CGM_Jupyter_Breakout_Session_170512.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# CGM Jupyter and DesignSafe Breakout Session\n",
    "## Adam B. Price <br> May 12, 2017"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Introduction\n",
    "\n",
    "1. [What is the Jupyter Notebook](https://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/What%20is%20the%20Jupyter%20Notebook.ipynb)\n",
    "2. [Notebook Basics](https://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/Notebook%20Basics.ipynb)\n",
    "3. [Jupyter Notebook Docs](https://jupyter-notebook.readthedocs.io/en/latest/notebook.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Outline\n",
    "* [1. Cell types](#1.-Cell-types)\n",
    "* [2. Imports](#2.-Imports)\n",
    "* [3. Tab completion and documentation](#3.-Tab-completion-and-documentation)\n",
    "* [4. Data types](#4.-Data-types)\n",
    "* [5. Read demo csv file in pandas DataFrame](#5.-Read-demo-csv-file-into-pandas-DataFrame)\n",
    "* [6. Make a plot from DataFrame](#6.-Make-a-plot-from-DataFrame)\n",
    "* [7. Read fast data binary file](#7.-Read-fast-data-binary-file)\n",
    "* [8. Plot data from binary file](#8.-Plot-data-from-binary-file)\n",
    "* [9. Store data from binary file in a dictionary and make a plot](#9.-Store-data-from-binary-file-in-a-dictionary-and-make-a-plot)\n",
    "* [10. Widgets](#10.-Widgets)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 1. Cell types"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "## 1.2 Markdown cells"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Heading 1\n",
    "## Heading 1.1\n",
    "## Heading 1.2\n",
    "### Heading 1.2.1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Mardown is useful for taking notes...\n",
    "\n",
    "*italic* and **bold** text\n",
    "\n",
    "Bulleted or numbered lists:\n",
    "\n",
    "* Item 1\n",
    "* Item 2\n",
    "\n",
    "\n",
    "1. Ordered item 1\n",
    "2. Ordered item 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "And rendering equations with Latex\n",
    "\n",
    "Inline equations like $A=\\pi r^2$\n",
    "\n",
    "Or equations on their own line...$$E=mc^2$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "<!-- display image in markdown cell with HTML -->\n",
    "### Look at this huge centrifuge; it is for geotechnical modeling.\n",
    "<img src='images/centrifuge_top.jpg' >\n",
    "Photo credit: https://cgm.engr.ucdavis.edu/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Some helpful Markdown resources:\n",
    "1. [Jupyter Markdown Cells Documentation](https://jupyter-notebook.readthedocs.io/en/latest/examples/Notebook/Working%20With%20Markdown%20Cells.html)\n",
    "2. [Markdown Cheatsheet by Adam Pritchard](https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 1.2 Code cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "# This is a code cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello World!\n"
     ]
    }
   ],
   "source": [
    "# Press Shift+Enter to execute a code cell in the notebook.\n",
    "print('Hello World!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Jupyter will display unassigned output of a statement on the last line\n",
    "# of a code cell without requiring a print statment. \n",
    "5 + 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The same goes for the name of a variable...\n",
    "myvar = 5 + 6\n",
    "myvar"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 2. Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "# Imports.\n",
    "\n",
    "# Set matplotlib backend for interactive notebook use.\n",
    "%matplotlib notebook\n",
    "\n",
    "# Importing allows for access to code that is in another module.\n",
    "import pandas as pd  # imports pandas as pd in local namespace.\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 3. Tab completion and documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'0.19.2'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Two-dimensional size-mutable, potentially heterogeneous tabular data\n",
      "    structure with labeled axes (rows and columns). Arithmetic operations\n",
      "    align on both row and column labels. Can be thought of as a dict-like\n",
      "    container for Series objects. The primary pandas data structure\n",
      "\n",
      "    Parameters\n",
      "    ----------\n",
      "    data : numpy ndarray (structured or homogeneous), dict, or DataFrame\n",
      "        Dict can contain Series, arrays, constants, or list-like objects\n",
      "    index : Index or array-like\n",
      "        Index to use for resulting frame. Will default to np.arange(n) if\n",
      "        no indexing information part of input data and no index provided\n",
      "    columns : Index or array-like\n",
      "        Column labels to use for resulting frame. Will default to\n",
      "        np.arange(n) if no column labels are provided\n",
      "    dtype : dtype, default None\n",
      "        Data type to force, otherwise infer\n",
      "    copy : boolean, default False\n",
      "        Copy data from inputs. Only affects DataFrame / 2d ndarray input\n",
      "\n",
      "    Examples\n",
      "    --------\n",
      "    >>> d = {'col1': ts1, 'col2': ts2}\n",
      "    >>> df = DataFrame(data=d, index=index)\n",
      "    >>> df2 = DataFrame(np.random.randn(10, 5))\n",
      "    >>> df3 = DataFrame(np.random.randn(10, 5),\n",
      "    ...                 columns=['a', 'b', 'c', 'd', 'e'])\n",
      "\n",
      "    See also\n",
      "    --------\n",
      "    DataFrame.from_records : constructor from tuples, also record arrays\n",
      "    DataFrame.from_dict : from dicts of Series, arrays, or dicts\n",
      "    DataFrame.from_items : from sequence of (key, value) pairs\n",
      "    pandas.read_csv, pandas.read_table, pandas.read_clipboard\n",
      "    \n"
     ]
    }
   ],
   "source": [
    "print(pd.DataFrame.__doc__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plot lines and/or markers to the\n",
      ":class:`~matplotlib.axes.Axes`.  *args* is a variable length\n",
      "argument, allowing for multiple *x*, *y* pairs with an\n",
      "optional format string.  For example, each of the following is\n",
      "legal::\n",
      "\n",
      "    plot(x, y)        # plot x and y using default line style and color\n",
      "    plot(x, y, 'bo')  # plot x and y using blue circle markers\n",
      "    plot(y)           # plot y using x as index array 0..N-1\n",
      "    plot(y, 'r+')     # ditto, but with red plusses\n",
      "\n",
      "If *x* and/or *y* is 2-dimensional, then the corresponding columns\n",
      "will be plotted.\n",
      "\n",
      "If used with labeled data, make sure that the color spec is not\n",
      "included as an element in data, as otherwise the last case\n",
      "``plot(\"v\",\"r\", data={\"v\":..., \"r\":...)``\n",
      "can be interpreted as the first case which would do ``plot(v, r)``\n",
      "using the default line style and color.\n",
      "\n",
      "If not used with labeled data (i.e., without a data argument),\n",
      "an arbitrary number of *x*, *y*, *fmt* groups can be specified, as in::\n",
      "\n",
      "    a.plot(x1, y1, 'g^', x2, y2, 'g-')\n",
      "\n",
      "Return value is a list of lines that were added.\n",
      "\n",
      "By default, each line is assigned a different style specified by a\n",
      "'style cycle'.  To change this behavior, you can edit the\n",
      "axes.prop_cycle rcParam.\n",
      "\n",
      "The following format string characters are accepted to control\n",
      "the line style or marker:\n",
      "\n",
      "================    ===============================\n",
      "character           description\n",
      "================    ===============================\n",
      "``'-'``             solid line style\n",
      "``'--'``            dashed line style\n",
      "``'-.'``            dash-dot line style\n",
      "``':'``             dotted line style\n",
      "``'.'``             point marker\n",
      "``','``             pixel marker\n",
      "``'o'``             circle marker\n",
      "``'v'``             triangle_down marker\n",
      "``'^'``             triangle_up marker\n",
      "``'<'``             triangle_left marker\n",
      "``'>'``             triangle_right marker\n",
      "``'1'``             tri_down marker\n",
      "``'2'``             tri_up marker\n",
      "``'3'``             tri_left marker\n",
      "``'4'``             tri_right marker\n",
      "``'s'``             square marker\n",
      "``'p'``             pentagon marker\n",
      "``'*'``             star marker\n",
      "``'h'``             hexagon1 marker\n",
      "``'H'``             hexagon2 marker\n",
      "``'+'``             plus marker\n",
      "``'x'``             x marker\n",
      "``'D'``             diamond marker\n",
      "``'d'``             thin_diamond marker\n",
      "``'|'``             vline marker\n",
      "``'_'``             hline marker\n",
      "================    ===============================\n",
      "\n",
      "\n",
      "The following color abbreviations are supported:\n",
      "\n",
      "==========  ========\n",
      "character   color\n",
      "==========  ========\n",
      "'b'         blue\n",
      "'g'         green\n",
      "'r'         red\n",
      "'c'         cyan\n",
      "'m'         magenta\n",
      "'y'         yellow\n",
      "'k'         black\n",
      "'w'         white\n",
      "==========  ========\n",
      "\n",
      "In addition, you can specify colors in many weird and\n",
      "wonderful ways, including full names (``'green'``), hex\n",
      "strings (``'#008000'``), RGB or RGBA tuples (``(0,1,0,1)``) or\n",
      "grayscale intensities as a string (``'0.8'``).  Of these, the\n",
      "string specifications can be used in place of a ``fmt`` group,\n",
      "but the tuple forms can be used only as ``kwargs``.\n",
      "\n",
      "Line styles and colors are combined in a single format string, as in\n",
      "``'bo'`` for blue circles.\n",
      "\n",
      "The *kwargs* can be used to set line properties (any property that has\n",
      "a ``set_*`` method).  You can use this to set a line label (for auto\n",
      "legends), linewidth, anitialising, marker face color, etc.  Here is an\n",
      "example::\n",
      "\n",
      "    plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)\n",
      "    plot([1,2,3], [1,4,9], 'rs',  label='line 2')\n",
      "    axis([0, 4, 0, 10])\n",
      "    legend()\n",
      "\n",
      "If you make multiple lines with one plot command, the kwargs\n",
