squatAnalysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy import signal\n",
    "# from dataProcessing import PARTS, requiredParts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the 2 files\n",
    "FILE_1 = \"squat3\"\n",
    "FILE_2 = \"squatfar4\"\n",
    "\n",
    "squat1X = np.load(\"./data/\"+FILE_1+\"X.npy\")\n",
    "squat1Y = np.load(\"./data/\"+FILE_1+\"Y.npy\")\n",
    "squat2X = np.load(\"./data/\"+FILE_2+\"X.npy\")\n",
    "squat2Y = np.load(\"./data/\"+FILE_2+\"Y.npy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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Tpw9e7bm7UtKSuT+++9XbP/NN9+ozl2yZIli3iOPPOJSrVo4CtF69+5daSAjInLu3Dm70Khz585Ot3nttdcU82vXri2xsbGa6o2MjLSr9eOPP3a6jVqI1rRpUzl58qSmfb700kuKbe+8806HczMyMhRzGzZsKEVFRZr2o5Unz0EAAABvQIgGAAAAXRCiKR07dkzxaK46derYPfKqMlarVTp16qSoZd26dQ7nq4Von3zyicu1V4e7QrTw8HBN+ysrK5NmzZrZba/lXUKXde7c2aVt1UK05s2bKx5BVxm1OzuOHTvmcL63h2i273x66623XK6vMg899JBiH2PGjHF5jSlTpijWGDBggNvrFFE/p2fMmOHyOqNGjVKs8c9//tPlNXbs2KFYo02bNqrzZs6cqZj37rvvuryvyqiFaP7+/poDJhH7sM/Hx0e2bdumOjcrK8vuHV1Dhw51qWbbd9k1atRI8vPzHc5XC9GmT5+ueX+bNm2yC/0uXbqkOjcpKUkxt3379i59Ni08eQ4CAAB4A0I0AAAA6IIQTSkwMFCxRp8+fVxeQ0QkKChIsc7IkSMdzlUL0Y4cOVKl/VaVO0K0m2++WdNdKZc98sgjiu39/PzK30emxVtvvaXYfsiQIU7nq4Vold2dYuvChQt2j5ibNm2aw/neHqL98ssvirl33XWXS99hZdLT0xXr16lTR86ePevyOpmZmXbnmh5sv6+rr766So+wa9OmjWIdreGyrb/+9a+KddTeB7d48WLFnC5dulRpX86ohWgvvPCCS2uUlZWVv0Pv8nD0XsGff/5ZMc/X19dpWK1m586ddjVHRkY6nG8bovn7+7v0e1RUVFT+DrXLIzExUXXu6dOn7faVnZ3t0uerjCfPQQAAAG9AiAYAAABdqIVoISEhLo/KLjSbJUT717/+pVjj+++/d3kNEZGYmBjFOs4ek2d7bFq2bFmlfVaHO0K0fv36ubTPN998U7F9t27dXNp+3Lhxiu379+/vdL5aiLZlyxaX9iki8thjjynWeOmllxzO9fYQLTU11e6YvPvuu5oeyamFbRhy//33V3mtm266SbGWK3dBaWX7ffXo0cPlNWyPaZ06daS4uLhK9bz44ouKtRYvXmw3x/a9dj4+fwbKzu66cpVaiLZkyRKX1xk0aJBije7du6vOGzx4sGLe3XffXaW6bYMkZ/+YwTZEq8p336pVK8UaGzdudDj38jsgL4+ePXtKamqqy/tU4+lzEAAAwBsQogEAAEAXaiGaHswSojVo0ECxxocfflilUHH48OGKdZw9rsv22FT2ni09uCNEGzFihEv7/OCDD6oVwgUHByu2f+qpp5zOtz0/atWqVaWg4YsvvtD83Xp7iCYi8sQTT9j9BjRq1EjeeOMNWbFihWRlZblc82VDhgxRrNu1a9cq9VNISIjdO7Xi4uKqXJcjtt9XZXc3qlm6dKlijWbNmlX5M/fo0UOx1uTJk1X3+Z///Ef1Oxw4cKD8+uuvVbr7ryK1EM3Vx9yK2D8+9JprrlGd98ADDyjmvfPOO1Wq+7nnnlOs8+STTzqcaxuivfLKKy7vr2PHjoo1wsLCHM61vVv5ctj11FNPydy5cyUlJcXl/V9mxDkIAABgNEI0AAAA6IIQ7X/y8/PtjoW7xvXXX6/52Lz66qsu1e0O7gjRvvnmG5f2afu5Bw8e7NL2roZFtufHdddd59L+Lvvhhx80r2OGEC09Pd3uDhrb0bZtW+nfv7989913LoUnzz77rG495ezRfFVl+32NHj3a5TVsw113DkdBdVpamt2dTWrf4YABA+T77793+XGxaiFaSUmJy8dmzZo1mtZp3759tX5bLgsICFCs4+xOSNsQ7f3333d5f7bvwvztt98czi0pKbG789l23HDDDdK7d2+ZOHGixMXFaX7UqhHnIAAAgNEI0QAAAKALQrT/UXu0nbtGgwYN3Hps3M0dIZqrAVF1P3d1Q7S//vWvLu3vstDQUMU6derUcTjXDCGaiEhWVpY8//zz4uvrq+l8vvPOO2XatGly6dIlp+v26tVLt54KDQ116Thq4Y7vy/ZORXeODz74wOF+z5w5I88++6zm77Bz584yY8YMKSwsrPQz2YZo/v7+Lh8XEZHY2Fi7OjIzM+3m2b47bfbs2VXa39dff61Y5/bbb3c41zZEGzp0qMv7cyVEE/kzSBs+fLhcffXVmr6zm266ST777DPVY1aRUecgAACAkQjRAAAAoAtCtP9JTk7W7cKjs1CKEK1qn5sQTV1VQrTLDhw4IAEBAdKxY0dNYczNN9/s9L1P999/v249tXz5cs2fSyt3fF+ffvqpbp9ZS7Czf/9++fTTT6VDhw6avsOWLVtW+m5AQjRtXA3RLsvMzJTJkydLt27dpG7dupV+Z/Xq1ZOQkBCH6xl9DgIAABiBEA0AAAC6IET7n5ycHLtjsXnzZpfWqApCtKp97pryOMcmTZq41AfVCdEqysnJkVWrVklAQID07NlT/Pz8VC+q+/v7y7Zt21TXePLJJxVz33jjjSrV4inu+L4mTJigWKNdu3Y6VKpNTk6OhIWFSUBAgPTo0cNhQHP11VdLbGysw3Vq4uMcPRmiVVRYWCibNm2S8ePHy+OPPy6NGzd2GGhNnTpVdQ1vOgcBAAA8hRANAAAAuiBE+x+r1SpXXXWVYo1ff/3VpTWqghDNmBCtVq1akp+f79I+Rewflda+fXuHc59//nnF3KCgIJf2ZbVapXbt2oaEaLby8/MlNDRUevbsafeb0bFjR9X3Nb3xxhuKeU899ZRbatGLO0K0H3/8UbFG06ZNdai0avLz8+WXX36R7t27232HnTp1cridWojmyrvxLvvuu+8Ua1xzzTWq8x544AHFvHfffdflfYnY99+TTz7pcK63hGi2ysrKZNOmTdK/f3+pVauWXfiZnp5ut403n4MAAAB6IUQDAACALgjRlO655x7FGiNHjnR5DVcRohkTovn4+FT6GDs1jz32mGKNF1980eHcgQMHKuaOGDHCpX2pvafPqBCtouHDh9vVtWvXLrt5M2bMUMy5+eab3V6LO7kjREtISLA7NqmpqTpUWz1qj/xLTExUnasWoi1ZssTlfQ4aNEixxgMPPKA6b/DgwYp599xzj8v7EhG55ZZbNP+ee2uIVlF4eLjdIzrV7kYzyzkIAADgToRoAAAA0MWVFKJFRkYq5jt7/40jtuFA586dXV7DVYRoxoVoH3/8sUv7vHDhgvj7+1d6Efsy28/40ksvubS/+fPne2WIVlJSIo0aNVLs58cff7Sbp/aewT179ri9HndxR4hmtVrt3uk1ffp0HaqtnuLiYrnmmmsUdS5cuFB1rlqI9sILL7i0v7KyMrvjMmzYMNW5ixcvVszz9fWVEydOuLS/+Ph4u5ojIyMdzjdDiCYi8sgjjyj2ofaIVLOcgwAAAO5EiAYAAABdXEkh2tatWxXz//KXv7hcZ0JCgt2/9F+1apXL67iCEM24EK158+aSm5ureZ+TJk1SbF+rVi1JSUlxOH/u3LmK+a1atVJ97KEj9957r1eGaCIiHTt21HSR/q677lLMe+aZZ3Spxx3cEaKJiPz3v/9VrNOyZUspKipyc7XVd/vttyvqDAkJUZ2nFqL5+/tLWlqa5n0tXbrUbg1Hd4JmZWXZvYPP1cC7f//+iu0bNWrk9PGtZgnR3nnnHU1hplnOQQAAAHchRAMAAIAurqQQLSUlxe7uhZycHJdrffrppxXrXH/99XL8+HGX17msstCEEM24EM3Hx0cGDx6saX8nTpywu3Pnsccec7rN3r177fbn7G6YikJCQlTrdWeIVpWZTAUAACAASURBVFpaqqkWWwUFBXbHIjQ0VHVuWFiY3WeYNWtWlfZ7mStBpCvcFaKlp6fL1VdfrVirX79+1arN0Weu6nd48eJFqVevnqLGlStXqs5VC9F8fHykd+/emr6Lc+fOyY033qjY9s4773S6zeuvv66Yf9VVV6k+MlTN2rVr7Wr95JNPnG7jyRCtqt+ZiEiPHj0U+/jggw9U53nyHAQAAPAGhGgAAADQxZUUolmtVmncuLFimy+//NLlWg8fPiwNGzZUrHPjjTdKTEyMS+vk5ubKjBkzKn2sJCGasSGaj4+PBAYGOt325MmT0rZtW8U2tWrVkj/++KPSOtu3b6/Y7pZbbpGMjAyn2yxYsEDq1q2re4j27rvvSr9+/SQ2NrbSz3GZxWKRt99+2y7gOHPmjMNt/vOf/9gdu+HDh0tJSYnm/VqtVomJiZHevXs7fOxgdbkrRBMRGTt2rGrodPbsWZfW2b9/v7z77rsOQ51BgwbJgAEDJC4uTvOaFovF7n19devWlezsbNX5jkK0y31bVlbmcF85OTnyj3/8w267FStWOK3x0KFDdo9Ove666yQhIcHpdps3b7YLeBs3biynTp1yup0nQ7T58+dLr1695LfffnMpUFN7vGtYWJjD+Z46BwEAALwBIRoAAAB0cSWFaCIir776qt3n6dGjh4wcOVKmTZsmISEhipGVlaW6zurVq6V27dp2az344IMyf/58OXLkiFgslvL5VqtVsrKyZMOGDTJlyhT517