From e0600d5228de3ab8f9b4f746082d86163efac9b8 Mon Sep 17 00:00:00 2001
From: GitHub Actions <actions@github.com>
Date: Tue, 3 Oct 2023 00:16:24 +0000
Subject: [PATCH] site deploy

Auto-generated via {sandpaper}
Source  : 6b185ffddc4b06127514e8bafac53fc2c6c06b1c
Branch  : md-outputs
Author  : GitHub Actions <actions@github.com>
Time    : 2023-10-03 00:15:56 +0000
Message : markdown source builds

Auto-generated via {sandpaper}
Source  : b925071a3f4e89dc22f0fdd12e96daf42bcfd871
Branch  : main
Author  : The Carpentries Apprentice (beta) <64428345+carpentries-bot@users.noreply.github.com>
Time    : 2023-09-12 10:49:44 +0000
Message : [actions] update sandpaper workflow to version 0.13.0 (#582)

Co-authored-by: zkamvar <zkamvar@users.noreply.github.com>
---
 00-before-we-start.html                       |    6 +-
 01-short-introduction-to-Python.html          |    6 +-
 02-starting-with-data.html                    |    6 +-
 03-index-slice-subset.html                    |    6 +-
 04-data-types-and-format.html                 |    6 +-
 05-merging-data.html                          |   12 +-
 06-loops-and-functions.html                   |   18 +-
 06-visualization-ggplot-python.ipynb          | 1228 +++
 06b_matplotlib_plotting.ipynb                 | 6723 +++++++++++++++++
 07-visualization-ggplot-python.html           |   16 +-
 08-putting-it-all-together.html               |    6 +-
 09-working-with-sql.html                      |   10 +-
 404.html                                      |    8 +-
 CODE_OF_CONDUCT.html                          |    6 +-
 CONTRIBUTORS.html                             |    6 +-
 LICENSE.html                                  |    6 +-
 aio.html                                      |   40 +-
 discuss.html                                  |    6 +-
 extra_challenges.html                         |    6 +-
 images.html                                   |    8 +-
 index.html                                    |    8 +-
 instructor-notes.html                         |    8 +-
 instructor/00-before-we-start.html            |    6 +-
 .../01-short-introduction-to-Python.html      |    6 +-
 instructor/02-starting-with-data.html         |    6 +-
 instructor/03-index-slice-subset.html         |    6 +-
 instructor/04-data-types-and-format.html      |    6 +-
 instructor/05-merging-data.html               |   14 +-
 instructor/06-loops-and-functions.html        |   20 +-
 .../07-visualization-ggplot-python.html       |   20 +-
 instructor/08-putting-it-all-together.html    |    6 +-
 instructor/09-working-with-sql.html           |   10 +-
 instructor/404.html                           |    8 +-
 instructor/CODE_OF_CONDUCT.html               |    6 +-
 instructor/CONTRIBUTORS.html                  |    6 +-
 instructor/LICENSE.html                       |    6 +-
 instructor/aio.html                           |   48 +-
 instructor/discuss.html                       |    6 +-
 instructor/extra_challenges.html              |    6 +-
 instructor/images.html                        |    8 +-
 instructor/index.html                         |    8 +-
 instructor/instructor-notes.html              |    8 +-
 instructor/jupyter_notebooks.html             |    6 +-
 instructor/key-points.html                    |    8 +-
 instructor/profiles.html                      |    8 +-
 instructor/reference.html                     |    6 +-
 jupyter_notebooks.html                        |    6 +-
 key-points.html                               |    8 +-
 pkgdown.yml                                   |    2 +-
 profiles.html                                 |    8 +-
 reference.html                                |    6 +-
 51 files changed, 8182 insertions(+), 231 deletions(-)
 create mode 100644 06-visualization-ggplot-python.ipynb
 create mode 100644 06b_matplotlib_plotting.ipynb

diff --git a/00-before-we-start.html b/00-before-we-start.html
index c751398ef..a2b574991 100644
--- a/00-before-we-start.html
+++ b/00-before-we-start.html
@@ -641,8 +641,8 @@ <h3 class="callout-title">Keypoints<a class="anchor" aria-label="anchor" href="#
         <p>Materials licensed under <a href="LICENSE.html">CC-BY 4.0</a> by the authors</p>
         
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-        <p>Built with <a href="https://github.com/carpentries/sandpaper/tree/0.13.3" class="external-link">sandpaper (0.13.3)</a>,
-        <a href="https://github.com/carpentries/pegboard/tree/0.6.1" class="external-link">pegboard (0.6.1)</a>,
+        <p>Built with <a href="https://github.com/carpentries/sandpaper/tree/0.14.0" class="external-link">sandpaper (0.14.0)</a>,
+        <a href="https://github.com/carpentries/pegboard/tree/0.7.0" class="external-link">pegboard (0.7.0)</a>,
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@@ -665,7 +665,7 @@ <h3 class="callout-title">Keypoints<a class="anchor" aria-label="anchor" href="#
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   "dateCreated": "2015-03-19",
   "dateModified": "2023-06-05",
-  "datePublished": "2023-09-26"
+  "datePublished": "2023-10-03"
 }
 
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diff --git a/01-short-introduction-to-Python.html b/01-short-introduction-to-Python.html
index 280225018..d24e3dfea 100644
--- a/01-short-introduction-to-Python.html
+++ b/01-short-introduction-to-Python.html
@@ -992,8 +992,8 @@ <h3 class="callout-title">Keypoints<a class="anchor" aria-label="anchor" href="#
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-        <a href="https://github.com/carpentries/pegboard/tree/0.6.1" class="external-link">pegboard (0.6.1)</a>,
+        <p>Built with <a href="https://github.com/carpentries/sandpaper/tree/0.14.0" class="external-link">sandpaper (0.14.0)</a>,
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diff --git a/02-starting-with-data.html b/02-starting-with-data.html
index 99d404689..ebe35be14 100644
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+        <p>Built with <a href="https://github.com/carpentries/sandpaper/tree/0.14.0" class="external-link">sandpaper (0.14.0)</a>,
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       and <a href="https://github.com/carpentries/varnish/tree/0.3.0" class="external-link">varnish (0.3.0)</a>.</p>
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@@ -1348,7 +1348,7 @@ <h3 class="callout-title">Keypoints<a class="anchor" aria-label="anchor" href="#
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   "dateCreated": "2015-03-19",
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index 56b8e656d..cedf5f1ec 100644
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         <p>Materials licensed under <a href="LICENSE.html">CC-BY 4.0</a> by the authors</p>
         
         <p><a href="https://creativecommons.org/licenses/by-sa/4.0/" class="external-link">Template licensed under CC-BY 4.0</a> by <a href="https://carpentries.org" class="external-link">The Carpentries</a></p>
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-        <a href="https://github.com/carpentries/pegboard/tree/0.6.1" class="external-link">pegboard (0.6.1)</a>,
+        <p>Built with <a href="https://github.com/carpentries/sandpaper/tree/0.14.0" class="external-link">sandpaper (0.14.0)</a>,
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       and <a href="https://github.com/carpentries/varnish/tree/0.3.0" class="external-link">varnish (0.3.0)</a>.</p>
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   "identifier": "https://datacarpentry.github.io/python-ecology-lesson/03-index-slice-subset.html",
   "dateCreated": "2015-03-19",
   "dateModified": "2023-08-18",
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diff --git a/04-data-types-and-format.html b/04-data-types-and-format.html
index 4406634df..9dd075c78 100644
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+++ b/04-data-types-and-format.html
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+        <p>Built with <a href="https://github.com/carpentries/sandpaper/tree/0.14.0" class="external-link">sandpaper (0.14.0)</a>,
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       and <a href="https://github.com/carpentries/varnish/tree/0.3.0" class="external-link">varnish (0.3.0)</a>.</p>
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diff --git a/05-merging-data.html b/05-merging-data.html
index 3f7019aa7..f07cc5fba 100644
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-<div id="collapseSolution1" class="accordion-collapse collapse" aria-labelledby="headingSolution1" data-bs-parent="#accordionSolution1">
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-<div id="collapseSolution2" class="accordion-collapse collapse" aria-labelledby="headingSolution2" data-bs-parent="#accordionSolution2">
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 </button>
-<div id="collapseSolution3" class="accordion-collapse collapse" aria-labelledby="headingSolution3" data-bs-parent="#accordionSolution3">
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         <p><a href="https://creativecommons.org/licenses/by-sa/4.0/" class="external-link">Template licensed under CC-BY 4.0</a> by <a href="https://carpentries.org" class="external-link">The Carpentries</a></p>
-        <p>Built with <a href="https://github.com/carpentries/sandpaper/tree/0.13.3" class="external-link">sandpaper (0.13.3)</a>,
-        <a href="https://github.com/carpentries/pegboard/tree/0.6.1" class="external-link">pegboard (0.6.1)</a>,
+        <p>Built with <a href="https://github.com/carpentries/sandpaper/tree/0.14.0" class="external-link">sandpaper (0.14.0)</a>,
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   "dateCreated": "2015-03-19",
   "dateModified": "2023-05-19",
-  "datePublished": "2023-09-26"
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 }
 
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diff --git a/06-loops-and-functions.html b/06-loops-and-functions.html
index c3051d118..2bde63460 100644
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 </button>
-<div id="collapseSolution3" class="accordion-collapse collapse" data-bs-parent="#accordionSolution3" aria-labelledby="headingSolution3">
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-<div id="collapseSolution4" class="accordion-collapse collapse" data-bs-parent="#accordionSolution4" aria-labelledby="headingSolution4">
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+        <p>Built with <a href="https://github.com/carpentries/sandpaper/tree/0.14.0" class="external-link">sandpaper (0.14.0)</a>,
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@@ -1714,7 +1714,7 @@ <h3 class="callout-title">Keypoints<a class="anchor" aria-label="anchor" href="#
   "identifier": "https://datacarpentry.github.io/python-ecology-lesson/06-loops-and-functions.html",
   "dateCreated": "2015-03-19",
   "dateModified": "2023-05-18",
-  "datePublished": "2023-09-26"
+  "datePublished": "2023-10-03"
 }
 
   </script><script>
diff --git a/06-visualization-ggplot-python.ipynb b/06-visualization-ggplot-python.ipynb
new file mode 100644
index 000000000..8b11dc6a7
--- /dev/null
+++ b/06-visualization-ggplot-python.ipynb
@@ -0,0 +1,1228 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true,
+    "toc": "true"
+   },
+   "source": [
+    "# Table of Contents\n",
+    " <p><div class=\"lev1\"><a href=\"#Learning-Objectives\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Learning Objectives</a></div><div class=\"lev2\"><a href=\"#Disclaimer\"><span class=\"toc-item-num\">1.1&nbsp;&nbsp;</span>Disclaimer</a></div><div class=\"lev1\"><a href=\"#Plotting-with-ggplot\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Plotting with ggplot</a></div><div class=\"lev1\"><a href=\"#Building-your-plots-iteratively\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Building your plots iteratively</a></div><div class=\"lev1\"><a href=\"#Boxplot\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Boxplot</a></div><div class=\"lev2\"><a href=\"#Challenges\"><span class=\"toc-item-num\">4.1&nbsp;&nbsp;</span>Challenges</a></div><div class=\"lev1\"><a href=\"#Plotting-time-series-data\"><span class=\"toc-item-num\">5&nbsp;&nbsp;</span>Plotting time series data</a></div><div class=\"lev1\"><a href=\"#Faceting\"><span class=\"toc-item-num\">6&nbsp;&nbsp;</span>Faceting</a></div><div class=\"lev1\"><a href=\"#Challenge\"><span class=\"toc-item-num\">7&nbsp;&nbsp;</span>Challenge</a></div><div class=\"lev1\"><a href=\"#Customization\"><span class=\"toc-item-num\">8&nbsp;&nbsp;</span>Customization</a></div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# Learning Objectives #\n",
+    "By the end of this lesson the learner will:\n",
+    "\n",
+    "* Create a ggplot object\n",
+    "* Set universal plot settings\n",
+    "* Modify an existing ggplot object\n",
+    "* Change the aesthetics of a plot such as colour\n",
+    "* Edit the axis labels\n",
+    "* Build complex plots using a step-by-step approach\n",
+    "* Create scatter plots, box plots, and time series plots\n",
+    "* Use the facet_wrap and facet_grid commands to create a collection of plots splitting the data by a factor variable\n",
+    "* Create customized plot styles to meet their needs\n",
+    "\n",
+    "## Disclaimer ##\n",
+    " Python has powerful built-in plotting capabilities such as `matplotlib`, but for this exercise, we will be using the [`ggplot`](http://ggplot.yhathq.com/) package, which facilitates the creation of highly-informative plots of structured data based on the R implementation of [`ggplot2`](http://ggplot2.org/) and [The Grammar of Graphics](http://link.springer.com/book/10.1007%2F0-387-28695-0) by Leland Wilkinson.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "echo=FALSE, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "\n",
+    "surveys_complete = pd.read_csv('data_output/surveys_complete.csv')\n",
+    "surveys_complete"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "from ggplot import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "# Plotting with ggplot\n",
+    "\n",
+    "We will make the same plot using the `ggplot` package.\n",
+    "\n",
+    "`ggplot` is a plotting package that makes it simple to create complex plots\n",
+    "from data in a dataframe. It uses default settings, which help creating\n",
+    "publication quality plots with a minimal amount of settings and tweaking.\n",
+    "\n",
+    "ggplot graphics are built step by step by adding new elements.\n",
+    "\n",
+    "To build a ggplot we need to:\n",
+    "\n",
+    "- bind the plot to a specific data frame using the `data` argument\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "- define aesthetics (`aes`), by selecting the variables to be plotted and the variables to define the presentation\n",
+    "     such as plotting size, shape color, etc.,\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "eval=FALSE, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot( aesthetics= aes(x = 'weight', y = 'hindfoot_length'), data = surveys_complete)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "- add `geoms` -- graphical representation of the data in the plot (points,\n",
+    "     lines, bars). To add a geom to the plot use `+` operator:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "first-ggplot, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot( aes(x = 'weight', y = 'hindfoot_length'), data = surveys_complete) + geom_point()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "The `+` in the `ggplot2` package is particularly useful because it allows you\n",
+    "to modify existing `ggplot` objects. This means you can easily set up plot\n",
+    "\"templates\" and conveniently explore different types of plots, so the above\n",
+    "plot can also be generated with code like this:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "first-ggplot-with-plus, eval=FALSE, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# Create\n",
+    "surveys_plot = ggplot( aes(x = 'weight', y = 'hindfoot_length'), data = surveys_complete)\n",
+    "\n",
+    "# Draw the plot\n",
+    "surveys_plot + geom_point()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "Notes:\n",
+    "\n",
+    "- Anything you put in the `ggplot()` function can be seen by any geom layers\n",
+    "  that you add (i.e., these are universal plot settings). This includes the x and\n",
+    "  y axis you set up in `aes()`.\n",
+    "- You can also specify aesthetics for a given geom independently of the\n",
+    "  aesthetics defined globally in the `ggplot()` function.\n",
+    "\n",
+    "\n",
+    "# Building your plots iteratively\n",
+    "\n",
+    "Building plots with ggplot is typically an iterative process. We start by\n",
+    "defining the dataset we'll use, lay the axes, and choose a geom.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "create-ggplot-object, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot(aes(x = 'weight', y = 'hindfoot_length'), data = surveys_complete, ) + geom_point()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "Then, we start modifying this plot to extract more information from it. For\n",
+    "instance, we can add transparency (alpha) to avoid overplotting.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "adding-transparency, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot(aes(x = 'weight', y = 'hindfoot_length'), data = surveys_complete) + \\\n",
+    "    geom_point(alpha = 0.1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "We can also add colors for all the points\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "adding-colors, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot(aes(x = 'weight', y = 'hindfoot_length'),data = surveys_complete) + \\\n",
+    "    geom_point(alpha = 0.1, color = \"blue\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "Or to color each species in the plot differently:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "color-by-species, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# ggplot(data = surveys_complete, aes(x = weight, y = hindfoot_length)) +\n",
+    "#    geom_point(alpha = 0.1, aes(color=species_id))\n",
+    "\n",
+    "ggplot(aes(x = 'weight', y = 'hindfoot_length', color='species_id'),data = surveys_complete) + \\\n",
+    "    geom_point( alpha = 0.1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "# Boxplot\n",
+    "\n",
+    "Visualising the distribution of weight within each species.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Rmd_chunk_options": "boxplot, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "R code:\n",
+    "\n",
+    "```R\n",
+    "ggplot(data = surveys_complete, aes(x = species_id, y = hindfoot_length)) +\n",
+    "    geom_boxplot()\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "boxplot, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "ggplot( aes(x = 'species_id', y = 'hindfoot_length'), data = surveys_complete) + geom_boxplot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "By adding points to boxplot, we can have a better idea of the number of\n",
+    "measurements and of their distribution:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "Rmd_chunk_options": "boxplot-with-points, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "R code:\n",
+    "```R\n",
+    "ggplot(data = surveys_complete, aes(x = species_id, y = hindfoot_length)) +\n",
+    "    geom_jitter(alpha = 0.3, color = \"tomato\") +\n",
+    "  geom_boxplot(alpha = 0)\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "surveys_complete['species_factor'] = surveys_complete['species_id'].astype('category').cat.codes\n",
+    "\n",
+    "\n",
+    "xlabels = sorted(set(surveys_complete['species_id'].values) )\n",
+    "xcodes = sorted(set(surveys_complete['species_factor'].values))\n",
+    "\n",
+    "ggplot(aes(x = 'species_factor', y = 'hindfoot_length'),data = surveys_complete) + \\\n",
+    "    geom_point(position='jitter',alpha=0.7,jittersize=0.4) + \\\n",
+    "        scale_x_continuous(breaks=xcodes, labels=xlabels) + \\\n",
+    "                         xlab('species_id') + geom_boxplot(alpha=0)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "Notice how the boxplot layer is behind the jitter layer? What do you need to\n",
+    "change in the code to put the boxplot in front of the points such that it's not\n",
+    "hidden.\n",
+    "\n",
+    "## Challenges\n",
+    "\n",
+    "> Boxplots are useful summaries, but hide the *shape* of the distribution. For\n",
+    "> example, if there is a bimodal distribution, this would not be observed with a\n",
+    "> boxplot. An alternative to the boxplot is the violin plot (sometimes known as a\n",
+    "> beanplot), where the shape (of the density of points) is drawn.\n",
+    ">\n",
+    "> - Replace the box plot with a violin plot; see `geom_violin()`\n",
+    ">\n",
+    "> In many types of data, it is important to consider the *scale* of the\n",
+    "> observations.  For example, it may be worth changing the scale of the axis to\n",
+    "> better distribute the observations in the space of the plot.  Changing the scale\n",
+    "> of the axes is done similarly to adding/modifying other components (i.e., by\n",
+    "> incrementally adding commands).\n",
+    ">\n",
+    "> - Represent weight on the log10 scale; see `scale_y_log10()`\n",
+    ">\n",
+    "> - Create boxplot for `hindfoot_length`.\n",
+    ">\n",
+    "> - Add color to the datapoints on your boxplot according to the plot from which\n",
+    ">   the sample was taken (`site_id`)\n",
+    "\n",
+    "Hint: Check the class for `site_id`. Consider changing the class of `site_id`\n",
+    "from integer to factor. Why does this change how R makes the graph?\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "## Challenges:\n",
+    "##  Start with the boxplot we created:\n",
+    "ggplot(aes(x = 'species_factor', y = 'hindfoot_length'),data = surveys_complete) + \\\n",
+    "    geom_jitter(alpha=0.3) + \\\n",
+    "        scale_x_discrete(breaks=xcodes, labels=xlabels) + \\\n",
+    "                         xlab('species_id') + geom_boxplot(alpha=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "##  1. Replace the box plot with a violin plot; see `geom_violin()`.\n",
+    "\n",
+    "ggplot(aes(x = 'species_factor', y = 'hindfoot_length'),data = surveys_complete) + \\\n",
+    "    geom_jitter(alpha=0.3) + \\\n",
+    "        scale_x_discrete(breaks=xcodes, labels=xlabels) + \\\n",
+    "                         xlab('species_id') + geom_violin(alpha=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "##  2. Represent weight on the log10 scale; see `scale_y_log10()`.\n",
+    "ggplot(aes(x = 'species_factor', y = 'hindfoot_length'),data = surveys_complete) + \\\n",
+    "    geom_jitter(alpha=0.3) + \\\n",
+    "        scale_x_discrete(breaks=xcodes, labels=xlabels) + \\\n",
+    "                         xlab('species_id') + geom_violin(alpha=0) + \\\n",
+    "            scale_y_log(base=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "##  3. Create boxplot for `hindfoot_length`.\n",
+    "ggplot(aes(x = 'species_factor', y = 'hindfoot_length'),data = surveys_complete) + \\\n",
+    "    geom_jitter(alpha=0.01) + \\\n",
+    "        scale_x_discrete(breaks=xcodes, labels=xlabels) + \\\n",
+    "                         xlab('species_id') + geom_boxplot(alpha=0) + \\\n",
+    "            scale_y_log(base=10)\n",
+    "            "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "eval=FALSE, purl=TRUE, echo=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "##  4. Add color to the datapoints on your boxplot according to the\n",
+    "##  plot from which the sample was taken (`site_id`).\n",
+    "##  Hint: Check the class for `site_id`. Consider changing the class\n",
+    "##  of `site_id` from integer to factor. Why does this change how R\n",
+    "##  makes the graph?\n",
+    "\n",
+    "ggplot(aes(x = 'species_factor', y = 'hindfoot_length', color='site_id'),data = surveys_complete) + \\\n",
+    "    geom_jitter(alpha=0.01) + \\\n",
+    "        scale_x_discrete(breaks=xcodes, labels=xlabels) + \\\n",
+    "                         xlab('species_id') + geom_boxplot(alpha=0) + \\\n",
+    "            scale_y_log(base=10)\n",
+    "     "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "\n",
+    "# Plotting time series data\n",
+    "\n",
+    "Let's calculate number of counts per year for each species. To do that we need\n",
+    "to group data first and count records within each group.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "yearly_counts = surveys_complete[['year', 'species_id']].groupby(['year', 'species_id']).size().reset_index()\n",
+    "yearly_counts.columns = ['year', 'species_id', 'n']\n",
+    "yearly_counts"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "Timelapse data can be visualised as a line plot with years on x axis and counts\n",
+    "on y axis.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "first-time-series, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot(aes(x = 'year', y = 'n'),data = yearly_counts) + \\\n",
+    "     geom_line()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "Unfortunately this does not work, because we plot data for all the species\n",
+    "together. We need to tell ggplot to draw a line for each species by modifying\n",
+    "the aesthetic function to include `group = species_id`.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot(aes(x = 'year', y = 'n', group='species_id'),data = yearly_counts) + geom_line()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "We will be able to distinguish species in the plot if we add colors.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "time-series-by-species, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot(aes(x = 'year', y = 'n', color='species_id'),data = yearly_counts) + geom_line()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "# Faceting\n",
+    "\n",
+    "ggplot has a special technique called *faceting* that allows to split one plot\n",
+    "into multiple plots based on a factor included in the dataset. We will use it to\n",
+    "make one plot for a time series for each species.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "Now we would like to split line in each plot by sex of each individual\n",
+    "measured. To do that we need to make counts in data frame grouped by year,\n",
+    "species_id, and sex:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "yearly_sex_counts = surveys_complete.groupby( ['year', 'species_id', 'sex']).count()\n",
+    "yearly_sex_counts['n']  = yearly_sex_counts['record_id']\n",
+    "yearly_sex_counts = yearly_sex_counts['n'].reset_index()\n",
+    "yearly_sex_counts"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "We can now make the faceted plot splitting further by sex (within a single plot):\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "facet-by-species-and-sex, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    " ggplot(aes(x = \"year\", y = \"n\", color = \"species_id\", group = \"sex\"), data = yearly_sex_counts, ) + \\\n",
+    "     geom_line() + \\\n",
+    "         facet_wrap( \"species_id\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "Usually plots with white background look more readable when printed.  We can set\n",
+    "the background to white using the function `theme_bw()`. Additionally you can also remove\n",
+    "the grid.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "facet-by-species-and-sex-white-bg, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    " ggplot(aes(x = \"year\", y = \"n\", color = \"species_id\", group = \"sex\"),data = yearly_sex_counts ) + \\\n",
+    "     geom_line() + \\\n",
+    "            facet_wrap( \"species_id\") + \\\n",
+    "                theme_bw() + \\\n",
+    "                theme()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "To make the plot easier to read, we can color by sex instead of species (species\n",
+    "are already in separate plots, so we don't need to distinguish them further).\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "facet-by-species-and-sex-colored, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot(aes(x = \"year\", y = \"n\", color = \"sex\", group = \"sex\"), data = yearly_sex_counts) + \\\n",
+    "    geom_line() + \\\n",
+    "    facet_wrap(\"species_id\") + \\\n",
+    "    theme_bw() "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "\n",
