WFS Noise.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy\n",
    "%matplotlib nbagg\n",
    "from matplotlib import pyplot\n",
    "MPL_COLOURS = [\"b\", \"r\", \"g\", \"c\", \"y\", \"k\", \"m\", \"#D35400\", \"#117A65\", \"#A569BD\"]\n",
    "from tqdm import tnrange\n",
    "import pandas\n",
    "from astropy.io import fits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import soapy\n",
    "import aotools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "CONFIGFILE = \"conf/simulation/sh6x6.yaml\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "GS_MAGS = numpy.linspace(10, 25, 10)\n",
    "E_READ_NOISE = numpy.linspace(0, 100, 10)\n",
    "\n",
    "RUNS = 4\n",
    "TEL_DIAM = 7.9\n",
    "R0 = 0.20\n",
    "WAVELENGTH = 500e-9\n",
    "CENT_THRESHOLD = 0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10, 10, 4)\n",
      "(10,)\n"
     ]
    },
    {
     "data": {
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       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
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       "    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",
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       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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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qxQApjhVPREgQIAAAQIECBAgQIBAoQQEgIUaR27FCABzo6/8xgLAyh8BAAQIECBAgAABAgQIECDQagEBYKuFy7G+ALAcc0qxSgFgilPVEwECBAgQIECAAAECBAgUSkAAWKhx5FaMADA3+spvLACs/BEAQIAAAQIECBAgQIAAAQKtFhAAtlq4HOsLAMsxpxSrFACmOFU9ESBAgAABAgQIECBAgEChBASAhRpHbsUIAHOjr/zGAsDKHwEABAgQIECAAAECBAgQINBqAQFgq4XLsb4AsBxzSrFKAWCKU9UTAQIECBAgQIAAAQIECBRKQABYqHHkVowAMDf6ym8sAKz8EQBAgAABAgQIECBAgAABAq0WEAC2Wrgc6wsAyzGnFKsUAKY4VT0RIECAAAECBAgQIECAQKEEBICFGkduxQgAc6Ov/MYCwMofAQAECBAgQIAAAQIECBAg0GoBAWCrhcuxvgCwHHNKsUoBYIpT1RMBAgQIECBAgAABAgQIFEpAAFioceRWjAAwN/rKbywArPwRAECAAAECBAgQIECAAAECrRYQALZauBzrCwDLMacUqxQApjhVPREgQIAAAQIECBAgQIBAoQQEgIUaR27FCABzo6/8xgLAyh8BAAQIECBAgAABAgQIECDQagEBYKuFy7G+ALAcc0qxSgFgilPVEwECBAgQIECAAAECBAgUSkAAWKhx5FaMADA3+spvLACs/BEAQIAAAQIECBAgQIAAAQKtFhAAtlq4HOsLAMsxpxSrFACmOFU9ESBAgAABAgQIECBAgEChBASAhRpHbsUIAHOjr/zGpQoAn529IF70+b93G9rP33FgrD9qeLS3RbS3t0V7W/a/WPLXtvpfO9qX/3nZ79vq12W/W/HaFX9f+dMBgAABAgQIECBAgAABAgSaIiAAbApj6RcRAJZ+hKVtoPQBYKvkl4WHWZi4LCzMwsGOZcHiCmFj9vvs541r25cGkMuCxaW/WyGEXOH3y8LK1QeWy8LMtuhYad0Vw86l4efya5f9uXv4uepaK/bWc4i6fN0V98iunbugMz7zhzu6jeDrr9s7xq87PEYM7YjhQ9pj+JClf13y90Ozv2+PYR3tS0w9CBAgQIAAAQIECBAgUBUBAWBVJr3mPv2bsHOQl4AAMC/5iu/bCAWzkHBJMNgRI+p/XRocrvSzenjYLVjs6WdL1lsWOi4PIJf9LFtX+Fjxw6d9AgQIECBAgAABAjkICABzQC/glgLAAg6lIiWVKgCcPmt+7HfmJRUZjTZbJTAse0XiCkHh6sLGVULJodl9y17JWH+FYw8/W11Imb3yMXsVpQcBAgQIECBAgAABAtUTEABWb+Y9dezfCJ2DvARKFQA+M2t+7L9SAJjlKV21vPjsS6BvAlkIuCRwXPYW6RVe9djtFZBDO+oh5QqvYmy8SnLFVzkuf6v1/EWd8fYf3ditoJvOOCbGjR7etyJdTYAAAQIECBAgQIBA0wUEgE0nLeWCAsBSji2JoksVAPb0JSDLAo6urlp01bL/ZYFgLWr1v3Zmf+5a+rNlv6/VapH9fMm1XcuvXfGaJX+u35ettfT67Nrl92X3d1tr2e9X2m/FfbM/dzbWXV7vslpWvjb7eeeSGrtfu/Tvl6617M8r9p7d09Naq3Vacv2qa63ssKLRwsVdcccTL3T7P4SN1x0ei7pqkYVR2f+Es/n+/4nN1hsR2280OrYZNyq2GT8qth0/csmft9xgZAzNPlTSgwABAgQIECBAgACBQREQAA4Kc+E3EQAWfkTJFliqADDZKZS0sTUFsstaWtzZFQsWL/1fFggu/XNnLFjU88/mr/C7JdeteN+Se1b6WbbesnUb6y+9blGnl4au7mhlXw6zxfrrLAkDtx0/KrYZN7IeEI6KzceuE0OEgyX9v0plEyBAgAABAgQIFFVAAFjUyQxuXQLAwfW223IBAaDTkKxAFj4uzALIetiYhYLzVwgRs593CyXrYeL8JX9dHjYuv2952Lj8vhUDzeXBZrZvWR9DO9piy/WXBoJLA8Llf95s7DqRhYceBAgQIECAAAECBAj0TUAA2DevVK/2b1OpTrb4fQkAiz8jFZZQIHurdRYCNoLCeqDYLYCsv9px5Vc9Nq5ZQ3C5Spi5uCvmLeyM2QsWt1Qr+wzDrbJXC64QDG5bf3vxJmNG+JKTlupbnAABAgQIECBAoMwCAsAyT695tQsAm2dppb4JCAD75uVqAoUV6Okt2V945R4xffbCeGj6nHjw2TlL/vrc3EUt6SH7cpMsGNx63MilbytuvIJwVGw8Zni0tflHXUvgLUqAAAECBAgQIFAKAQFgKcbU8iL9W1HLiW2wGgEBoKNBoGICM+cuaoSBD06fEw/Vg8Hszy/Mb80rCNcZ2tEtGFz2qsFtxo+MDUcLByt2BLVLgAABAgQIEKikgACwkmNfpWkBoHOQl4AAMC95+xIomED2bdLZqwOXhILLgsFn5y798/Q5MatFby8ePXzIknBwybcUr/RtxRuMGuaVgwU7J8ohQIAAAQIECBDon4AAsH9uqd0lAExtouXpRwBYnlmplEBuAlk4+Oyc+luJG68anLs0LHx2Tsxd2NmS2tYdMaT+LcVL31K85AtJ6t9cPHbksJbsaVECBAgQIECAAAECrRAQALZCtXxrCgDLN7NUKhYApjJJfRDISSALB5+ZtaARBj44vf6qweytxc/OWfLNy614jB05tBEGZqFg9nbiZZ89OGbE0FZsaU0CBAgQIECAAAEC/RYQAPabLqkbBYBJjbNUzQgASzUuxRIol0D2bchPzZpff1vx3CWB4LK3GD88Y24sXNyacHDcqGErfAnJ0rcXLw0JR0X2lmMPAgQIECBAgAABAoMtIAAcbPFi7icALOZcqlCVALAKU9YjgQIKZOHg4zPnxUPT5za+lGTZtxVPmzE3FnXWWlL1+NHDG28lXvq24mXh4MgYOUw42BJ0ixIgQIAAAQIECIQA0CHIBASAzkFeAgLAvOTtS4DAagUWd3bF48/P7/ZtxQ8veUvx3MjCwcVdrQkHNx4zfPnbiuvBYBYQZl9SMmJoh4kRIECAAAECBAgQ6LeAALDfdEndKABMapylakYAWKpxKZYAgUWdXfHYc/NWetXg0s8dfPS5udGKbLCtLWLTMSOWvpV4pW8r3nKDkTF8iHDQySRAgAABAgQIEFizgADQCckEBIDOQV4CAsC85O1LgEDTBbLPFJz23NIwcNk3FC95i/H0OUveblxrwQsH29siNhu7To/fVjxyWEccdNbkbn3edMYxMW708Kb3bkECBAgQIECAAIFiCwgAiz2fwapOADhY0vZZWUAA6EwQIFAJgfmLOpe8fXhZMLjitxU/MXN+Sww62tqic6XUUQDYEmqLEiBAgAABAgQKLyAALPyIBqVAAeCgMNukBwEBoGNBgEDlBeYt7IyHZ8ypv3Kw/grC7DMHp8+Jp2ctaKrP+f+2Txy/52ZNXdNiBAgQIECAAAECxRcQABZ/RoNRoQBwMJTt0ZOAANC5IECAwBoE5ixYHA8tCQPnLvlr9grC7AtJslcQTp/dv3DwpH02j/88fldvBXbyCBAgQIAAAQIVEhAAVmjYa2hVAOgc5CUgAMxL3r4ECJReYNb8RfHws/W3FWefO1h/1WD2bcUz5ixcY3/rjxwaZxy/W5y07+bRln3LiAcBAgQIECBAgEDSAgLApMfb6+Y88+81lQubLCAAbDKo5QgQIJAJzJy3KG6Z9ly86fs3rBHksB3Hx5knToitxo0ER4AAAQIECBAgkLCAADDh4fahNQFgH7Bc2lQBAWBTOS1GgACBVQW6umrx8xumxVl/vjNmzV+8ygUjhrbHh47ZKd5+6LYxpKMdIQECBAgQIECAQIICAsAEh9qPlgSA/UBzS1MEBIBNYbQIAQIE1i7w9Avz49O/vz3+NPXJHi/ebdMxcfarJsSeW4xd+2KuIECAAAECBAgQKJWAALBU42pZsQLAltFaeC0CAkBHhAABAoMs8Lc7nopP/Oa2ePKF+avs3N4W8dZDto2TX7xTjBo+ZJArsx0BAgQIECBAgECrBASArZIt17oCwHLNK6VqBYApTVMvBAiURiD7ApHzLr47fnTtw1GrrVr25mPXic+/co+YtPNGpelJoQQIECBAgAABAqsXEAA6HZmAANA5yEtAAJiXvH0JECAQETc9/FycfuGtcc9Ts3v0ePlem8UnT9gtxo8ezosAAQIECBAgQKDEAgLAEg+viaULAJuIaak+CQgA+8TlYgIECDRfYOHirvjOFffH1yffF9mfV36st87Q+M/jd41/fdEW0dbmKUPzJ2BFAgQIECBAgEDrBQSArTcuww6ezZdhSmnWKABMc666IkCghAIPPDM7Tr9walz34Iweq5+4/bj4wisnxDbjR5WwOyUTIECAAAECBKotIACs9vyXdS8AdA7yEhAA5iVvXwIECPQgUKvV4pc3Tosz/3hnvDB/8SpXDB/SHh84esd45+HbxdCOdoYECBAgQIAAAQIlERAAlmRQLS5TANhiYMuvVkAA6HAQIECggAJPz5ofn/39HfGHW5/osbpdNlk3zjppQuyz1foFrF5JBAgQIECAAAECKwsIAJ2JTEAA6BzkJSAAzEvevgQIEOiFwOS7noozLrotHp85f5Wrs48DfPPB28RHX7JzjB4+pBeruYQAAQIECBAgQCAvAQFgXvLF2lcAWKx5VKkaAWCVpq1XAgRKKTBnweI47693xw+nPBS12qotbLbeiPjciXvE0btuXMr+FE2AAAECBAgQqIKAALAKU157jwLAtRu5ojUCAsDWuFqVAAECTRe4edrzcdqvb427npzV49rH77lpfOqE3WKjdUc0fW8LEiBAgAABAgQIDExAADgwv1TuFgCmMsny9SEALN/MVEyAQIUFFnV2xXevfCC+9vd7Y8HirlUkxowYEh//l13jtftvGW3Ze4Q9CBAgQIAAAQIECiEgACzEGHIvwjP03EdQ2QIEgJUdvcYJECizwEPT58THL5oaU+5/tsc2Dtx2g/jCSRNi+w1Hl7lNtRMgQIAAAQIEkhEQACYzygE1IgAcEJ+bByAgABwAnlsJECCQp0CtVotf3fRonPmnO+P5uYtWKWXYkPZ4/6Qd4l1HbB/Znz0IECBAgAABAgTyExAA5mdfpJ0FgEWaRrVqEQBWa966JUAgQYHpsxfE5/5wR/z25sd77G6njUfHWSftGS/aev0Eu9cSAQIECBAgQKAcAgLAcsyp1VUKAFstbP3VCQgAnQ0CBAgkInDp3U/HGRfdFo89P2+VjrKPA3zjQVvHKS/ZOdYdMTSRjrVBgAABAgQIECiPgACwPLNqZaUCwFbqWntNAgJA54MAAQIJCcxduDi+8rd74n+uejC6aqs2tsmYEfHZV+wex+6+SUJda4UAAQIECBAgUHwBAWDxZzQYFQoAB0PZHj0JCACdCwIECCQoMPXRmXHahbfG7Y+/0GN3x+2xSXz65bvHxmNGJNi9lggQIECAAAECxRMQABZvJnlUJADMQ92emYAA0DkgQIBAogKLO7vi+1c/GF/+2z0xf1HXKl2uO2JInHbcLvH6/beK9nZPRRI9BtoiQIAAAQIECiIgACzIIHIuw7PunAdQ4e0FgBUevtYJEKiGwCPPzo3//M3UuPLe6T02vP8268dZJ02IHTZatxoguiRAgAABAgQI5CAgAMwBvYBbCgALOJSKlCQArMigtUmAQLUFarVa/Obmx+Jzf7gzZsxZuArGsI72eO+k7eM9R24fw4d0VBtL9wQIECBAgACBFggIAFuAWsIlBYAlHFoiJQsAExmkNggQINAbgSz8+/wf74gL//FYj5fvsNHoJa8G3H+bDXqznGsIECBAgAABAgR6KSAA7CVU4pcJABMfcIHbEwAWeDhKI0CAQKsErrz3mfjPi26LR2bM7XGLNxy4VZx63C4xZsTQVpVgXQIECBAgQIBApQQEgJUa92qbFQA6B3kJCADzkrcvAQIEchaYt0q7JkkAACAASURBVLAzvnrJPfG9Kx+Mzq7aKtVstO7w+Owrdo+X7rFpzpXangABAgQIECBQfgEBYPln2IwOBIDNULRGfwQEgP1Rcw8BAgQSErjtsZlx+oVTY+pjM3vs6tjdNo7PvmKP2GS9EQl1rRUCBAgQIECAwOAKCAAH17uouwkAizqZ9OsSAKY/Yx0SIEBgrQKLO7vih1Meii/99Z6Yt6hzletHDx8Sp75053jDgVtHe7unLWsFdQEBAgQIECBAYCUBAaAjkQl4Ju0c5CUgAMxL3r4ECBAooMC0GXPjjN/cFpff80yP1e271dg4+1V7xk4br1vA6pVEgAABAgQIECiugACwuLMZzMoEgIOpba8VBQSAzgMBAgQIdBOo1Wrxu1sej8/+/o54ds7CVXSGdrTFe47YPt47aYcYMbSDHgECBAgQIECAQC8EBIC9QKrAJQLACgy5oC0KAAs6GGURIEAgb4Hn5y6MM/94Z1xw06M9lrLdhqPirFdOiAO3G5d3qfYnQIAAAQIECBReQABY+BENSoECwEFhtkkPAgJAx4IAAQIE1igw5b7p8fGLpsZDz87t8brX7b9lnH7crrHeyKEkCRAgQIAAAQIEViMgAHQ0MgEBoHOQl4AAMC95+xIgQKBEAvMXdcbXL7k3vnPFA7G4q7ZK5eNHD4/PvHz3+JcJm0Rbm6c1JRqtUgkQIECAAIFBEhAADhJ0wbfxTLngA0q4PAFgwsPVGgECBJotcOcTL8RpF06NW6Y93+PSR++yUXzuxD1is7HrNHtr6xEgQIAAAQIESi0gACz1+JpWvACwaZQW6qOAALCPYC4nQIBA1QU6u2rxo2seii9efHfMXdi5CseoYR1xykt2jjcevE10tHuKU/Xzon8CBAgQIEBgqYAA0EnIBDw7dg7yEhAA5iVvXwIECJRc4LHn58Unf3NbXHLX0z12sveWY+PsV02IXTYZU/JOlU+AAAECBAgQGLiAAHDghimsIABMYYrl7EEAWM65qZoAAQKFEKjVavHHqU/Ep393R0yfvWCVmoa0t8U7D98uPnD0jjFiaEchalYEAQIECBAgQCAPAQFgHurF21MAWLyZVKUiAWBVJq1PAgQItFBg5txFcdaf74yf3zCtx122GTcyvvDKCTFxh/EtrMLSBAgQIECAAIHiCggAizubwaxMADiY2vZaUUAA6DwQIECAQNMErn3g2fj4hVPjgelzelzzX1+0RXz8X3aN9UcNa9qeFiJAgAABAgQIlEFAAFiGKbW+RgFg643t0LOAANDJIECAAIGmCsxf1BnnX3pffOuy+2NxV22VtceNGhafPGG3ePlem0Vbm6dATcW3GAECBAgQIFBYAQFgYUczqIV59juo3DZbQUAA6DgQIECAQEsE7n5yVpx+4a3xj0ee73H9I3feMD73ij1iyw1GtmR/ixIgQIAAAQIEiiQgACzSNPKrRQCYn33VdxYAVv0E6J8AAQItFOjqqsVPrns4zv3L3TF7weJVdlpnaEd85Nid4i0Tt4khHe0trMTSBAgQIECAAIF8BQSA+foXZXcBYFEmUb06BIDVm7mOCRAgMOgCT8ycF5/87e3xtzue6nHvCZuvF2e/akLsvtl6g16bDQkQIECAAAECgyEgABwM5eLvIQAs/oxSrVAAmOpk9UWAAIGCCdRqtbj49ieXBIFPz1qwSnUd7W3x9sO2jQ8dvVOsM6yjYNUrhwABAgQIECAwMAEB4MD8UrlbAJjKJMvXhwCwfDNTMQECBEotMHPeojjnL3fFT697pMc+ttpgZJz5yj3isB03LHWfiidAgAABAgQIrCggAHQeMgEBoHOQl4AAMC95+xIgQKDiAjc8NCNO+/Wtcf8zc3qUOGmfzeOMl+0WG4waVnEp7RMgQIAAAQIpCAgAU5jiwHsQAA7c0Ar9ExAA9s/NXQQIECDQBIEFizvjW5fdH+dfel8s6qytsmIW/n3iZbvGiXtvHm1tni41gdwSBAgQIECAQE4CAsCc4Au2rWe0BRtIhcoRAFZo2FolQIBAUQXue3pWnPbrqXHjw8/1WOJhO46PM0+cEFuNG1nUFtRFgAABAgQIEFijgADQAckEBIDOQV4CAsC85O1LgAABAt0Eurpq8bMbHomz/3RXzFqweBWdEUPb4+QX7xRvO2TbGNLRTo8AAQIECBAgUCoBAWCpxtWyYgWALaO18FoEBICOCAECBAgUSuCpF+bHp357e/zl9id7rGv3zcbE2SftGRO2WK9QdSuGAAECBAgQILAmAQGg85EJCACdg7wEBIB5yduXAAECBNYocPHtTy4JAp98Yf4q17W3xZJXAp587E4xctgQkgQIECBAgACBwgsIAAs/okEpUAA4KMw26UFAAOhYECBAgEBhBWbNXxRfvPju+PG1D0dt1e8IiS3WXyfOfOWEOGKnDQvbg8IIECBAgAABApmAANA5yAQEgM5BXgICwLzk7UuAAAECvRa46eEZcfqFU+Oep2b3eM8r9t4sPvGy3WL86OG9XtOFBAgQIECAAIHBFBAADqZ2cfcSABZ3NqlXJgBMfcL6I0CAQCICCxd3xbcvvz++Mfm+WNjZtUpXY0cOjTOO3y1ete/m0dbmqVUiY9cGAQIECBBIRkAAmMwoB9SIZ6kD4nPzAAQEgAPAcysBAgQIDL7A/c/MXvJqwOsfnNHj5ofsMC7OPHFCbDN+1OAXZ0cCBAgQIECAwGoEBICORiYgAHQO8hIQAOYlb18CBAgQ6LdAV1ctfnnjtPjCn+6MF+YvXmWd4UPa44PH7BjvOGy7GNrR3u993EiAAAECBAgQaJaAALBZkuVeRwBY7vmVuXoBYJmnp3YCBAhUXODpWfPjM7+/I/546xM9Suy66Zg4+6QJsdeWYysupX0CBAgQIEAgbwEBYN4TKMb+AsBizKGnKraOiA9ExPERsWVELIiI+yPilxFxfkTMbUHpm0bEHRGx7N9WLo+II1uwT7akALBFsJYlQIAAgcET+PsdT8UnfntbPDFz/iqbtrdFvHniNvHRY3eOUcOHDF5RdiJAgAABAgQIrCAgAHQcMgEBYDHPwQkR8ZOIGLOa8u6pB4P3Nbn8X0XEq1ZYUwDYZGDLESBAgEB6ArMXLI7zLr47/veah6JWW7W/zceuE58/cY+YtMtG6TWvIwIECBAgQKDwAgLAwo9oUAoUAA4Kc5822Sciro6IdSJidkScFRGX1v/+dRHxjvpqWQi4X0TM6tPqq784Cx1/FxFPR8Syf0MRADYJ1zIECBAgkL7APx95bsmXhNz15Nr/0XzTGcfEuNHD00fRIQECBAgQIJC7gAAw9xEUogABYCHG0K2IKyLisIjIPln88Ii4ZqUST4mIc+s/+0xEfLoJLYyuv/U3e6vxmyLiR/U1BYBNwLUEAQIECFRHYFFnV3znigfia5fcGwsXd622cQFgdc6ETgkQIECAQN4CAsC8J1CM/QWAxZjDsioOiIjr6n/z7Yh4dw/lZV8peFtE7BoRz9dfrbdogG18PSLeX3+l4VERsewNTALAAcK6nQABAgSqKfDg9DnxnxdNjSn3P9sjwDWnHRWbjs1e7O9BgAABAgQIEGitgACwtb5lWV0AWKxJfSEiTq+XdNAKYeDKVZ5Wf2tw9vOXRMRfB9BGFjpmrzLMXnG4Z0TcLQAcgKZbCRAgQIBAXaBWq8Wvbno0PveHO+KF+dk/Zpc/PnH8rvHvh23HigABAgQIECDQcgEBYMuJS7GBALBYY1r29t859W/i7f5vC8trPTgiptT/9rMR8al+tpF9JeFN9eDvcxHxyWX/zlL/q1cA9hPWbQQIECBAYJnAvU/Nihd/JftH/PLHNuNGxuSPHBnt2VcFexAgQIAAAQIEWiggAGwhbomW9qyzWMN6JiLGR8QtEbH3GkpbPyJm1H9/QUS8pp9tLHslYfZtwhMiYr4AsJ+SbiNAgAABAqsReHb2gnjR5/++ym+/+6b94sW7bcyNAAECBAgQINBSAQFgS3lLs7gAsDijGhER8+rl/DEiXraW0rJvCB4VEddGRPaKwL4+to+IqfVvF175bcTN+AzALdZS0CYRcUN2zbRp02KLLdZ2eV/bcz0BAgQIECiOQPZ24OO+dmW3bwjef5v144J3TyxOkSohQIAAAQIEkhQQACY51j43JQDsM1nLbtgwIp6ur/6LiHjdWnZ6qv4FINkXgmSv3uvr428RcUxE9LRXMwLAZWustS4B4FqJXECAAAECCQj8+qZH4yMXZC/yX/648L0TY9+tshf2exAgQIAAAQIEWiMgAGyNa9lWFQAWZ2JbRsQj9XJ+HBFvWktp2bXZPfdHxA59bCNb+38j4oWI2CUinljpfgFgH0FdToAAAQIE1iawcHFXHH7upfHkC8s+cSPipbtvEv/9xhet7Va/J0CAAAECBAj0W0AA2G+6pG4UABZnnIP1CsDsMwbvrH/W4Psj4ps9EDQjAFzbe3q9Bbg4Z08lBAgQIDBIAt+54v74wp/uauzW1hZLvgxk2/HZp3p4ECBAgAABAgSaLyAAbL5pGVcUABZnaoP1GYA/iog3RsSNEXFgRHS1KABcm2wWEE7LLvIW4LVR+T0BAgQIpCIwa/6imHjW5Ji1YHGjpTccuFWc+cr+fJpHKir6IECAAAECBFopIABspW551hYAFmtW0yNiXAu/BXiziHis3vK5EfHP1bT/s/rPs1cKfrb+5wcj4romcgkAm4hpKQIECBAoj8BZf74zvn35A42Chw1pjymnHRXjRw8vTxMqJUCAAAECBEojIAAszahaWqgAsKW8fV78iog4LCLmRMTYiFj+8oDuS2Xf+jul/qMsoPtUL3faJiKyIK8/j+wzA9/SnxtXc48AsImYliJAgACB8gg89cL8OPScybGoc/n3ZX3gqB3i5GN3Lk8TKiVAgAABAgRKIyAALM2oWlqoALClvH1e/AsRcXr9roPW8Iq70yLirPp1L4mIv/ZyJwFgL6FcRoAAAQIEWinw0QtuiV/d9Ghji7Ejhy55FeDIYUNaua21CRAgQIAAgQoKCAArOPQeWhYAFuscHLBC6PftiHh3D+W1R8RtEbFrRDwfERtFxKImt9GMLwFZW0leAbg2Ib8nQIAAgWQF7nlqVhz7leyF/8sfn3n57vHmidl/q/MgQIAAAQIECDRPQADYPMsyryQALN70lr0NOHv77+ERcc1KJZ4SEdnn92WPz0TEp1f6ffY23R+s4fe96VgA2Bsl1xAgQIAAgQEIvPUH18eldz/TWGHLDdaJSz9yZAzpyP5bnwcBAgQIECBAoDkCAsDmOJZ9FQFg8Sa4T0RcHRHrRMTsiMjeFnxp/e9fFxHvrJd8T0TsFxGzBIDFG6KKCBAgQIDA2gSuuf/ZeP13r+122Tf/bZ942Z7Zd3Z5ECBAgAABAgSaIyAAbI5j2VcRABZzgidExE8iYsxqysvCv+Mj4r4efu8VgMWcqaoIECBAgEA3gVqtFieef3Xc8ujMxs8nbL5e/O4/Dom2Nk/RHBcCBAgQIECgOQICwOY4ln0Vzy6LO8GtI+KD9aAv+7y8hfXA74KI+GZEzF1N6QLA4s5UZQQIECBAoJvAH299It730390+9lP33FgTNx+PCkCBAgQIECAQFMEBIBNYSz9IgLA0o+wtA34EpDSjk7hBAgQINAsgc6uWkw677J4ZMby/6535M4bxg/fmn0vmAcBAgQIECBAYOACAsCBG6awggAwhSmWswcBYDnnpmoCBAgQaLLAj655KD7529u7rXrxhw6PnTdZt8k7WY4AAQIECBCoooAAsIpTX7VnAaBzkJeAADAvefsSIECAQKEE5i3sjIlnXxLPzV3UqOtV+24RX3rNXoWqUzEECBAgQIBAOQUEgOWcW7OrFgA2W9R6vRUQAPZWynUECBAgkLzAl/92T3z9knsbfQ7taIsrPjYpNl1vneR71yABAgQIECDQWgEBYGt9y7K6ALAsk0qvTgFgejPVEQECBAj0U+DZ2Qti4tmTY8HirsYK7zx8u/j4v+zazxXdRoAAAQIECBBYKiAAdBIyAQGgc5CXgAAwL3n7EiBAgEAhBc74zdT4ybWPNGobPXxITDn9qBgzYmgh61UUAQIECBAgUA4BAWA55tTqKgWArRa2/uoEBIDOBgECBAgQWEHgoelzYtKXLotabfkPTz9ul3jXEdtzIkCAAAECBAj0W0AA2G+6pG4UACY1zlI1IwAs1bgUS4AAAQKDIfCen9wUf77tycZWm4wZseSzAIcNaR+M7e1BgAABAgQIJCggAExwqP1oSQDYDzS3NEVAANgURosQIECAQEoC/3zkuXjlf03p1tJ5/7pXvPpF2T82PQgQIECAAAECfRcQAPbdLMU7BIApTrUcPQkAyzEnVRIgQIDAIAu85r+viesfmtHYdaeNR8fFHzo82to8bRvkUdiOAAECBAgkISAATGKMA27CM8kBE1qgnwICwH7CuY0AAQIE0ha45M6n4t//98ZuTf7gLfvHpF02Srtx3REgQIAAAQItERAAtoS1dIsKAEs3smQKFgAmM0qNECBAgEAzBbq6anHsV6+I+56e3Vj2oO02iJ+/8+BmbmMtAgQIECBAoCICAsCKDHotbQoAnYO8BASAecnblwABAgQKL/DLG6bFx359a7c6f/cfh8SeW4wtfO0KJECAAAECBIolIAAs1jzyqkYAmJe8fQWAzgABAgQIEFiNwILFnXHYOZfG07MWNK44fs9N4/x/25cZAQIECBAgQKBPAgLAPnEle7EAMNnRFr4xAWDhR6RAAgQIEMhT4L8uuy/O/cvdjRLa2yIu++ik2GrcyDzLsjcBAgQIECBQMgEBYMkG1qJyBYAtgrXsWgUEgGslcgEBAgQIVFlg5rxFMfGsS2LOws4Gw5sP3jo+84o9qsyidwIECBAgQKCPAgLAPoIlerkAMNHBlqAtAWAJhqREAgQIEMhX4PN/uCO+d9WDjSJGDG2PKacdHRuMGpZvYXYnQIAAAQIESiMgACzNqFpaqACwpbwWX4OAANDxIECAAAECaxF4/Pl5cfi5l8birlrjyg8fs1N88Jgd2REgQIAAAQIEeiUgAOwVU/IXCQCTH3FhGxQAFnY0CiNAgACBIgl8+Bc3x0X/fKxR0rhRw+Lq046KEUM7ilSmWggQIECAAIGCCggACzqYQS5LADjI4LZrCAgAHQYCBAgQINALgTsefyH+5etXdrvy8yfuEf/voK17cbdLCBAgQIAAgaoLCACrfgKW9i8AdA7yEhAA5iVvXwIECBAoncAb/+e6uPLe6Y26txk3Mi75yJHRkX01sAcBAgQIECBAYA0CAkDHQwDoDOQpIADMU9/eBAgQIFAqgavunR7/73+u61bzf/+/feOle2xaqj4US4AAAQIECAy+gABw8M2LuKP/bFzEqVSjJgFgNeasSwIECBBogkCtVouXfeOquP3xFxqr7b3l2LjovROjrc3TuSYQW4IAAQIECCQrIABMdrR9aswzxj5xubiJAgLAJmJaigABAgTSF/jtzY/FB39+c7dGf/mug+OAbTdIv3kdEiBAgAABAv0WEAD2my6pGwWASY2zVM0IAEs1LsUSIECAQN4Cizu74ogvXhaPPT+vUcoxu24U33vz/nmXZn8CBAgQIECgwAICwAIPZxBLEwAOIratugkIAB0IAgQIECDQR4HvX/VgfPYPd3S76+8nHx47bLRuH1dyOQECBAgQIFAVAQFgVSa95j4FgM5BXgICwLzk7UuAAAECpRWYs2BxTDx7csyct6jRw2v32zLOefWepe1J4QQIECBAgEBrBQSArfUty+oCwLJMKr06BYDpzVRHBAgQIDAIAl+8+K44/9L7GzsN62iPq06dFBuNGTEIu9uCAAECBAgQKJuAALBsE2tNvQLA1rhade0CAsC1G7mCAAECBAisIvD0rPlx6DmXxsLFXY3fvffI7eNjL92FFgECBAgQIEBgFQEBoEORCQgAnYO8BASAecnblwABAgRKL3D6hbfGz66f1uhj3RFD4prTj47Rw4eUvjcNECBAgAABAs0VEAA217OsqwkAyzq58tctACz/DHVAgAABAjkJ3P/M7Djmy5dHrba8gDOO3zXefth2OVVkWwIECBAgQKCoAgLAok5mcOsSAA6ut92WCwgAnQYCBAgQIDAAgXf86Mb42x1PNVbYbL0RcfnHJsXQjvYBrOpWAgQIECBAIDUBAWBqE+1fPwLA/rm5a+ACAsCBG1qBAAECBCoscONDM+LV/31NN4GvvnbvOHGfzSusonUCBAgQIEBgZQEBoDORCQgAnYO8BASAecnblwABAgSSETjpv66OfzzyfKOfXTcdE3/6wKHR1uYpXjJD1ggBAgQIEBiggABwgICJ3O7ZYSKDLGEbAsASDk3JBAgQIFAsgb/c9mS8+yc3dSvqx/9+QBy244bFKlQ1BAgQIECAQG4CAsDc6Au1sQCwUOOoVDECwEqNW7MECBAg0AqBzq5avPjLl8cD0+c0lj90h/Hxk7cf2IrtrEmAAAECBAiUUEAAWMKhtaBkAWALUC3ZKwEBYK+YXESAAAECBNYs8NPrHomPXzS120V/eP+hscfm66EjQIAAAQIECIQA0CHIBASAzkFeAgLAvOTtS4AAAQJJCcxf1BmHnjM5ps9e2OjrFXtvFl973T5J9akZAgQIECBAoH8CAsD+uaV2lwAwtYmWpx8BYHlmpVICBAgQKLjANy65N770t3saVXa0t8XlpxwZW6w/suCVK48AAQIECBBotYAAsNXC5VhfAFiOOaVYpQAwxanqiQABAgRyEXhuzsKYePbkmLeos7H/2w7ZNj55wm651GNTAgQIECBAoDgCAsDizCLPSgSAeepXe28BYLXnr3sCBAgQaLLAp393e/xwykONVUcO64hrTjs61hs5tMk7WY4AAQIECBAok4AAsEzTal2tAsDW2Vp5zQICQCeEAAECBAg0UWDajLlx5HmXRfbNwMsep7xk53jfpB2auIulCBAgQIAAgbIJCADLNrHW1CsAbI2rVdcuIABcu5ErCBAgQIBAnwTe/7N/xu9vebxxz/jRw+OqUyfFiKEdfVrHxQQIECBAgEA6AgLAdGY5kE4EgAPRc+9ABASAA9FzLwECBAgQ6EHgtsdmxsu+cVW335x90oR43QFb8SJAgAABAgQqKiAArOjgV2pbAOgc5CUgAMxL3r4ECBAgkLTAv3332phy/7ONHrfbcFT8/cNHRHu7p31JD15zBAgQIEBgNQICQEcjE/BM0DnIS0AAmJe8fQkQIEAgaYHL7n463vKDG7r1+N037Rcv3m3jpPvWHAECBAgQINCzgADQyRAAOgN5CggA89S3NwECBAgkK1Cr1eK4r10Zdz05q9Hj/tusHxe8e2KyPWuMAAECBAgQWL2AANDpEAA6A3kKCADz1Lc3AQIECCQtcOE/Ho2Tf3lLtx5//Z6J8aKt10+6b80RIECAAAECqwoIAJ0KAaAzkKeAADBPfXsTIECAQNICizq74vBzL40nZs5v9PmS3TeOb79xv6T71hwBAgQIECAgAHQGehbwGYBORl4CAsC85O1LgAABApUQ+O4VD8SZf7qz0WtbW8QlJx8R2204uhL9a5IAAQIECBBYKuAVgE5CJiAAdA7yEhAA5iVvXwIECBCohMCs+Yti4lmTY9aCxY1+/+3AreILr5xQif41SYAAAQIECAgAnYHlAgJApyEvAQFgXvL2JUCAAIHKCJz15zvj25c/0Oh32JD2mHLaUTF+9PDKGGiUAAECBAhUXcArAKt+Apb2LwB0DvISEADmJW9fAgQIEKiMwFMvzI9Dz5kcizprjZ4/cNQOcfKxO1fGQKMECBAgQKDqAgLAqp8AAaATkK+AADBff7sTIECAQEUETrnglrjgpkcb3Y4dOXTJqwBHDhtSEQFtEiBAgACBagsIAKs9/2XdewWgc5CXgAAwL3n7EiBAgEClBO59ala8+CtXdOv50yfsFm85ZNtKOWiWAAECBAhUVUAAWNXJd+9bAOgc5CUgAMxL3r4ECBAgUDmBt/3whph819ONvrdYf5247KNHxpCO9spZaJgAAQIECFRNQABYtYn33K8A0DnIS0AAmJe8fQkQIECgcgLXPvBsvO4713br+xuv3ydO2GuzyllomAABAgQIVE1AAFi1iQsATbxYAgLAYs1DNQQIECCQsECtVosTz786bnl0ZqPLCZuvF7/7j0Oirc1/D0549FojQIAAAQIhAHQIMgHP+JyDvAQEgHnJ25cAAQIEKinwx1ufiPf99B/dev/pOw6MiduPr6SHpgkQIECAQFUEBIBVmfSa+xQAOgd5CQgA85K3LwECBAhUUqCzqxaTzrssHpkxt9H/kTtvGD986wGV9NA0AQIECBCoioAAsCqTFgCadDEFBIDFnIuqCBAgQCBhgR9f81B84re3d+vwLx86LHbZZEzCXWuNAAECBAhUW0AAWO35L+veKwCdg7wEBIB5yduXAAECBCorMG9hZxxyzuSYMWdhw+CkfTePL79m78qaaJwAAQIECKQuIABMfcK9608A2DsnVzVfQADYfFMrEiBAgACBtQp85W/3xNcuubdx3ZD2trjy1Emx6XrrrPVeFxAgQIAAAQLlExAAlm9mrahYANgKVWv2RkAA2Bsl1xAgQIAAgSYLPDt7QUw8e3IsWNzVWPmdh28XH/+XXZu8k+UIECBAgACBIggIAIswhfxrEADmP4OqViAArOrk9U2AAAECuQuc8Zup8ZNrH2nUMXr4kJhy+lExZsTQ3GtTAAECBAgQINBcAQFgcz3LupoAsKyTK3/dAsDyz1AHBAgQIFBSgYemz4mjvnRZdNWWN3D6cbvEu47YvqQdKZsAAQIECBBYnYAA0NnIBASAzkFeAgLAvOTtS4AAAQIEIuK9/3dT/Gnqkw2LjccMjys/dlQMG9LOhwABAgQIEEhIW12ExQAAIABJREFUQACY0DAH0IoAcAB4bh2QgABwQHxuJkCAAAECAxO4edrzceL5V3db5Iuv3jP+db8tB7awuwkQIECAAIFCCQgACzWO3IoRAOZGX/mNBYCVPwIACBAgQCBvgdd8+5q4/sEZjTJ22nh0XPyhw6OtzVPEvGdjfwIECBAg0CwBAWCzJMu9jmd35Z5fmasXAJZ5emonQIAAgSQELrnzqfj3/72xWy8/eMv+MWmXjZLoTxMECBAgQIBAhADQKcgEBIDOQV4CAsC85O1LgAABAgTqAl1dtTj2q1fEfU/PbpgctN0G8fN3HsyIAAECBAgQSERAAJjIIAfYhgBwgIBu77eAALDfdG4kQIAAAQLNE/jlDdPiY7++tduCv33fIbHXlmObt4mVCBAgQIAAgdwEBIC50RdqYwFgocZRqWIEgJUat2YJECBAoKgCCxZ3xmHnXBpPz1rQKPH4CZvG+W/Yt6glq4sAAQIECBDog4AAsA9YCV8qAEx4uAVvTQBY8AEpjwABAgSqI/Cty+6Pc/5yV6Ph9raIyz46KbYaN7I6CDolQIAAAQKJCggAEx1sH9sSAPYRzOVNExAANo3SQgQIECBAYGACM+ctiolnXRJzFnY2FnrTwVvHZ1+xx8AWdjcBAgQIECCQu4AAMPcRFKIAAWAhxlDJIgSAlRy7pgkQIECgqAKf/8Md8b2rHmyUN2Joe0w57ejYYNSwopasLgIECBAgQKAXAgLAXiBV4BIBYAWGXNAWBYAFHYyyCBAgQKCaAo8/Py8OP/fSWNxVawB8+Jid4oPH7FhNEF0TIECAAIFEBASAiQxygG0IAAcI6PZ+CwgA+03nRgIECBAg0BqBD//i5rjon481Fs9e/TfltKNixNCO1mxoVQIECBAgQKDlAgLAlhOXYgMBYCnGlGSRAsAkx6opAgQIECizwJ1PvBDHfe3Kbi187sQ94o0HbV3mttROgAABAgQqLSAArPT4G80LAJ2DvAQEgHnJ25cAAQIECKxB4E3fvz6uuOeZxhVbjxsZkz9yZHRkXw3sQYAAAQIECJROQABYupG1pGDP5FrCatFeCAgAe4HkEgIECBAgMNgCV983Pd7wveu6bfutN+wbx03YdLBLsR8BAgQIECDQBAEBYBMQE1hCAJjAEEvaggCwpINTNgECBAikLVCr1eJl37gqbn/8hUaje285Ni5678Roa/PUMe3p644AAQIEUhQQAKY41b735Flc383c0RwBAWBzHK1CgAABAgSaLvDbmx+LD/785m7r/vJdB8cB227Q9L0sSIAAAQIECLRWQADYWt+yrC4ALMuk0qtTAJjeTHVEgAABAokILO7siiO+eFk89vy8RkfH7LpRfO/N+yfSoTYIECBAgEB1BASA1Zn1mjoVADoHeQkIAPOSty8BAgQIEOiFwA+ufjA+8/s7ul3595MPjx02WrcXd7uEAAECBAgQKIqAALAok8i3DgFgvv5V3l0AWOXp650AAQIECi8wZ8HimHj25Jg5b1Gj1tfst0Wc++q9Cl+7AgkQIECAAIHlAgJApyETEAA6B3kJCADzkrcvAQIECBDopcB5F98d37z0vsbVwzra46pTJ8VGY0b0cgWXESBAgAABAnkLCADznkAx9hcAFmMOVaxCAFjFqeuZAAECBEol8MysBXHIOZNj4eKuRt3vOXL7OPWlu5SqD8USIECAAIEqCwgAqzz95b0LAJ2DvAQEgHnJ25cAAQIECPRB4PQLb42fXT+tcce6I4bENacfHaOHD+nDKi4lQIAAAQIE8hIQAOYlX6x9BYDFmkeVqhEAVmnaeiVAgACB0grc/8zsOObLl0ettryFM47fNd5+2Hal7UnhBAgQIECgSgICwCpNe/W9CgCdg7wEBIB5yduXAAECBAj0UeCdP7ox/nrHU427NltvRFz+sUkxtKO9jyu5nAABAgQIEBhsAQHgYIsXcz8BYDHnUoWqBIBVmLIeCRAgQCAJgZsenhGv+tY13Xr5ymv3ilfuk/3j3IMAAQIECBAosoAAsMjTGbzaBICDZ22n7gICQCeCAAECBAiUSOBV35oSNz38XKPiXTZZN/78wcOirc3TyRKNUakECBAgUEEBAWAFh95Dy56xOQd5CQgA85K3LwECBAgQ6IfAxbc/Ge/68U3d7vzR2w6Iw3fasB+ruYUAAQIECBAYLAEB4GBJF3sfAWCx55NydQLAlKerNwIECBBITqCrq7bky0AemD6n0duhO4yPn7z9wOR61RABAgQIEEhJQACY0jT734sAsP927hyYgABwYH7uJkCAAAECgy7w0+seiY9fNLXbvn94/6Gxx+brDXotNiRAgAABAgR6JyAA7J1T6lcJAFOfcHH7EwAWdzYqI0CAAAECPQrMX9QZh54zOabPXtj4/Sv23iy+9rp9iBEgQIAAAQIFFRAAFnQwg1yWAHCQwW3XEBAAOgwECBAgQKCEAt+cfG+c99d7GpV3tLfF5accGVusP7KE3SiZAAECBAikLyAATH/GvelQANgbJde0QkAA2ApVaxIgQIAAgRYLPD93YUw8e3LMXdjZ2Omth2wTnzph9xbvbHkCBAgQIECgPwICwP6opXePADC9mZalIwFgWSalTgIECBAgsJLAp393e/xwykONn44c1hHXnHZ0rDdyKCsCBAgQIECgYAICwIINJKdyBIA5wds2BIAOAQECBAgQKKnAtBlz48jzLovOrlqjg1NesnO8b9IOJe1I2QQIECBAIF0BAWC6s+1LZwLAvmi5tpkCAsBmalqLAAECBAgMssD7f/bP+P0tjzd2HT96eFx16qQYMbRjkCuxHQECBAgQILAmAQGg85EJCACdg7wEBIB5yduXAAECBAg0QeC2x2bGy75xVbeVzj5pQrzugK2asLolCBAgQIAAgWYJCACbJVnudQSA5Z5fmasXAJZ5emonQIAAAQIR8YbvXRtX3/dsw2K7DUfF3z98RLS3e4rpgBAgQIAAgaIICACLMol86/DsLF//Ku8uAKzy9PVOgAABAkkIXH7PM/Hm71/frZfvvPFFcezumyTRnyYIECBAgEAKAgLAFKY48B4EgAM3tEL/BASA/XNzFwECBAgQKIxArVaL4752Zdz15KxGTfttvX786j0TC1OjQggQIECAQNUFBIBVPwFL+xcAOgd5CQgA85K3LwECBAgQaKLAhf94NE7+5S3dVvz1eybGi7Zev4m7WIoAAQIECBDor4AAsL9yad0nAExrnmXqRgBYpmmplQABAgQIrEZgUWdXHH7upfHEzPmNK16y+8bx7Tfux4wAAQIECBAogIAAsABDKEAJAsACDKGiJQgAKzp4bRMgQIBAegLfveKBOPNPdzYaa2uLuOTkI2K7DUen16yOCBAgQIBAyQQEgCUbWIvKFQC2CNayaxUQAK6VyAUECBAgQKAcArPmL4qJZ0+OWfMXNwp+/QFbxVknTShHA6okQIAAAQIJCwgAEx5uH1oTAPYBy6VNFRAANpXTYgQIECBAIF+Bs/98V/z35fc3ihg2pD2uPvWo2HDd4fkWZncCBAgQIFBxAQFgxQ9AvX0BoHOQl4AAMC95+xIgQIAAgRYIPPXC/Dj0nMmxqLPWWP39R+0QHzl25xbsZkkCBAgQIECgtwICwN5KpX2dADDt+Ra5OwFgkaejNgIECBAg0A+BUy64JS646dHGnWNHDo0ppx0VI4cN6cdqbiFAgAABAgSaISAAbIZi+dcQAJZ/hmXtQABY1smpmwABAgQIrEbg3qdmxYu/ckW33376hN3iLYdsy4wAAQIECBDISUAAmBN8wbYVABZsIBUqRwBYoWFrlQABAgSqI/C2H94Qk+96utHwFuuvE5d99MgY0tFeHQSdEiBAgACBAgkIAAs0jBxLEQDmiF/xrQWAFT8A2idAgACBNAWue+DZeO13ru3W3Ndfv0+8fK/N0mxYVwQIECBAoOACAsCCD2iQyhMADhK0bVYREAA6FAQIECBAIEGBWq0WJ/7XlLhl2vON7vbYfEz8/j8OjbY2Tz0THLmWCBAgQKDgAgLAgg9okMrzLGyQoG0jAHQGCBAgQIBAVQT+NPWJeO///aNbuz99+4ExcYfxVSHQJwECBAgQKIyAALAwo8i1EAFgrvyV3twrACs9fs0TIECAQMoCnV21OOpLl8XDz85ttHnEThvG/77tgJTb1hsBAgQIECikgACwkGMZ9KIEgINObsO6gADQUSBAgAABAgkL/Piah+ITv729W4d/+dBhscsmYxLuWmsECBAgQKB4AgLA4s0kj4oEgHmo2zMTEAA6BwQIECBAIGGBeQs745BzJseMOQsbXZ607+bx5dfsnXDXWiNAgAABAsUTEAAWbyZ5VCQAzEPdngJAZ4AAAQIECFRA4Kt/vye++vd7G50OaW+LK0+dFJuut04FutciAQIECBAohoAAsBhzyLsKAWDeE6ju/l4BWN3Z65wAAQIEKiKQvfpv4tmXxPxFXY2O33HYtvGfx+9WEQFtEiBAgACB/AUEgPnPoAgVCACLMIVq1iAArObcdU2AAAECFRP4xG9uix9f+3Cj69HDh8SU04+KMSOGVkxCuwQIECBAIB8BAWA+7kXbVQBYtIlUpx4BYHVmrVMCBAgQqLDAw8/OiUnnXRZdteUIpx23S7z7iO0rrKJ1AgQIECAweAICwMGzLvJOAsAiTyft2gSAac9XdwQIECBAoCHw3v+7Kf409cnG3288Znhc+bGjYtiQdkoECBAgQIBAiwUEgC0GLsnyAsCSDCrBMgWACQ5VSwQIECBAoCeBm6c9Hyeef3W3X33x1XvGv+63JTACBAgQIECgxQICwBYDl2R5AWBJBpVgmQLABIeqJQIECBAgsDqB1377mrjuwRmNX++08ej4ywcPj/Z2T0edGgIECBAg0EoBAWArdcuztmdcxZ3V1hHxgYg4PiKy/zy+ICLuj4hfRsT5ETF3AKXvFxFHRMT+EZF9Dd+GEbFBRCyMiMcj4tqI+GFEXDqAPdZ2qwBwbUJ+T4AAAQIEEhKYfNdT8bYf3tito++/Zb84apeNE+pSKwQIECBAoHgCAsDizSSPigSAeaivfc8TIuInETFmNZfeUw8G71v7Uj1ecVVEHNKLey+IiDdFxPxeXNvXSwSAfRVzPQECBAgQKLFAV1ctXvLVK+Lep2c3ujhw2w3iF+86uMRdKZ0AAQIECBRfQABY/BkNRoUCwMFQ7tse+0RE9iE560RE9gz5rPor8bK/f11EvKO+XBYCZq/km9W35ZdcfUlEdETElIi4MyKeiIjsPTnZKwH3ioh3R8S29XV/Ud+3H9us8RYBYLNFrUeAAAECBAou8Msbp8XHfnVrtyp/+75DYq8txxa8cuURIECAAIHyCggAyzu7ZlYuAGymZnPWuiIiDouIxRFxeERcs9Kyp0TEufWffSYiPt2PbYfU11/drVnYODkiDqpfkIWC3Z+t92PTlW4RAA7c0AoECBAgQKBUAgsWd8Zh51waT8/KPtlk6eP4CZvG+W/Yt1R9KJYAAQIECJRJQABYpmm1rlYBYOts+7PyARFxXf3Gb9dfibfyOu0RcVtE7BoRz0fERhGxqD+breWe7NWGP6tf8x/1zx1s5jYCwGZqWosAAQIECJRE4FuX3R/n/OWuRrXZd4Bc9tFJsdW4kSXpQJkECBAgQKBcAgLAcs2rVdUKAFsl2791vxARp9dvzV59tywMXHm10+pvDc5+/pKI+Gv/tlvjXdmXj/yhfsVHI+JLTd5DANhkUMsRIECAAIEyCMyctygOOXtyzF6Qvdlh6eNNB28dn33FHmUoX40ECBAgQKB0AgLA0o2sJQULAFvC2u9Fl739d05EZB+Gs/yZcfcls0/Lzj6/L3t8NiI+1e8dV3/jjyPi/9V//bKI+GOT9xAANhnUcgQIECBAoCwCZ/7xjvjulQ82yh0xtD2mnHZ0bDBqWFlaUCcBAgQIECiNgACwNKNqaaECwJby9nnxZyJifETcEhF7r+Hu9etf2pFdkn1T72v6vNOqN2RvLc6+BGT3iHh/RJxYvyR7j86EtXxmYH+2FwD2R809BAgQIEAgAYHHn58Xh597aSzuqjW6+dAxO8aHjtkpge60QIAAAQIEiiUgACzWPPKqRgCYl/yq+46IiHn1H2evtstedbemR/YNwaMi4tqIyF4R2N/HQxGx9WpufqBeR/ZNwX19ZAHfmh6bRMQN2QXTpk2LLbZY2+V93d71BAgQIECAQJEFTv7FzXHhPx9rlJi9+u/qU4+KdYZ1FLlstREgQIAAgdIJCABLN7KWFCwAbAlrvxbNXn33dP3OX0RE9iUca3o8Vf8CkOwLQbJX6PX30VMAmL31OPt24a9HxKx+Lrz8P+mvZQEBYD+F3UaAAAECBEoscOcTL8RxX7uyWwefO3GPeONBq/vvkiVuVukECBAgQCBHAQFgjvgF2loAWJxhbBkRj9TLyT5/701rKS27Nrvn/ojYYQBtZO+1yT5wJ3sL8LiIOCQi3lN/K3IWRL43IrJXG/b1IQDsq5jrCRAgQIBAxQTe9P3r44p7sk9AWfrYetzImPyRI6Mj+2pgDwIECBAgQKApAgLApjCWfhHProozwrxeAdiTQPYZgxdHxP4RcWs9FOxrCLi29/R6C3Bxzp5KCBAgQIBALgJT7pse//a967rt/a037BvHTdg0l3psSoAAAQIEUhQQAKY41b73JADsu1mr7sjrMwBX18+uEXFH/ZdnRcTHm9y4LwFpMqjlCBAgQIBA2QRqtVqc8M2r4rbHXmiUvteWY+M3750YbW2eppZtnuolQIAAgWIKCACLOZfBrsozq8EWX/N+0+tvw83jW4B7quyeiNgxIu6NiGZ/LZ8AsFhnTzUECBAgQCAXgd/d8nh84Gf/7Lb3L955UBy4XfbJJB4ECBAgQIDAQAUEgAMVTON+AWCx5nhFRBwWEXMiYmxEZF/G0dMj+9bfKfVffDYiPtWiNq6OiIkRsTAihjd5DwFgk0EtR4AAAQIEyiiwuLMrjjzvsnj0uXmN8o/eZaP4n7dkn0TiQYAAAQIECAxUQAA4UME07hcAFmuOX4iI0+slHRQR3T8UZ3mtp0VE9rbc7PGSiPhri9pY9g3BM+qvTGzmNgLAZmpaiwABAgQIlFjgB1c/GJ/5/bJPHlnayN8+fHjsuPG6Je5K6QQIECBAoBgCAsBizCHvKgSAeU+g+/4HrBD6fTsi3t1Dedm39d4WEdln9D0fERtFxKIWtJH9Z/fr6+teHhFHNnkPAWCTQS1HgAABAgTKKjBnweKYePbkmDlv+VOa1+y3RZz76r3K2pK6CRAgQIBAYQQEgIUZRa6FCABz5e9x82VvA87e/nt4RFyz0lWnRMS59Z99JiI+vdLv3xIRP1jD77OQMVv7H2toffPsP7zXQ8bssn+PiO83mUoA2GRQyxEgQIAAgTILnHfx3fHNS+9rtDCsoz2uPHVSbDwm+540DwIECBAgQKC/AgLA/sqldZ8AsHjz3Cciss/eWyciZkdE9rbgS+t//7qIeGe95OwLOvaLiFl9DACXBYTZZwj+PiJujohn6mtkwd+kiHhrRKxX/9nf628z7moylQCwyaCWI0CAAAECZRZ4ZtaCOOScybFw8fKnHO8+Yvs47bhdytyW2gkQIECAQO4CAsDcR1CIAgSAhRjDKkWcEBE/iYgxqykvC/+Oj4jl/5l8+YVrewXgir9fW/c/jIj3RcTctV3Yj98LAPuB5hYCBAgQIJCywOkXTo2fXf9Io8V1RwyJa04/OkYPH5Jy23ojQIAAAQItFRAAtpS3NIsLAIs7qq0j4oP1oC8Ly7Jv4s0Cvwsi4ptrCOXWFgBmryzMvmn4qPo3/Gav+ts4IoZGxMz6HtkrEH8cEbe2kEcA2EJcSxMgQIAAgTIKPPDM7Dj6y5dHrba8+jOO3zXefth2ZWxHzQQIECBAoBACAsBCjCH3IgSAuY+gsgUIACs7eo0TIECAAIHVC7zzRzfGX+94qnHBZuuNiMs/NimGdmTfg+ZBgAABAgQI9FVAANhXsTSvFwCmOdcydCUALMOU1EiAAAECBAZZ4KaHZ8SrvtX9O9C+8tq94pX7ZE8dPAgQIECAAIG+CggA+yqW5vUCwDTnWoauBIBlmJIaCRAgQIBADgKv+taUuOnh5xo777LJuvHnDx4WbW2euuYwDlsSIECAQMkFBIAlH2CTyvcsqkmQlumzgACwz2RuIECAAAEC1RD46+1Pxjt/fFO3Zn/0tgPi8J02rAaALgkQIECAQBMFBIBNxCzxUgLAEg+v5KULAEs+QOUTIECAAIFWCXR11eKYr1weDzwzp7HFITuMi/97+0Gt2tK6BAgQIEAgWQEBYLKj7VNjAsA+cbm4iQICwCZiWooAAQIECKQm8LPrH4nTL5zara0/vP/Q2GPz9VJrVT8ECBAgQKClAgLAlvKWZnEBYGlGlVyhAsDkRqohAgQIECDQPIH5izrj0HMujemzFzQWfflem8XXX79P8zaxEgECBAgQqICAALACQ+5FiwLAXiC5pCUCAsCWsFqUAAECBAikI/DNyffGeX+9p9FQR3tbXH7KkbHF+iPTaVInBAgQIECgxQICwBYDl2R5AWBJBpVgmQLABIeqJQIECBAg0EyB5+cujIlnT465Czsby771kG3iUyfs3sxtrEWAAAECBJIWEAAmPd5eNycA7DWVC5ssIABsMqjlCBAgQIBAigKf+f3t8YOrH2q0NnJYR0w57agYO3JYiu3qiQABAgQINF1AANh00lIuKAAs5diSKFoAmMQYNUGAAAECBFor8Ohzc+OIL14WnV21xkYfPXan+I+jdmztxlYnQIAAAQKJCAgAExnkANsQAA4Q0O39FhAA9pvOjQQIECBAoFoCH/jZP+N3tzzeaHr86OFx1amTYsTQjmpB6JYAAQIECPRDQADYD7QEbxEAJjjUkrQkACzJoJRJgAABAgTyFrjtsZnxsm9c1a2Ms06aEK8/YKu8S7M/AQIECBAovIAAsPAjGpQCBYCDwmyTHgQEgI4FAQIECBAg0GuBN3zv2rj6vmcb12+34aj4+4ePiPZ2T2d7jehCAgQIEKikgACwkmNfpWnPmJyDvAQEgHnJ25cAAQIECJRQ4PJ7nok3f//6bpV/540vimN336SE3SiZAAECBAgMnoAAcPCsi7yTALDI00m7NgFg2vPVHQECBAgQaKpArVaL4752Zdz15KzGuvttvX786j0Tm7qPxQgQIECAQGoCAsDUJtq/fgSA/XNz18AFBIADN7QCAQIECBColMBF/3w0PvyLW7r1/Ov3HBwv2nqDSjlolgABAgQI9EVAANgXrXSvFQCmO9uidyYALPqE1EeAAAECBAomsKizK44499J4fOb8RmXH7rZxfOdN+xWsUuUQIECAAIHiCAgAizOLPCsRAOapX+29BYDVnr/uCRAgQIBAvwS+d+UD8fk/3tm4t60t4pKTj4jtNhzdr/XcRIAAAQIEUhcQAKY+4d71JwDsnZOrmi8gAGy+qRUJECBAgEDyArMXLI6Dz7okZs1f3Oj19QdsFWedNCH53jVIgAABAgT6IyAA7I9aevcIANObaVk6EgCWZVLqJECAAAECBRM4+893xX9ffn+jqmFD2uPqU4+KDdcdXrBKlUOAAAECBPIXEADmP4MiVCAALMIUqlmDALCac9f1/2fvPqCsqM8+jv92l96liIiAiCIWpPciVY0lGkvsvcSo0dhixaioGDW2qK+9d40ae+i9V0VFRKogICC9Lbv3PaPL4BKWvWXmzv//n+895z3vCTvzf57n88w5XH7u3kUAAQQQQCBjgWVrN6vbP4Zpa0Ghf9Zfeu2va484MOOzOQABBBBAAAHXBAgAXdtoevMQAKbnxl2ZCxAAZm7ICQgggAACCMRW4G/vztDbk3/w569esazG3thLlcuXia0JgyOAAAIIILArAQJAngtPgACQ5yAqAQLAqOSpiwACCCCAgAMCc5avU58HRxab5O/HHazzuzR2YDpGQAABBBBAIDgBAsDgLG0+iQDQ5u3Z3TsBoN37o3sEEEAAAQQiF7jwxUkaMmu538c+e1TU8Ot6qExebuS90QACCCCAAAKmCBAAmrKJaPsgAIzWP87VCQDjvH1mRwABBBBAIACBCXNX6tSnxxc76dHTW+n3LfYO4HSOQAABBBBAwA0BAkA39pjpFASAmQpyf7oCBIDpynEfAggggAACCPwikEgkdMITYzVj0Wpf5ND61fTRFV2Vk8PbXB4TBBBAAAEEPAECQJ4DT4B3RjwHUQkQAEYlT10EEEAAAQQcEvj0yx912WtTi030+kUd1Hn/2g5NySgIIIAAAgikL0AAmL6dS3cSALq0TbtmIQC0a190iwACCCCAgJECBYUJ9frncC1YudHvr3vTOnr5gvZG9ktTCCCAAAIIZFuAADDb4mbWIwA0cy9x6IoAMA5bZkYEEEAAAQSyIPDK+AXq98HMYpU+u6qbDqpXLQvVKYEAAggggIDZAgSAZu8nW90RAGZLmjo7CxAA8kwggAACCCCAQCACm/ML1PneoVq1Yat/3omt6uvBU1sGcj6HIIAAAgggYLMAAaDN2wuudwLA4Cw5KTUBAsDUvLgaAQQQQAABBHYj8PDg2Xp48Hf+FWVyczTybz21d42KuCGAAAIIIBBrAQLAWK/fH54AkOcgKgECwKjkqYsAAggggICDAt53/3W+d4g25xf6013crbFuOeZgB6dlJAQQQAABBJIXIABM3srlKwkAXd6u2bMRAJq9H7pDAAEEEEDAOgHvcwC9zwPc/qpSvozG3tRL1SqUtW4WGkYAAQQQQCAoAQLAoCTtPocA0O792dw9AaDN26N3BBBAAAEEDBRYsHKDej4wXIWJHc3d+LtmuvTwJgZ2S0sIIIAAAghkR4AAMDvOplchADR9Q+72RwDo7m6ZDAEEEEAAgcgXu3QBAAAgAElEQVQELn9tqj758ke//p5Vy2vUDT1VvkxeZD1RGAEEEEAAgSgFCACj1DenNgGgObuIWycEgHHbOPMigAACCCCQBYEZi1br+MfHFKt038mH6Y9tG2ShOiUQQAABBBAwT4AA0LydRNERAWAU6tT0BAgAeQ4QQAABBBBAIBSBU58apwnzVvlnH7BnFf33r92Vm8tb31DAORQBBBBAwGgBAkCj15O15ngXlDVqCu0kQADII4EAAggggAACoQgMnbVMF7w4udjZz5/XVr2a1Q2lHocigAACCCBgsgABoMnbyV5vBIDZs6ZScQECQJ4IBBBAAAEEEAhFoLAwoSMfHqnvlq/3z+/QuKbe+lOnUOpxKAIIIIAAAiYLEACavJ3s9UYAmD1rKhEA8gwggAACCCCAQJYE3pm8SNe/+0Wxah9c3kUtG9TIUgeUQQABBBBAwAwBAkAz9hB1FwSAUW8gvvX5DsD47p7JEUAAAQQQCF1g67ZCdbtvqJat3eLXOrr5XnrizDah16YAAggggAACJgkQAJq0jeh6IQCMzj7ulQkA4/4EMD8CCCCAAAIhCzw54nvd+9ksv4r3O0CGXddDjWpVDrkyxyOAAAIIIGCOAAGgObuIshMCwCj1412bADDe+2d6BBBAAAEEQhdYuzlfnQcM1fot2/xaZ3dspP4nHBp6bQoggAACCCBgigABoCmbiLYPAsBo/eNcnQAwzttndgQQQAABBLIkcPcnX+uZUfP8ahXK5mrsjb1Vs3K5LHVAGQQQQAABBKIVIACM1t+U6gSApmwifn0QAMZv50yMAAIIIIBA1gWWrN6k7vcN07bChF/7r30O0F/7NM16LxREAAEEEEAgCgECwCjUzatJAGjeTuLSEQFgXDbNnAgggAACCEQscM3b0/Xe1MV+F953/425oZcqlsuLuDPKI4AAAgggEL4AAWD4xjZUIAC0YUtu9kgA6OZemQoBBBBAAAHjBGYtXaujHh5VrK/+xx+iszvta1yvNIQAAggggEDQAgSAQYvaeR4BoJ17c6FrAkAXtsgMCCCAAAIIWCJw7vMTNWL2T363jWpV0tBreyjP+9XAvBBAAAEEEHBYgADQ4eWmMBrveFLA4tJABQgAA+XkMAQQQAABBBDYncDYOSt0xrMTil3yxJmtdXTzesAhgAACCCDgtAABoNPrTXo4AsCkqbgwYAECwIBBOQ4BBBBAAAEEShZIJBI67rHRmrl4rX9RiwY19MFlnZWTw1tinh0EEEAAAXcFCADd3W0qk/FuJxUtrg1SgAAwSE3OQgABBBBAAIFSBT6csURXvjGt2HVvXdJRHfarVeq9XIAAAggggICtAgSAtm4u2L4JAIP15LTkBQgAk7fiSgQQQAABBBAIQGBbQaG63zdMS9ZsLnbalFv7qFaV8gFU4AgEEEAAAQTMEyAANG8nUXREABiFOjU9AQJAngMEEEAAAQQQyLrA48O+0/3/nV2s7kdXdFHzfWpkvRcKIoAAAgggkA0BAsBsKJtfgwDQ/B252iEBoKubZS4EEEAAAQQMFvhh1UZ1vW9YsQ6vPaKp/tLrAIO7pjUEEEAAAQTSFyAATN/OpTsJAF3apl2zEADatS+6RQABBBBAwAmBleu3qM1dg4vN0qbRHvr3nzs7MR9DIIAAAgggsLMAASDPhCdAAMhzEJUAAWBU8tRFAAEEEEAg5gIDv1qqS16Z4ivk5eZo8i19tEflcjGXYXwEEEAAARcFCABd3GrqMxEApm7GHcEIEAAG48gpCCCAAAIIIJCiwKatBWrVf6A25xf6d/7zlBY6qY339oQXAggggAACbgkQALq1z3SnIQBMV477MhUgAMxUkPsRQAABBBBAIG2BS16erIFfL/PvP/KQunrq7LZpn8eNCCCAAAIImCpAAGjqZrLbFwFgdr2ptkOAAJCnAQEEEEAAAQQiE3hn8iJd/+4Xfv2KZfM07ba+qlA2L7KeKIwAAggggEAYAgSAYajadyYBoH07c6VjAkBXNskcCCCAAAIIWCiwasNWtb1rkAoTO5p/9py26nNwXQunoWUEEEAAAQRKFiAA5OnwBAgAeQ6iEiAAjEqeuggggAACCCDwi8CpT43ThHmrfI0/tt1H953cAh0EEEAAAQScEiAAdGqdaQ9DAJg2HTdmKEAAmCEgtyOAAAIIIIBAZgLPjpqruz75xj+kVuVymnhLH3m/FZgXAggggAACrggQALqyyczm4N1NZn7cnb4AAWD6dtyJAAIIIIAAAgEILFy5Ud3vH1bspHcu7aR2+9YM4HSOQAABBBBAwAwBAkAz9hB1FwSAUW8gvvUJAOO7eyZHAAEEEEDAGIGjHh6pWUvX+f1c3K2xbjnmYGP6oxEEEEAAAQQyFSAAzFTQjfsJAN3Yo41TEADauDV6RgABBBBAwDGBBwd+q0eHzvGnalSrkoZf10M5ObxNdmzVjIMAAgjEVoAAMLarLzY472x4DqISIACMSp66CCCAAAIIIOALzFy8Rsf+a3QxkYFXd1fTulVRQgABBBBAwAkBAkAn1pjxEASAGRNyQJoCBIBpwnEbAggggAACCAQnkEgk1OXeoVqyZrN/6HVHNNUVvQ4IrggnIYAAAgggEKEAAWCE+AaVJgA0aBkxa4UAMGYLZ1wEEEAAAQRMFbj9w6/04tj5fnuH7VNdH17R1dR26QsBBBBAAIGUBAgAU+Jy9mICQGdXa/xgBIDGr4gGEUAAAQQQiIfAmDkrdOazE4oNO+6mXqpXvWI8AJgSAQQQQMBpAQJAp9eb9HAEgElTcWHAAgSAAYNyHAIIIIAAAgikJ5BfUKg2/Qdp7eZt/gH9jz9EZ3faN70DuQsBBBBAAAGDBAgADVpGhK0QAEaIH/PSBIAxfwAYHwEEEEAAAZMErn5rut6ftthvqdsBtfXKhR1MapFeEEAAAQQQSEuAADAtNuduIgB0bqXWDEQAaM2qaBQBBBBAAAH3BT798kdd9tpUf9AyuTma0q+vqlcs6/7wTIgAAggg4LQAAaDT6016OALApKm4MGABAsCAQTkOAQQQQAABBNIXWL9lm1r3H6St2wr9Qx45raWOb1k//UO5EwEEEEAAAQMECAANWIIBLRAAGrCEmLZAABjTxTM2AggggAACpgpc8OIkDZ213G/vmMPq6fEzWpvaLn0hgAACCCCQlAABYFJMzl9EAOj8io0dkADQ2NXQGAIIIIAAAvEUeGPiQt303pf+8JXL5WnqbX1VvkxePEGYGgEEEEDACQECQCfWmPEQBIAZE3JAmgIEgGnCcRsCCCCAAAIIhCOwfN1mdbhniBKJHee/eH479Thwz3AKcioCCCCAAAJZECAAzAKyBSUIAC1YkqMtEgA6uljGQgABBBBAwGaBk/5vrKYs+Nkf4YwODXXPH5rbPBK9I4AAAgjEXIAAMOYPQNH4BIA8B1EJEABGJU9dBBBAAAEEEChR4MkR3+vez2b5X69Ttbwm3NRbubm8beaxQQABBBCwU4AA0M69Bd0172SCFuW8ZAUIAJOV4joEEEAAAQQQyJrA3J/Wq9c/RxSr9/5lndWq4R5Z64FCCCCAAAIIBClAABikpr1nEQDauzvbOycAtH2D9I8AAggggICjAn0eHKE5y9f70/25RxPdcFQzR6dlLAQQQAAB1wUIAF3fcHLzEQAm58RVwQsQAAZvyokIIIAAAgggEIDAfZ/P0hPDv/dPalKnsoZc2yOAkzkCAQQQQACB7AsQAGbf3MSKBIAmbiUePREAxmPPTIkAAggggIB1AtMW/qw/PDG2WN9Drj1cTepUsW4WGkYAAQQQQIAAkGfAEyAA5DmISoAAMCp56iKAAAIIIIDAbgUKCxPqOGCIlq/b4l934++a6dLDmyCHAAIIIICAdQIEgNatLJSGCQBDYeXQJAQIAJNA4hIEEEAAAQQQiEbglve/1GsTFvrFWzesofcu6xJNM1RFAAEEEEAgAwECwAzwHLqVANChZVo2CgGgZQujXQQQQAABBOIkMPzb5TrvhUn+yDk50oSbe2vPqhXixMCsCCCAAAIOCBAAOrDEAEYgAAwAkSPSEiAATIuNmxBAAAEEEEAgGwJbthWoTf/BWr9lm19uwInNdXr7htkoTw0EEEAAAQQCEyAADIzS6oMIAK1en9XNEwBavT6aRwABBBBAwH2BK16fqo+/+NEftOeBdfTC+e3dH5wJEUAAAQScEiAAdGqdaQ9DAJg2HTdmKEAAmCEgtyOAAAIIIIBAuAL/mb5YV7053S9SLi9XU2/rqyrly4RbmNMRQAABBBAIUIAAMEBMi48iALR4eZa3TgBo+QJpHwEEEEAAAdcF1m7OV5v+g5RfkPBHfeLM1jq6eT3XR2c+BBBAAAGHBAgAHVpmBqMQAGaAx60ZCRAAZsTHzQgggAACCCCQDYGzn5ugUd+t8Eud0HJvPXxaq2yUpgYCCCCAAAKBCBAABsJo/SEEgNav0NoBCACtXR2NI4AAAgggEB+BV8YvUL8PZvoDV61QRlP79VXZvNz4IDApAggggIDVAgSAVq8vsOYJAAOj5KAUBQgAUwTjcgQQQAABBBDIvsDSNZvVccCQYoVfvbCDuh5QO/vNUBEBBBBAAIE0BAgA00Bz8BYCQAeXaslIBICWLIo2EUAAAQQQiLvA8Y+N1owf1vgM53ZqpDuOPzTuLMyPAAIIIGCJAAGgJYsKuU0CwJCBOb5EAQJAHg4EEEAAAQQQsELg8WFzdP9/v/V7rVe9gsbe2Es5ObyVtmKBNIkAAgjEXIAAMOYPQNH4vGvhOYhKgAAwKnnqIoAAAggggEBKArOXrdMRD40sds9HV3RV832qp3QOFyOAAAIIIBCFAAFgFOrm1SQANG8ncemIADAum2ZOBBBAAAEELBdIJBLq+cBwzV+50Z/kyl7765ojDrR8MtpHAAEEEIiDAAFgHLZc+owEgKUbcUU4AgSA4bhyKgIIIIAAAgiEIHDPp9/o6ZFz/ZOb7VVVn/+1ewiVOBIBBBBAAIFgBQgAg/W09TQCQFs3Z3/fBID275AJEEAAAQQQiI3ApPmrdMqT44rNO/L6nmpYq1JsDBgUAQQQQMBOAQJAO/cWdNcEgEGLcl6yAgSAyUpxHQIIIIAAAghELlBQmFD7uwdr5Yatfi+3HnOQLuq2X+S90QACCCCAAAK7EyAA5PnwBAgAeQ6iEiAAjEqeuggggAACCCCQlsAN736htyYv8u9t37im3v5Tp7TO4iYEEEAAAQSyJUAAmC1ps+sQAJq9H5e7IwB0ebvMhgACCCCAgIMCg79epotenuxPlpsjTbqlj2pVKe/gtIyEAAIIIOCKAAGgK5vMbA4CwMz8uDt9AQLA9O24EwEEEEAAAQQiENicX6BWdw7SpvwCv/p9Jx+mP7ZtEEE3lEQAAQQQQCA5AQLA5Jxcv4oA0PUNmzsfAaC5u6EzBBBAAAEEEChB4NJXpujzr5b6X+17cF09c05bvBBAAAEEEDBWgADQ2NVktTECwKxyU+w3AgSAPA4IIIAAAgggYJ3Ae1N/0DVvz/D7rlA2V9P6HaGK5fKsm4WGEUAAAQTiIUAAGI89lzYlAWBpQnw9LAECwLBkORcBBBBAAAEEQhNYvXGr2tw1WN5vBd7+eursNjrykL1Cq8nBCCCAAAIIZCJAAJiJnjv3EgC6s0vbJiEAtG1j9IsAAggggAACvwic/vR4jZu70tc4uc0+euCUFugggAACCCBgpAABoJFryXpTBIBZJ6dgkQABII8CAggggAACCFgp8MKYebrjo6/93veoVPaX3wZcJi/XynloGgEEEEDAbQECQLf3m+x0BIDJSnFd0AIEgEGLch4CCCCAAAIIZEXgh583qus/hhWr9eYlHdVxv1pZqU8RBBBAAAEEUhEgAExFy91rCQDd3a3pkxEAmr4h+kMAAQQQQACBEgWOfmSUvv5xrf/1C7s2Vr9jD0YMAQQQQAAB4wQIAI1bSSQNEQBGwk5RSQSAPAYIIIAAAgggYK3Aw4Nn6+HB3/n9N6hZUSOv76mcHN5eW7tUGkcAAQQcFSAAdHSxKY7FO5QUwbg8MAECwMAoOQgBBBBAAAEEsi3w1ZI1OubR0cXKfnZVNx1Ur1q2W6EeAggggAACuxUgAOQB8QQIAHkOohIgAIxKnroIIIAAAgggkLFAIpH45XMAF6/e5J91dZ+muqrPARmfzQEIIIAAAggEKUAAGKSmvWcRANq7O9s7JwC0fYP0jwACCCCAQMwF7vjoK70wZr6vcGj9avr4L91irsL4CCCAAAKmCRAAmraRaPohAIzGnap8BiDPAAIIIIAAAghYLjDu+5U6/ZnxxaYYc2Mv1a9R0fLJaB8BBBBAwCUBAkCXtpn+LASA6dtxZ2YCfAdgZn7cjQACCCCAAAIRC2wrKFTbuwdr9cZ8v5PbjztY53VpHHFnlEcAAQQQQGCHAAEgT4MnQADIcxCVAAFgVPLURQABBBBAAIHABK55e7rem7rYP6/L/rX02kUdAzufgxBAAAEEEMhUgAAwU0E37icAdGOPNk5BAGjj1ugZAQQQQAABBIoJfD5zqS59dYr/Z3m5OZp6a19Vr1QWKQQQQAABBIwQIAA0Yg2RN0EAGPkKYtsAAWBsV8/gCCCAAAIIuCOwces2tbpzkLZsK/SHeujUFvpDK++tDi8EEEAAAQSiFyAAjH4HJnRAAGjCFuLZAwFgPPfO1AgggAACCDgncNFLkzT4m+X+XEc330tPnNnGuTkZCAEEEEDATgECQDv3FnTXBIBBi3JesgIEgMlKcR0CCCCAAAIIGC3w9qRF+tu/v/B7rFQuT1P79VWFsnlG901zCCCAAALxECAAjMeeS5uSALA0Ib4elgABYFiynIsAAggggAACWRVYsX6L2t09WInEjrLPn9dWvZrVzWofFEMAAQQQQGBXAgSAPBeeAAEgz0FUAgSAUclTFwEEEEAAAQQCFzjlybGaNP9n/9zT2zfQgBMPC7wOByKAAAIIIJCqAAFgqmJuXk8A6OZebZiKANCGLdEjAggggAACCCQl8MzIubr702/8a2tXKacJN/eR91uBeSGAAAIIIBClAAFglPrm1OYdiTm7iFsnBIBx2zjzIoAAAggg4LDA/BUb1OOB4cUm/PefO6lNo5oOT81oCCCAAAI2CBAA2rCl8HskAAzfmAq7FiAA5MlAAAEEEEAAAacEjnhohGYvW+/P9Kfu++mmow9yakaGQQABBBCwT4AA0L6dhdExAWAYqpyZjAABYDJKXIMAAggggAAC1gg88N9v9diwOX6/jWtX1tBrD1dODm+5rVkijSKAAAIOChAAOrjUNEbi3UgaaFm6pZGkKyUdI6mBpC2Svpf0tqTHJW3MoI/qko6V1EdSa0n7SqokabWkmZI+lvRc0f/OoMxubyUADEuWcxFAAAEEEEAgEoEvflit3z82pljtwdd01/57Vo2kH4oigAACCCDgCRAA8hx4AgSAZj4Hx0l6VVK1EtqbXRQM7vhPzMnP8TtJ70sqX8otSyWdIWlY8kendCUBYEpcXIwAAggggAACpgskEgl1GjBUS9du9lu9/sgDdXnP/U1vnf4QQAABBBwWIAB0eLkpjEYAmAJWli5tJcn7T8cVJXkfIjOgKITz/vdpki4u6sMLAdtKWpdiX2dJekVSoaRBkj6XNKPou/28UO5MSacWnel9l2EXSdNTrJHM5QSAyShxDQIIIIAAAghYJdDvg5l6ZfwCv+eWDWrog8u9t1O8EEAAAQQQiEaAADAad9OqEgCathFppKRukrZJ6i5p3E4tXi/pvqI/u0PS7SmO4IV7PSXdI2lhCff+RdKjRV/zvgOwV4o1krmcADAZJa5BAAEEEEAAAasERn33k85+bmKxnifc3Ft1q1Wwag6aRQABBBBwR4AA0J1dZjIJAWAmesHf217ShKJjn5J06S5K5BZ9Tp/3K+W8z+zbU1J+8K1oUtF3GHrfKVhX0oqAaxAABgzKcQgggAACCCAQvcDWbYVq03+Q1m3x/lvur6+7TjhUZ3X0Pt6ZFwIIIIAAAtkXIADMvrmJFQkAzdqK9115NxW11PE3YeDOXd5Y9KPB3p8fKWlgCGPcL+m6onO9YNILBIN8EQAGqclZCCCAAAIIIGCMwJVvTNOHM5b4/RzetI5eusB7O8ULAQQQQACB7AsQAGbf3MSKBIBmbWX7j/9ukFSj6MeAd9VhJ0lji75wp6S/hzCG9yPA3o8Ce682kqYGXIMAMGBQjkMAAQQQQAABMwQ+/mKJrnh9mt9M2bwcTe3XV1UrlDWjQbpAAAEEEIiVAAFgrNZd4rAEgGY9Bz9Jql30Szla7qa1PSStKvr6O5L+GMIY3i8GOazox4u9ntYGXIMAMGBQjkMAAQQQQAABMwTWbc5X6/6DlF+Q8Bv61+mtdFyLvc1okC4QQAABBGIlQAAYq3UTAFqwbu+ToTcV9fmJpGNL6dn7DcGVJY2X5H1HYJCvYyR9XHSg9/+PS+NwL+Db3Wuv7T9WvGjRIu2zT2mXp9EBtyCAAAIIIIAAAhEJnPv8RI2Y7f233V9fXvjnhYC8EEAAAQQQyLYAAWC2xc2sx3cAmrOXOpKWF7XzlqTTSmltWdEvAJkpqXmAY9Qs+nFf75OqCyS1k7TjZ1iSL7TjP3mXcg8BYPKoXIkAAggggAACdgi8NmGBbnnfe5v266tq+TKa0q+vypXxfp8bLwQQQAABBLInQACYPWuTKxEAmrOdBpIWFrXziqRzSmnNu9a753tJ+wc0Rl7Rd/4dVXTeHZJuT/NsAsA04bgNAQQQQAABBOwXWL52s9rfM6TYIC9f0F7dm3r/zZcXAggggAAC2RMgAMyetcmVCADN2Y4J3wH4lKRLiki8H/09oei7ANNRKu1nevkR4HRUuQcBBBBAAAEErBE44fExmr5otd/vWR0b6q4TgvzBDWsoaBQBBBBAIEIBAsAI8Q0qTQBozjKi/gzAAZJuLOIYJenI33wmYRhK/BKQMFQ5EwEEEEAAAQSMEXhi+Bzd9/m3fj97VaugsTf2Um4ub8GNWRKNIIAAAjEQIACMwZKTGJF3H0kgZfGSFZJqRfBbgG+QdG/RnFMl9Qzht/7uzEgAmMUHi1IIIIAAAgggkH2BOcvXq8+DI4oV/s/lXdSiQY3sN0NFBBBAAIHYChAAxnb1xQYnADTrORgpqZukDZK8d4bbSmjP+62/Y4u+dqekv2cwxmWSHi+6/xtJ3SV5QWTYLwLAsIU5HwEEEEAAAQQiF+j1wHDNXeG9tfv1dXnPJrr+yGaR90UDCCCAAALxESAAjM+udzcpAaBZz8E9km4qaqmjpAkltOf9qK73I7vey/tR3YFpjnG2pJckec/B3KLwcUmaZ6V6GwFgqmJcjwACCCCAAALWCQz47Bs9NcJ7m/Xrq2ndKhp49eHWzUHDCCCAAAL2ChAA2ru7IDsnAAxSM/Oz2v8m9PN+IceluzgyV9JMSQdJ8j5Vek9J+WmUPlHS25K83/z7Q1H4Nz+Nc9K9hQAwXTnuQwABBBBAAAFrBKYs+Fkn/d/2H9z4te1h1/VQ49qVrZmBRhFAAAEE7BYgALR7f0F1TwAYlGRw52z/MWDvx3+9H8cdt9PR10u6r+jP7pB0+05fP0/SC7v5uvelIyR9JKmcpOVFdXZ8QnVws+zuJALA7DhTBQEEEEAAAQQiFCgsTKj9PUO0Yv0Wv4ubj26mS7o3ibArSiOAAAIIxEmAADBO2y55VgJA856DVpLGSKooab0k78eChxX979MkXVLU8mxJbSWtSzEA9H60eIikSkXfOegFhl+UwuB9h6D33YZBvggAg9TkLAQQQAABBBAwVuCm977QGxMX+f21bbSH3v1zZ2P7pTEEEEAAAbcECADd2me60xAApisX7n3HSXpVUrUSynjh3zGS5uzi66V9B6D3HYOp/tKQ8yW9GPDIBIABg3IcAggggAACCJgpMGzWcp3/4iS/uZwcadItfVS7SnkzG6YrBBBAAAGnBAgAnVpn2sMQAKZNF/qNjSRdVRT0eWHZ1qLA7x1Jj0naWEIHBIChr4YCCCCAAAIIIIBA8gKb8wvUuv8gbdxa4N/0j5Oa69R2DZM/hCsRQAABBBBIU4AAME04x24jAHRsoRaNw3cAWrQsWkUAAQQQQACBzAQue22KPv1yqX9I72Z76rnz2mV2KHcjgAACCCCQhAABYBJIMbiEADAGSzZ0RAJAQxdDWwgggAACCCAQvMAH0xbrr29N9w8uVyZX0/r1VeXyZYIvxokIIIAAAgj8RoAAkMfBEyAA5DmISoAAMCp56iKAAAIIIIBA1gXWbMxXm7sGaVthwq/95FmtddSh9bLeCwURQAABBOIlQAAYr32XNC0BIM9BVAIEgFHJUxcBBBBAAAEEIhE489nxGjNnpV/7xFb19eCpLSPphaIIIIAAAvERIACMz653NykBIM9BVAIEgFHJUxcBBBBAAAEEIhF4aex8/f3Dr/za1SuW1ZRb+6hMXm4k/VAUAQQQQCAeAgSA8dhzaVMSAJYmxNfDEiAADEuWcxFAAAEEEEDASIElqzep871Di/X2+sUd1LlJbSP7pSkEEEAAATcECADd2GOmUxAAZirI/ekKEACmK8d9CCCAAAIIIGCtwLH/GqWZi9f6/Z/XeV/d/vtDrJ2HxhFAAAEEzBcgADR/R9nokAAwG8rU2JUAASDPBQIIIIAAAgjETuDRId/pwUGz/bnr16io0Tf0VE4Ob8tj9zAwMAIIIJAlAQLALEEbXoZ3GoYvyOH2CAAdXi6jIYAAAggggMCuBWYtXaujHh5V7IufXNlVh+xdHTIEEEAAAQRCESAADIXVukMJAK1bmTMNEwA6s0oGQQABBBBAAIFkBRKJhLrfP0yLVm3yb7mq9wG6um/TZI/gOgQQQAABBFISIABMicvZiwkAnV2t8YMRABq/IhpEAAEEEEAAgTAE+midv/gAACAASURBVH/8tZ4bPc8/+qB61fTZVd3CKMWZCCCAAAIIiACQh8ATIADkOYhKgAAwKnnqIoAAAggggECkAhPmrtSpT48v1sOov/VUg5qVIu2L4ggggAACbgoQALq511SnIgBMVYzrgxIgAAxKknMQQAABBBBAwCqBbQWFanf3YP28Md/v+7ZjD9YFXRtbNQfNIoAAAgjYIUAAaMeewu6SADBsYc4vSYAAkGcDAQQQQAABBGIrcN07M/TulB/8+TvuV1NvXtIpth4MjgACCCAQngABYHi2Np1MAGjTttzqlQDQrX0yDQIIIIAAAgikIDDwq6W65JUp/h15uTmafEsf7VG5XAqncCkCCCCAAAKlCxAAlm4UhysIAOOwZTNnJAA0cy90hQACCCCAAAJZENi0tUCt+g/U5vxCv9o/T2mhk9p4b5F4IYAAAgggEJwAAWBwljafRABo8/bs7p0A0O790T0CCCCAAAIIZChw8cuTNejrZf4pRx5SV0+d3TbDU7kdAQQQQACB4gIEgDwRngABIM9BVAIEgFHJUxcBBBBAAAEEjBB4Z/IiXf/uF34vFcvmadptfVWhbJ4R/dEEAggggIAbAgSAbuwx0ykIADMV5P50BQgA05XjPgQQQAABBBBwQmDVhq1qe9cgFSZ2jPPsOW3V5+C6TszHEAgggAACZggQAJqxh6i7IACMegPxrU8AGN/dMzkCCCCAAAIIFAn88alxmjhvle/xx7b76L6TW+CDAAIIIIBAYAIEgIFRWn0QAaDV67O6eQJAq9dH8wgggAACCCAQhMCzo+bqrk++8Y+qVbmcJt7SR95vBeaFAAIIIIBAEAIEgEEo2n8G7yzs36GtExAA2ro5+kYAAQQQQACBwAQWrtyo7vcPK3beO5d2Urt9awZWg4MQQAABBOItQAAY7/1vn54AkOcgKgECwKjkqYsAAggggAACRgkc9fBIzVq6zu/p4m6NdcsxBxvVI80ggAACCNgrQABo7+6C7JwAMEhNzkpFgAAwFS2uRQABBBBAAAFnBR4c+K0eHTrHn69RrUoafl0P5eTwVt3ZpTMYAgggkEUBAsAsYhtcincVBi/H8dYIAB1fMOMhgAACCCCAQHICMxev0bH/Gl3s4oFXd1fTulWTO4CrEEAAAQQQ2I0AASCPhydAAMhzEJUAAWBU8tRFAAEEEEAAAaMEEomEutw7VEvWbPb7uu6Iprqi1wFG9UkzCCCAAAJ2ChAA2rm3oLsmAAxalPOSFSAATFaK6xBAAAEEEEDAeYG//2emXhq3wJ/zsH2q68Mrujo/NwMigAACCIQvQAAYvrENFQgAbdiSmz0SALq5V6ZCAAEEEEAAgTQExsxZoTOfnVDsznE39VK96hXTOI1bEEAAAQQQ2CFAAMjT4AkQAPIcRCVAABiVPHURQAABBBBAwDiB/IJCtek/SGs3b/N763/8ITq7077G9UpDCCCAAAJ2CRAA2rWvsLolAAxLlnNLEyAALE2IryOAAAIIIIBArAT++uY0fTB9iT9ztwNq65ULO8TKgGERQAABBIIXIAAM3tTGEwkAbdyaGz0TALqxR6ZAAAEEEEAAgYAEPv3yR1322lT/tDK5OZrSr6+qVywbUAWOQQABBBCIowABYBy3/r8zEwDyHEQlQAAYlTx1EUAAAQQQQMBIgfVbtql1/0Hauq3Q7++R01rq+Jb1jeyXphBAAAEE7BAgALRjT2F3SQAYtjDnlyRAAMizgQACCCCAAAII7CRw/gsTNezbn/w/Peawenr8jNY4IYAAAgggkLYAAWDadE7dSADo1DqtGoYA0Kp10SwCCCCAAAIIZEPgjYkLddN7X/qlKpfL09Tb+qp8mbxslKcGAggggICDAgSADi41jZEIANNA45ZABAgAA2HkEAQQQAABBBBwSWD5us3qcM8QJRI7pnrx/HbqceCeLo3JLAgggAACWRQgAMwitsGlCAANXo7jrREAOr5gxkMAAQQQQACB9AROfGKMpi5c7d98RoeGuucPzdM7jLsQQAABBGIvQAAY+0fgFwACQJ6DqAQIAKOSpy4CCCCAAAIIGC3w5Ijvde9ns/we61Qtrwk39VZuLm/djV4czSGAAAKGChAAGrqYLLfFu4gsg1POFyAA5GFAAAEEEEAAAQR2ITD3p/Xq9c8Rxb7y/mWd1arhHnghgAACCCCQsgABYMpkTt5AAOjkWq0YigDQijXRJAIIIIAAAghEIdDnwRGas3y9X/rPPZrohqOaRdEKNRFAAAEELBcgALR8gQG1TwAYECTHpCxAAJgyGTcggAACCCCAQFwE/vH5LP3f8O/9cZvUqawh1/aIy/jMiQACCCAQoAABYICYFh9FAGjx8ixvnQDQ8gXSPgIIIIAAAgiEJzBt4c/6wxNjixUYcu3halKnSnhFORkBBBBAwEkBAkAn15ryUASAKZNxQ0ACBIABQXIMAggggAACCLgnUFiYUMcBQ7R83RZ/uBt/10yXHt7EvWGZCAEEEEAgVAECwFB5rTmcANCaVTnXKAGgcytlIAQQQAABBBAIUuDm97/U6xMW+ke2blhD713WJcgSnIUAAgggEAMBAsAYLDmJEQkAk0DiklAECABDYeVQBBBAAAEEEHBFYPi3y3XeC5P8cXJypAk399aeVSu4MiJzIIAAAghkQYAAMAvIFpQgALRgSY62SADo6GIZCwEEEEAAAQSCEdiyrUBt+g/W+i3b/AMHnNhcp7dvGEwBTkEAAQQQiIUAAWAs1lzqkASApRJxQUgCBIAhwXIsAggggAACCLgjcPnrU/XJFz/6A/U8sI5eOL+9OwMyCQIIIIBA6AIEgKETW1GAANCKNTnZJAGgk2tlKAQQQAABBBAIUuA/0xfrqjen+0eWy8vV1Nv6qkr5MkGW4SwEEEAAAYcFCAAdXm4KoxEApoDFpYEKEAAGyslhCCCAAAIIIOCiwNrN+WrTf5DyCxL+eE+c2VpHN6/n4rjMhAACCCAQggABYAioFh5JAGjh0hxpmQDQkUUyBgIIIIAAAgiEK3D2cxM06rsVfpETWu6th09rFW5RTkcAAQQQcEaAANCZVWY0CAFgRnzcnIEAAWAGeNyKAAIIIIAAAvEReGXcfPX7z1f+wNUqlNGUfn1VNi83PghMigACCCCQtgABYNp0Tt1IAOjUOq0ahgDQqnXRLAIIIIAAAghEJfDjmk3qNGBosfKvXdRBXfavHVVL1EUAAQQQsEiAANCiZYXYKgFgiLgcvVsBAkAeEAQQQAABBBBAIEmB4x8brRk/rPGvPrdTI91x/KFJ3s1lCCCAAAJxFiAAjPP2d8xOAMhzEJUAAWBU8tRFAAEEEEAAAesEHhv6nR4YONvvu171Chp7Yy/l5PB23rpl0jACCCCQZQECwCyDG1qOdwyGLiYGbREAxmDJjIgAAggggAACwQjMXrZORzw0sthhH13RVc33qR5MAU5BAAEEEHBWgADQ2dWmNBgBYEpcXBygAAFggJgchQACCCCAAAJuCyQSCfV8YLjmr9zoD3plr/11zREHuj040yGAAAIIZCxAAJgxoRMHEAA6sUYrhyAAtHJtNI0AAggggAACUQnc/cnXembUPL98s72q6vO/do+qHeoigAACCFgiQABoyaJCbpMAMGRgji9RgACQhwMBBBBAAAEEEEhBYNL8VTrlyXHF7hh5fU81rFUphVO4FAEEEEAgbgIEgHHb+K7nJQDkOYhKgAAwKnnqIoAAAggggICVAgWFCbW/e7BWbtjq93/rMQfpom77WTkPTSOAAAIIZEeAADA7zqZXIQA0fUPu9kcA6O5umQwBBBBAAAEEQhL427sz9PbkH/zT2zeuqbf/1CmkahyLAAIIIOCCAAGgC1vMfAYCwMwNOSE9AQLA9Ny4CwEEEEAAAQRiLDD462W66OXJvkBujjT51r6qWblcjFUYHQEEEEBgdwIEgDwfngABIM9BVAIEgFHJUxcBBBBAAAEErBXYnF+gVncO0qb8An+G+08+TKe0bWDtTDSOAAIIIBCuAAFguL62nE4AaMum3OuTANC9nTIRAggggAACCGRB4NJXpujzr5b6lfoeXFfPnNM2C5UpgQACCCBgowABoI1bC75nAsDgTTkxOQECwOScuAoBBBBAAAEEECgm8O8pP+jad2b4f1ahbK6m9TtCFcvlIYUAAggggMD/CBAA8lB4AgSAPAdRCRAARiVPXQQQQAABBBCwWuDnDVvV9u7B8n4r8PbXU2e30ZGH7GX1XDSPAAIIIBCOAAFgOK62nUoAaNvG3OmXANCdXTIJAggggAACCGRZ4PSnx2vc3JV+1ZPb7KMHTmmR5S4ohwACCCBggwABoA1bCr9HAsDwjamwawECQJ4MBBBAAAEEEEAgTYHnR8/TnR9/7d+9R6WymnRLH5XJy03zRG5DAAEEEHBVgADQ1c2mNhcBYGpeXB2cAAFgcJachAACCCCAAAIxE1i0aqO63Tes2NRvXtJRHferFTMJxkUAAQQQKE2AALA0oXh8nQAwHns2cUoCQBO3Qk8IIIAAAgggYI3A0Y+M0tc/rvX7vbBrY/U79mBr+qdRBBBAAIHsCBAAZsfZ9CoEgKZvyN3+CADd3S2TIYAAAggggEAWBB4aNFuPDPnOr9SgZkWNvL6ncnJ4i58FfkoggAAC1ggQAFqzqlAb5d1BqLwcvhsBAkAeDwQQQAABBBBAIAOBr5as0TGPji52wmdXddNB9aplcCq3IoAAAgi4JkAA6NpG05uHADA9N+7KXIAAMHNDTkAAAQQQQACBGAskEgl1/ccwLV69yVe4pm9TXdn7gBirMDoCCCCAwM4CBIA8E54AASDPQVQCBIBRyVMXAQQQQAABBJwRuOOjr/TCmPn+PIfWr6aP/9LNmfkYBAEEEEAgcwECwMwNXTiBANCFLdo5AwGgnXujawQQQAABBBAwSGDs9yt0xjMTinU05sZeql+jokFd0goCCCCAQJQCBIBR6ptTmwDQnF3ErRMCwLhtnHkRQAABBBBAIHCBbQWFanPXYK3ZlO+ffcfvD9G5nfcNvBYHIoAAAgjYKUAAaOfegu6aADBoUc5LVoAAMFkprkMAAQQQQAABBHYjcM3b0/Xe1MX+FV32r6XXLuqIGQIIIIAAAr8IEADyIHgCBIA8B1EJEABGJU9dBBBAAAEEEHBK4POZP+rSV6f6M+Xl5mjqrX1VvVJZp+ZkGAQQQACB9AQIANNzc+0uAkDXNmrPPASA9uyKThFAAAEEEEDAYIGNW7ep1Z2DtGVbod/lQ6e20B9aeW+3eCGAAAIIxF2AADDuT8Cv8xMA8hxEJUAAGJU8dRFAAAEEEEDAOYGLXpqkwd8s9+c6uvleeuLMNs7NyUAIIIAAAqkLEACmbubiHQSALm7VjpkIAO3YE10igAACCCCAgAUCb01aqBv+/aXfaaVyeZrar68qlM2zoHtaRAABBBAIU4AAMExde84mALRnV651SgDo2kaZBwEEEEAAAQQiE1ixfova3T1YicSOFp4/r616NasbWU8URgABBBAwQ4AA0Iw9RN0FAWDUG4hvfQLA+O6eyRFAAAEEEEAgBIFTnhyrSfN/9k8+vX0DDTjxsBAqcSQCCCCAgE0CBIA2bSu8XgkAw7Pl5N0LEADyhCCAAAIIIIAAAgEKPD3ye93z6Sz/xNpVymnCzX3k/VZgXggggAAC8RUgAIzv7n87Oe8GeA6iEiAAjEqeuggggAACCCDgpMC8FRvU84HhxWb79587qU2jmk7Oy1AIIIAAAskJEAAm5+T6VQSArm/Y3PkIAM3dDZ0hgAACCCCAgKUCRzw0QrOXrfe7/9Ph++mm3x1k6TS0jQACCCAQhAABYBCK9p9BAGj/Dm2dgADQ1s3RNwIIIIAAAggYK/DAf7/VY8Pm+P01rl1ZQ689XDk5vO03dmk0hgACCIQsQAAYMrAlx/NOwJJFOdgmAaCDS2UkBBBAAAEEEIhWYMai1Tr+8THFmhh8TXftv2fVaBujOgIIIIBAZAIEgJHRG1WYANCodcSqGQLAWK2bYRFAAAEEEEAgGwKFhQl1vneolq7d7Je7/sgDdXnP/bNRnhoIIIAAAgYKEAAauJQIWiIAjACdkr8IEADyICCAAAIIIIAAAiEI9Ptgpl4Zv8A/uWWDGvrg8i4hVOJIBBBAAAEbBAgAbdhS+D0SAIZvTIVdCxAA8mQggAACCCCAAAIhCIyc/ZPOeX5isZMn3NxbdatVCKEaRyKAAAIImC5AAGj6hrLTHwFgdpyp8r8CBIA8FQgggAACCCCAQAgCW7cVqk3/QVq3ZZt/+l0nHKqzOjYKoRpHIoAAAgiYLkAAaPqGstMfAWB2nKlCAMgzgAACCCCAAAIIZE3gyjem6cMZS/x6hzeto5cuaJ+1+hRCAAEEEDBHgADQnF1E2QkBYJT68a7NdwDGe/9MjwACCCCAAAIhCnw0Y4n+8sY0v0LZvBxN7ddXVSuUDbEqRyOAAAIImChAAGjiVrLfEwFg9s2p+KsAASBPAgIIIIAAAgggEJLAus35at1/kPILEn6Ff53eSse12DukihyLAAIIIGCqAAGgqZvJbl8EgNn1ptoOAQJAngYEEEAAAQQQQCBEgXOfn6gRs3/yK/y+xd569PRWIVbkaAQQQAABEwUIAE3cSvZ7IgDMvjkVfxUgAORJQAABBBBAAAEEQhR4bcIC3fL+TL9C1fJlNKVfX5UrkxtiVY5GAAEEEDBNgADQtI1E0w8BYDTuVCUA5BlAAAEEEEAAAQRCFVi2drM63DOkWI2XL2iv7k3rhFqXwxFAAAEEzBIgADRrH1F1QwAYlTx1+Q5AngEEEEAAAQQQQCBkgRMeH6Ppi1b7Vc7q2FB3ndA85KocjwACCCBgkgABoEnbiK4XAsDo7ONemQAw7k8A8yOAAAIIIIBA6AJPDJ+j+z7/1q+zV7UKGntjL+Xm8s+A0PEpgAACCBgiQABoyCIiboO/+SNeQIzLEwDGePmMjgACCCCAAALZEZizfJ36PDiyWLH/XN5FLRrUyE4DVEEAAQQQiFyAADDyFRjRAAGgEWuIZRMEgLFcO0MjgAACCCCAQDYFEomEev9zhOau2OCXvbxnE11/ZLNstkEtBBBAAIEIBQgAI8Q3qDQBoEHLiFkrBIAxWzjjIoAAAggggEA0AgM++0ZPjZjrF29at4oGXn14NM1QFQEEEEAg6wIEgFknN7IgAaCRa4lFUwSAsVgzQyKAAAIIIIBA1AJTFqzSSf83rlgbw67roca1K0fdGvURQAABBLIgQACYBWQLShAAWrAkR1skAHR0sYyFAAIIIIAAAmYJFBQm1OGeIVqxfovf2M1HN9Ml3ZuY1SjdIIAAAgiEIkAAGAqrdYcSAFq3MmcaJgB0ZpUMggACCCCAAAKmC9z03hd6Y+Iiv812++6hdy7tbHrb9IcAAgggEIAAAWAAiA4cQQDowBItHYEA0NLF0TYCCCCAAAII2CcwdNYyXfDiZL/xnBxp0i19VLtKefuGoWMEEEAAgZQECABT4nL2YgJAZ1dr/GAEgMaviAYRQAABBBBAwBWBzfkFat1/kDZuLfBH+sdJzXVqu4aujMgcCCCAAAIlCBAA8mh4AgSAPAdRCRAARiVPXQQQQAABBBCIpcBlr03Rp18u9Wfv3WxPPXdeu1haMDQCCCAQJwECwDhtu+RZCQB5DqISIACMSp66CCCAAAIIIBBLgQ+mLdZf35ruz16uTK6m9euryuXLxNKDoRFAAIG4CBAAxmXTu5+TAJDnICoBAsCo5KmLAAIIIIAAArEUWLMxX63vGiTvtwJvfz15VmsddWi9WHowNAIIIBAXAQLAuGyaAJBNmylAAGjmXugKAQQQQAABBBwWOPPZ8RozZ6U/4Ymt6uvBU1s6PDGjIYAAAggQAPIMeAJ8ByDPQVQCBIBRyVMXAQQQQAABBGIr8NLY+fr7h1/581evWFZTbu2jMnm5sTVhcAQQQMB1AQJA1zec3HwEgMk5cVXwAgSAwZtyIgIIIIAAAgggsFuBxas3qcu9Q4td8/rFHdS5SW3kEEAAAQQcFSAAdHSxKY5FAJgiGJcHJkAAGBglByGAAAIIIIAAAskLHPuvUZq5eK1/w3md99Xtvz8k+QO4EgEEEEDAKgECQKvWFVqzBICh0XJwKQIEgDwiCCCAAAIIIIBABAKPDvlODw6a7VeuX6OiRt/QUzk5/NMggnVQEgEEEAhdgAAwdGIrCvC3vBVrcrJJAkAn18pQCCCAAAIIIGC6wDc/rtXvHhlVrM1PruyqQ/aubnrr9IcAAgggkIYAAWAaaA7eQgDo4FItGYkA0JJF0SYCCCCAAAIIuCWQSCTU/f5hWrRqkz/YVb0P0NV9m7o1KNMggAACCPwiQADIg+AJEADyHEQlQAAYlTx1EUAAAQQQQCD2Av0//lrPjZ7nOxxcr5o+vapb7F0AQAABBFwUIAB0caupz0QAmLoZdwQjQAAYjCOnIIAAAggggAACKQuMn7tSpz09vth9o/7WUw1qVkr5LG5AAAEEEDBbgADQ7P1kqzsCwGxJU2dnAQJAngkEEEAAAQQQQCAigW0FhWp392D9vDHf7+C2Yw/WBV0bR9QRZRFAAAEEwhIgAAxL1q5zCQDt2pdL3RIAurRNZkEAAQQQQAAB6wSue2eG3p3yg993x/1q6s1LOlk3Bw0jgAACCOxegACQJ8QTIADkOYhKgAAwKnnqIoAAAggggAACkgZ+tVSXvDLFt8jLzdHkW/poj8rl8EEAAQQQcEiAANChZWYwCgFgBnjcmpEAAWBGfNyMAAIIIIAAAghkJrBpa4Fa9R+ozfmF/kH/PKWFTmrjvU3jhQACCCDgigABoCubzGwOAsDM/Lg7fQECwPTtuBMBBBBAAAEEEAhE4OKXJ2vQ18v8s448pK6eOrttIGdzCAIIIICAGQIEgGbsIeouCACj3kB86xMAxnf3TI4AAggggAAChgi8M3mRrn/3C7+bimXzNO22vqpQNs+QDmkDAQQQQCBTAQLATAXduJ8A0I092jgFAaCNW6NnBBBAAAEEEHBKYNWGrWp71yAVJnaM9ew5bdXn4LpOzckwCCCAQJwFCADjvP0dsxMA8hxEJUAAGJU8dRFAAAEEEEAAgd8I/PGpcZo4b5X/J39su4/uO7kFRggggAACjggQADqyyAzHIADMEJDb0xYgAEybjhsRQAABBBBAAIHgBJ4dNVd3ffKNf2CtyuU08ZY+8n4rMC8EEEAAAfsFCADt32EQE/C3ehCKnJGOAAFgOmrcgwACCCCAAAIIBCywcOVGdb9/WLFT37m0k9rtWzPgShyHAAIIIBCFAAFgFOrm1SQANG8n2ztqJOlKScdIaiBpi6TvJb0t6XFJGzNovYyk5pLaS2pX9P8PlrT9054bS5qfwfnJ3EoAmIwS1yCAAAIIIIAAAlkQOOrhkZq1dJ1f6eJujXXLMd7bQ14IIIAAArYLEADavsFg+icADMYx6FOOk/SqpGolHDy7KBick2bhv0u6fTf3EgCmCcttCCCAAAIIIICAjQIPDvxWjw7d8dayUa1KGn5dD+Xk8M8FG/dJzwgggMBvBQgAeR48Af5GN+85aCVpjKSKktZLGiDJ+5kM73+fJuniopa9ELCtpB3/qTb5WbzwzwsBvddmSdMl1ZHUpOjPCACTt+RKBBBAAAEEEEDAeoGZi9fo2H+NLjbHwKu7q2ndqtbPxgAIIIBA3AUIAOP+BPw6PwGgec/BSEndJG2T1F3SuJ1avF7SfUV/dkcp38lX0nRHStpX0kRJXxbVelHSuQSA5j0QdIQAAggggAACCIQtkEgk1OXeoVqyxvtvw7++rjuiqa7odUDYpTkfAQQQQCBkAQLAkIEtOZ4A0KxFeZ/JN6GopackXbqL9nIlzZR0kKTVkvaUlB/AGASAASByBAIIIIAAAgggYKvA3/8zUy+NW+C3f9g+1fXhFV1tHYe+EUAAAQSKBAgAeRQ8AQJAs56DeyTdVNRSx9+EgTt3eWPRjwZ7f+59N9/AAMYgAAwAkSMQQAABBBBAAAFbBcbMWaEzn93+36J/nWLcTb1Ur7r3STS8EEAAAQRsFSAAtHVzwfZNABisZ6anbf/x3w2SahT9aO6uzuwkaWzRF+78zef5ZVKfADATPe5FAAEEEEAAAQQsF8gvKFSb/oO0drP3STS/vvoff4jO7uR9cgwvBBBAAAFbBQgAbd1csH0TAAbrmelpP0mqLWmGpJa7OWwPSauKvv6OpD9mWlgSAWAAiByBAAIIIIAAAgjYLPDXN6fpg+lL/BG6HVBbr1zYweaR6B0BBBCIvQABYOwfgV8ACADNeQ4qSNpU1M4nko4tpTXvNwRXljRekvcdgZm+gg4A9ymlob0kTfKuWbRokfbZp7TLMx2P+xFAAAEEEEAAAQRKE/j0yx912WtT/cvK5OZoSr++ql6xbGm38nUEEEAAAUMFCAANXUyW2yIAzDL4bsrVkbS86OtvSTqtlNaWFf0CEO8XgjQPYIygA8BEsj0RACYrxXUIIIAAAggggEC4Auu3bFPrOwdpa0GhX+iR01rq+Jb1wy3M6QgggAACoQkQAIZGa9XBBIDmrKuBpIVF7bwi6ZxSWvOu9e75XtL+AYxBABgAIkcggAACCCCAAAK2C5z/wkQN+9b7ZJpfX8ccVk+Pn9Ha9rHoHwEEEIitAAFgbFdfbHACQHOeA9e+A7C0n+nlR4DNefboBAEEEEAAAQQQ8AXemLhQN733pf+/K5fL09Tb+qp8mTyUEEAAAQQsFCAAtHBpIbRMABgCappHuvYZgKUxeAHhIu8ifgS4NCq+jgACCCCAAAIIZE9g+brN6nDPECV+84EuL57fTj0O3DN7TVAJAQQQQCAwAQLAwCitPogA0Kz1rZBUi98CbNZS6AYBBBBAAAEEEIibwIlPjNHUhav9sc/o0FD3/CGIj52OmyTzteSsIQAAIABJREFUIoAAAtELEABGvwMTOiAANGELO3oYKambpA2SakjaVkJ73m/9HVv0tTsl/T2AMYL+DMDSWuI7AEsT4usIIIAAAggggEBEAk+O+F73fjbLr16nanlNuKm3cnP550NEK6EsAgggkLYAAWDadE7dyN/gZq3zHkk3FbXUUdKEEtq7UdKAoq8dKWlgAGMQAAaAyBEIIIAAAggggIALAnN/Wq9e/xxRbJT3L+usVg33cGE8ZkAAAQRiJUAAGKt1lzgsAaBZz0H734R+T0m6dBft5UqaKekgSd7PZXgfxpIfwBgEgAEgcgQCCCCAAAIIIOCKQO9/Dtf3P3k/mPLr6889muiGo5q5Mh5zIIAAArERIACMzap3OygBoHnPwfYfA/Z+/Le7pHE7tXi9pPuK/uwOSbfv9PXzJL2wm6+XNDEBoHnPAh0hgAACCCCAAAKRCfzj81n6v+Hf+/Wb1KmsIdf2iKwfCiOAAAIIpCdAAJiem2t3EQCat9FWksZIqihpvSTvx4KHFf3v0yRdUtTybEltJa1LIwCsIunkne67SFKXoj/zQkbvF5Jsf02X5P1fkC8+AzBITc5CAAEEEEAAAQQCFpi28Gf94YntHzv96+FDrj1cTep4byV5IYAAAgjYIkAAaMumwu2TADBc33RPP07Sq5KqlXCAF/4dI2nOLr6ezHcA7itpXgrN7eo7DVO4fZeXEgBmKsj9CCCAAAIIIIBAiAKFhQl1HDBEy9dt8avc+LtmuvTwJiFW5WgEEEAAgaAFCACDFrXzPAJAc/fWSNJVRUGfF5ZtLQr83pH0mKSNJbROAGjuTukMAQQQQAABBBCwSuDm97/U6xMW+j23blhD7122/YdGrBqFZhFAAIHYChAAxnb1xQYnAOQ5iEqA7wCMSp66CCCAAAIIIIBAkgLDv12u816Y5F+dkyNNuLm39qxaIckTuAwBBBBAIGoBAsCoN2BGfQJAM/YQxy4IAOO4dWZGAAEEEEAAAasEtmwrUJv+g7V+i/f76X59DTixuU5v39CqOWgWAQQQiLMAAWCct79jdgJAnoOoBAgAo5KnLgIIIIAAAgggkILA5a9P1Sdf/Ojf0fPAOnrh/PYpnMClCCCAAAJRChAARqlvTm0CQHN2EbdOCADjtnHmRQABBBBAAAErBf4zfbGuenO633u5vFxNva2vqpQvY+U8NI0AAgjETYAAMG4b3/W8BIA8B1EJEABGJU9dBBBAAAEEEEAgBYG1m/PVpv8g5Rck/LueOLO1jm5eL4VTuBQBBBBAICoBAsCo5M2qSwBo1j7i1A0BYJy2zawIIIAAAgggYLXA2c9N0KjvVvgznNBybz18WiurZ6J5BBBAIC4CBIBx2fTu5yQA5DmISoAAMCp56iKAAAIIIIAAAikKvDJuvvr95yv/rmoVymhKv74qm5eb4klcjgACCCCQbQECwGyLm1mPANDMvcShKwLAOGyZGRFAAAEEEEDACYEf12xSpwFDi83y2kUd1GX/2k7MxxAIIICAywIEgC5vN/nZCACTt+LKYAUIAIP15DQEEEAAAQQQQCBUgd8/Nlpf/LDGr3Fup0a64/hDQ63J4QgggAACmQsQAGZu6MIJBIAubNHOGQgA7dwbXSOAAAIIIIBATAUeG/qdHhg4259+7+oVNObGXsrJ4Z8UMX0kGBsBBCwRIAC0ZFEht8nf1iEDc3yJAgSAPBwIIIAAAggggIBFArOXrdMRD40s1vHHf+mqQ+tXt2gKWkUAAQTiJ0AAGL+d72piAkCeg6gECACjkqcuAggggAACCCCQhkAikVCPB4ZrwcqN/t1X9tpf1xxxYBqncQsCCCCAQLYECACzJW12HQJAs/fjcncEgC5vl9kQQAABBBBAwEmBuz/5Ws+MmufP1myvqvr8r92dnJWhEEAAAVcECABd2WRmcxAAZubH3ekLEACmb8edCCCAAAIIIIBAJAKT5q/SKU+OK1Z75PU91bBWpUj6oSgCCCCAQOkCBIClG8XhCgLAOGzZzBkJAM3cC10hgAACCCCAAAIlChQUJtT+7sFauWGrf82txxyki7rthxoCCCCAgKECBICGLibLbREAZhmccr4AASAPAwIIIIAAAgggYKHA396dobcn/+B33r5xTb39p04WTkLLCCCAQDwECADjsefSpiQALE2Ir4clQAAYliznIoAAAggggAACIQoM/nqZLnp5sl8hN0eafGtf1axcLsSqHI0AAgggkK4AAWC6cm7dRwDo1j5tmoYA0KZt0SsCCCCAAAIIIFAksDm/QK3uHKRN+QW+yf0nH6ZT2jbACAEEEEDAQAECQAOXEkFLBIARoFPyFwECQB4EBBBAAAEEEEDAUoE/vTJZ//1qmd9934Pr6plz2lo6DW0jgAACbgsQALq932SnIwBMVorrghYgAAxalPMQQAABBBBAAIEsCfx7yg+69p0ZfrUKZXM1rd8RqlguL0sdUAYBBBBAIFkBAsBkpdy+jgDQ7f2aPB0BoMnboTcEEEAAAQQQQGA3Aj9v2Kq2dw+W91uBt7+ePruNjjhkL9wQQAABBAwTIAA0bCERtUMAGBE8ZfkRYJ4BBBBAAAEEEEDAZoHTnh6n8XNX+SOc3GYfPXBKC5tHoncEEEDASQECQCfXmvJQBIApk3FDQAJ8B2BAkByDAAIIIIAAAghEIfD86Hm68+Ov/dJ7VCqrSbf0UZm83CjaoSYCCCCAQAkCBIA8Gp4AASDPQVQCBIBRyVMXAQQQQAABBBAIQGDRqo3qdt+wYie9eUlHddyvVgCncwQCCCCAQFACBIBBSdp9DgGg3fuzuXsCQJu3R+8IIIAAAggggICk3z0ySt/8uNa3uLBrY/U79mBsEEAAAQQMEiAANGgZEbZCABghfsxLEwDG/AFgfAQQQAABBBCwX+ChQbP1yJDv/EEa1Kyokdf3VE4O/8ywf7tMgAACrggQALqyyczm4G/mzPy4O30BAsD07bgTAQQQQAABBBAwQuCrJWt0zKOji/Xy2VXddFC9akb0RxMIIIAAAhIBIE+BJ0AAyHMQlQABYFTy1EUAAQQQQAABBAISSCQS6vqPYVq8epN/4jV9m+rK3gcEVIFjEEAAAQQyFSAAzFTQjfsJAN3Yo41TEADauDV6RgABBBBAAAEEdhK4/cOv9OLY+f6fHlq/mj7+SzecEEAAAQQMESAANGQREbdBABjxAmJcngAwxstndAQQQAABBBBwR2Ds9yt0xjMTig005sZeql+jojtDMgkCCCBgsQABoMXLC7B1AsAAMTkqJQECwJS4uBgBBBBAAAEEEDBTYFtBodrcNVhrNuX7Dd7x+0N0bud9zWyYrhBAAIGYCRAAxmzhJYxLAMhzEJUAAWBU8tRFAAEEEEAAAQQCFrjmrel6b9pi/9Qu+9fSaxd1DLgKxyGAAAIIpCNAAJiOmnv3EAC6t1NbJiIAtGVT9IkAAggggAACCJQi8PnMH3Xpq1P9q/JyczT11r6qXqksdggggAACEQsQAEa8AEPKEwAasogYtkEAGMOlMzICCCCAAAIIuCmwces2tbpzkLZsK/QHfPjUljqhVX03B2YqBBBAwCIBAkCLlhViqwSAIeJy9G4FCAB5QBBAAAEEEEAAAYcELnxxkobMWu5PdHTzvfTEmW0cmpBREEAAATsFCADt3FvQXRMABi3KeckKEAAmK8V1CCCAAAIIIICABQJvTVqoG/79pd9ppXJ5mtqvryqUzbOge1pEAAEE3BUgAHR3t6lMRgCYihbXBilAABikJmchgAACCCCAAAIRC6xYv0Xt7h6sRGJHI8+f11a9mtWNuDPKI4AAAvEWIACM9/63T08AyHMQlQABYFTy1EUAAQQQQAABBEISOPn/xmrygp/9009v30ADTjwspGociwACCCCQjAABYDJK7l9DAOj+jk2dkADQ1M3QFwIIIIAAAgggkKbA0yO/1z2fzvLvrl2lnCbc3EfebwXmhQACCCAQjQABYDTuplXlb2LTNhKffggA47NrJkUAAQQQQACBmAjMW7FBPR8YXmzaf/+5k9o0qhkTAcZEAAEEzBMgADRvJ1F0RAAYhTo1PQECQJ4DBBBAAAEEEEDAQYEjHhqh2cvW+5P96fD9dNPvDnJwUkZCAAEE7BAgALRjT2F3SQAYtjDnlyRAAMizgQACCCCAAAIIOChw/39n6fFh3/uTNa5dWUOvPVw5OfzTw8F1MxICCFggQABowZKy0CJ/C2cBmRK7FCAA5MFAAAEEEEAAAQQcFJixaLWOf3xMsckGX9Nd++9Z1cFpGQkBBBAwX4AA0PwdZaNDAsBsKFNjVwIEgDwXCCCAAAIIIICAgwKFhQl1vneolq7d7E/3t6MO1GU99ndwWkZCAAEEzBcgADR/R9nokAAwG8rUIADkGUAAAQQQQAABBGIkcOsHX+rV8Qv9iVs2qKEPLu8SIwFGRQABBMwRIAA0ZxdRdkIAGKV+vGvzHYDx3j/TI4AAAggggIDDAiNn/6Rznp9YbMIJN/dW3WoVHJ6a0RBAAAEzBQgAzdxLtrsiAMy2OPW2CxAA8iwggAACCCCAAAKOCmzdVqg2/Qdp3ZZt/oR3nXCozurYyNGJGQsBBBAwV4AA0NzdZLMzAsBsalPrtwIEgDwPCCCAAAIIIICAwwJ/eWOaPpqxxJ/w8KZ19NIF7R2emNEQQAABMwUIAM3cS7a7IgDMtjj1tgsQAPIsIIAAAggggAACDgt44Z8XAm5/lc3L0dR+fVW1QlmHp2Y0BBBAwDwBAkDzdhJFRwSAUahT0xMgAOQ5QAABBBBAAAEEHBZYtzlfrfsPUn5Bwp/yX6e30nEt9nZ4akZDAAEEzBMgADRvJ1F0RAAYhTo1CQB5BhBAAAEEEEAAgRgIeL8IxPuFINtfv2+xtx49vVUMJmdEBBBAwBwBAkBzdhFlJwSAUerHuzbfARjv/TM9AggggAACCMRA4NXxC3TrBzP9SauWL6Mp/fqqXJncGEzPiAgggIAZAgSAZuwh6i4IAKPeQHzrEwDGd/dMjgACCCCAAAIxEVi2drM63DOk2LQvX9Be3ZvWiYkAYyKAAALRCxAARr8DEzogADRhC/HsgQAwnntnagQQQAABBBCImcAJj4/R9EWr/anP7thI/U84NGYKjIsAAghEJ0AAGJ29SZUJAE3aRrx6IQCM176ZFgEEEEAAAQRiKvD4sDm6/7/f+tPvVa2Cxt7YS7m5/FMkpo8EYyOAQJYFCACzDG5oOf7WNXQxMWiLADAGS2ZEBBBAAAEEEEBgzvJ16vPgyGIQ/7m8i1o0qAEOAggggEAWBAgAs4BsQQkCQAuW5GiLBICOLpaxEEAAAQQQQACB3wokEgn1/ucIzV2xwf/jy3s20fVHNgMKAQQQQCALAgSAWUC2oAQBoAVLcrRFAkBHF8tYCCCAAAIIIIDAzgIDPv1GT42c6/9x07pVNPDqw4FCAAEEEMiCAAFgFpAtKEEAaMGSHG2RANDRxTIWAggggAACCCCws8CUBat00v+NK/bHw67roca1K4OFAAIIIBCyAAFgyMCWHE8AaMmiHGyTANDBpTISAggggAACCCCwK4GCwoQ63DNEK9Zv8b9889HNdEn3JoAhgAACCIQsQAAYMrAlxxMAWrIoB9skAHRwqYyEAAIIIIAAAgiUJHDjv7/Qm5MW+V9ut+8eeufSzoAhgAACCIQsQAAYMrAlxxMAWrIoB9skAHRwqYyEAAIIIIAAAgiUJDB01jJd8OJk/8s5OdKkW/qodpXyoCGAAAIIhChAABgirkVHEwBatCzHWiUAdGyhjIMAAggggAACCOxOYHN+gVr3H6SNWwv8y/5xUnOd2q4hcAgggAACIQoQAIaIa9HRBIAWLcuxVgkAHVso4yCAAAIIIIAAAqUJXPbaFH365VL/sj4H7alnz21X2m18HQEEEEAgAwECwAzwHLqVANChZVo2CgGgZQujXQQQQAABBBBAIFOB96f9oKvfmuEfU65Mrqb166vK5ctkejT3I4AAAgiUIEAAyKPhCRAA8hxEJUAAGJU8dRFAAAEEEEAAgYgE1mzMV+u7Bsn7rcDbX0+e1VpHHVovoo4oiwACCLgvQADo/o6TmZAAMBklrglDgAAwDFXORAABBBBAAAEEDBc489nxGjNnpd/lia3q68FTWxreNe0hgAAC9goQANq7uyA7JwAMUpOzUhEgAExFi2sRQAABBBBAAAFHBF4cM0+3f/S1P031imU15dY+KpOX68iEjIEAAgiYJUAAaNY+ouqGADAqeeoSAPIMIIAAAggggAACMRRYvHqTutw7tNjkr1/cQZ2b1I6hBiMjgAAC4QsQAIZvbEMFAkAbtuRmjwSAbu6VqRBAAAEEEEAAgVIFjv3XKM1cvNa/7rzO++r23x9S6n1cgAACCCCQugABYOpmLt5BAOjiVu2YiQDQjj3RJQIIIIAAAgggELjAI4O/00ODZ/vn1q9RUaNv6KmcHP55Ejg2ByKAQOwFCABj/wj8AsDfsDwHUQkQAEYlT10EEEAAAQQQQCBigW9+XKvfPTKqWBefXNlVh+xdPeLOKI8AAgi4J0AA6N5O05mIADAdNe4JQoAAMAhFzkAAAQQQQAABBCwUSCQS6n7/MC1atcnv/qreB+jqvk0tnIaWEUAAAbMFCADN3k+2uiMAzJY0dXYWIADkmUAAAQQQQAABBGIscOdHX+v5MfN8gYPrVdOnV3WLsQijI4AAAuEIEACG42rbqQSAtm3MnX4JAN3ZJZMggAACCCCAAAIpC4yfu1KnPT2+2H2j/tZTDWpWSvksbkAAAQQQKFmAAJCnwxMgAOQ5iEqAADAqeeoigAACCCCAAAIGCGwrKFS7uwfr5435fje3HXuwLuja2IDuaAEBBBBwR4AA0J1dZjIJAWAmetybiQABYCZ63IsAAggggAACCDggcN07M/TulB/8STrtV0tvXNLRgckYAQEEEDBHgADQnF1E2QkBYJT68a5NABjv/TM9AggggAACCCCg/361VH96ZYovkZebo1uPOUh/bNtAlcuXQQgBBBBAIAABAsAAEB04ggDQgSVaOgIBoKWLo20EEEAAAQQQQCAogR9+3qiu/xj2P8dVrVBGZ3RoqPM676t61SsGVY5zEEAAgVgKEADGcu3/MzQBIM9BVAIEgFHJUxcBBBBAAAEEEDBEYOX6LWpz1+ASuymTm6NjDquni7rup+b7VDeka9pAAAEE7BIgALRrX2F1SwAYliznliZAAFiaEF9HAAEEEEAAAQRiIPDjmk264vVpmrLg591O26FxTV3UbT/1brancnP5Z0wMHg1GRACBgAQIAAOCtPwY/ua0fIEWt08AaPHyaB0BBBBAAAEEEAhSIJFIaOK8VXpm1DwNmbVMiUTJpzeuXVkXdNlXJ7XZR5XK8TmBQe6BsxBAwE0BAkA395rqVASAqYpxfVACBIBBSXIOAggggAACCCDgkMDcn9brhTHz9c6URdqcX1jiZDUqldWZHRrqnE77qm61Cg4JMAoCCCAQrAABYLCetp5GAGjr5uzvmwDQ/h0yAQIIIIAAAgggEJrAzxu26vWJC/XS2Plavm5LiXXK5uXouBZ768KujXXI3nxOYGgL4WAEELBWgADQ2tUF2jgBYKCcHJaCAAFgClhcigACCCCAAAIIxFVg67ZCfTRjiZ4dPU/f/Lh2twydm9TSRd0aq0dTPicwrs8LcyOAwP8KEADyVHgCBIA8B1EJEABGJU9dBBBAAAEEEEDAQgHvcwLHfb/ylyBw6Kzlu52gSZ3KurDrfjqxdX1VKJtn4bS0jAACCAQnQAAYnKXNJxEA2rw9u3snALR7f3SPAAIIIIAAAghEJjBn+Xo9N3qe3pv6g7ZsK/lzAmtWLqezOjTUWZ0aac+qfE5gZAujMAIIRCpAABgpvzHFCQCNWUXsGiEAjN3KGRgBBBBAAAEEEAhWYOX6LXptwkK9PG6+VqzfWuLh5fJydXzLvXVRt/104F5Vg22C0xBAAAHDBQgADV9QltojAMwSNGX+R4AAkIcCAQQQQAABBBBAIBCBzfkF+nDGEj03ap6+XbZut2d2O6D2L0Fg9wNqKyeHfw4FsgAOQQABowUIAI1eT9aa42+8rFFTaCcBAkAeCQQQQAABBBBAAIFABbzPCRz13YpfPidw5Oyfdnt207pVfvnNwce35HMCA10ChyGAgHECBIDGrSSShggAI2GnqCQCQB4DBBBAAAEEEEAAgdAEvl26Ts+Pnqf3py3W1oKSPyewdpVyOrvjvjqrY0PVqlI+tH44GAEEEIhKgAAwKnmz6hIAmrWPOHVDABinbTMrAggggAACCCAQkcBP67bo1fEL9Mr4BVq1YTefE1gmVye1rv/LdwXuvyefExjRuiiLAAIhCBAAhoBq4ZEEgBYuzZGWCQAdWSRjIIAAAggggAACNgh4nxPofTfgs6Pm6vufNuy25R4H1tHF3fZT5ya1+JxAG5ZLjwggsFsBAkAeEE+AAJDnICoBAsCo5KmLAAIIIIAAAgjEWKCwMKER3/30yy8MGT1nxW4lmu1V9ZdfGHJci3oqXyYvxmqMjgACNgsQANq8veB6JwAMzpKTUhMgAEzNi6sRQAABBBBAAAEEAhb4eslaPTd6nj6csVj5BYkST69TtbzO7dRIZ3ZopD0qlwu4C45DAAEEwhUgAAzX15bTCQBt2ZR7fRIAurdTJkIAAQQQQAABBKwUWL52s14et0CvTlig1RvzS5yhQtlcndxmH13QpbH2q1PFyllpGgEE4idAABi/ne9qYgJAnoOoBAgAo5KnLgIIIIAAAggggMAuBTZtLfj/9u4EXLKzrBP4v7uzx4SAIRCydNIgY5CISBJDFnRQQEBUHEaRBwQkiI6OjuOGODOKGw44PjqII8imMDIoOAqKiCAjWQhJQBBEjJCdhCwQspKll3ne26eayuXeurWcqjpV93eep5/uvnXO973f7z333lNvfec7eftHrll5evBlNw1eJ/DbTjoqLzhrR07f8QDrBDqfCBDotIACYKfTM7PgFABnRq2jVQIKgE4JAgQIECBAgACBTgrUOoF/96kb8trzLsuFl31hYIxf95DDc87ZJ+apJz8kB+y3tZPjERQBAptbQAFwc+e/N3oFQOfBvAQUAOclr18CBAgQIECAAIGhBT7x2VtW1gl858euzc7d668T+ODDD8pzzzghzzrt+NzvkP2Hbt+OBAgQmLaAAuC0hRejfQXAxcjTMkapALiMWTUmAgQIECBAgMCSCnzulrvyxguuyB9/6MrcetfOdUd58P7b8r2nHJvnn3liTjjy0CXVMCwCBBZJQAFwkbI1vVgVAKdnq+XBAgqAzhACBAgQIECAAIGFE7jj7p1524evyevPvzxXfv7OdePfsiV5wkkPygsftyOnbL+/dQIXLtMCJrA8AgqAy5PLSUaiADiJnmMnEVAAnETPsQQIECBAgAABAnMV2LV7T977z9fndedenouuGLxO4KOOvV9ecPaOPPmRD87+26wTONfE6ZzAJhRQANyESV9jyAqAzoN5CSgAzktevwQIECBAgAABAq0KfPTqL66sE/iuj1+XKgyutz3kfgfleWeekGeednwOP8g6ga0mQWMECKwroADo5CgBBUDnwbwEFADnJa9fAgQIECBAgACBqQh89otfyh9ecEXe8qGrctvd668TeOgB2/J9px6f5595Qo57wCFTiUWjBAgQ6AkoADoXFACdA/MUUACcp76+CRAgQIAAAQIEpiZw+90789aLr84bzr8819z8pXX72bol+fZHPjgvOGtHHrP9/lOLR8MECGxuAQXAzZ3/3ujNAHQezEtAAXBe8volQIAAAQIECBCYicDOXbvznk9en9eee1k+ctUXB/b56OOPyAvP3pEnPuJB2c86gTPJj04IbBYBBcDNkunB41QAdB7MS0ABcF7y+iVAgAABAgQIEJi5wIevvDmvP+/y/PUnrsuAZQJz7P0PzvPPPDHfd+px+aoD95t5nDokQGD5BBQAly+n44xIAXAcNce0IaAA2IaiNggQIECAAAECBBZK4Oov3Jk3nH9F3nrxVbnjnl3rxn7Ygfvl+7/p+Dz3jBNyzBEHL9QYBUuAQLcEFAC7lY95RaMAOC95/SoAOgcIECBAgAABAgQ2rcCtd92bt160d53Aa2+5a12HbVu35CknH51zzjoxjzruiE3rZeAECIwvoAA4vt0yHakAuEzZXKyxKAAuVr5ES4AAAQIECBAgMAWBe3ftzrs/8bmVdQI/ds0tA3s49YT755yzd+TbTnpQqjBoI0CAwDACCoDDKC3/Pn5rLH+OuzpCBcCuZkZcBAgQIECAAAECMxfYs2dPLrny5pVCYD04ZM+e9UPY/tWH5AfPPDHPeMyxOdQ6gTPPlQ4JLJqAAuCiZWw68SoATsdVqxsLKABubGQPAgQIECBAgACBTShw5efvWFkn8E8uuTp3Dlgn8PCD9suzvml7nnvG9hx9P+sEbsJTxZAJDCWgADgU09LvpAC49Cnu7AAVADubGoERIECAAAECBAh0QeCWO+/NH190Vd54weW5/ta71w1pv61b8rRHPSQvOOvEPPKY+3UhdDEQINAhAQXADiVjjqEoAM4Rf5N3rQC4yU8AwydAgAABAgQIEBhO4J6du/Ouj1+XPzj3svzTtbcOPOj0HQ/IOWftyOO/9qhstU7gcMD2IrDkAgqAS57gIYenADgklN1aF1AAbJ1UgwQIECBAgAABAsssUOsEfujyL6ysE/jef75h4FB3HHlonn/WiXnGNx6bgw/YtswsxkaAwAYCCoBOkRJQAHQezEtAAXBe8volQIAAAQIECBBYeIHLbrw9rz//8rztw9fkrnt3rzueIw7ZP8/+pu35gcduz1GHH7Tw4zYAAgRGF1AAHN1sGY9QAFzGrC7GmBQAFyNPoiRAgAABAgQIEOiwwM133NM1Z1S8AAAgAElEQVSsE3hFbrxt/XUC99+2Jd/5qGNW1gl8xEMO7/CIhEaAQNsCCoBtiy5mewqAi5m3ZYhaAXAZsmgMBAgQIECAAAECnRC4e+euvPNj163cHvypz902MKazHnZkXnD2ifnmr3mgdQI7kT1BEJiugALgdH0XpXUFwEXJ1PLFqQC4fDk1IgIECBAgQIAAgTkL1DqBF3zm8yuFwPf/y40Do3nYUV+1MiPw6Y8+Jgftb53AOadO9wSmJqAAODXahWpYAXCh0rVUwSoALlU6DYYAAQIECBAgQKBrAp++4ba87rwr8mcfuSZ371x/ncAHHHpAnn369jzn9O154GEHdm0YmzqeKuju2r0nO3fvyX5bt2S/bVs3tYfBjyegADie27IdpQC4bBldnPEoAC5OrkRKgAABAgQIECCwwAKfv/3uvPnCq/KmC6/ITbffs+5IDthva57+Dces3B788AcdNtcRV+Gril5V/OoVwPb+vXvv/3c1r/UKZM3/972+e092N4WzLx+/e1+bK8f3Fdd27ep7baNj13t9iJh641lzTDXWJq7+sfcnYuuWpPK0/7atOXC/rTlg29bs3/t729aV11b+9P7d9/rer2/Zd/ya+67RRvX15Ta35IBt25o29ra1Es/WrW4nn+t3zODOFQA7nJwZhqYAOENsXd1HQAHQCUGAAAECBAgQIEBghgJ33bsr7/jotXnteZfl0utvH9jz4x7+wJx09GH7ClL7Cla7eoW5LxfM1i3S9RXwvqLg1bSzu1fo29fu3iLf7j0zhNFVKwL1oJn+YuG+ImVTsOwVEXsFywP2q2JiU0BcXXhc/fW+1zcsSK7at2ZObtmyuUsfCoCtnOIL38jm/i5Y+PQt9AAUABc6fYInQIAAAQIECBBYVIGaXfeBf71pZZ3Ac//1pkUdhrgJDCVQtb+VQuMaxcZeMfHAlZmSaxQk151J+eXZls94zLErhc8ubwqAXc7O7GJTAJydtZ7uK6AA6IwgQIAAAQIECBAgMGeBT33u1rz+vMvz5/9wbe7Ztf46gXMOU/cEOitw6a8+eeU26C5vCoBdzs7sYlMAnJ21nhQAnQMECBAgQIAAAQIEOilww2135c0fvDJvuvDK3HznvZ2McVBQ27ZuycqfLVtWHpaxbVvzdz04Y+vWldfq61ubv3v/3/t38/q2LdnaO37lgRvV5ta97a17/Aavb7vv670497a59murY+qNq9YFvGfn7ty7a/dKsbb+ve/v3tebv+uhL/XavTv35J5du5rj9qw8DGZfG31t1ddX2l31+j27qs9de9tq1jhcuJNjygFf8gvfmiMPO2jKvUzWvALgZH7LcrQC4LJkcvHGYQbg4uVMxAQIECBAgAABAksuUOsE/sVHP5uLr7h55WEb9y2U7S1a1d2OX1G82ldw25ptW5JtaxS+eoW2r2zzvsW2lSLcSvFt+CLeZl/jbVanZZ0T9yk8rhQZv7Ig2V9M7BUpq4DYX0xcXYzsFSbvXtVmr619Rcp9hc37FkFnZdDfT91WfOmvPXkeXY/UpwLgSFxLu7MC4NKmtvMDUwDsfIoESIAAAQIECBAgQIAAge4L1LqWVWDcV3jsmyG5VjFyb7Fx7+zImiVZRcf+mZH7ipH9MyNXZkHu3a9XjKwi9f8+5/TOAykAdj5FMwlQAXAmzGN1sj3Jjyd5apLjktyd5DNJ/iTJq5LcOVarX3nQ9yd5fpKvT3JEkuuTnNv08cGW+lirGQXAKeJqmgABAgQIECBAgAABAgQIlIACoPOgBBQAu3kePC3Jm5Mcvk54lzaFwU9PEP7BSd6W5CnrtFErAP9ykpdO0MegQxUApwSrWQIECBAgQIAAAQIECBAg0BNQAHQuKAB28xx4dJLzk1SB7vYkL0vy/ub/z0zywibsKgKekuS2MYfxliTVXm3V/u8kuTbJyUlekuShzWsvSvKaMftQAJwCnCYJECBAgAABAgQIECBAgMCwAgqAw0ot935mAHYvvx9IcnaSnUkel2T1bbg/k+TlTdg1O++XxhjC45O8rznunUmenmRXXztHJvlwkuOTfDHJjiQ3j9GPAmDLaJojQIAAAQIECBAgQIAAAQKjCCgAjqK1vPsqAHYrt6cl+VAT0quT/PAa4W1N8okkJzXFuaOS3DviMN6VpB5VVEXGE2tJgDWOr9mBNUuwtp9N8ooR+9hod7cAbyTkdQIECBAgQIAAAQIECBAgMKGAAuCEgEtyuAJgtxL560l+vgmpHiXUKwaujvLFza3B9fUnJXnPCMM4LMlNSQ5I8u6mELjW4fX6jc06hDUL8YwR+hhmVwXAYZTsQ4AAAQIECBAgQIAAAQIEJhBQAJwAb4kOVQDsVjJ7t//e0TyRt2borbU9NskFzQv1oI5fHGEY/bf/VrHxNwYc+zdJntjMFDxkjJmGg8JSABwhaXYlQIAAAQIECBAgQIAAAQLjCCgAjqO2fMcoAHYrpzXjrtbf+1iSbxgQ2v2TfKF5/U+TfO8Iw/ixJK9s9q+1//58wLH1YJAfb17/uiSfHKGfjXZVANxIyOsECBAgQIAAAQIECBAgQGBCAQXACQGX5HAFwO4k8qAkX2rC+ask37FBaPWE4EOTXJikZgQOu9WMv59rdj41ySUDDvzpvrX/vj1JzQgcdqsC36DtwUkurh2uvvrqHHvsRrsP2639CBAgQIAAAQIECBAgQIAAgZ6AAqBzoQQUALtzHjwwyQ1NOG9NUg/hGLRdn6QeAFIPBDl5hGG8Ksl/aPavB4l8asCxP5Lk95rXn5Hk7SP0s2fYfRUAh5WyHwECBAgQIECAAAECBAgQGE1AAXA0r2XdWwGwO5k9LslVTThvSvIDG4RW+9Yxn0nysBGG8bokP9js/9Aklw04tvar/Wt7TpI3j9CPAuAIWHYlQIAAAQIECBAgQIAAAQLTEFAAnIbq4rWpANidnC3bDMCN7ul1C3B3zj2RECBAgAABAgQIECBAgMCSCigALmliRxyWAuCIYFPcfdnWANyIykNANhLyOgECBAgQIECAAAECBAgQmFBAAXBCwCU5XAGwW4m8KclXewpwt5IiGgIECBAgQIAAAQIECBAgsKgCCoCLmrl241YAbNdz0tY+kOTsJHckOSLJznUarKf+XtC89stJfnGEjh+f5H3N/j+fpJ4KvN5WT/19YhPHIUnuHaGfjXY1A3AjIa8TIECAAAECBAgQIECAAIEJBRQAJwRcksMVALuVyF9PUkW52k5P8qF1wntxkpc1rz0pyXtGGMZhSWqm4QFJ3p3kyescW6/fmOTwJB9McsYIfQyzqwLgMEr2IUCAAAECBAgQIECAAAECEwgoAE6At0SHKgB2K5mn9RX9Xp3kh9cIb2uSTyQ5KckXkxw1xsy8dzWFv5pheGKSa9bo55lJ3tJ8/WeTvKJlKgXAlkE1R4AAAQIECBAgQIAAAQIEVgsoADonSkABsHvnQe824CrOPa6Zfdcf5c8keXnzhZcm+aVVQ3hekjcMeL1e6r8N+B1JvifJrr52jkzy4STHN0XGHUlubplKAbBlUM0RIECAAAECBAgQIECAAAEFQOfAWgIKgN07Lx6d5PwkBye5PUndFvz+5v81K++HmpAvTXJKktvGKADWITW7r9qrrdr/7STXJjk5yS8keWjz2ouSvGYKTAqAU0DVJAECBAgQIECAAAECBAgQ6BcwA9D5UAIKgN08D56W5M3N+ntrRVjFv6cm+fQaLw4zA7AOqwLj25I8ZR2C3Ul+ZY0Zhm2JKQC2JakdAgQIECBAgAABAgQIECCwjoACoFNDAbDb58D2JD/RFPqqWHZPU/D70yS/m+TOdcIftgDYO/xZSeqYRzVPHr4+yblNH/Xwj2ltCoDTktUuAQIECBAgQIAAAQIECBBoBBQAnQoKgM6BeQooAM5TX98ECBAgQIAAAQIECBAgsCkEFAA3RZo3HKRbgDckssOUBBQApwSrWQIECBAgQIAAAQIECBAg0BNQAHQulIACoPNgXgIKgPOS1y8BAgQIECBAgAABAgQIbBoBBcBNk+qBA1UAdB7MS0ABcF7y+iVAgAABAgQIECBAgACBTSOgALhpUq0AKNWdFFAA7GRaBEWAAAECBAgQIECAAAECyySgALhM2Rx/LGYAjm/nyMkEFAAn83M0AQIECBAgQIAAAQIECBDYUEABcEOiTbGDAuCmSHMnB6kA2Mm0CIoAAQIECBAgQIAAAQIElklAAXCZsjn+WBQAx7dz5GQCCoCT+TmaAAECBAgQIECAAAECBAhsKKAAuCHRpthBAXBTpLmTg9ye5IqK7KKLLsrRRx/dySAFRYAAAQIECBAgQIAAAQIEFlnguuuuy2mnndYbwglJrlzk8Yh9PAEFwPHcHDW5wClJLp68GS0QIECAAAECBAgQIECAAAECQwqcmuSSIfe12xIJKAAuUTIXbCgKgAuWMOESIECAAAECBAgQIECAwMILKAAufArHG4AC4Hhujppc4MAkJzfN3Jhk1+RNTr2FB/fNWqwfmp+beo86mKWA/M5Sez59yfF83GfVq/zOSno+/cjvfNxn1av8zkp6fv3I8fzsZ9Gz/M5CebI+tiV5YNPEx5PcPVlzjl5EAQXARcyamOclsO/BJUmOS3LNvALR71QE5HcqrJ1qVI47lY7Wg5Hf1kk71aD8diodrQcjv62Tdq5BOe5cSloNSH5b5dQYgekIKABOx1WryyngF9ty5rU3Kvld7vzW6OR4uXMsv/K73ALLPTrfv8udX7+D5Xf5BYyQwAIIKAAuQJKE2BkBF6edScVUApHfqbB2qlE57lQ6Wg9Gflsn7VSD8tupdLQejPy2Ttq5BuW4cylpNSD5bZVTYwSmI6AAOB1XrS6ngF9sy5nX3qjkd7nzW6OT4+XOsfzK73ILLPfofP8ud379Dpbf5RcwQgILIKAAuABJEmJnBFycdiYVUwlEfqfC2qlG5bhT6Wg9GPltnbRTDcpvp9LRejDy2zpp5xqU486lpNWA5LdVTo0RmI6AAuB0XLW6nAJ+sS1nXnujkt/lzm+NTo6XO8fyK7/LLbDco/P9u9z59TtYfpdfwAgJLICAAuACJEmInRFwcdqZVEwlEPmdCmunGpXjTqWj9WDkt3XSTjUov51KR+vByG/rpJ1rUI47l5JWA5LfVjk1RmA6AgqA03HV6nIK+MW2nHntjUp+lzu/NTo5Xu4cy6/8LrfAco/O9+9y59fvYPldfgEjJLAAAgqAC5AkIRIgQIAAAQIECBAgQIAAAQIECBAYV0ABcFw5xxEgQIAAAQIECBAgQIAAAQIECBBYAAEFwAVIkhAJECBAgAABAgQIECBAgAABAgQIjCugADiunOMIECBAgAABAgQIECBAgAABAgQILICAAuACJEmIBAgQIECAAAECBAgQIECAAAECBMYVUAAcV85xBAgQIECAAAECBAgQIECAAAECBBZAQAFwAZIkRAIECBAgQIAAAQIECBAgQIAAAQLjCigAjivnOAIECBAgQIAAAQIECBAgQIAAAQILIKAAuABJEiIBAgQIECBAgAABAgQIECBAgACBcQUUAMeVcxwBAgQIECBAgAABAgQIECBAgACBBRBQAFyAJAmRAAECBAgQIECAAAECBAgQIECAwLgCCoDjyjlu0QWOSnJa8+fUJPXnq5tB/WGS5404wCcn+aGmnQcmuTHJxUlek+SvR2zL7u0ItJHjQ5J8e5InJDklycOSfFWSW5NcmuRvkvx+ks+1E7JWRhBoI7/rdVd5/0SSE5sdrkxywgix2XVygWnk99uSPDvJWUmOTrIzyfVJ/jHJ+5K8Kcntk4euhSEE2sxvfW/+SJLK70OTHJrktiSfSvLu5mf0DUPEZJd2Bep35lOa77dHJKlro3uTXJvk/CSvS3LeCF26zhoBawa7tpFf11gzSNSYXbSRX9dYY+I7jMA0BRQAp6mr7S4L7BkQ3CgFwK1Nke8FA9p7bZIXJdndZZAljG3SHH998yalCn6DtioGVvH3rUto2OUhTZrfQWP7zSQ/1beDAuDsz4Q283v/JG9I8l0bDOPRST46+6Fuyh7byu9zkrw6ycEDFL+Q5JlJ/nZTSs9n0B9IcvYQXf9RkhcmuWfAvq6zhoCc8S5t5Nc11oyTNkJ3beTXNdYI4HYlMEsBBcBZauurSwL9bz6uamYKPLEJcJQC4MuSvLg57h+SvDzJZ5pZCD+bpN5Q1lb7vaRLAJsglklzXLOEzm2carbCXya5JMnnm5kM39O8cak3J7uSPM1sz5meVZPmd71g63u2Zu/WTJX6c1gSBcCZpnals7bye79mdt9jmiH83yRva35O1/ftcUm+Ocm/a76HFQBnk+s28ntmknqjWj+D6wO2+t39F80Ms+OTPLfJaY3oS0kemeSy2Qxv0/fy6eY6qGb7/Wnzu7SutbYleWzzAcsxjdJbkjxrgJjrrO6dTm3k1zVW9/Lai6iN/LrG6m5+RbbJBRQAN/kJsImH/9LmTX690a9bwOoWostHLAA+PMk/JdmvKQw9rnmT0WOtWxv+vrl1tG41OylJ/VK1zUZg0hyfkeQnklQ7n1wn5JpRVAWF+llahd+vWVW4mM1IN2cvk+Z3LbV6c/qhJFUs+m9JambvdgXAuZxgbeW3ZhjVLLG7k3xvknesM5r6Hq78189q2/QF2shvfSjz1CbUH03ye2uE/T+S/Ofm669K8mPTH5oemg/M6nvv7c0HZKtRjmxm2Nd1VG1VhK9i7urNdVY3T6f63ps0v66xupnbiqqN/LrG6m5+RbbJBRQAN/kJYPj7BMYpANabjVp3qLb6RPvCNTxPT/LB5uu1f71Jsc1HYJwcDxNpzSaq2UO1VeHoI8McZJ/WBdrIbxUKqmDwL0nq9qRa51EBsPVUjdXgOPntn2HyM0nq1m5bNwXGyW/d2lu3d9es7CoorbXVDNAvNi/Uz+beTNBuKmyuqL4jyTubIb8yyY+vMXzXWYt7TgyT32FG5xprGKXZ7zNOfl1jzT5PeiTwFQIKgE4KAnsFRn3zUd871yR5SHP7cM3uW2+rhcj/TZLPNrebDVr7SD6mJzBqjoeNpIq6v9vsXDOM6nYn2+wFJs1vFfpqRm89QODfJvl/Sa5QAJx9ItfpcZz8/p8k35fkliQPTnJXZ0YjkNUC4+S3HthS36+1NEM9yGu9rR7KVQXCerDPyeg7I1C56z105119szl7AbrO6kyqxgpko/wO26hrrGGlZrvfqPl1jTXb/OiNwLoCCoBODgJ7BUZ987GjueWzjq0FyH94AGS9Xg+JqK2O691qzH62AqPmeNjoep9o1v41E/DPhj3Qfq0KTJrfv2qeWFlPgv2BJjIFwFZTNFFjo+b3gKbwd1Cz5t+/b3qv23zrg5v6u57erSg4UVpaO3jU/FbHH07yjRvMADy8OQ9q/7od9RmtRayhSQUe0OSu2qmZgN+5qkHXWZMKz/f4jfI7bHSusYaVmu1+o+bXNdZs86M3AusKKAA6OQjsFRj1zUf/1PefTPLbAyDr9d9qXq/1iuqTbtvsBUbN8bAR1qLzvTcuj0jyz8MeaL9WBSbJbz0htBaiv7mZrVszhmpTAGw1RRM1Nmp+a0bYRU2Pv9j8jP7l5sEQRzRfryeP1rpjv9bM+JwoQAdPJDBqfquzenrsa5peazmO318jglck+enm609I8t6JonRwmwJP7/vArB6g9nOrGned1ab27NvaKL/DRuQaa1ip2e43Sn5dY802N3ojMFBAAdAJQmCvwKhvPmrG3/9q8GpmSa1Rst5WMw56t4XWcTUj0DZ7gVFzPEyEj2pmodRsoo8368YNc5x92hcYN7+1hlgVbR+U5EV9BYWKUAGw/TyN2+Ko+a0nwL6x6aweOFFPGa2H9Ky11bIMP5/kv48bnOMmFhg1v9Vh/dx9fTNjt54CXP+uh7xcl6SeAlwPf/nuJrIq8v6XiaPUQFsC9eTmWh/5tKbBU5rfpf3tu85qS3v27QyT32Gico01jNLs9xklv66xZp8fPRIYKKAA6AQhsFdg1DcftaB8fWJd25OTvHsAZL3em/VXMxHqIQO22QuMmuONIjwwyXnNU55r35oF2FvQfKNjvd6+wLj5fW3ztN96M3rmqqc4KwC2n6dxWxw1v/0zr+s237oVuH5O19Od/zFJ3Rpat+z/RpJ6UERtVSyq2Sa22QuMmt/+COtDtpckefQaYb8/ya+b+Tf7hG7Q40/1PZSnls3oPUir/zDXWZ1L29ABDZPfjRpzjbWR0PxeHyW/rrHmlyc9E1hTQAHQiUFgr8Cobz7+a5K6nay2b03ydwMgH5/kfc3rddyvQp+LwKg53ijIP0hyTrPTHyZ53kYHeH2qAuPk93HNrZ+7mqeDVmGof1MAnGrKRmp81PzWbK9f6evhb5sPayrX/Vs9Kfjvk9SMhpoJ+nWrisAjBWnnsQVGzW+vo3oAV83crA/a9luj9yr+/nlzG3A9iMs2f4Fvbgqyla8bmgez1N+rN9dZ88/VOBEMm9+N2naNtZHQfF4fJb+useaTI70SGCigAOgEIbBXYNQ3Hz6ZXrwzZ9QcDxph3S5Ys0pqu7h5auwdi0eyVBGPmt+aXfCxZs2/mpXbWyesH0UBsDunyKj5rXzW+m+9rR4W8Q/rDKeWaOg9HKJuOVtdCO6OwvJGMmp+S+LsZtZ1zeC8srnFtwq9X2hu6a9Z2VUErsXqr03yxOZJ38ur2P2RVYH93CR1W2AVZ5/UrMO5VuSus7qfz9URjpJf11jLnV/XWIuXXxFvEgEFwE2SaMPcUGDUNx/WptmQtHM7jJrj9QZQ68T1Fpv/VPMm9KbOjXbzBTRqfmsGb80wuTpJzSJaq4CrANid82jU/PZ/n9ZDXY4aMJSayVuzTWqrf7+uO8PeNJGMmt96c/mZJMc0T3Ou23/rqc5rFSQuaW4Br6cG11pztvkInNgsm1FP4a6ZuHXb76Bb7l1nzSdP4/Y6an5dY40rPZ/jRs2va6z55EmvBDYUUADckMgOm0Rg1Dcfnk63eCfGqDlea4Tfn+TNze2CNeOkbh+8ZvEoljLiUfN7d5IDkrwhyXvWEXllkiOTVIH3Pzb71K1qg275X0rcDgxq1Pw+JclfNXHXzL+aAbjeVrOQeuu41uzeWhfQNluBUfP7Xc2tvRXlL/TNyF4r6v5bCb+hmfk729HprYp+NfNvR3OLfS2Z8UcbsLjOWpzzZpz8usZa7vy6xlqc/Ip0kwkoAG6yhBvuugKjvvmoi9iafVBbPdW3Pqleb6vXf6h5sY67XB7mIjBqjlcHWbeTvb1ZZ6qeMlm3n/XOgbkMSKf3ERg1v/Xk13G2Wi/uW8Y50DETCYya3+3NU5yr07qlt27tXW/rLxbWbYe/OVGkDh5HYNT8vjjJy5qONnoQV/9Msmcmees4ATpmbIH6EKV+bj6iaeHHkrxqiNZcZw2B1IFdxs2va6wOJG+IEMbNr2usIXDtQmAeAgqA81DXZxcFRn3zUd87NfOrPvWs20DrFsL1tlpY/muT1ALkx1lgfm7pHzXH/YHWg15qNlHddvb5JLUI8j/NbSQ6Xktg1Py6OF2s82jU/Nboapbu8UluTXLEgJ+9NbvzfzYcz0rylsWiWYpoR81v/xqPT0vylwMU+vNbaz3WBzm22QjU+ow1Y7o3A7cKt/XQlmE211nDKM13n0ny6xprvrkbpvdJ8usaaxhh+xCYg4AC4BzQddlJgVHffNQgfi/JjzSjeWySC9cY2elJPth8vfb/0U6OfnMENU6OS+aM5hbRQ5Pc0jz1udaSsnVLYNz8DhqFNQC7k+Nx8vtbSX6yGcITmiePrjWi9/fN6qyCYa0LaZutwKj5rfXj3taEWAWlKiytt9V+tX9tj0nykdkObdP2dkjzu/PMRuDXmge1jALiOmsUrdnu20Z+XWPNNmej9NZWfl1jjaJuXwIzEFAAnAGyLhZCYNQ3HzWohyf5ZJJtSWqR8Xrc/Zf6Rntw83S7WnR8Z3P7y78uhMZyBjlOjmu9qCoO1OyhekhErRV2/nLyLPyoxsnvRoNWANxIaHavj5PfKub9S/MAiI83a3bWbMD+7dlJ3tR8oWb51rpjttkLjJrf+plcs+rrTeptSarIVDlevdXtwTU7cGuzf50Tu2c/vE3XY62v+s7mycs1+N9J8p/GUHCdNQbaDA5pK7+usWaQrDG6aCu/G3XtGmsjIa8TmIKAAuAUUDW5EAL18IaH9UVaa1y8ovl/FXheu2oUb1xnVLUGUW/mQS00XzMRal24hyb5uST1ZMLaar+XLITM8gQ5aY4rhxf0PT20ZhK9dwOeekBE/bFNX2DS/A4ToYvTYZSms09b+a01/V7ehFjFwPoZXWsCHp7ke5pZ3PUhThUG68MaH9JMJ5+rW20jv/UU73rSZG23J6mH9vxtkpuTPChJPSjkhc26rbXPc5qHOM1mhJu7l7rNur6/aqtbgKv4N+iWwHuSXOo6a2FOmjby6xqru+luI7/DjM411jBK9iHQsoACYMugmlsYgSroPXeEaNf7XqlZBfWEwR8c0NbrmoeAmHUwAngLu06a43pKYT0hdpTtpUl+aZQD7Du2wKT5HaZjF6fDKE1nnzbzWx/A1Acy6/0cr6L9d/ct1zCdEWm1X6CN/FY+6zbvnxiQ2+rz3uYDOA93md05OOr6X7VeZ80CXWtznTW7vA3bUxv5dY01rPbs92sjv8NE7RprGCX7EGhZQAGwZVDNLYxAG28++gdbT5GsJ/2emqRmE96U5OLmCcF/vTAqyxXopDl2cdrt82HS/A4zOhenwyhNZ5+281vrtNaarfX07qOT3NXMOHpHM3Os1ve0zU6gzfzWun7nNLd419Of67bgmhH46ebps68eMLtsdiPeXD1No4DgOqs751Ab+XWN1Z18ro6kjfwOMzrXWMMo2YdAywIKgC2Dao4AAQIECBAgQIAAAQIECBAgQIBAl0CvThkAAAbASURBVAQUALuUDbEQIECAAAECBAgQIECAAAECBAgQaFlAAbBlUM0RIECAAAECBAgQIECAAAECBAgQ6JKAAmCXsiEWAgQIECBAgAABAgQIECBAgAABAi0LKAC2DKo5AgQIECBAgAABAgQIECBAgAABAl0SUADsUjbEQoAAAQIECBAgQIAAAQIECBAgQKBlAQXAlkE1R4AAAQIECBAgQIAAAQIECBAgQKBLAgqAXcqGWAgQIECAAAECBAgQIECAAAECBAi0LKAA2DKo5ggQIECAAAECBAgQIECAAAECBAh0SUABsEvZEAsBAgQIECBAgAABAgQIECBAgACBlgUUAFsG1RwBAgQIECBAgAABAgQIECBAgACBLgkoAHYpG2IhQIAAAQIECBAgQIAAAQIECBAg0LKAAmDLoJojQIAAAQIECBAgQIAAAQIECBAg0CUBBcAuZUMsBAgQIECAAAECBAgQIECAAAECBFoWUABsGVRzBAgQIECAAAECBAgQIECAAAECBLokoADYpWyIhQABAgQIECBAgAABAgQIECBAgEDLAgqALYNqjgABAgQIECBAgAABAgQIECBAgECXBBQAu5QNsRAgQIAAAQIECBAgQIAAAQIECBBoWUABsGVQzREgQIAAAQIECBAgQIAAAQIECBDokoACYJeyIRYCBAgQIECAAAECBAgQIECAAAECLQsoALYMqjkCBAgQIECAAAECBAgQIECAAAECXRJQAOxSNsRCgAABAgQIECBAgAABAgQIECBAoGUBBcCWQTVHgAABAgQIECBAgAABAgQIECBAoEsCCoBdyoZYCBAgQIAAAQIECBAgQIAAAQIECLQsoADYMqjmCBAgQIAAAQIECBAgQIAAAQIECHRJQAGwS9kQCwECBAgQIECAAAECBAgQIECAAIGWBRQAWwbVHAECBAgQIECAAAECBAgQIECAAIEuCSgAdikbYiFAgAABAgQIECBAgAABAgQIECDQsoACYMugmiNAgAABAgQIECBAgAABAgQIECDQJQEFwC5lQywECBAgQIAAAQIECBAgQIAAAQIEWhZQAGwZVHMECBAgQIAAAQIECBAgQIAAAQIEuiSgANilbIiFAAECBAgQIECAAAECBAgQIECAQMsCCoAtg2qOAAECBAgQIECAAAECBAgQIECAQJcEFAC7lA2xECBAgAABAgQIECBAgAABAgQIEGhZQAGwZVDNESBAgAABAgQIECBAgAABAgQIEOiSgAJgl7IhFgIECBAgQIAAAQIECBAgQIAAAQItCygAtgyqOQIECBAgQIAAAQIECBAgQIAAAQJdElAA7FI2xEKAAAECBAgQIECAAAECBAgQIECgZQEFwJZBNUeAAAECBAgQIECAAAECBAgQIECgSwIKgF3KhlgIECBAgAABAgQIECBAgAABAgQItCygANgyqOYIECBAgAABAgQIECBAgAABAgQIdElAAbBL2RALAQIECBAgQIAAAQIECBAgQIAAgZYFFABbBtUcAQIECBAgQIAAAQIECBAgQIAAgS4JKAB2KRtiIUCAAAECBAgQIECAAAECBAgQINCygAJgy6CaI0CAAAECBAgQIECAAAECBAgQINAlAQXALmVDLAQIECBAgAABAgQIECBAgAABAgRaFlAAbBlUcwQIECBAgAABAgQIECBAgAABAgS6JKAA2KVsiIUAAQIECBAgQIAAAQIECBAgQIBAywIKgC2Dao4AAQIECBAgQIAAAQIECBAgQIBAlwQUALuUDbEQIECAAAECBAgQIECAAAECBAgQaFlAAbBlUM0RIECAAAECBAgQIECAAAECBAgQ6JKAAmCXsiEWAgQIECBAgAABAgQIECBAgAABAi0LKAC2DKo5AgQIECBAgAABAgQIECBAgAABAl0SUADsUjbEQoAAAQIECBAgQIAAAQIECBAgQKBlAQXAlkE1R4AAAQIECBAgQIAAAQIECBAgQKBLAgqAXcqGWAgQIECAAAECBAgQIECAAAECBAi0LKAA2DKo5ggQIECAAAECBAgQIECAAAECBAh0SUABsEvZEAsBAgQIECBAgAABAgQIECBAgACBlgUUAFsG1RwBAgQIECBAgAABAgQIECBAgACBLgkoAHYpG2IhQIAAAQIECBAgQIAAAQIECBAg0LKAAmDLoJojQIAAAQIECBAgQIAAAQIECBAg0CUBBcAuZUMsBAgQIECAAAECBAgQIECAAAECBFoWUABsGVRzBAgQIECAAAECBAgQIECAAAECBLokoADYpWyIhQABAgQIECBAgAABAgQIECBAgEDLAv8fbMNoCbAA7EUAAAAASUVORK5CYII=\" width=\"640\">"
      ],
      "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",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x269c7b98278>,\n",
       " <matplotlib.lines.Line2D at 0x269c7b98470>,\n",
       " <matplotlib.lines.Line2D at 0x269c7b98668>,\n",
       " <matplotlib.lines.Line2D at 0x269c7b98860>,\n",
       " <matplotlib.lines.Line2D at 0x269c7b98a58>,\n",
       " <matplotlib.lines.Line2D at 0x269c7b98c50>,\n",
       " <matplotlib.lines.Line2D at 0x269c7b98e48>,\n",
       " <matplotlib.lines.Line2D at 0x269c7b9f080>,\n",
       " <matplotlib.lines.Line2D at 0x269c7b9f278>,\n",
       " <matplotlib.lines.Line2D at 0x269c7b9f470>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load some data from YAO for comparison\n",
    "yao_result = fits.getdata(\"YAO_data/readNoise_YAO.fits\")[:10]\n",
    "print(yao_result.shape)\n",
    "yao_photon_mean = yao_result[:, 0].mean(1)\n",
    "yao_photon_err = yao_result[:,0].std(1)/(yao_result.shape[1]**0.5)\n",
    "print(yao_photon_mean.shape)\n",
    "\n",
    "pyplot.figure()\n",
    "pyplot.errorbar(GS_MAGS, yao_photon_mean, yerr=yao_photon_err)\n",
    "pyplot.show()\n",
    "\n",
    "pyplot.figure()\n",
    "pyplot.plot(E_READ_NOISE, yao_result.mean(2).T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c35f06bb5848462586a9985eab61027a"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cd4bcc91e8e34fa28a897e94b23a4c09"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bc26a1bf3b0d4f9aa9a176bf41861a4a"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "***\n",
      "Set GS Mag to 10.0\n",
      "***\n",
      "***\n",
      "Set EReadNoise to 0.0\n",
      "***\n",
      "1 of 1: Loaded configuration file successfully!Starting Sim: 2017-06-29-12-22-47\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "Creating mask...\n",
      "Turbulence summary @ 500 nm:\n",
      "| r0 = 0.19 m (0.55\" seeing)\n",
      "| Vbar_5/3 = 21.85 m/s\n",
      "| tau0 = 2.67 ms\n",
      "Initialise Infinite Phase Screen 1\n",
      "Initialise Infinite Phase Screen 2\n",
      "Initialise Infinite Phase Screen 3\n",
      "Initialise Infinite Phase Screen 4\n",
      "Initialising WFSs....\n",
      "WFS 0: 64 measurements\n",
      "Initialising 2 DMs...\n",
      "Making DM Influence Functions...\n",
      "DM 0: 2 active actuators\n",
      "Making DM Influence Functions...\n",
      "DM 1: 49 active actuators\n",
      "51 total DM Actuators\n",
      "Initialising Reconstructor...\n",
      "Initialising 1 Science Cams...\n",
      "Generating fftw3 plan....\n",
      "If this takes too long, change fftw_FLAGS.\n",
      "Done!\n",
      "Initialise Data Storage...\n",
      "Initialisation Complete!\n",
      "Making interaction Matrices...\n",
      "Creating Interaction Matrix for DM 0 \n",
      "1 of 2: Generating 2 Actuator DM iMat\n",
      "2 of 2: Generating 2 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 0 has 2 valid actuators (0 dropped)\n",
      "Creating Interaction Matrix for DM 1 \n",
      "48 of 49: Generating 49 Actuator DM iMat\n",
      "49 of 49: Generating 49 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 1 has 49 valid actuators (0 dropped)\n",
      "Interaction Matrices Done\n",
      "Creating Command Matrix\n",
      "Invert iMat with conditioning: 0.0667\n",
      "Command Matrix Generated!\n",
      "4999 of 5000: sh6x6  Strehl -- sci_0: inst 0.43, long 0.48 \n",
      "5000 of 5000: sh6x6  Strehl -- sci_0: inst 0.44, long 0.48 \n",
      "\n",
      "Science Camera 0: Long Exposure Strehl Ratio: 0.48\n",
      "\n",
      "\n",
      "Time moving atmosphere: 0.00\n",
      "Time making IMats and CMats: 1.37\n",
      "Time in WFS: 56.34\n",
      "\t of which time spent in : 0.00\n",
      "Time in Reconstruction: 0.16\n",
      "Time in DM: 4.43\n",
      "Time making science image: 89.44\n",
      "\n",
      "\n",
      "\n",
      "***\n",
      "Set GS Mag to 10.0\n",
      "***\n",
      "***\n",
      "Set EReadNoise to 11.11111111111111\n",
      "***\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "1 of 1: Loaded configuration file successfully!Starting Sim: 2017-06-29-12-25-48\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "Creating mask...\n",
      "Turbulence summary @ 500 nm:\n",
      "| r0 = 0.19 m (0.55\" seeing)\n",
      "| Vbar_5/3 = 21.85 m/s\n",
      "| tau0 = 2.67 ms\n",
      "Initialise Infinite Phase Screen 1\n",
      "Initialise Infinite Phase Screen 2\n",
      "Initialise Infinite Phase Screen 3\n",
      "Initialise Infinite Phase Screen 4\n",
      "Initialising WFSs....\n",
      "WFS 0: 64 measurements\n",
      "Initialising 2 DMs...\n",
      "Making DM Influence Functions...\n",
      "DM 0: 2 active actuators\n",
      "Making DM Influence Functions...\n",
      "DM 1: 49 active actuators\n",
      "51 total DM Actuators\n",
      "Initialising Reconstructor...\n",
      "Initialising 1 Science Cams...\n",
      "Generating fftw3 plan....\n",
      "If this takes too long, change fftw_FLAGS.\n",
      "Done!\n",
      "Initialise Data Storage...\n",
      "Initialisation Complete!\n",
      "Making interaction Matrices...\n",
      "Creating Interaction Matrix for DM 0 \n",
      "1 of 2: Generating 2 Actuator DM iMat\n",
      "2 of 2: Generating 2 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 0 has 2 valid actuators (0 dropped)\n",
      "Creating Interaction Matrix for DM 1 \n",
      "48 of 49: Generating 49 Actuator DM iMat\n",
      "49 of 49: Generating 49 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 1 has 49 valid actuators (0 dropped)\n",
      "Interaction Matrices Done\n",
      "Creating Command Matrix\n",
      "Invert iMat with conditioning: 0.0667\n",
      "Command Matrix Generated!\n",
      "4999 of 5000: sh6x6  Strehl -- sci_0: inst 0.42, long 0.31 \n",
      "5000 of 5000: sh6x6  Strehl -- sci_0: inst 0.40, long 0.31 \n",
      "\n",
      "Science Camera 0: Long Exposure Strehl Ratio: 0.31\n",
      "\n",
      "\n",
      "Time moving atmosphere: 0.00\n",
      "Time making IMats and CMats: 0.63\n",
      "Time in WFS: 57.35\n",
      "\t of which time spent in : 0.00\n",
      "Time in Reconstruction: 0.18\n",
      "Time in DM: 4.37\n",
      "Time making science image: 88.94\n",
      "\n",
      "\n",
      "\n",
      "***\n",
      "Set GS Mag to 10.0\n",
      "***\n",
      "***\n",
      "Set EReadNoise to 22.22222222222222\n",
      "***\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "1 of 1: Loaded configuration file successfully!Starting Sim: 2017-06-29-12-28-39\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "Creating mask...\n",
      "Turbulence summary @ 500 nm:\n",
      "| r0 = 0.19 m (0.55\" seeing)\n",
      "| Vbar_5/3 = 21.85 m/s\n",
      "| tau0 = 2.67 ms\n",
      "Initialise Infinite Phase Screen 1\n",
      "Initialise Infinite Phase Screen 2\n",
      "Initialise Infinite Phase Screen 3\n",
      "Initialise Infinite Phase Screen 4\n",
      "Initialising WFSs....\n",
      "WFS 0: 64 measurements\n",
      "Initialising 2 DMs...\n",
      "Making DM Influence Functions...\n",
      "DM 0: 2 active actuators\n",
      "Making DM Influence Functions...\n",
      "DM 1: 49 active actuators\n",
      "51 total DM Actuators\n",
      "Initialising Reconstructor...\n",
      "Initialising 1 Science Cams...\n",
      "Generating fftw3 plan....\n",
      "If this takes too long, change fftw_FLAGS.\n",
      "Done!\n",
      "Initialise Data Storage...\n",
      "Initialisation Complete!\n",
      "Making interaction Matrices...\n",
      "Creating Interaction Matrix for DM 0 \n",
      "1 of 2: Generating 2 Actuator DM iMat\n",
      "2 of 2: Generating 2 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 0 has 2 valid actuators (0 dropped)\n",
      "Creating Interaction Matrix for DM 1 \n",
      "48 of 49: Generating 49 Actuator DM iMat\n",
      "49 of 49: Generating 49 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 1 has 49 valid actuators (0 dropped)\n",
      "Interaction Matrices Done\n",
      "Creating Command Matrix\n",
      "Invert iMat with conditioning: 0.0667\n",
      "Command Matrix Generated!\n",
      "4999 of 5000: sh6x6  Strehl -- sci_0: inst 0.15, long 0.15 \n",
      "5000 of 5000: sh6x6  Strehl -- sci_0: inst 0.15, long 0.15 \n",
      "\n",
      "Science Camera 0: Long Exposure Strehl Ratio: 0.15\n",
      "\n",
      "\n",
      "Time moving atmosphere: 0.00\n",
      "Time making IMats and CMats: 0.56\n",
      "Time in WFS: 57.51\n",
      "\t of which time spent in : 0.00\n",
      "Time in Reconstruction: 0.15\n",
      "Time in DM: 4.38\n",
      "Time making science image: 89.75\n",
      "\n",
      "\n",
      "\n",
      "***\n",
      "Set GS Mag to 10.0\n",
      "***\n",
      "***\n",
      "Set EReadNoise to 33.33333333333333\n",
      "***\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "1 of 1: Loaded configuration file successfully!Starting Sim: 2017-06-29-12-31-30\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "Creating mask...\n",
      "Turbulence summary @ 500 nm:\n",
      "| r0 = 0.19 m (0.55\" seeing)\n",
      "| Vbar_5/3 = 21.85 m/s\n",
      "| tau0 = 2.67 ms\n",
      "Initialise Infinite Phase Screen 1\n",
      "Initialise Infinite Phase Screen 2\n",
      "Initialise Infinite Phase Screen 3\n",
      "Initialise Infinite Phase Screen 4\n",
      "Initialising WFSs....\n",
      "WFS 0: 64 measurements\n",
      "Initialising 2 DMs...\n",
      "Making DM Influence Functions...\n",
      "DM 0: 2 active actuators\n",
      "Making DM Influence Functions...\n",
      "DM 1: 49 active actuators\n",
      "51 total DM Actuators\n",
      "Initialising Reconstructor...\n",
      "Initialising 1 Science Cams...\n",
      "Generating fftw3 plan....\n",
      "If this takes too long, change fftw_FLAGS.\n",
      "Done!\n",
      "Initialise Data Storage...\n",
      "Initialisation Complete!\n",
      "Making interaction Matrices...\n",
      "Creating Interaction Matrix for DM 0 \n",
      "1 of 2: Generating 2 Actuator DM iMat\n",
      "2 of 2: Generating 2 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 0 has 2 valid actuators (0 dropped)\n",
      "Creating Interaction Matrix for DM 1 \n",
      "48 of 49: Generating 49 Actuator DM iMat\n",
      "49 of 49: Generating 49 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 1 has 49 valid actuators (0 dropped)\n",
      "Interaction Matrices Done\n",
      "Creating Command Matrix\n",
      "Invert iMat with conditioning: 0.0667\n",
      "Command Matrix Generated!\n",
      "4999 of 5000: sh6x6  Strehl -- sci_0: inst 0.21, long 0.07 \n",
      "5000 of 5000: sh6x6  Strehl -- sci_0: inst 0.12, long 0.07 \n",
      "\n",
      "Science Camera 0: Long Exposure Strehl Ratio: 0.07\n",
      "\n",
      "\n",
      "Time moving atmosphere: 0.00\n",
      "Time making IMats and CMats: 0.60\n",
      "Time in WFS: 56.78\n",
      "\t of which time spent in : 0.00\n",
      "Time in Reconstruction: 0.16\n",
      "Time in DM: 4.41\n",
      "Time making science image: 89.48\n",
      "\n",
      "\n",
      "\n",
      "***\n",
      "Set GS Mag to 10.0\n",
      "***\n",
      "***\n",
      "Set EReadNoise to 44.44444444444444\n",
      "***\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "1 of 1: Loaded configuration file successfully!Starting Sim: 2017-06-29-12-34-21\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "Creating mask...\n",
      "Turbulence summary @ 500 nm:\n",
      "| r0 = 0.19 m (0.55\" seeing)\n",
      "| Vbar_5/3 = 21.85 m/s\n",
      "| tau0 = 2.67 ms\n",
      "Initialise Infinite Phase Screen 1\n",
      "Initialise Infinite Phase Screen 2\n",
      "Initialise Infinite Phase Screen 3\n",
      "Initialise Infinite Phase Screen 4\n",
      "Initialising WFSs....\n",
      "WFS 0: 64 measurements\n",
      "Initialising 2 DMs...\n",
      "Making DM Influence Functions...\n",
      "DM 0: 2 active actuators\n",
      "Making DM Influence Functions...\n",
      "DM 1: 49 active actuators\n",
      "51 total DM Actuators\n",
      "Initialising Reconstructor...\n",
      "Initialising 1 Science Cams...\n",
      "Generating fftw3 plan....\n",
      "If this takes too long, change fftw_FLAGS.\n",
      "Done!\n",
      "Initialise Data Storage...\n",
      "Initialisation Complete!\n",
      "Making interaction Matrices...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating Interaction Matrix for DM 0 \n",
      "1 of 2: Generating 2 Actuator DM iMat\n",
      "2 of 2: Generating 2 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 0 has 2 valid actuators (0 dropped)\n",
      "Creating Interaction Matrix for DM 1 \n",
      "48 of 49: Generating 49 Actuator DM iMat\n",
      "49 of 49: Generating 49 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 1 has 49 valid actuators (0 dropped)\n",
