t-SNE Visualization.ipynb

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    "## Thanks to http://blog.applied.ai/visualising-high-dimensional-data/\n",
    "## Interactive magics - comment out if running from another script\n",
    "%matplotlib notebook\n",
    "%qtconsole --colors=linux --ConsoleWidget.font_size=12 --ConsoleWidget.font_family='Consolas'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/madness/Documents/Projects/git_better/venv/local/lib/python2.7/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n",
      "/home/madness/Documents/Projects/git_better/venv/local/lib/python2.7/site-packages/sklearn/grid_search.py:43: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. This module will be removed in 0.20.\n",
      "  DeprecationWarning)\n",
      "ERROR:root:Can't import Theano: No module named theanets\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorflow not installed\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from app.process import get_cleaned_processed_df\n",
    "from app.evaluation import get_training_and_validation_df, complete_columns, drop_text_features\n",
    "\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.manifold import TSNE\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from IPython.html.widgets import interactive, fixed\n",
    "\n",
    "sns.set(style=\"darkgrid\", palette=\"muted\")\n",
    "pd.set_option('display.mpl_style', 'default')\n",
    "pd.set_option('display.notebook_repr_html', True)\n",
    "plt.rcParams['figure.figsize'] = 10, 6\n",
    "np.random.seed(0)"
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   "source": [
    "def plot_2d_tsne(df, y, file_name, preprocess=False):\n",
    "    if preprocess:\n",
    "        from app.preprocess import ColumnSumFilter, ColumnStdFilter\n",
    "        ppl = Pipeline([\n",
    "            ('clmn_std_filter', ColumnStdFilter(min_std=10)),\n",
    "            ('clmn_sum_filter', ColumnSumFilter(min_sum=10000))\n",
    "        ])\n",
    "        df = ppl.transform(df)\n",
    "\n",
    "    from app.preprocess import get_text_feature_names\n",
    "    for c in get_text_feature_names(df):\n",
    "        df = df.drop(c, axis=1)\n",
    "    df.fillna(0, inplace=True)\n",
    "    \n",
    "    X_tsne = TSNE(n_components=2, perplexity=40, verbose=2).fit_transform(df)\n",
    "    df_transformed = pd.DataFrame(data=X_tsne)\n",
    "    df_transformed = df_transformed.join(y)\n",
    "    \n",
    "    if y.describe()[\"unique\"] == 2:\n",
    "        palette = sns.xkcd_palette([\"bright green\", \"royal blue\"])\n",
    "    else:\n",
    "        palette = sns.color_palette(\"colorblind\", 8)\n",
    "    pl = sns.pairplot(df_transformed, x_vars=df_transformed.columns[0],\n",
    "                      y_vars=df_transformed.columns[1], size=12, hue=y.name, palette=palette)\n",
    "    #pl.savefig(file_name, format='png', dpi=900)\n",
    "    return pl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": true
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   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "[t-SNE] Computing pairwise distances...\n",
      "[t-SNE] Computing 121 nearest neighbors...\n",
      "[t-SNE] Computed conditional probabilities for sample 1000 / 1412\n",
      "[t-SNE] Computed conditional probabilities for sample 1412 / 1412\n",
      "[t-SNE] Mean sigma: 21.308717\n",
      "[t-SNE] Iteration 25: error = 1.1753436, gradient norm = 0.0075094\n",
      "[t-SNE] Iteration 50: error = 1.0121229, gradient norm = 0.0072799\n",
      "[t-SNE] Iteration 75: error = 0.6600252, gradient norm = 0.0062746\n",
      "[t-SNE] Iteration 100: error = 0.6341822, gradient norm = 0.0048861\n",
      "[t-SNE] KL divergence after 100 iterations with early exaggeration: 0.634182\n",
      "[t-SNE] Iteration 125: error = 0.5597788, gradient norm = 0.0046245\n",
      "[t-SNE] Iteration 150: error = 0.5427228, gradient norm = 0.0053316\n",
      "[t-SNE] Iteration 175: error = 0.5418280, gradient norm = 0.0049467\n",
      "[t-SNE] Iteration 200: error = 0.5443574, gradient norm = 0.0051958\n",
      "[t-SNE] Iteration 225: error = 0.5439426, gradient norm = 0.0047960\n",
      "[t-SNE] Iteration 225: did not make any progress during the last 30 episodes. Finished.\n",
      "[t-SNE] Error after 225 iterations: 0.634182\n"
     ]
    },
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       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[t-SNE] Computing pairwise distances...\n",
      "[t-SNE] Computing 121 nearest neighbors...\n",
      "[t-SNE] Computed conditional probabilities for sample 1000 / 1412\n",
      "[t-SNE] Computed conditional probabilities for sample 1412 / 1412\n",
      "[t-SNE] Mean sigma: 36.074332\n",
      "[t-SNE] Iteration 25: error = 1.1543134, gradient norm = 0.0076742\n",
      "[t-SNE] Iteration 50: error = 1.0051516, gradient norm = 0.0066463\n",
      "[t-SNE] Iteration 75: error = 0.6508905, gradient norm = 0.0043332\n",
      "[t-SNE] Iteration 100: error = 0.6011693, gradient norm = 0.0050383\n",
      "[t-SNE] KL divergence after 100 iterations with early exaggeration: 0.601169\n",
      "[t-SNE] Iteration 125: error = 0.5365755, gradient norm = 0.0046109\n",
      "[t-SNE] Iteration 150: error = 0.5139616, gradient norm = 0.0057973\n",
      "[t-SNE] Iteration 175: error = 0.5203577, gradient norm = 0.0037983\n",
      "[t-SNE] Iteration 200: error = 0.5166495, gradient norm = 0.0045150\n",
      "[t-SNE] Iteration 200: did not make any progress during the last 30 episodes. Finished.\n",
      "[t-SNE] Error after 200 iterations: 0.601169\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7f41b8db2950>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Plot the class distribution in the training set\n",
    "df = get_cleaned_processed_df()\n",
    "y = df[\"label\"]\n",
    "plot_2d_tsne(df, y, \"raw_class_distribution.png\")\n",
    "plot_2d_tsne(df, y, \"preprocessed_class_distribution.png\", preprocess=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[t-SNE] Computing pairwise distances...\n",
      "[t-SNE] Computing 121 nearest neighbors...\n",
      "[t-SNE] Computed conditional probabilities for sample 1000 / 1443\n",
      "[t-SNE] Computed conditional probabilities for sample 1443 / 1443\n",
      "[t-SNE] Mean sigma: 21.036028\n",
      "[t-SNE] Iteration 25: error = 1.2031515, gradient norm = 0.0078495\n",
      "[t-SNE] Iteration 50: error = 1.0329822, gradient norm = 0.0067116\n",
      "[t-SNE] Iteration 75: error = 0.6719437, gradient norm = 0.0048756\n",
      "[t-SNE] Iteration 100: error = 0.6213125, gradient norm = 0.0049665\n",
      "[t-SNE] KL divergence after 100 iterations with early exaggeration: 0.621312\n",
      "[t-SNE] Iteration 125: error = 0.5409960, gradient norm = 0.0049663\n",
      "[t-SNE] Iteration 150: error = 0.5146534, gradient norm = 0.0053696\n",
      "[t-SNE] Iteration 175: error = 0.5174559, gradient norm = 0.0048222\n",
      "[t-SNE] Iteration 200: error = 0.5174844, gradient norm = 0.0057167\n",
      "[t-SNE] Iteration 200: did not make any progress during the last 30 episodes. Finished.\n",
      "[t-SNE] Error after 200 iterations: 0.621312\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[t-SNE] Computing pairwise distances...\n",
      "[t-SNE] Computing 121 nearest neighbors...\n",
      "[t-SNE] Computed conditional probabilities for sample 1000 / 1443\n",
      "[t-SNE] Computed conditional probabilities for sample 1443 / 1443\n",
      "[t-SNE] Mean sigma: 36.059741\n",
      "[t-SNE] Iteration 25: error = 1.1378976, gradient norm = 0.0066493\n",
      "[t-SNE] Iteration 50: error = 0.9720532, gradient norm = 0.0058938\n",
      "[t-SNE] Iteration 75: error = 0.6038578, gradient norm = 0.0061586\n",
      "[t-SNE] Iteration 100: error = 0.5709066, gradient norm = 0.0046164\n",
      "[t-SNE] KL divergence after 100 iterations with early exaggeration: 0.570907\n",
      "[t-SNE] Iteration 125: error = 0.5008261, gradient norm = 0.0039405\n",
      "[t-SNE] Iteration 150: error = 0.4761257, gradient norm = 0.0051941\n",
      "[t-SNE] Iteration 175: error = 0.4823245, gradient norm = 0.0036604\n",
      "[t-SNE] Iteration 200: error = 0.4817390, gradient norm = 0.0036875\n",
      "[t-SNE] Iteration 200: did not make any progress during the last 30 episodes. Finished.\n",
      "[t-SNE] Error after 200 iterations: 0.570907\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7f41b8c77ad0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plot the similarity between the training and the validation set\n",
    "df = get_cleaned_processed_df()\n",
    "val_df = pd.DataFrame.from_csv(\"data/validation_data.csv\")\n",
    "df[\"origin\"] = \"TRAIN\"\n",
    "val_df[\"origin\"] = \"VAL\"\n",
    "df, val_df = complete_columns(df, val_df)\n",
    "df = df.append(val_df)\n",
    "y = df[\"origin\"]\n",
    "\n",
    "plot_2d_tsne(df, y, \"raw_validation_data_similarity.png\")\n",
    "plot_2d_tsne(df, y, \"preprocessed_validation_data_similarity.png\", preprocess=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as colors\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "\n",
    "def plot_3d_tsne(df, y, file_name, preprocess=False):\n",
    "    if preprocess:\n",
    "        from app.preprocess import ColumnSumFilter, ColumnStdFilter\n",
    "        ppl = Pipeline([\n",
    "            ('clmn_std_filter', ColumnStdFilter(min_std=10)),\n",
    "            ('clmn_sum_filter', ColumnSumFilter(min_sum=10000))\n",
    "        ])\n",
    "        df = ppl.transform(df)\n",
    "\n",
    "    from app.preprocess import get_text_feature_names\n",
    "    for c in get_text_feature_names(df):\n",
    "        df = df.drop(c, axis=1)\n",
    "    df.fillna(0, inplace=True)\n",
    "    \n",
    "    X_tsne = TSNE(n_components=3, perplexity=40, verbose=2).fit_transform(df)\n",
    "    df_transformed = pd.DataFrame(data=X_tsne)\n",
    "    df_transformed = df_transformed.join(y)\n",
    "    \n",
    "    if y.describe()[\"unique\"] == 2:\n",
    "        palette = sns.xkcd_palette([\"bright green\", \"royal blue\"])\n",
    "    else:\n",
    "        palette = sns.color_palette(\"colorblind\", 8)\n",
    "    \n",
    "    fig = plt.figure()\n",
    "    ax = fig.add_subplot(111, projection='3d')\n",
    "    le = LabelEncoder().fit(y)\n",
    "    y_transformed = le.transform(y)\n",
    "    for i in range(len(df_transformed)):\n",
    "        ax.scatter(X_tsne[i][0], X_tsne[i][1], X_tsne[i][2], c=colors.cnames.keys()[y_transformed[i]], picker=True)\n",
    "\n",
    "    ax.set_xlabel('X Label')\n",
    "    ax.set_ylabel('Y Label')\n",
    "    ax.set_zlabel('Z Label')\n",
    "\n",
    "    plt.show()\n",
    "    return plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[t-SNE] Computing pairwise distances...\n",
      "[t-SNE] Computing 121 nearest neighbors...\n",
      "[t-SNE] Computed conditional probabilities for sample 1000 / 1412\n",
      "[t-SNE] Computed conditional probabilities for sample 1412 / 1412\n",
      "[t-SNE] Mean sigma: 21.308717\n",
      "[t-SNE] Iteration 25: error = 1.3142426, gradient norm = 0.0115610\n",
      "[t-SNE] Iteration 50: error = 1.2407621, gradient norm = 0.0151237\n",
      "[t-SNE] Iteration 75: error = 1.0407314, gradient norm = 0.0062780\n",
      "[t-SNE] Iteration 100: error = 0.9932517, gradient norm = 0.0093801\n",
      "[t-SNE] KL divergence after 100 iterations with early exaggeration: 0.993252\n",
      "[t-SNE] Iteration 125: error = 0.9568894, gradient norm = 0.0070254\n",
      "[t-SNE] Iteration 150: error = 0.9376045, gradient norm = 0.0094212\n",
      "[t-SNE] Iteration 175: error = 0.8988386, gradient norm = 0.0095329\n",
      "[t-SNE] Iteration 200: error = 0.8545364, gradient norm = 0.0100293\n",
      "[t-SNE] Iteration 225: error = 0.8402870, gradient norm = 0.0096419\n",
      "[t-SNE] Iteration 250: error = 0.8072374, gradient norm = 0.0102596\n",
      "[t-SNE] Iteration 275: error = 0.7902698, gradient norm = 0.0098565\n",
      "[t-SNE] Iteration 300: error = 0.7688914, gradient norm = 0.0092979\n",
      "[t-SNE] Iteration 325: error = 0.7479278, gradient norm = 0.0094997\n",
      "[t-SNE] Iteration 350: error = 0.7246047, gradient norm = 0.0096251\n",
      "[t-SNE] Iteration 375: error = 0.6914927, gradient norm = 0.0088616\n",
      "[t-SNE] Iteration 400: error = 0.6799055, gradient norm = 0.0086712\n",
      "[t-SNE] Iteration 425: error = 0.6601742, gradient norm = 0.0083910\n",
      "[t-SNE] Iteration 450: error = 0.6355015, gradient norm = 0.0085172\n",
      "[t-SNE] Iteration 475: error = 0.6164883, gradient norm = 0.0083033\n",
      "[t-SNE] Iteration 500: error = 0.5903838, gradient norm = 0.0088641\n",
      "[t-SNE] Iteration 525: error = 0.5712383, gradient norm = 0.0078002\n",
      "[t-SNE] Iteration 550: error = 0.5424371, gradient norm = 0.0084581\n",
      "[t-SNE] Iteration 575: error = 0.5036281, gradient norm = 0.0076161\n",
      "[t-SNE] Iteration 600: error = 0.4578319, gradient norm = 0.0065916\n",
      "[t-SNE] Iteration 625: error = 0.4190072, gradient norm = 0.0075620\n",
      "[t-SNE] Iteration 650: error = 0.4119676, gradient norm = 0.0057068\n",
      "[t-SNE] Iteration 675: error = 0.3864913, gradient norm = 0.0052563\n",
      "[t-SNE] Iteration 700: error = 0.3723025, gradient norm = 0.0061661\n",
      "[t-SNE] Iteration 725: error = 0.3641056, gradient norm = 0.0047603\n",
      "[t-SNE] Iteration 750: error = 0.3467711, gradient norm = 0.0043690\n",
      "[t-SNE] Iteration 775: error = 0.3350907, gradient norm = 0.0052639\n",
      "[t-SNE] Iteration 800: error = 0.3276932, gradient norm = 0.0043598\n",
      "[t-SNE] Iteration 825: error = 0.3347631, gradient norm = 0.0042122\n",
      "[t-SNE] Iteration 850: error = 0.3198147, gradient norm = 0.0042402\n",
      "[t-SNE] Iteration 875: error = 0.3267655, gradient norm = 0.0034961\n",
      "[t-SNE] Iteration 900: error = 0.3255308, gradient norm = 0.0043578\n",
      "[t-SNE] Iteration 900: did not make any progress during the last 30 episodes. Finished.\n",
      "[t-SNE] Error after 900 iterations: 0.993252\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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y00KEMlUJZs1CpDki+tIc8Ey/VZzYzWJ955Qmd/sFhA31pl4royMNTE9q+xvuBCgANGbSQoQPX7GW1OAGEfKDocBgWTCQ6qVi/BIFVguAkQEg4gT3YMCxB1BChB3nLye5dZqIv3aXa/SdediTROvM8TzjwQCFCB6s0wBosfPeGsKEONI2WGeEpBNlsRtSNC485CNrQgPlZ42UcVyezuTcRsmBYjTMsMg9NxYsNlywTJ5t05h4jbORAkVL2NhELwXWjx3OBKgANGbVQoQPX7GW1OAGEfKDvOMgHraKiJDNuMlJSXWHagNoQgPeU3FYMSrbB7vlilAsr8QaAHJPnN1RaeA8uLOZRcktJoM3RzyyrlNgAJEb34oQPT4GW9NAWIcKTvMEwJONyuxbogAkRoZzorlYvHwujEyKUBkXHLEs854xe3GAiIbeTncii2vY8jU+RQgmSKbul+3Fhy37lyJYk1Sj2TgjFRB8DruYl7GwXNJwAQBChA9ihQgevyMt6YAMY6UHeY4gUTxHRLXIRt99Xo6Fcvtt27SbYoCxN2iogBxxykTZ7kVIImunQvCRMagRAkzdGVilbBPHQIUIDr0AAoQPX7GW1OAGEfKDnOQgNvCgTJ0sTKIu5VXi4fztilAsr8QKECyz1xdUVeAJBu5051Lzo0Xb6Jb0yTR+mFNk6FbV7zyAAEKEL3VQAGix894awoQ40jZYQ4RSGTtkCHaA8tFcMg/sTSUlpYauYNcFiD27FzxgtDpgmVkCXjqJJMbeE8DSfPkoRi/aatJMgHLIPg0FwabGSNAAaKHkgJEj5/x1hQgxpGywxwgkKpiuQosV25W4m4hmw+J25AgdF3rhyAQASL9mIjbUCJBKqvrHio2RQSXuJ2pWibSr7pvtdliDIgubffth2ID7350qc/MtfF7CYK3J6KQO5X3htsjXpyJei+xpolbijzPDQEKEDeUEp9DAaLHz3hrChDjSNnhEBJIVbFchIdsGER4OAPL5e8SoG1KgJiM21CCyYQAkXsUTqponEyX3Lsblxa7SBnCaU546VzbBHthlM9jV2tIZYvzct/ZPjddq0k6DyVoNcn27A7v61GA6M0vBYgeP+OtKUCMI2WHQ0AgmfCwP+VPFlg+3AWI3eVMWWbkSa8SN2ra1EZYiY18Eib5vInP57HnkwBJ9PHkXPfqnpznZyo7l3q/0WoyBF8geXJJChC9iaIA0eNnvDUFiHGk7DBLBOSLWtycxJLhdJmQzbYSHuJGJMIjVWD5cBUgKqWw/C8MhI09BsQpQGT64sWApOPSkm2LST5v4vN57MNBgCRa93YhEi8Y3v5xpxsEn8ydS72XmJ0rS18wOXgZChC9SaEA0eNnvDUFiHGk7DDDBOxf8s6aFs7AciU83A6ps7PTqgNiIvbBZNyGqsIuY3NzqM1svFgXZ30StwIk2ZNj9VqyDZru5szLfXvx4XfTbzbOyXcBks8ZyNT8ek2+kK47VzrCnO5c2XgX5vY1KED05ocCRI+f8dYUIMaRssMMEYjn+iACRMVyxNtsex2KSQFiMm5DWXNSCRDZpIilQ8W6KEuH3X9dBIiq6i58dAVILgmTfN7E5/PYZQ0ciQLE9NrXFSZ2ISUPUdSDFFpNvH4T5Ob5FCB680IBosfPeGsKEONI2aFhAsniO1RAtWze4m22vQ4lXwWI3L/bWBdneuBMCZCh2Jzl8yY+n8dOAeL+kyaeldBNnJWXIHh5CGG34kpbuYaz8jsrwbuft1w4kwJEbxYoQPT4GW9NAWIcKTs0RMBNYLl8qcrTfEl16+ULOtEQnS5dOrfi1W0q2bUSWUCU8JBryf2reJhkLJwCRPqWDYv98OqKosPJ3lY3ziSfN/H5PPbhIkDkfSDvHRMumF7fE6bcudQ6kntI9DmQLNaEQfBeZy5751OA6LGmANHjZ7w1BYhxpOxQg0CqwoHOwHLZeNsDqjUubTU1KUDcuk25GbOzL2eQvTBItuGwXyOXBUgiFm6eGttrmOSjy8lwECAyf0OxeXfzHnJzzlAKkGTj8yLMpR9l7fA6FwyCd7NKhu4cChA99hQgevyMt6YAMY6UHaZBIJnwcGZxsgeWO+MZ0rj0oCa5LEBEbEkdEGVZEcuP1yB7udl8FCCphInadMVzZZHXshEAr7v2KEB0Ceq3z1UB4nb9q/eB83zTqYPjuXPZxacJa7T+bA6/HihA9OaUAkSPn/HWFCDGkbJDDwSSuVmpjFbyv71iub1752baw6XjnurMEKXTn0kLiIgO+SeHCiD3+nRT3ctwEiDO+bG7n6jXhjozl9s1RAHillTmzss3ARKPhPM94GX928W6W8p053JLSv88ChA9hhQgevyMt6YAMY6UHbog4LZiearA8lwXICIapLJ6OofaSNiDxE2kCHZWaE8UA6Lia9IZ+1C1cbOJ9+LOYn+Sm+mnuvmeRWqo4oZMrjUVvJ3puTY55kQiPFEqajfujHYhksw6neo+7OKEQfCpaKV+nQIkNaNkZ1CA6PEz3poCxDhSdpiAgHyRyeY3nttQOsHUchnnZloXvkkLiGxmZHxeBYiwcKbSFXY6YsbO5UgXIInWyFALEwoQ3XevfvsjQYCkWv/yOq0m+mspEz1QgOhRpQDR42e8NQWIcaTs0EEgVeFAe2C5l2DqTAgQkxYVrwJEiTDhIYdyOxN+XvtKtggpQLy9Rd08MY5nKfH6FJ0CxNu8ZOLsI1mAJOOZLXHudOeS94Q9K5n6Wf4u/+T74kg6KED0ZpsCRI+f8dYUIMaRssP3CcQz3SsLg7ymXH90YhpMVhuXYQ+FAHFj/ZEvW2FXWlqqvb4oQLQRWh3YA969PDFOJEwoQMzMi04vw0GAZHMdmX4POOfOPh92cfLUU09h7dq1+MY3vqEz3XnXlgJEb8ooQPT4GW9NAWIc6RHfYbL4DtlEq81bosByLwBNVhs3LUBSiQYvqXRT9eWFGQWIF1rez013Uybt8jHuRhFiDIj3tZKJFtkUIInGn+57QPqzC/REgvCPf/wj2tra8OUvfzkTCHO2TwoQvamhANHjZ7w1BYhxpEdsh24LB0r2Jkkn69VFJR5Y0wLEZExJItGgsnvJl6vbVLoUIO7eVm6C0N31lJmzsuXKkpnRJ+813wWIPXuUic+moZgDuWYuCJBk9+7lPWAPXLfPye23346amhp8+tOfzgjm//qv/0Jra6v1HSWJPy6//HJMnDgRBw4cwD333IP29nYrtu+qq67C2LFjMzKGeJ1SgOihpgDR42e8NQWIcaRHVIfJsgTFcy0StyvlcmUClMlUtzKeTAoQZz0TFe/ihoNJAeIUbUdaFiw3vLN9jtr8qifA9ifIaiwmajlk8r4oQDJJ133f+ToPTquJ8z0gm/777rsP1dXVaGhoQEVFBS677DJUVVUZeZhlJyz1oFTykLfffhvLli3Dd77zHfz0pz/FqaeeipNPPhmrVq2CuIJdd9117idH80wKED2AFCB6/Iy3pgAxjvSI6NBLxXJ7YLnJGAsBnQ8CpKioyBpnsnomqRaNEiDypaj7dNaNAMl1S0IiXvk67kRPrt24spgIgE+1/ty8nu81NIaTBUTmK906QW7mOhvnqPmQ9a0Scbz++uvYu3cvNmzYYFkoOjs7LWv6mDFjrH/nnXeecYvEq6++iuXLl+OrX/0qbrjhBtx2220xttdee60VhzJy5MhsIAEFiB5mChA9fsZbU4AYRzqsO0xVODBVYLlJC0MmBIgply679UfGmaqeSapFI/2pp3IUIIlpDTcBkkxoqddMBMCnWn9uXqcAcUMp8+fkqwXESSbZe/nqq6/GV77yFcydO9dyi9q3bx/279+P+fPnW0LExPHb3/7WEjryeSuxJvLddvfdd+Omm26Kdf+DH/zAssLMnj3bxCVT9kEBkhJR0hMoQPT4GW9NAWIc6bDsMJnwUK5Fbp7wmxYgJtPTysTpChAlPFQqXfndRPFAChB3b6sjRYCYFibSn66wHS4CJFEBP3crcOjPOhIEyBVXXIH//M//xOTJkzMO/LXXXsObb76JSy65BHfddRe+973vUYBknHpmLkABkhmuafdKAZI2umHfUG2mxYXIuTlxbrTtNSuSgdHd4Dv7zhUBEi/eRVwgJOuXCbepTAoQJSDtbPN1I5+v4xb2mQ4e9hL8myy2K9H7mwIkN74S8n0eFMVk7+UPf/jD+POf/2zFf2Tj+NKXvgSxdtAFKxu0M3cNCpDMsU2rZwqQtLAN60Zq8yFfAM4NtPxNRIQ84ZfzxLVInhi6fXqaCQEicSUm6mPIpHqNKUmWSleJBpMWEBN9yRzIJkX6koMCJDfezkP15NqUMMn3jW8+i1f7Cs73eVD3kkyQn3HGGXjllVcyEucirq5iqVfiRoLQ7733Xvzwhz+0gtBPOeUU69/KlSvx9NNPMwg9Nz4+XY2CAsQVpuydRAGSPda5fiWnm5X9qbsSHiovu9eK5erenZtfXSYms0N5ESBuU+lKkKQJ0SBjM9WXU2RRgOiuQjPth0qAJBq9mwB4aWt/YGGvWm2GSvZ6GU4CRKyvbh8KZY+wtyslEyALFiyAuEZl4mhqasKdd95pPYySQ7JtffSjH8WECROsOBNJw9vR0WFZtq+88kqMGzcuE8OI2ydjQPRQU4Do8TPemgLEONK86zBRfIfa3MuXmfysU7FcQfFqYUgF02R2KDcCxGsqXVOigQIk1Urofz2fN5G5JkBMCZNkGfPczWp2zsrntWMnNByqucv9JHo/yDyJBSRTAiQ7qy29q1CApMdNtaIA0eNnvDUFiHGkedNhqsBysVbIh70J4WEXINKvyrGuC8tkbISMJV5MidqYKPcxLxXcKUB0Z9hb+3zeROaLAEk0I8r1Rz5XvGTmkv5y4Wl9Pq+dI0mAiIvUxRdfjBdeeMHbh8MwOJsCRG8SKUD0+BlvTQFiHGlOd+imcKAyPctGWzbdplyIEm3wdYBlUoBI37KpUkIsnVS68mUpQfwmMuuYEjN0wdJZcZlrOxwESCLXH1NxJpmjn/kkAJkc+5EkQCTlrgSFP/LII9lCmjPXoQDRmwoKED1+xltTgBhHmpMdeikcKMJDBZab3EDniwCRoHYRG3YhJkzSeUprkp+pvihAcvItmtDlJDdHe/io0nH9ySVhkuksZNmYR2XFGS4xIMLMWVBx/fr1+PGPf4zf//732UCaU9egANGbDgoQPX7GW1OAGEeaUx2mEh4qKFwEh2yynV9cpja9CorpoHHp15RlQDfDV7yJN8nPVF8iQOxucAxCz4237HC2gHgl7DUA3kScCQWI11nK7PmJsnlJNfT7778fP//5zzM7gBzsnQJEb1IoQPT4GW9NAWIcaU50mKpiuYpnSBXfIWl4VcyDiRvLRQHiTKUrv5uo3SG8RDQo1y1dfqYEiD3ORdUvkb/JYc9opBIP6I47m+3z2Y+fAiT1SsmkMMl3/kJvOFlAElnUnnrqKYgI+f73v596wQyzMyhA9CaUAkSPn/HWFCDGkQ5Zh/IFqiwY8QoH2uMZRFTIxjiVW5FpAWI6ZkNZQILBoOc4i3ipdIWH3LOpuiIm+ZkUIOJmJsyUEE20aJX7Q6p1MmSL3nFhCpChm4l0XLBMjTZdYWIX3cNJgJiIOTM1N+n2k2g9PfDAA9izZw+uueaadLvO23YUIHpTRwGix894awoQ40iz3qHaHMpm1/m0XT3hTjeeQTaqsgmVfk0cmRAgXjfmyVLpmk7ra1qA6FpT7G5mMp9KhKr1oZ6i2jd09nl3WtZyTZhQgJh4l6bXx1AKkGQjdhtnos7LN9Ftv/d8Xv/OOUy0nu666y7rc+uzn/1segs1j1tRgOhNHgWIHj/jrSlAjCPNWofOzaB9s+t0K7IHlnsZYKYEiMnMWm4EiNtUuqYFkkkBotOXM6OXrAHlZpYsBsQeAOoltepQCZN83oDl8xP4fHT9cStM7FYS589ePkuzcW4+r/94QipeML1UI58+fbpVHPBIOyhA9GacAkSPn/HWFCDGkb6QwlkAACAASURBVGa8w0TxHSIWVA5+2VSqwHIdc3w4HLbuR1LJmjpMBY2r8STbmHtNpZsJAaLibHT5pSNAnBYwZclyG4SeKq2q3FMuCZN83oBRgOi+Q/TaK/528ZxLa9vN3eXz+ncrQL773e/i7LPPxuLFi90gGVbnUIDoTScFiB4/460pQIwjzViHqQLLRYDI4aVQXqrB5qsASdf1TAkQUxYakxYkLwJE3b8IDVk3IjxUamVnIgAVC+N2A5BszaTri2/KYpLPGzAKkFSfRpl9PRX/oV7bbu5+OGTyUg817DGN9nv/6le/iquuugonnXSSGyTD6hwKEL3ppADR42e8NQWIcaTGO3RbsVw9rZbgYlOHClI22acblykv45eNubIyJNt4u+3TpIUm2wLEHuOhYnecVoxMCpBEjLO1eaMAcbvKzZ6Xjy5YTgKJ0r6mIpXu2pZ+TQlvNcbhJkDiWe9FfNx4442YNWtWqqkZdq9TgOhNKQWIHj/jrSlAjCM10mGyvPbx3Grkg1pV7DYpFvJBgCjXMwEvwdSJNt5uJyaXBUgidy43wsO+SbFn+jJpAXHLWJ2X7uYt0caNAsTrDJg5/0gWIMkIZjvO5EgQIEuXLsVvfvMbjBo1yszizaNeKED0JosCRI+f8dYUIMaRanWYqnCgqmItm2xnYHkmxIKzarbWzb3f2IsrUarryReuCBD5ojcR8yLXEwGSTlrfeGM16cIWz5piTzbg9v6HwgKSah7jvZ7u5i0f65fI/adyAUqHYbbaUIB4I53u2k5lMcnnNWQnmOxBwsKFC7F8+XKjcYneZm/ozqYA0WNPAaLHz3hrChDjSNPqMJXwcFYsj2eazoRYyESfJgSIPZWusBNBZsryY9JFLFMCxFnDRGI87Bmrki3CfBEgie4hnc1bqo1bWm9aw43yefOYz5YnNY25kEZY1yKYz2vI/nZKZslZsGABXnvtNcPvvvzojgJEb54oQPT4GW9NAWIcqacOUwWWK6uGm8DyTIgFe9VsTzeW5GR7zIaXPtUmx85ENt7yuxymMnXlsgBxZjnzIjwUa2etk6F0wfIy/6nOlfWh/ilOzja5XMcknzePFCCpVqfe626FibpKPtcykXugAIm/XihA9N5HFCB6/Iy3pgAxjjRlh7IJkifjymXG3kC+aOwVy1XhOTdPcDMhFjLRp9fA7FRMTFoZZC5EgOgW/FNzKmOT8etaZ2QeTGU5k/HIPao6IMNFgAjzeBvhfLGYUICk/OjM6Am5YAHxeoNOYWL/3d5XvAddbr5TvI7H1PmJ3gvykE3S777yyiumLpVX/VCA6E0XBYgeP+OtKUCMI03Yof1LwOmGpALL46VNdTvCTIgFp7uO27EkO8+tAEkUbO/84jQd+2LCRUzdv87YnBYfU65mbgSIjD9fN2RuY0ByTZhQgJj4dEm/j3xc7867tWfySmd9S3+5IEwSvReamppw5ZVX4q9//Wv6E53HLSlA9CaPAkSPn/HWFCDGkR7WYbynT2oTLlYQe2C5cqlJ50sgE2IhE32mslg4MzqlquKus8mPN/tDLUCUxUfWhfBX1hhTrmYUIMnf80O1caMAyfxncbIrDDcBkuheh2p9e5ndRO+F+vp6KwXvvffe66W7YXMuBYjeVFKA6PEz3poCxDjSWIfJAstlk6v81d1mL0o1Uqdvf6rz3bzu3Ky6aZPqnEQCxJ7RyUsqXRWgL8UDTRzpxqjEu7YXcWR3NZO+VNyPWkephJvbe6cAcUtq8HmZ3rilW4civbsx24oxIGZ5ptubjohyG2eSjTiqRO+F1atXWyl477jjjnQR5XU7ChC96aMA0eNnvDUFiHGkMRO204rhfLItr0tsgNvsRalGmgmxkIk+nZtynYxOwsR08L1bF7FU8+F2bKmEh7oOBUhq4kOxETYlTChAUs9vps5Q68ZZtDNT18tUvzoCJNGYhkKYJHovvPDCC3jmmWfwox/9KFMIc7pfChC96aEA0eNnvDUFiBmkdrGRSHgoFxp5sq2sH7rByfbRK7EglgDTosZkn/YsVl6yfCWaqXwVIG5jXNR9e7GmJFvVznUSLwhd2mdiM2Pm3Za4l6EQIKk2bk6BYj/f/jRZuZ3ES7GdaW66/ecS93TuhQLEO7V0hYlcKZWLcaLPnkceeQQbN27Et7/9be8DHgYtKED0JpECRI+f8dYUIHpI3VQsjxdYbmoz6Ry9ySreqm+TfdrjO6R/EWMS45DqCynZLJkOvleV1U2k9Y0njpTw8JpwwOSasc8pBYjeZ4DX1qYsJl6vm8nzKUAySdd937ny0EB3jSe6j9///vcQF9kvfvGL7qEMozMpQPQmkwJEj5/x1hQg6SFNVTgwVWC56af2drFgqoq3yT7tbkbys/ATq4qO8FDjMy1ATLk6yfjs82wXX15iXNR9ZkqASP8qxa/93ZArmxkv79B83ggLb/vTYfsTZsUgV9OpJqvb4GX+hurc4WAByYd7iGcNdK5zVcNH/neu91/84hcYPXo0PvnJTxpfKvL5etddd2Hv3r1WTamKigpcccUVGDlyJNra2vDb3/4WBw8etB6Y/cM//ANmzpxpfAypOqQASUUo+esUIHr8jLemAPGGNJnwsFfnFjeKZEXiZGMqH3hSi8HkYbKInhqXTp/x3IzU30zdey4LEFW/Qyw9MudKeKTjZpNJAaLqlVCAmHw3eusrkd+77tNkb6NI7+zhIkDSeV+mR8x8q3wQIInu2unOZf+9vb0dv/rVr1BdXW3VzyotLcX555+PMWPGWA+xTB3y+bphwwYcffTRVpfPP/88Vq1aha9//ev43e9+h9raWlx44YXYtm2bFQR/6623GnN1dnsPFCBuScU/jwJEj5/x1hQgyZGqWA31xZQqsNxNxXK5oulNs7oLkylk7QLEa2E+59N+eypd0/duOlWwqeKBMi7pS9WlSKdquX11msz25XSrowAx/tHquUOvQehufPCzZTGhAPE83cYb5LMAscOw34f8XX7ftGkTdu3ahbfeesuy1nZ0dFj/ampqMHbsWHz0ox/F+PHjjTLdvn07fv3rX+OWW27BV77yFdx8882orKy0rvHDH/4Ql156KebMmWP0mqk6owBJRSj56xQgevyMt6YASYxUvrzli1U+8FTVaHW288m+M2VqqokyvWnOpADxImrcpNLNdQGia2mwZ/USi4f8Lk/tdA+TbnsUILqzYb69VwGSaARDIUwoQMyvB689DkcB4nzg9y//8i+45pprLCuFuEWJu9SBAwes38VCYvIQl6uysjJccMEF+OY3v4lf/vKXse5FmMg1Tz31VJOXTNkXBUhKRElPoADR42e8NQVIfKTK/1Q+1MUFSQkQ+5N9OUeeaot1xGssQyZqdsidmEwhaxc1yqUs0QL0kkrXtPgyzTJdAWJ3wVOCVNaLzEkuChB7rBAtIMY/Wj13aEqADIUwoQDxPN3GG+Rz/JMdRrL7uPzyy/Hzn/8cEyZMMM7P3uETTzyBNWvW4Gtf+5plxaYAySjurHVOAZI11O4uRAFyOCd78JsSIBKUJhsEFZirU7FcrugUNu5mK/VZmRAgifpUXxReU+maFiCmWXpxdUrFwOS9mrSAOON6clGAqGDU1Kt+4Ix83oRlWoBkUpjkcxV39XmsXCW9rLdcOjef175bAXLuuedCUvFKgHimjqeffhorV660xIeKMXG6YP3gBz/A0qVL6YKVqUnIUL8UIBkCm263FCCJBYj6QFcZglIFlnuZA7VpNllfQ65vMoOTuh9nWloZu3raL1/aXlPpmhYMpvtzs9GPJzzipRM+kgRIOoIh3num41AI61/eg7ceq8cJF07DnNPHoawmeNip8a6XaBNmamxe3uNezx0qAWJCmCi3r3wt5DccNu/D4R5SicEFCxZgxYoVnj0O3L4XpcjhG2+8gf/3//7foAQxEoQ+YsQIXHTRRQxCdwszB8+jAMmxSaEAOXxCVOC5bETVkz2xgMhG2+Rhsr6GGlcmBIjqUzbYskmyF1QUJl7dz0wLBtNiLpkAUeJLGMjPKjg/EQOT7mEmY2fSsYDYN/H2n6OtrWhbuRKHXnsNo84/H8XTp8OX4Alloj7s76uVy7bivz/7dOxPX7z7HMy/cGrs93CkG3tbd2BrwwZMrZuNsZWTUOTvz4bj3IT5cAjByMsIhB5DT/BChPynI4qauG/joRYp+ZL22E2MiQB2BsB7/Zww+Vmbqq98dyFLtXFPdf+59HqyuRAB8tprr2VkuIcOHcJ1111npd1VBYLl++1b3/oWWltbrTS8DQ0N1j5A0vDOmjUrI+NI1iljQPSQU4Do8TPemgLkcKSyAZXNgPLjFwuA+tnkBOikt000jnTjF5Ldl9y/EmJyXrpxL+oapgWD9GtSzCUqHpiO+DIptoZKgPgLmmOb+Oaiq7GjrQRbGzbFNv+dL61Ax5qXMWnpWJSVr0DYfz56ys8etNFXIqVh+XKM/MdP4FCtH9uaNsb6CAZKLPEgm9Q7PvcsXn94M8prijFhXi1GT6nEVbedab0ux/amjXhu3cMI+kswonwkjh53IibWTI8rQEojy1De+tnY8m6rvBtd/gsHLfdkgibR+yITYiVfBEg8JmrTKBYQtRm2/29vk4vCZDgIkOFwD7JOEt2HvP/POOOMjAkQk9/tmeqLAkSPLAWIHj/jrSlADkcqH3R2VwIvWaC8TFCmBIhsZEzkRxcOImhkQy6HWIHSCbiPx8SkYFACxFQBRvtGXxgoQZKO+Mp3ASKbxfLex61NfG9BDd7t/R+8s283mtoPIhTpwtlzlwK/fxzTPlqO2tLrE270O95+G+u/9S3r9cqffhsvHRp4innW7Auxt2UnJtRMtawZf39yLza+sAknHRdC5L3XUHPGWag9/UPwVVZaAuX5DY+iIhDF8aM6UdX7PDr8S1BQcg6iqB5kAZFzK9s/h2DoYWvsUf88RH1T0FZ2W0zM9Aua9Xhu3aOxsS+eewkmjZgd961sF1J1ixahYv58a1xehEoi8ZLvAkQYKAFi55EPFpPhsHkfDvegBEi8tSRpdz/ykY/gueee8/I1O6zOpQDRm04KED1+xltTgMRHav8izURgt1w1E8LGTfxCqkXkTKWr0hGbKhyoBIPJ+BeTYk4VDxRLjwgwnWxnuSxA7LVd7EHoaoOsNsTVnVdbm/jG4u9hXfvJ2HVoG8ZUjsehzgb0RHtwim8eRtbeiuLex2JLKxS8FK3lv0aopwt7W3di6/73ML5vBErW7samuUFsbd4cO3dK3WxLzOxt3oGz516KUb7JaF/xEupv+k7snNm33orqhQut33ce2oLxRa9jTOhrhwkeuwuWWDbKe58EQm+gPrQEWxoPYerIGRhTOTvmsmUJmvUPo75hQ6yvaXWzsXDOpYNEinqx+fnnseHb3447LvmjYhfPqiKvJ3Idk9eGqwBJ9HmTS8Ik34Pok23cU33e59rrieZC6oBIbMZDDz2Ua0PO2ngoQPRQU4Do8TPemgIktQDJRFyFEiCp0tt6nXAdN51EqXRNiBrnfZgUDNK3qf5kUyTzrTaD9gKKXudCzjfpbqaEkYmUvnbxq+45FOlGS1cDNh14z7JGjK6YiCJf0LKAlLZdi9XRO/HMhtdjGE6efjYqgtUYFxiNUvwVFT03WFYGX2Qt2st+jO6ii2LuUqrRgrrT4EMBXmh4eVA/q7e/aomQ08ecgfFtxdj7wANoXL48dk7t4sWYefPNFs9QtBujur6CYPiRwwSPrGGVzUhctZrbNqO6fByeWz8QUyIiZ/KIfv9tEQw7GlbgmfV/i/W1ZM4ZmFR3ymECRM7d/ZvfYO999yHS0mKdr8ZV2NcUc1MLBy/D+tbJg6wqcs3CAh+eWftg7Dr2cRyJAiSXhAkFSDqfbplpk2gu1q5di5/97GdWLMaRelCA6M08BYgeP+OtKUCGToBkwrLiVYDEy+Ykm267BUgEiFgCTFpATAkGNXu61iS7u5kqHugsPpnum8+Uu5nJjFrCS8SvcjHragnjvZd2YdXjWzHvnNHom74PUydPxYSq6fCHD6CoYBOe2t6E+oaNMQzT6ubg9Jnnw18YQOPePWjzH8C2pq2YMmIqyntGYuT4CZa7VP3BdQNtRszGSVXH42CwC1sbN2LSiOk42LYXTZ0H0dHdhrOap2D7j3+CCVdeiW0//3ms3Zxbv4MRC0+13KzEAjKh6A2MDv1b7PWOih+jt2A0Qr6T0NNbacVsybW7ejqsWJFtdgvHyLlYOPvimMDo61mN3S3N2NLYhOm1IzCuqhqFgeNjAsUSaCrw/cA6jO+tQcEzb6Dx3gehLDP2WJOewGl4aM+Vg60qI+eiprQOK7e/FItdqSyuwekzzouN40izgHh9P2XSYkIB4nU2Mnd+omxwr776Kh5++GHcdtttmbt4jvdMAaI3QRQgevyMt6YASS1AMhHYLVfNhGXF7SZVZXNSmb6SpdL1KmrcLFJdweC8Rrr9Od3NVCpd6c+EpUHGmWsCRFllZGwituSeJej7v//5qRjWz951Oqrmd2He2PlofuEFtK9bh8glp+H5bQPnqCf4YhnYuGsNXtr2eKz9gskfxqyJH8C2xg1WwLg6xLowq6oVYf9JVlxGR7gNe1t2YEfjJkyum4Xi1zZi580/xKiLLkLptGlo+/vfMers4zDqA++ir/YChH2nxGJAPji6C9V9yxENnABfZD0CoSfRVnUPOvtOtMSVWEBe3vQUTpxyBl7ebBv3nEswubY/xkPGXth3CP7IavjQgCjqEPEfB3RVIritDYH3mhA+phbra/fjufUD93HmuIUYuT+KimOOQWFZWSzWRPqU+1rde88gq4qygOxo2mQJkX2tuzG5diYmVk+LuYPJ+0zGnY/HUG7gTQiToRy/qfkeDvcgLBIJkCeffNKqz3HTTTeZQpZ3/VCA6E0ZBYgeP+OtKUDiI7UXI8yEC1KmBUiip/f2NLIyBpXdK1mKTJOuP4p2uoIh0RvAa3+J3M2sDWRvrxWfM9wsIHaxpeZeEgvImvjFPz1piRA5FlwxF1OPG4n1r+7GCRdOx+ieDaisK0WktAjNtT7s7N6DKTUzMKZ2GgKFRQj0FeKlbU9jw/53YtOj4ij6Y0B2YOvBdZhRW4lpwadR3fMbNJffgfbC863X7AJl4bTz0fRP11ouTv6qKsz9wTUoGfM23n7jVLzxRDtOuGgWRh8fwNPb/ohJtTNw8eStKO3+H3SEL8D+Ncfh4AvrULtoiRUcHi0twv623Sjd14YmtGFX70FMKByJEagARlSh8L2taHz+edQuXIjoUZOxpmVtLCtX9aZulN+3ybqfnqmVeOjkjahvsFly6uZi3rjjsXbvaqvNpIoOjG47zzpfBMjBysewq7UAWw4O9Cmv7Wyux4sbBmJllIgTC8ue1h2WpcaZWtj4h34GOsy1GiZyi16EiTo3X+uYJNu4Z2C6M9plIkvgvffea6XBlQKBR+pBAaI38xQgevyMt6YAGToBkgnLSqKgZ51sTm6tKl4Wp3IBkqfvJg637mzJhIcah8nAcelTLCAmMnSlK4zswkPFHIn1TYlPud8Vf9loWUAk9e2F//ZB3Hvjq7Fp+cIdCzGlaBO2/+IXqDz2WOvvNWeeiZJTzsa6l/dg5bJ6HPfhieiavBX1nf0iZMmcszBhxImx1LoV4dtQ3Plry9ogR1fgYuz0/wBv71hx2Mb+xK6J2Pvggxi56BSMPnoFXllxGf77X94YGM/dSzD6tD7saNqMhRM7UdlxHepXXY91N9weO0e5Romw3vSd76DljTdQNmMGOjZvRvUZC1B6wrHYceMtsfPH//t1eLF6eyyz1wdeDqB41cF+QVHix+pPBvHM9gHhIJm7Vmx5zjpfDsmcNatyO6LNu3Hw3dFoeH4Fqs9agO5ZY4DyQoyuGI+iwIjDXdLedwdzWoqc8SEm3iOZ7CMXBUiy+1WCw/m/vU0upgtOdk/5NgeJ7iWRALnzzjstq/RnPvOZTC7lnO6bAkRveihA9PgZb00BklqAZMIFSa6aCcuKc/PsjG1IJ6g63Y1vssXqVjC4XfCp+lM1PORe1MY7XspQuZ5pAWIq3sXruOIJD3XPipcqrtl8sAPrXtqFvRubsXNdI958dEsM/YcunYGPfxwIHziAtnff7Xc7KinBDv9xg9y2rr5zISLz6jGxdBLGj/EDhTOsPmTc5X1PoMJWj2Nf8Da8eWAMxlaMw7MbbClwZ1+MSXVzBlyjejfjvz5/CG88XB8bz0mXTsfnf73E+l2Cv/29G7D2xkfR8OzzsXPqFi/GjPeD1p2Zq6b/4idoeuRxHHp2IMi95uxF2PIPH7AycU0bORfnFS9C5W/Wxvrb97kZ2Fl88P3ih3PQGW7Hii3PxF6XNhJXcmj5cmz5j/+IiZ3RX/uCJWwWzDwDk0Yce1hQvqQxnlI7K6EwURvkTNQdcfvecnNevm9+1fiV6MhHYZLvc6DWWSIB8qMf/Qjz5s3D0qVL3SzJYXkOBYjetFKA6PEz3poCJLUAyYQFIFMCRPqVJ+7iWqM2oMrPP133Aq8bXzeLVDbA8mUv4zRxxOsvXoC9ivFIdk3T95ttAZLKyqNEqQ8tKIr8DYHuZQgHP4Jw4DT0ohxvSSVyWzzIV//3PEyMrsWm730vhm3mTTdh2V+L8eIfB9ySPnTRNFzz8bmITvEhOmMnIoUzY8UIC/ua4YuuQbD7z2gtOAmrD5RiVPUHMDHYjF2drbEA8AkllUDZ/Jj7jKzZl//yHu6++qXYtT97xwKcdtlRg1xsmpc/jQ3X3xg7Z/Yt/47qRedav9trd5QtOBn7JgYxcnsHdt/0w9j5gy0gl2Ja6XQUbW2Df3srQh8cjWilH9FiXyzN7oG2nXhm7cOWBUSC3JfMW4rRlRPR9NDjqKuahrL9BegY3YeDLZvx+sx2lPiDWDT3I+gOd/anJW5Yj+l1kzC5ZA2CgTpsbJuGNXtW2uqr9GfqSqdIoon3k9c+8n3zm2r8+WAxyeckBmq9qc/seN9V119/Pc477zwsWrTI6/IcNudTgOhNJQWIHj/jrSlA3AsQUzEB9ic94gpjMruUEktyDeVuk+hJv9vFZHpDLtc1HYBv788ZYK/qXSSLc7GzUPdrqk5JtgRIKuEh99gXaYA//KIlOnqKzkagZ0X/Jt0/G76eVegpWoyuUB1WvjAGby7bgxMumo6jz5qInf9xExqffTaGSSwMvR/+An5w6YD14su/WITTjvXDP/JeFONnUFXHfTgUS1HbHTgfm9rGoq+gBuOrp6K280sI9LwYS9/bEzgTzWV3WOJZHXt27cLWt1rw3lP7cNS5YzD1xCpMnDQ5JgZkXttXvoz2jTvR9s47qDj2WFTMmoiy+afHRIqvoAO+yHsoDv0f2gtOQXvnCQi9uw2Ny59H7aKFiM4bHANS5C9Ga5NYhfZg1ePb8MELpmDugnGoKSl+Pzi9EV1zy9Awogd1TQGUrOtAz1G16C0uROXvBmqKNF8yAX/qfQwnTT0JY6rmYG/Lduw6tBUzR83E+II/oib8SzQHPoNNPf+IrQe3YGzNZFSX1KKmpM4KTldV3xWLXHXNSrWBd/tZM1TnpTv+XBImw12AfOlLX8LnPvc5zJ8/f6iWyZBflwJEbwooQPT4GW9NAZJagGRiA25t+qJRayOuK0CcT/qlb7EsKPcaE4vGVCYnNZZMCBDhIKJLYmvkZ6/Cw87J5P16DZBPNF+J1qEb4WGJj74++Lv+gvKWf45doqP8RyhACKXtA0X/Osu/h6LO36K98pcIFcyHv6AVjctfwYbrvx9rN/eWLyJ4/Aex5pVSvLVsiyVUjj15E8b4vhyL81DFCEt6HrUqqatDCRP5vbRnGcrbBl5TwekBX9A6XcTFnscfQffMUWgNRlAZ8qOkoRi7G6ux8rF6zL9wGuaePg77fvp9NL/51kCcx4knYMbNt1jB7G0rV6Jx+XMYedZsjD76bVQE/hATR3bXJqeb0+uPbMKdnxtw0/rS75bg9MkjYsHpEhvSdf5ElP1l6wDPi6ai5NmdKOyKWH/rProGW84tRG1JFLtbGgdlxjpn9ok4xn8d3o3ciqc3vBXrw55d7LA0xo4Uwibe2yb6yPfNr+nxD4UwMX0PJtaF1z6SWUA+9alP4ZZbbsH06dO9djtszqcA0ZtKChA9fsZbU4C4FyCmnoirK+q6djmf9KtUurLhtVe5NrFoTG7IZTwmA/CFgyoeKJtIN5m9UjExeb+mBYhah3bhkSquRQmQkkP/ZFU1V0dX2ddRGNmAYGggwDocvABtBR/Ctq5jsKXhIKaNnIwJhRvRviqEg8+vQd2i01F3TCeKKrpQGN2EcPEViBRMQKD3PZS3/FNMgIjQ6A5cNChFrVxXCRNLMOIQfOEXEAw9gRbfedjSOgbFwTGYWDOwyZAYDhVXETpwAOGP34RffXGgcOAX7z4HM6p3Yv2134zd1+xbb0HVWQvR8sILgyqXi3CadvzN6Ck606rUrjaKzvUgVsP//uxTePORgdiTS79xAj41uQbBNY3W6ZIdS0RIYGsromNK4dvXiZ5pVSjs7LH+Jkfb5bPQO/NdlHbdhof3fBJbGgZia6bXTceFk97BYzuOHfR3iSc5e/ZCFPW8go0tVYel81VFFFOt4Wy+nu+b32yNPx1hooR4qvnM1j2kGofO60qAxEtHffHFF+MPf/gDamtrdS6R120pQPSmjwJEj5/x1hQgqQWInGFyQ6qumK5lRQkP2cTL4dxwm9rw2smYciNSfZoQIMJBBfLLzyI+ZHPu1tUq2ZvJ5P2anA8V3yObDfnnRnio+xTBEuh+aJAFpK3i1yhEC8raro3hEKvI+tYpg6qeq6f1fb5xiPomIFK0BH2NLwykvl14GkYecwCBqjIU9LWit3AMwv7TrBgQe5E+a1NeeTe6/Bda15O5ennzXzGqPIgZ5XtR2bscHf4lKCg5xyo64dL1SAAAIABJREFUKIc9hmPsRz6CP/yqMZYyWF6XIPl/ue0UtL7+OhqWL0ftokUo/+AH4a+sxJbvftfhOnYmTvjGRnSXfCY2Bvs6sFtB7BYQyQ725f89B8dUlaLiTxst4RGZXIHuD42Cf383/DvaEJlUgWhdCQqbQ/DXt6DnA9XomRJEae/XEQi/iLejtw+ydCyeey6OKnkA73V9DM+uG1xfZU7lVlS0fhqHir6Evb0XYcOBvZgwYjrGVk6yXLNyLSg93ze/Qz1+XWGSzHJgfNOQwQ6TCZAzzzwTf/vb34xa9jN4KxnpmgJEDysFiB4/460pQBIjtcdOmNyQpitA7Btu6UOsHPKkyLnhTpURKp1FZPr+dTKAKQ4iYuTehYNsruWfCBATh8n7NZVyWNVjsYtOt/E9KvajILoPfQVVCISfteI9+tCLaOBE+CJrURR62BIWvQVleHJLdFAl7+l1M3HJ+IdRFP4rOip+hsLIGux+dc6g1LfKutBR8Z+DNvdi5SiKvIKikAS7XxQTJmqepLL5+KLXMSY0kN/fLlLUeWrTvVKC5D/7dGyav3j3uZh/4ZTY78JJPUF1ZsCae8u1GLWgHCHfCYj0VcVEkK+7F8Xb21H0XhN6jhqB0JQKHOrqxvqX9wCtEZwybyTK61vRM28EojVB+Pd0wLe7HT0zq1H8xn7L+iFuVx1LpyP44m50XDwVgdG3IxxchMLeVlS2/oMV61EfOgfbm7sxc/QxVqxHSSCCnnA9drd2YkvDfkwbOQdjq6egtvs6dEeDqA8twZbGZkytm4wx1UeLH11/XZUcqxcy1Bt43fd8ro7fizBRD2HsNax0uWS7fTIBsmDBArz22mvZHlJOXY8CRG86KED0+BlvTQHiToCYfIrtFCCpXLvkQ1k227Jplw1nqlS6mRAgpu8/HQHi5CDCQ2VLSae/ZG8mkwJEdz7sKYRlzMlqithdiuwpRe2xH1Ior73yTvR0vYHt3fOxpfEQpo6cifGVI1AZeQCRwEnYfCgyyAJiVf7etQ/VHxiFgurZCPSuw3s3PoKGZ1+MYaxb3G9d6C0cGXNvcsZYyMlOt6dIbw9qu76IYOiRWF92Ny3nPHUcCmH9K3vw1rJ6nHjRWBx70tuoGFGBkP90RPqqLSGqBIjdelK3aBEqTzgBhRUVsTGoTVvJxlZU/t/G2KXaLp+JjtmV1u/lG1qtuA+xeoirVdeHRqP47QaEZ1T1C+AtLZb1w3egCwhF0XX6GPibuhBY14zItCpEa4uBum0I4hc4FLwGu1q7UX9wC6aNnIoJlUGMaT3TKl7YUnwNtnafjM0Ht2LGyKno7e3Es+tfiI1JVVN/Zu2Dg/6WCy5ZubqBd/uFmW/j9yJM7A+oTFiH3TJN5zx576pYPmd7ChCAAiSdVTXQhgJEj5/x1hQgQydA5MrJXLvsdRy8pNI1HeAt48yEABFR5SYAPx4Hp4+waQFi8n7TFSDO2iUiuEQYJRKsXaEOK8NS/cH11pP0CTVTURIss77QnbEf3cWfwHtdl+OZ9S/H3gBL5pyBWVWtiPiPRqhnP3a39mDLwb0Y3zcCBU+/jsZ7H4Qq8OdDMxqXv3pYYLrEV4gFJOw/HcHISwiEHkNP8EL0+OcjEFkZ+13EgrhnqSOZm1aid2hx74rDYk46fRcMEiCqbTyXJV9X9P2MVk2ITK2Ef3cHAuuaLJEhVo72JRMQOBBC8ev7gGI/oqNK0Ccdlvjh39iMyKxq+Le3IbjqgHWZzvMmI1ruR0FhGKXL9sbiQrqWTLL+Hppdje2Nbw9yt1oy9xwcW3g1JE2x3UVrbPUklPhLUd+wPnb7EhtSU1qHldsHUhKr+iOJYlmMf2Ek6DDfNvDO28j38dtdsOwiP966cBZYlPNzRZgkEiDynXbuuefi5ZcHPq+ytbZz6ToUIHqzQQGix894awoQdwIk3U1kqgmL96TdbVajRH1nQoCYvn83GcCchfSU5SfefYsAcStoUs2JacHllV084aE2CIksM7LR2Lz/PTy79qHY7S2etxQzRh9l/e7MftVadT+e2tyILQ2bY+dLUPSl4/5oxUeE/QtQ2LcPO+55GXvue8DKJiWHvcBftK0N3fX1OPDEExhx8nGo+8A++KtHWi5WwcjLgzJftVf80sq0pSqhO12sUrlpOedMeFS2f25QQL1YTVrK7rRiY+IFsTr7KF3XHMtoJa91XDwN6O2z4jfCR9dCvqxKl21F19kTURDpRfGLu9F95niU/nV7rCsRHfJ3cb8KHVWLznMmomjDIRT0IhYX0icdRfvQdfpYLF/3IOobNg2IirqZuGjSavgjawYFqUttkROmnoFXNg2ODSks8EEsIPL6iPKROHrciYMC9t2s7Uyck88b+OEQP5HMdSmeIMlVYaLSbztdSw8ePGil4H3ssYFkGZlYx7neJwWI3gxRgOjxM96aAsSdAMnEpt6+0ZUNkxIebqp1J1sIJgK8nf173USnWqjJBEg6AsyNoEk1Jvvrpi0gqYouqg2EmjuV0cz5ZDKZAHl6zYOoPzhQGFCejp9z9Ef6A5at+h9SdPBR9BRfjB7fh7ClaQ+eXffX2G1LoPlxvs9bGaJCJVehpO3fsbv+Rqy77nsxATLn1u+iauH57xfI6y+oN7VuFiZW9KCy92lEfUch7P8Qyju+6RAHF6Kw9xACPa9Y13NmwhLB4g8/j3Dxx9BTODcWgJ5szuJZTRJZQOIKmAe2xDJaWWM6qjaWwcrKcFUaQPC9RnSeM9mK95DsVn0lfhStbYp1F543AgVdESvrVftl09E9uwol61tQ9tBAtiuJC+kZWYjIWB+2HdqCZ9cNxK8smXsuZlQ2IRhehjVdV+LZ9QOC44JjrkB3T2es+vrYyonWdVsbdyPy7ga0/20FahcutNzKfJX97mJDdVCADBX5/uumEiCJRpdrrlyJBMimTZtw8803409/+tPQgh7iq1OA6E0ABYgeP+OtKUCGVoDIhlKJDyU83FTrzrYAMS3A4qUglk2MWDK8ZncSFqYFiEnBlYydU3ikql2SjgXEHgvSF22BP/wSirofRHPR1djZXor6A+sxo7YS04JPo7rnN1aWqoLOCAp2HQX/2gKEppdg7/ZV8FW2oPaYHvTWXYatTdsGuRIp8SIWDmkPBKwsTupIZgEpjTyG8taB2iTxAtDjrfd4VhNnDEhSAeO0gNhqeEi8R+e5ExF8pxEFLWGEPzQGxS/sOswCIqLDv7UVkelV6JlSgWhlESru3zxY2Bxdi+4LDgJFvegJ78L2zunY0rAd00dOw5jKSQj4axBoCKH3vb3YOaULDQWHMKJkFEbVTLCG39zVgE0H3rNc6iQLVudLKwalFha3uJpFixKmFDb+pRGnQwqQbFBOfI10BUiuCZNEAmTlypX4/e9/j9tvv31oQQ/x1SlA9CaAAkSPn/HWFCDuBIhpq4JKpas2p6k2nl4m3nQ8hFw7kwLE6XIkT//dZndSXHRrqjj5ZlqAeBUeanzJguMTxYCotnJNpytWW9X/IlK0AP7QSygKPfh+lqrTEVzbhfL7d8WwdHy8BsFx/wgpUojCCjy1aY+jpsUMXDruD5aFo7v4k+govxWB8N8QfL/PiH8+Cnu3I9h9P3qKFlluWnIEetcj2HXXoDokyQLQ470P7PEdXjZiEgNStK3NynwVPmoE+kr9qPxtvwUp9MFR6JlSjsCG/kDyyLgy+CXIvCtinSd/j06qQF8h0DO5Eoj2IvB+ZqzIlEqU