+    "# Challenge\n",
+    "\n",
+    "> Use what you just learned to create a plot that depicts how the average weight\n",
+    "> of each species changes through the years.\n",
+    "\n",
+    "<!-- Answer\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "yearly_weight = surveys_complete[[\"year\", \"species_id\",\"weight\"]].groupby([\"year\", \"species_id\"]).mean().reset_index()\n",
+    "yearly_weight.columns =   [\"year\", \"species_id\",\"avg_weight\"]  \n",
+    "yearly_weight"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "average-weight-timeseries, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot( aes(x=\"year\", y=\"avg_weight\", color = \"species_id\", group = \"species_id\"),data = yearly_weight) + \\\n",
+    "    geom_line() + \\\n",
+    "    facet_wrap(\"species_id\") + \\\n",
+    "    theme_bw()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "eval=FALSE, purl=TRUE, echo=FALSE",
+    "autoscroll": false,
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "## Plotting time series challenge:\n",
+    "##  Use what you just learned to create a plot that depicts how the\n",
+    "##  average weight of each species changes through the years.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "The `facet_wrap` geometry extracts plots into an arbitrary number of dimensions\n",
+    "to allow them to cleanly fit on one page. On the other hand, the `facet_grid`\n",
+    "geometry allows you to explicitly specify how you want your plots to be\n",
+    "arranged via formula notation (`rows ~ columns`; a `.` can be used as\n",
+    "a placeholder that indicates only one row or column).\n",
+    "\n",
+    "Let's modify the previous plot to compare how the weights of male and females\n",
+    "has changed through time.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "## One column, facet by rows\n",
+    "yearly_sex_weight = surveys_complete[\n",
+    "    ['year', 'sex', 'species_id', 'weight']].groupby(\n",
+    "    [\"year\", \"sex\", \"species_id\"]).mean().reset_index()\n",
+    "yearly_sex_weight.columns = ['year', 'sex', 'species_id', 'avg_weight']\n",
+    "yearly_sex_weight"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "average-weight-time-facet_sex_rows, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot( aes(x=\"year\", y=\"avg_weight\", color = \"species_id\", group = \"species_id\"),data = yearly_sex_weight) + \\\n",
+    "    geom_line() + \\\n",
+    "    facet_grid(\"sex\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "average-weight-time-facet_sex_rows, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "# One row, facet by column\n",
+    "ggplot( aes(x=\"year\", y=\"avg_weight\", color = \"species_id\", group = \"species_id\"),data = yearly_sex_weight) + \\\n",
+    "    geom_line() + \\\n",
+    "    facet_grid(None, \"sex\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "# Customization\n",
+    "\n",
+    "Take a look at the ggplot2 cheat sheet\n",
+    "(https://www.rstudio.com/wp-content/uploads/2015/08/ggplot2-cheatsheet.pdf), and\n",
+    "think of ways to improve the plot. You can write down some of your ideas as\n",
+    "comments in the Etherpad.\n",
+    "\n",
+    "Now, let's change names of axes to something more informative than 'year'\n",
+    "and 'n' and add a title to this figure:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "number_species_year_with_right_labels, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot( aes(x = \"year\", y = \"n\", color = \"sex\", group = \"sex\"),data = yearly_sex_counts) + \\\n",
+    "    geom_line() + \\\n",
+    "    facet_wrap( \"species_id\" ) + \\\n",
+    "    labs(title = 'Observed species in time',\n",
+    "         x = 'Year of observation',\n",
+    "         y = 'Number of species') + \\\n",
+    "    theme_bw() "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "The axes have more informative names, but their readability can be improved by\n",
+    "increasing the font size. While we are at it, we'll also change the font family:\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "number_species_year_with_right_labels_xfont_size, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot( aes(x = \"year\", y = \"n\", color = \"sex\", group = \"sex\"),data = yearly_sex_counts) + \\\n",
+    "    geom_line() + \\\n",
+    "    facet_wrap( \"species_id\" ) + \\\n",
+    "    theme_bw() + \\\n",
+    "    theme(axis_title_x = element_text(size=16, family=\"Arial\"),\n",
+    "         axis_title_y = element_text(size=16, family=\"Arial\")) + \\\n",
+    "    labs(title = 'Observed species in time',\n",
+    "        x = 'Year of observation',\n",
+    "        y = 'Number of species')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "After our manipulations we notice that the values on the x-axis are still not\n",
+    "properly readable. Let's change the orientation of the labels and adjust them\n",
+    "vertically and horizontally so they don't overlap. You can use a 90 degree\n",
+    "angle, or experiment to find the appropriate angle for diagonally oriented\n",
+    "labels.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "number_species_year_with_right_labels_xfont_size, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "ggplot( aes(x = \"year\", y = \"n\", color = \"sex\", group = \"sex\"),data = yearly_sex_counts) + \\\n",
+    "    geom_line() + \\\n",
+    "    facet_wrap( \"species_id\" ) + \\\n",
+    "    labs(title = 'Observed species in time',\n",
+    "        x = 'Year of observation',\n",
+    "        y = 'Number of species') + \\\n",
+    "    theme_bw() + \\\n",
+    "    theme(axis_text_x = element_text(color=\"grey\", size=10, angle=90, hjust=.5, vjust=.5),\n",
+    "          axis_text_y = element_text(color=\"grey\", size=10, hjust=0),\n",
+    "         ) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "If you like the changes you created to the default theme, you can save them as\n",
+    "an object to easily apply them to other plots you may create:\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "number_species_year_with_right_labels_xfont_orientation, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "arial_grey_theme = theme(axis_text_x = element_text(color=\"grey\", size=10, angle=90, hjust=.5, vjust=.5),\n",
+    "                          axis_text_y = element_text(color=\"grey\", size=10))\n",
+    "ggplot(surveys_complete, aes(x = 'species_id', y = 'hindfoot_length')) + \\\n",
+    "    geom_boxplot() + \\\n",
+    "    arial_grey_theme"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "\n",
+    "With all of this information in hand, please take another five minutes to either\n",
+    "improve one of the plots generated in this exercise or create a beautiful graph\n",
+    "of your own. Use the RStudio ggplot2 cheat sheet, which we linked earlier for\n",
+    "inspiration.\n",
+    "\n",
+    "Here are some ideas:\n",
+    "\n",
+    "* See if you can change thickness of the lines.\n",
+    "* Can you find a way to change the name of the legend? What about its labels?\n",
+    "* Use a different color palette (see http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/)\n",
+    "\n",
+    "After creating your plot, you can save it to a file in your favourite format.\n",
+    "You can easily change the dimension (and its resolution) of your plot by\n",
+    "adjusting the appropriate arguments (`width`, `height` and `dpi`):\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "ggsave-example, eval=FALSE, purl=FALSE",
+    "autoscroll": false,
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "my_plot =  ggplot(yearly_sex_counts, aes(x = \"year\", y = \"n\", color = \"sex\", group = \"sex\")) \n",
+    "my_plot += geom_line() \n",
+    "my_plot += facet_wrap(\"species_id\") \n",
+    "my_plot += labs(title = 'Observed species in time',\n",
+    "                x = 'Year of observation',\n",
+    "                y = 'Number of species') \n",
+    "my_plot += theme_bw() \n",
+    "my_plot += theme(axis_text_x = element_text(color=\"grey\", size=10, angle=90, hjust=.5, vjust=.5),\n",
+    "                        axis_text_y = element_text(color=\"grey\", size=10))\n",
+    "my_plot.save(\"name_of_file.png\", width=15, height=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "Rmd_chunk_options": "eval=FALSE, purl=TRUE, echo=FALSE",
+    "autoscroll": false,
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "## Final plotting challenge:\n",
+    "##  With all of this information in hand, please take another five\n",
+    "##  minutes to either improve one of the plots generated in this\n",
+    "##  exercise or create a beautiful graph of your own. Use the RStudio\n",
+    "##  ggplot2 cheat sheet for inspiration:\n",
+    "##  https://www.rstudio.com/wp-content/uploads/2015/08/ggplot2-cheatsheet.pdf\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "Rmd_header": {
+   "layout": "topic",
+   "minutes": 60,
+   "subtitle": "Visualizing data in R with the ggplot2 package",
+   "title": "Data visualization with ggplot2"
+  },
+  "_draft": {
+   "nbviewer_url": "https://gist.github.com/7e01571f0b181ec58e4880ef2a50aaa7"
+  },
+  "gist": {
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+    "description": "SWC/python-ecology-lesson/09-visualization-ggplot.ipynb",
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+    "version": 3
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+   "mimetype": "text/x-python",
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+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.0"
+  },
+  "latex_envs": {
+   "bibliofile": "biblio.bib",
+   "cite_by": "apalike",
+   "current_citInitial": 1,
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+  },
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+   "toc_cell": true,
+   "toc_number_sections": true,
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+}
diff --git a/06b_matplotlib_plotting.ipynb b/06b_matplotlib_plotting.ipynb
new file mode 100644
index 000000000..3ceba525c
--- /dev/null
+++ b/06b_matplotlib_plotting.ipynb
@@ -0,0 +1,6723 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "# Plotting with Pandas and Matplotlib\n",
+    "\n",
+    "This is a brief supplement to demonstrate the replication of the plots from Lesson 6 using matplotlib together with Pandas.  \n",
+    "\n",
+    "**GOALS**: \n",
+    "\n",
+    "- Use matplotlib to customize plots\n",
+    "\n",
+    "- Plot data from Pandas DataFrame\n",
+    "\n",
+    "- Use Seaborn to include additional Features in Visualizations\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Matplotlib in the Notebook\n",
+    "\n",
+    "We can use the Jupyter notebooks to investigate the plots interactively by using the `%matplotlib notebook` command.  By doing so, we create a figure object embedded in the notebook that also allows saving, paning, and zooming.  Further, we can continue to interact with a single plot across many cells unlike the more traditional `%matplotlib inline` magic command.\n",
+    "\n",
+    "First, we import the plotting library `pyplot` and abbreviate it as `plt`.  We also set the style to be `seaborn-white`, a clean simple background.  We also import the Pandas and Numpy libraries per usual.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib notebook\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('seaborn-white')\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "### A Simple ScatterPlot\n",
+    "\n",
+    "To create a scatterplot, we can generate some random numbers using the `np.random.randn()` function to represent the *x, y, color,* and *size* of the points for the plot.  Next, we create a figure and assign an optional `figsize` argument.  Finally, we apply the `BuPu` colormap available from matplotlib's built-in colormaps.\n",
+    "\n",
+    "Somewhat like `ggplot2`, we can continue to add elements with additional lines.  For example, we add a main title and $x$ and $y$ axis labels."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'];\n",
+       "    var y0 = fig.canvas.height - msg['y0'];\n",
+       "    var x1 = msg['x1'];\n",
+       "    var y1 = fig.canvas.height - msg['y1'];\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x;\n",
+       "    var y = canvas_pos.y;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"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",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x112934c88>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x = np.random.randn(50)\n",
+    "y = np.random.randn(50)\n",
+    "colors = np.random.rand(50)\n",
+    "sizes = 1000 * np.random.rand(10)\n",
+    "\n",
+    "plt.figure(figsize = (10, 8))\n",
+    "plt.scatter(x, y, c=colors, s=sizes, alpha=0.4,cmap='BuPu')\n",
+    "plt.title(\"A Simple ScatterPlot\")\n",
+    "plt.xlabel(\"A Label for X\")\n",
+    "plt.ylabel(\"A Label for Y\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Pandas and Matplotlib\n",
+    "\n",
+    "We can load the `surveys_complete.csv` dataset into the notebook as a DataFrame named df. Now, we can call plot functions on the DataFrame itself or with a conventional matplotlib approach.\n",
+    "\n",
+    "Similar to the first example, we can directly name the $x$ and $y$ values by reference to the DataFrame's column names.  By taking a quick peek at the head of the dataframe we can see the names of the columns that we are interested in plotting and call them accordingly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv( 'data_for_plots/surveys_complete.csv', index_col=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>record_id</th>\n",
+       "      <th>month</th>\n",
+       "      <th>day</th>\n",
+       "      <th>year</th>\n",
+       "      <th>site_id</th>\n",
+       "      <th>species_id</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>hindfoot_length</th>\n",
+       "      <th>weight</th>\n",
+       "      <th>genus</th>\n",
+       "      <th>species</th>\n",
+       "      <th>taxa</th>\n",
+       "      <th>site_type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>845</td>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>1978</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NL</td>\n",
+       "      <td>M</td>\n",
+       "      <td>32</td>\n",
+       "      <td>204</td>\n",
+       "      <td>Neotoma</td>\n",
+       "      <td>albigula</td>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>Control</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1164</td>\n",
+       "      <td>8</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1978</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NL</td>\n",
+       "      <td>M</td>\n",
+       "      <td>34</td>\n",
+       "      <td>199</td>\n",
+       "      <td>Neotoma</td>\n",
+       "      <td>albigula</td>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>Control</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1261</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1978</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NL</td>\n",
+       "      <td>M</td>\n",
+       "      <td>32</td>\n",
+       "      <td>197</td>\n",
+       "      <td>Neotoma</td>\n",
+       "      <td>albigula</td>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>Control</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1756</td>\n",
+       "      <td>4</td>\n",
+       "      <td>29</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NL</td>\n",
+       "      <td>M</td>\n",
+       "      <td>33</td>\n",
+       "      <td>166</td>\n",
+       "      <td>Neotoma</td>\n",
+       "      <td>albigula</td>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>Control</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1818</td>\n",
+       "      <td>5</td>\n",
+       "      <td>30</td>\n",
+       "      <td>1979</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NL</td>\n",
+       "      <td>M</td>\n",
+       "      <td>32</td>\n",
+       "      <td>184</td>\n",
+       "      <td>Neotoma</td>\n",
+       "      <td>albigula</td>\n",
+       "      <td>Rodent</td>\n",
+       "      <td>Control</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   record_id  month  day  year  site_id species_id sex  hindfoot_length  \\\n",
+       "1        845      5    6  1978        2         NL   M               32   \n",
+       "2       1164      8    5  1978        2         NL   M               34   \n",
+       "3       1261      9    4  1978        2         NL   M               32   \n",
+       "4       1756      4   29  1979        2         NL   M               33   \n",
+       "5       1818      5   30  1979        2         NL   M               32   \n",
+       "\n",
+       "   weight    genus   species    taxa site_type  \n",
+       "1     204  Neotoma  albigula  Rodent   Control  \n",
+       "2     199  Neotoma  albigula  Rodent   Control  \n",
+       "3     197  Neotoma  albigula  Rodent   Control  \n",
+       "4     166  Neotoma  albigula  Rodent   Control  \n",
+       "5     184  Neotoma  albigula  Rodent   Control  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'];\n",
+       "    var y0 = fig.canvas.height - msg['y0'];\n",
+       "    var x1 = msg['x1'];\n",
+       "    var y1 = fig.canvas.height - msg['y1'];\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x;\n",
+       "    var y = canvas_pos.y;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"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",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x112e863c8>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize = (10, 8))\n",
+    "plt.scatter(df['weight'], df['hindfoot_length'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'];\n",
+       "    var y0 = fig.canvas.height - msg['y0'];\n",
+       "    var x1 = msg['x1'];\n",
+       "    var y1 = fig.canvas.height - msg['y1'];\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x;\n",
+       "    var y = canvas_pos.y;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"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",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x10726bf98>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize = (12,10))\n",
+    "plt.scatter(df['weight'], df['hindfoot_length'], s = df['weight']*4, alpha = 0.15, c = df['site_id'], cmap = 'magma')\n",
+    "plt.title(\"Information About Animals Physique and Foot\")\n",
+    "plt.xlabel(\"Weight\")\n",
+    "plt.ylabel(\"Hindfoot Length\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Plotting From the DataFrame\n",
+    "\n",
+    "We can also plot directly from the DataFrame.  Now, the `figsize` argument is a keyword in the scatter function itself.  This demonstrates the range of direct plotting methods available.  For more help with the DataFrame plotting use the built-in help with `df.plot?`.  \n",
+    "\n",
+    "Below, you see a scatterplot and a boxplot produced from the DataFrame with a single call."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'];\n",
+       "    var y0 = fig.canvas.height - msg['y0'];\n",
+       "    var x1 = msg['x1'];\n",
+       "    var y1 = fig.canvas.height - msg['y1'];\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x;\n",
+       "    var y = canvas_pos.y;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"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",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x10729b9b0>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.plot.scatter('weight', 'hindfoot_length', c = 'site_id', cmap = 'viridis', figsize = (10, 8),\n",
+    "                title= \"Plotting from the DataFrame\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'];\n",
+       "    var y0 = fig.canvas.height - msg['y0'];\n",
+       "    var x1 = msg['x1'];\n",
+       "    var y1 = fig.canvas.height - msg['y1'];\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x;\n",
+       "    var y = canvas_pos.y;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"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",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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1EslCCCAAAIIIIAAArUlwCNYtdWeHA0CCCCAAAIIIIAAAl4LkIB43TxhBrd8+fIwAydqBBBAAAEEEEAAgdQFSEBSJ66/HZCA1F+bc8QIIIAAAggggEBcARKQuFKUQwABBBBAAAEEEEAAgYoFSEAqJqQCBBBAAAEEEEAAAQQQiCtAAhJXinIIIIAAAggggAACCCBQsQAJSMWEVIAAAggggAACCCCAAAJxBUhA4kpRDgEEEEAAAQQQQAABBCoWIAGpmJAKEEAAAQQQQAABBBBAIK4ACUhcKcohgAACCCCAAAIIIIBAxQIkIBUTUgECCCCAAAIIIIAAAgjEFSABiStFOQQQQAABBBBAAAEEEKhYgASkYkIqQAABBBBAAAEEEEAAgbgCJCBxpSiHAAIIIIAAAggggAACFQuQgFRMSAUIIIAAAggggAACCCAQV4AEJK4U5RBAAAEEEEAAAQQQQKBiARKQigmpAAEEEEAAAQQQQAABBOIKkIDElaIcAggggAACCCCAAAIIVCxAAlIxIRUggAACCCCAAAIIIIBAXAESkLhSlEMAAQQQQAABBBBAAIGKBSZWXEOgFcybN+81EydO/JOBgYE36RB69fnQs88+e6+mBxYuXHifPt+jcaqWf2HChAl379+/v0vzDAgggAACCCCAAAIIIFCBQN0mII2NjVvl9u+TJk1q7e/v/66+vr6vKvH4JS3r1fhWzd+iBOXlhoaGzykJ+aSWvUMjAwIIIIAAAggggAACCFQgUJePYCnR+D6ZLbz66qvv2bt3b+8zzzxzTAnHjyoR2aqE4+c0PnDo0KEjdtdDyccHVPaOtra2aRU4sykCCCCAAAIIIIAAAghIoC4TECUYyzQ+dezYsd9WMnJEY4ces3rHwYMHO5VwXK9EZG/+7DigQdONM2bMWJBfxicCCCCAAAIIIIAAAgiMT6AuH8FSgvEqJSC3iuxRPYI17+LFi3M1/0UlIi9r2XQlI+cjnP1a16NxemQZkwgggAACCCCAAAIIIDAOgbpMQOTUo/GCbm6sGzTbp+TjTzT9kxrP6S7I1MHl9jFB85P1eTayjEkEEEAAAQQQQAABBBAYh0C9JiDPyGrC0qVLJ+3evfuiuekOR6MSDZt8WuNijY/YzPz58226r6enxx7FKjocP37ctbS0FF1XycKuri535MiRSqqoyrYhxh1izNa4xJ3dKY51dtac21jHEeBnMo5SMmWwHu5o130MlQnUZQLS1NS0Q49dfVs/UL974403fujSpUvXKfmwHrDW63OCkpH3KfH4mh7Vekm9Zd2vz88fPny4uxR1a2urmz17dqnV415uyUca9Y47oJgbhhh3iDFbcxB3zJMygWJYJ4BYRhV4l4FVYVGsKwQsc/MQvUOM2ZolrbjPnDlTZqtTvFCgLhMQ6/lq7ty5y9XN7gNKRI4K5ZKSjgfV69VGTTcsWLBgpt4D2alxhua3KWGx7wRhQAABBBBAAAEEEEAAgQoF6jIBMbOOjo4X9PHjRfwG9IWE67XcRgYEEEAAAQQQQAABBBBIUKAuu+FN0I+qEEAAAQQQQAABBBBAoAwBEpAysCiKAAIIIIAAAggggAAClQmQgFTmx9YIIIAAAggggAACCCBQhgAJSBlYFEUAAQQQQAABBBBAAIHKBEhAKvNjawQQQAABBBBAAAEEEChDgASkDCyKIoAAAggggAACCCCAQGUCJCCV+bF1EYFdu3YVWer3ohBj9luU6BBAAAEEEEAAgeICJCDFXVhagUCIF/MhxlxBE7EpAggggAACCCBQNQESkKrRs2MEEEAAAQQQQAABBOpPoG6/Cb3+mjrdI96+fbuz0YZNmza55ubm3PSqVaucjT4OIcbsoyMxIYAAAggggAAC5QiQgJSjRdmSAtFEo6ury7W3t5cs68uKEGP2xY44EEAAAQQQQACB8QrwCNZ45dgOAQQQQAABBBBAAAEEyhYgASmbjA3GEli+fPlYRbxbH2LM3iESEAIIIIAAAgggEEOABCQGEkXKEwjxYv7JJ58s7yApjQACCCCAAAIIIDAuARKQcbGxUa0JbNu2rdYOieNBAAEEEEAAAQS8FCAB8bJZCAoBBBBAAAEEEEAAgdoUIAGpzXblqGIIrF+/3i1dujQ37tmzZ2jaljMggAACCCCAAAIIpCNAN7zpuFJrAALr1q1zNtqwZMkSt3v37gCiJkQEEEAAAQQQQCBsAe6AhN1+RI8AAggggAACCCCAQFACJCBBNRfBpiWwevXqtKqmXgQQQAABBBBAAIGIAAlIBIPJ+hW46aab6vfgOXIEEEAAAQQQQCBDARKQDLHZlb8Cu3bt8jc4IkMAAQQQQAABBGpIgASkhhqTQ0EAAQQQQAABBBBAwHcBesHyvYWILzWB7du3Oxtt2LRpk2tubs5Nr1q1ytnIgAACCCCAAAIIIJC8AAlI8qbUGIhANNHo6upy7e3tgUROmAgggAACCCCAQLgCPIIVbtsROQIIIIAAAggggAACwQmQgATXZASchsDy5cvTqJY6EUAAAQQQQAABBAoESEAKQJitT4G1a9fW54Fz1AgggAACCCCAQMYCJCAZg7M7PwX6+vr8DIyoEEAAAQQQQACBGhMgAamxBuVwEEAAAQQQQAABBBDwWYAExOfWIbZUBSZOnOgaGhpyo+0oP23LGRBAAAEEEEAAAQTSEeBKKx1Xag1A4NKlS0NRWvIxMDAwNM8EAggggAACCCCAQDoC3AFJx5VaEUAAAQQQQAABBBBAoIgACUgRFBbVn0BjY2P9HTRHjAACCCCAAAIIVEGABKQK6OzSP4HnnnvOv6CICAEEEEAAAQQQqEEBEpAabFQOCQEEEEAAAQQQQAABXwV4Cd3XliGu1AS6u7tdb2/vsPq7urrcmTNnhi2zmaamJjdlypQRy1mAAAIIIIAAAgggMD4BEpDxubFVwAJz5851x44di3UEbW1trrOzM1ZZCiGAAAIIIIAAAgiMLUACMrYRJWpMoKOjY9gdELvxMXu2c0eOONfSMvxg7Q4IAwIIIIAAAggggEByAiQgyVlSUyAC9khVsceqLPkoTEACOSTCRAABBBBAAAEEghHgJfRgmopAEUAAAQQQQAABBBAIX4AEJPw29O4Idu3a5V1MBIQAAggggAACCCDghwAJiB/tUFNRkIDUVHNyMAgggAACCCCAQKICJCCJclIZAggggAACCCCAAAIIjCbAS+ij6bAutsD27dudjTZs2rTJNTc356ZXrVrlbPR5mD7duR07jrnp06/2OUxiQwABBBBAAAEEakKABKQmmrH6BxFNNOxL/drb26sfVMwIGhudW7TokrNPBgQQQAABBBBAAIF0BXgEK11fakcAAQQQQAABBBBAAIGIAAlIBIPJZASWL1+eTEXUggACCCCAAAIIIFBzAiQgNdek1T8gEpDqtwERIIAAAggggAACvgqQgPjaMsSFAAIIIIAAAggggEANCpCA1GCjckjlCfT1Obd//0RnnwwIIIAAAggggAAC6QqQgKTrS+0BCJw759zKlVc7+2RAAAEEEEAAAQQQSFeABCRdX2pHAAEEEEAAAQQQQACBiAAJSASDSQQQQAABBBBAAAEEEEhXgAQkXV9qRwABBBBAAAEEEEAAgYgACUgEg0kEEEAAAQQQQAABBBBIV2BiutVTOwLVE+judq63d+z9nzlzuUz+c+wtnGtqcm7KlDglKYMAAggggAACCCAQFSABiWowXTMClnxcdZVz9hl3mD07bsnLycepUyQh8cUoiQACCCCAAAIIXBao2wRk0aJFvzYwMPAJMdglaoNGzQ786rPPPvvZhQsX3qf592icqmVfmDBhwt379+/v0jxDIAJ258OSjyNHnGtpGTvoo0ePulmzZo1dUCXsToklK7YP7oLEIqMQAggggAACCCAwJFC3CYgSi6UaP6qE4+NDGppQ8vEufby1r6/vlokTJ77c0NDwOZX7pJa9I1qO6TAELPmIk4A0Nw/EKhfGURMlAggggAACCCDgr0A9v4S+VMnF7sKm0bK1Gh84dOjQEbvroeTjAypzR1tb27TCsswjgAACCCCAAAIIIIBAeQJ1mYAMJhMLRfVu3fF4ccGCBQc0vt/olHBc39/fvzfPeECDphtnzJixIL8sq89du3ZltSv2gwACYwjw8zgGEKsRQAABBBCIKVCXCYiSidcq0XhE4yYlI3P0eYfuevyykpFfkdt0vfNxPuLXr3U9WjY9siyTSS54MmFmJwjEEuDnMRYThRBAAAEEEBhToC7fAdFNjQ7JrDAdvQNiH99S8rFBichPKtk4p8+ptnBwmKD5yZo+m1/AZxgCk61/gTMx+uHV4TR0qY+BuP3w6iX0yU798Dr64Q3jTCBKBBBAAAEEEPBJoC4TkPnz59+sOxo/qkTkd/KNoSRjipKPC5p/WuNijY/YOpW16b6enh57FKvocPz4cb3AHKOrpaJbD19of2XN/6V106ZNQyuXL1/ubAxh6NLF/BHrfqqKQ1dXg+twt7iW2cdiRRGv/6vLVVlLH3Jt7ujRf3X28no1Bx+sx3P8ocTNz+N4WjeZbUI5RwqPNsS4Q4zZ3Im78OxLbx7r4bZ23cdQmUBdJiDq3eqs3vP4Td316FAS8rf6XCbGe5SE/LI+ZyoReZ8Sj6+pzEuNjY336/Pzhw8fLvmNEq2treqWtYwvkRilze68805nY37YuHFjfjKYT0s+kvIY70HbzYzXKAU5caQ3Vu9W5XbDO292kzsxa0qsusd7DHG288E6TpyFZUKJm5/HwpbLbj6Uc6RQJMS4Q4zZ3Im78OxLbx7r4bZn4j4xMXwz5iICdZmA7Nu374CSjjVyWK9Pu8I/oeTjPj2O9X813aAX0mfqDslOjTM0v62pqcm+E4QhMIEee0SqxcaxAx9obo7XX+9gVT1jV0kJBBBAAAEEEEAAgSICdZmAmIPufGzTh42Fw4ASkfVaaGNVh1AeuaoqEjtHICMBfh4zgmY3CCCAAAI1L1CXvWCF0qpc8ITSUsRZDwL8PNZDK3OMCCCAAAJZCJCAZKHMPhBAAAEEEEAAAQQQQCAnULePYNH+9SEQ9z0x6zUrbtm45epDmKNEAAEEEEAAAQTKEyABKc+L0oEINNnXdGiI3zlZOR3x6htA9G57fh+X98S/CCCAAAIIIIAAAnEESEDiKFEmOAFLEC7oW116Y3wPod3RsETFvrok7te5WPJh+2BAAAEEEEAAAQQQKE+ABKQ8L0oHJGAJQjlJgiUfcROQgBgIFQEEEEAAAQQQ8EqAl9C9ag6CQQABBBBAAAEEEECgtgVIQDxu3w0bNngcHaEhgAACCCCAAAIIIFC+AAlI+WaZbbFtW7HvScxs9+wIAQQQQAABBBBAAIHEBUhAEielQgQQQAABBBBAAAEEECglQAJSSqZKy9evX++WLl2aG/fs2TM0bcsZ0hGYPt25HTuOOftkQAABBBBAAAEEEEhXgF6w0vUtu/Z169Y5G21YsmSJ2717d9l1sEF5Ao2Nzi1adMnZJwMCCCCAAAIIIIBAugLcAUnXl9oRQAABBBBAAAEEEEAgIkACEsHwbXL16tW+hUQ8CCCAAAIIIIAAAghUJEACUhFfuhs/99xz6e4gpdp37dqVUs1UiwAC5Qrw81iuGOURQAABBNIWIAFJW7iC+nfu3FnB1tXblAue6tmzZwQKBfh5LBRhHgEEEECg2gIkINVuAfZfdYG+Puf275/o7JMBAQQQQAABBBBAIF0BesFK17fs2teuXevyX0B48uRJ19ramqvD3gfZvHlz2fVltcH27dudjTZs2rTJNTc356ZXrVrlbPR5OHfOuZUrr3anTzvX0uJzpMSGQDyBkH8e4x0hpRBAAAEEQhYgAfGs9aJJxsyZM93x48c9i7B4ONFEo6ury7W3txcvyFIEEEhdgJ/H1InZAQIIIIBABQI8glUBHpsigAACCCCAAAIIIIBAeQIkIOV5ZVp6xYoVme4vqZ0tX748qaqoBwEEKhTg57FCQDZHAAEEEEhcgAQkcdLkKrzuuuuSqyzDmrjgyRCbXSEwhgA/j2MAsRoBBBBAIHMBEpDMyePvMP8yevwtKIkAAggggAACCCCAgN8CvITud/sQXQoC3d3drre3d6jmnh7n7r77tOvpucKdOTO0ODfR1NTkpkyZMnwhcwgggAACCCCAAALjFiABGTddOhuuX7/ebdmyJVf5nj173NKlS3PTa9ascevWrUtnp3VW69y5c92xY8dGHPWDD45Y5Nra2lxnZ+fIFSxBAAEEEEAAAQQQGJcACci42NLbyJKMfKKxZMkSt3v37vR2Vqc1d3R0DLsDYgxHjx51s2bNGiFid0AYEEAAAQQQQAABBJITIAFJzpKaAhGwR6oKH6uyL05s4VsIA2lBwkQAAQQQQACBkAV4Cd3j1rvyyis9jq50aBs2bCi90tM1c+bM8TQywkIAAQQQQAABBGpLgATE4/Z8+eWXPY6udGj03lXahjUIIIAAAggggEC9C5CA1PsZwPEjgAACCCCAAAIIIJChAAlIhthxdmW9YFnPVzbme8GyaVvu8xBi3A0NDS4/mm1+2j4ZEEAAAQQQQAABBNIR4CX0dFzHXWuovWCFGPfAwMBQO1nSEZ0fWsEEAggggAACCCCAQKIC3AFJlJPKEEAAAQQQQAABBBBAYDQBEpDRdKq8bvXq1VWOYHy7DzXu8R0tWyGAAAIIIIAAAgiUI0ACUo5WxmXvueeejPeYzO5CjPsNb3hDMgdPLQgggAACCCCAAAKjCpCAjMrDynoRePzxx+vlUDlOBBBAAAEEEECgqgIkIFXlZ+cIIIAAAggggAACCNSXAAlIfbU3RxsRWLlypZs2bVpu7O7uHpq25QwIIIAAAggggAAC6QjQDW86rtQagMCOHTuGopw6dao7f/780DwTCCCAAAIIIIAAAukIcAckHVdqRQABBBBAAAEEEEAAgSICJCBFUFhUfwLLli2rv4PmiBFAAAEEEEAAgSoIkIBUAZ1d+ifw2te+1r+giAgBBBBAAAEEEKhBARKQGmxUDql8gZ07d5a/EVsggAACCCCAAAIIlC1AAlI2GRsggAACCCCAAAIIIIDAeAVIQMYrx3bBC6xdu9a1trbmxpMnTw5N23IGBBBAAAEEEEAAgXQE6IY3HVdqDUBg8+bNQ1HOnDnTHT9+fGieCQQQQAABBBBAAIF0BLgDko4rtSKAAAIIIIAAAggggEARARKQIigsqj+BFStW1N9Bc8QIIIAAAggggEAVBEhAqoBe67vctWtXcIfY3t4eXMwWcIjWQUITNAIIIIAAAggkJkACkhglFeUFuCjOS6T/iXX6xuwBAQQQQAABBJIVIAFJ1pPaEEAAAQQQQAABBBBAYBQBesEaBYdV8QW2b9/ubLRh06ZNrrm5OTe9atUqZyNDcgJYJ2dJTQgggAACCCCQvQAJSPbmNbnHaKLR1dXlQn2nIoTGwTqEViJGBBBAAAEEECglwCNYpWRYjgACCCCAAAIIIIAAAokLkIAkTkqFy5cvByEjAawzgmY3CCCAAAIIIJCYAAlIYpRUlBcI8aI41N6kQrTOnyd8IoAAApUIhPr/diXHzLYI1IoACUittCTHUZEAv8gq4mNjBBBAIHMB/t/OnJwdIpCYAAlIYpRUhAACCCCAAAIIIIAAAmMJ0AvWWEKsr1kBurOt2ablwBBAoEYF+H+7RhuWw6o7gbpPQNra2qbNmDFjt1p+44EDB9rtDFi4cOF9+niPxqkDAwNfmDBhwt379+/vsnUMtSNAd7a105YcCQII1IcA/2/XRztzlLUvUPePYE2fPn2Dmnl+vqmVfLxL02/t6+u7paGhYbaSjxYlIZ/Mr+cTAQQQQAABBBBAAAEExi9Q1wnIokWLfkpJxnyNj+YJNb1W4wOHDh06Ync9lHx8QOvusDsl+TJ81p4AvUnVXptyRAggUNsC/L9d2+3L0dW2QN0mIHPnzp2j5OL3Ll269LP9/f0D+WbWsus1vzc/r8eyDmi6UY9pLcgv47P2BPhFVnttyhEhgEBtC/D/dm23L0dX2wL1moBMmDhx4l8q2VjX0dHxQkETz9BjV+cjy/p1R6RHy6ZHljGJAAIIIIAAAggggAAC4xCoy5fQ9Z7Hh5VUHNXNjb8uYnZOicnUyPIJmp+s+bORZYlOdnd3u97e3hF1dnV1uTNnzoxY3tTU5KZMmTJiedYLyonbl5izNmJ/CCCAAAIIIIAAAsMF6jIBEcHPKKm4WonIdwY5mpWQ3KJ3Qm7Tcnv8arHGR2zd/Pnzbbqvp6fHHsUqOhw/fty