{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Defining Custom Display Logic for Your Own Objects"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In Python, objects can declare their textual representation using the `__repr__` method.  IPython expands on this idea and allows objects to declare other, richer representations including:\n",
    "\n",
    "* HTML\n",
    "* JSON\n",
    "* PNG\n",
    "* JPEG\n",
    "* SVG\n",
    "* LaTeX\n",
    "\n",
    "This Notebook shows how you can add custom display logic to your own classes, so that they can be displayed using these rich representations. There are two ways of accomplishing this:\n",
    "\n",
    "1. Implementing special display methods such as `_repr_html_`.\n",
    "2. Registering a display function for a particular type.\n",
    "\n",
    "In this Notebook we show how both approaches work."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we get started, we will import the various display functions for displaying the different formats we will create."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from IPython.display import display\n",
    "from IPython.display import (\n",
    "    display_html, display_jpeg, display_png,\n",
    "    display_javascript, display_svg, display_latex\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementing special display methods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The main idea of the first approach is that you have to implement special display methods, one for each representation you want to use. Here is a list of the names of the special methods and the values they must return:\n",
    "\n",
    "* `_repr_html_`: return raw HTML as a string\n",
    "* `_repr_json_`: return raw JSON as a string\n",
    "* `_repr_jpeg_`: return raw JPEG data\n",
    "* `_repr_png_`: return raw PNG data\n",
    "* `_repr_svg_`: return raw SVG data as a string\n",
    "* `_repr_latex_`: return LaTeX commands in a string surrounded by \"$\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Citizen: pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A prominent example of a package that has IPython-aware rich representations of its objects is [pandas](http://pandas.pydata.org/).\n",
    "\n",
    "A pandas DataFrame has a rich HTML table representation,\n",
    "using `_repr_html_`.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import io\n",
    "import pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Writing data.csv\n"
     ]
    }
   ],
   "source": [
    "%%writefile data.csv\n",
    "Date,Open,High,Low,Close,Volume,Adj Close\n",
    "2012-06-01,569.16,590.00,548.50,584.00,14077000,581.50\n",
    "2012-05-01,584.90,596.76,522.18,577.73,18827900,575.26\n",
    "2012-04-02,601.83,644.00,555.00,583.98,28759100,581.48\n",
    "2012-03-01,548.17,621.45,516.22,599.55,26486000,596.99\n",
    "2012-02-01,458.41,547.61,453.98,542.44,22001000,540.12\n",
    "2012-01-03,409.40,458.24,409.00,456.48,12949100,454.53\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "         Date    Open    High     Low   Close    Volume  Adj Close\n",
       "0  2012-06-01  569.16  590.00  548.50  584.00  14077000     581.50\n",
       "1  2012-05-01  584.90  596.76  522.18  577.73  18827900     575.26\n",
       "2  2012-04-02  601.83  644.00  555.00  583.98  28759100     581.48\n",
       "3  2012-03-01  548.17  621.45  516.22  599.55  26486000     596.99\n",
       "4  2012-02-01  458.41  547.61  453.98  542.44  22001000     540.12\n",
       "5  2012-01-03  409.40  458.24  409.00  456.48  12949100     454.53"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pandas.read_csv(\"data.csv\")\n",
    "pandas.set_option('display.notebook_repr_html', False)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "rich HTML can be activated via `pandas.set_option`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td> 2012-06-01</td>\n",
