bayesian-sparse-logistic-regression-with-spike-and-slab-priors-using-edward.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "import edward as ed\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from edward.models import (Bernoulli, Laplace, Normal, \n",
    "                           Empirical, PointMass)\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.datasets import make_moons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use('seaborn-notebook')\n",
    "sns.set_context('notebook')\n",
    "np.set_printoptions(precision=2,\n",
    "                    edgeitems=3,\n",
    "                    linewidth=80,\n",
    "                    suppress=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'TensorFlow version: 1.4.0'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'TensorFlow version: ' + tf.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Constants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = 10000  # HMC nbr. of samples\n",
    "P = 1000  # Nbr. posterior (predictive) samples\n",
    "\n",
    "seed = 8888\n",
    "rng = np.random.RandomState(seed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Toy Dataset (\"Moons\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    *make_moons(500, random_state=rng),\n",
    "    test_size=.2,\n",
    "    random_state=rng\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "N, D = X_train.shape "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "    canvas.addClass('mpl-canvas');\n",
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       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
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       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
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       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
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       "\n",
       "\n",
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       "    };\n",
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       "\n",
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       "    // Updates the figure title.\n",
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       "\n",
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       "    var cursor = msg['cursor'];\n",
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       "        cursor = 'pointer';\n",
       "        break;\n",
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       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
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       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
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       "\n",
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       "    fig.image_mode = msg['mode'];\n",
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       "\n",
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       "// A function to construct a web socket function for onmessage handling.\n",
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       "    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",
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       "\n",
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       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"700\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(7, 5))\n",
    "\n",
    "cb = ax.scatter(*X_test.T, c=y_test, cmap='coolwarm')\n",
    "fig.colorbar(cb, ax=ax)\n",
    "\n",
    "ax.set_xlabel('$x_1$')\n",
    "ax.set_ylabel('$x_2$')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gaussian Prior"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model specification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = tf.placeholder(tf.float32, [N, D])\n",
    "\n",
    "w = Normal(loc=tf.zeros(D), scale=tf.ones(D))\n",
    "b = Normal(loc=tf.zeros([]), scale=tf.ones([]))\n",
    "\n",
    "y = Bernoulli(logits=ed.dot(X, w) + b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Maximum a posterior (MAP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "qw = PointMass(params=tf.Variable(tf.random_normal([D])))\n",
    "qb = PointMass(params=tf.Variable(tf.random_normal([])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000/1000 [100%] ██████████████████████████████ Elapsed: 2s | Loss: 113.618\n"
     ]
    }
   ],
   "source": [
    "inference = ed.MAP({w: qw, b: qb}, data={X: X_train, y: y_train})\n",
    "inference.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.15, -4.49], dtype=float32)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_map = qw.eval()\n",
    "w_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.44861546"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b_map = qb.eval()\n",
    "b_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Hybrid Monte Carlo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "qw = Empirical(params=tf.Variable(tf.random_normal([T, D])))\n",
    "qb = Empirical(params=tf.Variable(tf.random_normal([T])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000/10000 [100%] ██████████████████████████████ Elapsed: 21s | Acceptance Rate: 0.903\n"
     ]
    }
   ],
   "source": [
    "inference = ed.HMC({w: qw, b: qb}, data={X: X_train, y: y_train})\n",
    "inference.initialize(n_print=10, step_size=0.15)\n",
    "\n",
    "tf.global_variables_initializer().run()\n",
    "\n",
    "for i in range(inference.n_iter):\n",
    "\n",
    "    info_dict = inference.update()\n",
    "    inference.print_progress(info_dict)\n",
    "    \n",
    "inference.finalize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "w1_min, w1_max = -.2, 2\n",
    "w2_min, w2_max = -8, 1."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.JointGrid(*qw.sample(sample_shape=P).eval().T,\n",
    "                  xlim=(w1_min, w1_max),\n",
    "                  ylim=(w2_min, w2_max))\n",
    "g = g.plot_joint(plt.scatter, s=3.**2, alpha=.4)\n",
    "g = g.plot_joint(sns.kdeplot, zorder=0, n_levels=6)\n",
    "g = g.plot_marginals(sns.distplot, kde=True)\n",
    "g = g.set_axis_labels('$w_1$', '$w_2$')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Laplace Prior"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model specification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = tf.placeholder(tf.float32, [N, D])\n",
    "\n",
    "w = Laplace(loc=tf.zeros(D), scale=tf.ones(D))\n",
    "b = Laplace(loc=tf.zeros([]), scale=tf.ones([]))\n",
    "\n",
    "y = Bernoulli(logits=ed.dot(X, w) + b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Maximum a posterior (MAP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "qw = PointMass(params=tf.Variable(tf.random_normal([D])))\n",
    "qb = PointMass(params=tf.Variable(tf.random_normal([])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000/1000 [100%] ██████████████████████████████ Elapsed: 1s | Loss: 106.517\n"
     ]
    }
   ],
   "source": [
    "inference = ed.MAP({w: qw, b: qb}, data={X: X_train, y: y_train})\n",
    "inference.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.17, -5.56], dtype=float32)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_map = qw.eval()\n",
    "w_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.68323755"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b_map = qb.eval()\n",
    "b_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Hybrid Monte Carlo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "qw = Empirical(params=tf.Variable(tf.random_normal([T, D])))\n",
    "qb = Empirical(params=tf.Variable(tf.random_normal([T])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000/10000 [100%] ██████████████████████████████ Elapsed: 23s | Acceptance Rate: 0.910\n"
     ]
    }
   ],
   "source": [
    "inference = ed.HMC({w: qw, b: qb}, data={X: X_train, y: y_train})\n",
    "inference.initialize(n_print=10, step_size=0.15)\n",
    "\n",
    "tf.global_variables_initializer().run()\n",
    "\n",
    "for i in range(inference.n_iter):\n",
    "\n",
    "    info_dict = inference.update()\n",
    "    inference.print_progress(info_dict)\n",
    "    \n",
    "inference.finalize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.JointGrid(*qw.sample(sample_shape=P).eval().T,\n",
    "                  xlim=(w1_min, w1_max),\n",
    "                  ylim=(w2_min, w2_max))\n",
    "g = g.plot_joint(plt.scatter, s=3.**2, alpha=.4)\n",
    "g = g.plot_joint(sns.kdeplot, zorder=0, n_levels=6)\n",
    "g = g.plot_marginals(sns.distplot, kde=True)\n",
    "g = g.set_axis_labels('$w_1$', '$w_2$')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spike-and-Slab Prior"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model specification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = tf.placeholder(tf.float32, [N, D])\n",
    "\n",
    "w_mask = Bernoulli(logits=tf.zeros(D))\n",
    "w_raw = Normal(loc=tf.zeros(D), scale=tf.ones(D))\n",
    "w = tf.to_float(w_mask) * w_raw\n",
    "\n",
    "b_mask = Bernoulli(logits=tf.zeros([]))\n",
    "b_raw = Normal(loc=tf.zeros([]), scale=tf.ones([]))\n",
    "b = tf.to_float(b_mask) * b_raw\n",
    "\n",
    "y = Bernoulli(logits=ed.dot(X, w) + b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inference"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Maximum a posterior (MAP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "qw = PointMass(params=tf.Variable(tf.random_normal([D])))\n",
    "qb = PointMass(params=tf.Variable(tf.random_normal([])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000/1000 [100%] ██████████████████████████████ Elapsed: 2s | Loss: 286.974\n"
     ]
    }
   ],
   "source": [
    "inference = ed.MAP({w_raw: qw, b_raw: qb}, \n",
    "                   data={X: X_train, y: y_train})\n",
    "inference.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.3 , -3.53], dtype=float32)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w_map = qw.eval()\n",
    "w_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.046046846"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b_map = qb.eval()\n",
    "b_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Hybrid Monte Carlo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "qw = Empirical(params=tf.Variable(tf.random_normal([T, D])))\n",
    "qb = Empirical(params=tf.Variable(tf.random_normal([T])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000/10000 [100%] ██████████████████████████████ Elapsed: 32s | Acceptance Rate: 0.416\n"
     ]
    }
   ],
   "source": [
    "inference = ed.HMC({w_raw: qw, b_raw: qb}, \n",
    "                   data={X: X_train, y: y_train})\n",
    "inference.initialize(n_print=10, step_size=0.15)\n",
    "\n",
    "tf.global_variables_initializer().run()\n",
    "\n",
    "for i in range(inference.n_iter):\n",
    "\n",
    "    info_dict = inference.update()\n",
    "    inference.print_progress(info_dict)\n",
    "    \n",
    "inference.finalize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "w_mask_samples = w_mask.sample(sample_shape=P).eval()\n",
    "w_raw_samples = qw.sample(sample_shape=P).eval()\n",
    "w_samples = w_mask_samples * w_raw_samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.JointGrid(*w_samples.T,\n",
    "                  xlim=(w1_min, w1_max),\n",
    "                  ylim=(w2_min, w2_max))\n",
    "g = g.plot_joint(plt.scatter, s=3.**2, alpha=.4)\n",
    "g = g.plot_marginals(sns.distplot, kde=True)\n",
    "g = g.set_axis_labels('$w_1$', '$w_2$')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "mixtures = np.right_shift(np.packbits(w_mask_samples, \n",
