Xf/GS++OC39g4Z+macgxV3q5Q4gZtUnSM59IHfwp502wV94kBsFKEABClCAArUvwABi10fF3ZXZtVVy6dGjR2+ZSqX+C0CmBvoQQEvmdSdZC0Tu2rYAsFCeWGit5edFba7rfgbgKa310fkFo9HoVGPMAVrr/m0rjEajUWPMTGPMWfF4/OrszyORyP8opeRpyi+11jcVdSAAGECKFVt/f3kKcuGFZ0MGpssWGvq/cPqMKKricgeQ5IJ/wSyTydyAkSMbccYZ5/LpR1E9xJ0pQAEKUIAC1RNgALGzr4sAIqcYjUbl9aaLARwEYGDeaUvweDiVSk2aNWvWomI5Ghsbh4VCofeVUhe2HeQeiUTOU0pd4jhOY0tLS2Z6pS9bcF33CQBbOY5zdEtLy39c190cwC0AtnUcZ9uWlpbFxR4PA0ixYu3vf+utN+P119PDd1SvYQgPP7CoissZQExyFZJxeaiXDkg/+ckvsP32OxR1fNyZAhSgAAUoQIHqCTCA2NnXTQDJP80RI0b079atW69kMrli9uzZy2wImpubx3qe90p7r0y5rvt/AOQ1qp201q+0baepqam7UupmpdTxeT+TsSCHaa1nl3JcDCClqK1fJpHQuO66K3M/CDcdC9XQp+DKyxlAUp+9Be/j6f6x9O+/MSZNmoxQqPiB8gWfDHekAAUoQAEKUCBQAQYQO86aDyBjx45tWLFixe8B3BaLxdJ3bQFuruvuCuB5pdRJsVjstvyqI5HI8UqpW40xe8Xj8efbNpuZ+necMebSUCj0bDKZ3MRxHBkP0uB53h6lrMzOABJM5xpjcMkl5+Hjjz/yK3QG7ojQpmMLrrycAaR19v3Amk/9Y9l//wNx4IGHFnxc3JECFKAABShAgeoLMIDY9UHNBxA5Pdd1lyilfrmhaXhLZcg+AQFwitb65jYB5Gey/ohSase20/FGo9FtjDFvKKXOicVik7PlRo4cuVlDQ8NcY8zv4/H4r4o9rmQyZYotw/3bF3jkkUdw332yPmV6YcKGUUcWTFWuAGLWLkNy1pcrtk+Zcj222EKGMHGjAAUoQAEKUKBeBMLhUF3cQ9eqZ13gRaPRS2UweCqV2reUcR4bwndddwgAmQv1Yq21jDHJba7rypS6EwEMbzu43XXdkwHcCGB7rbW8dpVf7g0ArVrrbxTb8QwgxYp1vP+CBQswbtzpuR3CjT+E6ta3oAbKFUBSi9+At+jf/jGMGDECV155VUHHw50oQAEKUIACFKgdAQYQu76oiwASiUROBbCbUmo/Y8x0pZRMj7uinVM3WuvxxZK4riuD11/QWh/WJkg8BGAXrbUMLl9ni0QiZyilrmrv6YjrujOMMV48Ht+62GPhK1jFim14/0mTzsfChQv8nZzNd0do460KaqBcAST5/mMwK9MTtR1wwMH+/7hRgAIUoAAFKFBfAnwFy66/6iKAuK6bni6o800CSNGjeSORiAwkP7ahoWHLGTNmyJS88tqXTPkrM1/9UWstAWidLRqN7mWMeRrAeVprWUHd3zJPVGYbY+6Kx+Mndn7I6+7BAFKs2Ib3f+ih+/D00+mlY1SfkQgP3b+gBsoRQIzXiqQ/zCh9OZ955vkYMWJUQcfDnShAAQpQgAIUqB0BBhC7vqiLANLc3LxnMpksaGxEIpF4rliSpqamoY7jyHiOuFLqYmOMuEw0xjQ2NDRsO2PGjI9c15VXsS5QSrmxWGxOJmxIANnZGHOZMebFUCi0mTHmXAByV/kNrbWsV1LUxgBSFFenO8+Y8Q5uumlKer9QD4Qjxxe03kY5Aoj3xXykPviLfyg9e/bE1Vf/Go7jdHoO3IECFKAABShAgdoSYACx64+6CCCFnGJTU9PAcDjcq731Ogos/zXHcWRBQZkVC8aYaY7jnBmLxWKZsCHjQS6QhxzZKXZHjBjRo1u3bvL3Mrp5KIDl8iqX4zgTW1pa3imk3bb7MICUotZxmVWrVuGMM06R/vR3Co/6PlT3jTttpO1g8Y4KhBuPgerWr9P6ZIfUJ6/C+1TW0wTGjNkGJ59c9BwFBbXDnShAAQpQgAIUKK8AA4idb10EENd1U8aYI+Lx+MMdna7rujL241da62F2JNUtzQASvP+ll07EggXz/YpDg78Np5/baSMSWJL6j4C3puN9ne4IuycU9ERFKknOewJmRXo9S5l6V6bg5UYBClCAAhSgQP0JMIDY9Vm9BBB5aV4W93ukvdOVBQEdx/mDPInQWvewI6luaQaQ4P3vvPOP+Pe/X/QrdgZsi9BmuxTUSPLDf8J8Hu9wX9U3gvCQ7xRUl+zUKqufJ7/w9z/55NMxZkzRcxQU3BZ3pAAFKEABClCgfAIMIHa2NRtA8qbALeYM39Ba71BMgVrblwEk+B559tl/4oEH7vErVr2GIjz8oIIaManVSM55EGj9fP39G/oiPPJwqFBhedevS56oZLYrrpiCfv0Ke3WroIPlThSgAAUoQAEKVEyAAcSOupYDyBBjzD4Avq6U+hmA94wxn7R3ukqpFIDZnuddlUgkZtmRVLc0A0jw/rHYTNxwgwzvkUEgG6EhclzBjZjW5f7YDbNsZq6M6jcaoYE7QDX0Kbgeb+VCpN5PP8Dr1as3Jk++oeBXtwpuhDtSgAIUoAAFKFARAQYQO+aaDSD5p+W67hzHcX7W0tKSnk/1K7wxgATfuUuXLsG55365PEzY/QlUqFvBDZnUWiT1rbn9iy0vBb2l7yG1cJpfR2NjBOPHn1Nw+9yRAhSgAAUoQIHaEmAAseuPugggdqdYX6UZQILvLxlQPm7cL7BmTXpAeXjE4VA9BxXcUBABJLXo3/AWv+G3ufPOu+LYY08ouH3uSAEKUIACFKBAbQkwgNj1R90EkMbGxqZwOPxdz/O2UEo1dHDaJa2EbkcYbGkGkGA9s7VdfvmFmD9/nv/H0JB94fRtLLihIAJIcv6TMMvTbwcedND3sN9+3y24fe5IAQpQgAIUoEBtCTCA2PVHXQSQSCRymFLqbvnyWsYRb+CUS1oJ3Y4w2NIMIMF6Zmv7/e9/g7feet3/ozNoZ4Q22a7ghgIJIHMegFmdHsJ0wgk/xQ477Fhw+9yRAhSgAAUoQIHaEmAAseuPugggruvOADDMGHNVKBR6NZlMru7otEtZCd2OMNjSDCDBemZre/DBe/DMM/9MB5CNt0Jo890LbiiIANIqM2Cl0pftGWeci1GjmgpunztSgAIUoAAFKFBbAgwgdv1RLwFE7twu0Vpfbne6tV+aAaQ8ffTMM0/hwQfv9StXvbdEeNgBBTdkG0CMl0Qydkuuvcsvvxb9+3e+GnvBB8gdKUABClCAAhSoqAADiB13vQSQDwGcq7X+k93p1n5pBpDy9NEbb7yGP/zhpnTl3TdBw6ijCm7IOoCsWYrkbHmDEAiFQrjhht/DcZyC2+eOFKAABShAAQrUlgADiF1/1EsAuRHAZlrrwu8a7VyqVpoBpDz0c+fOweTJk9KVh7qjwT2x4IZsA4j3xTykPnjcb2+TTTbFpEmTC26bO1KAAhSgAAUoUHsCDCB2fVIXAWTEiBE9Ghoa7nQcZ7kx5nee580BkJ5Ttc2WSCTaWbbaDqmSpRlAyqO9bNkynHPO6bnKw9GToJyOJlNb9xisA8jSmUgtfNavtKnJxbhxZ5fnJFkrBShAAQpQgAIVEWAAsWOuiwDiuu6nMnYYQL9OTldmwZKZsup2YwApT9d5nofTTvspUqmU30B41Pehuhc2DsM2gKQ+eQXep6/47crsVzILFjcKUIACFKAABepXgAHEru/qJYA8Z4zxCjnVeDy+VyH71eo+DCDl65kLLjgTixdLlgVCww6E03tYQY3ZBpDkwmdhls7029pnn/1xyCFHFNQud6IABShAAQpQoDYFGEDs+qUuAojdKdZXaQaQ8vXXlClXIR6PpQPIFnvB6T+6oMasA8gHj8N8kV4E8aijfog99ti7oHa5EwUoQAEKUIACtSnAAGLXLwwgdn6Bl2YACZw0V+Gf/nQr/vOfl/w/O5vugNDAbxTUmG0AaZ11N7B2qd/Wz39+GrbeetuC2uVOFKAABShAAQrUpgADiF2/1E0AGTFiRP+GhoZxSqn/BdAIoBeA5QBaADzsed5vEolEuwPT7YgqW5oBpHzejz/+CP7+9/RsVKpfFOHB3yqoMZsAYoxBMvYHwCT9ts477xIMGTK0oHa5EwUoQAEKUIACtSnAAGLXL3URQKLR6GBjzHQAWwKQRQnfB7AqE0JGAJDpjN5KJpN7zp49e5kdSXVLM4CUz/+ll17AXXfdng4gPbdAeMShBTVmFUCSK5GM35Fr57rrbkaPHj0Kapc7UYACFKAABShQmwIMIHb9UhcBxHVdWUb6B/IGS58+fe597bXXWrOnnZmi9zil1PUAfqO1PsOOpLqlGUDK5691C66/PrMGR7gXGiI/LqgxmwDirVyI1PuP+O307t0HkyffUFCb3IkCFKAABShAgdoVYACx65t6CSAygvdOrfW5HZ1uJBKZopQ6SGstr2fV7cYAUr6uW7LkM5x33pf5tNC1QKwCyNIWpBY+45/UyJGNmDDhvPKdIGumAAUoQAEKUKAiAgwgdsz1EkDWKKVOjMVid3V0uq7r/gjALVrrun6/hQHE7oLeUGlZC+T003+B1ta1/m7hkUdC9di00wZtAkhq0cvwFr/ut/GNb+yM4447qdP2uAMFKEABClCAArUtwABi1z/1EkAWGWNujMfjl24ggMjy0uO11gPtSKpbmgGkvP6XXTYRH344328kNGQfOH2bOm3QJoAk5/8DZvlsv40DDzwU++9/YKftcQcKUIACFKAABWpbgAHErn/qJYA8BGBnz/O+nUgk3mt7ys3NzVt7nvekUuqlWCx2uB1JdUszgJTX/7bbfofXXvuv34iz6dcRGvj1Thu0CSCts+4B1i7x2zjppJOx3XZjO22PO1CAAhSgAAUoUNsCDCB2/VMXAWT06NFbpVKpfwOQ16vk/1uMMSuVUjIV79cA7AhghTFm53g8nl5yuk43BpDydtwTT/wFf/3ro34jqk8jwkP37bTBUgOI8VLpKXjh+W1MnHgZNt98i07b4w4UoAAFKEABCtS2AAOIXf/URQCRU4xEIv+jlLoawF7y5XXeaacA/MMYc2a9hw85JwYQuwu6s9JvvvkabrnlpvRu3fqjoVEmV9vwVnIAWf0pknPu9ysPh8OYMuW3CIVCnTXHn1OAAhSgAAUoUOMCDCB2HVQ3ASR7mttss02vVatWRRzH6WWMWbFy5Uo9f/58WRPkK7ExgJS3Gz/5ZBEuvFCGC6W3QmbCKjWAeHkzYA0fviXOPvvC8p4ca6cABShAAQpQoCICDCB2zHUVQMaMGdMbwNoZM2akpzHypzYduVkoFFqVSCQ+t6OojdIMIOXtB5kJa8KEX2LVqnRmDW15KJyNNvxaVKkBJPXRC/CWvOO3s8suu+OYY44r78mxdgpQgAIUoAAFKiLAAGLHXDcBJBqNXmCMOccY8814PP5m9rSj0eiJxpibjTGXxOPxy+w4ql+aAaT8fSCLEcqihLI5m+2C0IBtN9hoqQEkOfchmFUf+3UfffSx2H13eXuQGwUoQAEKUIAC9S7AAGLXg3URQCKRyPFKqduUUi8DOCYWi83JCyDbGGOuBbA3gOO11n+2I6luaQaQ8vs/+ugDeOqpv/sNqb5NCA/ZJ/AAYowMQL8VMDJECf7rV/IaFjcKUIACFKAABepfgAHErg/rIoC4rjtDZr7SWh/W0elGo9EHjTGjtdZj7EiqW5oBpPz+6wxED/dGQ0TWsOx4K+UJiLfqY6TmyuzRQENDA6677iaEQuHynxxboAAFKEABClCg7AIMIHbE9RJAVssyClrrOzs6Xdd1jwXwB66EbndBdIXSn3++DGeffXruVMNNx0I19Onw1EsJIKnFb8Jb9JJfZyQSxemnn9UVaHmOFKAABShAgS4hwABi1831EkA+VEpNjsViN2wggMjURqdrrTezI6luaT4BqYz/RRedg0WL0uMzQoO/DaefG2gASc57AmbFXL/O/fb7Lg466HuVOTG2QgEKUIACFKBA2QUYQOyI6yWA3A7gOwAO0Fq/1faUo9HofsaYqQCe0FrLk5C63RhAKtN1U6fegenTn/cbU/1GIzy44wHixT4BMcZDUt8OeGv8+k89dTyam+v6zcDKdApboQAFKEABCtSJAAOIXUfVRQCJRqODjTGvApCnG3EAc4wxa5VS/QHIV9eDAHycSqV2nDVr1jw7kuqWZgCpjP8rr7yM22+/Jd1YQx+EG38Ipdr/OBQbQPLHf8jCg9de+xt069a9MifGVihAAQpQgAIUKLsAA4gdcV0EEDlF13U3BSArucm7LNmFGwyAhcaYv4TD4UkzZ85caMdR/dIMIJXpg/XGgTQeA9WtX7uNFxtAUp++Cu+T//p1/T97ZwIeVXW+8ffcmckOJAQCRPZk7gQRVNxQUcGtLsVq1brjglJbrdq6VVu1St2wWrV/rHXf91KrVhQXEFxQxAVFMnfCvgQSCEv2ZOae/3PuJCEJCSS5k9y5yXuex8eQOd855/t9N8m8c875Pr8/D7///Q1d4xRnIQESIAESIAES6BICFCD2MLtGgDR2c8yYMRk1NTXJaWlpxYsXL661hyC+rClAui4ed911G9ati26YaQOOgKfvmJgIkPCq/0BWRrWwuvuh7oCwkQAJkAAJkAAJdB8CFCD2YulKAWLP5fi2pgDpuvg0qQeSOhTeoS0LhfbsgMhINcLGUwDU5hzrf3RdNDkTCZAACZAACXQdAQoQe6wpQOzxi7k1BUjMkbY6oGEE8eCD90ZfFx549UsgNN8u/dsjQMwdIUTWf2CN0bt3b9x11wPQNK3rnOJMJEACJEACJEACnU6AAsQeYgoQe/xibk0BEnOkrQ4YiYRxww3XoLKywurjGXwitF4jbAmQ8PoPIHeoPAnAoYdOwAUXXNJ1DnEmEiABEiABEiCBLiFAAWIPMwWIPX4xt6YAiTnS3Q6oMmGpjFiqiT558GYf3WEBImUEYeOZhvS706Zdif32G9e1DnE2EiABEiABEiCBTidAAWIPMQWIPX4xt6YAiTnS3Q749ddf4amnHo328STD678QQjQ9MtXWI1hm+TpE1rxlDeXzJeC++x5i+t2uDSdnIwESIAESIIEuIUABYg+zGwSIx+/3H56QkGAsXbp0oz1349+aAqRrY1RZWYkbb7wa4XA4qkGGnQotJbvJItoqQCIb58Pc+qNlO3bs/rj88t91rTOcjQRIgARIgARIoEsIUIDYw+wGASJ0Xa8EcKFhGK/aczf+rSlAuj5GM2c+iKVLl1gTaxlj4Bl4RLsFiJQS4YLngHC5ZTtlylSMH3941zvDGUmABEiABEiABDqdAAWIPcRuECCqCOF8KeWPoVDot/bcjX9rCpCuj9Fnn83Hiy8+E53Ymwpv7pQmVdGlGUY4+Hhdal0Bb+AyCM3bZKFmxUZEVs+KihjNg3vv/TtSU9O63hnOSAIkQAIkQAIk0OkEKEDsIXaFAMnLy9MjkcidmqYJKeUbmqatkVKWteR6MBiMfpTt0kYB0vWBKysrxR//+HuYpmlN7hl+OrTkAU0WEtn0GcySH6D1HQPPgF13NqKvf2/Z5OWNxlVXXdv1jnBGEiABEiABEiCBLiFAAWIPsysEiK7r6p2hquym1hut8NZKMwzDYw+Js9YUIM7wf+ih+xAMLrMm1/ruB8+Aw9q8EOv41fIXgNpSy+bcc6dgwoSJbbZnRxIgARIgARIgAXcRoACxFy+3CBB1Pma3wqMeg2EYF9tD4qw1BYgz/OfPn4tXXnk+OrmvF7w55zc5hrW7VZmVmxBZ9W+rixAC99zzd/Tq1dsZRzgrCZAACZAACZBApxOgALGH2BUCxJ6L7rKmAHEmXjt2bMdNN/0BajdDNe/wMyGS+7dpMZGiL2Bu+dbqq+t5uOaaG9pkx04kQAIkQAIkQALuJEABYi9urhQgI0eO7OPz+VIBlAaDwei5l27SKECcC+Tf/34vQqGgtQAtc394sg7d42Kix69eBGp3WH3POut8HHXUrsUM9zgQO5AACZAACZAACbiGAAWIvVC5RoDouj4SwF8AnAigbyO3VW2QWaZp3lFQUFBsD4fz1hQgzsVg3ryP8NprL0YXkNAH3pHn7vEYlqzajPDK1ywTdfzqrrvuR58+6c45wZlJgARIgARIgAQ6nQAFiD3ErhAgKguWaZpfAMgAsBKAAaBSCJEqpRwFYDCAdUKI8cFgcIM9JM5aU4A4x3/btq24+ead2au8I86CSMrc7YIixV/B3Py11Scnx49rr73JOQc4MwmQAAmQAAmQQJcQoACxh9kVAkTX9ZcBHAvgl4ZhLGjuciAQOEFK+QqAVw3D+LU9JM5aU4A4y/++++7EypXLrUVo/Q6Gp/+Bu11Q7YpXgOoSq8/pp5+NY4453lkHODsJkAAJkAAJkECnE6AAsYfYLQJkoxBiZjAYnN6au7qu31lXLV3thri2UYA4G7o5c2bjzTdfjy4iqT98I85sdUGyZnv0/kddmz59BjIz+znrAGcnARIgARIgARLodAIUIPYQu0WAVAshpgaDwRd2I0AuAPCEYRiJ9pA4a00B4iz/TZs24vbbb25YhFUV3ddyRfPIlu9hFn1m9R08eAhuvvl2ZxfP2UmABEiABEiABLqEAAWIPcxuESDrhRBPB4PBP7fmrt/vv0MIcalhGNn2kDhrTQHiLH81uxIgSoiopg08Ep6MfVpcVHj1fyEr1luvnXjiZEyefJrzi+cKSIAESIAESIAEOp0ABYg9xG4RIM8C+IWmaWfl5+e/39xlv99/shBC7Y68yUKE9h4IWgP//ver+Oij6GMm0obBO+TkXbDISA3CxlMATOu1G274M4YPV4na2EiABEiABEiABLo7AQoQexF2hQAZNWrUsEgk8hUAdcBefeScD6ACgKoForJgDQJQCOAQwzCiH0k+YbM7AAAgAElEQVS7tHEHxPnABYPL8NBD90UXIrzw6lMhNE+ThZk7liOyPipS0tJ6WdXPNU1zfvFcAQmQAAmQAAmQQKcToACxh9gVAkS5GAgEsqWU6pD9KQAal6hWwmNWJBKZvnz58iJ7OJy3pgBxPgbhcBjXX/87VFdXW4vxDD0FWmrT3AaRwnkwt/1kvX7wwYfioosuc37hXAEJkAAJkAAJkECXEKAAsYfZNQKksZvDhw9PT0hISA2Hw2UrVqzYbg9BfFlTgMRHPP75z4fxww/fWYtpqSp6bcELDdXPL7zwMhxyyJ6rpseHZ1wFCZAACZAACZCAXQIUIPYIxqUA0XV9u5Ty8lAopOp/QNf1iJTyzFAoNMueu/FvTQESHzGaO/cDvP669fhBJGXBO+KMhoXJ2lKEC55v+Pfddz/A6ufxETauggRIgARIgAS6hAAFiD3M8SpAqoQQz1RXV1+zatWqKl3X1U3f0w3D+I89d+PfmgIkPmK0YcM6/PWvt9YtRkTvgXgSrH+b2/IRKfzY+nrAgEG47TZVgoaNBEiABEiABEigpxCgALEX6XgVIO8COAGAbKd70jAMbztt4qo7BUh8hMM0Tdx449UoLy+3FuQZ8nNoaUOtr8Mb5kJuX2Z9PWHCRJx77pT4WDRXQQIkQAIkQAIk0CUEKEDsYY5LAZKXl5cppbxRSjlGSpkkhDgSwDIpZfGe3A2FQpP21CeeX6cAiZ/oNLkH0u8gePofZC2udvnLQM1W62t1+VxdQmcjARIgARIgARLoOQQoQOzFOi4FSHOX1BEsKeUZvANiL9i0bh+B9977H95669+WkUgdAu/QyZCRaoSNJxsGuuOOe9CvX1b7BmZvEiABEiABEiABVxOgALEXPlcIEFUHpLS0tGjdunWV9tyNf2vugMRPjJrUA/Ekweu/2Kp8HlnzlrXItLQ03HvvQxDCFT9G8QOWKyEBEiABEiABlxOgALEXQL5zsscv5tYUIDFH2uEBKyoqcN11VzbYe3MvgLmjAGbRF9b39t57H1x55R86PD4NSYAESIAESIAE3EmAAsRe3ChA7PGLuTUFSMyR2hrw1ltvxObN0atHnsEnwdwRgtwRsv79s5+djF/84nRb49OYBEiABEiABEjAfQQoQOzFjALEHr+YW1OAxByprQH/9a//w/fff2ONofU/GOaO5UD1Fuvfl1zyaxx44CG2xqcxCZAACZAACZCA+whQgNiLGQWIPX4xt6YAiTlSWwO+/fZ/MHv229YYoncuZOlKQEasf//pT3dgr70G2xqfxiRAAiRAAiRAAu4jQAFiL2YUIPb4xdyaAiTmSG0NuGjRQjz99GPRMbREwKyOihEh8OCDj8Ln89kan8YkQAIkQAIkQALuI0ABYi9mrhMgo0aN2sc0zRzTNFOllKU+ny9/2bJl0UP53aBRgMRXEFevXol7752+y6L69euPO+64N74Wy9WQAAmQAAmQAAl0CQEKEHuYXSNA/H7/6UKI+wEMae6ylPInKeWVBQUFn9jD4bw1BYjzMWi8goqKclx33e92WVRe3mhcddW18bVYroYESIAESIAESKBLCFCA2MPsCgGSl5f3M9M03wVQIqV8S9M0wzTNSiGE2gUZLYT4OYAkAEcYhrHIHhJnrSlAnOXf0uzXXnsFKiublqCZMOEonHvuhfG3WK6IBEiABEiABEig0wlQgNhD7AoBouv6RwAya2pqJq5atWpbc5dHjBgxwOfzzRdCBIPB4Cn2kDhrTQHiLP+WZr/zzluxfv26Ji9NnnwaTjxxcvwtlisiARIgARIgARLodAIUIPYQu0WAbBNC3BYMBh9qzV2/33+9EOKPhmFk2kPirDUFiLP8W5p95swHsXTpkiYvTZkyFePHHx5/i+WKSIAESIAESIAEOp0ABYg9xG4RIFVSystDodAzrbmr67o6D/MvwzDUUax2t0AgcKCU8m4AqrCDBmChEjTBYPDr3Q0WCARGSCn/BuDoun5fmKZ5fUFBwdJ2LwIABUhHqHWuzYsvPoPPPpvfZJLf/e5ajBo1unMn5ugkQAIkQAIkQAJxSYACxF5Y3CJAggDmG4Zx2W4EyGNSyomhUEhvL5KcnJxcj8ejqs19rUSIEMIE8EclRkzT3L+goGB5S2OOGjVqUCQSWQxguWma0z0eT7KUUqVGyjBNc5+CgoJoCe12NAqQdsDqoq5vvz0Ls2e/02Q21gDpIvichgRIgARIgATikAAFiL2guEWA3AngRgD3AXjcMIwV9W6PGjXKb5rmNCnl74UQdweDwVvai0TXdbWzcqoQYkgwGCxV9qNHj06rra1dA+BtwzBavG2s6/pjQoiflZeX561bt866pZybmztO07SXAPzBMAx1cb5djQKkXbi6pPPcuR/g9ddfbjLXPff8Hb179+mS+TkJCZAACZAACZBAfBGgALEXD1cIkOzs7JS0tLTZKssVAAkgDEC94U8G4FV14QB8aJrm5IKCgmiluHY0XddLAMwxDOPsxmaBQOBFKeXJhmGkNx/ugAMO8JWWlqodjgcMw7ijHdPttisFSKxIxm6cJsUI64b9xz8eh8fjid0kHIkESIAESIAESMA1BChA7IXKFQKkzkUtEAicI6VUWa4CAFIBlAkhfjJNc1YoFPp3R1Dk5OQM8Xg8q+suuTepOOf3+/8khLhD07Sc/Pz8VY3H13V9XwDfSil/FgqFPujI3C3ZUIDEimTsxjGMfDz44IyGAdPS0jBjxsOxm4AjkQAJkAAJkAAJuIoABYi9cLlJgNjztBXrvLy8A0zTXCSEuCIYDP6zmciYBkB9b3zz+iKBQOAXUspZUspJQoiLAaicrCkAFmma9of8/Hx1N6TdjQKk3cg63cA0Tcyc+XcsW7YUPp8Pv/jFGTj66OM6fV5OQAIkQAIkQAIkEJ8EKEDsxaXHCxBd1yeoC+5CiMuCweCTjXH6/f6LhRBPKJERCoWapEEKBALnSSmfl1IWAHjF4/G8J6XcS0qpjmMNF0Lsp4qStDc8FCDtJdZ1/SsqKuD1epCQkNh1k3ImEiABEiABEiCBuCNAAWIvJK4QILqub627+7EnbyMANgNY4PF47lu2bFloTwb1OyAArjQM45FmAuRyIcRMIcQhzdPx6rp+FgB1M/nvhmFcW2+Xl5c33DRNJTxmGYZxzp7mb/56OBxRd1zYSIAESIAESIAESIAE4pSA1+txxXvoOMVnXd6O+xYIBBZLKVV9j1F1i1WZqrYD6F33n/r26rrL6H0BpAEo1TRtQn5+/g+7c1DX9b0ArAVwu2EYtzfuq+v6bQBuBTDUMIz1jV/Ly8ubaJrmxwBONwzjP82Eyw9CCI9hGHu3Fy4FSHuJsT8JkAAJkAAJkAAJdC0BChB7vF0hQMaMGZNRXV2tsmAtk1LOCIVCy+rdrqvhoVL0Dvf5fKctXbq0rO5+xrNCiA+DweAZe0Kk63qR2jUxDOP0ZgJEXWw/3DCMgc3HyMvLyzRNcxOA3xqG8VgzO7W+asMw9tvT3M1f5xGs9hJjfxIgARIgARIgARLoWgI8gmWPtysEiK7rzwLwGYZxbmvu6rquam+UGIZxpeqj6/pf6sRB1p4Q+f3+R4QQF/h8vmFLly5VKXmVfT8AKvPVU4ZhXNXSGLquf6hSARuGcXj966ouSSQS+UlK+XgoFPrtnuamAGkvIfYnARIgARIgARIgAWcJUIDY4+8WAbJFSnllKBRqWg2uke9+v/8iIcSdhmGoI1WouyT+hGEYqlbIbltubu5gTdO+FUKEhBC3SykVl1ullDk+n2/fpUuXbtR1XR3FukUIoQeDwZVqwLr7IwuEEO9GIpF/aJqmdkrUMa5BpmmOa62C+u4Wwx2QPUWLr5MACZAACZAACZCAswQoQOzxd4sA2SGEeGh3Vc51Xb9dCHFdMBhU9UHUDsZdAM42DGNkWxDl5uburWmaqrSusmJBSjlP07Qb6jNZ1d0HUVXW9caV2HNzc8drmqbmOgiAugQ/zzTNPxUUFCxty7zN+1CAdIQabUiABEiABEiABEig6whQgNhj7RYB8i6ASVLKW6SUrxQUFKyrdzsnJyfL4/GcCuBvQogfg8HgYbquXwrgYSHEc8Fg8HJ7iLrWmgKka3lzNhIgARIgARIgARJoLwEKkPYSa9rfFQIkEAgEpJSfAOhft/xaAJUAVGashLrsV+Wapv0sPz//c7/f/18hxD5CiCOCweAGe4i61poCpGt5czYSIAESIAESIAESaC8BCpD2EnOhAFFLVpmwqqqqLhVCHAlgWF3V8WoA66WUCyORyBMrVqxYo/r6/f79kpOTQ0uWLCm3h6frrSlAup45ZyQBEiABEiABEiCB9hCgAGkPrV37umIHxJ6L7rKmAHFXvLhaEiCB1glUVVXi888XoLi4GP3798dhhx2JpCS1cc1GAiRAAu4mQAFiL36uFCCjR49OqK2tPTsSiby3fPlyVcOj2zQKkG4TSjpCAj2ewJtvvoE5c9QVvmg7/viTcOqpeyzN1OO5EQAJkED8E6AAsRcjVwqQuiKARVLKSaFQaL49BPFlTQESX/HgakiABDpO4L777sTKlcsbBhg5MhfXXXdzxwekJQmQAAnECQEKEHuBcLMAKZZSTqQAsfcA0JoESIAEOovAzTdfi23btjYMn56egbvuur+zpuO4JEACJNBlBChA7KGmALHHL+bW3AGJOVIOSAIk4ACBmpoaXHNN0yzoQgg8+OCj8Pl8DqyIU5IACZBA7AhQgNhjSQFij1/MrSlAYo6UA5IACThAYP36dbjzzlt3mfnPf74D2dmDHVgRpyQBEiCB2BGgALHH0pUCpO4S+jmRSGQ2L6HbewBoTQIkQAKdQeDrr7/CU089usvQU6dejgMOOLgzpuSYJEACJNBlBChA7KF2pQCx53J8W3MHJL7jw9WRAAm0jcBbb83Ce++9s0vnE074OU455ZdtG4S9SIAESCBOCVCA2AuMawTIxIkTvYWFhVMAnCSlzJFSpmqaVgog3zTNWaFQ6N/2UMSHNQVIfMSBqyABErBHYObMB7F06RJrEC1Rg1ltWl+PHj0WV1xxjb3BaU0CJEACDhOgALEXAFcIkJEjR/bxer0fAhgHQK1ZVUCvBJAMIBGABDDH5/P9YunSpTX2kDhrTQHiLH/OTgIkYJ+AlBI33ngNysrUZ0RAn/16Yft30a979eqNe+75O9SFdDYSIAEScCsBChB7kXPFXwBd11XexquEEHeEw+Fnli9fvrbe7dzc3BxN0y4DcL0Q4i/BYHC6PSTOWlOAOMufs5MACdgnsHlzMW699caGgYZckI21z29o+Pf06TOQmdnP/kQcgQRIgAQcIkABYg+8WwTIciHEO8Fg8OrW3NV1/XEAEwzDGGUPibPWFCDO8ufsJEAC9gksWrQQTz/9mDWQL8OLIedmY+1LG1C7NWx97+KLp+Ggg8bbn4gjkAAJkIBDBChA7IF3iwCpAjDNMIznWnPX7/dfJIT4p2EY6liWaxsFiGtDx4WTAAnUEXj55eexYMFc61+9RqWi/9GZKP54C0qXlVvfO/LISTj77AvIiwRIgARcS4ACxF7o3CJASqSUd4VCob+15q6u678HcIthGH3tIXHWmgLEWf6cnQRIwD6B6dNvQWHhemug/kf3Ra9RaShdVobij0us72Vn74U//9nVp2XtQ+IIJEACriZAAWIvfK4QIH6//z0AI6WUhxcUFBQ3d3nEiBEDfD7ffAArDMM40R4SZ60pQJzlz9lJgATsEVAXz2+4Yedp2SHnZ8PXx4va7bVY+0Jhw+AzZjyMtLQ0e5PRmgRIgAQcIkABYg+8KwSIrutHAPgIQAWA/wIICiEqTNNUqXj3llL+XGXDMk1zUkFBwRf2kDhrTQHiLH/OTgIkYI/Ad98txmOPzbQG8aR6MPTCbCvjlcqMtebZDYiUR6zXpk27EvvtpxIbspEACZCA+whQgNiLmSsEiHIxEAicYJrmw0KI3BZc/lEIcXUwGIweOnZxowBxcfC4dBIgAbzxxsv4+OMPLBKp/hQMOH5ntqtNczajPKQ+RwKOPvp4nHHG2SRGAiRAAq4kQAFiL2yuESD1bvr9/lFCiIAQIhVAmaZpPy1btixkD0P8WFOAxE8suBISIIH2E7jnntuxZs1qy7DfURnovU+vhkF2/FiKzZ9stf49dOhw/PGPt7Z/AlqQAAmQQBwQoACxFwRXCBBd16dEIpG5jet/NHfb7/cfJ4TYxzCMv9tD4qw1BYiz/Dk7CZBAxwlUVVXhuuuuhGlGq54PPnsgEjITGgas2VKDda9stP6taRruv38mEhNVLVk2EiABEnAXAQoQe/FyiwCJSCnPDIVCs1pzty4L1m2GYaTbQ+KsNQWIs/w5OwmQQMcJGEY+HnxwRlRgJAoMmzq4ScVzdQ9k9ZPrYFZLq88119wIXQ90fEJakgAJkIBDBChA7IGPWwESCATGSin3q3PvGQD/B+DrltyVUiYLIa5SH7gZhtHHHhJnrSlAnOXP2UmABDpOYM6c2XjzzdetAZKHJmHQ5KxdBit8qwiVa1VpJ+C0087Ecce5OnFhx2HRkgRIwNUEKEDshS9uBYiu61cAeEAV0gUQ/bis9Wb5IYR4LBgMXm4PibPWFCDO8ufsJEACHSfw5JOPYvHir6wB0g/ojb7jd92QLlm4DdsW77D6HHjgwbjkElf/yu44LFqSAAm4mgAFiL3wxa0AUW6NHj06oba2Vu2CLASg8jq2uAMihIgIIVbk5+d/bg+H89YUIM7HgCsgARLoGIHbb/8TNm2K1vrI+lk/pOWm7DJQWUEFit7fbH1/4MBBuPXWOzs2Ga1IgARIwEECFCD24Me1AKl3Tdf12wC8aqgDxt28UYB08wDTPRLopgTC4TCuuebynRfQzx2EhAy1gd201WytxbqXoiJF0zx46KF/wuPxdlMqdIsESKC7EqAAsRdZVwiQ5i7W7YycHYlE3lu+fHmRPQTxZU0BEl/x4GpIgATaRkDtfKgdkKiyAEb8egiEtuufGBmRWPnYWiCaKAu33XYXBgwY2LZJ2IsESIAE4oQABYi9QLhSgOTl5WWaplkkpZwUCoXm20MQX9YUIPEVD66GBEigbQSWLv0BM2dGs6B7+3gx9Pxs6+stn27F9h9K0WdML2ROyLC+t+b5DQjvCFtfX3HF7zF69Ji2TcJeJEACJBAnBChA7AXCzQKkWEo5kQLE3gNAaxIgARKIBYFPP52Hl156zhoqeXAiBv1iAMywiVWPrYumERHA8GmDoXk1bHhzE6rWV1t9zz13CiZMmBiLJXAMEiABEugyAhQg9lBTgNjjF3Nr7oDEHCkHJAES6AIC77zzJt599y1rprRAKrKOzYRZY2LV4+saZh9+2WBoCRqKPtyMsmCF9f2TT/6F9R8bCZAACbiJAAWIvWhRgNjjF3NrCpCYI+WAJEACXUDg5Zefw4IF86yZ+uzfC5mHZbQqQLZ8vhXbvy21+h5xxCScc84FXbBCTkECJEACsSNAAWKPpSsFSN0l9HMikchsXkK39