       "      <td> 569.16</td>\n",
       "      <td> 590.00</td>\n",
       "      <td> 548.50</td>\n",
       "      <td> 584.00</td>\n",
       "      <td> 14077000</td>\n",
       "      <td> 581.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td> 2012-05-01</td>\n",
       "      <td> 584.90</td>\n",
       "      <td> 596.76</td>\n",
       "      <td> 522.18</td>\n",
       "      <td> 577.73</td>\n",
       "      <td> 18827900</td>\n",
       "      <td> 575.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td> 2012-04-02</td>\n",
       "      <td> 601.83</td>\n",
       "      <td> 644.00</td>\n",
       "      <td> 555.00</td>\n",
       "      <td> 583.98</td>\n",
       "      <td> 28759100</td>\n",
       "      <td> 581.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td> 2012-03-01</td>\n",
       "      <td> 548.17</td>\n",
       "      <td> 621.45</td>\n",
       "      <td> 516.22</td>\n",
       "      <td> 599.55</td>\n",
       "      <td> 26486000</td>\n",
       "      <td> 596.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td> 2012-02-01</td>\n",
       "      <td> 458.41</td>\n",
       "      <td> 547.61</td>\n",
       "      <td> 453.98</td>\n",
       "      <td> 542.44</td>\n",
       "      <td> 22001000</td>\n",
       "      <td> 540.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td> 2012-01-03</td>\n",
       "      <td> 409.40</td>\n",
       "      <td> 458.24</td>\n",
       "      <td> 409.00</td>\n",
       "      <td> 456.48</td>\n",
       "      <td> 12949100</td>\n",
       "      <td> 454.53</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date    Open    High     Low   Close    Volume  Adj Close\n",
       "0  2012-06-01  569.16  590.00  548.50  584.00  14077000     581.50\n",
       "1  2012-05-01  584.90  596.76  522.18  577.73  18827900     575.26\n",
       "2  2012-04-02  601.83  644.00  555.00  583.98  28759100     581.48\n",
       "3  2012-03-01  548.17  621.45  516.22  599.55  26486000     596.99\n",
       "4  2012-02-01  458.41  547.61  453.98  542.44  22001000     540.12\n",
       "5  2012-01-03  409.40  458.24  409.00  456.48  12949100     454.53"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pandas.set_option('display.notebook_repr_html', True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
      "<table border=\"1\" class=\"dataframe\">\n",
      "  <thead>\n",
      "    <tr style=\"text-align: right;\">\n",
      "      <th></th>\n",
      "      <th>Date</th>\n",
      "      <th>Open</th>\n",
      "      <th>High</th>\n",
      "      <th>Low</th>\n",
      "      <th>Close</th>\n",
      "      <th>Volume</th>\n",
      "      <th>Adj Close</th>\n",
      "    </tr>\n",
      "  </thead>\n",
      "  <tbody>\n",
      "    <tr>\n",
      "      <th>0</th>\n",
      "      <td> 2012-06-01</td>\n",
      "      <td> 569.16</td>\n",
      "      <td> 590.00</td>\n"
     ]
    }
   ],
   "source": [
    "lines = df._repr_html_().splitlines()\n",
    "print \"\\n\".join(lines[:20])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write a simple `Circle` Python class.  Don't even worry about properties such as radius, position, colors, etc. To help you out use the following representations (remember to wrap them in Python strings):\n",
    "\n",
    "For HTML:\n",
    "\n",
    "    &#x25CB;\n",
    "\n",
    "For SVG:\n",
    "\n",
    "    <svg width=\"100px\" height=\"100px\">\n",
    "        <circle cx=\"50\" cy=\"50\" r=\"20\" stroke=\"black\" stroke-width=\"1\" fill=\"white\"/>\n",
    "    </svg>\n",
    "\n",
    "For LaTeX (wrap with `$` and use a raw Python string):\n",
    "\n",
    "    \\bigcirc\n",
    "\n",
    "After you write the class, create an instance and then use `display_html`, `display_svg` and `display_latex` to display those representations.\n",
    "\n",
    "Tips : you can slightly tweek the representation to know from which `_repr_*_` method it came from. \n",