/+pQhB3H1s3K0mhmgtW7aUFi1aKL7bsLAwuXTpUvk2KSkpEhgYaBeq+vhof7zc7Nmz7ba96aab5Mcff1TcKZmXlydhYWHy73//u3xex44d7fbtzhCtYpDSqlUrGTp0qCxfvlyOHDlid3H/1KlT8tNPP6k+YvK1115zWtOFCxfswkQfnz/D6S+//FK2bdumOO4iIpcuXZKEhARZtGiRDBw4UK6//vry7ebNm+d0f1XlzhDNarXKCy+8YPeZGzRoIO+9955ERUXJuXPnFNuUlpZKcnKyrFixQoYNGya33XZb+XYDBw5U3U/F37zWrVvLhx9+KKGhoXL06FG7cOvUqVOyaNEi6dKli11db775psPPYhuiNWjQQPE4z7///e+ybNkyycvLU+xr6tSpct1119ntS+v71GbNmmW3bZ06deTDDz+UPXv2lP8Gl5WVSVxcnLz99ttSq1Ytu22WL19e6b48GaLNmzevfE6TJk1kwIABMn/+fElISJDCwkLF3HPnzklkZKQ899xzdp+rffv2TkM4T52DAAAA3oAQDQAAALq40kK0pKQku0dYORvO1gwNDbW7o6HiqFWrljRp0kQaNWqkeuFW6zElRDMmROvQoYNs2LBB9Y6vxo0bO7wTzMfHR5544gkpLi7WVKfVarV7BFvF0bBhQ9Xz7Prrr5cjR4643AdVDdHURoMGDaRZs2Z2dwRVHH/729/kwoULlR6HtLQ01QCu4qhXr55ce+21To+9j485QjQRkcLCQnnllVecfhY/Pz9p1qyZ3aMVbYeWEM3Zd2j7jrGK44477lAEYLZsQ7RGjRrJvn37VMPlhg0bOj1funbt6tJ7CIcNG+Zwrdq1a0uTJk0c/v76+vpKUFCQpv0YFaKpDX9/f2nWrJnUr1/f4ZzGjRvLnj17Kq3JE+cgAACANyBEAwAAgC6utBBNRCQiIkKaNWvm9GKg1jUPHz4s3bp107SWo3HXXXe5/di4W00N0UT+vOtQLQxwNAYMGKA5QLssJydH7rvvPs37aNeunRw6dEhEXO8DV47Lm2++Wa1z+6mnnpLz589rPg7FxcXy8ccfOw10KhvNmjWTdevWad6nK9wdol02Z84czb9JasPf318mT56suvZrr71Wre+wb9++lYagaiGaiEhsbKziDsHKxqOPPuo0rHNk9uzZ0qBBA5c+V9OmTWXJkiWa9+HpxzlW5zu74447JCkpyaXa9DwHAQAAvAEhGgAAAHRxJYZoIn8+Pu7777+X5557Ttq3by9NmjSROnXq2H1WrWtu2rRJnnnmGWnSpEmlFxvr1Kkj3bp1k9GjR8v+/fsrXZsQrWqf210hmsifd0m9/vrrDu+g8fX1la5du0pUVJRLNVZUVFQkkyZNkhtuuMHhudOsWTMZM2aM4tGGeoZoRUVFEhUVJUOHDpW77rpLrrrqqkrP73r16smzzz5brSDr9OnT8tlnn0m7du00XcC/5ZZb5K233pKwsDCX3qPmKr1CNBGRgoICmTZtmnTp0kX1UbG2o3nz5vLcc8/JDz/84DTkKiwslMjISPnvf/8rnTt31rR2/fr15fnnn5eNGzdqqt1RiCYikp2dLe+//77Tu3Y7derkUqClJisrSz766CO58cYbnX621q1by4gRI1wKd0U8G6JZrVaJi4uT0aNHS48ePZzecXZ51KpVq/xxws7eQeeMXucgAACANyBEAwAAALyAxWKRhIQEWbZsmYSEhEhgYKAEBQXJzJkzJTQ0VBITE+3eaQPv4CxEuyw/P1/Wrl0r06dPl3HjxsnUqVPl/9i78yiryjtf3A73Bu5N0t3pcNu77KQhookaTRzTGVrN0En6movmZ0cT0uams7xt2wmdJuncBgTBERQEURkcQJwBjUOUeR5UZJ5nQUYpJoFiqKKqznl/fxCqPdQuKKjateut8zxrvWv1as979uds9je6/Pie8/LLL4fNmzc3WI58Ph/mz58fnnrqqdC7d+9w3333hccffzy88847p/wvxxvKwYMHw/z588PLL78cHn300dCzZ8/q+/D888+HBQsWhPLy8ga95rZt28Kbb74ZnnrqqdCnT59w7733hv79+4enn346zJw5s9bfLYxZaWlpmDRpUnj22WfDQw89FO65557Qt2/f8OSTT4YJEyaEDRs2hHw+f0rvffDgwTBv3rzw0ksvJf4ZLly48KRPUh6vRDuqvLw8TJs2LQwaNCjcd999oV+/fmH48OFh7dq1p/Q5jmfZsmVhxIgR4dFHHw333XdfGDhwYHjppZeqT2/GpqqqKqxYsSK8+eabYfDgweGBBx4I99xzT+jXr18YOnRomDlz5kl9BWZdpPkMAgBkQYkGAABQD3Up0YCa6lKiAQBAlpRoAAAA9aBEg1OjRAMAoKlTogEAANSDEg1OjRINAICmTokGAABQD0o0ODVKNAAAmjolGgAAQD0o0eDUKNEAAGjqlGgAAAD1oESDU6NEAwCgqVOiAQAA1IMSDU6NEg0AgKZOiQYAAFAPSjQ4NUo0AACaOiUaAAAAAAAAHEOJBgAAAAAAAMdQogEAAAAAAMAxlGgAAAAAAABwDCUaAAAAAAAAHEOJBgAAAAAAAMdQogEAAAAAAMAxlGgAAAAAAABwDCUaAAAAAAAAHEOJBgAAAAAAAMdQogEAAAAAAMAxlGikIpfLhbKysupVUVERKisrLcuyLMuyLMuyLMuyLMuyLMsq8lVRUVHQIeRyuaxrjURKNFJRVlYWTjvtNMuyLMuyLMuyLMuyLMuyLMuyrOOusrKyrGuNREo0UqFEsyzLsizLsizLsizLsizLsiyrLkuJRlFRolmWZVmWZVmWZVmWZVmWZVmWVZelRKOoVFRU1BiArL9j1bIsy7Isy7Isy7Isy7Isy7Ks7NexB3EqKiqyrjUSKdFIRWVlZcEAVFZWZh0JAAAAAABoAmLpEJRopCKWAQAAAAAAABpXLB2CEo1UxDIAAAAAAABA44qlQ1CikYpYBgAAAAAAAGhcsXQISjRSEcsAAAAAAAAAjSuWDkGJRipiGQAAAAAAAKBxxdIhKNFIRSwDAAAAAAAANK5YOgQlGqmIZQAAIA35fD6UVVSF3QcOhy17DoW12/eHpVv2hjnv7w7TV+8I45ZtC6u2lYZcLp91VAAAAIBGF0uHoEQjFbEMAADUxez1u8P9Y1eGTr9fHH49fEH4p2fmhpuHvBt+NPjt8INHZoRvPzg1fL3X5HDp3RPC+d3GhtadRtVpXTfgrVBaVpH1xwMAAABoVLF0CEo0UhHLAADAiTw5Y12dS7FTWb96YX7WHxEAAACgUcXSISjRSEUsAwAAx7N2+/7wuc7pFWhH17Kte7P+qAAAAACNJpYOQYlGKmIZAAA4nn99cUHqBVrrTqPCLU/PyfqjAgAAADSaWDoEJRqpiGUAAKA2q0tKQ5tGOIV2dC3ctCfrjwwAAADQKGLpEJRopCKWAQCA2vzy+fnHLb2+0G1MuOSu8eFrPSeFbz04NVz78Izw94PeDjcPeTf832fmhn99cUH4j5cXhx5/WBZ6jVkZ+k9cE56Yvi78+PF3Et/v5iHvZv2RAQAAABpFLB2CEo1UxDIAAJBk5bZ9tZZn8zZ8GHK5/Cm/95rjnHCbvX53A34KAAAAgKYplg5BiUYqYhkAAEjyz8/OS/W3yzqOWJj4/jc+9k7I50+9oAMAAACIQSwdghKNVMQyAABwrKVb9tZ6Cm3plr0Nco33dx4I53QZnXiNmWt2Nsg1AAAAAJqqWDoEJRqpiGUAAOBYtzw9N7HcuvXZuQ16nf94eXHida4f8JbTaAAAAECzFkuHoEQjFbEMAAB81JLNtZ9CW/HBvga91uYPD4Zzb08+jTZpRUmDXgsAAACgKYmlQ2g2JdratWvDyJEjw0MPPRT69OkTXnzxxbBkyZKsY6Vq7dq14ZVXXgkDBw4M9957b+jbt28YMWJEWLRoUaiqqso0WywDAAAf9YthcxJLrX95fl4q17vj9aWJ17v24Rkhl3MaDQAAAGieYukQoi/RRo8eHa688sqCm/3RdeGFF4Znnnkm9RwbN24Mr732WujWrVu49tprw1lnnVWQ45prrmmQ61RUVIR+/fqFiy++uNbPfNppp4WPf/zj4brrrgtbt25tkOuerFgGAACOWrDxw8RCq03nUWHVttJUrlmyryx8vuuYxOuOWfJBKtcEAAAAyFosHUK0JVo+nw+/+tWvjlskfXTdcMMNoby8vMFzdO3aNbRq1eqE12+IEm3OnDnhwgsvrPNnPu2008LcuQ37+y11FcsAAMBRPxs6O7HM6vDiglSve8+byxOv+7d9p4Uqp9EAAACAZiiWDiHaEq1Tp04FN7hFixbh5ptvDv379w8DBgwIt956a/jEJz5R8Jr27duHfL5h/2XU9ddfX6cyq74l2owZM2p8ns997nPhl7/8Zejbt28YNmxYeOSRR8Kvf/3r8LWvfS2ceeaZSjQAqKN5G3bXegpt7fZ0TqEdtXN/ebjgjrGJ13994ZZUrw0AAACQhVg6hChLtIkTJxbc3LZt24bVq1fXeF1JSUm44oorCl47ZMiQBs3y0RLt9NNPD+edd1748Y9/HHr37t1gJdry5cvDxz/+8er3+ou/+Ivw4osvHnfPrl27Qv/+/cN77713ytetj1gGAABCCOEfnnw3scT6t+HpnkI76oGxKxOvf03vKaGyKtcoGQAAAAAaSywdQnQlWj6fD5dddlnBCbQVK1bU+vqSkpLw6U9/uvr1n/nMZ0JZWVmD5Rk4cGDo169fmD59eigtLfwv1RuiRKuqqgpf+cpXqt/n7LPPTiwMm5pYBgAAZq9PPoX2uc6jwrod+xslw56Dh8NF3ccl5hg5Z1OjZAAAAABoLLF0CNGVaFOnTi24sR07djzhnv79+xfsefrppxshacOUaIMGDSp4n9GjRzdsyJTEMgAA8JPHZyWWV78duahRc/SfuCYxx9d7TQ6HK51GAwAAAJqPWDqE6Eq0Dh06FNzYlStXnnDPhx9+GFq0aFG9p127do2QtGFKtAsuuKDBfletMcUyAAAUt7ff25lYXJ3TZXTYsOtAo2YpLasIX75rfGKeZ2dtaNQsAAAAAGmKpUOIrkRr06ZN9U1t3bp1nfddddVV1ftatmwZysvL0wv5R/Ut0WbMmFHwHkOHDm34kCmJZQAAKF75fD7cOPidxNLq