      "apply to all those lines, e.g.::\n",
      "\n",
      "    plot(x1, y1, x2, y2, antialiased=False)\n",
      "\n",
      "Neither line will be antialiased.\n",
      "\n",
      "You do not need to use format strings, which are just\n",
      "abbreviations.  All of the line properties can be controlled\n",
      "by keyword arguments.  For example, you can set the color,\n",
      "marker, linestyle, and markercolor with::\n",
      "\n",
      "    plot(x, y, color='green', linestyle='dashed', marker='o',\n",
      "         markerfacecolor='blue', markersize=12).\n",
      "\n",
      "See :class:`~matplotlib.lines.Line2D` for details.\n",
      "\n",
      "The kwargs are :class:`~matplotlib.lines.Line2D` properties:\n",
      "\n",
      "  agg_filter: unknown\n",
      "  alpha: float (0.0 transparent through 1.0 opaque) \n",
      "  animated: [True | False] \n",
      "  antialiased or aa: [True | False] \n",
      "  axes: an :class:`~matplotlib.axes.Axes` instance \n",
      "  clip_box: a :class:`matplotlib.transforms.Bbox` instance \n",
      "  clip_on: [True | False] \n",
      "  clip_path: [ (:class:`~matplotlib.path.Path`, :class:`~matplotlib.transforms.Transform`) | :class:`~matplotlib.patches.Patch` | None ] \n",
      "  color or c: any matplotlib color \n",
      "  contains: a callable function \n",
      "  dash_capstyle: ['butt' | 'round' | 'projecting'] \n",
      "  dash_joinstyle: ['miter' | 'round' | 'bevel'] \n",
      "  dashes: sequence of on/off ink in points \n",
      "  drawstyle: ['default' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post'] \n",
      "  figure: a :class:`matplotlib.figure.Figure` instance \n",
      "  fillstyle: ['full' | 'left' | 'right' | 'bottom' | 'top' | 'none'] \n",
      "  gid: an id string \n",
      "  label: string or anything printable with '%s' conversion. \n",
      "  linestyle or ls: ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) | ``'-'`` | ``'--'`` | ``'-.'`` | ``':'`` | ``'None'`` | ``' '`` | ``''``]\n",
      "  linewidth or lw: float value in points \n",
      "  marker: :mod:`A valid marker style <matplotlib.markers>`\n",
      "  markeredgecolor or mec: any matplotlib color \n",
      "  markeredgewidth or mew: float value in points \n",
      "  markerfacecolor or mfc: any matplotlib color \n",
      "  markerfacecoloralt or mfcalt: any matplotlib color \n",
      "  markersize or ms: float \n",
      "  markevery: [None | int | length-2 tuple of int | slice | list/array of int | float | length-2 tuple of float]\n",
      "  path_effects: unknown\n",
      "  picker: float distance in points or callable pick function ``fn(artist, event)`` \n",
      "  pickradius: float distance in points \n",
      "  rasterized: [True | False | None] \n",
      "  sketch_params: unknown\n",
      "  snap: unknown\n",
      "  solid_capstyle: ['butt' | 'round' |  'projecting'] \n",
      "  solid_joinstyle: ['miter' | 'round' | 'bevel'] \n",
      "  transform: a :class:`matplotlib.transforms.Transform` instance \n",
      "  url: a url string \n",
      "  visible: [True | False] \n",
      "  xdata: 1D array \n",
      "  ydata: 1D array \n",
      "  zorder: any number \n",
      "\n",
      "kwargs *scalex* and *scaley*, if defined, are passed on to\n",
      ":meth:`~matplotlib.axes.Axes.autoscale_view` to determine\n",
      "whether the *x* and *y* axes are autoscaled; the default is\n",
      "*True*.\n",
      "\n",
      ".. note::\n",
      "    In addition to the above described arguments, this function can take a\n",
      "    **data** keyword argument. If such a **data** argument is given, the\n",
      "    following arguments are replaced by **data[<arg>]**:\n",
      "\n",
      "    * All arguments with the following names: 'x', 'y'.\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(plt.plot.__doc__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 4. Data types"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "## 4.1 Built-in data types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# String.\n",
    "my_string = 'this is my string'\n",
    "type(my_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "int"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Integer.\n",
    "my_int = 3\n",
    "type(my_int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "float"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Float.\n",
    "my_float = 3.1\n",
    "type(my_float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# List (mutable).\n",
    "my_list = [my_string, my_int, my_float]\n",
    "type(my_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['this is my string', 3, 3.1, 'appended entry']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_list.append('appended entry')\n",
    "my_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'this is my string'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# First element in list.\n",
    "my_list[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1.0, 4.0, 9.0, 16.0]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# List comprehension.\n",
    "a = [1., 2., 3., 4.]\n",
    "[x**2 for x in a]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tuple"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Tuple (immutable).\n",
    "my_tuple = (my_string, my_int, my_float)\n",
    "type(my_tuple)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Second element in tuple.\n",
    "my_tuple[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dictionary (key: value pairs).\n",
    "my_dict = {'1': 'first value', 2: 'second value'}\n",
    "type(my_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'first value'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_dict['1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['this is my string', 3, 3.1, 'appended entry', 'appended entry']\n",
      "set(['this is my string', 3.1, 3, 'appended entry'])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "set"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sets (unordered collection with not duplicate elements).\n",
    "my_list.append('appended entry')\n",
    "print(my_list)\n",
    "my_set = set(my_list)\n",
    "print(my_set)\n",
    "type(my_set)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 4.2 A couple other data types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  1.   4.   9.  16.]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Numpy array.\n",
    "my_array = np.array([1., 2., 3., 4.])\n",
    "output = my_array**2\n",
    "print(output)\n",
    "type(my_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>my_array</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   my_array\n",
       "0       1.0\n",
       "1       2.0\n",
       "2       3.0\n",
       "3       4.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Pandas DataFrame.\n",
    "my_df = pd.DataFrame(data=my_array, columns=['my_array'])\n",
    "print(type(my_df))\n",
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>my_array</th>\n",
       "      <th>output</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   my_array  output\n",
       "0       1.0     1.0\n",
       "1       2.0     4.0\n",
       "2       3.0     9.0\n",
       "3       4.0    16.0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df['output'] = output\n",
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     1.0\n",
       "1     4.0\n",
       "2     9.0\n",
       "3    16.0\n",
       "Name: output, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df['output']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>my_array</th>\n",
       "      <th>output</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   my_array  output\n",
       "0       1.0     1.0\n",
       "1       2.0     4.0\n",
       "2       3.0     9.0\n",
       "3       4.0    16.0"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df2 = pd.DataFrame(data=np.asarray([my_array, output]).transpose(), columns=['my_array', 'output'])\n",
    "my_df2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 5. Read demo csv file into pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "# Read csv file into pandas DataFrame.\n",
    "df = pd.read_csv('data/demo_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time, s</th>\n",
       "      <th>CPT, N</th>\n",
       "      <th>FB, m</th>\n",
       "      <th>ICP1, g</th>\n",
       "      <th>LC, N</th>\n",
       "      <th>LP1, m</th>\n",
       "      <th>PPT5858, kPa</th>\n",
       "      <th>PPT5859, kPa</th>\n",
       "      <th>rpm, rpm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.732</td>\n",
       "      <td>-8.193489</td>\n",
       "      <td>0.001727</td>\n",
       "      <td>0.002858</td>\n",
       "      <td>-3.875657</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>-2.148362</td>\n",
       "      <td>1.676645</td>\n",
       "      <td>999.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.757</td>\n",
       "      <td>-8.141563</td>\n",
       "      <td>0.001723</td>\n",
       "      <td>0.002965</td>\n",
       "      <td>-3.836547</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>-2.148026</td>\n",
       "      <td>1.676952</td>\n",
       "      <td>999.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.761</td>\n",
       "      <td>-8.106561</td>\n",
       "      <td>0.001715</td>\n",
       "      <td>0.002950</td>\n",
       "      <td>-3.909718</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>-2.148149</td>\n",
       "      <td>1.678231</td>\n",
       "      <td>999.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.757</td>\n",
       "      <td>-8.102640</td>\n",
       "      <td>0.001726</td>\n",
       "      <td>0.003036</td>\n",
       "      <td>-3.950031</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>-2.148680</td>\n",
       "      <td>1.677248</td>\n",
       "      <td>999.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.762</td>\n",
       "      <td>-8.132675</td>\n",
       "      <td>0.001726</td>\n",
       "      <td>0.002951</td>\n",
       "      <td>-3.928496</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>-2.149088</td>\n",
       "      <td>1.677736</td>\n",
       "      <td>999.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   time, s    CPT, N     FB, m   ICP1, g     LC, N    LP1, m  PPT5858, kPa  \\\n",
       "0    0.732 -8.193489  0.001727  0.002858 -3.875657  0.000300     -2.148362   \n",
       "1    2.757 -8.141563  0.001723  0.002965 -3.836547  0.000302     -2.148026   \n",
       "2    3.761 -8.106561  0.001715  0.002950 -3.909718  0.000302     -2.148149   \n",
