{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "hide_input": false
   },
   "outputs": [],
   "source": [
    "from preamble import *\n",
    "%matplotlib notebook\n",
    "import matplotlib as mpl\n",
    "mpl.rcParams['legend.numpoints'] = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluation Metrics and scoring"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Metrics for binary classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "data = pd.read_csv(\"data/bank-campaign.csv\")\n",
    "X = data.drop(\"target\", axis=1).values\n",
    "y = data.target.values\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predicted labels: ['no']\n",
      "score: 0.887540\n"
     ]
    }
   ],
   "source": [
    "from sklearn.dummy import DummyClassifier\n",
    "dummy_majority = DummyClassifier(strategy='most_frequent').fit(X_train, y_train)\n",
    "pred_most_frequent = dummy_majority.predict(X_test)\n",
    "print(\"predicted labels: %s\" % np.unique(pred_most_frequent))\n",
    "print(\"score: %f\" % dummy_majority.score(X_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.90278721957851804"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "tree = DecisionTreeClassifier(max_depth=2).fit(X_train, y_train)\n",
    "pred_tree = tree.predict(X_test)\n",
    "tree.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dummy score: 0.803729\n",
      "logreg score: 0.912013\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "dummy = DummyClassifier().fit(X_train, y_train)\n",
    "pred_dummy = dummy.predict(X_test)\n",
    "print(\"dummy score: %f\" % dummy.score(X_test, y_test))\n",
    "\n",
    "logreg = LogisticRegression(C=0.1).fit(X_train, y_train)\n",
    "pred_logreg = logreg.predict(X_test)\n",
    "print(\"logreg score: %f\" % logreg.score(X_test, y_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Confusion matrices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[8911  228]\n",
      " [ 678  480]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "confusion = confusion_matrix(y_test, pred_logreg)\n",
    "print(confusion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_binary_confusion_matrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most frequent class:\n",
      "[[9139    0]\n",
      " [1158    0]]\n",
      "\n",
      "Dummy model:\n",
      "[[8111 1028]\n",
      " [1024  134]]\n",
      "\n",
      "Decision tree:\n",
      "[[8809  330]\n",
      " [ 671  487]]\n",
      "\n",
      "Logistic Regression\n",
      "[[8911  228]\n",
      " [ 678  480]]\n"
     ]
    }
   ],
   "source": [
    "print(\"Most frequent class:\")\n",
    "print(confusion_matrix(y_test, pred_most_frequent))\n",
    "print(\"\\nDummy model:\")\n",
    "print(confusion_matrix(y_test, pred_dummy))\n",
    "print(\"\\nDecision tree:\")\n",
    "print(confusion_matrix(y_test, pred_tree))\n",
    "print(\"\\nLogistic Regression\")\n",
    "print(confusion_matrix(y_test, pred_logreg))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Relation to accuracy\n",
    "\\begin{equation}\n",
    "\\text{Accuracy} = \\frac{\\text{TP} + \\text{TN}}{\\text{TP} + \\text{TN} + \\text{FP} + \\text{FN}}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Precision, recall and f-score\n",
    "\\begin{equation}\n",
    "\\text{Precision} = \\frac{\\text{TP}}{\\text{TP} + \\text{FP}}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "hide_input": false
   },
   "source": [
    "\\begin{equation}\n",
    "\\text{Recall} = \\frac{\\text{TP}}{\\text{TP} + \\text{FN}}\n",
    "\\end{equation}\n",
    "\\begin{equation}\n",
    "\\text{F} = 2 \\cdot \\frac{\\text{precision} \\cdot \\text{recall}}{\\text{precision} + \\text{recall}}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "f1 score most frequent: 0.00\n",
      "f1 score dummy: 0.12\n",
      "f1 score tree: 0.49\n",
      "f1 score: 0.51\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/andy/checkout/scikit-learn/sklearn/metrics/classification.py:1117: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 due to no predicted samples.\n",
      "  'precision', 'predicted', average, warn_for)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import f1_score\n",
    "print(\"f1 score most frequent: %.2f\" % f1_score(y_test, pred_most_frequent, pos_label=\"yes\"))\n",
    "print(\"f1 score dummy: %.2f\" % f1_score(y_test, pred_dummy, pos_label=\"yes\"))\n",
    "print(\"f1 score tree: %.2f\" % f1_score(y_test, pred_tree, pos_label=\"yes\"))\n",
    "print(\"f1 score: %.2f\" % f1_score(y_test, pred_logreg, pos_label=\"yes\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             precision    recall  f1-score   support\n",
      "\n",
      "         no       0.89      1.00      0.94      9139\n",
      "        yes       0.00      0.00      0.00      1158\n",
      "\n",
      "avg / total       0.79      0.89      0.83     10297\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/andy/checkout/scikit-learn/sklearn/metrics/classification.py:1117: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.\n",
      "  'precision', 'predicted', average, warn_for)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(y_test, pred_most_frequent,\n",
    "                            target_names=[\"no\", \"yes\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             precision    recall  f1-score   support\n",
      "\n",
      "         no       0.93      0.96      0.95      9139\n",
      "        yes       0.60      0.42      0.49      1158\n",
      "\n",
      "avg / total       0.89      0.90      0.90     10297\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, pred_tree,\n",
    "                            target_names=[\"no\", \"yes\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             precision    recall  f1-score   support\n",
      "\n",
      "         no       0.93      0.98      0.95      9139\n",
      "        yes       0.68      0.41      0.51      1158\n",
      "\n",
      "avg / total       0.90      0.91      0.90     10297\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, pred_logreg,\n",
    "                            target_names=[\"no\", \"yes\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Taking uncertainty into account"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from mglearn.datasets import make_blobs \n",
    "from sklearn.svm import SVC\n",
    "X, y = make_blobs(n_samples=(400, 50), centers=2, cluster_std=[7.0, 2],        \n",
    "                  random_state=22)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "svc = SVC(gamma=.05).fit(X_train, y_train)                                     \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
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     },
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     "output_type": "display_data"
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r5h3tIr0mv0om3/FZD2cX9zNY0Xzzmhz3UTjWziF7iD3mA0BrAHwb/fxrXCGs4RIppCL55fRiFfIRTte5DkMHSdyct7jEP11Dr3WTxvrzkRZz4d9cEKfyKEviZz/yrye5nsn1ndJaDhMRd8lPaEhhHUR+V585HvZ63uhIZQhhdpzKqo2hHALnLnXTEJDHf8cZ1shhBBZSLwAa2KUx74EcH3EsvFIjwArVg+sRH49GuO2b3zE8mg9sBI9B7EufF6AM4eCSacoxxEiE6lMT4SX4PRKGQinqIlUaH6Qr+Hc6KAiIj3HpAUc79kB4B5jebSeCLfH2HfkL9dVKeQehOMNK+HMUwI4IfY+OL0mIv03Ews5O2K9qSjr2Rvtte4WZd/5cH5xfxeO74ZI9PxX5vVMpCdC6LlV9F2SA2e4S7RJ3H+GJnHPVuR78ZHvZa/vtUL05xW6to6sJ0J1xjjEpqW7zpIoj/0FzjxiQggh6hh/RPiXWYhQqBQtwNqO8vNE3YHwu7YAqQmwQuP3I7uQh36JrOjLtyGcrtnXRixfg/LBUqLn4DGUXaSZvI7yd1W5AOUnixciU3kBic0Fsw6OBzWLs7/b4BRhlZkLJhp/hjMZb4hIr7nfbU+Bsaw+nDlG7o84VlUKudPhFLvPoOyXchvOXClPwgk6fMb60Qq5WP5SlUKulXucRVEeq2ohVx/Oa3h+nDZEY4m7z1AvkkTPf2VeT/O9swDlh7ZbcHpQJTIXzENw5t0xz8Ecd9uBcbYVmYt8r2Lke5Uj03wvGl44w/1ujlh+k9tGbwXb5sJ5T0SGcblw2q3h2EIIUQdZCudL6VQ4oU9o3oWKemD9Cc7ta0+DM/HmdXDuulKVACuI6gmwcuDcNXATyu6g8meU3YUwcm6CSC6A0706NLTvbES/C2Gi5+BKOF++R8MZJtjdXX6Je5yz4QzTvBjOnXMUYIlsYRKc9/gGOL8kz4fzOfwK4RfaDeBcHG+EM0xhPJz5P1bAuftRiI5wflX+BM5F9ng4gUBFd+P6PzhFwww4/hKaRPg3xjqRXtPXXedlOMM5Zrr/343khnLEohfKhpBMM5b/1V3+dMT60Qq5WP5SlULOglNUPA/nnA0G0MR9rKqFHOAM594HxzMPh+P/x8Hp0XqMu875cH5cmQ3n1/vj4Pjrf4z9JHr+K/N6mu+d0HfJl3DOZxGc93Kid+PqD2felj/D+R49Cc4EyvfG2U5kNvK9ipHvZbfvxeIUOJ+LC+E899C19qkR690MZ/ijydXusX8H53r7cDjBVSnC76wphBCijpAPp3v6NjhfBqEvsop6YDWFE+Bsc3UHnC/7aAHWx8bfHd11EumB9QnCf62p6MLkQMSyzgAegfNFvRXOxc5qd/v6qBgbzhfr1+72/4Azn0kpnIngQyR6Dlq6bdnhPha6wPDD6cG11X1sA8rOj3kcITKZ2XBudPAznF//Z8D5DPwjYr2GcOaV+xjO3HJbADyLsrszhegMx6++gRMOfITwoizSc5bDmdz2Wzif5w/gfL7MOUoivQZwhrQ8AWfumJ3u/yPveHQrgM+jPOenozy/WGyG83zzjWVnILoPhPwhEX+pjF9G43A4vUj2RhzzaTivSySR5zB0nGiFHOAUrv+A0+tiF5zw/iY4Xgs4hf/f4RT9P8M5zzcg/E61lTn/ib6eH0cs6wTn/O6C49VXoayXbyKF3Gg4E1L/BOe1vgKO94vsRr5XMfK97Pa9WCyEE9j+DOe5nxJlnVtR/rWy4fTcex3Oa74VzmsebY5eIYQQImt4BM5FnxBCCCGEEEIIIcRBzoXTDfUHOL8a/R1Ol3qTfnB+1dgFp7uqJjYV1cFyOL/0jIfzi9qdcH45WpjCNgkhhBBCCCGEECIN6QanezTgTNB3Jpzu0Za7rB6cYVoXwZmMrw+ceYuW1W4zRRZyOpy5JXbC6W7/Bpx5KIQQQgghhBBCCCFi4kPZ+PbQnTTmwQm0zLHiS6FhXkIIIYQQQgghhBCiFpkO4Hs4dxA5AOD/GY9dCWdYockIOCFXvVppnRBCCCGEEEIIIYQQLo3gDA080lh2E4B7ItYL3e2tTcRyC0BbOLcdliRJSlZtUTaMOVuQP0qSVB2SP0qSJEVXNvqjECIOFpwJ3fu6f1+JxHtgtQVASZKkalBbZBfyR0mSqkvyR0mSpOjKNn8UQsTBC2A3gJnu33NRfg6sZYg+B1YDANy0aRN37NiRUVq0aFHK21AX2pyp7c7ENmdquzdt2hS6AGlQgz6XChoA4OSlmzht1Q6pJrVCKqdUvyZStejUy+SPUjUo1X6Ubkr16yFViyYvzVp/FEJEsBRAC/f/zQHcAGA7gJbusnoAvgJwIQA/nJ5ZXyD6XQgbAOCOHTuYaSxfvjzVTag0mdhmMjPbnYltJjOz3Tt27MjWC5AGADht1Q6W/JpSTehXUkJK9eskJa1lv5M/Skkq1b6TKUr16yQlrWmrstYfhRARPAxgM4CdcIKq/wMwKGKdPgCeg9Mz62sA58TYlwKsWiQT20xmZrszsc1kZrZbAZaUtFJd+GSKUv06SUlLAZaUtFLtO5miVL9OUtJSgCWESIaMDbAee+yxVDeh0mRim8nMbHcmtpnMzHYrwJKSVqoLn0xRql8nKWkpwJKSVqp9J1OU6tdJSloKsIQQyZCxAZYQIj1QgCVVSqkudrJdqX59pTApwJIqpVT7R7Yr1a+vFCYFWEKIZFCAJYSoEgqwpEop1QVMtivVr68UJgVYUqWUav/IdqX69ZXCpABLCJEMCrCEEFVCAZYUV6kqVs42tKYalOriS0VdxkkBlpSQUu2R8kf5YwqkAEsIkQwKsIQQVUIBlhRXqS7OVKCpQEuRFGBJCSnVHil/lD+mQAqwhBDJoABLCFElFGBJcVWbhVh1FWN1vWhT4VYtUoAlJST5Y+Yp1e+ZLJACLCFEMijAEkJUCQVYUlzVRjGhAk0FWhpKAZaUkOSPmadUv2eyQAqwhBDJoABLCFElFGBJcVUbxYQKNBVoaSgFWFJCkj9mnlL9nskCKcASQiSDAiwhRJVQgCXFVDYVYiraVLQlIQVYUkzV1Gc03f0xmz0y1e+pDJMCLCFEMijAEkJUCQVYUkzVZHGWzgVaqosoFWhpIwVYUkzV1Gc03f0xmz0y1e+pDJMCLCFEMijAEkJUCQVYUpjqclFW1wq5VL/XMkAKsKQw1bQ/yiPTR6l+r2WAFGAJIZJBAZYQokoowJLCVNMFWi0WToNK/sQGLUYyr2EfdhtxLqev2KPiTAVapaQASwpTTftjLXrk6BP+zWYdA/TX78l2h57EwtO/UoAlf6yUFGAJIZJBAZYQokoowJLCVNMFWi0VZwMDd9LyNCFwLYEHaHsGsXWP42s1QKs1qUCrMSnAksKUJQHW+JPeo+0pILCWwN9o2UfRX78bi1fuTb2fyR8zRgqwhBDJoABLCFElFGBJYcqSAKugySACNxOgqy8Iy8spi7ekvqBSgZYxUoAlhSlLAqxOA5fSsn9p+GMpbW8XDjniL6n3M/ljxkgBlhAiGRRgCSGqhAIsKUxZEmDl5nci8LhRoO0hLB8nLNiY+oJKBVrGSAGWFKYsCbBa95hD4BzDH0lPzhj2n3ZT6v1M/pgxUoAlhEgGBVhCiCqhAEvKiKJstaGV8dWx/xLanvEEthHYR2At8xr0YGBFaeztkmlPAm2pVtVU4Zbq92CaSgGWlI3+ODhwH21PGwIbCQQJ/B8ty8fJp3xZvf5Y2x4pf6xVKcASQiSDAiwhRJVQgCVlY4E2bckONm0/jbByadkN6K/XhWPnvll9xY8CrDohBVhSNvpjYEWQnQeuoGXl0vY0pcfbkIOK/1T9/qgAK6ulAEsIkQwKsIQQVUIBlpRuBVrxqv2csuQbBlaVVrkImrjgfxx7wusMnHmgZgqmFYaWV4/GznmTHfsuYpvuczn08A0MnBEsezyZAk4FWtJSgCWlmz8GVgc5del3zoTrVfTHKadt4ZjjX2HRst01FypVsz8WLvyaXYedw1Zdj2Xfiddy+pKfq+aPiXhkqt+DaSoFWEKIZFCAJYSoEgqwpHQq0AYG7mKOvzUBMDe/I4fO/GtqejqlKMAacdQ/adn5tKyFBM6m7WnO7sPPV4CVIinAktLJH8fMfZUFjfsRAG1vQ/YYvZ6BVcHU+2AtBViFC79ijr8Nbc90AhfS9hzKJm2nlIX8CrBqVQqwhBDJoABLCFElFGDVUaVRUXawOJv3Gi07n8CDBHYSuIWWncdJCz5J39BpaSW0OL4athhH4DJjcuVXadl5nHbKjvB9xWpPsmFWqt+PaSoFWHVYaeaPRWfuptfXnMB5BL4n8CxtT0sODtyXvv5YzR7ZdfBa2nbAnbeLBH6k7WnGETOfLr8v+WONSwGWECIZFGAJIaqEAqw6qjQMsLoMW03Lmh92ZyzbO529x/2/9C3QqjnAyvG1IfB82O3tYfk4fs4HCrBSIAVYdVhp5o9Dj/wrPd6uRnhDAuvZvOOM9PXHavbIlp2OJnBJ+N0TvRPZb+KNCrBSIAVYQohkUIAlhKgSCrDqqNIwwOo2Yi0t+5iIAGsiD534u/Qt0Ko5wGrZ+WjC+qVRpN5Jr68lixftVYCVAinAqsNKM38cPusx2t72Tqh90CPPZcsus9LXH6vZI/uMuZq2px+BXe7z/4CW5eP4499TgJUCKcASQiSDAiwRl9tuu42HHNKXjRq14gknnMTvvvsu1U0SaYQCrDqmmgquqqFAm7BgozuE8Lfu7d0vpO2tz8LTNtdc0XWGoaoGUKfF0cnxNfGYj5nrb0+Ppyc93lG0bD+HTttQfl/mcWMVbRUVapHFWqrfl2kqBVh1TGnsj8Ur99FXrzNhnUzgXQJ/omU34PAjH6tcMJWu/piAR04/8Sc2bjGBtt2CHm8hLcvPrgN/HX1fifpjImFWqt+XaSoFWEKIZFCAJSrkvvvuY25uEwK3E3iWubnTOXToWAaDwVQ3TaQJCrDqmNK4QCtZQx529BOs12QQLSuXDVqM5Kjj/lWzvQbSLMAKFWmDJ9/P/mNvZuGczRUXZwqwalQKsOqY0twfJ578EZt2mE7L9tFfrxsHFN1R+Z5V6eqPCXpkYGEpD5v+JPuO/iPHH/Vu7H0pwKpxKcASQiSDAixRIUOHjidwtdHdfCe93ny+++67qW6aSBMUYNUxpWuBtprJ3RI+XlEWrwBLtuiKVlydFEPzo2huHEXbZr6xT/O4ZruiFWuxCrXKFGjnxlGq39c1JAVYdUzZ6o+xPDJT/TGWR5r7TdQfY4X98se4UoAlhEgGBViiQnr1GkLgDiPA2s/c3Cb897//neqmiTRBAVYdU7YWaFkeYBUd/yP7j7yJPYdcwrG/eEMBVi1JAVYdU7b6Y5YHWMVz93PIhIfYY9CFHDblUQZOLFWAVQtSgCWESAYFWKJC1q+/lH5/bwIfEfiZlrWWrVp14oEDB1LdNJEmKMCqA0rXoizZAi1aUZbIUJd4BVgyRZdZUB0fQ8e4mpWcJpV8zlxfe3o8g2nbR9Gy8tlr8G+i9zqIVqyZhVplCjSzAFsXR1larCnAqgOqaX80PTJV/mh6ZG36o+mR8fwxSY8snrWXjZtNpO3pQMs+nrbdii3azGRgXmli/mh6pPyxUlKAJYRIBgVYdYQvvviCTzzxBLds2VKp7fbt28f580+mbXtpWR527tybb7zxRg21svI88MADnDQpwIkTi3nfffelujl1EgVYdUAKsDI6wGrf+WRa1mzjzoQv07J8nHLMtwqwalgKsOqAFGBldIA1YPgdtD3djDsTbqNtt+SwyY8qwKphKcASQiSDAqwsJxgMctmylbTtHObnd6HHk8tLLrms0vvZvn07P/nkk7SavP2qq35Hn68ZgUsJXEafrzmvuOKqVDerzqEAqw5IAVZGB1gF9QcReNAYCk7ano4cMfVpBVg1LAVYdUAKsDI6wOrUbSmBZWH+aNnHs8fACxRg1bAUYAlRd1gP4G0AOwB8BeBPAAQSrUEAACAASURBVNpFrNMPwLMAdgH4EsC6GPtSgJXl/P3vf3dDnv+6X8z/odebz9deey3VTasSwWCQjRq1JPA346Lj72zQoDlLS0tT3bw6hQKsLFVtFGW1GWBVpiiLN19LrAIs3lws8UKpIw39IopKklObtnMJa4Hhle/RsnJZOONrpw1mG6MVa+a5iTUfVjJFWSxlUbGmACtLVZv+WBsBVjx/ND2yNv3R9Mh4/pikR/YbcANtuy+Bva4/7qJtd+CQ0X9JzB9Nj4znj6ZHyh8VYAlRh7gYwEAAXjgf+LsBvGE8Xg/A1wAuApALoA+ATQCWRdmXAqwsZ+nSZbSsRWG/LPl8R/GSSy5JddOqxL59+9wvvc+M5/YFAXDPnj2pbl6dQgFWlkoBVtYEWBMm/5deb1Pa9lQCp9G2m7BLz1+VtUEBVo1JAVaWSgFW1gRYRYHdrFd/sBtinUHb052Nm0xg8dH7FWDVsBRgCVF36Q+gFEBD9+95ALYAsI11lgL4KMq2CrCynPXr19Pvn2KEPEHm5w/gLbfckuqmVZlhw8bRtpcQKCVQSts+g0OGjEl1s+ocCrCySCrKKh72UtHwFrMAizWkJVoBllCRFXRVamh/JUQWFm5mz57r2bnzGTzssCcYCATL9m+2MVqxZp6bWMMJQ++hdTF0fhTFWjeLCjQFWFmmTAr2Exk2mKg/mh5ZVX+sbICfsD8Gk/bHoqLd7NfvBnbqtJQDBtzO6dP3JO6PpkfG88dYHhnNH2N5ZBb5owIsIeouqwF8Yvx9JYC/R6wzAk7IVS9iuQKsLGfLli1s2LA5vd75BO5hTs5MtmrViTt37kx106rMBx98wFatOtLvb0u/vx1btuzA999/P9XNqnMowMoiKcDK2gCrQinAqjEpwMoyKcDKygCrSv6oACtpKcASom4yGcBOAIXGspsA3BOxXk84AVabiOUKsOoAH330EefMOZGHHjqcp5yyiF9++WWqm1Rt7Nu3j08++SSfeOIJ7t27N9XNqZMowMoiZUJRlmyAVdWi7CTGH+pSqeIrXii1x9BuVzsMbTf0raHtUbTbUJyizSzW5pNTjvmGXQeuZdM2AXYduJZTFnxTdu7iBVhmIXZBFMUq1LKoQFOAlWXKJn80PTKePyYyRDBRf0wowI8XSkXzR9Mjq+qPMTwywh+LT9jLPsN/z2btDmf7nqdw/PHvVeyPpkfG80fTI7PUHxVgCVH3CAD4HsDhEcvVA0vUWR544AF269afBQVNWFJyFD///PNUNynrUYCVRVKApQDLKNCKjv+R/vyutD1TCFxN2zOF/nrdWHTqjwqwEpQCrCxTNvmjAqwqB1gt2x1F29OLwBW0rIW0PfU47ri3FGAlKAVYQtQtjocTXk2O8thclJ8DaxkqmANr0aJFXL58OZcvX87HHnssRWWwEFXjqaeeYm5ufQI3EXiZXu8J7NChO/fv35/qpmUdjz322EHPWLRoUbZegNS9Ak0BlgIso0DrO+KPtD2D3XkG6cw16B3EfhOvV4CVoBRgZZmyyR8VYFUpwBo/411aVh6Bb8vmmbUWs3XXOQqwEpQCLCHqDosBbAcwKsbj9QB8BeBCAH4AfQF8Ad2FUGQ5hx9+NC3r18aE9fvp97fhk08+meqmZTXqgZUFyqSiLJECrTLzuixyFa8om8vo87ZEDauiFV+xCrBoxdeOiKJri6uvDH1u6JMoMh/fYihUtJkFoNF24/l0PfRswjop7C62lnUiuw75Vfk7boVe63WGYhVlNRFgJfverOHPlgKsLFBtBvu16Y+mR8bzR9Mjq+yPrIQ/xgrwo/mj6ZHx/NH0yGj+aHqk0W7j+Qwb/zd6PN3D/BG4lQ2aj4ntj6ZHxvPH6g6w0tAfFWAJUXcIAtgL4EdXO91/zUCrD4DnAOwG8DWAc2LsSwGWyBomTy4hcHnEHRe7ccOGDaluWlajACsLpABLAVaUAm34xMdp280IfOF66ue0Pc04fMbjCrASlAKsLJACLAVYUfxx6lHf0bL8BJ5w/fEn2p5R7Db0HAVYCUoBlhAiGRRgiazhzjvvpN/flsB/COwhcDnr1WvCXbt2pbppWY0CrAxVthVlyQ6LOdVVvKLMHAITd6jLPkOxAqpow1uiFWJfGQXXR4Y2GnoviszHze1C+zQLtejDZgJHBdmh82m0LD893hG0LD879D6NgUVB59wlG2BVtSirqfdrDXzOFGBlqGrTH2vKI+P5o+mR8fzR9Mgq+6PpkfH80fTIeP5oemQ8fzQ9Mpo/mh4ZY1jhLLL/kFtpWbn0eIfQtpuxQfORnHbyjtj+mEiAFS3Yz1J/VIAlhEgGBVgiawgGgzzrrF8zJyePANiuXTe++OKLqW5W1qMAK0OVwQFW0Rm7WLxyvwKsGg6wQr0oxs14hwPH3s3xM94NP3cKsOJKAVaGKoMDrOln/szpZ/6sAKsWAqySWWRhyWYOGnsPR0x7hoFFpRX7owKsMCnAEkIkgwIskXXs2rWLn3/+OUtLS+Ouu3//fm7YsIG/+93v+MYbb9RC67IPBVgZqgwrykrWkBMWfsiGrcYQAG1vA3Y77DwGVgQrPyzGnLB9oav5ho4zZE48HLcoCw05SWSy9coMC4xWlL1t6C1Dr7syHzeLttA+zWLQLCKN5xl63ua5Mc9dvADLVLJFWW0ECTVYrCnAylBloD8WnfEjW/eYQ1hewvKwVbfjOG3Jjtj+aHpkPH80PbLK/mh6ZDx/TGRYYLRgP54/mh4ZzR9Nj4zjj6ZHxvPHWB4Zbzh1lvqjAiwhRDIowBJ1lh9//JH9+w+n39+BeXkBer35XLNmbaqblXEowMpQZViBFlh1gP763QhrEYGvCDxP29OB/abcoABLAVbaFmgKsDJUGeaPJWvINr3m0faMJ/ABgY20PRPZpsdcBVgKsNLWHxVgCSGSQQGWqLNceull9PuHufNlkcBGejw+bty4MdVNyygUYGWoMqxAGz3nJVqeJgT2GTdq+CMbthijAEsBVtoWaAqwMlQZ5o+BVQdoWbkE3jb88V1aVg6Ll+9TgKUAKy39UQGWECIZFGCJOsuUKb8gcEXYLZALCkbz9ttvT3XTMgoFWBmqDCjKTI054RVadiMjcCaBa9io1fjqmdflBEMx76IVrSiLNodLrEIsWlH2paFYBdqHrswA611D0Yq1WAFWqNCrRIBlznljFmhmIRytsFkXQ5Upyqr6vkpxoaYAK0OVYf4YWHmAlu0n8Lrhj2/Ssn0sPnN/dH80PTKeP5oeWWV/ND0ynj+aHhnPH02PjOePpkdG80fTIxMIsBL1R9NT4vljLI9MJ3+sokcqwBJCJIMCLFFnWblyDXNzDycQdC/2tjEnpwH//e9/p7ppGYUCrAxVphVoq0qZ36gPLWsegY0EHqFlN2bLLiXsP/UWFi3drQBLAZYCrNpD/phG/liymmzf5xTanuEEXiHwKi27H+s3H8Te437DwlM3K8BSgKUASwiRFSjAEnWWr776ik2btqHfP4XAr+j3d2Fx8UwGg8FUNy2jUICVQUrzoqx41X4GVh0IK8rMW8JPOvlzNusQIGDRshvQsprRsk6k7e3LgkZ9Oe30H2IPi1lkKN6wmJmGot5RK9pQmESKMlObk5AZdsUq4KKFXWZRFioAzZDNfD7G8w0VqeYQwnh3IUz2/RjrfRHrTmqRStMwSwFWBqk6/bE6woXIEH91KYtX7ovpj9OX/cQOfU+n7SkgrFwCPlr2sbS9k+nxNuLYOW/GHlodzx9Nj6yyPybikcn4o+mR8fzR9Mho/mh6ZBx/ND0ynj8m65FV9cdEPDIF/qgASwiRDAqwsoBgMMjrr7+eXbr0Y6tWh/DMM1dx9+7dqW5WRrBlyxaef/4FPOGEE3nbbbdx3759qW5SxqEAK4OUpgHWtDN2sE3PE2hZObTsPLbvdxqnn/lTuQItpFHHvUTLrk9gi9t7cj9tz0j2HH1ZnQmwpk17kyNG3MPJk19QgKUAKxXIH2spwAqsLmX3kefTk9OYgMWmHYo4+bQvYvpj0dJdtL0NCTxhDCdcwWbtA3UmwCou/i9HjXqA48b9nYHAfxVgKcASQmQRCrCygOuu+yN9vlYE7iTwKH2+wzhjxuxUN0vUERRgZZDSNMBq1e0Y2p6JBN4l8Dptz1B27L8k5oV438I/0uMtDJu/DriErbock/zExLMNRR0WYw6N2WUo2iTE3xgyizZz3VBRZ+7rZ0P7osh5rH//G2nbBbTtdgRy2L79SQwEvmf4pMhmG6Id1zyW8RzN5368q5MNmec0VoEWT/GKr+VJqDJFmwKs6kD+WEsBVp/Ca2h7OhJ4hsDHtKy5rNdkIAMrglHf8+Pnv0fLyjOmRyCB55jjbxc7wIrnj6ZHVtkfTY+M54+mR8bzR8cjx4x5gbm5bWnbzWhZ+WzUaDSnTv2M5SeNr8gfTY+M44+mR1anP8byyGT8MZZHVmeYpQBLCFFLKMDKAjp3PpTA3caFype0bQ+3bNmS6qaJOoACrAxSGgRYU5dt56ETr+IhQ8/ksCMfZtHyXYTlIfA/w8P+RdvbIGYoMfq4l2jZDQhsPdgDy7KHsdvwdVkfYE2e/KF7t7HH3Of+CW27PQcOvCmpAGv8+Dc4YsRTLCrambYBVtHi3Rw8/T4OmHIrp5zyjQKs9ED+WAMBVvHKvRwYuIuHDFnOftNu5PQzf2K9pkMJ3Gr440+07AKOm/dW1Pd80bLdtL0NCDxlbLOETdpMzvoAKxDYTb+/C4HzCRwg8CMtq5AdOpyUVIBVWPgxDzvsCRYWfpW2AVZg2QEOn/k4+02+gRPmbVSAJYTIehRgZQHNm3eI6Cq+g5bl4caNG1PdNFEHUICVQUpxgFW46Gvm5neg7R1F4HTanpZse+iJUQKsl2h76scMJQIrgmzdfQ5tTysCswk0cd6Dlpdte57I6Yv3ZG2A1b//dfR4xkb0PlvHVq1mHSzQxo17gQMGXM3Rox9jILA16nGnT9/O5s0DtCw/bbs9PZ6GHDp0Q9oFWBPm/5c5/ja0vb3o8Q6nbedz+BGPKcBKPfLHag6wAqsOsEm7QtreLgSW0Pb2Yf1mQ1jQZHClAqySlWTfydfRsvMJ6xgCHQhYBMBGLcdx8kmbsjbAmjDhLQI+AnuN8/Ukc3PbH/THwsL3OWDAdRw27B4WF38d87hdu/6KlpVLj6cLLSuX3bufl3YBVtHiXWzYcjRtTyt6vBNpWT72GHGJAiwhRFajACsLWLRoGX2+0QQ2E/gTgUYEwAYNmvOWW25NdfNElqMAK4OU4gDrkCEraXlKjKEtX9Cy/GzWoZi2Z5I7hPAN2p5h7NhvcYXzeQRWlHLoLx5mjr8dgQUEfiDwEW3PIHYdsrZ8gGXeWcss0EJ31jIDrBmGohZoZiFlFlrboyhWQBUsr18YmmVodpmGjv4/2p5OBPYfLNAsay47HbKMgSNK2bHjUlpWHj2ecbSs+mzV6lgGAvvLHatHr4to24MIfOe+HnfRtuuz6Jgfy85J6ByZ53GFoWgFT6z3hTlfT6igWhpDxjwyzdqXENZpxnvmBubmdWBg8YHwbWojzFKAZSJ/rOYAa+jMDbQ97QjsdN/re2l7+7JNz2Pcz/yzBD6hZc2rcAhhSGPmvMaGLYbTsoYR+IzANlrWHDZsObZ8gBXPH02PTGN/nDJjKwEvgU+NAOsG1qs/hCUzgxw48C5alo8ez2G07XYsKOjHKVO2ljvWyJHP0LIaEnjH3cdbtKz6HDX1xfL+aHpkPH+M9b6I5o+xPNLwx54jLqPtGULgJ6OduZw47+Py26WhPyrAEkIkgwKsDOCnn37imjW/YocOvdi372G86667wh7fuXMnp0+fScB2v7j/RGAfgb8yJyefr732WopaXn38/PPPfPXVV/n111+nuikiAgVYGaQUB1iN200lcG1Y7yFPzlAOmHorW3ef407i7mf7Pqdy+rKfKizOSlaSE0/8yL3b1m5jn3+lr6Br1gZYxbP2Mr+gNy2rmMADBJbTtutxQuEHHDXuebfoChVv39C223Pw4PvKHatBwzEEbjbOW5C2pzOHT3o8rQIsj7cxgVeNdu4nAE6a/5kCrNQif6zmAKvHmItoeY6L6F25nB37L2K3w86jx+v8ONm0/TROOvnzuP5YsoL0+loSeNrY33YCYOHCzVkZYJXMDrJth/m07T4EbidwBS2rIQcN/ROLSnbQtusReNg9F/toWUXs1GlJuWN17XoWLWt+2GthWSewW99fp1WA1azd4QSuCv9O9Y7gwCl3KcASQmQtCrAygMMPP5o+3zACDxG4nrm5TXjHHXeUW2/t2rX0+YrDvsi83nlcvXpNClpdfWzYsIH16zdlbm5jejw5POmk01haWprqZgkXBVgZpBQUZaa6DD+btqeQztwkJOAEUBNO+pAlK8ni5fsYOPNA/MLM1eSTNxGWl8C3hu/9ifkN+iQeYEUbQhj3LlvlJ1aPPbwlSiFWEmTJMXR0kiHzTmBmIXR2uKYs3cqOA5ewoPFAtuh6FMfOe50lq8meYy+h7ZkdUQAvY8c+i8P3vYhs0ekoAmcb6/1Ay67HsSe8Wf645nvo3BgKPW62NV5RZg5bOjm66jUeSuBqo53P0/bUZ9GC3c52oWIukTCruobKVKJYU4CVQUpRsB/SsKMedYdFb3ff67tpe3twwLRbD/Y6LV6+N2F/LFlB5uZ3IvBX4/PzBQGbU0/dlliAFW0IYZX98efE/dH0yAT9sXj1PvYcfynrNR3Kxm0nccgv/sKS1eTIY5+j7W0b4Y8PMr/hgHL+eOjo39L2jjF6fgZpe0eyz8TfRz9uov5oemQioVUcf+x06HJa9tHG8/melt2Qo494KdwfTY9MI39UgCWESAYFWGnI/fffzxEjJrF//5G84IILaNteAl8ZX1A3sWfPweW2++1vf8u8vInuOqUEHqfH058LFixgMBhMwTOpOt999x1zc/MJ3OVeSPyPfn9n3nLLLQltv2/fPt59991cvnw5b7rpJv7000813OLYBINB3nvvvZw581guWHAa33zzzZS1pTpRgJVBSnGANWXJt8xr0IO2ty8t+zhadkN2HrQy8YIsSoHWrH0xbc9kAi8QeIi2px37jL8mbQOs4uJ9VQ6wysktggaV3EPb293tgRvqVTWKvUddWa5AGzXrRWeOHPyawJ20PYexSdsp0Y9rvodqOcAaNu1Rdy6f0wmcRdtuwp7DLivbTgFWqpA/VnOAFVhdyhaHHEHb05qWPZe2pxMbtRrH6WfsSdofe45aT9tziNvr6FnantFsdcjsxIcQ1nKAVVy8j4FAaUIBVuDMICct/JxDjnyIPcZexE6DFrFVj5ls2mE8G7cdyUath7JhqyFs3HYUm3aYwGYdJ9OZC2wOgbUEriBQxIbND+OomS9w/LHvc8ovt7D41L2cetJ3zPG1pmUdT+BeWvaxzPG34dRF29MqwJp07Gf05jSnZf+CwIW0PT3ZrF0JA6cGFWAJIbIWBVhpxo033kSfr6nbJfgm5uZ2cO84tccIsB5lq1aHlNt28+bNzMtr4P6qPopAMwIT6PXW44IFp2dkiHXfffexoKB/xC9ml3PKlBn8+OOPedxx89mlS3/Onn0CP/zww7BtDxw4wLFjp9DvP4TAYublHco+fYZw9+7dKXkuy5evpt/fhsA6er2nMDe3gM8991xK2lKdKMDKIKUqwDIu1IuW7uKAabeyx8jzOfKY5+LO4xKvQJu2+Ae2P3QhvTnN6Cs4hL3HXsnAsmD5AMssfqIVaMcZiluglcZQlJ4ER5IlR5LDRj7MvIKeBMD8+n054oh/OO0yi5zfGLrO0G2u7q5Y02/bw3qtB9DOGUngN7S9U+hr2JlTf7O9bF9/cHU1OXLZ82ze6wjWb30Yu009l0X/bxdLrmZ5XWXIbON6Q+e7Mt9vZhgWrSgzw7v5sTUm8Crbdz+VbQ6Zx2GFj4QXcZFBViJhVqz3qQKsyiB/rM4Ay/XHwIpSDjviEXYfeR4HlzzA4uX7quSPgTNL2WPUJczN60hvbnN26LuIRafvLB9gxfNH0yNrwB/HF77PRs3GEwBzcluzz7g/lLXN8Mfpl+7hsBMfZrvD5jG3XrPQZ6va5cktoK9+S3rzGtHOqUd/o/Zs2XcGO49dwu5F57HvrGs57OSHOW7NW45vJuqPpkfG80fTIyvwx8mzvmCXvmexVcdj2XfUH1l80t7y/ljbYb8CLCFEDaIAK83o0KEnnTmsQmHNmwTyaFln07mryjf0+UZz6dIzo27/yiuvsHPnHnTuOvPjwS7jOTn1+dJLL9Xys6k6Tz75JP3+1kaPAtLjWcZZs45n48at6PXOJfAQPZ6T2LBhc37zzTcHt92wYQP9/vAJUfPy+vH666+v9efx3Xff0ePJJfCe8dpeyFGjCmu9LdWNAqwMUhoEWEkXYzEKtIMyL8Qji7MUB1jjC9+nZeURuJ7AJgK/pWXnc9IvP6/WAKvkbnLatT+w55GXsHmfmexafA6nXLU1fF9GgJWwIgKsqRdsZ8+pF7Bjj2L2LLyIU8/dXqMBVsn8iHUVYKUD8scaCLBq1R/TJMAqPmIvc30dCCylM3/fX2nbTTik+KGDAVbhmZvZZfwq5uQ1qrHQKmlZFuu17MW2g+ew36wbOenXm9hv1o3s2Otwdh2xmBNXfFSjAVZC/qgASwiRRSjASjMKChoTeNkIOXYRAFu37kyvt4C2ncPCwhLu3Lkz5j7mzVvA8LlNyLy8Gbziiitq8ZlUDwcOHGD37v2Yk1NC4BECFzInJ5+rVq1iXt5Ils1PQPr9E8Ke40UXXUSf79iI3ltnctGixbX+PN58803m5DQIay/wRNSedJmGAqwMUhoEWMXL93Lg9DvZaeBS9i38I4uW7kqrAGvqkd+x56GXsl2HBRww+FYWF++tcoHWrec5tKxjwrzI9hax9+j/V+0B1sF1bzZUjQFW0cU72aRJZ47w+nkZwOFeP5s26cKitbsVYCnAymylQYAVWBHkiKP/wc6Dl7PnmEtYeOrXaRVgFc/ey/6DbmG7DgvY89BLOXXqd1X2x+GjH6dtt6cz9UXIIy9m8w4zWHTabnYddRZtb16FIZKvUWs27jqCrYbOZIeJJ7Pz1KXsUrySXYpXsvOUJeww8WS2HXkcW/YPsEn30azf9lD6G7Wh7fXVSKiVC4tHAjza8tKfk8/xi95TgKUASwhRTSjASjOOPPI45uTMpHNL3AO0rLPYvXt/HjhwgG+99RY/++yzuPu47LLL6fePMS4GdtPvb8tHHnmkFp5BdHbv3s133nmnwuAtFlu3buVJJ53Kdu16cMyYKXzmmWe4bt065uaG363H4zmRa9asObjdo48+Sp+vJcsmRP2JeXk9eeutt1bjM0uMPXv2sH79ZgTuddtSSq93No89dl6tt6W6UYCVQUpxgBVYeYBN2k6m7e1K4Aza3v6s12Rg8iFWsgGWOd9L6KL/BHLKrG/o83eibY8jcDZtTzc2azadgcOD7h23GFGoRd4li47M+VsWkt0GrCWsIgInEBhHYB0tzxT2mn55eNC0wdCzht5wtdHQhzEUevxtQ/8x9JIrc/9PGXrUUKgt95ap3/zr2Ts3jwdc4z0AsEdOHvvPupkllzMskCs+Yy+7jzif+Q37sUHTkRxYeLdz/kPnfK6h4+PIXNcs3Coq1BZTAVbNIX+sgQCr6/BzaXsaEziNtqeInpwmHP/L92s3wIrmjyeRgTmlbNqyiLanu+OP9lj6fJ05Zdq3lfNH0yMXksOnPUbLbktgOYGxBE4hsJIN241mQbNuUQMif4v27DzrDA677FFOeWpLeY+M54+uRwbeCrLo+V2c9MjnHHv3GxxxzT85ZP2f2f9XN7P36b9htxPWstOMxWw7eQ5bDC9m456HsaBNN3ry6iUUZA0BGLA87DzweMcfTY9cQQ4supMNmo9kfsP+7DHsQhafujc8jKouf4wV9ivAEkJkIAqw0ozNmzfz0EOHMCenAX2+ZmzZsiPfeuutSu1j27ZtbNu2C/3+cQTOZV5eHw4fPo4HDhyooVZXzPXX38C8vAb0egvo89Xj1Vf/vsr7fOWVV5iTU8Cy26u/wZycBmFzSpWWlnL69CPo97dmTs5c+v2dOGzYWO7Zs6fCfQeDQe7cubPa73T4l7/8hTk5fhYUHMa8vEPYrl1Xbtq0qVqPkQoUYGWQUhxgDZ35V9oec1jvPtreAew7+bq0CLC69zuftj3Z6Cn5A227KUeMerpKAdbQwg0EcgicTuBmAsMJ5HPiWZ9mXIDVdfoanmjZZrdWzrW97DZxbbkAq02PebQ9AwjcR+Ba2nZTDph4qwKs7ED+WM0B1pRFW9w5T98u+3hZp7B1t+PTIsAaMfkftO3mBHa47QvStieyR88LqxRgTZ37PYECAlMI3EbgWAIeOhOuhwdCrQ47gqMufYGBZ4Ll/TGJACumP5oeGcUfA38Lctrd33Psb9/kgDPuYOeiZWx4yOCYQVa9eq0YuCwY5pH9Cm+k7WlG4I8E7qXt6ce23U9SgCWEEHFQgJWGBINBPvfcc3zwwQe5d+/epPaxbds2XnLJeh577Dxee+21Sd19LxgM8qOPPuJXX32VVBtI8u2336bXm0fgCbcofIY5OQV8+eWXk95niPXrL6PX62NeXjt6vT6ed96F5dYpLS3lI488wnXr1vGBBx7gvn37Ktznk08+yZ4dOxIAO7ZowXvvvbfK7TTZsmULb7/9dm7YsCHp1zbdUICVQaqOAi2ZQs0NsHqOvYS2J3woHbCCHfsvqpn5XqIVarGGy8wnW3U4jsBFET07p7DvoOtYMotl876YhdiRhkLFhFk0rCHb9z2FsE409rublqcJR659Nrw4ei9Ypm/3HNTxwW94fPAbnhz85KAWBT88qGXB9w5qSXAjlwQ3hj2+IPj5QZ0Q3MwTgps5e+/2gzp8+88c+/S/HCqVoQAAIABJREFU2HnhInY8YTFH/d+/WLKJZYXeK2UadsEjbJLj42b3yXwFsJHXx+FLHnOGKLqTFk9Z+w1heenMaRN63rexoGH/suLKDPpmGTLPaWiZuW60Ys085/GGE8Yq1JL9LCjAyg5Vpz9WNuxfTY489jna3nYR/vgQ8xv1rxl/rORw676HXUuPZ2pE+y5g67bHV84fTY9cQw4M3Enb09MYNXB+uQCoca/DOOaB/1Toj6ZHxvNH0yOj+aPpkYdv/5mF73zE7it/xfZHL+Tg6+5n4PPS8DDM9cex171F27LZKkqI1W74XBZfs++gR+Y16E3gbuNc/o+wvJx67LbyHllVfzQ9Mtnh1jXgjwqwhBDJoAArzQgGg1yxYg1zcvy0LJvt2nXjiy++WOvt+PDDD9m9e3/adi4ty8Np036R1PC/Cy64gDk5RxHYQOA3BF6kxzOXZ511VrW089tvv+Wzzz7LrVu3VnlfmzZtYn5uLn8P8FuAdwPMz8nh66+/Hrbejz/+yOuvv55r167lU089lZF3d6xOFGBlkFIcYA2f9ThtTwsC3x0McmxvT/afekuNBlhTTv6GbbrNpSenKf31erDv+BuiBliHDvud22PoZ7d9n9Ky8ji28I0qBVjNOpYQuDI8GPMN4aDT76n2AOvUXW9w6j1XcsINF3H+Vy8kFGANveNeWjn5tDwLCPs0Wt4CDrjy9qgBVuDvpew0/ljmeXI40ldAv8fLzqPnMHBtMCzAmrjyf4SVY5xLEniKOf52CrCyA/ljNQdYU5dso2X7CfzrYA8nyzqebXufWKMBVvHS/ew65Bzm+Nsxx9eah/Rfxemn7ikXYI0peY2WVUDgM4amZbDt/uwz8PdVCrB6jb+ctucId58XhoU+lieHvRZexsDjB+L6YyIB1uID73PG4zdz/B/W8Zi3H0kowJr46jv01mtK23c4gdW0fW3Z/uhTogZYJY+T/Rb/gR7LZltPTrkQq3nvaZx+wU8sWU96fa0IPBv2wwZgc9JRnynAEkKIClCAlWbceuut9PvbE3iDzl0HL2P9+k25e/fuWmtDMBhkr16DaNuL3S/UzfT5xvK005ZWel+XX345Las5gfYEjiDQgLbdmevXr6+BlleN3/72t5yclxc2NGa+18uVZ5bd8XHr1q1s27YL8/IG0+v9JXNzm/D005elsNWpRwFWBinFAVZgVSlbdplF29OCln0cbU9HNmo9ntPP2FP1Ai1asXYGGVgWZMMWo2jZJQReInAPbU+zg/MxBU4+wMApQZacRBbN282GTUfR9rSj7ZlBy6rHjt2Wld19a3YUmUVZaNiH2Zb1ZJ+Sq2l7exP41rWWJ2nZuSy8fzNLPgoe1Oy92w7K7ClwPp/nutJnecl3d/Oq0g38HR/mDbyfV/94O3/16nqeevfpnHnhURy7YDxz/H7anvq0Pc1p2TYHHD6Iv7j4GM65/mQufngNz37nav5m5728NPjUQTVo35nO0MaQ9T1If9NWnHdgE+cHv+Lh238+qFDBNuaBV9l/5U0c88fXWPJPlg0zdCd7D1wZZH6j3gTOonMX2e207Ens0Ps0lpxAR2ZR9os4Mou2aMWaOezGHE5YmQCrBobLKMDKIKU4wCpZTfYefxUtO4+250ja3iHMzWvLSQs/rRl/dD3ykEFraHt6E3iMwFO0PYPYvtdpjj+eUsrAKaUHhxN27LmUll2ftmcGbU87NmwymkVH766cP5oeuZ4cu+R1WnY+gRvDwytvLoevfywhfzyfz/Os7Y/yir1/OeiPId3Ou3g77+KNP93CLof1YY6vOXPzJ9L2+lm0+hdh6/6eGw4q5I/95s6g5Z1v+OPntDy5nPnhC5wf/CrMI0P+OOkfn7H/qlt46JKrmduoeXhPrKHzGLgyyPb9FtLyTCHwg3u9v4oFDfsxMCdY3iOr6o+mR8bzx1ocbq0ASwiRDAqw0ozx46dH/FIfZF5elxqZgH3btm384Ycfyi3/7LPPaFkeOndADLXjH2zSpG2lj7F+/XoC3elMSk8CXxDw1fqE8sFgkA899BCPOup4nnjiKfzPf/5Tbp2rr76aEyMCrBNycrh61aqD66xadRZ9vmlGV/dP6PH4uHHjxtp8OmmFAqwMUooDLOcuW6UcfuRj7DHqQvYaexnbHbqArbsfzyEzHmJgRbDaA6xxc96hZRewbN4tEriG9ZsMY9M20whY9OY0Z88hlzFwYpDFv9zPoeP/yt6Dr+ToopfLwqsqBFjFF+5lix5H0rLz6cntScvjZ/8Vtzi9rhIIsGY/eCGbNnduH9+4cT0OnD2anYd3o2WVnyMmUTXq0IK9Dh/BiefMcZe9a5yf7wiAx/2wMWaAVbKRTnAVUkSAVXIVOW7hW/TX70LLbkDL8rFJ60JOW/C9AqzsQP5YAwFWyUpy7Nw32XPMJew59lJ2GngGW3Y5mn0mXcPpZ/xc7QFWYFmQHm9DAs8bn/83CeSyXY8FtGw/LdvPdt0XsGjuLpacRI6e9m/2HnwFh014mMXH7K+8P0YEWCXryW4T1oWHV7aHh132ZJhHxvLH0966lR0P7UQAzPfnsvicY3h98L6wAOva769n98O6uNeju93n+V/aXh/Pe+/KCgOslgMGErjdvDSkt6A7Jz9yR8wAy/THiXd+xPwWh4Q9v36zb+TUFdvZuN0kWpaPlt2A/nrdOO6Yd8r8UQGWEEJERQFWmhEIHEVgnfFFuY8+X0v+85//rLZjbN26lePHFzkXCZbNGTNm88cffzz4+DfffEPb9rhhU6gd97Jjx16VPtbs2XMJnBf2xe/3T+Pvf1/1idzfeustnnLKIh555HG8//77KxzKt27dBfT5mhNYS49nEXNy8vn444+HrfP111+znt+5NfxnAG90hxC+/fbbB9cZM2YagWvDnk9BwVDed999VX4+mYoCrAxSqgKsqMMJHyOsPAJHE1hM29Oc3UdckHARNnXRdyxaujNuoTbm+Fdo2Y0J7Dc+t7fRshvSsn5J4CMCj9P2tGH/sbeUv3W8WUyECjWzKDPXDQ3LMM/578s07up3OOycRzjlzm9Z8k6QJe8EeeTOHQd1RvDdg/oNH+Nv+BhXvX8D/TkeXg3wmCTDqsTkITCBzoTCF7Nppw68OPgPXsJ/hg3BMYcehgq1ojd2c/CvH+TgX93HadfsKJuU/iIycEEpx57+OifM/bCsUAqdz5mGSuLILNbM4Cva6xBrOKECrOpE/lidAVaEP04+9Qt6cpsT1mQCy2h5DmXTdlMTDvmLlu7k1EXb4q4XODNIy/YReMvwx08I5ND2jCDwGoHXaXtGs23XE6vHH02PdL2xe1F4gNXnrN+V88ho/njp3ofZvHl9rrYsbgP4AsDWfi/Pva2EL3MtX+Zavs0VHD22HZtZfgKXhF2/5RWM5rk3FPJtruDbXHFwm5e5lv/kev6T61myvJDe3EICB9ztXqXtyeHZmx/kJfxnmEdG88fA+6UcuOZuevwFB5+f7fVx4vKPWHIROeGM/3LsMa8zsKQ03B9Nj6yqP5qvRTx/VIAlhEhzFGClGU8++SRzc+sTuIHAS/R4ZrJt2878/vvvq+0YkycHmJNzBIHNBD6jzzeeRx89h9dccw0vvvhivvPOO5w581j6fMMJ/I3AXfT5WvOaa/5Q6WNdfPEl7t0QQz2WdtDna86nnnqqwu02b97Myy+/nGvWrOHzzz9f7vGHHnqIHo+ftr2AwLn0+Vpz+fLVUfe1c+dO5ubmE3jZuHC5kv37jyi37nPPPcfBvXoRAHt26MANGzaEPb5y5Rrm5k43ns9n9Hh8/OCDDypxVrILBVgZpDQKsAoa9SHQjEADOnfom0BYeXFDqUknf85Grca5AXwO2/VeGHsI4goysPwA/fW6EFhFp1fp