/8VmAbloKnrLoygYuwLlkX9FpHAqeoLnIOI/CgUFxVZcTCRwOtqiJ2H3oV7Ut2zBtMoZGD16Gva37caaPW+iqf0gQpEuXHjMFWj90Z2DUgvXLl6Mjn/9MKpLa2Nper18Xuiem+8uTPk+fpm/ZMHbuvNrb2933XJaT9R5OjEm8l0g7Z2f/8899xxefPFF/OAHPzB5O3nXFwWI3pRRgOjxM96aAiQxUns6Q1ObepVCVvpTh3zYSmYjU4fpeAgZl2kBpgSD3LsJy0++CBAlPNOt1i4CJFmRyXhZsOwCxBmMLpv9rprfWhYktYmx4iuc7klHV6H7siZEfEejrOO7WNt54aCaFkvmnI7jCz+DVv9SbO75BOobdmBq3WyMrZqMEl+XLSD9IoRs9UFK265Fd9m/obT9xtjyd2sBifd+8SJA7BsmK/NOVxSBDQcRqG9HdGoVyh/ZFruEWDqKX9iNvqoiK9NVx2XTUdDWA39jt2UB6Zldg8C2Visg3RIvUyv6RcqEcis7lvy9/fIJKB2z0IqDkaxXneXfR3nbl6xryO+rev+EZ9c/G7vm4rmXYErpOpT1PI6WwoVYfaAU3b0lOGpH0SALyPh/vw4vVm+3BIqqom7qs8RNP4k28IlqleRaDZN01owbLtk8J1sCJNE9mRImiQTIQw89hK1bt+Kb3xwoNppNvrlyLQoQvZmgANHjZ7w1BUh2BIh8QMdLpauKCRYVFRmbW9PuSCYFiHMDnijWwSsMJUAkq5aJjC4mLT4yx8qtLF3hoXjoxKbEs4C0V/0GkZKl1vjknzqcAdpS0btrbn/dDIm9iHS9atW02NLYhGkjZ2B8RQGqe+7Bmu4rExbVUxvttqp7EPadEgsiDxVfgah/Dnw9byAcXHpYnRAva0F3MymB9ZEDBzBqZS+Ca5tjlw7NG2EFmvfWFCM6uhQ+KTw4s9oKNI9lwTp/iuWmZdUDOWdSf+D6in3W73KExBXrsgMo7votukv+yfpfVaXvCZyGh/Z8yhGgPhtLx/0uFjezL3gbdoc/hDGFdWhftQqNy5ej/IxTsG10BGvb+rNlDUVWLKcAcaY+rpg/34pRsWcds2qtTK2wUhvHC4j2Mue65+quGd3rm2ifyHXJRN86fXgVJnIf8Swg99xzj/X5dPXVV+sMJ27b++67D++88w6amppwww03YMKEftfHAwcOQK7b3t5uZWu86qqrMHbsWOPX99IhBYgXWoefSwGix894awoQdwIk3U19qhSypi0L1iavt9dKm1taWmpsvehagOzCQwYlwkPuPVUNFLc3IP2LdSDXBIiMS8SMerLnrFrv9v7UeToCRPqwB6NLUcBo8EwU+OtisTfqOk73pLBts6hiLwLh5QgVfxyRwjlW0LhYs5avf+SwQPgLJ29Cacd/oF9ozIav5030BJeit3AEKpuXWpcUC4AIk1DhyV6RDDrf1GbSKcCUBSR80mgrC5aqCRI+qhYlz+3sz4L1vkiRgPTWq+bC1xIeFIwutUW65lbHqpjbg+jjWUAkLfLxhVfFMoeFgpegseS/4S8MxDbtu5rrraxY6hALyISq6TERHs8dRgtwnMZOAeIs/qhSN9uZ9ru4VSCwsTlW+DFa4jM9NFf9mVozri6WoZNyVYAkul03wkTuSdLuVldX4/XXX0dtbS2uuOIK4wQ3b96Muro6/PjHP8bnP//5mAD56U9/ilNPPRUnn3wyVq1ahaeeegrXXXed8et76ZACxAstChA9WlloTQHiToB43dS7zeQ03AWI0+XMXr09WQ0Ur0s/1wSI09IjG0ERW7rWGV0BYomQvj5LcMgaVa5/Kvjfzl09jfSH+hDc2oqArUq4bBadrjTy+7bGDXhu3cODNsRzKreirO2rh7latVf+D6KoQCC62nLt6vGfOKg2SLw1kMp9x9RmMtDWn9kqsP4QeubUoKCntz/24++NsZogYv3omVZlZcEqfW6nlQXLqo4+dwQKW0MIbGu3aofIeeE5NQjNrIJ9ky1Crr9WyjIrDqcNJ2FXWwHqGzZa7muTKjowuu28GIZ9FX/FzrayQVXQ5UV7ZfQxlRMRKOx354xnWXAKEt31qK4ja0UEqPzbdMMNaHnzTZTNmIGOzZtRdeKJmHXLLbHgfBFvktq46L3GWAV5Jc68vu9NnG9qzZgYS7p95JsASXSf6kGNrEt5cPPnP/8ZO3fuxL59+6yHOGKBUP/GjRuHY445xnJJNXF8+9vfxhe+8AVLgLS1teE73/kORISoeJRrr70W3/jGNzBy5EgTl0urDwqQtLDFGtECosfPeGsKEG8CJNkTdvVFZk+lmiqgWteyEG/0pjfjcg2vFqBkwkONORMCxJRFJV1h6LT0yJejbA7kn4xN9zAhQGQMyi1MjSmeACnoa0Iw8iZ8m2ai7P7G2NBls9g9rya2we3fSL9sBVM3F30JB7trBmVtKglE4IuuR0nXrwYFmzeU/BRbu056P5Xv7KQB1PZrSGFDZyFDNTjdzaRl+dnZjsK2HpQ8uxOh40cCBX1AXwF8ezsQPqYWhaHeQbVApH5Ib4kPveVF8LWEEFh3qL+woQSlb2u1BAx6e9F+/uSEokCtG7WJt8RD70EURV5GMPwEuosuxeb26Xhu3aODxJ1UQbdnOXOuLzdPmqWNPd5N/e52rdotIDL+0N83oORgL8r2F6BjdB+6Rhai6OhZUBaQjvMmAX4fAvW2CvLhKFo/Nn1I3LF014xbTpk8bzgIEKclzc7ra1/7Gi6++GKMGTMGe/bswd69e7F//3587GMfw/Tp042gtQuQHTt24O6778ZNN90U61sC4C+77DLMnj3byPXS6YQCJB1qA20oQPT4GW9NAeJOgCTb1KvNg3qq7CWuIRMB40MpQJTwkA2ubEZU8cB4T1qTZXRKZ6GbFDReBUg84SHpleW+TYpMU9m5nGOKJ0BKIsusOIW+p25F0Zq22JSEjh6Bv518IJZ1qRrPWEUHmwOfQX1oCTY3tmHqyHkYV1mHKvQLExENvYW1g1yuVvXdd1i8iGyo4x1uK6XrbiZlkxx8Y3+s3kf7JdNQUFgA/4ZDiMyqQWRUMYpf2WfVB1GHxHZEJpZblhF7/Y+2f5gFX3MY/u2tCB01AuGZ1YgWxf8KdG6+ZN3saNqMv218wio4WOQLwlfgG1wZvW4u5o07Hmv3ru4P+K+chCK/O5HrRpi4zWYkfUlgfUnvK1Ytl8jWb6H8gYFijW0fm4Guo2qsGBB/Qzd8TSGU2+qkSDHHyIggumf1xxhl+xjqAG4T9zvcBchnPvMZiECYO3euCVxx+zApQKRwohzq+0++C9Q/9ZAhHesjBYje9FOA6PEz3poCxJsAsT9hd2460/Hv92pZcLMAlAAxZQ2Qa6ZyQZNr2oPs5cm/fNAm+5AdDgLEjaUnHwSIqsGiXJxUpfFA+EV073kQpQ90xpbevqVj8H/dD7+fdWkpPlD8KxSFnsDb0dsHZ8aaey6OL7g8FsMgLle9KLZS80oQ9lObDx4WL7Jw9sWHPQVXY1EB2zKQRKl6dQSIyv4V2NJi1fsoemM/QmeMR9nD/Sl1xXVIrD++th6UPzhQQb7jQkmzW4TAhiYUr+7feFhuRosnomzZVisrlrhi+Xa1J4x3UOOO9IWxr1UKPG7A2OpJaGjbiw373rUqnzsro581+0Ks2PKcNQ9ymMiAlY4wkTZl0cdR0fZZSDB97/P/gcJDvTH3KhFoyrpRvKMDxa/tG1TMUV5vv3iqJc7sLnap3O3cfBa6OWc4CJBE2aPc3H+unJPMAvLRj34Ud9xxR0aDwE26YP3sZz+z4jDFY0LcXOWffB+r/+VnESSnnHIKvCSgoQDRW60UIHr8jLemAHEnQOQs9YTd/lRb/m6Pa/A6Qak29l77U+ebtAbYBYjTBS1VkH2y8ZtyJ1LXMCloUokGN8JDjStVX17mOFMWkN6egxCxoawV4uIk7j8VrZ9FCP+K6N7L4VsXRNvsMrzpX4t3mlZaw5asS+fNqENJx4/x8J5PDqoNMq1uJpaO+9/Dqp9LO+G3vWnjYfEiuWABKb9vkyUaQsfVIfjaPgTXNg2IiB1tCJ0wqt+ysbm5/2dJx7uxeVBWLKuSelkASsxI4Lo6nC5sioe8l3a1bBnE5OTpZ2P19lctkeGsjN4ZbseKLc/E+s1kBqxkwkQeNFR1fR2+6DZEImegd+cnEVjfisikCisFcXhmVSz4vuKRregdVTrIhU0yrIWnliO4tc2KMwqdOAqFHREE1jZlJUCdAsTLJ1Dmzk328GDJkiV44oknjCZWcd6JXYDIaxL/IQJB/kkhxKefftp1EPqKFSvQ2tpqJUbp6Oiw/snP8vktsS3ynSB/k+ruXlLwU4DorT8KED1+xltTgCRHai+IJJt6eWqhqv66ecqfasJMp4/NxGZcbZDsWabcBtkPNwHiRXioezdp5cqEAJF78nf+5bBq5N2+01AceQVF4WUIBT9iPd3e1rQv5hYkxfFOn3kupo0YhUDkDWxqqcQz6/8Wm/IlDguIs75HONI9KIA6mQtRvKrnUdQctrx0LCDSmT37V+eJoxBoDlubZWfQdMdFUxEtD6CwOzrInahjqVRGb4EIEPj7EHyrMebOpQYrLmxtx1WjuMeHkFRPL/FZgkwebLywcdlgq1DdHNSUjRxUZFBZFcVFy5kBK5GAS/U5lO7rlvtVVxQl2w4isLkdkSnVKPvL4PopXbMqUVBQiMCudvhFuO3usAo7FoSi6JlQhsjoEkt8iPATy5FYn5yCTbKHZeoYDu5L+VyJXs1rsvfuggULIJv6dNyWUq2bP/7xj/j73/9uCYaysjLLUvH973/fijGRNLwiFOTB25VXXgkJfB/KgwJEjz4FiB4/460pQFILEPtTfvkAFJOpCBETRybiNWRcJq0BdgEiT2tUvIAwUCIsHRZiAVF9pNPe2SZVkT4v13BaLeyxLbIGvFi9TAsQtQa93I/zXPv9yb3FK1DYXHpHrEikegIebm5C68qVOPTCi6g560xUzp+PYE2ttYEOR0PY27I9lqVpXOVIlBduGFT9PJ5o8OJqk+pcXQEinOyxD/5dHSiUIoV7OwcFTVsuh0fVWjVAitY2xfBKKt7e6iCiY0rRWxlAQagXhe09liuWOsSFbV91O465txsdF09Fy8xiS4jtatqKMdUT8eKGx2LnilvVlNrZMbe0WI2N559H7VlnIXrUZKxpWes5BkRn7TjblqxrRsV9myzR1VfiP8y9qvvE0Sh+c79VlLEvUIje8gDgK0BhS7i/iOO8EShoD6Psie0J+8hkgDoFiMnVkH5fqQTIa6+9ln7nWW6p1pRcVh5iSiavlpYWa+8wa9Ys6yFmOnsIChC9iaQA0eNnvDUFSGKk8iGiCrTJh4X8nqwKdTqTk4l4DRmHafcm4SBP3+VQsS5261A6927qab66tsl7VskB5GmY+lnuNx2rl0kBYqpAon1MiSwgnb4LrDWvvih9aEbj8lex4frvx6Z75o03omX1atScfDJUwTlrA9+1H8HI3xDs/StC/g8j5DsNfcHRh6XuTWfdJGujI0AGFcqbVY2C7oi1oUYvDguajo4IWi5CvWPKBmfEWjoNfeJiVuxH0YZmhObUIDK5HL0bD6BsfRtaZhVjddFGtKMDl74x23LT2nRuER57909WnMdxk05GWVEltjX2p+IVq1AwUBITIIeWL8fG66+PIZh16y0YsejsIckepcRa2Yt7rIKL1ufOmeNR/OJuS4D59nWi8/zJKH1ye6wYo8TL9PlwWCax9o9MR+kT/W5qtIB4f1cMBwtIIlc4+ftZZ51lWUDy7ZCxr127Fo899hh2795tfX+Ia5fci1hWFi9e7OmWKEA84TrsZAoQPX7GW1OAJBcg8gGiUuma3jCrK5uO11ACRNe6oDZzKiOU9CsWkHSe3MSjLDxNPM3PlABRm/10hYcaV64LEBlfX0RSvr6CotAySIFCEQyRviprY6uyeQWjr+K9Gx9Bw7MvxqZTnsJH2trQsnIlVME5ebGo512Ud3wO/t7+J/+tRf8NFI9AMHSflRErURpd3Q84HQHiLD4o2Zn821rR5yscnPXqqFpEplSgINpnxTjYa31ERxSjaF0TSl7ZC2lfeKATbZdMtTJardnzJsRtTeI5zhn3YRx3fw8khe+zRfJktw81pXXY17obE2qmWuKjAIXY27IDWw72WzjGV0/Fthu/h8Znnx3gv3gxZt5885AIELtgE+uGsGibUoRto1tQf2gjptXMwqTOOoz63YD1p/OsCUAh4N/Xebil5KTRKH5jP7oWjENhRw+K3m1AZFqV5aYWLhtIaBEvO5fOuqEFRIeeubaJ5kFcoz7xiU/gmWcG4p3MXTWzPTU0NODXv/41TjvtNEyaNAm/+c1vLPeudevWWaJEaot4OShAvNA6/FwKED1+xltTgCRHan/Kb+rps/OKpt2lpH8dsSSbOJUVyW71EQuDSfcz0zx17lnNiT2blxJcqbJ5pXpTmkw0YIqZsmgFClutGh5F4ccQCl6GsO9U9PSWxm4pUNiJouir8EffQ2F0B3atmI91N9wee33KV7+KXffcg0hLC2oXL8bYL38T617eg7ee3I4Tzh+PYz+0EeNL/hUh/0XoDYxDSdedVlsVD5LKpSoVW+fr6QoQlQEruGYgvW543gigtw89M6pR9tjAJloKDspTfSk4GB1disJ9HQjNHwVfUxeK1jejZ1YNfHvaLderrpPHIDSpDJG+CPYfehubDu7GtOrZmLynAoGiAMJTq7AztAtt3YfwWv3y2O1Ihqu9zTtQU1aHQ50NViasi4/9R0RWvI3t3x2wQE3+3ncw9pwLhkSAHFYtfuk0rB9zEM9uHqhVsmTGJTj+ns6YBaT9ozOs2A8p7BgvzsPX3YvgxmarAKTUUvEd7LLcsjpmV1ps7MHwCpZuccV8FyDJskd5ff8M5fmJ5mH79u341re+ZRUlzJdDxXSJ0PjLX/6C66+/3rKEPPDAA7jxxhstAXL//fdbP3s5KEC80KIA0aOVhdYUIMNTgKSzUVXCQywe8rNyN1Nf8KaFUjpjTDZbOgLELjxU/RIZX2npwGY83bejaQEiY/WSOcU5bmWRkX4q+p48LPi8y3+hlTo3GH0ZRaFHEQ3MR2FkB3r9kxA9tAn73zseB59/DzWnn4HQvgPY83//ZwmQubfdho17RuD2zz8fu+QX7jgD5yxV2oZjAAAgAElEQVT8J3T6v47SyE9iFpGO8lvQVzjGqgJut4h4FSTO89MVIDLgeBYQcSfquHSatYH2b2pBZFolxP3KEqdvHUT42FoUHuxGgb8QpU8OBF9bqXlLfIhMKkdgV0d/Ffl5ZWiZ6MOT9U8g4C+yrCESxC+WjZc3PTmoxseUutmWpUREiMqENaVuFmaXz0T322vQ+dLrKF3wIRQfdxTqRpspxOZlfccTbGLdeGz0m6hvWh/ralrdXJxbssiybISPqkVhWwi+hm70zKxGYWsY/vrW/kxXwrW4MO4cKCuSEh92ERLvb3ZhYg9aThTATAHiZeYzd26ieZAA8dtvvx133XVX5i5uuGe5F/keeeedd6zsWWLpWL16NZ577jlcc801lgvW66+/jn/7t3/zdGUKEE+4DjuZFhA9fsZbU4C4FyBei9O5nSyTsQvqml4293bhIe0T1TMxPU7TPNNx6XIKDxVcblI0mOxLh5kID9Ve3Krk3qs7r0a8+holPY9axQXV0Vn+PRRGdyLqnwVfz9to7/scmlbuR8PTz6Bq/nwUjR6N0ilTcPeN7+GNR+tj7U66eBq+cvto9EX6UNN1jvX33oIaSH/lbV+OnddU9AQ66gPoePddlB1zDIpmzEBhWVnCJ/uJMmjpCBB7BqweiQHpigC+QvQGC1GAAivgXOIaRIyI6xQifegrKkBfWQDB1QcPr21xyVQEN7dY2Z3UIdmz2oq6sdq/wUplrFLnbmvckDD9rhIj88Z+0IoJ2d+2G00dB1BXPgajKyfAXxhw+1Fj9DynYBPRtb5uP57Z/XjsOqo2iRKKxdvb4d/bCd++DoiFKVJXAt+hbiszVs+0KqtGiNMKpaxIqQbvRpjEc9+S96f8XTemLdX4MvX6cLeAvPTSS3j88cfxk5/8JFMIM9avFCR88MEHMXPmTMsrob6+Hp/+9Kcta8748eNx7rnnero2BYgnXBQgergy35oCJDlj+WJSX1om6znYr2o6G5T07WajKl9c6p6kTarMTrkuQLyKLmfhRHtsi0nRYDLVspt5da5ou/AQcSnzLGMSXuV9T6C85Z9jTcQ1qjtwESrbP+cQJheioC+C7uJPIhQ4FxIMveHb3461m/q1r6HxlVfQfsYX8KsvvBD7+xfuWIjjL54Of2ELiqOvWjEmUoRQKqwr4SOCZM+OO3Dg98ti7Wo/8Qnse/bZQcHt9vtKVENER4Co/uX97m/vge9ANwLrmxCZXYPgW45sV/I0v7MH0ZElCM+ugU8yXdmqe7dfPhFd88ai8oEth22oRdg0HldqFXMUC0hhgQ/toVYE/UHsaNyCSbXTrdgPVYDwzNkXWFXQR1aMi4mN3rY2tL71FhqWL0fdokWxBACZ/8YYuMIgwTanBv4dbeguCKN+Tjc2h7di6siBIHppJXNTurYZ5ff3CzJJudv+8Rnw7++y2kYmV1qV5it/N2BBEXe30KwqRIvTzzroRpjIeOyf9er3bPJM91om1ny61zbZLlExRYmVECvId7/7XZOXy1pfq1atsgSUfH+qtThnzhx86lOf8pxWmAJEb9poAdHjZ7w1BcjQCxAd16FEo0+2UVXCQ87xklLW9DhNCzo3AsSeUjlZGmGTokF422uo6LyJvQgQJTJUIgURHkpMx+6vqBP+8N8Q6H7UCj4P+0+DpMotjSwbZAHpqPgRelGFSOAkRArGY9MNNwwOhl60CCWfuxzRaCkOvNOLt57YjhM+PBlzThuH0rp+NzbhIE+Z5drlvU9YlbMtsRw4DfWPXIqO1e/E0JQcfTQOrlxpBbfPufU7GLHwVETRXwtC7uH5DY/GraJuT3+ZTs2A/nojb6Bw40yU3d9oxR/0VhUheli2q+nolWxO4V6UPboV3SeNtmpbiFtR7+huYOw76KpaipJ3GlH+l/5K6nJIYLq4dYWnV2DHBTXoiYaw7J0/WK9JFqxz5l2AUYG/Y0fnFESjHZhVtR8lPX9FV+A8bGwZjQJfnWUF6XxpxSABaE8AoLO+3LZVFg1fdxS+1giCq/YjOq7cyhwWrQ6iZ0olEO1FUX0ritY2onOCHx0VYZS1BFDzTIN1mfCcmsPia6SOSrTEj+C7DZbLlhQoFKESL/bD7VgTnaf6tK8Z57nxLCbprCvdsSZrP9wFiNTpkED0r3zlK5nEmJG+lSuWZLxas2YN2traMG3aNEydOtWz+JABUoDoTRMFiB4/460pQJIjtT8VM5nNyH5VNxtnrxMfb3Mfz93IS4B1PgiQRPERboWH4mxSNJjsy40AkXuV82S9KouHc9NkFyC+8Ar4ImsQ9R2FsP8kS4AEsAeBnlcRCD+FaOAE+CLrEez+Uyx4vOPtt7H+W9+yYj/kmHbTjXi6apMVt1BZXIPF85aiuqQuJhicG8jCvub3Y0yWIVT0EbSsG42Dv/t9bJlXnnceNv3kJ1b/dYvPxLybLkWo8ORYf/GK8I0snIy1L+3BysfqMf/CaZh7+jiU1fTHa9iPZHEmIryCXb9F31O3omhNW6wwnj3bVY9YPHa3W6JDaoBICloVkO7b0WpVRI9W+9GONlTuC6CwoBC+HW2ITuzPFCWuXM0fm4Lni1ehrmIMGtr2WtYOOabXTcel4/6IgugedJdfi/LWL8SGvi94G/5vTSOWzFuK1h/dOSTZsOyZr6yK5a09Vtavgarn1eiaW2WN2emi1XhWJQ7hAKa9Xm65sYkAcWYY6/7gSLRfOq1frHZGENzWXx39/7P3HVByVGfWdzrnMD055yCNsgSSUEAZgUCAlmSwwOslGXvXsL+xAQfABNu76xxh8YKzCUYEk5RQQjlLo8k55865+z/fa1V192hC93QP6XSdM0ej6VdV731VXfXu+757L+OJXDRtjPZZOFn70Svvo3klY4GfWInvk/Upms8/TwBkrPfRb37zG2i1WmYE+Fnc6Fk7PDzMFl7I0JB+pqokmQAgsd0BCQASW/zivncCgEQOQOJZlvNxApDQyXcskrLxBkqcvwY9kOOxjTU5jxZ4fNoByERZo0iABzc+7l5W491LSrCIhE4TcYnjVXjFMyG2/wN+YRaEnmr0ur+LU0eW4thbjZi/LhvpnjqokmUYKFJjf+8+/jKWZ8zBirz1kDSbIDkzyCaQ9iwxHK2NPM9DWlqKJIWCTTb9NhtcjY2wnj4NeXk5+nbvRs/rr7PjVT79AHIWn4BF/p2LoOVtuCTXoNddiRMdNShOnYFMbR7Ob+/Cz7a+x/fhgRfWY8GmQv7/kzmvM2K15R6IXXvg6HoNildsbF/n/DR4ChQQtpjhrkpB0ogT3lQl4y6Ia0eYWhNJy1ImhNtsGwtg1/qAIQv0+0xwLM+GXyKAqMUIe6UGBwVnGAeEsh7Lyq7C0aYPYXIMY335IswV3g+vaAZ8Aj2kzqApoV18HV5uW8MA3sw2ySeSAeFAxViO5aGywxSH0PIzam+/LBVN3XuRt2wzI6U75qVA6PTxJVkUZ3eBGuK6EXa/+BQiaP7vAh9T8y2lmA5H9Eg9ND6twOTzDkCeffZZzJkzB5s3b47Ha+JjPQaVXe3ZswdnzpxhWRx6xlD51caNG6HX66PuSwKARB2ysB0SACS2+MV97wQAiR6A0IQ5nmn4SFa1o73wnMwqrYDTpJVWXOj3qa680PnjDUDinVEKjWPoZHwqju1c1oKMCGMlp8bzWGMBkGiARygAoes5FgndrH4eavPdbCI+jJ9h+EQf+j88j7R181E3PAe/uifI8fjqC6uw5KpuNBil2NtwFMmqVKQJDahwGuA6Uw1VQQV0QxrIa6zoWidA35+DWQ7d9dfDm5QE1ezZEGoCMqsUa7fJBMvRvRjYtRepq6qQNrMWvtTNEPq6oQ4hxpvVL8BsWw7ziRMY3LUL0rlLsf8jIbb/KQAELr++BPc9t5Yv3xmPNxL63eJKz5y4F97uWyC8IIV7phrCjL9CKD4JnyAddvn9EHSmQ/3nWraSz8q0FOJLvEKIH+LRi+CV+CAe8sFTpIMvVYY9rR+gtuc05iQvwDxnKbQNLtgr1BjOcsMg/hV07t/DIygcNwOyouxq5EgzYTpxAv3vv/+xcUBCla/Gcj0nUnkoYZwDKwQsyCtF2G6Gs1QFd3kK1dFB3GuHYNCOJKEAwlYTPAWasHI1Uh+T7u2CaMgRAIJVBkyHI3qkAGS8Z/AnDUzo+099iOXZHu37ZTraj3cdHnnkEVx77bVYuXLldJx2Wo7JlV4R94PUr+bNm8dKrywWC959912kpaXh9ttvh1qtjur8CQASVbguaZwAILHFL+57JwBI5AAknqU0oWeNNxcitPZ/KpPv8SISb6AUbwAS6lhOx4517PE0iIzXsULvldHAgzPMjOQhMVYGhMjgZu2LrNSJJuIK8zfQePIZ1Dz2X+yQpHb1oXNzmMrV5dcX4lv//Vv02Lbi1KFyVH/Yiy23amB6+c98N9JvuA2pHTo0uw7CevoU/3fiedjMZmjmz0fyspnMj0TsfJvJ8rpFCyHwtcLt6kCLrRTDNhtW6Im4/ga/PxHiWw9tCnMGT3ngMfzsqUFYhh2gDMi8q/N5cvGHdW+NyRsJLbEJcEAChozDkq9iwKFDfV81ZutnItWsgHDED1GdkWU9fGoxczsXXxiCfU1umFcIx/UggGLaWgHhsBOiZhPcM5LRneHA2/Wv4DbpZmRs6+XHY76lGP7SY3C5+9Fir4JvDA6IXJYHu9uKloGLTunafEiEl5aZRXIPTKXNRBmQUMI4U5WyeyBuMUNo9UD5VjA7ZPpSJQRGFyTk9ZGnhmDIAVeVAdIjvWGEfeeMZLhnGSCuN7KytU86AxJtvD4uYPJ5ACATKXndf//9+OpXv4q5c+dGewk+kfY0Fq789dFHH2WqV5T14DZ6hj/55JP48pe/jPz8/Kj6mAAgUYUrAUBiC9f0750AINEDkHisik8HABm96k8PwXj4WHB9jTcAiWdJ23SArniBBopfvI41GmRxksnRZmlGk9DNg0acPjwXR9/uxsJNRZixTA+dtgbV33sTAzsCvh4irRbuO36A5/7zMFR6GXJmGLDx3lysvPxe7Nzz3/jFPedRcUU2vrRpCM7zQUK5cvZcFEqXoK/MGp4Buf02nFL0IFOWgaJsIdLNVwUn45oXYHGuQru5Bbsa/8lKlW6rMiDN9SQrT6JyMAJL57/7NgZ37uT3M6xZi5rkG5FZpkP50kzItQGJWopP+0gTzoe4kZNEbJ6+9JJsJpfd5KRx2bkVN0Bjk4Z5fRDI8IsEkO9sZ2pOApuXgRHOQE/Ya0OS0QXnFZlhE3DjzUVozDKicocP8nPDfN+5Ff6WwTrsvBAoP6NzE+cjTZ3D+jlarpeTuZ3+N0XgDKHKV4wDYvVAXD0E18xkuAoCq7lhvI1CDVRvt/DAgpVirc0Niwcr3RqyMxK7cltQwpkDcdTeqxbDnadmXiHx3mLNgETTn2gUuei4Y5HgR5+PI9FH+wyIpt/T3XYiAEKZgh/96EcoKCiY7m7E/fg//elPWekYkc5DNwImRKrPyMiI6pwJABJVuC5pnMiAxBa/uO+dACCThzT0wR6viWToWWPNBIyWWaVJKW1UfxrPcrHpyNRQH2MBSaGgi1NYiuV4odeFrjUZ/sWjtCEexxqtahVNxmP0XR6azaPfD71ei199eTvf7KsvrMO8awphO306jGxe8ovfwp6kg8zci6S2GihnV0KXfxw/+1Y+Dm9rY8DkWz8phW/Ha/yx0m6+Axp9MZzpQjjammA9eRKSqhmolvfh3NA51m5dxQrME9zFDBBpc0qvR1/Pw/jIcRrNIw3sb1eWrmHXonmgGUWpRcjU5MP47j40PvMMf67ib30LKZs3s5IUmrxxE2bP0DD67E0Y3PMhVMuXQDSnHKrkLIgFErYvtSVpW8uJE7y0bV+eHPt79iJTl4ctA8sh7nVAWj3E2tNE2nl5BnxiATzZCti0gKLDAfl5I5wL05jZHknLUqkSuakr323l++io0mPHwnZcYamC/tWgeaH5lhK059pxtvMomgdq+fbEp1leupGNaTz1r3irRE1E1OfiFbrCz0jjAkGYzC61I+dzv1gA9V/r2HhYuRr5poxynHfNMsCrEiPJ7oWoywq/Ssz+pcwHATPH4gzmETIdZPSPE4CM97aJBJiMp8j1eQIgYz1rr7nmGuYartMFVPA+7duhQ4fYd0GpVDL386GhIaxZs4YUrCCRSHD8+HE0Nzfj1ltvBS1mRrMlAEg00bq0bQKAxBa/uO+dACCThzQUgMTbDZzOPhUAwq0YcVmJ0WpH01EuFm8AEksfxyo/ouMRryFepPZ4XutYjjUdIGs0APnlv76DwyGrz3f/92LMn5ME2+kzkFWUwdrRBonWgbRZtTB1X4u+l/7Of3HS7rwFnY4U/GTrPlb6tOFLpdh4gxauuvMQVJZAUJAPx4lGqNM0kJWUQCgW40DbLtT2neWPUZRSjhuyXoLYfYD9jfxIan7ZANf6+dg3fIhlAublLcGhpl38PuSPAZMVmoYhGPfsg3rWLKhmzIBi1izWhr63stoRKF9vQlN5Hy788PHgpP6ZZ6BbtYrnh1A8jHv2oC7E26T46SfwvjIABEIzIEFOgwXuch2bUHtkgPJAD8TNFtg35IWt5JO0rPy9VlaSxMZ2UxE8Aj9Edj/8Ohkk5waZM3hPuhNv17/Mxnmy7SDj02SJs7DIXQn5BTObfFObVy+8xI8j3hmQUJWrSCf73ASYJo+jfU+cMw2wX5kN4YAdkvNDcM42QODx88RzGgjFx5MshU8n4V3jvblqUAaJAAiVdineDYlfHMnoE628T/5mmP4WkQATrheh76l4chSnf5QBiW66j8YCICtWrMCBAwdi5uJ9HOOgc/zkJz9h73TaaAGrvr4eKpUKKSkpMBqN6O3txezZs3HfffdFPaYEAIntKiYASGzxi/veCQAyeUhDH+zxNuOjs0dTisTVlxIYoP3I24HAx+gXTjyJz1yEpgKUJoruVAAI9YHGztXYhmYB4t2/WEDD6HFP5VhjEenjBbJGA5Ajrx3CL+4+xrpNWYynX5oJ48t/5YeRvvUapBX8EB7J5Wh7rQjWk0HwoJgzBw6vG6L0bNT3JkOeqkLaXD36PM2QObXwDysgybaiw1SHAn0JstPK0G1qC3P+Xlt5NcqUrZC6tsElvBpO8RUY2n8eA2eOw7/+clgVwIhjGE0DQZM6ziF8yNKP1fnrobQnYUjtQ8tgPfLV+ZCeaobSr0CaugzV7/8vBnbt4MdjWLsW1nuvRrIyjSloiYWSS7xNUtauhvYbN+F8dyPmp14Og0UHocXDgEQop4EUr3xyIbwCKqkauURalrgMroVpkJzog6dSArdaC0mrDZAIGfmaJHydJRrsbHsHTQMXsDZ/E4pHUiBtssJXoA0jZlOWpC5jCI391ShMCRj9SUTRraJO9J0cLZ07Ee+Cy5JwAIS+i/JjfWFqYOT87tGIAbmYZYS8OSrA64dwyAFRkymQ0SjSsNKqS5zVry2EVy2BcMQB5TvBDNJ4ZPTJsjZjjfvTDkDGu1ahwISL/+i2nwUPE67PEwGQ5cuXg7IKn5WN3M5pIYzmCpz5IGXA6Yd7R9HCIZWWRbslAEi0EQtvnwAgscUv7nsnAMjkIZ1uABLJRJwDHvTgoo2r/Z9opSve5WLxnuBHA5LGcvMez9siXiVYBBo4gDf5XTJxi2gAyEQKXvG6BqH3HPXc2nME5/dbcPifZqy9Mxf6ppOwnQwSxpXzZkOztBLm4/WQFZVj4C9BcBLq2VH59EPIWlqP/bu/AIHPDZ23A64qFfZ2B3gktK2pvAGZmlz0mmrR1N+AYkMyiqQfwO9egJ43zHA2NcFw222QFBbC3tCA/p07kbpmDfoyxdhV+yZ/nMXFa3Cy9SPmPVKWPhu5ycU8d4IaLU9eAtODT6Ps3x+G3+3GhR8EMyDZjz+CjjIlNDIt+kxdKEytgK7fjZq7AuaItFU+/TUUzP85kyD2iGagyfsA8s8ksVV6rhSL2hHA8KYrMFKlgLrbC4HTFwZQqAzJXSJHkqQGcGogqtMiye0PI62bbylDbcYA9tW9gy/Irkf66z2sXMkvFzGvEW7jJt/0/+kou7okgzGG8hQR9TnBAJf0Rrh8KyBudkF6dhDOBakQDrsgbhhhBHNPtoqRzCW1w8zp3KuTsHIsKmHzZijgWJgG+0w9WwlWbWuC7ET/JWOVVw9D9feAezpto0HRVLI23LE+qwAk9GkTWoIVWhY33j3yaQQmExHpP2sAJNZ3xUT7JwBIbNFNAJDY4hf3vRMAZPKQhgKQeJvxcS+J8Zyy6YXClT5RW5oQU5o6khR7NJPeyaMQXaYmkuNRm8lAUiTAgztXNJmkSPoXz2xXJGAmEung6QAgbOXYMwCB8yBE3nNwC+fBVJ0cZgyYsvWLsJ44ycABlThJi4thq66GtKAAgwcP8p4dlDXI+dJdcHf2wNXcDOX8+TgobETTUJDTUJRaidUVm6GyfB1CbwsjlBP3wynZjNbTt8PV3wfr4gq0GpuRqc+HTm6AXp6CYfsABq296DF2IC+5BL2mdt7Ab+OsW9jvTf1B34hCXQlKdnbAY7WiZOMXMdRfh4G9u6FeswIjBVp4ZEIcagwS2NdUbIb2Qj8G3n8fqhVLIKnKQIbqFSaLa9S9gV3NRiyxzbyEjE4lRC6DFAKTA9qXm5hvCJOd7bAwU0I4PPCpJejLcEHX6YPmhHFMYDG0JQ8uqxUZ7w5Aen6IN0FUvBdc/Z8uJSju+xBJBiRcqvhWJlXszVHzJovmm0qYypVPI0YSkqB6NcDhoY0yIvId7Xw5mpWI/FpJwGywTMdUs6jsKhRohBLfObK7Vy7kjxlJn8f7vn8eAMhoI8WxxjoVYBLJOyaS52gkbcYDIPQM3rRpE/PS+KxsFGuOE0V97uzs5PmYxPmgEmEqzZqKaEACgMR2FyQASGzxi/veCQAyeUhDHxTx9sLgzj56Ih4L8OCO+VkFIJPxW8a7YryyU5x8WuIJQCY6FvWbA5mTSQfHC2SNzj5x4IcmHU63HRZjH6TtA3CdrYZ66WVwDxlhJ8BRWAh3Tw988CN5xUaYTxxD9fcf4y9J2dPfh8yQiuFXX4XPZoNAoYDz/puwuzloEHhl+Sbk6Iqgw3aoTP8Gkv8lZatB4e3oGCiFx+fCh51BrgdlOtRSPdqG6pn8LHEjkhWp0CtT0TXcgjxDCTK1+egzd4aVda0s2Yju4VZka/KQnV7O5GpdXic6hhthdIxgxDqA5pCSrqKUSsxKmYcjPftBZV20rZ+xFjnyHnhE89AyPAiVQ4xMhx7CIScrIfIUayHqsMAxJxnSo72QXVS18iTLYL8qH8rXG/nJdv+N2VC1OCG9MALHymyEAgviOYhaAl4YfqmQJ22HmvONNfkO/S5wE8ZIMyNjtZ9ssj+WWSOXzXDNNDBFMFelnrmZ06Z+uSFcWnemAQKbG+JmEwNYto35YSVmXByIE0OqWqFAY6wSq1BvEi4W0fiFTFT6M/mb4dPRIhIAMhEAo89GA5Sx7qtIFLmmGpHxiPTEl3jggQfwxhtB+e2pnuPj3o+uy7Fjx7B7925YrVbmhk7gg971paWl+PrXvx51lxIAJOqQhe2QACCxxS/ueycAyOQh/bgACLcqEiq1ypkHTmU1Kp4TaIpSvCf4dMxQkDQaeIzHb5noZTpeJmnyq3xpC4ofBwimsn/oPmNdi2iAB3eseAEQOl4o6OUACP2dM+wj4vfsnEUoH3Cj7w/b+OEkb94MgSEZKQ0KeN129Io60H90P1LuuAVDWh/LXORJMqA62wbXvkNQ3nQDhlLFaHf3IFNfgAFLN/KSS1GQnAGHvRbdVheaBnqRrS+AVKhgPA/iQnAbcT0MF7kab58J+IuUZ8xGlq4QVqcJ6ZocaGUBV+GOkSa0DtazDElPSIaEyr7yk0vDxrawYDk7F4ENKuNal7cJ7fY21PSfwQx1BXK6/LAfOIrU1Wugn3c5JL0uiCwB/sfoSbejQgt7kQKG19pZP8YyJ6RSI9eCdGj/UBPMkrRb4CnTQdQaXPm3XlfElLPETUa4i7UBDoVWBo9GBK8suPLPxYeBBnKcrx6CuUyBkRwBZBrtuNwQVrLUbGbyuSQZ7E2RwZ0mn3CyHzr5pwyI1P5/8L//DPwSOcv2MMWvIi18pGTl8jI3c9dsA5JGEc6ZKpYwCeLaYdiXpkO+t4sHbTQeAg/mm0vYsybSLR4ZkHgo3UXa33i3mw4Vr487YzIeAKmpqWESvH/84x/jHbZpOx7Fjklmt7TgD3/4AxYsWMAqFw4fPowrr7ySZXMoqzMVX5MEAIntsiUASGzxi