1tLQUXRdn4bJly9yJEyfiFM2VaW1tdd/85jdjl0+rYDlx+xJzKQtL9o4cOVJqtbfLiTu7psE6O2vbE97ZeWOdnXWo5zbnyPBzxK77GCoTqMsERHc+ro+yLViwYKfm/1HL2zX9biUj71Pi8TW9C/JSY2Pj/fr8/OHDh7uj20Sn7eJ69uzZ0UVlTT///PMj7oDYjQ+r0q6JC3MbX+4mlBO3LzGXahhLPippw1L1pr2cuNMWfqV+rF+xyGIK7yyUL+8D6+ysbU8heocYc5rWxZ5OyfYsCn9vdZmAFDabEo6hl9CfffbZTysJmal3PnZqnKGy23TxbN8Jktpgj1OVeqTKko/CBCS1QMqsONS4yzxMiiOAAAIIIIAAAggkKEACIkzd+fihiOmAkpD1mreRAQEEEEAAAQQQQAABBBIUqNdesBIkpKpaENiwwb6PkiErgV27dmW1K/aDAAIIIFCnAvyu8bfhSUD8bRsiy1Bg27ZtGe6NXfFLgXMAAQQQQCBtAX7XpC08/vpJQMZvx5YIIIAAAggggAACCCBQpgDvgJQJllXx6frawx07jrnp06/OapeJ7CekuNevX++2bNmSO+49e/a4pUuX5qbXrFnj1q1bl4gHlbwisH37dmejDZs2bXLNzc256VWrVjkbGRBAAAEEEKhUgN81lQpmsz0JSDbOZe+lsdG5RYsuOfsMaQgpbksy8onGkiVL3O7du0OiDi7WaKJhfcq3t7cHdwwEjAACCCDgtwC/a/xun3x0PIKVl+ATAQQQQAABBBBAAAEEUhcgAUmdmB2EILB69eoQwhwRY6i9dy1fvnzEsbAAgVoQ4KXXWmhFjqFWBPhd429LkoD42zZElqHAPffck+HekttVqL138UshuXOAmvwSIAHxqz2Ipr4F+F3jb/uTgPjbNkSGAAIIIIAAAggggEDNCfASuqdN2tfn3P79E11bmwvqRfRQ4/b0NCgaFr13FWVhIQJVE6DXnarRs2MEEAhUgATE04Y7d865lSuvdqdPO9fS4mmQRcIKNe4ih+LtInrv8rZpCKxOBeh1p04bnsNGAIFxC/AI1rjp2BABBBBAAAEEEEAAAQTKFSABKVeM8gh4JBBq710eERIKAokK8NJropxUhgACNSpAAlKjDcth1YfAY489Vh8HylGOW4BemcZNN64NSUDGxcZGCCBQZwIkIHXW4BxubQk8/vjjtXVAHE3iAiQgiZNSIQIIIIBAhQK8hF4hYDmbd3c719sbb4szZy6Xy3+OtVVTk3NTpoxVanzrQ417fEfLVggggAACCCCAAAJpCpCApKkbqdsu4q+6yjn7LGeYPTteaUs+Tp1KPgkJNe54amGWWrlypXv00UdzwXergaZNm5abvvXWW92OHTvCPCiiTlSAbmET5aQyBBBAAIGEBUhAEgYtVZ3d+bCL+SNH4nere/ToUTdr1qxSVQ4tt7sklqjYPpK+CxJq3EM4NTgRTTKmTp3qzp8/X4NHySFVIkC3sJXosS0CCCCAQNoCJCBpCxfUb9/pEfd7PZqbB2KXLdhN4rOhxp04BBUigAACCCCAAAIIVCTAS+gV8bExAtUVWLZsWXUDYO/eC9Ark/dNRIAIIIBA3QmQgNRdk3PAtSTw0EMP1dLhcCwIIFAFAXpKqwI6u0SgzgVIQOr8BODwEUCgtgW4uKzt9k3i6DhHklCkDgQQKEeAd0DK0aqw7GSnt9DPxOyHV/tq6OpS+cH+eEfbt4pMduqH16XTD2+ocY9GFto66+2qt0gfzl06R84UOUea1C/zlKR7JAgNjXgRQAABBBBAwEsBEpAMm6XDzXUts4/F3uPY/V9drkrvtbtDrk3/dsauu5yCocZdzjH6Xnbu3Lnu2LH4505bW5vr7EznfPDdivicoxtezoKxBDhHxhJiPQIIpClAApKmbkHdc12HO3GkN3bPVuV0wztvdpM7UbC/pGZDjTup4/ehno6OjhF3QHp6nLvvvtPuIx+5wk2ePDxKuwPCUL8CdMNbv20f98g5R+JKUQ4BBNIQIAFJQ7VEnT32iFSLjSUKFCweaG6O3WevrkVTG0KNOzWQKlRsj1MVPlJlT149+GCLu//+2KdJFSJnlwgggAACCCCAwHABXkIf7sEcAgggUFMCdMNbU82ZysFwjqTCSqUIIDCKAAnIKDisQgABBEIX4OIy9BZMP37OkfSN2QMCCAwXIAEZ7sEcAggggAACCCCAAAIIpCjAOyAp4harukiPqcWK5ZZ1dTXE64U3Rk+9JXcSc0Woccc8PIohgAACCCCAAAIIZCRAApIRdL5Totmzy9lh3I549Q0gerc9v49y9jBW2XydocU91nGxHgEEEEAAAQQQQKA6AiQgGblbgnDhglNXqvF2aHcc7KL/yJF4PRxZopDG986FGnc85bBLTZ/u3I4dx9z06VeHfSBEjwACCCCAAAJ1JUACkmFz28V8uUlCi7rstbGaQ6hxV9Msi303Njq3aNElZ58MCCCAAAIIIIBAKAK8hB5KSxEnAggggAACCCCAAAI1IEACUgONyCEggAACCCCAAAIIIBCKAAlIKC1FnAgggAACCCCAAAII1IAACUgNNCKHgAACCCCAAAIIIIBAKAIkIJ621Cs9HHkaYImwQo27xOF4vbivz7n9+yc6+2RAAAEEEEAAAQRCESAB8bSlQu3hKNS4PT0NRg3r3DnnVq682tknAwIIIIAAAgggEIoACUgoLUWcCCCAAAIIIIAAAgjUgAAJSA00IoeAAAIIIIAAAggggEAoAiQgobQUcSKAAAIIIIAAAgggUAMCJCA10IgcAgIIIIAAAggggAACoQhMDCXQeosz38NRW5tz9mJ3KEOocfvk293tXG/v2BGdOXO5TP5zrC2ampybMmWsUqxHAAEEEEAgLIFu/eLsLfKLs6ury50p8kuySb8Qp/ALsaqNTAJSVf7SO8/3cHT6tHMtLaXL+bYm1Lh9cbTk46qrnLPPuMPs2fFK2v+1p06RhMTTohQCCCCAQCgCc+fOdceOHYsdbpv+utvZ2Rm7PAWTFyABSd6UGhEYt4D9AceSjyNH4iWeR48edbNmzRpzf/YHIEtUrH7+6DMmFwUQQAABBAIS6OjoGHEHJP97r9jvU7sDwlBdARKQ6vqzdwSKCthdrzh3vpqbB2KVK7oTFiKAAAIIIFADAvY4ValHquL+Pq0BhqAOgZfQg2ougkUAAQQQQAABBBBAIGwBEpCw24/oEQhSYNeuXUHGTdAI1KIAP4+12KocEwJ+C5CA+N0+RIdATQpwwVOTzcpBBSrAz2OgDUfYCAQswDsgHjRese7jenqcu/vu066n5wp1ITc8SF+6jysnbl9iHi7p59xkp7fQz8Toh1fhN6iLwREnSLHD0jk02dlLd/TDW4yHZQgggAACCCCQnQAJSHbWJfc0WvdxDz44cjNfuo8rJ25fYh6p6d+SDjfXtcyO153g2P1fXT4+68n5kGvTv9XrdnD79u3ORhs2bdrkmpubc9OrVq1yNjIggEB2Avw8ZmfNnqojMH26czt2HHPTp19dnQDY66gCJCCj8mSzslj3cbbnUl2s+tJ9XDlx+xJzNi1a2V7mug534khvrN6tSp0jhRHYXbR5s5vcicIVGc5HEw37cqj29vYM986uEEAgKsDPY1SD6f7LZVwAAEAASURBVFoUsC9xXrToUlBf5lyL7VDqmEhASslkuLxU93H2F+KWOH2xZhhrdFehxh09Bh+ne+wxqRYbx45uwO4ixDxH9FQfAwIIIIAAAgggUHUBXkKvehOUDmDOnDmlV3q85nWve53H0RGaDwLLly/3IYyyYgj1Rd1Q4y6rcShckUCIP48VHTAbI4BA1QVIQKreBLUXwMDAQO0dFEeUqECIFzyhXsiHGneiJxyVjSoQ4s/jqAfESgQQ8F6AR7C8byICrEeBwp7PShl0dTXE6wSroCe1UvWxHAEEEEAAAQQQSFuABCRt4TLrb2hoGLZFdN7nOwsTJkxw0fjycdtnf3//sGNiprRAk/WUq2H27MufY/8btx8sdcCr10ry9Y9dLyVMINSegkKNm7MOAQQQSEqgr8+5/fsnujZ1AGkvpDP4JVC3CcjChQt/QhfMH9UF8uv0+Z9qlvZnn332T615tO4+fbxH41St+4Iuru/ev3+/vnAh/UH7G9qJXbxH54dWeDgRTTJCits3SksSLlxwrjfG14DYXRJLVI4cifceuiUfVj9DfIFQewoKNe74LUNJBBBAYHSBc+ecW7nyanf6dLzfkaPXxtqkBeoyAZk/f/48XST/lS7uVx84cODrSji+R7CPLVq06HEtu1nTb+3r67tl4sSJL6vc57Tsk1r2jqTxqQ+BYgKWJJSTKFgnWDE7wiq2O5YhgAACCCCAAAKZCtTlS+gHDx48NHny5NfojsfXpW3PPL1a4yUlG2c0rtX4wKFDh47YXQ8lHx/Qujv0RXrT9MkQQ0B+MUpRBIGwBEJ9UTfUuMM6O4gWAQQQQKAcgbpMQAzoySefPLdkyZKrdPfDHnaxr2fesG/fvgNKOK7X40R7rYwNukNyQB+NM2bMWJBbkOE/SpIy3Ftyu3r++eeTq4yaalIgxJ6ZQr2Qv//++4M8h0I8R4KEJmgEEECgCgJ1m4CY9VNPPfWy7mxM1V/sX6/Zu5SMvFOf0/XOx3lbPzj0a32Plk3PL8jqs6eHr47Lypr9ZCvAxWV23vrDSnY7S3BPnCMJYlIVAggg4JlAXb4DEmmDgYcffviS5h9X8vEZ3f1Yo2TjnD6nRspM0LzdijgbWcYkAggggAACCCCAQMYC3d3xO2qx0OJ2a29l6azFFLIZ6jIBWbBgwZt1R+P9esfjtjyzJRlKPk5p/mmNizU+Yuv0wrpN9+luhD2KVXQ4fvy4XgLWm8AJDIrNRe98KKZcrfY4lt5ZSWAP6VfR1dWlnpnUNVNAQ4gxWxeDW7f2uu98pynXy4fv3PYX7fxftTdt2jQUrj3aFMLjTSGdI6tXr3b5Ox/qUMOpQ42c9+LFi922bduG7H2bCP0cMc+QzpN8+4cYc6jWocbtyzliyceSJdfoOin+Azzxu7V3bvLkfj0d0zlmRzB23cdQmUBdJiB6x+OburD/bt31uEuveGzSRf8bNb9WlD+mROQGTb9PicfXVO6lxsbG+/X5+cOHD+u0Lz60traqO9TYX9xQvJLBpd320zU4WPKhePKzwXxa8pGUR1YHHWLMZtPYGI71nXfe6WzMDxs3bsxPBvEZ0jmyZ8+eIVNLPi5dshu9/g+hnyMmHNJ5kj8jQow5VOtQ4/blHLG7GfZ0etzu548ePepmzZqVP9VH/bzctf0E19o6e8yeJc+Uc1tl1L3W78q6TEDUw9UJuwuiC/w/VBLyCTX/85p+p+6I2F2Pb2jdTN0h2alxhua3NTU1vad+TxGOHAEEEEAAAQQQ8Ecgbvfzzc0DYyYT/hxVfUVSlwmINbEeZ/pXffzXIs09oHXrtdzGqg6h9oJVVTR2HoRACI9cBQEZI0h77CrEgXMkxFYjZgQQQCCeQPyH6OLVR6kEBaLPySdYbepV3Xvvvanvgx0gkLXAhg0bst5lIvvbu3eoV/FE6suqEhKQrKTZDwIIIJC9AAlI9uax95h/YTf2Bp4U3LlzpyeREIavAiGe2z6/vO1rOxMXAggggAACxQTq9hGsYhgsQyAkAesFa//+ia6tzV5GDylyYkUAAQQQQGB8ApOdOus5Y98hPfbQoF45Y/fDqxfcJ7smVTpl7IopUbEACUjFhMlWsH37dmejDfYIVnNzc2561apVzkZfh7Vr1w5173ny5En1ItGaC9W6A928ebOvYQcd17lzzq1ceXWuC96EeoFO1SPEc3v9+vVuy5YtORfrWWrp0qW56TVr1rh169al6lVJ5daDXnSIzofYs170WJhGAIH6Fuhwc13L7GOxEOL1f3W5KvsyhUNOf9FznbHqplBlAiQglfklvnU00bB+t9vb2xPfRxoVRpOMmTNnOvrITkM57DpDPLctycgnGkuWLHG7d+8OohGiSYYlH9H5IA6AIBFAAIESAnNdhztxpDdW71bldsM7b3aTO1FivyxOVoAEJFlPakMAAQQQQAABBBBISaDHHpFqsXHsHQzYUyRlPCKgrxhhyEiAl9Azgh7PbkLtBWbFihXjOVy2qSOBEM9te5yQAQEEEEAAAQQqFyABqdwwtRq2bt2aWt1pVnzdddelWT1114BAiAnIPffcE6T8Cy+8EGTcBI0AAgggULsCJCAet22o3dnSXanHJxWhIYAAAggggAACVRbgHZAqNwC7RyCOQHd3t+vtHd7tYI8eVr377tOup+eKEb0MNjU1uSlT6Eowjm2tlCl2jtixWWcWZ86of8mCgXOkAIRZBBBAAIHMBEhAMqOOt6NQu7MNtbvSeK1S/VJz5851x44V73bwwQdHxtemLwfp7KQrwZEytbtktHOk2FFzjhRTYRkCCCCAQBYCJCBZKJexj1C7sw21u9IymqaqRTs6OkbcAbGASnUxaH/dZqgvgWLniN34mD3buSNHRnYEwzlSX+cHR4sAAgj4JEAC4lNrEAsCJQTscapij1TZF1W2lNHFYInqWVwDAqXOETs0O0U4TWqgkTkEBBBAoEYEeAnd44YMtTtbuiv1+KQiNAQQQAABBBBAoMoCJCBVboDRdv+Wt7xltNWsQ8CR7GV3EuzatSu7nbEnBBAYU4CfyTGJKICAtwIkIN42jXOh/udKN7zZnVT79u3Lbmd1vqdQfx7rvNk4/BoW4GeyhhuXQ6t5Ad4Bqfkm5gARQKDWBNQrszolGPuo8r3v5j/H3sI567+AHpzjSFEGAQSqJRD3/7SuroYR3dSXijlunaW2Z3l5AiQg5XmlXnr79u3ORhs2bdrk7CVjG1atWpUbczMe/kM3vNk1ys033+yefPLJ3A77+vrcxImXf4xvuukm98QTT2QXSB3sycefR0s+rrrKOfuMO1hPWHEHSz5OnSIJietFuWwFfPyZzFagvveW7+Ax/v9ps8oCs///8vsoa0MKly1AAlI2WbobRBMN+wKx9vb2dHeYUO10w5sQZIxqokmGJR+XLl2KsRVFxiPg48+j3fmw5KNY17rFjrFUV83FytpfAO0Xu+2DuyDFhFhWbQEffyarbVJP+7f/ly5ciH8HuFQ35KXMuANcSib55SQgyZtSIwIIIJC6QNyudZubB+iCN/XWYAcIIJCVgCUh5fyBJO7/lVnFz34uC/ASusdnwvLlyz2OrnRo9MxU2ibpNYsXL066SuorIRDqz2OJw2ExAsEL8DMZfBNyAHUsQALiceNv3brV4+hKh2bvIjBkI3D77bdnsyP2MvTeDRTZCNDDUTbOtpcNGzZkt7ME93T//fcnWBtVIYBAlgIkIFlql7mvnTt3lrmFH8W5cMiuHejyGOvsBLLdE/+PZOcd6v8jdEOe3TnCnhBIWoB3QJIWpT4EEEAgZYHJrtt1depNcb00PtZw7thZd6YhRkFVpH4v3GSnfnidHrJmQAABBBBAICUBEpCUYMdb7dq1a13+r1EnT550ra2tuarsvYrNmzePt9rUt6NrxNSJh3ZAl8dDFKlP+GhtvbR0uLmu7YZjsY6/JVapy4WsbIdrUzeUnWVslVxR/h9JznKsmnw8t8eK2dbTDXkcJcqYwPTpzu3YcUyfVwPioUCDhzEFE9L8+fNvnjBhwu4tW7a4G2+8MfG4Z86c6V566aXE6027wrvuustt3Lgx7d0kWv8R9Wk6O37H4onuu5LKlixZ4p566qlKqqjKtiF6+2Td/XK36z079jcR2h2N629w7pmnnb5TKF5TN81oclOurP4dkBD/HzFhzu1451kSpULthjzEcyTEmNP8edy7d69bs2aN6+/vX3rw4MEnkjif660O7oDUW4tzvAggELyAJQixkgQ9eaUcxDVf4+iKN/hW5wAQQACB2hHgJXSP23LFihUeR1c6NLpGLG2T9Bq6PE5atHR9WJe2SWMN/4+koVq8zlDPbbohL96eLEUgBAESEI9b6brrrvM4utKhceFQ2oY14Qrcc8894QYfYOT8P5Jdo4XadfqBAweyQ2JPCCCQqAAJSKKcyVaWfxk92VqprZYEOEdqqTU5FgSqIxBql8cXL16sDhh7RQCBigV4B6RiQipAAAEEqi/Q3a0X03uHv5h+ZrD33fxnNMomdac1ZUr1XzaPxsQ0AgggkJRAX59z+/dPdG1tzjU2JlUr9SQlQAKSlGRC9YTaNWJCh081MQQ4R2Ig1WGRuXPnumPHinfNW6yDtzb9Vu7srE53u3XYPN4dcqhdHlviHL3z0dBwuTPPSZMmjUjAvUMnoEwFzp1zbuXKq93p03TCkSl8zJ2RgMSEyqrYunXrnI02WLefu3fvzmrX7CcQAc6RQBoq4zA7OjqKXoAdPXrUzZo1a0Q0diHHUL8Cq1atcjba0KX+mtvb24PAiN7ls+RjYGAgiLgJEgEEhguQgAz3YA4BBBAIUsAepyr2SFWzvgCkpaWcryMM8vAJGgEEEEAgIAFeQve4sehi0OPG8SS0ULvPvPfeez0RjB/Ghg0b4hf2qOScOXM8iiZ+KKG+GB3/CP0pedVVV/kTDJEggEBdCJCAeNzMV155pcfREZoPAqF2Dbtz504f+MqKgR7HyuKquDAJSMWEsSs4depU7LIURAABBJIQIAFJQpE6EEAAAQQQQAABBBBAIJYA74DEYsquUKg9k2QnxJ5CFVi7dq3L30U4efKka21tzR2KPUa2efNmLw8r1B7H8j0D5VGj8z6/tMv/f/kWS/8zVOvouWxK0Xmfz+30W5Q9FApMnuzcr/3aaTd58hWFq5j3QIAExINGiIYQas8k0WNgGoFiAtEkY+bMme748ePFinm1LNQex6IXYnaBFp33CrggGP7/KwBJcTZU6+i5HNK5nWJTUnUJAUtA7r33DAlICZ9qL+YRrGq3APtHAAEEEEAAAQQQQKCOBEhAPG7s5cuXexwdoSEwfoEVK1aMf+MqbRlqj2NV4qp4t/z/VzFh7Aqwjk1FQQQQSEiABCQhSKpBAIH4Alu2bIlf2JOSoXxRWyFXY2Nj4aIg5rdu3RpEnLUQ5Ic//OEgD+OFF14IMm6CRgAB50hAPD4L6IbS48YhtIoE+vv7K9q+Ghv39fVVY7cV7zPUuEPsqrnixqpSBVzIVwme3SJQxwK8hF7Hjc+hI4AAAggg4LtAd3e36+3tHRFmV1eXO3PmzIjlTU1NbsqUKSOWs6B2BThHwmtbEhDP2izUrhE9YyQcDwXsUaDonY9895kTJkxwvv6VfuLEicNiy8dsx3Lp0iUPlS+HFGrcIXbV7O1JMEZg8+fPdx0dHblS1rOU/RzaMHfuXHfw4MHctC//WEzHjh2LHU5bW5vr7OyMXZ6C4QtwjoTXhiQgnrVZqF0jesZIOB4KRJOMULrPjCYZocRsTR9q3CF21ezhj1qskKJJhiUf0T8OxKogw0KWKBXeAbEbH7NnO3fkiHMtLcODsTsgDPUlUOwcMYGjR4+6WbNmjcDgHBlBkvkCEpDMydkhAggggAACCMQVsMepSj1SZclHYQISt17K1Y5AqXOkublZ50dBhlo7hx30kfASusfNR9eIHjcOoVUkkH/co6JKMt441N6kQo07xK6aMz4lE9vdnDlzEquLihBAAIE4AiQgcZQog4CnAqH2lHb48GFPRUuH9dxzz5Ve6fGaxYsXexxd6dBC7fZ4w4YNpQ/K0zWPPPKIp5ERli8CIZ7XZhdq3L60e5pxkICkqVth3aFeXFZ42GxehgDnSBlYdVp03759dXrk1Tnsbdu2VWfH7BWBFAVCPa9DjTvFpvSmat4B8aYpCASB2hMop2tEn7rOLBY3XX6mc34Ws7Y94Z2dt0/W3S+ry92zI7vcLdRQD7yu2c4T6+xqZE+8hcVd0wx1zXslXfOOgGEBAlUSIAGpEnyp3dINbykZlucFQjpHyuka0aeuM0ONO3+O3Hzzze7JJ5/MzVrvY9Ytrw033XSTe+KJJ3LTvvxTjrXF7NN5kjdcv36927JlS252z549bunSpbnpNWvWuHXr1uWLefFZjnfW1vq6D3fqqrnuajd2l7v2WnEu77ghHuuLrs296kKnXmaPV55SzoV0XkfbK9S4o8dQD9MN9XCQaR2j+lG/WS/T7rZfPDfeeGPiu7nrrrvcxo0bE6837QqPqF/E2dY/YkBDiDEbr+/nSLG/bpfqPtPnOyClYrY28Clui6dwsOQj2i1v4fpqz5dzjlisvnsvWbLEPfXUU9VmLbn/Qm+fzm2L5TVXdLtDT/c6dV405vDii51KSK8Zs5zdLZl3Q5M7cXqKFz1mhfj7xvfzutRJkFbce/fudfYHBnVfvVRdWvv1V51SGJ4t5w6IZw1COAjUkkCprhHtGH3uPrNU3D7HHOp5U8ra93Ok1rx9Obd73BTXfE28ROH0wGnXMsvuhYwxKLHpGaMIqxFAIFsBXkLP1rusvdENb1lcdVmYc6Qum72sgw61F6yyDtKjwqtXr/YoGkJBIBmBUM/rUONOptX8roUExOP2+dSnPuVxdITmg8DWrVt9CIMYPBa4/fbbPY6u9kJ77LHHau+gOKK6F7D3x0Ic7rnnnhDDrouYSUA8bubHH3/c4+gIzQeBnTt3+hAGMXgsQDeU2TYO/29n683eshGgy/dsnOtpL7wDUk+tzbEikJJA3K4zbfc+dZ9pve70jt3jp7OXY23If16eG/3fpiZHjzsRorjWtkneOf8ZqaboJNYjWeJ6543znyNrGrkkbe+4sXR1NQydKyOjfGVJ3Ppe2YIpBBBIW4AEJG3hMutfuXKle/TRR3NbWW8l06ZNy03feuutbseOHWXWRvFaFFi7dq3L/1X75MmTrrW1NXeY9qzr5s2bMz9ku9CJ23WmBedL95kW91VXOWefcYdyOnez7j5PnapOEuJbN5TjsbY2ietdTWuL07f/t8fjHdfajjctb0tsbIgfy6zLG8T412LO1x+jOEUkEFKX7zRYeAJ1m4AsXLjwDQ0NDZ8YGBiwXsRP6fPPnn322Y9bE2rdffp4j8apWv4FdbV79/79+9WRX/pDNMmYOnWqO3/+fPo7ZQ9BCUSTjJkzZ7rjx49XNX67g3Cd64jddaYFW3b3mdqHXUAkOVjcdqGmXqNjdc159OhRN2tWvAse+4urXUTZPpKOO46BffdE/vsnrBvK3bt3x9kstTLlWlsgcb2rbW2x+vb/drneca3tWNP0tp+VCxfi35W0n7G4P79p37Uxm1obVq1a5Wy0wb6ssr29vdYOkeOpokBdJiBKMGbK/B+UXPzagQMH/vL666+fry/r+vKCBQu+raSkX+veqvlb1H/+y5r/nMp9UsveUcV2YtcIeC1QTteZdiA+dZ8Zt/vR5uaBWImK1w1V5eDiWluYeFfeWHG9fbK2JKScpD3uMVauSQ0IIJCkQF2+hK6k4lohfkHJx1/oc+CZZ555Vp9/rzsdP6h1P6fxgUOHDh2xux5KPj6gdXfoG2EvPwulmayGZcuWZbUr9hOowIoVKwKNnLCzEqAbyqykL++H/7ez9WZv2QjQ5Xs2zvW0l7pMQJRYPK7kY+iOhr7F3J48Xa1vtPyWEo7r9bk3fxKo3AFNN86YMWNBfllWnw899FBWu2I/gQpwSzzQhssw7FC7z8yQKNFdPfHEE4nWR2W1JxBij1L3339/kA0RonWQ0OMIui4TkKjT/PnzJ1+8ePHvtOyCBnvUaobuhERfvOjXHZEeLZse3Y5pBBBAIAQBfgFn20q8t5etd4h7C/Fnct++fSFSuxCtg4QeR9B1+Q5I3knJxywlFv9HCUa3kpA36UW8C3o/5JzugkzNl9HnBM1P1ufZyDImEUCgQKCcri596T5zsut2XZ16U3ywm92CQxo2e+7YWXemIUZBbWVdDU92dmM14Tfnh0UU1kw51nZkcb2xLn4elOMd19r2VA1v6xGy196sjwz5/2/yn5FV6u2qSe+R8LMXNWEaAd8E6jYBWbx48VI9avUFJRd/r6es7Ksy+6xxlIw8rWWLNfmIzStJsem+np4eexSr6GC9ELXYm3AJD9brxBHr4iOwIcS4Q4zZTgsf4raepNTnUxldZ1r5eL1JWcnJk/vV01enO33a5pIbLO4O93rXdsOxWJWW8xNuZQ+5NsX9L4nHHSdY+6tf/i9/mzZtGtrEnuOuxrPc5VpbwHG9q21tser3ybAeC/V7xBbnulGvxl+Oy/WOa23HVA1ve6/mxIkTtvsRQ7Eue61r8m9+85sjylZzgW8/k3Es7P2x/PmrjnmcOubJbWbne74r+Dj1ZF0mC+tq9z6ZtWka+7v8v2QaNXtc5+CdD3vf4w/V9e76aKjqCevd+uXxXiUnb9b40qRJk/5Sn2dU7s5oOZtWPTfrDsruLVu2OL1HUri64nlLPmYX+9+14prTrSDEuEOM2VrRl7jtgqfgD5QlT7J8N54+dJ8Z9wsU7a++16vD7meett6ZSh7asBVNM/RX2Cur/1fYu+66y23cuHFYbNWYiWttsZXr7Yu1xW7Jh3632GRVh7je5VrbQWXtXewOiMVRqvtg3++A+PIzaYZxB0s+Ll26FLe4N+XSst67d69bs2aN0/Xh0oMHDz7hzQEHFEhd3gFR0nC32uhV+kXxG3rk6oOD7WW/MbbpbsgdSkJerTI7Nc6wZfrP7D2DZfhAAIEiAuV2nWlV+NB9piUIsZIEPXllXwTUfE287wwpQlT3i2JbmxTeFZ8vsb0DsLbHqYo9UtWsvwak8fRBxfhUgAACYwrUZQKiJGOdZGwsOgx+IeHHi65kIQIIIBCQQDUeuQqIJ/FQp03LvMf2xI+BCtMVCPFn0h67CnEI0TpE5/HEXPe9YI0HjW0QQACBUAT4BZxtS/3yL/9ytjus473NmTMnyKMP8WfSHjkKcQjROkTn8cRMAjIeNbZBAAEEEECgiIDPL+cWCZdFCCCAQFUE6vIRrKpIs1ME6lCg2Muj+W4z8595Fp9eHC2MOx9r/jMfs336FHc0rlCmC60t7rxz/jN6LHhHNcqfLvTOG+c/ozViHdUof7rQOl+D9V54pgAc67wOn/UiQAJSLy3NcSJQBYG5c+e6Y8eKd3Nb2MFbW1ub6+zsrEKUI3dZKu7CmG1Ln+IeeST+LyllbZGH4r1+/XpnvSHasGfPHrd06dLctPWSs25dydcNc2Wy/qeUdyjW+S6O827ReR96H8vHZZ+lrKNl8tM+/j8StbU4o/O+Wecd+QxHgAQknLYiUgSCE+jo6BjxBWJ2EMW6z7S/APoyFIu7WMwWr09x++JXThzFrG37kLwtycgnGkuWLHG7d+8uhyDTssW8Q7KOXvjaBXF0PlPIGDsrZm03PizZK+yG3Mf/R6K2vlvHaA6KeCZAAuJZgxAOArUkEGr3mcXipsvPdM7MYta2J7yz88Y6O+v8nnzohjwfC58IVEOAl9Croc4+EUAAAQRqUsC+PZoBAQQQQGB0ARKQ0X1YiwACKQiE2H1miDGn0HSZVRmq95e+9KXMjJLaUajWfOdKUmfA2PW88MILYxeiBAJlCJCAlIFFUQQQQAABBEYT2Ldv32irWZegwPnz5xOsjaoQQCBLAd4ByVKbfSGAAAIIIIBATQl0dzt1thHvkPK97+Y/x9rK+uaYMmWsUsmuL9Z9cLGug22vdB+crH091UYCUk+tzbEiUEWBaBeOFkZ0PtrbShVDHLHraIyhxDziIAJaEKr3zTff7J588smcdF9fn5s48fKv1ptuusk98cQTXrZAqNb2wvzZs2eHTPPHMWPGDGcXyVkPlnxcdZVz9lnOUKzb42LbW/Jx6lS2SUjo3QcXc2SZfwIkIP61CREhUJMC0STDLhqi874ecDTGUGL21TJOXKF6R5MMSz4uXboU53CrWiZU62iS4cPPpN35sOSjsFvd0Rq3VLfHhdvku+y1fWR5F6Sw++B8HMWO0cfugwsdmfdTgATEz3YhKgQQQAABBBAIRKCcbnWbmweclfd1KNU1djnH6OuxEZc/AryE7k9bEAkCCCCQuMCuXbsSr5MKSwssXry49ErWJCrQ2NiYaH1UhgAC2QmQgGRnzZ4QQGBQIP/cNiDpC5CApG8c3cO2bduis0FMh3ohf+WVVwbhS5AIIDBSgEewRpqwBAEEEEAAgVEFivUUZBsU6y2InoJGpQx+5WTX7bo69aLGmXiHcu7YWXemYezC9k79ZKdusFw63WB1v9ztes+O3X2XxdGsKLo69c/YYecQmmY0uSlXphN3bgf8E7wACUjwTcgBIBCGwPz585293GiDvQA7YcLlG7DW48rBgwe9PIjCOzXR+ehLvL4Fv337dmejDZs2bXLWc5ANq1atyo25GQ//sQv1ixcvDkWW9540aZK6OR37QmlowwwmQu8pKMSeu6xZ165d6/J3mU6ePOlaW1tzrW3fQL958+bcdJb/WDe5HW6ua7vhWOzdxn39w8p1uDZ1dWtX/skO9uL8qavmuqvd2HFbHLm844b4MbyouF91oTPTl+fjR0dJHwRIQHxoBWJAoA4EokmGJR/9/f3eH3U0ybCL4ei8z8FHEw37i3x7e7vP4Q7FFk0yfPcu7CnIDqJUb0E+9hQUYs9dZhxNMmbOnOmOHz9ui6s2WO9UrzrV4c7EuJNgQdrdhOt1If/M07qrcPnvAqPG/iq7k5DCjQTL569TenPo6d5Ycbz4Yqdra7tm1FjzK+0Y593Q5E5oH2nEnt8Pn2ELkICE3X5EjwACCCBQBYFSPQVZKPQWVIUGqeIu7VGj2I8b6VaCrs9ds67lq90TVo8e7Wq+ZkqsOE4PnHYts2Leu9Ex9lSxPdh1GAK8hB5GOxElAjUlMGfOnJo6Hp8PZvny5T6HVzI2e+yKIRuBUHvuWrFiRTZA7AUBBBIXIAFJnDS5Cum9JjlLavJL4OMf/7hfAcWIJtQL4lATkIULF8ZoFYokIXD77bcnUU3mdWzdujXzfbJDBBBIRoAEJBnHVGohAUmFlUo9EAjx3I6+HO0BYc2HsG/fvpo/Rl8OMP9Sty/xxI2Dn8m4UpRDwD8B3gHxr02ICAEEEEDAE4G4XZVauOV2V0pXpZ40ckphFOuq2ToqsCH/eXnOqacre9k8hbfN8zso8VkYR4liOrcbRsRcqmzcOkttz/L6ECAB8aydQ+0+0zNGwvFQIMRzO6RuYT1s8rJD8q1r2HK6KrWDLbe70mp2Vbp+/Xq3ZcuWXBvt2bPHLV26NDe9Zs0at27duty0j/+E9DM5WlfNs2cP121ra3Odncl3tzt8L6/MWffBNhTGcXlpsX9nFVtYcpnlUvl9lCzEiroWIAHxrPlD7T7TM0bC8VAgxHM7pG5hPWzyskPyrWvYcrsqtQOO211ptbsqtSQjn2gsWbLE7d69u+z2qsYGIf1MFuuq2cyOHj3qZs0afkGfdVfNliBcuOD0/Tpjt6Ld0bBE5ciR+D13WfJRhRs6Yx8MJbwRIAHxpikIBAEEEEDAN4Fyuiq12GN3V0pXpb41deLxlOqq2b4YtKXaffDqaC1BKCdJoHvpxE+Ruq6Ql9A9bv5Qe6/xmJTQPBEI8dwOtRcsT5q87DBC7Rq27AP1YAP7FvEQB34mQ2w1YkbgsgAJiMdnQogXaR5zEppHAiF2n/n617/eI8HaD+WDH/xg7R+kJ0d4zz33eBJJeWF85jOfKW8DT0qH2AugJ3SEUUMCJCA11JgcCgKhCOzcuTOUUIfifPzxx4emmUhfgIu09I1D30Oo50iocYd+vhC/XwK8A+JXexANAggggIBnAuV0Kxq3u9Jy6vSMg3BqXKCw++D8uZr/jB5+tboPjsbAdJgCJCBhthtRIxCcwNq1a13+C89OnjzpWltbc8dgz59v3rzZy+NZuXKle/TRR3Ox2S/ladOm5aZvvfVWt2PHDi9jDjko37pqzncjGr+rUtMf3rvRaO1hLwDn9zFaOda9IuDbOfJKZKNPhRR3qe6Di/0cZN198OjKrA1JgAQkpNYiVgQCFogmGTNnznTHjx/3/miiScbUqVPd+fPnvY855AB966rZEoS4XZWau/2FuJzuSumqtPyz1bdzJO4RhBR3se6Di3UdbMeedffBcb0p578ACYj/bUSECCCAAAJVEii3q1ILk+5Kq9RY7DYRgWLdB/vSdXAiB0glXgjwEroXzUAQCNSXwIoVK4I74GXLlgUXc8gB0wtgyK2XTeyhniOhxp1Nq7KXehEgAamXluY4EfBIoL293aNo4oXy7ne/O15BSiGAQCYCn/rUpzLZT9I7CTEBmTNnTtIM1FfnAiQgdX4CcPgIIBBPgK4z4zklVQrvpCRrtx66xq7dtuXIal+Ad0Bqv405QgQQQACBhAUKuyq16vPdlOY/87ukq9K8BJ8IIIDAZQESEM4EBBBAoIRASF1nljiEoBaH5F2qq1IDL+yulK5KkzsN6Ro7OcuxampoaBhWJDo/MDAwbB0zCJQrQAJSrhjlEUCgbgRC6jqzFholJO9iXZVaGxTrrpSuSpM7O+kaOznLsWqKJhmWfETnx9qW9QiMJUACMpYQ6xFAAAEEECgQKNZVqRWhu9ICKGYRQACBIgK8hF4EhUUIIIBAoUCIPdcUHkNI83iH1FrViZWusavjzl4RSEKABCQJRepAAIGaF9i6dWvNH6NPBxhqAjJv3jyfGGs6FrrGzq55J0zgcjE77frYE2dUfbQzR4kAAhUK7Ny5s8Ia2LweBC5evFgPh+nFMdJVc3bN0N/fn93O2FNdCJCA1EUzc5AIIIAAAggggAACCPghwEvofrQDUSCAgIcCa9euddu2bctFdvLkSdfa2pqbXr16tdu8ebOHERNSNQSsl6vonY98d6WTJk1yvb291QipZvcZUlfNoTdCY2Oji975yJ/X9jhWX19f6IdH/FUWIAGpcgOwewQQ8FcgmmTMnDnTHT9+3N9giaxqAtEkg+5K022GkLpqTlci/dqjSQbndfre9bYHHsGqtxbneBFAAAEEEEAAAQQQqKIACUgV8dk1AgiEI7BixYpwgiXSqgnYY1cM2QiE2lNaNjrJ7oVesJL1pDbnSEA4CxBAIHOBEHuvaW9vz9ypnncY4jli7UUCkt1ZSwKSnXX0XZDs9sqealmABKSWW5djQ8BTgVAvLj3lrMmwQj1Hzp8/X5PtwUEhgAACSQqQgCSpSV0IIIAAAggggAACCCAwqgC9YI3Kw0oEEEhKgO4zk5Ks3XpCPUeam5vd2bNnhxom313pjBkzXFdX19ByJhAISSB/Hudjjs4PDAzkF/OJwLgESEDGxcZGCCBQrgDdZ5YrVn/lQz1HokkG3ZXW33lbq0ccTTI4r2u1lat3XDyCVT179owAAggggAACCCCAQN0JkIDUXZNzwAhUX4Dea6rfBr5HEOo5Mm3aNN9piQ8BBBCougAJSNWbgAAQqD+BUC8u66+lOOJyBW6++eZyN6H8OAVC7SltnIdb1c0mT55c1f2z89oTIAGpvTbliBBAAIHgBUK9uHz88ceDtw/lAEI9R0LxjcbZ09MTnWUagYoFSEAqJqQCBBBAAAEEEEAAAQQQiCtQ971gLVy48BZhfenAgQMz82hadp+m36NxqnqB+MKECRPu3r9/P30p5oH4RAABBFIQCLUb3pUrV7pHH300J9Ld3e3y74HceuutbseOHSlI1W+VoZ4jIbbY1KlTnZ3P+SHfDe+UKVPchQsX8ov5RGBcAnWdgCxYsOBnpPagxqE7QUo+3qX5t/b19d0yceLEl/UD9zklIZ/UsndoZEAAAQQQSEkg1G54o0mGXbTxbegpnSCqNtRzJD2R9GqOJhl0w5uec73WPHThXW8ASjR+Vz9Q9+q4PxI9di1bq/GBQ4cOHbG7Hko+PqD1d7S1tdG1SRSKaQQQQAABBBBAAAEExiFQtwlIY2PjA3rs6vv6+/ufiLop4bhey/bml6nMAU036httF+SX8YkAAgggkK5AqD2lLVu2LF0Yah8SCPUcGTqAgCYmTZoUULSEGoJA3T6C9cwzzxwr0UAz9M7H+ci6ft0R6dE4PbKMSQQQQACBFAVCvbh86KGHUlSh6qhAqOdI9BhCmX7nO98ZSqjEGYhA3SYgo7TPOd0FmRpZP0Hz1gH22cgyJhFAAAEEEEAAAQQQQGAcAiQgBWi60/G0Eo7FWvyIrZo/f75N96kPbHsUq+hw/Phx19LSUnRdJQu7urrckSNHKqmiKtuGGHeIMVvjEnd2pzjW2VlzbmMdR4CfyThK4y9j37OS/66VTZs2DVVkd55CufuU1jli130MlQmQgBT46f2PP1cS8j4lHl/T9Et6V+R+fX7+8OHDr/RFV7BNa2urmz17dsHSymct+Uij3sojG72GEOMOMWZrBeIe/VxMci3WSWqOXRfeYxslVQLrpCTj1ROK95133ulszA8bN27MTwbzmZb1mTNngjHwNdD/v707gbOrqu8APtkpybAoWsCFCCEkYqJtbF1QCbV+IlCrxVoXWrBgXXD/CBXFYrWltLZNq7S2tu607oIKiPnQlmCldeMjH7asENQYXFiEJJCQZfo747zpm8dk5k3I3HffzPd+Pmfuveeee8//fu95993z7n1vJu2X0Pd0QNatW/cvuQNycb4HcnV+hndDym2eOXNm+Z8gBgIECBAgQIAAAQIEHqbApL8Dsn79+mti2Pz8VF86IRckryQDAQIECBAgQGBSC3TLI1eT+iB12c67A9JlB0y4BAgQIFBfgYsuuqi+wYmMAAECNRHQAanJgRAGAQIECHS/wJVXXtn9O2EPCLQINL6M3pJtlsBeC+iA7DWdFQkQIECAAAECBAgQGKvApP8OyFjBlCdAgAABAs0CF1xwQc8ll1zSn3XTTTf1LFmypH/6lFNO6TnvvPOai5om0DUCK1as6CmpDOVneHt7e/unly1b1lOSgcDDEdABeTh61iVAgACBSS9QOhmNjsaiRYt6rrvuuklvAqD7BZo7GuX/aSxfvrz7d8oe1EbAI1i1ORQCIUCAAAECBAgQIDDxBXRAJv4xtocECBAgUJHAiSeeWFFNqiFQnYCf4a3OerLUpAMyWY60/SRAgACBcRdYvHjxuNehAgIECHS7gA5Itx9B8RMgQIBAbQT8XGltDoVA9qGAdr0PMW2qX0AHREMgQIAAAQIECBAgQKAyAb+CVRm1iggQIEBgIgr4udKJeFTtk3atDYyngA7IeOraNgECBAhMeAE/VzrhD/Gk3EHtelIe9sp22iNYlVGriAABAgQIECBAgAABHRBtgAABAgQI7CMBP1e6jyBtplYC2nWtDseECEYHZEIcRjtBgAABAgQIEBgfAR2Q8XGdzFvVAZnMR9++EyBAgMA+FfBzpfuU08YIEJigAjogE/TA2i0CBAgQIECAAAECdRTwK1h1PCpiIkCAAIGuEfBzpV1zqARKgEBNBHRAanIghEGAAAEC3Sng50q787iJmgCBzgl4BKtz9momQIAAAQIECBAgMOkEdEAm3SG3wwQIECAwXgJ+LWi8ZG2XAIGJJKADMpGOpn0hQIAAgY4K6IB0lF/l4yTg193GCXYSb1YHZBIffLtOgAABAgQIEBhNQAdkNCHLxyqgAzJWMeUJECBAgAABAgQIENhrAb+Ctdd0ViRAgAABAgQITEwBPy89MY9rXfZKB6QuR0IcBAgQIECAAIGaCPh56ZociAkahkewJuiBtVsECBAgQIAAAQIE6iigA1LHoyImAgQIECBAgEBNBPy6W00OxAQKQwdkAh1Mu0KAAAECBAgQ2NcCOiD7WtT2dEC0AQIECBAgQIAAAQIEKhPQAamMWkUECBAgQIAAAQIECOiAaAMECBAgQIAAAQIECFQmoANSGbWKCBAgQIAAAQIECBDQAdEGCBAgQIAAAQIECBCoTEAHpDJqFREgQIAAAQIECBAgoAOiDRAgQIAAAQIECBAgUJmADkhl1CoiQIAAAQIECBAgQEAHRBsgQIAAAQIECBAgQKAyAR2QyqhVRIAAAQIECBAgQICADog2QIAAAQIECBAgQIBAZQI6IJVRq4gAAQIECBAgQIAAAR0QbYAAAQIECBAgQIAAgcoEdEAqo1YRAQIECBAgQIAAAQI6INoAAQIECBAgQIAAAQKVCeiAVEatIgIECBAgQIAAAQIEdEC0AQIECBAgQIAAAQIEKhPQAamMWkUECBAgQIAAAQIECOiAaAMECBAgQIAAAQIECFQmoANSGbWKCBAgUL3ANddcU32laiRAgAABAiMI6ICMgGMRAQIEul1AB6Tbj6D4CRAgMPEEdEAm3jG1RwQIECBAgAABAgRqKzC9tpEJjAABAgT2SmDFihU9JZXhwx/+cE9vb2//9LJly3pKMhAgQIAAgU4K6IB0Ul/dBAgQGAeB5o7G5s2be5YvXz4OtdgkAQIECBDYOwGPYO2dm7UIECBAgAABAgQIENgLAR2QvUCzCgECBLpF4Pjjj++WUMVJgAABApNEQAdkkhxou0mAwOQU0AGZnMfdXhMgQKDOAjogdT46YiNAgAABAgQIECAwwQR0QCbYAbU7BAgQIECAAAECBOosoANS56MjNgIECBAgQIAAAQITTMDP8O7hgM6bN++JU6dO/VAWPyXpR0nnrl279kt7KC6bAAECBAgQIECAAIE2BNwBGQZpyZIlM9L5uDyLLk2n46BMvznTFy9YsGD+MMVlESBAgAABAgQIECDQpoAOyDBQ99577wnJ3j+dj/Lfu3atXr26/EvhK/r6+k4bprgsAgQIECBAgAABAgTaFNABGQZq2rRpC5N9S8uiVemAHNuSZ5YAAQIECBAgQIAAgTEI6IAMg7V79+45yb6/eVE6H2V+dnOeaQIECBAgQIAAAQIExibgS+jDeOU7H1vT4fil5kVTpkzZP/NbmvOmT5++XzorPbfeemtz9j6b/slPftJz33337bPtVbWhboy7G2Mux1PcVbVq1tVJ/6Imbbs6cdbVWZeautG7G2MeT+vGdV+5Dqy29Uyc2nRAhjmWu3btuiWdkLNbFj0xnZAhj2Wl3Nzk9ZxzzjktRc0SIECAAAECBAhMZIFyHZj9+5+JvI/jtW86IMPIHnjggVdv3rx5x/z588/t7e392y1btjw3d0ROSvq15uL5rsiKNL5TM759586d25qXmSZAgAABAgQIEJh4AuXOR+l8lOvAibd31ezRlGqq6b5ajsmQx6v+OXc4fjXR35Hx29esWfPl7tsTERMgQIAAAQIECBAgQIAAAQIECBAgQIAAgUko4A5IBw56Hu3anWrLr2qVcTkGD+QOy9fzGNe5+WLT+sz3pMzpGX0s6cv5fyS/U/Iaw8KFC4/Irb8NmV+ZZb/RyK9i3E7sA3FMTdm3ZPqVSUcmlS/wl+ckL0zM38m40qHduFPuNxPY+UlPSepLuiWP3v3NunXrvpjpyocSd+r/VOr//ebKk39Z5r8Ty/dm+vSUOTtlFjWX6fR0biIel7jemTiemVTaeWnbH03MH8y4tPHSvjdn/k1lvi7DSHEn5mclziuTStso+1R+GW9rUhmyu32vyXH49C9mq/mbmJrPJyWuvpxPrs/4vNy1vbbpfNH4EY0S911JH4/9n2bckWEv4h6MM85Xx/mFgxkVTowWdwmlpUzJKualfbw5cZd2X9nQEstI7ePOtIfDEtiu5uCyfvmVlblZNq05v4rpMcTeaNtl/8rr4dpYnxPrVVXE2VpHS9xlcV6SU+7OUxWfSUxvLxnz5s07Pt81vTqTjdhLdn87yfv7rzauBUrmeA/txJsypyeOjyXV6pokjo/KY1B/leN9UmIr5+OfJl364IMPvuv222/flrg3ZNnb4n5J8geH5F+UYzI758gzBjNNVCrgZ3gr5f7/ynIienZO6Ack9eaFMj8vkNvzIvrGUUcd9ej/L9Vzd6aXzZ0796CmvJ6se1rmO/bzWO3Enhf3F/PiPjVxnnX44YcflO/RlE7IfyZddfTRR5+cceXDaHHnRHZUgvpS0vIcl4OSDs4+/GXSxdmf51Ye8ECFqf/lMXv5SPWnTHnjrc2Qi/jfTZu+PAF9Ne37CcUz/m/M/Kuz7N9rE2hLICPFnTbwqezHN5J6kw7IxcPcrN6Xi4UnNvLyJldp56MRflPbPjCxlPPFpfH/6pFHHnngQJm+WbNmHVHiLrEm9qXJPzPt6g8HlndkNMa4S+z9Kc4d6Xw0kNqIu5ynG+f4fvMSe+IuF3CVD02x7Kl9lJj60h6e3xxc2nzpcB/SnFf1dBuxN7ftsn8l3tU5J34143JB35GhKe7+4594Tkk6I+eYM5sC2tJo0wPj/nNLlZ2PRixtxlu7a5Kcyz5b9iEf4B4Tw94Ylw8Rj5s5c+a/NvbNuJ4COiCdOy6DJ8b00n+eF87ZCWVNOiFvbYSUC4g7Mv3NGTNmvLSRV8bJL5+Gf745r+LpEWMvF3GJ5xn5ktbx2a9vrFy5cuemTZvuz/Q/Jv+cnCDKiaETbW/EuGNfvu9zb+Is3/Upn6LtHvjez7sSc/nfMB0Zcrw/lPo/mM7p4zoSwBgrTYd5v8Rc7nK8thzz0r7LJtavX/+/eZN7Xpad2KlO6Ei7MlrcWffEXJCVT9mahynZn8F21byg4ukhMeRHNMprrHQ0Sqe6f4j9YJnVq1ffnsz/SLta8oulHfs7GFOJYLS4OxblQyseNe6sMqTMQzdRac6QWIZzTjSfTXv4g5aoyoddn2vJq3p21Nib23aC25X5j2b8+GOPPfbgqoNtqm9I3HnNXZdzxcqkJzeVqdPkqPEm9tpdk6TNPi1xff622267t2DmPXtDRuWu+k/KvKG+Ap24CKyvRocjywupfGKztBFG5vO66ru4+U0hn9I/PcvvSerIreVGbK3j5tgT8wuy/PKbb755S2u5vDF8MnmPyIXcca3LOjHfHHc+yV6ZGKYktm/lAvnsWD8jb2AzcxG9fKAj0okQS4fzw6n4v9JB+reOBDDGSvNJ+zOyypzc+fpi66rphPwseZflwvjFrcs6Pd9G3F/Jsahd3K1uabNzZs+efW7y78ingre0Li/z+ZDgmIyek/0pne1aDO3EXYtAW4Lotrj3EG+5g/pvOR++oCwvu5jz36yMfjvpM2W+DsMeYh8S2oIFCx6Z88tbk3lD3oPKJ/Z1GKbE8/j4PjfvgVfVIaBRYhg23sSfU0a9rkniWdrnJ/O+vTyntRfG+VF5zy6PJ5cPdfuHxP2JLL+7KZVrqFcNLDbqkMD0DtWr2mEE8sIuz2U/onlRTqRfyPw/lOe4V61a9f28kE4rL6aU3b+5XKenm2NPfIcmnm8PF1MuQLfnJHBPypRnjTs+NMddLo5z8npyYntj0suSLtyxY0eJ99O5C/XW4TpUVe1A2sGrc6K9IbG8IyfWC6uqd2/qSZyHxu6ucudrD+tvintx/nHGeyhSfXY7cSfmWn56mfZxddrGrqKWNrsj89enQ/2C8gx0zh0le0qyb02Z8v2QWXEvd6m+nrzvlIWdGsYS90CM5VPa0mjOyuugYxfGI8XdsGwq04j5a4n5FY3lVY6bYtlT++jJOW592sP1SaWT/Yl84PHCtJFrsu7P89qoMtwhdbUR+2DbLism1vKT+N9M6uiHBU1x75dYZsbyv/Pae23eZy7LfGOYk9dko5PUaCfvSjspd5ArHdqMtyflanVNkscaz0zH49T4vizpjMR3QOa/mem3xLFxHXJapi9tBo37RZmf3ZxnuloBHZBqvUer7dEpcGdzoXzyvjkvlMtyMXHqkiVL/jq3zl+0ffv2d+b5xubnSJtX6dT0YOx54ZfbtEcMF0h5zCX5j86bxI+HW96BvMG4S90Dn9Cfn8nzFy9ePPuBBx44IW8af5M35fL42OmlTCeG3L6/K3dlXplYvpKT61Ux7kQYbdWZC5c7cnx/Oe11xnXXXbdjmJXKP/AsnY8ht/yHKVdpVrtxVxpUm5XFe2na7vdGKF6ekz/yxhtvLJ/89aRTcljujnwseeV7WUtGWG9cF4017nENZgwbbyPuciE82jEZQ40Pr2i7seQ1We64n5rayodc5fGryi+EW/e0jdiHtO3W9Ts134g779+HxLQ8EvaovN6uaImnfAdkyIeOLcsrm20z3vKIU+2uSRJT+V5h/3cL8/64OG33bZlfkeuNJxTAur3XlJgMnXkOn/ueBU7Oieq/WheXN4Xk/X46Hydn+trGM/Wt5To8Pxh79uGSxHJSuRXaGtNAx+mn+dTi2tZlHZofjDtvFOU27scbcdxwww1bE+flmb8w7uX7IR0dEku5df9PiaWcaGv7yU0e/ynH9q6014d02PLmcHiWnZg3u9JGajW0GXfrY2V16QmO2pmL+WCZ3E0tHxJclLb0lHKB1MEDMRjTnmJojntPZTqQP2rciamdMlWF3lYs++23X/keyHFpE+VO3+JcHH+tqgBHqGfU2OvcRmJ459atW8v3OHu3bdvW/4XpEfa1k4v6nduJN+eNWlyT5HG7ZWmr9+Rx38EnQtIZuSH7cEYgZ6c9H9VJUHWPLOA7ICP7VLK0PLOaT7f/PpU9Li/s97dWmgvP8ibwyCz7s4w/0bq8k/PDxZ4TwFcS01W5FboiJ4dnlU/CFy1adHD28U3JvyBvFq/OuP9xkU7FPlzc8S1vvi9JzK8qdz8S29SUW5TxWQOdqk6FO1hv7N6Rme1JSwczfzExI3E/pjmlA3hAS5lKZstdj4Fj/L7Ec1Y59qUN5PiX7xxcmSBWDHTsym9TlkcQWuMuz55XPrQZd+snmKNeHFW+I8NXOCV3UQdjLcck9mem6JpywTH8KrXIHRJ3LSKamEH0t41yhyyv0RVJ5ftmn0va3QW7O9iu6xrrxo0bH4hp+fGY5+U8+Jq6xtmIqznenJ/L+/WQoS7XJPl1za8nsHvmzJnzkXy49YQSZPkl0Uy/J96350OlG4YEbqZWAjognTkcfbk4/3pe2Pcl3ZuLte/lYuCgPBLxrD1cDOzK8s8kHZIXfrmA6+TQVuzZj5cnyI8kXZRPwu/MY2NrEv8JmX9eyzOwVe3LqHHH9oqctMrPx56aT6o2Dhybz2b+89mfd1cVaEs9Qz5hj932tJ3yiMS2eDYvm5+8HzSnPFL0rpZtVTY7cIyfH7tlOfZrSxtI3H+XAD4Uy/JpYP+Q5adnYkjcKffcgcWVj9qNuymw5mPQlF3pZDsx9OU8s6FxzskxWZ8IpyTvBZVGOrSyscZdzpcllUdAfjp0U5XOtRV3pRGNXNlY4y2PYT0x54+Pj7zZSpaONfZKgmqjkofEnfeX67PeBbH9qxr+ouEe403M7xsm3lpck5SOUuJ7dt5H7k8q11Sb025vzPTjy/XGwCPAD9m3No6fIgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBeCeS/Dd90zDHH/PZerdzGSuW/LqeO+xYtWnRsl/SdAAAIrElEQVTwcMWz7LKk84dbJo8AAQIEukNgeneEKUoCBAgQqIPA2rVrnzSecdx6660/zPYPGM86bJsAAQIEOiugA9JZf7UTIEDgYQvkjsSf9/X1/WE2NGPKlCm3ZPqPM70w6Yyk7yf9TtKm5L9z3bp1X8x0T+4iPCZl35+852R2S8YfybK/yHRfWZ5tvj2js5J/YMbfnTZt2utWrVq1LuttSN7bUvaSuXPnHjRr1qzlmX9+yuzK+AszZ858+8033/xg1u/dvXv3R1PHCVn2QMbf2rVr1+vWr1//s8zvcVi4cOERKbdhxowZh2Q7d2c7v5Ht/l1WODLbWJFpnZM96llAgACB7hCY2h1hipIAAQIEhhMYuEAvnY8n5+7Eo3OBvjLTHxgo++yMVx1++OEH5+L9nKRPpQOxIHnl3H9ZOgg/zIX+Y3fu3Lk0y15y9NFHv6Gsl22eme28YerUqSdnm2Xd76VT8LmyrHlI5+OTKTc725ifsk9JuSft2LHjwlIm2y717dfb23vY/fffP7+US5m3Na8/wnR/JyixHpL1Lk36+8RxYMZfyDplnwwECBAg0MUCOiBdfPCEToAAgQhsTzo4F+evyd2DJ+VC/T1JTx+Q+X6mL1y5cuXONWvWfCVlrk7+S3Nh/9SM5+cuxtnlbsVtt932g8yXjsOrk3pS7tR0Hv4hdzxuKrNbt249P/N/VJY1hnxXo3R2fiv5b802tqxevfqudDr+JMv7t5H8bUmLt2zZctr+++//iMRxUtK5jfXbGZftp9zGxPmxjHdn/c9kfG076ypDgAABAvUV8AhWfY+NyAgQIDCqQDoW16ZD8Ypc7L8+dynOy92L8ojTe3PxvjPj25o3kDI/TDo0eUdk+X5Zr5SdklTuOGTRlN0Zl+GwdCZKp6R/2Lhx4wOZ+O7AbP8oj2QdUSaynZuyncY2ykamzps371HpLPxl7qjsyPzrUuxDKXN9tvmGPIL1zf4NtPEn6x6WtLGl6IaWebMECBAg0GUC7oB02QETLgECBJoFcrH/2FzYlzsdz8u4/HLUeekU/GtS6RQ8trlspucmv3RCfpTpO7NOuTNxcBnnMay5Sb8yUL5c9A+um0e49k8H4m/LeGB56WiUbezOHY7HNrbx4IMPHp7tLyrf81iwYMGx06dP/1yWPTWPaJW7Jd/II1ifaqzf5vhHWe/xLWUf0zJvlgABAgS6TEAHpMsOmHAJECDQLJCOwK/nwv6K3Pk4Jhf+23PBfleWl8efHplxbkIc/ZqMp2X84uQ9M+nThx566LeT99N0Kt6TDsysY4899hHpLHwh6f3JL8PFKXdW1lm4dOnS6XPmzCmPVh2/adOm+/uX5k/uvGzK6Kos+0DWn7N48eLZ+QL6vySvfE+jfAfkj3JH5iPl53TziNa92d7WZJfY2hlK56kn3zG5LKNDEufrM56W8YsyXppkIECAAIEuFtAB6eKDJ3QCBAiUX6NKp+ODSf+RC/TNGb8v6fcic2fSrbnwPy75P8v43ekUvCgdhw3lOyHpHJyc5YvTeflhvji+JtM/zh2QV2bck7sWn8zoA1nn8nQ6ymNaT86yU8qyDOVxrf4hdzZOzcT0rL9227ZtP0j5g7LdF5aFWfbOjO7Yvn372tR/d6aflrpK+XaG/jpuvPHGe1L4pKRXZhs/z/is1HFFOxtQhgABAgQIECBAgACBCgVywX560g0VVqkqAgQIECDQloA7IG0xKUSAAAECBAgQIECAwL4Q8CtY+0LRNggQIECgLYHclSn/T+TEpMFHuQZWbPyS1pF5BKw8PmYgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEHiLwf92mqZVykL9AAAAAAElFTkSuQmCC\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x102937c88>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.boxplot('hindfoot_length', by = 'species_id', figsize = (10, 8))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "deletable": true,
+    "editable": true
+   },
+   "source": [
+    "## Seaborn\n",
+    "\n",
+    "The Seaborn Library provides additional plotting functionality for data visualization in Python.  Here, we show how Seaborn produces a typical regression plot, a boxplot factored by sex, and a jointplot with histograms on the axes.  Finally, we add some additional layers to the boxplot by using a violinplot that is split by the `sex` variable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": true,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [],
+   "source": [
+    "import seaborn as sns\n",
+    "sns.set_style(\"whitegrid\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'];\n",
+       "    var y0 = fig.canvas.height - msg['y0'];\n",
+       "    var x1 = msg['x1'];\n",
+       "    var y1 = fig.canvas.height - msg['y1'];\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x;\n",