+7TsjoTVgM6wjZAnXMuGzcbWaIAVdpfBBAOswnOPY2+PzfwKwifLAnMsMB8WgUMIFBEoJDCYsCy26diA+fXKz8dSkbqP7cXTX70uboA17q/vMKdhK9q+HvT4+tDja8zRa/99MMA6KPOXfgVY2YD8sQYDrI79TyfQmoCfQD6BPoTdkCOPeb5Cf5z+/9k77/goyvWLn3dmtqaRhCT03msQCDV0QkkWUIpcUVEREVEUseu1YkfRa8Pe68+u2K7XhuWC145e68UuKooovez398dONrMhFAUkwpzP5/noZmffKcucfc+Z532eY1ZTt/XBbgMFkV1nIIOmfL1Fk792i/0xVgnSt0g/IDPK5eQ3Pfz4LsYEKZ20bocbWGWXbyScXT/JPdmtelL2zoZtMrCm/OsCCsIBNnpcqcskuveqlzSinvjfoQQswzEyhDSQii6zvxIM1eCmF8Zt0cC6+YcLyW9cl2CkCYHIECwnxJiL9k+aV1sysIa+/guZLbthBQqwAq1SODa/ZemW+dE3sHz48OGjSvgGVjXEfffdR4sWhQSD6RgTIBDIIRRKZ+7ca7d77F9//dX9sfBmV92LFCIS6U0oNBrHCXPFFVcyc+YJFBQ0pkmT9lxzzTV/qFj50qVLqVu3KeFwL6QTiUSa06/fUDZu3LjZz3zwwQfkpKczOBzmENsmIxDg/Fmzku8/9NBDGBMlNbNrEbYd5Mcff9xkvE8++QTLcjxPz0B6laysgs0eQ/nxrVu3jsWLF7NmzRog0UWwTp0mRCJdse1JhEK5TJly5O++LrsTfAPrLxTVxMAqPW49UoREwd71SN8jdUOyGXDop1sUaJl53Um0Wb8Q6UiM1ZJmRaducalM34nvkVajY9L0Kmg8xs3K8hpYc8nKLa5WBtZFG5+gVrtGm5hLlkSj1rmceM1Q7nx3Mide3p/iqMPzEkE5ODoQ6XgsK5MjzuiRFGcvL5vGbW9O4rz79mH/0/rTvawVWTXTNhnfG61H9uLAD+dtVqDV6NAPWcd6ROG5RPPbU3ZD3DewfAPrrxXVyMAKRhshjUD6lUQJhsOQ8igcessW+bFx5+MwVmekOUgzkelLZkHxFg2sodOWUbPBCKTEkuTs2iUYEyKxlLBijmVMYKcYWD2PmZ/COUWnPZbkx60ZWEe8NJuaIYd1HgPrQone/RsmjagHF00k6hgWS9RUiJD6I52FMY3p2rcp78SP3aKB9SBXc++ay5l57yTGX3YgZ78/mxu4Z5sMrOaH/x0rWExFM4tRqed64BO+gbV78qMPHz52InwDq5riX//6F5YVQcpHCiL1wbZDvP/++1Vuv3HjRmbPvoQGDVpTu3ZTTjnl76xdu3aT7VauXOmaOf/1TEz6IU3xvH6GSCSTFStW7JBz+fnnn5k9ezYHHzyZm2++ucrj8mLfUaOYalnJycjrEiHHYenSpaxdu5b8rCyyFEV6xnPMcQKBTN56661Nxlu/fj25uXWpKFIcx7YPobR09BaP495776VGjVpIhvT0HK65JmEgLl++nKuvvpqTTjqJp59+2u9C6BtYf52oJgZW8YFvIKVVMpUfQCaT0mPXbz77avJiEkvdaiH1QBqPFMF2crep1sugQ79m6NTllB21kUhGK2SmuGb+C1h2PToUX58wsLy1Wrw1RMpFRVV1RSZRIUDO9sT1nnjGE1/EiX0RZ1L8y2Scn5RMz3EXN7HveaM3MZT2kggHDe8tHsry+GiWx0fz1XuDCDuG2yTekhglm4AJcNaxLdm4uIz4N7GKWJqIFRtGsWLDKH5dN5In39mHU2d3o22n3CpNrEA4yL5zp/KP+MMcF38nGWNX/YIsG+ljz/eYqJ819JZfiM2mIryFo8uF1O8xsLxRVb2XbTGwyr8f38DaEfD5cScaWJsaSN8jieL939iigeWE6iC1J5GJeRCJLK4Qg6Z8tWWOPAZKpvxIyWE/EJsOdVsegmUXk6iN9z6W3Y86TSbuGH70cuT10HLk2RVck5FN6by1SX70cmRlfryLm5j74+XUrZXORNuwSOJ+ieygxR0PdE/y44YfymjdIMLRlvhMYppElhVieL88Vn80vEp+9HLk50zmcybz9k8H8PSPM5IG1yNcmYzyulmV+TG7U2+kmzzf40/ub5hbi7B+EWUXx6vmRy9Hbi8/ejlyWzq2+gaWDx8+qjF8A6uaYsCAQa55NQ/pPaRxGJPPBRdcUOX2Z501i1CoAdJEpBiBQCMOOeTwKrf9298OIhTqjvQS0j+RMpCeq2QGZfD222/vzFPcLNo0aMDjnqdpSBSEw7z22mv897//JWzbjFcAR/tQsZTvXjIyclm9enWVYz7xxBMEg1HS0oqIRltQUNCAzz77bLPH8Mknn+A4YaT73H08RSCQxoIFC3bWaf9l4RtYf6GoJgbWwMP+h0yQiq58IP2DaI2OWxRngw//xjX0D6Qi4+ffSA5Dpi3dooEVO8YT02HAgZ+SXWsAkrCdbFrsdQ5lh8arjYF10tPHIuNZJihhG9GhTTZ3vRBLirPl8dHEl8Z46Lau1MkOYBmREbK4+KTWxD+PJWILBtbCdwbQo3s+UUtE3H207JBPJD24iZFVOKYn0397LUWghWs3QbrT8z0+iROpSek9630Dyzew/lpRjQysQLiuO/8rv6/eRCa01ULuTrAmUksqMn5+Qspir7J7t2pgeflx2OG/UbfFwRgTxJgAdZodyLCJv+4UA6tRvyOSHJPdtlcKP27JwJp42d8IBWzyQzYRCceI+gURZs0t3oQf33+1H4XN0rCMcCxx0Mg6CfNqM/xYzpFf/TicMROakhmoWMbdq19DnvrhmG0ysOqP2w9jH+75Hn9AJnU5d/fD/ukbWLsfP/rw4aMS9pX0kqTlkjZKsiq930HSi5JWSPpa0hlbGMs3sKop8vMbk2gpXP6jtxIpzBlnnFHl9llZ+Uh1kHoiHYVUG2PCrFy5cpNtV61axdSp00lPz6VGjVo0bNgaY2Z69vUywWB0l/y7WLlyJb26dOFgY4i7B/SKRCQQ4Oeff2b58uVEAgEek6inEBHVJqAOGOPwwAMPbHbc3377jWuvvZaxY8dy2mmnbTW77KKLLiIcjnk9NGx7EjNnHrejT/kvD9/A+gvFjhZo22Fm5TUa4RYJfgjpCoyVRZcRD2y16LBl5yE9nHJvGiufnvvNJ3YCDJuxkk7Db6d1nwvpc8BbmxVo5TF8ymrKpm5ICLPy8Iou73KOCVWEV2xUEmdlZ8VTDazn4xXx7UZi325kOv9NRrkcuiL+MNkF6RVZCRLnSYQDhu//V8LG5TFWvj6c+y7pzC3nFvLjAyXwbIx1T5Xy2dUDWHn3MLg7VnU8koj4izF+enwIeWkO0yRelThLIirROGj4+2kt2O+I9puYWE2L23Lxqvu5nMeYFv+YQbfPxgqkI3M80ilYTjZtj7gi0T3sGk94/42UX9s/amB5l8tU1W1rawKtqqUylcXaH7kPfAPrrx3ViB9b9b0Yy66HdDPSXVh2CxoVztgqP9Yo6I50XAo/yuxNqz7nJ7rAHr+RbqOfpFXx+XQb/SRlx27cIj+WHr6O0sPXEpvGjuNHlyPL+bFOl3FJfinoNTKFH70ceaXHMrpu0bGEHIuX3ZN8XyInZPHEA93YuDzGhnfK+Of13bnuzA58dEt/eDZG/J9lfHHtQH66dQg8uGV+LOfIfm1qMNCI5yVukciR6GKLkSX5fMSRyZjHHOYxh8t5LBnT4h8z/r152JEMjDMR6QKsUAvyu40mmFUzec757YZXzY9ejtxefvRy5LYYWDuDH6vgSN/A8uFjz8FgJUysg7WpgZUu6VtJsyQFJbWT9JWkozczlm9gVVM0a9aR1La9a5AivPTSS1Vub1lBEkV7y7MSliCFePHFF4HEEsPyOk6V8eabbxKJZBIKlWHbkwgEMrj44kt22rltDsuWLaNds2Y0D4XIcJfKjLEsoo7DnEsqjuecM8+kZijEsRIDbZugbW/RvLrrrruIOg41JByJLMuie2FhSufFyrjyyiuJRvukTAKDwTGcfvrpO/Scdwf4BtZfKKqRQBs2YwVNi04iktmGzPzedB5x/1bFWew4KGg6DmlSSmaCMSFKjvyBkmlLCGc0x3LaYtl7Y6woLXudv0WBFptGqjj7nQKtQ4/rCUWaYqwo+Q33ZtDBX9L9wGfIy2mGJPIKWtDj2H/9LgNrxssXpJhGc9yTLYza3H1zZz56cwD5OZlEw40IBdtj5FAz6jCxfx2+vWHw5sVZJQNr7swOFAUtvEQ3TiIm0bV1Oh9xJDc+PYIa+ekpx9Nhnx7M2fAw0+IfMy3+MaOeu506Iw6k9vD9KDrviYR55RtYvoH1V4tqxI9lJ8RpP/ga0nO7EK3RkdZ9Ltri8uryaD/wKozVhor6fsux7NoUjZ5H2XEbqNkohmXXwrLHYdkF5DUaQdmMDVvnxz9oYPUc+iIZ2d0wJkxmzR70HDOfAQd+Qt2GxRgZMtNrkt24W5Jbcjv13yYD69CLhhMLOyncNc2IIyc34rfvhlHUvhahYDaRUHeMbDKCDkPa57DwwuIEP26DgfX+rf2I2Iblnn38Q6K7hGXEO6sO36qBNS3+MRM+fJpGE48if8BoOlw4l9Kn1tFy4lkV2bWWw5Cjl/oGlg8fPvYI9NWmBtZESUsq/W26pE82M4ZvYFVTXHrpHILBJkgLXTPqUOrXb7HZeksFBU1JFO2s+D23rM7cdtttXHrpZW6GlujcuXeVdbS++uorZs2axfHHH88rr7zyu471ueeeY/LkqRxzzLEsWrSIr776ilNPPpn9x47lxhtvZN26dds0zrmzZtE7HGa9xE8SsyQClsVtt93GySf/naysfEKhDNq378y4ceMYPXIk0484gnfffXezY3777beEbJtHJeIS/5NoINE0EOBcT2H4yvjhhx9IS8vGmBOQ/oN0LqFQGp9++unvujZ7AnwDq5rHzhJl2ynQqlo2EzuBzYsz9/3+kz7ECeZiOYOQmYSxMmnR6xxiJ0CjvWZgrDIqlha/hTFBBk/55vcZWN6sAa8gG58aXXo9gGXlkFhq/A7G7E8kvQUBK8A/XL6ZIxF0QgyctZjYs/GKcMXZMSxKxvXcx/Xcx8CjhyfFTQ2JNW4UBC2evbEHQ3vXx7YO8TywuI4shdnHiHY5UTacXgYzYxUxwxMnu3FxjEvK2jDUTjWwDpPoKtGnVRYbf42x8dcYz387maZtclJMrHFnjeCM+CvJSBYuXkhF3OKJ0z1Rfp13hIFVXqx4c8uWpnrCN7B2JHYPfvwzOHJ7+dHLkVvhx2EzVpKe2xnLaYs0DctuRG6DYZQdt4Euox7AsusjLXNv92VYdj26jHjw9xlY28iPA8sWY1lpJBpufIB0PpadTmakFocam48lHpYIWRU1oSIFDVP40cuR5fx4Pfdxys0j6RB1kpn6SJSFLM6c1oKLj29DONiOxMoFkN7Bks0REhmOxefHDIQzt8KPJ8dYOL2YbNuw3rOPOyUaSYQdw+qlpUmOLGfx+zxHWRU/lnPkgIc+S30oUHbdpvzo5cjt5UcvR26NH30Dy4cPHzsRVRlYl0p6stJ2Pdzt0qsYwzewqik2bNjAzJknEgolOkR17dpni+bJSSedjDHdSHT0Amkxth3m0ksvJRSqifQE0ldY1rHk59ffaiH1bcWcOZcTDGZhWUfhOBMJBKJkpaUxMhTiTIlm4TCjS0u3aawxpaVclJL3LvqnpVFWNoJwuBXSv5D+jaXu1LYipIVCPP/881sc89Zbb6VLKJQy5jkSnSSG9+27xc++9dZbFBeXkJaWQ+fOxZvNftvT4RtY1Tx2MwMrdgKUTFtC674X0bTbCfTc78XkGJn5vZFuSzHybacVRXvP2ykGVk7eUKSLPftbizE16GkFUjinJBCm1ajzt9nAal7cOils6kiMlCh0DHs1SWPDe2WkR6NICzy7WI+R4SOJfMswqGEuoxrnM6JRHrEGNbl6QHvWTS/dxMD69MQBBJQofLxRiWUyYVkYBbn9zMIUcfbPLydRUNezrDHkcORH9/gGlm9g7XqOq+4c+ScaWLETYPiMVXQceiNNus5krxH3UHrcOmInQLNuJyEzOYUfZSbTrOjknWJgtWw/C8sakbI/Yw0lahw2eP74N6UuUx58z9dbNbD++dvJ1MqP0ssyjJToa0SNqMWX/xpESa8GSJek7DdNHblNImYZutbOYlSzPEY0zmd4vRz+XtSMpYcP2cTA2nBhGQVhh5MlVitRAL6ZAkiGA0vqJPnxjxhYsYWQ1bhLBc+3He8bWD58+NgjUJWBdYOkuytt18rdrk4VY/gGVjXH2rVrt+n7WbZsGc2atSMcbkkgsC/BYBZHHHE0gwbFkM73/JBvJByuz9NPP73dx7Zq1SoikSxSC8BfTA2lJWcNSyXSAwHeeOONrY539lln0TsY5GKJwyWulEhzHDIzC5Ce8uzjC4wMZ0nUysigR5cu9CwsZHRpKU8++WTKmPPmzaOWbac8QZsoQ4Zsph9xxHZfAx++gVXtYzc0sJJRaYz67Q7DWAd4uGIxMkEGTPpspxhYNXIHIF3p2d8GjMmjt5W6tGW4E6LliFnbbGDlNsxLCpt8k8iKqmkb9h1Yi/j7Mdo1L0C6zLOLVwnJYYUSGaYDJMISh0rMlmhhW+zXrNYmBhYXx4gEQoSUhi2LgCIYXYhkWPzQwE3E2d0Lx2OMSR5b8+E9fAPLN7B2PcdVd478kw2szfFjYeltWE5LEiUpEqUpLKclnYbdvlMMrBZtT8dY+6YaWGZvosZho+ePZ1YysDrOvGGrBtbL8dPp0b8R+bZhikRLS7RsFGX5wmEcfUAzgs5Iz35/Iagor0gcJNFWIk9ioMQVEgNsi1aZEVYeOSzFwOLiGL0b1SasbCxZWLIIan8cqw03ndZxuw2spkOPq8g8q9HIN7B8+PCxR8DPwPKRgtWrV3PHHXdwzjnn8NJLLxGPxxk8eATSeZUMrHo7xMBavHix+8OzwTP+f3AUZLVnctI1LY277757q+N98sknpNs2XSSOl6gr0aiggIxXksoSAAAgAElEQVSMmkgvevaRaCc9X4nixjUlLpA4XSIrGOT2229Pjrl+/XrSLIcSOTwkcaIMjhLdtRYuXLjd18CHb2BV2/gzjKsdKdCqMrM2J8Y287kBh32GE8rDsociHYNlF9Cww5FbroF1uBveSb1XlHkFwKjU6FB4PZbVwM2GWoZ0AlIYKUSpLJZI3CgRtAP0P+ljYo9TEW6HLW8NrBu5mxu5GydU0aXqepf4lkik24bXry/miYuLCNghLDMF6WSCyuBMWVwlkS6xt8RxHg7+ViJkDPP79+fnWIyfYzGYmIjG6TVJtHn/CGkF0sfYls2yq4YSfzNG/M0YyxibjFHTKurVSOK0T67lch7j0PgXHBr/gtj7VMQ9npjlifJr7r22voH1V4PPj38xfhx+7Goy8oqwnPZIx2M57cnM68bwo9dsnR+9HLmN/NhvwCKMiSDdQ2I5351IDpJDc4V4X+I5iVwnRCS7UZJT8jqVpHQhrMyPN3I31zw7ntyQzU8ux62X6Bq2mHNUW764fyBZ4TSCdinSuQTVmP4K8bwSTSqOkeghJZcfbpBoZ1lcWliY5MdyjpzUrAm2mYT0KdJSpHWEA3k8dWy3JD96OfIFZiXDWw+rnB+9HNl5xv0pXDrklJ9S+dHLkb6B5cOHj90EVRlYB2rTGlhHays1sKZNm8aMGTOYMWMGTz311K7Wwz52IB544AFCoVykx5A+x7KOpqCgwQ5ZQrh+/Xpyc+uSumTnSKQMMhVkvsTbStSxWrx48VbHO3fWLPqFQsknc79I5AaDjBixD6FQd1dgfUNAIyhWmL9LhKRkFxok7pBoUa9eyrg5OXWwNYw0NSGsIUjPIBm+/fbb7b4GeyqeeuqpJGdMmzZtd52A+ALtLybQYifA4CO+o2Xvc2nYcRpdRz1K2bHxnWZglY2M07TFqW6dFyHlunz4LFJjJIvszDp0PeRRYpewzQZWOCOSFDXXefitf9jmxpM6wvwYr59UzCE9GtMiLxvH5cKQxCMSRUrUavGmPjSwLO7p3n0TA+umnh0J2ZlIVyDdTjjQjEN6N4WbNxVnyxjLI0tPwQlU1KwpnbW/b2D5BtZfL/ZQfhw2YyUdBl9Lgw5T6TD4WoZPX7Vt/PgHDKzYKNir6B4CgTruPRBFOolEXdEhSGEiwTTaDJtFq+HnVZg5xjBw/mdbNLBmzhlIWSQ10/XvEgcPrgvzY3x57iCOH9ycTvXziVqGsERQYrLEsRJTK/HjBGOY2aLFJgbWuyP6ErRDGJ2I9ABBZxAtCnLZcGPZdhtY/S5elGJgFR/xhm9g+fDhY7eFJSkkqUQJAyvqvjZKZFl9I+kcSWFJ7SV9Kb8L4R6Nyy+/guzsWkiiqKgvH3zwwQ4b+5FHHiEQCOM4vZDaIuUhvYc0m6AiBC2L8845Z5vGmjBmDGdXmlQMjUaZM2cO48dPxBgHSdS0ohRJpLk/+t4OMe9KRAIBFi1axM0338yCBQs44YSTCYc7Ir2J9D8CgX3o1WvQDrsGezr8DKxdHH+mEPuzxdofFXblE+6ZntjashhvN63NibLNCIbBg5cgGaTPPPT1DE6wFmWnx4mdQSLu8sT7cWLvx5nCZ8mYy/3M5X4ya9VIipqL3QG/lojahreu6QP/jMH5FbF0/BAWjehL67QwF0mcKNFfSmbCPiYRsSzuLynh2Hbt6JeXx4QGDXiif38+jMW4u9dedMmpQ+vMWlxY0pr1Z5bCOTF4PBHxHyribY6nT1nT5PE12KsxN3BPsuNW7DMq4v88sSMNLG9UJwOrCqHmG1i7OHY1H1ZnfvRy5Nb40cuRv5Mfy8o2EI22Q7rFw4/LkAnSb9qHxM6AwTO/w9hOkldaHXPuJhxZzo9zuZ+5z0+gRtDmB3fAtRKdwhb/mNZuE35cOWE4i0b2Y2LjuowyhoclClxORYlmG1nGcGnPnlzQtSuDa9ViaO3a3NKjBx/GYrxW0pshtevTND2fI4qa8uNJJSn86OXItzk+GTdwTzLK+dHLkcNuX5FiYHX+2/07xsCqih+ri4FViR99A8uHjz0HEyXFlTCvNnr+v4/7fjtJL0laKelbSX/fwli+gbUHIB6Ps2DBAp599tkdVry9HMuWLeOWW24hEqmBdCzSL+7kZD3GRLjqqqtStr3tttu49dZb+fnnnzcZ6/LLL6dTOJwUXV8qUQPr9ddfB+C3337jP//5D+eddx6N6tblcIn2StRPiLtp4AdJ1IxGCds2fdPSyAwEGB2LcdhhRxIIhDHGUFIygiVLliT3+/XXX7Nw4UJWr169Q6/NngLfwNrFsasFWTUTaMNnrKLLyIfoHLuPYUf9ulMNrJKS7+nY8Sbatr3CvQe+8wi0+VhWBp3H3MvwU9ckDawh1y6l7QGX0WzySfS89YUqDaz6hRXLabJtw0THUDNoMXlwvYQ4qyTQ4hMT8dLQnmTaNu0siyyJTInWEraEI1E/FKKlZXGxxERjyLAsHu/Xj/h+sWRwjidccfbJggE8ekcRX749iLc5nlOuHpQ8vmAkyPXxu30Dyzewqmfsaj6sZvxYdvxGeox7jk7Db2fQlK92qoE1fPgqOne+jw4dricQqI/0fx5+XIkUokXfMxly/FJiZ0B+x2FJXgnUyKXTxXdR+vbaKg2sBRtPZsjeLcgP2RzkGFqGLbq0zmDFo8M2y4/fjB1Ms0iE+sZQW4kSFB2NwXH5sUE4TLYx/F3iBIl0Y5i9115b5celdw3hsTuLeOeFvr/LwIr9HymmXacxd/gGlg8fPnxsA3wDazfHkiVLaNu2C4FAFuFwLXJz6yQNoe1FYnliGsFgE6Q0pH94JieLkSwsK8jUqdNZsGAB6enZRKN7EY12IRrN4tVXX00Zb8WKFfTo1ImG4TCjw2GygkGmTprEmjVrGDduX8LhLILBCPvuewDz58+nVnY2dQMBwhK13Sdq+UoUL/6feyA/upOSe+65h3Xr1rFq1ark/tavX8+hBx5IwLLICQapmZnJ448/vkOuzZ4E38D6E2NXi6/qJtAqZRX0O/gDAuE6WE5zbKcddiCbXvu+mpiIb21ZzH6eSCkuHvfERjfWUFT0MMZEsKzuSI1cDhyJ9C3SJ0idkZpjOc1Jq9GeIVN/ZuCsxQTSamMFijH2QRgni3anzGR/vmd/vucSnuQSnqRwfN+kqGncNp9TTmrOvMe6E3+yDJ6KsebR4YxrX5ewE8A2NsNrN+CrkSWs2zfGC0OGcGK7dhzTsSMdsrNpbQwvSNzjcuNST8bqZGMoq1ePJbFYMrwt5eN3lHHUwIYELdEmYhOwxPQzu3HD0yNTMgeu+P4qjop/yFHxD7fNwKqyiHt8K8GWBZp3WZNvYP0Z8PnxL8aPw6b/SmZ+Tyw7HzvQHWOCtB8wd9v40cuR28CPAwa8TzBYH8tqidQJyUZqjvQu0o9IByPlYtk9sAPZ9JnwJoUTb03hFROoQ07hYPZb/00KP17Ck8yPn8WLG87goscncPKJzbnlpk78umw4PBUj/mQZZw9sSVYogpGhfVY+rw0uZt2+MRaUljKrUydObNeOEY0akWMMt0p8pER9rGc9/HibRKNweLP8yJ0xbp1SSNg2tIzYRG3D4GENeWfNEfyX6dzKHcko50cvR5bdF0853732vSeVHydv7jr/AX70cqRvYPnw4eMvDt/A2s0xfvyBBAKjkFYhbcSYs2jYsBXxeHy7xl2+fDnhcLrnidrlJIoXn4N0A1IrpEOQFhMM5tC4cVuMOdNjcJ1LkyZtufbaa7nrrrtYuXIlAOvWrePBBx/kwgsvZP78+axfv56mTdsiNUA6DqkLUjaFhd3Iy6uH40QxEt0knpY4V2KMUpchHitxxJQpm5zD1VdfTfNwmM/dDK5bJdLDYX755ZftujZ7GnwD60+MXS2+qrlAy64zCJnpSHH39j+PaFY7yo6J71ADq7R0BcFgPaQb3f3EXfMqx70XLPf1CqT1WHY/mhedTv0ekzHWBM/xLcLYAfb++m1GfraAs368h0t4kqFnH5AUNZk5EVavKGPtqhg8FWPd46U0LshBqo90hCsKC+hYo4AFJX2oH62JJCw5WBIfujz4sESbStx4rUTXGjU2K9Aem1lEQcBKPhB4RyItYHHh7SUpwuvCjy72DSzfwNr1sau5r5rzY4seZ2LZPd35IEgvYkyQksOW7HADq6BgH9ekKue6K0jUwCpvUNGKiiXXJ5FdewAd9r/O5c5ybjkUK9iAPg/cxD7fvMNpX96WYmCVx9pVsWTwVIwDBpY/UDgUqQ9SFhEryPvD+9M1t547tiHXDnCDKjpmS4naq+X8+IFEwJjN8uOSq0sIWYanPWO0DducfFmfbTKwhty0NIVHi/Z/zDewfPjw4WMb4BtYuzmysvKRXvZoltUYs21F1beEZ555hkiksTvmT0h1kPoidUWqh5SBtAQJHKdcjH3pOY4bkGyi0b5Eo23Jy6vHp59+usl+nnjiCYzJRfrN/dwGpCIS9WZmIm3A0TiOdwe+V6KZxDr3dVyiVzDIxRdfvMnYw/r2ZU4lQdcmGuWhhx7armuzp8E3sP7E2NXiq5oLNGMCSP/13NLLkMSQqT/tUANrwID3SWQUlHdgXYiUjjTCFU1RpPM9x3EVOXWHkl67iERHrgrascJ1CddqiCwHYzl0+tsQJj95ToqweWNh36Q4u/eUzhjVJrEEB1eMNsfIpkYgDaNT3Pf+nWJgfa9EkfcX3derJLpZFoe0aLFZgTa9pBFHVeLI0SGbfQ5uk3J8Vy29xjewfANr18eu5r5qzo81ag1Auj6Ff2ynLV1HPLLDDaxAoLZn7vmTa7R3QjoGqRbSMI+59S6WnU6TQcciebklE1ljSGvYHBkLY2zqdenA6V/fvlkD68vbB2FkI31IxcOF/bBVQLusHBwzlMRS729IU1rSwIpLtHUfgpa/PlKiKCdns/x43/TOdArZKfx4mUS/fnW3ycDqefZLKTw6YManvoHlw4cPH9sA38DazdGsWQekmz2/rx9g28Eqs4x+++03FixYwA8//LDVcRctWoTjRNyJyRVIPT2TkThSMYmsrI2EQu0IBDKR7nLfX4NUwyPk4tj2JEaMGLvJfmbPnu1OdLxzhJNJPMX7wH39IDUU4EMlCnm2lOikRPHj/hIRia7t27NixYqUsSeMGcNxlpUceI1EXijEiy+++Mcv+B4I38DaztjVgmo3EmjhjBZIt3u44p/YgRxKj1q3+bouB7mRUo+pKlG2kVhsJbHYSoYN+8rtPPiqu5/hLi+V73cBUoRETcA4xhpNozYzqFt4MMaM83DlW0hhZE5EWo20GCfcjj6nHoTtVGQinHtJR36Jj4X5MU49sDnSgZU4cQpGNkGThbQx+fegOtFL4j2JNyUaKlEPq50S9bEyjeGA5s35vLSUb2Ixvqkk0M4f34pBASvZbn6jRNuow4iJrZPHZtkW1228i6nxT5ka/5TYh1TEnZ443RPl1zxFbHmv+XpP7CIDa3uFmm9g+fxYzfixbptDMGaKhzeWYkyUvhPe2To/ejlyK/wYi/1MVlYPpIvc/ZznzgnLuekXEtmqz7mv55BeoyuFY25BVt0UU0eKYJwSEssOf8FyxtOwT3eeYnYyfomPTcaTs7vh2PUr8eOdGOW5433i+ftp5Es8J/GZxDAlOhU2lqjrzh3716rFuyUlVfLjy2f2IscxrPTs7DDHMPagNizimJQaWOX86OXIdgf+I3mexgpQdtqGVH5M4cjt5McdbWBtL0f6BpYPHz62A76BtZvjjjvuIBjMcicS1xEON2fKlKMA+Pzzz3n00UdZvHgxt912G5FIJqFQTWw7yMyZJ251mWFJyQjC4UJXvE2oNGHYH6mEUGgwAbu8JbyD1BppL9eA2ujZ/iVycuoC8Morr9CrUyeiwSBtmzbFstKpKI68ksSTvADeJ2yO+uNI1LRtHAlLop/EaRKfKrF0pk7Nmnz++efJ43/ttdeIBgLMknhUYmgwSOe2bdm4cePO+0J2Q/gG1nbGrhZUu5FA26v0LoyVgXQC0t+x7BzaFM9JtIavQqANO2gFHXvdRIvCM+nZfz5lY+LbLNBatvw7lpWLdKIrxv7l4bO4a2AdgGUPIhCqQ8fim5AJIYWQCpHGIyuKrDSkdZ7P3kNOs5Z07F/R6a9bz1xefGMQSx4p4YFZXXDsAqRf3e1XINUnN5hGwGSQeEBQPtbZ5AUjBIwhaBKt5PtI1JA4RYmM1ebG0C83l8+GD99EoC25poSCtAD7OYZbJEoDhob10ikeXlFkvlHXpikCzTewSBFovoG1nbGr+Ww34sd+B72P5WRirIlIF2HZrchvPHqz/Fg2aQNdBz5Ki45n0Lnf/1E6et0282P37g9hTBRjJiN1RDqr0hyxL1JvjLU/xorSsfhWApFaCUNfFYXNE9n2b3o+9w2SePDXWUkDa9nGMfx70RDe+mQYXz84CMvYJGptlXPx3lgK4sgh8dCgfKxXCMgmw7aRRIYx9HJNrIlKLLseItEgFOLtwYM34cf4XWX0aVqDHgGLGyWOtEVayOah9/bfJgMrr8PQ5Hlm1++1KT/6BpYPHz58VAnfwNqNsW7dOk499XSysvIJBLKpVasZc+bMYf369Rx33MlYVoC0tHZYVhBjQkiPuz/2iwiFCnj44Ye3OP7q1as599zzyMmp40463nEnBe9hWekUFvZgwoQDsCRyFSKgYqRzkVq4E5SFnonEuXTvPoAvv/yS9FCIWW7WwKmSa1alI8WQ8rAVoZlEWA7SNUiXEwxmMXfuXFo3asQUJTKwvLOlK92naoN79045h+eff54hxcW0btCAIw8/nKVLl+7Mr2S3hG9gVRG7WiTtiQLN7abVY9zz1GlxALWajqco9lhyQl52RJyee79I+75XUzzqdUr2/4FwWnMsuyPGmoCxsmjS/PgqBNo6Tyx3YwllZd9RVHQbdeqMIxxuijSJisyqx7GsDOrVO4RW7c9jYNkXREyARnJoqwABpSGFyGjUGWOFSCx1LKerq8kr3ItDrhjvEXEiwzEELDF1n/r07VIHy+S5Dw7ysU0aI+rXpE40A8eMRnod6Q4CVgbndenCo6WlDKlbl6Mk6kk87uHGd5TowNUuPcr3o4bCmbFkxJ+M8dnNA5lyQH2KO2Qy4/DG3LHoCEKRCoE59Oz9uZR5HBD/jgPi3xFbSEVc54mZntjPjc2KsjWeKP8bVcdoN3wD68+Gz49/QX7sf/BHNOxwFHkN96b9gKspnbY22Xmw337/pX3faygaMo/SQ9aRV28EllUHYyZi2Y2pkdOX4fus2SZ+jMWW0KfPszRocBCZmYUY05ZElilIX2FMGrVrj6VpyxPoN+x9MtKakylDd1kEFEzhPulODz++i+WEuGP1VdzHdVz+8Tm0bpZJ1DEEbcPAwmyOP7gFlgkjjUFqixSmW24mvWvlETRt3YcNzxC0WjK2cXMeKyvjqI4d6WDbjJc4ycOPaySyJDJsi9dL+m7Cj8sfGMYZ+7WgT8cs9t+7Dre8fTivcCavcCaXMi8Z5fxYzpElz/yI5YSS59iq9/mb8mMKR24nP3o50jewfPjw8ReHb2DtxjjyyBmEw+2Q5iE9RjjchhkzjufFF190s7LKM5g+dg2i5zyThBM54IBDtrqPs8+eRTjcgkSxziBSXSSH/fc/iD59hpKVVZM8ibCKPOJuNVIGjpONdDy2fRCOE+LSSy9l1qxZDAqFOMtN4ZYrrhy1RxIXSKxXoj5BmWWRk5lL1659eeCBBwAYG4uxvxLLY5Z7JiGTJCa443k7EfrYfvgGVhWxq0XSHijQBk3+koImY7CcLCIZrek09PbkZLz0yPXkNRiFsXKwnaEYK52M7L2QKaEiE/QTZIIMGPbJNgu0WGwJRUW3EwzWd/mvDcYMwZgQhYU3JYTFeOjQ9XqiEjkK4Wg/92HBEUhBstr3xgQGuaLqVuxQDsPvuoC531yEsUxS4JziZpM2DlmMG1IXxwojtcaWmCZxokS2ZWiVUYOwFaYgkssphYW8HIsxLxajd14e50ukSbzh4cYf3fG7GMOs9q02EWjxJ2NsXF4R+87oniIuj3v3Kt/A2oJA8w2sKmJXc9QeyI/Dp6+iUeEMnGA+gXAdmhX9ndKj1yfviZbdzseYELYzGMuuRySjNcYq8JjrK7HsFhR2vfV38WO/fvPJzOzqPuQswJhRGJNF/fqHJflx2OjfcCQ6KUxIXZBuwlvM3dg1kR5Emocd7kD7Q8dzH9dxH9fRskNdplqG1RLLJIYHDMN75uHYAaR2WLIolZgl0cK2aB6NkumkkxXIYELTFrxQWsq8WIxD27RhiGUxVOLySg9AW0rEJErza1bJj16OLDevtmZgNT/ktBQe7XfQB76B5cOHDx/bCN/A2k2xYcMGQqG0SllOrxIOZ3DqqafiOBNJ/Y2eSGIpTOK144yksLALJSWjuOyyy1i9enWV+6lVqzHSo+7nviXRlVAEAlESHQkvwJaNdFKl/Q3h0EMPZezYv1EvtyaZjkO+ZRGUCCiEUVss7UNAIabIor4CZCuQMqm4RaLPXnulnPPzzz9PwBiy3EnH5RKHuIbWXRJpwSDPPPMM69ev/7O+ip2KNWvWcPPNN3PkkUdx/fXX7xJzbo82sHa1GKqOsbMFWqVlMbHjoOzYDUSz2mDMBKT/IN2OsbIoij1ObDrsNeQuLLsR0s/JDIBEo4ljU3jJtjvTuei+LQi0n934jljsOwYMeBVjIkjXIX3q8qhDt26PUlq6jPbtL6dWrX3JrTmAuhJRtfMY+SANpNmkU2gw6nACWXXJaNaG4psv4ZD4F1zNgzQsapYUOBE3eyoiEZKFdAdRNU4WIUbinxI5js2aA0r5LhZLxsexGBcVFlLfshghUapEt62VEpMliiXOlxjXtABuiyUj/n4ivoxP4sv4JJ5dtA9OsCL7qnmsmFPiCzklvpDYknWJeIKKuMgT3sLQo+KJqHL5UeUoF2qbKVhcXQ0sN46eswfzo8+Rfz4/ejnS82+7XptDseyuSC8gPYNlt6Fp55OJTYeBBy3GmCDS2y6VrMGYriSWOnunXUfTqOn0bebH0tKvCIUaIh2JtBjpLIxJp3nzGZSVraCo6H7q1D2A2nX+5j6sDHgMswEV3Fe7IeH85oQLGtDhpKOYuOYTruZBLvz+JiTxuRI1T9tLhCWiMkgH4mgSE+SkmPVRY3hrRB/iB6Xy4zP9+xMyhmkSTZWoibVR4jp3/vi0RJ1woEp+9HLkg1ydjHJuTOHHJesoufsHnLSs5PnltxxWNT+mcOR28mN1M7DcGDpzt+VHHz587ET4BtZuirVr12KMRWrByv9iWTZXXnkl0ag3I+oDpCYYU56tNQUpiOOMR5pNONyBvn2HbFITa+3ate7ywcc9+/gJKYhlHe2+juOoIUZ1PROT/+E4aSxYsIBJBxxAaSDAKpV3gXFIdPIqP7Z3sGVzmZs58Im7o7jEmECAIw8/nHg8znnnnEN2WhpBiWbGcI1EcyVqvQySuMgVf7m2Ta1wmJYNG/LFF1/som9nx2Dt2rV07VpMJNIKaQaRSDs6dCj6000s38Dy408VaFUYWD33fRHLzie1ltQsatYfQWw6NGx/JNKMVDFm9kGmtYdrvsCYEL37LaRbt6fo1++9rQq0li1PxLL2ThnXmL1p0eI0atYcjmW1RpqFNAQjEdTwSoJwMo33O4bYG3Fib8QZ9q+7qd2yCcaI/PxMGnVvnhQ5kjCyOM3NBgirNZYcFnkG/M3d7vvxJZsYWB+WlTGuXj0siagSxdwjEoUur/a1Lc7p3XKzBtaiZQfQuHlmxbEYw6Hv3r3bGFilx65nwGGfMmzGCt/A2jb4BlZ15McqDKzhR69yDaoPPNzzAnYgJ2HwD70H2+laiZuuQMqmogP0WiyrLR06zaVHj+fp1etlyso2bJEfe/R4AMsqoKJbK0iXkp3dj1atznFrCJ6MdARBCUfeJhRXVnCfMQx+6mvG/e9lGvfvgWUZaqSHaTd8L4zk1rbKw8hmtAKcIhFQkKi6MDf1pOjo2Nzfv8smBtbHsRjntG9P2OVFSyJDosA1r06WGFIvZ4cYWLV7jU7h9V5HvFztDayymXEGHv45JUf96BtYPnz42OXwDazdGMOG7U0gsDfSUqQfCQRGEIuN5ZdffqGgoCGOMxKpD4mlL00wxiEzM5969ZrhOH/z/OYvJxiswauvvpoc+8YbbyIjo6b7wxNFugDpSxxnLIFANtJsz+d/xZgMjDJwnGJsO8K0acfw3XffEbFtbEVxFKGLbKQ0KroVJiKqOhwlka4A6TIcLNFZIictjS+//JKbbrqJuuEw90oEJL7ymFy9lOi0lekaWr8qsQRxf8dhTFnZNl/LxYsXM2fOHObOnctPP/20M76u3417772XSKQJ0ir3Wq0hEmnDTTfd9Kceh29g+fGnCrQqDKxuY57GchqQmt10Gdm1S4hNh7Z9LsOyu3nE0RosuzFOoCaW3QvpcCwrn5p5Q7CsdCyrCcZEyMsbyfDhv25WoLVqdRKWNTKFryxrFA0aHIIxWaTWtipvPvGS+/pNjF2DHnP/ReyNOAMf/YxgMMClSiwVvFTCqLz5RbnYCWPJ4r9KZGEFVchRqugSeKlEy7QIGyeWJcXZk8XFHN2yJeMbNiRkDF1tmwbGkGkMecYwVaKLY1EnHKBzTjqdaqVx0b6tWX9zaVKcfbxqIgOG10sRXbEZA6oWaH9BA6to78cJhOsg2Vh2Gi2Lz/MNrK3DN7CqIz9WYWANm/4biWLoX3j46D9YVpTYdCge/x+Mle7OFV0j3hpPKNIIy26KdCSW3YZoWjuCoQZYVgGWlUs02oaBAz/ZLD/27PkglpWPtN6z30vIzu6DZWUgzff8/Qh3LnqZy9PvpPBN25lzqNmgDgfZCf57SOWZVjYV5S8WE1ZN7pHoLAtpKHspxGp3J/+WCBrD1w7mqU0AACAASURBVOMGJw2s1wcO5MQ2bZjUpAn5gQDNLYtCyyKgRDbXARIx2yLNMnTPz6RNboSjBjRk6VVD/pCB1fmGe1LOq1a7vTfPj9XEwOp/yEek53QisazTpnbLCQyfudo3sHz48LHL4BtYuzG+//57evUahDEWxlgUF5fw448/AvD111/Tp09/9wnbQqS1SLMxxqGwsCfSnBRRlpbWjTvvvBOAN954A8eJIj3mPln7P4/IimJMFKkJiZTxONIdOE6Yxx9/nGuvvZZ33nmHjRs30rB2bYyiJJbfPIPUmzRFcLSvR4j+FyOLbImxEodJ5Eq0kBjevz8A/YuKuFKJNvGZEhtUsZwmLDFF4jaJ7kosnUHiDgnbSiMtLYcuXfowf/78zV7HBx54AMcJE4kMJRrtSXp6Dm+//fbO/wK3gtNPPx3HOSjlezJmGjNnzvxTj2OPMbB2tfCpLvFn1W/5HQbW8GNWEwgVIJ1JolPpf7Ds+nQceCOx6TB0yi9E0ltg2X2QzsCYRjjBWjRuM4MWHc6kSZuZ7FV0D8aKIj3g3k8/YVmFtGp1HpVrvJSVfUOPHvfTsuVJJGq7XIn0JdKVGBOlVatZGNM55d6ULiOS3hJjwhgrD2OFaDH4bGLPxok9G6flwedQHAjwtsthqyWiCpKoL+jNwopymcqzqLIIytBQopVE1DG8OLUnzI4RPz7GRX1akWYZxprE9ne6B7NRYpwRfRtkM71HY0Z3KaDANtzgbtMyaDF9XEOWxcfy6Q8jaNerYcoxNOnbngvXPc6B8W+TEVsYT8R1VF33arwnkkJruSd+3kyUC7WdY2CVTF2CsSJIt7i/Z69i2bkUjZnnG1hbhs+PW+LH6sCRnuVfNRvEMNbeSEuQvsKyB1C35cHJeyK/4Wgsu5nLj70wJp26TQ6kZeG5NGl9LB173ERGRhek49z7ZB3GTKRmzdJN+DEW+45+/V6gffsLCARqIR2G9BnSPCwrn7Ztz3XvCW/G7H8wVhq2k4sxNZAJEojWTHJOeoPWZAYCvCyxyv1QBwmpWyWePY3xCtBHwihEWEGyJbooUU/1shFtYHYMZsf41749SLMthtkW9dz5ZfnDgCsk6kYDzOzdhEP7NSBsJepoPSIxJGDo0jSDnzaMYVl8LMviY3mO83mO892+iImozI99bn8DO5KWPKdAOIeSqd9vgR/jO44f/6CBVTYzTlqN9sgcRaLj7RdYdleaFp3kG1g+fPjYZfANrD0A33zzDd9++23K38499wKMcZAaueZTLaTGSL2QLBynPRWp4wux7UByyd1xxx2H9LdKk4ZRSGe4E5VD3f8GkHKR0th3331T9v/SSy/hmDQST9vKx/gFSwEyFSCiblg6BCmNoGyGuBOLDRL5MuRIFHboyNNPP82Abt04U2KuRI6bhbBSoqZCGDmElEGWgjzsGlqvSIQUQDqeRL2ccwmF0vj00083uXbr168nJ6c23i44xhxPcXHJzvvCthGPPPII4XAdKrI8fiUcbszdd9/9px6Hb2DtYVFdxFklgVY84XWiWW0TJo8VpWnnUyg7Kp6ckA856CdaFZ1HONoMY+ohnYplxXACeQwc9T+KejyGbbeqxGtzqVGjf4pAGz78e3Jy+mBZedj2AKQQtp2bECSB2nTs+A+ys/u4vFresn0VltWZVt0uZOghv9B779coOetHYpdA7Nk4/W54j1AwzeVMEVKYkRK5snA01uXUCgOpthJ1Wh6RuFGJ5YBlEr0aZybF2Q/TSghZhoUS70qku8ZV+cn9n0QNy2Apkbm6txLZqSjRmTDsGF74z0CaNk9P2XeN+nmc8f09VQq0sgUbKTpqHvV7TqbJoOPpf/BH1d7A6jjkBuxAz0rf+4nUbXOQb2BtGT4/bokfqwNHevixZOr35NYb6v5bNOQ3HsPQqcsrGl1MXkfHfjeSmVuETBrSdIyZjLGiFPV/nKH7LnM/u9RznyzCmOAmBlbTpkdhTBjbHogxudh2HpKwrEwaN55C8+Ynkcjcn+uOE0eaQs16MUoPW0fx6IUMPHUx7Udfk8I9crsTGjmMkkVUIqjaeJcoBrQPJbIIS9wrcbdEHYmBEiFbrL2gNMmRHbPTuNT9YKYSD0HLB/rNNbzSbIORaC3xg/veGomaAYt5L/bbZgNr4KOfE6pZO+V8mnU7ZSv8uOsNrP6HfIRMiIpMf5AeI5TezDewfPjwscvgG1h7ICoyqN5wf4wmIfWnIs37WaQIwWAOaWk9sO0gs2dfmvz82LFj0Sa1XAaSyNq6kkThz41IX5MoHN92k2VtTzzxBAGTTmp75A1YSucJiUuUyJbKVKKFcanEdIm9lEjtTjx12xvHyaBN6zbYEr2V6FwYcSPRPvkH91jOICSbNCWWH0qp9R6CwdGcfvrpm1yrzz//3P1x9dZweAPLivDaa6/t9O9qS9iwYQNDh44kFKpFMLgf4XBd+vQpYd26dX/qcez2BtbM5bteFO2uQmsHGlixmVB2bJzBU75h2LSVxI6pNCE/HHqNeoVExtRn7r28DJle5NUpo9eAVzEmE+lXz71+LLVrT/AIg9W0b385ltWGCoP/Q9d4Go5lxTAmijEZJLLBQi635hIINGDYgSsqhMO5iSi7byPpmflYiiA97/LwTUgOV0iEFcBoComs1grx01diqXugtZXostq5aRrMj8H8GC+e05P6QQskfpIIuUZW+ck1lxjgirZ/K9H04mz3va9SRKPHOGvbgP0Wv8SU+GdMiX9G7MN4RdwDzfc+E8vORZqJsSZgWen0HvZvYgeyGVG2ZDPxoyfKt/V24WKHGVh7ld2D7bTBu/zUWIfRsPBI38DaMnx+rK6xGX6MzYSSqT8y5PCfE/zo5cjDYdikFVhOlmdetg5pKqFwQ0rGfO8u+3vFw48PEgw2SOHHvn0Xuo0tPna3+ZXEw9E2SAdQkaV/KYmSEUUkllen0X/MRyn8OPS0ZVhO2MNBA91jehkpnfESjRUmqEFI9yJNQwoQlnjUw3UTZOjpjrHyn8NgfowNL5QhiS/cbQolrvF85iCJRhJPSHykRN3BEs/7jcIW9ZrXw3YC1Glaj8MePZUreCTJjV5+HPD0x0TyGlXi004YK5N2RVdvgR83x5F/gB//oIE1aMpXyDhI33u+99tIy+7oG1g+fPjYZfANrD0Q5513HqHQaM+PUQ+kO1IMnUikKbNnz+b2229n8eLFKZ8/++yzXWE2C+lNEkU4s0ikpn9P4snaAKTLkXpSp04TVqxYkTLGypUrCQeCOGqB9DmJJYynI4WoZwwdlMgKyHAc0gNBLIk2ErZCJGo5RJAcMmRjSTzvHvg6iX4SGdEszznd54rWAUidMcYhEEg14Gz7EGbOPG6Ta7VmzRrS0rKRnvZsfyFSE0KhdD777LOd+VVtFRs3bmTevHnMmjWLRx55hA0bNvzpx+AbWH/R+KsKtC0YWMmoLM6mQ9uel7vCKs2NI0l0ImyDVItQuAlZNXpjWd1JLCc7AWOiFBcvTBFo+fmjSHRY9Rr4/anIJtiHhHmOK+KuR5pGdvawVOHgGlh9Zr+NrSBGR1caszPHSLwtsbeCNFRkE0OpnsQFSmQK1LHE+Fhtnrm0OxteKGPJTSUELcNLEv+TOFGipsTpEoOVqKdlZBGQzXGyeViiscS1Siw3rLwvywlwzjc3VynQYh/GGXLDzxg77P4mVCznyS0YVq0NrGFHryQYqYvMZKTXkGZjrCh9DnrLN7C2DJ8fq2tsKz96OLJH7DkCoVruXCmAtC9SM6QGSM2wrHTq1D8Ay6pP4kHlJVhWTdq1uyqFH9u1m4PUtxKXnYm0v/v/d7v3w2oS2Vy3Il2IMRlV8mPdjhM8PJRFxYODk2ijIN9LHCGblkojqhAHK5Fpv9jd+WcSabKoL9G5VQb/z955h1dRZn/8vFPu3JJeSCC0UBISQgshEAgtkECSe6mKFEEBkd6LXbE31LVhF5fFirqKDRVx17Wvuvb1Z8OGDcXu0nI/vz9mkswNiQQFQbznec4DuXfKO3NnvvOe75zzPXedVcAPD9skVm4TH5eK3cRirdgvPmc7rsSLiEKJYqhYbBJb2H2zCCvFyQZTy7CF8a9BN30se/Hi3fCx/70vY6Wk1cHTw7BfrK5HN5KpnLD9oCWwQksgpVUIpffH1hq7FU1Pp9OQq6MEVtSiFrUDZlEC609oN954I35/F2oFjSchMs012fgIXffUS86Ew2E2bNiAphmIdHYmFPGIdMImtHIRyUPkOERCiBRSWTmq3nGMCIUwxYMtDGkQEC8+Efz+WBIS0snL68bVV19NvM/HXSIMFg8iKdiE2wWIFDsBqM4TrtnSzSLEiHLGswO7PPI21/FNQykTm9iqQuQhTNPuilifXXnlVei6H7uMZ5wT/D6Ox3MYJ598yj79bf6IFiWwDlL/owZf+4HA6nvEv1FagFoB9cewSfArnb+rUGoiqU1HkpW3nLj4PqQ1HUPxgOcig4FQmNTUoYiUUpux8yMiTbAzV+3yCltY+Lma7zWtOx06nE/oaGrdEbkuOfcdlOgYMqlO0JdFulI8LXbm1GAR8qVa2H13V0rH6+uA5U0ls10Km94aTI+OsWhO4JUkgt+jGNIvCV2vFkvegch/8EgCBQ1s18bnhei+DpTcdkVk1tWd1Hi/2f9BaXFECuk/iq6nUVb2eZ2yl82Ov+/yD13uDtYaGaBNcvleirgPnPo2TTJHYnhSiWvSm15jHtknwVnoxCiBddD6H5mg2scEVvnMn9DNROzOg7uw9UuTERlPbfb5VZie5nQuvJaExBKSkofQvfCO3fAxL28ltrbqT856YUTKsEksnO35qJWPcMoHU0L14mPx0c/UwaOLnPVmoIvJ3Q5JNV/sTNQ8U8cUwRCNbAmgi4YhCk2zsLwZ+PxtiInx88hTJRw7uSUesUuwY0QwlDC4XzLJiXHOXO9bRD7Dkj6McXRe4z06Pq+BaXWOwGtlTCN35tER+Fiw5C4Mf3yd8felthzvf4gIRUX/aAAfN+87fHRj5F4SWOXzvqdl59mY3mb44nLIK72S4LJwlMCKWtSidsAsSmD9Ce2HH36gadNMp0PhLej6cEQ8aNooRE5GqSb06FFMOBwG4P333+e0005jypQptGrVAV33opSBUgE8nkQ0zaRPn34UFw92OhD+6Hqw3052dvd6xzFy6FDOE+FpsUtYdohgiQ+R3oisQtenY1kxxJsm22se/h2oLXWswi4FHE5r8dWIb84QDY9kY+slLHXWc5cAvoBlBUhISENEEROTxNVXX/OL52z27NnoehvsbLO3EAFNm868eQv2+e/zR7MogXWQ+qEenO0FgdW+x0kobaILA951SCZ3d6ynMMwmhMZDaJTL6wRobdsuwybOKxE5G7v8pbps2s4MsAM0HZEuiMQTH19MefmP9QZooRuhSat8lJjYZTUvIDIbpftoN3kKlseDLoJHhNiAxfDTDycuPbEBsslClxgs8dAkxaKDR/Gu2ILwJ4jQMsXDVVd2xrKaYpN3UxDJaGBbgv2ywNbxMgL5DPzbXxoksCqW/4xuJiByryswPRKRDAwjlYED/33QElg1Xt/1FiWwGrJDAx8PZYxsJIHVc/h6NCOzDvmchF2qV/33TkRMBgbf/kV8LCra6OBjZwcfByOSgJ2hDyIPOHMz08HODEyzGQMHvl0/Pp4M3oRmLkwKYGfAmrSZMZO4xCRE7OwpXdcYMHkAo1dMRFcaPrFLpy2rel8j8Epn/BJPjM9DrKnYKLY24FoRvLri6Sf7OvvZ4ox3OyJjsDUNFdlFOUw8bziWv454vDaP7CkTCL0VpuLln2g1bsZueGr60xBZ5FrvWufceCko+NtBS2D9Ij5GCayoRS1qB8CiBNaf1DZv3syMGXPIy+vFxIlTKSurRNfTsTUG5mJZLTjvvAt44okn0HXLmTR4sfWyfkbkG0yzgrKyIF9++SUAW7duxTR91LY03oXHU8msWfPqHcOVV15Jjtdbo+NyoYgzadpW84A3zQmIGDQXP3YmwPjISYPMQmQ6IsKJIhwmJqb4EHkZTbPo2rU3SnkRWe9a5xy6du3Njh072LRpE//73//2eL7efvttDMOLyN+dSd4/Mc1YnnjiiX36u/wRLUpgHaR+qAdne0Fg5RavQNNLXRjwvRNAvej67DJi4wv3SGD17/+qg4XjERmLyBBEDJQahaYNcoKzmdgk2VUo1ZVWrebZ6zdAYPVa/CimCLr4UeKhnXhJNk1yTz+TYV9/y9Jd/2b+1n9w9c5buTZ8O1ndWtNBU3gaJJ5q3SP1lwT+kvvjfWi6z8HN7xG5CN0Xy6StrzRIYIXOhm6Hr0EpC/slRC4izRF5H5EpNG06JkpgHVp2aODjoYyRjSSwisc8i9ISiRTqbo0tA1H990so5WXo4d/9Ij5WVPwPw0jDzsA/AjuTyYNSfdG0wx187IbIZkT+hsgwAoFuBIPhBgmsgjn3RBJBopOnFC2GDSf46Rcsq3qBBd//i8X/e4bruIOKJSGyLYMHROggFiKpSE0JdoAM8ZIgwjGRk0lKNGHEiHQ0TUfkHefjk7CrCl5A5B0MM0hWrw6YVnX32R8QeQDNjCX4+G30XvNPYtt33A1TW/ecTd9ZL2JYydgl5kXOmB5E5CYsqzXB4NdRAitqUYta1BphUQIranz//ffoukl1ZpE4ZTCpqS1p0yYHkTjsEjxB5GvXMs/j98dHbOvaa69D1z34/QPx+dqQmZnDF198AdiZX6tXr+bSSy/lvffeY/v27YyurMSrabQWHSUau7dEPhu7BPBO598YRD52vvsCkWaILCZWvMSJoMlwZ+LxMoZhsXXrVlauvBrTjMFuRz8cERPTtDjnnHP45ptvGn2e1qxZQ2xsMrpuYVkxXHTRJfv0d/ijWpTAOsB+KAdi+4jAKp36mVMiMw+RRxGZi6gYNK0p9tv8RSgtQOHA+whNhNARLncFawMGvElh4f3k5l6EpsWhVCyaFqBt22VkZ59B27ZLnaDEndn1AJa3nR1AuAO06uP5C+QEzyNkeCOCqYVid9tSRgJKN/E1b0/5rRcw8fV78Bo6P4iwSAQlcVR35/pt7kdkNCKnEWjWioEXL8MIONkNTTvQ+7p/EHoxTOgWav00lzvHlZ9/O0pVaxBWZ+Peg9+f6wrG3qrH3WSWO4CrDtCqXE6tH+64m8A61uVzXF4dnLmvlYYCtOp7KkpgNWRRfDxYfS8JrODcMLHJhShtqEOoXIwoyxFbX4jIWWh6M9p2POkX8bG09DMKC+8nP/9WLKuVs75BevoR5OZeSHb26SgVg8jzLqiz74+yys/rx8fjoM/8p/AoLQKvKquJeS2AMnwYcal0WHY8c3e+jN/v4wkRHhXBEB8iLbDF5790ngFpiCSSI1oE5nYWE92Ip0VOK0yrK7b2aRqRGqhfIqII3X4BvmZ2Yw0jNoUOc84lo+LI3XBV98TQbdTNNcc1ZNxW57uzEPnU2eZXiAjl5a/uP3x0Y+Se8NGNkXvCx9+IkVECK2pRi9qvsSiBtR/tpZdeYu3atXz88ccHbAzffPMN119/PZdffjkfffRRzefhcJjXX3+dRYsWk5PTAzuj4DJE1iLyISLP4vcnoGl+RE7EfsvkQeQN14N8HampLQGb3MnK6kZKSgvGjJnARRddxN///ne2b98OwHvvvUdqanP8/i74/UMwDIvVq1cDcN9996FpphNIehD5p7P9z7Hf4F+GyH/RpQhDTGeZQifgysYQk0vE1jHQ9bGInIJlpXHccSfVHO/w4aPRtExEjsMjIXRRpIvg93hYVadDYl0Lh8M899xz3HPPPXzyySf897//5YcfftjXP9Ve2/bt2w+KcUQJrAPsf7YA7VeKuPcf+xpNWo3C8rehScvR9D/8NfL6XI7H2xpRAbz+9nTvd2dEgDaw4m2yc84gK+d0UpsMd1rDd0Api9zcv9C//8uUl39Htfhuaekn2KUmn7hwciWxcb1+kcDKn3QbLU0fO5yVwiL0EAtbS2Y2tlDwajQzQMnVpxDrMdkhwmgxnf29gF2aM5+63Qqr3azzt9IUStOdv2+mNvvibmKaZ7I0/DKjv/uSYR+9S/CFKpu8agSBVVb2pZOFVR2khlHqaJo1GxUlsA4ti+Ljweq/QsR9yNSvaJk7C8vfjvjUfhSWP0Cv4Eb8cZ0QFY9uppDd+WyCR1bV4OOQEV/RsfNfaJ99Eq3bzEUpD7qeg1IWGRmT6d//FUpLP8UtUG5ZbZ15ZjU+vopSFuXDf2yQwBp82kdookjZDdd82A00/o3IBjSrPb3OmIdp6LwsdldBJWmIrHTtbyd2RtYliHhYLraExVzR8EgcIo+jGx5Cc/oTm5LqaCc+5Fr/C0QUsz7fyGE/bWXw0/+kzbQpaObuLxHim3anZO47EfgYOhoCga7O/qu3eb2TgfVelMCKWtSiFrVGWJTA2g+2Y8cOKipGYpoxBALd0HXPAcnWefXVV4mNTcbv74nfPxjT9HLPPfewadMm8vKqSatO2F1gTsIuqclCxETTsjnyyCkkJWUgssR5yM7ELgu5E5HViKTi9cZy8cUX4/EkInIDIhvweErp1WtgxFhGjx6Prh9NrcbCffj98fz0008ArF27luTkai0WHbvzjYlduvgGpviY5ExIckWIF0FE0Vw0xomQounEemMJBFKIiWlKaWlFBGGXkZHlBHg30lS8fOLMHB4RwaPrfPLJJ/WewzfffJMWLbLQtBi83hxM08stt9yy/360RtiuXbtYuHAZlhVARCgqKtmtU+TvaVECax/6ny3Q+q1B2V4QWBE+Gypn7MAbaIdSkxyy5TqUFkNRxeOEjobCQfchysRuHGFia0VV67g8gVIeBlVsiiynGQXpzcajad2wu21dgtLi6V58x+7dn6pLNM6AilO3kZKcTU/D4i8ilImJIfHYXcBcujRqCenlR+CNiaONeBks4iKwqoOhlx2S/2zixcIjgiFeNOmPyPWIXISV2IQp295mWvgDmvTqjTJHIPJfRP6F5skie97ZhN4IE3rI8Supdfc5Hxuu9dAOxz+nQ4eTUSqAUuPRtCJMM5WSkgcIhV51/CXH33D5Oy6vr0TG3aWLWh/ruDv4bShAq68sxk2Iuq+3fXRPRwmsfeh/RjJqb/GxIYzcA4FVFx9Ds6Fp2yPR9CJsWYj70PS2ZOWfRehoKBn1LrqRhN3AwuPgUHXjio/RtBbk97x1N3zM67ISTUt1SKXVaFo2rdrPaxgfHYxs0/UoUnUP1m4kVntqG/Ksw0rNJKVbISnKxzDRnDnkX1z4uB1bquJuRIQ4ESyxsGQQIq9RLax+7MePMC38AV1PnIfm7YjI04i8gTIrSOoxlJ5XP0h6n1Eo3diNuNLNADn9LqByzPZ68HEHRUV3opQfTatA04ajlI8ePS6rBx9f2nf46MbIPeGjGyP3Mz5GCayoRS1qv8aiBNZ+sGuuuQavN5vacrvnG+zqtz+tb98ylFrsenD/lYSENFq2bItS1fX3W13fn4zICOw26CbPPfccV155pUN0rUHkFWedltgaBitRai5+fyqRWgnfYRg+3nzzzZqxpKe3xS7dqV4mjGnG89JLL9Uss3PnTs4991xMswX2G7I4RAx0SeIIUTVp3j+J3Q6+QoROOTkEvAGU6oXdNWcsIjdjGKNIS2tZc20XFQ1C5DwsCXGWK2UcEXoHAtx00027nb+nnnrK6dbVDVsHxs4683j8NWWRv2QvvPACl112GevXr6eqqmof/KK2XXjhCrze9k7QvRldn0pWVpca