       "3    4.757 -8.102640  0.001726  0.003036 -3.950031  0.000300     -2.148680   \n",
       "4    5.762 -8.132675  0.001726  0.002951 -3.928496  0.000302     -2.149088   \n",
       "\n",
       "   PPT5859, kPa  rpm, rpm  \n",
       "0      1.676645     999.0  \n",
       "1      1.676952     999.0  \n",
       "2      1.678231     999.0  \n",
       "3      1.677248     999.0  \n",
       "4      1.677736     999.0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display first 5 rows for DataFrame.\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display DataFrame type.\n",
    "type(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1801, 9)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check DataFrame shape.\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 6. Make a plot from DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
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       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make a plot using the Matplotlib pyplot API.\n",
    "plt.figure(figsize=[9, 4])  # Make figure.\n",
    "ax = plt.gca()  # Get current axis.\n",
    "plt.plot(df['time, s'], df['PPT5858, kPa']) # Plot onto current axis.\n",
    "\n",
    "# Set axis labels.\n",
    "ax.set_xlabel('time (s)') \n",
    "ax.set_ylabel('PPT5858 (kPa)')\n",
    "\n",
    "# Add gridlines.\n",
    "ax.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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wNPNFYPaheGl5iFwdytY1s98xBRA2xRA247KW3vHY2Ds6WnZWV8pgHb2wNhdEiCBQiFw6kqyeo3bX0dlEg+4JzgA03tGIrSMHLxROIUCSAHUG0kUQL0E2T5PAhRABgcJkIAzETAYsjD/7xOYuuYgbqRnwsvDFe88FI4+Taup3b6FWSiAFEC98UQB1EuQ7SmAjAESIAGnJ3D8UhKGLN6D7SeuKhaNqgWqt3lUDZKVXIVfKIAUQL1R5ZACeO7cOUycOBGrVq1S7+wtU6YM6tevj0GDBqFNm+w37lWtWhUnT8pZ24C3tzfCw8MxfPhw9OrV65bPcgMs7++dO1c2cd++bNq0Ca1atULt2rURFRUFN7ebZzwFBARg5syZub4zOL/r2svnzADay5NiP0mABApKINOQha+3HMf7vx1EaoYB3p5uGN6hJp6+vwpcCznrZ95HCiAFsKAxa2rncAJ44sQJNG3aFCJY48aNQ0REBNLT0/Hrr7/iiy++wIEDcvZ2tgD27dsX/fr1g3yRPvjgA3z55ZfYsmWLeo9vZmamqvfXX3+hR48eOHjwYM7bUooXLw5///zPbTIJoJeXF2bPno0+ffrkPC8KoN7QZXsSIAESuLsEDp9PxDuLo7DnVLzqSLPQIEzuHoHKgd53vGMUQAqg3iBzOAHs2LGjyraJsPn43Jp6j4+PV2JoEkDJCMovKRkZGUrqBgwYgMmTJ+dwNUnc1atXc9pqhW5qO3jwYPzwww84fPgwihXLfhMfBVArRdYjARIgAdsikJ5pwBebj+GjdYeRlmlAiWLuGNm5Fh67rzJc5IW+RVAogBRAvWFmnQBmZQHpyXrvaX17D2+ot2TnU65cuYKgoCA1/SvTubcrkgE0F0CTlElWULKBplIYAijT0Pfddx/eeustvPPOOxTA/B4kPycBEiABGyWw72wChiyOwr6z11QPW4WXxqTuESjvX7xIe0wBpADqDTjrBDAtCZhUQe89rW8/4izgmf9C2m3btuH+++/H0qVL0a1bN80CmJaWpqRvxIgRWLlyJTp16lSoAijZwx9//FFd/9ixYyrTyAyg9WHAFiRAAiRwtwikZRgwa8NhzN50FBmGLPgX98DoLrXR7Z6KRZb1Mx87BZACqPe74FACuHXrVjzwwAOaBTAuLg4eHh6QzQq+vr4qazh06NBbmBZGBlAEUK4vm0F69uyJSZMmUQD1Ri7bkwAJkEAREZA1fpL1O3g+Ud3x4TplMb5rXZQp4VVEPfjvbSiAFEC9wWedADrYFPAzzzyjduGKnJUtWzbXf8UVlgBKxm/RokXqfrIWUGSQu4D1hi/bkwAJkMCdI5CSnomZ6w7ji81HYcgCSvl4YtyjddExotxdyfoxA3jrs85/Ydidiw1HuLJ1AmgHI+7QoQOio6Ot3gSS19AKUwDlHo0aNcI999yjpoQpgHYQUOwiCZCAUxLYefIKBi+OwrGLSWr8j9SroKZ8S/lmb+S724UZQGYA9cagwwmgrLGTY2ACAwPVMTCRkZFqh+/atWsxZ84c7N+/XzHLbRNIbjALWwA3bNiAhx9+WN1Kjp2RjKCjFp4D6KhPluMiAcclkJyWgem/HsTcv05AJr1KlyiGiV3r4qE65Wxq0BRACqDegHQ4ARQgsrZPdgLLhg75fenSpZUIvv7665BjYgpLAFu2bKlEMq9DofOSRxHA3377Dd988w0FUG8Esz0JkAAJFBKBv49eVu/wjb2SfdpFzwaV8F6n2vD39iikOxTeZSiAFEC90eSQAqgXitb2VapUwdixYx1a4rSyyK0eM4B66LEtCZBAURG4npqBKav3Y8E/seqW5f291IHOLcPLFFUXrL4PBZACaHXQWDSgABaQ4L59+/Dkk09i9+7dcHV1LeBVHLsZBdCxny9HRwKOQGDzoYsYvjQaZ+JvqOE8dX+wepVbCS/by/qZ86YAUgD1fv8ogHoJsn2eBCiADA4SIAFbJZBwIx0TV8Vg4Y7TqouVShbH1B6RaBoaZKtdvqVfFEAKoN5ApQDqJcj2FEDGAAmQgF0RWL//PEYsi8b5a6nqJVO9G1fF4IfD4VPM3W7GQQGkAOoNVgqgXoJsTwFkDJAACdgFgatJaRi7Yh+W7z6r+lstyAfTekaiYdVAu+i/eScpgBRAvUFLAdRLkO0pgIwBEiABmyfwS3QcRv20F5eup8HVBXixeQjealcDXh5uNt/33DpIAaQA6g1cCqBegmxPAWQMkAAJ2CyBi4mpGP3zXvwSfU71MayMr8r63RNc0mb7rKVjFEAKoJY4uV0dCqBegmxPAWQMkAAJ2ByBrKws/LznLMb8vA9Xk9Ph5uqCV1tWx+utQ1HM3T6zfpwCvjXM+Co4fV87CqA+fmx9GwLcBczwIAESuBsEziWkYOTyaKzbf0HdvlZ5P0zvGYm6Ff3vRnfuyD2ZAWQGUG9gUQD1EmR7ZgAZAyRAAjZBQLJ+i3aexviVMUhMyYCHmwveaB2GV1pWh4ebY53XSgGkAOr90lEA9RJkewogY4AESOCuE5CDnIcticIfhy+pvtSr5I9pPeshvFyJu963O9EBCiAFUG9cOZwAPv/885g3b95/uBw+fBihoaHqtW3mnwcGBqJhw4aYNm2ael8wS+ER4BRw4bHklUiABHInYDBk4bttsZj8y34kpWXC091V7e59sVk1uDtY1s+cAAWQAqj3zwSHFMDz58/jm2++uYVN6dKl4ebmpgTQ/PNz585h5MiRiIqKQmxs9nsgWQqHAAWwcDjyKiRAArkTOHk5CcOWROPvY5dVhQZVSqodvtVL+zo8MgogBVBvkDukAMbHx2P58uW5shEBtPx8y5YtaN68OS5cuAARRS1l7ty5GDRoEBYsWIC3334bp06dQseOHTF//nwsWrQIo0ePRkJCAp599lnMmDFDyaezFQqgsz1xjpcEioZApiEL8/46gem/HsSN9EwU93DDkPbheK5xVbXb1xkKBZACqDfOrRJAWWB7IyP7hdlFWYq7F4eLvK9HQ8lN8MybWX5+/fp1vPPOO1i/fj0OHjwIV1dtC4VFAF966SW0bNkSU6dORWJiIrp3744GDRogICBACeCxY8fQo0cPJYWPP/64ht47VhUKoGM9T46GBGyBwNGL1zFkcRR2nryquvNASKB6h2+VUj620L0i6wMFkAKoN9isEsDk9GTc/939eu9pdfutT22Ft4e3pnYieJKV8/LyyqnfoUMHlZWTYvl5UlISypcvj5UrV+Lee+/VdA+pJALYp08fHDlyBNWrV1ft+vfvj2+//VZNMfv6Zk9BtG/fHlWrVsVnn32m+dqOUpEC6ChPkuMggbtPICPTgK+2HMeHaw8hLcMAH083DO9YC081Coark2T9zJ8CBZACqPdb6ZACeObMGcyZMyeHjY+Pj5I8kwCaf3716lXMnj0bv/zyC7Zt24YqVapoYioC+Nprr0EE0lQk67d48WLs27cv52e9e/dW2cGlS5dquq4jVaIAOtLT5FhI4O4ROHguEYMX70HU6QTVieZhQZjSIxIVA4rfvU7d5TtTACmAekPQKgF0xClgAZiZmQl/f3+1pm/ChAmamJrWAMp6QlMZM2aMWnu4e/funJ/lNyWt6WZ2WokCaKcPjt0mARshkJ5pwJxNR/HJhsNIz8xCCS93vNe5Nno1qKR5WZCNDKXQu0EBpADqDSqrBFDvzYqifX7CldvnBoNBCaCs6fvggw80dZMCmD8mCmD+jFiDBEggdwJ7zyRg8OIo7I+7piq0rVUGE7tFoKzfzeU9zsyOAkgB1Bv/TimA5sfAyBTwrFmz1JTxhg0b1KYOLYUCmD8lCmD+jFiDBEjgVgKpGZn4ZP0RzPn9KGS3b4C3B8Y+UgeP1Kvg9Fk/c1IUQAqg3j87nFIAzQ+CLlGiBGrWrImhQ4eqHbumIiIomzdE9HIrFMD8Q48CmD8j1iABErhJYFfsVbXD9/CF6+qHnSLKY8wjdVC6RDFisiBAAaQA6v1SOJwA6gViai+bQcaOHat2DbMUjAAFsGDc2IoEnI1ASnqm2t371R/HYMgCgnw9Mf7RuugQkb15j+W/BCiAFEC93wsKYC4EZRfvk08+qTZzaD0XUO+DcMT2FEBHfKocEwkULoHtJ66orN/xS9knKnStXwGju9RBSR/Pwr2Rg12NAmibAvgggMHyVhoA8s+XbgDMX0shc4q9LWLxVzkyzuxnsspVdiM8AUBy3/L5qwDOm9UJBPAJgC4ADACWABgIIDt3rq1QALVxYq0CEKAAFgAam5CAkxBISs1Qb/KY9/cJZGUBZf2KYWLXCLStXdZJCOgbJgXQNgWwA4CmAHYCkMPfchNAifA+Zo8/FUD2sebZRQ6x6yTnFgOQg49mGSVPrmsqq42C+TIADwDy8tvtAJ6yIqwogFbAYlXrCFAArePF2iTgLAT+OnIJQ5dG4dSV7DdLPX5fZYzoVAv+xeWvMhYtBCiAtimA5s8uKw8BDJBMdx4P2R/ARaPILTbWqQlgP4DGAP4BUAtADICGAHYY60gG8RcAlQCc1RJAACiAGkGxmvUEKIDWM2MLEnBkAokp6Zj0ywF8vy1WDVMOcp7cPQIP1tD2DnZHZmPt2CiA9iuAIn9pxqzfBgAjAVw2BkBrAOsBlARw85Rh4CSAmQBmAHjBOEUsdUzFHUAKgF4AluURTDKdbL6dqgSA0wkJCfDzExe8WfiXt7VfR9a3JMAYYkyQAAmYCGw8eAEjlkYjLkH+mgKeeSAYwzrUgm8x+auLxVoCFED7FEBZ15cM4DgAeYnsJOO6PcnuZRozfzKda7nvfRuAjQCGAhhhXEcYbhE0FwCMNk4h5xZPY4yf3/IZBdDarx7rayFAAdRCiXVIwLEJJCSnY9zKGCz597QaaHCgN6b2iETj6qUce+B3eHQUQPsUQMuwCAFwVA46N2b+ZA3fnRJAZgDv8JeSl2cWmTFAAiSQTeC3fefw7vK9uJiYChcXoE+Tanjn4Rrw9mTWT2+MUAAdQwAlDmTNn0wDfw7gTk4BW8Yc1wDq/RayfZ4EmAFkcJCAcxK4kpSG0T/vw4o92cvRQ0r7YHrPSDSoIodXsBQGAQqgYwigbNqQFbGyLvBnAKZNIE8aj3aRWJGp3gO5bAK5z7jbWOo8BGANN4EUxleL1ygMAhTAwqDIa5CA/RDIysrCqug4jP5pHy4npcHVBXjpweoY1DYMXh5u9jMQO+gpBdA2BdAXQKgxfnYBeMu4du8KAPkla/TkzL5zxjWA0wDIZowIAHIcjBQ5Bqaj8RgYeRO2nPcnpYlZXMoxMHKcTH+zY2BkRzCPgbGDL68zdJEC6AxPmWMkgWwCFxJT8N7yvfh1X/ZxteFlS2Baz0jUqyyHXrAUNgEKoG0KYEuj8Fk+73kAXjEeCn0PAPlWSH78NwDvWRzybDoIWrKA5gdBizSaiuTS5XxA84OgBzj7QdDy6rb4+HgsX37z7O1z585h4sSJWLVqFc6cOYMyZcqgfv36GDRoENq0aaN4ynt/T56UjdaAt7c3wsPDMXz4cPTqJZuqAXk7yKhRo7Bz505Vb8aMGao9S94EKICMDhJwfAKS9Vu26wzGrohBwo10uLu64NVWoXi9VSg83V0dH8BdGiEF0DYF8C6FQ4Fu63BrAC0F8MSJE2jatCkCAgIwbtw4REREID09Hb/++iu++OILHDggM+vZAti3b1/069cP8sX64IMP8OWXX2LLli1o0qQJtm/fjoULF6JBgwZ48803MXToUApgPiFHASzQd5KNSMBuCMQl3MC7y/ZiwwE5gAKoU8EP03vWQ+0Ktx4rZjcDsqOOUgApgHrD1eEFsGPHjoiKisLBgwfh4+NzCy/JFIoYmgRQMnqmrF5GRgb8/f0xYMAATJ48+ZZ2Iovmda15CCKcL774Inbs2IHq1atj1qxZaN26NZYtW4auXfM6G9yaO9hOXQqg7TwL9oQECpOAZP1+3H4KE1ftR2JqBjzdXDGwbRheejAEHm7M+hUm67yuRQGkAOqNM6sEUINyCgwAACAASURBVL70WTeyX91TlMWleHG4yBkCGop5BvDKlSsICgpS078ynXu7kpvUiRxKVlCygealoAKYmZmJOnXqIDg4GNOnT0diYiLefvttbNu2jQKo4dmyCgmQwN0ncOpKMoYvjcaWI5dUZ+pXDlA7fMPKylJ2lqIiQAGkAOqNNasE0JCcjIP3NtB7T6vbh/+7E67e3pramQugiNX999+PpUuXols3eSVz3sVc6tLS0pT0jRgxAitXrkSnTvJa5puloAK4Zs0adOnSBadOnUK5cuXUBdetW4d27dpRADU9XVYiARK4WwQMhiws2HoSU1YfQHJaJoq5u+Kdh8LxQrNqcJPtvixFSoACSAHUG3AOLYBbt27FAw88oFkA4+Li4OHhAZm69PX1VVlDWetnWQoqgB999BHk17Fjx3IuafoScwpYbyizPQmQwJ0icOJSEoYsicK243KQBdCoaiCm9oxEtaBbl9Xcqfvzuv8lQAGkAOr9XlglgI4+BfzMM89AMogif2XLls1z2pkCqC3suAZQGyfWIgFbJZBpyMI3fx7H+78dREq6Ad6ebhjaviaefaAKXJn1u6uPjQJIAdQbgFYJoN6bFUV7y13AHTp0QHR0tNWbQG7X14IKoGkK+PTp00owpaxfvx5t27blFHBRBAfvQQIkoJnAkQuJGLw4Crti41WbpqGlMKV7JCoHaluOo/lGrFggAhRACmCBAseskcMLoEy3yjEwgYGB6hiYyMhIyA7ftWvXYs6cOdi/f7/CkZ/UybrAmJgYVVd2Fj/99NPql2QLQ0NN537f/nGYNoHIvaZNm5azCUSmquXcwkcffVTv87Sp9swA2tTjYGdIQBOBjEwDPt98DB+tO4y0TAN8i7nj3U618ETDypo342m6ESvpIkABpADqCiAADi+AAkjW9slOYNnQIb8vXbq0EsHXX39dyZwWAZTzBKtVq/Yf3i1atMCmTZvUz+fOnYs+ffpApsrzKqZjYORcwZCQECWCjzzyCCQ7+PDDD+t9njbVngJoU4+DnSGBfAnsj7uGIYujEH0mQdVtGV4ak7pFoEJA8XzbskLREqAAUgD1RpzDCaBeIHrajx49Gr///nuOEGq51p9//olmzZrhyJEj6lxARyoUQEd6mhyLIxNIyzDg041H1K8MQxb8vNwxuksddL+3IrN+NvrgKYAUQL2hSQHUS9CsfaNGjdTBzvLfvIrs9pVp47CwMCV9AwcORMmSJdUbRxytUAAd7YlyPI5IIPp0AgYv3oMD5xLV8B6qXRYTutZFGT95IymLrRKgAFIA9cYmBVAvQSvbz58/HxMmTEBsbKw6pFo2gMiZg6VKlbLySrZfnQJo+8+IPXReAinpmfh4/WG13k92+wb6eGLsI3XQObI8s352EBYUQAqg3jClAOolyPZ5EqAAMjhIwDYJ7Dx5FUMW78HRi0mqgyJ9In+lfIvZZofZq/8QoABSAPV+LSiAegmyPQWQMUACdkLgRlqmOtPv6z+PQ/aqBfkWU9O97etmv5mIxX4IUAApgHqjlQKolyDbUwAZAyRgBwT+OXYZQ5dE4eTlZNVb2eAxqnNtBHh72kHv2UVLAhRACqDebwUFUC9BtqcAMgZIwIYJXE/NwLQ1BzD/75Oql+X8vDC5ewRa1Sxjw71m1/IjQAGkAOYXI/l9TgHMjxA/LzABrgEsMDo2JIFCIfDH4YsYtiQaZ+JvqOs92agyhnesBT8vj0K5Pi9y9whQACmAeqOPAqiXINszA8gYIAEbI3AtJR2TVu3HD9tPqZ5VKllcvcatWViQjfWU3SkoAQogBbCgsWNqRwHUS5DtKYCMARKwIQIbDpzHiKV7ce5aiupV78ZVMKR9TfgUc7ehXrIreglQACmAemOIAqiXINtTABkDJGADBOKT0zB2RQyW7TqjelO1lDem9ojE/SGOd8aoDeC+612gAFIA9Qahwwng888/j/j4eCxfvjxPNrt27cKkSZOwefNmJCQkoHLlymjZsiUGDx6MGjVqaGJqeu+vvL9X3uNrKnJvebPHxo0b1TWduXANoDM/fY69KAms2RuHkcv34dL1VLi6AH2bVcNb7cJR3NOtKLvBexUhAQogBVBvuDmdAK5cuRI9evSAiNuAAQPU+3cvXLiARYsW4dSpU/jxxx81MRUB7NevH7KysrB27Vq0atVKtaMA3sRHAdQUSqxEAgUmIMI3+ud9WBUVp64RWsYX03pG4t7gkgW+JhvaBwEKIAVQb6Q6lQAmJyejSpUqaNasGeSdvJZF5C0gIEATUxHAQYMG4bHHHsOePXuwdetWCqAFOQqgplBiJRKwmoD8w3NFVBzG/LwPV5LS4Obqgv4tQvBG6zB4eTDrZzVQO2xAAaQA6g1bqwRQ/tDJSDPovafV7d09XTW/m/J2U8Aifd27d8dff/2Fxo0bW90P8wYmAYyJiUFoaCjkHb89e/ZkBtAMEgVQV4ixMQnkSuDCtRS8u3wv1sacV5/XLFcC7/eqh7oV/UnMiQhQACmAesPdKgFMT83EFwN/13tPq9u/9FELeBTT9q/a2wngtGnTMHToUFy5ckWt09NTTAIoWcPhw4dj6dKl2LdvH65fv841gEawFEA9Eca2JHArAfkH+OKdpzF+ZQyupWTAw80Fr7cKwystq8PT3ZW4nIwABZACqDfknUoAp06dimHDhhW6AIoEhoSEYMqUKWpKmJtAssOSAqj368n2JJBN4Gz8DQxfGo3fD11U/x9R0R/Te0WiZjn5I5zFGQlQACmAeuPeKgHkFPBN3OYZQPnp9OnTMXPmTGzfvh0VK1bkLmAKoN7vJtuTgNpk9v22U5j0y37IK90k0zeobRheah4Cdzdm/Zw5RCiAFEC98W+VAOq9WVG0v90UcFJSEqpWrVqom0Ak+2fKdoWFheGpp56CTDXzGBhmAIsi3nkPxyUQezkZw5ZG4a+jl9Ug7w0OUDt8Q8uUcNxBc2SaCVAAKYCagyWPig4pgCdPnsSMGTNuGXKpUqXUeX8//fQTevXqhfbt26tjYGQDx6VLl7Bw4ULExsbihx9+0MTUMgMojb7++mu89tprauqTAkgB1BRIrEQCFgQMhizM//sEpq45iBvpmfDycMXgh2vi+SZV1W5fFhIQAhRACqDeb4JDCuC8efP+w6Vv37746quv1M937NiByZMn448//lBfIhFD2RUs6wNr166t6kimULKJY