    "                                      axis=1), 6).flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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AB+y62B/aYfZl0kA9iax4zJbvp8mJJ1z6r6MdvoiADyv8ye2zW4G8A37/NCjbSHOM1EZzeO7jO8vpyQvGZ0P4Gk72vsu13WM9PL4Fb7brgbA9930pP46x7MkvyOcy1J9tHTem3yffR3AUQD4LrrevonsP2E/H0Xi3fa4cgxURCDUBCQIQz086lyECFBQUQxOsx2Bta5n5++UB1tzIz1FFJ2EswC83n4R8QXkFL5wL7OXRNIh4IuVL0rul7vQdR1fbDycnIdW84BtvpR52DidFjpLfEHzhc3ClzJf/jyc2lmmQ5H3GIDttnPDA6rpDJxkL7n6m30vnQN+jadTxS/uvI5LsfiyPCYNQXi6vWx2A4BfAqiwRSsPyaZA5HOwpCsI+cJmPU/Z+4R4Lw9sfzxCc02PKgJRJsDIID+OcVl+OiVdm5osCGmrVgBgxPEGW/QxaQtt5MddEUhHEHJfM4UchRX7d5sdxeS2AQoc/jk/glE00Ub/G8AbXQ9wky0GKaAodPkhjW3Tzg63H90RWi/YHxj5zBSz7OcWAAttm836XrZtMJ/JKVxuuwsA7f57DwGV9V4CgPb8YXvPJoXuiQDebYusP9ht8hn50ZEfJSmYWVLtIeR76zsA3mB/jOTH0+dshnxHkCU5UcRxuwCFHMtuAPcA8CoI+VFytP3e5PtnjZ3g5gsArgHAPagUm2NtTmxzEYCmdCabrhGBoAhIEAZFXu2KwGACFHr8Kksxxz0t7sIXHQXdF10vM/4998BwvwtfmBQ1/LJLsUjB8z+uCviy5EuTDgJFIovzxZQvYkcMnQngP/aLny9iOgIsFHAUje7MbhSodBiOc32lpj151H4RzrXv/b7tVFCYUoSx8EVJp4Lic7gIIaOS/BrNL8EH7Pvp4PDPf2/z4h+nKwh5rfYQ6tcnAtEkwA9g/Pj19yQxNRQNLzY1WRB+zP5gx49QFDksJbZYoKijXWu1o4EUPC22gHNH3ngvVzCcbNtWp59X2CstnCin009+xGNEzyls9+0eBCE/8NHWsl8sFLAUOHyWH9p/RrHJ5ayvcrXDj40UsMNl/3TENaOMjJyyjLJXjFAMvw3AX+w/5wfI1Ul9TyUI2RcKML4H+aGS4pd8uMpmuauPQy0Z9SoIGWk8235XOtXzz/gO/l/7Y6rz54wg8l3FVSr8yKoiAqElIEEY2qFRxyJEgC9svrj5hde97MVBQDHGr671rhc1/44vZIo5LjHi11pG8vjS4XIc93JKRum4dJTLSykMWSgIGa3jC9QpFGj8iskvz1zi5BTH2WAffg2gwV7Ow5cfl3+6C5co8YXM5ap0Lvj1lEKOL2d3+bG9nOlQgnCi7Sh82172477/LjuSSnHJIkEYoR+MHlUEMiRAu8Tle/yYdGkadXixqcmCkB/X+PFqclICFC7L/JO9wuNfLkH4G/ujoLtbFK6MZCYfZcF3AVeROB8JnX7yQx5trlP4wY4f4tKNEFKkUaw5hT4i7ThXeVAEsTByx2W3jBZSBLEwSdfx9rLMQ2XQdgQhPya6hS9FE+ujYHff3wjgn6734lBZRsmIUUFGWY+1tzLw/eQuuRKEXCUzK6lurtLh+5UfQpMjgYyEkiGz2aqIQGgJSBCGdmjUsYgQ4FdNLiuiYOOeEUavkgvFD0Uel5O6iyPguE+C+08ozhgZ5JdWLmtxF75YGdXjF18WCkKKxnOSruPLmPV8wPXnzpImikm+9Pjif3KY8eFSHb7kuSyVX5iThS4T5nAJ6aEEoSN4HSHqbtKJPFbbwlaCMCI/GD2mCGRBwGuE0ItNTRaEjG5xv99rk/rrfGD7sL1vzrGvFDBccuguFDiM2A1VGLVj9M7pJ/cR9rgudp43XUHIVSoUpu5CQUMBR7HJQjHK9xU/PnLPON9DXH5Jm0xheqjiLBnlclp3IbvxKZ6V7ykuY+X2CJZDHTvhLB2l8HP2m7vbyJUgpAh+XVL/GZl1vzOTGVBQc9xVRCC0BCQIQzs06lgECPDlzQgfxR4jaMlJWxwEXgVhslPAelIJQr4g3ZFAXkdByOgdnRWnuJMeUHw6Qo3/n1/BUxUKRi47MiUI6cRwuVJyUhk6WPyK7rZ1WjIagR+XHlEEhiDAaA33MDMiNVwZSmilsqnZCkJ+1KNNdReKSmYa/eQQHWW0kxFBk4KQXWFEkMteuayTH+y4TYHLI5mA7FDFSSrDD3nuQnZj7Drcf+4kcXHeU4cShEzgwigcV6Rw5Qv3NLrLUIKQyzm5bDTZH3aey/3RMrk/Tv3kz60V/MDamwIA3zlPDDfZ9PciECQBCcIg6avtqBPgJncKL/f+jFRMhloyyn15fMkMt2SUX175ckxeMpqpIOTXYn4RTl5elKrvfi0ZZaIFLg1ylowycx+/bnM/irtwPyaXhrltHYXqrTqHMOo/Pz1/RAnQntJ5d++fHgrFUEtGU9nUdJeMMqnKn1MsGU0lCLl8n5ElZhc91FJMk0tGyeoCex8mV4t8y7a7jMoNV/wShM4yViZ2IYv77SQz7v4w0sgs18nLb53VKox8upd7MvrJTK7pCEKOHbc2UCC7E8INx0N/LwKhISBBGJqhUEciRsDZhM8jGpg05lDFSSrj3ojP6+lUMLNnclIZZqPjpnqn8IX9mRRJZTIVhKyXyWm4P4ZfhZPP8aJIc/aH5CKpDPcScrmS87Jmm9wv4k4qw0QK3EdJ54nLc1h4H1/O/BrttnUUxxTS7gx9EZt+elwRiCwBZ7/ZZtsm8uOWu/DvGZHiknZneWc6NnWopDLcI849gyzMtszrWG9yUplUgpBJxiiiaM/ZB3fhsksmVOFecGYB5QoTv5LKuLOisg9MjsOjg5jMhe8y9p0f5YYrfghC51xJrlbhkRZOwp3kBG20+dxOQVbuwjMnuZfTyVLKv2OmUi7X5TaNdAQh5ww/fjIhDhMBucU73z3cd08xqiICoSUgQRjaoVHHRjABChUureH+Di4FcrJnJj+ycxwCX/rc/8cvmzy0nmKIGUH5AuP5R6mOnXBSX/MLLl+MqY6dyEYQcpkrM4pygz37xDTi/GrOpa9M3ODsl+Cz8sssnyGbYyd4RiIzsTrHTtCx4p5LJx0504DTwaNzx301PMaDezooTPnl2m3r+NWdWfu4Z4dODesYbk/kCJ6OejQRiBwBRrjovHPpKFcR0Bby6ARGDbnP2hFhBOMkQhnOpg517ATFAleDcLkhBQttT6pjJ1IJQtpNJlXhUkT2l0f98MgdfiDjx0AeP+Rk0uRxE8zSyQRlzATKfW6ZHjvBJfi05+wnj+mgPe9ImiXOChcukWQEM/nDYKpJlWtBSLvOaCCXiPIf50Mkl48yoQ7/jDaehVsh+E6g3ef7hPs7eS/FLf+b7wxm5ObzcLUJ5wbfMekIQtbP8wi5aobs+b7lShTeS8FMMZ+8HDhyPzo9cLgJSBCGe3zUu5FJwNkHMdzTuQ9MZ5SLS1i43IgRODoXfMmkOpiekUQeqkthxmgYI2lDHUyfyR5Cp9/MtMb9FxSnFGR8wfIrNV/6XJLpFO41ofPAJa6ZHExPxyb5YHoeNuzOpMq2uH+EX6mZ6Y0ij/sHGT11H0zP67ish+zoMFBg6mD64Wai/l4ERh4B2gaKMNoNRut4Xh1XF3DlBT9y8b9Z+PEpHZs61MH0PCyeSVH4AZBRJNoo2kinJO/RTiZNwcKPfkzMRYFHYcYPcFxdwg+CPK6ChdEvrgbhuX78/xQ7Xg+mp6Dkyg/un+PB9E4dzhFE7r45GUwpvihM0ym5FoTOck8ev8RjL5xCgUqRz4+WjACyUODyoyKT/PDZnIPp+Xf8aMjoKs8L5DuTXLnvnsI4XUHIet5kjxXrYeEez/vsj5RaSprODNE1gRGQIAwMvRoWAREQAREQAREQgbwk4CynpVDlkUkqIiACeUxAgjCPB09dFwEREAEREAEREIEACHDPNrcj8Jxb7mNUEQERyGMCEoR5PHjqugiIgAiIgAiIgAgYJMDlr9xDziX5FIVDHYlhsEtqSgREIFsCEoTZEtT9IiACIiACIiACIhANAty/zv14zOrJI32YPEVFBEQgzwlIEOb5AKr7IiACIiACIiACIiACIiACIpApAQnCTMnpPhEQAREQAREQAREQAREQARHIcwIShHk+gOq+CIiACIiACIiACIiACIiACGRKQIIwU3LhuY9jyDOUtI4/PGOinoiACPhLgOeI8cDpPn+bCV3tsvehGxJ1SAREwGcCUbX3PmMdXL0EoVHcvjQ2GcA2X2pWpSIgAiIQXgJTAGwPb/d86ZnsvS9YVakIiEDICUTR3hsdEglCo7h9aawWQPPWrVtRW8v/qyICIiACI5dAS0sLpk6dygesA9Aycp805ZPJ3kdswPW4IhBlAhG390aHXoLQKG5fGrMchObmZglCX/CqUhEQgTARoINQV0ctGF1BKHsfphmpvoiACPhFIOL23i+sKeuVIDSK25fGJAh9wapKRUAEwkgg4g6C7H0YJ6X6JAIi4AuBiNt7X5gOVakEoVHcvjQmB8EXrKpUBEQgjAQi7iDI3odxUqpPIiACvhCIuL33hakEoVGsRhuTg2AUtxoTAREIkkDEHQTZ+yAnn9oWAREwSiDi9t4oa0UIjeL2pTE5CL5gVaUiIAJhJBBxB0H2PoyTUn0SARHwhUDE7b0vTBUhNIrVaGNyEIziVmMiIAJBEoi4gyB7H+TkU9siIAJGCUTc3htlrQihUdy+NCYHwResqlQERCCMBCLuIMjeh3FSqk8iIAK+EIi4vfeFqSKERrEabUwOglHcakwERCBIAhF3EGTvg5x8alsERMAogYjbe6OsFSE0ittq7EMArgIwAcBzAD4C4KksuiEHIQt4ulUERCC/COSZgyB7n1/TS70VAREIEYE8s/chIue9KxKE3pllc8clAH4H4EoATwL4OICLARwOYE+GFWckCGd89t8HNbfp2vMy7MLQt/X19eG5bc1Yt7sVc8bXYMGUOhQUDJ527mtmj6u2Klu/py2t6506eU9yO4lEAt+/Zy3uW70Hk0ZV4IOnzMbi6Q0D7fPvb16+Ffe8uBv1lSVYPK0eK7Y0YvO+dkwfU4XjZjSgsKDA6ofTJ/aP9/3xic24b80edMZ6Mb62HMfNGIWCgkL0JfpQUMjnK8C+tk7sONCBlu4exHqBymKgorQE25o60dUDFAEoKgQKC4Ga8iJMqi1HW6wXO5u7UVpcgNEVxdjeFENnAigEMLqiEHUVJdje3I2u3leY15YCNRWlaO6IWfXy3sVTarCrLY7NBzoxrroUMxvKsbUphrLSQhT0Ab2JBJo6YuiI96Gntw/xBFBcCNRXFmNSXTlqK0rxwo5mtHb0oo9PUwBUlRViTFWx1UZ5UQH2dcbR1pVARXEBxtSUYG9LzHpOPs+4mnIsmVaLwqIiNHXErc7OHVeNpzYdwMb9HaguLQJZnnnEBGxr7MD9a/agN8GW+lBbUYaLFk/B3Ak12LC3fWAeuMc40deHzfvb8NLOVms8zzxiPA4bX2PNG9bCerbs78Ce1m4cO6MBFy2ZgsLCQnCuPbu1Cfe/tNsap1PmjrXuT55vXudt8jx8eVdLPzerJ/yfPmw50IGXdrViVHkxJo6qwN62GJZMr7f6xj6k+p2k6oebw6yxVVi7qwW3Pr3daufiJVNw8bFTrWdNVYZ7Ls7tW1Zsw4rNjQN9y7SunBsTu8I8chBCY+/5m3WX8mK/RgdYt6cNT29pQmFhAV41swFT6isGNcbf5KPr9iPWk8Ds0ZXY09aN1u5ezBhdieNn1ls211027mvH8k1N1o/phBn1mDa6EvvauvHoy/vR3ZPA/Ak1OHpKLbY3deKbd67B1gOdlp18+/FTcMYR41FMIwtY9u63j2/BS7vaUIgEptRXYv3edstGjKoowdLZDaivLMOY6lIUFxVgV0s3qkqL0NYVx+3PbLfsJ39jFSUF1jOx1ol15aDZ2tHc1W9Pu3oQ7zdA1m+fNpXsE0m4y4uAurJCNHUl0EP7XpaMZIkAACAASURBVAAUFgHdrnFi/cUFQMyuz10F6+bf8zXAf1cVAz19sN4LvLyqhHa4EJWlRYj19KEz1mP93YA9su+rKAHKSwoR7wXauhMH9bOysL+NWMK2Y/Yz9SX6/5yF7bOeCXWVGFtTgsb2HvT2AfXlhXh5bwfa470oLizA+Joy6z2xry2O5o4e9PSyQwUYXVWKNy2ehIbKMssmjqstw0lzRlvz54kN+7FqRwu2HuhCZyyO/e1xlBYXYnpDJaY1VKCkqBC1FSXYtL8dz29vQUVxoeVjXLRkMqrLSxDvTeDeF3fjsQ2NKCksxNJZo6x51xZLDJpvfFc8uanReshjZ4zCzDFVKX8gyXObFz2x8QASiT6MqizB/rYYtjZ2ory4ECt3tKKtuwfVZUUYW11qvWOn1lfgPa+ZgdbOGB5bf8B657G/h0/o9zE41x5au8/6PUxvqMAJsxqs/j64dp/1Hp1YW4otB7rw9+d2oDuewMKpdfjUmXOttlMV3vvIuv3Y09KNcTVleM1ho1HGSWkX+gF/fHIbXtjRgtqyYlz+6qmYUp/62XnLml2teHZbszWer57dgAl1g3/bfliVPLL3fjy+0TolCI3itkTgMgAfdtnSrQB+BODaDLviWRCmEoNO27kUhXQ+f/rgeqzf24bSYr6YejF7bDU+cMrsAVHmvobG/YVtzVZXjpla1+8wHOJ6p85ZY6sth3vDvvaBduhc3Lpim+Uk8DVIAVFeUoQrT56FD592mCUMLvv1U3h+WzN6En1W32iw+WJ2XpolRQU4fHyNJZjosB8zpQ7PbWvCpn3t6ODFScX5MfHfB/9thqM7Am7rl8femBQVAA2VpTht/jhrfGbxBU3htrcV6/a0Y9PeNnTEeznsKCossARrTVkJJtWXo6k9hgMdPZZwLy8pRlVpIWaOrcZvLj8WP3toA+54YRc6Yj2W49QR67Ve1kdPGWU5D5xvnCO8Lt15mzwPeR8dzcb2bksglxQBBzri6I71Wv3stZ0rfoSgszB9dBVOmDUadHzdv5NU/XA4bNjbBs7Pe1/cg6bOWL+3VlBgOaD8kPHb9xx/kCgc7vdIXpf/Zpk1v0uKixDv6cWMMVW48d3Hea7Lz2mbRw5CKOx9shh0xsYPUfjf9ftx70t7rHnM+UaH902LJuGISXxNwXLc//jkVsue8vdGp5m/v6kNlZa950ejtx4/ZWD6PLWpEXet3G3NdRba4hNn1ePJTU3Wb4n18D46z39atg2tXT3Wn7Ht0qJCvGXJJFx5yiw0d8Xx6ZtXYkdTJ7p7XrH3jqDhz4du8pGTatDdm7AE0vyJ1db7aFtjV0p7zg96FEVukeXnvM+Xui2xSjuXQsimegZH3E5pqMCiaaMse19fUYzy0iK8tKMVm/Z3YH9bF7oJm/aec6GvzxJ8UxvKsaOxC53xhDXmHHt+XJ0ztgpfPG+e9QHgv+sPWM1yLjZ1xi0hOXd8DeI9CfCD2lGTa/GP53ZaIocl3tuHs48aj+Nn1A/qbvLc3tcWszo0prrM+iCwvbHTehdRZO1pjVl2nlVa3zkBjK0ptcRYeXERDhtfZYlZZ/6eMncMFk+rw08e2mg9Pz+KsH/sK98dfE+x7qc2HsCu5m577lsYMKmuAjdevghV5YNFIev5v4c34UBHzHq2fq4luOLkmQPP+vm/rcSa3e1WX2j/2cY3LzzSsvvJ5cE1e/HIy/tRUtz/YZU8LzluCg6zP+L7NT/zyN77hcBYvRKExlCjlP4ngIsA3O5q9rcARgF4Q5pdmcgPk65r+ct9uLm5GbW1/S/d4YopQchIzE2Pb7KcA6dQeF26dAYWTuUjw4rWONfwqy8jiXzDHjauBqOryyyhNtT1Tp27mjvRhz5MrKscaOfpzfstB7uvz1Z4FCSJPswZV4VvXbTQiqp89+41aI8lLEPYFX/l6yjfNzTiNObVZcXWV1a+nBj1orPf/yJQ8ZtAaRGwcGo9Zo+rwc7mDhSgwHpxrdzejP3t3ZZjRwHElyILg2K15aXWS+1AO6OsRdaLta68xIrEXrBgIlbubMHmfR2WwOmK91pR1ZqKEhw1uc56sXO+nTCzAU9uPJD2vE2ehyVFRdY8jvX2WfXzBdrcGe8XxX22dgMjuYUYW12GeCKByaPKcfiEukG/k1T9cDjwy+z6Pa14Zmuj5bzyhU8HmSzoEH3unPl4y3HTBg3RcL/Hvy7bghvuX2eJQadQFH74tDme6/JzbuSJgxAKez+UGOT45FoQ0km8/r71VtTOXfjh44rXzrT+6HePb7GcZ5bN+9txoD1uOcVHT661frcUd1eePMOytSw/vG+99eHHXRgBnFJfPmilyX/X90dQErT3dmF/Zo6pxBfPnYdlmxutKF9zV/9HJP72HcEy8CGvgEwKMbqaQ1dg2X32lSJTxX8CXGly8uFjrQ+3+9u6rbnQ1NmDvYwgd/Ygbgkl29YX8F0AlBUXWcKrM95rRTo5bozuMup40uwGLN/SjNau/jnGf/M9X1FSiCXTR6GitNhqg/c5os15So79R0+bPWguJc/tF3e2WoJw3oQaPL+txaqrpStu2eLmzv4542hidpsrdybWVVjPxg97M8e+Irp4z7zxVXh+R+ugCDl/Iw1VZagpL7bm7H0v7RlYzeN8iuDv5h3HT8X77d+Y0+mntzTiX8/vtt4zr9jzBM45ajyOnVFv+TKfuXWV9U51Cn2heRNr8NULjhg04BST19+7zhKV7sKPOe99zQxfJ0ee2HtfGZiqXILQFGlgEoDtAE4E8Lir2W8DOBnACWl25SsAvpx8bRgF4S3Lt2LFlqaDHstZJse/cF/DqIcjtvg1beaY/uWjQ13vVLxxb5v1fxkFcsq9q3ahqat/qaK7jCovwdXnzseyjftx/+q96O7ptQw5/3HcGCuiZetIGsua8hJrWQo9CWt5kxyENKdq5pdxDPii49Kg42eNBueGtZKsD1YkmIKP7ya3AePfV5YWWy9hvjyLCgqslyGdBo7fGK6jKuBS3n5B3+8g0JEosl/Q/fOnL5FAQYoll+nOQ7bPNpz6Obco+uiIOuKVfWX/6qvofDK6WWw9p7uk6ofDgb+Npzbsx+YD7QMcuMSKpaKkCOcePRHXvvmYQfUN93u8+pbnsHzzwb/X42bUe64r85Ef/s48cRBCYe9NCsKe3gS+dddaFLkcTI4mHeFPnn6YNbA/eXADWuxOvbynDe3dvVZE5ejJddZvlWLyzYsmWVEbCrpr71xrL8F/ZV6s3tmCeRMHf/y878U96Oql2HNbhD6Mqy7Dh0+bhac3N+PxDfstgcHVIhQGbmedtffbHC59LLeccl7HJYqMzqj4T4B67tVzxljLH3dakVwKrB4rQtbe1WOJEeejF8eJ7wcuA+V72xF2HEWawYbKEisKuL2pw/roy8KPcoz+MdrMDxANVaXWfe3dPQN22HlKzr3Pnj134KNDqrnN1UUs8yfWWJHkLquuXmsetdtzxj3HqMu4dYXPQyHFFUdOYf2MBu5o7h4E+uXdbVY/+ZGisT1mLbXmhww+Pz+QspDDqYePxldeP1jE3bFyF57b2jzowwmfi+2ed/QEa6vMTx7ciDIqa1eZUFuG6y8Z/O7gb+C797w8SDzylmTh7McsyRN778ejG69TgtAc8lw5CHkfIXzX0hlYMEyEcO64GjTYEZuhrneGjhFCKgXuYXBKf4Swo98Bt2d5f4SwGt++aAHWKEJobuZn2JIVIZxWj9lj04gQcg9OwRARwooSMOp7wcJJWLmjOY0I4Wg8uXH/QRHCdOdhcUYRwgocPuEVJ7c/UnlwP9KLEBbj8+fMx8XHTR1EfqgIofNcQ0UIP3LaYZ7rynDI07otTxyE0Nh7k0tGf/bQRmtZntux5n67S1/VH63mXtc1u9sswbWzuQs7m7osB50CkFEc2uhPnD4HFfzxA/jFI5us/YLOvnM6tHSMR1WVDoqk8HfNyCGjRe62j5pUg2vecCSe2dKIXzy6CS2djAz2oauHQrT/StoN50NNbXkR6ipLrP8eW1NmfXxq6lCEMK0fpn1Rpktoa8oKccrh4yyB09LZv+RyX3sMu1u60dIZt1ZcWKtF7TErLSpAVTmjfH3o6O61hA3nB5dlUkBxH+Hdq3Zjb2vM2o/IbQLc01dbXoJjp4+y9pZyvo2pKbX2/rnnGFeL/M9JgyNfyXOb++koULlkkvscKWAZGeR8tiLfdoTQcUEqSgutyPeBthiOmlyDcbX9UXCWmrIiay/hA2v2WStKnLK3tQtVpcWoLCtGTyKB+17cDQYfneWtpMGP1p8+8zBL5LnL5v0duPHxzdYHUadw3+FlS6daS0IpkK+46Zn+r992oTB97dzR+OhpcwbVRa4/fnAD2qx1u/2lPwJfhbce98oSby/zJN1r88Tep/s4ob5OgtDc8ORqCVFyj7WHUHsIzc3iDFrSHkLtIcxg2gx5S544CKGx9yYFIUXZX5Zvs6IudITrK0stB3RUZX8kvKO7B7/57xZL5FGPbTvQYf0dk8Aw6nHa4WOxdPYrkfJdzV34w1Nb0dbVAwb/uPz74iWT8a/nd2FXS5clChlZPOuIsVYEY9P+zoGIOZeqfuS02TjryPFWdOkbd6zB8s2NVl2MSvb0Dt7XTIFx/IxRaOP2gUSftYx7w74ObNnP/coHT0f31oJ098vl8ncQxroch5JjmbRyeMju8h4u1Z07oQqTR1VaH3AXTamztms8sHYv1uxqs5ZZMgJHoU69xCX/nFtT68utDwuMyDGKxfnQUFWCk+eOsfaC/2fVbvx1+Xa0dvegoK/PmgdM7EIxxkUgnG+Hja/G75/Yau0zZcK16vJiawkmI8Xukjy3uRKDhctVuWqI/eBz8IMI/+mMJSwB62w/GV1TakU0j5lSa833xo4eFKIPFWXFuGjxJExrqMQfn9pqJVKjOCVD7i3c3tSN1bu4PLX/97JmT6s1d/n74jUnzmqw9v2lSv71r+d34umtzdbF1H0Lp9Th/GMmDIjfm57YjH8+v9vam8uLJo+qwLcvOspaZZJcuAXn5hU7rARFrIxR2HefOM3ay+lnyRN77ycCY3VLEBpDbTXEJAM8YoJHTbDwU9AWADeYTCrDho1nGWXW0HHVh84yuqcNs+119UzKkc71zjV8JitLo6sdJ8vo/Wv2WtnghsoyyiQIoyqKrSyjXHfPL2vTR1da2SlpZNkGC/vE/llZRp/cjPtX77FeQoOyjNp7D50so9sbO6xlL9wGU1HMJRYl2OpjllFmqStJlWV0dDm2Ng6dZZQvb75ckrOMtnX0Wo4bXybVriyjZa4so5XMiMrsca0xK0veQJbR6XUoKiy09vbwdXOoLKMPrNnTvyTIzjL6ZifL6L6OgXkwMMa7W63lXHTUXtzZZrV3xnw7y+he7hvtr4fj6M7kOSjL6Oo91jMNZBlNmm8D2TjTnLfJ8/Dl3a1WP/gDtwIRdpbR1btbLaeW85HLShcnZxlNai9VP9xzfdaYyoEso3ygixZPTi/L6BDP5WQZZZbIxdNGDWRnTWUm02Hkh3nNIwchNPbeZJZRRhnW7m6zIj10tpOzhnLeUGhRNHL/1d7WbivT59zx1agqOzj9Ke3C2l2tVn38nfHfrIPJRuiIM0Mjo0L8s8fW78ODa/bjiEnVeN28cair6Bei/T/BPnAJ3vItTVZWaTrgu5s7rSyR3LPOyMiOpm7L9jMCQ3vP3ynLoy/vxYOr96CxqxcnHzbGiirR4WefmVxj9e42pi7Dxj1tlhDq7u139CfXlWLV9lZwFUtRUZ8lLCcwic6YasyoL7eWpD67vdXKeDm6qgjLNzZaNquSyaYaqqw9kC/tbMF2RlILClFUTEe82BJLbd194OMxE/W5R4212P3hqW2YP77a2nPW21eAuVxd0dqBxg5m6IxZmSlj8V40dsYwe2ytle2Yvj+zqS7f1IhYby+qS4qwubEb8yZWW5mvmW21Dwk0tsfR2tWLOWOqMK6u1BLXzFw6uqIUM8dVWmKOAm1faxx72rpw3Mx6LNvYaGWcZSbYqjLu1a62snBS5DHrKJO+MZHXGxdNRndvL7bs77T4c5kkCyODXFrMpf3dtvBq707g2Bl11juFUURez/m2o7kTsXjC2mLCTLROYfZX9qO4uNBKFEOxxqyb7vnGMaTvwH8zu/UrEbjBFix5bvNvOad4H/cEsg5+TOB/M9HN05sbrT15FKHPbWvBCTPrregc318Ufly6PG9C9UAmXNbHfau7m7sG9W93Sxd2NHVh1thKK5v5X5Ztsd63FyyYgCMn9+djGKocaI9Z78JpoyswuqrsoMsotrl9ZsaYShw7vf6gLPDuG5gIimPHfZdMyJP82464vffj8Y3WKUFoFDeYhpxJZK6whSGPnXgLgHkAdmfYFc8Rwgzb0W0iIAIiEDiBPBKEsveBzxZ1QAREIJ8J5JG9z2fMVt8lCM0PIY+ccA6mfxbAR+3IYaY9kSDMlJzuEwERyDsCeeYgyN7n3QxTh0VABMJCIM/sfViwZdQPCcKMsIXqJgnCUA2HOiMCIuAngYg7CLL3fk4u1S0CIhAqAhG390bHQoLQKG5fGpOD4AtWVSoCIhBGAhF3EGTvwzgp1ScREAFfCETc3vvCdKhKJQiN4valMTkIvmBVpSIgAmEkEHEHQfY+jJNSfRIBEfCFQMTtvS9MJQiNYjXamBwEo7jVmAiIQJAEIu4gyN4HOfnUtgiIgFECEbf3RlkrQmgUty+NyUHwBasqFQERCCOBiDsIsvdhnJTqkwiIgC8EIm7vfWGqCKFRrEYbk4NgFLcaEwERCJJAxB0E2fsgJ5/aFgERMEog4vbeKGtFCI3i9qUxOQi+YFWlIiACYSQQcQdB9j6Mk1J9EgER8IVAxO29L0wVITSK1WhjchCM4lZjIiACQRKIuIMgex/k5FPbIiACRglE3N4bZa0IoVHcvjQmB8EXrKpUBEQgjAQi7iDI3odxUqpPIiACvhCIuL33hakihEaxGm1MDoJR3GpMBEQgSAIRdxBk74OcfGpbBETAKIGI23ujrBUhNIrbl8bkIPiCVZWKgAiEkUDEHQTZ+zBOSvVJBETAFwIRt/e+MFWE0ChWo43JQTCKW42JgAgESSDiDoLsfZCTT22LgAgYJRBxe2+UtSKERnH70pgcBF+wqlIREIEwEoi4gyB7H8ZJqT6JgAj4QiDi9t4XpooQGsVqtDE5CEZxqzEREIEgCUTcQZC9D3LyqW0REAGjBCJu742yVoTQKG5fGpOD4AtWVSoCIhBGAhF3EGTvwzgp1ScREAFfCETc3vvCVBFCo1iNNiYHwShuNSYCIhAkgYg7CLL3QU4+tS0CImCUQMTtvVHWihAaxe1LY3IQfMGqSkVABMJIIOIOgux9GCel+iQCIuALgYjbe1+YKkJoFKvRxuQgGMWtxkRABIIkEHEHQfY+yMmntkVABIwSiLi9N8paEUKjuH1pTA6CL1hVqQiIQBgJRNxBkL0P46RUn0RABHwhEHF77wtTRQiNYjXamBwEo7jVmAiIQJAEIu4gyN4HOfnUtgiIgFECEbf3RlkrQmgUty+NyUHwBasqFQERCCOBiDsIsvdhnJTqkwiIgC8EIm7vfWGqCKFRrEYbk4NgFLcaEwERCJJAxB0E2fsgJ5/aFgERMEog4vbeKGtFCI3i9qUxOQi+YFWlIiACYSQQcQdB9j6Mk1J9EgER8IVAxO29L0wVITSK1WhjchCM4lZjIiACQRKIuIMgex/k5FPbIiACRglE3N4bZa0IoVHcvjQmB8EXrKpUBEQgjAQi7iDI3odxUqpPIiACvhCIuL33hakihEaxGm1MDoJR3GpMBEQgSAIRdxBk74OcfGpbBETAKIGI23ujrBUhNIrbl8bkIPiCVZWKgAiEkUDEHQTZ+zBOSvVJBETAFwIRt/e+MFWE0ChWo43JQTCKW42JgAgESSDiDoLsfZCTT22LgAgYJRBxe2+UtSKERnH70pgcBF+wqlIREIEwEoi4gyB7H8ZJqT6JgAj4QiDi9t4XpooQGsVqtDE5CEZxqzEREIEgCUTcQZC9D3LyqW0REAGjBCJu742yVoTQKG5fGpOD4AtWVSoCIhBGAhF3EGTvwzgp1ScREAFfCETc3vvCVBFCo1iNNiYHwShuNSYCIhAkgYg7CLL3QU4+tS0CImCUQMTtvVHWihAaxe1LY3IQfMGqSkVABMJIIOIOgux9GCel+iQCIuALgYjbe1+YKkJoFKvRxuQgGMWtxkRABIIkEHEHQfY+yMmntkVABIwSiLi9N8paEUKjuH1pTA6CL1hVqQiIQBgJRNxBkL0P46RUn0RABHwhEHF77wtTRQiNYjXamBwEo7jVmAiIQJAEIu4gyN4HOfnUtgiIgFECEbf3RlkrQmgUty+NyUHwBasqFQERCCOBiDsIsvdhnJTqkwiIgC8EIm7vfWGqCKFRrEYbk4NgFLcaEwERCJJAxB0E2fsgJ5/aFgERMEog4vbeKGtFCI3i9qUxOQi+YFWlIiACYSQQcQdB9j6Mk1J9EgER8IVAxO29L0wVITSK1WhjchCM4lZjIiACQRKIuIMgex/k5FPbIiACRglE3N4bZa0IoVHcvjQmB8EXrKpUBEQgjAQi7iDI3odxUqpPIiACvhCIuL33hakihEaxGm1MDoJR3GpMBEQgSAIRdxBk74OcfGpbBETAKIGI23ujrBUhNIrbl8bkIPiCVZWKgAiEkUDEHQTZ+zBOSvVJBETAFwIRt/e+MFWE0CjWlI19AcB5ABYCiAEYlaMuyUHIEUhVIwIiEH4CeeIgyN6HfyqphyIgAiEnkCf2PuQU0+ueIoTpccrFVf8PQBOAKQDeK0GYC6SqQwREIGoE8sRBkL2P2sTU84qACOScQJ7Y+5w/dxAVShCap345gOslCM2DV4siIAL5TyDPHATZ+/yfcnoCERCBgAjkmb0PiFJumpUgzA1HL7XIQfBCS9eKgAiIgItAnjkIsveavSIgAiKQIYE8s/cZPmU4bpMgND8O2ToIEwHwH6dUAXi4ubkZtbXcTqgiAiIgAiOXQJ45CLL3I3cq6slEQAR8JpBn9t5nGv5WL0GYHd9rAVw9TBXzAax2XZOtg/AVAF9OblOCMLuB1N0iIAL5QSBAB0H2Pj+miHopAiIwQggEaO9HCMH0H0OCMH1Wqa4cC2D0MFVssLOKOpdlKwgVIcxuzHS3CIhAHhMI0EGQvc/jeaOui4AI5B+BAO19/sHKsscShFkCzOD2bAVhcpM6diKDQdAtIiAC+UkgzxwE2fv8nGbqtQiIQAgI5Jm9DwGxzLsgQZg5O693TgPQAOACAFcBOMmuYB2ANq+Vua6XIMwCnm4VARHILwJ54iDI3ufXtFJvRUAEQkggT+x9CMl575IEoXdmmd5xI4DLUtx8KoAHM60UgARhFvB0qwiIQH4RyBMHQfY+v6aVeisCIhBCAnli70NIznuXJAi9MwvbHRKEYRsR9UcERMA3AhF3EGTvfZtZqlgERCBsBCJu740OhwShUdy+NCYHwResqlQERCCMBCLuIMjeh3FSqk8iIAK+EIi4vfeF6VCVShAaxe1LY3IQfMGqSkVABMJIIOIOgux9GCel+iQCIuALgYjbe1+YShAaxWq0MTkIRnGrMREQgSAJRNxBkL0PcvKpbREQAaMEIm7vjbJWhNAobl8ak4PgC1ZVKgIiEEYCEXcQZO/DOCnVJxEQAV8IRNze+8JUEUKjWI02JgfBKG41JgIiECSBiDsIsvdBTj61LQIiYJRAxO29UdaKEBrF7UtjchB8wapKRUAEwkgg4g6C7H0YJ6X6JAIi4AuBiNt7X5gqQmgUq9HG5CAYxa3GREAEgiQQcQdB9j7Iyae2RUAEjBKIuL03yloRQqO4fWlMDoIvWFWpCIhAGAlE3EGQvQ/jpFSfREAEfCEQcXvvC1NFCI1iNdqYHASjuNWYCIhAkAQi7iDI3gc5+dS2CIiAUQIRt/dGWStCaBS3L43JQfAFqyoVAREII4GIOwiy92GclOqTCIiALwQibu99YaoIoVGsRhuTg2AUtxoTAREIkkDEHQTZ+yAnn9oWAREwSiDi9t4oa0UIjeL2pTE5CL5gVaUiIAJhJBBxB0H2PoyTUn0SARHwhUDE7b0vTBUhNIrVaGNyEIziVmMiIAJBEoi4gyB7H+TkU9siIAJGCUTc3htlrQihUdy+NCYHwResqlQERCCMBCLuIMjeh3FSqk8iIAK+EIi4vfeFqSKERrEabUwOglHcakwERCBIAhF3EGTvg5x8alsERMAogYjbe6OsFSE0ituXxuQg+IJVlYqACISRQMQdBNn7ME5K9UkERMAXAhG3974wVYTQKFajjclBMIpbjYmACARJIOIOgux9kJNPbYuACBglEHF7b5S1IoRGcfvSmBwEX7CqUhEQgTASiLiDIHsfxkmpPomACPhCIOL23hemihAaxWq0MTkIRnGrMREQgSAJRNxBkL0PcvKpbREQAaMEIm7vjbJWhNAobl8ak4PgC1ZVKgIiEEYCEXcQZO/DOCnVJxEQAV8IRNze+8JUEUKjWI02JgfBKG41JgIiECSBiDsIsvdBTj61LQIiYJRAxO29UdaKEBrF7UtjchB8wapKRUAEwkgg4g6C7H0YJ6X6JAIi4AuBiNt7X5gqQmgUq9HG5CAYxa3GREAEgiQQcQdB9j7Iyae2RUAEjBKIuL03yloRQqO4fWlMDoIvWFWpCIhAGAlE3EGQvQ/jpFSfREAEfCEQcXvvC1NFCI1iNdqYHASjuNWYCIhAkAQi7iDI3gc5+dS2CIiAUQIRt/dGWStCaBS3L43JQfAFqyoVAREII4GIOwiy92GclOqTCIiALwQibu99YaoIoVGsRhuTg2AUtxoTAREIkkDEHQTZ+yAnn9oWAREwSiDi9t4oa0UIjeL2pTE5CL5gVaUiIAJhJBBxB0H2rmU8lQAAIABJREFUPoyTUn0SARHwhUDE7b0vTBUhNIrVaGNyEIziVmMiIAJBEoi4gyB7H+TkU9siIAJGCUTc3htlrQihUdy+NCYHwResqlQERCCMBCLuIMjeh3FSqk8iIAK+EIi4vfeFqSKERrEabUwOglHcakwERCBIAhF3EGTvg5x8alsERMAogYjbe6OsFSE0ituXxuQg+IJVlYqACISRQMQdBNn7ME5K9UkERMAXAhG3974wVYTQKFajjclBMIpbjYmACARJIOIOgux9kJNPbYuACBglEHF7b5S1IoRGcfvSmBwEX7CqUhEQgTASiLiDIHsfxkmpPomACPhCIOL23hemihAaxWq0MTkIRnGrMREQgSAJRNxBkL0PcvKpbREQAaMEIm7vjbJWhNAobl8ak4PgC1ZVKgIiEEYCEXcQZO/DOCnVJxEQAV8IRNze+8JUEUKjWI02JgfBKG41JgIiECSBiDsIsvdBTj61LQIiYJRAxO29UdaKEBrF7UtjchB8wapKRUAEwkgg4g6C7H0YJ6X6JAIi4AuBiNt7X5gqQmgUq9HG5CAYxa3GREAEgiQQcQdB9j7Iyae2RUAEjBKIuL03yloRQqO4fWlMDoIvWFWpCIhAGAlE3EGQvQ/jpFSfREAEfCEQcXvvC1NFCI1iNdqYHASjuNWYCIhAkAQi7iDI3gc5+dS2CIiAUQIRt/dGWStCaBS3L43JQfAFqyoVAREII4GIOwiy92GclOqTCIiALwQibu99YaoIoVGsRhuTg2AUtxoTAREIkkDEHQTZ+yAnn9oWAREwSiDi9t4oa0UIzeCeAeBLAE4DMAHADgC/B/B1ALEsuyAHIUuAul0ERCB/COSBgyB7nz/TST0VAREIMYE8sPchpuetaxKE3nhlevXZAC4B8CcA6wAcBeAXAG4C8OlMK7XvkyDMEqBuFwERyB8CeeAgyN7nz3RST0VABEJMIA/sfYjpeeuaBKE3Xrm8+ioAHwAwK8tKJQizBKjbRUAE8odAnjoIsvf5M8XUUxEQgZAQyFN7HxJ63rohQeiNVy6v/hoAfkk+1mOlEwHwH6dUAXi4ubkZtbXUhioiIAIiMHIJ5KmDIHs/cqeknkwERMAnAnlq732i4W+1EoT+8h2q9jkAVtjLRbl01Ev5CoAvJ98gQegFoa4VARHIVwJ56CDI3ufrZFO/RUAEAiWQh/Y+UF7ZNC5BmA094FoAVw9TxXwAq13XTAbwEIAHAbwvg+YVIcwAmm4RAREYGQQCdBBk70fGFNJTiIAI5AmBAO19nhDKXTclCLNjORbA6GGq2ODKJDrJFoJPALgcQCK75q27tYcwBxBVhQiIQH4QCNBByGt739ObAAoKUFyo135YZnpfXx9a27tQVlqMstKSsHRL/RCB0BAI0N6HhoGpjujNYIo0wMjgA/ZS0XcC6M1R0xkJQr6IntvWjHW7WzFnfA0WTKlDQYGmQ47GJKNqNCYZYdNNESOQJw5CaOx9vLcXL+/rQEd3L/r4BbG8CHPGVKNIwjDQX862nY34v1sexq59LSgpLsaxR03D5W88Ue/hQEdFjYeNQJ7Y+7Bhy6g/UgAZYfN8E50DLhHdDOCyJDG4y3Ntg2/wLAgpPH764Hqs39uG0uIixHp6MXtsNT5wymy9jLIcjExv15hkSk73RY1AHjgIobL3q/e0oq2rd8C209aMqiy2RKFKMAQ4Bp+//na0tHUOjEss3oPXn7oArz/lmGA6pVZFIIQE8sDeh5BaZl2SIMyMm9e7uDz0N0PclO0YeBaEz25twk2Pb7LEoFMoCi9dOgMLp47y+my6PgcENCY5gKgqIkEgDxyE0Nh7Co+ntzUDGPyaKSwEFk2ui8R8CeND7tzbjM9//2+oqiwb1L3J40bhc+8/J4xdVp9EIBACeWDvA+HiR6PZihE/+qQ6vRHwLAhvWb4VK7Y0HdTKkun1uGjJFG+t6+qcENCY5ASjKokAgYg7CJ7sPQXhs9tbkOBaUVfhPsIFk3VMUVA/lwPN7fjMd29FedK+wRmTR+PT7z4zqG6pXREIHYGI23uj4yFBaBS3L415chDYg6GiUe9aOgMLFCH0ZZCGq1RjMhwh/b0I9BOIuIPg2d5vOtCBvW0xFNp7xBN9fZhYW4Ypoyo0pQIkcN2v78b6rXtRVFRo9SIe78UVl7wWi4+YFmCv1LQIhItAxO290cGQIDSK25fGPDsI2q/myzhkVanGJCt8ujlCBCLuIGRk77c3d6GpM27NktFVpZhQU6b94gH/Zrpjcfzp38uwfstelJWX4Iyl83HCMTMD7pWaF4FwEYi4vTc6GBKERnH70phnB4G9GMhouacNc8ZVK8uoL0PjrVKNiTdeujqaBCLuIGRk76M5U/TUIiAC+U4g4vbe6PBJEBrF7UtjchB8wapKRUAEwkgg4g6C7H0YJ6X6JAIi4AuBiNt7X5gOVakEoVHcvjQmB8EXrKpUBEQgjAQi7iDI3odxUqpPIiACvhCIuL33hakEoVGsRhuTg2AUtxoTAREIkkDEHQTZ+yAnn9oeINDW0Y09+1swadwolJeViIwI+EIg4vbeF6YShEaxGm1MDoJR3GosFYGB/Y+7WzFnfI32pGqa+EYg4g6C7L1vM0sVp0vgL3csw0PL16K9M4aaqnKcd/LROOeko9K9XdeJQNoEIm7v0+aUiwu1ZDQXFIOtQw5CsPwj37oypEZ+ChgFEHEHQfbe6GxTY8kEXlq/E9f95h5UlL8SFeyO9eDrH3sDxo3W2ZaaMbklEHF7n1uYw9QmQWgUty+NyUHwBasqTZfAUGcoXrp0BhbqXMt0Meq6NAlE3EHIyN73Jvqwrz0GvvDHVJWisFCv/jSnmy5LIvDr2x7DilWbBx1bkkj04fSl8/GmMxaJlwjklEDE7X1OWQ5Xmd4KwxEK/99n5CBoiV/4BzZfenjL8q1YsaXpoO4umV6Pi5ZMyZfHUD/zhEDEHQTP9r65K451+9qRSPC4IaC4CDh8XDWqSovzZMTVTTeBru44Hn16nTWWJy2ZY3z/3t/ufQb/eWwViouKBroVi/XgsguX4tWL5miwRCCnBCJu73PKcrjKJAiHIxT+v/fsIGiJX/gH1UsPgxb3Q0UI37V0BhYoQuhlKHVtGgQi7iB4tvcrd7agu6dvgCztRWVpEY6YUJMGbV0SJgLrtuzBD266HzzUnqWstAQfu/Q0zJk2zlg3Ozpj+MIPbkcs3mNFCROJBEbVVOKaj74BRUWFxvqhhqJBIOL23uggSxAaxe1LY54dBC3x82UcAqk0DOI+DH0IBL4aDYRAxB0ET/aev80V25pRYC0WfaVwxeiiKXWBjJ8azZzANT/7N3bvaxlUwfgxtfjSledlXmkGdx5obsOtdz+DfY3tmDSuFhedtQRVFWUZ1KRbRODQBCJu741ODwlCo7h9acyTg8AecInf8s2N2N8eQ0tnHLUVJRhdVYpjZzRoiZ8vQ+RfpWER9wNRyj1tmDOuOusso/zqfMuKbVixuRHO0tPCQn199m8m5U/NEXcQPNv7Z7c3obWzF62xXksWVpcVob6yBEdNVAKQ/Jn1/T39yNf/ZC0VTS43fPFt+fYog/r75HMb8PWf34n9TW0YU1+DL1xxDo4/ZmZeP5M6nxsCEbf3uYGYZi0ShGmCCvFlnh2EZ7Y04gu3vYDGjhh6EkBxIVBfWYpvvOloLJxWH+JHVdeSCYzE/XsUg5f/Zhk27WtHSXER4j29mDGmCje++zhIFOo3EHEHwbO9X7GtCVsbOweEREEBcNiYShw5URHCfPs1femH/0BjS/ugbtfX9i/XzNey50ALzvqfHyDR24eCwgL0JfpQVFiIu3/1cYypr87Xx1K/c0Qg4vY+RxTTq0aCMD1OYb7Ks4Pw9OYDuPKmp9Ee70FRQQF6+/pQVVKMn126GIunN4T5WdW3JAIjcf/eX5dtwQ33r7PEoFMoCj982hy85bhpmgMRJxBxB8GTvWfk/r61+xBP9IGZRlmKCoCykiKcdtiYiM+k/Hv8ZSs34Zc3P4pifsUF0NOTwHsvejWOPzp/o2mfv/5v+OcDzw/af9jbk8CFpy/CVz96Qf4NknqcUwIRt/c5ZTlcZRKEwxEK/997chD4ON/9z2r86/mdiPf2IdabQGlRIUqKCnD+gkn41JmHh/+J1cMBAiNx/97VtzyH5ZsPzlp63Ix6XPvmYzT6EScQcQfBk71ntP3uNfsGHRHA6VOAPpw5z1wikohP2Zw+/o49Tbjnvy9adZ5x4hGYNG5UTus3XdlHv/5nPLhs7aCjUHiMxWknHI7rP3eJ6e6ovZARiLi9NzoaEoRGcfvSmCcHgT343j1r8M/ndqCw4JU9WYm+BC5YMAmfOEOC0JdR8rHSXO/f87GraVU9VITwI6cdhouPm5pWHbpo5BKIuIPg2d4/8PI+dHNvgPO27wMqSwvx2tmKEI7cX0n+PNmL67bj4k/+YtCKEEY+b/vBFZg7c0L+PIh66guBiNt7X5gOVakEoVHcvjTm2UGw9hD+bSWarD2EfSguLMAo7iG88CjtIfRliFSpFwLaQ+iFVvSujbiD4Nneb2vqwDPbWixbz1JSVIjjp9ZiXG1F9CaPnjiUBH78hwfwu38+gfaOblRXlePS178KH3r7KaHsqzpllkDE7b1R2FEUhCUAPgyAm5HuBHC3i/i3AFxtdASyb8yzg0CH+7JfP4W1e9qsRANMMjB3XDV++57jlbQj+/FQDTkg4GQZfXpLExZPG2Vlv1VCmRyAHQFVRNxB8Gzvaef3t3Wjo6fPChJWlBRifG0ZZo2uGgGzQY8wUgj09PRgb2MbxtZXo7i4eKQ8lp4jSwIRt/dZ0vN2exQF4S8BVAJYDuByAPcB+ISN7WkAi70hDPxqzw4CE5H87r8b0drdi9bOOGoqSlBTVoR3nTgTC3WQeOADqg6IgAgMTSDiDoIne8/l5E9va7Z2DboLzw9fOFlZRvU7EwERCDeBiNt7o4MTRUH4HIAFNuVyADcyWReAy2yRuMjoCGTfmCcHgc2NxKMKsseoGkRABPKBQMQdBE/2noLwme0tB51dx20CCybrHMJ8mO/qowhEmUDE7b3RoY+iIHwJwHwXZTL4MYApAGYDONLoCGTfmCcHgc2NxKMKsseoGkRABPKBQMQdBM/2fuP+duxvjw9kGk309WFCTRmm1msPYT7Md/VRBKJMIOL23ujQR1EQ3gHgGwAeTSL9bQCf4jFNRkcg+8Y8Owgj8aiC7DGqBhEQgXwgEHEHISN7v6WpE82dXAgDNFSWYHJd+UFHUeTD2KuPIiAC0SIQcXtvdLCjIghfZ+8VtN6HAJhurTEF6SMA9B/wkz/Fs4PARxtpRxXkz3CppyIgAtkQiLiDkJG9z4a37hUBERCBoAhE3N4bxR4VQRgDsA7AjwD8DkC7Ucr+NiYHwV++ql0ERCBEBCLuIMjeh2guqivRIxCP9+K5NVtRVlqCI+dMVPZrn6dAxO29z3QHVx8VQcjTTd8P4H0A+EJlIhnuG3zZKG1/GpOD4A9X1SoCwxIYiLTvbsWc8TVYMKVOS/GGpZbdBRF3EDK29z29PJy+wDp3VkUERMA7gbUbd+Enf34Ibe1d4CEuYxuq8Zn3nomGumrvlemOtAhE3N6nxShXF0XtzVAI4AIAVwI4HcC9dtTw37kCGkA9GTkIcmQDGCk1mRGBsM5V7cXNaDizviniDoJnex/v6cXL+zrQ0tVjHT5RV1mMw8ZUo0jCMOu5qApyTyAW78Fdj67Ctt2NmDahAWe9+kiUlASf2oH2/n9/9A80tnQMPDT/7LDp4/Hxd3FXkoofBCJu7/1AOmSdUROEbhA8eoKH0F8EYAuAOUbJ564xzw4CjdhPHliHZZsPoDOWQEVpIY6b3oAPnjpH0Y3cjYtqygGBMIuuobL1Xrp0hs7zzMHYD1VFxB0Ez/Z+5c5m7GyOobePW+dhRQin1Zdj7rgaH0dJVYuAdwI9Pb245md3YNe+ZpQUF4HicPK4UfjileehiIdnBlg6u2L4+Df/epA4raooxbc+9eYAezaym464vTc6uFERhHcDGOX6hyfyFtun9fItyT2F+Xook2cH4Zktjfji317AgY44ehN91pdiZp772oVHY9G0eqMTUI2JwKEIhFl06TzPYOZuxB0ET/aeH1TuW7sXnfGElUmNhS/9qrJinHbYmGAGMGKtUtQUcqlucfBRrmT0Xd1xrFq3A2NGVWP65NGBj8xDy9bi9/94AmVlJQN96e6O47ILT8RrFgf7zT6RSODT37kFsXjvIE4Txtbhi1ecGzi7kdqBiNt7o8MaFUHIfNsUfT8FcDuAFtc/rXbWUaPgc9iYJweB7V5310v4/ZNbEOvtA8+k4suqtKgA73zVdHz6rHk57JqqchMI69JHp49h7F+YRZfO8wzm9x1xB8GTvacTe8eLexBP9A0ShGXFhTj3iPHBDGBEWm1u7cBP//IwNm/fb0W3Fs2bine/6cTQJCF5/Nn1+P0/nwRFYUFBAebOGIdPvOuMQJdn3vT3J/DE8xsGrVTie+nERbPxjvNPCHzm/OuhF/D3+55FWWmxlamd+3KvfMtrseiIaYH3baR2IOL23uiwRkUQTgXwEQDvAbDD3jf4ewCdRmn705gnB4Fd+MzNz+L2Z3cMOAjOV+M3LpyEb1+80J9eRrzWMC995NCEtX9hFl1hZTbSf2oRdxA82XsKwn+u2o0e5pOxJwYjhWVFBTj/KOZaU/GLwDd+fge272kaEDfxeA9e96r5eMs5x/rVZNr1Mmp51XW3opeJhuzCvaZnLJ2Pi85aknY9ub5w5cvbcf3v7kO5K0LY2R3HZ95zBg6fOTHXzWVU37Ort+Kxp9ejuKgQZ7/myFBEVjN6kDy5KeL23ugoRUUQOlArAFwK4MMAJgP4NYAbAGw2Sj23jXlyENj0VTc/i79TENIz4Azos5LPQYIwtwPjri3MSx/Zz7D2L+yiS+d5+vebGarmiDsInux9f4RwN2Jc5eZShOUlBTj3CAlCv2Zve2c3PnntzQdF2+prK3HNR9/gV7Np17tu825rr15NVfmge6ZOrMfV7z077XpyfSHt6a9ufQxPPLfBiqr2JhJYumA23vOmE5XfINew86S+iNt7o6MUNUHohnsqgI8COAfAnQAuNEo+d415chDYrLNktLunf18JJwGXEF26dDo+daaWjOZuaF6pKcxLH9nLMPdPosuPGZm/dUbcQfBk7609hGv2orMngYS9iZC5OarLinHKHO0h9OtXwGWYn7j2rwclQhnbUIMvXXkulq/ajPWb92LxkVMxd8YE42KHmTKv/u5tKHVl7+RcOXLOZHzwbSf7hSXterftOoDVG3Zh/uyJmDxeeQ3SBjcCL4y4vTc6olERhLcA4EExyf8wzRqjhnxVhm/Hd3pTwZODwCqZVOYLt72Axo6YtZSouBCoryzFN950NBYqqUx61D1edailj8dMqcNz25qxLsCz7MK8NNMjal0+wglE3EHwbO9X7mzBrpZu9NiKsKSoAJPqyjF/vLKM+vlTueEPD2Dluu0oLup3LbpjPbjw9IV49qWt2Lh9vyXGumI9OOGYmXj/xSf52ZWUdf/0zw/hmRe3oNTeD8cVQ1+84hxMkgAzPhZqcGgCEbf3RqdGVAThzQCahvlnlVHyuWvMs4PgPnaiK5ZAuY6dyN1oDFHTUEsfrzx5Fn720Aas39uGUqbZ7unF7LHV+MAps41+NQ770kzfB0gN5A2BiDsInu19V7wXa/a2oyPWAyburyotxtxxVZa9UfGPQDzeiz/860kr0lVSWowTF85CSVEh/nrXCkuEOYXRxC9ccS5mTjEbseVy4vufWI1V63eiqqIMF5x6DMaNztdk6/6No2oOlkDE7b1R+FERhEahGm7Ms4PA/mkZnuFRGoI5I4M3Pb5pkHNGURjEWXaaE+bnhFr0TiDiDkLG9r6lM25tFq8tLzb6scn7CI/cO/7v5kfw/Jptgx6Qwuzsk47CBafyaOTsCvcuMlFMbTUXPqmIQP4TiLi9NzqAEoRGcfvSWMYOQtDLFH2hkWeV+rl3L4zHSOTZ8ATeXY3hwUMQcQfBs73nB6Z1+zrQHutBAQpQXVaEw8ZWW+fPqpglcNejq3Db3U8PjhDGevDZ952FOdPGZdyZ7lgcP/nTQ1i7aRd6evswbWIDPvKOUzGqtjLjOnWjeQKMJv/zwefQ2t6NKePr8Y7XH29Fb6NcIm7vjQ693ghGcfvSmGcHwVoy+uB6LN90AJ2xXlSUFuHYGQ34oOFlir7QyLNK/dq758cSUIkTs5PLjzE0+wT+tBZxB8GzvV+9pxXNHXF09TCdNFBeVIDR1aWYM4Zb6lVMEuAy0m/84g5s29loHb7eFYtj0bxp+NDbT8mqG7+65VEsW7XZOgqBhbZj6oR6fPZ/mDMvs/LYM+vxxLPrrZtfs2QOTjhmVmYV6a60CDCRztd+fufAGCYSfRg9qgpf/cgFkY7oR9zepzV3cnWRBGGuSAZXj2cHgUllvvi3leiI96CwoBCJvgQqS4rxtQuPwiIllTE6kn45/bk+RsKvfhqFnWeN5XoM8+zxh+xuxB0ET/aev9v/bmpEa1fPKwfTFwD1FSU4YbqyNwbxm+jp6cWjT6/D5p0HcMzcyVg4b2rWDv/V370V7Z2xQY/DpaM/+PwlKC15Zb9ius/774dfwO339h/AzhKL9+KiMxfjzFcfkW4Vus4jgZ//5WE8v3bboLnQ0RXDZ957FubNjO4RMRG39x5nUXaXSxBmxy8Md3tyENjh792zBv94dgfivX2I9yasje7MPHfBwkn45BmHh+GZItWHXO7dc+r605ObcaAjjtFVpYNeMEum1+OiJVM885U48Yws6xv8XE6cdecCrCDiDoIne097cM+aPVZ00Dl2gitFK0uLcPrcsQGOoppOJsDD4lvbu9BQV5W2QDzQ3Ibf3v4Ebv7PCiTsqOB4OzFMQUEBrv/sWw46+iId8p+57lZQjLgLzyz85ify9XSudJ462Gt+9PsHsGbTrkGd6OyK4QNvPRnHHjUj2M4F2HrE7b1R8hKERnH70pgnB4E96D+HcCt6E33WgfRMN839JJcunaZzCH0ZIu+VZrI80x3FY0Rg9c4W1FeVYv7EWsvB4F6idy2dgQVTR3nukMSJZ2RZ3+DXcuKsOxZwBRF3EDzZe9qEO17cA545637Zl5cW4Zz5me9ZC3gKjKjmOUZ/vXM5HnlmHbq64hgzqhrvvOAEHHXY5EM+J+/7/PW3o6WtE9t2N2Hj1n3WkmBGHbnv7MRFs3DZG0/MiNWHrvnjQaKUB8X/4HOXZFSfbhqewJPPb8Qvbn4E5WUlAxcXFhbguqsuyijKO3yL+XFFxO290UGSIDSK25fGPDkI7MFfntqMr//7JStC6BxMzwjhF86bj0uOn+5LJ1Vp+gQyXZ45WED04cUdLWhsj+HwibVWZsFsjrOQOEl//HJ1ZabzIFfth7WeiDsInuw959CdL+1Cdw/Q6xxMXwBUlRTgzPnRXYYW9NxmJLC5rRMTx9Rh2Qub8KvbHkVZ6StCoKiwEN+56s2HFAKrN+7Cd371H1SUl1qPs313I3bubcGY+iq8982vwRtOW4DCwv49hV7Lt355F7bsPDAgCjmPZk0di09dfobXqnR9mgRSfRh4++tPsAR+lEvE7b3RoZcgNIf7HwAWAuBn2UYA9wK4GsCOLLvgyUFgWzcv24Lv/Gc1DrTHrWVEXELUUFWCq86ah4uPm5Zld3S7VwJMO37Lim1YsbkRXNI5Z1w1/vDkFs9HURwcxevD/rYYGqpK8dbjp2HBlLq0lyIlP4PEiddRzc31uVxOnJseBV9LnjgIobD3nD//Wb0HbbHEoIEbVVaE0+cpQmh6NnM8fnTT/eAeve54D+bPnojaynK0Jy3PTGep4Atrt+P7v70XlRX9gtApc2eMx0ffeVpWj7a/qQ3f++292LG7yTqqZMr4UZYYVNbSrLCmdTMzxrZ1dHtaOpxWxXl6UZ7Y+zylO7jbEoTmhvETAB4HsBMAP/lcZzed2ZqOV/rtWRAyQvilv69CzPlkDKC0qADXvOFIRQjNzQerJYrBy3+zDJv2taOkuAjxnl6UlxZiybQG60XsLsPt//M7iidxYnhyqLmUBPLEQQiFvedv9t+rdqGrdzDKqtICnKMIofFf2K9vfQzf++09A/v6OD7lZaVYfMRUFBcVgZkluZeQCWE++/6zcfiMoaO4vObq796Gzu7YwIe+7lgPrrzktVhyZPYrfdi3bbsbrbonjxuV8cdE45DV4IgikCf2fkQwlyAMbhgvAHA7AB4yE8+iG54F4af+8gxufebgwORFiybhuksWZdEV3eqVwF+XbcEN96+zxKBT2rpimFxficMn1FgRPh4ozaNBPva6w7DwEFlgcxnFy2QPo9dn1/UikAmBPHUQArH3/OD0txd2D2QYdXjT2ly4YGIm+HVPFgTOvfJH2LGnaVANzDp6xOxJ1sfAzTv2W4KwrroCX/v4G3Hq8YdO8sbrb7z9cezc04zqylKcesI8nHfy0Z57+MiKl/HoinWI9ySwYN4UXHDqMRKAninqBj8I5Km99wOF73VKEPqOOGUDDQB+akcKX5NlFzwLwrOvfwird7Ud1Oz8CdW48+MnZ9kd3e6FwNW3PIflmwc7CBRjPDy6NwHraBB6c5WlxTj36An44KlzDvmizkUUL5fC0gsLXSsC6RDIQwchMHvf29uLv63ckxLrRRKE6Uy3nF5z+nu/j30H2qzkL07p6UngS1eei+tvuheJBFBVWYbDpo+zzhL82kffgLENNVbEkEldGK1LVXi+YXHx0H9/qIe474nV+POdy1BmH09BQfrqxXNw2RuWHvLZ2eau/S2or61EdWW0D0/P6SRRZYMI5KG9z9sRlCA0O3TfAvBhAJUAngBwPoD9HrvAz7ruT7tVAB5ubm6s9+JfAAAgAElEQVRGbS214fDlrO8/iDW72w+6cN74Ktz1iewOyB2+dV3hJpAqQsgvxa9fMBGrdragK5ZATUWJdXwEjwh556umW07But2tmDO+Jqt9gUONRCZHTHiNKHq9XrNGBBwCeeQgBG7vJQjD9bv57Hdvw52PrkQBFaGV4bsPY+pr8N43nQgeBO8WfDxGYvrEBusoin2N7Wioq8QbT1+I44+emfKheLD58lVbMHf6OGtv4lDiMfnmL9/wD+xvGuwPFBYU4HtXX4xi18oV932PPbMON9+1Ak0tHVZSm6ULZ+PSC04Ysk0+J7Norlq3AxPH1uH0pfMjnTkzXLMy3L3JI3sfbpBp9E6CMA1Ih7jkWjsxzKFqmQ9gtX3BGAD8WswF/l8G0GyLQjv/W1qd+Yp976CLvQjCk77xH2xt6Tmosal1xXjkc2el1QldlBsCqfYQzhhThfOPnoBntrUkNdKH5o4YKkqLrYQzPEZiqMyh2Qgur0dMeI0oer0+N6SzqyUbntm1rLuTCQToIOSdvY/H4/j7i/tSTiJFCM3/ttZt2YNrfvpvrN+6F/F4AmVlxbjmI69HU2sn7nx45SAB1t7Rjb0HWjFjCt2G/sKPhV//2Bsxpr56UOd//88n8OCytf3vhXgvDp8xHp+8/Iy0ziCkSG3r7B5UH5exXv+5SwYdgeBc0NEZw6e/c/OgDKZdsR5L1FIYpio3/PEBPLd6q5VJlRHI0aOq8eUPnp+yfvOjcnCL7Osdj6wEx2D6pNF4x/knHJS8Jwz9jEIfArT3UcA76BklCLMbcp7sO3qYKjYAGHzCa/8NPB18KwAmlWGymXRL1hHCxV+5CweSswxQqZYX4emvnJ1uP3Rdjgg4WUbvfnE36itK8LYTpllfWn//xOZBmUZ3NXeC60cn1DHA3F8oCi9dOgMLXWcLZiu4vCan8RpR9Hp9jjBnXE22PDNuWDemJBCgg5B39r6npwe3r9qbkqMEYTA/MAqq3/79cdzz2IuWyOA/jOht3LrXPhu4wIoc8tgHRtNK7aWc7C2Tzpy05DC87bzjBjrPTKD/e8M/Bomr7u443n7+8daewuHKL255BE+v2jIo0Q3b/eKV56W8lfsNf/f3J1BWWjzo7+fPmoAPvf3Ug+7ZtG0/vvbzfw/qHwXnWa85EheeHr6cBWs37cZ3b7xnYF8/388TxtThSx84L+2o63DM9ffpEwjQ3qffyRFypQRhcAPJ8x02A6AFfTCLbnjeQ/jmHz+CFVuTo0/Akml1uPWD2W5pzOJJInprKsExa0yVlWV0w962gWhgR6wHdRWlB72UkrOPZiu4vAogrxFFr9cHPS2y5Rl0/0da+3nqIARi7/lbvu35XQclleHpdG/SHsJAfhrcD3jVdbdakTKnxOM9WLpoNppbOrGvqc2KAPKIh8ef3YDiolfOEuxNJHD6q+bjzWcuHrj3Xw8+j38/9MJB0cCj507GFW957bDPyGMObvjDA1izabclSJlR9GOXnmZF8VKVl9bvwHU33osK1wHqXN56wtEzcNkbD06afs9/X8Qtdz89KHEa6z1yziR84K3hy1nAaOZL63cOes92dMXw/z50PqZOHO77/7C4dYFHAnlq7z0+ZTgulyA0Mw4nAOAnvUftMwi5ruIaAONpFwEMXq/hrU+eBeGfntiEz92+6qBWvnnhkXjbCTO8ta6rsyYwlOAY2C+4p806m5DOXXLUkBHCdy2dgQWuCGEuBJeX5DS5iigmP0fWYHNUQS545qgrqgZAHjgIobH31rETK3eha/AxhKgpBs46UllGg/hBbdq+D1+54V+orhqciGXqhHpc/b5XVui0d3bj6utuG5SAhhHCaz95IWqrKwa6vmYTD6i/e1AEjktLmW30glMXpP2ILW2d1pJUCsFd+5rx4FNrUVVRhte9at6g5ZKcU1/9yb+wa1+LJUL53yxf/cgFKUUk6/rSD/9uLRd1Co/HoKg9+zV0f8JVvn/jvVi/bXBUvaOzG1e95ywrkqtilkAe2HuzQHxsTYLQR7iuqpkH+gcAaJ2ZBIZnEd4F4GsAtmfZBc+C8M9PbMTnb38Rbh+B3yC/8cYj8NZXpd6wnmUfdfshCPx/9q4CPKpr6664uxNiBIK7O8XqLUXq7i6vRvXV21fX1/a1/WtUoECBIm2BFivuLklIQkLc3f9v7TDDTDLJzB1Lwsz53vveI3PvkX3OPfesu/dey1DAYajnri2ANqCrH/alFysipdGXP2dov1QmUHp9ey8epYC3vft7rrffCQ4IHWa/57O2aH9WiyVh9xC231NC0fe57y7WAkicp55x4S0E5ZlzSPIWeg0J1GZPG4yEOG1tQt77/ndrhbDF3a0pR49ENf++92I4Ojji938OIe10PrqE+uPC8f305u0xF/HH5dskn7GhvgGuri546vbzERHqrzZaVXWt9Cstq0AkMq6YMgiR4QGtGvWH5dvw97ZjcHV1lv7Fdw3B47dOb5W0pv1mB1i/4xjmLd+uZl1lXxge++ajswzKyWzPvp+LbXeC/f6cMbsdEHb+qVQMCG/5v634+3hLctPzEoLw9a2jOr9FOtkIlAAOQzx3rQGuuyd2w2frk5GkEYbaGimNUvBmSL80p0Xp9e05pZ0NwLanrazRto0fEBTt9/YcQmusSOVtvPftGhw9maUOo2QY6WO3TkN8VKjyyiS3sAGb9yZLqCOB39TRvaTuVz9bhVPZBZKHyLy9QH9vvHjfpXBxOat7q9kg+/HEO4uE2ZR6iU5OTogI9hWw+shNU43qm+qmU5kF2HEwFd26BovWoaEsqCY1asTN3O/nr9oprK8EvpT9uOWKMSIFYi/Wt4CN7/dWNbgdEFrV3BZpTNEBgT0Y+vIfyC9vyTIa5OWMXc/ZWUYtMkttVGoJwKELcNEz+P2WFC2iGl2kNJpg8Jedp/DzjjQ4OzqKdJavpyt83Jxw45g4LSIba9vM2u11JgBrbdtYuz0bPyAo2u9ramqw7IhuZSM7qYy1V+7Z9gjOlqzdi+OpOfB0d8FFE/ojIZYZJOYr2w+cxBe/bNIif2Gu4szpQ3D+2JahmvuOpeOnFTuwaPUuVFTWwtfLTYAjQeH4od3x4dNXm69znaAmejKZO0gPaEcFr53AjCZ30cb3e5Ptp6QCOyBUYq2Oea2iAwKHMPLVP5FdWttiNOG+rtj69LSOOcpzvFfWAByGhqbS1CqQuuZIFlLyKlFdVw83Fyf4ujvDz8NF9BDnDIs6x2fFPryOaAEbPyAo2u/tOoQdcQVbp0/zV+3Ahp0nWpKQ9YnBLTO1yV8Kisvx9HtLyGOGZX/vE3IZNDYiNMhXPgRGhPrh1plj4efjgUnDE7TCXa0zGnsrtmoBG9/vrTrtdkBoVXNbpDFFBwT24MF527HsYEsq8hn9Q/D+dSMs0kl7paZbQF8un74WlISmqq49VVCBQ5klcHIgFTrg6+ECJ4dGXDawC2KDvdE9zAcDu/rZv6DqM34n/d3UNWeJYdv4AUHRft9aDiHnxe4htMTqNE+dtbX12LQnEZt2nhCNwMiwANx0+Sj4+ZyVHNLX0sn0PLzy2Up4uJ8lc6msrsUD107CoN4kvT1bfl7ZBB7JFrp2yxGUlFfJjySVcXFylNy/8cN6SNipt6c75t5+AUKDfPR1weK/c32nZxfC2ckJ4cG+NvEeYhh4cno+uoYFmF0bkfO7ZutRkPgoOiIQ00b3aTW82OKTe6YBG9/vrWVmaccOCK1qbos0puiAwB5c8fEG7EkvbdGZwVG++PW+8RbppL1S4y3Alx4B2v82JKGqtgHhfu6oqWtoVZS+tZaUhKaqvInJuaU4kVOO2voG2SxcnR0lfDQywA0JYX6ig6gvD9H4kSu7syOCF2UjUH61SsNyV2ohVPIjjo5naeqV13j2DiXrxZR2lN5r4wcERfu9XZhe6epq/+sXr96NpWv3YeehVHi4u6J7dAiC/L0EDL760OXSwV2H0kB20T7xERjUK6pVIETB+vU76CUUhx+G94/FHbPHtbj+pxXbsXFXoly3bf9JUGieouwhAd6orWuAp4cLBp8BkdwXenWLwAPXtdQctKb1cvJL8d53a5CZVwxHBwdEhwfiXzdP1WJgtWZ/rNHWN4v/wafzNwhgp+zHBRP64rWHrjBL03yXvPr5KjDXU0X+w3zUZ++6qF3Jf2x8vzfL3BpaiR0QGmqpjnudogMCh9HrmRXQoUsPdyfg6Ku6xWgNHb4tHsoNtY0x16kO5dtT8pGaVyGfcHzdXdCni6+AQorS00NnKHOoZmhqfAgJb4Ekylo08/SpPIQlVXXCSFpb34iqunqE+bijtKoGPSP8EOzdRJveVh6iMWM25p6OAF4stfZbq5cv8Ju/3oGUvHIhkCBlfGywF765ZTjMAQo7qv6ijR8QFO331dXV+O1ogc5Hyhwewn1H0/H39mNgaCrBBkXT7flW+ncwkrfkF5fDz9tdK/xy75E0fDhvHQ4nZ6CsvFp9EB81sBuY//fYLdOwYv1BHDuZBTc3F1TV1KJvfBc8fOOUVu2enV+Mw4mZAiwPJmaBOoIEmpdOHICuEU3MoGQ+feb9JdLe6dxiJKbmyN8H9uyKPUfSMKh3FPw1vJNBfl548YHL9A/Ugle8+vlKIb5RrTd6N3vpYGq1YBew9+gp0YokC+nFE/shLMjPpOa41zO3dPuBFNTVN6B3t3DccOko8dJR5mP67e9p7e30JP/n0Zm4ZNIAk9rlzVv2JuGrRf9osdBWV9fi+stGYeLwBJPrN7YCG9/vjTWbUffZAaFRZutQNyk6ILDnPZ9Zger6lmMwFRB2hEN5h5oZAzvTFpDYk1aID9YeR1p+JaprG+Dm4ohGNKJHqA+CvN0wNNofOaXViphD2S19c6X6PTGnFEm55Sgsr0GAlyucnRxQV9+I3hHa4Tkq75SBQzb7Ze0NXvTZ09gBt1UvCX8+/itRS/CZoPD+yd1x5XDtkDBj2leSc2pM/cbeY+MHBEX7PT8aLD6QbRFA+M+eRHy3ZKs6pIzacheO74uZ086Kphs7x+fyfVv3JYtkQ2FppXjeJg1LwOzzh8qQCcpWbTqI7LwSAQQEGr5eHugZFybgcfKoXli//QTc3JzVJmotDLS5DT+bvwG7D6WK94f7CjUN595xAWK6NImt7zmchl/X7hWgynzxkAAfCRvcuPuEhGSqCu8lAc5DN0xpt2kioH7g1Z9afPiivd55Yo5V+kXgtnz9fri7uqjtSSZWU8iBmL+5Yt1+uLg0zS9DOPsndMV9107Ca/9biR+Xb9fy1jU2NIqH+Ns3bjF5zD8t3y5hys0/6IzoH4sbLx9tcv3GVmDj+72xZjPqPjsgNMpsHeomRQcE9nz866txqrimxSCi/V2xYa7xpDLtfSjvULNiYGfaOvCzint/2IWjmaWoqW9EUUUN3Jyd4O/pglBfN0T6e2BkXBC2ncw3mDlU1S1D5koFVE9kl8oLj2E5/Aq7NTlfS6OJHsL2FpVvb/BiiD0NXBJal7VV70/bUrEztahFtcNjA/DGLNO/GCvJOTVmbMbeY+MHBEX7vSVJZV745DfkFZZpTaOzsyPefWKOWTzUxq6PjnwfxeYff2uhln0obfDg9ZPRu1sELrn3YwGDlTW1KCqpkKGQhXTkgG7oEuqHfj0isftwWoshjh0Uj2suaT3/v6i0Ak+8vUjkJzSBnS7tw+aV//HPISz8Y5fcW9/QIP/71O0XaOkSWtvmfB899tZC8COEZvH39cQrDzaF1Vqy0DP36Fu/CKjWLATX1Fc0tjz34VIUnpl39Tw1NOL9p67C979txdtfr4arhmQI2x83OB7//fd1xjapvo+SJe98s1rLQ8iPDQ9eN1lkQtqr2Ph+b1Wz2wGhVc1tkcYUHRDYg1u+2oK/T7QMIzqvRyC+vs34L0HtfSi3iHUtXGlbB342/cGa40jJLxcwVlhRi+raemH67BXhi+GxgQjxdsXuU8UteqnPY8e5+vNwNkpIL+7hgiBvV0kp1nefpTxhppq5vcGLpdZ+W/XS+6PLQ/jA5B6YM9x0BtiOOtc2fkBQtN9b0kNIYMMDo2ahh/qjZ67WAh6mPtvnwv1lFdUSlslwzcVr9rawT/+ESEwe2RMEBEeSs8RLQy3AisoaiQC4acZo+W9uQSn+b/FmLSkJho3ed80kdY6fLnut3HAABPD09AX6eSGmS6C0ERkagKfuvECvidOzCkDBehLKTBvTW8hm2rvQQ7di/QG1LWpq6gQUnzeip8W7RtD2+NuL4O56FmCzUX8fD7zy0Ayj23/6/V9RUtZE6KMqBH3vzZ0DBzhg4s3voKKiGg6OTUd35oUu/vAuo/UrNduprKrBd8u2YseBFPFC0js5tG8M7r5qQruGgdv4fm/0WjLmRjsgNMZqHeseRQcEdv3m/9uKdTqE6SclBOEbE4TpWwU3o2LAbHXmotlZKZvCNVU5f2mFFcgtrdbid+LvIT5uyCmpEhCYVVKF0qpaAYUVNfUCAl+8vJ/oALamLdiWx471P7fkIDYcz5XDRkNjg+Qlxod64abRcRgY5d/mCtfMQ+we6q1mGbUkwYm+R669wYulAGlb9faP9LVIDqHm+owP9RbTM2xYc671zYclf7fxA4Ki/Z4ewiUHc6DtxwBIOzRzYIRJ0/ThvL9wNDkLjurDaZNMwe0zx+LPzUdkX5kysjdiuzaFJNpi4bOkImzhgZtkLTzwd4sKVpuD4Y+hgT7w9nLDyg0HERbki4ycIhDgkCH0/HF98dQdF8r13GPpJTqRkiNho8zxIsELyVRay91U6RHuOpwqHi3+l+0xp3DyyF648sJhRk1NZk4RHvnPAqRlFsLL0w3XXzoSN1kxtJC23bDzOLbtT4GTkwMmDE2QPFZrFLY9991fQY+vqvBvfbp3EXBubPlp5Xas23ZMHTLKuerWNRiPnfE6nsrMx5PvLsHpnELJ6Xzs1mkYN6SHsc3JfVl5xfjil43IyC6SfNb4qGDER4dKbmpHeHZtfL83aW6V3mwHhEot1vGuV3RAYPdv+2a7gIHahrODcXEEJvYMwZc3GS87oetQ3i3EWz5jJeeVS1hjR2KlbI+pbG6jzOIK5JbUYEAUk9Ep7dCIA+nFEhLq7OSIY5kl8PdyRbivO0qqauHh4oSHpvTAoOgmMgBjgBBBxnebT8ohnx5CEpDwyz7n/6XL+0m9hpLUqGxoaYITQ+aqNaBqyL2mXmPMPBjSpr56VSB8d1oRhkT7Y/bQriaF6+lrz5A+W/oaGz8gKNrvuT6WHcxGXTNE6OoIXNbfNEBID9Y7X69GaiajTQgyfDFpeA8sWbsPDB1lqamtF8/WuCHdLb0sOkT9DP+kph/z70gEQpKYj39cpw7D4/NFFk+G4Hm4ucr+TVDdJcxfBND3HT2F4vIqDO8bC3c35xZ5fhwk53THwVScSMkGQz6H9Ytp04PzGslXcouRW1iK4ydzUFvXFGZ53SUj8dgt02Wu/tmTJAQp3h5uuHhif4QE6paUIKilWDs9YVNufQ8FxRXqDwJ1dQ14+/FZuGB80zvkXC/Mufxq8T8StiofcQN9MPf28xVJgzS3ET8OfLt0C/YeOYW6+nr0iA7DXVdNMLu8hKpd9vvZD5dKeLLqg0JNbR2umDIYF07oGPNo4/u9VR8jOyC0qrkt0piiAwJ78MPmJDyz7GiLzrx2WS9cOybepE42P5Tz3/O2pirOcTOpEx3kZk1Pi8oz2tyjpwkAw/08oAkQGQ5yJLNECF0YIurj7qxT4qEtIKSrD4t2pWNXWpG8xPLLa1BaWQsfDxdM7xMmgOLTdUkGkdRo1p2SV4Zl+07DxflsCI05CU46yJS22Q1LAVJL1atrMJbKhTTn/Nn4AUHxfr9wX6ZO85uDZZRrk94sMmDGRgbjxf8ub5FX6OvljtceMQ81vjnXkbnrolzEX9uOi9eIgGnGlEE4npKNfcfStZqqqKyGt5c7An294ObqhEOJmWDuWxPYa0TK6Tx4uLpi0sgEXHbeQDXpiyH9LS6twLzl20HvHWUq2Ifvl20VkKoCk0UllXBwaMQnz18nXqZvl2zGpt2J4h1ijjjLM3dciMjwpo+OLJznb5Zsxs6DqeLlJPAlsPX2PBs6SoITAtQF791pSFfPiWvEDgdOCvHPwJ6RJn2M0zQIQT+nwsnJPBJCrRk7M7cYT7+/BF4eTBk5WyJD/fHUnU1e6fYuNr7fW9X8dkBoVXNbpDHFB4TLP1qPfRnaZADs2cBIbyx9YKJZO2mp3CqzdtIClbXmadGV8ydfF33cEBPkhbSCcq0QUhVoC/JyxdUjohWJwLfWh9HxQTpBOsNMeRz4fkuKXgDfvO4tSbkoqapHgCdFkM9uK+YiOLHAFNmr1GGBzvC82vgBQdF+X1NTg2VH8nWudXMAwuYVP/T6fNDLoXW4rW/AJ89f2655SJZ+2EnI8cZXf6CgqEzG2SXET/bSEf1isfNwKpw0tEEJIu65eqLkZ51IzRbtN01gxb5GRQTgydv05/Y1BxFPv78UpeUEfE17MOeCWoWHkjIl4oSFe3eAnxdefuAyMLeRuaDMGVMV/k6Cm/s1dAZXbTyEX1fvFoZSltTTBdi2PxldQvy11KzjIoPx60f3WNrc9vrNZAHmtT7x9mIJTdYsppLjmKl7Uo2N7/fmNKXeuuyAUK+JOvwFig4IHE3c3BUtckr4dy6Gk2+YpkPY3FqWyq3q6LMiYZlbTqKsql5N3OLt7oRRwgpa0AJwqXL+zGmv1uq6flQMtiTl6/QCqryHze3bnGymed1JOaU4eLoYAZ5ucD/DgkYPobkITjr6fFuif7q8u5bWeDPn+rOETewHBCja7ysrK7HieEsmWtrREoDw9f+tQnp2oRb4Cw7wxgv3XWqp5dBu9VLAO+V0Pvr3iMSH89Zi0Z975CUqnh1HR/TpHo7LJw/Cpl2Jws7JZ5eeH5K6vPTAZeJNIjgkW6ZmodzExGE9cM3FytI39hw5hY9/+Es0BlnYJgEhQSmFzI8kZ4pkUHiwL+69eiKiIgIF2D3/4VL4eLtr9YGC5E9reIje/OoPpElocFNhH5es2Ysgfy+17Ai9xA9cP0VISFor3NPkrHEGsLbb5HXAhhmqSZuezMgTD/IVkweiS9hZL62luvzGF6tkblXatcxdvW32WGG27QjFDgitNwt2QGg9W1uqJUUHBHYifu4K6JAhBL8RJpkZEHaGnCRzTEzzw/uJrBLM25YmeX+ODo5q4pYbRkYjp6ym1ZBMc9pL09uj8jQyZ3BEXCAemdoD+zNKkEhReg1iGEMBQXNPUmNjA9Ydy0VNXQMCvNwMEklvD8Bjjrm2Rh3mXAdK+tte7Srpo40fEBTt99b2EBIkvfvtGpRVkCnRAR5uLuJpMkWbTcnasMa1wu774zrsP5YuwIZkXwcSM1BO9kcNoOPm4oz3n7pSGCAXrd4tOXwEWtdeNEIrJ2zt1qP45fedEq5Z39CImIhAPHn7+VqC9c3HRSDJD24+XmeB3PqdxzFv2TaRJTh2Mht5RWUCQOO6huDLl24Q4FZZVSuAUNVPyic8/vZCAXiqQhA5dkg8rr90lPpvH3y3FifSmsTqVeVkRi4KiyuFJIf6f1NH9cR/HputcwrYj3m/bcfuw6moa2iQ3Lg754xTg1drzFtHboP77n++/B0pGfnireW/iZ1fuO8SIWqyZOFaYt7iyVN5cHd3wZSRvTB+mGlENebsr43v9+Y0pd667IBQr4k6/AWKDggczeAXfkdhVUtIGOjhhN3/VhamYoh1jM2B6iyAQdchuqKmDocyinXk1PXAnGFdQeD119Eckq/ivJ6hwhiqekkrtVdrdlKBOxcnR8lFJBjkF+zYIC+RrLhnUnyLL7WGAgJdwLGqthaRfp7IK6/RS3BiaDuGrK9z8Zr2zOVTuv6sbX8bPyAo2u/r6uqw5FCuzimyhIeQDRFkbN2fLN6p0YO6tQlsNDtGwpLl6w+IDh9D1i4Y11ftfbL2Gmurvb+3HcWPK3ao5Q74vKzbfkw8LGRc5T7Ov1GwfPOPTwrpyKfz1yExNVf2+15xEbjrqvFadikpq8T2AymICPZDn+5NZD9ZeSVSV1iQj1YI6JeLNmHf0XQBhF3D/HHP1ZMQGuQD2u+BV3/GsZRsFBaXC7DgHPTt3kVy+168X7eX9p89ifjht+1CNkMQEhMRhMdvm66lR3c0ORPvfbdWWKlZWG9sZBCevP0CyRllnqgqnFSX7eav2om1W46oryFA7B4din/dbLzucUdaE6b2JSU9Dy9/vlI+oKgK19CQPtG4bdY4U6vv1Pfb+H5v1bmzA0KrmtsijSk6ILAHV3yyEXtOlbTozOAoX/x633iLdFJppZ0JMOg6vB/LKkZJZZ188eVBgS9A6v0xXFMJcYvmy0EX82dbduJvzy89hB0p+dIXNxdH+Hm4ok8XX/Hk3TA6VoBo82IIIFA6P80lKeiV/GFbmt5cRaXr5ly5vjPk8rWXrW38gKBov+dzumh/llUBoTHrorqmFs9/9BuKyyol143hcwSFDFvsaOGF//1pHQ4naRP1bNmbJCyTVdV1qK6tg6ebC0YOjMNrD1+B979fi+MnKc/RlMNHb9yQ3tG488qmdy0BNLUEmUfIsRYUl+G9b9ciPbtI/h0V7o9/3TRVSGIWEFhtPaKWJeD8Bgf4iCeJGnLL/tqHbfuSZX8nSOvVLVyAG+375mOzEXCGvKb5HFHvkIL3IYFeSIgN12lzMqD+sekwyqqq0a1rCK65aFirYP/giQy8/sXvAkzjugbD3c0J1TXauaUElfSgkszG1suOgyn4bP4GLUBImyTEhuLB66fYtHlsfL+36tzbAaFVzW2RxhQdENiDm7/agnU6hOkn9QjENyYI05tzdO3pIeE4lHgndR3e88uqkVdWhSBvdzWLp4+bE24aE9cmccvArn4tJB/Yn9aYP1vTIVTlCSbmlnVrPlcAACAASURBVOJ4VploGfp7uGBYbAAcHJoOJvpE6PXNpyHAkXXokqRwd3XE4KiAFqxspvZJX5/N9buS9WFMm4aG7hpTd2e/x8YPCIr2e+oQ/npQO9RPNf+W8hAas74oML70L23Bdoay3Xdt24LrxrSl656U9Hys3XZE8uinj+2DruGBrVZNUPb39mNaDJDpWYXiEQwK8BIvG/eHe6+ZhH49uuCB136mKodWYYjl24/Pxs8rd2DzvmTRE6Q24K0zx2Lh6t1IzchXgzIyj3YND8Djt0zHK5+vFIF7zUIwedNlo/HN0i0CKAjsSsurJZlxeP8Y+ShJkfHPXrheK8TUXLZrXk9qRh5mPPgpGuobRUCduYwVlbU4f2xvrf2e4yIgdHXRFne3VL9MqTevsBTfL9smmn1kZr30vAHo1yPSlCq157C6Fo++tVCDjg2yJq6+eASmjOpltnY6Y0U2vt9bdcrsgNCq5rZIY4oOCOzB2Nf+REZJbYvOdPV1waanp1ukk0orbU8PiVLvl67DO78SV9bWI6e0GkFebiChTPcQHwnTbJW4Jdpfrk/KLdPSbNRmBW1EflkN8surcdWwKHmB7D5V3MK8wd6uOF1UKfUQnJ7IKZVDCT1zjFsqOHP/HNZh4QT/BTvS8PFfiepwI3a2vLoWEf5u6BV+1kNJjUoVuY7S9WLN65WuD2P6Zo02jOlXR7jHxg8Iivb79ggZNWaNfLVoE0iKolmYU8d8plnThxhTpcH3MGTy21+3qMNT6cG7ffY4DO+nW+ScshLPfbgMldU1Qh5DEo7uMaEC/gjwnJ2ccNeV4zFyYDcBho+8sUArR48d8/Jwk5DYH1dsV4ee8u8EdNT5U+3J9JgyH5DgYMKIBOTmlyDI31trzybYG9Czq9prSSmBE6k5AsSoA+ni7Ah/bw9MGd0bj90yzSSdPE2j0utIHcJgf2+t0N57X/pBZCxUHlHew+t6x4WhR2yYVEEb9+0egQeum2zwPLXXhfRkzn13sda80ObP33uJ5ISaq9DL/NPKnSgprZDQ2mH9YnHH7HEWfz+bq/+WqsfG93tLmVVnvXZAaFVzW6QxRQcE9qDvsytQ3qRNq1W8XYCDL5uXZdTYEbenh0Spd7L54b26rg55pTUI8nJBWU2DgK/e4b546fK+8pJsrf6RwkCa3yKMsoufO/LKCeAbcfh0iZqoxt/TGX0ifFFezXDQs19ZCay6Bnggp7TmjPmb7iuurG1iu4MDArxcER/qJSD17ondmghmskuh0ktUChLb8pg9uXAfdqY2ZzpshJerE3qE+ajBb7dgL4zpHowkEt2E+SiS2DB2nRlzn9L1YUwbvMdQD6yx9XfW+2z8gKBov+8sgHD7gZP434KNWnlr9BAy7y3SQKZFRiJUVtfC091V0SH6mfeXSKiqZlExgbb2jFCu4bd1+5BXUIbuMWGoqqrBio0H4e7qLM9tbW0Dbp8zFiP6x+H7pVuxcdcJdf4cw2HPH9tX2CRJIqJZSExD7Tl3NxfRJKTWH/ds5u6NHBAHkvbQ2Rgd0eTBZB4hPVX896oNB9TyEadzirDrUCq8PN3QNSxA8vX43a97VCgmDO+B1VuOCMjsEROKOecPU5yruXzdfvyx+TDKyqvh6+0ueokqT9Z1T3yFQ4mntcZVV1uPIf2iERHsL7mKBIb8WMnQW9prYM+uuO6SkVryFx1lf2I45+fzN2itTfZ5WN9Y3DJzjFm7yfDhU1kFCPT3Ek+kvdhlJ6y5BuyA0JrWtkxbig4I7ELvZ1agUgfNqIcTcOTVjgEITfWQmBLSZ4x3UvPwzoPJ1uT8FiBNlbPX2tiaNAqLxANIAhjmHAZ5u4pGYUZhJUqr6sTTJ6ylTMoP84GPuxM8XZzFG8kXLMFgfIg3WmoNNuJYVinKa+oQE+gl9ZJhhuBV1/26CGdaW7765kqXh1AlWp8Q7itMp/EhXticlI/kZt5RJf2wzOPVslZj1oe1+mYL7dgBIYqLi4vh66uffbC2thZLD+fpXBYdKWSUewhzqAhiSMzCQu/gVRcNN2hJb9x5Ar+t2y/Ajt6wK6YNxqiB+mnz2e79r/wsYEmz0PP3wdNXGdQ292JKR9Abp1kYAkovEn9f9OduIYJhCOWQPjGYMWUgPpr3Nw4nncaprEKRnyAIJWvohGHdsXlPsnik9h49JeCWeXgqEMiuknmSMg8JcWG4+sLhAgyf/WCpAGLar7auAXuOpGF4vxgtcEzhek8PN3W0Bj1dveIj8PANLfPUaBsCXwJsTYH0k+l5ePXzlU2gVdgwG4VkhvmSlBiht/edb1ZrhYLy9z+/fAgR1C0E8M2vm0GPmMuZD5nsPwEvQ2Y7WlGxtzLMV1U45v4JXduU2Oho4+is/bHx/d6q02YHhFY1t0UaUwwIuz+1AnXNchrYM2cHIPH1jgEI2R9jPST6AIq+WTDVO2kIYNA1Nrb77K8HUVFbp5aqIFh7ZUZfbEkuwNqj2SiqqFMT1PSOaKIPHxrtL+BQU0KCY2yed0jmU5LKaHr/GE7K8NOEsLOHS4LK5oQzbQFsTTbT/PImMOvh6oiHpiRgcHSAzhzC2GAvfHPLcHVYkbW8bvrm3pDf21ofA3TkgCr1thrSB1u+xsYPCIr2+6qqKiw/VtjhAaGqgxnZhUg8lYu+8V0EXBhSmNf1/EfLtAAIgc5rj1whIEtfeem/y5FTUKp12I8Mow7fRfpuld8ZOvnQa/NbeLcIpN58bFardew8lIo7nv9OnWvHPsdHhWDpJ/dhw87j+H3TIVCSIio8UKQiVO9EMoY+eH3LUEsylf66Zg/yi8ollJFMr3V12kQux05mCeOoZqHH8q3HZsPPx0P95wPHM/Dj8m3ILy6X8FaGm14ysb/8TokCEtckpeUip7BUPJkc6x1zxgugIwC++8UfsGVPshDseHu64obLRuORm6aq62cYLUGgZnF2dsT7cw0D4QZNjJkuIlh//O1Fch5RFTLHPnrzVMnP/OWPXSLxwdDZWdOGoH+C+XILzTSETl2Nje/3Vp07OyC0qrkt0piiAwJ70G3uCmi/Jpr6RaqRZDPrEFpkxHoqNRVctBeg3JNW2AQIa+rUzKSers545Yp+wgb6y85TmL/zFAK93BDk1QTs2sq7aw46+e95W1O1QlKPZ5dIfcHeblpW1SR30WcPAuCdqYVqaQsVq2qvCF/897ohakHmhbvSsTutSKckhSEguj3Wkq42W7MHQ28/W5/cqsZkR+l/Z++HjR8QFO331dXV+O3oWUFxzbnvSB5CU9Ykgcs/e5K0PnQRlEwe1Quzpw/VW3ViWg4+nPeXaPQxLJ8etMdunibC7YaWf3+8TICYqnCPIFvnQze0niP3+fz1WLJ2L4rKqkDyH29Pd0RHBOC1h65AlzB/ASAvfboC2XnF6g9nBFGP3jRNPIP8/XhKFnYeShPv4ZhB8VqePIZ1Lvt7v+gSsjDXsU7AmzarZ3llDV57eAYiQvzkuiYAtFDIcVSlqqYOj9wwGX17RAro/GLhJqRnFsLRqekIWV/XgCF9o/Dt67eq7yG4Zy4jpRN8vc+CTV7w8BvzW4BVssu+/1T7AUKuGTkHnWGD1Zx7hsAy3zO3oAw+Xm6YNqYPxgzqhrnvLIajUxNJm9ihgZ7SGQjw1f8hwtC1ZevX2fh+b9XptwNCq5rbIo0pOiCwB63lEHq5AIc6SA6hKZYyB7gw1jvJfusDULrGxnve/fMYtp1sOrzxwfT1dBXgNyw2UKQq9NWrL0xW1/2erk46cxA1yV30AWz+/v6aY0jNq1C/TBsaG0Tv8KGpCTqlLZrbwFSvrCnrpbX50CXzobpW1/pojfG1NXkPc/fZVuqz8QOCov2+s+QQmrJ2GY65ZssRLTBEb9ul5w3ExWe8Wvrqp5dv6/6TIjI/akA3xTl1J9NzRay+sLhCNu/wYD88edt0CQE9ejIbAb4e6nBJ5olRikLAYEmFhF727hYGf18v0Sy8acZojBvSXbpMOYh5v21DWma+mohmcJ9o+Y1hlxt3J0reIuuMCPXDM3ddpOUp3bw3CVv2JMm+PGFYD6RlFuD3jQfVoZqsx8fTTbypqkgGfSGSJNWZfvsHYL6jvKgaIbYnsc1bj80yyLP71cJN2H4wRR26SqA7ol8sbpvdpLlXWFIh/9uaTIa++VTyO2331eJNOJh4WkBwr7gw3DlHWydS9V7nRwN3N2exp6y7rUeEWEhVlHyIUNJHW77Wxvd7q069HRBa1dwWaUzRAYE9GP3K78gsa5lE2MXbCZufNb8wvUVG3Ual5gAX+sCVvjHpAgz8G71ku1IL1ZIPfLGogNqOlAKk5JfLC5b5gwwJra1v0GLebA2o6gOLrQGZAZG+er1a+gA227533i4czT6T39jYAF93F9E7HBrTBGb1lbb6z3vbAmf66lb6u6G2bF6vPjsp7Yf9et0WsPEDgqL9vrPITpiy1kvLq/DUe7+qq+DzS4Dyn3/NhIc7c6X1FwrLb9yVKHl51O678oJhiglOmCd3JDlTABnJWjbsPIEn31mMohKKxDujd3w4vn/9FixcvUdYODOyCpGaWSA5fy5OjhgxIE68Zm88eoVeD1NmbpHoNmrmtRFUEQCT4KW1QsDyv18obH9KokvCgnyFEZWaj6rCPM5Pf1oPdw1PIm2qIlEheGaY7T8MCa2pFRt3iwoWMM0QWUPIUAjYv1myBdQrZOnbowtumTFGciDprVWR7cR2CcKDN0xWy2Uwp5EEPdRsHD2wm+I50mUXglMSxzg7N3lSOY/9EiJx3zWT2lw4rQHC80b2FKIeezGPBWx8vzePEQ2sxQ4IDTRUB75M0QGB4xj0wkoUVbVMIvR3d8DeFwzLm+jA9tDrSdPXd21A4Iis4iq4uzjizgnx4u0yJieMB7NZn21GWn4lPFyc4ejQiLgQb8mjI8Pn91tS4OrsqGYRJSiMCfbEiNggkarQ16Y+L15bY9bnDW217lExImFBdlKSC6w8mIWq2noBgyStoTiyEhkJXf1gv1vTYORvlgCKxtrSHB8i9K1N++82zzqnaL+vqanBsiPaTJaqNXSuhIxyPPTQLfyT+XNlCAnwxlUXDEfXiACDHpf1O45j3vJtahKwnIISuDo746IJ/XHhhL56wVnzRggoPpu/Hm98+bt4/ChDQQ8h9V8nj+yJ4EAf5OSXSO4dgVlJeZXk3Q3uE4OZUwdh5jT9MhvMLVzw+04tKR/2o3d8hF4gw+voeaRsBnMsm79bCIqf/XAZyiqq1L9RJuKmy0dh1cZD0vei0goUl1YhPjpEDaLiIoPxxO3nG2Tz1i5679s1EmaqIhbie6VHdKjkH5KJ9ptft4itaGPmPD5154Uiw2FK+dd/FrQgBKJNPnz6qjbfu8zZpByFZoipkOs8Yg8ZNWU+mt9rB4TmtGbbddkBofVsbamWFB0Q2IkB/16JkuqWgNDXzQH7X+z8gJBj1Ady2pqMswd74wGaZv0qD9r6E7lwdnREQyPg6uQIL1dHPDClh3xZ3ZWmkmVo0hksqarFiLhAPDI1QV5K+jyWlvBOqdo8kVWC/RnFwlDq5uwsX5YpEUEwqGIFJXlAXlkNgn1c1deQ7dQQMGvYXDR9vWVh+9ePisGWpHyL5OsZa0tjPYuW2hjO1Xpt/ICgaL/n4XnxgWydS+FcAoSmrPWXmaeXXyJVkEEzjblxDsDIgXESWjn3tvMV5ROSZGTxaoaxHhVPpXgsHR0QEugj4OXiCf1w8ozcBEMUC4rLBWD997lrENe1CWAlncrB75sOi8eSenRjB2t/FDydXYTnP1kGd9emfEC2Qe/Z+eP64tqLRxhljuMns/DDiu3IyS+VvEOeELzc3QR40fP4f4v/0SKCSc7IQ9cwfwT4eCI+KhQ3Xj5KS5rBmE48+NrPApQ1C99/Hzx1Jea++6swr6oKx9yzWzgeNFHL8PG3FopnUrMwn/G9uVfq/RBLD+fCP3cjr7BM5nbmtMEioWEv5rOAje/35jOkATXZAaEBRurglyg6IHAs57+3DseyzybAq8bXK8wLvz/SdphEB7eFWbqnAgQqQXfKPLBQFiIywKMFA6e+RgkwH/5pNwoqzr50+M7zc3fB+IRgXD0i+oyHUAV6GsUr2T/SF5N7h8OQsE5N7xRflGT7NEV8vjm4IeAjwQ09pGQ05e/NCWp4zahuQfLFtHuot1l0BFsDZyE+riLFQakNVdHFjqpvbnT9boqnz5QPEcb01RbvsfEDguL9fuG+TJ3LxA4Im8xChlKCMnp3tuxLlr811Ddi1KA48cD1jA2XsEVDy0ufLkdqRj6Wrz+gBhSNDY0ICfKREM3rLx2Bv7cfg4+nu/xOEMqPgiSKiY0MwvC+Mfh6yRYQlPB3ErpMG9VSguOrRf9g854kSeLbdyxdukcwwnDVh26YYnC4LO9j6Odjb2kzaZJ9dO4dF6Bb1xDsPpyGT374Gx4e2iG4DK+9/9rzDDWN3uueeHuRFujjDR5uLnjm7otA4OZ2BgCrKvL38cArD83QW29bF/y0cjvWbTuuzhslCB89KB43X2FejUGTOmnDN9v4fm/VmbcDQqua2yKNKT4g3PTlZqxPbElFPql7AL653b4JqgABAUduWdMXSZXuH9k4NRk4DZlRgppfdqXjUAbZ4s4+cs6OwLUjo0UX8KwHzgn7TxXLSz7C3wOFFTUI9XGDu7Oj+muwvMBV4MvBQQCaCjQm5pQiKbccheU1WuLzSj11+sImjfWiGWIvzWta60ekvztyy7S/6vI+pXPDe5p7Xw0B4ErHYb/efBaw8QOCov3eFnIITV1ZP63YDoaN8oPS9gMp4s2jjMLQvjFSNeUvXrjvUoOb+c+Xf4i4+NqtR1BQVCHagwSEzFHrEROChNgwFJdWilA9SWcICIP9vcQzSRBGLxgBCQGhqjSgEQO6R+J4arbUQ9A4a/oQHE3OwgufLBfPHVlC+X7hu4oaefdcPVH2tvSsAlRW16F7dIhOBk220RqRzKDe0bhj9jgcTjwt2oKaOZmsu1+PSGnHXIVEOys2HFCH7/I9d9H4frh00gCRfmguVUEA/dgt0xU1Ty3Gb5duRXpWodh/2pjeAuD3HDkFsXNCJK65aIQWSZGiBuwXm9UCNr7fm9WW+iqzA0J9Fur4vys6IHA4499Yg1NF1S1GFh3gjg1PthSo7fgmMG8PlZC8GNIyQc13m09ic1IByqqahIPrGpqIV0bHB8LdxUUAHj1wgV4u2J9ehILyWhGip7etsLwagV6uiAv2kr/5uDsjp7RKXljBXm6iI9gnwhcvXNoHi3ZniDRFEKUpzojPa3rO9IWeqsajD/CZ2yPZmh1bC8McHR/UwkPZlgSH0vopIcHcTk1tR315nIasBfs1plvAxg8Iivb7ziJMb/qqML4GEpx8uXCTeNnoIaRHqm/3LmrhdQKEu68yHPTsPJiKL37ZKPs8ASY16sgEGhnqjz7du6g7SnkHsmjyd3rgWLjHZOWWoEuoL0ICfCS9gEAvOT0XCTFh4snMLSxDY2MDrpg6GI/cOBUPvPpzC/DCMbx4/2V4++s/kXI6XwApQxrvvWYiukU1haVqFnoav178D9zczkpScO8d2icat84aJyDz6feXorS8Um47lVWI3IJSyYm88oLhGNjLuDDJwpJyHDxxGt26BiMyLEAALBljt+1PkXaG94/F9DG9xS4rNxwQyQuS9ogkRmMjHrt1us7xtLXfP/fhMrBd1X5OltFHb26S8rCXjmcBG9/vrTohdkBoVXNbpDFFBwT2YMIba5CmCxD6u2HD3LPisRbpbSeplC8mgp4vNiShorYe4b4ewvhpTF6cCtTQe5dRVIXskiqE+7oh3M8NHq5nQ3AIaLr4ueNodpkQtaiS1atr65FXXo0ADxd4urmgoroWFTX1CPV1R21DA+rqGkW7cGS3QEzuGYrd4mFsKqrw0UBPV1w9IgqbE/OQnFcuoZZsr7Xx6Aub1ByTOTySqr7qIolRSjajBLjp84R2kuVqU9208QOCov3e7iE0/NEgQCOD5eLVe2TfJJFKcIAPnr7zghY6evpq3XEgBWu3HRVNv56xYfK/FKLX3JvYRkFROXIKSgUUqn5jDl9tXZ207ebiLP3gPMZEBosni/lujWgUuYhPnr0Wi9fukXBXluy8EpzOKZbwx4S4UDDdgbIIlVU14lkMCfTGKw9eroNIph5PvrtYQkc1gdLz91yMyPAmcp6C4jJ8t3Qb1mw5LHp89M4xL7Kmth63zRqLkQPi9JlF6/df1+zG7xsPCyEZbUE5jXuvnthm3t7xlGyZI7KrkvSHpDhKyomUHLz+5SrxAGu+I/vEd8F919rTZZTY0lrX2vh+by0zSzt2QGhVc1ukMUUHBPZg3Kt/IL20rkVnuvo6Y9PTprGEmXuEhnq0zN2u5stCQEpOmUl5cc1BDYlaNIGbqj3mxv2TmIeiirPzQ7BXVkVCFwf4ebqhuKIa1XWN8HZ3RnVdgwBVPsjOjg5CROPp5iTELmzzSGaJhI9SwqKmvgE5Z8DoybwKVNU1IMzPFc9d3BdDYrRFmA0hSOE1v+w81aZH0tB5aa09tacuu1RCYwd29Tubl9PY2MQyasLc6POEGtr/znRdez9TptrKxg8Iivb7zuYhpEj82i1HZYlMG9tb8tesXShjQVkIgo1hfWPMEjpIVtD5K3dImKiqkIG0T3wEFq3eLYQwUhqBwtIKEZH38nATzTuCO/6b3kJ6CB242zf9R8IdL5zQD+u2HZPfjqXkSDWUgaBwPO9lDmJmThHoCfXycseG7x5FTJdgLUBEEHg6u1DYVumh9PPxxGXnDRCQplnoTXvkzQXST80SHuKHZ+9qIqQToFtcfqb/Zz2OmteTqfSZD5aocwJ5T25+KWZMHYSgAG8cOH5aiG0uGNdXQmzNVQ4lZuCdr9fAs1kupCrv0lztdKR6CPK5/rLzSjG0bzT6J0TqJcvpSP238f3eqlNhB4RWNbdFGlN0QGAPEp5egZqmD4paxdUROP7axRbppDGVGgJKjKm3I9zTlpQDtQo3HM8VQoP6hnrxBtY3NCLM1x0+bs7yLqZXjl9W6xoa5WAgJDUeLgjzdUXfLn5yT0lVHY5llkguITUBk3PLcSijCBVnJp8hTbw3LsQTvz80QV4S7NdfR7LFi8ncxahAT/FU9mgGxlQ21AeoDAUfze3B+zKLK1Bb3wg3ZyeE+7mLjIUxHtq25lufJ7QjrBVz9uFceKZs/ICgaL+vqqrC8mMt88W5pjoaqQx1AL9ftkUtpUDP0y1XjMGYwfHmfATapS6CsRc++U3YKOmpYy5ceLAvnrv7Yrz+v1VYuHq39IusofTy1dTVoUuoP7qE+KFreCD2HkkTZlIVDuNzTFATFuiLf354HH/8cxgffL8WZRU1Ui/DTCnTQI8a7cjCFAOGWUZ3CcKO+U9j58EU/L7pEMgWmp5VhGB/T4wa2A2zzx+K7tGhOu1EsPzom79I2KZmIRPpqw/NwLHkLNEXpHSHu5sLRvSLw+A+UXByckDvbhHqqJfl6/YL6Q7zJJkzeeB4Oij6Tm8ovXeDe0cLGOa/H7juPMlVNEehJ/WJdxaJHIiq8P/fPnucYg+nOfpj6TrKK6vx0n9XSIgs54ye6nFDuncqwhwb3+8tvUS06rcDQqua2yKNKTogsAc9n1mB6pa69HB3Ao6+2nEA4bkcztfWwZy//XvZIRw6XYySyjqUVtcJGCLg4397hftge0qByFOwqGQsfN2d0CPcF9P7hAmA+2lbmpDSNOUSAptO5AkzJ78F8MF3cIDQq/u4u+CpC3sht7QaKw9kSlgrX8R8WZO85aL+Ebj3vO46vyq2BagGdPVroSFIuYox3YORRK+eBsjUBJYqzya9mbUNjZIzqRK6px1uGB0rbKfmKOcCQFJih3PhmbLxA4Ki/b6urg5LDuXqXCIdDRA+8/4SFJc15aipir+vp4Q4nguFnpqVGw7idE6RgLwLx/c9kw/XiG+XbMGWvUnYuj8FhcXlQt7i4e4i3jZ6KQP8PLFs7T4Ul1WhvqEBzs6OCPLzkrDSP754SMDXI28sEABIohR6N+kVOpVZICCSH/9YF0NQWTc1BfOLyyW8dP/xdAEKZDoNDfJBv+6RePquC1sFYc9/tBT5RWdz8AiySMBz84zRePKdxZIPz1JeUY29R9MREeqH8CBfIed59JZpwrRKuYb3vlsr+Zp7j5xCaQW1GBtRXlkDXy93EZ4f1DtK6onpEojHbzVf5FLyqVx8s3SLAG+Cz0kjEnD55EHnwhJrMQYSJm3YeULLy01v82uPXCHz0RmKje/3Vp0iOyC0qrkt0piiAwJ7EDt3RasdSXmj4wBCfd4ni1jTipXqyo1T5W80D8fMKqlCaVWthOpQsH5YdAAOZpZge3K+fHXly5TEM5SquHlsNxCMaYZzFlfWCsAsO/MlgECQifnOTg4I8HSV60l0cyyrDGXVdQIY+TvDUnuGe+PhqT11grC2ABXDOb/fkqKWhuC1B9KLESr5kx5aOYya1+aVVUsOJcfr7uIMNxcnNDQ2oEeoD4KMYHnVN6VtzYO+ezvb7+fCM2XjBwRF+31lZSVWHFdpnGqv1o4GCO97+ccWH524H370zNWtPmYMTaS3LTTQp1OFweka0Iadx/HZzxvg5uaM/ccywPBMODQiNNAXbz42EwtW7cD3y7aBOeUEeIwgmTSiJ+b951YsWLUTny3YgLzCcokqKS2rEuH5ijPvDIkGcXCQj3wMRSXjaO/4cGzee1KAETd87oOUcQgN8sWlEwfoFJnnNWQcJaAiuY2Tg4PIXDx841SkZOTjP1/+Di9PNxkeiXLoofL19hA5DN4bHRGI6y4ZISDlr21HBazuPpQm0S78QFlb2yBhroxdGTukyTMc7O+NB64/T0Jf6TFVkiPe1v5MEMywVE1h+c62n+vr7/vfrUFimvYHIY77rqsmYHi/WH23y181uQAAIABJREFUd4jfbXy/t+oc2AGhVc1tkcYUHRA6EyBUGs5naHiiRWbBApVqH95bCtaT+W3mp5txMrdcqM3dnBzQM9wX39wyHJ9vOIkmCYoypORViKeN9mHOIT2KKvULlYdwaq8QpBVW4WReOapq6+VFzTBV5iUybPSm0TFICPcVoKby7HHIKhKYphe6g1ZoaXPwoQJ6YX7uiAtu+jpZXVeHUXFB8nWa8818SXoohUXVwUH6oHphM78y0t8DN4yKEfemZl/MdUiwwDR2qCqVPlMdqvNnOmPjBwRF+z1t9efJlpqzNGVHA4SvfLYCmbnFWjnCZJ58+s4LWyxDHmoZInkiLQcNDUBEsC8umtgPhcUVGNI7Gl3CzBNBoHT9E8SlnM4TDx1ZPZUUAqSfmWfo4iwf+LLySkSYftrYPnjw+sl444uV+HLRZjBsk4VetAlDe+CNf83Ecx8thbOTEw6dOI1jqVnipXMS/Vx63WpFSkMVbkqvHGUtwoJ8RMeQnkIeBBlayra9PFwkdJShpxXVdbh0Un9cOL4fDiWexrzftgkBDsnNKG1BplOVpykjuxDPfbRMTdiyaVei9JNe3n49mthV6bEk4CQQY6hmUUmFhDO6uDgLWKT0AwE+Sc9GDIiT3El6DwliGbUSEeyHu6+egJguQUpMa9K1fM/y/dIZ3zEL/9glrK0MU1YV2veNf12BAF9lhDwmGdGEm218vzfBcspvtQNC5TbraHcoOiB0JkCoJJyv+bXNhdQ1yUisNYGmAtSWh3dtwXq+qJ5bclAE7wmc+NIP9HTBTWNise1kAVycHJGUU4pj2aWoZy6eS5MnsaSqXh026uQABHi5YXrfUGQUVuBYdrl45pi7xzpdnBzAUNQufh7w9XRBVW0jPFwdxUPp