0f3f26IE1j70aHC25wBtHxFYPUMPo+nNiWzwcALprcYSPCqMaTVzgp9V2DpXZ7lhA13vS5eCG3YL0CqGbyMr93QCMd1ISBpIQb+7621fHlxQVROchc6AoSd8Q3bwdGI9sWhShsg12Norbrg6GT2QhvL0QOQ87JJrC/tFxNOIPON8dhSWdOYUEdJFsLO4wohsRzOHkTtxFNPCHzAt/AFHfv4C6UOGI0pzAlEdX/M8+vztX7+awAqFPqdv34fIyppFXt7JDBnyrCs4ixJYh4hFCayDyfcxgTX0mG+xXya+78KfBzGt5oSOhvQWY5z54MnYjSsG1cGqE8hoOXk3fAyODNO1YDVxCcXExBaQ020FwXG7GsZHByODy3fR+cjriI1tiq2HWpfIykNkIcqMR7NaInI6IkeiiXLmkvdgVxBMQqQjmkyht3gZrxSi8rAzs8KInE1cq7YsCr/CtPAHTN3+Du1mzUWZfkSUvW9V3/4FUYqMDuMYPP3jX8BHGyMHDfo3OTmL6dBhASUlDzeAj1ECK2pRi1rU6rMogbUX9sUXX/Daa6+xc+fOX1xu2LAx2NpNtQ/zQKAfN9xww+80Utv8/gTqihTbE5JC7LdmTYjsOrMakV6IgN9fysqVKwG44ooriItLdx7eQqS+ywtO0HOz67OdGEYCzz33HB988AHnn38+bdpkYWdwVS/zIqbpZevWrRFjrqw8zBnXciew3IpP4rmgDunUS4RRImS3aoWuN0GkDyL9XMcTxucr4Jpr7O6CGzZswDT9GNKVCS7dg+0iZHi9PPTQQ7udv4KCfthv926oMzHLQEQxdOgIPv/883rP/ezZCzCMAH5/JZaVTu/eJY0Si2+MZWV1wyYUq8fzM4bh57XXXtsn299bixJYe/BowLVvA7TGEFjVk/B6ArXg3Cr6jX2Zjv0uR9Oz6mDguaQ2H0750T86xNApzucLsTvqVS+3DU1vRs/BD9klhxNhyJiv6N73dooGP0Zwwq6az+sSKwWld+ENZCEixCQW0GfCU7XHeAZ0O+xmlJ6I3ZEwFpFzsNu5P4rSE1FGU+wsAudlgXhJEANNTOxMsRh0MRgkFhtFMDQdzRuH7m2H5kklpnVXyh75jNDj4RrvdeqjiB6HyH3Y3bdGEhCNZk0L6DZsDcGjXALLcefOOgAAIABJREFUEYHSdy6vLm9xB2IvuPxZl1d/5l7WXSLjDtB+cty13xHUen0ElluYeE8EVkPXW5TA2pPtW3yMYuS+wcfGEFhuoqIeIqtk4nv0Gr7BuW63uHDvSXQzmdA0MK0MRPo7n9+FXbpcOzdU2kjadTqpBgcrxm+jcOB9FPT/O+XjfmoQH/uPfoX4FLsToMfXii4lqyLwccDc/6I0H7Y2VUN6flmInOrgWS5+ETzitckn8WOKn1bi5XkRkkwPnuQWaJ50NG8bjEAKfW58kpJ736XHmX8na9IpJGYV/cK+BFEaGW0mMGDEm43ARzdG7gkf3Rj5G/HRjZF7wkc3Ru5nfIwSWFGLWtR+jUUJrEbYrl27mDp1JrpuYhgBkpMz2LhxY4PLL1y4BI/niAiCwetN55FHHvkdRw2dO/dCZIUzhi8doqm6LfI32JlVf3UCuG8cYms5Itvxeltw3333RWzv559/xueLp7bLIE6Q1QqRbEQ2YXcQPBlNC/DII48QsCwqvV5CHg+GCIbRF6UW4PEkceqpp+825iOPnOQEjjtc+5hJpghfOx88KXZnrTgRRyT0OOwMhKkRRJPHM57ly5fXbPupp56itLQSj9KYpxS3iFBqWXTt0IFdu3btNhabACx3gtfq7X6N/dbxfkxz9G6lkmBnXhlGwDkfIPIjPl9Hrrrqqn3wq0JOTgEiN7nG9AO67o3IePs9LUpg7cEPkeAsuCxM92G3k95+LC06TafvUS8emACtAQKrYv42svucRSCpO4lNB9Fj2L0RBFb/8a/QNn8pHl9LlBbjdCcNIJKP3VHwL2h6M7oNupngMWGUloTIhc499g72W/yp2BlZvTHMdAaOepvQRCjofzdK86EbXdG0NGLiulF2+JbdArS+o15EaX5EbkTkA0TORjPiKJu7pSZAC50B+YffSlzzPnji2mB40xERlObH3zQLzTjcDhDlPAwx0cVuId9EBEMES9PJMC0GeX2Yuk7HZedT9vSX9Fh5L0WrHyf47122lpWLwMroezTiZOvqcjxp4uVqES4TIVG36FR4WaMIrOLiv9OixeE0azacwsIrD3oCa8icrXQfvpZeYx6hcunO/RKgRQmsPfghRGAVH/kMzTtOJT1rPD1G3UtwWfj3x8cGMDK4KEy3ijXEp/UjNrknuf0uJjh/Vw0+lk7ZTE7xhQQSuiDKg9LiUSoWkUzszPzzUKqYlh1mEpoGcUndnflRdVleHiIDnLnJJET56d7/DkITYcCw/+KxmqPpmeh6FoaZQt+Kf++Gj+VTfsL0pCGyFDvz6w6UFkevIzZE4GPxsc+R3L4Cw5uKqGodv192w/lXE4WhFC01HY+mEdM8k2aV40gq6Eds+zz8GW3QLG+jtpkgQorSyWg9uFH4OGjQv2jbdjrp6RV07nwqlZXP7gEfDyyBVblwO4WHPUjByLspX/jDfsHHKIEVtahF7ddYlMBqhK1cuRKvt50TxOxC5AoCgQR+/PHHepd///33CQQSMc1JiFyJZfWiW7eiRpWRffTRR1x00UWsWLGCDz/88DeNe8OGDXg8fkxzIkoFsTuxuDOJFjlkka1hoFQrRP6CZRWTl1fAzp07+frrrzn33PMYP/5oVq5cyfnnX4jHE49S8xGZiC2k3gqRHGwNBDsDwDA8dGnfnotdO7xWhNSYGI45Zjrr16+vd8zPPPMM9luyj13jvIKA7sESRVuxxdo1UWgR2i+PIhJPbSfFVzHNGJ599tnd9vGf//yHsSNHUpiby5KFC/n666/rHUuvXiVOwBpAZC62ZkMeIsOcfWxFKX03kf5LL70Uj6czdgvpudjaMqcxduyk3/R7Vpt9PbbA7ozzOqZ5OF269IqWEO57ixJYLm/T43g0vSkiyxE1C6X5KRq78fcP0BogsJq2n4Cmd8XOBr0YpcXRvXItoQWQU7wCparf2s/AJtq/dwKwjtgkeIDkjCEEp4cJTYM2eYuwy5KfwxY4n45N+rdAZCQiYzHMJgwa+SG6kYjdqdUO5pRWTqv2c3YL0DLzFqBUJNGuG8V0GnJ1RIAWOgNCl0P5ih/xJeUgek9EJiNaa2wCfQ1+8fCkCFUi3CaCJcJMEdI6dCH/olvIXnQ2yb2GYmfO6igjDlEayd2HMmjdexEEVvMBUxE1D5HtGGLxjGuA94gQb6X8YoBWXv4ZGRkjsF+SzERkGUolkJOz4KAlsHqOfghNj0E3O6HpzfAndKR09mf7PECLElh78EOEwOoxep0t+K3mI3Iymp5Ch77n/f742ABGdhp0FZqeisiViNyEpmfRussCQgugaPRGND2AqNaI9MDuirfTxnpJwC6fboHly6R86g+EpkGvig3OnO9W7BeOf3Pu/ybYwuqzUZqf3mVPkJg62JkLhR1fTiCuK8EjwxH3bUHpXehGByKzYo+nafaR9eJj6HJI7zIOUckOVleTS/uiK2tD7qGnCA+IsFOEz0QwlM6g0ZsaxMdg8Ftyc09ysHs4Imeiae1p0qTkoCWwSo55DyuQiWa0RDc6oJuJ9Jnw5D7HxyiBFbWoRe3XWJTAaoT17l2KyOWuB2oYn68tDzzwQIPrvPTSS/Tu3Z/mzbOZNOmoRp3jxx57DMsK4PMNwecbisfj/81ZW2+88QaLFy9l7NgJaJqFyGbXcUzF50tm1qxZPPjgg8yYMYc+fcpYvvx0vv32W7755htatGiP19sPkVPwevMoLOzHI488QjA4wulQuAaRGGzhyy8ReRuRG4mJsbMGNrkCoS3OBOD7778HbM2r5cvPIC0tkyZNWnHCCSezfft2ysqGoeudnIDwMjyeBFauXEmrVllomg/DiCMhoQm67sVdMmhnUeiYZmt03VNvhtfe2PPPP4/fH49lFaJpbbDLeY52jtXOxlJK47DDxjFixFjWrl1LOBxm0KByRJpid1U8GpEYPJ4enHnmWb9pPNUWDoc566xziI9vgq6bVFaO5tNPP90n2/41FiWwOKQCsfoCoiGzv3Y6y73qwo9zSWg68IAGZdUlMaXTNyPKIJL4Xklsci/yh9yCXTp9p3OdunX/XnDuaxB5GN1MpnLGDkKzITgrTMuOc5xMLcHwpKLpPSIwR9MHkNH+SJSWXCfougdfTB6haUR469x5iDrWtRxoRn869V+5exeo46BL+Q0ovQMibbGJsw6IeNBFY27k2wgGiXC6g7HBy3eR1nkMSh+CnYXbBJH7EXkbpabgS8wheFIVoZMhdDL0Gf0kSotB5GpEhC9d233dCdBqMwk+dPmrBIOvkJjYC7tj4lWuIW1E02KpqHiUUOgJQqGnXF4dnLk1sD6krOw/dO16CQUFf6Wi4lNCoa3U6sZQ66NdXo++WESA5j6nTnBWuXA7ppVObXn4TpQ2iozcyfs8QIsSWBzy+BhaAjFJ+UR2u/sXmh5LxaKfDzg+hhaDN9AOW+y8enyvIspDr5GP4/FmYDfyyUbkXtcyO5353SuIfIlSPvqPfbVG5L1LyQ2OkLug6XGI8mFn89dq9iU1Herg7/+5Pv8KEWHopG8i8LH74LXoRm4dLD2J9Lbj68XHgce8hU1WDcAm2jpRrY+l7yPCygqk0aRVhVO2OA2/ZHC3Cx+rRIhTHvr23VgvPoZCr9Ku3UzsDN6xruP6GqVi6Nv3ul/Axxci8LGi4v8oKLiGrl2voqzsnb3DRzdG7gEfQwshtfVwRE3BFscPI3IB3tis2qzCKIEVtahF7QBalMBqhAWDh6HUya4HzzYsK5knn3yy3uU/++wzmjbNxOfriaZNw7JSmD59zh7307ZtJyJb615O69a5hMNhtmzZwuGHH4nXG0tqaksuvPCivc64GTfuKLze1ogsx+MZi98f/4tlZytWrMDr7eM8wKpLIZuzbt06wuEw3br1xjQLsLOwfnaN+ways7uT16YNV7ge9DeJkJmeXjPuJUuOx+vtgK1T8CBebydmzpzHtm3bOPXU5bRr14UePfpz5513Eg6HOfHEU9B1D4YRh9+fgM8XS23WQxhNm8TAgUNYv349mzdv3qtz05B9+umnXHzxxZx11lnMnTvPGe9TiLyFYQxDqQC6PgeR5VhWOjNmzHaE392B9FwsK5EtW7bskzG57UBlXbktSmBxyAdo/Y96zSnXrXJd1xvx+Fv9rkFiQwFa/6Nec9qdu/X51iAqBqU1cwIzrxPsuEm4exBp7fz/W0SEIVO/qgnQQrOh/NifGHzUJ2T1OA2ljXetCyKTneBMxy4JrP78FJLSh9QEZkMmbaVw6IN0K7nFGedt2O3YL0HTA5RN+bzeAK190UnY5NVk7OxfO5DQlZcjXAMJi9BNhFkixPoSKFn+Lnbm1ZnYOjXuLlw70PRk+hz9dA2BFZoD+UNuwxtoj0+EOWJnF2wTYawyaJE6qEECq0+fv6FUPDYR+HLEc1JE0PV4kpJ60a/fql8ksHr2XI2mBdD1AnS9PR5PC0pKXtwvBFb/o151CDv39fwolj+z9tqLElh7sig+urBJN+pqjm5HRBg886MDjo+hxaAZ8diNX9xyCBZKi0Oks4ONmUSScJ9hZ9V/hAjoRh49yu+JwMfKmTsZfNTH9Aw+hKa3JJJ8ugmbAPNhZ2rV3muankDl1J2EpkHllO0UVTxGz4qHHULsNOyOr/ehtAR6hh6qFx97Hv4QSktBpCsi3znbfgoRjXRRvCfCehGudPAxUwQlQnzLHijdi91htil2Zu5oRI5B5DSU1omWhcdStvDLGnzsO+YF4lJ6o4lQKMK3Du5eJkKMmUhl5ZZ68bGi4nnnZW8fIl+Eg1Id0bQYYmI6UFBw9i8SWIMGPYlltUDT2qHrPdA0P4WFt+83Aksz4rAbOlWP1+7OWDpr8z7FxyiBFbWoRe3XWJTAaoQ9/vjjmGYAm1x6BNMMkpub32BJ4OLFy/B4Kl0P8g/QdYv//ve/De5jx44dDoi7iY/PEBEef/xxYmLSsDthvYDIOiwrg6uvvnqvjmPXrl2sXr2aww6bwKJFS/fYFXHy5GnY3WXCiDyIyHEYRlfOOsvOJPrmm29YuHAJppmAUkdgv2F7FK+3BVdffTXr16/H7/Ew2uPhCI8Hn2ly9913Azbx4vfHI/Iv1/G+iGn6ePbZZyko6IdpesnK6sqDDz7I/fffj2WlIPIfZzz3omkeDMPC7y/G7+9AWlpL3n///b06J3tjO3fuZPHi4/B6Y9E03RG2X+4a/0vouonX26pOkHsrWVn5+21cB9r+1ATWHzAo6z/lNVJahTC9zUhqXkbfic83LIzueOXC7RhWE+wyERCpQmnj7NKOusvv76CsngAtuHAXlr81tuD5LmwyqgV2uUY1qfU3h2TpgMgtiFyP3e20+qXBBfjjcgnODUdO6h2NmOKxzzmkR/Wk/nVnew8jEsJu7nAhdsc/D23zlxKaB91Kb8bUTFoafixlkJrUGdNqjojgj+1I0ZCNtaUdkyK956D12GXe1aXStcSQKYqzRXhKhOliawJ6RGja8jBHZ6snIkXOGN2B0040LZXevZ9wlZ38WOP9+/+TBG868ZqHGGWSEmjN4MEPUtsVy50psJHu3U9F1ztjl2POcT33rsDO/HoGkaXoehxlZQ86JTLVZTF2V63Kyv/i8WQgci3VLyREptCkyfDGl8U01FnL/Vs610vZrC0o5aG25Nz+/ePT+9deh1ECa0/WOALrD4aPQ+Z9RYu8Y/H4WhCT1J380G17xqElkNIqhKjpEde/FcgkuLjqgONjaDE0bTcepY1E5Cfskr+hDkZWd8t+E5usinPw4k5EumCXS4PIkyjloXTqZ/XiY/nsH9GNeGzSKoydZdUJkROws0B9iJxIdVlibHIBoXnQb8x/iPWmkKp7idcsEvwZ+OM7ISIYnjTyilY2iI9DxnyFLfHgJuhBpBN+3cc4Ef4lwsUieEVIEkVSXA4eb0tsofcy7JcPh0esr2nD6JB7br34OHToOzRLKsRSBimahd+IoahoTYP4WFq61rn/l2M3SarO4H8RuwTzLkSuQakARUVX1MHHWoxMSxuGUkdRS7rfiGk2pbJye+Pw0Y2Re8DH0GKc38DdwOhpND2mNqMwSmBFLWpRO4AWJbAaaffffz/5+cWkpWUyefKxfPnllw0uW1w8hMhSCggECrjjjjsaXCccDtOiRRYi17nWW0WTJq0wTa8zsfjW9d1NdOjQPWIbTz/9NNOnz2LGjDk899xzv/mYb7zxRrzeLESOcgKRYxDJIS2tVUQ20ccff0xpaQilNGJjUzjjjLNrMoPeeecdTj/9dE499dSIbK+qqip03UTkNdcxvY9SyiG2TsZueXwFpuln2LDRiCyJOKc+XwnnnHMO1113HXfccQc///zzbz7mxlhVVRU7d+4kMbEZkQTcLpQyMU0fIo9Qne3g8ZQxf/6i32VsB8KiBBZ/mACtbO4WdDMJkQXYDR1OQjNiGTTtgz0GQz1GrrOFys1CNCMTb0xbBh/70UFBYIUWQ/HYZ/F4M9D0FJTyobRERNa77s8q7GzR1ojE4YvNRTfi0PRsdKMLuhFP78P+FTGhD86tonLu9pogLbvX2SjlQdNbOYHPiU7gF4tIMbYgfDoiKWT1OpOyaVswNZMHnEF8LUK27iW36CLKJ/1AcEqkBkzdAC04MYxupGOTbdXH8SyaFqB93on4xMArXnySiiGZGGYqlq8tkVkUw7CJun9gl5DPxettSzC4s94ALRT6nGBwM3363EffvncRDL5NZFv3ugHanShlYgvTN0UkF1tXzIPIBldQ2I+8vEX1ElglJY8553MLIj866zyDYaTuFwIrtARadZ3v/I7nI2oxSvPTa8wjUQKr8XbIEVjBZWHi0/qgtKGIPIbItSgtnh4j7tkjFg2c+jYeX3N0IwvdyEfTYyga89hBg49lx35ObEpPlBZAaYloRqIzz3ITPyXYnZdj8Pha4/E1R2lp6EYxSnnI639FHXwMUzHnfwTnhwktgMLhD6AbCWh6c2fO2g+bIMtBpJtD4GQiEiAhbSDBuWFSErI4QRRVIuwQO+OzZcsKyif9SHBKlZ0x1AA+hiZBUpMSRCa4juF7lJZAXuGVWKLhFS9+ScSUNoiYpDYbjlITqCUar3eIpJsc/LkWpXyUlL7XID6GQp/Tv//jFBWtoaLidQfH6sfHYPAx/P422CWaRQ5GFjl4d55r3CeRllbaIIFlmunYWq/VJZq7EPEwcOBb+4XA6h66w3lhcwIiZ6Pp6WT1OWOf42OUwIpa1KL2ayxKYO0HW7r0eDyeodS+KXkPXbf4v//7v19c795778U0/ZjmeExzAqbpY8SIkRhGBbuX6d1OZmZezbp/+9vfMM0YNG0Wuj4D0wxw++23/6bj2L59O/n5RU4gUq2dVYVlDeLkk0/dbfldu3btVUnbyJFjnUy1LxH5CtMcTU5OPn5/74hJlWEcRX5+D0zTPUkJI5JJXl63XyQT96eNHDkWw5jo+p1vIDm5Gddddz267iEQ6IPX25zs7C589dVXB2SMv4f9KQmsP1BQ5va8wZejGf0i7i9NH0Z2nzMalWVQNutLupavpseIe6lcuL1R61QHbcFlVeSWXII/oRO+uFyy+55d2/ntVwZlddvBV87dQZ8xTzPgyDdJTB+EyNmuY30LEYO23Y+jdMpmQvOgfOZPdC9fS/6QWxg6/dvawGxBmKyepztlQUJSRhmDjtlkn4OZn9MteLMTgHyBLVo+xbWfHxGJoUvpKgqCd9HeCLgjRC4XoUV6cW1QMb7WSys2M6D0DYKjqmrKQbp3X4tSAexs2HPQtKa0b38qweD/yMm5AMNIQUSIi+tFnz4PO/fit3WOW3dKQIX4+EIGDnyYSP0pd8lKZABm+3qXP7Cbd+48zyb2tA6IWJhmAnYTC3dWw3A6dJjjBHlvOb6ZUGgzAwf+CzuTQpzAdyoiFxIb27O2LOZwl//Kspiaa2gZBJdW0bV8FSmth9EsZxLFRz4TSUhHCaw92Z7x8Q+Gkf2O+o8TtP/ounYvICmjrFE4VzH/ZwqG3UW3ijUMmbO18fjoYGTh6PuISyvGCrShRecZtd1J3RjZmG01gI/B+WH6T3iF4jHP0b7HqWh6uYvI2YZS6aS1GUX/8a/UEPi9RjxK18GrGHT0BxH3VPfKtViBNogI/vg8ig7fSGgJlM//iaIjNmJ6m2LLQ9yMnfW6yzV3KyatzTDKjv0CEeE7F1C8LIJHsyKJFwcfh4a+of/gV6gY8XMNLgwc+DaaFofIJEQuRdO6kZQ0iGDwf/TsuQ6fLwsRwettS48et+D1ZmPrAbph2YdScc5ymRQWXusQR43Fx42/iI/FxRdjGIko1RKlEtD1GJTKILLc8iKSk/vWwUcbIysrN2GaGQ42CjbReD9K+Rg69LvG4aMbI/eEjw5GFh2xkfSscaRmjiR/2G0Ejw/vc3yMElhRi1rUfo39YQms999/n3Xr1v3mTn37w7744gsyMtri8+VjGEfh8SQye/aCRq37xhtvcNJJJ3HiiSfy+uuvM336LOzuLZ2xu2d9hchrGEYWp59+BuvWreOqq64iMTGdSIHO1WRktPvNx7Jq1Sq8XjehZL9lV8pDnz6DmDhxMmPHTuKuu+4iHA7z3Xffcc455zJkyEiWLTuBf/7zn5x44kksXbqMF198MWLbX331FQMGlGNrtSjy8npQWlqKaeZEkHWaNoPx44/EsmKw32I9gsiRiGSg65V06VLAiSeeyKxZszj//PN5++236z2WxnSB3Bv74IMPaNYsE5+vDYFAdzwePw899BBgZ6WtWrWKBx98kJ07d+7T/R5sFiWw/jjeod85aPpIIibvagptCpbuMSiqXLiDvJLLScoYStOsIyme8NxeBWdZfc5A0zOxtVDWoukdaJ2/aDcCq3LRTioWbPtVBFaNz4OikRvtUjo1xyZ+9Ba06jQ/cvLegHcqucrRc/kHIptQajKBxM4EF4drJveprYej6cXYb9MviTinSutCfvmtFB/xDDGahx9cX85QOpntJ0QEZxVjfia9+RGIGCjlw+trT79+L9UEaUVFj5GePo7U1OHk568hGNxBKLSNUGgbpaUf0L37TfTr9wTB4FZMMw2Rv7vGcxV+fw6Vle9RXv7fmjf6+5LACoUeoKzsNgoKTqFv35UUF1/hEGbrsQn+u1HKS07OAgKBXDyeZrRoMZYhQ94gFNpMQkJv7DKezxzCrQsiFj17PrDfCKwad98jUQJrb+yQI7B6j3sCTU8jUhvtRmJTihqFcz1GriO19UhSWg2je2htLV40wnsdscEhz/6CyMMorZzY1MJa0Wzneg0urqJi/s+/isBy42Pp1M8wrXSUNgKRi9H0QuJSelI5Z+ce8bHfhP84ZcqrEfnUWT9A6YxPa+6vnP4XouktsIXLh9chjObTMm8GFXN+xqNbPOf68jYRkgIZEQRWcFyYrLwzUcqLUrHoeiLdut3sIrHeomXLmSQnV5KTcz4VFd/X4GN5+VYKCtbQq9c6gsGtNGkSxO7AXb3LV+3SyNIXKS9/w8k4rYuRv43ACoUeoKLiXgoLz6BXr3MZMuRedD0eu+R8ByKvoGktaN/+GBITizDNNFJTBzNgwP2EQptp124+SuVhVyV8jp1xFku7dqc2Hh9/BYH1e+BjlMCKWtSiVtdOF5HNIvKDiPxDRDrWs8wfjsAKh8PMmbPQyXDpiKaZHH/8yQd6WLvZ999/z7XXXsvJJ5/Mxo0bf7XY9oYNG/B4ErA1CTo6QK8zatQRZGV1xudrhd9fgp0NcI7rofwhIsKuXbt+03G88sorGIYfW5vrXuxOL7did6UZjy2CeTyWlc6CBUvo2LE7Xm8vRC7CNMsR8WIYIzGMozBNP2vWrNltH5999hkTJ07GMGKwSxUFO+PsYkTWYZoxPP300zz77LNoWiy2bsMERN7B1jBIRGQMImko1RRdt1i9enXN9p999lny8goREZo3z+LOO+/8TefEbdu2bePee+9lzZo1h3SW1S9ZlMD64/iAqW+iNC/2m/EwIhtRWgzF45/ZY4DVLHsimt4BkcsQtchukT72X40msAxPCu6SMpEXULqfyiXbbeJq8Q5ad1uIpvsR0UhtPZyymZ//agIrNA/6jn2B5h2m0qTVKLqWriY4t6pRBFZsci8i9T/+h9Ji6TfxpZrJffmCH8jsvgjdk4ytp1Jd2vEPOyA6ZjPB+WGapveiu25xowjzRMPSPPQ77OUIAqtd7kloWg/sTNftiJyCZbUhGNzlBCjVpSw7Xb6Nzp1XopSFrndEqRhSUyvo1OkSlIpBZDpKHY1SfgoLb6RWWHj/EFi1328gFNpAp04LnCBNxzCSaN16nCP2fj0iG1CqlISEIkpLX8J+ieHuDvkohpFGKFSbiRYlsA46O+QIrMrF2zG9zbCbH2xH5F00PYec/iv2iHGdSq9B0xOddc9F01PJ6X9Rowms1MwRRGpq/ozSEyme+GwNgdWp7Fons0mISe5O3wkN6Bc2Eh8HT/6YNl2XktJiGB16n0f5jO8bhY9t8peg1NERpJRmlJBXclnN/RVcGqbjoMvwxrTF1vF7w1n2EzS9KQXBu+2y7O7Hk6Z7uUyE80SI1Tx06X99BIHVc8B6NC0JWwswjMg9KGUxaNCmOvjoxshtFBc/gWGkommZaFo6Pl8WhYV3oGlxKDUakfloWgrt2s2tBx/3LYEViaEb6N37EiyrBXZ2rEWLFqMd0v9k7PL+ORhGEkOGvI5lZTrP7Orz/R0iBiUl70YJrKhFLWqHlC0VkQ9FJFdELBE5R0Q+ERF/neX+cATWww8/jGUlI/KuA+RvYpqxPP300wd6aPXaN998w6JFS8nKyqe0dFiDnQsbsp07d5KXV+AQVGmIGBxzzDEsWXIcljXIeXuD88AzscvxQORMOnbssdfj/eijj1i1ahXr16+vIb8mT57uCKi3IbIkZ6dDOP0TkddRSscwmjsTv+pU8b7U1vmvJSnBMam6AAAgAElEQVSp2W6k2iuvvIKue7F1ZM7FLsu5GxGLQCCB6667vmbZ+Pgm2NoUOIRaU1fg+IMzxiUEAon8/PPPfPXVV46m1hmIbEJkFabp59///vden5uo1W9/GgLrDxqURfgy6FJ+E7qZiCgLTY+l48DL9xhcDZq2CVHuUmIQOZWUlqFGBWfBxWFHJ8mtefcxIkL5gh8ZNO0D4pr0cIig5xF5F6WNJrHZoN9EYEX4nAZ8jwTWp4jcgig/fSe9tNukvmLpNlJaB1FaLLrZGaU8dBp8bc0Yy2f8QHbhqTRL7UarzNH0Hf0ioRkQmuj44eDzd8QW860+NztQKpZ+/Z5n6NAttG49E58vm4SEohoyqrT0KUeIfKOzzlY0rSMdOy6muHgVrVsfTmbmOPr3/2udQGuD4+7gap3L/74Hdy/r3kb1dmsDvIqKZygpuZfKyudISKibqfYdSvnp3ft+RDTnPFd/tw7LyrQD0vq6ae2Nrkt9AVpD98c+CspCJ1LT4XH+pVF8/MP4Miie+BzemHY23imT5rnTqFy0c48Y5/E1d+Yt1dfwI+hmMsFFuxqFkQnpA4nUTg2jGa3pefh6yhf8SPOOR2GX2d6Dnam4HN1Monze97+awPq1+BhJYP2IyDqU1oWOAy+pl/Ro1/s0lPKgm11RykvzjscQXFRlN+CYG6bLoBvISO9N82YDKRjy90h8nAgtMqcjsjCSMNNKycv7C8HgNnJzzyEQ6Ewg0Jnc3NMIBjcRDL6Nz9cOm1AMI7ITpcaTljaYQYPW0b79VFq2HElh4QqCwcfqwccN+wkfazEyGHyBkpJ1DB36BO3bz0KpURHHqOu96NTpYkeLdq3ruy2I6Awe/HHj8fHYBn7Thgis3wkfhy49ZPExalGL2q+w90VkjutvXUS+EJEJdZb7wxFYS5YsQdOmR4C8xzOB5cuXH+ihAfD2228zbNgYmjRpzcCBFWRldcLjGYjI7Sh1Mqbp5/nnn2/09q655hq83vauyf2DGIZFx449EflrxHkQaYFl5eD398Tvj+eZZ57Zq7FHajc1Izc3n61btxIOh7nuuuvwepPrBCBV2NlQjzhBlIZIRZ0xLUWk+vf6HhFhy5YtbN26lSlTppOc3JwmTTLR9aaIFNRZdx6TJk2JGOPSpSfg9XZE5HFsnZS6be1nI7IQwwjw2muvcd111+H3F0UsYxjHMnv2vEadk127dnHrrbcyadJUTjttOZs3b96rc/pnsCiB9Qdy561qxaL/MWDym5TP+7FRwVWfcU+i6elEanbciT+hS6MzDNLaHu50wfoGkR9Q2kSSMkopm/MlpjcdO5PSrU3yNSIag6d/sltwVrlgO33GPc3Ao9/eLwFabQnhfGwNwBxEfKS0ClKxaNtuAVrw+DB9J79IwYi7KZv9eSTJ5t72DJe7CKy4+N5ECq9vQcRDSclbJCYORNMGYBP2F6FUDD17riY//xJ0Pb8O/l1McnK/PWQK/H4Ellv8PSamM7VdLEFkF5qWTHHxw6SmVqJpgxB5DpFH0LT2ZGefFSWwDm47ZPExuLSKgVP+j7JZWxpJ0FdhZxG+47q+P0dEKJ/3Q6O20bHkUjQ9G5H3sPWiLrUJqgU/ktB0AHZziOMiCC7dyCM/uHuXxOCiMP0m/oe+418kuKBqn+NjbQnhiQ5ut0YkCW9MOwbN+HA3fAydAINmbqJgxF0MmPqmfZ4bi48ToU3WMpQaH3nsehe6dr2Rdu1OQtMyHWz5G5rWmnbt5jN48BPOffc/13r/Rtfj6smmqg8f9z+B5cbHzMyjEDm2DkkXJDf3dHJyznCO8SFE/o1SQ0lOLt87fIwSWFGLWtQOcosTkbCI9Kzz+cMisqKeZf9QBNbFF1+M19vXFUiF8fnyue666w700Pj2229JTExH16dhZwmdgJ0V9WbNA0nXFzJmzMRGb3Po0JGInB/xUAsEetC79wAMw03kbUbXLc4880yuv/56tmzZwgUXXEirVjk0b57Faaedzo4dOxrczxNPPIGmGdhCwT8hsh3LKmHp0uP5/PPPiYlJQqkSRJoh8ix2CvOJzt/bsDvXzEMkxjWJ+wqR5tgt60HkBtLTM6mqqqJHj34YxmDnPK3CTjHvHHGcSs1m8uRjI8a5Y8cOliw5ntjYFDweH7re3BkvzjhyEDkRj8fPd999xzXXXIPfXxyxXV2fyYwZsxt1/o84YhJeb0vsMslK4uNT2bRpU6N/vz+DRQmsg9z3RiC9AS+f/xO6WV0+bJe3aHoJmfmLGr2NsplfkJDeH1EmojzEphQy+NiPyOl3Pppegp09uc51r36FiEbpjM0RWQVFh/8D00pzug1apLYcRvnsn/YuKNtDoBacGyaz6xLszNfqTqPfoBl5dBx0acOT+urrw33O3YFjfQHaKMjvcavTNfFaRB5A0/qSkjKU/v2fdgTcv3Odl7NITu5P795XO2U1bsHpo0hI6MiQIbfVCarudPntjt/cgN/u8up13NtqfFDmFiPu0OF4NK0jIu87WH0qHk8LKit/ZujQLWRkTEbTYjGMNNpnLyc4fFdkRy13UDbN5QdhWUyUwPqD+W/Ex9ASSGxW4ujtVTnz0+OJTSls9PqVi3bSPHcaokyUFsDja07REf+gz7inHGwYj8iyOgRWLt2Dt0fg4+BpHxGT2A2lxaK0OPzxHSmZ/F7DJYG/EiO7l69FVKwzP3UynLQjSWt3+J7x0Y2Re8LHiTCw9P/QtBjs8rrHEJmMx9OMoUM/dsqU/+k6L/9E1+MZOvQxlPJilx1Wf7cKw2hCScl1Dn79Ej42hJH14aMbI/eEj26MrMXH3r3vRqlY51iqyyS9DBz4BsHgNrKzz8I0m6JpMTTLOIohFVv3Dh/dGLknfHRj5H7GxyiBFbWoRa3amotNYGXX+fw2Ebm2zmd/OALrq6++Ijm5GaZ5OCKr8HiG0bRpJt9///2BHhrXX389fn8BkVkKw4hsVXwZxcVDGr3NqVNnYBjTXOtvw7LSuOGGG/D7E/B4jkDkNLze1owbd3TNeqeeejpebxtsYfe/4/V2ZNas+fXu44ILVjglfEMQyUOkLXbG19/o3Lk3K1ascEjD5x2Cy4+dleBDqXgsqyP228d3sTOuLOyW8l40zY/XOwCvtxzT9LFu3TpWrVqFTey5O2Vd4GzzFOxSvzUYRoCnnnqqZpybN29mwYLFFBcP4fjjT+TTTz+lZ8/+WFY77EyJ9ohkYJpxnHfeBYAtqG9ZAew3lx8hshbTDDQqO+3111/HMHzY6fr2OE1zLDNmzGn07/dnsCiBdZD7PiCwQkugx4h70HQ/upGLpicTl9pr7zttLYGSY95j4NS3awSOW3ebh92o4gzsblVPIvIGoioju38thor52zCtNEQudQLFLWh6Ie0KT9mnwVloHnQbcjO62TOC/BY5j/j0Pgw85q19SmCFRkG3HjcTE9MDy2pLZuZCyss3U1T0AJrWtM4z5SZiY7sRDD5DQkJ3NK0AkWsQOcbB5C5YVjPKym46qAisyspNZGSMxW5Z78HrbUffvs8SCu1w3KVjU19L+CiBdbDZoYGP+4jAGjjlLSx/KzSjBZrRGtPblH6TXt7r7ZTN/Jz+R71aU7bYPXQHutnNIW5inTndB4gch+FJrc3wcgislJYhlDoSuxHONkRNIyF94D4nsAZN/tC5rre7sOkZND2OvpOeJ7isap8RWKFRUDzgGZKShuDxtCY9fSwlJf+hsnKLa+5ZPYZ3EVFUVj5J27aT0bRmiFyEyGmIBFCqEE3z06fPhQcVgRUKfUJu7nKHqLPQ9SS6dbt63+FjlMCKWtSidpDbXmdgzZ49m4ULF7Jw4ULWr19/oOPhPdqHH37IjBlzyM/vx9y5C/n0008P9JAAuOiii/D5KusEPDMQGeoEIJ/i9eZw2WWXNXqbr732GpYVg6YtQuRmLKuEjh0LqKqq4v3332fRoqUcdtgEVq9eHaEtFRubQq1WFIi8hGn62LZtW80yW7ZsYdasuU5A8Ty1ZYHDEZmLps3hsMMm0LNnH2eZJETiEMnAbpH+JCKXo+s+h7S61NnGm4gci677+eSTT7j00ktZsWIFmzZtYufOnY6OVRy2hlb1+G4hObkFycktEBHS0lqzZs0a7rvvPk466SSuvPJKUlOb4/EMQ2QlllVKq1bZbN26lb/+9a8cffTRVFYGmTFjFo8//njNMa5YcTGm6XcIMw8xMUncdNNNPPjgg1x++eW88sorDZ77O++8k0CgW53f8xp69Rq8dxfGIWjr16+vwYzZs2cfqhOQfRqgVS7ZSY+R95A74EKKxz/T+A5VBxGZNWTOVgqG/50+457cqw5bv0iMjVzndP561yGaYxHRSGpeStmsLQyd8w0dB15Cqy6zySpajtJSiOwSdiuBhPz6g7LZLp+5B68TqPUe/QSalkxthtOjiAQQlYJSXmJTexKbUog3pj2t8xcwdMF3hI6DgdP+j9TWIzA8TYhvUkxh6H6yCpcTl9ybJq0Oo3jkM5EB2ohwrYeqCIWqKCl5h8zM2aSmVjjCvudhlxVtRtM60eH/2Tvv8Liqo43POXe7epcty7Jk2ZbVXSRZ7pIsyZJ23W3cC+7YYLApoYViIIQQugMp9JACyUcSaiAJEBIgAULvvZPQggs2xt7f98c5knZlCRtjEoJ3nuc89q72nlt273vPvDPzTtFaQqF7aGm5ndzcoMXTeYg8iUgYperIzBxKRsYIUlPLSE8fSv/+k5gw4aJunbK2tmtobLyEtrZrujho3TllkeU2D0SMx+yIFEF+J2J8TCj0MU1NL1NX9yTB4I6enbJDIsZCO7oTI+7JKYss4dzbvXQgnbIYgbXf+Bg8Nszo+fdTPP57VE35zT7pTn3d8LHtqE+pmX471dNu/fxOql+Q0FLaa/HnKoxsg+CLL2TswkdoO2onQ9quI69iDcXjz8dIOTwbgY9vIiK0rN7aPWm1r/gYiZFHGG0/pf2IPGz384o9tjiUTsYX35+U3nV4A/lkFc6ibvnzhI6DiUd+TN+KNbh9vfEnFlM6/lLKGy4nObuelKxGhk74+Z4EVhd8nDjxQ4qKvk1GxmQrhD7J4vRWlJpLWtoYQqF7CAbvpqxsA6YyYDymKyqInEp8fH969RpLamoFaWnl5OZOYMyYM7rFx2DwpzQ1/YDW1it7wMdIjNwbPkZi5J742NLyFuPHP247KUYQV18WHyMx8muEjzECK2Yxi1mkdaeB9S/5BmhgfZ3t+eefx+XyYXRcwoj8DZcrEa83Dp+vN47jYcaMeZ9bytedPfzww0yefAjFxdVs2HAsH3744ed+PhwO43J5EHk8YhFjBJO3bNkCwPbt28nPH4zbPRSjXxBJ0vwMkT74fAmcf/75eDyZHY6RiWKlW2eqvdTvaEtguTHZW6MQ8ZKYmL7HsT399NNo7bX7PBGjT/AyIgM544wzAdi9ezfhcJipU2fj9Wbjch2K2z0ApVIxOlpGP8XvL+Wqq67q8Trcc889eDyJiPzZHvuNOI6X0tJh+Hy9CQRacLn8HHPM8d1u/9prr+E4bkzHRRDZidc7nhNPPHlfv7qDwmIZWHsfLeu3kZg5Eu30RTtTUTqBvIrD/+cctK9iBDeE6Vt2GCJutNMfEYf+1ScbwmzN+/ji+6NdtYisRzt5iPgxGlGdWVGpvZsOOIEVPDxMctY4tFOF0f6Lw2Q6hTHljaWItCFyM8oZR2qfJlqO2mK6hKlViNxPe2ap0mXW+fwWSgcYPfWBHgmsurqncZxkRIbac3UsvvoRcZOd3UJr6wOEQvcQCt1DRcWxOM7YLhg+zDqT30Fkvt12HC5XMg0NF0Q5Z0OGHIbbnYaI4HanM3Touq+UwDJjL1kFMQLrf8EOKIGVV7kWpRPRzjS005fEzJG0rNt20ONj6GioaL7SNt3oh4iftL5ttB65g+CGMBn9JqGdfIuPIzAZ8pGC339BuxJpW/vZASWwQkdA/2Enop0+FucGIrIQUx78KSKLESlE5A+IWobbl83EI/9Nel4b2qnD6Kb+HKXSUSoF02n7PLTOoGTUxT0SWK2tW4mLK0epErsWdUVgpI+EhFImTLitAx/r6q7FZPdHZrEeba/T8ZiqgThE6lDKR3X1MVH4OGbMGcTF5SMiaO2nsHA6weAvvjICKxofYwRWzGIWs4PLjhaRV0WkRET8IvIdEXlDvgFdCL/uduWVVxEIJONyJeBy+Vi1ag1btmzhnnvu4aWXXvqPHcfUqbNtttKHiHyMyzWPMWOaAPj0009Zs2YNLlcqpmzHRWQKtlKLGDCgjGeffZa6umZM2WCncLMhqSKdpbPsYqAB0ykmA5G+aO3n8MPXc95555OR0Re320djYwit3ZhuPUWW9HJIScnh008/7Tj+P//5z7jdyRhNmKMQucw6jBd07NfjmcPpp5/e4zU4/PB1aL066ljd7mZcrhxMej2IPIdSHvr2LWLmzPk8++yzUXOcfvqZuFw+/P42/P4CBg4s3yuBeLBZjMDa+yhpuBDtGkKnoOyrKB1gzIKH/ycdtNZ1n1BafxFZBTPpX3X8nkLrX4jA2k1exeFW+yUF7UpiWOgGQkfDwJGnW2enPePqQ0QSULoYkV8g8l2Ujqdmym1fisBqW/kZdfOeY+Lyf0c5aC2rt1I08izi04YjKqOLE3QtItW062Mp5WPQ6I1op7jL5xYgEolDx5Dd75AeCazc3GWYZhgJmGYVYUyHQg8jR15OZ/mJcdDGjbvCar28Yud/wuLqOxH7XIvIfJSaQX5+a4dzNm7c2XbbG6zj+UuU8jF+/PdjBFaMwNqbHTB8HLPoYZSOQ+Q1+3vdjnZVUlJ/4f8kPgY3hBk+6df0GjCX3LJVjF3wjy9JYF2BduJROg1RHvpXn0hwQ5jaWXehnTQ6OzHvRqmRiEq0a6fL0U4/CqtO7h4f95HACq4K0zDvZRqXvBOFj8HDw1Q2X0Nan1b7G38pAnNete/twOh1DadozJl2vRkZgLgSo13a/vq3uL05PRJYlZVXotQgTNbpJkwm/6MolcngwccRDD4chY+trXficiXT2SFyt932poh9/gITVL2IhISBHfjY2nqVJfdPxnS5/jta96aiYlWMwIoRWDGLWcy+IjtVRN4Rka0icrcYMqurxQisr8D+7//+z2Zd9cPtTmLYsNF89NFHB2z+l19+mdNOO43jjjuOBx98sNvPvPfee4wc2YDWLrR2M2TISN5880127NhBVdUYXK5+mC5+iYgMsqTTOkQacLkCPPHEE5x88mloHcCUprQ/6D/ERLMu6Vg4iGQiMiLiM6/bRUoBjpOG46RhOmjdguOMIykpG683D6NLsBKXK8DNN98cdfznn38+Wucgkm+drzKMIPxk+zoBEQ9Tpsxk+/bt3V6DE088CY9nZsRxYUWEB2L0vk6wC6kaRKbgOMtJSEjjnXfeiZrn8ccf54ILLuDXv/51FMkWM2MxAmvvI3vgXEw774hmAq4myiZc2r3T0p0WxYEe++isBTeEGTHzTvpXHUtJ/YU0HfYeKb3q0K5yRL6Ddibj9mV3iq1/wVHZco3t+PeCJWt+hdI+mlb/k+zC2YicGX0PuyaQ0a+FuOQhpPRuNORV185aX4DAqgn+HrcvB1EelPbRv/IEgmvCHXOYNu8/wUT4P4w4ltMQCdKeESo6HlEeRKqijldkvcXa9tc/Jil9XIdzFpwaprr2JvoVHE5R0VkkJo7GBANWRc2jVDPFxesjnKC/dIy8vKkolYDW01Eqy2Jl5DFcg8hIRM4nPb2GUOgXhEI3MHDgDJSa1WU/0xg0aL51xu604y8Ro3uNq1DoNRob/87Ikb9j4sQXCYX+RSi0NWLsjhjWKWvvoDWdTi2Xrnou7U5ZpD5OpAPerp/zddB1iRFY+4WPZU0/wHE3d/nNnk72gLk9Y8fXBB9DR8P4xU8yYMTJDBp1OvXLXqSw+iRbFv1tRB2G0gFGzPzDfuFj/dIXUMqLyO9pJ6i1k0711JspbbgEx9XS5bqdRlLmSBLTR5KQVkNZ3SaC63bvN4FVP+8l4lOG0Z7plNl3Ki0rNkdlY42d+zhKJyDyh4jjuAvTodAEH5Qej+NOtevHyM6Av8Hol7a/fgYRh+D8cAdGjql7mILCo+nf/zjy8lYhMhaRki7n/R0yMpq7xcehQ49HKS9aT0TrofZ+fDdi25fte3+zXQp/QSj0C0aMOMlqaEUGJC4kJaWqCz7euU/42NLyNKNG/YoJEx7dN3yMxMgvi4+RGLkva43/ED7GCKyYxSxm+2MxAusA2/bt20lMTEfkCvuw24rXW8eRR244IPP/5S9/weuNw+udiuMswuUK8KMf9dyB8bXXXovK/Lrmmmvw+wdgMpD+YYmgbZho1GHWIUth2rQ5uFxeTOQ/DlPudxtKTSctrRd+fyombduHiVxd3mUxUYzIEkwmwMnWgfNgsrcc2tqCjBvXwuTJh3DPPffscdynnXaaXfy0d9/aaedUiAzBlOfch883nGXLDuv23F988UU8nniziJR7UWqpPd5WRC5FpBFDZiVinNM/4fM1cfbZZ3/5L+ogshiBtfdhMnMaIhbC/0Y7adTOuutrT2D1G7LeRPnVcrRrFC5vlskE6NCGCqOdEIU1J+6Xg5bVfyYiZ0Thh+OuZkjrtRSP/z7aGU6nUPDrKBVg7Lx/7NEavm7Bc1Q2XsOYQ/7eSUDthcBqXvIB2olD5MeYsuhH0U4vhjb/osMByC1ehXbSMWT6EEyJ9UaLGb/EEPnftq8vthhzjZ3vrxY/T7DH/wHaGUrR8LM6nLO8fmvROhORI9C6Ea2TEOmFSDSxpHUN5eUnd+ugBYN3MGrUBQwevJSKisNtVlW7M7kDo/9yNFoPZfDgeR0EVlHRHLRu7bKfJgYPXvKFCKxg8Bny81ci4kbr3igVoKzs+zECK0Zg7dOondOeSdTe2CWMduoZNGrj157AGha6HqX9KD0b5UxD6YDptCqPRNxX3yUpe9x+4WNJ/YVoV1dybz25pSsZPe9vljh6s+Ne164hlI6/aA98bFr+HkObf0bN5NtpO+yzfSKwgqvCJKRWI2qlxft30HoseSVrO7avbLzaamGVYwKhl2FKrTMwmadhRG7FZOmvsuu4dXbd+SomOFlj8XInSi0hrXdrBz4OHf0zlAqg1GKUmo9SfkxJdA6RUhYiG+jVa1q3+BgK3Ul9/dUUF6+kvPww4uL6Y+QwwnYci2k8tIr09KoOAmvkyNOsDuLOiP2cSXp67RcmsIYOvQit49E6GxE3ubmLCQY3xwisGIEVs5jFbD8sRmAdYLv//vvxeruWmvyagoKy/Zpv27ZtHHXU0WRnF1BYWEFe3mBM2V/73LcQH58WJc7+ebZhwwaUOsxu+zcMSRT5cL4ckWFo7cLtTsSUo8y3RE9vfL4U3njjDY4++hhcrskYgukYTEZT+2LiUQxx9SYiUxGpRKQvRocLDFmmGTBgMEOHjmbTpk1RAvQAU6ZMoTO7oX0ci4kCPhrx3oN4PH527969x7ledNElNgMtHRE/gUASHs/IiO9mF0ajoRyTTdGK1is56qj1+/VdHawWI7D2PpoOfw9vfAHaNQaR49BOf9LzggSPCUcvIL9qp2xvzlrX6P+yl2xWUXuJcRhRUxCV1+XePIPswtl7dza7jqMht3QlSkVmG32GdvWletqttByxhYT0KrSrAO3MQukk+pau7lyI24V54fCTEOXBcY9E6QSy+s2gbfVn0Q5Z5AJ/BYxovZNAYjkiSdbR+hftmR9ZeTMJrYZxsx6zIupvWAfuJEQy8cUPJCFjOCIOSsfh9vVCqXSLLb/FEFCm217vgQvQTgLalY9SAdJzQrQu2U5oAYxte9xi5Ssd11epubhcmfb90xC5D5EjcLnSaG7+O6HQ83ZEOkrRzlp5+QaUcqPUEIvxaSiVTlJSGS0tv7bO1200NFyF1n5MltsTiGxE6zgmTPg/O9eDdjwZMV6OGKb8parqSrTOolM8+o8o5aW+/vloZ6x9zMSMuREj0imL7KJ1IJ2y9vFVOWUxAmu/8DF4bNhoI7kKLT6OxhdfQNPa93rGjv8GPnbByOCG3Xj8uYhcF4Ff7Xp5kY0m7sbt6/P5ZFUP+Dik9adoV2nUmlI5syisPp7ghjB9SlagdDLamYV28knMqKFl7dYofKwK/Qal/TiuoWgnh0BiCU1L3o0mrrrgY92s58joMwlDPAXp1AK9C7e3F6HV0LpiBy53usW8MCI/QaQA7WSR2qcOES9KJ6KcREzw8QVMhlUFJgCqSM9twxPIQztZaJ2OP2EwDbNfIbQA2ubtwnFlYEr82q/lpZbw92NIftNMSKk4Ro78zT7h45gxl+ByJaP1QLs29aN1Hh5PBnV1P6K9HDAYvBm/vx9KzcUEfK9DqSSqqs7ugo8Pfi4+NjY+arPofmev0ytonUdl5VWfj4+RGPll8TESI/flPvoP4WOMwIpZzGK2PxYjsA6wvfrqqziOB5G3opy7ceMm7td8kybNwusdgcgtmKi+1z6wj8OkXQ9DRHjllVe63f65556jrW066el9GTu2mVNOOcVmYG3DRAhT7TxnWUcpH5ELcBwfbrfPLhIWYDKovGjt45RTTufRRx+13f0uwxBhvRDJQ6TFbtNe9rPILuZOsa//jkgyJuo2BBE/Hk/OHllUM2fOtJ9732633R6nYLoctl/bx3C5PHsQYK+//rr9Hu6jPePFlDKuIdrxnonIqZjW1MV4PMn88Y9/3K/v6mC1GIG1b6P5iA8YPO4ccsuWU9l6NW0bdn49nLPPIbCqpvwWx13W5Z65ApO52X4fbkY7JZQ1bNovAmvswkdN1oKcjMhNKD2ZQFJxRxeytqM+ZVjoBopGf4eRh9xL8MhwFIE1du4/7PbP2ON5H+0UUDnhmh4JrFGT/mK3ORuTHdCKEU3fjah15AxYQmg1VNRdhXYqEPk5nXxRLi8AACAASURBVPo8rYi4UToJ7SQysHYjtdP/ZB2yt+nMGF1DQsYI27FrMyOm3MH46U92OB7BebsIxA+2mBt5fa8iMXE0xcVnEwiU4HJlkJ7exPjxd0c4Z8ZBmzDhNjIzG9A6gM/Xl/Ly4zoyAiZMuJbKyg1UVBxFWdlh1NRsJBi8iU6tltsIBm+lrGwtgUA/lPKTmFjOqFGXRjh7+0Zg5ebOR2RD1Hk4TjOlpRfGCKwYgbVPo+3onVS2XU1u2XIGj/sezYd/0DNufE0IrOY1H9jv9uOI3/7zmE6AV9vXu1FqPtkD5uwXgdVyxFa8gTyUnmPXgUejnQTql71oSbQwIw+5h6LRZzEs9CvajtwZhY+ta7fjuNMwmaMmQKD0ZHKLVvRIYDUv/ACXJxNRyxG5A5EjMUT/m4j8Cl/cgI7yQkNM/RRD8ICRhvCazDDlpteAeTSv/ghDhP2GjkCI/BRRcQTX7qJt7WeMnP5nRk36K8Flu819vwD6DjjcXt/I0u0XEVFUVf2KxMRqHCedhIRhVFdfY/GoEx9bW++nX795OE4yLlcqBQVzaWu7lVDoTlpafsewYcdTXn4kZWVrGDbsWxHkfidGjhjxHZKSSlHKj8/Xj8rKE7vBx88nsCorL8Rxarrg/EaysmbFCKwYgRWzmMVsPyxGYH0FNmPGPHy+YkQuRanjcbsD/OlPf/rC87zzzjso5RBNhlVgxMxrMNGcyxFJ4sc/3rOM8OOPPyYlJRvHWYnI3YicjMcTR3l5NR5PDoYMW44RRs+2RJMgkkt6em969SpE5MKIff8OkRS83v5s3HgmN998M/n5JSilGDx4GI2NjdaJa8IICP8OrX3k5OQhMsPOUUsnmdW+2BmI1i7ef/99wHRRPO+881AqAaOvtRCRfJSKo7Z2HB7PBLuIeQGvt55DDlm4x7n/9Kc/JS4uUpcLRA616eDtmWDPY8oH77TX02HhwiW89dZbX/i7OpgtRmB9g0YX56lh+Sso5aEzsyaM0pNIyqpFKS+OezzaSSO1TxOtR27v2Tnby/5Gzfkrablt+BIGk1u6ksbV7+w5R7vobOSC/EgoGXcB2tU1W/N4+gxaugeBNfHQj+lfeQKOOxvTiar98zsQMQS30gFGT3mA1qU7SM4Yax2vKkwJ9EpMS/YHaS+NUcpLYdWJiOqLKY/ZhMlK9ZJVMDW6jDHC8ahpvB2l2zOt2rMbdiPSTH7+UV1KSoy4b1PTIxQXf5sBA9YxevSviIsrQqk5mKzU69E6hWHDvmsdqgc+dzQ1/Z74+GKUSkbrPrhcqYwadQWh0JM0N/+VysozGDLkPCZOfIxQ6M2I8WHE2E4otJ3+/Y9B60i9wd1oPZih1T/rLIE5JGK0izNHCg+viBiR16xdt+dAOGUxAutA2sGHj5EYaTOwvIF+mA6jneWCvoRBNuOpGu0qxBuXT8PyVz+fwPqcfTWsfJWcwYvxJRSR0W9K980/IoW5I/BxzJyHUDqF6KqAW/DFDdyDwAqu3E3ZmB/giyvEBEcjMXUiIoegnRyKay8gtAL6V5xg13zD7Ppxql1XXmOx7Fm005eBNadhApupmGDpdxFJx+3L6REfm+d8YDG3H0byobOELyGhult8bG19l4qK71NYuJaqqsvo02c2Wg/DdKK+G63L6NdvbgTp1DM+trX9hd6921DKh+MMQCkvpaXHEwo9SWvrPxg+/HzKy8+koeFeS1b1jI/V1TeidS6m3Nxm0aml9O132OfjYyRGfll8/KJltzECK2Yxi9nX2GIE1ldgn376Keeddx7V1XWEQjO5995792ueF154wXbs+yTi4X0GJroXSWpdycCBQ/bY/vLLLycQGBa1cPF4ZnHsscdRXT0GpY6w779gnbSLMWKW38fl8tt9PxSxn0/sg+ZqsrL6dexn9+7dNDS04fMVYjoWViPiJT4+jZ/85HJ++MMf2oXIarv9yxFz/gsRQWsPzzzzDFu3bmXMmEZcrni0TkXEhePkorWbhQuX8dFHHzFp0iyU0mjtMG3anG5/v3/+85/xeiN1esDlms+gQeU4jg+fbwgiDi5XGi5XAr169cXjicPrzcJx3Bx++HrC4fB+fW8Hm8UIrG/Q6CbToH/V8SidhNIL0K5heOP60bjqbcYveYaK5p9Qe8jdBDeEv7hzdtye+/rc0QOBNTx4o20v366TFUY7TQyq3hit57IyTFL6KLQeg8m2uoBoB60v/oQialpuI7QCSkdejHZK6NTledA6a4dFbaddrfQeMAvR5ZiSllJEZiKqkf5Dv9Wjg1ZWexmOq9FiegCR6YgMQutUmpre2cNBGzfufhwnBa3rUWqu1YIJRJw3iHyP1NSR+0Rg5eRMRqkQJrs1jMg5eL19qK29Eq3jcZzhOE4FjpPC2LG3f66D1tDwDFonInIEIjei1Ax8vgJap3wSI7BiBNY3a3TBrOGTb0RpP9qZgnZa0E4ctYfcTdPqf1LZcjXDJ99I65E79o5v+4jHe8XHLgRW0/J3rSbXCxE4cTqpvZr3ILAKyo9DO/mITEJkShd8XILLnUZJ7UUEl4cZO/1Ri0FPRazlUogWZAeR75Dau9kSW4dhJBsaEDmUhPRRPeLj+MlP2vLtWy351YQRb3czatS9e+BjS8ubxMeXo3UxIkut1pSPaC2y+9E6jmDw73vFyIqKk9C6H53dXO9FKQ+jR/8cvz8frQtwnLEo5aGy8tzPxce2ti0EAqUo1YbphngcWscxvvHJGIEVI7BiFrOY7YfFCKyvsYXDYQoLy9D6SEsevYPbPRSl3ER3cbmNrKz8PbY///zz8fujO9RovZZVq9ZQWTmazqjhadZ5ilx01GMyDeIwQsT3IlKHSSO/gJSUXh37ueuuu/B4IgVYX8ftruKkk04G4P333ycQSMaUDCYQHa38NSKJZGXlsWvXLk455TS83mpMSv5uTLmOh7S0HE466dsdXQC3bt3Ktm3berx2r7zyCoMGleFy5SNyHC7XYgKBZF544QUeeOABNm3axCOPPMLtt9/OzTffbAXrb7PH9Bw+Xy9uuOGGA/yNfjMtRmB9g0Y3DlNwQ5iRs+9lYO23KW/8IRMP/3jfCKf/EIHVdvhOEtKq0M4IRM5H6cm4fb2Nxktkt8GWWxGVhCG1j8eUPL9kceYnaCeBiYs/7nAS0nNCmEyBSFzMQdTUiNdhRIqJSy7CaF5VY7KwUhBxk5Jdz/CWGwmtgdEz/kafAcvIzpvNsAm/YtzkJ60uyhOIPIzIt1Eqm9LSi2wpSbSDlpkZQuRwTBnPc5guX+4I3AWRTSQnV+0TgeV2ZyPyp4htdyLixefLQ+TciPe/RXx8OUVF36Ky8gJaWt7cw0ELhbYzbtyjZGXNJBAoJzd3ORMmvBEt0t6dgxYjsP6X7eDDxx4wq27p8xSNPpPBY89hworXvzg+foUEVuhIyCtbi3byEPkOotaidICRU++JIrCaF3+AKB+mQc6dtDe2MRjwAEonMmrSXzru0cE156Cdti74OAtRmURmGomsxePvi6g4TBOfkXbuAHFJpZSMvoC2VTtpWPga+aVHk5k7nZLaC5k4bzNuTzYiV2I6W38fkSFkZc3oFh+Li89E6ypE/mkx9U27fo3UJ3sMpTwEg3/bK0ZmZzcRrTcLjjOGlJThKDWVTs3XW9E6jqKi4yktPZ3Gxme6xcempnfJy1tDIFBORsYURo9+YO/4GCOwYhazmMWsW4sRWF8je+qppzjnnHO44oor2Lx5MwDPPPOMJbE8aO2ipWUq/foNRqljMGUv/8TrHU1jYwt1dW20tk7jtttuA0wXPkPMtAtsPtCh8XTssd/CpH1vw3TQmkn0QmQyRsfqbLsI8GL0ow5DxEtzc2vHcV966aUEAk2YTIB51qmKR+sAZWWVeDymNNHpEPJs70az1s7t6chSM8TalfYYTrULnl8jchM+XxkrVqz93Gu4c+dOZs1agFIuTHmgDxE3ffoM4JFHHmH58jU4jhsRYcCAch5//HEuu+wyAoG6Lud/AnPmLPpqvuhvmMUIrG/o6KLHMjT0cxLSa/DFDyB/6Hpajti8d6dqbwvmA0BghY6Eias/pqj2O6TnTqJgyLFMWPRmh3PWtvIzcotWW4JJI9LH4kK5fS+A0gnUNN/W4SwUVZ1tcWxaBCZsQ+lUlI7DaBDeidH4S8UQ8+2aN2GMZmA2IotQKoV+pWttd7IjEDkF7WQxoPJUBg7ZiFIeHGckSieRnhmibcqnhKbRRRdlJx5PHiJj7DF7MTqCPkQWYzRiLkSpJPLy5tLW9hzRell7joSESkR+EHF+z9lzFoxWYXup9QuIKJSajtal+HwDaGp6mz26ZU3BjO70W+ay985Z3TllkY5Z5Pce6azvjST9bzhnEWPd+TF8/EaOLvg4esHfSOvbijeQT3bh7A6Nqn3Cx54w8gARWMF1u6lsvJqMvGn0KVrGmFkPR3UfLBtzKdpJsviYYjGtApP5FI+Im0HDzuq4b2tabkc78RbjOjNflW7E7e2F0tMQ+T2mXNCHSAGmK3V7NcC1dh04H6UHkdl3Ki53OkrPQOS7aKec1KwJVDXejNYBHGcI2umL3z+QCS1vdouPvXrNw2Roee3cmfYcii2W3YpS/UlKGsLEiY/asr+e8TE//1Bbnt2Oj5+idQ4eTy5GB/K5iPNJQqlqtK5D64SIDLFu8DESI/eGj5EY+WXx8WuKkRM3fGPxMWYxi9lXaDEC62timzZdisvlw+ebRCAwhIyMPh3C7OFwmOeff5633nqLRx55hGnTphMfn4Hj+NHaRUFBKR5PNiLfQ6lT8XgS+elPfwq0a0Gl4HLF4fEEOPPMswF4+umn7cIiDZH27IFrEPkA00nGj9GZ+tQuai6JeJBfR1ZWP8LhMG+//TYXX3wxjuPD6L6UYyJfuzARMx9Gf2sbJutBMFG9tZiSwh8SCCR3nGdNzRgMsXauPbY/ROz3UdxuH9u3b+/xOl544YV4vYPsMYTtOcXj9Q5i8uQp9m8/QGQ2IkNJT+/NL3/5Syts39k1yO2eT0tLG1deeSXvvffeV/vl/49bjMD6ho4I52nYpOtROhnTtOFmtDOG9L5tXxmB1bT6XbL6z0JpP25fDoPHnktwfbhHAit0JNGL+gjnrLj2+2inyDocOzCdR8+29/o7mA5XmpTMeloWbmV06AGUjscIDqciMseQQ3oIyZnjGD3tb8SlDMFko86xGOUiuqX7/dbx622dqERMyeK/EfkeIq2IctM4+y3qQy9QWXsNoxrvIzg1bJyzbhw0n68/IiMQeReTkXsEIgH8/sGYEu1kRA5B6zySk2tobX3icx204cN/YHUGT0PkB2jdn+zsyfa4Pfacghj9mYDF689QqpX8/PUxAitGYMXw0Y765S9YQudEgwdqCR5/Di1HbPlKCKy2oz6lYNixOO5UtCuRvmWraTlia48EVo/4uAZGT3vAkvJ32jXTTEQm2P9vxjQNSsLt6039zBdoWbgFx5WEyA8xpdgjEbkIUZNxe3sxbuZjZOXPwAQnx9n1XhadDXWwWOnCdLfug4gLpafb96+1uBpgaN0vaZ7/AUNH/ozqcbfQNmVnj/jYp888i9eP2rXctYi4SEgYigmcuhGZhNbD8Hh60dBwz+fiY339H2zQdSUiV6H1eOLiSnC7+9g1sQdTLn4bprS8FrN+3khCQk2MwIoRWDGLWcy+QosRWF8D+/e//43HE8CUhJhIlss1n7lzF0d97pJLLrGOhLYPZA/Tp0+3GU4PRCwOriYvb3DHdp988glPPPFE1Pe8c+dO/P40RJYh8ktEfmQdMsF0FLzJzvWEfTg/FzH/a4gIp5xyOo7jIRAYaDOeIrMQ2gWJ0xG5x/7/eNozogyB9AoiEykpGQrAypVr8XgyMNlZ7Wnmt0fM9yYi0pGd1p2NHNlINNkGIoMQWUJcXJZdnKUjcgKGRHNz9tlnk5s7ALd7GiK/RamjEXHj8w0gLm4EXm8cd9555wH+1r85dtAQWJHjYHLUjoPErNFd7qv3EeWhftlLX9wp685Bi9g+uCFMYsYI69A8hiHMelPe+KN9J7DauzGtgYS0WkzEvFPrKrp0bjcmC6uMAZWnMKDyZJRaYP/2IqZsr4DUXnW0LNlKaAUMqjrNdgUDU5IY18VB+x4io+zfBlln7Y+YrKkRGNKojEBCCa1zPuksFzkkYkwjyllTKgnTEawzI0zEoaLixyiVTmfH1k/QejAVFRd10WOJHs3Nr5CXt4xAYDDx8cMpKTmXhIRh1mHbhtG0GYMJZlyMKbm8GpErSUoaR2hKD92yuit/6akE5ogeRk/OWHdO2f50pYsRWAfC9o6PBwlG9q/5FkrPjrg3w2hXBZUtVx8YfOyCkflDj0Y75Rhx8gfQzih6D1q47wRWRMe6gspjUGpJxLHPpWvpnEgjImNJyWygpvn3VicrjCHkNyIyFI+vLxPmvk5oBdSG/oh2cunMUBpDdDn2/RYzN2Oy9uMQOQeT0ZqH6UgbQusE6mY8t0/4mJBQZbeLPO5Siou/h1K+CHwOo9R8cnLmfi4+trW9y+DBG4mPLycQKKV///X07bscpWoxgY9PEFmHIfxXY0Tul2EyVnXP+BiJkV+khPrL4uPXFCNjBFbMYhaz/bEYgXWA7LPPPuOEE04mNbU3SUlZHHHE+s/NFIq0++67D58vq8uD9yby8oo7PhMOh3G5Eq0z9QEmKt4HE3UXIsXKRf6By+Xntdde63Gfl112mU2FTsd0eUnHEEbKLiZOxXQg7IMhzc7qmF+pU0lN7YPj+OkUyHzeRvPPijiOj63z87hdFOVYB+wRjCBnAJH+9OtXxGOPPYbjeDCkVnsZzmR7bD9D5Cwcp5mxY5ujrklXmzZtDiLrEfmV/fdCRJJxnFbS0trP5S8Rx3gxBQVlvPXWWyxZsoJ+/UpISemDUrMjFl+b6NUrn927d3+BX8TBYzEC65s//Eml9p5qv28+Q+nE7rthfUEHrfGwt8nqPxOl/Xj8ufSv+pYpt4vCtJ+QkF6zXwRWSnYjJhu0fa5DMER2e8bl1ZgMgStJSKmhZMSFKD3anu9SRL6F0jWU1J7f4WCMnvY3m6XV3j1wvXVkNmBK+gJ0Zo8ej9KJGFK+jE59mJ2I5JKYMgRfYAAJySOprL6S4KzwHg5aMLibPfVc3kBEUVBwFFrP6vL8OJq8vKU9Omf19Q/jdmeh9UiUmodS8fTvf7S9jzdHzHOPfTZgsX0GSs2hb96qGIEVI7BiBJYdfStWIXJk1D2oXc2U1F/4pfGxbcOn5A87GsedhuNKJq98LY47BUNeRZT/KhctR2z7wgTWoOrT0DpS1+9STMnfx/b1U5jA4x2ICKNCD6B0Aiazfi1GVmIxmX2nd9zfLcu24riSLbaGMTIWHouNR2Oy69vXircgEo/SA+1+3o44lmkEEgYSF19CIL6cAcWn0Dpje7cElsfTF0O+RwYmcujTZyFa9+6Cj78hECjpER9bW98mMbEGrQtRagla55CR0WbLuCODqp9gArLP2e8jC5FNBOLKYgRWjMCKWcxi9hVajMA6QHb00d/C5yvG1P3fhc9XxaJFy/dp23/961+WvHms48Go9TpCoZkdn3nqqacwUfyXMF1eCjFRLQeT+XSaXSh8holoZeM4Xq6//nq2bdvGpk2bWLRoGRdddBFbtmyhqWkyhqRagSGWyvF4CqisrMKkYQ/BpHc71ilLRGQISpUg4sZx8jEEU+SioA2tA5hSmd9h0sfj7KIlHpHrIz77gZ3bi9aZ+HyJeL35XebbhNYJdrHTgIiPxYuX8eqrr9LQ0IbWDikpvfj+98/vILPuu+8+2xmnl11YlWBKCOM58cQT7YNyZ8Q+HiQuLiXq+/B6Ix1TMGVHwltvvXXgfjDfIDsoCayDzFErrD0Z7Qy3zsVORE7FG9eP4NG79tCC+SLzBo8Jk5BehdIzMaUfv0XpNEQFLEacbnFkNL6Eoj21Xro4aHULniVn0BIS00aSX7GBpkP/xfCW/7Plj1cgcrPFz/aSu2EYkv0mRE4io88Umha8ZwmnNESOtTjnxhso7OjAFVoNA4db/SrXAES5yc6fSVpOk8Xj9ozY3YgMoW/JSrQrEROhb8eVYzFBg/HW8SlCqSyKh12wR7ZBcGrY4loGxim8GSMY72f48F9bB20L7cSY1pWUlV3SRei4c+TkLEKpRXSS9A/aa+LQGUQAQ+K1dxVbjkhf3O4sGia90jNZFdFJbK8lgj0JD3fnjHX9ne2PU/ZfcNQOSgLrICP7a2b9Hu2kYro2hxH5HUp5qV/x0pf7vR4L/YYehXYqMQTJfaZZhfJajLkKEwycgIh0liz2gI/NKz6k/9BvkZg+it4DFjBu3hM0LHjFlj+eggnuTcSQMl5MtqjH/u33uNwZtC3dTSCx2L6/0g4PjjuN/NINtCzeTGg1VLfejONKQjt5KBUgKWMUOYMW2+02RWDMehLTa4lPrsAELCOxx4NIDUbmIh2lSsnKmdFtNlZy8hgMAfYdTIbtXET8DBv2a5SKXl+LrCQ7e06P+FhR8SPbzbC9WdJHaJ2N11uIKU1sn+cti5nvYIILGSjlp3rcLZ9P5u8rPn6REsH/UXyMEVgxi1nM9sdiBNYBsri4FEy0uv3B9iSO49nnLKwTTvg2Hk8qSq3F651MIJDE448/3vH3N954wz4oF2KEhduzB9pbDHsweivp1uF4BZHrSUhIp7S0Cp+vApET8PmGMnjwEObPX4JIrl38/N4uKHycccYZnHvuueTkDESpeEx0zBBOStVjSLQ7EbkcQ3KFO87Z56snGAySkzMQkTgcpx8uVyqGvMrBaMq0X5/N9nwesXP82J7DP2h3/BynGMcZjIlygcjLuFwB+vQpwOVahMgziNyM15vFtddeC8Cf//xnXK5kOstpdqF1FevXr2fXrl0kJmZhIowmy8txVtDUNCnquxg0aAjR4sZ/JBBIZseOHQfuB/MNshiBxTfeQWtd/wlZhbMQ5ULpAL74/oxZ+NCXXjCPW/yYzWTaFnG//cB2C+yHSBVGk+9wlPIxduEjPRJYDUtew3GnoNQyRK5F6Yn4EwbTumoHQxqvI5BQgkgAUVWYTNYMDNlUg0gxojzUBu9hwtw3EeUhuu38WkRGoZ2+DBp+VkfnrsaFb1PTdjsTFrxOaDXUz3+BhNShKD0Ik3k1An/8ICYu+4jSsRdjggPvYbJSfRH7+ASjlbUMj7dvtw5afuFxKJVt8b0PItnk5CwjGPyM1NQmtO6PyDq0Lic+vpKWls09OmiBQAUiN0acH2jdh7S0iWg9DEPo/dReo2UYbR8v+YXraJr2z8/PtooRWDEC6yAjsILHhhk4aiNK+1A6EcedTGXbNV/69xo8JmyJ78jy5CcQ8SIq3675LsBo+iVQ3vSTHgms4NpdxKcOQzt1iFyDqDVoJ4G6ec8xevr9JGfWIyrBYsuRiCq1GDUMkXJExTNg2EZCy8HrLzBzdBzT9YhkodRo0nq3duBjy7ItjAjdybhZj5tOh0vfJ2fAApROReRIlJ6OdhIYO+sfTFj8tl0T/g0TNMzAyFu0Z+QvRWQSotw0TH11D3ysrr3ZdjostdelAL+/iGBwF4WF30apZERWoPVEHCeV8eOf6hEf8/IOwwRuI/FxNtnZU9A6ExNEuIVODbAfICqZjKwWxrc9tfds1BiBFSOwYhazmH0pixFYB8i0jiRfQORVRBRbtmzZp+3D4TB33HEHa9YczimnnMrrr7++x2eqqsZYB+i3UQ9WkykQZ/89n84Sld0o5cbrHWAXBCY67/eXsmrVKrs4iSzTOYvx41sAUxJZWFiK2z0JkZtQ6lRcLj9eby/72S3WwZyMyHVoPRcRL253In5/ImPH1tGvXynB4GTi49MQOdQuLB7FRK1mY7LIOtO9HccI03s8swkEKvB6U+iqxeD1NtjW859GvH8RAwZUArBp0yYCgZYu1+d0ZsyYB8Add9yB1xtHIDCcQGAQGRl9eP7556Ou80033YTbHcBxVqPUMbhcifTqlUt2diFz5szj3Xff/TI/lW+cxQgsvvEOWvuYcNibjDv0CYLH7j4gC+YxCx5E6aQu9/NVeOMLMWV4EeVsai29ixb1SGAVDj8R7USWwuxCOwMY1nwDoTVQOOREtDORTtL9ekymwZGIfA+l+5JXdDi1wbutfkskhvwKQ9jfjtuT3eGgtY+2FTvpVTAPUR60k43S8aTlNFI86lwmLvuI0BpomP+KcTwlxWLhiC77OBORiSjtjyKwRtbfS0rqBNzuvsTFl+N25+B251BQcCytrdsJhcK0te1gyJBryc8/gvLyy2hp2dKjcxYK7aZ37wUodWjEvv+BUh4aGl6lf//j8XoL8ftLSEkdi89XTHpmkFF1f2XE2DtIy2ojIbmWovKzaJ27I0ZgxQisg57Aah/N6z5k7OJHaFm/zbx3AAgspX1d1pYvmt+T8iHy14j3f4k3rqBHAqtm8u1op3cU1iq9kH6l6witgZq229BONp2lg69hgqNTEbkEpWtISBlO65Id9vf8WsS+37XvvW60Eee+sAdGDh5xLkp50U4fRLlJTK+icOgJ1M9/qQMXtCsVE8istdi8O2Iff0YkB6WTGNP6cAc+NgRfpVfvuXg8ecTFleD1DcBx0ujVay6NjW92iKjX1v6BgoKjKCo6k8bGt+z73eNjefllaF0asW7+GK17UVX1OyoqfkxcXCVebwEpKeMIBCpITBrFkOqfMr75GXrnLSQ+sZq8wrU0zngnRmDFCKyYxSxmX4HFCKwDYOFw2JbO1WGExv+JyBRE/Ac0a2fz5s307l1IdGToeUQcHMeNyVbYGPG3+9HaheMsinKUlFrF7NmzbefCyAXC5ZSXj+zY37vvvsvSpavIzS1i5MgJfPe730VrNyJP28+/iUgZgUCWLfW7BSPqmYbJuMpD6wK83kRcrgZMuaLPPqwS2A/N0gAAIABJREFUEDkK020wGxN5C7Bp0yZOPfVUysuHWaJqTITD+TGmlDGOTpIOTEZVAjfddBP3338/bnciJqUbRD7F5xvOeeed13Fe77//Ptdccw033HADn3zySbfX+sEHH2T58tWMGDHGOp01iJyHSD2JiZl88MEHB+x73Zs9/fTTXHfddTz22GP/sX1+ETuoCayDmMw6ECN47G78iYMQtRaTmfQQ2ikkt3QpjqukC8HzA1J6Tei+XfxR0Gew0auKipq7JlI65iJCayG9z2R7D7f/vY5oYeHnEHGRmt2EKDcm07S9DHAKRqj3UZT27eGclYy6EO0MxpRYhhH5GdqJY+Lyj6L0ZlJ6NSGqBkPgJ0Y4i2FMmXQxWX1nGidnMYyf/CRax2GI/D+h1ELcnlxGN9xPU+ifnfoqkXowk9tHuPsxJUzdhOdwuTLQTh1KLUGpRAaWnGHmOiRiRGQSVNffaruVbUTkKrRTQXbe7D2dsb05YpHOWHf6LQdC4+pr5Kwd9ARWDB+/1MgpXoJ2xmOIq1dRupX0vJD9TX0UgV9PGGyKJLAi8LGy8Uoc16gumHomWf1mEVoLxSPPRTvTIv72bUw5YfvrT1GqF4lpNbi9OV2w9nsYfb+dKJ3MmBkPReHjmBkPoVQAk10FIo+hdDK1U+6KwseB1RtROo/2skSRv0fsYyMiA/H4cmlb8hmhxdA6fztefz+Umo8pGzwDUX6Gj/oN9S0v7QUf6REfW0PbSEisRusiRFahdR5pma0EZ+zqHh/nwoRpb+C4UhC1ApGfo/RkfHGFtC75pGeyam/4+FVpAH6N8DFGYMUsZjHbH4sRWAfAjMC6F6NDoCwYj0NE9UiQ7K899NBDeL3xuFzzEDkBlyuTRYuW8d3vfg/H8VqyZTYi63C7k0lJycBkbbWX1H2Ez5fLz3/+c5KTs6wD9xkir+DzFXPOOd/bY5/nnPN93G4/Xm8mSrktCeVF6xwCgSRCoemIHBex6PHY17/BZGgl0adPAab8MA6RfEwJogeTJn4rIs+g1FwGDCjn8ssvx+crRORZTJbXOEROxOMptNv3xehbvYPIvZhSyBmMGtVIOBxmzpxFeL0ZuN0L8fsHUVw89HM7F/Zk4XCYxMR0RPrTSZiFERnOueeeeyC+zr3uf82aI3EcL3FxtbhcfubPP/RrJyYfI7CIOWhfYtQtf47EzFpEBKUD5A87hqbV/7SZBzfb++5DtFPJ4LHn9EhgDWv9JdrJoTMz4AGU8jJ+3jNWrHgjokZE3Mv9MOXTnVmgJutrHUbE2Ich0FMxHVoLECkiK2/mHgRWSnYTnV0adyFyB0r3prLhakJrIbgmzNhDHmHEpDvpVbjAatgEMDqDJ9tnhw9foJDGOe90EFj9itZ16RB2CyJ+U96t3OTlryU4Y/c+E1jBSbupHX0Xg4vPJq9gDZnZQfLyVzGy7t4OZ695yvuMGHcnDcFXogis5PR666i2H8vbppxn9qsxAitGYMXw8SsaLUduJnvgHEyQT5HRbwpNh71PfOoQTGfn3Yh8hlKLSc+b1COBNWHp61YL6q6O+1c7/amov5zQWqidcpcts/un/ft89uzqNx4jYTEWk51VaXExHlO2NxyPrw/Blbui8HFQ1elofUjEPA8jMp7cwYd2kFf1C16idsrd9B9yAo47w64XUzAB20WIeFA6wKjgfR34OGz8r9DOQDoDsS9g9AS9iPKQmjaB5skffCECa3zDU5SWXUh+/3Vk9ZpCTu58ho24nrbpnxGaCa0ztlNbdxdjmx4hOCfcgZEDyk5B60hd2N1oZzBD6q6LEVgxAitmMYvZAbYYgXWAbN68JXi94+2D+R94PK0EgzP2adtwOMwjjzzCww8/vE/kxLPPPsu6deuZPXsh119/fYeA+UMPPcTatWtpaGhk3rxFLF68BK+32i440iyZlMjYsU189tln/PWvfyUrKw/H8aO1i3nzDmXnzp1R+/r73/+O2x3ZIv4B63hdi1JLycrKY+3adbjdC+3fqxFZEPEQ34VIbzyeOLSOt4uSIKZ0sYxorantuN1J1NdPxAhw3orJ8voOjtOXCRMm2BLG6zAZXILJYjgVkWspKhrecT3vuOMOTjnlFK677rr9zoL77LPP7D5mdlnErWPFilX7NecXsXvuuQePJxmRl+1+38Lrzea3v/3tV77vL2IxAqubcfxextfAMdrv0U1b96jRzTbBY8PUzv4jg8acwbBJv6Tt6E/3mLP5iA9pXb+9Y56hbT9DaT+OaxBKx5HeN8j4Jc+SW7KcuJSh9B60kLpDn+9Y1AeP3E1u8UpEeXBcA1HKQ/Ho8zschInLP8IQ4AMwJH/AYlF7U4crrPPzKSYbzENS5ghMhugvMIR8ETmFS/YgsHoVzMN013oPo2XVCyM87CYpcwT+hEEonYDSyfgTBpFXugqjZ/hj65xtRGQ2hZXf6nRylkNO4RI6Mx0+so7iFdZhewHt5FMx4ifRHa56GK2H7CAtcyJKpdIpzjwQpf1U191MaAGUVv8ApXxopwBRHnIHriZ46G5Cy8EfX0K0btZulE5hzIy/H/huWQeyBOa/7KzFCKxuxsGAjz1hZA/bjV/6FIPHnU1Z82U0r/twj7+3HLmFlnWbO+YZu/BRPP4ctKsP2snEnziIcYufYsCIbxOfWkVabhu1M/8YRWaVNfwIpX04rgEo5aXXgPm0rf2M0BGGZPcGCixpNBejp5pjMQ2Mbp8XkSct/hST2qvOvncBputqG/74gQRX7Y7Cx7Kxl6KdGkzwYK7FsaGIuPEnFJGUUdtRfu24UxhYfRqOq9CuAZdhsvU3kpg2OgofK8Ze3iWrbAQme2s7Ih+hdAs5/RbvEz6G5kJhybdtcGEEJmiRi0gchaWnEFoAI5vvxeXORDu9USqepPQxTJz/EaGlkDtoJXvoZjltFI86b//x8T9RIvhfxscYgRWzmMVsfyxGYB0g27x5M1OnzkZrB6UULS1T96nM7I033qCoaAhudwJudyIFBSW89NJLB+SYxo9vQ+QiTNbQHxH5Pj7fIK677rqOz+zatYsnn3wyStfpk08+YfXqI4iPT8Xj8aP17C4EzkKMqO9u/P6+/PCHP8TrjUPkJIzg56ldPl+J0VHYZRdDw+3nkhD5UcTnPsXtTsbrTbAOYJ5dQD2Mz5fDjTfeSEpKNqacphem8+IniLyFzzeE00/feECuW6T1719ind6X7DH+E6UyueGGGw74vrraaaedhsczN+paKrWGo4466ivf9xexGIHVzTgYHLR9JLCCx4bJKTkU5aSinTloV38SM2poOWprt05fcEOYkbPvpaT+QoZP/g1VU29m7MJHmXj4v/H4+6D0HER+hVJLcXnSaVr1blS2Qf2SF6mZchtNy9/do3W8L34QImsQOQOjJTjIOmztGVe3RtxveVaTJfK9J1HKQ8uybYRWQ3BVmIlLP2bU1PtQOoApNW6mU2fmV9bBm2Kx6lNErcEXl4+ocjrLo8MoPZSy0ZuiHLSSEefbZhpXYDS7irpg6/dIzw7tk3NWXv0jtFNEZ9ni85gsipPx+QsZP+k5W7Z9J6bT1hqUTmXo+J8TWg75pRtQeqzdPozIxbi92dTPf5kxM/5O62E7YgRWjMCK4eN+EFjlE3+C0j60MwXHNQKXN5O6Zc/2iLt1hz5HacMlDGn7GdXTbmHkIfcQXL+LtL6tlij6GSIbUTqO2pl/isLH5lXvUzPlNuoWPdfRnbAdH/sMWoZICEOo/xIT/PQiUowJPp4RgT1L8Qb6IHJC1BpOO5nUTr47Qsh9G02L/onb2xuT0dqbziyvFywG9cFk1IcRucZiqQ/TibYzcJjdb04UPo6Z+hCiXJjgwRv2Pvt3xDYP4LhS9gkfx7c9ZfHvGbvtFoxW4QmIclM/9RU83j6YLNTfI3IMogaTO3AloaVQ1fgbqyH2ot3+fpTyMXr6A4ye8TeaV3wQI7BiBFbMYhazA2QxAusA25YtW75QuVpT0yRbDvgJIjtwnBXU1Iw/IMeyZs063O5I8ulD3O4EHnzwQXbu3Mmdd97JbbfdtkeG0qJFy23m1r3W2avp4jTVY7RkwgQCA7nxxhu5//77qatrJSkpE6Uy7EPctJM2qe+vRmx/IwkJ2axatcrqcE1EpA6lxuB2J6LUOkyEL4zIUSiVTkVFDbt27eKBBx6gd+8ClHIh4kPrAFq7mTJl9lfSJfDBBx/E7Y7HCIoORcRLXd1Edu3adcD31dWuuuoq/P5SDPFnnFy/v5YLLrjgK9/3F7EYgbUfY28O3NfZsdsbgdXFWRs9/36UTsToQ4HIDrRrCCUNF+4xd/DY3aT0qcdkWCYiEk9yr/G0HLGV8sYfol1VRHY+1U4jg8d8d49ymcjW8ZEjt3g5hji/DJFfIKqYtN6N9vdbTWfb9HssbmlEHozArn8hIjQv/ZBR0+8jLqkcEcHlySS/YgPaySA6Syls9xfZev1hO3cChkC7CJE2RHzUL3iZ0BoIHhYmr3gtSgVQegwmW8yPSDKdGWMgsp7eBQuiBYJ7GL3zFyByShcsn4gpIxeKa85FOfX2OgzCNN7IxBsoJHhYmInLPyYlux6l49BODi5POum5rYhyo3QKLk861ZNv2bvYcE+k1X/7d/0VOWgxAms/xjcBH/cFI4+DlqO22k6D7eXMYUStJKtwZrfzD6g92WJBAiIpePx9qF/6IuOXPI1SfkQ+jLi/TyO9b6hnfOyCkUOaf4bJzDwJkZsQ1YYvrsDuLxGR1+koH5Zki2PnR+Gd4xpIVevvaFz8Nmk5LYgISvvIGbCIQNJgTDZVJAYFMQHO9tdbEJVozy8TE7Bci4ib0jGXdJTfDZlwrRWFb8+S9WMkPJ6JmOv/8Prz9wkfy0f9CMfV0OXYzkRkNo5rMKW1F9tgwkpMdtoSREoRFU/z4g8MZpeuQykP2lWAUl6y+89A6QDaSUdpH4Nqz+q5hLqn38g3HB9jBFbMYhaz/bEYgfVfNCP+7nR54L6JiLB169YvPf8rr7xCYmI6Hs9URE7H5xvIxIlTeP755+nduwCfLwe/P4/U1F488sgjAOzYsQOXy4Np1dzusKVaZ+YWRJZjMhZeRuQsEhLSoo519+7drFx5OFq7cbsz8HjiUMqhM+IGIhczdOho7r77brT2YjRnLkSpfnbxFEl2majae++9F7WP5557jnfffZf77ruPX/ziFzz55JM9Xoddu3bx7LPP7rfw+ubNmznnnHNYtWoVd999937NsT+2bds28vMH4/XWIXIRHk8L2dn9+Oijj/5jx7AvFiOw9mP8jzhoDatfo6ThQsqbf0TzER9EO2j7SGCVTrgY7Wrt4hicSu+iBXvsr7j+fAxZfB6GRJqJiA9RAdLzmtDOrOh51EoKhm3YJwJrzCEPIiqAyCpMFmgeojw0LHgVpZMtaZOJKR9xW9JoMiKNGA3BLSi1hOTM8Uxc9m8cVzIiZ2GySm9G6SQS00dislPbj/FV6+RdGYFnyXbeizCZqOmIHIV2BjK85UZCa2DUtL/Y7oztel4foHUeHn8uSk9C5DZEzkbpAKMn3b9PDtrAIaehnSY6CcBtmEzWY/D48hjacD1KpWMyZj/t2K+oFEZM+kOH4zhu7uPUTruLkjEXop0B9hzDiFyJduKZeNjHMQIrRmAdFPg48ciPqWi5gpL686lf8WI0Pu4jgTV28SOW4O8k5kX+iDeQv8f+6la8iMmIWo0JMJ6CyYxSpPVtthqAkfNcS3xa9T4RWC2rt+LyZGBKmhswGoEBhjb9nIS0GkPWiB+TRRWwa7WjMJqkz2ICbZfguJJoWb6FpMyxKH2IxbB/oJ0y0nIarCB9+zHuNDgsIft6l8WfMkQutPgfQGQ6ItMp+H/2zju+qvL+49/nOeeu7B1CWCEJCQGSsJIwAklIQsYNyEZAZO8dBFeh1k3dtaJW3NrWX8W9bdW6Wled1aq1DhS3CCIzef/+OCfJvRkIIWHo/bxezwty73Oedc753uf7eb4ju5qqxVA+dzvaCLH3pNZ1SlURFJaBNvpgWb7eiDY6kpF32UHJx0Hlf0XrWCzLq7rDBy8iC1HKydDR/7RluceW43XjHUKP/r+ul48jZn5E3gmPMXjsUzah+JRd90WUDmPw+KcCBFaAwAoggAAOEwEC6yiitraW8PA4RB722XA8i9sdyr59+9qkj48//pg1a05j7NgpXHvttezZs4dhw0ZiGPPtH99alDqNjAwrftSuXbtQStNgBm1ZTCnloXPnnvTs2RenMwgRoVu3njz//PPN9vvpp5/y3HPPsWPHDioqxtoWXX9B5HKcznDuvPNOiooq8bcI2GJvEDb5fPYAERHxzcYGe/TRRwkJicLtTsQ0gygoKGtC/D399NPEx3dFayeG4WD+/KVHxHqqrfDNN99w5pnrKCz0csopp/q5eh4rCBBYrSjHgYI2cOzdlluLWYJh5mE4ohg289VDJrAGTf4b2oimIWPWfrQxhPThFzbpMzSmPxahvR+LxBpgEz6TEBWOKA8NFlFvIhKM6epASs4ZVCzddUACq1vmckTNtRWTdxH5EMMcRp/hG8kqugGLtMq3FSgTkVstAkdKsCyxnHhCexIaNdAir1RPHzkFImuJ6VRuu7/MQ+QCLNfEwVgk1W+xDgNKfK7ZjeU+cwUiHmI6VdK35DbS885DG41j71WTmHwykfHDUCoSpaPplDqDyll76pWwwnHvMGDEnRRN+G8TBa10yuc4XB2w3LLrEmpEIOKi/4g7qJi1G8OMxgoM7RPHRY8hY/BFTQIPR3Usw4p901DXMHsycNTdAQIrQGD97OVj4dz/4HB3wDD7o81ylHLR13vLIRNYZSu2obQHked93qU1xHStatJn94GrsIikWqyYfEVY1kcDEdXPzhJ6rf3914j0QelQOqbPoHjOJwcksPpX/AXDzLCv/RQr2/RpJCRPoWDyW3bbfREZikWizcGylF9q79tcOFwJRMTlYzrjbJnp6853H06PRcJblp+X2W31wHIXPBORTKwD0h99rhuLyDJEdSM0aiAZgy8it+pR213PVz7eRVBoHzqlzkTpaJSKICJuGCVTtvrIwC8YMGIz+aNewDur1k8+emfVEBFbgHWIEWTPMQiRCLr1WkXVXIiIHYp16ODb7yXEdjqhiXxMH3Qu2hjvX1fNpXu/6gCBFSCwAggggMNEgMA6yjj//AtxuRLtTcf1uN1JnHrqme3ap9Ym/lZfXyEibNu2DYDKynE4nZVYp0z/w+Uq4sQTZ9Rfv2vXLj7//HPeeust5s1bRHn5WK655pompNv27dtZvHg5sbFdiIpKIDa2GwMHDmfz5s0AdO+eicidPuOoxTSj7c3MEkSq0TqcCy7Y0GQOu3btIiQk2mez9h0u1yBOP71h7Xbu3EloaDQiF2MFD30HtzuZ1atXH9Bi61jB/v37ueeeezjjjDO45ZZb2sVFsi0QILCOYDlCylrlKftweBIRudnn/TyFqMSSgyOufIq3upbYpNFosxsiK9DmQDzh6ZQt/65Jv2FxeVhuGyuxgq3fhMhGmwCqICiil60sJdj/ViByJ0oPoEPKJKqqoXDmO8R3n4grOIW4bmMYPu11qlZAUvYKRCZhuQI7bRInnp5DL6JqGRSc+CZJmctwhyQhsspPLimjCyn9T7cJtN9ixflLxd/aYRWJaTMZduK/iOt2AqLCULojSvfAMMMwnR2wrBXWNVKAhtlzmYDIOrTRmejEUiuQer0lVC3aGEKH7uPQRjwWyX8H2sikU/o8vPNr6dJzMUq5MMy+iHLSPXOtX+Yr7/xagsJ6YQWwfwvLRSiGtNxz65Wv9NzzENXbp99v0UYseSc82iRbVoeUKYic4jOP3WgjhsGT/n7wMa6OthJ2BBS1AIF1BMsRJLPik8cjap6PDLgHwxFJxfIfD1lGpudvsKyw1Hy0MRpthpF/8stN+kwd/CtbXtyJ5dJ3CSJ/xLJYKsJwRNn7p2gsQr4nIncjagLu4O5ULN9F2ZJtdMtegTskjfD4YQwcdS9VK6B/ZV1Gv4m2bHQjEkdM5wqqlkHpnM/pMXA9EXEDEZXTSIZNIjFtOqYrwT4k2GzLtK996mzGHZxKyezP6NpnKdqMQ1QY2rCCubuCk7DcrQsbtX02Ftk+EJFz0EYOwRGZ9hj/61NvLZEdCuwDhLMReRClRxMU3pvKefvIKrjRlo99UDqMqIRSKub86CcjO6fNR6m+WEmL/oGo/sR0qsS7qJaqxZA//kV7XT61+6xBGyNIHbiuiXzsU7QRbQ7C3+W9gvSh5x0fMQCPkIwMEFgBBBBAaxAgsI4yamtr+cMf/kBW1mB6987lyiuvPKhMhIeD+PhuiPyfzw//EwQFRdRnIPz6668ZOXI0SimU0owaNZHvv/+e/fv319d59dVXcblCMM1ZiFyI253K+PFT/fopLvbicg3DsjC7HqczmltvvbX++2XLVuJ0FtMQd+Z226UwDOv0y0AkhsmTT/Jrd9++fYwZMwHLesBXgfwjaWn96+tdd911OBzRiNyPRWBZ7otKhWOaQQwaVFRP2h1rqKmpobJyLG53RwxjFh5PDzIzc9i5c+fRHloTBAisI1iOkIJWvPBj+57u83m/XkGb4YesnFWttgixflW3063fUnoX/46yFd83229WxY1YZJULkVd9+r4TkRjC4/LQxmCsU/vf+nz/KaJMCk5+E9MVZyuWjyCyAsOMoHjOFvJPfMlWhGZhZUH9BpERdOg+qT6IcdUS6D/yzzZJ9CSW1dh6TGcciWlzELXQ7m8HIrFYwYPfR+Q2lA6hX/kdjJjxP8slZ8F2+pf9mf4Vf6F84U5cQclYxFiKj2L3hq2I+aaY/whRToIjMtHGQETORxsjcAd3xxWcghXMva7uu4gy6Vfyf7b7S5379X9QOowho5+pV87yx71kuyXu8rn+94THDqsnsMrn7iAksh/a6IXIfLTRmbiuJ+BdWtNEQRsysS5w/bmI3IfSZYRGD8C7qiZAYAUIrJ+1fKxaC05PF0Se8HmXalEqmOEnv9EqGTl4ylMkDVhJ2tCzGLHwo2b7LJr/XyzyvRciV/rLPzFtAikEK6bUCT7f12CYPejnvYOIhEK0UYjIfYhcitIh5J7wEOWLf0DpuuyAn2GR2KfidHdqeP+XwIjpH9gWY5sQ2Y7IHSgdRFruuRhmH589WSmWpdXriDyBNlJJGXAmBdPexrtkP5VL9pE76iH6lt5CyeytJPaYgeXe7UTkX9QR6JaLYUcaYoHuRZtpxHQqQRudEVmP0jPROpjYLqMRtcxn3nvRRkf6Ff/ZDtD+qP3592ijH+k55/sQ/DVoHYR/zMPXUMpF5YK99TKyU9pstBGHqLlosz/ukFRK537VRD6OXPCtZfGqZmMlAlmG4YigZP6nAQIrQGAFEEAAh4kAgfULxLXX/gGnMxIro8yFuFzxnHPO+U3qbdu2je+//569e/eyePEKnM4gtDbwesfj9Y7FMJb7/NBvxTBcvPPOOwB88MEHaO2wla3+tuKYQUpKn/r2v/32WzIzc3C5ogkKysDh8GCdbq3Ccq35EpE8tHb5jeu8887H6exuK7lf+YzhNxQWVgDw299egtZORAZhuegMwDJnX29v7L7H6Sxi4cKl7bjSP427776bioqxVFaO4957763//LHHHsPliqUhC89uPJ5MNm7ceBRH2zwCBNZRKu2oqFVU77atjR7xeb8uwuHu2irl7GD79a6ppXOfBfbz9J1P3y8h4qBb3yVosxSRZPyzA+5BKTepeWc2Sqtun3oPOY+RC7622/W1CngBbYb5uRp6l9aSlnc+2gxHRAiOyCJ/0oskpEzFcnOpu/ZVLLJN4QpKIjiiFxYZZRIWM5g+hVfRKWMOqbnrKZ6zhfD44VgB08dhpZEfiEXShyDyJ/8xm90YOOpeMvIvIr77JHrknkXJ3M8xzChEnvGpuwMRIT6pCstt0ddyYSJd+yysn9fQif9A6Uj8g8BfS1jMYL/5Vyz5keySG0juv4YB3jvxLtvfYmD2QRP+SlRiKe7QdLpmLWHA6LuIS6okunMhWaWbqFy97/hSxNpYOQsQWEextDOR5Q5Nwz8D3z8QcTByybZ2lZF9vbfaMuM+n773IeImIW2STVKf1GhsYJjDSc37le0KuN3nu/OI7lRB1UpwBXXHck30kas6mOFTXveTEQO99+IK6oaI4HB1pG/prfQp3IhhFvhc+zUW0WZiOKIIjR6IiIlSblxB3ehTdBVd+ywmKXsFw6b8i5SBZ6KNE7Bcr51YyYPqgscv8JuL0tPokbuevmW30SFlCt0yl1Ew/d9Edyq3r/edd1+6ZMxBqdRG8nEjIZH9feR+DUo5EXnNp87biDKpXLynod7yWnJGP0jKgLX0Kbqa8kXbWwzMXjjrXRJSp+AOSSOu+3hyxjxIYsY0IjsOocegdZQt33b8y8fDlJEBAiuAAAJoDQIEVjtj+/btnHfe+RQXj2LlytV88sknR3tIANx7772MHHkCRUVe/vjHP1JbW9ti3VNPPQO3uw8iLyDyDk5nFcHB8fhn1oKgoGQeeeQRAF577TVM04MVQ+ByLEuDtSjl4uuvv65vu7a2lqeffpq77rqLe+65x1YAfS0EHkEkyG88SUm9sVI8j8Yix25GZD2mGcTjjz/Oli1bMAynPV5rEyYyBCvTVwhWmngQeYiEhOT2WeCDwBVXXInTGYVl7n4WLlcUV155FQAbNmzA7R7XaMO1llmz5h218baEAIF1lEo7Kmgliz+z72koVsDgaYh4MBzR7aqc1ZWQ6H6ILLPJlh8QqSKiQz7FCz62T/+LseJVfWXXOQN3aCppQ85uGjtKzSa5/ymUL/nBVlDe8vn+fpzuzk3Tmy+DysV7GDn3a7xLa6laBgMqN1sn7/ISljXAjSjtoWT2F8QnTUTp0VgWA9uw3AvDEclDqWwMRwxZJdfbFksuLG8hAAAgAElEQVSnYlluxSFyIlbMrxKslPJLsIgtB4Uz/utj7fQsruDutmJXiEXu7UZkOZ7QuhT3uTRYP9Qg0hOlXBRMfdNSvJbsxxPSA1FLEPkckefRRjf6FFzlP/cVzZSDSPeemrvOlvcZWNlrOxCZWIz3lJrjW0ELEFgt4RcrH6vWgsOdaD/vE+33NgIRkxFzPmh3Gdm173I7O+m3tiw6F8MRQ8Wq3XjC0hEZiRUb6y3q4mUp5aJ/1R1oIwF/y/UbCI0ZRNVK7GDt1/h89yWiHIyY8WET+ehdWkPp3K/wLtlP1TIonrUFpd2I3G7Ln+fROoqcqgfpPfwKO+HDu7a8noDl4tgfkTxEecgq2YTpiEbpkxA5HyupRioWuZ+AZV16NiLDEQkhq+T6evlUMudTwuOHYWUhjLdlaS0it6K0B21G2vfKNybXAkSCyS65uX5OHXvMsIPMv4vIe2hdQofkKT8tH1vKLOhT8sY/ikXIxSKyCJFMHJ5OlC758viWj4cpIwMEVgABBNAaBAisdsS+ffvIzMzB7c5D5FKczjFERSWwdevWoz20Q0J0dCf8A81/iYjC6RxsK1Eg8igOh6c+019NTQ0eT5itoPmSMJkUFhY128/111+PFfhzi0/9mzCMCL96qanZWOTZDkTGYwUl9nD55ZcDsHnzZoKDsxr1ew2WMn6tz2dX0adP3gHn/r///Y9Nmzbx0EMPsX//fj766CMWLlxKTk4R1dVr+PLLL1u1pjU1NURExNOQRQdE7iEyMoHa2loeeeQRXK44GqxQ9uDxZPP73/++Vf21JwIE1lEq7aiglS79ylYG7sYiktYgcqWVGesIEFgFc97GHZqK0hEoHUxobC6lSz6nai3kjn/IJnPcFnGjgnGHJDN02osk9pxhK0Z1rj3/QOlQBk96mqpq6Nx7AdrIROQuRG5DG53pOWRDi0pJ0cz/0il9NiGRA+jUcw4JqdMQZVlZmc54ckbfj3d5LUo5sILK17kFerAsP+fYSlgCnTLmMnjC34nsOAKL3NpoK59f2nXdWNZZ16DUMIIj+lC5bA8VS3+0s4NdiEU8Dbbn7cET1pOYzhVYgZQ7YMUEuxaRcixXxZl0zphbP5/Ck/9DeOwQRARthJI84Ay8y2sOjaxq5v6WLvwCy5qsPw1up9usDIaTHjtqipV3TS09h2/AGdQFbYaT2HMGI5d/e0QVtQCBdZRKOxNYnrCeWMkXTscibP+CiEHx/C3tLiPLVnxPVOdSlHKjjWicnkSGnvQPqtZC4dx3CYsbYr+PBqLCMcwI+lXeTp+Sa205c4kte7agjT6kD72AqmroW3EryohC5DpEHkAbQ4ntMqpF+Vi+aDspA88gJCqHuK5jSBlwqp0d0ECUm7RB51G1AsLjC2x5V2ctFop1mHgS1kFEBO6QVIpmvk/nXhaxZMm0OoKuCouA6me3czKGGU7RzPeoWgnRncpRejKWxfoce+6hmM4YuvaZjzIGYR0SZCByFdahTAgi5+EJ7ek3Hyu2n7V2HbpPomzhtsOWj1WrwR2SbM/hcxoOGfJJGfSroyYfq9bCwLH3EByZhTaCiepUSsGsN4+ofAwQWAEEEEBrECCw2hH33nsvbndnGkieWlyuctat+/XRHtohoSmB9QUiCqWCETFQKgKtTa6//gYA3n//fWbNmmUrko3dWgoRUTz11FNN+vnXv/6FUkFY7n5325uoCPLyhvrV+93vrsTl6oxlhdEFkdNRqozw8Fg++OADNm3ahOVe+KVPv5OJiorHNDtiuRFehNMZxv/93/+1OO8rr/w9huEkOHgYbnci6elZREZ2wOGYiMh1OJ1ldO2axo8//njIa7p79277R9uXrPsQEWHv3r3U1NQwcuQo3O7OaD0fjyeDXr36N8myeCwgQGAdpdLOClpc97H2afRziDyINpKtALRHgMCyyIca8qe/yPBZr+NdU9vw3RrwnlLLyGXfUjT7PYZNfxVvdQ09Bp2FNnpiWTcFY7meOEjP31CvXFSu2ENq3q9xh6QRFN6HXgVX4F1e26xyVjr/KxyueJSajsifETURERdKV6CNAThcCRTNeB/v8lo7eHIdaXYGVhDlutP+XYik4QlLI2/so3TKmGUrSL4uQFlYGcUaXIK0mUx/71/IHfsI2uiCv9XEekKjc/EuryWiwwhbqduIRWIVYxGOXyByGdGdKpvMrWzh91Qu3dM6a6tm7u+giU9YWSLljEbyvoyMwouPmnLWa8QV9trdh8g/UcZIojuXHVEFLUBgHaXSzvIxo/AStNEVK8bmP1C6hOjOFa2Tj62UkYVz3mHotOepXL3X/7s1ULb8e4rnbyF/2ouUL9/JoIl/tQLFy2+wLJqs/VuHlElUrthT/373Lb+FkKgBuIKTScpeRfmiHc3KCe/yWiI7FKKNIVgZW09DxIEy+qONMpT2kDPqPqpWQEyXUVjWUyDyji3/Xq7fF4tMR8RFwUlv0r3/KRiOGESqfeTIKVikf0N2QqWn0i1rOeVLfrDfr4996v8VUQ7KF/9Ij9z1KD0VK1ahIDICkZlYsblesuI6NibmFu+kfPHONpOPlav22X0PayQfLyKm66ijJh/zp79gWwVfba/HChyueMpX7jhi8jFAYAUQQACtQYDAakdcccUVeDwVjX6wzmTKlBlHe2iHhFNPPQOnMwMrxsPbWK54YViZwt5G5HocjmCee+45nnzySZzOYJTqhshULEuEB2wlbpP9dy/Gjh3bbF/FxV4MIxYraGdHHA43b731ll+d2tpali1bgeVOs7V+bR2OKYwbNxmns+6kLgkrW1gF1slXJKY5EhEPcXFdufvuu1uc8xdffIFpumiIN7MHw0jCNIf5KJL78Xh6ccstt7RqXbOzB6PUKXZ7NWi9iv79G8i6/fv3c+edd7JmzRpuuOGGVhFlRwIBAusolXZW0MqXb6dz7/kYjkgc7kR6DD4b76r9h6SUeatrGTz5aXqXXMmQqc/4E1GtLS2kqXcFJfmQQtsReRwRoWT+Z02VDF8lpJGCUrFkF6VzPycj/2K0Mdznfa/Fcu/7PVbA5pkkpE6lagWkDFyHNlKwrDDGYKV+95X7q3AGdbJjUC1DqTFYBL8XpfPtw4A1ftdos4qM4ZcwoOouOx7ZGVjWXSDyG2K7jKZqBWTkX4Q2etvf+QYq/hpt9KLX8MtbdntpIwWtdOHntlLah4YDmy8RFcagE588agpaUHhvLJcmn7g8ymwxSHZ7KGgBAusolXaWj95TakgfdiFOT2fLui9jFmVLvjtk4qpw1n/oU3wVA8fe3ZSIOlwZ6dNPx7TpiKylwQrqFbSRSn/vHYckH73L9lMydytDJj1nE2I7/ORcg9X9JlxB3fAuryF3zCMoHWrLzkuwYgf6ysfNKB2F0kEoPR2R+bYs64tS4xBxoI3GmQ8vJLbbWErnf2Vbxc6yZV8tIn+z3N1XwNDJ/7SD07+EFZNrvV1nL0pPIb77hHaXj1Wr8bEa/sjnHuTQY+jZR00+dslaiKhFPmtai2H2oW/VbUdMPgYIrAACCKA1CBBY7YiGOFD/tn8cvsHtTubGG2882kM7JOzdu5ehQwttwsjAcmFJx9ciQKklnHjidDIz87BcXYYicj0iBVim2oKVTeYuRGI58cQTmTVrPuHhcSQmpnL55VdQW1vLnj17+N3vfkdJyWjmzVtcHxS+Me68806Cg7MbbWiuoUOHbpjmyfbm4AYsEi0MK+hz3UbrExyOMB555BHWrDmNrKwhTJgwjddff72+/XvvvZfg4IxG7Y/AMmtv+MzlGs/55zcNgH8weP3114mO7ojHk4TH042YmETefPPNVrV1NPGzJ7BO+Z6qM1u3OWs3pay9FLMWyKHWFG91DR1SJqN0BIZZjtLhJKRNwbumpl3G6wzqhr9L7teIaEoWfNp0fM0oHt4VtfTI+w3aCEVEMF0xiJrVSAZMRWSd/f+HcIekUbUSvMv3kz70Qtyh6TjcHW0Frc4Ca7clf5RpK1F1ba3BE5ZORsHFZJZca2fU+sz+7nWU8tC37BZ7PMVY7oVuRGaidCi54x6utyqLT55oZdlSVhwebaSidBBxSWOoWL67xbgsP1kO4X6n5J6JdVDQBZHJiIQTmzSqbUjLVj6n7pBURO7xWfMfEOWkaN57R0xB+9kTWL8k+ej77B2mfKxaDb0KLkcpJ9osRpvdCI7MZOSyb9rlPemYdhKWlZQvWdGL/t4/H5R8rKqGAVWbcXo6IyJoMwKluzeSj1fTYElqJZgoXfAVVSuta0Ojc3G4OmLF7HulfhwiU9FmDFa81Lq27kMbYaTmnknehMft+IXP1u+ltdGT9PwLcIekoFQfRE5GJAqRcivjYc6v6sedNuR8lHKijA6IuFAqAW3EEhTei+J5nxwR+Zg74WGsA9xQrLhpSbiCkyhb/t1Rk4+JGbOwrNsa7qHhyCOr/PojJh8DBFYAAQTQGgQIrBawZcsWNm/ezBtvvHFY7Zx++jrbDW0wDkcolZVj2bt3bxuN8sjhgQcewOVKQOR7rKDp/RttXFZjmsE4HEFYpsjn2HWexzJVn4PIbVguhEHk5g7H6SxG5GlE/oLL1bHZDHuffvops2cvICUlmzFjJtffj48//tgO1F6XbnkvLlcBWVkDUGp5o7F1arRxA4/nBDp06ITLVYDIzRjGEtzu0HrC7K233rLJx8/rr9G6BK2jaTBVfwuHI5gXX3yx1eu6a9cu7r//fh544AF2797d6naOJgIE1hEsxxGBNXDMvXbA4LpMoV+ijQ7kjL+/XcabmrvOtkR6AZH3UHoskR1H+I2pZOFWRi75tlllpF/57fZ4n7OVr1k2IVNn9fSqLcuet/9eQVy3sf4n8jaZFdOlwiak5qB0MsERmbaLna8b4KO4gpMtsm/VfjqkTrYUOxWHiEFK7no7c+Gvfa7ZjKgg+lbe3mT8RbPeY/Ckpxgx92NyxtzP8JPfaL1i1goFrWoN5E36G/Epo4lNGkm/UX9qW7KyFc9pat46tJGFdYj0NUrNJjRmQOtJtQCB5Ytfnnz0ffYOUz6WLvzcJmXq5MletDGC5JxT2+U9yRv/qJ2h8G4sonw9pjOa8mU76sc0csm3lCxoxmK1Gopmv28n0LgFy6L+VpuI+pMt177EijH1W3s+f8HhSsC7fH8TGdlj0DmWRZY6CaWHWDH+lIuGOIJguQsKJQu31pN9VmytWEQcRHcuJ3nAqWijFCueFFjWTQ6S+i7Hu3K/3/hLF37BoIlPUDz3I/LGPcrgSU/jXVVzROVj4Zx36dx7BtFdCuhZcCEVq348qvLReiYisBIb/YjIlWgjmNKlXx0x+RggsAIIIIDWIEBgNYMNGy6ySacsTNPD2LEnsm/fvla3995773HLLbfwwgsvHDDb37GM/fv3k5dXgMfTG8vVxYXIxTah9TBWBp5JdnbC9faPodc+cYq0/w0mIiKeq6++Gq1NH8UWRG4hNTXbr88ff/yRxMRkHI6xiNyJ1ksICgrnww8/BODccy/ANN0EBZXj8SSRnp7NOeecYyudf8cK/nmrtemRAT6bnJ04nQk4HJE0uLuAwzGDhQuX1vc/btwU3O4URM7G6ZyCxxPG+PEnYhgugoOz0NrBGWesP3I34RjFL4bA8i0/NwWtDa0K6kpKzlpEzfUjjpWaTUreae2yaa+s3ku3vivRRhAimtikEyhd+AVVq2HE3A8JjxtiP6eaDqlTKF++02+8MV2qsKxH68Zbg6gYRDkwzO5YLn8eRC1AG1UYZjjDp7/WrGJTuWof/Uf9hZSctWSX30zpom/QZhgiD1FvdaBmkJA6xVIcF3+DOyQZbQxF5HS00YOoTqUoI4wGkr7O7UQYMe+jNr1XrS6+ilJ7EQaHqJT5lsqVe+jUa54dZF8I75DPiPkftH4MAQLLF788+diGMjJnzP0Yjp5+8lHkRsLi89vt/elTeg0OdwIiQkj0APJPepGq1VCx/EfbxdBARAiLHdQkm2LPYRvQRlWj8RailAdtdrYJqCBETUCpGSgdRN/yW1okf4ac+CwpuafTq/BSShd9RUSH4fjH0LNdEKtr8FbXEtttFNpIRuQ0lC7AGdSFyI7FWIH0fS2IBtG38rajLxuPA/lYtdoiBg1HJCKCKySZvEmPH1H5GCCwAgjgl4FMEXlQRLaKSK2IFDVTJ0JEbhORbSLyrYjcIiLhLbQXILAa4T//+Q+G4ULkRfsH8Qvc7u7cdNNNR3toRx27du3iqquuYvLk6UyZMsUmpQTLXeZ3iLyBabrweMLweEbgdo/CMJysW7eOHTt21JN377zzjr3GP/psPO6hU6cefv3dfvvtBAVl+BBP4HKN4/TTz6yv8+abb3LFFVewefNm9u7dy7hxU7Bc/ULt08EQRDyEhMTgdg9D5Fd4PL1ITu5FUNCgRpux8/B6x9e3vW/fPjZt2sTo0ZNYvnwV77//fv3477rrrnoi7ZeOAIF1BMtxRGBljdyENvvQkJVuL9rsRXbFDe26ga9cvY+KVbv95hMWNxilZmJl9fwQbQyiW9+VfuON6z7eJt/r5MF+tJFIv4o/kjf+cUoWbGXQxCdI6reStCFnH9j1pNn1uAGlXGizAsPsi8PdkaI571O1GtKHnm/H26qTdTvQRjzBkX1obIFlOuOoXLmnxXWvWLGLlJwz8IT2JDQ6h+zym1usWzx/C936riAioZjkAWvrCb+fk4JWtRrKl+2gdFErrQoOU0ELEFhHsBxHBFbhrHcst1/51Ifgn0OnXrPb9f3xnlJDxcof/ebTvf8atDEQkQ+wsofOJTR6IN7q2gaio/AytDnC/0BCTyB54FoGTfgbhTPfoXDmO6TknkHygDXkT3v5kKyX8k96GcMRiWEORpvFVhD4MfdTtRoGT37ajh9Yl5W5Fm2UEdkxv4kFllJuCma81eK6e6tryRp5HSFRA/CEZZCat75FeVqx/EfS8y8ksmMJiRmzLKvWn6F8rFy5h5IFnx2+xWyAwAoggABaQLqIzBaRfiJSI80TWA+IyKMiEikiUSLymIjc3UJ7AQKrETZu3EhQUHEjYmMdEyeedLSH1mp8+OGHnHXWWaxcuYq///3vbdLm3r17CQmJxjIf32uv0+V0757BkCHFuFxhJCQkNxvgvLa2lh49sjCMRVjBlv+L292P004706/eZZddhsdT3uherGbWrHktjqu0dDQiFyDyAyLvIbKXoKCe3HTTTZx//gVMmTKDq6++mvfee892Qfyr3e5W3O4UrrvuujZZn18SfpEE1tFS1NpSQWsHpcyPNFi+k+DITLSRi8hZaCOX4Kis9nObaGGOxQu3IKKwrEXr5MjjONwd/cabO+5hOyjxzYi8ilKzcIckU7lq32Gvxcgl35I/9QXyT3qFjIJLyC67gfJl2+u/75h+Mg2xtWyXZbOS7v1XoY1QlC5BqfFWXKyKWw7YV4fUKWhjAFa8wT+gjRiyy25oOqbF3+D0dELpMYhcizbKcYemUr7shwMrYkdSKfN9TtviuTzcsQQILF/8tHw80jLyOJKPVashsedMO5PhmShjPIYjksI57xw5+WjP04of+JCP/NmBiOlnhVWycKttRfprLFe/i1A6iMLZ7x72OlSs2E3+tJcYPuMN+pRcTe+iKyie93H995mlf8Awi/DfC55PTNfRVgwsnYnIDJSOokufRQfsq/eIq9BGPFaM1jvRRjaJGbOb1PNW1xLVqRRt9EPkKkQtRBshLZNYAfkYILACCCCAg0JzFlhd7M97+3yWaX/WqZk2AgRWI9x333243Z0R2VP/Q+l0jmXNmtOO9tBahZdeegm3OxSX6wS0no/TGcaGDRe1SdtXXXU1DkcIWi/CNE/GND0EB0ei9XKsODQbcDqDmmQRBMutsnfvgYgIWhtMmTKzSQyoBmu4p+x78R9crnjuueeeFsd066234nYnYgUI3YvIZQQFhbN9+/Ymdf/wh+twONwEBaViGC7Gj596WK6iv1QECKwjWI4zBa1s6ff0HH4RCWnTyCi8mLIV3x9x5ax0yVeIaES2+FkyuUJSmoy3b8WteELT0UYwMV2rKJrz3xbnll1+M+7QHijtIaZLZYt104acj9JutBGNNoLpPeKqJnX6FG9Em70R2WmP72OUDqFPybWICkJUPCLxiLjIHf9Ii2MqWfAZlhvQJz5zvZHgyOwmdTMKLkGb+TTE5apBm5l0yZxH76Lf+bsQHYcElre6ln6VtxOZWEpkYil9K249/IDyAQLLFwEC6zCLd9V++lbcSse06STnnMqIBR8eWfloz9MT1hORP/vIjK2IGFY8LJ/xDp36D8Lj81HaQ2hMDoMm/q3FuQ2d8rxl+ardhET1J2/C483Wyxn7IKYz1orFpBx0ypjbJNvt8JPfQCk3Iu/b49uFNvrTY/CvcQYlISoakQREnPQYfO4B19wVnIzIHT5zfR9RphUb0ade/tQX7AMNn4MPNZ/oziPpVXgpQ6f+w89C7XiTj1WrYciU54hPnkBYXD7pQ887/MOlAIEVQAABHASaI7BGiciPzdTdLSLeZj4PEFiNsG/fPjIy+uFyDUPkGkxzOiEhUXz00UdHe2itQmFhBUqd6vNj/SxOZ1Cb3fNnnnmGhQuXsGLFKsrLy7HSFDeckjkc01m1anWL12/ZsoXvvvuuxe9///uNOBwePJ5OGIaDZcuqDxhH7IcffmDy5KmYphOlDBISknjyySdbrP/111/z0EMPtZjtMICfRoDAOoLlOFPQ6suRVsoazTE+eQLayLfJ8HvQRld6Dvttq+eTO+4hOyDybYi8jqg5lrXWyr1+9QZPespWgl6wZeKTKO1h+Mmv+dWrWLGLiIQCtJGINkejdChdMhfjCUvDctXuhUgSIjG4gpP8FSe7FM5+107VbmIFWa6Tw4/g9HT1q1u2dBsxXUsRGU5D5kMQGYfScRhmKUq5Gqy9jkMCq+fwS9BGHCKXIHIp2uhA+vANR1xBCxBYR7Acr/LxKMvIXkWX20kn7kLk72ijkNhuo1s9l5IFn9nZU3+DlUDhkmattcqWbkMbIbY1VC0i/0MbKfQp3tikzaR+q1E6GG2OQhudCYsbRMeeJ2PFWE1EJBsrS6vZbObZ8mU7iOlSadd5upG1maJ4/if1dStX7iU5Zy1KJ9CQxANEfo9IBNocVS+j6/s4zuTjkBOfQekgRE5FZBPa6Edst1FHXD4GCKwAAji+cYNYhFSN/W/j8rdmrmmOwJomVnysxvhcRKY083mAwGoG3333HWec8Styc0cwe/YC3nvvvaM9pFYjNrYrIk/4/ADXYpohvP76623az8aNGzHNcEQK/AgsrZcyf/4iampq+Ne//sXrr79+yIHsv/32W5588kk+/fTTA9a7//77CQ6OwO1OxDBcFBSUsXPnzsOZVgAHgV80gXUkFLXjWSk7khv5A5TylTvomrUE0xWPKziJnsM24D2l5ifXwVtdS/qw3+Jwd0RpF/Hdx1OycCtx3cfhH5vKipeVN/5Rv+u7D1htB7K/wVawuiDSg9S8XzXta9V+csY+QEbBJQyd+g8qVu6zla1L62W3yFxE3JQt/b7J9WFxQxBZiEg6Vmr0PYh8hTKG0y17WX294Se/humMQRvZiAy0CbIHEfkPVgKMZ+z+7sMwwylfufPo3r8Wntf8k16mW9/ldM1eytApzze5b6YzDn+3qEcxnTGHHufF9/0LEFi+CMjHtpKPR1lGetfUklF4Ca7gZExnHF0yF1K2/PuDWoecMfcRFN4bUSZhcYPJn/oCvQovRZv+oTiUMaGJ3Bt4wt0YZk+bUCpCpCMifQmPz2+2r/xpL9Gr8FIGjrmXylX7MByxiJyAlbDHSgYk4mbA6LubXJs8YC3aGIzIdERKEPnWIvrVMkKi+tUfCpQt3UZIdD/btbMAK2HRb7AssTIQOZv6eFs6lPyTXji696+F57V4/iek5q2jc++59B/1F7zVNX7fxyWNQeR0n3v0NUp5KJj970Mfw2HIxwCBFUAAxzeCxIpX1VIJbeaaNrPAWrx4MStXrmTlypU8/PDDR1sfDqANUVExFq0X+fxIPUhQUHibEzs9evS1FS23vYnYj8jfcDjCue2220hO7o3DEYppBtOr14CfJKMOFdu3b8fjCUPkJupSOrvd2Zx33vlt0v4TTzzB8OHldO+eyfLlqw5oNfZLwMMPP1wvMxYvXvxz3YAEFLQDlPyTXiZr5CbyT3r5mCewmsz9INchs/RatJGIyAOIvI7S4wmLzSO6sxf/jIW1aLN7fdDhupI+9FyUykIkGpEbEXkUkSEER2b+5PoOn/GG/V75WlP9CxFHE2WkbMl3dt0vbYuBHogEI2IQ08XrF28rMrEEkdU+bf4BK9mFgchkvzkpHUH+9JePjfvmM98BozejdBBKzUHUApQO9osNVrlyr70e//OZz8eICBXVu1unnAUIrMYIyMcDlBHzPiK77AZyxz/SxCXuWCOwWisfh5/8mm3Fc7VNgK/HMMNJHbQObXj9CSw1neSBa/2uHzz575broATbxNDTiMxB6VA/mdVc8VbX2nLrMZ9+ahBxkzPmgSb1PeG9EdmMFQi+FBEnIk7cIckUznqnvl6PQWfZ2WDrwoi8gWXV6rHlakPyIW166TXi