8aMyZVxbgKYmZmJyMhIyM5gCiAFUO+Xk+2dj8Cxi9cxdEkUtp+4qgZ/f7VA9TaPqkE+zgeDI74tAQogBVDvV8ThBFAvEGkv5wVKxnD16tVO/zYPPTy5CUQPPbZ1JgKZhix89ccxfLj2EFIzDPDxdMOwjrXwdKNguDLr50yhoHmsFEAKoOZgyaMiBTAXMKtWrcLs2bMh/2UpOAEKYMHZsaXzEDh0PhGDF0dhz6ns9cTNw4IwuXsEKpX0dh4IHKnVBCiAFECrg8aiAQVQL0G2z5MABZDBQQJ5E0jPNODz34/i4/VHkJZpQAkvd7zXqTZ63VdJ88H35Ou8BCiAFEC90U8B1EuQ7SmAjAESsJLAvrMJGLwoCjFx11TL1jXLYFK3CJTz97LySqzurAQogBRAvbFPAdRLkO0pgIwBEtBIIDUjE59uOILZm44iw5CFAG8PjOlSB4/Wr8Csn0aGrJZNgAJomwL4IIDBABoAKA+gG4DlxqD1ADABQEcAIQASAKwDMEwOezcL7E0AWlgE+ucA+pv9LBDAJwC6AJAX9C4BMBDAdSu+IBRAK2CxqnUEOAVsHS/WdmwCssZv8OI9OHQ++4/o9nXKYVzXOihTglk/x37yd2Z0FEDbFMAOAJoC2AlgqYUAytu6FwP4EsAeAPJC2o8AyItu77MQwEMARpn9LFmk3+z/VxsF82UAIpbfANgO4Ckrwo0CaAUsVrWOAAXQOl6s7ZgEUtIzMWPdIXy5+RgMWUApH0+Me7QuOkVKfoCFBApGgAJomwJo/jSzLAQwtyfdEMA2AFUAxBorSAZwN4BBeYRGLQAxAKTtDmOd9gB+AVDJIpt4u+iiABbsu8dWGghQADVAYhWHJrDjxBUMWRKFYxeT1Dhlqnd0lzoI9PF06HFzcHeeAAXQMQSwLYDfAASYZfhEAOsge3znAKwAMF6OqDOG1QsAPjBmEE2R5i6vXwXQC8CyPMKvGAD5ZSryTqHTCQkJ8PO79aXi/Mv7zn+BHf0OjCFHf8IcX14EktMyMP3Xg5j71wlkZQFlShTDxG4RaFe7LKGRQKEQoADavwDK4o8/ARwA8LRZVLwE4KQxkxcJYKoxS9jdWGcEgN4Awi0i6QKA0QDm5BFh8loL+fyWQgEslO8jL2JBgALIkHBGAn8dvYRhS6IReyX73+u9GlTCyE614e8tK3VYSKBwCFAA7VsA5U8D2bghU7YtLdb3WUZIKwAbAIQCOAqgoALIDGDhfPd4FQ0EKIAaILGKwxBITEnHlNUH8L+t2St5Kvh7YVL3CLQML+MwY+RAbIcABdB+BVDkb6FxJ3BrAJfzCSt5EaRsHZN1fr8CKOgUsOVtHG4NoLy/Nz4+HsuXmzZe3zpkecfvyZOSXAW8vb0RHh6O4cOHo1cvmTkH9u3bh1GjRmHnzp2q3owZMzBoUF5LMW3nDwNb7AkF0BafCvt0Jwj8fugihi+JwtkEWYUDPH1/MIZ1qIkSXsz63QnevCaPgZEYkDVytlxy2wRikr8wAJLZu6hhALKreAuAegCiAJg2gcjOYdltLOUhAGucfROIFgHs27cv+vXrp85R+uCDD/Dll19iy5YtaNKkCbZv346FCxeiQYMGePPNNzF06FAKoIYAza0KBbCA4NjMbggkJKdjwqoYLNp5WvW5cmBxTO0eiSahQXYzBnbUPgkwA2ibAuhrnKqVqNoF4C0AGwFcARBnPAbmXgCdAZw3Cz35PA1AdeNRLrKjVzKDsgZwhmzWsDgbUI6BkRXFcjag6RgY2RHs1MfAaBFAyeiZsnoZGRnw9/fHgAEDMHny5Fv+JJBsoXlda/6YcHFxwWeffYYVK1Zgw4YNqFKlCr7++muULl0aL774ohLNevXq4dtvv0X16vLIHa9QAB3vmXJENwmsizmPEcuicSExFS4uQO/GVTGkfTi8PWU/HgsJ3FkCFEDbFEBZzyfCZ1nmAZBNGMfzCAvJBsru38oAFgCoC0Cmfk8Zd/XKAdLm5wDKQdCzLA6CHnAnD4LOyspCRmrqnY3qXK7uXqyY5lPyrRVAuV1AQAAkKyjZQPOiVwArVqyIDz/8EPXr11eZxN27dyMkJARDhgxBcHAwXnjhBXXv1avF5R2vUAAd75lyRMCVpDSMXbEPP+3OPrs/JMgHU3tGomFV+SOZhQSKhgAF0DYFsGiefuHcxao1gOkpKfi4d8/CubMVVxkwbzE8vLSdlm+NAKalpSnpGzFiBFauXIlOnToVqgCOHDkS48fL6T3AP//8g8aNG+P//u//lPhJ+eGHH9CnTx/cuHHDChr2U5UCaD/Pij3VRuCX6DiM+mkvLl1Pg6sL0O/BELzZtga8POQsfxYSKDoCFEAKoN5oc0oBjIuLg4eHB0RQfH191SYQydBZFr0ZQFlLaNpccvz4cZX927ZtGxo2lPO7gY0bN6J169bI7RgevQ/WFtpTAG3hKbAPhUHgYmKqEr/Ve+VYVqBGWV9M61kP9SvL8a0sJFD0BCiAFEC9UWeVADrKFPAzzzwDyRSK/JUtWzbP6WW9Arhs2TJ07dpVPaMTJ06gWrVq2LVrl5oSlrJp0ya0atUKV69eVVPBjlYogI72RJ1vPPJnnkz1jlmxD/HJ6XBzdcGrLavj9dahKObOrJ/zRYTtjJgCSAHUG41WCaDemxVFe2umgPPrDwUwP0K3/5wCqI8fW99dAucSUjByeTTW7Zfz9YHa5f0wrWck6laUV7qzkMDdJUABpADqjUCHFEDT+X3mcEqVKoXKlSsjP6mTdYExMfKaZaBjx454+umn1S/JFoaGyjnc2orsAmYGMAUy9S2ZTy+Nazi10WUtErhzBCTrt2jHaYxfFYPElAx4uLlgYJswvNyiOjzcXO/cjXllErCCAAWQAmhFuORa1SEFcN482XB9a5Fdvl999VW+AmiaqrVs36JFCzVlK2Xu3Llq84b8RZFXoQBCrbGkAOr9irJ9URI4fTUZw5dG44/Dl9Rt61Xyx/Re9VCjrLw2nYUEbIcABZACqDcaHU4A9QLR0n706NH4/fffc4RQSxtnrEMBdManbp9jNhiy8L9tsZjyy34kpWXC090Vb7ergb7NqsGdWT/7fKgO3msKIAVQb4hTAAtAsFGjRpg1axbkvyx5E6AAMjrsgcDJy0kYuiQK/xyTs/iB+6qUVOf6VS8tZ/qzkIBtEqAAUgD1RiYFUC9Bts+TAAWQwWHLBDINWZj71wlM//UAUtINKO7hpt7kIW/0cJVD/lhIwIYJUAApgHrDkwKolyDbUwAZA3ZH4MiF6yrrt/PkVdX3xiGlMLVHJIJLedvdWNhh5yRAAaQA6o18CqBegmxPAWQM2A2BjEwDvvzjOGasO4S0DAN8i7ljeMeaeLJhMLN+dvMU2VEhQAGkAOr9JlAA9RJkewogY8AuCBw4dw1DFkch6nSC6u+DNUpjcvcIVAwobhf9ZydJwJwABZACqPcbQQHUS5DtKYCMAZsmkJ5pwOyNRzFr42GkZ2bBz8sd73WujZ4NKuX5FiCbHhA7RwLMAKoY4EpdfV8FCqA+fmx9GwLcBMLwuNsE9p5JwODFUdgfd011pW2tspjYrS7K+nnd7a7x/iSgiwAzgBRAXQEEgAKolyDbMwPIGLA5AqkZmfh4/WF89vsxyG7fkt4eGPNIHTxSrwKzfjb3tNihghCgAFIACxI35m0ogHoJsj0FkDFgUwR2xV5VWT/Z6SulU0R5jH20DoJ8i9lUP9kZEtBDgAJIAdQTP9KWAqiXoB20l1fYtWrVClevXkVAQECR9ZhTwEWGmjcCkJKeiQ9+O4j/23IchiwgyNcT4x+tiw4R5cmHBByOAAWQAqg3qB1OAJ9//nmY3gXs4eGB4OBgPPfccxgxYgTc3d3V69tEhkylTJkyaNasGaZPn47Y2NhbPssN7saNG9WPza9hqhcXF4dy5crlNJs5cybmzJmjrhsUFISePXti8uTJ8PLKXn80ZswYjB079pbbhIeH48CBAzk/u379OoYNG4bly5fj8uXLqFatGgYMGID+/ftrfvZaBFDeXWwqfn5+qFu3LsaPH4/WrVtrvo9lRQpggdGxoZUEth2/os71O34pSbXsfk9FtdGjpI+nlVdidRKwDwIUQAqg3kh1SAE8f/48vvnmG6SmpmL16tV47bXXMHHiRCVSJhk6ePAgSpQogcOHD+Oll16Cm5sb/v33X5UlM5WBAweqs5bkWqYSGBiIv/76SwmgXENkyVwmXV1d1f9+9913eOGFF/D111+jSZMmOHToEPr06YPHH38cH374YY4ALl68GOvWrcu5hkiqyKKpSN82bNiAr776ClWrVsXatWvxyiuvYOnSpXjkkUc0PX+tAijjbN++PS5duoR3331X3Wvv3r0ICQnRdB8KYIEwsZEOAkmpGZi25gDm/X1SXaWsXzFM6haBNrXK6rgqm5KA7ROgAFIA9UapQwpgfHy8ypiZysMPP6xE7u+//84RQPPp0O+//x5PPfWUyrxJBs5UJJtoeS35TItQvf7669i/fz/Wr1+fc723334bW7duxZYtW3IEUPq5e/fuPJ+jZOJEGt97772cOg0aNECHDh0wYcIETc/fsr/Jycno0aOHYrJq1So1LSwZwGXLlqFr167qmpLNrFChAj777DO8/PLLWLNmjbqfCKHIcuPGjfHRRx+hevXqefaBGUBNj4eVCkjgzyOXVNbv9NUb6gqP31cZIzrVgn9xjwJekc1IwH4IUAApgHqj1SoBzMrKQla6Qe89rW7v4uGqeedebtL26KOP4vTp09i5c2eu8ibi0717d0RFRSEiIkKzAFapUkVlGUXSZDq3adOmOW0lA/jqq6/it99+Q6NGjXDs2DF06tQJzz77rJqOliJtZOrZ399fTQuLVMkUsUxbm4pkAHft2qWEVoRMZE4yfyJuDz74oCaW5gIoDaQfvr6+Svi8vbNffWUpgCLIku38+OOP8cYbb2DJkiWqTmRkJGRaetSoUThx4oSSV1PW07IzFEBNj4eVrCRwLSUdk385gO+3xaqWcpDzlB4RaB5W2sorsToJ2C8BCiAFUG/0WiWAhrRMnB31l957Wt2+wrgmcPV009TOXABFWCUD17lzZyUxIluW2TDJdMnavJMnTypJ8/S8uWYorwygTP3Kde677z4lgDI9++2336rs3r333pvTT5Gnd955B9KPjIwMtW5P1gSaikxPi0xJ1lH6IesBz5w5o7JsMj0tRa4vEjh//ny1hlFk68svv1TrGrUW05glIynZxLCwMDVFbT5WcwGUDOHgwYPx+eefq2lxkT7LItPEpUuXRnR0tBLg3AoFUOsTYj2tBDYevIARS6MRl5Cimjz7QBUM7VBTvdKNhQSciQAFkAKoN94dUgAXLFigMmrp6ekwGAxqenf27Nnw8fHJEUD5vYiZyE69evWU7Nx///238MxLAHOD3qJFC5W5ExGUItL1xBNPqGlTue6RI0cgawr79et3y3Su+bVkulmyirJGsG/fvuqj999/Xwmf/Fc+27x5M4YPH66yd23bttX0/E0CWKlSJZWNXLhwoZrGNS8igMJMfn7jxg0ld1OnTkXv3r1VNVkrKVk/kVyRP+GalJSkMpEdO3akAGp6EqxUUALxyWkYtzIGS/89oy5RpZQ3pvaIxAMhpQp6SbYjAbsmQAGkAOoNYKsE0F6mgCWLJpk2yXDJtKlkzkzFJEOS2ZINHLIL2JRts4RpjQBKxkzW9sk6QynNmzdX4ifiZioippLNk6xfXtOmDRs2VGInU8EiYjI9LBs+JItpKi+++KKa0pZ1eVqKacyylk+mcmVTiflUt1xDBFCYyb3lniKA5qVmzZpKQIcMGaKYigBK5s983aBlX5gB1PJ0WCc/Ar/uO4eRy/fiYmIqZLP6C02r4Z2HwlFc46xAftfn5yRgjwQogBRAvXFrlQDqvVlRtM9P2rRs4DD1M79rmY+nXbt2SiRF1qTIRg352ZQpU3KqyWYTyewlJib+JwMnlUQMK1eurKaC5agX0xdcpopld66piMgdP35crS/UUszHLBlJmU6Wn9WuXTunueUaQPPryvEzsjNZso8itlJEduX3FEAtT4B1CkLg8vVUjFkRgxV7zqrm1Uv7YFrPemhQpWRBLsc2JOBQBCiAFEC9AU0BvA3BvARQzveT8/jq1KkDyXLJGsBPPvlECVmbNm3UFWWDh0zlfvHFFzlTwHJ8i4jhjz/+qOrI+sAuXbqozNrZs2cxevRotakiJiYmJwPXsmVLNeU6a9YsVe/3339Xx8DIteW/Woql9L755psQGZWfS2ZPyu0EULJ9kimVncfSRznXUI7U2b59OwVQywNgHasIyEzDyqg4jP55H64kpcHN1QUvPRiCgW3C4OWhbS2wVTdkZRKwQwIUQAqg3rClABZAAKdNm6bETqaaZRetbJKQ9XHmh0PLpg85e1DWBEo9mVIV2ZOfmd7GIWsEJasmGTb5XA6kls/Nj1Y5d+6cWvMncnnlyhUlgTKNLBJnOrxZRFV25IrQ5VZyy3pKhlHOIJTPatSocVsBlGvKWYXSRjbKyKYV2eAicsoMoN6vINubE7iQmIL3lu/Fr/vOqx/XLFcC03pGIrJS0b3Bhk+EBOyBAAWQAqg3Th1OAPUCscf2sgFF5FOyjrZUuAbQlp6GbfdFsn6ywUM2eiTcSIe7qwteaxWqfnm6Zx+uzkICJHCTAAWQAqj3+0AB1EvwLrdPSEhQU9FyiLWc7WdLhQJoS0/DdvsSl3BDHe2y8eBF1cm6Ff0wrUc91K5w8y07ttt79owE7g4BCiAFUG/kUQD1EmT7PAlQABkctyMgWb8ftp/CpFX7kZiaAU83VwxsG4aXHwyBuxuzfoweErgdAQogBVDvN4QCqJcg21MAGQNWEzh1JRnDlkbhzyOXVdt7ggMwvWckQstkH4DOQgIkcHsCFEAKoN7vCAVQL0G2pwAyBjQTMBiysGDrSUxZfQDJaZko5u6KwQ+Ho0/Tamq3LwsJkIA2AhRACqC2SMm7FgVQL0G2pwAyBjQROH4pCUMXR2HbiSuqfqNqgeptHtWCfDS1ZyUSIIGbBCiAFEC93wcKoF6CbE8BZAzclkCmIQtfbzmO9387iNQMA7w93TCsQ008c38VuDLrx+ghgQIRoABSAAsUOGaNKIB6CbI9BZAxkCeBw+cTMXhxFHafild1moUGYXL3CFQO9CY1EiABHQQogLYpgA8CGCxvAwNQHkA3AMvNnrMsdBkLoB8AOd30TwDySofDZnW8AHwA4AkAxQD8CuBVANmno2aXQACfAOgCwABgCYCB8kYxK2KKAmgFLFa1jgB3AVvHy5Fqp2ca8MXmY/ho3WGkZRpQopg73u1UC483rJxzgLkjjZdjIYGiJkABtE0B7ACgKYCdAOTFsJYCOBTAcAC9ARwHMB5ABAB5MWuKMYjmAOgE4HkACQBmGSVPrmsqq42C+TIADwDfANgO4CkrApECaAUsVrWOAAXQOl6OUjvm7DUMWbIHe89cU0NqFV4ak7pHoLx/cUcZIsdBAnedAAXQNgXQPDCyLARQsn/yZnPJ7r1vrOhvzOyJ7P0AQP5fTkQVkVtsrCMvbN0PoDGAfwDUAhADoCGAHcY67QH8AqCS8R5aApQCqIWSndfJ7VVwRTEkCmBRULade6RlGPDpxiPqV4YhC/7FPTC6S210u6cis36285jYEwchQAG0PwEMAXBUjr0CsNssDn83/r9M4bYGsB5ASQDZC2eyy0kAMwHMm8S6jgAAIABJREFUAPCCUSKljqm4GzOIvQAs0xjjSgDPnNkJP79b3yKRmpqJc+fSUbVqFXh5ySy0fZQXXuiH+fMXqM56eHggOLgynnnmaQwfPgTu7u7YtGkz2rZ9OGcwZcqUQdOmjTF16mTExp665bPcRrxunczGI9d6p08fR7ly5XKaffTRJ/j88y/VdYOCSqF7926YNGk8vLxkhh8YO3YCxo+feMttwsNrYN++PTk/O3/+PIYPH4m1a9chPj4BzZs3w0cffYiwsFDND8Q05kuX4nLeQ2zZ2N39ZnbGz88PderUxtixo9G6dUvN97GsmJKSihMnTqJcOQ8UK+ZW4Ouwoe0TOHz+utrkITt9pTSpXgoD2oQh0MfT9jvPHpKAHRK4du06KlaUlWYqaZSdbneyYusHR1lmAJsY1/xVABBn9qwWApC6jxszfzKda2ld2wBsBCBTyCOMU8jhFs/7AoDRAGQKObci1zS/rpy6evqnn6vCx+fWk/ddXSsgwH80KlcuA09PW8d8c6ivvDISFy5cxuzZ45Gamoa1a7fgnXcm4b333sBbb/XFH39sR+fOfbFz58/w9fXB0aMnMXDgOLi5uWHz5h8RH3/zezR06FQkJl5X1zKVkiX9sXXr7pxrlChxU5xLlw6Eq2s2x0WLVuG110bj00/HolGj+jhy5CRee20Uund/GJMmyRJRYPLk2fjpp7X46acvc67v7u6GUqWyvV7elNCu3bPw8HDHhAnvwM/PB7NmfYv16//E1q3L4OOjbSG9acwnT25BQEDur9fy949U42zbtikuX76K8eM/wcaN/+Dvv5eiWjVJKltf0tKycOrUBcQnjIXBIIlvFhIgARIggcIgkJRkwKOPnJBLUQALA+gduIatCeAYoyDeMtRfVt8DH59bMzQuLmXh6/MWgoNFAO3ntUz9+49AQkIivv9e9sdkl65d+yExMQnr13+HP/7Yhk6d+iA29u8cGRJZ69t3CHbuXImwsGo57XK7lnyY2zUsY+fttyfg0KFjWLHi65yPRoyYhh07ovDbb9kZykmTPsWqVevx55+yVPS/5fDhE2jQoBO2bv0JtWplZ/wMBgNCQ1tg9OiB6N27p6aQtexvcvINPPPMICW3ixbNURz8/Orgu+8+RufObdQ1z527iBo1WmLmzNF44YXHsHbtH5g+/XPs339ESa5I7dSpwxASEpxnH9LSDIiNvYDrSR8iK8t8/5KmbrOSjRPIyMzC9dQMZGbJH3NQhzr7eLrDxX7+vWjjhNk9EsibQFJSJjp22CUVKIA2GiiWAni3p4BzzQAmJCRApv3MS27rtyQjlZ6eXuSoZSrXRePfKs8//zzi4+OxfPnNjdePPvooTp8+jZ07dyK39XDLli1D9+7dERUVhYgI2Y+TXXK7lvzcdI0qVaogNTUVdevWxZgxY9C06c09Ot999x1effVV/Pbbb2jUqBGOHTuGTp064dlnn8WIEZLAhWozffp0+Pv7q2nhxo0bY/LkyQgOzpaq6OhoREZG4siRI6hevXpOvypXrow2bdpg7ty5mp6F+ZilgfTD19cXMm5v7+wsovCV/+/atav6/6tXryIwMBAff/wx3njjDSxZskTVkf5cv34do0aNwokTJ7B79+6crKdlZ7gGUNPjsbtKN9Iy1XTv138eh7hf6RLFMKFrXTxc5+byB7sbFDtMAnZGgGsA7W8NoGkTiGwAkY0gUsS8ZOrWchPIk8ajXaSOTPUeyGUTyH3G3cZS5yEAa+7kJpC0tDRMmjSpyL8mIkyentrWEplLmwjr+vXr0blzZyUxIluWAhgXF4eePXvi5MmTStLM75OXAB48eFBd57777lMC+NVXX+Hbb7/F1q1bce+99+bwEXl655131FRuRkYG+vfvjzlzbs7Or169WslUeHg4pB9jx47FmTNnsHfvXpQoUULJdmhoKO6//358/vnn8PHxwYwZMzBs2DA89NBD+PXX7PWI+RXTmPfv34/HH38cYWFhEEE1H6u5ACYnJ2Pw4MHqnv/++6+SPsty6dIllC5dWkmqCHBuhQKY35Oxv8//PnpZvcP35OVk1fke91bCe51rIcBb2/fT/kbMHpOAbRKgANqmAMqiMNMKfcnPvmVcuyfvP4o1ruEbZnEMjPwNa3kMTEejFMqiNNN8pqwhNBU5BqYsgP5mx8DIjuA7dgyMvQjgggULVEZNBEqmTJ966inMnj1bCZRJhuT3ImYiO/Xq1VOyI6JlXvISwNz+OGjRooXK3IkISpH7PPHEE5gwYYK6rmTxBg4ciH79+uG9997L9U8UyVxKVvHDDz9E3759VR3JWsrv9+zZo9Yptm3bVmXcpO8ikFqKacyVKlVS2ciFCxeqa5kXEUBhJj+/ceOGkrupU6eid285rQg4fPiwyvqJ5Ir8CdekpCSsWrUKHTtKqP63UAC1PB37qCNTvVNXH8C3/8heNKC8v5c62qVVeBn7GAB7SQIORoACaJsCKNsmZbOGZZlnFDrTQdAvGQ+C3mI85PmQWQPTQdCSBTQ/CPqcWR05CFrOBzQ/CHrAnTwI2l6mgCWLJpk2yXBVqFBB7f41FZMMSWZLpr1lF7Bk23Ir1gigZMy2bNmCv//+W12qefPmSvzef9902g8gYvrSSy+prJ9ps4jlfRs2bKgkT6aCzYtM04uAi5jJdSX7+Omnn2r6I8005pdffllN5W7YsOGWqW65iAigMJN7y5S03Me81KxZU8npkCFDFFMRQMn8mU8bW3aGAqjp8dh8pc2HLmL40micib+h+vpko2AM71gTfl5y/CgLCZDA3SBAAbRNAbwbsVDQezrcOYD5SZs1Z+Lldy1z6O3atVMiuXRp9oaOBg0aQH42ZcqUnGrff/+9yuYlJib+JwMnlUQMZX2fTAUPGCAu/98imTiRMcn+yTSwlmI+ZslIzp8/X2Uoa9eWpHN2sVwDaH7dy5cvIygoCJs3b1ZiK0VkV35PAdTyBOyzTsKNdExatR8/7jilBlCpZHFM7RGJpqFB9jkg9poEHIgABZACqDecKYC3IZiXAM6cORPVqlVDnTp1IFkuWQP4ySefqA0fsjlDimzwkKncL774ImcK+JVXXlFi+OOPP6o6sj6wS5cuKrN29uxZjB49Wm2qiImJycnALVq0SP1eppdlvZ1MI8s1JJOntVhK75tvvgmRUfm5yGR+AijZPsmUdujQQfUxNjZWrUPcvn07BVDrQ7Czeuv3n8e7y/bi3LXslxM936QqBj8cDp9iN7PpdjYkdpcEHIoABZACqDegKYAFEMBp06YpsZOpZtlFK5skZH1cq1atcq4mmz4mTpyo1gRKPZE4kT35WUCAvAIaao2gZNUkwyafN2vWTH1uvuNXNpLI5hU5ELp8+fJ47rnn1BpCy80qsiNXhC63klvWUzKMixcvVm1q1Khx2wygXHPdunUqKykbZWTTivSrZcuWFEC930Aba381KQ3jVsZg2a4zqmfVgnxU1q9RNVlxwkICJGArBCiAFEC9sehwAqgXiD22lw0oIp+SdbSlwjWAtvQ08u/Lmr1xGLl8Hy5dT4WrC/Bi8xC82bYGinvyLS7502MNEihaAhRACqDeiKMA6iV4l9vL5hCZij5w4IA628+WCgXQlp5G3n0R4Rv90z6sis5+OVFYGV9M6xmJe4LN3zRpH2NhL0nAWQhQACmAemOdAqiXINvnSYACaNvBIbv6f95zFmN+3oeryelwc3XBKy2q4402oSjmzqyfbT899s7ZCVAAKYB6vwMUQL0E2Z4CaIcxcP5aitrksW5/9iv6apX3w/SekahbUd4qxUICJGDrBCiAFEC9MUoB1EuQ7SmAdhQDkvVbvPM0xq+MwbWUDHi4ueCN1mHo36I6PN3t553fdoScXSWBO0KAAkgB1BtYFEC9BNmeAmgnMSAHOcuBznKws5TISv5qrV/Ncre+B9xOhsNukoBTE6AAUgD1fgEogHoJsj0F0MZjwGDIwvfbYzH5lwOQV7pJpu+tdjXwYrNqcHdj1s/GHx+7RwK5EqAAUgD1fjUogHoJsj0F0IZjIPZyMoYuicLfxy6rXt4bHIBpPeshtIxt7Ri3YYTsGgnYJAEKIAVQb2BSAPUSZHsKoA3GgGT95v19AtPWHMSN9Ex4ebhi8MM11Rs9ZLcvCwmQgH0ToABSAPVGMAVQL0G2pwDaWAwcu3gdQxZHYcfJq6pnD4QEqrd5VCnlY2M9ZXdIgAQKSoACSAEsaOyY2lEA9RJkewqgjcRARqYB/7flOD5cewipGQb4eLpheMdaeKpRMFyZ9bORp8RukEDhEKAAUgD1RhIFUC9BtqcA2kAMHDqfiMGL9mDP6QTVm+ZhQZjcPQKVSnrbQO/YBRIggcImQAGkAOqNKYcXwLS0NHh6eurlVKjtbbFPhTpA48X4JpA7QfXWa6ZnGvDZpqP4eMNhpGdmoYSXO97rXBu9GlSCiwvX+t35J8A7kMDdIUABpADqjTyHE8CWLVuibt26cHd3x4IFCxAREYGNGzeqvwxnz56Nn3/+GZs2bUL58uUxbdo09OzZUzE8ceIEqlWrhh9//BGffPIJduzYoa7zv//9D/K+3VdeeUW9b7d58+aYP38+SpcurZl91apV0bdvXxw+fBjLly9H9+7dMWbMGHW/77//Hh9//DH+/fdfhIaG4tNPP0WLFi3UtaWfrVq1wpo1azBs2DB1/8aNG+OHH37Azp078dZbb+HMmTPo3LkzvvrqK3h721a2hwKoOUQKVHHf2QQMXhSFmLhrqn2bmmUwsVsEyvl7Feh6bEQCJGA/BCiAFEC90WqVAMpbBAyGG3rvaXV7V9fimrMZIoAiRyJsIl1SwsPDVftSpUphypQpePDBB/Htt99i8uTJiI6ORq1atXIEsGbNmpg5cyaCg4PxwgsvID09HSVKlMCECROUYD322GNo27Yt5syZo3kcIoBXr17FqFGj0LVrV9XOzc1NCWClSpXU/WrXro0PP/xQCejx48dVX00C+MADD+D999/PuX/FihVRrFgxNZbr16+jW7duGDx4MIYOHaq5T0VRkQJ4ZyinZmRi1oYjmLPpKDIMWQjw9sCYLnXwaP0Kmr8nd6ZnvCoJkEBREaAAUgD1xppVApiZmYxNv0fovafV7Vu2iIabm7bslgigfDEko2ZeRAD79+9/i7iJWN17770qM2jKAEomzSSOkml78sknsX79erRu3VpdTqRr7ty5KhuntYgA3nPPPVi2bFlOE9P95HomccvIyFBS+MYbb2DIkCE5Arhu3Tq0adMm5/7Dhw/H0aNHERISon4m45LrSabQlgoFsPCfxu5T8RiyeA8Onb+uLt6hbjmMe7QuSpcoVvg34xVJgARslgAFkAKoNzgdUgDDwsLw5Zdf/kcA582bh+eeey7n52+++SZ2796tpohNQrZt2zY0bNhQ1ZGfi/hduHAhZ8r3m2++wdtvv40rV65oZi8C2K9fP7z77rv/EcDff/9dZSRNRbJ5AQEBkPuYMoCW93/99deRlJSU02b06NFYsWLFf6RXcwfvUEUKYOGBTUnPxIy1h/DlH8dgyAKCfD2V+HWMKF94N+GVSIAE7IYABZACqDdYrRJAe5kCrl+/vppWNS+SAdQigLt27YK0l2ISMJm+FSmTItm/QYMGIT4+XjN7EUBpI79MxSScWgQwv/vLekJZWygya0uFAlg4T2PHiSvqXL9jl7Klv2v9ChjVpQ4CfWxrc1PhjJZXIQES0EKAAkgB1BInt6tjlQDqvVlRtJcp4LwEUNYFynSvqciGCpmaNZ8CLmoBnDp1qprulSJTwDKtKxk+8ylgCmBRRI7t3SM5LUO9yUPe6JGVBZQpUUxt8mhXu6ztdZY9IgESKFICFEAKoN6AcyoBDAoKgghXs2bN1O5e2dghm0BkA4YpI1fUAiibTSRbKRtRZsyYge+++05tApG+as1AMgOo92tge+3/OnpJvcP31JXsTVeP3VcJ73aqDf/iHrbXWfaIBEigyAlQACmAeoPOqQRQjliRqdLNmzerY2BEBmVXr5SCCqBJ0kTaZKo3t3K7KWARPhFAmb6VY2BmzZqljn6RQgHUG9721z4xJR1TVh/A/7bGqs5XDCiuDnR+sIb2Y4fsb9TsMQmQgLUEKIAUQGtjxrK+wwlgXkBkDaDswjUdw6IXnKm9bNaYNGkSYmJi4OGhPTuTm3AWVp9s5TpcA2jdk9h08AJGLI3G2YQU1fCZB4IxtH1NlPDSHlfW3ZG1SYAE7JUABZACqDd2KYA6Cfbq1UtlEeW/1hQKoDW0HLtuQnI6xq+KweKdp9VAgwO9MaVHBJpUD3LsgXN0JEACBSZAAaQAFjh4jA0pgHoJFrA9BbCA4Bys2dqY83h3WTQuJKZC3tzWp0k1vPNwDXh7ujvYSDkcEiCBwiRAAaQA6o0npxFAvaDY3noCnALOm9mVpDSMXbEPP+0+qyqFBPlgWs9I3Fc10HrQbEECJOB0BCiAFEC9QU8B1EuQ7fMkQAHMHc2qqDiM+mkvLielwdUF6PdgCN5sWwNeHm6MJhIgARLQRIACSAHUFCi3qZSvAMoO1uLFi+u9D9s7IYEbN27k7K728vJyQgK3DvliYqoSv9V7z6kPapT1xfSe9VCvcvYh4ywkQAIkoJUABZACqDVW8qqXpwBmZmbi0KFDKFOmDEqVKqX3PmzvhAQuX76sXqNXo0YNuLk5b3ZL3qCzfPcZjF0Rg/jkdLi7uuDVVqF4rVV1FHN3Xi5O+JXgkEmg0AhQACmAeoMpTwGUC8fFxalXnokEent7Q45SYSGB/AiI8CQnJyv5k1foyZmLzlrOJaSoTR7rD1xQCOpU8FNr/epU8HdWJBw3CZBAIRCgAFIA9YbRbQVQ/iI/d+6cVe+91dshtnccAiJ/5cqVc8p/OMh3Z+GOU5iwcj8SUzPg6eaKAW1C8XKL6vBwc3Wch8yRkAAJ3BUCFEAKoN7Au60Ami4u08Hp6el678X2TkRADsV21mnf01eTMXxpNP44fEk9cVnjN71nJGqULeFEEcChkgAJ3EkCFEAKoN740iSAem/C9iTgDAQMhiz8b+tJ9Sq3pLRMFHN3xdsP1UDfZiFwk+2+LCRAAiRQSAQogPYrgCcAVMklDmYDeA3AXAC9LT7/FUB7s5/JtsoPADwBoBgA+fxVAOetiC8KoBWwWJUE8iJw4lIShi6JwtbjV1SVhlVLYmqPSISU9iU0EiABEih0AhRA+xVAebO7+fa/ugDWAmgFYJNRAMsC6GMWNakArpr9/xwAnQA8DyABwCwABgBNrYg0CqAVsFiVBCwJZBqy8M2fx/H+bweRkm5AcQ83DG0fjucaV4Urs34MGBIggTtEgAJovwJoGRIzAXQGEAYgyyiAcjhY1zxiR7YQXgTwFIDFxjo1AewH0BjAPxpjjgKoERSrkYAlgSMXrmPI4j34NzZefdSkeilM6R6J4FLehEUCJEACd5QABdAxBNATgLwP6kMAk4wRI1PAIn9pxqzfBgAjAVw2ft4awHoAJQFk/+2TXU4CEJmcoTHyKIAaQbEaCZgIZGQa8MUfxzBz3WGkZRjgW8wdIzrWwpONKjvljmdGBgmQQNEToAA6hgA+BuA7AMFGEZRIknV9yQCOA6huFMPrxuxepjHz941x7Z955G0DsBHA0DzCUdYKyi9TkW2JpxMSEuDnJy7IQgIkcDsC++OuYcjiKESfkVUXQIsapTG5ewQqBPBtOYwcEiCBoiNAAXQMAZTNG5Lp63Kb0AkBcBRAW2PmT6Z+CyKAYwCMtrwPBbDovrS8k30SSEnPxKRf9uN/W2Mh6/78vNwxqksd9Li3IrN+9vlI2WsSsGsCFED7F0DZCXwMQHcAP+UTjbLmT6aBPwdQ0ClgZgDt+ivPzt8NAntOxasdvgfOJarbt69TDuMerYMyfny/8d14HrwnCZAAQAG0fwGUjNzLACoDyLhNUFcCEGtcF/gzANMmkCcBLDG2CwdwgJtA+EcDCRQOgaTUDHWm34KtJ5GVBQT6eGJY+5p4rKF8XVlIgARI4O4RoADatwDK+6Bkjd/3AIaZhZEcHCbTtCJ254xrAKcBkPV6EQDkOBgpcgxMR+MxMNcAfGL8eRMrQpKbQKyAxarOQ+DPI5dU1u/01Rtq0N3uqYiRnWqhlK/5Elrn4cGRkgAJ2BYBCqB9C+BDxsObJXN3yCy0ZDX5cgD3AJCjYGSH8G8A3rM45Nl0ELRkAc0PghZp1FoogFpJsZ5TELiemqHW+n23VRLuQMWA4pjWMxJNQ4OcYvwcJAmQgH0QoADatwDaQpRRAG3hKbAPNkFgy+HsrN+Z+Oys37MPVMHQDjXVMS8sJEACJGBLBCiAFEC98UgB1EuQ7e2eQGJKOib9cgDfb8vO+lUOLK5e49akOrN+dv9wOQAScFACFEAKoN7QpgDqJcj2dk1g86GLGLYkCmcTUtQ4ejeugiHta8KHWT+7fq7sPAk4OgEKIAVQb4xTAPUSZHu7JHBNsn6r9uOH7adU/4MDvVXWr3H1Uv/f3nnAyXFV6f7r3NOTR6PRSBrlaGkkOeEgZ4MtY2NsbBF33wIPdllYzO7ykCM4rgO2CbvwYJddFtgED+SAsY0xNtjGtpxkWznnOJJmpMmdqvr9zu2qmZp2j6an74Sunu/qN+ru6jq37v3fU9VfnRvKlfVhoUmABMYWAQpACkBdj6cA1CVIe9cR+MPmJtz66HocbktH/T6zdDpuvGIeIkGO9XNdY7LAJDBGCVAAUgDquj4FoC5B2ruGwImuOO7+zUY8+s4BVebp49JRv7NnMurnmkZkQUmABBQBCkAKQN1TgQJQlyDtXUHgmfWH8fXH1+NYRwxeD/C582fgq5fNQ0nQ54rys5AkQAIk4CRAAUgBqHtGUADqEqR9QRMQwXfHExvw1NpDqpyz68rUun6nT60u6HKzcCRAAiRwMgIUgBSAumcIBaAuQdoXJIFUKoUn1hzEnU9swPGuBHxeD/76opm44dI5CAcY9SvIRmOhSIAEciZAAUgBmLOz9LMjBaAuQdoXHIGmtqjq7v39xiZVtvn15Xj4o0vQOFkeoc1EAiRAAu4nQAFIAajrxRSAugRpXzAEJOq3cvV+3PPkRrRFkwj4PPjyJXPwxYtnIeiXR28zkQAJkEBxEKAApADU9WQKQF2CtC8IAvL4tlseXQdZ2FnS4oZKNdZvfr24OBMJkAAJFBcBCkAKQF2PpgDUJUj7USVgmin8/M29uP/pzeiIJVWk76uXzcXnz58Bv49Rv1FtHB6cBEhg2AhQAFIA6joXBaAuQdqPGoG9zV246ZG1WLWzWZXh9KlVeHD5EjXTl4kESIAEipkABSAFoK5/UwDqEqT9iBOQqN/PVu3Gg89sQXfCQDjgxYpl89UTPWS2LxMJkAAJFDsBCkAKQF0fpwDUJUj7ESWw82gHbly5Fm/tOa6Oe/aMGjXWb9q40hEtBw9GAiRAAqNJgAKQAlDX/ygAdQnSfkQIGGYKP355J7717FbEkiYiQR9u+eB8/NnZ0+Bl1G9E2oAHIQESKBwCFIAUgLreSAGoS5D2w05gW1M7vrZyLdbsO6GOdcGcWtz3kUWYUhMZ9mPzACRAAiRQiAQoACkAdf2SAlCXIO2HjUDCMPGjl3biH5/bhrhhojzkx9c/dAo+duYUeDwc6zds4JkxCZBAwROgAKQA1HVSCkBdgrQfFgIbDraqsX4bDrap/C+ZNx73XbcIEytLhuV4zJQESIAE3ESAApACUNdfKQB1CdJ+SAnEkya+/4dt+MELO5A0U6gsCeCOqxfgI6dNZtRvSEkzMxIgATcToACkANT1XwpAXYK0HzICMsZPon5bmtpVnssWTsA91zairjw8ZMdgRiRAAiRQDAQoACkAdf2YAlCXIO21CUQTBr773Db86KUdMFNATWkQd1+zEFctmsionzZdZkACJFCMBCgAKQB1/ZoCUJcg7bUIrN7TghUr12Ln0U6Vz4eXTFJdvuPKQlr50pgESIAEipkABSAFoK5/UwDqEqR9XgS64kk89Lst+Omru5FKAePLQ7j32kZcvrA+r/xoRAIkQAJjiQAFIAWgrr9TAOoSpP2gCaza0aye4bu3pUvZXn96A27/0AJURgKDzosGJEACJDAWCVAAUgDq+j0FoC5B2udMoCOWxAO/3YT/em2vsplYGVZLu1wyry7nPLgjCZAACZAAQAFIAah7HlAA6hKkfU4EXtx6FLc+ug4HTnSr/T919lT1KLfyMKN+OQHkTiRAAiTgIEABSAGoe0JQAOoSpP1JCbR2J3DvUxvxy7f2q/0aqkvwzesX47zZtSRHAiRAAiSQJwEKQArAPF2nx4wCUJcg7fsl8PymJtz62Do0tcXUPp9ZOh0rls1DachPaiRAAiRAAhoEKAApADXcR5lSAOoSpP17CBzvjOOu32zA4+8eVN/NqC1VUb+zZtSQFgmQAAmQwBAQoACkANR1IwpAXYK070Pg6XWHcPuv1+NYRxxeD/D5C2biq5fNRTjgIykSIAESIIEhIkABSAGo60oUgLoEaa8IHG2P4Y4n1uPpdYfV5zl1ZXhw+WKcNrWahEiABEiABIaYAAUgBaCuS1EA6hIc4/apVApPrDmIO5/YgONdCfi8Hnzxolm44f2zEfIz6jfG3YPVJwESGCYCFIAUgLquRQGoS3AM2x9ujeLrj6/Dc5uOKAqnTKzAQ8sXo3Fy5RimwqqTAAmQwPAToACkANT1MgpAXYJj0F6ifr9avR/3PLkR7dEkAj4Pbrh0Dr548SwEfN4xSIRVJgESIIGRJUAB6F4BeCeAOzLcZQuA+dY2D4C7APwlgCoArwD4IoBtDpswgG8B+ASAEIDfAfgSgKZBuCEF4CBgcVeohZxvfmQt/rTtmMKxuKESDy1fgnn15cRDAiRAAiQwQgQoAN0tAJcD+IDDV5IA0r+qwE0AbgHwaQC7ANwDYBGABQA1PvWdAAAgAElEQVSi1j4/BHCVLK8GoBXA9wGYAM4bhP9RAA4C1lje1TRT+J839uL+pzehM24g6Peq2b2fP38G/Iz6jWXXYN1JgARGgQAFoLsF4LUATs3iNxL9kwXUJLr3sPW9DKqSyJ6IvV8AkM9H5YlaAFZa+0j0cBOAcwG8lqM/UgDmCGos77anuRM3P7IOq3Y2KwxnTKtWM3xnjS8by1hYdxIgARIYNQIUgO4WgCusyJ1E9FZZEb+9AGYC2AHgNADvOrzrRevz3wK4FMDzAGSNjROOffYA+C6A7/TjldJVLH92kn67/a2traioEC3IRAK9BAwzhZ+9uhsP/W4LuhMGwgEvblw2H59eOl3N9mUiARIgARIYHQIUgO4VgB8EIOETGfc30RoPOBlAo9XVK2P+JgE45HCtXwJIAfi4Ffn7SYaYk13fAPBHqws5m1dmG3sICsDROYEL+ag7jnbgxpVrsXrPcVXMc2bWqKd5TBtXWsjFZtlIgARIYEwQoAB0rwDMdFCZ6CHRu69a3bjDJQAZARwTl4b8K5k0TPzby7vw7d9vRTxpojTowy1XnoJPnTUVXkb98gdLSxIgARIYQgIUgMUjAMUt3gTwHIB/HcYu4Ez34xjAITwh3Z7VlsPtuHHlGqzZL3OKgAvm1OL+6xahoTri9qqx/CRAAiRQVAQoAItHAEp38D6rK/h71iQQmQAiE0EkiVCT1XYzJ4F8EsAj1j7zAGzmJJCiOsdHpDIJw8QPX9iB7/1hGxJGCuVhP77xoQX46BkN8Hg41m9EGoEHIQESIIFBEKAAdK8AFHH3G6vbV8b6yZp/MiNYlnmR2b2yDMzNGcvALM6yDMyVlihsAyDCUdLSQfgQI4CDgFWMu64/0IoVK9di0yFxIeD98+tw70cWob5SlplkIgESIAESKEQCFIDuFYCylMuFAMZZgu9lALdZXb/ia/ZC0H9lLQQt38siz1sdjmgvBC1RQOdC0IcH4awUgIOAVUy7xpIGvvf8dvzwxR2Q2b5VkQDuvHohrjl1EqN+xdTQrAsJkEBREqAAdK8ALBSHpAAslJYYwXK8s/e4muG77UiHOuqVi+px14cbMb7cuULQCBaIhyIBEiABEhgUAQpACsBBOUyWnSkAdQm6yD6aMNTs3n/7006YKaC2LIi7r2nElYtkJSImEiABEiABtxCgAKQA1PVVCkBdgi6xf3N3i4r67TrWqUp87amTcPvVC1FTGnRJDVhMEiABEiABmwAFIAWg7tlAAahLsMDtu+JJPPjMFvxs1W6kUkBdeUhN8rhswYQCLzmLRwIkQAIk0B8BCkAKQN2zgwJQl2AB27+6/RhuenQt9rV0q1J+7MwG3HbVAlSWBAq41CwaCZAACZDAQAQoACkAB/KRgb6nAByIkAu/b48mcN/Tm/HzN+TR0sDkqhK1oPOFc8e7sDYsMgmQAAmQQCYBCkAKQN2zggJQl2CB2b+w5QhueXQdDrVGVcn+/JypuOmK+SgPM+pXYE3F4pAACZBA3gQoACkA83Yey5ACUJdggdi3diVwz1MbsXL1flWiqTURPHD9IiydVVsgJWQxSIAESIAEhooABSAFoK4vUQDqEiwA+2c3HMZtj6/H0fYY5Mltn106A19bNheRoL8ASscikAAJkAAJDDUBCkAKQF2fogDUJTiK9i2dcdzxxAb8Zs1BVYqZtaV4cPlinDm9ZhRLxUOTAAmQAAkMNwEKQApAXR+jANQlOAr2qVQKT607hDt+vQHNnXF4PcBfXjgTf/+BuQgHfKNQIh6SBEiABEhgJAlQAFIA6vobBaAuwRG2P9Iexe2Pb8AzG9KPfJ47oQwPLV+CJVOqRrgkPBwJkAAJkMBoEaAApADU9T0KQF2CI2QvUb/H3z2Au36zESe6EvB7PfjSJbPxN5fMQsjPqN8INQMPQwIkQAIFQYACkAJQ1xEpAHUJjoD9odZu3PbYevxh8xF1tIWTKtRYv4WTKkfg6DwECZAACZBAoRGgAKQA1PVJCkBdgsNoL1G/X761D//w5Ca0x5II+rz4yvtn4wsXzULA5x3GIzNrEiABEiCBQiZAAUgBqOufFIC6BIfJfl9Ll1rQ+eXtx9QRZIzfQ8sXY+6E8mE6IrMlARIgARJwCwEKQApAXV+lANQlOMT2ppnCf7++Bw/8djM64wZCfi/+z+Vz8bnzZ8In032ZSIAESIAExjwBCkAKQN2TgAJQl+AQ2u8+1okbH1mLN3a1qFzfN70a37x+MWaOLxvCozArEiABEiABtxOgAKQA1PVhCkBdgkNgb5gp/OSVXXj42S2IJkyUBHy46Yp5+Itzp8PLqN8QEGYWJEACJFBcBCgAKQB1PZoCUJegpv32Ix24ceUavL33hMpp6axxeOC6xZg6LqKZM81JgARIgASKlQAFIAWgrm9TAOoSzNM+aZj40Z924rvPbUM8aaIs5MetV56CT541BR55oC8TCZAACZAACfRDgAKQAlD35KAA1CWYh/3mw21Y8au1WHegVVlfNHc87r9uESZVleSRG01IgARIgATGGgEKQApAXZ+nANQlOAh7ifT94IXt+L9/3I6EkUJF2I/br16I60+fzKjfIDhyVxIgARIY6wQoACkAdc8BCkBdgjnar9vfihUr12Dz4XZlcdmCCbj32kbUVYRzzIG7kQAJkAAJkECaAAUgBaDuuUABqEtwAPtowsA/Pb8N//LSTshs3+pIAHdd04irF09k1G+Y2TN7EiABEihWAhSAFIC6vk0BqEvwJPZv7z2OG1euhcz0lXTV4om468MLUVsWGsajMmsSIAESIIFiJ0ABSAGo6+MUgLoEs9h3xw1869kt+PEru5BKQQm+f7h2Ia5onDgMR2OWJEACJEACY40ABSAFoK7PUwDqEsywf31nM256ZC12N3epb647bTK+8aEFqC4NDvGRmB0JkAAJkMBYJUABSAGo6/sUgLoELfvOWBIPPrMZP1u1R22prwjjvusacen8CUN0BGZDAiRAAiRAAmkCFIAUgLrnAgWgLkEAL287hpsfXYv9x7tVbp943xTcetUpqAgHhiB3ZkECJEACJEACfQlQAFIA6p4TFIAaBNuiCdz31Cb84s19KpfJVSV44PpFuGDOeI1caUoCJEACJEACJydAAUgBqHuOUADmSfCPm4/glkfX4XBbVOXwF+dOw41XzFePdGMiARIgARIggeEkQAFIAajrXxSAgyR4oiuOu5/ciEffPqAsp42L4MHrF+PsmeMGmRN3JwESIAESIIH8CFAAUgDm5zm9VhSAgyD4zPrD+Prj63GsIwaPB/jceTPwfy6fh5KgbxC5cFcSIAESIAES0CNAAUgBqOdBAAVgDgSbO2K4/YkNeGrtIbX3rPGleHD5EpwxrToHa+5CAiRAAiRAAkNLgALQvQLwFlkiDsB8ADJ19FUANwHY4nCRnwL4dIbL/A7AFY5t8iDZb8nEUwDyeAn5/ksAmnJ0NQrAk4BKpVL4zdpDuPOJDWjpjMPn9eALF87EV94/B+EAo345+hh3IwESIAESGGICFIDuFYDPAPgFgDcByKyB+wA0AlgAoNPyExGAsojcZx1+EwNw3PH5h/KEMQCfAdAK4PsATADn5ehrFID9gDrSFlXdvc9uTGvp+fXleGj5EixqqMwRLXcjARIgARIggeEhQAHoXgGY6RGybsgRABcBeMkhAKsAXNuP+4gSOQrgUwBWWvtIRHETgHMBvJaD21EAZkCSqJ9M8JCJHq3dCfi9Hnz50tn40sWzEfR7c0DKXUiABEiABEhgeAlQABaPAJwNYBuARQDWOwSgiL+4FfX7A4CvA2i2vr8UwPMAZCDaCYeryaMovgvgOzm4HwWgA9LBE9249bF1eGGL6GqgcXKFivqdMlEwMZEACZAACZBAYRCgACwOAShhpScASLTvfIdrybg+eaDsLpl3YHUTd1jRPcOK/P3EGvvn9Mg3APzRGlOY6akyTlD+7FQOYH9raysqKsauyJGonyzmfO9Tm9ARSyLo8+LvLpuDv7pgJvw+Rv0K43LHUpAACZAACdgEKACLQwDKOL4PWuJv/0nceyaAHQA+YEX+pOt3sALwTgB3ZB5jLAvAfS1d6jFur2xPB1ZPm1qFh5Yvxuw60cZMJEACJEACJFB4BCgA3S8AZdLGNQAutCJ9A3mZ9E1KN/C/AMinC5gRQIuwaabwn6/twTef2YyuuIGQ34sVy+bhs+fNULN9mUiABEiABEigUAlQALpXAIrC+B6AjwC42Br/N5CfNQDYa00KkS5jexLIJwE8YhnPA7CZk0BOjnLXsU7cuHIN3tydnlB91owafPP6xZhRWzpQG/B7EiABEiABEhh1AhSA7hWAP7DG8En0z7n2nyzlIusCllldtSLsDltjAB8EIP2SMlFEloORJN3HV1rLwLRZolK2L83RO8fUJBDDTOHfX96Fh5/dgljSRCTowy0fnI8/O3savIz65egy3I0ESIAESGC0CVAAulcApvpxHlnzT9b/KwHwuAxJsyaHHATwLIBvZCzybC8ELVFA50LQIhpzSWNGAG5raseKlWvx7r70hOnzZ9fi/usWYUpNJBdO3IcESIAESIAECoYABaB7BWChOFHRC8CEYeJHL+3EPz63DXHDRHnIj9uuOgUff98UeOSBvkwkQAIkQAIk4DICFIAUgLouW9QCcOPBNqxYuQYbDkrvOHDJvPG477pFmFgpAVYmEiABEiABEnAnAQpACkBdzy1KARhPmvj+H7fjB3/cjqSZQmVJAHdcvQAfOW0yo366HkN7EiABEiCBUSdAAUgBqOuERScA1+4/gRW/WostTe2KzbKFE3DPtY2oK5fhkkwkQAIkQAIk4H4CFIAUgLpeXDQCMJow8N3ntuFHL+2AmQJqSoO4+5qFuGrRREb9dL2E9iRAAiRAAgVFgAKQAlDXIYtCAK7e06Jm+O482ql4fHjJJNXlO67M+dQ7XVS0JwESIAESIIHCIEABSAGo64muFoDdcQMP/W4LfvLqLqRSwPjyEO69thGXL6zX5UJ7EiABEiABEihYAhSAFIC6zulaAbhqR7N6hu+e5i7F4PrTG/CND52CqkhQlwntSYAESIAESKCgCVAAUgDqOqjrBGBHLIkHfrsJ//WaPBUPmFgZVku7XDKvTpcF7UmABEiABEjAFQQoACkAdR3VVQLwpa1Hccuj63DghDwtD/jU2VPVo9zKwwFdDrQnARIgARIgAdcQoACkANR1VlcIwNbuBO59aiN++dZ+Vd+G6hJ88/rFOG92rW79aU8CJEACJEACriNAAUgBqOu0BS8An9/UhFsfW4emtpiq62eWTseKZfNQGvLr1p32JEACJEACJOBKAhSAFIC6jluwAvB4Zxx3P7kRj71zQNVxRm2pivqdNaNGt860JwESIAESIAFXE6AApADUdeCCFIC/XXcI3/j1ehzriMPrAT5/wUz8/QfmoiTo063viNibpomjR4+iqakJcpJ2d3cjlUqpBanD4TBKSkp6/iKRCOw/v59RzRFpIB6EBEiABFxOgAKQAlDXhQtKAB7riOH2X6/H0+sOq3rNqSvDg8sX47Sp1br1HHb7RCKBLVu2YMOGDdixYwfi8figjxkMBnvEoC0KRTDKdudfIBDo+Syi0efzDfjn9XoHXR4akAAJkAAJFCYBCkAKQF3PLAgBKNGxJ9YcxJ1PbMDxrgR8Xg++eNEs3PD+2Qj5Czvq19HRgTfffBNvvfUWOjvTTyKRFAwEUVdVi4pgGcLeIDwpqChgzEggZsYRNWKIJmPoikXRHUtHCIczSfRRhKIIQVsw2u9Pti2f/cVG/uSY2V5P9l1/NpnbB8pDWIpNtr/M74aTO/MmARIggeEgQAFIAajrV6MuAJvaorjtsfV4blOTqsspEyvw0PLFaJxcqVu3YbWPxWJ49dVX1Z9E/ySVR8owr3wappyoRHVrGF54cipDCinEkUTUk0DUl0A8aCIWMNT7hM9E0mMg4TGQTBlIIImEvJpJ9WekDJgpE4b8mdZ701TbmHIjkCkSByMeh8s2W8nlWMO5XfK2b0QGevUgLa7FxQdikI1nNhE+2HwGytf5vf0+2zabq/O1v/eFai/lLSsrQ3l5ubrpYip+AhSAFIC6Xj5qAlB+YH61ej/ueXIj2qNJBHwe3HDpHHzx4lkI+Ar3AmYYBlavXo0XX3yxJ+I3obwWjdEGTGuvhhe9ZffXlsBXHYKvNAD4re1GCmY0qf5S3QbMbut9zNBtyz72IipN9WfCsF7ls+GRLfLP/j69j+mxXh12ap/M7WLvSSHlBQx5tfeR/dSfWAEp+zt5b//zQAnTlMexzTqeskn17KnKp/5Z29Rn5/f2dnub9TqkEJkZCbiMgIi/mpoaNDQ0YNq0aZg7dy5KS0tdVgsWNxcCFIAUgLn4ycn2GRUBKAs5y4LOsrCzpMUNlXho+RLMqy/Xrc+w2Yv42LRpE55//nk0Nzer41SFynFG1wxMT9RKPATeiB8lC2sRXlCD0IxKeMO5T+pImSmkYoYlDg2kbJEYNWDGDKSSZvovkX6F9dqzzUiJuoLkI6/O92qb0fud/bnPPpn2w9sjPSztlJaMKo5lvdpCs3dL5j6ZFr3itTef/m367mN/UnnYJVFC2Hn8k9v0xZ69Efprmt5a94+3j62MS8hMKfHk3mR/6t1mv7NJZ9TtPfXt2xZORs6W6m2HjLZSh7MZvrdt++aXjfV77dNbZIyAs2zZSpO93XrsHX6WWUZ7H7kRslOvH/VXj/SeThZ9afT9vucYYuFJoQtx9epMEhmcPXs2zj77bMyaNSsdtWUqCgIUgBSAuo48ogLQNFP4+Zt7cf/TmyGPdAv6vfjqZXPx+fNnwF/AUb+9e/fi2Wefxf796YWoS/xhnB6fjnnxiSriF5hchrJzJyGypBaeQGGPWczVYZRIlHGJtqjMIiBtsal6m2U/w+wrPtPKJ92tqPJTYb70NsdnNfyxz2fHvqZl79hH5dfzWSKDvfnKB1Ueex/1ue+xrV/ZdLns38uM92qzna/zvW3Sn51ze4ad+tjnOFY5rf3Sx8xSJqswPcNEs+Qhu6ifdvsH3v6dT2/suVKqr537yDjJoBfekoC6gVF/JfJnfVbv038eiWLLtHxnHk7/sNo/lXEz0fPZ3i6vtm/Z7Sj5qG0WA/XZ9gurTS2f7GnPDJs+2+02z2Daw9+G6fTJk7Vpv/vbvmWdWbZ/Z9k/7Wu2vzoa3Tpun7L1+H0vk16/dvp47/ElSt6FGFq8HWjytmK/txnN3vaeU76urg6XXHIJ5s+fTyGY64WwgPejAKQA1HXPEROAe5u7cNMja7FqZzp6dsa0ajXDd9b4Mt06DJu9LOUiEb/NmzerY/i9fiwypmJRbAqC8CPQUIbKy6YhNLeaF9RhawVmTAIkMBABEb9mRwLJlm4kDnQgtrsN0S3HcSLRjk2+/djsO6jGEkuaMmUKLr/8cvXK5F4CFIAUgLreO+wCUKJ+P311Nx763RZ0JwyEA17cuGw+Pr10uprtW4ipvb0dL7zwAt5+++30+n3wYB4m4/TodEQQQmBiKSoum4bwKTUUfoXYgCwTCZAAUgkD3Zta0PHyAbTvbcE6/16s8+1V44AlNTY24rLLLkNlZWFPuGNTZidAAUgBqHtuDKsA3HG0AzetXIu39hxX5TxnZo16mse0cYU5KDkajeKVV17Ba6+91jOzd5qnDmdGZ6A6VQb/+BJUXD5NjfPzFKh41XUI2pMACRQfgdjuVrQ+sxvHdx/Bav9ObPUfSvdq+P04//zzsXTpUrW2KJN7CFAAUgDqeuuwCMCkYeLHL+/Ct3+/FbGkidKgD7dceQo+ddZUeAtQOMmSLrKOn4i/rq4uxXSCtxrv656J+lQVfFUhVHxgGiKn11H46Xoc7UmABEaFgPRmRDe1oPWZXTh8tAmrAlvVWEFJFRUVqlt44cKF7NUYldYZ/EEpACkAB+81fS2GXABuOdyOG1euwZr96QvLBXNqcf91i9BQHdEt65Dbi/B74403sGrVqh7hV+Utw5nRmZhm1sJXGkT5pVNQdvbE9AB4JhIgARJwOQGZlNP5xiG0Prsb22MH8UZgGzo9MVWrqVOn4oorrsCkSZNcXsviLz4FIAWgrpcPmQBMGCb++YUd+Kc/bEPCSKE87Mc3PrQAHz2joeDuKOXZvPL0DhF+8l7dAXsiODU+DbONevhCAZRf2ICy8yfDGyqOWb26jkJ7EiCB4iIga5C2Pb8XJ1btw1rsxhr/np7xgaeddhouvfRStbA0U2ESoACkANT1zCERgOsPtOLGlWux8VCbKs/759fh3o8sQn1lWLd8Q2ov6/e9/vrreOedd3rG+FV6SnFqbBpmmRPgCwdRdt4klJ83Cd5IYEiPzcxIgARIoBAJJI51o/XpXTi28QDeDGzHDl/6qUwyJvDCCy/EOeeco8YKMhUWAQpACkBdj9QSgLGkge//YTt++MIOJM0UqiIB3Hn1Qlxz6qSCifrJuJc9e/aoaN+WLVt6eFWjDEvi0zDTnAB/aRBlF0xG2TkTB7V4sy582pMACZBAoRCI7jiB1id3Yv/hA2p84DFrDcHq6mosW7YM8+bNK5jreqEwG81yUABSAOr6X94C8N19J9RYv61NHaoMVy6qx10fbsT48pBumYbEXiZzrFmzRi3lIuv52WmKOQ6NyamYZFbDX1OCsqWTUHpWPbxBdvUOCXhmQgIk4FoCsp5g1+omnHhmF7ZE9+JN/w50e+KqPlOnTMXFl1yMGTNmUAgWQAtTAFIA6rrhoAVgNGHgO7/fin/900718IbasiDuvqYRVy6aqFsWbXvTNLF7924l+uSxbfLcXkl+eDE7ORELjSmoTpUiNLMSZedNTq/jV4CzkrVBMAMSIAES0CBgxpJof3E/Wl7Zi3eNHVjv29czPlAWkL744osxc+ZMCkENxrqmFIAUgLo+NCgB+NbuFjXWb+exTnXca0+dhNuvXoia0tFbP0q6eA8cOID169djw4YNkEWc7TTOLMd8YxJmGfUIhUKILBmP0nMnITixMNch1G1M2pMACZDAUBIwuxJof/kAml7ZiXeNndjiO9grBBsacP4FF2DOnDnwerlKwlByzyUvCkAKwFz85GT75CQAu+JJPPjMFvxs1W71fM668pCa5HHZggm6x8/LXkTfoUOHVJRPhN/x4+mFpiUFU37MNCYo4VebqkBwRgVKz6xHyaJadvPmRZtGJEACY52AUwiuMXaqR8vZTxSpqa7BuUvPxZIlS7iY9Ag6CgUgBaCuuw0oAF/dcUw9w3dfS3q5lI+d2YDbrlqAypKRnSUbj8exa9cubN26Vf05I33+lBfTzPFK+DWY4xAaF0HJ4vGInDEBgdoSXUa0JwESIAESAGBGk+h84zCaXt6JNV3bVUQw7kkqNiWhMM48630488wz+Xi5EfAWCkAKQF0361cAtkcTeOC3m/Hfr+9Vx5hcVaIWdL5w7njdY+ZkL+P5Dh8+rESf/MnYvmQyfaGR5E/50GDWYIYxAVPNWoRrShFZXIuSReMRmFTKsSk5UeZOJEACJDB4AinDRPf6Y2h+cTc2NG3HBt9etHujKiN5dvrsWbNwxvvOVN3DPh8n2A2e8MAWFIAUgAN7ycn3yCoAX9hyBLc+ug4HW9Mn9J+fMxU3XTEf5eHhi/qJuBPBt3//fiX25E+ezetMZakwphq1SvBNTFUj3FCJknnVCM+vQWByGUWfrjfQngRIgAQGQUCG48T3tKH9tYPYtGEjNnj24bD3RE8OZSWlWHLaqWhc1Ij6+npeowfBdqBdKQApAMVH/gbACgD1ANYAuAHAGwM5j/V9HwHY2pXAPU9txMrV+9XXU2sieOD6RVg6qzbH7HLbTaJ7LS0tahyfCD6ZxCHv7Vm7di6BlA8TzWq1ZMskswY1oUqUzK1GeF4NwvOq4SsbvcknudWUe5EACZDA2CBgdCbQ9c4RHFi1DRtad2Kb7xCinkRP5WsqqrFwSSMaGxtRV1dHMajpFhSAFIAfB/AfAP4awOsA/g7ARwHMA3AkB//qEYCv7+/GbY+tw5H2GDwe4LNLZ+Bry+YiEsx/BXgReq2trZAncBw5cgRNTU040nRErcuXNHq7c+1yhlIB1JkVqDerlOAbH65CeGa1WrYlNKMSgfpSLtuSQ6NyFxIgARIYLQIqKri7De2rD2Hz+k3YbhzEPm9zz6QRKVdlaQXmzJ+LOXPnqHUF5akjTIMjQAFIASii700AX7ZcR+bi7wPwPQAP5OBOSgB+4ccv4Zmt6ce4zawtxYPLF+PM6TUDmsdiMXR0dKgJGfarzMiV6F5LcwtOtJ6AiMBsyZfyoiZVhvFmBerMStSlKlBTNw7BKRUINpQjNL0C/roIBd+ArcAdSIAESKAwCaSSJqJbj+PE2wfU5L0dqcM44G3pIwZ9Xh8a6idh2uwZmDp1KmSdQVm2i+nkBCgAx7YAlFumLgDLATzucJWfAagCcE0OJ5ASgJ+44VaEwmHMGl+GOXVl8Ho8kLu49B/Ua8IwkEgaSCYMRGMJdHR3I9mPuHMe15vyoDxVohZgrjHLUJ0qQ7WnFJHSEFABGBUmjCoTRqUpKzYzkQAJkAAJFCOBJOA/5gMOA0ePtOGA0Yx9vmZ0ePqO9fZIhLCkFJUVEVRVRlBVXorKsgiCAT+7jR1+0dHZiXOWXa8CqgDSEZwxlsRXxmqaBOAAgKUAVjkgPAjgIgBnZwEjt1XOW6tyAPtvvvnmvO+4ZDZuJBVEBCGUpIJK7FWkSlBuhuFPJGEmutCVbENH4jja4sfQmjiGzmTrWG0z1psESIAESABATWgi6sLTUFo6EbFwGEf97TjsOYEOazZxJiSvmYIvmYQnHgPiXYCRgMcw4DGS6s+KVsAjUQvInyQPUjKmSSkFeU3/qW2Znx3b0ja9+/R87tlm5+dVs55lX/s1na/1vXqx87FLZYULzToAABasSURBVOdtF9GWMWm7VNo4I4/0Jud30VgM9z78kGymAByDZ1Q+AvBOAHdksvrRim+jNBhRDmy5sXpNu3b6n0zICMCvFloOpnxK3HkSCSSNbkSNTkSNLvXalWxHR7IV3cl2pJDu/k27s4QSrVenK6uTNWO7vWkMNiqrTAIkQAJjhoAleLzwozpcj/ElU1FSMg5GuBSdfhPN3g60eDrQ7k2vQ8vUS0CGYD3wgBrpRQE4Bh0jny7grBHAZ7/0MEpDJUqfpSyhZsALM+VD+tWLRMqj/mLqvRdGyg8TfhipIBKpEEwM7RIxQU8nSrytiHhb1Wv670T6s693W6m3BUFPV/omi4kESIAESGDUCchvRqdZjXZjAtqMOrQb49Fp1KDLrEanWYMuoxpdZpX6DekvBTxAlc+Dcq8HYZ8Bry8O0x9FwhtFpzeKGJKIeRKIIYGYJwkTJgz1fwqmJx1FkCCGDENKBzTkX29gI/1d77b0d9bnVHo/+3Mfe+u79IqH6f/Vz0/KDnbY22Wj833vvuniiZXE9DzwpNLvnfunLXu3pd/ZVkBnrAuXf/czFICj7u2jVwCZBCJLvsjSL2l/B2Tl5u8PZhJI63PfRkVZpNe1UmY6nK7EoPO9ve29r6aRQtLwIJHwIpH0IJmUVy+SSQ8Shg/JpA9x+Yv7EUv4EbVeY3EfYvLe8XmwQzv9fgNlkQTKSuLqtVTeq1f5nERZJI5wyMiYUOJQjD3qMds2+0S1CPdRmkORh8N5RrUcQ1iXARnlwDTvPHTa0G4LnTwc3Tk92TnvTgbIO+96O5j2uRkaTF2chmrwr3UNsF+tX7lBXht6ryOZ9lmuJ3K9UdedbNca+SrX69LJjuXMx9FdmPWYJymLs1djIFtVnP6vn8pVnN8LBzMBmEnANFR3Z/q9vBrp9z3bZLv1p7pCDcAXBPwhx2sI8AfTn/v8BRyf5b39OQB4fIBXFnGWrkmv9We/98AwPDh+wo/jx/1obfWirS39197mQUc7YJq53ZWXlJiIRFIIl6QQDpkIh1MIh02EQunX9DYTwYCJQMCE32fCLygTXphRL8yYBymptvwlPKr66WT9donaSqXg8ZiAx4THYwAeEV6Gtc16tT+r19594EmqfeEx0jaQFSzS79PbHJ/V76XjT8bJDxSdeM/3Gdz6+b6tK47Kz/6CAnD09NeoH1mWgZFJH1+whKAsA/MxAPMBNOVQugEfBZdDHkO6S8pMIdadRHd7HN3tCXS1yav9l1Dvuxzfxbvfu5xMtgL5Al6U14RRURtG+bgSVIyT1zAq5H1tGOGyAAcYD2lLMjMSIIFiIGAkTZxo6kLLoU60HOzseW092g25XveXvD4PyuSaK9famjBKq0LqL1IRRGmlvA+ipCIIn0/iFkyDJcBZwIMNFQ2WsDv2lyVg7IWg3wXwFWtNwFxKX3ACMJdCO/dJxA10Ho+h40QMnSdi6Dge7fnccTy9TQRjz5jgfg7gD/l6RWFNGOW1aWGoBOL4EoRKOEV5sG3D/UmABNxDwDBMtDZ1WwKvo1foHemG2Y/QC5b4UTOxFNX1kZ6b6/SNdRiRyhC83tyigO6hVDglpQCkANT1RtcLwFwAyB2siMH25m60NUfR3hxFW3M32o/JaxSdrbEBBWIo4keFLQrVqyUQa0vU3a3Pz7vYXNqC+5AACYwuASX0jnT3ieZJdK+1qat/oRf2oWZSqRJ7NZPK0qJvYqmK4nkG6uIc3eoW7dEpACkAdZ17TAjAgSAZCRPtLb3CUInEY2mx2HasW3VFnyzJ9a+0OtQTLZS737RATIvDYIkP/qCPd8MDNQS/JwES0CYg67bGOpPqxlaG0Mi1rfVIF44f7lJdudJ1K2O2s6VAyCn0bMEnQi9EoafdMkObAQUgBaCuR1EA5kAwHk2qqKFcONXrMYkedqP1WFooJhPZn3aSmbXX70FAhKDPXjfKXiLK41hyynpvGzvurrON7c929531htyZT5Zemb42znWo0gXJlufQH7u3YNnmwzh5nvTYWUBlL78jx2ycB8rnvZiyghqQXdZ8ehygp5BZ5wj1hfIeb85u0/eAso8v4IPf74WMlfUHvSqird5bf/K9/VlepWtP2kDNDXC+Ztum9pU5BJZNz3vb1vl977YcTs2i3kWEnFxbRMzFuhKIdibUe3m1/2LyviuJaEcivU9HAt0diX4Fng1MhrzU1EesqF5Z+nVSKcqqKfTc4lQUgBSAur5KAahJUC7ScpfdJt3JEjW0I4dHJYLYrbqeBxp/qFkEmpNAURJIr8UrIjO9QG56PV1LLMpbe7sso2GNwFA3BradtWaGysNpa3+281DZ9s2j7/7p7+181Q2ROp5DuFp3SekyO8rZY2ftbwlmmTwh4+okEmcapvWaggxXiXWlBZ9MhjOT+S+KGir1I1IRQllVEFV1EVTVR9KvEyKqZ0LxY3ItAQpACkBd56UA1CU4gL0IROliTsZNyISVZNzouTu3H7WXXvUi/dg9+31