diff --git a/.gitignore b/.gitignore
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+++ b/.gitignore
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+*.json
+/data
+
+**/.ipynb_checkpoints
diff --git a/.ipynb_checkpoints/Change_The_World_Writeup-checkpoint.ipynb b/.ipynb_checkpoints/Change_The_World_Writeup-checkpoint.ipynb
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@@ -0,0 +1,5296 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Ferguson - 2014\n",
+    "**Sophia and Victoria**\n",
+    "\n",
+    "In Ferguson Missouri the Summer 2014, an unarmed black teenager was shot 6 times and subsequently died from his wounds. The white officer was not indicted by a grand jury 3 months later. \n",
+    "\n",
+    "The initial incident and the following decision incited both a physical firestorm as the streets of Ferguson were filled with flame and protests, and virtually through social media as people from around the world weighed in. \n",
+    "\n",
+    "This project explores the phenomenon of social media activism, news sharing, and the relationship between the virtual and physical world through analysis of 13 million tweets over the two weeks following the shooting, and 15 million tweets about the indictment decision in the two weeks following.\n",
+    "\n",
+    "Specifically, we are interested in the kinds of visualizations helpful for understanding social justice-related events over twitter. Using spatial, temporal, and aggregate type graphs, we present a variety of graphs to highlight the various traits which could make the study of twitter data compelling."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Getting a dataset\n",
+    "To get the dataset of tweets mentioning Ferguson in the time after the shooting and around the time of the indictment, we found the following [list of tweet ids](https://archive.org/details/ferguson-tweet-ids). Since the Twitter API terms of service do not allow posting actual tweet content on the internet, we have to \"hydrate\" these tweets from their ids. \n",
+    "\n",
+    "We did this using a tool called twarc.py. [Documentation Here.](https://github.com/edsu/twarc). This tool allows us to point twarc.py at a file containing tweet ids. Then twarc hydrates the tweets by querying the twitter api for those ids, 100 at a time. In all it took the two of us about a week and a half to collect all the data. \n",
+    "\n",
+    "Unfortunately, as [this blog post](http://inkdroid.org/2014/08/30/a-ferguson-twitter-archive/) mentions, there are some gaps in the dataset containing the tweets after the time of the shooting. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Importing everthing!\n",
+    "Let's get ready to do some cool data things! Admittedly, we are using a specil package called [cartopy](http://scitools.org.uk/cartopy/) for mapping. To install, there is a pre-built binary/package for Anaconda which you can get through the command line: `conda install -c scitools cartopy`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/Sophia/anaconda/lib/python2.7/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n",
+      "  warnings.warn(self.msg_depr % (key, alt_key))\n"
+     ]
+    }
+   ],
+   "source": [
+    "% matplotlib inline\n",
+    "import pandas as pd\n",
+    "import json\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import time\n",
+    "from datetime import datetime\n",
+    "from datetime import date\n",
+    "from datetime import timedelta\n",
+    "\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets\n",
+    "import matplotlib.cm as cm\n",
+    "import seaborn as sns\n",
+    "\n",
+    "from matplotlib import animation\n",
+    "from IPython.display import HTML\n",
+    "from tempfile import NamedTemporaryFile"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Reading in Data\n",
+    "Here, we're using a function that we've developed to read in the data, a certain number of lines at a time. This function will take a while to read in all the tweets. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def ReadToDf(linesAtATime,filepath, max=-1):\n",
+    "    '''Read in the .json file of all of the tweets and convert them into a dataframe\n",
+    "    \n",
+    "    This function also has an optional argument max that can be used to speficy if only a certain number of tweets \n",
+    "    are desired.'''\n",
+    "    start = time.time()\n",
+    "    df = pd.DataFrame()\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filepath) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print \"number of tweets parsed: \", i\n",
+    "                print \"total time elapsed: \", time.time() - start\n",
+    "                df = pd.DataFrame(data=data).append(df)\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "        #Allow us to handle the last few tweets, and to truncate the data if we just want to run unit tests\n",
+    "            if (max > 0 and i >= max):\n",
+    "                break\n",
+    "        df = pd.DataFrame(data=data).append(df)\n",
+    "    #return the aggregation\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "number of tweets parsed:  500000\n",
+      "total time elapsed:  8.42842698097\n",
+      "number of tweets parsed:  1000000\n",
+      "total time elapsed:  18.3847298622\n",
+      "number of tweets parsed:  1500000\n",
+      "total time elapsed:  29.5955348015\n",
+      "number of tweets parsed:  2000000\n",
+      "total time elapsed:  42.0361249447\n",
+      "number of tweets parsed:  2500000\n",
+      "total time elapsed:  54.7786529064\n",
+      "number of tweets parsed:  3000000\n",
+      "total time elapsed:  68.3164279461\n",
+      "number of tweets parsed:  3500000\n",
+      "total time elapsed:  83.3426258564\n",
+      "number of tweets parsed:  4000000\n",
+      "total time elapsed:  97.4800388813\n",
+      "number of tweets parsed:  4500000\n",
+      "total time elapsed:  114.210583925\n",
+      "number of tweets parsed:  5000000\n",
+      "total time elapsed:  132.300080776\n",
+      "number of tweets parsed:  5500000\n",
+      "total time elapsed:  148.048592806\n",
+      "number of tweets parsed:  6000000\n",
+      "total time elapsed:  168.449382782\n",
+      "number of tweets parsed:  6500000\n",
+      "total time elapsed:  187.605800867\n",
+      "number of tweets parsed:  7000000\n",
+      "total time elapsed:  211.799097776\n",
+      "number of tweets parsed:  7500000\n",
+      "total time elapsed:  234.145410776\n",
+      "number of tweets parsed:  8000000\n",
+      "total time elapsed:  258.229158878\n",
+      "number of tweets parsed:  8500000\n",
+      "total time elapsed:  286.702250957\n",
+      "number of tweets parsed:  9000000\n",
+      "total time elapsed:  313.91174984\n",
+      "number of tweets parsed:  9500000\n",
+      "total time elapsed:  345.321898937\n",
+      "number of tweets parsed:  10000000\n",
+      "total time elapsed:  387.382420778\n",
+      "number of tweets parsed:  10500000\n",
+      "total time elapsed:  427.470818996\n",
+      "number of tweets parsed:  11000000\n",
+      "total time elapsed:  472.723701954\n"
+     ]
+    }
+   ],
+   "source": [
+    "shooting_df = ReadToDf(500000, 'data/cleanedShootingTweets.json')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>coordinates_x</th>\n",
+       "      <th>coordinates_y</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>retweet_count</th>\n",
+       "      <th>retweeted_status_id_str</th>\n",
+       "      <th>user_id_str</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_verified</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>499906559254986752</td>\n",
+       "      <td>33</td>\n",
+       "      <td>None</td>\n",
+       "      <td>1241255414</td>\n",
+       "      <td>Baris_DR</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[760827962]</td>\n",
+       "      <td>[VistoHLK]</td>\n",
+       "      <td>499906559552802816</td>\n",
+       "      <td>8</td>\n",
+       "      <td>499905751163604993</td>\n",
+       "      <td>762556028</td>\n",
+       "      <td>FrantasticRadio</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[1670129570]</td>\n",
+       "      <td>[SMBoucher_]</td>\n",
+       "      <td>499906559585951746</td>\n",
+       "      <td>1318</td>\n",
+       "      <td>499797954627403776</td>\n",
+       "      <td>983639826</td>\n",
+       "      <td>arisandhraaal</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[93292598]</td>\n",
+       "      <td>[TuckOnTheRise]</td>\n",
+       "      <td>499906559628288000</td>\n",
+       "      <td>34</td>\n",
+       "      <td>499739127949316096</td>\n",
+       "      <td>1676578380</td>\n",
+       "      <td>Jupvcx</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>499906559653449729</td>\n",
+       "      <td>2</td>\n",
+       "      <td>None</td>\n",
+       "      <td>117810285</td>\n",
+       "      <td>annemariemingo</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[63004503]</td>\n",
+       "      <td>[mlcalderone]</td>\n",
+       "      <td>499906559661854720</td>\n",
+       "      <td>2977</td>\n",
+       "      <td>499906107926917121</td>\n",
+       "      <td>1588428578</td>\n",
+       "      <td>TiniDo</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[1178700896]</td>\n",
+       "      <td>[ajam]</td>\n",
+       "      <td>499906560026370048</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>156824708</td>\n",
+       "      <td>HiRhy</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[18197912]</td>\n",
+       "      <td>[jackfrombkln]</td>\n",
+       "      <td>499906560190324736</td>\n",
+       "      <td>48078</td>\n",
+       "      <td>499531968229683200</td>\n",
+       "      <td>315935087</td>\n",
+       "      <td>_FlightToAsia</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson, SisterPatriots]</td>\n",
+       "      <td>[347627434]</td>\n",
+       "      <td>[LindaSuhler]</td>\n",
+       "      <td>499906560328749057</td>\n",
+       "      <td>60</td>\n",
+       "      <td>499763033414328320</td>\n",
+       "      <td>732980827</td>\n",
+       "      <td>ChristiChat</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[11771512]</td>\n",
+       "      <td>[OKnox]</td>\n",
+       "      <td>499906561222139904</td>\n",
+       "      <td>110</td>\n",
+       "      <td>499906334796812288</td>\n",
+       "      <td>18237351</td>\n",
+       "      <td>uplift17</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   coordinates_x  coordinates_y                      created_at  \\\n",
+       "0            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "1            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "2            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "3            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "4            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "5            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "6            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "7            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "8            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "9            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "\n",
+       "       entities_hashtags_text entities_user_mentions_id_str  \\\n",
+       "0                          []                            []   \n",
+       "1                  [Ferguson]                   [760827962]   \n",
+       "2                  [Ferguson]                  [1670129570]   \n",
+       "3                          []                    [93292598]   \n",
+       "4                  [Ferguson]                            []   \n",
+       "5                          []                    [63004503]   \n",
+       "6                          []                  [1178700896]   \n",
+       "7                  [Ferguson]                    [18197912]   \n",
+       "8  [Ferguson, SisterPatriots]                   [347627434]   \n",
+       "9                  [Ferguson]                    [11771512]   \n",
+       "\n",
+       "  entities_user_mentions_screen_name              id_str  retweet_count  \\\n",
+       "0                                 []  499906559254986752             33   \n",
+       "1                         [VistoHLK]  499906559552802816              8   \n",
+       "2                       [SMBoucher_]  499906559585951746           1318   \n",
+       "3                    [TuckOnTheRise]  499906559628288000             34   \n",
+       "4                                 []  499906559653449729              2   \n",
+       "5                      [mlcalderone]  499906559661854720           2977   \n",
+       "6                             [ajam]  499906560026370048              0   \n",
+       "7                     [jackfrombkln]  499906560190324736          48078   \n",
+       "8                      [LindaSuhler]  499906560328749057             60   \n",
+       "9                            [OKnox]  499906561222139904            110   \n",
+       "\n",
+       "  retweeted_status_id_str user_id_str user_screen_name user_verified  \n",
+       "0                    None  1241255414         Baris_DR         False  \n",
+       "1      499905751163604993   762556028  FrantasticRadio         False  \n",
+       "2      499797954627403776   983639826    arisandhraaal         False  \n",
+       "3      499739127949316096  1676578380           Jupvcx         False  \n",
+       "4                    None   117810285   annemariemingo         False  \n",
+       "5      499906107926917121  1588428578           TiniDo         False  \n",
+       "6                    None   156824708            HiRhy         False  \n",
+       "7      499531968229683200   315935087    _FlightToAsia         False  \n",
+       "8      499763033414328320   732980827      ChristiChat         False  \n",
+       "9      499906334796812288    18237351         uplift17         False  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shooting_df.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "number of tweets parsed:  500000\n",
+      "total time elapsed:  18.6331429482\n",
+      "number of tweets parsed:  1000000\n",
+      "total time elapsed:  28.0015799999\n",
+      "number of tweets parsed:  1500000\n",
+      "total time elapsed:  38.5282449722\n",
+      "number of tweets parsed:  2000000\n",
+      "total time elapsed:  50.155023098\n",
+      "number of tweets parsed:  2500000\n",
+      "total time elapsed:  61.9974660873\n",
+      "number of tweets parsed:  3000000\n",
+      "total time elapsed:  89.0536670685\n",
+      "number of tweets parsed:  3500000\n",
+      "total time elapsed:  105.817389965\n",
+      "number of tweets parsed:  4000000\n",
+      "total time elapsed:  120.09651494\n",
+      "number of tweets parsed:  4500000\n",
+      "total time elapsed:  134.684483051\n",
+      "number of tweets parsed:  5000000\n",
+      "total time elapsed:  150.199685097\n",
+      "number of tweets parsed:  5500000\n",
+      "total time elapsed:  220.092925072\n",
+      "number of tweets parsed:  6000000\n",
+      "total time elapsed:  252.059778929\n",
+      "number of tweets parsed:  6500000\n",
+      "total time elapsed:  270.389688969\n",
+      "number of tweets parsed:  7000000\n",
+      "total time elapsed:  289.102723122\n",
+      "number of tweets parsed:  7500000\n",
+      "total time elapsed:  313.567158937\n",
+      "number of tweets parsed:  8000000\n",
+      "total time elapsed:  340.885793924\n"
+     ]
+    }
+   ],
+   "source": [
+    "indictment_df = ReadToDf(500000, 'data/cleanedIndTweets.json')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>coordinates_x</th>\n",
+       "      <th>coordinates_y</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>retweet_count</th>\n",
+       "      <th>retweeted_status_id_str</th>\n",
+       "      <th>user_id_str</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_verified</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:14 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>541719359513980928</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>555589804</td>\n",
+       "      <td>wallyworkswell</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:14 +0000 2014</td>\n",
+       "      <td>[EricGarner, BlackLivesMatter, Ferguson]</td>\n",
+       "      <td>[1241761556, 125412208]</td>\n",
+       "      <td>[StatenStories, rockwitlili]</td>\n",
+       "      <td>541719360960995328</td>\n",
+       "      <td>11</td>\n",
+       "      <td>541718719156989953</td>\n",
+       "      <td>2251226729</td>\n",
+       "      <td>Iluvthewayymmf</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:16 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[11131522]</td>\n",
+       "      <td>[stimulator]</td>\n",
+       "      <td>541719365561745408</td>\n",
+       "      <td>52</td>\n",
+       "      <td>541683660483608576</td>\n",
+       "      <td>30693810</td>\n",
+       "      <td>Peta_de_Aztlan</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:16 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[11131522]</td>\n",
+       "      <td>[stimulator]</td>\n",
+       "      <td>541719365700173824</td>\n",
+       "      <td>52</td>\n",
+       "      <td>541683660483608576</td>\n",
+       "      <td>98631494</td>\n",
+       "      <td>Humane_Being</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:16 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[959596692]</td>\n",
+       "      <td>[KennettDems]</td>\n",
+       "      <td>541719368993087488</td>\n",
+       "      <td>11</td>\n",
+       "      <td>541717992925827074</td>\n",
+       "      <td>2904274533</td>\n",
+       "      <td>_forwardhope</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:17 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[14116807]</td>\n",
+       "      <td>[ShareThis]</td>\n",
+       "      <td>541719371194716160</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>64157934</td>\n",
+       "      <td>HauteLifestyle</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:18 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[407754987]</td>\n",
+       "      <td>[Ignacio_RT]</td>\n",
+       "      <td>541719374357606400</td>\n",
+       "      <td>84</td>\n",
+       "      <td>541714248511291392</td>\n",
+       "      <td>965597011</td>\n",
+       "      <td>martinezarcaya</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:18 +0000 2014</td>\n",
+       "      <td>[Alaska, EricGarner, Ferguson, BlackLivesMatter]</td>\n",
+       "      <td>[487600344]</td>\n",
+       "      <td>[Bipartisanism]</td>\n",
+       "      <td>541719375821025280</td>\n",
+       "      <td>722</td>\n",
+       "      <td>541464022613516289</td>\n",
+       "      <td>165341521</td>\n",
+       "      <td>VanessaHrndzzz</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:19 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[407754987]</td>\n",
+       "      <td>[Ignacio_RT]</td>\n",
+       "      <td>541719379218825217</td>\n",
+       "      <td>84</td>\n",
+       "      <td>541714248511291392</td>\n",
+       "      <td>438948938</td>\n",
+       "      <td>harrysotopo</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>-122.46199</td>\n",
+       "      <td>38.290648</td>\n",
+       "      <td>Sun Dec 07 22:22:21 +0000 2014</td>\n",
+       "      <td>[ICantBreathe, Ferguson]</td>\n",
+       "      <td>[21879831]</td>\n",
+       "      <td>[ZerlinaMaxwell]</td>\n",
+       "      <td>541719388324253696</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>73267550</td>\n",
+       "      <td>SofieRKarasek</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   coordinates_x  coordinates_y                      created_at  \\\n",
+       "0            NaN            NaN  Sun Dec 07 22:22:14 +0000 2014   \n",
+       "1            NaN            NaN  Sun Dec 07 22:22:14 +0000 2014   \n",
+       "2            NaN            NaN  Sun Dec 07 22:22:16 +0000 2014   \n",
+       "3            NaN            NaN  Sun Dec 07 22:22:16 +0000 2014   \n",
+       "4            NaN            NaN  Sun Dec 07 22:22:16 +0000 2014   \n",
+       "5            NaN            NaN  Sun Dec 07 22:22:17 +0000 2014   \n",
+       "6            NaN            NaN  Sun Dec 07 22:22:18 +0000 2014   \n",
+       "7            NaN            NaN  Sun Dec 07 22:22:18 +0000 2014   \n",
+       "8            NaN            NaN  Sun Dec 07 22:22:19 +0000 2014   \n",
+       "9     -122.46199      38.290648  Sun Dec 07 22:22:21 +0000 2014   \n",
+       "\n",
+       "                             entities_hashtags_text  \\\n",
+       "0                                                []   \n",
+       "1          [EricGarner, BlackLivesMatter, Ferguson]   \n",
+       "2                                        [Ferguson]   \n",
+       "3                                        [Ferguson]   \n",
+       "4                                        [Ferguson]   \n",
+       "5                                                []   \n",
+       "6                                        [Ferguson]   \n",
+       "7  [Alaska, EricGarner, Ferguson, BlackLivesMatter]   \n",
+       "8                                        [Ferguson]   \n",
+       "9                          [ICantBreathe, Ferguson]   \n",
+       "\n",
+       "  entities_user_mentions_id_str entities_user_mentions_screen_name  \\\n",
+       "0                            []                                 []   \n",
+       "1       [1241761556, 125412208]       [StatenStories, rockwitlili]   \n",
+       "2                    [11131522]                       [stimulator]   \n",
+       "3                    [11131522]                       [stimulator]   \n",
+       "4                   [959596692]                      [KennettDems]   \n",
+       "5                    [14116807]                        [ShareThis]   \n",
+       "6                   [407754987]                       [Ignacio_RT]   \n",
+       "7                   [487600344]                    [Bipartisanism]   \n",
+       "8                   [407754987]                       [Ignacio_RT]   \n",
+       "9                    [21879831]                   [ZerlinaMaxwell]   \n",
+       "\n",
+       "               id_str  retweet_count retweeted_status_id_str user_id_str  \\\n",
+       "0  541719359513980928              0                    None   555589804   \n",
+       "1  541719360960995328             11      541718719156989953  2251226729   \n",
+       "2  541719365561745408             52      541683660483608576    30693810   \n",
+       "3  541719365700173824             52      541683660483608576    98631494   \n",
+       "4  541719368993087488             11      541717992925827074  2904274533   \n",
+       "5  541719371194716160              0                    None    64157934   \n",
+       "6  541719374357606400             84      541714248511291392   965597011   \n",
+       "7  541719375821025280            722      541464022613516289   165341521   \n",
+       "8  541719379218825217             84      541714248511291392   438948938   \n",
+       "9  541719388324253696              0                    None    73267550   \n",
+       "\n",
+       "  user_screen_name user_verified  \n",
+       "0   wallyworkswell         False  \n",
+       "1   Iluvthewayymmf         False  \n",
+       "2   Peta_de_Aztlan         False  \n",
+       "3     Humane_Being         False  \n",
+       "4     _forwardhope         False  \n",
+       "5   HauteLifestyle         False  \n",
+       "6   martinezarcaya         False  \n",
+       "7   VanessaHrndzzz         False  \n",
+       "8      harrysotopo         False  \n",
+       "9    SofieRKarasek         False  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "indictment_df.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cleaning Data\n",
+    "This is where we're going to clean data that we've read in. The only cleaning that we need to do is that we need to convert the \"created_at\" column to a datetime object. The rest of the cleaning data is done in the script `development_scripts/clean_json_data.py`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def recodeData (dataframe):\n",
+    "    # Creating a parseable dataset    \n",
+    "    dataframe['createdDatetime'] =  pd.to_datetime(\n",
+    "        dataframe['created_at'], \n",
+    "        format = '%a %b %d %H:%M:%S +0000 %Y')\n",
+    "    \n",
+    "    # Pull out hour and date data since we use these a lot and it takes a long time to get to them\n",
+    "    dataframe['createdDatetime_Date'] = dataframe['createdDatetime'].dt.date\n",
+    "    dataframe['createdDatetime_Hour'] = dataframe['createdDatetime'].dt.hour"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's recode the dates for the shooting data and the indictment data! These opperations are done in place, so we don't actually have to return anything"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "recoding shooting dataset\n",
+      "recoding indictment dataset\n",
+      "recoded all datasets\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('recoding shooting dataset')\n",
+    "recodeData(shooting_df)\n",
+    "print('recoding indictment dataset')\n",
+    "recodeData(indictment_df)\n",
+    "print('recoded all datasets')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Getting a Subset of the Data\n",
+    "Here, we are going to get a subset of the data. We are doing this because there is too much data to analyze in a timely manner. If we were going to tell the story of how the twitter world reacted to Ferguson, we would re-run our analysis on the entire dataset. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "shootingSubset = shooting_df[shooting_df.createdDatetime_Date.isin([date(2014,8,14),date(2014,8,15),date(2014,8,16)])]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>coordinates_x</th>\n",
+       "      <th>coordinates_y</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>retweet_count</th>\n",
+       "      <th>retweeted_status_id_str</th>\n",
+       "      <th>user_id_str</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_verified</th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>createdDatetime_Date</th>\n",
+       "      <th>createdDatetime_Hour</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>499906559254986752</td>\n",
+       "      <td>33</td>\n",
+       "      <td>None</td>\n",
+       "      <td>1241255414</td>\n",
+       "      <td>Baris_DR</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[760827962]</td>\n",
+       "      <td>[VistoHLK]</td>\n",
+       "      <td>499906559552802816</td>\n",
+       "      <td>8</td>\n",
+       "      <td>499905751163604993</td>\n",
+       "      <td>762556028</td>\n",
+       "      <td>FrantasticRadio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[1670129570]</td>\n",
+       "      <td>[SMBoucher_]</td>\n",
+       "      <td>499906559585951746</td>\n",
+       "      <td>1318</td>\n",
+       "      <td>499797954627403776</td>\n",
+       "      <td>983639826</td>\n",
+       "      <td>arisandhraaal</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[93292598]</td>\n",
+       "      <td>[TuckOnTheRise]</td>\n",
+       "      <td>499906559628288000</td>\n",
+       "      <td>34</td>\n",
+       "      <td>499739127949316096</td>\n",
+       "      <td>1676578380</td>\n",
+       "      <td>Jupvcx</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>499906559653449729</td>\n",
+       "      <td>2</td>\n",
+       "      <td>None</td>\n",
+       "      <td>117810285</td>\n",
+       "      <td>annemariemingo</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[63004503]</td>\n",
+       "      <td>[mlcalderone]</td>\n",
+       "      <td>499906559661854720</td>\n",
+       "      <td>2977</td>\n",
+       "      <td>499906107926917121</td>\n",
+       "      <td>1588428578</td>\n",
+       "      <td>TiniDo</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[1178700896]</td>\n",
+       "      <td>[ajam]</td>\n",
+       "      <td>499906560026370048</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>156824708</td>\n",
+       "      <td>HiRhy</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[18197912]</td>\n",
+       "      <td>[jackfrombkln]</td>\n",
+       "      <td>499906560190324736</td>\n",
+       "      <td>48078</td>\n",
+       "      <td>499531968229683200</td>\n",
+       "      <td>315935087</td>\n",
+       "      <td>_FlightToAsia</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson, SisterPatriots]</td>\n",
+       "      <td>[347627434]</td>\n",
+       "      <td>[LindaSuhler]</td>\n",
+       "      <td>499906560328749057</td>\n",
+       "      <td>60</td>\n",
+       "      <td>499763033414328320</td>\n",
+       "      <td>732980827</td>\n",
+       "      <td>ChristiChat</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[11771512]</td>\n",
+       "      <td>[OKnox]</td>\n",
+       "      <td>499906561222139904</td>\n",
+       "      <td>110</td>\n",
+       "      <td>499906334796812288</td>\n",
+       "      <td>18237351</td>\n",
+       "      <td>uplift17</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   coordinates_x  coordinates_y                      created_at  \\\n",
+       "0            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "1            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "2            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "3            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "4            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "5            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "6            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "7            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "8            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "9            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "\n",
+       "       entities_hashtags_text entities_user_mentions_id_str  \\\n",
+       "0                          []                            []   \n",
+       "1                  [Ferguson]                   [760827962]   \n",
+       "2                  [Ferguson]                  [1670129570]   \n",
+       "3                          []                    [93292598]   \n",
+       "4                  [Ferguson]                            []   \n",
+       "5                          []                    [63004503]   \n",
+       "6                          []                  [1178700896]   \n",
+       "7                  [Ferguson]                    [18197912]   \n",
+       "8  [Ferguson, SisterPatriots]                   [347627434]   \n",
+       "9                  [Ferguson]                    [11771512]   \n",
+       "\n",
+       "  entities_user_mentions_screen_name              id_str  retweet_count  \\\n",
+       "0                                 []  499906559254986752             33   \n",
+       "1                         [VistoHLK]  499906559552802816              8   \n",
+       "2                       [SMBoucher_]  499906559585951746           1318   \n",
+       "3                    [TuckOnTheRise]  499906559628288000             34   \n",
+       "4                                 []  499906559653449729              2   \n",
+       "5                      [mlcalderone]  499906559661854720           2977   \n",
+       "6                             [ajam]  499906560026370048              0   \n",
+       "7                     [jackfrombkln]  499906560190324736          48078   \n",
+       "8                      [LindaSuhler]  499906560328749057             60   \n",
+       "9                            [OKnox]  499906561222139904            110   \n",
+       "\n",
+       "  retweeted_status_id_str user_id_str user_screen_name user_verified  \\\n",
+       "0                    None  1241255414         Baris_DR         False   \n",
+       "1      499905751163604993   762556028  FrantasticRadio         False   \n",
+       "2      499797954627403776   983639826    arisandhraaal         False   \n",
+       "3      499739127949316096  1676578380           Jupvcx         False   \n",
+       "4                    None   117810285   annemariemingo         False   \n",
+       "5      499906107926917121  1588428578           TiniDo         False   \n",
+       "6                    None   156824708            HiRhy         False   \n",
+       "7      499531968229683200   315935087    _FlightToAsia         False   \n",
+       "8      499763033414328320   732980827      ChristiChat         False   \n",
+       "9      499906334796812288    18237351         uplift17         False   \n",
+       "\n",
+       "      createdDatetime createdDatetime_Date  createdDatetime_Hour  \n",
+       "0 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "1 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "2 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "3 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "4 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "5 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "6 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "7 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "8 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "9 2014-08-14 13:13:06           2014-08-14                    13  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shootingSubset.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "indictmentSubset = indictment_df[indictment_df.createdDatetime_Date.isin([date(2014,11,23),date(2014,11,24),date(2014,11,25)])]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>coordinates_x</th>\n",
+       "      <th>coordinates_y</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>retweet_count</th>\n",
+       "      <th>retweeted_status_id_str</th>\n",
+       "      <th>user_id_str</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_verified</th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>createdDatetime_Date</th>\n",
+       "      <th>createdDatetime_Hour</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[Atlanta, Ferguson, cnn]</td>\n",
+       "      <td>[16252233]</td>\n",
+       "      <td>[sgallman]</td>\n",
+       "      <td>537368500663508992</td>\n",
+       "      <td>269</td>\n",
+       "      <td>537356966684033025</td>\n",
+       "      <td>2526260324</td>\n",
+       "      <td>infinate_words</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[edshow, Ferguson]</td>\n",
+       "      <td>[26379293]</td>\n",
+       "      <td>[ahuntre]</td>\n",
+       "      <td>537368500671889408</td>\n",
+       "      <td>4</td>\n",
+       "      <td>537366422583009280</td>\n",
+       "      <td>1197490142</td>\n",
+       "      <td>SexyLiberal317</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[34643610, 52419540]</td>\n",
+       "      <td>[EricBoehlert, NBCFirstRead]</td>\n",
+       "      <td>537368500739002369</td>\n",
+       "      <td>42</td>\n",
+       "      <td>537310708493725696</td>\n",
+       "      <td>408855841</td>\n",
+       "      <td>LaDow</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[148116121]</td>\n",
+       "      <td>[scottbix]</td>\n",
+       "      <td>537368500814491648</td>\n",
+       "      <td>2558</td>\n",
+       "      <td>536965701337382912</td>\n",
+       "      <td>187314413</td>\n",
+       "      <td>SwAgOnALLMaDDeN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[1496971]</td>\n",
+       "      <td>[GlobalGrind]</td>\n",
+       "      <td>537368501791772672</td>\n",
+       "      <td>204</td>\n",
+       "      <td>537289646708113408</td>\n",
+       "      <td>419066409</td>\n",
+       "      <td>CerezaChampagne</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[8839632]</td>\n",
+       "      <td>[NBCNightlyNews]</td>\n",
+       "      <td>537368501804343296</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>23618466</td>\n",
+       "      <td>wbaltv11</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[569467464]</td>\n",
+       "      <td>[RealLucasNeff]</td>\n",
+       "      <td>537368501959548928</td>\n",
+       "      <td>18</td>\n",
+       "      <td>537358807371100160</td>\n",
+       "      <td>257448308</td>\n",
+       "      <td>Sara_Laylaa</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[102817657]</td>\n",
+       "      <td>[CubanRendezvous]</td>\n",
+       "      <td>537368501997277184</td>\n",
+       "      <td>4348</td>\n",
+       "      <td>537320870902263808</td>\n",
+       "      <td>387339834</td>\n",
+       "      <td>chanelyousif</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[46343528]</td>\n",
+       "      <td>[Gia_Nova]</td>\n",
+       "      <td>537368502081159170</td>\n",
+       "      <td>43</td>\n",
+       "      <td>537358089888870401</td>\n",
+       "      <td>1660502162</td>\n",
+       "      <td>ealxpatcarvalho</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[214622133, 2538201518]</td>\n",
+       "      <td>[iSmashFizzle, fergusonlibrary]</td>\n",
+       "      <td>537368502152462336</td>\n",
+       "      <td>1011</td>\n",
+       "      <td>537113989407571969</td>\n",
+       "      <td>2364576554</td>\n",
+       "      <td>RuthAnnAngle1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   coordinates_x  coordinates_y                      created_at  \\\n",
+       "0            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "1            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "2            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "3            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "4            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "5            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "6            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "7            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "8            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "9            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "\n",