wDQmgRIgARiQeDxxx/Bt99GM6X3PTQd6eN6typAtn2zAyVfbLP6jht3IC699LexWALHIAESIIEuI0ABYg+1KwSIrutTIpHI3OXLl69tzV2/33+cEGIfwzCityBd2rgD4tLAcdkk0MMJPPTQfQgGl1kU+k3qi957p7UqQHb8VIbNc0usvoHAKFx99fU9nB7dJwEScBsBChB7EXOLAIlIKc8MhUKzWnNX1/Xfq4yOhmHsWnrXHqMutaYA6VLcnIwESCBGBO6++y9Yu3aNNdqAE/shdWRKqwKkfHkFNr0XLUY4ZMgw3HSTKvXERgIkQALuIUABYi9WcStAAoHAWCmlqoKu2jMA/q+1SuhSymQhxFUABhuG0cceEmetKUCc5c/ZSYAEOkbglltuwJYtUVEx6NQsJO+V1KoAqVxXhcL/Rks4ZWb2w/TpMzo2Ka1IgARIwCECFCD2wMetANF1/QoADwBQpXRVEsfdNcsPIcRjwWDwcntInLWmAHGWP2cnARLoGIE//OG3qKqqsowHnz0QCZkJrQqQ6s01WP/qRqtvUlISHnjgkY5NSisSIAEScIgABYg98HErQJRbdZfN1S7IQgAzW9sBEUJEhBAr8vPzP7eHw3lrChDnY8AVkAAJtI9ATU0Nrrlm52c/Qy/aC95UT6sCJFwewZpn1jdM8tBD/4LPpz5rYiMBEiABdxCgALEXp7gWIPWu6bp+m5TytVAoFL3h2I0bBUg3Di5dI4FuSqC4uAi33fbHqHcCGHH5EAhNtCpApCmx8tG1DXvbd9xxD/r1y+qmdOgWCZBAdyRAAWIvqq4QIHUuiry8vGH5+fmr6l0eNWqUPxwOnwigWgjxb8MwogeQXdwoQFwcPC6dBHoogfz8n/Dww3+zvPf28mDolL2sr1srRKheW/PseoTLIlY/lQVLZcNiIwESIAG3EKAAsRcpVwiQnJycLE3TPhJCrDIMY7JyWdf1YwG8AyChDsGmcDh8yIoVK6JpWFzaKEBcGjgumwR6MIF58z7Ca6+9aBFI2isR2acO2KMA2fDmJlStr7b6nXXWeTjqqGN6MEG6TgIk4DYCFCD2IuYKAaLrurr/oUrlnmUYxuw6AfITgIEAztc0rcI0zecAzDEM41J7SJy1pgBxlj9nJwESaD+B559/Cl988all2HtsGvod0XePAmTz/BLs+KHM6nfYYUfg/PMvbv/EtCABEiABhwhQgNgD7xYBslII8UIwGLxFuZubm7u/pmmLAUw3DMNKIK/rujqA/FvDMIbaQ+KsNQWIs/w5OwmQQPsJ3H77zdi0KZrVKuu4TKTpqXsUIKXBchR/uMXqN2DAQNx2213tn5gWJEACJOAQAQoQe+DdIkAqAVxsGMYrjcTGnaZpHlhQUPBt3ffOBvCsYRiJ9pA4a00B4ix/zk4CJNA+Aps3F+PWW29sMBo6JRveXt49CpBwaRhrntvQYHfHHfeiX7/+7ZucvUmABEjAIQIUIPbAu0WAbJBS3h4Khf5VJzY+AeA3DCO73n2/3/9rIcSdhmH0s4fEWWsKEGf5c3YSIIH2EXj//f/hv//9t2WUkOnD4LMHNQywu0voqtPalwtRW1Jr9T/11DNw/PEntW9y9iYBEiABhwhQgNgD7woB4vf739M0rXdCQsLJ1dXVEwGov3b/ZxiGqn5uNV3X1d2QXoZhTLCHxFlrChBn+XN2EiCBthMwTRPq+JVKw6taxiF9kHFgnzYLkK1fb8fWL7db/fv3z7KOYWma1vYFsCcJkAAJOESAAsQeeFcIkEAgMElK+Z7K8FjnbnHd8at1deLjVQBn1B3TUpfRXdsoQFwbOi6cBHocgcWLv8KTTz4a9VsA1vGrtPpf07tPw6tMrGNYz29oqAdy6aW/wbhxB/U4jnSYBEjAfQQoQOzFzBUCRLkYCAQOlFKeDsBnmuY/CwoKlte7ruv620KIT4PB4L32cDhvTQHifAy4AhIggT0TCIfDmD79zw27H2n+FGQd3/QE7J6OYKlZiuZsRlmowpowK2sA/vzn6fB6d4qYPa+EPUiABEig6wlQgNhj7hoBYs9N91hTgLgnVlwpCfRkArNnv4233/5PFIEABp8zCAkZviZI2iJAarbWYt3LhQ27IJMnn4YTT7TKPbGRAAmQQNwSoACxFxpXCZDRo0en1dTUTNQ0LUdKmSqlLAWQn5CQ8MnSpUtr7KGID2sKkPiIA1dBAiTQOoE1a1bhb3+7C2oXRLXeY9LQ78ho7Y/GrS0CRPVvXBNE7X5cd92fMHToMIaABEiABOKWAAWIvdC4RoDouv4HAHcASI5+3tbQJIASIcQ1wWAwWorXxY0CxMXB49JJoAcQKCsrw7333oEtWzZb3nrTPNbuh5aw6+XxtgoQ1U/tgoTLItaYKh3vjTfegtTUtB5AlC6SAAm4kQAFiL2ouUKA+P3+c1UhQgBBIcRLUkpDCFFpmmaqpmmjpZTnARhimuZJBQUFc+whcdaaAsRZ/pydBEigdQK1tbV4+OG/YfnyULSTAAadmoXk7KQWjdoqQJRx5YYqFL5Z1HAUKzdXx+9+dy18vqbHuhgfEiABEogHAhQg9qLgCgGi6/oXQojqtLS04xYvXhxNGt+oDR48ODklJUXVBik1DOMYe0ictaYAcZY/ZycBEmiZgDpu9fjjj+CHH75r6ND3sHSk79+7VWTtESBqkG3f7kDJ59saxhs7dj9ceulveSmdDyUJkEDcEaAAsRcStwiQHQD+aBjGI6256/f7rxJC3GEYRro9JM5aU4A4y5+zkwAJ7EqgpqYGTz31KJYs2Sk+eu2dhn4TMyBE639G2itApJTYPK8EpT+VNxEhU6f+hjshfDBJgATiigAFiL1wuEWAqByNVxuG8fhuBMjFQohHDMNQd0Rc2yhAXBs6LpwEuiWBiooKPProwygoMBr8S81JtlLuCm33f0LaK0DUBNKUVmre8uWVDfOp41iXX34VUlJSuiVjOkUCJOA+AhQg9mLmFgGyREoZDIVCZ7bmrq7rr0kpR4VCoTH2kDhrTQHiLH/OTgIksJNAUdEmPPLIg1D/r28pI5MxQIkPz57/fHREgFgiJCKxac5mVKzYKUIGDBiI3/zmaqtWCBsJkAAJOE2AAsReBPb8F8Te+DGx9vv91wshVJHBV4UQahckv7q6uiIhIUGl4t0bwDQhxC8BXG8YxgMxmdShQShAHALPaUmABJoQ+OGH7/HMM4+jsjJaJFC1Xnunot9Rffe481Hfv6MCxBIhZt1xrGU7j2OlpKTioosuwz77jGW0SIAESMBRAhQg9vC7QoAA8Pj9/meFEOeqv0stuKz8eNIwjMvs4XDemgLE+RhwBSTQkwlEIhG8886beP/9/zXBkHFIH6Qf0Hu3dz6ac7MjQCwRIiW2Ld6BrV9ubzL0CSf8HCef/At4PJHqsGQAACAASURBVJ6eHCr6TgIk4CABChB78N0iQCwvA4HA4QB+IaXUAaQCKAPwk6Zps/Lz8xfbQxEf1hQg8REHroIEeiKBzZuL8fTTj2HlyuUN7guvQP9jM5GW0/77F3YFSP0iypZXoPjDLZDhnZ8/jRiRg0su+TUyM/v1xFDRZxIgAYcJUIDYC4CrBIg9V91hTQHijjhxlSTQnQionYaFCz/F66+/jKqqqgbXfBk+DDihHxL6dqwWR6wEiFpQTUktNr1XjNqt0errqiUlJeHMM8/F+PGHt2tnpjvFjr6QAAk4Q4ACxB531wiQESNGDPD5fFdFIpFHly9fvrbebV3XTxJCTJRSzjAMI1qa18WNAsTFwePSScCFBLZv346XX362SYpd5UavUanIPCIDmm/XCudtdTOWAkTNqcbb8ulWlDa6F6K+r+qFnHPOhejTp09bl8Z+JEACJGCLAAWILXyqjm38t1GjRg2LRCKfARhkmuaEgoKCL+pX7ff7LxJCPAWgEMDBhmGsj3+PWl8hBYibo8e1k4B7CKhdj6+++sLa9aio2HnRW0vU0G9iX6Tltv/IVXPvYy1A6scvK6iw6oWY1WbDlOqC+plnnoODDz6UuyHueQy5UhJwLQEKEHuhc4UACQQCL0opjxNCTAkGg3PUB2GN3VZ3Q6SUb0gpPwqFQufbQ+KsNQWIs/w5Own0BAIlJSV4+eXnsHTpkibuJg9NQv+j+8Kb6o0Jhs4SIGpx4fIwij8uQeWanUfG1PdVhqyzz56Cvn37xsQHDkICJEACLRGgALH3XLhCgOi6XiKlvDsUCt3XmruBQOAGKaWqlu7qvzoUIPYeaFqTAAm0TsA0TXz66Sd4883Xm9z1EAkCmYdnWMeudlfZvL1sO1OAqLWoXRx1HGvLZ1sha3ZeUFd3Q0499UxMmHAUNK3jR8ja6y/7kwAJ9BwCFCD2Yu0WAVImpZwWCoVeas1dXdcvEEI8GgwGVXYs1zYKENeGjgsngbgmoIoJvvjiMwiFgk3WmTwsCf0n9oU3LTa7Ho0H72wBUj9XuDSM4k9KULm66W6I3x/AeeddxOKFcf1kcnEk4E4CFCD24uYWAfKVECIUDAbP240AeVfdETEMY397SJy1pgBxlj9nJ4HuRkDtesyd+wHeemsWamtrG9xTdz3UJfM0PSWmux5OCBA1p9oNKTMqsGXB1iZ3Q3y+BJxyymmYNOk47oZ0t4eb/pCAgwQoQOzBd4sAmQLgGQBvAnhNSrlSSlnj8XjSpZSjhBDnSykPEUJMCwaDT9pD4qw1BYiz/Dk7CXQnAmrX49lnn2hS10P5l+pPQb8JGfCkdG4hv67aAWkcs0hFBJsXbEV5wc4K7up1VTfkwgsv5W5Id3rA6QsJOEiAAsQefFcIEOWi3+//sxDiVlUVvZnLygeVGP4uwzD+Yg+H89YUIM7HgCsgAbcTULsB8+d/jFmzXkdtbU2DO0pw9DsqA6kj7We4agsjJwRI/brKV1Rg8ycliFTszFmSkJCA0047E0ceeXSn7fq0hQv7kAAJuJ8ABYi9GLpGgCg3c3JysjRNO03TtL2llMlCiCIp5SoAs92efrc+jBQg9h5oWpNATydQWroDzz//FH78sWmGq7S8VOuiuSep6y5lOylA1HMQqTKtC+pl+TvTDKvvq0xZF1xwCXr16t3THxf6TwIk0EECFCAdBFdn5ioBYs9Vd1hTgLgjTlwlCcQjgYICA0888U/s2LF9565HsoZ+k/oidUTX7Ho05uK0AGnYDVlZgc1zSxCp3LkboooWTp36G+Tm6vEYSq6JBEggzglQgNgLEAWIPX4xt6YAiTlSDkgC3Z6AOnI1d+6HmDXrVahL5/UtZUQy+k/qC09y5971aA1wvAgQtb5IZQTFc0tQsbKyYbma5sHpp/8KEyceyyNZ3f6nhA6SQGwJUIDY40kBYo9fzK0pQGKOlAOSQLcmEIlE8NprL2LBgnkNfgoPkDkhA71Gpzn2xlqlxt26aLtVp6O+qTojGQf1gbdX7FP+tiXISqjt+LEMJapuSGSnxRFHTMKvfnUuPB5nhFpb1s4+JEAC8UWAAsRePChA7PGLuTUFSMyRckAS6LYEVFrdJ5/8J5Ys+a7BR28vDwac0B+JWQmO+R2pimD965sQ3qHygzRt3t5e7HXmwC69i9J8DdVF1dg0ezPCZTtVyNix+2Pq1Mvh8/kc48aJSYAE3EOAAsRerChA7PGLuTUFSMyRckAS6JYEwuEwHnvs/5pcNk8cmICBJ/V37MhVPeiiOZtRFmqaBrdxENL8Kcg6vp+jcVFHsja+W4zqjTuzhO2zz76YNu0KeL3O7NA4CoSTkwAJtIsABUi7cO3SmQLEHr+YW1OAxBwpBySBbkdAHSVS9T2++uqLBt9SRiYj67hMaN6uy3LVEli1ttVProNZLVvlriUKDJs62LHjYfULM8Mmij7YgooVO++FHHLIYZgyZarja+t2Dy0dIoFuRoACxF5AKUDs8Yu5NQVIzJFyQBLodgTmzJmNN998vcGv1NwUZB2bCeFx/ld67bZarH2xcI/Mh5w3CL505487yYi0REj58p07NqpWyHHHnbhHH9iBBEig5xKgALEXe+f/WrVh/QcccICvtLT0WgAnSykHCCFa2x+XhmHktGHIXboEAoEDpZR3AzgEgPoIcaEQ4o/BYPDrto4XCAQelVJOA3CRYRjPtdWucT8KkI5Qow0J9BwCa9asxowZf4VpRu8vJA9OxMCfZ8WF+FDrqdlSg3WvbNxjQAafPRAJmc7dU2m8QCVCCt8uQtX6auvb6jL69df/GUOHDtujH+xAAiTQMwlQgNiLuysEiK7rjwG4FIDKL7lJ/Y1rzW3DMEa0F0lOTk6ux+P5BsDXSoQIIdQ8f1RixDTN/QsKCpbvaczc3NxDNU1bAEAxvZgCZE/E+DoJkEB7CagUu/fddydWr15pmaoL53v9apCjF7qb++BGAaJ8UEUL179a2HAxfdiwEbjhhj/zKFZ7H1L2J4EeQoACxF6g3SJA1kkpQ+Fw+OyVK1cqARLTpuv6MwBOFUIMCQaDpWrw0aNHp9XW1q4B8LZhGBfuYUKPrutKwKj+J1GAxDQ8HIwESKCOwDfffI0nnnikgceg07KQnJ0UV3zcKkAUxMr1VSh8s6iB56WX/hbjxh0YV3y5GBIggfggQAFiLw5uESCqrO9VhmE8a8/dlq11XS8BMMcwjLMb9wgEAi9KKU82DCN9d/MGAoEbpZTXaZp2gmmai3gEqzOixDFJgAQeeOAeqGrnqqXmpGDACc5mkmopIm4WIMqfTe9tbrgPoqqk/+EPajOcjQRIgASaEqAAsfdEuEKABAKB903T/DIUCt1qz91drXNycoZ4PJ7VQojbgsHg9MY9/H7/n4QQd2ialpOfn7+qpbnz8vKGm6b5o5TySq/XOzcSiaizEbwDEutAcTwS6OEEtmzZjFtuuaGBwl6/GojE/vFxh6JxaNwuQKqLarD+9Z13WKZPn4HMzPgTej38x4Huk4DjBChA7IXAFQLE7/ePEkK8C+C27Ozsl+bNm7drdasOcsjLyztA7VoIIa4IBoP/bDyMruvqQrn63njDMNTOxi5N1/V3pZTJoVBo0qhRo4ZRgHQwEDQjARLYLYFPP/0EL70U3QT2Zfgw5NxBcUnM7QJEQV370gbUbo3+mTn33AsxYcJRccmaiyIBEnCOAAWIPfauECB1WbBUhqrfq7uCANQh3ZYuorc7C5au6xMAzBdCXBYMBp9sjNPv918shHhCSjkpFArNb446EAj8Skr5nBBi32AwGKQAsfcw0poESKB1Akp8KBGiWu8xaeh3ZN+4xNUdBMjm+SXY8UOZxXfChIk499wpccmaiyIBEnCOAAWIPfauECC6rj8O4BIAqrJVTLNg1e+AALjSMIydtzsB+P3+y4UQM4UQhzRPx5ubm9tb07RlUson64+GUYDYexhpTQIk0DqBBx+cAcPItzr0OyoDvffpFZe4uoMA2fFjKTZ/stXiGwiMwtVXXx+XrLkoEiAB5whQgNhj7xYBshnA96Zpnl1QUFBsz+Wm1rqu76V23AHcbhjG7Y1f1XX9NgDq3slQwzDWN3ttJoDjNU0bn5CQUKVeq6ioGKZp2o8Afp2UlPTSkiVLytu71nA40nr54PYOxv4kQALdhsANN1yPNWtUoj1gwEn9kDoiJS596w4CpHxlBTa9q/7sAMOGDcO9986IS9ZcFAmQgHMEvN44qPzqnPu2Z3aLAOnsLFjqSNcCwzBObyYy/g3gcMMwBjYnreu6umw+tK7uR+OXlYBQXGU4HB6xYsWK6DuGNjYKkDaCYjcS6GEErrnmGmzcGK0wPvCULKQMia/0u/XhaCxAvF4vsrOzkZ6ejm3btmHDhg0Ih6N3K+KpEGHzR6libRU2vhVNxztw4CA8+OCDPexpo7skQAJ7IkABsidCu3/dLQLkbQA/GIZxsz13W7b2+/2PCCEu8Pl8w5YuXapS8kLXdZX2RGW+esowjKuaW+bm5o7zer1N3gFEIpGBQog3hBB3CiFmp6amLlq8eHFte9bMSujtocW+JNBzCNx++5+waVOdAJncHylDk+PS+XoBosTHpEmTMHXqVKuyeCQSwZNPPom5c+daIiSuBcjqSmx8J7rZrgTIrbfeGZesuSgSIAHnCPAIlj32rhAggUAgG8AbAF71er3P14sEe67vtM7NzR2sadq3QoiQEOJ2KaXicquUMsfn8+27dOnSjbquq6NYtwgh9GAwGC1D3KzxDkisIsJxSIAEmhOYMWM6Vq2K/urJOj4Taf7UuIRUL0CGDh2KGTNmWOKjvikRcv3112Pt2