/veCQAyeUjpYcIBgHh7YXBnp8kgvQS5lwk9sAj4TAV4cMeMNwCJhKsyeTTDW3ClSTROLrbRAg/uiPHuXzzL7UKvxVSAx3QCEG5ySfGn30OlXvMNpZh/zAzryaCvh2LuXOhu2gJZoxW6V1rYZNyTr8bpK93Y2fgWf4GvzFoF2e/fhHbDBrhsNsjKS/DPgZ3I1OUiRZ2J7pE25CYXoccYLKWi0izqw84LQcBDGRCFWAWX1wWRQIjukXZk6HLRY2yDXpGCHlMnqJ+5+mIcbfkQYpEETrcD9b1BojwRtuflXYFTbQcZuCEAk6rOYhkUKvPSi/XIPONDa54Fe/p2Y+VwHjqf+AEbC/mfLPvhHyE7NXRJ6RS5fyfZPRicq8AFZTsW2isguTAMT5EWECCMkE0ZEJlbDIE/CaImI2vjyVRAeqwPspNB7gMdkwBIktMLx9LMQLal1QRXhR6OUiJsB0AI92wYPQHvuSEDnXkuFo+xttHtyW+DVKgcZdpLmgtdfkhaTJCcGeQlcCE3Qew5CkFjGQTDiksyOZxiFd0X5i9VImnECemZQVCGxFWgYucgrxBhfYAXon496P1BXBh75aX9mOi5MlnWZqJ9Py8ZkFjfFZE+t7QqJOIAACAASURBVKcLmIwHQI4cOYK//e1v+MUvfhFpFz/xdjQWuh6k3EX9f/DBB3Hw4EEcPXqUeX/s3LkTIyMj2LJlS9R9TQCQqEMWtkMCgMQWv7jvnQAgk4c0FIDEW4o2dDJK5yGd8HitxsVzAk1RioY0PnlUA8ejiTl37KkCj9EAJF5GkfGMHx2LmzDSPTRZqdV48ZtqBiS0LIfrB4FekccDR10d8/sgNStJcTHaHB08ANDI9LhGtACDfwg6mxvuvAPy2fMCHhvNZkiqB2Gfo8MHvo/CMhdFKRVYol8Ef08ffAIBzgnb0WbrRFXOInzU8AE/xFAyOZVBLS1Zj25jK5r7a5Clz4dGrkfLQD2qu44zOd5rZt+G813HoVcYwmR5KcshSBJgb907l0j20jmqO09gXv4VjPcxWtJ3WelV0DhlSPcZMCS3YugXz2FoR4AfkrxiBRYuvAfiJtMlpVPEaXApgGPCanS5u1CsKsNsXylULzcwdSsipwvbzcyorz/DDU27B7oPB+BYlwvZ9nbYrs5nylrKbY18PFgZUrORlWMlef1hIIY4IJaygOEfbTTR0b3WHFbmZJ+pw/4lA5ibu5T/bnHtxypZIsDjyVDAujKLL8UJJXaTcpWwz37RjTwIEIRuP1RvhJ+bCPmkEubTywI8GMqMzDLASZmWiyaCoQCISswIlIhqh+GcoYO3SB+WiYnkORI6tkjLz0KfGePJv0Zz7k+y7XRkQKIZT2jMJyvlCl1QC/19PADywQcfsMn7U089FU2XPtG2HAB5//330drainvuuQfvvvsu2tracO+997Lf29vb2d+j3RIAJNqIhbdPAJDY4hf3vRMAZPKQTgcAGU04DpXUnbxHkbXgJr0EauK1TUYaj+Q8oYpe9DtNxqmPsWR7uPPGo3/cseIVPw5ocWPlsluRxGp0m6mUwZkGbDi/px1H32rEomuLMXNlLjQpChgtRnirqzEcAi70W2+HYEY5Biw9GLL2MX6F22yCtGMQnupaiGdWoC85CQW5cyASBFzGPT43ek2dsLpM2F8f5HrQpF8kkMDlcaAiYy4jkLu9LpaZCDXa4+R0KSMS6mvht9uZClbP229BMm8mOrKSUG2uARnzlaZV4VzXMbSEGPYReFlWugGdIy2wuayQiWWMM5KuzcGwtZ+R1JcUr2PlXOe7joX1gTIkC1EC15ETUM+ZB1t/H2q/HeC2EACZe/M3WOlVqAeIvVKDoWwfRuzDKBzSQ2zzAzIxkoh0LhOyf/0KMctg+LQS+HRSeA0yCIacSHJ7mVyviAwLu6zBMqZyPUAlTI1Gdi7Jqf5wxa0qA4z/UsQDBYHDC3m9KYxHQRkQa54Mad1iVpZF3hvuAg28ksDrN5IMyFhtZHs64SpWo/EqJSt5k4rlGK1QRYR8KbW7LD0sM8KR58cCQLb5KehYp2ZZrnhKCkfy/UpkQCKJ0tTaRAJMRvOQRmdyXnnlFUbi/sY3vjG1TkSxV19fH1588UVYLBbG1bjrrruQmZkZxRECTTkAsm/fPmY4uHXrViYjfPLkSVx99dXYsWMHNBoNbrrppqiPnQAgUYcsbIcEAIktfnHfOwFAJg9pKACJVYVoPKWjeK62cyOaDsJ8LI7eocCD+kj8FsoGcCaKk1+JyVvEE4DEGj8aL5U10Ri58cYKBqMtM6P2h/5Rh19++X0+eF/9/QZcfn0pOoaaIXx9Jxynz/CfyebOgfiqVfCfa8DA7t3QrVyOhlQ7Gu2tjPxNClZsEitWI1cfIBpznJGFBSsgE8vRMdyCjIuTfqfHiaqsBUhT57B2++vfvyT7sKL8GvSOtCMnmdzNA74W9J0b2bcPNSETD5LO3aNrZSCD2rWPNGJP7T/5vhO5vShlBitj5LKIfeYObK9+nXE8aOMATutQfZhk76riqyH91d8ZcZ621Hvvhb2zE8OHDiF90ybotYUQkbxs7TDjOiS5fLDrgN58HzLbRVCeGoG7RMdL67qzlHAuzQxTgOrbWog21QCahutQpC1Ffo8WmnoH43pQCRubvJA8bZYSyn+2wPwvxRB4wYjs3EbZEdvsZP7/BBSIP0L7U99cRRr05/qQ2i1iBPBQRS7KdDgulkDJWiwMnHAcEMqAeKQCltUS9zsgPdQTBny4UjNXlQG2ZAGkNjAyvXNRGpKsHmam6M1TM9dzv0IE8dnBS4CT5bpCBoIu5WxEX3Y1+ZMgshafdQDC9f/jKsGKLKoTt5oMmNDnb731FkhOnUjolCW///77p6QaFU1/f/zjH2Pp0qVYvHgxTpw4AcpgPPLII9EcIqztwMAAOjo6UFRUxDggxGOh4xIBncqvCgoKoj52AoBEHbKwHRIAJLb4xX3vBACZPKShAGSqJTATGehRD+K12h46GppA08OcyO3x2qairDUW8ODME+MNvKbSv/FiM1UAEgo8uFIrjl8RLwBCZWaRqNJQX37xpXdxeFtQCvXy60vw1d9fxTw0srrcsP31NT4Emju/AFtvH1q/+yT/N27iH/TbKGQgY1nJVawNxxmh8qjRxG5Soko1i6EtreTbzchawMqnukZaGQfE7fXA6/NgVvZl8BiNMB8/zsCPdt48WC5cQN9bAV5J8to10D58H3TyFLb6Xtt7Gn6/D510HF0h0hwyePcdgWL2bEhKSpgCF2VfyPSQMi6hxn383/trkKnLQ1qHA94jJ+Hq6mIgRDFvHnSbN8N07BgGdu1CwZfvRfJpD4QjTgh7AiDFsSQD1kUpUFQbIWoMcDoom0Gbu1QbNgknYHHydim2t77Nx3Vd9jUo9edD1GtjJG7yzfCmygGvD7IPO+FcnoUkowv00uQ+9wsA++IMtspK119xuBdJPrBSJwITfkESHIvSGPigLMpota3QEi6atIocPkiaTMylnMrE2DHfah6z1Ax+MEdzT5YC0pMDLA5UbmW6rQx+pRjqP9ey/5MCmGN1Thj4CuWZxMLZiNdzjDvORP4T8T7XdBzvswhAxooDp+RF9x9dE1KOIhI3lSoNDQ2xDDllI7Kzs9m/BBSUSmXcQmo2m/Gd73wHBEI40RnKujz88MNITU2Ny3noXUeAirIfOp1uSsdMAJAphY3fKQFAYotf3PdOAJDJQzoWAKEU7WQlQ6NVnbiV/rH2m+pkd6LeTwdhPhI/C65Po4HHWB4m8QZenyQACQUe9BLjxkvxiNf1pXOYrEb0WTrQ1F+DotQK5OgLIZde+jLm6qpPfdCM/7k1mCn43ofXQ57rQX3PWRSri6DoMjK5XdmcKnjyMzHwP7/B4I6ga7h+zWo03jYLcpcesrZCnPxnC+ZfU4iqFXlQ6qV8BoTGSeTuDE0u2vrrkCfNQtKOo/B19KL0qafQMliL5tZmJDVmoOnAENZ9dQZsqj6mXMVI5Loi2PYdRO2jj/K3dcF//Ac6XnyRAZPyZ5+F7sor2Wf0HWobamB8D8q2zLNnwfanl/n9Uu+6C9JZs4IvHvI6uahOE7oCS+VjpsEu4MQFDO3dB92CBRDY7VDOmwd7by/fFyKiL332RWjfaOezCoJeKzyF4U7l5IpOKk8kRxs6+SdVrNcX14VxZIqTK3CVZBXUfwy6u1u2FDMw465Kgbh6EL40Baj0iUz7aMJvu6YgQGAv1cFZqIa0zniJjC1lSOR1RohazBAQAXwMI0Pu3pA3W6B6pYEBh1DlLj5zQhyOmQZigEHxdgvsK7MAsZCBGwJMxA2hkjHz5gJIGwJAxrlcDqgGIGxVQlTtC0gVt9tYO9NNxXz5WKiy1uRP4elpkQAg0xPXaI86Ho/le9/7HlauXImqqip0dXWxn56eHmzYsGFKGYTx+kX8jBdeeAFPPPEE3+TZZ5/FjTfeiPLy8miHw7fnnjn0B6406/nnn2cAaubMmVEfNwFAog5Z2A4JABJb/OK+dwKATB7SUAASSQkMN/Gm0ht66EwEPLizTwdYiDdhnvoaibJWJMCDG3e8Jubc8aIBSJNd+UivyUTAI97jpPupvvc8doWoRK2dcQOK02aEZURcIxZW2sM8Jyq1GFCJsffVRsxalwJvpgWtQw3I1uUz/oZCooJYKEWvsQMaoRKG6gHUfy/oGl701ONoKBIi6UwunrvnQz5s9z2/GnOvzmX/7zV3YsjaC5VMA7VQDc/uw+h+7vcB4PDMM9CtWsWyEafe6cBv794JlV6Gu16ehVPmINAhErnvd6+i782g27lhzRooiouhKCiAesECdi6WIdm1C4ZVqyCYVRqQ991VA3uIcztlMAxf/GLQ38Bmg6uhAdYzZ6C8mCFJUijY8UZ27w4DPWVPPAH9lVei4fvfDwNiZd/8DpJLF0DhEDI+yHhO5d4UORQfdgTLn2gSX6lHTXo/dtQH/QzWlm5G1UHpmApY1C+SpKXsBCdzSypY5DkiOTvIAIltTS5kVCp1bpC/Js6qZHRvMMDQ7oe4wQhvvia8hOvmUthm6FipFSlRUakUlU4RkBBfGIJ9bS7v4s58Oq4rhN/nh8DuZaDKviY3zMGdMhs+uRC2OQRSAsBQ7n4zzN/F5f5XyJ/PhvW6Qtgrp7byO9l3daqff14ASLyES6Yax1j3Gw+A/Md//AfjYlx22WWxnmLC/acLgISelAMgjz76KO644w7MmDEj6jElAEjUIUsAkNhCNr17JwDI5PEdC4CMpbQ0mlwdjapTpJPdyXsbbDFdAGQ8b4xogEe8J+bc8SIBSJHGcLJrEgnwiPc46SW2/fw/why/SW3qMs08GN/bAUVZGVvFFzdaoHulmR+qcXMu6nb/Bb5b12F387u8z4XjwDGoViyFpLIEST398F9ogHzWbMZ/GProIySvuhKuGbmwSLzY8VgXjmwLSqYu2lyILf8zg5VEURajZbAemdpcRjTXijTw/f4N6BcvZsDBq5BgxD6A1/7zAo6+0YSKK7Ix/0kv2owhDukplVgsqED7//4vTKdP8+BFv3o1DyQILDT+8IdQlpTA2tCAvPvugyQlBbLUVPQ/9xw/3tEZEOeZM+h/6aVLPqfvdv23vx0GNAxr17KMzfCuXWHAJP/J70CweC5K37dDem5sp/LhLfkQJYmgfjXA26BJ/MiWEjhylLBeOIZBLdDm7EKBuhB5/iyo+5L4CT8DV7eVQTjiYrK75AzuJZdwUoianw5hjwWSFksQkJTrWDZC9XI9P67eGzJYGVbGa93sb5TJIH4IqUwR0CDZX0e+6lIi+sYCyD7sgPmOcoh6bJdkOLxZKvj0kku5HTMNcKzMgs0gZuCDfnS2+yB1BmWUneLNcAz/BJ5U2ZQVriL9zkbbbjz1pWiP80m1/6xzWChuE5WREfj47ne/G1MWIpJrE88SrLE8bLjSMnp3PvTQQ8yEMC8vL5KuhbVJAJCoQ5YAILGFbHr3TgCQyOIbakY4lms5reDQhJU2ynhwHIfIjg7eCZuATby2WAnzY/VjLM4GvUA4sEP7jFVqNd6YJpvkRxuLjwOARAM8QgHIVPg4oeVCDpcNXSNtsLksl6hNKX0S+F7YBkVJCfTLlsFw2An5RVdu6oOjQoPzfe+jYU0OuiydYT4X9Hnp44/DsX8/T8I2bNkCZ3c3XFfOx/aGAG8ht2MlXvzKQf6S3PXrJZDOH0CGNjeM0L0yaxXUrSNIWbAYAnWAXM0R0At7V2H/iy0Y7rLgpufKwjIgK8uvQc9IO/MI0SQpIO+3QZ1bCKFGw45BL/HOt7fBWqhHh38AOUkpUDYOwvT+TmTceCPkGRmwnjjBywkTB4SbFA/84Q+wnTzJ9z00Q2I9dQo13/oWAzy0cRkbr8nEZ1tkyxahIxOMjH+X6lboX2lhbTmncmHtEExlUghUCmjOB0GCs0yHl99sRN7idFRkGDH4yiuQV1YivfJK6N7oDFPVIgdxgcsbLrt7YyH8oiRIq43MYVzgDP/c9KVKCMxuiGoGMVIqRaO2D/OPaiA/P8KP1Tk3BT6FGNKT/czYkIz+xnIodyzPhE8lgqjLBtnBHp7jQcR3r14KwZADSUiCahQpHh4fIBPBXqCCR5oEle8dqM3/xp/frHkBNuE1/P8nK12N9jsfS/sEAIklevHZdyIAcsMNN+D3v/890tLS4nOyCY5C/I8lS5awn+PHj4MkgGMhoY93qq997Wt4/PHHYTAEsobRbAkAEk20Lm2bKMGKLX5x3zsBQCILaSgA4XgG9LepTrxHn5VzPyduSby26QIgnF9JLMCDG+N0AJB4uZePziBNBXjEMk6PxQJ7TQ2sFz06bFlavF7zN4ylNuVy2JD5m10wHj+Oku9+F5l5i/gMCK3CD1+VitM//x6k/3knGvxdKP7rWQzv3MXfaobVq6HLyYGjIUBW115zDdwOBwYPfgT5FYvgLcmBwZmD+vMmHNnRitkbc+AsaMWMkpmo7j4ZlpEp1JWwvmRs2cJKr+h+IaK6WChGujoXFqcRMo8WWkkqnLIRxg3JSy5Gt7GNSeXSRhK+cpcQRfnz+OwH/b1nsAk7G/7Jq1qtyl8P00PPQFlezrIWXBZO7PIzt2/mDl6uhFvpQvevfsaPlzIkSZWlAYJ6fy3yNQWQnmiCQqFhGZtQ0HOq/SPU956DUqZmrulLM1eiwpINGYGCmXoMZQODvmGM2AZwxUcGPjtCZVJenQQHhEk4sasNdz69CL6eQcjccshPjfDcDLo+jsszmFyuYmcHpOdDSqpmGiCwuSFuNo3prk4lV86qFLTrR/BBS6B07TbpZmRs6+XHSmVSxCMhngenojWeFK87T8VUsEg6mDIvHM/DWaGDwOuHuN4YVhIm7LVDfqCLnYuT2hX4hyH1HoDE+RZc0mvhEC6FxxduLjiWgMInAUwSACReb5upH2eiLM7q1auZbG08hVTG6ykRxEmG12q1MhneO++8E1lZWVEPjLgktJCoVquhUqnYv0SYp9/ph0qwfvrTn7I20W4JABJtxMLbJwBIbPGL+94JABJZSEcDEPo/p9wRzYr/eGebDrAwVcWuiSLCKWvR+Dllp1jGH+8ysXiqanF9o5cfBxBHk8sju3vAu7xH8iKlFzL9EPDoe+EF/hTq22/B2+7DkIpkWJC/DDW9p9mEmNSplicvgenBp9kqPvEmSr/9PYgaRyC2+gCpCOLaIVhSvejxdcBWlQnp6Ra0fi9o7hWaAaHMgWzZMtQ/HuSBlD3xfZSeDKzY0cTassiApkwj0tXZrLQqVOqW60vyypUofuwxxoNqH6aSJD/MjhHmXJ6hyUa6Nhc2p4X5jdDknjgoHAAhbxCDIhVz865gsQioVrWjqb8a6ZpsDNsGWNui5DJk/GoHD3a4yYyqzgz134OlSYM35sIs6IPj1BkoyXCxpATtjk7mB8LFMNSDJPS69po7MGjp4futlulYJmpJ8Vq0DtZje/VrzCBxSeYKVI3khpHCafLvFDrRPdII/eIFkLc5oXk7nKBO52KGhulySPrsYRkQ+rt8R3vA3E8uCuNosEn/jUUQN5thmqVCu7QfTaZ6LEi9HKn9UkYIJ7I6eZJITw8wMEEqWo7ZKRANO5li12gyufOydMh3dzDfEoHRxWdBbKtzAmaE5wYDUsEErrQSCI0uBo5oI87KRCRzLps3+t/QWI8GJtMNSj7rAOSzzmGhaz8RAFm+fDnz0Pgsbb/73e8YV5IqJehf+qH3Jr0vOYnwX/7yl1MaUgKATCls/E4JABJb/OK+dwKARBZSmniGroBzWYB46a9PB1iYimndRNGg8dMEnyPTUZkZZRtimSR8mgEI5+FB454q8ODiGWmmx202w15by5zJpcXFcLW3w3L4MDuMfO5cHJkfMP8j0z2ZRIG2wQbkqHLhf+ND9L8YcCsvf/pppG7YgGNNe7HQWAL9q4FyIdqMWwrgK6hBkvMC+s5kYGD3UVB5kbc4GwYL4DhzDtIrLkfvi38O40WkrFmLhaV3BCebM/XovzH3omN5LXINxXC5HZDY3AHlK4cDwpvWo9XSyuRv0zW5rAzrQH3Qj4RKrg417uKzGaGO6PS7WqJFbnIJAx/tI03YUxuUsOXaLk5bjJROJ1Rz5kCk0bB7k7ax3MEPLTMyqV9qQy7e/ro+KKtNMJZKcVJaD7PAilUVm8MyLnSslqFa7LoQJI+Ta7pcrERecgkoO3Ku8xg7J2UeNGZJwAcjRCXKb3PgyP5fIPfuu5FZr4TsHHE60nincHuRHFaFjTmFawQpkPQ4mOwuMw9MlUPz0gX++vVvLUaS1QVlrQWeUj0krRbmUE6b5YYieNIVEA05IWoYYU7s/iRA9Vojr6JluaEYSR4vlG+1MEK55PwgDzLMt5RBXD8MyYXhS2R4TV8oYxkQVQioI9NB+XutDBzRxmVAInuiBlt9ksAkAUCivVrxb/95AyAEMrgx0e/cD70DOCCSn58/pUAmAMiUwsbvlAAgscUv7nsnAMjkIQ1VteIyIfRvrJ4OoWeON1igY0ei2DX56APH4TIAXE09reTHAjy488a79Cweqlqh46V+0lhjBZqRAC0quSKVpoG//IW/LMmbN2Nk+3bGzdBtuRF9KQL4dCoIBEK2+l6gLYLsbDskniTQ/kTITl68GCIVLUmfgWKbHtJzAW6DuUqBHnkX+g/tRdqVFUiaswgNjgFUdx5nJoMqqRYKjwHOeiVynW3o+p+gF0jFE0+h+GQyP9kcvjEPDTlG7AxR41pdfA2S/voBlGVlsCwowK7GoPTvptlfQHXXCTQNBCVnCZg4PHaQAzplEKqyF0AoEEEilEKdpITBkAuxy4c+Zx/O954Kcz2nfWdmLYBOkUo3aJjXR7o6D/oGB58BoRX7/pty0JVsQYbAwHgdg7t2IXXBMqR7cqA+ZwO5hzdnG1GSOisMgHDlY039QRBApP9VuRshb7VCfH4QwyViNOr6Mf+oFtIm8yUT+8HVWhx55t9BGaGKzfdA+3KAyM+Vxp14+iE42ttR8thjGJmdg1JLFiQCCZI8PghsHvhlIojqhhjH46SkDoa0HCRBgKoDIshPDPD3imN+Kst4hIGE64oAn58popGKlrNSD9UbTaxMLBQEuWalwFWggqTdwvgfBHx8yTIIOyzMH8RVEODySFrMLLPinpHMeCGURRE1m0BGha5CdVxJ5hMBE25BiPoU+hyK9pn0eQAgFIPQDH0kz/RPU5vxsjg0cacSrI8++ujT1N1PtC8JABJb+BMAJLb4xX3vBACZPKTchJRb8Y/HJHf0WeMFFkKPyx1zLMWuyUcdDjy4DAC9FOiFMZX61bHOGe/Ss1iuTSjwoPFSdodWrciRN9ZtLAASSjCn49vq62Has4dlP7hNMXcuxOnp8CclYfjkSfjTk+G9egn21AUn91zJU9ZDX4NsbhWSqpsxuHMH0tbNRnryZVC92s8mu03lfbjww2BZVf6T34VxdiYONHzAAACZCPbsS8JLDxzCujsKcdk8F/w1h5G6ehFE5fMgHwC0dQ4Yy2Rw5CtwpPejMF8LjvtBfe/56jo0DQYUrujYc3IXQyFR4sOQLAaXASlIKYVekYI+UxeKUrKRJfYiyaqGKGsG3I2NOOypgV6dhkNNQc7K2sobkJdcyo7PObHTeQhIVWUtQr4sn8nMEkHbLxUy7oJzlgE9nSdQ+1jQZ6Tym4+jqDYNrmINmq9WIlWVxWdR6NhChxfNxnrsaAhKA6+bsQXlPYawif7AllwIxWLo/9YUQiw3w1yuQP/5A2j4+f+g7JmnIZ47C7pOH5Q1FthyRGjZtw0d//gbGwepb3VtXYwsXR5Ku5OR+o8At4KunfHWYuz3HWOeJ+nSdFgOnUKmIh/69/v5e8X4bzPHkOU1wJOlhCdHBU+ajB0r6XQXUv7RwR976OZ8+IuIa+JhvBnxRYd0T5qcZVTIvTx0C/Xv4NR96PNoJ/9T+U4REHdflFPmDCf9o4xWoynj4spoP6sT+M86gGL3t8/HQP9oKeHh4WFs3boV77333lRulc/lPgkAEttlTQCQ2OIX970TACSykIa+oGKZ5I53tljBwnjHHa3YFcloxyJbcxmASFbyIzkH12Y6AAj1PxKuBdeH0cCDOC00Xnox0rWOhzBAaNzY+YhgfrHUijgJwmJyF2+GrtcG859DDPXuvBM+sZiZ8dmam5HyX99GraM5PBtwkfQtzsqE+rIFaP5O0Exr/vO/hsyfAemQD2d2/BbGo0d5CVvtokVwfuU6JCUJ0GPswNzcJXj5wTM4si0gIUteHevvmY0bHxTjg7oGdI60swk+cSYKDGXISS4KU7/igBDtq/v197GnezczJuTARXnmHJgdJnQMNzHlrBRlOobtRLj2h5VmrS9fhDyVCW22AqhbHRjUAN0Yhl6ZyngieQYqy3IxQJOpzcfRlg+hUyRDJBAzV/RsfQEKDRUskxJKtibfjmMNf8JAiMliyuq1WDDrTliXpGIwzYP0eiBJLISzILCaT/t7WgbQVOFAo6MJhcnlyEorhuG1tjD/DftMPc5d4UTJcBpk1SMwVirQqOmDRCrl5YiVlxVDLGqA0rMTFtFVMB7xovbhR/ivS8lT38epbDOSVelYcTA1XMmqysDUq+je4eSBc268FXmLroKqTwjHZRlMIUtgcYfL+t5SCscMPTsHB3hNQ71Qtbt4MGnOFECl0ELd7gkDVZGUVHGlJrFmCCN9ZownpzzVMq4EAIk08tPXbjwQ1dzczNzJ//73v0/fyT9jR04AkNguWAKAxBa/uO+dACCRhTTUCyTSev7IjhxsNRWwMNk5onEGHwt4jF6VinfJVLy5L9Fcm/GAB7eCGs++cXETe71wdnXB3d3NJFm5Tb/1Dmxz7EepphjFVi1woRHirGxI8/Nhb2vDwO7d0C9dipEKUo5CWDaAm/gXP/MEBl5/C4M7dvLHTbvuaqR8/Q6c7a7HTJMBSf1DcHd0QJyTA1FGOoZyVGgdqkdpehXz8zj7bjd+9eUgT+OBF9bjyjUv4IJ1NT6oDXAdaCPTwExNLl/6lK8ugPfl9zH4t9fY55W/p2vAXwAAIABJREFU/R3MegmsUif2NwSPR0RvkhEmRawBSx+sThOEScKw0qzilGJszGvBa03ZmJEyA8rjzTBVZKLfb0ReShl21bzJ80aumf0FdozWwQaka7J4cvq6gmtR4s8PywjQ6n9j1QBqnvouP46Kx59CRs58SC4MwVymgDEDSD5jgyg7BY4ZOmheaQwnXuulIKNBv0ocRjYn/42d0qOYl7cMwiQBI8hniTOQLcqCP1mBIdcgbM5etAw0otigR5F0Oxyua2A662GmiimrVsFemgGr1EOpBBR1aMKUrAgMtOXamMeK/x+70PP3l5ngADm0Z2/diqJ5VzPwwJdVXSyd8uQoIe6gUrEhuGcmM2Bl9VvQa+rAsHMIGqcIvncPIHPlWmQ1aEaZGoaTysd61nxcAIT7Tg69/DK8AwNwdXWxssTRhpPUx9AMTSTAhNtnLGWuyZ6vn/Tnn5cMCMVxdBbq5MmTzJ2cSN2ftY3jSca73wkAEltEEwAktvjFfe8EAIkspKEAJN5ZAK4H0YCFyHoNRHLMSIAHd754ZyziOcmnPkYCQEZzWsZT8Ypn3yhujsFBmA8fhr29HTKxOKzUSj53Do7Ml/B8iNlZC5F9wQyf14vGJ4NcjOKnnmCu5Bq5jmUDyNBOdrIRSrkVmrml6D/Qi6ZnnmWXK+3aa6GdNwfDHx0CrfTLNBr0/+VP/K2TsnUrm8BRaaHf6oLbZEG3bQTNx0w4814XFl5bjIqlGUjV7IDX/hGanOvRODiEwtQSZGjKIRXL2ao6fTc85Jlx7BibTKeuWIUMYzqkHinemFONxqFw3kdF5lwY7cOgl4EffpapCC3NogxIlmIIfz3bhWxdLpaLi2A+XgvN8uXYazzKl32xsrHCFWHZE46cnqPJx+bTM+CqMkD1akBamLae27Iw1HEeI3v2I2X1ahgyKmH4W1vw8xsy0J1iQ+VRCZwL0yE0ucKM/jhJWyJ4uwvUENeNwFGhRYPdhe7WdizZ0AlV0nvweK6C8GQZJEdcOPWvKlh8VnzU8AF/HhrjDMWbsKh+xksHt4804GjzHiwv2wih3Ye0XjFUtTY4Z+gwmOnDMIwwO43oG+lAtk+PpO1HGOCr+s1vwsBDQNY3HSNFHqgtaub5wW0EZAY97ejdtg3O3l5m5khAJu266zDz+vs/dRmQUC+WrJtvhsDthu3sWUgLC+Hu6WGeKtJZs9jwrMNO1OzvwrG3m7BwUxEqlmVBqZeO+ajkgMlYpnEcIAn9d/TvkT5/p7vd5xmA7Nmzh3lx/OhHP5ruMMbt+GRoSECKZHfHAiGxXq8EAIntUiUASGzxi/veCQASWUg/qwBkImO+aIDHdAGQeHNfJgKHHPCgNrRNJh8cjTBA6Err6JVU1/AwjGfOwO/xoOGpgPRt6X/+J0whtc36rbdjm+MA+2xWziIoJWq0DTUiT5IJ/5t7+MxC8to1UH3jbjT116AsLQ9Zwl2QCcwQeNvh84pQ9/p8SDMyYDxxHNq5s1H/5NPsmNoFC5B22WXh/JJ580AgxGexYOTAQQzs/RCyKxaiO0eCgSQj41JkaQogFpiYr4PYtQtO2c2w+MrRZepH80AtU7jK1ORBIgpo2tPYSRVJQlyC+hGcu9wRxp/gAMKKso2wua1wuKzI1OXD7rKgub8GxSk5SFMI0Ga04UjrCawono0SrQ8O0ZVsok6TdI74nqnLg1ykCMuekHwvyRLPUlRh9lt+2K8pgLDfzlSlSIbWmibCoaSTWFK8jh2Py3Bw97d9pg77F/djiWUGFG82w3JrKZJsnoCkbaEGok5rUHXqphT4CvtwdK8Mz3/9FH74ngT5mq/zDxSb/zcQbZ+NPVf0YdDWH1Y2R1metcXp+LDFihx9IStJo63H1MEyRHKxAhaniTnLaxUpqO89yyY2YSpiWauQ0uWCavZsqDu8YeBhZEMqumt2o0i1AtLzQ3yfSCq31nWIXaeWn/+c/3v5s8/CcPlynmTOEc+pDG2ibSoZkNAMxWRPX3K+r330UZbpGf2dSbn9dkgrK5F00Tvp+FvN+NW/BUAelQ9+7cUNKF2cwWdExjovLQxw5WOhnKzRmROun9HwSyYbWzw+/6yXkFEMxpuUv/HGG6itrcVjjz0Wj1BN6zG4hZj9+/fj8OHDuOOOO5BO3L2LCzQcGDly5AiT5V2xYsWU+pMAIFMKG79TAoDEFr+4750AIJGFNBSAxDsLwPUgni7eEx2THobcRJ0z7YuUhBnPrAD18eMAINECDy52kfbN7rQy/gaBgtzkYrg8TiilKjaxJKnc/nMn0S+woMPdjWx/Mlu5Fjt9MCxZAmdrC1BRBFOGAjJNMqwuM7w+b9hEM9TjI/vxR9BZpsLSknVwO06iw+RA00A3svQF0MrUUJoEUOhTIdWIUfPokxi4WI6VdtcdSFt0OYb//Ff+hiczPvmcORjatQu1jwS5CHSOPboAl2Jl6SZ2jUInaRzpmztQqH/GaIKyy2ZDj6kNjcO1KNSVsrEdbN+NlRWbYLIN8t4aGdo8BkJaBuqRo85HQZcaIokEngIfkhQSePzaQKbA5US3pR3NQ7XITS5ialAf1gXleZeVboDKLkFBtRjKPi9zACcFKPKtEPbY4CxSofEqOdLUOaz7iuqRsAwHqWG15dhQdV4Dxa4O3tuC2spqR6D+Sx3bj3lyfK0NEu9L+MH/uxvGfi+eeOENKP1BsrpLtBm+HY+gaY0Eg45+RvbntrUVV8HjteNg8xEGmNZUXI9SWw6k5wfgnmGAO00Gs8OLC/s62Yr+yjsr0GM4Hga2SIp5VcV1AQKvwwdJwzAk1cOw54ow1HEKpjPHUbj5PmjfDpDZaaMMSM/gOQzt3QtFURHMp08zdS7t0qVh5ouhk/GJnpDRAJCAl0vbuMCVOyd3D9G/9d/+NpODJgCdumAB7OfO8d2h7B0D0D4fAxkvPrgHvS0m5MxIRkqOGkmCJCh1Upzd2Yb567KQ7qmHJl0dZjQZCkDGG2ckZVyfFDD5PACQ8cbwxz/+kWXwH3jggche0p9gKw5gvPzyy9i1axeqqqqwZcsWZGZmsl5x/h9/+tOfGD/xpptumlJvEwBkSmFLAJDYwjZ9eycASGSxDQUg8Z6Ecz2Ip4neWMeMBXhwx4smKxBJZLlJ/lSVukaf4xKyt8fDwBZtk2U8Rh8rEgBCbRp6z2NH9ev87twq//Kyq1CcNgM1dR9hT9du/vMrU5fD+8I2qDeth2dWIQ417mST6RR1Bup6zzLVqJaBgIIUbUWGcpQeHACy0jBSpIUmJRsFKWVoGqjGzuqgPwWdV+tTocSaCU+BFv0HdjNgQavHmh8/iuEkC+OX+KsbIJtTBXdOOjTJGWj53pMY2L6dP59+zWo03jYLMzLnI0dbHMhqCATs8zFlaVMrsSRrI87tbr+k/IVI3JRJ4ABA31Up2Kc4zVb8J/IEWZ91Nea+7Ibtumw4KyXwQsfOL+2woUnQjjPDJwNk+JRSxkVpG2pCYWo5spS50DQ42Kq/u0gLCMAb+zE1qVuK4FQAgjQthHYvRCMu+AYtkNeYYClXoC/dhX7vIBaMFDHlLFepFvZK3cXMjhciMuM71Q/n3FTIkh+C2L0H2/f+L/7vm42XZEAssufhb7wCktoRxifpTrPjzOAJFBkqkOnQI/ngSJgHSbI8BcleDYpqZBAUp+JA7VD4iv7ORdjXEgRbK8qvgVamZ6C1ZaAOhaoCpPu1GPrt84wfQVv2Vx+CwqFkGRwuq+FyW5kU8fChQ0jbuBGy4mII1QGZ3Wg3DoCM5oqNdZyxgCtlzzhQQvc0+atc6D7JZ9bc52pQ861vMY+X0m9+EyPbtvFj0956Bw4eFSG9WIO8Wam4sL8TJ99rwZx1+Wg7O4CUPDX+9r2ghOvdz8yB5JXHUfzNb0K3ahXrYiQAZLyYfBqASSz9j/ZaT1f78cZAZn2pqaksm/Bp3zgA8txzz0Gv17MsR1dXF774xS8yN3UOgNDn5AGyYcOGKQ0pAUCmFDZ+p0QGJLb4xX3vBACJLKRjARBSR4qn9OR0ARBuRZF7CHIqT5GNPLxVJJPyaI8bT/I9jZHiSB4txAehLVrgwfU/krFSmw/OvYZQnwiuDEgulGOJfC4O2k/xkrSkCpWiykT3SCuydPnw+DzoMraiNH0WGvuqGQdkXt6SMJL5leWbYJCnYdDex4wHC1LLkaMvxv76dy85b4o8FSt3G+BYmglHrh/GY0dhrW9F7ZIU1gdOqpY8PyxOI2ZlXQbV6bawDEj+k9+BZ0E50rQ5EEIUBkAoNmNNJEeOSvGzrUG5TCKvL7y26NISpyo92q/R4VQbSfiO7QlC5yhOrsD1R8rhUwrhuHEETsFC1g/FgR7803AkTP63PH0O1jovB5VP0URA5PFD1OeE7EQfnIvSIeq3w+6xoyXbjKaRehQri5GeUQRdvYOBozO3ynDBXgORUAyP141KeQVm/80B28Z8GMvk6LK2s1X7opQ8FMjPQSbWwCleBql7P1Tmf0O//cs4efxquF0SLFnfBaXgXZhF6yAaXgzd77r5rwMZ/XkMUoj77OG8lBsyUJ85hGPNe1k2hMBXeXcqfvzSORzeFuRv3PXzK5C/ToLm/lqkabNhsg9DI9OG3Sur8jcgo80Ke309FLNmQVZZCVx8To3OakRTCjXRJJwZOwonLtUaD7jOyJyHt88EfW848E7AkrJi7YONyNcVQZokRd1wNfI1RdC1GyEWKNFp0mDHnxoxY0U25CoJnnsgKL7wxR+uQNOJXhz4exDIL9qUj1XytyHS61F6sRSSFifiqeA1lTIuiu1U3yOfZwDy1FNPYdGiRdi0aVO0r5SPvT0HQIivQuBizpw5+PnPf87eRbfeeitycwMllj/+8Y+xePFiLF26dEp9TACQKYUtAUBiC9v07Z0AIJHFNhSARDIxjeyo4a3iLe9LD0V6ALISDaGQTcQjLbWaaMJBafF4gq94ARAaJ+deTtdrqsBjNACZKDszXgakuvMEluWvhunHL0Dy9Tuwq/5tNvkfDS5WVVzLVn0JfOiVKWwyyaRrlanoM3Yiz1CMDFUKLG4Ltle/w6s/kReF32/FjgvBST/LgLiUKD0nwojBDGv9WahmZUJZ6EKjS4vttcHVYG6iR2VWV+asgfHIEfSTGtPq1dAsqIJSfhwS5z/gkmyCQ3QF/EnJ/C1xSSmNNh//95X9YZPly68vwX3PrYW01QLVX+tC3LLLYK/UXuIuTiDrYONOfnxcBsR+rRa+srNwiK9n97G8zog6ZSe2h2QCSPGq1JoFd5kPUs9+iJ1vwyXdBJdoOSQXAPn2dpy+QYjtbcHswdqK61F1QALZiX6MXK7H4BIPtNIzUHt3wO3fCPHBEvgdapxb4sSOumCWicjjc4X3w6b+EbyCDIi8NRC59sEluhEe6wI0+E2o7jkGsVCCG87OukRK11WZzNzHpdVBXoajKhkHrxjC4aZAlozA19rUDTh0sIvPgNDf73t+NWZfoUGttQHnuk8wSeRLsmUpFVjYo2VZDWtzM/o/+IBdU/WCBXyJFXchxwIg0YKS2DIgNzBJ5tqeoO8NgXef34ssbV4YsOLuV65crXePEL+9fwcbSsUV2VAbZDj6ZkA+mrYF1xTh8htK8OuLnBD6G5cBqfyv/4LQ72emn5yXiCAOXj8TPfOnAkwiASWfZwDy8MMPszKmZcuWTeV1+rHuwwGQ73//+7j++usxa9YsWK1WvPjii+zfm2++GQUFBXj66adx7bXXYvbs2VPqXwKATClsCQASW9imb+8EAIkstmMBkHiVDXE9IABCL6poPCzG6j09DGkiztXWUt/jZRxI54sXYOD6HolS12Qvdxorl/FgE9U4ZafGGys3oXC4bOg398BoH0TXcCvjgCi9Yqi6jHCduwBZeTkcUgGM6TKYvBYMW/svWfmvyJgLj8+NtqEGBjzIk6PQUAZN3QCsrS3wr