jaidhyani/bmi.ipynb

## bmi.ipynb
{
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  {
   "cell_type": "code",
   "execution_count": 888,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"da21600.0005\" \"qas\"         \n",
      "\n",
      "The rpy2.ipython extension is already loaded. To reload it, use:\n",
      "  %reload_ext rpy2.ipython\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import rpy2.robjects as rob\n",
    "import seaborn as sns\n",
    "\n",
    "# Load data using Rpy\n",
    "pd.options.mode.chained_assignment = None\n",
    "\n",
    "rob.r['load']('DS0005/21600-0005-Data.rda')\n",
    "print rob.r['ls']()\n",
    "rob.r('qas=da21600.0005;0')\n",
    "%load_ext rpy2.ipython\n",
    "%R -o qas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# some column renaming for more intuitive interpretations later\n",
    "def qas_preproccess(qas):\n",
    "    qas.rename(columns = {\n",
    "            'H2GH4':   'H2GH4SportsLimitations',\n",
    "            'H2GH5':   'H2GH5HygeneProblems',\n",
    "            'H2GH22':  'H2GH22PoorAppetite',\n",
    "            'H2GH28':  'H2GH28SkippedMedicalCare',\n",
    "            'H2GH29E': 'H2GH29ESkippedMCScaredOfParents',\n",
    "            'H2GH29H': 'H2GH29HSkippedMCGoAway',\n",
    "            'H2GH30':  'H2GH30WeightSelfPerception',\n",
    "            'H2GH31':  'H2GH31TryingToChange',\n",
    "            'H2GH32A': 'H2GH32ALastWeekLoseDiet',\n",
    "            'H2GH32B': 'H2GH32BLastWeekLoseExercise',\n",
    "            'H2GH32C': 'H2GH32CLastWeekLoseVomit',\n",
    "            'H2GH32D': 'H2GH32DLastWeekLosePills',\n",
    "            'H2GH32E': 'H2GH32ELastWeekLoseLaxatives',\n",
    "            'H2GH32F': 'H2GH32FLastWeekLoseOther',\n",
    "            'H2GH32G': 'H2GH32GLastWeekLoseNothing',\n",
    "            'H2GH33A': 'H2GH33ALastWeekGainDiet',\n",
    "            'H2GH33B': 'H2GH33BLastWeekGainExercise',\n",
    "            'H2GH33C': 'H2GH33CLastWeekGainWeights',\n",
    "            'H2GH33D': 'H2GH33DLastWeekGainSupplements',\n",
    "            'H2GH33E': 'H2GH33ELastWeekGainSteroids',\n",
    "            'H2GH33F': 'H2GH33FLastWeekGainOther',\n",
    "            'H2GH33G': 'H2GH33GLastWeekGainNothing',\n",
    "        }, inplace=True);\n",
    "    qas['SelfPerceptionUnder'] = (qas.H2GH30WeightSelfPerception <= 2)\n",
    "    qas['SelfPerceptionOver'] = \\\n",
    "        (qas.H2GH30WeightSelfPerception == 4) | \\\n",
    "        (qas.H2GH30WeightSelfPerception == 5)\n",
    "    return qas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 883,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "# utility functions\n",
    "\n",
    "# snums('foo', 20, 23) -> ['foo20', 'foo21', 'foo22', 'foo23']\n",
    "def snums(s, lo, hi):\n",
    "    return [s + str(x) for x in xrange(lo, hi+1)]\n",
    "\n",
    "# copying R's cjoin\n",
    "def cjoin(*dfs):\n",
    "    return pd.concat(dfs, axis=1)\n",
    "\n",
    "# get all cols in dataframe containing string\n",
    "def grepcols(df, s):\n",
    "    return df[[c for c in df.columns if s in c]]\n",
    "\n",
    "# get dummies from a dataframe, filter by allowed dummy values\n",
    "def dumitdown(qas, colnames=None, allowed_cats = None):\n",
    "    colnames = colnames or qas.columns\n",
    "    cols = qas[colnames].applymap(lambda x: x.astype('int'))\n",
    "    dums= pd.get_dummies(\n",
    "        cols,\n",
    "        columns=colnames,\n",
    "        dummy_na=True\n",
    "    )\n",
    "    dums.columns = map(lambda n: n[:-2] if n[-2:]=='.0' else n, dums.columns)\n",
    "    if allowed_cats is not None:\n",
    "        cats = map(str, allowed_cats)\n",
    "        dums = dums[filter(lambda x: x.split('_')[-1] in cats, dums.columns)]\n",
    "    return dums\n",
    "\n",
    "# 'fix' a column by replacing values outside a range with mean or 0\n",
    "def fixcol(col, minval=0, maxval=1, method='mean'):\n",
    "    goodmask = (minval <= col) & (col <= maxval)\n",
    "    if method == 'mean':\n",
    "        col[~goodmask] = col[goodmask].mean()\n",
    "    elif method == 'zero':\n",
    "        col[~goodmask] = 0\n",
    "    return col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 875,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# automatically identify column data types - 'days', 'range', 'yesno', 'choice', 'other'\n",
    "def get_coltypes(df):\n",
    "    def coltype(col):\n",
    "        try:\n",
    "            values = set(col.unique())\n",
    "            if all([v in values for v in range(1, 8)]) and all([v in range(9) + [96, 97, 98] for v in values]):\n",
    "                return 'days'\n",
    "            if max(values) > 8:\n",
    "                return 'range'\n",
    "            biggest = max(set(filter(lambda x: x < 6, values)))\n",
    "            if biggest == 1:\n",
    "                return 'yesno'\n",
    "            else:\n",
    "                return 'choice'\n",
    "        except ValueError:\n",
    "            return 'other'\n",
    "    return df.apply(coltype, axis='rows')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# get exact age, to the day\n",
    "def getbday(qas):\n",
    "    bdays = qas.apply(\n",
    "        lambda x: pd.datetime(\n",
    "            int(x['H2GI1Y']) + 1900, \n",
    "            int(x['H2GI1M']), \n",
    "            1), axis=1)\n",
    "    bdays.columns = ['birthday']\n",
    "    return bdays\n",
    "\n",
    "def getiviewday(qas):\n",
    "    iday = qas.apply(\n",
    "        lambda x: pd.datetime(\n",
    "            int(x['IYEAR2']) + 1900, \n",
    "            int(x['IMONTH2']), \n",
    "            int(x['IDAY2'])), axis=1)\n",
    "    iday.columns = ['iviewday']\n",
    "    return iday\n",
    "\n",
    "def get_age(qas):\n",
    "    bday = getbday(qas)\n",
    "    iviewday = getiviewday(qas)\n",
    "    age = (iviewday - bday).dt.days.values/365.\n",
    "    agedf = pd.DataFrame({'age': age}, index=range(1, len(age)+1))\n",
    "    return agedf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 990,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# get daily activities\n",
    "def get_daily_acts(qas):\n",
    "    dailies = grepcols(qas, 'H2DA')\n",
    "    dailydums = dumitdown(qas, snums('H2DA', 1, 7), allowed_cats=range(4))\n",
    "    dailies.H2DA8 = fixcol(dailies.H2DA8, 0, 160)\n",
    "    dailies.H2DA9 = fixcol(dailies.H2DA9, 0, 90)\n",
    "    dailies.H2DA10 = fixcol(dailies.H2DA10, 0, 90)\n",
    "    dailies.H2DA11 = fixcol(dailies.H2DA11, 0, 168)\n",
    "    return cjoin(dailydums, dailies.loc[:, 'H2DA8':'H2DA11'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 985,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def tobedtime(s):\n",
    "    # convert '10:54P' into minutes after noon\n",
    "    # 'AM' times are 'later' (we interpret\n",
    "    # people as going to bed \"after midnight\"\n",
    "    # rather than \"before noon\"\n",
    "    if s in ('999996', '999998'):\n",
    "        return np.nan\n",
    "    ts = s[:-1]\n",
    "    ss = s[-1]\n",
    "    hours, minutes = map(int, ts.split(':'))\n",
    "    return 60*hours + minutes + 12*60*(ss == 'A')\n",
    "def getsleep(qas):\n",
    "    schoolbed = qas.H2GH42.apply(tobedtime)\n",
    "    summerbed = qas.H2GH43.apply(tobedtime)\n",
    "    sleephours = qas.H2GH44\n",
    "    sleephours[sleephours == 98] = sleephours[sleephours < 98].mean()\n",
    "    sleep = pd.DataFrame({'schoolbed': schoolbed,\n",
    "                          'summerbed': summerbed,\n",
    "                          'sleephours': sleephours\n",
    "                         })\n",
    "    return sleep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 881,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def get_foods(qas):\n",
    "    foods = qas.loc[:, 'H2NU1':'H2NU80']\n",
    "    foodctypes = get_coltypes(foods)\n",
    "    ynfood = foods.loc[:, foodctypes == 'yesno'] == 1\n",
    "    rangefood = foods.loc[:, foodctypes == 'range']\n",
    "    choicefood = dumitdown(foods.loc[:, foodctypes == 'choice'], allowed_cats=range(6))\n",
    "    fooddays = foods.loc[:, foodctypes == 'days'].apply(fixcol, axis='rows', args=(0,7))\n",
    "    vitamins = fixcol(qas.H2NU82, 1, 7, method='zero')\n",
    "    return cjoin(ynfood, choicefood, rangefood, fooddays, vitamins)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 968,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def getheight(qas):\n",
    "    # in inches\n",
    "    height = 12*qas.H2GH52F + qas.H2GH52I\n",
    "    height = height.apply(lambda x: x if x<96 else np.nan)\n",
    "    return height\n",
    "\n",
    "def getweight(qas):\n",
    "    # in lbs\n",
    "    weight = qas.H2GH53\n",
    "    weight = weight.apply(lambda x: x if x<=350 else np.nan)\n",
    "    return weight\n",
    "\n",
    "def calcbmi(weight, height):\n",
    "    return 703*weight/(np.power(height,2))\n",
    "\n",
    "def getbmi(qas):\n",
    "    height = getheight(qas)\n",
    "    weight = getweight(qas)\n",
    "    return pd.DataFrame(calcbmi(weight, height), columns=['bmi'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 848,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# get H2GH health info, excluding self-perception\n",
    "def get_health_info(qas):\n",
    "    # health = grepcols(qas, 'H2GH')\n",
    "    hcols = qas[filter(\n",
    "        lambda x: (('H2GH2' <= x <= 'H2GH41') or ('H2GH45' <= x <= 'H2GH51')) and \\\n",
    "            not any((x.startswith(l) for l in ('H2GH34', 'H2GH30', 'H2GH31'))),\n",
    "        qas.columns)]\n",
    "    coltypes = get_coltypes(hcols)\n",
    "    choicecols = hcols.loc[:, coltypes == 'choice']\n",
    "    choicedums = dumitdown(choicecols, allowed_cats=range(0,6))\n",
    "    # gym is a special case\n",
    "    pe = fixcol(qas.H2GH34, 0, 5)\n",
    "    yns = hcols.loc[:, coltypes == 'yesno'] == 1\n",
    "    hcats = cjoin(choicedums, yns, pe)\n",
    "    return hcats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# get all the features we're interested in\n",
    "def getfeatures(qas):\n",
    "    honestymask = (qas.H2SU8 == 3) | (qas.H2SU8 == 4)\n",
    "    qas = qas_preproccess(qas)\n",
    "    age = get_age(qas)\n",
    "    height = getheight(qas)\n",
    "    weight = getweight(qas)\n",
    "    bmi = calcbmi(weight, height)\n",
    "    sleep = getsleep(qas)\n",
    "    hcats = get_health_info(qas)\n",
    "    dailies = get_daily_acts(qas)\n",
    "    foods = get_foods(qas)\n",
    "    sex = qas.BIO_SEX2 == FEMALE\n",
    "    #features = cjoin(age, sleep, hcats, dailies, foods, height,\n",
    "    #                 qas.SelfPerceptionOver, qas.SelfPerceptionUnder)\n",
    "    features = cjoin(age, sleep, hcats, dailies, foods, \n",
    "                     pd.DataFrame({\n",
    "                'sex': sex,\n",
    "                'height': height,\n",
    "                'weight': weight,\n",
    "                'bmi': bmi}))\n",
    "    bmimask = (~bmi.isnull()).values\n",
    "    features = features.loc[(bmimask) & (honestymask), :]\n",
    "    features = features.loc[:, (features != 0).any(axis=0)]\n",
    "    features=features.fillna(features.mean())\n",
    "    return features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# get features and BMI\n",
    "features = getfeatures(qas)\n",
    "bmi = features.bmi\n",
    "features.drop(['weight', 'bmi'], axis=1, inplace=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1105,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#scale features\n",
    "from sklearn import  preprocessing\n",
    "scaler = preprocessing.StandardScaler()\n",
    "sfeatures = pd.DataFrame(scaler.fit_transform(features))\n",
    "sfeatures.columns = features.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1106,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "        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",
       "            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",
       "            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",
       "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",
       "\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",
       "    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",
       "    // 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.send_message('closing', {});\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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",
       "            fig.waiting = false;\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",
       "            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",
       "            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",
       "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",
       "\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",
       "    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",
       "    // 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.send_message('closing', {});\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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"
    }
   ],
   "source": [
    "# get some BMI transformations\n",
    "%matplotlib notebook\n",
    "bmipercents = bmi.rank()/float(bmi.shape[0])\n",
    "bmi_bc = boxcox(bmi, lmbda=-0.5)\n",
    "bmipbc = pd.DataFrame(bmi_bc, columns=['bmi'])\n",
    "bmi.hist()\n",
    "bmipbc.hist(bins=20);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1107,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# over/underweight boolean masks\n",
    "overweight = bmi > 25\n",
    "underweight = bmi < 18.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# male and female boolean masks\n",
    "femalemask = (features.sex).values\n",
    "malemask = (~femalemask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1163,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# utility function for running regresisons and printing out fit\n",
    "\n",
    "def getfit(x, y, model, train=False, mask=None):\n",
    "    if mask is not None:\n",
    "        x = x.loc[mask, :]\n",
    "        y = y[mask]\n",
    "    if train:\n",
    "        xtrain = x.iloc[:-200, :]\n",
    "        ytrain = y[:-200]\n",
    "        xtest = x.iloc[-200:, :]\n",
    "        ytest = y[-200:]\n",
    "    else:\n",
    "        xtrain = xtest = x\n",
    "        ytrain = ytest = y\n",
    "    model.fit(xtrain, ytrain)\n",
    "    print model.score(xtest, ytest)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1140,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.324434607226\n",
      "0.309936264511\n"
     ]
    }
   ],
   "source": [
    "#get some models\n",
    "from sklearn.linear_model import ElasticNetCV, LassoCV, RidgeCV\n",
    "margs = {'cv': 15, 'n_jobs': 1}\n",
    "LM = lambda: LassoCV(cv=15, n_jobs=-1, alphas=np.arange(0.004, 0.007, 0.0001))\n",
    "\n",
    "lamalemodel = getfit(sfeatures, bmipercents, model=LM(), mask=malemask, train=False)\n",
    "lafemalemodel = getfit(sfeatures, bmipercents, model=LM(), mask=femalemask, train=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1171,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H2GH33GLastWeekGainNothing    -0.020812\n",
      "H2GH51                        -0.016030\n",
      "H2NU78                        -0.015529\n",
      "H2GH33BLastWeekGainExercise   -0.015319\n",
      "H2NU70                        -0.014403\n",
      "H2GH36_3                      -0.012408\n",
      "H2NU33_1                      -0.010865\n",
      "H2GH33FLastWeekGainOther      -0.008691\n",
      "H2GH21_1                      -0.007127\n",
      "H2NU80                        -0.006116\n",
      "dtype: float64\n",
      "H2GH38_2                       0.007440\n",
      "H2GH29D                        0.007714\n",
      "H2NU13                         0.009733\n",
      "H2GH29G                        0.010042\n",
      "H2GH22PoorAppetite_0           0.010632\n",
      "H2GH32GLastWeekLoseNothing     0.010913\n",
      "H2DA4_0                        0.018180\n",
      "H2GH32ALastWeekLoseDiet        0.042756\n",
      "age                            0.044540\n",
      "H2GH32BLastWeekLoseExercise    0.083140\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# male coeffs\n",
    "mcoefs = pd.Series(elmalemodel.coef_, index=features.columns)\n",
    "mcoefs.sort_values(inplace=True)\n",
    "print mcoefs[:10]\n",
    "print mcoefs[-10:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1172,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "H2GH33BLastWeekGainExercise   -0.045291\n",
