{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The goal of this tutorial is to provide an overview of the use of the NumPy library. It tries to hit all of the important parts, but it is by no means comprehensive. For more information, try looking at the:\n",
    "- [Tentative NumPy Tutorial](http://wiki.scipy.org/Tentative_NumPy_Tutorial)\n",
    "- [NumPy User Guide](http://docs.scipy.org/doc/numpy/user/)\n",
    "- [Introduction to NumPy from SAM](http://www.sam.math.ethz.ch/~raoulb/teaching/PythonTutorial/intro_numpy.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "NumPy is the fundamental package for scientific computing with Python. It contains among other things:\n",
    "- a powerful N-dimensional array object\n",
    "- sophisticated (broadcasting) functions\n",
    "- useful linear algebra, Fourier transform, and random number capabilities\n",
    "\n",
    "The NumPy array object is the common interface for working with typed arrays of data across a wide-variety of scientific Python packages. NumPy also features a C-API, which enables interfacing existing Fortran/C/C++ libraries with Python and NumPy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Basic Usage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The NumPy array represents a *contiguous* block of memory, holding entries of a given type (and hence fixed size). The entries are laid out in memory according to the shape, or list of dimension sizes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Convention for import to get shortened namespace\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a simple array from a list of integers\n",
    "a = np.array([1, 2, 3])\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3,)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print out the shape attribute\n",
    "a.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('int64')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# And now the data type\n",
    "a.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.,  2.,  3.,  4.,  5.])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This time use a list of floats\n",
    "a = np.array([1., 2., 3., 4., 5.])\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5,)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float64')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "NumPy also provides helper functions for generating arrays of data. `arange` for instance creates a range of values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3 4]\n"
     ]
    }
   ],
   "source": [
    "a = np.arange(5)\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 3 5 7 9]\n"
     ]
    }
   ],
   "source": [
    "a = np.arange(1, 10, 2)\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "`linspace` is similar, but is used to create a linearly spaced array of values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  5.    7.5  10.   12.5  15. ]\n"
     ]
    }
   ],
   "source": [
    "b = np.linspace(5, 15, 5)\n",
    "print(b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "NumPy also provides simple ways of performing mathematical operations. For instance, in core Python, you can do:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.0, 10.5, 15.0, 19.5, 24.0]\n"
     ]
    }
   ],
   "source": [
    "print([x + y for x,y in zip(a,b)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Using NumPy this becomes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  6. ,  10.5,  15. ,  19.5,  24. ])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([   5. ,   22.5,   50. ,   87.5,  135. ])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a * b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "NumPy also provides mathematical functions that operate on arrays:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.        ,  0.78539816,  1.57079633,  2.35619449,  3.14159265,\n",
       "        3.92699082,  4.71238898,  5.49778714])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = np.arange(0, 2 * np.pi, np.pi / 4)\n",
    "t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  0.00000000e+00,   7.07106781e-01,   1.00000000e+00,\n",
       "         7.07106781e-01,   1.22464680e-16,  -7.07106781e-01,\n",
       "        -1.00000000e+00,  -7.07106781e-01])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sin(t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Basic Plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Set-up to have matplotlib use its IPython notebook backend\n",
    "%matplotlib notebook\n",
    "\n",
    "# Useful import to have around\n",
    "from IPython.display import display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "# Convention for import of the pyplot interface\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Create some example data\n",
    "x = np.linspace(0, 2, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "            fig.waiting = false;\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.send_message('closing', {});\n",
       "    fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x108549908>]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Go ahead and explicitly create a figure and an axes\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "\n",
    "# Plot our x variable on the x-axis and x^2 on the y-axis\n",
    "ax.plot(x, x**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SJCmvYoTjj08HaoweDTvskHUiKRuNKsMhhNWArsDBwI9JRbju658BLwIPA/fF\nGGfmKKckScqh3/wGbr8dqqrg5z/POo2UnQaV4doV4POBk4A2wKukwvs+8AUQgO8AmwCdgGHA4BDC\nMODyGOO03EeXJElNcf31cMUV6WCNI4/MOo2UrYauDE8G3gXOBh6IMX66rDeHEL4LHEYqzycAazQn\npCRJyo0RI6BPH+jXL31J5a6hZbhrjHF0Qz+0tizfCNwYQvhVk5JJkqScevZZ6NEjrQZffXXWaaTC\n0KB9hhtThJtzbwhhpxDC9SGE10MIX4cQPggh3BtC2LyB968ZQhgWQvis9v5nQggdm5pdkqRS8dpr\ncPDBsNtucMstHqohLdKk/ymEENo34D07N+GjzwUOBZ4C+pBmj/cAakII2yzn57UCRgKVwGCgP/Bd\nYGwIYbMmZJEkqSR88AH86lew8cbwwAMeqiHV1dR/L3wjhPDr+l4IIawUQrgSGNeEz70G2CjGeGaM\n8eYY46XA7qRxjvOWc28XoDPQM8b4+xjjDcCewAJgYBOySJJU9KZNg733hrZtYdQoaNcu60RSYWlq\nGZ4I3BlCuL92pwkAQgg7Av8AziKtzjZKjPHFGOM3S1x7F3gD2HI5t3cB/h1jfKDOvdOA+4CDQwgr\nNjaPJEnFbNHpcl9+CU88Ae2X+991pfLTpDIcY9wHOAXYG3g9hHBECOFS0h7DKwF7xhjPykXAEEIA\n1gOWtz1bR6CmnusTgVWALXKRR5KkYrDodLk33kgrwps5MCjVq8nj8zHGocB2wBSgirQP8U3A9jHG\n53MTD4DuQAfg3uW8b31gaj3XF13rkMNMkiQVrIULoVevdLrcQw9BRUXWiaTC1eQyXPvAWiWwFfAJ\n6UjmzuRwBTaEsCUwBHgBuG05b28LzK3n+pza7yvnKpckSYUqRjj7bLj7brjzTvjFL7JOJBW2pu4m\nsSVpJOIS4BZgM9LDaqsCL4UQBtSW5Sar3bFiJOmEuy4xxricW2aTTsdbUts6r0uSVNKuugoGDYLr\nroNu3bJOIxW+hh66saR/AJ8B+8QYn6q99lwIYXvgSuAi4CBgp6Z8eAihHTCKdHLd7jHGfzfgtqnU\nPwqxfu33Kcu6uW/fvrRb4hHbyspKKisrG/CjJUnK3k03wXnnwYABcPrpWaeRmqaqqoqqqqrFrs2Y\nMSNvPy8sf8G1nptCuA3oE2OsN1kI4efATTHGTZrw2W2BJ0kPxO0VYxzfwPvuI23D1qHuKnIIYRhp\nnGOtGONRG6TCAAAgAElEQVT8eu6rAKqrq6upcKhKklSkHnwwPTB30kkwZAiEkHUiKXdqamro1KkT\nQKcYY30bJjRZU3eT6Lm0Ilz7+jOkh+saJYTQmvSg3C6kI6DrLcIhhPYhhC1DCHVXtkeQdp04rM77\n1gG6Ao/WV4QlSSoFY8akI5a7doU//ckiLDVGU8cklivG+J8m3HYNcCDwKLBOCKHHEp95Z+0vrwCO\nBjYGPqy9NgJ4CbglhLA1MB3oDQTgwiZkkSSp4FVXp2OW99wTbr8dWrfOOpFUXBpUhkMITwKXxhj/\n3pgPrx2XOLd2X+KG2J60K8WBtV91ReDOOr9ebL4jxrgwhLAfcDXpKOeVgQnA0THGSY3JLUlSMXjn\nHdh3X9h6a7j/flhppawTScWnoSvD7wJPhhDeJ53o9jTwjxjj13XfFEJYHdgR2Is0nrARae/hBokx\n/qyB7+sF9Krn+pfACbVfkiSVrI8/hl/+EtZZB0aOhNVWyzqRVJwaVIZjjL1DCFcDZ5BGDwYAMYQw\nnbT1WQDWAr5T++vpwF3AdTHGyfkILklSuZo2LRVhgCefhLXXzjaPVMwaOiaxHfBhjPHMEMI5wE+A\nHwNbAov+JzgdeIt0QMa4GOO8POSVJKmsffVVGo2YPh2eew6+//2sE0nFraFjEq8APYC7Y4zzQwi/\nAy6JMV6av2iSJKmu2bPTw3KTJsHYsbBFzs58lcpXQ7dWmwWsUuf3PyVtYyZJklrA/PlwxBEwfnya\nEd5hh6wTSaWhoSvDrwL9QggLgUX7C+8UQpizrJtijA80J5wkSYKFC+HYY2H0aHjkEdhtt6wTSaWj\noWX4DGA48Nclrp2xjHsi4G6HkiQ1Q4zQpw/cdRfccw/86ldZJ5JKS0N3k5gYQtgc2BT4LjAWuIy0\nxZokScqT3/0uHa88bBh065Z1Gqn0NPgEutrjjN8C3goh3A48FmN8KW/JJEkqc1ddBZdckr6f4A76\nUl406TjmGOMxOc4hSZLq+POf4dxzYcAAOOecrNNIpauhu0lIkqQWcscd0Ls3nHEGDByYdRqptFmG\nJUkqIA8+CL16wXHHwaBBEELWiaTSZhmWJKlAPPFE2ku4SxcYOtQiLLUEy7AkSQXguefg0ENhn33S\nmERrNyeVWoRlWJKkjE2cCPvvD7vuCvfdByuumHUiqXxYhiVJytCrr6bV4B/9CB5+GFZeOetEUnmx\nDEuSlJG33oK99oJNNoHHH4fVV886kVR+LMOSJGXgvffgF7+A9daDJ5+ENdfMOpFUnizDkiS1sA8/\nTEV4tdXg6adh7bWzTiSVL8uwJEktaOrUVIRbtYK//S2tDEvKTpOOY5YkSY332WdpRnjOHHj2Wfj+\n97NOJMkyLElSC5g+PRXh6dNTEd5kk6wTSQLLsCRJeffFF/DLX6YRibFjYYstsk4kaRHLsCRJeTRj\nRtpH+IMPYMwY2HrrrBNJqssyLElSnvznP7DffjBpUnpYbrvtsk4kaUmWYUmS8mDmTDjgAHjttbR9\nWkVF1okk1ccyLElSjs2eDQcdBNXV6UCNnXfOOpGkpbEMS5KUQ3PmwCGHwIsvwujR8OMfZ51I0rJY\nhiVJypE5c+DQQ9PWaSNHwh57ZJ1I0vJ4Ap0kSTkwdy4cdljaOu3RR+HnP886kaSGcGVYkqRmmjsX\nDj8cnnkmFeG99so6kaSGcmVYkqRmmDcPunZNO0Y8/HA6XENS8XBlWJKkJpo3D7p1gyeeSEV4n32y\nTiSpsVwZliSpCebNgyOPhFGj4MEH4Ve/yjqRpKZwZViSpEZatCI8ahTcf386ZU5ScbIMS5LUCItm\nhEePTivCFmGpuFmGJUlqoLlzUxF+8sk0I+xohFT8LMOSJDXAou3TFu0a4cNyUmmwDEuStBxz5ny7\nj/Ajj8Dee2edSFKuWIYlSVqGOXPSyXJjxqQi7D7CUmmxDEuStBSzZsEhh8Dzz3uynFSqLMOSJNVj\n5kw48ECYMCFtofbTn2adSFI+WIYlSVrCf/4D++8Pr7ySTpfbbbesE0nKF8uwJEl1zJgB++4Lr7+e\ntlDbddesE0nKJ8uwJEm1vvgibZk2aRL87W+w445ZJ5KUb5ZhSZKA6dPTThEffpi2UOvYMetEklqC\nZViSVPY++STtFPHJJ2kLtW23zTqRpJbSKusASwohrBpCGBhCGB1C+DyEsDCE0LOB9x5T+/76vr6b\n7+ySpOLz0Uewxx7w+efw7LMWYancFOLK8LrAAOAD4BVgTyA28jMGAJOXuDaj2ckkSSVl8mT4xS9g\nwYJUhDfdNOtEklpaIZbhKUD7GOOnIYROwMQmfMaoGGNNjnNJkkrIO++kItymDYwdCxtumHUiSVko\nuDGJGOO8GOOntb8NTfyYEEJYPYTQOle5JEml41//SqMRq6+eVoQtwlL5KrgynCNjSGMRM0MID4cQ\nNss6kCSpMNTUwJ57Qvv2aUW4Q4esE0nKUiGOSTTHTOAWUhn+CtgR6Ae8EEKoiDF+lGU4SVK2xo2D\n/faDH/4QRo+GtdbKOpGkrJVUGY4xDgeG17n0SAjhCeBZ4ALglEyCSZIy99RTcMgh6SCNRx+FNdbI\nOpGkQlCqYxL/L8Y4DhgP7JV1FklSNh56CA44IM0JjxplEZb0rZJaGV6Gj4AtlvWGvn370q5du8Wu\nVVZWUllZmc9ckqQ8u+su6NkzrQrffTestFLWiSQtS1VVFVVVVYtdmzEjfzvkhhgbu4Vvywkh7AhM\nAI6JMd7ejM95GVg1xrhVPa9VANXV1dVUVFQ0PawkqeAMHQqnnJLK8F/+AiuUyxKQVGJqamro1KkT\nQKdcb59btGMSIYT2IYQtQwgr1Lm2bj3v2w+oAEa3ZD5JUrb+8Ac4+WQ49VS46SaLsKT6FeQ/GkII\npwFrAos2vDkohLBoF8jBMcavgCuAo4GNgQ9rX3shhFADVJO2VqsAjq19/bKWSS9JylKMcMEFcPnl\ncP75cOmlEJq6a72kkleQZRg4C9io9tcROBQ4rPbXt5O2TYv89zHN9wD7A3sDq5BOsxsKDIwxfpb/\n2JKkLC1YAKedBjfeCFddBeeck3UiSYWuIMtwjHGTBrynF9BriWsDgAH5yiVJKlzz5qXZ4PvuS/PB\nxx+fdSJJxaAgy7AkSY0xaxZ06QJPPw333pt+LUkNYRmWJBW1L7+EAw9MxyyPHAm//GXWiSQVE8uw\nJKloffIJ/OpX8D//k1aFO3fOOpGkYmMZliQVpfffh733hpkz4dlnYdtts04kqRgV7T7DkqTy9eqr\nsNtuacu0F16wCEtqOsuwJKmoPPcc7LEHrL8+PP88bLLc/Yckaeksw5KkovHoo2k0oqICxo6F9dbL\nOpGkYmcZliQVhVtvhUMPhf32g8cfhzXWyDqRpFJgGZYkFbQY02lyvXrBscemQzXats06laRSYRmW\nJBWshQuhXz8491y44AIYOhRat846laRS4tZqkqSCNHfut8crDxkCvXtnnUhSKbIMS5IKzldfpfng\nceNg+HA4/PCsE0kqVZZhSVJBmTo1PSQ3eTI8+WTaRk2S8sUyLEkqGO+8A/vsA/Pnp/2EPUxDUr75\nAJ0kqSC89BL8+MdppwhPlZPUUizDkqTMPfww/OxnsNVWaU54ww2zTiSpXFiGJUmZuuEGOOwwOOAA\neOopWGutrBNJKieWYUlSJhYuhPPOg1NPhT594N57PUxDUsvzATpJUoubNy+dJnf33XDttdC3b9aJ\nJJUry7AkqUV9+WXaN3jcuLQa3LVr1okklTPLsCSpxXzwQdpDeOpU9xCWVBgsw5KkFvHyy3DggbDy\nyvDii/DDH2adSJJ8gE6S1AIefRR++lPYaKO0n7BFWFKhsAxLkvJqyBA45JB0stwzz8B3v5t1Ikn6\nlmVYkpQXCxbAWWfBaafBGWfA8OGwyipZp5KkxTkzLEnKuZkzoXv3NB4xeDCcfnrWiSSpfpZhSVJO\nTZmSHpR7++10zPIBB2SdSJKWzjIsScqZV15J5TcEeP552GGHrBNJ0rI5MyxJyomRI+EnP4H27WH8\neIuwpOJgGZYkNdvgwXDQQfDLX8Lf/w4dOmSdSJIaxjIsSWqy+fPh1FPTbhFnnQX33w+rrpp1Kklq\nOGeGJUlN8sUX0K0bjB0Lw4bBCSdknUiSGs8yLElqtEmT0oNy06bBU0/BnntmnUiSmsYxCUlSozzz\nDOyyC7RqlR6UswhLKmaWYUlSgw0dmo5V3mknePFF2GyzrBNJUvNYhiVJy/XNN+khuZNPhpNOStuo\nrblm1qkkqfmcGZYkLdPnn8MRR8CYMTBkCPTunXUiScody7AkaanefDPtH/z55/Dkk/Dzn2edSJJy\nyzEJSVK9Hn8cdt0V2rSBiRMtwpJKk2VYkrSYGOHqq9PWaXvumR6U+8EPsk4lSflhGZYk/b/Zs6Fn\nT+jfH84/Hx58EFZfPetUkpQ/zgxLkgD43/+Fww6Df/0L7r4bKiuzTiRJ+WcZliTx3HPQpQu0bQvj\nxkFFRdaJJKllOCYhSWUsRvjzn9PDcVtvDS+/bBGWVF4sw5JUpubOhRNPTPsG9+6dtk5bd92sU0lS\ny3JMQpLK0JQpaSyipgZuuQWOOSbrRJKUjYJbGQ4hrBpCGBhCGB1C+DyEsDCE0LMR968ZQhgWQvgs\nhPB1COGZEELHfGaWpGLy3HNpFOKDD+DZZy3CkspbwZVhYF1gAPBD4JXaa7EhN4YQWgEjgUpgMNAf\n+C4wNoSwWe6jSlLxiBH+9Kc0H/zDH6ZV4Z13zjqVJGWrEMvwFKB9jHET4JxG3tsF6Az0jDH+PsZ4\nA7AnsAAYmNOUklREZs1K+wf36QOnnQZPPw3rrZd1KknKXsHNDMcY5wGf1v42NPL2LsC/Y4wP1Pm8\naSGE+4AeIYQVY4zzcxRVkorC5Mlp/+C333b/YElaUiGuDDdHR6CmnusTgVWALVo2jiRla/Ro6NQJ\nvvoKXnrJIixJSyq1Mrw+MLWe64uudWjBLJKUmYULYeBA2G8/6Nw57R+83XZZp5KkwlNwYxLN1BaY\nW8/1ObXfV27BLJKUienToUcPeOKJVIgvuABaldrShyTlSKmV4dlAm3qut63zuiSVrIkT0/7BM2em\nEYm99846kSQVtlIrw1OpfxRi/drvU5Z2Y9++fWnXrt1i1yorK6l0wE5SEYgRhg1Lu0Vsvz0MHw4b\nbZR1KklqvKqqKqqqqha7NmPGjLz9vBBjg7bwzUQIYUdgAnBMjPH2Brz/PmB3oEOs8wcLIQwj7T28\n1pK7SYQQKoDq6upqKioqcppfklrCzJnpOOXbb4dTToFBg6BNff+NTJKKVE1NDZ06dQLoFGOsb7OE\nJivaKbIQQvsQwpYhhLqr2yOA9YDD6rxvHaAr8KjbqkkqNW++CbvsAiNGpDJ8ww0WYUlqjIIckwgh\nnAasybcjDweFEDas/fXgGONXwBXA0cDGwIe1r40AXgJuCSFsDUwHepP2K76wZdJLUsu4+2448UTY\ncEOYMAG22SbrRJJUfAqyDANnAYum3SJwKGm1NwK3A1/V/nqxGY8Y48IQwn7A1UAf0u4RE4CjY4yT\nWia6JOXXnDlw5pkwdCh07w433girrZZ1KkkqTgVZhmuPYl7ee3oBveq5/iVwQu2XJJWU996Drl3h\njTdSGT7hBAiNPatTkvT/inZmWJLKzfDhUFGRTpN78cU0ImERlqTmsQxLUoGbMyftFtGtG+yzD1RX\nQ8eOWaeSpNJQkGMSkqTknXdSCX7rLfjzn+Gkk1wNlqRccmVYkgrUXXelsYjZs2H8eDj5ZIuwJOWa\nZViSCszMmXDccdCjBxx6aBqL2H77rFNJUmlyTEKSCsg//wlHHgkffAA33wzHHONqsCTlkyvDklQA\nYoTrr0+nya20UloN7tXLIixJ+WYZlqSMTZsGBx8Mp5+etksbPx622irrVJJUHhyTkKQMjRmTZoPn\nzoVHHoEDD8w6kSSVF1eGJSkD8+fDBRfAL34BW2yRZoUtwpLU8lwZlqQWNmkSdO8ONTXw+9/DeedB\n69ZZp5Kk8mQZlqQWEiPccgv06QPt28MLL8DOO2edSpLKm2MSktQCPv8cunZN+wcfcQS88opFWJIK\ngSvDkpRnzzwDRx8Ns2bB8OHQpUvWiSRJi7gyLEl5MmcO9Ov37UNyr75qEZakQuPKsCTlwSuvpC3T\nJk2Ca66BM8+EVi4/SFLB8R/NkpRDCxbAlVemeeDWreHll9PqsEVYkgqT/3iWpByZPBn23BPOPx/6\n9oUJE2DbbbNOJUlaFsckJKmZYoSbb04FeK21YOxY2GOPrFNJkhrClWFJaoYpU+CAA+D449PWaa++\nahGWpGLiyrAkNUGMcO+90Ls3tGkDjz6aSrEkqbi4MixJjTRtWjo4o7IS9t4b/vUvi7AkFStXhiWp\nER5+GE46CebPh3vuSaVYklS8XBmWpAaYPh1+/Ws45JC0bdrrr1uEJakUuDIsScvxwANwyilpNfjO\nO1MpDiHrVJKkXHBlWJKWYto0OPJIOPxw6NwZ3ngDune3CEtSKXFlWJKWECPcf3/aKWLBArj77lSK\nLcGSVHpcGZakOqZOTSvBXbvCT36SVoMrKy3CklSqXBmWJNJq8K23Qr9+ad/gESNSKZYklTZXhiWV\nvcmT037Bxx4LBx+cVoMtwpJUHizDksrWggVw3XXwox/BO+/A6NFpdXittbJOJklqKZZhSWXpn/9M\nO0T07ZtWhP/1L9hnn6xTSZJammVYUlmZNQvOOw86dUq/HjcO/vQnWH31rJNJkrLgA3SSysZTT8HJ\nJ8PHH8PAgXDOObDSSlmnkiRlyZVhSSXv00/h6KPTQ3IbbgivvgoXXGARliS5MiyphC1cCDfdBOee\nm35/003Qq5d7BkuSvuXKsKSS9NprsPvucOKJcNBB8Pbb6UE5i7AkqS7LsKSSMnMm9O8PHTvC55/D\nmDFpu7R11806mSSpEDkmIakkxAiPPAJ9+qQZ4YsvhrPPdi5YkrRslmFJRe+991IJfvxx2HfftBr8\ngx9knUqSVAwck5BUtGbPhgsvhG22SYdmPPggjBxpEZYkNZwrw5KK0mOPpdXgjz9O+wX/5jewyipZ\np5IkFRvLsKSi8u676Qjlxx5L+waPHg1bbJF1KklSsXJMQlJR+PprOP/8NBLx6qswYoRFWJLUfK4M\nSypoMcLdd6ft0j7/PBXi/v0diZAk5YYrw5IK1j/+kQ7O6NEDOneGN9+Eiy6yCEuScqcgy3AIoU0I\n4coQwpQQwqwQwkshhL0acN8xIYSFS/n6bktkl9R8//43HH88dOoEX34JTz+dxiI23jjrZJKkUlOo\nYxK3AocDg4BJQC/g8RDCz2KM4xpw/wBg8hLXZuQ0oaScmzMH/vhHuPTSdFjG4MFw0kmw4opZJ5Mk\nlaqCK8MhhJ2BI4CzY4zX1l67A/gXcBWwWwM+ZlSMsSZ/KSXlUoxw//1pi7SPPoJTT037B3/nO1kn\nkySVukIck+gCfAMMW3QhxjgXuAnoHEL4XgM+I4QQVg8htM5TRkk58vLLsOee0LVr2initdfS6rBF\nWJLUEgqxDHcE3okxfr3E9Ym133dowGeMIY1FzAwhPBxC2CyXASU13wcfpAfjdtoJpk9P26Q99hhs\nuWXWySRJ5aTgxiSA9YGp9VxfdK3DMu6dCdxCKsNfATsC/YAXQggVMcaPchlUUuPNmAGXX55Wf9dc\nE4YNg169YIVC/KeRJKnkFeL/+1kZmFvP9Tl1Xq9XjHE4MLzOpUdCCE8AzwIXAKfkKqSkxpk/PxXf\niy6CmTPh3HPTjPBqq2WdTJJUzgpxTGI20Kae623rvN5gtbtPjAeWuzWbpNyLMW2Lts02cPrpcOCB\nMGkSDBxoEZYkZa8QV4anUv8oxPq136c04TM/ApZ5aGvfvn1p167dYtcqKyuprKxswo+TBDB2bFoB\nnjAB9t0Xhg+H7bfPOpUkqZBVVVVRVVW12LUZM/K3Q26IMebtw5sihHAV0BdYK8b4nzrXfwNcAmwQ\nY/y4kZ/5MrBqjHGrel6rAKqrq6upqKhoXnhJAPzzn+nY5FGj0gNyV14JP/tZ1qkkScWqpqaGTp06\nAXTK9fa5hTgmMQJoDZy46EIIoQ3p4I2XFhXhEEL7EMKWIYQV6rxv3SU/LISwH1ABjM53cKncvf8+\nHHUUdOwI776bVoLHj7cIS5IKV8GNScQYJ4QQhgOX1x6h/B7QE9iQVIgXuQI4GtgY+LD22gshhBqg\nmrS1WgVwbO3rl7XIH0AqQ1OmwCWXwF/+AuuuC0OGpOOUPTlOklToCq4M1zoa+D1wFPAd4J/AATHG\n5+u8J9Z+1XUPsD+wN7AKab54KDAwxvhZvkNL5Wb69DQC8ac/wSqrwGWXpdPjVlkl62SSJDVMQZbh\n2hPn+td+Le09vVh8pZgY4wBgQH7TSfrqq7RP8DXXwMKF0L8/9OsHSzyDKklSwSvIMiypMH39dVoF\nvvpqmDULTjkFfvObNBohSVIxsgxLWq6ZM+GGG+Cqq9Kq8AknpN0ivve9rJNJktQ8lmFJSzVrFgwd\nCldcAZ9/Dscdl1aCN9ww62SSJOWGZVjSf5k5E268MY1DTJsGPXvCgAGw8cZZJ5MkKbcsw5L+33/+\nk8Yh/vAH+PJLOOaYNA7xgx9knUySpPywDEtixgy4/nq49tpUiI87Ds47DzbaKOtkkiTll2VYKmOf\nfZa2SLv+epg7Nz0Y178/bLBB1skkSWoZlmGpDP3v/6Y9gocNg1at0hZpfftChw5ZJ5MkqWVZhqUy\n8s47aXu022+H1VaDc8+F006DtdfOOpkkSdmwDEtlYPz4VIIffBDWWy8dm3zSSbD66lknkyQpW5Zh\nqUTFCKNGpRL897/D5punPYOPOgrats06nSRJhaFV1gEk5da8eWkMYrvtYP/9Yc4ceOABePPN9ICc\nRViS9H/t3WuQlcWdx/HvH1EG8YIGkJtZi7gERIlAMOpG42VjIcZLFJMoitdKqZXKmnWtVMXlhRqt\nrNZuVqOmlsSIGkPAFUtTIWpWpQjeYEW8IBYgK0RARZGLgghO74s+kxnGGWZgzpxz5pzvp6rrGfqc\npvpo0/ObZ/rpViPvDEtVYt26fOf3F7+ANWtyEL7zTjjuOIgod+8kSapMhmGpi1u6NG+PNnUqfPYZ\nTJoEV18Nhx1W7p5JklT5DMNSF5QSzJ4Nt90Gjz4KffvmnSGuuAL69St37yRJ6joMw1IXsnkzPPAA\n3H47vPYajBgBv/oVTJzoWmBJknaHYVjqAlasgLvuysF3/Xo444x8V/jEE10PLElSRxiGpQpVXw9P\nPZVD8COP5D2BL78crroKhgwpd+8kSaoOhmGpwnz4Idx7L/zyl/nEuMMPhzvuyPsD77NPuXsnSVJ1\nMQxLFWLBgnwX+He/g+3b4Zxz4Ne/hq9/3aUQkiR1FsOwVEabNsG0aTBlCrz4Ihx8MFx3HVx2GfTv\nX+7eSZJU/QzDUomllIPvlCn5LvCWLTB+fN4i7dRTobv/KiVJKhm/7Uol8uGHOfzefTe89BIMHgzX\nXguXXprvCEuSpNIzDEudqL4ennwSfvMbePjhvBb4tNPghhtg3DjvAkuSVG5+K5Y6wfLlcN99cM89\nsHIlDBsGP/0pXHCBa4ElSaokhmGpSNavhwcfzCF47ty8Ddr3vpeXQRx9tDtCSJJUiQzDUgds2wZP\nPJED8COP5D9/85v5yOSzzoK99y53DyVJ0s4YhqVdlBI891x+GG7GDFi7FkaMgBtvhIkTYeDAcvdQ\nkiS1l2FYaqdFi/Id32nT4K23YNAguOgiOP98OPJIl0FIktQVGYalnViyJK8Dnj4dXn0VDjgAJkzI\nAfj446Fbt3L3UJIkdYRhWGpm2bIcgGfMgIUL84Nwp5+el0GMGwc9epS7h5IkqVgMwxKweDHMnAkP\nPZQPxNh77xyAJ0/Op8L17FnuHkqSpM5gGFZNSgkWLMgBeOZMeOMN6NUrH4v8k5/kqztBSJJU/QzD\nqhnbtsGcOfDoo3kbtBUr8hrgM8+EW27JW6LV1ZW7l5IkqZQMw6pq69fDY4/lADxrFmzYkHeBOOMM\nOPts+MY3YM89y91LSZJULoZhVZWU8pKHWbNymTMHtm+H0aPhRz/KIdht0CRJUgPDsLq8zZvh6acb\nA/Bbb+UH3k46CW67LT8Id/DB5e6lJEmqRIZhdTn19XnP3yeeyOUvf4GtW2HIkBx8x4/Pyx/cAUKS\nJLXFMKwuYdUqePJJ+POfc3n33bzbwwknwM9+lrc/GzrU5Q+SJGnXGIZVkd5/H2bPhqeeyiF4yZJc\nP3o0XHIJnHIKHHusB2BIkqSOMQyrIqxdm5c7zJmTQ/DLL+f6oUPh5JPhppvyXeA+fcrZS0mSVG0M\nwyq5lOCvf4W5c3P4nTMnnwAHed3v8cfDNdfAiSfC4MHl7askSapuhmF1uk8/hYUL4dlnG8uqVfm1\nww7LD7tNngzHHWf4lSRJpWUYVlGllE92mzevscyfD598ktf3jh0LEyfm9b7HHgt9+5a7x5IkqZYZ\nhtUha9bAggXw4ouN4Xft2vzaIYfk8HvzzTn4jhoFe+1V1u5KkiTtwDCsdqmvz3d8Fy7M4behvPNO\nfv3AA+Goo+DKK/N17Fjo16+8fZYkSWpLxYXhiOgB3ABcCPQGXgH+NaX0P+1o2xu4Bfg20BOYB1yT\nUnqp83pcfTZsgNdeg1deaSyvvgqbNuXXDzoIxoyByy/PW52NHg1f/KJ7/EqSpK6n4sIwMBU4B/g5\nsBS4BJgVESemlJ5prVFEdAP+CIwkB+IPgKuA2RExJqW0rLM73tWsWwevv/750vBwW/fuMHw4jBwJ\nZ56ZryNHwsCB5e23JElSsVRUGI6Io4DvAv+SUvqPQt39wGvkgPsPO2k+ATgGmJBSmlloOwNYAlwP\nTOzErlesTZtg+XJYujQfXNG0fPBBfs8ee8Chh+adHS6+OF9HjMhB2DW+xTVt2jTOO++8cndDNcCx\npiwK2n4AAAkwSURBVFJxrKmrq6gwTA6024EpDRUppa0RcTdwc0QMSimt2knbdxqCcKHt+4VAfEFE\n7JlS2taZnS+HTz6Bt9+GlSvzmt7ly+HNN/N1+fLGh9kAeveGL385H2Qxfny+Dh+er57kVhp+01Cp\nONZUKo41dXWVFoZHAUtSSh81q59fuB4JtBaGRwELWqifD3wfGAosKkYnS+Wjj2D16lxWrWr8umn4\nfffdHdsMGpQPrhg2LAfeIUNyGToUvvAF1/VKkiQ1VWlheACwpoX6hrqdrVYdAMxuo23ZwvD27bB+\nfV6n27R88AG8917L5aNmPxLst19er3vwwXDEEXDaafnBtYYyeDDU1ZXn80mSJHVFlRaGewJbW6j/\npMnrranrQFsWLYJt2/IWYg3ls8/y6WnNy9atsGULbN7ceG0omzbBxo2fLw07MXyu03V5d4Z+/XIZ\nPjyfyNa3bw6+DWXAANhnn519AkmSJO2qSgvDW4CWVq/WNXm92G3rACZNWtye/v3NXnvlINu89OqV\nS//+8KUv5QDbq1e+7rcf7L//jtf23MndtKn1MK2uZcOGDSxY0NJqHqm4HGsqFceaSmHx4r/ltKL/\nDrzSwvAaWl4KMaBwXd0JbQ/Jlwva7FxTDXeJN27cpWYSY8aMKXcXVCMcayoVx5pK6BDg2WL+hZUW\nhl8CToiIfVNKTe+Ffq1wXbiTtguB4yIiUkqpWduPyVusteRx8rZrb9G4pEKSJEmVo44chB8v9l8c\nO+bG8irsM/w8cG1K6d8LdT3I+wyvTSkdW6jrTz6dbllKaXuh7jvA74FzU0oPFer6kA/u+FNK6fxS\nfx5JkiRVtooKwwARMZ18nPLPgTeBi4CvAienlOYW3jMVmAQcklJaWajrBswFDgdupfEEusHA2JTS\n0tJ+EkmSJFW6SlsmATnk3ghcCBwAvAx8qyEIF6RCaaxIqT4ixpOD8A/Ju0fMAyYZhCVJktSSirsz\nLEmSJJVKt3J3QJIkSSqXqg3DEdEjIv4tIlZHxOaIeD4i/rGdbXtHxJSIWBsRH0XEUxExqrP7rK5p\nd8daRFwcEfWtlH6l6Lu6jojoFRHXR8RjEbGuME4u2oX2zmtqt46MN+c2tVdEjI2IOyJiUWFeWhER\n0yPi79vZvijzWiWuGS6WqcA55AfxlgKXALMi4sSU0jOtNSo8iPdHYCRwC40P4s2OiDEppWWd3XF1\nOVPZjbHWxGTg/5rVbShqD1UN+pLHygryVpIn0OzZidY4r2k37PZ4a8K5TW35MXAM8CDwCvlsiB8A\nCyLi6JTSotYaFnVeSylVXQGOAuqBf25S14McVJ5po+13Cm3PblLXB1gHPFDuz2aprNLBsXZxoe3o\ncn8OS+UXYC+gX+HrMYWxM6mdbZ3XLLtUOjjenNss7SrkINy9Wd2h5FOD72+jbdHmtWpdJjEB2A5M\naahIKW0F7gaOiYhBbbR9J6U0s0nb94EZwJkRsWfndFldVEfGWoOIiH0jYo9O6qOqQErp05TSe4U/\nxi42d17TLungeGvg3KadSik9lwrnRTSpWwa8Dgxro3nR5rVqDcOjgCUppY+a1c8vXI9so21Lh6zP\nB/YGhna8e6oiHRlrDZ4m/+rw44h4JCIOLWYHJZzXVB7ObdplERHAQcD7bby1aPNatYbhAcCaFuob\n6gZ2UlvVno6Ml4+Be8hrnM4ir3k6GXg2IgYXs5Oqec5rKiXnNnXERPKcNL2N9xVtXqvWB+h6Altb\nqP+kyeutqetAW9We3R5rKaUHyQ8NNHg0Ih4H5gDXAVcWq5Oqec5rKhnnNu2uiBgG3Ak8C9zbxtuL\nNq9V653hLeSHmJqra/J6Z7RV7SnqeEl594kXgHZtAyi1k/Oaysq5TW2JiP7k3SE+BCakwhNxO1G0\nea1aw/AaWr49PqBwXd1JbVV7OmO8vE0+ilwqFuc1VQLnNrUoIvYH/gTsB4xLKb3TjmZFm9eqNQy/\nBAyNiH2b1X+tcF24k7YLgdGFBdzN234MLClOF1UlOjLWWjMEWNuhXkk7cl5TJXBu0+dERB3wB/KW\nat9KKb3RzqZFm9eqNQz/N7AH8P2GiojoQT4M4fmU0qpCXf+IGBYR3Zu1PQg4u0nbPsC5wB9SSttK\n0H91Hbs91iKib/O/LCLGA6OBxzq746pOzmsqJec2dURh273p5AB7bkrphVbe16nzWrS9JKNriojp\nwLfJp4K9CVwEfBU4OaU0t/CeqcAk4JCU0spCXTdgLnA4cCuNJ5oMBsamlJaW9pOo0nVgrC0lbwvz\nInn7odHApcAq8ljzDop2EBE/AHqTfzV4BTCTxt8+3J5S2ui8pmLpwHhzblO7RMR/Aj8k3xl+sPnr\nKaXfFt43lU6c16p1NwnI/9FuBC4kr1F6mXz7fW6T9ySaHS+ZUqov/AR7K/l/UE9gHvnkHb9hqCW7\nNdaA3wOnAaeQ90RcDfwXcL3fLNSKa4C/K3ydyD+EnV34+j5gI85rKp7dGm84t6n9vkIeP6cXSlMJ\n+G2TrzttXqvaO8OSJElSW6p1zbAkSZLUJsOwJEmSapZhWJIkSTXLMCxJkqSaZRiWJElSzTIMS5Ik\nqWYZhiVJklSzDMOSJEmqWYZhSZIk1SzDsCRJkmqWYViSJEk1yzAsSZKkmmUYliRJUs0yDEuSJKlm\nGYYlqQpERM+IeCMiFkdEXZP6AyNiTUTMjQjnfElqxolRkqpASmkLMAk4FLipyUt3AvsCF6eU6svR\nN0mqZN3L3QFJUnGklOZFxC3AjyPiYaA/8F3gn1JKy8rbO0mqTJFSKncfJElFEhF7Av8L7FMoi1JK\nJ5W3V5JUuQzDklRlImIMMB/YAhyWUlpR5i5JUsVyzbAkVZ9xhWtPYGg5OyJJlc47w5JURSJiJPmu\n8P3AKKAPcERKaWNZOyZJFcowLElVorBe+AVgf2AkMIQcjB9IKV1Wzr5JUqVymYQkVY/JwFeAS1NK\nH6eUXgVuAC6JiFPL2zVJqkzeGZakKhARo4HngbtSSlc3qe8GPAcMBEa4XEKSdmQYliRJUs1ymYQk\nSZJqlmFYkiRJNcswLEmSpJplGJYkSVLNMgxLkiSpZhmGJUmSVLMMw5IkSapZhmFJkiTVLMOwJEmS\napZhWJIkSTXLMCxJkqSaZRiWJElSzfp/qeeJT+JQVI0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108549eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add some labels to the plot\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('f(x)')\n",
    "\n",
    "# Needed to reuse and see the updated plot while using inline\n",
    "display(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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GRMQzwM6lyClJklTNZszItk/7wQ/g/PPzTlN+FVuGm3A38BPgh8BzLXzvu8Da83tB//79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\nLMOwJEmSapZhWJIkSTXr/wHkshJ+DgChhwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108549eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's add a title with a bit of latex syntax\n",
    "ax.set_title('$y = x^2$', fontdict={'size':22})\n",
    "\n",
    "display(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "            fig.waiting = false;\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.send_message('closing', {});\n",
       "    fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x109767710>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1)\n",
    "\n",
    "# Plot a set of different polynomials.\n",
    "# The label argument is used when generating a legend.\n",
    "ax.plot(x, x, label='$x$')\n",
    "ax.plot(x, x * x, label='$x^2$')\n",
    "ax.plot(x, x**3, label='$x^3$')\n",
    "\n",
    "# Add labels and title\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('f(x)')\n",
    "ax.set_title('Polynomials')\n",
    "\n",
    "# Add gridlines\n",
    "ax.grid(True)\n",
    "\n",
    "# Add a legend to the upper left corner of the plot\n",
    "ax.legend(loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Exercise"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Make a plot containing:\n",
    "- 3 different plots with different styles. Suggestions:\n",
    "  - sin, cos, tan\n",
    "  - exp, log\n",
    "  - sqrt\n",
    "  - Any others you want to try\n",
    "- Use labels and a legend\n",
    "- Add labels and title"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Indexing and Slicing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Indexing is how we pull individual data items out of an array. Slicing extends this process to pulling out a regular set of the items."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Create an array for testing\n",
    "a = np.arange(12).reshape(3, 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  1,  2,  3],\n",
       "       [ 4,  5,  6,  7],\n",
       "       [ 8,  9, 10, 11]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Indexing in Python is 0-based, so the command below looks for the 2nd item along the first dimension and the 3rd along the second dimension."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[1, 2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Can also just index on one dimension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 8,  9, 10, 11])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Negative indices are also allowed, which permit indexing relative to the end of the array."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0, -1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Slicing syntax is written as `start:stop[:step]`, where all numbers are optional.\n",
    "- defaults: \n",
    "  - start = 0\n",
    "  - end = len(dim)\n",
    "  - step = 1\n",
    "- The second colon is also optional if no step is used.\n",
    "\n",
    "It should be noted that end represents one past the last item; one can also think of it as a half open interval: `[start, end)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 4,  5,  6,  7],\n",
       "       [ 8,  9, 10, 11]])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[1:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  2],\n",
       "       [ 8, 10]])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[::2, ::2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2,  6, 10])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:, 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2,  6, 10])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ... can be used to replace one or more full slices\n",
    "a[..., 2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Using the data below, write code to solve the commented problems."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "a = np.arange(60).reshape(3, 4, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Decimate the data by a factor of 3 along all dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Pull out the 2nd 4x5 slice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Grab the last column from all dimensions (result should be 3x4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Broadcasting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "\"The term broadcasting describes how numpy treats arrays with different shapes during arithmetic operations. Subject to certain constraints, the smaller array is “broadcast” across the larger array so that they have compatible shapes. Broadcasting provides a means of vectorizing array operations so that looping occurs in C instead of Python. It does this without making needless copies of data and usually leads to efficient algorithm implementations. There are, however, cases where broadcasting is a bad idea because it leads to inefficient use of memory that slows computation.\" (NumPy User Guide)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