/73cuKfQjho09b3EPF+5b2Ioq6jKJBMAAABAQ4ulQ4iqRNu3b1/BTW3fvn2d93bu3Llg75IlS1JMekR9S7Q77rij4D3Wr1/f8CFTEssAAFC8Zq5JPoXWtsvosGn3wUwyHTxcGS6/Z0JiridnrMskEwAAAEBDi6VDiKpEmzVrVsFN7d69e533DhkypGDvyJEjU0x6RH1LtO9+97vV+//kT/6k+v+/evXq0KlTp/ClL30p/Nmf/Vlo2bJl+OxnPxv+7u/+LvTr1y/s2bOnAT/FqYllAAAoTvl8Ptww6O3EsqrzK4szzTZk5vrEXJffMyEcKPf3UwAAACB+sXQIUZVoL7zwQsFNHTJkSJ33Tpw4sWBvr169Ukx6RH1LtFatWlXvv+CCC0JVVVXo0aNH+C//5b8UvPex60//9E/DoEGDGv4DnYRYBgCA4jRt9Y7Eourc20eHzR9mcwrtqLKKqvDX901KzDdw6tpMswEAAAA0hFg6hKhKtMGDBxfc1FdffbXOe+fNm1ewt0uXLikmPaI+JVoulwunn3569f6vfOUr4dZbby14z//6X/9r+Mu//Mvw53/+54ll2m9+85t0PlgdxDIAABSffD4frhvwVmJJ1fW19L/uuS6em7UhMd+X7hwf9pVVZB0PAAAAoF5i6RCiKtH69OlTcFPHjh1b570rVqwo2NuhQ4cUkx5RnxJtz549NQqzo/9327Ztw8svvxzKysqqX79+/frQsWPHcMYZZxTsGzZsWIN9nlwuFyorK+u0ysrKohgAAIrP5JUliQXVebePCR/sPZR1vBBCCIcrc+Eb909OzNlvwuqs4wEAAADUixItBXfffXfBTZ08eXKd965bt65g7y233JJi0iPqU6Jt3rw58XTZxRdfHHbt2lXrvmO/8vJ//I//EQ4ebJivperRo8dxv0byeKupDgAAxSWfz4f//cjMxHKq++tLs45XYOTcTYk5L+o+Lnx44HDW8QAAAABOmRItBcV0Em3nzp01iqjTTz89LF68+IR7f/7znxfse+KJJ07xExRSogEQuwnLazmF1nVMKNlXduI3aESVVbnwzT5TE/PeP3Zl1vEAAAAATpkSLQX1+U20+fPnR/WbaOXl5TWKqO985zt12rt48eKCfTfeeOMppK9JiQZAzPL5fPhf/WckllJ3vbE863iJXl+4JTHv+d3Ghh2l5VnHAwAAADglSrQUHPtVhUOHDq3z3kmTJhXs7dmzZ4pJj6hPiRZCCB/72McK3uPee++t895Pf/rTBb+h1hD8JhoAMRu7dFtiIfWFbmPC9tKmdQrtqFwuH77bb1pi7rvfbJrFHwAAAMCJKNFSMGvWrIKb2r179zrvHTp0aMHeESNGpJj0iPqWaBdccEHBezz33HN13nvZZZdV7/uTP/mTk752fcUyAAAUh1wuH77/0PTEMureUU27jBq79INav4Jy296mWf4BAAAAHE8sHUJUJdq+ffsKbmr79u3rvLdLly4Fe5csWZJi0iPqW6L96Ec/KniPl19+uc57v/71r1fv+9jHPnbS166vWAYAgOIwanFyEXV+t7Fh5/6m/bWI+Xw+XPtw8tdQdn0t/X+eAQAAAGhosXQIUZVoIYTQpk2b6pvaunXrOu+7+uqrq/e1bNkylJen/y/M6lui3XfffQXv8fjjj9d57/nnn1+97+yzzz7pa9dXLAMAQPNXlcuHv+2b/JWIvcaszDpenUxeWZKY/9zbR4dNuw9mHQ8AAADgpMTSIURXonXo0KHgxq5ateqEe/bs2RNatGhRvaddu3aNkLT+JdrSpUsL3uO2226r0779+/eHM888s3rf3/zN35z0tesrlgEAoPn7w6KtiQXUhXeMDbsPHM46Xp3k8/nww4FvJX6O//fyoqzjAQAAAJyUWDqE6Eq0KVOmFNzYjh07nnBP//79C/YMGzYs/aCh/iVaCIUnyv7n//yf4fDhE//LvqeeeuqUfzuuocQyAAA0b1W5fPjWg1MTy6fe4+I4hXbUW2t3Jn6Oc7qMDut27M86HgAAAECdxdIhRFei5fP5cMkll1Tf2BYtWoQVK1bU+vrt27eHVq1aFXy14aFDh2p9fevWrQv+4OqjIUq0IUOGFLzP3XfffdzX7927N/zVX/1V9evPPPPMsHbt2lO6dn3EMgAANG+vLticWDx9sfu4sOdgHKfQjsrn8+Gmx95J/Dy/Hr4g63gAAAAAdRZLhxBdiRZCCOPHjy+4uW3btg1r1qyp8bqSkpJw5ZVXFrz2iSeeOO57N7USLZfLhS996UvV73PGGWeEhx9+OOTz+Rqv3bp1a/jqV79acN1bb721Xp/hVMUyAAA0X5VVuXBN7ymJpVPf8Sf+OuimaPb63Ymfp03nUWF1SWnW8QAAAADqJJYOIcoSLYQQfve73xXc4BYtWoSf/exn4eGHHw4DBw4Mt912W/jkJz9Z8JqbbropsXz6qJMt0bZs2RLatm2buD76Pi1btkx8zU9/+tMTXmP16tUFp+lOO+20cPHFF4c77rgjDBkyJAwYMCD8/Oc/Dx//+McLXnPppZeGgwcP1vmeNqRYBgCA5uvlecmn0C7qMS7sPViRdbxT9rOhsxM/123Pzcs6GgAAAECdxNIhRFui5fP5cNtttxXc5OOtH/7wh6G8vPyE73uyJdr7779f5wxJq64n1ObOnRs++9nP1vl9v/3tb4ddu3bV6b3TEMsAANA8VVTlwlUPJJ9C6z+x5un1mCzctCfxc7XuNCos3bI363gAAAAAJxRLhxBtiXbUqFGjwuWXX15rmXT++eeHYcOG1fn9mmqJFkIIpaWl4Te/+U2NU2kfXZ///OfD0KFDQ1VVVZ3fNw2xDAAAzdOIORsTS6Yv3Tk+7CuL9xTaUbc8PTfx8/1i2JysowEAAACcUCwdQvQl2lFr1qwJw4cPD3379g19+vQJzz//fFi8eHHWsVJRWVkZpk2bFoYNGxZ69eoV+vbtG5577rnE34XLSiwDAEDzc7gyF77ea3JiyfTo5Kbz98r6WL51X62n0dZu99toAAAAQNMWS4fQbEo0mpZYBgCA5ufF2cmn0L581/iwv7z5/P3ol8/PT/ycPf6wLOtoAAAAAMcVS4egRCMVsQwAAM3L8U6hDZr6XtbxGtTKbcmn0S7qPi4caEZlIQAAAND8xNIhKNFIRSwDAEDzUtsptEvvntAsi6UbH3sn8fM+/+6GrKMBAAAA1CqWDkGJRipiGQAAmo/DlbnwjfuTT6E9Nq15nUI76o1FWxM/7/cfmh7y+XzW8QAAAAASxdIhKNFIRSwDAEDzMfw4p9AOHm6efx86XJkLV9w7MfFzz31/d9bxAAAAABLF0iEo0UhFLAMAQPNQUVX7KbTBzfQU2lF9x69K/Ny/Hr4g62gAAAAAiWLpEJRopCKWAQCgeRgxp7h+C+2jPth7KJzTZXSNz37u7aPDzv3lWccDAAAAqCGWDkGJRipiGQAA4ne8U2iDpjbvU2hH3frs3MTPP2DK2qyjAQAAANQQS4egRCMVsQwAAPGr7RTaJXeNb/an0I6auWZn4j34eq/JoSqXzzoeAAAAQIFYOgQlGqmIZQAAiFtFVS78zQPJp9AGTi2eU1i5XD58q8/UxPswYXlJ1vEAAAAACsTSISjRSEUsAwBA3EbO2VTrKbT9RXIK7aihM9cn3oufDZ2ddTQAAACAArF0CEo0UhHLAAAQL6fQCu09VBG+0G1M4v14f+eBrOMBAAAAVIulQ1CikYpYBgCAeI2cm3wK7ctFeArtqE6/X5x4T+4dtTzraAAAAADVYukQlGikIpYBACBOFVW5cNUDUxILowFTiu8U2lFLt+xNvCdfunN8KKuoyjoeAAAAQAghng5BiUYqYhkAAOLkFFrtfjjwrcR7M3LupqyjAQAAAIQQ4ukQlGikIpYBACA+lVW5cHVvp9Bq88r8zYn3pt2jM7OOBgAAABBCiKdDUKKRilgGAID4vHScU2ilZRVZx8tcWUVVuPTuCYn3aNGmPVnHAwAAAIimQ1CikYpYBgCAuBzvFNqjk9dkHa/J6DVmZeI9+veXFmUdDQAAACCaDkGJRipiGQAA4vLyvOSvKvzSnU6hfdSm3QdDm84179Pnu44JHx44nHU8AAAAoMjF0iEo0UhFLAMAQDycQjs5vxg2J/FePTF9XdbRAAAAgCIXS4egRCMVsQwAAPH4vVNoJ2XKyu2J9+vq3lNCLpfPOh4AAABQxGLpEJRopCKWAQAgDpVVuXBNLafQHpnkFFqSqlw+/M0DkxPv2dRV27OOBwAAABSxWDoEJRqpiGUAAIjD8U6h7XMKrVaDp72XeN9ueXpO1tEAAACAIhZLh6BEIxWxDAAATV9lVS58s8/UxDLoYafQjmv3gcPhvK5jaty3Np1HhU27D2YdDwAAAChSsXQISjRSEcsAAND0vTI/+RTaxT3GOYVWB78ZuTDx/j0wdmXW0QAAAIAiFUuHoEQjFbEMAABNm1No9bdg44eJ9++yuyeE8sqqrOMBAAAARSiWDkGJRipiGQAAmrZXFziFVl/5fD784JEZiffx9YVbso4HAAAAFKFYOgQlGqmIZQAAaLqqcvnwrVpOofWf6BTayRgxZ2Pifbxh0NtZRwMAAACKUCwdghKNVMQyAAA0Xa8t2FLrKbS9h5xCOxmHDleFi3qMS7yfy7buzToeAAAAUGRi6RCUaKQilgEAoGk63im0hyauzjpelO56Y3ni/ez8ypKsowEAAABFJpYOQYlGKmIZAACaptpOoV3kFNopW7djf+I9Pb/bWL8vBwAAADSqWDoEJRqpiGUAAGh6qnL58K0Hk0+h9ZvgFFp93Dzk3cT7Ouyt9VlHAwAAAIpILB2CEo1UxDIAADQ9ry90Ci0t45ZtS7y3335wasjn81nHAwAAAIpELB2CEo1UxDIAADQtTqGlq7IqF77ac1Li/X177c6s4wEAAABFIpYOQYlGKmIZAACallpPoXUfF/YedAqtITwyaU3iPb7t8u5SqwAAIABJREFUuXlZRwMAAACKRCwdghKNVMQyAAA0HVW5fPh2LafQ+jqF1mC2l5aFtl1G17jH53QZHbbtLcs6HgAAAFAEYukQlGikIpYBAKDpcAqt8fzqhfm+MhMAAADITCwdghKNVMQyAAA0DVW5fPhO32nJp9DGr8o6XrMze/3uxHt95b0TQ0VVLut4AAAAQDMXS