      "H2GH33GLastWeekGainNothing    -0.032678\n",
      "height                        -0.022711\n",
      "H2NU78                        -0.018897\n",
      "H2GH27_1                      -0.014852\n",
      "H2NU63                        -0.013283\n",
      "H2NU79                        -0.011899\n",
      "H2GH51                        -0.011553\n",
      "H2NU70                        -0.011337\n",
      "H2GH33FLastWeekGainOther      -0.011048\n",
      "dtype: float64\n",
      "H2GH36_0                       0.009211\n",
      "H2GH32FLastWeekLoseOther       0.009375\n",
      "H2GH39_0                       0.010868\n",
      "H2NU6                          0.011633\n",
      "H2NU38                         0.014365\n",
      "H2GH37_0                       0.015911\n",
      "H2DA8                          0.029835\n",
      "age                            0.029952\n",
      "H2GH32BLastWeekLoseExercise    0.040188\n",
      "H2GH32ALastWeekLoseDiet        0.048993\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# female coeffs\n",
    "fcoefs = pd.Series(elfemalemodel.coef_, index=features.columns)\n",
    "fcoefs.sort_values(inplace=True)\n",
    "print fcoefs[:10]\n",
    "print fcoefs[-10:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1160,
   "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",
       "            fig.waiting = false;\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",
       "            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",
       "            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",
       "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",
       "\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",
       "    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",
       "    // 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.send_message('closing', {});\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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": [
    "%matplotlib notebook\n",
    "\n",
    "plt.scatter(bmipercents[malemask], \n",
    "            lamalemodel.predict(sfeatures.loc[malemask, :]), \n",
    "            c='b', alpha=0.1, s=30, label='Male Predicted')\n",
    "plt.scatter(bmipercents[femalemask], \n",
    "            lafemalemodel.predict(sfeatures.loc[femalemask, :]), \n",
    "            c='r', alpha=0.1, s=30, label='Female Predicted')\n",
    "plt.scatter(bmipercents[malemask], bmipercents[malemask], c='black', label='Actual');\n",
    "plt.xlabel('BMI Percentile')\n",
    "plt.ylabel('Predicted BMI')\n",
    "plt.title('BMI Percentiles: Predicted v Actual')\n",
    "plt.xlim(0,1.)\n",
    "plt.ylim(0,1)\n",
    "ax = plt.gca()\n",
    "ax.set_axis_bgcolor('white')\n",
    "plt.legend(loc='upper left');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1164,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.280944754265\n"
     ]
    }
   ],
   "source": [
    "# model everyone at once - no gender split\n",
    "elallmodel = getfit(sfeatures, bmipercents, LM())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1170,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sex                           -0.047087\n",
      "H2GH33GLastWeekGainNothing    -0.028306\n",
      "H2GH33BLastWeekGainExercise   -0.025009\n",
      "H2NU78                        -0.020972\n",
      "H2GH51                        -0.015978\n",
      "H2NU70                        -0.015013\n",
      "H2GH33FLastWeekGainOther      -0.011632\n",
      "H2GH21_1                      -0.009952\n",
      "H2NU63                        -0.009050\n",
      "H2DA4_3                       -0.008248\n",
      "dtype: float64\n",
      "H2GH25_3                       0.007907\n",
      "H2GH38_2                       0.008488\n",
      "H2DA4_0                        0.010367\n",
      "H2NU7                          0.010420\n",
      "H2GH22PoorAppetite_0           0.010693\n",
      "H2GH32FLastWeekLoseOther       0.012369\n",
      "H2DA8                          0.013644\n",
      "age                            0.041425\n",
      "H2GH32ALastWeekLoseDiet        0.049646\n",
      "H2GH32BLastWeekLoseExercise    0.055806\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "coefs = pd.Series(elallmodel.coef_, index=features.columns)\n",
    "coefs.sort_values(inplace=True)\n",
    "print coefs[:10]\n",
    "print coefs[-10:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "############################################################\n",
    "# EVERYTHING BELOW THIS POINT IS EXPLORATORY               #\n",
    "############################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\n",
    "def getcor(features, target):\n",
    "    cors = features.corrwith(target)\n",
    "    corsort = sorted(range(len(cors)), key=lambda x: abs(cors[x]), reverse=True)\n",
    "    cors = cors.iloc[corsort]\n",
    "    return cors\n",
    "undercor = getcor(sfeatures, -bmi)\n",
    "overcor = getcor(sfeatures, bmi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "metadata": {
    "collapsed": true
   },
   "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",
       "            fig.waiting = false;\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",
       "            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",
       "            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",
       "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",
       "\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",
       "    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",
       "    // 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.send_message('closing', {});\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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": [
    "#%matplotlib notebook\n",
    "#plt.hist(height.dropna().values, bins=height.max() - height.min());\n",
    "#plt.xlabel(\"Height in Inches\")\n",
    "#plt.ylabel(\"# People\")\n",
    "#plt.title(\"Height\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "metadata": {
    "collapsed": true
   },
   "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",
       "            fig.waiting = false;\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",
       "            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",
       "            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",
       "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",
       "\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",
       "    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",
       "    // 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.send_message('closing', {});\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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": [
    "%matplotlib notebook\n",
    "from matplotlib import cm\n",
    "plt.ylabel('BMI')\n",
    "plt.xlabel('Age')\n",
    "plt.title('Age v BMI')\n",
    "plt.hexbin(features.age, bmi, cmap=cm.RdYlBu_r, label=\"BMI\")\n",
    "cb = plt.colorbar()\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "metadata": {
    "collapsed": true
   },
   "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",
       "            fig.waiting = false;\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",
       "            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",
       "            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",
       "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",
       "\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",
       "    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",
       "    // 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.send_message('closing', {});\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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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AAReHDU7xL8BXgh+AAT+rr9Y+hmc+m/57alBVtpT7VGPosAtxp4cwItBH+2ToGf3BZ5FPqPMqtV/SxBIBBiY9tT5pNIvAEeZCatBR9lQYKt8Ie3REGDkb+kDlXzeenvqt1z2yv1b2HP1o9k+ZMJLqXAM9SmjmS5Rv8exFBJLqu8RV6OMJVffq3epeIeLiSA+265YkpPRItZjxqU0Ve/mzoxLDMAMwI3XFjY2BjmA18xSTSBWBjE4SBCoHnqtvmPL2vQXWv8taU+CtJn5NLFnfkeBgwnSKquVy1KdSlbpa585iVC+UICqAFt3ug5e5vO67WHwVVlvefk2rn3Snm3lAvbkRKGcpfr9J+3ZDjyHvUFO1O8m1DG2I3Z7LKm+2quxZI/1vR1LclWtuoKyG2JJxYttnBuuFAatmPISdD1cBTm03tzuuWN9fSPv93uVBo12T8a95+bb72q6J6M/nG8/aXT7e3F7UK62u9qN547Z292OvndFfPv7exxLxcqQzxf2GBxtLMX11W6PJc6AOQNujPAMwIWrGIClLxiAi5iIITyp1RYXL8JFZvRPRlzEv708mWMARqxwBlwPV5wBaz7irEUfoGMYrnt50Ixr+27PWng1RfYQZ8BNJ1/uyQNnwJwB108phndgD9hWHiPZzS4Gbgy7OY4t7WIISzKWiy3tZk3GMWbtbGSdjGTuode1z7Z/5LPnZ/u6+8o1oNbbszNSYU8S78pzUh8Dt32mPMdSscwcx5R3vwccS/oSvquKwzcudbuWmkfPiMwZcD1c7dsMWLGgFVNZBwE5I9bZvoq4U2W46kQWGxtZldKY9oDzPQtjVmcM67ZNtjSAQC2ZutqgZvaKgVzHlvYxUhUxRGcg68zuon0FW9pur8puVoxmmz08g8lIbcqWNjMbk/XetO9lG9D3aYmIFWtPscVNYk1sLPntSXZ381iSbGRbZYAemxxL5QqKprHk6qu2Y6lte03GJQZgzoDrpxTDO5QQh4/96mLgwoReFqP/aKy9ekZqUSajZwH4bzv7ugwW6jtF+6r2fCxHBT4mQ9NvTw7mtjrH7bCnMlQbs93Whrq+UqVXbdlTk4ntthcTS0363s2W3p2xpN5TvWRNvQeq7An/rlYhyJI824pH7Hs/qliq73t31YWNfe1axbG997wEzQAcDMDqJbWJIMjPWAlLB3yXWISLYLMflbC2g6zlshmrqha3t7u/lLBe/epX0yc+8QkBpA95yEPo6U9/eml8gG+Xlpbop3/6p+mjH/0o/fM//7P4/Mtf/jJ993d/N93jHvfYvP8nfuIn6N73vvfmyphtoGmTef/Hf/zH9NrXvo5+/dd/je53v/tVfu4zn/kM/fzP/7xY2VhZWaEf+ZEfoe/6ru8S97ljqeAxfPGLX6SXvexl4t61tTXC833bt33b5u+cOXOGHvGIR9Bzn/tcetSjHt1IUY8BmAGYAVjzQNwgHEOucg/cDMBFh4xyMhfX97sPgHUwCWFm//mf/zm9613voje84fcoy1J63OMeR6997Wvprne962aHwN6znvUsAc6/+qu/WgLgH/qhH6K//du/rYwnbcua2sDyLW95C33lK1+hj33s4/TsZ19XAkbVoKc+9akCdAGa//3f/00Pf/jDxSQCWyVNAPhpT3saPfaxj6WHPexhdPz4cXrGM55B//AP/7D5vC984QuF3e///u+nRz7yUQzAjZHFfiMrYRl+YS3oMH1m30rBuGlB7/UM+N///d/p9a9/PV1++eWETGhiYoJ+5Vd+hQ4ePEgf+chH6Dd/8zep1+uJwRxZ0hVXXCHA6A1veANNTk6KjOlnfuZn6JprrqEXv/jFNDU1Rf/5n/8pAO6d73wnffCDHxT3HTp0SGRp+Px1r3sdffKTnxT70ddeey29+MUvoa997asCAL/zO79TZKq33347/eIv/iIdO3aMHvjABwpQATj87u/+rnh7EWc33XSTyFjN6xWveCVdeeUVm39+6UtfSve6173oMY/5XrHEjOfDc1533XUlAMaz4Hcf//jHNwLgV7/6NfSIRzyc7n73u5eaINv7CPrUpz5JJ0+epOc85zn0oAc9aPMeZKpow8c//vHS99BGZJn6de7cOZqdnaUnP/nJ9MxnPtMKwM9//vPpO77jO+hRj3oUfe5znxPPhT46ffo0vfzlL6c77riDBoMBPeYxjxFAa76/+I3p6WnRx2gv2oo+wPVXf/VXAozvfOc7013uchfOgLcIvvg6A3ANANvVXQpCitkHLmUa3OdiUisGrmtvCd+1L/G62cgKDOyKXtW9OfUi+vZE3Uo8bnu2tvvZ0gWxrepb9/6163nrGMc2FautsLlD+0rtObr612XPF0s6sU/3oS828dlHPvJhsRyLgfbiiy8WIImBGIP4ox/9aHrHO94hwPNf/uVf6A/+4A9EFvmnf/o++qZv+ia69NJL6b3vfa8Y7H/t135NAPDGxgb98i//MmHZ8tu//dvpYx/7mFj2/au/+gAtLBylz372s/Se97yHfu/3fk80E6ACcL3nPe9JD37wg+nd7363AGVMClZX1+hFL3oRPfjBDxL3/cAP/ID4TmgsITtEFiuXVRN6+9vfJsD8Fa94xaY9FUvI9HQA/tKXvkTf933fJ5Z+b775ZlpYWBBtAiiaRDzldwDw4x73/fSsZz2TbrzxRkKG+U//9E/i47rKAFffA4CRmZpL0LD3ta99jZ785CeJic6tt94qfPet3/qtYmKELB+Z6/r6Oj3ykY+k66+/ni666CLnuPSzP/uzQiXvZS/7KTEZ+bEf+zHxHfT9ne98sYgJ97hUVA3wErQbqRmALQCsv0wmeUEnW5QZgIVmrXq5FHjrGri6tq1Py9jGvi7sFULtpj0F9IV2swRHuz3F4i2Ym6a9Jgxc9RxqwHCxvnGfac/GEjXtqe/YmOOuvtLZ4ZItXQZ2tHHr9hSTuGnfV9ugnn/0sVT0vWrDv/3bv9FrXvNaet/73iuA8q//+q9F5vrsZz+bsLSplmnR1uXlZQGQ2B/9/d//fQFAAFoA9JvedD391E/9b3H/D/7gE4Wfkfndcsst9KAHPZge9rDvpgsvvIhe97rXCqB/ylOeIsDo+uvfJADkSU96Mj3ucY+lD33oQ4LUiH1PZJCvec1rRFb827/92yIbrosl/X1RsQkAhP0HPOD+4s3Hsu6JEycEAJu67ADgH/zBJwjARPvwzH/xF/+/WJ6dmJikn/7pl9Hhw4fpBS/4X85YwkTit37rtwRYg+l83/veR0xwDhw4uEmSDOl7TBqe8pQfFgD8Ld/yrZsAqMYlgCR+ExkuJgx43ve970/pB37g+8VEAasOuJAJ/+RP/iTd9773FZMs/b3H56985avoy1/+kmg7QPg5z/kJ0U/IzH/t136dLr30EvEbuoxseWws3omO7fQUT/bIZUge5ww/2rdlSIPBILfVuvlZf3a9Yhs4KteO1p6dcexrX122FJrZxtuTRwnaM/lwfVz43XWKlTowI4yNjL6vamnrk4ZqTbS9bldOGnYulgB4ICghk8X1N3/zN/Qnf/InYin0ec97HmH/VD/8Axnufe5zHwHSV155FX3gAx+gt7zlzfTmN7+ZsNT7jd/4jSKDVH3/pS/dRH//939Pb33rW8XSM4Do/PMvEOCOTApAjmVPZHjIcP/hH/5RANvb3/52sUyNpWxklMiYr7jiylL29fnPf966BI3nueyyy4YT0Ixe9rKfpnvc4xtFJogLGfrMzCz96I/+aEVrGaQrtAMAbKp4oa/+7u/+Tjzrm970ptKIqfc9Jgy/8Ru/sTl5wWoB/ATgVhfa4FuCNmNJX4I2xxEQxDApAtjiM2Tsr3zlK4VvkNFiiVx/7+FTrERg2RlbCZiEAJjxjuB7+F9MirBqcMEFF4gmY2KCDBsELZDS6sa5LgTWAy4G4HpnBTm03tzuuYOlKIu+wAvM8oHjI0UJAAYQASAAjD/3c6+jmZkZsR8L4HvjG99IR48epU9/+tMCMJAB3f/+96cPf/jDYoKE5VgszQIwX/KSlwi2MAAYmRhsIhvDhb3k+fl5Ov/88wUhCnYRa/htAOPd7nY38T0AMID5bW97WwmAcf9ll13uXP70VS4ANJH1Yhl1dXVV/B72YDGBML+nABhL7riwh432Yj8az/uqV72aJicnCMQk81LvDvz2pCc9STw79mSRoaINtqsps921BA2b3/u93ysmTFjyv/XWk/SoRz2S3v/+92/u36NfsASN1QT8t8qIVXv+8A//kG644Qax/WBeqn2YUFxyySViCVpdvrbzErQb33gJ2vANAzADsPm6bAe5yvVK7qSsKQD4537u50S2pkhYv/RLvySWlQE+2E8EYQn+AKEHy6qvetWrCOStI0eO0NOf/qP0kpe8WCxVLi4uCgBGBolMGaQtELLm5uZEtoXMC+Qu/O9//Md/CHdg7xd7xwA+HYAB6LhHZcBbAWBkdAAXMIPxHJhEPOEJTxBZOpZ2kc2ePXtWZHxoN9py5ZVXikkBsmksVX/qU58Sz4D9U/wb2SYADfvXioSlAzDKgJChw9YLXvACMWmJAWD8FvbRYQcZNH4XqwHoG7QVkwnsZ6OdeDYALYD/oQ99KJ06dUr0AVYYcC9KiX74h3+40gwANyZGmHipCxOOCy+8cLP0kgG4vYSRAZgB2JpJwC2cAcvgGCcAxnIo9lzjypXcpWr7PZawHw6gxiRCf3fUygE+q48lPowBPuIl6HqA37dL0K7zgOv3bG37gAURIWwfEHu2Vd3puj1bG4MZXVmn0hNyzmisPZMEpYeYr30+drOS76sulRWkMv0ztcfa5h7wAHvK1j3g2L537SnH2mu+/4+lZADwW9/6R1aVslH3fSyb28Xk385YAmHtAQ94QEneE+8V9oCRsSsA9r+Lbfd92/bsseRjouN5ez3eA3ZBKmfAhmekFnRR7mKyAyXrT4Kjrn9sv6/QCpbfKbMNfSzoWHv67NvHRm6iCWtjNzdhLdexoNFG6YuCFWy+xE3Z1/p99faKcimTBa0z1lVpks2eum+QZrQyyGmNutTNM5rtEfWH40w5RjiWynrhsqROByKz783YRLzgO74Yqe/74ndj7am+11nLalKiM+pDY6nMgpbvRL09H/MeE1AfQ3+04xKzoN0ZLQOwBYDVUpE+kOq31WWi6gW3ZWbhma299jU2G9EnDWb7XFlq3QzXlXm3bc/FpPbVUbtWLqT/4FsMzGXxEbOEqdz3Ga2lRMtZh3D+lH5NJRlNd6s123577sy2jjlu87s/NjmWVH+56nZHHUtqMhq2ihO3QuYfl6qnfbUVS0zCYgB2e8ABwArgWAtaOshPDnIdjr4/pShvW80oTzqVmOpSTocn7bszO0muMiePtrLMpgxc26RtNEz5uP1Rl99j+8O1lz0KKcpi8hB3BnUTKcrqRMAnQypPhqv7DgMwAzADsOaBtgk27kGOAXj7Bs04QIrr+92nBa2/0CFa0FvtDwbgwvNNY4kBmAGYAZgBuBIDsVkLZ8D6IDyqWvG4CQdnwEVfcQbcGAZGdiPvATuWoNW+nW3fRO3NxZ2TGXbupm+vSlclKi8zFkSOMFUn7GraznBV5/dWmdn17Qu35ztz1dYfat8On5nLob6+8u0p6xJ75Wwro42M6FyaUI5NWO2a6WQ01a22gWOpnDUpIDCXL/d+LFVjPbbv6yoX9tK4xBkwZ8CNZzSSBV2Usdg0lHVWpyLCmIO5/m8XQxON0kstXMxfeV/BGPa1T+oty70ZG0NYtV1nXuoDn04YwrPpRLSyvTJ5SCd3NbdX2ADzE79dZszKAU3X0i7aV9UytjHHbfaUP9URbfpExsXONfsK962mRCt5h/pJRjMdon5P7gs3YfHa7O1MLBXELDPWtzeWmve9YqX7Y7O5PVWR0HYs2freVjUQ2/ch45IC6O0el8qxbo8lZkEzADcGYNQB93rVI/nq2LQ2vWL1gtuIXH578qAAM3uNt5da9Yr9jE+ZDdsJNu5TmFy1mytt7BwAACAASURBVBLkRmmvmonqwGsGRKxvUY7Ubbmv9mos7Z6+r67U+Jj89bEZHktyMlkl6o12HEmtOuqxsa5K90LHJdaCZgBuDMAsRakvF45qfy+O1ena33MRZfBkg0EKYQBrPLi+59o7UxlPDFPeFZCx7Fz3/l7c3mlTgo25PO/yxX5XwjL7My6W4vpqt8cSL0EzADMAG7WuyiG+AZ8HTeklBuDi9YlhHPtWHmLttU2u2h2TOQZgxApLUdbD1b6VouQMmDNg2/K0uezWZALjA5fdnrVwBix7aLSrKQzADMD14Is79i0Au7Sg/YxZkLaSyqEGsQzcNJWaq+ZyHgaDLJMydVUGqU//WGo22eyB/GRX57IzqX2sTkmCsuvPunxhEmH08IO9DWjJdhPqGvtpsfbQPpsWdF1fufSF0SeK1GMux+LfITrb0hftxpKPKT9usSRjU0rCNumrJrEeE0u2d3E7+l4SCsPHJXesu8cRVywhnnkPmJegm00r5HJjiQVtlgM0ZSPrhBQXKxaNqmPMypIcO1sag7skUpXBVS2n2ViTdns6g7Rsr6yLDVCWzOR4RioIYXIQ1JnTyhd4Vny+keai1CelhCD6ONvNaaKL5zXZ0gXz0mfPLCtShBI7+1rXDS7rR6vBM5aRqg9uHEujiaUyk9/Hlt7uWCre07r3XteCrtPSVpm6GgdiY1OfGOjvffNxpJi06+MS7wHvcwC+5ppr7p9l2XvzPP+4etRut/vMLMu+mYj+JxGtEtEX+v3+j9xwww3rPjQGAOvLiy42sovl6MqUJcC4WYk+1qT71J8YlqMcgGxkGV/7MIjZ2dx+e4nlpCAFti57y4OcVvMqg3QaWsu9avav7IUyx83JlZkVue3Zs+hYZrsvltwnXHEsNXlPXXGrskO7lGJ4FQLHUvH2mOMIA/AYAHCapi8/ceLEA9SjXn311Zd0Op1/7XQ69/zc5z5328LCwhuI6LOLi4uvDwHgGIZr24zUtu21vb/nJsTESVGeXM2ILFrLE0lGByaqwKwmN7blQJUd2EtC7Fq2+M5uYUvvjr5nKUo1ZrAUZTF6Nh1HGIDHEICPHj36lCRJHri4uPhDePyFhYXvJKKXLi4uPogBuJmIupkRuicj7R7GwABceJ4BWPoi9rCIttnSDMAMwD78CP1sX0hRDpeg/yBJko8R0cV5nv9jkiTniOjA8ePHXwinXHvttV+fpum7FhcXr2EAZgCWmTFnwMUybhwDd3SlanHtYwBuMpmLq8PnDDgUbqv37wsAPnbs2MVE9MA73/nOb//yl7/c7Xa7f5rn+T8kSXI4FoAVQcamjawICiZ7WGdNmvuHSibRZU+VudgYmoqYpJfC1NlTRHUza41hD6vvIHxcTGrzeX3s5jp7Sms508j2nTyn2V5OPQs73GdPfebrK9czjarv0VdtxpK011wXu4glm065JCbZ+n4vxJI63F5/d3zs5iKWqrrOHEv6Pq+sunCPc0UsxSxBHz58eOvotgcsnH/+gaiKoqgvjcofCwsLzyai5yVJ8qHjx48/Eb979dVXP6Tb7b7g+PHjD/W1I8uy3FXzOar28++A6Uzi4PullGi2SzSJQw52ddRxr7EH2AM2D4QC8K23nszPO+/IWDgz1DfKKbtqKFxYWHgyEd1jcXHxBZiuHzt27J15nn8sSZJn5nl+r8XFxZMLCwtvzvP8X06cOPE7vp51a0FLcrSNNalqQcM0Ut3ayC57ctnULg+pdJ1d2s02Ri/suZboYu213T5oLfe6VeKVr31t+6/Onjq9SY8rf/vajaVR+kKVb9kmqbshlnx9FdO+ur63vW9b6Y/dHEuuKom6cSnmMAbOgP3zj10FwHe/+91nV1dX30RElyVJkuV5/tGLL774eTfffPNjiej5RLSeJMmnjx8/fh0wzPdorIRVeGd0+3txe1CuAXW06kVxbXfFoOuZ5GTJvQ+6O8habl9wLMke98uaxu1z7/ZYCs3yWIqyPvnfVQBc39zmdzAAMwCb0cJa0IVHYrWbGYAZgJuOwgzA9Z5iANZ8xFmLPkD7MkJXuVJcFskZcOF3zoClL2Lfxd0RS5wBow8ZgMcYgDc20tzUWvazm5U+s4t1Cl3nsv5sHVtaySbaGcx+e1VGL/SF7drSSroxpH1ou0urWtkL0cX26+1K6UufvRD2MNoHe67znm262PV9L/ujqc52vT3EEcfSVmOpys5tN5akLnv7sSTHnjLnQVVkhMQ62ibLhNqNpRh7PYi5B1wMwPXOCnJovbndcwekKFVZRqG1rOsBSy1j/H9dY1bNvlH+Ifd6Chq+GnTt9go6v9ue1HxWg4puTx0mrqtAKeKIqX+spBIBaE3t6aUmNnsKtHz29JIY0x58pcBLlXfhOXUt7aKkSbbbpqesvtPEXtFX0p7+nWrf17dPt4fSJb3vRx1LqmRtr8aSq+/V39uMJfQVLgV4Cuh2RyzJcQSHHPR6EpBjY2kwAHHTPy6Z44iS1nSNc7CGz5qMI7wH7Ma3fVEH3CZ8m1rQoepPkgFpZ0v7l8fsy7CxbOQYxqeP5Rhnz66p61sqVGBr16r22bMv38XbC19Kj2Hg1vmCY0m+3bHsa58WtLsyYDfEkpxohrDNd2ssMQAzADfG6OYAPDpG6m7f32tbC5rVi4pw3R19z1rQqkdYirKITVbCagwrzhs5AzZcwwDctQZLTPbuY8z6DjtgAGYANoOQtaALj8QSzdyTuTgSJAMwA/DWPcAAvOmB2BITzoDV/pokZNmu9gfNOMZs00FTfwZfXIyuvCjueXky12QyxwDcOpA0NMgZsAOAC01Ymz5uoeWh71X6GK4+ey7dad2eyYDcTnvm3pgiR5nayOX2ldmWxTNV9WLj7Mlzh3G521fuqywnOrueUZoTTXeJpvsFu1TXP3bZ8+kpox1t9L2rH/dyLMX0/SDNaWkg+RPTPaKpIfEIfo6x54/N+lgK6XuOpWLSaYtn3gPmPeCG8xHxsgsWtD4o6wOAPvCabGQfO7dqT5bX2OzJLMpk06KMQoKPvX3Vch2dPexj55r29BIQHfAKe5LlrbddZ2jaGLj4fcmaLAC0bK/c/jp7MtEsszDxF1lqRLSa57Q6ECcSqPSUuklOc72E+t3Ch+o7PntDA6VyMl/fm0xvVyzp8bLdsST7UbFpd08soV0raU6rGRhHRV/1hn2VDONGScDqpXNNY6nqW5T6yHdPsX1dsVTX95IlXMjDbtWeq9LA/d7LFo4ylsos//pY6vVwhErzi8uQ6n0V5NB6c7vnDpcWtMq+bEuMPulDvzayW1vapjGrBgwbQ7iOLR3H5sZEpKrDHLMfXNc+FyM1xrcrGxmdSwWFtBJYc52MprRMWL/BR7CJYaT6+l4OmtX2xTzvqJn3bcbSuY2MVrJqjME/892MJrVMWPXVKGMphn2NdnIsqXmvGEOC8IIBuB4Pgxxab2733MFSlEVfjG5/L24PyjUREADsGNRnk5SmJ+xEMx9gtr2364r4vb1XHK4FvbSR0mpm74+5blZaitZ91vbersveaHXF4/a5d3ss8RK0G994D9jwDQMwA7D5urjYo74VCfmZe0Dd7YNmHFmLAVj1a9xkjgEY/uMMuD4h5QxY89G4ZS3ts6U5A1bhNG6xxBlwMZDEllrt9skcZ8CcAddPKYZ3DAaD3NQe1lmOdjayJBBV2bRgS7vJUWofUN8i0QlQMfbs+tHy4Vz6uD4taJMN6mOkKn1cU882li3dxB6eS39m9BUYtecyojQ39oGzjOZ6OU31y0ueRfuqfeVnuNb1r9/eXoulur5XKwU6b6Cu7wcp0bmUKAUhUdsTT7KMZrs5TfTcOurbH5s+trTse10CFrHIsVTs5ytfsBY0A3BjAIYQh84eloNKlUFq6qCqJUfFbNaBwbSnf2bqz+ogWZTr2FmOqg0mCEkmpo0hLHWsTQazWkrFc9axm832qb1RnRlZtVcMVM0YqWUtbd2eGuTUwOeztwyCTyr419RPcprtJaR04cvM9mr7lP90kFTsZrtv9WOmffb2VyzJ/ihPggomcPkzk9leaJsTLQ9SwVrHnGkiIZqf6GzicdnezsSSr++bx1LR93sllurGORv72hyXOANmAA4CYHUzRMyVELppwLVU6GNLx7OH29OWxnO4yVXh+se7xZ6rrwAO64OMJi3M5+3QblarGma8cCzpS60u3XOijTSjCQvzOebdiY3NmL7iWHL3LwMwA3AUAO+W/Ti3hFwcaaNtgo2bkepuH0tR6gPW6HTF4/qetaBVb7EWdBG3TWOJATgIgIcKC37I2rckLNaCZi1ohL5vghDHcI0jmu2OyRcDMANwFRAYgBvndc4bK2VISYcBWHkrdtnLPWjGLfG67PlqFH1td784ce2Lqcn0LfONaonc5Qe15+wSnGgfgN1+bzuWXM8cH0uFCpQ+yvjiL2aJN5Z5z7FU9MqoYsnse86AAzLg3gQDsEki0olHpnyizoJ0SVZKewUBymUP9+kMUp2Bi890QHDZ09vusqfIVqH2TLKNKU1ZtleQkmxsblsbfL7VNWZt7OE27aEfcelSh/LfuZABlVeZAVtuX7kfFYnIZU+2vWxvP8aS0uZGnUHfIFrtxlhq+t77YpNjKQHxM2jFdKzrgCdmxhuAB6hhqYBdUW5i/0wOyTowlAfrcglQMSBXy1RcL3OdPRsoKDBW86+m7SsGf6nfrE8KXEDja59ur1riBS1Z6Qc7o7IKhOWysCrYqdIvva/0AR7Po2cD/omO7HvFHleTDP/zFuUrvnhxfaaAWpWn1fW9AnDTt7spllYzqc2da9KmKDXCwQuTHRfL39b3UnvYVt4n48wdS+o9KGtz1/WVW7Nd9d9ujqXdMC5xGVJABjx9YLwB2KcFHSdHGL68GL8cKA+RMK/YpXQ34cS+7KgAP3Tpdre3L3ap2seUH6dYAibetpYVhy1oATqVZDQ3YdeC9m+jhC99x9iLfxft7XMtA8e+O+6hXR40EarbrVZ6QnXKfb/FGXAAAM8cGm8AZinKIlj2qhb0aPV748hVrldytzDvmxJs9OdwTzjcADxJKc1Ptkn8i+sPV9tHG0txVQ27PZYYgAMAeP48BuB+v1fxWOzM1Uce2R0M13D93lhCTAxZK+a3Rjtoxg34u33QZACWPTTaWGIAhs/Heg/44EUMwO0CMC9BK7AZHSO13SXy+MmXu+/jAHhvxhIvQRe9PY6xxBlwQAZ8p0vGG4BBwvJpzJqf6UQXG2tSkiBMdrMikvg/c9kzyTuKRGT+jprBK3nJUHsqbFzs5uakLkV0aU46U3tiNuKMSUoy26cY0XatZckm1wdC3Z6vf2P6vtpX7r5vEks+e77PQvp+LUV/kTg3WacUxLVPMscFCQtnNOvnS2cZTXWJprvNCYwFYc4VS4qEJbXZ1RXTdp29zrFUxG1ILOHdYhJWAACfd8V4A7AS4oh9YRXg2vRxY8CksOcuU2lalqOeyVb2UseYVaBWZpAWL2W1LCcVzGZzAtKcPWyW+dh1rJvaq4KnXxfb1ld1ZWE2HfCtTCT017ZJiVfdxKQullAetJwm8mAElMQR0WwnI6UMWdYBl6Va9ljS+74AQhQYLA1ywu/0EqK5Btrc0n/7L5b8fVU8rzmp2sq4VDehbgqsvnFEL59T4xJnwAEAfMFVDMD6rLlNFmEsK3E3iCfEtN33HRbiKF5Kn59GJZ5wdj2jtdzORp7vZjRp0WdWKyx6mVqTd2djkFG/RXttx1KMvVim/H4UdTHjmQE4AIAvWmAAbjKIjJJctdvJWm5yFWtB77ZYcgHF2bWU1sjORp7vpDRpHOGonmt0TPk4glLbxD/Wgi7ApClRjwE4AIDvclcG4N02aDIAyx6JLdHZn4NmHCAxAHMsmXAQ/165dAfKsckAHADAl96dAbgZAIczUmOWceUynz3QByi07xTnpurd7KvJTLOMet3qcmN8+8JFEWKW+dpuH/Ykux2pwBUyKO3mZUNwDxAX7iVeeywtrWe0OqIl6BhBjFFuZ8TEpm8JOmbJfTvY0qPazuAlaDfgmp9UDmO4/B4MwCrbshOPJKPXp6eM75vavi5GpamBaxJd1O/oJCcMstizW89IsFRneglNgdUyvPTf0u1tHlAPhms3p9l+dxN8yuSJgrVd1z49oFxEIdxjSjjWkbpspCkbycnXPpeeMvx3biMVrFz8Dli4M8Pzgv326vteySTqGuGuvtfZ61XSniSJhcTSxpDkBDFVaC3PaiQnvQ0uHWt879wgoXT4u4qEhdVnU8daJwOZ9vZnLPkkKyVpyhwTMME7N8hpIyfqDklnffzHcFJdN460GUtF+6oa5raqgbr33jYuqXFTjQlMwqoH4goAX/lNexuAFxYWfiPP87v1er2npGl6PM/zD2puePmJEyf+0eeW0DIkfbBpXoZUvMz20hZZSmGzt5oSrWZEeaJlsKD6JznNdYl6BrkFA2Wa5XQuSyjNE0lblaM6dSinWXynUz7owQ8MhS627ZAFDBr4CR2MC8anvXTEVzak7Nl9W7VnY2Gq/sZnawOiNerQACcDaL7oCv/l1EmSUtt99mIYqS5wkoNyfalHtaRNlvksp0Trwh1aXEBruZvTVNceSxJUqweAoAyJcqJJaxmSOzZtfb+fYwlnduB9s5W0raSWsqs8owkxMSqXXcX3/dbKGW2xJLW0q+WRMtb9fW+LJS5D8oNwBYCvvu/eBeCFhYUHEdHLiWij2+0+NU3Tv19cXLyyfh5S3NG+FGX4UrVPfef21YwyfZAdNh2werhvX15sm+Hatj5u20vLvvadXstoQxTYVK9D3awygVEZaNvaza6YjPEF8PKONW1CoRmfTjKajdJaZl1xBYw2lrfK9lxVEretZKWDJ1SXdCmnw5P2w4Fi+t43tsXacy1Vx773vAfs7qUKAC98294E4Kuuuupgr9f7QJIk12VZ9gvDDHgXALCbLBNDrrp9NaUsqbJVfQC8tJ7Sau5guEaVmPgIQOEC8LEkENf3fAPFqbWUBg62b/sA7PZTHADb7fkBOKXZCZfWsrt9TRmu+nPE7e3u3VgaDFKITFi7Mg6A44h1bcaSb8Lpl4V1t50BOACAr73/3gTghYWF6/M8f2ev1/v0YDC4fgjAHyOivySiy5Ik+VSv13vhDTfcsOSbNbafATMAK3+3XRLCACw9ywBcvNGjnMwxAOt+ZwAOWWlV91Yy4Ls+cO8B8MLCwqOJ6GGLi4vPuOaaa65I0/RNExMTj9jY2Hj80tLSH918882rCwsLb0yS5Nbjx4+/yA/Ag7xvqXks9kbCjvvzMWbRjtBjv/bjEnTs0lbMcYneJeienR2ObBD7Zba+isn6fLHk84XrM+xnn1ofbtwZwT2TZDQzRkvQo4wlX9/ftpqVeRrDfulRTgcndj6W3FUSag+4Os7F+jYmAz58+HAMnu2575x//oGyo7/hIXsPgI8dO/bWPM+vyPN8PUmSKSK6JkmS9xw/fvxpqkeOHj36PUmSPHdxcfHBvl7Ksix37fftht5dTyEXSELOT13Y0cSJbjNCU7faSsH6BfkI5C3tYxBCZnqShLXVS5S/ZPJ3QDKBTVtbtvo7W/0+uCRooyAsDS+4DBiFdluOU97qT2779+F7kPNWUiIpECkvEOMRE44V6G1v1zj/gOs9BeMe+te78d3Yrv4KBeBbbz2Zn3feke1qzq6yW/HNNz5s7wGw7tFrr732cixBdzqdV+Z5/vTFxcUngr539OjR1xPR+okTJ17s64FCC7rQY7UxcG0auLpWsK+MxsYeDrGHAXd5IMtoVHlDb1jegGfTS050kogqUwEBGAPz9LD0xvyOq324TyekIJMDwxrtWckAagWSTyQZTYNhK/T3UaJRzAwwk1aXaU9lm021tGFH2TO/U9bbLZdfrA4yWh7IgXC2m9BEqYyr0Im2sbntfaUzUs2DAAp72xlL6FcQ7jARmqyUmfmY9/ZY98VSne60rcxMt2eLJfS9uppoX+t977JnLxfU488emyGx5GLKq3K3tSwRk6H5ieJwi3KZT4jOe/uxhHfTLDNTfSX7w2xfWCyFAjCOIxzbDPj/e+TeBmAsQWdZ9gfIdI8dO4aSpHsT0XKe5zdNTEw8q24PWAGwCkC3FnS7e7sx0pa+PSiXPbxoGOi6GmCrQS/m7F3fUXO+w9b9bbcTuWL399xyiZLpa8tGfO1rX4ij3Vjyt72ZepE+SfXFBUtRSk95hTg2UrJta6kJhI1lHS/EERNLcWdaNyXqxQDwoUPjsQRd2QO+16P3NgBvdX1hLwFwLCux6YtTHoTtL+leBmDfoLmXAdgPmAzAW5lc709ZUwbgreJG7PcrAPw/HssAXGSEcYEZU14UkwEzABdhH5OlMQA381+Mb2NWU3zAGBvrbTPvGYCLmGk6kecM2A3PFQC+7+MZgJsBsCsjdLMIYwrjAeZqf8bsRp/e89pGJpSMzOVVaQ9ZUDta0GjbHWt2cZCpJKO5KAauXVsagx/2q2wkOZ9+r69cyWUvpq9i2dIxjFRv3w8ymtL291XcQBoR26z6fneTWHf5tu1Y8i3JxvSHz976IBOqZzp3YtNPA7sgi2+C4IvNmLbHVl20GUu+5w0ZlxiAAwD4W5/EAKwIEtgfVMQQtRes5AfVZ64D6nUSVqy9st6uTU8ZxCYJ0Kp9YF8ubWSUEQhauTj0XOnPqoPNTWJKQQhR9grShSKWqedV+q7y5RySdxIiwfrMIG4pZS5nuzlNdBNKRPua25PgClKI2p+V5C2XlrHpW93vyn+SZNKePVvf633VRt/X6SnbYnNlIxMM+dzoe137Gr7EnAiEIEUmkxOHaiwpv9uf165/vJVYKrSvfbG+tViCL86sZ0KfGcGqa6LXxZKczMbHEr69E+OIiiU1GVeT7/hxqWnfy+dlAA4A4Ps9ZbwBeDBAgU9ZD1hnfNoYvXK2Wv6OGryUfqpdG9nOEB7KsZY0idVs3vZbgo0MIX6UJ5kyi3lGUx154EDTtuvPqwNu0QYZUKY9nMIDpjUAXz9tyW+vYFTataUlcNrY0mI4FCzrIpvXmeg2eyajU84XpJ6yzZ6v73V9XJOspz6T/ivatx2xtNn3uta37CxRDiaknQ350iTPaL4rT4Nyxab5TC6t6rrYLHxbZoc36Svfu1iNTX8srQ71mXN99WeoiT7fI8IBYVuNpeK9r8bmVmMpZFxqEpsh9vS+d8W6y17PtszgxiQCC3psSVjf8bTxBuDdroTl2gsDftzu0AOeSlKac8oRuve5R8dwjdtrj1HC2i3kKtf4E8P09ilh5WlKSdchQ9pJadIiOiMBNYastbtjyStD6hRhsW+HwEftxxJLUcKvYw3AD3gGA3C/36uMj6MtCwh/ERmAiy7zKfa0P2jGTR4YgKUH2idrufuDAbiIulGSPnkJOmAJ+kHXMQAzAMuA4QxY+mE7Jl8MwAzAZgzEMr3bjCVfvMe2jwE4AIAf8hPjDcAbG4PcdsKJj5UYo98bwiLUu89ZVpHldAf0FS1HFYKNPNu3s4d9ohI+trS5v6ra6GNhxtiLaV8sI9VXYhKjBR3DSI2JJZ8WNPaBxaG/lmvecRJWHbt5VH0fE0u+vj+1llU5EhJx6FA/L/EWlLt2Syy1rSnvf68kv6M6QQg/6Wz4ztvPX3Tg0lgvQX/Xc8cbgKEFrfa/FCuzjo2MYFWA2oTl2MSeyb5WJAg7G1kelr2RJ7SaaYfNg31MOc32wIjGPQXhxmdPfiaZsbpEnc5wzXPTnipvkszxMltati9J5OHlagA37emEpSr7uiDIFAQnl70ia1WkGt0efkcfgHzM9qbsZpN9DW3m1TyhuU4uyn62O5bWM6kRvkm2Qt8nYKMntJbltAbi6hCI86EUKNo0N2SrqwHXJI8VcSCJajImyn2fZplkwacJzXRzmuwWZKvdFEtg7C1t4D3BqzCclGSZYEJPg4FFttjc+VhSk7/tHpd0ohWwUY1lPrZ0k3Gk19N0Xt3J4OYnYw3AD/tf4w3AhRa01Is1WbZqadbGVK5nOcoYs7MIq5/VM2Zt3yE6t5HSepYI0ffpXlELHGMPv7BZbmRowsazm5X2cFljVv6W8nsIY7aJvaqOtZrk2NnS4X0FXWw0fylNKNcKsPtYgRAM23Ib2o4lxOTSsMQGfT+j1QKjBvjsQLYPbdNrqXt5tnkQRTU27b5VzHt8ei5NRNmburo5yt9yoQMeYi+OLd2k78uxtD7I6dxAnnCFMr2yjnoTe9sfS3WxOZpxqdAI30oVBy9BByxBP+IlDMB1y6kKlLoOdqlrzzB2D6Vte20zXN1qQ24y2W7Qgm5bCWs9zenMwL7a5j8WMEa/N5yo1/a5wZL4lzm2PeKY9zGxFEPkimGbqwmTTcSm7VjaDt6BexyJIxI2HUcYgAMA+FE/xQDMAFwNmBg1H9/AyABc+HhUjFQGYN3nsaDjUmmzl23hF3cL854BuMH694hvqUhRfu/PMAAzADMAxwyanAEXcRNbe84ZsPQhZ8BjehrS972CAVgHYBvjU+192o4q1PduTBjD4BLKIJX23NrNofb8DNdUKAHZtJZ9jFR5vKFdWzqmfXH27Euy/r5ya0u7nhdKX2c3cjo8WdXZ3hhkYj90oO2HqhiY62Q0qZGx1N+xNwuS1Iy2V68+azuWsEd9dj2ngYUpP5dAlCOs77GXegaMJgvLejZJhR71bo0lyHb2OoVMq/6uuo/ylEQ0+3sfHkt1sQnSpIuNvNPjUsg4wkvQAUvQ3/8aBmCdMasCTe33KkKSyUbWGb1qBqteEpPRq8shwp46EECJ+as9JqV/bOrPVu2VyS6K4asITToz28aoNFmOJqNX/TvGnosdjjaZ9kxGpcmW9rHNbfbq2M02/WO9DXrfg+B060pKpwcJpXlCU52czptKaK4vGfCbDGGCLnYugBgsHxCSZntSnlNNphBLJX1myFUS9y/IjwAAIABJREFUQDihqV7Z3nbEEtoHohjah99Vut0m817f89T7Cm0/u54Rqt6gOy0eZkjsgva3Yla74hnxbYsl/J6pO+1j4Oo2msYSJjxLg5wGkO3M85Iuts9em7GkOCQKYPWqga2MI23ba2tcYgAOAODH//x4AzDqgDFA6DNPP3tYDb52drMq4wmzJzNlk+xhloiUZ+2SPWzOziVbNd6eOdMuBogqo7dJ+1z2bG0HGKrBycUcD7WH9tvIc4VgfTnrwP1rg5xuXiFaN7SWkzynCyZyOjBR9Tt0sbHn2hf9WBCzYE8ykkkyh/XjqvKcpju5YK+7ntfUP66PTXffb2RyYtA1MlgTzFSc4bdWxYEPCZX0lLFGk2Wi7dMoeTNWQ3Tw0jPiJrHk1livapHrvrDpWC9v5KI0zKyVT7KMDvRJsKFt7XPFZkwsudjN+LuasLTZ93ieNu3FjEusBR0AwE/85fEG4L2qBS2zlf2n3xvDcG1bivLcRk5fWrGzmy+ayOgQTruwXK62b6REpwf2l3I3sKV9sbS0ntJq7tCWdgh76Jl0dVvGx+YOF37wkQVZirLw/qiIf/hFzoADAPhJv8IAvBelKBmAiyBnAG420PoGYddkjgG48G0MUc9PrgovLXMP7bKm3rZfrZbAR1VGyQAcAMA//BsMwAzAMmBYC1r6gTPgYgBhAGYADlnt4QzYN0UiqpQhPfV3xhuAXVrQAKP2WYlh7GYf8zCGLe2z52c5utncMdrNkmzmZnzaZvFbYZCG2ju3kdGXlo392uF7hSXog5NVnW1f+8CkPr0xlFkz3s+ZTib2UU32cD3zfjSxBF+sDAlc5tByoJvRBA4gNq5Rx5KLeX96LaMN87xstLVGC9r33rtiCc9sF+xwjyMu3en6996t3exiS7vbF151URebXRw6HXCNtRTl039/vAFYaUErQPCzEqGZLAkzis1caA9LPWUs8yg2Mz5rznI09HaFRKPPnthrGWr1Ss1eH1vaxfg0ST26/mwdI1WxpRWhqU4XWxGcwBjuJTnNdIn6wwFcTngk0cskBaHcZzkj2sgSweBV2sN6++SgVRB1bG1S7YM9aDev5W575zaIbl1DyZAEYhxoP9cjumimQ5RJyT5lDwSslUFOa3lnk2GMMUjv+0FGQg4xVUSsPKd+ktP8RIfyTDLjQ2IJvtf7qr7v7bGEycEyCGJJQvN92S9mLOHZVnTd6SyjyS7RXL8jVk1wwRejjiX1/Cabu2C2d2hpIyvpYqMfp4Vka1nDPDaWTLa0OY5IJr+s8y2qJMrjSFWzXYJ5HFtaTW7lxEgRJX3jUluxVJDKugzAjglIJQN+xvXjDcBKC1oNYHrJkPKhKkWyZW0+BqlehqL3h/qOz56b7evTU3YxlX0M0jB7etlOCMMVDGEM4mZGAgGH6aGYv2kvFTWzRCt5OctqomVs8x/siUMMDHs4wAKlNKaWMQbO21ZTWh4kdP50IgZtdWFAhb0NAKvTXtm3sLc8SMVEYqabiEMbbHFhY7a3HUuqHtkkWE0kGWGOYepYC93pDcn0NvWUC+B1x5ICaf15Y2NJ2XDpTpt9r0qRAAuYNOhEdP1Agqb2/OxreUiJ7Xn1kkZzxcM1juzFcYn3gN3pfwWAn/V/GIALoN0dJAYXcSNWW7pttnSMetGp1ZQGiZ1Ne6iXWY+GW0YJTGZnHM92Upru2+25lsVXB8N6WMv7ASGJ6Ykwe7tdCQuP6er7s2sprZGD3dyBSEeYL2LY6ypDs4u6xBGU3LEZ9267YsnlVzxT+2StuLa7x5E4e03HEQbgAAC+7o8YgBmAqwHjZ1TaX2DfIMwAXPh4lCUhDMDS77EMYQbgIm4ZgN3A2vSTSgb84+9gAGYAZgDmDLiIgXnOgDedwQDMANwUXJvcVwHg57ybAVgH4FDNVZ1wZXaAUqQKYbi69oLULN62b1zHEFbEsWr7QP4pq4DhHp2QYrbdJDcpm0JqcZBSL+kIeUX9gj0s/yq5RvMzKCrNGntzuGdtkNLKIKloGcP6fDcTqk5m+6BXvC7kIKvazesbGa1mROsGMxZtX08zOm8yEfrNZvsw87ctk64PyVymPXy/SyBtVbWHfX01qljC8968nFEnqbYPal8H+lDMqi79u/pexmZMLMn9UtcSdHhs1tmrqs2p98r23tdVGoh+DtBEr+v7tu3ZzhD2PW98+8p9z0vQbiiuAPDz3ssArA98LkYvXjT9Mx2k4G6dkaqDqGlP/7fOULTZU2Drs6cvr0nbkgijM3AVy1HZK+sflxmaiihSaC3X21sFS1lJLRIJJq0i6uj2wBZeTSEPKNu3qSkM9rPQRiaa6kn2p2KNSnAstIwnKRVkqJ6hLY0zLKBXjLMCID0ItitY1tPDQ+rVZAgfiwPah4fKrwxSWksTSjERoYwO9IgumO4IQpYeF3ofmH0Fe0sZVJETysFeF+qHHeg10kRCgumMPnD1YxuxZOt7JYmps2lPr2Z02/pwEpJnNJkQzU7I553tEoGEVcR6fd+3F0uSQNi+vXIs6WxkvZLBnPi6+l4HsOp7X7DZzclU01gyxxFfpYHts1HGkiueQwH4Ix/5ZH7JJZdaJWObZJV76Z4KAL/gz8YbgAeDNLfPfouyGFtGZJtdulid8kVt354ts23C0HQ9r17GU2S2UrPWNjvH38GMXQcLWKeWijQ6o0N9IpTjmOzmlQ0A4BCkys6lWcgbdqtZOV52NMPU7xWZ8kZGS3qZjJaWz3QzmrEQimDvpmXaLDPSmzGdZHTJjF1nW9Vu2nS7T63Lch4zK+/kGR2EfrShwVxMkqrs9bpYCu/7jL6yQnR2UK1v7uYZXT5LlZre2FjSS3Oaay0DKFFCY+979E+YDni4PQWutndb+gKTkyo5zfW8Tezp5WcqBuv6XvqivEIx6liyjRVqnOt2w8qQnv8778uf9cB70KFD+/9IwgoAv+gvxhuAWQu6gB7XfpePNHTHaiayR9t1uGcnawlxhwh2s4tIg6PmzrnsedjNN57JaGARasCS+OVz9lJGH5nntpWU8k51gMZwdHjCPk+PJQfFMOW/cNau64z2XTWbi8mSecWym2NiKY74F8fodf2Wq93wS/vs5jimtyvjG2Us+eIiNAN+6R9+IH/qNy+MJwC/5K8ZgFmKUr7SMYMmA3AxHDIAb20yxwBc+M8HcAzAe2nRudzWSgb8v/+eAZgBmAG4tATNGfCmOzgDLiKDM+BmEwTOgN0ThAoA/9Q/7m0AXlhY+I08z+924sSJBywsLPwwEf1PIloloi/0+/0fueGGG9Z98yW/FnR1r0Xu66RiD8bFbg7ZU1b2whmf9j3lYt+pqrUcw26us3dmPacN49xc4e/hHjDIUuYlloyFmqPxWS4VqcBErrKv3QxXnFm7hOP+LPtisziz1sKwxv71F89J+UjzmupkdOm0ew/Y1vewd3oDUpNVeyCEHbLsAeN3N9KUuhFMdHzXpj08QGw67H35nJ2Jjj3gq+bcjF4f897HJ3AxhN17rIVco94nLv5EEZvuPVEXu9nNvsY+tN2eJHDZ2OHu2PRzP6Cx7h5HbP7z+2J3jEuhe8BjvQT98n/duwC8sLDwICJ6OcYxInoyEX2w0+nc83Of+9xtCwsLbyCizy4uLr7eB8CQotSZyToDVy7LFoOCzvoziRflzwqt4Dp2s8lkVANGU3tKtxffcz2HvMeuY22CsosRrvulsAffdIW84upgeGg7WNiEMiAptTgYYJApM1wxsECDeAnayEPwBkhNdcGE7oq2Kr/obG48Y7l9BcMVWsu6PRwYD5Z10u0Kpi9AFbrTOlkFE4BbVjI6IxjcYC3LCcCF0wlBorra94WeMmJD1z9GezGJ0rWHdaY3hm3oWE8MZTfxHNCjhsymktZUBLOmfa+zm3V7ANTZHm2WaRWx2qGTKymdRmnX8Hmx343nhbbzTseS1CsumMT+vi/i2YxhnRGux4vNnurH+ve+kNlUWzUm8UkHx6b2bOx6G7vZZk+vktjqOGLG0lbsdRT9vuFK8VgD8M9+eG8C8FVXXXWw1+t9IEmS67Is+4UkSa4nogctLi4CiGlhYeE7ieili4uLAGnnpbSgY1mE8gWqauD6GaRy8LDNzs3yBdXweEZqWehfd4RZeqE+M8G2/B27PTzP2Y1MlCBN97olUrQ58BXPRLQyyGgAfeG+LIWpts/tW1tmJuQrB0S5hY2Mk4cmO9VMb22Qi4MXwNqemyhnOD6Gq6suFtrDyIbB2hblSNoFsAXY2Wqiwb6e6roybxcTPRP61ucwATKY6MJer8q+xuTnllV5GMbhqXL7YvpeZaIKzMrZazFJquofu2NTB1HdniuWfNlw0b6wWKpjN9ue1zeO+O2VD/gw3/vQqgvXuz2KcSl0CXqsWdCv+tjeBOCFhYXr8zx/Z6/X+/RgMLg+SZK/SpLkTsePH38hgvfaa6/9+jRN37W4uHhNEwBWL+luONA6huEac9h67P6eiyzjs+fbP3Pbi2O43raaUW5hZvcop0NIhy1X2/t7zqPwMF1DlmcpZ8EE5HBfnkZkXj7f3r6aUmbR2Qa0HurLFZwQe/5YksumYfZ8/RguaxoTt7EMYRcxkbWgiwgw+yMUgMe6DvjVn9h7ALywsPBoInrY4uLiM6655por0jR9EwOwu6ShqYarmX26JiMxbOlRDpouAO5TLs7ytV0xoOOaKMG+D4ApTZHmVpoxjgC822MpBoDbjqXYyYMrPn2lVm1M5EMBGOcBHz68/2uA8cKff/6B8gD0uk/vPQA+duzYW/M8vyLP8/UkSaaICFnuHUmSfPD48eNPxINeffXVD+l2uy84fvz4Q5tmwL77+LO944Hb17CnW736CQlBjFFcSxskZC9tF95A21snAbiqaVLXXgiAYBnfvJCnov7YklDXmeTP2QPRHggF4FtvPZmfd96R6N/bS1+s+ObnP7f3AFh3+LXXXns5lqAHg8HjJyYmPpzn+b0WFxdPLiwsvDnP8385ceLE7zQB4K3tAbv37ex7N759seKAc73dvr2bpY2cTq/nVi1jndRi+sG1h+ljS7v2qGHbZU8e+g6CVVV72L3nLc+f7SSSmKWDSN0+oDjzN4O4ZflKMrknOmPoRPvsKWINloXLqk5E5zYg55VUdKdhTx10PzCWwpfWJGP7yGRCfUN3um4P2BVL61lu3QOeSuTh8y42Mrxjfha7B9xm3/tiaWuxGb4H7NJTrnt3bPwEVyzheXXJVtt73/YecMy45NOW1mMpFIDHOgP+pRv3NgBjCTrLsj9YXFx84MLCwuOJ6PmQ+02S5NPHjx+/DrhQB8A6YaGObagIV7pcnBwwsHcn2b76y9ScBV0G5SZMWDB/T64ldGYjFwQcXcsYLC9ZNiGBw7SnJPB8LGgbQ1PZK7Oqi0lD+XkToc8MQBRUaE0bGX7UWcY66QZEqhUlLWmwqst95WbCboBlPMiLM2/BihZtyIe604k4NCKMAS8HcJRRLWvt03WszVhaS2Xpz3pKdOuq1LSGZnSPUJqU05GpLvUpEzrYOFxCxZIa0EJiSbGqBQu9iwMV7H0PsWqdwa32iHUWtItt3jSW8Iy6NjdlGYHfBl1se9/LyYCNtazHcJ3+sc7Ql6zqamyamuhS+7ooJbK9EzrRUi0JmxO3mFjysaD1vt/KuBQTS4Wfw8elUBY0AHgcZCjRD5U64Nd/YW8D8FaXHwaDQW7Td62r32u3bjf8JBkcbPCFc2SVUoQE5PlT4XXA8KWdYOOujdRBVO8L+E9qI1cJO/08ozmHNvLZdZxmVNUr9tUV+xifZ3BAg+3g+Rys51wc6mBbGbD5AgMuZDRXIXtZ0b7O6WAvF6VO5nVuPaNPnbL1VU6Xz2R0l5nwE6lcfRVTV+xb1ZCfhcUSvnNqA0z0qi8mKaPZfmjdbl3Ne6g936lJvhUouxa0Dt4hsaT2YkNq3uvqgHd6XELf91BPF3CNNQD/6k3jDcB7VQsa2e9/npWZr3kd6ad0PtYeLZeP0BFHiHEzXE+uDLNOox04ceeAUe6jbjm1ltLABphg9PYyJ2DaJg6w6bXXxWBRBYlYctXBbkr9XtXv5zaIPn6HfUS6ei6ji2bsWto+QsxuZsqjJO22NZwKZQPglOZRhxUYm20z5V32fASltpnyfmKim1Tpwra2yVqx7Qtdgh5rFvSv38wAvBelKBmAi2HIN2gyABd+aoPhqg/+rgGfAbjwkm8yFwtw+w2Ax7kOOPmtrzEAMwDLV5ozYOkHzoCbgTYDcP0kkAG4fi16nJWwur9z63gD8MZGmuP4yqpKj3/fM5SV6N9TLghcerj6GKnYA8Z5tuIsXv0a7m2ePxnKcA1nX6v22fYIMTif3gADrrqfO4F9QCg0GfuvGKyW1jOpz2wsrcN/8z0SxKmQvhJ7tnl1yRNSlQd6OAM3wl6GZzL9ntHBnv28YpC2Pn2KLLrTOV05k9OdZ8LOA0bf4zL3rxX7GjtwIexmX2yCzR1qD/KjQt7TovU9kUCm1N6+QZZTr1Pdb45XpAo7Xxg+dbPy/ecBo0fQ9pDYhN93w3nAeG7X+cL4LDSWWAvaPekwSVi93z053gAMKUq9VMcsL9BfSBcrWGaPZcaxja1pvuA687eOLa1eBB2UwTQ9uUZ0aj0TWsY4+B16ypCCBDNXaQ+jLabWq81eleFayGzqjM/CXlnjGWxVLD8q9jXYtijVWU0FPRyNEO2b7QMQJQta17NVbQJ7GWVLAG9Ep9SNTsRh93fqp3SoD51pO2PWZg8MZABxOrQnGjksK5qklKZ7iQAzk8zl6vv1Acp+cPCC3H/vJjnNDUusysxVTX87J/qv0xmdXCdxYANKhC4W4Fv4QrGRXX5Js4zWB0TLuSyxmkmkrCUGSIDyypD1Da/NdXIxuVCxafOLbYKnslrYQz+sUpeSPDyW0Pe6LrbZ92mq3hfZv5APRckWpDoVI1yPJRmbhVyjj91cV9VQsKrL9nz64zoQwb7qK8SCYLYnCcXEkl8zumhf/bgkGfrNx5EiNtW4VIwJ+CzUXsGWDmVBj3MGPPF7tzMAq/mKerFcpxyF1FOqoLbpPSO4JUjZJP3smWgB3tUMAVrGX1vJacqip4wSlzlLxiHtudnXaumsytAsv7j6XM9Vcwxt5OUU2sMAujJpTA5AVXYpBt871lO6Yy2hDeOEoU6e02UzYacmCa1qvSRKazhaNN/NNst2bKsQ1Wxd6ljjmunb+9HW96jZvmUlp8vnOyKzLPvP3fdrA5wglcgVBb3teU5TnZxWh6Csf+ZaafDFEvodwGvTqo6JJV/f431DuRnabl6znZQmxcEV5c/Uu2PWZauJhi2WVKyr8iv9t+rtAYiq7dsYyLavG7HpiyUFjm2OI3h/2rTXxrgUSsIaZwCeeuMpBmAdgPeqFrRLDxgDAsptusF6wO3q98ZoQd++mtEt63aG8MWTKR1wsGlde9kAFmQrtms2SWl6ws7Oddnz7+/F6Vi7bJ5ZS2ndwQ53aktHakH7Yymjbkta0PFkLTdDuG229H6MpVi2dFNJWwZg6xAj/mguQc+86QwDMANwNWD8L2m4gD4DcOHjmPIiBuBm/mMALvzkLlWLmxxuFwBf9ytvz3/8ofehI0f2vxylCcBzf7jEAMwAzADMGXARA5wBF77gDFj3RbOTtUIz4Ot+6a35jz/sm+nIkfPcqeM++cQE4Pn/c44BuNg/sp+5qsgfLrYvvm9j9GLGaDsrWJFEfPbM/UO1f2SzB5btOccZuEpfOMRe0b4yOxJLhiDWpDi/VxCXiuVc7PUtDSRjFmf76iRmRSAx/QR7IGkN8sRqD/rWkHw8B+Up7cIh8hdN5QSOkel31Ve25wXxR+hEG3uOkG6c6+biPOKm9tC12FMWe34T5vPKPX5bXMTGEvy7mmrSmkN/9EHE6hCtpMkmKUy5SpG0QvseBzssDxJKbecLd6vnWPti0xtLYLxnlrOb85zme/b+dcWSvs9rPq8/Nuv7artjSbbdvv+vSFr2cUSStHbbuBQKwOO8B3zwLSsMwDrbVWf74sVQjN5CY1Zp1pYPE9cZzS57ij1c6CkXzEFdS7p4ISUT0WUPQIiBF2L8QDwx6A8ZvhOdnCCwpKQR5Qsu7emMyuJ5YQLayAWbG/8tSR6JIOZs6h/LGYtg4M72OnRukNEaxoLh3mACJmtXlgzpjF6doQmNZDBfN8uUcFB9R9pbHqS0qpX6SIYvpBwTunAyp7m+JKLp9iSZpgAHG6NZgSsINMsZ0UaWCKa4JPuY9ux9D1KQaJ9gvsqJAQ55mO5J9rksLZETl+2IpXVBaAMZi8SkYWJYQgc/K91p9P20o+99sYn+V8uWur0+DsTobj2W1LtkxhJKwoQfOx0yD6TQS5BcsWTre/QBZBlLLHz8RoPYNNnXNgZyG7Ekta/L44j+nu7VcalrI5x4MthxBuDDf7Q23gC8sTHIexb5QFkbWWUcK3AMZTerbNh1mDn+HsK+xqz+1AaA1663OzdRrUn0sa997UMJD4Deeq6dOuTAfMHyXBwubyO1iYzdZ0+OniWLaPvBPgDHpd3s7itbG3yMVF/fI+tdE5MDg8w1bF8/on1txtIgTQVJKiSWfH2PyQ/GU5s9F2PWZw8HbWACYYuluU4mmPzVUPJXDdgyQNgQZzJbdcXrdMBHE0uqDjjMt6Mcl2S5VWgsMQC7ZxvmEvSRt2MQr7+CxLXrze2eO/aqFjSS3tsxebJoQU8lKc05GL0+cpVrv2sJtbyZnSGM7AWZi+3CoRA28BOAbiwrq++7GL34PEYLum39XjGoG6Unqu0uLWhftMcyUt0EGx9D2P1ZU4KN/ixtx9JcF8dFunSxXcQ/N6GobV3xtmOJpShlNI1zBnzeH9tO8q6OGAzAmk92w6DJAFx0yCgF9BmAC78zANfHoL9ULW6y5JrQ7YZxSWwlmClzTb41zgB8wTsFUaj2YgBmALYGCWfAhVs4A64HJN9qCmfA+uRmfE5DGufDGO78riFbswaC9y0AYw8Y+69KWg5+KFidVcanJCZJDdcqY3ZIJjHOT/XZw2eSbOGyB7nG6nmxLr1d2OtRTvP9qlawIorZ9Gd1sos+gYU9KG0JlrW51JxhfzCnFHuixmcguxzsU2X/EPakfJ/lvNg8o04C/1btAeihBT1paDfrvq1q1maCBGbb4/c9L6QREfDm2b6wBfUrsR9uKjRlGc11ZfvMWFL2wBrXfRsbS9j/x7S5b9iLjSWQ0qS9Mptb2gMpz6VVraREy8vGsbE015OkMpMnoUhQbja3hb2eZQTVsfUsqWyRgDR3YKKq3eyPJbtiG8YL3/PK/fDtH0diY8nVvthYgi9CzwMe5+MIL333mAMwtKD1F9wsHdLLWnSmsp/hWmY36yUEbdgrWLZEqylKRjLByNXZpAAQlKFM9Ig6BrtZZw/b2deK6V2URpSkHDFZ0PSPpVZzTikIL3lOOOpXlebobOQy+1qThvTYU+U8ap8Zcog46hha0DrzHIOc2Y86OUfJjCrGrAJrffBMBcAWpT7YS5/qJmISoTNwVVkLyqfE8KppS+taxrCH0iF1GETVXhO2dBFLpj2lPVy0rwBKNamrY94jflaGZVlTHaKpjjxz2cYil9y4MlPeZKJLsJGArLN4dXu+WDJjE3bMvsK/TWayOlAC7QNTXMl26pUB6K1+QuIsajxLNTZllUAbsaQIj8pe9b0vM+/VxEwxxfWqC0w8Rj0umX639b2uY62PI6FL0IuLX8wPHTpcuwy7H24wSVhXvocBeHMNXg3Soaw/NcM1A8RlTw1ONoJSHFvafQA6ZPsP9lx6sakYLG1bNq79JIAtTq2ZtrBVVzZS6nU6IjOz+cKqqTu0B/KNySc7s4aTkaosTNg+0E1pwsJe97GbFSjpGapqJ9q+nKEi2LiGp0uZJw/hrqU1nLRkZ/ROJJnIvqxs6V5eya7loC/rxm1MeRdzHJ4+AB1rC3nJZ291PRX11ThEwLxcS+k+Fj0Aps1YirGH9p1F1mvRlu4QVlASR2zal3tjmfKudyc2NuPHJbfevI3d3Na4xADsniqYAPx172UALgEwa0HL4PETOkYjRSlKVhxsaYj1T4tTlaqXi5TlYvrCgo8xe9ABcMi0zgzsuzO+vXHX5AHtcJF2fFKU8zi4wOkLu3rR2bWU1hza0n57KE2xHT4Rrs/si7NYhvDJlayyPYDfwYQIma/t8v1WTCy1z5aOk450M+Xj7DVlyjMANwfgY+9jAGYAtsQLA3DhFAbgwhcuQPIDZrsHe/h+iwG46CsGYDcQ7tQnZgZ8t//LAMwAzADMGbAWA5wB1084fKspnAFb9jU8iAcS1sGDB2l+/sDmHvxOAeR2/64JwN/4ZwzAAoAVIQP/bWPTKjfpn/nYzcqeIkzpHasIGeZv+eytgn07wOHvVe1h2MvyhLD6Vtr/UgepCxZreS8VzGac0YtFXFPLuGhfQUpR7S+eq8z2VYQMm/989sDmVgQPkz0M0tFGRiXVLPQDfIG/z/dzOm+qW9pmdfnd51ssdcO3WZ5TMiThqOeFNCIkN6ETrS+9CpZohv1wkkccamOOIoqhjYrgBHvY4r1pKaNzG0RfN090yVyxJKqIXbhv1tirRNYJwTHoJuv2xJK12HtNBDFNP5fYz+TPRFvWQeAz9kunk5QmRayU3wPVPrws0AHX9/ldsYS+gmznWprQZDenmZ6rr5rFUhN7Qsfa0MUGDwKSo9AON9+D4r33xXq57xXpEJsPpia6z54ijpljQvw4IkmSIeOIqw1yDJTa0jH29O+ELkH/5Jv/RozBT7nP1bTfyVgmAN/z/WMOwFmW5Wo2q8hIOhjrgWUyPuE6naFpYwqa4O6yp+QPTcYnCmLAMAbjVg3yKPHBgAvtZNyvlppEic+QAYo9LzB4FXlIvXhWexkUiHCwOwCh0ILWmd446Fw/0NzHOC7KnWTb1KBn2tMcKBmUAAAgAElEQVTLoVyMSvgLcojQDz6bQnda80We02Qnp/MmSWgV6wObbk8xSnV2Lp4zo07B3ta1tLFnCEDT9JR1e4qZrdsDmxj61UJbWiuVWh8e3H7zMtGXVzCZkKALUDh/IqevP4R+hY5zoaVNm7rYUptZBw2lYw3wFFcynFjlOAgjF4AAwpHeVzrTW2dz4+vqYHkA8txER9hQmtDqXrDsoX29WXqVZzSREE13EzoHEp0em8NY6lJHTPAKrW9M9nIxuegmdbFUAJ6KpTSXfZ8CINDR8MvQXi+RZXyqP9BupYs900F/oByuYGYropv+3hexuUlqL9lT7xjAfRW66koCNs9oCrrrPVesS3u+cUTEg8EcN9nmTccRG8u/blwaurPynkr2dfNYUmNCaBnSK/7kQ8JDj/+Gi8YOgO/952MOwC4t6M3yF8tqik95yfWZejFsDFzffusdaxmlFunDBFrLEw6WY4Z6Wjt72GUPowTs2Q9bt2vCqkHBpbUswcOu3YwBxsa+9vnvP8/mNLD4Yrab0SUzdns+RiqkPNWBCpupBFZA8owOTYbZ8/nizHpOf/c1DPtVwtbRuYwuBNJbroO9TNTmmhdY6KfWJfia13QnoxmjVlrd4/OFq69w+pUAX9uqokcHfHgyRqV9k0kmDtMIYd6jba6+mqSMbLrnauJmY6/72NwufWbYc6qgeXXAMaGR5Vvm5Xvvfe+BnHdV7W3HuBTKlh7GUZBuxDgD8Df/xZgD8G7XgvadzYrDDuyA7mak3rGaUWo5wAEvtUu7uX2CTRwL88YzmRWAoaB0yawdxHz7cbetZFVxEQAw5XR40j6G+Mlpdr+fXicBwLbLB8AHOilNWNjNOAXrDocOOJaQZ5064OFa0Evr6WYds9l+H9Pb9Rlql+expm+5fL5tm1zl+i0fiHm1pbsQoLAfJOFSZoxletsjqa5ywd33brJWnFRm6BL0OAPw/f6SATjv93uVmHYFpS/TkZ+1G+gMwEXXMABLXzAAFzERW17EAFz4kAHYNaVp/+/mHvADPsAAzAA8jDPOgKUjOAMuBh7OgAtfcAZc+MKXaHAG7AZuE4C/c9wBeDAAb7Ksw1zHIJX7w1XtZpfWch3LcT2T7GbIK+oX7C0PIGdoaA+DcAO95x5Vlr0UY1YSkkzt4aE97bB7/J54nlzak1q8xfIrmL7LGzmhaVPG3qIk91R9AXtgiiJTU4fdq+fS2dI2RqoiHZmMY3zvq6tES9Ck1pfQRbtzunAShLTy86J9IKVN9rqmdLNgvUPfel00X/N7DrlCkJnsjFnY63WSivIUyEwDIcNZjSWwhD96O9HJdYghFr4FW/qy2Zwumq7qFWMJd7qT0zRIS9o+MPwDe9IPxl4qyHnop26VyQ+2+YajfXgmXDhrWd9aTBF/GyCXaWSvYUcizvA9PG9H36cekqOE1KOhEpZDRz3P6UA/LJbQ93jeytm+NX3liyWEvKlxLfWU5Z6tLTbXQO7KuqT4byqmQYoU76KhmV333gtWgEYeU/bUe2V+ttVxKXycG05IDR6CGudc9kJJWM9/w5+JAPzR+92Njhw50n7auYssmgD80L8Z8wwYWtA6u1mJk9u0gk22tGL9qf5V32lqDwMYSljUoIySFwyeipWo7OnawyBfgbGsl3QoqTqT4arKCnz2FPiq8hsQkGZ7Uugfusi3rCZSbpGI7tRP6XBfaiO72M0YYMFYXh2qLGGiMNOVIvu29sn9sSrbV+kIy/AsSkQwGbhlNReM44lEMqAPgA4+XP5X9pRvFaLMQhdb23pUvtV1rNETYFMrmU3VBrRPscuVdCN0ttVWpq6nDBtznZwmekq/twDDm85mdOKsLFs63Mvp8vmEZiFOjCcUbNPiUtrX6G8wq2EPByPopWab2t+Glrb0RWEPDOvNcqM8pzmtP1bSQvsaTZkRWtBlPWXRPpSoDNEZ5VBgc4u5C+ypQxQopymt3AjlYssDEsxlxDD0mQfDCUiTWJIT3aLvRbnTkAmNX5/pAcirfW8yx12x5GPe492xxeamjrVsmoiBub6cuNS99z42snpHdSZ/nT30i9KJ1icMeqmRXqmh27OxpV329NI+mz3pJ6lZDu3r0Az4eb/zXvGWP+M77k5Hjpy3i+Cy/aaYAPw9f8sA3FCIw04c8rGlfaQSF6OyA+3hCflimdfqRkaTFs1k3IcMx0UCcTFcfWfbrg0yUfZjXmjfVXP5ZnmT/rmQjnQwZue7su22y62uZGdfq0HQrF9Wtk+tZjSwEM0moAc8UWXgwh6e1+Vblz1xFAP+n4WROtfJaMqil41k8wtnMjqIkw+MyxdLmBi5yHOYDGDSYDYDqxenN2S5lXn57OFACZv/AFiwZ2Pl36mX0XnTHVEvrV/w7ZfPZUJ3OiSW3PrH/r5yS0fKUiUbIcr17qiJjI3lj/IyVBpgsmJeMSpyKvMOZUv7mO1oV5v25KpB/fOGAvA4k7Ae9fcMwA0BuGVy1UpKWafKBsUwdSiC3ezXs7WzpX37ez5wvnpWnphjXuc2UlrJ7AzXuU5KUw69YtcgEsM4RptuW5WnQ5kXjmlEeZHt8rKlHfZ8RD2A4oxDe/h2R9+jXS6byEBNkRD1HC7lKh9Zy2fP9RlqhVHGZvPtkX5K56M43XJ98WxWERBRt7liKZYh3HYssRZ00aHbpQU9zgD8mD0KwMmxY8d+Ls/z+0FLIEmSW4joFXmefzjP8w9qY8DLT5w48Y/WUWH4R7H+PLxiB/wYFqFrEGYALnortj8YgKUPGYC3HksMwAzAPvwI/cxcgn7cP+7BDPjYsWPfmmXZj504ceJJcMDCwsIfEtEnieh/Li4uXhnilP0CwL4MDnuHICiZV2wG/HUz9uPvfPbazoB9z3sSrKEdzoCnKaPZ4d606fe2M+A5nFtsqf2FTOYpsMxsog2DlDqW4xxFFu7ItvdCBuxaTo6dzDEAMwCH4EndvSYAP+Gf9iAA6w95r3vdq3/mzJn/S0R/kyTJdbEArEgXOslALQmq/RlFMlC/rzN69cPfRfah6ara2b5glxaHteM7umatqRerk2p0e2o/FLrD0Nud7Rd6u4pghHuwOqif4Qt7SP0xSIMco+9jgtyDz0Au0o8DxP4vGMdYWQUBRreHfdLb1qWSLJi7ulawT09Zkd7w/Ppem+95oc4EKUZsser7wJtktWwoJ6gtk/dzKEQpTWeTLS0JN66+x991spJo61BfGH4ytYcFgCXJZvvUtpkiweA7ILjpxwEqshr8h/4QkotqlUYjQG1KT6rPoHpGjr7Hfq3cpiZF6sKzgByFOQoWjKGaVdrHHPY9zKvvqPcADoI9sMc3tH1lqFvNdqV8p66NrGITv2XGErYDLprKRVw27XvcJ6UR5aUz5VXfg3s23SvrYrtiSb6n9XrKZvt08mX13fbHkiJrgazUdBxRsVl+7wvGdpvjkmxTWRdbZ183GZd4D9gNwyYAP/lf9jAAHzt27OfzPEcW/CfdbvcX0zT9GBH9JRFdliTJp3q93gtvuOGGJd+sJE1TsQitB3dRXiOGoU1gUIGotHJ10FVgrD5z2dNLC1S5DpiiYFNiAFNSkHX20OZ1lKToZRHDEhDwe1BcVSqxySFGD0ZtQp2krC+M5xUD5LC+Qh94ocOMgwrAnxKHEihpyaH2cJ8Sun09p2Xt8HmUZSD5A5kMA7N+WHwTRqXJYlUDHsq10EZ9DzKB9nBXHnQAdq6qN1LsbhBlIH2I0iJFIDFZolUGqdqVKPc9mNArOFgA+sJauRbIToIljdIgETIawIv2QWdbEmJ0pjwmSMsDeVCBbk/XMhbPodkTzGf1zuLvWn9gAgdAg582tPIq5QtoNpe0tOGuYV+B/Y1yos39GA8zezNuU6l9DQDfJPtkw8MrMIFDU7WVCKnpTXRggkQpkuIRmO+VjdGr3mFzkiYmRziooqSlLXWxEev43xB7+lhhVjWo913fC42NJVURoLavitiUbGJTn7mYLNhjs0gSZJxV7dkrDYYRWyqHKvrDr4ttY5ujnbFlSE+452V0ySWX7usTkUwAfuq/7mEARmcjAz579iyWoD9HRDcvLS390c0337y6sLDwxiRJbj1+/PiLfAAcowXtW84alYYrAAf6uEEavTj5yMFGRhjcBgSzLN36JAfPrGW0bmHZwucugo1P7s/nW9ferjgqyKI5jTa42Mgqm7JrVcfp97rah+wWk5FQRurtqxllNtlQDYArse3xhYtYh1z7Tv2cEgvD1edbX1y4vodsGasWtivmvRLMewvDOr7vwbxvr32x7Oa2x5EYtnSMtrScf9qEw92jMMqQpqdnUchET/uWY/v6QIbzzz9Q2gv8kQ/uQQC++uqr79rpdPqLi4v/gW49evTo9yZJ8rTFxcWHq24+evTo9yRJ8tzFxcUH+wAYpyEFxovP3Mg+EwAMQf7A62BfLt2aF8IA9vQMqInps+tEmAfYrqNzyOibWGl2z+1rJM75CbkgkOCQHg4x0+heHJCAlQfzwvb74YlGJko3uez5LMmKTPt1ZkNmx+aF7xyZDG+f77dc1iAUMtsP/y3XN1ZSuSRuuw4IYZn2fostNfNAKAD/4p9/Ip8/dIjOnTlNT/kfl9Lhw4eb/dAevMv0zTP/bQ8C8MLCwmOI6HmLi4sPwDbOwsLCLxPRtxHRjYuLi0/EGHT06NHXE9H6iRMnXuzrp91+GIOrHMObAWPP0DjXVvngQDerKG7hM18GTB57vnKlr5u1n+YTS4hxkat8WdpsJ6VpR/mTL8twC+i7D5Jw6Xb7ANjnC5c90ZfDpelKbHv7KqWNoUCK/j2RAU9IVaYQez6/uz6bopTmIg5jcPnpHM5ydmbA4aVv/tUZ32EW9szZV6oWW2rlGs9i36uYKo62pShn5w/S8tnT9Pi77+8jCc0M+Nkf3oMAjABcWFh4NRE9EACcJMlXe73eMwaDwavzPL83eDF5nt80MTHxrLo94PYB2D1AuwLd99Jj38xWc+sDYN/SYNtL0DH1wjFCBehz14k4vuf1LUFDatF2/KJ/0HT3r3MJ2pMBe5fcHac1Sfy1A6bPF6fW7KdJ+ZagY048Eu3LshKJS4HGFI4jbHEJ2g/AdjEUtMUn2NHmEnRsLPniIg6A2x2XfO0LzYBRBzyjAHifnwls7gE/5yN7FIDbWn2waUH72c2F/rGNlWjTdy3bM9mbmTg8HPrCkGtUWQheXEg6gjRzoJ+UslbYw2eCNGXsV22SdKTuXSmrATlqDqQonUwlBiOpL3wOBCeT/apLJBr2MDk4uyEJULnejqFGL/SZwUjViTPqO70ES5GG7jSY2cNtbVP/GG0EE9nUxS5JOJrPm0nmM9ja+kCI/wYLeTXNaR4ELW2dXGe4msx2QSIa6h+D5a33lat9+PupNRxET3ThdJlxrOz1LX0PgtZZoWJV1omGnvJ6ht0yEkQ3nTCHrHOiA6bykEU9zGgVCQtth/9KilpDqcv5PiQjLSQs1SGGb2WcCY6ilS2t3k+9ffAt2PrYBplB32sZt2Dle/pe2TNJWCAxL2dY+i+fWYz24YwzLHfrGusFo7eqYe7re0UexO+bsSSZ/GH26mLJbk8StHBVqy7aHZcKIqp8R81Yt/WH0tLu6yUQDQbqcQbg5/37iAB4YWHh5ZtRau+UfHFx8RUN+qvVW3Qt6EKP1cYilKt+ZXZzUXJgUvcRwD57GLhQSoOSE0WkwlmpU1ivTGT95m0bcgMLGcoFkxlhTwtlIGBNl6QCtdKRCmN2+H0wcfUSJTWgYOwA8KqD7tVgvelkk4E7XP0Ew1Unv4CNjDEQzQcTV2n0Ki1jpS39tdWENoYlNjjH97yJYk+6PLhidlEsidp0sa0M4eG3kGTpJUqqLAz+u22N6PRQZhMEqQsn4RsZnWXGbDHgoa+gp6z2V7GUisMpwFvSy0CE5vEAICn3Jv9rKaEzA/kcR/o5ff0heRiB+Nzoe5Rv4dK1tFU2if8F2EBHWukpo+3QdcaePljqqgRIMIMHKa0MErlnjmx5uCWBz0QZV0Y0kRAdmQIrWW7UoyTt7EYmfsdkc5cmOpo9vX0m6OqxBOBdQnuGoIuVGOh445HN0pY6jXVbpcGKkEGV76g5iVQa6yZomGzfJnrKoh+0EkP9vffbC4+lKht5+8clO/tafxfLJUrlcU4mF5wBuyHKzIBf+NHRAfD1Hn6I4HMsLi4+tVV0bWCsuRBH+BKOd39vJaPMwrYEQJxeyzcHKv0RAFgK2MxH8y0VuvZ9l9YzWs3tLCmXPYQL5Aht7NxJksuLtq1E32/F7BXfjjY42NfznYwmLUyzM+s5fWVVKDhXrosxwXEJZzjYyL5jC//jtow+v2z37b3vZNfFFi+BY2/33LpbzvGSyYzmLG33CXGgLhrPa+sr5167Z2m5baa8791x655LGVIbIx6xOe/oX58WdIwQh39f3/7uxB+B2e645Gei2yVtze+EAjBOQ5qcmaO15aV9fyKSCcAv/fiIALgBFu7ILc0BeDRa0D75wJlOSjMOQpFLvQiDOrSlcYKRecWc9SrY0g494OkkpVkH7fTMWkrrFgIQ2hQDwN6zWXv2fXMA8M2rdi3oO0+kdBAFxZbLV1502KEt/fGTGX1xxQ7A9zrsJoa59gx9fXX5tN2eL5Z8feUjfzknZh6t6jiegPt98xGAXDyBiSTbzPTNLvbrqNvJVS5dZLGSMEhRCxsUS1hbuZMjltonV7lBO0ZT3vxOKACjDGlqepZWV87t+xORTAB+2SdGBMBHjx799jqErdNtrvt+zOcMwPaBwpcBMwDLSPNlLQzAxdvIAFz4wjWZG2cAHuc94J/95IgAeGFhAdtRN+V5/nkXUJ44cQJlRSO9mgNwu0s9rpk6shaQdmxH3M125LFz1sshwODLgM+uZ7TmWIJ2lZH4MmDfCUA+wQ5XBoylQez92pZJnSIVyPgdGTCW9r+yZs+AL5rM6JBlidJXnuUD4I/dmtFNq44M+FBG0w4msCsD9i1BXzZlP3nJtwQ9Ba1qx3bBHav2ow/F/iqkLy3F3aNcgsZRgDqxSn8f4jJg97vtPipTKWxV38YYMZl4AG53XNqJJehxBuBXjgqAjx49+tQkSZ5ARBcnSfKeNE3fduONN35mpGhr+TEFwDqZwK256tYrFhmRwabF30ziFkg6Z3GouCKRavvAfco2tXF1ohDsnNfP6OCEZByDvAN2LC78XwAzVqbXB2WiEM51BfsWzdKJQvieIJIkiSDelLSM1QHwsGeQxMDAFQdvD7WMV/Iie8YB64f6cn8V8oqpQs2hPcwbQB776lrR9qkkpwumIMMoHaX0ceGz5UFKqwOwL6Xu9ObB6znRV5czWoIWtKFlrLS08VuwUUgJSnsgJUEow9QyRqkS2oDv6VrGSkvb1ldY0oSohFrZV7+FCdTnz2R06xrRRkp0ShChZF9BDvMu07lghgPrZ7UzfEskJ4OJrrS0IRd6y1pC62C7CRnJnOaG2twm6UyRkmSXFSQsEZMoEUK8goneA8O+mJQIch4IgkYs4bxkiF7AHgh9071Cc3wKh0F0E0kQ1HWstb6Hz0HAUySs6U5OF0zmUihD63sVm0r/WGf7rg9y+vxSTnesSyb1VfMJTQ7brioNpIZ5WWMd5EYQ3PCUNi1jG/GokIKtxpIiuMEgJDxNjXWbvYJ9LXWxV7SJryuWpC8KMud2jksm4culy96EbBq6BD3OAPzaT48oA1bYd+WVV17Y7/cfR0SPh1JgkiRv63Q6b//sZz/7xZ0AY5Qh6frMKuj1tpjAKksBXPR8ezkCElShWYt1AE1eUGQUEPYfDoSqNEOVymDf8tBEUjrcHfWrAEcMhnj59e1dqbdblDUpTVh9ABCDt1ZaoLSHYQ9ApNcdw94yDg4Yaj3r5Qg4ZQmD7p0mAZBFqYKyB41k/F23t5FmdHp9CHb9ZHNvWrVPTghQEqOVlQx1rAGIpwGiGvkKWsbQWT5vSrZdr+vF4DUYHnixgYfTynJgC39D+0q1wHkm2MHoRV1PWQEX+gra0mbJGJ751tWc/ns5KQ2uKP2CTvFcnwilPnpZThcTrqGudIm9LlJNHHqR00w3qWhpnxkQnduQKk96zSqY6NCpBsscpUj680p68FBXulQyllE/wcSjPIHE84qSsfWc7tgYgr42qYKu+KG+BEJdC9oXS8hcT2/kNNlJRAma4iXUxSY+/+/lnL66inYUqwoAroumiO4yUy7Lwf2Y6GLCIDXWy7Ep319ZR637T1UGiIltUvatK5bE5CGRbHQ8j2mvqIQo29sQExqpAW6LJXs5oyzVUlcb45Li/OkTVtiXTPTwcQ5fCdWCHmcA/oUbRgzAOrBdc801V6Rp+rgkSX48SZIvHz9+/FtGDcKjEuLwE2LkcqDtcglxyJekGStRtxujt+tjMMdoLfva4BKLwDO4lp3BDr9k1u4/3/6je5/boQqFjLuT0YxjG+Cjt9qZykIJyyH16POfi73ui6UY7WZkhof79lj62nJGdwzsvr10yh23zqVbh/iJmvjqoKLH7YduyUonMKnP7jyV0dcdaFO72a0F7Ysl17YHC3HUj+jjDMCv/+wOAfDVV199306nA9nIRxPRp5Mkeevx48ffUt9d7d7RPgDb2ZuxjNQ2WIlbBuCNlFYzO1nLqzSV2ven/ACc0sDBlo4BYB9bum0A/tjJlJYtfooG4E5KExbWuy+WXGx4kcE7mMo+AL5lOaXbB/a+jwLg1Mdudu9nxgFw+G/5VOm8zPtuRj0UYxuXH4DjmN6uEbB9tnRc+0KXoMe5DOlXRwnAx44dO5Zl2ROHe8G3ENEfZVn2jhtvvPHWdmG1uTUG4MJXrsFniQF400m+DJgBuD6W/PrHDMDKgz4/7TcAHucypN88PqIMeGFh4d/BJcrz/M+73e47kiQRbOi1teIsnf/6r/+6qTl0tnPn+vog71uyjLaXjrz1vYmdxVq3LMdL0DIGfEvQviVtJ3P3/7H35kGWHPed37feffR9zUzPAczVA2AAEOAFipd46VpK3JXkjaUsWSFrQ+td2xHrI3a9DoePfxyyNhRWOMJWeG1tyLJsrWWtJOsmJZKSKJESSIDENQCm58DcV9/d736vKh3fzMqurKysN9ONxgADVEYwOOh6lZWVmZW/PD6/7y9FDIPP2t0WtECav/Beb0EPW8Glve8wUn6vt6CH6p4P3KtI1vvuVsA7p5uHlS/bgo7G3EwLenf2x/YD/leL988AXwqLnBrxbnFx8ejuXmv3dw1Ia1gEsyYP5badQdNqg6ifdu8aqQqe2IaZDAiGkA6lG6WurxFIexiYEsEicVk4lsuEJ+z8GDSeQBD1JkwtY0Jd3QGhriQ0xfwIW7UCD30L7KF+NIGgQ1XKPkagC8vXGCgadbIU17EmiLPWU/AJwR87KPswCItA1UafUpbGVl+g9Jn3VzwJYpn5EUYjTU6t55wXnetuSyQ6tIzBAPWe0mB2BbXnk0mWk77VQBonQqzbG22KlCCmLqYhLJLcDERvQjolBDJOMCG6mJbxNtijrpn9jEzARp8kt0CF0I9B3rNu+XwCX4T6dHzfYfKibF8CfeU8hSDysfCRBIUafTeERXhsluAbSXAD6NN9yRckpeMA3rC+qfSUVXJJQt5qs369mNscvQYmSwKHaqShIwCP70vIjhAW+/rOICzVKUwIS+fHPi08pQW97RsXAoJ1AnGUYjXaQ+sp636i2/5u0Bn7EqVCZdmNbe3djkv8Tvndsw/GgTkVm1LDVmnk872OS1pCNIOw0u2RbYD/9fn7ZIB3byLf2ju1GxI7jza4abi/Ghyiwd+kJpNGPNKJjg+gAo2BkO4/JDRHDFcU3YE1OWlrI2vXDDM/PSlw3bPtmiHdQ4CeYbi0awanH7ZbE1d5yj0kPqDQDYRl54C9IunY6GxwvuJjvupJMpuuMp3QVYarq31l5Q5FV5Q73dx2TN+Sp3SYlQBV3A2pTUp0oAa1WsFwNxEAV2U0/CwHdZZF6OZTyQmcGBFyoFnvC6wa5WMgeLqMaGLcpJG1W46pp8wSxdyQLFce7TLG9+N7aW1ufk70RV3vKzekNaN8pGUPVVVgBtLDc9XIx5luQzQYHP6Tri2+fEfWx+1upAVNnW26IfGMmUExWLfajNXzAeYqgGb7Yu/r+9LPnB5HW4ZLG3u2biutfa2/PgYMYQALeV5cIlQWlV1rI0sXL8tFLq0vxd18bH3hSHvYHPxZ3gubnMApYzJXy8l3l98lPQlIInvUwRboGhwBJzqsUxWfJBkAZJjbkMutSYJufKblIqcnwHcbR5IugSo/6WJo6bxrFzS+5k7HJX7b7FPmhFW7jO0kv52OSzs9A34vQ1i/duFtNMCPPvro477v/4DneWfOnj37pbfW1Lpzf7uEOIbpz6Ztfw+PVerebtt12MIUPWWOPd9adoe1q+XTCeFc4Na+ZqvsRojjtbUAK303/TpTcusBFyEwniL3N0xEJE0bedgxxfmNALe67vJ9Zs6tO608hdw08s1msB1Awu7Jm50gNrnS1+kie3zUTXQPE/YYzwcx16ft5wnKmrplPoeJuqRpc+vJo4t8HnYGmqYmJQ1fShjE4VKUuwgxCeUe6A6hvPOtb656ddAOu32H9c20reC388grM8D3vgL+9Yv3yQCfPHnyKc/zfo3jLYDfD4LgF3O53O97nve3QohnAPz84uLiL99vI3zvBnhvtaCHDTBpA/tuAngPNcBD9HvTBk12l2eX0gxwulZ1LvAR5Nw07W60oF9b87ejRdl9ZrrkjkU7zADXPR/VFB3rtAF/mAG+sBHgZooB/uycj9GUoPRped5q+VhPoZE3O26d7eEG2IcppGLW4XjeR9GhZazOit0xlIdpVe+1Ad4N2b5bLei0ti/QAKdM5oZpQadNondvgHfudTHcoKePc+nMSfyezADfuwH+N2/cJwN86tSpvwiC4PBCIOcAACAASURBVLcBfMXzvJ8OhTj+3uLi4ounTp2aF0L82eLi4unMAKcHW88McNQ7MgMc1UVmgKO62N0KON3oZAY4qtu3ygCbbkg/8fQRHDp0eFsV737bg7f6efYZ8G9dvk8GeGFh4fXFxcVHwhfMLyws3F5cXJzRL7ywsPDa4uLio291Bdj53/sK2L2tpAAGdbZkp7TtId5CYMYVMk+eBaUIbHT7SgPXftSw/LgCZvhAwiOJd0/ZruPvajw3c2gj8xzuuWW3KMJYkZKO8aDu+pn+QGkIu7bsHq4GMaUvfU+nF6BkKX3pa8O2eGfL7vel8tR4Ka4cpvNLo5FZt9z+ZTkcfSe17a82AlxOCUf4ubmU8IGKB5SgjJ2ubQVopOh2s19shfGNzfuocHV0xL2lvd4O0Pfc7TFVcOs9s+0rXoBxSo9ZKY0QZv1Rd3rUcY/q627hi15fbYO7+gulSKle5rqWZoB3E46QZU8Lb0gGYDwlvOFwf1z3OMIVMM/xnRrwlD1NEepJe5YEFnvu/HazpT1sXHqz4Qi1GxKfQaHbn/2eU5iYmLzfpuC+PM82wL975f4Z4JiBtQ3u22mAIx1UT57BmQRkBCCoazHi866BuZP5kcwlDU3KlnJ+pvawGejbLIMO8k4ql0OzCelIvWYGUYcnJfFGJXmqBnCt90wyx9afTdMe1sQsJxRSYq/gSWKa3YSGnAAMg6tTUnMrVEjicHysHkgKmTaEJK4OeC8lAQluCU9qIROo0uXTYBTBUco/jobBASTI1VagFfOeKtGNR2kPm21FQveNpoetMOD9WEEFeaetJEXa8KPJAGUayYUxP1PLmCAT4R2Ssnr7V8t3LrUDXGtSQtSTUoOzVVUXcqAItbTVfxhay0Z+LN+ZDQVHMRFwemyckpTxvsS6bdLX2iclBBAmqxfV+xIEu90WaPgeWFbJtoWTqUhL28NGT+Bcw0OfkqEApou+dH3StlxDWMxvSebHaE6UECXRrcpHbWtOXqjrTINAoIoGgeW7uOnjYkNpaZ8YAT48mws1xoHNXiCJcT2UmM9iXyc9T2p6X9WT0p+qbyqN47D6YrrdPE9m+/E6PQSqoSFu9gUubqmz0lpOYKbqSdJa5hGCUXoUNaEzgkwE/XT/iTTHhZzsKrhRS1Oq/LSWtjyXt7S5acCiEwQTHkzPTwOb+lmucSQBfBGyi/XNCAK9l3HJlR/7Oj0Q9MJBn79HUJx7nIu0uZMgqobYWG8qeIprapRu3zSExV+0tjbwxSf2v2cM8O9dvX8G+PxgMPgMK7lcLnu+73/V/u/FxcUT92UaYjyEWtAc9eK6qmK7g7qoyfCTdFKJ+pqZHzs7XXk46MXcTdS0UhmEfFxbWg9SdLFpc2CO6fcK6VbDYdPURQ5HIlQ4cBXi1CSv0a1EBoIQdFGJVjG2m4p5jeXjL2kMO6EetK4+DnrUHib9XDFWiMyv1RdY3FT61yoHlchAc1Clhq/pEsFrNJIBBDZtVyO6R8nnqAACZt3SLUe6/gR858g1SFVtgK0+Jzt5kKvdTqHrCAlsTgjstiftfaGhAilowpr3ctUzWxbK5cpRfzQytvY19bCX22rmNFOJ9I91+1KPmgEMZHgEwyJx6sBrNDa+6XbFSaCgMSNBH8+POtt32lxDKGrcHAfZVoyytdbzLGBLSLerE6OQKzpTV5xG43YbeHYFWOpJy79dhZPFAM9MKw1zYdUFg3Y0Sd0z4Iix80LdbtLfnCTZJD/bihM19rHYbg1dsiCw3AGWe9QIj/qS3NEoALNVJd5svy8pe7YvV9LbfVYoI6mT3fZyshtwImm0R2jgyRCMlPMwBa8ilyKXBnw0jrg8F9LGCk6SuILlpNDUUddGUn4rDprbNS7p7559yc7PdIfaSX7avcoeN3V+u3VDei8a4D+6dv8MsGLth6TFxcWUWHt3u3P319/pSljDgqNrcX377elqMJICFKWFmmMeadt3rb5bYpH3HKoEGEnZHksTT5gsBdjH5ZYjbXbdQBF/erzmpnO5WmkG7vy2un7MJcV85LGaO6zdWpcrV3fYwvmKm2Bmvmnw0rDeOSxMYxpstL217FhoDKu/K1vuduQi8kPTKpiAnZ5b8vGddTc8R5p7wrG1zCElLWb0VMHHHLdwHGlY3+SRQ2KyKTWsA+yrudu+nvNRdYjs6MmPi74e1peGgXppW+mZFOXdx+b38gr4yzfukwG+ezO8Pb/IDHBU75kBVnWRGeCoT2QGOKqLzABHdTEMCM22oNNtmX0G/NWbmQEWxWIhUWO7l6LcuVtA1fNRT1mxZivgqGmyFbCqi2wFHPWJbAVsGsV0/+P75fbI0mQG+N4N8F/efs8b4HQt6LAzJWpzN5Qjz3TWe2GgUSvHYVQiwafYGWB4r5wgqAImykfoJC284bD8JExknjWHObf6AVopW7xDt6CXCOcktwc5aM5V42d2+iWGbcmmbRlz21BCSo66GKbfe7QWbANIZiWudgRe3ZSVm6jbYVvQo3l3fsNI+WHlS2sr+qAeG1HnqHYaJohxedMdLpEw4IemCBMl24rE+3fW3Fu8n54LMOnYguZZJeVGXeT9ZCF9yzjtffmOaVvQ9Esm3OVq+92EypRb0BKGS9ZtPRfI+NuulLYFrSCvnXlJMP90D4qde13cLT+aAFdf2s04p0BVR8dMt0nQbkj8SbfVAF2RxsfH5R2jo2PvKpckewX8V+91A+z7gfREilOJPK6OOrqt4RpRk0kqkfloN6JIKziQfyMJLOUGNZgSAiaSDPbU82wqkXAO5R9jAdZJfIbUJg3mNlLC94ACTxjM3dSx1gCHKz9+aIS9+AylF6sGGQ1nMR+Wm+RzYJSdROU+gkWhzrL+7jTxudYHrjaApiRz1YDGQexQnXSrAm400ctnET4hdKRoXxNKCsDqIbE7V+b/RwNudxBguQsJrZDe1fXH/Aj13Gyr4O+yfsNBlfrM9CAZK3qoFxScotuKE4AX14CVrsB02YStBMYLAg+PUG6TZG9EI/N9qTm93PXw+IQKvKDz6/QDXCeEBQaOJwUc1S2D3V9sehgtCIwWo77EowDWdcNRFyw7322s5GG6FBHM/Jsmlwl+yelDOJli25Mgvt7xJNBEYl63B8GyiZLA/qonZVG1DWZ+jbB8b2xRgxvbOsycAMyUBY6NepJQj+mKh32J5DirfBvQCtvj0hbVuYCFMWyDe1pLm5Mo2edMoIqgXx5Sy/hqM96XWHb2iYlisu3196GpX7Nv0iOAgBglQc2yE1IkPMZ+KMsQ1p/+DnIe60jR/Dq/YTSyvsaxREFOUdvrMUIbaH3t7vnt7bikJodJ7es4HW6Ocwosc41zGs4qFEI0fYjRNS+Zbkj8e7laRy6fR6fVwM88c+JdRUTbBvhvlt7jK2DtB2y6ANkrgbTgByZF6KYcVTeLE9EAVyl05akUaCyVu4k2eJrQtKlErkKpBSxJNov4JKnMLCior91X7pafnOkPlFHlQG/6H1K/V7ptWPrHJETpVsLyTpcZXCBaDUSDja1ZC1xp+FjueJguCzw0Gr0v8+PkggMiyxILsiA4yVBmImaM6ZZU9KXx5D1LvagMWhuZ7y5doYxA8hw0aeg4mEsy1vC1pS42AaTLDeCbKznpSsXEnA9XA/muh2rA/nr0LJLSJKxpmC40PLVqCtOxuo9jIx4afeBiM9K+5t3HRwJpbG+2BW52IhiJE6b9FSG3l2mIlJEMU1gXqlDG+wKYKymdbWo1m/rH7JukkWlobnc86UoVpQA8dCELZbpW8Tp3Y9i+tzsC19pR+WjcVzokrIHDI14supPWWiZpbvcl9k3qnt/qcLIR5VfLC3xyVtHc7NdaS1v227A/29rcHKrYl/g+HOK5GtXfjm57LlCVp5ZBS9M1rCCU1nLoWqXrogJfuuWwntrGbs0wzwBOQFh+dqHkdx/pWKePI/ExwaSbd5dfXEv77nRzclziX+5lnHPT0uH3EgbleDNb0KZhfje6JNkG+NvLmQHeXkC+UwJap50/DyN6R3M+yinEZ5qwx7Bg66l6wCRPC+6zpmHnTMPk+c5turfZGZlIr5DND1POQQIfIkXacr3jJmY5CB+uu+lmxvK91HLTuT/xUCB9lO1Eg/RXS+78JgpuzWQ5IYNPk5/Ijxt3XFG6tj89BlDIu8s3kfdRcEhHcpJHv1nTlUo/dK7kY4r+YI6URkvzTafLKW0S+EBKe7y6GmA5Rbf7Rw4GMlqVnTgpSpPrvNrw0QzcZU/rm6mhJ0Ofbi+lbtPu22spyr1mTuREJtwls+t2t+PcW6WEZVLQ7zUD/N3VzABnBtgxCGcGOKqUzACrusgMcNQnMgMc1YU98c5WwM55rfyjvQJ+MTPA0QxktzPD9JlmusbsbqjEbAUcdexsBRzVRbYCjuoiWwFHdZGtgNMN4dt1xTbAZ9azFfD2CnhYiMBhVGIaRchzVkI3OwlZJs/uFEmY6CMyhJylRqV/RL1dks/2s3jOyuDoWm7QzHS94+NOj2eUyW3UtC1Ulo3yeC4alHVkn2Hp56XVH4GXi01ukybftyCojOUhsF5KCj10fExW8jHlJj6LKlGEkFyhCkkpk742z3/VVh3w+kaA1zeTOtY85/vheTe5e6Mp8Pwq1Zkc9ZcPUDAlk8KK4C9HClQkS74v4a6xooLM7JSmjcyya11iu+03uwJXWgIFR1+aKQeYIJxm6U7znPSlVaXpbedHkG2mJGLntbqczR7PUnNOHevbzQBnG8n3Jbz3qTmGiExeq+R4tp2km/m+l7YCdB39hefAkyX3t5MP+5JLa5myos4t6FAxzSUAwnNvqYi2Aw141lXad0CmgFnZfZP3pI1LrIvOwD3GqHFkb+nmtHHJ/u6zFfC9r4DPbmQGWGgIQpN9rD4NUGg4K436c+nZbgdyp+QjZRQN2Epr4PLD1aShSWiq/GytYCWfx9/RuNgBx2WAcFKWIQHNAZzN2ugrmpb5mbrTGtJgfso9igZLnalJoKYApYoU9o1tGjTU22XZXflpOtysPw1n2XXLrJfaPjYotRjWk4atNFBTyql64DtopSvKKV5pCCkTOZYXOFgnSKQGcMJZ0qjklDby+YaHLmlcANSJlsQrhCSg6yHAQ7iIYBklQvnvK03gRkfl91DVl+QyjRRlJmm8KXdJqIiB4Vd7Kog69bi19jWNykRBUa/8t+LpVX6TRR9TJZUfNcFvdgj/qLbiQEo5TSYaYb4Tm0BraXeFB257UpKTZ/3sJyTAOxJeU9rI0xVFfLNMlzYDLHUJ7XlSLpSgEduUfWSsIGQZ+G9TF/t6Ezi7Eci6Hc2r/AisMVHHmuUiCdwLCM8pcI+GY7kjsOUrOphEMidG0phwUhj2JRLfr6xjO0byPCcAJR7xhzrbFQ8lPsvSP2btae1mak5TkpLeBLYuNn3pScHLb8kkqUNtbq1/bGqiE1JTpF+yrxPO4nfEOuM7SkKb8CNBNcbKHqKnnDaOsE/o715PVFkECWWGRSFqsK2JHsSJY/1dSa+EgYIyWSaS7ZysyPobqrMdjSN6oq/rVgNYuuwmbJWmY22OIwoeVW21UwNsuiGZposuST/3idOYnp5Ot2gP2BV7BXxh6z1ugPt9X3pKmCvOYXQzDQrtkH0P+wGvUYCfA0QMHgrdjeQAFpKCut+w4yrjGi+D/pBsFwb+XbqckMIdxKlYmSefxYGfLiB2BKQgwEhBoJiL6x9Llx0SvQNI4xXT1GX/YGbylayVSkp+UdmTmrX6WbfCgTS2zBKBNDDUxbYJUmo+P7cC3Ol4GBgrThqRQxWBT+5PakFTG/laU6Anh6h4oo4w34aBAuJlELINOY5L42OscKhlzOdRT7lr+zcHgaSnJU8Uq3chDefBWtx9SvcXGr2bbVj6zAADVXA1J3cAYqs9AWoSM9Hwmr7KLBsnRvQ3t/22ObGaqwjpRpPQFYfA6xvAUjcX08xmrR2uCjw+CRmFy0wclC83BZY6Xpxe5yQwJ/DouOt9BW62VPns9i0gwNG6UHrZFpTFZ7GOaATttmIZR2nkDVcy+RmEOuUq+Ee87HQ3Ir0uDarRvnKFJ5RLmOmepPszJx6lQn47wEX0DdM1zN3XtVeDS/uakzDuaNnfKTXRWQZWuT0uUVOeuuwx7XD1wqBLNrk6u/7UJDjuCqXHkfTy3X1c2istaNsNSddrp93EP/reJzE9vR007wEzt8ni2gb4cuPBNMDeqVOnfkEI8QmOQ57n3QHw7wshfgzAfwygA+BSsVj8h2fOnKH8RWraaynK1bY78DyHAA6o7i2rnZ8V0yaudt3EbOqWGh3bU8Ui6PvqJlyH5TdM7CBtu40h3kz3IbNxhtHcX77m1nw+WQ/w6Xm3QMK1ho9GCjErIyQ5tmfTNLZZzmbXLWbBa2l0M1c1x0bdXfDiRoAbYbQk+xczxXSyWAvv2/d0Bj4avpsQPlbzUXKQ8qSlv70kYhMbne8T4z5OjrvzO7MaYM2xlc5pwUem3aT8ctvHcs+d3+Njbm1plmVxk8cR7q1q+i+70jAt6GVGCXG0/bAwg8NI/t1oQW90ffQdNDzfJU1XnLsv6313XxoeZjB9jNlrhmWnK+D3MgV9tfkAGuBTp059LAiCf3Lu3LmfYldcWFj4NSHEoud5/0Eul3v69ddfX1lYWPjfADAE4i9lBjiqgcwAR3WRGWBVF5kBjvpEZoCjuhgGir5VWtDmWP1e8AO+2XoADbDZSB/4wAeKm5ubfwDgq57nPbG4uPjToVH+LID/cnFx8XOZAc4MsKsPZAY4M8B2v8gMcGaAh9mLN3vN3oJe6jzABvjUqVP/UgjBVfDvALjued7U2bNn/xkr6dFHH33c9/1/u7i4+MiwSuv3B8IlYjBMw5XbTRqosPNmGDbXVhnPlij556Kbh+WXto1LGIt6u06hihDKcuHXaVvGfF+5pe3YlgsYPN06G9bvPUz/OI2aXO0EuNN16+0Oy+/PbhCGSW43UtP5s/OeBITsdL0ZYMtxD7eZWYcu/WMpvmBKYRqZKq1g15anilvr0u2mytXD1G52lO+NLUpVxs9y9eNmS4FTT1lyARJ5Sb4vwSwCUS4d64drQSxus34OQa/nV0TyXBvAI6MBHp1w075n1gKsOQQ2CLoxVrB99srnrbR5/OAu3+kxt7Y0+9G5LZ6HJ+u95PG81F0+wlI1x/Y082Nfd2lV0wBT5nMndPMwz4Vh33aq7rkQGC9S4jP5vgQ8eX7t+rb5vnZMbN3Gw7049m5cCr95tzpNykD8Xt6CXus+wAaY7ckV8NbW1q95nvcaAdKdGuAgCCQFrak/DWCZdPM2sRijEomsRsCI1kEl8docUCs4NDDb+syApnp1fnGKMJmfFnG3aWlCJNRmljSoF+nnagCrnvfQF9R3jgAPDgTU020HOcyVCWNFms8ctKllTJk+uhiRkNX5cnDmgM6BLgZHiQAlTxGbapC5uy4235c0LOlkutyQkN0Gu7TcYi4n9aIpGWnq45JUXu3lcKnB/w8D2ENgiupWIx4O1ahPHGkjs84oz0hj2fIVZax1rPm+Z9aFdDv6zH7KIYYDrlBE9IUtRfQeHQHKegAnnVsQmCt7uN4SuNOJpDO1nvJoIYflrqovbSKVUQZGKPtYQaQ7ze+OriLwcK0ZSHnFTgh20QXnSI3Pz0nQyXxfnZ/se4auM59I+vroiIdr7QCXGt42iEXgjInPmq+GIFbYwQlnTZXYLzw8v+rhhtStVoQ064D09cJogBOjkY61pBDpHoOcpK2Xe+rfTBXCY2VgqpzsS1qbm25xHKH1ZIXlGysAs7UcRnMBGBhMT4x6A0Wbr/ctjXChykf6V+uo68mjgiEpp5nDw/UAMxVCVap8GkiiMY9prIegJPMjxMhk67Lr79Y0Zvq7Z181NeCjcST8Ph358RvjWCE9FbY11hWIWCvkDHBK5aEXBZTNbJkgVuguNUK3LdnWyXFJl2/ndPO9j0uali7Yvm13WTbSANdHVfAFM8kt6Cf3v6u0oGdnx2KTk43eA2iAT5w48VgulysuLi6+yAY7efLkj3ue95v839mzZ3+Sfztx4sT35/P5//zs2bM/MKz9tRb0XfrIji/TNYVGkuM3yUSXL/BOM+W4J11yOKJbiVhLtQCp4ayT1L7tq99v9kMd6fAiXXH2VZQLze2uDj2hLtKrhwaQLi4dCx/mQEk3JWnA3eyL87WY1/UWcJN4nJHGizRK8efzMrMmCcruSerTTHRFud2GHFjnKvG6ZbAGlo1Gd2CU3Q8gVw7Ue/7KbXXuqdPJUeAD08Bml9rN8WfxGlevrCu+t06czLyxpZ5Bw28qQXLwZxkJzFhFl8EkpsrJBSrbgS5QdMt9YkIFntBpo0dJSdX25jvxum73wzVguhLdw/xeXlf1xI0SM1HS+vCI0vNm2c3J5qsbwEtrkPrc0jUmTATCPzgFzNeTzcv3vdyE1Gem8TVj4bAv8RtY6wIMzmEm/p79le1o9lu2fZ39T2pIx/sGRy/WEYlf9lHzu+I1uuaQmFbudyqxrz8yrvqF/R3yPfk//kbqn+9o7Zasi938hX2T36h0ceLk4x6+K+mKxDYK1PiSEs10N8V50/fsFML6r379T0V1JEkpMhjDP/3+pzAz8+6hoO26afYfQAO8sLDwowD+08XFxU9zIr2wsPA/ep5XA/BDQogPLC4uLi8sLPy6EOIb586d+1+H9SjTAL8blbDoGnM+RQ8YQ/R7U89HObmpu3WOh4EZr676WB246deZkptI3a0W9FSRgiDJUezchsBvXXWPsMfrPoopesBpUpT0G2b0Jlei+ISLEOZv02hkGq7JopuUv7Dh42bXXX9PjfsYoTWyEgfor9zQ0Y/iF0+PpdPNf3jVxw0jUIRphD8/76abW30frRTafKsbOLe3me/JkZ3nN5Zz09zM78JGYLlFqdJz12dh3G3ZhvXbYWEG06Lu7Sa/+6kFnfZOrKfhZY+iQJm96c1KUdINqVpNzuykG9Kn3l1uSPYKuMvtoHtIb8O8cHipFhYW/nsAn2Gf8Tzvlu/7P5vL5f4OgP8MQM/zvFfOnj37H3LXKTPAbkH++2mAz6z6WHsnG+Caj6IjoAH7zm4M8K0mBS3cA/7RmjtwRmaAoy91mEEfZoDT4gbfTwO81+5Ke78wcE963i4D/F4+A2Y03Huwvw7a417uegB+k62A3auqvV4BZwY4+hgyAxzVxV6vgDMDHNVtpgX9zjNANgV9ryV8x62A77Xgd/udbYBdWsYKgOCsMWmstNSii6bl1gy3Qm2i8m7UJMvs2kLt9H0JFdl6tlTH4UmZli8035kQ1Z2OwKaD3K14PnoiqQXNxiZMY8ZH3c5TCMyWBKYqca1gzuNutnyMFHIYK8e7C69dbgS40Y5i4xrDhAS/qFVtnr/xnquNQEorUhIxtuUlgBvNAPsrHoqWbjLfl3COXT7eTyL6a7c8XJXUcZS48vzeGUXnUpIydg0CH5kJcHoiimOsrze6oXyktd3Ns/fFDSpjKSnDWNkDwlwBDo8kdazXOoE8Azw4El85M78vX/elpjMp13gSOFAWODqmpCvNdLsV4MVVoGWrdkm62cfDI7mE7jQV1r5+R+CNZlIXm9Kf75+i1KSrrVRft3WsWSQqiN3pJvNjn50rC0yWk/lt9VTftA9lmd/+sgo3aS8d+JeNrsD1UErUrItjtQD7a6FUpXGBdUthmImSSyNcgU/ub1uR8q5t6DRNdPbNbkCp12Rf0hK19nfP72C5E2C8GElN6uLf33FJjTGuccke53Z6BvxeXgHfzT7p6+9qA6zpPX5o5r/58qaBNa+ZBLP6nTofUVqvSpou0lWNDKrWlrafZVKTNETD8iMAxEFVaggT9goJX9K4JFonpLi9piZZJqDVF7jd9SQ5TWlEGj3K90lZSx9oBGrQp6YuB3l+aHzfFgcNEU48pHsTf+VJUnOOWsFFDxsdgUtNRf+SzGUZjo/lJCzTGvjoUDc4lwPlJNe6ke40zbH6rElZU5dYDTLrHYFXN4R0VaK9Ibl7esKTBPGddiBhLroj0e3iQEVgnogx+I5K+5oyfVVPaRmPlJR2M6/x3TngUg7xK7eVTvRjowGenoIMZMH3vdUWuBAGjp8qBCgVVH4kjE+NAQfqOZha39IIGNrDSy26FanyUV6RR7OVkKrp+IpEp/EYyQdSnpKTJkoSXtoSWO2rz4wTnCemPCkbeW4jwDeWqE8d6lFXgMN1ZWyVcKSSqqQKEvPbV8+hK0luIclhvi/7EvWd+R71PCcuSmox5wmM5oF9tZxsVtbrjRbrSZHtBMkYx5e/O1IlmUuyn1rInOwpXWwaPGpzb/iqX1FudSbUsTb7EgMKrPQE1kLNcZLPSidb6VjPVjxUi56sW5LBaiJEUjySW50s+JgssY+ovmRqovP9FTnvodHjBMKT5/O1vMDxESFdixR4rs8xPax1A6z1FM3OtqLrz0yoY53UbDe/YRV0xMyP331yHFHayLYuu9JsJ2inSGf9rdv5bXRYZ0qmlN/KeAGYq6rJStqYtZNxxPRceLPjklpUKHI8M8DpZjVbAVt1Qz/gsNPEVypEEw3XAXPWqT5Ot2Ytf+daRZti57b+LFew/BjcGq5JjVk+o9sPcK0ducJsF54RYTiQlJP5sQw0gPR/pF9vfGWmJg1csdnlo040lfsSmrUikMEcNvtewv+VWsakh21/Wn6ojNJD8tr266QrDVdtHDxtrWX6B5PapatU3P9VYLqotJbtqDUc6MYZhKGgHXGiN6Z7C105xsuWz2foKkWSVrst6buY36nRQK3ILZ1t+g6f24RcRdv+uXT1oT3pWytR/pKGmAEZ7Pdl/ZFcv9yMa1+zLJPFAE/Qa0O2odmOAvWckGQsB20zedQKzjMIRdL/mpGCtvpJ/Wh2CBpE6YllrfJZo1zR8ZzbjgbFsj9J/Whbn1kIMJiGChIRta0+owAAIABJREFULx/zYyAH2S+tumXZD1UhJ3t232T5mJMdeYo+3gxGIt2UHNrSnGy07MhiYSCIA1XXt0gD494FG/Zt96nZ7jt02YVAjbKwli4720xNBKH8uS0sm3V7pJYsH7+ru41LrhX7Xo9L4U7hjhZsw4Ix/MTTRzA+rlyURkfHnLuQ97qKfCf8LjPAVivstRb0buL87kbyTUbkId3s8JuYLvqYpW+CI3Gb07eDNIS/kwIUDnp4rwlXJcThBpTOb/i4kUL76q1H+7UYOnGevjWONF5Ih6vSzrmbfYGrLfcY8shIgJma+1kvLKfrTqd9/Fx5ucLd8ffXm4wWlWxHbnBQ6MLlM0NzGKToCzMak/MYRdBNyA3qDctPhsd0bG+z5najBc2JhWu7l3VxvM5oVsl63y2gdH7TXe+cEB1K6Uu7gau4pb8phVGSqeb5qKX4D13c9GUQETtJXfERd2/abV283VrQacEY+Jblah25fB50SfqZZ0488D7BmQHODHBmgMM+kBlgVRHcps4MsKqLzABHA+RuFga8e6+2oM2h+t2iC50Z4MwAZwY4M8CxryAzwFF1ZAY4M8Bpu1V78ffMAFu1mK4Frc6A74X601nulm4e+D7yKbR0GoXJWLeXmpGcn/laPPfcV0kSmiwfA9VLwMXeug6lEV1a0I0eaV/3PZu9MP6x5anG81LCL64txfVOIIGwhJaxEDi7IXDboRVMwIfxbCUZa6VxuW2oAqbbidvT9vmg/M2Q96Xe87WWu26pOz1fT2oFs25fWBFohjCbWQ7Nmbt0otUqQwYRtooucL3JGM3J96VU5wemHLGgZS4+WVVnfmn6wjy3o9qWq3xSdtKli82z8r6SqrTLzrb6YIoWNI8fllLanlKfkqJ29M1jIwKllC1o19mmOhNVoKHthcBv6kLDrdutYTZXvx0WcjBN91xqc1MBzHG0U/WoVe3uS5RcTcScBkDQkhKp92NcGubFkTYuhX/f0RlwGgWdrYCjGthRhe7FTOF+5UE3JNMF4F7o5rvR0vxQtfEelh+fq4lmflh0QSmG+o5as5ZndiaJbVKOPAcm9MOBUA5aIkCfspODHCZLAR6qReCKzi+Xy6PZ96VOtBwUQg1cEq6klqmPqw00PyZuTZ5rKOqZcoykZ+WzAupRU2s5H6Nxia2SsD5SB8aKXiw/ESjC9WbHU8HrDS1jlo8E8vlmHiViPZ4GkwRmigInx6mlnAODF5DOJbnK+8cKinaW+sFGfopqpTxjDtTObfvBtoGRW8/SbuRg/pt14ZHm9DxJly93GPxBGRhCQvwXz2sPVAIcqkW60wS6lruUuiTRrFyTlDETksYuh65DpJPb2mCJADdbwLNrOdBF5tGxqO1ZdvaggchJUpcB7DkYa73nybInKVqS2dINhu4wod4M4SbFRUcGVV1jMIO8dIGijKNue/2+ZA45yWKbSoMqAjQHwNVWDqNyQkfpUfUsQlHUzG4GeRRCEludYysIjO1BnW8aVA1isS/xbP1mV+mA83RTwVsqP5LgW0EecyVfugTlaGxDjWPiDOU8CW4h/197F2ii2aaHSUh3fIGOyKMMRfUTxOLv+RxqV8uAGprqJxNhtD3rh5M9HdjAdhEyDbFNI2uymO/I819Cg3I0MEh5shZyqzaXAwE9vp/+7nV+vEYgcYuaz2H5qvwGq56kvU0viXv14nCNI9qNyuV1kT7OKbo7bVzK2753dxnMMwN8d2v3rjbA6vtQ7gBM9uw3jRTkb01ja1bj3fKjpq/6OONVq90p7DJE+anObyZGVaHrC91O6HtqpoeqAQ7UosAL+hoJVhrbohR+j/sl0ohQQ/hCQ7lymIkDJEnaBl2LLAK34qlVKn1czUUMDQ+DFDCAgR1JiJDPatfDa5sMIBF/Fsnnw3Xg1HjcT5QU9ZWmkFrRdSvaDfOr5T3pIkWXJp04/m31SBw7ViN6NRwaZfMe1i2Naz80Fvoazc3xkQCEYmwfV5LhDATBotmrtp4f4FoT+NaKF4NzmN+Hp7iSTxLClLxc7ajgFSOleF3QX3u0AIgEEa0clPhKLtp8vCBQyNFXLt6XOJlY6UBGaJKUsJEOlEkVk861fXAFyp6QFPNE6Majb+NkgnW01PFkwAcz5YQvCfANqy/R7emhKv2DaQTjfYmTLOlCl0uuArliY378rswOyKeynqgPvmJHb0ppe5aTbk/TJXo7JFeptrti1GcUOS51mi3SWxteOYmxVvl0qSOlbq9sOWFY6tB3HNL/2kxvxbikFg7u9zXdlsz3VeNmNC5lZ8DpBjXbgrbq5u1Swlpt+wiswU92fkAOZG4HfzfFyvteWvGx6SepSS5YPzyltuLsNAyy+MatAEuOUHPMIy1M3qGqj4fpWOpIw5SwnlsOtiP3mLceqwd4atpNHDe7PtraP9l63okRt1Y1BzO1ok0mL/AhHO3BX17edNO+jJpDv1RX4orZuaUL4A+vubWWadx+4EC4ArUy5UpzkEI3zxT9hCGNbnfnN5L3USmmt9VK6K9rFoNvuq/iDrfJidlUCnmfpgVN27fRc9PIh6s+HkrpSyO59LIv01/Osd0rw0g6jgf4fsPanrsT9Du2k14xutp+vZveVmmeBpzSMIKUK+093fzOkqJMc0My66LbaoAuSYcOHX6gXZEyA5wZ4O0ayAxw1BkyAxzVBSdLmQFW9ZEZ4KhfpE069iIYQ8URjMGejNBR7me/59QD7YqUGeDMAGcGOFsBI1sB39vkKzPAb70BvpczYJbi3eCKlBngFANswk329i9nfryepgnLLNOoSRnc3FKd0jCIfVYli+YHqPBs06GNzDNMwkaUsDMT4RYGmKfUok2kkpbeXxE4NRHXHibA9fxygH1V4OHReH48s319U+BKK3mmzO1nKlIt9yylJUCqRE2WknXB8+abbSHPFW2t5ZIXYLULvLCe1Il+YszH4REjEHz40lRT+p0rAs/MeBJKMdNSW8lRfu/+nFJwChO3O19b8yVgpeX89DXKdH7zjsATkx721ez8BM5tCinvaWstj+QCVBmz2DrrI8dEfeHRopJrNNNWT+C5VVK4yff90GQg5S5bjq3Ssbwi0VUbR6nRFyCJfmqccI69halOf+0zYN4t6XDuQFuiLLKtWgJX2sm2ny4GGCsq+MpOM7xWQmK7lvkREtTAVew+oSBEninbif1sf5VKZfFrzG9APfKytw236XvlNjMDMDu2oIvwJbdgP4tnyjMlgbWeh55NoosAjH+9v5Zse1O60Sy7knbV8FW8PfgsSq66xEsq7Es59ziiFa7ux7hkwljme6WdecshSyoDRufXb8UZcGaAE5/Iu+MPioJWmro0omlknyIvKdeoCUBllE2KULtDMD/1b+YX/U7rxerOatKazGublJRnwUovtpzPSa1nBhqnnrImQ0cKnpTtu9QAaHRIoZq0qwSBtqlbRcwujDGgeg5n1wO8tM4A6dTAFThYFfjonCfhKkle+mrQ5vtu9oBb3ZykoBdGBEZD6UZN/pK45mBJKph6ynHq25NygBxkOSjyQ6W8IqElIlwkmAshVc3B8/UN4I1WDnOlQKr9qLM3BfhIIjXn4fevBPirO8CdXk4akfdPAT94UNUzJyHUTCbMxTw+OA28byon4a/X1wOs9D05xFKq8+ERpWP97JKPF9c8rPZzUieZNPKn9qv8qEd9o62MHl1/JksCo6W8rIvRQkieU0I0pK+F8LDe87HeI3Ck9YWVNjLzIzhGFxylx61kQa9385gvC3x8Tkj6Vya6+AxIgfO5CirTbc92JbTUDzxca1JRjPRyDmOFAA/XBI6PEVoiZRzFAVb/ZsqhmmMwAEXgmuQvgbrOQNHi0mAH1Ekmtaze91BVEc1R+RSZTVcanl0ro6faikQ9vwu2KYlw5mdS2hLYMYh1PqsxADoiJ2EpAkc6PwJX1Inms7e1vj2VH40jJ1OsW5PeNylj1nM9TwhRlV1qoneUseWkYbxEst/omz3VhzUdTstCDwVOLHXQCPZjFz0c01MOAvQGQJNuc0LECG5Tx5r1QLpbeheEmvLmODJ8XFJGTxnHvRuXzPxcXhx6/DINrznO5dICJaeYjGwFfHdb+q6loAeDgXBFLBpON3PGl0usbG1ja1brsPykpF9AA2OtBKyBIJafH+BKUw1a8aQoTA5oNgREo84yuvSKaWBosORAbyVGs6FLj4vMLoFGKbnK58e50U/qKctBsKeI1MRKRQhIiIarMosS5YD7y2eB1xvJ8lGmkJOLJGEt8MhYgJyXB6lzM9H9Y3ELuNZJ7hrsKwc4WE2uRDlpWBjhroErSo/ANem3m8yPAzjrIrmyFThY4WQjqc297afs8MHl5Ofrd+CIcCXwvnGBE2PJVTnLzkmDNKJW3dJg0Q84IYlJX1pGA5Juxcm+qSeMrrZiLbggtDQye9j7EmhjgA9X34wb7KiFaThIFlcLye+UfZP9gRG47LTRDXCr49Zu3l8JMEEfICvpb5uG06abaWyZbD1qlm/ACGt7OI6wHHs5LnGscJHPw8Y51m1Bz3bublfkLzIDfPeKetca4HeCFvRm1637ymYRXE07wiByC/niFn07k03TGfhoOIhobfx05COz2TkUfXSWM/vkoMSoNvUUzVpuw1YsVyCd726I1EbXl/6brvQ/vBLI1bidDpUDHBt309In6j4KjvpjHmfWAqw5hC646qKwhys9MRYk3EH0765subWg6Zu9wa1RRzrN4A406I6Uhw/fQT5zm/UrN6MVrnnrBybS6eG91oIeRnpzwuTa+h6mLT0sv5mSm27m1u1ISv/j7kE1hfROI4tpgG+m6JQfKPkYp6+QIw0T6bCNsr59t1KPacP13tPS6V4Xw8qebUGnG9TsDNiqm8wAqwrJDHDUMTIDHNXFbg1mZoBVHaYFOuC1zACrOroXNyT+TrsiPcjRkTIDnBng7di/ZlVkBjgzwAlpUDkxS4+ulK2Aoz6TrYCjutjpCnhYNCR7LfmgR0fKDLDVou+EM2CSrJQ+3OkZ8OWmAmHsxHMnngHbZ3o8B2QQcwI+9mDLs7QPTLspTMYgJRhjl4+ze3kGXGZw9/iWLRWfVroKcLGTpFUl95Y8V1ztCgROreoA/9PrCtKy06FKgEfHk3XBtzwlRTmSZ8CEc17bhNSktsnxyYKCymwlI56sHqkyznHyDJgym69vCKciFc/QeQacbCuBh6sBjjjy45koITopY2nVbacf4C/uuM+U086AmV+toACpxBkw40TzvN6iuVnPuz2zZSsl629IfhASCBxYimNqd0ZBUK5QmcP6ZpGgXwqfQCTAPpfls6h8dqPj7ptz5QCT5bgyl1zJSjgzGUub1+4nS8LvnpryabS0S+Hqbkp+76QzYPO7f1BdkjIDbI3eSQp6GN28t7ThvVPQPto0mi4Kegu4wxi/UhuZAb6FPPeiFKKpZcyBivxIMZfDZo+EqxrASWFOlRQVXKUwvKGTTMNBGUEl92hQ2p4HKVlI/WNS0OUAhxkwvaSI1JWOwAvrHlq+B6pZzVJHOCTMSURLRSILMGN+V5vA9Y6im6k9LKGv0K3jGqURfQ9nVgOcbUBSy4xcs78C7KvlQFWqmqdcsTiI02Xm9Lhyv6KW8tVGgPVQVrOWU5rC1Da+sOnjcotyiCS9A0wUgNGyyo/SmnSbYn402CtdRQXTaH7PDCR8xsS/f+mGhzdaHp4a93FsROlss275PxK3ZHEINPEdmB/bQ7qsIK8I9dEwEAEg9bJJZt/qenh01MfJ0TCofBhM48ymJyUXOXgSZmOACropPVx3UNACIDlNadENPweqlR2ueUp7WChgj3KjnJAVPcAX6uz2XqllSqeSqub7MhcSvaSWSfUutQJshjDgsPwIqVVI/BdyYPAC0tjKeEcEPLmemIa3YF93980++2aP0qw5TFMTvU5NdEU300WIamh8XxLcPNLVmscsq5QVtfpmXvB3bJ+8/B4Id2nOyHQ5qng+KuxXO/KmUMY7zZsioqDTxyU5jgwEOsjL/lbLR8S6AqkUJHmv3hl3p6o1fW16j0Tle6so6MwAJ9YeD/4ftBTlvfgBp2mkshbSfIRdkVr4UdBAuv2AKbNHMfu45q/WMnb5AXMFfX6T2sNKt1YnLfXH6+V8fOZO+db1boCpsnKTiSUhUPSoPczBJL6yDUK6+bYFqvBXh6qMdANca8fz46TgkTEhXWeCRKQbpTu9uGXrCwP7S750KbL1e/k+z6+o1Y3tZ0tDSSL6I7M5mJAr6+LSli/doEpWXXDwenmd7xzXj5btCiEDD1xuJf123z+udhr+eiX+vqy7z+0T0s3J3mkIZLu7owhxdc0JypmteH5ctNJHeLXHurDaIxCgrvOjE/SXtsAx4WO14+GW5bPN3E+Pk8BVxttqfOkCp+A+Oz+WT2DLAfiRHOdkiJMXM7Fur7dEqPOd9FNm16NxNLsF24ouR2y/BKkc9k2u5LXrznZ/D2lu9k0Lesfxui9X/4lVOXdxPAZoSPpYMyAFX4eQl91taWxZzq4NyQnVHoxH4FqJSj7dAToO05Y2jahZt8PGEU7wGNxlp+OSdq20wbE0v2e5A3Cf/IAzA/zg29vEG7xbtKBpXFz0sDK0blq6nk+nRBniT0doMSuNg86FTbd+b3fgOwdn3v9QLf1Z316iG1Zya3nYGeNax8ftnptI/emjXFEl82v0BLiSdqXlto87KfndanH17NrqF1i1DKLO+xPTAWZrbrq503fT0lwlrzGylYNsny2ma1U/M+WjLFU14qkfkvJKBCOeDlZ8jDtcavirNN1p2Zd6brr5Ia6sU7Sbr26l6zCn0c0I0vWtx3I+Sil08/kNd99kiM4DdXd7DPNCmCq6PQOGwVV1z0c1xWtgd2fF6drNwzTl6bfuIrB3S0u/VVKU9+qGlBngzAA7ayDtYxxGOe51MIbMAEdNkxlgVReZAY76RGaAo7rIDPDbZ8iyM2Cr7rMVsHsVma2Ao46SrYBVXWQr4KhPZCtg06DH/YV3SkHfqxuSOXSbLkmjo2MPTISkzACnGOC7xe/lbbuhCHmffQ6z0Qmw2ocENsxzLH32RdCDYJGpPczt02eXBQ5UgUcn4mdSjN+73qWmrhdq7hov6QfoMRbuIH4uVvAETowI+EJgbRA3wpRIJEh1YszDTCV+przS9rHGuMPWGSFhnjcaAozlOl6ySdEoUDvPRXWSZ2h9H3e6Hq5a2sM8n6TqFM9EL1rkM09WCTTd7igIzEwMi7cw5uH4aFwrWJ+hU4uZgd/NREiJf1/vI7EVTsKaO7V/ecdLhDLk9iTp9UtW+RiU/oNTlJZMtj0Ja0JLi1vJ+LhUxWK84tet83D6JX/vHGUsgYvN+PtShpTCHN837+GAoYtNY/mNOwGWOsCJsfh5OM8hCaKRLB6z4gtTO5xl0JCarifm9yfXAtzsKOlPU4+CbU9wjBDY6cl425/bEPiLW4ThVIxms+1vtnwZv/qxiXhbUQaSMBf7ZiLkpBBg3+XZv6l9zfZtD3xs9FQMa/PsnTU2X1WSlJ5F5UtFKnku71ACCxSEyLNjm4WQcpeEtSyRFymxmud3sLO44vY5qq4nXbc8i65agiO8h7scZEmocW4mGVe8QDI73l92O86ZAJf5HFd+OzXAO3FDMp9Nl6Ret42feebEAxMhKTPADgNsdn6X9qk2vCYoYUMT5n+79KSZR88HbreFCnRO2TqD5KTbDolWLd+n9WfHSzkZNOHclqKH+YEfKAt8eNaT8nykanscHT0PHBQYiICSjEIE8Aguh1KGvNb2SeHmwfM6BjGg1jLfl65JdzqeBJQuNQSWu4rUpRvHfJWDqgcqb9Eot8OAD1p32hd5cCC91fZC/2IFoTC2abXA80R1/sz/EWiiHCKNOovc8Y0AEob2MMt3sB6RvyzfxS0VTJ0SkmQvWU+cUvQGAm+0PXBsP1QTUi+aZ6jUPJ6rAIfrOSk7SNenbQAnCLBF7eEgB05eaER5jfmxPgg7MbQtwTHttsP2vdAAvr6Uw0ghwGghcitiW91qA0u9HJ4YV2CbLh8NCWlrAjEsnzQabJNAGUdKa9KQk/rW0pwE3S41gRudHD4+G+DEaOgyI4Q8z39+zcPNFnB+SwXMIPnNLdb3TwI/dCiHS1sB/nYZuBLCcNTqPloHDtZzYPALuT2NSI+bbUVDQ7KafUS1VQDGfycERcWw378GvLal6paTko/NMRhGHps9NSFTZ/gC8xWBD86o9/2DawJnNjwZRKKaEzhaF/jgNP8bUrZTnZ97GM0HODqiCO4aY/3mlS4728IPqWW2oanPTONHeIrtwzciKCcDfYR1y/do+nlMFX3ZF0kmb+utSy+jnPxemOS/NSEtjXf8WfQGoAHchsV4X2jYzDyk0QvBp7uNIy49ZZZFjyMEtRh8hZMh+Sxq0HsC1IAn3mAGTeA9nKi2RE7qVrPuNb9xL+OS3N0IlK49z4zN8WvYOGdeMyHWPAm0HaTdnAHr7B80d6TMAFsdo98fiIIDYEnzj1MfiS9JRhtw0J3QRR7SzeZyK0UfVwRqxp4ghAXObgjYxDHLQFeI75tPznB5rdn30WaEGUd+jIw0Xkpq1tKd4t9epotGElTZVwowW9UeobH5L7jCuenwpaXhpWuNKzINy87ADwnhB/qq5hU9nPBVFQLPLQsnrJXqqwpIlyG6RyWSEHKy4Yo8xPLRdcXld/rCKo1jsi5ovBnkwXUP3aWennTn1+gRnmP57DFLBckYdZR9tRPgv3kRTjDscDWQq0o7ahInP9+3n3WbrAsO2jMVd9/89nKA37mSXK3zfb/4kMCIdMWKl50Tt6tt7igkn8VV/lSJNHLyfT9/QGC+nuyb9LFmYIjA9htnowpaKPe3w1W+dK2zta/DwCeutqIbFCdnCR91QLq9ueA+fvecdKrgIfE0bBxR2s3u8q33KDWazI+TAe6suEjqge/LFe9OxqXh45wKOrHT/PKmK8Y9GOLMAN+9knY0