+       "     entities_hashtags_text entities_user_mentions_id_str  \\\n",
+       "0  [Atlanta, Ferguson, cnn]                    [16252233]   \n",
+       "1        [edshow, Ferguson]                    [26379293]   \n",
+       "2                        []          [34643610, 52419540]   \n",
+       "3                        []                   [148116121]   \n",
+       "4                        []                     [1496971]   \n",
+       "5                [Ferguson]                     [8839632]   \n",
+       "6                [Ferguson]                   [569467464]   \n",
+       "7                        []                   [102817657]   \n",
+       "8                [Ferguson]                    [46343528]   \n",
+       "9                        []       [214622133, 2538201518]   \n",
+       "\n",
+       "  entities_user_mentions_screen_name              id_str  retweet_count  \\\n",
+       "0                         [sgallman]  537368500663508992            269   \n",
+       "1                          [ahuntre]  537368500671889408              4   \n",
+       "2       [EricBoehlert, NBCFirstRead]  537368500739002369             42   \n",
+       "3                         [scottbix]  537368500814491648           2558   \n",
+       "4                      [GlobalGrind]  537368501791772672            204   \n",
+       "5                   [NBCNightlyNews]  537368501804343296              0   \n",
+       "6                    [RealLucasNeff]  537368501959548928             18   \n",
+       "7                  [CubanRendezvous]  537368501997277184           4348   \n",
+       "8                         [Gia_Nova]  537368502081159170             43   \n",
+       "9    [iSmashFizzle, fergusonlibrary]  537368502152462336           1011   \n",
+       "\n",
+       "  retweeted_status_id_str user_id_str user_screen_name user_verified  \\\n",
+       "0      537356966684033025  2526260324   infinate_words         False   \n",
+       "1      537366422583009280  1197490142   SexyLiberal317         False   \n",
+       "2      537310708493725696   408855841            LaDow         False   \n",
+       "3      536965701337382912   187314413  SwAgOnALLMaDDeN         False   \n",
+       "4      537289646708113408   419066409  CerezaChampagne         False   \n",
+       "5                    None    23618466         wbaltv11          True   \n",
+       "6      537358807371100160   257448308      Sara_Laylaa         False   \n",
+       "7      537320870902263808   387339834     chanelyousif         False   \n",
+       "8      537358089888870401  1660502162  ealxpatcarvalho         False   \n",
+       "9      537113989407571969  2364576554    RuthAnnAngle1         False   \n",
+       "\n",
+       "      createdDatetime createdDatetime_Date  createdDatetime_Hour  \n",
+       "0 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "1 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "2 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "3 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "4 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "5 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "6 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "7 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "8 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "9 2014-11-25 22:13:29           2014-11-25                    22  "
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "indictmentSubset.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Understanding The Dataset\n",
+    "In this section, we mostly want to explore broadly the data we have -- both the shooting and indictment-related tweets. We will do this for large scale temporal and spatial visualizations first, followed by more specifically aggregated comparisons amongst different axes of data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Visualizing the Number of Tweets Over Time\n",
+    "One of the first things we sought to visualize was the number of tweets over time, expecially as people reacted to important events related to the shooting and indictment. We were interested in seeing whether there were dectectable spikes in the number of tweets mentioning Ferguson as people reacted to these events. \n",
+    "\n",
+    "In the dataset related to the shooting, we have approximately 11 million tweets worth of data. Over the course of the first week, statements from police, from the family of Michael Brown, statements from the police officer Darren Wilson, and unrest from the streets were recorded and shared wildly across the web. To get a general understanding of the data, we are going to plot the number of tweets over time and annotate this plot with important events that happened over the course of the two weeks. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First, we will group the tweets by minute, and then count the number of tweets that happened each minute. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def plotWithEvents(df,eventlist):\n",
+    "    '''Given a dataframe of tweets, this function will plot those tweets, grouped by minute, and annotate the graph \n",
+    "    with any events that we would like.'''\n",
+    "    groupedTime = (df.set_index('createdDatetime')\n",
+    "                      .groupby([pd.TimeGrouper('Min')])\n",
+    "                      .count()\n",
+    "                      .reset_index())\n",
+    "    fig, ax = plt.subplots(figsize=(10,10))\n",
+    "\n",
+    "    groupedTime.plot(kind='line', x='createdDatetime', y='created_at', ax=ax)\n",
+    "    plt.title('Number of Tweets by Users')\n",
+    "\n",
+    "    ax.set_ylabel('Count of tweets')\n",
+    "    ax.set_xlabel('Date/Time')\n",
+    "    \n",
+    "    for i,event in enumerate(eventlist):\n",
+    "        plt.axvline(x=eventlist.get(event).get('date'),ymin=0, ymax=4000, linewidth=4,color='g',label=event)\n",
+    "        plt.text(eventlist.get(event).get('date'),2500 - (eventlist.get(event).get('offset'))*500,event)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To put the data in context, we map for a variety of calendar dates and times, as called out by [this](http://www.nytimes.com/interactive/2014/08/13/us/ferguson-missouri-town-under-siege-after-police-shooting.html?_r=0) article."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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YDx8+RK9efQEAjRs3KTTgOTk54fr1qzh//izs7MogOzu7yM9JXxjwiIiIyCjVrFkL169f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\nRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x491256e50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#calendar dates learned from a variety of news sources, especially http://www.nytimes.com/interactive/2014/08/13/us/ferguson-missouri-town-under-siege-after-police-shooting.html?_r=0\n",
+    "calendar_dates = {'AntonioFrench': {'date': datetime(2014,8,14,7,0,0), 'offset': 0},\n",
+    "                 'Obama2': {'date': datetime(2014,8,14,11,40,0), 'offset': 1},\n",
+    "                 'SilentVigils': {'date': datetime(2014,8,14,18,0,0), 'offset': 0},\n",
+    "                 'DarrenWilsonNamed': {'date': datetime(2014,8,15,8,45,0), 'offset': 0},\n",
+    "                 'CharacterAssassination': {'date': datetime(2014,8,15,12,30,0), 'offset': 1},\n",
+    "                 'StateOfEmergency': {'date': datetime(2014,8,16,15,0,0), 'offset': 0}}\n",
+    "\n",
+    "plotWithEvents(shootingSubset, calendar_dates)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's do the same thing for the data regarding the tweets after the indictment!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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b9MOfhdypbCQ0AhoAAPCbwlq4Cn1vM9d5SWfOu3NYqUZAAwAAflPUtyydd2pK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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x47f98fa10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "calendar_dates = {'IndictmentDecision': {'date': datetime(2014,11,24,20,15,0), 'offset': 0}}\n",
+    "plotWithEvents(indictmentSubset, calendar_dates)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our Thougts on this type of Visualization:**\n",
+    "\n",
+    "On the bright side, this type of visualization makes it immediately obvious if there are any gaps in the data, which, unfortunately there are. Additionally, we can see how the number of tweets mentioning Ferguson reacts after important events unfold. One thing that we find expecially interesting is how some events seem to cause a spike in the number of tweets, while some events cause a decrease in the number of tweets. \n",
+    "\n",
+    "However, while this visualization tells us about how many people are interacting in the twitter discussion about Ferguson, it does not tell us *who* is interacting or how they interact."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Visualizing the Location of Tweets \n",
+    "To start to understand who is interacting in the twitter discussion about Ferguson, we decided to start visualizing some of the location-based data that we had. Although many of the tweets are not geo-coded we, wanted to use the tweets that were to get a sense of who was engaging in this dataset, by understanding where people were engaging from. \n",
+    "\n",
+    "To do this, we first created a heatmap of the number of tweets origininating across the world. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Before we get there, though, we have to filter out only the tweets that have location data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "latLonPopulatedShooting = shootingSubset.dropna(subset=['coordinates_x','coordinates_y'])\n",
+    "latLonPopulatedIndictment = indictmentSubset.dropna(subset=['coordinates_x','coordinates_y'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we are going to define a function that plots a heatmap of the number of tweets origininating across the world, or at least a heatmap simulant called hexbin. Further, we should note that this will be a log scale graph, which will allow more clearly for ALL tweets to be visualized, but the density of certain locations to be still visible."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def createTweetHeatmap(tweetDf):\n",
+    "    #create a simple cartopy map\n",
+    "    plt.figure(figsize=(15,5))\n",
+    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "    ax.coastlines()\n",
+    "\n",
+    "    #straight-up coordinate data which we just finished recoding\n",
+    "    plt.hexbin(tweetDf.coordinates_x,tweetDf.coordinates_y,cmap=cm.Reds, bins='log') #add bins='log' to see a log based chart\n",
+    "    cb = plt.colorbar()\n",
+    "    cb.set_label('log10(counts)')\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And now, let's create some plots!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/Sophia/anaconda/lib/python2.7/site-packages/matplotlib/artist.py:221: MatplotlibDeprecationWarning: This has been deprecated in mpl 1.5, please use the\n",
+      "axes property.  A removal date has not been set.\n",
+      "  warnings.warn(_get_axes_msg, mplDeprecation, stacklevel=1)\n"
+     ]
+    },
+    {
+     "data": {
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a2WFV6POdu1jz3Crs9ogQ9SOAjt0xOOOs//ef8MnTPE5QvKAooPpAksFg1P+3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\nH+/Ywqwpz2FTLKxeOp93fvVLZldV0N2G1pMW8CPzC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lskypdeW8hAcGlNGaAo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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x49c6f9850>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "createTweetHeatmap(latLonPopulatedShooting)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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7LLpnAceOH+fy1asAlI4fz/33LU2akW3H6/XwwOpVKfcBhEIhTpw6zZGvvsKy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\n6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9j+8v9Q43RhUARZaXamlmg7WWLkPSi5PZuESdRw4MODnP7sDI89srwVn+/KRTw/eIYK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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x4539d6b90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "createTweetHeatmap(latLonPopulatedIndictment)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our thoughts on this type of visualization:**\n",
+    "\n",
+    "First of all, the reason that we used a log-based color scale in these plots is because it makes it easier to see where people are interacting -- otherwise it appears that all of the tweets are coming from Ferguson. We think that this visualization helps us better understand who is interacting in the twitter dataset, as we can begin to see that the Eastern half of the U.S. as well as the West Coast of the U.S tend to be the ones that interact most. There is, however, additionally, a dark point in the middle of the coutry that represents Ferguson. Beyond that, it looks like people all over the world, especially Europe, are talking about Ferguson in our dataset. \n",
+    "\n",
+    "After looking at this visualization, one of our thoughts is that it would be interesting to see how many people interact at a given time -- a combination of the first two visualizations. We pursue some variety of this in the following section."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "### Plotting tweets based on location and time\n",
+    "As we saw in the last visualization, it would be interesting to create an animation of the number of number of people tweeting from various locations across the world. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First lets declare some functions that every animation needs, courtesy of and adapted from [this blog](http://jakevdp.github.io/blog/2013/05/12/embedding-matplotlib-animations/)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#Note, the animation code courtesy of and adapted from http://jakevdp.github.io/blog/2013/05/12/embedding-matplotlib-animations/\n",
+    "VIDEO_TAG = \"\"\"<video controls>\n",
+    " <source src=\"data:video/x-m4v;base64,{0}\" type=\"video/mp4\">\n",
+    " Your browser does not support the video tag.\n",
+    "</video>\"\"\"\n",
+    "\n",
+    "def anim_to_html(anim):\n",
+    "    if not hasattr(anim, '_encoded_video'):\n",
+    "        with NamedTemporaryFile(suffix='.mp4') as f:\n",
+    "            anim.save(f.name, fps=20, extra_args=['-vcodec', 'libx264', '-pix_fmt', 'yuv420p'])\n",
+    "            video = open(f.name, \"rb\").read()\n",
+    "        anim._encoded_video = video.encode(\"base64\")\n",
+    "    \n",
+    "    return VIDEO_TAG.format(anim._encoded_video)\n",
+    "\n",
+    "def display_animation(anim):\n",
+    "    plt.close(anim._fig)\n",
+    "    return HTML(anim_to_html(anim))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Unfortunately, it's not as easy as we'd like to create functions that create animations for us (the output gets lost), so there will be some copy-and-paste-coding here!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<video controls>\n",
+       " <source src=\"data:video/x-m4v;base64,AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAA5nBtZGF0AAACrwYF//+r\n",
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+       "Jal0b28AAAAdZGF0YQAAAAEAAAAATGF2ZjU3LjI1LjEwMA==\n",
+       "\" type=\"video/mp4\">\n",
+       " Your browser does not support the video tag.\n",
+       "</video>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# First set up the figure, the axis, and the plot element we want to animate\n",
+    "fig = plt.figure(figsize=(10,10))\n",
+    "ax = plt.axes(xlim=(-180, 180), ylim=(-75, 75))\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "scat, = plt.plot([], [],'o', alpha=0.2)\n",
+    "\n",
+    "# animation function.  This is called sequentially by the animator\n",
+    "def animateShooting(i):\n",
+    "    startDate = date(2014,8,14)\n",
+    "    queryDate = startDate + timedelta(days = round(i/24)) \n",
+    "    hour = i % 24\n",
+    "    subset = []\n",
+    "    subset = latLonPopulatedShooting[\n",
+    "        (latLonPopulatedShooting['createdDatetime_Date'] == queryDate) & \n",
+    "        (latLonPopulatedShooting['createdDatetime_Hour'] == hour)]\n",
+    "\n",
+    "    scat.set_data(subset.coordinates_x,subset.coordinates_y)\n",
+    "    \n",
+    "    return scat,\n",
+    "\n",
+    "# animation.Animation._repr_html_ = anim_to_html #this yields a depreciation warning, heads up\n",
+    "# call the animator.  blit=True means only re-draw the parts that have changed.\n",
+    "anim = animation.FuncAnimation(fig, animateShooting, frames=72, interval=5000, blit=True)\n",
+    "\n",
+    "# call our new function to display the animation\n",
+    "display_animation(anim)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And now, the same for the indictment data!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
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+       "AAEAAAAATGF2ZjU3LjI1LjEwMA==\n",
+       "\" type=\"video/mp4\">\n",
+       " Your browser does not support the video tag.\n",
+       "</video>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# First set up the figure, the axis, and the plot element we want to animate\n",
+    "fig = plt.figure(figsize=(10,10))\n",
+    "ax = plt.axes(xlim=(-180, 180), ylim=(-75, 75))\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "scat, = plt.plot([], [],'o', alpha=0.2)\n",
+    "\n",
+    "# animation function.  This is called sequentially by the animator\n",
+    "def animateInd(i):\n",
+    "    startDate = date(2014,11,23)\n",
+    "    queryDate = startDate + timedelta(days = round(i/24)) \n",
+    "    hour = i % 24\n",
+    "    subset = []\n",
+    "    subset = latLonPopulatedIndictment[\n",
+    "        (latLonPopulatedIndictment['createdDatetime_Date'] == queryDate) & \n",
+    "        (latLonPopulatedIndictment['createdDatetime_Hour'] == hour)]\n",
+    "\n",
+    "    scat.set_data(subset.coordinates_x,subset.coordinates_y)\n",
+    "    \n",
+    "    return scat,\n",
+    "\n",
+    "# animation.Animation._repr_html_ = anim_to_html #this yields a depreciation warning, heads up\n",
+    "# call the animator.  blit=True means only re-draw the parts that have changed.\n",
+    "anim = animation.FuncAnimation(fig, animateInd, frames=72, interval=5000, blit=True)\n",
+    "\n",
+    "# call our new function to display the animation\n",
+    "display_animation(anim)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our Thoughts on this type of visualization**\n",
+    "\n",
+    "We really like this visualization -- it's super cool to see how the world talks about Ferguson, and see when various parts of the world are engaged in the coversation. One insight these plots appear to give us, is that while the rest of the world has some periods in which they talk about Ferguson less, the twitter users in Ferguson are *always* talking about Ferguson. Improvements to such a visualization may stem from incorporating labels for events, over time, allowing a viewer to immediately understand a particular ebb or rise in tweets.\n",
+    "\n",
+    "Although now we know where people are engaging, and when they are engaging, this plot still does not tell us *how* users engage in the conversation."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hashtags\n",
+    "To get at the question of how users are engaging with the dataset, we decided to look at one of twitters unique features: the hashtag. This is a quippy oneword statement often indicated by a pound sign in a post by a user - which twitter has handily aggregated for us already. \n",
+    "\n",
+    "To do this exploration, we first have to do a little bit of data re-ordering. Now that we've seen what sorts of visualizations are helpful for understanding the dataset on a very high level, let's explore different methods of visualizing hashtags in the dataset. To do this, let's create a dataframe that has one row per hasthag,tweet combination. So, a tweet using two hashtags would translate into a dataframe with two rows. \n",
+    "\n",
+    "In this case, these visualizations take a long time to make and the data takes a long time to reprocess, so we will transition to using only the shooting data here. We are doing this because it seems we learn similar things about how helpful a given visualization is whether or not we are using the shooting or indictment dataset. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will create this dataframe by looping over the rows in the dataframe, and looping over the hashtags in each tweet. For each tweet, we will create a json object that represents the row that should be added to our new dataframe. \n",
+    "\n",
+    "**Warning:** This is super slow, so don't run this unless you have to"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def convertToHashtagDf (df):\n",
+    "    '''convert a tweet dataframe to a dataframe of hashtags'''\n",
+    "    numprocessed = 0\n",
+    "    hashtagRows = []\n",
+    "    hashtagMap = {'MICHAELBROWN': 'MIKEBROWN'}\n",
+    "    for i,tweet in df.iterrows():\n",
+    "        numprocessed += 1\n",
+    "        if (numprocessed%500000 == 0):\n",
+    "                print('processed {} tweets'.format(numprocessed))\n",
+    "        for hashtag in tweet['entities_hashtags_text']:\n",
+    "            mappedhashtag = hashtag.upper()\n",
+    "            if (mappedhashtag in hashtagMap):\n",
+    "                mappedhashtag = hashtagMap[mappedhashtag]\n",
+    "\n",
+    "            hashtagRows.append({\n",
+    "                    'createdDatetime': tweet['createdDatetime'],\n",
+    "                    'hashtag': mappedhashtag,\n",
+    "                    'tweetId': tweet['id_str'],\n",
+    "                    'x': tweet['coordinates_x'],\n",
+    "                    'y': tweet['coordinates_y'],\n",
+    "                    'date': tweet['createdDatetime_Date'],\n",
+    "                    'hour': tweet['createdDatetime_Hour']})\n",
+    "    print \"creating dataframe\"\n",
+    "    hashtagsDf = pd.DataFrame(hashtagRows)\n",
+    "    return hashtagsDf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "processed 500000 tweets\n",
+      "processed 1000000 tweets\n",
+      "processed 1500000 tweets\n",
+      "processed 2000000 tweets\n",
+      "processed 2500000 tweets\n",
+      "processed 3000000 tweets\n",
+      "processed 3500000 tweets\n",
+      "creating dataframe\n"
+     ]
+    }
+   ],
+   "source": [
+    "shootingHashtagsDf = convertToHashtagDf(shootingSubset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559552802816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559585951746</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559653449729</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906560190324736</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906560328749057</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>SISTERPATRIOTS</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906560328749057</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561222139904</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561251504129</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561264062464</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>CUBA</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561645367297</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      createdDatetime        date         hashtag  hour             tweetId  \\\n",
+       "0 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906559552802816   \n",
+       "1 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906559585951746   \n",
+       "2 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906559653449729   \n",
+       "3 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906560190324736   \n",
+       "4 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906560328749057   \n",
+       "5 2014-08-14 13:13:06  2014-08-14  SISTERPATRIOTS    13  499906560328749057   \n",
+       "6 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906561222139904   \n",
+       "7 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906561251504129   \n",
+       "8 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906561264062464   \n",
+       "9 2014-08-14 13:13:06  2014-08-14            CUBA    13  499906561645367297   \n",
+       "\n",
+       "    x   y  \n",
+       "0 NaN NaN  \n",
+       "1 NaN NaN  \n",
+       "2 NaN NaN  \n",
+       "3 NaN NaN  \n",
+       "4 NaN NaN  \n",
+       "5 NaN NaN  \n",
+       "6 NaN NaN  \n",
+       "7 NaN NaN  \n",
+       "8 NaN NaN  \n",
+       "9 NaN NaN  "
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shootingHashtagsDf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that we have a dataframe, let's look at the tweets that use hashtags the top 10 hashtags (to get a feel for what people are tweeting)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[u'FERGUSON', u'MIKEBROWN', u'GAZA', u'MEDIABLACKOUT', u'JUSTICEFORMIKEBROWN', u'NMOS14', u'DONTSHOOT', u'PALESTINE', u'STL', u'TCOT']\n"
+     ]
+    }
+   ],
+   "source": [
+    "numTopHashtags = 10\n",
+    "popularHashtagsList = (shootingHashtagsDf\n",
+    "                   .groupby('hashtag')\n",
+    "                   .count()\n",
+    "                   .reset_index()\n",
+    "                   .sort_values(by='createdDatetime', ascending=False)['hashtag']\n",
+    "                   .tolist())[0:numTopHashtags]\n",
+    "\n",
+    "print(popularHashtagsList)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For framing, these hashtags had/have the following connotations on twitter:\n",
+    "\n",
+    "*Ferguson* - a flag for simply talking about the shooting and current events\n",
+    "\n",
+    "*MikeBrown* - used often to memorialize the teen\n",
+    "\n",
+    "*Gaza* - used to reference other unrest in the world\n",
+    "\n",
+    "*MediaBlackout* - initially in reference to reporter arrests, then carried on to imply that reporting in Ferguson failed to tell the whole story or was limited in detail\n",
+    "\n",
+    "*JusticeForMikeBrown* - this not only memorialized the teen, but took a stance of decidely PRO-Mike Brown\n",
+    "\n",
+    "*NMOS14* - a call for a national moment of silence, peaked during a night of silent vigils both physically, and as the data will show, virtually\n",
+    "\n",
+    "*DontShoot* - an allied with Mike Brown or BlackLivesMatter hashtag\n",
+    "\n",
+    "*Palestine* - similar to Gaza in purpose\n",
+    "\n",
+    "*STL* - used as a flag for the greater metropolitan area, St. Louis\n",
+    "\n",
+    "*TCOT* - used as a unifier for Top Conservatives on Twitter\n",
+    "\n",
+    "Now that we have the most popular hashtags, let's filter the hashtags dataframe for just those hashtags. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559552802816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559585951746</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559653449729</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906560190324736</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906560328749057</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561222139904</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561251504129</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561264062464</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561704460288</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2014-08-14 13:13:07</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906562589478912</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       createdDatetime        date   hashtag  hour             tweetId   x   y\n",
+       "0  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906559552802816 NaN NaN\n",
+       "1  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906559585951746 NaN NaN\n",
+       "2  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906559653449729 NaN NaN\n",
+       "3  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906560190324736 NaN NaN\n",
+       "4  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906560328749057 NaN NaN\n",
+       "6  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906561222139904 NaN NaN\n",
+       "7  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906561251504129 NaN NaN\n",
+       "8  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906561264062464 NaN NaN\n",
+       "10 2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906561704460288 NaN NaN\n",
+       "11 2014-08-14 13:13:07  2014-08-14  FERGUSON    13  499906562589478912 NaN NaN"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "popularShootingHashtagsDf = shootingHashtagsDf[shootingHashtagsDf.hashtag.isin(popularHashtagsList)]\n",
+    "popularShootingHashtagsDf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's count the number of times each hashtag was used in a given minute. To do this, we will group the dataframe by datetime.minute and hashtag and then aggregate by count."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>DONTSHOOT</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>25745</td>\n",
+       "      <td>25745</td>\n",
+       "      <td>25745</td>\n",
+       "      <td>173</td>\n",
+       "      <td>173</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>GAZA</td>\n",
+       "      <td>130</td>\n",
+       "      <td>130</td>\n",
+       "      <td>130</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>JUSTICEFORMIKEBROWN</td>\n",
+       "      <td>286</td>\n",
+       "      <td>286</td>\n",
+       "      <td>286</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>MIKEBROWN</td>\n",
+       "      <td>3236</td>\n",
+       "      <td>3236</td>\n",
+       "      <td>3236</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>NMOS14</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>PALESTINE</td>\n",
+       "      <td>28</td>\n",
+       "      <td>28</td>\n",
+       "      <td>28</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>STL</td>\n",
+       "      <td>993</td>\n",
+       "      <td>993</td>\n",
+       "      <td>993</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>TCOT</td>\n",
+       "      <td>106</td>\n",
+       "      <td>106</td>\n",
+       "      <td>106</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-14 00:15:00</td>\n",
+       "      <td>DONTSHOOT</td>\n",
+       "      <td>102</td>\n",
+       "      <td>102</td>\n",
+       "      <td>102</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      createdDatetime              hashtag   date   hour  tweetId    x    y\n",
+       "0 2014-08-14 00:00:00            DONTSHOOT    289    289      289    0    0\n",
+       "1 2014-08-14 00:00:00             FERGUSON  25745  25745    25745  173  173\n",
+       "2 2014-08-14 00:00:00                 GAZA    130    130      130    0    0\n",
+       "3 2014-08-14 00:00:00  JUSTICEFORMIKEBROWN    286    286      286    0    0\n",
+       "4 2014-08-14 00:00:00            MIKEBROWN   3236   3236     3236   16   16\n",
+       "5 2014-08-14 00:00:00               NMOS14     18     18       18    0    0\n",
+       "6 2014-08-14 00:00:00            PALESTINE     28     28       28    0    0\n",
+       "7 2014-08-14 00:00:00                  STL    993    993      993    0    0\n",
+       "8 2014-08-14 00:00:00                 TCOT    106    106      106    0    0\n",
+       "9 2014-08-14 00:15:00            DONTSHOOT    102    102      102    2    2"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hashtagTimeCounts = (popularShootingHashtagsDf\n",
+    "                     .set_index('createdDatetime')\n",
+    "                     .groupby([pd.TimeGrouper(freq=(15,'Min')), 'hashtag'])\n",
+    "                     .count()\n",
+    "                     .reset_index())\n",
+    "hashtagTimeCounts.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that we've gotten the counts for a particular hashtag every 15 minutes, let's plot this over time as a line graph."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x5821df450>"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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JiQmzZ8/G1taWjz/+mMzMTKpWrYq7uzsqlYoBAwbg5eWFwWDAz88PtVpN3759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\nBEEQhBHv/we8UY1hH9a4wQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x58098f650>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "\n",
+    "for hashtag in popularHashtagsList:\n",
+    "    filteredHashtagTimeCounts = hashtagTimeCounts[hashtagTimeCounts.hashtag == hashtag]\n",
+    "    filteredHashtagTimeCounts.plot(kind = 'line', x = 'createdDatetime', y = 'tweetId', label = hashtag, ax = ax)\n",
+    "    \n",
+    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
+    "plt.xlabel('Time')\n",
+    "plt.ylabel('Number of Tweets over Time')\n",
+    "plt.title('Hashtag useage over Time')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Since the number of tweets using the \"ferguson\" hashtag is so high, let's also make this plot and remove that line from the dataset. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x4ba6a67d0>"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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p06hZsyYvvPBCtjXfq1Spwrp16wgJCeHdd9/ls88+U85NnDiRdu3aPXRP5hSCxMREBg8e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Chyk6oCTSe82ZGulDGJQCcEkqKlDGlwCRxUTYdWxNAE1Xr/2NIFrE6MLyYMUi8lXrjMaAZ6awan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\nK8N14YUMJUZwSg7cFhcBeykVj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FCyH13XcJhN+Sr0WCYG6KzzGUU128svAKB19BQXlxsB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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x527f45110>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "\n",
+    "for hashtag in popularHashtagsList:\n",
+    "    if (hashtag == 'FERGUSON'):\n",
+    "        continue\n",
+    "    filteredHashtagTimeCounts = hashtagTimeCounts[hashtagTimeCounts.hashtag == hashtag]\n",
+    "    filteredHashtagTimeCounts.plot(kind = 'line', x = 'createdDatetime', y = 'tweetId', label = hashtag, ax = ax)\n",
+    "    \n",
+    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
+    "plt.xlabel('Time')\n",
+    "plt.ylabel('Number of Tweets over Time')\n",
+    "plt.title('Hashtag useage over Time')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our thoughts on this visualization**\n",
+    "From this visualization, we can very breifly see trends in hashtags - as they pick up steam, as they persist, or as they die. What's useful about this, is that hashtags serve as both a method of labeling one's own post, or calling out other groups (that perhaps don't share the views in the post). Ferguson and MikeBrown persist because they are general tags which immediately capture, on either side, what is going on. MediaBlackout is more short lived though wildly popular, and was triggered after some arrests of reporters during the unrest in Ferguson.\n",
+    "\n",
+    "Since hashtags can be 'polarizing' in the sense that many label what could be perceived as 'sides' of an argument, it would further be interesting to understand who is actually tweeting certain hashtags across the US, thus exploring - are there communities that only tweet certain hashtags? Are they geo-located by stance?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Hashtags by Location"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Thus, to explore geo-located information, we create a new dataframe primarily of populated coordinate information."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "latLonPopulatedHashtags = popularShootingHashtagsDf.dropna(subset=['x','y'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>2014-08-14 13:13:07</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906566502776832</td>\n",
+       "      <td>-82.729054</td>\n",
+       "      <td>28.031176</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>370</th>\n",
+       "      <td>2014-08-14 13:13:23</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906630168088576</td>\n",
+       "      <td>10.711095</td>\n",
+       "      <td>59.927393</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>638</th>\n",
+       "      <td>2014-08-14 13:13:33</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906675026198528</td>\n",
+       "      <td>-77.034159</td>\n",
+       "      <td>38.926960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>816</th>\n",
+       "      <td>2014-08-14 13:13:41</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906705330036736</td>\n",
+       "      <td>-77.036776</td>\n",
+       "      <td>38.903024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>822</th>\n",
+       "      <td>2014-08-14 13:13:41</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906707519471617</td>\n",
+       "      <td>-80.503679</td>\n",
+       "      <td>43.414038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>919</th>\n",
+       "      <td>2014-08-14 13:13:45</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906723331981312</td>\n",
+       "      <td>-88.143910</td>\n",
+       "      <td>42.086162</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1233</th>\n",
+       "      <td>2014-08-14 13:13:58</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906779070087168</td>\n",
+       "      <td>-73.838375</td>\n",
+       "      <td>45.476223</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1307</th>\n",
+       "      <td>2014-08-14 13:14:01</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906790557904898</td>\n",
+       "      <td>-90.273212</td>\n",
+       "      <td>38.568488</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1500</th>\n",
