TASK8.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x19bcec4a940>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "data = np.arange(10)\n",
    "plt.plot(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x19bcf821780>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot(2,2,1)\n",
    "ax2 = fig.add_subplot(2,2,2)\n",
    "ax3 = fig.add_subplot(2,2,3)\n",
    "plt.plot(np.random.randn(50).cumsum(),'k--')\n",
    "ax1.hist(np.random.randn(100),bins = 20,color='k',alpha=0.3)\n",
    "ax2.scatter(np.arange(30),np.arange(30) + 3*np.random.randn(30))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"k--\"是一个线型选项，用于告诉matplotlib绘制黑色虚线图。上面那些由fig.add_subplot所返回的对象是AxesSubplot对象，直接调用它们的实例方法就可以在其它空着的格子里面画图了，如图9-4所示："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x19bcf1ff128>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 1.,  3.,  4.,  3.,  8.,  3., 10.,  7., 10., 10.,  6.,  6.,  6.,\n",
       "         4.,  5.,  3.,  4.,  4.,  0.,  3.]),\n",
       " array([-2.08325062, -1.86267633, -1.64210205, -1.42152776, -1.20095348,\n",
       "        -0.9803792 , -0.75980491, -0.53923063, -0.31865634, -0.09808206,\n",
       "         0.12249223,  0.34306651,  0.5636408 ,  0.78421508,  1.00478936,\n",
       "         1.22536365,  1.44593793,  1.66651222,  1.8870865 ,  2.10766079,\n",
       "         2.32823507]),\n",
       " <a list of 20 Patch objects>)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax1.hist(np.random.randn(100), bins=20, color='k', alpha=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x19bcedb6588>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x0000019BCF04D4A8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000019BCF135E10>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000019BCF726E10>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000019BCF300080>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000019BCF3452B0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000019BCF44D4E0>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,axes = plt.subplots(2,3)\n",
    "axes"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "默认情况下，matplotlib会在subplot外围留下一定的边距，并在subplot之间留下一定的间距。间距跟图像的高度和宽度有关，因此，如果你调整了图像大小（不管是编程还是手工），间距也会自动调整。利用Figure的subplots_adjust方法可以轻而易举地修改间距，此外，它也是个顶级函数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, sharex=True, sharey=True)\n",
    "for i in range(2):\n",
    "    for j in range(2):\n",
    "        axes[i,j].hist(np.random.randn(500),bins=50,color='k',alpha=0.5)\n",
    "plt.subplots_adjust(wspace=0,hspace=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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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 0x19bcf8b4e80>]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from numpy.random import randn\n",
    "plt.plot(randn(30).cumsum(),'ko--')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x19bd3a343c8>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = np.random.randn(30).cumsum()\n",
    "plt.plot(data,'k--',label='Default')\n",
    "plt.plot(data,'k-',drawstyle='steps-post',label='steps-post')\n",
    "plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x19bcffef080>]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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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 0x19bd485f128>]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(1,1,1)\n",
    "ticks = ax.set_xticks([0,250,500,750,1000])\n",
    "labels = ax.set_xticklabels(['one','two','three','four','five'],\n",
    "                           rotation=30,fontsize='small') \n",
    "ax.set_title('My first matplotlib plot')\n",
    "ax.set_xlabel('Stages')\n",
    "ax.plot(np.random.randn(1000).cumsum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "要改变x轴刻度，最简单的办法是使用set_xticks和set_xticklabels。前者告诉matplotlib要将刻度放在数据范围中的哪些位置，默认情况下，这些位置也就是刻度标签。但我们可以通过set_xticklabels将任何其他的值用作标签："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "rotation选项设定x刻度标签倾斜30度。最后，再用set_xlabel为X轴设置一个名称，并用set_title设置一个标题："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x19bd604fb70>"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from numpy.random import randn\n",
    "fig = plt.figure();ax = fig.add_subplot(1,1,1)\n",
    "ax.plot(randn(1000).cumsum(),'k',label='one')\n",
    "ax.plot(randn(1000).cumsum(),'k--',label='two')\n",
    "ax.plot(randn(1000).cumsum(),'k.',label='three')\n",
    "ax.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA3AAAAKUCAYAAABFSNr3AAAgAElEQVR4XuydB7gURdaGy5wjZsGsYNY1y2JOiGLEhBgxLRjA7GIWc845i4oKZsScFcWsGFlzFlRUzPo/b/17Zmv69sz0zO2eOz33O8/jo97prq5+q6u7vjqnTk3y999//+1kIiACIiACIiACIiACIiACIiACDU9gEgm4hm8jVVAEREAEREAEREAEREAEREAEPAEJOD0IIiACIiACIiACIiACIiACIpATAhJwOWkoVVMEREAEREAEREAEREAEREAEJOD0DIiACIiACIiACIiACIiACIhATghIwOWkoVRNERABERABERABERABERABEZCA0zMgAiIgAiIgAiIgAiIgAiIgAjkhIAGXk4ZSNUVABERABERABERABERABERAAk7PgAiIgAiIgAiIgAiIgAiIgAjkhIAEXE4aStUUAREQAREQAREQAREQAREQAQk4PQMiIAIiIAIiIAIiIAIiIAIikBMCEnA5aShVUwREQAREQAREQAREQAREQAQk4PQMiIAIiIAIiIAIiIAIiIAIiEBOCEjA5aShVE0REAEREAEREAEREAEREAERkIDTMyACIiACIiACIiACIiACIiACOSEgAZeThlI1RUAEREAEREAEREAEREAEREACTs+ACIiACIiACIiACIiACIiACOSEgARcThpK1RQBERABERABERABERABERABCTg9AyIgAiIgAiIgAiIgAiIgAiKQEwIScDlpKFVTBERABERABERABERABERABCTg9AyIgAiIgAiIgAiIgAiIgAiIQE4ISMDlpKFUTREQAREQAREQAREQAREQARGQgNMzIAIiIAIiIAIiIAIiIAIiIAI5ISABl5OGUjVFQAREQAREQAREQAREQAREQAJOz4AIiIAIiIAIiIAIiIAIiIAI5ISABFxOGkrVFAEREAEREAEREAEREAEREAEJOD0DIiACIiACIiACIiACIiACIpATAhJwOWkoVVMEREAEREAEREAEREAEREAEJOD0DIiACIiACIiACIiACIiACIhATghIwOWkoVRNERABERABERABERABERABEZCA0zMgAiIgAiIgAiIgAiIgAiIgAjkhIAGXk4ZSNUVABERABERABERABERABERAAk7PgAiIgAiIgAiIgAiIgAiIgAjkhIAEXE4aStUUAREQAREQAREQAREQAREQAQk4PQMiIAIiIAIiIAIiIAIiIAIikBMCEnA5aShVUwREQAREQAREQAREQAREQAQk4PQMiIAIiIAIiIAIiIAIiIAIiEBOCEjA5aShVE0REAEREAEREAEREAEREAERkIDTMyACIiACIiACIiACIiACIiACOSEgAZeThlI1RUAEREAEREAEREAEREAEREACTs+ACIiACIiACIiACIiACIiACOSEgARcThpK1RQBERABERABERABERABERABCTg9AyIgAiIgAiIgAiIgAiIgAiKQEwIScDlpKFVTBERABERABERABERABERABCTg9AyIgAiIgAiIgAiIgAiIgAiIQE4ISMDlpKFUTREQAREQAREQAREQAREQARGQgNMzIAIiIAIiIAIiIAIiIAIiIAI5ISABl5OGUjVFQAREQAREQAREQAREQAREQAJOz4AIiIAIiIAIiIAIiIAIiIAI5ISABFxOGkrVFAEREAEREAEREAEREAEREAEJOD0DIiACuSNw9dVXu1133dXtvPPOjv9uT7bAAgu4Dz/80L3//vuO/24EW2uttdxjjz3mrrrqKrfLLrs0QpVUBxEoIvD666+7QYMGuSeffNKNHz/e/f3334XntRH7VD2az/rtI4884vjv1toxxxzjjj32WHf00Uc7/rutLa12TZtTW3PR9ZuDgARcc7Rju7oLe5k2ykeiLeE/+uijjn+WW245t/nmm7dlVYquffbZZ7vvvvvOD+azEBlpCzjqSp2xRhh4lGvItAYlSR8WWH/wwQf++eI5i7NGE3CvvPKKu/32272ofOONN/yAffrpp3dLLbWU23777d0ee+zhpphiipIIfv/9d/88XH/99e69995zU001lb/3/v37uy233LIsupdeesmdfPLJ/to8V/PMM4/bdNNNvXiYffbZS5777LPPunPOOcc99dRT7ssvv3STTz65W3DBBd1GG23kDjroIDfXXHMlbbLCcePGjfMcHnjgAffCCy+4jz/+2E066aRuvvnmcxtuuKEbMGBAxf7J4P6MM85wo0aNcj/++KObf/75Xa9evdxhhx3mpptuupJ14lg43HrrrX7CAf6rrLKKv5dyYuGnn35y5513nhs6dKh79913vdBaZJFF3A477OAOOOAAN+WUU1bN4euvv3ZdunTxzwFtsPDCC7vJJpvM/fvf/3bdu3f3DBptUqTqm6zhhLSFiQRcDY2gU0SgRgIScDWC02ltR0AC7n/s7YPZaJ4oGxClNbMbfdrSFnAIFAbLGAPGRrZ1113Xffrpp+6hhx5y8847b+ZVTSLOkhyTeUX/e4GxY8f6Ab9Zp06d3Jxzzuk++eQT98UXX/g/r7TSSm7kyJFulllmaVGtX375xa2//vreU8Mgf8kll3SICsrFDj30UC9M4mzYsGFuu+22cwjAOeaYw3Xs2NG9/fbb/vy5557bl7nQQgu1OBXBsv/++/tnb9ppp/X1//nnn72X9Y8//nAdOnTw7b3ssstWhbFbt27+mtgMM8zghQvlci+Ui6i65ZZbvEiMs7Be3AviZ8yYMe7XX391iy++uC971llnbXHqN9984/75z3/6e0f8LrHEEg4RRRtMMskk7vzzz3f/+te/Wpz31VdfOZ5vvGUITa6B0Ob/qe+KK67oHn74YX8v1Rj3sd9++/nzqTN1Cq3efaqaumd57E477eSee+45d+2117qVV1651ZdqNAGXVrumzanVoFWACDjnJOD0GOSOgATc/5pMAi6dEMo8Cbh6d9gk4izJMfWqNx6zrl27+gF7nz59vLfJ7N5773UMxvBMbbPNNu7mm29uUS2E1LnnnusF/YgRI1znzp39MXfeeac/B/HCf+NVCw1Rvdhii7mJEye6I4880h111FHei/b99997UXffffd5AcGAGRFj9p///MdfA4Gy++67u7POOqsgUPht2223daNHj3b/+Mc/vBetGqNdEPl77bWXZ4IgxRBSu+22m/fMzTjjjO6dd97xIjc0rsWgHlF58cUXe68l9f7ss89cz549fV3wRt52220tqrTZZpt5RiussIL/N15Iyrnssst8XagH9xT16CIkEdZwvOuuu/y/Ma659dZbu2eeeca3KYKjGkMsXnTRRe7ggw92p556ajWn6tgqCDSagKui6jpUBHJHQAIud02mCkvAScC1Zw9cvd8AScRZkmPqVW88aH/99Zf3ZMXZkCFDXO/evb2IIFQR75YZ/4/g++2337ynZ+211y4qAlF2/PHHx4opwvsIgVxjjTV8+GRo3377rReEiLmo+Lvgggt8aOZss83mPv/8cy/6QiMkE/GG8Xs1oZQI1fD+wnKpy6KLLuo9Y4hG6h8aIbN33HGHF7zXXHNN0W+ENhKSCGfCVZdZZpnC71ZfPGh44EJvKAdR3nXXXddC/L322muFcp544gnvwQsNryGePLybeAG5flJjvSzvDIXdJyVW23EScLVx01kiUAsBCbhaqOmcNiVQSsBFvSj33HOPO+200xwDCgZrq622mjvppJMKgwTWdAwePNjP6hLixGzwCSec4NZZZ50W98daLgYxDAD23XdfP7vODDEDPmaXmR1m1p3Z7DjjOGZ+qRNrLQgLIjyIdR377LNP7LoOm6UnjIpzOJ/ZewZlhGptscUWJduBdSrwwFiHw/F33323D0XCU0DZhFNRxsCBA2PrHXr3mDlnHQwz33gFuE/W0Jx44omOEDUzE1alKlbNAApPB+3HYI/7J9yN0LbjjjvOr/srlcTkwQcf9INkBoF4GiZMmODD2QgnYwZ++eWXL6qetW2pOkfDQFnbQ0gWTPFcMNiHNwPeQw45JDakjAEvzx5l4U1gHQ8eDwakrMHhGUhqpdbrhM8o64x4tllHBANC3/CK8HzHhQ3GXRvGUQETHheG7YYCbuONN/brCGkDxAEeIDxQ9Jmpp5469jZrYZqUV/Q41kGZqGHdGeuyzHjO99xzTy9saNuo0XcIJcTw9NGHzPg7v7NuDoEYNTxYl19+udtxxx39M212+umn++cSbxVeqajBxkIGP/roo6L+VisDOw9PGu+xvffe23uozLgmgpI+SMgh3ruo0Rfpa6ztQ9Sasa6M98J6663nPXxRY40f4oxngVBLW0fH9fGU8bzwzMYZ9Xj66af988W7pJKV69trrrmmf49gWfQpvi/Dhw/3EwGsPeS9Tbjpqquu6sVyqXWA4Xsf4U9SENqAbxSile8P3tNSxjPC+k08mbw3KY9nk/cf53F9s1Jr4Fr7zajmPW914T1KEiS84q+++qr74Ycf/DuSEOatttrKv+/Ng2zfGdqQZ5D7pU/RJ/m2Uv9y7cokD+9wrsUkA9fmeWfyBib9+vUr9HPKKcWJCQz6NN9F1trSRrxbGBPAG28z33mZCGRBQAIuC6oqM1MCSQQcs9q8hHmR8hF46623/NqPmWee2S/GR8iQzICBER9vBmt8MJj9Zq0Js+ih2UCAjyciDHHEh4UXOLPBhAfx/8y8R2e8maHeYIMNHOs7+LiQSIEwKz4c2Oqrr+5DtaLizz7kDPwZFPE7s9mUw0w/Az8+1gwOECgMOs1Yb8PaFowBJWFHXJvZe3gw+87HnQ8XHxgGVdGBvQk4RCYCFC6ENCE+qDsz4Yi3l19+uSBauA+EAwNRBn/c60wzzVSoFwOIcoMPO5APLOFU5sng3livQ7vRZgz0ECNxa/9owz///NN/kOHAR597ZTBE3eHCwNWMwSYDLRs8RwerfOhN9DFAoF54A7gOwo31NAg0ePAsIdLCxC1MIPA8MSieZppp/Boo6sEgFYEDHxtwJOk4lQabJKZg4MxzSdvCgvrxb+4D0ZIkEQT15nnHM4IIpg14zswQakcccYT/X+uTiOtLLrnEP6P0B85jAoL+sckmm3ixELVamCbhVOoYvFi8FzAGiksvvXThUEIYr7zySv+MXnHFFbFF0H7cUyjU6IMWqllKZDHI43mlD9MeZvQrxA7PN89pdE0ZoZeIfOpsa8hac//huUzC3H///X4ShwkaMyY/eGZ5tnkvxiV8oa0ZqEeFGuuOEC38zqRW1Ogn9OGoOOS9gRgkbJN3dJwRTsqkBO9TBEolo28TNgtvnkneV9ZO9AX6NpZFn6KdeU/wXuU9hGCl/agH73a+UXETN/beR9ASzss7g7J4xjgXY2KLSZqoMWnC+xohwfsJwcf7j+eVvsgkDkltzEoJk9Z+M6oVcHxfeD/YO5h24lvFhAj9lfcH72++35gJOJ5RniW+yXi4+fZSFn2wVLvyHuQZtW8L/ZnzeBdzPZ5PvgdhUrBSnJiMueGGG/y1EMnUmXpSDt+wOM92pWdWv4tAUgIScElJ6biGIZBEwBE+xQeQcB2MWXcG3s8//7x/efOhOPzww/1HkA8c4g4vGh97BBWCJjQTcAxk+JgSWmSCiZk31sPwkeTjaS90zucljojhQ45nj/AtW2tCHfig4pGJC1OyDzn1o654MGwgRbkMCJKsgWOQiuBkxpzBgBkzwghDBtzRGXiOsbK5JgMc1rrYYJcPJDzffPNNP4hn8BVaa5OYUCbClQ8rrE1U8TGnnWhHPrRxAo71Oj169CjyVCC08ZjRjnCj/mGIXZI1cDAnlI17RhAjoE3Q8PFn0I+Xk7pa4giYWCga5zBoCxMwcF0GC4iupFZpsEl7Uc+bbrqpICQRYQzW4XfppZf69UxJLUl4pB3DtbkOIsgyLjJQoj0YVCIWeA7NamWatO5xxyFU6Pc22LNZfY61pB88zyZOo2WY5wlxgkjBTIQhjLmncI2bnW+eJ0ILOSYURSakiBLA0040AMdQLs8GzxftiSciLeO9w6CXSZzogBXx2rdv35KeSOrAe44BLINtGzDzd/4focLvvA/jjHcnwp3r2ISOhZIm8cAhwhC7SS30Tsdlmc2iTxGxQXvaOj6rK+KWyUMmbWAQRjBwjD07PB9k+kTU2oSLeWt5d9GXw0k/+jjil+cGpjxH4WQizx8TmUxSmJUSJq39ZlQj4BBnCDHembBioiP0inOfvE/wWpq31gQcfReBzLudvovxLbfvXFy7ImCJPEFwMeHI99mMc/mdyacwLDiOExOXTALQBkxMhZO+fJuYeOE3vIQyEciCgARcFlRVZqYEkgg4PAckIgjNZrL5G4KL2crQGJgT0oaFs338fxiKQxgjWexCswEcgzPEmnlg+IhzbqnZdQb81CV6XvghZ/DLcXGWRMBVagwGEAwm+CcczFrZnE+YaRh6w98Y9JHEgMEm3prQWiPg8FQxY82/4/YVYyaa0LVSAq7c/TIYYnDOYJjZfLMkAs5CvHj+aG/aLDTqy4w3s68MlpgIwPgbHks++NVmEYy7l0qDTbwmXA/vYGjMBuNpQVDSdkmtGgGHoMXbEfUmW2IQBmHUw6xWpknrHj0OocHADA80EwQMkENj4IbnknoxqRFn5gVi3Zp5cPDqkuCEyRnLdBk9N3y/EDoYDq7xRhGGSAineVnsfAaGeJLiwhhr5cB59F2eA955DNjDvo+Hh3BgBtJ4bOOMwS9eWN5teOnMGGQTYcDvpbJbUi7vUQTJgQce6E9lUsYyIYb9x8plggyPMqyYBMGjlNRaK+DS7lOE3TGJQjZTspqGZgIOdjCMGu9b2yaDCUAzRAniI+7bVopTrdsIVPpmVCPgmKDjnWQRFtH3Vlzdw1B9+h6TenEW966EOROi0XdRuWcpjhPfEIR4te/TpM+sjhOBSgQk4CoR0u8NRyCJgIsurOcmGBiZ94uPRhhGZzfJzCazcHjHWJNiZgMARAxiJs5s8IcHiNh3jLU/xNkTKnPhhRfGnmcDfDxhrL8xsw95uQ9UUgFHhjsEK+sFGAjhDcErhVmIHAPMMDGAlY3oQHxEzULRogM4jmuNgDOhzcwq4TBx4Vs2iC61fQL3BDdCLhHjiD17BhAY0VTwSQSchYaVWuNE+ZYsIfTgmMcGbyeD9DjvTDWdrJKAi4ZJWdk8t4hKZpzhk9SqEXAINdtPLyz/xhtv9N6YaBhlrUyT1j08DlHB2ismGxAKzPhHny0mBljjGXqGoteyJBx4MhiIY6y/4e9Rb1R4LuXamjkmIWwtHcfwnCOY2DMNj4Sl++e5RFjxHiH1frXp80txskEs98+aMrJjhsZziscfr8bjjz8eWwyeJNqP+vF+MeP/ebcwyRG3npjjEKWEaXIdJlXMeL8SPomHDhbmBcHbhkBG9GHRa1Z6Hlor4GrtU7xrefZ5fyLa8XZiTCDwbuI9hhAIzd4PUa+oHcO3BS96KH7xuhFeiLilPfH8JbFyAq4134xqBBzvcLxufPv4BiYxE3BMFBFdE04+hOfHvSvNc8x7kDWQpZL8hOXEcTKPOpONMM9iv9MkLHRM+yUgAdd+2z63d55EwOENiW4yy8DIvCZ8PBFcUWP2j1l6Xuxh6IMNAMqtjWFzWwYdhDydeeaZvmhCLPh4Ex4Ut+8RxzB7SHhieB5/tw95qbpyTBIBR6gUM+WI2nIWTVZgZVM/W08Xns8gjQ8n9TQxaL+3RsAhAGBRbi0MC/upX5yAIyEEYXLl9nMjPAxvh1kSAUdIIIMwBC2iNc4YaBI+Fgp2ZtHxolIfBvjMrONN4TlOMtscvU4lAUd4IB6UqJmAIGyO/05q1Qg4RAZrT6Nmg32SovDfZrUyTVp3O46BMxM2rJuCH8963B56beGBI5SZkFfeOzz3iBp7d/E3hCITL3itGChGPb/VsiAqgIkGjIEzYZBRawsPHHUgeoFnBIHLe4VnFZFpawapK3VGrDAxk9RaK+Bq6VO8xxDlNnkUV9e4RC+V3vuWCTVM5GIZPFn3xgRkNJNpKU6lBFxrvxnVCDgmSl988cXYaItS9TYBx8QDnttSFveuZCKHpQC8Awm1ZBKCCQUmd/jmxInBOE5885jgoE/Cm2MYM1AOAjq612DSZ1XHiUBSAhJwSUnpuIYhkETAlRq8hxm+4mbMSgkPGwAQckXoVZwRUoVQC8WBLWRH2JVavxJ3HuVXqivHJBFwLPgnqQXCA+FD+CcJPmxdhc2GR7MtJinb6hjl3RoBR3IS1heVSnrBfePlRCRFBZyliGedG14wkj+wXgbPKnVlLQUD4uh5SQQcA8nQ01CuQ0TLZ+0XYXAIBxbRm+ERQ2xGw1PLlV1JwJUaPNk9hhlKk3TqagRcXMgr17CMlmHmP/7eGqZJ6s4xtBmTK4SXkQgEz0/cZtocy+CLmfVq18AhsPC01rIGjhBCJnzwVuG1ihpChfcInga8+XiiMEvQET0eTy/PfZyRAARPKM9guTBRC/ErlY2TskutgbNsnNWugbP6MkmCd4koCTxY9GUGxNwXocG8X4kUIGIgqbVWwFXbpxjUM0nDO4d6MwnGM4cwR4DbhEa0PyR578el6jdvULXCtpSAa+03oxoBZ+sh6Z9hSGi5tg2zUFom0bjjS70riR6BI/0hTCBFhA6im/DKcKKkFCc8qXyv8MDjRTcjMRUTWYhtCbmkvVTHVUtAAq5aYjq+zQm0pYBrCw8cg5hS4RmVRJaFOVriDkssETaieR0aRcC1xgNnGwGzNglhHDXzLNQi4Ajp5GPPjG805Cxpp2CtEIM7Bh2EVuGxw5uHd7SUqIiW3UwCLg2m5dgjVBAsDNRYn0dClXL7h9G/EaF4qBD7cWZZKBm0mfcKT5l5U2nTcPNwK8OyUBIeSfIKM2b9eaZOOeUUP3iMMzzoeHIRe4gbrFSK/FIimpA8xB+ClkkD1kOWMsImERdJslDiwUDAmiFEeZcwWcQANmp4pHjm8YrG7fdWrj1Zl0iYXbWbeddbwFk9w/YK78vWTKYl4NL0wKXxzahGwJkHDlHGezmJtVbA2TXworH+k+edRCT2HJMAhkgOsyRrBZlQYIKOjJisWefdQ9QNk7oyEciCgARcFlRVZqYE2lLAlVsDR0w9GSmrXQPHwnyyg5VaA1dOwJULJaQRbN0TIVovvPBCi3Zhdp+BLYO6NAUcoU94fKJlJnkwbA0c6dRJCFHNGrjOnTv7LSGi6eHtunhByVgWFXAMuk0kl/LeWoZCBvYWgpbkfkodw3oVwuIQb6VSrsedW28BR0gbgrOUMKCOlbx0pTxwaTMNeTE4o50QTjxL1CHcMiCOLWuLWGOUZB84wvrCTaoJyST0rNp94Kz/RweNYf3wqNEvmNUnTLVaI7suSS4QTXgM8AqVM0LQWRvE8dXuA2cZZJPsA0d2zVLhyHHCjxBkPB3lIhri7qveAs6yikY3bbe6mdc1LQGX5hq4NL4Z1Qi41qyBi+MXtn+pd2WpZ9/WhkYnWZIIuLBMS3DCBAh9KWlIa7X9Wse3bwIScO27/XN5920p4AAWTXDC3ywkhpAZ1nEgYLBKWSgZWLE+qlwWynICjkEfCTmYWSe8KmqIA7KWMbi0dSXhMbaegr+lKeDIbMeMJPdXKpyr1MMXZqGEn20FYcezxgwvSFwWSltzyFonwoBCQySTFCHuvDDBDWskwu0WrAyympKkg2uQaCFOWFbboQgHI2FGuSQ30TLrLeDM+0MSnlIbjtcq4LJgarxIisA6R8KZCE0MkxKVaifEASKBZ4Q+Hd3I3PoLzwDrdkLbb7/9fFZKQpJtjyn7nYkS3gmEXEUTKBE2xkA/uj7QziV0EkHJv+FFht1qjHsnHJlBPsINAZfEbJPvuC1OEK94MhHJ0eyqcIE17zRCHkORy3UtCQyCksmUpEboOuKQvk9frqb/1VvAWUbI6KQc94pohR3tmZaAo1zLKloq4Uoc5zhhksY3oxoBx7NPnUnQwwRodFuFuHqn5YGLls1kBZNKvP/5DphVK+D4Rtl98E4J989M+rzrOBGoREACrhIh/d5wBNpSwDFoYK8a4vVtYELacVI3syiabHGExpmF+8AxI826EHuZM9Dhw8XLPi4ZR5I1cCQ/YX0Fg3qSnUQTtzAQJUsWiRJYV8aH1bLE2Uax3BP1TFPAwYMwEsJQEJnVGqKU8wj5ZMBrWdXwyLGeCQEVJ8QsXT0DSEJiuHeMQQmcYM29RnnjdWP9CKnJqTeiOmokB6BchCmhmgzWw8EpITPMXjO4YKBvYXRkmuvdu7cXlISymnEPDKxZ81Mu62G0HvUWcAgGvD5MEjCzHJdFs1YBVyvTSs+TeTjw7rD+MGlWPsq1+0VwEbaIVxfjeeLZw3Mat16HCRKO5Z7CvoZo472ABw3hhyc8ZGh9mGtEk5jgGSasEzHJOk4mh9gsOKnxPLI2j6yz0c26K5VBWKftx0VUAWnvqTchdvRv7qNUCnXr/2E/pI8hqAkvpBzKJzIgNAbQDJx5V9oaJHgSVk22Ss5jPW9UWFe6l3oLONuyg7Banj/bC47JOJ4FIgR4D6Up4MJ94GyLgnBTeEK3eXdV2gcujW9GNQKO5wIOhNMibPGYh9v08M4n6oF3e3QfuFo8cKw35Zq0Q5jIiEkWnhMEZTT7apyAw9NOKDRh1OF3gOeXvoZ45xtAJEprMw9Xer71e/skIAHXPts913fdlgKOwR0x7ryUCZlkBppZQz4IhEIRS0+CkNAQDwze8fKQ5IA1ZwxKmEXGGFzapp/heUkEHGuqmJFGBLCeiAEkYRsM8iw9NYMm254AQcSggoEhM8GEmCE88RikKeAshIT74eNG8gjuhw8k/1Qy+BCGxEcd474YwCJSmallbQGehKgQYw82BoWwhgPnMeDGE8DHmvPwQsQJZlu3gsClbRF0GINHvJgY7Y7oos0x2CPIGSDzMafeWBheRzkM4m0TeFJfMytLWRgDbDyVSYYGjh8AACAASURBVMNs6i3gGPiR3MOyaPL8wAgRa/uo1SrgamVa7vmxEDCOQcCXW1sYl/CDNmRdF+XYs4BXGPGElVrXxG+E9rE3FCHJPBfMwtPPeT5IkIBAiXqkOI/QSNtmhNl/jqEeDPiZGOC9wZo7S2BSqf/Y7xZSzH2US5SDsLQ97cKyefYZjFrb825jwoo+RdncT/R9x/m8W0jiQT+gH+KR5x1lUQDnnHNOrCfR1r8yUEdA0ycIiWZQTP8njLdaBtSn3gKO54V1srx3uAcEHG3Ae4NJBd5deGzTFHDcJ5NdrPmEF+8bBBFCmOeIyamod66UZ6m134xqBBz15n2Ip9+82ggf+gshyfzD8xfuzdoaDxwJSnj+MBLu8G2CF88qzzXfUSZM7J3PcXGc7Fnld+pqnnu+A/R3nnvag++YTASyICABlwVVlZkpgbYUcHyYEHHMsDMjj1BALDEzz98I14ozPlB4lDiHhAd8XBF8fGwJS4vLVJVEwHEtBCL1YsCJp40BXzTTILP8XJ+ZX/uwMxOLsGM2O20BR72YgWQgYANY/lbNh50ZapKOMHBFcDKbzMw8adZZz4T4jBNiDFYItWKmHoHLB5rBAddGKJU6j484awpJ9sD1bM+mqLClXswIk4gAnlwDYcxgAKFD+JRloOOemdFFoCOEGIwwEEGEsh4LzxwelqTijfLqLeC4Js8PAxa7XwZUIfvWCDjKr5ZpuReMrbdL8hIqta6Ptud+bZYdAcWAjr5fKpusXY9BKOF+TOaQ9IbnD9HP+6FcKBXePvoLe53xXmHAz6CQ/on3ARFUrdmzUum8cp4MQjBJeoLHmIEp7xa82WyGXG79Gv2CNUWIWvoTogyPHl75Uh40wjEJE7W+ghC2rTcQkrVsu9EWAs5ELF5D+j/vZdqeBC+8hxCyMEhbwHFdJoZoLzx/fGt4dpm84lq8a0LvVrnQwNZ8M6p5z9uziXgi+ymTf0zUMYGBMGIyjeeN0FtL8d8aAcf3iHc373XEFn0NkUtfQWyxZUR0i5E4TrQhyxboH5RJOfa80rZM9JRLmFSpT+p3EahEQAKuEiH9LgIJZnAFSQREQAREQAREQAREQATqQUACrh6UdY3cE6gUgpP7G9QNiIAIiIAIiIAIiIAI5IKABFwumkmVbGsCEnBt3QK6vgiIgAiIgAiIgAiIAAQk4PQciEACAhJwCSDpEBEQAREQAREQAREQgcwJSMBljlgXaAYCEnDN0Iq6BxEQAREQAREQARHIP4GmEXBkCyPlOJssk8GILGJkk2OfmqiRQW3o0KF+byNSFFtmLfauIXMQGeWiRvpfUk6TWYxsSaSC51j2eIozMhSRCY8NhcnGxUaspCkn46D2BMl/x9EdiIAIiIAIiIAIiIAIiEBbEGgaAWfpkhFfbJaLgCol4GyjVvYaQbSx7w4p2J966im/8eJLL73kU5abkdqYjR1JEcvmj+x7M2zYML9/Fht2sq9IaFybdMmkjrdNlhFypHsnHTTpqWUiIAIiIAIiIAIiIAIiIAIiUC2BphFwDz74oN8sEwF2zDHHFPZzinrgPv/8c7/HBxulItTYm8YM79jFF1/cQpSx0TJ74LCvCvtQYXjVEGnsOcUGkOwBZcZGruxlcsUVV/h9V7Dff//d7zHC3iPPP/+83+RTJgIiIAIiIAIiIAIiIAIiIALVEGgaARfedDkB9+yzzzoEGZsYs2lkaGyy3LNnTx8qecIJJ/ifxowZ48MlEW5sDBwaYZt9+vTxm5Ueeuih/qfvv//eh2DiESQ8M7Qnn3zSe/IIpbzooouqaScdKwIiIAIiIAIiIAIiIAIiIALNmYWynIAbN26cm2eeedz888/vCI2cdtppC4+BeeAeeught8466/i/45Hj76eccoo75JBDih4ZQiTnmmsu1717d3fvvff63+677z7//5xz4YUXFh3/559/uplmmsl7CRGGMhEQAREQAREQAREQAREQARGohkC788AB57TTTvNiLLoG7sUXX/Thl6FQO+igg9wZZ5zhbrvtNrflllu2YDvDDDO4ueeeu+BtIzEKa+w4Z+DAgS2OX3rppd3bb7/tk6xUsn/+85+xh1BPhODCCy9cqQj9LgIiIAIiIAIiIAIiIAJ1IzB27FifS4IEgLJsCLRLAQfKa6+91ocy/vzzzwWym222mfe0de7cufC3Pffc01122WU+fNLWv4VNwXo6kpvgjcNOPPFEH4LJOX379m3Ral27dnVPP/20mzhxok+eUs5KCbjnnnvOJ2pZZpllsnkqVKoIiIAIiIAIiIAIiIAI1EDg1Vdf9TkmyDshy4ZAuxRwRx11lBdqJ510ks8qOf300/stCPr16+cmTJjgBVaXLl088T322MOvlSNJyrrrrtuiFaICbvDgwW7QoEH+HNbZRa0aAVeqyU3YsaZOJgIiIAIiIAIiIAIiIAKNQkDj1Oxbot0JODxpG2ywgSM0klDK0BBxa6yxhuvdu7cjQQnWliGUEnDZdwBdQQREQAREQAREQAREID0CEnDpsSxVUrsTcGy+feaZZzoyTm6yySZFXEgyQlgj2xGwGTjWiElM1DGy7xi6ggiIgAiIgAiIgAiIQPUENE6tnlm1Z7Q7Ade/f393wQUXuKuuusrtsssuRbzGjx/vOnTo4P7xj3+4F154wf+WZBsBQjEPO+wwf3ySbQT22msvLwxrNXWMWsnpPBEQAREQAREQAREQgSwJaJyaJd3/L7vdCbghQ4b4EEkSgDz11FN+/ZvZAQcc4M455xw3YMAA76UzS2sj74022sg9/PDDjiQkK620Us2tq45RMzqdKAIiIAIiIAIiIAIikCEBjVMzhPvfoptGwJE0xJJ6sL/bK6+84tZee22/VQBGRkgeKDJGss7tmWee8fvBEUZpSUyef/5517FjRzd69Gg355xzFuhTHucSYknSk9lmm80NHz7ckSb1rLPOcgi/0D7++GO38soru6+++sptvfXWbsEFF/T7w1Gn/fff35199tmtall1jFbh08kiIAIiIAIiIAIiIAIZEdA4NSOwQbFNI+AIh7zmmmtKEgtDJknhf/rpp7tbb73Vvfvuu16YderUyW288cY+g2Qo3qxA1sTx22OPPeZ+/fVXt+SSSzrW0yHo4uyjjz5yRxxxhBs5cqT74Ycf3CKLLOI39/7Xv/7lJplkkla1rDpGq/DpZBEQAREQAREQAREQgYwIaJyaEdhmFHDZo2qcK6hjNE5bqCbxBB599FHvAT/66KPdMcccUzdMn332mc8cy/W/+OIL74H/4IMPSl7fJn7ef/99t8ACC6Rez6uvvtrtuuuuRWtuqQ9e+Z133tnxe14t7t7yei+qtwiIgAiIQHoENE5Nj2WpkprGA5c9qsa5gjpG47RFI9XEhEFYpymnnNLNPffcfhN6NphHONTD2krAsUUIezayznWhhRZys8wyS4sQ5/D+JeBqfxqyFHCI/mOPPdY98sgjbq211qq9kjpTBERABESg7gQ0Ts0euQRc9oxTv4I6RupIm6JAE3CdO3cuhPayMT1i6qWXXvJihgQ6hPNmbW0h4H777Te/DQhildDlJCYBl4RS/DEScLWz05kiIAIi0MwENE7NvnUl4LJnnPoV1DFSR9oUBZqA22yzzdztt99euKe///7bh/GxRhTBwnrQrK0tBBzrTueff/6qQhMl4Gp/EiTgamenM0VABESgmQlonJp960rAZc849SuoY6SOtCkKLCXguDk8b6ussopPvmOb1PN31omdeOKJ7u6773affvqpm3nmmd3666/vjj/++BbhlmRevemmmxzZWj///HM39dRTuxVWWMHvgYjXK7RSAo7rbbjhhu6dd95xN998s+vZs2dF9rfccovP3Prqq686xOhSSy3l+vXr5/r06VM4lzA7EgxFrdIaPBNw7733nmOLEcQt6+gINd1vv/184qHQygm+uN/SWANn9/bzzz/7NYXUc9y4cW755Zf3WXDJePvJJ5+4gw8+2D3wwAOO42jDCy+80GfaDe3KK6/04p6MuLTFDDPM4Lp27eqOPPJIt+KKKxYdG9Z9pplmcqeccop77bXX/BYotG8pAff222/76//000/unnvucauuumqh3Ntuu82dd9553iOMx7RLly6e8Z577lmxLddcc01/XZkIiIAIiEBjE9A4Nfv2kYDLnnHqV1DHSB1pUxRYTsCNGjXKD6RDAUcGVsQBA/kePXr4wTRerGHDhjkG7Gy1EYZb8vtUU03lN7qfa665vIhDDJBlFZG15ZZbFjjGCTgShTCw//rrr92dd97pGJBXspNOOslnc+V6vXr1cpNOOqlDBCBY+PvgwYN9EYgJtvtgH8dll13Wbb755v7v3F+5NVQmushA+8ILL7htttnGTTbZZP5+ELRHHXWUX4tl1pYCDrH75ptvOvaTHD9+vBfT0003nd/PkvrjfUTMIc4eeughv11KVNQSYrrccst5EdyhQwf34Ycf+jZEGNNmodgygcb1KA/P7sILL+wmn3xyd8IJJ8QKOBhyPGsv77//fv+8mSEwyf7L2kQEP3VBcI4ZM6ZoexWuyz/UnUQvllyGf8NfJgIiIAIi0NgENE7Nvn0k4LJnnPoV1DFSR9oUBZYTcLvttlshE6KFULJBPZ4QEkXw32YINwb/JATBg2KGAIsmQfnyyy+9Fw5vHF4ss6iAw+tHeezDyJ6IiMBKhsBcfPHF3bzzzuv3Zpx99tn9Kd999533JvL7iy++6AUJVkt2RxNkJHqBhW0hgkDivtjTEdG06KKL+mu0pYBD8I4YMcILH+yMM87wGTdnnHFGt9dee7lTTz21gBSxd9ddd3lvaehZi2tD7g/hB1MSwJiZgEPQ8ox069atqMmiHjjanOvOMcccXpiFzwprEhF2iPDrr7/eCzzs999/93+74447HJMM1ANTEpNKvUO/i4AIiEDjEtA4Nfu2kYDLnnHqV1DHSB1pUxRYKonJ448/7r1LJDFhkIwYQfggUAgTxGsVNTagJ2QSIYM3rpxRBmFxYSr+UMAxcMdDNP300/uBPUlWkhieLwby559/vg+ZDO3aa6/13pkBAwa4M8880//UGgGHp49Q0NAIQeS61ANPHNaWAo52DEUUXkj2r4QrQnraaactVB+RRIgpIZOsf6xkCC/bs9LElQk0ngU8klELBdyss87qtt12W7fYYov5cvCYhkb5TAZQz9lmm63oN8T90ksv7QYOHOhFKSYBV6nF9LsIiIAINC4BjVOzbxsJuOwZp34FdYzUkTZFgXHbCEwxxRR+HVR0G4GLLrrIbypPqCEhh1FDaD399NNFHhxCJlkvxwAdz9Qvv/xSdBrHmyfPBNw666zjRSNCg5A6/p3UCMlERBISuMwyyxSdRugfIXWUT3gf1hoB98QTTzjrV3Yh1tzBhnoQttnWAu7777/33jazP//804czshYOQR4anjTCVQl1ZPsIM9Ye0oaEJ7LWj3VoofE3vJGYCbSTTz7ZHXrooS2azX7v3r27F+Z48FhLyTrKqOHZ5Fr7779/i9/wwlEnwng5H5OAS9pLdJwIiIAINB4BjVOzbxMJuOwZp34FdYzUkTZFgeVCKKM3yNqxQYMGVbxvhBiheyTNQMwwwOf5QzTgmWNNGscgCMI9u0zA4fX79ttvvTeILJiTTDJJxWvaAYhOxBlr9Cy00X5DPBJKSHggYYJYawTcW2+91cIziLcITxL1QKBgbemBY51a1OAZl9wjbg0iyUUIUSS5CPe0xBJLeO8dbWiJTUIvqgm0Ul48+93amOeJ5DdxxkQC4bPljLWKPEMScIm7iA4UAREQgYYkoHFq9s0iAZc949SvoI6ROtKmKLAaAUfII6GPl112mevbt2/F+2d9FV4YPCWHH3540fFkEbz44otjBRzZDfGWEfJIpkGOSyriGtEDZ2sJWX8X3U/P6hsnglh3aAk4qhWaloWytQIOjyueV7JYbr/99kVtiBeNtYmV6h6eZAKOMkl8g8iNevzseBKmILgJ+0xi8sAloaRjREAERKAxCWicmn27SMBlzzj1K6hjpI60KQqsRsBZVsrdd9/dXX755RXvf++993aXXHKJTyNPBkMzRAXeOMIc4zxwpL1n/Rjr1ViXhdhjbVkSszVwiM3+/fsXnWJrvMJ1U9UKIwo0j1rSNXBcj9T9eBxJ9GL2119/+bWF//nPfyqKoGrrmZaAYy2irXPD82aGN5MMll999VXFuscJOMQp69823XRT7zGNC7k0gUiW0yRhtHjyeG4IBV133XWTPC46RgREQAREoEEIaJyafUNIwGXPOPUrqGOkjrQpCqxGwHHDrFkiuyPhcwy+Q2NdEiLPnjU8b6ylwtuCmDNDzCBqsFICDm8K67UIo7zxxhu9GEOUVbIwCyVJWCz5BWvBqDvrueqdhRLvVe/evV1U+LJPHQlVsEperLYScHhA8biSyRIxhyHAaT/qn6TupQQcQnjixIluk0028c/Baaed5jNkmt17771+jRvr8kiIEk2MAzM8s7ZlwAUXXOCfE7x8iH+ZCIiACIhAfghonJp9W0nAZc849SuoY6SOtCkKrFbAjR071q299to+IQnZDfGksR4KLwlJPcgsyNowjGPwvDFI32qrrVzHjh29+Hv22Wf9eioyDJYTcJSBiEP8sIH3AQcc4D1ZlcyEI2vR2KPN9oGjPuE+cJRTrTDiHPPAIS64n0r7wHH/7G3GtdiQnOyJbD/AHnTwwTPXqAIOsYvwJcskHjNEFO1MfUkSw7q5SnUvJ+D4DT5428iYSfvSzma0F55OhDjseIbw+rGNAZMFiOPtttvOH/7GG294tiTg4Zlhw3G8hOHm7ZWeHf0uAiIgAiLQNgQ0Ts2euwRc9oxTv4I6RupIm6LAagUcN01yEjZXZh8uBu8km2DftdVXX93tsMMOReFrCJVDDjnECx1CBtn0mTVPiDfCHSsJOK5HIgvKxQsThj+Wa4ChQ4d6DxFhmhgCat99920xmG+NgGMPOwQECTtI1MIeZqwRZN1Y1BC+CBPuF0FJiCPp70kMQ6KWSiKo2nqmFULJfRDiyLpEQmERcpRNyGPSulcScPxOkhREHOKQLSrgaIb3j20hEGwTJkzwe/uxlpBtBvC0hVsMXHHFFX6LCNqGDJZxyVqaouPqJkRABESgyQhonJp9g0rAZc849SuoY6SOVAWKgAiIgAiIgAiIgAikQEDj1BQgVihCAi57xqlfQR0jdaQqUAREQAREQAREQAREIAUCGqemAFECLnuI9b6COka9iet6IiACIiACIiACIiACSQhonJqEUuuOkQeudfza5Gx1jDbBrouKgAiIgAiIgAiIgAhUIKBxavaPiARc9oxTv4I6RupIVaAIiIAIiIAIiIAIiEAKBDROTQFihSIk4LJnnPoV1DFSR6oCRUAEREAEREAEREAEUiCgcWoKECXgsodY7yuoY9SbeGNe75dffvEp/dmM2WyJJZZwHTp0aMwKq1YiIAIiIAIiIAJNT0Dj1OybWB647BmnfgV1jNSR5rLA7bff3t10001FdV9ooYUc+5TJREAEREAEREAERKAtCGicmj11CbjsGad+BXWM1JHmssA11ljDb5Yc2lRTTeXwzMlEQAREQAREQAREoC0IaJyaPXUJuOwZp34FdYzUkeayQAm4XDabKi0CIiACIiACTU1A49Tsm1cCLnvGqV9BHSN1pLksUAIul82mSouACIiACIhAUxPQODX75pWAy55x6ldQx0gdaS4LlIDLZbOp0iIgAiIgAiLQ1AQ0Ts2+eSXgsmec+hXUMVJHmssCJeBy2WyqtAiIgAiIgAg0NQGNU7NvXgm47BmnfgV1jNSR5rJACbhcNpsqLQIiIAIiIAJNTUDj1OybVwIue8apX0EdI3WkuSxQAi6XzaZKi4AIiIAIiEBTE9A4NfvmlYDLnnHqV1DHSB1pLguUgMtls6nSIiACIiACItDUBDROzb55JeCyZ5z6FdQxUkeaywIl4HLZbKq0CIiACIiACDQ1AY1Ts29eCbjsGad+BXWM1JHmskAJuFw2myotAiIgAiIgAk1NQOPU7JtXAi57xqlfQR0jdaS5LFACLpfNpkqLgAiIgAiIQFMT0Dg1++aVgMuecepXUMdIHWkuC5SAy2WzqdIiIAIiIAIi0NQENE7Nvnkl4LJnnPoV1DFSR5rLAiXgctlsqrQIiIAIiIAINDUBjVOzb14JuOwZp34FdYzUkeayQAm4XDabKi0CIiACIiACTU1A49Tsm1cCLnvGqV9BHSN1pLksUAIul82mSouACIiACIhAUxPQODX75pWAy55x6ldQx0gdaS4LlIDLZbOp0iIgAiIgAiLQ1AQ0Ts2+eSXgsmec+hXUMVJHmssCJeBy2WyqtAiIgAiIgAg0NQGNU7NvXgm47BmnfgV1jNSR5rJACbhcNpsqLQIiIAIiIAJNTUDj1OybVwIue8apX0EdI3WkuSxQAi6XzaZKi4AIiIAIiEBTE9A4NfvmlYDLnnHqV1DHSB1pLguUgMtls6nSIiACIiACItDUBDROzb55JeCyZ5z6FdQxUkeaywIl4HLZbKq0CIiACIiACDQ1AY1Ts29eCbjsGad+BXWM1JHmskAJuFw2myotAiIgAiIgAk1NQOPU7JtXAi57xqlfQR0jdaS5LFACLpfNpkqLgAiIgAiIQFMT0Dg1++aVgMuecepXUMdIHWkuC5SAy2WzqdIiIAIiIAIi0NQENE7Nvnkl4LJnnPoV1DFSR5qrAl9++WV36aWXumHDhrkvv/yyqO6TTjqp69u3r9tkk03cpptumqv7UmVFQAREQAREQATyT0Dj1OzbUAIue8apX0EdI3WkuSpwn332cRdffHHZOq+wwgpu9OjRubovVVYEREAEREAERCD/BDROzb4NJeCyZ5z6FdQxUkeaqwJHjRrlVl111bJ1Pv/8812/fv1ydV+qrAiIgAiIgAiIQP4JaJyafRtKwGXPOPUrqGOkjjR3BW688cZuxIgRsfWed9553Xvvveemnnrq3N2XKiwCIiACIiACIpBvAhqnZt9+EnDZM079CuoYqSPNXYHlvHDyvuWuOVVhERABERABEWgaAhqnZt+UEnDZM079CuoYqSPNZYHdu3d39913X1Hd55lnHjd27Fh533LZoqq0CIiACIiACOSfgMap2behBFz2jFO/gjpG6khzWeCzzz7rVltttaK6n3feea5///65vB9VWgREQAREQAREIP8ENE7Nvg0l4LJnnPoV1DFSR5rbAkMvnLxvuW1GVVwEREAEREAEmoaAxqnZN6UEXPaMU7+COkbqSHNbYOiFk/ctt82oiouACIiACIhA0xDQODX7ppSAy55x6ldQx0gdaa4L3Guvvdxbb73lRo4cqbVvuW5JVV4EREAEREAE8k9A49Ts21ACLnvGqV9BHSN1pCpQBERABERABERABEQgBQIap6YAsUIREnDZM079CuoYqSNVgSIgAiIgAiIgAiIgAikQ0Dg1BYgScNlDrPcV1DHqTVzXEwEREAEREAEREAERSEJA49QklFp3jDxwrePXJmerY7QJdl1UBERABERABERABESgAgGNU7N/RJpGwF1//fXuiSeecKNHj3avv/66++2339zw4cPd5ptvXpLi/fff78455xw3atQo9+OPP7q5557brbLKKu60005znTp1Kjpv/Pjx7qijjnK33367+/rrr918883ndt55Z3fooYe6KaaYosU1fv75Z3fCCSe4G2+80X322WduzjnndL169XLHHHOMm3766VvVsuoYrcKnk0VABERABERABERABDIioHFqRmCDYptGwC2wwALuww8/dLPPPrvPxPfxxx+XFXCDBg1ygwcPdh07dnQ9evRws8wyixdajz76qLvhhhucPXywmjBhgt8wecyYMW7jjTd2Sy+9tHvqqafck08+6QUiQjG0P/74w62//vq+rG7durnVV1/dvfbaa+7ee+/1AvGxxx5zU001Vc2tq45RMzqdKAIiIAIiIAIiIAIikCEBjVMzhPvfoptGwD344INuscUW854xvFzHHntsSQF36623em/YVltt5cVaVEwhwCaffPIC/cMPP9ydfPLJ7sgjj3THHXec//vff//tPXDXXXedozzKMrvkkkvc3nvv7XbaaSd3zTXXFP7O+XjlTj/9dHfggQfW3LrqGDWj04kiIAIiIAIiIAIiIAIZEtA4NUO4zSbgQlTlBBzCq0uXLu6LL77wXroZZ5yxLOW//vrLzTvvvG7ixInu888/d9NOO23heM6ff/753YYbbuhGjBhR+PvKK6/sQzk/+ugj7+Ezo4y55prLl/fmm2/W3LrqGDWj04kiIAIiIAIiIAIiIAIZEtA4NUO47VXAvfzyy2755Zf3HrObb77Z3XfffT68ESG3zjrreHEXGhskL7744q579+4+BDJq/IaQ++GHH9wkk0ziWPvGGrfOnTv7kMuoUQ7X/PLLL90cc8xRUwurY9SETSeJgAiIgAiIgAiIgAhkTEDj1IwBO+eaJoQyRFXOA3fFFVe4vn37uj322MO98sor7rnnniucigDbb7/93FlnneXFGHb33Xe7TTfd1O27777u3HPPbdEi/MYxn376qZtnnnl8AhXWyPH3O++8s8XxlHP++ef7NXSsjStn4Tq88LhXX33VLbPMMn4NnkwEREAEREAEREAEREAEGoWABFz2LdHuBBxr2VjTNtlkk7lFFlnEXXbZZd4jhxcOUffGG294gdWvXz9Pf8iQIa53797u3//+t1+/FjV+4xi8bXjjnn76ade1a1d/Dpkxo0Y5J554ovfm4Y2TgMv+IdcVREAEREAEREAEREAE6kNAAi57zu1OwCGeEFF42F566SW37LLLFiizLm2ppZZyZLQcO3as/ztJTnbccUdH1srjjz++ooDDs8aDyzkkOGmNgCvV/OoY2XcMXUEEvrqQlQAAIABJREFUREAEREAEREAERKB6AhqnVs+s2jPanYC74IILXP/+/X22SrYdiBqZLN9991337bffuplnnrlNQygl4Kp9nHW8CIiACIiACIiACIhAWxKQgMuefrsTcA888IDbYIMN/Do11pJFbaWVVvIZJNkTjo29lcQk+4dQVxABERABERABERABEWgOAhJw2bdjuxNwP/74o9/smzVw48aNK9oD7vfff3dzzjmn+/XXX93333/v94JjGwGSk5Bdkq0HpplmmkKr2DYCCEIyS5pV2kaA8hCGtZo6Rq3kdJ4IiIAIiIAIiIAIiECWBDROzZLu/5fd7gQcN00WSrJRHn300X7Tb7OTTjrJHXHEEW777bf3iUnM4jby5jc26mad2y233OK23nrrwvGVNvI+7bTT3EEHHVRz66pj1IxOJ4qACIiACIiACIiACGRIQOPUDOH+t+imEXCXX355Ia0+e72xRcDaa6/t17qZaLMH6uuvv3arrbaaT1Sy7rrruuWWW85nobz//vv9JtujRo3y/zabMGGCW3XVVf3m2z169PDhl6Tw55/NN9/cDR8+vKil/vjjD7feeuu5xx57zHXr1s1npSRck8yTeOcef/zxIs9ftc2sjlEtMR0vAiIgAiIgAiIgAiJQDwIap2ZPuWkE3C677OKuueaaksSuuuoqxzFm33zzjffA3XHHHe6rr77yYZWbbLKJ98ix9i1q48ePd0ceeaS7/fbbHed26tTJl3