      "Interaction Matrices Done\n",
      "Creating Command Matrix\n",
      "Invert iMat with conditioning: 0.0667\n",
      "Command Matrix Generated!\n",
      "4999 of 5000: sh6x6  Strehl -- sci_0: inst 0.08, long 0.04 \n",
      "5000 of 5000: sh6x6  Strehl -- sci_0: inst 0.07, long 0.04 \n",
      "\n",
      "Science Camera 0: Long Exposure Strehl Ratio: 0.04\n",
      "\n",
      "\n",
      "Time moving atmosphere: 0.00\n",
      "Time making IMats and CMats: 0.56\n",
      "Time in WFS: 56.78\n",
      "\t of which time spent in : 0.00\n",
      "Time in Reconstruction: 0.18\n",
      "Time in DM: 4.37\n",
      "Time making science image: 89.80\n",
      "\n",
      "\n",
      "\n",
      "***\n",
      "Set GS Mag to 10.0\n",
      "***\n",
      "***\n",
      "Set EReadNoise to 55.55555555555556\n",
      "***\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "1 of 1: Loaded configuration file successfully!Starting Sim: 2017-06-29-12-37-12\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "Creating mask...\n",
      "Turbulence summary @ 500 nm:\n",
      "| r0 = 0.19 m (0.55\" seeing)\n",
      "| Vbar_5/3 = 21.85 m/s\n",
      "| tau0 = 2.67 ms\n",
      "Initialise Infinite Phase Screen 1\n",
      "Initialise Infinite Phase Screen 2\n",
      "Initialise Infinite Phase Screen 3\n",
      "Initialise Infinite Phase Screen 4\n",
      "Initialising WFSs....\n",
      "WFS 0: 64 measurements\n",
      "Initialising 2 DMs...\n",
      "Making DM Influence Functions...\n",
      "DM 0: 2 active actuators\n",
      "Making DM Influence Functions...\n",
      "DM 1: 49 active actuators\n",
      "51 total DM Actuators\n",
      "Initialising Reconstructor...\n",
      "Initialising 1 Science Cams...\n",
      "Generating fftw3 plan....\n",
      "If this takes too long, change fftw_FLAGS.\n",
      "Done!\n",
      "Initialise Data Storage...\n",
      "Initialisation Complete!\n",
      "Making interaction Matrices...\n",
      "Creating Interaction Matrix for DM 0 \n",
      "1 of 2: Generating 2 Actuator DM iMat\n",
      "2 of 2: Generating 2 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 0 has 2 valid actuators (0 dropped)\n",
      "Creating Interaction Matrix for DM 1 \n",
      "48 of 49: Generating 49 Actuator DM iMat\n",
      "49 of 49: Generating 49 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 1 has 49 valid actuators (0 dropped)\n",
      "Interaction Matrices Done\n",
      "Creating Command Matrix\n",
      "Invert iMat with conditioning: 0.0667\n",
      "Command Matrix Generated!\n",
      "4999 of 5000: sh6x6  Strehl -- sci_0: inst 0.06, long 0.03 \n",
      "5000 of 5000: sh6x6  Strehl -- sci_0: inst 0.08, long 0.03 \n",
      "\n",
      "Science Camera 0: Long Exposure Strehl Ratio: 0.03\n",
      "\n",
      "\n",
      "Time moving atmosphere: 0.00\n",
      "Time making IMats and CMats: 0.56\n",
      "Time in WFS: 56.84\n",
      "\t of which time spent in : 0.00\n",
      "Time in Reconstruction: 0.17\n",
      "Time in DM: 4.42\n",
      "Time making science image: 89.41\n",
      "\n",
      "\n",
      "\n",
      "***\n",
      "Set GS Mag to 10.0\n",
      "***\n",
      "***\n",
      "Set EReadNoise to 66.66666666666666\n",
      "***\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "1 of 1: Loaded configuration file successfully!Starting Sim: 2017-06-29-12-40-02\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "Creating mask...\n",
      "Turbulence summary @ 500 nm:\n",
      "| r0 = 0.19 m (0.55\" seeing)\n",
      "| Vbar_5/3 = 21.85 m/s\n",
      "| tau0 = 2.67 ms\n",
      "Initialise Infinite Phase Screen 1\n",
      "Initialise Infinite Phase Screen 2\n",
      "Initialise Infinite Phase Screen 3\n",
      "Initialise Infinite Phase Screen 4\n",
      "Initialising WFSs....\n",
      "WFS 0: 64 measurements\n",
      "Initialising 2 DMs...\n",
      "Making DM Influence Functions...\n",
      "DM 0: 2 active actuators\n",
      "Making DM Influence Functions...\n",
      "DM 1: 49 active actuators\n",
      "51 total DM Actuators\n",
      "Initialising Reconstructor...\n",
      "Initialising 1 Science Cams...\n",
      "Generating fftw3 plan....\n",
      "If this takes too long, change fftw_FLAGS.\n",
      "Done!\n",
      "Initialise Data Storage...\n",
      "Initialisation Complete!\n",
      "Making interaction Matrices...\n",
      "Creating Interaction Matrix for DM 0 \n",
      "1 of 2: Generating 2 Actuator DM iMat\n",
      "2 of 2: Generating 2 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 0 has 2 valid actuators (0 dropped)\n",
      "Creating Interaction Matrix for DM 1 \n",
      "48 of 49: Generating 49 Actuator DM iMat\n",
      "49 of 49: Generating 49 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 1 has 49 valid actuators (0 dropped)\n",
      "Interaction Matrices Done\n",
      "Creating Command Matrix\n",
      "Invert iMat with conditioning: 0.0667\n",
      "Command Matrix Generated!\n",
      "4999 of 5000: sh6x6  Strehl -- sci_0: inst 0.06, long 0.02 \n",
      "5000 of 5000: sh6x6  Strehl -- sci_0: inst 0.08, long 0.02 \n",
      "\n",
      "Science Camera 0: Long Exposure Strehl Ratio: 0.02\n",
      "\n",
      "\n",
      "Time moving atmosphere: 0.00\n",
      "Time making IMats and CMats: 0.59\n",
      "Time in WFS: 57.48\n",
      "\t of which time spent in : 0.00\n",
      "Time in Reconstruction: 0.20\n",
      "Time in DM: 4.38\n",
      "Time making science image: 90.67\n",
      "\n",
      "\n",
      "\n",
      "***\n",
      "Set GS Mag to 10.0\n",
      "***\n",
      "***\n",
      "Set EReadNoise to 77.77777777777777\n",
      "***\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "1 of 1: Loaded configuration file successfully!Starting Sim: 2017-06-29-12-42-55\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "Creating mask...\n",
      "Turbulence summary @ 500 nm:\n",
      "| r0 = 0.19 m (0.55\" seeing)\n",
      "| Vbar_5/3 = 21.85 m/s\n",
      "| tau0 = 2.67 ms\n",
      "Initialise Infinite Phase Screen 1\n",
      "Initialise Infinite Phase Screen 2\n",
      "Initialise Infinite Phase Screen 3\n",
      "Initialise Infinite Phase Screen 4\n",
      "Initialising WFSs....\n",
      "WFS 0: 64 measurements\n",
      "Initialising 2 DMs...\n",
      "Making DM Influence Functions...\n",
      "DM 0: 2 active actuators\n",
      "Making DM Influence Functions...\n",
      "DM 1: 49 active actuators\n",
      "51 total DM Actuators\n",
      "Initialising Reconstructor...\n",
      "Initialising 1 Science Cams...\n",
      "Generating fftw3 plan....\n",
      "If this takes too long, change fftw_FLAGS.\n",
      "Done!\n",
      "Initialise Data Storage...\n",
      "Initialisation Complete!\n",
      "Making interaction Matrices...\n",
      "Creating Interaction Matrix for DM 0 \n",
      "1 of 2: Generating 2 Actuator DM iMat\n",
      "2 of 2: Generating 2 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 0 has 2 valid actuators (0 dropped)\n",
      "Creating Interaction Matrix for DM 1 \n",
      "48 of 49: Generating 49 Actuator DM iMat\n",
      "49 of 49: Generating 49 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 1 has 49 valid actuators (0 dropped)\n",
      "Interaction Matrices Done\n",
      "Creating Command Matrix\n",
      "Invert iMat with conditioning: 0.0667\n",
      "Command Matrix Generated!\n",
      "4999 of 5000: sh6x6  Strehl -- sci_0: inst 0.03, long 0.01 \n",
      "5000 of 5000: sh6x6  Strehl -- sci_0: inst 0.04, long 0.01 \n",
      "\n",
      "Science Camera 0: Long Exposure Strehl Ratio: 0.01\n",
      "\n",
      "\n",
      "Time moving atmosphere: 0.00\n",
      "Time making IMats and CMats: 0.55\n",
      "Time in WFS: 56.99\n",
      "\t of which time spent in : 0.00\n",
      "Time in Reconstruction: 0.15\n",
      "Time in DM: 4.44\n",
      "Time making science image: 89.82\n",
      "\n",
      "\n",
      "\n",
      "***\n",
      "Set GS Mag to 10.0\n",
      "***\n",
      "***\n",
      "Set EReadNoise to 88.88888888888889\n",
      "***\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "1 of 1: Loaded configuration file successfully!Starting Sim: 2017-06-29-12-45-47\n",
      "Pixel Scale: 15.19 pxls/m\n",
      "subScreenSize: 122 simulation pixels\n",
      "Creating mask...\n",
      "Turbulence summary @ 500 nm:\n",
      "| r0 = 0.19 m (0.55\" seeing)\n",
      "| Vbar_5/3 = 21.85 m/s\n",
      "| tau0 = 2.67 ms\n",
      "Initialise Infinite Phase Screen 1\n",
      "Initialise Infinite Phase Screen 2\n",
      "Initialise Infinite Phase Screen 3\n",
      "Initialise Infinite Phase Screen 4\n",
      "Initialising WFSs....\n",
      "WFS 0: 64 measurements\n",
      "Initialising 2 DMs...\n",
      "Making DM Influence Functions...\n",
      "DM 0: 2 active actuators\n",
      "Making DM Influence Functions...\n",
      "DM 1: 49 active actuators\n",
      "51 total DM Actuators\n",
      "Initialising Reconstructor...\n",
      "Initialising 1 Science Cams...\n",
      "Generating fftw3 plan....\n",
      "If this takes too long, change fftw_FLAGS.\n",
      "Done!\n",
      "Initialise Data Storage...\n",
      "Initialisation Complete!\n",
      "Making interaction Matrices...\n",
      "Creating Interaction Matrix for DM 0 \n",
      "1 of 2: Generating 2 Actuator DM iMat\n",
      "2 of 2: Generating 2 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 0 has 2 valid actuators (0 dropped)\n",
      "Creating Interaction Matrix for DM 1 \n",
      "48 of 49: Generating 49 Actuator DM iMat\n",
      "49 of 49: Generating 49 Actuator DM iMatChecking for redundant actuators...\n",
      "DM 1 has 49 valid actuators (0 dropped)\n",
      "Interaction Matrices Done\n",
      "Creating Command Matrix\n",
      "Invert iMat with conditioning: 0.0667\n",
      "Command Matrix Generated!\n",
      "2406 of 5000: sh6x6  Strehl -- sci_0: inst 0.05, long 0.01 "
     ]
    }
   ],
   "source": [
    "data_frame = pandas.DataFrame()\n",
    "\n",
    "fig = pyplot.figure()\n",
    "ax1 = fig.add_subplot(1,2,1)\n",
    "pyplot.xlabel(\"e Read Noise\")\n",
    "pyplot.ylabel(\"Strehl Ratio @ 1.65$\\mu$m\")\n",
    "\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "pyplot.xlabel(\"GS Magnitutde\")\n",
    "pyplot.ylabel(\"Strehl Ratio @ 1.65$\\mu$m\")\n",
    "\n",
    "for r in tnrange(RUNS):\n",
    "    for n_mag in tnrange(len(GS_MAGS)):\n",
    "        for n_rn in tnrange(len(E_READ_NOISE)):\n",
    "            gs_mag = GS_MAGS[n_mag]\n",
    "            e_rn = E_READ_NOISE[n_rn]\n",
    "            print('\\n***\\nSet GS Mag to {}\\n***'.format(gs_mag))\n",
    "            print('***\\nSet EReadNoise to {}\\n***'.format(e_rn))\n",
    "\n",
    "            sim = soapy.Sim(CONFIGFILE)\n",
    "            \n",
    "            sim.aoinit()\n",
    "            \n",
    "            sim.config.wfss[0].centThreshold = CENT_THRESHOLD\n",
    "            \n",
    "            # Make iMat with no noise\n",
    "            sim.makeIMat()\n",
    "            \n",
    "            sim.config.wfss[0].photonNoise = True\n",
    "            sim.config.wfss[0].GSMag = gs_mag\n",
    "            sim.config.wfss[0].eReadNoise = e_rn\n",
    "\n",
    "            sim.aoloop()\n",
    "\n",
    "            data_series = pandas.Series(dict(sim.config.sim.saveHeader))\n",
    "            data_series[\"gs_mag\"] = gs_mag\n",
    "            data_series[\"e_readnoise\"] = e_rn\n",
    "            data_series[\"long_strehl\"] = sim.longStrehl[0][-1]\n",
    "            data_series[\"wavefront_error\"] = sim.WFE[0][-1]\n",
    "            data_series[\"cent_threshold\"] = CENT_THRESHOLD\n",
    "\n",
    "            data_frame = data_frame.append(data_series, ignore_index=True)\n",
    "            ax1.scatter(e_rn, sim.longStrehl[0][-1], color=MPL_COLOURS[n_mag])\n",
    "            ax2.scatter(gs_mag, sim.longStrehl[0][-1], color=MPL_COLOURS[n_rn])\n",
    "\n",
    "            fig.canvas.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "long_strehls = numpy.zeros((10, 10, 4))\n",
    "for i in range(10):\n",
    "    gs = GS_MAGS[i]\n",
    "    for j in range(10):\n",
    "        e_rn = E_READ_NOISE[j]team\n",
    "        print(long_strehls.shape)\n",
    "        long_strehls[i, j] = data_frame[data_frame.gs_mag==gs][data_frame.e_readnoise==e_rn]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_frame.gs_mag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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