mtj3rZcsX1oc+Pw09H3q3vmeNbcf6+HYeKjvnwTLX5bbXhszYMcvhVB3ekxybem2ylDFLGdSalHay3mY7RBpJ/8fOOR9HHtmY9D1Eeo+s5XEWO8sO2W1OzqTXpp/9slX/ZMfOKKMID/FR5asJI/1qb0ta2+OGEiiyn/BWEwNSstyH7bu925TAkWNY38nnHh8f5nOu2LIXDRkqDSCs/vzp95H0ZxF56e2970vKg4iUB1XElql4CVAAUgDqejcFoC5B2pMACQyKQI8YVMu0Wc8bdwjE9PfWd1akzL4XyHbTpMS/vVyfLGVvjchQ+8oxrPX67Dwl8/T7tIJ33nj17pO+MbKXObHz6rnZ6HPT1puffSNi10Htb82gddZVom8+Xzq66fV51bAQ+ZOud5lwFooE0q8lfgTCPo6/G5SHjY2dKQApAHU9nQJQlyDtSYAESIAESGCECVAAUgDquhwFoC5B2pMACZAACZDACBOgAKQA1HU5CkBdgrQnARIgARIggREmQAFIAajrchSAugRpTwIkQAIkQAIjTIACkAJQ1+UoAHUJ0p4ESIAESIAERpgABSAFoK7LUQDqEqQ9CZAACZAACYwwAQpACkBdl6MA1CVIexIgARIgARIYYQIUgBSAui5HAahLkPYkQAIkQAIkMMIEKAApAHVdjgJQlyDtSYAESIAESGCECVAAUgDquhwFoC5B2pMACZAACZDACBOgAKQA1HU5CkBdgrQnARIgARIggREmQAFIAajrchSAugRpTwIkQAIkQAIjTIACkAJQ1+UoAHUJ0p4ESIAESIAERpgABSAFoK7LUQDqEqQ9CZAACZAACYwwAQpACkBdl1MCcN++faiokLdMJEACJEACJEAChU5ABOCUKVOkmJUA2gq9vMNRPs9wZDqG8pwOYNcYqi+rSgIkQAIkQALFRGAGgN3FVKFc60IBmCup7PupCCCABgDtelkVnHU5gP2sW8G1y0AFYrsNRKhwv2fbFW7bnKxkbDd3txsjgO5sv1EvtS0Ai9GBWLdRd6+8CsB2ywtbQRix7QqiGQZdCLbboJEVhEExt1tOgBkBzAlTvzsVswOxbnq+MVrWbLfRIq9/XLadPsPRyIHtNhrU9Y9ZzO2WEx0KwJwwUQDqYSo462I+8Vm3gnO3nAvEtssZVUHtyHYrqObIuTDF3G45QaAAzAlTvzuFANwC4H4AMb2sCs6adSu4JsmpQGy3nDAV5E5su4JslgELxXYbEFFB7lDM7ZYTcArAnDBxJxIgARIgARIgARIoHgIUgMXTlqwJCZAACZAACZAACeREgAIwJ0zciQRIgARIgARIgASKhwAFYPG0JWtCAiRAAiRAAiRAAjkRoADMCRN3IgESIAESIAESIIHiIUABmH9b/g2AFQDqAawBcAOAN/LPbkQsZcbydQDmA+gG8CqAmwBscRxdfOIuAH8JoArAKwC+CGCbY58wgG8B+AQAmUn1OwBfAtA0IrXI7SA3W7Oz/xHA31kmbq7bZADfBPBBABEA2wF8FsBbLq+bD8CdAP7cOpcOAvgpgH8AkHJZ3S60rglnAJgI4CMAHh+Gc6sGwPcAXA3ABPAIgL8F0JHbqZHXXierW8BqrysBzLSejvQcADkHpT3tlMt1YzTqJuUbqO2c0P4ZwBcA/D2A77qgfrnU7RTr+nIRAD+AjQCuB7DXql+htt1AdSsD8ACAawGMsx7d+k8ApA3d4Jd5nay5GlEA5kqq734fB/AfAP4awOuWwPgogHkAjuSX5YhYPQPgFwDetE7y+wA0AlgAoNMqgQhCEYqftk6WewAssvaJWvv8EMBVAD5jXey/b/0QnTcitRj4IO8D8EvrAd9/dAhAt9atGsA7AKQuwv4ogDkAdlh/QsStdbsVwFctf9sA4EwAPwFwGwC5ULupbiLO5RxYDeDRLAJwqNrot5bAFBEi4kt4yTn9qYFPjbz3OFnd5ElIKwH8q3UzLP4qN14i7qU97ZTLdWM06iblG6jt7DqIqL8DwHgAD2UIwEKt30B1m2UFL34M4OfWdXMhgNccv2durduPAFwK4PPW834vs66hEgh5YhC/Z6Pll3mfsLkYUgDmQum9+4jokwvul62vvAD2WXflcrfhliQXMRGsctf3EgDxB7ljl+jew1Yl5OIukT0ReyIe5bMIEPmxkYu+JIkobgJwrnXRGM36yx3f21ZE8usA3rUEoJvrJj4lwuKCfsC6uW5PWv71OUfdJKIlEWqJCrq1bhK9dEYAh6oeEqmR6Izc5NjR3ysAPG09t9sZcRuu8zCzbtmOI+WTHpFpVhQpl+tGIdRN6tJf/SQKL9f+ZQCessSfHQF0S/2y1U2u6wkA/6sfh3Fz3dYD+H8AJJBhJ7lBE0Envw9uqduwnMsUgIPHGgTQBWB5RvfOz6wu02sGn+WoWcy2unYlwicninTfSFTpNEs42QV70fos3UxyN/U8ALnLP+Eo+R7rgvidUatN+sDSDi1W98wLDgHo5rrJD750szdYYv0AgB9YEReps5vrJhHAvwJwOYCtAJYAeNaKCv63i+uW+UM7VG30v60bNDn/7CRddhKdl16Ix0bg/MtFAH7AakcZRtKW43WjEOrWnwCUm3zp1v61Fd3cnSEAc7kuFkL9MttO6tUK4EEA51vX/l3W8Bl7+IJb6yZtKRFA+T2TLmC5ObrYivxJD5YEPdxSt2E5rSkAB491EgD5AV4KYJXDXE4giaSdPfgsR8VCTnwJgcsFWk58SVInGfMndTzkKJV0p8qFQ7q+JfInXU4y9s+Z5G5fuiilm2u0koxJlK5DiT7ID6JTALq5bnbX+7cB/Mqqn3SxyRAEEbxurpv4oQxFuBGAYXUbShvK03Xc7JOZP7RD1UYimGV4hgw3cSaJ5EvXpHTVDXcaSADKeDG5jmwG8GdWYXK5bhRC3aS42eonw2IusaJ/8n2mAHRL/TLrJmPY5VovQQ2JiMk1XCLKck5KfeXm3611k7aU3ykRgX8BIGkNVZLx7TKES5Jb6jYs5zQF4OCxFosAlB8KGRsi4m+/y39spfhTrC4xGeOx1qpPsQjAuFU3ERF2kvFxInSl232oxMXgzwZ9CxHtMpZKJlTJGMBTrciKjAt0s7gdqwJQxiRKF75EqyXaItE/t/3QZradTOqRLt/THZNaikUA2r9nMvbPOYZUggMyLvyTLhJJ2YT716wJjfIqvVQyaURuLmV4hkR0KQD1r+FjKodi6AKWSRvSVS0ng4T77TRU3VSj4RAS4pfuL4ki2UkGoctFQWZKSsREZs66sXtbLly/twYy23WTmdlyxy7jktzcbjJ2VmY3i0/aSeol4/9kbKlb6zYWu4BF/ElvgbSZdK01O9rUTV1tmW0nqwhI9F2uI85ri3wW/53uoq7EzLrJ75kIPVn5QWbe20nOSQkOyNhjt7RdZt1KrO5tmfAhY43t9G/WDYpEOt1St2H5TWUEMD+sMhBYujxl6RdJ0o0l0+XlR6yQJ4FIe8vyEXL3I3fnzqVdpB72QHWZACITQSRVWBNFMieByJ2h3OlLEnEl3T2jOQmk3Bpw7mxR6aqWcsnFTKJLMgbEjXX7HyvC6ZwEImMtZbiBRP/c3G4iEqTL17ksg3S3yRI3c11ct/4mgej6nz1RQmbXymB2STJ+Umb4S9RttCaB2OJPZqdL16FMFHMme7D9ya4bhVA3KXNm28nyIbKsjzPJmNz/tIbDyDJabqlftiiZLAcmY7+dk0DkZlomYkmEzK11k98uGd8oPV1yftjpXwDMsM4bt9QtP6UygBUFYH5YZSycdE/JMgwiBOUO8WNWxKKQ1sLLrJ1MHJATWqJ/zrX/5CSRk12SjOGT9bucy8AszrIMjKz5JaJQunhEVEpydlHmR3ZorZxdwG6um3T1ykVaxnhJhOUsawKITJ6QiRJurpus+ScTBuRcEpEuEVoZs/PvjvGkbvFJmYEuE6skybI90o0tY6pkUpLcIA5VPWQG4wRrDKi9DIzMCB7OZWBOVjcZQyYrAkgX6Ycy1gOVussQBkky7GSg68Zo1E3KNlDbZV6ZMruAC7l+A9VNAgIyU1bWtrXHAMrsZgkSvFzgbTdQ3eQ3oNZasUN6UmScvvihnJv2eNlC9suh/UXMyI0CMH+8sgSMvRC0LDXyFWuJgPxzHH5Le2HdzCNJtEV+iCXZiyWLuJAJInIBkEWeZYamnexFQeVu3rkQ9OHhr8KgjpApAN1cN/lhlbErEmGRbnvpkpJ11+zk1rpJ5FaWaJAfoTorgiXjke52CAe31E1+MOUHNDPJzaLcLA1VPWSxZOltcC4ELdef4VwI+mR1k4W8nUNJnPWXaKCch5JyuW6MRt2kbAO1XWabZhOAhVq/XOomM5Ql8i5RZAkOyM2mzHgezDV/NNpuoLrJJBe5bkqUXMonIlBuMKUHxf49LNR2G9SPXT47UwDmQ402JEACJEACJEACJOBiAhSALm48Fp0ESIAESIAESIAE8iFAAZgPNdqQAAmQAAmQAAmQgIsJUAC6uPFYdBIgARIgARIgARLIhwAFYD7UaEMCJEACJEACJEACLiZAAejixmPRSYAESIAESIAESCAfAhSA+VCjDQmQAAmQAAmQAAm4mAAFoIsbj0UnARIgARIgARIggXwIUADmQ402JEACJEACJEACJOBiAhSALm48Fp0ESIAESIAESIAE8iFAAZgPNdqQAAmQAAmQAAmQgIsJUAC6uPFYdBIgARIgARIgARLIhwAFYD7UaEMCJEACJEACJEACLiZAAejixmPRSYAESIAESIAESCAfAhSA+VCjDQmQAAmQAAmQAAm4mAAFoIsbj0UnARIgARIgARIggXwIUADmQ402JEACJEACJEACJOBiAhSALm48Fp0ESIAESIAESIAE8iFAAZgPNdqQAAmQAAmQAAmQgIsJUAC6uPFYdBIgARIgARIgARLIhwAFYD7UaEMCJEACJEACJEACLiZAAejixmPRSYAESIAESIAESCAfAhSA+VCjDQmQAAmQAAmQAAm4mAAFoIsbj0UnARIgARIgARIggXwIUADmQ402JEACJEACJEACJOBiAhSALm48Fp0ESIAESIAESIAE8iFAAZgPNdqQAAmQAAmQAAmQgIsJUAC6uPFYdBIgARIgARIgARLIhwAFYD7UaEMCJEACJEACJEACLiZAAejixmPRSYAESIAESIAESCAfAhSA+VCjDQmQAAmQAAmQAAm4mAAFoIsbj0UnARIgARIgARIggXwI/H+PA0z7bvVfTQAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xceca3c8>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Pandas built-in plotting (built on Matplotlib).\n",
    "df.plot() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pandas built-in plotting. Specify keys for plotting.\n",
    "fig = plt.figure()\n",
    "ax = plt.gca()\n",
    "for yattr in ['PPT5858, kPa', 'PPT5859, kPa']:\n",
    "    df.plot(x='time, s', y=yattr, ax=ax)\n",
    "plt.gca().grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 7. Read fast data binary file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Define a function to read a CGM binary file.\n",
    "def read_binfile(filename):\n",
    "    '''\n",
    "    Reads binary file with standard format used at UC Davis CGM.\n",
    "    Returns a list of [sensor_ID, raw] where sensor ID is \n",
    "    a list of sensor Xdcr Location ID values and raw is a numpy\n",
    "    array of data.\n",
    "    '''\n",
    "    \n",
    "    # Open binary file for reading.\n",
    "    with open(filename, 'rb') as f:\n",
    "        line = f.readline().decode()  # Read the first line.\n",
    "        \n",
    "        # Read lines until excel config header.\n",
    "        while line != '[excelconfig]\\r\\n':\n",
    "            line = f.readline().decode()\n",
    "        \n",
    "        # Skip sensor header line.\n",
    "        line= f.readline().decode() \n",
    "        # Read sensor info into list(s).\n",
    "        sensor_ID = []\n",
    "        # Read first sensor config line.\n",
    "        line= f.readline().decode()  \n",
    "        \n",
    "        # Read lines until line only contains a line break.\n",
    "        while(line != '\\r\\n'):\n",
    "            # Append the 5th comma separated value to the sensor_ID list.\n",
    "            sensor_ID.append(line.split(',')[4])\n",
    "            line = f.readline().decode()\n",
    "        \n",
    "        # Read lines until data header.\n",
    "        while(line != '[data]\\r\\n'):\n",
    "            line = f.readline().decode()\n",
    "            \n",
    "        # Read binary data into numpy array.\n",
    "        raw = np.fromfile(f, dtype='>f')\n",
    "        raw = raw.astype('float')\n",
    "        \n",
    "        # Reshape array.\n",
    "        N = len(sensor_ID)\n",
    "        raw = np.reshape(raw,((int(raw.size / N)), N))\n",
    "        \n",
    "        # Return a list of outputs.\n",
    "        return [sensor_ID, raw]\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fromfile(file, dtype=float, count=-1, sep='')\n",
      "\n",
      "    Construct an array from data in a text or binary file.\n",
      "\n",
      "    A highly efficient way of reading binary data with a known data-type,\n",
      "    as well as parsing simply formatted text files.  Data written using the\n",
      "    `tofile` method can be read using this function.\n",
      "\n",
      "    Parameters\n",
      "    ----------\n",
      "    file : file or str\n",
      "        Open file object or filename.\n",
      "    dtype : data-type\n",
      "        Data type of the returned array.\n",
      "        For binary files, it is used to determine the size and byte-order\n",
      "        of the items in the file.\n",
      "    count : int\n",
      "        Number of items to read. ``-1`` means all items (i.e., the complete\n",
      "        file).\n",
      "    sep : str\n",
      "        Separator between items if file is a text file.\n",
      "        Empty (\"\") separator means the file should be treated as binary.\n",
      "        Spaces (\" \") in the separator match zero or more whitespace characters.\n",
      "        A separator consisting only of spaces must match at least one\n",
      "        whitespace.\n",
      "\n",
      "    See also\n",
      "    --------\n",
      "    load, save\n",
      "    ndarray.tofile\n",
      "    loadtxt : More flexible way of loading data from a text file.\n",
      "\n",
      "    Notes\n",
      "    -----\n",
      "    Do not rely on the combination of `tofile` and `fromfile` for\n",
      "    data storage, as the binary files generated are are not platform\n",
      "    independent.  In particular, no byte-order or data-type information is\n",
      "    saved.  Data can be stored in the platform independent ``.npy`` format\n",
      "    using `save` and `load` instead.\n",
      "\n",
      "    Examples\n",
      "    --------\n",
      "    Construct an ndarray:\n",
      "\n",
      "    >>> dt = np.dtype([('time', [('min', int), ('sec', int)]),\n",
      "    ...                ('temp', float)])\n",
      "    >>> x = np.zeros((1,), dtype=dt)\n",
      "    >>> x['time']['min'] = 10; x['temp'] = 98.25\n",
      "    >>> x\n",
      "    array([((10, 0), 98.25)],\n",
      "          dtype=[('time', [('min', '<i4'), ('sec', '<i4')]), ('temp', '<f8')])\n",
      "\n",
      "    Save the raw data to disk:\n",
      "\n",
      "    >>> import os\n",
      "    >>> fname = os.tmpnam()\n",
      "    >>> x.tofile(fname)\n",
      "\n",
      "    Read the raw data from disk:\n",
      "\n",
      "    >>> np.fromfile(fname, dtype=dt)\n",
      "    array([((10, 0), 98.25)],\n",
      "          dtype=[('time', [('min', '<i4'), ('sec', '<i4')]), ('temp', '<f8')])\n",
      "\n",
      "    The recommended way to store and load data:\n",
      "\n",