5+LpoEmpGuyeZnZotRKXJkvRZtFj6aBLsYB0cnlyKxTwmHrRu+2INcjfeu1EFeI0WnVYMBmYbyUAXM3k4olOd3SjJksvLQaTPeO3PM+ZPbfIcnbBb8wC3b5fXCI1oddAm5yxMUhlABMDb+981oIs4hYXosiXSnjdEhlSuaobRe7MWwf4GNWaChHlk2HbtkImoZrUawrZu3lEjPcOU7U/Po96BcvgWbhQojFCriHTOgU9KLRWI9iVQmykzIg1aggFr4Dlf0evp9mzQsQv1MF4bAT2y6rDVPjIv7E1b7ljLjN+Bz3NEPpv5/f1yr8LTym9XjfuhNNg8FMDZHHr8/6M3wCAwS+QQg91fCKZsAhuB9t9jKcHQw4thMwuE26OUxKd+RfCuBMk0DV5YXyotcKnXDkpkL8n+WvPPgiMNY90o4CxSx0HLPixNvNmLkhA76ibuSnZiDJ7cGurp1jAto1FZuR1uuFpb4eTT/4AT+e8mee4cuOxuJiCG0uVpbFJIHHASxjfQejASA2twU9xja0DtYj31CKdE0OI93vCTGnJKBBWUDypgktQ+SyivQZ3fumt7Kx7UdHWZeIcH7jI5fhDw/v5bt49y/XwO3wQCwT4cyOVixYl400Tx20OcmQqtUY+MMf+LbEheKUtCJ7G8SvVaxlXJ91ADIRh+iee+7BQw89xCbzn/aNAyDkW3L33XcjLy+PdZmuD5VdDQwM4MEHH2SKXnfeeSeKi4unNKQEAJlS2BIAJLawTd/eCQASeWxDswfxnoRTLyKRkJ2ot6HAg8t4cM7lsYKa0PPGe+xTBSCMlBwCPCjjQRNjyvrEw718PLA1mnROkyoiT9OK9ExFOZLbzRh5I7hqrrnqKjQ//zzyH/smhrLlYZKz3MruosKVTJKW3MBJWUp4qBqW3fuQdO8W7O3+kA8/zy8pvQrl2mYoTf8Oj/hy9rlTdBsEJ+aho3E7rKdO8vso581ExiYnek/kY/jIaRg2rEe/zs+4IZnaPKgVGtaW3X9WK1x1h2E90wpR2QycqxNBpvWhfMUsKHQSCJMskLgPsOyIW7oJTtEyeKEPSKAe6MKxt5qweEsJtPMd2FUbjAEBnfxxnMvnqOawkifazPemQKj4CEJ/KzyCMjS91IC2Fy56i3zn+0gvXgS/QgRhuwWeQjU8Bjlz6pa1WSHTPQiJJ3hOp/R6OAd/zDIwp24W44Oud/iYrMvfhJnn1PDppEhyeCFY8Dik7m38507xZrZvnbQdO5re4v/OZUDsqkchtzwDgX+YfWZTPIwP2mZCpw5ksWibk7wAi31zAsaEZVJ0GMzwSPwQOHwoM2VAXmOGu1IPl8yPFkEXMzrMTSlGt6mdgUNS+dJIdTA5RxjfhVb/i1IqMHdAi6FMOdqcXZiTvggjziG0jlCpUjFS3Ap0/ugnEKnVGPwweN+QyzqVHdF3ZqwSOl11H2q+8Q1+nKGAZaJnTjQAhM67v/593sxySfEa9Jm7maQ0ge4CQymoNLC+7xzjCI0GJidbP+IJ++56NX5+1wewDAfum2/+4zr2O91/TD76ikyokoPKbBxRndoO/vGPsJ0Mfj/G8hKJ/K0wPS0jASbcmbnFsUgyJtPT26kfdSIAQqVLP/3pT/nypamfZfr35ADIV77yFTzxxBOMuxIqw0teJkajEU1NTaDSspSUlCl1KgFAphQ2fqcEByS2+MV97wQAiTykoQBkqpPmic42VX+RUOBBng70w/WVy4TEMwMS77FHq/41FvAgwEUv4HiT5EePdXTJFa10Lyu7CkebPoTJMYwF+cuQu6sh3OOjqgr9x49DvXEt/FfMhs1lZtkSylr0m7vYZJNAh8/vg8vrRFX6QlhPetFSa4NsXfslGZOZWbOgV2ZDKXZB5NoLseNNuGXXwSNZAb8gGZYTJ9D/4ov8rZa+dT0cRiMG9jdAUVgI85kzSF6xArply1hZDvFlaKP7jyZm/S+9xO8rWPsv+MGDdXjg9+thGXTg2NsNuOxqOeYvfAcGxT9g1r4Ip2Bx8AGfFHjE7659M4yfQqvWq8qvgwBm7K3fB5PTyE+qOb6HuNkEV5UauOpZJPnN8CAXRx/xwnj8ODsmeZksLLsD7nI9ZHs6WVkXqTqR07f6jWb4rjgORdJX+L5QBsTl2cgkgZ0OK1qzzGgcqUVxagGyBZnI+Gkry3548tVwbT4flj0hCV3Z/xZi4OY8tGs60TjQhGLigCjOQSpSwCfIgsZ4A38ui+rXqBmuRLuljc9iFSQHnMvr+s/B6jBjRtY8HpzQfbO+4DoU1krg00qheK8VznmpeP//s/ce4G0dV9rwSxAgAIJEIdh7b6Ikq8tW766SSxy3xCV2HO+/qV++XTu2E1uOZSfr7DrFseN8m3UcJ3GvkmNLspolRZLVJYpi770TIEEUAvyfM9RcXIAACRCgJHsxz+OHFjAzd+bcwb3zzjnveTNLUd51hvXrSeeEsmUldozA1teHMJUKpoYGNL70kqBun/7QQ2j9+9+ReNNNrml2L3hAvHEx8g92o+mPfxTmIwYswQAgnq5La948MszWQaImlXlEZqYsZJez2IbRNtDAUjOnR2ciMlKDmp4K5CXMAByjKGs9gZSoXLQetEMlV6BoZQYilaMY7euD4YsvoMzMRLheD2tTE8zV1VDNmQN5Xh4gl8Obmrrvb4JLU9M9jMud00Ojcs/GJf7s0ox64qtOBECuvvpqfPDBB4ieYoKESzFfSh187bXXsvBf90LhWIcPH2Y8kKkekIUASGB3NQRAArNf0FuHAIjvJhUDEH83zb5cxV8AMhHw4Nfzt09fxnmpAMhEwIOPO9j8HE8AhJPOi6MLkdo6iuGDRxG1bDEaEh1ISshFYrsNXaIQD+4BUf/6ceyp+1QggtOmnBOPVxRch25jB3IiMzF6qha9e/ZAPn8FsCIJuys/EW7L2qJrkBWTCUfYGHCg+fKNCN98jAwOYriyEqZTJxA1Mw7R6Q04/4dORGbmjdN+0K1a5QJACHyIT4flM2bjjX2JmLU6Da+KQly++9+LkHiVEZXd3ciKK2GZqLgWCA3WW6peh+0M6geA+p46JF4IKcuQpLKMVwQoTLdGIiLlfhb6ZZLci3/e8iITyqNS9PCTyK6Ihy1LzeoSYDHPjcPgjdmQl/chor4R9nlVkMo+hVV2PSzKZcw7Q0XhOIRIw49YvxQ2ZYr6FRx1yyA/08OyQ43kOiAjrRPbVtitV0NyphDhjeGw6+SwzlICyTWQ2f/BuCUjkkJmc8XIQcgsH2HEcQ0cw0UwR9ai0ZaCxp52FEQXIKliFLWZJuxs/ph5M8bxNWIKcU34SkSU98Eer0R4+xDOEuek2pnKd+PsbzJgSl4BSuvMNVdIH6P93XfHezrWrMGozYboWbMQrlRi4MQJxK5Z48IBuZQeEK7hQveE836IcK6LjB3z/sUVCnMcOHAAbW+8wcQSk6+7CVnLb4a8yoC+XBlOyqtwuvc4VqWtRcy5DmhWroS5rAym0lImUjjS04OI1FT0vPEGIufOhUOpRP/Jkyy8jHRT7K2tGDp9GpGzZyMiJwfTzQHx5bnqbx2+eXcPD/YFmFwu3pKJPGjLli3DoUOHpkzQ99eewajvSXxQ3G9ZWRmKSLvmwkGNv9cMARB/LeZaPwRAArNf0FuHAIjvJp1uAOKrvggPO2IZf6RSdtri7YHma5++WwEsxSD3tPjTzltd6o+HjHmq4wvwuJgAhNLu7q/8FCv60tGy2Rlnn/3UkxisrUbCkhWAzY7h0tNQFhZisKkZkvRElEZ3u3kzCqFVxUIulSNsVIKS1PlM84CE13gpfOW3MMSaUNvTg+zYRKRHtiBMdRvbABMAMXSbcG5fE45urcE138pF9GAtevftQeyGDdDOK4FCdgQyy6doq7wNbW9+4BqWs24d8p9+mq0fbmNPHpB33zBCGiFxIfkuvDEbGd/vYfH6VMRaIPRvTzwDUk5v7D6EneXOWP2VBdchezgZ2kO9sBVqMJzQjb7SUnTvPQX9qpWQRenQvvUDxM1fhgRbCqJLTRi6PgvKXU0Qq5HbimPgUEkRcbqbpci1xcvhUEjZ2Oi3oR58EHKLKMRKfiMMUWMn/jR3qhP1SQPsGWpI21vgmFWOcNl22CKuh0WxnKUBdidoEyFecaid6Ytw8GQt6ENY6xxEv17JxjdQokJTRCcazU1MVNBFsyR3A1R2BbJOh0N9xshSFffPUaM+dRB13eVYrFsETbMDiiojLAVaWDJVGNVEsnGQPsbA0aNIveceF1CZv2ULlDrdGMG6uBjy/HxINBqXn1UgHBB3G/gTguV+3bjoZPQMdoC4IeKUzLSWMvUFggYIhQoufPjX0O8zCvMgvZbXzR8gRZOOJREzYevoQO877wjfx3zta7A0NjLdkIg5c1Dz3HPCd/mbN0NityP6iiswqtUyoPZlLJPZ3pcwLnePyVQ3xlO132QAhDwGoeK0QAiABLYaQgAkMPsFvXUIgPhuUjEAmY6UuTyFrDf3rD/Ag8/qywBAvNnSH+AxXQDEE9giDkj3YAcGfvkSei8I/dH19atXM7VziVyOpNtvR59qBIe6j0Cr0iMiXM6E/fZVfCwsuMU5a9HaX4+OgRZQPHx6TB4anvy5iyaHfu0azH48G47wFITbK2GXpMMqWwFHmI6BwIpDrfj1N8a4DT94LAbdLz7jBC/PPovYdevYhtU6MIDevXtR9dRTwvekfq1duRIOjAhCirP0sxHZ0g/TmTOQ5s/AuYpwRCZoYB124KUHnUJ6D/xhGeqSnVmreIgV3/TQZrPD2ILeoU7EqOKREJ0CAiB7yj9ArVjjJLYAG8/NQrjRCsvsWLQ3Hsf5Z59wzmHLz5B8VR1GHVkIq8pj2bjIKyE/2YWRLA2i3nWmqR38eh5MxVqP2g6RI1sRZXhA6JfCs4alruk9SbNE2mCEfdkJqCxOMvtg9AuwyNYJWiQCqHm7BvLSHqFPS4kOg7cmAiYlZE2DCDfaoNqKLHNiAAAgAElEQVRax8K8CFz0rItHi6IXvaYOKCJUQiIAnvGLh5SZCjUYtVigLOuH5qMmoX/DjWkwX5HI/s0VwuNvuGFMULC0lHk6lMnJ6BKFUk1EsPYnC1Y4+oQMY2Luz2SbYE9PV/F1vYWEUbheHwlkPvooEyFcuPR7UJQbhO4o5fJbxcdRpJ+J6E++QJhEwtYsL5TdKmrxYhh270Z/czN6do/xcvjvNO222zB08iQiS0rG1NSnOQuW728Z32tOxfbUu6/ARAxGpguYeJsDfU5q4SEA4roeQgDE99+Hx2dPYM1DrYNtgRAA8d2iYgAS7JS5NApvAodTAR58VtMhmhhs8EX90QuOcxHcgQf3tvj6EgwmSd6bt4fs2rV9Oyoee0xYQNkPP0w3EcqsLPadXSllYoOjNU0Y3H8YcXfdhv44GduAU2aoCEUkzrefYvHvlB0rQ5+PqFOumhxpP3kCmauSENEohfR8OEaK7LBlKRAeUcrSzY7IlsI4mI4D26KQcP4D9O91brQIfBT94hfCyb21rw/9R4+iZ/cuxK66CjGz7ZCqNWgazsDOsg+dKXCLb0ZaTJ6wUaG5DvYPo/xAC45va8C86zKQMU+DjxucXBF3D0hDbzl2nXeGEq0t2oT0mALwz7keycyEuSg+IIM9WwOHTILSv/8nuj8bS69KJXbtSsx9xMCyTtkkK2EbXQG7IpxxnKLfqoasxqlybi3Swbgpi3FZ3LUdaAMdMULk+a2wym+AVbpECM/i12LChF1mKHT/x4WQbpVfh2Hlgy5cF2pDgIWyaPFCfBQSLaRC14/6oJal+eVl6CYdRovKILVuw0DYKpzoVOJ0ayUoI9f1HfNhj1PCnKHCiFwCW3094o85oDjfL7Q3F2kxeEcBe07YDQYYT5xA965diNuwAeq5cyFRqaaNYO0NwE11Eyx+6vKQML4mSpIXIE2XMzbHC4KJRVffB/WHTjDWfUsq6lKM0NR0w/TRJ9CsW4c+UeKH2G98A7LUVFgbG2Fqa0P1li3CJfOeeALmgwcFQcNLmQXL97fP+JrBsD3v1Z1fIgYqvM508EtoLdO13XVkKHXtzTffzFTFQ8VpgRAACWw1hDwggdkv6K1DAMR3k043ABHzFzgg4ZmxJgu18jaLYJOy6TrBBiAczFEokDirlb/Ag9vgYgAQule9R47AVFUFw+nTiJ45E6baWnRu3YqCLVsQJpejt/QUorJyUPvEZuH2FP7qVxiZk4uYjnAcsh3DgE2U4YhS617Q5KB0qBFXXIW6njhcc5UOqredJ+1DtyVDmbjGmYEp6ikYTLMwcKwHlT91brQKn30WcevXg1IFN/fVobarHLnxM5CiliFqZBfMdgnqhmejpqv+giiiDacaDyNFm46rcq++QAKuYGru9tERHKzaIWQwWpa2BlJbGKpMVciOzkVCUg7z8lBhp9rlH6Clv1GoT32uKryRkYspBW+/icK3GpAVnYvMAT1UzVZY5sSj68w/UfGYKATtzy9hIA6o7apDdmwmkjSZkEl1Y4C1ZQjSVhNktQOwLJIjLOEEZPaPmXYJZeciL5F78XTq714ncmQbogz3Cx+bop6CZKQCRtXzAiijLwmwRNQbXVTGKcUwV/bO1uQh94QU2iN9Y6l+v9vo4llplz+P10t7sDRvA9J1Y4CPP2Mafv1r5C+9FZptrcI4yAMyNDOOYiBhq6nBcEUF43ZIkpIguRBGNB0EawamBn8IhflvwlgowxiFsNHv1dMG0ven6li4ntkwAG2zA9GVJliLY2DNUsOuHBM3pHsmMY0gon4QEee60Z8XgWpNJ073nMA10nno+8vfELVoESISE2FuaGChZ/bhYYSR9lFiIgtBM54+zVIM61esgFQiwcDHTk/k5ZgFyxf7BROAeLueOzAJNr/EGwAhFfEf/vCHeP/9930xxf+aOiEAEtitDgGQwOwX9NYhAOK7ScVkv0BT5nq6Kgcg5Angmgy0KaeNuK+n/+79ikHNVPtw7zPY3h8ulshfblMFHnycwSTJTxQedv6RR+CwWKDKy0PbO+8IZGnyPOQ9/jhajS0wPP/f6NslCv9YswaZjzwMs82MHms3dlU7U7yuLb4JuZTl50KYxPGPa7Dvb+V4/IZsyEvH0r1SsZRoINnwCGS2g2P/VtwGm2wxRnuPo+PcHHTtKUXs6hXQLFoBmUbDRA4/K3O+yNcVrsfs8IdwZuQZ7Kg4Bk6mNx88BuWSBVDOyYVRJsOu82NtiECtlEa68Fcoc9Wm08Xse9PSZFhTI4Xx0TrrMFSge9CAdkMLI5vHRqmRoC7wmAaWUuLmDyTBmq2G1TaEwWMH0L3nc8SvX4DeojzsqnCKLa4t2oCsmAzIR/ZDZt4Gu2U9ws7PgKPkPFSOh4QxeAqx8vWXPhZutBsyy8ewyxYhfKQc1og140K2eH9iUONO8F6XuwklhyJY5i5Z6sMunpXhiI2oGX0CWmUspJKxTGQcgFCIVZhpBPGJMyBvMsMyKwZWvRwOtQIjJDD4yivCCX7svfdCVlw89oy4AE6IYK26QLCeangRASx5vRGyc72wFSshS3wJcrzMxsnt620D6auteb2JvEmCJ+TIEWjXrUKNog9n+sfCrZanrUHaQAQjlKsWLEC4TIZOkW1iNm1CeEICFIWFrL5jeBiWc+fQ/Xen+vqX1QMSLNv7e6/488nTX3FfvvBLaA7idc/bE1n7+eefZ0J+oeK0QAiABLYaQgAkMPsFvXUIgPhuUjEACXZ2KX6aRRteKoECDz6ryxmA8FArsQckELDF53yxAEjnjh2o+cUvxhGByfNAIGRv+TZkVlnQvPlZYZFl/uAHUKSlIXblSgzbTGjtq2eeiey4QpblSClXCXWJYF5xqAVz9ArotzYInw/elorIxFXs30wET/kQIixvQ275iJ3602f28EyYozdDMnIOu2p6YLAYRVoSebgh/SS2Nc5Gc3/rODJ9wTObcS59VFCo9pQOdm3+RmR26VCv70NtfxWy4gqE7EU0robec9h13nnKvKboOmTEzBjzjril6OVpeM0LE2CZEYMoww/GdEBkC7G1oQC13c4wp+zYfFydmwD1wI2CPYzqtxBheQ1yixPMWeQbMRj1POyjUUI9X7wfnOsgte6BVb4REnsTRiU6jyFb7k8Oj3yG2CJcrVyNiNJu2FeccvGAiEGS+0aMb7ot6jg0NMtx/ON6zL0uE5mLNTjfewjpEYmIOtsI6/7DoBN81e23oN3QNCb8GF/MspJJ4PQg0Fg9hdBM9PRzBwW07qQZz8EWsVqwx1RO4d3vg6dwNUuJHoZbcxhg5XwXPtaUJ3+CfdqGMU2QohuREZPPgBvzSr72GuN28KK78UZIFAqYKyqEjFf0nbWmRsiCJc/J+VJyQC4lAPG2bibjl7ivQa7PIo4uoL4p+9V7773HdECms5w9exZbt25FS0sLVqxYwRTLxe/ON954A+fOnWO/ndWrV2PVqrHn7qUqIQASmOVDACQw+wW9dQiA+G7S6QAgfBPOPR40GvKA0EY8WCWYIUk0pkC9P3zTwvvhL59gaZVcDADCNjHEqfjiC1i6ulg61N6DBxG3Zg20CxdCptWiquMcBrvbEH+uFwNHjiB69mwWpuUwm124Gfw+e/JQsRf6kBXSmgHISntgK9HDlimFw3wWvSea0b3nJPSrl0E/Rwu9Y5NzU655DWGwwmY6gQrLjS5pb9N1SZgt+Q7zgJzt6ETO62ddvDSxa9ci+t+/g21nnKfE1826ExZbH5p6m5CjK0TY8fMID5ehOs6MMuOYUjjneUxELKb5uHsJOAnblqNhm0655SCihr4FR5gWpxwv47Pz24V5rS26DiXyP0FhcYYDDSu/BYe0BCrj/xHqUdjUiCSLKbh7I1B7+n1FjnyIKIOIgK7+b5ikN/j8U3Sf29rCG5HXnwhZyxBsRUC49jhk1vE8FG8nwUc+rMLLDzo9aA/+cRWaU/cxzZmVSSuheGUr9HfcgfZEKcQpbmljzsO6aPDuoTOTxfPT9+pxJHs9jF/PZRwUsXdkLGQqWgiZ8mascdm3JLEYOnEKPXv2IHbpCiQZk1iWMyqcT0PjoIxflB2OF9IoGfrOtdBG6qFDCqoOduLYtlosvjkX+Yn96LmQAptS6+o2bmSpeHlR3/YNyAqKEalVsHmwuYSPAbUvW7kcAYgnG/rDLyHFcHr/EQA5fvw4E/WbztLZ2cneZ3Qt4vuJAQiN4ciRIywUjDgpW7Zswfe+9z0kJSVN55Am7DsEQAIzfQiABGa/oLcOARDfTSoGIIFmlxITren/uceDHoL0AA7mS5EACCmhB6vPqQIQd+DB50y2JAAWLAASzDTBk4WbiU/8+KaOPiMbmW3D6Bpsg/x0DXrf+ZDpGZCmBedm+BMSJ36Jk616d+1ySddb8OwWJC0bQYT5XSZKaItYgwjT/6DcOAM7K44Ii5y0F9Jj0hAVVgaLuRFN5iJIjzWi4Wc/F+oUPLMFkcuuGuMydJUjWZcBrVIJjVyOtl4j6noqkRoWi7CdX0BRmC+cRmfHFjCehyeQISap28zDaO9vQE1/JXK0+cjo1CD2vWYY7iuGxGQTQn6QegRDimS0GIZQ09OLHH0MUqI1UFnbEGX7FhuvRXEnRmSL4QiTQzJqgMy6lynDU9gURk2Mp6C0fTRpBix+L9SDDzBPEi/kSTFE/fe4Dbz4qSE+0feU4pb0UcR1PHliPAEQAua/f2A7jn5YK1xuwaZszHtMitLmo8iOKcBSxSwgNhH7W3airmcMCFJxz0pGn/mzEaQxRpYPINoLyd5TyBQJQnriCPAx9Q93s1BAAk/kVdswWIiax38GSrOrys1F4i23It2YDlueDtZMJ6Bx94CQSruOMs6NjuL41jr8/gFndrYtn21EnGoYxmPHEDlzJoaOHYPp1CnBLsr5CzFYvBZ7Xz2HGavSULgkEVExX840vN5Aq+9vtEtbk78PaBT8N/HSSy+hoqICSqWSfbZgwQKkpKSw/5KTk9nn01HIC0IHV2IA8sILL2Dx4sWYP38+u+S7777L3tMbN26cjiH41GcIgPhkJq+VQgAkMPsFvXUIgPhuUjEAmWp2KTHwoCu78x2CuXnmMwumR4D69Df8zBvw4Js+f/ub7I4F04aTARDxWDwJQ9Icrf39zFNCGYsoVapu4UJE6MYTpCebF/+e7EXpScWnwhTyRcCGrmfsMaF0XzPaKnugurZl3Ma0OHkuU5Im0bfE6DTIhizMQ9Ozbx8j6RKxWarXM/B0uvkQSxNM5aqc1dgjSiO8LOZKSN7/HJWbcpgeyLrC5UiPvZJtDL1txKkfxbl+RG2rY6lpSUNjeG0a7CopJA4g6i1nuNXA3flQxP1fyEb2M1BBxYEYmEd+ClnkLkjZ51dCZfwhCz0bVj2CCMtHTGhQMtrHeApm2Q1eNUBonEN9FpQfaGUn6PNvyMGsxa1IkTgVzoein4Mp4h6PG2vuBZBW9cPKtEcULEOXeEPl6z0Vbya57doHmoEzqXj5wT1CN2IPyJqim5ARk4fT2xtgT+rBKaPTS+CelWyicXgLm5FaHJA3myBtN2EkMRLWNBWbH60xzTu1rimIZ8SgWVeHiPj4McVx0UbR0TMAw4lj6Dv6BeLWb0CfPhylpvPIe6MUsmg1dHPmwNbcDHluLqxF6YiNz3JJFcvD0YhETkKCtD7D1Wo2jj//aB866g3oax3E/f81GwUzyhGJf8AsvR6W8CWwVbWh6wKPgAQJoY9F177PIS1ejC9OyZG/Kg/zrs/y9TZdVvW+7ACEjEmHT3Qf3TW2Xn/9dfT29iI7OxtESKcQKYPBgIceeghz5swJ+n3wBECeeuopfPOb30RW1tj62LdvH+rq6nDvvfcG/fq+dhgCIL5aynO9EAAJzH5Bbx0CIL6b1BMA4Sc1k/UyGfDg7YO5eZ6uPn0FDJMBD/GGmjwGwTrdmkzYcLJ7Jf7eFwBCGwFuEy6o6B7TzDblVivzQgUaXkfXGidYeCHjFY398HuVeOH+7YjSKXDvWzNdNqZcfZri56msK74F8c0m9Lz1FiKSk2FtbYX2O/ejK9KG2q4yJFxQKzeY+6GQKlEn0vDI0uZivjUNZ6Pbka6NQrJGC4nMdXPgftpP/45+sxqKsl7BzOY5cRjalA3VR65pa4cXxTPehMx8HPa221gaYluRGiM6HeSaxzAqiYLE0Qy5ZYxrMuYNmQOp9aBLqt2JNEDcT9C/+6eVWLb+MGS2fQz0jEhnwiy5yuOSIS+ArKkJ9nmVkMq2wyq7DhYliRb6Dy5pfdB/tG7EYVyLEq7GYJkCJ7Y1YO71mchcpMH5gSPIiiXF8DSmrfKHBz+DKiEcM25VoyesCUmKbORl5bOsZL7wXrz9HmiNMF5JdwWyYguQQGD1Alk+qsKIaBFY7N8Qh/p//IkR46Pvug2GLD0S1KlsDP07d6Hv6BFEZmXBeOYMYpYvR/isQqCyEWEjVhg+dSYZ0N19F9rVDqhrejCw7wD0q1ZBPX++ADjEHhYCJj0HjqD/wD6or1oO/VwVUhQ3C9Ppkb2MEekGGM+Ww1pVibAYDaqfcob0xH/vMXx+TI17n18xoefGn+fFxaz7VQEg7imzyYbPPfccCgsLWSpeXgYHB0EaWe7P1ols/stf/hJdXc5U2FSX1hD9Lh577DHoLhwE+QJA9u7di/r6+hAAuZiLPMjXCgGQIBs00O5CAMR3C4oBCD3EyLMwGQBxBx7kwqVNqLfwm2CnuKXZBRvU+BJ+JtYumYxQ70t/vt+l4KYJnijcjIdaESDwBjzE4w7WfaDrWXp7GdmWnwoT74S8KjSm3933CY58MCbQt/o7BZhztx5djnpGdKewsJquMoGQPi9jGdL31gjEXYqbtzx4M/Y07hSGviR3PSraz6Ak5QrsFWWkWpV9DbIj7VApdmMkvAQ26QKvm2++Eaa/IwfakLRzTNOhf5EO1XNHUNtXhWydM22tZW48RtKjMSodQJhEAeXWdsFjYl6ZCvvsY1AN/whm1Q8ROegULjSoX8Nw+DrWN/+NedMAoe9p885tRW0W3ZiL77+kgcz2+YRzYkDqwzo4lp5AJP5FsJW/2bfE/BSr/HpYpcuwq3I/arvOC30WJc+FThWLgaFezElfgn5TF6o6z7GkBUnqdJz9pI2FIRHgTC3W49rvzcaMRXoYTpxgejRir4E/vyN3PgvnlVAfEsqQ1TzEvCNWNdBbdQT9h/ez7hWzZ+HoPDly4oqgVyXA8NtXEFVQwMQAeRhiwc+3ID4yD+3Ve2A6fVoYluKK2UBhLmq+/2PhMwq50nog/7qHZhVu+b/ImfOYkJ56OHwjhnR/wlDfMEwDNvS/9lt0b9sqhHzJk5KhuuV+xBcm+GOWy6buVxmAPP7449iwYQMjfl+MEgrBuhhWvvTXCAGQS38PXEYQAiC+3xBPAIR4C55OZPwFHnwU7qJ8vo/Oe81gg5qJAIM/wIOP+MsGQPwFHnyewfLMcG8L8Xp4EfNPuAeEf/fD167BvOtyYLaZUN9dhYaeKpYat8/UzdTXyQPCw1QUubkoXZ3iknI3OyYfc4dTIMtLQJdtGLXdlcIJvDu/wX0VuoQ4XZ+NwqXJMNQaoO2zINZgw/klFnxW7eRcUNra4pNKOJKioHq/BrYsNawFOtCLQ9poHAMlFIoVbwfSj0PiaMdomAYy62eC18NqV48TIuSAxJ2j4O4B+dc/rWchOb54DuQDvVBIH3bjjIzpY0zEhRDbyF1zhABMpbEIO8veFaotzlmDkw3/xPL8a+EYtY8jm8eHZ6JsfwuOba3FynuKYegy4/i2asxaFAVd2z9h+Mc78LaJ9/bUoPm7ZysT80rE93XehjQkD52B49Qh1p3yjpvxqf0ES99MRPEZQwmwdbbBUlPDxAH7Tp7EiMGIeSX3oCt1AB3vO5MdRN11K3o+3YXurduEoekprfXPf+5iUxrfeHL6aiz49/NCeureiJdhcaxmYoYE1GOuugp2i4Wl4iVPjG7JEsjT0hA1e3YwHrMXvQ9P4UsXfRABXpDm4MkDQmTvBx54QOBfBHiZSZt7AiCchP7973+fHTYSCf273/0u46JcqhIKwQrM8iEAEpj9gt46BED8M6kYbHjKLjVV4MFH4UvIj38jDq5HgK7tif8yFeDB5zFVPo03OwTThmIPCN1b2vzTZ7QOuDfL1/sRLCDIx+AtZI3S9577vAlHP6rBgo05mLE8DdF6Jao7zrnogVA4Voo2G0qHhInakZYCxcl3JIRjV/mHwrSI62H40RbkPPwwO4n2ZXPOG3va4BctTUbVF+1ISdegNGw/arudp/3Z+iKsKdyEqHeqGcdgJEYBy/IUqD6oEcYzdFMO7HIJzIVaYSziMXnb1Hi6T2wjfbCVbd7n35CNwiXJUOmcwM7rGhsxQ+XYBTmaXDwwvnpAiOdBpOycsM1QWsWk9xvRo3wBLf11LKVuuj4HlhELIiNUSNFm4UD1py7ekSx9IYb+kYa0GTEoXJqC0t1NLqTsbz8zGxFvPwnNggXIe/ppn4ARt6W7B4TWS6o2GwQ6+X3lXpf19xch3XQco1kpqFENoLS3FAScaM2td8xC919fA3nXKMxPXlQEx6gEOV9EY7hQhX69AYN15YiYNQPl8m4k1JvQsvkXgundwRMfn7sHJP0nTyB2sQV65cfot9yAgeEFQF0VKh/+d6EvAjI9O3cy8VBKCJH98MOIv+kmn+zi6+/8YtX7sgMQHqLrCYAQ9+Lpp59Gbm7utJqzvLycaY3Q4RCNh56pd955J2bNmsXec2+++SZKS0vZ8z6Uhndab8VF6TwEQC6KmX2/SAiA+G4rqikGIGJyN9+c0uaQymShVt6uOtUMUxPNIpgbcjEAoYc1J17T38tFrT2Y8+WbfZrbVIEHvzfBAiC+eIzEJ/B8w7aj9F2XzSudaK/Iu57dQ1rXFEbG+rabx2L/O8qQAj3CdhxBzxvvgtKf5jz1lLDUvIUR8grh1lG8+N3dOPLhWDgYFQpxeuiPa8de9pUDqJI1YUfrP4TvaZNrtVsxsy8VujfqmAeEVMTlIs4IaURYS2JgzdbAHjH+leIPAOEX9gdUUZtOYzNysBmS8CjYpYWQ2o7AFrESZtlG2KGd9KFCm/sDVdtxR4keiZYfCfUJwAxgLQbMfegwNEOjjBG4FFTJHRTM1a7H/9xyGoN9Zvzkw03Y/co5l5CyBddnYJVyGxJvucVjGJN4oKMmE6zV1Rg6cwaqWbMQnp2JRnMz6sljpklF31AXUnXZyNQXsNA1dZQdC6+wYOTcYUQuWIqktVehzdGNms5ziNeksPp6mQ7x+yohkcuZKrmlrg6K/HxItDqoOsKgagfMM3Sw5MfAIhlB52ALJGYrFFXt6N+5G/rVqxA9dx5Laz3UZ8b5/a0o3dOEq27NR1quHObSU8y7oVm6EobIbNRXmjBnRQLC2usxUlUGZW4Weg4dQvv77yPxppugv/LKMU9MSgrzxNgMBuRt2fKlBSCeNu+TLr7LpMJEAGTTpk147bXXoNfrL5PRXh7DCHlAArsPIQASmP2C3joEQPwzqXu2Dp7aNlDgwUfxZQAgnP9CtggEePA5+8qn8fVOBQuAcOI439ASqAzkhX8xAYi7rWgu7h4QiulP1eSwFM18A87XMbUfOnUK5Y88Iii85z/zDNTLlzMb8PhzDkI8/VVU9OOfX7Tjdz/eKwxHHOJEOhPDKgdqC82oMdciIy4fSSYtYo8YYSqIRrg6EopTPbBnaVg4Fi+mazIxGh4Gu1oGc77GBRBxD2Qg92mydUZzJU/ElYk9DDxw8cdh5UNMd2SyIg5vmp2cjznxJmhG92BEsQnDkkWo6e1yCZOjTT+J7VFhGbIGGtDcW4vs6GxIWq3Y/bc27PxrHVbcVYSS1en4/f1O3ZTv/NciFGYMIooAhVo94dAsZ86g69VXhTqkEH4qqgu9pk6niGVcEVYVbMSp7Q2I6jiN7hefEeoXPPsstCtXYsRhQ9tAIxp7qzFnOAkwDGJ0ZAR9Hzq9auprr0Xdyy9DTlmzUlKQ/eijCDPZENE0xivhWbeM5hGcP9CG49tqMXNNOhQyOzJS7BitKkVEbj6iZxZAolKh6Yt6hHdUIWygA5rCQvSIlM7VV1+Nuv/3/5D17W+7EN7pc4dCAe2yZZPdssvy+6kA7ctpIhMBkJUrV4JI3/TMDRWnBUIAJLDVEAIggdkv6K1DAMQ/k3IAQg9P7ralDcVUPR7uV/c1w5Q/ow4mqBGHWk3V4+Fpc+wLod/XOQc6X/cwOroucX0mO/GfbHzBAka+eEA8jcVkGUQLKa93ljPl8rjoZHQZW1mWIyKoJ2kyIA0be+HTXCnLkOH4cUYeJiKzbs4iKNusoLSzFpZ2Vo6RiDEFal5sDivajU0YMPVg+eF4GByjOGlz4MieBixcn4WC9emI1Eaw6lxLgjwcloUJGIoPR+zbjew7+qz365lQdtgQ3muGPVkFadUARrLVcETJEFHRD1jtTLjQYhse0ywRZWuSX9DemOyeTPV78kR0D5SNgQfHHljk18Iescon7wddU+zJIE2MdcU3IVaVjKb+Guw6/74wLApj6hvqxtLcqwU7D1SfRxcMaLK0MD2WqKFoPPvNM7jnV8tZCJkzpCwHFO7G7T3RXOl+97z2GkwiFXFSWB/ZtFIQpKRxXjfrDhjNA7CZRuF46VX07BIJBK5ejaRbb4UiJwfSC2lyu//yF8hTU2FpbHQhmytLStB1/DgGjh8HBy7h1R3oKz2FrqMHELdgKbQlV+BEjRm/vXssS9bG/68YG65VYrjsHORZWbC1t0NZVISIkhIMHD0FyUA3bC0tUBYUwNrUhMEjY/o3SuJ4xMVDYhiAvbeXZXqjbF2Rs2dD+7WvsdCwL2P5qgAQT/pUy5Ytw+HDh7+Mt2VaxxwCIIGZNwRAArNf0FuHAIh/JmVZfC7wAKglPTxJODDQzTJL2ogAACAASURBVCkfxWTx/f6Ndqw2bcjpZRWI0J878ODCgf6kRPQ2du4B8Ubo93fOUwUgnvg7PLQuGCmCLyUAcefohIcZUdNV7aoyXnwTC6/hKWH5X762VeUDGKnvFjwWWTH5SNRnMk4AFarf3F+Lio7TLP3qUvNsJL7bxsAEaX4MX5kIU2608FuRmh2IqDci4lwvrLNiEXGmC/LSXlAGLHu8EuGNRtgKYxBms0N+sA1Dm7KgPNQOaYMRkuERQS3bW7amYP0mPa0/rtXR3FeHvPgZiFP0QWt9ATb59bBIl06aitddJ4VS3BJo+mftDibU1zvYBUqDmxlbgJLkeYiPThXsVl37Bfa1OrVBViSvQlhPBhJyNIy/YjcaYa6pQecnn0C3eLGgmzHZ78iTBySsKI+Bu8F+C8LbY3D4nWpkXaWFtKAHmS2DaN78rNBt5g9+AGtnJ2KvvJJxiiiMi7wTlOBAs349+j74QKirv/NOtH++D9GzZ0I3fxHLTNW/bQfKn/6ZUKfopz/H4foEbPvtCeQtSsLt92ph2fam8H3Mpk2wdHRAd+utGNy/H/2i/um7/p07GdCQrr8V5qh4JMh7MXzOCV4UBF5mzPArretkNryY34cAyMW09uVxrRAACew+hABIYPYLeusQAPHdpLTBEofR0CacNjkEQIJVpnq6PdH1A/GquIvrkaeH5uyJgB+IDYLZn7+Aa6LEAcG8H8ECIP6Q9j0lB6D7JLF8ju2VLajpdoY2ESdkdeEmdn/pGtSWbEMgm4Bm1Ae1KJs56MLZEAveWe0WdA62YshiQGtfA9JjcpBuiUPs4UFYZ8TAnBGFEbnrK4D6jd7fjohT3TAvTULkziaYV6Qg8tMGYTkR6XwkSgpHvBLS5qExwDIjhqllOyKl47M1xRZhZcENgSxHn9uSrRS2TxFtuFto4ysRnRrw0Dey9cioFc39dS7hV0madCRHpsJ8ZCyTU/Jtt+ELaQ1qeyqE62XrC7CqaEyBnoon5XBPaWzdJ2npMcJSUw1r2VlEFM+EPCcXcn00MDwMw5lyWM6dhS0pF/v3mZG0IBbKghZktEtg2PM5omfOhLmtDbqSEpcwJ/1dd2HEYEAYcYxUKgyXlUGRl4dwrRajERGQ6HWI0OiYHaoffxzdnzk9KrFr10J73w+ZhodKakaY3Qbj/v0MVFCJnDWLhQRG5OSg+89/dvGwkHeDOCdDo2qcOD2KFcsk6HvnLRcAJC3MQ7gy6ksJQCYKX/J58V7iinwO7h4Qen6vW7cOBw8evMQjvPwuHwIggd2TEAAJzH5Bbx0CIL6blL/geXx5sDaU4hH4s7n0deRT8ap4Ax78msFWVw8mAPEVcPEXIL+P7qr0NNdgAxC6pjh9rq/30N81MtH9ozEo+r+LMtP12FFxTOiac0LEHA8OPqgSeSu2D+1CTW+5c/N7gRNAfTb11cBo7sPh2t3C9ysLb0BObPE4ki//LdFfVbmBidqR58NapEPEyS5X0nlxDIy357nwTsRhX5fCA8InSBtn9eCDkFucp/sWuTMV72TkdjEAaR6g8CtnPysKrkOyJhOWA18w5Xsq5CnQ//k/sbtmTHyRCmUNy9AXsP+ne1f52GNMqJIXSh7gSwYsymz16r99zrREmst6cPd/LIciSopUeScG33OmypVfdxt27rYi99s2aGxJiG03ov7pn0KVm4u4efMwXFoqXFs5axZ6y8rYv5Ouvx7m0lIGDKR6PSz19SyESjFjBsIiI9G/ew8qHhubJ5WCLc9AHhcHy/kyyJKSGIFdnpnJQq8ovIq8KL3SJOx/ux6bbolEz19fc875rrtg0qTj70+dQPbceFypOzNOb8Rx42roI5NYG29cpqn8Pi9Gm68CAKFnFD/gENusu7ubpeD9+GPnGr8YNv0yXCMEQAK7SyEAEpj9gt46BED8Mym9qPjLaqqhPhNdkQOQyQQO/Rm1P5voyYAHv26wAUgw+/MFgPiaNpjqkdeLFHgDLcFaLxOBVPf7R6BKHCbHX/oR5g8wMnwQtZb1qOnpRVZcLmKjs9FpbEN9VwXjiCSqSflaDvJsEK9DYhoBZBIX3Y61xTcxTRAqJxoOoGeoE/UitfTs2CKsKtw4jrQutmX4sF0IxTItiIfMOIKod6qEKoM358A4Y4xs7mmj6C2caTpDsMTj96S0bpUuhXxkP2SWbR7DstzHTEDjYPV2l5TEY+FX8zH8p7cxTNmpqqtZQoDcF38DQ6ISDf01yNDmMDFCyjJFoVIUElZQL0HN485QJl80QMhW7qKMlMJZlxSFNVmVsJQ6xQLJu6BYeCW0w5GwylUYVFrRd/IELKXHkXzNBvS+8boLECh79NExcDJ/PstApVm3zoWQTmR3+cyZjHPENDv27EHsBQX0gc92IUIf41I/5tZbGaHeKI3FkQ9rcOUqDeS2AUikUgyfPw9pSgrjiDiMRpjOnIEivxDSqEh0/c//COMirZJy7SCuylkvgGMxqL3cQclXGYBUV1fj5z//Of4uSiQQ6LP3q9I+BEACu5MhABKY/YLeOgRA/DOpGID4stH1r/exOPpgErLp+r54VSbbuLrPI1iq3tMBaIIplOiL7Xy9x9MJQGjdUP/eVNk58BC8eI5eyGz7IbXuhkXxdVhRiPr+TpcTeA4uarvKBWJ0cfI8JGnS0G/qQYwqHnFRyYzvQSCnqa8WRnOviweE+iBeCRXOKeH24mPhQCHc7IC8zoAwoxWjCilkFf2wFWhhzYqGLUo66UaRxnApNmaelNblIwcQZXhAWBruYVnuXpt1xbeMExkkArpUEoEIhwR1PRWMcB6+/wy06Tmo+81v2KaeQAnpsxivSBfEC4ujC5HbrUT/ns/9UkE/+mEdXnpwhzDm+3+zCtt+fQLfeyIdjs+cwoicXxF93U1473UDZq5MgzolGp/8/hTu/lEaZIYumCndblYWS3dramtD7/79SFi7FqZjxxjpm4ABL0R213/zm04vmcUCS3U1I8RHLliIoSOHXcOrrpgD9fJlMDc0IjySSOllzDMy0tMDWXo6al98EZn33uvCCdHdfDMcNhtsjY1AcS6qVf1ISMhFui7Phb8nBiHu65WP93LwllyKde7rc87Xet6U3I8fP45XX30VL730kq9d/a+pFwIggd3qEAAJzH5Bbx0CIP6Z9GIBkGARsicDIP4CD26tYAOQYPbnCYDQPCnUyt+0wZczAOHEeLE4IvGR3D0e3jb/YlBCnpLd5R+O0wmhsCwKC6rtGhMLnBe3GPOshVCVD8I2IwaWLDXsirGNP+mH9A/3YGC4h3FAMuMKoJSpcL7tJPOSJGszoJAphR+ceIMnGe2DvGwYUW81s++JuG68owCW9PGeJ85R4fMS/xX/msW/Vfo8GB6RiUKqeOiaL2FZ41TGY4twVc46RuLnuhuG4X7ERSdhX4VTFXx1znUYfeUjdH7kFC8kpfChB6/B8Yb9bPqUreqK9CsxM2Wh4Hny5SlX8c82NJ7tQeWRNuQvSkJKkY55RZbcmIY1V0dD0ngeisxMWC+EQMlnzMYb+xIxbLRi/YMzodYpoKnYAUtVJRMcpGxTioICBi7YPR0agqW2lnkmet95RxgS94Bw24rJ8ARWdJs2oed1kVflzjsxsGMHopcscfWMbNoEc3Mzhrq7odJqx2Xd6i0vh6qwEL0bShCt0IAT/31ZF+KQQU/rzR2UBGu9ebtv3vgTvtzny6WONwCye/duloL32WedCQ4ulzFf6nGEAEhgdyAEQAKzX9BbhwCIfyYVb2r8CW3y5yrB5EPwl6W7V2WqwIPPI1iaFtMBaMT3xdeQMm/3J5ghccHymHEvGSUE8CaOyF/unrwOnGBOa1nM8ajtLseuMmcKWMEDcuHzGcnzsHRoJnTvOAnig7fnwzIjxgVU8DVHOhA7y5wn5wRm+Imz+HdE/y+zHYTiPS0iSo1CXyQ4SGl2+RwEgcQL6XYpbTB5X8SggG/M+IYwWGE1QnjQhZTE0fPmCboa7uFUFBKlxU4XD8hQ9HNwhCXAKl3IMmRxIcKYqDiW8Wpp3gZmG5vdwhTSqzrPsexaZa0nXZXi44qwwJSG0n/5F8FOFGLFPSAFibOgi4xFp6EVWZRaWZ0uZCmb6BlE9tr6nydw8K0K6JKjGAdkxopUrL5vBtoaupG5WoW4ASv6Xv2rQAJX3XYv+qoaYDt7iAkRpqy+CtbaanSLQmdi77oLirlzXS89PMw8HEOnTyOyqAh2kwkSZSQ6zFrYwlXQ13zmkg5Ye9PNcMgiYasohWr2bNgHjRg+c2a8J2XWLETOnYuO2m5o46NhfEcEWm6/Hd2HDyO6pAS61avZmgo0i5S7t8QXYOIL2PHlXfFVBiDvv/8+amtr8cgjj/hiiv9VdUIAJLDbHQIggdkv6K1DAMQ/k4o3TsE8HRePIph8CHcAwkN16OXLSddTSaUbbAASzP74feHK3oHMM5ghccEAIDQe7vGgtcg9Hnxj4w/w4GuZTqbNVVUwm43oS9egvr8W2fFjuiDksTDbhpkqN5WinXYoz/W7gITB2/I8/og+r/wHKtqd3AHKskUidjRGPk5qSOtPM/xjOOruR+TbYxmOqPTfmoWhIjUbA82bdD7EGhm0aZeFK2C2mRAZoRI22+4by8lOr+lak3lLJsos5YkEnx2TAKnjPOTmN+CQFiF8pBxy89/BQ7GGbUMMaNR0liFJm4EkdRqUsqhxHJeG3ip8VvaeYBOWKECWBOOxYywrFumzEBiyR0bAYO5Fr6kbB6rGdDOoiLOUeXvSDfVZUH6gFV98VIOceQloqejD/r+fBxeNbG5pQc2hbsiGR1GSb4et4jxkRbMw2NKKpl9uFrolPY8IpRKwWIQQrNHwcEQtXcrquINBW1UVuv7yFwHQxNx2B/7zp434weZMGN7+G2sjjY2F7hv34OxJC2KSVUjK00DSUIGet98exyWhjFunKiLw+ubjePiNtdDb22EqLWWhYOS1IV5IRGEhwqOjpzVUz9f1xted+K+vb6OvAgCh3yn97tzfP3/+85/ZM+5fRCDbV7t81euFAEhgdzgEQAKzX9BbhwCIfyb1BECCSRin0RAAodNt2jgHq5BXhYeI0Macq3pPtf9gZwALFgARezyCMc/LBYDwE1vyePDNnDhMbyLgwdvSX+7xEJ/Emk6dYloNVCjkJf6BByDPzh63NAhQXGksQuIHHcJ37h4QAiutAw2o6ypHWkwO2gcaUdE+Fu8vJqzzOXDvhnJkK2SGUpjb7oO8zIiBfAVORlQiNiGNcUhovO4hYkTSJq2MDH0eTjb8U/AikC08bWzcJzTZRpHbiH431T/9qcfMUtSnezjV6rwlKI7pgczyMUYiViDcVgqF+U/s8pQhq0vxW5YxrKGnConqFPSZukFq59w7NEppb48fR9f27dCtXAFLYQrKByuRqEmFXpWAhOhU1hf3/IyaTLBWVzMNjuNpJpAnixcO+tw3/2JbUPar3z/g5H7c89wKaBOVyF2QiGi9EgfePYf/fuhz1iRKp8ADv12FKLUEjm0vuwoRrl2LzPvuQ+crrwghWHH33QfH4CCGzpxhuiARubks4xXZ1FPq3B3V+UjLUSI/zQJVjBzm9nb07v8cuqXLUD8QTwPA3NUJsNbUwNY/AIlcgeHy85DmzcC5KilsiEBirgaZs+Jg+uR92Lu7ncKDIq7JpeBQ+LrePIVzeVq7tM49ifhN9Zl+sdt5AyC/+c1vkJKSgjvuuONiD+myv14IgAR2i0IAJDD7Bb11CID4Z1IxAAnm5lQ8imDyIYK9IefjnA4Awk/0/bsjY7W5Z4dOzjjQCgYw5Pc4GJycqXpAxokIhoeD1ohYWNI91IpswkOtvAEPbufuV1/F0AUF7IhlizE0LxcNw80shCf5gheE6tLGtru9EXOs+dBUmmEu1sKWpUF4tJPX4R7GRalk2/ubkBqTjWRtpgsHRHyfJY5eSOxV2F3bheGRYYQhDO0DzUjRZmJF/vVsLk0DNdgtSlNLJG0CHknadAZEiG+yIm+sLm3M3PkaZIeJQmDoOzGQ4+uK/ho//1xIhUv/prAnzcqVbAqNfVUCeZ/4F/fNSYJ28F+F6ZminoJi6Hn2b6Pmr6geiMHOMicHgqmdD3ZjbuZStPU3oLG7CikOHcJ2foGeN95F6pOP4nyGDR0DLUjRZTIvknhsnDNB4NF87/XY275PuPZkHhCas3v2q0U35uLe/1qB0t1NaKvqR9P5Hhz9yKkXs+yOQtxwSxTQ1YCa554TrsVssngxA0MUXqWi0CubjXk5eOF8D/q3mTJeicK1yAPy8+9XY+OP5+PEJ7W4/eujqN78pNA294knse+EDrc8toh9RiFjJ7fX4ZrvzsFf/u1zDPaZ2efcc+NJWJGybXHb0b3mKdWn8swJRhv3MC5PQNEdkPB1yn/XwRjHpejDWwjcU089hauuugrXXHPNpRjWZX3NEAAJ7PaEAEhg9gt66xAA8d+k3GUczM2peBTB8Aa4Aw962JP+RLBOzIKV0YnPe6qARgw8uMeDXtDBzCQWLE6Ov5yhiVIF05i4KKT7ChYDD1qrfDPubaVzD4inDazYa0HejabearT0NyBdn4v2/kak6LKYB4IXMWGdPiMvhTYyBukxuUhQj53ceyrUd7uhmQEEg6kH7YYW5h3QRyUy8jrdZ6rTdsG7Eq9JAZG0+0xdoFP+Y3WfCx4QmrN7WIf49Nl90zeOWyLiTXB+h6WvFzENRpZZSr96NaLmzoUkKopNhQQEOwdOo7a7BTOScpAT/gLklq3CNC3yjbCO3omwxkLIyoZhzFfiqKwMp3uPszos3W7KQgya+7BXRDhfFnMlDD/aguj581Bzx0y09Tfiull3spAzCkfLii1gYXKDr78tcCbGAGQeGoabxr73gQPi7gGhDbxUJsFv7v6UeTyu/+FcvPHEP4X5PPz+RsRWf4awcAlGIyPRd+wYdFdeCd2KFZBER7N6DPyZzeh96y3Q+uKFMl7F3n33WBjewADzZFCYlLJ4BuOA9PRLkDEzDkP9Ftje+i/07HZqypDdZV//P4hNj2KK7zTuXa+cg0orx/GPa4VrEIB66I9rGemd+mdgaPZsJlhI3hcql8ID4s+bZjJvCe9LvM6DxS/xZ5yB1PUGQH784x8z78eVV14ZSPdfybYhABLYbQ0BkMDsF/TWIQDiv0nFD/1gbU7FowgEgHjzeAQ7rOtSAxB3jwdtxjm4CrZnKlj32FcAMhlxXpzRi68b7pnjnhD6N4Xw+bIp4RwQW0cHjnkI4aFTdF7+Wb0TYZIwNHZXIysyGwtsxYiuHGYZsWzZGlSbql2I7EvzrsboqAOt/Q3Iji928aiI1zx5Tg5UfooFWSvGcRgIYIiLdcSC3qFO9Jq60NbXgNSYHJbVSKvUQxoWIVTlNhGfcrvbg+zlzi0Rk+U7jc3YeYGYn6BJwezUKxEXNSZeJ94kRjp2Qjn8MsLsrbBEPoQIy0cIHykDZfcyRL8GSfVCRL3p1DZpvykRr5s/YJ4b8hIRUDjReACVHWeF8Wdpc5H00m7E3fY1tOdGsfnZHFYcrNoBMXk9sc3monERd//9TNxvorArsT0ZB+RgK45trcX8G7JRtDQFrz28H0c+qGbV1n57JkqWp+Hkp3UoWZ0ORbERyb1GDL3+LgvZo4xX0StWQF5c7HKfLOfOsdS4fR9+KHyuu+NubP1gCHmLklC4NJkBCXH2MBozAYt3thzBj3+mRc3PnRyT3J89iV9t7sPXHl+EeddngcZdfbQd/W0mvPrvYyFiVLgHRPzbcLcFByDBOpDx/y3ifwvxHMQcKnFPnrwl/l/p4rTwBkDuv/9+RkAvdltPF2dUl/dVQgAksPsTAiCB2S/orUMAxH+TigFIsAnjNJqpeAPohcRDfDxxH4IZ1kVjnGo4kTdr+wpo6CUsTjsrBh6872B7pgiABMN7NBkA8QV4uIda8Y0UT6nrvhnhm3Dx34lWvHsI1arsa5ChzoZMrWYnyoMVZRg+fRaS4jxotZlI/GuL0B3xQQbylcxLUdt5HvGaVETL1dgpIlG780B4Y/KcEDGbQphchAzjihiRWlzGQANpkzhVw1cWXo80Xa5AWOd2EgMyzg1xt4mn9MNLctejtb8RtV1lLAxM2z2C/tffg3rFEsQvXiac9PNxcS0Qi20A9cOzUNtVixx9AtLk4ZDbc6D4rB/y0h5hGpYSHT5f3AmVXAO5VI7qznNI1+e5cGZWJK9CnD0afbow1PVUslTG4WESGMx9gocoLCwcRbpiWCornSf9ubkMGPgKQDxt1LlXZNmdRUgp0KHmeAcWbspF4ZIkxlmxNJuhMfcirKEcylkzoczPF7wL1B/ZuOe11yCJiEBEYuIYKb2gALW9erQ2mhnRfdaaNAYk3NcsDwn7198sQKamC30HPodu2XLU98fh9z84Cu7h4PMz9Vtx/kCLAKAKl4wBm4nKlxGAiOcjTmHri7fkcgMmE3mgbr31Vrz44otITk72/+X8FW8RAiCB3eAQAAnMfkFvHQIg/ptUDECCvbHnAIQe0LTpnaxMBjx4exonByaT9enL9xcbgHgCHhPFbwfLa0G2CBbI9Kaq7imMzFctD+qTb6w5wdx98y0GLZ4AidgrQGFOzR0VqO+tQqokDmE7jiB29nzo16xhoTScrE52Sfj6N5C0F5AMj7AlQ2lzeUYs8lIMWQ0403TE5VSfvBnugILatg004vOKf6A4ec44IUPaeJMKu6x2ANKqfpgXJ2FH347xquEp85GkSXdZvmJSPPVD2aZk4XIhta/NYUPLQK2L1sb64q/BPmp3ybjFw6FIidxdWZzsy21IWavEmbrWpVyH4vJo2DPULh6QoVvVcOQcwBnjQuyv/EQYM3lD2vqbEK9OQWxUAvpN3UJYFoGz1UUbmQeEQAiVlQXXIzt2zPNAY6DxMTVxD+mCffld8zoTeRfCZWH47d3bWXhWarEe6x+aiSvWZ4zrXsxNIS/JSN58PPPdMsbVuOOpJWit6MW9z68YB5TEIWEJWRo89Md1+Mu/7UPdqS52DXcPB7+wO+fnfwsA8TbPyYCJJ7K7Lx5Tf9bRRGPzxsFZv349Pv74Y0ReCJcLxvW+Kn2EAEhgdzIEQAKzX9BbhwCI/yadbgDiizfAV+DBZxdIWJcnC3EvBBfD89+Kri28ARp6iXIuBLXgHo/JXpTB8loEE4C4p212DyPzV0SQZ5ERa3n4shnh3hLxCTkHJtRXzTPPwEKCbtXVbEMbu24d8rdsgZisTtdRXTEH2Y4FkNUZ2GV5Rix/MmEJdTvLkabPgTxcDqvdgsaeGiEVsFyqgOJcL0bqu1FbaEajrRkJunTsq3QK9DEi91A3ludf62ICb9omvBKpvDf31UCnimOk90x9HvOkHKze7gJweDjUwPHjzB7pTz4uZPtiwEaTDhqne0asnJhCrFetwUicAvL6bsjOGTFSLIEjvQ0jkTocbe3HuZbjLBSLCvFBohRqaJQxsI1Y0GlsYx4hru/RYWhhaXt7BttZdrHs2CKsKtwobOInShfs72/UG0E9pSAG7/3yC6E7d48E/4Jl5yKOx+nTcKQV4LNPjNj+ylgY2rzrspl4Yd7ixHHDcg8Jy56bgNoTHX55OCab61fJAzLZXMXfi3/z7t5UXu9ieEsm8oAsW7YMhw4d8il81J+5fxXqhgBIYHcxBEACs1/QW4cAiP8mFQOQYG/saTQTeRf8BR58dlMJ65rIMpOFE/lrVfc5TxV48OsGy2vBAUgw0iJzAEKgbaIwsolS6nKCOW0SOLl8MjA20b3w5C0Z2LcPlY8+KjSjE38SbzOfOePiAYm7515olRmION0NW4ketiw1HJFSli1LLGhIp/RtA01Ii8kWtEUEAOBF/JC+52OjOWu2NqBs5iB2tP6DNaUNeaImfSyVrSYVfUNdLO0vgQFxcSfFu3tg+PfkXSBehVqhw7K8a8bxQsQekMLnnkN/cbxLCJi7aCMfA809LSqb6WPIbcQTeZFxQwzSm1BtuwO1XfWIVyezsCYCFOLMXjNT5mEUYThcswu58cUuniGqV9ZyAsvzr0G8KC1v1eOPe0wX7G84Fh//RAR1XsebR0K8oT31aT0jtfPy7RfWYPa6NERqvXt5OTdE3M9U5+H+G/iyAxBvKWz9fe7y+pN5S6geP6RwBypTueZE9icAcvjw4al0+5VvEwIggd3iEAAJzH5Bbx0CIP6bVAxAgr2xp9F4AiCThelMNotgj9P9NH+y60/2Pd+QU2rZqXg83PsPJgAJVpgdD8HigMEfEUEOyOivJy2Pyezrz/e2/n6mQ9G9axcTuqOMT2FRUQizWIQTbZZVKD0d1pYW2FpbIUtOhiI7GxKVim3Ma7vOC5ekTf/qnGsxXFEB04kTiJw9G4q8PI91CxJnY3HqejSc7WZieDNWpaF4WTJiDCPYPrQLNb1OjYuChNmYkTof51qOeQQ3Q31mNBmrsL/e6Slx56BQ6NfOc+8JHgj+Pc+4RR6SLH0+tD0j6Prrm8wemoULsa9517g5rsy/AZQ1q2WgDvWUSleXAa0yFoNWAxp7qpGjj0NOxIdQj7yPk/aXsbPiiGAjElUcBdBtbGNA5MbiOzEw3IuGgVpkaLIZN+bTKqdKfXZsIdblJEBuPwjTaDb6HDOgiEiDaf+hceBRu2qVP7ffpa67N4L4FVTEpPWCJcmImoRz4dpPDuOSeONpcGHEY9tqMf/6bIGsPuVJeGgYAiCTW9PdW0It3AHgVL0l3uxP75WVK1cyD0iojLdACIAEtipCACQw+wW9dQiA+G9S8UlQsDf2NBqxdyFQ4MFn50tYlz+WmA4AQrbkLzSuXj7V0/1ggQaySaB9ib059P/cm8Ln5s3jQdf2VcvDn3vnb12eJYtCaSLnzoU8JwejERGwnD3LwrKo0OdhcXHoP34cuOc67KlznnbTpj6BMjX9aUyMjwrpQUReAO9KngAAIABJREFUcYWLt4R7NZp6qpGhTEO0UYldr7Uib2k2Fq3LQE1/BT6r/kjowxuhnVf44sManP+iHjNuVaMnrAkZunxkJuUworptYACGo0cZV0K7cjl6M6OhiNEjLjoZ3YMd6B3sQGx0EhLVqXCMOliKYMNwLxLUKdAo9Sz8SuzlIQBBSubx0clo6q9BVUcphszGcZyW9QULkBXVjJ0NatR2VwhzydYXoCAqD+UD5chLmAmbddjFhquyrkavrR/l7aeZp6YkaTbCR7tR1d2JHL0OcSolOs3xSJTEYvDECZa+ltLWRlO64Ohol3CWqfymvPErvGUy8rbGfOFpePK6uJPV/V3D7vV5GOKXKQuWeA7B9oD4Y09fvSXUpyeeCQcyXK9HfG2DwYDbb78dO3fu9GdI/2vqhgBIYLc6BEACs1/QW4cAiP8mFQOQYG/sOQCh0C7ahHNhPXd+gL+jDvY4xeFEU9nQ8PHzkzACH5425/7Ok9cPFDSIrxtIX9ybQ3Oj+0n3gQskXu7Ag9vAnXzOwQPnhLBUrHPmCKJ0+ttvQfjXN6DBUI+suDGtCtN7H2FEpEqtIj2Ie+4RtD2aemuRqElzIYOvTFqJyNowbP/HML71m1VC3drOcmSoM6E4WQulUg31ggWQaTTjlsqHzx3Djj+OqbATWTohU836odLz2WeuwoLPPsuI9pQumPgVYh0Sq92Kxp5K6CJj2eeke0LaJF3G1gvZvlJYCBh5LggUNfXUoKLjDBNIHJfVK7YAM5OL0DFocAmpWha7BKaf/gapj/07JHnpON3wT9T2VjoBSkw+5mWvZEKFNMb02FymC8JV5tcVLseAJRwzUxa6pAeezjj/ieL4p/q79cY7IV2PYIVf0di+CgDkUosout/jyYCJGIzwZ587AGxsbMTDDz+Md95xCnVOdS1N1G737t3Yv3+/oBdExPdFi8YELqkQCZ7zUObNm4cbb3TNxDcdY/KlzxAA8cVK3uuEAEhg9gt66xAA8d+kYgAS7GxQ9BCnzTg/WfSUZtb/EQc/bS6NM1CxP7HQHgdbwcp8EghocLfvVHg+nkQEqV9uMzH3Qnw97i3hGWImExGcylrwt42YfE5gQ71iBTQbNghZsRS5uehvbnYRjYvftAk5jz7K1rHdYIDx8GH0fP45tPPmQTI8DNWsWVDMmsWGwtf63sqtrmFNMfmYUx+JTt1s8NAfm9GIodJS1P7qV5DHxzOifM4jjzDwwIvg3di1G2EFC/HFKTl2/rUOP3ztGsy5Zizta+Vjj6FbdMrKifZlbSdwsGq70Bd5NsLCJIgIl+NA1fZxoVonGg6gtOWY8DmFmxUlzcHHZ/7OwMec9Ctds3oV3cT4MCMOq0B8T9VmInJ/GXreeh/qFzejsa8Gaao07K1zjmNl1gaEySOwp9wpcMj5IkRgz44twOz0q2AY7nOKFLqJEPqzQSQDTHawMB0AhK4b8oBM/gv11/M0eY/TU8M9jMsTiKR11trayg7b+vr68PLLL+NPIm/pdIysoqICGRkZoJBfuubTTz+Nn/zkJ4iNjUVlZSVef/11PProo+w38B//8R/YuHEjSkpKpmMofvUZAiB+mWtc5RAACcx+QW8dAiD+m3Q6AIg41IqTL/lJuf8jHN9iOoASbabpAe6uOj3ZeMVCegQ8CGTR/Ak0BGvOUwEN3sbtT18TaXlw0MZPLvk64mEpPKWuL+rlk9k4mN9zD4h28TLEpFwBZYudkc4tqUqY6isxXF6OUY0GlU88IVy24IJHgT5w9zbkb94MzbJlLIxLXJoHaly1PZJWIr5fCWluIVQ6BatK3JTBigo6wobxzBlEz5qFMKkUSbffLnTlfr3kf3sCjqIrMBpnQH1vBbLiCqHttKL83gfGjZfCqohEzwtlmSpMno3zrSeRoEnFiN2Gs81HkaLLZOmE3Qn362d8jWXEIm4JaXsQGGHK5V0VSNfnwGKzQBERCZPVgPOtp6BSRKMkaT7U5zsAvQZdsYDRbEBWdDb6hjrHOCDaHGhVsSjrPM08K7xQxiwSeaTsXevyr8ewdRi7qp18FxpfRkz+hEvB1w2iGJBwYDJdAMQT72QyXQ9/17tYR8PftpdD/S8LAPFmKxq/eE199NFHzONA2QvpnTBz5kymA5Kamsr+0+v1fr9n/LlPmzdvZurr+fn5DHzExMRgw4YNrIt9+/ahtrYW9913nz9dTkvdEAAJzKwhABKY/YLeOgRA/DepGIAEmg3KHXjQZpw2oIF6F9xnFeg4PVnJX60NXzbnX1YA4quIIN0HvnHzdBooTqk72Qm0/yt3ai0YB6S2FmqTBpptrUInPO0ufcC8DseOCdwD9fz5QlhUxaOPjsvMlPPUUywMhnt4yBZ0kt8+0MREBjNUGUiABoqYeCaqx39zdc8/j6icHFRv2SKMI++JJxB33XXCv929G+SNkXznFhfOxprCTdCWd6N7+3bErFoFe3EGKgarWNjUXpGXgbJYHarZJXg4SBxQWduNiJICJCTnOcPCuspRopmB8LJ69O7ZC/2qVUJoGM2tncjuZe8jR5mB1NZRmA8eQ9Tyq4AZWQiLjkKMKh7GvnaM1jZhtLwGipnFqFENIjomATa7lSm+p+lzXYQKyTujsSsRfq4e/Xv3sf7qE+0oM44BKEb+L9zE7MwLX3OTrS1fvSVUb7pCgXzhi0xtRY+FYFHx9/BkqtcLdrsvOwDxZH/6jEKfjh8/juXLl6OlpYX919bWhttuuw0rVqwIthlZf+fPn8err76Kp556ChTq/Pvf/x4LFy7EggUL2PelpaXYvn07fvzjH0/L9f3pNARA/LHW+LohABKY/YLeOgRA/DepGIBMlYztCXiI42H93dxPNgtvIniTtZvoe1+1NibbnNM1ghHSJR4reS3oPtELJdAyUaIB8X30pEDvS0pd8UZIHLMv9pCI/z/Q+Uy1fdSbVW5q3k7hwYn67NjxKWoe/5lQJWfLU4hdvW7cxtXe18cUs20dHZAlJUGekYEwtVoAbNTB8NmzaH/7bZdwL/3atUwckBd3D0jJH/6Ao0pSNRdl5tIXoPCkCeqSEtjT4/FR+VsMZBARnkAI0yGJK8SQZRCHapyEWK4HknDLLYhdu1a45sjQEPr27kXV5s0u84xevoyFb+2r2oaWvnqs6EtHy+ZfCHVSn3wUe7X1WFV4A9R13eh/7XXhu8g7bkFXWiQOVu8QPiOhwvb+JsRR6t6hLqRUDLr0l/LkT7BP28DmQiArO35MpJCXiUL/fAUl/PfqLZyGvvdGPp7q2gt2uy8zAJkuz1OwbTxRf97s/7e//Q0DAwP4wQ9+IDSfCtj65S9/ia6uMeFK8dqndfnYY49Bp9Oxjwng/O53v8O3v/1t5OTksM/cAcjZs2exY8eOEAC5mAtkmq4VAiDTZNipdhsCIP5bzhMA8fXknl4eE2lA8NH4urn3dfRTBUoT9T9Zqlsx8PC0OXd/OUw1pMvTGIOZncxTX8EAHrSOPGl5iDeJnjaMnkK4fF0HgdSTl/a4qHmLPSAT9Xu+8iAiqzth2n8EkcsWwZQbj6L8JeOaDH3xBbr//nfh89i77oLqwikk3/SOGAzoP3DAZaOf/8wz0NDpqNkMW3U1bL29sFmt6Nm/H7Fr1jBPRJO11cUDQroeEZ8egyIxEcZz56BcuhBNyWDeA0oFzAUN3UOsqJ3pid8h/pprkPqAM4SLQsPa3nwTPXv3CuPXrV0N7b//CxLUaajvrURZ63HkvH4Wfbt2O+usWQ37t65DYl84HKXlGD7jDLFSXjEbjatycbLhgFCfCxXGqOIwbBmEbsc5dLz5NhOMpEJgbOjbVyNyyIF4SQyi84oE75E3ECv2driHZFGf3oCJeCPM74/4Lx+0OxiZDOgEskZ9bRsCIL5aanrqecvi9Yc//AFqtRr33HPP9FxY1CvxTl544QXcfffdKCx06geFQrCm3fSX7AIhAHLJTO/5wiEA4v8NEQMQX0/ufQUefDSTbe79HbWv4/SnXxqjJ4E+erlzzslkwEN8vWB6faYLgEx2HyfyePC2NGd/tTzcN4l88yfe5PF1ycNKgr3Rk5hGmOq5rLTHRXjQ25qhMdJGo6GvihG7KX1s72AXluVfPU4wkProeuUVpprNC+mFxLnFXbNwsMZGDFZWou/IEcReCHUKV6thPn0aXRfSAlPYVty3voXwjAzmaSF1dQqDIkCRJktE2I4jUKn///a+A9yq4mp7IeXCpVwuvSNNqqAiiAWNJTZUlP9TREUxCVGxF2ygBnsviVE/A7ZoBMUENRYgHyoiKgoKUiT0jvTexf95B9dh7mafs2efmX3OPueueZ77AJep78zee72zWk1a+Oc/J8Zj7YE+v22b19PyjYtp0cZ51PCXGlR9yRYqKFOO9qxYQYjkxflMYBJW2LRpif6aDBlM81uUU2QGeUV+2rSUyk36kRbdc19iTGhA4MOy4rFnqNXNN9Omj/eHL65xaV9a3rAcjZ+9L/kiChzPN2/fQA1rNKdtOzfR8nULqeHeYiozdhKtHf4ONb/1ViqoV48WDx1KNY47jhr+7neJiE86ucDZ0Iks+vaeFz/yq5tw8Rn0C2XrJTJx05YIAQnzpndfNxkBefjhh6ljx47Us2dP94NqPcKsC5qPSy65hNq1K6klZCd0OKXjmXjsscfo7LPPVn4p2S5igmW3A0JA7PBz3loISHqQspDHgn0yZ2w/gdXEZtplFCesMAoC4p1jkFYgCGmXWh+XYYfRFz6YHEYX6zBNIoi6UebySKUtyZYJFwumLGT8TLuVUzaS+sGsCWF5kYvDW4I0IKjPDvEq9G+DBlT1hBOo8FfBQI/WhbrVzz6b9vzyi8r1gZwYVTp3pnJVq9LGL76glcOHq7/rGosap5xMxbdfTcWFtalCuX0ZumHONe+RR6hh375UrqiIKhYV0YZRoxJT55DEqLf+yy+psHlz2jx1KhUf353Wtq5JNeo2obrVGiXq71i3ljZ++w1t+HS8yj+yt93BtPWVkbTqvfeo3nnnUfHhh6vEjmUPbU27GtWmrWV30c97f6atOzdRxQpVlNlVcWFN+nnvnhLRteCbUrRwE21oXIVq1GpEm7ato4Wb5lOzuu2ogYa37XlhIoEzrYey1YlJqudcJ9L8XtLrZ0pbkg8EJFdzmGC/k5lVQeg/66yzVDLCKMvTTz9NCPkLZ3MuvXr1SpAR+KJMnDhREZAjjzxSwvBGuRkZ7FsISAbBNhlKCIgJSgfW0Z0X/W7u0yUePFJUBCSdqFXJEMIc8RFkwdw2Z4lLrY8rAoJ95LDI+BhxWGQWlOKYy0MXEjNpwuUlHrpDvclTpnxA5s6lbdOnU2GHDoTwvmV/tdXm9l6SwflEdHKCv4OgVOre/YDIXMUnnqjMlbZMm0a7Vq+m+Y8+mpha6wceoEp169K2775T2doLWrakeQ89lAjXW+P446lm+/YltDQYv/iSS5QT/tYpU2j9V19RrdNPo3JF1ejnZSto14IFqq+yVavSlokT1d831CukXeX3mWIuWvtfalK1Ke19e6zSYIDkNL3/bvq0zAyqVaUudSo6lH6ePoc2fDaeik44nsoc2pyW7V5Fa7eupoV6IsNabahBxfpUedYK2v7FN1Tx2CNpaYMyyqQsKGFjKlKisDzooBJmXDr5wLOP/w/SltiQErTVtc78b5MzlaxONhP52cybSRsHcLDtK1vtkxGQAQMG0NVXX02HHXZYtqYW63FFA2K3PUJA7PBz3loISHqQ6gREF5xtiQfPJkzoV9MVuDRxwpggICics8I2Z4lrAoKPHAhXOoWFaSYyEIDQlwnxYNOjOOXyiNKEi4VPCNQoEEq9AmM6e+DXJllSRHUOYZ41Z44iCFWPPZYWvvRSiehbnOuD++XIXdCQ1DrpJKpUvz6tfvHFxLC1+vWjHRs30uyBA/etq6iI2t13H60dPnx/nYsuogrt2lG5ypUTZ2P9F18Qbd5c0pzq3HNpw5gxtHfbNqp7UT9a0bgc/WfO/pweKs/Hqx9S+SPa09L6+3xRTmp9LlX5fiHNu2t/eOMW999L249oSZt3rC2ZyLDVGVT5h6W0ZPC9ibmxSRmHDA6zB0HnBX0F+SLxuWChmcePg7ZECEiY0+C+bjICcvHFFxMcyJs125evR0pJBISA2J0IISB2+DlvLQQkPUh1AsKaAPQEgRX/x+F007XDdxnFiVfoSsDXSRb6LigoUJoQ2+JS62OT98SbRBDr0skMm5547drjSDyC9sTWJCdK8zK/ueskA9oE9sHwq5ss23kyTPy0K9V79aKNX3+dMOOqethhtGf+fKWlqdisGe1auZIqtW1LhdqN7dKhQwmx17ZPn54YCnNVc587l6qfdjpNbryd5q3bn2+kGTKkN+pKWzeuoQWbFlCDyi2oVkFjWvuXR2ndf/4v0Q/MxCrc2JcOKlOWtu/eSsvXL6KmtVpRUaUatObBPx/g4D6vz6HUvkFnX5+boLOhEwbOUcO+I0wqdJJhavIXB22JEBDT3Xdfjy93/EyRYX41YsQIql69uvuB86BHISB2mygExA4/562FgKQHqe4DAsEZL1UXxINn49KJ2hUBYeLBN90scICAuCjZJiDJwgUzmYHfhy5w+QlocUsimM6+mJhw6QJo1Gvesm4Hzfx8GX37/jw68uwW1P74honEhKnWlyo3iV+7VNoVJqHAZsPIkfTzmjW0a/lypdEohBnWxRers4FnYtMXX1CZ7duTa0DO70sr65Wnscs+SEwDOT3KlylPZT6YSBWqVaNdx7Sjldt/ohbzfqb5mgak+f1DVJhdlOZ12lKl8pWpqGKxSpK4ftwnJcIdN733LtrTpY3yQfHzuQk6G6YmdV5tCRN07l8nJskCJGRaW8LayXQviIKwi/L/dd+bKMeJqu9UBAT5PyZMmODkQiuq+WezXyEgdugLAbHDz3lrISDpQYoPF4fTRQ/QAEBAdfVBc+XDoK8uXQGfb/YxJxQ2tcK/8X+uCIhLszPeG4RHDipBeUqwTl67Hj0I/bI9PIfUzdXEZkEY6aTEK2CirYmQiXo6meh6bkuq3aQa/d+wH6jDSU2oXfeGVKXGgSZzk96dR3/9/ejEFK8Zdhp16bkvZr/Lkky7wsQbf+I53/nDD7T6lVcSQ8MRvWLHjgly+vOmTbRr8WLau2FDSR+QLyZSlWZtqPraarS7wkE0t/Numr9+DtUpaqicy2evnEbH1+5OlStVo3HLx6lcHmc17EFlf1xM6z+fQMXdj6OKndrT99tmUnHl2ioDetOaLalyQVX6ccXUXxMhLqJ1n3yinO71ZJBhcXKh2bLVrnmJDa/BlQmXfm51shQWq0zXz2cC0r17d/rqq68yDWnOjCcExG6rhIDY4ee8tRCQ8JDiA8gaCgjjrM53kfSOZxMVAeGwuCarTkY8mGS5nqNLAmKS+R3rwxpAVoKSCOpmV6lueJPlWjDBO851vLfh7OehC5lb1u+kHycsp8n/nk+dz2pObY6tT5WLCxLZpoHNN+/NV2Si+0VtqWHrYpo3+Sdq1aUeLZm1jjqd3EQRi+2bd9GsCcvoq3fm0EmXd6BxL0+nr0fNTcBz1LktacDQUyOHK5lJnYkZmC4883kpt/sXqrBoCxVMW0u721eivQfPp6/XlqHpyyYnMq03r9maWn25ln6pX5NWNi6gekt20k9PP0+VW7akrXPnUvPbbqONHRvQuB/fTaz/uFan0zcLPlN9nNr+f6hpzVZpY6OvOWyoaJNB/XDh3+mEQDfPSRYeGPX1tqyBCpoHn2XuV++D5+D3Z1C/mfr/XI7gxXuWzIleCEjqUyQExO4pEwJih5/z1kJAwkPKQhcnkYvCXMrGhyHZikwF/CDioZMkG0dv7zxd+r2kIiBhiIdXwOGbYcxd93vRBXFdkPLaxYc/bdltYWqGg1mypqJKcUVq1K4m9bq9C234adt+QnJcA3rj9gm0cOpqOvWKjvT32z9PLK7PvcdSQWE5ZVo16d251KJzXVo2ez1999EC6nPvMfS3a/cn74tKA8KTCbPmMLujnyUmJciRMm7W/rC+SHS46cYHVKSuFn95gta9+wGt/8/+tatEg1ecQZO15ITNarWhvb/8TIvWzqHmtdvSyW3PDTMtVVdfc9QmdX6Ty7S2xOsErRMjL7Hh+bqOxBV6k35tkK