fIIYe4KaecssXxEydO9NsO3HjjjX49HaGZvXr18uXPMMMMrWpZdYxW4dPJIiACIiACIiACIiACGRHQODUjsEGxTSPgskfVOFdQx2ictlBNREAEREAEREAEREAE/kdA49TsnwYJuOwZp34FdYzUkapAERABERABERABERCBFAhonJoCxApFSMBlzzj1K6hjpI5UBYqACIiACIiACIiACKRAQOPUFCBKwGUPsd5XUMeoN/HGvR6JddiQfsMNN3STTDJJ41ZUNRMBERABERABEWgXBDROzb6Z5YHLnnHqV1DHSB1pLgskOc6CCy7ofvvtN7/9xeDBg3N5H6q0CIiACIiACIhA8xDQODX7tpSAy55x6ldQx0gdaS4LHDp0qNt2220LdWcvQvYklImACIiACIiACIhAWxHQODV78hJw2TNO/QrqGKkjzV2Bzz77rNthhx3c+++/X1R3/n+BBRbI3f2owiIgAiIgAiIgAs1BQOPU7NtRAi57xqlfQR0jdaS5KvCHH37wG9R/9913Lep94YUXun322SdX96PKioAIiIAIiIAINA8BjVOzb0sJuOwZp34FdYzUkbYo8O+//3bnnHOO+/LLL13v3r3dAQcc4DdjZ7P4ySefPPsKlLnCyy+/7JZffvnYIzbddFN35513tmn9dHEREAEREAEREIH2S0Dj1OzbXgIue8apX0EdI3WkLQq89957XY8ePVr8fciQIW777bfPvgJlrnD//ff7rJNxNu2007rx48e7qaaaqujnDz74wI0cOdJtscUWbo455mjT+uviIiACIiACIiACzUtA49Ts21YCLnvGqV9BHSN1pC0K7NevnyMcMWr77bef98y1lT399NOuZ8+ebty4cSWrgMBbf/31i35ffPHF3VtvveVF6d13391W1dd1RUAEREAEREAEmpyAxqnZN7AEXPaMU7+COkbqSFsUuNJKK7nRo0e3+Dup+knZ3xb2559/unnmmcd99dVXhcsfc8wx7qijjnJnnnmmO+igg/zfTz31VHfwwQcXjvn5558dnjkzwkNlIiACIiACIiACIpAFAY1Ts6BaXKYEXPaMU7+COkbqSFsUuNhii7l333039kIjRoxwG220UfaViFzh7bffdl26dCn6q4V03nHHHW7zzTf3vy211FLutddeKxwXPU8Cru5NpwuKgAiIgAiIQLshoHFq9k0tAZc949SvoI5RGunnn3/uvVFzzz23GzBggJtkkklq4j/vvPM6NsqeYoop3AknnOAOPfTQQjmTTTaZ+/TTT31Sk3padN83rv3oo4+6Nddc00UTm1x11VVul1128Zt8zzzzzA4vnJkEXD1bTdcSAREQAREQgfZFQOPU7NtbAi57xqlfQR0jHil7o2222WaFEEMTN7U0AKLn+++/9+IHj9tqq61WVAxr0aJ/q+U61Zzz73//25144olFp/z6669uyimndN9++62bddZZC7+ZF+7444/3IZahScBVQ13HioAIiIAIiIAIVENA49RqaNV2rARcbdza9Cx1jJb4ESWLLrqoGzt2bOHH008/3R144IH+/9944w03YcIER4IPPGd77bVXWe8cnrc//vjD4Yl78MEHHUlAQuNv6667bl2fg0022cTdc889hWual40/cP+EV77zzjv+986dO/t7XWSRRdzvv/9eVE/+v623QqgrOF1MBERABERABESgbgQ0Ts0etQRc9oxTv4I6RkukZFiMiqw99tjDXXrppT4Zycorr+xFjtkzzzzjVl111aKCSBJy7bXXuksuucSNGjXK/8ZauKeeesrNPvvsRcey1xp7rtXLnnzySdetWzd/uUknndSxmXeYmIS/k9zEwjoXWGAB763bYYcdWlTxxx9/dNNNN129qq7riIAIiIAIiIAItCMCGqdm39gScNkzTv0K6hgtkSLQnn/++aIfWBtGGCVChvDD0C666CK39957F/2N7I3hWjd+ZMPsF1980QuhG2+8sXA8/73ddtul3rZWIJ7EXXfd1XvSEKGs6WNTcaxTp07uo48+ir32NNNM43755Rc311xz+dDJf/3rXy2O++abb1yHDh0yq7sKFoH2SgDPPFt4ELo8aNAgjwFPPh59PPb8LhMBERCBZiegcWr2LSwBlz3j1K+gjuF8qOQLL7zgNt54Yzf99NP79V+sAwuN8EEySe65557usssuK/rt3HPPdfvuu2/hb4RXzjTTTC3aCtZPPPGE994de+yx/h/siiuucLvttlvqbWsFrrPOOu6RRx7x/8vA76GHHipci3V50Xu1H2eZZRb33Xff+bV7iNHDDz+8RR0/+eQTHxra3ozNzBdccMGi2ybJDV5Lwm8R9GzSXmvim3rz5H5OOukkLwpoU9ZCskn7Msss4xPbsGch3lqMiYy1117bHX300Y6tJ9q74aH+8MMPS2J4//33HcdUaxJw1RLT8SIgAs1IQOPU7FtVAi57xqlfoT13DMIcGYCefPLJfmabdV8PP/yw3x/NDPGCiJlhhhn8urcNNtjAPfDAA0Xt0L9/f3feeef5vyHOVlhhBffSSy+1aKsNN9zQ3Xffff7vZLe0NXVRAZh2I5cTEdx71FNo18dT98UXX7ipp57aHXDAAZ5T1N577z238MILp13lhi/PBBxeTfOe8jyRUfT222/3onjgwIHujDPOaPh74VlFkJFoh9BaPMWsa2Rig5BfvKxkHuU5kIBr2ZyIM/rJYYcdFtvW9B3eI9XaxIkTvXeckGvzcssDVy1FHS8CIpB3Au15nFqvtpOAqxfpFK/TnjsGiTuini/2P2MAjjGoZSsB1sRhP/30k1t22WUdoiVq48ePd3is+A0PTJxttdVW7tZbb/U/sTbOwi7Liag0mrqcgGPQPuOMM8ZeZqGFFnJ4DzCECnvAYWx9gFjBSO4Cl379+rWrUEoTcGQqtefFIDLoXmKJJXzCF8Q/oaiNbOahveGGG1qsc+QeRo4c6bp37+7bHZMHrrg1EXC0M/9kbRJwWRNW+SIgAo1GoD2PU+vVFhJw9SKd4nXac8cgLMw8Z3FIe/fu7cPJHnvsMf8z2SeXXnpp99dff7U43Lxo11xzjd8zDcMzFWay3GmnnRy/Y9ddd53j/7HZZpvNff311ym26v+KYu+2qaaaKrZsNuzu2bNnyesiQt58880Wv+OZQ9iG1rdv3xahpZncUIMUWk7AUUW8sKx3ZK0hoYihEc562mmn+eQ2iF+EMs/CQQcdVJTRE3HN+kqyhRK+yyQB6xERU4Tf8t+h8dzxfDGJwEQBobnU84gjjigb6ojAxLtWKpQ2vAYeawv9jTZFmNgHjxTrRe+++27vlcQDZeu5oqGnw4cPdzfddJNfd8pzRV3gh0drvfXWK7pMKB4RntSHxEJ4qJhsCH/faKON/L0/99xzft0YIdJnn312iyRCCFTagw3rEWGEUC+55JI+LBqBXsmqEXC33Xabu/nmm32d2RsS9iuuuKIPT+Z+QqsmhJJJg8GDB/voAMolKRHrW/H6sx5XJgIiIAJ5JdCex6n1ajMJuHqRTvE67blj4E179dVXS9I85JBD/NoWBlzYBRdc4D1NGIM8BtRmJuDIVnn55Zf7P3PetttuWziGc88//3z//8OGDXN45MziBvppNDPCMCogrFw8i3jWStk//vGP2FBQQuziQkSr3ROODJY9evTwA04ycUYzf6Zx/1mVUU7Affzxx/5eEC1MAIRG+zNxQJsgKPDakhUUkYH3l+fCPKbsRcj6Mwb2TAYw2H/llVf8IB3RgEDkfDMTcAgX1nTClskBJh1ssiCOR8eOHb3QRAQgzssZAunqq6/2QpG6rbXWWoXDbT0cYpO/I+KoA6HJlM29sTaUrK2sKTXjdyYZeN4QpYg4vJpkR73lllvclltuWTjWBBrCjokVQpoRWxx74YUXFgQcIhehjGi07K/wJFss+y4aYyYx4M59kwmWfk29Ederr756oS+XY1KNgMM7zzrb5ZZbzq+XtHulL8AnFIxJBRz3zvNG5ljugfsl3BuPOffB7zIREAERyCuB9jxOrVebScDVi3SK12lPHYNBJNkU2TS7a9eufmBbyhh8M1gk1BEvCEYmR8IuMQam4T5qiDuyNIZeKwbvDI7NmOXHy4KxFo5BphlCslx9am1y6sBMfNTmn39+76kpt4cbA1gG21FDINhavvC3agUcawfhhrGX3sUXX1zrbdb9vFJr4BCjeJTgSkgiAsIMDy4D91VWWcVv6M66SgxueHtgMXToUNerVy//dzxwhKqGm6rz9+uvv9716dOnKDshfzcBh6Bg7Vq4lrMcoAEDBnjPFM/JPvvs40OHqaeteYueWymEkv6FwEdAhRvU8yytscYaXnSFfQfPWdQrh6DEC0cdwpBluzZ1igv5DH/HC2mTJHjNaQvWuCLgrF6IQ+qC6I5OdIwbNy5RWHC5NXAI2VDkxt0rIo57JZTZwrW5v6QCziaDmBywCSZrs6T3UPcOpAuKgAiIQEIC7WmcmhBJ6odJwKWONPsC20vHiGaGZMBcKnySTa7xMDBwxguH8IoaiQkY9JoRLkaGSjweGAKJQX64/oywyR133NH/jmdhm222KZyPNwXPVtoWrsljAEuoGgNrxFklb0uYvdLqhScI7wfCNmrVCriQDZ4J2zg8bQZZlBeXhdKuw1oxngWyNNpeevxmIbtxbc3zyaTBFlts4QizK2dwxvOGyEKwmJmAixvIlyuPBCXUF0FkbUjIIR4xnlHWaob7BJYTcNwbYoR7Peecc1pcduutt/YCF+91XKbW8ATjFWZxtGsTdhjd6oNz7XdEk2VetTItvDlMGoTAI4SSiY5aEo1QdrkslEkzdTL5w0QRQtImfZIKOHgiRJlcsvDtLJ55lSkCIiACbUGgvYxT24KtXVMCri3p13jt9tAxGByTPp91J2ZhUo6VVlqpaDB4yimneOGGHXfccX4gHjW8JYSM2do1BpuEQV155ZX+UNbP4SkJRQphclwLiwoAPCaIqrQNr89SSy3li0WY3nXXXYkvQYgfnqLQ8GKeddZZ/p+oVSPgyMBJJk6zcH1g4gq24YFxIZTcP+F3hIPi1SIcEE+UCRU8bzyD7OkVl1iGiQI8Ua+//nrhzgiXRAghVvCmWPIYDiBUzhLL8P8m4AgV5FrVGuHC9957rw/nxFtmZeNVJlzRJifKCThECGKEsERClKPG/eAB434QYRgeKCZAEFIIGPYeDC30mNm1EZXmGQ+Ptd/hHz5fHGOCiD595JFH+tMIcyaLKFthsD8jwg/vfCVxGV6zmhBK1gOyXYOJxui9hu+IpAKOtYuEobJ+DyHHujfe62GYarXPgo4XAREQgUYh0B7GqW3NWgKurVughus3e8dgUE2oIgOmUoZ4Yu2IrWlDtBAmiIXp/sPz8aYRcsVgKc5Yj0M4Gmt5CL1EDEUFHV4OssrZ4BKRmbaxFsoGyng/8PwlNQaDzO6b4XljAM69RUO1OCapgMOjQuKO0NgzbciQIUmr1ubHVUpigkA44YQT/D+28TtexrgMplExYJk/2eCdiQBCLXkeEQqW0RLvLx4j6mFmAu4///lPi5DEWoCx3o7rMwmAxxrPFVZOwJFIwzadLndNymANHaIUoUfoKe8ivNCIJ/ac4xiEI540C0O0axMKHZdMpVzdSv1GCCLbPSB8CbUk/JXkPhZWWoldUgHHGjW8poh8Qkm5b7tXQjvZI5J/7J2cVMBRP9qcZ46kMUxYYawNRBiXS1RU6d70uwiIgAi0NYFmH6e2NV+uLwHXCK1QZR2avWOEAqYUGgY/DJoZrDL7jsgxD8mll17q12dFjeQHhCCuvPLKscUy+GUTZIxBoW2CHB4cZsHEa4OITNvwXnBPmHkFk14Dz4QlcOEc1u/hJSJzIl4ZvHGhJRVwjz/+uB+8h0boIAPpvFglAcdAmvYMtxkgtJDnAn6lMoOG9w9jrsP6yNCbAmcSYbA/WJyAq3Xj6Dj2iCdCafHikqURKyeSCEvmuWazezKTVjIyJLIPIUIjulE8EyCsi4wTcKVCE2sRcFZHPFkIKIQzocYILDyolTZjTyrguEfEPPd88MEHF6Gx5Ee1CjgrjAkhwljxpOK5JSoAr14W4dmV2la/i4AIiEAaBJp9nJoGo9aWIQHXWoJtcH6zdwxm6o8//nhPloQI0ZAl/s6GuXg2GBhHB2t4hRA+UWNQyXqw+eabr8VvhGMRjmb7ZpVqVgauluIboRSuieMctgCYcsopW/VU2ACcQnbfffdEWfXsgnh9Qs8l4aIWRmf7UYWVSyrgSBpBOGdoeEkZdEbLYxNprllpEN0qSDWcXEnA2TYRiDjEOWaCJBykl7s0zyvCKQz95XhbZ2brLK0M88ClKeAIdWSSAm+OhXZSfzxIeNqsb1kdyHpIpsekzxqhkKynRBxaqC9l8SwhOhC89RJwYVvgbX7ooYe8QIZzOUsq4BC0bO3A1hyEPJpxryQwwtPZWgEX1pNsoXj/Qy9wDY+6ThEBERCBNiXQ7OPUNoX734tLwDVCK1RZh2bsGIRl4R0iXIkBtGW8C7NIGia8ItEBcoiQwXfcXlCWiALPUXQj55dffjl2/U+0acI9tRhs7bzzzv4QPHZ4PbgG3sBSYZpJmppwUMI3MdYmWdbHJOeG4XBxGf8I+7KwT7yRhMElsThRTOZDyjPD68Qm63hQ2YoBj0gjWTkBh/Am5I91ZKG3BZGCKEEMkcUzmkSGzIuE8dp2Cqxx42+k5bcMiYTHkQGVrQfSEnCIMFgz8RAaIp11YTyDYZZQW1eJYLSsrOF5ttaPfhH1KrMxOCLP3jvmlWI9m21sT1mssRw4cKAvNksBxzOHhzr0iHLfiFa8b6zPi+63F30Okwo4W08b9U7i1bY1t7UIOJ4rktqEGW+pI2t52Uvv9NNPd6w5lYmACIhAHgk04zi10dpBAq7RWiRBfZqtYxAyxIAKEYeAQ0xhhDASUsRaHjNC9hhoh3tpRZExCx/dTJhjWMuEB46wqzDNOx6zX3/9NQH5/w2wODgcwJKFkPVqZkk9W3EXZRCNyMTiEjuUqyihfoTEsV4t6h2081ifBfNqNiMnLA5vVGh4bcItC6JbGJApsVRa+0SwUz4obhsB2gnBhTjDA4tXhRBWwh3NaGe2TyCrI8KaZ5VnCJGGKENMMejGWHO2//77e2FFtkSeKwQ52wMwQcEayjRCKFlLx15hiBYyT/L/rNeypCLRbQkQOHieqTcizoSfrX1j83oEOQlJunXr5kUr/Y86I1DoL5Yun2PwvOEF5x4RIUyosB6NfsfkS5YCjncEGSh5D3CfJIlh7RneRsQrExeVLKmA45ngXmlH+jftSHgjXk4mbPBA1yLgEGg8M3hFSc5E+40ZM8azo1/yDqwkQivdo34XAREQgbYi0Gzj1LbiWO66EnCN2CoV6tRsHSP0CoW3zhoiBEyYfCOJMCol4MgmZ/tsMfC09VsMqvHAJDEboHMsyVKoH0ZCBdsvjv9PUk+OY/BJqGG43g7PFQlCMNYY4fFI0xggIpYRcpY8oVL5tu4pPI6BtG0Ojicv6g0i8UOYkr/SNbL+vdQ2AoTiIuwRzXhVQvFmdUKo0t4INtghaBABCDoEkYXl0u4kjMFrSlgkrEksQ0ic7RmYhoBjTSKDfRKGILIIleU+SLpCqCvPZTTFPsKUEGDaDKEffU65L4QFa0WpO/2CNkWYI4zChD2UASuEG95nxDz3SJ1IVJKlgCN0mQkTPL1427hv3hV4JAkDLbdPorVnUgHH8VyHe+XfGPvRca8kC8LjXYuAwyNKGCrtSPsRJo4QJiyZtXZRz1zWfUPli4AIiECaBJptnJomm7TKkoBLi2Qdy2m2jmFpwaMI2TyY5Aq29oqBGrP+lSzcGNiOZYBOinVb48aaFhKW4JnAy8d1khihVOy/hTF4O+KII/x/M6CzNOfRgXGpcsmkiQBg8Mng2kLCbO8rziNkM25LhCR1LXUMg3IEVzWeRxI5xAlJBARehDgPHbwJKZSJgAiIgAiIgAi0HwLNNk5txJaTgGvEVqlQp2bqGOyDRJKA0Htlt88aHrwZ7E/F7PfQoUML2RnLIUKUEZZkabpZnwSzTp06FZ2GN4UQqV69eiVOPMK2An369PHlhAkh+G8EnVkSD1yY5AOvB6nD8chZeBVlnXzyyd5rkqYRXmlp7/GeJEk2Qhgrm01HjT3Q4BxNnsJx4f5YadZfZYmACIiACIiACDQugWYapzYqZQm4Rm2ZMvVqlo6BB4qwrFLrz8LNueOyTZZrOtZ4seaNtOJJBErSxyBc60aSAcQWhgAljDKpgIuuw2MzcbxxeLPeeeedQjkkhjjggAOSVi/RcQhaW8+UdJ0ayVquvfba2PIR4aTHJ9lFaOw/F7cWMVEldZAIiIAIiIAIiEAuCTTLOLWR4UvANXLrlKhbs3QMEkOUy7DYiB4ckhaQURALM0RG7yXqgeP/uR/CJTt06ODFkGWwpCzW1rHmKJooxDYXT/MxZe0aqd4x1nWRpAMBaqGh4bUIm8TzxlqjUkYCiTihduutt/okFzIREAEREAEREIH2Q6BZxqmN3GIScI3cOk0u4EjuQCKA0Ei8gEeHhA+IjDS9Z2k0dbih9U477eRYr4bZflF2jaiAs3TkhC+SQpwkJbbXmJ1DwpKTTjqpqJp45thKIU0jZTxiMmrRcMq4fePi6kFa+rg6hhtJp1l/lSUCIiACIiACItC4BCTgsm8bCbjsGad+hWbpGNwHYZRmJBXBm0MWSVKEN2IabbLvkbYdI/MeCVjIQMjG4eyVVkrAhUKUpClktYuGjrJuj8QfoUX3n0rjYVpzzTV99ruosQE33kEzUrVH1w3GXZ80+mECl/AYUtsTXikTAREQAREQARFoHwSaZZzayK0lAdfIrVOibs3QMQjJs5T+3Cb/T2p2MiM2srFfFmGQobF/Fok8SIiSRMCRbTLpvnNZhJGS1dM2Sg/vwzY6t7+xrxcp06MW9RQSennppZf6wxDhbOhtdvbZZ/t90epteBPZ2w1RaoZ3l3WGSdLM17u+up4IiIAIiIAINAuBZhinNnpbSMA1egvF1C/vHYPwQsL42Ay3lOBp1GbBo1RpbzM2ryY5SGjVhoKy9sw246723ErsSA5jG0+Hx7KB+GabbVb4E2vfwk3Uw7Zik/BbbrnF/wlRxNpAjO0UEE5k+MTYEBphWG8jgQrbUESNJDSE7spEQAREQAREQASyIZD3cWo2VNItVQIuXZ51KS3vHYOwSbsHgK244opFYq4uEGu8CBvush9dOWMj6B9++KFwCN4gEpTw76SWNL1/0vLC48aMGeOWXHLJFqeSUIbELGZsCk0mz6ghwAmZRKxhrFdkXR9G0hW2f2B7ATYoxviN9XD1tFJ7C2YRklrP+9K1REAEREAERKDRCeR9nNrofKmfBFweWilSx7x3DELw2N/MjPVY3bp1y0VLIF4mnXTSsnVFrP3222+FY9hzDW9anBHOePfddxf9NGDAAJ8dMiv79NNPXceOHVsUjyBjw24zQg6///77FsfBgNBI6onhcUTYYtddd53bcccd/Rq/0047zf+tLUSTBFxWT4/KFQEREAEREIHyBPI+Ts1D+0rA5aGVmkzAde3a1T399NP+rl5++WW/V1ueLElIIxtym9Bjo3BS6scZ68NIahIaG5vvtttumSH56aefHF7CqLGVgIkuE2Zxa/UQcCNGjPChk1GzMEwyU9o94K0jC2c9TQKunrR1LREQAREQARH4HwEJuOyfBgm47BmnfoWsOgabX7Pm6eGHH/Yeli222CL1uk+cONHh2WHTZ/49bty4ih6t1CvRygKTCLhwg+yFF17YJzmJMzhHN+oeNmxYJuzt+ggwvISIzNBCz2HoaeTvtkn36quv7jOHfvzxxz77ZtTIILrOOuv4TKK2Nxz73V199dWtpF7d6RJw1fHS0SIgAiIgAiKQFoGsxqlp1a8ZypGAy2Erpt0xvvjiC7fpppu60aNHF2jMOOOMfq8wUtunaY888ogf4GNcM7oXWprXyqqsJALu22+/9QIVI5EHnsY4wzO39dZbF/2EgCazZZbGdgHjx49vcYknnnjCr08M1/otvvjijrDX+++/34dYdunSxSHwuL8JEyYUlcE2C2wU/u6777rFFlvM/8a9cE/1NAm4etLWtURABERABETgfwTSHqeKbUsCEnA5fCrS7hh42ggtl5pVAAAgAElEQVR9ixrZ+sjal6Ydc8wx7thjj/VFEq5H2F7erFQWx/A+Bg4c6DM9sgcaCT0++OCD2NskW+L6669f9Fs0nX8WfFiTx9q8qJGFkmeBtW+hAI3LJMkWA2w1EBrhmdNOO22RAMQDGZcMJYv7sjIl4LKkq7JFQAREQAREoDSBtMepYi0B1xTPQBodg33XGFRTFt42wifjjL3N4kLlagWJ9w0vHJbFHme11qva8/Ba9ujRo2yKfPZEe+WVVzzfMCulXevQQw/1Ke3ZUiE0wi0RfVkam5HjLSsl4L788svCRupsWP7MM8+0OHaPPfZwl19+edHf8cyZsRE75bC3HyGllZK/pHm/EnBp0lRZIiACIiACIpCcQBrj1ORXa59HygOXw3avtWOw/owQOISbZT7cbrvt3E033VSgwIB78803LwzYJ5tsMvfoo48Wpf2vFRmZFQ888EB/+nTTTee+++67XG+qDEdS7ZczPFLcK4aACbcSYO+0tdZayxGiaJuAw5vwyxlmmKFWzInO69Onj7v++utbHLvmmmv69qY+CyywgP+dOproDk8IM1Hy92233bboWVp55ZUL20MwYYCgq5dJwNWLtK4jAiIgAiIgAsUEah2nimNyAhJwyVk1zJG1doz99tvPnXfeeSXvg6yC99xzj4sOfjkvmimxGhiIlhtuuMHttNNOhdPYZHnkyJHVFNOQxxL++OCDDxbqdscddxRtho0QM+8bnkzbG40TEEoIJoQsYojQRQR13Cbbad98mCUyLHueeeZxbDPw9ttv+7Vu2EYbbeSzTkaN+w7DPy180o5jbZ+F4LK1AFsM1Msk4OpFWtcRAREQAREQAQm4ej8DEnD1Jp7C9WoRcIgo1jTFhfJZldiA+eKLL/b/e9FFFxU2dSZU7tJLL62p5q+++qoPNfzkk0+KzscTaBtB11Rwg5zEPm6IXjNCCBFl7G0XNdaXIfDMnn/+eb+JeVtY6GGLXp9nZOzYsT4ZCYZHdvjw4S2q+dlnn7l555236N7Dg8K94HhmSZBSL5OAqxdpXUcEREAEREAEignUMk4Vw+oISMBVx6shjk7aMQiHxHNGsgkyIXbq1Kls/cONnBlsr7HGGv54PGfXXHNNTffOuXGeF9LKk14+78YG5E8++aS/DbJTIpQRrIRHhjbnnHP6TIxLLrlk4c9vvPGGW2KJJdoMQalsmjPNNJOvk23ijVfwxhtvjK3nnnvu6b2rPGd9+/YtOgbRbs/cCiusUJTlNOubloDLmrDKFwEREAEREIF4AknHqeJXOwEJuNrZtdmZSTsGA28GshjrnQhjw/g3e3TtsssuRfeASLMwx1GjRjmSV2DlBvBhAWRaHDJkiN/bjTBA1nOR7RAhgFgIE1wQfrfuuuu2GcO0Lsw2C++8844vbo455vBJO1gLNnTo0MIlWAPHGjA2zw4TeZAF0taZpVWfasohuYjt71buPJ4TQi5L2R9//BG7lpHEJWSkxBCqCNZ6mQRcvUjrOiIgAiIgAiJQTCDpOFXcaicgAVc7uzY7M2nHCD0siCU2V8ZI48/eXOZhsxsJ9x8jQyGZCrFK2wl88803bqWVVipKlc+6OTIpDhgwwJeBp2qaaabxe4lhX3/9tZttttnajGFaF5511ll90hFsqaWWcq+99prbfffd3ZVXXlm4RBg+GLYJYg/R11bG+jTbg472KRXiuPfee/uQ2moNbyQiHuNZKLWZebXlJjleAi4JJR0jAiIgAiIgAukTSDpOTf/K7adECbgctnVcx2DjZfbkIt07ogIRMcUUUxTuDk+P7UVGOBwD92WXXdaNGTOmcAybLy+yyCL+//m7hfsREmhZK+NwHX/88e6oo44q+glBQPnnn3++/zvePerN3m8kMGHvuWawUJDZhtX777+/O/fccwu3FyZsCY9n6wbLUNlWLAhvJfkIa9l69uwZWw3uhyQrtdjUU0/tfv31V5+BEi9kvUwCrl6kdR0REAEREAERKCYgAZf9EyEBlz3j1K8Q7RhkMWSNW6nNoqMVeOGFF7x3jdA/RBohcOxV9tVXX7mppprKHx6myCfToHnO4m6GdVCXXXZZ0U9zzz2369q1q7v11lv93wnJJK18sxnr+K699lp/W2T47N+/vxs0aJAbPHhw4VZtc2z+EAq4P//8s657o5VjH01IEh7LfnUnn3xyTU03yyyz+CybrKvj3/UyCbh6kdZ1REAEREAEREACrt7PgARcvYmncL2ogMOjtsMOOyQuecKECYV9xkaPHu3OOuss16tXL59t0Ix09/PPP7//X9sbrNQFwrV24TFkMXz55Zf9n9LeEDzxzWZ8IMKH5B14mBCxhAwidg4//PDClcM1hPxGBk5Eby1hiVneDmGOcZMARx99tDvmmGNqujTbEuB5Y70dnrh6WSMIOCZECFPl3wj7Dh061Ov2dR0REAEREAERaDMC8sBlj14CLnvGqV8h2jEYYB933HGJroNnDNFRyVifZRsvk8Xy6aefLnlKmHWxY8eOLbYM4ERCPM27V+naef+dsNF99923cBu77rpr0Zq4cHPvRrrXCy+80PXr169FlRCdeOFqsYUXXriw9g1Pr62Jq6Wsas5pawHHHoesHZ04caKvNoL9kksuqeYWdKwIiIAIiIAI5JKABFz2zSYBlz3j1K8Q7RjbbLONu+WWW/x1DjzwQHfGGWeUvCaJSx577LGKdSIxB2vpMMItCbssZZRpCTBY7xUNtyRZCUlL2osRUhlukYAosrWAjcyATKV9+vRpUUU8hSQyqcVI7GLZJ1nzhzeOzKRhNs5ayq10TlsKOJK3sOb0448/LlRz9dVXd0899VSlaut3ERABERABEcg9AQm47JtQAi57xqlfgY5BinaEAeurSJ5B9kOMcC3Wr7H5dlzadsL9ouvV4iqIl4i095hlVyx1I6y/s1BJEl6wJ1hozbJpd9KGvPPOO327mB100EE+eUuj2+233x6bXIYQXcJAazGykxKmi7EdAfv/bbzxxkWbn9dSbqVz6i3gXnnlFb+mlHZn24xodlFEK5ujy0RABERABESg2QlIwGXfwhJw2TNO/Qp0DJvN32qrrXyGSNYXscaGlP4YCSPYmJvU7WwfwLo3jPT2hPRVMsLdLIvlYost5t5+++2Sp5C50ganhNqdcsophWMRjISOZe1xqXQ/9fz98ccf9+sGzY488sjEIa71rGf0WqVED5uSd+/evaaqhd7ZsAD2ykPYrrjiijWVW+mkegq4L774wm+TQJgwQh1WTHqExn54eCBLbZ5e6X70uwiIgAiIgAjkhYAEXPYt1TQCjvAvwviY7X/99dfdb7/95oYPH16UmKMUzlNPPbWwxof9z0i+EbXx48f7VPl4KQgHnG+++