+       "    var y = canvas_pos.y;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"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",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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wu4pDQJ5VXgQiPoHDql/4C9IBH7A26J85+bm5q47fvz4jD8WjR988MFtpVKpuQNaNBNpCEAAAhCAAAQSSUB6YPuhQ4cuJLJwXS4UHkABnpycnJXge+vo6OhRef++oti8gQ+uJv7C9XLTTTe5wcHB8KHU79uvo6NHj7qDBw+6YrGYenvCBmBbmEZ69rNcb1YLWbYP29LzOQuXNMv1JgePe/TRR8Pm5m4/jwJw0deyRN9H1d/vSxJ9X1Z8j/oBfkTi7wOKn1Wet/h8a8UmkLImkrzN2OZJpCum3tJVX+HSUndhGunZp97SU1dWUquvvIfcCUA18/6gr3Ttv8PvSwQ+pP1DPk0MAQhAIM8E1jsvZ56ZxWk7/OOkyb1aEcjNNDCtjOcYBCAAAQi0JuDn5awsVIOJ1i1N6B0B+PeOdV6fhADMa81jNwQgAIFVCETn4YymV7mUUzEQiPKOpmN4BLfIOQEEYM5fAMyHAAQg0IpAdB7OaLrVNRyLj0CUdzQd35O4U14JIADzWvPYDQEIQGAVAkywvgqcHpyCfw8g5/wRuRsEkvP6xnwIQAACbRG4etuwu+/uW9rKS6b4CcA/fqbcsZkAHsBmHqQgAAEIQAACEIBA5gkgADNfxRgIAQhAAAIQgAAEmgkgAJt5kIIABCAAAQhAAAKZJ4AAzHwVYyAEIAABCEAAAhBoJoAAbOZBCgIQgAAEIAABCGSeAAIw81WMgRCAAAQgAAEIQKCZAAKwmQcpCEAAAhCAAAQgkHkCCMDMVzEGQgACEIAABCAAgWYCCMBmHqQgAAEIQAACEIBA5gkgADNfxRgIAQhAAAIQgAAEmgkgAJt5kIIABCAAAQhAAAKZJ4AAzHwVYyAEIAABCEAAAhBoJoAAbOZBCgIQgAAEIAABCGSeAAIw81WMgRCAAAQgAAEIQKCZAAKwmQcpCEAAAhCAAAQgkHkCCMDMVzEGQgACEIAABCAAgWYCCMBmHqQgAAEIQAACEIBA5gkgADNfxRgIAQhAAAIQgAAEmgkgAJt5kIIABCAAAQhAAAKZJ4AAzHwVYyAEIAABCEAAAhBoJoAAbOZBCgIQgAAEIAABCGSeAAIw81WMgRCAAAQgAAEIQKCZQKk5SQoCEFiLwNkLM+5zXx93T52acnt3b3f33Dnmrt42vNZlnIcABCAAAQgkhgAewMRUBQVJCwETfxMnzrnKQjWILU2AAAQgAAEIpIkAAjBNtUVZE0HAPH/hEE2Hz7EPAQhAAAIQSCKBXDUB79u3b1uhUHigUqnc9eSTTz4TrpCxsbHdi4uLn9axXdpOa7vn2LFjL4TzsA8BI2DNvuYB9MHSBAhAAAIQgECaCOTGAyjxd8jEnypnf6sKkvj7g4GBgY9L9N2s/c8oz++3yscxCFifv9EbdrhSsRDEliZAAAIQgAAE0kQgNx5Aibt3aHu3xN2nohV0+PDh0qlTp+4YHx+/285NTEx8cv/+/f9Ru0VtC3aMAAFPwAZ83Hf3LT5JDAEIQAACEEgdgdx4ACXq3iaB97eqoYFoLT399NPX6NgFbV7sWTx1880374zmJQ0BCEAAAhCAAATSTiA3HsDVKmp4eLiwsOC1XyPnwMzMTLWRWmXHrm1x/SpXJP+Ut8fHyS9x+yX0Nvm4/SuTn9Pb5OPkl7j9EnqbfNz+lenI6e3ycTpK3V4pvU0+bu+qdOTyNvk4HaVur5TeJh+3d1U6cmXRpk7JL/OGdXqDtOVX0+5TGgTyqvAgkHoT8Avq/3e17DHRV1Q+S79I+8uUobf5wQcf3FYqlZqHhPqTxBCAAAQgAAEIJJqA9MD2Q4cOWQtg7gIeQFX5kSNHKqOjo38l0fcmib5PKX6zHda2ovjTuUa46aab3ODgYCOdhR37dXT06FF38OBBVyxaV8jsBGxLZ10mud5scvDPf3PCPXX6gtt73Tb3hteMdjw5eJLt2+gbg20bJdif67Ncb3Nzc+7RRx/tD9iEPDWPAnDRs5fQ+6gGhXxJ/QO/rPg9GiTyCR37ZZ0/U61W3+TzrRWbQMqaSPI2Y5snkdw4vDLJjRIfN1+3ELyPvJO9q7MvfGvSTZ48HzzQYkuvd6AQn7ne1VucT6Le4qTZ/Xtl9e9jJ+RyJwDl4ftBD0j77/D7k5OTJ7X/Wp8mhkBaCPiVSay8EyfOuxdeqLgf+VdpKX02yhmdDDyazoaVWAEBCGSJQG5GAWep0rAFAmECUbHx/fPz4dPs94BAdDLwaLoHReAREIAABDoigADsCBeZIZA8AlGx8eKryskrZMZLxOTgGa9gzINABgnkrgk4g3WISTknYOLDmoHNE1jrAziXcyK9N5/JwXvPnCdCAAIbI4AA3Bg/roZA3wmExYeN2nvooYf6XiYKAAEIQAACySZAE3Cy64fSQQACEIAABCAAgdgJIABjR8oNIQABCEAAAhCAQLIJIACTXT+UDgIQgAAEIAABCMROAAEYO1JuCAEIQAACEIAABJJNAAGY7PqhdBCAAAQgAAEIQCB2AgjA2JFyQwhAAAIQgAAEIJBsAkwDk+z6oXQQgECEgK19bGvt2ryHNgm2zYNoU+EQIAABCECgfQJ4ANtnRU4IQCABBD7/zQmteXzOVRaqQWyTYBMgAAEIQKAzAngAO+PVMvfJ02fcppEhNzRYclu3bHKlElhbguIgBGIg8NTpC013ia6F3HSSBAQgAAEItCSAUmmJpbODhfKwWxgou8tzi+7c6fOuMFB15VLRDZYKbkTCcNPIsCsUcLZ2RpXcWSRgzbd+2br1Nt/uvW6bmzx5voEnuhZy4wQ7EIAABCCwIgFUyYpoOj8xMDDghoaHXXlok3PFITe3WHZnLsy54ydfcE9/73n3/efOuvNTF50t10WAQB4JmPjbaPPtG14z6kZv2OFKxUIQWx9AAgQgAAEIdEYAD2BnvDrObc3BvknYZN/Fmao7e+Gsk3PQDZaLbtNw2W3ZsjkVHsI4vDcdA+SCTBGINtdG0+0YG177uJ385IEABCAAgeUE8AAuZ9LVI9YUPDQ84oqDI2o2HnTnr1QDD+Ezp553zz5/1l26fMUtLi52tQzrvXkc3pv1PpvrskEg2lwbTWfDSqyAAAQgkHwCCMA+11GxWHRDI5tcsTziKm6w1mR84nl38vQL7vkz59zMzEyfS7j0+Ki3JppeyskeBFoTsOZamm9bs+EoBCAAgV4SoAm4l7TbeFbQXFwfRTxXde77Z644V73gBgclFNVkvG3rZlcul9u4U/xZzFtj/bd8wHvjSRC3S4Dm23ZJkQ8CEIBAdwkgALvLd8N3Lw8O6h6DzhqFpyuLburZKVdw1UAMWh/CLZtH3NDQ0Iaf084NzHsTHcHZznXkgQAEIAABCEAgWQQQgMmqj1VLE4wyHqqteCDnYCAILzx/SR7CKXkFC8GgkpGhstu0SX0M1bQcd8B7EzdR7gcBCEAAAhDoDwEEYH+4x/JUE4SDIe/fvNyEM5cX3PPnzmhUcW2UceAl3DTshjU9DQECEIAABCAAAQgYAQRgxt4D8/wVNajEgjUbz2rumUvqR7i4UO9HqL6EWxCEAR/+gQAEIAABCOSVAAIwBzXv+xGaqSYIL75w2Q0sXlCzsQaWSBBu7WE/whzgxkQIQAACEIBA4gkgABNfRfEXMNxsHAhC9SMcWLR+hDVBaB7Cfo00jt/ale9oE1t/4VuTzqazsRHNNsjF+jkSIAABCEAAAlkngADMeg23YV9UEFqTcWV+1j1/9oJ77vlzGmVcciPDQ8Fo4yytafz5b0401pS16W1shPN9d9/SBjGyQAACEIBAmgjYAgvT0zNuembWzVWq2p9NU/G7UlYEYFewpvum1mRcUF/CgdKIm3dltzBfcBf0walWLgaDS2wNVtuKxQE3PFjWAJOhVHoMnzp9oamimNi6CQcJCEAAAqkkUKlU3JUr0252ruLmF6puXoJvYWHRFUrl2nfVgHOFsv7JeUAA5vwFaMd8G20cNAmHJqC2dY31uXLTGnVcmZrSVDQLgSgsaZHjYkGjk9Wc7L2Gdn0Sw97rtjU8gFY+JrZOYi1RJghAAAKtCZhXb3Z2tubVm18IhF5FYq+q2XIDR0ZBiyZoRoySptNF7CxnCJPlTDjSAYFg1HFozkEbeVzRNj+36M7busYafWxT0nivYTDoZMtmF6x40sFzupH1Da8ZXdYHsBvP4Z4QgAAEILAxAtVq1V2pN+GayPNevYFiyZXknBgYsFYr58qomrZBg6ptVGTshEAwR2F9FRN/nXkNL0sYnj19zhUHFgMvYVkew+GhwcBb2GtRyMTWvmaIIVAjYAOjoqv9MDCKt6PXBObn592ly9Nubl5NuBJ7FTU3Sf+5YnlQzoOaV68or178yx302tL+Pi83AnBsbOz1chf/unCXJU4+PT4+/pth9Pv27btTAxw+o2Mn7LjyfndiYuJt4Tzsb5yACcPh4ZHgRuYttPWOpy9VNHn1tKAvNSObMNw8MuxGtCW1CXnjNLgDBJJFwMSfX++bgVHJqpsslsYPzLiigRkm9OYr6lKk2MmbZ4MTBwYG8ep1seJzIQD37t27Sy/aB9WP7bZHHnlkav/+/V8dHR19rQTeNzxbiYwf1vZbEoa/548R94ZAq2ZkE4aXz2vgyQsX1Xxc61NozcdbNm9K5YCT3pDkKRDYGIHoQKhoemN35+o8E4gOzJhTnz3z6oUHZhTl3LON0BsCuRCAg4ODr1X/gW9J/J2tY/2kxN5Pa78hALX/ConEEYnDt2j/aW33Hzt27HuKCX0iEB544puPz12acoXFqkSgfiFq/WMbaLJJXsIsTU/TJ9w8FgLBQCjvATQcDIzipeiUgHn1bGCG9derefXUhCuvXnRgRnmo0zuTP24CuRCAgrZHW1jMndJLen0YpgThWR37Y/MKyjv4LqX/WOdfFc7Dfn8JqE40F+HSRM3mJbxyYc49d+ZSMNCkXCqqA7BGfykeGR4M5i20awjJIUAfs+TURauS2GTo0T6ArfJxDAJGYGFhIRB6M7NzgchbPjCjRBNugl+VXAhACTuNQ20OEgaSD0tB3r57fUoi8CPyBP6O+g1uVZPwRX98pbiqDqoLBfNRZSeYTRZ8nFTLTOCVBms/JYOpaTQEeXq+6s5cuKguhRpsopov1uctDPoVapUTP9jE/nhlLXibfJw0+z77tcfVx+x8UKxjz5xzln7XTx1sq5jeJh+3dVGKMnm7fNyPom/fXHbv/Hcva3p0HOXx9/Bx0wNSnvA2+Tjl5jQV39tksR+YMW/Trej7oaL+etXFgaAJt/Y31f7Y2t/b2i1s1G6SQ9K/23rBLhcCUCBPSig0vHnav06i8KQHrAEgQ2pC/AWJwA/4YxbLjT0fTq+0Pzk54WxAQxbD+LHxTJllf8QWFyrBH6kzf/13gcdw08hQQxRmxdijR48m0pR/mXxO80cufVr+ZXLaPfRQZ0I8qbbFBTzL9mFbXG9J9+6j70Y3oybc2dlK8Fm1z+vX/tcDwTQrJY3CtR/dWQhmxTXb8t3hMBcCUIMMvqlfMO+X0Nu5ffv285cuXfpZvcQf9i/x5OTkrDx+b1XT71F5/76i2LyBDx4/fnzG51kt3rdvVPMQZQul/Toy8Te2f0yrgixzoK6GI/HnvG37ZduAJq2e0x+7ohzCQb9CNR8Pq/k4rf0K7Ze6fckePHhQIrf+UzxBNfKyJ482PIBWrNEbrnK33tq+BzDJtm0Uc9LrbiP2YdtG6HXv2sbADE23MqeWkwX11dOCGRqEWwoG2/m/lQcz+D1Qkc3nnjvePbgpuHO2VMsKwB977LHTEnXvk5fvWxcvXtTsQe7P5O37kkTfR/Vr50sSfV9WfI9E4UeU7wOKn1Wet6xwu2WHTSAl8ct2WUHXcSAPtvkmYcNjk1ifv1xxZ86fa/QrHFS/whF5CTdvGknNr9/oyOp1VH1XLvmZHzuwrI9Zp5+dpNoWF7As24dtcb0lnd3HvHqrD8wYdsG8evbt2CJk8Xsg6U3ULaoh9kO5EIBGTSLvTxTZ1ggSge/wCZ1/SPuHfJo4vwRMEIZFoeaubgw2KZU0JY28hDYljQlCjTDPL6h1WM7k2+uAxiUQWIWAeVdtm52bD/rp2Zq31mxb22wC5UWniRMCr15txQwGZqyCM1enciMAc1WrGBs7gbAotB5rtqLJ+UsaaFKtBKOObUoaW+5uqL6qSaderdgLzA0TR4AR0ImrksQWyDx2Juqsz7IJu9pKGHVRp+45VZ03YVe19lpba3NAf3/0w7WoptsgWAe3+oCM5HUESSz23BUMAZi7KsfgOAhYR2ibqd652ghkazrWoDh3SdPSVM5c1vrji/pjrBHKaj42YeinpjGPIXMWxlED6bsHq2ykr866VeJok6yJOe+1M1EnWRcIu0KhGAi7AVvk1oKEne2aqEPYBUT4ZwMEEIAbgMel+SAwdWnWfeWBp9zJ5y6666/d6l73b/a67Vtaz2Ia9hQaHftDPq9/5sxjePmKRiBfaPQttGlphgZLQVNyuMk5H1TzZ2V0VY1oOn9Esm2xiTwbZDGjZc5mNeBgQZ678Lq2fqBFIO5qTjzHF3K234mkWcf7lrQaoTyJI2Di7/jpqaBcFlv6jT9+oKNyBh7DoL/gUp9BE4az01X3wpTmK5RUNG+hicJBjSjfsnmEJe86Ipz8zLaqBqtsJL+e2i2hibtpiTtb8eLs+Yvu9LNngqbYoGnWmmft1581zZbLjaZZ895lbMKIdnGRL4EEEIAJrBSKlCwC5vkLh2g6fK7TfWsOHh4eaVxmTcnz8hbakndyGWgKHjUjB6PM9UWiKWusWXlYTc+Dg+WgaahxITuJJ8AqG4mvopYFNE/etETe5dDSZubNW5S4K2tePCe/XbUwrG1In88izbMtKXIwiQQQgEmsFcqUKALW7Os9gFYwS3czmLcwvOSdPcvm1LfRyItyG16U12GhctmWaVkSiIE4LKiLUNVduTIdND0xEKWbtdT5vRkB3TmzXl3hB13YkmaztqyZBF7FRtPW46KEXqmkSYPVVFuS5gt/cdpgDQIE0kgg/B6nsfyUGQJdJ2B9/qJ9ALv+0BUeYOIw2s/QsppAtCYn+zK6OOvcM6fPa3JrfV/VPYjmRbQm5iF5Dm2Sa8ThCoA5nCkCNtdb0AfPRtJqlJYNtPAjam0krXXSDaZJMavljTeR1+iPyyjaTL0LGLOcAAJwOROOQKCJgA346LTPX9MNepywqSCGhptFnvkozFFx+eK8e+7sFYlDG6Vc63NownDT8JCaoocYodzjuuJx8RGYm5tzl6/MaEWLStNgi0Jd1A0MyIPHKNr4gHOn1BNAAKa+CjEAAu0TiHoPG8JwSs3KL1wMRijXpq2RN0QCcQRh2D5ccnZEwLxz5rE2r7YFH/t9n7bYN9EGc+PJkzcvkVfRtdZMO690RUuYDRS0fJkGWg0MaNM3G4MtAqz8A4EVCSAAV0TDCQjkh0BUGPp5DS+en3HVypIw9E3JI5rw2jyGNCXn5x3p1FITa+aVs351M7Pz7sy5i+7k6ReCkbHWty5wx6nZ1cTdgLnmFIJ927Xm2Ua6JgAHNCfegPLbwCl777xHryjHnm0ECECgMwIIwM54kRsCuSJQ1hQWGurYsLnhMdSE1wtn/YTXS03Jw6yE0mCVl51gOhSNkJ0J+tlprjuJu4WKJjOW566g7gj246K6WHaLxWF55mpdE/jiycvbgZ1JJsDnMMm1Q9kgkFACUY9hWBjaSii+j2FtJRStmqL2OGtONkHpm/YSahrFWoGAeedmZ2eDfnY2oXEwqbHiqoSeTYdSNDecRsmq5wAeuRUYchgCSSKAAExSbVAWCPSBQCcrnaxVvKgwDKav0T8zmvD67AVbO1lT1wQiwZry5CGyTU1+FptItBHKgddxrQdxvmsErG+eCT2b5Lgh9OTV02Fnq1fYcobWYluQ3tOg8qbQzrvUTp6mm5KAAAS6QgAB2BWs3BQC6SEQx0ona1lr/bZqayc35zSBaJv9YyLxzAVNgC2R6Aei2EjloolDm/ha+yZOoqHWb6zWhyx6jvTqBGZmZtwljZz13jzrm2fTCS2NnC11NKCinXepnTyrl5qzEIBAHAQQgHFQ5B4QSDGB6Mom0XSvTDORGJ4AOxCHEiPzNn3NpYqbk1fq+2pefvLEs/IaapI2Bd+c7AcP2GCCYFCp9GBR9yvV50Ec1JrLeW2CtsEYts2qj978vObD08jZOUG1raBmWxs56z165tXbSIi+O9G03Tt6LJreyPO5FgIQaJ8AArB9VuSEQCYJ9Hqlk/VAtFGf5kEcHBrWHIeb2x59bCLSVlDxTdDVhYrEow1O0LJ68izaZs3P5l20JughDWLpVj9FE6nmwbTYb7WpUKx5tSpBNu+mLlxyZ8+dV5lsdehaqOWtjZC1wbHBcbuHTtskxhZqx+2+tXzBMRlv1+pmEng2yXFJ3Gp/8gc0N95QF/76t/MutZMnMIp/IACBrhLowp+ArpaXm0MAAjETSNJKJzGb1rjdUhP0UOOY7QReRsWaSs5dnpOnbOqiWqArNS+ijjc8ipa53lfRPIu+76Kfo84LLy/KbJWJ4JgEmt8PvJXePRm0WJv41PJ9Ola7z4Cbd0NuumJCrebhtMc2Bd/SXY+l64LgDzfl7UOinXepnTx9KDqPhEDuCCAAc1flGAyBZgJpW+mkufTxpUx01YRXs0hs9QQvHBtuOlNgIVG2gnxrdavGMWumTXto511qJ0/aOVB+CKSBAAIwDbVEGSEAgb4SYORqX/HzcAhAoAsE6g0IXbgzt4QABCCQEQJ+5GpFo2SPn55yliZAAAIQSDMBBGCaa4+yQwACPSEQHakaTfekEDwEAhCAQIwEaAKOAeYf/o9/1ihCTZBaLrqhQW2Kg/0gLrhhTUExWNYUF/648gyWanl9vrLO2+hEAgQgkDwCjFxNXp1QIghAYGMEEIAb4xdc/cSJKTertS83GrxIDIRiREiasPRicSluLS7DQtP2y6XaSMONlo/rIZBXAoxczWvNY3eUAP1ho0TSm0YAJqju5uZtLrCqu6jJIOIM5lcMRGOTiIx4JCUUTSx6D6ZNoHv2hWl32T3rRobKjesRl3HWDPdKCwFGrqalpihntwn4/rD2HN8f9o0/fqDbj+X+XSCAAIwB6i/8zK2uslgIZtaf1VxiNsP+bDDTvtbUnKtoX3F95v1GHM1n1+iYdTKPO5hv0p5rW8fhny+seslq4nKZ17Lu1QyLyJo30ybhXWo6H64LVTyXq6LnJAQgAIGeE4j2f42me14gHrhuAgjAdaNbunDPtVtjW8B+IVgRwDyBNcFmorCVaFwSmiFxGc6r64N7hI7ZElBxhw2JyzUKY10iw8LQeyhbiUbvuWwlLodCfTDtvBZ9qK2QsMbzOQ0BCEAAAs0E6A/bzCPNKQRgwmrPVhkYGbIt/qoJxOVcTTA2RGULoWjickaey9Pff85t2XaVhGRt7dBl15hIVV4Tml0Rl1KXgQDWM+IO5rkc+saZZoFZ91AGAjPYb/ZMLheXfiBPrTndhOaQBvPYsmLBqg9xF5r7QQACEOgzAfrD9rkCYnx8/CojxsJxq3gJBOJyWOJyeO1qt1UJHnts2v3QD+1feVmqUPGi4tILw7BoDMScF5w+liANezv9fjjuirhU2WcCodsFcSl12RCL8jguCcrw/pK4XNZUHuqL2fCA1gUp4jL00rELAQj0nAD9YXuOvGsPXFsJdO3R3DhLBDoRl53avaB+kSYka2JS+3WvYzvicna+IoHZfI31y5yenQ/Wf13QWq1xB1sDtlvi0qYKstHiDWEYEYt27sqlC+7R708G0w/5pnEvQv11TQK17vm0gT94LuN+G7gfBCAAgWQSQAAms14oVYhAUU2qm2wbLoeOrn+35t18TN7NH9JNBhrisllY1kRjWGR6r+TyfLWBPv78nHkWJVirXRCXVanLdsTlI8+c7BhQIC4HQ6PDI+IyLBqXvJZ1MSoRibjsGDkXQAACEOgbAQRg39Dz4CQQiFtchm2yEd2BgJQgbBaSS+KycTzk1WwWmHat5W8WmV0Tl7MSr9riDlFxOWxN43XPoxeO3ku5JDSXxKUdMw/lc+fn3Y4zl9WNYTA0ZRELGsVdX9wPAhDIPoHcCMCxsbHXLy4u/rqqtKxmrk+Pj4//Zrh6dX63zn9ax3ZpO63tnmPHjr0QzsM+BDohYP31bNsck+cy/OyVxOX0zLx78qln3M5d17l5jfoOvJJhARoSmjWPZURc6rx5GeMOgecyLnH5wNmm4hUKA6E+l/Jg1gfjRIVlU9o3o9dFaCA6w4K0vm/1R4AABCCQRQK5EIB79+7dJXH3wXK5fNsjjzwytX///q+Ojo6+dmJi4hu+UnX+DyQMPy5h+Gmdu1f7v69zb/TniSGQJAIriUtr3i7MPqfm7Re3NXinlU2BuAyLRhuwU0+bx3LJQ7k0gMcLzUYzeD1fkF8eTH+8K55LNbVPz1q/zkorczZ0rF1x2fBaSjh6oWnHak3lzc3q3vOJuNxQ1XAxBCCwQQK5EICDg4OvrVar35L4866DT0rg/bTYBQLw8OHDpVOnTt0h8Xe38ZQw/KRE4n/UblFb/O1h9hACBBJKIBCXI/JcjsTT5zJs5kri0vpMNovImmcyGMBTP2dTE509f8GVB4drA3v8NRZrNHlXPJc9EpfB5OdasrFSmXVX/cvD9fXDl1bm8c3jFgfN563EZcibaV0bCBCAAARWI5ALASgAe7R9LwTilDx+1/v0008/fY28g7bkhRd7Fk/dfPPNOyUav+/zEUMAAhsjsBFxGR68Uyzab7OloM9zsIqO9Zf03krvdVzez7LukYx6OSUkbYCNv64R90BcTi2Z4k6fPRdKrW+36JvFQ6JwSURGPJINMYm4XB9troJAOgnkQgDqy2HZz2F5ABtrrg0PDxfsyyUSBmZmZhp5IueaklV19l8oLLu+KU/aEmaTBR+nrfyrldfb5OPV8sZxzhZP/4u/e9qdfP6Su37nFvcT//oHnM2l1Y3gbfJxN57Rr3t6m3wcLYc0jxvRKGbb1NU3enrd6SZxGfI61prC5akMHauJxmYRGvZi1vIuNYlb/i4MFnc2vdEVNYnbFncwcenFpE18bvtBOohr4tI3ideOK4+8m2fOTLvpgefcsCa5t+mKlprI/TKQBa3Ss+xPddzFj/1+/n30cewP6OMNvU0+7mNRYn90Fm3qFFIuBKCgnJTge5WHo/3r9Ef9pE/v2rXreTUBb1Pa/vqY8jH3wpYnnnjijOI1w+TkhIu/2/yaj+1JhvFj4z15Tj8e0ivbjmg95Wen5gMTH798xZ07d84dfrm9bt0LvbKtexasfOck2WZ/KDbZZn9JbRvR1hRszRnL1eyx9FlMXNpvLRuwYxOez1e01eMgbft2zh+PnFvpuL+Hf06csYnLdfe5fOjRVYti+q+s0d622ajvcmn5fvic5RlUniBv5JogX/1627f+nN0MSXov47Yzi7bZ23DNtvh+KMbNvBf3y4UAVHPRN+Xhe/++fft2bt++/fylS5d+ViLwwx7wkSNHKhr48Vfq9/cmjfz9lOI369wRbW259fbtG3WlcrZQ2q8j+9CP7R9zhYz1J+q1bV/5p3+S12NJAFyuFOpzEPo3ML6417bFV/K175Rl28z6uO0zcTlf8d5GH9eauJd7JWvTDYWbz32eZg9n/T5qKu/Gj14the5mJTBntfxk3MFE4jLPpPde1pvKvWdyyatZn4qons+fX5oHU9MTSVhOTh7jb2XcFdbl+1W0SMC55453+SnJvn22VMsKrB977LHTEnjvKxQK37p48eKgsv2ZhN6XJPQ+qj+SX9Kgjy8rfo9E4Sd07Jd1/owGjbxphdstO2wCKdonaVmmlB7Ato1X3A3XbnXHTy/18rJ0t98X6m3j9davO8RZdyX9hR8Zjt+SZnFZm+dy2ejwUH/KGa28c/rZF9yWrdvdnBeljT6YkWb0LolL86hWFiru8kz8zeLmuRz5ptYWbwjJWrN2WCj6ZnJrNrepiryYDI7rOotbzY/Zbc9lO29HnO9kO8/rRR59x/fiMYl+Ri4EoNWARN6fKLKtESQC3+ETk5OTJ7X/Wp8mhkBcBFg8PS6S3CcpBPRjORAsJlq2tFGo2gCeWXm+x9b88bNMXDaEYt1LqX6TS2IzKj6bz3kvZtA3sy5I4/ctynsrLWHCshvisqz+k148thKN3qvp+1TW0qGBPuGBQBGBmgRx2cbrQ5YuEciNAOwSP24LgTUJsHj6mojIAIEGgU7FZePCNna8uLRm7SYRWReHfpCOTTnUJB79QJ9Ivtp9Klo9pxL04eyGuLRmfNsuT9f6EbdhZttZWolL81p6UWnnL2tt8fHnnnAjQ+WaEK17K73QHI56M+vN5YjLtquhbxkRgH1Dz4MhAAEIQKCXBMLicquN3okh+OmJDhw4oBHd9bXFw17LiGhsJS7DYnRp+qG6dzMQn91prmxXXB49fqJjUmuJSy8yw4Iz3GS+dDzkzTRxKQFqS0sSNk4AAbhxhtwBAhCAAARyTiAQl6VaX764xKVHapOcz9ua4N4T6eOQuFzyajbnayUum4/1V1x6GzuJTVyGBWSj/6QE4pCmgVpqMl/yZi4JSstTdOVCta3uC52UK215EYBpqzHKCwEI9JyAzeX4lQeeciefu+iu1yAe69fZrbkce24cD0w8AfN4BQJGwiXusCQuKxKYGuUd8l5Oa/DOU8efcS/a+eJgOqKGAA2EZ7PQ9J7LXopLt4Fm8SFNEfR/v8HWiMhvQADmt+6xHAIQaJOAiT8/kttiS7/xxw+0eTXZINBfAqv9gFlNXFrzdnn+eQ3e2b3m4J1WFi6Jy1pzdlhceo9lQ1SGvJqNY1qFpyEsdT4sLq35mrAxAgjAjfHjaghAIAcEzPMXDtF0+Bz7EEgagX79gFlNXG6UkYnLqKD0A3fCQtELyCAOeTcry1f/2miRUnc9AjB1VUaBIQCBXhOwZl/vAbRnW5oAgbQQiP5giabTYke4nCYubVlB29YT5ufn3ZnTT67n0sxck76FFzODHkMgAIG0ELA+fzdet11LjhWC2NIECKSFQPQHSzSdFjsoZ7wE1ied4y0Dd4MABCCQaALM5Zjo6qFwaxBgMvo1AOX0NAIwpxWfR7N9R+gT6s+1uTTvdt8w667eHtNkYHkEis19J+DfaWvSM68Oo5P7XiWJLAA/YBJZLX0vFE3Afa8CCtArAr4jdEWjx56dmnd/8XdP9+rRPAcCXSHQeKcXqkEfRUsTIAABCLRDAA9gO5TIkwkC0Y7PJ5+/lAm7MKKZgE1dYZsFm5y3UCgEm+1bsHNnp664P3/gSXfy2anAc/YT6tN3lWbvtbzFYjG4zpYNC2/+PsFNEvLPsnc6Mlq502LiUeyUGPkhkF4CCMD01h0l75CANZE1jeTc2c4y9h0+JGfZl8TUE+7Esxfcnp2b3f/+b37Qbd80GIgoj8Ok14DaG2x90KIJMh2wfRvJN1A/5sWWTe+g/wPxVfWxdqom7OanXVVbYbFUE3e6T03kmdCr3a88UnLl0lAg5iqVmhhcqFZdtbqgvAVXGi66//G/Trhnz824waFh95y8wQ88/Kz7v/7ty7Tm6oKrVCrBs+1+wX+FmiC058/rXFVlWahvtl8rr8qsacls38pjtgRy08qn/yztdJ/y4GBQLs9lo/Gyd3qDo5O9R9HKxXyHG60drodAsgkgAJNdP5QuRgK+I7T1Adw1XHY/8a9/IMa7p/9WNi1CtWILzi/W1tqsiytznJlQ8wIriOuirSSxVRNTs25oeMSdubTo/v5fzrj77r6lJnp0NxNE3vu2EUomNs88u83dsHtn25PSSm+1DN97YUZ6bGlVhWeeveyGhoa0tcze0cFA/Bm0ULBjJiynp2e02sK8qyxIRKrZNhCQgYiUZ1Kx1YHZad7Gdpj5dzrcBzD02I534/YodlwALoAABHpGAAHYM9Q8qN8EfEdo+4J97LHHMr2Ul9lYlddrMfB8Vc0HZS41c0c1xJ3Vh01rYputrblj87AbHt7esYcqKqaOn74Qm+jr1juzd/d2N3HiXOP2lo4rtBJudqxcLgdbq+eYQJybm3PPnyq6q7eWgywLC/I2qspMKNqqB5VAMKoKiyU3WFe2/p1udc/1HIvbo7ieMnANBCDQGwIIwN5w5il9IJD2/kzea2RNl1JzEm6CWBdwJijMyRQ0U2rHzpmXrlqsurKblZjTgudDg4GnzPq0tetRWk81dVNMrac87Vxzz51j7nNfH3dPnZpyVn5L9zNYfZZKpcALuWXzphU9nPZOzM7OustXZhpLZC1UtU7s8HBbHsO1bOzUo5j2z9haPDgPgSwTQABmuXZzblsS+zM1RJ08dIsSdkUpN9+k2qqJdWjLsLw95cbAhLWq1Dx/27dtcVu3bllRRKx1j07PJ01MtVP+q7cNB83U7eRNUh4TisMSe7b5YE3LFy9dkSCcb/IUFuQpLMnraNe0Gzr1KCbxM9aureSDQN4JIADz/gZk2P5+9mfy/enUlStoYi1aU6vEXnlQnrmtw0FToHl8shDSKqaywN5ssPdox1XbmszxnsLpmblg4Io1H9v0RxarDVkDb/Q+6jrzDG8k9PMztpFycy0EIKC/HUCAQFYJdLs/05I3r6L+dVV9oVpfOo30rPenGxm5qiPvS1brAbt6T6CVp9CXwjyGts3NmcdwaVSzicNgdLNiDQMKvIdr/Ujp9mfMl5kYAhCInwACMH6m3DEhBDrtzxQutok7a061jvi+/51vqvXevFK56IblzbMO+dbPLgvh7IWZZX3jzMNHyA4BE3W2hZuRo9bZuz8zM+umZ82DWPceKq6qOXlwsDbFjl2zkc9Y9JmkIQCB3hJAAPaWN0/rIYGV+jOZuLMm2tnpKxJuNklwbW66YtHiWp+8kgTdkL7oBgdrfek66UfVQxNjf5QNjPCjYy22tE3pQsgXAftBs1mDUWwLB/McXrky7WbNeyhP4ebBqvs/XvWSppHJ4fxZ2mfAS5ZqE1uMAAKQ9yBTBLznzk+BEszOqwatYLoTNc1arMGx7uotRfcDe64JvHeZArBBY2xUbDhE0+Fz7OePgHkOt23b2mS4feb8yGTzFtY2jVzXxNfmLczKjycGvDRVO4kMEEAAZqAS82KCibqKPHdVNcsGnrrAY1fz4MlxF3jzbJWJcnnQDZZrHdz9sl5hRta8ZZP+ZqXZNmzbRvfTOKXLRm3m+o0RWKm/oXnZr9jE1/IWLixo8uu5aTc3I697aTDoX7jRASgbK3XnVzPgpXNmXJFsAgjAZNdPLktnQm9ublbLfS3qy0IjZzWwoiSxNzSkfks7tgYjaLPiVUhaBadxSpekMex3eZLSj9Mmvt6uzYL96Hr++9vcjdfvDFaICa+IEoxOtv6FmuTSlspL6g8zBrz0+83m+XETQADGTZT7tU0g6Iun1Q8W5dGzEbTBKFprotXyYpuu2RF0VG/7ZmSMhQBTusSCsa83SXI/TvvhZs3IJg6jwUSieQxnNPDERKE1JS9oyTxb+cSEYb8DA176XQM8P24CCMC4iXK/4Bd+MA+eJjoOpqCVJ8/Ens1Ha4MubJqUYPkxjaLdfNVW+uHxzkAgRgLRfpvRdIyPivVW5vnbumVzsPkbt+pfaOIwOhrZ5+9mvNKgsm4+k3tDoJsEEIDdpJuDe9sfaGuuHVCzbblcE3cWb9q2Kfilb7/4u7kMWQ4QYyIEOiKQpX6cK/Uv9KOR54I5DWsTXNschlXzGJZWXnO5I5BkhkDGCSAAM17BcZsX/CKfmdEgjEU3ZPPgqV/erh3bWzbpxP1s7gcBCKxNIA/9OFuNRjYy9vfJ+hde0RyG8/MLbq7ejFzSaOSk9i1cu0bJAYHuEEAAdodrZu5qTbkL8vDZYIxBDcYYGiy5F19N/7zMVDCGZI5Anvtxmsdw06aRYPMVa4PKLl26HExqPStRWKlocJlmCjARSYBAngnwCchz7Ydsj468tWlVSouz7tqrht0W9cuxP6wECEAAAmkjYF1QbO5Cv1qyeQltMmu/ysl8xUSh1kjO2LyFaasnytt7ArkQgGNjY1v1of+U8I5quySx88bJycknorj379//9zq2WZvW/wrCO48dO/bt+n6mornZWc2RXNF8ebW1a4dHym5zaOStjch79tSW4Jc04i9TVY8xEMg1Aft71mqVE2vtuHRZcxUqDiaznu/PYJNcVw7G95RALgSgBN9v6Ffgd8bHx/+txOAd2v+kKL8yTPrw4cOlU6dO3SDBd334eBb2o/32TPRd86LNq64FmgW7sQECEIBAuwRsapodVzVPT2ODTS77pe/kJTRvYXVR3WGGhmkVaRcs+RJLIBcCUL/4flIf5DusFiQC/1Kevl379u27Xl7Ak75mTp48eVCdhBd07hs6tlOi6SMTExMf8efTEJvQ8ytlqNWjNtWKplwZGirTb6+LFZiUiXe7aCK3hkAuCVg/we2Rpe+sdeTCxUuar7CiVU4W3IIEIQECaSSQCwGoitnzxBNPfC9UQae1b56+hgDUB327PIXf0K/A+/QB36rtyIEDBx5XOBK6ri+7gbDTL9Gq/vDoH3VVGdAo3IJGtWmKlWCaFZtqpXZsRNOv2DJnNNv2rqqSPPFu7yjwJAjEQyDpP6hsNPGOq7Y3jL0oMfjU4oyWO7GRx/oTPVDI1BrIDUPZyRyBTAlANe/eLbH0IdXSoq8pCaGTOrbsJ5qagdXrdynUhd6R+pEzutcfSRDepbQ/Vj+1PKouaMb6gsTZBoL1ydOSGBqZJmEnMdck7ILVMcr6o1KbW2+tx6jca2VZ87z9yrXg4zUvSFEGb5OPN1r0J09NafqJpbtYOq57L921vT3/XB+3d1U6cnmbfJyOUrdfSm+Xj9u/Mvk5vU0+Xq3En/3a427ixPkgy7FnzjlLv+unDq52SV/PDQ0Nuh3bt7oX77wqmGqm1hqEbTcAAB28SURBVJfwSuAdnNd3QzDAZEB9rbWaSdp+mNt3mwUf9xV0zA/Pok2dIlomjDq9QRryq1l3UuV8lfr3BV5AS+uD+KNqDj7ly69jr9b+rPI8YMeU/kVF1yr9K5ZuFR588MFt8hxOnbkwv6Q4W2WMHDOBVqnMu+JA1ZXMcydP3qbhQVbEiHBKS/LL/3jOfe/sXKO4e64edHf98I5Gmh0IQKB9Ah/7+nPOJnX2wX4Qv/3Oa30ylbGJwukZLXFnzgLZVtGE1YsShSVNWi1nRCptSnuhTfxcs62s7+LK9kOHDl1Iuz3rKX+mPIArAZDY+4rO/Zy231Sz7mEJsIth8Ve/bqfi+2+//fY7pqamRrT/VnkO31E/t2q0b9+oK5VXRmkf/mC926ILRt0Oq0/els2bEj0xqf1SP3r0qDt48GCiy7lqxaxwMm7bXvKDM+7z35xwT52+4PZet8294TWjzuZi60eI27Z+2LDSM7Nsm9mcZfs6se1lTx5teACNy+gNV7lbb02uB7AT28weHxoDTNSXsOYprPUnLGmOwqRMWm1esvFj425s/5i6HmVLqFbmK+7cc8d9deQyXlm1ZAiHBNivqW/fH42Ojh6V+JvRh+tnzTyJwduVfr+8fHdp+5yafW+7ePHiw/pFZm/6f9IgkH9oB4N9MOwDa3315ufkCVI/PfPq2Zq3ZY243bTNRtwOpfKXntmVlD9G7dRFJ3nism3njs3uPa+/tZNHdz1vXLZ1vaDreECWbTMcWbavHdt+5scOOOtXa2sY27J2trKJXZf00I5tYRssv/XXDgcTk5cvX3EzcxVNR7OgPoVVV0jApNX+Oy5c1rTvW0tc3kMuBOCTTz45pYq+O1rZ6vf3HR2zfn5BkFfwl7RjW2dBnX9L5UU14Zbcpu1bgqbctPX16MxgckMAAhDoDoE8r2RiorDVpNWXp2cDQWj9CRlk0p33Lo93zYUA7HbF7t51Nf33ug2Z+0MAAqkiEB7Ne6O6Rtx83cYGyqXK+JgKa46E6KTV1nR88dKVxoTVgSh0A3JCJKfpOCbzuU2XCSAAuwyY20MAAq0JhAWCb+rrV9/J1iXk6EYINE+PdN698ELF/ci/2sgdudYI2NyEO67yC9vVmFjT8ZXpGc1NqIEmwYTVGmio/nsDhVIqRx9T070hgADsDWeeAgEIRAg0C4RzQb+v++6+JZKLZFoJWB++cPj+eU2SR+gKAWs63qo1220Lhzn1Sb98ZWbJWyhRaF3fChp9bCufEPJNAAGY7/rHegj0jUBUIETTfSsYD46FgHl1J06ca9zrxZFl1hon2OkagUHNPWhbONjgh5mZWXdFW8NbKK/hosY+ltWMzLQ0YVrZ3kcAZrt+sQ4CiSUQFQiW3kigSXkj9OK/1kbv+tG8tT6AS3Nlxv807tguARN4mzaNBFv4Gj8tjTUjz2n08bxGIduAE0J2CSAAs1u3WAaBRBMICwTfB3AjBaZJeSP04r82PJrX+qg99NBD8T+EO8ZGwK977H+G2bRmly5ddk8vzrrC4pyrzg9orkpNZK2FtUpqPrb8hHQToAbTXX+UHgKpJRAWCHEYEW1CjqbjeAb3gEBeCNgIZPMUXqWpza679urGXIwm5qfVfGybb0Je0MomA8VSIAyZAi09bwgCMD11RUkhAIFVCMTdpLzKo7p6ypqyv/CtyaaJkBkd3VXk3LwDAjbgxFayss0H8xbOaj17W+5uTitf2VJ3Ngq5qthJGEb7IfrriPtLgAb+/vLn6RCAQEwErEl59IYdrqSVeSy2dBqDLStogyfsC9Ria9omQCDJBMzrNzw8HExPs2vn1W7Pi69xP7Bnp7vxhp3uums2uaFixRWq8hjOTbvZ6SvBsodJticvZcMDmJeaxk4IZJxA3E3K/cJla0qHA03ZYRrsp4mAF4YmDn2wUci23N2VwFuo+Qo1AnmAaWk8np7GCMCe4uZhEIAABFYnsFerZkyePN/ItNHR0Y0bsQOBBBCwUchbt27RViuMNR9PaxJrm69wtr7+sfUnLEemr0lA0TNXBARg5qoUgyAAgTQTeMNrRpf1AUyzPZQdAqsR8INNbMCJDzMzM+6SBKFNRTMvD6H1KTRRSF9CTyieGAEYD0fuAgEIQCAWAllpyo4FBjfJJQFrMg43G/tBJrVVTRbcnEShjTwuDQ41RifnEtQGjUYAbhAgl0MAAhCAAAQg0D0CK/YlvDKtVU3mgqZj60toE1cPShRafsLaBBCAazMiBwQgAAEIQAACCSIQ9CWMrH88ryloLmmAyeycvIRqPram46KWt2PS6tYVhwBszYWjEIAABCAAAQikiEBZK5TsuMqvZeKcjTi+ogEm09Ozy7yEKTKra0VFAHYNLTeGAAQgAAEIQKBfBMxLGJ202nsJL82zNjUTQffrzeS5EIAABCAAAQj0lID3Eu7auaOnz03iw/AAJrFWKBMEekDAlhyzVSZsomGba85WzmDJsR6A5xEQgAAEEkAAD2ACKoEiQKAfBEz8seRYP8jzTAhAAAL9J4AA7H8dUAII9IVAdImxaLovheKhEIAABCDQEwIIwJ5g5iEQSB6B6BJj0XTySkyJIAABCEAgLgIIwLhIch8IpIyA9fkbvWGHKxULQWxpAgQgAAEI5IMAg0DyUc9YCYFlBFhybBkSDkAAAhDIDQEEYG6qGkMhAIF+EWDEdb/I81wIQGAlAjQBr0SG4xCAAARiIsCI65hAchsIQCA2AgjA2FByIwhAAAKtCURHWEfTra/iKAQgAIHuEUAAdo8td4YABCAQEIiOsI6mwQQBCECg1wToA9hr4jyvJwToc9UTzDykTQI2wjq66kqbl5INAhCAQFcIIAC7gpWb9puA73Nl5bDVLix939239LtYPD+nBBhxndOKx2wIJJhArgTg6OjovQMDAz967Nixe1vVic6/V+ffrXNFbb+rfB9tlY9jyScQ7WMVTSffAkoIAQhAAAIQ6B6BXPQB3Ldv35DE3X+QuPs9bYutcOr8rTr39rm5udvK5fLtyvPeAwcO7G+Vl2PJJxDtYxVNJ98CSggBCEAAAhDoHoFcCMBisXiHCT+F962C8i7l+eLx48dnHnnkkUva/8LCwsIbVsnPqQQTYJWLBFcORYMABCAAgb4TyEUT8Pj4+FdF+qv79+9/y0rEC4XCHp37duj8KR17RSjNbooI0OcqRZVFUSEAAQhAoOcEMiUAx8bG7paX70Oi6Jt5B7T/jPryvXItsrquIK9fU7aqQtOBFRLyFDrbshS8PT7GtnQQ8PXl43SUur1Sept83N5V6cnl7fJxekq+dkm9TT5e+4r05PA2+Tg9JV+7pN4mH699RXpyZNGmTulnSgDK0/dFAbCt4yDxd1J67zp/oe3bMZ9eLX700UdXO53qc0ePHk11+VcrPLatRie557Jcb0Y9y/ZhW3I/V6uVLMv1tprdWT+XKQG4kcqS2PtzbR/bvXv3h3bs2FGYn59/vbyCKzYZh5910003ucHBwfCh1O/bryP70B88eNCpD2Xq7QkbgG1hGunZz3K9WS1k2T5sS8/nLFzSLNebBny6LDtvwvW40n6uBaBG+d4uT9/71UR81+OPP/4d9RH82JYtW/5R4q8kMfiHOv7QSuDCx00gZU0kefuwzZNIV0y9pau+wqWl7sI00rNPvaWnrqykVl95D7kSgBJ0/00VblsQTPRp56560un8H2jfNgIEIAABCEAAAhDILIFcTAOT2drDMAhAAAIQgAAEILAOAgjAdUDjEghAAAIQgAAEIJBmAgjANNceZYcABCAAAQhAAALrIIAAXAc0LoEABCAAAQhAAAJpJoAATHPtUXYIQAACEIAABCCwDgIIwHVA4xIIQAACEIAABCCQZgIIwDTXHmWHAAQgAAEIQAAC6yCAAFwHNC6BAAQgAAEIQAACaSaAAExz7VF2CEAAAhCAAAQgsA4CCMB1QOMSCEAAAhCAAAQgkGYCCMA01x5lhwAEIAABCEAAAusgkKu1gNfBh0sgAAEIdETg7IUZ97mvj7unTk25vbu3u3vuHHNXbxvu6B5khgAEINBtAngAu02Y+0MAArkiYOJv4sQ5V1moBrGlCRCAAASSRgABmLQaoTwQgECqCZjnLxyi6fA59iEAAQj0iwBNwP0iz3MhAIEGgSw1m1qzr3kAfbA0AQIQgEDSCOABTFqNUJ5UETDh8uEvPuze9/t/HcSWJnROIEvNptbnb/SGHa5ULASxpQkQgAAEkkYAD2DSaoTypIqAFy5WaPP6WPq+u29JlQ1JKGy0mTSaTkIZ2y2DDfjgHWiXFvkgAIF+EcAD2C/yPDcTBKJCJZrOhJE9MCLaTBpN96AIPAICEIBArgjgAcxVdWNs3ATo7xUPUWsmNe+pCWhjSrNpPFy5CwQ6IRDti/v6V+/r5HLypowAAjBlFUZxk0UA4RJPfdBsGg9H7gKBjRCIdmn5/Dcn3KEf3MgduTbJBBCASa4dypZ4AgiXxFcRBewhgagHyX4gMQl2Dytgg4+KdmF56vQFCcDNG7wrlyeVAH0Ak1ozlAsCEIBAygh4DxKTYKes4urFjfa93XvdtnQaQqnbIoAAbAsTmSAAAQhAYC0CyzxIkUmx17qe8/0lYB7b8BRGb3jNaH8LxNO7SoAm4K7i5eYQgAAE8kOAQVHprutol5aFhQX3TLpNovSrEMADuAocTkEAAhCAQPsEoh4kSxMgAIFkEsADmMx6oVQQgAAEUkcg6kFKnQEUGAI5IoAHMEeVjakQgAAEIAABCEDACCAAeQ8gAAEIQAACEIBAzgggAHNW4ZgLAQhAAAIQgAAEEIC8AxCAAAQgAAEIQCBnBHI1CGR0dPTegYGBHz127Ni9rep5//79f6/jNu15pX7+ncr77VZ5OQYBCEAAAhCAAATSSiAXAnDfvn1DEn6/oe3d2r7YqrIOHz5cOnXq1A0SfNe3Os8xCEAAAhCAAAQgkBUCuWgCLhaLd0j4LSq8b6WKO3ny5EHlWZAX8BvaHpK38F0r5eU4BCAAAQhAAAIQSDOBXAjA8fHxr8qz9ysSeDMrVVapVNougfiNcrn8ukKh8Grle8+BAwcOr5Sf4xCAAAQgAAEIQCCtBDLVBDw2Nna3RNyHVBmL9QoZUPyMxN8r16qgxx9//Ijy2GbhjO71R9Vq9S7tH7EDqwVbLse2LAVvj4+xLR0EfH35OB2lbq+U3iYft3dVenJ5u3ycnpKvXVJvk4/XviI9ObxNPk5PydcuqbfJx2tfkZ4cWbSpU/omkHIT1LT7FnkBXyWP4M9FjdY58/rNSiw+YOeU/kVF15rn0NKtwoMPPrhNnsOpVuc4BgEIQAACEIBAsglUKpXthw4dupDsUnandJnyAG4Q0U5df//tt99+x9TU1Ij23ypv4jvauedNN93kBgcH28mamjz26+jo0aPu4MGDTn0oU1PudgqKbe1QSl6eLNeb0c6yfdiWvM9TOyXKcr3Nzc25Rx99tB0Mmc2TawGoPn63q5n3/fLy3aXtc2r2ve3ixYsPqw+g9Y38TxMTE//QTs2bQMqaSPJ2Y5snka6YektXfYVLS92FaaRnn3pLT11ZSa2+8h5yJQAl8v6bKty2IKjf33e0Y/38gqCm4V/Sjm0ECEAAAhCAAAQgkFkCuRgFnNnawzAIQAACEIAABCCwDgIIwHVA4xIIQAACEIAABCCQZgIIwDTXHmWHAAQgAAEIQAAC6yCAAFwHNC6BAAQgAAEIQAACaSaAAExz7VF2CEAAAhCAAAQgsA4CCMB1QOMSCEAAAhCAAAQgkGYCCMA01x5lhwAEIAABCEAAAusggABcBzQugQAEIAABCEAAAmkmkKuJoNNcUZQ93wTOXphxn/v6uHvq1JTbu3u7u+fOMXf1tuF8Q8F6CEAAAhBYNwE8gOtGx4UQ6B0BE38TJ865ykI1iC1NgAAEIAABCKyXAAJwveS4DgI9JGCev3CIpsPn2IcABCAAAQisRQABuBYhzkMgAQSs2TccounwOfYhAAEIQAACaxFAAK5FiPMQSAAB6/M3esMOVyoWgtjSBAhAAAIQgMB6CTAIZL3kuA4CPSRgAz7uu/uWHj6RR0EAAhCAQJYJ4AHMcu1iGwQgAAEIQAACEGhBAAHYAgqHIAABCEAAAhCAQJYJIACzXLvYBgEIQAACEIAABFoQQAC2gMIhCEAAAhCAAAQgkGUCCMAs1y62QQACEIAABCAAgRYEEIAtoHAIAhCAAAQgAAEIZJkAAjDLtYttEIAABCAAAQhAoAUBBGALKByCAAQgAAEIQAACWSaAAMxy7WIbBCAAAQhAAAIQaEEAAdgCCocgAAEIQAACEIBAlgkgALNcu9gGAQhAAAIQgAAEWhBAALaAwiEIQAACEIAABCCQZQIIwCzXLrZBAAIQgAAEIACBFgQQgC2gcAgCEIAABCAAAQhkmQACMMu1i20QgAAEIAABCECgBQEEYAsoHIIABCAAAQhAAAJZJlDKsnHetgMHDtxYrVY/pvSLtFUGBgbeNz4+/pf+vI9HR0ffq3PvVrqo7XePHTv2UX+OGAIQgAAEIAABCGSFQC48gBJ//1nC7hMSdLeq4t68uLj4WcUD4UqU+LtVed4+Nzd3W7lcvl3n3ivhuD+ch30IQAACEIAABCCQBQK5EICqqE/Nzs7+iVWYROAxRYNjY2NbLB0Kd0kAfvH48eMzjzzyyCXtf2FhYeENofPsQgACEIAABCAAgUwQyEUTsDTff/e1tX///l/S/nfVBHzRH7O4UCjsUfTt0LFTOvaKUJpdCEAAAhCAAAQgkAkCmRKA8urdrebdD6lmFuu1Y828z0gAvtLSOv/LOv82efdeVT/fiHS8oOONtO2o6bjadGCFhJqNVziT3sPyfgaFN9uKResSmZ2AbemsyyzXm9VIlu3DNj5zSSOQxe/tThk3K55Or05RfvXx+7AE3iH9IfrxJ5544rlo0SUO/70JvomJif/Hzin/ryp/VeLxt6N5ffqhhx7aU6lUTvo0MQQgAAEIQAAC6SFQKpWuv/XWW7+XnhLHV9JMeQBXwqJm3/fr3M3Dw8M/8s///M+XW+WT2PtzbR/bvXv3h3bs2FGYn59/vbyCb2mV1x+75ZZbTj388MPXz8zMNDUn+/PEEIAABCAAAQgkk4A0wVb7Hk9m6bpfqsx7AF/+8pdvlkB7QShN4V/QZjZbE/FPqo/fi+X0e7+8fHcp7SQU36PIpoEpSQz+ofoJ/p4dJ0AAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQKCnBDI/Cjhumlof+EaNHP6Y7vsibRWNFn6fRgv/ZfQ5mkfwvTpnI4ptFuXf1Ujjj0bzJDWtst+rsv+oynxvqzJqtPTf6/hmbZX6+Xcqb3gVlVaXJeLYWralsd40h+VWTVn0KQEe1XZJ7+cbJycnn4gCT1O9ySabhunXZUNZ7+Kn9Rn7zbA9Or9b5z+tY7u0ndZ2j95BG+2f+LCWbfv27btTMxR8RoacMGNk53c1P+nbEm9YvYAq/zaV/wHNkXrXk08++Uy43GmuN7NjNdvSXG/62/CLes/s776ixW/v2bPnnUeOHPF/320RhdR+3qze1rIvzXVn9q035GUt4PXyWXadvlz/sz4kn9CXza06+WZ9WD6ruElIS0Tcqjxv10zjt5XL5dt1/r0SjvuX3SxhB/QhGFLZ/4PK/nv2h6BV8Q4fPmxzR94g+1+u7bb6lnjx145taa03vZO/ofr6juriZsW/oi/fT0brLk31tnfv3l36XH1Qnx37EXKT9n9UdfPasE069gey9eNms/ZNLP1++HxS99uxTXb9sLbfqn+2bkuZ+Dtk4k/8W/69S2u92fukvyGr2pbWepM4siVP36K5b1+hd+7lsqN8+vRpmxKtEdJcb+3Yl9a6a1TQOncQgJ2D+9Ts7Oyf2GX6sBxTNKhfR1sit7lLL9QXjx8/PvPII49c0v4XtALJGyJ5EpfUkm93qKz6rC++b6XCnTx58qDyLOhD9Q1tD+mL+V0r5U3S8XZsU3lTWW+qj5+Ut+X/Nd51b/QufVldb2kf0lRvg4ODr9U7+C19ds6q/LYm4Sdl4097W+pi9g7Zaj++nASSCd7XaStaOslhLdvqZX+F7H+dPl//pO1Ptdk65akIqqd3aLOWj2WT66a53gz+arbVKyeV9abvpnMq//32fVW342G9fy+p77u019ta9qW57nwdrTdGAHZITprvv/sPiv4w/5Iu/66+iJpWAtEvYPuD/b3QrU/pWNMXcuhcYnZlx1dl36/oD53/Q7CsbFo2Z7v+OHxD3pnXyaZXK8N75N08vCxjwg60Y1ta602o92h5w/D7Zk2iTe9byupt2edH71zDnqeffvoa2WeTutcWrK7FUzfffPNOHUt6WNU2K7w+f2dl7wf1WbxN8dd06I+TbpQvn3kr9Vn7WzPDH/NxyuvNfmisaJvZmNZ609+OSb1rf2M2vPSlL71W0f16775kaQtpr7dW9smsPwuMq/+T1roL27Ce/VwsBbceMPLq3a0PwYd0rW8KtT9oz+iD8kq7n87/ss6/TS/OqywdDjpe0PHwIadmumrTgT4m1rJttaI9/vjjR3TeNgtndK8/kmm2ksoRO9DvsBHbUlhv9qVzUuVuftlUCRKzTe9b0ust/N5YPYTTti87G/Zo+aaCftUvy6IVfxp5oieTkl7LNiun/sbc68sr0fER/dD8Hb3XW6M/NH2etMRprrd2GKe93ur9278sW/+L3ru/9jZnpd7C9nnB621Me915OzqNEYArENMf2y/qlG3Lgpo9P6w/5If0JfRK/bp4LprBvpQliq7zx23fjvl0v+PVbFurbPoyMq/frD4w1s/HOqjbl3XF9pMQNmJbWutNdTKp7TrVifcCLnvfkl5vkXfnpOqi8cNK+9fpPWt8fnbt2vX8qVOntukae/dM9FnT7xZ9Fs8oTnpY1Tbrqyrx/guqyw+EDVG3k/lwOo37Ka+3VZGnvd6s/7O+p0z8/bbevQ+Hjc1Cva1mX9rrLlxXne4v+6Xd6Q3yll9fpO/XF9LN+lX0I63En/HQ+T/Xdvfu3bs3qVlqi/ZtROOfZ4SVNbN94Pbbby/rg2Nfwm+VbX+aBdvSWm8q91e0/ZzVQb05/qKEcLQPVmrqTf01vylT/je9XzvtPdP+z5qNZp8FG52od+6v9Fl8k6UVv9kOa1vmFtSxRIW1bNPo7VkV+K36wrI+jU6xeQMf9N1O7FhaQ5rrbS3maa43+5zp8/UXsvH+qPgzu9Neb2vZl+a6W+u9XOs8AnAtQqHzL3/5yzcraf3+9qi56W/0xfNdbdZRe4++eG9XbL+gnJrbvqPoY1u2bPlHjaz6//Th+rhc6g/ZuTSGsG36A/E52fN3Fy9efFiein+UPdZc8A9ptMvKHLYtrfWmd+zXZMotEgtH9Sv+gxIZPxu1LU319thjj52WwHuf3q9v6T07qn3rZ/slfb4+Khutu4F5nm2U4v+pY/+i+Odk93vteNJDm7bdo8/Yv7f6VGwi9+1Jt6tF+XzXGRPoqa+3iH0r2ZbKetPfi5+XfVu1/ZrqKvhOU5eD39T+f037583qrU37Ull3Zh8BAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCDQCYH/H0t020mU+Pw0AAAAAElFTkSuQmCC\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x119a63a90>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plt.figure()\n",
+    "sns.regplot(x, y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'];\n",
+       "    var y0 = fig.canvas.height - msg['y0'];\n",
+       "    var x1 = msg['x1'];\n",
+       "    var y1 = fig.canvas.height - msg['y1'];\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x;\n",