4egRCMVsQwAAE3DHxZtrfUU2p6Dh7OO1+zk8/nwvX7TE+/56CUfZB0PAAAAaOZi6RCUaKQilgEAIHvH/S00p9BS8+ysDYn3/MePv5N1NAAAAKCZi6VDUKKRilgGAIDsvbpgc2KZ80Wn0FK1v7wyXHjH2MR7v6akNOt4AAAAQDMWS4egRCMVsQwAANmqrMqFa3pPSSxyHnQKLXXdXluaeO+7v74062gAAABAMxZLh6BEIxWxDAAA2Ro5Z1Pyb6H1GBf2HqzIOl6zt7qktNZTgAfK/b0bAAAASEcsHYISjVTEMgAAZOdwZS58vdfkxBKn/8Q1WccrGjc99k7in8Hz727IOhoAAADQTMXSISjRSEUsAwBAdp6btSGxvPnyXeNDaZlTaI3lzcVbE/8cvv/Q9JDP57OOBwAAADRDsXQISjRSEcsAAJCNsoqq8NWekxLLm4FT12Ydr6gcrsyFK+6dmPhn8YdFW7OOBwAAADRDsXQISjRSEcsAAJCNYW+tTyxtLrt7gt/iykDf8asS/zy+0G1MWLplb9bxAAAAgGYmlg5BiUYqYhkAABrfocNVtZ58emL6uqzjFaUP9h4K53QZnfhn8rWek8KO0vKsIwIAAADNSCwdghKNVMQyAAA0viemr0ssa664d2I4dLgq63hFq9eYlYl/Lq07jQo3DHo7lFf6swEAAAAaRiwdghKNVMQyAAA0rgPlleHSuyckFjXD3lqfdbyiVlmVC//w5Lu1Fmn/7+VFIZ/PZx0TAAAAaAZi6RCUaKQilgEAoHENnLo2saD5as9JoazCSaes7Tl4OFzTe0qtRdrQmYpOAAAAoP5i6RCUaKQilgEAoPGUllWEL981PrGcef7dDVnH44/Wbi8NX+w+LvHP6XOdR4Xpq3dkHREAAACIXCwdghKNVMQyAAA0nv4T1yQWM9+4f3I4XJnLOh4fMWXl9tCmc/JptIt7jAvrdx7IOiIAAAAQsVg6BCUaqYhlAABoHHsPVoSLeiSfbho5Z1PW8Ujw2LT3av1ax28/ODXsK6vIOiIAAAAQqVg6BCUaqYhlAABoHH3GrUosY67pPSVUVjmF1hTl8/nQccTCWou0f3xqdqjK5bOOCQAAAEQolg5BiUYqYhkAANK3+8DhcOEdYxOLmFcXbM46HsdRVlEVrhvwVq1FWs8xK7KOCAAAAEQolg5BiUYqYhkAANLXc8yKxALmO32nOckUgZJ9ZeHKeyfWWqS9Ml8RCgAAAJycWDoEJRqpiGUAAEjXjtLycH635FNoby7emnU86mjhpj3hvK5jEv8cz+s6JizY+GHWEQEAAICIxNIhKNFIRSwDAEC67npjeWLx8v2HpoecU2hReW3BllpPo11578SwbW9Z1hEBAACASMTSISjRSEUsAwBAerbtLav19NLYpduyjscp6DVmZa1F2nWPzgxlFVVZRwQAAAAiEEuHoEQjFbEMAADp6fba0sSy5QePzAj5vFNoMarK5cMvhs2ptUj7t+EL/NkCAAAAJxRLh6BEIxWxDAAA6diy51A49/bRiUXL5JUlWcejHkrLKsJ3+k6rtUgbPO29rCMCAAAATVwsHYISjVTEMgAApKPzK4sTC5brB7zlpFIz8P7OA+FLd45P/DNu01lRCgAAABxfLB2CEo1UxDIAADS8jbsOhrZdkk+hTV+9I+t4NJC31u4M59Ty5/zF7uPCmpLSrCMCAAAATVQsHYISjVTEMgAANLzfjlyUWKz8aPDbTqE1M8PeWl/r1zpe3XtK2HPwcNYRAQAAgCYolg5BiUYqYhkAABrWezv2h891Ti5V3nlvV9bxaGD5fD50+n3yV3e27jQq/PTJWaGyKpd1TAAAAKCJiaVDUKKRilgGAICG9evhCxLLlPZPzMo6Gik5XJkLPxr8dq1FWo8/LMs6IgAAANDExNIhKNFIRSwDAEDDWV1SGtrUcgpt3obdWccjRTv3l4ev95pca5E2fPbGrCMCAAAATUgsHYISjVTEMgAANJx/eX5eYoHyf4bOzjoajWDZ1r3h/G5jE5+Bc28fHRZu2pN1RAAAAKCJiKVDUKKRilgGAICGsWzr3lpPISlPiseYJR/U+hz8/aC3s44HAAAANBGxdAhKNFIRywAA0DBueXpuYnFyy9Nzso5GI+s3YbVCFQAAADiuWDoEJRqpiGUAAKi/RZv21FqaLNu6N+t4NLJcLh9ufTa5VO3w4oKs4wEAAABNQCwdghKNVMQyAADU38+fmp1YmNz23Lyso5GRjbsOhjadaz4T53QZHbbuOZR1PAAAACBjsXQISjRSEcsAAFA/8zZ8mFigtek8KqzaVpp1PDJU22m0nqNXZB0NAAAAyFgsHYISjVTEMgAA1M9Pn5zla/tINHv97sRn46Ie48KBcv9cAAAAAMUslg6h2ZRoa9euDSNHjgwPPfRQ6NOnT3jxxRfDkiVLso5VtGIZAABO3ax1uxJLks91HhXe27E/63hkLJ/Ph3aPzkx8Roa9tT7reAAAAECGYukQoi/RRo8eHa688sqCm/3RdeGFF4Znnnkm9RwbN24Mr732WujWrVu49tprw1lnnVWQ45prrknlulVVVeGKK66o8bmnTp2ayvXqKpYBAODU3fjYO4kFyW9GLsw6Gk3E6wu3JD4jV/eeEqpy+azjAQAAABmJpUOItkTL5/PhV7/6Va3l2bHrhhtuCOXl5Q2eo2vXrqFVq1YnvH5aJdoDDzyQeD0lGgBp2rDrQGI5ck6X0WHDrgNZx6OJqKjKhb++b1LiszJu2bas4wEAAAAZiaVDiLZE69SpU8ENbtGiRbj55ptD//79w4ABA8Ktt94aPvGJTxS8pn379iGfb9j/6vn666+vU4mXRom2Zs2a8N/+239TogHQ6F6ZvzmxGOn0+8VZR6OJGTT1vcRn5cbH3sk6GgAAAJCRWDqEKEu0iRMnFtzctm3bhtWrV9d4XUlJSY2vOhwyZEiDZvloiXb66aeH8847L/z4xz8OvXv3TrVEy+fz4Zprrin42kolGgCN5Y7XlyYWI7PX7846Gk3M3oMV4fxuYxOflyWb92YdDwAAAMhALB1CdCVaPp8Pl112WcEJtBUrVtT6+pKSkvDpT3+6+vWf+cxnQllZWYPlGThwYOjXr1+YPn16KC0tLfhraZZogwcPrn7v733ve6FHjx5KNAAazXWPzkz8KseDh/3vPTXVVrr+2/AFWUcDAAAAMhBLhxBdiTZ16tSCG9uxY8cT7unfv3/BnqeffroRkqZXom3evDl88pOfDKeddlr47//9v4d169Yp0QBoNGUVVeHc20fXKET+rv+MrKPRRK3feSC06VyzRGvbZXTYtrfh/uMmAAAAIA6xdAjRlWgdOnQouLErV6484Z4PP/wwtGjRonpPu3btGiFpeiXaD37wg+r3feCBB0IIQYkGQKOZv/HDxFNFnV9ZknU0mrBbnp6b+NzcP/bE/ywHAAAANC+xdAjRlWht2rSpvqmtW7eu876rrrqqel/Lli1DeXl5eiH/KI0S7fnnn69+z0suuaT6wVKiAdBYnnprfWIZMnLOpqyj0YS9896uxOfmS3eO9zWgAAAAUGRi6RCiKtH27dtXcFPbt29f572dO3cu2LtkSfr/tXxDl2g7duwIrVq1Cqeddlo444wzwpw5c6r/mhINgMby6+ELEsuQVdtKT7yZopXP58O1D89IfHaefef9rOMBAAAAjSiWDiGqEm3WrFkFN7V79+513jtkyJCCvSNHjkwx6RENXaL95Cc/qX6/f/u3fyv4a0o0ABrLNb2n1ChBLrxjbKjK5bOORhP3yvzNiSXaN/tMDTnPDwAAABSNWDqEqEq0F154oeCmDhkypM57J06cWLC3V69eKSY9oiFLtDfeeKP6vf7qr/4q7N+/v+CvK9EAaAwfHjicWIL85PFZWUcjAocrc+HKeycmPkMTl5dkHQ8AAABoJLF0CFGVaIMHDy64qa+++mqd986bN69gb5cuXVJMekRDlWh79+4Nf/mXf1n9Xm+++WaN1zRGiZbL5UJlZWWdVllZWRQDAMDJmbJqe2IB0mvMyqyjEYkBU9YqYgEAAKDIKdFS0KdPn4KbOnbs2DrvXbFiRcHeDh06pJj0iIYq0f7pn/6p+n1uvPHGxNc0Rol27DVOZjXVAQDg5Dw0cXViATJ26basoxGJDw8cDl/oNibxOVq2dW/W8QAAAIBGoERLwd13311wUydPnlznvevWrSvYe8stt6SY9IiGKNGmTp0aTj/99HDaaaeFP/uzPwvbtiX/S0olGgCN4edPzU4sP7btLcs6GhG5/dUlic/Rb0YuzDoaAAAA0AiUaCkotpNohw4dCm3btq1+jyeeeKLW1yrRAEhbPp8Pl9w1vkbx8df3Tco6GpF5b8f+xBLt3NtHh+37FLIAAADQ3CnRUlCf30SbP39+dL+J9tvf/rZ6/9VXXx3y+Xytr/WbaACkbcOuA4nFxz8/Oy/raEToF8PmJD5PfcatyjoaAAAAkDIlWgpeeOGFgps6dOjQOu+dNGlSwd6ePXummPSI+pRoc+bMCWeeeWY47bTTQosWLcLKlSuP+/rGKNFORiwDAEDdvb5wS2LpMWjqe1lHI0Jvrd2Z+Dxdctf4cOhwVdbxAAAAgBTF0iFEVaLNmjWr4KZ27969znuHDh1asHfEiBEpJj2iPiXapZdeWr33zjvvPOHrlWgApO3ON5Yllh7vvLcr62hEKJ/Ph+8/ND3xmXr+3Q1ZxwMAAABSFEuHEFWJtm/fvoKb2r59+zrv7dKlS8HeJUuWpJj0iPqUaH/6p39avbd169ahbdu2x12f+tSnCq539tlnF/z1FStWpPMhaxHLAABQdz8c+FaNsuNznUeFA+X+N55T89LcTYkl2rcfnBpyudq/xhoAAACIWywdQlQlWgghtGnTpqBcqqurr766el/Lli1DeXl5eiH/qKFKtIZYCxcuTOdD1iKWAQCgbg5X5sJ5XcfUKDu+12961tGIWHllVbj8nomJRdqUlduzjgcAAACkJJYOIboSrUOHDgU3dtWqE//4/J49e0KLFi2q97Rr164RkirRYhgAAOpm8eY9iUXHf7y8OOtoRO7hSWsSn61/ePLdrKMBAAAAKYmlQ4iuRJsyZUrBje3YseMJ9/Tv379gz7Bhw9IPGupXop0sv4kGQJqeeef9xKLjhXc3Zh2NyO3aX554yrF1p