rVxLUDKQuUomrPFWvbw4SOtiuhsJEACJNCYAAWIvefBFQJE1/XvVOZJAHl17lbuJgtWZkeQ5Obm7q1p2n0q6Ymyl1LO0zTtBpXdSv277j7ILepLwzBW7EaAqNcuNgzjuY6sgzsgHaFGGxLo/gRmznwQS5cusRzNPCIDfcbG9yX0sWPH4pZb1K/Mpm369OlYsmRJXAuQ7UtKsWVB9BL66NFjccUV13T/B4wekgAJtIsABUi7cO3S2RUCJBAIrJZSmm1x1TCMEW3pF699KEDiNTJcFwk4S+DFF5/BZ59Fs4H3GdcbmYemO7ugVmbvDjsgWz7fiu3flloeHn74kTjvvIvikjUXRQIk4BwBChB77F0hQOy56C5rChB3xYurJYGuIjB79tt4++3/WNOl5qZgwM/iszp3d7gDsun9zSgvqLBYT558Gk48cXJXhZnzkAAJuIQABYi9QFGA2OMXc2sKkJgj5YAk0C0ILFq0EE8//ZjlS2JWAvY6c5fkfHHhZ/MsWIMGDUJGRga2bt2KwsJCV2TBWv/6RlQXRWvdXnzxNBx00Pi4YMtFkAAJxA8BChB7sXCFAPH7/btkoWrJbU3TRDAYfMgeEmetKUCc5c/ZSSBeCaxatQIzZvzVWp5IEBh+6WAIEX+/wt1eB0RKiVVPrIOsiZZkuuGGWzB8uKtP9sbrI811kYCrCVCA2Atf/P31asEfXdfV/Y/6+hrNe9QX7rNqbxiGsTPlij02jlhTgDiCnZOSQNwTqKyswLXXXtmwzqEX7QVvavz9unO7AAmXR7DmmZ11Z++/fyaSk+Mz5XHcP7RcIAl0YwIUIPaC6xYBcmFLbkopkzRNy5VSng/gHSHES8FgcK49JM5aU4A4y5+zk0A8E7jppt9j+3ZVlxUYdEoWkuOwGKHbBUjl2ioU1hUh7NMnHXff/UA8PxJcGwmQgEMEKEDsgXeFANmTi4FAoJdpmp9rmnZvMBh8YU/94/l1CpB4jg7XRgLOEnj44fuRn7/UWkTmhHT02be3swtqYXa3C5Dt3+/Alk+3WZ7l5Y3GVVddG3eMuSASIAHnCVCA2ItBtxAgCoHf7/8dgGmhUGiMPSTOWlOAOMufs5NAPBOYNes1fPjhe9YS0wKpyDq2Q2WPOtVFtwuQog83oywYzYB17LEn4Je//FWn8uLgJEAC7iRAAWIvbt1GgAQCgakAHg4Gg/FZHriNcaIAaSModiOBHkjg66+/wlNPPWp57kv3Ysh52XFHwe0CZO2LG1C7LWxxnTr1chxwwMFxx5gLIgEScJ4ABYi9GHQLAZKTk5Pr9XpflVKmG4aRYw+Js9YUIM7y5+wkEM8EtmzZjFtuuaFhifF4Ed3NAqT5BfS//vU+9O0bf7tM8fyMcm0k0FMIUIDYi7QrBIiu6yW7cTNFfRhY9/p0wzD+Yg+Js9YUIM7y5+wkEO8ElABRQkS1/sf0Ra+8tLhaspsFSGl+GYo/iv656devP+644964YsvF9AwCa9euRnFxURNnExOTkJc3Ch6Pt2dAcIGXFCD2guQWAbKqLg3vLt5KKWuFEIUA3srOzn5o3rx50b1zlzYKEJcGjssmgS4i8Morz2P+/Giyv5ThyRh4cv8umrlt07hZgGz8XzEqVlVajh511NE46yyVYJGNBLqOwCeffIxXX205l87ee++Dyy+/Cl4vRUjXRaT1mShA7EXBFQLEnovusqYAcVe8uFoS6GoCweAyPPTQfdFpNWDolPiqB+JWAWIdv3p2fbTiFICrr74egcCorg4v5+uhBFQBTPXBwmuvvQj1dWttn332te4mJSYm9lBS8eM2BYi9WFCA2OMXc2sKkJgj5YAk0K0ImKaJW2+9ESUlWyy/0g/ojb7j0+PGR7cKkJKF27Bt8Q6LY2ZmP9x++z3QNC1uuHIh3ZdAeXkZXnvtJSxatLCJkwN8PvUZAwpra5t8f+DAQZgy5VIMHz6i+0JxgWcUIPaC5BoBkpubO97j8ZwspRwghGhx/9E0TRkKhVQ2LNc2ChDXho4LJ4EuI/DBB7Pxn/+8bs0nEgSGnpcNT0p8VEV3owCJVESw5sUNkDXRT55PO+1XOO64E7osnpyoZxIIh8P47LP5+N//3kRZWVkDhF4eD87MzERG3VGriJT439atCFVVNfQRQuDww4/ESSedgvT0jJ4J0GGvKUDsBcAVAsTv918lhPi7+lu7B3elYRjx8Ve4g3GhAOkgOJqRQA8iUFVVaWXDKi8vt7zuNSoV/Y+Oj2xNbhQgxR9vQemyKMvU1DRMnz4DSUlJPeiJoqtdSaCqqgoLF35m1fSp38msn39wQgJOzshAmqfpWxlTSnxRWoqFjYSKsvH5fDjssCNwzDHHo1+/rK50o8fPRQFi7xHY0xt6e6PHyNrv9xuapqkDj9dqmvY9gJrWhl62bNnqGE3ryDAUII5g56Qk4DoCn3zyEV599cWGdavL6OpSutPNbQJEXTpXl8/rm7p4ri6gs5FArAls2LAOn346H19++RkqK6PJDuqbT+1o9OqF/VNToYnW35qtq67Gh9u3Y0u4ab4dtSMyevQYTJhwFEaPHgtPMwETa184HkABYu8pcIUACQQC5aZp/iEUCv3Lnrvxb00BEv8x4gpJIB4IRCIR3HffX7FmTfQzFy1Jw15nDoSvt7MZcmq31WLtiyox4e7bkPMGwZden0F9T7075/XaHWGsf30jzCrTmmDo0OG4/vo/8c1b5+DukaNu374d33zzFb788vOGn9XGINQdj7EpKRjfqxdS2yga1JGsHysqsLC0FGVm9Nlt3Hr37o2DDhqPgw46FEOGDIUSJ2yxJ0ABYo+pK55KXde/lVI+FQqF/mHP3fi3pgCJ/xhxhSQQLwQKCzfgnntuR23dJdWETB8GnTYAnkTnLk+rDD6rn1wHs7r1TD5aosCwqYMdfWMUqTZR+J9NqNkSveDr8yXgpptug7rgy0YCdgiUlu7Ad999g2++WQTDyG8xq1WiEBiTkoJxaWlQdz460sJS4qeKCnxTXr7Ljkj9eFlZAzBu3EEYN+5A7LXXEEd/5jriYzzbUIDYi44rBEggEDhFSvkggGMNw1hhz+X4tqYAie/4cHUkEG8EVOacp59+rGFZiYMSMWhyf2g+50RI0ZzNKAtVtIoqzZ+CrOP7OYbSrDVR+HYxqgurG9Zw8cXTrE+N2UigIwTUXY7vv//GEh4FBUarqXQH+XyW8MhLToYvRlnWlOhfW1ODHyoqEKqsRKQVB/r3z8J++x2A/fYbh2HDRjDLW0cC3ciGAsQeQFcIEOViIBC4UUo5XUr5GYD1mqbtcg+EWbDsPQy0JgEScCeBt9+ehdmz32kqQk7uD82hnZBIlWkdbQrv2LUurLe31zoq5klyRiCZaufjnSJUb9z5J+TEE3+OyZN/6c7gc9WOEFBv+gsL1+P777+1hEf9UciWFtPH47EEx6jkZGT6OvfYYZVpIlhZifzKSqyrafW6LPr06YOxY/fHvvuOg67nsbhhB54iCpAOQGtk4goBEggErpFS3s8sWPaCTWsSIIHuSUC9GVIV0hcsmNfgoDqONfDn/eFNc+ZOSLg0jK2Ltjdkl1ILU9m6Mg7qA28vh9ZUFsbGd4objl2pNR1xxCScffb5PJrSPX80YuqVqsGzatUKa5dDiY7i4qJWx+/t8cCflIRAcjIG+nyOPF+lkYi1I6IEyYZmtUQaLzwpKRn77DPW2h1R1daZAa5tjw0FSNs4tdbLLQJktZTSlFJe6/V6f2AWLHtBpzUJkED3I6DeHKmsWAsWzG1wzpPqgcqOldg/wRGHzRoTqx5f1zD38MsGQ0twZuejurjGynYVKd95QOXIIyfhV786j0dRHHk63DGp+rkqKAjh228XWcJj+/ZtrS68r9driQ71X5ZDoqO1xZVFIiioqrIEidoZ2fXqetRSpfVVImT//Q/EmDH7ITnZ+cx68fqkUIDYi4xbBEi5lPL3hmHsPOhsz++4teYdkLgNDRdGAnFPQO2EvPXWLLz//v8a1io8Av0m9UWvQGqXrz9eBEhpsByb55ZARnZejP/Zz07GKaf80pFPprs8EJywXQTUz5Ha6Vi06EvrIvmOHdtbtVd3OnKTkpCbnAwlQGLZ5m3fjm/Ly63UvBP79InZ0OqY1oqqKkuQrKyuhrrM3lLzer1Wat8DDzwEY8bsi4QEVQ2BrZ4ABYi9Z8EVAkTX9a+EEC8Fg0F1Eb1bNwqQbh1eOkcCXULg008/sY5kqU9v61uv0WnInJAOzdt1OxBOCxAzbGLLgm0o/WlnlWlN03DOOVOsKtJsJNCYwObNRVi48HOoxA6tHa9SPz1DEhOtXY6cpKRdCgbGimitlPhHYSGUNFBv1H43aBBUrZBYNzXPmupqa2dkeVUVqloRI+pYljqiNX784cjN1blrCNYBsfssxv5ptruiFux1XZ8A4AkAZxmGoQoRdttGAdJtQ0vHSKBLCaj0n0888U+UlZU2zKvuhajsUwl9O/cibP2ETgqQmpJaqGxc9Wl21ZrS0nrh0kt/C10PdGksOFn8ElAprL/7bjE++2y+lTK3paZEx/DEROjJyZboSIpR9qrdUak2Tfzfxo0NXa4cOBCJnTyvqrausmkZlZUIVVWhsoUaI2pB/fr1x6GHTrD+S0/PiN/gdvLKuANiD7ArBIjf739QCDEcwGQASwGsaeUeiDQM43R7SJy1pgBxlj9nJ4HuRKCkpARPPPGIdZykvgmvQObh6VA7Ip1doMwJAaKOz5QuLcOWT7c1OXI1YkQOpk79Dfr27dudQkxfOkhA7XbMnz8PCxd+irKynTtkDT8naqcjIQGjUlKsI1ZdIToau+KEAGk8f70YUdm01O5IdQs7I2o3UWXSOvLIiQgE9u703ycdDHWnmVGA2EPrCgGi63pr96Wae68ESMcq+tjjGDNrCpCYoeRAJEACAMLhMP7733/jo4/eb8IjZVgS+k3KhDe1835ldrUACZdHUDx3CypXVzXx9ZhjfoZTTz0dHk9sz+jzAXMXAXUk8aeffsQnn3yMn376ocVaHZnq3kNKipUyN62DBQJjQcVpAdLYB3VHRN0ZWVpRYd0ZaenGyIABA3HkkUdj/PjDkJycEgsEcT8GBYi9ELlCgOTl5Q0XQrReVrcRg2XLlq22h8RZawoQZ/lzdhLorgSWLv0Bzz33JFSV5vqmJWnoN7Ev0nI65w1DVwqQsuUV2DyvBGbVzs+revfujQsumGpdpGXruQTUMcQvvvjMyhC3eXPxLiDU3QpVp0MVCHQqZW7zRcWTAGm8NpVNSwkRVfRwe2TXkoeJiYk46KBDoTLMDR48pFs/dBQg9sLrCgFiz0V3WVOAuCteXC0JuImAEh8vvPAMfvjhuybLTtNTkHlE35gXB+wKAaKKHm5ZUIIyo2nldZVC9PzzL0KvXr3dFCKuNUYE1G5HKBS07naoOx5qJ7B5U7sd+6WmWrsdnX2/or1uxasAqffDyhRWXY3vystb3RVRxx4PO+wIHHDAQVC1RrpbowCxF9G4FCAjR44cappm0apVq6x9dPXvtrq5YsUKdT/EtY0CxLWh48JJwBUE1BuHzz9fgDfeeBnV1dUNa1Y1Q/of3RcpQ2P3RqGzBUjFmkoUf1zSpLaH+gT2jDPOsd74dPYdF1cEvIctcuPGQixa9AW+/PILlJRs2cV79aZHZbBSwmNwQkLcPiPxLkAag90eDuP7ul0RleK3eUtISLAyaB1yyGFW1XWPg0fbYvnjQAFij2ZcChBd1yNSyjNDodAs5V7dHZC2HMFSd0BcfciXAsTeA01rEiCBthFQl3Cfe+4pFBQYTQx675OGvoelQ/PZT9fbWQLErDVR8vk27Pix6eVhlR50ypSpVpYetp5DoKhoE7799murZsfatS1/BpmmadYRqzGpqejlgjfAbhIg9U+auiuiMmipXZHCViqvq2ORqsjh/vsfhNxcv6vT+VKA2PsdE68C5GnTNP9RUFDwTZ0AeQZo8d7TLt4bhnGxPSTOWlOAOMufs5NATyKgjql89NEcvP32rCZHVHzpXvQ/NhNJA+wVHusMAVK1qRrFH25B7badR2pUwbTJk3+JY4453tVvaHrSs2fHV7WLp4TG5aPpogAAIABJREFUkiXf4vvvv8H69etaHE69wRmRmGgJj5FJSdA6oY6GHT92Z+tGAdLYn+LaWuueyLKKilZri6i02Pvuuz/Gjt3PyqKldkrc1ChA7EUrLgWIPZfcbU0B4u74cfUk4EYCGzasx7PPPt7002MNyDi4D9L37w2hdexPRSwFiDQltn2zA1sXbQcanfIYMmQYLrzwUmRn7+VG9FxzGwmo44LB4E/48ccl1n/btm1t1XKAz2fd61AXy1NdsNvR3JEdkQi+2LEDP1ZWNry0T3IyDu3dG71d5o/aFVlZVYVllZVWJq1dr61HXfT5EpCXtzf22WcsRo8e64p02RQgbfzhbaVbx/6q2Juz3dZ+v//iUCj09O4MA4FALynl/YZhTGv3BHFkQAESR8HgUkigBxFQl3TfffctvP/+/5qkJ03aKxFZx6l0ve0/3RorARIuD6Pogy2oWr/zzoq633HCCSfjxBNPgdoBYeteBNQuR1HRRqjsbeo/daG8pYvk9V7393qtQoHqv74ufh5U8b8Xi4tbzDDVx+PB+f37d3lNklg9Wep+iKq2ro5pra6ublWMqPmyswdb2euUGMnJyYnLFNoUIPaeDFcIkLo7IO+bpnlZQUHBLnutuq6fCOBfAPZiHRB7DwStSYAEejaB5csL8Mwzj2HLls0NILRkDVnHZrb7groZNrHqsXXRA7QCGD5tMDRv++6WqIvmSnw0Tq+bmdkPF100DTk5uT07WN3M+5qaahhGED/++L0lOho/g81dVW9e9kpIsCqTq0KB6S4WHY19+9/WrVDF/1pralfn5Az3Vx9XR8xUTRElSNQOSUuFDusZqAxaanckKkjGxE31dQoQe7+A3CJA/gLgBgC1UsobQ6HQo8rt4cOHpyckJDwM4DwAqwBcaRjGbHtInLXmDoiz/Dk7CZAAUFlZiVdeeR6LFi1sgiPjkD5IP6B3uzIHbfl0K7b/UIo+Y3ohc0Lb3zipT8C3Ld6BrV9ub7KGgw4aj7PPvgDJybHL1sWYO0dAHaVasuQ7S3QEg8tQ28rlZbXCJCEwPCkJIxMTrf8na+0Ts8552baZ1TM/c+PG3b4ZTxQCVwwc2K6fwbbN7lyviJRYX1NjHdFSoqSkhZTJjVc3ZMhQqDTb6u6IOoLpVLY7ChB7z4wrBIhyMRAIjDBN80EhxGQA8wC8BOAOAH2FEPdVV1ffWZ+21x4SZ60pQJzlz9lJgASiBNSboYULP8Urr7yI2tqaBiwpI5Ot3ZBYZMlqjbU6ulX00RZUrNj5SbC6oHrWWedj/PjDHXvDwWcjNgTUzsY333xtZa5atWrFbgdV9znURXIlOAb5fK66SN5eWlvDYTxVVLRHs0uyspDRTXZ8WnJ2WzhsCZFVVVVYU1MDdY+ktZaR0Rf77TcO48YdjBEjRnZpEgoKkD0+qrvt4BoBUu9F3XGrVwGkAsjXNO20/Pz8pnkk7TFx1JoCxFH8nJwESKAZgQ0b1uGxx2ZCpTqtbwn9fBh4cn9402J/9yJcFsbG/xWjZnNtw3xZWQMwbdoV1rlwNncSUMerFi/+yqpI3jz1c2OP1Cf8wxITraxVwxMTXXmJvKMR2lxbi2eLd63U3ny8C/v3Rz+fr6PTuMpOiY911dWWIFE7JNtaqL5e75A6mnnwwYdaNYDU153dKEDsEXaVAAkEAmOllDMBHA5gvToCCuDJxMTEG3744YfWU2LYY9Sl1hQgXYqbk5EACbSBQGVlBZ555okmFdS9aR4MPCULCRmxeyNUU1KLwreLECnbmStHHbW46KJLkZyc0oaVsku8EdixYzs+/vgDLFgwD+o5aqmlezzWXQ71X3ZCAjwuSpcbS94UIHumqY5nKSGi7o6oY1st7Y2oI1nqeNbxx58EVY29sxoFiD2yrhAgKsMVgL9KKX8DYCOAX2dnZ39QWFh4k5TyZgClAK4zDOM5ezict6YAcT4GXAEJkMCuBFTNkDfffAMffvhew4takoZBv8hCYj/7+furi2tQ+FZRk8vmxx57Ak499YwuPVbB2MeGgMpY9cEHszFnzrtQKXSbN5WpKqCyViUlIdPr5bE6ABQg7Xv2KiIRS4gE1VGt6uoWxYiqwH7GGed0SlpfCpD2xat5b1cIEF3XlejoL4R4HMD1wWBQCQ6r+