+       "    var y = canvas_pos.y;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"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",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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BERg4QQiC69icWrYtWvX+yORyAdQWwEv9msrXp/L5/N/GI1G/xbn7XgdGhkZee+ZM2dGca4kAiIgAiIgAiIgAiIgAstOoGoM6PDI9+zZsyuXy/17LBZ7JY5fxLWfOXr06IO7d+/+IM4TOP+1cHmdi4AIiIAIiIAIiIAIiMByEYguV0PzaQdG85/DG/1/ZzKZGO5ro/HM+5FPT/R9PFcSAREQAREQAREQAREQgZUgUHUGNLzMrwKIdc8///w/wYjehPOzHsyJEyfO4Zx5SiIgAiIgAiIgAiIgAiKwIgSqzoCejIP+EGkUCoVS/cvPRgr3RB566KE2Hmcrp2siIAIiIAIiIAIiUA0EZLtUwyzMrw9VZWS+9rWvjZ87d+5sKpXa/vTTTw/v2LFjC+Kgv4YQjp0c1s6dOzfDwP7qsWPHdpcbJo3neDw+UO668kVABERABERABERgsQgcPHhwwbaUbJfFmo3513O98xeff1NLdwfUNfZBceMYjWe2gpCN0wjpGGZYB4zoB3DtffiU9oVKerB3715raGiopKjKgADiy+2ZZ56xffv2GT60iEkFBMSsAkhFRcSsCEgFb8WsAkhFRcSsCEiFb8WtQlChYmS2mEn/Bi8mzaWtq6oMaBhuO2AgvxQeMmTs3o38v4UR3Yb8F2BEvyd8vdw5jUAZguXolM8Xt/Jsyl0Rs3JkyueLWXk25a6IWTky5fPFrDyb2a6I22x0lvaa2C8t38WsvaoMaCwc/P8wOL6m0vHjxw/jzb1TGToRAREQAREQAREQAREQgRUkUGqR3gp2R02LgAiIgAiIgAiIgAiIQHUTkAFd3fOj3omACIiACIiACIiACFQZARnQVTYh6o4IiIAIiIAIiIAIiEB1E5ABXd3zo96JgAiIgAiIgAiIgAhUGQEZ0FU2IeqOCIiACIiACIiACIhAdROQAV3d86PeiYAIiIAIiIAIiIAIVBkBGdBVNiHqjgiIgAiIgAisNgLZbNZ+/dd/3b7ru77L3va2txk2RCs5hK9+9av2vd/7vfbWt77Vfvd3f3eqzOHDh+37v//77e1vf7t94AMfsHQ6PXVtOU4+9KEP2Vve8hb3+trXvrYcTaqNVU5ABvQqn0B1XwREQAREQARWmsA//dM/uS584QtfsD/+4z+2X/qlXzJshDajW6dPn7bf+q3fsr/6q7+yz33uc3bkyBH7+te/7srQmP65n/s5+8xnPmPbtm2zv/u7v5tx71K++fKXv2zPPvusffGLX7R/+Id/cIb90NDQUjapumuAQFVtpFIDPDUEERABERABEZhB4JFHHrGPfOQjlkql7Ny5c3bLLbfY7/3e71lDQ4N985vfdAYnt4Rev369/fZv/7atXbvWvvSlL9nHP/5xGx8ft9HRUfud3/kdu+uuu+xHfuRHrL293U6ePOnq+PSnP21PPfWUYZdee/3rX28//dM/bWNjY/Ybv/Ebhs3JXP6P/diP2Tve8Q771Kc+Zd/4xjecd/ell15y/fjDP/xDu3jxor3vfe+z7u5uGxkZsX/913+d6j89xn/yJ39ikUhkKm/dunX213/911PveUKvLdtm2rFjh23YsMGeeOIJO3jwoMvjDxqq9FDzfqYPf/jDjgHPaWx7rzP739HRwWz7xCc+YZcvX7af+Zmfce/9jz/7sz9zDM6ePWt9fX3Oe/2TP/mT/rI7Hjp0yHEI950XyCGc2Hd6zVmO7O+++27juOkNVxKBcgRkQJcjo3wREAEREAERWCQCNOZo7NK7Sk/rP/7jP9o73/lO+6M/+iPn9Wxra3NeWRrKNLbvv/9++8u//Evr6uqyf/u3f7OPfexjzoBmd3bt2mU0IJ977jkXKsF6JyYmXAgFDe4//dM/dQYovbw0Ln/gB37A9u7d60ZCY/vzn/+8NTY2OqPzwQcfdPXRoP6bv/kbu3LlyowR0yjna65EI5wfAHyiIcq8cDp16pQzmH/8x3/cGcWve93r7Od//uddkV/5lV8xGvq///u/7/r2yU9+0uX/4A/+YLiKGefHjh0zluOHD7K899577dZbb50qw3OymStV0ve56tD1+iMgA7r+5lwjFgEREAERWGYCt99+uzOe2Sw9mzT8tm/f7jzS733ve61QKLhXLBZznlAayPSMvvDCC0YPNvN9OnDggDvdunWrZTIZ++Ef/mF79atfbb/wC79gyWTSHnrooan44s7OTvuO7/gOV0dzc7OxHzwy7d692/r7+905DfXNmzdfY0B7D7QrNPmDhnKxB7o4XINFiz2/NHRpsDPcg334qZ/6KWfgMvaY8dMMn6DRS8/7L//yL1/TRrgPPGccNT8IML3hDW+wRx99dIYB7T3QrsDkD/ap2ANN9sWpuO/F1/VeBGRA6xkQAREQAREQgSUmEDaAaWzyPY8McfiLv/gL1zoX4g0ODrowiu/7vu9zYRd33nmn3XTTTc7o9F30RiOP9LDSwH7ggQfsXe96l/NsFxuEbId1MzFsxKewkcjwklKpUg80QzYuXbpkW7ZscdUw7KKnp2dGlWvWrLGXv/zlRqOeiUYvFxsy5IPte+/xfffd57zwM24u8aaYKcNYwqlSDzQ/ELC/PvGcfVISgdkIzHzaZiupayIgAiIgAiIgAtdF4Mknn3QhDTRmuVDula98pb3sZS9z8csvvviiq/OjH/2o/eZv/qbxPY1DemjvueceF7fM+4rT448/bj/xEz/hytBjy9AO3st7/uVf/sUVv3r1qos9DsciF9fD98VGd6kys+W95jWvcaEmLHPixAljSMi+fftm3MKQDcZ8c4Ge90YzHpyedMaGM66b6Stf+cqUMT2jgqI3LMfQlYGBARezzBCO60mvfe1r3ZywTwxhoQf/euu6nvZ1z+okIA/06pw39VoEREAERGAVEaCX81d/9Vft/Pnzzjijl5UeUy4mZOgFjTd6aBkTTQ/tnj177M1vfrM1NTUZvdBcLMcU9hrfcccdLgyEC/PowaUxylAOGssf/OAH3cI4Gt6UhaM3ljHD5VK43nJlZsv/oR/6IbcA8ru/+7tdHxnLnEgknFf6/e9/vwub4AcGLvR7z3ve4zzi9EZT0o5t/8Ef/IHjwDYYTkIuTFxESM/2z/7sz7r34R8MA2G7XHzINvgB4nrSm970JqfCwdAa8vrFX/xFt6DyeurSPfVDYHpZbY2MGZ8c2+Lx+AA/+Ya/qqqR4S3ZMPjHm4tL9u/fPyPWbskarIGKxWz+kyhmYjZ/AvO/o9qeM4ZYMKaZMb7VnKqNG1lxEeTf//3fO6M2zI48mbzyR/jacp6TGWyOBdtS3nbRv8HLOXtBW/gAd13zpxCO5Z8rtSgCIiACIiACIlABAYaD0MusJALVRkAhHNU2I+qPCIiACIhATRGgfnO1e5+rFXi52O2V9jxXKy/1a/kIyAO9fKzVkgiIgAiIgAiIgAiIQA0QkAFdA5OoIYiACIiACIiACIiACCwfARnQy8daLYmACIiACIiACIiACNQAARnQNTCJGoIIiIAIiIAIiIAIiMDyEZABvXys1ZIIiIAIiIAIiIAIiEANEJABXQOTqCGIgAiIgAiIgAiIgAgsHwEZ0MvHWi2JgAiIgAiIgAiIgAjUAAEZ0DUwiRqCCIiACIiACIiACIjA8hGQAb18rNWSCIiACIiACIiACIhADRCQAV0Dk6ghiIAIiIAIiIAIiIAILB8BGdDLx1otiYAIiIAIiIAIiIAI1AABGdA1MIkaggiIgAiIgAiIgAiIwPIRkAG9fKzVkgiIgAiIgAiIgAiIQA0QkAFdA5OoIYiACIiACIiACIiACCwfARnQy8daLYmACIiACIiACIiACNQAARnQNTCJGoIIiIAIiIAIiIAIiMDyEZABvXys1ZIIiIAIiIAIiIAIiEANEJABXQOTqCGUJ1DIF2winTMelURABERABERABERgMQjEF6MS1SEC1Uhg4PSYnX1kyLJjeYunorbprlZr35Kqxq6qTyIgAiIgAiIgAquIgDzQq2iy1NXKCdDjTOM5EjFLNEbdke/lia6coUqKgAiIgAiIgAiUJiADujQX5a5yApmRvPM8h4dBTzTzlURABERABERABERgIQRkQC+Enu6tWgKJpqgL2wh3kGEczFcSAREQAREQAREQgYUQkDWxEHq6t2oJRKIRF/NcwNrBzGjeeGQMNPOVREAEREAEREAERGAhBLSIcCH0dG9VE+CCwbZNSRe2Qc+zjOeqni51TgREQAREQARWDQEZ0KtmqtTR6yFAo7mhJXY9t+oeERABERABERABEShJQCEcJbEoUwREQAREQAREQAREQARKE5ABXZqLckVABERABERABERABESgJAEZ0CWxKFMEREAEREAEREAEREAEShOQAV2ai3JFQAREQAREQAREQAREoCQBGdAlsShTBERABERABERABERABEoTkAFdmotyRUAEREAEREAEREAERKAkARnQJbEoUwREQAREQAREQAREQARKE5ABXZqLckVABERABERABERABESgJAEZ0CWxKFMEREAEREAEREAEREAEShOQAV2ai3JFQAREQAREQAREQAREoCQBGdAlsShTBERABERABERABERABEoTkAFdmotyRUAEREAEREAEREAERKAkARnQJbEoUwREQAREQAREQAREQARKE5ABXZqLckVABERABERABERABESgJAEZ0CWxKFMEREAEREAEREAEREAEShOQAV2ai3JFQAREQAREQAREQAREoCQBGdAlsShTBERABERABERABERABEoTiJfOXpncnTt3vi0ajf4mWm8qFAr/+9ixYz+/Z8+eW3O53EeR147XoZGRkfeeOXNmdGV6qFZFQAREQAREQAREQATqnUDVeKBvuummbTCe/zIWi73t6NGj+yKRyIHdu3e/Fcbz/8Qk/RLy9uJ4pKmp6b/X+6Rp/CIgAiIgAiIgAiIgAitHoGoMaHic3wkMnzhy5Mh5HHOJROK+bDZ7COdtMJ4fJCIY03+Lw308VxIBERABERABERABERCBlSBQNSEcMKB3AsA4vM5fwnEDjOfPwSP9BZyf9WBOnDhxDtc3+fc6ioAIiIAIiIAIiIAIiMByE6gaAxohG+zLa2E0vwrGcxqhHJ/F+UgJIPkSeddkwVtNj/U1+cooTcCz8sfSpZQbJuBZ+WP4ms5LE/Cs/LF0KeWGCXhW/hi+pvPSBDwrfyxdSrnFBDwvfyy+rvfXElhsVotd37U9Vs5iEagaAxoe6Aswor/y3HPP9XJwiIn+NPIOIm+DHywWGW5A3hn/frbj4cOHZ7usa2UIPPPMM2WuKLscATErR6Z8vpiVZ1PuipiVI1M+X8zKs5ntirjNRmdpr4n90vJdzNqrxoCGofx5DOwftm/f3n7y5Mk0DOU3wwP9WRrRCNt4FeKgH8D79+E9wzrmTHv37rWGhoY5y6lAQICfevmLu2/fPoP3X1gqICBmFUAqKiJmRUAqeCtmFUAqKiJmRUAqfCtuFYIKFSOzxUz6N3gxaS5tXVVjQMNAfmTXrl3/D4y3B2Ews19ffv755z8Gr/PDyPso8tqQ9wKM6PdUgoRGoAzBSkjNLCNuM3lU8k7MKqE0s4yYzeRRyTsxq4TSzDJiNpNHpe/ErVJSi19O7Bef6VLVWDUGNAcI3eeP48DXVDp+/PizeHPvVIZOREAEREAEREAEREAERGAFCVSNjN0KMlDTIiACIiACIiACIiACIlAxARnQFaNSQREQAREQAREQAREQAREwkwGtp0AEREAEREAEREAEREAE5kFABvQ8YKmoCIiACIiACIiACIiACMiA1jMgAiIgAiIgAiIgAiIgAvMgIAN6HrBUVAREQAREQAREQAREQARkQOsZEAEREAEREAEREAEREIF5EJABPQ9YKioCxQQKebOJdM4K+ULxJb1fBQQ4b5q/VTBR6qIIiIAIVBmBqtpIpcrYqDsiMCuBwdNjduVBs6PP9VqiKW6b7mq19i2pWe/RxeohMID5O/vIkGXH8hZPRTV/1TM16okIiIAIVD0BeaCrforUwWokQM/lucfSrmvxxqhFIuaMMXmiq3G2ru0T54nGM+ctofm7FpByREAEREAEZiUgA3pWPLooAqUJZEbylh1F/EYo0ZPJfKXqJ+DmD/MVTpq/MA2di4AIiIAIzEZABvRsdHRNBMoQSDRFjZ7ncGIYAPOVqp+Amz/MVzhp/sI0dC4CIiACIjAbgZn/gsxWUtdEQASmCESiEdt4sMW9pye6gDWEjIFmvlL1E+A8cb44bxnNX/VPmHooAiIgAlVGQIsIq2xC1J3VQ6ANCwbXvNJs9+5uS7UmZDyvnqlzPeWCz7ZNSRd2Q4+0PvyssglUd0VABERgBQnIA72C8NX06icQwW9QQ0tMxtcqnUoazYs5fysli7dS7a7SaVe3RUAERGDBBOSBXjBCVSACIiACZisli7dS7WrORUAERKCeCcgDXc+zr7GLgAgsCoGVksVbqXYXBZoqEQEREIFVTEAG9CqePHVdBESgOgislCzeSrVbHdTVCxEQARFYOQIyoFeOvVoWARGoEQIrJYu3Uu3WyLRpGCIgAiJw3QRkQF83Ot0oAiIgAgGBlZLFW6l2Ne8iIAIiUO8EtIiw3p8AjV8ERGBRCKyULN5Ktbso0FSJCIiACKxSAvJAr9KJU7dFQASqj0ClsniLLTtXabvVR0w9EgEREIHVSUAe6NU5b+q1CIjAKiUg2blVOnHqtgiIgAiECMgDHYKhUxEQARFYSgKSnVtKuqpbBERABJaPgAzo5WOtlkRABOqcgGTn6vwB0PBFQARqhoAM6JqZSg1EBESg2glIdq7aZ0j9EwEREIHKCMiAroyTSomACIjAgglIdm7BCFWBCIiACFQFAS0irIppUCdEoL4JMDaY4Q300NLIrIZ0PX0qd084v3VDg225t80SjVFraIlZdqxgvB4ed7h8ORa+TDwVcXWUY+fLlbteXP98yxffr/ciIALXTyCfz1ssFrv+CnTnshGQAb1sqNWQCIhAKQLVqEpxPX0qd084f+jCmA2dmbBIJGKFQsFaNzdYa0/K4qmobbqr1ajpHC7P/A13NF2DzZdJnx+39IWMtWxIWEtPcqoOf4Mvlx3Lz2jDXy8+zrd88f16LwIisDACg4OD1t3dvbBKdPeyEFAIx7JgViMiIAKlCNDbefaRIRiU5jyyPPI981cqXU+fyt2Tz+anxhdLml369oiN9mbdWHnke+b7cYfL00PN/HOPpcFjmoZvy6zgjGdeSZ/P8O0Mdr5cpWznW366RzoTAREQgfojIAO6/uZcIxaBqiFQjaoU19OncveMwEim95dpIp233ETe8rmCZccL7sj3zGdiuXB5l8n8Udwz7t+ZC3Vh2dxEwXKZ4F4eWRfz2Remcn3y16drDM7mW774fr0XAREQgXoioBCOepptjVUEqoxANapSXE+fyt3T1B13oRPE3tAStVhD4LOIJyMWjcG9jBfzmRiuES7vMpkPT3QGXmqfptsqWCwR3Mujq5uefMSRM02X83cGbfjr07nB2XzLF9+v9yIgAiJQTwSCv7T1NGKNVQREoGoIVKMqxfX0qdw90XgQ24xwZ8vBi7zutiZrhFGdgVeZR75nPq8zBjpcnmWYv/FgCxYYTk+ZbwuBH4h7TrgLjIHGW1cHrzP5cqzD18U2/HVXKPRjvuVDt+pUBERABOqOgDzQdTflGrAIVBcBLpxr25SsKhWO6+lTuXuK8xlrzFANeptptDJ0gt5fb9gWl88zALp35pyFy8ymwhEuF25jZm3T7+ZbfvpOnYmACIhAfREI+TXqa+AarQiIwPIRoNE4kc4ZF8nlRs0d+Z75TDQeKenmjUjfM5ZPX5xw5cPnvO7r5DF87u8tPs63jCs/nENscc6GoHYx1p+Z6i/rZv7lI0N2/skBGMEZNz7m+3Gwv+H7yrXPevpeGEX8cnaK0fhg1saHsm7cI1fGbegkY5oz5vJxjXUXG95sO8yoXHssxxS+Hj73c8Ey4TkKl+E1JREQARGoZwLyQNfz7GvsIrAMBLw0GiXXaFAOwIAe+tJL1rohCfm1a6XXfJfOPDJgRz97FYZiziZGcy7OoaEpDm9tzDbd0+JCH9yiOVxj0EK8MVZWqs33geXDknG+LR7DZYYuoq+nJ2y0f8KGz09YFLHLyda49dzebLe+a71d+PaQPfrn52zkShb9MosiRnnTnW229VUdLoyC4zz0z5egjgHjH4sG481RS+H+DBf5DeYs1RXERmew8G/wxXGMJefCN7pubrQcdKFHewNjfXwog/FjsSCGf+JPDlvbxgZrXtcQlN2Rshjipv3YfZ+pusGwjdYtDZZAv0vJ3IXHmgU/foxJhPiRB9VQPK821DUIHv69l9xjOSUREAERqEcC8kDX46xrzCKwTATotaQhRiuThhwNtZFTzuaclGALrrNcONGTSuOZiYvoaMwOncngnNah2eFPXoGRSGM4YgMwQPvxiicD2bdiGTzfh9nk3MJl4g0Ru/TUsA1fHrfRSxl4muH9hVIGF/1Rdu7Fb161Q5+4aKNXs8ij9xyeX8QxX3hyEB7gnJ15aNCe/0yvk6vjwj6qaAyegjHel4ExDk/1MJU3cpa+NG6Xnhx2UnWFPDZDGc/bhSeGYKiO4x5sLDOWs7GrUOuAQh3HXMgUnBE7gnpoYA+ew4eRF8fc2GMIgWafmR8DEx4vPpl2BjwZhmXuyJaMyIPMyI4MyZJ5Zx4etLMPT0sLsu1gLgpVIzXIMSmJQC0SGBgYsL6+PvfipipK1UtABnT1zo16JgKrnoCXRvOSawU6bN0rkGBjvvMiT0qv+QEzRpieZyZez+eCV87Jv8GLC6M0kIWbrGdSxs2XZ7s++T7493OVoYHLftEozsFopTeXBjbPKRU38ALDOVA/8sOvHMY1cjkLwzrjwj3oeS5gCHk6z9F/J0cH45X3cBw5GMmsN58N2nD5KOul7px0XagN9iPPfmBsrDeDftKjTQm7sX6Gmky2x0WJrAeebBrqTGGZu7BUHtty1xw/NmYIE8m58BH3Bj9YhnPB+n0qNWf+mo4iIALXT+DCgxP2/Oeu2OP3nzQa00rVS0AhHNU7N+qZCKx6AtPSaIHkGhfERfBXJxKHjBtctzF4e/FuSnrND5gL7BiqwcSQi2gs+Kwfg/wb7nSeUMq/cUe/KSk3LxGH8mzXp+k++JygznJlGhBuwX7RWI0lcISBS9csz9nX9m1Ju/zsMIxl95ZZ7hXDuJrWcmEgwjU6EjYxFBjxzkuN/tOTTsUNJjcO1Md44yhYRGj8Mh9Dptea48Iwp+pmG64ZlI+5BYcIuUA/o3jPK6mO2CTLIJwkwnrgUWY8NlNY5i4slce2pvmxLrNkG2LRXWvuresP5yKYqyCPcxLmF+TqpwiIwEIJdLR2WqQw/fdrofXp/qUjoFlaOraqWQTqngANRMbL0sij5BpNtKatgTEYSLAF14sXD1LObff3dDl+9Nwynrd1c8KFNrCSve9aAyMT4RHwsrbfmLQOvBgCQS9tsVSb7wOvlZNzC5fJwphdt7/ZmtcmrXFdAoYjjFUY6/QoU3buxld02a0/uN4aEcfsvMuwkxkD3XOgDcZwzDbf02Y3vb3bydTRe0vDuW1rgzV2JqwZcnM00GnYtqxL2roDza7PkSjipBFO0XN7q7VtSbpQlUQqhlhpGNhUqsOYIzC4GYvchHoauxOIh05i7Ck39hzCPNhn5tPzzOP6Ay2IMUfnkcIyd2GpPDIjOzIkSzLafHebbbq71Z2TF9sO5gKKIXhfirFrRD9EQAREoI4IyANdR5OtoYrAShAIS6NFEnl78tF+O3DnDYjpDbyYxcaz7+Pmu9ptIwxKL/nGfH9OI5DhD16Jgtf8ean6wn2g57SSMqyf7aXao4hfzjmvd7ItkJ5jfTvf1GVXT4y4EJM1NzWhP9Pj4XX2ffhyZtJbHnP9Yz8Za8z6vIwd1T1G+7KQ8muAtzvirjP0gsYqy4z0jdvj3zhi93znXnimgj/ZHAMNXu8F9mP3ffZ1M7+UzF0xj1L8iqUFCweneZfixzqUREAERKBeCMgDXS8zrXHOmwCNkbCM17wrqIMbihmFZdTC5zS46HWl4RtrhMcWRy/3FsZUXJ+7rzmQt+M9LesDBQrew2s0Dmmk8j4akzQY2a6fN557KTmeUxqOUnAT6Qk7+9iAO3ppONbhE8+DclnXjm/X5/MaE0MxRvsZr52x/lOjiH8etWP/fsm9xvrHoNJBFY4glCM7nrXLz6Vd2VEYxRefGUIbWMB3egw8gvGwTs+KR0rbXTk64sI7+J7tT0BaLzwWno/2TThjnv1gm5TGc+PCeFkH+8Y8JlfHZGy0Z8b84vlge/467wn3i+WVREAERKCeCcgDXc+zr7GXJRCW+Sone1b25jq5UMwohjCGsw/RQLxWdo4hAPQoz5aK65tLOi0sc1dAXEHrZsi2IeyBihMMD8lAGu7q8TEbh3c3Q6k22LGM4x0bgAGNBXgMJ+GrGWW7dzdb07q4NbYjTARhDWceHbThcxMMfYYEXczWvazZWtY2uPposHKMvfQ+U2BktsT7mxiGEXFtGu3uaTs9uBNlIgjTYBzz1ld3uD4OnZmwvpOjTnnEV3/8Q4dc2AhjqjNYgJighB1cIBNc4OcWE6Jq1B9L4Q50PIEPKuSSTTPEBDJ8LXHb/sY2a9vc5LzmpeTr6Jn2qXg+JF3nyegoAiIgAvi7KggiIAIzCdDb5mW+EohfpRFVLI028476e1fMiO8pLUfrkFJzU7JzMPKYKINGw7NcKq6P9TjpNBibpeaAdXmZO+oXjyLU4tJTIzZ4NlilR6/zRUjEsR+MIR4fhJcWsnPjI3gNII4XhiYNaqpEDZ2DBzuScxJ1V2G00nCk7FweZaKJqI1D4eLCo2nrPw0PM+ThKEc3eG5sbuOZg0X/qV4xAdWOCIdfbDxPljE4h8cQ1nHx0JBddBJ6GXjOqV83nQqQ0xvDGCagkpFDeMfEEGTu4P0e76NCCaqeLM6NaqjyQQm8cSziZ8xygQsh0fhzn+7DuHIl5evCz3jxfOh3YHoedCYCIiACJCADWs+BCBQRYBgAZbrCSbJdYRpBvHGYkY/ZpWJFdlJqjqELXETHRI8t44nLpWLmNDoD6bTpeQjPAevidaZA4g7l4TmmtBuT64+Tv6P0HExHLAA0XMqjXh6dIUubkqd4P3Y16CvvpyHL8jQ8aWDzehbjoKHq5OEwvvDYg1rK/+T9TKyvXOIllpuAcc/Y5wzCNFw/i26goZxj31DWjdsZxrg3QIGT0A08R74zoFkeZXMwnim1V0q+Lsy3eD5Ya/h6qBWdioAILCKBi5cv2IVL5+3ylYvW398vTehFZLvYVSmEY7GJqr5VT4BxnwzbCCfJdoVpwCtcxIjxs/QUO0k2hBhMyc5NSstRBo0L2wKxtpl18V1xfQy1CKTTpuchPAesy8vcsS1uckJJN0q7Mbn+YA6pSEEVjQiuGwzPKGXzoHjhEk6ZGAaR6grK8n560FmeXlco0rnrcYwj2RlsisK4Z/YlA692JYn108BlfWH7Nnyv6wrKNWDBYgyNOmMb72kAhxPDN2LoGxz+jnEBY6G3mbJ19Kq7mBTfCCtl/3FkHzg3MaiEUGqPzIrl68J8i+eDfQhf53slERCBxSeQxVdJ/P1PNqbs/Ncn7GL0iqVHBu2O+7ZbZ2fn4jeoGq+bAP9EK4mACIQIcLEU4z35R0yyXSEwodNiRnxPaTlacNxFb0p2btKTzxhoLgIsl4rrYz1OOg3GX6k5YF2BtBqv55xk3Lr9TVCyQCA2ErcJXw+JOPaDO/kl26IufjiJrcCTMFKdFjWNSrxaN0Jer4A4Z0jUdW1vNKdQAdk5LuzLY4ORJGKTe+5ssY4tjU4ejnJ0bRtTFqc631wJ/eeHgYYOGMUcPo3a4sQ8GMCpzpitv7XV1jsJvQTGQP266RTBBwFuAd4AneYYPqw0tELmrgPjgWHvtKYni3ORJo18SuAlEXbuDGgYz2z85nd0YlwxF+ddLF8Xlv8rng/+LoSvT/dKZyIgAotJYNO6LbZl/Vb36mzrsvaWDmtpalvMJlTXIhGQB3qRQKqa2iJQLPNFg0JpJoFSjHZ9Z/eU1BxLh2XnZt597btS9c0mnVYsc8c5YuhBWLaNsbxeSo5eVfYn8JQXoIgxamtvbkQ4RGDY02vNxDoOvn+jU7GgvFw7dJlpsPu6eWRiOwNnRqFwMW49+xotfTEPlZAo1D2wag9p08EWxDHnYKA3QAov4ZQy+l4YszW7UzaEbc2pb92JTVn6EW9NQ5hGP8NN2E/2O+hrwc59e8hevHDK7n3rrU76jx8oGmFse2k9lk9fnHAhFi3r44jhzrh63RbkKJtsjbg2unbA6E/hWwDUzTHwPiZ/XvyMl5oPd4N+iIAIiIAImAxoPQRVTSD8j33xP/BL3XG2542qpW5rseoP82Kd3jgKn4c5hsv7/FJ5s/WP5RlzHI0XrA/bXNNQY12UUeM1vrzsG3WgJ/oYozwBhYmcKxs26lgHjcHGToZoRLEoMDhnGIY3EmnQUi+ZeYFEXRaL4qCQcWLMdXPtnmbnYe17YcI64Eke65+w9AVsGIJzGrCp9pjz7tIQpYzc+SfHoEyBTU7WxuzIZ3uNnt5dr++wc09iNR68to2d7TDCJ+wcFinecHcjFDqGYbxmbdeb2u3K8zRcKRkXRfkx2/bqJhfqwBhuysf1Hh+1eANCLLCC8OwjadcOjXHuNMgQFErdHf2PXhjVSdva2Gn9L2XhBQ/GwljyHqh/NCPkYvxpcxJ5l58dd/euuyVlZx4etU6UXXNTi+PN+lg3j8Fc+lgORIJAwq7vhVHwbgK3mHuu/bwRWvic3MMa0w6qfoiACIiACMwgIAN6Bg69qSYCktGa32yEeTGsgT7zOBQqysmVhcszvpVf0TNRjYELxnwePZGlEu8//h9X7eqxUet7EZrHF6CAASduHAZa86aE5WHP0rjk1//ctY8pA+WIoX6zw0OHXTxysiUxJa127vFBu/DEEIxjLOjj4rhCsH027+cW4E5lAueMUW7f1miDp8exsA+ayDPFKlzcr3MNoKwVX3O9mPvHk3/eO1Xowf9xdur8oakzsyf/mqojM9MjH575vuw7OruL4psftItli/PCS39/ouz1RAtnu4BFj/jQh/AOytdxm26GoIxBAcQtMkSbjYj1vuunN1vPba12AnPXe3TUhcDkMsG25WyAsdJdOxrd/BMhVU7mehZ4n5IIiIAI1BMBGdD1NNuraKz0iIWl5Nh1vmeMq/eUrqLhLHlXw7wYWnDlSCDn1nNb8/Q5YoIZD0uOrdjiuZjvmYcHYXTjP3yzzzAHpnLM2R7LD7wIjyiKDp2hZ5QxxdzuOWdXDsGTuqvRLXCjF5w6xfS60hDOwAMdR1ywk5KD0Udptdt/ImGXnh52IQxUmcjS+QsjMNJM7ykXyqFueIa5WDAzXEDZEVjVNBlLJEZYIBSiqlOR8bzQvmbSYIW/5pEIvP25ycrTgbydM9QxN5yfMSiJPP2/Lji1kn7MHeOz0xdyTuKPMdicI6Z004Rjy/c9oedGv38LnSndLwIiUCsEgn8la2U0GkfNEKDRVSwVJhmt8tMb5uUMTngec3hxwxAe3YsSbkjkyPjaYr7j0BfmTn3hVI4522N51wZ3tYNBTYuLnk56Pymzxhjf/KTkmmufnmX2wZVBORrAaI7San0nx3ANnlLWQQMYR76cvjHP+XbymjtO1uHKBZfr/qfj4pmBIadkSgrPM0Q+daQH8YGHc+Kk7eB9pmwf1TzoieacMSSHc1/83HDelURABERABODQEQQRqEYCjMPk18bhxPd+4VM4X+czZeDoVaREGV8NkGXz58xnIkfKwBXzTULdIdk680upcsw5Dyzv2uDiO3ieGTNCOTV6LemVjlPWjnJwOHd9QHyu64Mrg3LIp9eU0mqd21Mu5IAOUOa7+BOcO3UJHJn8NXecrMOVCy7X/U/HxTMDQ07J1F94zxD5VPFo25x0c+Kk7bBLImX7qNwRwznnjLH/nHs3b6HnRr9/df+YCYAIiMAkgZn/WgqLCFQJAYZpMCaXIQT0hPEfc8lolZ+cmbwK1n4jQl1QPAuPL+XK6IDkwjCGd5AjF5sV8918dyCVVAlztsfy3AmPMdCtMMhcDDRCCBgz27EziIGmURZFTHQ4BjqDEIP8UKDJDNPNSavFkwm3XTZjoCNYIMhQBMZAB7rSOKZ8DDTqby6KgYY3ekaiAc6/bBz0dcZAz6hvKd7gA0BxDPRCmqkkBpoeasZAv+w9PS4GmjsZMgY6iUWVcXwgovHMROYtCPHh71zxc6PwqYXMku4VgbkJcCMVw1qGcKIO9Pr+wFxrb29HqBz/yCmtNAEZ0Cs9A2q/LAHJaJVFU/JCMS8W4lfu3mvoz70RVFze5zPOtbhsqQZ5/+3v2+C+7uf1sAoHlR6ovEGlC3q7abwzUYXj8W8+Y/vv3HuNCsfON1MrujClvMF+exUOekRnU+GgwkZYhYPtDp0LVDhYBz+Esczl56ZVOC4+O2bdO+JzqnBse015FY5LRwIVjg23pezUfwUqHFdPZlyoyrq9SSh2jNr6vY3YvCRhp78VqHBQCYN9Yoons/b0JydVOO4trcIxcG7UnvjKCbvne3ZYORUOStoxUd4ufTHrVEbInBwoY9eLDzk0iL0KB8seCM0dWfvwDJ6HVTgqeRZYn5IIiMDCCfiNVMI1+U1VToyd1IYqYTArfC4DeoUnoNaa5+KyxfwHl0bdapOSq2ROS3EqlVeuLpZlnCqT50Pu9DD7FGbH8j5R5SKsz+zvD+ezHuon0/iiQda2iRuLBEZWsaScr5dGc8fWRheKQQm3K0eHoUeccqoa/afG3MLF+JSXkyEgBs3icdyD0AHcy35QVu7Ss0M4h4f8YJsL+RjpzbhrNMQvHR6BkRiB6kfGunfS0IfKB8bGsVK+LYjZztj5b49Y6/qEq+/kN/ps3c1NOC/Y6Uf6rAse+WgMxu1DQ5ZsTlnvSWg5n4/Yztdi15FoDgvtCk4yrvfoCAxOSublrR8ScGO946g/Aa97xibGGSOctdGBrK27KWVNa5ps44EE8sbt+Nd6be2uJDSmsYkL9gIfuQqO2Lxl+CraOZtGWE3ezj815sJrbri33W7+7rWokzKACFGC954sWnpSbizMo5pGHKwo99e6IYoNV+Jor8E23hlHX7ktNxcBZgK+KNO5jf3Igi2YQ4M60ZSAxznhfi9Zn0/++fCGc8AQEnvud86Xmn6+pnOW52w+vw/L0yO1IgJLT4AbqUTcrkvXtiXP87VMVjJHBvRK0q+xtkvJotFLqTSTQClOLFEcOlGOHe/3EmSM02haF7dGbNSRHc9b+nwGxlcCX8EnXYgG6wi3l74whgVkEy5OmQYnd/PjhiRnHhmwo5+96gzSiRGs7ENA7TjCM9LY8IMhE8nmmHXtgcZxMmqn/2sA1yhPF0iltW1OOW1lGmfUgL50JB0oaiB8wsmnwWaLYZc8hhCkEH+bx2aBz/3es5bHojXG2zauScAb2mOnHui3F788OAMWY6TjCAPhltWUscsxJKM4ZGPGHfN7c/gT0+Wf+surU2+O/K+BqfNv/v60vNxTfzctb/fsx6HHVya9YGl75MPTZcPFnvrr6XYw6+FLQegJczCvbnvu0HhP/vHzriyZ8Lpj69f0gW8DPMxux8TNDXb8S/1YQAqjHHzX3NJoGw60XSNH55+L9PlxN88t2PmwpWf6uXGNrdAP37dw+Fa534cV6qKaFQERqHMCMqDr/AFYrOHTW0QDkAuZ5pJAW6w2V2M9pTjNVz7u7MNDFkiQBXq/l+BtbcPmIkxcwEejlzGsnI+wXB0X8F1EWab2G4LyNJq5WQePTNRY7j2agecUHlZsyc36siM4Qs7hwqNpi8NJO3aVFiw92pSUQ6gEvMhWaHBl+xvgXX1i2Kk/TBmAVITAc0FFiFHeC2PPnM4zDWsa6jl76p/O28BxWoszk5O6S0HWbgj5rGPakT6zYK28C4mgcOylxusM52IOQBdpitj5RwYx75jHWLDAk1guYgOYVFvcNsKjz9/P8HPBBvi8MLkPX+uT7vpKytWV+h1hn1eyTw6QfoiACIhAiMD093mhTJ2KwHwJ8GtgeovCKfg6fWZe+Ho9npfiNG/5OEjNUV6MycnAQf4tA2+j5++lx/g+LFfHkA9KxVGmjPJlTAyBYOwwj0yUMsvnUAYhur4MJc54nmU7A8HOgk4yjWEh+J/tsS0adsOXufugq2qG8eck61icL9hrYak6no9dgbXo75u83R+mNkrBvXWVyo23TD7nlR56buFNI5SJvJk/hhhpJyGIvPBz4SUPWTZ4boK59GEdzF/uVOp3hH1eyT4tNwO1JwIiUP0EqsoDvXv37n8GsgN4OTcZvF8fzOVyxxH387fIg+/LDo2MjLz3zJkz3GZBqYoIcOERFymFE98zX2maQClOlIOjGkU4lWPH+yk1R3kxJicDhxjZBEIsfJqWHovMkKtjjDHjaZmotMDEMA6GXfDI5FQzYigTwdf/uaAMJc5YnuEAzgPdz3xYZnBn0lBje+wvvZvcdvoKm6AxHNyOE5yG85wHGpm08VCG11JrsF01YotLGdFRlM9zX5jJZnFWH6nceMvkc36Y+JNxzO4cB+Zzk5TSMobB/LFs8Nxw7gNZRFfBCvwo9TtS7vdhBbqnJkVABETAEeA/a1WTEFN5x8TExD1Hjx69na/nn3/+MzCe/xEd/CW834vjkaampv9eNR1WR6YI8B9syqLR48WV/zxKdm4Kz9RJKU6Ug9t0d2Xs3P0oS2k6502GZ3jdbU1usR4XjDExBppWUFiujvNBb+N6lG3EYjzvzWMMNBen8cjEsI3WzQlrx2LAlp4GN49xhAZQT5rxtT372izVBYOfBhol65DfivCRVAfisDVemOwAAEAASURBVLsT1rGlyTbc3gxjjV5QVMi/MPiYHsUrgm414t7kGmShTubRAE92xGz/D22wG1+PlXJFiR8QIpCzi2OXcaz7w4+iArX2FuN1EnxgFSkzXqe1zSkO//XGe7LccFeb3fK9a5yxTI8y89bvx/MB5Q8qa/jfS8ar8/lAK5PPC54bxEDTeF7p39tSvyMr3adae8w0HhEQgYUT4J/rqki33HJLVyaTWdvQ0PA/4Ym+AZ36V6xg/3sc22A8P8hOwhv9t7FY7D9x+mt8r1RdBLjIp1IJtNl6zn/0aeDRE+UMtdkKz/PaUtZdaVfKcWK8clgdo7g+9p1hGKn2uO3/0R4nEzcKFQYqZHjJsrBkHI3YqyeoWhG3XW/psL4XxmFod7myvK99Mm66DwoT6yC1lmpf65pkflgWjUoZTB1bqagRsbv/rw320jf7XUjH1le0o8+0lIPrnLfRvi7UhVjbx0cQX90Ez6bZsf/Tb2t3p5xx/q1PHbV73r7TBk5lbAALGm+4B9uNP5+x2354nb3iFzfaia/2456IbXtNB2K9R+38M6O2521dMApjdvrhNIz0gh37j2Hb+cYmXJvARizQpL6z2Y59tc+Gz2dt5xsa7ci/I/4bKhybbkvawx+/AsWPiN302iZ7/BODWLQYtX1vbbejX0LZN0btiX8bgIa12R3/rcEO/Ttk6bD272XvjtvzuM547Zf/6Do7/H96rfeZnN3yrrgd+WzWxXTf+e42O/5Axrq2NNiO13fYqW+OW9e2CXv0/71qTVDLuP3719sLkLZbd1MT+hyzRz520bG49Xs67LkvDlu0KW/7Uab3OIOdDawa7eKzE1DzaLQhLAYdvpSBekaTXYaayeHHX7KXv2OHXT2es86tSbfYj8omDG3o3JbEQtFAhaOxC7Ho+HBz8P2bnHQdP1SlsMDUf2DitxD+d4q/q6k3Bv8E8HfNS9f5665TK/Sj3O/ICnVHzYrAshEopQPtG6ce9K584OzweTquHAH4G6oj7dq1aw9CNn4LHuj3Z7PZcXiaP4+efRmvt8CAfvVkL2Mwrofxvqy0w0MPPdQWj8cH9u3bZzDGq2Nwq6AX+HBiTz31lO3fv9/wIWXFeryUq+8Xu+7FZDZX33j9+H9cdZuWMPSBG1+MDyDuGXJqY9iWO9GK3QVhPDWvjzuD6Sqk2bgpCSXY8jl+LZ9znmbu79y0rgGLC+HBhsRa+qVxG0M945BjC8JBIAfXHHc71bG+prVROw9DmN8qcHFo84a4nYX8WyaNTkymeBMUIHAP1ToK8BbTM54ZLjjPZhYSa0PnMi5Wu1R4hq9j6ohHr2VdwnlQ05cnLBeseXSe0cZ1MPKgNJIpL34xVc1qOonizxRDZ2i4cl6zlObDAOh5J0vOC6bNEknsIAhjnYorrVDaaIXUHUMb6J0tp1BR7rkql7+auM3W18X83ZytnVq7Jm7zn1Eyg82xYFvK2y5XH+M6k9L9GB4Zslf/6Musu7u7dAHlXhcB2J7XNX9V44E+duzYEYz8Pj96GMp/ivOf8e9DxzKPVqgETvlQ86VUGQHPyh8ru2txS9HDeubhQD6MX9cX8FeE75t74lNes+ttcSnq9qz8can6xr6ffqjfaREHYQ9m5x+DhjHiWmlpUa6Mr0bEH194atha4ZG++MwwjC8yhFIGDTKUK+D3gUba0OkJa96Iso8Ou1CK8aEg5CY3xjJYiAYN4SS83Mn2nD33qX6EaEBLGOoc1DQ+9bXB4I87wwcmfxOzMHITLXkbPM1vDfB3CH+L+PeoH0Y/FyOynFPkqOQ3F7+y6SsZeM2jM4xnjnP0YiUVXO8srNx9ZMQ5xk9nKU9Q9YSfeRAik6dzmiIZwJqlpjQ0ufOZgo2AUdvbghCbcr8j5Z75pnWxJfs9WzmKM1v2v5P+OPOq3pUj4Hn5Y7lyyp8msNisNqzZVFYHeiDdj7/l+Bst22Z6AlbwrGoM6JtvvvkOPBQbYEjT88yHJDr5oWCD57Nz584NyD/j3892PHz48GyXda0MgWeeeabMlaXPzmFp6JUTCO0MfXFA42L44TMWa1xY+0tZ90KZzdU3Xr/0PFbWXg5iiclkDEZrNko5C9hciLCAbWVX8bX/BGSUx/KjNp4GL+TRk+G8GSiXQQw0d/qjMX35xSGboGID6s7RSEMey7tzaC6n+0ZtIoIX6h4eGnPxynlnYJeeh3GEbrCdCbQBP3RQnobf5GdY14fSt16bi/tGYdRPJfatxpOTpoORPAEVlKl544eUyXlh7DeVUMaGscsh5x3XTmEb7ngz8sv8jpR7rgYfOGN9S/R7Vm3TtNDfzWobz3L1R9yWi/S17Zw9ey7QeL/2kg0hhGP8mXPW1nbtepESxZW1xASqxoBG2EYDFgx+GLHQ/4kxTyAe+gM4/g1evwZv9KsQtvEArr8PBvQXkDdn2rt3r0I45qQ0XYCfaPlHk6EvKxXCQY/Z8xcQgFqUbrq7e1E80Itd92Ixm2vcvP7c+St2cRT6ykg0RrMXhuEhDjzQ4876Muva0Ghp6Jg5D3Q/PNBYEEhvRQZhHDSaE9CBpgea/629EfHDqIO6z+MIE3BSdSgTw18EfnBt6WQ8e4ONvzRkza3YhRB5eegxj18aCwxyfuFF424yJRF6MMYwD7ThPdAFaEk7xyr6S49qxUY04o4bEZIyivpcKmrLt1lLR3romRII5ZjAtwCBBxrGMRnTkAYDKqGkECqTwqJLzuHW3Z2Gv4m8zUr9jpR7rna/qsuO9oc3c3FVlKwjuLL6fi7W7+bqG/nCeixu8+dHZouZNm3aOKsHeve+buvs7FzMJlXXdRKoGgP6+PHj34Kh/BcwnLENgMXwj/i/QIXjfnidD8Gg+yiu8SPXC/gH4z2VjJVG4EoZgpX0r1rLrCg3GBGb7253GzlwcZSP74wnFuExXcK6F8xsrr7h+pZ7OhCnnJ+Kgd5wsHUqBpq6yoyBjiDWuWd/s4uBpqEcxEBDKYMSdS4GGkdYZIyBjhZiTlWDMdAIknYx0HGsLKDUGWOgk63B78/N7+yaEQO99XVtJWOgufVsGxbKhWOgO7CodEYMdCUPPbrYgp0J2Y+JpskYaBqRMCDrJQaa24m7IRfFQHMXyCbEuPsY6EIGcz4ZA13ydwQsS/0+JZKJkvkl66hkzqq4zIJ/N6t4bEvZNXFbSrqz180PxbNt5a25mZ3fcl5dBMtk8boLL/OHURtfUwmG9bN4c+9Uhk5qmsBSrr5fyroXOilz9Y3Xb3/fBqfCwbaopkAPI1U7GhELTQUFn88jVRcYrjF4dsKpcFBlgcoOrZAqY2w0E+vgIkOWaV4bszTia6nYwXyqcFDRg3JnOSwEZBl6pKmEkUWM9KXDiBFBk2ugMDEGw56pZT1ictEnlm2BoTc+BGMddfD+C0+n3fVkR8Qe+uIRu+ete2wCm7IMXZiwru2M2R6zZmxJ3r2r2Y2FixZ570jvOO4dsRte3ooPAgk33mgsay99a9g23ZGyvhez+MCAxXXoG7cjT1/K2tZ7m+zMo6NuHBtua4SqR5+NDeZs5+tb7YWvp2F0QpHjjV1ou2AdN8Tt+Jcv25nHR23/fW125okxS1/O2b53dthp5DHW+Ja3d9nZJ9JQyBizPd/VbCceGEVMuNnN39lt558ec4v7etAOFTTW7UnY2cdGXLz4ja9sB9O8UQkjEsnbSaiLsJ/duxqhUIJvExB3QwnD0b4C5P2wCBOLNP0cBWomWTdf6d4JO/zsc3bwVXuweDPQ9uYHJJaZS6mm3HNVLt9NpH6IgAiIgAjMSaCqDOg5e6sCdUGAxgGNuKVIi123i/ultBw9wOj3bInGJY0eysuFDVR/T7m++fviMPx8Yh6N5ua1iHdAyiN0Y/RqFnU3TBnINHa7oP/LRCPWJ1efC4/I2eXnRp2GNI3T1g0RGMYjkLSDVjSMcsrX0bAehkHpjWfWwXq7d7a46ujdjsaD3QwTjQW7eCiQzWjsbMZYEUKCemiEN3XD640jN3JpXM+QjogzjmnAu3HD493Sk3QGPY1zSvUlWyPghAWNYMs+Xz4yaP0vQfYOxvTmu9phlGbs6skRqFEkUB6LD2E8t8Jwb2iBekh3zt3Hvqbak9a8JuL6PTaas5bmhGuHxmrzGswJ4o5b4JVn2QJk+jph0LOOCGLA6fXlB4Yh1N29A/Wsa7b2TfjkAJzsexofANbuaXT38hsT3rfhQNzG+rNuvKN9YxjDhNsuff3LWt2HDrLueVmbM5g5p7zODyPk07yWCwD4wSjjvoEhG75i7tuBmDVgPgLDGd8U4ENRJUa0m6jJH/5Z8ob39dQRrq/4vLj+4ut6LwIiIAK1QkAGdK3MpMax7AQGoTJx5UGzo8/1wpiJVyQn1nt0xK4cGXEbkNCo5AYmNAbLJS83lj4/7rbcptHGxHjYrh0w3GC0XXl+2K48O2pZbJzBBXzN8AS3bUxZ9+5G2/HmLrvw7SE7/MkrNoYtwDMw9qOIs83CkJ8YRF0IoaWyBzczyQ5D8g6GKj8UNMA4YxzuBLzI3CmxGQbm3netgS5x6ww5vYnhLLSJx1zdBUSDhFMcQVcp7JCYxcLCHIx9binNtrnB4TNDWOQ7bdMHtzGcNxheuJrS5/MpW6KGxz5y5Zrc5z85rY/32IemY/Gf+VjfVNlHQ/c9PJU7jxOwJtdGbDyD72ndhyB+7uJuj83wTjfhg8PFZ0ewoQ3gOKMaHybb4pZH8ZGvnYKedCPi1mFE4zo/TvHchzrRq1yc/PPDkCjWiSphuAf3UBJvEIos4XCpUnUU11nufbit2fpU7n7li4AImM2lA72+H38MilJ7e/vUeoiiS3q7hASunYklbExVi0CtEKCn7dxjlLqgEQNjE9bM2UeG4KlNOo9heJwsy2uMP6bxzJSBsVroKtjRz161jbe3Ou9j+B6eT90Hs2fo/ISNwisZTkONE4g5ztsFhAO4OGfYXPSmDmJzkvYbktiEZNxO/1e/Hf38VfQPiwCpzwzDOQ8N5wLDOGiBMcGqGr2Yczv9RRF7nMHiwzEYXFFICUZh3Y0P5eAZLdjh+6/YOAzmAdTLbZ/zObQN2Tyn7FFkPLPaLBRB0jQE8X9DC8qjbzlIsF1jOLMwU6XG83zLusqr5AcUT2jE0rPO9X8IP8fcwcuMeOdBcB2A1Aml67jok0fyiiAmOoY1QxceG3Z5G/a34jkKgPfsbyn77Pnnh88mPen+2es5AOkO9ILPHu9n6AhTuefXXZzjR7itxahvjuZ0WQRqlkAWi1r4+18qJRtTdv7rE3YxOu0A4OYqd9y3XQsLSwFb4jwZ0EsMWNXXJgEaolmvEjE5RHrymF8cfuLK4hr1e7mdNhfIUTijAAMpm8m5uF7GDxcnfx89lqyb99BDzOS8w9B+5kYb3LI5nmeYAy7gLy8VNbIIn4glEd98ZjzYBAWbcLA9Wm+uHCthVbgH6/9c4h9tGkI+OXEPXkMZxk3noHFHDWm2RwOauyI6jzX6VTbxGutFn1yarr7sLfVwwc0lB+rY4AjOOXwgYT4VNtzckBVelK+LYu747UMmjW8OwJ1zwMT5p7e31LPnnx8atP45Ce4JJoH64P5+5peqg/mVpHBbvvxC6vN16CgC9UZg07otZRcR1huLah+vDOhqnyH1ryoJMHaUnudwoiHD/OLkyuKaNQTGM69Ttow7zCUSMbdYrvgevp+6D1YU6+Y9MXzV71MDwiMK8F7SmA1iZXEF7kaGA8SRz9XcbZuT8DAOOy8l26NtRuPbmVCsCuf0UPI9j6xn8qprD29cGcZt44t/t6nKeH9gvPGDAj3U0RjCM1zBEj8Yyk6j0PUbrbB6JcfWeaCJhM8CuMQwMQVocLvNU8iIrPBiuE4EC0KjUFlJwJNP7pxzJsaUM5V69qafn6Dc9D3BJPBbC39/uTpc5RX8CLfli5fqk7+mowiIgAisdgLBX9/VPgr1XwSWmQANzY0Hg4V09ETTe8stlQMDdGZnmMdrEFO2NXuCRX2JZoZ9RFwMNBePlUpT98GKat2ALZy7E077mfrPjVCooLpDJxYJ9tzRHHiOYYgxHKAN2zxzMVzHjUnbcm+H3XLfWld9FMYWDR3e29AeahP2VON6GMMJhHm4OGXELndFJxfvIT4aC/xo4e29bw0ULjqtHfXSA0pvKWXz4insFIlwj+LEGOiWNVjEh10F6YFmrHWiBQZ3B0rSsC5OoS4VX7rm/XzKXnPzCmaAQQQfRqh2wrhzPgfuQwjy28B1w4EWt503P+TEsD6UO0AmuKAWz1fPwWbr2tYIr3HBzQHnl1ubl3v2/PPD6yzH8py7QLElePZooFPxpFwdlZIKt7UY9VXarsqJgAiIwEoRoE9KSQRE4DoItGHR1ppXmu3e3Q0VjkRJ49lXG5YNK6fC4cuGj+H7qNjAr8qZaAjTEOKRaWwgUOGgWkZYpo6GDevY+aYuJy9HGTveRyOnAaGwXoWjqZuGFeXpAhUOGvVe3q5YhaNYTo8KH1dPjMHIj02pcPS8rBlxvgWn3sH+9Z8ac15SGuZPfOuQ7b9zr/Vh8SH7sfbmRqhpTARqIPDqU/KOKhwdW1NQ3cACRShaUBmEi9S8Ckcug81EoMJx7H9jq3GocKy9OWUn/3PIqXD03NaCOkbdB4DObUlI3g3BGMWHl90JO4S4X+pMb391u114JmM9+xJ2/Gt9Nnwpbze9udlefHDEGmDwb39Fh538xoCNQ/5ux2tb7Ph/pq0Riym34b5TDyH2HR8eNt9Jiby0U+FYf0uLXUJccs++Rifrxz63b0nM4EGVEBrC7VuSrgxDKzin5OwMaiwW5NwwppwKKPTgUmWFMnbPHTtiB1+x1Wnb8xnw8+7POc+lUvj5KXVP4WCgDMNr5eooVW+pvOK2FlpfqTaUJwIiIALVQkAGdLXMhPpR1QQYG1xsrDCP22gXGx+MVaU+M3WMWYYGEg3XPLzCLBuOM+agfd00phjfSqMy0E8O6mZ9w5eDOmiU+PZiDTlnmLJuerP5lTyvF6AvzDq8oU5DjV/7UyKN4QA00KjTzHbbIMlGg5ttsH9rdtOjHLiHg/JU5ci6fiWauJgx44xi9oFj5JHybx1bG9F2HkZr3Bl+zIunpmPCW9Z7FzXibrElOK+v3QOjEwY7jXUncxejQRl3hjS1n9nHRGMCknlc9MZ7ICW3k/VDWxrx5KyjbVMKWs6Ul2u0m96acovzGloS0KcO4oIpGbdub2vQp0TOGnEt0Rj82WOMLuu44a61UDRJYYwTlkiB85pArm7v96TsxQeGrGlNo224FdupQ/KPbd/0nesdX8rsbb5zpiudHya44LMVMe1su2tH0HcnE9gTtEvvMtvmHLP9zm2BNB3njostmbp3Tf9pbu3B3F6A5xrXgzLTbRbH27ub8cM/U/5ZCZcLnxfX5++/3uNi13e9/dB9IiACIrDUBKb/Si91S6pfBFYpgVLyXBzKmYcH7MoJc9uPc8c3euC4mQfVDbhAaxj6vhMDkA6D15G7Ba6/rRkbZsScSoY3eDfd02I5GOGUqbt4aNgpbdD4icHQXQdPKhd59UK5I4Ov7VnHutuaoNrRBmMvYy98ZcDJx9Hodl/3w/DNYcGZi3FGyESGHmp6OaHAwPCP9q3wMg/DeIbBnRnL2SVoNo9cyOAeLESDvFzzhqQ1dSWwU2Gw293Vk6OTuxlioSIc31BdQ9gBjXWEcyOMpLkToSLIa4Uc2gA8zOcfG3JjcdMMG4+bg6RaYPDCKEzCgB/ty7iNSShjd+Ijh6FEwkWIKA3HLBU/kojpzsAAzUKwxKcYNixJIdyBcnn5US60C0IbEI5tOe5sjvZdrDDCIpL4AFHI4v5JRRDHHfVH0Zc8VUdC6VuT5//FI523fAXOfeYgnQkORT+//VGsfkfb3Lxl7Co6w/ZLJdjBLsYdIRhRfjDAPDSvC7z/o9icJYb3KXzY2PaGdhjNzJ/eeZPP0UJSqed1oXUupD+6VwREQARqkYAM6FqcVY1p0QjQmKW8F41GGqNMZx8egt0UWE5RGG4uD2Va1iec8cz33Phi8MUJZ5fRC8gKLj6F0ARsLBLB6jHKzLEK6jPvelunDZ4btyHIz/mUg+Tb5WfTCF+AtjMbn0yXvj1ia29ttMP/0usMVBrVOXibaRgXICedGUJ5GIy8h+oNBbwsH4F6xjiM7qx1bm2CR3wc+r9oD55x9o36zaMwBvNwp7cgZIBttCKO+uLTw4F3Gvd7xZF4IzzIMGTHsFNhW08D6sjAO86+jwehI0QEu5JGsZNqQ9dHemm0x23oXNZxzKN/2f5J45MYUQbqbTYOubZ8oPI3OVqOzWw4g8rwf4xObJSnB3tGYh0YwziM5xj+ouWp9jdZL4+Uips1sSxflSb0Zax3jkphjFMqMINPHQksHh0bzbo48AnIFwYxz5gbWPicx9v+27rpZ6uMFGKlXSv5vC6wzkrbVjkREAERqCcCMqDrabY11nkTYNgGvYPeeGYF49iQhN7NZFtgUDOPZRiqQc8zQyncLnyUJaNxCJcrQyeyTocZChnwStK4pdXGUAsao04XGl5jb8fRi5yBUUwPtFtkiHpoeOUhezd4ahxeVhib2WArbsrS8UWdZxpQbDMCw60Aw5eL9xiewYppaFO7mW067y/box3LyxgQZfbYb7Y5hl0N/QI11sEytOPpyXVtoD5ussL7WVcW97rO+wEQCu5hXa4MOBboxoYah9OgZrlwWRaf/vzAu6cTDFYmMp81oXrn0fbl/HHWm5b2YsCX8xI8I2SA7xecUe9kDDGPY/gw0bQmeJb4HPGZC4dZzKeHpZ7XhdY5n/ZVVgREYGEEwhuppFIpF7Y1W43UgTZbM1sRXVsiAjKglwisqq0NAvTQcjFXODHOF6YjsqYtNJbhAj63oQmuuM0x8NU9bE58hc+f+OZ/UgWDcaI0qGnp0jCnV9qpcqBcUNIVRx527YM3NeyBjkL2rg2hGHHoOgfxzFz8FXhDqbIRgdoCjW/ngYYkGuXjnAEO65NhAwwnSCAsN4FwiSgMN+etnixPFQ72m9JmKYRfxM8gjhgGH+uIoC4metwLjMFAakAM8Dj+dlMlIo5FcxMIM3ED8M5Z1Mu6aHCT41g/+odbqUJh3tM8jdDVPSXh5lqY/MG/UjCiQ4748NXpc7RHaTjXPdbLbobqny64fGcBX85RIEVIbzjnh2ElDPHgPKagxuHTQqXfSj2vC63T901HERCBpSfgN1IZHhmy/W++0To6KFs0W1pj3IlQafkJyIBefuZqcRURoLFLCTqGcdCTR2Nk092QpENiDLT3mrIMF4Rxa27GQDPMoO3Ghpkx0Nj1zcdABwsSY257bMZAt21MIowiOyMGei2UHUrFQCcaErb3B7pdDHQEUmc0jH0MdKAJTSM3HAMdQQx0w1QMNNuilF0ERjxjoGnksV+MgaaBxzjrxnZUjHThCYSv0FsOY54x0DEYfHGEpzAGmv1mbDVjoHmcioGm4co6Ebvc0By3pvVBDDQt4BHE/9JDTgm3GTHQqDPJLapjs8dA0yhmeMxsMdDeU80jPb+lYqA5tqnE/vKFshUl/NWsOAYaC0P5AarBbYc+HQMdwYcVfsjhPEbwoYbfCrhnq4wUYkX9QqGSz+sC66y0bZUTARFYOAG/kcpAut8Zz52d2IZUqSoJyICuymlRp6qJQDl5rmaoKgw/fMZuurvb4ongV2nzXe1ua+65VDj8dXqH6aGlQT2bCkexkgcNpX3vXj+l8OGl6ajswLpokDXCsz2K8BB6uRkSwDJsg0cX+4x20xeDuAnKpTGfyYcPsB4qdniZNd7jVTjYvh8Dz1mWKhxXnh9xhiAl6MYGgtAX1sfrLsFAfvRrh+yuN+x121dThaN7ZxJ1sb/QRoaU2/DlMcjQjdimO5oQLgNda3j2mfpeQEA0EmXgxhE+EsdOi+eeHHYqHO1bGp1SCOOuqUrCvvEDD8/ZZxqnMahwHPlsr1uUuOXOZjvz6LhtfUUTGEWmVDiOfPqKtaH+G1/VhQ8vOafCQbm6y8+NOBWOW96BuU4lHV+qcHC8TB1bG5yM3dqbGpwkH1U4WvCBhP1gCvOlOornyA9dfv7JlywXmso9rwutV/eLgAiIgAhME5ABPc1CZ1VOYDENDdZF9QomGnjFhktxW7zuDctymPw9NFK5SyDvoYHcic0vmPx1Gko0qGhUUurNS9fFGuAVZjsMr8B93PKbRhwNWBqRzHPxzKiLRxq/gfxcIJtHA5T3+zp4dONEjLIzzrGAzRtsbJPj4RbiNPLcPVDLYJ/cPZNyeuxnFzZr8alzGw30jJ1/agheaqh1dDa7e3mddXfvapkyzvPZLIzhrDM4WT/HzVhpepDZ7+ELOdc+Jd4a4fqm8ct+Uk6va3sjyoMRFt9RQ5rjpxFMfWXey36SU/vmFNoNuKQvIjYcRjPl73wiv/5TgSY0jdyW9Y22CRuS8Lh7DWO7s9Z7YsQZwA0tDbbpzg6EVATycpSs2/66hPsQ0bK+AK9zEtfYHucn+MBD+T7K1rGvGw8gtAb9X9+UcmNlH+LJQNaOH2z44YCJfJvXTobWuJyZP8LPiZ9DLqbkuHmsxNAO5nM6NGRmC3onAiIgAiKwUALT/9IstCbdLwJLSGAxpblY14n/uGq9R2GNwOHXtavRdr65y8nQcQiVtMUyYRm79htSULaYcHJ0aYRFUCqupSfpwj/oEQzXmR2FtB3aycHYm5Ku40I95FH6jZrI7BPDMihVR28yY3u7sIvhml1Nlr4wZucgGZc+h0WLlLeDczcOhYoEZOxSMNSacT9l6mhg5+BV5sJBhgk0YwMRhik0IIab7cRh0I5DZo+xxVxEyB0MGZN78VnI6V3OwEiMOC/qre9ea/SsMz30kVN26P4rTv+a7xs6InbDqzqdekcant4WbGrCBY7nHh9yCh1cNEcJt413trmwEaqBXHrB7MgHn3UL/rgwMpLA5iEIDOY4MmDCxDhhLsDj/PDcxUYTUHAZYStBHrPos3VlJ685kPzLNrn4EGfXpFQ3dnMEg/6T40GYNO5lOAzDVMijeWPCtmAzFUrOnfpmvzNcWZAx4hsQEtEFw5n5aXy44e6NlB3sxIYwrWtTbu4pHXj2yUHrfXYU4+LGJzG79d3rbNvru2aEA7Uh/IXPjQ8PKvV+AJvJnH8KXusvvQSPetLNCUOGJE13zbQqQwREQASWjQD+aVISgeomQI9cWEqOBg7fM3++ydUFGbr+F8ed55IxwwM4P/PwoKuvkrZ8GbbtFtXB+GTcM/NpPDPRmKTBxX7Sc+j7T8OKbQ+8OGYDZ8ecdB0l4rg98zgW9Q1fyMJwZbjCiD0LiTsmhmBQ/uzCY2kYwgxbSNvASwi9AAgqOVA2jvHI3F578NSEjVyFrBxk8ahTTLUPXstCHWQIWtMT8EanL0BeD87J86hv5MqEUwUZhRf6wlPD8HajT86gg1EIz+5ob8ae/0yvGwM9z4f/FcYzFzbSuYm/HhP9BTv/6CDuQyNIQzDqz7N/6EeweJLhHQXUPeTy02hvvBd9pZoH+s7+ZQbQPzBwqh/EhpdT+widO2OYBjWnHK8cIifc2FkPo1BC1/BuVuOZlylD13ccfXbWNzJQJ+uhsc5Fk0OnM3b64avo86Bri8UYS+3G8uiQ9b6Ydqxp9LsFm2j/yjMj0NQG33MZu3w8bZeeHHHe+Wgc8eKom5KFp/6rzxnogapL8Nyw7ZLvkc/nKo/nKnOVvcZz5Z6v4PeBz5uSCIiACIjAyhCQAb0y3NXqPAjw63p66MKJ75k/38R7KENHY9MnnnPLZl6rpK3iMjR+KV/HsAhfL49cAMh++nhctsc8XqOndWKQ0m70EFNqLvAku6/poQFNzzA9uTSSnHcVtlIe99E4y6KfLp8GFG0oHjAcLgBkftZJ0bE+3jt55HW04V7I832lMUzNafaBHnFKqtFjTY+0b3tiKOfGwHhlbmTivcAcDxMl+CbAj4kG+gS0qI1t48CFfPxBDux3Hh5xNx4WZr95HYnyc36cbkx475K7f/K8+DB5b3F2xe9L3B/0N+hXbhDzCsOe42W+v8YwlPT5ybnhtckXsFkmzbmFNN2VYI7cWNAh3st8fjjxyT83fCaYrn3P55HPFXeJDO4KnquAJ59DJREQAREQgZUhoBCOleGuVudBgDGfjH8NJ75n/nwT76EMHT3PPvE8CZUEX99cbfn+FGg5ITFWmV/RM6bY18sjPbj0cDL+1dfJPHeNYQsMGaBE3GRHKHXmYp+xK2CUahd4MZbVJRyiqLMFoQUMvWC+u8aYAyR6TukhLSA/jjCD7AQ3P0EZ1u9sW9bNuFvWF8Rzsx/sQ4ztsRyYUlKNUndBnUHbDa0xN4Zka5PF0EZ2Gp0rRwk+qkwwMS65oRXbfF9h/9ASqoCYnhs/++3esSjR4VpwHX3HJY5kyrhm05NlHKBgmMgMJZYplR8qMusp7y9K7I/vV6wN8wo3exYfEJjv+opjHAoaLRuwo+QLwRh9FRxWAnHkMUJKcFElbwqu8l6G2FCxxCf/3LjnBJnXvuczzucK8zT5lzp4rlhpEFPu69JRBESgNghQBzrV0GjDY9ySVfrO1TyrRf8UVnNX1bd6JUBDhDGfzosHjyCPfO8MlHlCcXVBhq7jxuSUN7gd55vvbnP1VdKWL8OmGWrAr/ApX8d8xgAzMQaaxhP7SaPY959hCmy7/caUtW9KuR3/GCNM44nSblT2oLexc1uT3fKu4I8nvaANMFJ7DrbAwEQ88YEW7GQIQwwgqCVMyTju0kfjqg0L5Zq6ktYKqboUpOloMPNaHIYY42dp4LZgB0EaqhtQX9OaBhjaBRef3LO