1Fh5bZ9WccDAAAAUhBLhxBdiZbP58Mll1xSfWNbtGhx3N/72r59e2jVqlXBb4UdOnSo1te3bt264A+uPpRoTX8AAKib34xcmFhyLN+q5KD+Or+yOPH5+t1Li7KOBgAAAKQglg4huhIthBDGjx9fcHPbtm0b1qxZU+N1JSUl4corryx47RNPPHHc91aiNYxYBgCAuvnWg1NrFBzndxsbKqtyWUejGVhTUppYop13+5iwozT937EFAAAAGlcsHUKUJVoIIfzud78ruMEtWrQIP/vZz8LDDz8cBg4cGG677bbwyU9+suA1N910U8jn88d935Mt0bZs2RLatm2buD76Pi1btkx8zU9/+tMGuR9KNADSsvdgRWLBcePgd7KORjPys6GzE5+zvhNWZx0NAAAAaGCxdAjRlmj5fD7cdtttBTf5eOuHP/xhKC8/8X/JfLIl2vvvv1/nDEmroU6oKdEASMuMNTsSy437Rtf+dcpwsqavTn7OLrt7QiirqMo6HgAAANCAYukQoi3Rjho1alS4/PLLay2pzj///DBs2LA6v58SrWHEMgAAnNgjk9Yklhujl3yQdTSakXw+H77bb1riszZ89sas4wEAAAANKJYOIfoS7ag1a9aE4cOHh759+4Y+ffqE559/PixevDjrWEUrlgEA4MRueXpOYrGxZc+hrKPRzIyYszHxWftuv2kn/EpuAAAAIB6xdAjNpkSjaYllAAA4vnw+Hy6/Z0KNUuOKeycqNWhwZRVV4bK7az5vrTuNCtNX78g6HgAAANBAYukQlGikIpYBAOD4Nu0+mFho3PL03Kyj0Uz1m7A68Zn72dDZWUcDAAAAGkgsHYISjVTEMgAAHN+bi7cmFhoDpqzNOhrN1I7S8nDe7WMSn7vVJaVZxwMAAAAaQCwdghKNVMQyAAAc3z1vLk8sM95auzPraDRjv3tpUeJz1+n3fu8WAAAAmoNYOgQlGqmIZQAAOL6/H/R2jSKjTedRYV9ZRdbRaMZWbtuXWKKd13VM2LW/POt4AAAAQD3F0iEo0UhFLAMAQO0qqnLhC91qfq3ed/pOyzoaReAfnnw3sUjrP3FN1tEAAACAeoqlQ1CikYpYBgCA2i3dsjexxPj3lxZlHY0iMGXV9sTn7/J7JoSyiqqs4wEAAAD1EEuHoEQjFbEMAAC1e/7dDYklxrOzNmQdjSKQy+XDtx+cmvgMjpy7Ket4AAAAQD3E0iEo0UhFLAMAQO1+99KixAJj6Za9WUejSLzw7sbEZ/D7D00P+Xw+63gAAADAKYqlQ1CikYpYBgCA2v1t32k1yovPdx0TKqpyWUejSJRVVIVL7hqfWKStKSnNOh4AAABwimLpEJRopCKWAQAgWWlZRWjTuWZxccOgt7OORpHpM25VYon2nK8VBQAAgGjF0iEo0UhFLAMAQLK31+5MLC7ufnN51tEoMks27018Fv/1xQVZRwMAAABOUSwdghKNVMQyAAAkGzh1bWJx8YdFW7OORpGprMqFL3YfV+NZ/Ov7JvldNAAAAIhULB2CEo1UxDIAACT7p2fmJpZom3YfzDoaRejnT81OfB437vI8AgAAQIxi6RCUaKQilgEAoKZ8Ph+uvHdijcLisrsnOPlDJmo7GTly7qasowEAAACnIJYOQYlGKmIZAABq+mDvocTC4hfD5mQdjSI1b8PuxGfy319alHU0AAAA4BTE0iEo0UhFLAMAQE1jlnyQWFg8PGlN1tEoUocrc+HzXcfUeCavemBK1tEAAACAUxBLh6BEIxWxDAAANfUcvSKxRJu2ekfW0ShiP3l8VuJz+cHeQ1lHAwAAAE5SLB2CEo1UxDIAANR002PvJJYVew9WZB2NItZvwurE5/L1hVuyjgYAAACcpFg6BCUaqYhlAAAoVJXLhwvuGFujqPhWn6lZR6PIvb12Z2KJdvurS7KOBgAAAJykWDoEJRqpiGUAACi0ctu+xKKi44iFWUejyB06XBXOvX10jWfzb/tOyzoaAAAAcJJi6RCUaKQilgEAoNDw2RsTS7Sn334/62gQbhj0duLzuWt/edbRAAAAgJMQS4egRCMVsQwAAIU6/X5xYkmxcNOerKNBuH/sysTnc+zSD7KOBgAAAJyEWDoEJRqpiGUAACj0/Yem1ygozrt9TCivrMo6GoQpq7Ynlmh3vrEs62gAAADASYilQ1CikYpYBgCA/3SgvDJ8rnPNguL6AW9lHQ1CCCHsK6tIfEavfXhG1tEAAACAkxBLh6BEIxWxDAAA/+nddbsST/n0+INTPjQdP3hkRo1ntE3nUWFfWUXW0QAAAIA6iqVDUKKRilgGAID/9Ni09xJLtNcWbMk6GlS7643lic/plJXbs44GAAAA1FEsHYISjVTEMgAA/KfbnpuXWE68v/NA1tGg2til2xKf015jVmYdDQAAAKijWDoEJRqpiGUAAPhPX+s5qUYx8eW7xod8Pp91NKi2+8DhxBLt/xvot/sAAAAgFrF0CEo0UhHLAABwxPZ9ZYnFxP8ZOjvraFDDd/tNq/Gstu0yOhw6XJV1NAAAAKAOYukQlGikIpYBAOCI8cuSvyKv74TVWUeDGrq+tiTxeX1r7c6sowEAAAB1EEuHoEQjFbEMAABHPDB2ZWIpMWXl9qyjQQ1/WLRV6QsAAAARi6VDUKKRilgGAIAj2j8xK7GU2H3gcNbRoIZte5O/fvTHj7+TdTQAAACgDmLpEJRopCKWAQAghFwuH77YfVyNQuKqB6ZkHQ1qdXXvKTWe2c93HRPKK/0uGgAAADR1sXQISjRSEcsAABDCmpLSxFM9//rigqyjQa1+99KixOd27vu7s44GAAAAnEAsHYISjVTEMgAAhDBy7qbEMmLozPVZR4NavTxvc+JzO2DK2qyjAQAAACcQS4egRCMVsQwAACHc/uqSxDJi3oYPs44Gtdq0+2Dic/t/hs7OOhoAAABwArF0CEo0UhHLAAAQwrUPz6hRRLTtMjqUVfhtKZqufD4fvtpzUo1n98I7xobKqlzW8QAAAIDjiKVDUKKRilgGAKDYlVVUhXO6jK5RRPzvR2ZmHQ1O6NfDFySeRlu8eU/W0QAAAIDjiKVDUKKRilgGAKDYzX1/d2IJ0e21pVlHgxN6/t0Nic/vkzPWZR0NAAAAOI5YOgQlGqmIZQAAit2TM9YllhC/n7c562hwQmu3lyY+v//3mblZRwMAAACOI5YOQYlGKmIZAIBi96sX5ieWEGu37886GpxQPp8Pl949ocbz++W7xodcLp91PAAAAKAWsXQISjRSEcsAABS7b9w/uUYBcVGPcQoIovHPz85LLIJXbSvNOhoAAABQi1g6BCUaqYhlAACK2c795Ynlw81D3s06GtTZU2+tT3yOn33n/ayjAQAAALWIpUNQopGKWAYAoJhNWlGSWD70Gbcq62hQZ8u27k18jn/1wvysowEAAAC1iKVDUKKRilgGAKCYPTh+VWL5MHF5SdbRoM6qcvlwUY9xNZ7jK+6dGPJ5X0sKAAAATVEsHYISjVTEMgAAxezmIe8mlmg7SsuzjgYn5RfD5iQ+y+t3Hsg6GgAAAJAglg5BiUYqYhkAgGKVy+XDxQmnd77ea3LW0eCkDZ72XmKJNmLOxqyjAQAAAAli6RCUaKQilgEAKFbv7difWDr80u9IEaH5Gz9MfJ5/M3Jh1tEAAACABLF0CEo0UhHLAAAUq1fmb04sHZ6Yvi7raHDSKqpy4fxuY2s8z9+438lKAAAAaIpi6RCUaKQilgEAKFZ3vL40sUSb8/7urKPBKfmHJ5N/42/LnkNZRwMAAACOEUuHoEQjFbEMAECxuu7RmTXKhnO6jA6HDldlHQ1OycOT1iSWaK8t2JJ1NAAAAOAYsXQISjRSEcsAABSjsoqqcO7to2uUDf+r/4yso8Epm7VuV2KJ1vmVJVlHAwAAAI4RS4egRCMVsQwAQDGav/HDxLKhy6vKBuJVVlEVzrt9TI3n+lsPTs06GgAAAHCMWDoEJRqpiGUAAIrRU2+tTyzRRs7ZlHU0qJcfDX478dneUVqedTQAAADgI2LpEJRopCKWAQAoRr8eviCxaFhdUpp1NKiX3uNWJj7bo5d8kHU0AAAA4CNi6RCUaKQilgEAKEbX9J5So2T4YvdxoSqXzzoa1Mu01TsSS7Qef1iWdTQAAADgI2LpEJRopCKWAQAoNh8eOJxYMvzk8VlZR4N6219eGc7pMrrG8/13/WdkHQ0AAAD4iFg6BCUaqYhlAACKzZRV2xNLtPvHrsw6GjSI6x6dWeP5btN5VNh7sCLraAAAAMAfxdIhKNFIRSwDAFBsHpq4OrFEG7dsW9bRoEHcO2p54jM+aUVJ1tEAAACAP4qlQ1CikYpYBgCg2Pz8qdmJBUPJvrKso0GDmLC8JPEZv2/0iqyjAQAAAH8US4egRCMVsQwAQDHJ5/PhkrvG1ygXvtpzUtbRoMHsOZj8u3/XDXgr62gAAADAH8XSISjRSEUsAwBQTDbsOpBYLvzzs/OyjgYN6vsPTa/xnJ/TZXQ4UO6fRwAAAKApiKVDUKKRilgGAKCYPDtrQ2KJNnjae1lHgwZ1x+tLE5/1GWt2ZB0NAAAACPF0CEo0UhHLAAAUi027D4aLuo9LLBZmrduVdTxoUG8u3pr4rD84flXW0QAAAIAQT4egRCMVsQwAQDGoqMqF6we8lVgqXNRjXDh42P9G07xsLy1LfN5vfOydrKMBAAAAIZ4OQYlGKmIZAIBicP/YlYmFQutOo8LDk9ZkHQ9S8a0+U2s87+d1HRPKKqqyjgYAAABFL5YOQYlGKmIZAIDmbuaanaFN5+QC7UeD3w6VVbmsI0IqOv1+ceJzP3v97qyjAQAAQNGLpUNQopGKWAYAoDnbub88XHHvxMQi4eIe48KWPYeyjgipeWX+5sRn/xGnLwEAACBzsXQISjRSEcsAADRXuVw+/Pyp2bV+jePYpR9kHRFStfnDg4nP/s1D3s06GgAAABS9WDoEJRqpiGUAAJqrJ2esq7VAu/3VJVnHg0bx9V6Tazz/F9wxNlT4GlMAAADIVCwdghKNVMQyAADN0dIte8O5t49OLNC+229aKKuoyjoiNIqOIxYmzsHCTXuyjgYAAABFLZYOQYlGKmIZAIDmZn95Zfhmn6mJxcHnu44Jq7aVZh0RGs3w2RsTZ+Hx6e9lHQ0AAACKWiwdghKNVMQyAADNzW9GJp+8ad1pVHhu1oas40GjWrdjf+Is3PL0nKyjAQAAQFGLpUNQopGKWAYAoDl5dcHmWgu0f352Xsjn81lHhEaVz+fD5fdMrDEPF/cYF3I58wAAAABZiaVDaDYl2tq1a8PIkSPDQw89FPr06RNefPHFsGTJkqxjNaiSkpIwadKk8Nhjj4VevXqF+++/Pzz++ONh0qRJobS0aX09VywDANBcvL/zQLjwjrGJBdrXek4Kew4ezjoiZOKXz89PnIsVH+zLOhoAAAAUrVg6hOhLtNGjR4crr7yy4GZ/dF144YXhmWeeST3Hxo0bw2uvvRa6desWrr322nDWWWcV5LjmmmtO+j2rqqrCxIkTwy9/+cvw+c+Rer76AAAgAElEQVR/vtbPeNppp4UzzzwztGvXLkyfPr3hP9wpiGUAAJqDw5W50O7RmYlFwec6jwpz3t+ddUTIzNNvv584G8PeWp91NAAAAChasXQI0ZZo+Xw+/OpXvzpusfTRdcMNN4Ty8vIGz9G1a9fQqlWrE17/VEq0b3zjG3X+fB9d//Iv/5L5AxfLAAA0B/eNXlHr1zj2n7gm63iQqRUf7EucjX95fl7W0QAAAKBoxdIhRFuiderUqeAGt2jRItx8882hf//+YcCAAeHWW28Nn/jEJwpe0759+wb/PZjrr7++TsXWqZRoX/7ylwve41Of+lRo165duPPOO8OgQYPCk08+Gbp27RouvfTSGte76aabMv3tm1gGACB201bvqLVAu/Gxd0KV332iyOVy+fClO8fXmI/L75ngdwIBAAAgI7F0CFGWaBMnTiy4uW3btg2rV6+u8bqSkpJwxRVXFLx2yJAhDZrloyXa6aefHs4777zw4x//OPTu3btBSrQzzjgj/P3f/30YNWpUqKqqqvW1I0eOrFEaPvXUU/X4ZPUTywAAxGx7aVm4/J4JiQXal+8aHz7YeyjriNAk3PL03MQ5eW/H/qyjAQAAQFGKpUOIrkTL5/PhsssuKziBtmLFilpfX1JSEj796U9Xv/4zn/lMKCsra7A8AwcODP369QvTp08PpaWlBX+tviXaXXfdddzPdqyxY8cWXPOcc8456Ws2lFgGACBWuVw+3Dzk3VpPoY1fti3riNBkPDF9XeKcvDh7Y9bRAAAAoCjF0iFEV6JNnTq14MZ27NjxhHv69+9fsOfpp59uhKT1L9FOxfe+972C6y5fvrxRrnusWAYAIFaPTXuv1gLtjteXZh0PmpRFm/YkzkrHEQuzjgYAAABFKZYOIboSrUOHDgU3duXKlSfc8+GHH4YWLVpU72nXrl0jJM2mRDv2ayTfeOONRrnusWIZAIAYLdq0J7TtMjqxFPj+Q9NDWUXtX/8LxaiyKhcuuGNsjXn5eq/JWUcDAACAohRLhxBdidamTZvqm9q6des677vqqquq97Vs2TKUl5enF/KPsijRBg0aVHDd4cOHN8p1jxXLAADEprSsIlz1wJTEAu0L3caEtdtLT/wmUIRq+/rTTbsPZh0NAAAAik4sHUJUJdq+ffsKbmr79u3rvLdz584Fe5csWZJi0iOyKNF+97vfFVx36tSpjXLdY8UyAAAxyefz4dfDF9T6NY7D/b4T1OrRyWsS5+b38zZnHQ0AAACKTiwdQlQl2qxZswpuavfu3eu8d8iQIQV7R44cmWLSIxq7RMvn8+Gcc86pvubHPvaxsG/fvtSvmySWAQCIycvzNtdaoP3yhfkhn89nHRGarNnrdyfOzn+8vDjraAAAAFB0YukQoirRXnjhhYKbOmTIkDrvnThxYsHeXr16pZj0iMYu0UaOHFlwzeuuuy71a9YmlgEAiMW6HfsTf9Pp6O867T1UkXVEaNLKK6vCeV3H1Jifb/aZmnU0AAAAKDqxdAhRlWiDBw8uuKmvvvpqnffOmzevYG+XLl1STHpEY5Zo27dvD2eddVb19c4444wwf/78Br1GLpcLlZWVdVplZWVRDABADMorq8K1D89ILNDO6TI6zNvwYdYRIQo3PfZO4hxt31eWdTQAAAAoKkq0FPTp06fgpo4dO7bOe1esWFGwt0OHDikmPaKxSrSKiorwzW9+s+B6//7v/97g1+nRo0fBNU5mNdUBAIjBXW8sr/VrHAdMWZt1PIhG3/GrEufoJ4/PCrsPHM46HgAAABQNJVoK7r777oKbOnny5DrvXbduXcHeW265JcWkRzRWifaP//iPBdf6yle+Eg4fbvh/EaREA2hcm3YfDP/64oJaC7T2T8wKVTm/gwZ1NXPNzlrn6Rv3Tw7Lt2bzW7IAAABQbJRoKXASrabf/va3Bdc599xzw7Zt21K5lhINoHHsOXg43PPm8nDe7TV/v+nouvTuCaHEV9DBSTl0uCpc1H1crXP1hW5jwhuLtmYdEwAAAJo9JVoK6vObaPPnz292v4nWtWvXgmu0bt06bNy4scGvc5TfRANIV1lFVXhi+rpwcY/a/yX/0TV5ZUnWcSFKL87eeML56jVmpVOeAAAAkCIlWgpeeOGFgps6dOjQOu+dNGlSwd6ePXummPSINEu0Y7/a8rOf/WxYv359g16jPmIZAICmIJfLh9cXbgnfuH/yCf/lfutOo8KdbyzLOjJEbfSSD8IFd4w97pz9bOjssPdgRdZRAQAAoFmKpUOIqkSbNWtWwU3t3r17nfcOHTq0YO+IESNSTHpEWiXafffdV/DeZ599dli7dm2DvX9DiGUAALL29ns7w/9+ZGadyrPWnUaFHn9Y5oQMNICV2/aFqx6Yctx5u6b3lLC6pDTrqAAAANDsxNIhRFWi7du3r+Cmtm/fvs57u3TpUrB3yZIlKSY9Io0S7f777y9437POOiusWrWqQd67IcUyAABZWVNSGn4xbE6dy7P2T8wKS7fszTo2NCt7Dh4ONw9597izd+EdY8O4Zen83uyxtu0tC0Nnrg93vrEsjF26TWEOAABAsxVLhxBViRZCCG3atCn4DbC6uvrqq6v3tWzZMpSXl6cX8o8aukTr3bt3wXv+xV/8RVi+fHn9g6YglgEAaGzb95WFzq8sDp/rXLfy7Hv9pocpq7aHfN6/TIc0VFblwn2jV5xwFvtOWB1yKZRa+Xw+vL12Z7jtuXnhnC6jC67Z7tGZynMAAACapVg6hOhKtA4dOhTc2LqcwtqzZ09o0aJF9Z527do1QtKGLdH69etX8H6tWrUKS5cubZigKYhlAAAay4HyytB3wupwfrfj/w7T0XXlvRPDiDkbnUSBRvL6wi3h813HHHcub3l6bigta5jfSdt7qCIMnbk+fOvBqce95uc6jwp3vbE87C/3z1IAAAA0H7F0CNGVaFOmTCm4sR07djzhnv79+xfsGTZsWPpBQ8OVaI888kjBe/35n/95WLRoUcMFTUEsAwCQtsqqXHj+3Q3h8nsm1qk8u/COseHhSWvCwcP+dxMa29Ite8PXe00+7ox+p++0sG7H/npdo9PvF9e5UD+6vtpzUqN9rSSnprIqF/aXV4ad+8vDlj2Hwns79odlW/eGVdtKQ1lFVdbxAAAAmpRYOoToSrR8Ph8uueSS6hvbokWLsGLFilpfv3379tCqVavq15999tnh0KFDtb6+devWBX9w9dEQJdqgQYMK3udTn/pUWLBgQb1yNYZYBgAgLfl8PkxYXhK+fYJTJkfXOV1Gh66vLQk7StP/umGgdjv3l4ebHnvnuPN6UY9xYcrK7XV+z7KKqvD7eZvDDwe+dVLFWW2n4bbsqf2fZTk1FVW5sKakNLy5eGt4aOLq0P31peE/Xl4cfj18Qbj12bnh50/NDj9+/J1w/YC3wt/1nxG+1Wdq+FrPSeGyuyeEC+8YW+OrOI9dF9wxNnQcsTBMX73DCWMAAIAQT4cQXYkWQgjjx4///9m77/Cqy/v/42FUQEUR0TpqBRVFRW2l1lFHta46EOteqFVaS7UtVVs2FQh7740MWYqsEEIWZJAQEkJ2SAIJSYBsstdJznn9/uALP89Ick7IOckhz8d1va/LSz6f+/6czzl3xueV+77Nbu6tt96q1NRUq+Nyc3P1wAMPmB27bNmyRttuSyHaihUr1KFDB7MA7fDhwxd0Ta7iLgMAAC6UyWRSflmNItKLtOlQpiZ5J2nImkj9frp94dnN//XSp2silZbX/JktAFqWod6ocTsSGh23vYd7aUFgWqP7FWYWVmrS7iT96pu9FxyeWQYyy4OPq67e6MK70rLOVNQqNbdMuaXVLn0d9UaTjueXa0/8ac31T9XfvzusZ2bt120jGw/BWrIemOiniV6JSjhVwn6XAAAAANotd8kQ3DJEk6SvvvrK7AZ36dJFH3zwgebOnauFCxfqs88+U/fu3c2OefPNN5v8RdXREO3kyZO69dZbbdZP2+natavNY959990G2+7YsaNZG1deeWWDfTVUc+fOdfjetgR3GQAAYK/SaoNis4u1/chJzfJN0RcbovXSvBDdPdan2Q9SX1kQqoj0otZ+aQAasDkyS31HNr5P2tD1h82WX603muSflKsPV0Wo93DHvibcNnK3vtgQrc83RNt1/B/nBOtIVnEr3iH7lFYbdCCtQIv3H9PQ9Yf1uynmS2b2Ge6l30z00wtzg/Xx6kP67w+xmrn3qNaFn9DehBwdySrW6ZIqGRwI24xGkzILK+WbmKsFgWn658ZoPT8nWH2b2PfO1fXsrCAt3n9Mp0uYXQgAAACgfXGXDMFtQzSTyaTPPvvM7CY3VoMGDVJNTdNLZDkaomVkZNh9DbaqsRlqF9LuuRo3bpwDd7XluMsAAICfMtQblZJbJp+EHC3ef0z/+T5WbywOs3s/M3vrsamB2hV7ihkIgBuIzjyj33o2/jXgudlBiskq1sJ9aU3uqWarHpkcoAWBaWbLuQan5uvxaYFNntt7uJfGbI9XabWhFe/S/1dZW6fIjCKtCEnXPzdG60kHZuXa81rvH++r52YHafDKCH21JUbTfJK1JixDO2NOacn+Y/r35hi9PD/E4T3nWrt6D/fSu8vDtSUyS+U1/NwMx9QbTUo8VarDmWdUU8f+ewAAAHAP7pIhuG2Ido6Xl5cGDBjQYIjUr18/rV692u72CNFahrsMAACQzu5XNMs3pcWXXLOs+77Zq5Uh6aqtc98l2ID2KK+0Wq+2wH5mljV4ZYT8EnMb3COr2lCvGXuP2rXU4AMT/eQVe9ql4XxNXb1isoq1NvyEvtoSo+dmB6