f3+UZqmPSmlHC+l/CQUCk2yh8RZawoQZ/lzdhIggd0TmD9/Ll599YWGVL1aYp0I6d9xEWKJj/8WwayOFvhQn2Cq+x5HHunqX+c99lHavn07Hn30YaxevbIJgwQhsHdyMvZJSUGWz0fR0ewJoQDp+I9MeSRi1RpZUlEBdZemcVMJK6ZO/Q323nufjk/QgiUFiD2cbhEgBUKIy4LB4NxW3BWBQOAqKeVfDcNQuyWubRQgrg0dF04CPYaAukD81FP/gmlGj0qpNL3ZvxyAhPT2H8eq2VaLDbM2wayMig9N82Dq1F9j//0P7DE8u5OjVVWVuO++O1FYuKHBrRRNw8FpaVZF8oRulrkqlrFrLEBUbZvs7Gykp6dj27Zt2LBhQ0MdlJ50B6S9fFXyjFXV1fiitBSFjTKqeTweXH319cjN1ds7ZKv9KUDsoXSFABk8eHDyunXrWk+MDSA3N3ewpmnDDcP41B4SZ60pQJzlz9lJgATaRuD777/FE088gkjdpVBvbw/2OmMgPMmetg0AIFIZwfrXNyJcGhUy6k3CZZf9FmPH7t/mMdgxvgioY3rq2FV9G5uSgqN696bwaEOY6gWIEh+TJk3C1KlTrZ8J9TP25JNPYu7cuZYIoQDZM0wlRNSOyEfbt6OmLouWSmZx6613xuxIJwXInuOwux6uECBtcVHX9SsATDcMo29b+sdrHwqQeI0M10UCJNCcwNdff4Wnn/5Xw3GspOxEDDolC8Kz5z8tMiKtY1dVhdH7AerY1cUX/xoHHngwQbuYwE03/R7qCJZqatfjiN69XexN1y69XoAMHToUM2bMsMRHfVMi5Prrr8fatWspQNoRlsKaGry8eXPD/ZBrr705ZgVMKUDaEYgWuu75r4S98WNmreu6+qt0pbr2ASCx2cBJdd8vMQxjQMwmdWAgChAHoHNKEiCBDhP4+OM5eOONVxrs08f1Rt9D0/c43pYvtmH7Nzsa+p1xxtk4+ujj92jHDvFLQKXaveYalSsm2n49YADSGr2Jjt+Vx8fK6gXI2LFjccstt+yyqOnTp2PJkiUUIO0MlxIgG2qitYymTJlq1RKKRaMAsUfRFQIkEAhMklLOUTv0rbhbLYT4SRUmDAaD/7WHxFlrChBn+XN2EiCB9hFQRx1eeOFpfPHFztOvg07NQvJe6nOhllvl+ioUvrmz4Nqhh07A+edfzEvJ7UMfd70jkTCuuurXDTtiU7OykN6NC+bFOgDcAYk10eh4zxcXo6juPsgll1wes11WChB78XKFANF1/WMA2QDO0jRtnWmaxVLKiVLK7wAcpWnanwC8ahjG3+3hcN6aAsT5GHAFJEAC7SOgPvm+996/orBQlWcCvH28GHz2QGhebZeBzLCJdS9vRHhHNFPNoEF74cYbb4GqdM7mfgK33fZHFBdHxeXkjAzoycnud6qLPOAdkNiDjkiJfxQWor6y0E03/QVDhgyNyUQUIPYwukWAqBK8dxiGMXPkyJF9vF7vViVAQqHQfOX+mDFjMqqqqr4EcFcoFHrGHhJnrSlAnOXP2UmABDpGYO3a1bj33ulQ9UJUyxjfBxkH9NllsK1fb8fWL6N3BFTGKyU+YvWGoGMrp1UsCajsaF9/rf4c8w5Ie7k2z4I1aNAgZGRkYOvWrSgsLGQWrPYCBbCppgYvbN5sWfp8PjzwwEx4PN4OjLSrCQWIPYxuESDqluKFhmG8ojJipaSklEspJ4dCof/Vux8IBK6WUl5iGMa+9pA4a00B4ix/zk4CJNBxArNmvdZQqFD4BIZOyYYnqdFF2qoI1jy3AbI2Wr9YFRr85S9/1fEJaRl3BObMmY0333zdWtfIxESclpkZd2uM1wWxDkjsI/NTRQVmb9tmDTxs2AjrA49YNQoQeyTdIkBWCCHeCAaDNyh3dV1XH589aBjGbfXu+/3+i4UQ/zAMI80eEmetKUCc5c/ZSYAEOk6gsrIS6ghOWVm0Vmz6Ab3Rd/zOC+klC7dh2+LoxfO0tF64/fZ7oIqEsXUfAt999w0ee+z/LIdUhfOLsrK6j3Od7AkFSOwBf15aatUEUe2gg8bj4ounxWwSChB7KF0hQAKBwAwp5e8BqEKDt+u6/gGAQwBcBuAjTdOGmab5tMqOZRhGwB4SZ60pQJzlz9lJgATsEWj8CbiWpGHohdnWXRB192PNMxsaqp2fdtqZOO64E+1NRuu4I7B+/Trceeet1rrU3tfvBg2CR7jirYbjLClAYh+Cd0pKEKyqsgY+8cTJmDz5tJhNQgFiD6UrfiuoOx7V1dXvCSE2BYPBU3Jzcw/VNE1VRW9cdlf5cpVhGNGPXlzaKEBcGjgumwRIwCKgdkFuvvkPqK6O1vfof2wmegVSURosR/GHW6zvJSYm4q67HuDuRzd8ZlShvGuvvRK1tdG0pyelp2NUSko39DT2LlGAxJZpRSSCp4qKUF1XiHDatCux337jYjYJBYg9lK4QIPUuqmrnBQUF69S/A4HAWCnlFVLKYUKIjVLKN0Kh0Dv2cDhvTQHifAy4AhIgAXsEXn75OSxYMM8aJHloEgZNzkLhW0WoXBv9JPKIIybinHOm2JuE1nFL4OmnH8OiRQut9SUIgZMzMjAyqfW0zHHrSBcvjAIkdsB3RCJ4u6QEG+vS7yYnp+Duu+9HQkLzMnIdn5MCpOPslKWrBIg9V91hTQHijjhxlSRAAq0TWL48hPvvvzvaQQOGnp+NNS9sAKIJsnDttTchJ0fVlGXrjgSKijbh7rv/0rALpnz0JyXhkF69MMDX+OBCd/S+4z5tDYetT+z31C7JykIG66u0iEntenxbXo7F5eWordv5UB3POus8HHXUMf/f3pmAyVGUffx9a3ayuREQCSH3TlfvsoQrcnmGQ+RTVPzEE0EQDwQUxQ+BcB8Cih+ifipegBzet3giEgEF5VJgyXb15CCQEETFkECSnZ1+v+cdumNn2E120r2b2d1/Pc8+gd2u6qpfVc/Uv9+jtoS2ob9DgDSE6wUXQ4Bk45d7bQiQ3JGiQRAAgSEmoKl4zzrrNFqz5vmA8wneeHo2fK7235MnT665XxnzwjNChribuN0gEnjkkYfpa1/74iYiRG+3S7FI7ePG1c4HwSnpm06AHur5xVWrNroM9TU9rcx08pQpOLQzBUeFxrL166l73TpavH79xjM/kksOPvgwestb3p47MwiQbB8gTStA4sMHGx2dOOfylbiN9iDj9RAgGQGiOgiAQFMQuO66r9Ff/nLXC/qy334H0nHHaf4QlJFO4IknVtKNN15LS5cu7nOoLykWaXZrK81obaVdxoyhIoLV6RdPP13bSPdXVLypS9toLirU/tHbS49t2ECPbthAyzdsoOePNd20TJw4kd761nfRS1+6f+7iQ+8EAZJtFTazAFFjva4pjfkYcD+dc7OzIdm2tSFAti1/3B0EQCAfAn/84+10000vPBf26KOPo5e//FX53AStND0B3Sz+7W8P0K23/poWLy7321/NmKWCZNcxY2piZEqxSJMKhUHZODYztPVRRDc+9RStriZnd/+nty8qFOjonXaisaPMerghiujJSoWe6OmhlfpTqZBy6q+86EXb06tedRDNn38IjR07eGm+IUCyPUkD3thnu03jta21fyGilxLRSma+WYPMnXO3EtHzJ1iN0AIBMkInFsMCgVFG4PHHH6NLL914VNPG0S9YcCFNmzZ9lNHAcJXAypWP0z33/Jnuv/8eeuqpLcc6jDemFjOiwiT52W4UiBINoL7rmWfo4ZQlZPdx4+jAyZNpcuE/B3uOxFWlMRxP9fbS3yuV2o8KD42N2VLR84Tmzt2L5s3bj3bbbXcqDAEnCJAtzcrm/960AkS73d7ebqvV6ruZ+WgimkVEq4jo2yJyYxiGf8029OasDQHSnPOCXoEACDRGoFrtpVNP/RBF0X/e5Oqm4KqrvkyFQktjjeHqEUfgySdX0cMPP0hBsIjKZUfr1/fvdpQevLppvbilhV5cLG7y7/gh2HAO5SToW///W6VbnufLKVOmUOsIsnxUooj+2dtb+9HsX+pS9VSlQs9uxrKR5q8xZDNmzCJr22m33eZSW1vbkH+uQIBkeyKaWoCkh+b7/suJ6N0i8lYiUgfIRcx8Q29v77cWL178WDYMzVMbAqR55gI9AQEQyEbgyisvr20uk1IqWTrttDOzNYraI45AtVqtWUeWLCnTkiWLadmyJQOykKRBjDOmdvJ67adYpB3i/55gzLB04xopAqQniuhfsdCoCY5KpSY6+nIx29zCnjBhAs2cOZvmzCnRnDltNHPmnG1+jhAESLaPomEjQJJhzps3r7hmzZrXM7OKkdfrYYTMfCcR3VCpVH6wZMmS1dmQbNvaECDblj/uDgIgkB8Bfct9662/rWXDmjRpMh1yyGG0885T8rsBWhqxBJ577ll69NFl9Nhjy+nxxx+t/avpfTWmpJGiWaNUjNQESUqYqCuTaeKgd83s9IUnnqj5nOtGTU+Ub+YgfXWdSoRG+t81fcSybGn+NFPetGkzaj/Tp8+gmTNn0Y477tR0QhICZEszufm/DzsBkh5OqVSabIx5ExGdRET7MfP6IAgmZEOybWtDgGxb/rg7CIAACIBAcxLo6dlAmllrxYrHacWKx2r//cQTK2j16sbfO6oToJ6lsUOx+B/LSUsLvailhQpNIkwWrl5dO9Ni7wkTaP52223zSVHxt1Zdp2IrhloyErGxuaDw/jreqtnPdplKu+yyK02dOo123fX5H31ZMRwKBEi2WRq2AsRauycRHUNERxLRHCJ6WkS+G4ahipFhWyBAhu3UoeMgAAIgAALbgMCzz66tiZFVq1bSypXPi5JVq56g1av/3XBv9HQaFSEaZ6IWk9q/LS01sdLMFpOGB7qZCio0NBZDYzNqMRop16meBi1QepuxY8fSlCm70JQpKjaeFxz67/bb7zCszwOCAMm26oaVAJk9e/bOxWJRA9KPJaK5cZreX4nI9ZMnT/75fffdV8mGY9vXhgDZ9nOAHoAACIAACAx/AuvWPVcTIpv+rKR//OOphl251GKi1pKdWlpopzgrl/473FPiVkVqIkMzTmkQuP6o4Fg3wGDw9CpRy8XzQiP5mVr7b02Ly01iVcpzVUOAZKPZ9AKkVCq1GmPUyvEeIjqUiPRz4B6N+TDGfLu7u/uf2RA0V20IkOaaD/QGBEAABEBgZBGoaIrXvz+50WqilhMVKRqzpAHxjRSNJdEzSzRN8JT4/JJmzVYVidRS3K7q6amlt9UftXL0f6JG3yR22GHHmrBQK4ZaNRLBMWHCxEbQDftrIUCyTWHTChBr7StjS8dRRKQOgZrp6iZmvj4IgiDbsJu3NgRI884NegYCIAACIDByCWjqaLWOrFy5oiZOnv93RU2YRA1YBNRla+qYMTRtzJjawYrbtWybtNOaSUsP7nu8p4dWxKKjtwEXKrVcTJ2q7lIao/G865SKjcE83G84rS4IkGyz1cwCJDkJ/S4i+lUURXcx8xbTX4RheHs2JNu2NgTItuWPu4MACIAACIBAmoBaTJ588glasWJFLfhdD9nUzFxr164dECg9PHFGayvNbG2lWa2tg3aeh1o4VHAs27CBlm/YQKsqlQGd3FwsFmtB4HpA6K676s/zweDjxw/rnD4DmpssF0GAZKH3fHa3pizW2rRVcIvCI85UJ865YX1MKARIUy5HdAoEQAAEQAAENhLQQG0Ncl++fBktX/5oLWWwnl+iAfGbKxrkrpYRf9w48saNIz2/JEtR0fHohg0UrFtHi9evp/VbsHC0tLTQ9Okza6lt9SC/GTNm0s477zIkJ4dnGWcz1oUAyTYrzSxANOaj4eKc+2bDlZqoAgRIE00GugICIAACIAACAySgouSpp/5OS5cupsWLw9ohnBpb0l/Rt6VtY8fSXhMm1ERJI4Haz/T20l+fe466nnuOntuMe9jEiZNIDwBta/Oora1Us3CoxQMlOwEIkGwMm1aAZBvW8K0NATJ85w49BwEQAAEQAIE0AT2jxLlFtGhRF3V1PVQ7lLOvooHsL580iWaNHbtZgKt7e+muNWvokXXr+nSvUguHte3U0bE7tbfvVovhaETYYPYGTgACZOCs+roSAiQbv9xrQ4DkjhQNggAIgAAIgMA2J6CB7Oqm9cAD99K99/6lz3NK5rS20ryJE1/gmqU+6W7dOrp/7VrqrRuJio499tiL9tlnP9ptt91r526gDD4BCJBsjCFAsvHLvTYESO5I0SAIgAAIgAAINBUBFSOPPPIwLVz4u9q/W1N22uklNH/+obT//gciYHxrAGasAwGSDSAESDZ+udeGAMkdKRoEARAAARAAgaYloEHsP/rRd8m57gH1cbvtXkRHHnkU7bvvAcP6JPEBDbaJL4IAyTY5ECDZ+OVeGwIkd6RoEARAAARAAASamoAGsP/xj3+gW2/9La1Zs6bPvra0FGiPPfahN7/5KBo3bnxTj2c0dA4CJNssQ4Bk45d7bQiQ3JGiQRAAARAAARAAARDIlQAESDacECAxP9/3XyoilxHR/kSkibnvZuYzgyC4dzOIje/7HxSRU4loFhGtIqKFRHS2c27F1kwNBMjWUEMdEAABEAABEAABEBg6AhAg2VhDgGge7ra2UqFQuJ+I7lURwsyacOJMFSNRFO1dLpcX94XZ87yrmPkUEbmUmW9hZi/+7w1r1qzpWLly5XONTg8ESKPEcD0IgAAIgAAIgAAIDC0BCJBsvCFAiMhaex0RHcnM04MgqDlfdnZ2TqxUKsuJ6OfOuRccijh79uydi8XiSiL6knPuw8k0+L7/NhH5NhEd55y7odHpgQBplBiuBwEQAAEQAAEQAIGhJQABko03BMjzAuRfRPRb59w70jh9379JRF7vnHtRPeb29vYdq9Xqa0Xkz2kLie/7vogsIqJznHOXNjo9ECCNEsP1IAACIAACIAACIDC0BCBAsvEe9QKkra1teqFQeJSZzw+C4OI0Ts/zzmbmi4wxbd3d3csGgtpaeyQR/YiZ3xEEwfcGUid9DQRIo8RwPQiAAAiAAAiAAAgMLQEIkGy8R70AaW9vnxdF0T3MfHIQBF9O47TWfoCI9HcHOOfu2RLqqVOnjp84ceJ9RDQhiiKvXC5v2FKd+r9DgDRKDNeDAAiAAAiAAAiAwNASgADJxnvUCxBr7SuI6HZmfn8QBN+os4Acz8xfF5GDwjC8fXOoZ82aNXbMmDE/JKJDiOg1zrk7tmZqIEC2hhrqgAAIgAAIgAAIgMDQEYAAycZ61AuQxAJCRKc4575UJ0BOZOYvMvP+m0vHWyqVJhtjfq5Zs5j5bUEQ/GxrpwUCZGvJoR4IgAAIgAAIgAAIDA0BCJBsnEe9ALHW7kpEjxHRhc65C9M4rbXnE9F5RDSjv3M9Ojs7d6hUKrfpNcaYN3d3d+s5IFtdenurstWVUREEQAAEQAAEQAAEQGDQCbS0FEb9HjoLZMB7PgvW34noDufcW+oEiLpUvdw5N6UvyKVSqbVQKNwmInOY+bAgCB7MMhlaFwIkK0HUBwEQAAEQAAEQAIHBJQABko0vBAgReZ73JWY+plgszuzq6tKUvCpKXkxEmvnqGufcR/rCbK39IhEdKyKvDMPwr9mm4vnacMHKgyLaAAEQAAEQAAEQAIHBIwAXrGxsIUCIqFQqTTPGPMDMITNfKCLK5TwRaSsWi3t2dXWtstaqK9a5zGyDIFja0dHhVatVPe/j28aYq/qYhjXd3d2u0emBAGmUGK4HARAAARAAARAAgaElAAGSjTcESMyvVCrtZoy5gog0KxaJyEJjzCeCIAhii4jGg5yrxhHn3BJrrZ6Ofs1m8P/BOXdwo9MDAdIoMVwPAiAAAiAAAiAAAkNLAAIkG28IkGz8cq8NAZI7UjQIAiAAAiAAAiAAArkSgADJhhMCJBu/3GtDgOSOFA2CAAiAAAiAAAiAQK4EIECy4YQAycYv99oQILkjRYMgAAIgAAIgAAIgkCsBCJBsOCFAsvHLvTYESO5I0SAIgAAIgAAIgAAI5EoAAiQbTgiQbPxyrw0BkjtSNAgCIAACIAACIAACuRKAAMmGEwIkG7/ca0OA5I4UDYIACIAACIAACIBArgQgQLLhhADJxi/32hAguSNFgyAAAiAAAiAAAiCQKwEIkGw4IUCy8cu9NgRI7kjRIAiAAAiAAAiAAAjkSgACJBtOCJBs/HKvDQGSO1I0CAIgAAIgAAIgAAK5EoAAyYYTAiQbv9xrQ4DkjhQNggAIgAAIgAAIgECuBCBAsuGEAMnGL/faECC5I0WDIAACIAACIAACIJArAQiQbDghQLLxy702BEjuSNEgCIAACIAACIAACORKAAIkG04IkGz8cq8NAZI7UjQIAiAAAiAAAiAAArkSgADJhhMCJBu/3GtDgOSOFA2CAAiAAAiAAAiAQK4EIECy4YQAycYv99oQILkjRYMgAAIgAAIgAAIgkCsBCJBsOCFAsvHLvTYESO5I0SAIgAAIgAAIgAAI5EoAAiQbTgiQbPxyrw0BkjtSNAgCIAACIAACIAACuRKAAMmGEwIkG7/ca0OA5I4UDYIACIAACIAACIBArgQgQLLhhADJxi/32hAguSNFgyAAAiAAAiAAAiCQKwEIkGw4IUCy8cu9NgRI7kjRIAiAAAiAAAiAAAjkSgACJBtOCJBs/HKvDQGSO1I0CAIgAAIgAAIgAAK5EoAAyYYTAiQbv9xrQ4DkjhQNggAIgAAIgAAIgECuBCBAsuGEAMnGL/faECC5I0WDIAACIAACIAACIJArAQiQbDghQLLxy702BEh+QuKbAAAgAElEQVTuSNEgCIAACIAACIAACORKAAIkG04IkGz8cq8NAZI7UjQIAiAAAiAAAiAAArkSgADJhhMCJBu/3GtDgOSOFA2CAAiAAAiAAAiAQK4EIECy4YQAycYv99oQILkjRYMgAAIgAAIgAAIgkCsBCJBsOCFAsvHLvTYESO5I0SAIgAAIgAAIgAAI5EoAAiQbTgiQbPxyrw0BkjtSNAgCIAACIAACIAACuRKAAMmGEwIkG7/ca0OA5I4UDYIACIAACIAACIBArgQgQLLhhADJxi/32hAguSNFgyAAAiAAAiAAAiCQKwEIkGw4IUCy8cu9NgRI7kjRIAiAAAiAAAiAAAjkSgACJBtOCJBs/HKvDQGSO1I0CAIgAAIgAAIgAAK5EoAAyYYTAiQbv9xrQ4DkjhQNggAIgAAIgAAIgECuBCBAsuGEAMnGL/faECC5I0WDIAACIAACIAACIJArAQiQbDghQLLxy702BEjuSNEgCIAACIAACIAACORKAAIkG04IkGz8cq8NAZI7UjQIAiAAAiAAAiAAArkSgADJhhMCJBu/3GtDgOSOFA2CAAiAAAiAAAiAQK4EIECy4YQAycYv99oQILkjRYMgAAIgAAIgAAIgkCsBCJBsOCFAsvHLvTYESO5I0SAIgAAIgAAIgAAI5EoAAiQbTgiQbPxyrw0BkjtSNAgCIAACIAACIAACuRKAAMmGEwIkG7/ca0OA5I4UDYIACIAACIAACIBArgQgQLLhhADJxi/32hAguSNFgyAAAiAAAiAAAiCQKwEIkGw4IUCy8cu9NgRI7kjRIAiAAAiAAAiAAAjkSgACJBtOCJBs/HKvDQGSO1I0CAIgAAIgAAIgAAK5EoAAyYYTAiQbv9xrQ4DkjhQNggAIgAAIgAAIgECuBCBAsuGEAMnGL/faECC5I0WDIAACIAACIAACIJArAQiQbDghQLLxy702BEjuSNEgCIAACIAACIAACORKAAIkG04IkGz8cq8NAZI7UjQIAiAAAiAAAiAAArkSgADJhhMCJBu/3GtDgOSOFA2CAAiAAAiAAAiAQK4EIECy4YQAycYv99oQILkjRYMgAAIgAAIgAAIgkCsBCJBsOCFAsvHLvTYESO5I0SAIgAAIgAAIgAAI5EoAAiQbTgiQbPxyrw0BkjtSNAgCIAACIAACIAACuRKAAMmGEwIkG7/ca0OA5I4UDYIACIAACIAACIBArgQgQLLhhADJxi/32hAguSNFgyAAAiAAAiAAAiCQKwEIkGw4IUCy8cu9NgRI7kjRIAiAAAiAAAiAAAjkSgACJBtOCJBs/HKvDQGSO1I0CAIgAAIgAAIgAAK5EoAAyYYTAiQbv9xrQ4DkjhQNggAIgAAIgAAIgECuBCBAsuGEAMnGL/faECC5I0WDIAACIAACIAACIJArAQiQbDghQLLxy702BEjuSNEgCIAACIAACIAACORKAAIkG04IkGz8cq8NAZI7UjQIAiAAAiAAAiAAArkSgADJhhMCJBu/3GtDgOSOFA2CAAiAAAiAAAiAQK4EIECy4YQAycYv99oQILkjRYMgAAIgAAIgAAIgkCsBCJBsOCFAsvHLvTYESO5I0SAIgAAIgAAIgAAI5EoAAiQbTgiQbPxyrw0BkjtSNAgCIAACIAACIAACuRKAAMmGEwIkG7/ca0OA5I4UDYIACIAACIAACIBArgQgQLLhhADJxi/32hAguSNFgyAAAiAAAiAAAiCQKwEIkGw4IUCy8cu9NgRI7kjRIAiAAAiAAAiAAAjkSgACJBtOCJBs/HKvDQGSO1I0CAIgAAIgAAIgAAK5EoAAyYYTAiQbv9xrQ4DkjhQNggAIgAAIgAAIgECuBCBAsuGEAMnGL/faECC5I0WDIAACIAACIAACIJArAQiQbDghQLLxy702BEjuSNEgCIAACIAACIAACORKAAIkG04IkGz8cq8NAZI7UjQIAiAAAiAAAiAAArkSgADJhhMCJBu/3GtDgOSOFA2CAAiAAAiAAAiAQK4EIECy4YQAycYv99oQILkjRYMgAAIgAAIgAAIgkCsBCJBsOCFAsvHLvTYESO5I0SAIgAAIgAAIgAAI5EoAAiQbTgiQbPxyrw0BkjtSNAgCIAACIAACIAACuRKAAMmGEwIk5uf7/ktF5DIi2p+IDBHdzcxnBkFw7+YQe573LmY+nYjaiWgtEf2qUqmcvnTp0ie3ZmogQLaGGuqAAAiAAAiAAAiAwNARgADJxhoChIja2tpKhULhfiK6V0UIM0dEdKaKkSiK9i6Xy4v7wux53juZ+SYi+jIzfyuKop2Z+TNEtGbq1KnzFi5c2Nvo9ECANEoM14MACIAACIAACIDA0BKAAMnGGwKEiKy11xHRkcw8PQiCNYq0s7NzYqVSWU5EP3fOvacvzNbaJUS0zDl3cPJ33/dfLiJ3iMgJYRhe2+j0QIA0SgzXgwAIgAAIgAAIgMDQEoAAycYbAuR5AfIvIvqtc+4daZy+798kIq93zr2oHrO1dk8iekBETgrD8Or03621K5j5viAI3tjo9ECANEoM14MACIAACIAACIDA0BKAAMnGe9QLkLa2tumFQuFRZj4/CIKL0zg9zzubmS8yxrR1d3cvqxMZxxCRWk7mO+fuqPvbLUTkOedmNTo9ECCNEsP1IAACIAACIAACIDC0BCBAsvEe9QKkvb19XhRF9zDzyUEQfLlOSHxA4zuI6ADn3D11f/s4EX1aRHYPw3BR3d++xcxvCoJgQqPTAwHSKDFcDwIgAAIgAAIgAAJDSwACJBvvUS9ArLWvIKLbmfn9QRB8o84Ccjwzf11EDgrD8Pa6v53DzBdGUWTrg9Sttd8konc75wqNTg8ESKPEcD0IgAAIgAAIgAAIDC0BCJBsvEe9AEksIER0inPuS3Ui40Rm/iIz71+fjtdaW7OARFE0t1wuP1JnAfkOER3hnJvY6PT09lal0Tq4HgRAAARAAARAAARAYOgItLQURv0eOgvtUQ/PWrsrET1GRBc65y6sExLnE9F5RDTDObci/Tff948WkeujKDq4XC7/oU643MbM05xzXpbJQV0QAAEQAAEQAAEQAAEQGGkERr0A0Qm11v6diO5wzr2lToD8kIhe7pybUj/xpVKp0xjzkIicGobhF+rqPUVEt9Zn1RppiwfjAQEQAAEQAAEQAAEQAIFGCUCAaLoqz/sSMx9TLBZndnV1aUpeFSUv1jM+iOga59xH+gJrrX2Emf8dBMHLkr9ba/+LiH4hIkeFYfijRicE14MACIAACIAACIAACIDASCYAAUJEpVJpmjHmAWYONbBcRJTLeSLSViwW9+zq6lplrVVXrHOZ2QZBsFQXhed5RzDzT5j5ehG5VkSmM/MVRFR2zr16JC8cjA0EQAAEQAAEQAAEQAAEtoYABEhMrVQq7WaMUfGgWbFIRBYaYz4RBEEQW0Q0HuRcNY445/QE9FoplUpvMMaoOOkkotVE9MMoihaUy+VntmZCUAcEQAAEQAAEQAAEQAAERjIBCJCRPLsYGwiAAAiAAAiAAAiAAAg0GQEIkCabEHQHBEAABEAABEAABEAABEYyAQiQkTy7GBsIgAAIgAAIgAAIgAAINBkBCJAmmxB0BwRAAARAAARAAARAAARGMgEIkJE8uxgbCIAACIAACIAACIAACDQZAQiQJpsQdAcEQAAEQAAEQAAEQAAERjIBCJCRPLsYGwiAAAiAAAiAAAiAAAg0GQEIkCabkJHcHWutnqWiP/WlQkSPi8jPx4wZc1FyGv1QsLDWHkJEtxDRcc6564fontcS0bHOucJQ3E/vYa19nIicc+7gobon7gMCIAACw5lAR0fHzGq1+j9E9Bpmni4iERHpQcQ3E9GVzrl/5DG++D7a7gXOuYvyaHNLbVhr30NEeoDy/DAMb9/S9fg7CORNAAIkb6Jor18CsQA5L4qiI4loRerCScaYlxHRWUS0vFgs7tPV1dUzFChjAfJbIjp+qATInDlzZhhjdiyXyw8MxRhjAfIYEYUQIENFfNvepxnF/paIYEO0JUL4+1AS8DzvCGb+jr4cI6IvENGDURSZQqGwv4h8jIhMFEX/VS6X72+0X9bazzPzxCAI3qt1582bV1y9evXc1tbWlV1dXasabW9rro+ft2tE5CAIkK0hiDpZCUCAZCWI+gMmkAgQIvLSp8knDfi+f4KIfFVEjgnD8FsDbjjDhdvCApKhu1td1VoLAbLV9IZfxWYU+/UUrbUPEtFnEuE/d+7c7detWzd7/PjxwYMPPvjs8KOOHo8UAqVSqc0Y81ciujuKoiPK5fKG9Nja29t3jKLoDiKayMydQRCsaWTs1tq/MvP9iQBppG5e10KA5EUS7WwtAQiQrSWHeg0T2JIAKZVKuxljHiaic5xzl+obJmvtJ9Q6QUSziOhfRPRnZj4jCIIg6YC1NmLmS0XkXiK6hIjmEJFuuC91zn0zuS7+UrmamV8mImuJ6Hsi8htm/lnaBcta+2IiuoyIXk9EOxLR34noZz09PWcvW7bs39qe53nHM/M3jDH7RlH0YSJSq06ViL7pnPu47/snioj2XevfXa1WT1i8eLH2Sd2hrotdsEz8/2rW77P09vbOWrJkyXL9Y3t7u/b7fBE5UNkws76R+2QYhr9IVTa+718uIscy86SYyUdilwFYQBpetcOzwpaetW0h9tMkOzs7d6hUKk8NpeVxeM4ker0tCFhrv6rfCUQ02zmXttZv7I7nea9i5oVEdLpz7n9Tn+VfYubbReRCrR9bUC53zn09dY0Qke6/9N/jC4XCH6rV6iYuWPq9RkSfJqIuItK2phDR/cx8jDFmQrVa/RIR7SMiK40xZwdB8P2kc77vz46i6GJmPoyIJuv3oYh8W0Q+mYgpCJBtsbJwzzQBCBCshyEjsKVNkbX2HUSklo93Oue+a61VEXKmfvgaY24RkV1FRD/oq2vXru1cuXLlc6kPdP0iGK8bcmZer4KEiPaqVqsdixcvLquJe82aNY8Q0SQiOoOZ9QNZBcZriagj2Qh1dnaO6enpuY+ZVYScS0QqdPTvn9IvAufcK+J71vxnieg2IrpTRG5l5rcT0YeI6CYR2YmZP8PMU0REvyh+6ZzT8akA2SQGpFQq7ZOehEKhME5EfkBE/0zc0ay1+xKRvnH7o741FpFeZn4fER0lIm9MRIi1Vr+otN9XGmNuFpE2ETmZiGYS0d/ggjVky32b3mhLz1ofYl/Xpa7pU+P1vo6I/qBukc657mQwe+yxx4T169efo88oEe0Si/PbmPnMIAhWJtfNmjVrbGtr60Ui8jZm3klEyiLy2TAMryuVSq82xuhzs3ET1tvbO7tQKBzMzOoSMp+ZixqbpWs8CIJr0jCtteepr3yhUPAXLVoUWmt3jV8Y6LO8Xeyj/zXn3Gfje2zTucDNhx8Ba62u5UXOOY0R7Lf4vv+oiCxzzr069V2kL9HWRFF0ORE9Y4zRz2Nd268LguDX+nlvjLlXYx5F5IJx48Yt6+3tndyPALmTiDZEUXRFoVB4iX6XiIh+P+k6/6wx5rEoijRmZJ/W1tbpDz300NP6HVapVPSZ1ZdUpzPziiiKXqPxl8z8v0EQnJ76DoML1vBbniOmxxAgI2Yqm38g/W2KfN+fFEXRq5n5y0TUUywWOzQGxPO8q3Qj4pzTDXStWGs/QER63WHOuVtTH/rPFovFmUkAe3t7+2ujKPoVEX3YOfdF3/ffKCI/qQ82t9b+iIjelAgQa+2xKiyY+c1BEKhlpFY8zzuRmb+ogsU597vEX52IrnHOqRAg3XSNGTNGLSTPPvfcc9Mef/xx3cRpn9UK83rnnIqaFwiQ+pmz1n5NN3gism8Yhovi+/+amf2enp6OZcuWrU/x0DgScc6piGFr7ZNE9HBaaKTGvhACpPmfkzx6uCUBUi/2fd8/VQWCiFwtIt81xuxARLrRn05EeyZvga21+oLgzWrdU+uarklm1o1+4Jw7ILUuf05E+zHzAhFxzKzP38eJ6ANjx4799vr1648moqtVSERR9PNp06Y9tHLlSv1dsiG6M94E3uOce0OaibX2b7opc87tVyqVJhtj1JWryswaX6ZWxkNVEMWC54w8eKKN0UMgXlP/ZuYvBEGggrzfYq3VdX6Ac26n1HdRJf4uqsVyxO3p5/LvkrUcW+2vS1yw+gpCjy0g/x47duz0xCUx/i55NxEd7ZzT+BTyff8gEfmdiLwpDMOb29raSoVCQS0n1zvn9DuvVnzf/5OITHfO6TOdvHCAABk9S7vpRgoB0nRTMnI7tJnAWB10j74RYuaP9mfyjj80a1mrROS9+jY19aF/q3NO3/LUirW2nYgeEZHzwjC8xPO8i5j5bCKakW4/caVKhInv+/qB/O5JkyZNuO+++zQ7V620tbVNLxQKjxLRxc658xPzNRG9S601qftqwKJaGtS6knzwXyIiZzrnWuK+9ZsFy/f9d4uIZuPSoPia+9j8+fNbVq5cqT7GKnY2irG4rU+qlSiKovHGGH0TrG+azw3DUH9fK/EbMXU5uxMCZOQ+X+mRNSL2N2zYwMaYJ+IN0tuSdjo6OnapVquLVSg4506LBa6uTXXl25ipJ7ZUnhFFkS2Xy4tja92fieg9zrkbkvY8z/s1EbWGYXhQygqyMftcvUuItVYF//Fjx47dKdmAxZsrFTSnBUFwlbVWLaSXRFG0Z7lcVleV5Jn7nIicWCwWdxnKrHqjY3WN7FH6vj9VRPRz/DLnnH5n9Fustd9WQe6cGxt/Hqs78N1BEGhSlY3FWqvWRN38q3uwfj/pdQMRIL9xzv1X3XfJWVEUTSmXy+rCqN9NKjj0mTg2CIIb++ustVafRf2+0u8hgQvWyF7Hw2F0ECDDYZZGSB9Tm6I3MLN+wNdKFEU/YOZ1zrm90i4T7e3ts6IoWsDMrxUR9X9VtwwtwszvT1wz4jdFNznnjknajOM9wiStobX2K0T0vmKxOC6dYcv3/cNF5JeJANFNEjPrG191L9lYYhGgmbm+4Zx7f/LhzcyvCYLg98mF1lr141VLg8at1Eoy7iTtbr0LVnKd53kdzPwXIvpBuv7s2bN3LhaLukFMXFbqV4R+mXnVanWKMUZdtE50zqkP88ZirdW3cY9AgIyQh2kLw2hE7Ftr1a3wdnUhTPuRx2v3TmY29Ruq9O2TeBJjzCHd3d0LrbULVKhr2tK0W1a6zkAESOJjn+6XtVYz5V1UKBRmLFq06Alr7e/UFcw515lu3/M8TZv6myiKDi+Xy5rlDgUEBkSgs7NzYqVSeUYt7fUvfOobsNbqd8c859zO8fOicRvfS9xtU5/t32fmw51z6gLciAC50TmnVvk+v0v0lynrSVrMa0ziKWq9jOMQkybUWq7foxEEyICWAy4aRAIQIIMIF01vSmAzb2Xfqm4fIvKhMAxVKFDsa65+rBM0piGKovsLhYJmxtlXRL6W9g2PBcgmH9R9CBDdkJ9QL0Csta+LA7RrH97WWnXb2qtegMQxJJoJRX3LP7g5AcLMt6WzmwxEgEybNm3c+PHj7xERWbdu3X6J+5aySAmQG9SHt691Va1Wg5aWlnlRFKnPcF8CRAPpN3HNwvocuQQaEfvWWo1d0je5fRUVvY855zQJhG6cdEOjbk3q8/4SIkrOstGXAjUxbq3VlKUnTZo0aWzaiphufCACJLa4qEvVHc45jTnR+2uiiWcSIW2tVRdFGwf01vdfH6f3hWGoFkcUEBgwAWvtMiJ6wjmnCT/6LfH5SvpiR4O9a8KCiL7jnHtXupLv+z8Qkdc45zR2Y1AFiLVWxYe6Fut3wZVRFC0vFAq9cVD6ERAgA14GuHCQCUCADDJgNP8fApvzS7fWqsuGWjy8crn8TJyD/WfMfHIQBBrzUSuJi9JWCBANSlc3kZnlcnmj9SUV21E7BySOv3hPsVicmLaUxNaYJSmLigbsXtOXBWRrBEicGestKrDSQb/xsAvWWnXB+mmyEetrXbW3t9soiroTt7PkmljcqAvWH2ABGR1PZCNiPyVAPqLZe+oJVavVqro3lUqlacaYR5j56SiKNKBV/1vjkd6kwbTJs+D7vro/nTJ27NjJ/aXTHaAA0dirzzLz8ZMmTdpp7dq100REXcI+kMoopAIkMsa8Q0Re8H2mAbjd3d3/HB2zjlHmRSBedx+JomiPtGtfnajQ2Itb0y/OYgHyglg7a60+V1Odc6UhECA/JKI3FovF7bu6uvRzv1Zia+FBECB5rRK0k5UABEhWgqg/YAKbEyCpDclnNY2ttfbNRKQfpP+dCqTTtLzqS6v+tfqWX4O1k7dOm7WAeJ73FmZWM7i6bn0j9aGsKWwPTwWh69vgb8VuH5qJqlY8z/swM19ljHlld3f3n/K0gPi+/1616mwuJam1Vvv5it7e3hlLlixZnfTL9/2PakBuLNJUqOjJvGrpeGXqmpqFKXYNw0noA16xw/fCRsS+pndWy1l6I9XXyK216tLxOSLSt6hqKUyejXOY+cJEgHie9z/M/CljTEd3d7dLrlMhPHHixPEqCAYqQEql0gHqVsjMr4+iaHdmvqSnp2dKkg7bWqvuVbs756YO39lCz5uNQJxZTbNZlaMoOkRfiqX7GJ8DohYGdSHeK5XaVt1h17W0tExPYo/mzJmzXUtLy5PMfHMQBEelvrNucM7pi6y0G9XGk9D7suzXW9Pr6tas+J7n/ZSZX+Wc2z7pc0dHx+7ValUPTCwklkm4YDXbqht9/YEAGX1zvs1GPIDMPDdrBptCoTA3iqJnNXWnbqY1o00UReOISDc2+iZJ0xr+VEQWaJaogbhgxRmqdDM0nohO0xgUEdG0uPsR0dxk8x/HetylAYMichYza1D33sx8sfrJp7KY1NLwMvOh9TEgjVhANO4jTsl4nzFGT9fdpDDzSvV1b29vV/cqTcOrFg4d/xpjzBEiomNZEASBZj1RC9EV+jsR+UKhUPhJtVpt18B+InoRYkC22dIf8hs3IvbjJAUaY6TCtZZONC6aVU0Fh1rebrXW6vrUFNDzwjDUQ9ootq49pJ6CInJ4GIa3lEqlA+NYpLOdc3qeTq3EIrpDA3GT+A4ROSFxkepvQ6TuMCLyY2ZW98t/hmGoWetqxfM8TTN6eb0lslQqHcbMh1QqlfPTWeOGfCJww2FLwPf9g0VEXZk0I5ZmiLtfT0JnZs3uptmxeowxh6dFtn4XiUiXihBm1kQgz8Sf168yxhyqMVLxs7CCmXv1O00NjMVi8V/9pOFtOAbEWqsJI65Qd11m1u+APeL+atbIk/TlXRRFPzbGqPvxtZr2OjkJ3Vqr37nLYSkftst2WHUcAmRYTdfw7uyWBEipVOqMT5/VzB9H+L6vrh2XMvMsEVnOzFdo4LmmImRmfZP0kyAIjrbW6gGA+kFde5ukJY4B0cwgFwRBoOJBf6cHHf6fpk3UVLki8v1CoXBjvLF/b5J1atasWS9qbW29TNMaxgF8ehDVd6IourD+EKc+XLCWiMhtYRiekNp4na+iqS4L1jH6/6lsWv1N7oVJxiFr7X4iotm8tP+t8RklVyYnSWsDupns7e1VEfJOZp4Qf2l+xBijZyk8jS+W4f0MDbT3W3rWrLUbxX58lkZi3fheFEVX61k0ulkRkdpGPgiCP8Yi+B4i+o2IqLDQs27OZuZfiIj+q3FWnwqCYGmcnlTT4aoYVoGimx2NHfmguk91dHRo0gQ9Y0c3RXpOjiZfOLR+Q6Tj9X3/03qeiLqwxAd41tKPxn/TwzZVDOlhax83xugba01JrVm6/qSfI3rdnDlzZrS0tKj71iXOOT0rBwUEtkhAM2JFUfQJTYQSp6TWGA99KfXDMWPGfC7t4hQLC/37jXq4rbolapIqEXnMGHNROkOV53nH6fcZM+sLsbONMT+uVqtL0t9XfX2vxc/1xu8SvWcchK7uwTU34viFwmeI6K1EpGdK3U1EHzPGrBcRtVzqeVr6/aCH5G6ShleTqDDzo0EQzN8iHFwAAhkJQIBkBIjqIAACINBsBLYkQOrFfryZ1xTQai3bjYj07ezdGutRLpfVIlgr8Tk8uiHbRUSC+O+/jJM3aDatq5xzC2LLyCVEpMJBz0jQzdWldZswPTFaM/z0RFH0OmOMX78h0nvGwkcFip6vs3M6QUO8AdN0wRrjpelK1e1ED5G7vqen57LE+pHapGkabd0YooBA7gT6ssbnfpNBbFBTaIvIOWkr4yDeDk2PcgIQIKN8AWD4IAACIDAaCMTuWr3xCemjYcgY4xATGO4CxPf9M0RkLKyEQ7xwRuntIEBG6cRj2CAAAiAwmgiolSaKosvL5bImskABgdwJDHcBYq19v7pU9nd+T+7A0OCoJgABMqqnH4MHARAAgZFPoFQqtRYKhY8GQfCpkT9ajHBbEegrbmNb9QX3BYFmJwAB0uwzhP6BAAiAAAiAAAiAAAiAwAgiAAEygiYTQwEBEAABEAABEAABEACBZicAAdLsM4T+gQAIgAAIgAAIgAAIgMAIIgABMoImE0MBARAAgS0R8H1/oYjM0AMBt3TtcPu7tfYQIrqFiGqnQg+3/o+W/pZKpcnGmG8Rkc5Xj3Nuu4GOXQ+m1LTOyZlGI209l0qlVxtjbmv2NWytvS4+l8cMdO42d521Vk+WnzoSP5fy4DMS24AAGYmzijGBAAiAQD8EPM+7jZlnjsQv+liA/DY5lA2LoDkJWGv1RG49FPaCKIp+Wy6X9bC8ARU9LI+IliYCJK/17Hnef+vp4c652QPqSOoia+3nmXliEATvbbRu/fWxAPl9s69ha+21sQApZB2z1rfW3qGHJI7Ez6U8+IzENiBARuKsYkwgAAIg0CQCZP78+S0LFy7Ugw0HvcACMuiIc7lBclBmoVCYs2jRokcbaXSwBIjv+58TkTdszQbYWvtXZr4/RwEyHCwgECCNLFxc+wICECBYFCAAAiAwigj09ca4vb39ZSJyvrbi4FEAABgSSURBVIgcSESGmR+MouiTYRj+Io0mPgn9ZCLSU8vXEtFfiWiBc05PKq+VeIN4l4jcxcwXEdG1zrnTfN9/NIqiO5j5aiK6kpk7ReRJIvqqc+7y1H3YWnsaEZ1AROomtpqIfh3fZ0VyXalUajPGXM3M2nfty/dE5DfM/LNmd18ZRcvtBUON19+riUiISPcg4pwrxK5Vy51zr0pV0t9XmPm6ZHO/NQJkzpw527W0tFxMREcQ0S5E9DQR3UpEZzrnVqT6VLt16n7GWvsJtUYQ0Swi+hcR/ZmZzwiCIIjXe5QeS2K56OzsHFOpVM4noncQ0TQieoqIftzb23vOkiVLdE33WfpywZo7d+7269ev1/s+x8yvZOZ5URT9Poqiw5l5X2Y+kYi2J6KHiegj6eexvb19lp5/E7u7TSaix/VZmTRp0nn33Xdfxff9m4joFUEQzEw61N7e/tooin5FRNc7545Lfu/7/sUi8rFJkyZtv2bNmq/WW0A8z+tg5kuJSOd3LBEpo6ucc99MD1YPBTXGnCIiL9E+K08RubDOAqJzfwkRvYeZtxORPxUKhZOq1er3ReTpMAwPSn3mvIeITiWiDiJaR0R61s9Zzrnu0fysNfvYIUCafYbQPxAAARDIkUC9ALHW7ktE6v7wRyL6jIj0MvP7iOgoEXljIkJi8aHi4ctE9G0RUb/9y5l5WqFQ2G3RokVPpASICgXdmJ1tjHmsu7t7WbxxXKUbE92kMPNTURSdQUSHMfOhQRDoW1/yPO+zzPxhEdFrbhGR6cysm0dZu3btHitXrnxu3rx5xTVr1jxCRJOI6AxmfkxEXk9Er403IccjBiTHRZNjUx0dHV61Wv0fItI19oYoilaVy+X74/Xx2GAIEN/3fyAiB4jI6SKytFAoTBeRC3RYzrnO9vZ2G0WRxqRMiaJI+/TPJUuWLLfW6mb6TCK60Bija3FXEflfIqquXbu2U9diqVTaxxhzr4j8XNscN27csoceeuhpa+2PiehQ3Vgzs7qY7UZElzBzOQiClw1UgKgF8YknnvgdEc1uaWnZv6ura1VKpNyqIp6Z1RqxExF9gYiecc55+vx1dnbuUKlUHo4F+gX6nBDRfkT0SRVDzrl3+r7/XhH5WhRFM8vlsooTfYmg49b5WeOca0tt9HVjv9Y59/p6F6yOjo6Z1Wr1ASJSi9ZFzPxvEflvIjqZmU8OgkA/N/T5Pp6Zv0FEN6jAURHCzKfHAkrFaC02zff9S0RkgYh83hjzUxHZK+6Tfu64VAzQqSLyWRG5WkS+a4zZgYjOI6LpRLSnCswcly+aypEABEiOMNEUCIAACDQ7gXoB4nner5nZ7+np6Vi2bNn61GZDNxO6Idgn3pScRUR7O+fellxTKpUOM8Zo/fcHQaCbisQCMqO3t3e2buJS7anvvm785oZhuCjeZPgiskh974MgON1auysRLWPmzwZBoG+ea8XzvL3UxUVEPhqG4ed933+jiPyk3tJhrf0REb2p2f3nm32NDHb/Ehes9BoZTAFirVWLw9edcx9Pxub7vq69I4rF4le6urrW9mUZ9DzvKmYuOufU6lcrsRDXzfRhzjm1oujvorSVplQqHWCM+RMRneKc+1Kq7pFE9ENmfnMQBGqpe0Gpt4DEG31d769InpvUNX9xzh2Qav8yIvpEFEV7lMvlLmutbsTPZ+a9gyB4MHWdWkROr1aryqCnpaVFA/vf5Zz7Tvxcat//KCKnMfN0PRldD/M0xvybmc8KguCqegHi+74KgHdWKhW7dOlStWwmz+5PmflA59wUFUXW2vuJaLJzrpSaiz1ERK2py2IBolZQtRg9khakvu9/VESuJKKFKkDiPumLj9+lP5c6Ojp2qVari4noarW+DvZ6RvtbRwACZOu4oRYIgAAIDEsC6Y2Wvl1duXLlGiK6Jr3JijdV+pb0zCiKxpfL5Q39bJbUDSrUN57Oudob5XgjWU1vMFK/743fztaamzVr1tgxY8Y8F9//fdbaY4hIs+sc4Jy7J31Pa62+nb3dOfcuz/P0DevZRKTZvDa+4Yzfrn4dAqS5l+Y2ECAqcsdHUfS+MAxVNKh1bpMy0GD2JM5IRN4bhqGu1RcIEM/zzmHmC6MomlIul3UjXSvTpk0bN378+GeI6Arn3IJ+nqmNWbDUJYmIzo3FjmaJqpVEgIjIuWEY6nNaK57nncjMX1QXKOfcndba3zNzW9q9Ku7vK9VNSUROCMPwWmutPsO/cc6dMnXq1PETJ05U64W6en1fhYpz7rtJcHxK3GwSA2KtLavLlVpH6p7b96sQMMZ0FAqFZZVK5Vl9xp1z+vuNRV00RUQ/N+bE7pXapwucc+rGWSuxRecfiQCx1tbGwcxvD4JA+7qxaFYtZjabszb1xR+/GzoCECBDxxp3AgEQAIFtTiC90Zo9e/bOxWJR3yAm/vjp/unvhJm9IAiWtre37xhFkW763xhvjFrji0VENF5E37bWBAgzP1H/xR8Lk8edc7ppSMomPv6+76svuL7F7atoX+4IgmC+tfYr6o5RLBbHdXV19SQX+75/uIj8EjEg23yZbbYD20CA7KmWB3VjUhclItKN+XeCIPhBvPZ18/6C7HBx/MQCZn6tiOgb/GKy5mOr3zXxmt/EAuL7/pdF5IP9rWMiutE5p3ELLygp64ZaSN4gIreEYXh4+sLkmrTlUf/u+/4JIvJVETkoDMPbrbUaA/G0c05juzaWtra2UqFQcImAifurVoq9YqvmjzQ1srX2RiL6pwoT3/fPFZGTnHMaQ6PPeb0A0diLMXFcT/249Nk91BjTXa1W9YXB5fUCzFqrbmoviQXIgcYYdQk90TmnsSYbS2wZeUgtINbat6s76GY4q0ufxu6gNCEBCJAmnBR0CQRAAAQGi0A/AuQGdYPq657VajVQC0jsOqFBnmp9uF39wzVvv274ReSStAAhonpf/sQyslkf/1iAXCoibzXG6BvVTYoxZt2iRYtCa61uSk6oFyDW2tcR0c0QIIO1evJpd6ACJLbQ9WQNQo97XWhvbz+0Wq1q4LaKaBUj+tb/v/Tv9QJkjz32mLB+/XrdwE9QK0QURfcXCgV9e7+vxkxonFQQBJsTIB+IoujlhUJBLXz163h1f9m/UgJErTS/ISIV1ceEYagxKrWSEiAb+6C/70OAqKvjv+sFSByHowHiZzvnLvM87y0qyKIo2rFQKHxC42Wcc4daa9X17APOuT2ttZre+knnnFop+xMgdxpjThORvvaW6oI5SUTUktmXANFEFi9WAaJJMaIoUovPB51zX0vDs9aqe1dXnQD5SPyZtAnnarVaVVe0fFYtWsmbAARI3kTRHgiAAAg0MYG6jZZaIFRI/FQDUvvrdkdHx+7VavVBEbkiDEMNHK8Va+0r1C0qLwHied67mPkGY8zruru7dfPVZ4mDZM9IB87qhSkXFAShN/Ea7EeAqM/+39Ob5ba2tumFQuHRnATIJkSsteoyeG6SAKGP2KgjNKNaOoA63uS/W0Su35wAsdaqe9XFzLxbki1roNOREiCaXe5ya60GoO9TrVb3XLx4sQaRNyJA9FDOduecBmRvLO3t7fM1i1Yi1GPXJt3YqzDTvt+irk9x7NW91Wp1aqFQ0Pk5OUnuUG8B8TzPMbNaSzaxtqTvG8dsqCDTzHga5L6xWGvVErtOBYi1tl3jP+LMdxsz5MUHWGoGsz+oAEmEioh8KAxDtYqiDCMCECDDaLLQVRAAARDISqCPLFiaavcVvb29M9LpQTXgk4g2aPaaUqm0tzHmPmY+TQNQkz5Ya/WtrLpB6BtNdc/qz9IxIAtIHDyqgevfds4dm9wnjhX5QhRFX9aMSfEb2+/Xu6BYa3Us6q4CAZJ1oQxi/X4EiAYnqwuOpqytFd/3PyQiX8wiQKy1mlVpQbVavTDZwMeb+NqaFpGjwjD8UX28hLX2zbHb1n875zThgRZNy6uZoDSLlboH1d7OaxC6ZnVK3KrizHJ/Tgtzva6zs3NKpVK5WNPilstl3dC/oPQRhK5xIA9pamx1P4z7XosTSYugmNcmLliJRZGZ9w+C4N7Uc6vWzlOr1ershIm1VmOuNBveScaYw7u7uxfG432amb8gImcVCoVpqWx39S5YGnvywWq12r548eKN1kvf94+Oomh2GIaaUldfEjxkjJmcjktJeCVB6LHlS4XGHc45tWrWirX2FCL6fBIDEqc6VuHysHNOU/8mRYPYPxe/WKklCkBpPgIQIM03J+gRCIAACAwagXoB0t7ermcK6MajW33C1bXKGHNEnAFnQRAEn44FgKbXVGvJR0SkYoz5oIjoRkOFygOa17+7u/u+frIZDUiAxJuoK/TeRKQbz++qW4amT9X9W7Va3Vc3N3F/HBGNJyLN1PO4iOh5C5pidC4EyKAtn1wa7keA1JIeMPOVIvIzTbvKzJpxrZOZf7K154DEQdVLiGglEX0qiiK1qLyYmTXL2qze3t65Krz1PAwR0fudrKl6jTFd8frWcyo0GcM4Ivqf2NVHnxNNDbtAM1NZa1cwsx62+T/Pe/2UH/A8TwWyZr262BjzuyiKNAOcBqdv19rauqem6h2IAIk33kmsQ80qsgUXrK+JyHyNAYnPP/mbZrpiZnUjWxWfI6L91/N3Ppz0wfO8TzGznuQ+KYqi7ZLEE77v/0ZE9o6tU7unxMAmAiS2VmkmKw1g/wQzq0VF4700NmxjkovYrUtPjteMW5o5b2oURbX4MWZuSaXh1TiaD8QpuzXd8F6aZStOr9udpOGNRYmKje9FUXR1oVDQeTpJRDS99yFBEGgsCUoTEoAAacJJQZdAAARAYLAIxAJEs0el8/vvJyIa26EpPTW4XP3Dr0yfpeH7/stFRL/o1T3i78z8lSAIPhXn69dDwP7mnHtFLED0QLn0G8lEgNT/Xl3AekTkujAM9eDBWonTbWqWHH17vY6Zf1+tVs8rl8vqllErpVJpN2PM/2nGLCJ6VkS+XygUbozF1HvrDz8bLJ5ot3ECfQkQ3/d146tpbzWLkh5it5CZdSN5PzP/sk6ALHHOHaJ37ms91/cozqqkb+B1Teo5EZqZ6o5CoXC+xhTF62lvFbzMPIOZbw6C4Cjf998Un0czS0SWM/MVGvdhrf0mMx9FRCqMjvY87zj9m2ba0rgKtRLGZ9WcQ0RHx5tmTQX8C13HaUtMH31V64a6R21ixfM870a9ZxRF6uI0Wa9JB8LHz80mFpB4XNOMMZ8motfE5+YsFZFrwjD8TBKAH3N8DTPrgZ9/SieKiIPPL9DzOMIw/FjS39gF6xjnXEvyOz1PRXmpACKiiXFK7auDINDPDU1qkTzfGtCuQfo7EpHGqagYVOvGHokAiTOGqbVDzxJh/Qwwxny4Wq1qrIieA1Kb/3jc6hanL0L0rBUVgndHUXR+uVy+q/HViRpDRQACZKhI4z4gAAIgAAIgAAIgAAJbTSA+0+U255xal1CGMQEIkGE8eeg6CIAACIAACIAACIw0Ar7vq1V1z8TypeNLHfB4oXPuwpE25tE2HgiQ0TbjGC8IgAAIgAAIgAAINDEBz/M+yMx6ivy1mnXMGLOzBvVrooIoiuaWy2VN54syjAlAgAzjyUPXQQAEQAAEQAAEQGAkErDWahyYxoZovFpF41Pi1Lx/G4njHW1jggAZbTOO8YIACIAACIAACIAACIDANiQAAbIN4ePWIAACIAACIAACIAACIDDaCECAjLYZx3hBAARAAARAAARAAARAYBsSgADZhvBxaxAAARDIm0B82vJ98cnMZ9YfPJj3/YZje/HZJQt6e3tnjRkzpiOKoptF5MgwDPUkdRQQAAEQAIFBJgABMsiA0TwIgAAIDCEB4/u+HmI2JggCPYW42tHR4VUqlTHlcrlrCPvR1Lfyff9iPcW6t7d39pIlS5b7vv9pEXkfM+8eBIGemI0CAiAAAiAwiAQgQAYRLpoGARAAgaEk4Pt+7SRkPR3cOXfPUN57c/eaP39+y8KFC/WE4qYo9QIkPnX5USL6pXPuuKboJDoBAiAAAiOYAATICJ5cDA0EQGBUEShYax0zl4MgeG0yct/3F4rIDOfcHP2dtfabRHQ4ER0oIt8wxuwnIk8R0fmTJk361po1az5LRG+P6/+4WCye0tXV1RPXjYjoS8x8u4joQWCziUjz8V/unPt6ck9rrV53uYgUmPkkETk7DMPPE5HxPG8BMx9DRDOJ6Fkiuj2KorPL5fIjpVKpzRgTar7/MAzPS8+etfZYIrpORF4bhuEtc+bM2a6lpeVSInqjng1ARCuY+aZqtXpJuVzekBr/4SLyaR26XiMiVxljXpK2gMRjW0BEF1Sr1d0WL15cHlUrB4MFARAAgSEmAAEyxMBxOxAAARAYDALW2kOI6BZmPjYIghuTe9THgFhrr4037X8TkRsKhcLSKIouUqsJEf1QRFYR0Y+Z+SAVJSJyUhiGV6cEyMNEtCaKosuJ6BljzLlEdDAzvy4Igl8n16lIiaJotYhcVigUlqtrk7VWrTNqYbgkiqI/MPOLmfl8Itq1WCx2dnV1rbLW3isirWEYzk1z8n3/ZyKyr3NuqgoZa+3dRDSDiPT+jxDR/iogYitGTUD5vu+LiJ4Z8Nf4EDNRQUREs4ioPXHB0mvnzJkzo6WlZRkRXeyc0z6hgAAIgAAIDBIBCJBBAotmQQAEQGAoCVhrLyOiT+im3Dm3YgsC5Fhmfk8iVHzfP0hEbmXmW+qsJ+qWdE8QBEelBEilWCzOVLGgvyuVSpONMU8S0e+cc29IXfdsT0/PTsuWLVuvv+vo6JhZrVaXENHnnHOnJf2z1rargGDmS4MgOMfzvNOZ+fJqteonlojOzs6JlUrlKRH5ShiGH7XWvoOIbiKiNzjnfplq62NE9Blm3jsIggettVcS0amFQmHOokWLdCza31ZjzFIi2jktQPRvnuepBemfzrkDh3LucC8QAAEQGG0EIEBG24xjvCAAAiOSgLVWN+Ivdc6pO9LG0o8F5NhKpTJ16dKlKhyora2tVCgUnIicEYbhFakN/Z1EtN45d2giLJj57iAIXpa+h7X2D0Q0PeXmpS5Yv0/qxXXVhepaZj40CILb6uovVlcu59yrY6GyNN0Xz/Peycw3isjLwjD8s7VW3b3e4ZybmG5HA+6r1WpARCc6575qrb2diHZxznl191M3tHfXCxBr7XeI6Ejn3NgRuUgwKBAAARBoEgIQIE0yEegGCIAACGQhYK3VoPMJzrndBiJAnHNFIlKhkFgn1CpwvHNON+e1EosXcc4dnAgQIvqec04tEGmR831mPtw5Nyl13Xecc+9KiZkzieiTzLxbEAQqEjYWa60KnZ0ToWCtvUv/mFgirLU/JKK9nHNtcfu/IqKNcS513ERdvNSNylobqEWjD8Gk7mOn9yFA/o+IPhRF0fblcvmZLPOBuiAAAiAAAv0TgADB6gABEACBEUCgP/eh/iwg/QiQ45xz129BgGwiLPRa3/d/ICKvcc5tlxIgNzrn1OpRK77vnyEil/YjQP5IRC92zvnxtaeKyP8WCoXpq1evXj1x4sS/M/NV6qKVEiAHGGNeJSIv+B4zxjy1aNGiJ5SJMeYf9QIkTrv78XoBEp8Pcla1Wp21ePHix0bAssAQQAAEQKApCUCANOW0oFMgAAIg0BgBDd4movEZLSADESALE4tI0sPY1Wmqc660GQFytIiouDnMOXdrenTWWg3+XpK06/v+VBF5TEROJqKnmPl7URTtkZxlEgezv7enp2diEmPSFy3f9/8kIi9J+pXq73eJ6ChYQBpbY7gaBEAABPIiAAGSF0m0AwIgAALbkIC1Vt2S5g00BmRrLSDMvK6lpWV6V1fXv3S4cTrcJ5n55rpg9U0sINbaXYlIhcZXnHOnJKja29vnRlGkmarOcc5pWt1aieNK/iUizzLzXOfcnsnffN9/q4h8l5nfFwTBNak6es37NKtXuVx+ylr7BSI6KYoiWy6XNc6Epk6dOn7ixInajx0RA7INFyxuDQIgMKoJQICM6unH4EEABEYKgUazYG2tABGRLhUhzPxJTcMrIpoG91XGmEO7u7sXxuJBY0s2ESD6e9/3PyciHxIRTfurAeLTmPlcZh6/YcOGPZctW/bvlJjQdLma2UvP9LjSOadxG0nRM0/uZOY9NFjdGHO/Zs0yxlwgIk875+bpKfDWWhUk9zLzg1EUaUphNsacTkSTiWhuP1mw/uWc05TEKCAAAiAAAoNE4P8BSig9iusrKQIAAAAASUVORK5CYII=\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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": {
      "text/html": [
       "<img 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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def normalize_by_optimal(d):\n",
    "    return {k: np.divide(v, d[opt]) for (k, v) in dict.iteritems(d)}\n",
    "\n",
    "'''\n",
    "opt, best_ml, ... provide shorthand for the full name of these algorithms\n",
    "'''\n",
    "\n",
    "opt = 'Optimal, \\n full state knowledge'\n",
    "best_ml = 'Reactive,\\n learned \\n (improved)'\n",
    "naive_ml = 'Reactive,\\n learned \\n (simple)'\n",
    "hand_designed = 'Reactive,\\n hand-designed'\n",
    "randomized = 'Randomized'\n",
    "\n",
    "# J_max and J_min data optianed from MATLAB\n",
    "\n",
    "J_max = dict()\n",
    "J_max[opt] = [0.30849, 0.33055, 0.29739, 0.27013, 0.28509, 0.32797, 0.29082, 0.29635, 0.28968, 0.27174, 0.25783, 0.25974, 0.25449, 0.33618, 0.27354, 0.30538, 0.26728, 0.31295, 0.26009, 0.29585, ]\n",
    "J_max[best_ml] = [0.38918, 0.52431, 0.37626, 0.33761, 0.36627, 0.4121, 0.41105, 0.43362, 0.42124, 0.41577, 0.35259, 0.3119, 0.3405, 0.46662, 0.34855, 0.37407, 0.43151, 0.42422, 0.34608, 0.39384, ]\n",
    "J_max[naive_ml] = [0.48525, 0.56434, 0.47486, 0.42704, 0.48771, 0.47742, 0.4522, 0.57487, 0.48552, 0.4158, 0.38666, 0.43664, 0.42592, 0.4906, 0.43679, 0.41704, 0.38977, 0.53715, 0.41171, 0.47002, ]\n",
    "J_max[hand_designed] = [0.46821, 0.57251, 0.6398, 0.51179, 0.52219, 0.58051, 0.5726, 0.7182, 0.65291, 0.84841, 0.89547, 0.73193, 0.73582, 0.6111, 0.63856, 0.48259, 0.85066, 0.55229, 0.58293, 0.53825,  ]\n",
    "J_max[randomized] = [0.86631, 0.87509, 0.86944, 0.90191, 0.79784, 0.93097, 0.8577, 0.88791, 0.89405, 0.90922, 0.72233, 0.76951, 0.8249, 0.95679, 0.73112, 0.69088, 0.88714, 0.89781, 0.77605, 0.85871, ]\n",
    "\n",
    "J_max_norm = normalize_by_optimal(J_max)\n",
    "\n",
    "J_mean = dict()\n",
    "J_mean[opt] = [0.048015, 0.045439, 0.053838, 0.053029, 0.050003, 0.054249, 0.057654, 0.048237, 0.057099, 0.064338, 0.050653, 0.048447, 0.054243, 0.060876, 0.047659, 0.041983, 0.056871, 0.05655, 0.053815, 0.055249, ]\n",
    "J_mean[best_ml] = [0.08245, 0.063708, 0.085025, 0.077708, 0.068393, 0.07671, 0.094097, 0.075124, 0.08123, 0.10635, 0.074664, 0.069793, 0.083935, 0.11073, 0.069267, 0.055399, 0.093638, 0.084665, 0.081371, 0.083421, ]\n",
    "J_mean[naive_ml] = [0.10266, 0.096672, 0.12342, 0.11544, 0.11177, 0.11999, 0.12877, 0.10344, 0.12319, 0.13033, 0.11947, 0.1095, 0.10993, 0.12446, 0.11028, 0.086372, 0.1186, 0.13237, 0.11498, 0.11814, ]\n",
    "J_mean[hand_designed] = [0.14219, 0.18054, 0.42077, 0.25486, 0.25654, 0.29392, 0.29536, 0.40678, 0.37611 ,0.6335, 0.68867, 0.52136, 0.52637, 0.28425, 0.36832, 0.20528, 0.63878, 0.26501, 0.33202, 0.25315, ]\n",
    "J_mean[randomized] = [0.46067, 0.44715, 0.48969, 0.48641, 0.46268, 0.49984 ,0.53552, 0.46658 ,0.532 ,0.59298, 0.46891 ,0.43533, 0.50874, 0.58613, 0.43509, 0.35328, 0.52241 ,0.53825, 0.50742, 0.50572, ]\n",
    "\n",
    "J_mean_norm = normalize_by_optimal(J_mean)\n",
    "\n",
    "def plot_performance(d, controllers, ylabel = ''):\n",
    "    df = pd.DataFrame(d)\n",
    "\n",
    "    df_sub = df[controllers] # specifying the order in which we want the columns\n",
    "\n",
    "    plt.rcParams['figure.figsize'] = (10, 8) # hardcoding for figure sizes\n",
    "    \n",
    "    fig, ax = plt.subplots()\n",
    "\n",
    "    ax = sns.violinplot(data=df_sub)\n",
    "    ax.set_xlabel('Controller used')\n",
    "    ax.set_ylabel(ylabel)\n",
    "    \n",
    "    ymax = np.max(pd.DataFrame.max(df_sub))*1.2 # ugh, I really don't like this hardcoding here\n",
    "    ax.set_ylim([0,ymax])\n",
    "\n",
    "    fig.suptitle(\n",
    "        \"Comparison of performance of controllers\",\n",
    "    )\n",
    "    \n",
    "    plt.savefig('cache/'+','.join(controllers) + '.pdf', dpi=600, facecolor='w', edgecolor='w',\n",
    "        orientation='portrait', papertype=None, format='pdf',\n",
    "        transparent=False, bbox_inches=None, pad_inches=0,\n",
    "        frameon=None) # hardcoding to get export as nice pdf\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "plot_performance(\n",
    "    J_max, \n",
    "    controllers = [randomized, best_ml, opt, ], \n",
    "    ylabel = 'Maximum cost-to-go for controllers',\n",
    ")\n",
    "    \n",
    "plot_performance(\n",
    "    J_max, \n",
    "    controllers = [randomized, hand_designed, naive_ml, best_ml, opt, ], \n",
    "    ylabel = 'Maximum cost-to-go for controllers',\n",
    ")\n",
    "plot_performance(\n",
    "    J_max_norm, \n",
    "    controllers = [randomized, hand_designed, naive_ml, best_ml, ], \n",
    "    ylabel = 'Ratio of maximum cost-to-go for controller to optimal maximum cost-to-go',\n",
    ")\n",
    "# plot_performance(J_mean_norm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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