    "For example in my solution the svg representation is blue, and the HTML one show \"`HTML`\" between brackets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is my simple `MyCircle` class:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%load soln/mycircle.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now create an instance and use the display methods:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "c = MyCircle()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "&#x25CB; (<b>html</b>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_html(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg width=\"100px\" height=\"100px\">\n",
       "           <circle cx=\"50\" cy=\"50\" r=\"20\" stroke=\"black\" stroke-width=\"1\" fill=\"blue\"/>\n",
       "        </svg>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_svg(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\bigcirc \\LaTeX$"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_latex(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "alert('I am a circle!');"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_javascript(c)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding IPython display support to existing objects"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When you are directly writing your own classes, you can adapt them for display in IPython by following the above example.  But in practice, we often need to work with existing code we can't modify.  We now illustrate how to add these kinds of extended display capabilities to existing objects. To continue with our example above, we will add a PNG representation to our `Circle` class using Matplotlib."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model citizen: sympy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[SymPy](http://sympy.org) is another model citizen that defines rich representations of its object.\n",
    "Unlike pandas above, sympy registers display formatters via IPython's display formatter API, rather than declaring `_repr_mime_` methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sympy import Rational, pi, exp, I, symbols\n",
    "x, y, z = symbols(\"x y z\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3*pi/2 + exp(I*x)/(x**2 + y)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r = Rational(3,2)*pi + exp(I*x) / (x**2 + y)\n",
    "r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "SymPy provides an `init_printing` function that sets up advanced $\\LaTeX$\n",
    "representations of its objects."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAFAAAAAlCAYAAADV/m7fAAAABHNCSVQICAgIfAhkiAAAA9xJREFU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\nifjCwUhTPWrTpk2bFuJflVvSLV1580UAAAAASUVORK5CYII=\n",
      "text/latex": [
       "$$\\frac{3}{2} \\pi + \\frac{e^{\\mathbf{\\imath} x}}{x^{2} + y}$$"
      ],
      "text/plain": [
       "        ⅈ⋅x \n",
       "3⋅π    ℯ    \n",
       "─── + ──────\n",
       " 2     2    \n",
       "      x  + y"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sympy.interactive.printing import init_printing\n",
    "init_printing()\n",
    "r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To add a display method to an existing class, we must use IPython's display formatter API.  Here we show all of the available formatters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               text/html : HTMLFormatter\n",
      "              image/jpeg : JPEGFormatter\n",
      "           image/svg+xml : SVGFormatter\n",
      "               image/png : PNGFormatter\n",
      "  application/javascript : JavascriptFormatter\n",
      "              text/latex : LatexFormatter\n",
      "        application/json : JSONFormatter\n",
      "              text/plain : PlainTextFormatter\n"
     ]
    }
   ],
   "source": [
    "ip = get_ipython()\n",