/GYv10CcYeVwMR88o5eluenu3GwMXyu39vjXO6HaGLgxcxkBvQHxz2yZuE4htvTc22Ab2D/2gV5sWLuOGe/a3uvwWtJfsprEIPOg7+5dAeDUZMLzFxSEDHUNjwueUreM4nUEKrjGsa3RjZzm8wtfwDhW6n2V/MAa6E+ofzgAP7FFXj/Mmo9+tWxADfXcX+tzm2uJI6OF3Y7mz1bpvbHGs+SGB3np+eFmzDx8wEK7BDzlrd7bYugNNzouf5w6J6ONezOfWezunnmMOhs8Nx+Q83cXvkc/rjBNPoBhT8HwFvw983pREQARqi8DAyFXreU3C7rhvu/Sdq3xq5/hnpsp7r+7VDYHFlOZiXQfet8GFMRBgsQpHJW2xTLGMXeEgQzkCdQYvFeeNnOI62a4v61U46KkOS8nxXi9V51U4eA894AyvYEwzQyMo1Za+mJ2SgfNf7dMIHsZiQCbWTVk5StuF22A9DDHhdbZX3CeqcPADgE/3/NxWu+MnNk6pcHTtanbX/X1+3OH+UXaOyhrsdxbbcj/2wNN24O5bnAoHPfNUAiGDYgk6jtmHv/CcY6EKR+e2QPaueW3MycGxDvafah3k0Y0FmJTv43lTd9TOPTGMbx2iTmnj9MOQx5tU4WBfqcJxHluXbzwQjIOydFTh4AcJz4NSfpTQY31r9zTDGA5k+Q5+YCP6k3EqHF07UqiL35RMywQesA3Q9p5w19knqnow8cOGn0e24Z8b8in1vgd9G+45YwfuvAHx4cE3LyynJAIiUHsEetZskv7zKplWGdCrZKLUTTjqYDTMJiVHo80bJuTlz0sZG8zzsmJhtuE6aND4OsL1+XPDgr4sFrMxpjoG77HvH+sIXJvhmqf7zzhnGoNcOBbBd/OpjgReQVkaa2zTJxpr1FRmHkM8eC+NZRq29CjTwKRh1rE17s55X3hcbZvotkVv0KcGboaCcdNr6o01vqcB68u4E/xwY4G3msfixD517YD3OmR0s74gcezB/Y2d3JkxyKecHI3kGLYxb8C+APRmd26bltAjA9ZLY7gV4REcF9+3bQp0rYN8fnBgOEgc9wbjoqwey9LIb90ATvDW83r7ZKgEx73lnul+bH8dd2GZTpSu2/oKqJaAL0Mpem5rcxf9HHGMXAS4dk+weY6/0z+HTWuS8OIH3nd/LdE0/Rw2dtGbT1k8z8eXmj461gj/8anUe6qOBOE90+V8eR1FQAREQASWn4AM6OVnrhaXgEApmbgEdraj4cXwCXqA50rhOjKQmqPpGEcdXnaO9fl8GsBUlhhGmNr5zhPWc0er3foD61wTVNygt7JU22ceGbBD/3wJi9CohIHQhtub7dZ3rXf9C7fv72WFrC8Nb/PFQ2moYsBYxH3cfZAhDw0IzZgYQcwHwkga0D/GzPJrfy87x/t9vayjlMRecZmrJ8acoc7xdu9utB0hiT/2n8oQXNzGUBqGe7SuT5Zk5NmNDWRsGEY/gTJsYnyz2blHBu3YF/on6wkk9Fp6UjYEib6hM2CD8YTr7z02Yr1HRtxiQ37wYDhE87oG15eRXsgHQrKP4RcJerTxwYLSe/yA4eeC8zbOflzKuh0QuW15105IBTJsBADYV8+cnn0/xlI8yatc8qw5//5ZCdfN+3yffHuVPJvl2lO+CIiACIjAyhAo7xZZmf6oVRGYNwF6GWmUcKHWtEzcOAwieFuRx2v/P3tvHiVXcp13RlVWZta+oAAUtm70CqCBRq/sbpIiJdKUREqiSEoekiJnoUVJs3jOzB8z/sdzjueMzxmf0YznzFg+HstjS7J1ZFkWKUqiRB8OtVgUF7GbvRC9oLF0N3vDDhRQ+5LrfL94eauiEplVmYWsDRXRXXgv34u4ceOLeO/dd9+NLxKvcH3RS2SoHNR20M11KDY5oZ0T7Z0cjRy/8eacu/rqtGefgF4Nj+EVUcCd+964p8OjTu9drqobr+bZr173RjAeSQzhKwofePdpLQkeUN0tlBXdHvR6eLMx6ibPiYFD8copGX8Tb+u3OJXbszqn47A7EEdM8tRnkkeydiGjFsUe58M8LAoCdR0sIMRU0/bz0oM8Xn8ZzyTqIh/thq+6GqMF7N6U4a82YrAiz+N60rkzX0vk4KHmpYA8bfK+gwe/MS5NfntKVHmi3IPKjz4lnfz3V93pP77q44/z8mxDAQgTCPVQ7rRWFDz39EQyJlRmTH3m9RDmMK5Qx6Q4nMeln9cVQ5r+Et7Q9pEwnkkhnv5AnX8MRz8OwzFUkU1fgmW98VFHbDwcEYgIRAQiApsQgWhAb8JOiSo1hwCf3/H4kYwmzui+OOa9gUFYBMeq01IZonSDhk5/GG0L+6ITYz8vqja8ixhMTELD8wkFGV5QjLMwhXUTajA/la9MrktyoS/GHOesDVae0BDkIRs9jF7OcyhropvnUNaS1hznz8rjHUYeydqFDHQn+faoXtMtzMMxJgh6aj3JJC96kAeZyCbBwUw+5EJ952WCVwUjfqMz1G200XM2q1xJFHBwGucmEv2MVo88M1fyPq+n1KNMRT7c0sgD7wrxife6z14veLkF0fD5yX9qnulFrPTs9ST+Gx1plx8bFbnUAeWe10+yOUea0cIp0PaFKcQzPF69bzhy3PD2uFRk05dgGSbrg/BY3I8IRAQiAhGBzY9ADOHY/H0UNVwBAbyYeCxJeHbxdCb7ibeScxaL60/U+GepjMRbSjbYL0wedGLse+YIffJnlT++/ycUcpVY4qqY4bBu4mmzvWk3pwlultC3S8c5Z22wc9DtyTT0Hkv0MHo5z2AhT6rXow8KuqS9Vh7PKfJIi+3Cc13BRVsfkyvdDZekbNnrwCIp8t0ncpUHPRI5TARMvLIwYJAvJT2gvjPZhhF1ozPUbdTlGTN0DA9xWjHQmcoB2uAXXJGc7t3EQVvfqUxFPsweJh+sSZnuZDVF7+0VDZ8d93pJZyYCdu1IGFFgOKF9yPa6VNoHIwmhIvSh1dut1Rqh7QtTiGd4vHp/EWvkLY4hkw1VIriGCb2sD8LjcT8iEBGICEQENjcClcfR5lYyahcRWA4BQihupolTXC4sC7JxOUee5dISGSoHtR10cwV5LxPaOdHeaeE6jg/d3el2He1x8B9Dl4ZndLco4A68b8DT4VEnk9mq62YS2KFP7vAGMx5PvKC7H+7WJLcBP0HM2rBQVnR70Oth4RHP23dAHNCahFeUF7f/oH7DbjGvczpOLDKr+ZE89VmFOcPahYxaFHucD/P07c146rrsgF4Q5Jml7fulB3m8/oqvJlEXFHe0uyhHbzVGC9iJMWNEbcTzjDyP6zHnDn88kYPXlhcI8pTF1AEe/MYza/JLRVHliXIPg9wYRI79wi535FO7vAGc1gQ8KADhoqYeyh351E534L39vg8oM6g+83oIcwxZ6ugTs8eA9PO6il7Q95fwhraPZN72EE9/os4/hiNyqHNhDFVk05dgWW981BEbD0cEIgIRgYjAJkQgeqA3YadElZpHoB5NHN49DJtGUiiDWFuMOxKMC8T/TihmNqSTK7cV3DN/8Yo7/vBBN3Cg2xuY5K+mKeMYyRvaR3vdj/9vPV5W15A80v0JdR3nwvpDvU0eOhnlHSwclDGdaCMhFglrRPJejM4cwyh+4Od2+vYgA+POvJ7IY5+6yUf+zgHFH8tLTiw2+oX4MTlx32N9C3VxDpyQgT6mQ3ictlMPCTaJF1+67PY9ImPyiYGa+evJCfsAhg6S6QI9HyEZhHVAm2fnwc7qRkfrU3CgjeAV6so+WJhc8+QTg14LD69E8E91H3LK8EE2yfoTfeyYPxH/iQhEBLY9ApPTzHvZte1x2AoARAN6K/RS1LEhBDBGjF6MAuF+QwKUCRmzN/JLmBKYPHj+6SkZQhibCcsFHuHXvj7qLj3n3Nx3Lrnhw93uvgpbRbUe1G3sDCETBhMe5ayUYbbIAIEBVq13KK9zkNUCF+XhqSUMoJppJGTLMJ2NmSPTe3P5fnmwJzQRMdSvd4+8zzUYTPBEG/UdbUNfa189fYxar+jXAqdUQstWLYfjtLfWcYziobtlgQfJdAnrv6SJjab3xHlNgqxiRaH4+T+vz5TCeZObsKZc9bgQKjPyuFhTxLZCP9VLYX+RZ7n+rCcjHo8IRAS2JwL3/sSOuIDKFun6GMKxRToqqrk+COD9NEYPPI5Ov1/90jV9dsdrm3g9YWk4J+aMcS3cwRLLxLvCLgHLAuWrk8mUD3qBCYOJcWNigKAc3lBCcRthC0G2yavH5hCyZZjOIZNEdXmseM6zNHk9po7qNoW/q+U105ZQzmr369UPDmFfer0qzCb1sAt1oDx9DauHxU7DOgJTB3XGFBGICEQEWo3AwIBC+tqjadZqXNdCXuyltUA1ytyyCPC5HS+qJc8kQTxzQJ4AkwI8zsTbWiK+F5YFCxGw42xNpjEzcIw6FhkgEjn+WCVshDz1kskLz4dlCaOw+F3LEzJJVJcnHpvzxqBBGWOPCOWarOpttTzON1KuWs5qf9erHxzQI0zGbBIeq6cr5WHk8MuWVwrQhzB1UGdMEYGIQEQgIrB9EYghHNu372PLayBAXGrCSJGc9EwS8kQbiwRHYaXoVbwwtHWWYIlgchrlq9OizEUmDOrwjAzyPOPBJjXKyLAob7GmsCxxu+Z5thz8tnje6vJ4VzkfMmjQHs8eIdVqtcnksq2Wx7FQH36vZapXP+1FjzAZs0l4rJ6ulIeRA0o8S/QVTB0rYWL54zYiEBGICEQEbk8Elj5dbs82xlZFBBpGgPjVkA3D6Ter3kF3Zl5dWBoOiDljQEtsl2Rb4ZWEcQGWBcpXJ5MZMmFAzTYoBgjKManPM0A0wBaCbJNXj80hZMswnUMmieryMKtxvk1ccPWYOqrbFP6ultdMW0I5q92vVz84hH3p9aowm9TDLtSB8vQ1rB546fFEwzqyv04/h2XjfkQgIhARiAjc3ghED/Tt3b+xdatAoJpJAQPt/o8NLzBGYFiRHvnFEVc8cskdP36H6xrI1DSerfpQZjUTBuEAeDSpp9EUyqtVtpotw3Q2+bXKl9+jRU6kS6hfozrVkmd1rce2Xv31jjfKhGE4snR7Iywc69HWWEdEICIQEYgIbDwC0YDe+D6IGmwAAkwCW85wxXAM2RMwQENmCFQmD7Rs1UZmPdmhTJgwLFk99cpZvuptKK/6HL9r6Rzmqy4f/g71C8sstx+WXy7fWp2rV3+t47WO1dMLHGFdiSkiEBGICEQEIgKGQDSgDYm43TYIhJRnxL8a5VmzAEy8O+eufUcMFqdH5UHu8HKQUU2bhhd0pdQqnVaqJ56PCEQEIgIRgc2LQKkUJyhv3t5ZqlmMgV6KR/x1myOAl/cmajPxBHO8mUT+C89N+SIdTDJU9MX5JijSwrpapVMoM+5HBCICEYGIQEQgIrB2CEQDeu2wjZI3IQKEbVRTm9WjMVtOfS+nsnS25WuGIs3KsG2VTqHMuB8RiAhEBCICWw+ByAG9dfoshnBsnb6KmrYAgXqUZ83Sknk5LLQSpGYo0oJiG04DF+oS9yMCEYGIQEQgIhARWBmBpRbAyvljjojAlkaAyWM3UZs1SB8XNhw5+96TzAQssNCKIkD2N0GRVi2rFTqFMuN+RCAiEBGICEQEIgJrh0D0QK8dtlHyJkWgHrVZs+r2a3Lgzg+IQ/nQsOvsSy+wcTRKkRbW1yqdQplxPyIQEYgIRAQiAhGBtUEgeqDXBtcodZMjYDRmbOslJvflpopaLKXkt7UmGmrtEU93F8ppRHZYp9XDMSjtQllhvrgfEYgIRAQiAhGBiMDmQCB6oDdHP0QtNhkCRis3dXHeTV3Ka+nutFbpy66a8q5e86weJjLeCqVePfnxeEQgIhARiAhEBCICrUcgeqBbj2mUuMURMFo558reeKY5Uxfz/PQUeLU80atpstUDBR6r3HkqvFVQ6q2m7lgmIhARiAhEBCICEYHVIxAN6NVjF0vepggYrVwxV3bFfEJqz7aYSyjwON+KZPWEslZDqReWj/sRgYhARCAiEBGICKw9AjGEY+0xjjVsMQQWqe7KLpVO3jHZpjLax1vc3Zr3zsV6FgEijKNV8helxr2IQEQgIhAR2AoI9Pf3bwU1o45CoDWWQIQyInAbIcAkPmjlsJZ796R9y4iBxnjmeKsm+Vk9UODljQqvhfJvoy6JTYkIRAQiAtsCgbiQytbp5uiB3jp9FTVdRwRCWrmOzjatXlj2nuFWGc/WlLAePM+tlm/1xG1EICIQEYgIRAQiAq1DIHqgW4dllHSbIYAxux60cutVz23WPb45RgHYqomdtyNGsU0RgYhARCAi0HoEoge69ZhGibcRApFmbvN2Zuybzds3UbOIQEQgInC7IxA90Ld7D8f2rRqBSDO3aujWvGDsmzWHOFYQEYgIRAQiAssgEA3oZcCJp7Y3ApFmbvP2f+ybzds3UbOIQEQgIrAdEIgG9Hbo5djGVSEQaeZWBdu6FIp9sy4wx0oiAhGBiEBEoA4C0YCuA0w8HBFgch+0dZFmbvONhdg3m69PokYRgYhARGA7IRAnEW6n3o5tbRqBSDPXNGTrViD2zbpBHSuKCEQEIgIRgSoEoge6CpD4s/UIbHWqsUgz1/ox0SqJ1jfIy00VXaSzaxWyUU5EICIQEYgILIdA9EAvh048d8sIRKqxW4YwClgBgTjGVgAono4IRAQiAhGBliMQPdAthzQKNAQi1ZghEbdrhUAcY2uFbJQbEYgIRAQiAsshEA3o5dCJ524JgUg1dkvwxcINIBDHWAMgxSwRgYhARCAi0HIEogHdckijQEMgUo0ZEnG7VgjEMbZWyEa5EYGIQEQgIrAcApsuBvrw4cP/WAoPnzlz5osPPPDAg8Vi8V/p94D+XpmZmfnCuXPnZpdrUDy3eRAwqrHz3590hbmS6+hs97RwHI8pItAKBOIYawWKUUZEICIQEYgINIvApjKgDx069JFyufyFtra2r9EQGc+/o81/d/bs2e/o3D/s7u7+B/r9P3Eupq2BQKQa2xr9tJW1jGNsK/de1D0iEBEIESiVSi6VSoWH4v4mRWDThHAcO3ZshzD6X2U8/yOwuu+++w5o04/xzG8Z07+hzWfZj2lrIWBUY5vZ81wqlNzU5ZxjW51CGr7CXMFdOTklj3rB55256NzlFyfc/MS8u/7GjJu9nvPnbrw56/IzeTd5cd7NjeU9vZrVUcwVI+VaNci3+HsrjLFbbGIsHhGICGwDBCYmJrZBK2+PJm4aD3Q+n/8X7e3tf19vXwdlRDv97RfE5w3mN95444K80ByLKSLQUgTOfX/cnf2T6zJ4iy7dnXKHPrHDHXiSqCHnQoq0iycm3NWXp12pmFRfdkU3P+ncqcIP/YFUl5PnQOEpei1Npdtcca7sOrrbXdeOjOvdl3blgnOF+ZLLT5Xc8JEut/Nwjw9pwYMaU0QgIhARiAhEBCICWweBTWFAyzD+ZUH2zunTp7+p/S8An0I52jGkq9LN7sGqDPZTHmu81vYzbldAwLCy7QrZb5vTeIXPfPWab09HV5vGXfJ75OFuh1fz3DPj/lw5VXQXn53yx1LKN3u94Mo5nbIrqKyvJIrOL7ZrR6k9VfZ5ixMl17mj5Mv2Hcj4Y4zqa6dm3NB9WS+/Z0+HP+4L3ub/2Piy7W3e3JY0z7CybUuE3uZCDCvb3ubNbVnzDC/btkzwbSyo1Vghr9Uyb2P4N7Rp9vjfUCVU+Wf0t0fG8w9kNO+Q8dwjbzTG8l5TTCEde3X8nP1eafvqq6+ulCWer4HAyy+/XOPo7Xsod0PGrMIwUoETuDjn3HPfHvPHrr0hYzjj3Jxs7Fxe+eRd5rWsbO9mjNLEZk62leMlHWvrKCt0w7npsXlfdmpsToa1jqedK0nW22dnXbv2p5855/Beb6e03cZZK/o2YtY8ihGz5jGjRMRtdbi1otTJkyddf39/K0RFGWuMwKYwoBXn/JPWTjzQMqJ/TCwcv6z9F/X3QZ3/tgzqL8qA/g+Wb6Xt0aNHXSYjyyemhhDgjZeb5vHjx7fVBAY80DN/9c5NGL3ng3d6r/CZS6P+XGFv0Y1997I/hge6OCsPNMYyswgwoPnDtcxvNhjKsI3od89gxpWn865XW46Rraz8Bw8NOY1rd/ip4SSvL3l7/7Ndx9mt9GrErHn0ImbNY0aJiFvzuIFZK5Pmg7nh4eFWioyy1giBTWFA12ub4qE/r9mo/0pGNK9jb8rY+Hy9vNXHmcUaZ7JWo7Ly7+2GG+09/MmdN8VAp7NyDSsdeGrAQcPXpnvk3id6kxjoXNlle1OymZMYaJ9RVnG9GOg2WdGUDWOgdz7QpfHZ4WOgO9Kb+jL0zWv1P9ttnLUCv4hZ8yhGzJrHjBIRt9Xh1opSEftWoLg+Mjbdk1ve5t9W0/lzr7/++klt3s9+TNsDARgvWF2OBTK8B3eVza4lh2MwYszeKLju4XZ34QdTLjdRdPuf6Hb7nux0s+NFd8cTne7t7065TPe8e/NbM65vT1rne93pP7vmsnIKfOh/2el+8JVRN3ej6I59vMt99/dm3d4DHe74Jwfdqa/PuJ2Ka777gwPurW/Pubs+2OkuvphzXUMpPymRuOnJSzm3+2i3Jh/isnaud2TxK4mxfXA8IwO9mfbXai9ytkJaL93Xq56tgHnUMSIQEYgIRARuDYFNZ0DfWnNi6a2MQMh4YYuurIahopYccHn+Ny/4yXzTNxSAPF8bqWcrh5//57XPn/3yIsXQd36QrOlz4fWCu/DNZCLiO38241745wqsVloq410f+yyns9w7znX2pl2mL+V692bcg5/b7fr2Zt0b37juRhUXTYzHjvu73H0f3eEaaX+t9jZSziu5wf+sl+7rVc8GwxmrjwhEBLY4AuPj4z60b62aMTAwsKby10rvzSg3GtCbsVe2oU54B32ohIzHdFcSSMzv/v3Zpj2xN8l5RishFgvu0nOioIODro7xvNawl2W3F9W+siYpzubzorfrcLOjBXfmj0fdnkd63Nhb8y6VSdo+rv1zz0ys2P5W4bbWba8lf70qC8/QAABAAElEQVR0X696arUxHosIRAQiAs0gcOk7OXfFJQ6ZZso1kndqZsI9/tl73NDQUCPZY54VEIgG9AoAxdPrgwBhGyz3bcYztfKb44QzNJpqyZmfLLiZUS2Ski8usmc0KrDV+SqsHbBzFEWDB1PH3HjeL+JSzGsFqnRiQLM/r/CSldpfq72rwa3VzWxE3nrpvl71NNLmmCciEBGICCyHwGDfkGsrJ8+B5fLFcxuPQDSgN74PogZCgJhnwjbCxG+ON5Nqycn2dbhUtwgx0pr4167VTDYy0Rx5odu0TRH+LK7zzoG0j4WevryoG4Z0tj+1YvtrtXc1uG0EJOul+3rVsxEYxjojAhGBiEBEYGMQaM462RgdY63bAAEmzO1/ss/Tu+VnS37L72Ym0gFTTTlP9bmD7x9ye97To9gvebOzGwMo/M8i/XAdPU4TC9OumC+7ruEOd/hTw+7A+wbc4F1ZeaVLOl5yA9o/8FT/iu2v2d5V4LYRiKyX7utVz0ZgGOuMCEQEIgIRgY1BIHqgNwb3WGsNBJj4Rswzn9zxGmL4rCbVk/Ph//nuuiwcF0/MyHgtu5EHM+7Nv551dzyVXmDhOCCD9Oxfjrrpi0V3+GO97tQ3xtz11+fdsU9k3TNfmXZ3Hul2D3xsSEwdU27Hwaw7+L5+z76x79Gsu3o657J97W73sV6xfxR9WMrAHVltxTaiF4WeXWnX3pG8xz76xb0uN5VwijbDwlGvvavBbr3LrJfu61XPeuMX64sIRAQiAhGBjUEgGtAbg/ttUSuTs27V2K0GAqO5XsxzWB/lqLujs81v+Y3RjWHKMejqJi/mxG6REi3dmBs/n3P3/Gi3O/vnE65NXuADj6Td937zmivOOPfgTJt77jdEKyeCjZ0/79z1b4hB4xUJ/BZSlQ5dcu5ssnvmVS3tDbmi0rdKCrnQwo2vvTzjrhVm3A2W+ZGYG+NX3IWvt7vc51Puh/+x4MYulN2P/Ff97vpbade3L6047z5PlQeX9J0/MuBy016cqPU6tF9cEgdOmxsxqpfDLZG+dv+G/bKal5710n296lk7pDen5Fvt/83ZqqhVRCAiEBFYHoFoQC+PTzxbB4H1pgUL68vPFv1qfoX5kjzBs5ocmHAqt6fbXM/ujLv88qSbeHfeyaZdkl76zWRVQQ6e/O3FU8/9n0l5jlz7g8pxM575WTGe/ZmK8ez3T/h//T83/mhx/8z/y37JPf2rzBhM0l/9g0X6O+dkkC+kc65NsdBprW6I9Z3pzbhOxWyPPN7jDn5gwF15aXpV1HYL4td4J+yXW6EeXGM1o/g1QiD2/xoBG8VGBCICmx6BaEBv+i7afAricbqJKm4VlHONtiysD+/ytVPzipEueyMaGjj2SVoC3k1dnXfjb4lxY9EmbrSaDctXFhtHnjags5Yr7BrscFdOTLu5UfHeqZXNUtutV0PCfjH2lNVQD66XvrGe1iIQ+7+1eEZpEQEQuHxVDpbS6sIXV0IQGruRsdvD7NsMfNa3B5IrjZp4vqUIrDctWFgfccpMsisVyrI1y65U1DYJG5atqXCHaSYg6tii87elbV8rYaYv7WFyYalYEvVe3mV6OuSdTmj8GqW2Wysdq+WG/WLntgqFnukbt6tHIPb/6rGLJSMC9RAoaMGAik+oXpZVH892aXXcv865y+1rwzO9asWaLLhZ+KyjAd1kx8XsraOcaxTLkIYslZFHVhRv7eJP5h2dZbnL7Yse6Ex/u5u91qYJiDKiG61gE+SD1g6F21O0j7+UYqJF2+FbmSjYKLXdejUn7Berc6tQ6Jm+cbt6BGL/rx67WDIiUA+B/bvviDzQ9cDZZMeT6f+bTKmozuZGgMlYraCca7SVYX1MEoTibejuTte7L+Np4DoHOsSl3OH3R4716XzG+SWzG61gg/P5GOjuNpcWvV1G8c941HdrZcLDn9zp29kstd16NSfsl1uhHlwvfWM9rUUg9n9r8YzSIgIRga2FQPRAb63+2jTarjctWHV9AMEn5Fth4fjOv6ywcHz6ZhaO0qOqwCYSHtK+TSQ8pn2bSPiI9isTCYd+TuwbFRaOw190noXjWB0WjgPvqc/CAdUd8cTZ/o6E0/o9/Q2xcEiTDUnV/YJRFdP2QSD2//bp69jSiEBEYCkC0YBeikf81QQCGEv1KOeaELMkKxOTjLYN43j6KhPp5JmVd/bC81NasS/thg/1Ksa57MbentPvdveOaOqmlO+eD/W5K6eKrnto1n37/7lKSLQ79vMd7pnfFN2cCDhOvTPq8n+eVLcuLBxfUSD2a0l9L52YcKN/qn1dcQ9+8ZI7+4daTGWvE81eyV16Je9mJ/Lu6MeH3eSlsl+VkBCVsbdz8kCz6ktilBZzRVHz5cWVnfHc0bxA8BmdfuDchKj6OJfKJDHTSc1r/+9ajIO113rta2CMhn209jUu1rCeda9V/69nGxaRu/W9rar3rbc8SogIbC8EogG9vfp7U7cWSqzXv3HdXX9t1s1cz7vpyzlXEGVdXhMDi/OB6qJ9y8hLi3Gi+RYL6YVfv3lixDP/++Ly2GY8LxRY652K8Uw1o1+pVCbGjVf+WbKfu+Dcn/6K/qmkV/71mO16mznVpY2YRXr3ZlxHtt3NXMm5VFbLe+vFYviBbjd8f49f/jw3lXdv/uW4X5gF7/XRz+x0hz++a1FW3Ft3BDaS3m0j624V0Fu1DVtV71b1W5QTEdhOCMQY6O3U25u4rXhtzj0zIQq6ecUvy/MsTysUdXA8LzGeaYOM0NzkUuN5EzdtdarJe16cFZuRmEYm3pkXr/WcvMyaZyiWjvmpkrv43LRr1xzDstg6Xv1ywm9tVHKvfkmhKfJIx7QxCDCWQ5pHvQP53xxf67SRdbeqbVu1DVtV71b1W5QTEdhuCEQDerv1+CZtL97k+Ymip6grzMtozin8QQZHUQZkzbTFaOpqtmGlgzRdfyW1tShPO9RGnr5PuJTyRTcnBpK5MS0PPl9cpPJTESb0Ec4R08YgwFiGzi9MRu8XHluL/Y2su1Xt2apt2Kp6t6rfopyIwHZDIIZwbLce36TtJZY325/yFHVO8b9+8RDF9sKmIfPwZq159Vtqo9ycZ6sfIfRZf+1qa0reZjyZ7fLOY0i3pdpd55AmGipLh8I6WJ7cEp5oYqFj2hgENpLebSPrbhXaW7UNW1XvVvVblNMaBNZyIZXWaLjxUlq5IAwLsqw2RQN6tcjFci1FgIlIB57ql0e14GOge/bKYhSXMzHQqWxVGEedGOiWKrTRwmQZ14qBbhNPdKYSA12SVxre5aOfHr4pBnq9JxJuNFybqX7GMjSPhHHgebYlzjm+1mkj625V27ZqG7aq3q3qtyinNQis5UIqrdFw46W0akEYW5BltS2KBvRqkYvlWo4AlFiPfXFvwywc199ojoUj/eMKb/jzlqtdX+D9OlWZSDj8tzWRcIGFQ6x4FRaOH/2v99Vk4ejZlV5g4SgVEsMrpReHeiwcxz83smEsHPUB2L5nNpLebSPrblWPb9U2bFW9W9VvUc6tIxAXUrl1DNdLQjSg1wvpbVYPE2qICeSzZrXnLTwHLOQrlwru4oszbuf9aXf55Jzr25N2XUPt7vTXRl26r93tPZpxZ/7suhZLaXdHCoPuhT+4oomGBXf8E93ula9N+2iOnp0z7rWvO7fnAzNu+qwEy+B85RWxcFTIOdbVeKZhb/NPkvLyFkNhh05dCrHo7Cu5bJ/imoXTzFjepeRZJhH/DWakvLzvTAacuqw26PTQXV1u8GCnx4uVFsOEx3nobtF2BCnEuboPgmxxd40QAPNW0jzSnzmNiVrXVHUTGq27FWMklIEe9a77ah3D3yYD6koWS7I2thK/sL5m9k0306mZspa3loxaxyz/rW6bkR3mvdV616p8qGO8l60VylFuswhEA7pZxGL+FRFYjsopPEd4BmbgW9++4a6fmlsyEW65Ss7+/vTC6W+dWNz/9gsz/vil5yqnNY9umsVNNioF8/gm/qSihFR89h8nwdsTZ5z72jcvLmj30m/dWNj3wc3Y0RUyjXYZ3p2DHW6fwlx65Z2eEktJr14yevdmfbgAnq8whThbCEF1njB/3N/cCMxdce7MV0c9I02r+rMVYySUwQsfr4EdXamFsJVGxpzJmLo0v+K4Xu9eMt3CUJzl2lQrPzpXh/PUOrac3GbaXUuHerKr8+59vLuZqtYlb7WOhEfVa8+6KBQriQhUEEhcXRGOiECLEMBTUI/CKzwHr/GYKOtGX592ozKeY6pCgDeLgImOn7PXC+7Ss5Nu/HyC19Ql3NoJ3mBrKcSZCYXrSaNmOsRt6xCgPydPJ/Ja1Z+tGCOhDDzHUFByTXNtNzrmTAZv0rwUkuqN6wSB9fvXdKMtjeBeKz/UnOefmfR4LMjQb443KreZFtfSgfsxx6tTrbwXnptS3uqcG/e7lo712rNxWsaatysC0YDerj2/Ru1ejsopPAdNXTFfctNXFJ6gG/bNt/c1UnCrigUg/eXmii43njzhwK+Y00RLTVQDW0shznasOo8dj9vNjwD9WQq+ZqDxrfZnK8ZIKINx6MejH5PJWGxER5Nh9wPaVm9cc249k+kW1rlcm2rlh5pzfnJxMSdk8ZvjYVpObphvpf1aOtSTXTOvKDBL4aJVK1W4xudr6lh1v1tjFaL4iEBdBFYbwtF2+PDhD5VKpT2SnARvaue11177d3Vriie2BQLECfKJOUz85jjJzkFTl0q3u57dHe6qTjGIohHtIar9DwDpL9OZcpmBBEvwS2WSE4YvhVfqg9oVxKObFQH6kxCeMIXXVHi80f1WjJFQBuOQ8UjyFJTaNqLjggxd/Avl64xrL3wd/1nQLahzuTbVyg81Z9viI9JLyvZ16F639G63nNyg+hV3a+lQT3bNvPpilc+uWM26ZaipY/A8WTdFYkURgRoIrMqAvv/++3+jXC7/VHt7+1kZ0f5OoCWH2UYDugbI2+kQEzyWo/BaODdfcoN3ZfUYyYpZIudjoLcTTiu2FbsYe6TiqOJn544Ot+eJviUx0FjVYBpOrFmpD1asO2bYVAjQn31HpJLC/VkkB4Oous+bVbgVY2SpjLIb0PXMOC3o2m5Ux1BGr6grLba/1rhuto23mj/UDS/uSm2qlR9qTtKSGOinNHu4+ljVNewzrOKfWjrUGyu18u57T6/7YbKw6Spqb32RWjrWa0/ra98YiduJB7qzs3PJs2u9EYfGzrmdq652VQa0jOWPTE1N3XfhwoVk1taqq48Fb0cEmODRvz9bczZ+9Tnaf/wXRuqycJz600UWjh/8XoWF4ydrs3Ac/5nuBRaOE/9EguW16/mJDZxIiNew8um9/xPOTfxFotMTv9LuzvxJyXXude7Jz+11b/7NrGfhOPIzO9yNt0tu15Eul+lJuaunZ93wfdklLBztHfIQ6ZN+NVuBJC9J1TjzIIpp6yLQudu5ww8N6/N62wJDxa22phVjpFoGOjE+8Rw2OuZCGSuN61ttc7PlQ90aaVO9/LXuh7WONatfrfz1dGgkb4kA6E1kQKNzM+2p1catdmy78EBPz0y6Rz56lxscHNzALtrpNmIhlSvReN7APt8CVfPwDCmomAxiD1ZTv1QoyTjM+XjOPnmfBg50KqY35959ftS1ldvdPR/sdBdO3tDy1aJw2zekUOm8OJMLbt/RdpebKCgutOzGxqbd9ddlKyuYaHZ2VhOQnLukP59kvHaJ2W2Bp2NERy9XzrV6s18Cz1eEPqnt96XTh2Q/f8+5bul2/Hine/HsnEuJLKNvsM8NHii4wUMp172z2/XrfEYGR6Y347oGC57KrmsoJUO61xsinYMqpASGuanEJd2m5Qkzvcknc3+yxj/VfVAjy5odCvs7NKQ4XpxN2uKC1RPXTJEqwfX0qsp2089Gy5HP+giDK6Rku0logwcMM7IjM7yObD/EuFpsqDvnwjI2Rkxv5Id5OD4zWhClZErXZlI/xyYvzvvrFlpFKBS51rmeyds9nPhlwKHa6Ax1CXX29U9r0STJ8vuVsq3Azzeozj/19CG7tYe2r5RCOWHe8Lj1XfiSwP701bzHjJdjS2G5ECc7X2sblmE/JzyR32j5WjI3yzEbp5tFn7XUY7vwQI9PjXnjeWhoaC3hXFPZTbmljhw58n60UdjG36lsf7ejoyOZOq0Dp0+f/huOb2R6+umn+6XT+PHjx10mgwswpkYQKBaL7sSJE+6RRx6RN3TlB0YjMi1PSENkVFc8NN793riYJfKuKAOZGenlirfWym3XbZsWYexSuMadHxxwOw/1+M/1YPHGN6670bOyPoXVjvu73H0f3bEp6ZzC/rbP3niROH7umXH39hvn3MF7D2jlyYF11b+eXiuNs0bLke919dH112ZdXsZLe7rN7bivS3SDtakGV6qX8yFmu3eMuPY2zTEQTZxRQKZXoIwLdbdrr5pmrl6eycvzbvJdXnCLak/JDT/Q5ToU63zh+Uk3eT6vYVj24/SRX9qruQwZd/ZPrss4FzWl1prvO5ARl3vnQtiD9f+SUIYKHdm574/7sjOjOTcnppm04obTClPBoNxxb2ddqsbl8Gvkfha2OxynyA11srbbtUhbwhTKCTEO+8iOEwoCywjhKnnhOnkup3sfXxVS7tAndrgDTw74Pq+FU1hn9X6ow+SluZpyq8vwOywHBtDY/XD09Jo8B2rVfzscY6zJ5mjKlqrVbrNdut454B1ItfLcTscwoA//7E63GQxoXYOr6r/FV94GekaG8+/yp6z6MO5+QjHQ/8aOaftvGxARs2wzBPCE8DBgeOINgerq+puz7uqr0/5hWcahKgO6vPAats0AqtFcMJmVJ+/qqzPeGwcN1rmnJzxFmE2+BEeosMB3M6Wwvxdou9T/ePMYBySbEMfv9dK/nl4r1d9oOfLRH/RLu56lsCzQh1MXNLDVRatpq9UNZrxULdDEyYiFLo7f3sOoa6uWfCsfXnvVNHPWL9V5UqrvijjWZ2XUmkf96slpd+EHolF8O+fatfBPW6rdzY6V3Mv//oo7/cfJakUY9LT7ihZFSmkyGnLRLawnHBcsFIThjdFNPTkZ6tOis5sbL0hO3s+PAMBa7QOX1aYQm1AfjqMrOlEvxjNp9NRsci1WjdlQjt3fPMZBH4EDfXXjzbkFqr6J8/PCd8ZjBWYk6gQP2gpu1Xr5TDX+CXWgLrCnD0K5tKk6heWsrs1GY1etc/wdEdhMCDQVA3327Nm7UV6e6EPyNp8NG3Lo0KEnwt9xPyIAAnwuxuvCDdqorvg9r4clN3A9N72BEdGqQkC4eINCOJGM5suYCqD6wkgD3zBUpkrKuv8M+9sqp7/5tM+WB7wlfq+X/vX0Wqn+RsuRj/6gX2Bd4CUIpgW8jPQd43ylugwX21rdYMYLZikvIW0lb2RSD4lrqiPL6n03Y2nlw2svKZNMiAv7pTrP3Bh6U19yjeJ5JpyCtjhe2vQ/X0K4hnMVY7dnV9aViqJBK6qM/nJTivPvJ4xlsf+pxxLHJ87nhItCN8S8UeIlWnKRUZwXw4xeRMiDHtTTLH5WT61tiI2dpy6OE/rgdVKbaQsvC7Sb65EX2FCPUI7d35DHi4D1ETiwXyoAGoZxyhvmeU22TOkrBe1N5jYUPR7oUY1TWKcXEvwT6uDrkq5t0jmUy/XXO7L0i2xYzsQVNhmNnekVtxGBzYhAUwb0Aw88sFee5jZ9sviK9n+SfXmhy/Pz8/JXuN/T332bsZFRp41DgLg/Pg2SjOqqTaMuq5jJ2asyNWRZlPUg9il5vlR+bPONMMEw5o+vS3joJvQ53RIGBxRZFrNqxzd6G/a36UL/ExfLthys0sDv9dK/nl4r1d9oOfLRH/QLfdUmpyKGdFq0g57WTf25Ul2Gl22tbjDDA01ISJtCODI9CQUk+RIaw9qUcVbe8tnLV0gzZ/1SnadzEL2TCxPjn4SHNaU+mx3V8eSUj6/NDHS4rmEeAdJRXmkMTqc/i9EP+99nqvzD8f79GR++AGbtiFBRjMmUXgqogjyJHsnkybD8reyH2JgcG4+0k5AKrHnfFu2Bmb8WNbcj7MdQjt3fkBf2ETiAfXuHxkUFuLT6MK0FZ3x7hRmJOsEDPcJkeoXHwv1QB1+XdCXRFyTkWly6P1D5Jyxnxzs2GY2d6RW3EYHNiMDSK3UFDWU4/5ZudOf0QD+m/fPss1X8zxsqagsoryAlnt5OCDD5A9ohHsJ4sKC62nF3l9t1tMfTsmFoOBnUGAgxJQiASZcMzl1Hu72Bsl+0Vwfe2+9p/8wTDY5QZG22CUJhf0O5Rr/T/xhFbEm2KMh60lHV02sl/BotRz76g37B04gxTR/27tPAliW4mrZa3WCGBxrZUD8W5JFly2+uKcO4ui1WPrz2fHl5Pq2M9Ut1nqLq2/1Ij9qQ8YYjOuw61uP2PapllA9mvGe2LM9p12C7WHR2uyOfSqigiPWl3bsf7vbLjteqJxwXTBok9peXRP/CKMOyR/HBnRWjvG8vXtObqRrR51ZSiE2oD8fBBJ2oF0OXRPy3lWFryY5V4xf2UVELk9BXQ3cTz53c6GDg2P1It8cKzEjUCR6MFeRV62V1Vm9DHagL7OmDUC5tqk5hOasLGju9o8UUEYgINIDA4p2ggcyWRTzQ/1aLpvxn9nszbS0QP04ibK5X9CK0ZpMI0cQ+weL1yM/kFUs57Ybv7XDvfG9SkwjLbtf97e7kH067O99bcs/9O2Imnbv3p517+ddVuFsPl19QjOC/1r4e7Hf/onNvflX7U3ow/ZTiC9lX8lRxX9fOEf29zBEl9k/7vfX7R6wa7pL+HtPfC/rTnKMjf8e5M1+WZ2rAuUc/k3Yn/yDveu527qnPH3BvfU/xovLYHfqYaOzeKnhP3+6jvcIM733y6RzcSBaPat4wf3AD/rH+RD8+BZNCnew8evOgtlTIF9wLz7zoHnvqYdeRbuoD2JIxhMzqOsLf1IdeIX5hmfC45TWMKcc+8oxVgrJ2PGyPtcu2lJkXQwwGCewNszfERCGvHtjQdxzHG2iMFpSzPqVODOKUbEYm2ZL47A61GJg98vhxNz9WXpBnuFu5UH+8nZOKJcajiU5XTupiURq6O+tGX593Q3d1agJgZqHvwANd0Y3r891nptyBJ3pUVh7nGwUHSw7nSeSBPWdurODlTV+V0TzEF4Y2d+3MjLbtOt6la1gea7XF5IJb2NYQj7mxvMb+nBu8s8NdfHHO7Tne7ToH04oblq7SGVkk6qBPwJT2mmwMROJ8OdephYYmr8y7V1897Z788EN+UjTHjUkkxJe2zGllT7bgREgJmKErbSRRbupywR+nHhtXc+OK0b6Qc8Oa0Ivha+Oj1rhB7+r+Qg/YTMBx5+FutS25HsIx1LMr7XWxOhlb9MfAHVlfp1ew8g/tN53Ddq00dqnP+qU9W3Y/ePYlf30ymdzaFI558jdz3HSsV87Ob9Utz844ibD53rsdJhEuPtmaaP8999xzZ5hd3oNyOp2eUVz0hjNIRgM67JnG99fagDZNnv61tzXh6IZo6JKHsR3f1lt5nIlzbddDOy1Dq1MrlfXK83b3Rwa9F4+YSIwSPFPVDAAbgZvN3J+6pAmhr8/62Fw+Ew8f6nL3rsAMstpxZnUaFv13ZHxIS63fC4wH8rTawhy9exeZMEJZIVNCuN8Mk0HYByY7xAYP9NyUYsAVC0tsMHGvux/p1YI4GTcrI2xGy9kTc8vkww4ZhddOzbjcpH7rpQrP5SNfGHGvvfFDVz41KPaNxOPcp/b3jcgDLe+lnJUyKGXsaJ8b+vUfzrorL834MJKyHu5zMtwLMPbbJafxlpZB17Wrw/Xv09udEnXvuLdLL7YTmryqCXPk1XtRz54OGdtdbm460R+dsjKWh+/r9MbqpRemZLjCvOHDlz21JOMYFpmDHxpwM1eJK07OhzqPnZt3Y6/NKUa8IONNlJRFTbxU7LHnTde7Il7QdI9CvfoyugZk2IvlgxCJORnCLDBUkm5MtOMFo1te8h33Z8V+Mi8DeM5NnNOYlKiS4rf7d2dddkBGqPIyIZDFiCbenvNzMGh3pi/l9r2nz8c4jwp3RSW6sgzRzGCH6x5KuxzeYTUu0y0DW1vYRdLZlHvnb8bEdDGvY0m4x/HP71I/7buJ1YJrlsTEQBurHMNw/sFvXfSTC+m0Ab3QPPqLe/Sikl1gcqFju/fIG9+vFy7dA849N+GmZbDTlk7pd/w/H3GHP77Ly2fcnfzSZXfxhWk/xrh/PPi53V5edd3V95BwzE5emHdTbWNu/8FFxpfw3mN5w7Ysx7DildM/9crZ+a28bbUBPfG8XqQ0DrdaanZRFBYxefyz92xpFo7mXECVHtXb1ne1u09/uDVwP/UrHrqgiYSXdZP5tLzTz+hYTBGBJQjg2cJ45oYTU4AAD3vZBXjiS3kZC3rIz1zLu5O/f9Ud+cRO720jNw9CPv2G3qBAyrrs4kVCDx7ueN+Y7U/K6pM77AMwhrRaR6sTwwHPI4YMjAV7ZIT637oD+d+P9ngP5bVTGDaVeFOVSWjDMl5vQgLQH1kdikHFWCWNPNyjfX3/Vtr9cJdnMmDfjA3k73ssCUXheK1kei7BRjjhQYb2jXAAHot4n2FYyR0QjRkeT3kT58cxMsuidcSYVsyzMrYrDnjyXN69+tUrbmJc1IWKKiBGdeLdeeGed4Mfzy7oPKJwgKTdJRnPMJ9rEpkmrs3Ia+zpIQmVsqTxVtSExMl3pZNitC1Wdjwz5668POvr9lmlw/TFgr6azMtwK/rFfbp2yLurWHw8lp6CUuEkGJ2EFpUEn49dVrwv7Byn/nDUHXh//806vzrnLr047Trl2cUjP3dDHcgHlsTp7p8ohMrn1OZUtuhDfmgzbecFAhwL9tWjpyg5Rffql0fdbnmtp68wKTFpaJu+XI2/k5OxSZ7kUXdRLCKat7PQxnlNlrx6CraRgj/eOdQmA1wvHeqPPhmvk2cTL/Tuh7SvvuC67D3Q4ZlICDshNprJgye/dM0d+/SuhbHFuCTBzELcs38hqBw7r2MXoAKUPAutANPTf3xVY7rPG9U+Xl1jByYUXhb1fJXhnxjPvKzmplWn7g/3/eQOLwOWnsti37D4c9pz+qvX3F7J45jpU30PCccsL5uknNxgY6U54ZHy1xhjkXLhtRPKq3fc7gNWB3LCcnbeVxr/WUBgKy6ksrpFUW5tEZMFwDZwZ1UGtG70f6ab0HfPnDnzW+guw/mzupl8WLu/oe0/1fb9HI8pIhAicEVGQ1HeqphuRsB7/PTA5GGDgQX7AZ9kmc1PPC0Jrw/GFeEAG5WoHz14GLKFpQADoSw7Wr/c/GRiALZSR6vTHr4YLHg1MdrwjrFNfgtApWrGA34bkwOf8tEbWRZPThkMQmNNmJPRyblGmAwoa8n0DLGhP2HPIF64rDCEsk62tZdlCFZYO1SP4Ui+olg7KIPFJXta+yVNtlXoB2NCBjQ4M1bA3TNlVNg4jOkB/mnaireW8ePHFQom0JiqkqtDOsb4SnclBh4vGt4dUjW85mUM4zmnTl70YHfIyXXCkt1tzACWvsjzSUK93spTZCzLmG2TkzvUGawx7ksFmDeS/L7eBe0Wd4qqw2lRpaLa0gYG+skCSn7cqerivLCc0Z+81EkfIo8xqSSckutJ+Xk3Urtoh5/IKiM6SQq5kbFcEn1cm15Y/LVHe3QS45q2kvBe+/arv2Yu0wHKI0+7z6j6qJ/7m40tX0j/wMzCeCCm2xJGOC8fniWjMtGPfV6ephU2wjjEgOYYfUm7CmonY8iRH4wljC8OhJz08CUDPn3pZhNE0XVeoR4c57wl9AvvIeGYpd52qQlWRWLr09Rfm7EllBdeU+Fxq8fqsOuXPNV6WLm41XyJ3XfourLxuTUQuR0WRVkN0qvqJRnPj5jxTKWit/t93bQe17HntNXabzFFBG5GYLcmxaU69BTzT7ebz2/nI34ypXDBu0xsJJ/5+SzPbH5LGIsW52rH1ntL/ejBg5ot3i3POKEHLw/9rMJPWq2j1WltxTjEC2fGAtvkN9jpT3p4rORdJfGb4xwjNpStP65y/pzOY/DbPp5RZNI2884in7LLJdMzxCalmNmUwiXgTG5TmIScejKopIsMeM/aEeCI9zYlnVllEo8lhhf1d+0S20pvUjMMNuBNezxTBm3z+ifb7MAiewbeTT+uKFp1zZn8hC0Cvdq04IsmuC0Ot4WmZjVRkJcJj4fqRyfwwoPv5WrMIs8nXhAYx8pDXH9KXuBqnSnbLp0JG0mYRZTHyi/UmuykVAfyPI7CSivJiEc80cVfK8Kso1t/CqtI+pD6UYBCyE3GRDshUh67Sl+guv9TSIowa1cMM+W49qiD9mbFREJb+cPrTfthIekekWDyqArffu1QP/c3G1vWDPqYayJM3TvTCnFJe7l23Pezvjz1KCSF/iRxjH6mXZ1D9EGCBRWjK/eHhMVEY0Ty7HpIyiahNhwPk78udA1bCsfsQr3CijHrrwcwV6q+dqz8csftPmB1WBmTZ+fD43E/IrCVEFi8kprQGiNZXNB3WRFR2h3Uvi47f/tlG1NE4CYE0t1pzdYfavlKhzdVtNUO8DzWMzYtQyAr4w0+XB6yxz6r+EY9qG2GPLGTGxm+AazU7+M6ZTz07dPS4zIqMRLwJMLwAGNIq3W0OvFsggVWi2dJkA7+t7bGmmBML57xAAYMJW8Yqgx6Y1SyRRYeVGOzwNNn+6WcYpQbZDLwFVT+MT0xqhawkXHWpVja/rsUOyuj2RtEPW2eYYWYY+rxrB3KR5+PiPkCAx7Dl+N9B9Lu6Cd3u+EfSSrBcw1lHAwZMGWYzotMD5L5kIKHlTBSe4Zl6CZhuIkA/pVsXtD67kgMOQxI+pFwld3H5f+wp4Iw6tkro24o6/XvkKcanIhl3qv69zzc69uT0oRFvNiZQQzPxFMKO8cDPz/sr/WbdBYbxR6xPRDnCSYYhxiJzhylqh+jmwm3HTJsMWoJc/GYyqiF9zojnTFwvTGut5Kjnx72BicrIqZltHu+cQ2VgTszKtvpjVhCN/aKRaRL5fxLn6pExq4HktU+M+qXwpwmDepY/8Gsn3/g47bVB3hkwYj+Gdzf7ZlI+JLgvcUyco99RqFWur/Z2LJrFmYWrgkbu2z369iRn9vp+5avBHiaqefIp3a5O96n1Tl1HSGXP/p5UBMyB/Z3SaeMv08Q5oWu3B+YvMi4g6VnhLEkzzNeY3Q98smd/viSuqvuIeGYNYaQzLDGlfqIscU14nWuunasfdXXVHgc2SSrYzk9fMb4T0RgiyGQjPAmlT58+PB/KiP611TsL7Vt19vwj2n732j7kLa7FAP9d5sU2bLscRLh6qBc7eSu1dRGLDSfO4fuSmurpamV+sRcceqrE+7+j3a7d74/4w2jO5/Iuud/f9T19GfdfR/udM/+zqg+5Tr3vl/a6c6dyCnesegO/2SXe/ErNzTJqege+VSfe+vbMpSeyrnnfkcxfHoIP/oLWff935l3BbFi7PqUYk/FhEHKflSfV79x8767T8fe0t979Pe0/khH9feq33OdH9OEsP8v2R/6eedu/KH29Yn68Bf0JeZL+roqu+Bjf2+XYk+73M7729zJP72uGdrt7sjPDLnLJwtu5FiXn2D1w78a1yQlKKsGPAsAnzSZWY8ByEOI2fcYe3yC5hMo3hp7ICW1b+y/plfILoAxs5KOtzLOrE7DYrnfoANu6AemVsZQC8taXvOIGd7k4fM0nmeLVbXyy21NdogNsvkUT98irxkWjrLCeU6cOOEeevAhz8JBeXA2PWvpH7JwcP76G0l4AYwW44p9Jm4VlgtkkNDPcDKWnL0yyLy1XTlv+ofMENRDGAEsHPQ/LBCM5cGDnd64w0A0DKt1NrYS2oNs2CW6FIN8+eSc6PJ6fHlkwwDiQyukB5giD8MbnW+VhYO2WF+ga8jCYXqr2pvagB4hC4cxaJDX+h/97HqodYz6jDWDyZA2xsgLHiT/YqGtjeXlWDgoZ5ja/QMZtermeJgsT5vCNiILR4jMyvutnkS4FZfy3kyMGiv32M05ZLuuyhaWidF8UqjG78oD/ayM5Z9W6YIG0N9/4403Xtex5/fs2XNOBnTzQmOJ2xaB8MYOxRQPKR4YfHIkmg/vTro763Ye6ZUXrtPtuCuh1OrZ3en2PVRwZZ3v2d3jDj4hz+ARea8eGdQn1wn39t9MyrvY647+tDwvihUdOdapWfNzbv9jor3KT7mpqzk38kCfO/KRccXmltyxjw+6N/sn3djFnHvgoz3upcKYj5889oFud3JsVgZs2h36SL878/U5d/B9zr1UnJQ+He6Bj/W7E18alVcs5R775LB750DODe2Tvkcz7j/OvO3uPTzs7v3RQbdjcMZ7EYcPSZ8zOf+w793V7fZqclP/gT59tk/ib7N6IXjw03t9f4NNW3tiIHOAh2rvSGIg8ZsHsD1E+d1MsociD3JSLYPLHvCh3LAc51f6ndVqc7VSdTnycKyodya2eELtmBkMoSHHuVBnyxPKJb8ZF2YAhuXIy8pyiSFdcJdfmfYUblkxG0AVB9bzk+WF8IzZ6zm/fPSOezvVF4mHFHkYJiTkGMUcRgp1khJKsrzktLsxTfbCQO3oxDjTREGNN+T5vuxJXjIKc6JtezOhQEOmvyY6ZEhqclinXpzy0zkZkrPung8PaDKhDMWLwuxooieGnadkkydySjRvCcVcQfUkL2F46EnWdkII+vZ2euM9LTaJobvT3vjEUL6oyXwYq7idiV8nLplwlZ2HmJCZUO9h2Bq1W0b6I/fGD6e8fnd9UONaYQ28GCQYJzGzZoxmekrune9MuaF7MqJq65UhqmW634CGLXl5xpvcLvDOPz+jF85Oyeh0PbrmRl9LrsdxMV10yhM9JaYSPNng6Fk7pCehLqOvTWuioDz68iJDR5ckxUzPK574HLG2BZeSzvUSfcKXHxtD3fLuJ+OIsIykr8HaYymj1q5FynUPZ/0ffXztTEITyIsD5cEjlYESUDHH2mesWFlkWX2dYggJDW30RDbjM0xWlpcevM5mbJPH5CGH852DScnwuJUPZdp+mI/LknAX9EuJoaRWOT+O+WJQSfS1jUk7VmtbXa5WnlrHQv2QUSs1kqdWuXgsInArCNQejQ1I1MTBI8q2S0b0ggwZzt9qoOiaZoke6NXBeyueweVqhL7olS9fcZefn3bT10UfNcHEIyZ6qZQ975YTcBuda9On6LQ+9xKX+Mgv7dEn8D4/ux2PXUhHhkHCp1FjgFgNBCFtlNGbdQRUZ+zXqicsx/nl6OJqlTddq+XQHtK5Z8bd22+ccwfvPaCFR2QZKb3+jeuiIJvVQzuhciO0gVhTbizoCTZ4+6bFxUtbMB52iEbNx8cqD5+Zja4uLDd1CUozmAvaZNTOio0jl0xm07jjE39WhlVBE6Z6RdXWuyfrZibybuKNef/pnPjYXr0kQTVX1GdxlpWmbjyGvPCRaH/PCEayPNVif8ixbDeT5mRbECIBp25pniWV9ZKkxvSKQaVXIQaTF+c8dZ1MH69bSuEPtCkv4znTJ/5hGYsLjBSqp11RFRkZRel0xsfrZoTJxHl9VWHCoGTnpY/Cc6UQOqX8Yh0zwooQkJSOpWUItatBhAoQ1zoi9pLR16fdVRnotISinWLX6OoXL7SwRFfCOmb1ApoXPm2yqpgw16u2wtpxSawVTqEOC0ntJYSDxUOwb/hUD37+Gk8cqQtZ/UsT130C4eLxZvaIzKF88k6zULJDDnPCVjBYPfMIZ3w/KoRG2OdFI0iI1OQ7857GjrjqLvX9yHGxueglxSgZAcTTDurFqiDjuDArbvYuxc4rD+EzI8d7/HhhTF96cdI9/y/Oi8VDEw6lEy9SGJ3EJxcUSkHYCN7yalq5KdHYJeww6QVZK13v9a4pGDK4h4TXY628teRX5+vb1+FOPv1Dt3fnPhn2HSveh859f9wz4MyMaqxooiULzvDydav3L+vUav1qyW0kj8lbi230QIvtZmrMHf7ZnZuCkm41fbyuHmgtpPJPpOQv6++ieb5lSHNLO7Qa5WOZ2xMBvAJQNkHFVG4T64Bm8xPf69OtPEC3KFw81Mt6wM5qdv/Lv3fZU3FhOIV0anvkDcSAqaabaqbJHnejapN30+jZQqo2KOCq6wnL8dCHWcHo4fxvXeIhfRw61dKzWg75jM6L/XZhQILyDoq3cdHfYXBOiQ2BNNkN3YKMMCm4B3q5V+c9jyzG/Pwl8oh9AKMTK02Jrxjk9QayxhX7Iw91e1ovzhPHiyFNewjrgZ0BQ3dOdIoYhFOiapMpKuNZoQF+0mYS6zsp6jQmueU0bolLhjoOejP6i7sdrAm0FSYL2DI817L6DsMODuI8bHJpGZVSE15iqMpcSmECCqFgAh1fYGDPaBM1W6ozMbamRBdXbVyW5LEviYEjp7rn5A0mLnpOdWOY+7uurqmi6uiQFV2U53D01JyMH7VVscEYtbOqly8pQkbGfsldennCjb0hXaSr103lZy+z8IvaQh+obfAzc72CJS8qJRmlk8LQZQRiaDxLKnjmp5ILuljBt7oNZPNJeW852T2kShD4t2UD45nzUndKFIJZXiJk3V95cYrR4veJuZ54Sy9YxSkfY51QMiaYMl469OLC15KCmg3XNTHbYADHda84uM99b9ydEvXc7HUGlsDUCws6lCu82Dk5CzoyyaqUIa0cw9Yznkg9/+InWbWuo7B5ta4prh/GvueP1/VKQs5KtHImt1omj/CzX7uuZRc1liRPXb+sXnieuR8wYDCeSaOnZsUR3r1sOZ+xgX+q9aNINU6N5Gmgqk2V5fLVS36sLadUs5zLy8lqxTk4nZ3b2QpRW0oGt7umk26qn8zn8/e++eabl5suHAtsGwT4DAhlEx46bnSLVFfbBoKbG4qdISx44ODN7N/f6Y0aJgyRwIpPx3iUwK/WJ1SfcZl/KEd5jF7kmWxCIGw/pKeyesJyiS6L9HDohKyQPo48tfSslkM+o/PK9CUPen9MIQN4j9GJhzUGIYlP9LxYYGRinObx7Mrwg7LMe3NlAIEf8beW/EIiarOe5b6cp3hTGdgUoKXzY0/nvMFZKbRIHSj5U/pMjzi6oSIW1rCCMMP4LaCD9PTjGMMVGepH2s/CG/47HAfVDuQsGeuV3xjVOa0kuKAL7U3+93Vgg1ndiA8TBn+Ka0hK5RSO5PWoqge53o/Blj/VZ/mgfksmzmnBEk9LJ1X5Ci8Z9iVoUa7KyUhGBhPlyjIM2S+qboz5ZZPybWSC5u+mpDayME2mR7HnagtjDTpB+g9aO64LT2VHv3KM9rKf5+uBsFaHeho+9TMvFIw9xiNeV8Yq5zV9MsFSdeldSrR4lT7y8nRKOBqtHOEZjCW+BrBFFmPGrsOb9NeBmteUrh/KdWlRFUuMR8Ip7PoPj1fLr5Zp13cp+TDki9a6vk0m9XA/YGIs1yUsJbQFPHk5rK7PyjW6rdaPctX6NJKn0fo2S76VeKBXx7m81q3b+pzOq0Fo8cprrvQ70XhuDrDtmJuYPJgF/A1W3hs8L95oWcZQuO1xou2ylPB0EgdO4mFjFFJgReJzLPitJlGO8iTkmWyMcdunTlJYT1iOc+QxerjkN/GiCcUbv0lh+eSInK5B/XYMpg6MDJnAdsgzI6R78WyiS/IA5mSmN7ktYaxAs4aX2GPk42UTfDytWOCBplxabcagoJyneKu00bNaqApvEKq4svjkDUj9bpOnNtUr7RCNKkkVnnK3Q5jhaSM0IqUJVhiUGOVeiPqR9mNge6upUg45FdUSWZXfmm3tmSpmtVAFdXg5MnLJD72dr1f7Cwpq15Kng5sCQTFW6CVkblT7NJZ2UX+lDniZS+io4+DgqdxUB9RvSSbCMxRTXdHB10mb1S3IJcwBGe2dvBx4MD39HmEcCa2aDCQZ83UTstBngxLsHR6PsH41nRUH8bYTiuPNXeBQ/9EHXBeErPCSB15l5eF4G6x+cFXLiOY3L3Ukxh7jkeuXsTp7TeBV4GVLPe063yZjlphdT+OnvmAFR8K36JuF61BGtL8WVW65673mNaXYdpn2Xif7h/HIpEy2YWrkOuVewfWdD6yCWuVMLvWQnwGL8UyiLeBJu5drj8+8wj+12lytTyN5Vqhm051eiQd6u3Iub7qOkkJLr7LGNfymmDh+TXHQH9HEwffbX+PFY87tgAA3USiboGKCGB4+WSaoECe46pG3hYEjBprHDDRZxz834g6IsgobKKRTw2jhGLF+9SbMrASBx13lvWzJgxYLSio8TLYf0lNZPWE54khR1ujh/G8dCOnj6ulZLYd8RueF7iV9EidB73XHe422S5+6K3RqfIJeoNGSzoNijvAUXfp0n+RJYloHdJxz0JuRevcsliP+ljLQeeFJ7NcSzH7cYW/omY9B2imjHt16FeIxsKfbDUPhxnn9Q94+saJ0a1IWFGMsndyrejp3yDhQeUJB/Kd86TpwZ1ZLPSumXAws2KwYTHjPswq7IObd27E6hpze4U6FC8ABrFpkmGU0gY34Yz9pTBl7FYPqllL3+hhozTP11G30X2efJoopjCDjX1RUofIT64zHOaVjww8wGQ8l9IKj+gl9YSlqviLwQrLneL/b9aDaqoS3lPZ0jSizltP29HAKVyFEoVttZWnxduTqawbLWO+4UxMOxTqzJKl8mhcQYZYCG/Qhj/ZvShzjIriVBD5qXnUiBpqXKPRYSGpW7/50ZVIe9ISaqCxD1r88qe3QC7Ksep/i3Rkr9AN9zfGMaOnSeqkgHAYDHBo/MCCemjZw/R7//IjGgSrRCwbH0MHT62k8MFYyFYrHkFaOjAm1ImNPjVG5la73WtcU1w/XFWPYx31rixwMfbbVx+06N2yqZaLIoY9r0EofJmxSfjm9qMfuD0nok6I/FANtcqvrs3ob3Zqc5drRSJ5G64v5IgLNIqBLpfkkw/nNGqXKWlDlnhrH1/VQnES4OrjXahIh2vBZ1OiVjIUDTwL7F05M+klZu49m3YUfzLv9j3d6ajvoqdh//a/HPQvH3T/W69781oxn4dj72KDyJCwcD3x8QGwG+rRcYeF495k5d0D0d+8+k7Bw3Pe3+txrf1lh4fiEWDi+FbBw/EmFhUMsHie/VoOF4w9rsHD8glg4ng9YOP7NIgvHu6Lfw+O+58Fud1UsHIN3tLk3vjnlWTh2iQ3EPq0axZdhw2dI89bY/q0+fJaTzbnl6qG/wvMr/UZerVRdjjyFfMG98MyL7rGnHnYd6cQKIp8xbIBDwoIgo0TJ9GB/uTwJA0RCVxeWQza44y2DLSFk4ZjU0sUhCweYV7NwIAud0IPUDAsHjAhzY/kFFg5YPUjIs+PD9ycGR8JMkzCCcF2MvzOzhIXj+3/5snvyI8c9ZrQHZgjYRYjDhoXDxhZUiNSzQC8nQxsWDrDDyEpwsDbldc0lLBwY3LCLEPaDflx/vg6VMxaOkEpu7K3pBRaOwnzSV+SnHVzb1DOliYywcLz97UUWDuqYG1vKwjEofmNj4ejb16kJn3P+U71n6tDy6rDrhCwcyLX7xyUtW86LQcjCQd1j7067F/76dffBTx/VZFFNEK1gRht4OTImFbzI9Dv9S99aP4OBYUa7wANs8K7a+LRrlHF1480ktiVk4UAP5IF7LVq5cMyaLD9Alvmn1jVV6xgi6h2vFh/mY07CD1444Y4dOu5f1BrRK2ThMErARspV61Hvd6hfPbmN5Kkn/1aPr/ckwq0+Ye9W8V6L8vpatypbuMZ7/MrqyVC+e+VcMcd2RKDejYwbHxRY3jPXn/YPWPAZvjdZYo2HzYEnO5VHnrq9be7gBxIe2aN9XXo4zcmD2OWO/GzC5MDDfufhAT2Uejx38tA9CTcsZXcfledHHqRdR9q1KIG8hmI9OD7Uv2AYZAf6/MMZurFDk1k3J3qyPY/0u44e2BVEA3Znl7vnb3WLUivtHsj1+IljO+4bcu//b+WZUcJYaUslD0s+x+58SJ6oBwflhepyuw5DI4UHKytqsE5viDz2Xwz4hyifR7u0YAQPZjAi/pk248XhGA9atjygq1MtTDlmLyU8nMHXZNhDhq3J5mFtyfdFjXrC82E5MyrsfLjl4WmGF3VglBrlWWi4QkuGpxjPZG6MWG/FFFfiaanLt1GGBsbN3HhBf5r8p3aFyfKEOHGMxBamDsphFKELejEmZq7l/MsaWHcPJ3y77LPEMSEZ8xPqe+mTGICiTVMfghG0biTo6CxRD3GYeJ9JGLEYVjBeEBPbs6tLHMiJdxeZUNjRbspdPS0KPS1Qke5OdOjeKYYP5bn8yoz0I1Sk3c8Z6MhiSItLWZ5t9Jw4N+tmNK8ISraCmDqmxfiR0svHtbNzrk9tJQ90aK4Suzot9owerV7o+7lCO8cxjM7cVM4bq3c8xSIo8qoqLOXNb95wd76/X/VjWCYGObGtYDd1WWwfau8cdHTflSF8r+gbD6msdNxxT5faAl954gFFD/igaTN9N6QFQNB555Gyp5/jfHtHUS+Z9E/i5faG8GDG3fXB5HoBU6Pcsxh3yvXuznpDnmt/8KAmhcpQp314ypFBW9KCHWOf1LO7y+14WJ7jXvWxno3ce0j0V5fy8tt7bRk3wUuOd7/6nNqT/OSepetSWNRL1D18f0/lOqeNGiOK16e80crR/0aFyDXOH9eOUSxy3q4X2mvJjFO7V9jxcOv1rMhjzFteOx7mDfepk2s7vDdwnhATuw+FOiOvVvL9o3FI8l95amVa4ZjpwrVdXU+9dlSXMZ1XqCqejgi0DIFVGdAPPfRQz9zc3K9Ki6PZbPY/0f4/mp6e/nsXLlxYLjquZUpHQZsTgVp0QmhqNGWe6kiTeTplePJZbl60YfM35KGZL/qbNuwMTLKC+QBaLMI9Zq/K0OKZiANQ5zv1CdqbTPpNTCZ5oJbKy9iBTaEkwQsUVhrdeKcwTrgJ52bEtqDJUQWxHiRC0E7rpfwfsk6WSc/+0yvJWZ5riSNySe7X3RsL5/l8jwfx4I8NJQaazmCAGGUVNGGwMfC+S/zg/vf2+hXPyIMhwCfTkG6qHqYnv3TZXXxB7CaavMMn4x3inu6rGBMmw8pOXRJlFt5WLdXcu1erBVbVsaQx+rFQTlRb19+Y9cYhuu6Qt3REq9xNSH/0nRRNHPRz82IVmddkKowGQhn4PM6n654dGTchyrZpvSzAvoKuxJXyif2tf3bKdclbzyp9c0wm1MQsJurlpulsxRtLBvRr+5/od90yxibEB3zjtTkfj0obHvzcLhlaCXvB6NkZd+H7EwvUZBmFCmG4zMhonLqQV53EaBJWQTiCYmDV/T37FY4xICP05LT/XM0Ys9hZHz9cGTuMsQ6Nsd49XZ6ZYloGpaQpJEmTGBW/Ci5zip318bMaH4p28JRlvDBNXSAvLwv8oz+dRw+o1Dp70p7WMSeDPxyLPuyhTgzxW79+SgO6kt/yYOyIhxvDnEmW01fyMtblbRYDCPzc6FjQ9QX1HjR5yyaNSfqHhCFU4AXH6vFHg3/UDu+zUf2d6idCHLie87q2iAEGlyFRDY6/lff108gOHWMyI8Y57CDgDIME45cV+FhF0Pp57JwWfoFaWXm45tq4zlUHfH3teukpauVLeJ/RgZdy38f6wX/cP0Ye1XW127kLhQk3eaEgnuZpN3p6VmOTSZR5H3FBX8xPSucZ4aL/0YexxQsYkw1ZipxUlKFrMcvUBc1ieB3Z9ZJc54vUiWBAiAPj1O6B1DN8qMv16Fo8//SUx4L7Eg2BntDKHNACS0YRB14cX+5eUZ2XepFRL5nO1feGvY8rBkVpQvSjb/7FuBs9q0EgGLj27/vojiX3pnqymz1uutS7B9aSt5oyteTEYxGBW0GARs5t0wAAQABJREFU23HTSQbz/61Ck/ob0dt9Tn97ent7f12/v9C0sFjgtkAAbwAUQzzQ8MiRQpoyvFTTlzCOdD9Oy8OoT6Lz8jRmZcTwUC3ogQX9F94QDC24bfNX9TDWg5zHGEaPEydtXh6zoowDHvBdijHkE/aMvE7EiJIWjGd+6OFf0MNxvi2p19OKmQHC+WZTDeN5iQjO629OLwWXX5lyOw7qYSTleajz/4QMKk9lpmwsTczD9NUvXfMP2QXMhCExlhj8dTFVuMrlF2dkjCmPoJ48JyNlRt7Nn9ViHaonpLKiDoxnUmLE63N5UIc/EfxjdaIctHAJtZeMJH01GNeiHWP6GrD3MTyQzl0WPSH9iEHIlrrLmkSEMcnvrl0KRXhbRqT6gReiHPRnMibb9Ltd9F6TohfjhWdaBg6eabxhvODgpXTy6pVkmF99dVpfH7Luyssz3uubkkELndzpP77m9j2mLxJqH3mgBvT1a3xMvC0KNoxajgkfYq4LfgiwSE2y+t6EqPPG5ALH6yq1FSddAYE2qHrYHAoa0ynRtjFuispLXCgvAinpzstCSTR49BP1oAd97/tDLxjEAftJi1wKyfBL9FOe2ctiBdkl72O18YwKErVsqshayKN6odmb1NhirKNITltin71RL4EY8G3Cd8Wk4nb9QN22bKLJACd9oPZzWsJ77oaMYmxceRGJsT//9LSM4g7hpZCVG/o6oOuie3cSAgG+ZYxw4TR3veiunJxyg1MK33ppVi8EEovxjHyuKaWyrv3ygOoQ3zJ96lsK3uzoraUk1w1jyt8/pPuVl2bc4IdEwyhathHFPWM8k6avzPtxhle6XZjMXU90Rm/GyaRe1FLSaX6cF1M6T/vQGBL77hXSdaSvVfA6h9cZY4+XJq5LEnHxpLNfve52PdxVoWpM5PFF7a2/HlMeYtW1GMzZZPARs+/LiBpuj15UE4q45GWEFvt7xc8OL95fK9cx1+zSvAn9JNdH6M32wvXPwjUu7KrvDReem3KlO3QPeXbKjUEvqb4jQTUJFaXdm/zBFvxjuoBfrXtgrSpWU6aWnHgsInCrCCRXR/NSnlQYx/+oYvmXXnppWvuf1v4TzYuJJW4XBDB+8CCEiU/gGGCeqskbHAklFN4w6I6gPuLTN4aGf1DyAOehqD+Ok3hA+oek/6X9igHBMbxQ3EwxeDQfSycrmWzDb/JxnnL8Jt8aJq+v6sjL087nWTCBho0EwwHeQDPQmN3PZ2S4gC35/MKSVA9TPLrgR/JYIcd7b5NjyLCYWPKBPymhzEpCEJBdK1mdntJKcnwf0U9Wh9rFOXQm5IXjbHHpoQuLR/g+VJn5a4l+4O6ZKir94duvvEyiK8rzzBZDzFOHKY8vX5GXF4bEzKI75UhsMVqhSITmDsPW6k9kq43yhJYkw+ev1OvHgnT3Y0deRe91pqj+FpLl1QGO+/GlAkUZhGCRUJolMpDn606qUWYVqvz59lZk1JJd/RVkIU+zO5W66Tc+9/s2o7eOo/8C7hXsmhXfSH7f77qmre1seTFJtvxI9EEWXnJ084mt/sAYajjCL+hn/6JLBsvnM6ssL2A6lvSL9iXX52GrZMd9/2oc5hUqhPcW7myuA+rhZd2PM8a0dPHlqadSFzLQhXFdktHu/xinysv9hjGQ13jnGgivM+onZjq8r3FsfkoLAF0SlWflGuQYY5pFebiXJfmT+ngp8+el8/U35rzu/oD+4X6Y3CsWO9LuFVzrtDNM/OZ4rbR4jasd1fcGXUsFucYI3bBzyGCfF7J6941a9TRyzHQJ81q7wmPh/mrKhOXjfkSgVQisygOtys1fY3pw5VduY3YobrcTAsSu4U0JE5OXjKas3KFP3vIeklLyMqdm9XlZi0r4z68c5k8jCO8SqU2fSvWI8V47HD+V55tnOMAT7T0++lSLB7BNHijzQCelK//iwVIiHIAkJr2knqXPGn+uVf+gF/oSfuDjLrVvnqt0L+EAiTKe2kqNxuuS0XFLYAiWpLqYVmi0yANe4ArVGwwLJGQQB+n7Q8DZ52e2eMnQyOrwBYJ/FuvUhDzJMXoqHy4j1cuiN0MGoQGs+tfuFwFBCfpBdctj5RedUB1Z8ep7b6F04HM5uJDw9vl+1j8p6dw2rvK6E3nqMPUl55J+FQaKVSUmGd0pZ+X57M+ETQYGiz5Y/Yls0cvJ413UKoA+vzbeW6of6I4xwip0bVrcxzzQC0OioiNyCUUwPVhMhMVSMLC8nrz4KS91E6/sByhlK3+0F8MSGdokyWTrF/oRz7wwsC1Ps1tkSgz9Zh5oB42djlM3iRfImowY/uyt/0N/4fnNa+W+hfbzZEEHXcds/XWBGgqpapN3WTkX8uINhsXBx0+nNZHR4o1VLsQn+UqRtIvy3hBnp9LOpL+SuvCcpgcV+qCGdyou2zyp0Pm1aZKl90DjJKYO+0OUZKELY4TwMFK77lVeb59R5zXu7TpauM6UjxjchXpot1K2N+3DNWZYXbKSGNPwlnMP4IuK3RcJNyMRrsGS5WwtgWNyr1g8ZvcKsA/zmgx0q5UWrnFhV31v4Lru0Icd2EjsHDLYh4qy3n2jVj2NHFvQJchs7QoOLdldTZklAjb5j+qFVKoXTdmui5Zsxm6r3HqaVu2EmDj+B5VKa/uw/n5T+882LSUWuG0QwNAgtpaHmp+co21IU4ah0qNlczM9MqxkWBPC0H+n4jAwMvRQy8qI7NqNkaLnmUITeEj1HtBDRs8UnpH+2aUHWloPxqwm42G44AXi0+rwfcQkyphSpiUUVnrWdIgmLKGmEpXVkAwrGd2V52Dz2K90tXBef53Sb+TBXjd4T6ePTU10U9iGqLKg9CNm23supcrRz+xUGzWJUJ4fsANDsCTVxVTxop7WDS+avGKsTIdc4kpNBp9ukUVbrf6EOivpJ6vDVxT8Y3VSEFo4T+2lGHLiQKGNO/xJLVOmc0W9xIyoTuouSwe4lqE648UHg6VfzArtWpZu4GBWBgkLLfAQVn/IOGKFNwyQPtGLESdN3qz4dKGVw3hK6SUDWjaM5F1HezRxrcvtfU+v9zzjsQO/I5/a6SkSMZzJAzWgN54VQ4E8Po/Tbm/EaphlBAX9UpInjXCiftHB7dEnbl46vMHO8KH/GB4aN3zex8jFIIKmbGB/lw8lgdKMNqY1rggh4mGPnt5AlVzGK3R1/fqET5gRRpKPW9Zx+oa6ukZSiucV9R0hqjq+JC3aR0sOL/xAXphH5Yn5hoaNawrsOgcI/8EIUj3CCpq8jsqYWpBTa0eyuH74g5JvST3V+aWDx1t5mWMATV6nri8fuiKPLas17n+v6CtlkdJnGKXQyfHWgcFHHeQFD67h3cd63dA93b6f2wWar58Lnz5RIga6TW/AjMfuYbVR8d2UpS95yUsLS/oEAxjcd2slSsYQtGwYqMNHkomdPZqMyMIjxOgTc9y5I9GZfqNcn8KFujQm6cMuxdHzxxgnXt5oFrkupI2/vuw6o2+5Hxl1onlqD31yh7vzfYOePhIvLlgQr37ss7u8EY+3FfnU579KSDLxy0yWTCjidD/13uW25F6hfqy+V6DD0ryJjFrhGx5Lyah3b9in6wxM9z+h+5envky81NAnQplX776B3NUku9+AX3W76slbTZl6sjbjcRZSySuWir+x6VG358fSfplslsrm7/HP3uMGBurHt2/GNt2uOlXfvhtqpzig+/Qp8/9S5k/oj9v51zWZ8L9/+eWXbzQkYA0zRRq71YHbKho7/zlWn5PxEtjNlmNGQcbDE0oo847ARkHiN5OCmO0+9nbOe2CY3T4zqsljihncpQfgPB4uJWb4Ex5B/DO0XdTD50or279fNFaSgSEHC4dRUKET9fHQgoXjXcX0wcJx9wf73bXXEhaOPYpXvPZa3rNwnFM8IPG29390yLM7UDcsHDBKkAbuSrtn/uK0O/bgvaKsgy0kYXBg0pDROZGPhyntNvor8EBf2sxDrhZmlLNU6zzHVmLhoLyVDeu3fjH5tbZhOTMG8LBR1s6BJ/srsXAQWhCycDz7V6+4Jz78oCyOxBJETkgZZp+e6ecQx7C9ZhyYLhg/6EFiEhgpHBN49NB9XMtz4+nkpYr+gDGBYxjCsHDw6RyPNzJCPchLoh4YIGDh4AsDefAMIueq4mwZp+VSYvVxDHmwcOBdvPLqjDeeuoYyC+1lzBoLB2N5XMt8M34pR9p5uFsTMWc9JdsH/vYDHjNYLshjLBx9Ws0y1A8mFFg4pjUBF0YUEtRwtJH6oIwzFo5LJ8bd9LWCZ+HIKdbbG3Qa45RFBtgkx1JLWDjAmtAaaPjoI4wfxjN9hH4cxwiEhYO2gD99Ztd7SHnnJ+1JBuOAZP2c7ipr2fFZt1exwVDzEeIBRiT6AP1oK+1CBmPIKPeYrHvy7Mvu0cce0TtWwnJD3xk9H2O6Wmd0DKkGbdyjV7hv13F4Hdk4tGuCcWHXN/py3u6Bdh2FDBvkqS7DsTDPSveK6ryUXy6ZzuG9ARq7EydOuEceSXCr1nk5ebdyznQBvxDX5WSupsxy8lZ7bi1p7CJl3Wp7pbly+iK1KlsYf0bT6cyZM0wg/JXKX9PlY4HbFwFuftV0QnbMHkLW+uQGWPQPQB4OcPKSdh9LHvrsdw/Lg9mVVh55rfRp2m6wncqfSicGmD2UU5m0pxAjz8jxrH/o8ekTo4GEHkb3hY6HfirxSnGua0fyoO8c7BSllrydeuAdfD/GtyY6agJdWQ+W5BNqh9vzcMK7m9HiEQP3ycg5Iq+xPGu9e9oWHpo8rC0ZHpmEsc/rYUYe9dhDyvKH2+UeEoaZPXCsHnuQwgZiLw9tciuFoSLUQb7Q+DXDkHb6fRmaGEFeBxlI9AHGEm0z+i104IWBBCWbtQcWDAxg+hyPFkYO+zAxZAZ9dtUtQ1R1LLgZtefHSoVijP0OeYLRkbZQZ5iW6q/V5PRlg4QevMxgEPES1r8/eWlDhpdfeRGQWeN/2+dv2jpyvM/rmXg3k1AYyrQpRsiMI2sL9dGPSRvL6vuEU5i4bIwnysGogqGWVUjPriOVARA0gjr3PCSaxYrxCEUb+3sfTcYvmHfpGui9E9zFdCGWGugT0/L4Dt2tMBbVQ4K9hH5LZTiuibnqW+8t97ondG/kQ/YdT+FuT7Du289iMywZz2IxlT5SnRin1N07klDDcQ3c8X7Vy1cGyeSLEm2j/6Ed5DiJBWw4jq6kBH8o6HhpTq4/w5FV/CiHDMaIHx+qMxzX0NtZwjNs1wN8y+hBW+1Fh3JQE1Jnmw/vSkqSj2uDstwLyOcZSggr0373Ti0ao7/qRB4S5ZCB3oms6pyVcas6LPnwLf3g2rZyvLSFKWnn4o3C7gnVeew6Sncneth1bvkME+qpJcPyVW8NF47bvSmcxMr5ap2rZbTqd6hLozJXU6ZR2TFfRKARBJZe0SuUUKjGv1wuiyYT/pfLnY/nticCRjl07ayopE7N+s+5OU2imRGfbX6KeM2y69dnzSf/7v4l1EtWrppqiZXVoFJD3oVnJ11OE9tIhIHsfbLfP0R5nYQJ4PrrYlpQiAGfyo2aCoMJKql7K7RMJ377gnv1y6N+gh8xyvf8RL+YPUrukmai52ZEwSZjgYc9hkuPvIlO8ZG8sPKJv01OwQu5CffafxiTAZDQTa1EIeWV1T+0r5reynQij7UfDyBGG59dMU7qHaeM0VlNnJsTi8Z8Eh6jlev2PNbjHvzMiC9v+V75vSuahZ/zXng8hW0KFifEgZgZwi34/M7yzmyZeJWSUdKtz9fzMob4JI/BaG0987Wr7uXfueI5dds7hO/RLu89hbXj/PfHk5AVVYxhXVY4xdkbp7yRh2xWe2unDhkqGGCMB2JE24Uvsd3Q202cy3kdiLEeuKtTtGd97pJYQNCfiV1pGS9Z/cGRjAcUKrMOxW32KGygJGfuzHV9YZABT2x6tqdDK6bpE7+8wjZ+CAPolud15MEeP2EM1oYkZj1Zga9vT6en7bsizuYZTQpjMmG3qMj2HO/xBhysD0w8wzvZq1Cl3j0yyPTyNn1BXzyYMKa247WmXUbbR3tZWprV8aBwY8x26DwTzPz4Vb9fFs3erF40piecO/Orr+i4jDqdFFw+3IDxCg1kCfo4hSqMPN4jnuauBYo0Po2zumBRRjzj064B6oC5AwMPKrm0Qhr2Pt7vehVXDlsL/XtV19e0PL2EHRBHzQsYRktBcihDmwi/IhQimWDJuOGlJ+XH28EPDmoRlTF3SXSL9KG1FW/86OtzGkeMOdHC3d/pBg7Ii67rdTm6xepxDxMMVHDQY85dl87qW8YklGv3/PjST9xhWesP+iK8rtScm1JYbqW8FLb81fcsu3ZvqmCFAyav+h5gxVY6b/niNiIQEWg9Ak0Z0Kr+fOtViBJvZwQwEqB7YovxTJoTX+yUKMx4KCTevzZRj+XcqT+66qnJ8MxYOZ7SIdUS/KlQNo0oxvGqPol7CrEKgLOim7r6yrTL3yV+WP2nKV8JDZtkKDpYs/FFraZ4S6jzoGiCZo94Soxnkk3wO/1H130MLEZdAfosGQ8Y6cSTXlJYB8tC4wHDiBr9rgzzV6+5lFxo5slEv3oUUhVVffughYIeyibrmE5+qWBlBDc+LJl3r5o2KzxOGTCjbrzlM/osj7eYmf2dsiWuiF7r3TvH5Y2t5BO9FgwpxOjyKZ42dnTBaCGkiENX3LLHTBR5XcKoXbPivIEjQ3FALzAwFbjhpL4Rrbx48vevygsqj17lq8BF4dQuarPLyu95dn3DWelPjASCO6PJiN7zLON3TmELXTtVh9y+eDM9v7KMtQlxCBMvzXEMQG8MKs514p1598q7s66HRVFksMEIMqtQH5bk5sUKA5PAMvS9phCAwfv0eX8i4QyGCYXpqReenVD8q0IOoKBDExl1E2/JGJexiFEPXzR5+QMnXtqg7ZuUQUk/M74Ys4V5cVjLuKWjGCPETE9B16ivJVMXFEKhsUJsLN5VWB+yQ6Kc09j3XkmVgd3h2qmZiiErA/jhHv0W9Z8ayx+0h4p0l/GvcaiXC8JCSGidcD4TeoTXN/GgXpGOl34gSjgo0uTdHX8Hru6iv17mRTdH2BNzCAhNmhV9HAZvmwxvqOQuPDMuz7e+pghvaOVoqyr3+jMmKE9irKTVL7zslBgHeuEpatww3viiwDyHKydm/BeGafFw83JCzLxvqygHmXwJ/zsvFLTx4nPTyUsuqAqTWnSLdj/QaX89YLC/+qVR3y+MxZwmZOKFxwPLNXVeL9blu7y6C/cSyhKbDd6kPY8qRlvHuK5q0bNV10mZenk5Z/nBLLxnGeVdrTooVy+ZPGsz+cL6VzpfT248HhGICLQGgaYMaHmY/+FK1cpL/SXl+8xK+eL57YEAhgOGsvdiyTjBwPA0dvLW8VD2xpq8aXg44Xjlc6x9FqccDw8m32BkssVYwpM2J8OHiXg8RBKLSTL0MOZzeU6LemCEM5Pee8aUh4e+p1zLyziXfYNxDc0ecalQy5nxLCFabloeX+nULl15GJIo7+uD0koGEbKZRJWH8knmjH1KJy/6WTv4XSuBC7RQ1jbysI9OnCP5F4zKp3H7jdxaxylDiAN146Rk0p+a4vFBV35gCFo+6LXAxi9wQj+QRUV9e7UP2wQ/6B+ov1ioAoo0GDagf8NLjFz6FQzB3ZdVfyEMrKfFPFAUtvxGPoYW8gS91yvJmpwD07IMbj8mVBavMfR2pZz6UYr5chSVzp7+TjpgIPuXLeVj/OT0NYMxwJgpQ7lSqZdFWvw40QmWfGfFP0IcwN/GTyJX40cYEk7AgjDQlvkkObAo4LUlX9KYRL+iGCWYvEk4kdeR09KnMIPXHv3BgnYJK9VZmNGLiX778aN+IlQEuRiBhKvgEWYccB6vLTiCl6ejC3CjkSVdH7I5JU/nlZ9wJe9lpj7hQ6J/+arAS0xCw6bxK1YJ8Ka/PN4VufQlmPA5n3GC3h5LazJdKZnqxoo+tEv7lZdMr6f0oK1gwiJI8Ll36KMN/UJCLnu0i3wcLuXhhJcxL+MWrzDt9+NB58lPyALbcNyDE2OOF0RPZ0lfg7F+t4ndB3noRQrL+vuQ5JOoA284cq0ef6LyT1jOjtfLy3nLD2Z2Xddqi8laaWvy7EWZ/GH9K51fSX48HxGICNwaAk0Z0A1WdX+D+WK2bYAAnjY+fcK6YBRPnsZOXq+y4koxIEh8yu2Up9MMUSvH09Y8tGz5jIwHsFPMB3jY+KS8kOTa4mFDuIV5oNtv6Dyfm+W5a5dR4z1uGvV4NYlh3X20e9F49ookn/5ZwMVYGfxhGcu+PulNWzBWMArSCkdgIZEwoZ+1Izwe7tM+WBKsbZxjH504RwK3MPEbubWOJ3ip/aobDzQ0bSXFAtN2dMWzB4OB5YNeC4881pDvA+HMCwEGGX+ECOiMzgk3tRecOUZ4BuwGZEIuBiwYgntRBp9PqotwAhbRmLqUhGBgcFMGeUXJT/pNvzmqcx5TlUMXPKKwYPit+qFdiuHpxdjCm1nW7zYtmII3kWPka5PxTUz6zFUk6piHTvIku8MzbbBPu4i31b7KgH8eCjol5Hr2F8Vf44EmMVaSpPAOtcWHlaTArFKHZKQ0Hr3hXNGdBiEb9pe2MdXFWEG28KNPOtS31GN9gnzkEjKBbhiLjAM8zYSYgGMZukf1DfWE471d4wGj0S9MozZ5Wer/lEDhywIJpgvv0Zc+tAd5KXmPUzLkva7g7f+S6xNM8EAzTtCb68/3HeLJpw0GO/oU9ZLSprqge/MYcBxs1da0dO9SHLUPCVIpm6ODXDzQLFri20J5vXzAcJFIT64DxgO/yU9Kxm2yz29wYsxhAPtrGvylr6ebk/7I+//ZexPoOK/rTPCiVhSWwkqAIEiJOyVStFaLshU5kh3H7bZjx0nbTpxJfOLsp+NJp2e6z5xM0jPpnE4n53R6PEl32m7bk5OluxM7Sds+kW3Flm3ZliVqpUSJ4r6IIEBwwQ7UXpjve3891EOxAFQBVUBV4T6p8P//W+6773uvWLdu3fe9uOeUX9SW/wbZ95zXh/c+s/1Qtk2FfTKf771idVm2UB+YLfSBuSwcC+uWkhbkOZXd/lcqd5rprSKgCFQBgfy/SJUTjn8+Vpfgvf4DvF7ft2/fcVx/k1LuvPPOu3D/DF4n8PrC9u3b8c+/pnpBgB+SjP/jtedOb+p4qh1pxEhfRc8ZPXWkHrvzQ1vwAewtSduOn9guDRs/3Bl3SyNlCww3UojR8OMrgk1QWxDD2ol46k5QrpE2ztKwkVmBVFHcFMOYaFI0kWYv2BKUgx8mNRs9mp4BeMeHcAzuQ53GyOYxztw0x6OKaUxsBc0T+Yfp/WHqeVjkDlALMRnvL67Uz47DFBT5w/GRFor0UJ6XKrugE8vs+Gkg0tPGK3GkXF4L81mfZQYbYNTSS+5b6g2DE6r2gclgx0MdRq6pB3otYkNPJbEhfZzhgGXcMenAYIDxNLsoKLZCiBmmLMaYkx7MGDYw+Hhlf8SQtFykhKM3kTiRdq57b6sJCaA82pw0xEwc+U7INsYhf1kAnd2OXB/YQMZj3s3mLVjZ0Z2go7s9AnpD9A9jicYR1wsp4u76SB/0R3wz5pKx6FHQ5XGTGUMtuBZo7NHA7j0cMQY4j7um0ce4Zm7w2vbWqKG/s+vHyEV/A6C224L4aCbWJUbEbh6/XJC2j/14HmRvzW5/oAPl3i5VrhHOi4mB7ms2a4XY04BiP62IsebR5VzrNH4Yw8twh17017U7kqMNmzdrglRnXL9cs4Z3GCqRApAY8AsoMW3t8zbNEid6VmnYks7wLswFDVb+YtLSGzJ60INNo9LQs3WANg0bPxnOZH4VwPuP78VtRzoMHR7fc6SV43uUuvPFTXlsT2Ybsz5grHKTIekLQ9gIyfcVsTJzBM913z0tcvAn+gw29GQvjBWUgwP3tBk9jM7AZ+ABUBXuihi2EuJejG6x8P3AZ0sByS8fxJE0mWZzI9/bb+W/OZSGIaKufc/wVwu+9/m+Y7y6fV+xTmFy27nvwWJ13X4K/83i+8T+G1jYx3LPK/W/UvlysrWsdhEgD/TVayMyMTUuHudz7eq62TW79V+NNSICI/clhHDcV64YtPun+Ef/X4Ph47GdO3eGQ6HQCXhk/gl+cv0byPokZH4fdX4X90Hc/9ZS8pXGbilkls+vFI3dUr3QU0ajk4aYtyPfY3ew9Fr8QC9mdNp2/LB26aNsPuVZ+rJC2jP2x3bW2KXRYu/pwXI/CF26Lcs8EZ9AnCg2OpG6jhR79HjRUGDfDKUIdzbJq6+9aiifyMLBPHqIi41jOVz4czRToU7Ms+Ok7q6+S+WzDcMTqIvLwkG93fa23kosHGxnfy7n2CwLh51Dd6xkv7A0cdwsyES86U1doIpDrPOxF4/L3ffehRPaEFcOg6ywD7ahwcL5ZLJj4ZWJIT7s12XhIHZ2btmfy8JhadGIx8wo4plB7cb2rO+uH8olRjbfjtHmcQ6Iu2V9ceuzT1KqkUmGdIvEiu1s33zm+mWinEJMmcfEvt17rt/YVFJeeeF1uf/huwwLB+tRHtckr0x2Hu082zVg9bBrjLItTpRtaR0Z028xse81Xql/4XuA+ZalhbhzXvjeoGx7b/UgXi4GXD+sx3xXZ46Betm+WadwvbJO4bq34yQtnsWXOrl0bP7cSUpuW9vfUv2w3Ca3XTGdbD17tfVXGoutv9LVyltK15XKV5Lvllf7c8Dtq1HuK01jN/YC/o2ZmZZ7fmKndHaCQxycz/x1SlP1EIDtuSpbOPdDX/UUK1UyjOKvou4TeM1HIpF+GM7+dBqRhD5flMYz5WChfg7/GH4Ht0sa0KynqfYQ4AcPP9j4jz2ppPjMD+yefZ73zmrsfhgwzzUoeBIcDQHKceWRmo4fLkz0armJ9fhhbpOlpuKz++HLD3aXfovl1M+jxWJohWcgUB4TvZgMR6CHkTqR2YFGBPVlKAHrWfnFjBzKsGPjeHjP+vbLgDUSiYeljHNlerRunsHBdsZwxaYsYsF61I8/V7djYx2TkQM9PeMyBmMjC09r60K8Oet27/E8r6zfebtnDPGe+PlA+eWN3TMCrbxw1MOD+tNgaOsH7aBj/HBsTF278vL4TKqx7j3eb+yURaxpfPKeca00npnHRCyYH0a4DJOnhzc/LGPfzLPzTDzoebXtLR5kh+ja5RnllGN1ax/w5o31+CWAX+pIgUfZNnFMdr74Zc/2acvZluEzTAlskqUcQz+GLwJcF9TFYkX9+AXB5lsKNxrzdq5Zn/qZuhgfQ4o8Srj8Wm7LM7wtUAlafdje1d/Fhn1zTbJOFBzSHAvvDU65Pj09yDyDA0XwYgpg46c3bt4DD8ihXMqiQR1o5i8JHgZWD149XbwvFBwjE/uy9IecW4utV+qtMe8+l+PUsfNm1gq+lNgvWpZqkLJ5uE8Ge5ZZxx4IY8fHPPuFwu2jlHtXV8orlmw/LFughytWscQ8V16xJiuVF2ujebWLwGDfDpmKTBnjuaurq3YVVc3MGVm1BEMGh7T8Hgzl38QXgi9Ase14XbEKnjt3bhhe6EH7rNf6QmAlyiW33FJ5kdaLtFOxyZTZyMXwAEtBx9FzV7rZWIM6/Diz9fkRvBxNlaV7I71ZHIwEpEEjBRZl972lFewRs2AviOGDnUYnqLZwGl4bDCdLocc+uet/ZARG+7OjMn4+bsIJaERRBtlCSLHF9qTsMxvQ8GHPGNRO0HZ14sQzV1fSr42AGSKBTZLsz1C1PdQOHRJGBuV27wubZ1LUkWUj0udtXCOjAjdMsV3vIdLHtS4au8Vp+MUpHIYxgY1szMGHO8IAtoL2b9s97cYg4s/M/BJhsaHujPMmkwSNTzIL0LM3AWpAbtyi/l1mLDzIAxRkoD9juA0p3Kws9mPlEWsyVcwj4qX16k2EsHhUY3YOp6/GZRp0dXQGcLwMD9n+YIehBitG90fZti0NOvY5PZIwTCRWd4YdmBPenHXDMdrkrrmRY1NCOjoaSdxUytCeez6+zfRv+3HXpb2fwdyR9i45l4ZHFxihPUO+GZ5CxhfGtVsaQepn6QMZs2vxmwFVnaV4tPSA1PG1/3EdbB5xieMLXub5Ibnrp7aaObL6l3O180BsiO/gQ22GHYNzVwy/wjkgBjdPz8nwc1ynpKVDDDJCJ0gJwq+tGazzCHiYGXpCKrl+vI/IiuLKd7Gn7i7+Fk+uK6sP67t1bD7bFpsTlvM9SvaRG+dA/ZdbZ7Zfyiq2lmw55brJ7Xsp/dz6eq8IKAKbB4G8O6NyYy7+tbxE+Qjh+B3EOf9+S0vLP8Db/G67e9tpvtjF6BS4t/xZhS9NpSFgsbLX0lqVXotGyRBospgYD8mNbnxm3CI9KG65LzQvEyc8yjt+CI9diBnqMhPfCuNqHM+Xn5lgaKExtgrrs5yJMauF/TCfXr1TX75BW9x4oki/RnYPbhQbOz8nN/GiEceNWAnQqjFNwdikwXrqy1OQi+Nu4UmbeD0GOi4YAbG4oQVjPCVjbcfOx+TCU+OGWowxodOn40Z+OwxRnEcMKrxpbKLK4kCWVjMWrvHxSzGJgVmE/RpKNXzQv/ZmDLRmbSbGN4Mg1hNfuCFb3hKB8QxqBaRZ8DyTvYGnp3kHkghkzxpDeuA+HAYDjC8/S8wZZw6+6pfBx4zT5gxucO4mwcxwFXRf2+5DjC9053xEen0GG8r3I7aYNGqz6I/YM5EOz2wqg5BAK9vPmNhx/sTINz65hVsQm2vnlvNqsU7B6GKKXUK8+ZEMdMMcohWGbDYFkiaO9+2gZKPubNeHGGbWm8Cc0lPLVDj/dj29iTUx+soMJRrdSXc3djpj4nAp17QDHsXWHL2XxA5IGQ86MSPed/xE98K6ddcZ4565RsnqMQWqPybDSY3lAtW9jXL4ktGETYc8Bppjax8cM7R+/MLDuGKuP+KXAgf3zBUwx0BHsoBku7Ny8kvXjWx+UTJsMICOlIAdt09Afxz/voT30yhS5I9d8yxizHgW64nUgzzqmmuUeLv4sY47B5xPxn5fe30a6xT0hwB0Hu/TKVAQBlGXGzX5K870UMJ84RrHe2j8wpxsxZczOz92TVjdl3zP4/3Fvlm/Be85XpmsHHfduHPC9yXng+tmC2L1+R7llxnbL2UUXUvOmmAdm0rRz64l26ber/bff3ut9/Gsh/6VxoprmC/KrbTs9cBjM/WxKgMaXuA/QljF/+YChbzPIu+X8EH6m25+qfd79+49GAwGfW+88cZrQ0NDMcj7Oyyi+/EP9YCVgToDMDaG7PNy1xMnTixXrGVLIIDj2JcoWVs2f06lR8iwW+REcSf+7NEhwwrgljN/5rpXKX52Ap5N/iwOD9eNmDFquVFo9vUJwzDAjVWF9WdzbRPnUYcfok4/lJqE0XsDnuMm/JqfwGczuZ7pQhu/hgMycEvOWn5YGwN6mi3QBscpxyM49hjtEh00/KDjDRhKMGzGrk4ZOjvYP0ZHGhIJcB1nI3FjTMXh8SWd2Nw0uNnwC3cKzzeGJyTROoGQDa8/1k9jXJSRxWZGQ7VH2aOTRhfKjMH4vQFjLQ4suSGOenNscAtLIo4O0Jh5169MSqpz0ow9DZo15lNenPccIC+84pWE9/HCayMShleYssafHDLY+OGkJc4JjJ9tU34P+zh04CY9huRlEKqQhC43oRNxJmamzQXgA9mcW3IUL2ANWWzLDW2XzwJIJtQLgDaNhv0M5pgbv1KYZ8PygLbPPQnj+RSwA07WgC6cf0+QN6+z+NeBGyJZJw55Kep3bQIGq5cXOzkhc0XWXAJzmQR21G8eG82oBzH/wVdelzhk2nVk12XsDORAJ2KW9L4HwCuf08T5ip8CvrPTMYP32ZewhoYhN4ch147B701wogMbw2aBvNR1hNhAb8EYSOdnQxBmp2Jy/vUrMrftinnP2HGXcrVrnvPKxDmN4X1w6Sxk5SJ3WMfi59WCrrk5mDrntZlBHbtOoapZ/ynQwWVIBUJ9MfabVycNfpyDZAfWYS5qpvB9uNR7PoH1wzasP/W9IRlH3+6/G+ZLYG7dsI6dE7ZjmuZ7NOq9969cuWLkcC0yXSuyltw1YSrl/pSin/33y23XCPfV+hxoBGyqPYYrV4Zlahq/8hwflmg0Wu3uVP4aEAiU0xZG7R+gfjdeH8J9LiIRHzpNTQEYtj9KWSdPnvwOr+UmyLgT37b+xaOPPvoYDGh8jMmHYIx/BnIfQF+PwDj/Hp4/gefHS5F98OBBwUbEUqpqHSDAb7r8R/Pw4cNiN91UEhjjicTPqYXpwJEe401zyzHHMjoFKwOpH0wOV+dmZQrWTRRxrfR8mfxDsJJwy+fC+qOob+rs5kEJXn3bD/PpjZv79pvGlpyKJSROYmN8IHf1RTx5qGPbTaOcqX0gJP37W+VabE76d8HiQ7o6MS0T4zicpCMqs7CQaZRSRyo2Ccujg8cDY3Nh+ipONIRl0dJO/WHYIT62d1urbMXYqCv1H4fFNAuqNvYbJD1bmAwB89LdD2838rK4z4zMSS9IaK6P07qC4RlAaAgsf3qgw2BCYPJhbFsG22Rgd5s3FujEwdFYGz86DOMbGQY3oxoYFHyy665+hBvwLSey711d8r1nLpt7Np2OJ2if42d5772Uhg7WA21o+MAL3QOdrAeaDYkPx0nMOa8Wa2JJjOayMdmxdwDrDFYqlGFdelySp8bNfTtwQ5ZJD75rh5yOwXPLbw9O6nfm32ZnB7FuQMxMDzR1n8IvA3Hq1+cdmMF6/ThO+44iay67FaEpPxglUgZ/M/8w4t7+gf1y7gnPA+qusz7E7l/D3FHvqZzlnLoJjzSXkjcswm4YNFrbsQ6Q9t7XKaOBOZlBmAoTdfQn09KDQ0+sB5r57Vu4bsAVDdnMZ5qL4eCYKE7YO9QN/VfngeY82MSx+GNJuX0vGW08tF38bD1eOQdn4uPGAx1/44ZMz6UwT56XP8MjxOFNJz0fDU7K7dnKw1jQEK+tu3L3OYHu+3DJ93xu/bDJ/ke65fTEWK61d2Efdt24c2Lfl6OTM7JlZ4sMDw/L4OAg1maTWYtsfXLkxq1ryVkTXg/e31L0c8fjtq3X+2p/DtQrLsvpXWkv8eDgNmmfbpP9h3tEY6CXQ37jy8oyoKHud/F6K178V/0KXibhH/o0/iH7Z/Z5NdczZ878HeKf78U/eq/gw5jy/wbhHH8Lr/MbMOg+CyOaX8UuoOxjpcinEVgNQ7CUvuu5TtVwg33GmFcbt2hjGQPB3BJ0yjOkmgKtFT+DaRx2456nlvEwC352MsZ4x9s6DcyUV1iflFj8iM0mSbXlxcYu9IN8jvHAB3tNrKzZqIX+GAMtGWykK4iBZgwrY4ujA81oFzDtbFxn586IxMKT0tHdbGKQSak2D32Nfm+PLsRAtyOOk/GTWcRAk35v6wMtJgaaY7O6krt6ZM6LgSbtV7EYaNJ2MSaaNHr8ab8VscYMF2BIAA+QoJ5bQQnGzYB27NtB1cdEnLbd27EQA812JgYadF+SxYZIuFwZQxyKhBaw4ZHNpIpzY6AZFmNjoAU8wFvf2oaxLI6BpjFNWRZzizUxNic63k7j378oBpqn7FE2Y6B5qp2Nv6U+Ox7qxC8FOJYdMemc2ML5tzG2t+F47y7MCU9jpO7cSNi1x4uBXlg3oPKzetGza9ck8SB2jIH2DtjwgSatR5rbm1HHw89dZ/OppoU1Gm73YqB54lxhDDTXl5GNo9Rvf7hbuvGlzo2BtvhFOvIx0OQo3w+aQSYbA804Y56+yXW/oL+pUdofd83bGGhSD/LXlmL42TqMQ+ccWJz6DrXj1wIvBroJ829Ce6Ab4OO3cMRAw/hHftcSMdCLdHfwd7GlV9m+b4Ph4ELfVk93TRdrx/XGGGjKofFM3W2/RdeSuyZcOEvQz8p1mzXCfdU+BxoBnCqPgf9+8qVzUGWgKyDecz2UKQjG7A9ZZowym1a9utLYrQ5ifos+duyYoWTjG7daiV4du+PexkK6fbnlzLd1eW93ztMosW2Xq2/b2rqU4SbjiQYFVyEFFutTru2PDAzFKPR88BIfO/aKHNp/2LBwsD8mq5+VvxILB9uwbSGlGtkLXBnuM1k4LI0ZdXVZOKw8lw3D4lTIwkFmh2I4uf0SD9axtFzU06Urs/3ZcrdfljFZeSF8DSaN3X1H7l4waqxubMd7yrYsEV5r2M3OfFh8Wea2tfNs+6IM5tl5dNtZuYUyyJ4xds5j4SCdoU1uP8yzmNl7YkLauzB4tz1GCjK4BE0e2TbIVuHqV4zCzcpwx86xTGFz5cmzb8gDD+cxs3qVe3Wx4Xpyx+Xqt9QcFFunlMExk+6RYS9MFuti8r0a+b9uHeZabK0+zHPr2Hw3r7BdOpWWl46+smidsQ4T2620Jrya3t/l+nHrNcL9en0ONAJWdgzELBCA92KNydoukTe3mxCOAzhfQD3QawS1xOb4RW1V85f/hCixI1ZDrPIxGNH/Fbc/hhdlfB2Uc79+/vx577dOZGjanAi4Hzb2g85Fgnk0lOyHJMvsfWF9PvOD2CZLxcVntx+3Du/dD0hrMBQaMaxDo5hGjtdvxhgBNGLoGaahOTOaMJ4wfyiIWGB4kHEENI1Ew4ELj7gPoRY2WV05FjdZXaiXS/Fl8s2x0TjCPMfn69F9eXzSth37o+6Ua+nxKIfeZh4eYTGjB5tsD3wmp7WlYnMNZItT74E2I4/UdVYP9mNlUX8zHkPV5+VbXIH8Qpkdp6mbm6elaLu8sYFyLgFvOeJq2W+xxHqG/g3jDbZ4fRXWY1t3zdhx2XquDB6PTf2KGfWsXyiLRjMPESlM7hhd3d38tn5vrfbsywX9QoilEXTlUT9L4cZ8K8/IymHu6sW6wVFvHK4ctw7bummpMjsPtq6rv80rrGPz3brRwfz7kuXmlxTMC99vLtZuGyvHXl0d3Tm09255MTmFebadlb/Ule3cf0uWqmfzV9uPba9XRaAcBHiQSjrNDRXYmKKpphFYlQGdSqX+CKMKIWzjvfBW+hHC8Ul8A/sU8n6+pkerylUVAZfyyf4EW0gP5dYppIXiz8E2PGKp9hyAK6OwHsvOPTEGuq2YkDYtNsa4Yv4k7Mcpc61y6CP9BgM3lCQ5k5ILT05KfBohIvh3K9ztw2bBJNgRYAzjf24sI5MCf4pPxSAPHvoAjujtOYjQDHhUgydvmhAKmoSWOo8b6ihzBrRlPOUuCB5pwxUN+jDGiyYmQc03Af2uI9QARnx0kNRfHk3d3E30DXYNsnbwNDmGhjCkoQXUeM3wZGagl6WMS+P47CmH+o1e8eGjs4YZgx/8PDlw4J6o+SLAsAomO/ZpfEEgywbxsSETljbO1rH42nYcz9g5xvp6OpGubO97ukuiViONGhkSuKmQ8bj8qZ3GodtXsTXAvi31GEML+OXB0gpyTEutMepqcSqk1qPM5dYRy4ul1bQpJsfmWXmuruaIclSwa2ng/jw/d2E7G9bg4mBlFiuz7St9LbfPleqvVL6c/mxL5o1iNHbLtdMyRaAWEJicG5O7P7jTHKBSC/qoDksjkHehLV2nWMnbEMLx84hbPoZNgy/i/hdQ6W3FKmre5kCA3iIaQsYYg8eUVz4z3ya3Dj2ekxcTMoEXDQZ6Nhm7yhhXelyLtaccV0ZhPVN2FBv7IJO7+GfBW5wANRzjPH3YKDUKCrYhUFYNHZ1a0JN0Xie+eNOoSOOZP8fdPBmHhxPeT2wAJGMEeZNjoLOjMZ7CXrZ5GI8M0L764qzEsBOAlGTsk+PhuKgHKcJiMITp5aWne+oS+KYhg0wSIy/MgDkgITHEdDPNXcdWQBynTD2oD41npmvgoiZlXWLKMxqvgQqNdG4zV73fyafxs/lV5MV4EhyM8gw2Q577msdEwH4Zy0sd2afBE9jYsfOYbspj/HQAeDMRf4YwFM4j21xBW04O+2Z//AJAHmCOmeUc83KJnkkzv6hkmSBOffkm5ObngnPv1YFxbtcA+iUVH/shr7L54oH+yUlNfZZaY56urAOWBtaFbLfucuvINCryZzVtiohZyLLyXF2nh5OY4/xa4rwNY73wy5tNth3LFnDKvdeWK7PtK30tt8+V6q9Uvpz+ti3rWOYOd96Xa6tlikAtILC1d9AcosI4aE21jcBqZ8izePJjA0kAzQ9NmxUB/qROj5eb+OyGNLh1aNxlUuC65AucyHymd9E9SbCwPWW7Mmxfth7LEvAiG5nYVJeB0UbDg5vy+MFK2eTqpUFqUxxxq2nQxtGjyh393KxFrzPrG6OFQ0I2ab9YbF7MQzmNwgyMa/JI58fixVdSFx42QjmmfxjI3OhHw5x1uaGQfTKxnDGZ1CONcjJmWH2JC58tRuzLeMbRjqfF8dQ+tqesFI6QzuT6o85Uln3RQGciNnbsRuecbI6NifgzPKVwHtnG4Mo5wpya/tgnxwT5LOd4l0uMqaV8N3FDoeW0Zj7H6K0BDxfmsV8a7AYzjNH2nYLnndjYuWddJrs+7PpiHttStlvX1mO5TW65zXOvq2njti+8t/JcXY0OHJvR2cPB/ArhkcEYEbadK8/qvlyZW7+S9+X2uVL9lcqX030tbZeTq2WKgCKgCBQisKoQDgh5HjHQn0Hoxh9TIL4p/a+4vMB7TZsTAXpA+XO/m/jMfJvcOvTa+hEGwURvKY9uYxiBuc81KGzPbFdGrprp1/bDOGDKncfR0/SQZmGI0PvMcAb2SaYE447NNW7uQkgFTp1jWIDZR8DQTqqD+vTw8d6EcfCdQjsUeeQI5qkXjBX1tyA2GYdI5MfCfL/R07RHA9M/2Dd4YEUQB7Kwrg+eal+MHUAU9GP8JvUIoJwhI+yIWFBnyrH37Mvud2AsdAAy+Uz9g9jA5qdekGe+DCCfXluGiDARG5jj5t7oDNlM5LtmIv7RQZ46yAHmE+nq0AsqYo5QRvlMPFWR2Sy3+OdbLb7jxjjK5wEZNoXaEZYCRhGbOEZvDXjymU+dg21ZsHNQJ57k6JUFEZJDbKiA23d+fYCmza4vXM26QnVbN1+PvXip2HqzZbyupo3bvvA+Ly+vK3XwsPZ+2WAb/kKQQkiQTfl2NsdjrWA+U+H8rTSuvJTV3a2kT6HUleqvVF4oz322bd11Vu3xu/3rvSKgCGweBBZ/UpY4bnxg02AOwXB+Eq9v4745mUyu6gCVErvUajWOAA1OxmHSQ5tC3C6vfGa+TW4dhjV07AxLJ15p0MjRECJlFg2ypdpTjiujsJ4pA20bZfLgklawAoQ7YWiRWQse0/67W2Q7KKu2H4ku6OnDiR08stnIhi1HBpKeO5phLMEIhcHIAz0CCEGNIAaaVHo8pKMJxirt0K33t0pkkJ7TedMnx8NxUQ9ShEVwNDg9nwzriN4eMnHU5AkeeKBN2kD3FcHJh0w0cGmMUg/qE4SRzMQjxWlg0kClh7kPNG+k92vbii8BSO0wdrciLwLjlJ430uztea9H78d+aWBSR8NNzPkANnbsaehMeaSpo4eTifhz02HhPLIN23Jy2Df74xHZ9PBzzCznmJdL/LJh5heVuImQ6cAHeyA3Pxece68OWD/sGkK/OzBn7IceffbL/nlkOPVZao15unrGuakL2W7d5daRUa7In9W0KSJmIcvKc3VtB992566wGS/XEt9H27BezJe2XEvbrth7bbmyhY4rfFNunyvVX6l8OfVtW9YhjR2TO+9ejv5VBBQBRWDtCCz/qbeCfBy5Henu7va9+iqCNWskWSoYHgiiB6mUPimVoi9i6AGNOXqC+GFWLLl1WO7WZwyuoWTrChivLOm+mOjBJE0YYz4pe/JyTCZwVHP3Lr+ceXJKum8LS/9hHLpyPCH9h0Jy9VVwBiNtxdHXF38wJXHEL+/9EXAzvxjDEdYZ2fuuDrn22pxMXknJ7sfaZAjHODNGefcPt8vIK2kZuDsg55+agdHrlz3v7MYR1YhNxYa7vjuDcvobOFQChs2B93bJiz84L3u23y6D98IQzHqGL73JHDvZMG6Cu5hGUXNH0IyTOrGcGDCswaWjY5vEFEIdYDySWo/sHC7FHsdNrJh4TwOLV4aSMPSC3mMawOzXUrFZFg4a8azPK/uIjafNUePscznKMsq382jnrZDGzpZTL1vHbcd8m8jC8cL3XpX7Hz4MSzrvuXbXAMdTqBPlWuoxd+xu37YPXq0edtxL6WPrLVXuyrT3q2lj2xa7WnmurqxnMcnCa1+MYtK2K6Y7yyxedj0W67uSecvpU6yflerbchcXzrfN57iZLE7uWliOxq6YLprnIVCpz4HNhGelaexSb7TLgfdtUQq7dVxEcAoXN1ZW0GFVIRy7du3qB5XdX0H2Y/F4vAnhHD/A/U9hM+GVFfrT4gZHgB9i/MBeLhXWsfXJ0mAPmWCsbTqG0/1glDLWll46Ywhgnc+N47ANejEXh9Qu16Upe/kzOK85l17442v2Vl780/z9y5/2NhQuFOLmmT8Eh1iR9Opnca4x0nm5BMMVnmV4S3c+0mU8XtNggOCGOMb0MiyBnlUyXNhEDNr6PU9yG6jWXNaBNA5dgX2OLwsI0cBP+vSgMZ37xjSMYHq0vTyyT7jt3HyXii02njIb6GauJmT0+IyJKWYoBMNZ7vrpvkV6mY7wp3COmM88K6tQD5YvpQvLbKInmr8OnHl83GzudHVmnaVksG+Xemwpujzbj6v/cnXderbtStfVtFlOpivP1dW+L5Za5267QvlTVxJmzovNU2HdSj0vp0+xPlaqz/LC9eaytBSy+PB9YhlZ2NYf8dZssb41TxFQBBSBtSKwKgMaxvP/C4P92UQi8eHm5mY/4i1/E6//BGU+tFaFtP3mRMCwNHx5zBh3jFedGSWVGzymEWzww6lvxoiG2zeDUIxMzfzekZ8rnuZ87dgMToqLguljCuwYOFIaxj6NZyYa09vuazdx0/lW3h09apb5gowkN97AzkSkrfd6R1Ab5gx8geDP+PTAM7E+jxe37dx8UuLRgGCysmmRk7Vjesjz6Ee6/QZrMmEspZcR4PyxsvhdvbA/VltJF9ahjOmTIp07Vi+DcjQtjcBy82TXxdKta6ekcByM6+f7aOs9beaXlBtveDsr+cw1yfXnrv3aGYlqogiUjsCNm9ekf8ILPyu91dI1Ozo6zMmGS9fQktUisCoDGp3diWO2f8rp9LfhhT7hPOutIlAWAvzJPgE+ZsYqLzBnwOgjjZzZEMd7MmGU6XUuS4m1VIZ+acTozl1LwRsNnmewRzRH8/8I0hPNMVqvs9sVf4Kmp5BGKWOXycDAxNhqbhIkywUNBHJR28T6lGfbufmUZ72XVjbbk7WDX0RIj2SYPmBVU8+l9LIy7dXKssYz89k/8+19sTKrC+uwro1NNY3wp1wZtp1eiyOw3Dy5c1G8de3kFo6D7wePpQXrDes5/z7xfpWx66iexlg7aKsmtYJAuLlZRp5Kyqgv/4vpanWbmZuS+z+6W8NBVgvgCu3yn8grVCwoDjz66KOB73znO4YA69ChQyEcruJ9ihZU1EdFoBQEGOMcbgsKaeUETluGGDTlNvFls7kNfVitoGYGt1kpEte5DvQKkPGiDxsCYaCSPcJN9ERzjMUSYzkZysBE43uBPSLHkrHAguE0Zn3Ks+1sEZ9tbCjzFmTDwDcnGJI5A4lMH2R7oJ5L6WUqOn8WZDl5bn8r6cJmlGH5ea2YcmXYdnotjsBK81S8Ve3lFo6Dm2I9lhasYfzbkH+feGvaXUe1NxrVSBEoDYHBvh1Y3t6aLq2F1tooBFY7S08MDw9/ad++fe/jC8bz32MAT2zUILTf+kfAsDR8sNswLNALG4a3tbkLcYzYFMeDN8hMEaKx14WNcmDCoJFdS8kPZ3Mffkr2g8Ju+0NRwzBB/f7tlFoAAEAASURBVOgxY2IMNMdYLPFndcZvcmMiGUnIImIZPZhnWTB4v8BOgfqUZ9u5+e7P9FY2PXZk7WjfHkRYTJPxdJPNgkwYS+lVqKuVVagH85crc+WwXvsdXk6hzqXKcOXp/a0INAqOhePgVz7D0oK1zA2xfI9YFh+uSb4X2EaTIqAIKALrgUBxl9gSPe/cubPz4sWLE9gs+K8QsvHbiPH8HVSlVfA1xEX/uyWaabYiUBIC3GTHeFwybzAUgB6opVg4pq7ETZx0dJsPrBiTi1g4th4Oy40zcFPjQ7XvYESGEY88jQNUdj0Cto3n5wwLx753d8rNs3G8ErL70VYZOYZdiVjJg/e1gIUjCRaOkIy8HJMQjs7e/taoCX+4fjImvfuCcunpKUmCKWP3Y+3y4tPn5MDeXdJ/EAYwNjxSZ36IczMTx8LwCHp4VzJSWZ/xm/zZmjKY7L01Ctxym1fYzua7gLt1yGhAdgYar62kz1vCqHfbu/euLDtWW75cma3Da3MfGEze0iPZhMfh7OpcqgxXnt7fikCj4FhsHPMP5Jl+OPLC98mtaGiOIqAIKAKVR6AsAxq0cP8IFR6E8fwpGNGfxP3vVl4llVhvCHCzz0ofYsXqMC82ho1tMG47wZM8dzOLGOGAxCficuGpObntoYhcfm5Wpm8kZNtBnzzz+Zv85VYOvN8nz38WEUM4tbrpMdjJ384h9nZcnxeJvldk6iu4hzOq9ydFbvwt7rEjPyWjcgK/lSRBtDEfvCZnn0QcJfbrhaIhOf7FpPjg2fY1tcpZrPJwa1iGX+OR3vCY9s/L5BDDKzwKrQRiib1DPOAJm8GR4deThkquKXf0qh0rjVWGTdBAdKnZ+Gzp6mjEMllD28ZvUgYTr5aOzBrWNt9ibp9Zj+1dg5RlTMyzsps7fdLs0UV7hWX+dWXZsVpj2i2zYt2xc06YitXzShaXFcq3dWrhWo5u5dSt1NiWw7hSfayHnMJxFD7bdb0eumgfioAioAhYBMoyoNGoDyEb/xbXn4ARPWKF2CuM6t+393rdHAgsRTvmjr5YHZY/+8eXZeT5GbOJjBsHSTtFg9SmZ+0Nrq8598+/kQ+3XzCeWU4yRSRjPPMGNqgxnnkPWuhjn+KNl178I3sHmrp/nztxAVnffcWj+Bh+Nk/1cenr+ft8K5Hn/sijv7skV+QpvHoONcuud3SxW9Ds4djwqylz4EcKYRnT4JDmRj7+1NwUmJfZ4bS3oQ9GNunqQnhZurv2gbBhFCDt3NjZGFhIPGPahxjr7r0RbCzEJkD0wXakvItNprB5kTssRXr2R2TPe7oX6LxcfSt9X2xe6TF0E6kJXTq/fe+D5e6x97nVit6XIr9ow3XILEe3cuqug+rahSKgCCgCikAFECjXgP5F9PnTePFTcl8F+lcRdYwAvWorUZcVrXMUfMbptIzg8BJ6k8i0QePSNZ7rEZabJ+LSunVaEM5kxoNRydRwwhjPHE/79hB4jhMyw0NPtodx7DYOhLmUMCEbPFGQibRyHi1Xk8wMpwzVnGEhQRlp8aZaEog0QYgH8Oq/u1Wuo88pyOzAQTLMnLgI/l/gW206r6LzWkAjZqgJQTvGtEDn9w9jEv2AyVr2TynylxVQxcJydCunbhVVVtGKgCKgCCgCFUagLAMaHuZvov9vHjhw4DRo7P6wwrqouDpDgCEEpdKoufRmpE6bGY2DSo2WM4xBeE49H2udAVCoLgYRu56Vpm54yGHgBpv9kpoBRgmEfGBzYRZh2dkEeKxBWMOjuZnmQStHer408oP4WkpsYmMpw46RipN2DrR+gImpyY9QGcjzwYPtw3HiDNkg/tx0SXnMo2zK4NxU86ftUuaeYSn2IBlvBIxXhc7T9mnpaynyl25d3ZJydCunbnW1VumKgCJQDwiMXr+KDwp8gFQgkcauf6I0M0/5ossHvDRkc3IRtvFzvIVHbMTeu13CwP4L91nvGxsBxr2uRF1WrA6p0/yRZhiEiNflvxN4mfCGeocL44hsASZBbCTM/fsXbMNz2KMM8cFJ7AOvM+m3aOzyW0MTaOW4kY98z0zEJtJNDzZCO2CAk85v3ucZ2yYP8qwHmgYy8Sf1nZGH9pRNGW68tBFc4T/F5rWQRoybJ63n2XbP54B3sKLNKnotRX7RhuuQWY5u5dRdB9W1C0VAEahxBNLzOIHX+yd/zZqG8TlbCqe08kWvDuqyDGh08bO5bnpwvQOv78CYTuGD/YdxfRnPakDnANoMF4ZfkDqKYRz0hNKAKqSSKloHR14zjbw4Y2KgfbAvGQMdaKvvMI6eg83Stx9sHBibjYGObguDmi9owjgyoN5q7Q1J29bgQgx0FJsnvVhmeKBbsEEStHI2BrptWxCMIYiVdmKgKc/GQPNgia5dzdKMUwW9GOh5EwM9CHyJezVT0XktoBHjFwPSjrkx0Pvf3y3XAtj9uUIqRf4KIqpWXI5u5dStmsIqWBFQBOoGAeWBrpupkrIMaHiY382hYSPhl3H5mTNnzrzBZ4R07MLlP/Ne0+ZCoBjNVCECS9X50T/cW5SFY+LSHKjkKs/Ccc+vyAILx/2/KgssHId/Ms/Ccc8HPRaOQz8ZlgvPeCwc9/1MzwILR8/ekJz55oRh4dj5SLscfeKc7BwclJ0Pd8FozXt++dM9WTjIV0svJGNhLdMGjaqlWDgsrZylrKMMymKiHCuPz8xnHpNl6qBXmvLXIy01r27flprQjn0eNCrXjrk1lr4vRf7SratbUo5u5dStrtYqXRFQBBQBRaBSCJRlQNtO4XHeCWPaGM/MQzz0BYR0bLflet1cCNBgs/G2NBStYWeNxkiXH9R0KRm/GJdQS1KOfn5UwlGf3PmeqLz8t2Pw1s7jvllOf3VebntnQl78ywxCF0TGp7C2PuNh+Rop6nKHxT9/AQYlaJuZFrFw8DeQFFg4TpsiEyJxA7R2JoGFYwS8MUnIFMQUT8AJOnke97lwAnqNw2CHCIR5uh/imDGmJny/jPR6v6WNX5zDwS5+wyvdf6hNEpOkjAtJ536RHYe7zD37sWO3eITgVWeiPFLWeeVNoJELLqKSKzzi28WUWNlk5fGZxrPtLwy+6nKTO1fsbzXJ1dNt78rmlwI7vgzj3stIS8kvQ0TVqpajWyl1XcxYX5MioAgoAopA7SJQ/qeuN5ZpeKF/NRaL/XkW5yy3t7f/MkI41n5we+3ipJqVgIBL1zVzFewQQ0lzst7NM7OSnMZmOBi3brr4DzkrGJnXj3pUcVdf8GrQzLLGs8nJUdSZ+3wzr7L9CyPZpJM2A9dL+fvRv8nfn/t87h4GtaWxowbfen7SFLz5nVw5Lif/Kr/r7Zk/GM0X4C7QDUP8nstg3whKpIOn/HlxyQxloefRJhcbG+riltt6pV7XKm+t7ZfTs5qyl+u3nssUs3qePdVdEVAENiMCeddWGaP3+XyfgBf6Ey0tLbNtbW3TMJ4/zLwyRGjVBkOA3jNLacdDRkYRghEDC0NsIimJ8VuN50YZfhosbeDBkGsY7/iFuIlP5gZCYkFMmFxsyEZSWF4uFmuVt9b2y+lbTdnL9VvPZYpZPc+e6q4IKAKbFYFVGdAnT55EBMfpB8PhcA9evbh/GHkXNyuIOm4vdIEbCZkYj0tqtQw2v6VmYER6dmTDwhS76Y3XUspxoLxneAUTrxYbk4E/brnNK/W6Vnlrbb+cntWUvVy/9VymmNXz7KnuioAisFkRWFUIx969e7fD4/zr8Xh8C65N2ERo8EMstHqhN+lKYjwuQxOYGP9LajWmYBvcsQznbGAjOtLjl1jaYyGx43Yp3VxsDCj445bbvFKva5W31vbL6VlN2cv1W89lilk9z57qrggoApsVgVUZ0DCa/xqAMRj0ZcRAN7BptFmXRfnj5qYnS2lHerX+u1tyMdA+metKFY2BLr+X2mvBGGgwMUvf3c0mBjqNY7ttjLPdCOZiQ89zYXm5o1qrvLW2X07faspert96LlPM6nn2VHdFoLIIrOYgleZmnKuwho3H5IEW6a3sQDaBtFUZ0MClB2EbP7QJ8NEhloFAIV0XYztJX7ZaFo7d73M2EpKFw24k5N68YhsJI8jnRsI78LIbCW/HfW4jYf9H8a3vCTyj7Z6fETn3RdyDheNtPxeSV7+YlJYukcM/3iFnv5GVO34sJBeeTom/hQwhXXLx+x4Lx+4f7pJxHL9NFo6B+1vl+PE35PDhHTCeQeGBxJ/j6VEs/MesEJvCctO4jD9rlbfW9supWk3Zy/Vbz2WKWT3PnuquCFQOgXIPUpmdm5Z73rNTOjs716BEr/AkQk3lIbBaA/o8wjiiZ8+e5dcWTYrALQhkkhmZvJww3tb5rE+Ssxmzma5ta5vsf2darp+MgcatWXbc22m4jbfc2S7pZFr6D/lk4h3jArpg6evLyJktc