mPg7PvKOu6Y7S3vtgQrcCjeW69ZCecy2g0KSK9SGO3x+s3E/9/0P+rb/Zqyp5k9k4EAABAm+cuGYLbh2jnpKamauPGjZo5c6amT5+u9evXKzY2trUvq91ylwEAAIHJeXpsatOzPS6k+o7y1iTvJJVUtY2ZIgAcV1NXr+FbYy/468F93+yV5+4knSissLvvtLwyvbEkzK72P1wVoayiyhZ//eU1dYo/WaJNhzI18sc4vTQvxKX7iLV23TZyt/qP9dGACb56ZHKAnpqxT3+cE6xXF4bqnWXh+mhVhD5bF6V/bTqi//4Qq3E7EjTJO0kzfVP06ZrIZt+rARN89b+dCYrLZv80nA3ODmUUadyOBD0wsfEZsn2Ge+kvayN1IK2Azw4AAADaJHfJEC6aEA1ti7sMAADt18niKg1ZE+m0B64DJvjq9cUHNNmbvwYHLhYmk0nrwk/o1hGOByKvLAjVD1HZqjY0b6k1k8mkzZFZus+OGbN3jPbWwn1pDu0hZjKZlFdWrciMIv0Qla2Zvin658ZoDVoYqvvH+7Z6iOXM6j/OR39adEDDt8ZpVWi6QtMKlH2mUkUVtaqsrWtwpqAjzlTUam1YxgXNaPzDzP1aEJim7DMtH5Ki7TIaTYo6UaT/7UzQg57+zf7srA3LYKlQAAAAtCnukiEQosEp3GUAAGh/auuMWrgvrUX2y7lrzB69NC9En2+I1kzfFG2LPqmYrGJmnAEXuYj0Ig2Y0HSwdMdob/3n+1jFZZe0WN+F5TX69+YYu75GPTsrSFEnis6fW1dv1InCCgWl5Gtt+AlN9ErUkDWRem52kO4c47o9xO793169v+Kgxu9K1H++j9WHqyL0xznBGjDBV72duBzknWP2aOCCUH21JUbLg49rf0q+ckqqXT5LJ6OgQrN8U+za885W9R7upc83ROt4frlLr7u9qzbU67uDmfrfzgTND0jVrthTij9Z4pRgymQy6XDmGY3flaiHJjUvOLNV/cf6aNyOBB3jswMAAIA2wF0yBEI0OIW7DAAA7cuBYwV6asY+hx443TZyt/4wc78+XROpSbuTtDEiUwePFyqvzPUPXgG0HaeKq/TSvBCbXzeenL5PK0LSVVLpvEA97FihnrTz69mfFh3QY1MDdUszZtBdaN01Zo/eXBKmiV6J2hlzSicKKxr92mmoNyqnpFoxWcXyTczVuvATmumbouFbY/Xx6kN6cV6wHpjo1+jea7eP8taL84I1bNMRLdp3TAHJucoqqpSxBWaUtSSTyaSoE2c0alucXTMMLeuWEbv1n+9jme3sAoczz+jJ6Q2Pt99M9NMbi8P09fcxWrgvTd5xp5V0ulRVtfbPPDWZTDqSVayJXol6ZHKA08fm+ysONronIwAAAOBs7pIhEKLBKdxlAABoH/JKq/WPjdF2PVR6aJK/lgUd176jecosrFSdA8uhAWhfqg31mrInWff+b6/uH++rv6yNVKgL9x+qqavXHL9U9R3l7fJwrKHw6tWFoRq3I0FbD2crLa/MacFVvdGkvNJqxWWXyD8pV1sis+STkKOMggq3DAVq64zyScjRZ+ui1HekY+9n35HeGrcjQXll1a39Mi46tXVGTfNJbjS0baoe9PTXW0vDNHxrrJbsPyafhByl5Jap2lAvk8mkmKxiTdqddEHBWe/hXnpjSZhenBfs8LmPTg3Q0qBjKq6sbe3bDQAAgHbGXTIEQjQ4hbsMAAAXt7p6o1aFpqv/WJ8mHyLdOmK3JnknqYL9QgA4qLVnpaYXVOjd5eEuDcxuG7lbL80L0Ygf47QxIlOJp0od2oMNDSupNOi7g5l6Y3GYQ+9Jv9F7NNk7mTCkhSSdLtVzs4OcNoZ6Dz+7tOmFBmffHshQXunZAPXc7MZ/bIzWbSMdm3l6+6izy88mnGq55WcBAACAxrhLhkCIBqdwlwEA4OIVdeKM/jjHvr/IfnNJmFJyy1r7kgGg2Uwmk7ZFn9T945veq83RYObZWUH6dE2kJuxK1LrwE4rJKla1wf5l6tB8WUWVmuef2uhSgpbVf6yP5vilOmWvrvagrt6oBYFpDodQrqrXFx/Q6tB05ZY2PvMwr6xac/1T9VtPv2b1sTPmlCpr+QzBNpPJpDMVBPYAAODCuEuGQIgGp3CXAYD2y2QyqaauXmXVBhVV1CqnpFqZhZVKyytTwqkSRWee0cHjhQpOzVdAcq72xJ/W9iMntSUyS+sPntCq0HQt2X9M8wNSNdc/VStD0rUlMkt74nN0IK1AcdklyiioUGF5jWrr+Mt8VyqqqNV/vo+16yHRgAl+2hZ9stVnkQBASymurNXwrfZ9DTxXvx7vq1cWhOofG6M1c+9RfR+VrUMZRcorZe/HtuLcDKPBKyPsfl9/9c1eLQs67laB59nXWaT5AanadChTheU1Lu0/vaBCgxaGtnpQZll/WnRAK0PSdbrE8f3vDPVGecWe1htLHJvZeK7uHLNHj00N1KCFofrk20j994dYTfNJ1qrQdO2IOaUDaQU6mlOmgvIat1xKFY45UVihuf6pemrGPr0wN7i1LwcAALg5d8kQCNHgFO4yANqbeqNJBeU1OppTptC0Am0/clIrQtI1ZU+yvtoSo49XH9L7Kw7q/RUH9cHKCA1eGaEPV52tj1ZF6OPVh/Tn1Yf0ybeH9Mm3kfp0TaSGrInUX9ZG6q9ro/TZuij9bX2Uhq4/rKHfHdY/NkZr+NY4TfRK1CzfFC0NOqb1B09oW/RJ+Sbm6kBagY5kFSstr0yniqtUUmWwe/8pk8mkipo6nSquUnJOqQ4eL9TehBx9H5WtFSHpmumbonE7EjRs0xH9efUhvbbogJ6euV+/9fTTHaNdv3fM7aO8NWCCn56cvk8D54foveUH9dm6KH39fYzG70rUbL8UrQhJ1+bILO2JP62Q1AJFZ55RWl6ZckqqVV5T57R9ZVyl2lCvpNOl2hlzSsuCjuu7g5kKTM5T0ulSFVfWXvCDWqPRpA0Rmbrvm6aXRuoz3Etjt8erpMrQQq8OANqWQxlFemVB6PmveY9MDtA7y8I1fGusFu07pt1xpxV/skRl1XwddDeHMoocCkR+6+mnteEn2vQf9ZhMJgUk5+pViwCr70hvDdt8REeyip3av9Fo0rcHMuz6GXHY5iMKTs3XuvATmrArUZ98e0hPzdjX4jPXXl0YquXBx3Wq2PHgrCGJp0o1fGus034W7jPcSwMm+OrZWUF6Z1m4Pt8QrXE7ErQgME07Y04pv8y1oShaRn5ZjVaHpp//nvLTSstjJQcAANB87pIhEKLBKdxlAFwMauuMOl1SpbjsEgUezdOWyCwt2ndME3Yl6p8bo/Xe8oN6bnaQBkzwu6BN0V0dOP16vK9+NyVAz80O0qsLQ/Xu8nANXBCq30/fp/vH++rWEW1ziR1n191jffSgp7/+MHO/Bi4I1XvLD+qva6P05ZYYjduRoOk+R7V4/zGtCz+h7UdOKvBonhJPlaqwvMZlIVxJlUFRJ85o86Esee5O0serD+mxqYHq3cTnr9/oPXpy+j69syxcwzYf0TSfZK0NPyG/xFzFnyxRUUXDQVv8yRKbv9jbqoELQhV/kv0+ALQPlbV1bTo8QfOYTCYFpeTr5fkhdv8M8ejUAH0fld2mZgsZjSbtjjutF+Y2vfzywPkh+iEqu8Vn1p0srrJrT8H7x/vKJyGnwXbqjSZlFVUqKCVfa8IyNG5Hgj5cFaEnpgXqFjt/bn1lwdng7GQLBme2lFQatDz4uB6bGujyn2Wfmx2kiV6J2p+Sr6pa95kl2d6U19Tph6hsfbAyotHP74y9R1v7UgEAgBtzlwyBEA1O4S4DwJ0Y6o1KyS3TjphTmuaTrE++PaTfTQlo9VCHcp+6dcRuPTzJXwMXhGrImkiN3havef6p2nwo63zYVmBn2GYymZRTUq2Q1AKtDk3XqG1xemtpmAZMcHzfDUeq7yhvPT4tUG8uCdM/N0Zrsneyhm+NtSsgvvd/e/XdwUy3n9EHAMA5JpNJe+Jz9Mys/XZ/L31qxj55xZ5u1e+HhnqjfojK1lMz7N/r7Vz9eryvpu5JvuCgyWQyaUtklvqP9Wmyz7+sjVTBBSwtaag3Kr2gQoHJeVoZkq4x2+P1/oqzf+j27vJwLQ06pqyiygt6Pc1Rbzw7A9CRZUJb+ue6d5aFa+G+NMVll/AzWiurrTPKNzFXQ787rNtH2Tdb8bGpgSz7CwAAms1dMgRCNDiFuwyAtshkMul0SZUCj+Zp8f5j+temI3p+TrD6jnT9EoRU+yzLsG3UtjjN80/VgsA0Ddt8RAPnh+huOx44taX6+vsYl++rAgCAq9QbTdoWfVKPT7N/ZtELc4MVmJzn0gfgNXX1Wn/whB6deuF/CNZn+NlwKzStwOHXkF9Wo0++jWyyj/7jfLT1cHa7CAnSCyr0zc5Eu0JFZ9Wvvtmrod8d1saITGWfcX2o2B4ZjSaFHy/U8K1xuvd/TS+JbqsOZ55p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wYMHm/X14YcfNtk2IRoAAMDFgxANAAAAcKHW3hPt888/N+v7oYcealY7lsvT3XTTTQ0eaxmi3XvvvQ739/7775u1MX78+CbPsXytTc3+KSgoMNv/yMPDQ4GBgQ0eX1hYaPVe+vj4OPza6uvr1a1bN7N2Vq5c2eDxzQnRfvjhB7NzrrjiClVWVjZ6zq9//Wuzc8aOHdvo8ZZ7ZL311ls2Q4mmynKMdOjQwebMvLvvvtvsuGnTpjV5Hyzl5eW5JESTrO+Ph4eHrr76an322WfauXNno3u/2cOREO3UqVNWxyYkJDjc565duy44RJs1a5ZDfdbX11v1mZWVZde5tbW1WrdunV566SWr2bT21sCBA5vshxANAADg4kGIBgAAALjQjz/+aPVQdvbs2S7r33KPq3fffbdZ7WzatMmsnUsvvbTBYy1DtMcff9zh/j788EOzNsaNG9fkOTExMVZhzIkTJxo8ftasWWbH33bbbY0uE5eSkmL1Xqampjr82iSpX79+dgdCzQnRDAaDrrnmGrvDW8v9rjp27NjovZOk3r17NyuUsKcKCgqs+rPcS27Lli1N3gdbLANMZwUeqampVu+B5efzzjvv1Mcff6xVq1YpIyPDofYdCdESEhKsji0qKnL4NVkurdicEG3VqlUO92vZpz33yt/fX3379r3gz+KTTz7ZZF+EaAAAABcPQjQAAADAhWwt3ffRRx+5rH/LfZA+++yzZrVjuXeYh4dHg3uOWYZoTzzxhMP9NSdEk6QBAwbYfZ7lvmuTJk1qtO2DBw9a3YPc3FwHXtX/Z7m31PDhwxs8tjkhmiR9+eWXdr8PlrP4nn322Sbb7969u9NCNFsBXpcuXcyOac4sQMk6jHNm4JGdna0XX3zR7tf9wAMPaPny5XYtuepIiBYaGmp1bF1dncOvJzU19YJDNHs/vz/laIi2efNmde7cuUU+i/Z8/SJEAwAAuHgQogEAAAAuVFdXp65du5o9YL377rtd1n97C9EWL15sdt4vf/lLm/t6RUREmB3XqVMnnTp1qtG23S1ES05ONjuvQ4cOSktLszrO1n5ymzdvbrJ9y6UwW7JshSTuGKKdEx0drWHDhumOO+6w6/X37du30X3yJMdCtMjISKtjm1re0xZbM9qa4uoQLSMjw2q2oYeHhx599FFNnjxZfn5+Onr0qIqLi1VdXW01+7Q5X78I0QAAAC4ehGgAAACAiz311FNmD1g7duzY7PDFUW1hOUdXhmglJSVWex/t3bvX6ri//OUvZse8/PLLTbbtTss5nvPII4+YnTtixAirYzZs2GB2TK9evVRbW9tk29dff73ZeYsWLbL7uprD3ZZzbEheXp5+/PFHffXVV3rkkUf0s5/9zGaQdsUVVyg+Pr7BdhwJ0Y4dO2Z1bFOhsS22ZrQ1xdUh2kcffWR1H319fe3ua/78+YRoAAAA7RghGgAAAOBic+fOtXoI7Onp6ZK+LZfpe/jhh5vVzqRJk8zauemmmxo8tjVDNEkaPHiw2blvvvmm2b9XVlbqiiuuMDtmx44dTbZbWFho9T7aCuiaUl9fbxX0rVy5ssHjLySEWLVqldm5N9xwg+rr682Oefrpp82OGTZsmF1t33vvvWbnjR8/3u7rao67777b7uCxIXl5eVbvYWsHHqWlpVq/fr0eeOABq2trbD9BR0K08vJydejQwezYgIAAh691+fLlbTpEq6urU8+ePc2OXbFihUN9jRkzhhANAACgHSNEAwAAAFyssLDQaim6m2++2a7ZPhdq2bJlZv1269atWXsh/elPfzJr56WXXmrw2NYO0YKCgszOveSSS1RYWHj+39esWWP279dff73d9+TGG280O3fixImOvjTFxcVZhQKNLd13ISFERUWF1d5lu3btOv/vGRkZVuFKQkKCXW1bzvgZNGiQ3dfVHO+++65Zf2+99ZbDbXh7e7e5EO0ck8mkv/71r1bXl5mZafN4R0I0Sbrrrrsu+LP76aeftukQLT093ey4zp07q6qqyqG+LJfAJUQDAABoXwjRAAAAgFYwdOhQqwfBI0eObNE+bO39lZSUZNXvzp07HWq3rKzMaubU5MmTGzy+tUM0Sbr99tvNzp8zZ875f3v88cfN/q2x/cgsvfnmm2bn3n///Q5dlySNHj3arI3LL7+80RDvQkOIIUOGNBh2jR071uzfHnroIbvbtVwG8sorr1RFRYVD1+YIy2X2evTooerqaofasBUCtaXAo7S01Gp5x4bGq6MhmuXn4K677nLo2qqrq9WjR482HaJZ7lt4/fXXO9RPcXGxLrvsMkI0AACAdowQDQAAAGgFOTk5uvLKK80etHbq1En79+9vkfY9PT0VFBRk9f9NJpNuvfVWs36ffvpph9qeMWOG1UPsxvZqagsh2pQpU8zOv+eeeyRJaWlpVq8lLS3N7nbXrl1rdX5ISIjd55eXl1vtJfbaa681es6FhhCWwULnzp2Vm5sro9GoX/7yl2b/5sjSd8XFxVbLYjYWrl6ojIwMdezY0ay/5cuX231+fn6+1ay8thh4WO79tnHjRpvHORqiWc7Q9PDw0ObNm+2+Lssx1EsWCwAAIABJREFU1RZDtMOHD5sdd9lll9n844KGfPPNN1Z9EaIBAAC0L4RoAAAAQCuxFcB069ZNXl5ezW4zLy9PAwcObPTBra092dauXWtX++np6br88ssdCuHaQoiWk5Ojzp07m7Vx6NAhjRgx4oKurba21irk6N+/v91Lxv3973+3ei9CQ0MbPaclQoj+/fubtTFt2jTt3bvX7P9dfvnlKi8vd6hdy5lsXbp0cShUtMVkMjX4by+++KJZf9dcc43y8vLsatdyOUhnBh7NWTJVOhv0derUyez6GgraHQ3RJOmee+4xO/7aa69Vampqk+eFhYWpW7dubT5Es7Xnnb+/v119REVF6ZJLLiFEAwAAaOcI0QAAAIBW9K9//cvqIW3nzp31xRdfKD8/3+52ysrKNHXqVLPZbQ09uC0vL7eacXTJJZdo+/btjfZx/Phx3XLLLWbndezYUcHBwY2e1xZCNEl65ZVXzNr45JNPdMMNN5j9v3Xr1jncrq1Q8plnnlFZWVmD55hMJpuzXJ555pkm+2uJEGL27NlmbfTr189qacpPPvnE4XZLS0utPiOXX365w9dYU1OjDRs26OGHH250T7bw8HCr2Wj33Xdfo0Ga0WjU119/bTMAclbg8c477+jTTz/VkSNH7D7HYDBYvSfdu3dXZWWlzeObE6IFBQVZ7YF3/fXXm+2T91Mmk0mrV68+P4Ova9eubTpEk6wD4379+qmgoKDR9oODg9WzZ0+bnw9CNAAAgPaFEA0AAABoRSaTSX/7299sPqzt3r27PvzwQ23YsEFZWVmqra09f57RaFR6ero2bdqkDz/80OFl6UJCQqxmuHh4eOjtt9/Wvn37ZDAYzl9fcnKyxo4da7UPmoeHh0aNGtXka2wrIdquXbvM2rAMD5qzp5Z09h49//zzVvfmhhtu0Pz583Xy5Mnzx1ZUVGjbtm169NFHrY6/5pprdPr06Sb7a4kQorCw0GqWjeX9CA8Pd7hd6ey+e5ZLlXp4nF1Cc/78+YqNjbWamVVSUqLw8HAtWbJEr732mtlsx8aWCpWkL7/80qqvnj17asaMGcrMzDx/XEVFhbZu3aoHH3zw/HF9+vTRtdde6/TA46cBbt++ffX1119r27ZtysjIUH19/fnjTCaTMjMztXLlSqtZYh4eHvrqq68a7KM5IZok/ec//7H59efuu+/WsGHDNHPmTE2bNk1Dhw5V7969zY6xtbRrU1wdoi1evNjq+BtvvFFLly41C1tramoUEBCgDz74wGws/P73vydEAwAAaMcI0QAAAIA2YN68eerSpYvNh9k/rSuuuEI9e/a0WprQsq677jodPXq00T6//fbbBtvp0KGDrrrqqkb7+eCDD+xapq6thGj19fVWM89+WkOHDnW4zXMKCwv10EMPNdh2165dbQZL5+rqq69WWFiYXX21RAghyWqWk2WAciEiIiL0i1/8okU+y02FaLW1tVbLOv60unTpYvPed+vWTeHh4S4JPCxnQVqOte7du+vqq6+2uXzguXrwwQcbDXmbG6KZTCYNHTq0ya89luXp6an09HSre9oUV4dodXV1+t3vftfg6+jevbt69Ohh89+GDBnSrK9fhGgAAAAXD0I0AAAAoI1ISUnRwIEDrWYEOVJXX321PD09G1zyzZKvr2+jwVJDocT48ePtfl1tJUSTpJEjRzb4uqKjo5vV5jlVVVVWs1jsqfvuu08pKSl299NSIZqvr2+D1zRr1qxmtflTBQUFeu211y7o83zLLbcoOzu7yb5qa2v13nvv2d1ujx49zu+N5YrAY9CgQc2+Bx4eHnrvvfeaHNPNDdHOWbFihXr16tXktfTs2VPr16+XJMXExJj92/XXX99kP64O0aSzIffDDz/s0D0fNmyYjEYjIRoAAEA7R4gGAAAAtDFJSUn6+uuvdfvtt9v1sLdXr156/fXXtW3bNrMlH+1VVVWlqVOnql+/fk32M2TIELMl8uzRlkK0Y8eO2Qx17r///ma1Z0tkZKQGDRqkyy67rMF72bFjR/32t7/VunXrZDQaHWq/pUI0o9Fo9bDfw+Ps/nhN7RnliISEBJv7z9mqDh066Fe/+pW+/PJLhYaGOtyXt7e32XKNltWtWzcNGTLEbNlMVwQelZWV2rlzp/72t7+pf//+Vvu42aorrrhC7733nt3Lal5oiCZJxcXFWrZsmV544QX16dNHl156qbp06aJf/OIXeuGFF7Rw4UKzvf4sg9i77rqryT5aI0STzs5Imz59um688cZGx+Wzzz6rkJCQ8+cRogEAALRvhGgAAABAG5afny9/f3+tXLlS06ZN0/jx4zVjxgytWLFCO3bssOvhsSMyMzO1detWLV68WJ6enpo7d642bNigqKgomUymFu3rYldbW6ugoCCtXbtWM2fO1OTJk7V8+XLt2rVL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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Find and plot convolution\n",
    "\n",
    "def convSquat(sig, win):\n",
    "    filtered = signal.convolve(sig, win)\n",
    "    fig, (ax_orig, ax_win, ax_filt) = plt.subplots(3, 1, sharex=True)\n",
    "    ax_orig.plot(sig)\n",
    "    ax_orig.set_title('Original pulse')\n",
    "#     ax_orig.margins(0, 0.1)\n",
    "    ax_win.plot(win)\n",
    "    ax_win.set_title('Filter impulse response')\n",
    "#     ax_win.margins(0, 0.1)\n",
    "    ax_filt.plot(filtered)\n",
    "    ax_filt.set_title('Convolved signal')\n",
    "#     ax_filt.margins(0, 0.1)\n",
    "    fig.tight_layout()\n",
    "    fig.show()\n",
    "\n",
    "convSquat(squat1Y[0:25,0], squat2Y[20:70,0])\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}