    "for mime, formatter in ip.display_formatter.formatters.items():\n",
    "    print '%24s : %s' % (mime, formatter.__class__.__name__)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's grab the PNG formatter:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "png_f = ip.display_formatter.formatters['image/png']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use the `for_type` method to register our display function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "png_f.for_type?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the docstring describes, we need to define a function the takes the object as a parameter and returns the raw PNG data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<r Circle with r=1 at (0, 0)>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "class AnotherCircle(object):\n",
    "    def __init__(self, radius=1, center=(0,0), color='r'):\n",
    "        self.radius = radius\n",
    "        self.center = center\n",
    "        self.color = color\n",
    "    \n",
    "    def __repr__(self):\n",
    "        return \"<%s Circle with r=%s at %s>\" % (\n",
    "                    self.color,\n",
    "                    self.radius,\n",
    "                    self.center,\n",
    "                )\n",
    "    \n",
    "c = AnotherCircle()\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from IPython.core.pylabtools import print_figure\n",
    "\n",
    "def png_circle(circle):\n",
    "    \"\"\"Render AnotherCircle to png data using matplotlib\"\"\"\n",
    "    fig, ax = plt.subplots()\n",
    "    patch = plt.Circle(circle.center,\n",
    "                       radius=circle.radius,\n",
    "                       fc=circle.color,\n",
    "                       )\n",
    "    ax.add_patch(patch)\n",
    "    plt.axis('scaled')\n",
    "    data = print_figure(fig, 'png')\n",
    "    # We MUST close the figure, otherwise IPython's display machinery\n",
    "    # will pick it up and send it as output, resulting in a double display\n",
    "    plt.close(fig)\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'\\x89PNG\\r\\n\\x1a\\n\\x00\\x00'\n"
     ]
    }
   ],
   "source": [
    "c = AnotherCircle()\n",
    "print repr(png_circle(c)[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we register the display function for the type:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "png_f.for_type(AnotherCircle, png_circle)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now all `Circle` instances have PNG representations!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KfPzvhv8VHYOI3Mzi/MX4Z8k/0dbeJjqKw7A4bHCy9iSe3PCkx99iR0TO8ey3z2Jvpedc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\nTkSuQmCC\n",
      "text/plain": [
       "<g Circle with r=2 at (1, 0)>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c2 = AnotherCircle(radius=2, center=(1,0), color='g')\n",
    "c2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KfPzvhv8VHYOI3Mzi/MX4Z8k/0dbeJjqKw7A4bHCy9iSe3PCkx99iR0TO8ey3z2Jvpedc\nLGdxXEVdcx0yczNRZOYb/IioZ1raW/DkxidxvOa46CgOweK4im9PfIul+5aKjkFEbu54zXG8/fPb\nqDnn/tc7WBxd2F+1H9M3Txcdg4g8xPLC5dh0fJPbPxzI4riC0rpSzNg8A42tjaKjEJEH+cOWPyC/\nKl90DLuwODrR0NyAJflLsK96n+goRORhzrWdQ/qmdJyqPSU6So+xODrxQ9kPeCf3HdExiMhDHTYe\nxt/z/47GFvc8o8Hi+IViUzHSN6eLjkFEHu69ve8h50yO6Bg9wuK4RH1zPd7d865XzKdPROKlb0p3\ny1t0WRyX+KH0B3xS+InoGETkJcobyrEkf4nbnbJicfzHUdNRTNsyTXQMIvIyi/IWud0pKxYHzj8d\n/s6ed3iKioiEcLdTViwO8BQVEYnlbqesvL44SswlmL6FT4cTkViL8hYhtyJXdAybOKQ4amtrMWPG\nDJw+ffqKy5SWluKll17CzJkzMWfOHJSVlTliaLs0tzbjs8LPeIqKiCTB8K0BZfXifzdejd3FsXbt\nWhgMBlRXV3e53Pz58/HAAw9g4cKFGD9+PDIzM+0d2m4F1QXI2JMhOgYREQCgyFyEjcc2Sn4uK7uL\nY+zYsViyZAl0Ot0Vl6mqqoLFYkFKSgoAQK/Xo7q6Gmaz2d7he+ys5Szm7p6Ldmu7sAxERL8057s5\nOGQ8JDpGl1xyjcNoNEKlUl32WXBwMIxGoyuG79Tu0t3YXbpb2PhERJ1pbG1EVm4WGpobREe5Ipdd\nHJfLOw7V2trqquEvU2IugWGbQcjYRERX89nBzyT9xkCXFIdWq+1wWspsNnd5estZWtpasPLgSl4Q\nJyJJM2wzoLy+XHSMTjm0OC69