XyYHIIlTNdv5+EhQ0DhvWDN2ZxzzukThZAMwjxbtTZvKODCMsj6+OSTT7YoloHjsGHD/EbavXv3jt10OXoSx7JeiX+TzKRchku8DTBhkMpgf6211vLFkSL/hx9+aHeD1ldffdVvoWB24oknFiU1qbXdsz6PdY48Q1FjsoAQwFpsww03LJnBFPH2/PPP11JsxXPqJeDi1g0+8sgj3isetTB5UMUb0AEFArbZfdIsu0KXPgHYM0nBNw8vukwEREAEyhGQgMv++WgaAcdHnkyHs88+u2PvKdafJBFweJYQbIgVwgbjBBwDLxJ5sDca4V9LL72094AhlsjcyHVCw3tF6v1HH33Ub2DN4JcQR8TNKqus4tegtSahRykBV+uGy6UeM9vDq1LiEzboxvuASGWNEyGT77//vg+lbMuNqrPvPvFXCDN4cgR7qBFa2uiGWCf0Fi8t/23GhIjtCVjtPZR6Vq2c8DrVll3u+HoIOAa1hEZG72Ho0KGOdalRI8Ry0UUXTfM2G6YsG+CHW2akVbn2KODiPLV82xBRhCKzzyeZXetleRNwTCLync3q/VIv7rqOCOSVgARc9i3XNALuwQcfdIT64RnDy3XsscdWFHAkG+Ah+/33312XLl0cXrw4AUdKeDLxhaFwfBiYjWQjZPY6I5TRjJBBxNROO+3kN7A243y8cqeffrpPNlKrUec333zT4RUM7bnnnnOsOUrL2LsL8Tr55JN7RqERsokIxdNpYpRQSjYDb+8GM9iZXXrppV4Y5cXw2M4wwwyF6jIZQnbRWmyvvfZy3H8py2qAVQ8Bx31xf1EjYQ3bBkQt7f5ZS3tkdY4EXLpkEXBMiFnyIPoJmYHvuusuH9FBhlO2qKiXScDVi7SuIwLNQUACLvt2bBoBF6JKKuAQUkcccYTPsEjmRsRWVMAh8uadd16fDhzvEmGCZgxsCS8kTGzEiBGFv7NhNaGceGLCgS9lkJqf8hBgtRod49NPPy0Ka8xCJISzwM8884xbddVV/YwmIpSwQLYP4N+dO3f2t0LY2MMPP1zrbTXNeTwzYbp8noUVVlghV/cXtj1hsLWG/fKcb7LJJoWtBKIQ8izgEGkXXHBBi3YN14Ey+YFHHmOSad111y06nmcFz38omHP1oPy3shJw6bYa/Y8wbEsOZaWTIIcIEL49rDvGA1wPk4CrB2VdQwSah4AEXPZt2W4FHOFMhE6SSIE91AhLiRNwb731llt88cV9YgJCIKPGb3xMba0Xa98Y7CJqCLmMGuXcd999fja11vBCOgYDP8I32SiZTbyzSBISDuIJo/zkk098eCTeSDMyWpp3iX+X87Zk/zg3zhXCxC5//vlnJu2T5d0SKsykBPdBX2lN8o1x48Y5tpKIMzy4cWtIa703JknwWjDwtcysYVn0VwbGF198cZGXtJbr4WHHA1/OmNRgTRzGOtQtttiicDhebYQ9XmvCsDfaaKNaqtEQ51Qr4PBSs/aY6AXOZb0s4eZEToTrR7k5C6FkbSnREHieSNJEohjeReutt14RAwuf413MHplDhgxxPINkyz3rrLMcE2y8yw4++GD3wAMP+Iy+hLyznpH3aWiEE7PumSyjJKtBaLNOlGiKaAIe1oaRIOqqq67y73buhTpzztZbb+0jL8IJwHINV0rAcQ7RHjxLo0aN8vdixjN00003+XWlTDYSAs/zddhhh7VgRHg/zyZ8eO6YyMRDTF+k7xP2TcimWSkBh7eesFnKYzLDPIbUn0RObKnC9eFMgi1C67FS6+lKXceeASZb+Wbfc889PikQbcqEYrjmtNS7intlctcMLz3vAd4VRJQw2co2OLQt7Ue4M88pk6XRdxTvdKJ9+O6ydCOL729DdGxVQgRqJCABVyO4Kk5rlwIO8cNggUEAHjfWEpQScGR43HTTTf3GzOeee24LtPzGMbzk+fizXogZUv5OOvmoUQ4hVq1JDFGvjhH9EDIwiWawJITMNihuzYbPVTyzuTiUTJQmbsnEmDdjAMhaLiYcCE1ujYVhttFy8CjMOOOMrSm+6FzEpnmEyxWahlcUMcbgvpTRf8ItNBjgE3bN4JvkRgwSEQ1mWXkjU4NbpqBqBBwDefoE3lk8kkyk8TeEGe9mBvth0hwG7zxDDJiZKEOwsU8lDGFMWy6zzDKF2pmA69mzp78GAoVwc8QNQpF3LyKF6AkEEOKMTL1xe2Syvpf6IRbJ8stgnTanrRAtRCWYmYBD0DBJx78RBeyLyXeBzKvUIYlV8sAhSAmlDEO1WQZAODv7dhLpQR+mrjBjn1DCLs1MwNG/mWBAwNLPYfPss8/6+yKpkX0D4oQVdeB8BBATGdyfGefBjG8sdbHvLWKLtqxFwHEeYaV4tGk/nhmeASZCEHSILwyRRlvQVog2M54LS7DFFjz0PcpjIhSOZGymre644w5/3EknneSFbXSJBOXZuGDQoEHu+OOPT9KkOkYE2hWBeo1T2xXUyM22SwF35pln+tlXPlb2AS4l4Ji9JXNjqb3M+I1j8LYxu2+Z/Pg7a+qiRjmEHSZJzW4dIFoGs7oMWOIyTqb5MEcFHAMnwsBCY5bS1r0hWBGuMhGIEig1K45Xg0FUmsZADhFQyqKD02quTbIeJi3IuhqGTceVgTghzHjgwIH+ZyaAGBgiCBAqUWsvAm777bd3eD8YGIeigv0r8Rh16tTJCx4zS1DFsQgg84YQMcF7e8899yxMInGOCTg8QLQRIgwjTB7vDRMGtCEeQDPEHuvL8F6FnjU8RoiN0BCFCD8SUoXvQxNw1I8JHPu28MzgKSJhFtEahNBXsrg1cOzxyTsWQYa3q0+fPkXFxNWVSA+Y4o2Dr5kJOP4/FCg8l4g5QuH5lpG8C4sKODyY9DNEEhMSLCMIzfo7nC+66KIiD365cMxyHjiuRd34dhKajNFe1JFnhpBS84SVS2Ji+12yXpz2CyeQ8OrhXUPQ8W6iXO4TgRgazyLlwLReYayVnhn9LgKNREACLvvWaHcCDrFBiA4ffcJEzEoJuBtuuMHtuOOOrtRMW1TAIQp5cDknLrwqTwKOGeQ4L2LcY8kHmxnZWWaZJfunVlfIHYFSAo5Bp4VH2U3RRxmcMjAiBMsGa0lv2vpgqePxjkQHnEnLLpUcJXo+A0lC83gHsBcixjYihKQysx9n7UHA4TVBsLMuEk9H1BBYCC0mqYhkwEzAMbjHa2aGJwZxxmQWoXVmNnhHROH5MUN0MCAnxB1hE4YzMtnGM5d0n0wE38iRI72YsmyQJuD4lhCtEBrhlHiGkk5ylQtZRgAT9s+zlMT2228/d9555/nwRetrJuBgZSG+VpYJYyYciBjBQmHFNwwhhfccYRO3xQj1xxuIl3DWWWctqmZrBJytxQ4LJOMrHkayTlq0QzkBh0eWtosrK8oTLzvCHvFowpvJG/6b77zWfCd5AnVMeyQgAZd9q7c7AceLnZcxM7yE05gphLLlw8ZsMWFLSQyvAuGoMhGIIxAOSBnQWQZV81yH54Rry8JBZDVkS3nhWuN94/rsBZkkZArvG7P7DCzDLQUY+JbyDrYHAYdHjPA33sPhZvfWtnhU8LDAjXVjGKKDtUjRrLv8RogiQgHvi5kN3qPhuXhWmAzAG/biiy8WPU60FW1DiB8CxYyQXCImEAeIEcL4QuNvrA/GTMCxfQqiKbTLL7/crxVmQiLqOSvVX6JJTBAOCAbLcMoauND7Q8gkdUWc8O7G8xda6FEzATdgwABHREpoxgKRyHowzEQXXkeEIBMUhBuayI7eA/2dkM64ZF21CjhYc0/R9Wa8I9imJXxXlBNwrMelHXmmKhnPIl70wYMH+3BKzDy5iH4mcGUiIAItCUjAZf9UtDsBN/PMM/uZw0rGrCQfgUZNYkL9sw6h5BosSrc1buWYHXDAAT5BgEwESg1I7e8MOllvguE5Yc1OaKHYI/yLNU7VWikvXC3eNwa+eM8QC2SWJbSqktng18K1Kh3P7+1BwFlEQyUetl6Q48rtAxf3W7nBuyXXQMCEFib1sEQXhDwSKkmWUMLHl1hiCe+9Q0BYYpPQqxUmMWFCMLRyv5XqL3FZKDn2iiuu8F5d/mGdLUb0A8cjchg4IVIJA6Su3BsC1L5pHB93v1aPuN9MdBFhwfpDJijwvpXazxTOcWsKuUatAo5EI4jUqJlXPBTf5Z4BQlwXXnhh/22vZISU8oxxn7ZUgLV9rHmHtYXnVipHv4tAeyMgAZd9i7c7AcfMKJnqoka4DS/o/2PvTMCtnNr/v14yZAyZMxeVkDQol4iUWaWISoYylaJISqmkEELmKZUQIryiQSghhd5EUUkZKqGQeE2///VZ/9/av+c8Z8/7Wfvsfc73vi6Xzt7rWWs9n7XX3ut+7gmXCSwExMiRDIEvcJKT4A7FwS34he3KCPC0n4Ohk1RlBOgvnR+PRMufz42B6yhPH1NJOkXTU/Wh98svgaBSFoyl5CEEWf2CQjIFd1iKV4MwXUphK1y21jcS93AATyZ8/oMZJp07V7pJVei7IihwuKPhfpgopjge47JS4C6//HIbv0WMM26LQXHZhMtCgXOJsoIKHvF8lK/AAkemzqBcdtllNttiFAocSXhwQ0VZwjJF/Fu8guKJFGXmxUMQXGHjxYnjOst9MU5wz/EZiMoCR3ZNlMF0LHDM15UlQrFFkSPmDqbBBETpfiepnQhUFAL5PKdWFKbh+6xwClyihU7kQkn7eIW8ed25egXdfXg9VSHvESNG2GD6bCWfGwN3IKxrQeFgE/7x4glwONYh2/vTdeWPAIfHPn36WLc43N2c5QB3wnAaeKwHwfpXLsNrplTCVrhsrG+M6RJcJBsf5QsXPNzPyFZIvBWJI5B0SzBUBAWOh2A8wDruuONKJURKxLesFDgXKxWug4gbHwoISUXKQoGbNWuWtW7hvojCgzhPCUpnYCFywmeK/USmzagUOBQr3AmJ5WRvkAQlnGY/mQKH4oR1MF7dUBd/F0+BI/Qh3Rg4LIS4mxInGazJCRdXIiWdGDincJLIhrh2FDi+u6LIYpvp95nai0AxEcjnObWYuEQ513KjwBFj4FwKOfzxg8UPhIvhwt0kUVZHgCZT4PjB4ek9/vw8deSHk7H4jxTEPH0PCj8aHEp5Ck8QPRYGfmjxp8c6h7UvketJOoubz43hsmoG50UMkIuNcIcHnlRLRCAdAi5ehbbxkjqwZ7FuO8HtjlqHiQSLBLFFxJqFa3M5K1y21jfG5Hsk7HKHGyiuYFjoOegT24VbKN9DHGqD6eXdA6BUbCqCAgcDl3SCh0BYMoICTxSUYHxcWSlwJLrisM7auhp9rBFZRV0CrHwrcPAhXT9KEw/SXCF5LG9YNfkedrXY4Ipbu8uCGqUCR99Y/LD88RvIQ8xgsqFkChzXYmVn/+CJ4uL4iPHjtxLreyIFLt0slLg8uxqDwcQ3jO2swGShpHwEdfqc4C7L73ewPAPvofTxe849osyFC6yn2tt6XwQqGoF8nlMrGlt3v+VGgXMKWKKFJCtYOC4h2DaZAkc7AuhRWoh9IJMabiRcg1UhngsJbpq4mVCnBtcPMq/xo4I7RvAHI5sPXj43BoH/1KsKJhDApTIY6F/MB89s+Oua3AhQ2PeWW26xnZAWPlg/itdILhR0cw7G+sQbmRg6EujwUOSTTz6x8S1OUO5wm+agGVbu0r0LDnrhODwytHKA5TDI/JKlEsfizveEEyx0ZPcLFhXmvWLeRy6uie9FrGvxBGUaRRxrPUox1iLWjsQYrDmudVhFsGwFE3CUlQJHohPmxvc7n1EO9SiXKG1kvkSp96nA8ZsRVMb43WFMPuNkQaTwtis8zgMPLG/sGwp9E6/JZ5aabjxMJF4tagWONXZZQxmTveyUuFQKHIomCii/Lfwu4tLIXkKBwy0zngJH4hFqyqFg4cKaqA4c8+LhALXe2LtknOW7Aauly1Lp6rHSn6sDh4UPZZ3feFcvzn2OeUjrSl7ES1KT7neJ2olARSGQz3NqRWEavs9yo8BVpAXM98Yg/iNYgJa4OJRTJ8V88KxIn5tCudegVQBFLqjccJBzroduvli9KZwbT8Ltc3VPjjcG2fRIaBEUDq6MlY5gxcGa44QsdtSM5Kl+UIp5HzkFLhkPLK/OcoWlg4MwlhviBDnwk80RJZsDfbA+XFkpcNwLFhoe3KFsoshxsL/55pttXDDufj4VuDBLlBCsSSgvuDCi/ASFhxjsJRQ3LHVYgfmeRnmjjIEPBY7xsfCxp7GsEi+Iy2IqBY7rWH8yR7psx2TX5MEID0PiKXBcQ9Ij9h7fB9Rswz2UteCBQFAo7s2DomeeecYmPuFBJEW9gw9NmCuKHt468ELp5SED6x1mi9JI9koeLMQrjZDO94DaiEBFIpDvc2pFYuvuVQpcEa56vjcG7mn8oDrBVYwaRPzohV12ihCnppxnAsSicQhFwgc1rC/hwt5YEBKl3sfdCncsJ/HSomdyeyQrwsUZyxDJDhCsHRzagoK1gFpm6QiHyKCVkTHWr18fSz/v+ihmBS4dDmojAtkSSKbEZ9tnJte5ZETs4+DDzEz6UFsRqEgE8n1OrUhspcAV8Wrne2NQ9BZXE4Qnk/yNaw5PTsm8l2mh5SJGr6lHQABXJXcgw0qA25yTpUuXmho1apQYhThSlKp4Qs0rF5/E+9kcsHg6jyUIlzTiZlx2WQ5tWF222247W7DZCcodn/9w4oZEaHD1QslEaUOZc/XNXCwO11FUGquURAREoDSBslbg4mXy1DqJgAgkJpDvc2pFXAtZ4Ipw1ctiY1DsFZchEpiQpEEiAtkSCLo94kpIMW8nxB1R+y0oxLGgXOEyRVId4licmyUueVjdnCSqPZVsri5eJtwGdy1ctHAJwzqG+xqZ7XC1ihf3mmwMYkhR0IgRC4pL2EK9LhRJiQiIQGEocNSLHTVqlHWTJfMm8XmJHiRpzURABEoSKItzakVbAylwRbji2hhFuGiacowAyhAKC0JGN1fUm79dEeEgLhJGEKdCZkIOUFiwsJghnTp1Mk888USsOa69roZcushdv+H2HNqwMLuMdCSJIBYqSgnWvCNuR9bsKOmqr/JCoCwscC6uE+s4XgDEsoYfwJQXvroPEYiagM6pURMt3Z8UOP+MIx9BGyNypOowzwQqV65sEwKQuCIYX0aCj3CNxIMOOiiWRMJN08WL1a5d25b3cOJcfDO5HRTCiRMnlrqEedCfS7LSpEkTQ225KIWSJGTKRObMmWPLjEhEQAREQAREoJgJ6Jzqf/WkwPlnHPkI2hiRI1WHeSawww472Jgw/u9KVAQtc8Hp8PQdF8pgZjji6MgoR3mQoFCig7qNmQgFeqk1h1BuIJgVEwucq/OYqpxBJmO6tmRdxFXTSd26dW3SFLhQqoMMmBIREAEREAERKCYCOqf6Xy0pcP4ZRz6CNkbkSNVhnglgeVu9erXBEudqvvE3r4eFBDoU0cUS54TkJyQSCQuJRagXlYm4or9cg7KG0hZPcN/ElSpKIcMmqerjSbLyCVHOQX2JgAiIgAiIQJQEdE6Nkmb8vqTA+Wcc+QjaGJEjVYd5JkDsG6zhWBAAACAASURBVDEm1IsieQf/jxf/xrSwRlFgF6UtHaFmE4lHUgllMIjFIykPGSERammRuCSeYCkjA2WUQkkFijVjUQwLlrivv/46yuEi6QtL6QknnFAieyi8qYt3ySWXRDKGOhEBERABESheAjqn+l87KXD+GUc+gjZG5EjVYZ4JkH1y8eLFdlRi4e655x5DgXj+HRaSCJDeP1z4OtGUyVa59dZbJ70jxsNVErdIygVQjgChYHfQ0hfshPkmei9XfOFYPtcf1kmslIUk8MVVNSytWrWKuZsW0nw1FxEQAREQgfwS0DnVP28pcP4ZRz6CNkbkSNVhnglg5Zo/f74dlcK47du3LzEDLHSUGyDBCdYdisl36NAh4SzJDkf9NmTt2rWmatWqCdtS043abk6IQ5s3b579E6sgSU3c38FOVq5c6S0LHdZFkpiE5ZNPPjEod4UkUuAKaTU0FxEQAREoPAI6p/pfEylw/hlHPoI2RuRI1WGeCTRu3DgWw0Yaf2LcgrJgwQLTpk0bQ2FvZOTIkSXqvYWnS2zarFmz7MupFC2KaVPw28lOO+1kfvjhB/snCuOqVatK1aLjPdrsuOOOXki1aNHCTJs2rVTfuFi2bNnSy5jZdioFLltyuk4EREAEKgYBnVP9r7MUOP+MIx9BGyNypOowzwSaNWtmY94Q6ryhsDkhLo2i11jGsEAh3bt3t26WiQQFaOrUqfZtXCJr1KiRsG23bt0MxbvjCUra999/H9dV8rfffosVEI8aV6JSBvfff7+NkSskkQJXSKuhuYiACIhA4RHQOdX/mkiB88848hG0MSJHqg7zTOCkk04yWJeQoPsjfx9wwAHW8nbEEUeYDz/80LYhW+P06dPtvx988EEzadIkm9jEyRlnnGFefPFF+ydFv1EKEwkFuZ1iGG6DckJ5g2rVqpV4C6WS5CgkW/EhF154YamSCG4csmqSXbNQRApcoayE5iECIiAChUlA51T/6yIFzj/jyEfQxogcqTrMMwFS9aOEIdtss41BKXDi0udTOPvdd9+1LweVvG+++casWbMmlhHyrLPOsorVhAkTbFvKCzRq1CjuHWFd23nnnRPe7Z9//mmtf1WqVCnRJpv6cpkgvfLKK81dd90V95J33nnH4HJaKCIFrlBWQvMQAREQgcIkoHOq/3WRAuefceQjaGNEjlQd5pnAOeecY5OXxJPevXub2267zRx33HHmjTfeKNFkyy23tAoWFrFRo0ZZS9rgwYNN3759zeOPP27b4ppJXF08oc4bsXXxxJU0oKxB2OK166672rp1voT0+w899FDc7okPbNq0qa+hM+5XClzGyHSBCIiACFQoAjqn+l9uKXD+GUc+gjZG5EjVYZ4JXHDBBTGFKzz0ww8/bNP7Y4mbPHlyibextjlLW/CNyy67zDzwwAP2JRKaUHoAJRB3yaAks3ShHBLnhvBvsmA62X///c2yZcu8UTr//PPNmDFj4vb/yiuvpF1CwdsEAx1LgcsHZY0hAiIgAsVLQOdU/2snBc4/48hH0MaIHKk6zDOBoMIVHvrtt982Rx11lLn44osNylxQKLRdt27dUrPt1auXzVQZFKxwLlEKr4ezT4Y72X777W38G0IZApeZkr8pe+Di8Xygev/9963bJ1ZALG7Dhw+PxfhhqQxmzfQxfiZ9SoHLhJbaioAIiEDFI6Bzqv81lwLnn3HkI2hjRI5UHeaZwNChQ82AAQPijurquPXr188qMk4aNmwYt1Ya71ME/KabbirV3//8z//Y11DGgrXhcJEk3i0oxMZ999139qXTTz/dvPzyy7G3sZCNHj3aK6WPP/7YMF8SsHAv3BPiLJJeB8+gcylwGcBSUxEQARGogAR0TvW/6FLg/DOOfARtjMiRqsM8E3j22WcN7pBhIT5t4sSJ9uX+/fubYcOGxZosWbLEVK9ePe5MSXZCaYKg2yMNnQJHYe4GDRrErj355JOthcu9zxtknnTFwKklt88++8Ta33vvvebyyy/PG6W7777b9OzZ0453xx13JK2Bl7dJ/e9AUuDyTVzjiYAIiEBxEdA51f96SYHzzzjyEbQxIkeqDvNMAGtTONV/5cqVbYISl6rfuRUytU6dOpmxY8cmneW6devMueeeGytPQH8bN26018yfP9+6QTrp0KGDmTJliq355sSVL3B/z5kzx5BshYyUuGJut912eaOEtY/SAkiPHj0M1scTTjjB7LLLLnmbQ6KBpMCV+RJoAiIgAiJQ0AR0TvW/PFLg/DOOfARtjMiRqsM8E8B9kcyOKF1OateuXao+G3FtZJq88cYbze67755ylkFXyd12280cfPDBtkTBkCFDTMuWLWPXd+3a1cydO9cqdk5ou3DhwhJjYKHzVfst2c3Es1BiQUSpLWuRAlfWK6DxRUAERKCwCeic6n99pMD5Zxz5CNoYkSNVh2VA4KKLLjKPPfZYbORkMW6ZTC+cQZJrsVy5+Db+Jhvl8uXLY8W/eY3EKvfdd18mQ3lrS5Fzip2H5Z9//ikThTI4Dylw3pZdHYuACIhAuSCgc6r/ZZQC559x5CNoY0SOVB2WAYGpU6eWsIoRwzZjxoycZ7LTTjuZH3/8MWk/JEhZunSpzUzpBIVu3333zXn8KDog22a9evVKdfXHH3+UqlEXxXiZ9CEFLhNaaisCIiACFY+Azqn+11wKnH/GkY+gjRE5UnVYBgT++uuvEspIVKn6995771gykkS3hUsmMW0uUUiLFi1sTFyhCK6bFPcOl1H46aef8hqLF4+HFLhC+ZRoHiIgAiJQmAR0TvW/LlLg/DOOfARtjMiRqsMyIoDSFoxDC2aFzHZKNWvWNJ999lnSy2+55RZDMfHWrVubTTfd1BBzVggJQsKTXrRokSE20MmaNWvKfJ5S4LL9ZOo6ERABEagYBHRO9b/OUuD8M458BG2MyJGqwzIiQCp/Uvojffv2LVH3LdspHXHEESmLbt96663mmmuuyXaIvF5Xo0YN6+6JrFixwmBhjEKwgNLf/vvvn1FcnRS4KOirDxEQAREovwR0TvW/tlLg/DOOfARtjMiRqsMyJHD//ffbTJMDBw6MxLrUtGlTM2vWrKR3VEwK3Iknnhhz78SyeOCBB0ayWmeeeaZ5/vnnTZcuXUq5aiYbQApcJPjViQiIgAiUWwI6p/pfWilw/hlHPoI2RuRI1WE5IuCKdCe7pWJS4Fq1ahXLlom76WGHHZbzan3wwQemfv36sX7iua5inZs2bZp1MyUxjBMpcDnjVwciIAIiUK4J6Jzqf3mlwPlnHPkI2hiRI1WH5YhAuDxBvFsbMWKEufrqq4virikm/vTTT9u5vvfee6ZRo0Y5zxur26OPPhrrhzp5F198sa3Nh6DQEXu3ePFi06ZNGzNx4kQpcDlTVwciIAIiUDEI6Jzqf52lwPlnHPkI2hiRI1WH5YjAoEGDzODBg5PeEdkdUWKKQUi28vjjj9upvvnmm+aYY47JadoUT99zzz3Nb7/9VqKfdu3axcoqkO2ySpUqsfeDFjpZ4HLCr4tFQAREoNwT0DnV/xJLgfPPOPIRtDEiR6oOyxEBLEuplLPff//dbLHFFkVx1xQYf+CBB+xcKfDdsmXLnOb93HPPGZS1eEJik3nz5pltt93WHHzwwVLgciKti0VABESgYhLQOdX/ukuB88848hG0MSJHqg7LEYFwgfDwrQ0fPtxmvCwWueqqq8ydd95ppztp0iRzxhln5DT1e+65x1xxxRVx+yDejjE22WQT888//8TaYK3bcsst7d+ywOWEXxeLgAiIQLknoHOq/yWWAuefceQjaGNEjlQdliMCX331VdJU+ygw3bp1K5o7vu6668zNN99s5/vUU0+Z9u3bZz3377//3uy8884ZX//tt9+a3Xff3XzxxRc2Dq9Dhw6l+mjYsKEZMGCAOe6448xWW22V8Ri6QAREQAREoHwQ0DnV/zpKgfPPOPIRtDEiR6oOyxEB4rXImkisVzx56KGHTNeuXYvmjkkwcsMNN9j5Mu+99trL/n+33XZL+x4++ugjU7VqVXPjjTdmVDLADbBw4ULrUlm9enWzbNmypOMSf0hJCIkIiIAIiEDFJKBzqv91lwLnn3HkI2hjRI5UHZYzAliB3njjjbh3RUKQzp07F80dU/Lg2muvLTFfMlM++eSTCe/hm2++MWPGjDEnnXSS+fLLL20myc0339z88ccfWd33zJkzzdFHH206duxoxo8fn7SPKOL0spqkLhIBERABESgIAjqn+l8GKXD+GUc+gjZG5EjVYTkj0KtXLzNy5Mi4d4XigwJULHLvvfea7t27l5puvNptrtGxxx5r3nrrLev2uGrVqoS32rhxY7Ny5UqDwpdMWrRoYV566SWzfPlya4kLxscFr6O/2bNnm3/961/FglfzFAEREAERiJiAzqkRA43TnRQ4/4wjH0EbI3Kk6rCcERg7dmxCK9szzzyTMAtjIWKYM2eOOfLII9NW4H799VezzTbbpHUrFOpu3ry5OfDAA82SJUuSXnPmmWeaZ5991nTq1CmhFW7KlCkGZU8iAiIgAiJQcQnonOp/7aXA+Wcc+QjaGJEjVYfljMCCBQvMYYcdFveuHnvsMUNttWIRUvtjSSMBiRMsXBs3bjSvv/66Ve6I+XOC5Q0LXDqCtaxJkyambdu2JYp1J7oWK1yNGjXiWuFkfUuHuNqIgAiIQPknoHOq/zWWAuefceQjaGNEjlQdljMCxHoF67zdddddpmfPnqZSpUo2JoxC1sUk06dPN9S3e/rpp+20uTfi0XgNl8aPP/445rZIpspzzz03rdubP3++VXSvvPJKA6N4QhkD5456/vnnm9GjR8eNhZP1LS3kaiQCIiAC5Z4AvyvUE3377bfL/b2W1Q1KgSsr8jmMKwUuB3i6tMIQqFevniH7YrVq1cyKFSvMrFmzbObGgw46qGgZMPfPP/+81PyxzjkrXLI6b+EL6QuL2ogRI0yfPn3icvnggw/MEUccYd9r3bq1uf/++82PP/5o6tSpE4uFk/WtaD9SmrgIiIAIRE5gn332sRmTpcBFjjbWoRQ4f2y99SwFzhtadVyOCKC0kYnxtNNOM4cffni5uLMGDRqYefPmlbqXr7/+OmZVDJYdSHXTJC/ZY489zAMPPGAuu+yyuM0XLVpkatWqVeK98847z/z999+xWDhZ31KR1vsiIAIiUHEIbL/99uaQQw6RAudxyaXAeYTrq2spcL7Iql8RKGwCxx9/vJkxY0apSX722Wc2EQmCq+jdd9+d1o2sXbvW1oebNGmSta6Fhddwn9x3331LvYdih2LcqFEjW7JBmSfTQq5GIiACIlCuCZBIC/dJ4qtlgfO31FLg/LH11rMUOG9o1bEIFDQBMkaSuCQsH374oalbt65NRNKuXbu07qF+/frm/ffft4oXiVKOOeYYG0uHNQ4rHha2N99808YNxisaTpzhmjVrTJUqVdLOepnWxNRIBERABESgaAk8/PDD5uKLLzZHHXWUFDiPqygFziNcX11LgfNFVv2KQGET6NKli01cEhbi+3CtJOFIukIWy8qVK8eaU1fuzz//tAW/XY05lLuffvrJKmlh+fnnn+1TVokIiIAIiEDFJTBq1ChDeR7qq06ePNm88sorFoYUOL+fCSlwfvl66V0KnBes6lQECp7A3LlzTcOGDUvN87XXXjOPPPKIee6559K6B0oPvPvuu2m1DWf0dBc598vff//d/mBj0SNwXSICIiACIlAxCCxbtsxUr1497s1KgfP7GZAC55evl96lwHnBqk5FoCgILFy40AaHB4Xi2itXrjTUgEtHmjVrFjeWLt61WOM23XTTmFXOtcFtkxi43r17mzvuuMMmQ/niiy9KlG9IZy5qIwIiIAIiUJwEiLcm7jqeSIHzu6ZS4Pzy9dK7FDgvWNWpCBQNAVwacW0MCpkiSSyCdO/e3VBOIJFQjmDx4sVp3+/WW29tC4eHZeDAgTZezgn16ki0IhEBERABESj/BDp06GCefPJJe6O