      "    >>> np.save(fname, x)\n",
      "    >>> np.load(fname + '.npy')\n",
      "    array([((10, 0), 98.25)],\n",
      "          dtype=[('time', [('min', '<i4'), ('sec', '<i4')]), ('temp', '<f8')])\n"
     ]
    }
   ],
   "source": [
    "print(np.fromfile.__doc__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Read a binary file.\n",
    "file_path = 'data/04262017@113846@131514@212.6rpm.bin'\n",
    "[sensor_ID, raw] = read_binfile(file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(256000L, 6L)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check shape of raw data array returned from read_binfile.\n",
    "raw.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ -4.35389951e-03,   1.37446392e+00,   4.27390633e+01,\n",
       "         4.21561737e+01,  -1.34481573e+01,   2.36345935e+00])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print the first row of raw.\n",
    "raw[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "# Contruct DataFrame from numpy array (raw) and list (sensor_ID) read from binary file.\n",
    "df2 = pd.DataFrame(data=raw, columns=sensor_ID)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ICP1</th>\n",
       "      <th>FB</th>\n",
       "      <th>PPT5884_CENTER</th>\n",
       "      <th>PPT5884_LEFT</th>\n",
       "      <th>LC</th>\n",
       "      <th>Tbar</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.004354</td>\n",
       "      <td>1.374464</td>\n",
       "      <td>42.739063</td>\n",
       "      <td>42.156174</td>\n",
       "      <td>-13.448157</td>\n",
       "      <td>2.363459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.008124</td>\n",
       "      <td>2.290807</td>\n",
       "      <td>42.746765</td>\n",
       "      <td>42.245983</td>\n",
       "      <td>-13.400112</td>\n",
       "      <td>2.169969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.008240</td>\n",
       "      <td>1.741001</td>\n",
       "      <td>42.696686</td>\n",
       "      <td>42.382549</td>\n",
       "      <td>-13.379796</td>\n",
       "      <td>2.122214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.008521</td>\n",
       "      <td>2.242998</td>\n",
       "      <td>42.690971</td>\n",
       "      <td>42.462929</td>\n",
       "      <td>-13.364147</td>\n",
       "      <td>2.198787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.028796</td>\n",
       "      <td>1.605542</td>\n",
       "      <td>42.728409</td>\n",
       "      <td>42.463150</td>\n",
       "      <td>-13.394073</td>\n",
       "      <td>2.165852</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ICP1        FB  PPT5884_CENTER  PPT5884_LEFT         LC      Tbar\n",
       "0 -0.004354  1.374464       42.739063     42.156174 -13.448157  2.363459\n",
       "1  0.008124  2.290807       42.746765     42.245983 -13.400112  2.169969\n",
       "2 -0.008240  1.741001       42.696686     42.382549 -13.379796  2.122214\n",
       "3 -0.008521  2.242998       42.690971     42.462929 -13.364147  2.198787\n",
       "4  0.028796  1.605542       42.728409     42.463150 -13.394073  2.165852"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show first 5 rows of DataFrame.\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 8. Plot data from binary file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xd2f4e80>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plot from constructed DataFrame.\n",
    "df2.plot(y='Tbar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "ax = plt.gca()\n",
    "for yattr in ['LC', 'Tbar']:\n",
    "    df2.plot(y=yattr, ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0xd53eb00>]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plot using numpy arrays and offset data.\n",
    "data = raw.transpose()\n",
    "plt.figure(figsize=(9, 4))\n",
    "plt.grid()\n",
    "plt.plot(data[5] - data[5][0])\n",
    "plt.plot(data[4] - data[4][0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 9. Store data from binary file in a dictionary and make a plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "# Construct dictionary with sensor_ID as keys and data arrays as values with dict comprehension.\n",
    "data_dict = {key: data[idx] for idx, key in enumerate(sensor_ID)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'FB': array([ 1.37446392,  2.29080725,  1.74100113, ...,  1.70116019,\n",
       "         1.69319201,  2.65734458]),\n",
       " u'ICP1': array([-0.0043539 ,  0.00812405, -0.00824009, ...,  0.03386421,\n",
       "         0.02110533,  0.02222905]),\n",
       " u'LC': array([-13.44815731, -13.40011215, -13.37979603, ..., -13.86628628,\n",
       "        -13.81165218, -13.90609455]),\n",
       " u'PPT5884_CENTER': array([ 42.73906326,  42.74676514,  42.69668579, ...,  65.87110138,\n",
       "         65.88224792,  65.94219971]),\n",
       " u'PPT5884_LEFT': array([ 42.15617371,  42.24598312,  42.38254929, ...,  50.77403641,\n",
       "         50.74829865,  50.80138397]),\n",
       " u'Tbar': array([ 2.36345935,  2.16996932,  2.12221432, ...,  0.65004313,\n",
       "         0.78425115,  0.80236512])}"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "# Plot with seaborn styling.\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "# Set seaborn plotting context.\n",
    "sns.set_context(context='notebook', font_scale=1.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1409b048>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make a figure using data dictionary.\n",
    "plt.figure(figsize=[9, 4])\n",
    "ax = plt.gca()\n",
    "x_attr = 'FB'\n",
    "y_attr = 'Tbar'\n",
    "plt.plot(data_dict[x_attr], data_dict[y_attr])\n",
    "ax.set_ylabel(y_attr)\n",
    "ax.set_xlabel(x_attr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 10. Widgets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "# Imports.\n",
    "import ipywidgets as widgets\n",
    "from IPython.display import display\n",
    "from random import randint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c7b94d3d69d34efc867a8358ead36d5f"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Simple widget.\n",
    "my_button = widgets.Button(description='My Button')\n",
    "display(my_button)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c7b94d3d69d34efc867a8358ead36d5f"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hola\n",
      "Hi\n",
      "Hi\n",
      "Hi\n",
      "Hi\n",
      "Hola\n",
      "Hi\n",
      "Hi\n",
      "Hi\n",
      "Bonjour\n",
      "Bonjour\n",
      "Hola\n"
     ]
    }
   ],
   "source": [
    "my_button"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def my_button_callback(self):\n",
    "    greeting = ('Hi', 'Hola', 'Bonjour')\n",
    "    rand = randint(0, len(greeting)-1)\n",
    "    print(greeting[rand])\n",
    "\n",
    "my_button.on_click(my_button_callback)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "98989e5585314a66b9e004fda0db0916"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.myfunc>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Interact example\n",
    "def myfunc(n):\n",
    "    '''\n",
    "    Prints the square of n.\n",
    "    '''\n",
    "    print(n**2)\n",
    "\n",
    "widgets.interact(myfunc, n=(1,20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "# Plotting widget with our dictionary example.\n",
    "def update_plot(ax, data, y_attr):\n",
    "    '''\n",
    "    Updates plotted data.\n",
    "    '''\n",
    "    line = ax.lines[0]\n",
    "    line.set_ydata(data[y_attr])\n",
    "    ax.set_ylabel(y_attr)\n",
    "    ax.relim()\n",
    "    ax.autoscale()\n",
    "    plt.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0xd474278>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Initialize figure.\n",
    "plt.figure(figsize=[9, 4])\n",
    "ax = plt.gca()\n",
    "y_attr = tuple(data_dict.keys())[0]\n",
    "plt.plot(data_dict[y_attr])\n",
    "ax.set_ylabel(y_attr)\n",
    "ax.set_xlabel('Index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0998dd70eb694080b4e025b4b5d450ec"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function __main__.update_plot>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Widget interaction.\n",
    "widgets.interact(\n",
    "    update_plot, \n",
    "    ax=widgets.fixed(ax),\n",
    "    data=widgets.fixed(data_dict),\n",
    "    y_attr=list(data_dict.keys())\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  },
  "livereveal": {
   "scroll": true,
   "start_slideshow_at": "selected",
   "theme": "lato_custom",
   "transition": "zoom",
   "width": "1080"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "0176d9544f4040ffa9d7bf1ad548c707": {
      "model_module": "jupyter-js-widgets",
      "model_module_version": "~2.1.4",
      "model_name": "ButtonStyleModel",
      "state": {
       "_model_module_version": "~2.1.4",
       "_view_module_version": "~2.1.4"
      }
     },
     "025c62a7c9aa4d619d98e6f0c346a623": {
      "model_module": "jupyter-js-widgets",
      "model_module_version": "~2.1.4",
      "model_name": "DropdownModel",
      "state": {
       "_model_module_version": "~2.1.4",
       "_options_labels": [
        "LC",
        "Tbar",
        "PPT5884_CENTER",
        "FB",
        "ICP1",
        "PPT5884_LEFT"
       ],
       "_view_module_version": "~2.1.4",
       "description": "y_attr",
       "layout": "IPY_MODEL_10d9546a533a4e7dab929315df43932a",
       "value": "LC"
      }
     },
     "0411d1cfe057464a9c7ed0e31c3149eb": {
      "model_module": "jupyter-js-widgets",
      "model_module_version": "~2.1.4",
      "model_name": "LayoutModel",
      "state": {
       "_model_module_version": "~2.1.4",
       "_view_module_version": "~2.1.4"
      }
     },
     "0480b11eeb9f4aac928d2a85f5548c86": {
      "model_module": "jupyter-js-widgets",
      "model_module_version": "~2.1.4",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "jupyter-js-widgets",
       "_model_module_version": "~2.1.4",
       "_view_module": "jupyter-js-widgets",
       "_view_module_version": "~2.1.4",
       "layout": "IPY_MODEL_fe9ea1071ecf47e8b0caa90c318786cc",
       "msg_throttle": 1
      }
     },
     "0612822cd7b74944a65b4590f346432f": {
      "model_module": "jupyter-js-widgets",
      "model_module_version": "~2.1.4",
      "model_name": "IntSliderModel",
      "state": {
       "_model_module_version": "~2.1.4",
       "_view_module_version": "~2.1.4",
       "description": "n",
       "layout": "IPY_MODEL_69d382701f464576bcfc02e64119890f",
       "max": 20,
       "min": 1,
       "style": "IPY_MODEL_ced32b882a6e47c1b25f72bc39495b5a",
       "value": 10
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