oGMymS6WRXh4OJRKJfLy8gAAOTk5UKvVCA0NdeTwNimoLsDbOW+7\nfFwiou4oMhVhy/EtomN0ytfeDWzYsAE7duyA2WxGRkYG4uLiMH36dKxYsQIAMG3a+Wk8DAYDFi9e\njGXLlkGtVsNgcP2porrmOmTkZPCCOBG5hTm75uCm6JsQr40XHeUyMqtE7/vaunUr9Hq9Q7f5Q+kP\nuHfNvQ7dJhGRM829aS5mDJ0BucyxVxZyc3ORlpbWo3W95slxU5MJf/nhL6JjEBF1y1s/voXDZw+L\njnEZrymOvRV78UPZD6JjEBF1S1NbE1YeWomWthbRUS7yiuKoaKjAS9+9JDoGEVGPvLf3PRw8e1B0\njIu8ojh+LP9R8k9iEhFdSZu1De/nvw9Li0V0FABeUByn607jhZ0viI5BRGSXzw5+hgNnD4iOAcAL\niuPfZf92i9kmiYiu5t0970piKhKPLo7y+nK8uvtV0TGIiBxi3dF1OGwUf4eVRxfH3oq9KK0vFR2D\niMhhPj7wMc61nhOawWOLo7qxms9tEJHHWV64HEdMR4Rm8Nji2Fe1j3dSEZHHabe2Y82RNWhtFzO7\nOOChxWFuMmPeT/NExyAicorFeYtRZCoSNr5HFkfh2UL8VP6T6BhERE7R3NaMDSUbhL1i1uOKo6G5\nAVm5WaJjEBE51ds5b+Oo+aiQsT2uOIpMRVh/bL3oGERETtXQ0oCcMzlCxva44th8fLPoCERELrHg\npwWoaqxy+bgeVRzHa44jc2+m6BhERC5xtOYoDp11/d2jHlUc+yr3oa65TnQMIiKXWV643OUPBHpM\ncZiaTMjYkyE6BhGRS2UfyUaxudilY3pMcRw2HkZeZZ7oGERELtVmbcOu07tcOqZHFEdreyuyj2SL\njkFEJMT/5fwfTteddtl4HlEcx8zH8PGBj0XHICISorKx0qUXyT2iOArPFqK5rVl0DCIiYVYeWonm\nVtf8HnT74mhsacQH+z8QHYOISKh1xetwrPaYS8Zy++I4aj7q8gtDRERS09Le4rLTVW5fHHkVebBC\nzERfRERSsnTfUtQ31zt9HLcuDqPFiPf2vic6BhGRJOwu3Y1jNc4/XeXWxVFiLsFhk/j37xIRScXe\nir1OH8Oti2NXKa9tEBFd6r2978FoMTp1DLctjoqGCizJXyI6BhGRpBwxHUFJTYlTx3Db4jhZexLl\nDeWiYxARSc6B6gNO3b7bFse+qn2iIxARSdLHBR+j7pzzZgp3y+KoPVfLKUaIiK5gb+VenKo75bTt\nu2VxnKw9if1V+0XHICKSrCJTkdO27ZbF4cwdQkTkCdYcWeO0uavcrjia25rxxeEvRMcgIpK0zcc3\nO+10la8jNlJaWopFixahrq4OarUa6enpiIqK6rBcVlYW8vPzoVQqL35mMBgQExNj81inak/h25Pf\nOiI2EZHHOtd2DidqTyBeG+/wbTukOObPn48pU6YgJSUFubm5yMzMxBtvvNFhOZlMhokTJ2LUqFE9\nHut47XFOoU5EZIOdp3fijn53OHy7dp+qqqqqgsViQUpKCgBAr9ejuroaZrO50+WtVvsmJHTF4/RE\nRJ7g66KvcdZy1uHbtfuIw2g0QqVSXfZZcHAwjEYjNBpNh+Wzs7Oxfv16aLVaTJo0CcnJyTaPVXOu\nBl8e+dLeyEREXuFE7QmU15cjpFeIQ7frkFNVcnnHA5fW1tYOn02dOhUKhQIAUFBQgAULFiArKwuB\ngYE2jVNeX46DxoP2hSUi8iKn604jOcz2v6Dbwu5TVVqttsNpKbPZDJ1O12HZC6UBAMnJydBoNKis\nrLR5LFe+jJ2IyBN8X/q9w7dpd3GEh4dDqVQiLy8PAJCTkwO1Wo3Q0FCYTKbLSiU3Nxft7e0AgMLC\nQlgslk7vvrqS3Ipce+MSEXmVr4u/xtlGx17ncMipKoPBgMWLF2PZsmVQq9UwGAwAgBUrVgAApk2b\nBgDYvn07li5dCoVCAZVKBYPBcNlRSFdqmmrwZRGvbxARdcepulMoayhDSKDjrnPIrPbe5uQkW7du\nhV6vv/j1wbMHcfOnNwtMRETknj4d/Snujrv7ss9yc3ORlpbWo+25zZPjpXWloiMQEbmlH0p/cOj2\n3KY4SszOfTEJEZGn2npiK+qaHTfNulsUR2tbKzaf2Cw6BhGRWzpiOoKqxiqHbc8tiqOysRI5Z3JE\nxyAicktt1jZUNFY4bHtuURxVlirUnKsRHYOIyG1VNtj+zNzVuEVxVDY67g9MROSNfj7zs8O25RbF\nccx8THQEIiK3tu3kNoddIJd8cbS2tWLLiS2iYxARubUjRsddIJd8cVRZqnhhnIjITm3WNoed9pd8\ncZiaTDCf6/zdHkREZDtHvZtD8sVhbDKKjkBE5BFK6x0zA4fki8PUZBIdgYjII+SUO+a0v+SLg+/g\nICJyjP3V+x3yTJzki4MXxomIHONYzTHUNHl4cZibzNhftV90DCIij9Dc1gzTOftP/0u6OGrO1eBE\n7QnRMYiIPIYjrhtLujjM58xoaW8RHYOIyGN4fHFwYkMiIsc6WXfS7m1Iujgc+eIRIiICjpqO2r0N\nSRdHfUu96AhERB7lqPkoWtta7dqGpIujrK5MdAQiIo9S3lCO2uZau7Yh6eI4arb/kIqIiP6roqEC\nja2Ndm1D0sVRbCoWHYGIyKNYWi1obPHg4jjTeEZ0BCIij2Pv9WNJF0dFg+Nerk5EROc1NDfYtb6k\ni+Nc2znREYiIPE5DiwcXBxEROZ69fylncRAReZnmtma71mdxEBF5maa2JrvWZ3EQEXkZc5PZrvVZ\nHEREXsbYZLRrfRYHEZGXsXdqdRYHEZGXOWs5a9f6LA4iIi9ztsm+4vB1RIjS0lIsWrQIdXV1UKvV\nSE9PR1RUVI+XIyIi5znXKoHnOObPn48HHngACxcuxPjx45GZmWnXckRE5Dzt1na71re7OKqqqmCx\nWJCSkgIA0Ov1qK6uhtls7tFyRETkXG3WNrvWt7s4jEYjVCrVZZ8FBwfDaDT2aDkiInIu4UccACCX\nd9xMa2vHVxPauhwRETmPFVa71re7OLRabYfTTWazGTqdrkfLERGRc8ll9v3qt7s4wsPDoVQqkZeX\nBwDIycmBWq1GaGgoTCbTxbLoajkiInIde4vDIbfjGgwGLF68GMuWLYNarYbBYAAArFixAgAwbdq0\nLpcjIiLXkdt5zCCzWq32nexykq1bt2LkrpGiYxAReRx9hB7zEuYhLS2tR+vzyXEiIi+j9FPatT6L\ng4jIy4QEhNi1PouDiMjLhPRicRARUTfoAux7DILFQUTkZYIDgu1an8VBRORlgv1ZHERE1A0BPgF2\nrc/iICLyMn4+fnatz+IgIvIyHn3EoVKorr4QERF1S5AiyK71JV0cEYERoiMQEXkcj35yPCqI7yMn\nInI0jz7iSNQmio5ARORR1Ao1evn2smsbki6OOE2c6AhERB6ld1Bvzz5VFRYYJjoCEZFHiQqKglqh\ntmsbki4Oe8/DERHR5RK0CZDJZHZtQ9rF4cfiICJypHhNvN3bkHRxaAO0oiMQEXmUSGWk3duQdHEE\n+wfbfRGHiIj+y94p1QGJF4c2QMs7q4iIHMgRZ3IkXRyBfoHQh+tFxyAi8ggqhcruKdUBiRcHAKRG\npIqOQETkEeI18Z5/xAEA4YHhoiMQEXkEfYQegX6Bdm9H8sXhiAs5REQEpIY75gwOi4OIyEs4ajYO\nyReHNkCL6KBo0TGIiNye1xRHaGAoboq+SXQMIiK3FugbiLBeXlIcAHBrn1tFRyAicmspYSnec8QB\ngKeqiIjsNLL/SAT42veu8QvcojgilHyFLBGRPQaFDHLYttyiOEJ7hfKog4jIDo78C7h7FAcvkBMR\n9ZgjL4wDblIcAC+QExH1lCMvjANuVBx9VH1ERyAickuj4kY57MI4APjas3JpaSkWLVqEuro6qNVq\npKenIyoqqtNls7KykJ+fD6Xyv+/XMBgMiImJsWmsaFU0/OR+aGlvsScyEZHXGRI6xKHbs6s45s+f\njylTpiAlJQW5ubnIzMzEG2+80emyMpkMEydOxKhRo3o0VlRQFIZHDsf3Zd/bE5mIyKvIZXLEqGz7\nC7rN2+zpilVVVbBYLEhJSQEA6PV6VFdXw2w2X3Edq9Xa0+EQ4BuAcYnjerw+EZE3Sg5NRlRQ52eC\neqrHRxxGoxEqleqyz4KDg2E0GqHRaDpdJzs7G+vXr4dWq8WkSZOQnJzcrTEH6gb2NC4RkVeamDgR\nQYogh26zy+LIyMhASUlJh89DQkLw0EMPQS7veMDS2tra6bamTp0KhUIBACgoKMCCBQuQlZWFwEDb\n54aPCoqCwkeB5rZmm9chIvJmyWHd+wu6LbosjmeeeeaK36usrOxwWspsNkOn63wa9AulAQDJycnQ\naDSorKxE//79bQ4bFRSF6yOvx67SXTavQ0TkreQyOWKCHHt9A7DjGkd4eDiUSiXy8vIAADk5OVCr\n1QgNDQUAmEymy4olNzcX7e3tAIDCwkJYLJYr3oF1JQG+ARifOL6nkYmIvMq1Ydc6/PoGYOddVQaD\nAYsXL8ayZcugVqthMBgufm/FihUAgGnTpgEAtm/fjqVLl0KhUEClUsFgMFx2FGKrRF2iPZGJiLzG\nxKSJUCqUV1+wm+wqjujoaPz5z3/u9HsXCuOCZ5991p6hLuqn7odg/2DUnKtxyPaIiDyVo14V+0tu\n8+T4BdFB0ZiYOFF0DCIiSdMF6NBP3c8p23a74pDJZBgV27OHCImIvMX9SfcjWuWcWcXdrjgAIDY4\nFn5yP9ExiIgka2T/kU7btlsWRx91H9ze93bRMYiIJEnho0D/4P5O275bFoe/jz/uT7pfdAwiIkka\n2W8k+gQ5b0ZxtywOgLflEhFdyf1J90Ph2/3HHWzltsXRV90XKWEpomMQEUmKDDIkaBOcOobbFkew\nfzCevPZJ0TGIiCTltr63OfX6BuDGxQGcf7hFBpnoGEREkjEleQoC/WyfPLYn3Lo4+gf3xx197xAd\ng4hIEvx9/JEUkuT0cdy6OAL9AvF48uOiYxARScL4hPGIVcc6fRy3Lg4AGBgyEP4+/qJjEBEJNylp\nEnx97JqC0CZuXxz9g/tjUuIk0TGIiIQK9g/GAO0Al4zl9sXhK/fFhKQJomMQEQk1JXkK+qr7umQs\nty8OAEjQJCCkV4joGEREwtwVe5fLxvKI4ohRx2DW0FmiYxARCTEkdAgSta6bTcMjigMARvQZAbnM\nY/44RESFVaFVAAAXf0lEQVQ2mzVsFnS9dC4bz2N+0w7QDsDYAWNFxyAicimVQoWUcNdOv+QxxRHg\nG8BnOojI60xLnYbYYOc/u3EpjykOABikG4T+6v6iYxARucxdsXdBJnPt1EseVRzhynA8d/1zomMQ\nEbnEHX3vEPKKCY8qDgAYFjmMT5ITkVf4fervofRTunxcjyuOeE08fn/t70XHICJyquigaCSHJgsZ\n2+OKw0fugwlJE3hrLhF5tJdvfhm9g3oLGdsjf7smaZPw8DUPi45BROQUIb1CcEPvG4SN75HF4e/r\nj8cGPyY6BhGRU7x444sum5eqMx5ZHAAwUDcQo+NGi45BRORQKoUKv475tdAMHlscSoUS6fp00TGI\niBzqueHPIV4TLzSDxxYHAFwTcg1ujrpZdAwiIofw9/HHnbF3io7h2cUR7B+M527gA4FE5BmmXzcd\nCZoE0TE8uzgAICUsBTdH86iDiNxbgE8AJiVNgo/cR3QUzy8ObYAWL9z4gugYRER2mf2r2UjSJYmO\nAcALigM4/5KTMQPGiI5BRNQjaoUa98bf6/LJDK/EK4ojSBGEmUNnQgZp7HQiou547ZbXEKeJEx3j\nIruLo7a2FjNmzMDp06e7XK60tBQvvfQSZs6ciTlz5qCsrMzeobvlmpBr8Lshv3PpmERE9opURuL2\nvreLjnEZu4pj7dq1MBgMqK6uvuqy8+fPxwMPPICFCxdi/PjxyMzMtGfobgvwDcDjQx6Hn9zPpeMS\nEdnjjV+/gT7qPqJjXMau4hg7diyWLFkCna7rd91WVVXBYrEgJeX86w31ej2qq6thNpvtGb7bBuoG\nYtawWS4dk4iopwZoBuBX0b8SHaMDl1zjMBqNUKlUl30WHBwMo9HoiuEv8pX7YlLSJAT7B7t0XCKi\nnnjr1rcQqYwUHaMD366+mZGRgZKSkg6fh4SEYO7cud0aSC7v2FGtra3d2oYjDNAOwFu3voWnNj3l\n8rGJiGw1dsBYDI0cKjpGp7osjmeeecYhg2i12g6npcxm81VPcTnLbX1vw3Xh12Fv5V4h4xMRdUXh\no8Bzw5+D2l8tOkqnHHaqymq1Xva1yWS6WBbh4eFQKpXIy8sDAOTk5ECtViM0NNRRw3dLeGA43rz1\nTSFjExFdzcs3vYxrQq8RHeOK7CqODRs2YPbs2TCbzcjIyEBWVtbF761YsQKfffbZxa8NBgPWrFmD\nmTNn4uuvv4bBYLBnaLulhKXwFbNEJDl9VH0wJn6MpN9iKrP+8lBBIrZu3Qq9Xu/UMYpMRRi5aiTq\nmuucOg4Rka2+uO8LpPVLc/o4ubm5SEvr2TjSrTQXSNAm4K1b3xIdg4gIADA6fjSGRw4XHeOqvLo4\nAOCOvndgWMQw0TGIyMsF+ATgj9f/UbIXxC/l9cURrgzH327/G58oJyKh/nbb3zA4dLDoGDbx+uIA\ngOTQZPzl138RHYOIvNSImBEYFTtKMrPfXg2LA4CP3Of8wzYR0nzYhog8V4BPAP7y678gNFDM4wk9\nweL4jwhlBObfPp+nrIjIpdzpFNUFLI5LJIcm4/Vfvy46BhF5iVv73OpWp6guYHFcwkfugzEDxvAu\nKyJyugCfAPz5lj+71SmqC1gcvxChjMDfbv8bAnwCREchIg/29h1vu90pqgtYHJ1ICUvBOyPfER2D\niDzUA0kPuOUpqgtYHJ2QyWS4q/9deGzwY6KjEJGHiQ6KxvM3PA9tgFZ0lB5jcVyB2l+NWcNmITY4\nVnQUIvIQPjIf/OPufyBW496/V1gcXegX3A/vj3qft+gSkUO8detb0Ec4d/JWV2BxXEVqeCrevv1t\n0TGIyM2NjhuN+xLug6+8y/fnuQUWx1X4yH1wT9w9mJgwUXQUInJT4YHhePnmlxHSK0R0FIdgcdhA\n20uLF258AXHBcaKjEJGb8ZX74sO7P8QA7QDRURyGxWGjWE0sPrjnAwT5BYmOQkRuJGtkFob3lv47\nNrqDxdENKWEpWHbPMsjgnvdeE5FrzRo2C3fH3Q0fuY/oKA7F4uimX0f/mm8NJKKrSuuXhievfRJB\nCs87S8Hi6CaFrwITkybi8cGPi45CRBLVT90P826dhwhlhOgoTsHi6AFtgBbPXf8cJ0Mkog6Ufkp8\ndM9Hbv+QX1dYHD0UrYpG5p2ZCOsVJjoKEUmEDDIsu3sZUsJTREdxKhaHHRJ1iVg5diVUCpXoKEQk\nAZl3ZmJEzAjRMZyOxWGn6yKuw2ejP4PCRyE6ChEJ9MrNr2Bs/FgofD3/dwGLwwFujL4RH979IW/T\nJfJS01Kn4bHBj0GpUIqO4hIsDgeQy+RI65eGrDuzREchIhe7P+l+zBw2E5oAjegoLsPicBA/Hz+M\niR+D1255TXQUInKRETEj8PJNLyMs0LtukmFxOJBSocQjgx/B09c9LToKETnZ4JDByEjLQLQqWnQU\nl2NxOJjGX4MZ+hl8QJDIgw3QDMCye5ahf3B/0VGEYHE4QZgyDH/61Z/w8DUPi45CRA4WGxyLT0d/\n6lGz3XYXi8NJIpQReOnGlzB54GTRUYjIQfqq+2LFmBVI0CWIjiIUi8OJIpQRmHvTXJYHkQfop+6H\nVWNXIVGXKDqKcCwOJ4sMisQrN7/C01ZEbiwuOA6rxq5Cki5JdBRJYHG4wIXTVrxgTuR+EjQJWDF2\nBY80LmH3W9Nra2vx4osv4vnnn0dMTMwVl8vKykJ+fj6Uyv8+WWkwGLpcx5NEKCPwwq9egEqhQube\nTNFxiMgGqeGpeH/U+159IbwzdhXH2rVrsW7dOtTX1191WZlMhokTJ2LUqFH2DOnWwpRhePb6Z8+/\nuH73y6LjEFEX7ux3J/52+9/QV91XdBTJsetU1dixY7FkyRLodDqblrdarfYM5xE0/hpMGTIF7935\nHue2IpKoh695GBlpGSyNK7D7VFV3ZGdnY/369dBqtZg0aRKSk5NdObxkKBVKTEycCI2/Br9d/1s0\ntzWLjkRE/zFr2Cykp6YjNDBUdBTJ6rI4MjIyUFJS0uHzkJAQzJ07t1sDTZ06FQrF+emGCwoKsGDB\nAmRlZSEwMLBb2/EUfj5+uCv2LmSPy8aDax9EfcvVT/cRkXO9OeJNPDjwQQQHBIuOImldFsczzzzj\nsIEulAYAJCcnQ6PRoLKyEv3793fYGO5GLpPjpuibsHbCWkxeOxlVlirRkYi8klwmx6K7FuHeuHsR\n6Oedf5ntDofdjvvL6xcmkwlms/ni17m5uWhvbwcAFBYWwmKxICoqylHDu7XUiFSsm7gOQyOGio5C\n5HXUCjW+HPclxg0Yx9KwkV3XODZs2IAdO3bAbDYjIyMDcXFxmD59OgBgxYoVAIBp06YBALZv346l\nS5dCoVBApVLBYDBcdhTi7RJ1iVh2zzIs+GkBPjrwkeg4RF4hSZeEpb9ZisGhg0VHcSsyq0Rvddq6\ndSv0er3oGC5najJhzeE1eH7H87BCkv9piDzCuAHjMPfmuegX3E90FCFyc3ORlpbWo3X55LjEaAO0\neGzwY/j8vs8R5BckOg6RR5pz4xzMu22e15aGvVgcEqTwVSCtXxr+OemfiA2OFR2HyGP4+/jjk3s/\nwe9Tf8/bbe3A4pCwlLAUrL5vNSYkTBAdhcjtxQbH4ptJ3+CeuHt4EdxOLA6Ji9XEYt7t8/Bu2rvw\nk/uJjkPklh4f/Diyx2VDH6GHTMYZG+zl0ifHqWd0ATo8OOhBDAwZiCc2PoHjNcdFRyJyCwE+AXh3\n5Lu4s/+dUPurRcfxGDzicBM+ch8MjRyK7HHZeHTwo6LjEEneQN1ArL9/PSYkTmBpOBiLw830D+6P\n1255De+Peh/+Pv6i4xBJ0lPXPoVVY1fh2vBreWrKCXiqyg0F+wdjYuJEJGgT8Ny257CnYo/oSESS\noPHX4L0738MtMbcgSMHb2Z2FRxxuSiaT4drwa/HJvZ/grVvf4oVz8noPDnwQGx/YiN/E/Yal4WQs\nDjcXGRSJ3w35HTbevxH6CO970p5I46/B8tHL8ddb/4oEbYLoOF6BxeEBfOQ+SI1IxfJ7l/Pog7zK\n5IGTsfH+jbgn7h5eAHchFocH4dEHeQuNvwafjv4Ub936FhJ0PMpwNRaHh7lw9PHp6E+RdWcWVAqV\n6EhEDiODDDP0M7DpgU24O+5uHmUIwruqPFSEMgIPDXoIQyOGYtn+Zfh7/t9FRyKyy/DI4Xh9xOtI\nDk1GgG+A6DhejUccHi5Rl4iXb34Z6yetR2pYqug4RN2mDdDiH7/5Bz4d/SmGRQ5jaUgAi8ML9PLt\nhRuibsDKsSux+K7FUCt4eE/SJ5fJMXPoTGx6YBPGJ47nbLYSwlNVXiRcGY4HBj6A68KvwxeHv0DG\nngy0treKjkXUwV3978L/u/7/ITk0Gf6+nCFBanjE4YUSdAn44w1/xLeTv8XvhvwOMnBKBpKG4ZHD\nsXbCWrw/6n0MjRzK0pAoFoeX8pX7IjksGX/59V+w+YHNGBM/RnQk8mIDNAPw+djP8dmYz3BLzC28\nW0riWBxeLsA3APpIPTLvzMQ3E7/BjVE3io5EXiQiMAL/+M0/sHbiWozsPxIhvUJERyIb8BoHAQBU\nChVujL4Ry0cvR35lPub/NB/fl30vOhZ5qN7K3phz0xzcFH0T+qr7io5D3cTioMtoA7S4re9tSA1P\nxcGzB5G1Nwv/KvmX6FjkIQZoBmDOTXOgj9AjWhUtOg71EIuDOqUJ0ODG6BuREpaCg8aD+LjgY3x2\n8DO0W9tFRyM3dF34dZj9q9lICUtBuDJcdByyE4uDuqRUKDEschiGhA7B1JSpWH14NZbsW4JzbedE\nRyM3kNY3DX8Y9gcMDhkMXS+d6DjkICwOsom/rz9SwlNwTeg1eGTwI8g5k4N5P83DydqToqORxAT5\nBeGp1Kfwm7jfIFGbyHdjeCAWB3WLr9wXibpEJOoSkdYvDYeMh7Bs3zKsO7oOVlhFxyOBrgm5Bobh\nBlwbfi1ig2P5ylYPxuKgHotQRiBCGYHre18Pg8mAHSd3IGNPBoxNRtHRyEX85H54aNBDmDxwMpJ0\nSTwd5SVYHGS3Xr69MCRsCIaEDcF9CfehyFSE1YdXI7soG81tzaLjkRPc0PsGPHHtExgcOhjxwfHw\n9eGvEm/C/9rkUH3UfdBH3QcjYkZg1vBZOHz2MD7Y/wF2nNrBU1luLj44HtP00zA0YijiNHG8duHF\nWBzkFL4+vkjQJiBBm4A7+t2BYzXHkF+Zj8V5i1FQXSA6HtkorFcYpl47Fbf2uRXxwfEICeST3cTi\nIBcI9AvE4NDBGBw6GPfE3YOTdSdxxHgEqw6uwo7TOzhDr8QM1A3Eb5N/i2vDr0VfdV/0DuotOhJJ\nDIuDXEoToIEmQIOUsBSMjh+NU7WncKzmGNaXrMeXRV+itrlWdESv4yv3xa0xt2LyoMlI1CWir6ov\nNAEa0bFIwlgcJEyAbwASdAlI0CVgZP+ReHb4szhZexKHjIfw5ZEv8fOZn9HS3iI6pkdK0CZgXMI4\nDIschv7q/uij7sM365HNWBwOcPjwYSQlJYmOYROpZpXL5BcvrN8cczP+Z9D/oLyhHMVVxTjeeBxf\nFX2FnDM5PK3VQ/GaeIxPGI9hkcMQo4qBT6MPkvpK7+egM1L9me2MO2W1h13FsXDhQhQXF8PX1xdq\ntRpPPPEEYmJiOl22tLQUixYtQl1dHdRqNdLT0xEVFWXP8JJx5MgRt/lhcZesvfx6IU4ThwPfHcCT\nY57EI9c8gvKGcpTWleJk7UlsO7kN/y77N8obykVHlRyVQgV9hB4j+41EgjYBMaoYRCojL3vGYt26\ndW5THO7yMwu4V1Z72FUcN998M2bMmAG5XI5t27bh/fffx2uvvdbpsvPnz8eUKVOQkpKC3NxcZGZm\n4o033rBnePIigX6BiNfEI14TDwB4+JqHUdVYhbOWszjTeAaldaXYfmo7/l32b5TVlwlO6zqXlkS8\nNh6RykiE9gpFeGA4FD4K0fHIQ9lVHMOGDbv477GxscjOzu50uaqqKlgsFqSkpAAA9Ho9Fi9eDLPZ\nDI2GF+Go+2QyGcKV4QhXhmMQBgE4XybVlmoYm4wwWUwwnjOioqECuWdykVeVhxJzCSytFsHJu89H\n5oO+6r4YHDIYw3sPR191X+h66aD110IboEVYYBhLglzKYdc4tmzZAr1e3+n3jEYjVCrVZZ8FBwfD\naDSyOMhhZDIZwgLDEBYYdtnnU4ZMQUNzA0znTDA3mWE+Z0Zdcx0aWhpwpv4MSmpKUGQqQnl9Oc40\nnEFja6PLMvvKfRERGIFIZSRiNbFI0Jw/taRSqBCkCEKwfzC0AVqoFWpoA7Sc/4kkocviyMjIQElJ\nSYfPQ0JCMHfu3Itfb9q0CUVFRXj11VevuC25vONbaltbeaGTXEOpUEKpUCJG1fk1uLb2NtQ216Kx\npRGWVgssrRa0tLWgub0ZzW3/+eeSfz/Xdg6t7a1oa29DO9rR3t6OpqYmKAOV8JX7Qi6Tw9/HHwof\nxfl/5Ir//vslXwf6BSLQNxAqfxX8ffxdvFeIekZmtVrtmgdi7dq1+PHHHzF79mwEBXU+BUFlZSXm\nzJmDv//97xc/e+KJJ/Dmm28iNDS003V27tyJlhbeiklE5Ax+fn4YMWJEj9bt8amq9vZ2fPDBBxdL\nISDg8nvATSYTZDIZNBoNwsPDoVQqkZeXh9TUVOTk5ECtVl+xNAD0+A9ERETO1eMjjsrKSsyYMQOR\nkZGXnYZ6+umnER8fj/feew8AMG3aNADnb8ddvHgxamtrPe52XCIib2L3qSoiIvIuHa9YExERdYHF\nQURE3SKpuapqa2vx4osv4vnnn7/i1CWA+OlLujN+VlYW8vPzoVQqL35mMBi6/PO5Kp/o/didDCL2\nY2ds+RmVwn4FbMsqlf1q6/RFUti3tmaVwr5dtGgRDh06BJlMBj8/Pzz++ONITk7usFy396tVIr7+\n+mvr1KlTrQ8++KD11KlTXS77zDPPWPPz861Wq9W6Z88e6+zZs10RsUfjZ2VlWTds2OCqaFar1fZ8\novdjdzKI2I+/ZOvPqBT2q61ZpbBfrVar9eeff7a2tbVZrVar9dtvv7XOmTOn0+WksG9tzSqFfbtv\n376LWffs2WOdNWtWp8t1d79K5lTV2LFjsWTJEuh0Xb/svrPpS6qrq2E2m10Rs0fjW114/4Gt+UTv\nx55kcOV+7IwtP6NS2K+A7f8/AeL3K3B++qILd2fGxsbCZDJ1WEYq+9aWrBeI3rdDhgyBXC6H1WpF\nWVkZYmNjOyzTk/0qqVNVthA9fUlPxs/Ozsb69euh1WoxadKkTg8VXZ1P9H7sSQZX7seeksJ+7S6p\n7dcrTV8kxX3b1VRLgDT27aFDh7BgwQJoNBrMnj27w/d7sl9dVhy2Tl9iC2dPX9JV1oceeqhb40+d\nOhUKxfkJ6AoKCrBgwQJkZWUhMDDQYXl/ydZ8UpgGxtYMIvZjT0lhv9pKavv1atMXSWnfXi2rVPbt\nwIEDsWTJEuTl5eHVV1/FwoULOyzT3f3qsuJ45plnHLIdrVbb4RDKbDbbdEhuq66yVlZWdmv8Cz84\nAJCcnAyNRoPKykr079/fIVl/ydb944r9eDXdyeDq/dhTUtiv3SGl/Xph+qLOZqIApLVvr5YVkNa+\nBYDU1FScPXsW9fX1l00P1ZP9KplrHJf65XlBk8l08Q926fQlAGyavsSRrjb+pVkBIDc3F+3t7QCA\nwsJCWCwWp94F0lU+Ke3H7mQFXL8fr+bSn1Gp7ddfulJWQBr7tb29HUuXLkVBQQHmzJlz2S81qe1b\nW7MC4vdtfX09cnJyLv73//777xEaGoqgoCC796tknhzfsGEDduzYgZMnTyIyMhJxcXGYPn06AEhu\n+pKuxv9l1rfffhvFxcVQKBRQqVR47LHHkJCQICSf1PZjd7KK2I+/dKWfUSnuV1uzSmG/Xmn6ounT\np2PTpk2X5RW9b7uTVfS+ra+vR0ZGBsrKyuDv7w+dTocpU6YgJibG7p9ZyRQHERG5B0meqiIiIuli\ncRARUbewOIiIqFtYHERE1C0sDiIi6hYWBxERdQuLg4iIuoXFQURE3fL/AR8SQcFGS9m7AAAAAElF\nTkSuQmCC\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_png(c2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## return the object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# for demonstration purpose, I do the same with a circle that has no _repr_javascript method\n",
    "class MyNoJSCircle(MyCircle):\n",
    "    \n",
    "    def _repr_javascript_(self):\n",
    "        return\n",
    "\n",
    "cNoJS = MyNoJSCircle()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Of course you can now still return the object, and this will use compute all the representations, store them in the notebook and show you the appropriate one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cNoJS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or just use `display(object)` if you are in a middle of a loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for i in range(3):\n",
    "    display(cNoJS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Advantage of using `display()` versus `display_*()` is that all representation will be stored in the notebook document and notebook file, they are then availlable for other frontends or post-processing tool like `nbconvert`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's compare `display()` vs `display_html()` for our circle in the Notebook Web-app and we'll see later the difference in nbconvert."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"I should see a nice html circle in web-app, but\"\n",
    "print \"nothing if the format I'm viewing the notebook in\"\n",
    "print \"does not support html\"\n",
    "display_html(cNoJS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"Whatever the format I will see a representation\"\n",
    "print \"of my circle\"\n",
    "display(cNoJS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"Same if I return the object\"\n",
    "cNoJS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"But not if I print it\"\n",
    "print cNoJS"
   ]
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 0
}