43FNTlHhsfheInVYSE3+fASlw/th661kKnDe06lgEioIAyUfI/hgUYtdwd9xqq60M1rGaNWsmvRcX55bODVNjjtpvqeSFF14wrVq1StVM74uACIiACJQDAnhhzJ8/397Jt99+a3bffXf7b51T/S+uFDj/jCMfQRsjcqTqUASKjsChhx5qs0aGhTi0L7/80lx//fXmpptuir19wAEHGOIVEJKd4PaYruAeuWrVqpTNx40bZzp27JiynRqIgAiIgAgUNwFinyk1Q/IrvEJ4yOfKyeic6n9tpcD5Zxz5CNoYkSNVhyJQdAS6detm7rvvvlLzPuKII2xGSp6KBguYE6dQp04d+zrKXbzSAIkgbLHFFta6l0qYT6KC4Kmu1fsiIAIiIAKFT+C3334zZER2rpPM+NxzzzXjx4+PTV7nVP/rKAXOP+PIR9DGiBypOhSBoiOwfPlys//++5eat0tQwo8s7pRO+vXrV8Iil8kNp1uk+5ZbbjF9+vTJpGu1FQEREAERKAICxLNdeOGFZsmSJSVme/TRRxvc53G1d6Jzqv8FlQLnn3HkI2hjRI5UHYpAURLo0aOHoQZPUE499VTz8ssv25eCilf//v3N0KFDs7rPdBW4a6+91tx8881ZjaGLREAEREAECpfASSedZChZExZKyeClERSdU/2voxQ4/4wjH0EbI3Kk6lAEipLA1KlTTcuWLUvM/ayzzjITJkwopcB17tzZPP7441ndZ7oKHG41Dz/8cFZj6CIREAEREIHCJZAoFjpeQiydU/2voxQ4/4wjH0EbI3Kk6lAEipIAwePEsgUzRF5wwQXmscces/dDgVWXuKRXr17m9ttvz+o+R4wYkZZrJAHtzz//fFZj6CIREAEREIHCJLBu3Tqz4447lpocdUBvu+22Uq/rnOp/HaXA+Wcc+QjaGJEjVYciULQEsHo9+uijsfmT3MTVgFuwYIEtN0AdNzJWuhTP2dzsZ599ZhXDW2+9NeHlTZs2TbuYeDZz0DUiIAIiIAL5JzB58mRzyimn2IHPOOMMs+2229papKNHjy4R++ZmpnOq/zWSAuefceQjaGNEjlQdikDREgi7UZJEhGQiTjZs2GA22WSTEglNsr1ZMkw+8MADCS+vXbu2+eSTT7LtXteJgAiIgAh4IrB48WLz+uuv21qde+65Z0ajUHrmzjvvtNekk21Y59SM8GbVWApcVtjK9iJtjLLlr9FFoJAI4EZJEW8ngwYNMjfccIOXKbZo0cJMmzYtYd+77rqrWb16tZex1akIiIAIiEB2BCgDs99++9li29tvv72NVW7Xrl3KzkhMRaIssho7IQsl7vnJROfUlGhzbiAFLmeE+e9AGyP/zDWiCBQygWCSEZ+p/EeOHGmIpUsklSpVsvXi0k16UshMNTcREAERKC8EZs2aZXBxd8J3NPHRKHWJZOnSpaZGjRol3t53333NF198kfI7XudU/58cKXD+GUc+gjZG5EjVoQgUNYGgwjR48GAzcOBAL/eDOyZ1gKj589dff8Udg7iI7bbbzsv46lQERKB8EaCe5ZZbbplTfG75IuLnbijvct1115XovGHDhmbOnDkJB8TyRqmaoJDQ6uqrr045SZ1TUyLKuYEUuJwR5r8DbYz8M9eIIlDIBIIKHD+u/Mj6lJkzZ5pjjjkm7hA8nU32VNfnvNS3CIhA8RAgHqt58+Y2IQaxvEceeWTxTL7IZkq2yDvuuKPUrEluVadOnbh3069fPzN8+HD73jnnnGO9L+rXr5/WneucmhamnBqVGwXuiSeeMJiI582bZxYuXGjdeHhKTLBmUH744Qfz3HPP2UK3BNs7f+DGjRvbNNlHHXVUXKBfffWV4cM8ZcoU88svv1iz8qWXXmoI6o/nLkRab56CT5o0yaxdu9bsvffehjpM+BNvttlmOS2aNkZO+HSxCJQ7AsHvIJ6Y3nXXXV7vkeyWhx12WNwxOAzwHUXAe7i4q9dJqXMREIGCJ8DZDCv9zjvvbCh5EqxNKeu9v+Xr2rWreeSRR0oNgFv8lVdeGXfgiy++OFbXk7MvMdDpis6p6ZLKvl25UeDwy12xYoX9UsAcj8IVT4EjgxpKV7Vq1czxxx9vzfb4AdP277//NmPHjjUdO3YsQZS+SMW9Zs0a07ZtW8NYfJj/85//mJ49e8Yy87iLfv75Z4NC+Omnn5qTTz7ZHHLIIWb27Nnm7bfftgolY+Ui2hi50NO1IlD+CHAI4jCEIkfcwv777+/1JleuXGn22WefpGNMnDjRtGnTxus81LkIiEDxEJg/f7454YQTzPr16+1D9AEDBtiH7k7CGXSL584Kf6Znn322eeaZZ0pN9Pzzz7elAOIJdT0xQiAffvihOfzww9O+UZ1T00aVdcNyo8BNnz7dHHjggdbSRRY24kDiKXAzZsyw2XROOukkm1rbyTvvvGOOPfZYm2qbLGoogU4wHT/99NO21hLxHwiZ31q2bGneeOMNM3fu3BJmZfyM8Tfmy2nIkCG2PZXqscCNGzfOWgDPPPPMrBdNGyNrdLpQBMolAR4+UaeHot4NGjTwfo94IaSKc7vkkkuSlhzwPkkNIAIiUFAEDj74YPtgG2nWrJk9P4Xlu+++sw/iJdES4Mz72muv2U433XRTa7BATjzxRPPqq6/GHezoo4+2hgeEh3Z77bVX2pPSOTVtVFk3LDcKXJBAMgUuGSkUMvywgwqZM/Vjdfv8889LXM4Hmw84rpT333+/fe+ff/6x9TU2btxoVq1aVaL2EpY8nlozTqINk85KamOkQ0ltREAEfBHggVTwAVi8cdINdvc1R/UrAiJQWATSyU6LdxReUcHSKIV1F8U5G8KDMFQguMAfeuih9t/16tUzH3zwQdybqlmzpvnss8/sexg+goaNVBR0Tk1FKPf3pcAFGJ566qnmlVdeMR999JGpW7eufYcnFjy5wO2S4oVB4QkG9TSw+rmnShRKrFWrlr2GJ+Jh4T0UOZ5gp/NlFm+JtTFy/+CrBxEQgdwIpPr+wvsALwSJCIiACEAg1XeGo0Qc7b333lsi7b0I5kaAUB7yQyAYJnbccUdrhUNh5kwaT3bZZRebwwHPtF9//TWjCeicmhGurBpLgftfbN98841NTIJC9vXXX1sTM3LPPfeYK664wtx+++1x6x+xKXhCQWAu8u9//9ucdtpp9pq777671KLwHm0Yb4899shq0bQxssKmi0RABCIkkOowhiv5sGHDIhxRXYmACBQrAc5ImSQ1Ij8B56RU3zPFyiPf88b7CzdIeKK44SmGlxhCcj++r7GwYawgKyjvV65c2fz+++/WNd+1TXfeOqemSyr7dlLgjLH1jPADJqUtwZwEdTrhANK/f3+biadLly6lSDuzNC6TfNiffPJJ06FDB3vN0KFDS7XnPdpgscMal0zcBgi3ceZv55uc/fLrShEQARHIjkCqgxWZzchwJhEBERCBRYsWmdq1a5cCcdFFF9nkGnglhSVTtz1RTkxghx12sMljiF3GAoeXGYn4EgkeZ5dffrl9u3r16mbJkiUZ4ZUClxGurBpXeAWOWA7Sq5KghCxujz32WAmQN910k7n++utt+lW+aMISVuDGjx9vs1hyzY033igFLquPpS4SAREodAKpFDglMSn0FdT8RCA/BHgwTsbueEoadcZuu+02awUKy/fff2922mmn/EyyHI+CGyTukAg1OqnVedVVV5XKoJ4IAdknyUKZiUiBy4RWdm0rvAKHqyNukmeddZa1jDnXSYdTLpTZfbB0lQiIQPkmkEqBO++888yYMWPKNwTdnQiIQFICKG0oYWTuDgsue1jmiHmLF2NFaShyDEhyI+A8w+iFbOiUncGNknPv888/n7JzkvXNnDkzZbtgAylwGeHKqnGFVuDcEwhqXWDCr1SpUimISmKS1edKF4mACJRzAtS0fPHFFxPeZbt27eLWHSrnWHR7IiAC/0uA2rmEiqxbt86+gqL27bffmh9//NH+PWrUKNO9e/eEcW6ffPJJXLdLAc6MQL9+/QyWTgQvM7zNEJSyY445JmVn1DMmwV8mIgUuE1rZta2wCtw111xjzfZknuQJxGabbRaXYDplBIKuQpQRIDkJvtvUkyMuzokrI0A1e1ePI5tl08bIhpquEQERiJIABzEC3RMJ360U65WIgAhUTALkFpgyZUrs5vv27WvT1hMfywMgPJyw5Cey5r///vt5qWtZXlYHqxo5HUgWg8sjCtrxxx9v8zG4It6zZs0y7gxJPoXDDjss5e1jqZswYULKdsEGOqdmhCurxhVSgXNPI/hyocp8qsxIiQp5cz2FwcNfMvEKebM6uBRRyPvZZ581bdu2zWrBuEgbI2t0ulAERCBCAsncKDk4TJ8+PcLR1JUIiECxEJg3b14p5SucJM7dS6LvEQp9H3vsscVyy2U6T0pYcTaEJf/nbBtPePBGhk+ErJRkp0wlyYp9J7pW59RUVHN/v9wocCQZcVkZ58+fb7PrNGvWLOY/TQZJPlB8gVx44YVWaeMpULzChDwZcnXgQIzlrGHDhua7776zihdBoFjQGIPA3DvvvLPESvz888/myCOPtL7dp5xyiqHUAHPjP/p+4YUXclo5bYyc8OliERCBiAgED16USAla3Jo0aWJmz54d0UjqRgREoFgIkByO89dbb71VYspLly41BxxwQKnboM4YXkthoeQSZyhJagJ77bWXLYGVTMhASSZK971NfCKvpRIKenOezUR0Ts2EVnZty40CR+r/ZAHz7snPoEGDzODBg5PSiveUiCcVWO5wB+BDT1pV6mWQZjXe0yN8vCliy1MQMimxuZhjnz59zOabb57dav3vVdoYOeHTxSIgAhERCH73Ec/Cg65GjRrZ3rPJXBbRtNSNCIhAGRJw9XCDU2jQoIH1VoonPPjBTQ93PjJ733HHHbYZbnu8LklMyz3JOAAAIABJREFU4MsvvzTXXnttynhjyggQNoQBwwmK9iabbJISL9/p7733Xsp2wQY6p2aEK6vG5UaBy+rui/QibYwiXThNWwTKGYGgAvfggw9aN3EX95vNU9tyhke3IwIVggCKAA+qd955Z3u/WN/efPNN+28UBvIC8AA7nvXNAXK1dCm/dMMNN9iXgwk3KgTILG7yjDPOMC+99FKpK8m1gJHh1VdfNe3btzdkkoyXqC/4HU4bYuSqVatmk5bUr1/fxtSxlk2bNs1odjqnZoQrq8ZS4LLCVrYXaWOULX+NLgIi8P8JBH/8H374YVsrk1IsHOiIreDpsEQERKB8Ezj77LOtBYgkJez9W265xd4wISokgsvE6wjrW+/eve31d999t6HUE+UEdt1117ghL+WbbOq7SxQ/OHHiRNOmTZuUHcAa5ijXuLySiK9q1ar2Qdw333xjUKxr1KiRsp9wA51TM0aW8QVS4DJGVvYXaGOU/RpoBiIgAiUVOOKQUeBcPAuFY0kjLhEBESi/BFDQqlSpkvAGUegyEb5Hunbtai8h5GX//fe3lv19993XkKgjVdK5TMYq9rbkW9h+++3j3ga5INLJMMn6EPLDGobrIOfCR+fUXOild60UuPQ4FVQrbYyCWg5NRgQqLIHg01+nwFG019V54oCx7bbbVlg+unERKM8EsLCTHyBRLTH2Pt8BmQiZJ4877jh7CRnAn3rqqdjlFKTmNcn/J0BMoYs5DjMh6Z5zaS0LXjqn+qcuBc4/48hH0MaIHKk6FAERyIJAUIF79NFHbbwL8RO43iC4PX366admxx13zKJ3XSICIlCoBIhTGzJkSNLpkaGbTN2ZCPVzXZp7LEhk+3biCn9n0l95bXvfffeZbt26xW7v6quvtklKnFATLp0EJb746Jzqi+z/9SsFzj/jyEfQxogcqToUARHIgkBQgXMJB4iXIF24k6uuuiqWVS6LIXSJCIhAARIgTuqHH36IO7Nbb73VxsC2bt3abLbZZhnNHpc+Uttv2LDBugfioukkG4Uwo8GLpPHnn39uDjrooBKzpUyVOxvyRqauq1Hfus6pURMt3Z8UOP+MIx9BGyNypOpQBEQgCwJBBc6VXzn00EPNxx9/HOutTp06Jf7OYhhdIgIiUEAEcJHGVTosBx98sOnfv3/Obo5krVy1alWp/omJcxkqCwhHXqfywQcf2OyQQcGtdPz48YbyDXhCUOO4rAug65zq/2MhBc4/48hH0MaIHKk6FAERyIJAUIF7/PHHTefOnW1MRrDeE8Hx69aty6J3XSICIlCIBMhWGFYQnn/+eWtxi0JIXLJ8+fJSXVF39957741iiKLtAwV52LBhsfnffPPNtg5coYnOqf5XRAqcf8aRj6CNETlSdSgCIpAFgaAC5xIMkNBg5syZsd5wg1q/fn0WvesSERCBQiQQzBTJ/FAgUCSiEix5xM6GpW3btubZZ5+Napii7Kd79+4llNh33nnHNG7cuODuRedU/0siBc4/48hH0MaIHKk6FAERyIIAMSnEuFEygFpN1H068cQTzZQpU2K9Ec8SjGPJYhhdIgIikCYBHpb8+eef3jIQkt2wQ4cOZvr06XZGY8eONZ06dUpzduk1O+KII8yHH35YqvEJJ5xgpk6dml4n5bQVJRXGjRtn765du3a2/l4his6p/ldFCpx/xpGPoI0ROVJ1KAIikAUBAuVxl6xevXosJgY3qkmTJsV622abbcwvv/ySRe+6RAREIB0CxKQ99NBDtgBzjx49bAKLOXPmGOJRo5SXXnrJnHHGGSW69GEB4owze/bsUlNv2LChva+KIqzr7bffbg455BBTs2ZN+z2Lsuy+Xz/66CNTt27dgsShc6r/ZZEC559x5CNoY0SOVB2KgAhERODcc88tUbuJwt6//vprRL2rGxEQAUdg1qxZZsCAAYaYtLBcfPHF5sEHH4wUFhYwZ3mjY+q8ff311zZrZJTSvHlz8/rrr5fqEiVm0aJFUQ5V0H1RGgAFLpEsW7bMFjovRNE51f+qSIHzzzjyEbQxIkeqDkVABCIicNFFFxlKCjipXLmy2bhxY0S9qxsREAEIvPLKK+bUU09NCANLWdASniu1//73v2aHHXYwv/32m+2qa9euhr2eqJB0LuOddtppNqNiWKgP9+233+bSdVFciwV1xowZBkU2mZR1se5kc9M51f9HTQqcf8aRj6CNETlSdSgCIhARgXCQPXFx7tAX0RDqRgQqPIEmTZqYd999NyGH008/3bz44ouRccLa17RpU9tfixYtSsS5RjbI/3ZEbNdzzz1XqtuKYs2fMGGCad++fUqsv//+u9liiy1StiuLBjqn+qcuBc4/48hH0MaIHKk6FAERiIjANddcY2677bZYbxwwOGhIREAEoiGAFWrPPfdM2hm1wubOnZvzgFjPqTNG/JsT36nrifN64okn4s596dKl5oADDsj5vgq5A2L90lm7si7WnYyhzqn+P2FS4PwzjnwEbYzIkapDERCBiAgMHDjQ3HjjjbHeNttsM/PHH39E1Lu6EQERCGd6jUeEYtjffPNNzrCo73jBBRfE+tlkk03MwoULTa1atXLuO1EHxO89/PDDCfsnyy1WwPIqO+64Y6namSSD2rBhQ4lblgJXXj8B6d2XFLj0OBVUKylwBbUcmowIiECAwPDhw02/fv1ir2y66abmr7/+EiMREIEICPzwww+2bMc///yTtLeo3A2HDBlibrjhhthYt9xyi+nTp08Ed5K4CzJpjho1KmED3r/rrru8zqGsOl+9erUh1i8sKGt4Muy1117m+++/N0cddZR5++23y2qaKcfVOTUlopwbSIHLGWH+O9DGyD9zjSgCIpAeAVcbLtiaw2aw6Hd6PamVCIhAmMBTTz1lyPSKkEKehEGXXnqpLedBAexPPvkkdgn14CpVqpQTxKAy9cILL5hWrVrl1F86F1MY/NZbb401JdPiF198EfubOnSJXCzT6b+Q2xC3GI+xs7Z9/PHH5vnnn7flBAo1AyV8dU71/ymTAuefceQjaGNEjlQdioAIRESA1OUcKIOCCyWulBIREIHMCMycOdMmI5k3b57dQ1i0XTHrJ5980sanBaVevXqG+mAIdcTIHJmLBMuC+Kj5Fm9uWPyw/DkZOXKkzchIPTQEF9JXX301l9uK5Fq+17AUkmkX6xiZI4cNG5ZT/b3rrrvOEGMYlkJ2l4wHU+fUSD5iSTuRAuefceQjaGNEjlQdioAIRERg7NixpnPnziV6o5A3MRwSERCB9AmgoGFtiifEoq1du9YQLxWUY489NlYX7ssvvzT77LNP+gPGaUms2bRp0+w7n3/+ualRo0ZO/aVzMW6affv2jTXlO+Wkk04yO++8s30tqgQt6cwlUZs1a9aY3XbbrdTbuWToREHGNTKeSIHLZbXK57VS4IpwXaXAFeGiacoiUEEIPPvss+ass84qcbfEbOy0004VhIBuUwSiIZAonT69cw4gtX9YKB/w8ssv25cXLFgQs1plO6PDDz/czJ8/314ehUUvnXk89NBD5pJLLok1nTx5sk1aggUSRWbfffc1y5cvT6crb23C2XaDA2XjMr5ixQp7X4lECpy3pSzajqXAFeHSSYErwkXTlEWgghCgAC+FeINCNjyy4klEQATSI8CBHevZV199ZeNHwwd4XPVwtwtLx44dzfjx4+3Ls2fPNtSLy1Yo3k0dR4RyINRzzEcsKzXgUF6dzJkzx5Ban4dAKJFY87Hql6U0a9bMvPnmm3GnkI3lM6go0ymxjVhg33jjDYNCe+GFF5bl7WY8ts6pGSPL+AIpcBkjK/sLtDHKfg00AxEQgfgEXn/9dRuvEhQSEOy3335CJgIikCYB3BZdqnySk7Rt29YMHjw4dvV//vOfuLFWl19+ubn//vttO+LEiBfLVoL12E444YRY7F22/aV7HUrLcccdF2u+bNkym7CDGDhKGCCrVq2K68IYbwwSf1AKAYX06aeftsleshWsa7ivJlPgyA6ZyBUy3rjhzKK9evUyt99+u1XaUVS32267bKdbZtfpnOofvRQ4/4wjH0EbI3Kk6lAERCAiAvHiOBYtWmRq1qwZ0QjqRgTKJwEULxKQDBo0yMaAjRs3zt4oKfM5yF9//fWxG0/kphfM4DhhwoRS7szpkuOhC/FurlwBFqFgPbh0+8mmHcopGTad/PTTT1aJYXzq0iGTJk0yZ5xxRsru77nnHnPFFVfE2pGG/7333svKI4CHUyjSderUMe+++675+++/bb9Dhw61CUz4D0H5Dj/ESjZRMmqiLDspD0mfdE5N+dHMuYEUuJwR5r8DbYz8M9eIIiAC6RGYO3eudXcKCofS4IEsvZ7USgSKlwCHe1L7H3jggdb17+uvv7aZJLGIObfE4N0FLW4oKqTsX79+vc06ScKMxYsXx1Kzt27d2qaSjyc33XRTTNGjGHaXLl2yghjs55RTTrFxdflwn2SysELRcuKU1aAyRr3JYKKTRDd5xBFHmA8//LDE22eeeabBTTNTadq0aam4Q5RckrtceeWVsdp0ZA0lFjFdIWaY2GHkmWeeKeE+mm4fhdZO51T/KyIFzj/jyEfQxogcqToUARGIiADKGqnMgzJ9+nRz/PHHRzSCuhGBwiZA4Xo+75QAwHI0ZcoUc/bZZ5uVK1faEhsodBzyiVfDYoYcdNBBVhEIC/2wf3CnwwKHOyGp611GxnB73qN2G4IbHu546QjxVlxbq1Ytc9FFF5lu3boZLGEIimiDBg3S6SaSNhs3bjRbb711rC8X/xfMcEupASyVqQQFa+nSpSWakT0SF8xMBDfHqlWrlrqEeN+XXnrJ9OvXz6BUItTqa9++fVrdY22jXyysJGkh4VMxukyGb1bn1LSWP6dGUuBywlc2F2tjlA13jSoCIpCaAPEmhx56aImG8epVpe5JLUSgOAlgPWvTpk1ak8fNEYXimGOOidv+3nvvNcS1pStjxowx559/vm2erpJDopTq1asblImwkBkRd8p8Wd/c+CRfwU0xWLQbVk4xQvGNVy8tPH/YYsHE6klNPBS3zTff3NZty+SecGc977zzSvG5+uqrzYgRI6wb5YABA+z7jz76aMqkI4yPwobLOZY9BLdLV7Ih3fUu1HY6p/pfGSlw/hlHPoI2RuRI1aEIiEBEBMLuT3RLIV5cjCQiUBEIBN3pcrlfFAwyuO6+++5pd4NrJS6CiEuGwb8pKfDggw/awt/uDOE6vfvuu03Pnj3jjuEUlLQnEFHDDRs22Fi1o48+2mbARLBatmrVyv4bxljgcBPFPRvlh6QtZMqkDYlGEDJW/vrrr9bKteuuu5pPPvnEvk7/QStfqmkH3RyDbR955BFrsbzjjjtM79697VtYMrt3756wSyyCLjsorpYofEiizKKp5laI7+uc6n9VpMD5Zxz5CNoYkSNVhyIgAhESIGkA8SpOSHfO4UQiAhWBQLy4q2zum0M+pQAyEdwtyRiJEP+GgoM0atTIukIiuHgSW+eEdk6JCI9FTCuFswtBXnvtNVvQG7nsssuscob1Cxk9enQsyYqLQSN2zt0nWXCrVasWi2HDnTUYZ5fs/uBFwfR4pQuoxceZDOUY91iEQuR9+vRJ2CXfh/Gsh7jcorCWB9E51f8qSoHzzzjyEbQxIkeqDkVABCImEEzKwBNqnlRLRKCYCKAAcGjHLZH6YyTNiJeAxN3TkiVLrItfOGlGuvdM6vmgwpaNRQYlDWUNobYYCVFQBINKGG7OZFJ0cuSRRxpqrYWlZcuWBqWpUCRYXoD7QmmLJySKwRoXTMFPCQKUOOLVEIqTH3bYYUlvDWte5cqVbdwhLqZhcQlmiGkMulgOHDiwRMmH8HXxrHm4dZJtM9nnq1DWIZ156JyaDqXc2kiBy41fmVytjVEm2DWoCIhABgSCsXAu0D+Dy9VUBMqUAG53ZFP99NNPY/PA1TCYkj48QZSkDz74IOt5Y7W59dZbY9dnmo6eC8lWSSKSZILi4+LkSBhCbFi8+DcyaTpXxKxvKsILiYlzrofnnnuuLXQdTyh6jUXx22+/NXvuuadtwnVkBHVlCEj5Ty23eLJ8+XLDdxbulricdu7cOVZPD27bbrutLeJ9ySWX2GQvyMSJE22JAQS3U9YRV0kUv3CsHXF94bk3btzYxsOVF9E51f9KSoHzzzjyEbQxIkeqDkVABCImQOIAEgggHITjPeGPeEh1JwKREUgUF0YtsGCRaTfg6tWrM4pV4zoUA6x7TigyjfKBUoWsXbs2bubDZDcZVFoStQta9oKWcjJhfvbZZ7HLXPbHyKDm2BGWTdxTEeL8UJriyVVXXWUzcJKan+yfCNZECngTq4YkSzSC0sZaOBkyZIjBqoZQXoGMk2HB4nfyySfbly+++GJbCmHy5Mk206ir5+euwcUVV9egkKiGhDXlRXRO9b+SUuD8M458BG2MyJGqQxEQgYgJEDeCWxCHQDLZ8VRbIgLFQgAFIVGttXiKDdYzF4+Vzj0ee+yxhqyKJNZwwkMPlJT+/fvbgz+KSKYSdBtMdC3ZElFKkGA81m233WZQXIkPK0S3ZyxizvWT2nSvvPJK3FskPg5lNJg4ifVs165dLIvlqaeeamvbxZNgvCDv4xbrFLrx48cbrH9heeuttwxriuBSSdkBJ+Gi67huklQmKLB3SVAyXfNCbK9zqv9VkQLnn3HkI2hjRI5UHYqACHggQK0q6hpttdVWNhOcRASKhQBZDbG2xZN4roXEXVHvLSgk8nHZCElsQdZE4qpQLt5++2170K9Zs6at/xaVmzHKJbFeK1asSIg6mFkS6ziJShDcnkkMgisf88FVsJAkUSxaeI7ExxHjRk1KJ1g7WQ93T6wB7qbx5IADDrClE5ygmOEyiaA0Oktb8FoYwjKe8N3Hd6ATlPbvvvsu9jduqrjqMqfyIjqn+l9JKXD+GUc+gjZG5EjVoQiIgAcCPC13abuxDHA4lIhAMRBIlkmSw3e4kPY+++xjLVdBwQpNLBT/x9JFEg6UI7IVOssbZQJ4HYsSsWhRCAohisbPP/8ct9i1c9dbv369VSKxEO2yyy4GN9BMaqNFMddM+ohXoiTe9SjT4eQruDFi1USRQonmfrF4xpMqVarYhCJOyEBJEhvEZZ0MX0d9uT322CNuf8zbxeIxtlPmULSxhO69996xWnCZ8Cjktjqn+l8dKXD+GUc+gjZG5EjVoQiIgAcCxApxOEV4er7//vt7GEVdikD0BPisJnL7xf2NrIZOsLCEH06QVp5YqLKUYEbK4DywUD322GMl6qrhJvjUU0+V5XRTjk1MIIpXKiGJy6JFi2wz4t5we3QZJ1GkiBOsVKmSTdwSVlhRtimwnUiSZa+kLAHKWliCWT+ZV+3atW2T8lS4O3zPOqem+pTm/r4UuNwZ5r0HbYy8I9eAIiACWRDgUEicD0IGOdKVS0SgGAhgDcNChcsd2QuD2SWnTp0aq7XGveCqV69ePXtbLVq0sJkOMym+7YsH1j1qn4WFfYlSg3Lj3Agfeugh07VrV19TiaTfdOL7GAglz7kotmnTpkSyExTvhQsX2vnE8wqYN2+eadCgQcL5JnsQlajYN/FxTZs2tX0Gk50E6/RFAqiAOtE51f9iSIHzzzjyEbQxIkeqDkVABDwQ6Nmzp02KgLjiuh6GUZciECkBskBuvfXWtk9cI7FMufT1vEa2QNwQnfC+S2zRq1cvmwGxEIRYPSxNYTn99NNtvNb1118fe6sYLORYzLbYYouUaKnPxr0jnTp1MmPHjo1dgyKFGyRCbUqStTjB7ZTkJskkWWZQMluilIVl0qRJ5owzzrAvB9sMHjw4lt0y5U0VWQOdU/0vmBQ4/4wjH0EbI3Kk6lAERMADAVJuu0NiMTzh94BAXRYZAeLBOOS7gtokmEAZuPHGG2OHbZJYBDMgkmKe95FC+5zHi2kjjT3lA4ISzpRYiMtGgpZM69JRq+2BBx6I3U6NGjVsfTYnuJOiVMGJGDksk8nk999/T6hEYrE99NBDzVdffVWiC9xVGQcJlqcYOXJkiUyZhcg82znpnJotufSvkwKXPquCaamNUTBLoYmIgAgkIfDwww/H4oCGDh1q06NLRKAsCVAb7P7777cp20kcEhasImSLDAqKA8knqlatamu0YQUiu6qLewu6ziVKclFW9xxPgcOaGCwajeskimcxSKZJVijF4Gq/cX9HHXVUqYLZZOwkkQgu3q5eJQlJiJULS6raeFgJqaVHjTo+S4grLM6/hw8fHqsjVwhxkr7WXOdUX2T/r18pcP4ZRz6CNkbkSNWhCIiABwK4TbZq1cr23KNHD3PXXXd5GEVdikByAmRCJfMjMWHBxCThwzhKGhkHsbI4ueaaa2wmSYR4qhdeeMH++7nnnrPFpBGsLiSqQLIpvu1z/UaNGmX3HklZgqnxg2OuW7fOkHmxGCRTBY6HRjw8coICj8IdlP/85z92DVHQqd+25ZZbWkUrXh2+VAqc65eMniiBtMelk5pzJ510kqEGn5uPy4xZDNwznaPOqZkSy7y9FLjMmZX5FdoYZb4EmoAIiEAaBN577z3TuHFj27IYstylcUtqUoQEiPmKV7Q57A4XTGCx22672Vg2lDQXdzVmzBhz/vnnxwjgmkfSkurVq9tU/CgAKHCFJiiuKGiJynikq5QUwn2hWOGaTZKZYMZHMkf++eefpaY4bNgwW8IhKJRZ6Natm5k+fbp9me8pEtWgvCMkd6EIeLykLpmwwvI2evRo2yfJcMgKymfGPciiUHzr1q0LAWvkc9A5NXKkpTqUAuefceQjaGNEjlQdioAIeCDAE3+K4iLNmjUzM2bM8DCKuhSB5AQSWW3uu+8+m60QCxUKAbFKLqlF3759rRUmKLhNUr8NZc0JB/0777zT/knZANziClESxY916NDBPPHEE4U45YRzIiYRaylKF/XXKEyOYk3dybCwNiRTCktQueJ7CeXWFeIm4QjWVop/O6FmG7FyfI+lKzwgoAi4c8sMX0etupYtW6bbXVG10znV/3JJgfPPOPIRtDEiR6oORUAEPBDYsGGDffKM8FTbpe/2MJS6FIGEBFK53ZF5EAsdypizjpDMwmWWDHZ8zDHHmJkzZ8Ze4nPtitVzwEcxKFSJx4E96jJuFuq8E83ryy+/NLg/4pq4+eabWzfRcO2+REllunfvbrOJIiSkoXC3W28UQjwG6tevb99HAXRKeqaMgslvwtfyOTr66KMz7bIo2uuc6n+ZpMD5Zxz5CNoYkSNVhyIgAp4IcDgk8cPOO+8cq83kaSh1KwKlCGAt43Dv0srjDvnf//63VDti2LDEucLzweLLwca43mG5c0Lyi5UrV9o/C90lDmvbk08+WeLeM3EJLPSPF1Y43FyDkkgR79OnjxkxYoRtSlwc9fCIT0NIckP2ymeeecZ+Z1122WVxyzGkwwOXSa6PJ9QWdPUD0+mrmNronOp/taTA+Wcc+QjaGJEjVYciIAKeCOB6xJNynv4To0JAv0QE8kWABB0utqlu3bo29ilebBNWF+qCkQqeeKpff/3V/j8s/fr1K+FaSWwZ1yC44mXiYpcvBm4clFkshEElpzwpcCQFOe+880pgTZTp8YYbbjBDhgyxbeGBJc9lq4xSESfZTbt27eIu9aJFi0zNmjXz/THIy3g6p/rHLAXOP+PIR9DGiBypOhQBEfBEgCfMH330ke29mLLdecKhbvNMYMmSJTZWCmnevLnB8kLikbAEiz8Tt+QsceF2ZKS89tpr497Fhx9+aA4//PA832Fmw61Zs8bsu+++NtMmCTRQVsqLkKylWrVqJW6HrKEuE27wjVtuucUQ54hgJZs/f36sXlyUsWlvvfWWjYOLJ658QXnhH7wPnVP9r6oUOP+MIx9BGyNypOpQBETAE4FGjRrZ7GsI7ki4UkpEIF8EOIwTI4UQ10RtroMOOijp8Pfcc4+11MUTLDqUJIgny5Yts3FYhS7EXk2ZMsXex1577VXo081ofuE4P6z+lSpVKtVHsKA2ljcUuLFjx9p2UcamER8ZL7kK45AUZ6eddsro/oqlsc6p/ldKCpx/xpGPoI0ROVJ1KAIi4IkA31ezZ8+2vfOEnNpIEhHIF4G2bdvaosoIiSjIFLnVVlslHZ76hZQeiCfEkBFLFk+oIebcNfN1fxqnJIFgkhlS+AfLPgRb4i7rXGkpS4CXAO6OCOUkjjjiiEjQYumsXLly3L6IDU70XiSDl2EnOqf6hy8Fzj/jyEfQxogcqToUARHwRICYoDfffNP2TizcPvvs42kkdSsC/0fgjz/+sBYmV4eLgzIua1iAU2WlpC4YluN4MmHCBGvJiyeJrD1al/wRIKEMZQBY55deeskW5Y4nQUWcYt8ocJMnT7ZNP/30U1OrVq3IJh1013SdHnLIITbuLtVnMbJJ5LkjnVP9A5cC559x5CNoY0SOVB2KgAh4IkCdo6lTp9reiUei6LFEBHwTIEU8qeKdkLRi0KBB9s/dd9/drF69OuEUqF9I8p14QsbCs846q9RbFKx/5513fN+W+o+IALFx1HpDrrrqKqvA+XrQhGLfoEEDW0aFwvBHHnmk6dSpky38Xl5F51T/KysFzj/jyEfQxogcqToUARHwRIAaW9RZQogHqV27tqeR1K0I/B8BDsrBBB3BemfExZ188smGDJIk1glLstpoCxYsMIcddliJS4ixIiX8oYceqiUoEgLEAJ544ol2tpQMQIHzGatLBlA+a+U15i287Dqn+t8IUuD8M458BG2MyJGqQxEQAU8EyHQ3adIk2zuJAsKHX0/DqtsKTiAYe/nEE0+UilsjHnO77bazSTwo4uxk++23j5UFSIQQawpxUk6w9I0aNaqCEy+u2587d65p2LChnTTfUXgHYCFDfvnlF7PNNtsU1w0V2Gx1TvW/IFLg/DOOfARtjMiRqkMREAFPBM4++2xbEBfuRFi/AAAgAElEQVTh0FS/fn1PI6lbEfg/AsRaEg+1ySab2JT58Wq60Zq08yhzTshY6WKhEvEMp4YnNf8uu+wi/EVEgDXbbbfd7IxJWIJ1DNdZ5K+//lK9yhzXUufUHAGmcbkUuDQgFVoTbYxCWxHNRwREIBGBjh07mvHjx9u3yUbZpEkTwRKByAgQtzR9+nTTo0ePmBLFAZzkFX///bfZc889zddff51wPEoKfP7557H3b7755oR13lwjLDTUUvvxxx9t8WdiqCTFRQCXRrKR/ve//7UJT3CDXbVqldliiy2swi/JjYDOqbnxS+dqKXDpUCqwNtoYBbYgmo4IiEBCAhdccIF5/PHH7fsctknzLRGBKAgE45gooI2Fl4LcS5cuNTVq1LBD8Hs5a9ashMNhfaEAt5N3333XJplIJdQ0/Pbbb03dunVTNdX7BUqAAu+4TgZlhx12sIq5JDcCOqfmxi+dq6XApUOpwNpoYxTYgmg6IiACCQlQd+vhhx+270+bNs00b95ctEQgJwIvv/yyGTBggE3DHhRcddu1a2f+/e9/m9NOO82+Ra2vhx56KOF4xx9/vJkxY0bsfcoPJHK3zGnSurjgCATdu93kqFMZdKktuEkXyYR0TvW/UFLg/DOOfARtjMiRqkMREAFPBEjwQEp3hNgiYowkIpALAUpRLFu2rFQXJKWghtv1119vhg0bZt+//fbbTa9evRIOd/nll5v777/fvk+8HG6XkopBgILtrVq1KnGz55xzjqFGnCQ3Ajqn5sYvnaulwKVDqcDaaGMU2IJoOiIgAgkJEB9055132vfJRkmRXYkI5EKAotyJ4pSee+45c/755xtKASCpEucQ/0ZRZSxvWIq7dOmSy9R0bRER4DOy7bbbxmaMS+Xbb79tY+IkuRHQOTU3fulcLQUuHUoF1kYbo8AWRNMRARFISKBPnz5mxIgR9n2KILdt21a0RCBrAr/99ptNPuEEdzfKBFx77bWl+sS6QsHmVPLxxx/bBBa492KFk1QcAhRl53uJZDckWSJ7qSR3Ajqn5s4wVQ9S4FIRKsD3tTEKcFE0JREQgbgE+vfvH3NnwzUJFyWJCGRLgMQhHLYRko2QdIQizPXq1SvRJVkFKRyPVUUiAokIYIWjLATnKmoASqIhoHNqNByT9VJuFDiewJFpiuKaFGPEHYInb2H/ZgeDL3YOFjNnzrRpZA8++GDTu3dvQ1BrPPnqq69Mv379DFmvSCFMhqtLL73UXHbZZeZf//pXqUvIYjRw4EDrMrR27Vqz9957m86dO9unhLkGSGtj+N8YGkEERCAaAoMHDzaDBg2ynZGNku9BiQhkQmDFihX295ki8G3atDF16tSxl7uabcTDERcXFJLnPPjgg5kMo7YiIAIREdA5NSKQSbopNwocNVn4ksd3mfovKFyJFLj58+ebo48+2hZrbN++valatap5/vnnbRHHkSNHmiuvvLIEMvpq1KiRofAj7j+MhSJHBqyePXvG4jvcRT///LNp3Lix+fTTT83JJ59s/esxzeNbna5LR7Kl18bwvzE0ggiIQDQESCbBwzJEMUbRMK0IvfAQ1MVL4t7okpaQlARlDjn33HNtjUEekoYLaT/yyCPmoosuqgiodI8iUHAEdE71vyTlRoGjkCeuEli6eNrLU99EChzK1Zw5c8zUqVNjKa2xqqGkLV++3NYFqVatWow+Lj9PP/20efTRR82FF15oX//zzz9Ny5YtzRtvvFEqSPq6664zFAMlzfGQIUNs+//5n/+xT57HjRtnCLI+88wzs15dbYys0elCERCBPBMg/o04OOS+++6zXgvpCN+xuDdRl0lS8QgEPzfBu+f3G7dJpFu3buaee+6xXjQ8uA0KpQROOeWUigdOdywCBUBA51T/i1BuFLggqmQKHFYx3CUJVqYmUVBww+zUqZNVvlxA9E8//WSteljdyFYVFCxqWPJwpXRpiP/55x/rn79x40YbFB0MtsaSR4Asit+rr76a9epqY2SNTheKgAjkmQAZKMlEifBvDtXEmiTL9Mb3Z+3atc3q1avNK6+8YqjVJak4BIYPH25DFuLJ7rvvbn9bEcoF3HjjjfbfKHAock4Ip6BIt0QERCD/BHRO9c+8wilwDzzwgH0CfMstt8SeCjvMuEjutttuMb96Xn/ttdfs31zD0+OgUC+GgwhWPxRDZPHixaZWrVol+ghew3soclj84sXOpbPk2hjpUFIbERCBQiDA9yaWEgRF7PXXXzfbbLONTTDBd2c84SEangxO8GCQVAwC33//fdpp3IMWXVwocaV0QnZKijJLREAE8k9A51T/zCucAnf11Vfbwp4TJ060wdBhoSYIT/ictQ33jCuuuCJhMVDi2z777DObNAXBbeO0006z19x9992l+uc92qTz4+I2QLiTBQsWmEMPPdTG1ElEQAREoJAJEPdGQomwJIsHJg75rrvukgJXyAvraW5jxoyxddzSkaCbZLi4N7/JuSYMS2cOaiMCIlCagBQ4/5+KCqfAcZDgQIH7JG6UYcH9keQmWOMQF4CfKPj+qKOOMu+88451maS4KGmyO3ToYIP2hw4dWqp/3qMNFjuscclECpz/DaARREAE/BIg8+QFF1xQahAelpHwKZ706NHDjBo1Sgqc36UpyN6JMx89enRacyORGA8zEWLgiV9HqlSpYtatW5dWH2okAiIQPQEpcNEzDfdY4RS4rl27GrJTkfQkXlxFWIG76aabrJ99ooxWYQWOjFgdO3Ys4ZsfhJ6JApdo+bUx/G8MjSACIhANAfdQK15viVwj8WDA+8GJXCijWYti6OWAAw6wGaHTETJVuiQ3xJevXLnSXrbpppvaB7ESERCBsiGgc6p/7hVOgSsmF0opcP43gEYQARHwS8DFEWeiwBEzF4w5lgLnd40KpXfiw4NxkSSycfHl4TkS8+Y8ZXiPLNFdunSxzfr27WtIhCIRAREoGwJS4Pxzr3AKnJKY+P9QaQQREAERcARIVuIKLwepJLOSkDSK72onUuAqxucpGP92ySWX2M8AbpHUa/3www9LQDjhhBNsKSAnZIBGcaMeLNlOiWWXiIAIlA0BKXD+uVc4BS6dMgI8ueOHAEmnjID7oaE9PyJkvvrtt99sCmzi4py4MgItWrSw2S2zFW2MbMnpOhEQgXwT4DuUmKSw8N34zDPPWHc5LCfBkiuUZnnwwQelwOV7scpwPLI6kwWaLJQIrrfUYHUyadIk07p169jfvXr1ssnFJCIgAoVHQOdU/2tS4RQ4kEZVyPvEE080M2bMMO+//75p0KBBbLXiFfLmzfPOO88W8n722WdN27Zts15dbYys0elCERCBMiCw3Xbb2dIpiSRc1sUlm3LtZYErg0XL45A8+CRrs6sXyNC4R+Im6WTRokW2NqATYiRdeYo8TlVDiYAIpEFA59Q0IOXYpNwocCQZcWn158+fb8hO1axZs5g/PU943QeK9/k3T/xwzahatap54YUXzLJly8zIkSMNKayDguWsYcOG5rvvvrOK13777WctaIzRs2dP664RFDKrHXnkkYYfHIrWUmqAufFfstTZ6a6lNka6pNROBESgEAjwnfnll18mnUpQSeP7mpgmKXCFsHp+57B+/XrTuXNn89JLL8UGatmyZSkvFYp0U6zbSbCEgN8ZqncREIFMCeicmimxzNuXGwWOujH4zycS0hIHa8ssXLjQZop86623DD8MBx98sOndu7dV6OIJ2a369etnpkyZYp8kU3OGOI3LL788bkFusmMNGDDA4PaBS8hee+1lx+/Tp4/ZfPPNM1+pwBXaGDnh08UiIAJ5JlCjRg2zdOnStBW4cCp5WeDyvGB5Go51PfbYY83MmTNLjEj5nmAhd/fmv/71r1g7YuIOP/zwPM1Uw4iACGRCQOfUTGhl17bcKHDZ3X5xXqWNUZzrplmLQEUlQM3LxYsXp63AhR/ISYErn5+c2bNnxzxjgnf42GOPxa0d6MpLkKmS5Ca5Pgwtn1R1VyJQ9gR0TvW/BlLg/DOOfARtjMiRqkMREAGPBCi2/PHHH6etwHXq1Mk88cQTsfZS4DwuThl2TRISSvuEJZF7JMnB8IIh5pyarRIREIHCJKBzqv91kQLnn3HkI2hjRI5UHYqACHgkUK9ePfPRRx8lHCFYUgCXc1zaiTl2IgXO4+KUYdeEGQwdOtTOgIyTEydONDVr1jRz586Vda0M10VDi0CuBHROzZVg6uulwKVmVHAttDEKbkk0IREQgSQESALFoTyRkKWScgPEI++///7m22+/LdFUClz5/HiRBIzsk8iLL75omjdvbhOVbLLJJuXzhnVXIlBBCOic6n+hpcD5Zxz5CNoYkSNVhyIgAh4JNGnSxLz77rsJR6D+16pVq2xm37p165ZqJwXO4+KUYdfBWMc333zTHHPMMWU4Gw0tAiIQFQGdU6MimbgfKXD+GUc+gjZG5EjVoQiIgEcCHMzDmQaDwzkFbtq0aaZFixYlZkLmQeqEScofgTZt2tgSPoiySpa/9dUdVVwCOqf6X3spcP4ZRz6CNkbkSNWhCIiARwLHH3+8mTFjRsIRtt12W0P9zPHjx5uOHTuWUuCo2RlMIe9xquo6jwRwmXz99dftiNRhxX1WIgIiUPwEdE71v4ZS4PwzjnwEbYzIkapDERABjwQozDx16tSEI5DE5M8//zR33nmn6dWrV6l2vFepUiWPM1TXZUGgfv365oMPPrBDr1271lStWrUspqExRUAEIiagc2rEQON0JwXOP+PIR9DGiBypOhQBEfBI4JRTTjGTJ09OOsLvv/9uBg8ebIYPH16q3YYNG8zWW2/tcYbqOt8E1qxZY3CddUICG9V1y/cqaDwR8ENA51Q/XIO9SoHzzzjyEbQxIkeqDkVABDwSaNWqlc0ymEzWrVtnrrnmGvPII4+Uavbjjz+aHXbYweMM1XW+CQwaNMgq7AiZJ6nxJhEBESgfBHRO9b+OUuD8M458BG2MyJGqQxEQAY8E2rZta2t8JRPqvnXr1s08++yzthlulcS+IatXrza77rqrxxmq63wSIKvoQQcdZJYsWWKH5fPh1j2f89BYIiACfgjonOqHa7BXKXD+GUc+gjZG5EjVoQiIgEcC7du3NxMmTEg6wtdff226dOliXnvtNdtul112iRXzXrFihdl77709zlBdJyKwdOlS880335imTZvaRDLErPXo0cPst99+ZsyYMVbRzlTmzZtnGjRoYC+rVauW+eSTT5SkJlOIai8CBUxA51T/iyMFzj/jyEfQxogcqToUARHwSIDMkmSYTCbLly+3GShnz55tm9WuXdt8+umn9t9YaqpXr+5xhuo6HoEFCxaYxo0bm40bN5ojjjjCKuHBdXjllVfMySefnDE8EtWMHDnSXnfjjTea66+/PuM+dIEIiEDhEtA51f/aSIHzzzjyEbQxIkeqDkVABDwSuOCCC8zjjz+edAQUt6OOOirWBouPqx2HhQaFTpJfAocffriZP39+wkGHDRtmrrvuuowm9d5771ml0InKB2SET41FoCgI6Jzqf5mkwPlnHPkI2hiRI1WHIiACHgl07do1bnKS4JDUinM1wXidxCeTJk2yTVTk2ePiJOm6cuXKhuygiQSL6bhx4zKa3IknnmimTJlir6lXr16sjEBGnaixCIhAQRPQOdX/8kiB88848hG0MSJHqg5FQAQ8ErjsssvMAw88kNEIxM09/fTT9hqsNo0aNcro+mwaE++FpbBNmzZWuajI8scff5gtttgiKQIsdCjXmQixc19++aW9hMykp59+eiaXq60IiEARENA51f8iSYHzzzjyEbQxIkeqDkVABDwSIOnFqFGjMhrhvPPOM2PHjrXXzJgxwzRr1iyj6zNpvH79eqssomgi++yzjyEmj6QdFVWIPzz44INL3H6TJk0MrFxsIun/qdGXbiITSgVQz48slHvuuachcY1EBESg/BHQOdX/mkqB88848hG0MSJHqg5FQAQ8EggmrUh3GNwuH374YdscS1AyV750+0zU7oorrjD33HNPibdRNlBQypt88cUXNhkJVkZS+SeS559/3px55pkl3iapySGHHGJjFd955x37HlbLAw44IC1MQaXwhBNOMFOnTk3rOjUSAREoLgI6p/pfLylw/hlHPoI2RuRI1aEIiIBHAn369DEjRoxIOgLxVsFiztSEu/fee2PXLFq0yNSsWdPLLPfff39rcQvK2rVrTdWqVb2MV5adHnnkkWbOnDnmwAMPNJ999lnCqdx0000lskPSnmQylSpVMsGYxrAbJApi9+7dTd26dQ19BK2YwQQm55xzjnnyySfLEoXGFgER8ERA51RPYAPdSoHzzzjyEbQxIkeqDkVABDwS6Nevnxk+fHjSEfbaay/z1Vdf2Ta4XOKW51LN81o2GQ/TvaWdd97ZfP/99yWaE6eFK2V5k6BCtWrVKrPbbrvFvcVOnTqZJ554wr7Xv39/07t3b7PDDjvYv++8805z1VVX2X+zrn379o31QbkBFxc3efJkc9JJJ8Xemz59usHyhqAEPvTQQ+UNr+5HBETAGKNzqv+PgRQ4/4wjH0EbI3Kk6lAERMAjgRtuuMEMGTIk6QhYu5wS9dZbbxkO/7fcckvsGgo/v//++5HPkngsrH///e9/S/RdHksX/Pnnn2bzzTeP3SdF01u2bBmXaf369WMZIlGsq1WrFms3bdo006JFC/s37FCuL7nkErs+xx57bIn+gq6oZBVt3bq1fR8F8I477oh8PdWhCIhA2RPQOdX/GkiB88848hG0MSJHqg5FQAQ8EqBY88CBA5OOQHKLX3/91bZ5++23bYbCsNvlypUrDZa6KOXnn38222+/fakucTNs2LBhlEOVeV/EFF588cWxedx8883m2muvLTUvlNptt93Wrsc222xjYBS03OFuittpUDp06BC3WPsHH3wQy+iJRQ/LHjJgwICUSn2ZA9MEREAEsiKgc2pW2DK6SApcRrgKo7E2RmGsg2YhAiKQHgHc7HCjTCabbLKJ+eeff2wTYqWeeuopc9ddd5W4hBT/nTt3Tm/QNFuRhKNGjRqlWvvOfJnm9CJtFs6qSakGOIfl22+/tVkiEVwi582bV6IJ1sp0E7yQ7MQV7qaUhMv0iXWV2EiJCIhA+SOgc6r/NZUC559x5CNoY0SOVB2KgAh4JIAlLZPD+ty5c83o0aPNfffdV2JWt912m43FylSwID322GM2sUbYxW/27NmxeI1gvy+//LI59dRTMx2qoNuHFTiSwpAcJiwobLisImSrnDhxYqk2u+yyiyHRSyoh06SLe7v99tvN1VdfbS8h6yeJaiQiIALlj4DOqf7XVAqcf8aRj6CNETlSdSgCIuCRQDDpRTrDfPTRR/aA/+ijj5ZqPmvWrLgKV7gh8XTEfO2+++7W+ueSqKxYscLsvffeseYvvPCCVVLCgrsfboHlRcLxb9wXCt0vv/xi67J999131i0SKyhWTpfA5PLLLy+RDdTxoHQAGSfjCb9RuMEilCNwcW+DBw82gwYNsq/7sKaWl7XSfYhAsRPQOdX/CkqB88848hG0MSJHqg5FQAQ8EkAZo9ZaWFAgUB7CQr0xrHbjxo2LO6t41wQbLlmyxNSpU8cqIyTWqFevXuztoUOH2qyKToJufVtttZXZuHFj7L1U43hEFnnX33zzTYlEJG4AEongzogCd+uttxosa0E3VeIXr7/++lLzOe6448wbb7wRd564ZlIYHaEYu4t7u+aaawxWVOS5554rVWcu8ptWhyIgAmVCQOdU/9ilwPlnHPkI2hiRI1WHIiACHglgbbngggtKjUD6/nhueBR8JmulUwLCF6ZSrHDZI2U9QtFp3CSdkC0Rpc0J45AlE9luu+1swg4nqcbxiCzyrps3b25ef/31jPsl8UmXLl1KXUeWTpQ4FL+w4CbpFDXcYF3cG/937JNlwMx4krpABESgoAjonOp/OaTA+Wcc+QjaGJEjVYciIAIeCZAQ5Pjjjy8xQpUqVWxcXLzkJhSYxt0uUaHnVIoVKe+xOCG4BQZd/U4++WTzyiuvxOZC0WlXMPz888+3rn1OSNYRTLvvEZH3rsPxb+kO+O9//9uccsopcZtTIqBjx47WTTIouMxeeeWV9iUsqS7u7cwzz4y1Ralu0qRJutNQOxEQgSIioHOq/8WSAuefceQjaGNEjlQdioAIeCQQzvSIhY0C0vfff38Jd0Y3hWXLlln3xwMPPDCui2UqBY6yAM6Shlsk7VE2kEaNGtksl07atWtn3fmQmTNnmqZNm8beW7NmjXUpLHaBJYXRnZCg5OOPPza///57ylsjoQmZKBMJxdZ79eoVe5tyEFjdnBsmZQpwWeV11hyLKxlHf/zxx7jlG1JOSA1EQAQKnoDOqf6XSAqcf8aRj6CNETlSdSgCIuCRAIoCBZ+dOAUMK024VABtvvzyS7PPPvuYhQsXGpKOhLNBhhU4EnR8/fXXZr/99rNDJLM2HXrooeY///lPbC58nzoXS+rM4S5I5kQESyBKZLHLqlWrzB577BG7Df4+7LDD4ro/hu8VS2bw2vD71Otr1apV7GUSxKDUYW1zQk05EtKcddZZ9iXq61FnTyICIlA+Ceic6n9dpcD5Zxz5CNoYkSNVhyIgAp4JkMIfxYmYNJehkKLSxFiFBWXM1SFDWcNiE5SgAvf333+bo48+2rz77rvGJdxIpsBVr17dkOTECS6WFKZGcJk877zzzIQJE+zfWOqw2BW7UIsN7ggWx2eeecbAAUtnKkE5rlSpUsJmWPJQip2gbJOwpmXLliWuOeSQQ6zVD7n00kut9VUiAiJQPgnonOp/XaXA+Wcc+QjaGJEjVYciIAKeCWBVo7YaKeWJUUOwcFGLLCxYiHC3cxJWyHAJdK+F4+v++OOPpHFrlBWgUDWCIoiLJRZCEqqQkAPl4sEHH7Tvl5dEG8QSupIIxB2SdfLwww838+fPT7nqqdxVN2zYYLCwOUGJJi7OWUPjDTBq1ChD7KFEBESgfBLQOdX/ukqB88848hG0MSJHqg5FQATKiMBBBx1kPv/88xKjEydVtWrVhAocStpmm21m37/uuuvMzTffHGuLorjvvvsmvBusSViVkPXr15sddtjB/tu5Vgb7e+qppwwp8Ytdhg0bFos1dFkhd9ppJxuHlkpSKXBcj9vkV199Zbtybqco67hN4mIZFsoPhAuqp5qH3hcBESgeAjqn+l8rKXD+GUc+gjZG5EjVoQiIQBkRIOYsXLAbxcIpVkwrbIEjQYmz+pBg48MPP4zNHvdM9x2Z6JaIcaPUAIojCiTC37xO+nvqlSG33357iQQdZYQo52GDrqqTJ082J510knVLTaacwWPgwIEpWTK5SZMmWVaUaMD65iSRhRVLJxZPiQiIQPkkoHOq/3WVAuefceQjaGNEjlQdioAIlBGBHj16GFzqghJU0OIpcC47JPFvWOKcIkKmw0ceecScc845Se+GLIwU+OY/F+PmYsNQcFzafDIpBssKlBGinIcN1sUjA2itWrWSJnohqyQKWa6CJTWcxZO/WT+JCIhA+SWgc6r/tZUC559x5CNoY0SOVB2KgAiUEYG+ffvamKyg/PrrrzY2zUnYAkdmStz2UPQoGRBshzslqetTCXF0FPtu0aKFbYolkIQqxMe5BCpkakwnTizVWGX9fo0aNQylHBDHdscddzTr1q2LTQ1XUTJDEtNGVk6uyVX++uuvmKur64vi39kUFM91LrpeBEQgfwR0TvXPWgqcf8aRj6CNETlSdSgCIlBGBIYMGWJuuOGGEqOHC2iHFTgXZ7V69WpDUpKgXHTRRaVcMuPdGhkYcb3E8ob07t3buk9izdt1111tvTKseyg0xVzMG0V1yy23tHF/3BfMEIqZB8szoOBRugHWwZpxuX4swmt37rnnmvHjx+fara4XAREoYAI6p/pfHClw/hlHPoI2RuRI1aEIiEAZEcBV7+qrry4xOpaboBIRVgKwimEdQwkjHX5QSJfv6rolu6WxY8cakqFgeUNcCQL+HXQ5/OijjwwlEIpVKMmw11572emHi5hT1mHMmDGmSZMmpm3btl5u8YwzzjAvvfRSrG/q/uE2KxEBESi/BHRO9b+2UuD8M458BG2MyJGqQxEQgTIiQMp+UvcHJVgmgNfDCpyrz7ZgwQKryAWF7JXff/99yrshkQeFuz/55BPb9u6777b1yxCSmGCNQ4iBIxYuKIsXL7bJOnAzxJoUrlOXcvA8NiCej7g+hDmPGzcuj6MbQ0kI3CZhhoUP5btKlSp5nYMGEwERyC8BnVP985YC559x5CNoY0SOVB2KgAiUEYFXX33VnHzyybHRsbxhgQtKWIEjhgqlAEWucePGkcwcSxRFvBGUsmA2xWDZAt6nKPXChQtjbXELRLAILlq0yDRv3ty6LeZTcP10SpKLH/zhhx9KlGMgwQsupmUhLtFMsiLrZTEvjSkCIhA9AZ1To2ca7lEKnH/GkY+gjRE5UnUoAiJQRgTCqea32GILW1g7mQL30EMPma5du9pkGChLiQTL3gMPPFDibRKUfPPNN6UuIRU+7n4IVrk6derE2jiF0b0QVEKw1vXv39/G0k2bNs02wR3x2WefzSvRESNGGIp041JKpkni98IWynCB9LxOUIOJgAhUGAI6p/pfailw/hlHPoI2RuRI1aEIiEAZESBhSeXKlWOlALAekSkxmQLXs2dPc+eddxqKRZ9++ukJZ47V57nnnoslKqFmHPXlyD4ZFpS22rVr25cpT0DBbyfPP/+8ad26dezvsAKHRc5Z72hUrVq1WGHrfGDlPoNunCijKJXOPZQ5YKl855138jEdjSECIlDBCeic6v8DIAXOP+PIR9DGiBypOhQBEShDApQE+Oqrr+wMcD387bffkipwruj2008/nbTmG4oN/2Gto0g3LoQ33XSTmTlzZqx/yhgQy9iFO28AACAASURBVHbhhReWGLNbt27mvvvus68RNxZ0qQwrcGR3DCZioUg1xarzJWSQDKb9x710xowZJYa/8sorzciRI/M1JY0jAiJQgQnonOp/8aXA+Wcc+QjaGJEjVYciIAJlSODYY481b731VmwGLl7KvRAvbooaZljGksV0hfuhv0GDBpnBgwfbrtu0aWMmTpwY986pJ3fdddfZ93DDvOSSS2LtwgocFkTKITjZbrvtzE8//ZQ3ok8++aTp0KFD0vG454EDB+ZtThpIBESg4hLQOdX/2kuB88848hG0MSJHqg5FQATKkADWr9GjR2ekwFHAG2XsqquuSjjzeArcjz/+aJo1a2ZLCOBK6Yp2hzsZNWpULN09pQ569eoVV4Ej7oy+cOl0Qt04XEN9y5QpU2wR9DfeeCPlUNxP9+7dU7ZTAxEQARHIlYDOqbkSTH29FLjUjAquhTZGwS2JJiQCIpADAdwar7/++owUOBqfffbZZsKECRkpcDRGsUuVDfGxxx6LWfewrg0YMCCuAkcSE7I90j4o4VIIOeCJeykJU1q0aJF2t48++mgpN9G0L1ZDERABEciAgM6pGcDKsqkUuCzBleVl2hhlSV9ji4AIRE3gqaeeMi4Vv1OwgmMkUrZq1apl0/YnkngWuHTnjmLYvn172/zaa681uFQ6Cc4Hq9bq1attspSgEMfns5TA8OHDTb9+/dK9HRsDSOygRAREQAR8E9A51TdhY6TA+Wcc+QjaGJEjVYciIAJlSOD99983jRo1is0grHgdeOCBZsmSJRnPMBcF7t///rc57bTTYmPOnj3bNGnSxP4dVOAuuOACW5YABSko69evN7h5+hIsgkOHDk3ZPcWz9913Xzs/XDslIiACIuCbgM6pvglLgfNP2MMI2hgeoKpLERCBMiOwdu1as8suuyRU4Cia3bJlS/Pzzz+bDRs2pD3PXBQ44srI5uikZs2a1toXTtl/1llnmZUrV9qi4kFZs2ZNiXtKe9JpNuzdu7e54447kraGKfOQiIAIiEA+Ceic6p+2LHD+GUc+gjZG5EjVoQiIQBkSQCnie406ZSQ0IV4rLNRmo9YZhb7//PPPtGabiwIXtgoyIP1t3LjRbL311rHxTznlFLN8+XJbPDsoK1asMJRHiFq497/++ssmVQkXKQ+Ple9smFHfq/oTAREoTgI6p/pfNylw/hlHPoI2RuRI1aEIiEAZE6B490cffWSOPPLIEkW0w9OibEA4YQh12MKWJgprjxkzJuu7ogh2nTp1Slw/f/58W3T8oIMOir3etGlTs3jx4lJ13z7//PMStdmynkjgQpTHevXqmWXLlhmUMzJqJpPDDjvMMGeJCIiACOSTgM6p/mlLgfPPOPIRtDEiR6oORUAEioTAZZddVsry1KBBAzN37twSd4BbZtWqVbO+K2LYdtttt5TlALDGoXyGZcGCBeaQQw7Jevx4F7700kvmjDPOSLtPyiQcf/zxabdXQxEQARGIgoDOqVFQTN6HFDj/jCMfQRsjcqTqUAREoEgI9OzZ09x9990lZtu2bdsSWSD79u1ryNKYq1Ao/Mwzz8yqG4prn3POOVldm+iiW2+91WbEDEuNGjUMLpvUowtKLi6kkU5cnYmACFQoAjqn+l9uKXD+GUc+gjZG5EjVoQiIQJEQoO7abbfdVmK2xIMFE3qE67blcmuUN6DMQTZCdso99tgjm0tj1+AuOXnyZKtIDhw4MG58IMobCUtIqPLyyy/HrpUClxN6XSwCIpAlAZ1TswSXwWVS4DKAVShNtTEKZSU0DxEQgXwT6N+/vxk2bFiJYVHorr766thr/E2WxigEixeWr2xk/PjxJerbZdPHwQcfbBOkULSbRC6vv/56qW6cuyiFzZ955hkpcNmA1jUiIAKREdA5NTKUCTuSAuefceQjaGNEjlQdioAIFAmBwYMHm0GDBpWY7ejRow312Jzcd999hli5KGTUqFGmR48epbradNNNrUKVTLCYMd9s5ffff7dJU5zEi/XjPZKb0C6YeOXhhx82Xbp0yXZoXScCIiACWRPQOTVrdGlfKAUubVSF01Abo3DWQjMRARHILwFi2/r161diUJJ7nH766bHXHn/8cdO5c+dIJjZp0iTTunXrEn2RuIRsmWFrGElTvv/++1hbLGJPP/101vNYtWpVCRdMYt3iFTT/559/YsXFp02bZlavXm3at29vNttss6zH1oUiIAIikC0BnVOzJZf+dVLg0mdVMC21MQpmKTQRERCBPBO4/fbbS7hLMvzbb79t68g5GTdunOnYsWMkM5s3b57B8hUUFDdq1ZGoxMn5559vmjdvXmLc+vXrl8qOme6kqPdGfzNnzoxdsuWWWxqscmFRrFu6VNVOBEQgHwR0TvVPWQqcf8aRj6CNETlSdSgCIlAkBOK5NC5atMjUqlUrdgfUf6MOXBRCfTnKCTjB+rZhwwYzZ84cG9/2xRdfmG233da8+uqr1ir34osvxjJX7rjjjuaHH37IahqJXDfjdSYFLivEukgERMATAZ1TPYENdCsFzj/jyEfQxogcqToUAREoEgIPPvigufTSS0vMFiWLYt5OiInDIhaF4J5IvJuTZs2amRkzZsT+/uWXX8wWW2xhNt9889hrLvEIL6xbt85UqVIl46mgDKIkpiNS4NKhpDYiIAL5IqBzqn/S/6+9c4HXasr7+N+1SBmSW0qNXBsNEsrLDGNccgu9My5Drl3QCKNCysjIYBQaSslMpjFGRBOjjLwNXUh0MWWUmTCU0KhGZAzv57fMPvZ5znPOeS5rPefZz/6uz6dP55xn77XW/q6117P+639DgAvP2HsLvBjekVIhBCCQEAISzs4///xqvVX+s7gAJfPGzGuKebyNNtqo6naZNcrPrK5y4okn2pQpU9wlL7/8su2///55N9+5c2ebM2dOTvchwOWEiYsgAIESEWCfGh50qgU4+RiMGzfO+TIo144iiu26667O+fvSSy91ZjHxIj8LRRR78cUXTaeyHTt2tEGDBjk/hWxFEcEU8lo+DBs2bDCdyiq0tRzbiym8GMXQ414IQCDJBBSaP+7f1qxZM1uzZo1bs3/5y1+6R1Pwj7jZY7HPu9VWW9nHH3/sqtG6L7+4uko82fjEiRMLSgbepUsXmz17dr1d79u3b43E5vXexAUQgAAEAhJgnxoQ7n+rTrUAp6hlSnq6zz772Pe//30XxUumMQsXLrQDDjjAfXlGp7pTp061448/3vRFfsYZZziTmYceeshkuqMv6FNPPbXaaM2fP98OO+ww+/zzz51AqOhkjz76qPOXGD58uPXr16/g0eXFKBgdN0IAAgkn8PDDD7uE1VFp06aN/f3vf3dCnA7kpO367ne/6/UpdbD31ltvuTqj9upq4I477qha45VDTsnH8y1a52fOnJn1tu9973v2zW9+0wmVo0aNqnHYmG9bXA8BCEDAJwH2qT5pZq8rtQKcTFNkoiIh69lnn63ycZApigQ1OaRPmjTJunXrZjLP2WOPPWzVqlUuopg0aSo65d1vv/2c4CfBbMstt6yirLrlvzBt2rQqDZ18JQ4++GC32VAo6F122aWgEebFKAgbN0EAAhVAQEFCtC5HJReNWLGPLaFQh3IqssxYu3ZtnVXqYDBKayB/vXvuuSfvLui7SVYf2YqCp0gTSYEABCBQjgTYp4YfldQKcMrNI03a0KFDnRlkvETRv6JEqE8++aQT6pQUVX+LlxtvvNGuu+46l+snMo1cvHixE/Ky+Ur85je/sbPPPttuvvlmGzBgQEEjzItREDZuggAEKoCADte6du1a9SSyntBBWciiNv70pz9VNVGfz1k8ofbRRx9tsuDItygFwbx587LeJlP82267Ld8quR4CEIBASQiwTw2PObUCnMwkv/3tb9vhhx/uzCajKGP6Yj7hhBPchuDVV1+1Pffc0wYOHGg///nPnclk3HRHwyMtm6KF9enTx+6++243YjJp0e+6p3///tVGMQpJfdxxx5kEw0IKL0Yh1LgHAhCoBALKwRb3O5aJ+oMPPhj00eIaNR3aybe5rrJ+/XpTugGVdu3aZU2+XV+HZSIpa41s5dZbb62RC6+++vgcAhCAQKkIsE8NTzq1ApzQRk7v8oHTKalMIbU5kK+DtHCRo3z37t3tkUcecaeh8o2LF+X4kX9b/BT4Jz/5iSnZrO7J9I3TvTLB2Wmnnez111+vc4TjiWnjF0r47NChQ63mNeGnDS1AAAIQaBgCzz33nDt4i8rFF19cFbwkVI90sDdy5EhbuXKlO9DLDHCVrV2t8bp+0003dcm346kIcunnNttsYx999JG7tFWrVvb2229X3eYzUXkufeEaCEAAAvkQQIDLh1Zh16ZagBMyacl0mqoIlFFR+GmZVu68887uTxLuFDZafms6TY0XRbJUoJODDjqoKmdPz549naml7skWobJly5YuuIm0cXUVBLjCJjV3QQAClUsgsnqInvDqq6+2m266qewe+NBDD7VZs2a5fi1fvtxFOM61yF9a0TVV2rZta3vttZfzy46KzDkVyIQCAQhAoBwJIMCFH5XUCnBKA3DBBRe4yJAjRoxwZpM6IX3qqadMYZll/qL8PZF2TV+Yy5Yts912263aqEgQ22yzzaoJcBdddJGNHTvW+Uxk+5LNVYCrbfh5McK/GLQAAQiUJ4FXXnmlmiWEUrsMHjy47DorX2f5PKsoUFaukTEj/+zogWT1oaBYUYoE/V1+1nvvvXfZPTMdggAEICAC7FPDz4PUCnDSkElTJrOYSy65pBppmaecc845TjMnf4eGMqFEgAv/AtACBCCQLALxACHq+bBhw5xZY7mVIUOG2A033OC6lU9i8XjScN0rK45jjz22ms/bv/71ryofu3J7bvoDAQhAAAEu/BxIrQB32mmnOe3bokWL7Fvf+lY10vI1aN26tYs8OWXKFIKYhJ+HtAABCEAgJwIyZVdal6jcfvvtdvnll+d0bykv+vWvf23nnnuua1LfMfquyaVkCnAKnKUIx/rOikp9UTBzaYdrIAABCIQigAAXiuzX9aZWgJPJ5BNPPJHVtCUy0VEAEgUiySWNgKKgKRqaSi5pBIo5NebFCP9i0AIEIFCeBN58802XTDsqMi1UIJNyKy+99JJ16tSpqlsffPCBNW/evN5uZgpwvXr1cgG1lBcOAa5efFwAAQiUAQH2qeEHIbUCnJzeZSIp0xQlhlUgEhX5tOm0U9q5O+64w3784x+7RN677767vf/++1kTees+JfKOwkbrdxJ5h5+8tAABCKSPwIoVK6oCTOnp5W8sf+ZyK9KSKXrkO++847o2Z84cO/jgg+vspu7ZeOONq12jIC3y85MWT5GLZZap3KMUCEAAAuVKAAEu/MikVoBTeGadjiowiYQzRZpUEBMFHpEGTTniFEFsyy23dKOg4CbS2m211VYuAXijRo1cXjhFkpw4cWKNdAHz5893TpyKbinNnIKhTJo0yd544w0bPny49evXr+DR5cUoGB03QgACCScgTVaLFi2qnmL8+PGmgCHlWJQHVDnbVCZMmGBnnnlmnd2MR5+MLrzlllvsqquuso8//thFQtZ3U6aWrhyfnT5BAALpJcA+NfzYp1aAE9rVq1e78NNK0qowz/pSVMjmU045xXTqmZnr5/nnn7frr7/epQvQSWnHjh3dSWi2VAGqX4nABw0aZDNmzLANGzZY+/bt7corr6wytSx0eHkxCiXHfRCAQNIJrF271rbeeuuqx9BBmvzEyrGMHj3aevfu7bqWi+ZMibuVwDteylXDWI686RMEIFAeBNinhh+HVAtw4fGGaYEXIwxXaoUABMqfgJJib7HFFlUdfeyxx+zkk08uy44rF6isO1R69Ojh8o7usMMOtfZ13rx5duCBB1b7XOb8OlSkQAACEEgKAfap4UcKAS48Y+8t8GJ4R0qFEIBAQgjILH3TTTet6q0SXMuXuRyLfKMzc4cOGDDAbr755qzdVb64I488stpn+eSQK0cG9AkCEEgfAfap4cccAS48Y+8t8GJ4R0qFEIBAggjEfcCeeeaZGkJPuTyKgmJJW6j/46W2NACTJ0+uoU1csGCBdejQoVweiX5AAAIQqJcA+9R6ERV9AQJc0QhLXwEvRumZ0yIEIFA+BOICnHyTDz300PLpXEZP2rVr54JXxYsiGiuwVWZRoBOlDIgXRZ5UoC0KBCAAgaQQYJ8afqQQ4MIz9t4CL4Z3pFQIAQgkiEBcgJs7d24Nv7FyehSZd06dOrVal2oTOkeNGmV9+vSpulbC32uvveYiJFMgAAEIJIUA+9TwI4UAF56x9xZ4MbwjpUIIQCBBBOIC3MKFC23fffct295feumlpmTj8VJb6gOlHFDqAZWuXbva/fffb9tvv33ZPhsdgwAEIJCNAPvU8PMCAS48Y+8t8GJ4R0qFEIBAggjEBThpqPbcc8+y7b3yfl5xxRXV+jds2DAbOHBgjT4PHjzYhg4d6v5ezvntyhY2HYMABMqCAPvU8MOAABeesfcWeDG8I6VCCEAgQQTiApwiPSp/Z7kW5Rk96aSTqnWvb9++duedd1b7Wzzptz4o5/QI5cqafkEAAuVBgH1q+HFAgAvP2HsLvBjekVIhBCCQIAJxAW758uW26667lm3vlyxZYvvss0+1/p122mk2ceLEqr+9++671rJly2rXlHN0zbKFTccgAIGyIMA+NfwwIMCFZ+y9BV4M70ipEAIQSBCBuAD35ptvWuvWrcu295mJx9XRQw45xGbPnl3V50mTJtmpp55a7Rn+8pe/1BD8yvYh6RgEIACBGAH2qeGnAwJceMbeW+DF8I6UCiEAgQQR6Nmzp40ZM8b5vi1evNg23njjsu59XOBURxVdcunSpVV9HjJkiN1www1Vv/fr18/kO0eBAAQgkEQC7FPDjxoCXHjG3lvgxfCOlAohAIEEEfjkk09caP7OnTvbDjvsUPY9zxTgtt12W/vwww+rCWx33HGH+/3xxx+v4TNX9g9IByEAAQjECLBPDT8dEODCM/beAi+Gd6RUCAEIQCAYgUwBTr9//vnnVZrDiy66yMaOHevaf/rpp+2oo44K1hcqhgAEIBCaAPvU0ITNEODCM/beAi+Gd6RUCAEIQCAYAUWdHDlyZLX6V69ebdtss43725lnnmkPPvig+3nWrFlOs0iBAAQgkFQC7FPDjxwCXHjG3lvgxfCOlAohAAEIBCPw8ccfW69evWzChAlVbSxbtsx222039/vJJ59skydPdj8vWLDAOnToEKwvVAwBCEAgNAH2qaEJo4ELTzhAC7wYAaBSJQQgAIHABH7wgx/Yww8/7Fp58cUXrVOnTu5nmUwqbYBKXLAL3B2qhwAEIBCEAPvUIFirVYoGLjxj7y3wYnhHSoUQgAAEghPo3bu3jR492rXzxBNPWNeuXd3PMpmcM2eO+3nFihW24447Bu8LDUAAAhAIRYB9aiiyX9eLABeesfcWeDG8I6VCCEAAAsEJKFWAUgao3HvvvabgJSoymVy0aJH7ee3atda0adPgfaEBCEAAAqEIsE8NRRYBLjzZgC3wYgSES9UQgAAEAhEYN26cXXDBBa72wYMH209/+lP3s3zh/va3v7mfFZ1yk002CdQDqoUABCAQngD71PCM0cCFZ+y9BV4M70ipEAIQgEBwAtOmTbNjjjnGtXP++efbfffd536WyeR7771njRo1sk8//TR4P2gAAhCAQEgC7FND0v2qbgS48Iy9t8CL4R0pFUIAAhAITmDx4sXWvn17187RRx/tkpGrNGnSxNavX2+ZCb6Dd4gGIAABCAQgwD41ANSMKhHgwjP23gIvhnekVAgBCEAgOAH5t2299dauHQlyr776qs2fP9/2339/97e2bdtWmVIG7wwNQAACEAhEgH1qILCxahHgwjP23gIvhnekVAgBCECgJASaNWtm69atc4LcRx99ZLfccosNGDDAtX3hhRfamDFjStIPGoEABCAQigD71FBkv64XAS48Y+8t8GJ4R0qFEIAABEpCYJ999rElS5a4ti6//HL78ssvbcSIEe73X/3qV9ajR4+S9INGIAABCIQiwD41FFkEuPBkA7bAixEQLlVDAAIQCEhAvm9PP/101hYefPBBO/300wO2TtUQgAAEwhNgnxqeMRq48Iy9t8CL4R0pFUIAAhAoCQFFn7z//vuztjVp0iTr1q1bSfpBIxCAAARCEWCfGors1/UiwIVn7L0FXgzvSKkQAhCAQEkIKP/b0KFDs7b15JNP2nHHHVeSftAIBCAAgVAE2KeGIosAF55swBZ4MQLCpWoIQAACAQnce++91qtXr6wtTJ8+3Y444oiArVM1BCAAgfAE2KeGZ4wGLjxj7y3wYnhHSoUQgAAESkJAWrbjjz8+a1szZ860Ll26lKQfNAIBCEAgFAH2qaHIfl0vAlx4xt5b4MXwjpQKIQABCJSEQDyZd2aDL730knXs2LEk/aARCEAAAqEIsE8NRRYBLjzZgC3wYgSES9UQgAAEAhL44osvbJNNNsnaghJ7K8E3BQIQgECSCbBPDT96aODCM/beAi+Gd6RUCAEIQKBkBK666iq77bbbarS3dOlSa9euXcn6QUMQgAAEQhBgnxqCavU6EeDCM/beAi+Gd6RUCAEIQKBkBDZs2GCNGzeu0d5bb71lrVq1Klk/aAgCEIBACALsU0NQRYALTzVwC7wYgQFTPQQgAIHABHbaaSdbuXJltVZWrVplLVq0CNwy1UMAAhAIS4B9ali+qh0NXHjG3lvgxfCOlAohAAEIlJRAmzZt7M0336zW5po1a6xZs2Yl7QeNQQACEPBNgH2qb6I160OAC8/Yewu8GN6RUiEEIACBkhLo0KGDLVq0qFqbMq3cfPPNS9oPGoMABCDgmwD7VN9EEeDCEy1BC7wYJYBMExCAAAQCEujevbs98sgj1VpQhMqNNtooYKtUDQEIQCA8Afap4RmjgQvP2HsLvBjekVIhBCAAgZISkL/bDjvsUK3NL7/8sqR9oDEIQAACIQiwTw1BtXqdCHDhGXtvgRfDO1IqhAAEIFByAu+++661bNnStavok4pCSYEABCCQdALsU8OPIAJceMbeW+DF8I6UCiEAAQg0CIHJkyfbXXfdZZdccol169atQfpAoxCAAAR8EmCf6pNm9roQ4MIz9t4CL4Z3pFQIAQhAAAIQgAAEIOCBAPtUDxDrqQIBLjxj7y3wYnhHSoUQgAAEIAABCEAAAh4IsE/1ABEBLjzEUrfAi1Fq4rQHAQhAAAIQgAAEIJALAfapuVAq7ho0cMXxa5C7eTEaBDuNQgACEIAABCAAAQjUQ4B9avgpggAXnrH3FngxvCOlQghAAAIQgAAEIAABDwTYp3qAWE8VCHDhGXtvgRfDO1IqhAAEIAABCEAAAhDwQIB9qgeICHDhIZa6BV6MUhOnPQhAAAIQgAAEIACBXAiwT82FUnHXoIErjl+D3M2L0SDYaRQCEIAABCAAAQhAoB4C7FPDTxEEuPCMvbfAi+EdKRVCAAIQgAAEIAABCHggwD7VA8R6qkCAC8/Yewu8GN6RUiEEIAABCEAAAhCAgAcC7FM9QESACw+x1C3wYpSaOO1BAAIQgAAEIAABCORCgH1qLpSKuwYNXHH8GuRuXowGwU6jEIAABCAAAQhAAAL1EGCfGn6KIMCFZ+y9BV4M70ipEAIQgAAEIAABCEDAAwH2qR4g1lMFAlx4xt5b4MXwjpQKIQABCEAAAhCAAAQ8EGCf6gEiAlx4iKVugRej1MRpDwIQgAAEIAABCEAgFwLsU3OhVNw1aOCK49cgd/NiNAh2GoUABCAAAQhAAAIQqIcA+9TwUwQBLjxj7y3wYnhHSoUQgAAEIAABCEAAAh4IsE/1ALGeKhDgwjP23gIvhnekVAgBCEAAAhCAAAQg4IEA+1QPEBHgwkMsdQu8GKUmTnsQgAAEIAABCEAAArkQYJ+aC6XirkEDVxy/BrmbF6NBsNMoBCAAAQhAAAIQgEA9BNinhp8iCHBm9rvf/c5Gjx5t8+fPtw0bNtguu+xiXbp0sbvuusuaNm1aNQpvv/22XXPNNTZ16lRbt26d7b777ta7d2/r06ePbbTRRjVGa/Xq1TZ48GB77LHH7P3337fWrVtbjx49bMCAAbbZZpsVPLq8GAWj40YIQAACEIAABCAAgYAE2KcGhPvfqlMtwH3xxRd23nnn2fjx422PPfawo48+2rbcckuToPbMM8/YvHnznDCnor8dfPDB9t5771n37t2tTZs2TpBbsGCBXXbZZTZixIhqo7V27Vrr3LmzLV682Lp27Wr77ruvzZw5055//nnr1q2bTZo0qeDR5cUoGB03QgACEIAABCAAAQgEJMA+NSBcBDizW2+91fr37+8EsNtvv9023njjKuIS7lSiv51xxhlOU3fffffZ+eef7z7797//bcccc4w9++yzNnfuXDvwwAOr7r/66qvt5ptvtuuuu85uuOEG9/cvv/zSaeAeeOABmzhxop122mkFjTAvRkHYuAkCEIAABCAAAQhAIDAB9qmBAZtZajVw69evt5YtW1rz5s3tr3/9q22yySa10l6zZo21aNHCad1ef/31atdJo3bYYYc5U8p77rnHfSbhT3WrjRUrVjitXlSkydt1112d4PfHP/6xoBHmxSgIGzdBAAIQgAAEIAABCAQmwD41MOA0C3DySzvllFPsyiuvtBtvvNH+8Ic/2LJly2y77bZzwpX81aLy1FNP2XHHHed83e6+++5qo/Kf//zHtt56a3e9zCVVXnvtNdt7773dPU8++WSNUdRnEuTkR5fNd66+YefFqI8Qn0MAAhCAAAQgAAEINAQB9qnhqadWAyfTRgluV111lQsysnTp0iraCjDys5/9zH2mMnLkSOvbt6/94he/sCuuuKLGqMi/TVq8zz77zH02ZcoUO/HEE909d955c6Gr5gAAIABJREFUZ43r9Zmueeedd2znnXfOe5R5MfJGxg0QgAAEIAABCEAAAiUgwD41POTUCnAyeVTkSZlOdurUyWnW2rVrZ7NmzbILL7zQ/vGPfzit3AknnGA33XSTXXvttTZmzBj3WWY59NBD3X0ymdxiiy3st7/9rZ111lnuHgmJmUWf6Rpp7KSNq61EL0Dm5y+++KI1btzYOnToEH6G0AIEIAABCEAAAhCAAARyJLBw4UJr0qSJcyOihCGQWgGuZ8+eTiCTf9obb7xhO+64YxXhadOmOTPKI4880kWjlDZu0KBBNnbsWLvgggvqFeAmTJhgP/rRj9w9Q4cO9S7AzZ492wmeBx10UJhZkbJatdCoIBD7HXi4+uWp2mDqnylcYRqGQJhaWQP8coWnX55RbVI0bLrppk6xQQlDILUCnMwjb7vtNjv88MNtxowZ1egqWqQ0adJyffTRR5hQhpl7ZVMrqv4wQwFX/1xh6p+paoSrf64w9c+UueqfKfPUP1PmaRimmbWmVoCT9k1aOPmjTZ48uQZtRZ1ULjcl9iaISWkmY0O1wgIehjxc/XOFqX+mbDZgGoZAmFpZA/xyhadfnlFtcA3DNV5ragU4RZzcfffdnd9bPICJ4HzwwQcubYA+V9qAXNII9OrVy0aNGuXYKo2AgpN88skntnLlSqfNi0qURkBJwyUYFlJ4MQqhVvs98PTLkwU8DE8EDbiGI+C/ZtZV/0xZA/wzZZ76Z8o8DcM0s9bUCnACcdRRRzkft/vvv9/OPfdcx0bmk0oXoAAnSsatACYqtSXyPvbYY2369Okme18FQ4lKtkTe+uycc85xibwffvhh6969e0GjzIJTELZab4KnX54IcGF48qUI13AE/NfMuuqfKWuAf6bMU/9MmadhmCLAxQhI89a5c2dbvXq1nXTSSVVRKBUkRKkBZs6caU2bNnV3SHOmoCGrVq1yglfbtm2dBm3BggV22WWX2YgRI6qxlfnlIYccYkuWLLHjjz/e1aek3/rXrVs3mzRpUsEjzIJTMLqsN8LTL08EuDA8+VKEazgC/mtmXfXPlDXAP1PmqX+mzNMwTBHgMggsX77clBNOkSf/+c9/WsuWLZ2Apr81a9as2tVvvfWWXXPNNTZ16lSXhFvml9LWXXzxxVkTckswVD3KMyezzFatWjlNX//+/W3zzTcveIRZcApGhwDnF12dtTFP/cOGqX+mbDZgGoZAmFpZA/xyhadfnhzghuGZrdZUm1CWDjMtQQACEIAABCAAAQhAAAIQKJ4AAlzxDKkBAhCAAAQgAAEIQAACEIBASQggwJUEM41AAAIQgAAEIAABCEAAAhAongACXPEMqQECEIAABCAAAQhAAAIQgEBJCCDAlQQzjUAAAhCAAAQgAAEIQAACECieAAJc8QypAQIQgAAEIAABCEAAAhCAQEkIIMCVBDONQAACEIAABCAAAQhAAAIQKJ4AAlzxDKkBAhCAAAQgAAEIQAACEIBASQggwJUEM400BIF///vfttlmmzVE07QJgYIIfPnll7bRRhsVdC83QSA0AdbU0ISp3xeBaC1lTfVFlHrKjQACXBmMCAuM30H44osv7IorrrBVq1bZb3/7W9PvG2+8sd9GqA0CHghobl599dW2xRZb2PXXX2+sBR6g/rcKWPpjyZrqjyU1hSWgufrjH//Y/vOf/9g999zDmhoWN7U3IAEEuAaEP2/ePOvYsWMD9qDymh4zZoxdc8019uGHH1qzZs3sr3/9q+2www6V96AlfqLly5dbmzZtStxqZTc3duxYN1c/+OADO/744+13v/udNWnSpLIfugRPx7rqFzJrql+eUW1LliyxvffeO0zlKa01vqa2b9/eZsyYYdtuu21Kafh7bOaqP5Y+a0KA80kzx7rmz59vF198sb344ov25z//2bp06eJOizbZZJMca+CyTAIzZ860Sy65xBYuXGhHH320vf/++7Zy5Up78skn7dvf/jbACiTw0ksv2aWXXmpNmza10aNH2ze/+U1ONAtkGd0Wn6sHHXSQO2TYf//97ZlnnnGXYEJZGGDW1cK41XYXa6pfnlFtL7/8svuu0nfUo48+ah06dMBKpEjU8bl6+OGH21tvveW+s6ZNm8YBbhFsmatFwCvBrQhwJYAcNSH/gYkTJ9qAAQPsH//4h/vz6aef7sz8KIURkJDWt29fe+SRR5yg1rt3b/vOd75jw4cPN50ca2Hv3LkzX5B54v3ss8/sgQcesP79+9s///lPa968uQ0ZMsQJc5TCCGiuyrRHa4DmqjZxnTp1sh/+8IcmDefSpUutVatWhVWe4rtYV/0OPmuqX55RbVpTpWXX9/97771njRo1cuvBz3/+8zANpqDWzDW1T58+7kD8yiuvtKefftqkOdpzzz05dMxzLjBX8wTWQJcjwJUQvNT5p556qq1fv97uvvtut3C//vrrTvg45ZRT0MLlORbSYB5yyCG200472QUXXGCnnXaa7bvvvs7f7aabbrJBgwbZz372M+djRMmdgDbEmpO9evVyX3z9+vWzUaNGORPKe++91/bbbz++EHPH6a784x//6MwkW7Zsaeedd56bq9/61rec1v3ss8+2Bx980J566ik76qij8qyZy1lX/c0B1lR/LOM1yS9La4DedW2Ohw4daiNGjHA/6wD3iCOO4JAxT/R678Vtl112sXPPPbfa97984MX3/vvvtx49euRZc7ovZ64mZ/wR4Eo4VlOnTrW77rrLfvKTn9h3v/tdd0J0zDHHuBMj/axABgTcyG9Ahg0bZjJDO/TQQ61x48ZVN2szfOKJJ7rTzhtvvBGu+WG16667zpn3/vKXv3SChgJs3HDDDU4Y1s+K7kmQiNyhSuP+i1/8wrp27WqHHXZY1VyVsCzN5s033+w2eFoPWANy56orWVfz41Xf1ayp9REq7HNZhPz+9793h4r6zrrvvvvsoosusjPOOMPGjRvnNHKsqfmx1V5KLhMym4x//+ugUdY4+v/CCy9kTc0Pq7NeYq7mCa0BLkeAKwH0yL/tX//6l+nfjjvuWKVt06m8Nm63336703SwgOc2IFE463hYa7FTkQ+R/Im+//3vuw2x+FJyIxDN1XfffdedDkvrJoFi2bJl7oRT81dfimLLXM2NacTp008/rdpk6G/6J22xDnUuu+wyd7Bzyy235FYpV1WtoayrfiYDa6ofjpm1RGuqAmt98sknTmOkv2l91TqqoDsS5s4880zW1ByH4PPPP7dNN93UMdx8883dXfHvf5mqiuePfvQjGz9+fI61chlzNVlzAAHO83hpMyGBoUWLFs5vSCZ92Uq0AMnvRTba2ihPnz7d/U9Ak+rEcmGaKUx8/PHHzp9IYyBhrnXr1p5HOvnViZECP2y33Xa2/fbb2zbbbFPrBkJz8le/+pU7MZa5ym233eaieyHEVZ8H2ZhmzpSIWaRpk6O4tPDiKmFOGxMCmeS/BugO1tXc1iXW1Nw45XuVuD7//PPu+1/r6q677lpnFX/605+cBkkWORMmTHDuAGjga7779THNzPkmiwftq7SuSpOk7zZK/lzjdzBXy28GIcB5HJM77rjDfvrTn5pO2nUytNVWW9lVV11lZ511VlbBLBLUInttOTTLbpvyNYF8mUYncRqDk08+2UX4UyRFfaFSviYgcz4JYevWrXMHBgqqIRNJ+RTIPDLbJkJ59c455xybM2eOM63UvKYUx1R3z50712mKFfb6ueeeA2kGgXzXANbVuqdQvjxZU3N7JRU4S+anOsTRQcLOO+/s9gMy5ZcAUdvBrPziJLzJjFpBoyhfE6iPaW3CrqJQylxdFg6KTE2pTqA+rszVZMwYBDhP46TFV75BMok89thj3QL+0EMPOT8i/a5w9pklWnwkbOjkTUKffOF0ahQ3DfDUxcRVUwjT+EOecMIJjvuzzz7rIlOiLTK3ibj88stdSgAFzlEIawlm8sFQQI2BAwc6v8Fo05apCZJ2WYF4dGIsIU5pBSKtR+ImmKcOF8tU7//uu+/uhGkJc/qZ8hWBQtYA1tXaZ08hPFlT638blc9Rh2I6NJQ/tt5lWSwoumzPnj1d0LLa1tTXXnvNRaOVxYhM/7Qmx10D6m+9Mq8ohqnWgAMOOMAJbzrA1c+UrwgUw5W5Wl6zCAGuyPGQULB69WoXDVEatz/84Q/Oxj0q2iQ//vjjzr9Nfm6ZJdr8Rk63Oq3T9SqqNzIFTJNZRbFMo9MjRflU0A0JGgovTDEXVvnggw92Aq0iSyoqosoLL7zgTPjeeOMNJ9wpUmK2UziZCClEs3w2dNosDbPK2rVrnSCXRrPKYphG77X8NWSiIg2cTH/SXopdA1hXq8+gYnmyptb+Rr799tt24IEH2l577eUiSkZr6ooVK9whmSJ7KiqyDsdq+x6PgkQptYjMqFU++ugj27Bhg8tjlqbvfz17MUzjGngJzo899pg7RKcUxzXix1wtn5mEAOdhLORHpBMeCQuKMKUFRP/kXKvgD3Kk1SKupJJ1hQlXMt8FCxY4p9vddtvNmbi98847NmvWLGcKkKbig+lvfvMbZ/KnwBAKEIFvobkTXgkLUcRDbXSleZOmTX4GiuYlbbAc6+PBduJzTyeaOmnW5xKO5Ziv02b50Yl12vy3imWqzbUEZr33kydPNmmO07Zhy7a2+VgDVC/r6ld0ffBkTa05U+W7ru91HXzJR1hrqop8WRctWuR83JT3Teb80q5ne7eV1FuaOwltWkuVhFrCh76zZMmTtjXVB1OZr+qfeGofwPe/uTgLzNXK2UkjwHkYS4Wsl711dHoWLdCRyZ6+9C6++GIn5CnktcIFR0XXaMGX35EEtf/5n/9xG2OdvCmBsoS/sWPHus/TtIgXwzRiGznd6gtU9VHMHTAoRYC0bzLtyXT+jvwxFYJZG4i42Wl84yHt5rXXXuvm9N///ndThDWZZuh0ThuXNBUfTLX5k5ZYGw6ND8XcO8u66m8mFMOTNbX2cVCuMeUhlQ+xco9mfv/LtFKWCjr0mjRpUrU1NR45Ubkg5Ve8xx572AcffOAscLSnkOVO2gIbFctUe6WHH37YfvjDH7rDMVmMUMzlxWOuVs5MQIDzMJZS97dt29bly5KAJpOH+MIsM0htiOWoLHX+SSedVMNv6M0333T3Xnrppe4zCXJyNtfpcRqLD6biriigciaXaWuaI1FFm4roBE5h6yV4bLnllm56RZ9LEFNAEx0eKFiJ+GWeGCvClwRAmQWpaK4q+E7a/Ax8MlWkVK0LOui59dZb0cD914yKddXf6s+a6o+laooOt/7yl7+4dVLuD9L2RNF8ozQha9ascVr1mTNnukNauVtkaoMUdEOatsj/OK1rqk+mf/vb36xz5872ve99z5m2ptkH3idX5qrfdaSY2hDgiqEX2/gqR5ZOOKUtU2LOqESbvClTprgNmnyPFFQjXrRR1sZNJi4yX7vzzjtdzq20lohZMUzFTguNhAo5h8u3SD6KaS8y45FfhgQ3nfjGA2ZEmwoJENpI6DRZp8pR0ZeAtJpKPK05K8FYhwxpnqtiUwzTiK2CHSkwjPJC6SAn7cXHGsC6+vUs8sGTNTX7Wym/YAUv0/eNBDh9x2d+///61792miCZ8umaeNG7LxN/maazpn5FplimqkMBTPbbbz/n8y3hOW1uKNlma7Fcmavl9c2MAFfLeGizKp+gww47LCfbaeUaUTjgbt26uWhUCmSSeeIjbZps4SXAxQMVvP76626RkQlVpNUor2nipzelZBr1WJo3nYxSvv5iVKhqadB0UCDNcGTyGM1Xme/svffeTqB44IEHqpJPSzMsEwxFsVRQnhtvvBGs/91sFMo0DlCHPxdeeGHFM83Hv491tf7pUCqeaVtTc+WqiNGyQJAPvAI8yZT8G9/4RjUrHLFTTji5R+g7Sf7CUVHkaR2C9e3b11lFVHIpFdOIoTRv8vmmfEWAuVpZMwEBLst4ymdNJmZyKJb5Q22am7iZpE7flMdNGgppMOJRD6OUAFqgVbc0bZkJPmXu16RJk8qaXbGnKTXTtJhLyPRWJjsKmNO4cWNHPNuzx+eqNMVytte81gY5nmxe18l8Un6DmpOKsBgvK1eudO1og1KppdRM0zJXdfqbixacdTW3N6vUPNMyTxVRt1mzZvUOQnyeKuiTvvMVdEwRpaWRi4pSAuiQTIe7ShOiA9v4e6AgUDocU+CSSi2lZpqroFgJvHN5L5mrlTDSNZ8BAS7GZPbs2c5pWAKWIvNJyJo4caJTw2eW+EsTmZ4p51iPHj3cKZtO5GR7rWAkUdAS5c+SgCdTCTkqp6HANMwoK6qpcjrJ/yKKYNarVy/na5G5oGf+rs2CApDooEEOzfq5TZs21XIPSkPcvHlzl0evkoW1+OjANNxclamtDsS0FmqOai2MtBTx4Eysq/WPgeYpPOvnlO8V4qo1UfNUh6kyNZdmTMJWfWuqPr/nnnucKaRMKKVJk/l+/Ptffm3vvvuuM+ePUg3k28ekXQ/TMCOmAwMdiis4jsxu6xJYs81d5mqYcSl1rQhwZm4DrOAhilqkJJqK/ChbX2kq9KJkC+SggdLJmgSUxYsXO98VJTVW6H/5D8kETaYS+pteLoVtV56tY445xr14lV5gGmaEdVo7dOhQF5lMc6tdu3amRNA6GFDqCZnjSBiLn7hFc1UO9NKqKbKf/LY0T+WbKW2cokrq1FnaYr0HMgdWNERFRaz0AtMwIyyuOhzQYZZ8e7feemtTABxpjhSRT2ul5qzWRwlxkSDHupp9PODpf55qndSBlgQurataO2XRoMi6skSQP7vcGnSYq4Na+VHF56nWVAllWlM1b7VeKrWK9gMKWrbddtu5+pUeRGvq+eefX5Xnzf/TlEeNMA03DuvXr3euCzq8VYlSJGVrMS64aW4yV8ONS0PVnHoBTidmOo2Q+YL8T3TiJl+1wYMHuxdFmw+ZRmYWaT60+ZUfkTYkCg985JFHussUnl3+LAqeId82nTrr1E2ncXJmlnlaLmrvhpoUxbYL02IJ1n6/co5pE6DwyPJf0/xSkcmvEsAqktn//u//VqtABww6TJBvptJRKLiD5uarr77qgufI11PaYvl7KnS15rLMJGVeqYiUlV5gGmaEdVClQyv5oMi8TBHhFFhAhwUKoKP1UgFbZO0QFdbV2scCnmHm6SuvvOIOVrWW6tDqoIMOMkUw1Pe/Ao5kS0MTranDhw93gp0O0LRWyuVCVjgS2GS5ozkvAS4KTKQxlCaukr//NUow9T9XZZ47bNgwl95HFlw6DNMhrtbS9u3b16qFY676H4tyqTHVApxO2BRsRKfBMiXr0qWLbbHFFm5snnjiCRf8IjMvk06LteGNokYde+yxToiTJiQq69ats8cff9yd3MkcQ6d2+lKQ1kQnfJVcYBpudOVHoMAiCvUvM9wWLVpUNSbN2+mnn+40vZpr0Smo5qEEtxdeeME0V2V6FY88qS8FRZpUsBJtNDT/ZQI0cuRIa926dbiHKZOaYRpmILQGHnHEESafSc1VmZVHRWvEXnvt5SwfpPlQ7kEdcs2YMcOZBOl61tXq4wLPMPNUtcoCQXnClMpDczYqEszkt6a9gEwrFaBEf5Mwpn2B/NmyzVOtz/KD075AFg/yT1aSbv2e6fse7qkatmaY+uev73JZh3Xq1Mm59kiQk6JBQcX0HZ9ZNFenTZvmcrMyV/2PRznUmCoBLn7qpc2qHIsVpGHbbbd1udtUomvk+yNfDZlQyBQifq9eHi3Q0npEzsqZeV1UlzRzMkmTEKeTkkosMA0zqtlOaN944w23eMs/Taa78QMDaeVk7itBTpuEKLKkNh1axLUB0WZDJZqrcbt55YiSMKOi07xKLDANM6rZuC5dutTNIx2K/d///Z9rWPNN/zQ3o4TxMjGTdljaD9bVr8YHnmHmaWat0fqnw1vlZ33ttdfcoZj+rjGQZlgHXwr/v2rVKmdFI9cIWeXI0kGb5+OOO67amhofO0XzlcmbTF/jUadL83QN0wpMw3GXxYwOt7p37+78MnU4pvVVc0ya3aOOOqqGFk4Htpqr0iwzV8ONTUPVnBoBLlPAyub0Gfcbkl27tGraDGvh1kYjuifumBzfEGcOYqWbScA0zGtbF1cli5dJhEx7tJDLHPKRRx5xZsDaJEjTocMIndTpAELajngC82wHDWGeorxqhWmY8aiNq9ZIrZ06HNMGQn7E8sOQCa+K8mFJcJPJmcwsx40b5zYiUWL5tK6r8AwzT6Nas30nn3XWWc4MTS4R8mXL3BtEeTEl6I0ZM8YddMWjVKZ1TYVp6edqtPeM5qjS+mhe/uAHP3ApfmRBE9/HZkY3T/tcDTtipa89FQKcNrfSTGhySxMm9X5kHlabICfNmWzfdcoh0564CVA0TGl+GWAa5mWti6taVGAd+bhpYVZQCG2KtfHVJuTAAw90Ap02zNJyRAF4dF+kcQ7T6/KuFaZhxqcurpqfMoeUpYJOfxXMJNIKKzKdfDhlVjZ9+nRnSqk0LAp0UpfgFuYpyqdWeIYZi/Hjxzs3Bh1qxUv0/S0fWPlpKgK1tGuRT2a0N1BaEW2QtZ5qnirqnzbJ+jzuvxmm9+VZK0zDjEttXGtrTd//CpgjixwdLuhgLNshRZr3qmFGqjxqrWgBTg7xCkzy8ssvu9NgbXSlWZMZxKBBg5x5ZG1FGxCFupbgt2DBAneCXOkatVymJExzoZT/Nflw1XyUH6YipckuXpvkuO+GNiEyUZMPpz5P67yFaf7zMJc76uIqQS1KnPvss8+aUlssW7bM+Q/pQExmQIpy+t5779miRYtcJFRF7dMcTkMS82x84ZnLrMv/GqUD0mGtBC9tcjXPZFWTeWirYBAK4iQhT5tgBRnJLPLV1EGE/NoHDhyYf2cq5A6YhhnIXLlma10m6goIpXmrxOWK65DmA9swI1SetVa0AKcIe7IN1qIrZ2Sd8CoKZP/+/Z0fkAI3yMwsc7JHG14t1ArTqoiS8jGimItaCFP/MyFXrnH/NWndFNJai7ZO4vSztBzyvZSvnBLG6p9CtaexwDTMqNfHVWvsSSed5NJbyPxcB2WKbhoVWUHIN0P+wwq6o/81hxWEJ42HDfD0O08loOngVYcDinqqoE3y8VWwJgUfyyzyUVNKiyFDhriDL/m2yURSc1H/JNhJC9e2bVsXkVoBI9KmeYOp3zka1ZYv19p6IT9NrbuKnHrNNddUXRatp2lcV8OMWHnVWrECnLQT2rhGWog4dp0Ay4RHAp0CQyhkenyCRz/Lz0iCm6JHKU9c2tXQMA3z8ubLVb3QqbHCViuVgE6HVeL5tHQwoVyG0nKkJfJZfHRg2nBzVebmCsOudVVFOQeleVMgCPljSlCLijYd2nxEAlyYXpdvrbnMU3jmN34yyZVQLN9gRX5WcAf5tmnuSdOrgDmZG1pZNUgDrHVVAlqkRY60dTKdlBWO/I4VsTJtBaZhRrwQrtl6oqBROrSV/7t8i5VmQNFSV6xY4XyMKZVJoGIFOOUhOeSQQ1yIVSU9zAw8EuXN6tevn1vks/nCPfroo27Bls+R/IrSXmAaZgbky1W90MIsUwltTBTyPy6kKRy2UmPIJ07RVOOBIcI8QfnVCtMwY5Iv1/pOfqXR0PxVYB6lFkhbgWeYEZc/oTS9yu+mOSgrHJlAaj8gLUUU7CGelFsHuzqwlcZOh7cdO3as6pwipMoPLjKhzLZfCPMk5VMrTMOMRb5cM3sRKRakRZZ1mQ7I5KcZ+dNpP1CpkaXDjEhyak28AKdgI8qzEpVoYZXfmzaw8g3SSUTkQB99rpNPbX51OqzTYuVni16EaNOhMMCymVdib53mKaJaGgpMw4yyD67SGMuURyZp8u+QCZpOjhUpTUKdTNZknqY5rahUEuQqucA0zOj64Frbuqoe6+RZkf9k7qP5K7/NSi7wDDO6mVwjdwgd2Oo7PzJ1lAmkDmPlAz969GjnOpFZdK+sGZTjTdY7+nmfffYx+Scp+bz2B0o3IO1GJReYhhldn1yz9VC+tPIz1j5ARRo55YqLH0SEeTJqbSgCiRXgtBDL1EE51qQ2lgOnBLJ4kQCnMOry2ercuXPVR5GApvsVKU2O9joFySwy+VFSY9UhE4q4oNhQAxayXZiGoeuTa8+ePW3UqFFOY6wgEYo6pQVbaS50mqz3QT/LYV9+n5VaYBpmZH1yzbauaq7KXFK+SdJqyCxNPsZKj1GJBZ5hRjUXrmo5+q7Xeqlok4pEKQ3F8OHD3b4hm4ZYWgzNUbUhXzj5yG2//fbO/DLKpRXmqRq2VpiG4R+Sq3qs+fn73//eBYeSxU3Lli3dgW7cVD3Mk1FrQxNIpACnUwUtsjKDUF4hhfpXkYmE7H2lodCk1iTWaZpO0mQyqetVIi2c8rlI86bFWcmOo9QC0aDoxE2hriUcSj1dyQWmYUY3BFelEtC8VZk1a5Y7fNBhg4r8PXQoUckFpmFGNwTX+LqqwwUFiJDfW5MmTZy5mszZKrXAM8zI1sVV/pRaG7OZOMpqQdpezUlZKSh/Vnw/EFngKCCUtMeTJ092lg7aF/Tp0yfMw5RJrTANMxChuMZ7qz2AFA2av4oCPHTo0DAPQ61lRyBxApxMHjVZZdqgyXr44Yeb8gpJwFLI9B49ejgTCWnLojDWjRo1cqe8cl6OC2cyr1AQCJ1eKMO9bOYzP8/0nSu7EfTQIZh6gJililBc586dWyOypCL+6TQ5OqQI80QNXytMw4xBKK6Z6+qSJUtc4Cj5J0tTXKkFnmFGNheu0pTpYDebEKeQ64qQesABBzjzMu0jMkva/Ntgmty5qp5LgSErM2nc5BdPSQ+BxAlwEtqGDRvmwgQrd4uKNq4Kna5w1MqPpc8VQlgaNmnh5Hgscx7lfpNzp2zdFRpY/yInejmTK6pfGgtMw4x6KbnWFywizBOWvlaYhmEemmta5mc0OvBsuHnSZCO6AAAMpUlEQVQqfzVZIWQTxJQLVn6Xiiwd7RPk667DXgXRSWO+11zmKkzzn8+l4Jp/r7ijkggkRoDTBkBF4X1l2qCwqRLGZO4gZ2X5/+h0V35v+l1BTOSILMHs6quvdoKdcsBcf/311cZPQU6UI2bGjBnOdjhNBaZhRhuu/rnC1D/T6PCLddUfW+apP5bxmvLlqsAjcqXITP0joU4aJ6UXkpZOPsRz5sxxgc50mCtBJYpMGeZJyqdWmIYZC7iG4UqtNQmUrQCnqFHf+MY3nK9EFEFS3T/77LNtwoQJLhqUTCGiEp22yedN/+QLN27cOKedk42w7lu+fLk7fdOivW7dOleHEnXrtK6SfTEiRjANswTA1T9XmPpnqhrh6pcrPP3y9PVdJf9KuU1kK9oTKGG3/OCicskll7jAJvG9Rpgna7hai52rMM0+dnBtuDmd9pbLToCTUKW8bNKKKfqjzCTleBxFf5KtrwQwOWpKoyb/NpVIgJOJhPK46P/p06e7FAAqs2fPNkXwU6hVLdISDmU6oRxvithXyf4YMA3zmsPVP1eY+meqGuHqlys8/fKMavPJVf5ucouIm+/KckcRJpWMW0m7dQis/Ubc/z3MkzVcrTANwx6uYbhSa+4EykaAU6hV+a1pcVVIaTljSksm08emTZtWmUTqdwlwysmm4CPZAo9IqzZw4ECXW0hmEVGRwKaXbtmyZbZmzRqXFybyo8sdWXKuhGmYsYKrf64w9c9UNcLVL1d4+uUZ1VYKrjoQlnWO/N/23HNPtz9Qou9KLTANM7JwDcOVWvMnUBYCnHIDSZum8L4KNiI/tyg61OWXX+5MHRRdUomJFZhEgp4iTSpASd++fWvkZ5OWTREnlTpAKQQy7eDzx5S8O2AaZszg6p8rTP0zVY1w9csVnn55RrWF5hpZ58hf/qGHHnKHtzKZrOQC0zCjC9cwXKm1MAJlIcA98MADTkBTbjdFjFR0yPjJXIcOHZwWTiGpmzdvbs8884wzh1Q0SfnDKU+bin6XeaSclNu3b+/CqsrkMo0FpmFGHa7+ucLUP1PVCFe/XOHpl2dUG1z9c4Wpf6asqWGYUmvhBMpCgFPESKUFkACnCFCRzXqkOVPOFv1NfmyNGzd2TytBT35wMoFUZElFn4yKgpZIqJMppTR7aQthLQ4wLfylqOtOuPrnClP/TFkD/DNlnvpnyjyFaRgCYWplDQjDlVoLI1AWApwELNmny68tU9j65JNPnD+ctHBPPfWUM5eUkKcgJ3I+lnllp06dXCASpQFYuHChE+zkoDxlyhTnT5fGAtMwow5X/1xh6p+paoSrX67w9Mszqg2u/rnC1D9T1tQwTKm1cAJlIcDV1f1XX33VpIGTP5t83uLJOT/99FMXpCQKF7z99tvbZ5995kwp5aCssLeUmgRgGmZWwNU/V5j6Z6oa4eqXKzz98oxqg6t/rjD1z5Q1NQxTaq2bQNkKcJGgFqUNkPOxQv5Hfm7RY+n3uXPnOudkBTiRECezyUpOC1DopIZpoeTqvg+u/rnC1D9T1QhXv1zh6ZdnVBtc/XOFqX+mrKlhmFJrbgTKVoCLun/eeefZ448/7vzfFPo3KooopYAlMqfMXPRze/T0XgXTMGMPV/9cYeqfqWqEq1+u8PTLk+//MDx59+EajgA1l5pAWQtwGzZscL5vSrr9wgsvODYykXzuuedswYIFTiPXqlWrUjNLdHswDTN8cPXPFab+mapGuPrlCk+/PKPa4OqfK0z9M2VNDcOUWusnUNYC3Pz5861z584uOqUScL7yyiv2xBNPuBxw77zzjv35z3+uSiFQ/6NyhQjANMw8gKt/rjD1z5Q1wD9T5ql/psxTmIYhEKZW1oAwXKm1bgJlKcBFkSjvu+8+6927t0sHoAiVI0eOtHnz5tmJJ57ook+2adOG8c2RAExzBJXnZXDNE1gOl8M0B0gFXALXAqDVcQs8/fKMaoOrf64w9c9UNcI1DFdqzY1AWQpwUdfPPfdcGz9+vHXp0sUFKtltt93srrvucrnfKIURgGlh3Oq7C671Ecr/c5jmzyyXO+CaC6Xcr4Fn7qzyuRKu+dDK7VqY5sYp36vgmi8xrvdBoGwFOKUIOOGEE2z69Om2zTbb2JAhQ1zKAErhBGBaOLu67oSrf64w9c9UNcLVL1d4+uUZ1QZX/1xh6p8pa2oYptSaG4GyFeDUfZlJfvjhh3bttddao0aNcnsirqqTAEzDTBC4+ucKU/9MWVf9M2We+mfKPIVpGAJhamUNCMOVWusmUNYCXGRfzCD6IwBTfyzjNcHVP1eY+meqGuHqlys8/fKMaoOrf64w9c+UNTUMU2qtn0BZC3D1d58rIAABCEAAAhCAAAQgAAEIpIcAAlx6xponhQAEIAABCEAAAhCAAAQSTgABLuEDSPchAAEIQAACEIAABCAAgfQQQIBLz1jzpBCAAAQgAAEIQAACEIBAwgkgwCV8AOk+BCAAAQhAAAIQgAAEIJAeAghw6RlrnhQCEIAABCAAAQhAAAIQSDgBBLiEDyDdhwAEIAABCEAAAhCAAATSQwABLj1jzZNCAAIQgAAEIAABCEAAAgkngACX8AGk+xCAAAQgAAEIQAACEIBAegggwKVnrHlSCEAAAhCAAAQgAAEIQCDhBBDgEj6AdB8CEIAABCAAAQhAAAIQSA8BBLj0jDVPCgEIQAACEIAABCAAAQgknAACXMIHkO5DAAIQgAAEIAABCEAAAukhgACXnrHmSSEAAQhAAAIQgAAEIACBhBNAgEv4ANJ9CEAAAhCAAAQgAAEIQCA9BBDg0jPWPCkEIAABCEAAAhCAAAQgkHACCHAJH0C6DwEIQAACEIAABCAAAQikhwACXHrGmieFAAQgAAEIQAACEIAABBJOAAEu4QNI9yEAAQhAAAIQgAAEIACB9BBAgEvPWPOkEIAABCAAAQhAAAIQgEDCCSDAJXwA6T4EIAABCEAAAhCAAAQgkB4CCHDpGWueFAIQgAAEIAABCEAAAhBIOAEEuIQPIN2HAAQgAAEIQAACEIAABNJDAAEuPWPNk0IAAhCAAAQgAAEIQAACCSeAAJfwAaT7EIAABCAAAQhAAAIQgEB6CCDApWeseVIIQAACEIAABCAAAQhAIOEEEOASPoB0HwIQgAAEIAABCEAAAhBIDwEEuPSMNU8KAQhAAAIQgAAEIAABCCScAAJcwgeQ7kMAAhCAAAQgAAEIQAAC6SGAAJeeseZJIQABCEAAAhCAAAQgAIGEE0CAS/gA0n0IQAACEIAABCAAAQhAID0EEODSM9Y8KQQgAAEIQAACEIAABCCQcAIIcAkfQLoPAQhAAAIQgAAEIAABCKSHAAJcesaaJ4UABCAAAQhAAAIQgAAEEk4AAS7hA0j3IQABCEAAAhCAAAQgAIH0EECAS89Y86QQgAAEIAABCEAAAhCAQMIJIMAlfADpPgQgAAEIQAACEIAABCCQHgIIcOkZa54UAhCAAAQgAAEIQAACEEg4AQS4hA8g3YcABCAAAQhAAAIQgAAE0kMAAS49Y82TQgACEIAABCAAAQhAAAIJJ4AAl/ABpPsQgAAEIAABCEAAAhCAQHoIIMClZ6x5UghAAAIQgAAEIAABCEAg4QQQ4BI+gHQfAhCAAAQgAAEIQAACEEgPAQS49Iw1TwoBCEAAAhCAAAQgAAEIJJwAAlzCB5DuQwACEIAABCAAAQhAAALpIYAAl56x5kkhAAEIQAACEIAABCAAgYQTQIBL+ADSfQhAAAIQgAAEIAABCEAgPQQQ4NIz1jwpBCAAAQhAAAIQgAAEIJBwAghwCR9Aug8BCEAAAhCAAAQgAAEIpIcAAlx6xponhQAEIAABCEAAAhCAAAQSTgABLuEDSPchAAEIQAACEIAABCAAgfQQQIBLz1jzpBCAAAQgAAEIQAACEIBAwgkgwCV8AOk+BCAAAQhAAAIQgAAEIJAeAghw6RlrnhQCEIAABCAAAQhAAAIQSDgBBLiEDyDdhwAEIAABCEAAAhCAAATSQwABLj1jzZNCAAIQgAAEIAABCEAAAgkngACX8AGk+xCAAAQgAAEIQAACEIBAegggwKVnrHlSCEAAAhCAAAQgAAEIQCDhBBDgEj6AdB8CEIAABCAAAQhAAAIQSA8BBLj0jDVPCgEIQAACEIAABCAAAQgknAACXMIHkO5DAAIQgAAEIAABCEAAAukhgACXnrHmSSEAAQhAAAIQgAAEIACBhBNAgEv4ANJ9CEAAAhCAAAQgAAEIQCA9BBDg0jPWPCkEIAABCEAAAhCAAAQgkHACCHAJH0C6DwEIQAACEIAABCAAAQikh8D/A6I/CSvoOHqbAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Important dates in the 2008-2009 financial crisis')"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(1, 1, 1)\n",
    "\n",
    "data = pd.read_csv('examples/spx.csv', index_col=0, parse_dates=True)\n",
    "spx = data['SPX']\n",
    "\n",
    "spx.plot(ax=ax, style='k-')\n",
    "\n",
    "crisis_data = [\n",
    "    (datetime(2007, 10, 11), 'Peak of bull market'),\n",
    "    (datetime(2008, 3, 12), 'Bear Stearns Fails'),\n",
    "    (datetime(2008, 9, 15), 'Lehman Bankruptcy')\n",
    "]\n",
    "\n",
    "for date, label in crisis_data:\n",
    "    ax.annotate(label, xy=(date, spx.asof(date) + 75),\n",
    "                xytext=(date, spx.asof(date) + 225),\n",
    "                arrowprops=dict(facecolor='black', headwidth=4, width=2,\n",
    "                                headlength=4),\n",
    "                horizontalalignment='left', verticalalignment='top')\n",
    "\n",
    "# Zoom in on 2007-2010\n",
    "ax.set_xlim(['1/1/2007', '1/1/2011'])\n",
    "ax.set_ylim([600, 1800])\n",
    "\n",
    "ax.set_title('Important dates in the 2008-2009 financial crisis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "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
}