+       "      <td>2014-08-14 13:14:09</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906825593319424</td>\n",
+       "      <td>18.378632</td>\n",
+       "      <td>-33.930716</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1608</th>\n",
+       "      <td>2014-08-14 13:14:14</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906846472540160</td>\n",
+       "      <td>-73.986029</td>\n",
+       "      <td>40.757285</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         createdDatetime        date   hashtag  hour             tweetId  \\\n",
+       "35   2014-08-14 13:13:07  2014-08-14  FERGUSON    13  499906566502776832   \n",
+       "370  2014-08-14 13:13:23  2014-08-14  FERGUSON    13  499906630168088576   \n",
+       "638  2014-08-14 13:13:33  2014-08-14  FERGUSON    13  499906675026198528   \n",
+       "816  2014-08-14 13:13:41  2014-08-14  FERGUSON    13  499906705330036736   \n",
+       "822  2014-08-14 13:13:41  2014-08-14  FERGUSON    13  499906707519471617   \n",
+       "919  2014-08-14 13:13:45  2014-08-14  FERGUSON    13  499906723331981312   \n",
+       "1233 2014-08-14 13:13:58  2014-08-14  FERGUSON    13  499906779070087168   \n",
+       "1307 2014-08-14 13:14:01  2014-08-14  FERGUSON    13  499906790557904898   \n",
+       "1500 2014-08-14 13:14:09  2014-08-14  FERGUSON    13  499906825593319424   \n",
+       "1608 2014-08-14 13:14:14  2014-08-14  FERGUSON    13  499906846472540160   \n",
+       "\n",
+       "              x          y  \n",
+       "35   -82.729054  28.031176  \n",
+       "370   10.711095  59.927393  \n",
+       "638  -77.034159  38.926960  \n",
+       "816  -77.036776  38.903024  \n",
+       "822  -80.503679  43.414038  \n",
+       "919  -88.143910  42.086162  \n",
+       "1233 -73.838375  45.476223  \n",
+       "1307 -90.273212  38.568488  \n",
+       "1500  18.378632 -33.930716  \n",
+       "1608 -73.986029  40.757285  "
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "latLonPopulatedHashtags.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def createHashtagHeatmap(hashtag):\n",
+    "    plt.figure(figsize=(10,7))\n",
+    "    subset = latLonPopulatedHashtags[(latLonPopulatedHashtags['hashtag'] == hashtag)]\n",
+    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "    ax.coastlines()\n",
+    "    plt.hexbin(subset.x,subset.y,cmap=cm.Reds,bins='log')\n",
+    "    plt.title(hashtag)\n",
+    "    plt.axis([-180, 0, -75, 75])\n",
+    "    plt.colorbar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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V1ZGbm4vFYkEURZ555hmSkpJ8lj948CDjxo0jOjqa69ev895776HRaNBqtUydOrVdo6ms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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x5285738d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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48WP5c39/f4KDgwkKCiIyMtLhioCu0lqLISQkhDlz5ijxEQodcDXgs7eorq52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ehmkqesZ3bt2UBw6803sWD+PL73wP0IIfjyq68BwbIlS/D6fOx5aR/HT5ykra2N5/a8yJvvvMem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\nL2AQXJImSbAAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x4b7971510>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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PsmrVKpefY1RUFBcuXOh3vMpQU1dXx/379+no6HBYIh0XF8fOnTvdGlt29+5d\nmpubu9S+kSSJ69evk5OTQ2BgoJz9deHChSxevJjW1lZu3LhBW1sb06dPd1qt12g00t7e7q5TGZGM\n7uge5/ToCmlpaaGkpITdu3dz4sQJOW+8IAiy/zUyMpIFCxb0eJBHjx5RXFwsfxZFUQ72fPFmLioq\n4urVqyxYsIDk5OTBnp+CwpjDarVy6NAhNm7cyIULF5g8eTIPHz5k8+bNGI1GYmNjB9x3XV2dvMLG\nnuvDYDDQ0tKCTqcDbLU23njjjQEt/y4oKCA/P5/Vq1c75LJoamri/PnzREdHs2zZMvm5kJGRgcFg\nYNOmTUP2Mm1vb+fkyZPMnz9/2DIN5+bmUltbK38eN24cs2bNGhGxY8ePH+9imZo0aRKzZ8+WP7e1\ntQ04fi43N5dnz57JeVuGG3e7Qv7V17WukO93DL8rpEfFIiMjg7S0tB4fVNeuXSMiIqLHH6E/BZme\nP/7NmzdJTU1V4iYUFJ7jgw8+YMeOHdTU1NDa2kpKSgplZWXU1NSgVqspKyvD29ub5cuX9+thf/Pm\nTRoaGpgwYQIqlQq1Wo1KpcLT05Pg4GD8/Pxc8nKXJIkrV67Q1NREfHw8ycnJcr91dXXk5OQgiiKd\nnZ2sWrXKbff/uXPnmDlzplufNyaTiaNHjzJv3rwRXT6hoqKCZ8+e0dhoe2l1dHTw8ssvu6x/nU7H\nW2+9xT//8z+7rM+BoigWg2fQwZv2JEP2mhaCILBmzRoHTXsgioWdM2fOYLVa0Wg0JCYmEhcXR3t7\nOw0NDdTX1xMZGUlsbCzFxcV8/vnnADx+/Bi9Xs9Pf/pTZTmqwpjBng0zJSWFyZMnc+LECbZv3+70\nGrcX0rKbpxMSEpg5c2a390NJSQkPHz7ssdR7S0sLn376KevWrXNZquvS0lK5lszGjRuHdYau1+vJ\nysrqsqR2KDl+/Licc2Ukc/78eSorKwkJCUGj0TB79mxiYmIG/XyVJInLly/T2trKli1bhrXqrR13\nKxa/9+17krm+8BcdDS7tbyAMem2SIAgsWrRI/mw2m0lPT5dTMVut1kGt47enKjabzRQXF3PhwgX8\n/f0JCwtj8uTJVFVV8cknnxAZGcn27dsxm82Ulpaybt06RalQGNVIkoRer6e9vZ38/Hz0ej27du2S\nzdLPB2u+iJeXF8uWLZNNyyUlJZw9e5YtW7bIPvvnmTRpEk+ePOHo0aMOD3f7vEMQBMxmM2vWrKGw\nsJBr167GROQhAAAgAElEQVShVqtZtmxZv7JvvkhcXBxxcXFyYbL9+/fj4+Mz4P4Gg7e3N83N7q0M\nqVarR7xSATgUeWxvb+e3v/0tSUlJvaaod4ZOp5MzuFosFpYtW/aVq0fyPKox+Jpya3XT4uJifHx8\niIqKoqWlhcDAwCF7+f/3f/83X//61xXlQmFUYbFYOH/+PAaDAU9PT3x8fPD19SUxMVFeOWEymThz\n5gzR0dEsXLiwSx/2FNUajYaAgAA2bNgAICcNM5lMqFQqtm/fPqiARavVSnZ2Ng0NDWi1WlatWtXt\nJMJsNtPQ0EBkZGSP537kyBGXmtj7y507dwBcvvrEGS0tLWRkZLB79+4hP5Yr+e1vf0tMTIyc8dXD\nw4MJEyYQExPj1PVWW1vLrVu35CKA/v7+LFiwYMRmT3a3xeL/+rnWYvG99uG3WLhVsTh48CCtra0U\nFBQwYcIEpk2bhiRJqFQqQkNDmTNnzoAuNkmSuHjxIp2dnajVaoxGI1OmTHEILlJQGA189NFHbNq0\nqcf74L333sPT0xMvLy+qqqrYvXs3ISEh8ks+PDxczmtQWVnJrVu35LaSJGG1WgkODnbpKouDBw8y\nc+bMbl/IkiTxzjvv8Nlnn7FhwwZmz57ttD7Fw4cPMZvNwxq4ffXqVQBWrlw5ZMcoKioiLy+PAwcO\njPrJj8FgoLKykvLycof07GD73SMiIpg7d+6IcHP0BXcrFn90sWLx531QLO7evcuvf/1rDh486PB9\nRkYGf/jDH9BoNOzZs4d9+/YBsHv3btlNOWHCBH7+85/32L9bFQur1Up9fT1BQUE0NTXx2WefyUvW\nGhsbWbt2ba8R7faIeHstAUmSMBgMrF27dlAmWQWF4UKSJBoaGmQl4M033+xX23fffZfAwECWLVsm\nxz5YLBYKCgrkKrFBQUE9WgsGi8FgICMjA71eLyfj6m7p6Pnz5+VKxWB7UM2ZMwcPDw+uXLnCjBkz\nhr1ceWlpKTk5OezevdulKxUePXrE/fv3mTJlirLqbYTibsXi//N37Xvr27qeFYv//M//5MSJE/j6\n+vLhhx/K31ssFjZv3syxY8fw9PTklVde4T/+4z/w8/Pj5Zdf5tixY32Wwa2KxWARRZH33nvPQXtS\nUBjNZGVlUV1dzYQJE5gwYQLjx48fdHrp/Px8CgoKWLBgAYIgkJeXh8Vi4bXXXuu1rdVq5datW4SE\nhBAXF9etq8RZnIad4uJiHj58CNhiCBYsWNClTPrt27cpLCwkLS2Nzs5O7t27J9dd6UsJeHdgsVg4\nduwYM2fOJCkpadD9HT58mKSkJJdmQFVwPWNdsbh48SJTp07lRz/6kYNiUVhYyK9//WvefvttAH7x\ni18wd+5cIiMj+dGPfkR0dDRWq5Uf/OAHzJkzp8djjJrE8k+fPiU7O5tdu3YpSoXCqKelpYUzZ86w\nbNkyl6djzs/PJzQ0lPv372M2m1m0aFGXwmM3b96ktLSUzs5O9u3bh4+PD48fPyY3N5fVq1fT2trK\nuXPn5EJu9tw19gy4YFMugoKCWLlypYMCMnnyZNnNYTabuXHjBtevX5etk4IgEBMTw9atW7l27RpR\nUVEDrpA6lGg0Gvbv3092djb37t0btGs1KipqTJRkV3AtKtzrClu/fj2VlZVdvm9vb3dwwfr6+qLT\n6YiPj+fNN99k3759PH36lG9961ucP3++xwR5o0KxaG9v58aNGxw4cGC4RVFQGDTV1dVkZmby6quv\nDol/3VkJ9xd58OABa9euJSMjQw7Ci4yMJDIykujoaKKjo/s0S29qauKTTz7Bw8ODjRs3dvGja7Va\nli5d6vCdKIpUVFTIlpT6+vq+n9wwsGzZMg4fPsyUKVP6VKK+O5YvX87HH3/M/v37XSidwmhnpKwK\n8fPzc8iC2tHRQUBAAJMmTZKT4cXGxhIUFER9fX0XK+TzjIpsollZWb2Weh4OzGYzJpNpuMVQGEXU\n19eTmZnJSy+9NKxBe6+99hr19fVs27ZNnnm8+GDpCyEhIezZs4e1a9fyySefyGbknlCpVEycOJG1\na9eyfft2t+aNGCi7du3i/fffx2AwDLiPjIwMpY6RwojhxSiIhIQEysrKaGtrw2QycfPmTZKTkzl6\n9ChvvfUWYFvh09HR0WsM1KiwWKSlpVFYWMixY8dGxNKsxsZGrly5QlFREaIo8tOf/tTpfpIkUV9f\nT1hY2LCW71YYGbS0tHDx4sURUUlTo9G4tEqoj48P+/fvJz09XS42BTZroysTag0XHh4efO1rX+PM\nmTP4+fnJq1/syqE9QLY7ZdFisdDc3Dzqx0HB9QzX9MJ+rZ4+fRq9Xs++ffv4yU9+wje/+U0kSWLv\n3r2Eh4ezd+9efvKTn/Dqq6+iUqn4+c9/3uv7bFQFbx4+fJh9+/YN60v69OnT1NXV4eHhIRdTe/Fh\notPp+PDDD4mIiCAsLIy6ujpEUSQxMbHH7IcKY5uPP/6YvXv3jujf//z58yxdutRlOQYePHiAj48P\n8fHxLulvJNDY2EhRUZFDrInVaqWqqoqkpCSnsRhnzpxh5cqVSnzYKMDd777/CXStsvn11uF3LY5Y\ni8XBgwfRarX4+PggCAINDQ1s2rSJEydOIIoiaWlpvZZxdyWSJHH8+HHmz59Pbm6uvL7XGX5+fowb\nN65LeuTHjx9z6tQp+YEUFRVFcnIyKpWK1tZWWlpaCAoKUgK8xiB2y9VIVioA1q5dy8mTJ11mGbRY\nLP0qrf7gwQPy8vL42te+NujVMUNFaGgoS5Yscbrt888/58MPP5QTQHV0dNDe3o7ZbFaUCoWvDCNW\nsXjppZdIT0+XYxhEUSQwMJBdu3ZhNpv59NNP5RoigJxN0NX55iVJIjMzk9raWlatWoWnp6ecQ8OO\nyWQiOztbrv4IOE1Rm5iY6FAivrKykosXLwIQGBhIYGAglZWVclphe9R9cnJyl2MqjC7u3bvX7cto\nJKHRaGhpaXFZf9OmTePKlSt9qoR68eJFQkNDOXDgAB988AFf+9rXRrwi9iJJSUkkJSWRn59PQ0OD\nnDl169atwy2awgjF3atC3MGIVSw8PDzYvHmz021ardZpsaTs7GwqKytdFuhpX2u/evVqOQufXq9H\nkiTq6uq4d+8era2taLVaVq5c2e+Xvz36vidaWlq4c+eOrGykpaWNiNLCCv2js7NzxP9ukiRx9OhR\nlwYYenl59SngMTs7m/Hjx8s5HrZu3crhw4eHNb33YFCSXyn0lZGyKsSVjFjFYiA0NDSwbNkywFbm\nNycnh5SUFLRardOMnuXl5fj7+xMUFOS0v6lTp1JYWIhOp5MtEN7e3kiSRElJCUuWLBlyd0xQUBCr\nVq0CbJaRc+fOyZUgR/qLSsGR9PR0Jk6cSExMzLAV2uoOi8XC+++/z5YtW4Ykg21mZiYzZ8506uZ7\n+PAhkiQ5JI4KCQlh9erVHD58mP379486y4WCwleZMaVYTJkyRY7BiIyMZN++fXz00Ud4eXmRnZ3N\nuHHjaGxsxNPTE5VKRXZ2Nv/0T//UbX8+Pj54enp2WVKalpY21KfiFA8PD7Zv347RaOT8+fOIosjS\npUsJDw8fFnkU+s62bdvo6OiQFd6ysrJ+pe4ealpbWx2SX7mSnTt30tzczIMHDygtLWXfvn14e3vz\n4MEDCgsLCQ8PZ8WKFV3aRUREsGbNGj744ANeeeUVRblQ6Dc1NTVkZ2fj4eEhZ4utq6tj8+bNQ5ri\nvj+MxfWCo2pVyGAwGo00NzfLloeMjAxmzZrV7fKvkpISsrKy2LFjR7cWjeHGZDJx48YNOcHQ89kP\n7TeRJEksW7aM0NDQ4RJTwQnFxcW0trYyb9684RZFxl7Mz2w2s3nz5iF5kdvTZGs0GpKSkpg2bVqv\nbez1RRTlQqE/NDQ0kJ6e7uBOq6io4MaNG+zatavbdu5+9x0Kcu3E8NWWOpf2NxC+MorFi5w8ebJL\nnEZLSwtZWVkYjUbi4+Pp7OyktrYWlUqFSqWis7OTHTt2jCoXhCRJo9pXPZb58MMPR+Tv0tDQwLVr\n13p8+LqbhoYGLl++3ONqLAUFO/Zqum+88YasjFZWVpKZmcncuXNpampCEAR8fX271G5x97vvAxcr\nFq+MAMViLFpheqS5uZkjR444uA/sybdu377N+vXrSUtLIysri4SEBHbv3s3OnTtZunQpVquVsrKy\nYZS+/wiCwJw5c8jPzx9uURReIDU1lcuXLwO24l9Pnz6luLh4SNwR/SEsLIypU6eSk5MzrHI8T1hY\nGIsXL+bUqVPDLYrCKCA3N5f169c7WLiePXtGSEgIgiAwefJk4uPjuXPnzjBKaUMlCC79GwmMqRiL\nnrBYLHJZ5927d6NSqZAkifz8fAoLCx1mjp6ennh5eeHn58fdu3cpLi4mMDBwyGo7DDXTp0/nwoUL\nXL58eWhSCksiWCy2fwUVaDS2fwEkCUQrWC0gCKBS2/4E4YttIogW2/9ValBrbNvsba0WW3tBAJUG\nVKrn2lptf5Jka2fvd8hlMtv2EYQvtg1MpqjI8ZSUlHDy5ElUgsDECdGoBTh1/BiSIICgIjIqivnz\n5tlmAHaZ1GrbWDiVSWXbPhCZVCpQa0EQSEpK4vixY7YxksfpxfF/bpy69PuCTBoNIHSVCbqOv/13\nf0GmmJgY9J2dZF6+TOqyJQOQSfziehrANWFvK0kOMn3Z1gLW4bxOncg00u+dIZSpuqqKxYsXI0kS\nkr4dmqpYFOELiRMRgsIRNFosFguBAQFgMTnez5L05XEVBsSYVyyampq4cuUKKpWK1atXExgYyMOH\nD2VzV3JyslNz9Ne//nUuXrxIYmIie/bscbfYLmfDhg1UVFTw/vvvs2rVql6XufYJiwnMRtvN/jxm\nHG96XpyBC44PjC4Itjy3zmbu3fVrMSInxxWEHmSSvmjWX5n48gHotN+eZLKfT1eZVsxP7tJ2xpQE\nWabKqmpOfHwYUbSwaMF8JkRHg6WvMjk5V7tM3Z6r/kt5TZ1g7HhhDJ4zcj7f1mLso0wM4JrQy9vL\nih4xe+aMF47Xy7ki2fZx6XX63Dh1e532JBO9XKdDJZOTfodUJvsuTq6JPsnU/b3T0/1s1bdTf/0C\nIRYdGDpBssrbJK0XFt8g3rtVwqv794BJ79ivsQO83JfMbCyqMGM2xkKSJG7fvk1VVRWbN2+WAxvL\nysp48uTJV7oY0Lvvvuua5ENmI5gHXpRJoe9IkkRmVjatbW1s3ZQ25Gnta2vruHH7Nls3Dc8KqO44\ndfZTJEli3epVI27JrsLIQDKZEMse894ff8+ry1IQQoMRNF9mcbWoPXnvRiGvfOs7+DiJlyt6XAze\n/m57930c3H2V0IGwr7nWpf0NhDFjsbBarZw/fx6j0YharUb4wnRqj7rPzc2lqqoKf39/1q1bN8zS\nDi+pqancuXNn8EWotJ6g8fjS5Go1dz9jURgUgiCwcsVyWltbOXX2U/n7qMhI5s9NcamL7knpU/Ju\n3uKlvcNf8O9Ftm3ehNFo5NLlq3R0drJh7WolK60CAGLRQ6xnP4SmemhrJqCsjtKWSlrVHiQnTEL9\nxl8ijIuktamFkHorly5fobm5hQMv73dYUacweEa9YtHU1ERWVhYmk4mNGzdisVjIysrCYrFQXV2N\n2Wzm9u3bpKSksGjRouEWd0QQGxvLjRs3qKqqYuXKlYMrOCXHGQg2xUJhSAkMDGTH1i3y57Jnzzh2\n4iSCIODj7YO3txc+Pj54e3kRHBxE+Lhxfa65YTKZOHnmU6KjInl538h1/3l6erI5bQOiKHL2/AW8\nvbxZvXKFUkH4K46ka4WacjDYXBtGq0hxWydPdY3MCfIB3wAEjZbw8HHs2r4NsFXfPXbiFPt27xw2\nuRVXyAjBbDaTnp6OXq8nNDSUBQsWkJWVRXt7O8HBwSxfvnzEFjAaSRiNRtLT09FqtWzYsKH/HVjN\nNneIKNLV76rgTiRJwmw2o9fr0esN6A16mppbqKurp6Kqim994w2n7fR6PTmf5aFr1yEIAhvXrcXL\ny8vN0g+Omppabty+La+mEUWRlDmzmdSH+iR944s4DYURSenTp+TeuIWvrw9iZwftT4pYGhFMjIdA\np9aLk0XPePW730MIDHFq2fv8UQFtOh2LFy4A3O8KORrSta7UYNjTVOPS/gbCqFMs0tPTycvLIy4u\nTk6nLQgCq1atclmp568aZ8+eZfXq1f3Pz6HEWIwKTp45y/YtXevuZOVc53b+Xb7+2qsEBAQMg2RD\nx2d5N2hobBxxMSIKrkOv13Pm3AUix0ewbMlih23Z1z+jpbWVLWkbefDwc548fQqAwWBk8/o1+FiN\noFIh+AcjqNRcybxGa1sbsRMn2p6DimIxKEadK2ThwoXExcURGxur+MX6ycmTJxk3bhx6vZ729na2\nbduGIAjMmDGDkydPsmvXrv5VhtV42JaMiRbH5Xj9nt31ZUY4kFmjvc1g2g6HTN1tG5hMoug87mX5\n0iWoVCoePipkyaIFQyCTK8Z/YDItXriAjCtXaWhoJCws1Emb0XZNKDLZ20gSpGdcpqOzgx1bNzu1\nTqtUKuJjYwGYOSOJmTNmYH18C6uuhUP/+hZb5iUREuCH5OEFnr6smBaHOnwiF9IvERgYQLC3+yap\nY9EVMuqckgEBASQkJChKxQCwWq3Ex8ezaNEiOeU3wKRJk9ixYwcnT57sX1IkQbDlTNB6gtaLgZuM\ne24jDdjVIr3w70DaDnaf7tr01La7ba6XaeniRdTU2mc4rpbJFeM/cJlWpa7gxJkznDxzlorKShfK\nNNh9umujyNSXNoePHGXOrJns3La1W5f3s/IKpk+b6thW14y6s5WXV8wl64HNIo/JALpGhC+eMevX\nruZ67o0ByDZwVC7+GwmMOouFwsARBIGOjg4iIiK6ZHf08vJi79695OXlUVRU1DczoNUMZpPNWtFl\nNcjAZy2SKCK1tyAZ2kHXDI3V4OsPQREIvgEIfo7Lx/ra79DP7gayz2Bl6r1fD60Her3eiavLts/E\nmBjKnj3rY0yC+y0uA5VJpVLx5huvI4oily5fpbW1jRlJ090s00D2UWTqaZ/1a1aTf+8+a8NXddvW\ny8tTbmsyGfmvdw4SNS4UOtpoa25kzaKFNleuUQ+6FqSC+1gjYyFmMhFaJZ5msCiKxVeInTt3kpmZ\nSUNDA+3t7U73mT9/PqdPn+6bYmHPsueUQcxajJ1IBbm22YQdkx6a65BUapi7thfFwn0z/sH3O1iZ\neu933ZpVfHLqDPv3vFj7w7bP3OQ5nDh9po+KxciyuDi2cd5WpVKxfu1qTp391IliMRavicG0Gfky\nhYaG0NjU1G3bzs5ODAZ7AjWJ67l5vLRnNyEhwbZvJAmx5CGce9+xYekjKH1EcrPzZ+NQMRaTfCqK\nxVcMe30Ks9nMpUuXWLt2rcN2lUqFv78/x48fJygoqOcVNhoP211hT8NrtWK72V+84Z+fcfRhpuvt\nh2pBGljMSGYDktmEoFIjeHiB1sOW6rdP/fY0u+6nTL1+19d++yKT/Ukz0PNxxMPDk8SEeB48/JyZ\nM2Z02U8QBKxW6wDkHbhMrhn/0SLTWL1Oh0cmk8mMyWRyuk0URQ4fOc7rB77Mpjxj+nTOp2ewP8oH\nmmuhrdlmCVVrwcMLNGqYNBVh+nwE3wBUFVXdyDc0CGMwykJRLL6CrF69mvz8fM6dO8f48eOZMWNG\nl+1gq/b63nvv8Y1vfMN5R4JgUy7AplgYO7uxYEjd/N/5foK9b60HgranYNLe+u1pJts/mXr/zpUy\n9TZr7L9MKclz+PjYJ4SEBBMVGemwtb29HU9PT7fL1P/9Bi5TW1sbra1twyTTaL1Ou1MChvfeOXL8\nky55J9rbdWRm5dDS2sqendvkGLz6+gau5+VhMhmpuf85462djl3qbbl3hMg4VBETbP9XD3910NGO\nolh8RUlOTiY5ObnHfYKCgnrOami12nL6S6KTXBYjbdboCpkGY0kYiEw90X+Z9u3eScaVq9zOv8fm\njetRqdSAxPn0Sw5Jt7r2MRCZBjr+g5khd0Wna+diRgaSBClzZmM0Gr9QooZSpsFYA4ZKpu7266lf\nV97P3V2n/ZOporISXXs759MvAQKiaEUUJfx8fVmzKvW5HCwCktlAXs41EsJDmTotBuGpCjo6bLFh\nej2YjLYJjMWMdP081qZahHGRiE06VNHKqpDBoCgWCj1iNpsxm83O3SGipYdsm6NjJvv8Nslqta1t\n7+L0dMWsfSBte2Jg/a5ZtZKWlhY+/PgoIcHBdHR2MDUxEY3G2aPAPTL1fVvvMomiSNHjYoq+KD/f\n1NSMr68PgQGBZH+Wi7+/HxNjYoZYpsFYKIZKpu72c6VM/W3Xf5kmREfz7Te/tKA+v7rtxbZiWQFp\noZD7MI+PLzVw7UERgb4+/NWejYT4BkDxwy8mRAAdcOsyEiDVt8C3/rEXeV3HWFQsRl2CLAX3YbVa\nMZlMHD16lL1793bNyCiKX9YHkQM5+zszeX7/F9v2tM1ZXy8ep6e2IBo6kKpKbCmAjR22YFGNB3j7\ngqcPQnQiKi/ffsg7eJm676e3GXL/ZWptbSUwMKgfbYdKpsG3bW1t5ez5i/j5+TFlcgKJkxP4/FEB\nlVXVbFy/loefP6K1TcfSxYt66Pd5XH0+Q3VNdNd2OK/TkSGTJElgMZN/5zaPCwrYvHoFPoFBCJ7e\noPEE0Yqk77CtCuloo9MiYfLyo7S+gYDoOLe9+06HRva+Uz/Y2ljt0v4GgmKxUHCKyWTil7/8JbNn\nz0aSJN566y3Cw8MJDw/Hx8eH1NRU/Pz8QPWcWdnQ0cMqETv9md31debX23G62a+1EapKHL8zG0Gv\nA0CImTZgmZ5//PVLpm63u36cbG6u7l6Ggz1uf2QaXNvMrGxaWlt5ae9uuV5IbW0dz8or2Jy2gYaG\nRoqfPPnC3WP/ZQY6/oMdp+7aDUam/m4bzTL1tt+X2yVJ4viZT4mPjWX/61+Xvzt/8RJtOh0eHlo5\nFkOSJHx9fPHyMvC07BkLouN6OYbrUI1Bk4WiWCg4xcPDg8TERFJTUwkODsZqtVJUVMSzZ89oaGjg\n7bffZtaMJNauXIEgSTjmsnhxdtGfmd+LvDgT7KltT/5cJzPKkAiESTOQTHqbUmQy2JJ9efogePnY\nzKw9SPa8TJLFhGQygKEDqaMNBBC8/cHLF8HTG8Ee5OqyWXvvMnX/EnU2Ts7kcI1lpCeZPj1/EYvV\nZumSJBFBsCkGVqsVlUqQzdxfGlYFh+V5FouVeSnJTIyZ4HCMixmXOfDyfkRR4g9v/yczpk/jwcNH\nzEia9lz7wYxTTwzEutHdNT5U10R3MnV3TQxEpt4UExffzy/0+8vf/Aupy5dR+LiYp8+eoVarMZnM\nrFi6hIiI8G5lGhc2rgeZXc9YXBWiuEIUusVsNpOTk0Nrays6nY5XXnlFnhFmZWWh17XS3FBPRPg4\nUpcvc2np7p7py0zKvf1aH2RBS73zjXGzUUcnuF2moWPwMomiyAcfHWFV6nKio6IctqVnXOHj45+w\nYe1qtFotoiiSPHsWsZMm9anvK5nXmJwQz4ToaB4VFFLf0EDq8mX8+l9+z3f+1zfw8/PDarW6IXvv\n2PztXN/v0MgkSVD0+DFTEif369nk7iJkn4ZF9b5TP9jU4N7lss5QFAuFPtHW1sbFixfRaDSsXr2a\ngIAAbt3Io7SkmPCwUGpqaokaH86yJYtfuIl78rPaP/dnJtJTP9C3B9RgfL/OZZKsFiST0Zbcq1MH\nSAjefuDpi+DphaB2Zhzs6/kMxqff33FylcXC+cui5Ekpd+8/QJIkNq5bg4+PD62tbTS3tNDc0kJI\ncBBxsbF0dHRw4VIGKpUKXx9f1GoVTc3NzJoxkymJCS8c80uZWlpayLp+/YviY44yXr56jda2ViwW\nmzVEpVIhSRJb0jbi4eHpsO/gr9PuxslV1+lAZBrqe2eoZepOAXHtvVP0+LFbFYtzLlYs0hTFQmG0\nYbFYOHToEOvWrSPqi5nmgwcPePDgAcsXzCUzM5MlixYQFxs7vIKOaL5KM1kbnZ2dfHzsE5Jnz2L2\nrJnk371HaVkZGo2GkOBggoOCCA4Ooqq6hpInpaxOXUF4eDgg0d7eTt7NW7R32FawTJ2S6PQYxSVP\nuHHrtkOshXO+PNfjJ0+xfcvmflgvRuKMf6gYeVYId+Bui8X5ca5VLDbWD79iocRYKPQLjUbDa6+9\nxs2bN/ns6mX0xQ8I0wpYq6soqy7g5Q1pHL2WSez4cPD0ln3mfZ8h08vnvvjw+9uvu2XqbSbbk79/\nIDL1ZdY4dLPr5uYWTp75lO1bNpOZnU1JaSnJs2eze8f2LjJFjh9PbV09xU+eEB4+DhDw8/NnzaqV\nPcp0J/8upWVlvLJ/b59ksn9+WvaM9z/8iEUL5jN1yhRcM079vSa6azuc1+lgZRqKcXLX/awwWBTF\nQqHfqFQqFi5cyHx1B28feRs8tVhEkbqWWp7UFqOpbsTS/Dmab/8DeL5Y+OpFpG7+35fPfd23P/2M\nBJmc9TkYmQZ63P7MOJ23raquJjMrh/i4SeTk5rJ54wYnOVFs+0qSxJ/ePcj2zZsZNy6sXzIFBARQ\n9qy8TzI9//kHf/E92+qBk6desIQMZpwGek30dpye+voqyTRc9/PQMBZVGUWxUBg4MVNYtHELqo5W\nZgR4gIcnh580MmvPVkqDx5Go8aD3WUlvM/OetnfXX3d+VZ7b3l2/rpbJ2fFHukx96bd3mQqLiigo\nKsLDQ0v4uHBWLFvWo0yCIBASHPKcUtF3mU5/eo5VK1Zw/8FDNBoNGo0GQRDQ6dpp07URHBTEzBkz\nUH2xtu/uvftU19SRtmEdgmA7tslkwsPDo8/HHPw4DeSacHb8/srUU39jRabB3jvuQzUGVQtFsVAY\nMKrwaJL/7G84duwYs3btAn07m5qbOPLJCaZ5BzJFbUsZ3T39nZl3992L2wbTr6tl6mu74ZbpeRP2\n4BWnUFUAACAASURBVGW6eu0aJpOZlpZWtm/ZTHBwUJ9kch6837tMb77xNVrb2rBYLFgsViwWC6Io\nMm5cKAnxsTQ0NvHHt/+T2EkTsVisTJwQjcGol/vz9fFFr9c/p1h0d0xXjtNA+u3LMfuyfbTK1N9+\nh+reUegJRbFQGDhfZLZTixasnW1oBIHg4CDWrEwlIT7uuR178/HDwGd3Pc08emK4ZHLHrHF4Zfrd\n7/8vkiQRO2kiB17ej0aj7eWYX/5/fEQEz8rLybhyjYXz55I0fZpTmYxGA0eOn+TAy/sBCT8/P1vC\ntm5kqqmto+xZOUGBgWzasJ6QkBDuPXgo58dobWv7IgtpX66JgYxTb9fpQGbXQ33v9Hau7papr9aS\nwcrkXsaevQJlVYjCIDAbwWzg/oOH+Pr6Eh8XO9wSKYwAuq/f0Le277x3CB8fH7y9vZAkCa1GiyiJ\nqAQVmzauRxRF3nnvEAEB/uzZuWPAcj4uLuHho0cALFu82IkLRuGriLtXhVwaF+3S/tbWV7q0v4Gg\nWCwUBo5KDWoN8QnxXL+eS2xoMJZbuYhV5Ui1NUh6PcK4CFQR41EnzUI9eeoXL5ye/J+9MZi2Q9Vv\nX9q6+1z76uN3vUzdKxW9yyQIKmbNnEH+3Xs0NDQSGRmBn68vTc0tjP8iW+KHHx9lz87tPCuv4KOj\nx9mSthFfX59+n0/i5AQSJ0/uVabh++2Gql/l3um9rftwW15BN6IoFgoDR60BtQZfT186rWD4z/+L\n9dol57suX43PD//+i089+T97YzBth6rfvrR197n2xcc8MmWal5LMvJRk7j94yOOSEqpravDy8qKp\nuZmTZ86yZmUqAQEB+Pr6YDabqamt/cL1NtbGaaj6Ve6dvrV1D2NQr1AUC4WBI4kikq4RmmsRK4pQ\nBfkiTZ2G1NyM1NQEFjMEh6AKj0QVHIokighOExcN3+x6YG37368kSWAyIHW0I5mMCF6etloiHp4g\nvFgtoLt+3TdOtsqQFlv1R2OnbS/fAFtuEodkUo5tJVtjsFqQzEYkixlBrUHQesEXKzXsPCl9SnlF\nBW06nfydKIo0NjbxzTdeZ9bMGcyaOdPhfCwWCzdu3SEzO4fYSZO+iLEYvnEa+n4VmUa2TArOUBQL\nhQEjVRQiFeRiMlvQtFSjXTAb7ZSJSJKE2NqGMHEOmqlJCJ6evfX0wr993darhEPUtn/9igV3kHIv\ngq7ZoQcJAYLCUL30F+CQ26G7ft0zTpLFjHj2PagoAdHquJeXD8Kub6EKHe+8bUs9UslduUKsfYsE\n4OGFKmUNgtYTURQ5fOQY3/v2/yIgIACTycT59EtYLBb27Nz+ZX+SyOPiEj4vKABsCdrmp6SwZNGC\nPp9P37f1xti+Tt3TdqzJNHjGYhEyRbFQGDg+gRAaRVlREZMiwm3OQr9ghJBINL4BEDjuhdntcDNM\nM5IJ8Qie25CaauHJI2ioBB9/CA4DXz/E4ts2a4BPAELQuOcqoboWqVOHVF4CzXVIulbw9EIICIao\nWITQyC9/K40WYW4qUnwSVJZCWSF4+kDiLISwKPD26/4gvoEI8bNs9VKaakDXBN7+EBqF4BuAwWzh\nUvplDAYjb77xNQICAsjMyqapuZkNa221QwAaG5u4mpUFwLQpU9ixdYsbi9y5ElfHDgw1vVnLRhKj\nbWydo5RNV1B4DlVYFIRFUdYgsXxDCoIaBA/PEax/D8+DRuUXCH6BEDcdae5KxPtZ0Nbw5Q6NVUiN\ntvz+UlQi6viZLpdB0rUgfvCvttLwz38PNoXw5e8jhEYAtkeyMCEBJiTAzEVIVjOoNH16sau0HhAc\nAcERSNGTwWpFbzRyPfcGbboiPDw8WLMyVVYgwLbUc+e2rYCtou7JM2cJDAhkx9YtbqhAOtS4OnZg\nqOnNWjaSGG1j+9VBUSwUBockote14evvD1YLSOJwS+QihmbGIwgCgn8IkmgBQydYTF9sUIFGCyY9\noqETQesBKrWTSrEDlEnjAeOioL0N2ltsvxWAlw94+SC1tyD5B9msFS/EwQhqbQ/H7l6m65/lUldf\nj5enF0sWLSAwMNDpfm1tOq5ey0KlUlFVXcO2zWkOikf3jMTZ9UicKY9EmdzNyB2D/5+9N4+O6sjz\nfD/35qbULiGxi82AMdhmMcYsFjsGY1ZjXJRdVLnLU939aqpmptw1PVUz51W5esZmlpo+PdXdnnnv\nTXVNu8o23tmMsY0NXjCYfTf7JkCAQCAhKfcb748rpFQql5s3by4S8TlHR8qMiF98byhu5u8XETci\ndwMx80jHQmKegA/h9xDye9q/ILsN6fsQUgePAkYhggFEw3XEyX0Q9On7gly/iLh+UV9/UVCCcu94\n1PyilDUp7nxsS3+EEBriVj3iyNfQ1ABuN9hsUHMUreYo2BxQ3ht12FgUNXy0ILlIdsfOXRTk57eN\nRMTjme8sp6GhAa/XR/WUyUlcVS5G17n45ZWLmjJN7rZBJh0LIQQvvvgix48fx+l08tJLL1FVVdWW\nvmbNGv7pn/6J4uJilixZwlNPPZWwTDSkYyExj6Kya+8+Hn5oXLaVdEkUuwOlRx80TUO0NELdRfA2\ntSYCfg/i3BG0ojIoLEUp7oFii3/LiqAfcesGtDQggn4UVz4UlaMUlqKoKoqiopRVoI2bgWi8AY03\noL5Wf4IH9Cc6Gq6jnTmMkl8EpRUo7qK40yBC0xDXryJOHILrV6hr8VJf38y8733f0GZZiqJQWlqa\nTNNJJBITbN68Gb/fz+rVqzlw4ACrVq3ilVdeAeDmzZv87ne/Y+3atRQWFvLcc88xefJkjhw5ErNM\nLKRjITGP3UF+WSUtmg2c+RDwdqOpkMyhVvYD+iEGjEC7ch7OHYZQQB/BqK9F1NcCIBwu1HGzUBzR\nn7LRzh1BXDnXYfSobb17QQnq6Olt0xxqfpG+gLT3IISmoR39GhrrQQuCPwhXzrStvxD9hmMbNDKm\n/uB///dwtQaC+vRKzY1GRrgchC7sw/a9n6A8OCHFFpJIui+ZfCpkz549VFdXAzB69GgOHz7cllZT\nU8N9991HUZE+QvrAAw+wf/9+Dh48GLNMLKJtKiCRGOb+UaM4euSwdCgMIITQH+X0eRGhIJG76SuK\nguJ06eseIkYmBArC40W7eQPh83YqC+hrNBwufb1GB8M2CPjB04wIhToVU1RVf+ojmsNid8XcGlAI\ngQj4wWHTNbcyrDifvTea+PDyLa7U1upTPtFPDpBI7nr003Wt+4lHU1NTm+MA+uPbmqZ/dg8aNIhT\np05RX1+Px+Nh+/bteDyeuGViIUcsJOYJ+CHgxUFIH62QREVrrEfUX9EfM22d6hAA+cVQ0Re13/C2\nRz3VHn2gRx+E34douEbwqy0EjxwidOwYNLcA/wgOB+qI+3HMmodj6uy2DxO1/3BEv2EIbzPcuo44\nvAOu18KtGxAKoe38XHceBgyHsY9i6z2gTaNt2Dh9/UVzIzRc1/evKCpHKSrv9MhwqL4W6q/CjcsQ\n8KGOH687SjcbEDfrIajRY1ATr+04iPvkYXoVaLrjUtlfv9YOe3ZIJJJMUVhYSHNzc9trTdNQW0cx\ni4uL+cUvfsFPf/pTSktLGTVqFGVlZRQVFcUsEwvpWEhSQ1G6dDQqhNAXod68Br5mcLj1dQV5Bdbt\nm6Cq7T93UBT9rJXI0YVWTUILgaaBTQGHHcVma19+ptrA6exor82sguIuBHchodsNoDqguRlCrR8M\nAR9cOA5BP9qA4dBvCEp5z/b1F4WlUNh5vYMQgpuXajm25Svq9u+mvMjJsPsHcqzuBnW3btPsD1DS\nsw+4y8kvzsNma+C3fzmKIndeu+Yo1yqR3O1k8q4YN24cW7ZsYd68eezfv7/DQWuhUIgjR47w2muv\n4ff7ef7553nhhRcIBoMxy8RCOhYS8zicYHeg2VzgyNPn9rvQlIh28xri7CHdoQifIlBURF4+6qhH\nUfLcKdejtn5Zi6p7QQshQkF9EaZq7zR0qd24jDh/VH8UVQthKy/ENmUCYsojEBKoIyehlJSjOBNv\nomUbPhqGj0ZoIcSt64g1v289kdYP548jzh8HVUUUlqLMewa1Z/RTFve89wHr/tNvuVlzCX+LB4Hg\nFhoX7Qp5xQUMX/AYrqJC/u3i79Cvb1+gdUQmFGrd0ls/rK5rbnAlkaSXTN4Vc+bMYdu2baxYsQKA\nVatWsWHDBjweD8uXLwdg6dKluFwufvjDH1JaWhq1TCKkYyFJCU0IVJutax7Rp4X0pyEi1x0ITX/f\n4mtSFEX/go33ZIem6XtMaB01KQhwOaCwMGL771bJres3FJst4jFR9NcuN8JmA2+wc33eFt0JEBpK\nxKiC0DR816/juXYdv0ef7jpBkGY0yoM2KoWNv/nlv6Oiqn8Hx0EBsNlybOdVieTuRlEUfvOb33R4\nb/DgwW1//+QnP+EnP/lJwjKJkI6FxDzBAPhauFF7EU9DPW536tF9JlF79EGU9UI03YLb9QifR3/i\noqgMpags4aOdadFU2R/Ro4+uqfEm4sZF/Ys/EIBgALHnE4TTDRX99DUaCH3Dq9b1DkK1QWlPKO2J\nUlmF2uqEKAXFqCv/LaL+Glw6g7hyvnXqxwn5+YjTexDnD0GPvlBQivfQMQKnTuHd8hkDay/zL6vc\n1PZxcxEn/YoKGTRsIBMeupeBQ/vjuLAb7eoR6NEfSitRy3t1y01/JJJ00B1H8qRjITGP0FAVWPnM\nCt5bu56nly3NtqKkUVQVpbgcisstty2EQHhu64shHW6U0goUe+KFi4pqg8IyfTrhxiV96iJ8gx+/\nR18IWi5AhPR9KAI+PU1rfX3zGiLoQyvvg1JQrK+fUFWUit5Q0RttwD36o6m3rrXvwhn003TiMKcO\nnOL62s3017yUOPTdP4UCVQVOBo96gMZ+/XhmwTT9HJA7U18+D9y4CO4CC1tQIun+dD+3QjoWklRw\nuMDuxB4K4HLn64vzutAai3QhgkG0b7frX7a+Fn3TKUDYHZBXgDJkNGoMR0a7eQ1Rcxy8zboDcQe7\nQ1+TMeJhFHdxhyPIhRgDwQBazTHd4QgF9Z8LxxAXjiNcbsgvQr1vYvs+FnfO89A0CPpZ+9e/5tRX\nO7lZew3fbf3JFbvTiaOkgEkL5vFNgZ3J1dU0tLSwcGo1amWFPoUU9OubYNkcnY5Fzx65u32zRHI3\nIJdpS1JDURCqnTJV4fg3O7r0EyKWIULQfFt3DsLbIxjQt9GO86iW8NzWRwLCnYo7ZYN+FHchisPR\ncT2DoqA4nPpGOwFf+wiEblF3brzNUdeMKKoKDhfXa2q5cvJsm1MBUOvzsOPqFdSePVny9HIuXLnC\nlEmPUFlZoR9UZrOhuNyoefmdNGUX2QclXQfF4p9cQI5YSEwT2LuDwFuvol25xNi6q2y8cgN11P0M\nmDkbdcBgbGPHo7qi7xLZnVEcLtTxsxG36qClEeH16Id7ufKhpEI/Ij0MreYU4mYdXDwDNSf1UZ+K\nnvqJqL2qUMoqIE/fXps4R6org++H3gPh1g2ErxkCfpTW0QqltLLDF7/mbYGmW4jmBrhxmZU/WUjt\nEw9x9lgNN+oaCLlLqXOoXEFjxr/+C1yFBZw9f77tqQ9JIuSoicQYueOQW4d0LCSm0S7VEDq4p+2p\nivkVJaw/eJCmMyfo73Bie+FFSiZOwFZg5KTK7oVid6JU9EMEe+ojEK58fbQhyoeIOPwNnDvWcaTh\nyiXIu4UyfjZqRR9jdSoKSn5x66LOBDRcR1z4Vh/NAOwOO1XDB1A1fAAUlnE6vx///PpqNE1jw+bN\nlBSX8NDYMYZ0SEA6FZK7GUXEGLs+ceIEgKHNMCR3JyIUQjt/htDB3Wi1l7jy6Zc0XrzGmouXmK3Y\nIBDE3qMcV79+FI0fw+Bf/jWKLZp3fie6ixblxUtLRLrKxrcrQiG047v16YzWkQMURd99Mq8AZcB9\nqMU9OpQVwQB4PQiv/kWv5BdCnjvi0dF415H8tQohIBTUd/nUAroz5HC1bmaln2CwdsMHHD9xikce\nHs+06ilx6rVGU3JlzRybni1Nqdo1U7br3Tvp15TY7omTp8BdlLHvvn39Blpqb+yl85baM4McsZCY\nRrHZsA0Zhm3IMBAC395TNH21l3uDAY4KwUiHk+CNeoI36smr6hdnRY+I+G00LRHpKhvfrggF4NbV\njntRCKGvc/A2w+D7O5VV7A4odKAUxhttiHcdyV+roij6FE2cJ1WCwSAeryeGU2G9puTKmjk2PVua\nUrVrpmzXu3fM2zVa1mq7qaOocipEImknFNCjcaGB0Bjym39P+Zzp9Dt5mve3fk5h0Ee+206eXVDk\nO0vwH/4GddRY6F2F0n8wanEZsSOayL8j03MrkhWe2whPk378+fUrulNhd+qHidkdUFCir7HIL9LX\nPWRAU+IyifOUl5Uxb87snNIUu4zVfSIXNclRoMxokqSCdCwk5tE0/ZjtVhylJVQueByAH/35n/Hh\nC3/OYnfYuoHTR9FOHwVFQf2//gMUdz6TouOHgNmIJ7ORrNCC+tRH082OCUG//lM1FlvvQRnVFK+M\nEEJ/FNbhTLgJ2IxpU1m74YO0a0ouT6wyVveJZPLEKpM7/VRqMkpmRy664dpN6VhIUsDuBBQQIX3U\nIhTizk1ZUFBA3+d+yrcOG/f37wtNDfp+B6UVKEXF4MoLM2R2TjbR6EY84pW9c6fHrle7UYu43ror\npq8Z/D79iHHVBqqKMuRBfT2F09XpCPTEmsLrN64pXpoIBtDOHgSfV9frbdH/f3n5+sLS/sNQC6OP\nIOkLTlPRFO9ak8kX+V6mNRntp9E0paOfJqMpU/dOLmpK5d5JP9KxkEjCURR9S2gAIfQnDMJGMCZP\nmshnWz/n2M3bjLxvZBxD8aILI2mx0uMRr2ziURPReB3qajq+HWzd/dLhQinrGfMxsvCvn+j1mrnW\nBGWDfrh6oWN6wKv/3K6HqhExywaDwRQ1RcPo/87qPpGKplzrp+nWFOuLtqu1Uyp6JWaQjoXEPKGQ\n/mUqBHfWWbSjfyjNnD6djzd/Sn6+m0EDB0YYMBO1mJ1XTRS1JKdJ6TMEnG6Er6X1LA8f5OXrp6Hm\nFeptodgABREK6Pk8zYiW2/qUSVG5/mho3p3HUNWUNUWmC58H4WtBeJqgsV4fObHZQVF1pzC/EFwF\nKHkFYFOj2q2trcVuj/Yxkcr/zupI1mifIMl649m/GzSF24Lsakrv/RzddmaQ+1hIJOFoQX0BZ1Ta\no4DHZs9k7YYPOjgWQZ8Pe9TNs6yIOFOJhoyVVfPyod89cey05xeXzyDOH+n49o3L7R9tkxZB1Mdw\nk9PUIVVohI58jdLS0DHhzv9r6BhsvQfHtOv1etm2/Rtu1NfHOAMmlyJZs33CSLrUZPW907U1SYwg\nHQuJeWx2EC5AhC3kjD7H7AiEePG7z+G5UY9ys5HK2y24y8soHVBF2aAqHvnLH1I+aEBE2UhbyUQm\nkRFNZ02x7UampaZJ6T8MpfdgRNALnhZEwIfiygNnfusaDJsBu4k1BQ/tJbD9K8S1K4hrtWiNDagl\nJVBaglpWhvPp7+mntjrdYUevd2wnn8/Hu2vWUl5WxqRHJlBSUpKBdookFbtGy8YaLciEJrP91EpN\nsex0B02p9tPM0g0HLKRjIUkB1QbOsA2cvM0d1li0IxjiymPXpq3kA/UixE4RgtqLjPz2OACT/9Vf\n0PlDJtFro3mTjVqMpsXWpH/86WmKooDDgeJwgLsoav7k6omeFty1g+CHazqkaA234AKIyp6ofQZH\nGXbVy96+3cTho0c5dvwEz654GqfT2SHdrKbYr+ORil0jZZNxcoyUTacmo30+HfdOLmqKVS4b/dQa\n5FSIRBKOpp9u2ba+Qot2sqn+4TRg4sPM/L//mlsXLnLzfA2NFy7gsQmuq4JBPYoQe7agNd8PpT30\nszTyC1EsjaQ6azJnN3pZraUJUV+Pdq0W7dJFEBpqn/6ovXqj9KhELShIoC/1a3VMm4XidqNdvYJ2\n9Qo0NaJU9kSp7I3aty8Eg+2LbcOuZ8++fdRcvMiUiZOYOOHhsA+67hbJEpFuZnQjmq5sa4pm10pN\nxMmXaU3RsFpT9/uizzTSsZCYJxTUHYu46DdtfnkZ1S/8uL3oF+vg4HYA9l++zs5PNzLr/EG9RGkF\ntu/9FcY+fKOlJyIVu9HLelb9Cu3w/qi1OX/4Y1wLlyXQl/q12u4Zju2eRNsQdyxXV1dHzcWLLFm4\nIC2aoqdlK5I1qylRv8pGO5mN2nPv3sk9TZkdteiGAxbSsZCkgM0OwhllxCJxlKJOehwxphpu32TM\nret89PlXNE2ZQlGf/iiFJa2xhpWRCDHyJWs3mi1w/+JvELduoF29inbpAgjRYcQiG5rCywotqC8i\nbX2KJdh8m4079+MuKmHhtEfRmhpRO20nnqqmWNF3spG4lZpi2cpVTd19dMBsWas0RbOV2W96tRt6\nFtKxkJhHtYEzbHvqtjUWiaMUxeFAcZRBcRn0G8KMex7ks62f88ToRxKWjZ5mJN0Ku9HT1IICKCjA\n1m8AjHu4w0datjR1+NvvQ5w7AgguXLvBl4eOs3jyOArdeXDxBPSsSoOmWPnTMTpgVBO0f7GY0WRk\nyiDTmoykp6IpXr5MacrkvWPEwZLEQzoWEvNoWutUiEj4VEiiaMOdl4fX60OI8KHBTM29J460BUI/\nCTTgA28Lwu/RD+9yFaA48/TDvMIij+gxiLWa4r+OaCeHC6XvUE6cOsmJK7d4dt6M1p03C/RTVzXN\nhF2rIv5IjI5uZFrTnS+dVDUl00+NaIqlIV2a0thPo9rJtKbM0g0HLKRjIUmBUKB9t8k2zEfXj06a\nyNYvvmDGtKltaZs+3kzj7ds4HHYqevTg0cmTYqyiTm8kJW7XIw580SFNhP1Wxj+mbzQVl3RFd4le\ng2Kz0VQ5kIP7TvL0j3+O0EKgqBFtmazdVKLReKRyrVJT+jWlr5/mtqb0IJ8KkUjCUe1gcxBv581k\nopJevXryxbavCQQCOBwOQKHF08LyJ5egKAq1tVd49bXVLFk4v3V/hVj2otUZGfEYjZT095SCMhg3\nG/wtiObbUHcRvLdBdYCiII7tJOQuatt5U6nsj6LaiKZJa7oFt+rad+3Ugq07YLqhoBS1Rx9iRWDa\nzatw+1Zr2WY93MkrRHG5Ee4CFJ8XcecskKBfPwckzw15RXy28xBPLV2sX08HbWbaKVHbxbId7/+T\nKC2WXSOaYo0GpEuTkQjajKZo9s1oimUvVzVZez8n1iRJBelYSMxjs4EtX/+701khIuJ3NDqnLXh8\nLhs+3MTSRQsBwdAhQzh77jxDBg+iT5/ejB83hqvX6mI4FvHqNBoZRi+rqApKfqG+DXZpT0K+Fmiq\nB1p3svQBTbf00g4XSs/Izb7CRjouHIP62og6rus5+g+HHn1i6hVnD0HL7Yiy1/QczjyE3xuRdkNP\nc7kRgKqGbx2eSjtFw2hUaTYtFU2xyqVLk5Eo2Ywms3UatRfNAcolTUbtpkuT9Shq4jxdDelYSMwj\nBAQDtJ1uqoViZDQeybrdbgryC6ivv0l5eRn3DBnC9m92MmTwYEAw8r4RvPP+WoYPG2rAbjySmWOO\nMoJRUtm23gJfM8LvRYRAa/ESul2Pat+NrUclao8eqAUFKGr7p4dS2hOhKnpZb7P+2K6iQkiDqxfR\n7HlQVEazBl/u3E0oFEK0SnA3XqP5Vj0EfIR8LTw8Yij9+vfX10qorZuVeZv1n2AAXG49La8QUVuT\noJ0SRe2QbDsZq6uraDI6uhFNUzr6aTKako3aiaMzl0emopU12ieSrdMa5FSIRBJO0K+fjpmQ5CLZ\nObNm8OY777Fi+TIKCvK5dPkyQmgoin6Ed2lJCXV116msrEhg16ymxHrVHr2hR2/9VSjEjV/8Fb7t\nO2jzAMIo+cV/oHDhorbXat8hiNZdMEXQj/b630HjzXbru7YC8OqOo/zwpf+Oe+BQ/X0haGlpIT9f\nHyUSfi9f79zNoastPDHvEc5fuMDO3XtRVYVJDz9Enx7l4HK3fXBVNWpcqLnAgKpoT4DEvtbEaUbS\nky2bi5qyOeIiNZnXlIpeiRkUIaJ8EgInTpwAYPjwRBvuSO5aQgEIhO282YFU5k4FBw8d5srVa8yZ\nNYOGhgbWb9zEsyueRlVtCKHxx9ffZOUz34nh7ceq26ymRCgELpwjWFND4NxZvNu2od2sw33/CGx9\ne+EY0J+LNhcHTteAy429pByhqGiahs1mR2u4TvON68waXkXl9YtQWAwDhrPhwHHmL3sKR1FpXE1n\nzp5jz779DKjqz4TxD6EoCm++8x5zZs6gvLwM0J0Srekm7739Dk9Onwhej/4ki8sNBcUopT31p1wM\nXGsq7ZS4TCp2kx356IqarGh/qSkeJ06eBndhxr77To8cZqm9e46etNSeGaRjIbEGIfThdxFrOiR5\nrl2r46PNnzJ7xnQKCwt4d806vvfd72C326mvv8m+AweZNWOaZfVZhebzoO35GKV1w7BtR04SCIaY\nPnoEAMrYmagFHdeICCHY+NHHeD1eHE4HXq8Pv9/P4EEDmTJpYtIahBD86Y03eWrpYtxuN8Lbgrbn\nE9Zt283c8Q/gcnZ0IpSxs1ALIjfIkkjuPk6cPAXuoox9950ZZW09Q46csNSeGeRUiMQ8QujrKrTW\nNRbC2qilZ89KVj7zXdasX8/oBx7g6WVL+dMbb/LcymcpLy+j9soVPB4Pbrc7KbupaDJiV7E7UUp7\n0Xizng+/+JrRA/syYmBffb+IvAIIhTqVVRSFJ+bNjbAfS1NivYqi8J2nnmTDxk0snT8XzdsCLjdz\nJ09gw1c7WfboOH1dR15+xD4WuRE15mIkm5qmVO2aKZvua+2Kmqy2K4mGdCwk5jG8xiIR8eddlyxc\nwLtr1rJsyWImPTKBdR9sZNET81mxfBl/euNNli1ZRFFRtFNDU5k7NTtPDDdu3mLLsSsUFxWx2k5C\nggAAIABJREFU/Gf/AZunUV/r4C4Km7oxOtdv5P3ommw1x9FO7EGraB9FcgEOFQI9BuAcdC9KXkFG\nNRnHSNmupClVu2bKpvtazZTNtiar7aZON1y7KR0LSQqoqv4kgqaRrpuypaWFS5drqejRA4B7hw/j\n+MmThEIh7HY733/2u7z17vvk57t5ZPx4evXqmRYdRjl77hx79x/gqaWL27+w82KNqKSZir6ovQdB\nz4Gtj7cKKO9DrwftXHcV099dmB1ddwUy+pUYozueFdINn6CVZAybA/IKwV0ErkJQbJZX8dv/8fdc\nvHSJadWPtr03vfpRXlv9FkIIVFVlxfJlLJz/OF9t3255/cmyc/deli1ZnBOPkNlKeqAVlWMbPg71\nkcdRJ8zHNvwhJj72BDsPfZtted0c6VRI7l6kYyFJDSH0p0NCrWeGWMwvf/4CNRcvcfjI0bb3iouL\nefyxOaxZv6HtPUVRKCos4tLly5ZrMIrH46GstNQCS9Y5JX169+Lc+fMoitq2l4aq6lt5h0KdF9o2\nNDQQYz13FyL7Tp1EYhRFsfYnF5COhcQ8AR94GsHv0ddbdHrkNHUcDgfff/a72O12/umf/8gHmz5C\nCEFlZQXjx43ljbfeacv72OyZHDx0hK93fGO5DiOEQiEcDitmF637Yp8yaSLbtndujzEPPtDmrO3Y\nuYt1H2xk3Qcb+e3/+Af+9b/9d+w/cNAyDZmnqztGkruJO/vzWPWTC0jHQmIeRSVT+9GOuHc4P/je\nM0x8+GFef/Ntzl+4QFX//jw0dgyHDh9py/f43Dn07dOb11a/lRFd4eTn59Pc0pLxehMxfeqjbP3i\nyw7vBQJBXC4XAEWF7Wstnly0gOrJkzl99mxGNUokku6DdCwk5rE79PUV7mJwutPuZNhsNnr0KOfZ\nFU9z/kIN+/YfYPiwoZw8fbpDvkEDB1JQkJ9WLdFQVZXm5txzLPr17UtDYyN1ddfb3qu7fp0e5eUA\njBp5H4uemM+iJ+Yzdsxoevfqid0u13VLJJlAToVIJJEIoT8VkuF5+amPTuF8TQ0ARYVFXLlytUN6\nIBDMynC+3W79AlYrWPTEfL7Yto3LtfrhZ1euXqWiokfUvNVTJrN4wROZlCeR3LVIx0IiCSfoB28T\n+Jr0/SzSsMYiHjab/iU+e+Z0Pt36eYe05U8uoaCggD++vprGxsaM6Nm7bz9jR4/OSF3JoigKTy5e\nxMebP+P9deuprKjoNB/76ZbP2fzZ1uwIlEgk3QY53ikxjyDjIxXh1NVdp6mpicLCQsaOfpCj3x5j\n5H0j2tKHDb2He4YM5tXX3uAH33sm7Qubai5dYtzYMWmtIxUUReG5lc/GTG9obCDfnd/WphKJJP0o\nao4MM1iIHLGQmMfhbN3DogAceRlbyHmH7z/7XbZ88SWffLqF4cOGsvGjTzhw8FCHPKqqsnTRAv75\nT69z+/btjOrragQCQUbcO4ytX36VbSkSyV2DnAqRSCJRFH33TTXzXclut7Nw/uPcP/I+Xlv9Fv/y\nL/4FXp+v09qKkpISvv/sd/nw480cP5G+k//ULLSBlXznqSfZtWcfmpbZKS2JRNK96NqfhJLsEgyA\n97a+l4WvJeNrLO7Qp09vnl3xNG+/t4bhQ4dSe+Vqp42yVFXl6WVLuVBzkdNn5KOUsXjw/lGMG5Ob\n60Qkku6IqiiW/uQCco2FxDxCaz0nJPvY7XZWPrOC99au4/6RIzlz9hz9+vbtlG/OrBm8t3YdRYWF\n9OxZaVn9oVAop0YsAoEABw4dpvbKFQKBAA6Ho21HTSEEw+65p8N6lDvcO3xYpqVKJJIMIYTgxRdf\n5Pjx4zidTl566SWqqqoAuH79Oj/72c9QFAUhBMeOHePnP/853/nOd3jyySfb1l3179+fl19+OW49\n0rGQmMfh0veyCAZBhCAUzNqoBeiLE6v69+daXR3VUybHzLd00UL++Ppqvvv0UzgcjljWSGYHx8u1\ntfTp1Ss5wTExcxy4zo0b9Xz2+Re4XE5GjhhBzcWL2O12CvLzmTl9Wlu+b48d5901axk0cCAPGVpw\nal5T+uhKmrJJLmrKNLnbBpkcZNi8eTN+v5/Vq1dz4MABVq1axSuvvAJARUUFf/zjHwHYv38/f/d3\nf8fTTz+N3+8H4NVXXzVcz13hWJw6dQqbzcbgwYOzLaX7oai6c6HZIMrZE5lmwviHEuZRFIXlTy7h\ng00fsWThghi5kvsQulZ3nZ6VFUmViY2Z48D1UYoPNn3EwvmPc+rMGfYdOMjSRQu4XFvL6rffY+SI\nEfTsWYmqqtw34l7uG3Evu/fuY90HGwFoafFw77ChjI06FWJOU3rpSpqySS5qyjS52waZ3IZ7z549\nVFdXAzB69GgOHz4cNd9//I//kb/9279FURSOHTtGS0sLzz//PKFQiJ/97GeMTvBY/V3hWGzfvp2i\noiLpWFhNKACB1jNCOo1U5GLU2P6+2+0mFAohhGi9sVPTO3b0aNasX09V//4WaU2u/LVrdbz48n9m\nxtRqPtr8KRMnjOfhh8YBMKCqir94/jmOnzzF7n37CIVCBINBZk6bxvhxY4GxbdYOHDzEu2vWsnTR\nwpya2ume5GIUnYujQLHIRU25TVNTE0VFRW2v7XY7mqZ1uNc/++wzhg8fzsCBAwHIy8vj+eefZ/ny\n5Zw7d44f/ehHfPTRR3E/H+4Kx2LlypVtfwcCAX7zm98wb948Hn300TilJAnRNNCCMRJzMWrs+P6s\n6dNYv/FDFj0xP04ZY6iqQkF+ATdu1NOjR3kSJWPXK4Tg3PnzHPn2WIcTR71eH9OrH6WysqKtfM+e\nlfzdf12FzWZr2zgsnJKSkg6jOT6fjx07d3GroQFVVVFVlSfmzWX0gw8weNBAXlv9FrNnTKdPn95J\nXIskOXLxSzEXR4FikYuakieTUyGFhYU0Nze3vY50KgDWrVvHD37wg7bXgwYNanMyBg0aRGlpKXV1\ndfSKM/V7VzgW4TgcDhYuXEhLSwuvvvoqe/bs4Uc/+hEjR46UEVqy2J36o6ahICD0tRb6rllJGroT\neUSLQOKlpWIXSktL8fsDlmmaM2sGGz7c1OqomNGkv3f+Qg179u1DVVWGDBrE44/NaXUW9HQhYM36\n9SxdtLBDWafTGfNaI3G5XEyrvuNYK2z6+BNu3rxFWVkpxcXFrHxmBZ9u+Zyde/YSCgWZMXUqZWXR\njoTPxv8ukd1c1BSZL5c0JWtXarKSTE6FjBs3ji1btjBv3jz279/P8OHDO+U5fPgwY8e2j2K+++67\nnDhxgl//+tdcvXqV5uZmKivjL3y/6xwLgEceeaTt7wULFvC73/0OTdP4m7/5myyq6oIoCtjs+o8Q\nEGo2uXhTRPw2mpaKXbh2rY6y0mhfluY0qaoax1ExbvebXbt5etnSmOn7DxxgcGsEYcxuIgRz58xi\nzfoN2O12XE4Xs2dOZ9YMfbHnpcuXeX/desrLyxjz4AMM6lB3Nv53iezmoqbIfLmkKVm7qZTtbpq6\nFnPmzGHbtm2sWLECgFWrVrFhwwY8Hg/Lly+nvr6+w1QJwFNPPcUvf/lLnnnmGVRV5eWXX04YhCtC\nRN+T+cSJEwBRPZruRlNTE36/n0OHDjF16tScOdM+5wkFIejTnQktmZGKbEUtHflf//ufWLZ4UeuU\ngjWazp47y/ETp5j32GxTeoUQYdMzncuePXeO02fOMXvmdMOako3Q9h84yKXaWp6YN7dT2vZvdnH1\n2lWWLFxo6Hqs0mTebrR8uaQp2bK5ce9kRlMqOs1rOnHyNLgLM/bdVz/5fkvtlX8dfUFmJrkrRywi\nKSwsZOvWrRQUFPDGG29QXV3d9myvJA5a6yOmSZOtqKUjEx8ez5WrVzusVUhV0+BBg2hqambXnr2t\niyeTs3vz5i1KS0o62b3DvgMHeXLxoqQ0JZN25uw5/rT6LaZVT2H9xg+JjDuEEAzo3x8QXLx0iV17\n9mKz2ch359O7V09Onj6NzWajokcPJj0yIcJJz3Ykm2y93S26Tldknu5rNYMVmjJDdwxkpWPRSn19\nPdXV1Tz00EP84z/+Iz/96U+zLSn3sbfO6YuQPmrR9rhpvMgjMoK4c1MZidAibcezG+u99rQxox/k\n/XXr6dunLz16lCWhKVq+9vceuH8U765Zy8MPPZS0pi+//pr5c+dGyafX1dzcYkqT0XYaMngQv131\nn6KkdbZ7+sw5NE3w8EOjKSst49Tp0yxZuABFUbhcW8vaDR/gcrqYMW0qeXl5SWiKdg3R9Ma6VjD2\nvzPbT81oitf+3VVTZu9n85oi80lSRa5WbKVv3768//77vPvuu3zve9/LtpyugaLoB5E53eDM1xdy\nJow8ItNF2HuJIrRoZWPZjfVex7QlCxewbcd21n2wkUAgEJZmJOKJrWncmNF8tnWrYU1CCDZu+oiK\nHj1wOOwx7AoKCvJNa4pdf/gHfSy9ne1Oq57CY7NmsO/AQQoK8hn94ANt0VffPn1YsnAB/fr15Xev\n/C82bvoIj8djUFO0azCmydj/LtaXixFNybdT4vZPVVMssq0p8/ezOU3R8mUORbX2JxeQIxatTJw4\nkdraWvr06ZNtKV2HUAhCfv2x0w57WVgRNcaKxozYMx7JKorCoifm09zcwvvrNjD6gQe4d/jQOHUa\ni6QGDxrErVsNrFm/AYAxDz7YuuhRzyeE4OKlyxw8fIRAwI8QMHXK5IhHVduvJxDw09LSQmFBYUSa\ncU2dCW8TPe/t200UFOS3Ls7qbCMU0nh/3Xp6VlYy7J4h9OrVk2AwyMlTpxk2dChCCyF8LeDzIFoa\nGeX0MXL5PJqFnXfefpuZs2bRr18/QN8lFKCwsACXyxVFU7RrMbtOIvzv8NeRdUUj3EY0Hams3bhj\nMxVN0d5LlyYr7Ca6jkjMjEwl2yei1ZcZ5FRIN0c6FUmiBSHoj5JgJBqKlZYosjAaoSWnqaAgn6eX\nLeXDjz7h9JkzTJn0CCWd1joYsd3O2DGjGTtmNEIItnz+BYeOHCEYDKIoCjabjX59+vDYrBlxthVv\nv561Gzay6ZPN/P1//68paYqX53/+f7/n3mFDafF40DQNn88ftl+GzrVr1/D7/dwzZBC/f/WPBINB\nnE4nPSsrGTigCntjHZv+9Hsu1tVTkOciz+nAZrPh8wdoaWqhfIm+PmT7NztpamqmoCCf27ebOHXm\nDH/5L34YdQ8O49dqJro2QvL9yXjUbqSuXNJkpd147yfKk64+YVSTJB7yqRCJebSQfsKp0ECIsM2y\nIiMCiH2zxssb7XU8O7HyJrLbEZ/Pz7bt27nd1EQwGGLC+Ieo6t8vZU0NDY2UlBQb0NTZ5vZvdjFo\nQFXrhlXJtlOi+Wf99dlz5/lm126q+vdD0zRu3mrgytWr/PkPn+ugpa7uOjv37GHmtKncutWAy+Ui\nGAzx+ltvM2NaNSG/jwfuHYrq94Dfh+JwQl4BitMFdheKAjUXL/HNrt04nQ4URSXP5WLOrBkx9Ma7\n1nikp52s76exyubCvZOLmpLtE8lpOnHyJLiLMvbd1zDd2tOES7YesNSeGaRjIbEOX7PJp0Rym00f\nbwbgsdkzLdpEzcjwb0feXbOWJxcvSuOwabuma9fqCIVCSe+66fV62frFV2GP2lqnyVpSsZuLmtJF\nLrZT+jlx8lRmHYsZRg4BNE7Jlv2W2jODnAqRmEcL6VMhbSMW0Q4hy1bUGI9EowUd7cx7bA719fW8\nu2YdBfkFzJoxNWJNQLKako3CFBRFjXAqrG6n9vT24+Sj2W3XFGknL88dZf+OaKTaTkY1xepr0XQl\nW9YqTcR4nYwmory2sk+Y0WS0nZLRFKtPJXc/G/vfSVJBOhYS84RirbEIJ9GHVbzXRr5oYuU1oynW\nB5egvLyM5U8uoaWlhU8+20IwGERVVUY/cD8DBwwwqcn4tdpskSMlRsomSktNU3Jl42mwQpMRu6lo\nyqV+mouaYjltVmqKpdPKfppMW1iDXLwpkYRjs4NwJvlUSKJoIpJYUU28SMRslJJYU35+Pgsen6fn\nEIJde/axc/deRj9wP8OHDYta74mTJzl95hwP3D+S/v36Jq3pq693UF6WzMFm8do/vC6r28noKEWy\nmqLlM6MpUVmzmqJpTIemZO8dM5pipZnRFK8/WKEp9fs5uqYMf9Gr0rGQSNpRbfoeFnfwNrcu4DQb\nYUYjVv54kUgqUYrxiEVRFCaMH8eE8eM4dPgIazdsQNM0+vXty4jhw9i5ey83b91i5Ih7mTm9mgOH\nDvPNrl306d2byRMfMaQpGAzy1dfbGTv6QT786BNaPC04nU4KCwpoaGwkEAjidDrQNA1FUSgsKGTW\njGlhUZDRdooWcSbbTkZHBJL938WrIxlN8aLrZNvJqEYrNZnrp8lpsrJPWNVOmbmf2/MnW0YSiVy8\nKTGPpkGo9amQtiPUrYw4rYyQk9VkPmqvuVjDyVOnGTdmNKUdDjnT8585e5Zde/by9LIn4xyZ3F7v\nrVu3EAIURT+RNRTSaGlpprCwsNWBaNdRX3+TDR9+xMQJ4xk+bGgnW9HriX898dvCfDulr2y6+kRX\n0pTNeycXNRnva5l+KqRxzkOW2iv+ZI+l9swgHQuJeQI+CHizraJLcuNGPRs/+phnVzxt0ZMmHdm5\new9er5epj06x3LZE0p3J9FMht+eOt9Re0Ue7LbVnhhzZAFTSJVHtYHO0buUdGXorEb+jpUVDifiJ\nly/We7HKpaIpXJsZux3TevQoZ/GC+fzx9TcJBoOd0hMTX9Oo++7D4/Ga0BstnxlNyaYb/d90BU2J\n9Ga7nXLp3smEpnifTclej8QI0rGQmMdmA1c+5BWCu0h3NNowOj8aLS38J16+WO/FKpeKpnBtZux2\nTisuLubpZUt44613uHjpYpz6k9ekqgo+v8+E3mj5zGhKNt3sfHouakpl7UC6NMXKF8+ukiA9mbqy\neT/H+v8kup8zhKJY+5MDyMWbEvMIoa+x0EL635pG9HnSeHOcsfLFe8+o3Tvv5a4mt9vNymdWsG37\nDnbv3Y/NphIMhnh00iQqK3uYvB74aPOnPDFvrkFN8a4rXp3JaYqdZqWmOx+suaapa/fTrq/JbD9N\nP4p8KkQiCSPoN7jGwopIyozddEd31mmaMmliew4h+HjzZ60jDjB7xnTy8/Opra2lobGREfdGm/vt\naE9RlLAzSKyOZI2mp9JOZjUZbf9c1JT7/bTrajLbTyVmkI6FxDyqqk9/dNjD4g5GogAzkUIqdruG\nJkVRmDtnFgA+n4/Ptn5JoHUjss1btvLrX/4i7BTUeHat0B2rTLKRqtH6upsmM3mkpuxryiA5Mn1h\nJdKxkJjH5tB/AITQ97EQd7b1NnIzm4kUUrHb9TS5XC4en9t+9kZLi4fG241hjkX08qqh4dVUrjXZ\nSNVofd1Nk5k8UpOxPNnUZCHdcCpELt6UmEcICIXCHju9EzUmi9Ho2qzdrqYpVprCiuXLOHP2PDt2\n7oqZJxQKcft2U8Y0gX5w2R9e/RN/euNNrl2rA8Dj8bb+nfl2Ss1usvUlmydWGanJWJlc0iSJhnQs\nJOYJ+sHXpDsVdw4jy3jUYqRMV9MUP0KbNWMaXq+XU6fPRM1z8dIl7ou6DiM9mrZt38GOXbt4buWz\nbUeuA6x++x0+3fp5Arvp0ZSa3WTrSzZPrDJSk7EyuaQpdRRFsfQnF5BTIRLzqKq+h4Vm1qGQmGX6\n1Go+3fI5jY2NjBvb8djl8xdqGDxoYNrqrq29giY0bKqNzVu2Uj1lElMmTeRPb7xJcXERvXv3oqmp\niUAwyIT7R/H+uvVomkb15MlhJ6d2JbL71IBE0tWQjoXEPHfWWNw5Mt3vibKIU5IuZs2Yxv/+P68y\nfNhQCgsL297XNA2bzWZpXUIINn28mUAwAEC/vn3xeDw8u+LptiipsLCAkuJi1qzfQEF+Ad9/ZgV5\neXmMGnkfQgjWbviAkSNGhG01bo7bt2/j9wfC1pmkG+lUSNJIN1xjIR0LSWoIoZ8REgolziuxnKFD\nBnPu/AXuHzWy7b3pU6t5+701LH9yiWX1vP3eGqY9OoVevXrGzDNowAC+/mYnP/7zf9EpTVEUlixc\nwP/z+z9w/ORJwk8SUBSFJ+bNbdva3Ov18u6adRQXFwG6U3P02+M0NTcz7J4hVPXvx4Waizy38lnL\nrk8iyRo5Mn1hJdKxkJhHnhWSdW43NVE9ZTIejwen09k2UnHvsKFs/2Ynkx6ZkHIdQghcLmdcpwLg\n6LHjlJeVEQqFYo6Y/MXzf9bpvcbGRl5/821KSoqprKjgzNlzPDZrJpWVFQAEAgEu1FzkZz/9MW++\n8x733Xsvly7XpnxdEokkPchDyCTmCfp150JOf2SNxsZGNnz4EYFAgIbGRv7Vj/+yLW3Xnr14vV6q\np0xOqY5Tp8/g8/kYNfK+mHmOfnsMn8/HvcOHsemTzTy5eFHS9YRCIa5eu0bfPn06pX177DjHT55k\n34GDDBo4gCcXLaSkpCTpOiSSRGT6ELKWZdYeFJj/7jZL7ZlBOhaS1BEaBIMQlE5GttixcxflZWUc\nPHyEoUMGM2b0gwAcPnqUq1frmDVjWof8fr+fDz/+hEAgSHNzM2VlpeS785kxrbrDaMPl2lrWb9zE\nd5cvo7i4OGb9oVCINes3MHvGdPbs28/M6dNi5k2VU6fPsHvvPlYsX5a2OiR3Lxl3LJ561FJ7+e98\nZak9M8jHTSWpIQRoAn2Bm1zkli0mTniY4cOG8tTSxSiKws7dewC4f+RIWjwtvLtmLd8eO05d3XXe\nevd9Pv70M6ZXP0ppSQmVFRU8/tgcxo8bwx9fX01Tk74Hxp0v8L94/s/iOhUANpuNPr17s+mTTzts\nT54Oht4zhJ6VFTQ2Nqa1HolEYg45YiExj5wKyUmam5v5YNPHPL1saYf3d+3Zi9/vZ+KEh7HZbGzc\n9DEj77uXnpWVvP7WO/zg2e+iqiobP/oEEOS58pgza0Z2LiIBN2/eYvU779K/X1/mzp6F0+nMtiRJ\nNyHTIxaep6stted+60tL7ZlBOhYS8wT8YTtuSnKJAwcPceTbY9xuaqKyogdOp5PHZs3E6XTi8Xj4\n0+q3mDt7JgOqqgBoaWnh7//n/8u/+6t/k2XlyeH1evlg00eUlZYyY9rUnNkgSNJ1ybhj8Z2pltpz\nv/mFpfbMIJ8KkZjH4QS7Q9/DIhTUj1CXoxc5wegHH+DBB+4nEAi0OxNvvMmAqipmTKvGbrPRr2/f\ntvx5eXkMGzoki4rNkZeXx7Ili7ly5Sqvv/k2z3xnuXQuJJIsI9dYSFJDUfTdN23SR801FEVpmyJw\nu908tXQxddevc+78Bex2OzUXL7blVVWVosIiTp46nS25KdG7dy/mzp7F2g0fZFuKRJIcqmLtTw4g\nHQuJeUIB8N4Gz23wNcvRihynuLiYpYsW0NjYyFNLFzNoYMdtv+fMmsG3x09w40Z9lhSmRkVFDzRN\nw+PxZFuKRGKY7nhWiHQsJObRNHlOSBcjLy+PsWNG43a7o6YvnD+v9eCwrsnECQ+z6ZPNbP9mZ7al\nSCR3LdKxkJjH4QJ3ETjcYHeCYrY75eKRxtnUZOY48GTyxCmtKOTluZKwm+4jspPL07dPH5YuWoQ7\nL49PPt3SKb25uRmv1+xusbKfGkNqSopuOBUiJ8YlqaGo+gJO7CmcF5KLRxpnU5OZ48CTyROflpZo\nUwmZ1pSKXcGY0Q9y7vx51n2wEdCvyWazUV5WRiAQwOf3IYSgqn9/xo0ZbXAIWfZTY0hNSZEj0xdW\nIh0LiXlCAf2RU6FFWV+RzaOmY9V9N2kyYjd6HqfTkaa6zWsyw6CBA8PWkUS3e6HmIms3fEAwGGLx\ngvk4HKleezLIfmqMXNQkiYd0LCTm0TT9ZNOoZPOGTyW6TheZ1mQ+Qkv9yPXsjrgkY3dAVX8GVPXH\n6/Xy+ptvM2/O7ISHraVb093VT42Qi5qsI1cWXFqJXGMhMY/dCa4CsLvA5kDvTtFukkQ3jhLx22ha\nojqM2L3bNBmz275vnlF76dcUv654NhLbzcvL4/vPPsPOPXs4feZsCpq6Yp+QmozZSBPdcI2FdCwk\n5lEUff8KZx443a1zhdGiiESRhYj4bTQtUR1G7N5tmhLb9Xp9YVGUUXvp1ZS4rng2jNlVFFg4/3G+\n+GobBw4eMqmpK/YJqcmYDYlRpGMhMU8oqO9f4W3S97IQ0RZvdu1INjl7uRhJJa9pxPBhfLrl8wT2\nMqvJmD1r+sSfff97nDl3jkAg2CnNWk2J9OZSP42Xr7tqygxyHwuJJJw7W3lrIZKbB+1akaxxe7kY\nSSWv6eDhI0yfGuso5+xoMmbPuj4xc9pUvty2LUkbyWpKpDeX+mm8fN1VU4bohlMhcvGmxDy21hX0\nonWjLC18xCL85gyfIomcLjE65B4tn1G70aZocllTLLvp17T1iy+YPvXRsAWcRjWZuZ50tX/qmkpK\nSmnocCx7utrfuKbs9dNc1JTO+7n7IoTgxRdf5Pjx4zidTl566SWqWg8iBDh48CD/5b/8FwAqKir4\nb//tv+FwOOKWiYZ0LCTmUVVQwzZT8jbHeEokXhRmRVSSyG4qZbOhKV3RW2xNZ86eY+/+Awyo6k9V\n//4mNFkZmafrWu+8F+2LqXNZVVUJhUKtTlY8xyBzmhLXZYWmRNeay/eO1ZoyQAanLzZv3ozf72f1\n6tUcOHCAVatW8corr7Sl/+pXv+Lv//7vqaqq4p133uHy5cucPHkybployKkQiXlCIfB7dIfCczvM\nqVCIP1esxMhnJC3W3GlkffHKRiMdmhLVn4ymeGmpa9p34ABPLV3MhPHj4+RPpyYj7W+kbDwiI9f4\n7T9pwiPs2LkrIl942VQ1xbKbaj+NVq+Zfmqlpmzez8nqzezIhaIqlv7EY8+ePVRXVwMwevRoDh8+\n3JZ29uxZSktL+cMf/sDKlStpaGhg0KBBccvEQjoWEvNoQQj69d8dNsgSGIsgIvMZSYvRXCQJAAAg\nAElEQVQVBUfWF69sNNKhKVH9yWiKl5aaplOnz9DU1Gwgfzo1GWl/I2XjkVz79+xZwa2GBj7YtClN\nmtLVT6PVm6l+mov3c7J6szRykQGampooKipqe22329E0/bP75s2b7N+/n5UrV/KHP/yBr7/+mh07\ndsQtEwvpWEjMY7O372Ghhm+qFC/aSCaqNxqVGKknXZoSpeW+pm3bd7Bw/uMGysYj1Ws1Wza9mp6Y\nN7f1QzQZ/dF0WKUpXh1SU2xNsUYpkrmeNKEo1v7EobCwkObm5rbXmqahqrobUFpayoABAxg8eDB2\nu53q6moOHz5MUVFRzDKxkI6FxDyqTd/DwpUPeYW6owHEjzaSiZaMRiVG6kmXpkRp0fIqEa8zr0nT\nND7/8ivefOddZs+cTnl5uYGy8Ui1/c22kxlNRttfIITg5s1bEWXT0U/T3ScyrSld7WQmb/h7ydw7\nGSKDT4WMGzeOzz//HID9+/czfPjwtrSqqipaWlqoqakB9GmTYcOGMXbs2JhlYiEXb0rMo4UgGKDt\nrJC2p0LufKjc+Zs4ryOJLBsvXzy7kWXNakpk14ymaLaSuZ5EaZHX3dlu7ZUrAHznqSdN1pNs3nCM\ntn+6NBn9P8N7a9cyb87sFDSls09EuwazfdpqTUb6phlNRHlt1b3T/ZkzZw7btm1jxYoVAKxatYoN\nGzbg8XhYvnw5L730Ei+88AIAY8eOZdq0aQghOpVJhCLa9+7twIkTJwAMeSeSu5SADwJmj6CWZJOv\nd3xDv759GDhgQLal5Cw1Fy+y/+ChsGkiyd3AiZOnwF2Use++4I+fsNSe/ZUPLLVnSkO2BUi6MKpd\nPy9E0+h4wml4VBAtIlDC0iB+JBIr+jZjN/I9o2Wj5eu6moSAi5cuM3nixBiajESGyUTEiTUZ7xPx\n6rJWU1X/KurqrrN+46bWs1MEHo+XaY9OoXfv3kloMhqlGylrVTuZ7afJlo2Wz2pN8eoyo0mJkTdN\n5MimVlYiHQuJeWw2sLnbX7ftYxF+o0a7oYWBtGjpVtmNRryy8ex0PU0HDx1i/LixdP5AFVHyx7IV\nT1Oy/9fw95JtJzOaol1r9HrHjR3DuLHt71yuvcLFy5c5euwYDY2NFBUWMWXSI7jd7g7l0qkpcVqi\nuozatUJTPH25eu8kKiNJhHQsJObRNAi1rrFoO0I906MQRu1Glo1WR7Sy8fJ3PU3nzl/g6LHjfPfp\np5LUlGzUmMiuFe2UeU357jzeXbOO53+wkqH3DKGxsZHPv9xGi6eFwoJCplU/isvlimPXek2x751o\n+bKtqSvcOxkmR873sBLpWEjMEwpEWWORbLRqVdSSrN1YeZPJ3/U0ORx2hg8bakJTuiLkaOm5q6m4\nuJhf/NW/oaSkpO31vMf0xZ23b9/mk88+w+/3M/qBB7hnyOCMaEqujmTz3+33s8QM8nFTiXlUW9ge\nFpFetxLxO1paPBLliWc3VlmzmhLZTbcms23YOV/fPn2ouXjJVNl0abKurBm7Rsvqf6uq2uZURKYV\nFRWx4PF5PLl4EUePHefq1Wsm9CajKR5G+nMmNXXF+zlDZHAfi0whHQuJeWz29j0s3EURm2QZjUxi\nkWxUkqjOVDQZjWjSpclsG3bOd/TbY5QUF3HtWh2fbf08qbLp0mRdWTN2zUbQ8etY8PhcPv9qG0Jo\nnDl7jitXrhqsMxlN8TA7gpEuTV3xfs4Q3dCxkFMhEvMIoa+rCIXQ11ncmaeMvGHjzecmymdF2Uxq\nijdPbFRTIm3mr3XUyJHc/PprPvlsS4wTTLPR/tn436VXk9fr5dz5C6zd8AFDBg3iWl0dO3bp544U\nFRYy6ZGHyc/PB1pvIy2EzWY3ocnItSYiV+6dbGsyakOSCOlYSMwT9Bvcx6IrRrJG7CbKb1aT1dFd\nR02PTp5E/359OX+hJsmy6dNkvmxuanK73fz1C/86qqqGhga+3LYdf8APgKIoBAIBhBDMn/sYeXl5\nSWgyojcRuXLvGC2bSbsZIMH22F0R6VhIzKOq+l4WHfawuIORKMBMhGDEXqw8RuqzWlOiPKlGScnb\nvVxby87de3l62ZMp1m2dpuTymCF3NJWUlDB3zqxOdn0+Hxs/+ph8dz6PzZ6JEndYOxf7aS5qMkOG\npxNyZPrCSrqfqyTJHDYH5BXo6yvcRaAYXWMRmScZjNiLlcdIfVZrSpQn1Q/G5Ozu3bef/QcO8fSy\npRbUbY2m5POYIfc1uVwuli5ayPhxY/k/f3wNj8djsaZ099Nc1GQGOR2SKtKxkJhHCH19RcCn/xB5\nCqRRjJRJxW4uajKTJzVNfr+f8zU1zJ/3WM5oSq1MV9Jk3H6PHuWsfGYFb7+3hrq661nS1FXvnVTK\nZmnkoBsu3pSOhcQ8QT/4mvR1FkG/7mhkPGoxUiYXNZnJk5qmzZ9tZc7MGTmlKbUyXUlTcvbtdjsr\nn1nBF9u28e2x41nQ1FXvnVTKZmmkohs6FnKNhcQ8qqo/YqppdL4p5QrrXOP+Ufdx8PARJk98JNtS\nJAZQFIVlSxaz/8BB3lu7Drvdjqqq9Ondm4fGjsm2vAwiP0u6GtKxkJjH5tB/hNCPTPd7whZxyg+C\nXGNAVRU7du5GCJFgYaAklxgz+kHGjH6w7fWRo9/y9Y5v7iIHsZt/lnTDp0K63xVJMssdpyIUzLYS\niQHuPNYo6bqMGnkf1+rqsi1DYhXdcCpEOhYS8wT84LkNvmYI+qI8cirJJYQQ+P1+jh0/kW0pEguQ\nDqIkV5GOhcQ8CjnjIUsSoygKf/b97+Hz+Xh/3Xr5xdSFGTF8uHQQuwtyxEIiCcPu1M8JySsEhztn\nOrUkPmPHjGbKxIn86Y03pXPRRbl3+DBOnDqVbRkSK5COhUQShbbOnBudWpKYnj0rmTGtmh07d2Vb\nisQEcvGtJJeRjoXEPEE/eJv0dRYBj1xj0cXo368fZ8+dl6MWXRCv14vL6cq2DIkVqKq1PzlAbqiQ\ndE0ErZtiSboq8+fO4d0167ItQ5Iku/fuY/y4sdmWIbECORUikYThcOpnhLgKwO4CRXanrkZpaSl9\n+/Tm4qVL2ZYiSYLrN25QUdEj2zIkkqjIbwJJaiiKvvumTe611lWZ9MgEtn8j11p0FVpaWtA0Oe3Y\nbZAjFhJJGKFA+xoLX7NcYxGX3Ljho6EoCj3KywwceCXJDLH7ihCCd95fy+IFT2RQjyStSMdCIglD\n0/RdN7v7lruWkNttNH1qNVu//CrbMiRArL4ihOD1N99m4fzHsdlsGdYkkRhHjl9LzGN3gmoHLaiP\nVoQCrZ+JyX6JKgbKGMkTq0wqZdOlyUye9GlSVZWiwkIaGhooKSnJCU252E7psZu4rKZprU7FvIj/\nj7x3rCubin3zKDnyJIeVdL8rkmQORQGbDRwu/QeV3DxmORc1mcmTXk1zZs3go82f5ZQmc3lyUZN5\n+5qm8ac33mTRE49HcfrkvWNdWXlsulVIx0JinlAAvM36GgvPbRChsEQjm2aZuQmM2IuVx0h9VmtK\nlCddHwTJa7LZbFRW9ODKlatpqjtd7W+Erqvp/XXrWbpoAcXFxSlqSnc/zUVNZsiNL+eujHQsJObR\ntPZpkE4YiXisjloS1ZmLkWy6oiRzmqxZa5Hp9jdC19R0oaaGPr17U1RUZIGm7jYKlM17x0LkiIVE\nEobdCa58fQ8LmwO9O0Xr2EY7e7rKZlKTEuPvZDQl0pbKtcYvqygKQwYP4vSZswa1pF+Tsbq6p6av\nd+xk8sRHUrRrrabuez9n6UtZOhYSSRiKojsUzjxwukFViO7tG40A0lU2k5pEjL+T0ZRIWyrXmrjs\nhPEPhZ0hkon2z8b/Lvc1fbb1cyaMf8gCu9Zpss5uKmUzaVdiBulYSMwTCoKvpX0vC83oGgsr5mvN\nRB5mNaVrJMGopsxHjTOmVfPpls9zSlPismbspjKCkaqm2H1i3/4DFBUVMWTwIAN1GdUULy1d947R\nPLl4P2cIeVaIRBKGFtIXcEbdyyLV6MLqqD0VTekaSTCqKfNRY98+ffB4Pdy8eStnNCUua8ZuKiMY\nqWqKbvODTZvweL08/NA4g3UZ1RQvLV33jtE8uXg/S8wiHQuJeWwOcOS172cB6FFAZCQQL/ILz58o\naknFbjIRnNH83VvTE/PmsumTzQnsxosm091O2dQUi0R242sKhTT8fn/Yuorsa7q77+cM0A3XWMgN\nsiTmUVVQw45u9jbrT4l0Il7kZ9W8drJ2Y+VNJn930qR0SguFQrhcToN2k6nTqKZk6kgmf+drNa4p\nVllrNJ07f55h99yTpCajdZjTFL9sd7+fM0COOANWIkcsJOYJhcDvad/Los2pyFTUkqxdK6KW7qpJ\nRKSB3W5HCN3BiG7X7EhCKn0iXl1GNYko75lvp8SajOTT7bpcLvz+QJKaItPMaEp0rWb/d/H05fq9\nIzGLdCwk5tGCEPRH2ctCYHyOOZnI5E7+RJFULLuJojTFYL6uoilamhFN7cyeMY3XVr9FMBik87XG\nm/tOn6b4dnNJk5HRjY7p+W43Hq8nC5qM9tNYZbvjvZMhuuFUiHQsJOax2dv3sFDDD0WKHHWI9zqS\nyLzRuPOhkaieeHajvY72gZLIbqY0GbWbKAJLrv1LSkp5auliXlv9Flev1rW+n6ymaHWk0idSadNM\nakq+T7jdblpaPHHymtV0h0zeO9HKRiNX7p0sIZ8KkUjCUG36HhaufMgr1B0NoPOoQ7zXkcQbsYjM\nl6ieeHaNakpk14wmJeJ1MmWNpCWj6Q6xNeXn5/P9Z7/LoSNHWPfBxrCpkWTa31pNsetJpv0zoSm5\nPpGX58Lr8yapyUi9kfnS1U/vEKtsLNJ5P5vtpxKzxHUs9u7dmykdkq6IFgK/t30vi1D4GgvC/u7O\nkayRyCkyb7ojfus1KYrC7JnTmV79KG+/t4YDBw8Z0BSZbq2mxKTa/mZHIaLpMKap9spVevfqlSBv\nrDrSo8lcP01XO5nJG/5esiMjGeBumwqpq6uLlyy52wkFIegL28viDumOZM3Uky5NZiOnrqgJiouL\nWbF8GTabjTfeeodLly9bYDc1TbHJZNRrTT89cvRbRt03wlDeznV0tXsnk5pEnLxZHsG42xyLqVOn\nZkqHpCui2tv3sFDCu5LRaCNaBJMoTYnIF62ORGWjkQ5NiepPRlO8NKs1xUNPv3/UKFYsX8bZc+d5\n8533qK29kqImI+1vpGxi7dE1xcufLk2d7Xq8XvLzC9KgKVP9NBfv52T15saXc1cm7j4Wbrc7Uzok\nXRGbDWxhfaRtH4t40UX460SRRay0eDaNlI1GOjQlqj+XNCkYGw1or1dRFB6dPAkhBF98tY0vtn3N\njKnV9OxZaUJTKtcTr2y0fMlfazvRyprV1NmuEJrBMlbfH7E1ZaefZvN+zvCoRQYXXAohePHFFzl+\n/DhOp5OXXnqJqqqqTvl+9atfUVpaygsvvADAk08+SWFhIQD9+/fn5ZdfjluP3CBLYh5N06dBhNZ6\nhHqIdm8/2gdU5N/EyB+NVOxGpuW6plh2c1OTosC06mqE0Hjn/bUsf3KJwbLpav9UrifTfaKjJkWJ\n/JLJhX5qtmw6NaXzfs4wGZy+2Lx5M36/n9WrV3PgwAFWrVrFK6+80iHP6tWrOXHiBBMmTADA7/cD\n8OqrrxquRz4VIjFPKAABb/teFm3efjLRh9EIIRW7ZqKlbGqKZTeXNekjGCNH3Msbb73DjRv1Bsoa\n0RSPxJqil8mGplh22987+u239OvbJwc0RbZhLrRTtu7n7sWePXuorq4GYPTo0Rw+fLhD+r59+zh0\n6BArVqxoe+/YsWO0tLTw/PPP89xzz3HgwIGE9UjHQmIe1aY/YqraiD2/m8qceDSMzJ0msp0tTUZs\nGLVr1F4qmpK1C6NG3seK5cv4Ztdujn57LIGNzGhKzoZVdpNv/2+PH+ehsWNySpOxfN1VU4bI4OLN\npqYmioqK2l7b7XY0Td/csK6ujn/4h3/gV7/6FUK0O1h5eXk8//zz/P73v+fFF1/k5z//eVuZWMip\nEIl5bPb2vSuE0NdYiMiTThNFjcliNmqJlS+TmozYMGrXqL1UNCVrV0dRFB6fO4f1Gz9kZNsTDonq\nT68m4zasspt8+zudTgP5st0n7iZNGSKDUyGFhYU0Nze3vdY0DbV1jcemTZu4desWP/rRj6irq8Pn\n8zFkyBDmz5/PwIEDARg0aBClpaXU1dXRq+2x6M5Ix0JiHiFaj05v3dJbCBLPf0YjfN47VlmjNpK1\ne7dpMmvXqI3WV4pCx6gxHZqsbv/safL7fTjskY5FrPyZ0STvne7HuHHj2LJlC/PmzWP//v0MHz68\nLW3lypWsXLkSgPfff5+zZ8+yZMkS3njjDU6cOMGvf/1rrl69SnNzM5WV0RZotyMdC4l5gn59jUVC\nEt2sRqIWozaStXu3aTJr16iNsHfazo9Jlyar2z97mg4ePsLwYfdETcuWpsRpd5umNJHBp0LmzJnD\ntm3b2tZQrFq1ig0bNuDxeFi+fHnUMk899RS//OUveeaZZ1BVlZdffrltlCMW0rGQmEdV9T0shEbH\nQ8ggvd6/mWjHSLlUyJamVMqnqz10u0qnIV4j9aVXU3L1pTuC1e03NjZy5uw5xo8bm6F6E2sy/n46\n60yU3k1GGDI4FaIoCr/5zW86vDd48OBO+ZYuXdr2t8Ph4Le//W1S9cjFmxLz2ByQV6CfE5JXCEr4\nQWTpvOHNRDtGyqVCtjSlUj5d7aHb7exYGKkvvZqSqy/dX1oCIQTvrV3PU0sXZ7DeeNxN944kXcgR\nC0lqCA2C/397dx4cRZn/D/zdc+VgkkEhhCskgSWAgCQRUOQ+wk1Q1qC4aLn6W6t2/9oqd8vaqq1a\n9g/FP6xdq36uv6rVrdplvyhRqC+HCoEIQQENEkggXCEhB0kwhlyQa67u3x9Dhplk7unpnkzer6oU\nzHQ/T39mMp35PEc/bcPQSZvBULMlG87xoql1Hcw+oVC61RjOa43GmDw78vVR5G/a6LdrWcmYwseY\nghIly3DLiYkFhc5qDnCOhT9qtmTDOV40ta6D2ScUSrcaw3mt0RiTd48//ljwoQR1vJF07oRzPJV6\nQIYsijb8xd4rIuUImocTj2Iv46bwuV4LT0NJkqd5KETDH3ssKHQ6veNn4LJTS5+HSZxENFhvby++\nPFqEhfNz1Q6F1KaJveSSiQWFx3UtCyIXbI17Vt/QgPMXLuL5/M3Q6/Vqh0Nqi8GhECYWFDrrwDoW\n7PIm8kaSJNQ3NKCjoxMAcKniMn796k4mXhSzmFhQ6AQ4ZjRzLJ0GsVqt0Glj88+LZLdBut8OdHc4\nPvtGE4TksRB0j3ofWlp+xvfnzzsfZ0yZgpSUsZAkCc/nb2FSQY/E4GchNs98UobO4FjLQhQddze1\nmZlkEACgvuEO0qekqR2G7Ow3SoGu9iFXQ0l6AzA5C/aUdBQVf4OE+ARs3byJCQT5p+DKm0phYkHh\nEQTH5CNx4N4QTCwIqK65jZXLl6odhvzsD+cUuei3WFH0QzmEsXcRN34Kli9ZjOTkZJUCJFIfEwsK\nnc3iWMuCV4LQIBarBXFxcWqHITvt7GcgWc2QOluB3gcov34Dt+7ex/O//QMMo5L8V0A0WAz2ajGx\noNBJEpMKGnEEfRwwdhL+9/ARTJ+WhRfXz1Y7JKKowsSCQqePc8yzsNseXnJqZaJBI8Lhr77G4mee\nQWrqOLVDoeGOl5sSDSIIgFbn+NduVTsaooj77uw5zJg+nUkFySMGh0JiL1Ui5ditQH830PcAMPew\nt4IAAGazGXGGWJpf4f6H/+fWVsyckaVSLETRjz0WFDpRHDJDnujn1lakjktROwwZPbrSqbX1HiaM\nH69iLBRzeLkpkQudAdDoHGtYSKJjroUkIfhLTiN1S+OBMuGUVSMmpW+bLm9MP7X8jMkTJwZYrzIx\nBVev95j0eh0sFovPfUbO55QxyYJDIUQuBAHQah2TOPXxCP3EjNQtjaVB/4ZSNtx9vJXxVVbp26bL\nG1Nr6z2kpIwNsF5lYgquXu9lR48eja7790OIyXe94ZcNdx9vZRgTBY89FhQ6u9VxvxBJ9DC/ItKt\nllD2icWYoq93w2yxQKfz9KdlePS4+NrHZrN5eW3h1StfWcYkT0wK4lUhRC4GlvL2KNKtllD2icWY\noqt3w2azQfI6iXd49Lj42qfqVjWmT5sWVJlIxxQ4xhQYhXsuYvC26bGXKpFydAbAkPDoniHQwHO2\nL3j5v6/9gt3fV9nhFpMQwHY5Y/K1zdcxh24vPlmCNStXRFVM/usLPKar129g+i9+EcYxY+lzOpxi\nCvUzQaFgjwWFThAcSQUASBJg7vXSgyF5+b+v/YLd31dZf/VGW0z+Wmhyx+RrW3Ax9fb1utwnIzpi\n8l+f/5gkScKXR49hZtZ0L3PtwvmsRevn1NswQjSfO+GWVQGHQohc2O0P72gqOoZF3E5QX+PegY6F\nBztm7m+sPdyYBr5RgjluODH5EsmYBu8XeEx6vd5HuVBjCvQz4Tmm8D8TAvb/70EsW/ysy6JYvmLy\nF688MYX+PgVar5zns7fPabAxBbo9kN+Pr3NHQTF4VQgTCwqdaPOx2mb0t66DjymcekMp60skYxq8\nn9oxBfqZiExMl8rLMXvWzEErbfqKKZzWc2Axhfc+RdO5o0RM3n4//uqlUMVeHwwpR6t3XGY6sJ4F\nAO/zA+CyffBjb3MLfG3zVFeg9QYSUyjxxmJM/o7r/n9RFF0eh1OvHDENFvz7b7VaUVVdgydmzYqa\nmAIrq+bnNBpjCiVehQgaeX+iAHssKHQaDaBxWbq5v8fHVSIDgmndBdry83ecYFtLIzEmb93NgR9X\nFEXY7XaP28KpN/Sy3sr56rp33/fI10eRv2lDAGWViyn4Y8r9mVAzJn/7yR2TAmLwqhAmFhQ60Q7Y\nLI75FW5rWbiOXXoa33TdBvg+oQePlfoq62vs1N+YazAxDY4v2mMaXM5TTJ7iCC6mskvlWPBUrowx\neasnmPfJ0+vx9nlyP+at6ttIHTcOCQmJLvsF8juIVExKf07DjclfYhKt507sfdErjYkFhc5ucyQW\nQ8jZQvC0v79WY6gtykBaaN7qjcaY/B1X3pgSExJgsfibcxNKTN7qCabe4MpevXYddxqbsH7tmgBi\n8nbM8HuBAt8mV0xyfiYC/V1G27kTbJkwxeDkzegYkKHhSat7uIaFDtBovezka5wVGNo6CGTbQEvE\nV72+eCvrqd7hHJOven3F4ate7zH9Yto0VNfc9lLWUz1yxuStHl9lPddz9vsf0NbegfVr8/wc119M\nkfpMKBmTr/fbX72BxIQQYvIUYyTOHYVwjgWRC43WsUDWAHOPoxfDjb9WjFwttmBaGcq0er3HFEjr\nTq2YQm8xx8UZYLaY/RxH2ZgC7/GSYDabceDgYTyVk40ZWdP9lFX7MxHOcZX4nEbqffIkUucOhYqJ\nBYVOtAM2KxzzKySXiZuuf5D8jXH62tfTY1/1eNvXX72RjMnbH9vYjEmSAo1pcNlQYwr2M+G9bFHx\nSfzyuXzExblMSFY1JjXPnYHHoX4mIvE+KXU+K4yTN4lc2G2OBbKG8NdiCHTfYFoTcraGGFMoMXV1\ndSHJaAywLrlasqG+VvfHVqsVomj3klSoE1MsfCZiK6YIiZLhCznF3isi5Wh0j9awcDs5XMc1/Y1r\n+3rO33Zv27yNq/qKKZBtocTk6fjRHlMg9Q7ddu6HH/HsM0972R7omHk4rzXYso6YRFHEp4VfYO3q\nVSEcM5yYQvlMyBGTr/piJaZInzvkC3ssKHRaLaB9OMfC7V4hgba6PG3zVzaQ+sKpV+6YAi2ndkyu\nXdihxWS29CM+Pt7L9kBbguG9T6IoQqPReNl/cLe6BLvdjj17P0PBtueQmJjop5x72UBjCmxboPUG\ncsxAtg/XmIKtN1Lnjox4VQiRC0kCrBbA0gdYeh1zLjzy32r0vA3w32rxVq8/asWkRKsxlJi8/TEN\nLKbe3r6H9wnxVUewMXnjPab/+exzHDv+jZ86JOe2g0e+xPZfPg+j0egnpoFjhfo+eat3aEyBl430\nuePvtSodU6C9JXLGpABeFULkwmYBrP0B7BjqeLrrc6G0PKIxpki10AI9ZmRi+qakZNBQgjoxpYwd\nA0DCgYOHoNfrYTZbsHLZUowdO8Ztv5aWFnx79hxmz5qJUaNGBRBToOP4Sv7ueO5EPiYKBRMLCp1G\n61jDQhIBcXCXqb/WneRnH2/CKRupegMpq/Rr9VVW3nolSYLZbPEx8VG5mDasy8OPZRfR09uDTevX\nQRAElHz7HR50dzv3ttlsGDtmDF54fisEQRPxmEIvG6l6ee74L6sgXhVC5EKrc/wAjmGR/h5A8nSv\niMHCaSFEqnUR6ZiUfq2BtAzlqffs9z9gsXPSpvoxLXgqF0/MnIE9ez/Dr1/diVUrlqseU2hlI1Uv\nz53AyiokSoYv5BR7r4iUI0mOS04t/Y4hEWmghRCsQMc/5aw3nLKRjsnbNjVi8levgJ9afsaECROi\nKqZRo0ZhzJgxHrepE1Oo9YZTljEFVjaceskTJhYUOpvFsdqmzfzwniEior11LU9ZtVpoasTku972\n9naMefyxqIrp0RCNiKvXrkdJTKHWG05ZxhRY2Uj15ARIEOT9iQJMLCh0Go2HNSyiWXScdO6iMabA\nfXv2LJYtWax2GB5t3bwJlyouu9zKXQ2h9EypyV9vWTQZbu/tyME5FhQ6rd7xI0mOW6db+lzmWEQj\nlVokPkVjTIHp7e2F3W6HVuvtBnTqMxgMKscn99yBSPPXWxZNhtt764VGuYaZJEnYtWsXbt68CYPB\ngHfeeQdpaWnO7UVFRfj444+h0WiwefNmvPrqq37LeDJcmpoUrSTRcb8QuwXD6mT2S80WTzS2Gt2P\nbbVa8X//3z+xesUKdcIB4O99ulJ5FVMzM5QKxu3Y0SUaY1JaFL8HCg6FFBcXw93zoTsAABhkSURB\nVGKxYN++fXjrrbewe/du5zZRFPG3v/0N//nPf7Bv3z58+umn6Ozs9FnGGyYWFDqrGeh7AFj7HHMs\nJFHtiGSkZpIUja1G92Pr9Xo8MWsGRo82qRQP4Ot9un//PqqqqzE/N0fRiKIzuY7GmJTG9wAAysrK\nsHTpUgDAvHnzUFlZ6dym0Whw9OhRjBo1Ch0dHZAkCXq93mcZb5hYUOgEjfduPOcqcB4yaJ+rxAkA\n5CjrgSaceoXQy/paEU+NmPyt0ieE8VqdMXnaHGpMwb3WqlvVOHDwMJ7P3xJ4TBF5/70d92HZiJw7\n4fzufH0mojCmiJ07CvduKLjyZnd3N5KSkpyPdTodRPFRg1Cj0eDEiRPYunUrFi5ciISEBL9lPOEc\nCwqdTu/4GbjsVLQ/WjRr4OSUJMfzA8t9a3QP/yAMbBcBm83xr1bnKD+4rN3mOGF0LhNFB+Z1DNyq\nXaMdWtZudezjLyat7tEXgWtMkDzXK0dMWu3Dia+eYhIc20OJSaN59Ho8xjT4/XeNycv7PxCTTuf4\n9+F2u9YA6BMCjEk/aJt8MdnsIpqamnDp4kWIdjuypk3Dr9/4P15isgF2ewgxiQ8/4wG+T67v/0BZ\nb58JnzGFee54i8nv5zTM81m1cwehn88D5078wB16FaJgImM0GtHT0+N8PPTeOkBeXh7y8vLw9ttv\n4+DBg0hKSvJbZjAmFhQ+QXAkGPBwrwhBcF9Ia8h2DaA3eK/XW1nh4Zevt4l5guC482qw9TKmgGMS\nNFqIWp3nPzIyx9Td3Y1//OMfmDVr1pDddTodJkyYgC35+b4nagrCownHQcekCe19EgRAePhlFlJM\nan0meD7HotzcXJw6dQrr169HeXk5srKynNu6u7vx29/+Fv/6179gMBiQkJAAjUaD3NxcnDx50mMZ\nb0bGu0lEsktISEBHR4eXhajkZTQakZWVhfz8/Igfi0hRCl4VkpeXh7Nnz+Kll14CAOzevRtffvkl\n+vr6UFBQgPz8fOzcuRN6vR4zZszA1q1bAQBnzpxxK+MPEwsiCtqDBw/Q29urSFIxwF/3K9GwpOBQ\niCAI+Otf/+r2XGZmpvP/BQUFKCgoGFJucBl/eKYSUdBKSkqwZcsWxY7X2dmJ5ORkxY5HRKFjjwUR\nBU0URUUXnjKZTPjpp58UOx6RYobNysWBY2JBRFFBFEXs3bsXiYmJzkljra2tuHv3Lrq7u7FixQq1\nQySSX5Tc30NOTCyIKCoIggCTyYT8/HzY7XZcvnwZEydORG5uLudXEA0jTCyIKCh3797F+PHjZa9X\ncGm5abVa5OQovWomkQo4FEJEI11FRQVWrlyJr7/+GgCwatUqxMfHy1J3fHw8Dh8+DIPBgLq6Orz5\n5pvsraDYpom9oRCesUQUFLPZjLi4OFitVixatAjffPONbHWvXbsWa9euxaxZs2A0GnH58mXZ6iYi\nZbDHgoiC1trairFjx+LKlStYtGiRbPXabDYcOnQIY8aMQUFBAeLi4mSrmygqxeBQSOy9IiKKqLi4\nOBw6dAjz589He3s7Hn/8cVnq7erqwt69e7FlyxasWbOGSQWNDAreNl0p7LEgoqCsX78+IvWeO3cO\nO3bsgMHg5b4ORDQsMLEgooDZbDb885//RFpaGnJycmSbtAkAVquVSQWNPDE4FMLEgogCdv36dWzY\nsAGTJ0/G2bNnsWTJEtnqtlqtstVFNFwIUTJ8IScmFkQUsNraWmzZsgWCIIS9EqYkSSguLkZ/fz/s\ndjvS0tLkCZKIVMXEgogCJkmSLC2sO3fu4Ntvv8WGDRtkm/xJNCxxKISIRqp79+7JtlhVaWkpfvWr\nX8lSF9GwFoOJRey9IiKSXWNjI06dOoXNmzeHXdeDBw94KSlRDGNiQUQ+9fX14e9//zuysrJgs9nC\nrs9oNEKr1aK0tFSG6IiGOY0g708UYGJBRD4lJCTg/fffh8lkwpEjR7B79+6w6hMEARs3bkRycjIK\nCwtx/Phx3Lt3T6ZoiYYZQSPvTxSIjiiIKKoJgoD+/n5YrVb84Q9/kKXOWbNm4cUXX8SSJUuwd+9e\nWeokIvVx8iYR+dXQ0ID6+nq8+OKLstcdHx+PKVOmyF4v0bDAdSyIaCQqLS3FCy+8IHu99fX1OHPm\nDNauXSt73USkDiYWROSTxWJBXFycrCsEdnZ24tixY8jMzORlpzSyRcm8CDkxsSAin7RaLbRarax1\nFhUVYfv27bKti0E0bMXgUAjPaiLySavVwm63y1bf7du3kZGRwaSCKEbxzCYiv+QaBrlz5w6+++47\nPP3007LURzTsxeDlphwKISK/JEkKq3xbWxuKioqQmZmJV199VaaoiGJAlCxqJScmFkTkV0JCApqa\nmjBp0qSgy0qShMOHD+O1116LyVtEE5G76Og3IaKolpeXh5KSkpDKCoKA0aNHRySpcJ37YTabUVRU\nJOt8EKKI41AIEY1Evb29GD16tNphOPX396OoqAg2mw0ajQaSJMFut2PVqlU4cOAAZs2ahblz56od\nJpF/MdiLFx3pDRFFNZvNFtYlp3PmzMHJkydlieX27dv45JNPsG7dOkyZMgUmkwnbtm3D888/j4aG\nBpjN5qhKgohGGvZYEJFfycnJAIBLly4hJycn4HJ3795FaWkptFotqqqq0NTUhFdeeSWsWKZOnYrM\nzEwcOnQICxYsQGpqKvbv34+EhATMnTsXO3fu5FwOGj6iZPhCToLkZbp3VVUVACArK0vRgIgoel29\nehXXrl3DuHHjsGzZMo9f4JIkoaysDDdv3kRdXR1mzpwJvV4PQRCwZcsWFaImCpzS333i1e9krU8z\ne6ms9YWCPRZEFLCLFy+ivLwcs2bNwsWLF7F582ZMnz7dbZ8TJ04gLS0N/f39+OMf/wiDwQAAaGxs\nxPHjx3lfEKIYx8SCiAL2yiuv4Omnn8bly5eRk5OD/fv3Q6/XY/PmzZgxY4bz9uo3b97Ezp07nUkF\nAEyePBk1NTVoaGjg3UyJBsTgUAgTCyIKSlZWFsaNG4eDBw/izTffREtLC4qLi7Fnzx4YjUbYbDZs\n2rQJcXFxQ8ouX74cn3/+Odrb25Gdna1C9ERRJgaXtuccCyIKiSRJKC4uRmdnJ9avX4+kpCS0t7ej\nr6/P70JaVVVVuHz5MsaNG4dFixZBr9crFDWRb4rPsbjxvaz1aWYukrW+ULDHgohCIggC8vLyYLPZ\ncOLECXR3d2Px4sUBrc6ZlZWFrKws/Pzzzzhx4gSsViv6+/sxe/ZszJkzR4HoiaJDLF7BxMSCiMKi\n0+mwYcMGSJKE77//Hj/88AO0Wi0EQUB2drbH+RT37t1DYWEh0tPTkZGRgQcPHuD69euYOXOmCq+A\nSEWcY0FE5JkgCHj22WedjyVJwo8//ogff/wRer0eGo0GBoMB3d3diI+Px+9+9zt0dXWhvb0dqamp\nWLhwYViLcBFRdGBiQUQRIQgCFi5ciIULFwIARFFEf38/EhMTnfuMHj2aq2TSyMahECKi0Gg0Grek\ngogQk0MhsfeKiIiISDXssSAiIlKLgkMhkiRh165duHnzJgwGA9555x2kpaW57dPX14fXX38d7777\nLjIzMwEA27Ztg9FoBOBY6O7dd9/1eRwmFkRERGpRcIGs4uJiWCwW7Nu3DxUVFdi9ezc++ugj5/bK\nykr85S9/QUtLi/M5i8UCANizZ0/Ax+FQCBER0QhQVlaGpUsdNymbN28eKisr3bZbrVZ89NFHmDp1\nqvO5GzduoLe3F2+88QZee+01VFRU+D0OeyyIiIjUouBQSHd3N5KSkpyPdTodRFGE5mGvSU5ODgDH\nkMmA+Ph4vPHGGygoKEBdXR1+85vfoKioyFnGEyYWREREalHwqhCj0Yienh7nY9ekwpuMjAykp6c7\n/z969Gi0trYiNTXVaxkOhRAREY0Aubm5OH36NACgvLw8oPuhHDhwAO+99x4AoKWlBT09PUhJSfFZ\nhj0WREREalFwKCQvLw9nz57FSy+9BADYvXs3vvzyS/T19aGgoMAlpEcxvfDCC/jTn/6El19+GRqN\nBu+++67fXg7e3ZSIiOghpb/7pIarstYnTJkta32h4FAIERERyYZDIURERGqJwXuFsMeCiIiIZMMe\nCyIiIrXEYI8FEwsiIiLVxF5iwaEQIiIikg17LIiIiNTCoRAiouhlt9tRV1cHrVaLjIwMtcMh8i/2\n8goOhRDR8NfW1obCwkJ89dVX6OvrQ1tbm9vtoIlIOeyxIKJhp7GxERUVFbDb7bDZbHj88cdRUFCA\n2tpaXLlyBRaLBS+++KLaYRIFIPa6LJhYENGwYLVacezYMdy9excNDQ3IycmBXq+HTqdDV1cXDhw4\ngOnTp2Pr1q1u9zogimox+FllYkFEUam5uRnff/89dDodBEHAmTNnMHfuXMycORNvvPEGtFqt2iES\nkQdMLIgoqoiiiP3792PixInYtm0bBEHAF198gd///veYOHGi2uERyYs9FkREkVNfX4/i4mIUFBQg\nOTnZ+bxer2dSQTGKiQURkaxEUURJSQk6OjqQnp6O119/fcgcCavVivr6eqSnp6sUJREFiokFEamm\ntLQUtbW1WLNmDcaOHeu27erVq6irq4PdbodWq0VjYyMTC4o9HAohIgpfbW0tSktLsWDBAjz99NNu\n25qamnD69Gnk5ORg/fr1nKRJMY6JBRFRWK5evYrm5ma89NJLbs9bLBYcPnwY48ePx44dO3jJKNEw\nxcSCiBRVXV2NzZs3uz3X3d2N/fv3Y8eOHYiLi1MpMiIVxGACzSW9iUhRy5Ytw6lTp9yeKy0txbp1\n65hU0MgjCPL+RAEmFkSkKIPBAKvV6vbcqlWrUFJSgpqaGpWiIiK5cCiEiGTV39+PGzduwGazYf78\n+W7bLBYLPv/8c7zyyituzwuCgB07dqC0tBRXrlyBIAhYsmQJxowZo2ToRCqIjl4GOTGxICJZDKyY\nmZycjCeeeAIWiwWFhYXYvn07BEFAa2srjh07hpdffhk6nec/PQNXiNjtdpw5cwYtLS1YsWIFxo0b\np+RLIVJMLE5SZmJBRLI4cuQI1q1bB5PJ5HwuKSkJR48excaNG3H27NkhPRXeaLVaLF++HJIkobCw\nEOvXr8fo0aMjFToRyYhzLIhIFhqNxi2pAIDU1FRMnjwZ586dAwBIkhRUnYIgYPv27fjqq69ki5Mo\nqnDyJhGRZ96ShieffBJWqxWTJk0KKUHQaDRYtGgRDh48GHRiQhT9BJl/1MfEgohk0d/f73Xb8uXL\nUVVVhQkTJuDixYtB1z116lQsXrwYn376aTghUoy7desWbty4gY6ODiahKuIcCyIKSk1NDSorKyEI\ngvOnp6cHS5Ys8Vlu7ty5MBqNqK2tRU1NDaZNmxbUcVNSUrB06VKcP38eCxcuDOcl0DAjSRLKysrQ\n3NwMQRCg0WjwzDPPuF01dOTIEUyYMAEmkwmVlZWorq7G9u3bkZiYCEEQ0N/fj9raWtTV1Tkvd3ad\nOCmKImbPnq34a4uW4Qs5MbEg8qG9vR0VFRVISUnB5MmTYTKZYnIWdyB++OEHNDc3Y+rUqcjPzw/6\nfTCbzTCZTFi9ejX27t2LjIyMoO8DMmXKFFRUVARVhoa3W7du4cKFC3j22Wedly/b7XYUFRXBbDY7\nrzASBMG5ffr06ZgzZw5KS0vR29sLURQRHx+PjIwMrF69GgaDweOxjh8/jlu3biEvL0+ZF+cIXLlj\nKYSJBZEXtbW1+OSTT/D222/j3r17uHLlCjo6OpxfqIIgOLtbXbtdu7u7sXHjxpi7iuGnn35CTk4O\nMjMznc/19PTgzp07uHPnDqZNm4apU6cOKWe329Hc3Izq6mosWLAAADB//nxcv34dc+bMCTqO3t7e\n0F8EDRuSJOHUqVOw2WzYsWOH2zatVouNGzf6LP/YY49h1apVQR1z7dq1yMjICDZUGkSQvAxEVVVV\nAQCysrIUDYhITTabzW2NhcbGRpw/fx5ardbZ7e+PJEk4evQo3n//fYwaNSqseO7duzfkduJqkSQJ\nly5dQn19vfM9SkhIwKRJk/DBBx9gzZo1iI+PHzK2rdPpMGHCBMyZMwd6vR5WqxV79uzBa6+9FtKd\nS6urq9HR0eFMUii23LlzB2VlZbBarVi5cqXin3/Fv/s6fpK3vsfGy1tfCJhYELn48MMPkZaW5kwi\nBk6PgYRi8Okyb948pKenyx6HKIooLCzEY489hs7OTqxcuRKpqamyH0cJkiShtbUVFRUV6O3thd1u\nx/r165GYmBhynZ999tmQViwNPzabDTdu3HAu5S5JEiZNmoSnnnoKGo061xYwsQgfEwsKSHV1NSor\nK2EwGPDUU0/5/JLr6elBWVkZsrKykJqaOqzmJLS1taG8vByrV6/2u68oiigvL0dDQwN0Oh02bdrk\n9bVaLBbcvn0btbW1bhPHRFEEAEyYMAHJycno6upCV1cXmpqasG3bNphMJkiShHPnzqG9vR2SJLkl\nPRaLBUlJSVi9enXArf+mpiaUlJTAaDRi5cqVSE5OBuD4I2+z2RAfHx9QPQDQ19eHW7duoampCTab\nzW2b65+WlJQU5+RNOVy4cAEmkwnTp0+XpT5SjtlsxvHjx2G326HX6zFjxgxMnTpVtURiMMW/+zpb\n5K1vtPoNECYW5Fdvby8++OADzJ49GxaLBdeuXYPNZsPYsWMxfvx4rFy50m3J5Y8//hjz5s0D4BiX\nd235D9R39uxZ/PnPfw6oFS5JEiorKzFq1CiPY/hy++KLL7Bhw4agvgTb2tpw6tQp5905BxKAgf8b\nDAZkZmYiMzPT48Sx5uZmdHd3w2QywWQyBfXl3tnZie+++875ePCxASAtLQ2TJ0/Gt99+C5PJhDVr\n1sBqteL06dPo6+sD4Bi31mq16O/vhyRJGD9+PJ555hm3Y7W0tKC8vNx5aWl8fDxmzJiBiRMnep0Q\nFwmff/45nnvuOUWPSeHr6elBYWEhduzYgYSEBLXD8Ujx774umRMLExMLGob6+/vR1taGtrY23L17\nFyUlJdi1a5fbl+rly5dRU1MDvV7vLCeKIiRJQlxcHFasWIFr166hubnZuU0QBKSnpyMtLQ11dXVo\nbGx0lpk7dy66urpw8+ZNbNu2Lagv3mDZ7XYcPnzYGavJZMLkyZOH7aQuSZLQ2NiIuro6LFq0yOt9\nOgZraGjAhQsXnL9DSZKQkpKC7Oxs1b4UzGYzDh06hDlz5uCJJ55QJQYKXV1dHS5dugStVospU6Yg\nOztb7ZCGYGIRPiYWMcBsNuPKlStoampyPuepS35wz4G3571153srP5hri3nwY0mSIIoi9Ho9srOz\nMWHCBGcXqCiKaGhowJ07d5CZmYmJEycO6R61Wq344osvMHv2bMycORPnzp1DZ2cn4uLisGTJEme3\nvlzsdjvu37+PqqoqNDQ0ID8/35lAUeTV19fj6tWrsNlskCQJdrsdmzZt4u9gGOvs7MRXX32FZcuW\nIS0tTe1whlA+sfhZ3vpM6t+wz2diUVVVxcQiSpjNZnR2dqKjowNtbW3O7moAznHK4TafIRw1NTVo\nbGxEdnY2TCYTzGYzLl68iO7ubmg0Guf7YDQaMWfOHI8TBa1WK5qbm52L7uj1ehgMBiQmJiI1NRWj\nRo1yez8HxoanTZvG1nKESZKE06dPw2g04sknn+SQxzDX29uL0tJSWK1WJCcnIzc3N2p/p7W1tcjM\nzFTuu+9+q7z1JafIW18IvCYWwKPMjYiIaKSYNm1aSJdCh2SkJRZEREQUQQ/uyVtfkvrr3nDlTSIi\nItXE3vB1dFw4TERERDGBPRZERERqicEJ90wsiIiI1KJgYiFJEnbt2oWbN2/CYDDgnXfecbvk9+TJ\nk/joo4+g0+nwy1/+EgUFBX7LeMKhECIiohGguLgYFosF+/btw1tvvYXdu3c7t9lsNrz33nv497//\njf/+978oLCxEe3u7zzLesMeCiIhINcr1WJSVlWHp0qUAHDdQrKysdG6rqalBenq681YG8+fPx/nz\n51FeXu61jDdMLIiIiNSi4FBId3c3kpKSnI91Oh1EUYRGoxmyLTExEQ8ePEBPT4/XMt4wsSAiIlJL\nokmxQxmNRvT09DgfuyYIRqMR3d3dzm09PT0wmUw+y3jDORZEREQjQG5uLk6fPg0AKC8vd1u2fNq0\naaivr8f9+/dhsVhw4cIFZGdnIycnx2sZb7jyJhER0QjgeoUHAOzevRtXr15FX18fCgoKUFJSgg8/\n/BCSJOGFF17Ajh07PJbJzMz0eRwmFkRERCQbDoUQERGRbJhYEBERkWyYWBAREZFsmFgQERGRbJhY\nEBERkWyYWBAREZFsmFgQERGRbJhYEBERkWz+P6L1U6dArakCAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x52c884b10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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UqcM9vUlGRgalpaV4enoyePBgFAoFKpWKsLAw6buMfXrasHjXyYbFD/urYdGC\nIAhcuXKFsrIyfHx8mD9/frdPIzMajZw5c0Z6eMgXysBHEAQqKip49uwZdXV1eHt7t/nz8vKSvAxa\nrZbjx49LhkZsbGyHZly0pqmpiczMTNRqNYMGDSIsLIzQ0FDc3d0xmUwYDAZcXFysnvff/OY3+c1v\nfuMUI9hgMHDw4EHGjRuHwWDg6dOnrFmzpkOelQsXLjB8+PB2Yyz0ej1HjhyxGLa5d+8epaWlLFmy\nxKLtgwcP0Gq1baqvdhZBEDh+/Dje3t7dniStpebNa6+91u9jtJqamti3bx8LFy4kPDy8t9Xp18iG\nRddx2qwQtVrN3//+d+bNm0dBQYG03NvbG39/f/z8/AgJCbE5E6GjtNSeCAgIYO7cuXK8hUwbHA0q\n7S6qqqqcnuL61q1buLq6MmHChA5t9+jRI86ePcs3vvENh47J0aNHJXe50Whk7NixFrNfWjh9+jSD\nBg1qMw23qxQXF3P+/HkSEhIIDg7G29sbT09Pp/6e9+7d44svvmDjxo1Oy3XTGzx69Ihbt26xYcOG\nXp9NNRDoacPiN57OvUf8QFPlVHmdwanTTXft2kVoaCjjxo0jJCQEURRpamqivr6euro6ioqKqKmp\nYdq0aVbTGDuCVqvl7t27qNVqvL29mTRpEunp6VRXVzNnzhzZWpf5SqFWqzGZTFbjFMrKysjIyEAU\nRWJiYpg4caLT+tVoNNIb8rBhw5wm90Wys7Opra2lsbGRnJwcZsyY4TTvCJiTYR07dqxfDoUUFhaS\nmZnJ0KFD243d6UuUlpYCSN7GvpZVtqcNi/e9nGtYfK+p9w0Lh8zbFgOhvYQ2q1atIi0tjeLiYmnq\nVsvJExoaKo1xZ2VlkZWVxcSJE+1WyBRFkYKCAu7du4cgCFLAV1xcHP7+/hw+fJiJEycybdo0DAYD\nx48fZ/jw4T1aZ0JGpjc5cuQIw4YNo7a2tk3OkuDgYNasWeN0r01dXR2HDx9m27ZtHX5DfvbsGTdv\n3pR0ampqYunSpTYDJlvfH8rLy0lISOi84la4dOmSwxlS+wJPnjyRqsxGRESwYcOGHhkOfvjwIY8f\nP5b6ask2O2vWLIsaNqIokpmZyfPnz/H395cSkT148ICcnBwAwsLCUCqVUmxUTk4O3/3ud7t9H2R6\nDrt3hQsXLvDgwQPq6+tRqVRs27bNrjBfX1/WrFnTbqfTpk0jJiaGP/zhD2zdupWYmBhpXet0ygqF\ngqioKJZZyD+eAAAgAElEQVQvX27Vqh03bhyZmZlSEN348eN7PcJcRqYnEEWRQ4cOMWbMGIYPH96j\ngXmHDx/m5Zdf7pTBcuvWLdasWWNhAJ08eRKA5ORkq/tQVVXF8ePHmT9/vtP3MSwsjNOnT3c4XqW7\nKS8v54svvqCxsdFiivSIESNYu3Ztj8aW3blzh5qamja1b0RR5MqVK2RkZODv7y9lf502bRozZsyg\nrq6Oa9euUV9fz7hx46xW69XpdDQ0NPTUrvRJ+nd0j3XsDoXU1taSl5fH+vXrOXz4sJQ3XqFQSOOv\noaGhTJ061W4nDx8+JDc3V/ouCIIU7Pnixfzo0SMuXLjA1KlTiY+P7+r+ycgMOEwmEzt37mTZsmWc\nPn2aUaNGcf/+fVasWIFOpyMqKqrTssvLy6UZNi25PrRaLbW1tajVasBca+O1117r1PTv7Oxsbt++\nzYIFCyxyWVRXV3Pq1CmGDRvG7NmzpftCWloaWq2W5cuXd9vDtKGhgSNHjjBlypReyzScmZlJWVmZ\n9H3w4MFMnDixT8SOHTx4sI1nKjIykkmTJknf6+vrOx0/l5mZybNnz6S8Lb1NTw+F/Je3c4dC/k9j\n7w+F2DUs0tLSSE5OtnujunTpEiEhIXZ/hI4UZGrd//Xr10lKSpLjJmRkWrFr1y7WrFnD8+fPqaur\nIyEhgYKCAp4/f46LiwsFBQV4enoyZ86cDt3sr1+/TmVlJeHh4SiVSlxcXFAqlbi7uxMYGIiPj49T\nHu6iKHL+/Hmqq6sZOXIk8fHxktzy8nIyMjIQBIGmpibmz5/fY9f/yZMnmTBhQo/eb/R6Pfv37ycx\nMbFPl08oKiri2bNnVFWZH1qNjY1s2bLFafLVajW//vWv+cUvfuE0mZ1FNiy6TpeDN1uSDLXUtFAo\nFCxcuNDC0u6MYdHCsWPHMJlMqFQqYmJiGDFiBA0NDVRWVlJRUUFoaChRUVHk5uby4MEDAB4/foxG\no+FHP/qRPB1VZsDQkg0zISGBUaNGcfjwYVJSUqye4y2FtFrc09HR0UyYMMHm9ZCXl8f9+/ftlnqv\nra3lxIkTLF682GmprvPz86VaMsuWLevVN3SNRkN6enqbKbXdycGDB6WcK32ZU6dOUVxcTFBQECqV\nikmTJhEREdHl+6soipw7d466ujpWrlzZq1VvW+hpw+IP3o4nmXOEbzdWOlVeZ+jy3CSFQsH06dOl\n7waDgdTUVCkVs8lk6tI8/pZUxQaDgdzcXE6fPo2vry/BwcGMGjWKkpISDh06RGhoKCkpKRgMBvLz\n81m8eLFsVMj0a0RRRKPR0NDQwO3bt9FoNKxbt05yS7cO1nwRDw8PZs+eLbmW8/LyOH78OCtXrpTG\n7FsTGRnJkydP2L9/v8XNveW9Q6FQYDAYWLhwITk5OVy6dAkXFxdmz57doeybLzJixAhGjBghFSbb\nvHkzXl5enZbXFTw9Pamp6dnKkC4uLn3eqAAsijw2NDTw29/+ltjY2HZT1FtDrVZLGVyNRiOzZ8/+\nytUjaY1yAD6merS6aW5uLl5eXoSFhVFbW4u/v3+3Pfz/9re/8frrr8vGhUy/wmg0curUKbRaLe7u\n7nh5eeHt7U1MTIw0c0Kv13Ps2DGGDRvGtGnT2shoSVGtUqnw8/Nj6dKlAFLSML1ej1KpJCUlpUsB\niyaTicuXL1NZWYmrqyvz58+3+RJhMBiorKwkNDTU7r7v27fPqS72jnLr1i0Ap88+sUZtbS1paWms\nX7++2/tyJr/97W+JiIiQMr66ubkRHh5ORESE1aG3srIybty4IRUB9PX1ZerUqX02e3JPeyz+5ONc\nj8W3GnrfY9GjhsWOHTuoq6sjOzub8PBwxo4diyiKKJVKBg0aRFxcXKdONlEUOXPmDE1NTbi4uKDT\n6Rg9erRFcJGMTH9g7969LF++3O518Omnn+Lu7o6HhwclJSWsX7+eoKAg6SE/ZMgQKa9BcXExN27c\nkLYVRRGTyURgYKBTZ1ns2LGDCRMm2Hwgi6LIxx9/zNWrV1m6dCmTJk2yWp/i/v37GAyGXg3cvnDh\nAgDz5s3rtj4ePXpEVlYW27dv7/cvP1qtluLiYgoLCy3Ss4P5dw8JCWHy5Ml9YpjDEXrasPizkw2L\nf/mqGRYmk4mKigoCAgKorq7m6tWr0pS1qqoqFi1a1G5Ee0tEfEstAVEU0Wq1LFq0qEsuWRmZ3kIU\nRSorKyUj4M033+zQtp988gn+/v7Mnj1bin0wGo1kZ2dLVWIDAgLsegu6ilarJS0tDY1GIyXjsjV1\n9NSpU1KlYoDw8HDi4uJwc3Pj/PnzjB8/vtfLlefn55ORkcH69eudOlPh4cOHfPHFF4wePVqe9dZH\n6WnD4n99nfvc+ob6K2ZYdBVBEPj0009Zv359n5iGJSPTVdLT0yktLSU8PJzw8HCGDh3a5fTSt2/f\nJjs7m6lTp6JQKMjKysJoNPLyyy+3u63JZOLGjRsEBQUxYsQIm0Ml1uI0WsjNzeX+/fuAOYZg6tSp\nbcqk37x5k5ycHJKTk2lqauLu3btS3RVHSsD3BEajkQMHDjBhwgRiY2O7LG/Pnj3ExsY6NQOqjPOR\nDYuu028Mi6dPn3L58mVSUlL67NicjIyj1NbWcuzYMWbPnt2lvBPW+Pvf/86gQYOkImlTpkxpU3js\n+vXr5Ofn09TUxKZNm/Dy8uLx48dkZmayYMEC6urqyM/Plwq5teSuacmAC2bjIiAggHnz5tk0QAwG\nA9euXaO8vFzyTioUCiIiIoiOjubSpUuEhYX16bf3y5cv4+vr2+Wh1UuXLjFy5MhuTYEu03V6+tn3\noa9zvXP/pK5wqrzO0C8q1jQ0NHDt2jW2b9/e26rYxOobnCiCtbc6a8tb7Lu+IGMg6+wMGV3UubS0\nlIsXLrBt61YUL2avdILOr7/2Wrs637t3j0WLFpF29qwUhBcaGkpoaCjDhg1jWFhY27d0K/tdXV3N\noYMHcXN3Z9myZZbj6KKIq6srs2bNslgmiCJFRUWSJ6WioqJPn1+zZ81iz969jB492rJEfQf7mzNn\nDp999hmbN2/udp372zXRL3TuJgbirJB+YVikp6e3W+q5N9A9volQW4mbUQuCETx8wMsHZVTz+LIg\nmE9QReuHhwCCaD6bFEpo8ReJgvl/hbLViS1aymhehCiY2yiVmBdakUHzKrFZhlKBRfJYqzLEVhdb\naxnt6awwL3NU55Z9bLPfzSqKovVj16s6K2z/Vkplc3+tdW4W8oLOFRUVXDx/gZc2rgddY+d0Vira\nHiOFCKKCL88v+zq/vGk9d+/eZfXi+Sib9fBRKWmorgSN2uHjHOTlyoYVS2nSaji0dzfxcZMYHRPT\n9rdqdS4qFQqGDxnE8CEtiYEEc5997ppoOUdF1iUvZsff/8r2LS/h4enRqfMr7fwFFsycZv7d5WvC\nuTrbuyba6CyahdvSWdsInvJQe1foF4ZFcnIyOTk5HDhwoE9MzaqqquL8+fNknz+O0KTmP7auMq8Q\nAb+g5hMZRFGkoryS4OBBbesqCCIgtBXecrKLrZeJXy63kGGyrqDVtjb6c4YM8YX/oR2drfTZ0rb1\nqu7c7w7rbKc/U6v1dmTU1tZyJjWVrZs3tvqdO6GzE46RSgGT4yZ+uUzSx/Tl5w4cZy8PDzavX0Nq\n2nlycrKl5Q0NjSxeMJ/Bg1uNI9vUue9eE26uKl7ZsoljJ0/g4+1DQpx5WKTFS2kOkG01ff6F88to\nNFJTU8PgQYFgMlrp76t5TdiVYdG2+6+JL3UWrbfrJgagw6J/GBYAY8aMkTL0ObtaY0c4evQo5eXl\nuLm5senbP2TU8HCoKUXh7Q8u5joqarWa3fsOEDJkMMGDBpGRmYkgCMRERzNhfGy/n14m0znOpJ1n\n6+aNffr393D3QK1WdzqOafHC+Rbf791/gLqhwdKw6Ke4ubmxLmU1VVXVPMrNtYg1MZlMlJQ+J3bs\nGCZNnNBm21OpZ0lesqinVZbpB8hDIT3Ijh07cHV1xcvLC4VCQWVlJcuXL+fw4cMIgkBycnK7Zdyd\niSiKHDx4kClTppCZmcmmTZvAqDdbwYFDW1nDIj4+PgwODiZl5Qpau/oe5+bx+fET0g0pLDSU+EkT\nUSpdqKuro7aujgB/f4KCApu3afE/tnIXtln+4rIXP2NjfYs8a9u92J812uu7p3W2JaOndLbV1iyv\noqKK4EFBzUZFR3Vu0akjOnd0v83LFi2Yz5Fjx1m/ZrWD+21fZ6PRhErl0mq5/fPr3v0HZF2/wSvb\ntuLqqnphO1syOntudO6aGDQoiJmD2iYmAwUPHj5k92f7mZo4GV8fHxqbGmloaMJgMODj4yvJaCv7\nq3dN9LzOjsoY+Ny5c4f33nuPHTt2WCxPS0vjgw8+QKVSsWHDBvNzDixmYoaHh/PLX/7Srvw+a1i8\n9NJLpKamotfrAfNUU39/f9atW4fBYODEiRNSDRFAyibo7Hzzoihy8eJFysrKmD9/Pu7u7lIODQx6\nEM2ZDC9fuYq6VfnfoSFDWiRIy2JGRRMzKlr6XlxSwpmz5wDw9/fD38+P4pISamprpb4D/P2JnzTx\nyz4tZIpWlr34ub311j474grsqIzu1tmWjI7I64rO9tvevXePmdOn2m1jnc7q3DkZKpULtc3nnzOO\n89gxMZy/mM7wiAg7Ops5c/Ycg4IC2b5lM7v2fsYr27Y0G2KOH+feviZix40ldtxYbt+5S2VVFV6e\nnnh7e7NqebIVGV/ta6Lnde6IjJ5D2cPGzEcffcThw4fbvJgbjUZ+/etfc+DAAdzd3dm6dSuLFi2S\nDIpPPvnE4T76rGHh5ubGihUrrK5zdXW1Wizp8uXLFBcXOy3Qs2Wu/YIFC6QsfBqNBlEUKS8v5+6d\n29RV1+CqUjJv1gz8/TtWNnhYWBjDwsLstqmtreXWnbuSsZG8ZHGfKC0s0zGaNE19/ncTRZH9h46w\nYN5cp8n08PBAq9O22+7ylasMDRnCxAnjAVi1PJk9+w6wZdMGp+nSk8THyVl/ZRyjp4dCIiMj+dOf\n/sS///u/WyzPy8sjMjJSMiQSExO5du0aoaGhNDU18eabb2IymfjOd75DXFyc3T76rGHRGSorK5k9\nezZgLvObkZFBQkICrq6uVnMFFBYW4uvrS0BAgFV5Y8aMIScnB7VaLRXJ8fT0RBRF8vLymDl9Bt6e\n7iAKYDRg3dptz61nn4CAAOYnJQEier2ek2dSzZUgFy/q4oPKnl5d09l5MnpCZnfL/1Jmatp5hkeE\nExE+rIOFtrr7tzK/rfxj915WJi9rzmDr3N//YvplJsTGNg/zWa67/+AhoihKRgVAUFAgC5Lmsmff\nATZvWGclLqWnzy/5mujbMntSfv9myZIlFBcXt1ne0NBgEVvl7e2NWq1m5MiRvPnmm2zatImnT5/y\nT//0T5w6dcpurOOAMixGjx4txWCEhoayadMm9u7di4eHB5cvX2bw4MFUVVXh7u6OUqnk8uXL/Pzn\nP7cpz8vLC3d3d2k4poXk5GTzB00DGNp7G3PGCW6W4ebmRsrKFeh0Ok6lnkUQBGZNn86QIZ1JsGJP\nL+fp7Fy6+2bRfTqvXrGcxsZGiopLyLiaRUHhM9587VUn6OUcnevq6lslv3Lu77929Spqamq59+AB\n+U8L2LR+LZ6enty7/4Ccx48ZMngwc2fPaiMhJGQIC+clsWvvPitBrz19fsnXRN+WaV3+8+dlXL56\nFTc3NynXUHlFBSuWLiU0tG9UVO29qQiW+Pj40NBqOL+xsRE/Pz8iIyMZPnw4AFFRUQQEBFBRUdEm\nm25r+k3mza6i0+moqamRPA9paWlMnDjRZk2CvLw80tPTWbNmjU2PBkaDOX+FIFgEb5qxFrhka3nn\ngpj0egPXbtygorISUODiopS2E0WhOVsizJ4xnUGDgl7Y2p4e3adz12Q4I3DM0bbO0tm6jNy8POrq\n60lMSHBAj478Vp3XWRRFzpw9h8FoYMWypSgUyg7IcExno9HAgcOfo1K5EDt2LGPHjG5n/6CqqoZT\nzdN0LXWyRnedX1/Va6I7dO6MjI6c5+b/KyurSD13vtVwmoKi4iKu3bjJupQUm/09evwYPH177Nm3\nM2BI+406wLba8nbbFBcX893vfpc9e/ZIy4xGIytXruSzzz7Dw8ODrVu38uc//5mzZ8/y6NEjfvrT\nn1JWVsbXvvY1jh49+tXxWNjD3d1dMirA7PZ50aiora0lPT0dnU7HyJEjGTVqFGlpaSiVSpRKJU1N\nTaxZs+bLIQgXFeZELMZmw6L1iS++8L+95Y58boubmyuzZ86w20YURRtj1fb06D6duyajM3p0tq21\nfh393L6MUdEj2f3ZfhIT4q206cjxd57OCoWCpYsXUllZxaHPj7IuZXUHZDims0qlYvOGdQ61bWHQ\noECWLlrIvoOH2bR+LfbprvPrq3pN2KKnZXTkPBcRRZGjJ07y2svbpLXFJcVcunyFyfFxXMnMRKFQ\n4O3lZTEE177Ozqe35qG0eACPHj2KRqNh06ZNvPXWW7zxxhuIosjGjRsZMmQIGzdu5K233mLbtm0o\nlUp++ctftpvy4SvjsWihpqaGs2fPEh4ezowZ5odyTk4O9+/fJyAggNmzZ2M0GvnrX//Kpk2bJGOk\nsrKSU6dOkZiYyNixY83CtI1mj0Uf52F2DjqdTg4o62OUlJaS8+gxC+YlYTKZKCwqwmg0ET1yRK/n\nunjwMJvaujpmzZjeq3q0prCoiNt3v2D1iuW9rYpMH+dq1jUiwodZBMdfycyivl7NiKhIAgMCEEWR\nk2dSeXX7VottHz3O7VGPxZ5A20MKneGlmjKnyusMXxmPhdFolMo6r1+/HqVSiSiK3L59m5ycHLZs\n2SK1dXd3x8PDAx8fH+7cuUNubi7+/v5s27bN8obfUnhJylzoHHexfdefLWzLGDd2DKdT0zh34SIL\n5iU5oGd36+yojM5+7qjO2JDXGZ0dwdw+LDSUvCdPOXLsOEqlC8PDh+Hi4tKc68SsU+jQUKZMjm9+\nQ+g5nWPHjeXgkc+tyLInwxmudtsyIsIj0Gi0XEy/TNKc2TZ175jOttpiZ19685pob/9sfe4r10TP\n6Fz6vIwZ06bSmpnTp1m0NxoNzTP5Onsdy9hiwBsW1dXVnD9/HqVSyYIFC/D39+f+/fuSRyY+Pt7C\nqGjh9ddf58yZM8TExLBhg40pb64eoBLNMRa6RjruzrPnmuzoCW5fxtLFCykqLuYfu/cyP2lOK0u+\nN3R2VEZnP3dFZ1v70D2/1dzZM9usHR87TvpcXFLC4aPHEASB6VOnED5sWK/r3LnjbO+zozJECp4V\nMsnCdW2Pjux3T51ftuiMjP54TfSMziaTiaqqaiuxZeZ2RqOBT/6xy5xev9PXhHPoXd9k9zBgh0JE\nUeTmzZuUlJSwYsUKqaxzQUEBT548YcGCBV3vRNdkjq2wlpe+D/PJP3a1Sj4k0x8QRZGL6Zepq69n\n1fLkbk9rX1ZWzrWbN5sTO/UdWjLXLl4wv4NTdmW+SoiiyM49n7F9y+Y264xGIzt27mbLpg1Wp+z3\n9FDIZ04eCtkkD4U4D5PJxKlTp9DpdLi4uKBQKIiIiCAxMRGAzMxMSkpK8PX1ZfHixb2sbe+SNGcW\nt27fYbJF4KBMX0ahUDBv7hzq6ur4/PgJaXlYaChTJic41Uh8kv+UrOs3zBVY+xirVyxHp9Nx9twF\nGpuaWLpowQtZaWVkzNeLn58v+U8LqKurs4gvq6mpJSDAn9Rz56mpqWX7ls3Si6eMc+j3Hovq6mrS\n09PR6/UsW7YMo9FIeno6RqMRDw8PgoODKSsrIyEhgWHDhnWPEoIA2gb60/jcZwcO4enpwbw5sztd\ncEqm9yl49ozrN2+hUCjw8vTC09MDLy8vPD08CAwMYMjgwbi6ujokS6/Xc+TYCYaFhTaPR/dtBEHg\n+KnTeHp4smDe3F4tTijT99h38DB+vr7kFxTwz2+8btX4bmho4MTpVIvZRj3tsdjnZI/Fxj7gseiX\nhoXBYCA1NRWNRsOgQYOYOnUq6enpNDQ0EBgYyJw5cxy+mXYJvfbLoRC7wyHtBSM5QmcCjOwHP+l0\nOlLPXcBVpWLp4oU9qLM9GY4EbDnaryP92dq2r+jsiAxz3hKDwYhG04RGo0Wj1VBdU0t5eQVFJSX8\n09des7qlRqMh42oW6oYGFApYtngxHh7uPaKzs86v58/LuXbzhlTcTxAEEuImEdmc1KfjOnckWLFz\nOvfc+dUfde6YjPynT8m8dgNvby9EUaSxsYnZM2cwPCKcxsYmDh89xraXNtnU+cHDbOrVamZMmwaI\nPW5Y7A9ybqKuDdXPnSqvM/Q7wyI1NZWsrCxGjBghFVFRKBTMnz+/59+8dY1g6vvTTdvj+MnTLJg3\nt8/XspDpHEeOHW+utGtJesYVbt6+w+svb8PPr2N1bvo6V7OuUVlV1ediRGSch0aj4djJ04QODWmT\nz+fylavU1tWxMnkZ9+4/4MnTpwBotTpWJi9tU4Dr/MVL1NXXEzV8uPk+KBsWXaLfxVhMmzaNESNG\nEBUV1fvjYu7eIIpgMpi9F318KOTIseMMDg5Go9HQ0NjI6hXLUSgUjI8dy5FjJ1iXssqplWFl+gaC\nYN2bNmfWTJRKJfcfZveLoY+OMGPaVNLOX6Cysorg4EG9rY6MExFFkdS08zQ2NbJm1Qqr3mmlUsnI\nqCgAJoyPZcL4WMAci/eP3XtZtTy5uW6NmflJ5sJ7p1PT8Pf3I9Cz515SB2IIfb8blPTz8yM6Orr3\njQoAo95cK8RosNNIwZenzoufaedzezJebGPvswKTSWBkVBTTp05FFJHGHCOHD2fNqhUcOXaCjKuZ\nfUrnzsnoqP7t6ezIfnenztb0cIbOMGvGdJ6XlXdSZ0f1d67O9mV8yfykJA4fO8aRY8cpKi7pgM4v\n9tNzOsvXRPvb7dl3gLiJE1i7ehWurtZehBQ8Kyxi3NgxbWS4uLiwdfNGLmVcsdr3kkULuJJ5zYrM\n7kPp5L++QL/zWPQpjPpWNUJs0dE5/da8Hh2Z/2/rs4hCAY1NTYSEDEF8ISbEw8ODjevWkHX9Bo8e\nP2Z0zKg+oXPnZDhb587Ove8bOru5uqLRaJqHutrKGB4RTsGzguaYBGf/Vs4+zo6uB6VSwZuvvYog\nCJw9d4G6urrmHCGd+a36znXcORkD55pYsnABt+9+waIh82zq/GWckLkq9F8+3kH4MHPunvp6NYvm\nz7MqW6FQEDrUucGUX0X6ioHTP3H3BjdPULlh3QrvW6xdvYqi4mKyrt+goaHRapspkxPIbo6vkRkY\nLF44n8+Pn7S5fnJ8HLfu3O05hXoYpVLJkkULpHF2mf7NoEFBVFVX21zf1NSEVquTvl/JzOKlDetZ\nvWI5q1csZ/uWzQy1Yzwk9HDpA4XCuX99Admw6AqCyTzV1C4v/tKd+eWdJyNpzmwaGxsxGIycPXeh\nTSulUomvjy8Hj3zOuQsXMRgMXerP9vfulmHPFd8d/fWWjPbburm5ERM9knv3H1iXoFBiMrX2vPW+\nzs7tzxky+qPOtrbt39eEXq9Hr9dbbSUIAnv2HWTjujXSsvHjYjmVehYb8xR6HYWT//UFZMOiK+i1\nYNSZh0QccvFZ++4IzpWxYF4SCXETuXbjJvcfPGzTcsG8uaxLWU1C3CQ+3bWny/1Z/97dMqy5U7uz\nv96S4VjbhPg4HuY8oqS0tM26hgY17u6tp5j2DZ2d1x/U19dTV1ffBRn98dywtW3/viasVbltaGjg\n+MnT7P5sPxvWrpZi8CoqKsnIvIper6esrBxRFBFNbYevRYMesd2XRBlHkWMsuoKbu3m6qSiAdLK2\nXAAKrF9ALcttrXekbddlxMfFNWeja73csk1AQICDRXqsyXC+ztaXd/Y4f/V03rR+LWnnL3Dz9h1W\nLFuKUukCiJxKTWPNqhUOyXCOzh2V4Uhb68vVajVn0s4himYXt06nw93dowMy5POrL+lcVFyMuqGB\nU6lnARAEEUEw4ePtw8L585pjK76Udf3mLUaPiiHGU4DqJwglX5jv2R7eiCjh5jWor4GaSvOQ9qAh\nmEKicZkyr519cx59w8fgXGTDoisoVYCiOZeFCcsLw9ZF15G3Blttu0tGW3kGgxGDQd88pau9fepo\nf7boms6O9ffV1Hnh/HnU1tay+7P9BAUG0tjUyJiYGFSq1rcCZ+y3PZ07KsORtubvgmDi0eNcHuXm\nIooi1dU1eHt74e/nz+Wrmfj6+jA8IsKujL7yWznW9qulc/iwYXzjza99uVYUrWTU/FLW8mVLyLx2\nnb2nz3Ppahb+nu58d2MyQQFG8y279Bmoa0GnNW+g08CQKAf2zXnIhoWMJbpGB2aF9F9MJhMpK5ez\nZ98BNq5bg4eHR2+rJOMEAgIC2PbSJurq6gZMnY26ujqOnzqDj483o0eNYtXyZB48zMbD3YNlSxZx\n/8HDF4wKmYGAIzVyPNzdcQ2P4b3//QYeRq3ZePAPRunuCbNWItbXwKN7NLq4YgiLoqnkOXKRg64h\nGxZdwcUVFAoQxWYDo7XbDtpa4S+6/hxpY8816UhbbLSx359er+fd3/6eSRMmICLy6/d/x5DBQxgy\nOBgvT0+S5szCx8enkzpjY7k9nR3Zb2v71LH97l2drcnoPp39/QO6UecX5XXfNXExPYPaulpe2rhe\nGt4pKyvnWWExK5KXUFlZRe6TJ6xZtbIdndvrz3k6y9dE9+ssCCYOHjnKyKjI5mBOBaLoy6kzqdSr\nb+Dm5toci2FOie/t5Y2H7hlPCwqYOiSMnkI5AF0WsmHRFVzdQXQzGxW6JjrnanS0TXvuw464Mdvv\nzzyTIJqk2bMIDAzAZDK7mJ8VFlFZVcWHf/uYiePHs2jBvBemOHWXzo7IsLXM8f2WdXaWzi/Ks36+\nnzh1GmNzWvzWbm2TSUCpVEjfW0f0t35LNRqNJCbEMzxilkU/Z9LOsX3LZgRB4IMPP2L8uLHcu/+A\n8SFsQuYAACAASURBVLHjXnjL7chxdnS9vTZ98bfqjB59X+d33/89SXNmkfM4l6fPnuHi4oJeb2Du\nrJmEhAyxIsvM4B7O1NpXZnI4k35XK6RPoWtqjq+wdXPp3xgMBjKuZlJXX49a3cDWzRulCpLpGVfQ\naLTU1NYSMmQwSXNmO7V0t8zARhAEdu3dx/ykOQwLs3w7TE07z2cHD7F00QJcXV0RBIH4SROJiox0\nSPb5i5cYFT2S8GHDeJidQ0VlJUlzZvPe7//AN7/+NXx8fDCZTH0je69MtyGK5oJio2NGdeje1NNF\nyE4EO9c7sryypP1G3YxsWHQFvaZVLgt7xkV7Ec8d2aYjOEOGmfr6es6knUOlcmVB0hz8/Py4ces2\n+U8LGBIczPPycsJCQ5k9c7oDF3F373dHcLS/vqSzo/TG+WVraMBM3pN87nzxBaIosmzxIry8vKir\nq6emtpaa2lqCAgMZERVJY2Mjp8+moVQq8fbyxsVFSXVNLRPHx7bKCtuW2tpa0q9ctVp87NyFi9TV\nqzEajSiVCpRKJaIosjJ5WRdr5DjjOPel86s/6uwo7evc04bFSScbFsl9wLCQh0K6gltzNVBBAG0D\njrlFHVne3jpHcd6F7efnx4a1azAajezc8xmLF84nMSGexIR47t1/QMnz50RFRrBr7z5mTJ8qFQDq\nuF49fTNytL++pLOj9Mb5ZV1uU1MTnx04RPykiaxLWc3tO3c5fTYNlUpFUGAggQEBhA4NoaT0OVnX\nb7AgyZxLBcw5CrKu38DVVWU3yVFu3hOu3bjJSxvXW12/YF5Sm2UHj3zuBM+FM45zXzq/+qPOjtL3\ndB6Ijl7ZsOgKDnssWnAkGMmRdY7Skf4ck6FSufLy1pe4fvMWWddvoNFqGTxoEILJyLOch7w0fyoH\nDh4hclUyCi8/FD6BKNzc7crsbp07d5xtyehskFl79JX9dn5/NTW1Uun2i5cvk5efT/ykSaxfk9Jm\nm9ChoZSVl5P75AlDhgwGwMfHnKPAns63bt8hv6CArZs3dkjnpwWF/GP3XqZPncKY0THt77LV/exp\nj0Vfuya62p8t+sp+y3QU2bDoCqLQAaMCK+16+o2yMzLbylAqlUybkgjAh3/7GEQw6HSUFRWQb6pH\n1VCFkHMDpU6H6B2AImgohEejCBiEQqFsR4/u0dnxtu3J6GyQWXv0lf12bn8lpaVcTM9g5IgoMjIz\nWbFs6Qtlrr/cRhRF/vrJDlJWrGDw4OAO6ezn50fBs8IO6/ydb/8roihy8MjnHTAsuuM49+droqtt\n+4qMXvJY9Eqv3YtsWHQFd2+kqaYWs0K+OsyYOgWlUtlcNRJ2fbaf8RFRPLlylVFB5umoIoBShWLr\n/wH/oN5TVqZHyXn0mOxHj3Bzc2XI4MHMnT3LbnuFQkFQYKANo8I+R0+cZP7cOXxx7z4qlQqVSoVC\noUCtVlOvVhMYEMCE8bFS8PGdu19Q+ryM5KWLUSjMs0/0en0XYy1kZDqOcgCaFrJh0RUMOrNRIbZ4\nLRyZB46Nz9bc62BdhrU+rOFIfx3XWTRoEXVa0DYSOzSQg6kXiI2OQkRk6fTJ7Nvxd8a4ejFqcBgY\njeAbAH6BiIKp1dQqe+5I5+vcueNsTYYzdH5xW0d17ux+t6fzizK6rvOFS5fQ6w3U1taTsnI5gYEB\nDuls9mjZ6tu2zm++9gp19fUYjSaMRiNGoxFBEBg8OJjokSOorKrmzx/+hajISIxGI8PDh6HV6SQZ\n3l7eaDSaZsOiv59f/VHnF7ftzWtCpqvIhkVXMBleyLwptvO5vfXYWdaeDGs40l/HdRZK8qC8AAzm\nCoMuJY/Q595FhYmA+ioWjBlGdFhzWeJho1EMiUDh4d08W6R3dG772daynjjOHenPGfttr9/OyLDf\n9nd/+COiKBIVOZztWza1Shfevs5DQ4bwrLCQtPMXmTYlkdhxY632odPp2HfwMNu3bAZEfHx8WiVs\na8vzsnIKnhUS4O/P8qVLCAoK5O69+4iiufBUXX19qyyk/f386o86d6S/nromeoaBaM7I0027Qssw\niMnYToXTgYcoimA0APBF9iN8fHwYMSIKTCaEklwozTcbXqIACiW4e6IYNwOlp+2bv8zAwHr9Bse3\n/fjTnXh5eeHp6YEoiriqXBFEAaVCyfJlSxAEgY8/3Ymfny8b1q5pX6gNHufmcf+hubrv7BkzOjUE\nIzPw6OnppmcHD3OqvEUVxU6V1xnksuldocWoEO2V233xBquwsdzett0pw9421mWIogBGPaJeg6jX\nMjI8lLy8PDDoERvV0NTU7M1QgNIFPLzAw8dsiHWbzo7KcGSbzsjom79V1/rrnAyzUdE5nRUKBRMn\njEetVlNYWIzJZMLd3Q2NRouvrw+gaC6NvYYxMTHs3X+QxsbGTukcM2oUa1evYu3qVc1GRf86zo5v\n25n+bMnvK/vtyDZd6a/nUCic+9cXkIdCuoJeC2J7RcgccSu2t213yrC3jXUZwsNMqC2X1noCjdez\nEPIvm+NOWrPmTZRhI1q9wXaXzo7KcGSbzsho/7cSm+NxFC6uWKf9/Rab018rXKwNL3STzoKAQmWp\ns2jU8/+z957hcRx3vu7bPXkwyASYAOackxjEnCRKIikGkaIly/Za6+O9ex6fvd7rc499P6y9Z1fW\n2bPZ3vWec+9GK8sixSiJIpVFiVEMIsWcM0BkYPJ03Q89BIHB9MSeAKDf58GDnu6qX/06FPCfquoq\nTOYOYyL0e77uz4/y9clTnL94kdt37mC326lvaGD7rl0sWbiAoqJCCgqcBAIB7tytYfiwggTKjV6e\nHp7TK6/31onUNRLJk0552SNPYgFdMQKLdLDaH7RYaE7tHTmuoOOgongPsVZaPTVi5YmuIY+dBcEA\nwu8DCSSzFanOhLziEfC6EV4PmExITpfaBdL+DTaTnhPVSCRPKhrankMXj4G7GbxuQFHfJiosRx46\nPuKPSgyNc4fUN4+8bnWXvQDK+mEaOCozni+dgLYm8Lapz7fdCSarumKS36v6MFvA7kQaMAK5tJ+G\nD+1yL12+wvUbN2huuT+5nLpwVF1dPd//7nNMnDCeiRPGd8oZDIY4dOQIn+77IjyGY6Ou551qnUiM\nbNfjRDUSyZOKRnf1bJAuRmCRDnJ4xr7wt8jo5GvEn/q3M0mSwWJDsqgTX6mv6dmQLFawWJEKS5Lw\noZfndMrT0tfJs9+jBgUB74PdBdGWK4+hcT+o6NgiJDLp2Q2+tgeevYAl3Drn96jPfCgQTh3tD3bs\n50tRFN54awv/+Ye/T1FREX6/n917PyAYDLJ+zeoHKYXg/IWLfHPmDABms5kZU6cyZ9bMBM8levnR\n06ZeJxIj2/U4UY1E8qSi0Z09Z4+euAiZEVikg68t4q2Q3snVa9cZPKg61zbyFtPY2QglhGhpgFAQ\nqbg8RneIhsbEBYhQENFcB5KMVFiGlMFFtExjZqmeWxshGEAqKm/vDhEBH6LpHtgLkAqKOnSHxMfn\n87Hnw4/wen08/93nKCoq4tPP91Hf0MAjS5fgdDoBqKur55PPPwdgzKhRPLnyCWORO4MeibFsukFn\nTBaQZLWpWAnRuakt2nbHcQaR25GRcuSYBC2NaBF2MuWlriFECHH1NBf2fcb8scMJfX1PbRovrkCu\nrE5AA0QwiHL9jPot2OsGk1nVKBuIXNZXd8+x86WqET+tJJuRiqO9dZB4eZLJjFTaNyJfhj0XdV1C\nWrLYkfoMjKuhXDuN8LrxNNXzxddnafGHsBaXsPTJDTidBe1pm5pbWLNqJSARCATYvmsXxUXFPLny\niYh1PGKVF+tck71GuXy+urvnjvnz2XOsOmGQLkZgkQ4WG9ozb0bbjnecGPviaSSTVh8NEQohaq7h\nqbmFY2R/aHFDSx3CVZqwZ+F3q3NidOxOagZK+2fEc+x8qWpk9jpr5ROhEMhyh5HgQn0NWFHUMS5x\nPAtQr7ts0hhcm57nfR99QG1NDTarhTnjRlBc4ISq0Ziczk4azc3NfPLZ58iyzK3bd1j1+Ir2lovo\n5Sa6nbxn/TSi5UtEI9Xy8sVzvDLyxXMif3OzQ08MZ4zAIh18bRAKkasHMleEam9Acx3U30IEfIQU\noKAIygeqTfSFpXE17iM7ixDTliOaasHdAmYzFJYhFUQbp2Gg+H2IezegqRaa7qkDKMsHgtOlDqq8\nd1MdcFlQAmX9kPsP6/AGSVjD3YJouAsNd6ClAaw26FOF1G8oss2hi8/9Bw9ROHkecwf3h9ZGdWdh\nKVJh1yndn3l6A01NTXi9vrjTfhsY9DSMwMKgM5IMssjy6qZ6jI5Ohq4akrMIZBlhtnLo+NfMeHQl\n0ojRSAXFGpUktg/JYg03rWfOc/rXOb6G4mmF+jsIn0ft2rE5kGxO6FOF3GWF1xTLM5mRXCUIkwWs\nDrDa1fthtYPNiZDNcPkkXL0AF8+g2A9CcR+k4jKkMdORTCZ10G1hKcJkVucXuT9WQk72z0H4vNua\nofEuwqvOX1Lb5qXh8lUeXf80stkC7d030TUkCUpKSjppJnaN4u1PRKP7PF+JpdWip3tOR6Njt0nv\n+pKYKYzAIh2s4W93igLe+6/MxSLyeKz0iTT3xSOZ8hLXkAuKwi0UA3C1CnxmM3LUtxxS8ZEZz4mn\nTV1D3L4Mdy51OSJXVEXNIXXZo/35/myWsskEReVQVI7oO6hrIFdSSejwp3DzYuf8rmKkcQ8B4UDO\nEtZQFCQ5scGXWp7FzfNw70b73psXrjK2yJXgYMueUScST6uHhuFZX41o3SbZw3grxKAzfg8oQVAE\n+RnpZj4Cnzh+HFu2bWfM6FFJlJfKt6VcE9+zVDUCHC6Ez612S9jsSHYXIvynQwgQzfcQnla1K8kU\n7vYpKkO2F3RRDZw7S/DKZQKnvyHU1IR14iTMI0ZiHT8JSe74T15SW0vcTQh3M5SXgUlSx08EAmCz\ngcWGcu4IlFQgyRbwtCHq78KNy9CnH1KffjBwGLKjsw8BiKb7nuvBZAJXKZLNAYqCcDdBa4PaJSOb\noaCIUQ9VsefI15zcvYeHpk+nb99KvW6CDmT7+erddSL/yD/PPfFlJyOwSAch8jiogGz5sljuvzqZ\naHmpfFvKNfE9y1YH9B8aI5miBh1tzeoYCdmk/kN2FkVNrtyrJXj9GoEjh1GaG5FdTuTSUrq2HQh1\ninWvWx13YbHA8HFQUqmW4WmGe7fg9iW49A2ipQncbeDzgQiCrw1htSL1GxzFs1C7dtzNiMa7KPdq\nUG7VIJpbkexW5D5lyP36IpX1g7K+ardPIEhFvY+XXnsDp9OZZ4FFtp+v3l0n8o/u6Ln7YQQW6WBz\nov1WSO9BYx07gwgkWcZUOQgqByGGTgBJitldYHt4HraH5yG+/wNEKIRs1q6ucmGpOm5i4AhQQkhy\n5zkulPIqxOu/6jLlurRoHdLYaZo+JEnCVFkNldUEmnz4X/kHCKpv8ISEYH99C00rN+Kp8FFS3ACc\nocBZgMkk89cv/jmFhYUJXh0Dg95JT1ywywgs0iHgU7tCxP3Bm/He0Y48Tpx8Wu9lJ5MWjTRanmId\nj55GUbSOa3lGY3/ingUC4W0Dn0dtBZAkJLtLXZ7dYovrWd97peVZ+/50HdegfZ0lSUIym9XzFgrC\n1wZeD8LvRpLM4ChQz9tsRUKEZ4Tt7FlyFMCkOWprRXM9WKxQWAoOZ/uU6yLgU1snvG2IUADJ5kRY\nHTTU1NN44xZ1J04SbJEocbmoc7v5oKYevz/E3be2YhlYzR//4R8wYtZDmOw2jfPK9zoRTy+a50TP\nK/N1InOetY6n4jmRe6WPZxEMqM+zrw3h96ndd/ZwXZHkGJ6zSw/sCTECi7QIBSJm3hQa2/GOJ7Od\natpkPWntiwwqFOROU8dlyXPAj7h1QW3iD/rVvTYnYuQ0TBZrYhopHU/GcyIaWvuipxFeN+LGOfVV\n0WBATeUohFHTOy0UJkIBREsd+LxQXIFkcyDPWh5F84G2Uncb7l5W1wgBQl4vnvPX2PNPm/nm6h3a\nguoqvlecMn0GljFOMmGtbWaR1IatppG2//XPBMePjQgsulOdiKentS+V88qvepy8Rv7UCa3jSsNd\nuHNZHQMkBEI2qW9IjZqhjkGK67nnIYTgF7/4BWfPnsVqtfLCCy9QXf1g1uStW7fyr//6rxQVFbFm\nzRqeeuqpuHmiYQQW6WArUAMLJRRuYu75D2Y06urq8Xg8OBz6zIGQCJLFimnYZMTQSeE1K6Twaps9\nMf5/gOwogJHTwkvXB9WRXxHnHTp3RB3Dcb/bQzYhnEXIE+bFfAPE1G8wou9gUII0/uSPCF44j2hp\nYWmJxOLKISiV5RTOnsDXN29TVeRgYLGLkGxBmbkCy5jJyA57j7/+Bt0HU0UVoqIKQiGEElRnrpUz\nNw1+qmSzzuzduxe/38/rr7/O8ePHefHFF/nNb34DQENDA7/61a/Ytm0bLpeL733vezz88MOcOnVK\nM48WRmCRDkrwweqmQPymvY774x2PlTaeRrrlJa4hyzLPPfMttmzbzsb1a7ukFUKoAwv9PkQoGH7V\n0QZmS4wmwMQ9S5IM5sgWilTPW7/rLEIhcLcimurVwNPhQiosBrsDSYdnQ5JMYHkQJKjXOYAIeCEY\nAMmkXhdJUlcmtbuiNPZqeG5uwGQzIUqKUcxmMJkRffvhGtgPx7CRnL94m1mj+4HVgamoFHOfcuRO\ns2lG95z9OqFnednyrEVP8py9eyWBGnibTFGPR9fLLtks8ciRI8yfPx+AyZMnc/LkyfZj169fZ+zY\nse3joiZOnMixY8c4ceKEZh4tjMAiHfw+EFqLkGk9wPGa3VJtVtQilfKS0zCbTdhs1i5phRAo5w5D\n3a1OSkI2IT+0Qn3dMkeeM32dQ2//Gxz4CDoObC2twPTTv1Ff2YyjIUJB9c0NV1FC020r107DrQud\ny5NkpOnLka32+OUpIUKv/BpOHATACdDXQm1JIaX/7a/4i9++wsOzZtHY1MTj/88vkUuLI1pK8vFe\n6VmeHhr5XY+z5znf7pWWXs+jtbW104Bqs9kc7s6WGTJkCBcuXKC+vh6Hw8GXX37J0KFDY+bRwggs\n0sHqCDfDq98W40fU0T4nQrY1ki+vT3k5Fy5eYsTwYSj3biHuXlEXFfN71G/OsglpyASkorLwnAeJ\nNEmmc965vc6m9c/DymfVwZJKSB08WeCKEVSoKEc/RVw+o0617XOrU3MXlSEt24DsiLZ+hlqePHgc\nVI1GBP2IUBDZZFYHaMa5zsqZo4gzX0FLPZKnFcaMBcnEuXcOcezaXY7U3GP1h+sYVlLI/v2H+d5v\n/o6KiliLqWl9TjWtFvlfJ/JPozt6TiWPHuVlj2y2WLhcLtra2to/dwwQioqK+OlPf8qPfvQjSkpK\nGD9+PKWlpRQWFmrm0aInvumSPWRZ/YmJVrSeDNnWSL68h+fM5tTp01y/eBGl9g7Kvbvq2xpCUX/M\nFnAWIlntSLIpwcqUznnn9jpLkoRkdyBX9EPuOxCpqETt442X3e8Dn0f9CQbV4MLXFmMSnXB5oC5I\nJpvUZl+TWW2xiFueVy3D63mwEFxhEUFHEe4Q+PwBQm1tDAsqFJnNDBwwIKYP7c+pps0Xje7oOV7e\nTJeXSY1Ml5c9pPBr53r9xGLatGl88sknABw7doxRo0a1HwuFQpw6dYpXXnmFv/3bv+Xy5ctMmzaN\nqVOnaubRwmixSAdfW8RbIb2X0JlTLPt0J9v+8k8ZX+hgeIEd7HbsP/4ZpnFTkDSb4w06Is9ajpi5\nDNHaCI11SJVVSLb41y506xLcPNc+YFMA2JzIkxeHX1XVKG/SHPU1VHcrovY2UuUAJEcB9mkXufjS\ny1jv1XF96FD6ThjPmnFj4n5TMTAwyF+WL1/Ovn372LRpEwAvvvgiO3fuxOPxsGHDBgDWrl2LzWbj\n+9//PiUlJVHzxEMSGrMbnTt3DiCh6KTXEvSH3wpROgQY9y9nx0FHaGxHpo3cpsO+aBqRaWLpJaOR\nvGcRCqI0NUJ9Hf/xd3/LRtEaPiSp39or+2FZvQHTwI6vKenpOR3/HbWSO++OGkrDXUTdbTXg9PvU\nrjL7/UnUAuAJT6JmcyK5SpCqRiFF6Cm11xGNNWorQsAP99+9rx6D3GV+jgeeRSiICPrA60YEA0gW\nm/revtWu8c6+SvDEVwT3fYxSewfR2IBUWo5c2Q/zQ9ORXA62v/8hZ6/eYOaUSSycPxd50NgunpO/\n5r2jTuTeczr+9fCsh4aW/8zV43PnL4CjMGv/+44OHKyr3tSbV3XVSwWjxSIdzFb1n0YoAP7I5dNF\nxO9UthM9noheMhrJe5ZMJkxl5VBWzqwJ4zj8zjZmONT+faX2Lsqlc1jWbsqg58T8C0VR75kpWndM\nmveq+R7U3YBQOMj0tECrRe2W8HsepGtrQrR3i0T4a6xVB7sqHTTMFqRB47qW1yG/ZDIhmZzqbLAJ\nnxeETn9N8MBn4aAHxM1rKI4CTKMHI3lNBNua8bQ2s3BoBbhbY+glc716R51I3E8iaTJXJ2LrpeNZ\nD41k/Ceqlain7CDJXf8SdXeMwCIdfG0P+qUN2hn/Bz/iDVcZpsH9kGvuIFf0xTRpGnJJWc48hWqu\nQUMtNN5RW5gKy6CyGrkyygqhKSIPHo/oP1wNDnxutaWhpALMFkRbsxp4KEIdjOkqiVquPGIKonq0\nOg+F3wvOIqTiPjG7M9LB9vR3sTy6mtDXX6HU3EHuOwDzpKlQWIxwN1N2x82KidORJszT9GxgYGDQ\nESOwSAdJVld0vD9AUTshXZviiPI5ZmEaGonkSUUjPc8r165h94cfs2b9syl5Vtoaof6uOiVvwKc2\n6dudUDEo/PpkND1tz3JhGcJiQxQUqW9pOIvA4UpKI5FzkKx2pMpBXTQkVwm4SuKetzro0wn2IRo+\ntPOm4lmpr4FL3yAHm5HtCgSbEOePwejpyK5ilq7bxLadu5CLymOUG8+Hvp5TK09Lv7d7ztR5p1Oe\nHhp63Kvs0BPnlDMCi3SwhmeaVBTwtpJcc2q0z7HQ0kgkTyoa6XkuKCigb2UFX588xcQJ4xPK01Ff\n3LkKd690OSJXDo7hQduz5HAhOVxQ2rf9z02yGpGfkteIRex7FfsVr85pH3iL8Cyi/BE7fRhxfF8X\nNXnMtPbP2iPNc/d8JV+eln5v95yp806nPD009LhX2cEILAw643OrfeExWyt6L3NmzeTDjz/hm9Nn\nGDd2TFJ5peoxaneFpwUR8KlvlTiLEni9NwHtFPMpjbUIdws01ag7iiuRisqRXcVpe4pG/ZFjNJ8+\nS/3Bw3hr71GxaD4lE8ZTPmdmxPosoHha1TdJWhugqR5KK5FcxdDmRjTdgxsX1AC4eiRS30HIfQcC\nIM1YDH0GQGMNouYGIMBsQTlzACoHIxUUEfAHMnJ+Kvn3DdLAwCA9jMDCIKMsWbSQ9/d+iNPpYMjg\nwQnnk602qIy90E3WUYIQ8qtzPiDA5U/5dWOhKIh7t+DWFURLo/oGR3lfpKoR7a+XBtvaCLa00Hbj\nJv6aewTqGwi63WrTQ2R4FAqqg4h9HvA0g7cVYTZDYwN4WqGuVn3DxOtWz+M+sgkkE6LFjWhoUme2\nKSqCgB8p4OPW7duYMzS+I3wlMqhtYJD/9MT1dYzXTdNFCPWboK8N44+kNtt27uLJlU/k2oYu3K8y\n6fxBUC6eROx+nchnRlrzA+QBQ7qUJxQFOc6snfcJnfwcmus677Takact77IIWWjHK4hPdnXR8P/X\nv+bLb85RV18fXgPGwKB3kO3XTb8eMlRXvYlXLuuqlwpGi0U6BLzqq4VCofNAoch3tbWae6MNMEpl\nkFNkGfE0EnmfO5lBX9ppRWsTor6GwrvX2PI//gy5qJh+Q4czdPho6m7cofbiFZCgcsQQ+o4cTtnA\nATn3HO9ePYgnkrnOEfv7D0aasRjR0gitjWprQlFph/VTJITPrf54WkFRUBxOsLmQHAVEziURamok\ndOsWwRvXCF08hcluwVRehql6oPo2h82JEKJDvvBg0alz1EXG6mug7i4+WWbL2WuU7djCw8seoXjW\n1PDYjHSfL6NOdNWLVn5v8hzvXJL1TJT9enjOLD2wwcIILNIiFOrcrJz0gKFo6VMZ5JSsRrS0iWok\n41mgXPwGcfgzFlw4pU745CnkEh7+/uUtXDh4lPLb99T/s0MGsOYnP6Dk8UeRSiqRLJErlqraQghE\nUx2c+1q9/iMnIJVXRvzjS89zdFK5Vx08+73qK6SKAsV91MGkM5dq5FPzKvV3oPY6tDWCEAibA/oP\nQ3KMeKAdCBA4c5rWf/5fBE9/o07MBUhFRVjnLcS1dC0mp7Pdh+JuVn2YLEgllchVw6BqGC0tLRzf\n9zFnjx3hmY1PYjXLUHsRoXiRhowDydTJW2LXKlba3lsnYpffmzxr7c83z5nF6Aox6Mz9bhAlGJ5K\nOTcPZndABPwIvx/J7ggvYQxXr17jy08/pcpby+zxwx6MGjBZYMRUTOX9u+gE/+EXcOtq+z9QzBaY\nuQjTut9LeVBmpgmd/FwNDu5PnCXJ0KcKeeTUuJ4FhPMJdSG3Dn+EPDu30/bv/4JSV0v7qqYFBRT/\n+V9gnTi509wXwu9FOfm5OuD4flqTGYZO5NjNeq7fuMHc2bMp71OOpCjqc20298g/egYGsch2V8ip\nYcN01Rt/6ZKueqlgtFikQyioBhXK/bdCMtWMqUU6Gqk0haZenmSxhlsh1OOhNjf9JJlVo0Zw/LPL\n7Pn8KMvmTEW229QBhc11KDYHktUBFmv4H5yENGgkwu6Auhr1upf3Vd9+0PSRTnNx5Pl33RahIEpL\nC0rdPULNTch2B6aKCuSS0vA/dgnJVYYwmcHbprbayCbwqW9rCHsBktkaDra6+pCQwt0jXc/FNGgw\nlilTCd2+hVJbg1xSitx/AJKrEMls6ezZZFbfsrE5VR+yCewF3Ktv5PqNG6xZtfLB6ZpM4VVYznrW\nOQAAIABJREFUs9XUHv8698Q6kXnPWtuZrRPd33N26YmxuxFYpEPAB0LrrQA9mzG1SEcjlWZF/Tzf\n+C9/hO+royAEfYDTbjc3/QGql8xUk92+iLh9ESGbkCYvVpcdR2Ba/ayqIgQIETEYMd65xNtO/l55\n975P62/+HtHU9GC3Sab0r/4G86TpSCYz8pBxACh+H+Lk5+qcJ34P4tQ9QEKMmoapT1XSnq2TJmOd\nNFn9FAq1twRFSyuZzJhGqnNTCCEIBoO8s/t9nA5njEG16Vy7ZJ6vVMrTovvWidQ00n3O9a8T0bej\n5e1OnjOH3AMjC6MrJB2UkNpqIRQIBogfJecTsXxl3rMQAqW1jWDtHZTzXxGQ4eOTp3ni4elqV0i/\nocgVg8BiUbsAsuIreX0BEAyitDQT2v8RXDmJLAukUECdd6O4FGnZBuTCUjWtEBAKIgJ+kCS1FUc2\nx/nWou+9unb9Op9+/gVrVj2ByxVt9lE9yO3zlRo9zXO+6ue352x3hZwZMVxXvTEXLuqqlwpGi0XG\nycc/RhDbV+Y9S5KEqdCFZBmIaLuD1e/G5w+oby6YrWB3RVkuPHVfQggIBhBeNyCpE25Zreo/9zT0\nJQCzGVNpGdLAgYi2u9DcoM4pEQqApw18HoTdBWazWp7ZEu6qSNh95y0hwO9F+Lxqi43diWS2IIJB\nREszwudDcjqRClxdFls7f+Ei5y5c4Nvfejrpc02O3D5fqdHTPOerfnf0nDl6YIOFEVikhc+DdleI\nQSLIdgdMnIdQFOaVDuWTS1dZMmtR+6DB997fS3NLCxaLmT7l5cx7eE5KAwqVvb+DS6faF40TkgTj\nZiAvWJNWt6oQot2PPGk2TJqN8HlRjn4MATeYTIhzh9Q/dc5C5EmLEp49NNoU3OLebcR7r0JzvfoZ\nwGwhEHQQPHQA3G3taaXiUhx/969I4bdCWlpaOHr8hDEvhYFBHtETB0gbgUU6WGwPBm+2z8B4P1ru\nOJCo4/5o6DkwLtZ2x/z3PWmVp4dnNPZ3zSfJJvoPG8nnx04RDIawWNSBj26Pmw3r1iBJMrdv3+G3\nr7zGmlUrKS4uSvBcVeRFaxAzl0FLg5rO6UIqKAzbTM6z8HlRvngHWpvU1gmLRV2xdORk5OETkGx2\n5IeWI4I+tbVCCSFZ7GoriSzH9KzcvYZoqlFnyAz61fktbAVIg8chW2xI5f2Q1v8fCHcLwtOKJMlQ\nWILNYsPy9PcR9+6heNowFRYjlfcJt/qoZXz06Wc8tXZNlHsYbfBaos9XNLL1fKVaJ3LpGY39idbj\nTNwrw3NXfwbpYAQW6WAyq/8oQqFwYNGxMoiI37GIli+WRrT9iWynWl40MuN55WOPsvPdd1m7ehUg\nGDFsGJevXGXY0CH079+XGdOmcrempkNgEe9cVSSLFam4DIqjLd2epGe/B66dg7aWB8caahFVwxGh\nIJLJFP5xqm9hRKoKRX1mJKlLV4VorYeGu+0tK3jbwNKKNGQ8EG4dcTjBZgdHIZLZjGRV5/wwOZxQ\nXhG9vGAAJRCIaAFJ9TmK93zk7/OlX3l6aKRy/XN9r3qL5+whpb/8Ud5hBBbp4ItYd8EgbRwOBwXO\nAurrGygrK2X4sKF8eeAQw4YOAWDc2DG89fY2Ro0ckTOPUmEJ8rd/gqi7jTj+BVw9C34vfLodZf/7\nMHgU0pwVXRYnE6EQyq0LcO8meFrUvyiFZTBoLKYiNeAxDZ+CGDQW0VhLa0Mdn506T8hiht17ALCH\ngjR/9jHK+dMEG+qYUVlK1YxZ2J59HlPV4C5eQ8f3wcVTUHMD8fVFlMBNmL4I07Bxmb9QBgYGcTG6\nQgw6I4df7xMKnVc41Wqm1SKRZkCtJmA9NbT09PYcq2lSYvnSxbzx1hY2bVhPQYGLm7dutY83kCSJ\nkuJiamvvUVHRJw3P8dJoexZBP+LEfkRLvTrWweYAi41A7T0Cl+4ROnoJZduHmAZUYRowAL8wEbxX\nR+DGTZTmeix9SrEM6EvJ0xuQnEVI9oLODiw2pIoqXtm6m+9/5zlsNrVFQghBW1MT9onjEbV3Cd66\nwYGrNzhjL2BlcSlXr13n4OEjyLLEw7Nm0b9/f+TBYxCllYjGWgaUnON61TAG9emf4D3RunaJdLXF\n25cvdSJRP8lq6FsnkrtXqXqOl6a3eTZIFSOwSAerHXUWQ6F+A21HqylOi0Sa4uI1yeqhoaWnd3mx\nmibV5v5xY0bz/t4PWb50MU+ufJyXX3udZzdtRJZlli1ZxEuvvs5zz2yKiPaT8RwvTQzPbc2IA+9H\nBJPgu16L7/iZ9s/BkycAaDUVcuXOHc74/IC6gKht5kMUDxuP2awGp21tbpYtXtQpWKoaOACT6UE7\nqSRJuEpKoKQEhg7HDCwCLl2+wuY9HzKouoqn1j6JJEm88dYWli9ZTFlZOVJJOaJ6BA9NmM3b23cw\nZE5p7POLeV1ibSezL1/qRKLHk9XQt04kphHPUyrHk/XRkzxnhx7YYGHMY5EWPrc6tiLiH4yBPtTU\n1LJ77wcsW7wIl6uAzVu38+1vPY3ZbKa+voGjx0+wdPHCrPsSQkHUhpc8r72pTnhlNiNkE/6btQRr\n6xDYMPevwjxqDF/cvE3bqdPMLHAigkGsVVU4Z87ANnJkB03BO7vfx+fzYbFY8Hi8+P1+hg4ZzNw5\ns1PwKHj5tTdYN2M89rZGuHIahGD7tSZWrFmHY0juupIMomF8W84Xsj2PxaXx+pYz7NQ5XfVSwQgs\n0sEILLLC1h07mTxxAn0rK3lz89t87zl19s2XX3uD9WtW43A4cuZN8XmguR7R1gT1t6CoHArLkMr6\n0erx8c7uPUyZNJExo7Nfj/x+Pzte+g/WzBiHuHIW5dwpPM1edl2+y7pHHsHUfyDy1BmY+vTNujcD\ng3zFCCzSpweOR80iNic4CtUf4zWljLFm1Uq+OnYcp9PJnFkz2b7rHQA2bVjPG29toaWlJY5C5pBt\nDuSKgZiGjEOesgTTiKk0mFxs3vEuXx44xFNrn8xJUAFgtVqR+vTFNHku0sMr8R8/h+ncBeTrV/Hs\n+B2+f/4VyulvcuLNoHdjtM08QB07pt9PPmCMsUgHv7dDi0Uig40SGWSWqkYieqlo5Naz2+3h5q1b\n9ClXxx6MHjWSs+fPEwqFMJvNfOfZb/Hm5rdxOh3MmvEQfftWRNHK1Hl33pZkmctXrvDVsRPhsQ5y\nyueth2chBHJ43gy5tBTrpu+h1Nyh/9Fj1JeXM3DEcCiKnA+kdz1fvddzNupE5zTC50Z42xDuFggG\nkBwusBcguYojvpbly73KDj1xrRAjsEgHJZTg66bJDDJLVSMRvVQ0cuv5r/7+V8x/eA6LFy5o37do\n/jxeef1NnntmE7Iss2nDeoQQbNm2nfVrnoyilanz7rp98PBXPP3UuhTKS9aHdlohBMLngaZa/DU3\nUJrvIblKsK5cD8B8RWHrjp0Mf3J1muXp5znxMtItTw+NnuA5G3WicxqluR7q70DjHXW9HLsLKqqQ\nnIURs9Hmy70ySBWjKyQd7AVqN4jFgdEVkhl+9pM/5vqNm5w89aDJvqioiMceWc7WHTvb90mSRKGr\nkJu3buXCJgAej4fSkpKclX8f5ewhxLEPEReP0S/UwuW9b6Mc/wShqGOBZFlGkiRCoa7T0Tc1NaEx\n7MrAIC1MFQMxjZ6O/NBjyLOeQJ66BFP16IgVinsfPbErpHff0XQJ+tWl00OB8I6Od1Xq8DvafjT2\nxdOI1IunoXVc0tgfrYzcebZYLHzn2W9hNlv41/94mV3v7UYIqKjow4xpU3ntzc3tqR9ZtpQTX5/i\ni/0HsuZZCIHw+1BaG/HX3cYU8KD4POF/4vGus/Z5d95O7l5JRX2grB+4Spk7YxpfXL4LxRXh72hq\n2imTJrYHa/sPHmb7rnfZvusd/urv/4E/+q8/5djxE1n1HF8vlkZurrN+nhPR0DqezHnn0vMDDUk2\nIZnM4a5CvXxqeU5WL/tIkqTrTz5gdIWkQ8CP9iJk8ZogtfZF206sqTG9MrTKS1VPX89jRo9k5Ihh\nNDY28eobbzLv4dkMHjSI6VO9fH3yFBMnqFNeP/bocq5cvcorr7/Bs5s2ZtyzuHcLcfUU+D04FYXW\n0ycQ5RJMXKD2ISdcdjI+tTyrn+UBw4Bh7XuW9BvLZxcusmiYjAgGCF44j6euHmt43Eqhq4Ca2hoA\n1q1eyYVLl7l4+TJTJk/Kmufk9ZIpL9UytMpLVS/b9VgPvVx7TiVfOvfKQA+MwCId7E4IBtXgIhjA\neEAzi8lkory8jGc3beTTz/dRX9/A1CmT2bJteziwUBkyeDDHTnydFU9SxUCkPgMgFEQKBvDc9CPP\nWJFXzbsDBwzg4GdfcO73v0tZcxPKvVouuX2MGFSN+/s/YPyKxxk/bmx7+ta2NuobGnLo2MCg95An\njQy6kj9//bojiiB+MKHHUxOpkQnNTOvrUd6DdAvmzeXq9esAFLoKuXPnbqeUgUAw3JyfDMmft0S4\nKdNsQbY7sdgcEUFFftyr1Y89wpd1TdxRALOZGgUqigrDf9U6a8yfO5cnVz6Rstv4vow6kTlNvcnX\n806mvPzGGGNh0Bm/BwJedaxFRkcfJ9K0l65mpvX1KK9zOpNJnQ572ZJFfPDxJ52ObVi3hoKCAl56\n9XWam5tT0k+Wr44eY2qn7oP0NeNrJKZvKiriO1ve5tCTG/j02ecZ9me/pPyff4vz0cfaNT746BP2\nfvhxwpqxyafnK1XNTOtn2rMe5Ot5J1OeQbYxukLSwWpTl7dWlPCy6fDgoZaI/oDf3y9ppNXajkYy\nGvH8xEqbikbmPdfW3qO1tQ2Xq4CpkyfxzekzjBs7pj3NyBHDGT5sGL995VW+++1nIgY2JeI5uXt1\n/eZNpk2dkuR5xysvER+JeZYkid977tuaGk3NTTgdTlpbW3G5XHnhOfZ2NHp3nYhdXqY0eprn7CLJ\nedLMoCNGi0U6yGYwWcF0Pz5LZECQiHI8ke1YWolsx/MTK20qGlro5/k7z36Ljz79lD0ffMSokSN4\nZ/cejrePrVDTyLLE2tUr+Y+XX42YoTNf7lW88hLxkUxabY1AIMiY0SP5+LPP0ywvER/JpDXqhD7l\nZUqjJ3rOHkZXiEFnfG7wtardITl4IHs7ZrOZVY8/xoRxY3nl9Tf5zz/8fbw+X5exFcXFxXzn2W/x\n7vt7OXvufMb8yHk0YDMVnn5qHYeOHEVRjLVvDAwMUqd7/yXMNSaT2mrR/g8lsqk9cjsynIy2v+M+\nrfAz2v5kyouXLxGNZD0no6HlL9o+if79+/Hspo38bss2Ro0Ywe07NRETZUnIsszG9eu4dv0GFy9d\n1ig7VrnJeI5Gx2uT7nXWKjN9z5MmjGfalMkJlp2O50w9X6mWp4dG/tSJxDWSeb60ykynTsTazo86\nkWlkSdL1Jx8wxlikg8UOZqGOsfC1kXyTYKwmulgtINGOJVNevHyJaCTrOVWNxDybzWaee+Zptmzb\nzoRx47h0+QoDBwzoor186WK2bNtOoctFZWVFgmXE9xwKheK0WOh5naOl77wvEAhw/OuT3L5zh0Ag\ngMViaZ9RUwjByOHDO4xHecDoUSM7fMqk50w9X6mWp4dGftWJxDTS6RLI1b1KrU7E1zBanfXCCCzS\nwVg2Pa+QJInqqipqamuZP/dhzXRrV6/ipVdf51sbn8JisehS9q3bt+nfN/fLj9fV1fPhJ59is1kZ\nN2YM12/cwGw2U+B0smTRwvZ0p8+cZfPWbQwZPJjpmgNODQwMMk2eNDLoSq8ILC5cuIDJZGLo0KH6\nCksSmgORDXLCzBnT46aRJIkN69aw673drFm1Updya2rvUVnRRxetVAkEAux6bzerHn+MC5cucfT4\nCdauXsmt27d5/XdbGDdmDJWVFciyzNgxoxk7ZjSHvzravgy92+1h9MgRTG3vCjEwMMg0+TINt570\nisDiyy+/pLCwUP/AwupQfysKeFsxIozug8PhIBQKIYTQpWJPnTyJrTt2Ul1VpYO75KmpqeUXv/wf\nLF4wn917P2D2zBk8NH0aAIOqq/nh89/j7PkLHD56lFAoRDAYZMnChcyYNhWY2q5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CDL4bdDQnT3gWqZ9ZyKhh75ktHI9UC1VMpOzvP4cWNo+KKBPR9+FGVxrVja+f585Zdnr9fDlavX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\nWBAREZFkmFgQERGRZJhYEBERkWT+HyFYB52uOe5jAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x52cb89f50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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i7Nixcq//zp07XLt2rdkpjcbo9XrKysqa3Ov5+flUVlY6+GSYzWY++eQTnn76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\nZKJTK0L1iATuXRECTBUVUFGBeew4WLCQ0BYftDZx4e4DPj5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2gGstHr6914QGzK0uo2be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IIIYeSIaE84Fa8/MXJaUWRkl6g8Wn3JbFMOyiH7DrHHRhTWdcgVh+s3blAzaFCX5ZsL8TpkzyED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\nEUFERERhYRFBREREYWERQURERGH5/2bUW206RDV2AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x585537910>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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auX37Nvn5+XJZaGgoM2fOdBobQpIk9u7dy4svvijbNFgsFnx8fAgPD2fs2LGdmnF3tq2X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AJiqy0eEKwUG9tQocWkSdP+A0160TTphTctXvTCC9Ob9qJp08OKJq3WaI0p0ArtEtClgEVguxyW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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x5760ba190>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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mzZrFsGHDWi1Teno6M2bMQK1WM2PGDN566y3UajVOTk4sXLiQ2NjYNjsTlUpldznDHkOH\nDu1Quqa4ublx5coVxowZw+TJk1ssh6hUKiZOnMjEiRPlY48fP+bAgQMAREZGMnr06E7L7WuuXbtG\nZWWlEsG1gwiCwM9//nPq6uq4e/cuubm5CILA4sWLB73R72BmxYoV5OXl2T2nUqk4deoUb7/9NkuW\nLEGn0+Hi4sLrr7/O5s2bycrK4p//+Z85efJkmzut2lwKSUlJwcvLS7Zc9/HxITIyclAYdTUiSRLl\n5eX4+voO+NFYb2E2m7l9+zY5OTnyseDgYCIjI+36hpAkiY8//pht27bJNg0mkwlPT09CQ0MJCwvr\n8Ii7K2W9fPmyrCTY4/z584wfP56AgIB287NYLFy+fJnc3Fzmzp1LUFAQGo2GnJwcbt26JRtKxsfH\nc/r0aerr61mzZg1qtRq9Xs+TJ094+PAhLi4uLF++vNV6HzhwQI622t/Ys2cPM2bMIDs7m7q6OsC6\nvLRkyZJ2d7P0FZIk8de//pUhQ4bg4uKCyWRCFEW8vLyIjo7uNWdIA4WMjIwWy3NgXQI9deoUBoNh\nQG8pbYveXgr5kbb9JczO8FNjRbtp8vLyeOONN2yWQprz5ptvMmfOHNasWYMkSXJftXnzZn73u9+1\n2V922MbCaDSSkJDAiRMn+Jd/+RfGjRvXbuH7M/fu3ZPr6OfnR0XFlw9Dp9OxbNkyRdHoBDk5OSQk\nJBAbG0tOTg75+fnyOUEQGDVqVIsZA5PJxMWLFzly5Ag1NTUIgsCIESNYsGBBr67rS5LErl272LFj\nR4c/MJIkcfPmTQoLCzGZTAwfPpzIyEjZaHTv3r0sWLCg1ZmN+vp6Dh06xLx582RHX01JSUmhqKiI\n0tJSbt26xZtvvtktA1lHUl5eTn5+PqNGjZIHGY1bjy0WC7Gxsf3Wb4QkSZhMJnkJr6ysjMTERERR\nJCIiYsD3a47inXfeITQ0lKFDh7Jw4cIWfWGjk7VZs2b1UQl7judFsfjOd77Dnj175GO1tbV8/etf\n569//StarZaf/OQn8u6x9PR0fvzjH1NUVMRrr73GkSNH2nzH21wKuXbtGunp6UiShJOTE9OmTWP1\n6tWdqGLfkpeXx82bN+VRZOONsFgsjB8/vtURYVFREbt375adODVSXl6Oj48PCxYswMfHR37ZRFHE\naDQ+15bRjbYSiYmJjBkzhhkzZrSrmFVXV5OQkMA3vvENfHx8cHJyQq1WYzQayc3Npb6+Hr1eT319\nPTqdjlGjRvWIf4vGbbPHjh3DYrGg0WiYO3dum1sTBUFosVOjKVqtts3lEp1Ox7Zt2zh16hQlJSXM\nmDHD5vysWbNISkrixo0bvPvuu/1qRO3r69vi3jTew4qKCo4dOybPcjau04aHhzN69Og+VzgEQUCr\n1fL555/Lx1QqFSqVigMHDpCWlsbMmTN5+eWX23T8NpgxGo34+Pgwb948eYbRz8+PxYsXU11dTW5u\nLnl5eaSlpQ1KxaK36avtpo3985EjR9Dr9WzevJl169axc+dONBoN48aNIz4+HrPZzFtvvcX27dtR\nqVT87Gc/a/c9HjS7QiwWC6dPn5Y9wEmSxPDhw5k6darD1gNFUSQnJ4ecnBwqKipkr4eCIKDRaGho\naLBJ7+TkhIeHh/xzd3fHx8fHRlkxGo2Ul5cTEBDQpzMk1dXVZGdnM3HiRLnRHDhwALVajdlsJiws\nzK6NgtFoRK1Wd/nDZ7FYuHHjBiaTCbPZjMViwWAwUFZWRkVFheyKWxRF8vPzycnJwcnJifnz57Nj\nx45u1bk1jEYjly9flmexfHx8mD17dquKo8ViwWw22yxrfP755+1uNW3k5s2bFBcXs2rVqhbnSkpK\nSExMlLfLNqLVagkNDSUkJKTLrr8bqaqqwt3dvceUF6PRyKNHj3jw4AEuLi6sXLmy22XuDrdu3UKr\n1RIREWH3fHV1NVqt9rkcKPzhD3/g5s2bxMbG4uXlhZOTE05OTlRUVHDz5k2CgoIYO3bsoFsSb0pv\nf/vednbsjMWPG9qfsehpBoVicfHiRUpKSli2bFmHjd56A5PJRG1tLbW1tdTU1FBbW0t5eTlGo1FO\no9Vq8fHxobi4GEmSbFwvh4aGMmzYMIeP8gwGA5cuXaK2tlbO28PDg+DgYK5du4abmxsWi4Xg4GB5\nJP3gwQNu375NVFQUY8eOxWQycfLkSerq6vDz85N9TDQeb4zPMWzYsFZtL5py6dIlrl69yujRo/Hy\n8mLEiBEEBQXh4uKCKIoYDAbZLqO3FbDy8nLOnDlDaGgo06dPtzmXmprKw4cP8fDwwGg0IkkSEyZM\nID8/n6qqKgICApgzZ06rzzA3N5fExEQmT55sYyzZHg0NDWRmZpKVlcWtW7fkpSSVSoWHhwfe3t74\n+vqi0WjQ6XR4eXnh7e2NKIqy0tY40+bm5oZer0eSJNzd3fH29iYyMrJHPv719fV8+umnbN68uV0X\n7j3F2bNnmTFjRqsfxkY/Hk5OTixevLh3C9cPaNwl1PRnNBq5ePEijx49QqfT8fLLLw9aZ2OKYtF9\nBrxiUVhYSGpqqt3R3kBFkiTKysrIzMyksLDQ5pwoioSHhzNhwoRWP7DZ2dmkpqbazKg05iuKIi4u\nLsybNw9PT0+71xsMhlZHazdu3ODRo0doNBpWrVqFm5sbv/71r+V2YjAYWLt2LS4uLpjNZgoKCrh1\n6xaiKAIwbtw4wsLC7M4iXb58mYKCAtatW2fjgrovKCgoYN++fYwaNQpJkqitrWXt2rV4eHggSRKf\nfPIJLi4uTJgwgQkTJsjXSZJEWloaN2/eZPr06Xh6enLx4kUCAwNZsGBBCzmNthSNr6HRaGThwoUd\nMiRt5PDhw6xbtw5AVhwKCgooKChAr9fLzsTCw8PRaDT4+vri7e1t9x4bDAYqKipISkqS19cdjcVi\nYdeuXWzatKlPlhuKi4s5d+4cLi4uTJ06FR8fHx4+fEh+fj6SJOHi4sLs2bNJSkpqd8vvYMZisXDl\nyhWKi4sRBIHp06e38DEzGOntb99PXRyroP3IUO7Q/LpCm4pFYWEh0dHRvV0mu0iShNlslmNLpKSk\nUFtbi4+PD4sWLerztdveJC0tjQcPHgDWmYagoCACAgJIT08nJyeHsLAwIiMje+2eiKLYIVmiKJKR\nkcHjx49lD5lgfba+vr6EhITg5eUlR/y0WCw2Mx0TJ07sdOREURTJzs7m4cOHNu6rm6LRaBgzZgwh\nISE2Ck9ycjIVFRXExMS0uObOnTtkZGTIS24VFRUYjUaCgoLk5bdDhw7h4eHB0qVLycnJ4cSJE7z+\n+utt3qucnBzKysqYOHEiR44coaGhAX9/f5YuXdqqItmRZZfCwkLOnDnD3LlzO+R5stGbp9lsZtu2\nbe2m7ygmk0l27CUIQofcnfcUoiiSmppKVVWVvCuo8R6fOHGC6dOnd3s79ECjsrKSpKQkGhoaUKlU\nzJ49u01bocFIbysW/+VgxeIH/V2xOHToEOXl5YiiSHR0NKtXr+71aejr16+Tnp6Oh4cHTk5OaDQa\nNBoN06ZNe26Nq5pSW1tLQUEBxcXFjBgxgpEjR/Z1kTpNYzjv7Oxs8vLy5JDkKpWKhoYG1Go1ixYt\n4vbt25jNZgICAqiurqa6ulpeVrIX3EuSJOrq6uR7o9Fo5FkcURQRRZGoqCgCAwN5/Pgx2dnZmEwm\nOa+6ujrWr1/f7lp7fn4+arWa4uJi3NzcePjwIUajEV9fXxuL+r1799r1l9GUp0+fcvToUfz8/IiL\ni8PV1ZXi4mLOnj1LZGRki10LlZWVXLp0iTVr1rR7n/Py8nj48KGNa/TWqK+v5+jRozZ2I56ensyY\nMaNL711dXR0/+clPCAwMZMeOHZ2akekt9Ho9V69epbS0lJEjR7YwqB2MNHrBffz4MZIk4eXlxbx5\n83ps+/dAQFEsuk+Hl0KOHTvGhQsXAFi6dCkrVqzocSWjoaGB//mf/yEiIoIpU6YMyI+mQveQJIkr\nV66wf/9+3nzzTYxGIwaDAU9PTzw8PNrsANPT0/nwww95++23W/WvkZKSwpMnT1i6dKn8sWs+U9Ie\n7733HtOmTSM4OJj09HRMJhOSJDF58mR5dqCwsJDHjx/bXQ5pil6vp6SkpEVbz8zMpLy83MbGw2Qy\n8Y9//KNdz6VgdUdeXV3doSi0YB3Np6SkUFxcLCtg3t7e8kyhWq1m3rx5nQoS17hMlJaWJu+Lnzt3\nbp9Hss3JyeHSpUv4+Pgwc+bMQWE7oNfrqayslGd68/PzKSkpkc837fYjIiLs+qx4XultxeLnro5t\nb2/pB5Bi0ZSsrCyuX7+OIAjMmzevx6fKGh0yZWZmolKpWL58+aC1SFb4knv37vHb3/6WqVOnMm3a\nNEaNGoWXlxd1dXXU1tZSV1dn82vcViyKIqtXr8bZ2ZmioiLef/99Nm3a1Gr0UkmSuHDhghwVVBAE\nLBYLkiTh6urK7Nmz8fLykv03FBQU0NDQIIdIz83N5dVXX22R76FDhygtLWXo0KEIgsCaNWu6rIx/\n/PHHbNiwQfZ2WldXx549e9i+fXuHdi+cOXMGZ2dn5s+f3yF5+/btY86cObLvjBs3blBQUCDbHJjN\nZi5cuEBDQwOxsbFdqpPBYODKlSs20VhFUWTJkiW9ZoRdU1PDkSNHHLrc05ckJSVRUFCAq6sr/v7+\nCIKAk5MTQUFB8t8KbdPbisV/O1ixeHOgKhaNiKLI5cuXKSoqwt3dncWLF/f4NjKz2cypU6fkj4fy\nogx+RFGkpKSEp0+fUlVVhZubW4ufTqeTZxkMBoPskwKsI7LO7LhoSn19PcnJydTU1DBkyBCCgoII\nDAzE2dkZi8WCyWRCrVbbbfdf+9rXeOeddxyiBJtMJg4cOMCECRMwmUxkZWURHx/fqZmV8+fPM3Lk\nyHZtLIxGYws353fv3qWgoIAVK1bYpL1//z4Gg6FNnx6dQRRFjh07hpubW487SbNYLHz44Ye88sor\nA95Gq76+nr1797J06VKCg4P7ujgDGkWx6D4O2xVSU1PD3/72NxYtWkR2drZ83M3NDS8vLzw9PQkI\nCGh1J0JnaYw94e3tzcKFCxV7C4UWdNSotKcoKytzuIvrmzdvotFomDRpUqeuS09P5/Tp03z1q1/t\n0D05cuSIPF1uNpsZP368ze6XRr744guGDBnSYhtud8nLy+PcuXNERUXh5+eHm5sbrq6uDn2ed+/e\n5c6dO2zatGlAx75IT0/n5s2bvPDCC32+m2ow0NuKxTuuju0j/l1f5tD8uoJDt5t+8sknBAYGMmHC\nBAICApAkifr6eqqrq6mqqiI3N5eKigpmzZpl141xRzAYDNy+fZuamhrc3NyYMmUKiYmJlJeXs2DB\nAkVbV3iuqKmpwWKx2LVTKCoqIikpCUmSCA8PZ/LkyQ6Tq9fr5RHy8OHDHZZvcx4+fEhlZSV1dXWk\npaUxZ84ch82OgNUZ1tGjRwfkUkhOTg7JyckMGzasXdud/kRjdNnG2cb+5FUWel+x+LXOsYrFG/V9\nr1h0SL1tVBDac2gTFxfHmTNnyMvLk7duNTaewMBAeY07JSWFlJQUJk+e3Oq6d6Pc7Oxs7t69iyiK\nssHX1KlT8fLy4tChQ0yePJlZs2ZhMpk4duwYI0eO7NU4EwoKfcnhw4cZPnw4lZWVLXyW+Pn5ER8f\n7/BZm8ZQ6tu3b+/0CPnp06fcuHFDLlN9fT0rV65s1WCyaf9QXFxMVFRU1wtuh4sXL3bYQ2p/4MmT\nJ6SmpgJWN/ovvPBCrywHP3jwgEePHsmyGr3Nzps3zyaGjSRJJCcnU1hYiJeXl+yI7P79+6SlpQEQ\nFBSESqWSbaPS0tL4zne+0+N1UOg92uwVzp8/z/3796mursbJyYnt27e3mZmHhwfx8fHtCp01axbh\n4eH89re/Zdu2bYSHh8vnmrpTFgSBkJAQYmNj7Wq1EyZMIDk5WTaimzhxYp9bmCso9AaSJHHw4EHG\njRvHyJEje9Uw79ChQ+zcubNLCsvNmzeJj4+3UYBOnDgBQExMjN06lJWVcezYMRYvXuzwOgYFBfHF\nF1902l6lpykuLubOnTvU1dXZbJEODQ1l/fr1vWpblpqaSkVFheyErRFJkrh8+TJJSUl4eXnJ3l9n\nzZrFnDnDrl12AAAgAElEQVRzqKqq4urVq1RXVzNhwgS7sZkaGhqora3trar0Swa2dY992lwKqays\n5PHjx2zcuJFDhw7JfuMFQZDXXwMDA5k5c2abQh48eEBGRob8tyiKsrFn85c5PT2d8+fPM3PmTCIj\nI7tbPwWFQYfFYuHjjz9m1apVfPHFF4wZM4Z79+6xevVqGhoaCAkJ6XLexcXF8g6bRl8fBoOByspK\nampqAGusjVdeeaVL278fPnzIrVu3WLJkiY0vi/Lyck6ePMnw4cOZP3++3C+cOXMGg8FAbGxsj31M\na2trOXz4MDNmzOgzT8PJyckUFRXJf/v7+zN58uR+YTt24MCBFjNTo0aNYsqUKfLf1dXVXbafS05O\n5unTp7Lflr6mt5dC/sfNsUsh/1rX90shbSoWZ86cISYmps2O6uLFiwQEBLT5EDoTkKmp/GvXrhEd\nHa3YTSgoNOGTTz4hPj6ewsJCqqqqiIqKIjs7m8LCQtRqNdnZ2bi6urJgwYJOdfbXrl2jtLSU4OBg\nVCoVarUalUqFs7MzPj4+uLu7O+TjLkkS586do7y8nNGjRxMZGSnnW1xcTFJSEqIoUl9fz+LFi3vt\n/T9x4gSTJk3q1f7GaDSyb98+pk+f3q/DJ+Tm5vL06VPKyqwfrbq6OrZu3eqw/GtqavjFL37Bf/3X\nfzksz66iKBbdp9vGm41OhhpjWgiCwNKlS2007a4oFo0cPXoUi8WCk5MT4eHhhIaGUltbS2lpKSUl\nJQQGBhISEkJGRgb3798H4NGjR+j1en7wgx8o21EVBg2N3jCjoqIYM2YMhw4dYt26dXbbeGMgrcbp\n6bCwMCZNmtTq+/D48WPu3bvXYrq7KZWVlRw/fpzly5c7zNV1ZmamHEtm1apVfTpC1+v1JCYmtthS\n25McOHBA9rnSnzl58iR5eXn4+vri5OTElClTGDFiRLf7V0mSOHv2LFVVVaxZs6ZPo9420tuKxW/d\nOu5kriN8s67Uofl1hW7vTRIEgdmzZ8t/m0wmEhISZFfMFoulW/v4G10Vm0wmMjIy+OKLL/Dw8MDP\nz48xY8aQn5/PwYMHCQwMZN26dZhMJjIzM1m+fLmiVCgMaCRJQq/XU1tby61bt9Dr9WzYsEGelm5q\nrNkcFxcX5s+fL08tP378mGPHjrFmzRp5zb4po0aN4smTJ+zbt8+mc28cdwiCgMlkYunSpaSlpXHx\n4kXUajXz58/vlPfN5oSGhhIaGioHJtuyZQs6na7L+XUHV1dXKip6NzKkWq3u90oFYBPksba2lnff\nfZeIiIh2XdTbo6amRvbgajabmT9//nMXj6QpqkH4merV6KYZGRnodDqCgoKorKzEy8urxz7+//d/\n/8err76qKBcKAwqz2czJkycxGAw4Ozuj0+lwc3MjPDxc3jlhNBo5evQow4cPZ9asWS3yaHRR7eTk\nhKenJytXrgSQnYYZjUZUKhXr1q3rlsGixWLh0qVLlJaWotFoWLx4cauDCJPJRGlpKYGBgW3Wfe/e\nvQ6dYu8sN2/eBHD47hN7VFZWcubMGTZu3NjjshzJu+++y4gRI2SPr1qtluDgYEaMGGF36a2oqIjr\n16/LQQA9PDyYOXNmv/We3NszFr93d+yMxb/U9v2MRa8qFrt27aKqqoqHDx8SHBzM+PHjkSQJlUrF\nkCFDmDp1apcamyRJnDp1ivr6etRqNQ0NDYwdO9bGuEhBYSDw6aefEhsb2+Z78NFHH+Hs7IyLiwv5\n+fls3LgRX19f+SM/dOhQ2a9BXl4e169fl6+VJAmLxYKPj49Dd1ns2rWLSZMmtfpBliSJv//971y5\ncoWVK1cyZcoUu/Ep7t27h8lk6lPD7fPnzwOwaNGiHpORnp5OSkoKO3bsGPCDH4PBQF5eHjk5OTbu\n2cH63AMCApg2bVq/WOboCL2tWPzRwYrF1583xcJisVBSUoK3tzfl5eVcuXJF3rJWVlbGsmXL2rVo\nb7SIb4wlIEkSBoOBZcuWdWtKVkGhr5AkidLSUlkJeP311zt17YcffoiXlxfz58+XbR/MZjMPHz6U\no8R6e3u3OVvQXQwGA2fOnEGv18vOuFrbOnry5Ek5UjFAcHAwU6dORavVcu7cOSZOnNjn4cozMzNJ\nSkpi48aNDt2p8ODBA+7cucPYsWOVXW/9lN5WLP4/D8d+t75a85wpFt1FFEU++ugjNm7c2C+2YSko\ndJfExEQKCgoIDg4mODiYYcOGddu99K1bt3j48CEzZ85EEARSUlIwm83s3Lmz3WstFgvXr1/H19eX\n0NDQVpdK7NlpNJKRkcG9e/cAqw3BzJkzW4RJv3HjBmlpacTExFBfX8/t27fluCsdCQHfG5jNZvbv\n38+kSZOIiIjodn579uwhIiLCoR5QFRyPolh0nwGjWGRlZXHp0iXWrVvXb9fmFBQ6SmVlJUePHmX+\n/Pnd8jthj7/97W8MGTJEDpI2Y8aMFoHHrl27RmZmJvX19WzevBmdTsejR49ITk5myZIlVFVVkZmZ\nKQdya/Rd0+gBF6zKhbe3N4sWLWpVATGZTFy9epXi4mJ5dlIQBEaMGEFYWBgXL14kKCioX4/eL126\nhIeHR7eXVi9evMjo0aN71AW6Qvfp7W/f+x6OnZ3755oSh+bXFQZExJra2lquXr3Kjh07+rooCgrd\npqCggAsXLrB9+/YeWV+3F8K9OXfv3mXZsmWcOXNGNsILDAwkMDCQ4cOHM3z48A6N0svLyzl48CBa\nrZZVq1a1WEfXaDTMmzfP5pgoiuTm5sozKSUlfd8RtsX8+fPZs2cPY8eO7VCI+tZYsGABn332GVu2\nbHFg6RQGOoNxV8iAUCwSExPbDfXcF5hMJiRJGjBGSQp9T0lJCRcuXODFF1/s03Ls3LmT27dvs3bt\nWnkmwd3dvdPulX19fXnhhReor6/n4MGDREZGtjvSU6lUjBw5skueO/uKDRs2sGvXLnbs2NFl5eLM\nmTNKHCOF54IBoVjExMSQlpbG/v37HbM1q3H1p+lo0d6xxuPNjpWVlnLu3DnSHz1CFEV+8IMf2L1e\nEkVKSkrw8/f/Mq5CJ+R0uJzdrI/D5TwPdeyCnMqqKk6dOmWNpNnH9XFSq1tGCbW3KtrBPHWurmzZ\nvJmE06flYFNIErW1tSxfscLWGHMAtkGtVstLO3dy9OhR3D085N0vjVeo1Gq8vb2/nIFqJsdsNlNR\nXo5/cwPzQdrW+7WczsjuBQbhhMXAUCwAxo0bJ3vo63K0RrMRzCaQRGsjUqmQH6skWn8qNUhYG1jj\nMUFl/QFHjh2juKgIrbMzL8TFEj5mDBhqQRSt1wgqampq2f3ZZwT4++E3ZAhJpaWIokT4mDAmRUxA\nQLIvR6Xiy5A04rM8v5QNko0ca9klEK3r4KiarHM3r49KsF5rI0dqkqfKelyyJ6exSE3kCI2XN7mX\nkmDNtrkc4Vk6R8lBsB5vKkcSnnUKrcmxNLuXHZTTobYh2D4Le88MOHX0c7a9sBGhob6J7M63wTbl\ndKVtNJHjohKpKSl8ZsfUkWdmK2f5grk2cu7evUdNaSH+7q7222C32oZkfe691Da0ksiGmOWUVVSQ\nfvf2M1sTCUm0YJEk8vMLiZgwgSmTI5q8u9a2cfL4cWIWzbP2FXbaRvfbYAfahtwOmreNftAG+1P/\nZKwHbe85aVOWQnqRXbt2odFo0Ol0CIJAaWkpsbGxHDp0CFEUiYmJaTeMewssJhDNX/7d2BCb0nis\n6eBNEpFECwcOf86MaVEk19ezeeP6Z+csX6aVJJBE3HXO+A/xYd2aWJusH2U85vOjR2Xjt6DAQCKn\nTEalUlFVVU1lVRXeXl74+vrYyEYSbcv4TE7LspvtHHtWn6ZVFUWgeZ4iWAaQHJtjz65t9sxayrFz\nLzslx37bsPm7FTklJaX4+XojNJfVKTkdqE9X7mUTOcsWRXP46DE2xjdx7d2NZ2Y2m3BSCdb3pANt\n4+7tu6Rcu85L27dad8f0w7YxxMebubOmt0wL3H/wkN17PmPm9Gl4uLtTV19HbW0dJmODdSdbj7XB\n3mrrPdQG+1X/ZOd+KHSKfqtYvPjiiyQkJGA0GgGrwZeXlxcbNmzAZDJx/PhxOYYIIHsTbNPfvMYF\nVGawmJ81tKZvjdDsbyuSJHEh8RJFxSUsXrgAZ2ctXp6eNumNRiOXLl+hpsn69LBm2+sAwseEWWc4\nnl2Xl5/PqdNnAfDy8sTL05O8/HwqKitl2d5e3kROmST77WirrLbYS9PWdZ1N39/ldDSPnriuZfrb\nd+8xd3bbUYD7Q32cnJyorKzqQPqOPbPx48Zy7kIiI0eMaPe6U6fPMsTXhx1bt/DJp3t5aftWBEHV\navqul6/n2mDEhPFETBjPrdTblJaVoXN1xc3NjbjYmE7I6ahsR6bvD3L6Q7/R+9MHqkG4GNJvFQut\nVsvq1avtntNoNHaDJV26dIm8vLzWDT1V6i+n7oz1zU62bGg3bt4i7VEGS6IXsmih1ZOhXq9HkiSK\ni4u5ffceVdVVaDQaFi2Y3+zj3xpfyhkeFMTwoKA2U1dWVnIz9basbMSsWN5Bhz32Xpy2XsLOpu/v\ncjqaR09c1zJ9vb6+A8+tb+sjSRL7Dh5myaKFHUjfsWfm4uKCocHQ7nWXLl9hWMBQJk+aCEBcbAx7\n9u5n6+YXOiSnc+Xr+TYYObW1ral91wb7v5z+0G90tT5dR1kK6eeUlpYyf/58wBrmNykpiaioKDQa\njdVXgFFvna14Nn2Wk5uLh7s73t7edvMbNzactEcZ1NTWMgzrDISrqyuSJPE4M5O5s2d2fjmmk3h7\ne7M42trRG41GTpxKsEaCXL7MoR4BFXqehDPnGDkimBHBw/ss0FZrmM1m/rH7U9bErMLPz7FhnAEu\nJF5iUkSE7TLfM+7df4AkSbJSAeDr68OS6IXs2bufLS9sGPBurxUUnicGlWIxduxY2QYjMDCQzZs3\n8+mnn+Li4sKlS5fw9/KgrLQEZ2ctKpWKS5eT+el//KDV/HQ6Hc7OWnk5ppGYlct7uip20Wq1rFuz\nmoaGBk4mnEYURebNns3QoX3r/lihfdaujqWuro7cvHySrqSQnfOU1195ua+LJVNVVW3j/MqRrF8b\nR0VFJXfv3yczK5vNG9fj6urK3Xv3SXv0iKH+/iycP6/FdQEBQ1m6KJpPPt3Lti2bFOVCodMUFhZx\n6coVtFqt7C22uKSE1StXEhjYPyKqdnErQr9mwHje7C4NDQ1UVFQwbKg/mE2cSTjF5IkR+Pvbd6f6\n+EkmiUmXiY9b3eqMRl9jNBq5ev0GJaVWF65NvR82vkSSJDF/zhyGDPHtq2Iq2CHj8ROqqquZHtV/\nPE5KksSp02cxmU2sXrWyRz7kZrOZ/Yc+x8lJTcT48Ywf137/UlZWzsmE04pyodApSkvLSDh7zmY5\nLTcvj6vXb7Bh3dpWr0t/lAGuHr327fvYe6hD89teWezQ/LrCc6NYAFYrYtECZiOHDx9usWujsrKS\nxMtXaGhoYHRoKPX19RQ9c0WsUqmor9cTH7d6QC1BSJLUibVqhd5k92f7+uVzKS0t42JSUpudb29T\nWlrG2QsXv9yNpaDQBpIk8fePPuaVnV96t83Lz+dCYhLTIqdSXlGBIAi46XQ2S3DQ+4rFJw5WLLb1\nA8ViMM7CtI5RT0VhHnv37mVok5mKtPRH7D90mBu3UlmxdAkxK5aTmHSZsNBQNsavY/3aOObNno3F\nYiH7aU4fVqDzCILA1MmTuJV6u6+LotCM6AXzOHv+AmAN/pWVnU3G4yc9shzRGfz8hjAuPJykK8l9\nWo6m+PkNYc6sGXx+7HhfF0VhAJB89Rorli2xmeF6mpOLr48PgiAwZvRoRoeEcLMf9IsqQXDorz8w\nqGws2sJsNnPm9Bn0dbVsjLe6MZYkiVupt0l7lGEzcnR2dsbFxQV3dzdSb98h48kTvDy92P7i5gEy\nFWu7nWrC+HF8kXCGs+cvsGRRdN8VS8GGoMBAHj/J5PDRY1Y318HBqNVqPj92XFYuAocNY8a0qK47\nhesiERPGc+Dw570qsz1GBAej1xu4kHiJ6AXze0BCV7dOKvQ3CgoLmTPLdnv33NmzbP42m814eXn2\nZrGeGwa9YlFeXs65c+dQqVQsWbIELy8v7t1OJf3+HQAip0y2Ox396s7tnDp9lvAxYbywPr63i91N\nWnaOK5cvJTcvj3/s/pTF0Qva3eaq0DvYM1qcGDFB/ndefj6HjhxFFEVmz5xB8HMeGTP7aQ5Tmk1d\nOw5FqRgsWCwiZWXlrdqWmc1mPvzHJ2zbsqmXS9aSgTBU7SyDdilEkiSuX7/OpUuXiI+PZ/369Xi5\nu5P9KI3i/Dw2rFvHhnVrCQ0JaXal9TFrNBpWx6wifEwYto9eaPb/rtJenh091nE5wcOD2bF1C6fP\nXmgy3d6WnM7Qnfr0Rzn2ZPa0nJb5DA8azoZ1a9kYHy/Pbohi82fXfTnN61NUVIxGo20jnWPktH/M\nFkODgeRr16ivb+6HxrFy7NOd93TgtkHH9UWOktO+zBfWr+PEqQS715jNFnZ9vJttWzY3sZdzVH06\nj+DgX0dITU3lpZdeanH8yJEjbNmyhe3bt/OTn/wEsH5Lf/zjH7N161ZefvllcnLaNwcYNDMWFouF\nkydP0tDQgFqtRhAERowYwfTpVte7ycnJ5Gc/wUOnY/nSxbQ+OpHs/Lu9Y12hK3K6Irvl9dEL5nLz\nVirToiLbkdMZulOf/ijHnsyelmMvH+u/BQEWLVxAVVUVnx87Jp8NCgxkxrSoLi7R2a/Pk8wsUq5d\n58VNG9tI1305HTtmy9rVsTQ0NHD67Hnq6utZuWxJE8d0Pd02uvOeDvw22P/6wdYRBAFPTw8ys7Ko\nqqq2cVhWUVGBt7cXCWfPUlFRyY6tW5rsqBv8s1Z/+ctfOHToUAsfTA0NDfzv//4vR44cQavV8sYb\nb3D27FnMZjNGo5Hdu3eTmprKz3/+c/7whz+0KWPAKxbl5eUkJiZiNBpZtWoVZrOZxMREzGYzBQUF\nmEwmbty4QVRUFLOnT7PGC7GYsTYgodn/afZve9hL251j7eXdmes7VsaQUSFcvX6T/MJCFi1YgIeH\ne4/IsT1Gj9Wn9+W0Rk+2DSteXl7Ex8XJ57Of5rD/0GEEQYXO1RVXVxd0Oh2uLi74+Hgz1N/fGnOj\nzTJaMRqNHD56nOFBgc+WB3uuDXbnmTk7O7M6ZiWiKHLs5ClcXVxYsmghKpXaoXIcU5+uXN9f22Dv\n9E+OktPQYORRxhMys7OZOmXKs8ClAv7+fs92PAnU1taw/9DnbN64oVmevUfvSoNRo0bx+9//nu9+\n97s2x7VaLbt375ZDYpjNZpydnUlOTmbhQquTxqlTp3L37t12ZQxIxcJkMpGQkIBer2fIkCEsX76c\nxMRETp06hY+PDzExMc060yY4aazBZww1dE0b7o6G3Z6c1s53tpztX7t543oaGhpIOHsOjZOGlcuX\n9ogc+3n0tJzGzqan5DTSvFPrybZhv5yjRo5g1MgRSJKEyWRCr9ej1xvQG/QUFhVz+849cvPz+efX\nXrErR6/Xk3QlhZraGgRBIC52FS4uLg4oZ0eej708Oi5HpVIRF7uKwsIijp44KS/viaJI1NQpjBo5\n0iFyWk/XVn16q230Zhvsvf6pM2kzs7JIvnodNzcdkiRRV1fP/Lmz2bQhnrq6OkrLyppEQ7d9Pu7u\n7kycMJ4rKSlNjD3be/8cS29vCFixYgV5eXl2y+Hra7VJ2bVrF3q9nnnz5nHs2LFn0Y6tODk5tRtl\nfMApFgkJCaSkpBAaGoqbmxtVVVWcPn2axYsX21TeLo1h0+VofvY0YJqdawtHjDK6Ksfe9W2db3nO\n2dmZNTGrOHbiC/R6Pa6uuh6R01v1aalQdFZOe8dak2OP7owW7ZWxbTmCoEKr1aLVavHy8gYkQkOs\n5w4fPWY3r8SkK9y4dYtXd+7A07Odd8ehz6yz961tOcOGBbB2dazNtVdSUrhz736T4F+9VZ+mx7oy\nA9CXbbCtPNqip97ntuXo9XqOnviCwGEBbN28yUbOpcuXuXPvPmtiVjFl0kQOHz0OSBgMDayJWWmz\nDBAxYTznLlzk0JGjhIwc+awffD6RJIlf/vKXZGdn87vf/Q4Ad3d36urq5DTtKRUwABWLWbNmERoa\nSkhIiI2nyQ7RPGy6XQ24+bm26I7231059q5v67z1A+Pv54der6e2ro61q2MRBIGJEeM5fPQ4G9bF\nPZsG656c9nFMfdq+tity2jvWVrlaS9P3ckRRtJvXgnlzUKkE7j140GIrXsfk2Ctn/2gbc2bN5My5\n85SWlrUS+6Q32mBH82ktz+erf+qoHEkSSThzjrr6OuLjVj+bnf7yekkSESxmQkeNBGDSxAgmTYwA\nrLZ4/9j9KXGxMTZxaxrjMX2RcAYvL098XN3pLXp7KaQRe/5yfvSjH+Hi4mJjQzFt2jTOnj1LTEwM\nt27d6pDjsAG3K8TT05OwsLDOKxVgDZvu5AwqJ1o+TnuPV+jAuc7iCDkdkd0yjcUiMjokhNkzZ8ou\nv0Fg1MiRxMet4fDR482cInVNjv36dPde9pac7sgeeHLmzZlNYVFRK3IGyjOzf93i6IUcOnqMw0eP\nkZuX12NyWj82sNtG/5DT8tievfuZOnkS69eutVnylswmxKx7SOnXyE45z3ihGjHrLqLpy1hParWa\nbVs2czEpya6cFcuWcjn5ahfr1DVUDv51lMYlmCNHjvDZZ59x//599u/fT1paGi+99BIvv/wyCQkJ\nrFixAq1Wy9atW/nFL37BW2+91W7eA27Goluo1KBRWY03OxA2vfsjBns4Qk5nRhFfIghQV19PQMDQ\nJtqq9f8uLs5s2hBPyrXrpD/KYGz4mC7L6dnRV0/L6Y7s/ilHq9E+W+pq3Fpne93IESPIfprdzCbB\nEbL7tm2oVCpef+UlRFHk9NnzVFVVP/MR0hP1sXes/7eN/i+n5bEVS5dw6/YdljUPvmgxQ3UZSCIu\nGido0EODHlPAaD742y6Ch1t991RX17Bs8SK7cgQBAocFdLFOA4fhw4eze/duAOLi4uTj9+/ft5v+\n7bff7lT+A27GolsYDWCotaNUPB+sXxtHbl4eKdeuU1tbZzfNjGlRPHwWJ2bg01eTjP2L5UsX8/mx\nE62enxY5tV+4Nu4pVCoVK5Yt4UlWVl8XRcEBDBniS1l5ecsTWhcYO5167yAMWjcICIGwSC5fvcGL\nL2xk7epY1q6OZcfWLQxrQ3mIarI1tTcQBMf++gPPl2Ihidbfc0z0gvnU1dVhMpk4ffZ8i/MqlQoP\nd3cOHP6cs+cvYDKZ+qCUjqKro6nBhVarJTxsNHfv2R+NCIKAxWKxe05Bob9hNBoxGo0tjguCAFpX\nPjufwpZ/+jqqYSGo3L2ZFDGBkwmn+zwGT2sIDv6vP/B8KRZaV3B2B7WW53k0u2RRNFFTp3D1+g3u\n3X9g9/yGdWuJmjqFjz7Z0wclVHA0UZFTeZCWTn5BQYtztbW1ODs790Gpeo/q6mqqqqr7uhgKDmDv\ngUMtotzW1tZy7MQX7P5sHy+sXyfb4JWUlJKUnIzRaKSoqO+jfj4vPF82FgoykVOn2Hijs4e3t7cS\npGcQsXnjes6cO8+NW6msXrVS3jJ2MuE08XFr+rh0PUNNTQ2nzpxFkqxT3A0NDYNeiRrM5OblUVNb\ny8mE04B1x5Moiri7ubN0cXQTHyxWrt24ydgxYxg3NrxNfxGSKCJZzAiqLmwK6CaDcYj7fCkWRr11\ny6lChzGZzJhMptYdjikMKJYuXkRlZSW7P9uHr48PdfV1jAsPx8lpcHQFoiiS/iiD9IwMJEmivLwC\nNzcdXp5eXLqSjIeHOyNHjOjrYip0keDhw/nq66/Jf3+5u80+satWkHz1Gp/uO8CFS0l4e3nxxrf+\nn7zVVDIakYqzoKIIRAuSoEIsr0c1JqqnqyKjKBYDHUFl/T3ndhYdxWKxsG5NLHv27mfThvgWowGF\ngYm3tzfbX9xMVVVVkzgbA5uqqiqOnTyFu7sbY8eMIS42hvsPHuLi7MKqFcu4d/+BolQMQjritdLF\n2Rm1Ws2vfvbTJjujnqFWg7sPCAJ1+dkYte7UCCYGx1vRdzxfioXWBSRnsFjAaH9XhIIVo9HIf7/7\nG6ZMmoiExC9+/R5D/f0Z6u+HzlVH9IJ5uLv3nhMZBcczWJSKC4mXqKyq4sVNG+XlnaKiYp7m5LI6\nZiWlpWVkPHkyaJd7FOwjiiIHDn/O6JAQNm2IB6wzHCdPnaa6pgatViPbYkiS9CzWDmQVlDEzrPfK\nqRqEUxbPl2IhWpq49G7uQraz7mY74oLWHh2V013Z3ZNj3UkQRvT8+fj4eGOxWEh/lMHTnFxKy8p4\n///+zuSJE1m2ZLGdLU79rz4dl9Md2YNNTs8/s+MnT2G2WAAJSfpyu5zFIqJSCQiC6tm5L/NpOko1\nm81Mj4pi5IhgGymnzpxjx9bNiKLEH97/CxMnjOfuvQdMjBgv59kT9Wn9WGfkdEf2YJPTddn//evf\nEL1gPmmPMsh6+hS1Wo3RaGLhvHkEBPi3Ksffz68L9ek6/WUnhyMRpFb24KQ/82XQEfedA4aGumeR\nTRU6gslkIulKMlXV1dTU1LJtyyZ5RJiYdBm93kBFZSUBQ/2JXjC/14PpKAxcRFHkk0/3sjh6AcOD\ngmzOJZw5x2cHDrJy2RI0Gg2iKBI5ZTIho0Z1KO9zFy4yJmw0wcOH8+BhGiWlpUQvmM+vfvNbvvZP\nr+Hu7o7FYuma916FAYMkSbKzv870TemPMsDVo9e+fcf9gtpP1AliS/Mdml9XeL4UC5sgZE214O6O\nyNrTsDs7CuiIHHvl7Dk51dU1nDpzBicnJ5ZER+Pp6cH1m7fIzMpmqJ8fhcXFBAUOY/7cuR1w0tL3\n9emenJ5oG89HG3z85Ampd+4gSRKrli9Dp9NRVVVNRWUlFZWV+Pr4EBoyirq6er44fRqVSoWbzg21\nWoaKIcIAACAASURBVEV5RSWTJ0Y88wprX05lZQWJl5OJi13VogZnz1+gqroas9mCSqVCpRKQJFgT\ns1IOFd3Z+nT8mXX0vvVl23CkHHvX94822J6c9EePwdW91759JxysWMQoikUfIYdNV+gsZrOZj/d8\nxvKliwkKDATg7r373L3/gAXz5nAhMYm5s2cSGhLSh6Xs6vRsf5Uz8Kmvr+ez/QeJnDKZKZMncys1\nlczsbJycnPD18cHH2xsfH2/yCwp5/CSTJdELGfrMZXNtba3VW2yddQfLuLHhdmVkPH7C1es3bGwt\n2uPA4c9Zt2Z1N2cvHLlE4AjZCu3T+n3r7RmLk/6OVSxWlfS9YvF82ViYTdbtpvJySEdHdk1x1Miw\nM1p3Z8vZmWs7J8fJyYmd217k2o2bpFy7gd6gx3/IECQJcnJy2bY+jr179zLKTQ3ObggubqB1fraO\n2NP1aZwqccTorCNldMQIdPC3wYqKSg4fPca6Nau5cOkSjzMziZwyhY3x62j+zAKHBVJUXEzGk0xZ\nsXB392Dp4kVtyrl5K5XM7Kds27KpjXLT4nhWdg7/2P0ps2fOYNzYsR2qT8t70dX72pdt0N41Pd0G\nu3JtT8mRmh2jWVqF7vB8KRYWYzMbC6nZ/5v/2x720rZ3fWfTdVVOV67tvByVSsWsGdMBeP///g6S\ndSajMOMBTyqycCrPR8x9hEqlQnJxQzVuZi/Vp3kenUnbGTmt0ZVyDu42mF9QwIXEJEaHhpCUnMzq\nVSub+UT5Mg9Jkvjgw12sW70af38/u2lak+Pp6Un206cdLPeXf3/7m99AkiQOHP681ZmQjuXZlfva\nl23Q3jU9Lacr1/Zlv9E7DEY15vlSLJxcQDBat5tKIrYNqDsjzK7Qn+V0XOacmTOgJIeJI4aBoY7d\np84zOXw0T8zOhE+ZBhrts9y7J6e36tO2zP4mp3+3jbT0RzxMT0er1TLU35+F8+e1macgqPD18Xmm\nVHSubkeOn2DxwoXcuXsPJycnnJw0CALU1NRSXVONj7c3kyZORKUSAIHU27cpKCwiZuWKZ8GbBIxG\nYzNbi46gtI3+3Aa7Jqd3UQ1C1eL5UizUalC7WmctGpr7seioRtvWaKMz9Gc5HZc5edJE9v7+BBN9\nrc6zVs2Ywt6zSUyIDmCsc1NnNN2TY/8ax9enbZn9TU7/bRvnLyZiNJqorKxi3ZrV+Ph4d0jOl9b7\nnavb66+89Mww04zZbMFsNiOKIv7+QwgbHUJpWTl/fP8vhIwaidlsZmRwMIYGgyzHTeeGXq/vgmKh\ntI3el9Nb/YZCV3m+FAuTwWpnoXjedCjqYaGY/UfhZG7Ax0/DUrehjJk6ra+LpdBHvPfb3yNJEiGj\nRrJj65ZOuQsfFhDA05wczpy7wKwZ04mYMN5uuoaGBvYeOMSOrVsAcHd3b9NhW2FRMdlPc/D28iJ2\n5Qp8fX24ffee7B+jqrp60DgMUxhYDL75Cp6zXSEN9UqskB7gzt17uLm5MTo0pK+LotAPaC9+Q3vX\n/v2jj9HpdLi6uiBJEhonDaIkohJUxK5agSiK/P2jj/H09OCF9fFdLuejjMfce2CN7jt/zpxmdh0K\nzyu9vSvktP9wh+a3rCTPofl1hecwbLobqDUMTj2xbxgdGsKTzKy+LoZCP6E7jtIEQWDypInU1NSQ\nk5OHxWLB2VmLXm/Aw8M6I9EYGntceDif7jtAXV3X3POHjwlj/do41q+NU5QKhT7DauPjuF9/4PlS\nLOS7/3xVu6dxc3OjXl8v/y1ZzIj1tUiisuTUGSRRRDKbaGUS8blhelQkr7/6Mgvnz0WSJAoKCxEE\nKK+o4PDRYyxdFI2npydubjpMJhOFRcV9XWSFAY4kSYhmU5/0WYKDf/2B58vGQlkK6VHEwhyke1fh\n/jUwGpDcPGHmElTTohV3320g1lZCeSFUFVudt2lckAJHI/gM7TcdRU/wJDOLnNxcqmu+dFYniiJl\nZeV85ZWXmDxpIpMnTbS5xmw2c/X6DS5cSpJtOBQUuopkNiGV5EJ5AZiNSConxCoDqpDJfV20Ac3z\npVg0zlYoxpsOxWg0onHSgLMr+AXC0OFQ+BSGh4K7N/1Hj+6nqJ1A5wH6WjDWW+9ZJwweByKiKLJn\n737+5av/hKenJ0ajkZMJpzGbzbywfp2cTpIkHmU85v7Dh4DVQduMqCjmzp7VV0VXGEwIKmu/5eYJ\n1WXW99DQuzPagzEI2eDuvZqjdQVJsm43Nda3n16hQ2Q/zWHUyBGofPzAxw9pyhwwmxA0nd2693yi\ncnUH1/+fvfcOj+LK872/VZ2VhQIIJBBBIiMEmGAQOZmcjfHg8Zj1zt6979y945nn3fHe98543l0b\nb7j7zN0w953dCbv22MbGZIFJJpmMAYlkECIKEEggodi5zvtHSY1CdXdVdVV1ddf5PE8/kk76nqr6\n6fTvhDonCSSjD0A4MCK3o45F3G43Dhw6DJfLjQ3fX4+UlBQcO34CdfX1mDtrJhISEgAAz57V4ejx\n4wCAIYWFWLpoIR31oigOYzKB6dEL6NELhPMDrAksV6lpHeix6bEO5+edCr8P3TdZkbrpityNYZTQ\nEVOG1Hzyde7cvYeSyZNehDAsENSp0Pv1iC1LyfRtuSSv/5GmQwjAuV3wPXkC4vHClNED5rS0NkdG\nHdsACJxOJ06ePovGpkZYrTbMnDY14EAA/KueyxYvAsDA6/Vg5+49SE1JxdJFC2EymUXriK+fVjYo\ntgw18sWiTnSfGcOaQEdXlcFYjoXXFeLYdKn/HHIX2CmhI6YMqfnk67Q6W+FwCG2GpayOtHxydcSW\npWR6bXTq/vCfePab34C4XIGwjP/2I2Ru+EGYsuTdy5OnT6OmthZ2mx2TJrwUdJ+IxsYmHP3mOFiW\nxaPqx1i8YH4Hx0NPtqGETenTNvSho4dnpv3C6Xh0ZYzlWJgsvN0Ejk1vRw2vW8kecyhtNbbZFa9D\nCAe/36+6TvTuGx/GNT4DmhsAVwvAsoAtAUjNApsQbFMmrWzjRT7O5+UXgbpaeSfa6uDrmZED1mRG\n6oqlsI8eBfe17+B9VA3H6CLYhw4N1Ei+NgNC/CDPqnltTytOX7kJR0oqlrwyD6zZErKUda+uRkND\nA1wud9u238F19GUbQnnV0NF7+yRWR2/PTB9QxyLWMVv5T7dj09XwupXsMYfSJmHC1NU5d/4CXhqr\nxC6bSl5PqAZFqk5b2JP7QGtD56iUHiHqoJVtdMjX8BSovtUhrh4wW8Bk9QFAYE5Lg3lMMRLHFEfg\nTAhpE8DrAR5WAiCorW9AQ3UVJvbLDPJefefnwzAM0tLShBJ21wkZFilydaR+Scu0QdHaofKpbIMh\ndfT+zChKYSzHov3YdK69hx3K25US3xGxHrTY+PaWOdIeQcdylNNJcDjQ2upUXUfe9Qg1HDJ7i+nZ\n/OpxZwu/2sqe2JZU7jOVbhuk7QucuF38WTcWGxhbAmC181/gSelAVi7gcgKuZoBhAAKQusf8aner\nA0zbmoXu3/fybJB43SAtjSDPnwLOVsDmwMP6RgwbOQLIzAPhCBhTRw1Ajo4ebD0yG5RjB13rJaUc\nKTrRbAel5IECOmKembZjCPStkFhH8rHpYuMhECannHBhcnRC6UWuM2L4MGzdsRNDBheGSBe5TvD0\n2uiwmcG23Y30mYq3DeJ1g3x3GkyHDbQIAGbYZMBiAWuzA70HAQC4u9f4fTEA4MENvpS8oWB69Axz\nHdLuJXdmH/DwVqfQguLZ+PrGXVxtvIWxxcno2TNb9DUqUzc96kTy/662TjTbQa3ziLnGYFrqEI8v\nOxnLsTDbAIZtOzbdD3W8eyEi6ZnI7TnI6QF1jRenY7FYoIWOetcjhJxnro5tcFfOgty+Bjx7DHjc\nIMlpwKDhYIaPB2N1AAL3n+k7BPAPBGltBh5VAoQAjyrBPX3Aj7b0ygdrdYS4BnHXyE5aAOJq4def\nEAKSmAqGMMiobcTHn30Ou92Gnj17RqwTOo92tq5PG9Rb+6SGjlC82s+MIhdjORYmM/8JrLEQ65WL\nDQtGJN60FO1IdITixenwW1CrrxO+HLk6Qsh55urYBrl1Dai89CKguQEYPQVsYkpQHYZlAdYGJDAg\nPjdv8wDg9ALOJjC9B3bXAcCIuEaO48CyLPx+P06ePoOa2lq0tLQiNZWvT2JCIkwmFv9r498gOTk5\naDnhdEKni46tq6cjRKy2T2roCMWr/cy0IR53rTGWY+F1d1ljEQqtPFgxOkrURT0drtP++rF/PeHL\n0NY2mBlLgdz+ILXVgN8Hpn13UzF1MVuAfsOBlkZ+S3uLjR+xaBt/5XxefsfPlgag4SlIejaQkAIm\nKa3LzC+D2vLLeHbpCm7v2Yf6pERcZggS++bi6fPnYFkWP/3vP0Kf3r3DXo+Ya44MPemoBW2f1NXR\nDm3VtMFYjgXnF+lUANo1GGJ0lKiLOjrtvVe1deSVIU6H+Lwgzc+BxBSwFpuIMrS1DTYlHRg7rXss\nISDPa4FnNWD6FQR2OuW8bqClkXcOzBYwKRlASoawRGsjUH2bf40WAKqbgeQMIDE14HwQQkDqa1Dx\nN79E5alyHHO2oo7jMCAtHS//77/H5LkzYbfbRV9P5GliSUctaPukbx1jYyzHwuoA/OYOu29SA1KC\nZ8/q4HQ6u2ySpX84Zwvw4Ebb4XQ+wGQCZ0sCM2Bk29sT+oW7fBrk4nGgvhbwefkD33L7gxk8kn9j\nxO8HMZlB7ElgBowKuk04k5LBOxJ+L4jfB8Zs4acL23UuHge5fBqor8HEiXkY+/JA5DmtyJ2/EoNG\nDQcb52eaUChqE49b1cfj9E5wGIbfJOvF+2+UCGFZFuvXrcWuPXujXRXpcH7A02E3Vr8f8Dih5OAk\nIW0jIkF3fO1QHa8PvsZmccemtzQBDfX8K9QAP9XhcfH1b9+wzO8DfJ6QxTBoG5gwmfn/DdbEhwEg\nHIGn+hG4ulp43Xw5Zr8bVW43CscUUaeCQlEARuGPGMrLy7F+/fpu4YcOHcKqVauwdu1abN68ORC+\nYsUKvPHGG3jjjTfwV3/1V2HLN1bLQI9NVwWz2QybLfYOHGMTU0CGTgBpfMZPBdgSwKRkgDEp43j6\n710H7t8Equ/wu3X2HQxm+IQuiy6BprLLePbVfjzdvBW+hkYkji5C7x++hR5zZwZtKNiJc8CNnAhU\nXuGdij4DwOQOAEDarqcVcCTy1xPiUDPO2cJvrFX3CPC6QawOeBPScWvvcdzdsh0PL19Fj0Q7DqTY\nsOi1FWhOy8Qr65crcn8oFIr2/Pa3v8WOHTuQmJjYKdzn8+HDDz/E1q1bYbPZ8Nprr2HWrFlISuJ3\nF/7oo49EaxhvxCIul8pEn8yMDFTeuh3takiGYU1g07LB9uoPNr2nslMgJgtgs/FOhckMWO0Qsj/G\nYoY5JRlscjI4jkNl+WXs2vgrfPV3/4Sq8iuCIxiEEMBsAnLygPwCIDUVYADGZAab3hNsTn+wadlt\nByuFgGUBk+nF9IfZAsZsgTkhAY+sZpz2eWHJycXsV5agKjkbUxYuQXbPYHthUCgUqWg9YtGvXz/8\n67/+a7fwW7duoV+/fkhKSoLFYsHYsWNx7tw5XL9+Ha2trdiwYQPefPNNlJeXh9Uw1oiF1QFY7Pzw\nsNcNusZCOSZPmoidu/fA4bCHeTPAOJhyBwK5A0HGzARYJuiXfNLwoUgaPhR9/mwDPpz8Cu5duQ5U\n1wFnL2L3B7/CO/u/xMDxnbdNJ0/uATX3AfLijRyS0RvILZTkOrM2B5CVC5KZC8L5wJjMsAAoWN8f\n9UML0Hj8BBb96P8CY2KxdcdO+mwpFIXReo3FnDlz8PDhw27hzc3Nba+H8yQmJqKpqQkDBgzAhg0b\nsHr1aty9exdvv/029u3b12XRfmeM5VgQws9Ji34zRK/o7dUsPs3ihQuwbdsODMvtgwGZGTClp4NN\nSeW/VBXUiTUYkWsRGJMJvUePgtPtwdPb92CyWNCrYCD8XoH1GVY74EgG3M38mgqrgx99kFvHttGO\ndm5W3sKO0j3gOA5bd+1CakoqxhaP7pgDerRB/etQeOgz0xtJSUlobm4O/N3S0oKUlBT069cPffv2\nBQDk5+cjLS0NtbW1bRvfCWMsx8LjjJM1Fvp8Natl/36M//2/4cuKW1iRzq8jsE2dhuy//TuE3reW\nvgLWzvf/v38Ax3G4X3YZielpyOrfTzAd26MX0KMX/2qp2wUmMRkMo9zMZsGggXj/vf+JHaW7caOi\nEhNeGot+bY0Ljz5tUP86FB76zNphozQ733WKdeDAgbh37x4aGxtht9vx7bffYsOGDdiyZQsqKirw\ni1/8Ak+ePEFLSwuysrJClm0sx4I18UPH3UYs5G6CJNUbVlInVL7o6DgmTIAp868x9fARXD1xFJOL\nB8Pcuye4k3vApGYAuYPApmXGzPUory0uPcuyyB9TJKoM1mLnN72SodM1jHM2A41P+YWfBIA9AZ7m\nJjhdTkwrKQmaT6qO3PrFpo7YsqSmp+2TujrawUTJs2ifgiktLYXT6cTq1avx7rvv4q233gIhBKtW\nrUJ2djZWrVqFd999F+vWrQPLsvjggw9CToMAAEOCvNtWUVEBACgsLBSKjm26HZtOUZpNv/xLLC/I\nhrnDGxbM1GVgc/KjVynFia9hVu7OFd6x6MDhB01Iys7BhJfGRalWlNDElw3qgYqblYAjWbPvvrK8\nfEXLG111V9Hy5GCst0L8Xn46xN2C7mtomS4/5YRFGi/kuQZLF66ccPVQV2fh8hXY/bAZSM0AUjOB\nvoWC6bS/nkjiu5ZPVNIRDiMAiNsFrq4G/vsV4J5UgbS273shT4dwfpDG5/DfvgHubiVIYyOI3w/Y\nEoDULMyYMhGPn9QEKVvfNhg9HS3bDW1tsDtq6AgRDdvQBoZR9qMHjDUV4ut6bHpHSJefcsIijQ+3\nfbRS2kIoq5M8agJynAyuJiRg5IjhHVY+x+b1BC9fQ9twu8Dt/j3g9QRiCAB26Z8C9oSw5RBC2p7D\ni3hy9ii4bb/vnDMlHczPfgW2bbSpc2MVy89MK51otht6aJ+UqIcYHbVtQxv04gwoibEcC7MV/LHp\nPoB0Nb6O3n+oMHSJC/a7nHixOh2/pOXEC6G8zqQJ43HoyFF8d/0Ghg0dopPrieSZCZWvhk6QMJsd\n7MK3QFoaQJqfg7ElgElO77A/Rvc8hPODVN/mN4dzt4K0H0LWsy9YiwPM+GkwDRsD7ukTkMY6sOlZ\nYDKy+b0t2vD5Oq5Jii0bjI6OmrahlY6a7aAen1lHHUqkGMuxMFn4j+Aai1BerpARhvOG5cSL1YlU\nWwh1dGZOn4b9Bw8hIcGB/H79uqVr+/qLWKc7at83oYZWmk7waxcOYwDAZgdjswM9ur7qRQI16lSO\n3wfUVb9YsOxxAS0NYHr258tkTUBKGkwpaQLXCFRXP4bZ3HH/jdizQe11xP6PR98GpcUr1Q7q8ZmJ\niVOHeDwrxFiORdBj08N54sEQk0YtHbHeffR15s6eiR2lu9scCz4N97yWP5nz8T0gMRVMZm/+Y7Ho\n/npehIXSF9YhHjeIqwVorgf8PpDkHmASU8BY7BLr+iINcbWAuJqBxjoQiwVITOfLNJn5Y9NzC/mj\n0Zuf8/bv94PcvwaS3hNMQgpgT+zi4AAulwsnTp3Bs7o6rFm5XMK9CRUXL7YeqgcvBiXbDek2KE9H\nyXyxoEOJBGM5FkGPTQ/niQdDaqOipI5Urzu6OmmpqdhRuhssyyLLYcO46ksASwLeOrHYgHnfC+JY\n6O165NsGqXsE1Fbxo2YAUPcYJH84mFShV0bF6ZCae0B9TSA9cVXCxyTDMmoMGLsdTHpPIL0nuNqH\nwJM7/ChGcz3QXA+Smg3kDOBHQQC43W5s2b4TPdLTMWnCS0hNTQ1Rl9iyQeV0QvXgxRDNdkMrHb09\ns0h11CMOBywM5lhYHYDPDHCxfmy6GqMpYsvoGiZOZ1rJFHAnD4A7/w1u3azA1kdPAUcCVqxeBXbm\nMjCOxDCHf6l1PdrC9uoPkt2vbUt58Ot+Ijz0jOk7FOhTCG/5ebT+7jfwP6oGaXgOJiMTpoGDkPKL\nD8A67GCy+gCZOYDXC3LvKv+GVEMN0PQMDT7gSqMPFfce4vW1a2C1hjtULpo2GMs6FB76zNqhUyGx\nDsPwQ8M+EuM7cGrldYvx+MXrkNrHwOMqDHSYMXBgL9xvcmJH+Q307VOJl8aOCZdbtI66ZYQonYDf\nMt5sDtlYMCwL2ByK6TIAYDKBNLXAd78KaOG35SXPnsJvs4FpWyPB8OKA1ca/otp25Pr5azdQ9eQZ\nJi97FS9PnS6yoYumDcayDoWHPrN4xliOhcfZ1phSY4sG7JLvgUyYAVwvA1d9G33TM9AvuxfK713F\ngbs3MWvpCrBmoakQfUM4Au7ed8CDW8DjO4AjCRgwAsygIrBWKbtiRoZt2gyYRxbBc/wY/I+qYO6b\nD+uUaYLTS8ygYpDmetTeu4sqrxnL3v6vYOyJcdl7olD0TDz+yxnLsSDhFjtR1IRhGDC9coFeucCz\nR0D9E6ClAaMH5WPf1TtoamxGao90SWUSQsDdvwPfudOAyQTzhMlgc/po+wVJON5hdTbzaye8HsDj\njsoSMFOPHnAsWRY2nZ/jsPvYaSQ4ErD89e9Th4JCiRJsHP7vGcuxsCXwzoXXA/josenRhM3ozR/z\n7fcBDIsZBS/h6yNHsXD+PEnlOP/mf8B/+QLg5Yf1PZv+E46f/RLm4pfUqLYgjMkEU0ERyKBRvG2Z\nzUGPSNcD96uqcOz4SSxbvBBJSUnRrg6FQokzjOVYkLa1FSTWj02PD/i1AbwJ2u12uFyuDrtDiiwj\nIxNMRhbIk2qAYfjfufAOI+HaRhkYAGarIj12hmEADac+5HCz8hYqKivxvddejXZVKBQK6FRI7BM3\nx6bHJ1MmTcKRY99gxrSpgbC9+w+isakJFosZmRkZmPLypE5OgOPP3wHx++G/egmwWmEqGBLm7RKA\nq74DPH3w4tVjkxlk4GiwjvjuvTc1NeFi+aW2fSkoFIoeiMdpSGM5FkGPTRdCq9eU4u11Ovk6PXtm\n49iJk/B6vbC0LThsdbZi9YplYBgG1dWP8dEnn2HZ4oVITU0LlMGYTDCPKhatw6Rlg9gcwPNa/lXP\n1Aww5kiPHlcGrvYRcOsqyLMafkolMwcYUgQ2MTV85jAcPvYNVi1fKhCjf9uIXR21oO2TujqUSDCW\nY2Gx8R9Rx6Zr1WDE2+t0keksemUeSr/ai+VLFgMABg0YgDt372FA/3zk5PTCuDHFeFJT22HjJuk6\njCMRjCMRpEcvmU2IerZB9n4G1DzspMT0zgcUcCwIIWBZoQONY8M2YlNHLWj7pG8d8TBxeMa4sRwL\nvy+wpTFPuG16pYYFQ+x2wOHKDLeVsJo64X5XRsfhSEBiQiLq6urRo0cPDBzQH6fOnMOA/v0BEAwb\nOhRfbtuOwoJBEV9P122sw9ddmg7xeUGaG4HndQALMGlZQGJyl6ka/qAweFwgTc+BpBR+7YerFc2M\nGd/UNMN/8DCYHtkACBITEtHS2gqAwO/nMH7cGPTp3TtIfbrWLdT9CHXdwa8xdJ540AmXVg2dUGXq\nrX3SSzuohm1oA50KiXV87i7HphOB3yMJC0a4/KHSCcUH01NTJ9zvyunMmTUDn3+5FWtXr0RiYiIe\nPnoEQjj+dVWG3x68tvYpsrIyFboeIeQ8887puC9/Azy83SmWee0vwPTu1+kIc3LtDMjVMy+KSbAD\nw8bgk/L72PCX62Gz8dM0hBC0trYiISEBDMOAEIKTp8+g7NJlLJw/D/fu38fZby+AZRm8PGECcnJ6\ndapbn969cb+qCn3z8kRcg7hrFPd7LOuES6uGTqgy9dY+6aUdVMM2KHJhCCGCd7SiogIAUFhYqGmF\nVMXnfXEIGeE6REjxdiPxpuXotHuzcnU6pkeYPPrRuXT5Ch4/qcGcWTPQ0NCIXXu+wutr14BlWRBC\n8PGnn2P9urVtK6rD6cjp5XWtVygd4XjiagVpeAby7AnuPalB2aNnYBKTYbbawHF+cBwHk8kMwvnQ\nXF+H2cUjkJloB5PcA0xKGnZ9fQQL5s5tO100uM7tO3dw/mIZ+ublYvy4sWAYFp9/uQVzZs5Aj8C+\nIAwI4bB1xy6sXLZExr0C9GIbsaUj5/9dORtUv32KVKdjeoTJgyD5lNWpuFkJOJI0++67NaxA0fIG\nXrupaHlyMJZj0Y6oNRaUaFNTU4t9B7/G7BnTkZSUiC3bd+J7r70Ks9mMurp6XCy/hFkzpgnk1GpY\nU5zOiVOn4fV6MX1qSdA0hBDs2bcfbrcbFosFTqcLHo8H/fP7YfKkiZJrRgjBHz/7HKuWL4XD8WL7\n8B2luzF/zmxYbbZAE6s90Rt2VodwzoDW2pTwBL9vvGORrNl33+3hyuoMuFqhaHlyMJZj4fPwoxac\nH52NSu4/pxKeulyMo7N9124UjRyOntnZ+GLLNry5/nUAwB8/+xwrly3p9MUZiY7S19PY2IA9+w5g\n9KiRGDK4MIyO8vfS4/Fi9972hbAMiM8DV2M9du0qxarZU/nj6h3JgM0u08lQ4l6KSRd9G4yujtrt\nU6Q6obT1di/DQx2LyInD9agh8Hv5k027GZtcIxfKRwTihMIixTg6yxYvxIWyciQkJGDShPHYuXsP\nAGDt6pX4/MutaGqSMvqk/vU8ffoMm7duw6kz57Bq+dI2pyKcjnL3knB+cM4WWCwmvOg3EJBn1bA9\nuA5LYy28j+8C966CPH8SwciFEvdSTLro22B0ddRunyLVCaWtt3upPxhG2Y8eMNbiTYsdYNuOTI94\n1ELJXoTU9FJ6eWLz6VOntbUVDx9VIzODX6g5uLAAN27ehN/vh9lswRuvv4YvtmxDQoIDE8aNQ8+e\n2RFej9g6C3Pn7l1cKLuEVcuXyljtHZltcC1NwJO7gKsF8LrAWexA7QMQjgPDsmB69gWy+iCnLofy\n5gAAIABJREFUyYTa9F7ok9cXMJsFywpfr+jbhv51xJahRr5Y1NHDM9P+mzkezwox1ogFawLMVv4T\n8aiFkr0Iqeml9PLE5tOnzj/873/Gg4cPMa1kciBseskUfLLpCxDCgWVZrF29EosXvILjp05FUK9Q\niM939tsLWLlsicxXyCK0DU8r0FwPeF0AAMbrgs/ZHIhmADCsCeMnTcLZy1fBWCwd6hl7tqF/HbFl\nqJEvFnX08MxiY5RD7xjLsfA4AVcz3wBTYoJ3f/oOqh48xJWr1wJhKSkpeGXuHGzfVRoIYxgGyUnJ\nePjoUTSqCQBwOp1IT0uLmj6Tlg0MHgvkDAIy+gA5g5AzagLuVVV1SseyLBiGgd/ffQfahoYGBFl2\nRaFQVIBOhcQ6hKDza6YUvWOx8NMd129U4Pf/+TF69szGgnlzkZWViXFjivHZF1/itTWrAABzZ8/E\nV/sO4N79Krw8cYLmdfX7/bBYovcvxTAMGFsikJ0YCCvJzsUnm75Afr9+ndIWjRyJS2UXUJTXE6cv\nXUVtqw+MyYRz5y+iobEBb63/HkYXjdL6EigUwxGPG2QZa8TClgDYkwCzDdGYS6PIZ8jgQnz/e+sw\n8aWX8Onnm3Hv/n3k5eZibPFoXL5yNZDulXlz0DunFz7Z9IXmdUxISGjbFVNfTJ86BUeOfdMpzHP7\nMmwPbwLVt5HcVAvyoAKc24kVSxah5OWXcevOnSjVlkKhxDrGciwIoaMWMYzJZEJGRg+8vnYN7t2v\nwsWychQWDMLNW7c6pcvv1w+JiQma149lWbS06M+x6NO7NxoaG1Fb+5Q3f58Xtc/qkJGWAgAYPqAv\nlsyYgiXz56B4dBF69cyG2WyswUwKJVrE41SIsRwLjxNwt7QdnU7nkWOZqVMmB9YOJCcl4/HjJ53i\nvV4fysovaV4vfpdM/bFk4QIcObAXD098BXL1BB4/eojMlEQgqQcwoAjMkJfAJvCORsnkl7F00cIo\n15hCMQbUsYh1WBZxeZScQTG1HeY1e+Z0fH3kaKe41SuWITExER9/ugmNjY0dYtT7z7twsQzFRUWq\nlR8JDMNgxYoV2H/1LrZ9+x2ysrLB5AwEevcHk5wOhmHx9eGjOHjoSLSrSqFQYhxjjXda7PzH7+NH\nLigxTW3tUzQ3NyMpKQnFRaNw7bvrGDZ0SCC+YNBADBzQHx998hm+/711gUO/1KLq4UOMKR6tWvmR\nYrIn4K0f/hcA6HAI2gsaGhuQ4EgI3FMKhaI+DKuTYQYFMVb33c8fTw2PC917rkyXn1LC5KBnHTma\n2uu88fo6HD72DQ58fRiFBYOwZ98BlF+60ikdy7JYvmQx/vOPn0rcoVNIU43riURHvh7vVHQu0+v1\nYcjgQhz55rgIbUlqAr/Hsg0KaepNh7ZPketoA50KiXV8Lv7odNJ11010+Dvc1rBKbRerZx05mtrr\nmM0mLF7wCkYMG4pPNn2B//rDP4HL7WpbW/EiXWpqCt54/TV8tf8gblTIOflP3PWwEfc8omuDr65a\ngXPnL4DjuC7xsWcb6uoIaepNh7ZPketQ5GIsx8Jk4T/dvFMp3rAcb1orHTl5tdDp3jtWUicnJwev\nr12DzVt3oHDQIFQ/ftK2UdaLtCzLYs3K5bhf9QC3bt8JohdpT0lsD0htHfk2OGrECIwZXRQibWzZ\nhvY6cvNrpRPN9knsSIFe2idtYBlG0Y8eMNYai/btvAPHpsvxhuV401rpyMmrhY6U0SF5OmazGevX\nvYqtO3ZixLDhuH3nLvr07t0t7ZxZM7B1x04kJyUhOztL5vW0wwTC/H5/lxGLUD2gSHtk4fN7vV6U\nX76C6seP4fV6YbFYAjtqEkJQMHBgp/Uo7QwuHKRQPUPlZQTC1NAJFqa0DoPuebuGie0dy7dBefml\npBPKo5SO1u2TGBukyMVYjkWnY9OBF8YlpmEQQih/JGFSdITqGSo+/nUYhkFebi5qamtQMvnloGmX\nL1mMjz/9HK+tWQmLxSJYlrg6vgh/VF2NnJ49w+SXagfS7+WzZ3U4dPQYbDYrhg0ZgqoHD2A2m5GY\nkIiZ06cGcn13/Qa2bN+J/H59Mba4WLJO8HqKuZehtGLRBolAnJgylbANqfeStk/i7pt2aDnIQAjB\ne++9hxs3bsBqteL9999HXl5eIH779u34/e9/j5SUFCxbtgyrVq0Km0cIQzgWlZWVMJlM6N87u+3Y\n9HaCeazBwoKlEetVhwuTotM1Lly8MXTGjxsbNi3DMFi9Yil2792HZYsXydDpHlZT+xTZWZlh8ku1\nA2n30uv1YvfefVi84BVU3r6Ni+WXsHzJIjyqrsamzVsxbMhgZGdngWVZDB0yGEOHDMa3Fy5i5+7d\nAIDWVicGFwxC8WihV2Zj3za00QmmrXQbQdsn9XW0QcstvQ8ePAiPx4NNmzahvLwcGzduxK9//WsA\nQH19Pf7pn/4JO3bsQFJSEt588028/PLLuHr1atA8wTCEY3Hq1CkkJyejf7/FANM2YiHq2PRIe5NC\niNVRqidLdYTKcDgc8Pv9gq9dytEuLhqF7btKkZebK/J65OkES19TU4v3PvgQM6aWYN/BrzFx/Di8\nNHYMAKBvXh5+uOFN3LhZiW8vXoTfz8Hn82LmtGkYN6YYQHGgrPJLV7Bl+w4sX7IYLGsSpR359ejL\nNqKvE4l2vOlE45nFL+fPn0dJSQkAoKioCFeuXAnEVVVVYejQoUhOTgYAjBw5EmVlZbh06VLQPMEw\nhGOxfv36wO8e+PHL/+evMH/uHJRMeblDKqV6JuEQq6NUb4XqBCtj1vRp2LXnKyxZuCBibZZlkZiQ\niGfP6pCR0SNMeeJ0CCG4e+8urn53vdOJoy6XG9NLpiCrwwhJdnYWfvV3G2EymQIbh3UkNTW102iO\n2+3G6bPn8LyhASzLgmVZLJw/D0WjRqB/fl98sukLzJ4xHTk5vcJcv/jr6Rymb9uIrk4k2vGmo4dn\npi5aToU0NzcHHAcAMJvN4DgOLMsiPz8flZWVqKurg8PhwKlTp9C/f/+QeYJhCMeiHa7sKEx3rmFh\nYitaj+/Cf5w6jIsPavH2n/4phg0dEvJGUeKPtLQ0eDxexcqbM2sGSr/aK8JRCc29+/dx/mIZWJbF\ngPx8vDJ3TidngRCC7btKsXzJ4k75rFaraA2bzYZpJVMCf+/dfxD19c+Rnp6GlJQUrF+3Fl8fPoqz\n58/D7/djxtSpSE+P3pHwFEq8ouVUSFJSElpaXmwO2dFBSElJwc9+9jP86Ec/QlpaGoYPH4709HQk\nJycHzRMMQzkWpPk50PgME/Jz+IDEFCxcthz/+sUOcFu34f/9n/8juhWkaEpNTS3S05T7smRZVhFH\n5cy581izcnnQ+LLyS+jf5Rj0SJk3Zxa27yqF2WyGzWrD7JnTMWvGNADAw0ePsG3nLvTokY7Ro0Z2\nO4KdQqHEBmPGjMHhw4cxf/58lJWVobCwMBDn9/tx9epVfPLJJ/B4PNiwYQPeeecd+Hy+oHmCYSjH\ngp28BGT4y0DVTTC5+YAtAVkMg5/+RV94PB4c/eY4pk6ZrKkHSYkeW3fuwsqlSxQtc2xxEfbuP4j5\nc2fLyk8Igd1uCxp/5+5dPKurx+yZ0+VVMAgMwwRGQMrKL+Gr/QewcP48APzpqG99n59OPHXmLMou\nXW5b9EqhUCJFy6+bOXPm4MSJE1i7di0AYOPGjSgtLYXT6cTq1asBAMuXL4fNZsNbb72FtLQ0wTzh\nYEjHydsOVFRUAIAo7yRmIITfw8Ln6XbC6ZFj3yAxMRE3K2+hZPKktkV4lHimrPwSTCYTRo4Yrmi5\nl69chcvtDiyelEJdXT2uXLuGqVMmC8Zv3bETKxR2hjpy+85d/PrffotpJbx+1+aBEIK8Pn0wpng0\nHjx8iHPnL8BkMiHBkYBePbNx89YtmEwmZGZkYNKE8dRJp8QcFTcrAUeyZt999ZNHKlpe+onLipYn\nB0ONWMDjbHMoulNXX4+SyS9jbPFo/Otv/h0/+i8/1LhyFK0ZXTQK23buQu+cnAgWXHZn5Ijh2LJ9\nhyzH4puTJ7Fg3tyg8S0trZFULSwD+ufjHzb+jai0t27fAcdxeGnsGKSnpaHy1m0sW7wIDMPgUXU1\ndpTuhs1qw4xpJbDb7arWm0Kh6AdjrVZkgh+b3jsnB9t2lmLL9p343tpXNa4YJVosW7wIJ06fxs7d\ne+D1KreQc8zoIhzqcpR7KAgh2LN3PzIzMto27RImMTFBieopwrSSKZg7ayYull9CYmIiikaNDIxQ\n9M7JwbLFi5Dbpzf+6de/wZ69++F0OqNcYwpFf7R/LSn10QPGGrGw2gFi449N93Tu+U0c/xKqqx+3\nvV5HMQoMw2DJwgVoaWnBtp2lKBo5AoMLCyIut39+Pp4/b8D2XaUA0G3RIyEEDx4+xKUrV+H1ekEI\nwdTJk4OOnHi9XrS2tiIpUd3jzJuampCYmBh01bff78e2naXIzspEwcCB6NkzGz6fDzcrb6Fg0MBu\n6UeOGI4Rw4ehubkZW3fswoxpJeidwy+efvasDgCQlJQImy34uhIKJZ6Jx+lCYzkWnL/Dlt5dN05h\nBJwKvW5Ao6fNfPSgE047vE5iYiLWrFyOr/YdwK3bdzB50gSkpqZGpFM8ugjFo4tACMHho8dw+eo1\n+Hw+MAwDk8mEPjk5mDtrZocRiuBl7Sjdg70HDuKf/9ffibqe0Ajr/J9//y0GFxSg1dkKjuPgdnva\n9svICqSvqamFx+PBwAED8LuPPobP54PVakV2Vhb69c2D1WrFvgNfo+rhQyQmJMJut8JsNsPlcqPV\n6USPdN5xOnXmHJqbm5GYmICmpmZU3r6NP/uTDTCZujo0xrFB+drxrEM3yIpFjLV4093Cj1ZQKCFw\nu904ceo0mpqb4fP5MH7cWEUW8zY0NHRwVqRx6sxZ5Pftq+qI2p27d3Hm3Hnk5fYBx3Gof/4cj5/U\n4E/ferNTutrapzh7/jxmTpuK588bYLPZ4PP58OkXmzFz2lT4/X6MGjkCLMsG7Y1VPXiAM+fOw2q1\ngGEY2G12zJk1Q7Vro1DEovXizYbpQlvoyyf1SLmi5cnBWI5Fp0PIOnqskXrD4TzsUGXJ1RHKL7W3\nEW863UehpOkIh+3dfwAAMHf2zLYpAim9NPE6oeq4ZfsOrFi6ROCLOhIbFL6Omppa+P3+Lk5M+Hq6\nXC4cOXYC8+fOElHHYMSbDYqpQ7AyY7l9kmqDwf53xaTtmj4y26i4eQtwJGnnWMwYrWh5qYfLFC1P\nDsaaChF1bDpChAVLQ0SGhSpDqo5Q/lDxRtDp2rBI1REOmz93Nurq6rFl+04kJiRg1oxpbWsCxDS6\n4nVC5WUYJkjvPxIbFK579+PkxdXTbrcLOBVCeUPdt1i0QSZMWLg6BKuPFFsPVX402iepNtg1Tu7/\nvti8Yu4bRS7Gcix8Xv5108AJp1K9967xkfQypMRH0ssIl1cLnfYvxNjV6dEjHatXLEdrawsOHDoC\nn88HlmVQNHIE+vXtK6Oe0urY+fyPWLdBAi2eWfcwtXRCXU+o/ELxUu+5GB1lbFBZ22ive7Tap3A2\nqB108Was4/d0WWMh5AGH81aF0oYLC5VXTLzUekrJq4VO1zJiVychIQGLXuF3pCSE4Nz5Czj77QUU\njRyBwoJBgvkrblbi1u07GDliGHL79JFwPTzHT55Cj/R0SfUUKiecTuj42H1m0dUJlV9sfdRun8Tq\nGK190giWOhaxjdkOMB7A7wcIB2EDiqQ3KAWlehZq6khBbR2le19SEC6TYYDx48Zh/LixuHzlKnaU\n7gHH+dGnd28MKSzA2W8voP75cwwbMhgzp09F+eUrOHPuW+T06oWXJ04QoQf4fH4cP3kaxUWj8NW+\nA2h1tsJqtSEpMQENjU3wer2wWi3gOA4MwyApMQmzZkwT2QuiNhjrNqi8Tlc9tbX1qEOJFGMt3mzH\n7+PfEKFQVKDqwQPcrLyFMaOLkCZwyNntO3dx7vwFrFm5XJQD8Pz5cxACMAx/Iqvf7+f3tEhK6pa/\nrq4epV/txcTxL3UZQaFQKGLQ+q2QxjljFS0v5cB5RcuTg7EcC6+rbY0FF+2aUAzOs2d12LNvP15f\nuybsEcRyOPvtebhcrqBnjlAoFGG0diya5o1TtLzkfd8qWp4cdLIBqEZwHHUqKLogI6MHli5agI8/\n3QSfT/m9VYYPHQKn06V4uRQKhRIOYzkWVgdgSwRMFtC5NEq0SUlJwZqVy/HZF1/iwcOHipbNsizc\nHreiZVIoFBVgGGU/OsBYizcDN99Y/hRFvzgcDqxftxYnTp3GtxcuwmQywefzYcqkScjKypRd7r6D\nX2Ph/HkK1pRCoagBQ98KiXHcrUGPTadQosnkSRMDvxNCsP/gocCIw+wZ05GQkIDq6sdoaGzEkMHh\n534Zhgl5SiqFQqGohbEci/bRCkLXWVD0C8MwmDeH38HS7Xbj0JFj8Pp4h/jg4SP4xbs/C3oKKoVC\niTF0Mn2hJMZyLKwOgBDBY9MpFD1is9nwyrw5gb9bW51obGoM61io8aYJhUJRgTicCjFW68P52w4i\n86D74k2pD1euMSihI3bzIyn54k1HbBlq5FNPZ+3qlbh95x5Onz0XNL3f70dTU3NEOuHTdw6rqanF\nHz76I/742eeoqakFADidrsDv4rSpDSqXzwg6WtkGRSrGciy8Lv7D+RD5Nq5yd7dTQkdMGVLzxZuO\n2DLUyKeuzqwZ0+ByuVB565Zg/IOHDzE05DoMZW3wxKnTOH3uHN5c/3rgyHUA2LT5S3x95KgEbWqD\nyuUzgo5WtqEu7QcMKvXRA8ZyLEwWgBWa/VHS62ZExKmlE0pbLvGqE047VPro60yfWoJ796tw4WJ5\nt7h79x8gMzNDER0hqqsf4+GjR3j8uAZ//Oxz5PbpgyULF+CTTV+gobEJvXr1RHNzC7w+H0aNGI5t\nO3dhy/YdAqMXYtGrDerTNvSro4dnRtECY62x6HZsejtKet1ERJxaOqG05RKLOkyIPEo+M610hJk1\nYxp++x8fobBgIJKSkgLhHOdvOw1VORskhGDv/oOBRaR9eveG0+nE62vXBHpJSUmJSE1JxvZdpUhM\nSMQb69bCbrdj+LChIIRgR+luDBsyBIUFBRLr0fm+NTU1wePxtq0ziaYNhjq7whg2KE1HT+1GqPum\nMXG4xsJYjkXg2HR/W0C7cXU0MqHf5cSHC+tIuDwQyKdXnY7lRFtHzj2IREcp2xCfZ9CAAbh77z5G\nDB8WqPH0qVOxees2rF6xXLH7snnrNkybMhk9e2YHzZPfty9OnjmLP//TP+mmwzAMli1ejN/87ve4\ncfMm+IMESFsci4Xz54Jl+aPhXS4ntmzfiZSUZAAAIcC1766juaUFBQMHIC+3D+5XPcSb69cFuR49\n2oYcnWi2T1LyAML3JlbbJ42/6HUyfaEkxnIsJB+bHkl8uDCEiY/VPFLuVbzpKGUb4vM0NTehZPIk\nOJ1OWK3WwEjF4IJBOHXmDCZNGB+inI4E1yGEg81m7eJUdM9z7foN9EhPh9/fPmLSXeOHG37QLbSx\nsRGffr4ZqakpyMrMxO07dzF31szABmFerxf3q6rw4x/9OT7/ciuGDh6Mh4+qQ1yPHm1Djk4026d4\nbdPEXGMwLYpYjHUImd/Hj1j4/QDxQ5o3jRDpxOYJp6NUz0KOjpRr1IuO2GchRSdU3SPVESIy22hs\nbEDpV/vg9frQ0NiA//bnfxbIce78BbhcLpRMfjkincpbt+F2uzF82NCg13jtu+/gdrsxuLAQew8c\nwIqlSyTr+P1+PKmpQe+cnG55v7t+AzduVuJieTny+/XFiiVLkJqaIvO+CcVH2waF0IuOEvWJVEco\nXp32SetDyFpXKntQYMKWE4qWJwdjORbtdFtjQaHENqfPnkOP9HRcunIVgwb0x+iiUQCAK9eu4cmT\nWsyaMa1Teo/Hg6/2H4DX60NLSwvS09OQ4EjAjGklnUYbHlVXY9eevXht9UqkpKQgGH6/H9t3lWL2\njOk4f7EMM6dPC5o2Uipv3ca3Fy5i7eqVqmlQjIvmjsWqKYqWl/DlcUXLk4Ox3grxugFXs0inQsy8\nlxJzY1Qn9nS0mhMVf40Tx7+EwoJBWLV8KRiGwdlvzwMARgwbhlZnK7Zs34Hvrt9Abe1TfLFlG/Z/\nfQjTS6YgLTUVWZlZeGXuHIwbMxoff7oJzc38HhjtX+A/3PADpKSkhqyFyWRCTq9e2Hvg607bk8u9\nnlAMGjgA2VmZaGxsVFVHmzLk6ujPBqkOpR1jjVjQs0IoBqClpQW79+7HmpXLO4WfO38BHo8HE8e/\nBJPJhD1792PY0MHIzsrCp198ie+//hpYlsWefQcAENhtdsyZNSM6FxGG+vrn2PTlFuT26Y15s2fB\narVGu0qUOEHrEQvnmhJFy3N88Y2i5cnBWI4FIW1rLHxtizjpIh1KfFJ+6TKufncdTc3NyMrMgNVq\nxdxZM2G1WuF0OvHHTV9g3uyZ6JuXBwBobW3FP/+ff8Nf/uS/R7nm0nC5XNi9dx/S09IwY9pU3WwQ\nRIldNHcsXp2qaHmOz48pWp4cjPVWCMPwm2RxBIAvbHIKJVYpGjUSo0aOgNfrfeFMfPY5+ublYca0\nEphNJvTp3TuQ3m63o2DQgCjWWB52ux0rly3F48dP8Onnm7Hu1dXUuaBQooyx1li4WwFnI+BzgY5W\nUOIdhmECUwQOhwOrli9F7dOnuHvvPsxmM6oePAikZVkWyUnJuFkpvE243unVqyfmzZ6FHaW7o10V\nCkUaLKPsRwcYy7FgGNCFORSjkpKSguVLFqGxsRGrli9Ffr9+neLnzJqB725U4NmzuijVMDIyMzPA\ncRycTme0q0KhiIaeFRLrWB2AIxmw2KNdEwolKtjtdhSPLoLD4RCMX7xgvsDBYbHDxPEvYe+Bgzh1\n5my0q0KhGBZjrbEghN/Wm+u6OVasoVXdxegoURetdCjhYBgGdrtNTEro0TZ65+Rg+ZLFKCu/hANf\nH+72VktLSwtMJhPsdjmdC2qD+iJO2g0Npy8IIXjvvfdw48YNWK1WvP/++8hrW8D99OlT/PjHPwbD\nMCCE4Pr16/jpT3+KV199FStWrAicR5Sbm4sPPvggpI6xHAuPM05eN9XqH0WMjhJ10UqHIobWVjFT\nCfq2jdFFo3D33j3s3L0HAH9NJpMJPdLT4fV64fa4QQhBXm4uxowuEjmETG1QX8RJu6Hh9MXBgwfh\n8XiwadMmlJeXY+PGjfj1r38NAMjMzMTHH38MACgrK8OvfvUrrFmzBh6PBwDw0UcfidYxlmPBmgDC\ndTiErJ1w270GQ6o3rKROqHxUJ7J8amnHho7ValGgftG3jfx+/bqtI+ma5n5VFXaU7obP58fSRQth\nsQRrEpWwJbn59GMb+tNRywbjk/Pnz6OkhN83o6ioCFeuXBFM99d//df4x3/8RzAMg+vXr6O1tRUb\nNmyA3+/Hj3/8YxQVFYXUMZZjYbHxH1HHpqvhDSupEyof1Yksn9gyQjVS0bSNyHSCHSAmTTs2bKNv\nXh765uXB5XLh08+/wPw5swUOW4tEJ7h2ZOnj2waVyafV9USGlgsum5ubkZycHPjbbDaD4ziw7Ivl\nlocOHUJhYSH6tTnldrsdGzZswOrVq3H37l28/fbb2LdvX6c8XTHW4k2/l58OcbeA/4fs+ECZLj/l\nhCkR35VgefWgI6YeetNRMp5opKNkOWLi+bnY8HnjxzbsdgfeeP01nD1/Hrdu31FNJ7ZtUAg9t4OR\nPjON0PB106SkJLS0tAT+7upUAMDOnTuxZs2awN/5+flYsmRJ4Pe0tDTU1taGviSp9yCm8Xn4D+HA\n/0N2bDxJl59ywpSI70qwvHrQEVMPvekoHR9vOoDL5e7Si4r2M9NGh2EYLF7wCo4dP4HyS5dV01E+\nXm/tk1Y6attG/DFmzBgcPXoUAL+OQmh30StXrqC4uDjw95YtW/Dhhx8CAJ48eYKWlhZkZWWF1DGW\nY2G28h+GRWdvFhD2VIW8XaH0avRKI9GJrd6isjqRlBPuXkvRCVVOpDrh8kZ2D4YUFuDrw0dFlB1r\ntiFO5wdvrMftu3fh9XpFlB1PthEuXjsbFKejtm1og5b7WMyZMwdWqxVr167Fhx9+iHfffRelpaXY\nvHkzAKCurq7TVAkArFq1Ck1NTVi3bh1+8pOf4IMPPgg5DQLAYGeFtEOPTacoAoN47OF8/OkmrHt1\ndZC1FsagoaFB9ePflSE+bTCaaH1WiGfDXEXLs/5uv6LlycFYIxZeN+BqEXAqwnnIwZCaj+pErhOq\nV6Okjpj0oRp0qT0ffTyzI8e+wfSpUwSciliwDeV0UlNT0dDpWHa5OmK1peq0h0m1wfh9ZurqUKRg\nrLdCOD/ACR0+JvTPKaYXIDUf1YlcR2jOVA0dMemlaktNr9013r5zFxfKytE3Lxd5ubmq6YRHPzos\ny8Lv97c5WVrZhlid2LqXsa+jIjrZhltJjOVYWB2Az8w7F1E7Nl2JoUsxZVAddcqIB7rfh4vl5Vi1\nfGlEZchLo1+dSePH4/TZc5g8aaKqOsYklmxDXRidHBymJMaaCmEYwGwBWDOiZ2xK6GrldRtRxwh0\nvg+Vt26jubklSFpxZchPo1+d7OwsPG9owO69+1TVMSaxZBsUqRjLsfA4AWcT4KWnH1Io7Zw4dRqL\nF7wS7WrokoXz54HjuGhXgxLPMIyyHx1grKkQ0vG9ZgrFuHAch29OnMTjJzWYPXM6evRIj3aVdAkh\nBPX1z6NdDUo8E4dTIcZyLGwJvHPhdfMbZVEng2JQqh8/BgC8umpFlGuib7bu2In5c2ZHuxoUSkxh\nLMeCEH7RJqFDmxRjc+9+FfL79Y12NXRN1YMHsFqtyM4OvcsghRIJWp4VohXGcizi5th0CkU+hBA8\nePgIL0+cEO2q6Jq83FzU1j7Frj1fBc5OcTpdmDZlMnr16hnl2lHiBjoVEuMEPTZdiEiVPpfQAAAg\nAElEQVRfUxKbX6vXoeL/9UB1dLQsVxudS5evYNyY4vAJFa9L7NnGmOLRGFM8OvD3o+pqPHj0CNeu\nX0dDYyOSk5IxedIEOByOiGos/bpj2wbl6WhpG5RIMJZjEfTYdCEiNWCx+bVa5xH/rweqo6Nluerr\n3L13D9eu38Bra1ZFoS6xbxsJDge2bN+JDd9fj0EDB6CxsRFHvzmBVmcrkhKTMK1kMmw2m4ySldhQ\nTQ30pKNv25ANnQqJcfw+firE3z5i0dF7bf89krBghMsfKp1QfDA9NXXC/a6GTri0augIlRlKR23b\nEFumOB2LxYLCgkEiy6E22DVtSkoKfvaTHyM1NQUAkJKSgvlzZwNg0NTUiAOHDsPj8aJo5AgMHNBf\npk6ouse+DQYvM1Q6oXi1bYMiF2PtY+FrexuEtDsWHQ2JKBAWjHD5Q6UTig+mp6ZOuN/V0AmXVg0d\nMeWEK1NJ2xBbpjid3jk5qHrwQGQ51Aa7pmVZNuBUdI1LTk7GolfmY8XSxbh2/TqePKmRqSMUH832\nSVkbDF5mqHRC8WrbhkbE4T4WxnIsTFbAZAF/bHpHmDC/h4sXKktsOYxOdBhEptMxTm86Uu5RsHpJ\nKSdcWdHQ4X+/9t0NpKakoKamFoeOHOsQp6YNdowzhm0semU+jh4/AUL4c1geP64RSKsXGxRbjpHb\nJxWJQ8fCWFMhZgv/6bbGQoq3G4k3LbdsLXSkjBTI6QVoqcNIrIeaOkJlRXrf5NvG8GFDUH+yHgcO\nHe5wgqnaNtg1Lth9i4YNKmEb3a/H5XLj7r372FG6GwPy81FTW4vT584CAJKTkjFpwktISEjgUxMC\njhN72JkaNhjJfVFKR+t2I5QNRnH0Ik4wlmPh8wA+r8BbIV2NLBLay+pYplAY1VFPJ1Ravepody+n\nvDwJuX164979KlV1wn8ZIEy6SHWkosT18Dgcdvzf7/yFYOqGhkZ8c+IUPF4vAAKGYeD1+kAIhwXz\n5sFul7L4U4wNCoXp9V5qpaMj54GNv4kDYzkWfq+EY9PlItWDpjpUR1vtR9XVOPvtBaxZuVxVHWll\nqK0jpS7q6qSmpmDenFndwt1uN/bs248ERwLmzp6pwMZJkYwkREq86aiITqYvlCT+XKVQWOz8hzWj\n+zya1Icr1xjCzaFGmp7qRKYjtiwl02unc+FiGcrKrwg4FbH8zOJDx2azYfmSxRg3phj/8fEncDqd\novKJ15abT+o1aqWj1TOjSMVYjgVrAsxW/tPNm5Xq3cr1hqX2VuX2bqmOPB2xZSmZXhsdj8eDe1VV\nWDB/jsSy9P7M4ksnI6MH1q9bi81bt6O29qmE+knTEZ9P6jVqpaPVM1OZOFy8aSzHwuMEXM2ApzXa\nNaFQNOfgoSOYM3NGtKtBEYHZbMb6dWtx7MQJfHf9RrSrQ1GTOHQsjLXGghDQA8goRmXE8KG4dOUq\nPSMkRmAYBiuXLUVZ+SVs3bETZrMZLMsip1cvjO2wzTiFojeM5VjYEvg3Qnxeemw6xXD0zcvD6bPf\nghASlycqxiuji0ZhdNGowN9Xr32Hk6fPUAcxXojDt0Li74pCQciLD4ViQLxeb+CkTkpsMnzYUNTU\n1ka7GhSliMOpEGM5Fh4n4G4B/HS0gmI8CCHweDy4fqMi2lWhKAB1ECl6xViOBcui+3beFIoxYBgG\nP3jje3C73di2cxf9YophhhQWUgcxXqAjFjGOxQ44kgFbYrRrQqFEjeLRRZg8cSL++Nnn1LmIUQYX\nFqCisjLa1aAoAXUsYhy/H/C4+E/QDbIYGWFS0EqnazlytPWoI6SpNx3920Z2dhZmTJuK02fPqaoj\nrkwj2aAytsEvvo1tG4xPHQpgNMfC5+KPTid+BN8gK9zWsJFuF6uVTtdy5GjrUUdIU286sWEbuX16\n487de22jFtQG5REd23C5XLBZrarrSAuLRC9edGTAssp+dIA+aqEVJgtg6ridt5wejJwekB50guWN\npEcnpReghU6wfGJ7JpH2buX0gKJrGwvmzcGW7TsV1JGaVyvbkKITTdsQp/PthYsYN6Y4Ah2hPHpp\nnyLVkZo3mG1oBJ0KiXHMVn59hT2pLUBOD0ZOD0gPOsHyRtKjk9IL0EInWD6xPROpOl3/ieX0gKJr\nG2lpaeid0wsPHj5USEdqXq1sQ4qOErYhNb80nafPniEzMwPxYIOh9aJpGxS5GMux8HkAVwu/rTcA\n8T2HYCjRw1FDR2xeI+pE0rvqGhfK0ZCqrZVtdA+bNGECTp05h9DEk2107KGqfT2hypSn09raCo4L\n9oWstg3K/V+RkzfaOhpBRyxinMCx6V3/KcP1HIKhRA9HDR2xeY2oE0nvKlR6KTrRtI3uYQwDZPRI\n73DglRI6YvNGQ6djD1Xt6wlVpnQdQgi+3LYDSxctiFBHrg1G8r8SC7YhNo2CUMcixjHbAbONP+VU\nUU9cCmJ1ItWmOvJ0QmlrpROJtjyd6VOn4sg3xyXo6OmZxZuOsDYhBJ9+vhmLF7wCk6ljGxYfNqjf\nZ0aRirHOCjGZ+FWzfjPgaekSqVSvNRxKzD3K9bqpjjy01olEW54OyzJITkpCQ8NzpKamitDR0zOL\nN53ucJy/zamYr+DzESJ6NqjfZ6YujIZvchBC8N577+HGjRuwWq14//33kZeXF4i/dOkS/vZv/xYA\nkJmZib//+7+HxWIJmUcIY41YeFxtx6Z3dSoo2kJ7BXpkzqwZ2HfwkIoK9LnLgeM4/PGzz7Fk4Ssd\nnApK3KDhVMjBgwfh8XiwadMm/OQnP8HGjRs7xf/85z/Hhx9+iE8++QQlJSV49OhR2DxCGMuxIBzo\nsel6QPteASU8JpMJWZkZePz4iUoK9LnLYdvOXVi+ZBFSUlKiXRVKjHP+/HmUlJQAAIqKinDlypVA\n3J07d5CWloY//OEPWL9+PRoaGpCfnx8yTzCM5VhYHfzrpiYraO+JQunO9KklbWstKHrgflUVcnr1\nQnJycrSrQlELDUcsmpubO9mS2WwGx/Gd7fr6epSVlWH9+vX4wx/+gJMnT+L06dMh8wTDWI4FAOpQ\nUCjBYRgGA/rn49btO9GuCgXAydNn8fLECdGuBkVNNHQskpKS0NLyYikAx3Fg29Z4pKWloW/fvujf\nvz/MZjNKSkpw5coVJCcnB80TDGM5Fh4n4G6mx6ZTKCEYP25shzNEKNHi0JGjGD9ubLSrQYkjxowZ\ng6NHjwIAysrKUFhYGIjLy8tDa2srqqqqAPDTJgUFBSguLg6aJxjGeiuEYQCGpessKJQwzJhWgq8P\nH8WsGdOiXRVDcrGsHMnJyRjQPz/aVaGojYZvhcyZMwcnTpzA2rVrAQAbN25EaWkpnE4nVq9ejfff\nfx/vvPMOAKC4uBjTpk0DIaRbnnAwJMi5yRUVFQAgyjuJKQgB/D7A0xrtmlAouqb0q72YPHEi0tPT\nol0VQ7F77z6kp6XRKZAoUXGzEnAka/bd53//bUXLM/2Pf1e0PDkYayqE8wNeN7+1t+43yBKTXgkd\nPWxAE6lOOG0pOlK141dn4fx52HvgYATaerCN2LJBv98Pj8cj4FToyzb0oaOVbahMHO68aaypEK+L\nH60QRG8bZIlJr4SOHjagiVQnnLYUHana8avj9/ths1kj0NaDbcSWDd69dx8FAweqrhOcWNKJjw2y\n9OIMKImxRixMFoAVOjZdCCkPO5znG6nhiPWwI70esT0GKb0NJkiYFB25vU6x90ON3q1UnXB5w6VR\n3gbNZjMIIfD7/RHqSOkNqmGDQmFa2WAoupdps9ng8XhElEXbp+D5lWqfKHIxlmNhtgJ2oWPThZDi\nuYbzfCP1gsV62JFej9geg5TeBgkSJkVHaq+TCZFGDZ1QROOZKWeDs2dMxyebvoDP541Ap2u6UPdN\nDRsUClPSBhmBOHm2keBwwOlyhaibMjq0ferYRgSzDY2Iw6kQYzkWPi/gbuVfOQUgvccV7Hc5vRml\ndISQklcLna69ArV1ujYecnozUnRC1TMSHTFlq2uDqampWLV8KT7ZtBlPntSIyC+mjiREObFogwTd\ndeTZhsPhQGurU0QdpehEs30SW47W7ZPQMxNTpgqwrLIfHaCPWmiF38MfnU66eq9ivd1gv0vt6Sqp\nI4SUvFrodO0V6E1Hao9LqJejho6YstW3wYSEBLzx+lpcvnoNO3fvbpsaCZZfah2lppWrEy0bDJW/\ne7zdboPL3XXEIlKdaLZPkdRRalq5OsFsgyKXkI7FhQsXtKqHNpht/HQII3RsejuReMhSkOPxh+oF\nxLKOlPLV1gmVR2+2ESyP0joMGIbB7JnTMb2kBJu3bkf5pfDnBcjREc6jFx31bbD68WP06tkzRB69\n2WA0n5na7ZNGGG0qpLa2Vqt6aIPJzJ8XYrUjuFcaiYcsBTkef6heQCzrSClfbZ1QefRmG8HyKK3z\nIiwlJRlrV6+EycTisy++xMNHj1TR0ep69GaDV69dx/ChQ0Lk0ZsNRvOZqd0+aYTRHIupU6dqVQ9t\n8LoAVxPgpsemUyiRMGL4MKxdvRJ37t7D519uRXX142hXSSGi2zA7XU4kJCREtQ4USqSE3MfC4XBo\nVQ9t4Dj+Q6FQIoZhGEx5eRIIITh2/ASOnTiJGVNLkJ2dFe2qRUB059eDbIRMiWd0suBSSeLvikIR\nODbdgmj3TCiUeIFhGEwrmYI1K5fj6PET0a5OTMPoZCiboiFGmwqJOwI331iXTaFoAcMwGDZkMD77\n4ks8e1YX7erEHNe+u44+vXtHuxoUSsQY6xvW3Qq4mgGfG9Ee8qRQ4pHhw4Zi7eqVOHPuW1z77nq0\nqxNTfHfjBsYWj452NShaQ0csYhyGAZ0CoVDUhWEYvDJvDipv3452VWIKq9Ua7SpQokEcOhbGOoTM\n6gAsdnpsOoWiMnStgDQ8Hg8sZku0q0GhKIKxHAvOzzsVfh/QbTvcrn+HQ2p6JXXElBFNnVD5tNIR\nW4Ya+YygE74M4RccYtk21NO5dOUqCgsGRVi/SNIrqRPr7ZPG0LdCYhyvi/9wPnQ3LKn/hHLXaCih\nI6aMaOqEyqeVjtgy1MhnBJ3wZQgPWsSybaij09jYiNt37mJA/3yJ2tJ01MlnhPZJZeJwKsRYjkXg\n2PSuyH0YQvkYEXF61QmlzYQJ01pH7/fSqDovwpSbDolfGySEYOuOXVi1fJmqOt3DYlEnlLbatkGR\ngrGmQsxW/sNx/A6cAZT07kNtDat3nVDaam9/K1UnlHaooU4l76VWOqHQm44Y25A6DK53G5Q63P4i\nfNeer7Bk4QKwLNMtTih9d4xkg6G01bZBFdHJKIOSGGvEInBsevuW3qG83XDxjIj4UGEIEy+kIyVP\ntHSk3Be1dIgCOmKes9I6XcMiqZuYMCn1VdIGu963WLdBoesRbxs9eqSL0BZrg5HYW6S2EQs2GOqZ\nhaqbijCssh8dYKwRC7+nbeFmO6G83XDxkeZBmPhYzSPlvuhZR85z1konNmxQeHtqaoPt4YRwHaaL\nlH7OcspUypbV1okkj9xnRpGCPtwbrWifCmFMbQFyPNZwPUyhMCnetBidcGXrWUcoXq6O1GchRkes\nthBi66OVDrUNveq0trZi89btGDl8mIg8wXSEoDaonA1qBMso+9EBxhqxMFn4T2CNhRyPNZynLhQW\niTctp5egZx2heLk6Up+FGB2x2kKIrY9WOtG1jRdTx/FiG8ro3Lt/H2e/vYDlSxbBYrGIyBNMRwhq\ng8q1Txqhk+kLJTGWY+F1A34vv59FJxh0NyyhsK6ISROOWNERW4dYuZ5IdNTQpjYYnzoAIbwzUV//\nHABwsfwSfvDG9yS8NUNtQ3sdSiQYy7Hg/AJOBRDemw2GEl5urOiIrUOsXE8kOmpox5cNer1emE1d\nm5fYvR6pZTx5UoNTZ88G/s7v2xdZWZkghGD5ksUSX8WNL9swho4E4vCtEGM5FlYH4Dd32H0zisNf\nFEocc+9+Ffr1zYt2NTTH4/Fg38Gv4bA7sHTRQrq1OSU8cbjzprEcC4ZpW2NBAPjCJqdQKPKovHUb\nM6aVRLsamuByubD3wEEwDAOL2YJpUyYjJSUl2tWiUKKGsRwLdyu/xoJCoaiKx+uBzWaLdjVUp6z8\nEm7euo1lixd2WIhJoUggDke14m8MJhT02HQKhaIA/FbcO2EymbB6xTLqVFAoHTDWiEX7sek+D38Y\nGYVCochg5+49mDxxInr2zI52VSixDn3dNMYhhN/Wm/NDmVeXooVWddfqFTCl6kLRDj09d23r8s2J\nkxhcUECdiqijJ9uIADoVEuN4nIDX2bbOQufGFhKt6q6nV7Ni+XnFI8Gfh9vths2q1PoK/dlgTW0t\nhgwu1EiTEhw92QalI8YasWBNAOH4nTdB+L/b11xwfj6MYfkwhuHTEu5FGMCnIRz/N9u+NXh7mUzb\nq0NtXnInHfDhYnQY8KMr7WEMy//NkCA6/hfX11WHZQEiQQekQ907XqNMnfZ1LZ3CVNAB2sIErocI\nPTMhHXR4Zh10pD4zQR2FbEOyDYa4l1JtUOQzq3lah569cl7UIaRtaGCDoWxDjE57p5fjUFtbi5yc\n3gBjEnffIrINFoG+X0S2obANCl2P3PZJJRsUbRtCNtixPdAC+rppjGOx8R/SZpwd57ZChbUbfiCc\nExnW5i13C9ORjiRtnerIvpfR1pGgHUM2+Ph5E3L75gOOZHE6MWSDlhQfPEwV4EiSpq3U9cS4bUjW\niYZt2BKgKXE4FWIsx6IdobdDxIYBnY00ZJhQXp3pSNKmOsrqyNQOqqMPG6ytrUVxcXFcPrO09B5o\naGhQXYe2T3K0VdCJMwgheO+993Djxg1YrVa8//77yMvrvpHdz3/+c6SlpeGdd94BAKxYsQJJSbwz\nnZubiw8++CCkjjEdCwqFohputxtmc3w2LT6fL26vjRIlNHwr5ODBg/B4PNi0aRPKy8uxceNG/PrX\nv+6UZtOmTaioqMD48eMB8LvJAsBHH30kWif+JncoFErU8Pl8IO1D0nFIRUUFCgoKol0NSjyh4bHp\n58+fR0kJvyNuUVERrly50in+4sWLuHz5MtauXRsIu379OlpbW7Fhwwa8+eabKC8vD39JMm4DhUKh\nCHLw4EHMnj072tVQjatXr1LHghKzNDc3Izk5OfC32WwGx3EA+CnMf/mXf8HPf/7zTp0Du92ODRs2\n4He/+x3ee+89/PSnPw3kCQYd06NQKIrR2toal+dkEEJQWlqKIUOGgB4sRlEUDadCkpKS0NLSEvib\n4ziwbW+l7N27F8+fP8fbb7+N2tpauN1uDBgwAAsWLEC/fv0AAPn5+UhLS0NtbS169uwZVIc6FhQK\nRTHidWvrL7/8ElOnTg3ZmFIostDQUR0zZgwOHz6M+fPno6ysDIWFL/ZjWb9+PdavXw8A2LZtG+7c\nuYNly5bhs88+Q0VFBX7xi1/gyZMnaGlpQVZWVkgd6lhQKBRKCC5evIjhw4dTp4IS88yZMwcnTpwI\nrKHYuHEjSktL4XQ6sXr1asE8q1atwrvvvot169aBZVl88MEHgVGOYFDHgkKhKEa4uddYw+v1oqKi\nAq+++mq0q0KJVzScCmEYBr/85S87hfXv//+3d2dBUZ1pH8D/pzdobGgSQQRBFkdcwAjEJbijorjh\nxIiGRB0Ta3KRq6mamUpNVarGuVByYU2lajJeTHIx5YyOuEy5JKMoiWBEg4qCgAqC7Cgjq3RD7+e7\nyGePKM166NM0/19VV9l9+n3Pc8DmPP2u0a+9791333X+W61W49ChQ8M6DxMLIpKEw+GA3W6XOwxJ\nnT9/Hunp6XKHQd5skJkc4xFnhRCRJIqKirBw4UK5w5DMo0ePEBISAq1WK3coROMKWyyISBJ+fn7O\nxXTGu/LycjQ0NCAtLU3uUMjbeeEsI7ZYEJEkfvGLX6CqqkruMEatoKAAbW1tTCrIPV5ssCbVwwN4\nRhRENO75+PjAbDbLHcaImc1mHDt2DEFBQVixYoXc4RCNW+wKISLJjOflvHNycvDee+/Bx8dH7lBo\nIvHCwZtMLIhIEl1dXX2WCx5PrFYrHA4HkwpyPw/pvpCS910REcni+vXrWLJkidxhDJvD4cCxY8ew\nbt06uUMh8gpssSAiSZjNZvj6+soaw8t7HwyF3W7HkSNHkJGRAT8/vzGMjMgFzgohInpdT0+PR+wT\n8s9//hMXL14c8vvPnDmDHTt2QKfTjWFURAPwwlkhbLEgolH7/vvvPaIr4cXmSKdPn4ZarYbZbEZK\nSgqCgoL6vK+lpQVXr15FXFwcJk2aJEeoRF6LiQURjYooijCbzR4x8HHDhg24desWjEYjNm3aBEEQ\nkJeXh+7ubud7bDYbgoKCsH37dm6BTvLjrBAior4KCgqwdOlSucNwWrhwIebOnYsjR47go48+wurV\nq+UOicg1D+m+kJL3XRERudXTp08RGhoqdxh9TJo0CZMnT5Y7DKIJiYkFEY1Ye3u7x97ARVFEeXm5\n3GEQDUwQpH14ACYWRDRiV69e9djlr7du3Yq7d+963VbuRJ6OYyyIaER6enpgt9uhVCrlDsUljUbj\n0fERYRjrrowX3ndFRDTmrFYr/vKXv2DNmjVyh+JSaWkpYmJi5A6DaGDsCiEiAtRqNebOnYvAwEC5\nQ+nX8+fPUVlZiQULFsgdCtGEw64QIvIqlZWVKCgowK9+9Su5QyEanBdON2ViQUQj4imDIm02G5qa\nmnD37l04HA7Exsbio48+kjssoqHxkO4LKTGxIKIREQRh2Jt+jZTBYMBf//pXzJkz57VjKpUKoaGh\n2LJlCwdqEnkAJhZENCJarRYdHR1uWcdCp9MhNjYW6enpY34uIrfywlkhTCyIaNi6u7vR09Pj1sWx\n3NEyQuR2XtgVwk8qEQ1bXl4etmzZ4rbzdXZ2IiAgwG3nI6KRY4sFEQ2bw+Fw63gGvV6Pp0+fuu18\nRG7DWSFERGPD4XDg6NGj8PPzg0KhQFJSEp49e4YnT57AYDBg1apVcodIJD0v7AphYkFEHkEQBOj1\neqSnp8Nut+PevXsICwtDUlISx1cQjSNMLIhoWJ48eYKpU6dKXq/w0jc3pVKJxMREyc9B5HHYFUJE\nE11JSQlSUlLwn//8BwCwevVq+Pr6SlK3r68vzp07B41Gg9raWnzyySdsrSDvpvC+rhB+YoloWMxm\nM3x8fGC1WpGcnIzvv/9esrrXrVuHdevWYc6cOdDpdLh3755kdRORe7DFgoiG7dmzZwgKCkJpaSmS\nk5Mlq9dms+Hs2bOYPHkyMjIy4OPjI1ndRB7JC7tCvO+KiGhM+fj44OzZs1iwYAHa29vx5ptvSlJv\nV1cXjh49ii1btmDt2rVMKmhi8MJt09liQUTDkpaWNib1Xr9+HZmZmdBoNGNSP9FEJ4oi9u/fj4qK\nCmg0Ghw4cAARERHO4zk5Ofj666+hUCiwefNm7NmzZ9Ay/WFiQURDZrPZ8Le//Q0RERFITEyUbNAm\nAFitViYVNPG4sSskNzcXFosFx48fR0lJCbKysnD48GEAP68j8+c//xn//ve/odVqsXHjRqSnp+PW\nrVsuy7jCxIKIhuzBgwfYsGEDwsPDUVBQgGXLlklWt9VqlawuovFCcGP3RVFREZYvXw4AmD9/PsrK\nypzHFAoFLly4AIVCgba2NoiiCLVaPWAZV5hYENGQ1dTUYMuWLRAEYdQrYYqiiNzcXJhMJtjt9kGb\nV4lodAwGA/z9/Z3PVSoVHA6Hc0q3QqHA5cuX8ac//QkpKSnQarWDlukPEwsiGjJRFCX5htXQ0ICr\nV69iw4YNkg3+JBqX3NgVotPpYDQanc/7SxBSU1ORmpqKzz77DGfOnIG/v/+gZV7FWSFENCStra2S\nLVZVWFiIDz/8kEkFkaCQ9jGApKQk5OfnAwCKi4sRGxvrPGYwGLB7925YLBYAgFarde7Z46qMK2yx\nIKJBNTY24saNG9i+ffuo6+ru7uZUUiIZpKamoqCgAO+//z4AICsrC99++y16e3uRkZGB9PR07Nq1\nC2q1GrNmzcLWrVsBANeuXetTZjCCKIpifwcqKysBYEjZCRF5r97eXnz++efYs2cP5s6dC7VaPar6\nRFHEhQsXMHnyZCxevFiiKImk4e57n+Pmt5LWp1i0WdL6RhSD3AEQkWfTarU4dOgQ9Ho9zp8/P6Rv\nLAMRBAEbN25EQEAAsrOzcenSJbS2tkoULdE448auEHfxjCiIyKMJggCTyQSr1Yrf/e53ktQ5Z84c\n7Ny5E8uWLcPRo0clqZOI5McxFkQ0qPr6etTV1WHnzp2S1+3r64vp06dLXi/RuOAhy3BLiYkFEQ2q\nsLBQkoGbr6qrq8O1a9ewbt06yesmInkwsSCiAVksFvj4+Ei6QmBnZycuXryI6OhofPjhh5LVSzTu\neMi4CCkxsSCiASmVSiiVSknrzMnJwY4dOyRbF4No3PLCrhB+qoloQEqlEna7XbL6Hj9+jKioKCYV\nRF6Kn2wiGpRU3SANDQ348ccfuX4F0QteON2UXSFENCgX6+gNWVtbG3JychAdHY09e/ZIFBWRF1B4\nX1cIEwsiGpRWq0VTUxOmTZs27LKiKOLcuXPYu3evW7eIJiJ5eEa7CRF5tNTUVOTl5Y2orCAICAwM\nHJOk4uWxH2azGTk5OZKOByEac+wKIaKJqKenB4GBgXKH4WQymZCTkwObzQaFQgFRFGG327F69Wqc\nPn0ac+bMwbx58+QOk2hwXtiK5xnpDRF5NJvNNqopp/Hx8fjhhx8kieXx48f45ptvsH79ekyfPh16\nvR7btm3Du+++i/r6epjNZo9KgogmGrZYENGgAgICAAB3795FYmLikMs9efIEhYWFUCqVqKysRFNT\nE3bv3j2qWGJiYhAdHY2zZ89i4cKFCAkJwalTp6DVajFv3jzs2rWLYzlo/PCQ7gspcdt0Ihqy8vJy\n3L9/H1OmTMGKFSv6vYGLooiioiJUVFSgtrYWs2fPhlqthiAI2LJliwxREw2d22JFASsAABAjSURB\nVLdNL/9R0voUccslrW8k2GJBREN2584dFBcXY86cObhz5w42b96MmTNn9nnP5cuXERERAZPJhN//\n/vfQaDQAgMbGRly6dIn7ghB5OSYWRDRku3fvxuLFi3Hv3j0kJibi1KlTUKvV2Lx5M2bNmuXcXr2i\nogK7du1yJhUAEB4ejurqatTX13M3U6IXvLArhIkFEQ1LbGwspkyZgjNnzuCTTz5BS0sLcnNzceTI\nEeh0OthsNmzatAk+Pj6vlV25ciVOnDiB9vZ2JCQkyBA9kYfxwqXtOcaCiEZEFEXk5uais7MTaWlp\n8Pf3R3t7O3p7ewddSKuyshL37t3DlClTkJycDLVa7aaoiQbm9jEWD29IWp9idrKk9Y0EWyyIaEQE\nQUBqaipsNhsuX74Mg8GApUuXDml1ztjYWMTGxuK///0vLl++DKvVCpPJhLi4OMTHx7sheiLP4I0z\nmJhYENGoqFQqbNiwAaIo4saNG/jpp5+gVCohCAISEhL6HU/R2tqK7OxsREZGIioqCt3d3Xjw4AFm\nz54twxUQyYhjLIiI+icIApYsWeJ8Looibt26hVu3bkGtVkOhUECj0cBgMMDX1xeffvopurq60N7e\njpCQECxatGhUi3ARkWdgYkFEY0IQBCxatAiLFi0CADgcDphMJvj5+TnfExgYyFUyaWJjVwgR0cgo\nFIo+SQURwSu7QrzvioiIiEg2bLEgIiKSC7tCiIiISDJeuECW910RERERyYYtFkRERHJhVwgRERFJ\nhrNCiIiIiFxjiwUREZFc2BVCRERE0vG+xIJdIURERCQZtlgQERHJxY1dIaIoYv/+/aioqIBGo8GB\nAwcQERHR5z29vb34+OOPcfDgQURHRwMAtm3bBp1OBwAIDw/HwYMHBzwPEwsiIqIJIDc3FxaLBceP\nH0dJSQmysrJw+PBh5/GysjL88Y9/REtLi/M1i8UCADhy5MiQz8OuECIiIrkIgrSPARQVFWH58uUA\ngPnz56OsrKzPcavVisOHDyMmJsb52sOHD9HT04N9+/Zh7969KCkpGfSS2GJBREQkG/d1hRgMBvj7\n+zufq1QqOBwOKP5/WfHExEQAP3eZvODr64t9+/YhIyMDtbW1+PWvf42cnBxnmf4wsSAiIpoAdDod\njEaj8/nLSYUrUVFRiIyMdP47MDAQz549Q0hIiMsy7AohIiKSixu7QpKSkpCfnw8AKC4uRmxs7KDh\nnT59Gl988QUAoKWlBUajEcHBwQOWYYsFEXkNu92O2tpaKJVKREVFyR0O0eDcuIxFamoqCgoK8P77\n7wMAsrKy8O2336K3txcZGRn/C+mlBGX79u34wx/+gA8++AAKhQIHDx4ctJVDEF/uTHlJZWUlAAwp\noyEiklNbWxtyc3Oh1WoRExMDs9mMwsJCfPrpp3KHRuOMu+99YnOFpPUJYbMkrW8k2GJBRONOY2Mj\nSkpKYLfbYbPZ8OabbyIjIwM1NTUoLS2FxWLBzp075Q6TaAi8b+VNJhZENC5YrVZcvHgRT548QX19\nPRITE6FWq6FSqdDV1YXTp09j5syZ2Lp1a5+mXCKP5oX/V5lYEJFHam5uxo0bN6BSqSAIAq5du4Z5\n8+Zh9uzZ2LdvH5RKpdwhElE/mFgQkUdxOBw4deoUwsLCsG3bNgiCgJMnT+I3v/kNwsLC5A6PSFps\nsSAiGjt1dXXIzc1FRkYGAgICnK+r1WomFeSlmFgQEUnK4XAgLy8PHR0diIyMxMcff/zaGAmr1Yq6\nujrnQj1E5LmYWBCRbAoLC1FTU4O1a9ciKCioz7Hy8nLU1tbCbrdDqVSisbGRiQV5H3aFEBGNXk1N\nDQoLC7Fw4UIsXry4z7Gmpibk5+cjMTERaWlpHKRJXo6JBRHRqJSXl6O5udm5+t8LFosF586dw9Sp\nU5GZmckpo0TjFBMLInKrqqoqbN68uc9rBoMBp06dQmZmJnx8fGSKjEgGXphAcxMyInKrFStW4MqV\nK31eKywsxPr165lU0MTjxk3I3IWJBRG5lUajgdVq7fPa6tWrkZeXh+rqapmiIiKpsCuEiCRlMpnw\n8OFD2Gw2LFiwoM8xi8WCEydOYPfu3X1eFwQBmZmZKCwsRGlpKQRBwLJlyzB58mR3hk4kA89oZZAS\nEwsiksSLFTMDAgIwd+5cWCwWZGdnY8eOHRAEAc+ePcPFixfxwQcfQKXq/0/Pixkidrsd165dQ0tL\nC1atWoUpU6a481KI3MYbBykzsSAiSZw/fx7r16+HXq93vubv748LFy5g48aNKCgoeK2lwhWlUomV\nK1dCFEVkZ2cjLS0NgYGBYxU6EUmIYyyISBIKhaJPUgEAISEhCA8Px/Xr1wEAoigOq05BELBjxw58\n9913ksVJ5FE4eJOIqH+ukoa33noLVqsV06ZNG1GCoFAokJycjDNnzgw7MSHyfILED/kxsSAiSZhM\nJpfHVq5cicrKSoSGhuLOnTvDrjsmJgZLly7FsWPHRhMieblHjx7h4cOH6OjoYBIqI46xIKJhqa6u\nRllZGQRBcD6MRiOWLVs2YLl58+ZBp9OhpqYG1dXVmDFjxrDOGxwcjOXLl+PmzZtYtGjRaC6BxhlR\nFFFUVITm5mYIggCFQoF33nmnz6yh8+fPIzQ0FHq9HmVlZaiqqsKOHTvg5+cHQRBgMplQU1OD2tpa\n53TnlwdOOhwOxMXFuf3aPKX7QkpMLIgG0N7ejpKSEgQHByM8PBx6vd4rR3EPxU8//YTm5mbExMQg\nPT192D8Hs9kMvV6PNWvW4OjRo4iKihr2PiDTp09HSUnJsMrQ+Pbo0SPcvn0bS5YscU5fttvtyMnJ\ngdlsds4wEgTBeXzmzJmIj49HYWEhenp64HA44Ovri6ioKKxZswYajabfc126dAmPHj1Camqqey7u\n58Dddy43YWJB5EJNTQ2++eYbfPbZZ2htbUVpaSk6OjqcN1RBEJzNrS83uxoMBmzcuNHrZjE8ffoU\niYmJiI6Odr5mNBrR0NCAhoYGzJgxAzExMa+Vs9vtaG5uRlVVFRYuXAgAWLBgAR48eID4+Phhx9HT\n0zPyi6BxQxRFXLlyBTabDZmZmX2OKZVKbNy4ccDyb7zxBlavXj2sc65btw5RUVHDDZVeIYguOqIq\nKysBALGxsW4NiEhONputzxoLjY2NuHnzJpRKpbPZfzCiKOLChQs4dOgQJk2aNKp4WltbX9tOXC6i\nKOLu3buoq6tz/oy0Wi2mTZuGL7/8EmvXroWvr+9rfdsqlQqhoaGIj4+HWq2G1WrFkSNHsHfv3hHt\nXFpVVYWOjg5nkkLepaGhAUVFRbBarUhJSXH7/3+33/s6nkpb3xtTpa1vBJhYEL3kq6++QkREhDOJ\nePHxeJFQvPpxmT9/PiIjIyWPw+FwIDs7G2+88QY6OzuRkpKCkJAQyc/jDqIo4tmzZygpKUFPTw/s\ndjvS0tLg5+c34jr/9a9/vfYtlsYfm82Ghw8fOpdyF0UR06ZNw9tvvw2FQp65BUwsRo+JBQ1JVVUV\nysrKoNFo8Pbbbw94kzMajSgqKkJsbCxCQkLG1ZiEtrY2FBcXY82aNYO+1+FwoLi4GPX19VCpVNi0\naZPLa7VYLHj8+DFqamr6DBxzOBwAgNDQUAQEBKCrqwtdXV1oamrCtm3boNfrIYoirl+/jvb2doii\n2CfpsVgs8Pf3x5o1a4b87b+pqQl5eXnQ6XRISUlBQEAAgJ//yNtsNvj6+g6pHgDo7e3Fo0eP0NTU\nBJvN1ufYy39agoODnYM3pXD79m3o9XrMnDlTkvrIfcxmMy5dugS73Q61Wo1Zs2YhJiZGtkTiVW6/\n93W2SFtfoPxfQJhY0KB6enrw5ZdfIi4uDhaLBffv34fNZkNQUBCmTp2KlJSUPksuf/3115g/fz6A\nn/vlX/7m/6K+goICfP7550P6Fi6KIsrKyjBp0qR++/CldvLkSWzYsGFYN8G2tjZcuXLFuTvniwTg\nxb81Gg2io6MRHR3d78Cx5uZmGAwG6PV66PX6Yd3cOzs78eOPPzqfv3puAIiIiEB4eDiuXr0KvV6P\ntWvXwmq1Ij8/H729vQB+7rdWKpUwmUwQRRFTp07FO++80+dcLS0tKC4udk4t9fX1xaxZsxAWFuZy\nQNxYOHHiBH75y1+69Zw0ekajEdnZ2cjMzIRWq5U7nH65/d7XJXFioWdiQeOQyWRCW1sb2tra8OTJ\nE+Tl5WH//v19bqr37t1DdXU11Gq1s5zD4YAoivDx8cGqVatw//59NDc3O48JgoDIyEhERESgtrYW\njY2NzjLz5s1DV1cXKioqsG3btmHdeIfLbrfj3Llzzlj1ej3Cw8PH7aAuURTR2NiI2tpaJCcnu9yn\n41X19fW4ffu283coiiKCg4ORkJAg203BbDbj7NmziI+Px9y5c2WJgUautrYWd+/ehVKpxPTp05GQ\nkCB3SK9hYjF6TCy8gNlsRmlpKZqampyv9dck/2rLgavXXTXnuyr/qpe/Mb/6XBRFOBwOqNVqJCQk\nIDQ01NkE6nA4UF9fj4aGBkRHRyMsLOy15lGr1YqTJ08iLi4Os2fPxvXr19HZ2QkfHx8sW7bM2awv\nFbvdjufPn6OyshL19fVIT093JlA09urq6lBeXg6bzQZRFGG327Fp0yb+Dsaxzs5OfPfdd1ixYgUi\nIiLkDuc17k8s/ittfXr5N+wbMLGorKxkYuEhzGYzOjs70dHRgba2NmdzNQBnP+V4G88wGtXV1Whs\nbERCQgL0ej3MZjPu3LkDg8EAhULh/DnodDrEx8f3O1DQarWiubnZueiOWq2GRqOBn58fQkJCMGnS\npD4/zxd9wzNmzOC35TEmiiLy8/Oh0+nw1ltvsctjnOvp6UFhYSGsVisCAgKQlJTksb/TmpoaREdH\nu+/e9/yZtPUFBEtb3wi4TCyA/2VuREREE8WMGTNGNBV6RCZaYkFERERjqLtV2vr85V/3hitvEhER\nycb7uq89Y+IwEREReQW2WBAREcnFCwfcM7EgIiKSixsTC1EUsX//flRUVECj0eDAgQN9pvz+8MMP\nOHz4MFQqFd577z1kZGQMWqY/7AohIiKaAHJzc2GxWHD8+HH89re/RVZWlvOYzWbDF198gb///e/4\nxz/+gezsbLS3tw9YxhW2WBAREcnGfS0WRUVFWL58OYCfN1AsKytzHquurkZkZKRzK4MFCxbg5s2b\nKC4udlnGFSYWREREcnFjV4jBYIC/v7/zuUqlgsPhgEKheO2Yn58furu7YTQaXZZxhYkFERGRXPz0\nbjuVTqeD0Wh0Pn85QdDpdDAYDM5jRqMRer1+wDKucIwFERHRBJCUlIT8/HwAQHFxcZ9ly2fMmIG6\nujo8f/4cFosFt2/fRkJCAhITE12WcYUrbxIREU0AL8/wAICsrCyUl5ejt7cXGRkZyMvLw1dffQVR\nFLF9+3ZkZmb2WyY6OnrA8zCxICIiIsmwK4SIiIgkw8SCiIiIJMPEgoiIiCTDxIKIiIgkw8SCiIiI\nJMPEgoiIiCTDxIKIiIgkw8SCiIiIJPN/3KmppvlwnF8AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x587c87490>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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CEyZM6OKKMBgMXL58mS+//JKmpiYEQSA0NJRly5bZ1a8vSRIHDhxg//79Vj9gJEkiIyOD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\nMwwWREREFDMMFkRERBQzDBZEREQUM/8D/T0jQGse+9cAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x59042ecd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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esHnzZg4cOCDPAQuCIM+nxMXFMWPGjG4refDgAUVFRfJnURRlR8yXb9xHjx5x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\nIiKKCEMEERERRYQhgoiIiCLyP49MvYZ+D3P+AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x594928a50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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aa+ONN97oU/p3dnY2mZmZrFq1qk0ti5qaGs6dO8fYsWNZunSpdl5ISkrCbDaz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\nLIiIiEgyTCyIiIhIMv8//cbxthKiiUwAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x528d6d4d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for hashtag in popularHashtagsList:\n",
+    "    createHashtagHeatmap(hashtag)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our Thoughts on this Visualization**\n",
+    "\n",
+    "It becomes immediately obvious that certain locations tend to favor certain hashtags - in example, STL appears only to be used within Ferguson and Missouri, whereas Ferguson, as a more general hashtag, it broadly used. Further, the NMOS14 and MediaBlackout flags have clear aggregations within the US, potentially implying geo-located communities spreading information. \n",
+    "\n",
+    "To further our understanding, aggregating hashtags explicitly in support of Mike Brown or the officer Darren Wilson, could also yield more information about the relationship between hashtag users and their perceptions - beyond that of where they may be located."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Hashtags by Alignment\n",
+    "We start by creating alignment dataframes of different hashtags, then plot the total yield of tweets in these alignments in order to determine whether conclusions can be drawn about the distinctive populations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "mikeBrown = ['MIKEBROWN', 'HANDSUPDONTSHOOT','JUSTICEFORMIKEBROWN',\n",
+    "             'DONTSHOOT','POLICESTATE','RIPMIKEBROWN',\n",
+    "             'IFTHEYGUNNEDMEDOWN']\n",
+    "darrenWilson = ['TCOT', 'DARRENWILSON', 'UNITEBLUE','TEAPARTY',\n",
+    "                'SUPPORTDARENWILSON', 'GOP']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "mikeBrownDf = (shootingHashtagsDf[shootingHashtagsDf.hashtag.isin(mikeBrown)]\n",
+    "               .set_index('createdDatetime')\n",
+    "               .groupby(pd.TimeGrouper('Min'))\n",
+    "               .count()\n",
+    "               .reset_index())\n",
+    "darrenWilsonDf = (shootingHashtagsDf[shootingHashtagsDf.hashtag.isin(darrenWilson)]\n",
+    "                  .set_index('createdDatetime')\n",
+    "                  .groupby(pd.TimeGrouper('Min'))\n",
+    "                  .count()\n",
+    "                  .reset_index())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>384</td>\n",
+       "      <td>384</td>\n",
+       "      <td>384</td>\n",
+       "      <td>384</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-14 00:01:00</td>\n",
+       "      <td>284</td>\n",
+       "      <td>284</td>\n",
+       "      <td>284</td>\n",
+       "      <td>284</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-14 00:02:00</td>\n",
+       "      <td>220</td>\n",
+       "      <td>220</td>\n",
+       "      <td>220</td>\n",
+       "      <td>220</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-14 00:03:00</td>\n",
+       "      <td>236</td>\n",
+       "      <td>236</td>\n",
+       "      <td>236</td>\n",
+       "      <td>236</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-14 00:04:00</td>\n",
+       "      <td>290</td>\n",
+       "      <td>290</td>\n",
+       "      <td>290</td>\n",
+       "      <td>290</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-14 00:05:00</td>\n",
+       "      <td>348</td>\n",
+       "      <td>348</td>\n",
+       "      <td>348</td>\n",
+       "      <td>348</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-14 00:06:00</td>\n",
+       "      <td>270</td>\n",
+       "      <td>270</td>\n",
+       "      <td>270</td>\n",
+       "      <td>270</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-14 00:07:00</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-14 00:08:00</td>\n",
+       "      <td>274</td>\n",
+       "      <td>274</td>\n",
+       "      <td>274</td>\n",
+       "      <td>274</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-14 00:09:00</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      createdDatetime  date  hashtag  hour  tweetId  x  y\n",
+       "0 2014-08-14 00:00:00   384      384   384      384  2  2\n",
+       "1 2014-08-14 00:01:00   284      284   284      284  4  4\n",
+       "2 2014-08-14 00:02:00   220      220   220      220  0  0\n",
+       "3 2014-08-14 00:03:00   236      236   236      236  2  2\n",
+       "4 2014-08-14 00:04:00   290      290   290      290  0  0\n",
+       "5 2014-08-14 00:05:00   348      348   348      348  0  0\n",
+       "6 2014-08-14 00:06:00   270      270   270      270  2  2\n",
+       "7 2014-08-14 00:07:00   260      260   260      260  2  2\n",
+       "8 2014-08-14 00:08:00   274      274   274      274  0  0\n",
+       "9 2014-08-14 00:09:00   260      260   260      260  2  2"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mikeBrownDf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-14 00:01:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-14 00:02:00</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-14 00:03:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-14 00:04:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-14 00:05:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-14 00:06:00</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-14 00:07:00</td>\n",
+       "      <td>20</td>\n",
+       "      <td>20</td>\n",
+       "      <td>20</td>\n",
+       "      <td>20</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-14 00:08:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-14 00:09:00</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      createdDatetime  date  hashtag  hour  tweetId  x  y\n",