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LZg1Ay40bNywsLMLDw5l+KBKJIiIiLC0t79y5w3IlFRUVI0eOpHKGIZFIRo8e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7v7VyeTkpIE94KamZmBBQVaE0OH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PBg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\n6rd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mzZoFqdAcsCjL/2zcuPH777/38fHx9va+cOECLTHs2bMnPj4+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\nmZubOzg4tLgPQRB5eXkcDsfGxgYyBgAA1MjNza2srEQ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CQklJicVi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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('https://scipy-lectures.github.io/_images/numpy_broadcasting.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.        ,  1.04719755,  2.0943951 ,  3.14159265])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create some test data\n",
    "a = np.linspace(0, np.pi, 4)\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "NumPy can perform operations between arrays and constants:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.        ,  2.0943951 ,  4.1887902 ,  6.28318531])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a * 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "This extends to operations between arrays of different sizes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.        ,  2.0943951 ,  4.1887902 ,  6.28318531])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a * np.array([2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "b = np.linspace(0, 50, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4,)\n",
      "(5,)\n"
     ]
    }
   ],
   "source": [
    "print(a.shape)\n",
    "print(b.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "operands could not be broadcast together with shapes (4,) (5,) ",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-42-cbd5ee68580c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# This will not work because the array sizes are not compatible\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0ma\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (4,) (5,) "
     ]
    }
   ],
   "source": [
    "# This will not work because the array sizes are not compatible\n",
    "a * b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Broadcasting works by:\n",
    "1. Make the arrays have the same number of dimensions. If they are different, size-1 dimensions are *prepended* implicitly\n",
    "2. Check that each dimension is compatible--that they are the same or one of them is 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5, 1)\n"
     ]
    }
   ],
   "source": [
    "# If we add a size-1 dimension to end of a, they can be rectified.\n",
    "# The process of broadcasting will implicitly add a size-1\n",
    "# dimension to the start of b\n",
    "a = a.reshape((-1, 1))\n",
    "print(a.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   5. ,    7.5,   10. ,   12.5,   15. ],\n",
       "       [  15. ,   22.5,   30. ,   37.5,   45. ],\n",
       "       [  25. ,   37.5,   50. ,   62.5,   75. ],\n",
       "       [  35. ,   52.5,   70. ,   87.5,  105. ],\n",
       "       [  45. ,   67.5,   90. ,  112.5,  135. ]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = a * b\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5, 5)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Exercise"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Create a 1D array of 100 x values between -3 and 3, and a 1D array of 150 y values between -5 and 5. Use these to calculate an array of radius values.\n",
    "\n",
    "Radius can be calculated as:\n",
    "$r = \\sqrt{x^2 + y^2}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Logical Indexing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Logical indexing allows selecting elements from an array using a second array of `True` and `False` values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Create some synthetic data representing temperature and wind speed data\n",
    "temp = (20 * np.cos(np.linspace(0, 2 * np.pi, 100)) +\n",
    "        40 + 2 * np.random.randn(100))\n",
    "spd = (np.abs(10 * np.sin(np.linspace(0, 2 * np.pi, 100)) +\n",
    "              10 + 5 * np.random.randn(100)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "            fig.waiting = false;\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.send_message('closing', {});\n",
       "    fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(temp)\n",
    "plt.plot(spd);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True, False,  True, False,\n",
       "        True,  True, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "        True, False,  True,  True, False,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,  True], dtype=bool)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# By doing a comparision between a NumPy array and a value, we get an\n",
    "# array of values representing the results of the comparison between\n",
    "# each element and the value\n",
    "temp > 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 59.94085421,  58.83031031,  58.84980453,  58.74748457,\n",
       "        58.91166856,  59.2736831 ,  55.71808028,  57.14558846,\n",
       "        57.7187068 ,  56.60954469,  55.01564008,  53.6547195 ,\n",
       "        51.43505518,  56.25736286,  54.22407867,  50.21617013,\n",
       "        50.92135725,  50.26980959,  51.33724742,  50.53606382,\n",
       "        51.17178211,  55.27256196,  55.15509235,  52.28786784,\n",
       "        56.86603724,  59.49012436,  59.09612739,  56.5781568 ,\n",
       "        56.51427088,  57.22348803,  60.40483986,  59.46136604,\n",
       "        58.7726495 ,  62.14601469,  59.33285632])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We can take the resulting array and use this to index into the\n",
    "# NumPy array and retrieve the values where the result was true\n",
    "temp[temp > 50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 58.83031031,  58.84980453,  58.74748457,  58.91166856,\n",
       "        57.14558846,  57.7187068 ,  56.60954469,  53.6547195 ,\n",
       "        56.25736286,  54.22407867,  49.01743277,  50.21617013,\n",
       "        48.04619469,  50.92135725,  50.26980959,  45.96578237,\n",
       "        47.53657735,  43.99568218,  40.34747113,  39.08466618,\n",
       "        42.35807886,  36.59074848,  39.04743195,  32.7341674 ,\n",
       "        32.45509221,  31.00606921,  29.23736194,  33.92842907,\n",
       "        29.02609759,  30.5738094 ,  30.55430093,  26.17425503,\n",
       "        23.74424383,  23.17716381,  23.19616754,  20.73118679,\n",
       "        21.00613853,  18.11199313,  21.40786048,  19.043798  ,\n",
       "        24.43450641,  26.38058474,  24.96942595,  56.86603724,\n",
       "        60.40483986,  59.33285632])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# So long as the size of the boolean array matches the data, the\n",
    "# boolean array can come from anywhere\n",
    "temp[spd > 10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "            fig.waiting = false;\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.send_message('closing', {});\n",
       "    fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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JcLnc8whTec4b+c+cR/JDJgBM2AGusoAZVAIwP/8pzOn2XJL6f3vl76dGv7qCKAjgLGra5QA3Hhjae216zVybLuttOCCxQ0kZS/25Zel/feXjj5a2mef8P8bZsAMmAEzYAbGAwM0QiIAkwkesde8xRbSCisEl40EFoAWgLHrapQA3GADiW7eOlYuX/2qNNdc0ve+V/+ymHO9ww7Ba5Aw+pe+JJ1+ukRk0jADZsAMmAEzMNYZoGkDAfjGG5250s9+Vlp1VWm33SwA04w6ORi3vkYJQGxcaObADqYq8BCcZRbp+9+vumfoltp9d+nSS6Uf/CAI0Le8Rbr4Yonw9x/+EJpTDDNgBsyAGTADY5kBmjZOPTUIQH7HYvGpT0lrrintsosFoAVg7Goa3n+UAPz4xyVq+bCDqQoW54wzSocfXnVPabXVgq/gySeHbqc0iCiedpp0663S7LNXP7b3MANmwAyYATPQKwZo2vjZz0IKmEEKsfjkJ6X115cIsiRwCtgp4Nh1NUoA4uNHKhc7mKoggvfmm6F2ryoWXTSIP95ysmDkHFFJhmFfdVVnvlBVr8/bmwEzYAbMwPhigAjcr34lUUPXS5C1Ouus0ATyjnfEn3m99aRNNgm/zRaAwxw4BRy3tkYJQOoMiORhB1MVzAFmNNyxx1bdU1poofDGRAdyHhiEzbXx9x/9qPrxvYcZMANmwAz0FwPMque3hSBCL90kEJznnhtsYCZNiuf8E5+QPvc5iUZLC0ALwPgVFY4wSgBi5EynEUWnVbH33mFm8AknVN1Tmn/+8IVZZZXiffkyM3ru9tvD/GHDDJgBM2AGzEARA3/9q0R26bXXwgz7XoHfz/PPD0bQ73pX/Fk/9rHQEEl5lgWgBWD8iioQgLSaYzZJ0WlV7Lef9PTT0imnVN1Tmnvu0PCBCXUrlN2u7BUgWKk9NMyAGTADZmBiMTB1qrTkkp1LxZZlh3TtRRdJ//xnZ+rWP/KR4I7BsAULQAvAsuuw3XajIoBM8mDeIEWnVXHggRJROho2qgLDZyxgll++9Z5lIoVlzz0wIM05p3T33WH+sWEGzIAZMAMThwGe7bhHdCoVW5aZDTeULrtM+vvfg6VZLD784WABQy28BaAFYOx6SvYfJQCXWko64ghp3XWrnwLh+Je/SD//efV9CZNfd117q5d2tYJVzky0koginVXHH19lT29rBsyAGTADY50ByoUIKnQqFVv2fmnauPJK6fHHpfnmK7tX8XYrrhimgHz60xaAaZbcBBK3tkYJQGrsjjtOWmut6gc+9FDpzjulX/yi+r4Uyt5yS/vavlbdwlXP+sQTofZwppnCF/Xd7656BG9vBsyAGTADY5UBrMMoK0rGivbqOmna+M1vpEcekf7f/4s/63LLSQccEIY0JLANjG1gYlfWKAG4yCLST34iffSj1Q995JHSH/8o/fKX1felVf6uu0LBbivQ/PHDH4ZxdbEgXc39Ul+BAfZee8Ue0fubATNgBszAWGHgpptCY+FTT4VsT69A08bvfic9+GD4jYnF0ktLBFjwArQAHObAEcC4lTVKAPK2cuaZwZi5KhBmpHEvuKDqnsHb74EHQst+K+R9EaqfLezBl5Pj4RPF6B7e1maYoe7RvJ8ZMANmwAyMJQauvz5Yhz32WMj29AoEFW64QaIJhaxaLAh8HHNMCFRYAFoAxq6nZP9RApB6hfPOk1ZeufopqKOjkeOSS6rti3k043LKfEnzQuHVzja8NV9OaisoEOZLShczBp6GGTADZsAMjH8GfvvbMFzg4YfbBxc6ebdEHYk+3nOP9P73xx+ZzNhJJ0lM6rIAtACMX1HhCKMEIB1LdC998IPVT8EkD6xcLr+82r64tePRVCZMTz0Hqdp0MWy1sw1vTYcYb2pYwZx4Yhje/ac/9dYwtO61ez8zYAbMgBlozcDVV4dyIbJL7cqLOsklv1PUH95xh4SzRiwWXlg6/XSJSV0WgBaAsesp2X+UAGTWLsWryy5b/RQMv8bMmXFtVfDf/0pvf3u5Ql3erHbdtd6kkuw10SFGse6zz0ovvywtsEAw76xT/1jlfr2tGTADZsAMdJ+BK64IdXP33de+wbCTV0PnMb8vt90m4a0bC36bzj47TMOyALQAjF1PhQIQU2RqF7CDqQpGufHv2mur7Yn4euc7y7XqU8+x/fb1ZhVnr4o3NPyasIMB3/lO8ASsmsKudrfe2gyYATNgBnrBwKWXhs5ZGgyp9+4V8B7kt+TmmyWma8VinnmkCy8ceSx3AbsLOHZdjYoAIsR4a6lTuMrwa9LAv/99tcvCkBnhWcask3qOrbcO/2JBjQbGmljAAFLQhNp5WNgYOpZd728GzIAZmLYMIJooF/rznyXqx3sFpo9QY04wJR21q3t+BhYQzUxHEy0ALQDrrqdkv1ECkFQshat1WtdJ/9IJfOON1S7ruefCuJz//EfCDqYVqOfYfHPpy1+udo68rekQY7Yi3b8J+N+I4DrzjOOvyEcwA2bADJiBTjGAwwMv+XjM0vDXKxBAwGUCK5h03V7d8+NRS0NLup7QAtACsO56KhSANGMwQLuOeSX1c4cdFrwAq+Af/wjjcl59NdjBtAL1HBtvHNLAseAL9dWvhi9qAppASDM//7wtYWL59f5mwAyYgWnJAHVzzM8lKME4tV7hve8NncfXXBO6kGPRaISu4nRHsQWgBWD0upI0MDAwoEajocSOpe74GjqAmQeMiKqCJ58M43LoBsYOphWo58ALafLkKmfI35YOsV12CaH6BP/7n8SXjdqNOnWQ8VflI5gBM2AGzEAnGDjjjJDloSwJx4deYcEFg60ZtmidGFrAtCqaSt73vuE7sAC0AIxdzyNSwK+/HiJwZexY8k78619Le+8dxsFVwd/+FmrvEIDtQD0HIXU6gWOBXc23vhWKddOgaJfB21tsEXsG728GzIAZMAPTioHTTgvlQp2KxJW9j3nnDb+j/Camp3eU3T+7HQMKCFQQWUxgAWgBWHc9JfuNEICvvBJq8OrOTeRtZ/fdpXvvrXZZDz0kUTSLHUw7UM+BQNtjj+ItiWQSJcTQmmheEej2/e53w5tVGtttF1LSBx3U7mr8dzNgBsyAGRirDJxySigX6lQkrux9zjVX+B0lK5ae31t2/+x2ZMZIKadLsywALQDrrqdcAfjSS9KkSeXsWPJOzFvWjjtKf/lLtctie3yTsINpB+o5KIQlcleExFi6nfs7I+u+//1g2JkGI3eoD+TLa5gBM2AGzMD4ZIBmPsqFOhWJK8vCbLMFVwsaI2OHFlCWNP30wa2CUqkEFoAWgGXXY9F2IyKATMR417vK2bHkHZCOJ8LtRPSqgK5jWuWxg2kH6jmog8CzrwhJJBNh2crO5Ze/lI4+OhTXpoERNm+NVe+j3bX772bADJgBM9A7Bo49NpQLdSoSV/bKZ5lFQrgxHIGsVQxeey00JP797yEzZQE4zMF0McR635Gj4KrYseRxh+fRF74gUdNXBYzLYcYh528HBCau6KRui5BEMklFk1ouwi9+EUbAYQeTRtKV/O9/B0sYwwyYATNgBsYfA0cdFcqFcKiIjcRVuXt+NyinQoB+7nNV9hy97f/9n0QTyD//GezSEjgC6Ahg3MrKzAKuYseSd2I6Zz/zGYmu3irAeHqDDSTO3w5E5uaYo3V9XhLJpBkFR/Yi/Pzn0k9/OnpyCTWEGG+SNmCmo2EGzIAZMAPjjwFsySgXIhUbG4mrcvf46fI7dcgh0he/WGXP0dsSiKCWHWsyBiZYAA5z4Ahg3NoakQKuYseSd9oqQi69fxXhSD0HdYo/+EHxjfOmhIBrN4eRDrFzzsmfXYx3E9HMThhOx31E3tsMmAEzYAbqMIAAo1yIKVXUj/cK+OkutFBwxfjSl+LOivDDCDqbkXIE0BHAuJWViQBWsWPJO3GVVG56/yqpY+o5sKo54ojiW6dWgtmJ7eYw0iF20UUSdjBZ4A9I4S01goYZMANmwAyMPwbwpaVciBn11I/3AomfLqbN/F595StxZ00CGqSCiSwmsAC0AIxbWRkBWMWOJe/EVZo50vtXaR6hnoMuXzp1i0C3FHWC7eYw0iF25ZUSdjBZ/PjHEk0imEUbZsAMmAEzMP4Y2G8/6XvfC80Y227bm+tP/HRxtsBSbIcd4s6bBDRoBiGyaAE4zIFTwHFra0QKuIodS95p778/DKsuY+eS3p+uW1K7ZexjqOfg+McdV3zj2L9gmNluDiNzi6+7TsIOJgs6gzfZRHr66TiCvbcZMANmwAxMGwZIwWL1dfLJYexnL5C4UKyyShgmsPPOcWdNAhp0FU+XUjyOADoCGLeyMhFAumZZtGXsWPJOzAxhwt5lDJ3T+xOF+8Y3JCKI7UA9B93CJ51UvOUDDwSrGKJ3a61VvN2RR4a5xUT6ssDDiVb+uqbY7e7DfzcDZsAMmIHuMvDNb0qHHy4df3zwqO0FCFDQBUwd+YYbSl//etxZH3lEWnRRichiGhaAFoBxKysjAOmaZdGWsWPJO/Gjj4bIW5mRbun9L7tM2mcfiRrCdqCeg2aVn/ykeMv77gtC9IorpHXXLd7u0EPD2DrsYPKA6/rpp0sf+1i7q/LfzYAZMANmYKwxwGQq6rjJ9lDX3QsQQKFblxFw/HYQ3IjBgw+GufTZwIoFoAVgzLpi3xEp4D/9KSzaMnYseSd+4glp/vmDAWY6VN3uImnEYOwaXbvtQD0HtYrYtxThrrvCtJBLL5U++cni7Q4+OKSdsYPJA/syUi42hN/unvx3M2AGzIAZ6DwDiL4f/Ugi24MY7AUSP118B1dcUdprr7izMgP4gx8cXVplAWgBGLeyMgKQdCiLtqqPX3IR1MvNPbeULVZtd5HM7KWrl67ddqCeg1T1mWcWb4mQ5QtDbR91fEU44ADpscdCgXAevv3tEA2lW9gwA2bADJiB8cUAaV/M/sn2kA7uBRI/XQygGURAdisGRc2VFoAWgDHrin1HRAD/8IfglVR1kkdyEc8+G8wvs+3q7S4SLz6aOujabQfqORB47FMEhOzKK4favk03Ld5u331DjR8FwnnAO4rakRtvbHdV/rsZMANmwAyMNQZo/MDRgWwPDSG9QOKnu8020oILSvvvH3fWIns1C0ALwLiVlRGAdMTSKl93Bm4ygaPqCDWiedT00bXbDtRzIFSJGhaBv6+2WqjtazWGhwgfzR6IvDyQSuY41HRUSWm3uwf/3QyYATNgBrrPACbMlAshwlqND+3klRBAwQQa/792U6vKnLdowIIFYH8KQN4n9pX0n9TiwcnuC4P/m+FnmKQsL2lAEgnMAwoW2ogI4DXXBM8iumjrIJnBmx1Z0+5YfEERgdjBtAORQrajbrAICEmKb9uZf+65p/Tqq6FAOA8U3c48cxDEvMnVAV9eak+47lZj6eoc2/uYATNgBsxAMQOMYeO3hTQs9eO9ADZkiy8eBCAj3ChbikHRpCwLwP4VgGtKWj1nUU2ShHw7TdKBkhaVdIWkIyXlWSePEIBTpki77SbRRVsHRUOr2x2L6B8RPexg2gH7F5o7mNNbBATiJz7R3vyTe33LW0KBcBGo4SDtzKziOqAIGV5pkGF83U47OZpYh0fvYwbMgBmoygAZIMqFaMSIFWJlz00AZdllgwCcYYbw+xGDoklZFoD9KwA/LukjOYtqa0mHSZpb0v8G/07zO/8Wydl+hABEVJEWJfVZBzR/sOBxLn/Pe8ofAVGHFQz/2gGx+KtfBVFVBITkeuu1N/9EjBHho0C4CJtvLi23XL1OLkYCETmkiYTzMFuYKCDWMqQGDDNgBsyAGegeA9SAE1zAiiVWiJW9SgIo1KAjAHHEiB0nWjQpywKwPwXgdyXtOZgCJg38B0nfkfSoJCbXLi5pvdRiXUUS7RWIvZcyi3iEALz4YonO2D//uexSH7kdi535uTiXzzdf+WOUSesmRyNdfMYZEunqIhAh3GijkHZlwkgRvvY1abbZQoFwEUgbYBWT13WMwGtVG51+Z5kAACAASURBVEizCqloZjnOOKNEanz77aXrrw/1ifYXLL9GvKUZMANmoCoDuEAQWOBlP1aIlT03AZQ11ggCkKwYNjQxKJqUZQHYnwLw/ZJelPS4pHkGI34rS/qApGMlzSxpi9SCW0LSvZKQZE+1EoDYppCmvOWW+ssVAUjNHCbKZcFcX8LcrRo7kmMhxOjqomGlCBdeGOxsOC7DuIvAnMZ55w2itwjUGlI8jGF0GpyDtAL/PT2gO70NXcZMRzn77OH/imjE8oaoZ91mm7K8ejszYAbMQD8zwCQOImh05MYKsbI8EkDBPxYByEs/NjQxIKO1xx7B/iwNC8D+FIDZtTTDYLPHRoORvyUlpedflI4AYpuCaIqxPSHSxUJdJC/hXPAtQBDRLNHK2iXZlW34ItPpWwRSxJttFoQWX5wi8FBgcglCrQjJeDsaXN72trAVRb4M+kbswheFxnnAvZ1jk0ZO41//CpFHIoOzzx7zaPC+ZsAMmAEzUMQApUD8tnz2s/FCrCzLBFA23jgIQMqhCFjEgAgmFjbZ0iwLQAtA1lVaAFL7R8kpkcE3BhcdMbCdBhtCsuuwmQKePHmyZphhBt1/P+nbdXT33evUXq/UupH6pAuqLIg6YnbZytw5ORZRQmo58PorAulV6u0o+m3lwr7llmHETqttSGsz15F7WmIJiUHfq64a7GEQuXgF5hlYJ+N7EHl0gmWx2GKh+5gHlGEGzIAZMAOdZ4BmQH7XGAkaK8TKXt1NN4UABAKQ8ain0ZIZAbJQBx4YSrOmTJnS/AdeffVVHR88zGYZzApGnGV87jrd+LzsqKveTBIVcM9JmmtQ8K0maWkFQZx0AR80KProlz2qTBcwI9Gosbv22vrXN8ssITqHsCoLxsARaWs13i05Fl8G6vIQZEXgPrbeOmzXyoV9iy3CxJB2sxoZ54NlDF9qagpvvTWkrKnvIIVMOnqFFUZeDSL1t7+VLr88/yoRqO97n7TffmVZ8nZmwAyYATNQhQHqrHFg4IWd5rtegBrvrbYKAhDxWTRqtOy1nH9+aFTMlmY5AtifEcCLJX14sNbveUlUw5HEfHhwQSEEeS1AklArSAUCljB5GNEEwpsKKdarriq7NEdvR2qTBg3a4MuCGjvc0+nwbQfC4d/5zuiavPR+3MeXvxxq91q5sJMW4MHw9a+3Pitmosw4fv/7JRpHbr99uMYR30S8BLPj5FZZRWI/HgJ5IPp39dXlOp/bceK/mwEzYAbMwGgGPvIRiQEF/B7RPNgL8OLPBBKe/UzxICMVg3PPDdmibGmWBWB/CsCYtZTdd4QAxK6ECFtR1KrMieeaK3j0EVkrCwQdM3dpjGiHooLY9H6MdkOoUTfRqsP3U5+S1lordIi1wlFHhS8xaV3e5qjvSHD33dKHPhTeMt/97vBfqftAMCJq4SMPpAk4DnMjPWWk3afuv5sBM2AGqjPw4Q9Lr78eynXSzXjVj1R+D17sd945CEBKlaitjwFlRvym/f73I49iAWgBGLOu2HeEADzhhGDGfAlzRWqClCgha3yQyuJb35JefjnYtrRDUUt8ej/KIhB1DP9u5fGHuTNdYojFViAiSlcXEz3yTKNXXz2IuaThhC8rb5utZhuTPqY2EFFZpWO6HT/+uxkwA2bADAQGKN/BpQFfWpoDe4ErrgglQwhAyoNw14gBE634ly3NsgC0AIxZV6ME4LHHhpb5mAWL8THRMholygLh9MYboaO2HcrMKyZcTlq3SLAl50DUYRSKHUwr0AFMRzGRyqQTOL09IXr+hgM8k0Vo7Pj4x9vXFlI3SAMK12CYATNgBsxAZxnAxB+nBRr5sO7qBfChxf0BAUi/RkxAheulvIjfmGxplgWgBWDseh4RASTVSUdrTMgaWxVq8DDCLAu8+hBWiKx2oMGE8T6PPVa8JVE6GjsYw1Y055e9EWlYuGAHEwNqABG+FBmTcmDKB27w7axwiDxOmtQ7h/qYe/S+ZsAMmIHxxsDSSw9nWBBmvQBlVDQ2IgARf63Glpa5HjJKDGnIlmZZAFoAllk/rbYZIQAPOyy+aJXOVlLJiKuyoLMWIYQdTDtQU4G7+1NZS+vUjhyHkXY0aHAtRUjc2rGDiQXdvDSH0N1L3SG1ge2AUCa038rUut0x/HczYAbMgBnIZwDrLhwpyOKQmu0FsCojmIEAJJjSamxpmeuhpCkvkmgBaAFYZv2UFoCHHBLftk6nLJFE0qtlwXi0OecMti3tgP0LKdZnninekrevJARPY0sRSFMTJcwaNbe7hry/0/Cx8MKh+WXNNcvdC96HNJAMDEhvfWuds3ofM2AGzIAZKGKALAxZGRrzqB/vBXDSoJ4dAUjTYKuxpWWuhyxWXi2hBaAFYJn1U1oAYjb5yCNxfkkf+ICEkKTBoiywbFlggWDb0g6MXsPbiWkaRcD6hfFu2LC0MuFEfNEo8pnPtDtrub9jK0MDDCKVSSHtQN0jvol0BJOqMMyAGTADZqBzDNBghxk0zXbUt/cCybhSBGC7saVlroeSprxuYgtAC8Ay66e0ACSNGTu6BuGDkEtbpbS7SEybmYxBI0U7MGaON7oXcTgsAMdBhJLabeX9RBMG91zlWltdH0KOjmbe1spau5CG5v633bbdnfvvZsAMmAEzUIWB+eYLJUOU57RyZahyzHbbMtCA3x0EYLuxpe2Oxd9xssBPMGtjYwFoAVhm/ZQWgPjmxQ6vXmmlIIKqRNWom1tmmbBfO/zlLxKdXf/5T/GWHId6RiZ9tPJ+qhOtbHd9Vf+OXcC//13OA7Hqsb29GTADZqCfGcD+hakceOjljezsBjcMNMByBgHYbmxpmfMTzJg6dXQwwwLQArDM+iktAEmH4k/HW0tdMAGDrt4qdXVsi3BMfPRanfuhh8JMXjpvi8BxqEMkJdvK+6lOvWJdXor24/qYWcycxyzwRmSWsH0CO826j2cGzEA/MIAFDE2GdOLedltv7piuXbp/EYDUo8eet6g0ywLQAjB2RY/oAkY4/e9/0tFH1z8spsg0dRDVKwuiheyHcGyHv/1NWmihcJ1FoLGDLyHNIrTkF4G084knVutYbnd9Vf/O/WCdQxTwHe8YuTcpbN78Ws09rno+b28GzIAZ6BcGZp01ZJbw0SON2gvQtYtnHwKQWfSx5y0qzbIAtACMXc8jBCACbIYZ4nzp6IClpo1/ZUEN3tprhze1dqDblroOGigwXc7DjjsGM2rm/DI7uAh07eLdV8WzsN31Vf37m2+GcXH4PFHbmIB6Qqx0/vvfEAVMxsxVPb63NwNmwAz0KwMYQOMugZkyrgu9QNK1yzxg/Ghjz1tUmmUBaAEYu55HCEAEGOPJSEnWBUKOlC6dvWVBx/BGG4XIYTswO5e6DoQRYjUPfPEw/aTGj9F2RaDzmBrBKlNL2l1fnb9/8pOhUy2JgBLdZJQe/x1LAWpAmFtsmAEzYAbMQHkGGANHRgtRdv/95feL2TLp2iUCyEzg2PMWlWZZAFoAxqxT9h0hAKv48RWdeP31Q1dtGTGXHAPPwM02KycasX+ZbbYwO3immfKvAvsXWv6J8LXyYJpnnjAeCDuYaQlqPGhuYeg3wDuK1AEPDr78RDoZ02eYATNgBsxAeQbwV8WKBXP+v/61/H4xW9K1i10ZApB/sedlpCmZomxplgWgBWDMOh0lAKv48RWdmEgegq5MOjc5BqlOOrXKpI2xf8E7D/NkopV5YLwbdXOMZGs1ZQPzaSKEZTz7YolutT/XwJsiXlU41lObyJedSCq+gvgalpks0s1r9LHNgBkwA+OJAUQTL8+UAzEZ6tFHe3P1iE1e6BF//BbFnpea9hlnHF2aZQFoARi7okdEAKv48RWd+NOfDjV1ZRo6kmOwPWnbMo0j2L/MPLP07LMhEpgHZgU/8IBE+J/ZwUWgro5IIRY00xLcC2L1ueck0gdYFvAPL0H+hlB9+unwfw0zYAbMgBloz8Drr4cZ8xdcEF6wn3ii/T6d2IKMDqIPAUhm6/HH445KTTtBj2xplgWgBWDcysqkgKv48RWdmAVP/Rph67KoMpIN+xfehhBENE/kAfsXDK1fe0265ZbiqyCCiDfUkkuWvdLubUcnMOne3XaTrr9ewqQ6wbLLShQCw61hBsyAGTAD7Rl45ZXgrHD55WEqFL8ZvQBdu5wLAUhGjN+iGBAc4bcuOyrVAtACMGZdse+ICGAVP76iE3/+8xKCBTFTFlVGstEgMf304W1u3nnzz0DDBKlU6gXz/PWSvaghpEWflOu0BlFLLGvgj461NBCFPMywrDHMgBkwA2agPQP8BkyaJF17rbTppiGb0gskXbsIN5oicXGIAVOiaFikFCgNC0ALwJh1NUoAVvHjKzoxtXyLLx4iVmVRdSQbdR3MLF5wwfwz0D1L+hSPvbvuKr4KuohptKBZZFqDmj9G6JG6pss5DUxFmRhCXYlhBsyAGTAD7Rl44QXpXe+SbrwxeMLyv3uBpGuXCCDlTUzXigG/qQQpaAy0ABzJwXQxxHrfkRHAKn58RdzxtsLkCsLgZUENHvUN2MGUAcINg2TSpnmgCYX0LnOD77svf5ukQBiRyNvVtAZvqzSBMOYuCx5c1DtSS0LnsmEGzIAZMAOtGSDyRt00WSA8YXGO6AWSrl0EINktTP5jQGnW0ktLe+018iiOADoCGLOu2HdECriKH1/RiQl7E8GiELYsqMEjAoZwKwNStwz3ft/78remqxihRH0foioPGEljEYCx9HgQVSuuKH396+UaZcpw6G3MgBkwAxOZAWrveLYTBKAsCe/YXiDp2kUA4kXLeNUYUJrF8x9T6TQsAC0AY9bVKAFYxY+v6MR0LDF+B/Pisqg6ko3oHpMymOWbB8LuiMOrrw6p4jzwMKBLGGPp8dBdS1qBLuFsfWBZjr2dGTADZqCfGCBjQnbn4YelRRYJ06N6gWSgAgKQcqhWc+vLXA+lWR/5SAgAWACO5MAp4DIrqHibERFAImf4Fm2zTf2D0m5P59Vhh5U/RtWRbNi3/Pa34e0qD3QVf/CDof2/qAWfdABjghBV42HMGl6BiGseZoYZMANmwAy0ZoCX/0UXDZYs88/fenxoJ7lMBiogACmHajW3vsx5Kc1iUtROO1kAZvmyACyzgkoKQCJnLNott6x/UDpWacA46qjyx6g6ko2I3RVXjLRKSZ9tpZWkj31M+tnPilv/MZImUomxNJ1iYx3UCFLQTEqbh4phBsyAGTADxQzwrKR2jjpvypKIxOEL2G0wUAHBSTkUThWt5taXuRZKszbcUPra1ywALQDLrJjy24yIABI5I4K3xRblD5Ddkm5V0qtVRpdVHcnGl4roXtEINyZ74L903HHFrf9E/mafXcJYmojleACfz3bbBU8rwwyYATNgBooZoFGQ2jkEYC+f9QxUIPJIMKXd3Poynx+lWdjY8OxPwzWArgEss35abTNCACKoEHAYKdcFI3eIrp1wQvkjtIvoZY+E/QvjfRBEeaCrmM4pOouLWv+p/evlW2F5Noq3xAbgscfCrGDDDJgBM2AGihlgfCa1cwjAXmZ7kq5dBCDCs9Xc+jKfX1FplgWgBWCZ9VNaAFI3h8jASLku9t03NFacckr5I1QdyYb9C80QH/1o/jmWWCKEy/EiLGr9p/t3vvniw/Pl7zJ+y2uuCfOSqWskzW6YATNgBsxAPgM4RVA7hwCk3pvBAJTRdBtJ1y4CEOHZam59mWspKs2yALQALLN+SgtAWuUPOkjCSLkuDjggfOFOO638EaqOZKPD9/jjpbXWyj8H4XcimaSzi1r/KQxGSPaqM6w8G8VbYifAA+Wee0KKwTADZsAMmIF8Bm69NdTO8XuE48Mzz4SZ690GGTR8BxGAnRCeZLpoAGFaVBoWgBaAsWt5RAp4qaWkI46Q1l23/mEPPjhMrKiSpqw6kg37lyOPLL7OhRYKPoR0MxcJvL/+NdjI9Mobqj6jI/ck6sm4OAqMDTNgBsyAGchnAKswaucQgHi+PvWUNPfc3WeLDBrBCQRgJ4QnpVl4AHIvFoAjOXAiLG49jxCAeBbROFEUWStzqkMPle68M9TolUXVkWzYvyA0iyKVpHYxlt5ss+IULyPgGEHXK3f4sly0244IK8XN55zTbkv/3QyYATPQvwxcf32wNcMOhvGh1E/Tndtt8LtE5y4v6Z0QnpRmfec70iabWABmPzsLwLjVPEIAYpb5k58U19aVORWRuVtukc49t8zWYRu+nKRky45kQ7hRa1hUq0hzB/dB+J8IHwIzC9KohNapzxhPuO660KXN26zrAMfTJ+drNQNmoJcM4BVLFI5sD/YvzFknO9RtkEHDvJmu3U4IT0qzvve98HuWhlPATgHHruURAhB/uTPPDPULdfHDH0q//710/vnljoBJ5vTTVxvJ1q5bmc4rBCiRzKIOrDvuCH9/9tly1zlWtnrllVAHSJS1aBTeWLlWX4cZMANmYFoxwCQo6sDJ9mD1ddddvamd5neFTmDsuogA4kcYIzwpzTr8cGm99SwAs2vJEcC4b9cIAUjq9LzzpJVXrn9QmjOuukq6+OJyx8Ccc8YZq41ka+dXOMss0uWXByGLDQz/O4vbbgsp5KefLnedY2kr1wGOpU/D12IGzMBYZIBhATQDku3B7J/MFA4R3QbPZ8ygST9TA4gdTUzTHqVZP/pR6GhOwxFARwBj1/IIAUjq9LLLwhi1ujj5ZOmSS6Rf/7rcETBinnnmaiPZ2k0s4XjUf5AqJsI322yjr+Xmm4Pf4RNPlLvOsbTV/vuHt8qzzhpLV+VrMQNmwAyMHQYuvTSUCpHtwf6FzBSTQboNvAcZ20nXLl3ABBsQcXVBadaPfxymW1kAjuTAEcC6qyrsN0IAkjr9zW8kag7qAn++X/5SmjKl3BEYxUaEropXUruZxUQU+dIvuWSI8M011+hrueGGMPKO2sPxBmpbuHbEq+sAx9un5+s1A2agFwwwLeqQQ4IAw/6F3ySmRHUbH/6wtPvuoWuXch1+a0jj1gWlWWecEUytLQAtAOuuo7z9RgjATixW5u9iAYNpcRlgzkmEropbetFonOR8FN4+9JC08MJBJDE6Lovf/S4U6VIgPN6Q+AHee6/E26FhBsyAGTADIxkgEMFMerI92L9QlsSc+G6D8XNMxPr0p8MkkNigCqVZv/qVhLC0ALQA7OT6HSEAOxGupomEcDXdqmWAOScRuqJu3bxjULvHv+xwbLZNmkoQfrT8P/ywxBtUFukC4TLXOda2WX11aautRs+HHGvX6esxA2bADEwLBrAiO/HEUA7EbwGNgaus0v0rWW45Cbsu5tHz20Y5VExZFaVZpLMRlhaAFoCdXMEjBGAnClbxp6Ng9Q9/KHeZ2JkQocOwmchdGSRGm7ijZ5E0lZD6xVamKEqWLhAuc86xtg21LaSvSQ0YZsAMmAEzMJIBMlGnny5RMkMXLtkpXpy7DeoM8cNdf/3w24YjRkxjJVFEGiuz6Ws3gbgJJHYtjxCAnWhZp4uYlvU//rHcpWHOSYSOyF1Z0LxBJ/Buu43eg1QykcznngtvfX/6U34BbrpAuOx5x9J2pNiZdAJ/ZesA8WjED2uXXcbSnfhazIAZMAOdZ4BxpGefLZHtWWwx6aSTpDXX7Px5skek0xg7tLXXlhZcMDTrxVirUZpFA8syy4w8kwWgBWDsah4SgJMmNTpiWnnRRcG0EuFVBqRo6ZAiclcWGCHT4UuLfxY0kyQDuBGAFODmdX5deGGYJkKB8HgE3dPcJx5X1DqWARNUiIoifg0zYAbMwERm4JRTJJ7zZHtoCDzmmCDKuo202GTePEIU54q6wMKGgAr3kIYFoAVg3TWV7DckAGeaqdGMDsXOS8RGhrE1GBWXAXODqZlA0JQFHbDM8aXQNgsif4TMiQQidnj74/hZUFRLgTDzIscriILSyILhaDv8/e/SPPOEphEsZAwzYAbMwERm4IQTgvjjhZfo2Q9+ENKy3QYv5D/9aUg3Y9bPdeBcUReYWPN7irBMwwLQArDumkr2GxKAM8zQaLql05RBy3xdXHmltMceofauDNiO7ibsYMqC1CdvVtTBZfGPf0gUzRJRJAKYVzzLPqQG+GJSIDxegdCm2YXalnZgm332CQIfsY1VjmEGzIAZmKgMHHtsqP8jCkj9HP6pNGZ0GwQe+H3hBZ1ABYEGnCvqgsAMgZJspscC0AKw7ppK9hsSgNNP32jWzmHLgmlmXdDyPnlyWLBlwJsNBpectyyIelFcS6dVFkn3L00lfBGxAsjr/KJ5gtA8D4jxCgqDGThexsvw858PDxDSIKQTeDAZZsAMmIGJykCS4SHbg/3LXnsFa5Zug0wLopORpUQev/99aYMN6p31zTdDc+Tf/hZ+z9KwALQArLeqhvcaEoBvvtlo1pQRiaPmoC7w12MMDj58ZUCtIDMOiTyWBfYveAdSw5cFYojoIAKQ5hI6wfI6v+gOwyaAFPF4xUsvBbFOSjfP6ia5LxpssCPgobTrrtLee4dh5YYZMANmYKIycNhh0u23h2gcQYCvf13abLPu3+2cc4bUM3XqRB6/+11p443rnZffMZozn3wylPBYAI7kwJNA6q2rZK8hAfjaa41m7RzpQVLBdUHTBYOweWMpA6JRm2wSUpNlgf0L495otc8CY2dc1195JcxfZDRdXucXXoU4xfNFHc8gfY4g3nrr4rtAZMMBY/FIn1NMTPrYMANmwAxMVAaYAjJ1arDKIgjAc5JMSLfx7neHzBJNd0Qev/Wt+i/c+ONiz0ZpE8LSAtACsJPrd0gA/t//NYZq56g5qIuqM3bxC2RmInYmZcGb3PTTS9iaZMEXHsNMomO045PyzKu/SBcIlz3vWNyOtAYPByKaRUjGISF46dB+4AH7B47Fz9LXZAbMQOcYOPBA6ZFHwrORF2BefjHP7zYYbXrjjaHMJjbymLY1Q1haAFoAZtfvhZIIMH9CUjKADceg4yQx+XBA0imScirmhmcB//vfDTFypoohc94XCVsVpnRgxFwGTAzZdtvyKWOO+Y1vSK+9FryWsrj77jAz8YUXgv0LnV959RfpAuEy1zlWt6HphsHj2OkUAQsCRDZvwNTDkBq59daxeke+LjNgBsxAPAP77SfhfkC2B/sX7MP4rek2yE79+c+hAzg28pi2NWsQrknBNYCuAeR9hqA27kZrSbpWEhV8D0g6TdKBkhaVRKKTeNkxmcU/FAF8/vlGs0kAARiDO+6Q1lorpBvLAENjBEzZphGOif0LtYrHHz/6DNR88GX/5z9b11+kC4TLXOdY3ebf/w51gAjAbJEw18zfeXMk6ocb/j33DHddlzWQHqv37usyA2bADBQxQK3z88+HcXDYvzBBiqa5bgOHhWQCVWzkMbE1I6OFsLQAHMlBP9cAzieJgWurSaLiLhGAVIMdJmluRuMO0sXsB/4tUiQA//nPRrM2jJqDGCAwcD0nAlcGU6ZIu+9e3jaGY2L/QtMI9X1Z3HJLKLjlzY/6i29+U2JySBZEwRCrNIKMd9BtRl3kF784+k4uuSRETBGAgNpIHiTUaBLxNcyAGTADE5EBBgXwvGM0KfYvlALhUNFtUJ5EEySNeZ/4RMi+1I08JrZm3EfWussRwP6NACJ8p0j6paSfDAq9RAAeLWlxSeulFjojsG+Qminfl1L/fSgC+Pe/N5odS9QcxIDJFAy+5o2lDBiUzZtaWeNojon9CwIGG5csqL3YfHPp8cdD/QVjzwj9Z0FdHNdKl/B4B3WA3AtTWLLggYeNAA/BBJhBMxaJSK1hBsyAGZiIDCSjQo8+Oti/UAqDC0I3geMCApDfH16wcbigybFu5JHmSCzPXn89HDcNC8D+FYA7Dtb9JfaSRPoSAXiqJILFadmzhCSsmYn5pPtthwTg4483moKJmoMYpLtwyxzn4oslinXLjo7jmNi/kDLOE2/MTKTYl5QoX/ivfEVickgWnBPLmDwRWea6x9I21FviN0VaO3uviD0egBtuOHzF1Giuu26IGhpmwAyYgYnIwM47B0cLsj3Yv5ApYUhBN0Ft+gwzhAwUAwl47iICKXOqA5ojmSeMsMyW7FgA9qcAfK8k5lesLCnpnUUAJk0gR0liauC6qQXXNgL4yCONZqcUNQcxoOsK+xXeWMrg/PPDFxQ7mLLA/oWIYV76lprCHXYIKU/G75AWRRBmQYEwwol5kRMBjODDfocayMQxnjQEndCYbGPynYCUMCmF42gTMsyAGTADE5ABfgeojybbg/0LtixYsnQTPFcRndSgY6tG9I/fVcRoHRDIoJkEYZmFBWB/CkDkDNVv6eFpsw3+73MH6wIPl4RtZNLSQeCbeA8NIWk0I4CTJ0/W88/P0DQKvvDCdbROxNwaQt80I+S9seR9Ac49V6IjFzuYssD+BcHIlI8sqCkk9H/ffaHmg/o/ooBZkHamThE7mIkCInpEUhlvh3koxc9wlJ128pOfSOecIzG1xTADZsAMTEQGeO7PPXfIMGH/gpDqtv8ppU8MUqD5hMEKm24aSpGSdHRVnglkIFz/7//CnlOmTGn+A6+++qqOD52Qs2T0QNXTjNvt+7EJBJvm9LA2OHh8MOV7lSRib0kX8EGDou/XkogMFnYBT53aqGzInLdqCH3jWM4bCyKkHc46K0ThsIMpC+xf2B5fuyyoKaRL+K67gh0NFjC8CWZBcwhva4jPiQIeEnggUu/CQ4+ut5VXDiOQ0sCsm7pIxuYZZsAMmIGJyMCXvhScD8j2MJ2KwARTOboJggpEHZOJWjSAUFtPQ0odEMggdY2bQxaOAPZnBDBvHaVrAPn70pJ4NVhh8M3gxEFLmOy+QzWAd9/dqGzInHchhL5xLEeM4GDeDj/7WajlI3VbFrz08BJEh2sWNEJgdkwkDAFEGjgv/M4bGTUV1M1NJOCDiOgjJUw3NKP5eAClgUXPHHPEj/2bSLz5XsyAlQRPHAAAIABJREFUGZhYDFD+QwkM2Z7ttw+/S/w2dBPJszWZqEVNNobQBCXqgEAGtexEFLOwALQArLOm0vsMCcDbb2+IN6ZWhsJlTsZCxXeON5Z03VnRvqeeGtKUg1HtMqdo2r/QPHL55aM3P+886fDDQ4qY9C/hd2xmskgXCJc66TjaiKgmqQ5qUahzpAs4C+pTMJGmY9swA2bADEw0Boi+LbdcsALDDQEj5e9/v7t3yfOWtPOrr0pM1KL+nNn0WJfVAYbSlDIRWLEAHM1BP6aA66yjon2GBOCttzaGmidiToDw44uW1EC0OxZijkgeqduyQDRSO3gVCe8MqG3D8iQZMZc8ALLbpQuEy553vGz35puh+2yuuSS4ygPTUngrzuuQpnaQRpKIUtDxQpWv0wyYgQnKAPV3zEonAID9C925BAe6Ccpq5p9/eKLWdtsFGxesy+og7WtrAWgBWGcNtdpnSADefHNDzNil5iAGpH5nmmm4C6rdsUjnIuSI6JUFaWP+XcvckwzOPFOiyYHUZzoFkN2OAmFqFet+Mcte67TajokudGJnzUOT6+H+EYgHUSWaArWb8IKXoruEp9Wn5/OaATMQywAduB/7WPCCxf6FxkQssboJ/GnTE7UYv0m2JfucLXsN+NpiYZNXr+0UsFPAZddR0XZDAvCGGxrNZgFqDmKQ9UFqdywaOvDuww6mLLB/wciY/bJg8DeNJXS4ktLGjT2v8Je/8UWtG5ove61jdTs6qXm4ZHm/9NLgms84vSpp+bF6n74uM2AG+pOBtAcf9i/U5aUN8bvBCtZb6YlaODNQCsVM+jrgN44OZjxrs7AAtACss6bS+wwJwN/9rqH99w9DrGOQOKHzxkLoux0QIoS5SemWBTWDxxwTBEwWDP5G1FDfhvs6Ua68wl+ig3xR6xbnlr3WsbodKXdqY5hZmQZpkyefDLWDsfWgY/XefV1mwAxMfAbSUzioicYPlfKWboIBBZQdITYBWTXcMI44ot5ZsfAiW8OAhSwsAC0A662q4b2GBOBvftNovqUgxmLByBrEAw7m7cA56VwlalcW2L9QzHvrraP34AtOcwiRLNzXZ5klv/A3tj2/7LWO1e0Sk2geVIldDw9I0r+IQyKApPOpmzHMgBkwA+ONgfQcXrJAjFUjQNBN8EJN3SE2MIDUM+U4BCzq4Oqrg4sFoz6zsAC0AKyzptL7DAnAK69sFEbVqp6EujNqCel+agdqIx58MNT0lQVNI3yhmXqRBR2wvDVhak3tBwIm7+0r1qCz7LWO1e14KFGrec89YXILIK3+05+GyOrMM0t33BHMUw0zYAbMwHhjgPo/Sn1IoZIFIihBiVA3wYQqzsvLNCD1/PLL9eupr7gieAjynM7CAtACMHYtDwnAyy5rFNbVVT0J4oFUchnxQNqZ6SFF3ap55ybCxxeLyGEW+PrddJP0q1+F7i9S0nlvX608Aqve73jdfumlw5ikZE4wljmkxumQ5m9EWTHTNsyAGTAD440BnA54ljEGjmcZQYkzzujuXeA/S+r5mWfCeUg9M16Vl+s6IJNFnTov4xaAozmwDUydVTW8z5AAvOiiRjP6k9dZW/UUpF2JImGA2Q777BM6hrGDKQu6hmnrnzp19B7MFebLQqNIq7evVlNCyl7HeN+OKOhKK4U3TKKwSy0Vhpjj40gHHQak1LAYZsAMmIHxxgCG+AQB6KLF/gVxhk1YN0EJFcEF0s0gNvVMJuvgg6XbbrMAzPvcLADjVvOQADzvvEbzy5HnrVf1FLPNFoQkMwzbgc5jvAPDSMNy4Nh42CFasuDLQiEu00V4+8KZPU9crruu9JnP5M8JLncV438r3ix5UBF95f/nDTnpCqZBhNRFlc9l/DPiOzADZmCiMIDJPb8BvMxi/4I3LIMCugkCH1hokdUCsalnMlk0St58swWgBWDnV+6QADznnIYYo5Y3XaPqaem85TgrMIiuDb7xjTA3GDuYsqA1fuutpUceGb0Hvn54MZ12Wnj7ohs5L7281lrBBBmn9n4FUVIE3vXXB0scPgPGxwHmM/Ow7MQLQb/y6/s2A2Zg2jGw7LJBgFHigv0L40b5jesmsr9Nsanns88Oz2jmt2fhGkDXAMau5SEBeOaZjaZ1St583aonoZOU0DVDrNuBFCNdw7zllEX2LSu9H5Es6i+I+rVqMPnoRyVc2vMmYZS9jvG+HXWaCGG6qhP7l6Trl0YaBqjbCma8f8q+fjPQnwxQ0kLql5o83CFwN2BGejeRzU5RkkSzIkKuDqhZJIDBYAMLwNEcOAVcZ1UN7zMkAH/600ZzkSEGYrHAAmHBr7pq+yPVMcpsNR4nnVJuZTGz2moS595ii/bXOFG3eOkladKk0Oix0EISHdQJiJxi42MrmIn66fu+zMDEZmDxxUPkDzsYpkOR0SDI0U1k69PTTYl1zpsebGABaAFYZw212mdIAP7kJ42h7tnYk5BOZOHSRNAOdUbltBqQnU4pY/+CWMQ4OgsKhNn2s59td4UT+++IdepV8FSkZiYB3dN0c/P2yoPUMANmwAyMJwYWWST4/mHLQoMjY0KZENVNZB0q0rZkdc7L9SNc86YyOQXsFHCdNZXeZ0gAnnRSIypUnT7oYouFkPvHP97+8kjDzjefmlNIygL7l9VXl55/fvQe6ZQyNW3XXZcf1UTs0IFMx1Y/A8Nnon0YmE6XiafbCqafV4bv3QyMbwYYA0oKFTuY9Iz4bt4Vti377TfsUXvCCSHqWLe0it9R0takr7OwALQAjF3LQwLwuOMaTVuVTvgkMWKNrqt11ml/eTRh8KaGGCsLrhP7ErqHs5g8OaQ1Sf9SPMubU96XjwJhagT73ecOfyoMoTFLzeLTnw4Pz912K/vJeDszYAbMwNhggMACXbRM5sDh4rjj8pspOnm1WdsWmulimiu5ZqaBXHyxBWDe5+QawLjVOyQAjzmm0eyq7YRT+jLLBOPNDTZof3E0YVCsS+1eWWD/wjmoT8sCe5g55gjijkYQvny4qWeBRyGNJ9jBGPkMYAVDnSBvsYYZMANmYDwx8J73hJGgK64Y0qiUBOXZqXTynrK2LbhRxNirMcQAl4bEnit9rY4AOgIYu3aHBOARRzSaJsCdmJW4/PLBgiWxFGl1kTRhkI6lHq8sEKqML3v99dF70Lk6//whpcyXj2YU3qCyYEoJEUK6YI18BlgLPNBsBeMVYgbMwHhjYPbZw7N/ueVCIICgQJ6hcifvK2vbwohT/tUdsIBopT773HNHX6UFoAVg7NodEoCHHtpozi+k5iAWpGeJ6JFCbAeaMOjIrTJxgqYFmhdoVMjWrZHKRNxhAIoZNBFNLE2yYE4x7fXYwRj5DNAVzizNPL9Fc2YGzIAZGMsMzDpriJ5Ry0wdHWVGeSPVOnkPWduWs84KmSj8AeuglZOFBaAFYJ01ld5nSAAefHBD//lPaJuPBTNlEXSM4GkHmjCIwmHJUhZEKvEaxED6rW8duRdzH5lAwhg4jI5JX+aZaGJxwt/LWNWUva6Jtl1iBcO6mHHGiXZ3vh8zYAYmMgPvfGeIni2xRGjEIMt0zz3dveOsbQuRO5oR8a6tg1ZethaAFoB11lSuADzggEYzokbzRizo0MXeBTHWDjRh8I/ty4LZwXPOGWoA3/72kXshOjGg3mOPkL4sGqMz77yhO7iMWXXZ65po27EeeIhiu2MrmIn26fp+zMDEZoDfBhwjKBfC/oUgw/33d/ees36D1O5hBv3HP9Y7L6VMZLzypllZAFoA1ltVw3sNRQD33bchpkDgnB6LNdcMI9byOkuzx6YJgzQwdjBlgf3Lu98duoARKGmQdiatu8suYRpJ0SDtKuPqyl7XRNyO9Mkhh4RxSoYZMANmYLwwQHaIhkFM7iln4Tfmr3/t7tXjqkDjSWLbQvfugQdKf/pTvfOStibgkTfP3gLQArDeqsoRgN/+dkONRujejQXecjR3bLtt+yPVmcmL8ONaEYLUeaSBUGH0z447hi8iX6A77xx9HbPNFgpzSRcbxQwgqKnR3H13s2QGzIAZGB8MvPmm9Ja3hOgZdjCUAX3hC2FOfDeRtW1BCO69d/5vUJnrSE+2ym5vAWgBWGYNtdpmKAK4556NZlqV4dmxWH/9YLD81a+2P1KdmbykfvGu482ITq80EH+bbBLOTd0HqWBMjrOYZZZQl4EdjFHMALWUCG5bwXiVmAEzMF4YoD6cjBb14tjBYP/ymc9ITz7Z3TvI2ra0+g0qcyXULb766sgxncl+FoAWgGXWUCkBuNtujWZnLfYtsdhoo+CvRxSuHerM5M1+udPnYO4jtYd0r1L3gTH0X/4y+ioYc0ZtGx3DRjEDWMEwSi/PSse8mQEzYAbGIgPZIAH2L/jS/uMf3b3arG1Lq9+gMldCMyWRTGYKZ2EBaAFYZg2VEoA779wQI9ywT4kFETjmL1KH1w51ZvJmw/vpcxBRxAvwi18MdR+koR9+ePRV8HbIRBHsYIxiBuCQes5HHzVLZsAMmIHxwUC2TAj7F0aTPvdcd68/a9vC85Pfo4ceqnfenXeW3vGO0EhiATiaA08Cqbeukr2GUsA77NBoTtcg5ReLTTcN43fK1I2tsIK0777VZ/JS4EtBL/Me0yCiSNTvc58LdR9EAx97bPQd8VaFvx12MEYxA6RMMNbmjdpWMF4pZsAMjAcGso2C2L9g+TUw0N2rp+nwgQeC+TPgN4hpV3VfoHfYQXrXu0IjngWgBWCnV++QAPzKVxrN+brUzMUC8YX7OqPE2oEmDL40VWfy0uLPl5o5wmmkI4q03hONfOqpkdtgbzL99BI+d9jBGMUMJFYwdLHhp2WYATNgBsY6A1mrMMqAmFD18svdvfIDDgiNJkyhAtQe4nLBb00dfOUr0txzh07iLJwCdgq4zppK7zMkAL/0pYbw79t119hDhvQrYoHup3aoO5M3bfKZPkc6oohooRaRh0EaFNUSzaIehMYXozUDRIYxJKW20zADZsAMjHUGssMCSMEuuaT03/9298rJZvG7csop4TzUHhLcePrpeuellh0bm/32swDMY9Ap4HrrKtlrSAB+8YsN0UBRZSJH0albLdrsPnVn8qbH/KSPmY4oYv9CTSDpgDSYbEETCPUg+AkarRnohhUMfpNYBZFeNsyAGTADnWQgOy6UqNzCC0tvvNHJs4w+1re/HdLMiWvC7ber+bv67LP1ztsqmOIIoCOA9VbV8F5DAvBzn2s0zX6rTOQoOnmrsHV2n7ozedODvtPHTEcU77svTPqgIDiNF1+UsIHhi4qfoNGaAepC4awTc6I5Ew9heGfqTBmrIH8+ZsAMmIEqDFDfzQSQ118Pe1HLjB8gzx7qv7uFPfcMUcZjjw1nYBLJRz4ivfBCvTO2KqeyALQArLeqcgTgpps2RPNGlYkcRSdvVbia3YcmDAZm07xRBXg7YfS84ooj96KTGaFCxxfFuEQEaWBI41//kjCCph4EP0GjNQOMNzrnnGCr0wnQfU06Bpug44/vxBF9DDNgBszAMANMAGGK0SuvhP9GWpbfDMp/3va27jG1227SdNMN27bwrOM36qWX6p2zVUOlBaAFYL1VlSMAN9mk0azdw/IjFq1a17PHrjuTl7c5Zv3SbZwGYX4Gcq+xRrB/QRAmb4HJds88IzEKjjc17GCM1gx02grmF78Irvx05dElZ5gBM2AGOslAVnhR7kPWiPIfbFW6BazPaFBMbFsQotRQZ4MQZc/fylLNAtACsOw6KtpuKAW84YYNkbqlZT0WvAURZj/yyPZHqjuTF/uXM84I4fU0MLM+++wgLrJ1IMl2vUoHtL/78bFFYgXDw5OHWyxwt6c7jhpN0vDdTMnEXqv3NwNmYPwxkE298pyhbpxSlkmTunc/ZDUoL0pGqpKKJgjB8II6oCyLRkaszbKwALQArLOm0vsMCcD11280G0AozI8FdRCE2n/4w/ZHqjuTF/sXplRgOJ0GLfMM4MbSJtsJlmxHQTCdVVicGO0ZwHibphk62kjdxoL0PGOZcLm3GXcsm97fDJiBLAPZ5gvKfXCOoPwHX71ugZpmghrJSNWiIETZ8zPalLGq229vAZjHmbuAy66k/O2GBODaazdEZAbPoljQCcWbVpn6rrozeRdfXPrRj0KHVRpzzCFNmRI8nxIvqGzYH0sAbGoQqUY5BjplBYOYRPQzWg6HfOwN6DI2zIAZMAOdYuDWW9VsakzsVyj3IXtB+Q+/Ed0Ck6eoa09GquJBS5kTZUh4z1bF2mtLm28enpVZOALoCGDV9ZTdfkgArrlmQ/vsU30iR94F4IXEF+3kk9tfXt2ZvEstJWElwhtSGrzdXXddqLug84r/nQ3798oUtP3dj58tSG3QrLP++sEPkP+LeK8KHPHpzqMomrdlUvmYpxpmwAyYgU4xcNNN0mabhTIgQPcv06MQZGSJuoWttgrz5ZORqkm9Oc0odSYprbmmtPXW4Z8F4GgOHAGMW8lDAnD11RtNs9+qEznyTs8POuPXTj21/cXxpcCupepMXiaN4I7OW14aaYNoRAb1Htmw/733Squs0v2xQO3vfvxsQeQOY23S6/y7//7QaEOdJ2K7LC68UNp//1D/x4Dz3/9euuiisnt7OzNgBsxAewZ4riCaqMEDyfx4yn+oE+8WGD2K80QyUjVxnOC3iGBHVTCcgfQvTXMWgBaAVddPu+2HBOAqqzR0xBGh4DQW2XmIrY5HWJxu3aozeWmtZ9IIXVJpEOanAJgoE29ddHxlJ34gPniz6vZg8Fgex/L+fGZ0uvGmTW1gWWsFosOMRaJT+9prJVImdedkjmV+fG1mwAxMOwZ4tiCc6MJNwDOK7A9OEd0C6dr0SNVYz1kCFUzn4rgWgBaAnV63QwJwpZUaOu44aa214k9x6KHSXXeFlGErxMzkxf5l993V9C5MgzA/X3qaPJKwP12s88wzvBWRLFKYCEOjPgPUUC67bBBx1I+WARFm6lqwS0isGZjUQoeeYQbMgBnoBANXXRWEE01mCQgG8PJPV263QHMbzhQ0uIHYqVOISaKJHDcL1wC6BjB2HQ8JwOWXbwjDX0anxYJIIkW4557b+ki0xuPDR6EunVNVwJcMw2lC7gmSMD91H/gEFoX9//jH0HiAMDTiGCDVgpi+555Qz9cOFERjKp3Y9/A54QtIqsMwA2bADHSCgcsvD8KJbFACyoF49nfCyaDoGjfeODQmJiNVY+fO08xIQwnHtQAczYFrAOO+LUMCcJllGjrzzOoTOfJOf8wx0vXXS+ef3/riMMdkEgdzEukMrQLsX5g5TNFtgkRQYv+C6zsg7E+9WrrG8A9/CMKRehAjngGmx8D5ZZcFF/wiEHGlABtPrsSLa4MNQtkB5uGGGTADZqATDFxySRBO2MEkYO47pvZVaparXgvPs/RI1aIsVNnjcq14CnLcLBwBdASw7Doq2m5IAC65ZEPnnSetvHLsIdVMJWPzQbNAKzCjl5mwdOtW7SjlLYs5iaQfEySCEvsXXN8BApOHAJ1ZCXgI0FaPHYwRzwCFztjyMAC9lY3QlVeG1C8j+hLQLYcwJPpsmAEzYAY6wcAFFwThRCYqwZxzSjyDiKp1C+usE8qSkpGqsc0nRCuZmc5xs7AAtACMXcdDAnCxxRrNCM4HPxh7SOmkk8Kc3l//uvWxqP3iraxOhxT2LzSAYCWSIE9QIjBpVHj/+4e3Y6YtzuoUBBudYYDo8Te/GWpuisQ8D+Q77hhZGvDLX4ZmEhpJDDNgBsxAJxjguYJw4tmfgDpwHAeoq+sWMLnPjlSNaT6hXpEX67zafAtAC8DYdTwkABdeuCGEEUX9sSCaw5xeDJlbITFqruORRJgdEYg/XYK8lnsEJh1h6fviLXCPPSTsYIzOMMCbLlFZDLYx6M4Db8a8YCQWCWyDCMc2gZcAGngMM2AGzEAsA9QVn3hiKEVKgP0L9cd01nYL1NAT/UuPVKX5hKZInCmqgo7l007Lr823ALQArLqestsPCcAFFmg0vyxLLx17SOmnPw1zeq+5pvWxklFtdVzS84Zk55luEvanIDgd2STSiek10SijcwyQ2kVo0xiSF0lmfB9vs3QBJ6BGhnrATo2Z69zd+EhmwAyMVwZ+/vNgNfXb3w7fAWKK36ZuNpyttlrILlGelIDn2y23hJfjqsAeDTcNjpuFBWB/CsDvSvqiJKrcmGZLHItZCr9JLRCseY+TRLXDgKRTBrcpFIDzzNNo1kvUWaTZg5IOZE4vEzlaAbNoFjh2MK2aB/KOQTQpsYJJ/p43doeuU5pR0rWNpAEwvXbaserjqP32jAHEZgcbhjSSYex5o5g+9KFgm5B+aLY/k7cwA2bADOQzQNTs7LNDLXoC0qmUJ+EB2y3wO0N2KW1PxjQqXorrBFfyfr+Sa7cA7E8BiIsRDnYIO5Jmu0g6RBJ9tC9LmiSJMvvTJB0oicDzFZKOlHRMZuEPRQDnnLMxZKAc++UgzE4jyA03tD4SZsI0Z9C9WxWIBaaBUHeWgK5e/P8QlAny3qBodsGq5uabq57V27djAG8/PgPqPxOrF/bhZYC0SDKaKX0cDFt5SP7gB6OPzpQYbIKoo8EyiP/LG3WddEq7a/ffzYAZmBgMnHKKxNShK/jlGwQNFThUpDMQnb5bMh80tqUHFNCQiBDl96oqsEfjWZqXUbEA7E8BmF5DM0raQdJukhaRhJRiauBhkph4mEghRCL/2CaNIQH47nc3hgyUqy7S7PZlBRYpQ+q/6N6tCuxf6DxlGkgCunqJYOK9lAD7F2oSsY1JUFagVr0mbx8YwH4BwUf6JYns8uClFhN7hixIC/Pfqc1MA/seHpp4BfKSwOfK/0VkYuha543an5EZMAMTnwGeKYg/mhETYKnCSya+pd0CJTDf+97IEaVYknEdTK+qCuzRKKXKq823AOxfAYgr0JmSZpH0mCT+d9LScLSkxSWtl1pslL0Sj0PwvZT6700B+MILA5p11kZzfu/881ddoqO3L5tiJbpD+o/u3arA/gXj4f32G96ThgIEA+7rCRCJNCXQoJCAFDWiEDsYo/MMYOtDFJDUe5JuQbDz35gTnQW+jNjHUBOagKYS/AGJEB977Mg9OOYWW4zsAO/8XfiIZsAMjFcGeGbwAkoUMAH2L8wh32ij7t3VUktJhx8eGhQT8AJLUyQlS1WBowLPR46bhQVg/wrAZC28azDNu6Eklgji7lRJjJ3eIrVgKD9FIM4n6anUf28KwH/9a0BEAKmhw6g3FmWbLOiMWmMNCTuYqsD+hTerA0lyD4JpFKuuGoyGE+R9ISkERgTS9Wx0hwHmQdN8QxkAUUCiddRd5jnaJ/Y96ZnNRAQR+Yz1Iz2cBl3ErBnSPIYZMANmIMvAUUeFEh/sYBJg/7LXXmEKVLdABgrxmQ44EKioO2Rh5plDTTWBjCwsAC0AWRPMXkDykPrlfYcIIIJv3dSCaRkB3H77yTr55Bmaw7M32WQdrZPnOlnhG0Mqj9mwCLJW+POfg8EldjBVgf0Lb0d4yyWgqxcfJlKECQidIxLTb300qBCdyqYcq16Dty9mAFFHxI8HHyKfuj1qPrFiyAMdwtg28ODEFgjfRuo7WZNZUGKAwEy7/PuzMANmwAwkDOAtyu8BdjAJsH+h2WyzzbrHE7XJJ588stGEZ1vdMaszzhjsyjgGmDJlSvMfePXVV3X88cfz/5IJfLF7dzV2j+xRcKERBAH4KUn0PDEc7XBJ80h6Y/Cj21XSToMNIelPsxkBfOqpAdEFjI9eNtpS56MnssYsRGq4WoHWeCJC6dRf2fMxUYIvB+H2BHT1MjKHSFIC6i7oTE2/9SE0KKwlUml0jwE+G97AaQii7oaRf0Xd3gw7J0XCiwOinv34PKeffvT10exDbSciE48twwyYATOQZoAXREqCsINJgP0LL5Rf+EL3uOKl92c/G2k1Q/SOZ2CemXO7K+H5R2173px1RwD7MwKImDtb0jOS5pB0sKSPS8LBj+q3d6a6gA8aFH3M5DiqqAv4sccGhA/giy8Oz2httzBb/Z3aOsww//rX1ke58cZQy0XtYVXsvrtEnRhu7wlwfaf9/oknhv8bomK33Ua+9VETSENCuj6k6vm9fXsGqMXEe4sOtv/+d6QlQ3ZvorQ0BR16aEh3kD5OdxGnt+dzpzuOUYN16mraX7m3MANmYDwzQK0xL4rYwSSgdnjrrcO/boEa+nPPHWk2TTbjyCNDTXMV4GaBACyqzbcA7E8BSF8T/UQIParnaGWgFeKR1OJCDBIbXmEwNHziYK1gdv01I4CPPDKghRZqNJsnOhFRwVCacTiPPtp6ueONtM02ITVYFaQH6R5OT53IOy8i4mtfG/nWh2hEfFKYa3SXgR/+MKRd9twzjHwrAmIOc266wnnwpVM3efsQUeSBSiTYMANmwAykGdh335AJStcJY/+y+eZhDny3QA09z7L0uDmeaUQkP/nJamfF8QDrq6LafAvA/hSA1VZR662bAvDBBwe06KKNps0GPmuxyIvE5R2TKBzijMhPVWD/QiMA6dwEdH195SsjI495b32kJqk/xCjU6C4D1PNRF4PoptO3CLwsEC2caaZQOkDnXCtgNcOLAxNnDDNgBsxAmgHKfmgGxA4mAS+NlBzl1RV3ir055ggjUOk4TrDCChKC9FMUaVUAz04CMnnm+RzGAtACsMJyyt20KQCnTh3QEks0xFiut7wl9pBqThRhVi8Gvq3AtAiiQ9jBVAX2L9QO0tCRgOPtuqs0derwf8t766PGjHNaPFRlvd722MI0Gq3XFmldPK9w0cdItR2o36ResF2dabvj+O9mwAxMPAbIOFB2kraQQvzxe8Cotm6B2fOUQOE5mACrMzJW1DlXAfPRaZ4rqs23ALQArLKe8rZtCsC77x7QBz4QBGAnQHcm3ZwU/bcCdV605WMHUxXUjD3ySJj3mIDjYRFy990bsQ2AAAAgAElEQVTD/423PjqAiTQmwKiT6FF636rn9/adZwDLF4qo30pbUxuQ3iHdkojLdtv772bADPQPA9R903CGHUwCBBiNIAQJugVedMmAUfeXAGsySlVIP1cBzzaaMotq8y0ALQCrrKe8bZsC8PbbB/ShDzWab0ydAAKM2jsWcCvg9YYxJ+nYqjjkkBDpS0fxOB6pwbQ9CG99iFG6khOwDXUV6ehh1fN7+2nPAJYydNylp7xM+6vyFZgBMzCtGdh555A+TdcdI8CozSPL0C1QwsLvDwb2CbDBwre2avcxARRSykW1+RaAFoCx67gpAG+7bUCrr97Qy0wS7gAQZtivEMJuhQsuCKN5sIOpirw6vrzj8daHGCXVnIAUI2H1dP1g1fN7+2nPAJ9tkl6Z9lfjKzADZmCsMLDDDiF6RqAgAQKM1CxZom6Bpg1+/7CpSlC3+5gSKrIcRbX5FoAWgLHruCkAb755QJ/4RLCB6QRI5TH5gSLWVsDrjRmxdORWRV4nL+33dJ2mj8dbHzYk1IQkyOsgrnp+bz/tGeDlAZd8d3NP+8/CV2AGxhIDNAMintKTorB/WWyxcjXGde+FGnpKkxZccPgIdbuPsTPDVqaoNt8C0AKw7jpN9msKwBtuGNCGGwYj6E6ALwBfNNrYWwGrj5NOkrCDqYo8L7+zzgou7OnjbbllqMegKyxBnodg1fN7+2nPAIbj+E22sxua9lfqKzADZqCXDHzpS6GeOD0rHvsXykYoAeoGEt8+hNu88w6foW73Mc81IolFtfkWgBaAseu4KQB/97sBbbppo9lu3gk8/nj4ovGFKJr8wHlwaWcuL3YwVUH6lqaPS3FFHAT1YPxLHw+fQb5EtOEnoCD37W9v7UtX9Xq8fe8ZSIqki2wSen9FPqMZMANjgQF8aJnLi11YAuxf5pxTogmwG0h8+3CnYE59ApoQ8SxlfGkVMEiB4EVRbb4FoAVglfWUt21TAF5zzYC23LLRbIzoBPgCzDOP9Prr+aO8knPg0n7OORL2LVWRN8+XeYukAwdHJTYPSYSItzGc4RPwRZx11pH1IVXP7+3HBgNEmikj4C3bMANmwAzAwOc+Jy23XLBfSYD9C1266fnxnWSLwQQ0gTDbfvbZh4/MGNKPfrS6aT0WV/gJ0gSSBwtAC8DY9dsUgFOmDGi77Rq1RrLlXQBfAN60qAFkXm8RcGm/6KIQyasKLFxI+ZIGTEA6mYggc34TYP+CN1O6GJiOLN7Q0vUhVc/v7ccGAxR203GXTvWMjSvzVZgBMzCtGGAk6CqrhDGgCbB/oUkjPT++k9fHbHIEJgMKCDAk2GwzaeWVJUqPquCee8I9FNXmWwBaAFZZT3nbNgXg5ZcPaPLkRq2RbHkH5QuA6KILeOaZiy8Rl/Yrr5Swb6kK7F9OPTWYbiZg4PbVV4dRPAny7AC23TYM17ZoqMr62Nue6N8114wsBRh7V+krMgNmoJcMbLKJRPctz/8E2L9QlpSeH9/Ja0p+9xCC72RQ6yDyopFlznvnncHiqqg23wLQArDMOmq1TVMAXnLJgPbYo1FrJFvewZM3IWq0Zpml+PS4tCPgsG+pCsa4HX+8dMMNw3vyxf7DH6Tzzhv+b3mGoFttJS2++Mj6kKrn9/ZjgwE+b+xgKDtoVW86Nq7WV2EGzEAvGGDu7gYbSNjBJMD+BaszAgXdQJL5IhVMjXmCvHrEMufH4WC99cIouDxYAFoAlllHbQXgBRcM6DvfadQayZZ38KQWAiNLxnsV4cgjpT/+UcIOpiqo9WP/m28e3pPQPl8a6goTYP9CKpqu4QSf/7y07LIj60Oqnt/bjw0GqI8h7ULnOZYJhhkwA2aApgteDLGDSYD/63PPBeeJbiCpfacZJD3NKK8jucz5+W0kkllUm28BaAFYZh21FYC/+tWADjywUWskW97Bk24ojCznmqv49IceKhHmxg6mKi68UDr4YOm224b3pLj33nulM88c/m90gRGaT5s+Ux/y4Q9Xr8moeo3evjcMfOADwdqBYmvDDJgBM7DWWmHyBuIrAc+IJ5+UaBbsBhLfvqz7BSKUpsh0I2KZ85PdIH382GP5W1sAWgCWWUdtBeDZZw/osMMatUay5R28yA8puy0C7i9/CXYwVUGzB9Yud9wxvGfefGDq/HgzS499462K2grsYIzxzwD+XjQddau7b/wz5DswA/3FAF23PBdIvybA/uWhh4L1WDdQ5NtHGpqaeH7vquC664KAZW59HiwALQCrrKe8bZs1gGecMaBjj23UGslWdAF5jujZbXkj+tvfJOxgqoLmkW98Q6JTKkGe2EMU8gVKf+k33DDUVlT1Zap6jd6+NwyQ0qHuM90R3psz+yzTigFeHLEAct3ntPoExvZ5V1tNwvaFCFqCvAxRJ++iyLePRhTsYch4VQHNbYjHBx6wACzibboqhHrbUQw0BeDppw/olFMatUayFXGaNxMxuy0RvH/8Q8IOpir4sd9pJwmvpAR56d68Lz3ij3Rhuj6k6vm9/dhhgLrPj388pPotCMbO59KtKyHDwPMF03fSfIYZyDKA7Qpdv5T7JDjiiFAylK4R7yRz/BatsEJoNEmDOfTTTx9q1qsAP1uaGO+7L38vRwAdAayynvK2bQrAH/94QD//eaPWSLaiC+CN5/bbg0dbERjPNjAgYQdTFXQPY/LMW1cCGj5wTae7OEFeY8gnPiHRCJKuD6l6fm8/dhhgWDpdd9TKzDff2LkuX0l3GOAHFpsNGsymTpXmmKM75/FRxy8DzH+n6YNynwRYRuEakXaJ6OQdko1addXwm5YGmSrq4plTXwX42fIbeddd+XtZAFoAVllPeds2BeBJJw3o3HMbtUayFV0AnZk33RRG2RQBwcaPd9UvBsfji8yc3/Qc2DzLF6xh2Pb884evgvo/vADT9SGxRHr/actAmReOaXuFPnunGKCTk0kL66wTxB+eoIYZSDOAywM1f5T7JMD+hcwRwwe6AerRyUSwPtPYay8JazRsy6oAP9v99w+BlDxYAFoAVllPeds2BeBxxw3o4osbtUayFV0ARa+//a1Eh2YREGzUClYNjXM87F9o86erK0Ge6XOeOfRHPhLq/9L1IbFEev9pywDRIGpmePAbE5uBpNuSmeO8YJ57bpi1apiBhIGllgoTPyj3SUCt8GWXhX/dQJFv3z77SFiiVbWfIWjxgx9It95qAVj0ebkGMG4lNwXgMccMaMqURq2RbEWnpyvziitCTUQR6hbHcjxqOTD6pIYwQV63Vd54uMQCJl0fEkej957WDJD6JbVD7Y8xsRl48EGJH3jKPU4+OXR/k35LT1+Y2Az47toxgNE/3q+U+yTA/oVnBA2E3UCRbx9RPF5aqtrP8GJD2ppMWh4cAXQEMHYdNwXgEUcM6He/azTn6HYK+B4Ral9ppeIj1m2P54h54XZqAuedd6TfEl86jKavumr4OlZcMUwBSdeHdOq+fZxpw8Cii4ZmItL7xsRmgJqo1VeXmDREQwiWH7xodmvE18Rmc2Le3SKLBOuv9PMAJwg8YrvlFlDk23fQQaFWvar9DP64+Ndef70FYNEqdQQw7vvbFICHHjqgm25qCHPlTmGBBUK3FcOsi1DXIJPj5RXcbrON9N73Bn/ABHQK8u/aa4f/W159SKfu28eZNgwsvXSwWVh//Wlzfp+1dwwQafnUp4K/J8ASZrnlQsnJhz7Uu+vwmcYuA8x6pzaUcp8EiD8CAun58Z28gyLfvrr2M/jjnn56WNd5cATQEcDY9dsUgAcfPKDbb2+I8WqdwsILhzce3tSLQBcu26UFW9nz57Xc0xRCTRCdUwnOOiukiX7/++H/llcfUva83m5sMkCkmVmf1IUaE5uBvB9aTHZ54SQzgOWG0d8M5JWEsD6oCU/Pj+8kS0W+fXlOFGXOiz8uM++vvtoCsIgvRwDLrKTibZoC8IADBjR1aqO52DoFTFqpv1tzzeIj0oW75JIjBVvZ8+eZbm6+uUR6l7b7BNRR0GV8443D/436EB4EjAsyJgYDa6wRfB15CTAmNgPUcO2++0h/tGT+OFHB97xnYt+/7649A6wBmj2wg0lA/R9egOn58e2PVH6LIt8+ShNID1e1n6GkhawctfR5cATQEcDyqzN/y6YA3G+/AT38cKOjdgoIOwpY1167+BLpwl1+eQk7mKrIG7tD9IeQP8abCS64IBSJpzupqA8hFUDtkDExGMgb/j4x7sx3kWWAH0Xqqui6TPDmm9Jb3xpqrRZayJz1OwPYBFHrl3YFoCaddZOeH99Jni6/PGQh7r575FFpRqEEqWqJFf64iL+i2nwLQAvA2PXbFIB77z2gp55qNOsNOoVllgkt7K1qsujCpUYQO5iqSKwg3ngjWMmAjTcOXV9MCElwySUSQ8DTXkrUh1APwrggY2Iw4PnOE+NzpOidzECrjl6K4/lxzKbyJk2SqA/k5dPobwZmmSVE3Sj3SUBEEHPoO+/sDjd5vzWciTWNOKzaZMlAA+r/ioSjBaAFYOxKbgrAb31rQM8912h2TXUKRPZof99oo+Ij8qNNihg7mKrA/oUwP0bSb3tb2BuxiQjcfvvho+W9ldkypCrbY397Jrvwtv/Nb479a/UVFjMw66wSqbRWzRxFtVFlrKfMfX8wMPPMIUJMuU8CSgcYD3fvvd3hIC/bxJn4XeVvRancoqs56qhgAVNUm28BaAEYu5KbAnCPPQb08suN5ptKp0BRPg7ozNwtAi7tiDbsYKoimQbwn/9I73hH2Jt0M3WAX/7y8NGwf9lll5Ezg/PqQ6qe39uPLQb4zOk8J9prjF8GmPGLAGxl58NEBX7MsxGVBRcMkf105+f4ZcJXHsPAjDMGoUe5TwJSwpMnh67xbgC7Mer9sr597Zo5iq7lsMNC5qqoNt8C0AIwdh03BeCuuw7ojTcaTePMTgGzZVK7m21WfERc2hGIFO9XBfMWiRa8+KJE6gcQTdx66/AvASF0jp+eGZxXH1L1/N5+bDHAg511QNmBMT4ZeP31EM1nBmqr0hEK+W+5Jfh7pkG0h7RZq7rj8cmMr7oqA3SCP/SQRLlPAuxfeFHkv3cDRb597exciq7lkENCoxMvNXmwALQAjF3HTQE4efKA3va2RkeNVHkLJ7JHaq4I1Ovxd+xgqiIZCE8kkLFzIO+cmGhSU5SeGYxwpH4oXR9S9fzefmwxUHfg+ksvSV/4Qmgcson0tP1MmZfKDHFSXp/9bPG1MOOVFzr8PdOg7IQIMGUgRv8ygDk4ApBRgZT7JKAmkN+bv/2tO9wUCb12hs5FV3PggdLDDxcbSFsAWgDGruSmANx++wFNmtRozk7sFPgxRdhttVXxEdlm222DQKsKxkC9/e1hFBy1PyAv6kg4nh+T9MzgvPqQquf39mOLAbwkWQtYJ1QBY8WIHM00U1gnRJeYK2z0noFnnpHmmkvih7TVM4EpPv/61+jZqquuGuqJt9ii99fuM44dBl57TaKUIGsJRIMQGaf0b0Enr5omSnxns5NGiFTjiJG2IitzXl5muNaiEXIWgBaAZdZRq22aAnC77QY0++yNpl1Kp0B0D5sXBF4R6MIldcd2VUH3L7YPfEEYOwfwAMQEOl13mDczOK8+pOr5vf3YYoB0ydSpwf2/CugIpHSAWhu6x3lhOPLIIECms8toFSqjtyUyQ8oO4/avfrX4cHgAYvuSHf2GrycRnlbPnOiL9AHGPAOJJ+Q//ylR7pOAphBKC9Lz4zt5MzR7nH/+6FnDNIBQmkLZQhXQsUyGCz/dPFgAWgBWWU952zYF4DbbDGi++RoitdIpUN9Hl2+rB/nKK4euLOxgqoIfAOxf+NGg+B/kjXjLmxlMeoDQOkXjxsRgADHAG3bVaTYIPupUSRexprBcIIpEoxCRQKIJdJrzfykoJ51jdIcBBDwWLnyWaS/P7NkoLaGMI/vCSlMZfpC8VBr9y0BSSvD882GdJEhe9hBV3QBNlNSvYjeTBvYwOGL8+c/VzoqnIKVODC3IgwWgBWC1FTV666YA3HLLAS2ySKOjHZQ8jBGBO+5YfIm4tPOWg1CsAwrG6ehinBzIG/HGzGC8BmkWAUl9CD6C885b56zeZywywFsyD97sw7fdtWLQ+rWvSQ88MLwlDUa49iMISSWxzp5+OjzE+ZvRHQb4gVxhBYlobnqcY/ZszPzmO7/ffiP/kjcJqDtX6qOOZQYQftSFIwTTfpJ0BfNb0K3vME2UjIPDcDoNRCHr+a67qrFGcIRMF+njPFgAWgBWW1Gjt24KwC22GNBSSzWaYqxTKOPxlxexq3J+7F94q2PsHKCWiy8h6ecEyaB47GJAUh/CDzr1RsbEYIC506R/eQBXAYJxn33CDNlWIGL8vveF9WN0hwEas2jk4vNolY1A6PHymJ0ghDB873vrzRbvzh35qNOCAVK/1IWTCqZOPP1bQKMQUbVuoGjkW9GIuHbXsOuu4eWTuuQ8WABaALZbQ+3+3hSAm246oOWXbzR9+zqFMlM+8iJ2Vc6fdf7n4U/BbLqbk5b/JZYIaTyQ1Ic8+6yL/atwPda3zZv5XOaayxZo88Iw99wjjcfLHN/blGeAofdYuBD5KPrR42h5E3/470Wp4fJX4C0nAgM0f1AXzssadeIJ+C2gxIAGwm6AJkrqDM85Z+TReSllbaazDGXO387aygLQArDMOmq1TVMAbrLJgFZZpSGsNDqFMnN+8yJ2Vc7/rndJ110nMXYOUNNHF1Z6xFtSWE7ql6L+pD7khRckxgUZE4OBojFM7e6OyCE+W9nOvex+lBCwXrxu2jFa/+8XXyx96lPhx5JRb0VAJFK3ud12I7dolzKrf2XeczwxQD0vdeHJMz+5dn4LKB0grdoN0OjBHGB+g9LgN4rGpKr+g0y0mmOOML84DxaAFoCx67gpADfccEBrrtloWXhd9UR0UfK21aqWh6J6Oqfq+q8R5mciAGF9QE0fXVg0lyR46qnw3zGZpfkjqQ/B/w07GGNiMED0iOaN+++vdj9l53QmpQOsJyKBRucZIHLCiyOp3FZzyUkTU7eJf2MapI5J/9FFbPQvA488EsqCsuUaOEbgC5ieH99JlhBq2Epl/Snr+g9iWj3//KH22AIwnwMbNcSt4KYAXG+9Aa2/fqNpg9Ep4AHI2xb+bEXA8oHoSzpiV+X8hPkpuGXsHKCmj4Jb6oMSJN5ir7yi/9/enUBtl053wr+ClWDxhhAk2lTGmKeKGEIJlfIZkjZUOiSpiE+sQgglNMUiA9FYqmKshS5JaUMMIVmFUoQkRXyaSD5TJwhdxCxYN41G+3zrd5/nqFOnrnPOdYb7ee/nufd/9dvEc4br7Ps659rX3v/934n8S/v/HnO/OHZ7LYA/xiEYK/JK8oU8gxTyEBSEqFRFNQgsbwEtsyx6ont9v4f3mxZgu83k055WbQDGSgEt/yRxxaNpAU6YrBC6TxO5/vFLjpOjJvp45pkXvupU/UEdrQRJutbQiABGBHDu/F07gMcfv0r3uc+R9a56KWi/xkH7gz/ovqLdmGrLZsRuzP2F+UUNVHaByi+t3252swuuQjCWnEcd8WtHBMfcL47dXgtM1fhSbKDAoy/iVD81SQmdZW5yk+21w0EemR6/NqEUBKT0u3CjG1UcQSoDTZx2WiUF5JsS2F0LaJ92m9tUdJ8m6v7xikAIvy+Nrgh0Tou25N42tHjyXVm0cADDASyZR33HrB3Au9xllX71V49chFMz5+J4PBwyu/Iu0FpThdmM2I25pwgjDtcd71idpY0UXTcLRI22JtSnP12JzeKHBA6PBUg86ARTy/2UPpmPq3M4H0OwoaETaHEJLG8BJPrHPS6lu9yln5MpAivKctxxFx4DKaCzz66yAIHdtQC5lTvdqaL7NFH3j/ef1oqloYjSetP+luS0aEvuraMNWaR2tXt9bjiA4QCWzKO+Y9YO4J3utEoPfOCRNfdmKeBj2WU94xndV6TSjnxPDmYK8DxwuCwY4H46OpDrqNFWhRftUXxSVwVPuW+cs30WmCrTQnBYpWBf1Wn9tHM5q9tnte0akd6niPS3uEVKeFNd4IjrrtDOHOBe+UfbMbC7FqAnecIJFR+0iVz/+CWt1NWPnBatNoVj9Qe1pnTeox+dH2U4gOEAzp2/awfw9rdfpZNPPpJ+/dfnXu6C8y2sii5wrLogpYa7Jcw9BXXXAC87tIWh/W/tvpBK8TmctS7glPvGOdtngS7ph6GR6lQjEs35GAJeke4T97jH0JHT/v6qV1U6hl29P6dd9eCcJYKigtLG0EauC6r///ZvL0z1cCxJH2ng97zn4DxzjHR5C+D0kgryTWgi1z9+ybtz1ChNmINN4KXKcqEhjYGKeMENwZQcwgEMB3DMfModu3YAb3ObVXrUo44s2kS9azfUHASVdvwIEbkpaC7IudZwrln/71K/KqrwQ0QOxqYKp4wvztk/C5Bn4Rj4XelDlsKmxwakRANzTuvCkvHc974p0ackG7GLIHzr2RVs9VVzE/eV5qsF4GtbSf/iYRGHD+yuBfBAiYUryGgi1z9+SStx1DQneOYzL3zVf/3X6htjXo/BPe9ZbTbRqXIIBzAcwDHzKXfs2gG81a1W6fGPP5KEnJdCFx+ieX0fcuFxqbUpIP/ylKdUu72+l1uKT2XYta5VLRy4Q4pDAofHAlN39ypJzYdHPnLYFr/wCympzPOvBD740pEKGkgO9UXDyRSJfHkXbIp2EQrHpPK9qzZsObQ3dM1jpgru7qKtD/Mzn3de9Y6Sg2lD//jzz7+gf/ySduCo2YRqZdiE+3mvveNjoK+1TaH3IodwAHfTAfwvKaW70z1OKWlq87cppcellD7TmCSkkbWQppCne+mLU0q5ety1A3jzm6/SU55yZC3CuhRKNLk4ZnZHijKmgPyLhtleEout3ReZF+KZTXA0CXRe97pVQ24vluMCh8cCHAOUAx99guClUEnKCez6yDavM7Qjdyxu6StfWTl9b31r5dShKJA4MecsEDkoXlLNLhpOamYXIRrLfir52/yt2h41pzf3nndFfnbRlrv8zDZdRJRtJNog5SS6XPePX9JOviE0Qtt0ki5h6qF73/WulbQVSbUcwgHcTQfQ/uK1KaUPpZRIGdPMv2FK6RZ7k0QCTGv7l6aUMJuum1I6J6WEjdduK712AG9841V6+tOPJAvcUujSRKqvX+/kvRzkYKbAgiltJNyPXyH1J7LXXmSlmvFCcAb9J0eXHEzgcFlAlI2D3ywCGnpC1YJ4gG1R4dx59OlUAOs40QV9P81HlXu/9EtV6gcvSDUfjlAXz9b7wkmErujX0LMc9L9zxIm70/Hr6tdayzqptvReN4E3aNEk9xHYXQvYeFkXchsphYKqctv0gSWsxVGTZXryky98tan8ZJkJupiaKuQQDuBuOoDtuaCG9h9TSmILon0SVFgI+hXUYicSXP61k61rB/AGN1il008/so6MLYUuVfT6+sLhija8HEj4U0D+xU7P4t3HAWu2jFNdqNvAri6yU+x8UM6h9ygNOKaq/NhjK1Hhe997+ClVyZMg6RM3f+1rq1RvuxCB3iBuWpdGnc0MorgiiF11YERj0ToU2qB0cJzbqLs51J19mn//6EerCuIo8Bqey4f5iDe/ucoMyfq0Qf7FuykYsDQ4avrO+540IZptYyN6LRtVCg0S9AO2XoUDmLdBdAKp0r8knI/ZM9HpKSVlFU2ZVFLJ7yKVl1Jq1iKtHcDrXGeVzjjjyHr3vBTIOeD36fSRQ52y9XJIk02BCqmTTqr4Hn0vmZSwyIzFBcncTg3XKHC4LCCSzAGjB1gKmpGq9upK8r7zHvawqh8wB6ULdClFsDiiTViMjMs8RVVowubFOyBygfTd7mBQ+iwH/TjRWHxeEda6c0/7mfRTtcjmZJxs6qT/2z1gD7pdYvzjLNDXF5w2rQryun/8uCv3H/2AB1SV6ZzPJqa2H1V0dsopVWecHCICGBFALttfppTuk1J6694k0YhGavhXG5PmZ1JKH0kpSbY2k59rB/Ba11qll770yEWEVee8HHTVkNl16sihTtl6OcjBTIFF28shTN4XZsfL0DJO+s7CbCEXLQgcLgvgeOoDq1ijFG0x8b7zSirbicDabLQ7WaA8III/5znpIlQLmnaiis5TqZ6LbpU+z0E+DqdXxEOkNUfl8Gx9mmr1JlAEsO1kH2S7xNjHWcD7ZJP2vvdd9Lx2//hxV+4/uosiUjcjsNGzgSxFV8vD+vxwAHfbAcTY+28pJfLNf9WYVFSIBLibCd3eCOBlLvPwdPe7/2i66lVFQk5Y/5uLP/mTSuOvK+VVp2xzXJ7Se4uW4FlJA/cRbbWMo7FGVNMia1elc0TgcFlgik7fmG40uD02Gi95SbfdSEDgGCkEaUNkixhsW+fP/MVf5ASKUIyVsjksv6IWeyoovdNSvQSf27Co4yrr69pGvamUQmfHwG5agB6k9UdRUBvt/vFLWgiHVRQb/7CJunCJxBOaSinQGbRS9T7UOPfcc5N/8N3vfje9oGo7wq38eul1D9Nxu5oC/rWUkl+ecMtft37Qk1JKz0op+Xx+f+9vpuTv7BWENA9fRwB/6qdW6S/+4sio1NnQJHr+86suHyJvOXgZpGbH8iKa15Iu+sVfrKIGUrqIvblSe1EevV69nNpE4WiEVtjQL3jw/i7Cq/hijJzRGE4QWoNULp5eF/qcRPIUxsaJVLEMIoOI49qYiVz+2I/N48UevF/tghHXLd7sP23QcvJQbIj2QVqjjVoK6jOfSevNbGA3LWDz5X0yV9po949f0kIcNXPXetQEuoL3+gtfSOnKVy6/ow2RTlp3p/mRQUQAdzMCyJFT3XuvlFKuYZLauLoK+Kl7Tp/umCKD2Srgn/zJVXrTm44khPil4AXU59e/HKZWRjWvRf7l538+JV1HdPjAv8jxpziGL3xhVSH4V1BYfd8AACAASURBVH9Vlem///1LPWlcZ1ssoGruwQ/urrTNjXOMFNFzn1tJlOgH3AVRPo6ICEQbNifoCM5H8AZSFSqFUSFUKCqMIlPBGdo11L2WLaLvfGdKFsA2BD+8711SORbaLudx1+y5q8/7spdVPeJzLQHHUD7G2o+jJighot8ETqoN39iNCa4ryoggRw7hAO6mA6iy93siwK1JIeVbO4Q+nSKEt9oLDZ+x5zS259E6Anj5y6/S299+ZF1BtxSkuaR/3/KW/BWnaiM1r0Zug9OKm6XDhwiQlHIbiP4qM1U5/8VfVErt//2/L/WkcZ1tscCQcGp7nHWbwNKduTmtyGQvA5N97JNPrtI8T3ta3ioPelCVnqx7D4uUi5KLlgM+bJfzsy123tQ46mfnAHKSvc9t2MBJi5H7ycE1RH42QfLf1HPHdZe1ADkl3HNFVW0IBtTR9mXvWjlq1iSc9DYIUI/VKB3iNIcDuJsO4JLzdu0AHjmySu9615HsjnvqzezAVADXC1v7Ol4GE3ysOnrzOuRfRAl0HZHSFQESSWlDZNCCjDv06lenJJLT12x+6jPHeUfXAqRc7nznsq4eRoqPx2Eo5dxJLZ1xRuWgdaFLCqI+XnEIDqrIH5kTaSNRbKlrEAVDYlcBuGuoo3ccwDPPrN7nNizs3t8cv6u2X5fzuGv23NXnVQhmo0AOpo12//glbUSVwvuviKmNKQLUqCFnnZUSubMcwgEMB3Du/F07gJe+9Cr9wz8cWcsrLAXOn4iJkvscLICct7H9EZvXIv/CidR1REqXjliuwwcRXsdwEPC3Xvzi3e23utTvu43X6ZJh6BrrWBqCSB09vz76QBcRvB4DigLJFxFo0QjRQsVSNilgPotQWEzmoparecIT5l5p8+c3WzlyALu4T7i8vi1tmZ16hDWPMOc8bv4p4g7bYIGuSnxjm1IoVvpMOOa6geTE3qcIUFMEELCgERoOYN4Gu1oEUjonh45bO4A/9mOr9KEPHVkvPkvBTl16y+KWAw6P9K3KvakQaveS6KJgQeXg5Tp8iKbgZp14YsUNyem0TR1DnLc9FmjOh5JR0ZQTEdBHuAR9HQbq85vSRF3X5CTSpLSzJx1hzkoRARFrHNVm5V/J2HLHWIxEGW14th3NTj5sWLd4bI8bl1dkp4tbjE/5rGdVm8HAbloAb47eq0h6G83+8Utbh8rEIx6R0q82Bdj2bjKm2KweF76wSCZ5pBwiAhgRwLlzeO0AXvziq/Txjx9ZVyMuha6OCPX1VVNKfZGDmQpkW5XEuo70dfhoKqoPcROnjiXOO/oW+J3fqeRURI9KQFPO3CidgzYzaAef+lT31fsWgfosJHVpTI4O8WIbkhrO9xxd6v8lz1Uf4xocwJwkzZjr7MexIvcqJGUE2KWrBRbRbn2TfV9ysKlECVEgFthNC+B7CwiQg2mj2T9+aev0qRA0u1GV3rfZwCB3TjiA4QCWzqWu49YOoP/36U8fWUfTlgIeDt4dMegc9O1Emu1q+l4yDuX2+v+S55BqtmiI6rTR7Kk4VJ1cct84ZjstgEcnmse5KsHYvtAKDzgnfXNWBE+a+F5q9DtAp47+IKkSm5dmyqiPSF7yTM1jjIED2BalHnud/TieU20DKhWsmlI0X4/mNnxTiLhzonPoS8Ptx3PEPY6+BWwAccJzGx8brEc+sirWWBqoRrQ89ZpvY8iZy42F02hdq+kh7WPCAQwHcO4c/qED+LnPHVlLVCyFs8+uXgaiuDkQdJXmwsOaCnIQZDxUVCo24RDmOnwcf3wVUVGBOaRPOHUscd7Rt4D5RiC4NOXp40o25l//tWzs5Fl85L/5ze7jhyr36jNp/pGUaffCHlvI0jdyBTEcwJwcRtkT799RTUpIU96pPQJcXtHCrt94bCX4/j1h3Gm/LNC3SbBBsLEQyV8afZs/a6uN2BipNcENfYupWOQQDmA4gHPn8A8dwC996cg6nboUzjmnqmyUZstBGgf/iRzMVJB/UUVMc43cDJ5frsMHPlAdURjqUDJ1LHHe0beALhIciWZKtW9UuGTShR/8YNnYS3rN1lp2OQmT5l1sRBQ0tAtKLEx4bEsUblhsOIAinduOZnRVRNSil7OBd9w7j+eVg/dcxL/djWHbnz/Gt5wFyASJKJODaaPZP365O1ZX6uOfyq5JSY/pU65wRKbs+tfPjzQcwHAA587hHzqAX/3qkSTkvBTe9raKECtqkgMpDYr+5GCmwuKNPG4x7Ys4SoVxAvUAHupRPHUscd7Rt8Dpp1dc0K72g+0RjtWErLvX9PWa1evTGCwGfeDEkKFpt4YSndCvVGp4LlT1cwBpZG47mvxKNsAHlEpvwzuMUI/2kYNKcJWevg2B3bRAXyagpEhrqtVucIOUnve8lGSc2kBvQFvAey8F6Rgb2i5R+HAAwwEsnUtdx/3QAfz614+s+XRLQXpLFWJXes3ffejJwUyFdJBFGa+vj3PYlOawcIhKkpIIHC4LmAc2Atr9lUCkUJTAXCwBx0+RSVdPT23ddPIw5695zZIrXvSYRz+6+t84s3PxH/5D5QDOibLPHUPp+c0No+gdO9Zi2c1roHFc4xopPeUp+StL6eNWigIFdtMCIsc2VyrG22j2j1/aOloX6hOOetEGagjaQu5vXeMYEo8OBzAcwLlz+IcO4Le+dSRd6lJzL3fB+UMRPh98ZNyulk4lIyH/or1O3aFB9RfORBtSzVJy0kciKxZocjCBw2UBoqn+lXLeCMbi5ZQ6jHVLJ6ngXMGUClbvEI7aVDrFEMdtzC9G5JoDmBNHH3Od/Ti22eFD9I44d24Bx+XFtSITk4Osg99At5/AbloA9Uj/3RxNoNk/fmnr2PTZVOaifH3Rwdw4StrHhQMYDuDcOfxDB/C73z2y3nUvhSGOH47g4x6XEjmYqeDMiSBa9Pu6NDQFgptO49T7xnnbaQEcG5Ezc68EjtVRoktSJHeNPl6O6l4iz4pEHDcFxJvxWOdGqOtoJAfQYug/txl0Q6XPpM/pIKKG4Ei2ocJSAY3NYw6+KSK1aCGB3bSAKLromYBAGwqM6G9ugiMq4u5bkuP5jdWn9M7qjNPXpjIcwHAA577hP3QAv//9Iz8Uo517UecPVflK1T35yRXJdSqkczmQunvgV1gwcuk8XENdF0RXnvjElCzU0oWBw2WBocrz9tMqGsFR7ZIUyVmHgyd6neubLTIoCkDKZKrDJWqhOhmlYQ7qaKRr+O8Wk22GVPyrXlXZlpCz4hhOYRs4XPe7X0UvycEGT8pbK7nAblpAFNgGLKcHSv6FFqBs0NLoE24WtRaw0I60BEN0E9cIBzAcwJK51HfMDx3AH/zAf10OQzp/FjgLMEdxKnCEnK9dTnMBaV+v2SFC6sjLJdoQOFwWGCo8aj9tk0NaaomrX71yVOiJtbFEdxt0BpHMXCP70jE6ri5Yqf97u9hkzLX249hm+66+Vl5DOn99GnD78Rxxj6NvgYc+NKWf+IlKh7YNVfaKhLooBHNG36f1d+tbVwGInEZg7p4oEArKiNT7z/wxX08/Xv3R//f1OWM/qOdueWJj6826dgAvcYlV+t73lnUAReaE2rv4R0Lltar/VCuRdME1VM2Jz6VXq9RyG82OIXZ++BVLkOynjjvO24wFSjp1NO98yinV/2UelqKPy0P0HMmcFuFUcC6lL6VC5+D88y+oHvzkJ6vCiW1GM+rXt5kTvZHmFQXMgQi4LMDcCOo22yrG1m8B0WFyTLlCIP3jZYNkgpZGX7cP7UjJlnXN2/ZYvvrVSiGAyoXCsxwiAhgRwLlzeO0AXvKSq/Ttby/rAIqG+Fh/4xv5IVrokLw5cFNhoRT1QSDvixoQiL7MZaqUAO6H8noLTuBwWUDakNyPIowSnHxyxdkbI7nS10tU/1FVqrluNCXjcYyiFNSILgH10uvUbe5wAfEcu8RkS6+36eOavL8mH7B935vcpJKA4WjnoAqTDNC55256xHH9bbXAAx9YbX7IwbQxtl/4mGekoqEFnf7ibWg5qcVjrk9w7h51a8RvfzulS14yP4pwAMMBHDM/c8euHcDLXGaVvvGNZR1AxRlC7SZwDmMlOHLXaMp+9DUA1zHk4hevSMGcQTpiyPaBw2UBeneqvbs2He2nnRINaPaVbl9PNTEJilJh6Zz13/72lKSwPvaxeb+NQpgTT0yJAyhCLgKxzVD563ezkWtWBLfHTGqDnIZCkBzwgWUDzjtvm582xrZJC/QJiTezQUuPQfW5FnQijG0MURfax3/uc5Wc0fe+V3W7yiEcwHAA587htQN4ucut0te+tqwDqIrPi2AC56BgQ+WuCN5U1PIvdvv4gDoe5BqAC70bByfRB4DQbk5kduo44rztsIA5R2+LyHIJOEi3u11KtfZeyTl9vXrHViHn7sdxkyb67GdLRtN9TM2H5AByqu5613nX2/TZTe2/Pi5nX6WlMb7+9dXmbg63eNPPGtffrAVE2bRsJAfTRrN//NKjoKKhFekxx1z0yjqQ/MZvpCQ6WYKSrkPhAIYDWDKX+o5ZO4BXuMIq/fu/L+sAqsRDmMe3y1VEStX4WOc4e6UPRf5FBaeoSbMiuH1+U1dMCsC4uoRkS+8dx22fBUgmqMQjoVAiaTRFFBaJ28dcpWEbNjUiUPpST4XoIe4s8vcc1MLoHMCuBvVzrr/0uc3uH31cTrwo77uqyhyGWlAuPe643vZZwAZKkVZuY9cnMj73SfqEm8d2ICnZzIYDGA7g3Dm7dgCvfOVV+sIXlnUA6xC2aIz0axv4fz7WpDumwmIrHYR71dQEbF+v2RpoStpv6vjivP21AKcJEVsFXUlXG6r8OHt25qWgKcn5UIjQRpOTWnq99nH4gwpNuiLnpddFsSCFwgFEipcW22Y003bNvsDtMZP38Hc2yoGEjt9U4UtgNy3Qt0lTBEimSQHhkhgSbh672UShwncl4dSFcADDAZw7h9cO4FWvukqf+cyyDmBNYu3SIFuiWo/8i+uomOzT/2o2B2+KQs81Xpy/XRb4zncqwrQqXGn+IYytzHM9rcakIc23NpaQIKmjmJ5FsdJUnHFG1eGEA6gXtoKXbQaBXh0U8HW75HQ8iyiLCueuqmY0EN0ePv/5bX7aGNsmLUBrj8OFS9tGs3/8kmMYEm4e24GkRFIqHMBwAOfO4bUDeI1rrNL55y/rAA6VsdcSMGO6MLQfFrldyyeVV30Cz/SgcDOki5tt4eYaL87fLgtwEESbpU9KZE8UKaEO3P3u5c+hAwUnM9dqTPUuB05UeioUQihSIp+kldtUqHIXKWMTGmR4sNsM1dv3vnfVH/xTn0rpWte6qKB2LW7d5+CTn+JIzk2hb7OtYmz9Frjb3VKyociJhU/R/iyx95Bw89gOJCXzOBzAcABL5mbfMWsH8JhjVukTn1jWARwSsrSAEosmBzMVzWpBwp5acOVaQDXvdZ/7pHTccd2tpKaOJc7bDgvQzCIH05UibI5SRalCIvOhFH0RBLqCHK45GpPSU6r+9LhWBTgVnFFRMONxnZwm2tRrb+I8vwF+rnR8V/agJMWvzzcZDhGZwG5aQMETweff+q2LPv+mWoEOrXdjAw/WxuOPrwTduxAOYDiAc9/wtQN4veut0kc/uqwDOLQj0gVEmBtXaSqasht93I5mtPGXfiklO8SHPWzqXeO8bbZAX6u29riJxRIPp1dZCnp1UpDEittYSmJChFExSE5OonSctTNaR0VzfVFLr7Ufx/kNbOJESojf4nDKIuB01uDQ+s36inyGuMf78Sxxj6NrgeZmoj0SXHGbhD/7s2XHOJTxGks9UsWOuiGjEA5gtw2iE8i8ebx2AG94w1X6yEeWdQBrTkRXuqav4XvpI5F/UelF/01qTr/TnMBzk28o3YckLNUUOHwWuNrVqtaA5F2GIMVKiBzZuhTkhnT8yPWp7dMfK72+41S6qiTO9RsuvU5dVcsB/PKXK228bYbfAIfS+1lHQUnhcPhqKOzgFPfJ/EidawMmlU78PbB7FugTXUb5IJL+8pcvaxfvGN5xl3CzfvSyEqeeWnbfWsdTJiAcwHAAy2bN+KPWDuBNb7pKH/jAsg5gXRXV/ojXQ6xTVORgpqIpmiuipy1iTuC5JsS/8Y0p0XGjE6VSMHD4LEAHkEA4qZYh2DDYPOgaUArV6295S9Wxow0cNpXFNiNzQKaIRqaFbCrqiAMHEJ9Ixfw2w2+garlOxyuA8dtI09f4yEcqQes+oe+aJyiNrDdrYPcs0Ffc1beBm2OpOjrdJdxsvbnmNasuPyWwMbWhxIftQqSAIwVcMpf6jlk7gLe85Sq9//3LOoBuWlfsWdDasBPC6bGgTgX5FzwPkYGmjlj7epxMBSMWbh0EiHHakQUOnwUUdtgEdLUKq59YFIlWoJQh7cBSSB2JHuS0/vpEokuv77if+ZlKpoJ22FSgOjifA1i3S5x6rf04T6SPdqFOLpCLzpa0+htbCLQfzxb32F8LKHpS7CHT04b3is6kdoFLYkj31vp0laukJPNVAv2sKQ70tZUMBzAcwJK51HfM2gE89thVeu97l3cA7eL/5V/yyuh01OzWpWengvzL/e+fEtV0jqDKwdwOqynQS2SXJIYISeDwWYADoQPAUNP1utrWJkTkuBS6fVhE9Ndtg/is6N9/+k+lV8sfZwFT1S6iOBU2OjQvOUR4tqLl24y2w8cpx8+sHUJj7xOIbj7bmEKgbbZJjG2aBeh04vqRg2lDkaDNm7m1JIaEm2WozHHc9xLYtOkdTL2iC+EAhgNYMpf6jlk7gLe97Sq9+93LO4BEWzW1z5HZkdRBgcZUkH+xSIriqB4UOclxLERsRAFFDHHDaI2pygocPgv0EcCbT4ubakc+Vm8PjUB0wbxu42Y3S4nkUG7hGWNpmxQRgznizYoqVCxzAGuppDFj2O9jpeOleOuUbzslbDwli6LjxhQC7fdzxv02b4Eb37hqDarYrw30EO+wf0tiSLhZ5yC9gnPyUblxyFYpbPROdCEcwHAA587htQN4hzus0jvfubwDSM/sPe+pZBna6NNTK30oOmdecnwfkUCk+VyHBoT95z2vEow+9tiUnvCElMjBBA6fBZp6cn1Pp5KXs4Gzk2tV2HXuO95RRZA/9rGLHuF6Nhp4gHPgGaSvVBVPhc2Q3tccwLpQauq1Nn1erujDIq6giy1q4F2K8Oec7+YYxxQCbfrZ4vr7bwHFFiJ9uf7XZJ+kfzlYS2JIuNk76DtTGvDgoMoCfOAD3aMMBzAcwLlzeO0AHnfcKv3N3yzvAKrG05oJL6uNsSHx3IOSyhDxUYIv5Se6V0cWm8d74S0mIoacRDwMJfaBw2cBjv2d7pSSnp99UGCALE6/awxsaMy1XHWetCVtyjGyMrl7983l0rHWThAHsKZJlJ6738flZF+asjD1eFR3S7+rkOzD9a+f0gtekHcA9vvZ4n77b4Fc9LgeBQ7vJigRKotRQFar/POipVDGsCkrgRT1H/1RpWnahXAAwwEsmUt9x6wdwLvedZXe9rblHUBl8XZat7zlRYcwlhSbe4jmIt7X/9HLxOkTMSQ3IQzfjCzMNWKcvz0WIADrN5b+7AMpF4UiUsFj0Nx0tM8T8eac3OhGY6540WNx90QT9bCeCvp5KA8cQBFJm6RtRU74mRPf7mF81lkp+ScK2wccMItnbPK29Rff7Lh0AVL1nquib9KBlhyFqDTlga98JX9VWSebTRuTEjSDFl3HhwMYDmDJXOo7Zu0AnnDCKr3lLcs7gH1Cu2PL4nMPIQ3nY090uq//Y1MwWmpM4QmV9cDhs4BuEnr1DnW+OO+8qkgCeXsMiMhKT7abtHO0dPBQtUfuYQ76JI1KrmssCrAQyP13c36bO2PkWr/lUvn4W9LAb35zvxVue9sq7R0835LZcviO0fmG6oMIfxtNOtCSTz60obSZs9Ep1eMsGWc4gOEAzp3DawfwHvdYpTe+cXkHsI+LM1YYM/eg5F/wPSxuJC+kznL9H5uC0XTi9Gqdy9Oaa/g4fzMWUDmnCpSocB/MCXSBPpJ17vyuThO1/hxBWEUIc6Bvrzk9tUJeYYtuIqKbHMApxS5zxj/23Bx/KpfK12JPJbDFvQ8qoH1fyD0Fds8CV75ySjb9qunbKImsTbEYaoguNnRvc7AhpVZB67IEJZHKcADDASyZS33HrB3AX/7lVfrLv1zeASTLImWjqrENMiyid7mijdKH8kIJ9xOdRvhVCZz76JPAQNxXqWVML3tZ1TA+cPgsgGvDARpynmjOkWTQcmkM6n607U4TenYSHhaNVu03B095SsUxLF0s2veShuKEGgsHkEPsf8PJ3UagZtjAcZ5r5Lqq+L3QPoa6OPRlA7bx+WNMy1pAJx3ffOtLGyXcuimjGZIoIktj/bEelqCEqxgOYDiAJXOp75i1A3jf+67S6163vAMo2ibkbUfehvSMEH2uaKP