o7l7du+cX9wvKUrOZKndnDCK/NaDdML1lRUfq9YWMWuP4/IPzSt3BztJA+wIGcffHa4EMmqRnbjC/b/f4Ao6eY3uQFNcEjoSIyvdttxc9M9OjwUQjkGTgR/s7TR9z0TBp5i781nPLQVOg5kme8hMjg6hr7lSdBlgrlofoi+vI728GuCctQ2sfzZfdmt6c0XCQBeuJEVJHHXO39J1puioC66c//l3tGtPPNcDZR99h340f/XDB3yUHPnxTecqDHeefOev3vDxBzfc7fFTD7knN9zduNp0k+2so7EU+voLBwMZ+s+VOOlINcAuwwxgNOejnEJLc+XqMsAUOXFppbNMw/KbyDMIQbLsu5Wi5FGPyCXrnRsoPDpwpd3CVbuBSN8OLWjXO2cr4HeOLd1VSTIDrKotM8BR98kMcFQXmQGO6iIzwFFdZAZ4V+YG2Ra0VW+ZAc4MsP0pZQY4M8Cu4TUzwJkB3p3Zje7KDLBVgzwD5pltUvlFARquGLgK2lKgiJk0vOA6N+EZ8LUW0LPPdUK4gsdSiS22IMDZTUgoyhZToFzjJ/e544xKebyBIz8RYK4EjJe9xNY1t97+6DpBJ/tMT4AULuPj2u/LU9wrjQDX27nEmSPPy46O8FwxmV9R8GzTcY4lBMoyvFwyNjLL99wq9YqT+ZHo4k68XX88p5SAU40noPHENjzfUPnFt17VWe7hmjs+7itrPMv3ErrOVODizj7LboeIpCzm4xPuGLMrXX3+b21fBgHGisABx5looxfgX76aJKJ57s62Yt3awiY81/7gFAPYJ8vHfstnJc+HBV5cEfiD68CydczA/vdjh0kj5xLnuQUR4EpLUflm3fK/9peFhONsXWyW/UNTgST8beK42w+w3FNkti2ZpWPWunTUebatYlVbJHAIX0kQ0jgf1kS0jKXt0CnnO/NIwO5L3M4mlEfdbju/PqUgRQRF6V6oeBF1fm1/V+ybPIfehsqMrjssNjcJ9rxjXIrAruR5btq1YbS0HudcKn+7iQe8GzckXSV2hCT+/Z3slvSuMcALCwv/AsCPeZ43EEKczeVyPx8EwUtCiL8x+ut/e+7cua8Pm7UoLejI2NruAGlE4N0oR228TciBRnap7cug7Vq7maQpz0PpCkGSU8Mz/O9Nn7Swh2Y/wGroZkR94oM14PHJnAqUzhRSmco1Qrla2PmZBGnVo16vcuWgOw8HHIJePLu70fRxk7rLQU7qH7NMm35eEpiPjQpMljkIKolGbVw3ewJXm0Iab5Kps2XgoRHqKQM930fHVxKAHDx0fiw6pStHinwBT1KedB/h+1O6kjQtBzSW6Y0tgd+74cl8HqoG0jgqrWVqWgvc6OSlWea1WlEZVZZvswe0BTWjSTTT/UedcVIj+9lVD93Aw0xRaVXzrJrk9L6KwGHeAEVOk9hlG5DEfmUduNpRtC8BH97PRLnF76yr/E7UAjw+qSYXKj/gUF25lJl6yJxQvLoBXGrn5Ps+PiZQD7WlN7oCz64ot6fHRgN8aj8wwWtCyPI0Bjn4AvjzWz7+dtmTxpEkMd+XpDilMBfGOCnxpFziOOGwUA94rhTg+AgnU6TwBW62gWdXVdt/fBZ4ZFSpLrHfXmkAVzokxUmhh8S1Dzw5IfBjD3lSP3wjbHsSzYSvSCuTBudzIXxZJwT76Fc+ViK1rNyUGPxD6Wzz36rfs90OVAQ+OiMwRVI+EJIuf35NkexHSMeHOtYm1c82GCsEUOJT6j4GHKGMaSknZJ7bMp0sWGh4Bb97dmdNRIduRfwJvzl6FHACUfZI7lP7OyeParb6CnSThtjIr0j5x5wytqbOO3+mdac5OWf59PgwbBxh/6NnhOQoAkVYa1lMc1zi5L4dkvzahavE9pWwfUQ3m8ZWEuHyM1KDiCk1mUY32/mZCw7mJwNSqMXMjpih3boh6XFdR0iS32Kr8Y52S3pXGOBTp05S9MvPAAAgAElEQVR9TAjxy4uLi+9n31lYWPhtz/P+SAjxXy8uLh4dZnDta7YQRzr1x4EpCUWkabjqTu2ipek6c7vDQSGpMdvqBbjTVS4yZmLnpjF7eDQnKWb7ogQpHBqzHDwb0ocjCYgQeGr5ydUrB5lvLQW45QhMzsABHIBtupnlu932pYa1DlKgyygnHh0K5Cc1eis5IY2eS4oyFwTS5YZBDszEN3l0NMBSL7ma42B+oEq94uT70vgw6s9NaUSjxNyfmQpwajzuj8pfcCLz3dUAL6w7VtGDABeaSNQT8/vikQBPTSbz45B+aUvgu+vJuqAsIwMR0Cjb5fviER90SbNX1zSAv/SqwHkHGMbJxSPjQM4RkepQxcfFrRzW/XjdcjLw2X00tknt682uwLERgU/sS2o3n1nzpT+0TV/T1tD1if7GNi9IE8aVrytq0lMTDECSS2hfM48nxpTcpL0SpQ86yy89AKykIhklV4DShnLi6qCR6YNLn+OZSvI73eoqA+2i/Dm5oOuVDVzSOI4XVXQuO6X5AevJgAryEG8r6ULYF9L9yE5FwdW/m5Ye5sWhtKB3RnPb+e3UAL8ZCtp+73c6lPWuMMDs9qdPn66dOXOmwQY4efLkL+dyuctCiH/8Zg2wy4VIG1OXAZYfMI2fY9K3GylKLR/oIlIpMpFGIwvfT4gCsGwcACmsYTvqy447RG/32dsBrjsMMG/7xIybIB0WO/ZW001zM7/9Fbe+MCMYfXvNTcUeLPtJIfzwazxQNnx+jS+UPqVrYUQk+8P9wf0+jqRoGf/upQBLDpcaiqNw5etKP3s0wJNT7rL/9W237jQXZOt9N438mVkfJ8bdNPIvvOzj5c3kNW6Jf2xW71RYpQzSta/fN+4mqbmB8CPz7rY/t+EuA5+a1h68xm1ilwEezbv1rXnP8Vo63ZxGxA+Tokz7dvgsbju7whbKia01edE1PCy/dIU59xiixp5MC9r5kTn+mBnge62pPfrd8ePHT+Tz+T/P5/Mf933/OwC+DOCI53kvFwqFf6aNdNrj3mlSlJkBjloqM8BRXWQGOKqLzABHdfFeDcaQNp5nBniPDOu9ZHPq1KknhRC/DeCfFIvFv+33+19sNBq/cePGjc7CwsK/9jxv6ezZs/98WF5vmwHu+Ai89Ag2O10Bw/d5AJN41WwFHFXJg7wC/uysj+PvwhUwt6eTIRGB+7kCTvt2drsCHprfrvyF93YFnBaRSa2247rO5oDyVkZDqo+O38uQf9ffSAP85P53rDTl7OzYjs7H9Qvv6qa71tab+MGJEyee9jzvNz3P+6nFxcVv2VmdPHny857n/SeLi4vfd68G+E0UZ8e38pyVpLKMPhcm/u1Sg5CHEtqwj+7IP/FcZ7ocHS/xjOj1TXXfo+PAwyNRfvL8aECJQYJJ8cSztLGC8v9tUNsxTFIzuc/zXEhAh/Sp2QkerkNKLVKaz9Qd4D0ktqlzfGo0Xva/uN7Fn1zp4X0zJbxvthTbrmc+FL6SEn6OHds7beBvVhgo3igHiXEBjBbVfXr3X/Iw4c/Gi4CpwcBjPh6FMx/q/pqJ97C+n5gAnp6K8qNG9K++vIGvXevi9IFxzI1SL1Klvg8ZbH6jB1xvS/ZtO3EaRCr2ozPA5+axffbJ8r3RAC42qFtMOch43RJeY3vwXNl83/1l4JkZJcBAISvzfb+5TBgLElailrVO/N3n51Vfoayl2c/ImM3XVNlf2YjKzvKxLdg3CI+xr22/byCwuOajWhD4qWP5mGAG2+hrt1X0JcqPmme9T04QgFNl4HubSYah9ihJGq8/yooeGSG0Fu9/vJdlnyhDSoVyS1zXBdvw2Ijqf5QtNduY+bDueI3/M0+LbjRV2aixzm/HrFuWi4l1yPvMxP7EOiXAaLY964/CK/zm2sZHx7rV7znjyC+e+73/l/x+JTEd70sjBdVXdiYKee/PHfbLnZ4B/+IfvyBGJyb25OHNzQ38zIcPY3Jyck/y2+tMdlo3+vnvKAP85JNP1judzneCIPix8+fPn2EhFxYWPgvgHy4uLv4kj2VPnjz5SwB6586d+y+GVWIQBMIMeB1pmqq7+OFEGqlKK1iRjHEXAgVjKYAhPT9SqabmqgBdhhoDD9dbAW51tKYuNZQV9SjhC4/6vDJ3WSZCHjSC7cDDd1Y9XGupc0MCLYdr1Oj1UMwpEGRbzk5rQ+dIBSttWw1tseykLTf6niSE1dkW/yfQHyj6dayo6GYNncjy0Xjmczi7EeBqC9uqUnT9IWnLOvrV11p4dsmXAxIHpyem8vjBh6uSNObbaLcsngVS4J9gGmlSjie67CRKzzdIISvN3s2+kjIkhjNTEhgrMqiFUEYxBHAquQATRUWNkl1pkRQNwTYSqawxamazgUnMUvuaUNDDNYGPz3m4sNLC//7SBr6zpKwajf0jM1W8/8iUBKHW+xT9V+1BFx/qWt/qKAKZ9ci6Z36nxwT+7mGAg+7iJnC7p+qWbUVCl7rgDNBQzXvbdcG63egLCXd9dEpgmhZJWgYhiWH2i6stD396Q+BsQ7n6kD4nhcx4x89M0+2JllSVj/lxgnS1ncOxuupX2/0iCKRhvNZSAeSXw9jRzI/0MA3xrbaPxfUANzpqGJgrC3xqfw4/+nAB37gjJM2tJUzpcsXJz+G6h0/OGWVn0I8u5URZN9Q1RijBqc6B+d90TToSkvFaQY3kfINBMoSH6SI/xqhvkuYnKU+9cpLxWl2N/WWlC1xo5FAvqH6q60JpXDOYRw6vrFPmVbv4CcyVhAwMUS9QMz2qI2q206BRpYvlNM9kJe08ELLs9B8nfcx6ZD8lxEWtdpL/zE+7FRHGGinQHYt9eDfjSHJckq6Hvgf2exlII5zN7mZcMsls1zh3Nx3rgk2L3cWK0Q2pUjdWDm/C6r3ToyS9K1bACwsLPwfg54UQL2/PEDzvzz3POyCE+BC12YUQV0ql0j++2xlwuha0xvSTc49hGq40vi6QS7se8OO006trARYbtn+r+lVaQHD6F353RWwPYmaeDAhwkjsdDjBsLB84NWvpjvT8Ct1BkstQDkAK4kqW/dxGgJsOWIvG8f99fUMGn7DTZ+eL+NGTdaf0IQdwNwgn8JuXBNYcMBQBm3pBGVE77SszeIMLhhJokSB1yEButdr48mt3pGuHnT5+dAr10VHHECFwp8UAA8lnzRQFPn1A+0THb1Xt66pbgRN1t75woy/wK+fdut1PTwQ4OupuKxpi0sN24kr/q7fCCYl10R8McLXhJ+hr/uxj+/JO2Uu67fx3T1KHOfms8xsBXt5w6IBL2dA0iVJOPTkJTeZHg/3UtCddrux0eSuQbmiJJAS+syyckpMk5R/h5MWR33w5wJi05vE0TAOePtucFLny218OnLrsw/IbNo5wMkBp2p1oNyv3oXTy2aVVzbdPA8PCvHa0YHuzbkh2e7yToyS9WyjoNzFHit96v5Sw+NQ0WvqVVR/nm27CdabgPtvlivL5ZbpwJPs6Kda088I0CpNbnt9ecg/QefjwU/SFOaDeSKGlf/PVNSx3k031A4dL+OFjdWcbzhXd78sf/9Zl5cpkJ04qKo7Bnr9L02fmNSm873BZWdps4UuvLznL96nj0yinzNbXOj5ud5PtyNXz9x1wd9nZYgDhcPvgrx8bcdfFeg/4V+fcWtDfM+XjAOPuORIjDbUcGuGMpPO1W3QFS/Ylv9/H5WZyEsXsP74vhx6svVmuuD3g558K5O6Inc6tp9PSDD/pIo6ZB1euronUsVqAJ6fdtPm1ho9GiiZ6mq44J2ynJtz5HSj5GDfjMBovl3au2uwzMIXbHlFjfSIlv2FnsWmD33tRCzqtLt6pMFZmgK0WywywqpDMAEcdIzPAUV1kBjiqi8wAG/1iCKy103POvfQD1iXMDPCerVHf2owyA5wZYLuHZQY4M8CuUSczwJkBfrPWKFsBWzXY7/tyB9BUfzF1UG1lLG416XjctmKMkmbTsn/RNpYGMvjoopSIi7akePZ6pSEkQaziwkZJatkWhFTAiZ1/MXj4QODVTdKelL+IEuGeyZLA+6eQCDtIrVjCGgdqHkrG9iDLt9UVioilfKG5rc0A9R3KVkaQi34aA8e/sKYkGW0xBaoL/eGFJu60BlI+USdKb35yvoAfP15Hz9J1JpBCVyHqFduqXjyH/totEqvUYY7qj+9L2UpKWi5bOtYlnnkGAnO1fIwSZVnKXiApYCo3mepNPGtsdPr45sUV3G70YvT4WMnDkZlxHJ8dTbQVz3IpBXm5SQ3kqB2pnzXqdSXFPFItx+qW7UvIj0CdrWM96HWAdgOn5yeQL5jbvAI3mwK/dRloSsguqosyBpjoLOFDB8dQqsW3+HmWe2urh0PjZSvMnUCzJ0CamuprJi3Ns9x2r4/NXpA426Yi2qHRPKYqOUu1TYBw1E8eBR6btM5mKX3ZVP3M3vrn+TQhpvlasu0Z6J7fKIEmUwmMPfVgReDJyeR31RkEeHVdyO/N3grndvb5DSqixbkBtv2RqsCJcVLM8XNb9k3CZxOOUIr9AbfHSdIrAEsnCQx2Ceep78o8B2Z/pub4VDkCpra/KzmOqJ+/1eOSeaZsjkv8u3I7SqppabBLyZvGxznes1MIK1sB392s7+hQ/e7ZvXN+QT9gdpqIbpYittuykzyL0SCCSTfzDbR8HP+tdVDVv3XnVVrL1BHuhmeoNArShSKv9IXvdDx0qIMrgOV2gM1+qD+bI+2qgyYIpb1M/VnSpD0Ssuqcj/B1lxRzoLR410ICl+MAFauO0yXI87DUEfjWqicHlrGCkITq/qonDdQlOSiq/DjY0f2EAwYH5r9ZhpQ55Gf2vbMBTo4qKpxw1Z/e8iR5SfL35IhAQQ4+AleawLMrSiowN+iCxuR2O8CpMQ+fOVzBYxTW5YAFXxokwlOU1DuzqQK/kw7+6LQanCgv2BsAqyFxzDq60ACudzzsK1EakQELlPbwHZ7Bdjw0qQPsC7y46mGL9ZJTZacUITWt6bpxJzxLpgGv5BX5zfqTbkJNRVt7rQ20mg2sd3xM10vol0cRFEqShH1qKichI5LdJIVZBv59pSPw0prAxYaHmjfA2uYmrq8q/5uPHx7BBw+NIVcoSB1mTib4XFbb+8YC6V7DSdyF60v4v75xBt2+j5Nzo/iPPvUoHpqdkKT1128L/PFN1VaUmmRbMY9Saw1nX3oOK3duS6nDL37mw3js+EPUocSl1Rb+z5fXQKN0YKSAf/DYFObGKmCg+1c3BP56OcyvTPcpnouz7D6uN6m1rb5Vkto09nQ1otQoz5Jzubyksk+OsaU9FHIC1LG+2FL5fW5fgH/vKLCvptqDEqtbA9VW691Auk2xPxIovNj0JCVczQl8ZFppjrNfkaieriopSAJN1ERnX5cBQmrArPRlomeALz0G+K1Sl/yPr3tYH6i+9MwU5SRV29PdrF5U+d1uBXh9QwUgmSpSYhVYmFDlW+74kmbXZdpX9bb1pHUwFvYRnp9rKUh+o7WQhOZEd7UHbIT9lqpzLBv7O9+LuuRyMh5S9NSxll9PqKfMdzLHJQ1LaTW+NzsuJfNjgBkafaVVbQZaiMa5uBdHnJaOxs1sCzrdvmUrYKtu7l2Iw03nahFyF91MXWdSmC6EhavR7Y/TKBMNEfV9XTAK9WdpeGw9YDlgtAOs6I/dyI8r6CM1ulskwZJTI75cicjZvpVuNAMp0m+XnauU/RWBCw7t4TICLG4pI2om1tHHJrv4xHw5EYWJBptC/zcsfWbe/+hIgFlH9B5pbNs+Zqv5hJ8jB/rfvSpwvuF439FAivm7aOn1doCXN5PvS4M4aG+inasm6FK6Wn3/4aIksOPvC/zB+Q1868qGNORm4iTl77/vAFZ9GYUilor9Fl555SVcurORuPb3PvY0XhVzSn/YSoWrL+DCa9sOAdtX981MYfzE01ikALaVCJNdD+rOth/N9XG9ley1rJ3JCsnnJHhFmVQS4NLVxkiclPzCU264irs4f7sssOwgxzlh+vC0h6Kjbkn77qsltaVpvb55R+CVzWTbkw5/esqlp6yM7cJYPuGHLt2IBgLjDvKZEZq4A2F/i3x1Gqx1TjQc43A9Fzg14OlqyMmGW9I2XYhjGI2sXSjtYgyHtYaNc25amvmZO4U7NcBvJhqSo4rln1xRktJ+ez+jJ2UG2GqFezfA6QoxaXTzZtdHL4UeXu/6GDiuEYZap3azg25eSaFs+UqMsrTST9KvHA73lYXT6DAYg0sYnvl9dyXAGy03DcooP67gCe2+j8vh6sfu7D93zMcsFQoc6cVVN418qBLI4BOuxBVPR7jz+9VzbtcoThwWxt2bObebPs423PmVgi6Wpf9uPDFE40+cMNQqjMtfPbeMr3E/2pF+5PR+9PJ0qo6nZrOJb37jr+VuiJ1OnnoMvcnDzvz8F7+Ea7cd1Ha+hPLCM9tRm8ybj81NwK+61Yd4OHCz4x6u9tUKzrYfK/jYHLjr7188GmB/3eW+A/zZzWDbh9h84sdnfHxyvzu/sZyPkqmyYtz4by66+xKjYX1yn7sv1XM+qin5pdHNw7Sgt7rpOuXcSXC52cnQmVTacaS9p5uHGfT7r4S1125IugrNKEnu3nz/oydlBthqicwAuwe5zABHHSUzwFFdZAZY1UVmgKM+YbtM7XQF/FacAacZXPvv95uWzgxwZoC3ayBbAUedIVsBR3WRrYCjushWwGZdKBU/O2UG+F7NPZAZ4BQDrOP68rK9RZR2bRgt3eoHUu9XCs1ZQgsEnQghr/cYHi9agXYHQkpBEnQhgEVIQyeeGUtdZ18FXY/pz5IeZtjBnsBNQwiCQMiHp4SEvi5seVg1QvFRPpECEXy6SSPLuL6tQG5BNgmJ9aLy8ZzqBGErD7jRRoyMJdVJcRDKQV5vR3Qu3+ATsz5OT3iS6M7nVEB2JgJgPO8meLbRj+QMeY2ygwujqux2+Rp9H1t9SgZCxpnV+XFV8sIq4SZIWIfncDpNlwQeHxfynoY8o47q9vSYj0M1TwI5v3FZBbvXScJH1I/uDWQsYZ14Xnd6Moe5Sg7zdU9CNUysPyECbHQDvLHaxu+dXZPvqdO+0QrKlTLmx8oYq1W2z/zazRauXr+Krc0tbGyuo8+KDNP0vgMYnT+KSrmMlijGzgkPVgJ4/TZuX3wd58++un1PfWQUpz/4PcjVxrF4cw2rrUjUe6S9hPLWTdTGpyAe/gDyJQXFsT9XMUDfp/KVARDxYq+F8tIFHnCiPH8cGJneftZsKZBaytQjfn2LQKGuCwFv7TpynU186ugEPn/6wDYDwLZ6bV1gqUeIkLrYUVsxwHxrABwdAX7iqIeJcGuW1fhHV308v+rhIzO8lts+t+W3c6lBqFFpmJttf6gi8NFZgbGSOmM1z1ll6EDPiwW713WhYKQ4GMVrkhAWCuYjhKhDfbLt2wMfHf6N/cAWWAnUd09PAFMljF8z2Qp2IdvrYjfjEs+uZQxwameHsJdurLT8WLf87qn+Nl7idnj0nZrjnAlnMU8zP132bAUcjRP2vzIDbNWI7wdyF9rs+MqdSH6GcqDWBtmm/kw3AX0PoQx2fhLL2jLIgN9C6dYS2iyGUQyYH0noW21qQStDpAciEpUMLk5ohx8USWl9LkyXCMJaktzN0Q1Ev5SKUnCz7Uky9VDNcCEQyti9vql0nSXtGBohusPwXZc6njS8NPAqKZeSlR6kDjSNjtZuJj3co0D/JvMR0iBq9yCCJrw2kvfw0TnI99YGj9dIDrek8fXQDKUgmR/fcLXn4fQ43Yqi8tFFhTlsDjz5DqRbdX5U9horAlda6t2WQrqZRDMJ2NttD09Pe5JO1aph1MvlG9bzHj4wLVBjgcK6IGn7pzeA765Rr5gkrdZT5iDpY7nt49HJvCRpqf/LxHciCU2qnAMzKWLdVsGgj2evbOLsalcaXi1VSYzp8Gge0/UyNpdv4drymqSt5aBZ9FARfWx1+zhw9BRaxbHtspPWZX/k8+kWpTWYOYgXWqtYfPF5HHroKEbnH0Ib6nyaLlfdVgsvv3EN4+tvYGN9FTRyTDPjo6gfPIniwQVJCdOAMUngqiTQ6Ap4K5fQWbmNtbaSNauX8picnkX54Ck8Ms1nRGAb+QAyDG8sbaK7ehO3NtvbX9z75mr40ScOoDY6hssttqeqP7ZVOU+63wOVo1Z6UV+iNOQn54CHR4E/vKYMvG6rR0cD/P2HgMNVIel37cbH2qdB5t8YD/lgXXsTAPJbZNKW1TDInEQSU2C/SfvuNSWsV4I0QJxAsE8S2NJ6z/IRHEdCtFkqg2uDLIQkoQnvjRcoN8pAJKou9Dii9Obj45Jp7Phbe1xi2ShTyomw1r6GUN/baDFOMEfPUtrqJLa3J0FCSL1skuOk0s1n2R4j5rip3ZMKBYuc2+4B7n9kW9B3qSCnCPDd73kgfpGmBa3pVReVOCyc12onSPh0yo9RcEBTM1w7vbIaSFcfV0rT7+VAT3F7lzwfNWbpn+lKVxpu6IX5fXeVcoTJ+6i17JIVZP4XNklmu5/1owfdwdtJsZpG1CwnpQVLZpgl4yLL7tJu3ugFeHE9vqrVtw2TN/zhA+5nXdgU+F8WuXuRbKuTI+kACzW4Xe2x1hngN1/bivlr6/KNdlawsp6knnn98NHjaORqiWbk4H1svOSUIa17AzRFklJmJjee/TJu3r6TyC9fKGHfx76AtgNqKy6/gTvXLjn70uc+9hHkR5IgVxD4+NZ3X8FGd5C47yPH9+PkQwed+fHbYQAKV2IAET3ZMK9/z3SAzx5wtz0NNF2YXImG2N6Z4u84GeXEZqc08vlNt4xrOJNP1YKecBDWLMcwulmOJw6tavpru7Tc+fs0CVq6S8koVY78KJOaVn97qQWdGeC7m8p3rR/wXith7SZA9jAtaPrKukhqHefXFGLQzThf8Z2CAbx+vRFgw6F/zG3WF1bddPNkIZ2MvLoV4I22e5D7dw65JyPKALvvOVkf8qwGXT+S9613ArzkcD3h+z4+5o67zGtfmHe7x5zfFPifF91d/vRoAD9Fu/mpcXdbrbQG+H/Objm/ssnuCm6vuQ3wiRMnsSKiEIg6A85Pjo4VYyIc+tp4wcdGCo288tyf4tKN24lyeIUS9n/sC06qvLzyBm5ddRvgv/OJZ+DXkmHk/CDAt7/7Eja4NLTSMAO82QlwLcUA1/OBil5lpY9OB/jMAXdf4tEC3aZ2aoBdbkfMYzDwKTLhzG+oAXYYN2ay11rQm91ge4fKLmQaOc7jrgtboeqHddNs0cc0z4AcaZhW9U63oN8KN6S7mzT1i7u5K+21i1K2BW21TGaAVYVkBjjqGJkBjuoiM8BRXWQGOKqLvTTAb5Ub0r0a4TR3pU6rgZ955gQmJvYutnBmgB8wA8x1Tt/hL/wgrIB//BDPwJKrk2wFHHXCPV8B531s+O5Vy8pzX8alG8kt6AdiBZxz737segXsB/Ac0Zq4BZ2tgFX/vF8r4LdzC3qYkX4rXJQyA2zV+GBAXDACrXhZgwb8t5v6U5CGi1gkiEFt5G0IIqRLeRbEoN6km81zYJ6lUNaRANGmHz/LKnkBSB73E1rLSr+XYekYwN7c6OPZFreFH5/0cGgkFz/bCQLc6agA9BogktUhhJRLfHFlgOlJAj/RAE6ohvAVd6IIfZkCIQSMnrvZRq5cRQuRspPUPy4InB4HDtR4lmpqIwdY60JpDlu60zL4+oD3eSib58BCYOnGNZy5egfzC6cRFKJtWer6Xlpp4WonDxQrMcGRGvoYdNtYmKkiyJnKUyqw/bFRktaWnm0Q4Llrm/j/rufQL43EztTGCoGEUqilHdftFhjLC0yQHi15sW1A1sXNrS7+/EobjQH1lqMOSH5pqjDA1toyrqy1Yj1zpgQU6mOoTM9jQ0Rlpz5zRXQxXS2gXKnE2rHq+dhstDBaLaGTU3CUTtXeFi48/w10mxsxIprn7ccOzWPs0Wdwq1vAlnFsO5rz0Vu7hcHSZaw1uzE6fHqkgv0PHcfxg/vR9aIzZ77voN/Hi+cvSxnPLUkEqTRdyeOjx2Zw6sg8lnpxFamqF+B2V6DRj8A33sP8CFlRTpSayqaG9Gg+kH3sc/sJHcW/HYJnh2oq6L3p1SDlIwdCehPU6QVgaqKTepZ9FygVLM12ar4aErX6nTSYudwV2BgkNdtrnpAgllSHM7ai2W8ZJ5rnzXb5lD5zHATT45Kp3WyPI5T03NbLNp5FuIzSnQQ67WcNfMJq6ts2y0fQk54IEyX3OOcqn66Ld4IW9L2ufjMDvBc19SbyIAKtO47UapXBFCJ6WFOJ+lqc+qPp04NcpB/NTk1DQiJyG+YKzw3zgvSj+hgIQGg3BlLX15u+JKI5JeDRVTmvXGyoJ90lCR2oe+hmo6UbadSpGMUf3mr5+I2LPu50VZn+3Yc9/PDhvAxUwAFnMzxD4/fNWLgt/q3dxx+/egtfOb8s7zkwXsUnHz2Caq0uxeI5QJTyyq2CcA1lK9ssw0pr28WGwdCfPDSJer0mBeml2054VjtVEHhmRqBe9GQACeo9c6CSzyoHmKsoV63lDvBXS5QyVPFk/+5BakcDneYmvvbVP8fv/cmX1Kx83wF84R/8FCYOHZVBE750fg2XORMBcGSyhiOz4wi8ArrtFl64tirrjmPzp49N4MjUiHTtavUFlkLVsNG8wPcfEJitALc2OviVb1/D8zfUee3s5AT27Z9Hv1CW9PqaQV8frxPWUW5cHIx03FlOmBZG6G5FfesBvn61g7MbyqqRsOX/mj5waKSAufEqSoWC7CN3bt3A9dsr6A8G8PodrG2qMuTyRRw+8Qh6tSmpd7y+sYW1lqKR50bKOHFgEiJXhN/r4KVrq+iE7kun9o1hbmJE5r1x7SJeeeF56R7FNFMvod3zMTM5jlOPPYZ9h4/Kv5MAv7QxwI22QHXQxM0b10UgkWoAACAASURBVNHt9eQEbSLXQ67fka43xfoYVkrT9K+T7/mxh6cwNlKVxuvCagfnKfJMoGnQQa27hq1WB4/vH8HnHz+E+Yma7EtS1a3jyT7INr8ZgnxSCxmciNGFBkrru6a+g62ewPktId3caJSfmvIwXVF9aSQXSIPKtiYVP1NV2txMpNTJOvHtV7sCq2HbE2Y7UGWgkdDXyCCiuRJmW/H90r0kVNtrfWYa9jttISUq6cEwW/YwUlKF2OgwljUnnp50OaK2tHYzjNPNUX67GZdYf82+coViYuyIkVD72s6P17VBbvQElrpq8VDPqYAoynuBQFg0zpljY1p+Oz0DzlbAqp8OS+9aCOvelbDSNVJZcS4qkYLzA2P1Z1YwV3t2BBxe58qWCoYuWnpxI8AZh14x73t1uYdvrSabkOT1L36w4CQ+v/zabfzKc9djfqo6h3/66UcwNx6PqCM/xkDgV56/gSuhUTGfeGLfOMYnklAOf3NqJDDcm6K72LEIUd10wDej176Dc3/8f6DbVQbHTCe/8HM4h9nE35nfbK2IO62k/vGJ6RpOHJxxynx2l67hL8/ddur3Pnb6CTRDlx7zgVzlH5RVlPw8Nrea+M5Sz5nfRw/VUC4lpSjX1tfx3Le/JXdg7DQ1fwSrIklE83fzI0XcaCTfNx/0Ubv1Mra2VDAIM334ydM48fj7to2HvsZB9ZuvvoGLt9eSnYl+wiPjaHtJ+c35iarUt7aLzvz+0UIBT86P/f/svQmUJNdZJvpF7mtl7VVdvW/V3Wp1t1Yb27Iky9jGNhjLbDbbDMMwj+294Rh4wGFmmBmYw3nnzHsww3u8YYDHdobBgDGbF/Aiy0bWrpZaaqmreq/urn3JqsysXCPine/ejIrIiBtZlalSq9WOe45BXZHxx43/3rj/vf///d/vkUdj/tVZY2Nj6PzBWFzSkKoA8RFTuolV2Kb7+gykWHHB1ZhHX6jzXOdtu5OGp3KY9aveiBqox425O6fYuocc8MzzdfdP5AnX1f1rl3XRaBiI+GQG+KGReQhgY9EXd/NHMLfv31a5pQMDrJhkzT8FLmiXbrZugLeXC1oQAIS9sTqiElmcQMUFPbGq4+yaOr731EwN5xRAW7qOf+vtkZayYZYK/ubMDfzh6VnlbPm59xxBXy7jucZ0pd984jqWnL7U5q8ODWWR6+9XytuX1DdOie4fzJbUqGhj4glc+8c/Vsrb8cj3YyazT3mN5f1IxOFuu3MJ3LF3RHnP9NXLePmGYgcD4MTxO7EGr8FMhUzsyar3pvP5Is4ue40iH/5tBzKoOlz2VofacUEPDe/AQljN3cz849mygkC6UUX86nOoNrxo5Ie/5T7sPnxMqYvnXpnAa/Neo82NRjo3IE7w7jaQiaOg0BF/92/vTWM44zXaXNC/NKPmbj6U1jGWVs91oocbmvraOwfVBpOVoIo+yPudCR1ZRZlB9t3fAKtZoXhPO7CWXwqjH5885d3uXNDBCdjfYFtXghOwHhhgTobAANsfS2CAbV0EBtjWRWCAffKufOzMm5mG1M70qVKUXm9aUnAC7voE7E/A4F8NyT8vz48IgLFanoBV/rXXVgy8piizx1f6xnQNk4pDC0/A//VtEWUFlr86M40/OT2jnIM/+54j6FecgOmC/i/f6PwEvCdaxXrIe4rkw/1OwPrEE7jucwIeeeQHMJfZqz4BxyCYfdxtVzaKO/aNQlMgs69fuYyz0+oT8PHxcRSjWY88Aod4AlaFH2aXV/FaXuXwBN6/L426AEm1tmKhgG984wml92NgeBRLYbV7n3F0i8GqRWK9gtjV51ATAKLW9tDb78Ge8eNK/T175hzOLaoqOWlI9QxgXfFaA5kYCvDmLPMBv3xPGqMsXOxqJKXiCbioyO0eT+sY9TkBj8QM6IoxpPi3DxitAL7mM+n65QlYZRpI55n1IcTwI7CwWKpUCuy23J9qHlF+N/J4n9+61K08v3d2y+vUBf1mpyG1M8LOFKXtSEsKDLCPAbaKTltxDutjsIEGKk5Yi7JSCnUiDC3gAl3KTr5YIlAIwiCqkzwFrBdstTnSKa4SbAX0x1j4XF5jny4WdFwukuqQACcb8UkZl8hGtU5uZQOzZXt1HM8Cj+4NC4pEGmKLYYryrhZ1nC8Ai6vreOy1KSwUJAchGa/ef+dejA3kRFF09sEi72KxdYJgWIt3emkNlxZti398JIP9Qz2IRcJNWsAmgKNaRukLv42VV5/B8B33YcdHfgqRhIxlEuFKXRAou1wzMdUsZUidhxsVVCtlmPlZ5J/+O5RnLjWVHMWuR74PoX2nBO3mtUW75m4mFsHxXf2IRCNYzBcxMbe2odvM/KuIX34W2XQSOx/4DmT2HBXXuKjMLa7gxkoRml7DYp73SHduaGUa/Y//FoyFq8i+54dhfvsvboQNomYDRJeykPpAIoQk+QSFPB3zrzyF6xcmEM72I7/rPiDejKU36uitL8Oo17BrqB9DYztBABtbYfoSrr30NNbX11FJ9KIUabr/yaAWqsGsVxFJZbHcsw9GNLnxXqQLJFUpwbxOt3uytID0wjmY1RKqoRiKho1U7k1ExVwdHhrE0VP3ItMjXduVWh3nr1zD1cU1QUXpDDMkolFkMhkYWlhwlTvR0m/f1YMjIxkxn792fX3jPs6bO4eS6EnEcCAL3NUfEvOebali4sUVE0tVIBYmdavNPfzIsI6HRyTw78UVDUt1qSPeSnarvjg5l4FrZTumS3CiKOOpAcd7TEEXarFNkiGKyHuOasLFsZ6NSIAWPzXyeVsxU6sWMO/JRUnLaPfPCZpyZ0nQxWx9s07A5gYw02AfCEr0k+egj20aX+s9nPL4jeg63eCdr0sSUNrKO+1c54SuHWQzVlaIiheb65xbXqcG+FZ1QW98ZM3/2I60pMAAu7TaaKIVWo2n/IjUE842cM6Pz0lYLiewfTLiB0uaX0Z2uQBEHKkP9YYhFs7nVyAR0E1ADxdAgnzYh8sFYE7Uo20iGzUDmglMFkxMlcMtp59cWEdD1/GR3SHs72EaklzxiFCly5TxO1LPzVTslCLmGk8v5JFfr+DoriHoYfu00hM2RD+ulzVMrXMzIeXReIYbVUyvFHBsJAstGt+gbiTXMj/wC4//LZb/6dMtTEqju/Zg50Pfhf0PfVSkIlWapx/2JqaZuJDXUSqXBeeySFUielhrID5/Ho2la+g58TDyMTsxnu9bWS9hJBNHNpNy0CmaSBg1TE5OInT2S1iZuoBaQ6KR08kEdh05gfTbPoL5YgPXHQCmvihgllcR+sf/Cv3Fz2F1wfYQ7DjxTkS/91eRuuMBUfii1iw6wNQkbnJCpG187XlMzdhsU73ZNMKjh4GB3dArJeQrdp7P7t4khnI9KF56EdeuXka5Jq8lomFksjmsx3uR0upYLNh8yrlUHKHcMMyB/WJurDhO+oNxDeVyGcnZV7C+NIP1qoxBc+PVk06jpMWRTsSwVLLBYf3pBA7s24fY4BiuzK9ges0OnnNjQaOaSGdRNqMbsV9yCzM9JRGP4oH9/YjE7ZQnoodn1mq4UtQxmElg3UFvSYrUI1kTq3UNF4p28Q1RCzdqYm8K+L79RD3b3w4N2lwZmFk3MZZq/XboRWJa3YWCJop5OLmgdyZMnOqTRlek2DS/HYtjvZcb3GhroRQCI4leZjGJGospWKds8rgLVDOQiYVaTpbOlEXxXTi+bX73gu/d0FCVVVnkhCb3PHnWBe9061qxmTzn8qVas+S6Zac6brYuyTXOm/Lkt8loJ8/KGLld0pACA+zWwBvw73Zc0DfLJfTUnD+VIiuUrCjAI1wYH5sxsS5Ow63tg6MG7h5U0/ORMs+Pb5d5xyouWaanTPnQTe5OGC2neGdPnv43H0N+yVso/sgHPo59H/0p5WheWyrgggJhzR+PZhMoGF7wzQALRSS9Lk7es/LFP8ClF59SPqv/O34Gy5qCa/nSk6j/1ieU9+z+hU+heOqjymuRpz+FhUWZztXSYingwH3KewZWr2BpZkp5bXB4RGxEPC0SR/TQ20RKi7v1LpxF/upEZ/JCYaR2HREpQe6Wy6SxCvvE7bz+vSdGEE963c700vjxdrMKl4rPm3J/5U4Dh3PqeSs41hUZBVcKBl7Iq++5t9cf3TyeNZTARBYv2DCULmUQmd3j46r2A1cx9U7m93tbWjOQVCC2+ct2fPNKYW+Aq7pdH9q5sYMTsN8IBeUIPZrZbirKdhRtfjGZp+Z1nFlVozrp7rXyFp2db2eAP7xDx6kBtTwWT1Cl/FC2qJrjcIlbz2Ne4dWme9itwP1JAwVFDI+/e/bffgzLi14DfOwDn8Cej/6kcpbOLBdwLu8l8eePx3JJrCo2I+0McPHLf4iJF55UG7+P/AyW4DXAkUtPouFjgPf9wp9h9dSjSnnxZ/8cs/Pe90UbAzxUuIKFG2oDPDI6ijnWoHS3NgZ4cPFVLF45p+zf6OgoZlXy2hjgvmwaK6baAH/i1AgicbUBvubD250O6SgpNlHs8H+408BBHwO8UlEXurhSNPDCip8B1kXlJlXzLarRxgDviOnI+XBLd2OAU5qOlE//2q0j3RngzkGk7fqwnVSUgQva32BbV25bFHRggO3BDwyw1EVggO05ERhgWxeBAbZ1sZ0G+FZFQbvNYrvCDVtFRwcxYJdWt98Ad46WfmrewJlV9S6+nQv6KzMyvuRuH9ph4K4BHxf0qoHZZs1c933duKD3JnSUFGXsKPuZf/MxrChc0Mfe/wnseVR9Ap5eKmwwR7n7N9qTQEHBc9zuBLz6pT/AhdN+Luj/DcuaN9e5nQHe+wufwpqPCzr6zJ9jfqGzE/DA2hUsTatPwEPDI1jo0AXdP38Wy1NqF/Tw8IgA0HlaKIzkziNw4Pc2ftKbzSCvqMjEH3z85AiiiU5PwGpOZ8r793caONSpC7rNCfi+XjXpBZ+13S5oVoCyavo69dvOBU13fMpCpbkGpZ2Lt7sTcOfr0s1yQd/KKGi3rlWFGzpBRwcG2KVRFRd0KwChFRFI0FRFNwU9I//nRkurOFL5cVqlUZnv7wRPsDD6tRJwJg9RiNyuQUvuRxPX1iUphzNuxpPqUIwgLIK3QlhwkE70Rw2MJoD3jgI9cSd3s4mlYg3/eKWEXf1pAZqyGguik0eW75WLtfJEE6B1edVAlSAWLYzqRtzRRKKSx/KNq9i/bx/0FJG0cjMQRQPrNy7hpU/9FxgL17CSt1mVevsHED38LTj+kR9Btn/QUWrRxHDMRMio48W5Kkg6YsHdEpqB1MIkjJVppO58CKsRm1WpR6tBX7iGkd404oNjqMJG+yb1Mi69chr6q1/F4vSUYPFii0Uj6EklUB87ifDht2HZ4YZm7ePwyjVof/9/oDrxFIqrdmrSjqN3I/eJX0P45LcKykELMEf9pYx1rJx7DpHlKSyt2ujrXDqJ3O5xYPgA8qt5rDlK9JHPuVbXkViYRH5xDmRrEifwkCbK6JE8IpYbEIhhq2UTMcRyQzCHDgoOcIKPrDZgFFF/9SuI19exqiXAucVGMqS+ngyq4QTisRgWSzZyixShifVFmIkemLvuxIqjlOGOTAx7RwdQbIRxcaUCy3Zza7cnF8MdO/uwKxtrwQBEzAYWr17A5fkV9B46hXLYdvGTS1vAtUJAoU4+bTlfOEsJmnpoxMS7hzVkiPJqosM5ZmeWTUysAu8ahmCYshprZRNRfHpZw2SB89amhR2NmziVk2QZzqwBPotAp3QEGEuRKcqWRxAWmSOpNQGwc+QsxcjdHDfREw97QFhrNQLLJL0kudmtRgNGUDSBj5L73L7GNYZIa2YapKKt6wipUksN+S06OdEtkJPQmYMul/+Wa5aXo94GTam4pe0sDrc857Pc6Ot2XNV83u0KwvLb+HSCjg4MsEuLFhOW0+iqJ5xMG1p3xEijNAwh8sV6UwEseeS5ZRqSZVi1ZhoSv1Py3c5ViYeUbaFs4HpJfrBcdOdqjqIIGisLAT3kfk7ZHLPLFeDzNwxhjFk0IR61OXD3pgyczElAx2NXCvjMeWkYuEw9uD+HAwMZQVF5tUQCfLl4kcv4iOAyBlhf9OvzuigGwcbUqLF0CKbewOKVCZx75Uyz5xruuesUdu4/BH19DS8//g+4dql5CmvUMFSZQ2VtCfHRg1g88BCQkKfOHUMDuOuOcaTTGYwlyT9rpY6YeHGujOdmq6iuzKH41F+hMPGsfFYsiT3f+ZMwdp9CpLyC62eeQaMmUcL9g0M4etf90FI9WF1ewiuXb8h7TBO5pQmEr59FqFFBpV5Hsdw0QuEoBt/xHagNHkS8Ucby1XOCV5ktmp9C70t/g/rKDEbe8wmkPv6rCEXjYgEmk1mxpqNRr2FtaR5LK3n5LEPHQHEK9dVF9AyMInT03dCyA7Ib1XXoy9dRKK4jGothidSSzUW+Z+0aogvngWoJ9XIJa2uWEdcwMLYH9XgW8UwO+dxe1KNSf5wd/XEN1XoNsemzWPzqnwIN+V6Z4V1IjB4QKUt6JCFrQDefNZCMCvrRaK2IwuSzqOblqZ16G3zno6j378H+kT6M798j0srE3FwtYWJmFaWGgd39GQz05TY2nyMxHTEi7JcX8MSXPo+pyxflUKUyOPX+7xL9SMfI860JbmXxLFKxEmkMYH/axJ6MnZZzokfHnoyGhQrwexeAp5ak4SKH+k8fNnFnr+R7HkpoomgC29Wiia/P0RDydGsKDAQfRYBvvqJjpa6J9Km1mp36x43J0awBMqcRW+VMQ2JaEwursH/85oaTdg6xlWLIzIZr68Bi06PE55EjnB4Z9sq5jtDYkh+efeA64qxrzVxj9oFtsWoXnKCM4Zgh0doueW408lazODY3rFJnTupLay2zENMW97WY7obTiG8UbugoZPlWiQHLEfK2wAD7aWYLf98qFeVy2YChKMTOj45FC1SI6XYFsv2uMSPmL6+YqCn4hQ+nDYw2iendr/bZawauNQntnddY+u/FizeU1JHHd+SQ6FGTO+i1Gq62FugRYknobzI9p+AlasiZZawKRK+XFnH48EnM+xBJ/Mr3vQexmBfF/MITj+HTv/dbckVwtZG3fxBzhhocNHDgOJaq3ntY27b60heVs2Lo2P1YMBREIaaJdzz8XtRyOz33rRcKeG3yvPJ9D+3agXpuTPmsyvx1zKlcwcUVaM/95UYBD+fN/ScfwnL/uJKgZegbv4uFS2e9z4omEbvngyLP2t36Vi5i5cJLyv59zy/+ZyTGDnqu0WjzBN9wVD+yfjT/4tdw+vF/UMp7/w/+OLSB3Z5rHNYHhtSuW3pdvjRvb06dN//u29Qof8pjHjxz2d2NZC+TPiQ2LGk4mvbeQ3n0iFj5806ZS6xgVuB52tvIez7EnbmrUd6lgoG6As3NjbmsDuZtJB7pS6hDSu1c1W8VIo7AAG9uqDra0Wwu7tb5xdYNsA4j5EVUtjfAusPF2vrOeS5kijq/BKn++WUTdYUBPprRMcwSLYr2xRs6LiqQynRrPjt5HQUrqdZx79HRHNI5tQGuV2u4ZqefbtxFA2w8/3dYW5enRGfLNtZQmJ9W9m/HHfdjxsdg/urHHxYnS3c788SX8anf/b/V8u57L2Y0NTdy/75jWG6SNzhvTqxMoXJaVlVyt9Gjd2PW9Baf4O/e/aFHsW4RYzhuLBcLeHViUinv6P69KKcGldfqS9PK4glYX0XomT8XdJ/uNnTXw1joG1f3/Z9+G7NXFP2IJhC/98Oikpa79a9cwPIFy4PRevX7f/n/QnhEVkhyNp5Yi3VjI3fbeW3uhcfw4te/pOzfB3/wf4ExsEd57eFhdXrRRF7H4wvquf7f79dxz5D6mkhXUrBkEUsxUVAbsXcO+LNu+XFB0wC/VlAvi0cyOoZ8vlNmIagMsNhk+jA4tjfA3aCb/ePB7cBV/kxYrX24XdOQlBMYQHAC9tPMFv4eGODAAHOaBAbY/lgCA2zrIjDAti4CA6w2KN+UBnh8fPwXAXxM07SGaZoT2Wz2XxUKhe8H8NNk1QNwJRqN/ujZs2cVrMC2IrdugDt3QReqBC+pXVHLVcZ0vdd4Av7MlCys7W674zr29pAa0nvtC9cNXFGQZbASzvMXplsKo1tyj+7oRbpJQ+h+VqlUxlyzbqrzmjgBn/4C1ore0kvp2ipKi2pu6aEDx7AQ85YPpOxf/Oi7kM160cjPff0xfOYP/h8RV3W3wbvfi8WI+gQ8fOiEEu0bX72O6ul/UMs7eCcWWW1Iodt3fvBjqEa9p+Pi4iwmLlwEol4k8MGddEHv8IQm6BasLFzHvApyvDqH0POfFvWMPe973/uxmFVXfxp8+g+xeP5F7+oQiSN+1wdQVcjrXb6A/EX1Cfi7f/k3kRzx8mwTqFeoscSm9/R54/nH8co/0b3vPW1/4Id+Euj3uvAFFmHYAHmh3G0yb+DxBbUL+v+938D9Q+rvarFiKEtvLqwbOFdQy3vXgIERhQuaffIzwItlExNtXNCsR6w60JI4xGLscr5ziLgCHxc048B9PuUXbwcX9FslDcn3PKfX8SPvGEdvr83Q5/fb2wKEdeTIkXeZpvnbk5OT9xAAOD4+/mkADGj9y1AodPe5c+eWxsfH/zuA1yYnJ3+j3UHYCcKyqCedVG4b1HAaQKZAgrCsJSYOXRTzlmAPu5A2nyeACxr5mSGMqd50KZcbJvjxcv0l4pL3h62anawxyt2DAby2auKZZbnQMfZ2brkueJh3JTV8eE8IR3rlIl2oAxOrBuYqMlR6w0ExWao2sFTWsd4wUCuvY2ZFcjfzPU+M9aEnm0Y8rAl0q0XAUavVUMgvY7FQQzYZQyWWBSJRcR95m0nJV6830Fi4gulzL8qHmiYGIg00qmWwyHllvYBiswat1qhisDyL9ZVFpMYOYOnAgzBScqISgZskyCcUwr0HduCdJ8YFKpXI12cuTOPZK4vQS3lUX/06Cuefl8MYiWHw8CmUoxmkkkmsGMRcSz3t3jmGE3fdg3AyK0BRT01ObdTW5QLGgQvV11G//CLWLtnGZ6gng/VaHalcP/KZHahHJHK3d2gUO++4F2Yyh2xUE65DMUcMA+XH/xiLj39K9LVxx/uwdughqViCsGqLqBbX0NM3gMi+u6D1yI2HWS6isXIDa8V1gUYWJCDchJkmel79PKIv/i2M2rqgmcxnxoQ8LRLDoYc/ivCuO0Sh+hvzy8g3AWSxcAgD2YRAr8enX8Xs538XqMnAfTaVRCwSgRGOAEP7sNKzb4NbdSDcQK26jrhRRen6BMrLEoSVHN2LA9/x4zBGD2NHUsMgi7I35+ZSqYGrRQNVw8RQIoRsIiI2F5JLexnXlkuIVFZRmngG67OStzvbN4Bv+cCjSIzsERSskhFKbh53Jg0cTEsqRqrNmn+cTgT2cE4S5HRmBbhQksa2J2Liu3ebGEsDo3Hgzj4bjMjNLnmlGWnhULfU4xUbOE3Ewq+ShrVZe5pz9ViPCdJSElxNEFa0+b6sOZyKSAQ5mwVycha8J6BqqQbk67J/Ic3EWNxEKirlZRzynBST5NF2gi/7Ijr6uBiQua1mbiDR+ZdM2BA6ItYsHbFBZ1vhZxZzTrEuqdY5N+e9m0rXuocfkROEpcoY6dQF/VZKQ5KzwW6Vcgnff+8B7Nq121Nb2/1b/vu2MMCc68ePH0+dPXtWWJTDhw//digUumqa5vHJyckf5t/Gx8ffC+CXJicnv1WlCOtvqjQkFbJv4/dNXmd+YOo0JG+KAD8WGl5yMBP5rDt2/CKVImQKQ8wd8Ma22TSxWjPx+5MGnlzQcaNsn3ppCO/p13DPYAhztYiQaTXyMC9XdFxcNTFTtvmK+eH0hhqi4MBYXxplR4F5cjDzvmsLeSytrWNFENfKRsMVT6aQyaZF6ojFf8xrvXoBq2efQCg/g8WCjdhi6kRPVEPj6ssw8zPIr65uyMv19kHbdzcixx5Esa6jQph4sx0czODQ7jFcXiljcskOQHNt6lmfRePS80CqF4yfW41E/4lMD+581yNIDYyi7jidxfQKXrl0DaXSOhbWGxsbJ8FlXFtG7eUvI9SoYqVo953FGuIDOzHw0MeBvjFUHDnOTPFqXD2D/N/+Bm68+pwwFGxckPoOnED93u+SRRGKdt+ZNpQb3Q3kRrC6VkCB5a6arT8Rhr4yg+iT/wMrF16ERNdyIdfQP7YXsYd/BP33fxsKjrQrpmSxwMJqqYy6FmnyHEuBvUYJjef+BuFLzyBfKKHelMeZMzi6E9WRI4hFY1h0vG8yGka6sY7c8W9B4sg7UHTU9OX79kd1MM1mqtQ6l8YSGiJ6BYv5Am44JiB5sTOlWRzojWHk0HFUw3ZsPx2SxuRID5CIOFPuAL4XCywQO1ds8o0L3cJEsc6NH3CMDgoHEJJzdneSc7RZ8MSBmyAnNcOwJJpyf1eFmkzzIYraiR4mMptYJ1aX4saDRshqHGumEtKjxQ2x9Z0Kj0ZDft89sVauatJacq6xqBNlOeUxRYyIbBprfvvOdEbKWq6yYEtr/yiPhjgj96wtVJqbpyGp1yWB6BeFGTqTp7rH2hR8M6UhdeJ+5ly6XQywvWgfPHgoHA4/BuC3NU3rn5iY+HlePHbs2J26rv/l5OSkLHvj024WEQd3888tyVw8d8tEjJb8Qef1f/1kDc8qquRxIfvg7kiLMbfuu7FWx+kVFZ4SONEXQsn0uji5wFy8el0stu42nEujnrBzb53XUy9/Fjemrii1m534MgprtvG1fpS54wEUxx9W3jM62O/LVd17/Xnki1709f7xYxh/4NuU8q5fuYSz03YesvNHAy/9FZaWvNzNmT3HMPCdP6OUp/3Vv8eVr3xKeW3oo5/EgqEoyReJAyNeVDGFDL7wZ1h8+u+V8k7+2uex2ut1O7PYRn51baNYhfPm3OlPY+HpzyrljZx6EHOOnHHrR6FYAoe/48dQ8Em/DgAAIABJREFUceRQW9fiZh0LCkQ5r6fWF3GDLhhXo9360IldLZsh6yfjGYnkV7VGw0DeYXydv7mjRw3WGowaGPaRJ9zHjrzclmdy86TIauCJc5ePO3q16gOg4kmT3iuFPG4gmOurau3cx6xEpQpRiZxuNe35tpctvFlEHG9lFPQ3tQE+cuTISdM06X7+CQD33xoGWI1KbGeAs2Ed8aga1fkzT9bwjI8B/tDuCBqK+BkXxdPLagN8si+EYqcGuDcj8lBVLfPK50QlH1Xrmfgy1jo0wDsG+325qvtuPI8VRfpTOwN848olvLKNBjj0mf+Ay1/+M+X7Dj/6s5jXFalMbQzw0Ok/w8JTagN86j99DvmcF43czgD3vvhXmPeRN3rXg5j1gtfRzgAnUBcVh1StnQH+8IldygyA8YyOUR+EsN4wsLKtBlgnKYR6I8V0OgUGo70B1pWbCvEAH4MeoefJ1wD7I5jpxWLpR3fr3gB3g5b2v2c7qShpgNNZNZ5DOXi30B+FAT45uqX4L7s9NNTTVUZRVze9kXo6dOjQ3ZqmfUrTtB+cnJx85siRIz8I4IMTExM/wOceOnTo/eFw+GcnJiY+0K4fhmGYflWPtrP/NMDPL6kgKpJUwIeTHZ98po6nFrwLIE/AH94TVVbEmS428MKSuhj83QMRScrgatztXp66gbzD/Wz9ZLQ3g6qPAe559Qu42iRecMvsPf8V5PNNggrHxeydD6BwSH0C3jkyKGobq9rAzAtYWrVrEFu/OXDkGA6/S30Cnrl2BWeuLSnlDb38GSwoqCOze4+h/yPqE3Dkb/4jLn7xfyrljX7Xz2G2rjietDHAIy/9Oea+8bdKeXf/+hewnPWCoWiAV9fWlPm9/Wc+g9lv/J1S3tg9D2F63TuXhAH+yL9qcbdbAlKhBmbX1XMpW1nG1Kr3SM0T8Lef3K0s7HEkC4yo07dFIaIl74FadOXOHOCIVmy8H0sEDimcDvwBiWMUh1JxL78A1VuRdIMMWarGw77i8xA/5QKp2qbQZcwYc6ctX1O/bzsD3Okz3qjfdxoD/s+fe9HM9qqzMd6oPm6X3NLaKv7523ajr29zAJaYJ10am1vKAJ88eTJdqVReMAzjYxcuXBAMBMePHx9tNBpPm6Z57+Tk5OL4+PifmKb5xPnz5/9bO2XXag0zqjh9yhqZsramu7VzHfm5bRjXeWGZH2lnLuif/kYNLyg8qO1c0FNrNQFeUbU7ekNKV6N0Qd8Ai5e722BPGnpS7YKOn/lsS71f573Zc19GoeB1QafveBdK4+9R9m+wvx+LTVCL+we5689h1RG/tK7vPXwUR9/9QaW8KxcvYGLO2wf+mKfF/LLKBX206YJWjP1f/jtc/+pfKJ/V95FPYgVea6A1DbBqge577k+x8uzn1GP1q59DqU91Am6IeLKKYCPzwl9i+Rm1vMGTD2JRkRNAA3zoO36shcbT6lDMqCnv4fVEaQkzRa9A6YLercx3ZRWiHX4uaN1AXlHtis/yc0EPRA2MdOOC9ql6lA0b2NmFC7rdCTgX63wd8XVB80TtI68bl3G7da6dvHbXOjUywQl48+3ALWWAx8fHfwzAr5um+bLVdU3TmANB+OUnSeWqadorExMTZPxXb9+bN+q6LuagG/Vn72dtIAR/SEq59QZBGq1ADTcq0S2P99L9N1N2ci2bII9wMiLRoMI2N91ipiGBL398ycS5FV38t4Wkzmo1NOavYEekhpN3HkWjidoVr1Qr4+mLM6iE0zCTPSg2S7/FNROZiImqERKpTDUzvCEvEzIEknsuX8TyaqGlZN1gqIrKwjX0je4CBnahaEpENBGkPVET+eUVRC89iaWZaxvcwz3JGKLxJKqLN5CYOYvF2SYlJF0wew5Cu/+7ENlxEOtLcxuIXoLaBvr7Ue3bjUR1DctrBUHZx0YPQbRWQHX2KhJGFYsON/RAJolGJIHxu9+OHXsPoBqSLmBi1c3laTz71S8gMrQXa7G+DS7jbCyERDItKBjjk49j4cbVjS+gP5sWRBi9930QmTvehUJYph9RXqpewNTLTyH+9J+hdPkllNflUT2dySK5/xSKx94veIyXCuWN01B/KiaR2Jl+aJl+QYnIxv87xIL1Rgipf/p9lM5+DaVmalcqnUbq0H2oP/xj2HXgKErh1MbGrSeso9bQUahUYTQaWN6wfyYGtArWrl1AcuLLqExfRLEk4+XJRAJ7jt+L3Nu/HYsXX8HVa9c3eLH7sxlk992BzNG3IRaJOuQBWb2I2alLSPb0AdkBFA2JHSAS/miPhoNpHc9fW8XZxepGPJoI6Xt2pHHHWA5zFQ1Ljs0UCSUOZiCoGpkFYNWepm7J3bwro+HVPPnP7awBFizYnQJ2poDVWiuFI40eqSD3ZyDk2oAqE5zvBDdxnraCsAxoBO4T78j/7zgihwnCCpsCkZx0cLbz2yU1JSlluYEWC4a1MW8CrQi2YvaCyGNoXhOgrjABjnLEbSS15KNul3VBNDfXGac8vi/lsW+dyrOe5bfOycwP6Rlz01w6eaLtdU7qwSuPNJYWdnxzw8JfvFXSkOLxuKeGdCeFGPiutx0Ia2tD7P8rOw1JF6ddtzG2JiNPL0Q7VhwoWwIsUmFTIBOdqUt8msUXKxbvkI1yZFoS2XDoYiJ/biJqc+BaKT3LVeCr8xB5i9YHsVBq4PJqHbXVBVx7+ZkNvuJIJIL3vetbMLRjFFPzeTw+Ob3B3JhMxDGyYydCsSSqBgs62PuoHUlgMBEBD/+rDbtoA3e2xfwKllbWgMI8lqdsqsV4Oosdx++HlhkQvL5FR65ybG4SjcsvQGvUkDcYm27Grwwd/XMvw1y5IVC25Qd+FFq06ZOrriOxeBH1ahnhgd2o5XZsDFS0nIexOgdUilidu456tRm8NE30Rxow6lWEozEsNUiUK9+LaUnveMc7EU8mceXFJ/Hqs09syEsN7URy/0mEM/0oxftQj8iTKsEzuQtfhX7xWYT1GhbXbJBXOJHF4Q//M4SG92NtYRrXHbHu5NJFpF77IrRQGMWj70OlvwmWMk30hWpiI0REtLPwATdXg2N7oCd6ECZfddTmU45fP4PE138PZr2C0qnvRHnk2Ebfd42OIDcwLD7+6XUWqZDvy7mZRRXVahXG6gIWZ65t3BMrLaDnxmkkY1Hsfs/3IDt+78Y9KxfO4Nq5M4hwU3DsQYSSdny/L2qgXq9jfXEGly9ObtCAJlNpjO4/gt5cFvcNRbCPvtpmH16dK+KpqTUMpCJ4+GAfepNyfEnARQrIfB3gfDskcthlF0X6liG/ncM9wK6MHRbh9/HyigzLHMtpIgWMjfsY5s8z3WixArzqyOvNhk28d8TEjhTTiXivIw+Xp13aTPbXmWkghBpi+nADnIk67zGRCZsiDYlpXlVn7rOFfnelBlkpSvzW+F7c6Fnv25rm05rK45d14ZbHNCTLtrWXR2Sz7cFzoq/91iW5ZllnFXf/nPLcaGmZ4uVc5zo9Ab8V0pCsdKNczhur3mopwsAAK+zw1ok4OqeibAdUuLSqo6YAWTDO9DuTzpQPu9PnXz6Np158RbmbGN1/GLM1eTptaaEQxg4cRVlRMnBvWkM4qriH+Yinv4JL1+yTqy1Tw64HH0UJ3vsiM69h4bya3OHg/Q9iOWkbWGcf6fYrKOLS4fmLWDz3nPp9M3HMFhWQXsb+itexvOaNFSfGDkO/5yPKsEL/S5/G7NlmwQfXEwff8REsNrzIcfL3imVOEaYY0spYWPWSlfDnY/c8jEVFGUSjXoO+eE0aCVfbs3MMhYQs6uBuiakXMLPsdbOTX/tbH34QumKelWsNXC1734myzUvPYmrei/wjUPDffvfD0CLe+1gFScURLRadmJoektfIw6xCKpdrOkpN7437fR+f1TFRVIOrPjluICHcSa7m43LmrzKajoQPCKMdurk3xo2191H1ug5VWIu/9HPd+vE28x6iw/3Q3O3WmO64oP2BV9/MTFidop2VH2pwAlZ8l9ZWsbkDdOYFOn+9XN5eA3x5TW/dVTcf1s4AX3j5NJ7swgDvPHgU64rFrJ0Bzp/+Ci76GODdDz6KosIAR2fPYX5STfB/6G0PYykxopyXJFhYa1Zjcv4gsnAJC6+pjeKObAIzBQWkt40BTtIA3/udyj4MnPkrzLzyjPKanwH2A/IIoxOqYD5vlyV0Ct5573uwAC+zltmoCwOsipm0M8DJqRcwrTDAdJnRAKuQ8pW6jisK7vDNDPC/+5730Nfr0VMM/rznI3FDmS5HIe8aVPMSs39FRe1n3tPOAP/sEUNUBOvEAGdD/lkIfga4Hbq50fBHX3djgNthTgID7GfqtvfvgQHeXn1uSHuzTsCBAbYHNDDAUheBAbbnRGCAbV0EBvgNWvw7EBsY4A6U1clPt2qA8xUDDUXeIOPAfqhEvw+H4ZmpkoGy4d2pL5dN/OlVKE+EM5cm8NhTz28wJtnvqcliAooTYTgSxdj+cRQVz9qZ0hCLRj1uNDoFZl5+GjNXGP9tbeFIDHve/e3I614XdH/hCqZeeUHEEN3tHY98AOca3lQDPiul6SgrSCBGy9O4cuZplKtepG3/0DCWF+a9Q62F0KMXsTbLsoitLTG4E8apDwMpL6I7e/4xLD33RQaFW28KRdD77u9FXlH9qTeVAPmRSxWvK/yBsSSenJzaADttCNVCGLnvW7FieHNTEqYOrM1gzapV7OjJ/n17kQ+rkeh9SxO4dM1bhSqbTuPdD7wDuoK7mSexC4WQ57QtAEfXXsXs9HWP/ujS/okPvRPDWW+uc5JMVo5a2dbNFrWks56udY21p981RJCU9zuo1g2BMXBnDVDe0wsGzqx57yFb1s8f9eFsB+vWNtnmXG/WQ7pHH8KOELnPFf2LwUBWuKA7y5LwXxO6y7q4mfIsfIx7Yrj70GkM+K1AxBEY4E6sage/pQG2AA0EKwjEqoP71QIm8Fq10URCNj86LjoJhzfOjXJUySvXDazrEt3Y0E0UdEnJJ4xywcB8VeYarlSBs2tygSRKdCRuit/VKyU8+9Jr+MbL50Q/B8d2Y3T8LpRjOSQaJVyZmkKpLKkQ9+0cQ7pvUJRRDBkGppsFALis7UyFBVECQWQEg5HCka/VqNWwtl7GXElHTl/DyqWzqKzJeOCR4ycxvG8cRiQuABuTa7pYILmQvnskjFw8BLNexcTEJJ48LWPBh3cO49EH70euvw+lmo4v3jBwoSgBRGmzBkNvCHRyNhZGAVEBaqIH8WO7Q9ibDYmC98+dPY+/ffIlcU8824v+AyewGulBziihMPUqikvSEOdGdiEysFswfWWKM1g8/WUBhhJc1TETtco6IvEkIgfvQ/7Qw+JZjGZyA5Wvm8hVl1F44R9QbPJE5+54B5J3PoxStAfpRgELUxehN+oCDPXeu49i99ioiAFfvT6Nr744IdDT+/uT+KX33wkWulhcLeL/e/wM/v60JCoZ2LkPuf3HUQynkQnpmCvWhAHnEn7PSAJDaRplE4tLy3hq8rqQl4hFcfLQXmjJrEAfL5R1zDaZLseSwIEeotlD0It5PPPyq1hZKwqjcN8d49ixcwyhcEQAgqwYO+fSWELOJc6DqyXgQrNOLt3ImqELPuJMYw2zlydRLslY+uCO3QjlhmCGIjgxEMEDuzOCrpEyBqNNNCwkJeNq03W8XDFxsWBipqJhT8rEqX5N0D+yHevRcSCtCTrXmsFi9U3jaJoQsXUBiDRRZtZBUx4zEFhasWJqKNdNnF7RMFuV8r59TMf7RzVhFEt1U/xdviOpICUFJr8xAqosPAQ3zwRaCWCTBVpqIoHjMATaWHz3TQS0tVNNa4Yjb98GLG11HbFiqZbxVvEp8526lecEdTnXsm7lWf2zkNReNHcTGd5cNwMD7G+AAhS0SzfkgnZC8J0Tn//tRDDz35yMTEmIhDREXbtmJx+rM5bMia/rJoo6k+sdfM9NUMZMGTiXh5cgwzBwtZl+ZKVssA9c9NaWl/DkXAONzHBLdRWeJhvra4jHEyiEiPS1d+i5sIG6YYi+rznia1yUyfvLHNulSgOsyGS1dEhHpraKPcP9qCR5gnVwUjN2ppnYnWGhAmdc0ESjkEfOLGPv2DCMkA3a4bNeXarhK9fKWKrQENiNFHunhhJ490433N9EcXUV//PlBZFOZKVW8U7yAcdLSzD1BlaQhrNuUm+oDu21xxCZm8SCKx47NLYHoQd+AI1EDiTHt1pcM5BcnUIoFEUhM9ZSlzkX1rEjXMZdewZhxlxsEtUSDkSKeHB/P2Ix2zvAGOKLVxfwm6/pKMYHWuQRfMbT1/7eGGquikVRvYLZ/LrguXZ6Bxh7jEJHOgJEwmE0HOMRRwP55SVkM2k0Yq3VpfgswTke1Vrq+XI8GrqB5xd1rNWxkapFfXCTYBQWBSPTktk6l3alNHx8PIWDOTcbmwlW9nlsDpha11B2IO+52Xtg0MSPHoLgTXaeHvntFBomdENrSQ2iYaTBulGm8bTTk8R4mdIgf8sgsCfTKo91sMmnrPq2+S1ynohCEI40JAFaIrJcEON4+8fvPhYJC3S7szkNlJXKs5V1RLACONJ/LJnt1hHrgKBal2TqpIs/urnGSKhL6zVnupFbntOIu3Exm/XvrZaGpEovcpvQTtON/ExwYIBdmtl+Lmg1ipApGSvk1FW4rF5Z1jHpg+qcL+tYVpQFZI7sYzNmS2qR9Wq5iI7VhholOhQ1sKAguuDHWFrLtxgjS97B3jhSaTU90KmcPz/unT0sXed1Fb40V8ZfX1YDqH7ieErp4mRffvelFUzbdQ42RjJh1rBWUssbnfwcZlm1SdFGP/7LWA55KTa5XXDY5JY7P7g3iZ60mnrph/bqYHEDd7taMPC/PqOWeHd/CNGoGo0MU8dizSuPGh2K23nhzucxT9i5uXJe259SI4tpWJ6YqYk8V3dLm1XMMyFV0X7lvjQGxam9tTHV7i+maFC9Y//P9uv4xH713GzHtXxxVT3PDqQMnBxQc0uzaIeqdKIwjj7czSziQE+Oqm0/uKo7qke/xX37Y8Xd9a/TE/CbmYbULr3IredO0o0CA+yngcAABwa4OQcCAywVERhge1EIDLCti3YI6+3mgk69SVzQ2xXb3aK5CYg43IoKTsBSI8EJ2J4ZwQnY1kVwArZ1EZyAt2acOz0Bv5kgrMAAb3Xr8Ab9rhsu6G44Usn6Q/YrlQv65WUD55tAGPdr3iipSSoISPnKLEFhXncZK7pIliqvS9GP9IK0ecXCqogDutu+XAzZDF3QXnlHs4aHno33M07NYueGwgX98kIFf3Ox3BKvtZ75L46lsDunqCgEE7/z0ipmy15G5aRZR2m9rCTrHzj3eSxNnlbOnh0f/2UsKVzQyZAs7K4i/3//3hT60qr+AZ/YQ2SsdzyuFw3862fqysIZrE6ViKld0HQprijcuKQvZc3aKvEErsaauyUF4p0/25lQu3EZA35ito6CIhc7ZVZFLWVV++V7MxjNeNHwumniL64yt9urC+rohw+q0cMsBKIKWTDWe6lAchqvvH0pQ4C7VGhkP3kiHsp4r6JSA+tz53zQzdRTxB0AbirGb02wKCc7RUu3yxcW35cilNXNukRd+KGbu+WWDjmpt7awbgcGeHMl3VJc0Jt3d+u/WKwYZiZEcIX9ETtRiZSkQjdbE9e6ZhVn54fhh3IkeT4R0FbaBWUQKfr8koZqE31dbxosGkSCs55fIeeuBH1ZgBteO7cKXCwA6WgIS6KGryaKl/fHTBimhmjIEKAVi9yenLpGo4apfEUgdfVQdAOMQ6KE/RkTIUPHmfkyLqwZAs7B5W4woaGixbAzGxWxMYudiIXXCcBa0zUcybJguoZa00ATWJSLmoLaj8hdolatejHUzWurwIXlCmYKNcw1S92xaHlvMgItlsSHdoawM02kuFxww6AuTJxeNDC7Vsb1AmN7UuLBnhBODMZRrFRxZrqAa0S6kZYyAhzsT+LgYArTT3wW5196Fitrkplq91A/Hn3vO/Ge970fv322iifndFhlkGkQP344IYrAf/piBRNr0uATEXtqIIIP7COtZwhzFQgeZ3GNXNomEA1reGTEFDqzNlqVuoFX14BvzBs4lzcw1az0RN0dyGo41kf0uYaVml2IntzcvXEgomlYqEgUca1pbPenDHzbGEFMwFdmgMvrsg8EZxHpTdrGmmFgpaZtIJ/ZPyKhuSnb2URAW3OpL2JgNEF8goEnFjg2hMVpQt7hHg33DYVExaPT8zUxH9lYXOBEfxQP7k5hLCGBihZPOdNzOHuur4dwZsXE1bJMJSLYa3fSxKGshveOGDjWqyHZJMwg7zmR0NwAWAhoS380iL1RGokQXlszsSy4tAWpJNIhE/0JDbuShuBvtlKJnHzFhbopeao3ONZJS9msQN/kdJYUtNIos5G7meNtsU9RHsFe67oG0kFGNZs8xJkl0Q7d7LeOqLIuJFum/zpirW5bWZe2u38WOMvK8HBS8FrP6hSEFRjgze3VbWuAFyryq2Psh2VKucF1Ihl5zQ8R2A5F6I+MBIo1pnpomFizF1A5BLI4AxfjZxY15B2gGKKUeeohT/QTiyHBs2u1noguFmuuZzxBWJtjftxcwEo1A9Or61gnOqbZeuIR7MolsTMTwoFsCBagm+80sVTGq4s1NLQwSoht7LZDGhfQMFLREMo6kc/2tCCZxoE0NwBANh4SHLpWY3pL3dAwUzFbwGb0CiyslsAc61A8ATNsA3p2xE08PGKK8Xgxr0n0eNNVvrpewUqphv25KI4OJRFqvjCRr6enljFXqmN8pAcDPTbbVGHuOs4/9hkc6Evg5/7592B4wM5J/uyVCj59sYq7BiP4vsMphJsEvoyN/sm5Es4sG3hwZxzHWEWg2Zhuc6NEo8ECAa3ehmNZA3f1QhQ2eCFP0yMbT4bnVxqYK5s4nAthLGOffOnRWGvuAogQpjG3WqFmiLS0E73Ao/tCsnBHk2v5y9M6XljWxNxNOBigKI/Gh4h2gqss/mjeRw/JcBwYjAM70vZYMe3pqbmGKIhwrC+E8ZzcHLCVag18/XpZpPi8e2cSw46TLzcTvTFT4OBrDo8Hv6yJVR2XihrGkiZ2pm3ec6a+PTwkuZs5l5xobhpCwbMeAUZTdv8o79Kajislvq+J3oQtjyoZjhugSjkfnIcwSxfim9FaT8sm+Y+FPTehuRi+UjS0IaDcQAsHAEc03eSAV6OR5bccdslzbuzdWRLt0c1yP7ed6xJ76EU327zOW+2fam0MXND22uf+rwAF7dKIZYD5Z35wKRWPbLO4gvuDskT5c676owj/+qqOeQXClR/7l2fVXNDt6AMPpXXkFdR9JL2fWsijqPAiPrIrjmNDanTzM7M1cXJTtTv6Iy2pLNZvTvboOJRTI1yniv7Uh4KwX+GuHI0b6JWlZDzteFaHGVI/q9KgC957H0/q37VXvZdkjnLZh3uYKGaVW5cG7qW8Wh77rnSnMi815M9zbKWSuF/44SEd473q9/3sNR03Kt5rdQO4WlTPpfv7dOzOqOWx2pIfkpobVctL4+wjkfdRBUUlf1NrGFhTjAevfWSn2q3bH9ExzF2FotHL4ccTfTBtIKpwE68z/97HNW/qusf4bnzbPmjpgIrSHhg3IKtTA7yd1ZC2klLknFLblV7kb3JbrwQGODDAGxoIDLA9GQIDbOsiMMC2LgIuaFsXb1Qxhu1KQ+okpchpBrYjvSgwwFvVQGCAAwOsmCuBAQ4MsGoJCQzwG2+AtysGfLMRzd2YnOAE3MYAZ0PkhPUiKq1Yr6pSkjN24x4QxnzcMSL+hnirZ8hnu+p1k5Kt6JVVE2fy3mt3ZHU8NhfaKOpuPY/hwnv7DVwqee8ZSxgwyiV8cdrrg/6h8SQGMnElOvfKWh1fm21lquLzdiVN3D8cxUuKvj80qGMkGWqN5zUhMzHNwFfmW2PXlMfYMYFaX1/w9v3t/azVSiBZq5uX/7q7V0dFUWKR4LC+mKnU7QNDBh4cbmUis3QouYfteK31d7rwZ9dJr6jg7a4YuFgigM7rhn5bn4FrZc2jW9J2Egh1teyV1xuR9WeXBNCotb1vxMAelo901TrnXHpuwcCLivEYiJpYbajn0kfGdMQjHA+vbhkjvrLu1QXHKRUylcjsEz26CCMwnuts/JefPILGPrjDxLoC3dwbNjCQaI2FW9/O5YLaDU638N60qXRBVxuGJxZOeYwrlxs6khFHXW7rBUxJ06pCX5OqMh1tjTVvzBldXeGJ1LMEW6YijrrDzZskiNNfnmod2XxdIkWod575rUvsih+Zh1zn/OTp4jkWXqBTF3RggDc35bc1CCtiGgLwQeCLNdGseK9VwNqN+rMLYtvgIOsjsVCYNhe0BGTwY19v6AKdTFBMsWbibB6YrkqgCVN6+uOCoE6kXfzJZQ2rDQ17kiY+OGYKHl2iMZ+YB/7oijRmp/qAwxlJGE90NJHR1ysSqPODew0cz0mU6mvLNfz6C2VMl03sy4TwQ0dSGM5EBNiFJRCnmgaBCwsxSCTWN3QdLyzpeCUPAfD6l4dCuGcgJEBKBBL99XUNCzVNcAE/MmqiNy7Rs0R7LzfZtsbiBvamIWg7CQb7xiLw9LIsVP7IkIGDWYn4nFk38adXNGG0aDge3W1iOCXRs7PrwJPL8n2JeD1AbFUoJIBz603uYWmUDexOEUinCdaxr81rmKtpYO14xhpJmUlMroR4Nxcm04DGP7m4hzlWVV1HtQk20wwTq3VNILoFYKrOtLLm2MPEXFWiffclDbxjkNzWmig4f6lo4pU1GctknH4sSTSNhnrDxPmChsW65NI+0WMKekY2yn55VQLPhmMm7uojolz+jkYw0WTbqtZ1VAz5O4LCzuSBG5WQGKtHhg3sFhg071z60FgTqW2aWK0BN6pSFwRmDcQMkZ5Tb3BDB8xVQwKjtDewYHKeAAAgAElEQVRJgyP1xL5fWZebi8GYiQeGTAwl5fteLwEv5SWH+WDUwKBASUt55J3mXCci+9tGDRzJyW+OvM5zRHo30dLZJj8zNUqVMLWLIKSViiGAbYxBa4YBCa6X/RuKGeiJyrF3opHd/MdkkLMMPrEC5CEnl3bYJK+7iUTTEFs87/x2CMazgGx8FlO9SFXJicR54syEsFJ6ZJaE/d2XmmNlZSukIhriEYm+lqlKqnWEBSTk97v5uiT13M26JA2vLvpgoa+doC8aZdk92V//dU7qIjDA/gY1OAG7dLNebZg8CThRk+05UvnByJOZmiNVGhS3PPLPrjVkEQZnLjA/rPkyFxPu9lt3q9y10xAPxCmv9dpC2cDX5psfneOdaFB7wibeNgikXYCyakPHs/MN9CejtgGy7jUMXFuH4O51ImZpAMOGjhP9IWRc8qgHclUzNcNK87DEEX3NYgE0HC25zybfV6aGUO/ORnkk78/xHtf78tpCpblJaslHNsE0sjtyrShgcboxDBQb5KoOb6C8redxsyLpcb39q9SZ+mPl2dp7T+qCG4Xr60Q+t/adHNIncpKT2P2+RA5z7CWy2ZbHlBuCg5LUn/ukIuYYxNi35o4T2S4LOEgUumNvzOIFDQPDSS7uW59LXGBpMD3gJWGgTRDM5e4f9TecMLE/o3lyY4tVaWwFmtyZr2rKvh/LATkXuI45tvmqCUPBjSxy1MlTTU+DSx4R2GMp9VyyDJv7O2WB+2tlFj3xyqMHhfPWw/NukEfdRCwcFptH97yVGU3e756bFWbGub97Tr5U2BDpe52sI35oaf69m3VpM3lcx9xrj8UF7cdj/WalIQUu6M1P0rfcL24FJiymJancqeI0VFEXOudO/oszaoTr3Tkd+3vUCNIbRUPpTqWH6WrJEDmu7nYwrYsUElUr1wwUfNCld2QNr2EBT5ZqnmDKJ9LbD4FbrBtK9DURx+M5NVpaoHMj6r6LU5TCRUeDeW1d7fQhIlrlPmbfPzyqLuxe14FVH3JpblT80NKDUR3wQXr7oaUzYX3jhOweL7+51DzbeEr/ifFo6Cgq0PW8dlfOQEbBm8y5dHHNECdLd9ud1LE3qx4PnnB1Rek/yliuqMsC9jKPOaUe+3Z0icx1V+md7vJd6e3jgq41ZK68qrFwSiqm1kW7vvstom9VLujABb25WbxtXdCBAZaDHxhg+yMIDLCti8AA27rohooyMMCbG5etpCFtJb3oZqcUbf5m3l8ELmiXTgIDHBhg92cSGODAAKsW18AA21rZzmIMm6UhdZJedDNTigID3I0GXPfU6w0zonBRdotKlCAFrwuLCMg8mY4U1wRJAN1Ubn5X0xRxMZWrjPEoPy5oun6P5tTyrq+rOXoZj5wqmUrCCZIb7EpLkJG7FWtqggPGS49m1e8rEMes+6qQR9IGiXp2o2lNFGqktfTqdjjm874AshHDEw8V72BRDyrGo1xnPLw1Fm6997WigcvCPe3t34fHGCP09s80DQHYsuganTpk7FhyOrt1a2IoxsL0KncoNWcSk+oZD7pQEyIm75JnSqYtFaJXoFuh5u3meBR01ViZOJEzlaX7GFe8XDCVhB1E5e/Pds7dvFJT94/c5juSnaOHia1QEYoQYLWT4D93oLcNQtgCXKm+e0FCwvms4G4mPSzj/25e53byusm62FxeZ2jpzdDXYYtKbovr82Yu6LdCbHeLrxpUQ3IryjRNU6L85Ee3FVQiQRMWatD66CQlm0Q9WqhBC5VIFCUNrCD3V/DPcjklurliSEQmG2XQYC/UwsiFibq0OKQlTR9J49bqGibXNNxYl7VhCXDJRCSick/KxN6UzWdLIEtFxKPCILiL6E+5AJnIRUzsSkvu4WeXaIglNSBpMQ9liXCWSFAWRbcYpsjPzNYwQ4LpqGxgY3EnFzTlkZ+XKOUNA9MsoM5C7ewr+YwJPqPxYZrSUBzYnQnh/KqOqyVtg7lI8gtL0AzTgoQum4hZpu70JYh0NpEls2MTVCVxuJJPmn+Ph+x4tIj98iJRn0SrWkCsZkF2/pv1B5Yq3JDI/jFWy0Ltg4kQXsvreG1V20jHIdr33gETp/rDAlBH1jHJYy3TdsgNTSATNzhEtVvydiSBE30hwV9NukYL2EUE7mjSxGgqDILtSHcp54WJGIjU1QQQiLqVHNESLZ4Jy2eR8tI5lyBSXPieYQH6qhp2/6Q8Sd9I/ZYlX6Mw8JRH5D2N37QDeEZdCMRwOIzRhNQLvwknn3LNkDzWVlEQyuNYHewhl7Ik57TAR9b3omkhMM5PfIO1USWQTnwPppxL4n05XkwR0kxhwJJhUkMCkbA0Zs7vz8picD7LkkceclEDuSmPAKyRpCZSjyz0sSXP3V8V8tkCfTnXEYmilmMlNmDiWcYGutswJPp4K+vIZmjpTtclSx675ESOu7M43Ihoi2bTota0xt4qPBF258ptYp0CA7y5+b5tY8A0wGKhNmTagJrDVXKkulGOlqF0fpyWKimLp94Kc/8ES67dNvhn3by0JiB4f5kaUm49gdHokpQ+HOJJoFXe9ZKB82vyDBVynMD47yMZEtVDAEGcJ06mjPB/LN5AlLBzg848y0sF5hYDhxzgJsaJpwoGZivknG49tQl5OnNwgd1ZmWZkNRr8fBWigIGbcrI3omMkoYlTUYro52ZjasoLS+ZG2olTfxZqNxeFB5mdDelIhDWYogMOxDENfoR5nfACr6zTsLjFPlXyz/mKLnJbSfovTpbNxkWVudyJMPDIjpDYIFltvW5iucp8TxN9cVu3lDdT0lFsaDjSo2GAKUnNRppuck7TOO53cHPzMlOMFsrylBqPtsrj5ofjwv4xL9Wef+QcN0RK2MYGw3qWTrS0KdKamNLkHHuOFemRmQ7nRL0LjEBBzs14WNvgy6ZIymF+OFOk3HzKq1WmikFwPnPz4mxOYn/nKZDzqNDg/ORweNHcFZ19ABIupHdC05EMy420U569qfbyKVvfGzdpfa7+OVMQVfJU3729jrRyLVspiNyYZFjQwZXP7TRmrTra/nXJndJkPc/mr/d6AJxFHdS6sLmvtzsNKTgBq+rQtXxKb91/WAaYb7DdKMK1qhrBzGf58c9y9//8Eo2sd8+TDZM8QY2a5KmMp2V34/LFsoDypNnahmM6+ln2RdF46nanYoh+m8Czi4bSlTkY0zHoI29iRcecon+U+e1jJEDxulOvFAy8sKJGpA4TIezDPcycUJXrliemHqb1KJpm+HNL+6GluSnq85Hnx6DER/eEdcQU40jDx9Omyl3ZDinfG9ahCqPwMMt8aJU8GP4I61xYjRynPKKbVSUmh2I6BnzGngQ3cUehCKf6/b455s36cXO3424mKlpVMrDbb7tdmUG/qnvdxIr9+OTfiHWpe13IHGB3e71c0MEJeHP7edufgN+IiR4YYHtiBQbY1kVggG1dBAZY6iIwwDlfKxScgIMTsIj5dloNKTDAgQFWrSqBAQ4MsHtefDMbYHcakjvl6K2QXrT5GVb+IkhDcmnK7YLulHPVCfhwihbxw5ohaALdKEcCf8j5TLpHdyNYioCXiwpeZxZPl/iGVocEY3D8gP9pMSRZixyN9ziL21uXKOFUThcxT9IrtrQmwIV0eQS2OJuhG7ixDiUZxUBUR85RGH3jWQQFNUyczrNYfKs88iI/MExuX1ec3ATm1nVB17hQa9UT3/fuPhPTFYKbWuVlI5JrebFJhens+86kIWga3aUKKYFAqpW6qy6tPJrYBdxdg8WxYsU8q7C88zKBVNSrG+nNvxD0pnKTkqqT4DgVUp50qSxGL0FXdiOYbSRBoJt3LhEsxXipqtTjQNRAqSGpNZ2Nc1NgDRRobtI15olPqHifdTijCwS4G+nNeUnQFeOenrkkgIveurTsD1nbyg2tpQ6v6KdgkJJAPLdrnSEBot4jitCEGzTpfGdfzvYmLkSlC7+YLeX6yWuHHn6ryuP4EWtAXAB59Nk6jQE705D8Uo5u9fQiz0Lu84fAALsUY6Gg+Wd+aBYwxI3QJErRec3JMct7nShCIk25kDIOaaE4LTAJaw4TQEL5pMQj6pQgLS58RJ1ak5ixu5fzmjAKCU0WGufCTGgWlz8LLU0kLVNPKI/pM2fzJl7IhwUwZl/KlHyzBMqA6UzSeO9IGDjWA/TEQwJVXCQXb7UJ+iLqtAlGCjX5cUlUL5iXmghuvi9BPJeLwEo9BKbSWAhkhppJD0h0KjcLSU2Cotg/AoZIXfnKalggTR8aNrErRUAPBICLxeMbWkggwimfmxc2ps+8uiaN97EeHQfSmogpkr5wvgJcLhH0ZWI8I2OyAnnaMLBYBdYaIcEFvT9tIBOTuijV5PtSH30RXaC1GYOmvLU6hMFvIvM2dOHkHhbF2y30NCkcNQKuJLCGXNoEZjF+zkXVyT3sHHvnXCK3NCkzifQVz3Ug5aOsUR2S8tg/IqzJz8xm8R/TmPMadWbNJRaM59hbYzVfkcaWaTsDMUnbyf5Z8rhvY3lgotEJ5BPztlmknu9KeeQ/5viSw/xySRPpNf0xyfWdjvL7MMXYWcjilrlvSOR0WvBY2/zHFgLXQto6gVlUA9H3Akmt8TuQc8l6XwIcBYNcs380ApY8+3uWm1Mrdun8Tp1G2b2RdmZGuI2jZWDd371TnkxjtEFfrchsec2JHlb3T9KRutcey8irrrVbl5zv4V7nnP11ZnSo5FlgVK436811jshuYgDJ2x0mpL6D5owB307uZpUKAgPs0kqjoZvKikU+u/N2iEpOXC7gwnC456BhIBfz8u1SHhdgHjQ9nLW6gTPLwLqbs5YfL1gdx8uBS3lXCiamy1bakv3CNCsne01RVccNpqjVWQEHoqhDS2ue1tMRLyKVi9m1ounl6G32TxRhaKaGWDLF+zZoKL0nR8qbKxtYbYQ8+uPiwdMmjajbo8C8YmJD3KAxkRYGA71xL38vDRZRtjRSbnnkMr5R8epPnoa5QfFyX/M0vCsJgeR2y6szzY2bINepkv2j0SRK2H3qpfES6VOK/nFzweYGrrWbS9QfkdtxVvBxzU3qb7XeiqCX+wCZ6sPNn4ev2JB958bDPZdYeIHyPCf5pjzOJbc8Cz2syjTgWIlNpALdzI0bX0elW8mN3MrzbhkvaRy9Y+Xv0ZJcy6owlB+a220ond+VXEes9MetocOlwW817M7vykoDcucjt+vfZvKsjYKz73xOoU4+d/U6N5Ryuc02McaBAd58t9LRjmZzcbfOL7abCWu5rMNQ8PfyE2OZPPfiLD9S//jyS0s6CgouXk7xgxk1KnGqoGOqrEY3PzhooD/pdSEyzeRCQY1w5Sk27cNZe71AUg01UplVmlTuO56yelyFHawZwZzYkqHuu3TBK4guuJApCDUoM83UFJ+++yFcBRNW2WfKcwH0eda+pD8Ps9+MX6saqCkINfj7npCOWLPykft+v5hhu7nkd41jz7QpFVqap86ML1+xz3iYwBLzqRQkInHoyNIFpGjt0bnqZ3WL6PW7z29OsLvbj272/+5vdS7o5YoOQ1OP41AiOAH7fe/BCdilmcAAS4UEBtieGIEBtnURGGBbF4EBtnURGODuDpG3lQE+ceJEX7Va/R0A756cnNxx9OjRfYZhnDNN80mHen7l/PnzX/NTV2CAAwPsnhuBAQ4MsGq9CAxwYIC7M7v2XbeVAR4fH/+cpmmfNk3z1xwG+LHJycn9W1VUo9Ew/eI6lKHid5VgC29siW5B1k9VxYAZI+yNsUaq14XaTt6reVMAsdzIZwKk9mWh5B6eWzcEtaEbkUqID4un98e9sS8Cwi6v2+Aup/4IAlPFgPm+s+s2vaLzHsZeD2a8cUX+htSSGVGSuFUXLfJcXiwCgcjapXI1u4FuG/1ognNUKGUr5qhyaRONTNpNVTw8ohHZ7o1RMz68P03gk8K97xO3Yz8F4YSulkfmLncMXXgr2shr6DpCPnPTCUByjpWgPa0rYt4goI5j743zOsE57rBKW3kwkPYZe7/+tXvf9jFbu3i8833bjX07eRLMpRpfCfRSzaX2MVZDyHPrz2KqUj9LHQPm+7VbR9qNvZNqsnVedL7OESMxRDqyDhrTkHr6BoQubqeUI5UKbisDfPLkyXStVhsyDOPJbg2wFwXtRU1awBAVitACcthUbSGxqFYEcIq8h5Lyj2kYDF86+WKdH7sbKOGUx7jobIUpKFIeZbBgAT+coz0actFmLNgwBNUikYiLFROvrZoidYXGm+jXg1lgX7aVx5oLh4U0JQqXxofhQPadmwbKywgWIxsFTX1YKFnWq12p6shXtWYs00RP2MS+rIZsVBPUmiR3krqwkZLcDLTyz0ou7ZCQJykPBVd1EwRGjmMaAqc8k35z9ssy1g70MPmPLdStRMbKxc4G0Umj4kSDOlG8xDk5uYe5oWD60FAyDMZtl2qQ79sEFg3Gm6hy0lltIOq3NpcqDUnXaBVtd6Y3ObmM2yFSOV+YcsTUNqYLccNkGW/nvPWTx26z4D1RzE0o8cZc4nMtJLGbG9mJ/HX2j+lXHKu6Y+xjTZSsWp7Fo25zI7vHSvW9uJHE7F87Xnb/768dWlpyaVsb9a3OJX/0tS3POTZugGfrerO1ueS3jlg80VwL/NDXznXORlirx57fkljniFDnpoQbkOY6FyNaroP2k//n/zB/5METyOUkGcftknJ02xtgvmDT7ew0wM8D+AcAezRNezkSifz82bNni37zwcoD3gzd7CRnd58erAXX+XeZViO5h90nsG5Qk6wr+sqKifkqPBWBeFI60WuiN9bKMcs+X1zTRc7k8b6QQFo7m1VEoe7KISUqmwhXphK5OWtJAyiKGLhOArSFS2WJ9N6R4q7efhLlURc0oCoOXNUOnPJ4ko+FeWJv5SumPKYmGS4ubT6RGwPqnM9y55365Vpa6GHmxepuhHATcTyc8Op2QSTtahhKtr5vN3OJY1USSdwyVcfZDUueap7RoNQM6lfz0I3Sc5Ek4ljhabCq6rhPbdWG5C+30qq8JyK7cMBWvgPOW6badSrPaUSdz3EbZXcf/E9zrUbUum8zefydH1paNR7dy5NzyT0e3cwleRpu/75+c8m50dqKblXrXKd5wL/0R180f+Qd4+jt7evAbL81f3pbnYDdBvj48eOZer3+8WKx+KfT09OV8fHx39c0bWFiYuJ/38wAW5NW5UaS1zpnwuoGkSqMCPMvFUDCV5Z1XCipkYcPDero8+HitU6abh204xcWFXR80L5+1xLQkfFFuLZDfHaOcM1XdTRc5B3W+/nxAfvpgfetVnUPGciGvLCBiMK17DdON3su+QFi6LcgqcZW+HvdhtaP9c0PJdx+rqvHl8/sTt72zqV2fe+GC7obeTdzLrVDerfv+9bmUjcG+F+885vDAA8N9XTkHbC+y65uuhl7FOcJ2P28w4cPf1jTtJ+ZnJx831YM8M3o7+t5xmurwMSaWsJ7hoFcvDPpdHsykV7VOOCyaNzWG7ObGN+7Ga1QZ3lC9ZP6Yyyv11kvinWIEn6q1sdye+pMq84e8gb9muxUotSlq8nUN3UthjeoK4HYQAMdM2H9x089bv70+06gr+/2PwF3ujmxplOHy9nNm4VOAzw+Pv5eAD86OTn5A7Qfhw8f/g0AtfPnz/+CX4/eyGpIwQnY1no3J6R2OZ7BCdjWbXACds6zzr0p3ZxY23lTupEXnICDE3A7q3nLGeCjR48O6Lr+VU3TeObab5rmZCgUOkPmQtM07wewbprmVCwW+/E3Iwa8Wdyum1gLC4hfKUqqRGcbiJq4f0BSD3oRqa0Fv533+cWAyZjF4uRk4HJzGZNqkbHkdQX3cCYkuZb94lidMA+xn+3iWASOMbbt4R5+PTFgH3l8JxWXsbvYu6Xb1xe389cf5asYpLYzBuwsxt7JXGoXX+8GgeumSnTrdjvnkhOY5fw+bCCkmjFLNR63Vgy487nU6bqkWuc6PeUFMeDND6y3nAHevMtb+8V2o6DfaLQhJ3yhZmKyoIGA1Xv6NQzFSe6vNQ2WxWm9deTqBt8uNJCvONYE7nABsriMaZRtPmCtyWMNVBEC2Y2YecA4qRMJayFmN+Os7Ra5Sh5r9p3cw24O5deLgm4nz0otcaJJrXd8M5GrNgqagDc7hWkrKGh+LXIcZJzP7z22ioJuN/ZuI7+V/r2euWQZShWq2rrm7BP/1soZfeuhoHVdjpN3rGSBC3d2xnavS+3khfwKJfssyZ/8b39j/vgjdwUgrDYm67Y1wNudB9xdLmPn+XasSkTEsSrvVKZrdJ67Kfh2FcFOcvHSwKjQtFwIWHTBm8vYLl/RJpl3zjm38XZea5e7WakbKDS8XNUWSX+necCUxyIFKi7jVJjIYnXuJvvfSS6oPOX7j303c6nbPOB26OFO59L25+3evLnU7iQvT4c3Jw/4VphL3c7NsCzZtuX27LNnzF27dvuWe92yoLfAD287FPTr1fl2M2FtN1raL77HGd7XFcJ1uxGp/vL8Yrjbzd/LqiwlHz7qbrigmTqzxvxGRUuFDKREXrS33er8vduBcHW7aP2yBrpDN7/5cynggrZHuFsMS6cu6MnJq+Y3QwoSNRsYYNe6GRhgWyFv1UUzMMCvf9H0AxV1A56TLlxJfOJu3cq7WZu5wAC//rkUGGD/Y2FggAMDrHSTvpUXzcAAv/5FMzDAUoeBAX79cykwwIEB3rJnul7XTVUMczNUp5K9qVlD2K++MDul4j/2YyXarO4mczzViGPGzLysOu0RrjaFolN5W0Fzq2KE3SNIO6/hynq2jAH7xWxTipJ+7djIKI8xYNN9gjOJDmcM2MsGtRm7GXW6XSxH3dZw9UO4bre8zb4dlS44NxuGKWr+ujE8N3MuteeWVtcD3qx/qrVCfled1wNu3z9ZG/lm1ANuN5c6jQEHLujNzVVHQfXNxd06v5AoaJsGzp3+sBX+WblztonfWxGkEpVoLb7ea5Jj1glAsuRZho0nPBJmmE1u6ahmCr5ni2zCcs856fvayWuPcLV14UwDciJIJbey/bE7jY+oWS/AKhKY5dTtZvKshbk9IrW1f9aCY1HiWUXCnXzKlMtnWwt761jZaVpOQ0QqTCeXMeWRaIzx3632r91cco6BaqxUKFaVPFtnkkt7s7nUbuwtPUmEq438faPnEqlFSQrT0EKImAZSTR7rmzGX5Dcm39eaS+3Q0p3MJfd3r0LKv56xf6Pkvd51pFMUdGCAN7eHt7UBtl7fWqTdiF7rI1EBTvx2pM4PtVN56tMSUKwbiIc0xCKtw8H++SE0/U4jsn/+CFyLGECFbnYuLM6p4yTmd5+i/eWx734nC39+XD95BFBVDVMUkHCzebbXhTTQ7velcSA38nbJ22wuqcZ+u+eSJc8P3Xyz5hLHg3TaFUVOeTqkIx72ehqsuc6+q6oIdTqXLLezvzw1sr3dXLJOttvx3b9RY6+a669nbjrnUuCCDlzQm28pmr94KzFhdYtK3O74nj8gxp+jt10t1e0G2HTD37v9tV7bIXpvHq94d2Pv37/tBFdxI7dEPlF6dlyNueXZm8Qr3g1zVTsmrFt/LnU3N7c6lwIDHBjgwAA7NLDVD6f1NNtNSkhggJ3elFuhsEd3Yx8YYGscb8/NXGCAt2wgtvmHAQrapdDgBKyurtQ+V9ePbzcwwIEB9q5YfnMpOAHburJCKqr1vtu8eT+Z3crb6mYuOAEHJ+At71ssA2wBa5yFt+3FVMYi26F9/RCuankScdwJethGI9uFwZ2LvZ88P3Tu1uRtHVHZHi0tgWhsbj1ZIC13TMoGwvj3oRt5qnvssd96/6zYXHt5qrHavrlEnZYbhqgKlQprggvc7cXgv/10235udjP27eamVx4NQd0Eig2ttWSTaSIbMcHX8XJfB3PpVl+XAgMcGOCODLAfApJCnIheJwrVDThyIgf95FnoYWtBdKJpnahie3GXC5panjTg/J+103XLcxoHJ6rVifZ1GjonF7D139b7u1OltoL05ns6EcdOxKclz4n2tVGdreArZ5qH1JNMVXHKk+Ac29ioEMPWYu7clPjLaz/2zjSvrYz9ds8l8oAXGyZ0s2m8TBosUxSNECU0HOkozrF/I+aSBcp7PXPJ4rFOagYSYW/WQLu55B575zu6C2bcinPJQmJzjrwZc+n1rEvWGuMc+yANKTDAWzbA9XrDjES8blhppLw5iZZx9EMR+iFIpcFRc8lykWAqRCeoyfby1IjedmjpbuRZC4aK8WgzZLZKf93rtv1YqWKx7XXhL68dwtV/7Ld3LjHlKs+jowK8RAOWinoRwu0Qrt2MfTv9dTv25BxXcZF3K69dVkO3Y3W7zaVux573qXnPxd87ypoJ0pA2N1cdKXRzcbfOL251KsqAv9eeK36xq5vLXtQdgMVvxncTj+Ppd6VKA+z9LJOajnTML67fDlwlc7fdrVvqyO1ES1sbM780wG7AbrfGXPIfj7cyr3inLugrV2bNVCp16xiFN7AnAQjLpdzAANsKCRZNqYs3AhATGGCpgW4N+nanqgUG2J6R/mCt7jYInRrgS5emzUwm8waavVtHdGCAAwN823FBBydge1IHJ2Cnx6SdAVF7Mm7uXOrOwG3nZq7dhrNb3oHAAAcx4C1veRgDZgzT6X5zInrdsUrGPqw4oBfRq0Y3vz55Fuiolayg3jBEEfpouJXxic+SxbrVqFPGoZ2gD0tRTnCKMxbdDo1sgXvUvNOthcGt52yGlrZAW1vls92KPL8YP8FDbiT66xurmyOP47vWAAx40cMJlktUcFVbY9Vu7FVI/rf6XOL7+iGp/dHhavQ15+btNpfcYEjrO7XWOerI/S1uNpcikc7qAQcn4M3N1W0bA2YakhsV60zPcKbJqBCzlrFqRUtb1JASBeyWZ6GXVchnGdaTCF8/tLSFGOUvEyH+T4JX3PR4FhrUjc9c2lMAAAojSURBVG52o5HdiFkVx6wVh+P/3woi1Z/72l7cLDR2u/5ZCNfNuLTZLz90s9V3OVYSLa1CRFtgHyLPLXepBcTb+tjbGw/V2LfKk5ske5MjP7OtzCW+w3pDR0UXmGeEYAoO5UREbtSssd9sLvG3TgNlnQDfinPJQsH7Ie87mUt+aOnbcS5Zc/31rkvWuhGcgIMT8OZbiuYv3EQcnXKkOneQ7of6oTCtj9gPReiHlq7UdBRZeF4BvsmFDUSbi6+zH+0RpGr0dbv+tUPT+qG5u5enRnNbC4ZlKN3v64/Q7A4t7SdPGrnOkfLtEKTWBmerc4n7O+YCpyJe7utukPebjZUfevjmjr3afdx+bt7ac6nbrIv2c8kv66KdLvxc81vP4ggMcGCAuzbA3SAqtxvE4CevUNVRhRrhmiV5vaLsnjwZbi/C1R8QEzBhWROvG3Szdfp1p6O123Bsdq27sb85VJTtjH238cftBmsFVJT2UrrVuRQY4MAAb9kABz8MNBBoINBAoIFAA7eyBm7bGPCtrPSgb4EGAg0EGgg0EGggMMDBHAg0EGgg0ECggUADb4IGAgP8Jig9eGSggUADgQYCDQQaCAxwMAcCDQQaCDQQaCDQwJuggcAAvwlKDx4ZaCDQQKCBQAOBBgIDHMyBQAOBBgINBBoINPAmaCAwwG+C0oNHBhoINBBoINBAoIHAAN8Cc+DEiRN91Wr1dwC8e3JycoezS4cPH/45TdN+anJycv8t0NU3tQsqPR05cmS/aZp/pGlaBEANwPdPTExMv6kdfRMfrtLR4cOH///27j9GjrKMA/jzvHPTEk2bWoVoFTxud565c/FsbUWChqgYhMg/NkiIFCFafpQqJhqIhj9QYmIaNA1qGqMk/mGEkAgJxJAQLFxC0KBCtLC5m2euR5WqECoaF47r3c485tVt2FwgLaVl3pv53n+3mZ33eT7P5L63M7s7X2Xmy5h5qSzLBTPbPjs7e7DCMitfWkS+SURbmblvZtmaNWuu6fV6XyCirxDRAhEdiOP4y91u1x9T+IHASRFAAJ8U1je2UxF5gJnvMbPvDgdwu93uOOduJ6IxVR17Y3ut39av5SQiD5vZHXme35mm6ZfMLFLVn9Wv+2PraLmRiLyXiB5T1Zb/KmkRuYWZ35Nl2XXHtsf6bZWm6cfMbI+qfnhgcg8R/ZmItjvnNs3MzPxTRH5KRNOqurt+AugoFAEEcACTmJycfPvi4uKpZVn+7kgAb968Oe71enudc9vLsnwQr4CJljuJyLuISFX1VP+HNIBRVl7CcqPBK+In4jje0u12X0ySZDcz/0dVb6m82OoKcJ1O523dbvclX0KSJHucc38xs46qftE/JiLnE9G3VPXT1ZWJlesugAAOZMLj4+OjwwEsIt8houdVdY+IPIMA/v+ghp1E5Gwi+jkzP2Bm5zDz80R0Q5NPQS83GoSJD5XbzewF51xv9erV5+3bt+/lQA79SstotVrtKIoeIaI9zLw+y7IbfUETExNnFUXxK1Udr7RALF5rAQRwIOMdDpY0TbeY2bdV9eLBH1AE8GBOw05JknzUOedPQW9W1Rl/XY+Zt2RZdkkgY62kjGGjsbGxM0ZGRqbiOD632+0+lyTJzcy8QVV3VlJcQIumaTppZv708w4i+ggCOKDhNKQUBHAgg14WLLuY+RNmNu/LY+ZziOhhVf1sIOVWVsawU6vVOt05tzfPcxmcSpxg5vtVNamswAAWXvbP3KVmdpmqbh38M/chIvqlqp4VQKmVldButzcx893MvE1Vf5+m6TYiuijLsst9Ue12+4Ioir6RZdlnKisSC9deAAEcyIiXn4IeLgunoF/VeI1T9Y/76+QzMzNPich2Zr4Qr4BfvZwxeJV37/z8/AcPHjz4SpIk1zLz+ap6aSCH/ltehr9OvrCw8GRZlltnZ2e7voBOp/Pufr//+OBsyiER+YWZPZbn+U/e8gKxYGMEEMAVj3p8fPydRVFMMXNMRP4jNcrMT6rqlUdKE5G5pr8L+nWcnmDm7/l3QfvbIzPzwtLS0tVzc3N/rXislSz/escSEf2BiLaZ2SvM/HJZltc1+WNIInI1Efnj5qkjg2Lmh4hojoi+7j/OxsxPZ1l2vT+uKhkmFm2EAAK4EWNGkxCAAAQgEJoAAji0iaAeCEAAAhBohAACuBFjRpMQgAAEIBCaAAI4tImgHghAAAIQaIQAArgRY0aTEIAABCAQmgACOLSJoB4IQAACEGiEAAK4EWNGkxCAAAQgEJoAAji0iaAeCEAAAhBohAACuBFjRpNVCojIXv9lSxs2bHjf1NRUv8pasDYEIBCOAAI4nFmgkhoKDL468zf+3rLMfEeWZffVsE20BAEIHIcAAvg40PAUCByrgIj87767zNw1s8tV9XP+dxG5goh2EdGLzLzbzH7U7/fH/ddoJklyFTPfRESriWgmjuMr/L18j3VNbAcBCKwMAQTwypgTqlyZAiwieVEUn1y3bt1zvV5vzjm3MY7j8vDhw38zs3PzPP+TiPyQiHb2+/0z4zg+3czuK4pi0/79+58d3Bd6osk3T1iZo0fVEDi6AAL46EbYAgLHJZCm6afKsrwpz/ML/Q6SJNnlnPu7v+EGEf1AVT/gH5+YmEiKosiiKDqz3+9f75xbm2WZv0cttVqt06IoelZVTyEiO65C8CQIQCBIAQRwkGNBUXUQ8Le0IyJ/ynlp0I8jov1mdhsz71DV8/zjo6Ojp6xatWreB3BRFDcPnnNoyGC9fxOXqg4/Vgci9ACBRgsggBs9fjR/sgTa7fZa59zs4uLiGQcOHFg4so6IPG1mdzHz51V1o3+83W63nHP5IID99d/1WZZ97WTVhv1CAAJhCCCAw5gDqqiZgIhcw8wXZFl2yXBrSZLc6pw7zcyuMrNNeZ5Pi8j3/X1o+/3+6MjIyDuI6NdRFJ09PT39DxH5OBFtVVV/n1r8QAACNRJAANdomGglHIE0TX9bluWP8zy/c1kAb2TmB4noVv9OZzN7gYhuI6K7iqJ4/+CNV1cS0Y1E5Jj530R0Q5ZlfwynO1QCAQicCAEE8IlQxD4g8CYEOp3O+qWlpUNxHK/tdrsvvYld4akQgMAKEkAAr6BhodTaCEQi8gwR+c8FPyoiO4noWlWdrE2HaAQCEDiqAAL4qETYAAInXkBELiIif+03IqJ/mdkO/5ngE78S9ggBCIQqgAAOdTKoCwIQgAAEai2AAK71eNEcBCAAAQiEKoAADnUyqAsCEIAABGotgACu9XjRHAQgAAEIhCqAAA51MqgLAhCAAARqLYAArvV40RwEIAABCIQqgAAOdTKoCwIQgAAEai2AAK71eNEcBCAAAQiEKoAADnUyqAsCEIAABGotgACu9XjRHAQgAAEIhCqAAA51MqgLAhCAAARqLYAArvV40RwEIAABCIQqgAAOdTKoCwIQgAAEai2AAK71eNEcBCAAAQiEKvBftSvLNikZvnwAAAAASUVORK5CYII=\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "from matplotlib import cm\n",
    "sns.set_palette(\"colorblind\")\n",
    "p = sns.jointplot(x=features.age, y=bmi, kind=\"hex\")\n",
    "p.set_axis_labels(\"Age\", \"BMI\")\n",
    "cax = p.fig.add_axes([.98, .4, .1, .3])\n",
    "plt.colorbar(cax=cax, );"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 397,
   "metadata": {
    "collapsed": true
   },
   "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",
       "            fig.waiting = false;\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",
       "            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",
       "            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",
       "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",
       "\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,