8EBBr6Hj160Pjx49OFJu/bCQGx22IhIHb4OW8tBCQ9SPWPkWtNAGZkcoMfduZBAj4LIbweTjKYzKzMNUlySeTwkcYHrbCwMAETm9LogQJ0EhGURBB7wmY4yXK5sCCja0x0wTMoclDYPY2qPguEJmvmOTz3hzFUobC80mwsmbmW2hzTkIZdv194vnrYaVRUp5A2/LSVJo2aS9/+e35i+p17NKffXNqOnuj97xKk5P2nJlPPW46k4nqV6Zv351GXs1tQ2ySmWrZY8JpxrtmkLqpoXjxXJChcsWFRIkHiL+99psLxotQ+52yq1rVLCb8OJBrceFwrGv/f/ckJ4T+yeN08Wrx2bmDIXS9GfmuOixlhKlKCdejmkN78ITqZ9CMXpj4gQcTEO64rE9xUZzlfCciqVavoqquuovfee8/2Uc7b9kJA7LZWCIgdfs5bCwFJD1JdMHEtiEdFQFIJ+N7IT2xikwqdMH4WJihHRUC8Gp1MJxHUhRgmeWHNTkzwc1UnXfv/KR8toJ/mb6Th90ykNsc2pMrVC2j2xOVKG7J05lpFHI6/uC3975X/obNuOELV43LF86cos6vxb8xK/K7L2c1p87qddPLv2tORZzePLLQvBkx3za4wRz/rPvuMfvw15C/+jUzqm1vWouJpK1QkrqqdOtGO5cupwiXn0Pq9G5UPSL2iRlRcWEsleWxco3nSJI9+84zDmtPBz0Zb4l2zPj4/k0EkIiwpYbKUzlqT7Rt+HxeiGHZdyXxYZs+eTciE/vrrr4ftstTUFwJit9VCQOzwc95aCEh6kEZNQPxu8NOb6f5WfpqadIgH9+haS+NSk8T4QYvDUbvCJBFkbQn+jMokxUaQsj0Lfu2ZqKWbvwS+G8Ou/4S+eW8ewQzr6ue6U9WdK6n8irm0u35L2lXcmMa9OY8mDJ+tfEAatalBcyatoG7ntVLk5LvRC2moZmr1hz+fRNXqVKSDO9WmSkXlE1P2apFsBDzbNbvcBz1qV40TT6Sf2zWl2VvmUJtlBbT6rZHKBwSmWW1eHUqbalekdVtXUY3Kdah2lQZUUK5iIgpXkNlfnNbsCj8TbQnGQr1kASP0PrzExJSU8Bj6n9yXK21JLocQZrLvR6AmTZpEb775Jj377LOujkXe9SMExG5LhYDY4ee8tRCQ9CDVCYhrQZxf0jAhQhSnoI+f6Qp0AT8o8pNJn67X7YqAsICla1TYX4fXpZtIeYUNznkQFfFIhW02SIlLgRRakGf6fqQIyD3/2462v7c/aV/huX1o6rxC+vtt+3w/UOfaV06nNsc2UP/+5JUZygfk+zELqUn7WnRQ2TLKV4SLFxs2RVEEZOdO2j13Lm2dNo0q/5rFvGyVKqopO40jOtVBFSvS9lmzVEby8i1a0C8F+5zkvefD5Pxnqk5QOGHTM8NCMXDDO8VEy5mpNUYxDuPCkeq8Y3iJmp+5nVd7qZ9Fde7KpBZpotCW5CsBGTt2LE2cOJHuv//+KI5DXvQpBMRuG4WA2OHnvLUQkPQg1T9WUWgr8OFC4kCXBIRNpiBw4SMGAQRagaCPaDKEXK/bhSmbrtHBvJG9XDdViCvxCCIluvDIghW3MbGF9+ufzcFYoOGoR2GfCD0qVMVDO9LyTUU0/cs1dFy9mbR96veJ7grad6LJOw6jsmUPoiUz11D3Pm2pcbsainSgj41TZ9HOmT8QNW1NX3y+i5p0bhwYbpex2DF1Kq1+9dXEWMhiXqF9e3W2d/3wA619+20q+u1vaf27+6NHoU6ljh1z1pTF9MykMvvjs2MiTIc9F9mur5tbMdnCek0Jm05QvGvx05aENeHiZ1r/U3+m9T3R39H5SkBGjhxJS5YsoVtvvTXbRye24wsBsdsaISB2+DlvLQQkPUj9CIhLssAExCtApzfbfTbu0AjgT3yM8WNrQ8wExNW6bQiIV6OD9UGDxPilIh4sqCQzzUgX86jbpdQIlCmT8JnwJn9zRTx4fd4EfkUX9qXPJhJ1abeDdn/89n4C0qM3PXnnfDrqjIZ0yplVaffs6UoTgWzmO+bMKZFbo6j3JVS+TQejhIMYwJvFvEq3blSjd28lbK79+99p7+bNdFBhIW2bNi0xHyQQLLr4Qlq6fgEtWPMjNavdhhoUNU0raV/Ue51u/7opoa7l8Z4dFnb9tALpjp2tdulo9LyaDn5f6IQgCJtMaUvYjCzqAAlR7V8yJ/qXXnpJfZP69+8f1dA5368QELstFAJih5/z1kJA0oNUf/lHoa3ArLZt23bADX7Y2eJlz4I9Xu74tx4ZKmx/en3X607HqT2VKRnw05NDsoCANbgWwm1wdNk26HaX144/XZkeeYX/SocfRktOaEl1qQ5VW72Zds6cTpXatqWft22nnQdVpooFROvf3O9oikR+23/8kbZoCcgqH3441brsMl9o/PJw6ASmylFHUcUWLWjbzJlUqU0bKlejhiI3fhqQVY0K6T8z90WdQkEI24Nrto7U4d3lfifrK4wQzs9Fssht6WrYMrFO7/tIv0xwYWIW9DwFkRJ+3rxay0xpSzK9BybjJdPgPPnkk9SsWTO64IILTLoplXWEgNhtuxAQO/yctxYCkj6kfLPsWlvBM4IJFgRoPVSs6WwxJ2+SPfwOWhCT7OAm47gmIGF8SvzW5zW1Qthh/UPPwgKTD9Z45OpNoskeecmWXxvb0MBeDUilPr3o45+nqMR4p3e4gOqs+4VWvfQS7QWhbtmSDqpShdCGS+Fhh1G1Y4+llX/9a+J3tS6+mCq1a0cHVa58wJS3/fBVK3dIAAAgAElEQVQDbf7sM9q1fLnqE3WhRdm5cKEiMhWbN6c1//hHol3NPn0UCdm9YgUdVKkSbZ85M6F5+X7NdzR92bf7EwHWaksnHHKWIuomPgKme5Cpei6JtQvhO1Pr9ppb2Wp3U81b13T4aVb1c+PVPnK/OiHxXoygTiqzWBbg2ZyMn3F9zq4c3qPYv2QE5J577qHf/OY3dOqp0ScZjWJdmehTCIgdykJA7PBz3loISPqQ6h85F9oK70xAQDgXh+ksUwnmrn02MCeX6zYhICbEgz/IugCVrqBgintc6yW7CTc1OUmVkZrXrGskDmp3CM2utIamr5uu/rtz0+7U5NN5tPW779S/YQZV/cwzad3IkQnIavTsSeUbN6afN2yg3atXU7maNWnvjh1UrriYCg89tAS0GAt97fjvf6mgWTPavXIl7d2+naodfzwVtGyp6no1MoUdOxK0IpXat0/0xXPeAh+V1s1pXpWNas6ntDtPaUBQck0jkMznweXZjBsp0c93FJnbw2DnAhu9D52s6KTEm0TRW09//3nnHwdikmz+N9xwA1122WXUtWvXMLCXqrpCQOy2WwiIHX7OWwsBSR9SnYDYaCuSzQA+DOyvETRLfLh0J3MOOau3c+2z4ZqApCJIQetju2KvqQMLknpCPf4IewUG/sibmFUE7Ue2/z+MCY4+1yAhCr4UW6ZMoTWffEK1TjyRqnXpQuWLihJdLFw7h8bO2E8uTm3/P1R7yVZlAgXyUaFBAyo6/XTas2rVPm1Fs2a0a+VKKl+/vtJW7Zw/n8o3akQFjRvT3vXracfcuQltBbQh26ZModWvvVaCvJQpV452LluW8PnwOqSD4OxcuZJq9emTaOfV2lS9uDetb1pEdYsaUZWCar7b58WmRBQuzecmlfNyFOeCnw38mQ0h3JTMunR41zU9rkwJo9qbIDKrm7jpREMnFowxR/RKplnxW4O+P0xO9HqZJiXJCMjll19OgwcPpjZt2kSxFXnRpxAQu20UAmKHn/PWQkDSh1QnIGHIgumIMCHCGCATyUqQYO4VLl1H1nJJvPwIEgvSMCfDhxJY6LfypsQjSEgJErxzhZS4NMHxCkDoe8Mnn9DsO+9MHKtDHnyQik88Uf0bGMPsasXGxSoxXvPabVRivAq79ipzqd0//aQIRWVEnioqoo0ffaR+j1J8zjm0dvj+kL0wm0LEKphYocBPBKZaIDJe8y2QmLJFRSqs7q65c+nnzZupbMWKtG3GDKp48MG0e906NWZBq1aJeR/gt3JYJ5rRrSa1qX8Y1S9qYvqIOomoZDyYp2K6JDPd8cK2i+qZYk0P5pNu5Lawa3FdPyw2GJ/Dg+tr9l64MNkIimzI9ZiQ6P/mtUZFTJIRkF69etHQoUOpbt26ruHOm/6EgNhtpRAQO/yctxYCkj6k2SQgfsRDF8z9VoU2IAyuImthDJcEhOfHPiocUhfjhE0i6CKXh35zmMyES/efwDyDPvzpn7bULaMgHn4j/nfQIFozdmziv2qecgrVO+EEqlBcm6ruqUkHVa1CO5pVpr0Vy+1L+LZjL1VYvJk2rp9Pq97a73he65JLqEylSrR76VLlv7Fp/PiSxKJTp335O+bOVWOxU/rmCRNKmG/VvOACKl+vHpWpXZv2zJ2bCMULbUutvn1pz4YNah7QtlQ+7DA1ltKkfP99iahb1S6+kKqUr09Fs3fQz+1r0e7mRbS3sFxa26XfVuuCpi7Y2ZybTO11WosPaGSDjU64sqHpiQIPvc9UpITr4dykMovUCYmXZJi8m6LWlvDZ9ftWnXzyyTRmzBj1fZLij4AQELuTIQTEDj/nrYWApA+pTkBMtBVhR9IT6XFbXSPgJ5gHjeHSZwNjudT8MAGB4z00HsnWl+1cHl5BIZkpThgziaB9S/X/uu1/1ILZ2v/8p4QGpOWtt9LOKVOUpqLueX2o/hdlaes5zWl72yKlHSictZEqfvMTzadJtHWa5njeqRNVPfpo2vL111R4xBH0y+7dtEYzrap10UW0btSohAaEndKhMdmzejVtnz2bKh5yCJWvWZMKd1Wjg2pXp58+e69kJK0uXZRD+toRIxLwsSZF9wEp06YFVa9+MNV7fVmi3pYLD6Gd7WvYbMsBbcPeevsJjJnca6eLNyAmfvigmW4ymWuhsm0w5Esm/Kl/a3SSYRIoQScVXlKi45tsri61JakISPfu3ekrLRKeDXb52lYIiN3OCgGxw895ayEg6UOqfxT8yEL6Pe9riT7xwi4oKFB/ptIImI7lUmPhmoDAh4VxZOd7XQiLcy4PF8Kl6R5yvWwIo3pW7updu1KZjRuVXwZK5Y6HUXPqSnsrl6ctvfeZO1UZMYfKz9tIy4//hVaNfCOxRK+JVd0rr1QO5Tvmz1d+IeWbNqWf16yhbdOnJ/xEEMoXZlQ7Zs+mLRMnKvMtOKmDZGyfOUtFzdoxf54iNSh1+venLZMm0bapUxPjIkRw9Yv7UIVyBfuesT07af221dTso61Uafr6RL2dHWom1hB2X8LUNz036JPPf5A5YZjx41xX1/R452kieMd5banmpmt6ku11kLbEG9kO43kJbTa0JbynfpEdhYAEn1ghIMEYpaohBMQOP+ethYCkD6kevjUKAgItAGcsT6URCLMC1wTEheYHghUnScRaQLj0D1SciUeQIJHqVjddvxITASXMmUi3LsLhrh42LNGcNSDbejZPaA8Kpq9VJGRL12JaV2cjbZsxXWkuftmzh9aPGpVoi4SEv/z8M/2yY4ciFjCVqtC4Me348cdEuF2YYRVfcgmte/112vbdd8qp/YDcHhdfTDvmzaNKrVurcL+7li4tkf28sM//o20t61HTmvv9QdSZ+3WePKEoNCCmOOs31ux0rLfVnZa9dvqmY8S9nn77r2v1vLf5/G7g9ZiEwI3z2jlvUzqaHi82LOz7YZMsUIIrbYnXlMuLuX55h7ngO3fSSSfRxIkTI92eTz/9lMaPH680SsD6uOOOU+OiYM7Dhw+nGTNmKLKG35/4q39bpJMK0bkQkBBg+VQVAmKHn/PWQkDSh1QnICAIeKFBeHZR8DLkPB4Yh6NhmdjxphrfpckUxrEhIMBLJ1nQeoAgMQFJ5mCu34zyh1rfCxf4R9WHV7jUbyExZqqcHHEhHoyNHn63crtDqerumlS2qCrtblYt4T9x0LY9VH7BJio/fS1tO6qYtu/eQFumTaWChg1LOJ3DxGrdv/6VMLmqce658DCmde/sTxJYq18/qtC+Pe2eMUP5b6icIp7s5noCQzial6lQgSrUq0c7Fiygiq1b06K6e6luxXpUZcVm2jp9GlXusM85vVyFSol57u5Qs8QaojoLqfrlcwGtoH7GoyC02VhfsjHTPeOmmqRkgne2MUhGuFzMywU2eh/6nPB7k29SMmLz2Wef0bfffkv16tWjr7/+mm655RZq1KiRs2S5Xvzw/WMfE/x9yJAhNGDAAGrcuDF9+eWXag4IB7x161Z64IEH6Nprr6X69eu72AYnfQgBsYNRCIgdfs5bCwFJH1Jd6OVs4y4c6NjUipOhoU+Tl7zJSlwTkHQ0Pzq5wu0mR7bC/EFAQLbwe69wzv/WQ+oGOd6bYBKHOvoH3u9WF3PkjziwSSc5ZRzWiTlsHD1aRaqC/wYTg8J27WjnokW09fvvqWLTpio0LwpIxvZ586jKkUdSWTibV6xIv2zfTrt+/JG2z5mzz8dDi57FPh5oy47mHP73oKOPoAllZtNpezrS6n/8PQFHnYsvpUpdjogLPOoiw/SMuxAu47BwP8Jlm0wwFTZYcxw0SfplSiZN68JoklxqS/jdxu93CPqzZs2i+fPnK+1H1apVacOGDVSzZk1FRI4//njq0KFDJEd048aN9OCDD9I111yjCMizzz5L3bp1oyOPPFKN984776hv0znnnBPJ+Ol0KgQkHdT2txECYoef89ZCQNKH1DUB0YkHXnzoHxoCV5nLsVIbjYUfUmEISCrigb69pli6gMAfavwZtaN1+ifCbUs2v9Gd3HmEXLaB9xKDqieckEg4CBMsEAuE0K3SuTPtLqpMPy9eTLtm/EiVO3aiSoccoqJYIfngps8+o71btuwjMgsXKh8QJDAsA1Jbpw6VrVWLdi9eTFunTqWCQ9vTiuK9VKvOwfTLWx/SViQg/LVU7nQY1bq8n9vNS6O3dG//vUMFadniIHjrc47y9t9vG7zEJFv5XGzMrdI4XkZNXBBaP22Jl/B4L1C+//57+tvf/kYvvvgibdmyhZYuXap+QAxat96XGNRVmTJlCr3//vu0evVqOvfcc+mUU05RXd97773Ut29fatasmfo3tDMLFiygfv2y/27gtQsBsTsFQkDs8HPeWghI+pDqBMQki3eykXTBG7f/TD7QJwhDYWFh+pP0tHRNQExMz1jAQF3Oa+L18cA0/T5+yWy8TTJ0OwMtCx0luwV3ISBkYTklhtRNt+D7waFxE7fBW7fSnnnzaOvsfYkK1725Pz+In4ajXK1aVNyjB619++39Jlw9e9JBtWpRefiCHHRQYnw8s7umTKVVb+xPZphtDYh+C87mlq40nl5B3+/8oE42CK0rwuXiPGfyudLXnQuXKSaEVie1fJ68Z4/faVyX3/n48/PPP6ePP/6YHnvsMavtfOSRRxSx8I6NMQcNGkTFxcWJ/1q3bh0999xz1L9/f5V7xEtA4C+ycOFCISBWOxKvxkJA4rUfJAQk/Q3RCQherjBvCkMW/HwgdMEjnT6DVhNGYxHUF/4/FQFh4sF27N7s7Ml8PPjDpOfyYCHSKyh4hadMhb41wSadOmHMb7h/FhB0Z33+XTYES9t174GPx6uvBvp4MJFBgsNdK1aUzCPSsSNVaNiQirufTOXnb6TyM9bR7vY1aMfBVWjvrh20CwTnVx+QCi1aEBVVSRCVKIT/ZJhk+xY8k4K3fl51YTSuyQRdCN7JhPBMmlul8zyatDE9O/w+x557140+cCl20003qSFfeOEFk6Gd1XnjjTcU+YAWREywnMEa246EgMRsa4SApL8hfgQE5lJBAoyXeEDr4WfvjJez68zlemjf9Fe+v6Wf7wvf8CWL3BWGeEA4SYan6Qcwro6nXuHERfJELynRTddYoGLSZpMMz8XZ8RJNFkTXvvYabU0S5UrXgCgCMn++ygtStkoVWvOPfySmVaNnTypbty4V762ronBx4ehW2SZtmTY7CrNfJoJ3umcnHYIdZu6ZqJvOe0dfd7L3fSbmHvUYqZ4rfu/MnDlT+TjBvGrevHl0xx130BlnnEHXX3+9U3Njv7WuWLEi4VS+efNmpXHp06cPtW3bNuGEft1116nvLpzQ4R/SoEGDqGEz7l9MsIyh8q0oBMQOP+ethYCkD6lOQEzIgk48vM7XfrMw6TPs7E1MpsL0qRMQFnb1XB5eAqHf0icTwG3MULItWIbBziuAZ+JW1Cs8JbN/j1qTlMr8Rs9SXuWoo6igRXPaPmsWwVyrUqt9PiAo3noVW7SgbTNnKpMu+IAUNG5MVd9dokLsckmV3yMdwTLu+x12fqnq2+ATJ3Mrl5hwX6mw4TpsehT1sxXF+sL26TUz40sk/P6jjz6i7777jlauXKmISMOGDalVq1bK6RykpGnTpr4XcmHn4FcfGo85c+aoQCcocHLHDwrehSNGjKDp06er8SUMrwvE49WHEJB47YeYYFnuh24ahFsTRKzyajPw0uWQuibEQ5+S68zlLqN1YZ7s+8LZy/ESj1sSwaAb3VShby2PR9LmTNaAH4dZtY36k+5cbQTLsGOarDuZj4h3LITZhaaES5Vu3ajmhReWqGab30M/O7o2SRcqg+zfUddk3WGxjEP9oLOjC+j4O/u3xWHuUc5BF8AxDj/b2XJ4j3Ktet/ecw5BX9dg4////e9/08MPP0xXXHGFEvKXLVuWcDpfvny58rlo3759pqacU+OIBsRuu4SA2OHnvLVoQOwg1YVGL1mwIR48K/TpTcxnM2PXBATESje18n5wUmk8vHbgukbJZo0mbU0ES79swiZ9p6rjJ4hmct2m8w8SLP18S4LWzWZHqMfnJMhcMVWfugYE9XTzLG6n5yFxmd8jDD46cXGxbtM9zFY9frbYpNA7j7hF4XKNE59z/OnnZB7m7MTx3ZAMr6B1g2jcdttt6nuG8Ldxyq/h+gxE1Z8QEDtkhYDY4ee8tRAQO0h1AsJZxvE71nj4RX0KM6LrzOU20br0eevmZPi91/clmZ8Hf3xBhFDiFgXGKxz43VimG4Er1+3f09UkRbVuU01JmOfNpm6QGY5X8LYhXzbzjLptMnOrfBW8Gc9k6zbBO+jZYiKS7rvHZA7p1tEvVfzMSPHNeemll+jVV1+lu+66S/l7SEkPASEg6eHGrYSA2OHnvLUQEDtIvQQE/8YL15Z48KxcJw60JSBerQ5udBHFhAlIKgfzqARRux0Mbm0qOCWz7c7VdQcjs6+Gjo83bHLixV+mjCKbuXSja7p+bz1dEGXzOu8Z4jbZMP9Ld11B7YLMb/zamz5bcQ8kEVU0s7jjE+RcP2PGDJXd/IgjjqA777xTJRqUkj4CQkDSxw4thYDY4ee8tRAQO0ghQLDqGVoPfCjhD6HfVNmM4JqApBvaN5k5GX4PLQ3U6lg7fzD1NeejAG4qGLBAngkHc5tz5rKtLoCrl36Zfa99vuXNldDAYTHxCuCpwsuaaNpYY6JjGHZOmaofJIiGmYeJNiDdKFxh5mFSN8jsyKSPsHWCNG1+pqOutW1B2h58Ex5//HGVzA+Rpjp37hx2mVLfBwEhIHbHQgiIHX7OWwsBSR9S/hCwDwQLDCAgrorrxIFMQEzCBbPQCHOpZEkEOVliMp8Al6FlXWEaVT8sOLEwpo+Tr0K3vsYgAdyUtMX9ttvv/Lgg2bmIjy6IRm1OGSd8gsyOonrHJOtXJ22MU1QO77q2x+vzh/mBdMDU6vzzz6cBAwaowANS3CAgBMQORyEgdvg5by0EJH1IWSuAlzA+vkxEXBIQ14kDWWMRREB0rY6fOZluaqU7mvuZ4KC998YyfdTj29JPANdv//0c8vPFBCddAVwnbbqAybscd3yCboJtT2uchO5UZNNPELVdu0n7bOCjXzDENYkiY+cSnyCyuXbtWrr77rtp1apVSvvRrFkzky2UOiEQEAISAiyfqkJA7PBz3loIiB2kuk27a7KAmbnukwmIX7hgjMcfmWRJBFEnVWQr1njo5iNeUpJvzrj8kWfHepNIR7pgEIQPMHdtQmF36ve3jsIExXubG0d8snkDnm0TJZfmVq7OoZcc8bvM712VrkN3kAAexVqi6NPk/OjvaH5XsW+jN7cT/v/tt9+mp59+mm688Ua64IILYvu+igLPTPYpBMQObSEgdvg5by0ExA5SnYC4TvKHmUXRp19uERao0k0iyEIJO9365bTw3sa5jDBlt4vpt0735t9vxFzCJ+qb/3TxidpvQiebqc56+icq/ZYub7uT4c8XDFGbW6WPQvKW6eLj1WxmS9sTBSZe4uaHEdfhZ2vdunVUrVo15fe3YMECGjhwINWrV4/uvfdeqlWrVtTTLNX9CwGx234hIHb4OW8tBMQOUp2AuM6xwQQEH31oLFwVb24R9M9EJ9NJBE2EgriGnsR+Y/5RCmMm+Hj9S1ydk2RCqAnZjHIOpkKTa78bl2Qzl/DJprYnapyCni+MzxoDPOf4KQ1Fv2Bg4sHaziFDhtDGjRupRo0aNH/+/EQ2cWQxLyoqKg3wZG2NQkDsoBcCYoef89ZCQOwgjZqAREFqOLcI5g6NBwSrsMSDP0ZAz8TkKAzKQUKBbkKBfjNpnpSNm38vdqb4uHTm9rv5189+mP2Nuq5rfOKw5y4xY4FaN0/i32Ec3e+G1x43bY9LPJI9X7iY0XHheumacEU5Z5d9B4UUnjx5sops1aVLFzrkkENo5cqVKpP56tWrFQFBskGQEynuERACYoepEBA7/Jy3FgJiB6kuhNnm2PCbSRR9goBg3vjQgDyAfOhCvO5g7v0AZ+sW2LVQGXbXvTeCcTPDSCVU2moCsrXnYfcoVX3Gh2/z+TzpQqXX4b20mN4wBvoz5ud3o/sFZJr4uzwLQedE1/Dpz3m230FRY6C/4/y0ups3b6aHHnqIvv/+e+Vk3qFDhxJTQsj4NWvWUIMGDRSJleIeASEgdpgKAbHDz3lrISB2kOoEhEPcFhYW2nWqtXZJQPhmC1oVfCA4XwkPF0fiESQsJLNZthW6daEsTiZHYQ5WkNAdFGEq327+/bDznh/dL4nrcw6XfBW6dVy8e86CpBcnxsLvOQtzRuNUl7W6+NPUrDIfSIkJ0f7444/pvvvuo8svv5x+//vflxpTtDidT8xFCIjdjggBscPPeWshIHaQ+hGQoBC3YUZ0QWrwgYGPB4gHPqz8geX47KmIh/5RzoVkeq40AbrJEfbLtZlZmDPguq7JTTfXwfmOm7bHNR5eAVzP66MT0XwUuvX18bMeZG6VD0J3KtLljfIU9rwFEf84mXDp73e/dxzMq5DBHKa6jz76KDVq1CgsHM7q47kcOnQorVixQl2eIav6RRddRLVr1yZoZ15++WVlBobvWp8+fahVq1bOxo5LR0JA7HZCCIgdfs5bCwGxh1S/JYR5UxQEJJ0++ePCSQRZ48HJDdmh0muOAkTy6fY7lUDgd4PLaw9zE2p/irLbA9+C+uVxiZPAFBVKQec934RurwBuG1DBROiOS/Zyfe1B/g4uz1uczpCu9fC7WAIur732Gr344ouKgJx99tkZ9bXzwx3fsdmzZydMvz755BOaMmUK3XzzzfTqq69SzZo16ayzzqKFCxfSCy+8QA8++GDemYIJAbF7IoWA2OHnvLUQEHtIvQQkWY6NdEbChyIsqfESD9wI6dFbQEDwgeHf6VqcIEEsnTXEsY0uMPHHmH+n33SXhgSKWK+fnwcTUa/glE+aAK/5SZjEcqm0bcAoyMQt289FJp71OAndrkmXi/3LBj78rGP+fucdQj6E+rZt26rEgnGNbLVo0SJFkB544AG67rrr6P7771fhgVEefvhhOvfcc6lNmzYutik2fQgBsdsKISB2+DlvLQTEHlLd4c4vx4bNCExATEgNCxRBSQThV8IRXliIYid0/ndpDznJwrc3V4lXqLTZ2zi01U0wTOzesyEwRYWTN6Gei6heYYktk7mo1ujXrw3pcjHPbJ6hoJt/F+uz7cNEm5ROQACdcPo963AiRzLB0aNH0yOPPELdunWzXUqk7WFyVblyZerRo4eKvPXss88mxgMxgZP8McccE+kcMt25EBA7xIWA2OHnvLUQEHtIdQLCIW5dxosPIjWmxIM//PqKIYTxjxcJV47c9ghH04NXEEvm6+AVmPIhgaLL2+9UmoA4nqEgQSyK02YqdPO7JKrQ0nGNaJYJbVLQzX8U++6yT9Mz5Bd+Wzc183vPTZw4MWFqBW0CkgzGuXz44Yc0ffp0lXkd/ilCQOK8W/GZmxCQ+OyFmokQEPsN0QkIbpHwgsePq5KK1LhIIoh56g6IuSZQhsXZxQ2wqTAQtUBpu/aoHMyDbnGzYZ7kknSFxd2vvukZcpHPJW5rN8HPlTYpG4TTZH0u6gSdIYzBOPr5emzYsIH+9Kc/Kb8JhNZFXo+4lzFjxhBykYB8cIJerwkWwgWfd955YoIV983M8PyEgGQY8KDhhIAEIRT8/5kgIJwokGeDG62gJIL88eEPkP5vNsEyMbvRP2IsvOvalDjecqcS+OBw6yVdwbscXCNIGMh2AkXMD2sPinIUvNL0a+gY+eWaiMJR2QXhTH/F4VqaniFTUmKq5Qs3y+zWDoMRa3dLUzQ3xsdPsw2n7W+//VZFs0I2c5gx/eEPf6C+fftm3cnc5FSNHTuWJk2aRDfddJMK9sIFTuhIfghneXFCN0GydNYRAhKzfRcCYr8hOgHhCFMc4ta+dyJdq4KPCnw8QCCynUQw1S133EhJtkxPwghLLnwQ/M5bttZuevZNMGJigj7DmCfFfe0mGAVpk3R/AMaGE43yRUM+hZFOdbmgC996vWxo3Ez2Noo6Xt8mPUjK+vXr6YsvvqAZM2aoDOa4kMC3CoQEP4cffnhstQaY+x133KHC7rKJGM717bffTps2bVJkCokQ8TuE4c0FbU7Y/RcfkLCIlawvBMQOP+ethYDYQ6oLjtBKoCDkrasCUsOCBefywEdDJz6mSQSjzuURJCxlWhCIo+lJpkzc4rh202fChJR4Sa7edy6vPV2M/JIosrYrKnJrOtdM1dP3ndeOsVnbpmuDkxG3TM3V9ThBZx7fjr/97W/0xhtvKLOrU089VREQ5NVYunQpLVmyRIWyPfnkk11PTfpzhIAQEDsghYDY4ee8tRAQe0ijJCD4qEADgj9hLhWGeAR9kOxXbt5DKtObKEhJnNZugpJLUpJrazfBB3VMSQmbHZUmsxvGBxoPJiLeyHZx00qa7rtJvTCmZt5z5BdUgskJxg6jcTOZaxR1gvKZTJs2jQYOHEhHHXWU0hhUqVIlimlInxEjIATEDmAhIHb4OW8tBMQeUp2AwDwKHwPbKCJsr4/++GOo9xmUvZwFkag1HjboRUFKwggiNnPPRNuw2iS+6cXeZ9PPIxPY8Bg6cfPzKfETujM5v0yNlczsJgxxM/UrydSaTMfhdyVf0ujmemH68CO4TEDieo70ywY/f76tW7eqDOZffvmlcjI/7LDDTCGRejFEQAiI3aYIAbHDz3lrISD2kOoEBCpt/HB0jrC968QDH1JoPNiOGwQkiHiwIJKrAmgqUuI1mdBvJr3EI0xCubB7lO36qTDC3FgAS0cQy/ba0hnf6+fBzyOfCcaL+45C45bOvF20CRJAk42RSuOmn6E4k5KoNX1xxsjkomXcuHF0zz33KH+IK6+80mlkxnTO7ogRI2jq1KmIvEmDBw9WPicoyLSO7xz7TZ5xxhnUuey7A8MAACAASURBVHPndIbI+zZCQOy2WAiIHX7OWwsBsYfUBQHhj6lfEkHWquAF7RWm+IYz14lHql0wMZlgYpbvzrZenPTbXz+fIL7BzbcEinzuw2j6wpBbxs3+7RBNDyYCaNiRdY2bTt64H37PpRsQIOx8UtUPMjlyOZbeVxww0p95vO/05x5zXb16tRLwEeXqscceo6ZNm0YFR6h+586dS7Vq1VJzuuqqqxIEZNCgQTRgwABq2LBhqP5KY2UhIHa7LgTEDj/nrYWA2EOqExAIRHBE10MEBgnXnMsD9UAycHuv3+6DgDAx0bUAuhBWmp1Nvfim0pTY73Y8ejC5/TUhbnEQJsMi6lL49jO7YSFTv/2PUz6XVOZWYbE0qW+KUSa0JS7MrUzWHLZOJjDSz72faS3+/80331QZwW+55Rb6f//v/8XSfwUaDxAOXQOi/zss9qWpvhAQu90WAmKHn/PWQkDsIdUJCIQDOI0XFhYGdhwmiaCJ2Y03h0LgBHK0QjLhO18Fbu8NrK7tCptI0FRQipPAra8/E8K3KUaZELi9e88aH9P8PVE94pnGKEj4jmqdNv26xChI4zNv3jxFOpo0aUJDhgxROTHiWvwICF/YHXzwwSqBoDjJ+++eEBC7Uy0ExA4/562FgNhD6kdA8EJNFj0l3SSCmKkugOm31/yB5tXkoxbA5Nbfu5smQkAuaAG8t/4ufVxMMMp2VKBs33ybYhQFKckV4Zs1R3rIWz9tUliMMkE67b8CZj3oJlwmoYF571HXj3RC2w6Nx7vvvksPPvggde/e3WwiWazlJSDI71FcXKy+baNGjaJly5bRtddem8UZxndoISB2eyMExA4/562FgLiBVE/2tH37dmWC5SUgeMFGnUQwSAuQi74AroVvE2EyTqQkG8n0TDDyRgZy8ySV7CUd0hnFPPz6jErg9mp8sp293gbPsAI3xuL3pr732db42GBg0jbVexvt8T5CnQ0bNijtBvD45ptv6LbbbqPf/va3B2QGNxkzW3W8BESfB/xW7r77bnrmmWeyNb1YjysExG57hIDY4ee8tRAQN5B6CQiiYPHvvMTD6zgYFNkqjKNtMkHJa8KVC5oS18Qj1U6bCtyZNE2KmwCWCYGb9yiTe+/mDbCvlyCB2zQCV7Y1Pi4xSeedpGPp52gd9fyy2b++97qDORIFPvXUU4qgVa1alRYtWkQ9e/akrl27UoMGDZwmv41y/ToBgQYH3zc2wRo7diwhZ8nNN98c5RRytm8hIHZbJwTEDj/nrYWAuIFU/1Bs27ZNheHFhwIaj3Syl0d98xtnTQnPjcMPZ+v2M1ukJOq9d3PiSwrcLs1uvCY3uomjy7lnsq+g5003ccP68RPnHD5RYKeTTm//fnk4kpm4RjG3TPRpYmr3wQcfKEfzY445hurWrZvIYI5vDqJd3XrrrUo7EseCDOw//PADbdq0iSpXrqy+kddffz298MILCeKOKFm9e/eOtQ9LNrEVAmKHvhAQO/yctxYC4gZSLwHBRwACNH5foUKFEqESTTUemc7lESQkZcJ8KxvmRmFOgCkpCWvnzje++RBOOV0tQNw0PmHORTp1vVpJxg19xTUCVzrrNGmTjHRH+byZzCtTdYL8XFasWKEymOMd/NBDDymNBxc2zYJ5VrNmzTI1ZRknCwgIAbEDXQiIHX7OWwsBcQMp2+hC28HZy0E8vLdRfo6HcRY+M0VKcunW33tibIUkbo+zg5KvuUxSCdyMaaZJt5un364Xr8mN7gPBmHlJSToE126W0bTWzz7WZBLVLV2CG80K7HoNeu/he/HKK6/QsGHDCPkyzjrrLLsBpXVOIyAExG77hIDY4ee8tRAQe0j5I8q5OliI5Myu+HcY4hF3kxOXpCToA2y/O9npgYWkINMkzA6aMpRsmZplB6F9/hLs38QCtlcL4A0tnU9mN6Zn35bgZmt/g8bViZeLs2+iUYpbcAkOMOBHvGbNmqVC63bs2FFlCy8qKgqCNNL/T5bJfNWqVYokbdmyRfly9OvXj+rXrx/pXEpr50JA7HZeCIgdfs5bCwGxhxQfPjjTcRJB/B0fOvw7FfHgD3A+CJ9hSQnq54O5UZjT4yUlbIrHwrefnXuY/nOpbipTOxOBO06CZFjcvbf+6YRUNiW4cdSU6M9+1H4uJmcpE9Hc9DOiE08/4oUoik8++SSNGzeOHn30UerSpUvYIxZJ/WSZzDFX+KR069aNpkyZQqNHj6Y77rgjkjmU9k6FgNidACEgdvg5by0ExB2k7AcCAsJx21m41EeJu5+DK0RSkRIeI2oBxNVaXPXjR7wgAAVpSuIoSKaDiemtv7dvU0Eyk1HK0l0/br2xHhe3/l7BFv/mM6abb+H3phG40lmXaZughHqm/djUMz1Lrp85E+I1fvx4Gjx4sMpifs0116hLrLgVPYrV5s2b6a677lKEiZ+9gQMHKmf42rVrx23qOT8fISB2WygExA4/562FgLiBlD9WTC5YyGACwqYjfOvtWvhws4poe2HhQydlqUxu8s3cxlTjw5j4CZK5Gg3IS7xMbP2DTmO2BMmgefn9f7rEK52xgsibn+Ytao1S0K2/i3Xa9BG1RinIyXzdunV0zz330PLly+nxxx+nFi1a2Cwn0rY6AVm8eLHyT0H2dS5wku/Vqxe1bt060nmUxs6FgNjtuhAQO/yctxYCYg8pfD9mzJhBbdq0oYKCghK5AFhIYjt/Ho0Fyag//Pars+8hSOMT1nzLfkaZ7SFo/SazyVVS4sLcyAQfrhM3UhJXU0NTnGw1Sia3/mH2N5N19WdOvwzQ3+FBPkpBxBP/P3LkSJXfAyFpL7zwwgMS2GZyzSZjCQExQSmaOkJA7HAVAmKHn/PWQkDsIV2/fr0KkQgSgptdOA0edthh6gZo3rx5BGdC3G6xOt3v449Z5BspCfr4pkI+H0gJ1hCVuQ2wS0VK8P/ZNrmJev2mT27Ut9vJ5uGCeJqu0UU9U1JiapoUdOvvYs7Z6CPo3aQHEcHFU7LIbgsXLlSmSsh9cd999+WMyZKYYGXj1O0bUwiIHfZCQOzwc95aCIhbSJFk6dtvv1UOhKtXr6Y6deoQMtgWFxcrUoIfaEp0216TD7/3ps3trN32ZkM88oGURLV+013SzxP7lnDbTJCSbK/fBKcoNUq5sH4TjJjkBl2YeM0C425uZbr2MPVSPXPAZ+vWreoiCtGh8E2A2dJbb72liMdJJ50UZqis19UJCCYD/4+jjz5a/UyePJnGjBkjTugR7ZIQEDtghYDY4ee8tRAQt5B+//339Oqrr1Ljxo2VHezBBx9MSBA1depU+u6779Sf+BBVrVo1QUhASlq1aqW0J1yCbtkykRQwLDLZMDeJE07ZWL/pHmWClHjX78LPw3R9LurZapRyff2mGKbSKOl9lDY/N7/nn0ncypUrafjw4Spz+c6dO1UAgsMPP1wlDsS3Aj8IYRvn4pfJHATqp59+UmF4QbKwhssuu6xEosQ4rynX5iYExG7HhIDY4ee8tRAQt5AuWLCAduzYQW3btk3Z8dq1axUZAWHBz3//+1+qXr16CVICR0Q9kWGchG19cX4f3mzmMsk0Tjwex/THnmVz/aYnOujWNgzJ9Zrb5ML6XeLEzwD6zNdEkqnwgqkR+7npiRS5DX4X5jyZ7k1c6unmhn77jxwZcM6GhgDmuBDU4cAN7Th+4EcI53Nv4tq4rE/mEQ8EhIDY7YMQEDv8nLcWAuIc0rQ7REIn1pSAlCDuOkIZsukW/sSNGTuG8u2aV5DM5Ec/V+zcoyIlubJ+00MZFidd8CpNN96ME/ZfjyoFnL3CNv/OdA9yqV6QuVnQedKxykWc9MuXZCHFYZJ077330qWXXkr9+/f3JRkgIHEMuZtLZ7E0zFUIiN0uCwGxw895ayEgziF12uGKFStKkJL58+crO2KdlDRt2rRE5JRUH31XPgD5IHgHCUepbmyDBC+nhyDLnaXCiaemJ9PLp/DJyaD3M7fyuxBgc6V8DDDB5DOZk3Uq7LxnyosTE5M4kxJ+B2KOfskkYZoEfwkkFnzssceUmZUUQcAGASEgNugRCQGxw895ayEgziGNtEN8qJctW5Yw3YKmZNGiRerjxqSkU6dO1KhRo6SkxMYxOd8F7yBSAsGI65S2JIosYOuCF2vjGBMWGHP9ZjvVQxwmupOfoJ2LwraORxRaL1OcTCNwRfkS1t+Bflo/nA/4Szz//PMqOmLPnj1jGVoX5AhaF9a8nHHGGdS5c+cooZO+LREQAmIHoBAQO/yctxYC4hzSjHeIDyLsiOHkzj4lcHaEAzxICQgJHB7r1auXNinBomDjjY9raRO8+bbbS9xY2M5n23b9MAdpvUyEyFzOexMkeJo++CY4eSNLmfYdZT0TcyOX48cRJz2Tu1+QhTlz5tDNN9+sgorA1wN+fXEtgwYNogEDBlDDhg3jOkWZlwcBISB2R0IIiB1+zlsLAXEOaSw6xMcbDvEgJBx9C5FYmjdvniAlICd169YtMV/9o+8ncEOAzKWQwC42w0/wZm2A7gvAY+Wbw62N4G0qRNomvHOxz8n6yITgbYpTtjQAuuDtZ24UJf5636w94neTn+YtCvIWpPVBZKs///nP9OGHH9LDDz+sQtLGvXjD6cZ9vjI/yQNiewaEgNgi6Li9EBDHgMa4O3y0kRiRSQn+XLNmjbqt0823kBgL2o4pU6aoiD7t27dPOL5n6oMfBxiDhA7vHIPMt3JNUxKV4G0qbMeBlGRT8M6WsO0V+FnzGdcgA4yTfhnAv8NabC4ETJ6Br776SuW9OPPMM1U284oVK8bh9RU4BxAQDv0Lbfl5551HVapUCWwnFbKHgGhA7LAXAmKHn/PWQkCcQ5pTHUK4QAhgkBEOC4yILCAkEAB/85vfULdu3VQiRS76B1+/ieSPvfcGMteckvUbf1tzs1wkJTxnPaywHnktigMeN1ISlnxGgYlfn5l69kwE70ytOd1xgp69ID+lIF+fjRs3quhWMLt64oknqHXr1ulONSvt1q9fr97rWOeoUaOUb+G1116blbnIoGYICAExwylZLSEgdvg5by0ExDmkOdvh8uXL6Z///Kf6oB5xxBEqsgv7lCDJFDK465qSatWq5RUp0YUuCCdRJdILEoyyqSkJ8vPI5OE2JSUuzZJyUfBORUqwX2Ej3wUJ3pk8A67HMj1TfLHidwGBPt5//31lanXVVVdR3759S4RGdz3nTPQHMnX33XfTM888k4nhZIw0ERACkiZwvzYTAmKHn/PWQkCcQ5qzHeIWD9GzevTocYAqfteuXSqDOxMSaEtg94yEi0xKDj30UJXhnUscTEhMNiMbN/7eeWWblLjU+phgnm4dUwEyHVKSTXOrdPFI1U7HyuvP5WeWpJ+BuJpbZQMnhD5fvXq1ijQI3GBuBdOlBx98UAX2yMWC9zm032yCNXbsWJo2bZpyoJcSXwSEgNjtjRAQO/yctxYC4hzSUtMhCMiMGTMS0bfwAcNHrUOHDglSgr8XFhaGJiWZsv+P041/NkhJprQ+UT4UtkQ3ruZWUWCWiujyeKUtpwvW7SVfejZ3+MJ99tlnykRpx44dKrIV/OKaNGmifnBpU6FChSi2K7I+4fv3wgsvqHWjwO+vd+/eVKNGjcjGlI7tERACYoehEBA7/Jy3FgLiHNJS3SGSbk2fPj2hKfnhhx8UHtCOsKYEH2/dUdNUgHRJSnLlxj8qUhIHrU+UD4rJmWLBE3VtfX2iXEuUfbPWB2MAA92cC7/LtwSKfs8TX0IkM7vE+2zgwIHKLPWPf/wjrVu3jhYvXqx+EP68ZcuWdOWVV0a5TdK3IKAQEAJidxCEgNjh57y1EBDnkEqHHgTgPwIiwnlKoDWBf0XHjh0TpASmXAUFBYmWpqY2YUlJrhKPVIcqrPlWabrx13HTSYmfSVKuB08I8+IJeg6iev7CzDHquvpzgPeRN9DCtm3b6PHHH6fPP/9cZTIHAUl2IRB1kIaosZD+cwMBISB2+yQExA4/562FgDiHVDo0QGDz5s3K5phJycyZM5VWBEkTWVMCp3fO0osuTYSiZInuvKZG2cxlYACPdZUgUxv2AdDxsh40Bzrwki8mHXw+GDcsxY+Q5FpEN78tSdfXxeT5iyIHh+tjpb8Lkmm+Pv30U+WUff7556tkffp7yPV84tQfckfBLyRXfVvihGUUcxECYoeqEBA7/Jy3FgLiHFLpME0ENmzYoEIBc+LEH3/8UTnD65G3DjnkEKU94WIiFKEuhC4UjmyVD4KkKcy6wIU2fFvLmLCwnc3oW6ZrSbde0I2/3q9uhpRPYaaj0HyZPH9xIiVB5Au+ESAe+BPaD+THiGNZtWoVvfLKK7RlyxZFGPr160f169e3niqyo9euXZuuuOKKhIO6dafSgTMEhIDYQSkExA4/562FgJhDilux8ePHKwEOH7LjjjuOTjrpJNUBPsTDhw9XTtn44OL3J554onnnUtMXgbVr1ybykyAC1+zZs1XseiYl+LNFixYqZLCXlGCPdCGbBe2g+P/5tBXekKosDCYjcPlGSlxpvlKREiZ1cRK0vYSKz0EmfF1M/G8yjZVOQP0ifOH/33rrLRWG9sYbb6QLLrhAvcfjWp588kk65phjVI4mOMmPHj1aRedKt+B84GwsXbpURfdCaGH0HWcM0l1rLrcTAmK3e/F9ou3WlbOthYCYbx0ioLDzNP4+ZMgQpZ5HeMYvv/ySvv76a7rhhhsIPg8PPPCASurk4lbKfIaloyZu/1hTAlKC7O6I4gIyAhMuaEngc7Jw4UK67bbbEuTE77bWj5Tkw0fX5rY7rE9JXE9dJiKc6Vh5/UrC5t+IAsegG/8oxvTrM1taJS8B9cvtgzC7cDJv0KCBSixYs2bNTMGS1jgwX73rrrsIJIS1mZj/rbfeqrQX6RYmISBiIDUgYnXr1k23O2kXAQJCQOxAFQJih5/z1kJA0oMUiZtwU3TNNdcoAvLss8+qG6MjjzxSdfjOO+8ou+FzzjknvQGkVSgEVqxYoT6acBhFlBrYMP/000/qA8rakqZNm5a40csXQVsHKoypURiAcwmrqDAwxSsVKfHLv2Hab5h6QTf+YfqKqq5OSnQfHB7PlsAFkfDdu3fTc889p97V999/P/3mN7+JaqlO+0X0rWHDhqkLMC4PPfQQ9erVK3Q2diYd3gni4gZBQuADk2shhp2CHbPOhIDYbYgQEDv8nLcWAhIOUgi5yIKLxFTnnnsunXLKKaoD3JxBbd2sWTP1b8SNh0MfbHOlRI/A3Llz6aWXXlI5R/DRhBYEcfv1xInQiIAs6o7uiOGvazxySdD2Eg89nGgmnOzjhpXJbXf0J9F/hExhZeJgnS0MTMe1JXAmGEyePFlpDGAqi+R7eq4i03lmq54rAqKTj0WLFinTVpANaPmhQf7rX/9KV199tQqhLiUeCAgBsdsHISB2+DlvLQRkP6SPPPKIIhZewQ4CKpzz8ILmglt23J71799f3bJ7CQj8RSDwCgFxfmR9O4RvyPr166lr164HhNPkBhBMELefI2+BnMDmGY6mbL51+OGHK+1JLpGSTJgame5ipgRt73yCfF1M55/Jeq6x8mKQT6Fhg7BizRJrfrCPfqF1Yb4EzTVMOJ944gmVUDDXiksTLFzSvPzyy+qdiSSyzZs3p549e6rgH88//7xyxoeWX//25Rpe+TRfISB2uykExA4/562FgKQP6RtvvKHIB7QgYoKVPo7ZbAmBBZoq1pTgz5UrVypNlu7o7rWFjoPtfy6Y2WBvg4RHm+hbuYKB6RkPwsovgEK2Tc5M1+a6XpCmBCZWc+bMUb4d8OuAozZMrX73u9+pHz1wheu5Rd0f/D+OPvpo9QNtzpgxY0I7oSPAB7Kh4z3Xo0cP9R7EN61q1ap0/fXX065du5SW6OSTT6YzzjijRPTBqNcn/fsjIATE7mQIAbHDz3lrISDmkMLPgJ3KcQuF5FR9+vQhJNFjJ/TrrruOkA0cTui4OcLHT0puIYCbZDi2g4ywtgQ3ga1atSoREhiO73rJFCkxMTGJO+JBgnYQKYmzuZVr7L1Y8b+945TGENPAwOtoz6QXAvbQoUNp+fLlimzgvXzssccqrUeTJk2oTp06SbWlrvfQdX/wb0MYXgQ8QRjeyy67LOm3hiPbeTViX3zxhXq/4TuFMnLkSMLvoAE5/vjjFTYwJX7zzTdp8ODBBHNVKdlFQAiIHf5CQOzwc95aCIg5pLgdwo0a56HASxo//BEcMWIETZ8+Xb24JQyvOa65UBPmCf/9739LhASGyVfr1q1LkBKvqYJLUsJ97dmzR5mIZcLPI5N7Y0pKdIdlPzObTM45W2Ox0I3xcRaACRcOcZssKWe25ux63CDtFzB69dVXlaAOIbthw4YE/wn8wPQSzw9yfsQ96lU6uMEkFc8GQpQDJ5wJr8M5yAXCxsP5HiSjWrVq9Pvf/55q1KhB8Klr2bKlGvqbb76hLl26pDMNaeMYASEgdoAKAbHDz3lrISDOIZUOSwkCIAL40Os+JbiRRAZ3PXkiPux6YUE7TJK7OPl5ZHJ7g8xsgjQlmZxrJsZKZW6VSlOi593gm/BcDTdtogFEEtNbbrmF2rVrp0LWFhUVldgeXCjAjw/kI598ZbBIXIw89dRT6j30P//zP8qxHGRj1qxZytke+avg9/btt9/Su+++q7Qol156KR1xxBEKI/wedU8//XSrsL6ZeB5K2xhCQOx2XAiIHX7OWwsBcQ6pdFiKEYDdOT7eTErg7IqcMRCEmJQgqgzsrLnw7bV+s6/faHO9fNR6mBwVr8DJAqNO5HSM8pWUpJPTI99ISZCjPZ41CN/wiXj00UfpqKOOMjlieVOHtR2ffPIJTZo0SZEN5E3C++i0005Tuap27typwsVDS49AKtCUQAsCP7d//etfBPIG02ImJHkDTh4sRAiI3SYKAbHDz3lrISDOIY1dh+PGjVP5MVhwO/XUU0t8mD/44APlwwIBt3Pnziq8sBR3COCDD1MHJiUIcQntSYcOHRLRt/D3ypUrJwYFkYHgwInFdDMbbxZpb3ZzdzPPfk+mQrep+VYuYoW14bzgT78s3mF3KRdJiYmjPfwX7rzzTuXDAF+8uOevQDh3aCaqV6+uthD+gnCOtylMQNAHHMzxzsfvLrnkEvV+gebn448/pmnTpim/Efz/hAkTlHkpwu9iLhdffDEVFBTYTEPaRoSAEBA7YIWA2OHnvLUQEOeQxq5DmAkhCR8+MFDPIxLMHXfcobKH48MD+198uCGc4dYQyRMhEEuJDgE4xMJfiKNvgZSgQDsC0wk4mUJLghwF+o0/6vhpSvKNlLgQunOdlJiYGrk6oaakRD9nrsYO6ieIhOKd9qc//YmQywKhdREsIhcKCAjeAxdccIH1dP0SCiKQBnxgMMY999yjQuuiwCn/H//4B51wwgkJ3w4Qk23btpXQzFpPSjpwjoAQEDtIhYDY4ee8tRAQ55DGvkNk0IWKHcn6QD7gdAj1PApu5ObPn0+XX3557NeRbxNEGMzXX3+dEG0NDrNjx45VS0RGYk6eCFMu/XaSTbV0fxL+XS6SkqiF7lwhJWxqhP3PVrCBbJOSICdz/D9Mhh5//HHlZI6b+1zya3FBQLzEA3msWGuKs/PRRx8pnw74c8CRnOvDL+bEE09UZlhScgcBISB2eyUExA4/562FgDiHNNYdwj8Bt2JInAgTBWS7RfI+jnKCW3nEy8fNu5TMIQDzrGHDhqkwoWeffXbithLhnmEuweZbM2fOVJosPZs7NCbly5dPTNaUlMTNGTnopjuq3YgTKQkSuqPCwLRf07NloynRSSj64fDC+hwRyQo5KuBcjpDnCKmbawUEBGZj0EzAPOrMM89UUfXSKcgFgv6AFSLx4T0CnzNoP1588UX1fkC+Klw6cb4PEDbkO5KSOwgIAbHbKyEgdvg5by0ExDmkGe/QNIM7st7+5S9/UdnbEZ4RxUtAYAoEB04hIJndxg0bNijnUG/CQ79ZoC6c20FK8CecRiHE6KQEggaHi0YfpoJjNkiJC3Mr17uVaVJiInS7XqOr/kzPlgkp0c+CX14T+MJAoIYJETS5v/3tb10tw3k/Qe9laLbw3OKZg7kUMo/DFBYaadMCX7G3336b8N7u1auXen/AAR3+YxdeeCE1btxYvSPeeust9X45/PDD1YUGNB+s9TYdS+plHwEhIHZ7IATEDj/nrYWAOIc0lh3C7hfZ2hFuETfmXMQEK5bbFXpSSLoGQYN9SuD3g5tQPZs7SKee/dnUxCYqUmLiWBwaiAgbREVKgiI7RbikyLpmUmLqr4SJMA44bzinXnMqnO+BAweq7N+33XZbQksY2SIy3PEzzzyj8kqBJHBhkynduVyfFkIJwwwN4XahDUI9RAGDPwz8yf7whz+o6njPI7cHTLFgxqkHvMjwMmU4CwSEgFiAh5xJds2ltWsEhIC4RjR+/cGnAJoPRELBx0cv7IQOp3R88JHdHSZA+HhJyW0EcAuqkxIIIMh7oJOS5s2bl8iDYEJKbBPc8Rj5kFDRhpTkGgGzfRpSkRLuG2eLIzcxWUaeCmgTvvrqK+XvgfObDwXO85y4FEEnsDYQLK85GRzEV65cqfzC8Hf9EgE44P/q1atH48ePV3k9ED4XmhBEP8S7HIQNRAXjseY7H/ArjWsQAmK360JA7PBz3loIiHNIY9fh008/rbL/6qp9qOuZjCAM78SJExUBQXx4CcMbuy10NiGQUTbfgrYEAQfq169fgpQgYpp+++ySlMTR3MoZuL92FERKGFvcbifzcXA9pzj2p58FPdLbpk2blI8a3lcgzAjGgHwWV199dV5pPZChHe9lJl1nnHFGCe0H9gwmVu+9954Kk44IhaibLOLVyJEjFeHAex3Zy4cPH67C6t5www0S3SqOD0AacxICkgZoWhMhIHb4OW8tBMQ5pNKhzfNn3gAAHSNJREFUIJAzCEAIhG+QrilZuHAhNWrUqAQpwb9tSAkAwe0tC09+JjY5A1oaE2VSgvXjRy/ANV+TJyaDSg844OdkDmIMsyH4LUCIRnSnjRs3Ku1AkyZN1CUJwojnU0lmbgXNJXw44NcFUys/cyxoP/7zn/8o4gasRo0aRS1btlSa7HzDKZ/2POxahICERaxkfSEgdvg5by0ExDmk0qFjBOBgiQgvEJQRu16Pm4+PMW76kOgPghycKxFeUkr6CADTJUuWJCJvQVOydOlSOvjggxOJE2EGA82JKSnh2SSz709/trnR0s/cCjPXtSU6MclXUhKkAcP/w8EcwTFgjgRNLZ8xEBBoDPAeQNQ+aEfysYB0IdQ2ExJoQaChhqb6qquuUpGrvGQFFwgjRoxQJl3w/4Cvx1lnnZWP8JTqNQkBsdt+ISB2+DlvLQTEOaTSoWME4MuAjzBCTe7YsaMEAYFpwtdff63MDGArjpCc1157rRKOpbhDAIIhNCMgIxwSGOZc8CHRfUr0KF4gLfDzQIZnFiLZDwAzy1ch24t6mPDCQeZbuaop0aN8JSOhuOm/5ZZbFNFFYsEw0aDcnfTs9IQzsmvXLnrttdeU5sKbnwNBJt555x2lBQIxQ9H9QfAsQpOEMOpIIqvnAsnOimTUKBAQAmKHqhAQO/yctxYC4hxS6TAiBPwSdyGyV7du3ZTvCgo+0oh5j2zuUqJFAEITwofqpGTNmjUqE3X79u3VTfV5552nNFKpNCX5evMfdNtvuju5TkqConxB8EaQDDzfDz74oPL3iFtxrYVlMyrdnAqaj0GDBqmkiiBh3oIcQDBLAz4cQhcXMy+99JIiJrh4qVSpUtygk/k4REAIiB2YQkDs8HPeWgiIc0ilw4gQ8CMgsHnu27dvIqEWMrkj0Va/fv0imoV0mwwBCJpIrAYSWFhYqByGYZuO6DtIsMaaEuQr4eg/3FeuC9k6Jia3/banKBfwMonyNWnSJBVSFwL1jTfeGFsBOhNaWESqwoXKFVdcUSIfEJMUaH8R2WrChAmETOYgJNCYIGjElVdeqZ45KfmNgBAQu/0VAmKHn/PWQkCcQyodhkQgKGEXC6smBOTTTz9VpkJCQEJugoPqr7/+uhKKzj//fEU2WOsBMyzkJWHTLdirb9myReWj4eSJ+BN5DLyCvO68rZtveU2RvDkjHCwnrS74th+N4WjP0Z3S6ixkoziRkiCzM0S6uu+++2jWrFn0xBNPUNu2bUOuNjvVXWlhobmAT0e1atWoa9euiqwja/ndd99N119/vQoC4VcQchc+b0g+Cm0HQqt37tw5O2DIqBlHQAiIHeRCQOzwc95aCIhzSKXDiBBw9fGPaHqlvltoOpDgrEKFCoFYQACD8KmTEtzwIoQoa0oQwadq1ao5QUr0234mHnEgRZkmJUE44P8heMPU6o9//KO6KMgkSQs8mAEVTC5BTLSw0KhAmwEyDodznHU8N8jLNGDAgKSaIBA7PDOIdAVHcymlCwEhIHb7LQTEDj/nrYWAOIdUOowIAb+PPzuhX3fddeoGEU7osKGG47OU3EIANvCIZgYBC4LZtGnTlBM7/EmYlMDB1pvF2RtJKpOaEt3cKldyekRBSkxwWL58uTK3go8WCEicntFsaWG3bdum/KgQYANO+CDhyHeiR7rip5hNsfzygOTWky6zTRcBISDpIrevnRAQO/yctxYC4hxS6dAxAjA3QNIufJzxEYbpwUUXXUQdO3ZU4SgRfhLRX3CTKmF4HYOf5e5AKrG3cHTHD5yBUXBjzKQEWhOv863XdItJCUiC3086ywxyrk6nz2y1sSElurM9IjF5NRqI1vTyyy+rn8GDB1OPHj2ytUzrcV1rYXUndGg//v3vfytihnwfwFL/f+vJSwc5j4AQELstFAJih5/z1kJAnEMqHQoCgkCECCDcMogIkxJoTSD0gpDqpASmLVyYgPBNPQvc6lYsJCkxca6OcPkZ6zqIlOgZ3ZOF1oVPEELrYl/uvPNO5fOQyyVqLSySCUL7d8wxx9DRRx+dy1DJ3CNAQAiIHahCQOzwc95aCIhzSKVDQUAQyDACmzdvViZb7FMCwbdixYoJJ3cIwHB6h/lPuqQE7VjrkSvmVq63QdcseTO6I4oTSGHDhg2pXr169L//+7/0ySef0KOPPqoSB+ZyiVoLy5oOBGdA1nOEs4Z/DDK/SxEEGAEhIHZnQQiIHX7OWwsBcQ6pdCgIHIAAnE5hRgYBA+ZCEC4kWWK0B2XDhg0lSAmESPiP6IkTDznkEGXqYkJKuA7IBxzNWXMS7Sri1bufkzlmiN//9NNPyoQImbiROA+4wjwOOS0QKhY/3qAC8VpddmfDJAQaEDiZw5w0lxz0s4te6RhdCIjdPgsBscPPeWshIM4hlQ4FgQMQePLJJ5VZBZImTpkyhUaPHk133HGHIJVhBPiWns23YHdfvXr1EqSkRYsWimCgsGM8HOE59K+N+VaGl+tsOBMnc5COe+65h5CVG8EggCHIyOLFi9WfwB6/B95SBAFBIDwCQkDCY6a3EAJih5/z1kJAnEMqHQoCJRCAeRASh4GE8I3mwIED6dZbb6XatWsLWllGALfNuHVm8605c+ZQrVq1lKM79gs5Gm6++eYS4YXZpwRmSLqvBJai+5TwfschJG+6MOtO5n4hhvH/b7/9Nj311FMqmWDv3r0TOWD0MeGMzsQu3blIO0GgNCMgBMRu94WA2OHnvLUQEOeQSocxRiAbUWVwAzxs2DAaMmRIApmHHnqIevXqpTKES4kXAshn8uqrr6qwqI0bN1bEZP78+cqvQc/mDtMinVjkGynRtR7JnMyR9BNkGr4KSCwI4iZFEBAEokFACIgdrkJA7PBz3loIiHNIpcMcRCBKYiIEJHcOBHx17r//fkU0EAqVozbhfCCPBZtu4U8I38hYrfuU4N9eUuKNJuUXEjhumpKgEMNIJPn8888rzQfwOvHEE2O7yYiYhuhVy5YtoxNOOIEuuOCCxFzxeyQOZLMwhMD93e9+F9u1yMRKNwJCQOz2XwiIHX7OWwsBcQ6pdBhTBHbt2qWEjcMPPzyjN7VighXTA+EzLSQ+BAkxSZIHIrFkyZIS2dzxb2hGQEo6deqk/kSwgbCkhP1NMMVMmm+ZhBiGDxPMByHMI8SuNzFk3HYb+wnChGR/yCXkJSDINaP/Lm7zl/kIAoyAEBC7syAExA4/562FgDiHVDqMKQIQPhAaFDb9v//97xNJvuAcCyEF5lDJhD3b7MPw/0Bcf/xAEBozZow4ocf0nNhMCwI8NCPQkLBPCZyymzdvXkJTUrdu3RLD+GlJvJqSqEkJzjgIWLIQwyDSDz/8sDq/TzzxhPKRyaXil8PD73e5tCaZa+lCQAiI3X4LAbHDz3lrISDOIZUOY4wAckWMHDmSrrrqKnUzPW/ePGVGAqELDrQVKlSIZPYIUYowvEiihzC8l112mdEteySTkU4zigAEe5wz3XwLju+tWrUqkafE6z+RKVLiF1rXS8QRte3ee+9V57Z///456UyejIB88cUX6lICmpwzzzxT/LIy+nTIYGEQEAISBq0D6woBscPPeWshIM4hlQ5jigD7eeAWF4nRkDBt+PDhhFwQsPcH+fD6guDW97333lNkBXH5pQgCLhBARChE29JJCZzfoYXTHd2Li4vT1pQEmW6ZOJmvXLmSBg0apEyXHnvsMeXzErfyyCOPqLwZeuHnGHNnDP0IyKZNmxT5gHYJJBF+LcjYXqNGjbgtU+YjCOBcigxtcQ4EPAvwomgqBCQKVKXPOCLAQsmECRNUwjQkBTzrrLMUsfAjH1gDBLAXXniBjjvuODrllFNUJmxvcrAoHdjjiKPMKRoEYP40e/bsEqQEZxQZ3NmfBH8WFRWlJCV6hnKQEDbd0hMn6qF1kTDQe6bRx9///ndlsnj77bdTz549M+qLEgXCJuZWzzzzDB1//PHKT0yKIBA3BISA2O2IEBA7/Jy3FgLiHFLpMMYIQLAaO3Ys/etf/6KjjjqKLr/88pSzhUAI0ymYbDVp0uQADYnemAU/CHNMVOCwi+g73bt3z6kEbCNGjFC5MeAfM3jw4MTNt2R0z+zhhvP0rFmzSji6QxuBDOOsKYEvhjfDuNd8SyclvALO6O4lH0jOiLwn0AwisWC+JA70IyDQOrGGBGaSjz/+eCKscGZ3WkYTBIIREAISjFGqGkJA7PBz3loIiHNIpcOYIgDB7YMPPqBvvvmGOnbsSBC07r777kTiOL9pf/nllzRq1Ch68MEHfe3eEWIXN8jeqElMQN566y0VKemiiy5SZly5oi1BDgz4JMDsBuSLTW8ko3v2Dzeys8+cOTNBSuDXBO0JsrUzKenQocMB0amgzQOZ0DO6YzUg2DiX2GOQzv/7v/9T5x0BE/Kh/Pjjj2qNeP6xTvhg4XnEOwC/xzMMTPBzxhlniPYjHzY9T9cgBMRuY4WA2OHnvLUQEOeQSocxRADO33A2X7p0KV188cVKuH766adV/gKYV/kRA9w+w1QLAswdd9xxgPkV7PiRsA4CDG5S4VNy9tlnU9u2bRMIwKYcJjMQeLiEISFh6kYBO+zhBwwYoIRTCSccBcJu+kQo2enTpyfMt/B3nB1oR0BGUKBJgTarZs2aCXMqjtr11VdfKR8IDllbu3Ztatq0qfqB2Zc3apebWUsvgoAgEAYBISBh0DqwrhAQO/yctxYC4hxS6TBmCEA4g2lFYWGhiveP7NYob775Jq1du5auueYa3xnDQfWNN95QN8mXXnrpAQQEeUVAPCCcMVmBVgX9oQ1uXP/yl7+om2mEYUVSu2T5JXQTGTaJYS0KHJVbtmypnGUzXXQCIgkVM42+3XjwH3n33Xdp4sSJ6uwvWLBAOWvj5p81JTiPCMoA8oHQunCCR7tFixYlfkBCEB1KiiAgCGQXASEgdvgLAbHDz3lrISDOIZUOY4YABHkQAwhbnNkaUwT5eOihh6hPnz7UuXPnA7QgyN8wdOhQ5ZSKpGswc4G5FWslQDpg1lJQUEB16tQh2JC/9NJLdNppp9ERRxyhtC3PPvusunGGnTnMZjCHvn37hrpRvvLKK1V25q5du2YcWSEgGYfcyYA4888995wiERdeeKE6j/D5gBYLJlvIUQJzq6+//ppuuukmRbC9viBOJiKdCAKCgDMEhIDYQSkExA4/562FgDiHVDrMIQSQEBAmUgjL6xXAYLLy2muv0W233XaAI+6GDRuUPwlICm6VYY6FW2aQk3POOUf1B/+Rf/7zn3TMMcfQeeedp1B58cUXVZ0rrrhC/Xvbtm3KNAa31CBHiL4DB+OyZcsqgREmMci/gEhE2QiBKiZYOXSYtanijOH8QdOBc5lrZdy4cfT5558nnslTTz1VBY3ggmcP68MzgsuDc889N9eWKPMVBEIjIAQkNGQlGggBscPPeWshIM4hlQ7zBAHcDr/88stUr149atGihTJPwZ/QaOD/QE4goMP3A9oQRNaC7T3IBX4HB3RoRXADDZt6FAhWuH1GJnY4w8IJduPGjXTssccqsoGoWyeffLIiMChIkoboPRhH195kCmKdgGBMyeieKeRL9zh4DmD6VbFiRWXmeP/99ys/LPhuQZsJ80mcTRCQRx99VJF+9nUp3cjJ6vMZASEgdrsrBMQOP+ethYA4h1Q6zCMEQA7ghA6BCJGhEJYW5lgIq4v8IKeffrry8YBpC8hK+fLl6YYbblB5RWACA5Otfv36JTKsjx8/Xmk74Ng9adIkZQ4Dp3h28sX/I3QvnNZh1oU+0TciUaHvTBX4vvzwww8EPxj4s0AQvO+++xShkozumdoFGYcRGDJkiDKVRGhgkA8kCoSpI8pnn31G8+fPDwypLWgKArmOgBAQux0UAmKHn/PWQkCcQyod5jkCcC6HQP7pp58q4QfO6HASh88H8jGAgMDxHdoCRN+66667lLYDZjFI7gZCcfXVVytzLGhMQFZANpo1a6YEq9GjR6s+4C+CtkceeaS64Q3KbJ3nsMvySikCMFFEtDmYIuJZ+etf/6r8oVhLiGcIzwxyl0gRBPIZASEgdrsrBMQOP+ethYA4h1Q6LIUIwJdjzZo1SkMCu3tEFYLQBJORgw8+WJluLVy4UCVBhDYDN7nQMkCgQoQhaBvmzJlDy5cvJ/iXIDIRCjQl/fv3l9wEpfBM5fOSH3nkEeU7pRcO7jBo0KBEckAk8UQkOTwDeIZQvAQEzw58uYSA5POJkbUBASEgdudACIgdfs5bCwFxDql0WMoR4PC50HTAhAn+IvD7QPhf5ByBkzkKTLHgTAstBzQq3gIHd9z6IncDfEqkhEMAfjmIYgYcQfSgnYJpG/xx2GQOQjBM22De06pVq3ADSO1IEQAZRxQ5ROhq06ZNYiwxwYoUduk8xggIAbHbHCEgdvg5by0ExDmk0qEgYIwATEcQzQeO7U2aNFF/gqjAAXfChAn08ccfqyhcEJ6lhEMABAS+O+yc/Mknnyj/GtyUQzsFrM866yylmYI/D7J/SyjacBhHVRukEZqPSy65JEHYeSx2QodTOswSH3vsMZUAFEkXpQgC+YyAEBC73RUCYoef89ZCQJxDKh0KAqEQwE0vBOUlS5YoHxCEG8Ut/TPPPKP8S+APkkkH9FCTz6HKyIkBv5sHHniArrvuOhVZiSOLweQNoVz1m/YcWlreTfXpp58mJL7E88ClV69eCTICzSE0iCAg8JGSMLx5dwRkQT4ICAGxOxZCQOzwc95aCIhzSKVDQcAJApMnT1b5QDp16iQO6A4QRUQxRPTq0aOH0irBvIcLiAk0JcjZIkUQEAQEgTgiIATEbleEgNjh57y1EBDnkEqHgoAgEDMEPvzwQxVx7MYbb1RaJSEgMdsgmY4gIAgEIiAEJBCilBWEgNjh57y1EBDnkEqHgoAgECMEECEJ2iSQD3b295pgPfTQQypbvZhgxWjjZCqCgCBQAgEhIHYHQgiIHX7OWwsBcQ6pdCgICAIxQQBhj5Hw8aabblK5WLjACR3+BXBeFif0mGyWTEMQEARSIiAExO6ACAGxw895ayEgziGVDgUBQSAGCKxfv54QKQkO/QUFBWpGyEx/++23q/DI8AlB7hb8jrNsx2DaOT2FcePG0eeff56IJnbqqaeqoAooiPY2YsQIlRsHpbCwUBFDKYKAIGCGgBAQM5yS1RICYoef89ZCQJxDKh0KAoKAIFAqEUA0N4SQhqkbCCAijYEEgnSAgHz//fcqEacUQUAQCI+AEJDwmOkthIDY4ee8tRAQ55BKh4KAICAICAJENGTIkIR2SQiIHAlBwA4BISB2+AkBscPPeWshIM4hlQ4FAUFAECj1CMyaNUslfLz33ntVJnoQkHfeeYeqV6+u/n3yySdT586dSz1OAoAgYIqAEBBTpPzrCQGxw895ayEgziGVDgUBQUAQcIoAklLCbwWJ92De1Lt3b2rcuDGtWrWKXnnlFdqyZYtysu/Xrx/Vr1/f6dh6Z4888gitXr26RP+//PKLmtegQYOouLhY/d+yZctUJvP+/ftTixYt1O+2bt2qiAeSaq5cuZKQbPCKK66gZs2aRTZf6VgQyCcEhIDY7aYQEDv8nLcWAuIcUulQEBAEBAGnCGzfvj0RxQt+FO+//z7ddddd9OSTT6rkid26daMpU6bQ6NGjlc9FNsvy5ctVksdLL700ZVjjN954g+rWrUunnHJKNqcrYwsCOYOAEBC7rRICYoef89ZCQJxDKh0KAoKAIBAZAhMnTiREm7r++utp8ODB9NRTTyWiTg0cOJBuvfVWFfkrG2XFihVK83HJJZdQu3btSkxhw4YNyvwKBdqcxx57TNVr3bp1NqYqYwoCOYeAEBC7LRMCYoef89ZCQJxDKh0KAoKAIOAcAYQNRpQpmDtde+21tGfPHho2bJhy9OaChIq9evXKmlAPs6rFixerHCtcMB+QkVGjRtHUqVOpbNmyBLOtE044gY4//njnOEmHgkC+IiAExG5nhYDY4ee8tRAQ55BKh4KAICAIRIbAV199Rd988w317NmThg4dqpy840JAIlu0dCwICAIg9iJDW5wDAc8CvCiaCgGJAlXpUxAQBASB6BC45pprCNqOuJlgRbdi6VkQEASEgNidASEgdvg5by0ExDmk0qEgIAgIAs4QgAP6rl27qKioSPUJJ/Thw4fTww8/rJzQjz76aPUzefJkGjNmTNad0J0tXDoSBASBEggIAbE7EEJA7PCT1oKAICAICAKlCIHzzz+/CRG9TUQViegXIlq1d+/eW955551pvXv3PmTv3r2vEFFNItq4d+/ey995550ZpQgeWaogIAgIAkYICAExgkkqCQKCgCAgCAgCgoAgIAgIAoKACwSEgLhAUfoQBAQBQUAQEAQEAUFAEBAEBAEjBISAGMEklQQBQUAQEAQEAUFAEBAEBAFBwAUCQkBcoCh9CAKCgCAgCAgCgoAgIAgIAoKAEQJCQIxgkkqCgCAgCAgCgoAgIAgIAoKAIOACASEgLlCUPgQBQUAQEAQEAUFAEBAEBAFBwAgBISBGMEklQUAQEAQEAUFAEBAEBAFBQBBwgYAQEBcoSh+CgCAgCAgCgoAgIAgIAoKAIGCEgBAQI5ikkiAgCAgCgoAgIAgIAoKAICAIuEBACIgLFKUPQUAQEAQEAUFAEBAEBAFBQBAwQkAIiBFMUkkQEAQEAUFAEBAEBAFBQBAQBFwgIATEBYrShyAgCAgCgoAgIAgIAoKAICAIGCEgBMQIJqkkCAgCgoAgIAgIAoKAICAICAIuEBAC4gJF6UMQEAQEAUFAEBAEBAFBQBAQBIwQEAJiBJNUEgQEAUFAEBAEBAFBQBAQBAQBFwgIAXGBovQhCAgCgoAgIAgIAoKAICAICAJGCAgBMYJJKgkCgoAgIAgIAoKAICAICAKCgAsEhIC4QFH6EAQEAUFAEBAEBAFBQBAQBAQBIwSEgBjBJJUEAUFAEBAEBAFBQBAQBAQBQcAFAkJAXKAofQgCgoAgIAgIAoKAICAICAKCgBECQkCMYJJKgoAgIAgIAoKAICAICAKCgCDgAgEhIC5QlD4EAUFAEBAEBAFBQBAQBAQBQcAIASEgRjBJJUFAEBAEBAFBQBAQBAQBQUAQcIGAEBAXKEofgoAgIAgIAoKAICAICAKCgCBghIAQECOYpJIgIAgIAoKAICAICAKCgCAgCLhAQAiICxSlD0FAEBAEBAFBQBAQBAQBQUAQMEJACIgRTFJJEBAEBAFBQBAQBAQBQUAQEARcICAExAWK0ocgIAgIAoKAICAICAKCgCAgCBghIATECCapJAgIAoKAICAICAKCgCAgCAgCLhAQAuICRelDEBAEBAFBQBAQBAQBQUAQEASMEBACYgSTVBIEBAFBQBAQBAQBQUAQEAQEARcICAFxgaL0IQgIAoKAICAICAKCgCAgCAgCRggIATGCSSoJAoKAICAICAKCgCAgCAgCgoALBISAuEBR+hAEBAFBQBAQBAQBQUAQEAQEASMEhIAYwSSVBAFBQBAQBAQBQUAQEAQEAUHABQJCQFygKH0IAoKAICAICAKCgCAgCAgCgoARAkJAjGCSSoKAICAICAKCgCAgCAgCgoAg4AIBISAuUJQ+BAFBQBAQBAQBQUAQEAQEAUHACAEhIEYwSSVBQBAQBAQBQUAQEAQEAUFAEHCBgBAQFyhKH4KAICAICAKCgCAgCAgCgoAgYISAEBAjmKSSICAICAKCgCAgCAgCgoAgIAi4QEAIiAsUpQ9BQBAQBAQBQUAQEAQEAUFAEDBCQAiIEUxSSRAQBAQBQUAQEAQEAUFAEBAEXCAgBMQFitKHICAICAKCgCAgCAgCgoAgIAgYISAExAgmqSQICAKCgCAgCAgCgoAgIAgIAi4QEALiAkXpQxAQBAQBQUAQEAQEAUFAEBAEjBAQAmIEk1QSBAQBQUAQEAQEAUFAEBAEBAEXCPx/VFEe8NWcobYAAAAASUVORK5CYII=\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from '/home/madness/Documents/Projects/git_better/venv/local/lib/python2.7/site-packages/matplotlib/pyplot.pyc'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = get_cleaned_processed_df()\n",
    "y = df[\"label\"]\n",
    "plot_3d_tsne(df, y, \"raw_class_distribution.svg\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}