0oZrRGPdoc4bq6zTTfaKStNykiQKHzwKlHWZwhMxNc2MMuloc5tKYY67bPBZHlVOUazdXck0Vzojwdcu0i1+8SnXbLG0jcound1lRTVM4t/S3PfHE6v2e823ZRjvFmMosQNeT4gOqRhsig6TC+qpry+5y4aMUO6KfdAk3a0E3piOPamXr1Fvf2j2acADDAZwyV5vnrB3AX/mVVXr1q5d3AGspCh0S2pDiUcE7p21Wkzxet+DS5q0Nor3Eeam1W1TwiMjBBA6fBXQBkdYdihI1u8OMsUIX109kimhxX5uy0vsgiiueOvvs0jMufFy7InGp4pRpoxk+i74fnTSi8TVUcevUQs+tRml0V/pXJTAZjcDuWaBPCHwq9WPIis22pLljx7agK+G7hgMYDuDQvBz6+9oBfMADVukVr1jeAWw2eG8PRKsqGn4I71OhslG4n4wEB/A//+eKh9HGe9+b0i//ckr6NUrT2VWRgwkcPguQCdFHc4gnJkVs1/7614+3wWUvW0kKNfUtpZJVnX7hC+Ov1z6jJP3Td5c2H6ndZm3+CJe9gg3Z7/9+FfWsoYqbM92smsTvJC4/JKZLP1EKnCh3YPcs0BYVb1qAo2bN6euwMcViTZ557vyxLejoGFqncj3H6+uHAxgO4JS52jxn7QCedNIqnXXW8g5gn+be3e9eid2Sg5kKZfXC/XhZHEDcKY5eG//0T1XVL55Wrsfo1PvHedtngZKds1FLyYiUDUUKc0+YI5kPpYDGWOq1r03p2c+uRNSnQKurhz/8gkVOJ54zzqhkKrYRuYpHqV9pa20ca5RWeI8V3d1Gm8SYplsA5UGBYI7yQBqJAkVfj90pd24qTeTOH9uCjl6gsfZtUMMBDAdwyly9iAP4oAet0plnLu8ASrPiW+R6mkoLS9d6GacCyV24n2PHAZT+o+3WBu6Fog+O4mUuk5KSfdXDgcNngVKtuFI+Wc5CueKmoQVgjKVdSwTMvJ2CNtGdDmfX5mjK9Zc+p9mru7424XYiuE0epMIxovJDGo++OV/7WuX0BnbLAgoCOYCKqMjBtIEbaB7h7C4JAvAqfZtR7Ob1x7agswGUZcAD7EI4gOEAzp3D6wjgQx6ySi960fIOYE3ERspug8P2W79VyTVMhTZe9M6k3fAJ7ZpyfMOmzAR5DJGfuufo1HvHedtpAR9MciFD3SJIrZg/pcr8zacl9OwD3ew1qkuFa+GbzoVooo2RKMYUtCUkVOFLixLJ3kZI80qhNdNduf+ttMsLEWgRHqn0wG5ZoLkmiNS3wakyj7rkWqZaC+WE9BS6UQ5jOceupVDlla/sHlE4gOEATp2v9XlrB/ChD12lF75weQdQ1A3fQiuqNvztoQ+tdmNT0dztcQC7Ko6J91q0yYMQ6/V/zxXrnTrmOG+zFlA4QXR1qF+sFKniCFHjscj1k37pS1N61atSUtAwF/iEpEzGdimp79uONoiK49zO6S0895n6zkeQ98yc6Bo5e5b2SC6JnmzyeeLaR88C3/52xROVFcIPb0NUGf1o6rvV9WRDG8BclLvPSvireIoky7oQDmA4gHPftLUD+IhHrNJzn7u8AyjKJ5JBn6+NpdT6a74HB7BLc7Api3Gxi1XVwLpFBA6fBdr8t64nFH0+5php7dZybcqe97xKe0z6dS5UFOuFq7hpCtrpUxXwnFZRz21Eju/HmcabkrKr4R33PRnKGrzwhSmdc870KupttFGMqcwCCods7NB98MPbEFUjGdbVsq3sLhc9SqQO5UABWg76D9vU/M3flN1BOlma2jldCAcwHMCy2dR91NoBfPSjV+m005Z3ABVeiPBZbNvIRVGmPIyKLwumRRl5Pqfvhw9C/08E0PGqgXVHCBw+C3AYRJyJhPdhjlOUa1M2Vuerb2xzNQXx/aS4aImB4gnzX6XtNkKf1NUqJY5bjRyniswOJzZHKWk+19hoyzbaJMY0zQK4nwTPbZ7ww9sgEXW721XzbUmI1Jl3XQ6eDY353eUgtsciiyFKqWtVF8IBDAdw7hxeO4C/93ur9KxnLe8AWijxLXLt2VQI2+VITc2BlxzxlgMo/ZfT9/Micfi89HaFS7TrmjPmOHdzFpDiwc1rdpXI3Y1ki/k5RYaI1BAKw6MedcGVSz7YpU9t7Fe60vSuIo95TErf/35KpCcgp6lXOpb9OC43PhIYNEKb2oA3u1kl7SI93geFI2R+luBj7sfzxz2Ws0BTG9Zmvw1pVWuPAsIlMUQBEZw47bRhbnI9ptymqD3ecADDAZw7h9cO4OMfv0pPf/ryDqBFFt8C16+NPo3AMQ9Vq75LD+Ff5fT96tZYHEHEYLtEcjCBw2eB0vSp1oHajU3pF4vSQORctWkNXSeIRCtAmYu6un3qRgXXj96l9lNAENk7gBu4jSAF5b1UvFEj1x2EnI0oit+uD4pJREHJPwV2ywJdvbprKygO8u7q6LMkROq0l0Q9yGFs68kS0fNwAMMBnDuHpZ5j7QAAIABJREFU1w7gE5+4Sk996vIOIPkXfAsq/214Ce3SpYnnoO77KAJo0eBYtiHyx+HDBVT80e7jOuf+ce52WYB2nBaEdRu0rtFJA4ngaUk4Fm0Hy/k5J2bsdevjOZJz2rep9vUe1HIppd1Rpo537nm5vr8iuSK0Ijo1pLFF925/+/475jqLzB1jnH8wLNDsD/8jP3LRMdf0CgWES2KIdzp2U0LLEvo2lOEA7q4DqOHZw1NKN00pXTaldImUUnNK+9+fn1K6JQcvpYRJ8AeZCb92AJ/ylFX6/d9f3gHE1bHQ1pO5eX+LtF2TQpE5qEV5OYAWjZy+Xx1RIQfD8fzf/7viAgYOnwVIAmn3Z4evlVgXNIoXcRKlHouc0HDb6Rp7zfbx9CpJSjS7jZRekxi6jZXOGbBkgUrpGMYcl0upN6Wb6mvp7iE1TNewD7no4ZjxxLEH1wKkk7QBJAeTA26sAkAUCQWBS0EwA/9PpC+HN7+56lRVqu0paEKyTEFXF8IB3F0HUHfdy6eULp1SOrPlAHIIP5ZSUj/0hyml66aUBKafnVLaYwX9cEqtHcA/+qNVetKTlncACT3f6lYpCWe3QUwXcRaXag6IfdJg4gAi+Ob0/TgDHD4pISli0SERlsDhs0Ad7fWfqgG7MKc7Ri6lqquNThu5aPcUK+e6jZRexzhUyv7mb1Zn0MOjDahCehuRK6ppVu7XkRxOMbkYm7g+lPJAt9EWMaZ5FvjYx1LCFSUHk0PNB1cQSEN2KYjUKUB73evyV7RxkXFAUSkBbjJ6U59MVTiAu+sA1nPouJTSO1oOoM/+M1NKP9WICj4ypeTfdVqTb+0APv3pq/T4xy/vAOZSO/X9pXOI9uaqdktekPoY7X5e8YqUiN3a/eX0/Wq9QOLA7uf/zqUHxtw3jt1OC9TOvkhgTgh2ifmX0+gScVN9PKezTdOiNkgcNxubsSAh0+yLbVESSSCCu43A31Wp3JSLapP5pcVpeOJwDWl45qKH2/jcMablLcDBUi2O5pND3T/+m9+s9AKXQq5zTfPa73hHSiefnBIHtQQllJJwAMMBzDmAaOganf1fjYl2u5TSu1JKvLymutjaAXzmM1fpsY9d3gFEsL/2tfNaa9J0eBG5qt2SF6Q+xvWprIt6dLX/caxwP502nUK60gNj7hvHbqcFSh0F3FEfZdGCscjt9lEdVLOSl1kCN75xSs98ZlVENRbSxsZ4wgnVmW95S0oqg0XItxFth9UYaz23umCrduxLJJxy0cNtfO4Y0/IW+OAHq02TeZND3T9+KEMwdmRDPNvzzqsKzkq7+9hICm4oZupCOIDhAOYcQClhCkh4gjUkTXz+yR9/rvG/rx3A005bpUc/enkH8MEPrvoxkntpQ5WisHiuanfMy4fzp7xet4O+qI8UMJFesjRd6YEx941jt9cCpIH0e+5LFV7qUlWrJangsdBxhk4dXk+NUomS0nuVat7lrnf1q1ddSepiiW3nxOUUAdA0cDhxtn76pysJJ4VcXQK/TTtsKs1X+tvFcUfPAiTBbHy6ZKBqPriqeHqBS2Go/SBJIpSoIX3SejwoHLiM6CbhAHbbIFPns9RPeiCuk3MAT0sp3TCldLfGE/RGAI877uHpFreoCBEnnHDC+t8SEPIWaZEya+Pyl0/JrihXtTvm3iIlHMz73a+7/Y/rcQrwoLxYXemBMfeNY7fXAkPFAjUlYGpHGKr+Z56Zkp69NUSi/W/SmUtA9by5OkWmxsKGkF5HN7XFEyFfuvvBEs/pGl22w9GSzvX3urinhLvVjh4uNc64zvZbQOEUPi45mBzqSLJNAq3NpdAWX29fF/2CKkbXuNrHa6Dg/UXlaOLcc89N/sF3v/vd9AJNs1PS8+TrSz3LQbpOOIAX5QCelFJSO/TTKaXv7/2Yv5tSUhOoIKSJdQTwhS9cpYc+dPkIoCpExG1dEtq47GWrKschQvfQZFTNqcgE37AvrI9QSwcNubYrPTB0r/j7wbAAfqnenNKyOcyNAuQavxMa7xIin2K1OULVTcfJvZu9sKeMZdPniPCpnhT1bELET+cEm8Qxad06emixRTUJ7I4FhiJt9eavjiwvZZkhrc2crFHfvclTeR9QN7oQKeDdTQErYBeyuyOKT0rpMnsFH9/ZS//WVcCkYDl9b0opiQxmq4Bf/OJV+u3fXt4BVPWEuK3ZextScPga5GDm4Na3roSmpZv7iL2iQjhVdlRDXSLmjCfOPfoWGKrw1SgeBQEVgNTCWBB7ten48IcvONOGxi5/imxL7v64hOZ2roK+b7y5CMe2p0Sbjl7z2ThvUu04giKB7OEdL4H0sa4P+j0HdscCJVw7fHAbClSJpUBzU+S5CshdFGN7EKMq4TLiFXchHMDddQAfuCfzYm78IF1gBwmo81JK5JBNxVvthYbP2JOEac+ldQTwzDNX6UEPWt4B1LfTbrxuSdW8uQ+0iijVjnPwcz9XRf/Ib/Slh0RotOvSHQGRPHB4LTDEx8PDUUlKC2xKNfjf/V3V37omdM8Vbs79EkjgFqix/XvrrjfNzZD/LhK/NO9pqRmEn5uTcGqmhnG7FHBx3ktAAkg0CEUksDsWKKm2FSHXYnDJzYG1TnHhc56Tt/XYHsRapGJiPZzabwfCAdxdB3CpN3rtAJ511iqddNLyDqBdkabczydJ3YAF0y7MQixdNwd3uENKhG8f97h+cU/inwR8vaClRNw544pzj54FbAqkTgiR5+DjT5+yNJrUvgYtOilavDQQSSQpMbV1W26MJUKwufPqTgdN51baSyR+6ajHEr+wcRpbLiXHeSOvQSeQxhoSPd5mCZZOyZfcM445+hYo0dvzruLFTikA63pC2S7ass+mtpuBaDQB89Jvjup/TiAefRfCAQwHcO4bt3YAX/GKVXrAA5Z3AJ/0pGrH3u5BWn/0l+DoIN0juIuUuG4XRBppjWnaXVqKP9e4cf7RsYA5IYKmiCIHguCiSVOpAHbz9CRJSkCdUsYtRG1YAjZPrq/F1Bi0x1afu3SKesyY+o61QTQ2+mwKw5poysOQcEL1KNVR876fdValDxrYHQuozPfuoBd1QXT4Pe9Zjq7hPvjuCg2f8Yz8XelXoofIUpXA9wkPELWpC+EAhgNYMpf6jlk7gK9+9Sr9yq8s7wByymjz/df/euEheAlwr4i94mLNgcbwyLJ4hn0vF64hXhXx6dJFZM644tyjZwERI5WAevbmIJqkyk60bArqfsNSPlLIYwoUSu9HVkLxBidmDLqqDZt8ujHX2/SxnHDVmLn2jDhQv/3bFcXjjW+sJDFwqUrQ1kIsOSeOOfgWoC1r3UEZ6IIqeRX8N9UwdSH0KV64Rf2N6AtSNIciqEEYvU8FIBzAcADnTt+1A/i6163Sfe+7vAOIb2cR09GgiZqTlNv1j32gu92t2lnpKyya0AXVxrQC7RBL2/GMHUscvx0WGCJQv+1tFWdUKngK2kUVXVG3Kdeuz6FtqXPNa1877ipdkTIbIPqF5GW2CbmUdT0+77bfUlcEdrDJK+1momCEw0h6I7A7FshV6Lef3oZDIRcayFIQqVPN/oear2YgEILuVNqFqrn56RpjOIDhAM6dv2sH8A1vWKX/+B+XdwDJv6iUpL/XBDFX6R4pLumfObjnPSuy/CtfWYnEdsFuT99hshJ96YE5Y4lzt8MCv/ZrlXSIVFAOKktpR/ZFCfqepK0zR84ID3XJ4iK0CdGMpth0iXW7no3gumfGK9omcMI5a7nNW9OR1zccfaOpvdj3HN51KWOR3sDuWID8E563AqAudMkOzbGSojC0gyc/OX+VWsdS1gDndQhE3G1S8V67EA5gOIBD82jo72sH8OyzV+me91zeAbRj15Hhz//8wsNYkjMl1Sekb7HsqxBEwLUI4n9NXfiHjBl/3w4L9HWgMULzUWGSDhlT0O5SQXRZqlK0eykQm0adUHE8Bvpii4a3z8OFk6baNoeor3MDR14hyBOeUEUvdfIRuSkBDhXKB95vYHcsYP6bK+RgutDulLOEdaRrZZlOPTV/tbHSU2hNJKA0OAgHsNsGuy4EPXfurh3Ac85ZpbvdbXkHkPyLRVYz+ibq3RDNMnIwc+AFcQ2LcF2VmbseQrk02Mc/XglQBw6vBeycFWPQfcxBJIkTqGJwKprSJWP5aSX3fP3rU/rjP642UGMgckiQ+k2UPxtQVShK2cWLHHOPJY/Fx7z//fOV+Zxq3EVpNVEdTi27lMCzHn98Rc4P7I4FcGb9IwfTBfIvf/qnlc7eUjCHBRioUeRQZ71kD0gyDUF6mmyZAEcXIgIYEcCheTT097UD+La3rdJd77q8A/i856WEk2Tn3kTNh0CIJQczB148BHILZZ9EhJD6la9cOYl96YE5Y4lzt8MCds7mhPmXg+gfHqB06VSgMHBIUAtK0k5j76PbE2kJAshjIOpOpsaYmijpLDDmPksd28fHfOQjU+Jok4JBJ0HdQPUowdCCXHKNOObgWUA7RnO/b3M3JBQ/5alJTlEGOOWU/Nl1tbsuVITPhzCkZer8cADDARyaR0N/XzuA73jHKt35zss7gGecUUUiREiaGFsR1fcQQu/C67hEqjO7YLdH/0kBSl96YMhg8ffttwAeDomhdvV5PXKRQVSAV71q+rNc9aopIZzTHCxZdMbeSeRcCnRspbIKSBshY2qCLM41rpGSnqXbBNQNY/J7tNHsruAYG8f2c3U9y7Y+7zbZ/jCORfrXxq6PO3ujG6WkyGqhlvdrMyo2uvOdU7JpyWGsVqgx0hRUCNWFcADDAZz7Dq8dwPPOW6Wf//nlHcCXvKRaJN+iWV0DS/YmRb7l+BGSld7tgrJ6FVgijqKSgcNrgac/vSo+wgfKQTEEMfBSZyJ3jWZV7XOfW1EQ9LNdCmM7X9T37epI0IymLTXGJa4jFS9SKxXcht+JAyxlL7VGZ7EtKt81Bh0UFJjl+pAvMe64xnZaQCs20XMbiy6IrqFXUIVYCoThOWtdnTsUf+hAolCMSPkQrn/9qq0cmbMuhAMYDuDQPBr6+9oBfPe7V+m2t13eAcSzsAj/9V9feBhzOzE0r4Yn9KEPVRXFffIuXk48jB//8eoDETi8FsA9Ve1t85GDftCcia4UcYllmikaDicpmHa1e8l1uo7ROeDmN6+6jIxBlx4Zcrr0k6j8NqHrG2GMUr/vf3/F1xzrwHKEcYw554HdsQCuqAxP17vPEvh1sgR4okthiGMr+KBTiCi27MEQtEGUwRBV7EI4gOEADs2job+vHcD3vneVjj12eQdQJaPdu+hIE6IzWrj1ybYMDbz+O6kHemlesD55F3Ix9cvXJsiX3iuOOxgWGEoDDRWJlDwlvo/Wgrh1Ot4QNHbfpVDzZFUcWzhKQTRZ+kjlbBMiHviE3sltQl/EpsnVbBaElIzfAi/aIgsR2B0LSJsq8mtzYJsWUGEronzf+y5nl5Kqc++xLlSoGENwjA0lOaMuhAMYDuDQPBr6+9oB/Md/XKVb3GJ5BxDHSisr0Zgm9GEU2i5t7N73EBZzhF9tePrkXVRTiTwKrc8h/w8ZNP5+9C1AM05kqb3xqEdGGoQoK77cVDSV+jmCOoLgFS0F0TryRmO1Ms1z71a7+lW0U2XkkmnqJZ61q2jFtW0efUMUinBsCb53yWy0x7KJqOwSzxvX2KwFtGITCOiif7i7gkARZTJBS4HA+m/+ZvWvCwqaZKlE94agdz3xcxvNLoQDGA7g0Dwa+vvaAfzAB1bppjdd3gE0geuOBs2BqNgVkeuTbRkaeP13i69wP7mIvi4B5GLcV/i/Lz1Qet84bnstYN6JBOj3mQMtPOnVLsmGkifD+dFy7mEPqzpVqDDXvm0pSF9aMLwjrl2KrhZSfanW0mtv4jgSLzi8xtcG50+EUEGMaI2sgfe9BEM0gJJrxDEHzwJPe1rV6rOvhaKCQO+sIqulQGeTxFLfNesghSDEEPAEyTkde2z3keEAhgM4NI+G/r52AD/ykVW64Q2XdwBFG6SeyFI0YWHmkElzzQXJDy87Un6OSF5fnyyECMhxx/WnB+aOJ84/+hbw4ZSW7eob2xUlGzNy0QMfZ1wzDiVOIG7hUvjBDyp9S4sZ3bJSdAnIDjnFpddf+jip6tWqyhS00exqgrDP6cZxLAExbN+fUuHokmvGMdtvgZICL5ukk07qj9aNfdLb3S6l3/3d/qjikSMVXQlFYwhXvGIV+aYt2IVwAMMBHJpHQ39fO4Af/egqXe96yzuAFmJcnLbEgx29lA45mLmwgOAK6fTR1zWBXIzKMJHHvvTA3PHE+UffAoqOROY4TzmU8HWGnqLZ+mlTosMKlrwr2tqVoks+giNks4R/u02waHJ0pYLbQO3wd9zFkhRb83xcR1Xepa3jtskmMZbpFiCe/KUv9fNxyb/g7i7ZJUajARmFvs4dKB1oKTaLQ6AViDrV9+6HAxgO4NA8Gvr72gH8xCdW6ZhjlncALTpeClW6Tfgoa9e1ROssLzypB2H9drVx854WbCKyeiv2pQeGDBZ/334LiAT7nbuEwaUSyTWICk9FU2YE507qxxxbEnqW6nxBa7AUyOM2OJ6xCYuJTdASm67SsZQc15c+b2oh4kIRxi7lbek+pIq4jxZSMr445mBZQEAAbxZ1oAuiyXpiL9kVp6Rzx5WuVEmiCVYMQbcQmTPt5boQDmA4gEPzaOjvawfw/PNX6RrXWN4BFMJGtm13M+CoIakrypgLIX9kfru6tt5g89oWGhWBdn1dAsFzxxLnb4cF+vrLGuESMhCiad/5TiUz0qwIXtICaA1au0lZleIKV6h0LnEcmxCF1xpticKr0rGUHNdVtexcEjB4liI6ngdf0MJdApX+nIE+ZYCS68QxB8sC3kv8WXIwXRCxlwXo0uyb8sQlnTts6HTFEi0cwiUvWQVOfAO6EA5gOIBD82jo72sH8DOfWaWrXnV5B1C4m+PVFmjmqOFOLZGOwjF84hMrUc92x5Hmw0sJ0kCz67OoBg6vBWw48PO0X8rBrprjxiGaCp0pdBuxqdAOTtXpksKyxjXW6XFOV6WhaPuNb1y1yNsmKO4gdSG614aKSYul3xFxHtWj9Dfz7SEds0SWYZvsFWPpt4B5RG5FEVgX+ubcVPuWdO64+tUrTUt8wSFc4hLVunmta3UfGQ5gOIBD82jo72sH8POfX6WrXGV5B1DaCdm23aKNo4akTw5mLrT1Qr5H7O+TuBCJJIVh11faTWDu2OL8o2OButUgDT3yLG10pUnHjLYpN0HWAd9MgdGSIFdB5kg6uwR9lcOqiVXKOwbnblsgwqeNlo1iG83f8ZrXzKe2u55DoZmFXoegwO5YQGZJta33swvNAq6lLFPSuUMx15/9WUoqhvugAEzHKt2KyFV1IRzAcADnzt+1A/jlL6/SFa+4vAOo4gnZts3FEgZ/6lMrWZa5IDPzmMdU5FuVjl1wjGORyklEBA6vBWpnR4pW+6U2fvInq24wJVycLis1dfXItEg53vrWy9pUtIvzV0pW/+pXU5ICFjGzCDZRN6N3zOUvv+w451yN0+z58BPb+OIXq7ZZopYWQv1dS22sAlwXBc8b2B0LdHXCaVoAX1dxhV7TS6FkE9hsH9l3XxtXmzSbF2njLoQDGA7g3Pm7dgC/9rVVutzllncAKbLjW1DkbwJBW9Vfl07bmIeSyuPUWSjphnVBlFC0kCOYqzgcc884drstQFZEFV3d+q89WgRrm48b3GD6c4j4veY1lSNZQtiecidRbdWvXQ3m29cUMRAps4CIIDRRt6IaiipMGeecc6R4vZu5rgzf+EZKpDOIYnMAfS9KJDSMRwW41Py2pbzn2CrOHbaA4kKt1nDDu0CsmTMmC7UUSjp3oJ7gJuIf9sGcvdSlUrIBUjjShXAAwwGcO3/XDuBqtUpHfGkXRhcZHw9CGlaV31zQD5PWRSbva3OFJ4gvaLGJBvFzrb7d59ep0FzjdekVHCHpRZycqai73Og7usT1cuMQqcDba7d16xozzhwdQI5TDptyVKfa0HkiMdJ1eqm20YyE+K3GaCLWrfS+//2LOsNzxhvnbrcFHvjAqtMGdYgucBJ12pjTCah97ZLOHea6IATaQx/qaP1XvlJ1A+pCOIDhAM59GzfqAKrAI89iB9+EHocqcZfQ6CL4qrCDBIfWUV3wstsVcgSlnwOH1wKcPCTqT3yiiog1Ue+uVZZKBU8FkWJVqXiu0q2qa6VflwRenAhA6XztirjXYyrpLrDk+EuudZ3rVN+CLv6kFL5qSNFaRTd4jCWweBLT/eY3U7r0pUvOiGMOgwX6qsrr55MmNjdK36sSu5S8W0SdfTMImvehzmD4z764TDiA4QCWzM2+YzbqAHZFJBBhOYF9un2lD8bpwyFS8ccZ7IKX3a5Q9eaSO7/SccZx+2uBrmhXH09uzAhriSMRQE7at7+dEumGJTG2x7BONzZD7ar7ekycLVXLuHHbAhwnxVsilzkQw6YaoHLSRlJqvwTf+tbmHPOS+8cxR8cCqEB4olQmuqBQxPdhyUxQSecOygR6WSt66kPp5iUcwHAA575lG3UApWxIWfgYN2ER0o+3T7ev9MFe9rKqpc9DH5pvJ1Vfx8sulaZf65Lcj9JxxnH7a4GuQg/EaumaualBYtNawIlic6y6Ko7nPLVotcjii15UdhWdbmxuUC9yKI1AlN1tmaMUpHCiuzoeiPiJEOrgM8bJ3lbO4zJWi6t0WUAxIBH0nKxQfY6/yRAsyQUv6dxBL/SUU1I68cT+368ufuoqYqvPDgcwHMC5X4KNOoCf/GSVusHJaoIen6rJPt2+0gfT3QNXClG+T/yTLpRdIUdwyZ6tpeOM4/bXAooGcE1JqTQhOqY4gDMxB4SVkbnpzbmHdM3SwFkVRRctL4EOIJxFDlUO9PZslDiu2wK6hR/5SOVE50A6g1OL28Vpz8n6dD0LIr1q4Otdb1ueNsaxaQuU9Pm2DtiwLakGUcKvLe1AVLpJDQcwHMC579NGHcC6KtFuvAkSGroVkIOZC5WYdJ3srPrEPzmHdn52fSqBA4fbAhZ9BULatDWxlDzIRz9aychIu0rp4KctDXNWhLFP37J5T84fbiK5lBz6NPeWHnvJ9Th0IjF9cheKYJD2pc7amYShe4zpvTp0rfj7wbCASLF/eH5dIP+i0GJJPVj0D5z3vs1Gn+RRc6yf+lQlAN1eN9vPEw5gOIBz38qNOoAWRSX57XTb6aenJIVGDmYu9EolIaHncJ/4p96QuB92fWRjAofbAloz4X22Cde0KaVgVInOAW1Llal4rBabLt7dnHtIfdrgvPWtZVexAdL71jk5eO46DVV2xc0eVaJNiDfFcfX+4kaNgW8PqsmYXspjrh/Hbp8F7na3ShPWpqELKECoFUt2hKLbZ1MoYt0Fm1FFKqLZfVC8RjKmnTlrnxMOYDiAc9/AjTqAKi2J5La5DJq06/MpRTcXZ59d9Qcdqu6tq4Xt+pbsATl3/HH+Zixg0RcVJkTehIgdhw0/dQ5qovarX13JCy3R1aY9HlIzHJ9SuSRV7qIHXdXwKuVFFp785DlPvty5X/7ycAENFQH8QFHQsV09SoV3l3uiuNLRtkCJk4VSYAO4VE/4unOHd69PWqrEOWU/jiS+7lDEOxzAcADnvm8bdQDrisu2FIO+qXg/pdymvoc855xKQ2youreuFrbrUykZONwWUOnK4dGKsIml2hDiEJIXsaHAQxXRXhrSuRYrfMMSPPax1WaLOHoO2srhxdEi2wbUqa4+bp9FU6HI+943vq/vpno0b4PtYgx5C0iziv6JtHVBZkCPaGoUS6CEyuA+Jelpx1kbbWC79DzrMYcDGA7g3Pm7UQfw619PiYxDW89IJa4CkT/907nDT4kcBzL+UHVvXS1s11faWmv+6OIKR8sCNgW60LSdfelRFASp4Dmod/2iaa5VmqYdc0/p5Yc9rDxaqcCDsyQimYMqeO8ibuQ24F/+JaVb3arS6uvCfe5T/R2dhB7gGJCW4RRLCQZ2wwIKLVB9+vpnKwT88IeXCUCwqk0XDuBQ546SAhXXw1PmyLb1c9u/YDiA4QDOfas36gDWWlxtRXPROh90cjBzoQpTu6yh6t66Wtiuj2xM4HBbAC9U1WtbDsLvr2OMIqS5IABtLuk9jIu6NDiWnJfS1OeQCC7H8J//ub9jztLP0He9rk5BzXNU+EvXq/4ldD0GosAPelC+z/CY68SxB8cCJU6/QkARZfSNJWCDogp4qHNH1zepPQb0KJFvFIk+hAMYDuDc+btRB7BuydXeGeHrSQ+Tg5kLnRjueMfh6t7Xvrbig0k7W1QCh9sCXW3UzDlVsrijc0Fr0E7d7r+vDeHU+6gqNLf1NC6BCMNd7pKSVG8OUsM2TKVVxSX3nHOMtPn9758StYAuEHjH26Td+Hd/N+5uXVHgcVeJow+SBUSUCf57F7qgENC6oUBoCQz1Hq/vQa1CUVOfSLVjhzr61NcLBzAcwLnzd6MOYC3G2pZ5oMMnOkgOZi5ESXQJGKrutehJJ9n1tQsD5o4hzt8+C+AB6TKh9VITKmV9YJfY/WsAr6iC1uWSFYX1eFUDuvb3vldmXwR4ji/uYw54sApL0Ca2AcbBWZUK7gJ9T/QNkZ1zzx036tKIy7irxtHbbAHV/097WsW36wLerrmHY7sESrsLeTfxUod0aN/97krajNJAH8IBDAdw7vzdqANocBe7WErnn3/h6ig6fJxDXKy5EMr/2Z+tqiXxpbpQVwvb9XEEA4fbAhwLkTkV503ginKsliCAk2owv6Vr+jQop1paalknDJF0MhNDQBz3bnV1GliK/zg0jtK/61yCDtJX5GKxVLSCzzlWN3QoJV46zjju4FjgRjeq3kXvZBds1qwHmhEsgVrtQp9xwuZdQBehEygD1gdC7o79n/+z/7hwAMMBnDt/N+4A5vSR6PBp8t7QNDwPAAAS00lEQVRenKc8jMWDIC8R3Ic8pPsK2s7RE7PrIxsTONwWoAspytwWe12yEEK6yS6drEw70riEdesiqtIeuESTvVPmeQ5S3xyqscUUSzxL7hpkoGQB+iqoSduohEbqF70cA98DMlSc/sBuWOD616+CAW0B+ObTKwRECRobUe6yYK13q7vIxS/ebWfFh2RibHr6MNTTuz43HMBwAOe+1Rt3AHPtmOjwHTmSEjmYubCYCaufeWZF+O6Cisrjj692fbhBgcNtAR9Z1IO21teSfUAVmXBezOOhtM4Ua9fyEjTLiBoP4ZrXrLiIxpVDaWRh6D5L/Z0KgPZ13s0uiP6xrbR2l75h17k2mjagS/Z8XerZ4zqbscC1r12tBbi5XTjrrIpWsEQhmHvgsKKDyGr1tSqkSHClKw1vSCgKmLsKtvoQDmA4gHPfoo07gJe9bNWd4IY3vGCopS9CycN5SVzbS93WfGuer6WWqkC7PrIxgcNtAVXhNgccjCZEha5ylWUidiecUMm/bFJcvKTFVP18V7xi5Uzd/Ob537buXzxUXbhfM0OkxvsoFdwFtpXOJ3EzVr5Gyy9aau4T2A0LcMQoPrR7gDef3jdBY4CxRUVdFiRpJvI4xNVFUSKLNhT4KI3UhwMYDuDct3rjDiBdMi+aKF2N0lB4ycNpwYVX4aVXUdgFkRoaUXZ9ZGMCh9sCioJEvNryLEvywvQAxksTyRpq7zTV2le4QuXU6QwwBPwjIrLXuU7+SO+Krhq4StuAEjkO0RwFPUO9vnPPM9QZZRtsEGNY1gIi5d55RUNdUACmIn4p8XYyRda3ofdKQZN3dIj6VMKN9WzhAIYDOPft2bgDSCpDlKS5gJWSYUseToGJSkwE9y7yu+uIQiLJc0ZJawQOtwVwQjlnOsU0oQBIe7El+kGr6rPxGJp7cyyNM4T71hfRcP1acunzn68inDn4m8ro0qKSOeMuORdvEtG9TxDesz/gAcOtHnP3W7LlZMnzxDFH3wI4nyJo+LldUAiIWmBNWAKyUORd9Lbug00MnHZa/3EcWJqd//AP/ceFAxgO4Nz5u3EHUBWjHY0XpEZpOXzJw+FHXe1q1a5PRKYLxDVvfetq10c2JnC4LYDjgzMm9d+EAglOIH25uXANHMNN8krJwIhWDNEWFIr8xE9UKU+itDn4G+5taVHJXPsMnV9SkMOJ915r3zVUPdm+39JyH0PPE38/+hYQMVdEQQ6mCwoBbT6sCUsA1QTvdkivU2GaKGFXq8Z6LDaUnMT3vKd/dOEAhgM4d/5u3AHknJnQt73tBUOlcUS6hWTFXNRSGcr6+7SfiOr6KNj1uXfgcFtAlZ8UY3uXL/qHB7iEGLgooo85J9N1NwGRjCc9qX9z476qkUULFY6QpsmhLipxLGHlo42SghzZA1xL0h51BKV03NLH0n2baNNXOoY4bn8tgGNHR48cTBds2E49tWq5tgRwaxUY/vu/91/NPTmJQ1xWWQXHvOtd4QAO/T4/MnRA/L3XAht3AKVnRWOalYkEWqVhl0jDeemkmaX6+rSf/sf/qD4K2k+V8Kli3hxsC7zxjVXEqP2RF4kWeVpCC9J1FJvQohRd3gS8JxzWvub27luahtK+TuRDZPFoo0Smpe70M6TzmXsW6WMLqWsEdsMC5rdvvKKMLig8spnAl10C3v973atqCdkHfcMdowClDyr5bV7a2Yv2OREBjAjg3Pm7cQfwutetJrwK3BpEXaW0yMHMhR2VQhPK7n3aT4i6PgoigYjwgcNtAcU+Kkf97k2UCMWWWoa+nI8652tTDpWUtbZWKuf7ULoI4UiJgGzKYS21neN+4zeqCn6OdBdq6oZ0fleHk65zpY/9Rkul+sY8Wxx7dCygyMJmnxxMF3wbVOR+9KPLjFE3KvxzdKQ+lBYllcgjuU84gOEAzp3BG3cAdUuQJhMir7Fkj07EW1IzQ2k4ZPNjjqk+DsYUONwWwPUkHtxup2QO6AKyRCGQtKS+nnTAUB02gfvdryoAefSj+6+ux6+ImkrfPqgQxlvs00nbxHPkrlnSqq2O3Ivm+T3HQKSH3VwjsBsWIMRMloUcTBcUAtKM1RFoCYgwi9B/6lP9V9OijtMpI9aHl7yk6lOseUEfwgEMB3Bo/v5BSunBKaUfTymhvGqW1gx8b9wBFG1TcdXsTiD6hwdIDmYukGqJTeNL9FVK1hwpESFRycDhtoA0kHnW5uWokJUeXiICdsYZVSThK1+pCjA2AdqWZI7wAPtQKh1BI1BUTMrqaMNGUHSzr4NPXeUvmidzMAbbJnw9Zuxx7HgL1L3nh4TTbQ5Vlg85bKUjEHywlg05lM94RpWBamuTtu/juyJK7zsVDmC/DYID2G2fx6aUHpFS0hjKXufJKaWTUkrYEd/cO23jDiC+nYqr5oJDh48UjH9zof0OtX8VU33aT7UEht0hXuI24txzz00nYLwHZltAWpaT9816ptcT/khKUjZ9JHGHlvwWxMfp/w31AJ3zMNLYl7vcsHgs4riFY4jvRgsT9aJPM3POeMecKwpp4ZQK7sIXv1jJ2jz1qeemJz5x3LtBRuMe90jJNQLLWaDk3VjubuVXqqWQ8OxQHbqgMExluRZuS4BOp3dqKKUsY/De91aFSX3QHlGaeqj3dUQAIwLYN4+0kqY49Ly9g3QpNOXV3r68Xg9TSqvVapWO0IfYAJDuVT81JVqk33CalqjE/MEPqqpHPB89gbtQF4tsMl0313ynnHJKOm1IJGruTXbkfJEj6V6Vr832TJe4RJUmHdoElPwWKo05UjoA9LWAmmNyKWYL25B0BJ7tG95wUd3D9r0VSkm9LiGDM+e5nGvDRhrDeLpQS9eceOIp6TWvGRBQa10EyZ/6gJ7KgeUsUPJuLHe38ivp/a0IxLeeHEwXrBUyUl/6Uvm1+46UqqVoMVRU8pznVOL00rt9OP30Sq7sda/rPy4cwHAAu2aIlO/XUkrEV5pyl+emlD685wQ6d+MRQB9gFVdNkWY6fCqApYGXgEVdyq/ZbaR93bpYxK6PNuE2Yls/rNtoq6Ex1ZGjZnSOo/ajP1pV4vVFCFy75LeQppFKWq2GRjP973oaS2mpCuyDfYPIJqe0D6WcwukjLj8TPURarK83dx3hv//9T0mvfOU4B7C0RVf5iOPI0nfjaFiKo08Gxrfef3aBMoCixK9+dZlRdikOtK+ukp0kER3CPpQKmIcDGA5g1zxCSUdJVe7QrHX6c8VDKaWH7J24dgD/7d/+bWMRQBlNwrR4TDUsUsLhYzk9XQ9LBkbqq68SU7GINkF4GnqmbiNOPfXU9Mck4AOzLWAxUJgh0oUiABxABGt80KGAd8lvYTevTVm70nj24BsX0NKOLMSQELR0pwIPaeA+nHxy9Q4swYGc+5y4UC9/+XBBjmjO/e53anrRi8a9GzYBvjvS6JuK0M61wUE8/+///tR0+9uP+y324zm/851qo2STLxLYBfQQVIg+7umY8Sow/Oxnh+kXKtlF9/r0at1XhJKmp2KtPnAAr1ZVn3F3dzLOHRzA/AzpigC+NaX0wZTS7+2ddtWU0kDx+phXIY4NC4QFwgJhgbBAWGAfLUDW/bP7eL+tuVU4gN0/xSdTSqc3OICX2OMAEpR4xd5p7PfTKaVvbM0vGgMJC4QFwgJhgbBAWKDEApfdW9d/UHLwYTsmHMDuX1SUTxXw3VNKnEFVwL++VwX8rcM2EeJ5wgJhgbBAWCAsEBbYHQuEA9j/W9MBxPfD9XtfSknvjYUa4OzOJIsnDQuEBcICYYGwQFhguywQDuB2/R4xmrBAWCAsEBYIC4QFwgIbt0A4gPNMPNQpZN7V4+ycBf7LXlpesyIyxX+bUnpcqxjnpiml56eUKBsSGdE+3G8V2KwF3pBS0m9C48K3790qfovN2rx9ddJVT0sp3Tql9P2UkkZud0gp4TjFb7F/v4XeNs9OKd0tpXTJlNI/p5Qen1I6L96Ljf4IGh7K1Jnr+H24+/9f444l78DOrOvhAE6fiyWdQqZfPc7ssgD9BGptH0opESt4YUrphimlW+yd4KX/WErppSmlP0wpaVx3zt7H+E/CrBuzgC45D0gp/WJK6a4ppXfsfYDjt9iYyS9yYc7fm/e4y2Rwv5tSutUefSXei/37HdxJswAaI/fZ05R9VErp91NKV99zzOO92Mzv4ftz+ZTSpVNK1D+bDmDJO7BT63o4gNMnYUmnkOlXjzNLLXDzlNI/7r30on0a5D0zpUSuut75PTKl5N91Si8ax42yABmFv9+LNNHPrB3A+C1GmXH2we9MKb0npWQRayN+i9nmHXUBG1SZh7qT1GX2tOZus7dhjW/UKHOOPvi4vU1o0wEseQd2al0PB3D0vFqfUNopZNrV46wxFpD+PTmldMzeSaR7brDXw7m+zu1SSu/aK+b5X2MuHscOWsA3RIec16SUSK9yumsHMH6LQfMtdoCIBzFbaUeL37VTSuenlETMX78naRXvxWLmHryQ7MMvpJTul1L6iuY4KaX/ey81+fT4Rg3ab+4BOQdw6Huk3WtJB7C5Y9ua88MBnPZTlHYKmXb1OKvUAhyNv9xLsxDpBmF/qWFckBo6uqjeFqlaqIV56RAP/XEP2+P9nbD3pE0HMH6L/fv5ze1Pp5S+mFK6Z0rpn/Z+F92L7pRSenBKSRQq3ov9+U0ulVLCiZWSxMXkBN47pfT/xDdqX36AnAM49D3iAJZ0ANuXB9iPm4QDOM3KpZ1Cpl09ziqxgEXuv6WUHphSanaH1PAUJxD5ukZEAEssOv4YUSZpx5/bcz5cgQNYF4HEbzHeplPPqL9Jz0gpPaFxkbeklP7flNKPxnsx1bSTzvNe4Pk9Zi8y63v1sj1nXCoyvlGTzFp8Us4BHPoedUUA2x3Aigex7QeGAzj9FyrpFDL96nFmnwV+LaX0gr30yl+3DlSM8Ky9Di123vC7KaXf2SsICcsuZwHO94tafTSvsPd/v3qPFxi/xXL2HrrSx1NKij+aDqD0PI6sKtT4LYYsuMzfdUv/0l5h2gcal3x/Ssl78YX4LZYxdM9Vcg5gydqwU+t6OIDT52F0CpluuzlncuTwa+6152C0ryXNVVfYPXXP6XtTSsnuL6qA51j+oudKc6m4q+F78m97aUa75v8Tv8WyBh+4mkInzp/otyIEUScOxx33HMB4L/bv51BMYHOK+0euSkcpzrn/fG+8Fxv7IS62F+0250W/rQeyEt/ZowYNvQM7ta6HAzhvHkankHn2m3K2l/l7exIXzfMteipR4SZ7EUISGIjxZ+w5jVPuF+eMs0CTAxi/xTjbLXE0rTm8zMvtORm+UWfHe7GEaUdd40Z7agQ/u+eQ4Gc+Z69QKt6LUaYcdbCsBAkwoH1Z+zgigjQYS9aGnVnXwwEcNbfi4LBAWCAsEBYIC4QFwgIH3wLhAB783zCeICwQFggLhAXCAmGBsMAoC4QDOMpccXBYICwQFggLhAXCAmGBg2+BcAAP/m8YTxAWCAuEBcICYYGwQFhglAXCARxlrjg4LBAWCAuEBcICYYGwwMG3QDiAB/83jCcIC4QFwgJhgbBAWCAsMMoC4QCOMlccHBYIC4QFwgJhgbBAWODgWyAcwIP/G8YThAXCAmGBsEBYICwQFhhlgXAAR5krDg4LhAXCAmGBsEBYICxw8C0QDuDB/w3jCcICYYGwQFggLBAWCAuMskA4gKPMFQeHBcICYYGwQFggLBAWOPgWCAfw4P+G8QRhgbBAWCAsEBYIC4QFRlkgHMBR5oqDwwJhgbBAWCAsEBYICxx8C4QDePB/w3iCsEBYICwQFggLhAXCAqMsEA7gKHPFwWGBsEBYICwQFggLhAUOvgXCATz4v2E8QVggLBAWCAuEBcICYYFRFggHcJS54uCwQFggLBAWCAuEBcICB98C4QAe/N8wniAsEBYIC4QFwgJhgbDAKAuEAzjKXHFwWCAsEBYIC4QFwgJhgYNvgXAAD/5vGE8QFggLhAXCAmGBsEBYYJQFwgEcZa44OCwQFggLhAXCAmGBsMDBt0A4gAf/N4wnCAuEBcICYYGwQFggLDDKAuEAjjJXHBwWCAuEBcICYYGwQFjg4FsgHMCD/xvGE4QFwgJhgbBAWCAsEBYYZYFwAEeZKw4OC4QFwgJhgbBAWCAscPAtEA7gwf8N4wnCAmGBsEBYICwQFggLjLJAOICjzBUHhwXCAmGBsEBYICwQFjj4FggH8OD/hvEEYYGwQFggLBAWCAuEBUZZIBzAUeaKg8MCYYGwQFggLBAWCAscfAuEA3jwf8N4grBAWCAsEBYIC4QFwgKjLBAO4ChzxcFhgbBAWCAsEBYIC4QFDr4FwgE8+L9hPEFYICwQFggLhAXCAmGBURYIB3CUueLgsEBYICwQFggLhAXCAgffAuEAHvzfMJ4gLBAWCAuEBcICYYGwwCgL/P9YU3Rzh/XBUQAAAABJRU5ErkJggg==\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x109c61e80>]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make a copy so we don't modify the original data\n",
    "temp2 = temp.copy()\n",
    "\n",
    "# Replace all places where spd is <10 with 0.\n",
    "temp2[spd < 10] = 0\n",
    "plt.figure()\n",
    "plt.plot(temp2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 43.99568218,  40.34747113,  39.08466618,  42.35807886,\n",
       "        36.59074848,  39.04743195,  32.7341674 ,  32.45509221,\n",
       "        31.00606921,  29.23736194,  33.92842907,  29.02609759,\n",
       "        30.5738094 ,  30.55430093,  26.17425503,  23.74424383,\n",
       "        23.17716381,  23.19616754,  20.73118679,  21.00613853,\n",
       "        18.11199313,  21.40786048,  19.043798  ,  24.43450641,\n",
       "        26.38058474,  24.96942595])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Can also combine multiple boolean arrays using the syntax for\n",
    "# bitwise operations\n",
    "# *MUST HAVE PARENTHESES* due to operator precedence\n",
    "temp[(temp < 45) & (spd > 10)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Masked Arrays"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Masked arrays are a specialization of NumPy arrays to handle flagging individual elements as masked. This allows elminating values from plots and from computations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Create a masked array of temperature, masking values where speed is < 10\n",
    "temp_masked = np.ma.array(temp, mask=spd < 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "masked_array(data = [-- 58.83031030545722 58.84980452818231 58.74748457410556 58.91166855581026\n",
       " -- -- 57.14558845673389 57.71870679758818 56.609544686549064 --\n",
       " 53.65471950240981 -- 56.25736285858095 54.224078669317365\n",
       " 49.01743277275585 50.21617013100096 48.04619469334429 50.92135724690631\n",
       " 50.269809593454696 45.96578236782984 47.536577352837156 43.99568218426241\n",
       " 40.34747112603355 39.08466618269884 42.35807886074419 36.59074847933395\n",
       " 39.04743194721268 32.73416739763941 32.45509220611139 31.00606920913678\n",
       " 29.237361938454924 33.92842907159587 29.026097585722482 30.573809403160645\n",
       " 30.554300925170295 26.174255033333033 -- -- 23.744243830681548\n",
       " 23.17716380855608 23.196167536597404 -- 20.731186793984158\n",
       " 21.006138525176496 18.11199312599887 21.40786047855 -- -- --\n",
       " 19.04379800254196 -- -- -- -- -- -- -- -- 24.43450640500327 --\n",
       " 26.38058474167993 24.96942595103603 -- -- -- -- -- -- -- -- -- -- -- -- --\n",
       " -- -- -- -- -- -- -- -- -- -- -- -- -- 56.86603723585148 -- -- -- -- --\n",
       " 60.40483985694016 -- -- -- 59.33285631745498],\n",
       "             mask = [ True False False False False  True  True False False False  True False\n",
       "  True False False False False False False False False False False False\n",
       " False False False False False False False False False False False False\n",
       " False  True  True False False False  True False False False False  True\n",
       "  True  True False  True  True  True  True  True  True  True  True False\n",
       "  True False False  True  True  True  True  True  True  True  True  True\n",
       "  True  True  True  True  True  True  True  True  True  True  True  True\n",
       "  True  True  True  True  True False  True  True  True  True  True False\n",
       "  True  True  True False],\n",
       "       fill_value = 1e+20)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_masked"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "            fig.waiting = false;\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.send_message('closing', {});\n",
       "    fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x109cae630>]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1)\n",
    "ax.plot(temp_masked)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Masked values can be set after array creation by setting the corresponding value to the special value of ma.masked\n",
    "temp_masked[temp_masked > 45] = np.ma.masked"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "masked_array(data = [-- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --\n",
       " 43.99568218426241 40.34747112603355 39.08466618269884 42.35807886074419\n",
       " 36.59074847933395 39.04743194721268 32.73416739763941 32.45509220611139\n",
       " 31.00606920913678 29.237361938454924 33.92842907159587 29.026097585722482\n",
       " 30.573809403160645 30.554300925170295 26.174255033333033 -- --\n",
       " 23.744243830681548 23.17716380855608 23.196167536597404 --\n",
       " 20.731186793984158 21.006138525176496 18.11199312599887 21.40786047855 --\n",
       " -- -- 19.04379800254196 -- -- -- -- -- -- -- -- 24.43450640500327 --\n",
       " 26.38058474167993 24.96942595103603 -- -- -- -- -- -- -- -- -- -- -- -- --\n",
       " -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --],\n",
       "             mask = [ True  True  True  True  True  True  True  True  True  True  True  True\n",
       "  True  True  True  True  True  True  True  True  True  True False False\n",
       " False False False False False False False False False False False False\n",
       " False  True  True False False False  True False False False False  True\n",
       "  True  True False  True  True  True  True  True  True  True  True False\n",
       "  True False False  True  True  True  True  True  True  True  True  True\n",
       "  True  True  True  True  True  True  True  True  True  True  True  True\n",
       "  True  True  True  True  True  True  True  True  True  True  True  True\n",
       "  True  True  True  True],\n",
       "       fill_value = 1e+20)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_masked"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "            fig.waiting = false;\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.send_message('closing', {});\n",
       "    fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(0, 65)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1)\n",
    "ax.plot(np.arange(temp_masked.size), temp_masked)\n",
    "\n",
    "# Set plot limits to the same as before\n",
    "plt.xlim(0, 100)\n",
    "plt.ylim(0, 65)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Exercise"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Currently, the integral in the code below results in a bad value. Using masked arrays, fix this so that the integral returns the proper value of `2.393`.\n",
    "\n",
    "Hint: look at `np.isnan()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "nan\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/rmay/miniconda3/envs/workshop/lib/python3.4/site-packages/IPython/kernel/__main__.py:2: RuntimeWarning: invalid value encountered in sqrt\n",
      "  from IPython.kernel.zmq import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "t = np.linspace(0, 2*np.pi, 200)\n",
    "x = np.sqrt(np.sin(t))\n",
    "print(np.trapz(x, t))"
   ]
  }
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