8mOOwCqc/S6GIwptjELkFLTRkc69F/jVCY3Jw4r36Psb1qV1WQgDBFYAAQRwCGgpBlaN+MfAyrI/C8TAOgJ47bXXWL9+PRs2bGiRpNmyZQtnnfUbFi1awoMPPnjIFkmHgrfffpvw8FiCggbhdo/GNN1s2nR9m/fTpUtPRO7EMkFPwAqa7GDt2tPIyRmOYcxDZDciOzHNyZSXj2nT/h955BE8niQa4rmAyHX06zfssNt+9tlncTiC7FO4O3G5iujbd3C73rfjCQELrGbKsaSgtbFVgbe6lk4Zs1E6GMNRgNLBJPac2axb21FXylqruNVt8qNzsJzB36sAACAASURBVNxbGtxNlPLYKeU72ArX94ichemKo2L5j37zL56/BSsj6jU+bXyDiMngyc8ccJ0HnnCPrWT93efaa1EqokndilW7UEYQDdlz9yNyHoYzrsncLJed13za3I2IEBY/GP8T+X+htIuRy75p9dpWnrKPodOep2D2W22qoLlDezS6L/+H09OpgdhbA5EdixC1ECsL5j5ELSEiYfih93+Y72+AwGqmHEvysYVn7HBKn5JrUcqJ4RiCNjoSEt2fsiXf/ezkY1K/VXZ2V9/kE4NJG3oOSruxDhR3IvIXlA5i2EmvNPotqcF0dUBkkh+RIpLWhOxqXMqX7bBJpXN9rn0LEaNpNtU1ENGhgAZrVrAS+JgUzfvAb25RncqwXAV95mRkE9OtFKWH0ThTbO7ER1q9tt41tQyf9TpDT/on3lP2t9mz2yljNkrN8pnDR4hy1me9rVqDTTLmIbLNrnMb2gyjfOWOIyojAwRWAAH8cuASEbdYBNZI+2/D5/v7RORhEYkWkRixshDe1UJbAQKrDbFp0/WYpgenczIeTxkeTxgvvfSSX523336bkJAoXC4vSi3F5Yqhunptu47r22+/ZePGjVxwwQW8/fbb1NTU8Otfn010dCJBQRFMnz7nsJ+Bdet+jdudicg7iHyF1lNJTu7tQ2585rfJMAxHmxJAr7zyCg5HCL4BN5U6Ha93/GG3PXr0JJRa6zP+nTidETz//PNtMPLjHwECq5lyLClobUxg5Y57CG3E0pD+/TO0EUfO2Ad/dgpacGQ/RG71efd3IeKm+8C1lvKmPYgIQRF9yJ/2YrNrZVkJ/MWnjT2IeFBGOBUrmk/fXrUaCme9YxNYMVgZClch4iay4/Cm9ddA0oA1aCPZVui6W++kcpHUrxrv6v31cwuOzEbkCp/xPILhiGTwlKfRRghKn4jIKrQRQ8qg9Qe1hnmTHiOq00iCIrLoPnAN5Su2kz/9BZyeTmgjGqU8RHYsomz5d4etoHmra2x584HPHL5CRBqsNtZA4Zx3cYcko404tBGPK6R76zK8BQislvDzkI8tkACtLaWLvrLJm7rQDbvRRgHJOaf/7ORjt+xliFrgR/aI5BHduYjM0j9gOmMQEUxnfLPZU4vm/BdtRiKyrFEb+YgYDG1GptbLgVX70Y5Im8RajGXB1QFtRjUrHweOuQelQ+16eViHrIrYbqMZufSb+rl1yVqM0uN9xvIlSgUx6MSnbHkyDJEz0GY6UZ2KD8oluXDuf0hIm0pQeB86pp9E0bz3KV3yBWFxg1A6GGVE4grpzvBZb7TJsxsWOwR/6yowzLSG3+g1UL7iB6I6laJ0CNrsjjZDGTj2ntY9IwECK4AAAvgJdJWGWFm+ZZ1PnQgRuVVEtonIdyJys7QsGAIEVhth165dBAdHYrma1BEop5GfX+pXb8KEaRjGfJ8flrcxDEebu9QdCOeddwFud3es+CDP43IVUVZ2wmG1uWfPHmbMmIdhOBARsrLyeO+999izZw8uVzAi//SZ80NERnY45D6+/fZbzj77HMrKxrJu3a/5+uuvueOOO+jffxjJyZl07pyKyzUYkdsRWY/DEcQzzzxzWPMCyMsb0eRELigolfvuu6/Z+rfddhvZ2YNJTs5k/fqz2LNnz2GP4VhGgMBqphxLClobE1gpuac3Ot0FUXNIyTn1+FTQDrBmGQUXo41URF5C5HOsGFRdsQIHmxiOvijlJjFjlp9bX87YB4hIKMRyqR6FSG8sF7ZdWEFzkxEJJm3oeQdc6w4pU1C6AyJ9EUmzA8C/3qJClzH8YpQKtcmu7xF5FW0k07v4CqrWQs+CixBx2GU6IksQCcJwRJGcexpRncuITBxGYsbJ5Ix/4KCy9g068QmUDkbkPET+gjbyiUgoxBWSjGW1uh+RbWhjBF2zl7SJIh0ak0NDLBoQuZSg8F54T6n1c+epPGUfg6c8xaATn6TylH1HXDkLEFgtlGNJPrZAArS25Ix9EMPs0YiQuYmw2KE/O/k4dNrz9ru/GcuS5ypL5qlURJwYZk+UjiY0Jscvy9/wk98gPnkiyohGZCQiYYg8j2XddAdW3Kk8Ijs2HwurrvQecRWiQhDph0gvRLnJKrup5Xsz5j4c7s5Ysa0+QeRTlK4gPmUCVWstIt5wRNr9F2FZpCYi4iEl7zRiuo0iomM+HVLHk1n2h4NyRy5d8oVF5Km5iNyDUjNxuOKJT52E0qMQ+QErY/YpBEdltz5Tqo98TOpfjTbKaYgN9gJKOSlZtLWJu+Owma+SO+Fhyldsb/3zECCwAggggCOMAIHVRnj33XfR2sTfhe0fhIXF+dXr0aMf/qfx4PF04YknnmDnzp2cd975DBlSyvTpc3jrrbfaZawJCcmI3O0zhs9QSvPFF18cdtvbt2/n888/9/ts9epTcbuTsczJr8PlSuSCCzYcdJt79+7lpZdeolu3dFyufEQuwuUqIjo6EYcjHJHfIfJnXK5M0tJ6k54+gJKSUTz11FOHPR+ASy+9FLc7A8vipBaRG3G7Q5t9b2688Uaczih7I/dn3O4sJk8+uU3GcawiQGA1U44lBa2NCayskdehzUyfzfF+tJlNZum1PzsFzbt6P936rsSKgSKIDEPkHqxT/zft+W9BGx0ZMOrOevJK6RBEFiESixUzpTNWjCknIj2xXPgS6dTr5AOudeWqfWSW/oG47uPpmrWUwln/OWD9IVOeQxvRWG5zdfJ9E2Gxgxk24xU7Xs0/EXkVkZOwgrafjUiY7R6zAW0MJSii90GnVI9NOgGR9T79bUdUEKLctmJW9/nDuIKSDvue1CnO2gzDMAdjmMPQRjCDJv2tfeIJBQislvDzkI++z1YbyMeCmW+jlAuRrQ3PvlpEx7TpPzv5WLUGsspvQFSw/YynIHIvFsFfZ7m6C6WL6dZ3JVWroXjexxiOCJs814i8i0ixTRq5bZl5ByLTcIcm/+R6545/hIQe0+iYfjKDJj5xwLreVftRyuEju0HkP4gyKFu+DdMZjRXPawsiaxDpgMgYS2arboich9JTMczwg7bmzCi8CG2O8OmvFm0OtbM0Pu/z+Q+ICMWLthz2PSld8iWesHS02QNtVqKUm54FF7dfvLUAgRVAAAEcYQQIrDZCgwXWgz4/SKc3scCaNWs+DscEH6LrORwON1999RWDBxfhdg9A5CpMcx4eTxhvv/12m481OroTVjDhunF+h4hiy5Ytbd4XQE1NDZdddhk9ew6gT588rr322oN2H3zssceIjk60Nx3JPopZDUr1RmSqzzw+QWuTrVu3tun49+7dy4QJ09DagcsVS2hoNA888ECzdVNSsrCCNdeN6UO0Nvnyyy/bdEzHEgIEVjPlWFLQ2pjAKl/2A57wnrYrxQa0MRxPWDrly3b8LBW08uXb7ef7P/Y7fSFW5itfC4sVdO4zj6rVENmxGJHfIvJfm7D6HMtlrztW3JV9iFyJiJOcsfdTtnQb3bKX4QpOJjQml/5Vd7T63uSf9DJKh+EbaFjkCiISCkkfdi7amNBo3AuwLA0yaYjtsg9tZpBdeRMV1bvpXfw7YpPG0q3/SkbM/6DJWoXFDUVkk5+CpoxELNLvI5/PryEkemCb3JOqNTBy6ddkjryWPiUbKV38efsFxA4QWC3h5yEffZ+tNpCPVashocdUtJmCyLkoPR1thDL85Dd+lvKxag14wvtgxaSrReQ5ROLwP8y9E09YBlWrocegX6ON0fbnCYjch8jLWIcCN2HF5Ps7Ii669JmHt7qGjOEX4wnvjSesJ2lDz6Vy1b5W3RdvdQ3aaOwR8ApKu8mb/De0kdBo3Lci0sse21f1nys1m0695+JdU8uAMXfRIXUyiRkzGTL12SZrlZJ3apM4YUpPwXR2QOSPPp+/hVJOylZ83yb3pGLVbvqP+jO9ii6lYNZb7ZswIEBgBRBAAEcYAQKrDXHddZswTQ8Ox4m43VYMrBdffNGvzieffEKHDl0JCsrC7T4B0/RwySWX8eyzz+J0RiKyo/4HzTRnM3v2Ar/rd+/ezY8//nhY41y58hRcrgFYJ19fYprTGDAg/7DabA98//33dmbBjYicieXy4qt8zUFknM/fezAMN//+978Pqv3a2lpuvPFGcnIKGTiwgOuvv/6AxNqHH37Ic889x65du1qsY5GDf/UZ0y60dvD+++8f8vyPFwQIrGbKsaCgtbFS5ltGLvmWtCHnEJc0jrQhZzNy8TfN1z3ailYblciORbbb5E6brEmiwQKtFpGhaCOEoVP/SXBENpYFAYhMsMmhqxHpj2Vx4EHETXTnUrzVtUQlFqONQiyX7o0oHc6A0ZsPQCBuJ7PkGlJyT7MynPkEz/dW1xIS3d+O4fISInegjRj6Vf2RzJHXos1+jRS0kYjkIuLr1g5Kn0Tq4HVEd6lAG70Q2YDSkzEcUQ2BgO2SPvR8tJFlE3W1iFyL4YikQ+oUtJFpK4GXoHQ4/bx/Orhn7Bi454eTWStAYP1EOZbkYzvIyMpV+8gaeR3x3SfQLXt5y5aTR/sZb6NiBQQfgBXr9H2bvP7ER6asQySYzNLr6Jq9BJGl1JHrlsXVxYiMx3JtDkLEgdPTmbIl35Ga92u00R2RP2G5KKeT1K+6ZZJq1X4GjN5MSs6pZJffTMWKXX7fd81ebsurvyHyBNroR5fMRRTM/jdKubGSbNSN+2ws98TURnvPa4lIGEHa0PPseJDrELUSpYMZMPouv/6GnPiMfajwsn3tP1E6mJSc09FGDNZhxk1oI42umUuOP/l4mDIyQGAFEEAArUGAwGpjvPrqq/zqV7/iwgsvbNGi6YcffuDGG29kw4YNvPHGGwD86U9/Iji4f6MfycsYPrwCgJ07dzJ16iwMw4FSGq93PN98802rxrhr1y6mTJlpuzwKgwYV8cknn7Ruwu2IzZs3ExTU016Lx7FS0ddtirZiGDGYZm9EvsWyalhHp04p1NTUHFT7F1ywAZcrAcsF8Urc7kTOOef8wxrznDkLcTpHYFm17UWpU0lK6vmzzlgYILCaKceAglZZvYfuA0/F4UrA4Uqg+4BTqVzZctDwdilHe5PdRmXEgg8Jie5nKzgOtBGByHCs7IITsVxNTsUd2oPknNPRRi4iX2NZQnkRFUFst9H0GLSe5IGrGTTpSbzVtba7kYeGTFBWPKeIhKJm17N00Ve4Q1MtIkrNRhsxdO49369OycKtdEiZhDZCcQUn06f4amsO8/9nk2fjsdzYZ2C57DgRFWMTUJYlqzKi6F18JUqH+41N6al0zVrq11/Fit3EJ09ElBNtxGI6Y8gb/yiVK/eQNvRcgqP6E5FQdEBS7ph8bgIE1k/huJaPVWsgs2wTnrB0DEckCalTKFm4NSAfW1EqqncRnzIRUQ4rKLgRiVLJNkFVbZNSl6KUk+zyW2w35zo3vvWIBBMWO5jUvF/Rvf9q+lbcRuXKvXirazEc0fgfCr6INoKoXLm3KXlVXUNst9FooxOi5qLNdEJjBlK+fGcDubhyD937r8F0xmE6Y0nqV01F9W68a2oxXYmIZGPFUf0NIi5EhWO5fz9L/aGkMYSUQWfaboDP+IxtI8GRfZuMK23IuSjlQhsdUdpF+rDfUrUa+lXeTnj8cEKiB9Jz+EUHb1l2DNzzAIEVQAABHE0ECKxjBJ999hmG4UTkSfuHcBtudxYXX3wxAHPnLsLlGoSVJvh9nM5yKirGHnI/tbW13HXXXcyYMYcVK1bxyiuvtPVU2gyPP/44bncHrDgqtVhWAm4MIxfTDGbcuCnk55dgGC6czgji47vy8ssvH1TbtbW1hIbG4O9K+VdCQqIOmgBrDtu2basfk8MRRseO3Xnttdda3d7xgACB1Uw5BhS0rtnL7JPmxxB5DG1k0i17xZFV0I6lDfdhFu+aWgrmvE3RvPcYufRrO3hxLlYGrY+wXF8UBTPfJqbrKFthicbhTmDw5L83uy5Dp/7DVub2+8ih2wiO7Nds/ZTcX6GNYhrc/T5BKU/z7kmNSnr+hSidi2W52tci1iSC9GEb6Jh2EkqHYDgKUDqIzr3n07fydgxHTpNDlejOlc22XzTnvwyZ8lwTi4fj6nlpI6UsQGD9RDkG5GP/0f+HMqJssuKfKD2O0OgBfhaNARl5aKV44ScMn/kaFat2ExKdheV+NxWRfyAChiOX7PKbSc45A6WcNqETRO8Rv292TbzVtYgy8Y9Z9REi4kdK1ZXc8Y+gjTj7ANGyytdmJn2KN/7k+g858VmbrFqDyACsuFxpdEgZR6/CK1DKieEYijY6EBabR8HMf9vv9R6fsb2MNsObbb900VcMOfEZRi7++vh9VtpBPgYIrAACCKA1CBBYxxCuueZaDMNJcHAWDkcoRUUV9e5qliudb8DHD1FKs2PHjkPqY8mSlbhcHRA5BadzAh5P2DFLsOzfv5+UlN44HOPsE7hLMU03p512Gi+99FJ9vXfffZcXX3yR/fv3H3Tb+/bts380P/BbUxFh9+7dhz32d999l5dffvmQxnS8IkBgNVOOsoLmPWU/2ghC5EWf5/sFtBHkly0voJy1sqyBoIhMrLgvdev7Bkq7KFv6Pd7qWvKnvciQyU8f0OqtcuVenJ5OWK4qexH5BG1kkzbk7Gbrx3SpQuRyP1LJcAymb8WtP3kPOveei8hav2u1eQIZwy+iajXkT3uRrJGbGDb9X1SttoItK+VE5AW7/g9ooz/p+Rf+fJ+XAIF1KDhu5WPV2rpYdZf6vA8/onQY+dNeOvLy8ecmI9dAl6zFKO0b+2kX2ohj0MS/UrUaima/x6CJf6VsyXcHXJf47uNRegyWJegOlJ5GVGJps3V7DrsQbYxvRLqvoXOf+T+5/tnlN2M4hjS69mJiu55A1WoYMfd/ZJfdQN6Ex/BW1+CtrrEzrdbJ4xpEzSOma9XP91kJEFgBBBDAMYIAgXWMYevWrdx55528+OKLfm5nVoD4p31+WN9Da4MffvjhoNvesmULhuHAin1lKzB6GSecMKk9ptIm+Oyzz5gyZQaxsV3o128oDz74YJu1PXRoCYYxx1Yc92IY8xk0qKjN2v+lIEBgNVOOsoJWuXovogxE3vGRGf9GlNnqALjHy4Y7/+SX6JK1kMSMGeSMf7DdFLR+VX+0Y5ucg8iVaCOJpL7VDJ70FJ6wnogIpjP2J0//86e+gCs4CaWCEGWSkDqVihW7m63b1ALrY5RyH5QFVnb5zf/P3pmHSVFdbfytqp6FGWYY9n0REZBl2Pd9GdYBFwQFUURFUUZ20OQzmrhrVKKon4nGDVxiNBgVg5gArkExizFfojEukeCuILiBzJzvj1sDNU11T093dd3q6vf3PO8jU3Wr6tTtrmO9p2/dEjNytGN0wjtimPVl+KnbY25z7Kgb7ZEHw8S0mkhJy9GuIx8y+fuSDlPGAlYtCkABq7jZMAHudOTHg2JaTWXY7Bf8z48+fufHn7dTjh78Q2nReY6UTvyFTF25Py35cfRZ/1SP2BnnC3CXmNYIKW46WMYteM8uHkIMM1/a97rA9XHAak0472MpaTFSYOQIjFwpajpIxp+707Xt4RFYX9if6XcJj8Aae/a/7YL9a/a2X4tp9T1U4HfTkFlbxYwUiRXpJWakk+QWtJMxZ/0rNN8VP/IjC1iEkGRgAStDWLx4ueTn9xb1hpc/SV7eKJkx49Q67ePZZ5+VevXaRP3C9Kh06tQ7TVEHmxUrVomaE6ZYgCKJRI6cdJ/UDgtYLgqAQWt+9EwxzKmiXuf+oRjmFGnR6eRQm7OBJz0lhlkgMM4T4EIxrUbSdeS1aTFo01aLDJyxUZq0ny4lLcdJz7LbZcL5n4gZKRLgRnvEwEYxzAaHRh3EUvnygzL6jL9L2cIP4rabcP6nUq+os5iRPmIYZ9pzYC1M6DOYuuyANO1wnBhmQ7Fyxolh1EvokdJxZ78jvSffe2jerjB9X/wwaCxguSgA+bHHuJvFtDoJ8DcBvhLgB5Jb0E5Pgd+n7/y4he9JJK+pmNbxAlwmZqSLNOkwTcpXV6UlP46a/zdp1eV0adBspBwz6GKZWLFHipoMEsM4XdSE76+JafWQzkN+Umv/jD37bRl71ltxc1D5ikppetTxjjmwuhwxB1Y8Vc9VZUXGiGk1l5IWI2vddlLFbulb/qD0P26DN49PB+S74ld+ZAGLEJIMLGBlCPv375eKimWSn18kubn15LTTzpK9e/fWaR+7d++W3NwCAbYeGvKck3PiEW86zAZ27txpj0Z71S4KPie5uWPloot+qDu0jIMFLBcFwKBNvOAzadK+vPqzkSbtp8V+W2BIbriLmgyMesTueTGtIpmy/Ju0GDTnG8zKV1RJh94VAqM06keCFdKm25me9eXkxftivoWwNpWvqJKhpzwvpRN+IaPmvabnuxCg74sfBo0FLBcFID+WrzwoHfosE8PMEwBS2LBU7zXhw3f9qH7LxTBnOnLTbjHMYhl+2va058dpK0X6T/+NqDcU7nPEsEHy63f2rB/VWwg3SKdBP3B9C2FtGnPmm1I64Q4ZPPP3eh63D8h3xa/8yAIWISQZWMDKMKqqqlJ6o93//u/PJRLJk4KCiVJQ0FXatOkku3bt8jDCzGDDhg1SWBhtNO+UAQPG6A4t42ABy0UBMGjVmlDxqUy84LO0vC4+LTfcKbze3sppKDXn/VJz3Y1b8F76TIEda5fhV4thFIuauNiRV4yKI94U6LfGnPmmND96puQWdJDGbafIiLk79JuwoBi0NJgyFrBqUYDy4+Rl+6TsvF1SvkrT5O11/c6nkB+btJsuNef9ErFyhiQ0h17S16Ud65CTtwiMfFFv9PvcEcNDUq+4u9a+n3TBl9Kh9xLJKzxaipoMkn7lv9KfA7MkP7KARQhJBhawspC33npLbr75ZnnooYfkm2++0R2OFv7xj3+IZeULsOvQjVROzlw5++zzdIeWcbCA5aIAGbRUDI+WG+5UDFr7afbjg1X2df0LyS1oJ+XLD6bPFKwWmbL8OzEjxQJsEqCJqMnS3xDgLjHMQhk+548ybaXIsNkvSNse50jbHufI0FOe98mc7ZGcvOYC4xwBtgjwAzGtIhl39jtpO+bERZ/LmDPfSKzfQ27QWMByUZDyozPn6MqPdfnOp5Afu464VkxrgADf2PnxNTGMXBl79tvpuy7tWBu2Hi/AVaLe7lcuwF8EeFpMq4N0G32jTFup5qHq2G+VtOpyuvQtf9C3EVCNWpeJaY0R4CkBbhfDbCD9j/tN2o43Zck3Mnr+P5KfTzBE+ZEFLEJIMrCARbKWOXPmS35+WwEulLy8cikubiJvv/227rAyDhawalEQDJoH5icTNObMNyQnv5VYkW5i5QwW0yqQQTM2pd0UTKj42L4G9gnwVwFG2Y/KFEi/6Y/ItJUifaasE8OsLzAWC4zFYpj1pc+UdWnvk9IJd4gZGeAo6okY5gw5ZvCPPD9W+YpKad9rsZoM2ciT3IL2MvTkZ4Nn0NL8WMy0H8qh63/JTcyPzI/B0OTF+6RB82FiWi3FiowTw8iTLsOu9OW6zKt/jAC/E+BTAeYIkC9AvrQrPV/KV1TKqHmvixkpFsM8RYCLxbTaJjy/XyoaPf+fYhj59pyF1aPCfiYlLcak5XilE34pVqREYOSJGSmWHuNuC15+dObINOfHSatCmx8JIWmEBSyStVRWVspDDz0kp59+llxyyaXy3//+V3dIGQkLWLUoww3a0FOel/a9K6Rjv5Uy+oz/i9t28EmbpVWX06RVl9Nrnbg8fSbtK+lb/pD0mniXTDj/E19MQfnqKqnX4FgBrrYLRZUC41xp3G6KTFup5p7KLWgnwEMOk/Qrya3XNu0To3cbdb2YVnnU49LnS4c+iz0/Vs+y28W0OgrwT/vxzTVi5TSq+0gDFrAyAebHlSJjz3pLOg38gbQrPV8Gz3wmbtvRZ/yftCtdJM2PniW9J92d/AjFFFS+/KAMmrFJepbdLqPn/9O367Jtj3PEMI8T9dZnEeA+ieQ2PfTG1RbHzBEYFY4c9Z7AyJVxC95Na38MP3W7GFYjAQ46jv2AFDbs6/mxRs17XQyznj3Sq0qA34thFtb9kW4WsAghWQ4LWISQlGABqxZ5edOXLrPmppUiPcbdJoapXoVumKeLYRbENGk9y34hhtlAgIsEWC2GWSS9Jt7tu0Fz09Rl++XoARdJTr02klvQXo4Z/OPDbxurPt8U+3PY3JfEymkkVuRYMSMdJK+wvYxZ8C+Ztlpk6or99jXyX4dJ2iUADhm4dGnMmW+KYeQJsNE2TdvtNyNu8fxYDVtPkJqT6FeJGekoA098KhgGLd2mjAWsrMqPw0/dLqZV3x41tFhMq2HMEU0j5r6q2hpnCnCFmNZR0qbb2dpzY7V6Tfyl1CvuJpHcptL62Pky4fxPa+bHFHPkhIqPpKCkh5hWK7FyeolpFcjAGU8c2nf9xgOiCvwiVuQoGXzy79P8/4YDkluvjQCX28W1nWJavaXz0Ms8P1aXYZeJac2scY6Gcbp0GvSDYOVHP3IkC1iEkBRgAYsQkhIsYNWiDDVoU5Z+J1ZOIwGedtxw3yhFTQYecUNdvqJScvJbCvCYo+3DvowwSkTtSheJafW2z2WjmNax0rH/RTUNmgcGYPKyfdL/+Edl4ElPytSV+2v0c/3G/WyTVN0/V0j9Rqn/yl+28APpPekeGXDC4zJ12QGZtlJkwvmfyrEjr5MOvS+QAcc/Jr0m3iVWpIEYZpEYZj3pOvyatPRzs44zBLjEcY77xbSa1Drf17iz35FjBv9IjuqzRD1yyAJWJpDV+XHaSpHGbSYJcLHj+/6KGGY9mXTBHpdr4yQBVjravu/LCKNE1Lf8QTGtxgKsF+AFMcxyadB8uMrdHhWwpl0oUr7qoAyetVn6Tf+VTFz8eY1+7tB3qRjmFHvkpgiwTQwzXyZekNqbcycv/kr6TXtY+ky9XyZV7JZpK9X/ZyyelwAAIABJREFU23pPulva966QnmW3y5CTn5O8wqPEMAoERkRaHnNqWn5Y6D5mjZiRsTUKWKY1RbqOuCrudpMqdkv3MWukfa9F0nfqAzJ11fcsYBFCshoWsAghKcECVi3KUIM2/tyd9ud6wHHD/RcxI8VH3GBPWfqt3fYDR9v/CIDDI51Wqrc9DTl5W2JvBfRIU5ftF8PMFzVpcHVsz4kVKalp0NJVNLH3P3zudrFySsSK9BcrZ4BYkQYyfO4fUzSeD4lh5omVM0RMq73UK+4qI+a+Krn1WotpjbZHhbSQNt3PkclLvpZR815zNddeafDM36t5vnCLAFvFMI+Xwoa94k7GPPzUl8W0isQwZwiMhWKYxXLs6BtYwAo+WZ0fp60Uya3XXtSLEQ6PODTM+jJq3t+O+J4XNuwnwMM1ixeRtjJk1lZHrjogw2a/KKPmveZr4b9B81ECrHXEtk8Ms0BGzXvd0wJWvH6eUPGJFDToJmako1iRsWIYudJzws9Tmo9s1LzXJSevuZoTMdJbrEgDGTJrm5S0GCVmpIsAy8WMlEr9xv1k0gV7ZfQZf5eyhR+krZ8nnPex/abc5QI8L8BFYkaKZfy5O2NuM3HRZ5Jfv5OYkSEqXquDNOt4gpSvrmIBixCStbCARQhJCRawalG6bgC9MmoxVL7yoOTWayvAPQ5js0oati5zNXRqhNGl9mNqVQL8UIqbDTlkQHpPvk9Mq1DMSFuBkSttui3wZQ6YKUu+EcAQ4B3HefxNDCNXmcR0Fa5cNGnJbuk95R7pPeUembRkd3yjHON8Ji/+SnqOv03a9lxgF4t+Y5/TQTHM46V+o16qGHRo0vadYhj5Mnr+P3wxwwOOf0yKmgySnPw20vrY+VJ23odx2zdqPSFqFMsLYlqFMnnpXu8/Az8KVyxgZUV+nLZapHmnWQLjbMe19luxchrKlGXfHHE9d+i7VAxrkuMHgafEtApl0pI9Mm21yIjT/iS5BW3FtJqKYdaXBs2GHX6ML82q36i/APc5rsHvxbAayfBTX/Y1P05duV/6n7BBek68Xcad+06Nvk40P5avqJT+x/1G2vdaJPWKugiwzPH5XCu5Be3FMNsJ8PXhUaKRHlI64Q5f+nrUvNekSbtyyclvJY3bTJIRc1+N277LsMvtNyRW2vF+IYbVUIae+nwo8iMLWISQZGABixCSEixg1aIMNmgDTnxcDDNfzMg4sSKDxMppJCPP+KuroRhx2g6J5DYWK9JDrEh3ieQ2kZHz/izTVouULdxlz8P01KHHZ0zrKOk96W5fTEOT9tPFME8U4DMBPhLTnCwtj5mj1vto0GL1c6IGbfLir6R+oz5iRnqLepNXsTjfLgg8IYbZWICf1xjpYeX0PfQ2xKApJ7+NAM/VHMVi1JPRZ/49FAaNBaxalMH5ceyCtyQnv6VYkT5iRiaKYeRJn6nrXa/nCRWfSmHDUjEjbcTKGSKGkSt9pq6TaatFyldVSb3irvYPAAcF+EoMc4q06XaWL9fgsSOvE9M6VoA37cLORZJXeJT6gUF3foyVI2OcS5tuZ4lptRJgqQCWAG84cstudS0aNeehAhbLUX2Xas+FbmrR6RQBrqyZzyNl0nPi7aHIjyxgEUKSgQUsQkhKsICVoDLNoNkaf9770mP8WimddIdMXPJF3LaTl+6VvtMfkn7TfyWTl+07ZDZ6T75XrJwhUabhCml+9MwjbtjLV1TK5MX7PH2EZsJ5H0mj1mX2SCxDmrQvV3OrpPPRwTSYtp5lt4sZ6WWP4vhQgFwB/uXo04ulXlFXMa0yOfxWrX+KYeTKuLPfqXO/la+olGNH/lTyCo+WnLyW0r73Ypm8+CvvDNpqkWZHnSAwznecw+Ni5TSSKcu/CYVBYwGrDsrA/Dh56V7pPeUe6T7uZzL23Lfjtp266nsZNPN30nvqvVJ2/q5D1/XYc94WICLAd47rYJvk5LV0uSar7PwY+7Hcumrq8u+lbc/zBEaOAIYUlPSUUWe8lnH5cfSZfxfDyBf1ggwRoEvUCOJNYkZKxDCbC/C5VD8uaUaOlj5T1ifVdwOO/63Ub9RPrJzG0qzjjKTybDx1G3ODmFZ/AfYf+vHHMAtk5Bl/DkV+ZAGLEJIMLGARQlKCBawElaEFLC9MxqAZvxPTaiPO+bQM8yxpV7qoxs166YQ77cngIYUlpTJs9ouemoGy8z6UCed9nP55XdJk0Dr0WSzAkhojB4DmAvxEDONsMa1CGXji76RecVcxI93EtGaKYdaXowf+T1L9dezIn4pptRdggwBbxLSGSYtOp3hawBp91j8kktdUrMhgMSPTxDDzpffU+9LTpyxgeQkLWB5d4xMv+NwuHjmL0XdLYUmvGtfLsNkvSEFJTwEgOfktpdfEuzzNj5Mu2CPjzvmPlK/yYW7ANOTHftMfFiunn6MPfyVAgZ0zLxLDLJHuY26WZkedKKbVTExrtphWG2nUerxMXba/zv01bPYLYpiFAtwmwMtiGPMlr/CopPYVS5OX7pOiJgPEjHQU05olhlki7UrPC01+ZAGLEJIMLGBlGFVVVXLVVddI48atJS+vvsycOVc+++wz3WGRLIYFrASVrhvBH8SQboPh0NSV30thw1J7DpiHBVgpplVfRp/xf4du1IfM2iqGWSzqTYafCHCNWJEGMrHii5RNwKh5r0u/4x6RcQv/E2xTVov6TF0nZqSTAPtsg/aJGEaxNGw1Rtr1WiSj5r8u01aqeb/6TFknXYdfKcNP3Z50v+UVHm0XrxxvToMpExd9lnLhyvk5TFqyW0on/ly6jf6pjFnwr/T1IQtYXhLsAlYG5cdpF4q07XGu/Rjf3QLcKIZZIn2mrDt0zUxc9LmYkWIBrrXz4wYxzCL11s4U82PZwl3S//hHZeS8v2R0fhx77ttiGLkC/FMOzwvYT4qa9JVWXU+TQTM3ybSVamTpoBm/ky7Dr5ABx/826bkYW3WdJ8AKR36sFDPSQQae8IQ3+dH+LKau3C/9jvu1dB11tQyd81x6JnDXlB9ZwCKEJAMLWBnGz352k+TntxNgowCvSm7uVBk2bLzusEgWwwJWgsriAlb1HDAd+i6VwoZ9pXnHk46YvLZNt7NEvZ3JOddHP+k9+d6kjUD58oPSsvOpYhj1xMrpIzBypMvwq/T3R5KaumK/NGpTJqbVWkzrZDGtptK800wpX1VZ69wwySgnr6UAWx2fyR4BIGULd3lawPJNLGB5CQtYXl7bK7+XY0f9VIqaDJKGLcdJ/+mP1rhmek+6W6zIwKjHsJdI2+4LUroWu4++SQwjV6yc3mKYhdKs44kydeUB7f2RrDoNulgMs1BM6yQxI12loEE3mXjBZ2nJj82PninAZVH/zyqVfuW/8rSAFeb8yAIWISQZWMDKMDp27CnAA47/YX4hphmRd999V3doJEthAStBZXkBqzYD0bb7AoGxJMoM9E56bpJpK0X6TFkvptVBgI/sff5VvZEvHROE+9SP5SsPyoATH5euI6+SwbM21yxeeWzQ2vdeLKY1zB55tUcMY740aDYs9X2zgBUGWMBKR46Mcc30nnyvWJF+NQtYRoW07XFu0tfhuLPfsUcsbbf3+ZmYkS7pmSDcx34ccdor0nXk1dKn/H6ZsvzbtOXHftMeFtNqIcAr9uPxa8WMFMmkC/awgMUCFiEkjbCAlWG0bdtVDr82XQT4SiwrT958803doZE0sW/fPlmzZo3MmnWaXHvtdbJnzx7dIdWABawk5McNYpCMWgIGQs0nUl+A9QK8I8DFYuU0kkkXfJm0EWjdbb4AP6xh+szIZOkx/mb9feJHX9fh7V1umljxhRQ1GSBq8ntI/UZ9ZdyC99yNVl2ku498NGpL1jA/Bjo/Bi1HxrgWJ1XsFiunoQCX2PlxnRhmoQyb81LS+bHXxF+KlTMyalTXlerlGrr7IwPyY/mKKmnZeY6ol2kYkpPXSobM2pL5+dHHHDlpRWjzIyEkjbCAlWFceulPJD+/hwCvC/CJWNaZ0q1bP6mqqtIdGkkD3377rXTv3k/y8/sL8BPJzx8qRx/dXfbt26c7tEOwgJWEWMByVd+pD9jzLkGKmw2VEaf9KaVfso8ZfImY1jSHOTsgZqSD9D9hg/4+yQCD1qLTyfa8PFcIcIaYVqGMmLsj8w0aC1heEI78GLQcGed6HDF3hxQ3HSIAJL9+J+lb/lBK+XHwSZvtEUTfHsqRhnmKHNVvhf7+yID82H3MWjGtRgJcLMASMcwS6Tn+9szPjz7mSBawCCHJwAJWhnHgwAFZsGCRRCJ5AkAGDhzFxwdDzPr166VevS5y+BXKB6VevT5y++236w7tECxgJSEfDXQgHqGpo0Hw6hXxZeftkkheUzHMOQLcLqY1Suo36p3Rc7yk3cDZGnPWG/Yr6T92FABXSvNOs4JltFIVC1jJEo78GCtH6roufcyP5SsqpbjZEDGtIQL8rxjmGWLlNJRx576j/7rUpQTzY/mqSonkNbfno63Oj49JTn6rw29x1H0uXogFLEJIAGEBK0P5+uuv5fPPP9cdBkkzl156qeTknF5jiL9hLJLly5frDu0QLGAlId3mLOAFLM+0WmTcOe9I+94V0rBVmRwz5Ecyaclu/aZApxI0aINnPSNW5Kiox4vWSVGTwSxgsYAFhCU/ZmABy0tNXrJXOg+7TBq2KpO2pQvT+xbQTFCC+XHK8m/t6/q/jvz4ngCQqSu/Z35kAYsQkkZYwCIkwGzatEny8po6JqH+XPLz28ojjzyiO7RDsICVovw2a7UVttJh4HQVsHTf/GewJi3dI6ZVKMDjdu75RkxrpBw96AfaY0ubWMCqC8yPXkpTAUv7NZfBKm42RIDVAlTZWi4NWozQHlfaxAIWISQgsIBFSICpqqqSU045XXJyiqWgYIrk5jaS8vIZcvDgQd2hHYIFrBSVDQaNBayMVN9pD4hh5ouV00tMq7EUNx8qk5Z+qT2utIkFrLrA/OilWMDKOI2a/5rk5LcUM9JRzMhRkluvdea+4TYRsYBFCEmS0wC8AOBzAJ8C2AJgaFSbEgD3A9gD4AsA6wA0iLE/FrAICThVVVXy0ksvyS233CLPPvts4CbsZwErRWWDQWMBK2M14YJPpN9xD8vQOc9J+eoq7fGkVSxg1QXmRy/FAlZGasqKb2XgjCdk4ElPypQV32mPJ61iAYsQkiTnASgDUAjAArAEwF4ArRxtNgLYDKAhgEYAngHwWIz9sYBFMpavv/46UCORshUWsDyULrNWm4Hz8ibYj2JWuuZoqs3U+m16qfSJBazaYH7M9PzodY5kfswesYBFCEmR3QCOs//dDkAVgB6O9aX2sjYu27KARTKO119/XXr1GiwApKiosVx33fWBG5WUTbCA5aF0m7KwGTSvb9pp0LJHLGDVBvNjpudHFrCoZMUCFiEkBQYBOACgg/33dADfuLT7DkC5y3IWsEhG8d1330nTpm3ENFcK8IEAz0heXjN5+OGHdYeWtbCAlQbpNmfpNGt+GDQvb9Sd5x6kfqT8EQtYsdCXH4OWI5kfmR+zWSl85ixgEZLZ3A01SqrS/m+0trhs0xbAuwB+4lg2F8CHLm0/AjDHZTkLWCSj2LRpk9Sr106ASseri6+VcePKdYeWtbCAlQbpNmQ0aIdFg5bdSvEzZwErTdKdE5kflZgfqRQ+cxawCMlsCqDmq4qloqj2nQC8A+DqqOUcgUVCzebNmyU/v3VUAesqKSubrju0rIUFLB+l26g5TUayN7vpMmhePhbjpSlLVz9S/ijFz5kFLB+lOzd6UYRhfvSmHyn/lMLnzAIWIdlDKYAPAPzQZV07qFFczjmwetnLYs6BtWjRIlm2bJksW7ZMNm3apNsPExKTAwcOSIsWHcQ0FwnwbwF+K7m5jWTDhg26Q8sqNm3adChnLFq0KKw3IDRo6Si80KB504+UP0rxc2YBy0fpzo1eFF6YH73pR8o/pfA5s4BFSHYwFMDnABbHafMEgE0AGgNoAvUWwg0x2nIEFsk43njjDRk6dJwAkMaNW8stt9ymO6SshiOwNCnTjdqF4q1RS/Um3A9T5tZ/us0HlbiS+JxZwNIk3fnRi2vcy2KWF99/HfmROTJzlMTnzAIWIdnBFgAHAewFsM/WXgAXOdqUAFgPYA/UGwrvQ+zEwAIWyVgqKyt1h0CEBaysNWgsYOk1t5T/SuJzZgFLk3TnRy+ucRawmCMzSUl8zixgEUKSgQUsQkhKsIClSUExZyxg6TG3lP9K4nNmAUuTdOdHL65xFrCYIzNJSXzOLGARQpKBBSxCSEqwgBUg6TBnaSpgDZv9gnTst1w6D7lExp79dvrmdfHTlHlpbin/lcTnzAJWgJRp13icAtbYs/8txwz+kXTst0KGzXkp/fnR7xzJAlbmKYnPmQUsQkgysIBFCEkJFrACpEwzGDHMWfcxN4thFgmMBWKYM8S06svwU7ezgEXpVRKfMwtYAVKmXeMxCljDZr8gplUopjVTYJwthllfeoy7jQUsSq+S+JxZwCKEJAMLWISQlGABK+DKBLPhMFqTl34lplUkwFYBxNYl0rD1+JqGzIu3aSV50x0Icxs0/SAJeXn8RB630mDWWMDKAAU9P0Z9v0tajBLgckd+3CxWpESmLPsmfPkxLDkymfyYrhwZoPzIAhYhJBlYwCKEpAQLWAFXJpgNh+kac9YbAiNXgCqHQXtRcvJasoAVZAXFnAXMoLGAlQEKen6M+n5HcpsI8LIjP1YKYMrYc94OX34MS45kActVLGARQpKBBSxCSEqwgJVBygDjMWXFd2LlNhbgMYdBWyJNOkxLj5nQbdB0Gyud/eilUYtTwJq46DPpNuqn0r53hfSf/qiUr670zaCxgJVByoD8OO1CkcZtJwmw0pEffy2RvGYydeX+YFzXAekn7fKiH73sgxj5ceqy/dJ70j3Svtci6TnuVpm8eJ9v+ZEFLEJIMrCARQhJCRawMkgZYjz6lK8Xw8wX05omZmSoRHIby6gzXw+WsfCqn3SbLJ396EMBq2zhB5Jb0FZMa5QAS8W0WkurY+f5ZtBYwMogZUh+HDn/r2LlNBIrMlxMq1wMM1/6TnswONd1QPpJuzKggFW+/KA0bDVOzEhnAZaLGekjhQ1LZfKyFItYCZ4fC1iEkGRgAYsQkhIsYGWQMsh4jFnwLzl21HXSs+w2mXjB58EzFl71k26TpbMffShgdey/WgxrmuOR1A/FMAtk5Py/+mLQWMDKIGVQfpxwwafSs+xWOXbUdTJ2wVvBuq4D1E8ZnR+9/v+ES34ccMLjYlqtBfjKzo/fi2n1lR5lt/iSH1nAIoQkAwtYhJCUYAErQ5VtxiMIpixdxiQM/ZimYlbjtlMFWOt43ErEyhkkfac94ItBYwErQ8X8GIz8GLR+Cll+7DriajGtWTXyI7BS2vU6z5f8yAIWISQZWMAihKQEC1gZqmwzHkE1aLr7JSj9mCaD1nnIj8W0RgvwvW3O3hIYuTJmwZu+GDQWsDJUzI/ByI9B66eQ5cfBM38vptVEgE/s/Pi1mJEu0mvyXb7kRxawCCHJwAIWISQlWMAKgdJtQsJmJoLWN7W9gc/LPs0wwzpx8RdSUNJDzEgXMa2ZYphF0rH/at++TyxghUAZ9p1P6jutOx+ms2+YH2OqfFWVtDjmFDGtJmJap4hptZWSVqNlyorvfMmPLGARQpKBBSxCSEqwgBUCpfumW7c5C7JB8+I8adDi9s2U5d9K3/IHpOuoq2X43D/6+n1iASsEyrTvfDLfad35MJ19w/wYt2/KV1XJ4FnPSNeRV8mAEx+Tqau+9y0/soBFCEkGFrAIISnBAlaIlGk335lmytz6JF2mzEuD5nchMAjG3iNzygJWyBTUfBDk61lHDvAzP/r9/5wQ5UcWsAghycACFiEkJVjACpHCcsMddHPm7JNkz5EFrIwwaCxghUxBzQdBvp515AAWsDIiP7KARQhJBhawCCEpwQJWiBSWG+6gmzNnnyR7jlEGbeqyA9Jv2q+ly7DLZfDMZ6R8RRULWAEwaCxghUxBzQdBvp515ICo/Fi+okqGnvKcdBl+hfSZer9MWfotC1gByI8sYBFCkoEFLEJISrCAFSJl8s13Jpgyt35I9nwdBm3ykq+luNkQMSNHiWHNEdNqIq26niblq6pUGw3GJDD9pNmgsYAVMjE/+nvde1TAal9aIYZZIqY1W8xIFyls2EsmLdnjTX7UmSMzPD+ygEUISQYWsAghKcECVoiUCcYkbAYt2fN1GLSe424VM1IqwLf2q9A/EsMskaGzn2MBS7NBYwErZGJ+9Pe696CANWrea2IY9QR4z86PB8S0hkrXEVexgKU5P7KARQhJBhawCCEpwQJWSOW3SUlVug2XRuPRutuZAlxsmzMlMzJduo9dk9nmLNZ3xU9TluJ3jAWskIr5MWOu916T7xIrZ3SN/Aj8VJp1nKG1eBPU/ko6RyYRNwtYhJBkYAGLEJISLGCFVDRo/py7Bwai25gbxLQGCXDQNmd7xLSayuBZm8NhznQaNBawYsH8yPyYEdf7iNNeEcMsEuATOz9WimmVyTFDLmEBiwUsQkgGwgIWISQlWMDKAum+OQ+zPDAek5Z+KQUl3cWM9BVgiZiRo6RJ+6lSvrpSmzEJep/5de4sYGWBdF8PYVeK13r56ipp0Xm2mFYbARaLGRki+fU7yoQLPvEmRwQtR/qZH1M8dxawCCHJwAIWISQlWMDKAum+IQ+zPDIbk5fulZ5lt0qHfoul77QHZOrKA4Ep4gS1z1jASgnmR+ZHf6/3FK7n8lUHpd/xj0iHfoul+7ifyaQluwNTxElbf7GARQgJKSxgEUJSggWsLJDuG/IwS+ejHyxgsYCVPMyPzI/+Xu+68yELWCxgEUICAQtYhJCUYAEry6T75jxsCnIBS3ff1LX/kunHNM8ZxAJWlkn39RBGMT+m3ncBzY8sYBFCkoEFLEJISrCAlWXSfUMeNrGA5V3/BdCgsYCVZdJ9PYRRzI+p911A8yMLWISQZGABixCSEixgZal035j7JT/POQjFrKA+FpNsP9amNMfCAlYWS/d14IeYHzNPAcqPLGARQpKBBSxCSEqwgJWl0n0T7pdo0DJPATJoLGBlsXRfB36I+THzFKD8yAIWISQZWMAihKQEC1iU9htyLxS08/XTrIXBlAVULGBRur+DnilI58v8GAqxgEUISQYWsAghKcECFqX7JtgTBe18adBCIRawKN3fQc8UpPNlfgyFWMAihCQDC1iEkJRgAYvSfRPsiYJ2vjRooRALWJTu76BnCtL5Mj+GQixgEUKSgQUsQkhKsIBFZZxZy7TzTYdRoynz5Tu25CbmR8oh3d/LOnx3M+Z801XMYn5M+3ds0qrQ5kdCiIPpAF4D8IWtVwHMiGpTAuB+AHvsNusANIixPxawCCEpwQIWRYOWZrGAlXmyvx8sYFHMj2kWC1iZJ/v7wQIWIdlBS1vVjADwDYCejmUbAWwG0BBAIwDPAHgsxv5YwCKEpAQLWFQgTEycm+TQnGdd3h6l+e1SWSmX7wQLWFQgckcdvrMZfY7MkcFW1HeCBSxCsg8DwHCoAtaJ9rJ2AKoA9HC0K7WXtXHZR8YWsDZt2qQ7hDqTiTGLZGbcmRizSGbGzQIWFQjjksDNcsafJ81ZsOXynWABiwpE7qjDdzajz5E5MtiK+k6wgEVI9lAMYDeA/VCFqWcB5NnrpkMVtKL5DkB5jH1lZAFr2bJlukOoM5kYs0hmxp2JMYtkZtwsYFHajI3uuL0+n7ApW/osznmxgEVpyym6Y/b6fMKmbOmvOOfFAhYhmc3dUMWoSvu/0drisk0ugBMAXAg1GgsA5gL40KXtRwDmuCxnActHMjFmkcyMOxNjFsnMuFnAorSZGd1xe30+YVO29Fmc82IBi9KWU3TH7PX5hE3Z0l9xzosFLEIymwKo+apiqSjOthsBLLL/ndQIrJ07d8qXX36ZUVq0aJH2GLIh5kyNOxNjztS4d+7cGdYbkGIAsuSGnbL6ti+pdOqWJKU7bq/PJ2zKlj6Lc17X3sv8SHmgMOXHZM8nbMqW/opzXktuCG1+JITUwmYAN9v/bgc1iss5B1Yve5nbHFitoRIHRVFUqmqNcMH8SFGUV2J+pCiKclfY8iMhxMFpAI4BYALIB7AQwPcAJjnaPAFgE4DGAJpAvYVwQ4z9GVBJo5iiKCoFtcbhR5nDAvMjRVFeiPmRoijKXWHMj4QQBz8G8A6AfQA+BfAigJOi2pQAWA9gD9Rk7/dBJQhCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEZBVLAFQBuCxqeQmA+6EeRfwCwDoADfwN7QimA3gNKp4vALwKYEZUm6DFfRqAFwB8DvXY5xYAQ6PaBC1mACgF8BSAD6G+H2Nd2gQxbgD4CYBdUI/abgPQXWs0R3IygOcAfAn1ggUzan0pgGcBfAXgvwAu9TU6d64G8DeomHcBeABHvhgiiHETQgghhBBCCAkBXQC8DeCvOLKAtRHqDYcNATSCmgz+MV+jO5KWtqoZAeAbAD0dy4IW93kAygAUArCgCoZ7AbRytAlazADQFcBZAPpCFVncClhBjHsVgP8A6AYgD8BVUMWUAp1BRVEGVcSajyMLWPUBfADgCgC5UG8U3Qn1vdHJlQD6AIhAzal3P4C/ONYHNW5CCCGEEEIIIRmOCWA71KimrahZwGoHNeqmh2NZqb0setSFLgwAw6EKWCfayzIhbkBNrn+c/e9MiNltBFZQ434HQIXjbwvAxwBO1RNOXEbhyALWPAAfRS1bDOAtH+NKhF5QsVePuMuUuAkhhBBCCCGEZBgXQz3yBRxZwJoOVRiK5jsA5WmOqzaKoQpA+6GKJc9CjbQBgh13NYMAHADQwf47E2J2K2AFMe5iqFgHRS1/GsD1/odTK24FrBsB/C6q3RC7XX2f4krV0pvJAAAgAElEQVSE1VDFwmoyJW5CCCGEEEIIIQHgbigDX2n/N1pb7Ha9AbwHNYcRcGQBay7U3EfRfARgjtdBI/G4neQCOAHAhVCjsQB/404m5rYA3oWao6maTOhrtwKW33EnQhuoWLtELX8IwC/8D6dW3ApYdwJ4MKpdV7tdKwSD8VDzi5U5lmVC3IQQQgghhBBCAkIB1FxEsVQENYfNawCOd2ynewRWInHHYiOARfa//Yy7rjF3ghqxcnXU8kzoa47ASg+ZOAKrHGoE5PSo5UGPmxBCCCGEEEJIhtEeylR+AvVWvE+hHmn7GsDrdpt2dhvn/EbVc94EZV6majYDuNn+d1DjLoWa4PqHLuuCGrOTWHNgBTFutzmwPkHmzIF1Oo6cS2oJgjGX1KlQxavxLuuCHDchhBBCCCGEkAzEgHqkx6mXAKwB0NzR7gkAmwA0BtAE6g1zG3yN9EhOA3AMlEnOB7AQwPcAJjnaBC3uoQA+h5rQOhZBi7maPKh+rgIw0f7bcqwPYtwroR6P7Q6gHtSIt50I1lsITai+nABVwCqw/zagRivtAnA5VN/3BPA+9L/NrwLAFwCGxVgf1LgJIYQQQgghhISILaj5CCGg5sdaD2AP1KiL+6Ae0dLJj6FG2OyDGjn2IoCTotoELe4tAA4C2AsV9z773xc52gQtZkCN1KueK8upSxxtghg3oL4nHwL4CsA2qGJWkJiHmn1b/e+R9voeAJ6DGhX5AYAfaYgxmiqoFyfsxeHv8l7ULGgFMW5CCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEK8YAiAXwHYBWA/gM8AbAZwGgBTY1xBZAmAE1yWXwqg0udYkmUrgC2Ov3tBxV/i0rYKwGVJHmcegPkxllcB6Jjkfr1kFFQsYz3e38gE2lYBuCSBdiUA7gTwKYCvADwDoEeyAZJDMO8lDvNe4jDvxSfRvBeLblDX6T6oa/YuAA3rsO1voK75rwD8HcAKAFYK8RBCCCGEEB9ZCmVANgM4FcBwANMArIW6wZumL7RA8i6A+1yWtwIw0OdYkqWrrWriGatUjNxWAM+5LJ8H9Z0LipGrhLdGrhLeGrkXALwPYBaACQC2QRWzWiUXIgHzXl1h3ksc5r34pFLAagngE6gcWAaVE9+HypGJbvtnADMAjAZwOVTcVycZDyGEEEII8ZGRUDdva2Ks74D4Iz1yvQ4oA4hl5DKZMxDbWAXNyEWSjCUW6RiJ4KWRO85lf8UAPgfws2QCJMx7ScC8lzjMe/FJpYC1BsAXAIocy0bY+zy+lm3PgYqxU9TyB6FGZBFCCCGEkICzEeoXyUQMWfWv1SMAPAxgN9QvmdXMBfBXAN9CjQ65D0CLqH3MsbfZB+BLAH8DsMCxfgDUiIjPAHwD4G0AtyQQWyLbdQBwP9T5fgfgL3C/4e0FYINjX28AuNBe9y7UDXCVQ3fZ635s/+2kyI5jl33MN6BGfjipNhLVoz8+tbUOqlARj5sBvBW17E84clTBlQA+cvy9DYcfpan+XJ3nVQmgnb2+2shdAOAdAHvt7bvVEttWl/06j1kJYBCA9VDfhV0AbkLN72J7e7vzAFxrtzkIoIG9vgNq/0yPgfo8P4b6bv4H6rGx6kfEqo1XIv2f6OcZbeRMAFcA+ADA13Y/dENiRu5OADtdlt8D9X0kdYd570iY95j3gpT3YvFvO8Zo3gNwdy3bLrJjbBq1/HYAHyYZDyGEEEII8QkT6qZyfYLtq2/4/wPgGqhfbifY686x190PYBKAM6FunN8AUGC3GQ5183iDve14ABUAVtnrC6FGlWwEMAXqRvh0qJvLeCSyXRuom/2/AZgN9ejBnXY85Y52A6H65K9QjxWNhjKaa+31vaFuxp+CMo8DARxlr4ueC8YA8DyUaV1qn+8au5+ucLSrNnJvQxmZ8VA32t+g9hvyE+xjtrH/LoEyOl8BONvR7iWoX5mrcc4F0wTKqFXa+xtoK8deXwVlYH8H1VcnQhm6fyH+PEFdoUzlX3C4r6of36n+Lr0JZYDHAvgfO/ZLHfuoNnI7oeYtmQJluPKQ+Gf6FoDtUAZvBIBToIoM1SMaEu3/unye0Uau+jGVa+3tLoIyYpWo3cj9Earvo1llb1/gso7EhnmPeQ9g3gt63nMj3972Qpd1GwG8XMv2zaCuz4ehioBFUJ/9Pqh5sAghhBBCSIBpBnUTemWC7atvvq+PWm5C/cr9+6jlw+z2FfbfK6B+3Y9FP6ib07pOTp3Idr+EunGNnqx3M2qOpngOyqjmxdlXrEdpoo1cOdT5nxbV7g6oX8Qb2X9XG4m7otqthTIT8WhoH7P6GMdBmdo7oEw1oIzuASizXU30ZMbxHm2pNlzOSW5n2O0H1xJfvEdp3H6FfwLK/FdTbeR2uOwjkc+0sb19OWKTaP/X5fN0GrkSKIN0a9R2q5HYSIQ3ATzgsvws+zita9me1IR5j3mvGua94OY9N1ra257jsm4djhyV58bRUBO3V4+OOwjg4iRiIYQQQgghPpOMkauEGlHg5Fh7P2e6bPMugF/b/x5pb78OwFQcfhyimup5fV6CGgXQBkdiRSnR7f4L9auyc9sIgJV2TPUB1IO6ma2tPxI1ctcC+B5Hzl1SfaM/1fF3FYCTotpVz9fRrJZ4/ozDv5jfBPWL/SlQIyYA9et9JdQjJdXU1chFP5bU2V4+q5bYapsLpn/U8qtQ0zxVGzk3g5HIZwqoX/z/DjUyI3ruEyDx/q/L5+k0ciPsv0dHbdcOLGDpgHmPea8a5r3g5j2373yqBawmUCPXqkemjYQaCbcfh0dEEkIIIYSQgGKh7o/SVEL9gumkesTBZJdt/gjgD46/T4S6ud8P9ev4MwB6OtaXQhm/PfY+X7e3AQ7f1Fc6/tsuge1gHyt6DhfnL7Dtod6mVQXg/Dh9ACRu5O6A+qU8mi6o+Yt2rMl0q/u7HeJzA9T8H4C6Ob8AQHN7264ArsORcyjV1chFT2Zc/VmcXktsdZ3MOLoPq49zlss+EvlMAfWoyD1Qj91UPzKz0LGfRPu/Lp+n08jNsv8+Nmq7PCRm5LaDjxB6CfMe8170sZj3joxRZ96L9Z2vh9QeIfwp1LUSPcfXFVBzezU6YgtCCCGEEBIoNkLdnObU1hCxb76rRyLMd9nGORLBSQHUL+R/h/pFORoTau6QDVC//nazY+wbpehfhZ3bHcThCXc/hJrAto/LPvra+/ZzJEIVjhyJkKyRK7fbDbH/W33Of4ea0+RVl3gzzci5jXJJ5DONphTAL+x9TrSXJdr/dfk8o0ciVCH5kQi/hHpNfDR3g5O4JwvzHvOe81jMe0fGqDPvxfvOvw337+G7qH3utN9BzU8WzXQ79oG1bE8IIYQQQjQzAsq8/CzG+g44PFIg1s23CXVT/XTU8qGo/Zf9C+x9No6xvqe9jxlx9pHIdncD+Cfiz/ECqLdM1TYXzBtwN6fRJmSKHcPsqHax5g5J1sgVQRmMZ1DzjVtroUaBfI8jTXa0kTvFPlZ3l/2nYuQ2wX0eFy+MXKKfaTRF9j6rJ+1NtP/r+nlWG7kGUHPB3Ba13YVIrIB1nL2/EY5lxVDzKsW6bkl8mPdqsg3Me9Ew7yl05b1YrIF6dLbIsWy4vU+3t2s6uRtqBFb0Y7xXgY9jE0IIIYRkDEugzNxmqNe9D4d649FNUG91mma3i/dr9QIcnudlItSjDx9C3WjXs9v8BOoNWSdDGcg5UHNWvGqvnwrgt1CmYzTUL+yboW44W8WJP5Ht2kLNjfIKlPkYCVUY+B+oNzhV098+578AmGvv70yo17ZX8xsowzQVaiLl6kc2ok2IAfUr/JdQfVz99qZKqLczVZPqSARAPTpRBeAhx7ITcfjxi/ZR7aONXKnd9n+hJijuh8O/eKdi5G6EMjmz7H12tpd7YeQS+Ux7Qp3nuQDGQb097kGoR7n62G0S7f+6fp4jHcsug7rGrrO3+wESfxuXAeBFqALDyVDX1zaoAhYNV/Iw7x2GeY95r5qg5L1YtIJ6LHIb1DV3MtSjpC9GtRsJVcSc61g2CKoPXgEwE+rcL7eXuRVnCSGEEEJIQBkM9VjCLqibuc+gfkV2/uoaz8gBypj9BerG/VOo+TeaO9ZPgRrCv8tu8x+oxxpa2Os7Q91kvw01oe3HAJ6EehV5PBLdrpV9vJ1Q813sgho9MSeqXS8oY/gF1Fw5/0DNCV67AHgWyvBV4vBbnC6Full3Uh/KBO6yj/kGgMVRbVIdiQAA19htFziWNbTjedul/VbUnKMHAH4E1TffRx23EsqEO2lvL6/NyDWH+iy+tNtXm8d4Rs7Zh9XHcTNyQO2faVOoX93fgPq8PoM69/GOfdSl/+vyeTqNnAll5j6A+k79AWqenkqofq+NEihz+pl9HptR97fWkSNh3jsM8x7znjPGIOS9WHSHOt99UKOxfgn1ubvFE/1ZDYT6bHbZ278OVVir64g2QgghhJBQcjIO/3pZCXVDF49tUEZqL9TN1V7UnHiVEELCAvMjIYQQQgghhASEMiiTNh+JGbStOPJXX0IICSPMj4QQQgghhBASMKqHsydi0KLn3SCEkDDD/EgIIYQQQgghAaEuBu1TqHkd/gHgagCF6Q2NEEK0wvxICCGEEEIIIQEhUYM2GGrCZkC9SejPUBP1umFAvYWsmKIoKgW1hsonumB+pCgqqNKdHwkhhBBCfCdRgxbNSAAH4P6GnNYAhKIoygO1hj5GgfmRoqjgSmd+JIQQQgjxnVFIzaDlu6wrBiAbN+6Ubdu+pKhD+nLbtsBKd99QNbVx485qg1acUoZLDeZHKiXpzmvMpeFUQPIjIYQQQohvmFCjAyZAGbQC+2+34ejNAEy02wBAdwA7APw6xr6LAci2bV/Kq68KRR2S9gDiKAAhUA5t2/alToPG/Eh5Iu0BaFAAQgi9NOdHQgghhBDfmQegCsqcVTr+PRJAWwD7AAyz27YD8DKA3QD2AvgX4k9STINGuUp7AHEUgBAohzQbNOZHyhNpD0CDAhBC6MUCFiGEEEKId9CgUa7SHkAcBSAEyqEQGzTmxyyS9gA0KAAhhF4hzo+EEEIIIb5Dg0a5SnsAcRSAECiHQmzQmB+zSNoD0KAAhBB6hTg/EkIIIYT4Dg0a5SrtAcRRAEKgHAqxQWN+zCJpD0CDAhBC6BXi/EgIIYQQ4js0aJSrtAcQRwEIgXIoxAaN+TGLpD0ADQpACKFXiPMjIYQQQojv0KBRrtIeQBwFIATKoRAbNObHLJL2ADQoACGEXiHOj4QQQgghvkODRrlKewBxFIAQKIdCbNCYH7NI2gPQoACEEHqFOD8SQgghhPgODRrlKu0BxFEAQqAcCrFBY37MImkPQIMCEELoFeL8SAghhBDiOzRolKu0BxBHAQiBcijEBo35MYukPQANCkAIoVeI8yMhhBBCiO/QoFGu0h5AHAUgBMqhEBs05scskvYANCgAIYReIc6PhBBCCCG+Q4NGuUp7AHEUgBAoh0Js0Jgfs0jaA9CgAIQQeoU4PxJCCCGE+A4NGuUq7QHEUQBCoBwKsUFjfswiaQ9AgwIQQugV4vxICCGEEOI7NGiUq7QHEEcBCIFyKMQGjfkxi6Q9AA0KQAihV4jzIyGEEEKI79CgUa7SHkAcBSAEyqEQGzTmxyyS9gA0KAAhhF4hzo+EEEIIIb5Dg0a5SnsAcRSAECiHQmzQmB+zSNoD0KAAhBB6hTg/EkIIIYT4Dg0a5SrtAcRRAEKgHAqxQWN+zCJpD0CDAhBC6BXi/EgIIYQQ4js0aJSrtAcQRwEIgXIoxAaN+TGLpD0ADQpACKFXiPMjIYQQQojv0KBRrtIeQBwFIATKoRAbNObHLJL2ADQoACGEXiHOj4QQQgghvkODRrlKewBxFIAQKIdCbNCYH7NI2gPQoACEEHqFOD8SQgghhPgODRrlKu0BxFEAQqAcCrFBY37MImkPQIMCEELoFeL8SAghhBDiOzRolKu0BxBHAQiBcijEBo35MYukPQANCkAIoVeI8yMhhBBCiO/QoFGu0h5AHAUgBMqhEBs05scskvYANCgAIYReIc6PhBBCCCG+Q4NGuUp7AHEUgBAoh0Js0Jgfs0jaA9CgAIQQeoU4PxJCCCGE+A4NGuUq7QHEUQBCoBwKsUFjfswiaQ9AgwIQQugV4vxICCGEEOI7NGiUq7QHEEcBCIFyKMQGjfkxi6Q9AA0KQAihV4jzIyGEEEKI79CgUa7SHkAcBSAEyqEQGzTmxyyS9gA0KAAhhF4hzo+EEEIIIb5Dg0a5SnsAcRSAECiHQmzQmB+zSNoD0KAAhBB6hTg/EkIIIYT4Dg0a5SrtAcRRAEKgHAqxQWN+zCJpD0CDAhBC6BXi/EgIIYQQ4js0aJSrtAcQRwEIgXIoxAaN+TGLpD0ADQpACKFXiPMjIYQQQojv0KBRrtIeQBwFIATKoRAbNObHLJL2ADQoACGEXiHOj4QQQgghvkODRrlKewBxFIAQKIdCbNCYH7NI2gPQoACEEHqFOD8SQgghhLhyMoDnAHwJoBKAWUv7EgD3A9gD4AsA6wA0iNGWBo1ylfYA4igAIVAOaTZozI+UJ9IegAYFIITQiwUsQgghhGQbZVAmbT4SM2gbAWwG0BBAIwDPAHgsRlsaNMpV2gOIowCEQDmk2aAxP1KeSHsAGhSAEEIvFrAIIYQQkq2MQu0GrR2AKgA9HMtK7WVtXNrToFGu0h5AHAUgBMqhgBg05kcqJWkPQIMCEELoFZD8SAghhBDiO4kYtOkAvnFZ/h2AcpflNGiUq7QHEEcBCIFyKCAGjfmRSknaA9CgAIQQegUkPxJCCCGE+E4iBm0ugA9dln8EYI7Lcho0ylXaA4ijAIRAORQQg8b8SKUk7QFoUABCCL0Ckh8JIYQQQnwnbSMMZs5cJHPmLJM5c5bJ2rWbtN/wUfqlPYA4CkAIWa+1azcdyhkzZy4KgkFjfqRSkvYANCgAIYRSAcyPhBBCCCG+k+gcL5WoOcdLL3sZ53ihEpb2AOIoACFQDgVkhAHzI5WStAegQQEIIfQKSH4khBBCCPENE0AegAlQRqvA/tuI0f4JAJsANAbQBOotWxtitKVBo1ylPYA4CkAIlEOaDRrzI+WJtAegQQEIIfRiAYsQQggh2cY8qLdkVdqq/vdIAG0B7AMwzNG+BMB6AHsA7AZwH2LfONGgUa7SHkAcBSAEyiHNBo35kfJE2gPQoACEEHqxgEUIIYQQ4h00aJSrtAcQRwEIgXIoxAaN+TGLpD0ADQpACKFXiPMjIYQQQojv0KBRrvJiJ9+99JJsvuUWefS662TdZZfJ+08+6cl+dfcNVVMhNmjMj1kkvw9YtWOHvPjLX8pj118v919xhey47z7fY9Dd59mgEOdHQgghhBDfoUGjXJXqDqp27JBZZWXSskkT6d+tm/Tu3Fk6tm4tn//hDynvW3ffUDUVYoPG/JhF8vuAN69cKcWFhdKnSxcZ1quXFNarJ6+uW+drDLr7PBsU4vxICCGEEOI7NGiUq1Ldwa0XXiitmjaVjzdvFnn1Val85RWZNmKETBwyRA6+/HJK+9bdN1RNhdigMT9mkfw82Cv33isF+fnywp13Hlp2TUWFtGvRQj555hnf4tDd59mgEOdHQgghhBDfoUGjXJXKxq+uWycF+fny7C9+UWP5nm3bpEv79vKD+fNT238A+oc6rBAbNObHLJJfB/piyxbp0KqVXLd4cY3l1aNWR/frJ99v3+5LLLr7PBsU4vxICCGEEOI7NGiUq5Ld8Kvnn5eOrVvL1RUVruv/+cgjUlxYKNt+/vOkj6G7b6iaCrFBY37MIvl1oJPGjZPyESOk8pVXjlj31fPPS89OneTK88/3JRbdfZ4NCnF+JIQQQgjxHRo0ylXJbnjXJZdIz06dXM1ZtS6cN09mjh+f9DF09w1VUyE2aMyPWSQ/DvLmo49KXm7uoUer3fTEmjXSpnlzX0Zh6e7zbFCI8yMhhBBCiO/QoFGuSnbDoaWlsnbVqrht3tqwQXJzcuSjp59O6hi6+4aqqRAbNObHLJIfB7lw3jw5uawsbpvvt2+XNs2byxNr1qQ9Ht19ng0KcX4khBBCCPEdGjTKVcls9H8PPyx5ubnyxZYttbYdN3CgXBPjMcPapLtvqJoKsUFjfswipfsAB7Zvl+aNG8vmW26pte2lCxZI+YgRaY9Jd59ng0KcHwkhhBBCfIcGjXJVMhstP/VUmTNpUkJtH77mGjm6TZu4jxrGku6+oWoqxAaN+TGLlO4DbLj+emnfsmVCOe/9J5+UnEhE3n/yybTGpLvPs0Ehzo+EEEIIIb5Dg0a5qq4bfPfSS9KkpES23H57Qu33//GP0rRhQ/n9bbfV+Vi6+4aqqRAbNObHLFK6DzB1+HC5bOHChNuXjxghPz7nnLTGpLvPs0Ehzo+EEEIIIb5Dg0a5qq4bJDOiavXppyc1mbvuvqFqKsQGjfkxi5TOne/cuLHOI6oev/HGtE/mrrvPs0Ehzo+EEEIIIb5Dg0a5qq4bTBwyRK5atKhO27y1YYPkRCKye+vWOm2nu2+omgqxQWN+zCKlc+eXL1woU4YNq9M232/fLq2aNpVNa9emLS7dfZ4NCnF+JIQQQgjxHRo0ylV1afzltm1iWZa8+/jjdT5Qt44d5dHrrqvTNrr7hqqpEBs05scsUjp33u/YY2XdZZfVebtzTjhBls6enba4dPd5NijE+ZEQQgghxHdo0ChX1aXxb2+4QY5p1y6pAy2dPVvOPfHEOm2ju2+omgqxQWN+zCKla8ef/f73YpqmfPT003Xe9pFrr5XuHTumLTbdfZ4NCnF+JIQQQgjxHRo0ylV1aVwxa5acP3NmUgd66qabpGPr1nXaRnffUDUVYoPG/JhFSteOf3X11VJ6zDFJbfvFli1iWZb896mn0hKb7j7PBoU4PxJCCCGE+A4NGuWqujTu0r69bLj++qQO9NXzz0tuTo78+7HHEt5Gd99QNRVig8b8mEVK147POu44WTF3btLbD+rRQ+6+9NK0xKa7z7NBIc6PhBBCCCG+Q4NGuSrRhu8/+aRYliV7tm1L+mBj+veX2y66KOH2uvuGqqkQGzTmxyxSOnZatWOHtGvRIqWJ2H909tkye+LEtMSnu8+zQSHOj4QQQgghvkODRrkq0Ya//NGPZGhpaUoHu7qiQo4fPTrh9rr7hqqpEBs05scsUjp2+uajj0pebq58/cILSe/j+TvvlCYlJVL5yiuex6e7z7NBIc6PhBBCCCG+Q4NGuSrRhqdMmCCXLliQ0sH+tH69FBcWyoHt2xNqr7tvqJoKsUFjfswipWOnt6xeLeMGDkxpHwe2b5eiwkL50/r1nsenu8+zQSHOj4QQQgghvkODRrkqkUaVr7wiTUpK5IU770zpYHXdj+6+oWoqxAaN+TGLlI6dHjdqlFxTURGY/URLd59ng0KcHwkhhBBCfIcGjXJVIo3+tH69FNVh5FQ8zZ44US5JcCSX7r6hairEBo35MYvk9Q4PbN8uxR6NnLr1wgtl7IABnseou8+zQSHOj4QQQgghvkODRrkqkUbXVFTI9JEjPTngXZdcIkMSnEtLd99QNRVig8b8mEXyeocveDh31b9+8xvJzcmRb1KYS8tNuvs8GxTi/EgIIYQQ4js0aJSrEmk0eehQ+dmKFZ4csNqgfffSS7W21d03VE2F2KAxP2aRvN7hleefLyeNG+fJvqp27JBmjRql/Lh2tHT3eTYoxPmREEIIIcR3aNAoV9XWoGrHDmncoIFsv+ceTw5YtWOHNCwullfuvbfWtrr7hqqpEBs05scsktc7nD5ypFy/dKln+ysfMUJuXLbM0xh193k2KMT5kRBCCCHEd2jQKFfV1uDfjz0mOZGIfPvii54ddOKQIbJ21apa2+nuG6qmQmzQmB+zSF7urGrHDmneuLE8d8cdnu3z8oUL5eSyMk/j1N3n2aAQ50dCCCGEZBAGgJa6g/AAGjTKVbU1uP+KK2RAt26eHvSSBQtk7uTJtbbT3TdUTbkYNOZHKuPk5c7ef/JJsSxLvnr+ec/2ufmWW6RDq1aexqm7z7NBLGARQgghRCcFAH4O4DsAX9vLjgPwP9oiSg0aNMpVtTVYMnu2LJo509ODPvmzn0nndu1qbae7b6iachi05mB+pDJUXu7s19dcI706d/Z0n7u3bhUA8vHmzZ7tU3efZ4NYwCKEEEKITm4FsBnAMAB77GVtAfxdW0SpQYNGuaq2BoN79pT7fvITTw/6yTPPCAD5YsuWuO109w1VUw6D9gswP1IZKi93tuq00+ScE07wPMgu7dvLE2vWeLY/3X2eDWIBixBCCCE62Qmgkf3vLxzLd6f5uD8BsAvAPgDbAHSP03YbgP0A9trt9wJYGKMtDRrlqngr9//xj5KXmytvPPKI5wfu2Lq1bFq7Nm4b3X1D1ZTDoP0XevIjkJ4cyfyYRfJyZyP79pU7L77Y8yBPnzpVLj7rLM/2p7vPs0EsYBFCCCFEJx8BiNj/rjZo9QB8kMZjrgLwHwDdAOQBuArKKBbEaL8VyswlAg0a5ap4K3fcd5+UFBVJ5SuveH7g2RMnymULF8Zto7tvqJpyGLSP4X9+BNKXI5kfs0he7ej77dulID9fXn/oIc+DvPXCC6Vs0CDP9qe7z7NBLGARQgghRCdPAFhs/7vaoJ0H4DdpPOY7ACocf1tQRvHUGO23ArgswX3ToFGuirfSaxPl1Jrly2Xq8OFx2yCYYWcAACAASURBVOjuG6qmHAbtd/A/PwLpy5HMj1kkr3b02oMPSv2CAjn48sueB7njvvukQf36nv14oLvPs0EsYBFCCCFEJ10BfALgRahHUH4P4HMAndN0vGIAVQAGRS1/GsD1MbbZCuBTO65/ALgaQGGc/dOgUUco3kqvH2Nx6qW77pImJSVStWNHzDa6+4aqKYdB6wd/82N1DktXjmR+zCJ5taM7Lr5YRvfrl5YgvX58W3efZ4NYwCKEEEKIbhoDWAbgNgCXQE1SnC7aQJmzLlHLH4KaMNmNwQBK7H/3BPBnAA/GaEuDRrkq3squHTrI4zfemJYDf/vii5ITicg7v/1tzDa6+4aqqSiD5md+BNKbI5kfs0he7WjBCSfI6tNPT1ugQ0pL5d4f/9iTfenu82wQC1iEEEIIySaSGV0QzUgAB6DmhnHbPw0adYRirdi9dasYhiEfPf102g7ev1s3efDKK2Ou1903VE1pNmjpzJHMj1kkr3ZUeswx8si116Yt0KWzZ8v5M2d6si/dfZ4NYgGLEEIIITo5M47Shdv8Lp8g9vwu0VSbs3yXdcUAZObMRTJnzjKZM2eZrF27SfsNH6VfsVY8c+ut0r5ly7Qe/PyZM2XZnDkx1+vuG0pk7dpNh3LGzJmLqg3a+fA/PwLpy5HMj1kkL3by1fPPi2masnPjxrQF+sAVV0j/bt082ZfuPg+rYuRHFrAIIYQQ4jvvRulrqLle3knjMVcCeA/qtfD1oOZr2Qn3N2w1AzDRsa47gB0Afh1j3xxhQLkq1oqrKypkxtixaT34HRdfLGMHDIi5XnffUDXlGGHwHvzPj0D6ciTzYxbJi528cOed0rxx47hz+KWqfz7yiOTn5cn327envC/dfZ4N4ggsQgghhASJCICfAjgnzcf5MYAPAXwFYBuU6QLU/DL7AAyz/24H4GUAuwHsBfAvcBJ3KgnFWnHKhAly+cKFaT34y/fcI40bNIhpAnX3DVVTcQyaX/kRSE+OZH7MInmxk1svvFAmDhmS1kC/375d8vPy5B+//nXK+9Ld59kgFrAIIYQQEjTqQf36n4nQoFGuirWiW8eO8tsbbkjrwb9+4QUxTVP++9RTrut19w1VU7UYNOZHKiPkxU7OPfFEWXXaaWkPtn+3bvLQVVelvB/dfZ4NYgGLEEIIIUGjJYA9uoNIEho0ylVuC7998UWxLEvee+KJtAfQpX17eeqmm1zX6e4bqqZqMWjMj1RGyIudDO7ZU9Zffnnagz3ruOPkB/Pnp7wf3X2eDWIBixBCCCE6uSxKNwB4C+qV7ZkIDRrlKreFf1q/XhrUr5/W+V2qNXP8eLm6osJ1ne6+oWrKYdCuAfMjlaFKdQeVr7wihfXqyesPPZT2YG9auVKmDBuW8n5093k2iAUsQgghhOhka5QeB3AJgCKdQaUADRrlKreFd11yiYzo08eXAK447zw5ZcIE13W6+4aqKYdBew7Mj1SGKtUdvLVhg+Tm5MgBDyZXr03bfv5zadO8ecr70d3n2SAWsAghhBBCvIMGjXKV28Kls2dLxaxZvgTwxJo10q1jR9d1uvuGqqkQGzTmxyxSqjt45NprpXfnzr4E+8WWLQJAPv/DH1Laj+4+zwaFOD8SQgghhPgODRrlKreFY/r3lzsuvtiXAN5/8kmxLEu+ffHFI9bp7huqpkJs0Jgfs0ip7uCSBQtkXnm5bwG3a9FCttx+e0r70N3n2aAQ50dCCCGEBJSdAN5PQJkIDRrlqugFVTt2SOMGDeTle+7xJYCqHTukpKhIXl237oh1uvuGOqzmzdtIs2Ztqg1avFyZiTA/ZpFS3cFxo0bJ/7N33lFRXV0fPrZUY+8lisZoFAuIWEHsvXelCkgVBBQRBUUQqTKAiCBFBEE6KCD2BoJiYjdWxIYdjYVoLM/3B8onEZO8mjAx3met38rMXXPu3evMcYe9Z599vOfMqTCDR6qpIbOx+aB7yHvOPwVJCSwJCQkJCQmJikbnL+pjRArQJJWr31+4mpFB5cqVeZyVVWFG9FVWJtTB4a3r8p4bSf+vJUvWYmcX+DpAMxKSf5T0kepDb9CySRO2r1pVYQYvnDkTvVGjPuge8p7zT0FSAktCQkJCQkJC4u9DCtAklavfX8jw9aVtixYVaoTF1KlYTpv21nV5z42ksvoPB2iSf/yE9CGD7+/ejRCCW9u2VZjBcW5uKLdr90H3kPecfwr6D/tHCQkJCQkJiY+Ir4UQCkKIVm/oY0QK0CSVq99fWG5uzqSBAyvUiJBFi9Do2vWt6/KeG0llVU6AJvlHSR+dPmTwvpAQGterV6EGn05I4PPPPuPZB5x6KO85/xQkJbAkJCQkJCQk5ElLIcR+IcSLcvQxIgVoksrV7y9MHTwYFxOTCjUib906ateowcu8vDLX5T03ksrqjQBNUUj+UdJHqg8ZHDB/PkN79apQg58fOMCXn3/Oybi4976HvOf8U5CUwJKQkJCQkJCQJ6mvpCSE+EUI0UUIkSaE0JanUR+AFKBJKle/v9C+VSs2+fhUqBHFWVlUrlyZK+npZa7Le24kldUbAVq6kPyjpI9UHzJ41rhxzNfRqXCjVTt0IGbZsvceL+85/xQkJbAkJCQkJCQk5MktIUSdV6/vv/pvEyHEYfmY88FIAZqkcvXmm1+zs6lSpQqX0tIq3JB2LVuSJpOVuSbvuZFUVm8EaLeF5B8lfaT6kMHdFRVZ7+JS4UYbjB2Lna7ue4+X95x/CpISWBISEhISEhLypOiN14VCiK9evX4gB1v+DqQATVK5evPNj1FR1Prmm7e28lWEJg4YgPvs2WWuyXtuJJXVGwGa5B8lfbR634EvDh7k6y+/5PiGDRVutMzGhlFqau89Xt5z/ilISmBJSEhISEhIyJNDQoiOr15vF0JYCyFmCiEuys2iD0MK0CSVqzffRC5dSu/OneViyGJDQ7RHjChzTd5zI6ms3gjQfhKSf5T0kep9B17cuJGqVarwNCenwo3eFhBAq6ZN33u8vOf8U5CUwJKQkJCQkJCQJxOFEINfve4rSioLfhNSjxdJ/zG9+cZOVxfDcePkYkjs8uWotG9f5pq850ZSWb0RoGkJyT9K+kj1vgPTZDJ+UFCQi9HXNm+mUqVKPM7Keq/x8p7zT0FSAktCQkJCQkLi30Q1UXJk/MeKFKBJKldvvhmtro7MxkYuhpyIjeWrL77gxcGDpdfkPTeSyuoPAjTJP0r6aPS+Az0sLJg4YIBcjH6Zl0etb77hx6io9xov7zn/FCQlsCQkJCQkJCTkiUwI0UHeRvyNSAGapHL15pvWzZqxdeVKuRjyNCeHqlWqcHHjxtJr8p4bSWX1RoC2Skj+UdJHqvcdqDNyJI6GhnIzvFenTkQuXfpeY+U955+CpASWhISEhISEhDzZKIR4JoTIFULoi4+7ukAIKUCT9A69flGclUWlSpW4tnmz3Iz5QUGhzEmE8p4bSWX1RoCWIST/KOkj1fsO7Na+PbHLl8vNcMNx4977JEJ5z/mnICmBJSEhISEhISFvmgghFgohzouSHi8hQogecrXo/ZECNEnl6vWLn6KiqFm9ulxOIHytCf3742FhUfpe3nMjqax+F6BJ/lHSR6n3GSTPEwhfy8famtHq6u81Vt5z/ilISmBJSEhISEhI/JvoL4TIFEK8kLch74kUoEkqV69fRC5dSq9OneRqjKOhITojR5a+l/fcSCqrPwjQJP8o6aPR+wy6uHEjVeR0AuFrbV25ktbNmr3XWHnP+acgKYElISEhISEh8W9hkBAiVgjxRAjxo5xteV+kAE1SuXr9YoGeHgZjx8rVmA2urnR74yRCec+NpLJ6R4Am+UdJH5XeZ1C6TEa7li3lavjVjAwqVapE8XucRCjvOf8UJCWwJCQkJCQkJORJcyGEoxDiohDinhAiQAihJFeLPgwpQJNUrl6/GK2ujo+1tVyNOb5hA19/+WXpSYTynhtJZfVGgPaDkPyjpI9U7zPIw8KCCf37y9Xwl3l51KxenZ/e4yRCec/5pyApgSUhISEhISEhT54LIXYLIbSEEF/I15S/BSlAk1SuXr/4rnlztsjpBMLXerJ/P1WqVKFg0yY4JAVd/za9EaBJ/lHSR6v3GaQ7ahQOBgZyN75np05EOTv/z+PkPeefgqQEloSEhISEhIQ8aSNvA/5mpABNUrni0P+fQHg1I0PuBrVr2ZL0VycRyntuJJXVGwFaFzn7s78byT9+QnqfQd3at2eDq6vcjTcYO5YFenr/8zh5z/mnICmBJSEhISEhISHx9yEFaJLKFYf+HScQvtb4fv3wtLSEQ1LQ9W/TfzhAk/zjJ6T/dcC/4QTC11phZcWYvn3/53HynvNPQf9h/yghISEhISEhUeFIAZqkcsWhQ0Q5O9NTzicQvpaDgQG6o0bBISno+rfpPxygSf7xE9L/OqBg0yaqVKnCk/375W78lpUr+a558/95nLzn/FPQf9g/SkhISEhISEhUOFKAJqlccejfcQLha8UsW1Z6EuG/wBxJb+g/HKBJ/vET0v864N9wAuFrXUlPf6+TCP8Fpv/n9R/2jxISEhISEhISFY4UoEkqVxw6xJi+fVlhZSV/Yw4d4tirkwhf5uXJ2xRJv9N/OECT/OMnpP91gKelJeP79ZO/4YdKTiKs8fXXHF6//n8a9y8w/T+v/7B/lJCQkJCQkJCocOQaoB048Jx9+x6xd+9DsrIec/Dgi780LivrV7ZuvUlm5nW2b7/DgQPP/6fn7t//hL17H756bjG7dt0jM/M6W7bcYO/eh3/pHrm5z9i+/TaZmdfZtu0W+/c/5dAh2LfvEenpV4iNPUF8/M9s3lzIzp332Lv3IRs3XmLDhuNEROQREXGQ1NR8oqOPERa2n/DwXBISTpOd/YSsrMfs3fuQ7dvvsGnTJZKTz5OWdolt226zY8ddtmy5QWpqPgkJZ4mOPkpIyH48PFJxcYnBwyOR8PAcoqOPsHZtLmvXHiAu7iTbtt0mPf0KMTEniIg4SHT0UTZvvsb+/U/Jyipm48ZLhIfnEhKSRUhIFmfi4/m2USPcTE2JdnYmzNGRDF9fTsfFcTwmhkR3d1bOn4/n7NmstrcneulSYpctY8Py5SR5eLDd35+9a9awJyiInYGB5IaH82NUFCc2bOCnyEh+iori+IYNHIqMZG9wMLuDgsiLiCA/NZU727dzY8sWbm7Zwq1t2/hl926Kdu6kSpUqXEpLK/0O8vJesnv3AzIzr5OcfJ6kpHNs2nSZjRsvkpFxja1bb5KVVczBgy9K53Tfvkfk5j4rvUdOzlN27ixiy5YbbNt2m6ys4n90zefm/la65nfsKGLPngfs3fuQ/fufyD3Qel/9hwM0ufrHP1q37+Ob/voaffaGXy5mz54HbNlyg8zM6+zceY+8vJd/yfadO4ve8KuPOHQIsrOfsHlzIbGxJ4mPP0l6+lV27LjL3r0Pycy8TlzcSdatO0R4eC6JiWeJjz9NWNh+wsJyiIk5zp49D8nO/pW9ex+ya9c90tOvkJJygdTUfLZtu8WuXffZsuUGmzZdIinpHLGxx1m79iAyWQaurnG4usYSGLiX6OijREaW+OENG46TmXmDG5mZ/BwXx8GICA5FRlKwcSOP9+3jaU4ONzIzyVu3jr3BwWSHhHAiNpZxGhpoDx9OrKsroQ4OpHh6cjQ6mrOJiaT7+BC0YAGelpYEzJtHjLMzG1xciHN1JdHNjc1+fuwJCmJvcDA7Vq0iJzS0xCfGxHA4OprDUVEci4nhx3Xr2B8Swu6gILJDQzmbmMjtrVu5uXUrNzIzubl1K/d37eLRvn10V1RkvYtLmS+iOCuLm1u3kp+aypmEBC6npZGfmsrV9HRubNnCnj0POXjwRemc7tv3iJycp2XWwus53br1Jnv3PvpL3//76sCB56Vrfteue6X+MSur+B997j+p/7B/lJCQkJCQkPgIaCyECBdCnBRCXP6d/kmchBDXhBAPRckx9R3+4LO1hBDrhRD3hRBFQohIIUTNd3xWLgHagQPP2br1LklJhSQk3CE+voiEhNskJRWyY8e9dyaysrKKiYk5g7//EWSy8/j6XkQm+5nAwCNs3Hj5TxNgWVnFpKffJCHhOnFxdwgOPo2z824WL96Hp+cJZLILyGTHiIw8ya5d98q9R07ObyQlXSQg4DAy2RlksovIZOfw8MjCySmVefOSMTbOwMBgN1pa6WhpxWNgEImOTijjxoUwePAaBgwIo3t3GR07zqdTp6WoqQUzbFgcI0euYdo0fxwdN+HqmoWFRTqGhmmYmm7FyGgTurrrMTSMZdasFCZOjGTAAF86dpxP06bmNGxoR6NGy2nceClNGpjR9lsd+itZMr3fUrT72aKlPouZ/czQH7wEneGrmD4uEu1poejq+qM33Q290W7o9XdFs/sCRncyYlgrNYQQDK6jzLT6/dBu1I/RDdXoVluRjt8o0/GbgSh/oYFqtb50rdwLpSo96fq5Gt2r96Jf7e6MqtuZSfXboaPQA8N2Q9BpOxC9HwZipjSY+d2GYqM8GH3Fgei0G4peu3GYKGli2mM65uqTWDLOkDDzpSQvWEHaYj+yvFZxfm0ECo0bk+DuzsGDL9i+/S7h4cdxdc3G2nobhoZbmTYtgXHjItDU3ICFRSZLluTi6roXH59soqIKSEgoIiHhDomJhaSlXSUhIZ/Vq48jk51GJstHJjvDqlXHiYu7wL59j/7WNZ+T85TMzNskJhYSGXmZwMDT+PicYNWqM6xdW0B8fCHp6Tf/8QTaPxygtRHy8Y9C/DM+Ui7+MS/vJbt23Sc5uZD4+Ftl1u3WrXfemcjKzX1GUtJFVq48gkx2Bh+fi8hkZ1m58gjx8Rf+NJGVm/tb6RpNSLjD2rX5uLllsWjRLlxdj73yj8cJDS1J+JSXUMjLe8nmzYUEBx/Fx+fkKx99Hi+vg7i6bsbOLgkzs3QMDXeirZ3J9Onx6OuvZ+bMECZMCGbYsGAGDQpBTW01nTrZ06GDAz16BDBwYAwjRoQzYYIfNjaxeHjsx8YmE0PDjZiYbMHEZBM6OtHMnBmNkVEy06bFMHhwAF27LqJZM3Pq1bOhYUNnmjRZTtOGVrRqqkOfjqZMGeCCVj97dDSMsBkwCdtBxlgPc8BqjDvWk92w07bHQcuS+eOtsB48D4teFmh31mFU28HUrPYVXWu0ZnI9dbQb9mdiY3V61upE5xrKdP6mP0pf9kWlmjoqlXujVKUnyp+r0e1rNdRr92RYva6Mr/cDOs1UMWw7GN22g9FqOxCTToOY320wc7sNxVRpEFrtBqPbdiwmnaZg0l2L2b0mYzdCi9UmjiTM9yZ1kS+7PQL4OSSMyRoa2EyfzrPcXB7u3cvR6CRSvNYRYBvOUqNwbDSDMJngyZxp3riarCHcMYrly/fj5bWX0NAzxMffJT7+LgkJhaSlFZKSUkBIyEn8/E7h63sBmewc/v7HiYo6/ZcTmX9VBw48Z/v2IpKSComOvkpQ0Fl8fU/g5/cz4eEXiY29TmrqdXbvfiB3f/cB/lFKYElISEhISEhUOFuFEFlCCFMhhM7v9E8xTwhxSQjRXgjxuRDCVQhxVQjx1Ts+n/7KztpCiDpCiG1CiJR3fLbCA7Tc3Gds3HidhIR7pKU9Z/NmSpWW9oz4+LtkZNx8Kxm1b98jVq8+gr//NdaufUZUFKVas+YR3t6n2bDhzDuTWPv2PSIhoZDk5Mekp78gLKyAJUtO4u5+Hy+vYtzdbxMU9JCIiOcEBNzE3/8o27bdKXOPnJzfiIg4iUx2gdDQ4tLnBwbew9Iyj3Hjkpk8eQd2dnextr6NhcUDNDXzUVFJoVu3DQwYsImxY/PR0NhNu3axtGlziPbtT9Kr12GGDMll5MifGDv2ON27BzNsWBS2trdZuPA+hobH0dQ8iKbmWQYM2Iu6ejKDB2fRoUMKjRuH0qjRRhQUTtGkyWGa1smgVf1MFOpFodp0ITOUHTDvugC9tguY1sYFq0GxeGjvYeH0DCYPXk/f9g6M6OCGpVoADoNjmdsvFsPvrBn7zQCqiqrY1BqNv4Ix7o31mfXVcAZVHoWKGMPwSoPR/FKPGZ9bMbWKLZPEbMYKTaZ9Nolpnw3H4Kv+WNaZzOzaw1nUcBD+rUex+NvRzG82msVtJ2LXajhOTafgqmCCt9I83Dsb4KZkiFsfR+arWOM2wJIMS2/OeUVzcPlaDvnFMEhJGWdtbaLXHcbX9yiuriextf2ZefNuYGp6CU3NfDQ1C9HUPIup6WmMjQ9gY3OExYvz8fQ8SXz8L2zeDAkJD/DyOsLixXmsXv0LkZEvS7/LsLBfWbmygLVrz7Jr19/z72L//ickJxeSmPiAuLh7BAdfJyzsV6KiIDz8KatX3yE6+i5JSSVr9O9OnlVggLZDVLx/FOKf85EV7h/z8l6SmXmbuLjbbNr0Wxn/mJ7+gsTEX0hNvU5u7m/l+Kbj+Pjkl66t1woPf4pMVkBo6DGys8uv9MvJeUpKSskaTU9/QUzMbZydj+LqegtPz2Lc3YsICChi3boXBAXdx8fnBKmpBWWSGHl5L0lIyMfH5xTBwQ9Knx8aWsz8+ceYNCmdsWPTsLG5hq3tXSwsipg16yZ9+mSirByNunoCI0eeZOjQI3TosJ62bXNo1+4k3bodZsiQQwwfnsu4cSfp0ycGDY1VWFhcZNGix5iYnEZT8yA6OmcYNuwAffqkMmjQLlRUttC4cQgNGmygRYufaNr0JI3rZqLQIJPWDVPo1HAJ43+ww7SbA7M62GH43Tzs1VYQMSOa1VrrmDt6FWO7zGN02wXM7+2E92BfvAaFYKVojX7t8VQVVZlSvQ+yb/Xw+daYOTVGM6LKCHqI8fQXg5j++QxmfGHJlCrzmCQsGS90mVJtItM+G43OFwOZU2sis2uPwrbOIHxajWC5wmhsm41icevJ2H03giXNx7OshSHenebh1tkE9856uPVeiEMvOxb3NiNmpgunPaI4vDyC3BXrmT9pKqO6d+f0+vXsCNhAgnsqQQvS8J+Xg6flAWw09zJ3xo9Yz8hiyaxtuJqkYmFxEEfHiyxbdpKoqJtkZLxk48anrFz5M46OOfj732Dduhel3+Xatb8REHCd4ODTZGbe+luSWAcOPCct7Qbx8UUkJT0iJKSQkJCHREa+JCLiGUFB91i37hYpKcXEx99k+/Yiufu89/SPUgJLQkJCQkJCosL5RQjxTQU/M18IYf7G+ypCiJtCiBnlfPZbIcRLIYTiG9c6vbrWrJzPV3iAtnnzLRITfykTmP1e8fF3y/yRmpf3ktDQYwQE3CwTmL2pdete4O19mrS0K289Mzf3N5KSCtm48SmbN0Ns7F2WLj3BihVP8fcHf3+QyZ7h6XmbsLAnREVBcPAvBAYeJTv719L7JCRcQCbL/13C4yl2dqcxMDiCpuYltLWvoa39E7NnP8DC4jGDBx+jd+/zdO2aTbduuQwadBBFxXTatj2NqupDuncvpkOHn+jZ8zDDh19g4MAj9OiRR7du6ejrn8DC4gr6+lfR1LzKiBE/MXjwGVRVD9O2bTLNmqXz7bdnadHiAs2bH6NJvQO0qHuYNo0Oo9J0I+qNIulXdw6TFOZj1jECq66JzFIJwX50CrajE5jYxYkJHcPQUwxHu0MgVn1iMO24BPPGsxnx9XCaVGmAQx1dXBtMZU71SWhX08a8qjETxVDGCR00K81Cq5oNs6ouwaTKUrSFCcZiIrZVJjPjCy3m1NBh8TeTWVZzMMsaDCP028n4Nh+LZb3R2DaYxcpWRqxtMxuf7w3wVTTHs9MCfFQcCFZzw03NnjVj7DngEESBTyw/ekShN2gM0zU0WLE4g+XLTrJw4TkWLnyAldVNtLQuYmT0GyYmYGBQzNSpJ9HTO4uZ2c+4uNxh2bKbyGSnSU4uJjj4Mm5ul3BzK8LX9245a+k5gYHXWL8+v8z3/74JidTU6yQnPyY19QnBwdeJiHj21tpdvfo2SUmP2LjxKUlJhW8lKP7NeiNAk4d/FOKf85EV7h937bpPXNxtMjJevtM/JiU9JD39Rplx8fHn8fHJf6d/jIoCP7/LxMScLneNbtp0neTkR2zeDKmpv+Lqegx39wel/tHP7yVubncJCnpYmhTz9T3Ojh13S++TmXkDmewUa9f+VvrMyMiXODmdw8joKDNmnEZH5y6amj9hZnYLK6unjBlzit69z9Ct20GUlXPo1y8PZeU02rT5CRWVInr1ekbHjmfo2vUAw4ZdZPDgI6ipHUZFZStTpuQyZ84VDAwuo619i5Ejf2Lo0HP07HmM9u0306JFEs2aHadFi3yaNz9Jo3q5NKv9E60bHUOxcQZ9G8ejUW8h41rMxrBDAEtV1mHT2YvlQ4LxHb8Gs+52TFf0ZHbHlZi092KhagD23RyxbW6IYQ19hBAsqKWDc73JLKg5Fa1q05hdzYwZlUYwRkxFSxiiXc0S3WqOmFV1QVfMYaaYgl2Vyeh8Nh2TGjos+mYaLjWH4lxvEAHNJrL62ynYNBzBnPoz8WhuSFRbS7y/m0mAoinLO9ri23UhgWrL8ejjwMph88icI+OyLI6jbuuQGdnRpklTdiwPJMYpnkinrQQuyCPA9hh2OlksNjyLi8llnIzysZqexVzN7Rgbn8XR8Rpubvdwdz9FUtJDIiKu4+aWj6vrXby8bhER8bzMOoqMfMnq1bdYu/bC35Lk37LlDgkJ90hPf0FoaOFbCdioKAgKukdMTBHp6S+Ij7/xUSX5pQSWhISEhISEhDw5I4SoXoHPqyFKAqvuv7u+RQjhVc7nRwshisu5/kQIMfId96+wAC0n5ymJidf/MDh7XYmVlFRY2ttqx467+Pic+MPgrCTp9IDg4CNvVWHt3HmPhIR7bN4MGRkv8fc/zfLlt0qDs9fy9HxEQEBR6f18ffPZtKkkIZad/SsBAUff+uPa1/cGFhZn0NI6P6AEjQAAIABJREFUjpHRbxgYFDN69EEsLB6irX0NNbXjaGgUoqR0BlXV8ygqJtCmTTbKysUoK5cEaB06/EyXLj8zYMBFunXbR9++1+nd+xSDBm3CwCCfmTOLmDr1Fv37H0Vd/TQqKudo3DiJxo330KrVPRQUbtKg/kG+rZNLy3oX+a5BHr0abkKjYQpqNZwZ2sgO447R2HXfjFmXtRiphWPeLxTtDs7MVFqPcYdoZrRdj2ZHf+a0moNF/Xmof9mHrp+3x72OKXNrjEf/s7EYV7PArLIOpmICU4Uhk4UZ+pVsMKnqjFHVxRgLSyyFDnOqlgRyel9o4llTE5caw3GpMYyIphPxazIK69qTcahrxoqWloS3MSZQQRPvH2zwUVyCn+I8wtQ9CNBwIWDIfBJneXBJFsfPnutx0jRHsUVr/Jfk4GB7AFvbKzg4FGNoWICBwS+YmICJCRgbv2DcuAvo6FzE1PQq8+fn4+39K8uWnSM09CI+PgV4eNzHz+8l7u7/n7R8UyEhjwgNvciWLXc+aM3v2/eI+PhbbN4M0dF3WLPmQblrNyzsV9auvfWqQuweu3bdl3vg9R4B2jlRsf7xtQ/7p3xkhfrHvLyXpKQUvlV5VX6S/0ZpcjU7+wn+/kfKJI7KU0TEc/z8jrJv3+Myz83KKqlseX3v8PArODldfMs/ens/wdv7dmkCPyDgBuvXnyEv7yUHD74gPPwkgYFlE8JBQQ+wtj6Dvv5x9PUfYGT0nDFjjmJkVIiJSRH9+h2jX79rqKqeo0uXs6iobKV1600oKT1ESekePXs+oUuXAhQVjzFw4BV69MimT5/z9O17FTW1FHR0TqKvfxsdnfv073+Cfv2O0afPJVq02EzDhhm0bHmHVq3u0ajRERrX3kOLehdpWf8o3Rpuon+TTNRqeDGg7lz02oeyvHsMDsqrsVb1YPFAf2Z3tsWs4wrsu4Sh/90qzDr7Mfe7Wdg2MGNa9anUqVwT73qWzK0xBeMvRjCzmgnmVY2ZLcahJfSZKIzRE9bMquqI6WfOGAtrLIQ+FpUnYvWZGVpf6LLsG01cao3CpcYIAhqMIfzbCcyrPRr72ka4N7MhvK0ZQS21WPG9GbKOS/BVnE9g96WE9/dgRX87omY4c85zPRe8Y9i40JeqVaqQ7BBC9IJY/OftIMzxZ5ab5rJA9zAuJpdLZTH1MBaT92BqegNr6/N4eRWzbNklAgPPsnLlRTw8buPvD+7u91iz5tFba2nt2t8ICiogJaXwg6qwcnN/IzGx8FV14QOCgu688weqNWtusGnTs1dV1Dfl7vfewz9KCSwJCQkJCQmJCmeCKOmX0lQIUfl3+idoJkqCs7a/u75BCBFczuc1hRDXy7l+QwgxvZzrFRqg7dp1n8TE+38anJUE8XdKf2WNjT3HypU3/jSBFRUFMtnb/atSUv6/+io19QnOzsfw8fntrQBNJnuOp+fN0i0TwcG/EBZ2/NW2nuv4+p5763mOjucwNz+DllYBJiagp/eAMWMuoK9/mVGjTqCufgV19QJUVG7TtetZWraMoU2bo3TrBkpKv6CicpeOHa/SocMFevY8S6dOe+jbt4iBA4vo2jWaSZNOYmhYzOjRV9DQOEuvXqfp2PEkdepspEGDw7RqVUyLFg+pVyuLprUP0qpBIW1rb6VPw+30rRdH75oBaNR2Ql9xPXY9M7BSiWWa4gr0lN0wVgzErNMaDNvGoPV9LJNaODC7iTlWdRag+Fk7Rn6tgUft2Rh/PgntqmOYXdUKUzEB+0r6aAk9JgorDIU1xlUXY1LVHithjY0wYFZlHeZXs0TnMx3cqs/A+evxLK8+lOD6Y/CpPwqHmtNwqGOGR/P5rFLQIbiFFu5tbPHt4MRKRTtWd1/C+kEyvDQWEj7ZiZPLI7gkiyPUbDHffFkd38WHsDPfh63tbebP/wUdnYsYGz8rTWAZGhYzceItpk69iLn5bSwtz+Pl9Yjly2/g7HwAd/dL+PiUVN95eDwkMPCXcgOm4OCrxMX9eW+1P1Jm5m2Skx+Rnv6CNWuusW7d83eu3aCgW6SmPmHjxpLtXPIOvN4jQNMUFesfhfhnfWSF+sesrGISEm79Jf+YmPigtEo1M/M6MtmFv+gfC9i06XKZ527deoekpIelCX5v7+N4eDx4yz+WJDTulibx1679DX//o6WHYvj5HX9rfXt5XcXC4hyamqcwNn6JoWExY8deRkvrHFOn5qOmdop+/W6iolKIsvJV2rRJRkFhGyoqL1BSKqZbtyKUlArp0OESqqpnUVbOpmfPiwwd+htdu6YyZsx+9PUfMHnyDQYOzKdHj8Ooql6kUaPN1Ku3j5Yt79G6dTH16/5I01q5KDS4hEKdHHo12Ebf+sn0qbmG3jWXMuO7YJaqrmOZ6npMFJdi0XURlh2WYtfJk3mKoRh9F4ZW66XMa6KLTV1rhn09iPbVWuNVxxrLL7TRrDSM2dXMMa00g7lCE2MxkzHCEj0xB5MqDsyquojZwpoFwhR9MQ27apboVtVj0dczWFZ9Ei7VhxNQZwSrGo9gUc0pLKqtj/u39vgq6BPRShO3VuYEKDrj034Bq1QWEjNIhpe6I2FjF5HjEMw1/0TylkdQrUpV/E3cCbeKYYXlHsIcTrFoZjaOBmdKk1dLZxVgPvkkppMOYGp6B3Pz87i6FuHp+QvOzodwdy/xlyVJy1+RycpPKgUH3yIqquCDqlR37/6F+PgiNm+GiIibhIUV/4F/LCIx8SEZGS9JSPh4qlSlBJaEhISEhISEPHn5Si/K0T/Bf6oCq6Rx+8O/mMC6V2pXZOTPrF5d9JcCNF/f82zbdqv0mXl5L0lKukZ6+otX228esXTpCfz8XpYboHl63irtsRUe/oTVq49y4MBzUlOvsHLlpbeeZ2d3GlPT02hrF2JiAjo69xk37ira2ucZPvwkGhqF9OlzAVXVB3TpcobmzRNo1+7EqwTWI1RUbtO58x06dMhHVfU0nTtnoa5+h8GDH6OkFMPEiScwNPyVESMu06/fBXr1Oo2i4knq18+kYcMTrxJYj6hfM4dmdX6iVYNr/FB7C2oN99KvXix9aq5BvfYy9NpHMr9HOjYqiUzvsALdTi6YdQhldscgDNvFov19PFOaL8C8kQU2tRfSsEp9DGpMxL2WJcbVJqNbZSKzq85hthiPQ2UTtIUeE4U1hmIuxlUdMKmygHnCirnCEEMxE7tqluhV1cHl6xk4fz0Zz6+HsqreaHzqj2JpjRk41jHDrdl8VipoEaagi+d381jZwYmVigtY3c2RmMF+eGksImz8Eo65hHPVL4Eti1YihMB13jYWmGRja3uXefOK0Na+iInJy9IEloFBMZMmFTFlSgHm5neZPfsCHh4P8PAowsEhi+XLC/D1fY6/P3h5FZepuisboF0nJqbggwKltLSbpKY+IS3tGWvWFP7h2l2z5i4pKcWkp78gKenaR3Pq1hsBWkX7x9c+7D9RgbV370Pi4+/+Jf+YklJMZubtV2vsMr6+V/6Sf/T3v05S0sUyz83IuEVq6q+vql+fs3z5MVaseFKuf/TwKCpNMkRGvsTP7zh79z5i5857yGSn3nresmWXsLA4j5bW+dJ/mxMm3GDatDOMG3cGdfULaGhcp1u3m6io3KB16xQUFPbQrRsoKxejonIbZeXbKCoWoqR0CmXlA/TocYlhw56jpJTOsGH7MDQsZsKEQgYNukyPHsfo2vUCjRplUq/eQVq2vEurVsXUr3OYprXzaNWggNZ1s+jdYA996yWgVjOMPjXcmdI6kCXdIljefQMmii6YdbHHWtEdh46e2CiuwfT7dWi2WIRVo5nMrzuXbp8r0e/L7njXscbqCx1mVB6BZTVLTMU0FlTWw1LMZLSwQk9YMbuqA7OqLmBOJRvshTn6Qgv7z6wwqDITu+ozcKs+FZevhhNQezgBDUfiXHMqi2rp49nMHs8WukS30satpSWrOjoja7+QICV7ogf74K2+hLAxC9kzP5Br/okcXh7Bt/WbMn+SNWFzNuA9J5uQRSdZqLufJbPOlSawlsy6iMWUM5hOysPY+A6mpudxdr6Dl9djFi8+yPLl5/D2Li7dWu/tfesd/vEukZGXPmg7386d90hMfPCq8u/6H1YRBgc/KO1jGB9/86M5uVVKYElISEhISEjIk75/oH+K8vq73BLv7u/yQpTt79L51bV39sCaNMmM6dOtmD7dCn//zH/sD7kdO/7/j9U/3yJTxN69Dzl0CKKjzxAYePsvVhicZvv2stu+kpOvkZb2rDTwW7r0eGkC4035+b3Ew+Nmac+PkJBHBAcf5+DBF6SnX8PX9+0eM4sWncXc/Cza2lcxMQFd3V8YM+Yiurr5jBhx8tVWl3xUVYtQUjpLixYb+P77Y68SWA9QUblDp07Xad8+n+7dz9Kp017U1e8yePADlJVjmDz5OIaGxYwceYV+/c69SmCdoE6ddBo2PEqrVsV8++0j6tfKpmmdPFo3uEa72lvo02AXfevF0afmajTqOKOvGMX8HhlYq8QzVdEbnU7LMO0YjFmn1Ri23YDW9/FMaWGHeWNL5tRaQFVRhYW1jfCobYnx5xPQrTqW2VWtMRPjWVRpFjpCj4liDobCBuOqjphWWYC1sCqpwKqky/xqFuhW08G1+gycvp7A8q+HEFR/DCvqj8Kx5gwW1zbDvbkdgQrahLbQwqONLf4dnPBTXMDq7kuIHiQrSWBNWsIJ17Vc8Y1nv+taalevhaXeGuzM9mFrewdb2/uvKrCel0lgTZx4h6lTCzAzu4OFxXk8PR/i5nYbJ6cc3NwuIZM9e5XAekxAwL13/OJ/jdjYS6VbWd9HGRklzYfT0p4THHytTP+0t593m5SUX0lLe0Zy8jW5B15/JH//zFKfMWmS2esAbZioeP8oxD/nIyvUP2ZlPSYh4c5f8o/JyY9Kt7dmZFxFJiv4S/7Rz+8qGzcWlHluSZXg49JG8R4ex/H0fPSOBNbd0gTWunXP8fU9RlZWMXv2PMDX98Rb69vD4wqzZ59DU/NM6b/N8eOvMWPGWSZOPI+a2lkGDLhFt2436Nq1kO++S6Zly12oqLxESakYFZW7KCvfRFHxKioqP9O1ay69el1i6NBnKCtvZMSIbAwMHjFxYiEDBhTQvftRVFXzX1Vg5aCgUFRagdWk1oGSBFadLHo32EHf+on0qRlK7xouTG8dhJNqBK6qMZh0cGa28kKsFJdh38mLuYohmLRZi5bCYuY10mVeXRtaVvuWqdWH41XHmjmfazOj0jAsq1lgIqZiV0kbc6HPWGGJnrDCrMoijKraYyGssRdm6Ivp2H9uzcwqeiz8ehqu1afg8vVwAuoMJ6DhCJbUmIpDbX08mi/Ep4U+ka20cVOYzaqOzvi0tydQ2Z6YwTK81BcTNmYhWfavElhu6+jRToUZ/aYQNicGb8ssQh1OsXDmfhYb/n8Cy2lWARZTTmEy6SAmJrcxMzvPsmV38fR8iJPTQdzczuHl9Rh/f1ix4ine3uX/vzc4+A5RUQVkZT1+7zW/e/d9EhLuv6rAukF4+Nvbuf//efdJSHjw6geu6+Tk/PGpmv9C/yglsCQkJCQkJCQ+CeYKIQpEybHwXwohlgshroh3n7C1SQiRKYSoK4SoJ0pO2Ep+x2crfIvMm71W3qWSfhj/v0UgM/M6Pj5n/zQ4Cw9/QkDAEXJyylbMbN16pzRxlp7+ghUrTuDufu+t4MzLq7hMU29//8skJuZz6BClW2R+34Dby+sqZmZn0NQ8ibHxC/T1ixk16idmz77H1KkXUVM7hYbGdZSV81FVzeeHH2Jo0yYHFZXfUFIqokePX1FUPEenTmfo3/8Cysq70NC4hZraedTVE9DVPc/Mmb8wefIN+vc/hpraabp2PUujRok0bJhD69YPUFC4Q4O6OTSrk0uLegW0rp9N74ZpaDRMpE8NDwY1WIhxxxjsum/GQikSPdXVmKgFoNveDSOlSGa1j2ZG2ximt3VnTgsLtGrPooqogntdGzzqmGP55Th0q43BrJolZpVmYCkmM13oM0GYYyBsMKnqhHE1B0yFJVZCB/PK07H6fDY6n5f0wFpaYyQu3wwjvPEE/JqMZF7tKTjWm41nCytCvzdgtcIMvNvZ4KO4FH9FW0LV3Ajq74Zs4AJidJeR7x3DWa9ofvKNo7PC90wbZY+9VTa2toU4OBSjr5+PgcGj0gTWrFnPmDDhElpa+ZiZXWfu3PN4exezbNkFVq06jbd3AZ6eD98KyN9UWNivrFlz8YN7rZRskSmpqlm37iahoY/LXbtr1/5GaOiN0l4wW7fe/aDnVqT+BRUG/5SPrFD/eODAc5KSCt86nbX8CtXbpZUve/c+xNf36FvNtn+vyMiXyGTH39piXVL59f+JszVr8nFxuVLOFutneHndKt1ivXp1EeHhJzh48AW5uc9Ys+Y4a9Y8LPPMgIC7WFqeQVf3GIaGxRgZPWPMmOPo61/F0PA26urH6N+/EFXViygpnadz50xatUqna9dilJTuo6paTOfOBbRvfxoNjQK6ddtD797nGTjwLj17JjF9+jFmzryLtvY9+vc/jZraEXr3vkzTphnUr5/5qgLrAQ3qH6ZJrSwU6l9Eod5PdK+fRr8mGajV9KFvHTt024Xh2nM9i1VCsFJ2xb6vNxYd7LDo6M2CzmEYtF6NYXtPbFroM7fhbL6u9DVmNafjVdcKm6+nMavacGZVM8OkkgFWYiI6YibjhAl6whqjqo6YVHPGRFhhJWZhUnkiNp+Zo/mZLi7VZ+BSYwzO1UcQUH8UYc3HYldrHAtqGeLR3JbgNrMIbqmFx3dm+HV0wkfRjlXdl7Cuvzde/RYQNtmJE65ruegTy09e0Wj1H0W/Tr2JtI1BZr2TMMefcTbJZqHesTd6YF3CYvIxzCftxczsJpaW5/DyeoSrayEy2XFksnzc3e++qkh+8I4t1s8JCrpCfPyVD0rw79//hPj4kr6Y8fH3CQ4u/8eEyMiXBAeXVLOW6PrHWKEqJbAkJCQkJCQk5EIXIcQqIUTaq/8qVcAzl4iSvi2PhBC7RUmgJoQQzYUQD4UQvd/4bC0hRJQQ4r4Q4p4QYp149x9OFd6keOPG66SkFP9pf5fX22MOHSo5In7VqsNvBUdvV18VkJCQ/9Zzs7N/JT7+euk2wsjIQpyczuLr++KtU7ZCQ4tfJcOe4ud3nD17HpTaHhn5MytXlt0GFhJSjI3NaWbOPIqu7i10dYuYOvUgVlbFmJref9V4/TLKygfp3v0Iamo7adduC4qK1+jW7ZdXTdyP0K3bUYYPv4iGxiHU1E7RvfsuZsw4gJnZJWbOvIGW1g0GDfqJgQPPoap6CgWFZJo120KLFtdo0aKAJk0O07T2AVrUPUmbRj/RvXEqGo0T6FvXljEt7DDrsp65qhuZpbSGuUPjmDsygSkdFzO1SyT6ihFo/hCCWa8ozDvYMbLmaOpVrodz7dk41jZkad0JmH01Ht1qBsypZoKWGMZEYcj0SkboVJnHrKpOmFR1ZqYww1RMYX7Vyeh8ro95dR2cv5nCslqDcKk3nPDmk/BvPo7ZdUZjX98UPwVTItqa49tKDx9FC7w7L2JFFzvCNDzxVHNg9Ug7dtkGcMU3niPukRxZmcAMjf6odx/PMpcT2NldwMGhGHPza68q4F5gYgJGRr8xefIpdHXzMTM7j5PTLTw87uPldYb4+PsEBBTg5laIl1dxmabUbwZLq1ffYt26/A8+7ep1UmLTpt9ITn7E6tU3y63CCgoqIi7u/qtTtq5/8OmHcgzQ5OEfhfhnfGSFn0K4devdP+0TmJr6hJSUwjK92aKiTv1pn8DAwDulPf3efObBgy9ITv7/PoEJCQ9YuvR4mVNaS/pf3WfVqvuvEhgv8PE5Q2bm9dL7bNx4GV/fC2XWd0TEcxYuPIOR0Qk0NQswNCxm8uQ8TE1vYWVVzPDhx1FTu0i3bkfo2vVH1NVz6NhxEz/8cB4lpSJ6935Bx47n6Nw5j2HDrqKh8SNqaidQVT3AmDG7MDPLR1//Grq69xk69EeGDCnpE9i2bSZNmybTokU+LVteo3nzEzSpl02Luidp3fAEnRptom/jDNTrLGZUU0sMfwhimWoMtp1kOA0IwGt0MBYqtuh2XIFNp0CM2smwVQ1gQef5WDTWRgiBbU0TXOoY41BnMvOqT0CrmjaW1WYzs9IIxgttpgtjdKvZoF/VEdNqy9EXVswSM7CrMgnDz3SZVV0Pp2+ms6zWcFxqDyGgyQTCWkzBut4I5tY1xKOZMTHtLfFppcsqRVPcOy7Et4sdQWrLkak5s3LwPFJNvbniG88J90gO+yfgZWBC26YtiXaMJ8xhG8H2R/Gfe5j52jksNbqAi8llnI0vYTU9B+vpOzE1LWDBggK8vB6zbNlpNmy4S0jIVdzcLuHlVYyn5y3Cw5++tZbWrLlPaGg+27Z9eKI9Le0GycmP2LTpN9asKXzrR6LX1dDr1t1+VZ195285/VBO/lFCQkJCQkJCokIZKoR4KoRIESX9VZJFSe+UYfI06gOo8AAtO/tXEhML35nESkp6SErK2w1at269iUx2jODgt09xW7fuBStXXiU09BjZ2eX3xdi+vYi4uFukpT0nLe05K1f+jJNTPjLZM3x9X+DuXkRAQBGRkS8JC/sVH5+TpKYWlAn29ux5yOrVRwkIuFEmSPP2voap6WEmTtzJ5Mk5zJt3AwuLW8yZU8z06RdRUdmGikoqffqkMXbsZXr33kbr1ql06XKVTp0uoaLyEwMG5DJixDEmTLiIisp6NDQisbO7x4IFRejr/8z06cfQ1DzHwIGH6NlzM2pqO/n++xQaNUqiadM9tGp1jsYNj9Cs9g5aN8zih0Yp9GjkzNg2Nph0scWogzt6P/hiobEetxm7sZ+cwuT+oQxs78q49n6YdQ/AfkAcVmrhdK/VE4WqLTD8ejr2dcYT0FIfp/p66H0+homVJ9NLjGakGIHO54ZM/8IWrar26Ij5TKyki3bVSRhUHYXul8OZV0cX61qjWFx3EH4Ko1n+7Vicmo5hgcJ4rJuNZ0WzGfi2NmdFZ2tWdDLEvbMpK9RccOphzzJ1S+IMXDnnFc0xt3Uc8I4mPzwGj5kzUWyvirf3MVxdz2Brm4+d3T0MDPLR1i7EwKAYLa0rzJp1mpkz87CyOo6r621cXE4RGXmDzZshLu4ebm7HcXQ88dYJW+vWvSAw8DbBwafZvPnW3/Irf0mFy3VSU5+wfv1tgoLulFaxREa+ZM2aX4iIuEVq6lPi4m6VNuf+WPRGgDZeSP7xg5Sb+4yNG6+TlPSg3NNaU1OfkJh4/a1tW/v2PWLVqsOsWlX+dq/AwLv4+x955+mW+/Y9IiHhOhs3PiUj4yVhYQU4OZ3C2/tX/Pxe4un5EB+f20REPCci4hky2QXWr/+5TPVNTs5vREScxNe3oEw12KpVRVhZHWPq1D2MG7cXK6srWFvfxtLyETNn3qBXrz0oKaXRq1cqI0eeYtCgg7RpE0fHjufo0uUGSkrH6NfvIEOG5DFp0mV69dqEqupqzM0v4uj4CBOT80ybdgQdnXMMH36Mnj0zUVPbTocOGTRpkkCTJttp1eoUzZqcpEntnbRusIe2jXfQtYEnw1vNY6aiDSaKLli2dcGu+wpCp0QTOC2UOUNXMKGjPVM6uDCvmwtu/fxwHxjE1G/H8lWlL5j1lTbWtcbj11wXtyaGmHw1jqnVJtNXjGWwGIJ2NR1mfG6NZjV7dIUdk8UsZlSdxKyq45jxxTDm1NLCqvZ4FtYZhM+3I/BWGMfSpqNxVJiAdYvxuDWfim9rE1Yo2rCikwnuHQ3w7rUYt96LWdzLkvDpJdurT3lEccAzip+Do9nn6cnXX3xBkmc0ie6ZBMzfxqoFh3E13c887VwcDc9hq32YRfo7WWyYjonJIZYtu8PSpWcJCSkgPf0FycmP8fU9jYPDUQICyjZwf+2vVq06S3Lyh1Vfvdb+/U9ISiokOfkxCQm/EBR0o0wvrNDQYkJCbpCa+oT4+CIyMm5+0MEacvSPUgJLQkJCQkJCosI5KISY8rtrk4UQeXKw5e+gwgO0Q4dKklipqdeJj79JUtJDkpMfk5j4gPj4G6Sl3Xhnb4tt224RGHgYH5/TBATcZNWqO/j5XUUmO8a6dSffmbw6dKikgmrHjnskJRUSH3+X+Pj7yGTHWLgwC3v7n3BzO09AwC18fM6zcuURNm26XG7yYvfuB4SFHUcmO4G/fyGrVt3B3/86jo57MTGJxNAwFmPjbIyMjqKpmcWkSRmMHRvK0KE+DBsWyYABsWhoJKCktBoFBRdatw6gd+8kBg/OYMiQWIYMWY22djhz527ByGgXs2blYGS0Gx2dDKZMSWHixBgmTYpjxIgkevQIpGVLW+rVm0+9ev40bBhO/Xr+NKjtgEJ9U3q2s0RTbRkze85lemdNpinNwniAFyajIpk5Lo6Jo8IYMsiJURrz0RvohqnGCgy6udG85g98V70Zw2p2YWrNvhjXHYFNoxFMqNGXTtU606FKD5Q/H4BatcH0rzKKXmIEKmIovSoPoc/nA+n/dS8mfaXM9Bqd0anfGxOFYZi3HIRey34Yfj8E+07DmN+hL3oKA5ipMAbT76Zj3UkTa+UZmHedik3/mcg0F5Bu68OWRQHsWh7IqdVhXImJIcHVlUaNviUl5RK+vodwcMjC3DwLQ8MDTJy4mZEjE5gyJR1j450sWJCDg0MWS5bsZs2aCyQlPSIp6SHx8bdYv/4MISFH8fP7GT+/K6xadRt//2v4+v5MaOgJMjNv/61B0t69D0lOLiQu7hbh4Zfx9z+Pn98l/P0vEhJyidjYWyQlFbJjx72PZmtMOQHaISH5xw9Wbu4z0tNvEh9/nYSEX0hOfly6blNSCt/Zc2jPngeEhh7Dx6esb/LxOUlw8NF3Jq9ea9++RyQnFxIff5ukpIcEBZ2QCvr3AAAgAElEQVTBwSGbBQsO4up6Dj+/6/j6XsLP7yixsefIzX321j1ycp4SHX0aX99jyGSXWLXqDgEBN3Fx+ZHZs6MxNIzCyGgXJibH0NbOZcqUbYwbF8mwYTKGDl3DwIGx9O+fRPfua2nVypVWrWR067aBgQMzGDw4kSFDgpk2LQQrq42Ymm5n1qz9GBvvRU8vkylTUpkwYQMTJ25g9OgE1NXD+O47Bxo2tKVePS8aNgyjQf3V1K+1lG/rWtCllSlTejth0GcRM7roYNBlAvP6zsFhpAf241Yxe4w304fYoNnXAIuBc1g00JG53e3p1aQfdT+rzZBanZlYqxcGdYdh02AkWvUGoPyZMj9UVaXLZ/3p+flA+lcdRR8xClUxlN6VBtPn88Gof6nO2K+UmfFNJ7Trdceo5SAsFAZj0KI/+t8NwrbDcOw79seotQa6347A5LtpWChqYaWsg0W3qczurYXbBBtSrDzYuiiAHcsCOboyhEtRUeTHxVG5cmV+jFzPzsANRDpF4W0Zg5NREpZTo9EZEYjx2GCWGEaycl40Dg7ZODruIiDgOAkJD0hOfkR8/B1iYs4TEnIYf/8T+PldIiDgFitX3kAmO8vq1cfZuPFqud//+2r//ids3FjyN0Fk5DUCAs7j61uAn18BQUEXiYm5SUJC4d/ulyvYP0oJLAkJCQkJCYkK5554+0j4KqJkK8rHiFwCtEOHShJKWVmP2br1Llu23GH79qK/tG3qwIHnbNlyg7i482zYcJakpIv/k/0HDjxn165f2LLlDlu23GHz5kKSkvLZsOEssbHnyMi4xv79f9wcNi/vJTt3FpGQUDIuPv4C27ffITv7CZs3XyMk5BDe3tvx9d1JaOhBEhLOk5JymeDgLJYtS8PRMQFHx3jc3TNwcopl/vxIFi5MQCbbRnLyebZtu0t6+g1iYn5mzZocAgNzCQnJIyrqKHFxZ1m37gSBgVl4eW1lyZIk5sxZzfTpS5gwwZEZM1yxsFiJvX0EjgvXs8RhA16eaUSEHSAseB/uyxJZ4hiLm1saYWF5bN5cyObN1wlctZclC9ezwHo1TRorMHviNCIcnFk20wDLcVMxGzEJF11DohctYvX8hVhN0WOa+kjGqKozQ30wJsMnYDJ6EhZjp2A/bSbO+qZ4m1myarYl/rNtCJxrT+QiJ5KdnYlbvIQNS1yIW+zMWjt7/K3m429pS8RCJ7b6reRoVBSnYuI4FhPPzxviuLppE0Xbt/NrdjbXMzMRQrBv3yOys38lLe0qkZEnCAjIxt9/D4GB2QQF5RAefoS4uHNs3XqLPXsesn17EVu23GHr1rtkZT0mL+8lBw48Z+fOeyQnF7BhwzkSE/PZtu32P3Y8+8GDL9i79yFbt94lI+MGKSkFpKUVsmVLyZaYv6OaQc4BmuQf/0bt3/+kzLrdt+/RnyY3SxL1RSQmlvimuLjzbN9+5y8H/QcPvmDfvkelfjkz8yYpKReJjT3Hhg1nSU29xL59f960e8+eh6SkFJT61czM62RnP2HbtlusXXsYH5+drFixg+DgHOLjz5CaepX/a+/Ow6uqz66P3xAgEwQFFRUFsYqKAg8IgghWUEZFQQQEREFRUAZBg4KAgFCBgoqCigwyK5PMQ0CQCAEydXit1rYOdai1dXicqnUA1vtHQp6TcLITSHJ+J3t/P9e1LnL23idZSest9zY5Wbw4SzNmbNfEia9owoTVmj59k6ZMWa+HH16uRx5Zoxkztmv16jf16qtfaMeOz7R27btatChT8+ala/78TC1f/ketWfNXvfzyX7RgQbqeeGKXpk7dpOTkF3XHHVN1yy0T1KvXZA0ePFtjxy7WpPErNfnRVZr2+EYtemG/spYs0dYnntLyR6fppSlPaM+zC/XB5s36fNcupS9eppWTpmnBg+PVvtkVan9FC738+G81c/C9Su7RV8Nu6KlxfQfoxYfH6MXxE/TIbYN1e/tb1K1FO/W+8hoN6dxd997YU8O799aYW+/QYwMHa+aQYZo7dLjmDh+lZx8cq6UTHtOGKVP0yqRJenniFK2dPFUrxk/QnFEPae6IZC18eLy2zHpKv1+6VH9ZtUZvvLRGb768Rh9t2qQvdu7U92lpOpqVpV+dc452zZ2rX9LT9a+dO/XGy+u09/klSnl6vvY8t0h75y3UocUr9KeXX9G2bZ9o377vtHfv17n/TvxSr7/+rTIyDisr66hef/1bbd78kVavfkdr1ryr7ds/LbPf/pfzd4IftGvXl9qx4zNt3vyhNm/+h1JSPtdrr30V1S/aXsz5yA0sAAAQcX+1nN9YFaqxmb3joEtpcLqgkehLVtZRJSYm6Y8vveS+TJgczcpStWqnaMWK37muQnITsqC9Y8xHUk5T3Au7XHWV5owe7b5wIbmhTRs9nZxcrGujoK7vww0sAADg0mgz+8hyfmV7FzMbbmYfmtlDLkuVAAsayZcdOz5RhQoV9ENamvsyhaRRoys1ZcoK1zVIbkIWtPHGfCTlNMW9sF7t2tr93HPuCxeS0f37a0iPHsW6Ngrq+j7cwAIAAC5VNLMHzewvZvZ97p/JdvyPzZQXLGgkX557brdq1z7ffRGPdO06UHfeOc51DZKbkAWtujEfSTlNcS76IS1NFSpU0Cc7drgvXEgWTZigXzdtWqxro6Cu78MNLAAAgNLDgkbyZfToOWrd+nr3RTwyYsRv1a5dD9c1SG58vKAxHwOU4lz0h5UrlZSYqKNZWe4LF5KDL76oWjVrFuvaKKjr+/h4PgIAgChVIeTtih4pj1jQSL707Hmf+vcv3uunuMpTT21RvXqXuK5BsnNeM63Ad2AxH0m5THEuemnqVLW47DL3ZT3y1d69MjN9uWdPkddGQV3fhxtYAAAg0r4NefuomR0pJOURCxrJl2bN2mrChEXui3hk48b3FBNTqcx+WyApfhITq4UuaMxHUm5TnIsmDBqkAV27ui9bRM467TSlLVxY5HVRUNX34QYWAACItNYhb//aI+URCxrJl5o1a2nx4kPui3gkI+OwYmPjtG7d266rBD4LF+4PXdA6G/ORlNMU56Ie7dpp5v33uy9bRNo1b64F48cXeV0UVPV9uIEFAABQeljQSF527/5COf9/+Np9GY9kZ0v16/+PZs5c77oKyfb1gsZ8DFCKc9El9epp6+zZ7ssWkWG9eumBfv2KvC4Kqvo+Pp6PAACgHLjZzC7OfftXZrbfzPaa2fnOGpUMCxrJy8KF+3XGGbWVnV38XynvItnZUseOfXTvvVNdVyHZ+Ra0fsZ8JOU0RV3wc3q6KsXE6P1Nm9yXLSLPPvywOrVqVeR1UVDV9+EGFgAAcOkvZnZu7turzewlM1tkZlucNSoZFjSSl3Hj5qtFi/bKzo7+G1hDhkxR5879XFch2fkWtL8Z85GU0xR1wZ/XrlV8bKyOZGa6L1tE9s6bp7pnnVXkdVFQ1ffhBhYAAHDpm9w/K5jZl2Z2ipnFmdnnzhqVDAsayUufPiPVp8/9ys6O/htYM2as00UXNXFdhWTnW9CYj6TcpqgL1s2YoaYXX+y+aDHyr507ZWb6bt8+z+uioKrvww0sAADg0udmlmBmzczsj7nHYiz/byosT1jQSF5atuygsWPnKTs7+m9grV37Z8XGxisz84jrOoFPyIL2hTEfSTlNURc8NmSIbuvc2X3RYuRoVpZqVK+u7OXLPa+Lgqq+DzewAACASy9bzo/DHDSzSbnHGljOj86URyxoJC+1ap2jBQv2KTs7+m9gpaf/rJiYStq06X3XdQKfkAVtrTEfSTlNURfc2qGDHh861H3RYuaqxo21bPJkz2uioKbvww0sAADgUnUzm2pmj1rOj8aYmXU1sxHOGpUMCxrJ95fs3bu/UHZ29N/Ays6W6tW7RLNnb3NdJ/AJWdDOMeYjKacp6oJGF16oDbNmuS9azNzdvbvGDhzoeU0U1PR9uIEFAABQeljQiLKzpSVLMlSjxhl5j50X8sixN9u2vVn33z/TdZ3Ax8cLGvMxQPE6eTgjQ7FVquivr7zivmgx8+SoUbrp17/2vCYKavo+Pp6PAAAgSvUPeftOj5RHLGhE2dnSxImLdfnl1+Q9dl7II8fevOuu8brxxjtd1wl0Jk9eFrqg3WfMR1JO43XynQ0bVKVyZf2Snu6+aDGTMmeO6tep43lNFNT0fbiBBQAAIu3NkLf/Xkjed9CrNLCgEWVnS/37j9Ytt9yb99h5IY8ce3Pq1JVq2LCl6zqBzvnnXxq6oH1gzEdSTuN1ctMTT6jhBRe4L3kC+XDrVlWsWFE/HjxY6DVRUNP34QYWAABA6WFBI8rOllq3vl6jR8/Je+y8kEeOvbly5R9UtWp1ZWUddV0p0PHxgsZ8DFC8Tk4bNky927d3X/IEcjQrS1UTEvSnVasKvSYKavo+Pp6PAACgHIg1s8oFjlXOPV4esaARZWdLtWvX0/PP78l77LyQR469mZb2gypUqKCUlH+6rhTohCxopxnzkZTTeJ3s36WLJg8e7L7kCaZZgwZaM316oeejoKLvww0sAADg0h4zu7rAsavN7FUHXUoDCxpRWtr3uTeCPs075ryUR0If1q59vp57brfrSoFOyIKWasxHUk7jdbJZgwZa63EjKFpz+/XXa9I99xR6Pgoq+j7cwAIAAC59YWaVChyrlHu8PGJBI1qx4veqVu2UfD+K57yUR0IfFvzRRxL5hCxoXxrzkZTTFHbiSGamEuPj9ebq1e5LnmCK+tHHKKjo+3ADCwAAuPS5mcUVOBZnOYtbecSCRjRlygo1atQq3zHnpTwS+rDgi8+TyCdkQfvCmI+knKawEx9s2aKYmBj9dOiQ+5InmKJefD4KKvo+3MACAAAu7TGzIQWO3WM5PzpTHrGgEQ0YMEbdug3Kd8x5KY+EPpw0aYmaNGnjulKgU+BHCJmPpFymsBNbZ8/Wxeed577gSeTdjRtVuVIl/ZyeHvZ8FFT0fbiBBQAAXLrSzH4ws81mNtPMNuU+buWyVAmwoBG1bn29kpOfznfMeSmPhD5cvjxbSUmn8psIHSZkQbvWmI+knKawE9OGDVPP665zX/AkciQzUwlxcXprzZqw56Ogou/DDSwAAODapWY2x8y2mtnc3MflFQsa0Zln1tG8ea/lO+a8lEdCHx77TYQ7dnziulZgU2BBYz6ScpnCTvTt1EmPDRnivuBJpnmDBlo9bVrYc1FQz/fhBhYAAEDpYUELeFJTv5aZaffuz/Mdd17MIwUP1alzoebO3em6VmDj4wWN+RigFHai4QUXaMOsWe4LnmQGdu2qCYMGhT0XBfV8Hx/PRwAAUE60MrP5ZrYl93FTM2vtrk6JsKAFPAsXpum008467rjzYh4peKht2+4aOXKW61qBTYEFjflIymXCHfw5PV2VK1XSexs3ui94knli5Eh1u+aasOeioJ7vww0sAADgUm8z+8ZyFrRvc481M7PXyvBj3mJmb5vZ92b2lpl1L+L6iWZ22HL6fZf758pCrmVBC3jGjHleLVt2OO6482IeKXho0KAJ6tp1gOtagU3IgjbAmI+knCbcwT+tWqXE+Hgdycx0X/Aks2vuXF1w7rlhz0VBPd+HG1gAAMClP9n/vSDxV7l/xprZZ2X08VqY2X/NrJuZxZjZzZbzoshNPZ4z0cz2FfP9s6AFPD173qfbbnvwuOPOi3mk4KFp01arQYNmrmsFNiEL2lvGfCTlNOEOvjR1qlpcdpn7ciXIP1NSVKFCBX2flnbcuSio5/twAwsAALj0dcjb/5v7Z4WQt0vbi2b2SoFj681sgcdzWNBIsdOkSRtNmrTkuOPOi3mk4KG1a/+s2Nh4ZWYecV0tkAlZ0JiPpNwm3MGxAwdqULdu7suVIEezslSjenVlL19+3LkoqOf7cAMLAAC49Ecza5L79rGlrJmZZZfRx/u9mT1c4NjYIj7eRMv50Zh/m9nfLefHY84r5FoWtAAnK+uoqlU7RStW/O64c87LeaTgofT0n1W5chVt2PCO62qBTMiC9oYxH0k5TbiDN7Rpo6eTk92XK2GubtpUiydOPO54FFTzfbiBBQAAXLrdzD4ws7st57VTbjOzv5pZnxN8P4vN7KiZHcn9s2COvWbMu2Y2uMBzh5jZ3zzedwMzOzf37bPMbEXu+0kIcy0LWoCzbdvHqlixotLSfjjunPNyHgl3+MILG2nWrA2uqwUyIQvaPcZ8JOU04Q7WPessvTZvnvtyJczQnj314G23HXc8Cqr5PtzAAgAArg0ws/9nOa+18r6ZjTiJ95FgZjU8Ui33upP5DoOCqljO68RcF+ZckpmpZ8+h6tt3lPr2HaU5c1Kc/4WPRCZPP71ddeteFPac83IeCXe4U6e+GjJkiutqgcmcOSl5M6Nnz6GhC9oAYz6ScpiCB75JTZWZ6fPdu92XK2GeHzNGHa+88rjjUVDNl/GYjwAAAL72opmtK3CsqNd4KejYgtY+zDm+wyDAGT58hq699paw55yX80i4w8OGTVP79r1cVwtkHH6HAfORlFoKHjiwaJHOrFnTfbFSyP6FC3X26acfdzwKqvk+fAcWAABw6XzL+fGYMWY2KPdxWWphOd/JcJOZVTKzHpbz6+K9fstWTzOrmft2LTNbZjnfCZEY5loWtACnc+fbNHjw5LDnnJfzSLjDTz21Reef38B1tUAmZEFrZMxHUk5T8MC8sWPVvkUL98VKIV/t3Ssz05d79uQ7HgXVfB9uYAEAAFemmNnh3PzLcl6f5Rcz+00Zf9weZva25Sxqf7acXxkf6k3LWRiP2WQ5L1D8HzP72HJepLiwRZIFLcCpX7+xZs5cH/ac83IeCXd48+a/Kyamkg4e/NF1vcAlZEFjPpJym4IHhvbsqQf69XNfrJRyTq1a2rdgQb5jUVDL9+EGFgAAcKGL5bwo8Z1mFpd7LC738Tdmdr2jXiXFghbQFPWb+5wX9Ei4w5mZR5SQUFWrVr3hul7gMn362mML2n3GfCTlNAUPFPab+8prOrVqpefGjMl3LApq+T7cwAIAAC6sN7N7Czk32Mw2RLBLaWJBC2jWrHlLcXEJysw8Eva884IeKexUw4YtNWXKCtf1Apc2bW7wWtCYj6RcJPTB0awsnZqUpOzly90XK6WM7t9fQ3r0yHcsCmr5PtzAAgAALnxoZqcVcu40M/sogl1KEwtaQDNlygo1bNiy0PPOC3qksFM9egxR//7JrusFLrVqneu1oDEfSblI6IMPtmxRpZgY/ffAAffFSikrp05Vy4YN8x2Lglq+DzewAACAC18Vcf7riLQofSxoAU2fPiPVq9ewQs87L+iRwk6NGzdfzZu3c10vcKlatXpRCxrzkUR9Qh+smzFD/1O/vvtSpZi3161TfGysfklPzzsWBbV8H25gAQAAF74p4vy3EWlR+ljQApomTdpo4sTFhZ53XtAjhZ1avjxb1aqdoqyso64rBiqJiUlFLWjMRxL1CX0wduBA3XXTTe5LlWIOZ2QoMT5eb65enXcsCmr5PtzAAgAALvxkZo955Ed31UqEBS2Aycg4rPj4RK1a9adCr3Fe0iOFnTp48EfFxFTSpk3vu64YqFSuXOXYgjbdmI+knCb0QfsWLfR8gRc890NaNWqkZZMn5z2Ogkq+DzewAACAC6lmtreIlEcsaAHM2rV/VmxsvNLTfyn0GuclPeJ1un79xpoxY53rioFK48atjy1o+4z5SMppjr1xNCtLNapXV+bSpe5LlXKG9eqlkX365D2Ogkq+DzewAAAASg8LWgAzefIyNWp0pec1zkt6xOt0164DNXDgI64rBio+XtCYjwHKsTfe37TJdy/gfiwvPvqorm7aNO9xFFTyfXw8HwEAACKOBS2A6dPnfvXuPdzzGuclPeJ1evToOWrVqrPrioGKjxc05mOAcuyNtdOnq8lFF7kvVAb540svKSkxUUcyM6VsbmBFIj6ejwAAABHHghbANG58lSZNWuJ5jfOSHvE6vWjRAdWocQYv5B7B+HhBYz4GKMfeGDNggAZ16+a+UBnk5/R0ValcWe9s2CBlcwMrEvHxfAQAAIg4FrSAJSPjsOLiErR69Zue1zkv6hGv0/v3/0cVKlTQjh2fuK4ZmPh4QWM+BijH3rjuiis0b+xY94XKKM0aNNDqadOkbG5gRSI+no8AAAARx4IWsKxe/abi4hKUkXHY8zrnRT1S1CX16l2ip57a4rpmYOLjBY35GKAoO+cF3E9NSlLWsmXuC5VR7uneXQ/fcYeUzQ2sSMTH8xEAACDiWNAClkmTlqpx46uKvM55UY8UdUnnzv00ePBk1zUDEx8vaMzHAEXZ2Xpv40ZVrlRJPx486L5QGWXe2LFq36KFlM0NrEjEx/MRAAAg4ljQApbevYfr1ltHFHmd86IeKeqSkSOf0K9/fZPrmoGJjxc05mOAouxsrZk+XU0vvth9mTJM5tKlqlm9uo5mZbmuEoj4eD4CAABEHAtawNKoUStNnrysyOucF/VIUZfMm/eaatU613XNwMTHCxrzMUBRdrYeuv123dO9u/syZZj/HjigmJgYfbh1q+sqgYiP5yMAAEDEsaAFKOnpPys2Nl5r1rxV5LXOy3qkqEv27v1KZqZXX/3MddVAxMcLGvMxQFF2tto1b64XHnnEfZkyTsMLLtD6mTNd1whEfDwfAQAAIo4FLUBZvPiQqlevoczMI0Ve67ysR4pzWd26F+nJJze7rhqI+HhBYz4GKD8dOqT42Fi9tWaN+zJlnEHduumh2293XSMQ8fF8BAAAiDgWtABl2LDpxX5tKOdlPVKcy2666S7dfvtDrqsGIj5e0JiPAcqBRYt02imn6GhWlvsyZZwlkyapVaNGrmsEIj6ejwAAABHHghagtGrVWaNGPVmsa52X9UhxLnv00RfVqFEr11UDER8vaMzHAOXxoUN1c9u27otEIO9s2KAqlSvrwIH/uq7i+/h4PgIAAEQcC1pAkpFxWImJ1bRixe+Kdb3zwh4pzmXr1/9NlStXYUGLQHy8oDEfA5SOV16pp5OT3ReJQI5mZalWzZpauHC/6yq+j4/nIwAAQMSxoAUky5dnq2rV6srIOFys650X9khxLsvKOqoaNc5gQYtAfLygMR8DkvT0X1Q1IUF/fOkl92UilB7t2mnYsGmua/g+Pp6PAAAAEceCFpCMHPmEWre+vtjXOy/skeJe2rZtdw0bNt11Xd/Hxwsa8zEgWbIkQ6cmJelIZqb7MhHKk6NGndC/E8jJxcfzEQAAIOJY0AKSq6++USNG/LbY1zsv7JHiXjpy5BNq0+YG13V9Hx8vaMzHgGTEiN/qxquvdl8kgslculTVqp1SrN9KS04+Pp6PAAAAEceCFoBkZh5RUtKpWrIko9jPcV7aI8W9dMmSDCUlncqCVsbx8YLGfAxIWre+Xk+MHOm+SATzc3q64uIStHr1m66r+Do+no8AAAARx4IWgLz00h+VkFBV6em/FPs5zkt7pLiXpqf/rNjYeK1Z85bryr6Ojxc05mMAkvMLLpKUvXy5+zIRTvPm7TR27DzXNXwdH89HAACAiGNBC0CSk5/WlVd2PKHnOC/tkRO5/PLLr9Ejj7zgurKv4+MFjfkYgKxY8TslJibpcEaG+zIRzqBBE9S5822ua/g6Pp6PAAAAEceCFoC0bXuzhg59/ISe47y0R07k8rvuGq8uXfq7ruzr+HhBYz4GIKNGPamrrurivoiDzJ27U2effZ7rGr6Oj+cjAABAxLGg+TxpaT8oIaGqVqz4/Qk9z3lxj5zI5XPmpOjss89TVtZR17V9Gx8vaMzHAOTyy69RcvIz7os4SGrqN6pYsaK2bfvYdRXfxsfzEQAAIOJY0HyeWbM2qnbt80/4Bo7z4h45kcvT0r5XbGyc1q79s+vavo2PFzTmo8+zc+e/FBMTo+3b/+G+jINkZ0uNG1+lcePmu67i2/h4PgIAAEQcC5rP07nzbbr99odO+HnOi3vkRJ9y1VVdNGLEb13X9m18vKAxH32esWPnqVGjVsrOju6ZV1bJzpaGDZumNm26uq7i2/h4PgIAABynkZltN7NPzeyombUr5vMmm9knZvadmaWa2aWFXMeC5uMcPPijEhOTtHRp5gk/13l5j5zoU8aMeV5NmrRxXdu3cbigMR9JidKiRXuNGvWksrOje+aVVbKzpdWr31RsbLzS0n5wXceX4QYWAAAIkovN7C4za2pmR6x4C9poM/vQzBqYWayZPW5m/zCzhDDXsqD5OLNnb9OZZ9Y5qdd/cl7eIyf6lG3bPlZMTIz27PnSdXVfxuGCxnwkJ53du79QTEwlbd36obKzo3vmlVWys6WsrKM6++zzNHv2Vtd1fBluYAEAgKAq7ncYvG9mw0Iex5jZv82sX5hrk8xMq1a9oS1bPtDWrR+G5KO8bNv2sbZv/4e2b/+Hduz4RCkp/9TOnf/Srl3/1quvfqbduz/X7t1faM+eL7V371dKTf1G+/Z9p/37/6O0tB908OCPSk//RZmZR5z/ZTJI6dp1oPr2HXVSz3Ve3iMn87SLLmqiKVNWuK5eJsnMPKKDB3/U/v3/UWrq19qz50u9+upn2rnzX9qx4xNt2/axtm79SFu2fKDNm/+uTZve18aN72njxne1ceO72rDhHW3Y8I7Wr/+b1q//m1555a/5sm7dXzyzbFl2NCxoZT4f88/I/PPx2Iw8Nh9TUj7Nm5HHz8ev9frr3xaYjz8rM/MIv2wggpkwYZEaNGie99h5IQc59mbv3sPVo8cQ13XKJFlZR3Xo0E9KS/teqanf6LXX/le7d3+unTv/pZSUf2r79n/k/rP8YYH5+F6++XhsRpbT+QgAABBxxVnQknKva1Hg+E4zm1XI9apQoUK+WM5ftsosMTExqlIlVnFxCUpMTFL16jVUs2Yt1ap1jmrXrqe6dS/SBRc01CWXXK5GjVqpefN2uuqqLmrXroc6d75N3bvfoz59RqgGJ+YAABUoSURBVGrgwEc0dOjjSk5+Ro8++qKmT1+ruXN3avHiQ1qz5i1t3/4P7dv3XSCXwvT0n5WUdKoWLTpwUs93/gl45GSeNmjQBLVv39t1dc9kZh7R5s1/15w5KRo/foHuuWeSune/R9dee4uaNWuriy9uqrp1L9IZZ9RW9eo1FBeXoIoVK57QP3sVKlRQxYoVFRMTo5iYSqpUqbIqVaqsypWrqEqVWMXGxoUkPmzi4hLyJTY2PhoWtDKdjxUrVozofKxcuUrufKympKRTdeqpp+v008/W2Wefpzp16utXv7pMF1/cVI0aXanLL79GrVp1Utu23dWpU1916zZIt946QgMGjNGQIVP0wANPafz4BXr88VV6+untWrgwLe+m3N69XwX2PyxcdVUXDR8+I++x80IOcuzNuXN3qVatc6L635VZWUe1a9e/NX/+65o8eZmGDn1cvXoNU4cOt6plyw5q0KC56tW7RGeeWUennHKaEhKqKiamUonm47EZeWw+5p+R5Wo+AgAAlMhiy1mkjuT+WTCvhXlOcRa0c3Kvu6jA8VVmNj/M9UX+iExW1lFlZh5RZuYRZWQcVnr6L0pP/0WHDv2kgwd/1IED/1Va2g9KS/te+/Z9p9df/1apqV/rtdf+V3v2fJnvv3Ru2/axtmz5QBs3vqf16/+mdeve1qpVf9KKFb/X0qWZWrTogF54IVXPPvuqZs/eqpkz1+s3v3lZEycu1pgxz2vUqCd1332/0Z13jlPfvqPUvfs96ty5n66++kY1b95ODRo0V926F+n0089WfHxivoUwKelUnX32eapfv7GaNGmj1q2vV4cOt6pbt0Hq02ek7rxznO69d6pGjpyl0aPnaMyY5zV+/AJNmLBI48cv1PjxC/TIIy/o4YefVXLyMxo58gkNGzZd9947VUOGTNHgwZM1ZMgU3X//TI0ePUdTp67UvHl79corf1V6+i8R/8v+3Lk7dfrpZ5/0cup8WynG0nUiWbo0U1WrVld6+s+u6+clJeVT/eY3L6t37+Fq0KCZYmPjFRMTozp16uuKK65T164DNHDgWI0c+YQmTlysmTPXa+7cXVq06IBWrvyD1q17W5s2va9t2z7Wrl3/1p49Xyo19Zu87+w5dOinvO98LMvFtAx+RKZczcdjMzJ0Pqan/5w3I4+fj99o796vjpuPOd8J8qE2bXpfGza8o3Xr/qLVq9/UypV/0LJlWXrxxYOaP/91Pffcbj399HbNmrVBjz++SpMmLdUjj7ygBx+crWHDpunuux9V//7JuuWWe3X99berbdub1aJFezVs2FLnn3+patU6V1WrVs+7GVehQgUlJiapVq1zdf75l6pRo1a68sqOuu66nrrxxjvVu/dwDRw4VkOGPKYRI36r5OSnNWbMcxo3bn7IfFyocePma8yY55Sc/IxGjXpSw4fP0H33/SZkPj6m4cNnKDn5aU2cuFhz5+7UqlVvKC3t+4j/s7d371eqVKmyNm58N++Y84HgIMfePHjwRyUkVNWKFb93XSkv+/Z9p9mzt+nOO8epWbO2Sko6VWamWrXOVdOmV6tTp77q3z9Zw4fP0PjxCzR9+lrNmZOihQv3a8WK32nNmre0ceO72rr1I6WkfKrdu79QaurX2rfvu3zzMSPjcHmbjwAAABGXYGY1PFItzHPK7DsMevYcqr59R6lv31GaMyfF+V9cSyvp6b9oz54vtWnT+1q58g964YVUPfHEJj322HKNGfOchg2brkGDJuTdDLv++tvVvn0vXX31jWrd+npdeWVHXXHFdWrRor1atGivVq06qU2bG/TrX9+ka6+9RR079lGXLv11ww13qGvXAerSpb/at++lNm26qnHjq1S7dr3c/2Ibr4YNW+rWW0fo+ef3ROSGVvv2vdSnz8iTfr7z//E8cjJPy8w8opo1z9S8ea85rb99+z80YsRv1ahRK8XExOjii5uqd+/hmjr1Ja1b97YOHfrJ9Ze3WJkzJyVvZvTsObS0FzTmYwSSmXlEqanfaOvWj7Rq1RtauDBNs2dv09SpL+mRR17Q/ffP1N13T1T//snq0WOIunYdoA4dbtU113RTmzY3qFWrTvnmY8uWHdS69fW6+uob1a5dD3XocKs6d74tbz7ecMMdec+//PJrVLfuRUpMrKaYmBj96leXqWvXAZo+fY327/9PmX/uo0fPUYMGzfIdc/4/iIOEPmzXroeGDHnMaaV9+77To4++qDZtuqpKlVidc86v1LXrAI0bN1/Ll2dr377vXH/JipUyno8AAADlQkle4+Uz83iNF16kuOySkXFYa9f+WY89tlw33zxYNWvW0imnnKZevYZp06b3y+Rjrlv3tqpUic17ceKTifMvnEdO9qk33XRXiW7qnWyyso5q/vzXdd11PVW5chW1bNlB48bNV0rKp66/lKWSKPkOA+ZjOUxW1lFt3fqRZs3aoAEDxui88y5WbGy8rr32lpP+8eeicujQT6pV6xxNn74m33HnXwwHCX04ceLi427qRSqvvPJX3XrrCCUmJql+/f/RsGHTtG7d266/PKWSKJmPAAAAERNrZnGWs6B1zH0c43F9spl9YDm/Gj7ezKaZ2cfGb9mKimRkHNYLL6SqU6e+qly5ijp16qu1a/9cqh+jS5f+6tZtUIneh/MvlEdO9qnPPvuqTj31dB08+GPE6i5ZkqFmzdqqWrVT1L9/sjZufM/1l6/U43hBYz76LGvWvKX+/ZOVmFhNTZq00dy5u0r1/Y8bN1/16l1y3I9XO//EHST04Z49Xyo2Nl6rVr0RsQpbt36krl0HqkqVWHXu3E8vvngwql+H62TCDSwAABAkde3/XgsmNI+GXPOmmY0p8LxJZvapmf3HzFItZ1kLhwXNYTZufE89egxRbGyc+vdP1uuvf1sK7/NdVakSm++1XU4mzr84HjnZp2ZlHVXduhfpsceWl3nNlJR/qn37XoqLS9DAgWO1d+9Xrr9sZRaHCxrz0cfZu/crDR36uKpVO0XXXNNNmzf/vcTvMz39Z9WuXS/sbyR1/gk7SMFDN910l26+eXCZf+i0tB80cOAjio2NV8eOfUr876toDjewAAAASg8LWhRk1ao31LTp1TrttLM0a9aGEr2vbt0GqUuX/iXu5PyL4pGSPD05+RlddlmLMquXlXVUEyYsUrVqp6hjxz7aseMT11+uMo+PFzTmYxTk1Vc/00033aW4uAQNGzatRK8hOGnSEp177gVh34fzT9RBCh5aseL3iotLKNMb7gsW7FOdOvXVoEFzrVjxO9dfgjKPj+cjAABAxLGgRUmyso5q8uRlSko6VZ0799Nrr/3vCb+PjRvfU5UqsaXy2iHOvyAeKcnTU1O/UUJCVS1bllXq1V599TO1atVZZ5xRW089tcX1lyli8fGCxnyMorz44kGdd97FuvTSK07qx64PHvxRderU14QJi8Ked/4JOki4w40atdIDDzxV6h8uPf1n9e+frPj4RI0c+YQyMg67/vQjEh/PRwAAgIhjQYuy7NjxiVq3vl6nnXaWnnhiU7Gft3fvVzr//EvVu/fwUunh/AvhkZK+i1tuuVdduw4o1VoLFuzT6aefrXbtevj6xwXDxccLGvMxypKW9oP6909WXFyChg+fUezvxsrMPKIOHW7VpZdeofT0n8Ne4/yTc5Bwh6dOfUl16lx43GuElSRbtnyghg1b6sILG2ndur+4/rQjGh/PRwAAgIhjQYvCZGUd1aRJS5SUdKo6duyjV1/9zPP6Q4d+UrNmbdW69fUl+vGa0Dj/InikpO9i9eo3FRsbp927Py+V/62GD5+huLgEPfTQXN+9AHFx4uMFjfkYpVm06IDq1r1IDRo0K9aLjg8YMEa1a9fTrl3/LvQa55+Ug4Q7fOjQT6pZs5bmzEkplQ/zzDM7lJR0qnr0GKK0tB9cf8oRj4/nIwAAQMSxoEVxUlL+qbZtu6tq1eq6++5Hw/5Y4d69X6ljxz665JLLtW/fd6X2sZ1/8h4pjXfTvHk73X77QyV6H/v3/0ft2/dSrVrnlsmPJJaX+HhBYz5GcQ4c+K8GDhyr2Ng4de06UBs2vHPcNYcO/aT775+p6tVrFPmdP84/IQcp7NTdd09U48ZXlei7sLKyjuq++36j+PjEsC+aH5T4eD4CAABEHAtaOcgLL6SqefN2Skysps6d+2nIkCl67LHluuGGOxQbG6/Gja9SSsqnpfoxnX/SHimNd7N69ZuKi0vQ4sWHTur569f/TRdc0FCXX35Nkd8h5/f4eEFjPpaDrF//N3XtOkBVqsSqTZuuGjjwEU2atFR33PGwatQ4Q7Vr19PChWlFvh/nn4iDFHZq377vVLv2+Sf9Wlipqd+obdubdfbZ52nlyj+4/jSdxsfzEQAAIOJY0MpRFi06oMGDJ6tTp7667LIW6t17eLF+fOZk4vyT9Uhpvathw6arTp36Skv7/oSeN3PmeiUmJqlfvwdK7Uc2y3N8vKAxH8tRNm58TyNG/Fbdug1SkyZt1L59Lz377KvF/i4i55+Ag3idXrBgn+LiEk74NatWrXpDdepcqJYtO2j37i9cf4rO4+P5CAAAEHEsaCRsnBfwSGm9q4yMw2rYsKX69BlZrOvT0n5Qv34PKDExSTNmrHP9ZYia+HhBYz4GKM4LOEhRl/Tr94Auu6xFsW7UZ2Ud1YQJixQfn6i7754YmN8yWFR8PB8BAAAijgWNhI3zAh4pzXf3yit/VXx8ooYNm+a5cM2b95rOPfcCNWjQPHC/Rauo+HhBYz4GKM4LOEhRl6Sl/aDzzrtYHTv2UWrq14Vet3Hju7riimt1xhm19cwzO1x/WlEVH89HAACAiGNBI2HjvIBHSvtdLlmSoTp1LlSTJm20efPf844fOvSTnnxys9q2vVkJCVX14IOz+a6CMPHxgsZ8DFCcF3CQ4ly2Y8cnatmyg846q64WLNiXdzwr66iWLElXz55DFR+fqJ497+OflTDx8XwEAACIOBY0EjbOC3ikLN7t/v3/UY8eQ1ShQgVVr15DdetepOrVa+jMM+to4MCx2rr1Q9efdtTGxwsa8zFAcV7AQYp7aWbmESUnP6PY2DglJlZT7drn68wz66hq1erq1m2Qli7NdP2pRG18PB8BAAAijgWNhI3zAh4py3efkvKpVqz4vebO3amFC9NK9GvkgxIfL2jMxwDFeQEHOdGn7N37lVat+pPmzXtNc+ak6MCB/7r+FKI+Pp6PAAAAEceCRsLGeQGPREEFEhIfL2jMxwDFeQEHiYIKvo+P5yMAAEDEsaCRsHFewCNRUIGExMcLGvMxQHFewEGioILv4+P5CAAAEHEsaCRsnBfwSBRUICHx8YLGfAxQnBdwkCio4Pv4eD4CAABEHAsaCRvnBTwSBRVISHy8oDEfAxTnBRwkCir4Pj6ejwAAABHHgkbCxnkBj0RBBRISHy9ozMcAxXkBB4mCCr6Pj+cjAABAxLGgkbBxXsAjUVCBhMTHCxrzMUBxXsBBoqCC7+Pj+QgAABBxLGgkbJwX8EgUVCAh8fGCxnwMUJwXcJAoqOD7+Hg+AgAARBwLGgkb5wU8EgUVSEh8vKAxHwMU5wUcJAoq+D4+no8AAAARx4JGwsZ5AY9EQQUSEh8vaMzHAMV5AQeJggq+j4/nIwAAQMSxoJGwcV7AI1FQgYTExwsa8zFAcV7AQaKggu/j4/kIAAAQcSxoJGycF/BIFFQgIfHxgsZ8DFCcF3CQKKjg+/h4PgIAAEQcCxoJG+cFPBIFFUhIfLygMR8DFOcFHCQKKvg+Pp6PAAAAEceCRsLGeQGPREEFEhIfL2jMxwDFeQEHiYIKvo+P5yMAAEDEsaCRsHFewCNRUIGExMcLGvMxQHFewEGioILv4+P5CAAAEHEsaCRsnBfwSBRUICHx8YLGfAxQnBdwkCio4Pv4eD4CAABEHAsaCRvnBTwSBRVISHy8oDEfAxTnBRwkCir4Pj6ejwAAABHHgkbCxnkBj0RBBRISHy9ozMcAxXkBB4mCCr6Pj+cjAABAxLGgkbBxXsAjUVCBhMTHCxrzMUBxXsBBoqCC7+Pj+QgAAHCcRma23cw+NbOjZtauGM+ZaGaHzexbM/su98+VhVzLgkbCxnkBj0RBBRIShwsa85GUWpwXcJAoqOD7cAMLAAAEycVmdpeZNTWzI1b8BW1fMd8/CxoJG+cFPBIFFUhIHC5ozEdSanFewEGioILvww0sAAAQVCfyHQYsaKREcV7AI1FQgYQkShY05iMpUZwXcJAoqOD7RMl8BAAAiLgTWdC+M7N/m9nfLefHY84r5FoWNBI2zgt4JAoqkJBEyYLGfCQlivMCDhIFFXyfKJmPAAAAJbLYchauI7l/FsxrYZ5T3AWtgZmdm/v2WWa2wszeNbOEMNcmmZm2bftYqanfEJKXb1JTozauvzYkf7Zt+7i0FzTmI4l4XM81Zqk/UwbzEQAAIOISzKyGR6qFeU5xF7SCqpjZf83sujDnalvOX6wIIaSkqW2lg/lICPFbSms+AgAAlAslXdDahzlXwXL+UpVECCElSG3LmSeuMB8JIdEa1/MRAAAgYmLNLM5yFrSOuY9jPK7vaWY1c9+uZWbLzOx9M0ssw44A4ALzEQAAAACiQF37v9eCCc2jIde8aWZjQh5vspwXKP6PmX1sOS9SfH4kygJABDEfAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEHj/H+QFiMbpzF8ZAAAAAElFTkSuQmCC\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mglearn.plots.plot_decision_threshold()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       0.97      0.89      0.93       104\n",
      "          1       0.35      0.67      0.46         9\n",
      "\n",
      "avg / total       0.92      0.88      0.89       113\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, svc.predict(X_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "y_pred_lower_threshold = svc.decision_function(X_test) > -.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       1.00      0.82      0.90       104\n",
      "          1       0.32      1.00      0.49         9\n",
      "\n",
      "avg / total       0.95      0.83      0.87       113\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, y_pred_lower_threshold))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Precision-Recall curves and ROC curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import precision_recall_curve\n",
    "precision, recall, thresholds = precision_recall_curve(y_test,\n",
    "                                                       svc.decision_function(X_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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O+4z1nP5ww8/qEmTJtp///31zDPPaPbs2TrllFOUkZGR9hFIACLeqjwAv/pKuvxyafDgyq1DD5VC/lsGoJq4DcBAIBA85m/w4MFlbjto0KDgMYHxPDGkvJeAI+Nn+PDhys7ODrutJFp2R7yccfPNNys7O1urVq0Ku33QoEFq2rSpioqKJEl16tTRfffdF3PGkmDr27dv2O133323/H6/8vPzJUkrVqyQz+fTzTffHLbdrbfeKr/fr+XLl4fdX0kABgIBtWnTRqeeemrY1z333HNRn4OyFBQUqGfPnurcuXNw796aNWuUkZGhW2+9NWzbDz74QD6fT6+99lrwtljP5ahRo1SjRg2tXr06eFtRUZE6d+6sHj16VHi+VEQAIt6qPAD3Vb9+nD0MeMFtAObn5weP8Vu8eHGZ2y5atCi4bUngxEN5AfjCCy+E3T5t2jT5/X5t3LgxeFvJnrNIxx57rE488UQVFhaGrRdeeEE+ny8YZH369FHbtm01ZcqU4G2hSoLtn//8Z9jt8+bNk9/v16JFiyRJDz74oPx+f6ngLPn6kr2OkQH43XffyefzacaMGWFfV1hYqBo1alQqAAcMGKAmTZrom2++Cd728MMPy+/3a/Xq1WHPw549e1SvXj2NGjUquG2s57JXr1467rjjSt0+YcIEZWRk6Ndff63wjKmGAES8JUQABgJSs2bOy8CzZsVe337r6ZhASnIbgF9++WUw6jZv3lzmtps2bQpuu3Llyn36fhVR2ZNAHn/8cfn9/uDLs5ITLTfeeGOp+zjwwAPDji8MXX6/XwsXLpTkPNbhw4erdevW8vv9atWqVdhevFgngZTM+M4770jau6dv586dYdvt2rUrbM9gZAAuWrRIPp9Pb775ZqnH0KJFiwoH4I033qisrCy9++67YbffdtttMY8T9Pv9YS+px3ouDzjgAP31r38tdfvUqVPl9/v1XRpfToIARLwlRAAWFUn9+0vHHBN7NWokjRnj6ZhASkrHPYAVDcCbbrqp1H307t1bv/vd7/Txxx9r2bJlpdb27dtLfc3XX3+tsWPHyufzaerUqZIqHoAlewBDXyYN/fp47gGcOXOm/H6/nnzyyVKfK4m0vLy8qM/DmjVrgtvGei579eql448/vtTt48ePZw8gAYg4S4gArIhu3Zy3nANQtbw4BrBr165xPQZwyJAhatKkSanbY10HsDIBOGHCBDVp0iR4Nm9lNGrUSMOHD5dUdgD6/f5gAJYcA3j77beHbVeyZ3DFihVh9xd6DGDbtm11yimnhH3drFmzKnQM4AcffKBatWpF3XMnSatWrVJmZqYee+yxch93rOfymmuuUc2aNcOe96KiIh100EHq2bNnufebyghAxFtSBOD27VJGhnOW8IoVqbEirpIAeKa6zgKeO3euMjIy4n4WsCRNmTJFfr9fDz30kJYsWRI8Bq8q9gBu3bpVBx98sDp37qypU6dqwYIFmj17tu6++26dfvrpwW169uypyZMnKzc3V3l5eRoxYoT8fr/eeOMNSRXfAyhJ5513nmrWrKmJEyeGnQU8cODA4DbRzgJ+9NFH5ff7dckll2jevHm6//771aZNm3LPAt62bZuaNWumbt266cMPP9RHH30UXJ988klwuxtuuEE5OTkaM2aM5syZo7y8PM2YMUPnn39+8KXwsp7LH374Qc2aNVOnTp30zDPP6I033tApp5yizMxM/fvf/445XzogABFvSRGA330nNWki1a2bGqtGDeekFyARxOM6gIMGDdKiRYu0adMmLVq0SIMGDQrGX7yvAyhJO3bs0HnnnadGjRrJ7/eXug5gRQLQ7/dr3LhxUe9/y5Ytuvrqq9WxY0dlZWWpefPmOv744zVlyhRJ0u7duzV06FAdeuihqlu3rurXr69evXpp1qxZwftYs2aN/H5/uXsAJec6gDfddFPYdQDHjRsXdjHlkvuLvA7gvffeq/bt2ys7O1s9e/bU+++/rw4dOujSSy+N+fyV3Fe0FXkdwKefflpHH3206tSpo7p16+rggw/WiBEjtH79+go9l19//bXOOOOM4HUAjz766LSPP4kARPwlRQCmmtNOkyJezQE8U5XvBNKjR48y3wmkR48e1fJOIECyIwARbwRgNdu5U8rOdl4GBhJBVb8X8PTp00u9F3DXrl01ffr0ansvYCDZEYCINwKwmi1Z4rxTipnznsnlrWnTvJ4Yqa4qA7BEIBBQfn6+Vq5cqfz8/Lie8AGkIgIQ8UYAemD9emnt2rLX6tVSgwbS2297PS1SXTwCEIA7BCDijQBMUO+9JzVuLIW81zsQFwQgkHgIQMQbAZigbrpJysmRDjvM23XkkRLH7Kc2AhBIPAQg4o0ATFD5+dLs2d6uW2+V6tWTOG4/tRGAQOIhABFvBCBiuvJKqRLvF48kRQACiYcARLwRgIipRQvpqKOk886Lvi69VNqyxesp4RYBCCQeAhDxRgAipkcekSZNir4GD5aysgjAVEAAAomHAES8EYDYJ9ddJ/31r15PgapAAAKJhwBEvBGAqLSiIqlNG+nMM523tGN5tyZNkjZudPfzJADjr3379rqkEgfUrlmzRj6fr9T7+qaThQsXyufzhb0n8gknnKA+ffp4OFX1IQARbwQgKi0QkIYPlwYOZHm5zjrLeUeZjz5y9/MkAOPv008/1erVqyu8/e7du7Vo0SJt3rw5jlMltoULF8rv94cF4IknnkgARnzeCEDsIwIQSFJPPil16eIEuRsEYLjdu3d7PUJC8er5SNQA3FNNV+cnABFvBCCQpH73O2nyZPf3k4oBOH78ePl8Pi1fvlx9+vRRTk6OWrZsqXHjxoVtV/Iy48svv6xBgwapadOmatiwYfDzn376qfr376+GDRsqOztbxx57rN57771S32/hwoU6+eSTVb9+fdWuXVtHHHGEHnvsseDn27VrF/YS8IYNG3ThhReqVatWysrKUsuWLdW/f39t2rRJUuyXgJ966ikdccQRqlWrlpo0aaILLrhA+fn5Ydu0b99eAwcO1KxZs9SlSxfVrl1bRx55pP7zn/9U+HlbsWKF/vjHP6pOnTr6y1/+Evz8Sy+9pN69eysnJ0cNGjTQgAED9N1335W6n+nTp6t79+7Kzs5Ww4YNdeKJJ+rDDz8M+z7du3dXvXr11KRJE/Xt21cfRezKdhOAO3bs0LXXXqv9999fWVlZatGihc4++2z9+OOPYY8z0kUXXaT27dsHPy75OTz44IMaM2aMWrVqpYyMDC1ZskQ+n09vvPFGqfu44oor1KxZMxUWFgZvmzZtWtjP7bLLLtPPP/9c5mMgABFvBCCQhFaskGrVkn76yf19pWIATpgwQT6fTwcccIBuv/12zZ8/X6NHj5bP59PEiROD25UEYOvWrTVo0CDNmzdPr732miRp2bJlql27to477ji99NJLmjt3rk477TRlZWXp448/Dt7Hq6++qszMTPXp00fPPfec8vLydO+992r8+PHBbSKPATzppJPUuXNnPfvss3rvvff04osv6oorrtDatWslRQ/AadOmyefz6bzzztPcuXP16KOPqlmzZurcubN27NgR9r3atWunXr166eWXX9acOXPUrVs3NWzYsNyfcejzdscdd2jBggXBAHvooYfk8/l0+eWXa+7cuXr++efVpUsXdezYUdu3bw/ex6hRo+Tz+TR48GDNnj1bb775psaNG6fnnnsuuM3ll1+uJ598UgsXLtScOXN07rnnKisrSytWrAj72exLAP722286+uijVadOHd12221666239NJLL2nw4MH66quvgo/T7/eX+tqLL75YHTp0CH5c8nNo3bq1zjjjDM2ZM0evv/66CgoKdNBBB+lvf/tbqe/duHFjXXXVVcHbrr32WtWoUUPXXHON5s+fr8cff1z77befevfurUAZu+8JQMQbAQgkoauuco4DrAqpGoB+v1933XVX2O2DBg1SvXr1go+1JADPOuusUvfRt29fHXLIIWF7cgKBgLp06aIzzjgjeFv79u3Vq1evMueJDMA6derovvvui7l9ZAAWFRWpefPm+v3vfx+23X/+8x/5fL6w+2rfvr0aNWoU9vNcunSpfD6fnn322TLnLHneImfbvn276tevr8svv7zUnDVr1tSUKVMkSd98840yMjI0evToMr9PqKKiIhUWFqpz5876xz/+Ebx9XwPw0Ucfld/v1+zZs8t9nJFiBeCRRx5ZatvbbrtNOTk52rZtW/C2V155RX6/X0uXLg1+fUZGhm699dawr/3ggw/k8/mC/7MRDQGIeCMAgSSzc6fUoIEUskPFlVi/aAIBaetW79e+HONY8gv+22+/Dbs9Ly9Pfr9f77//vqS9AfjUU0+FbVdQUKDMzEyNHz9ehYWFwbVnzx6NGDFCjRs3liStXLlSPp9P06dPL3OeyADs06eP2rZtqylTpmj58uWlto8MwC+++EI+n0+PPvpo1Ps+++yzwz7u169f2Da7d++Wz+fTnXfeWeacJc/bunXrwm6fP3++/H6/3n777VLPx+GHHx4M6Iceekh+vz+4py2W+fPnq0+fPmrcuLF8Pp98Pp/8fr9OOeWU4Db7GoDnnHOOWrVqVaHHGSlWAN5yyy2ltl27dq38fn/Yz+TMM89Uly5dgh8//PDD8vv9Wr16dannrV69eho1alTMGQlAxBsBCCSZ5cudi3CbSSGvRO6zWL9otm51vofXa1/+81TyC37nzp1ht69YsUI+n0/PP/+8pL0B+NZbb4Vtt379+mCUlARK6MrIyJAkvf/++/L5fJozZ06Z80QG4KZNmzR8+HC1bt1afr9frVq10s033xz8fGQAluzpe/PNN0vdd+/evdW3b9+w73XBBReU2i7y5e9oSp630L2ekjRz5syoz0PJc1QSZbfddpv8fn/YS9KRPv74Y9WsWVOnn366XnvtNS1evFjLli1T165dw+JuXwPw5JNPVs+ePSv0OCPFCsBHHnkk6v2ceOKJOvHEEyVJW7ZsUa1atXTHHXcEP3/bbbeV+bxdfPHFMWckABFvBCCQhF5/XWrdWqqKExLTbQ+gz+crtQcwLy8vbLsdO3YoIyNDV111lT7++GMtW7as1JKkr776ap/2AIb6+uuvNXbsWPl8Pk2dOlVS7D2AoSeWhN535B5AtwFYVFQUdntubm5wT2m05+Lrr7+W5Byn6Pf7gx9HM3bsWNWuXbvU92jXrl2VBOC5555b7h7ASZMmye/3lzqjt3///lEDMNqeV8l5uTkjI0Pfffedpk2bFvxzialTp8rv9ysvLy/q87ZmzZqYMxKAiDcCEEhCp54qlfO7vMJS+RjAyJc8L7/8ctWrVy943FZJZEQGoBS+d6csHTp0qPQxgNE0atRIw4cPlxT9GMAWLVroD3/4Q9jXlOyBfOCBB8K+V1UH4LZt21SvXr1SZ1FHWrVqVbnHAI4cOVL16tUL+x4lYV4VAThjxoxyjwF89tln5ff79cknnwRv++WXX9S4ceNKBeC2bduUk5Oj22+/Xccdd1ypvy+rVq1SZmZm1HAvDwGIeCMAgSRTUCD5/c7LwLVr713lHN8fU6oGYORZwKNGjZLf7w87nivWHkDJeamybt26OvnkkzVr1iy98847eumllzR27Fhdf/31we1ee+21sLOA3377bT3wwAMxzwLeunWrevbsqcmTJys3N1d5eXkaMWKE/H5/8LIi0c4Cnj59uvx+vwYOHKjc3Fw98sgjatGihQ466KCwl7rjEYCSs3evRo0aGjp0qF577TUtXLhQM2fO1ODBg8NOLhk9erQyMjKCZwHPnTtXEydODL7sPm/evODjyMvL04MPPqhWrVqpTZs2pQIw8p1AKhKAe/bs0THHHKO6desGzwJ++eWXNXTo0OCxiVu2bFGDBg105JFHavbs2XrxxRd11FFHqV27dpUKQMk55nC//fZTRkaGZsyYUerzN9xwg3JycjRmzBjNmTNHeXl5mjFjhs4//3wtXLgw5v0SgIg3AhBIQt99J4swuBAAACAASURBVH3xhbPef1/KyHCODdwXqRqAfr9fn3/+edh1AEOjTCp7D6DknORx7rnnqnnz5qpVq5batGmj008/XXPnzg3bbsGCBerbt6/q1q2runXrqmvXrnr88ceDn+/QoYMuvfRSSc4JGUOHDtWhhx6qunXrqn79+urVq5dmzZoV3H7NmjXy+/2lrgM4c+ZMde3aNXg9uYsuukgbNmwI26ZDhw668MILSz0Wv98fdpxhrOctIyMjagBK0ty5c9W3b9/g9Q47deqkyy67TF9++WXYdqHXvWvcuLH69OkTdp2/+++/Xx07dlROTo569eqlvLw89enTJ+xYxlh7AEO3iWXHjh0aM2aM2rdvr6ysLLVq1UoDBgwIXmdRcvae9urVS7Vr11bnzp01c+ZMXXLJJaUCMPJEj0hz5syR3+9X7dq1w84IDvX0008HL01Tt25dHXzwwRoxYoTWr18f834JQMQbAQgkuXvucS4Kva9SOQBjhQyQ6AhAxBsBCCS57t2lVq2k3r2l446TyjiuPCoCEEg8BCDijQAEktyHH0rPPy+NGyfl5Ei//FK5r0/VACzrpUwg0RGAiDcCEEgRgwdLEW/UUCGpGIBAsiMAEW8EIJACduxw9v79/vdOBJa3rrhC2rzZ+VoCEEg8BCDijQAEUsBvv0mTJkk33VT+uugiKTNTKjl5lAAEEg8BiHgjAIE0M3q0NGDA3o8JQCDxEICINwIQSCMFBVKjRs5ewClTpPvvl9auJQCBREMAIt4IQCCNbN8unX++dMYZ0h//KJlJ77xDAAKJhgBEvBGAQJqaNk3q2lXassX5RbJu3Tpt3bqVxWIlwFq3bh0BiLgiAIE0FAhIhx8uDR0qzZ1boMaNW5T8MmGxWAmyWrRooYKCgqj/DhOAcIsABNLQb79JPXpIBx7orP33L1DHjlvVseNWNWmyVQ0aeL8HhMVK9xUr/iQCEO4RgADCXHihNGyY11MAKAsBCLcIQABBmzZJWVnSggXSxo0VX2XsqAAQBwQg3CIAAQTNneucGVzZ9ec/ez05kF4IQLhFAAIIs2tX5daRR0r33uv11EB6IQDhFgEIYJ8tXSrVri1t2eL1JEB6IQDhFgEIYJ9dd52UkSE1a7Z3zZ3r9VRA6iMA4RYBCGCfbd3q7AVculR6/XXJ55NWrfJ6KiD1EYBwiwAEUCXGj5dOPdXrKYD0QADCLQIQQJVo10464ADptNO4LAwQbwQg3CIAAVSJN9+ULrrICcHCQq+nAVIbAZg+JprZejP71cwWmtkhZWx7pJm9bWY/m9mPZvaSmbWNsS0BCKDK9OkjTZrk9RRA6iMA08M1ZrbWzA42sywzu93MvjeznCjb+sxso5ndY2aZZlbbzJ4zs/dj3DcBCKBKfPmlc1HogQOlq65y1kMPeT0VkJoIwPSw2syGh3ycYU7knR9l2wZmVmRmh4Xc1s/MdsS4bwIQQJXYsEEaM0YaNcpZhx8u/eEPXk8FpCYCMPXVM7OAmR0Vcfs8M7s7xtfcW7yyzQnCF8zsyTLunwAEUKX27JFat5ZefdXrSYDURACmvtbmBGDniNtnmdn0GF9zvJl9YWZ7zKzQzJaaWdMY2xKAAKrciy9KNWtKU6dKDz/srI8+8noqIHUQgKmvsnsADzCz3WY2xMxqmLMXcKKZfVP852j3TwACqFJz5jgv/5asZs2kc87xeiogdRCA6SHaMYA/WvRjAM80s18ibqtrTkT2jLJ9PTPTsGHDNHLkSI0cOVK5uble/70GkEIKCqQmTaS33vJ6EiC55ebmBn9XDxs2jABMA6PNbI05l37JNrM7zGydRT8LuK05J3xcbk4o1jKz8Wa21czqR9mePYAA4mrGDKl5c+nDD6Vt27yeBkgN7AFMHxPMLN/Mtlv4dQDbmHNtwGNDtj3JzD4w5zqAPxVv/7sY90sAAoirm2+WWrWSMjKcPwNwjwCEWwQggLj74QfnpJCvv/Z6EiA1EIBwiwAEEHfjxkknnSTt2OH1JEBqIADhFgEIIO6OPtp5lxAz6Y03vJ4GSH4EINwiAAHE3a5d0sKFUq1a0ubNXk8DJD8CEG4RgACqxaWXSoMGeT0FkBoIQLhFAAKIu6IiKSvLuR7ggQdKq1Z5PRGQ3AhAuEUAAqgWn34q3XKLE4E7d3o9DZDcCEC4RQACqDZ/+pNzRjAAdwhAuEUAAqgWK1Y4J4Fs2OD1JEDyIwDhFgEIoFpcdpmzALhHAMItAhBA3G3Y4Oz9W7HC60mA1EAAwi0CEEDc3XSTc/wfgKpBAMItAhBAXO3cKTVuLM2f7/UkQOogAOEWAQggrqZOlQ4/XAoEvJ4ESB0EINwiAAHETVGR1KmT9PjjXk8CpBYCEG4RgADi5o03pJYtpd27vZ4ESC0EINwiAAHEzYknSrfd5vUUQOohAOEWAQggLpYtk3JypJ9+8noSIPUQgHCLAAQQF+edJw0b5vUUQGoiAOEWAQigyn37rVSzprRqldeTAKmJAIRbBCCAKjd8uPS3v3k9BZC6CEC4RQACqHKtWklm5a9XX/V6UiA5EYBwiwAEUOV++UVaty72mjtXyspy3iMYQOURgHCLAARQ7S64QBoyxOspgORFAMItAhBAtVq71tn797//eT0JkLwIQLhFAAKoVlddJQ0Y4PUUQHIjAOEWAQig2mzeLNWuLS1d6vUkQHIjAOEWAQig2tx5p1SrlnOJmJJ17rnSV195PRmQXAhAuEUAAqg2n3wi3XXX3jVypHM5mM8/93oyILkQgHCLAATgmVGjpNNP93oKIPkQgHCLAATgiZLjAT/6yOtJgORDAMItAhCAJyZMkPr29XoKIDkRgHCLAARQ7X79VWrUSHrrLa8nAZITAQi3CEAA1e7//k9q3lx65RXn/YBLFv8pAiqGAIRbBCCAanf77VK3bnvX4Yc7ZwO//LLXkwHJgQCEWwQgAM/NmiW1bSv99pvXkwDJgQCEWwQgAE8VFUmHHSY9+KDXkwDJgwCEWwQgAE+99prUsqVUUOD1JEDyIADhFgEIwDOBgNSzp3TPPV5PAiQXAhBuEYAAPDNvntSkibR9u9eTAMmFAIRbBCAAzwwcKPl8Una21L179G0CgYDy8/P15ZdfKj8/X4FAoHqHBBIQAQi3CEAAntm2TVq5UjrpJGno0PDPFRQUaNq0aTriiCNKftHJzHTEEUdo2rRpKuCgQaQxAhBuEYAAPLVypZSVJa1Zs/e2DRs2qHv37mHhF7m6d++uDRs2eDc44CECEG4RgAA8NWKE8xJwr17OOvLIIuXkLJfZRzJbpKZNV+vee1dq8+bNWrx4sQYPHqzMzEyZmXr06MGeQKQlAhBuEYAAPPW//0kvvrh3DRnyb5mdKb9/gEaMWCEzacmS8K/Jzc0NRuD06dO9GRzwEAEItwhAAAkjEAgEj/kbPHiwrrtOOuWU6NsOGjQoeEwgJ4Yg3RCAcIsABJAw8vPzg8f4LVy4VHXqSMcdJ116aenVv/+PMntEZgcrPz/f69GBakUAwi0CEEDC+PLLL4MBuH79Zt11lzRhQvQ1ePBOmUlmR2vlypVejw5UKwIQbhGAABJG6B7AxYsXl7ntoEHrZJYnM2MPINIOAQi3CEAACSPyGMBYtm2TatbcLrOn1arVPzVvHscAIr0QgHCLAASQUKZNmyYzU2ZmpnJzc6Nu8/zz8+XzPS2zF1Sv3g4NGFDNQwIeIwDhFgEIIKEUFBQELwKdmZmpQYMGadGiRdq0aZMWLVqkQYMGKSMjQ2amww8/WTk5gVKXiQFSHQEItwhAAAlnw4YN6tGjR5nvBNKjRw8NGbJd/ft7PS1Q/QhAuEUAAkhIBQUFmj59eqn3Au7ataumT5+ub78tUHa2tGyZ15MC1Y8AhFsEIICEFggElJ+fr5UrVyo/Pz940eeRI6XTTvN4OMAjBCDcIgABJJ0ffnDeP/jjj72eBPAGAQi3CEAASecf/5BOP93rKQDvEIBwiwAEkFTY+wcQgHCPAASQVK68UvrLX7yeAvAWAQi3CEAASSMQcPb+1a4tNWkSvtq3l3791esJgepBAMItAhBAUlm1ynn5N3RddJH0u985gQikAwIQbhGAAJLazz9L9etLCxd6PQlQfQhAuEUAAkhqN9wgnXSS11MA1YsAhFsEIICktXGjczzghx96PQlQvQhAuEUAAkhaV18t/fnPXk8BVD8CEG4RgACS0o8/SrVqSX/6kzRiRPgaPVriP2tIZQQg3CIAASSlrVulsWOla64JX3/6k1S3rvTLL15PCMQPAQi3CEAAKSMQkI49Vpo40etJgPgiANPHRDNbb2a/mtlCMzuknO0vNrP/mtl2M9tgZpNjbEcAAkgZb7whNW0qbdvm9SRAfBGA6eEaM1trZgebWZaZ3W5m35tZToztR5nZKjM7xsz8ZpZtZl1jbEsAAkgJhYXSoYdKU6Z4PQkQfwRgelhtZsNDPs4ws41mdn6Ubeuas5fw1AreNwEIICU89ZTUrp20a5fXkwDxRwCmvnpmFjCzoyJun2dmd0fZ/o9mVmRmV5vZ1+a8/DvXzA4v4/4JQABJbfdu572An3jC60mA6kEApr7W5gRg54jbZ5nZ9Cjbn1+8/Ttm1sKcl4wnmdkP5uwdjEQAAkh6990nHXKI8zIwkA4IwNRX2T2A/Yu3/0PIbX4z22HO3sFo908AAkhav/4qNWsmvfaa15MA1YcATA/RjgH80aIfA1iyx/APEduXGYDDhg3TyJEjNXLkSOXm5nr99xoAKuyWW6Tu3Z3rAm7b5lwKBkhFubm5wd/Vw4YNIwDTwGgzW2POpV+yzewOM1tnsc8CfsmcS8U0s71nDa8zszpRtmUPIICkdvjhktneNXOm1xMB8ccewPQxwczyzbmu30Lbex3ANuac9XtsyLZ1zOwRM/vZzDaZ2ZvmXEImGgIQQFLbtUvaskV66SWpXj1p0yavJwLijwCEWwQggKRXVCR16ybdeafXkwDVgwCEWwQggKT35JNS27ZSQYHXkwDVgwCEWwQggKS2c6fUpo1zIWggXRCAcIsABJDUJk1yzgIuKvJ6EqD6EIBwiwAEkLR27XJO/DjoIKlfP6l/f+nzz72eCog/AhBuEYAAklZRkfT009JDD0l//7tUs6b07bdeTwXEHwEItwhAAEkvEJBOOEG69lqvJwGqBwEItwhAAEnv5Zedt4PjP2VIFwQg3CIAASS1Xbuk/feXpk3zehKg+hCAcIsABJDU7r5bOuwwqbDQ60mA6kMAwi0CEEDS2rRJql9fGjLEORnkuee4GDTSAwEItwhAAEnrf/+T+vaVjj9eOvhgycy5DUh1BCDcIgABpISzz5YuucTrKYDqQQDCLQIQQNJbsEDKzJRyc6VPP5XWrvV6IiC+CEC4RQACSHq33SY1auSsWrWkJk28ngiILwIQbhGAAFLGnj3SoYdKd93l9SRAfBGAcIsABJAypkyROneWdu/2ehIgvghAuEUAAkgJGzc6l4TJzfV6EiD+CEC4RQACSAmXXSadfrrXUwDVgwCEWwQggKS3eLGUnS2tXu31JED1IAAT03tm9m4FViIgAAEkvf79nQDs0iX6mjDB6wmBqkUAJqbxFVyJgAAEkPT+9z9p3rzS68UXpaws6YknvJ4QqFoEINwiAAGkrKuvdt4mLhDwehKgahGAiclfwZUICEAAKemzz5yLQq9Y4fUkQNUjABNTwMyKKrASAQEIIOUUFUnHHiuNGeP1JEB8EICJ6YQKrkRAAAJIOTNmSG3aSL/+6vUkQHwQgHCLAASQUn76yXkv4Jdf9noSIH4IwOSQaWaHmFkfM+sbshIBAQggpQwZIp16Kid+ILURgInvCDNbY3uPCww9PjAREIAAUsZHH0k5OdKqVV5PAsQXAZj48sxsqpk1NLNfzKyBmT1mZmd5OVQIAhBASigslLp1k26+2etJgPgjABPfT2ZWu/jPW4r/2cjMVnozTikEIICU8K9/SQceKBUUeD0JEH8EYOLbbGYZxX/+3pwflM/Mtns2UTgCEEDSW7NGqlNHWrDA60mA6kEAJr73zax38Z9fN7N7zGyCmX3h1UARCEAASS0QkE45RerXz3lLOC/X5s1ePxtIFwRg4jvBzI4u/vNh5rz0m29mf/JsonAEIICktnmz1LCh856/Xi6/XzrkEK+fDaQLAhBuEYAA4FJBgdSxozRtmteTIF0QgInvZDM7KOK2zmZ2kgezREMAAoBLt9/unIFcWOj1JEgXBGDi+8LM2kfc1t7MPq/2SaIjAAHApZYtnZeAy3uZ+NprvZ4UqYIATHzbYty+tVqniI0ABACXNm4s++SQ996TataU3n7b60mRKgjAxLfazPaLuG0/M/vOg1miIQABIM4uvlg66yyvp0AqIQAT34NmNtuciz9b8T9fM+fdQRIBAQgAcbRokfP2dN9+6/UkSCUEYOJraGbvmlmhmW0q/ue7xbcnAgIQAOKkqEg66ihp3DivJ0GqIQCTx5FmdnbxPxMJAQgAcfLEE1KbNtKOHV5PglRDACYPn5m19HqIKAhAAIiDrVulFi2kWbO8ngSpiABMfDlmNt3MdpnZjuLbTjezsZ5NFI4ABIA4uPpq6YQTnLeqA6oaAZj4HjCzf5vZsWa2pfi2Nma2wrOJwhGAAFDF/vtfqVYtacUKrydBqiIAE98623sG8M8ht//iwSzREIAAUMVOOEE69FDp7rv3bS1Y4PUjQKIjABPfBjPLLP5zSQBmm9kP3oxTCgEIAFXsyiulAQP2bdWpIw0Z4vUjQKIjABPfG2Z2ZfGfSwLwCjN72ZtxSiEAASBBvPOOE4Dr13s9CRIdAZj4OpvZj2b2vpntNrO3zOwnM+vk5VAhCEAASAB79kiHHy7deafXkyAZEICJraY57wTSxsxGFv95XPHHiYIABIAE8MAD0oEHSrt2eT0JkgEBmPh+Ln8TTxGAAOCxzZulhg2lOXO8ngTJggBMfM+a2R+9HqIMBCAAeOyKK6R+/byeAsmEAEx895nZr2Y208xuNbObQ1YiIAABwEPLlknZ2dLXX3s9CZIJAZj4FsRYb3s5VAgCEAA8Ulgo9ewp3Xij15Mg2RCAcIsABACPTJ0qdegg7dzp9SRINgQg3CIAAcAj7dpJWVlSo0bu1kMPef1IUN0IQLhFAAKAR777Tvr0031fzz8vZWRIn33m9SNBdSMA4RYBCABJ6tRTpWHDvJ4CXiAA4RYBCABJaPZs5+Xfn37yehJ4gQCEWwQgACSZ3buddw158EGvJ4FXCEC4RQACQJK56y7nfYMLC72eBF4hAOEWAQgASeSnn6Q6daTjjpP+/vfwNXo0l5RJFwQg3CIAASCJ/PqrNH68dO214euYY6SWLQnAdEEAwi0CEACS3LZtUqtW0syZXk+C6kIAwi0CEACS3OjR0gknSIGA15OguhCAcIsABIAk9vnnUq1a0vLlXk+C6kQAwi0CEACSVCAg9ekj/eMfXk+C6kYAwi0CEACS1KxZUosW0pYtXk+C6kYApo+JZrbezH41s4VmdkgFvqauma0xsyIz88fYhgAEgCS0ZYtz4sdTT3k9CbxAAKaHa8xsrZkdbGZZZna7mX1vZjnlfN2jZjbXCEAASDlDh0onn8yJH+mKAEwPq81seMjHGWa20czOL+Nr+pvZIjPrawQgAKSU996TateWVq3yehJ4hQBMffXMLGBmR0XcPs/M7o7xNY3Neem3i5mdYAQgAKSMXbukgw5y3g4O6YsATH2tzQnAzhG3zzKz6TG+5jkzu774zwQgAKSQ8eOlbt2kPXu8ngReIgBTX2X3AJ5jZktsb/CdaE4AZpRx/xo2bJhGjhypkSNHKjc31+u/1wCAKD7/XMrOlpYu9XoSeCE3Nzf4u3rYsGEEYBqIdgzgjxb9GMAZ5pwpvKl4bTEnIH80swuibM8eQABIEueeK2VkSK1bl14HHyzt3u31hKgu7AFMD6PNOabvEDPLNrM7zGydRT8LuL6ZtQpZZ5uzB7B18ddGIgABIEnk50vvv1969e4tnXGG19OhOhGA6WOCmeWb2XYLvw5gG3P2+B0b4+s4BhAAUtibb0r160vr13s9CaoTAQi3CEAASGIdOzoXhD7llNJrwABp506vJ0Q8EIBwiwAEgCT20kvStGmlV+/eUteuUmGh1xMiHghAuEUAAkCKWb7cOVt42TKvJ0G8EIBwiwAEgBRSWCj16iVdd53XkyCeCEC4RQACQAr5v/+TOnXi2L9URwDCLQIQAFLEN9847xH87rteT4J4IwDhFgEIACkgEJD69pX+/nevJ0F1IADhFgEIACng/vultm0l/nOeHghAuEUAAkCS+/JL56XfhQu9ngTVhQCEWwQgACSx336TjjxSGj3a60lQnQhAuEUAAkASGzdOOuwwadcurydBdSIA4RYBCABJ6sMPpZwc6bPPvJ4E1Y0AhFsEIAAkoe3bpQMOkO66y+tJ4AUCEG4RgACQhC6/XDruON7rN10RgHCLAASAJDNrltSwobR2rdeTwCsEINwiAAEgiaxeLdWvL73yiteTwEsEINwiAAEgiZx5ppSRIXXuHH317i0VFXk9JeKNAIRbBCAAJJHVq6X580uv3FznnUAGDvR6QlQHAhBuEYAAkAImTpQ6dZK2bfN6ElQHAhBuEYAAkOQWLHCuB/jJJ15PgupCAMItAhAAktiPP0otW0oPPuj1JKhOBCDcIgABIEkVFUl/+pN09tlSIOD1NKhOBCDcIgABIEn961+SmfSPf0gTJuzbuuUWadMmrx8JKosAhFsEIAAkqeeeky69dN9Xz55SVpZzZjGSCwEItwhAAEhDP/0ktW4t3X+/15NgXxCAcIsABIA0Ewg4F5Q+7TSOHUxWBCDcIgABIM1MnSq1asWxf8mMAIRbBCAApJHPP5dq15by8ryeBG4QgHCLAASANFFQIB12mHT99V5PArcIQLhFAAJAmhg8WDrqKOm337yeBG4RgHCLAASANPDII1LTptJ333k9CaoCAQi3CEAASHFLljjvFcxxf6mDAIRbBCAApLBNm6S2baW77vJ6ElQlAhBuEYAAkKL27JF+/3veKzgVEYBwiwAEgBR17bVSly7Stm1eT4KqRgDCLQIQAFLQkiWSmfN2b926xV49e0pffeX1tKgsAhBuEYAAkIIKCqTXX5defTX2Ovpo9hAmKwIQbhGAAJCGnn5aatCAvX/JigCEWwQgAKSZpUudt4ObO9frSbCvCEC4RQACQBrZuFFq00aaNMnrSeAGAQi3CEAASBO7d0vHHSedcw6XhUl2BCDcIgABIA0EAtIVV0hdu0o7dng9DdwiAOEWAQgAaeCf/5SaN5fWrPF6ElQFAhBuEYAAkOKefVaqW9c5+QOpgQCEWwQgAKSwBQuknBzpzTe9ngRViQCEWwQgAKSo//5Xql9feuwxrydBVSMA4RYBCAApaN06ab/9pIkTvZ4E8UAAwi0CEABSzC+/SIceKg0axOVeUhUBCLcIQABIITt2ONf6O/VUac8er6dBvBCAcIsABIAUsWuX9Ic/SMcfz7X+Uh0BCLcIQABIAb/9Jp1+unTUUdK2bV5Pg3gjAOEWAQgAKeDBByUzKTvbOfO3vPXSS15PDDcIQLhFAAJACti1y7nsS1nr00+lY4+VDjtM+uknryeGGwQg3CIAASANBALS8OHS/vtL+fleTwO3CEC4RQACQIoLBKTrr3euC/jtt15Pg6pAAMItAhAAUtxNN0nNm0tffun1JKgqBCDcIgABIIVNmCA1ayZ98YXXk6AqEYBwiwAEgBR1881S06bSihVeT4KqRgDCLQIQAFJMyTF/zZo5Z/8i9RCAcIsABIAUEghIV14ptWrFMX+pjACEWwQgAKSQv//duSD0qFHSAw+Uv6ZN451DkhEBCLcIQABIIVdcIfXvX7HVuLGUkyN9843XU6OyCEC4RQACQBp64AGpbl3p3Xe9ngT7ggCEWwQgAKSZyZOd9wP+4AOvJ8G+IgDhFgEIAGkiEJAmTpQaNpQWL/Z6GrhBAMItAhAA0kBRkTRihNSypbR8udfTwC0CEG4RgACQ4n77TTr/fOfSMMuWST//XLHF2cGJiwCEWwQgAKS42bOdS8NUdmVmShs3ej09oiEA08dEM1tvZr+a2UIzOyTGdk3N7HEzW21m24r/ebuZ1YyxPQEIAGlg+/aKr9dfl7KznTOFkZgIwPRwjZmtNbODzSzLnKD73sxyomzbwcyuK/6nmVlHM/vMzO6Jcd8EIAAgaPZsqXZt6fHHvZ4EZSEA08NqMxse8nGGmW00s/Mr+PVXmdknMT5HAAIAJDkv92ZmSjVqOMcLVnbdfrvXjyB9EICpr56ZBczsqIjb55nZ3RW8jzlm9mgZ908AAgAkSZ99Jn30UeXWmWc67yry2WdeT58+CMDU19qcAOwccfssM5tega+/yZxjB1vF+DwBCADYZ7feSvx5gQBMfW72AN5izrGDB5Rz/xo2bJhGjhypkSNHKjc31+u/1wCABBcISDffTPxVp9zc3ODv6mHDhhGAaSDaMYA/WtnHAD5gZl+bWZty7ps9gACASgkEpFGjpObNpf/+1+tp0hN7ANPDaDNbY86lX7LN7A4zW2fRzwLOMLOZZrbczJpX4L4JQABAhRUWSpddJrVrJ/3vf15Pk74IwPQxwczyzWy7hV8HsI051wY8tvjj482syMx2mnMdwG3Fn98W434JQABAhezaJQ0YIB10kLRundfTpDcCEG4RgACAcv30k3TccVKvXtKPP3o9DQhAuEUAAgDKtGqV1LmzdPrp0o4dXk8DiQCEewQgACCmjz6SmjaVrrzSOf4PiYEAhFsEIAAgqscfl3JypMmTvZ4EkQhAuEUAAgDC7NkjXXWV1LCh9O9/ez0NoiEA4RYBCAAI2rRJ6ttXOvRQ6ZtvvJ4GsRCAcIsABABIkj74QGrTxnlv319/9XoalIUAhFsEvBINTwAAE55JREFUIACkuaIi6a679h7vFwh4PRHKQwDCLQIQANLY5s1Sv35S69bSe+85F3ve11VU5PWjSR8EINwiAAEgjf3tb5JZ1azhw71+NOmDAIRbBCAApLGCAmnjxn1f//mP1Latc+II7xBSfQhAuEUAAgD2yezZUv360qhRzqVjUH0IQLhFAAIAKmXPHunGG6U6daRnn/V6mvREAMItAhAAUGFr1kjHHCMdfLC0fLnX06QvAhBuEYAAgAp54QWpQQNpyBBpxw6vp0lvBCDcIgABAOW6+WbnTN+mTaUzzqi6NWWK148sORGAcIsABACU6913nVirijV5stS1q1SjhvTUU14/suREAMItAhAAUG127ZIuu0xq3ty58DT2DQEItwhAAEC1WLdOOvpo6cgjnT9j3xGAcIsABADE3auvSo0aSZdeKu3c6fU0yY8AhFsEIAAgbgoKnLeIq1dPeuYZr6dJHQQg3CIAAQBx8fnn0uGHS716SatWeT1NaiEA4RYBCACoUnv2SLffLuXkSNddJ/32m9cTpR4CEG4RgACAKvPpp1L37s47hXz0kdfTpC4CEG4RgAAA13bvlsaPl7KznfcJ3rXL64lSGwEItwhAAIArc+dKnTo5F3f++GOvp0kPBCDcIgABAPvkm2+k/v2lhg2l++93jv1D9SAA4RYBCAColO3bpRtucF7uHTJE2rTJ64nSDwEItwhAAECF7N4tPfig1KqVdOyxvNzrJQIQbhGAAIAyFRZKTz4pdeggdekivfiiFAh4PVV6IwDhFgEIAIgqEJBeesm5pEuHDtITTzgxCO8RgHCLAAQAhCkslJ5/3rmeX8uWzsu+u3d7PRVCEYBwiwAEAEiSduyQHnhA6thRatdOmjzZuQ2JhwCEWwQgAKS5zZuliROlJk2ca/k98wyXdEl0BCDcIgABIE0tXy4NG+a8Z+9JJ0n//jcndyQLAhBuEYAAkEZ27nRO5jjmGKlWLemii6Rly7yeCpVFAMItAhAA0sAXX0j/+Ifzrh1dukhTpkg//+z1VNhXBCDcIgABIIX95z/S8cdLZpLPJ/XrJ91xhzRpUvWu+fO9fiZSCwEItwhAAEhhL78snXde9a9zzpGaNnXCs3ZtZ48jqg4BCLcIQABAldmxQ3roIalTJ+ct4+64g5ea44EAhFsEIADAtfXrpZtukho3lg4/3DnRhItHxw8BCLcIQADAPtm1S3rhBenUU6UaNaRTTnGO9eNSMvFHAMItAhAAUCmffCJdeaXUqJHzriG33CKtXev1VOmFAIRbBCAAoFybN0v33it16+ZcOPqii6SFC6WiIq8nS08EINwiAAEAUX3/vXT//VLfvlJmpnTssdIjj0jbtnk9GQhAuEUAAgCCVq50ztzt1UvKyJBOOEGaPFlas8bryRCKAIRbBCAApLFAQFqyRLrhBucdQrKypD//WXr0UenHH72eDrEQgHCLAASANLN2rTRjhnTBBc61+urVk849V3r+eV7eTRYEINwiAAEgxW3cKM2aJQ0eLB1wgPPS7tFHS2PHSnl5XK8vGRGAcIsABIAUs2WL9Npr0lVXSYcdJvn9Uteu0tVXS7Nns5cvFRCAcIsABIAkVlQkffGF884bw4dLPXs6wdepkzR0qHOh5k2bvJ4SVY0AhFsEIAAkiUDAORv3hRekMWOkPn2c4/dq1XJe0r3ySumpp6R167yeFPFGAMItAhAAEtTGjc5LtuPHO2+31rSpc/xe167SoEHS9OnOu3L89pvXk6K6EYBwiwAEAI/t3i2tWOHs2bv5Zunss6V27SSfT+rcWRo4UJoyRfrgA2nnTq+nRSIgAOEWAQgA1WT7dmnpUunJJ6Xrr5f+8hcn8DIynLdX69HDib1Jk6S33pJ++cXriZGoCEC4RQACQBXbvFl67z3nJdqRI6U//lFq21Yykxo2dN5S7fLLpXvukebOdY7r4z11URkEINwiAAHApSefdM64PeEE5zg9s70rM1M6+GDprLOkG2+U7r1Xuu++1FxLlnj9k0gfBCDcIgABwKUrrpBOPz2112mnSd27O2cchwaumfP2cd26SY895vVPIn0QgHCLAAQAhNm0SVqwwNmrN3iwdMwxzuVm/H7nmMWzz5YmTJD+v717D46qPOM4/uUmRgFBBCrBOCjeELzUYgWRCoqIURy0oyJS1FHbgWJFqLQd1HjD2qmO4G1UEEdtEZWxjFBTGYmgwlSr1DvViigtSqjKHRSSp388ZycnN7Jnd09ysvl9Zt4h2T27+z6c3bNP3utzz5mtXm22e3dT17jlUQIo2VICKCLSAu3Z4+sFvvaa2ezZZtddZ3bGGWY9enirXlGRLz0zbZqvLbhqldnOnU1da0lRAijZUgIoIpJnKit9IsqqVb4l3P33+8LRY8b4BJSiIp953KqV2cEH+4LSkyaZPfywLzWzaVNTRyANUQIo2VICKCLSzGzf7l2vS5aYzZnj3bFXXmk2fLh30e63X9WM4+OOMysu9nGKM2aYPfWU2bJlZp995usPSvOkBFCypQRQRCRBdu40+/xz75qdN8/srrt8j99Ro3yiRdeuVRMvjjjCbNgws8svN7vxRrNHHzUrLfW9gbdubepIJE5KACVbSgBFRHKsosIXcf70U18a5aWXzJ5+2uzBB83uuMNsyhSzK67whaCHDDHr18+ssNCsoMCTu9at/feBA80uushs6lTfCeT5530h6fJy7+aVlksJoGRLCaCISD127TJbv97sgw98YeeFC80ef9wXcJ4+3WziRB9XN2KE2cknm/XpY3bggZ7ApdYA7NbNu2UHDvRJFZddZnbttd5tO3OmT7BYvNjH3q1e7cmdZtVKQ5QASraUAIpIXqus9EkNa9Z469mSJWbz55s99JCPiZs61cfPjR7tCzn372/Wq1fVODow69DBJ04cf7xPmLjwQt/J44YbfNu2Rx7xfXxfftknXqxda7Zli1rpJD5KACVbSgBFpNHt3u0J0oYNniytXu2J04oVnkQtWuQJ1RNPeHI1c6YnWjff7EnXpElmV1/trWkXXugta0OHmp1yitkJJ3iLW1GRj5dLtca1aWN20EFmRx7px40caTZ2rD/XTTeZ3Xuvv96iRWavv2720UdeP02UkCRSAijZUgIo0sKlkrHycp98UDMZW7zYF/x98snaydi0ad6dWTMZGzbMuzzDyVi3bmYdO3q3aM2dJAoKvOu0sNC7Ufv1MxswwMfHjRjhY+XGjPGWugkTfAzd9Ok+nu6ee7w1b+5cH2e3cKGPuXv1VbO33vLZrps3qzVO8osSwJbjFuC/wFbgFeDYvRzbGfgTsAn4BngSOKCeY5UAiiTInj0+e7NmMrZypdnSpbWTsVmzfJZoSUn1ZGzcON+tobi4djJ26KFm3bs3nIz17Gl2+OG1k7Hzzze75BKfxBBOxm6/3ezuu32iQ81kbPlynwzx/vs+MWL9ep8ksXOnEjORTCgBbBl+DXwO9AXaAzOA/wD71XP8YuAloAtwILAE+Es9x+Z1AlhaWtrUVYiNYmt+vv/ebODAUhs0yJfzOPro6slYu3a1k7E4Svv2Zp07+wLAvXub9e1rdtJJZoMH+04QZ56ZeTnxxNKsHp/kotiaZ8nX2E4/XQlgS7AG+GXo9zbABmBsHccWAZVAv9BtxwW39arj+LxOACdPntzUVYiNYmt+KirMiosn25w5lrdl+PD8jU+xNc+Sr7ENHaoEMN91wpO3H9e4/W/AH+s4fhSwo47bdwHn1vP8SgCbIcXWPOVzbGb5HZ9ia57yNbYJE5QA5rteeAJ4VI3bnwYeqeP4y4Av67j9K+DSOm7vBNi6dets8+bNeVcmTpzY5HVQbIqtpcSW7/EptuZZ8jW2q65apwQwz8XdAliIv4FUVFRUVFRUml8pRPJWXWMAy6l/DGAF1ccAHh/cVtcYwFb4m6eTioqKioqKSrMqhfj3uOSpqcBafOmXAuBOYB31zwJ+ASgFugIH4bOAn4+9liIiIiKSUyX42L5tVF8H8BB8bcBTQ8d2Bp7C1wH8FngC/0tBRERERERERERE8lGUXURuA94GvgOWx16z7KUbWzfgcXw85Zbg3xnAPrHXMHNRzttCfHHwzcFj5uCLgCdZlPhSOuLDISqA1nFVLAeixPYK/nnbEhy/BfhFvNXLStTzdjnwLt578RVwb4x1y1a6saV6XraEyi5gN8n93EU5bz8CluI7SZUDC/Dx5UkVJbajgb8CG4H/4dfKDjHXL1MX49/Dm0nvmhdlFzBpAaLuIjIeKAbuI/kJYJTYegO/Cf4FOAx4B7gn/mpmJOp56x8cB/6Bnwc8F3MdsxE1vpQ5wIskOwGMGlsZ/gXWHESNbQrwKTAIP18FwAnxVzMjmb4nUxbgf4glUZTYWuEbDdwDtAX2B+YDrzdKTaOLEltH4Au8oaMt3jDwCn7ukmg4ngReQXrXvCi7gEkLEGUXkbCbSX4CmGlsKb8CVuW6UjmSTWxd8L8C342hXrmSSXznAX8HhpHsBDBqbGXArXFXKkeixNYRb5E5pxHqlQvZfOYKge+Bs2KoVy5Eia0z/vnqH7qtGNgeW+2yEyW2s/GW6LAzgD0keymVn9DwNS/qLmCS5zoRbQ3BsKQngNnElrIYb1FKmkxjm4F3RVXiF7kLYqld9jKJryve9XsM6V0Mm0omsZXh3VFfAx/is/z3j6uCWYga2wj8PF0PfIx3/76IfyklTbbXk1uBT3JdqRzJJLZZQSnAE8Jn8cmESRM1tpH4tTG8bMpZ+Pu0OI4K5kg617xRRFsDWPJc1F1EwpKeAGYTG8CN+JiRnjmuVy5kG9th+BdSEr9oIbP45gO/DX5OcgKYSWyn4F+y4K0ub+Nd+EkTNbaxwfHLgB/g3XO/B9bjrYNJks1nri1+Lbk+hnrlQiaxDcH/GNmNt479A+8uTZqosR2Ar6ZxJ7Av3uq3DL+ejImvmllL55oXdRcwyXNqAazbbfiYkT4x1CsXctG6OQC/GLTJYb1yJWp8lwBvUnXxOx2/GOZDbHUZgncntm/owEYWNbbzguPD3aKt8a7EEXFUMAvZnLeL8Ji6xFCvXIgaWx98UtLPgXZ4K+AtwL+Dn5Mkk/N2PD5ObgPeMn1N8BzDY6pjLqgFUDISZReRsKQngJBZbA/gH/pDYqxXLmR63lJOxS8YSZ2RGCW+ufhYso1B2YRfsMuBcfFWMyPZnrtUArhvjuuVC1FiS7XOnFXj+CQmgJD5eSsDHourUjkSJbYL8PVjwzri53JALLXLTraft/Px60vSWqXD0h0DGGUXMGkBou4i0hb/4rkdeBVvhUhaS0RKlNja4BMj3gN6NFL9shEltiOA0VRdwI7CZ+ytjL2WmYsS3wF4V32q/JSqi1rSWiQgWmzd8WQodd+xeGvns7HXMjNRrycL8FmW3amaobmOZC67ETU28JmnlfiyKUkWJbYiPEm/Cr9u7os3CGwmmUuKRD1vPwzuawOchieQSe2+b41/blLjFPcLfq9v6zftAia1lJD+LiJz8QtaRVBSPydVCenFNgSPYwdV63al1vFKqhLSi+1IPFn/hqo1Dh/Ev3STrIT035dhSR4DmFJCerEV4TObv8XP3cckdxJISgnpn7cOwGz8vbkRX3+tbyPVMxMlRHtPzgLeaKS6ZauE9GM7E1iBn7evg+MHN041M1JC+rE9gK//tw1vELiisSqZgfHU/X08BO0CJiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiLSNLbiOwc05FLgo5jrIiIiIiIiIiIiIiltqH/TdxERERFpJsqA+4AFwBbgY2BccN9P8M3eLwb+BewEugOtgSnAh/gm728Cw2o8bzGwEvgG2Ag8E7qvMnT8IcBi4Ovgud6lajP58cC60OPaA3cBa4LjlwEnh+5PHX8N8Bm++fwzQIe0/idEREREWogyYDtwDp7YjQS+AwZSlQAuALoA7YJjSoC3gT7Bc5wPbAN6B78PB3YAFwBtgX2AoaHXDCeATwEPB88NcARwaPDzeOCL0OPuA94JXqctcD2etPYMHb8buDt4zR54Qntz+v8dIiIiIvmvDHi2xm1PA4/iCWAFVYleyiY8yQt7Cfhd8PMLwKy9vGY4AXwMWAj0reO4cALYCk9Uz61xzD+BG0LH78CT1JQ/4C2MIiIiIhIow5OksDuBUqoSwLah+7rjCdwmvHv3G7yrdStwf3DM+8DEvbxmOAHsgrfYrQa+AuYErwHVE8BuweNqJorPhV63ZosheOvf8r3URURERKTFKaP6+DyAecBsqhLAcIvaPnhL3OC9POciYOZe7g8ngGEHA0uBJ4Pfa7YA7gDOq/GYVVRvAVQCKCIiItKAMnz83kg80Tsbn+wxiLoTQPAWuxXA0cHvBcBp+Pg98O7hbcBofGxfe6onfOEE8GLgMDzB6wS8iHcLQ+2E7n484esdPO9kfAxgYT3HgxJAERERkVrK8PF6qVnAnwA/C+6rLwFsBUwC3sO7f7/Ex9kdEzrmPOCN4P5yfFxhSgVVCeAMYC3ehbwB+DPQNbivZkKXmgW8Fu96Xk7tWcBKAEVEREQaUAbc2tSVEBEREZHGowRQREREpIVZihJAEREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREWkE/wd7RDiW24huXQAAAABJRU5ErkJggg==\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fe27528b940>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a similar dataset as before, but with more samples to get a smoother curve\n",
    "X, y = make_blobs(n_samples=(4000, 500), centers=2, cluster_std=[7.0, 2], random_state=22)\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "\n",
    "svc = SVC(gamma=.05).fit(X_train, y_train)\n",
    "\n",
    "precision, recall, thresholds = precision_recall_curve(\n",
    "    y_test, svc.decision_function(X_test))\n",
    "# find threshold closest to zero:\n",
    "close_zero = np.argmin(np.abs(thresholds))\n",
    "plt.figure()\n",
    "plt.plot(precision[close_zero], recall[close_zero], 'o', markersize=10,\n",
    "         label=\"threshold zero\", fillstyle=\"none\", c='k', mew=2)\n",
    "\n",
    "plt.plot(precision, recall, label=\"precision recall curve\")\n",
    "plt.xlabel(\"precision\")\n",
    "plt.ylabel(\"recall\")\n",
    "plt.title(\"precision_recall_curve\");\n",
    "plt.legend(loc=\"best\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "rf = RandomForestClassifier(n_estimators=100, random_state=0, max_features=2)\n",
    "rf.fit(X_train, y_train)\n",
    "\n",
    "# RandomForestClassifier has predict_proba, but not decision_function\n",
    "precision_rf, recall_rf, thresholds_rf = precision_recall_curve(\n",
    "    y_test, rf.predict_proba(X_test)[:, 1])\n",
    "plt.figure()\n",
    "\n",
    "plt.plot(precision, recall, label=\"svc\")\n",
    "\n",
    "plt.plot(precision[close_zero], recall[close_zero], 'o', markersize=10,\n",
    "         label=\"threshold zero svc\", fillstyle=\"none\", c='k', mew=2)\n",
    "\n",
    "plt.plot(precision_rf, recall_rf, label=\"rf\")\n",
    "\n",
    "close_default_rf = np.argmin(np.abs(thresholds_rf - 0.5))\n",
    "plt.plot(precision_rf[close_default_rf], recall_rf[close_default_rf], '^', markersize=10,\n",
    "         label=\"threshold 0.5 rf\", fillstyle=\"none\", c='k', mew=2)\n",
    "plt.xlabel(\"precision\")\n",
    "plt.ylabel(\"recall\")\n",
    "plt.legend(loc=\"best\")\n",
    "plt.title(\"precision_recall_comparison\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "f1_score of random forest: 0.609756\n",
      "f1_score of svc: 0.655870\n"
     ]
    }
   ],
   "source": [
    "print(\"f1_score of random forest: %f\" % f1_score(y_test, rf.predict(X_test)))\n",
    "print(\"f1_score of svc: %f\" % f1_score(y_test, svc.predict(X_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "average precision of random forest: 0.665737\n",
      "average precision of svc: 0.662636\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import average_precision_score\n",
    "ap_rf = average_precision_score(y_test, rf.predict_proba(X_test)[:, 1])\n",
    "ap_svc = average_precision_score(y_test, svc.decision_function(X_test))\n",
    "print(\"average precision of random forest: %f\" % ap_rf)\n",
    "print(\"average precision of svc: %f\" % ap_svc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Receiver Operating Characteristics (ROC) and AUC\n",
    "\\begin{equation}\n",
    "\\text{FPR} = \\frac{\\text{FP}}{\\text{FP} + \\text{TN}}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fe273a24be0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve\n",
    "fpr, tpr, thresholds = roc_curve(y_test, svc.decision_function(X_test))\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.plot(fpr, tpr, label=\"ROC Curve\")\n",
    "plt.xlabel(\"FPR\")\n",
    "plt.ylabel(\"TPR (recall)\")\n",
    "plt.title(\"roc_curve\");\n",
    "# find threshold closest to zero:\n",
    "close_zero = np.argmin(np.abs(thresholds))\n",
    "plt.plot(fpr[close_zero], tpr[close_zero], 'o', markersize=10,\n",
    "         label=\"threshold zero\", fillstyle=\"none\", c='k', mew=2)\n",
    "plt.legend(loc=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fe27399a5f8>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve\n",
    "fpr_rf, tpr_rf, thresholds_rf = roc_curve(y_test, rf.predict_proba(X_test)[:, 1])\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(fpr, tpr, label=\"ROC Curve SVC\")\n",
    "plt.plot(fpr_rf, tpr_rf, label=\"ROC Curve RF\")\n",
    "\n",
    "plt.xlabel(\"FPR\")\n",
    "plt.ylabel(\"TPR (recall)\")\n",
    "plt.title(\"roc_curve_comparison\");\n",
    "plt.plot(fpr[close_zero], tpr[close_zero], 'o', markersize=10,\n",
    "         label=\"threshold zero SVC\", fillstyle=\"none\", c='k', mew=2)\n",
    "close_default_rf = np.argmin(np.abs(thresholds_rf - 0.5))\n",
    "plt.plot(fpr_rf[close_default_rf], tpr[close_default_rf], '^', markersize=10,\n",
    "         label=\"threshold 0.5 RF\", fillstyle=\"none\", c='k', mew=2)\n",
    "\n",
    "plt.legend(loc=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AUC for Random Forest: 0.936695\n",
      "AUC for SVC: 0.916294\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import roc_auc_score\n",
    "rf_auc = roc_auc_score(y_test, rf.predict_proba(X_test)[:, 1])\n",
    "svc_auc = roc_auc_score(y_test, svc.decision_function(X_test))\n",
    "print(\"AUC for Random Forest: %f\" % rf_auc)\n",
    "print(\"AUC for SVC: %f\" % svc_auc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(41188, 63)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = data.drop(\"target\", axis=1).values\n",
    "y = data.target.values\n",
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gamma = 1.000  accuracy = 0.89  AUC = 0.62\n",
      "gamma = 0.010  accuracy = 0.89  AUC = 0.89\n",
      "gamma = 0.001  accuracy = 0.91  AUC = 0.88\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7ff697fe0208>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, random_state=0, train_size=.1, test_size=.1)\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "for gamma in [1, 0.01, 0.001]:\n",
    "    svc = SVC(gamma=gamma).fit(X_train, y_train)\n",
    "    accuracy = svc.score(X_test, y_test)\n",
    "    auc = roc_auc_score(y_test == \"yes\", svc.decision_function(X_test))\n",
    "    fpr, tpr, _ = roc_curve(y_test , svc.decision_function(X_test), pos_label=\"yes\")\n",
    "    print(\"gamma = %.03f  accuracy = %.02f  AUC = %.02f\" % (gamma, accuracy, auc))\n",
    "    plt.plot(fpr, tpr, label=\"gamma=%.03f\" % gamma, linewidth=4)\n",
    "plt.xlabel(\"FPR\")\n",
    "plt.ylabel(\"TPR\")\n",
    "plt.xlim(-0.01, 1)\n",
    "plt.ylim(0, 1.02)\n",
    "plt.legend(loc=\"best\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multi-class classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy: 0.953\n",
      "confusion matrix:\n",
      "[[37  0  0  0  0  0  0  0  0  0]\n",
      " [ 0 39  0  0  0  0  2  0  2  0]\n",
      " [ 0  0 41  3  0  0  0  0  0  0]\n",
      " [ 0  0  1 43  0  0  0  0  0  1]\n",
      " [ 0  0  0  0 38  0  0  0  0  0]\n",
      " [ 0  1  0  0  0 47  0  0  0  0]\n",
      " [ 0  0  0  0  0  0 52  0  0  0]\n",
      " [ 0  1  0  1  1  0  0 45  0  0]\n",
      " [ 0  3  1  0  0  0  0  0 43  1]\n",
      " [ 0  0  0  1  0  1  0  0  1 44]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.datasets import load_digits\n",
    "digits = load_digits()\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    digits.data, digits.target, random_state=0)\n",
    "lr = LogisticRegression().fit(X_train, y_train)\n",
    "pred = lr.predict(X_test)\n",
    "print(\"accuracy: %0.3f\" % accuracy_score(y_test, pred))\n",
    "print(\"confusion matrix:\")\n",
    "print(confusion_matrix(y_test, pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "hide_input": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "scores_image = mglearn.tools.heatmap(confusion_matrix(y_test, pred), xlabel='Predicted label', ylabel='True label',\n",
    "                                     xticklabels=digits.target_names, yticklabels=digits.target_names,\n",
    "                                     cmap=plt.cm.gray_r, fmt=\"%d\")    \n",
    "\n",
    "plt.title(\"Confusion matrix\")\n",
    "plt.gca().invert_yaxis()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       1.00      1.00      1.00        37\n",
      "          1       0.89      0.91      0.90        43\n",
      "          2       0.95      0.93      0.94        44\n",
      "          3       0.90      0.96      0.92        45\n",
      "          4       0.97      1.00      0.99        38\n",
      "          5       0.98      0.98      0.98        48\n",
      "          6       0.96      1.00      0.98        52\n",
      "          7       1.00      0.94      0.97        48\n",
      "          8       0.93      0.90      0.91        48\n",
      "          9       0.96      0.94      0.95        47\n",
      "\n",
      "avg / total       0.95      0.95      0.95       450\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "micro average f1 score: 0.953333\n",
      "macro average f1 score: 0.954000\n"
     ]
    }
   ],
   "source": [
    "print(\"micro average f1 score: %f\" % f1_score(y_test, pred, average=\"micro\"))\n",
    "print(\"macro average f1 score: %f\" % f1_score(y_test, pred, average=\"macro\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using evaluation metrics in model selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "default scoring  [ 0.9  0.9  0.9]\n",
      "explicit accuracy scoring  [ 0.9  0.9  0.9]\n",
      "AUC scoring  [ 0.994  0.99   0.996]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.cross_validation import cross_val_score\n",
    "# default scoring for classification is accuracy\n",
    "print(\"default scoring \", cross_val_score(SVC(), X, y))\n",
    "# providing scoring=\"accuracy\" doesn't change the results\n",
    "explicit_accuracy =  cross_val_score(SVC(), digits.data, digits.target == 9, scoring=\"accuracy\")\n",
    "print(\"explicit accuracy scoring \", explicit_accuracy)\n",
    "roc_auc =  cross_val_score(SVC(), digits.data, digits.target == 9, scoring=\"roc_auc\")\n",
    "print(\"AUC scoring \", roc_auc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Grid-Search with accuracy\n",
      "Best parameters: {'gamma': 0.0001}\n",
      "Best cross-validation score (accuracy)): 0.970304380104\n",
      "Test set AUC: 0.992\n",
      "Test set accuracy 0.973: \n",
      "\n",
      "Grid-Search with AUC\n",
      "Best parameters: {'gamma': 0.01}\n",
      "Best cross-validation score (AUC): 0.997467845028\n",
      "Test set AUC: 1.000\n",
      "Test set accuracy 1.000: \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/andy/anaconda3/lib/python3.5/site-packages/sklearn/grid_search.py:418: ChangedBehaviorWarning: The long-standing behavior to use the estimator's score function in GridSearchCV.score has changed. The scoring parameter is now used.\n",
      "  ChangedBehaviorWarning)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "# back to the bank campaign\n",
    "X = data.drop(\"target\", axis=1).values\n",
    "y = data.target.values\n",
    "\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, train_size=.1, test_size=.1, random_state=0)\n",
    "\n",
    "# we provide a somewhat bad grid to illustrate the point:\n",
    "param_grid = {'gamma': [0.0001, 0.01, 0.1, 1, 10]}\n",
    "# using the default scoring of accuracy:\n",
    "grid = GridSearchCV(SVC(), param_grid=param_grid)\n",
    "grid.fit(X_train, y_train)\n",
    "print(\"Grid-Search with accuracy\")\n",
    "print(\"Best parameters:\", grid.best_params_)\n",
    "print(\"Best cross-validation score (accuracy)):\", grid.best_score_)\n",
    "print(\"Test set AUC: %.3f\" % roc_auc_score(y_test, grid.decision_function(X_test)))\n",
    "print(\"Test set accuracy %.3f: \" % grid.score(X_test, y_test))\n",
    "\n",
    "# using AUC scoring instead:\n",
    "grid = GridSearchCV(SVC(), param_grid=param_grid, scoring=\"roc_auc\")\n",
    "grid.fit(X_train, y_train)\n",
    "print(\"\\nGrid-Search with AUC\")\n",
    "print(\"Best parameters:\", grid.best_params_)\n",
    "print(\"Best cross-validation score (AUC):\", grid.best_score_)\n",
    "print(\"Test set AUC: %.3f\" % roc_auc_score(y_test, grid.decision_function(X_test)))\n",
    "print(\"Test set accuracy %.3f: \" % grid.score(X_test, y_test))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['accuracy', 'adjusted_rand_score', 'average_precision', 'f1', 'f1_macro', 'f1_micro', 'f1_samples', 'f1_weighted', 'log_loss', 'mean_absolute_error', 'mean_squared_error', 'median_absolute_error', 'precision', 'precision_macro', 'precision_micro', 'precision_samples', 'precision_weighted', 'r2', 'recall', 'recall_macro', 'recall_micro', 'recall_samples', 'recall_weighted', 'roc_auc']\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics.scorer import SCORERS\n",
    "    print(sorted(SCORERS.keys()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def my_scoring(fitted_estimator, X_test, y_test):\n",
    "    return (fitted_estimator.predict(X_test) == y_test).mean()\n",
    "\n",
    "GridSearchCV(SVC(), param_grid, scoring=my_scoring)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exercises\n",
    "Load the adult dataset from ``data/adult.csv``, and split it into training and test set.\n",
    "Apply grid-search to the training set, searching for the best C for Logistic Regression, also search over L1 penalty vs L2 penalty.\n",
    "Plot the ROC curve of the best model on the test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# get dummy variables, needed for scikit-learn models on categorical data:\n",
    "X = pd.get_dummies(data.drop(\"income\", axis=1))\n",
    "y = data.income == \" >50K\""
   ]
  }
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