+       "0 2014-08-14 00:00:00     2        2     2        2  0  0\n",
+       "1 2014-08-14 00:01:00     6        6     6        6  0  0\n",
+       "2 2014-08-14 00:02:00    10       10    10       10  0  0\n",
+       "3 2014-08-14 00:03:00     6        6     6        6  0  0\n",
+       "4 2014-08-14 00:04:00     6        6     6        6  0  0\n",
+       "5 2014-08-14 00:05:00     6        6     6        6  0  0\n",
+       "6 2014-08-14 00:06:00    10       10    10       10  0  0\n",
+       "7 2014-08-14 00:07:00    20       20    20       20  0  0\n",
+       "8 2014-08-14 00:08:00     6        6     6        6  0  0\n",
+       "9 2014-08-14 00:09:00    10       10    10       10  0  0"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "darrenWilsonDf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x408960ad0>"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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2traAdkRTf39/JkyYgIODg26dmJiYdKOoOjo6Eh1tug4WBbbqpEQJR5RKW0uH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\nQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x407f4aa10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "\n",
+    "mikeBrownDf.plot(kind='line', x='createdDatetime', y='hashtag', label='Mike Brown Supporters', ax=ax)\n",
+    "darrenWilsonDf.plot(kind='line', x='createdDatetime', y='hashtag', ax = ax, secondary_y=True, label='Darren Wilson Supporters')\n",
+    "plt.title('Number of tweets by Users')\n",
+    "\n",
+    "ax.set_ylabel('Count of twets (Mike Brown Supporters)', color='b')\n",
+    "ax.right_ax.set_ylabel('Count of tweets (Darren Wilson Supporters)', color='g')\n",
+    "\n",
+    "plt.xlabel('Time')\n",
+    "plt.ylabel('Number of Tweets over Time')\n",
+    "plt.title('Hashtag useage over Time')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our Thoughts on this Visualization**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are certainly similar ebbs and peaks in the data, but what is immediately striking is the gain of Darren Wilson aligned tweets with time, as compared to the ebb of Mike Brown aligned tweets. Several relationships with more time could be explored here through detailed network analysis including: did people change their minds as more information was aligned? Did Mike Brown aligned tweeters begin to aggresively parody Darren Wilson aligned tweeters?\n",
+    "\n",
+    "A visualization like this of the aggregated, sorted data provides a powerful way of framing the different sides of an 'argument' being played out over social media on a grand scale"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Conclusions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "The union of spatial and temporal data visualization, coupled with contextual information, we find a compelling way of presenting large amounts of data. Further, aggregation of data metrics based upon research yields opportunity to tell compelling stories and reduce the complexity of the visualization. Opportunities that we were not able to implement - namely selecting other axes to which to aggregate data - may be worthwhile for a person interested in pursuing this particular project in the future. There may also be filtering techniques for the data that could also yield more clean or parseable visualizations. \n",
+    "\n",
+    "On the whole, it is clear that making compelling visualizations is a matter of creativity. The opportunity to build interactive graphs is truly an area in which we see strong potential for complex data being shown in a way that a human can interact with fully. \n",
+    "\n",
+    "When working with large datasets, it is also critical to understand how long it will take to collect and plot. We went through many iterations of our functions simply so that the time to run each was within a reasonable period of time (on the order of tens of minutes). Using ipython notebooks proved useful for this aspect, as once the data was read in, there was no need to do it again each time something was to be built.\n",
+    "\n",
+    "As for understanding social media and it's role in activism, there are clearly some relationships between present activism (physically acting) and virtual activism (voicing support remotely) - namely in observed patterns in Ferguson and Los Angeles, a site of protest during the events. What we were unable to capture here was whether one incited or caused the other, or if the relationship between the media and the actions was primarily active reporting/information spread (reactionary to events). Further work on this project could ask this question and dive more deeply into classifying tweets as action based or support based, triggering or reporting, etc. As a first pass, we are pleased with what these visualizations, and the others we developed along the way through our hypotheses, tell us about the data and have found them compelling with potential to improve."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/.ipynb_checkpoints/Hashtags_Over_Time-checkpoint.ipynb b/.ipynb_checkpoints/Hashtags_Over_Time-checkpoint.ipynb
new file mode 100644
index 0000000..5973f93
--- /dev/null
+++ b/.ipynb_checkpoints/Hashtags_Over_Time-checkpoint.ipynb
@@ -0,0 +1,459 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Mapping Twitter Data\n",
+    "This notebook provides the basis for developing spatial representations of a variety of interesting data that is presented in the Ferguson Twitter dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "% matplotlib inline\n",
+    "import json\n",
+    "import time\n",
+    "import pandas as pd\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets\n",
+    "import matplotlib.cm as cm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's begin with the data. We have two datasets. The first is data from the two weeks following the initial shooting. The second is data from the two weeks following the indictment. Twitter has provided an extensive amount of data for us, and we have developed a cleaning mechanism which can be observed in a seperate script. The data is placed in a data frame:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def ReadAndAggregate(linesAtATime,filepath,aggregationFunction):\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of lines\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print i\n",
+    "                df = pd.DataFrame(data=data)\n",
+    "#                 print df.info()\n",
+    "                #First time running through\n",
+    "                if (i == linesAtATime):\n",
+    "                    agg = aggregationFunction(df)\n",
+    "                else:\n",
+    "                    agg = aggregationFunction(df, agg)\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "            if (i >= 300000):\n",
+    "                break\n",
+    "        #Handle the last few tweets\n",
+    "#         df = pd.DataFrame(data=data)\n",
+    "#         print df.info()\n",
+    "#         agg = aggregationFunction(df, agg)\n",
+    "    #return the aggregation\n",
+    "    return agg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def createHashtagsDf (df, hashtagsDataFrame=pd.DataFrame()):\n",
+    "    \n",
+    "    #time based recodes\n",
+    "    df['DoW'] = df['created_at'].apply(lambda x: str(x)[0:3:])\n",
+    "    df['Month'] = df['created_at'].apply(lambda x: str(x)[4:7:])\n",
+    "    df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])\n",
+    "    df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))\n",
+    "    df['Minute'] = df['created_at'].apply(lambda x: int(str(x)[14:16:]))\n",
+    "\n",
+    "    #let's grab the coordinates from the coordinates field, which is actually a dictionary\n",
+    "    coords = []\n",
+    "    for i in range(len(df)):\n",
+    "        location = df['coordinates'][i]\n",
+    "        try: #want to make sure that null values don't throw an exception\n",
+    "            coords.append(location.get('coordinates'))\n",
+    "        except:\n",
+    "            coords.append([None,None])\n",
+    "\n",
+    "    df['Coords'] = coords\n",
+    "    df['x'] = df['Coords'].apply(lambda x: x[0])\n",
+    "    df['y'] = df['Coords'].apply(lambda x: x[1])\n",
+    "\n",
+    "    #now, let's grab the information from place, which is similarly a very detailed dictionary of elements\n",
+    "    name = []\n",
+    "    country = []\n",
+    "    coordinates = []\n",
+    "    full_name = []\n",
+    "    for i in range(len(df)):\n",
+    "        location = df['place'][i]\n",
+    "        try:\n",
+    "            coordinates.append(location.get('bounding_box').get('coordinates'))\n",
+    "            name.append(location.get('name'))\n",
+    "            full_name.append(location.get('full_name'))\n",
+    "            country.append(location.get('country'))\n",
+    "        except:\n",
+    "            coordinates.append([[[0,0],[0,0],[0,0],[0,0]]])\n",
+    "            name.append('')\n",
+    "            full_name.append('')\n",
+    "            country.append('')\n",
+    "\n",
+    "    mean_coords = []\n",
+    "    for box in coordinates:\n",
+    "        mean_coord_x = (box[0][0][0]+box[0][1][0]+box[0][2][0]+box[0][3][0])/4\n",
+    "        mean_coord_y = (box[0][0][1]+box[0][1][1]+box[0][2][1]+box[0][3][1])/4\n",
+    "        mean_coords.append([mean_coord_x,mean_coord_y])\n",
+    "\n",
+    "#     df['city'] = name\n",
+    "#     df['country'] = country\n",
+    "#     df['full_name'] = full_name\n",
+    "    df['P_Coords'] = mean_coords\n",
+    "    df['x_p'] = df['P_Coords'].apply(lambda x: x[0])\n",
+    "    df['y_p'] = df['P_Coords'].apply(lambda x: x[1])\n",
+    "    \n",
+    "    rowsToAdd = []\n",
+    "    for index,tweet in df.iterrows():\n",
+    "        for hashtag in tweet['entities_hashtags_text']:\n",
+    "            rowsToAdd.append({\n",
+    "                    'DoW': tweet['DoW'],\n",
+    "                    'Month': tweet['Month'],\n",
+    "                    'DoM': tweet['DoM'],\n",
+    "                    'Hour': tweet['Hour'],\n",
+    "                    'Minute': tweet['Minute'],\n",
+    "                    'Hashtag': hashtag.upper(),\n",
+    "                    'x': tweet['x'],\n",
+    "                    'y': tweet['y'],\n",
+    "                    'x_p': tweet['x_p'],\n",
+    "                    'y_p': tweet['y_p'],\n",
+    "                    'tweetId': tweet['id_str']\n",
+    "                })\n",
+    "    tempDf = pd.DataFrame(rowsToAdd)\n",
+    "    hashtagsDataFrame = hashtagsDataFrame.append(tempDf)\n",
+    "\n",
+    "    return hashtagsDataFrame"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "filename='data/cleanedShootingTweets.json'\n",
+    "data = ReadAndAggregate(100000,filename, createHashtagsDf)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "data['x'].fillna(value = data['x_p'], inplace = True)\n",
+    "data['y'].fillna(value = data['y_p'], inplace = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "data['x']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "data.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "#the cartopy map, going simple outline for now\n",
+    "plt.figure(figsize=(15,15))\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "\n",
+    "#straight-up coordinate data which we just finished recoding\n",
+    "plt.scatter(data.x,data.y,color='r')\n",
+    "plt.scatter(data.x_p,data.y_p,color='g')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, to add a temporal element to this, we add a slider which pulls in some of the time columns we also just pulled out of interest."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "latLonPopulated = data[(data['x'] != 0) & (data['y'] != 0)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "latLonPopulated"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "hashtagGrouped = latLonPopulated.groupby('Hashtag').count().reset_index().sort_values(by = 'DoM', ascending = False)\n",
+    "sortedHashtags = hashtagGrouped['Hashtag'].tolist()\n",
+    "topHashtags = sortedHashtags[0:10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "topHashtags"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def plotHashtagLocation(DoM, Hour):\n",
+    "    plt.figure(figsize=(15,15))\n",
+    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "    ax.coastlines()\n",
+    "    \n",
+    "    for i,hashtag in enumerate(topHashtags):\n",
+    "        subset = latLonPopulated[\n",
+    "            (latLonPopulated['DoM'] == str(DoM)) & \n",
+    "            (latLonPopulated['Hour']==Hour) & \n",
+    "            (latLonPopulated['Hashtag'] == hashtag)]\n",
+    "        if (len(subset) == 0):\n",
+    "            continue\n",
+    "        \n",
+    "        plt.scatter(subset.x,subset.y, color= cm.jet(i/float(len(topHashtags))), label = hashtag)\n",
+    "#         plt.scatter(subset.x_p,subset.y_p, color= cm.jet(i/float(len(topHashtags))), label = hashtag)\n",
+    "    plt.axis([-180, 180, -75, 75])\n",
+    "#     plt.axis([-180, 0, -75, 75])\n",
+    "    plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "DoM = widgets.IntSlider(min=10, max=27, value=17)\n",
+    "Hour = widgets.IntSlider(min=0, max=23, value=17)\n",
+    "widgets.interact(plotHashtagLocation,DoM = DoM, Hour=Hour)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "Since sliders aren't the most conducive, we actually animate this function..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "from matplotlib import animation\n",
+    "from IPython.display import HTML\n",
+    "from tempfile import NamedTemporaryFile\n",
+    "\n",
+    "def plotAnimationProperly(list_functions, data_to_plot, colors_to_plot):\n",
+    "    for i in range(len(list_functions)):\n",
+    "        list_functions[i].set_data(data_to_plot[i].x,data_to_plot[i].y)\n",
+    "        list_functions[i].set_color(colors_to_plot[i])\n",
+    "\n",
+    "#Note, the animation code courtesy of and adapted from http://jakevdp.github.io/blog/2013/05/12/embedding-matplotlib-animations/\n",
+    "VIDEO_TAG = \"\"\"<video controls>\n",
+    " <source src=\"data:video/x-m4v;base64,{0}\" type=\"video/mp4\">\n",
+    " Your browser does not support the video tag.\n",
+    "</video>\"\"\"\n",
+    "\n",
+    "def anim_to_html(anim):\n",
+    "    if not hasattr(anim, '_encoded_video'):\n",
+    "        with NamedTemporaryFile(suffix='.mp4') as f:\n",
+    "            anim.save(f.name, fps=20, extra_args=['-vcodec', 'libx264', '-pix_fmt', 'yuv420p'])\n",
+    "            video = open(f.name, \"rb\").read()\n",
+    "        anim._encoded_video = video.encode(\"base64\")\n",
+    "    \n",
+    "    return VIDEO_TAG.format(anim._encoded_video)\n",
+    "\n",
+    "def display_animation(anim):\n",
+    "    plt.close(anim._fig)\n",
+    "    return HTML(anim_to_html(anim))\n",
+    "\n",
+    "# First set up the figure, the axis, and the plot element we want to animate\n",
+    "# First set up the figure, the axis, and the plot element we want to animate\n",
+    "fig = plt.figure(figsize=(10,10))\n",
+    "ax = plt.axes(xlim=(-180, 180), ylim=(-75, 75))\n",
+    "# plt.axis([-180, 180, -75, 75])\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "scat, = plt.plot([], [],'o')\n",
+    "scat_top_1, = plt.plot([], [],'o')\n",
+    "scat_top_2, = plt.plot([], [],'o')\n",
+    "scat_top_3, = plt.plot([], [],'o')\n",
+    "scat_top_4, = plt.plot([], [],'o')\n",
+    "scat_top_5, = plt.plot([], [],'o')\n",
+    "scat_top_6, = plt.plot([], [],'o')\n",
+    "scat_top_7, = plt.plot([], [],'o')\n",
+    "scat_top_8, = plt.plot([], [],'o')\n",
+    "scat_top_9, = plt.plot([], [],'o')\n",
+    "\n",
+    "# initialization function: plot the background of each frame\n",
+    "def init():\n",
+    "    scat.set_data([], [])\n",
+    "    scat_top_1.set_data([],[])\n",
+    "    return scat,scat_top_1,scat_top_2,scat_top_3,scat_top_4,scat_top_5,scat_top_6,scat_top_7,scat_top_8,scat_top_9,\n",
+    "\n",
+    "\n",
+    "# animation function.  This is called sequentially\n",
+    "def animate(i):\n",
+    "    day = round(i/24) + 17\n",
+    "    hour = i - (day-17)*24\n",
+    "    subset = []\n",
+    "    color = []\n",
+    "    label = []\n",
+    "    for j,hashtag in enumerate(topHashtags):\n",
+    "        subset.append(latLonPopulated[\n",
+    "            (latLonPopulated['DoM'] == str(int(day))) & \n",
+    "            (latLonPopulated['Hour']==hour) & \n",
+    "            (latLonPopulated['Hashtag'] == hashtag)])\n",
+    "        color.append(cm.jet(j/float(len(topHashtags))))\n",
+    "\n",
+    "    plotAnimationProperly([scat,scat_top_1,scat_top_2,scat_top_3,scat_top_4,scat_top_5,scat_top_6,scat_top_7,scat_top_8,scat_top_9],subset,color)\n",
+    "    \n",
+    "    return scat,scat_top_1,scat_top_2,scat_top_3,scat_top_4,scat_top_5,scat_top_6,scat_top_7,scat_top_8,scat_top_9,\n",
+    "\n",
+    "animation.Animation._repr_html_ = anim_to_html\n",
+    "# call the animator.  blit=True means only re-draw the parts that have changed.\n",
+    "anim = animation.FuncAnimation(fig, animate, frames=48, interval=5000, blit=False)\n",
+    "\n",
+    "# call our new function to display the animation\n",
+    "display_animation(anim)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/.ipynb_checkpoints/Most_Popular_Hashtags-checkpoint.ipynb b/.ipynb_checkpoints/Most_Popular_Hashtags-checkpoint.ipynb
new file mode 100644
index 0000000..9fffa13
--- /dev/null
+++ b/.ipynb_checkpoints/Most_Popular_Hashtags-checkpoint.ipynb
@@ -0,0 +1,1599 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Most Popular Hashtags\n",
+    "**Sophia and Victoria**\n",
+    "This notebook will explore the most popular hashtags over time. In addition, we are also using this notebook to start developing functions that will allow us to read in/aggregate our data bit by bit -- we don't think reading in millions of tweets and converting them to a dataframe is a sustainable method once our tweet counts gets to be in the 10s of millions. We will be prototyping this functionality using the popularity of hashtags. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First, let's start by importing everything we need!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import time\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np \n",
+    "import pandas as pd\n",
+    "from collections import namedtuple\n",
+    "from ipywidgets import widgets  \n",
+    "from IPython.display import display\n",
+    "% matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the path to the json file containing the cleaned tweets. We can't push this to github, because Twitter's API terms of service do not allow this"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "filename = './data/cleanedShootingTweets.json'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the read and aggregate function. This is a first pass at creating a function that reads through the data bit by bit, and aggregates. This function takes in the number of lines to read at a time and a filepath, and returns a dictionary of hashtags and counts of those hashtags. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#This works if we don't care about time stuff. \n",
+    "def ReadAndAggregate(linesAtATime,filepath):\n",
+    "    i = 0\n",
+    "    data = []\n",
+    "    hashtagsDict = {}\n",
+    "    \n",
+    "    #Open the file     \n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        # Loop through all the tweets        \n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate after we've read through the right number of lines\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print i\n",
+    "                df = pd.DataFrame(data=data)\n",
+    "                allHashtags = df.entities_hashtags_text.tolist()\n",
+    "                #                 \n",
+    "                for tweet in allHashtags:\n",
+    "                    for hashtag in tweet:\n",
+    "                        hashtagsDict[hashtag.upper()] = hashtagsDict.get(hashtag.upper(), 0) + 1\n",
+    "                \n",
+    "                data = []\n",
+    "    return hashtagsDict"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's try out this function!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100000\n",
+      "200000\n",
+      "300000\n",
+      "400000\n",
+      "500000\n",
+      "600000\n",
+      "700000\n",
+      "800000\n",
+      "900000\n",
+      "1000000\n",
+      "1100000\n",
+      "1200000\n",
+      "1300000\n",
+      "1400000\n",
+      "1500000\n",
+      "1600000\n",
+      "1700000\n",
+      "1800000\n",
+      "1900000\n",
+      "2000000\n",
+      "2100000\n",
+      "2200000\n",
+      "2300000\n",
+      "2400000\n",
+      "2500000\n",
+      "2600000\n",
+      "2700000\n",
+      "2800000\n",
+      "2900000\n",
+      "3000000\n",
+      "3100000\n",
+      "3200000\n",
+      "3300000\n",
+      "3400000\n",
+      "3500000\n",
+      "3600000\n",
+      "3700000\n",
+      "3800000\n",
+      "3900000\n"
+     ]
+    }
+   ],
+   "source": [
+    "hashtagsDict = ReadAndAggregate(100000, filename)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we want to actually plot the top hashtags. First we need to get the hashtags and counts sorted by the number of counts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "sortedByCount = sorted(hashtagsDict.items(), key=lambda x: (x[1],x[0]), reverse=True)\n",
+    "\n",
+    "splitintoTwoLists = [list(t) for t in zip(*sortedByCount)]\n",
+    "hashtags = splitintoTwoLists[0]\n",
+    "counts = splitintoTwoLists[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now for the plotting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([<matplotlib.axis.XTick at 0x11d0357d0>,\n",
+       "  <matplotlib.axis.XTick at 0x124488850>,\n",
+       "  <matplotlib.axis.XTick at 0x151a7d390>,\n",
+       "  <matplotlib.axis.XTick at 0x1225390d0>,\n",
+       "  <matplotlib.axis.XTick at 0x1143398d0>,\n",
+       "  <matplotlib.axis.XTick at 0x114339490>,\n",
+       "  <matplotlib.axis.XTick at 0x136282ed0>,\n",
+       "  <matplotlib.axis.XTick at 0x136282910>,\n",
+       "  <matplotlib.axis.XTick at 0x129607d10>,\n",
+       "  <matplotlib.axis.XTick at 0x11fac6d90>,\n",
+       "  <matplotlib.axis.XTick at 0x152186490>,\n",
+       "  <matplotlib.axis.XTick at 0x15056f790>,\n",
+       "  <matplotlib.axis.XTick at 0x1369b1290>,\n",
+       "  <matplotlib.axis.XTick at 0x11d039290>,\n",
+       "  <matplotlib.axis.XTick at 0x11d0293d0>,\n",
+       "  <matplotlib.axis.XTick at 0x11fac6190>,\n",
+       "  <matplotlib.axis.XTick at 0x1192eb890>,\n",
+       "  <matplotlib.axis.XTick at 0x1192eb950>,\n",
+       "  <matplotlib.axis.XTick at 0x11faf6fd0>,\n",
+       "  <matplotlib.axis.XTick at 0x11faf6710>],\n",
+       " <a list of 20 Text xticklabel objects>)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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mlEYQBEFQTCiNIAiCoJhQGkEQBEExoTSCIAiCYkJpBEEQBMWE0giCIAiKCaURBEEQFNNW\naUg6UdLdkq6utE2XNE/SjZLOlrR65dyhkhZKul7Syyrt20m6WtJNko6rtK8gaW7uc5GkDSvnDsjX\n3yhp/0r7RpIuzudOlbR8tx9EEARB0J6SlcZ3gN3r2g4Bfm37OcC5wKEAkrYA9gY2B14OHC9Juc8J\nwGzbmwKbSqrJnA08YHsT4DjgmCxrOnA4sAPwAmBORTkdDRybZS3OMoIgCIJlTFulYfsC4MG65j2B\nk/LxScBe+fg1wFzbj9m+FVgI7ChpXWBV25fm606u9KnKOg3YJR/vDsyz/ZDtxcA8YI98bhfg9Mrr\nv7bd+wiCIAi6Z6I+jbVt3w1g+y5g7dy+HnB75bpFuW094I5K+x25bVwf248DD0las5ksSWsBD9p+\noiLrGRN8H0EQBEEH9MoX4B7JAVD7S4quqXBE5XhmfgRBEAQ15s+fz/z589teN1GlcbekdWzfnU1P\n9+T2RcAGlevWz23N2qt97pS0HLCa7QckLWL83X194Dzb90taXdK0vNqoymrCEZ2/wyAIginEzJkz\nmTlz5pLnRx55ZMPrSs1TYvzs/qfAgfn4AOCMSvusHBE1A9gYuCSbsB6StGN2jO9f1+eAfPwGkmMd\n4Gxgt6wgpgO75TaA8/K19a8fBEEQLENkt7YsSfo+aca/FnA3MAf4CfA/pBXCbcDe2VmNpENJ0UyP\nAgfbnpfbtwe+C6wE/ML2wbl9ReAUYFvgfmBWdqIj6UDgMJL56yjbJ+f2GcBcYDpwBbCf7UebjN/d\nW89Eu88pCIJgMiEJ20u5AtoqjVEnlEYQBEHnNFMasSM8CIIgKCaURhAEQVBMKI0gCIKgmFAaQRAE\nQTGhNIIgCIJiQmkEQRAExYTSCIIgCIoJpREEQRAUE0ojCIIgKCaURhAEQVBMKI0gCIKgmFAaQRAE\nQTGhNIIgCIJiQmkEQRAExYTSCIIgCIoJpREEQRAUE0ojCIIgKCaURhAEQVBMKI0gCIKgmFAaQRAE\nQTGhNIIgCIJiQmkEQRAExYTSCIIgCIoJpREEQRAUE0ojCIIgKCaURhAEQVBMKI0gCIKgmFAaQRAE\nQTFdKQ1Jt0q6StIVki7JbdMlzZN0o6SzJa1euf5QSQslXS/pZZX27SRdLekmScdV2leQNDf3uUjS\nhpVzB+Trb5S0fzfvIwiCICij25XGE8BM29va3jG3HQL82vZzgHOBQwEkbQHsDWwOvBw4XpJynxOA\n2bY3BTaVtHtunw08YHsT4DjgmCxrOnA4sAPwAmBOVTkFQRAEy4ZulYYayNgTOCkfnwTslY9fA8y1\n/ZjtW4GFwI6S1gVWtX1pvu7kSp+qrNOAXfLx7sA82w/ZXgzMA/bo8r0EQRAEbehWaRj4laRLJb01\nt61j+24A23cBa+f29YDbK30X5bb1gDsq7XfktnF9bD8OPCRpzRaygiAIgmXI8l3238n2nyQ9DZgn\n6UaSIqlS/7wb1P6SIAiCYFnRldKw/af8915JPwF2BO6WtI7tu7Pp6Z58+SJgg0r39XNbs/Zqnzsl\nLQesZvsBSYuAmXV9zms+0iMqxzPrugZBEATz589n/vz5ba+TPbGFgKQnA9Ns/1nSKiS/wpHAriTn\n9dGSPgpMt31IdoR/j+S4Xg/4FbCJbUu6GDgIuBT4OfBl22dJehfwPNvvkjQL2Mv2rOwIvwzYjmRi\nuwzYPvs36sfp7hc7YqKfUxAEwSgiCdtLWXe6WWmsA/w43ZRZHvie7XmSLgN+KOktwG2kiClsXyfp\nh8B1wKPAuzx2J3438F1gJeAXts/K7ScCp0haCNwPzMqyHpT0KZKyMHBkI4URBEEQ9JYJrzRGhVhp\nBEEQdE6zlUbsCA+CIAiKCaURBEEQFBNKIwiCICgmlEYQBEFQTCiNIAiCoJhQGkEQBEExoTSCIAiC\nYkJpBEEQBMWE0giCIAiKCaURBEEQFBNKIwiCICgmlEYQBEFQTCiNIAiCoJhQGkEQBEExoTSCIAiC\nYkJpBEEQBMWE0giCIAiKCaURBEEQFBNKo4gVkTThx7rrbjToNxAEQdATokZ4mRS6kxE1xoMgGC2i\nRngQBEHQNaE0giAIgmJCaQRBEATFhNIIgiAIigmlEQRBEBQTSiMIgiAoJpRGEARBUEwojSAIgqCY\nkVYakvaQdIOkmyR9dNDjCYIgmOyMrNKQNA34KrA78FxgH0mbdS5pfg9G005Gd2lISlKRzJ/f/fuY\nLDKGYQzDImMYxjAsMoZhDMMio5v+I6s0gB2BhbZvs/0oMBfYs3Mx83swlHYy/kFKQ9LqMafl+bvv\nvqulUtl5553bKp7lllulaxmjoLyGYQzDImMYxjAsMoZhDMMiY6oqjfWA2yvP78htk5R2iqe10gHz\nxBN/7VpGO+V15JFHdqW4eiGjXf9IIhkEXWB7JB/A64FvVJ7vB3y5wXUGt3jMaXPe7l5Gu/69kNGP\n9zGZPosVs5yJPaZNe3JX/SeTjGEYw7DIGIYx9EoG4Eb33pHNcivphcARtvfIzw8hvcmj664bzTcY\nBEEwYBpluR1lpbEccCOwK/An4BJgH9vXD3RgQRAEk5jlBz2AiWL7cUnvAeaRfDMnhsIIgiBYtozs\nSiMIgiDoP6McPRUEQRD0mVAaUxBJnxn0GIIgGE1CaYwYkh6R9HB+PFJ5/ldJjxWK2WMZjm+7Dq9/\nzzIcyzo9kPGDwut2qRzPqDv3uh6MY2T8jzmycVIjaYc+vtaGPZa3lqTXStp+Qv2nkk9D0uEtTtv2\npwpktPwH2v5jgYz928g4uZ2MiqynAO8G3gH82PYHC/pcBcwElgqny6//QOFr1ysIAWcAryZ9ty4v\nkHG57Y4UTRt5a5D28OwLbG77GV3K+6Pttj/a6vuof0+l71HSBbZfnI9Psf3mTmRIuoUUX7+kqfLc\ntp/dbgxZzmakjbK/t/3nSvsets8q6N/1/1TSbGBN25/LzxcBq5Le04dtf71N/558FnUytwD2yY/F\ntp9f0OeHtvfOx0fb/mjl3DzbLyuQ0dXnKelnwCG2r5H0dOBy4DLg2aS9bsd1Im9kZi894i8N2p4M\nvBVYC2irNICfk7581RuugacBawPLFchoNkt5DenH2lZp5Jvj+4D9ge8DO9i+v+C1ATYD/kBjpWHg\nWYVyLgMuJm1Xr7EW8IUsZ5dGnXqNpJVJKWT2BbYl3Vz2As7vx+vXhtHkuNHzZqxSOX7uBGTU38Sm\nAXsDHwKuKBmApINIk5DrgRMlHWz7jHz6M0BbpdEj/pPxK+J7bK8naSXgbKCl0qAHnwWApI0YUxSP\nAs8Enm/71kIRm1SOdwOqiVWfVjqMwuuaMcP2Nfn4P4Bf2d5f0qrAhUAojWbYPrZ2nD+wg4G3kPJW\nHdusX52MLavP85fqo8BLST+qEhnvrfQX8KYs42Lg0636Snoq8EHgjcC3gW1tP1TyuhWus71th30a\n8QbgIOAY27/M47vF9s4dyNhK0sMN2kWaEa7WqrOk7wP/Sgq9/gpwLnCz7fmlA2hhUhPwpEIxbnLc\n6HmJjE7OpQvypEEpmeebgQ8DVwKvtH1d4RjeBmxv+8/5u32apI1sf4nym9ezJP20xThfUyBDdZOg\n/8l9/54nCS3pxWch6SJgNdL94fW2F+bv960l/WtDmeC5KutJ+nJTIfZBbfo/WjneFfhm7veIpCcK\nx7CEKaU0ACStCXyAdKM+CdjO9oMTkLMJcBjwApLCOcgpcWJp/+WBA0kzn4uBf7d9Y0HX24B7ge8A\nfwVmJ72TsP2F0jF0i+3TJZ0NfErSW0jKrFN754IuFdgWwIOkmfH1ef9Op2NoNWG4oVBG7UYpxt80\nBcxo3m0ca0h6LWlWvEbFFyJg9XadJT2JNAl6P3ABsJftmwtfu8a0mknK9q2SZpIUxzMpVxr3UjgJ\na8Ea1Se2PwNLlMBT23Xu0WdxN2nlvw5pVbCQzr/fT5a0Lel/unI+Vn60VX6Zv5EsAxPldknvJeXn\n2468WszKt3RStISp5tP4HPA64BvA16r22g5kPI+kLJ4LHAOcavvxDmW8m7TKOQc4upOZi6QjaPHF\ntX1kgYwDbX83Hz8l9+v4s6iTuS3JLPVc22t30O+Kblc92Qa/D2n1dR/wHOB5tu8u7P8vti/qcgz/\n1uq87d8UyPhOGxn/0ab/HcBjJHPDUr412z8qGMO5wAdsX1lpW560qn2T7bbm1x75NI4HHrD98br2\no4Cn2v7PNv27/iyynNVJ94x9SKamNYDdbV9S2H8+rX+vbVflPfBprA18Eng66b43L7fvTFpVfr4j\neVNMaTxBsr8/RgMnWTtTSJbxOCm77s+BpZRFwVKxNo57SDOyRuPYqkXf6RNZGTWQ8y7gEJIdXcAj\nJAV2fBcyBaxqu5G5qVmfj9Vmkb0gR4TsQ7Jf32H7RQV9euqMnyiSXld6M2vS/7s0v0HZ9lsKZKwP\nPNpI4UrayfaFBTJ+ZLuriDFJqwDfIvn/rsrNW5P8aG9tN8npxWfRQOY6pO/VLGBD2xt0KmMiSLrY\n9oQj0iRtA1zlHt3sp5TS6AWSDmh13vZJBTKe2UbGbS363kOaTV8I/A640PZN7V6zTsZhwE7Ae2z/\nX257FvAlUsTMUZ3Ia/Iah9v+ZOG1LwcOJZmaAK4lKbBfdPH6Av7VdltneI9WOwtY2q9xH3Ae8Hnb\nfy+QMXDllR3N/wlsDCwgpecpDeWuylmb5FCvOfSvBY4vXf1V5DyrIuM62//b6Vh6iaTpwGKS0mj6\nO61c/5JW5wu/n9vT4Ltl+/YmXer7X0YKbvkD+Z4BXGT7kZL+S8mbikojL8tqX8RrOnSadq21Jb2P\n9M+7fII/yE2BF1UeTyP5RS60fUxB/xuBretvZNnGeZXtTTsdU4PXKA1VfSvpJvUR0iwSUuTLZ4Fv\n2f5Gm/5/Aj5meynTTulNWNJiWkRalThum0wE1gQOAFax/bYCGb0w6zyP5PSt3qw/b3tBYf8fkByn\nvwVeDtxm++AOx7ATKaLvu4zZ4rcnfRZvKlytdBXartZh7bZ9SsEYDgd+aPsGSSuSfAFbkywV+9r+\ndYGMMxu9PrAVsEGhue+8Bs1rAiuQkrRe2eB8vYwnkwrX1e4ZOwB3ke4Z72rXf5ysqaQ0JK0H/Aj4\nO+O/zCsDr7W9qEBG11pb0udJ/7jNSLO52qrhdy7cI1GR9WzgFSQfyXq22zrXJN1gu2Fp3FbnGlzb\nzAwlYGXbbQMtJF0HvLj+fUtaC7jA9uZt+t9CslnfQzJbPFQ5V7SCkLSQFHbdkBJ/RBv5peP4K9DI\nWdvWbJn77wl8HvgvxivgQ4EPeSx0tpWMBc4RgtmXcUmnikzSxcA7bV9R174N8N+2X1AyDlqEtre7\n2Ur6SpNTryH9Tkq+m9eSfGOW9HaS2fOlwKbASbZ3bCejgcydgI8D04FP226kVEplPR/4gu2Wq5m6\nPqsALyRZGvYnBT6UhtgDUy966qvACTUncI08KzmegnKxtp9fp7UPAk6RVKy1bX8ov+4KpB/1i0jx\n09+QtNj2Fs36SqrNFP4F2AD4P9IqYz/Spp0SFkna1fY5dbJ3IaWZL2UxaX9II/t30dKZNHFZSlHa\nvl8qCtZ5kLRR8TDgCklvqawcS2dEf+5WMbShNPPCLaSNkRPlk8BuHh9YcXV2bp+RH+1YEgFo+7HC\n/0E9q9UrjCzvSqVQ97a4y9B2dxHWXuGfFYvC7sBcp6CX65Wis4qRtCvwCdJ38jO2f9VJ/0bYvqwW\nyNLmtfcl3TO2Ifl0LwV+T5qs3dXp6041pbGF7dfWN9o+Odv5i7D9V2C+pNqHX9PanabnWJkUB756\nftxJWnm04gKScvgiaQf4Xzt8TUiK7gxJFzC24no+6X10Umf9ZNJmp0Z26u8XynhY0ta2r6o2Stqa\n5JxvS/5hHyVpHkmB/5g0myvlQUnr1n5AeRLxelJ48xElqz813usxnaTMSzcZ/rPETt6C5d0gEs8p\ndLb0Jrd1ZQUpUpjow3QQLEK6Ty8VsKEU7t5R6iJ1EdquiYe11/hHNvfdDeyc5dQoCpeV9ErS+B8C\nPm77gg5ev53sdSibGP03qfbQ14HzO/WB1jPVlEbDL6xS7HfJTu6eaG1J3yDZnB/JfX9HWmaWREU9\ngzG75DtSf63QAAAgAElEQVTyD+Ny4CKSmez/2gmwfW3+MezLmO37fOAdJQ7bipymN2ZX0iW04YPA\nT5XCTasK7ADSDbcdS6bCti/JTsMvkz7XtQrHsAbwT1jiuPws8F7S//gbwL8XyKjfl2DgfmA+6Udb\nQlNbv6R1CpzIj0nasN7en/0tRb6zEht7AV8E5kn6EGOr3+2Bo/O5tmjp0PbZ7iC0XePD2vdopEwL\nOBg4jWQS+4LtW7LsV1C+q/xM0v6I+4GPSPpI9WShv+wrLK0c1iTdA0r8TWuQfDEvAo6Q9BySRaF2\nzzi3QMbYeKaYT+OLwFOA99n+S25bhfRF/rvLwmUfoUutLeks0gala0gK4yKSQ77jf0Y2lb2FlFJk\nRqFjbWNgnXqHZLa33lUaoZJvRotrfoQcYLAXaYb+Vdv/LJSzLvAuKlEypHjytkpY0rfdIHxS0r8D\nR5X4ZyRdaXubfPw14F7bR9SfmyiSXm/79An06yiPlqS9SDfYzzBeAR8CfNT2Tzodw0SR9CpScEPV\nIf+5Uhu+ugxtV/Ow9lr/lv6hLOMDjE1KanWz7yP52m5p1z/L6MX+nfqIzdqE5FLb95SMo07eOqRs\nDsX3jHH9p5jSeBLJSXgg6cYmkl/gJFIETtubnFKZ2ZrWfhFpI1nHWjvbWZ9bkfM84IEsY06LfquT\n/Bm1ftuSdqpeRPKpnFbw2j8DDnVdRI2kLUn21iK7uqTfkwII7sxOzl+TPt+tSLH+TZ3LDWStRArz\nhJQGpHjF00Leq23/T8G11wDbZBv+DcDbnUMhJV1j+3ldjqUokixf2zSPlu22KR+yWe+DjL9ZH1tv\n/ht2JB1I601xLUPbs1lrHZLiqbIBaWLUdne4pEa/wzVJ/o0jbM9tJ6OXTPQ3ImkrxkdbrsDYZPVC\n25e16L40tqfcg2SP3DI/ntylrHWA95CiXh6fQP/1STuZvwT8L2nm3ur6e4GfkiJiXkKKUur0NS9t\ncW5BB3Kurhx/npSDCpIZ8OpCGcuTZsf3kmbHl+fjY4Andfi+liNFkp1CskOfVtjvMJJp6AyS2aE2\nmdo4/6i6/b7dXnjd90k3uRNJye2WA27p8rWn195PPx+kcN3fkGbm9+XjV/Tx9X8GbNmgfUvgzC5l\nr0kKly+5dgFwdbNHoYzab+S+ifxG8vVfJkV/bdjtZzulfBpKOfBvdzJ7LMgOz6MkdeLwbKa1v0IL\nm3SdjIMq/R/N/X9HStXQ0hFue0lmzBw5MREb9BotzpXmw4Hx4ZC7kBQZtp/oIOrmc6TZ9LOcw5Yl\nrUZSQp+nwGabTQD7khTGJSSH/gwXBgnY/rSkc0hpFuY5/9JIyu+9zXsWU7qc7yqPlpbeV/BLkl/m\nMUlF+wp6gaS3kVL1L7X3RtL6brP3Jss4k9YrjXa+gHXcYG+K7QU5EmvC2H5A5V/wV3XzWpnab2TG\nBH8jO7tJUtNGPrC29EvzD8ODpHHXzMcvIUUrvZ6UEr10Vno5SUFMWGuTcjS9Hnj6BPu/k7Q34X6S\nSes24F0d9D8VeFuD9rcCP+hAzpeAH+a/t5BnPaSb72WFMhbSYCZMUoYLC/rfQVK4byalMIEuZ+cT\n/J80m1EuAP7RgZzNgCNJiRIvIM0o1ynsey1jq6S3k5zwywGbk/Zb9OuzuK72O6trX4ukDEtk/Fur\nR8n3qsW5m7t8fzsD5xZeO68Hn2e3v5HLK8fnNDtX+phSKw1gOY+tJt5IKkByOnC6pLa7KgE8Vmhn\nJWDjHOXRkQ3e9geyjJ0lvT43X2u70c7PcUj6OGmFMtN1KUAkremyFCAfAX4g6U2Md5iuACwVktyC\n95E+x6eTosdqoZDrkkw+Jdj521vXWDrLPo1k838j8LikM+g8E2kv6MWMEts3AHOAORrLo3WppJI8\nWvX7CmrJNK9Xfyv/dbv3BuA/bB/YxRguk/Q2298cN7CUgaAoY6yWTg0DyTR1JynEvoTSmhmt6PY3\nUv3Q12xxrogppzQkLe+UumNX0mysRtFnkX98nyFFLC1xpueQ0cNcEEMu6RnAjxm/M/0Nko6m/c70\nN1OXAsT2/0nam5TYrURpnGF7O6XNfDWH6c/dYehd/iLPVSpvuq1Sptvr3GBjVwuuk7S/66oVStqP\ngrTktt8n6f2kDX77kOy8a0h6I+k9dZW9txQ32F+hVPvk/kY/+EZIeo/tr1Zk/gH4g6QPk2qGtKPV\nvoJVGndZJnS994YUTNEN7wN+3OXEqH4iYNL/s1Ext2asrhblfl2WoLKr3wi9qfUy9rqF3+dJgdIG\nvleQHEobkmppOIegnmR7pwIZXyTZF9/vpe2Lf3NBnh6lzWdnuPHO9NfbbrrBTj1IAaIeJOjLclYj\nZSLdnrFMpNuQfqSzXZDtVmOpXao1A55PB6ld6uQ9iTTL3oeUwrpt7YVeoFQX+7Mkc+GnSM74p5L8\nIvu7D2VSJb2AFAn4NOA45/LFSvsK3mx7n4nK7nAcLwa+R6r5stTeGxdscMtRbPvQZCbsglLCWc7O\npMhESKv5jiZG3SLpflKARcMqmS7LPNzVb0QpTfwX8hjen4/Jz9/nDrP1TimlAUt+3DWHZ22vxqbA\nU0q+iEp5ijatnz3mUNwbbG/SuOe4a2+0/ZxOz+Xz55DCYhulAPmEy/Lz175EDXFhISel9NO3Ap90\nDgfNDsJPABvbLl3C18ZfzWZ6TqvrK/32BNa3/bX8/PeksrsAh7sgMV0vUMpJ9jHSzv5vAC+3fbFS\nrY9TS5R0t0qjjewJ7RXp4vUmvPcm93+EtHG22c22L6WEu6WX/9NGvxFJK7jNVoEmocNLcEENnnHy\nppLSUEpjUMWkENdOIlRucpMssK3O1V23sJFyUdqZfpPtjRt0q13zXNLMpWEKENvXFrz+n4ATaD6L\nK/oSNXsf7c7VXVf/P6kfS8uINkkXArOc00Rn39SuJHPMd2zv2m4MvUDjNwhe70qixdKVnaTHSNUY\nlzpFeQqPZrKL94oMA71aDQ+aXrwPNSkzkFf6P7U9sxv5nTLVfBp/YMyGV7thPkXSVaQMqbcWyOjW\nvgjwM0nfpPHO9JY1JNybFCB/avQl7DGlDrba/0SkFeCdlf4mZRRuxQoeX1fgAqf60Pfnz7RfVDfe\n/a3uXOmkpNvSt62YUObBCb1QYwdybQx2wW7sScSbq0+Usje/BPhj9lmV8GJJn7a9JLhEaVf32SSz\nVUuUQrGb4ZoZs5QptdJoRnZUvd1224SDvbDBa+md6ZB8LMU70xvInEbKrf+9gmt75dM4ibQh8VPV\n1ZqkT5BMeG9u2rlH45J0c7OVmaT/tf3sTuRNFKW0F3+BJbWfaysGASvZbpswcFnOrvu50tBYbRGR\n0oC8onq+UdBAAxkvsz1PPc4U0G+Usi8cYvsaSU8nhexfBjybFL15XIGMlUhRgjfZ/oDSbvdfkuqk\nfL2g/wcbNK8CzAbWst02U+44eaE0Ep3aHidqg6+TsTJjP4j/dcFmtLwkfTep4P0ZpNQd7yZFylzV\nyolekbFmO7NPCXksJ5KK1ddClrch7ap+q+3FHcrr2P4r6XvAfC8dWvkOUlhyX5y/vUBdlr5tM8Pf\n1PaKEx7cBJmoTT9PrD5NXZQ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vsQTjCZ9GMGi2IKWLuB64Pm/kiplMcIvtPw56\nEMHShE9j9PifQQ+gl9jehrQDfFXg15IuAFYNJ/iU5ye1A0mnD3IgwXhCaYwe90raBECJ7+R6wVdL\nGskwRNs32J5jezNSHeSTgUsl/W7AQwsGRzVC6lkDG0WwFKE0Ro+DgVvz8T6kQjUzSDW2vzSgMfUM\n23+w/UHgmcAhgx5PMDBaRU8FAyR8GqPHY7ZrydxeBZxs+36SaeeYAY5rQkj6Cq1vCue3OBdMXraW\n9DA571Q+hhGOEpwshNIYPZ6Q9HSS83hX4NOVcysPZkhdcVnl+EhgzqAGEgwPkXtqeAmlMXocTrrR\nLgf81P7/7d0hTgRBEIXhVwEMBLMOhcSs5xQYPIoL4DkGJ0BgsGjuAAJF2AQPQaBWkIdYBjosokPC\n9nTxf2qmVSUtKj01Ve076fMXxVnLwH7D9vnwHBEn5TuA8aFPo0MRsS5p2/ZLsbalxX4uXQXbC2YK\nAePHSaMzEXFYPEuLesCTpJsM92oAGDeSRn8OflibaDFS/HgYJ92LiHjVVyF8k4InMG58nkoiInYl\nXdrebx0LgLzo00jC9qOkjdZxAMiNpJFEROxJmreOA0Bu1DQ6ExFXWm6Gm0jakXS0+ogA/CfUNDrz\n0Y/xfcTCs6T7olMcAP4ESaMzxd9G5UC3YRPnkh4kndq+XnVsAPIjaSQSEWuSppIubE9bxwMgHwrh\nidh+s30r6ax1LABy4qQBAKjGSQMAUI2kAQCoRtIAAFQjaQAAqpE0AADV3gHz7t0M4f1rAwAAAABJ\nRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x11d035810>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.bar(range(len(counts[0:20])), counts[0:20], width = 1)\n",
+    "plt.xticks([x+0.5 for x in range(len(counts[0:20]))], hashtags[0:20], rotation='vertical')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we also want to aggregate over time, so that we can understand how popular hashtags develop over time. To do this, we'll need to define another function for aggregation.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "#This works if we don't care about time stuff. \n",
+    "def ReadAndAggregateIntervals(linesAtATime,filepath):\n",
+    "    i = 0\n",
+    "    data = []\n",
+    "    hashtagsDict = {}\n",
+    "    #Create a named tuple that we'll be using as our dictionary key\n",
+    "    HashtagKey = namedtuple(\"HashtagKey\", [\"DoM\", \"Hour\", \"Text\"])\n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print i\n",
+    "\n",
+    "                #Recode some of the data\n",
+    "                df = pd.DataFrame(data=data)\n",
+    "                df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])\n",
+    "                df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))\n",
+    "                \n",
+    "                #loop over all the tweets\n",
+    "                for index,tweet in df.iterrows():\n",
+    "                    #Loop over the hashtags in the tweet\n",
+    "                    for hashtag in tweet['entities_hashtags_text']:\n",
+    "                        hashtagsDict[HashtagKey(\n",
+    "                                tweet[\"DoM\"], \n",
+    "                                tweet[\"Hour\"], \n",
+    "                                hashtag.upper())] = hashtagsDict.get((tweet[\"DoM\"],\n",
+    "                                                             tweet[\"Hour\"],\n",
+    "                                                             hashtag.upper()), 0) + 1\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "    #return the aggregation\n",
+    "    return hashtagsDict"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's create a plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100000\n",
+      "200000\n",
+      "300000\n",
+      "400000\n",
+      "500000\n",
+      "600000\n",
+      "700000\n",
+      "800000\n",
+      "900000\n",
+      "1000000\n",
+      "1100000\n",
+      "1200000\n",
+      "1300000\n",
+      "1400000\n",
+      "1500000\n",
+      "1600000\n",
+      "1700000\n",
+      "1800000\n",
+      "1900000\n",
+      "2000000\n",
+      "2100000\n",
+      "2200000\n",
+      "2300000\n",
+      "2400000\n",
+      "2500000\n",
+      "2600000\n",
+      "2700000\n",
+      "2800000\n",
+      "2900000\n",
+      "3000000\n",
+      "3100000\n",
+      "3200000\n",
+      "3300000\n",
+      "3400000\n",
+      "3500000\n",
+      "3600000\n",
+      "3700000\n",
+      "3800000\n",
+      "3900000\n"
+     ]
+    }
+   ],
+   "source": [
+    "aggDict = ReadAndAggregateIntervals(100000,filename)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's create a plot of the most popular hashtags, allowing the user to input time and the number of hashtags they'd like to visualize"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def plotHashtags(DoM, Hour,nHashTags=20):\n",
+    "    #Filter the hashtags, so that we only get the tweets of the appropriate day of month and hour\n",
+    "    timeHashtags = {key: value for key,value in aggDict.items() if (key.DoM == str(DoM) and key.Hour == Hour)}\n",
+    "\n",
+    "    #Sort the hashtags by count\n",
+    "    sortedByCount = sorted(timeHashtags.items(), key=lambda x: (x[1],x[0].Text), reverse=True)\n",
+    "\n",
+    "    #Split them up into hashtags and counts\n",
+    "    dictList = [list(t) for t in zip(*sortedByCount)]\n",
+    "    hashtags = [x.Text for x in dictList[0]]\n",
+    "    counts = dictList[1]\n",
+    "    \n",
+    "    #Plot\n",
+    "    plt.title('Hashtag Distribution (Dec {0} at {1})'.format(DoM, Hour))\n",
+    "    plt.ylabel('Number of Tweets')\n",
+    "    plt.bar(range(len(counts[0:nHashTags])), counts[0:nHashTags], width = 1)\n",