6C8Exk8CN5mGtCIDNnxYZHLf5nr8h24fte77/sxUN/9I4zjR2Ezw0hOgvXjwY+FYBDjwJEDQbnzR7rljcyUtCDk4sA/6ZHb9yVxch885w9EZdcjGaPTADznW+/laX5N0j6YBKuGT9q3hqX3jl5jHPMY7dZenwzcDYMZVHt+GO3WGOaV4Sv84sA48EJD2pbnNF/ThX0UM9Zt3xROXaxuxTqrhD5L6VEJ2cV0buS8WsNsqblt5DnQsSkCG41AuQepTM5MGOO5qwseIE3risBqDegxv99/HNzPNF0seZjAK/3L66q9dlZTCFgqruGXpmQYLBSpOI1msFSQky6NV0Gwz4m/zp9I9/Knb94yllO5nNh1GM/ncg+Qt2A8MytnPPP22hf4F87nT3tX/rUUdddfSMnp/za3UHDsM+ML94U3QXils9CXwUkBcBi3DwbhbW43rCLXXp2TpqBIM47L3vnOdrkBMadP3oSxHDAhLJRVeDIjvYuVTBZnNxyEfTD/7BNjMnYGb0no3rM/Inve072ITm899KhkHyprYxBYao1tjDbaqyKgCCgCtYfAag3os6CuO1t7w1GNNgoBeqtoOGYzWRk9NmO8o9QlS+5nGtB1lFKgfW6Cd5ne7iY4mqfeTOJ+WuJjOODFh1MFc3zWb3xxTDoeg5Gdo6YbOjqF/ZL4D+1IV8dETHiq4HKeYFOxxD8WZ1LhuX20D4SE/U9eTMCr7vU9gfsrRyvbv1VzKT0qOVbbl17XFwGd2/XFW3tTBBSB+kRgVQY0PM2/W5/DVa2rhYCl4krOpEFhB/cn/8cLJMl1mazungd9XhITWckiLMUHphF8eYSHeh4hJ6Cvy5+xguO5M4bjubkj/7aydHX2ZMK1gmFxtsYz5bEPxpqz/0wqu2BA8z4xnTZfZirVv9V/KT2YX+m+bJ96XR8EdG7XB2ftRRFQBOobgfwnfQnjQMjGl2A8/ziuZ2BE0DxalM6cObN/UYY+bBoELBWXLxgAhV0TjDZ4b+ElpRe33jzQnDSrO73JPn+ThDt98EDTLc2yJvEFcNB3CHR97flvCOEoYo4NZ5+pZv6sha4uLyV/Z3HO53iUeC09AcSKQ5+c95nlvA8j1IRtKp2W0qMafVVad5W3PAI6t8vjo6WKgCKgCBCBsj5Z8fP177ERqOt+EfbzL/GFR3PPK8s0bU4EGKJAGjuf3yf997R5RhuNT8QLC180puskMQbah9ANbhKkBzp6W0gG7m2XrRgXE2Ogme78cLf4UScdyxpv+/YjURk80m7uU7k8YlKp8A32aXHm11e3Dx9itdl/x86w8ULzIJtO3FOfSvZPHZiW0qMafXk96t/1QkDndr2Q1n4UAUWgnhEoywON0wZf5GCxgXALjOf/iNt+vOCQM/46eqRpdmjapAhYKq692LhGtgrLwtG6JSjTIwmZGU1Kz96wXH5mwjBeHHhfVIZenDMsHLt/uF1GXvFYOF7/hxwLx4GMPP3pHAvHY9hI+DkAC6N8ByjoFjYSvgN53/UA7/tIjoXjp8DC8fUcCwco6haxcDyeZ+G4firPwkGWEDKDkIUjnfBYOKau5Fk4aFTwp22Oa3okhbhmLHUYzy+/NCr79/dgU2FwwVBlHDDr0pNXDYPS4lzYB/Pv+8SAYQAhIiuxcHiorf7vUnqsXqK2rBUEdG5rZSZUj82GQCEP9Eocz8rhvHErpCwD2qoJ4/kP8PoXMKRfgu18SyiHrafXzYUANx8lphBzC+8ruZ8ZvsD4XOYnp5Ny5cUphD2E5PKr2GyHjYXTw9Ny5pvj4msV6RxMyZvfz0q4FQevjKaka1dYOra3yeDd+JZ2V1j2vWuL3L4/IW19QWnd4pfzW6eNsRsdbIbcadPvjiNtMvmujHTvDsmuu+YQF5yR297eLjsf9pkNdzRo7+vxuC7b+kMS3e4ZxcwPtYWkrZ9E0vnUsy/nas5l2djerl3e2yaTQcwzDPpCQ5VGs62bl1bZu6X6YH44uqq39aoUXEqPVQnTRjWFgM5tTU2HKrNJEHB5oEvjeFYO541aGqv9pJ1CvPPfb5TS2m/tIUDaq9e/MCojL81i41rKHDTCjXYMNcgm8vq++v/l7899eXbh4dtgkGAa+r6XNfSduBz/s0nzcPmbc/LCp5amnfNaLP3XB7u4tSeEzY3YCAidGNPcMhCEYd4KjufmhZMB6XXTpAgoAoqAIqAIbBQCLg+0cjxv1CyU1i/8Z6tKrx04cODhVbXURg2HAD3MQ89Oyegr4EjGikqCDSI1N49YXBjPYIDb6JQFLfLsWFJiY2mZh+eb8cJTF5Ny9eUZ8YcZg+TRzXEcmhQBRUARUAQUAUVAEVgJgbI80A77RitCOD6G58u45lhxRZSFYyW4G7OcsbixsZTx8HKzYCYDQ9Taova6wUPnwSgMNpqHbjSU58FXnY7zxMCsNEe9UBOOo9qhFxsMg3avCCgCioAioAgoAhVAoCwDmuwb7BNGcwW6VhGNggBjiCPdQdDXeRzJfoRIZGitknmDrxpYLj6sdDJqNEE3xnY2gS0k0MxYZe9HmErTzTXK3Oo4FAFFQBFQBBQBReBWBMoyoM+ePfvUrSI0Z7MjQIN0+0NRmXwzZmKgQ+AjnkesRLEY6I3AysRAd+djoLPprER3hkwMdAbx2U0Ifa403dxGjFP7VAQUAUVAEVAEFIH1QaAsA3p9VNJe6gUBhkIw7IHUbjSW7/35Pmkd5EbCuNz5/oi88dUZmbwRl4EjIic/nRvVIK5XioywG3ljeL0Fr1fxAkXcvk8gLOgLIl37RI787BY5+cScdOwIyu4fisrZJ2dk610t0rMvIie+dEMy2awcfH+PTEJ2L9gzhnCEdmwyI/vf04VYbAhDIjPIxKW4YQbpPdCCkBOPS5n5sfGMxCdShsGCXwjWkiwu1aKxW4tu2lYRUAQUAUVAEVAE1o6AGtBrx3BTSiDrxhUYqcOgprv26pzEppKSyZNqyJtP5h8mX3YgKmY8s5jGMxONZyZs9jvzWe92/AWRr79w3XvA31c+M2H4oI/70AixzTa9/t8mpeeOZklNZ0Gbh2O3Ea5x4VtTMLRbJRD2y+jrsxK7nvJCkBDO0YzT+7iDMHYzZSJNAhG/DNzXKoc+0g9DfXWMHBYX0vcxLISe7dXKsuPSqyKgCCgCioAioAjUFgJqQNfWfNSFNvSw0njmRjwaz1nwIbvG87oMAgaw8OUmGNM3X48jrplxzj7xhT22jfnkvHTcFpbpy5YSBJsHZ7GJEPkM0E7H5j2eaPBRk0mk47YpHJQSNrHSrviV7i0uZPUIRrzYauK0Glkr9aXlioAioAgoAo2HgHuQCg9J6Z+obzOto6NDcIp1400URlTfM9OQU1L7g2LYBj2sKZzel0nhoBSybtRKgipk3OAR4jRoaeTzYJf4BGKycW92NRpyaoSdJDOGp5qbC7OsyyvqkFFkNYwcFhdrPBMSg5Oye9TK6lA9FAFFQBGoaQTcg1TCkWYZeSopo74bNa3zUsrxC8D9H90tXV1dS1Wp63w1oOt6+jZGecb2MjzBDyPVH/RJ1ldDBjS8v2TcoBfYsm3QoG3u9COkw/kWjDhnH1hD6IGmoe0jMwceWYeMIhxjucni4rZTdg8XDb1XBBQBRUARWA4B9yCV5epp2cYjUL6VsPE6qwYbjAANU8NaAWOz7y0tMDr94kf4w7omrtzCr3947jnULM0wgJuwb9CybQzc14YwimZp3xEy1HX+cJNEYFC34TTCtm1hCeOeefRA99/dYhhFVrOR0OJCBze93rwqu8e6rgrtTBFQBBQBRUARWBcECk2QdelUO6l/BLgxjrG9e9/TbVg4pkdSYLlokovfuSFDr8Tkzve2yOl/nJGp8YT0HU7J8T/JjfkBXLEp0KQd+Hs5dw+mDnkJBvAHEMf8dZHQFpG3fbxNzn0vI737w7LvXd1y8elZY/je/nCnzN30Nuk1d/jk6quz2CTYJH2H2mAEwzMewsmD2CzI1NYfMp5ohleQ9zk5g1MSYdy2YAMhD1JhYv7czbSJWw5HA2XHPhshuT8WF/anLBwuMnqvCCgCioAioAg0DgJqQDfOXK7LSBjuYI3DdDwt109i0912v9w8mxC/f0qe/twYwiFEYq1TMvI/PZVGv+OoZo1nZlnjmfdH+QfG89951yRIPJ76qxmRcyJD34pJbH5CTqNsHqEZ90wMy+ugtyPV3SO/2iEXn0d8cyoNT3i3DL+cld2PtYAdZFbGzidk/3vbQHk3JeOXE3Lfx7rl6gnUg347QYU39HwM4RoB2Xq4RUaOzUomkZHtD7bJzXNp5EVgaDd5mwsRzkGaOxrdPAZ8pURP9EadaOjOz2q86CuNTcvrDwFdE/U3Z6qxIqAI1D4CakDX/hzVjIYuRdvlH0zI6PFZSc/eGv8MBjoZ+R8VUBvGs02nPmPvRI59Kn//rf9zcuHh4uPD5v7FP13Ikje+AMq7XBp+asTeynP/T54WbyGz4CbY3iTNXUHB+YrSujUMAzok+z/QDSO7o6BmbTy686MUerUxJxutha6JjZ4B7V8RUAQaFYGV3WmNOnIdV1kI0ItFSjZuzvP55+UqPLYeDVxZYuqqcmp6XhI4XCU2AV7pmbThjz79lTETW11rA3Hnh5smOU+GahDzpmlzIqBrYnPOu45aEVAE1gcB9UCvD85134tL0TY9nDS0b7fwMNf9KG8dQAah1PzCkEmArQP0eOlUxsRLM7a6lpI7P1YvpdCzSGzOq66JzTnvOur6RsDlga7vkYgU47FuJF5oNaDrfYWuk/4uRVv7tpChfcuQZoLxGg2cSNVH7miydDTh3RIM+k0sdK0N2Z0fq5tS6FkkNudV18TmnHcddX0j4PJA1/dIRAp5rBuNF1oN6Hpfoeukv6VoY1hANtMkW+9p9WKgU40bIsAY6HCnFwMdagM7B+IiGANdykbCdZqWhW7c+XGPEdeNhAsQbbobXRObbsp1wA2AgPJA188kqgFdP3O14Zq6FG2Hf7oPNHBpuXbCY+G4etxj4fjWf/RYOHrfUYGNhHsw5NxGwgO/InkWjp+Roiwch3989SwcV8DaUSkWjo2aKHd+lEJvo2ahtvrVNVFb86HaKAKKQOMgoAZ048xlVUbCjUjkTmYiNZt5xhHe2XRKzn/7htwAfd3uR8Jy5fmk9N4Rk0wMUR1zInN4rTmVwsLxdbBwfM/raa51WOZ+0CQzOFr81F8iDzHL/r4JOft9xDHjcXJoUt58MSE8OLFze1aGX4lLS19AevfhgBVsvMsmyRWNZ/BO+0NNMnUlJuOTaem/i6fEYFceEg9nIWc0Ke2YxcNXiE9zOzbugb5uoxN12CgKvWqPnWvPUiiWivVq2hQbR6XkFJNd7bxGXhPVxk7lKwKKgCKwFAJqQC+FjOYLKbDOPTEmN0/DKoZtGIg0SWIyI9dPzUhsFJZjLp38a+/mlM3AdfLLzkM1b3PGM7u4Rm5oUM65lHev/Sfmeel7v5e36q8+fdNmy4k/z1PhgbtCmlogheeweGexmHptg0Fpx8ExEC+hFj8OSfHLtgdb5AaM/NMnb+I5YE4dpMdPU+URWA0d22raFNO8UnKKydY8RUARUAQUgfpEQGns6nPeqq41PW5Xjk7LxEWEZoR8YKJokpEXZmV6NL7IeK66IhvQwTztbMd4pgozOGlx4uKcTA8lxY+TC+exgfLEF28aDzS910obV72JMmsxR6FYKkXfatoUG0Gl5BSTrXmKgCKgCCgC9YuAGtD1O3dV1Zw/lSem05JJeZ7mDMIbsqBwS07lPc9VVaDWhGPYhsoO4SHZBBzRpLSLIZQlnlfU0sblc/SuEghYOjZX1kpYr6aNK9/eV0qOladXRUARUAQUgcZAQA3oxpjHio+Cm9DC7QHxB70lYrzQoHALRTfpksGwDZUdPPE+RHKQ0i4Q8YvPidhQ2riKL0MjcDV0bKtpU0z7SskpJlvzFAFFQBFQBOoXgZqJgd6/f/+/xM/iPw+qMFzmnx8cHPyV0dHROzKZzGcBL89Ofm1ubu7jQ0NDCMjVVG0EuPFo8Ei7xHESn42BHnig1cRAxyfSDR3GUTQGeiAfA52JzyPm2ScHP9wjF88NwROdNc+DD7bXxEbCaq+N9ZZv1iKwJYViqRR9q2lTbFyVklNMtuYpAoqAIlCIQCMdpNLc3LzoM5E80CK9hUOu2+eaMKBhPL8VCH48lUq99eLFi3E8//nIyMivw5D+OPI/efr06e8j73dbWlp+B8+/Vbdo15ni3BB37ycGbmHhIAtFIJxdxMJx7lseC8fT/xkxDYgh7njvOm0kfASg5jYS9n0EXYOFY/B9eRaOu35Z5Mw/eCwcD/xsi5z6tsfC8Zaf6JTT3/RYOA7/+Ba5eT4lSTBu3P5IB8JW/PC+N8n4hZjEcywcqVjTwgEqloVjvmleZl4akv37e8DCEVz0D0WdTXXNq7saOrbVtCkGRKXkFJOteYqAIqAIuAg0ykEqs3PTcs97dkpnZ6czvF7hSYSNkmrCgIaXedzv9/86jeccsK/i+ha8ojSemYc6n0Od7+BWDWgCsk6JHrhwNL9MMkkcZX0jKZ23h0D31iqzN+aN4ZjBgSqYI2w2hGL9Iq1gflvgtngQec/lFOaXzxu5+0pcJvJCurpAKRcJSHd3k3TemZTMNE8ORDl+s2jZi8W0LSpd22LS2u+Xjts6pO/OoHTtDEtzZ7O09/sk3YFDUwI+GM2gpcN965aQJGdvjfnmxjJS1wVacTohQjtIG0eciiXWZRxtABsP0znP9VJ1i7XXvDwCxK1cir7VtMn3mL+rlJy8RL1TBBQBReBWBBrlIJXJmQljPHfxg7lBU94y2sABnjt37iy650v27NnTh8uv4/Vf8ILZ4yXUGYYXetA+63X9ETj258OGeSI+k5Q0jFObXs7dnP1K7gYMccP/3Zbiao1nZlXSeKa84/zjJY++LiXP/HubI/Lyae8+MSry+NNXFwpe+pOxhftFN7CDQ9EmeKHxhQCbBZloGrduDUj7tmZJJ7Lgus5KE2Kh++9tkaZDpkrRP5b+bOZqwrB4tG0NSttAWOnuiqKlmYqAIqAIKAKKQP0gUBMGtIXrjjvu2JnNZvGDu3wG3szv+Xy+99uy3PVWd2BBBftIbyhfmkpDwGJlr4WteOrgiS/cAA3yPGJ+C0sb6Bk8z8lJ/LGJ1jO8zDMjYCTBwMm60T4YMrR1o6/MCqixJf0YKDkKEj3PQ0cnQXcnMj3sWeLTIwlp6Q+YfBrkm9ETbdeXvRbApo9FELBY2WuRKppVgIDFyl4LivVxCQQsXva6RDXNdhCoNFawgQTRgXWfOA5iU2l8agmYmjGg9+3bd0/OeP59hG38KTzROwDUNgvW3r17BxATPWSfV7qeOHFipSpaXgSB48cdl65TPnMBkRCzsCW5Ym61F52aDXaLf8h42iAPUElM4wsZrrPTMcPCkQVXdBB7Il554TXxRxaPmycy8pAVuq9nrnu4ZYFb4rwXczJ7dOiWNoslNPbTUuussUe9ttEpZuXjp5iVjxlbKG6rw60Sra5cGZb5BvD9TWPDYOL4sESj0UrAUpMyasKAhnG8BewbXwNCvwbj+UtECiEblxGyMYvXI8ijN/oTMKAfLxXFgwcPSigUKrX6pq/Hb4n8R/Pw4cOCWPNb8EjfkZYrf3bKeKBTAViCm8WIhgHMOGd6ksPtfuOBbm33PNBZZAaicbn7gbskEFz8VqIH+tRVHLSCdqOTMwt49u9uhfe6SQ4c6dm0Hujl1tkCUHqzgMBK782FinqzgIBitgBFWTeKW1lwmcrErJJpcHAbPND40KnzxBjo/Yd7RGOgqzyRMNh+A8ZxO7r5NzCY/y9c52FkPI6F+dMo+xzy+BXmAozoj5WqCo3AYoZgqe03a72lcPO3+uXgR3pNDHQA3lY3BrqhsILBXBgDzfG1DRSLgYYxfDBujOdb1hq+g2w/0mGo19q3hRdioH3YZUm6u0KDu6EwLGEwS62zEppu2iqKWflTr5iVjxlbKG6rw60SrWDnNIQBzXE0+jpa7DarxOyvQsapU6d+G834KpbeXixT89YfgXs+vk3u+mifjJ2LGxaOiUuzcukHM7Ltbp+c+lpceg/OynOfRVxDi8jWR5yNhNVk4TgMHHJRJwd+Bd7ebwXlzn/WJG/8o8fCsfd9IiewobFtr8hD/8tWOfttj4Vjzzs65dIzc4aFY+vhdpm6go2R8ax072mWuZtZaQfvc2IqLeMghtlyR0RcGrvZ6ynhkdJk4XjlVeyYXCK59GfKwrEESJqtCCgCioAisIBAJXigC/mXF4Sv402jcT4Xg64mDOhiimlebSLgD/lhPEcQfsCjvuclujUMijbEKSAxNMGPqJmu3SL7D7TL+K5pnNYncuidQXn5agqeXdy/PyjPfhpGNkKBox8Qmcoxd7Rhu+jMkyKRRxFrzWAepMCPwNP9Te++FYbwLO79iIo//EGRY38GO/02kYd/rlve+FpMwp1NcugdW6R/YB70dH5sBJyVjsGgbDkYkfm5cWnpwkEo29ql/86AhNp90tLbIjt/KIyDYtLQ2S+9B9oM3RwPSAmDhcP03xyQ1r5myaazMKDTJo80d+1g0mAq5ac7l/4s1Gaa6R9FQBFQBBQBRaAoAmvlgS7Ov1y0qypnNhbnczGw1IAuhormFUXA0rJd/O64DD0NHjvPbl6oa2nsro2IXHsK5bn07AkYzEjkonj2Ne+ez9Z45v0MuVeQrPHMe2s88342F/2euQDj+VPMwaEp8Dx/41+NeQ/4e+7vLy3cF7v5geRp7Ew57GRuigzAaB64v00G7oniy4BvEc3c0HOTcvorYzCuMzht0C/7P9At2x9sHCL4YjhpniKgCCgCisDGILBWHujNwL+8MTNza6/1H6l+65g0pwoIcFMcj1LOpjNy9eVbjecqdFl9kfgCwA2CaRx0MvL8DJg1cCgMjGqOk+Ol55nGMxONZyY+M1+TIqAIKAKKgCKgCGxeBNSA3rxzX9bIeZoeY4TnrqclnXcilyWjFiuTJYOvTAZju+YNjOPkeHlkNz3PbuIz8zUpAoqAIqAIKAKKwOZFQEM4Nu/clzVyxgYzvKFlSwAMEvDaJstqXrOV6XEmV7Pfj7H18dxvhHRgnN54mxY8z6YAf+iJbunRt43FQ6+KgCKgCCgCisBmREA90Jtx1lcxZm6GI/2aL+CXrfeCcZCGZ70njIGHpJgY6Le2yXy6yXijOU6OlxsGGfPMZD3RfGa+JkVAEVAEFAFFQBHYvAioK23zzn3JI2c8MEMa2gdCsvPRqPTsb5aHPtkr3/0vF2TuTXhl7xYZ/58QtwUvnLpn0gP4+4J367Jt7Pp5EHr/BfIZGUGCwh94deStuL6EF6/P5vIcGfLDyHsKry6ROz4qchIy/Ojv4Y+3goUjIWHYuff/1Fa5fkpk4O6AXPze3AILx8mvjUm4LSC7HonKyLG4YeEYvD8qsfGMYeHoPdBijGKGZtC77BrI3DC47b52E7ZRWJbTUi+KgCKgCCgCioAisMkQUAN6k014ucO1zBszIwm58uK0zA4nYEzC+kXc8EI6n7uzxjMfc8Yzb122jQt/xpxcssYzH5/P5VnjmY+ODGM8M28cxvOneQMb/JLId39vFgYv2DSCTfLkq1dl+9s7xOdrlb0/ukXIw0z923vbTPz2leeT8KJ3mHy2D0fx53YxdbhxkLHPhSwcrEeDuq0f/HyaFAFFQBFQBBQBRUARAAJqQOsyWBIBy7xBa3kahvPUpYRks4h5cI3nJVuvUwF0yWJPXxNIMmJjGbn2+gw85BHvBEB4zGkYM86ZB58w8Tk6GF44RtuOcbk66zQS7UYRUAQUAUVgkyOw1oNUeIBJ/0TlTbuODjqnvM/RTT5FC8OvPMoLovWm3hGwzBukektMZSSbmZdMqpas5xzCVAlhJrxkEGqSnMmKH/sBGZJBr7I1nlnbMmyE2jxaOjvG5eqwnSZFQBFQBBQBRaDaCKz1IJVwpFlGnkrKqO9GxVSlUX7/R3dLVxdiKDUtIKAG9AIUelOIgGXeoMs5HPWLzw9XLly12USNGdFQS7Dprwlq+cEWEmrzQU2waiCemSEZbrIMGzYvP0abk2fhyOfonSKgCCgCioAiUH0E1nqQSvU11B4sAoutC5urV0UACFjmDVJutG8LS/T2sATDWDI0WGslQRfGQNNLHun2S9+hNmM8e4wh3qmC5HlOxbKLGDas+naMy9WxdfWqCCgCioAioAgoAooAEVAPtK6DZRHgRjzGDDPU4YFf3SaJ6TRijdMIi8jIy39zRaYuZiR6V9ywYvgeQiTFtzxx2z4mMvwN3CM++Yf+eUQuv5KVxM2sHPmlfpkemZeb5+Ky551tcuab4zJ+KSn3/2yvxCZDYM4QOfW1CWnpDchtR9rl7Lcn4VlukgP/tBshGVmJT2ak72AEMlImHKN7T7PMjKaNp5kb/TLgp6ZXmYYxk6u/m28Kc39KqePW13tFQBFQBBQBRUAR2NwIqAG9ued/xdFzk118IgXKtzRCOJLy1T84JzNkzAAVtOBEb6bh73tXazybvP/u5fHv8eMxmXkOHuI+8imnZPzNjDGQI90R2flwUPa+yweKvKCkzyaktS8i9/4shdOzPC87HvDD+x0yMc2zp2Zlyx0RhJOEpbmz2dThsdrhaNMC/Zy/gCyD+idnFp8maBoW/KHBbeOiC4r0URFQBBQBRUARUAQUgUUIqAG9CA59cBEgBdyLnx+Rq8/PyMzVgqMHc8azW3+p+8kveyUzoyJf/ef4k0vP/GH+3mRhX58fr5b+gPjDfpkB84fZGMiuc6dnk22j93BE3vl/74YXOiGnvzJmDjnhCYE85IS8zTZR/7NPjMnYmZhhDiE7x573dC/Q2Nl6elUEFAFFQBFQBBQBRaAcBDQGuhy0NlFdem6Hnp2Uqy/MSDqTWp+Rw1FMlrzp4bRMXEyYcAxz4ErOeDZKIDLjBjzaF757Q05/ecxk0XhmojFNjzST0f/olExCjj/oE3/IZ2ReOTptykwl/aMIKAKKgCKgCCgCisAqEFAP9CpA2wxNGPM8M5KUbCoLD+/6sW5wM594NjDc0Z5BXYg361x/LS5p6BhuB19dLvG4bVLXMRaa+pN6LwP9aUAz8Z4x3CzTcI0caHpRBBQBRUARqBkE1soDXcmBNDc3m/1EpLHDb7+VFN0QstSAbohprPwguOGuDQeR+GB8BlubwK+8PkY0DzSZp73r7QEEcbt36rc7QtbZclezjJ1Y7BmnJ5rUdUzUn9R71nhmHu/D7QFTxmdNioAioAgoAopALSGwVh7oSo1ldm5a7nnPTuns7ITIXuFBKpoWI6AG9GI89CmHADfVbX+oQ0ZfnzMx0CIFMdDVQAoeZxrMhTHQhivGhnHAjmcM9K539ErvvltjoHnsNpPR/0gUGyDTi2KgB8HsYRk6qjEElakIKAKKgCKgCKwWgVrhgZ6cmTDGsx6esvRMqgG9NDabvoT0bo/9m50rsnCsBFTHB0VmnvVYON7xq/0ycjwjzR1+2f1ol0xd8SjoyMJxEywcZNmYz3pGMFk4xkB3Z1k4hl/2WDhat3g/K1G/bfe1m7ANep6t8Wz1Yfl9nxhYYOFg2IYazxYdvSoCioAioAgoAorAahFQA3q1yG2SdvGJuLz0V0Ny43RcJqJJSZDCjmklFg6GS/Ek0YjIXQi3uJoNSDyRNPRzWw/7TZwyqej8IcRY45CTQLMf7Bjc7Oc3Bi9p89rAxsGwDBq9LN9yR9tCiEZiynNJM1Qj1LrYMHap6yz3s71SdU2KgCKgCCgCioAioAisBQE1oNeCXoO3/dIvnJBrx0ABt5pE45kJzZ/+d3HvHn///h8vefcI1/DDuG7pChlWjGwyK81dQWM8p+bSYNMAc118HnR2OO0HscsBGMk80IVHcYfgvc7E5g19nS/QJN17IojXDgtPH2Sy1HWp2QxiuFG+F+VbvXJ6pTUpAoqAIqAIKAKKgCKwFgTUgF4Leg3cNjYWW73xXAouoKzLzIjEEVvtI/kz0gx4ndOJeeNxzqQQ7Iz/MwmPPYP54Y6AYdEYO5OVvrtbJIFTCU27lpTZ8EiKuux81lDX0bAmC8dCeX9Yrjw3bYxwDeMwsOgfRUARUAQUAUVAEVglAmpArxK4Rm927knS1lQ/ZUwkRlaamnygmZsXQ2OXgeWco7LjcxNtafBSp+FRbvI3gVovg/usZFkPKRUHXV0S5bimE1lDV9cEGo952M+QmCvPGtlKYVf9OdUeFAFFQBFQBBSBRkfA263V6KPU8ZWNwJ53Rctus5oGfnyF8/l98DqTZg5mLyjqaCQLVybv8TJXxkEjjMMfbkJYhh/3PrTDPV5BxEf7Q02Goi6CzYSkq2uCXJ5amC9HGAjCPxgLrUkRUAQUAUVAEVAEFIG1IKAe6LWg18BtI90R6bsnUr0wjlwMdPOiGOjwQgw0QzAKY6DDYNGgEdy114uBDiMWmvXawOBBK5sUdUwM7eDx3eSBZgx02zaUwxBnjLSGbxiI9I8ioAgoAopADSKw1oNU7OEnax2aHp6yMoJqQK+M0aat8eOfPyiMhV7EwvFEiXA4LBwP/0uwcLzqsXAc+fiAxCY8Fo7oYLM5FZAsHJEuv8QnvWtyJiOWhWNmNC2R7oBh2oiNZwwLB41g1mGiR5mGtsuy4VLXFSsvcQRaTRFQBBQBRUARWFcE1nKQyuLDT9aqth6eshKCakCvhNAmLw9Hw7L9nlYZP5uR/v6kvLkcHvej8EW8dom8719vlatvzMvAXS3SdyiKg08yMo2jwaPbw9gMCIM3wrANhGzgRRo60teRto4pHMXJhzhk0MvzLxjHbf3eZkPGQ9tkKOsQGx1o9mQxnzLD0fzSDrXZ2npVBBQBRUARUARqF4G1HKSih5+s77zmrYz17Vd7qwMEhp6blK/+2tm8pk/nb4ve0XhmuiDy+K9d9e5zf5tAR+dtBoSB3OGT5mhQgu04WrvV43ru2R+RPe/phpHtnS44dzMpKWwU7L2zRXr2t5jwC1LQTV6OL9DUmTrTOJSlOwjPdEj2f6Bbtj+ox40uAl4fFAFFQBFQBBQBRaDiCOiOqopD2hgCs+msHP1zx3he47DmQUeXhVcZLHOIUc5Kci4jU5eSCNtImzjliYsJGXp2Uk59+SbYMsCcAeOZ6cYbc2g4byjoqNPQ0akcTZ3I7NW0JGdt3Xk5/ZUx8Efn6DvWqK82VwQUAUVAEVAEFAFFYCkE1IBeCplNnj93My1Tb1QBBFLS4ZUlZV0GlHPgd54HlV0mlQUPNE46nE6bZ1LQMZGeLgljOh3PmiO7ye3MumyXRXsa26S/y6a9g1WotyZFQBFQBBQBRUARUASqiYAa0NVEt45lt4AOLnpnFQaQo6YjO0YT6OtIS0fKOVLPtQ2EDBWdpaBj76SnC4Gyjuwb1InMGqxr6OxIfweeO9LfkY2Dx36zjiZFQBFQBBQBRUARUASqiYAa0NVEt45l+wI+OfLxvRUbAWOgfWSTw4pjDHQIxm709pA043RBeqM7d2Kz4kMdcuCDPcYoDsJoZmIMtGBTICnoqNP2I1HpQF0e9d26lewcMJxN3SYTA806mhQBRUARUAQUAUVAEagmAuquqya6dS6bG/J+8ei9cvkHV+X4305JYM+svPkXywxqGRYO0s6RhaNrVxhhGh4LRwi8zjwZkIn3ZM/gRsFt97WbcA1S22WSHlUdy5hY7tLUkX3D0tup8Wwg0j+KgCKgCCgCdYpAIQ90ObzOyt28vpOuBvT64l13vdFw7d7XKQfeF5KWrnZ58xtg1xiB9/d92MQHTmj/gMi7//ctMjcekf5DAbn49Czq+aV7b6dEeubB7xwwnmN/SKTz9ogJswjCqUzDmRR05IC2YRc0smkQs4w0dzSIGcJRmApp6iy9XWE9fVYEFAFFQBFQBOoJAZcHunxeZ+VuXs+5VgN6PdGus75IGfeN/+OsjJ0EhUZBmn3cy8hcFvn6b1wvKOXjsPhgNIfb/dKMuOTW3pAXo9wXkEhHUGavpwzDBsMvAjiKu30HykM+GTsXMxsCGc/cvS8ie0FtR6+zJkVAEVAEFAFFoNERcHmglde5tmdbDejanp8N047e4UvfG5OxU7caz6UqlUX4BRkzSFfn83uHm1x7ZQ6HqYRkagiFSPQ68zV3IwlDOSyxHIsGeaInSW0H2rroYNiEd5Tar9ZTBBQBRUARUAQUAUWgmgjojqtqolvHshlGceNUfM0j8LifQTWH47ZJRZdJZsEDnTH3FM5yvlhOirpshvR0HkUdjW/m2TjpNSujAhQBRUARUAQUAUVAEagAAmpAVwDERhQRbPFJ74G1h054zBugmkNsM6no/AjTCHf4zT1xYzlfLCdFHT3V3gt1QVfHPOqiSRFQBBQBRUARUAQUgVpBQEM4amUmakwPbtS7/ZFuOf04wjiKxECXoi5joGkEk24u0hU0sc19d7eYGOhQe8DEQJN9w42B5qZCHoqSwYmCjIEmbZ1l4CilT62jCCgCioAioAgoAopAtRFQA7raCNexfG7e+8m/PCQzozG5+uoc2DUS8vi/LY2F47a3d4JezmPhCEcDC2EYNJiZGJZBZg5LQUcjmXmWhYN1LLUd7zUpAoqAIqAIKAKKgCJQKwioAV0rM1HDeoRaQ3Lb20LGuP3In3TK9GhSevc3y833xcDpnJW+u9oknfDhUBSf7HlnxIwkHMUhKZ2eUVxIO8cK1pB2KehsXjjqhWxwIyM3GNoQDhrYvFePdA0vFlVNEVAEFAFFYNUIkAe6ORQxn3PK67xqGNeloRrQ6wJzfXZCGrtzT4zJzdMxmRtLyvj5mCRxCIp4Z58sGlRzF8/o9pkNgAHEObcMBKX/rlZp39ps4p15kmA5dHTs+8pz02azYSqWEbJBByJe7HS5shYpqg+KgCKgCCgCikCNIjA5NyY7371TOjs7oaHyOtfoNBm1dHdWLc/OBupG7++Vo9MyASo5bvKbwSmCyUkYz/i/WIojXCM1CxaN5DwOQGmSqYtJGT02I34c4d0E65fGMGWWkkzfqM92DOkgnR31CIThfS5TVin9aR1FQBFQBBQBRaAWENjaO2iM566uLuHL51MzrRbmpZgOOjPFUNE8E4+cmE4bHudMAhR02Ny3UspmYF+jGjcBzoOKLhVjCIbXjhR2pdLRsR7rM2VgkJPOzrxAgcdUjizTQP8oAoqAIqAIKAKKgCJQQQTUgK4gmI0kirHGYTBlkEXDHwYFHY7WXin5sD8QURzGA90EOrpgpAmxzl47UtjZWOaV5LAe6zPxKG+jA/VAaAhTObJMA/2jCCgCioAioAgoAopABRHwLJIKClRRjYEAN+oNHmmXzp1hc9BJ20BIQh2In8D/xRJjoIOt4HGGwUsPdHRnSPrvaZMMDjKcR+QG45ZL3fxn+kZ9tkvjgJUO6EA90ols2bKK6ap5ioAioAgoAoqAIqAIrAUB3US4FvQavC03/d37iQHDhMGhknbuxqlpuXkuIbc91CojiHGewDHd+9/bIbM3mqTztoChu+NBKX13tmHjYVri42npAZ/zfNa3EAO9EpsGY6DJG33HB3uMAW091yu1a/Dp0OEpAoqAIqAIKAKKQI0goAZ0jUxErapBbzB5nMmK8eLnR+Tq8zMwatPyzH/AgSeIeRa8jn3+hgg2GkoSL9I8w0ttwjnorUb7AEJAth/pkM5dzSuyabjsGwzVoOc61OadiGhp7iBVkyKgCCgCioAioAgoAhuGgIZwbBj09dMxPcJDz07K1RdmjHGcxQbBLEIzJI0XiTX4ovHMlDOqWZ5N8RkbEOfmZfilKZkADd5ybBou+0YQMdfKuGEQ1T+KgCKgCCgCioAiUGMIqAFdYxNSi+owdII0dlmwYdBYNp7n5RSlQY3EGGbvCoMbDBqJqcyybBou+4bXUhk3LA56VQQUAUVAEWh8BKZnpxp/kA0yQg3haJCJrOYwGIPMTYQ+MGEwMTxj2cTQDRjP9CAzNeHGBwaNcNSPjYRLs2m47BteS2XcsDjoVRFQBBQBRaDxEdjz7m7p6Oho/IE2wAjVA90Ak1jtITAOevtDHbL1gTZjGPtAUefDASnCr180kvnCBkOTaFzjxXIewCKoG2hpkm33RaVzd2RZNg2XfSMF3uly2Ts8BfSvIqAIKAKKgCJQnwjQeNbDU+pj7tQDXR/ztOFakpHjsX+zU+ITKYmBWSM6GEJIRlrGL8ald38z8ualpccn4xcS0twVkLa+EJg5UuYAlo4doMJLg+YOnmym5dg02E90MLxsnQ0HQxVQBBQBRUARUAQUgU2NgBrQm3r6yx+8P+SXrl1BQ0nHkwqTOL6bm/+YfAGftPaFcYAKwzT80rE9v7xYxxrOK7Fp0BO9Up3yNdcWioAioAgoAoqAIqAIVAaBvIVTGXkqpUERcOnlZq7G5dyTYxK75m0qNENGyEYg4Bm+LV04ROX+Vrnrw31Cj7Lb1lLTMV+TIqAIKAKKgCKgCCgC9YiAxkDX46yts84uvRyP1r4CSrrYKIzn3CZBow5o6zKpeUmCaUP883Lt2KxcOTqF0I2sXHlu2mwoVGq6dZ447U4RUAQUAUVAEVAEqoKAGtBVgbWxhLr0csmZjCQnYTwz5WjqvAf8pUMaoRrZxLxkkvMyhxjouZtpHLySq5+ryGfK1KQIKAKKgCKgCCgCikA9IqAGdD3O2jrr7NLLMTY51JFbNq4Hmjohm/HLPpw8SE91S28QGwsDwrANN/HZbih08/VeEVAEFAFFQBFQBBSBekCgpmKg9+7dGwV9y/fT6fT7z58//yaeD+H5cwCSpIivzc3NfXxoaChWD8A2ko6WXo6hGPQsD4KSLj6ei4G2A0UMtD8XAy2ZJulDDPTgkajZWMjjuNmWnmcbA02ZmhQBRUARUAQUAUUgj0A0Gs0/6F1NI1AzBjSM5YdgLP9XoLXfIobnv8L9J0+fPv39/fv3/25LS8vv4Pm3bLle1w+BQnq5h35jh0xcmpOJNxMycHeLxCdF2voDuGYNC0c4GjDeaGpY2FaN5/WbN+1JEVAEFAFFoH4QgN1TP8puck1rZqZwWt0v4fVrmI9hzgkM6u24RGk88zmTydAT/VHea9oYBGj4MoSDV1LWde9pk92P9UhzZ7O0bgnBuxyQ9oEwnoMLxrPV1G1r8/SqCCgCioAioAgoAopAPSJQMx7oM2fO/AIBhKfZ/LYPY3oQj1csqOfOnRtGGfM01RACSlFXQ5OhqigCioAioAgoAorAuiBQMwZ04Wjn5+d9MKILs0umboDHml7rwvb6vAQCFit7XaLaomwybgwdRewGkh8x0PPzWfPcujUfvrGoQYM9WKzstcGGV5XhWKzstSqdNJhQi5W9NtjwqjIci5W9VqWTBhRq8bLXBhxixYdUaawqLa/iA1aBCwjUsgE9BC23WU0R0jEAo5p5JaWNK0a4AAAb/ElEQVQTJ06UVE8rLUbg+PHjizOWecpgO+eNcyDfCOUrZZMis0eHxB/J5zX6XTmYNToWpY5PMSsVqXw9xSyPRal3ilmpSC2up7gtxmM9nxT79UR7bX3VrAGNkI3LCNmYxesRxEF/D4H1n4AB/Xipwz148KCEQo5lV2rDTVqP33r5xj18+LD4/f6SUKAH+tTVm7fUPXCk55YY6FsqNUDGajBrgGGvaQiKWfnwKWaKWfkIrK6FrrXycSNmlUzlfAZXsl+VVT4CtWhALxzPkc1mfxrG3OdgRJPX5QKM6I+VOkQagaUagqXK3Az1ysINdvb2Ix23UNQFgrW4rKo3e2VhVj016kqyYlb+dClmiln5CKyuha611eFWiVaKfSVQXB8ZNWfpwNu82w797NmzjMN4u33Wa+0hoBR1tTcnqpEioAgoAoqAIqAIVBeBmqGxq+4wVXolEGDIBo/y5tW9L4eizm1XCZ1UhiKgCCgCioAioAgoAuuNQM15oNcbAO2vNARcurp0DEY0mgUj/oWTBemJXim5MuyJhKW0W0mulisCioAioAgoAoqAIrCeCKgHej3RrtO+6DXmUdxkFQyEfTJxMSGTeAWam0wey1hnueTKCEZ8JbdbTqaWKQKKgCKgCCgCioAisBEIqAG9EajXWZ+puayk4x4FdyaZlUwq90p6RjPLWGe55Mqw9UppZ+vqVRFQBBQBRUARUAQUgVpBQEM4amUmaliPYIvPhGpQRX/IJ/6g973LH/IOumE4Bussl1wZtl4p7WxdvSoCioAioAgoAoqAIlArCCxv9dSKlqrHhiLATYKDD7bjpEGRdCIrnTvD0oFXOo7NhMhjGessl1wZqVi25HbLydQyRUARUAQUAUVAEVAENgIB9UBvBOp12GchXR2HwLAMepZXMp7tcAtllNrOtterIqAIKAKKgCKgCCgCtYCAeqBrYRbqRAcavKE2f8kGsx2WS123WhlWll4VAUVAEVAEFAFFQBHYaATUA73RM1CH/ZdDR1dO3TqEQlVWBBQBRUARUAQUgU2IgHqgN+Gkr2XI5dDRlVN3LTppW0VAEVAEFAFFQBFQBNYTATWg1xPtBuirHDq6cuo2ADQ6BEVAEVAEFAFFQBHYJAioAb1JJrpSwyyHjq6cupXST+UoAoqAIqAIKAKKgCJQbQTUgK42wg0mn5sALaXdSnR05dRtMJh0OIqAIqAIKAKKgCLQwAjoJsIGntxKD40xzQzLiA6GJfqhcEk0dkpdV+lZUHmKgCKgCCgCioAisNEIqAG90TNQJ/2vhU3DUtfVyVBVTUVAEVAEFAFFQBFQBJZFQEM4loVHC4mAsmnoOlAEFAFFQBFQBBQBRSCPgBrQeSz0bgkElE1jCWA0WxFQBBQBRUARUAQ2JQJqQG/KaS9v0MqmUR5eWlsRUAQUAUVAEVAEGhsBNaAbe34rMjpl06gIjCpEEVAEFAFFQBFQBBoEAd1E2CATWe1hKJtGtRFW+YqAIqAIKAKKgCJQLwioB7peZqoG9LRsGryWm7gRMTmTMRsSy22r9RUBRUARUAQUAUVAEaglBNQDXUuz0aC6rIUCr0Eh0WEpAoqAIqAIKAKKQB0joB7oOp68elBdKfDqYZZUR0VAEVAEFAFFQBEoBwE1oMtB6/9v795j7LjqO4Dv03EedlTUNLg21A52HNtgHm4gatoQ0qYRjwil4iGgKQ2FEmgoKiItVCWBRkIgVCKoGtSSQoFIlEJSQhMehSitoCqP0mCCYzu2UxQcO+EP2tSLWfzafs9m73Z993p3ce7aZ+98Rpo98zgze87nnJn7u3Pn3pH3ZxbwE3g/M5kNCBAgQIAAgcoFBNCVN9BCL56fwFvoLaj8BAgQIECAQLuAALpdxHxXBfwEXlc57YwAAQIECBCoQMCXCCtohF4vgp/A6/UWVj8CBAgQINAsAQF0s9r7pNW29RN4J60A/jEBAgQIECBAoEsCbuHoEqTdECBAgAABAgQINENAAN2MdlZLAgQIECBAgACBLgkIoLsEaTcECBAgQIAAAQLNEBBAN6Od1ZIAAQIECBAgQKBLAgLoLkHaDQECBAgQIECAQDMEBNDNaGe1JECAAAECBAgQ6JKAALpLkHZDgAABAgQIECDQDAEBdDPaWS0JECBAgAABAgS6JCCA7hKk3RAgQIAAAQIECDRDQADdjHZWSwIECBAgQIAAgS4JCKC7BGk3BAgQIECAAAECzRAQQDejndWSAAECBAgQIECgSwIC6C5B2g0BAgQIECBAgEAzBATQzWhntSRAgAABAgQIEOiSgAC6S5B2Q4AAAQIECBAg0AwBAXQz2lktCRAgQIAAAQIEuiQggO4SpN0QIECAAAECBAg0Q0AA3Yx2VksCBAgQIECAAIEuCQiguwRpNwQIECBAgAABAs0QEEA3o517tpZjR8b6Dowc7iupgQABAgQIECBwIgSGTsQ/8T8IzIfAoz8Y7Xvom/v6Do0e6RtaPNC3/NlL+s580uL5+Ff2SYAAAQIECBCYFHAFepLCxEISKFecS/Dc39/XN3zqwHha5l2JXkitqKwECBAgQGBhCgigF2a7Nb7UB/cfGb/yPBWiXIkuyw0ECBAgQIAAgfkUEEDPp659z5vA8GkD47dtTP0H5TaOstxAgAABAgQIEJhPAdHGfOra97wJ9A/0j9/zPJbvDh78yZG+kpZ7oMtyAwECBAgQIEBgPgV8iXA+de17XgXKFwaXLj9l/LaNcuVZ8Dyv3HZOgAABAgQITAgIoHWFBS1QguZFZwwu6DooPAECBAgQILCwBNzCsbDaS2kJECBAgAABAgROsoAA+iQ3gH9PgAABAgQIECCwsAQE0AurvZSWAAECBAgQIEDgJAsIoE9yA/j3BAgQIECAAAECC0tgQXyJcO3atS8dGxu7PrTD/f39t2zfvv2GhcWstAQIECBAgAABAr0iUP0V6FWrVp2d4Pl9w8PDF91///3rM33RmjVrLu2VBlAPAgQIECBAgACBhSVQfQC9aNGiSxM037Vly5YfhfZwxo/nKvTLFxaz0hIgQIAAAQIECPSKQPUBdKCXZ3xoCvieBNQrpsybJECAAAECBAgQIHDCBKq/BzrB8rQgP1egj8wmdPjw4b4yGuYm0LJqpXPbqtm5WlattNkac6t9y6qVzm2rZudqWbXSZmvMrfYtq1Y6t63kanm1UiKzC3Tbqtv7m70GchyvQPUBdCq2OwHzc1sVzPSyBNW7W/PHSu+7775jrbJ8BoF77713hrVWdRJg1kll5mXMZvbptJZZJ5WZlzGb2edYa7kdS2b+l7Off+Nu/YfqA+jBwcGv5B3Zu1avXn3WmWee+T8jIyNXJoi+aTaA9evX9+X+6dmyWT8hUN71lgP3aU97Wl/MucxBgNkckNqyMGsDmcMsszkgtWVh1gYyx1luc4Sakq2YdXPwGtxNzfndV/UB9NatW/fmVzeuHRgYuGvfvn0lIv5sfo3j9tlYShAoEJxNafp6btNNZlvCbDah6euZTTeZbQmz2YSmr2c23WQuS7jNRWl+8rCfH9f52Gv1AXSp9I4dO25NUkYDAQIECBAgQIAAgZMqMO0Leie1NP45AQIECBAgQIAAgcoFBNCVN5DiESBAgAABAgQI1CUggK6rPZSGAAECBAgQIECgcgEBdOUNpHgECBAgQIAAAQJ1CQig62oPpSFAgAABAgQIEKhcQABdeQMpHgECBAgQIECAQF0CAui62kNpCBAgQIAAAQIEKhcQQFfeQIpHgAABAgQIECBQl4AAuq72UBoCBAgQIECAAIHKBQTQlTeQ4hEgQIAAAQIECNQlIICuqz2UhgABAgQIECBAoHIBAXTlDaR4BAgQIECAAAECdQkIoOtqD6UhQIAAAQIECBCoXEAAXXkDKR4BAgQIECBAgEBdAgLoutpDaQgQIECAAAECBCoXEEBX3kCKR4AAAQIECBAgUJeAALqu9lAaAgQIECBAgACBygUE0JU3kOIRIECAAAECBAjUJSCArqs9lIYAAQIECBAgQKByAQF05Q2keAQIECBAgAABAnUJCKDrag+lIUCAAAECBAgQqFxAAF15AykeAQIECBAgQIBAXQIC6LraQ2kIECBAgAABAgQqFxBAV95AikeAAAECBAgQIFCXgAC6rvZQGgIECBAgQIAAgcoFBNCVN5DiESBAgAABAgQI1CUggK6rPZSGAAECBAgQIECgcgEBdOUNpHgECBAgQIAAAQJ1CQig62oPpSFAgAABAgQIEKhcQABdeQMpHgECBAgQIECAQF0CAui62kNpCBAgQIAAAQIEKhcQQFfeQIpHgAABAgQIECBQl4AAuq72UBoCBAgQIECAAIHKBQTQlTeQ4hEgQIAAAQIECNQlIICuqz2UhgABAgQIECBAoHIBAXTlDaR4BAgQIECAAAECdQkIoOtqD6UhQIAAAQIECBCoXEAAXXkDKR4BAgQIECBAgEBdAgLoutpDaQgQIECAAAECBCoXEEBX3kCKR4AAAQIECBAgUJeAALqu9lAaAgQIECBAgACBygUE0JU3kOIRIECAAAECBAjUJSCArqs9lIYAAQIECBAgQKByAQF05Q2keAQIECBAgAABAnUJCKDrag+lIUCAAAECBAgQqFxAAF15AykeAQIECBAgQIBAXQIC6LraQ2kIECBAgAABAgQqFxBAV95AikeAAAECBAgQIFCXgAC6rvZQGgIECBAgQIAAgcoFBNCVN5DiESBAgAABAgQI1CUggK6rPZSGAAECBAgQIECgcgEBdOUNpHgECBAgQIAAAQJ1CQig62oPpSFAgAABAgQIEKhcQABdeQMpHgECBAgQIECAQF0CAui62kNpCBAgQIAAAQIEKhcQQFfeQIpHgAABAgQIECBQl4AAuq72UBoCBAgQIECAAIHKBQTQlTeQ4hEgQIAAAQIECNQlIICuqz2UhgABAgQIECBAoHKBoZrKt2bNmqv6+/svuv/++69qlevcc899d6avKPNjY2PX7tix447WOikBAgQIECBAgACBEy1QxRXo1atXn5Lg+b0Jnj+QcayFsHbt2hdnflMC6vXDw8PPK+vPOeecM1vrpQQIECBAgAABAgROtEAVAfTg4GAJjnOBeezaqQCZvzzjLVk2tmXLloeT3p1A+vKpeUwTIECAAAECBAgQOJECVQTQ27dv/2KuMr8tQfRoW+WXZ9lDrWWZ3puAekVrXkqAAAECBAgQIEDgRAuc0Hugc0vGSxIA35hKtm7T6M/0gwmeL+xU8QTM0wL8LDvSKW/7sgMHDrQvMj+DwOHDh8fXFrd8IjBDTqtaAsxaEnNPmc3dqpWTWUti7imzuVtNzcltqsbcpovZ17/+9aXPec5z9iU+acU2c9u4Q65WG3RYZVFlAic0gM6V5s+k/mWc03DkyJHdAwMDy1qZE3wvy7i1Nd8pXbx48ZJDhw715X91Wm3ZLAL33XffLDmsbhdg1i4y+zyz2Y3aczBrF5l9ntnsRp1ycOukcuxlQ0NDj37jG98o38/632Pnmtuae+6558wLLrjgce9nbv9NrscjcEID6OMo6J0Jon8/2/39qlWrfj7pJZn/05n28/SnP33P5s2bV4yOju6bKZ91BAgQIECAAIFuCJQr0I9nP2X7EoQ/3v08njLY9mcTqDqAzk/W3ZafsduUcXOqVW7nePuuXbt+OFMVJz5Cmbxveqa81hEgQIAAAQIETrbAROziyvPJbgj/nwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQHmTSM8N55513bn7m7lup0K6JSj2Sh7Q8v0znlzzeneSKMp3fkr42v/BxR5k29PXlATcvjcn1sRjON4FvyW9o38BlukD60Cez9JkZ95e1sXpXfvR+Z36r/ObMlt8A/d7+/ftfvXv37p+U9U0eVq9evTQuX8tvsr/ogQceeDDzGzo5pe8tSd/7RKzWZBzJ8fvKnTt3to7fRhG2m6W/lZ/wLMflIwUi/e3OHJvvYFY0xs/pb0nfuSouSca+tXz58tc/8sgj5+WY/HBWH3U8MhsnG/+TfnWU29KlS6/et2/fVVmpr/0/01FTMXtPFlyefnYk/e0jiStuXLdu3VP1taOYGjcz7Ul/C1kgnfvZGUvnftbEOB485+T54nT6TVm2fnh4+HmZ/sA555xTTrCNH/L72mfH7H1xuaj4ZPqiNWvWXNp4mA4AsdmUJzVe0OpfCWZuT1B4S7JeW+ySbj3ttNPe0WHTRi1KIHhBCZ5T6XNbFT+WUwLmP8/x+O34bUj6tuT7eGubJqWdzFL/Z8fkjVP623jfYjYePJ8fn1cfPHjw/PhsjNPQ3r17r0lAU96MTTsemT12NCUQnOY2MjLyB/raYz6d/sbsBelf5bz/1NLfkudN5WKdvtZJq1nLeiqATtOdn45efjf6PzJ+OS9KJagpV5zLO8cS6Ixt2bLl4aR3J2C8vKxr+rBo0aJLY3NXXH4Ui8MZPx7Dlzfdpb3+GzZseEJczorXJ9K3Nme8Lv1rRfItzYm1BIt9OaGWK9GNt4vT6zK+IRZ7issxnF5W1iXf5blK/XdlOm9I7k5y9kT+sqgxQ7vZRMXPz7H52vS172T8WFyWluXMxo+1/w7FNd///vdHJ6y+m3RjxvbjUT+bACpJzlHT3NLHnpxV+toUp6mTOb9/PuemX8+ysVNPPfXsHH+DOWeVTyH1talQDZzuqQA6J4Ifpw1vTof/5aTvz9Ws2y+++OKhTC9Pp598uEqm9yZvCX4MsQnCpE2m97CZ3i1y5fnsLP3npFfmNo0LMv3c9K8rk07a5SE/JWAsno0ecnvU7+UF59+CMH6LWI63o/rYhFPr+Fue+UnDbLM3Y2tdYxzbzSbsHkz6ZzmfPSPpnvS3D06ANN4sfWZnXL5aPJ7ylKf8QpJrMm7LONmX9LNotA2d3NKvPpds+lqbVdvs4XySfUPegGzJ8rsylnOUvtaG1LTZElwuuCEd+SUJ8m5MwccmCl9eqB/MCfXCVmUy/YVctRl5+OGH1+UFfNobhSw70srb5DSObObQARLgbE22yavL6Vt/mfk3ddhUv2pDKX0sx1vb0r6W07T+lxf01rr2bZo0P5Zz2OSnZHnj9t58+rFzAoDZBEQ+Sl+Z2zPK91n+OsHNV9N3XtTWSVp9idkUmKlu27Zt+5esKuP4oK+1JI5Oc1HgHStWrHh3btO7Y3BwsHxye3SGPue0dpBen592UlkIFU5H/kxeXJ6U8ckTY5m+MPfuvnXjxo2nT6nDYE6uBzPuzrJlreXp+MsmlrUWNTndneDmF1sAmS5OxcswRSAvOJvSvyZfnKe88ZjsV/mIfVmWs5viViYnTCb7WJvT7rwZmTRM9mXpg403jNFZcXlji3Lx4sWDmT40Mc8sEDken5Hz+NcyeVPO/+/RzyZ6xyxJu5u+NjNYfNaXLwyWXBNfEL81/W5lZifPW85pRad5w4IMoGdopt8YHR393bI+V6kvSTKQE2v5WO/OdPjycftg+dJc0ksy/5WkjR/yTro4XFJOops2bRrO9JUJYO5sPEwbQO55WxSXG3Mv9BkZy/TVyfI3Gfcn0Pm1kj1Xv16ThF3BmDLkY+MfZPbHnZzieEfG4taXNykXJ9mXN8jj906XZU0dch4bSd3fmfNYua+3L+erP0yAeFuZZjZ+X/1ZcfhCOK7JOf6m4qKfFYWZh3Keb3fLLWnl1sfr9bXOdvFal083PlRuB43fKcl1Rc71pe91PPc7Pjs79uLSoV6q1NDQ0OvT0T+ad9hX58Xmx3nRGf/IPR+/35YX7/Llws2pb3nT8PacbH/YS3U/3rps3bp1b7yuzQnhrvyU0aLs57N5Qbr9ePfXq9vlp9X+Pf3npnwL+5up42BOkp9OoPepnFC/lzchH8668gWv/4rjK3vV4DjqNfkZZ47FV8Tp5naneF6XL/T+bfrgvckzGr/fOY7/00ubjJuVK12xekXOYx9LWl60t8Xm1aWizHIADg6+OTZLwnFdfK5POpZj8s6c//Wz0kmOMRzLLZav1Nc6oyV+uDVvLp65Z8+ezTkGy6dAnyqfgufcv7XTud/x2dnRUgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGAOAnkgwuV5kMv40+xmyp48d2fs+KCcPGjhNRnfPNP21hEgQIBA7wj01JMIe6dZ1IQAgRMlkKdM/lP+VxmPe8hT3Mrj3Hcc9w5sSIAAAQILSqB/QZVWYQkQINBBIFd/v51HgV+Xx+7emavEl+axzl/KY51/adeuXT/I/FszvzKblcewvynTA0n3Jej94zy2/pt5FHR5RPZvZ/rSDRs2PCGP4r058+syPpo8W/L43v48uvc15Qp0lj2U7VcnPSvjd0dGRl61ZMmSFyXfhzI/mvH92c9fJDUQIECAQA8LlBcSAwECBBa0QALYWxPYvmCiEi9MundoaOg3y3yWX5H1e5NenYD3uQmGNyW4/qOsun3lypWLS54MY+XPgQMHPphkd4LgdYcOHbos25xflreGzP9c1v1KxnMz/eTTTz/95dnfP2T95zL+VZYLnltYUgIECPSwgAC6hxtX1Qg0RSDB7K2p6/NLfTN9WQLmGzJelivKT8yiVRmXZn7lGWec8bVccb4nV5U/kmUHFy9evCbp5JBtW1eT+x544IFHs+KjkysfmyjB8pGMh7O/e5O/7N9AgAABAg0TEEA3rMFVl0AvCuQq8PbUa6R8IbCkucL8yaQX5yryFUn/MQHzQALeT+UK8bMyPrOMyXPhtm3bvpf1U4dDyTd5XkyAXILlySHrDk7OPHbV2m1wU0BMEiBAoCkCky8UTamwehIg0LMCtyVOfm+C3i+Vq8dJd6amb8uyTyfw/VLmX5YAe0Wpfe5n/q3BwcH/XLFiResWjnGU5PlcxteVmY0bN56e7V6Ve6vHb+8Yz3DsP4eyypeyj+1jDQECBHpKQADdU82pMgSaK5BAudzGsTZB7xeLQgmaM56Sq8z/mivOX8midybP53MLx3cSJP9J5l+4e/fun5S8reGnP/3pW7Luicnz3dHR0bJ9uXd6f1mf9KhAum3+88lydbZ7Z8lrIECAAAECBAgQINAIgfyaxxsSBP/qRGX7c6X69sy/thGVV0kCBAgQmLOAjxznTCUjAQK9LpArzuWe6BsTNA8mXZT5L+fqdfnCoYEAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAPAv8H7VHuu/LFrrQAAAAAElFTkSuQmCC\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.JointGrid at 0x11c1e3278>"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sns.jointplot('weight', 'hindfoot_length', data = df, size = 9, color = 'darkorchid', alpha = 0.4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false,
+    "deletable": true,
+    "editable": true,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'];\n",
+       "    var y0 = fig.canvas.height - msg['y0'];\n",
+       "    var x1 = msg['x1'];\n",
+       "    var y1 = fig.canvas.height - msg['y1'];\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x;\n",
+       "    var y = canvas_pos.y;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"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",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        event.shiftKey = false;\n",
+       "        // Send a \"J\" for go to next cell\n",
+       "        event.which = 74;\n",
+       "        event.keyCode = 74;\n",
+       "        manager.command_mode();\n",
+       "        manager.handle_keydown(event);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x119d5bbe0>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize = (12,10))\n",
+    "sns.violinplot('species_id', 'hindfoot_length', hue = 'sex',\n",
+    "              data = df,   split = True, inner = 'quartile',\n",
+    "              palette = ['fuchsia', 'gainsboro'])\n",
+    "plt.title(\"ID and Hindfoot Length by Gender\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
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   "identifier": "https://datacarpentry.github.io/python-ecology-lesson/07-visualization-ggplot-python.html",
   "dateCreated": "2015-03-19",
   "dateModified": "2023-05-19",
-  "datePublished": "2023-09-26"
+  "datePublished": "2023-10-03"
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