4OiI5NyyVhlLm/ef1xLoJYT6INCbX5Ebcfh0iXgpE8J8BRx6uTpLWOyh0yUI83XDkcxSlFTWyhfs2CAvDIsNFNelIUyp5p5nU+fT3P0xpj4lz5Qx9VvjHhs/ICja7ztTDmHq6Xy8/93aJsDT2AhfH0/868ap6BrRxHKpWSjrsPtImjBoSuTB8QzJQRvaL0bIUyYNT8D1l42yxnJUt8GcvR+Wb0dxSYUAHHrFKPNgqAeqorIGj721UK1Vy72auoPM5+sS4o91244it7hMPIeM3iCoIhijd27F+v0CAulZJOgS7cPGRrmP/6Z3jR44snNS/qJf9y6orWsAbX46t1jy+Hg9cxjJYMrfCBjphaS3bs4FQ7DvaLpEddBLR4BBUH73VRMwTMPTRFCfkVMk87Jt/0kBdAN6dYWft4fMy+4jpzCi/1nPFD8kerm5oKisSvpGgHgw8TTCg/0QGeona4EEN/yNhX0M8PPCyw9cZnGARr3CzxdsREp6npABjRwYh6svHG7xds25aBmm/Nrnq2ROaEOukfPH9sWc84easxmL1mXj+71Fbdu8cjsgtKq5LdKYogNCZwKEqheAIUySzXXxVOyavSJ8JQdNCRmJOQ7+5jh4a9fheEawHujf1U+YRU8XVSKzqBJOTme//hEkdgvxRogPwVSJ5AySXZQvXnrhCBhLq2uFcMbDxUnyEXk9r/FwdhIvXVpBBSoZluTgAE9XJwR5uSKvrEb+P78Msw2COQJJVydH+Hq4SJ5i8/y+5jYgSUxuSQ0GRPlJFmN+WTWOZpagZ4QvggUgQg4c14+KwZakfPFuEtRmlVTC08UJd0xoCiGatzVVHYaquseceYW6nlJzzKdFnn4jKu3sIbI2fkBQtN93phxCLmWCnV2HU2VVM3dO07OhudTnvrtYzcxJryJz5+jBGTOom9xDaYYX77tEcvXaKnwWlv61TzxlBJRxXYOEYIRhjkoKD96Pv7VI9llVIRgiayblEQwtuw6l4ueVO4VplEDExdkR8WcIXpb9vV/C51UhmayTIaAL3rkTr/5vJfYLKK6RUE4WAkZ61ggsmZsZFuyLvvERas8lcwmZr8jwzez8ErGbixM9d7VCAuPl6S46iQRy1BwM9Pdu2ncdHNC3e4R4QXt1C8f9156nHh5BIkFxamY+snNLxPtITyPtXHjGGxgfpU1YExnmjwvH9cOGXSeknnFDu8PX013G+enP64WxVLPQs/jW47Pg7+NpqFmNuu7lT1cgK++sx5pr85LzBuDSSQOMqq+9buL7muCc2pF8PvQ9E+3Vz9batfH93qrTYQeEVjW3RRpTdEBgD4a8sBIFVc14owEEujtg9wtN1NGdoWgCt7TCCiFFIdBQhSbyyyzDDBmeqCnOru+A8Om6JAEj+rT62qrHXOQdqjH+dTRbBOuph6gKXdmTVojiihoBaarCXLsRsYHILq1CKkNF6xtRfCaPhPmAUQEe4qUL8/VAtxCGjJzdAoZG+yM+1Buf/HUCyXkVAhi93JyQXlSJonICQmf4eZKgplHAqKuzI4K93SW/T0X6MjQmEDMHdwGZUnelFmJItL+EkbK++BAvbE7KV3sVj2eXoK6+USQxNMNxhsYEYNaQSJ2SEgxD/fNwtngNVUCUY+A9s4caJ45syFo313wa0pb9mrYtYOMHBEX7fWcDhPrWPtk2N+xKxJ+bD8Pf2xP+vh44kpzZRHICB4we1E08bDwETx/bFzOmtE0WQuKVn1ftELIVFgI6hiU+d4+yXHqSpLzzzWoBYJqFguv/unmavmFp/c6+E9S98NEyOGmE+hG4cZzBAV4yVpLLxHUNxtKP78Vb//cnvvl1s3iyCN6IS6k5SCZSegkZekp2UVXhe4Uhn/Twbd2bLAyo9BIWFFfgVHahCNmTuKZrWIAAuYrKasllZH4jC+1FIplBvaIwY+pAPPn2YgEcDA99/JZpGDmwm1xHz+36ncelv6MGxuH/Fv/TQouR5DF3zB6v00b/emOB6DcyXJQAkNqH9HS+88QcIdKxVCkqrRCAr/JMqtqhDZ6/V9nasFQfbaVeG9/vrTrNdkBoVXNbpDFFBwT2oNfTK1ClQ3aio7GMKgFumt4nyivQo0WgcjY8EQaBBmMP/s29iq3pDBoLXHSRgdDDdjCjWEJBKUDM8Xq6OOPly/vgrT+P40ROGdycHVFeXS8vUZLO+Hu6oHe4LypqqWt4ljqcgPnG0bEYGOUvXsLvtpxEUk45SqpqUVRRKwCM4ZzBPm7iCcwvqxLATJKX6toGCfeMDvLEsxf1xvtrE5GSVy7hRsxXiA32krxGAnRN7xQPPluT89WHMc63Zj+azz/vZYisSpJDBUTjQ71w0+g46buue3SJ3St9Ek0lYzGH11lpn8/V6238gKBov+9MIaP61uvKDQfw65q9ckgnUye9ghQUJ3nKyfQ8CYXscUazrqq6Do/cOAV9z+SutVY3w+lO52qT7tDL9Z9HZ7aaA8hnefXmI+J1ISgb2DMKI/rH4N8f/6YFUjRBl76xNf+d4aNkDSXBiqocTsqUkEp63OrqGiQXb2i/aEwf0wc/LN+GRX/ukf2VdiCwpbZhkL+XMHQyj6ysouqs6HxdPZ68/XzReaRHkKGqW/edlP2auYDV1XXiMfT1dpdcP4JsymBUVFWLtEVdbT26x4Tig7lz8ODrv4AASphMmaDuACz+8G409wRyHEvW7gUlJziHbIuMqM/fc7GEhTYvzIf898dLcTw19wzIb4SftztumTkWt84cq9Ok9HRyjTDckzmJM6cNVmsdKpmDkrJKsUlzeQ2Gsj57t/6P5vQmck74sYJe1xED48Sz2BnzEJXYzRLX2vh+bwmTtlqnHRBa1dwWaUzRAYE96Cwso21ZS5dunYrBkmE0mvp7fEO1BTQ02zHm4K8rnJDhleXVdQaDHX0rQxdQJQgjAMwoqpQQT3r0CDj50tmRkodjWeUSWurvSS+pJwrKa3DVsGjMHhqJz9Ynt+oF5XieX3oQ64/lSkhScWUNyFJKGasgT3fUNDRIjkmwtyvyy2tQ19DkZ/TxcMbASD8BqZovUr7475/cHVcO1xY5VhqGKUB180nRYCRAJcBk3RN7huCly/u1eNkqrV/JetMHXjXrMmc/9K0TW/jdxg8Iivb78vJyrEos0bksOhqpTFtrl8/Q428vkrw1VeHhn6GQYwfH40hSloR5CllJda0Aw8dvna73AE4NQOZXaRaGm77ZBiBcseEAlpwBprIP1NZhwrAEUGz96MkstZSEfMC6+2JEhBpHcNM8ZJHjqqqphbenuxDExEcF49qLRuCVz1eKrAC9cfTmMX9v5IBYIQ+75+oJoumXX1QmDKUEe7TTRRP6iYePfUzPKhCA++63a+WjYklpBUrKqiUP0d3VCa6urugZG4aYiED8te0YqmtrJUeS4YcEnSdSc7SAMENU6an9/IXrdU5pSno+Nu0+IYB78qierQK2d75ejZMZedL3jOwiAd/s+09v3S6eSBZ+VKRUBQl2CEqf+3CZjInvQHoVI0P88ew9F+ldB7o6+uZXfyAlI0+dA0rSnasuHIYpo3rp3WY/+WkdDhxLV4c8M3z4sikDccnEzhVuqnegVrjAxvd7K1j4bBN2QGhVc1ukMUUHhHMFEOoCbnwRMHcuOtBTwivLa5q8YASDhuYQGsPC2BZYI1AzJfRUtWJaAxV3T+yG/RklSKSuX6i3vAyZY8fcO+YQahKyDI8NxD2T4uXl2FoemervP21NEeKWzOIq1DdCqM4rauslly8myFO8hBF+7jiUWaomtOkf6YfjWSUgWzoPEppleGwA3pjV8mWoJJ9NNee8h0C0tLIWPh4uors4Z1jU2TGdYUJV2ULyXs4UQ0OHmz+ppoA6Y73OFtktzoFKbfyAoGi/P1c8hMxju/+VnyWMUbPQ08TwQXq5/vznsBCkkISFpDIixK6nSMjoyh3q0EBDQkaffu9XlJxh+lRVz7befmwWflt3AIlpOZL/NuO8gYgMb0mIo69Pqt8LisvwyY/rcSqrQEAexdnvunK8AB0Whkyy7wwlVYXJJp3KFaZV5vY9cN1kDNcgcGneLglbCLpSMwtALUGKw/MDG8NN+Y4oLquQD5ovPXAZNu5KREZOIQjm+PmPUhPUF6S0BG1OuQrNQtKaeW/eZuhQdV736ucrhXVWsxD8vfrQ5eKtpNdz1caDQjxDxkwvD1dhZqUtVIU5lfww0KtbhOK+8OPDN0s2i2wDV1Kv+AghlWEYbluFHwjo3W3uDVSR4SjuiI3fYOP7vVVn3w4IrWpuizSm6IDAHpyLHkKOS9MLqARoaM6KMQf/Vr2K0f4i0aACa6YynRoyJs2+8OvpybwyZBRWIdLPDXMv7oPBZAdl/KiOojn20qo67DtViOq6RrWwfWVNveTt3To2VvI1/zqWg6KKOq0cQobrnsguFcIZVeEh44HJPTBneJPQsLGlLbBOHcXmuZ+kTPf34stbe7zGhu2q7M/x8f+TdEclwdFWKJAxXmdjbWQL99n4AUHRfl9dXY3fjhboXBadyUPIATDPLe8MYQr/zWeQenqP3KQsR6/5fk+yls27k1BZU4O4LsG4bfbYNkllHn9roZDWaBbutR89c41BIFTpM0rAw0gNksA0Lz8u34ZNJMSprEFuURlOZxeigGGlQX6YOroXrr14JPp01w2GPvnxbxxKzFQDqF2HUnAyI18YPumCpH17xYdj1tQhOG9kT7H/sZPZ6BoeIB45FuYW0muo8tjJe7imHs/dcxGuuXiE0qFqXU/JhNWbD4s3UlUoJM9w3tSMArz2xUqtSBTmcSbEhouXWFUIzq65aIT039jCENdVGw9JyC3HTbteMXVIq9URSD7y+gI4Nft4QabVVx+eYWw3bPY+G9/vrTrvdkBoVXNbpDFFBwT24FwAhMYAN0Otbwjw0qzLGK+i6n5z55ap8v9KK+twNLMURVW1ktdBT1qgpysu6h+Oe8/rrhMUnh2HI/LLarAjpUA0CZl7SAIZTeIYkr5oCt+TZZTAi7TW1DLk/bpyCA2dA13XtTXnmsL2qnuZV0oyg3C/s1+vDQ0dbq2fxqw7U9aHKfY6V++18QOCov3+XPEQci0zfO+jH/4WZkx+gAkJ8sHjt0xXrPdn6nPx+YIN2HvklBr8cU+gLt4Tt52vt+qjyVn4de0edS7gtZeMRFgQp9S4wjDVqx79Ajn5pUJEU1lVDWcnZ3QJ9ZP8wYG9ovDWY7N0ErCQqbW0vFrsmltYiuKSShSXVyI+KgSuzs6IiggQYNw/gZ7JCSJf8eKnK+B+RgKCPSb4YTjpgj92iaeOB0pqDn77+q16PWn6Rkyv8KfzN4jnkuGaoYHeuH3WOCTEhQuBzo6DKVrvMYaVkhiH3ktVYa7l20/MVgNYfW02//10dhH+/ckyrbBWjvmZuy4SQp/Wyptf/oGU0/lqsE1Sn0kjewo4tRdlFrDx/V6ZsUy82g4ITTSgEbfz09o2AAMBDAaw14g6NG9RdEDgjd3mrhAduuaFYRHJb3QeBi2lwM1EO7d6uzEggZXpu88YsMgv1Td/vQPHskpEWoI5hAwfjfDzkPZigj3x8NSeGKSDgKXJk1Uo2oAkk6mpbUA+WUxdnET/TyUtoSKfaa3/d02Iw6LdGcIyGuLtipggL/QI94WpHlKVzXTJkLQWQszcR+ZzmiNsl+0bE/6pb54ttS7P1Xo72QGhXff7c41llCCB5Cr0mPWOjzAqN8zU54KAgN614yk5otkXExGE+6+bpJMYRbMtsn8+T+bQM6Gs3Beo+0dheZLHENyRPZVl2pjeCAuiPE/b5URqtpCfEGgypxKNDhJWGxLgLflrlJm455pJmDg8oUVFL/13ObbtT5GQVIZZNslLlKFPfISajIdjpQwHhepZ6C37fdMhlJVXwdvLA+eP7Y1LzxuI/MJSPPX+EpHu8HB3kfm58fLR6vv0jaOt35kbSJKdiBA/9Xz/tGI7Nu5iqOzZsGDmWDIsk3mlJMLx8XLDrOlDJXzY2MKQXLajGQHCeRs1oBtuuLx1nUt6Ez/7eQOS0/Pg6OSAwT2jcPMVYyziQTZ2bJ3lvk6233cWs+rspx0QWn/6PgDQA8CF7QUIzwUPofWnre0WjQGnbYELgidj5C9UxCvHsstwqqACdQ0MbQT8PFzh7uIkAG32sCidEg2894M1x5GSXy6spRxTQXm13Degq79OPce2chGN6b8xILhNoDYqRnSzzBW2a2z4pzHro6Ot8Y7Sn052QGjX/f5cChntKOtP1Q8SqvADnC7NQmrnrdtxXHLrxg/pIYDv+6VbsWV/soSaqwpBzI0zRsPbww2fzd+gDjOsr2vAHXPGY1i/mDaH/dPy7di0J1FA8sn0/CbSHQfAw81FGDy7hvrhuXsvwehBTRqumoUsqfe99CPKKjmORgm/9PRwEYbRwX2i5d8j+8fi1lljtQAR26A3kqBTJf3w1cJN2HU4TSt/j/eTnKc1LUn2JSOrEIvW7EFRaSUiQ/xw9cXDW0h36DJAYUk5nnl/qbo97q9uri74z79moryqGnkFpYiKCDSKYVSzvb+2HcXPK3aInIeqMAXi8skDDdKXJMgmmDQkn7W91jfzb5PS8hAa5IPgAO/26kar7Xay/b7D2U9Jh+yAUIm1TL+WIPBdALMAHGovQBg3d4WwlDUvXAwnO5GH0PTpMH8NugANW9ElfdAWuCBBzPdbUhQLsKvqpBYj2T7LquskjIegzsvVCbFnPIStSTTcO28X9qYXq4ligr1dRPuQ8hJXj4g22MtnqCdN017UQNTUKVRCBmQtL9y5Hv5pLCA3/5PUeo2d6IDQ7vt9TU0Nlh0hEUjL0tlyCK25xgxti4fpr3/dLLl19IqRuZOyD/N+2yrEM0UllaKd98pDl4vkAklYNL1NBBezpg3Gpt1JLQTYSZTy8oOXtdmVLXuT8H+LN0vI57HkbBAo8d1OkMrQzvFDe+DDp6/SCcoozXDeTe8ip7BUcgZJljK4dxR8vdxx7zWTEN0l0OBw3Bf/u1z0DzULCWBee3iGePZUhV7MrxdvRnpOoUSupGTkC0EMbUJQGuDniZcfuEzL89eaAUjes3j1HtFODAvylpxFyX80Y6F8xLMfLpHQWpHVOOPVZS6gJXUQzTiENqvauPME5v+xE+Xl1bJGBveJwt1XTjDI/tbqYyfa761lEou1YweEFjNti4rDAOwCwKziPGIvIwEhM8Q1s8SpLr6huLgYvr6G5SL0fmYFKutbDtzDGTjySucJGbXe1BnWki5Q0i3YSzxUSTmlKK2uF48bdQBfuryvsIPqAn0MySRxya40bTp09kIfIYoKsDSxjBYjNb9SWOkMySFk/59bcgCrD2ejgaFHjhDWVoLTm8Y06fwZChgM8aQ1t5emlqSKCEYJK6g1vHDWAp6GrTjzXtVZxtZJDggdYr+vr6/Hrwdz7IDQvI+KurYPv/9LtOZUHiB6z3IKSgXcFZdWqhmdh/ePwzN3XYg3vvhdS+ycz9ybj87C/a/+iLq6RtH90wSMHz97TZs9p4fy1c9XITUzXwBhVl6xyGAQTA7oFYm3HputM0eRIZjvfrcG67YdRU5BmdrTRlB79YXD8NitTfmQ1ONbtHo3svNKxSM454KhOj2itMOxlCztEN7GRrz1+Gw1GQ77+tR7S9R6iCdSspGRUyw5isx3ZKH97r1mIob0adszaqHp1FktbbDwz90SkksP2pzpQ7VIdKzZF3O2xTXw2NsLtTzWlMfgHE8b08ecTZlUVyfZ700aY0e52Q4IrTMTtPNKAP8AeIW8LiYAwhcA/Lt5txUBwmdXoLLODgiNmfq2AJEu7xFBDr++Fp4Rd9fUznvxsr469QApJbFwVzrm7zyFQC83BHm5yovWEEIUzUM9QWFWSQVq6hoxJDoAU3qHSe5gc0ZM1Zj+OpqN/emFKCirRWl1nYSN8gv2hIQQvDyjn5jL0DBQbVs0CslMfnm16CDOGdZV+tDcXsm5ZcgprUKPUB/xSKqKPhBszDyaco81gKcp/TP2XkO9usbWb677OsEBocPs97W1tVh6mN8fWxa7h1D/iiSRytK/9qG8shrdokIwY/IgtVg8vUcPvT5fK0ySgGbDzuOSG+ioIXtBcfKVnz+AvUdP4Y9Nh4WAhSCIoYd//HMYZDqlRALz75jDRw9faKAPnr/3klY7WVBUJiQ7ecUV6BMXjkY0iGenS4gfRgyIa9VbtmDVTglnpXeREhMEs/TOUYOQoasL379bJCXo8Xv5sxUgMUuTrEUjPN1dhCmT4ZmaJS0zH2988Yf8icCP7KX+vh4YkNAV44d2xwXj+4kX9c2vflcDxCNJmcgvLoefjwf694iUe/m+OX9sH4wd0l3Gbxdy179Gjb1i+4EU/G/BhhaezoSYUDx4wxRjqzX7fZ1gvzf7mNurQjsgNM3ybwB4Uk8VvQFMB3AlgIkA6JszBRCa7CHs9cwKVOnwELo7AUdftXsIW5tPfR4UXV4xghwK1PO/mgnw/p7OeO6SvhKCqUmSMiDSV0BiYm4pknLKUVhegwAvV8SHeKF7qI9aR1BXH/kiJpBUkblEB3khQQ+Zi+aYMgorkV1SBV8PZ4T6uAsoJLModf5mDe2qZhVtDlJvGB3bgqRGVW9b41jEvmp4QRnmmphdijA/d8QFN+UyVNfVYVRcsORBGiLxYNrjbNt3G+LV7QgWascDQqfb7+2A0PgVSwmHVz5fxQAPASYEK9Q4pK4dCz1xDwsgPEtswj34j38OwcdLQ5evEfDycsOL916CqWP6CGCqqq4T8EfG0v3HMsQTRxDF31xdnTCiXxweumGyMGpqFrZJkpN9R9Px3bKtarBG0fY754zHQ3oO8pRmeO+7tZJjuO/oKZSeyYMc3i9WQB5zHV++/zJ8On+9tMO8ROYikjmUIZJsf+a0IbhgXN8WhqWA/PL1B7B07V4BmSr2VBK8XHvxCAkN1QSElBA5lHgagf5eAggZybL/WDoSYkPh6OiELiG+uP+688weBmr8iji37kzNyBfArxn6yvf20D7RuHXWuA4z2Hbc7zuMDazVETsgNM3SIQCC9FSRDGABgEtJLKlxLcVyCMt+AHCTCd1QzDI69a01SMyvbtFkjyA3rH58qgld6Zi3GhrmqK/3+jworXkIs4qqUKtB68ovsQmhPpjWN7wFuUvrnrUoEV9vzbt3PLMYP+04hfyyarg4O8vhJTbYC9/cMrzNfADN9njviZymfBKCr2BvN/FK3jAqRnL71h7NbtIdJJGChwt6R/hKf1rz4NHuKmkKXSCS9tYMmeX1B9KLEeLjKpIVBeVVkssYF+QlX9yV5BTqm0v77y0t0FnyI9vxgNDp9ns+q4sPZOtc7ueqh5AyCis2HAQJWxiOOHV0b6M8TZ/P34D9x9O17iWL5ksPXIrIsCbB+fe+W4PjKdkiHC8gsaYOBSXlOJKUJXsYWUgZaUGheAqq08uoWTRF7klAQpH32vp6fPvqLULyoVkIuF77fBVKK6qwbvsxIWLx9/FUyztQf2/T909oEaA0n/ivFm1S5zEWlVTgwIkM8RJGRwQI8Lpk0gARg6fUQ/KpPBF65xiovze4d7SkDIwe2A3XX6abYZOMoNRpbO5B7BLij7l3nK8VMsq+kR3Vy8NNciA5Pl8fDwztEyP5mGyLoLItL6l9HzfNAm9+9QeSTuU2rVUuBAcHvHjfJQgO0F57prVi2t3tuN+b1vFOeLcdEFpn0qKZ563RVBcAjK+YfUaCIt2EbigGhDd/tQXrTrQUK57UIxDf3DbahK50vFv1efWU9FifB6W1HMLM4ipsON606RIM0usWH+qFm0Y35eVpFn1taF6r2R4ZRQ+eLoa7izMCPJvCeQrKa9A92BNzhkcL8NT8kq2qR6u9xkbsTC1EYUUNwnzc4OriiLr6RkzsEYzTxVUoq64XwMgDDg+aBI2+7s5QyVDosmVb46GWYfMQ1LggT2SVVuNIZgmcHR2RWVQhIvcq8Kkkp1DJ3Nqv1S+D0lFs1AkOCB1mv7c1QEhw9t63q2Wv48cqeqcomXC0bedcAAAgAElEQVTbrLEtlm99fYMIzHt5NIXkNy+sJ+mUdrgt864evnEKBvTsKpczRPTLhZtwLCUbLs6OGNI7GldMHYRH31yIE6k5ki8YEuSLwb2i5L7m5ZXPVyIrt1hAWYVoCDqJ9+7dJ+e0IIL5+Ie/JV+RfV36117U1jXI/2doJT2E2bnF4skjGczz916M+CimsWqXX37fKULy9ODx/UFARmIXfx93uLm5IDTQV4hp+vWIBElhdh1KVV87dnB38RC2pcHH3Mkn3l7UIgyRwO65ey6WPDxqCJ7KLoSvp7uEtv6+8RCqampw8Php+ZBJzynJeTg2guT3n7rqnCBw6Sj7p2Y/aF+GKyefyhVP8Iypg0zSxbTEGDvBfm+JYbdLnXZA2C5mNylktHmPFQPCiW+sQWpRSw9hjL8b1s89tzyE+rx6KmMa4kU0xIOiK7+Mf/v3skM4nFmCIC83eLs7oXuI7vBPlbB8WVU9SiprxRNXU98AhpJO7h2uxfKp2Z9tyflgyKUwzLk7o6C8VjQI3V0cRZC+NW+hZnsEYXUNDSJkX1zFHEKKurtL2Cp1/Cb1DMaRzFLRKCQoZNjrlF5hbYax6rNZc3vx3/O2psLV2RH704uRW1oNJ0cH9Ovii2Afd5mujpZT2D5biGVa7Qz5kZ3wgGBKioBJ+72thYy++81q0X7TOvTWN+CdJ2ZryRks+2ufACOCMJKlXH/pKNE11CzU21v8524tjxv3xLcen6VXzoBAcdXGg8jOL5WcwHFD4nV+kNt5MBVvf/0nEtNyUVldg6qqWgQGeGHm1MHiiaN+oAqsUsOQgIvlj02HJMyUHh32Pz27SD42xnYJkjBSvgeWfnQ3EuK0x8TcxUff/AVJablyD72o7m7OKCipkHr9vD3O5Dd647yRPQUspmcVCuDkGEg2wpDRtsqLnyxHTkGJut8EkZdNHoRLJvZvcdu8ZVuxcXeigGeCeYJ0fjgdM7ibeKlob13g2DK7X1P+I21DIE/ZCnsOo6UsbXi9nXC/N3xwHexKOyBsnwlptwMCh9vr6RWo0qFM7+EIHHnt3MohNMTjZqgX0dDrdC0pQw/aKmH5lLxy+eKcV1oNN2cnTO4dgtr6RsSHeKsBmObYyGJ66HSJgCceBipr6unygZ+nC9ydnVFZW4drR0Th0fN7ab3kVO0dzy5FeU29EAc4OQB1jQx1coCHi5MA0uraetEipDSELoKY1h4jpTZrGlMhDp8uETDIPEYOiOBzbHfaoKFNj6Q5H2dDPhKYsz17XYZZoBMeENptv7c12YmXPl0hAu+apbn8wd4jafj4p3UShq4q3DfJiEntPFXh3sgcvz1HTkkoqL+vJ669ZARG9I8zbKEacBX3mDue/14AET1z9EB6uLtKSGpUeICEcJJ4hoXhqYmpObJ/k/Bl/Y4T4uVjqGihhI96iDePXk80NCKqSyAeuWGKVngnyXEeef0XHDmZKSGhDM2sqK6RdwWjQfgxkAQyBIAUdGdeH8NFCU7vuHK8QRqBDEX9bMEGpGXkw9XNGSMHxOHqC4frBFefzV+PBb/vknBRhuNSVJ5jio4IlNBREtK0Fp5qgHkVXZKeWYiPfvhLWGJp46iIADx68zSdrKqKKlZwMeeH7LThwb4dSvpBwRDMfmkn3O/NbgNrVWgHhNaytOXaUewhtCVhen0eKk6LSsydshAqr5yPmxNuHBOnkyxFkwSGpDDm/Iqo2ZfTRZUoKKuGm4sjEsJ8hXlTM2RSc2w8vKw/niveO0o21NTWy8ve3dkRdY3/3955wEdRbX/8l947AQKhh47SVVABAcGG0rEC7z199gb2Zy/PjvIX2/PZ9QkCgkhVOkrvvYSShJIC6T2b5P85N7vLbrLJzuzOzM5mzv18/HwkO3Pvme+9e/b+5t57DkRQltiwQEzs18puRc/S3tH0QmQUlCHQzxe5FGiAosXRkQJUi3xRJRWVQmxSYBtKbp8YG4qeLaPQ0UnQGuIrVQxb+mLmyqM4daFICFKKzlpmqkRkkD86J0SgX+sYNI0MFoFzLCuFjrbCuvt1kytk3W2vwZcIGQUcUMcGkMEnCLL8fUlJCZYcrZu+hnA2xjOEtOL0567jwvdZCgXNoATpFj/x8f/W4uDxs8g4n48LuUUikAqd13vo9mvE9tLaJSe/GLn5RUhsFmuNMKrU9522UFIqBoreSVEfaTWNCm0bpW2TZPt7T9LJkpok7m/+d7lYRSPRRuKJXuAdPpmOwsJSEdWUzi/S7o3qqirExUTgsh5txBk8y9nFuSt2YPXmw0Lwbdp9En5+Pkg5e0H4aKqLGFH+QsqhGBoUgCaxEYiKCEbbhCbo1a2VEGnXDpR2JpN+k+i3saHfxy17TwpBTM9DhUQhiaI2CbH41303IDQkADO/WyNWQ9u0iMN7T45DbLQ6ydNf/WSx2NJqsbequhpd2jXHI3cOVaq7662H+FM+y237TqG03ITYqFBMvvkK9OzSSvW29d6Awf29pt3DglBT3Ko0JmuCQBYYSRBKmdjP3ZaKH7akCjFIP4iWoCl3XtFGBHLRstiu+lGE0vOF5aJ5CrRiibxpEUK1n620vAIlFVUivUNyRiGC/f1QUF4pRB296U2IDkXruBA8OqwTereuCYpgac8SUMYHPjhfVIaCEpOIrkdbTiurgHJTlVg5DA3yE0KtRVQwLm0VI1bsbFct3WVFz/TAjztw+FyBtS9IiMaFB+KytrHYfToPKWL11E9y4BxXbJK61diVuqXcI2XcSqmnMV5j8AmCLH9fWlqKxUdyHA6DxigIKVH8+9+sFIEyqiurEBkZgn+MvUoEl7GU//y8AT8v3ya2c1rO0pEYopx/tEVTy0JbOCkICyUF37j7uBBlVCJCg4QYoH9//MJtVpFC19N20aLScgzu2wltE+Ow92gabpv+pfgbbVUlwUgcmkSHIzwsCFdc2h6fvXyH8KdfzN2APUdqQhbQdtXikjKkpeeIs5YUGIfEMbVZYTIhPDRYrA5SvSRQaiKR+mPY5V0w6Yb+Iufhtn0paJ/YBN2SElx6MUq/tdff95E4R0nn2QIDA0R99N+doy7HXc98bRWLdG2T6Ais/OoxxVfPSIg/8sbsOuc2SZjTyrHaZdXmw5izdJvd9mTqD3oZQH3i7aWwuOaIEo0nucXg/l4uLreuZ0HoFj5d3CxrgkAWG0kQ0vM6W6H6eVsqZq1OFiLDUuhw+0NDkzCxP8WH0K7YChFLGgb4QEQljTWvENoGcbF9NkpNQYVSN/y4NQUp54thqqpGWUXNG+WWMSHix75LQiQ+uaNPrVyAvjhwJg+pOZS3kLaIVplzVNH2oWoyAaFB/vCn8OvmRPc9WkZZI5GSeKY3q9S2u+khdqXmYOaqoygtr0JESIDIw0htJkQFYdHuc5r0k5StxmqOCk8LUjWfzd2tuAafIMjy92VlZfjtcN0AYtS/jVEQWsbtmYwcsfWuU9tmdSb5B46dwcTpX4hLyS/6+fjC398Xd4+/CvdNosxQ2pZPZq/FnkNpOHQi3bxlEuie1EKIMNo6+fTd1zk0iPIgfv/bZhEYZtu+kzhyKhMlpWWgla3QkGA0i4sQ4rBDq3j8fdyVuPmaniJIzCez14kVSFp1W73lKErp7GJZhfidJIFM/p5WCSlaNQVPpd8MWqkkm9olNhGrr7SSumrzIREEh4LbUKqIaVOG12EthSQF5dm467hYtQwNCURVZRWu7tcRf2w6hN0H0+BjXj2kusrKTPjg2Qm47qqavLhKFRKbFAiIfvdtCyWif/lBChCvbvnwu1VITs20a4TE+mOTh1sDGKlrgTq10xZoCoZEL2hoEkFjkVbiqZ+lFoP7e6mYFLmOBaEiGD1aiawJAlna8bkldmkQLNYH+ALHGtkZQik9QyuEn68/gdzicgT50w8hEBUSKNItjHdzhVDu5Nd2ZYi2alIaBiqXtooSQq2+1bjaK0plFSbQllPaellRSWfw6LyMT03ggbgwPDq8k9gOa3sfbTel9qjdhMggHD9fjMIyk1gZrHmTDvjTBKGaVg790L5JGNrFh4s68krKUVpRJc4uhgT6oV/bWDwwpINLb43tn8UX6XmlYqWSnv/UBQp+YO+2+reNwVvjLpXS1ZKvkbLVWHJlLlzoaUHqgsmSblFi5dPgEwRZ/t5oZwilDMIl6/Zi2tvzRPAUSqkQHR4iEqF3bNsUT//DsfiSUi9dQytNc5ZuFxPg0OBAjLyqm9NtfyRGvv11E7bvO4nk1AsIDQ0U6SQSm0WLyKRx9WyR/Pintdh35LRVhJEAPnn6vDhfGELCihLJhwSKvHIWYUnfv+9+3SS2ix45lS62zFI7JCJPpJ6vOU9ofg4SgRSghj6jiM+DLuuE2MhQFApuQOaFAtDvTFx0mLB3wnV9MWJgN6morNfRyiAJ2/3HzgpRSLtUKE3H3OU7QLkKbd09neWkc33/GK98nryFq3Zj6bp91lU66supowdiYO8Osp9J7g10lnLf0TO1UpyU46UHbkLrFs4ym8ltTbvrZ36/GkdOptut8lLwpofvkL4N1+D+XrvOqjOz0rRpbkwhArImCNRm/1eXIau4blSZ+FBfbHvxeoXM8o5q6AfyxV/3Y92RTFRV+6DUVInokABckhiJqQPb10kLIeepXJ38WhLM70zJQe/W0ejYLAInzhcjqWm4XZRRW1scCRhK6n4utxTp+aU1qSLMKS+6tYhE3zax1hyIFtH605ZUkXKCtmeS+KOoo5kFZSguN4mAAxTcJiTAF3klFWLljlYIafXuSEYeTmeXijfHoYGUWqMaoQH+eH1MD+vWVDnc6FqyiZ7pi/XHUVxRieaRIaKdE5nFaBJB205qRCG90X14aEdM6K/s1l5X+07uc9Z3vacFqVLPUbseJVY+DT5BkOXvKysrsWC//cqDpU8a8wphfeOXxAdF2Vy//Zg1KXBVZbUIIDL5lgGYdH0/t4b+u1/9LsSg5QwjCSo6g0ZbKh0VsuejH9dgz5E0nM3IRXBwIO4edyX6X9JOBBap7/wdrQ4+9uYcu9Uzqp9W7A4mnxVnzWl7Hj0XbT2klZnHp1yMIE75Amd8s1IE4KHtquTvKAn92axcFNMZ8upqBAcHoKCwDMWlFWgaG44hl3USwXX2J59B2rkcsW0zMjxEHC2gtBJjR/TGA7cOEY9Jq48rNx8W0amHXt5F0ooQnR18edZvQqiTTXuPpOH46QsiiqptWf/dE6oFevlzZzK27T0FXz8fEWX10k416UXULmnnsvHv/ywTL16p0BGP1s1j8Ny9N6jdtKr1P/zG7Jr8hjaFnnHms5Mkt2twfy+ZkxIX8gqhEhQ9W4esCQKZOvD15ThbaL81gv7eMtwPfz3v3htSz6KQ37ol7cLxzCJrOgUSGYM6xeO10T1cWuGyWOHK5NciRJIzC0BBbrKLytC1eSRevaV7g+cm6ltRahIWgP1n80VQGMp/SGKPVtoc5Q6sbS/Zkp5fjLLyKqTnl9U4dl8fFJdVisAyJAj3n8lHRn4JSk0120opMirlQaQJxaieLTDt2s4Xt+zK3E5a2x4SymsOZ4ltTGFB/igqMyEyxB9vjb1UCE8lg/tQHzrbaix/tEm/w9OCVLql8q5UYuXT4BMEWf7eZDJh4YEsh51kREF4LCUDb3y2FPlFZTielilefNF3LbFZDBbOut9pOomGRjutZj0z45c6OfOSWjd1mIOQ6lqwchfmLNuGwyczrOcHKdDLt/+eiks71/+Si84IPvbmz1YBYbErMjxYnB2kFA4kqoS4MFXi0buG1UmrsWbLYfy0xP7cGtXbrmUTbNx9AlVVlSgoKgOdTe/WgVIn+whm5eUVOHU2RwQqI58bHxshbH/y7yMwZfQA7DqYiv/M3SDe2VHU0oAAfzw+eZg1sE19DH9auhXrtx2zPhP5+w07jokdKZSOg7a/9unWGjcOvgR3jLq80eUmpC2jv63ZCzpvR+lDJl7f163xKM8zq3M1bcOlMWVbKIDSO09IP5dpcH+vTsfUUysLQk1xq9KYrAkCWdDjxSUwxyqxMyg8ENj/auNKO+GM+MUJarVIp0DbJkk4jejWzO3toq5Mfi1RP49nFVmD3JBAHdw5Hq/e4lig0oRm7vY0zNmehtiwILFqRz/UIiLpFW2w8fgFJGcVgHIbUsCZbgmReOXmugLTkQhpHx+OAe1jsfpQBjILy9E8MghDOjcV9a8+nIn9Z/KQmV+GlOxiMUGgCRblTgz088GoXi3w+PBOdZLPSw1C44gfTRLojAulyfDzo7OVkeKcpNQ6nY0HPX3uSUGqFgclVj4NPkGQ5e95y6j9SKYoks99uFCcoaNIzOdzCsT/05m4h92MJpl69gJemvUbwmoFzqBVuvq2or795XL8umoPiktrtmpSodW/4QO6YOZzt9b5GpL/m710uwgMs33/Sfj7+yOpdbzwxxUVJgy5rDPGj+iLd79agbXbjgpBNqB3e3EOMSzEPqAH1UWrk5atiiS4SIyQqCwpLRdBd267oR/+NvZKZOcV469dyUKwHDmZISKTUjRMWh2krbFRESH48rW70KdbGzw/81dxFtK2JDaNwTP/bPhl8//9sApHT9mvZlOwmwG9apLX03k+S9C3hPhokeiei74J0LbflZsOipcCVGgb7sgru2PciIZzWdo+lcH9vaYdzIJQU9yqNCZrgkAWdH9hCYrsX9oIw8IDgP2vGcvJKjFBra9XXambRNCKgxkiOEtNmPRqcTYvwNcHD1zTQUQ9tV0Js64oZhWAVjkpiXxMWCAowAyliLh/SAfxBvzFXw/gUHq+EIyUUsPyWe1VtdpBajYmn8fx84UOxaRFsJ0vKMW2lGzQeXwShZS6ollkMN4Y00MkTv5+0ymxdchSbFNnNPSNqI/f5e1iseVktkt1qvIN5EolE1Bi5dPgEwRZ/p63jNYdmiIRfEqmdQWNhBCtbllSM0gezLUuJIH1zIwFduKOJsC3DO0lVrUcFQq48eX8P63bVym4C22ZpIAw/5w4CJNvHmC33ZLOGm7cmSwm2PSikMQcbQ3t3K45enVOxNQxA8WW1fe//sManZJW76g+Sj/haBcFCdlTZ7OFwExOOw/KI0grjKVlJgQF+OGeSYNw74SrsXD1bvzx10GxtfRMZo74nFZ/YqPDRG7GD56eKAJ+0TZBCtJjWyhIzXtPTWgQ7aI1e7B47V67XJAkjju0jhcC1NZ2EtCvPjQKic1jXe0uvk8DAuTvF6/bJ4IZUf/169EGN1wtb+eVwf29Br10sQkWhJriVqUxWRMEsuCSl5aioMx+Xzf9PSLIB/te8e4963IJKzFBra9NV+omEfTa4gPILaZ8VNUiDx+9yY4ODUSzqCAM69KsTh7Bi4KrZpWTVgEn9WtlFY+ubF2lZ3K2nZbyMda0XROhlBLJUzRQSm0xrEtzPHBNEubvOI0dqXXzoFlSZzTUX/XxaxoR5HKdcscHX688AXdXPg0+QZDl73mFsO74JZHxy8pdIqojrW6RWKNopEoUqvOr+X8hI7sAQQH+IqALRfisbzs7nR0b/9jnIu0DvSi7kFMotkI2axKBft3bolmTSLx4/43W+x9/6+c6kTBJtFFqBEuexVn/W4NDx8/ZC6iSmgAlbVrWH6DkxY8WiSAum/ecEFv+qZBY7t2lFW4fdTkuu6Qtnp2xQAQI2X34NAqLS8XLxh5JLTF17EBcd1V38W9agSVRa1taNI3Gc/9sOD4B9cs7X63AidPnERjgJwLaXH91d5w6c0H8zbYUFZfhqX+MrLMNVok+5Dr0RcDg/l7TzmBBqCluVRqTNUEgC7o9vwRCb9Qqof7AwdeNtUJICNydoDoTNXIS2ZMtLyzcj/VHs1BZDeQVl4sfx6hgf5HOITLYH3cNaCsihFKRsi1VyjWOnoHu+/1gBo5lFoigNJYSHeqPF27qLgLcfLr2OI5nFQpRWBMN1A//HNRe2EeTIFdWSW1tcdQ3F4Wo/aqjo3ORqnzjuFKPEjD4BEGWv2dBqP1QJZ9F0TvDQgIREuw8vP7vfx3AG58vw9nMXBFlk1b8urRLQNO4CJGonQShRcg9+uYcIdJsC63GffjMxSAdH3xbk4fRtlD4f1oFpQiP9ZX3v/4duw6lYffhNOvqKUX8vKJXO3Ro1RRP/O1aUL48WsnLKygWLyrpfOTjU4YhJrIm5REVEpRf/7IRfrRKKA5pAo9OHiZWMZ0VYrf3yBmknLsgBGjzJlFYveUwZtc660hi+50nxtU5Q+msfv7c+wgY3N9r2mEsCDXFrUpjsiYIZMFlr61AZlFdRdg0zB9bXxipipFcqXQCtPXopUUHsOHoeXE+LsDPR5zL65pQE3XOdnVNiuCSco0j6+xXK2uuINtImI7s3lxEKXUmpl1ZJXVGSo06nbXJn+uHgMEnCLL8PW8Z1c+4bciSC7mFePzNucjIzhMBbixCsraQo/QEtDpnjWJaWSVWIe+ZcLW1+g07kkVqCUoibyn0/+9Mb1hA0erma58twY79KUIQkvBs1TxG5B7s2j4BD91xjaiOVvIycwpErkLaWtoiPrrOyiNFL1256ZDYQjriyu7ijKGrhfz9j4u3YvOekyJnYtPYCEwdPQCdJAhMV9vk+/RDwOD+XtOOYEGoKW5VGpM1QSALxny0HrvOFNQxpnfLCCx4eJAqRrpSqVVsyIxO6UpberunoUAxtRPTX1yl8xPbjmoHWHFVQNWcPaSUHFnih53EIAlTOp84ZWA7u5QcDfWVM9HoCns16nTFDr5HewIGnyDI8vfeJAgPJJ/F/D92ITu3SAQQmTiyj6Em/eu3H8X3v20RW03rE3J0Zu+LuX/i0Ml0EdW5W4cE3DP+aut5QctLOwoWQyt1oSFBIn3F38YMFKt5zkrGhTw88sYcpJ/PQ/P4aJHygcbQk38faXfGklYK563YYd2+2rV9cxHJ1BLZ1Fk7rnxOz15UUo6YyFDFI0q7Yg/fow0Bg/t7bSCbW2FBqCluVRqTNUEgC0bOWIMjmZTg2750aRqK5dNq3gJ6urgqYjxtt5LtS2XgTBzR57TaR5FCfXx9cE3nptYtnc7sJRHoLCCNVDudtcWfMwEpBAw+QZDl771FEObkF+FfHy60S61Dp9jemT62TnRMKWPEG68hPzpn2XYRzZMCttCW0fqEHK3eUYRPy7lBy/PSiiJFGE09lyPSRgQFBeC+iYPQq2tryUhoBXDuiu04nnZebF+tfcZSrFq+O88uByIFzxk1pCdGXXOp5Hb4QiYghYDB/b0URIpdw4JQMZQeq0jWBIGsHPT2KqTm2B/6pr+3iQnGuqeHeexBbBt2NRCKLoyXYITU1U9nYq+hpixC8D/rjqPEVJPcnYK+yE3R4MyGxt5XErqTL9GQgMEnCLL8vbfkIZy7fDvWbD1iFTgU1IREzw2Deogond5eaEsobXuktBe0wjV2eO96o5qSICspK0dEWLDslTA6B7jizwPwD/AX2z1pZ0dIUCDenj6mwTy2cvjuPJCKj39aU+d8ZIdW8Xh8ynA5VfG1TMApAYP7e6d8lLyABaGSND1Tl6wJQo0gXInUnLI61upJEFoCoYgD+kXlIicfbVek/ICUesGbixYrapY2tp3KxqkLReJgv+UcIolC28A07rJ0NWiNVFHsrn18f+MiYPAJgix/74kVQvpenzpzXpxzo7QA9UXYtB2VlJx93bZjMFVW4tCJdBQU1rywvLpvEmY+N0kxMeOJbwIlhqeE9SVlFVYWlArijcdusQvG4q5tFHzl6fd+QbnJJGK5+Pn64NIuifD39cWb08aKs3dKlHNZuXjho0UIDgywVkcCvp+IqHpVvU1Q5NFvF25CWnq2WPUdcWU3kf+RCxNoiIDB/b2mg4MFoaa4VWlM1gSBLJj6341Ym5xTx5hrkmLw9d0DFTXS1Ul/fQnah3SOxyv1JGhX1HCFKnP0/PVFyVRSpFlW7c7klCCrsCbpsSUgTJPwILvANO4+qtSgNdT+PEpDkZKDPq2jcb6wHCfOF4l8go7OPrprF9/fOAkYfIIgy9+T/5m/N93hQBjfs/6Ik66OnHOZufjw+9XIzM4H4ANKyv7E1GsRGd5wUBFaQaMto/uPnUVBcakQTmR7n26tRSLrW2/o76pJmt5HZ+/++OsQKCgz2R0fG4ENO47hu4WbxPZNSyFfeFWfJNx+0+WK2Ef1PfnefGzde0rwo0L8osJDcEmnlnj/qQkinYVShfIn7jmcJp6JxK2fny9efvAmxEWHW5v4ZsEmzPt9u1jpvfzSdiLXYlZ2oUhbQYWilD5y5zXo0bGlUmZxPY2QgMH9vaY9yoJQU9yqNCZrgkAWTJu9E7/sPlfHmLG9EjDj1j6KGenOShjda0m/IAKaVFchMjgAHZqGYfKAdta0C4oZq0JF9T2/Enn0nAltS8qIs7klYoU1NNBPvDUODfBDUKCvXZ5Cdx9dSj/ThGXq19tw6nyR2MZUWFqOavhgWJemInm9mCCYKhVduXT3ufh+fRIw+ARBlr+n790v+zLqdCR948apIAhf+2QJ0i/kXVwJq65Gl3bN8cidQ50Opr92Hsdjb80BnUej1af2rZoIgREdHoLXHxvt9H5PX7B170l8Of8vkZSdxE9VZRXuv3UwTmfk4re1e+DvdzFNjkXs/qOBFTXb56FonkvW7UNRSRloa+b4EX3tAsksXLULr368BCXlFcgvLEV0RIiwo7CoDH26tUKf7m0wYmA39O3eRhFMNK4osMyhE+cQHRGGUddcYrfa+enstZj14zoEBNSkKyopKYefnx+GXtHZrv1ObZrikbv0cUxFETBcieIEDO7vFefZUIUsCDXFrUpjsiYIZMF1H67F4fSiOsZ0aR6G5Y8NUcxId8+WWURNfmmFEINx4ZTTyT7tgmLGqlBRfc9/ebtYbDmZLVbGLIXEkNQ8es4EmL2Y9kV2Ubl4W0yF8gQ2iwwWwjopPgDwqRAAACAASURBVMIuyb07CJydM/x5WypmrU4WYpAKbQEuKTehe8sotI+/+FZZSsJ6qXY6E81S6+Hr9EXA4BMEWf5eyzOEdPbt4TdmCyFiW0KCAkTidGeFokhS4nUfH1/LOyJxS2xUGF59+GZnt3v88+dnLkRuQYmdHbRNk87VPfX+fPj5XuRSWlaBZ+65TlLkzxNpWXj3q9+tOfdoC2pSG8oLOEK0tefIaXz0w2rsPpQGU1WVSAtRUkoCzBehwUG4qm+S4FlhqsR9kwaht4wAM65CHf73D3A+t/Di71u5Sfybzk7aRiKllBbTp17rajPW+8jXL1m/Dxt3HhfP2bFNM0wZfQWCbLa1ut0IV+ARAgb395oyZ0GoKW5VGpM1QSALBr+9CikOgsq0jQnGWgWDyrh6tsxCSepWRFWoKlBpfc9P2yWzCsrMCd3lb5d0JrTrbrf1QU5RmTiH06d1jFVYa7ki9/S8PdiekmulWlpeibzSCjSLDMJl7eLE3+WIYmfd40w0O7ufP9cvAYNPEGT5ey0FIX3npr8zV2wFtC1x0WF45SFpgo62Iu5PPmNdTSsvN2HU0J4YNUTf0Svp2R989X/w9bMXwyTKZj47CVv3ncS8FTtB0VTDQ4Nx7cCuuGHQJZK+ZB/9uBqHT6TbncWk84j/fmw0msVF4v9+WC3yAaZn5eFoSqYQf2VlJnp3ioG92ovUE5bSpkWsSCGhdrnqjndQWHIxTgHxST9fgJsG97AGoykrN+Gum6/AoH4d3TZn+Z8HMP+PndaUHbRNtVPbZhzkxm2ynq/A4P5e0w5gQagpblUakzVBIAu0ijLqrqCTM6nX42pQQ89/aWIU6CxhcmYhkpqGo2dilKTgC9R/zoR27YA8BSUVKCgzITzI3241jupSckWuodFde4VQBAsqLEOHpuHo3DxS8TOEzkSzKt9ErlQTAgafIMjy91oKQur8hat2Y+m6fQg0J0Wn7Z806b+6r7RJP61uUVL1w6cyEOjvi/6XtMMtQ3vW8Y20XXHdtqNieymtMk25ZYCiZ+RcGcgvf/wbzudcXBWjOhLio/Cve28Q1dE2y/yiUoSHBMnK1/feV7/j1NkLdiYVFpXiX/fdIFbCZv1vjRCMVChx+9nMPJSWVyAyLASJzWPs7qOchM/fd6MrjyfrninPfY2dB1Otq6LVVdUIDw/C8Cu6IuN8PoKDAnFVnw4YN6KP5N+9hgx45ZPFyMq2z61MK6kznp6I0BDaWcTFWwkY3N9r2m0sCDXFrUpjsiYIZMG4jzdgRxod+rcv/VpHYd4D9UcJk2u9HEFXX93OtiLSfUq0I/fZpFyvll3OhLajz8/lFcMHPmgedTG4g5Ircs541D5DSNt62sSF4vFrO+HE+WLZothZe85Es7P7+XP9EjD4BEGWv6fv3cJ9Gaiq1Z20jjVWhTOE1MyfO5OxZc8JcWbsmss6o2eXREUHE+Xp+3bhZgQG1Gw/r6yqQrsWTfDU3eqvfDX0IIeOn8Osn9ai0lQpzhAGBvjj8cnD6k0vIRXK0vX78OuqPXZnBgP9/fHOE2OFsDyYfBYffLcKQWYRTr87FMWTgrcUFl9cpauoMGHkVd0x9lrl4gTU9wy5+cW446kvcfLMBRF0Jj42HLP+dSt6dmkF2i5LfVc7h6JUHo6ue+mjRbiQZ38Mhl4WUDAdSt/BxXsJGNzfa9pxLAg1xa1KY7ImCGTBO8sO4JN1p+oY8+Dgtnjy+u6KGilF0LnboJ5Xg9R4fmdC09Hn7ZuEieAtJ7IKPRbV0xJldGdqrogyOr5voqKTAttx5Ew0uzvm+H7PETD4BEGWvxdnq/alo7TmCLG1RAb6YETX5p7rRDdafuuLZSJQi22hLZLvPjUO0RGhbtTs/q0U9GXt1qPi/N7gfh3r5OpzpQXym/+d9xd2HEwBbaGNiwnH1NED7KJzbtiRjN83HgCldmjZNBpTRw8UuQw/n7MBFPk0IMAfvTon4p8Tr1bN5zp6tuNpWaBE9t2TElRtd8HKXVi+4YBVNFMaDOJgWZ11hTvfow8CBvf3mnYCC0JNcavSmKwJAlkwZ2sKnl+4HxU2r40pGNjro3tg0mXKRCFT5UnrqVSPq0Fqb2F1JjQdfU74XN2mqlZ/qsXJmWhW63m4XvUJGHyCIMvf0/dg6cFMlJmqrKuEFPU/xN8X13drpn5nqdDCG58vxbmsPLuaS0or8Na0MSLNgyfKroOpWLJhP/ILStCiaTQm33I5YqMuBstSwiYSe7TlNKFJpFNxRSKSCqXvyM4rEsnp9bB1ksTpgpW7kVdQgtYJMWLLqBKBX2ic/7BoC7YfTAGthLZLjMe9E692mu5EiX7hOtQlYHB/ry7cWrWzINQUtyqNyZogkAXvrziM7zenoryyCvQmzdfHB4F+vrjritaYPrKLKkY6qlQpMaC31SA9iRGlGKsxKNTm5Ew0q/FMXKf6BAw+QZDl70kYrDicJXy9yfwCkIKAhgT4YQSlfNGwUK5BSkx+JjNXbOO7/uoeIj+d3LJ43T78tvriFkr6nlsC15AA0rqknLmAVz9dLFYFaZso2UOBY958fLRT4aa0rRRd9PO5G3DsVIawp2enREwdM9AaoVTp9uTURwF1Xvi/RYIP9ZOpsgot4qPwwv03KnKOkGyhui15EeXYxtfql4DB/b2mHaO999T08QzRmKwJAhGZ8ccRLNx1GnklJlC0x+BAP0SF+GNM70Q8fq19niC1CCopBpSsS4nn3ZWag5mrjqKkvAqRIQGICwtERWWV5jn29MalNls9b/VVYhxwHeoQMPgEQZa/Jx/w++EMFJVXX1whBBAZ7IvhnbVbISRh+q+ZvyK/sMQ6+adopJS0vlM7eXbQM/24eCu27TsFSlVBgVMonUKTGO1XBykIzuRnvsKB42fFuUEKGNM9qYXI+frY5GEiKbyW5YNvV+JYSoZViNJq2dX9OuLOUVdoaYbDtn5YtBkbd5+wJqaniyha6vQpw9EtqYXH7XNkAPUvncUkcc3FMwQM7u81hc6CUFPcqjQma4JAFuw4dQF3fbkVJRVVIkQ1/XiFBPjih39chj5ta1IAqF2UFgN6WQ0iOx74cQcOnysQP8o0ESJR2DUhEv3axopzc1oVpRkrbbcet/rW94x6XmlVul/0Xp/BJwiy/f2yA+dQZLLv1eggXwzvIk+IuTMuKPDJ+9/8YXemjr5TJJ4euM213LeUWsBUWSlW5ShQCQVVUTJQiZTn/fbXTfhq3p/IKyoVl1sCunRr3xz33ToY/Xq0rVMNXUO5BYtLy9G1fYKsiKMN2UTi5dE359gJLrqeROpb08dKeRxVr/nkp7U4ePycXRsU+OX2Gy/DkMu0eREt9QFpe+5nc9bj5OksIQZ7d2klVlq1Hl9S7W3M1xnc32vatSwINcWtSmOyJwh0hvDFRQfFlg3KVUSvNv39fPHqzd00O0Oolhjw9MSdRNjMlUdx6kIRfH1q3iqSKGzTJBSPD++Mnq2iHU4QxNm+jAIkNYuQlYKioRGlFmNno1hqH+htq29DYvDTtcddzhvpjBd/Lo+AwScIsvw9+Z7fDmSAXL3w9eYS6OeDm7prF1Rm75HT+PC7lXY58cgUyhX3yJ1D5Q0Am6spsucPi7fgfHYhwsOCMHxAV7EVVavy3AcLRCTN/cfOws+vBjAxpzQbHz4zyS4yKH1GQWfe+XIFTqfnorq6CtGRobhv4iB0aud+X1CahUff/FnUS7/tAf5+YjU2KjwYbzw2RjUktE11zrLtSEvPQWRYMMZc2wutE+q+WN60+zi+mv8XgoICrLaQqH/3yfEID72YK1E1Q2VU/NZ/lyP1XLY4TkOFVlqvubwLbr2hv4xa+FIlCBjc3yuBUHIdLAglo9LthbImCPQUd3+zFZtPZsNUVY3Kqmr4+frA39cHA9rH4Ysp2jg8NcSAHrZI1oiwHBw8m4/80gohCquqq9C1eQQ+vqNvnbMSatpsSVBfUFaJ/JIKsVIZEeSHKQPbORSmSoxwOc8j51olbHO1Dr2vtLr6XN56n8EnCLL8fWVlJRYfzEI16GxVTY/7+kJMdG/u4b4IkTqGSKw8PeMXUDJyS6H/f+C2wejdtbXUauyuo+2iT7w7X6zKWQqtFE7TcAuiJfdgytlsnM3MQYWpCiFBAfjq9cno3rHudtHP5qzD3iNn7FbxIsND8Majt7h9jo443PPC99h24JTY9RMcFICkxHiMv66PaqkmqM2XP6YcgPli9Yz+TW2/8tCoOgF+6LNvFm7E5j0nxYouPff4EX0wuH8nl/pfrZtI4D7+1s91Vm6jI0Lw+qOj1WqW662HgMH9vabjggWhprhVaUzWBIEseGrubizcfRZV1bQ4WC3y01HkudG9WuCdCb1UMbJ2pWqIAT1M3C/a4IsLheVCFFIAh0eHdUSv1vZJgomJmjY7yv3XtkkYvvlbf9W2vsh9HjlbfS1pK3ak5KBvmxhV01bYjldPrbRq8kX0wkYMPkGQ5e/p+7X4YAbKTPZ5J8ICtI8ymnL2Ar5ZuAnnMvMQHhqIoVd0wQ2DLnF5BP65Ixnf/rrRLkolPe8lnRLFmUItyqrNhzF76TaxXZXapoTwV/Rsj3vGX+2w+X99uAB5hTXbS22F8ftPjXc7IubqLYfx429bkXruAnLyi4XATGwajXkz7xU5IdUoYivwtysRHOhvFbQUqO6yHm3FFktHhc6Rns8pRMtm0Q1GGN206wQ+mb0WlLN2zPBemHS9Ni+r6UXD42/NrbP1Ni4qDK88fLMaGLnOBggY3N9rOjZYEGqKW5XGZE0QyILZW1Lwr4X7hSC0nCEkQfjGmB64VcO0E3LEgBRyepi4yxW6atosVgg3nURhaaUQppHBAQgP9sPkAe3Qy8HWVSmMnV1Dz/P7wQzrimRceKDYq2YRcM7ur+9zT4hbiy1qrGa7yoHvAww+QZDl78kfLT2YgRIdCELL2KXVQjqX5W5E0B0HUvDpT+sQHHxxCyI9b59urfGPcVdp9lVZu/UI/tyZLFYHe3RsgXHX9q73hdub/1kmoqzaFlqtpQTqAQHuibb3vv4dp85csKubEtM/f+8NSGqjTkTZbxZsxEc/rhFnOSl9RNuWcWgaG4Gu7ZvjwduvcbkPfl6+Da99ulSsZPv4+oDOR064ri9efnCUy3XKuXHWj2uwP/kM/M1CuqzChLHDeuP6QdptR5Zjb2O+1uD+XtOuZUGoKW5VGpM1QSAL3v/9ML796yQKy2pyU9FJt/AgX0y5sh2mj9Au7YTSNPQycZcqdOm6udvTMGd7GuLCgmART+WmSkwe0NbtbZ1qik1HfUfP88LC/Vh/NEucX6GtsiRCOzQNw5QB7m1T/XlbKmatThb1Wgq9OX5oaBIm9ndty5nU8SdX5Eutl69zjYDBJwiy/D29SFl8IEPknLWsEdKPfrAfcGOPBNc6QCd30fmzZz9YIM7lWcQlCYcX778RLZvX3Y3habM37zkhcuVt3nsCUeEh4vwkCakRV3bHhJF93TZv5nercCw1064eClzz2iO3iCTtShcKvDLtrZ+xdX+KeLFMhVI+9OzcUohBWil1tYy8ZyYyLuTb3R7o74eN/3sK/v7+rlYr+T4aRz8s3ozDJ9IR4O+PK3q1w42DLnH7JYZkA/hCKwGD+3tNRwILQk1xq9KYrAkCWfDusoP48q8UkZvKHFNG5CG8++q2eGJkV1WM1KJSb5q4W2xNzizA8awi5BSVIyYsUIinpPgI3D+kg9s/PloLZMuZRXoeOrNIZ0pItA3uHI9Xb+nh1vM8PW8PtqfYv1mnMdW/bQzeGnep6sNLqshX3RBugFcIgby8vDxERpLrd14W7jtnzUFouTrAF7jlEu8WhPQslNvwu183i0T1dMZr1DU9NU/1YGFKAolW5JrFRdRZIdx5MBWfz1kvVgEpeX3KuWzERITiqXtGYkDP9m75Rkv7B5PP4cPvVyHQvNJILwMS4qNFnj81ysJVu7HizwM4n1uI42lZKCszwc/fF1f3ScKs529z65kG3vY2isvK7cw2maqw9tvpaBITrsbjcJ06JcCCULuOYUGoHWu1WpItCN9bfgifrTuBSnGGsCb4HAVIu29wezxxnfcKQgKsl4m7s0ibtmKNrr1QVI7sojJM6tcKE/q1cuvH1DLQtBbIlhVJy/MUlFQgIiQAI7o1E8/kTqlvhfDhoR0xob97dbtjF9+rPQGDTxBk+XsSBYsOZNQRhEF+wCgvXyHUfuQ5bpEY/+fnDdh1OA2UWzE+Jhx/H3slurS/GLTH0XZOCqzy9vSxiItWTuBs35+CFX8dQHFJGdq0aII7R12O0BDatq98+W3NXixZv1dsq6SVwZKycgT4+WL4gG6YeH0/txoc98hnSE7NFNtFLYVWVdd8M0218+9uGcw3q0bA4P5eNa6OKmZBqCluVRqTNUEgC56cuwvzd9YElbEU8rvj+1BQmd6qGGmkSqUIMa22c8oRyM5ErLM+VHNF0pNnCJ09N3+uLQGDTxBk+Xv6Ts/fm16ng+iHf1xP718h1HbkOW5t0Zo9WLxmLwIDL25lpAif70wfaxUvb36xDGcy7Hc4FJWUi+iiLVTYzimFy5n0HHy3qGZ1NTIiBNdf3R1X9k6Scqu4prikHE+9N98unQkJwzceuwUxkWGS63F0IeX/u/Ppr5GdWyTqJ1H770duwUgNU4q49QB8s2IEDO7vFeMopSIWhFIo6fsaWRMEepS/fbUZa47aHz6nvw/tHIev/naFvp/WC6yTEmlTTfHkCiIpItZZvUrU0VAbliijO1Nz0ad1tGZRRt0Vys648efyCBh8giDL31PaiQX77c+VWWiPZ0Eob+DVc/Xb/10ucvDZlsKiUrzy0M1o07ImH9+Sdfvw66rdVtFIPoXSLvz7sdGK7AaR+yAiDcj7v4ioqJbzl+XllXj6npHo0CpecnW0ikc5CClqaFx0GMYM743uSS0k39/QhSaTCYvW7ENhcSnGj+ir2kqnrQ3UL0vW78OWPSfFam+3Ds1x+42Xux3wRxEgBq3E4P5e015nQagpblUakzVBIAtGzliDI5nFdYzp0jQUy6e5HhlMlafzwkqlrP6pLZ7kYpMiYqXUKWdFUkp9nr5Gb/3kaR56aN/gEwRZ/r4+QcgrhMqN5A+/W4nk1Cy7CmtvByU/8t2vm7Btf4rIxZgQH4l7JwzyWPCb7ftP4dPZ6xASfHE7qdYpO5TrAeVqWrZ+P35ZtQtBATWrvSScKY3Jg7cPUa4RrkkWAYP7e1ms3L2YBaG7BD1/v6wJApk77pMN2JFqH8GL/t6vdSTmPeA4f5LnH9N7LJC6+qcn8SRFxHpPDyhnqVJCWTmLuCaDTxBk+XvyMb/sTbdGGLWMHorVO4ZXCBX5Mh05mY4Z3660RkAmEUERRKdNvbZO/eUVJiEII8KCFWnb1Uq27T+Fz2dTyo7agrAl7ps02NVqvf6+lz5ahAt5RXbPQTtTPnhmYoM5E73+wXX8AAb395r2DAtCTXGr0pisCQJZMO2nHfhlT91zJeN6Ncf7t7of/lqVp/SiSr1xVUmqiPWiblDEVBbKimBUtBKDTxBk+XuazC7clyHSC9mWxhJlVNGB5UZlFOFz2Yb9oDQPHds0xfgRfeBvkyLHjaobvJVSb9Dvjdy2SLQ++d58kEC1bBklofrk30cIMWvU8vyHC5FbWGL3+MRqxtMTNdmyalTuDT23wf29pkOCBaGmuFVpTNYEgSx4cu5uLNh5Bra5iv19gLF9WuKdCb1UMdJolXpi9c+ds27eKGK1GFMslLWgLK8Ng08QZPl7+l4v2p+OSps8hEQ7kKOMyht0OruaRMpXCzZi75HTIsJnh9ZNcP+kIbJES9q5bJGy42xWrsiLeN1V3TGofyedPam25sxeug1rthxGgHnLaFV1NVo3j8Ez91yvrSHcmpWAwf29piOBBaGmuFVpTNYEgSx4f8VhfL85BeWmKhFplCKMBvr7YvKANpjmxYnpVaHrJZUqIeg8IWL1jlcJrnp/Rm+zz+ATBFn+nsbv70eyUFxeae1m+tEPD/bH8E7Sg4d42xhp7Pb+sGgzNuxMtm5TtYjC6VNHNPZHV/X5aEX96182YveRNFDew3aJTXDfpEEiABAXzxAwuL/XFDoLQk1xq9KYrAkCWbArNQfPL9iH7OIKVFZVw8/XB7GhAXhjzCXo1TpGFSO5UnUJ8Fk39fiyUFaPrSs1G3yCIN/fn87F+aIKlJlqNo4G+fsgITIYPRKkJbZ3pY/4HnUJPPP+LygsKbNrpLKqCv/37K0cEVMB9LQCS6uDgeaVQgWq5CpcJGBwf+8iNdduY0HoGjc93SV7gkAT3E/WJGNbSjZKy6sQHOiL/m1i8cA1SR4Jga0nmN5qC59189aeY7vlEjD4BEG2v88rrUDy+SJU0BmBaiAwwBed48MQFnQxb57cPuDrPUvA0Vk3Sis885mJss8TevZJuHUm0DABg/t7TYcHC0JNcavSmOwJAlnBqx6q9IXHKuWzbh5Dzw1rTMDgEwSX/D3tBMkqLBMv/JqEBYpdIVy8l8CClbuxfMM+61m3ClMl+nRrjXsnDvLeh2LLmYADAgb395qOCf5V0A73KQBtajX3LIC33DTBpQmCm23y7TojwGfddNYhbI5qBLxkgsD+XrURwBWTv/919R5s23cSlZXV6JqUgDtuvIxXB3loNDoCXuLvGwV3FoTadSNNEL4E8IVNkwUA7JPeyLeHBaF8Zo3yDl71bZTdyg9Vi4CXTBDY3/PIZQJMgAm4ScBL/L2bT6mP21kQatcPNEH40Pyfkq2yIFSSJtfFBJiArgl4yQSB/b2uRxEbxwSYgDcQ8BJ/7w0ondrIgtApIsUuoAlCMIAAAKkA/gfgAwAmN1tgQegmQL6dCTAB7yHgJRME9vfeM6TYUibABHRKwEv8vU7pyTOLBaE8Xu5cPQ3ATgDZAAYCeBPA1wDo73JKAgD6z1LCAKzPy8tDZCSHEZcDkq9lAkzA+wh4yQSB/b33DS22mAkwAZ0R8BJ/rzNqrpnDgtA1bpa7KCDM006q6ArgsINr/g7gc8oRDMA+oVDDFb4M4KXal7AgdK8j+W4mwAS8g4AHJwjs771jiLCVTIAJNBICHvT3jYSg9MdgQSidlaMr4wHEOaniBIByB9d0B7AfQBcAR2SYocgKoTUASUYBkppFoGdiFOcglNEJfCkTYAKeIeDBCYLX+vvMwjJkF1UAPkB8WCDiwgI903ncKhNgAkxABgEP+nsZVjaOS1kQeq4f7wDwHYAmAHLcMEP2GUJOUeAGbb6VCTABjxLw0gmCx/z96bwSnMsrha+Pr+i3qupqtI4ORrNIOtLOhQkwASagXwJe6u/1C7QBy1gQatNtAwBcDmANAEo1Qf+mgDLLAExx0wTZgrC+JOZ3DWiLXq2i3TSHb2cCTIAJqEfACyYIuvH39PJv95l8VFXb90eAvw8uTeAz5+qNUq6ZCTABJQh4gb9X4jF1UQcLQm26oQ+AT8zbQ4MAnATwPYAZMs8POrJWtiCctz0NO1Jz69TVt00MxvdN1IYIt8IEmAATcIGAF0wQdOPvSRDuSMurcxzA1wfonRjlAn2+hQkwASagHQEv8PfawVC5JRaEKgPWoHrZgpBWCL/deAJnckpxobAcceGBaBkTjKkD26MnrxBq0GXcBBNgAq4SMPgEQba/P5hegHP5pSipqBJnCMMCfNEiKgSdm1I8My5MgAkwAf0SMLi/17RjWBBqiluVxmRPECorKzFsxnpkFpTC39cXpqoqNI0Ixqppg+Dn56eKkVwpE2ACTEAJAgafIMj29zvScnA6txTVpAZBmrAaHeJC0aMFrxAqMR65DibABNQjYHB/rx5YBzWzINQUtyqNyZ4g/LwtFbNWH0NltQ8qKqsQ4OcLP59qPDS0Iyb2b62KkVwpE2ACTEAJAgafIMjy91VVVVh57DyqqgDLMUL60Q/w98WwjhTPjAsTYAJMQL8EDO7vNe0YFoSa4lalMVkTBLLg6Xl7sD2l7hnC/m1j8Na4S1UxkitlAkyACShBwOATBFn+ngThisNZ4gwhRRel4uvjAzpDOKJLUyW6g+tgAkyACahGwOD+XjWujipmQagpblUakzVBIAvqWyF8eGgnTOjfShUjuVImwASYgBIEDD5BkO3vVx3NQkGpCfAx/9xXVyMmNACDk3iFUInxyHUwASagHgGD+3v1wDqomQWhprhVaUz2BIHPEKrSD1wpE2ACGhAw+ARBtr/fkZqDM/llqKyqOUXo5+ODVjHB6JXIKYY0GK7cBBNgAm4QMLi/d4Oc/FtZEMpnprc7ZE8Q6osyOmVge85DqLfeZXuYABOwI2DwCYIsf29JO0EnCEtNVUIQBvn7ws/Xl9NO8PeKCTAB3RMwuL/XtH9YEGqKW5XGZE0QyALOQ6hKP3ClTIAJaEDA4BMEWf6eBOHeswUw1cpMH+Tvgx6cmF6D0cpNMAEm4A4Bg/t7d9DJvpcFoWxkurtB1gSBrKcVwu83nUKg/8UUE+WmSkwe0JbzEOque9kgJsAEbAkYfIIg299n5JciNbfUnHQCIJHYPi5M5J/lwgSYABPQMwGD+3tNu4YFoaa4VWlM9gSBJgSfrj2O41mFQhSSGOwQH477h3QQ0ei4MAEmwAT0SsDgEwTZ/p76Ma+kAlmF5SIxfbPwIEQE++u1e9kuJsAEmICVgMH9vaYjgWf/muJWpTGXJggkCveczkNyZiGSmoajZ2IUi0FVuocrZQJMQEkCBp8guOTvleTPdTEBJsAEtCJgcH+vFWbRDgtCTXGr0hhPEFTBypUyASagRwIGnyCwv9fjoGSbmAATUIWAwf29Kkzrq5QFoaa4VWmMJwiqYOVKmQAT0CMBg08Q2N/rcVCyTUyACahCwOD+XhWmLAg1xappYzxB0BQ3N8YEmIAnCRh8gsD+3pODj9tmAkxAUwIG9/easuYVhmHZ5gAADXRJREFUQk1xq9IYTxBUwcqVMgEmoEcCBp8gsL/X46Bkm5gAE1CFgMH9vSpMeYVQU6yaNsYTBE1xc2NMgAl4koDBJwjs7z05+LhtJsAENCVgcH+vKWteIdQUtyqN8QRBFaxcKRNgAnokYPAJAvt7PQ5KtokJMAFVCBjc36vClFcINcWqaWM8QdAUNzfGBJiAJwkYfILA/t6Tg4/bZgJMQFMCBvf3mrLmFUJNcavSGE8QVMHKlTIBJqBHAgafILC/1+OgZJuYABNQhYDB/b0qTHmFUFOsmjbGEwRNcXNjTIAJeJKAwScI7O89Ofi4bSbABDQlYHB/rylrXiHUFLcqjYkJQlpaGiIj6X+5MAEmwAQaLwGaILRq1YoeMApAfuN9UodPxv7eYB3Oj8sEjEzA4P5e065nQagpblUaawngtCo1c6VMgAkwAf0SSARwRr/mqWIZ+3tVsHKlTIAJ6JyAEf29pl3CglBT3Ko0Rn3YAkCBC7X3BLAewCAAe1y435O3sO2eoe/N3ImYN9vPtl8c8xEAzgKo9szXwGOtsr/3vt8q9jse+7p4tb/nccP+XtNvDgtCTXHrrrE+AHYA6Atgp+6sa9ggtt0zHebN3ImYN9vPtntmzDeWVnn8eK4nmb1n2Hszd/698syYMWyrLAgN2/Xiwb3ZWbLtnhm73sydx7xnxoy3c/ccNWVb9ubvrjfb7u3j35vZe7PtPG6U9X9cmxMCLAiNPUS82Vmy7Z4Zu97MnX9gPTNmvJ2756gp27I3f3e92XZvH//ezN6bbedxo6z/49pYEPIYaIBAAoB7AXwO4JyXkWLbPdNh3sydiHmz/Wy7Z8Z8Y2mVx4/nepLZe4a9N3Pn3yvPjBnDtsorhIbten5wJsAEmAATYAJMgAkwASbABIxOgAWh0UcAPz8TYAJMgAkwASbABJgAE2AChiXAgtCwXc8PzgSYABNgAkyACTABJsAEmIDRCbAgNPoI4OdnAkyACTABJsAEmAATYAJMwLAEWBAatuv5wZkAE2ACTIAJMAEmwASYABMwOgEWhEYfAfz8TIAJMAEmwASYABNgAkyACRiWAAtCw3Y9PzgTYAJMgAkwASbABJgAE2ACRifAgtDoI4CfnwkwASbABJgAE2ACTIAJMAHDEmBBaNiu5wdnAkyACTABJsAEmAATYAJMwOgEWBAafQTw8zMBJsAEmAATYAJMgAkwASZgWAIsCBt31z8I4EkAzQHsAfAwgK0NPPIEAK8BaAvgGICnASz1ICI59k8F8HUtW8sABHvA/kFm7n0BJAAYA2ChEzuGAJgBoDuANACvA/jGC2wnu9c4sJOeO11j+58FMBZAFwAlADaax/ARJ3boYdy7Yrtexvz9AOg/8htUDgB4FcAyL/I1Gg9V1ZqT4zPJCD2MfQsMObbrZeyT7ezva37n2N/L+1qzz/fs/FJebxngahaEjbeTJwH4DsB9ALYAeMz8498ZQKaDxx4IYD0AclKLAdxunkz3AbDfA5jk2k8ThJkA6PkspRpAhgdsvx7AlQB2APhFgiBsZ2b8GYD/AhgG4EMANwJYobH9cm23CELinm9jK42xKo1tXw5gNoBtAPwB/BtADwDdABTVY4texr0rtutlzI8CUGl+iUS/KVPML0R6m8VhbfR6Ya7x8FS9Obk+U0/9INd2vYx96lS5PpP9vTJfBVd8pp7GvCv262Xcs89XZgzrqhYWhLrqDkWNIRFIE+OHzLX6mleePgLwloOW5gAIA3CTzWebAew2i0pFjZNQmVz7yVGSiIqWULeWl5AodbZC+LZZ/JF4sRQSNvQs12lpbK22pNhuEYQxAHI9aKujpuPNLz8Gm192OLpGb+PeYqMU2/U65ukZss2i8Esv8DU6G7YumyPXZ+pp7Mu1Xa9jX4rPZH/v8hBv8EYpPlNPY772w0ixX6/jnn2+OmNa01pZEGqKW7PGAgEUAxhfa6vit2aRcYsDS1LNWxZJVFnKKwBGA+ipmeU1DbliPzlKWl07A4DE704Az9WzQqHl40iZINDKLNlLq7iW8jezwI3S0lg3BGEKgCDzSufLAP7yoN2WppPMq1aXNLDKradxb4tMiu16HPN+5p0I5GtohfCgzn2NDoapIia44jP1MvZdsV2PY586kv29IsPZpUqk+Ey9jHlHDyjFfj2Oe/b5Lg1X/d3EglB/faKERS3Mwoi2R2yyqfAdALRacrmDRsrNW71+svnsAQAvAWimhFEy6nDF/gEAOgLYC4BE1BPmsx10Ju+0jLaVvlTKBOGo+fzjmzaN3wBgCYBQ83k4pe2SUp8U22mrKK0SbjcLwrsB3GUeYyRyPVXopcAi8wuQqxowQk/j3mKmVNv1NOZJdJOvoTO7heYt5/WdP9Yjc0+NU6XadcVn6qUfXLFdT2Pftg+l+Ez290qN+ov1SPWZehnztQlItV9P4559vvLj2KM1siD0KH7VGnflB1ZPjtIV+2vDDABwCAAJ3BdUI+284sY+QXBEYB0AehNLwtBT5VPz2R4Sgw29ENDTuLewkmq7nsY8rfK0Nr+MoZ0J9GKAXj45WiHUI3NPjVOl2nXFZ+qlH1yxXU9j30iCkP29Ut9Y+3rY56vDlWuVQYAFoQxYXnSpK1tw9LSVwhX7HXXPXAAmALd5sO+kCEJv3jLqCO27AEiI0dtMT5RZAGhbNEX/O+nEAD2NezJVju16HfNk10oAxwHc68BIvTH3xBhVuk1XfKZe+sEV2/U69tnfKz2yndcnx2fqZczbPpUc+/U67tnnOx+nur+CBaHuu8hlA+mQPqWYoFQTVGhLAjlDcj71BZWh7YkUPcpSKGw/bcGkSKVaF7n217aP9rVT+HvatjZNa+Nt2pMyQaAgA7RFlLZgWMr/AMR6QVAZR2j/AFBgTgGhJXryZxQ0iYL40DZWSp3irFCQAT2Me1ds1+uYJ7tWm/0NnXmpXfTC3NnY8LbP5fpMPfWDXNv1OvbZ32v3rXHFZ+ppzLtiv17HPft87ca9ai2xIFQNrccrpjDeFNiB3tCTMKSAJRPNOdooFQOlpKAALJRmggqdN6Stfs+Yz67dag7K4sm0E3LsfxEARUVNNp8bo/yLFBCHcgE62ramZgeFA6AD4lR2mQUp5eqjyIskyumsYEsAk83XWMKQfwzgKwBDAfyfh9JOyLWdxhWtwpH4pvNjtFWQXkKMALBKTcgO6v7EfHaNVgdtcw/m2ZzD1Ou4d8V2vYx5Gs+Uc5DGdoRNypqRAOjlgF6Zazw8VW/Om32+XNv1MvapU+X6TPb3ynwVXPGZeprnuGK/XsY9+3xlxrCuamFBqKvuUNwYSjlhSUxP6SMeMeckpIbWAjgFwPYNPiUppoTolsT0T3k4Mb0c+z8wr0g1B5BjzgH4vFmQKQ7WSYX1JWsngUu8KeE8MabrLIX+n56BcubRmbfXPJSYXq7tNEb+aRa4FNmWVpQpKbmjZPVq9wO9nXdUKGIrMdfzuHfFdr2MeUotQbkzKTk1iW8aA7TqTWJQz8zVHo+eqF+OzyT79OTz5diul7FPDOX6TMs97O/d+4a44jP1NOZdsV8v4559vntjV5d3syDUZbewUUyACTABJsAEmAATYAJMgAkwAfUJsCBUnzG3wASYABNgAkyACTABJsAEmAAT0CUBFoS67BY2igkwASbABJgAE2ACTIAJMAEmoD4BFoTqM+YWmAATYAJMgAkwASbABJgAE2ACuiTAglCX3cJGMQEmwASYABNgAkyACTABJsAE1CfAglB9xtwCE2ACTIAJMAEmwASYABNgAkxAlwRYEOqyW9goJsAEmAATYAJMgAkwASbABJiA+gRYEKrPmFtgAkyACTABJsAEmAATYAJMgAnokgALQl12CxvFBJgAE2ACTIAJMAEmwASYABNQnwALQvUZcwtMgAkwASbABJgAE2ACTIAJMAFdEmBBqMtuYaOYgC4IzAPgC2Cs2ZrWAE4AWAtguPlvCQBSAdwA4A9dWM1GMAEmwASYgFwC7O/lEuPrmUAjIsCCsBF1Jj8KE1CYwH8BkAgcYa73HQD3AzgCoJ/5by8CuB1AVwDVCrfP1TEBJsAEmIA2BNjfa8OZW2ECuiTAglCX3cJGMQFdEHgPwEDzf6EA0gB8aV4xTALgB+AUgLcBzNKFxWwEE2ACTIAJuEKA/b0r1PgeJtBICLAgbCQdyY/BBFQg8DyAiQAuBfBPAI8AuAfAbwCaABgN4DsALQEUAPgcwE0AWgBg36JCh3CVTIAJMAGVCLC/VwksV8sEvIEAT9q8oZfYRibgGQIPAZgGoD2AfQA+BrABwG4AAQBWADgK4GGzeYPM20nTWRB6psO4VSbABJiAiwTY37sIjm9jAo2BAAvCxtCL/AxMQB0CdwKYAeBWAPMBJAKINQeR6Q1gB4DuAA7Xap7OErJvUadPuFYmwASYgBoE2N+rQZXrZAJeQoAnbV7SUWwmE/AAAdr++TOA3wEcBzAdQBSAXACzAcTZBJyxNY8FoQc6i5tkAkyACbhBgP29G/D4Vibg7QRYEHp7D7L9TEA9AleZt4hWAOgM4KQ5DYUJQJU5uMwiB82zIFSvT7hmJsAEmIAaBNjfq0GV62QCXkLg/wEOgfan571PAgAAAABJRU5ErkJggg==\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(ncols=2, figsize=(9, 4))\n",
    "\n",
    "fig.suptitle('Posterior samples')\n",
    "\n",
    "ax1.scatter(*w_samples.T, s=4.**2, alpha=.6)\n",
    "ax2.scatter(*w_samples.T, c=mixtures, s=4.**2, alpha=.6, cmap='Blues')\n",
    "\n",
    "ax1.set_title('Zoomed out')\n",
    "\n",
    "ax1.set_xlabel('$w_1$')\n",
    "ax1.set_ylabel('$w_2$')\n",
    "\n",
    "ax2.set_title('Colored by mixture')\n",
    "\n",
    "ax2.set_xlabel('$w_1$')\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  },
  "nikola": {
   "category": "",
   "date": "2017-12-20 01:30:33 UTC+11:00",
   "description": "",
   "link": "",
   "slug": "bayesian-sparse-logistic-regression-with-spike-and-slab-priors-using-edward",
   "tags": "",
   "title": "Bayesian Sparse Logistic Regression with Spike-and-Slab Priors (using Edward)",
   "type": "text"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}