+    "    plt.xticks([x+0.5 for x in range(len(counts[0:nHashTags]))], hashtags[0:nHashTags], rotation='vertical')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we're going to create the sliders!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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QdL2k70taNpdNBu4pnHNvLpsMzC6Uz85lI+rYfg54VNIKXcoWBEEQlKBMMMWd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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x13be03ed0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "DoM = widgets.IntSlider(min=10, max=27, value=15)\n",
+    "Hour = widgets.IntSlider(min=0, max=23, value=10)\n",
+    "nHashTags = widgets.IntSlider(min=0, max=40, value=50)\n",
+    "widgets.interact(plotHashtags, DoM=DoM, Hour=Hour, nHashTags=nHashTags)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this plot, we don't have data for all the days, so there are some days/hour combinations that will error due to lack of data. \n",
+    "\n",
+    "This potential method of aggregation works pretty well, but it would be really ideal if we could use different kinds of aggregation functions and have this ReadAndAggregateIntervals function work with many different kinds of aggregation functions that we might want. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#This works if we don't care about time stuff. \n",
+    "def ReadAndAggregateIntervals(linesAtATime,filepath, aggregationFunction):\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print i\n",
+    "                \n",
+    "                #First time running through\n",
+    "                if (i == linesAtATime):\n",
+    "                    agg = aggregationFunction(data)\n",
+    "                else:\n",
+    "                    agg = aggregationFunction(data, agg)\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "    #return the aggregation\n",
+    "    return hashtagsDict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def aggregateHashtags(df, hashtagsDict):\n",
+    "    #Create a named tuple that we'll be using as our dictionary key\n",
+    "    HashtagKey = namedtuple(\"HashtagKey\", [\"DoM\", \"Hour\", \"Text\"])\n",
+    "               \n",
+    "    df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])\n",
+    "    df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))\n",
+    "\n",
+    "    #loop over all the tweets\n",
+    "    for index,tweet in df.iterrows():\n",
+    "        #Loop over the hashtags in the tweet\n",
+    "        for hashtag in tweet['entities_hashtags_text']:\n",
+    "            hashtagsDict[HashtagKey(\n",
+    "                    tweet[\"DoM\"], \n",
+    "                    tweet[\"Hour\"], \n",
+    "                    hashtag.upper())] = hashtagsDict.get((tweet[\"DoM\"],\n",
+    "                                                 tweet[\"Hour\"],\n",
+    "                                                 hashtag.upper()), 0) + 1\n",
+    "            \n",
+    "    return hashtagsDict\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100000\n",
+      "200000\n",
+      "300000\n",
+      "400000\n",
+      "500000\n",
+      "600000\n",
+      "700000\n",
+      "800000\n",
+      "900000\n",
+      "1000000\n",
+      "1100000\n",
+      "1200000\n",
+      "1300000\n",
+      "1400000\n",
+      "1500000\n",
+      "1600000\n",
+      "1700000\n",
+      "1800000\n",
+      "1900000\n",
+      "2000000\n",
+      "2100000\n",
+      "2200000\n",
+      "2300000\n",
+      "2400000\n",
+      "2500000\n",
+      "2600000\n",
+      "2700000\n",
+      "2800000\n",
+      "2900000\n",
+      "3000000\n",
+      "3100000\n",
+      "3200000\n",
+      "3300000\n",
+      "3400000\n",
+      "3500000\n",
+      "3600000\n",
+      "3700000\n",
+      "3800000\n",
+      "3900000\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{HashtagKey(DoM='14', Hour=15, Text=u'DEVELOPMENTS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'SHARPTON'): 8,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'KABARI'): 5,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'ROBERTMCCULLOCH'): 3,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'JOHNHOTZ'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'NO'): 2,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'ILLEGAL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'ITSTIME'): 2,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'DOESNTLOOKPEACEFULTOME'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'FERGUSONMISSOURI'): 4,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'TEACHERS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'BOUFFON'): 2,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'KITDANIELS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'FLASHBACK'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'RCFEED'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'HELLINAHANDBASKET'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'LHHATL'): 8,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'BULLION'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'MUSLIMS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'PHX'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'FAILMEDIA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'FREEOCELOT2014'): 2,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'LEGALIZE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'ECUADOR'): 3,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'THEREALNEWS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'MURDERER'): 3,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'SCREENWRITING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'ODINFEELS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'RENISHAMCBRIDE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'NEXTBIGCHARITYCHALLENGE'): 3,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'TLOT'): 60,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'SOCIOPATH'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'RISINGSTAR'): 2,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'JUSTICEFORDARRENWILSON'): 2,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'SIMONSAYS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'SOPOWERFUL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'BURNINGMAN'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'AM\\xc9RIQUES'): 1,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'FLASHBANG'): 1,\n",
+       " HashtagKey(DoM='17', Hour=17, Text=u'BOSTONFORFERGUSON'): 1,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'\\u0130YIDEBENBUSAATTENSONRA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'ISRAELUNDERFIRE'): 3,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'PRESS'): 4,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'NIXON'): 2,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'ASSHOLES'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'NOCOMMENTARYNEEDED'): 1,\n",
+       " HashtagKey(DoM='19', Hour=11, Text=u'NLG'): 2,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'NEWJIMCROW'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'OAKWOOD'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'PSF2014'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'SBOT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'HOTEP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'THOMASJACKSON'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'WAGEPEACE'): 3,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'DREDSCOTT'): 8,\n",
+       " HashtagKey(DoM='14', Hour=22, Text=u'JUSTICE'): 5,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'DJKINGASSASSIN'): 3,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'VOTEORDIE'): 1,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'HISPANIC'): 4,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'NOVOTENOGOPPROBLEMS'): 3,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'XDA'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'OURLIVESMATTER'): 4,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'SGF'): 2,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'YOUGOGRANDMA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'REPUBLICAN'): 1,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'LOZTELETOBIIZ'): 12,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'INTERNACIONAL'): 4,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'OLIVERCROW'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'AMERICANCHEESE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'ACAB'): 7,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'MAKEAMERICAABETTERPLACE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'EXECUTIVEORDERS'): 14,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'EVIINSONTEAMA'): 2,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'CNN'): 89,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'OBSTRUCTIONOFJUSTICE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'RIPJAMESFOLEY'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'C2GTHR'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'EE'): 4,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'COMBAT'): 1,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'LOCALGOV'): 2,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'NEWWORLDORDER'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'GOP'): 54,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'LEVIN'): 1,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'THUGS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'AND'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'BRAZIL'): 8,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'SECURITY'): 2,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'LETUSHOPEITENDSWELL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'VFP'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'TANKS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'CAPTRONJOHNSON'): 3,\n",
+       " HashtagKey(DoM='14', Hour=23, Text=u'MYAWHITE'): 11,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'JIHAD'): 2,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'SMART'): 6,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'STEPUP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'SARCASM'): 3,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'PAULCALLAN'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'MAIL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'LOVEMYCHURCH'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'CHARLIERIEDEL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'SAIDNOONEEVER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'DISASTER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'INSANITYCHECK'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'BREAKINNEWS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'CNNFAIL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'RETURNTHESERVE'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'SOLIDARIDAD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'ALQAEDA'): 1,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'RICKPERRY'): 2,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'CAREYGILLAM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'STANDUPORFALLDOWN'): 3,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'THEBLACE'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'FOCUSPLEASE'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'YOU'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'LIBERIA'): 3,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'GADGETS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'SHAKEITOFF'): 8,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'OPINIONJOURNAL'): 2,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'MEDIABLACKOUT'): 9,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'I'): 2,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'CANADA'): 2,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'YOUPEOPLE'): 1,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'RESPONSE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'SERIOUSLY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'DJ'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'FEATHER'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'PHOTOGRAPHY'): 14,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'CLEOWILLIS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'GODISGOOD'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'BLACKBOYS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'AFRIQUE'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'BB4SP'): 8,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'FRANCE'): 14,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'STOPPOLICEBRUTALITY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'BELGIQUE'): 1,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'SOMEGOODNEWS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'ASBURYPARK'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'UNDESIRABLES'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'LAW'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'\\ub3c5\\ub9bd\\uc6b4\\ub3d9'): 2,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'IDFGIRLS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'BORDERCRISIS'): 5,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'TWIBDOCKET'): 11,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'THEWHOLEWORLDISWATCHING'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'REVALSAIDSO'): 2,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'RACIALLYPROFILED'): 2,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'SCOTTOLSON'): 5,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'STANDFORSOMETHINGORNOTHINGATALL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'TRECASMENA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'VOLVIOCAYENDOYCORRIENDO'): 4,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'LIVE'): 12,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'URGENTE'): 4,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'GLOBAL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'NOTODOEST\\xc1DICHO'): 2,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'SEANBELL'): 1,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'SHOUTOUT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'MIKEBROWNLAW'): 3,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'BORED'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'CORRUPTOFFICERS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'JEZEBEL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'DEMANDJUSTICE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'CHICFILA'): 3,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'CV'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'CNET'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'BANKERS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NIEUWSVIDEOS'): 5,\n",
+       " HashtagKey(DoM='14', Hour=19, Text=u'GUN'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'JERK'): 5,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'HOPEFUL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'REPRORIGHTS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'MAGOP'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'YOKELCHANG'): 3,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'INTERNATIONAL'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'TEAMLOVE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'HOWCONVENIENT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'PERFECTTIMING'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'NOT'): 3,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'THEGOSPEL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'STLOUIS'): 15,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'OMAHA'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'BLACKAMERICA'): 2,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'SOCIALJUSTICE'): 4,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'NORTHKOREA'): 2,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'FOCUS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'LIBERTY'): 9,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'CHILLING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'NDAWAY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'DNC'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'PROBLACK'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'CARDS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'WALGREENS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'GUN'): 7,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'HELLO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'KNOCKOUTGAME'): 1,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'MUNDO'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'EMERGENCY'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'NBCNEWS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'OURTAXDOLLARSATWORK'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'LAVERDADOBRERA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'SALINGFOLLOW'): 4,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'NEWORLEANS'): 17,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'GEEK'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'AR2'): 3,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'EDUCATEKCPT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'PETITION'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'KABARI'): 6,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'INSTITUTIONALRACISM'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'LABORDAY'): 3,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'INVALID'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'LITTLEBLACKBOYS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'HUFFINGTONPOST'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'COLLAGE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'COPPEDNEWS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'SPSU'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'MYDU'): 2,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'DBENEWS'): 4,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'FILISTIN'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'RIOTING'): 2,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'SUPPORTGOOD'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'NOM\\xc1SRACISMO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'MEDIAINGERMANY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'HANNITY'): 2,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'THEPSHOW'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'BIAS4COP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'PAIESTINA'): 2,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'WRONGFULARREST'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'UAREAGREATSENATORMARIA'): 5,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'MORELIES'): 2,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'MEDIA'): 6,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'WECOMING'): 4,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'STLCITY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'MILITARIZED'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'QUERY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'WELLACTUALLY'): 2,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'YOURESOLOVEDHARRY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=22, Text=u'RIP'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'RACES'): 2,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'HANDSUPDONTSHOOT'): 203,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'JORDANDAVIS'): 3,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'DC'): 28,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'NIOWA'): 2,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'BLOGGING'): 2,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'HANDSUPTURNUP'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'ABD'): 3,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'DMSANTANA_21'): 2,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'LAW'): 6,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'FML'): 2,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'REDACTED'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'20H'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'DOTHERIGHTTHING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'FREEGAZAMOVEMENT'): 3,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'DONTSHOOT'): 98,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'UNEMPLOYMENT'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'WESTERNAFRICA'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'I'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'FERGUSONPD'): 66,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'HALLOFFAME'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'CONSPIRACYTHEORIES'): 6,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'NBC'): 6,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'NATIONOFTROLLS'): 2,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'AMWRITING'): 2,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'WELLDONE'): 2,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'STARTUPNEWS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'THEOLIVIAFOXSHOW'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'2NDAMENDMENT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'IPROTEST'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'EDITEDVIDEO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'COUPLE'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'GOVJAYNIXON'): 4,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'MOSAIC'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'PRAYINGWITHOURFEET'): 2,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'PIGS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'MS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'REAL'): 14,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'UNCLETOM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'CITIZENJOURNALISTS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'ERICHOLDER'): 20,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'NOVAYAISGRACIAS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'LIMBAUGH'): 2,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'BLUE2014'): 12,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'THELASTWORD'): 3,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'HAIKUFIGHTCLUB'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'TITULARESEU'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'REVOLUTIONNOWORNEVER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'SERVICE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'USA'): 112,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'RHYMES'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'NBA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'FASCIST'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'INROCKS'): 4,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'CIVILREVOLT'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'MOUTHHUGSFORTIM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'CHANGE'): 4,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'PHOTOS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'HIDDENNEWS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'POSH'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'7CI'): 2,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'MYCOUNTRY'): 6,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'UNITEDNATIONS'): 13,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'MIDDLEEAST'): 3,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'TNTWEETERS'): 8,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'WESTERWELLE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'BOISE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'AGENTPROVOCATEUR'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'SM'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'BECAUSEITSGOINGTORAIN'): 1,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'EZELLFORD'): 7,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'MAYORBILL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'STATENISLAND'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'POLITIE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'ABD'): 3,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'JAYNIXON'): 8,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'TROOPS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'POLMTL'): 7,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'BUNDYRANCH'): 35,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'HISTORYSHOULDNOTREPEAT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'CURRENTAFFAIRS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'NOTALLCOPS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'MIZ'): 1,\n",
+       " HashtagKey(DoM='19', Hour=11, Text=u'INFONEWS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'NATIONOFCOWARDS'): 5,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'NBA'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'KONDOBYJAYMONI'): 6,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'JUSTICEFORFERGUSON'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'PHX'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'DEAROBAMA'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'LETSGETFREE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'\\u0623\\u062e\\u0628\\u0627\\u0631'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'FREGUSON'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'MP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'ROSARY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'SATIRE'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'DONTSHOOTMEBRO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'IDOTHINKTHISISTHEBEGINNINGOFSOMETHINGMUCHBIGGER'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'SOUTHDAKOTA'): 8,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'TYRANNY'): 17,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'FIRSTAID'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'BETTERLATETHANNEVER'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'JONSWAINEISAHACK'): 11,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'CT'): 4,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'METAMEDIO'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'BLACKLIVESDONTMATTERIN'): 2,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'PHLED'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'STARTUPS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'OHPOL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'LIBERALDREAMS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'CHAMAKOSERIOO'): 2,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'MIFF2014'): 2,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'STOPSHOOTINGATNEWSVANS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'OPENSEASON'): 5,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'OOGOMOOG'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'BRAZIL'): 6,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'RICHMOND'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'FBI'): 27,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'NIEUWSVIDEOS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'UGH'): 1,\n",
+       " HashtagKey(DoM='14', Hour=20, Text=u'ICANT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'MADDOW'): 58,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'ISTANBUL'): 4,\n",
+       " HashtagKey(DoM='14', Hour=23, Text=u'THEFIVE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'DAVIDLETTERMAN'): 2,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'FREEDOM'): 2,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'CANADA'): 2,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'VIEWHOLDER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'MILITARIZATIONOFPOLICE'): 7,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'USNEWS'): 3,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'NEVERFEARHOLDERSHERE'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'HELPINGORHURTING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'GOVERNORS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'MARTHAVINEYARD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'ERICHOLDER'): 65,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'AFFRONTEMENTS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'DATOS'): 2,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'BLOODCUZZ'): 5,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'A19'): 1,\n",
+       " HashtagKey(DoM='14', Hour=23, Text=u'WILDWEST'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'KENTUCKY'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'CBTU'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'TERRIBLE'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'PHOTOJOURNALISM'): 13,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'SHARPTON'): 14,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'DISARMTHECOPS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'REFORMJO'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'DIREITOSHUMANOS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'WELLACTUALLY'): 10,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'PAKISTAN'): 2,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'INSPIRINGED'): 2,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'FINANCENEWS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'YOUTUBE'): 3,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'NOTICIAS'): 11,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'LOUISCOUNTYPOLICE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'NATIONALACTIONNETWORK'): 2,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NFLF'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'MINI_SWAG1'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'SOSEEUU'): 6,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'JUSTICEFORMIKEBROW'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'HUFFPO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'AUTOFOLLOW'): 7,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'ARTONFIRE'): 3,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'FREEGAZA'): 5,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'BOYCOTTSTL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'KIWANECARRINGTON'): 2,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'STLSHOOTING'): 1,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'SPREADCAM'): 2,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'HARLEYDAVIDSON'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'MOVEORYOURENEXT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'HARASSMENT'): 2,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'FRESNO'): 2,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'ROBERTCOHEN'): 3,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'TEFPOE'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'MADRID'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'OTTAWA'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'SOUTHERNDEMOCRATS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'VOTEBLUE2014'): 3,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'NOS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'THINK'): 3,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'NORMSTAMPER'): 3,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'FPD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'TALIBKWELI'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'AMIDFERGUSON'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'TELMI'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'HOWMANYMORE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'LIVESMATTER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'BLATANTDOMESTICTERRORISM'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'FUCKTHENRA'): 1,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'HSV'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'IRACK'): 2,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'ULTIMAHORA'): 3,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'STFU'): 2,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'GROWUP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'STLRIOTS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'ANOTHERSHOOTING'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'WESTBOROBAPTISTCHURCH'): 4,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'SHAME'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'KEEPTHEPEACE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'TYRANNY'): 8,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'APPRECIATEYOUMYBROTHA'): 2,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'TGDN'): 24,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'CCSS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'SORRYFORYOURLOSS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'SHAWSHANKREDEMPTION'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'DMEDIISON_21'): 12,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'CONSTANTCONTACT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'AUDRELORDE'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'CLASSACT'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'PEACENOW'): 1,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'M5S'): 4,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'PAYATTENTION'): 4,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'INTERNACIONALES'): 3,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'DONTSHOOT'): 60,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'HANDSUPHOUSTON'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'COUNTRY'): 3,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'KILLING'): 2,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'CROOKEDSYSTEM'): 3,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'MIKEBROW'): 3,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'FERGUSONPROTESTS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'GUNSENSE'): 2,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'YEREMIITO21'): 3,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'CROWDFUNDING'): 3,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'REDLINE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'PEOPLEAREAWESOME'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'MISSISSIPPI'): 2,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'LOUISVILLE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'CAUSEYOUSHOULDBE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'POLICEMILTARYBRUTALITY'): 9,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'ODD'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'MA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'PUPPET'): 2,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'NCAT18'): 8,\n",
+       " HashtagKey(DoM='14', Hour=23, Text=u'WASHINGTON'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'JAMESPARROTT'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'PARIS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'TRGGRRADIO'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'DICTATORSHIP'): 3,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'COMMANDPYCHOSIS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'PLANKPROTESTING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'CLUSTERFUCK'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'APPALLING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'TIMESSQUARE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'CRITICALMEDIA'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'RIPROBINWILLIAMS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'DOWNTOWN'): 4,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'MINORITIES'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'N4TM'): 3,\n",
+       " HashtagKey(DoM='14', Hour=22, Text=u'WELLDONE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'ECIG'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'DEMOCRATICPARTY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'RW16'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'POLAND'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'CORRUPT'): 1,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'UNCATEGORIZED'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'TULSACOCAINBUST'): 1,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'COP'): 3,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'P3'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'SECONDHOME'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'SWAT'): 2,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'BLUMOB'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'CHRISTIE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'SIXPACK'): 1,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'BNEWS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'EVERY28HOURS'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'TRIGGERHAPPY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'FREEDOMOFPRESS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'DENVERMARCHFORJUSTICE'): 3,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'BIAS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'MAKINAHD'): 3,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'SPEAKUP'): 7,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'AMERIKKKA'): 3,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'NOTSPORTS'): 36,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'STANDUPFORYOURRIGHTS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'FUCKYOU'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'GOFUNDME'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'ORDERNO'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'REPORTERSARRESTED'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'CCOT'): 10,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'GOTV'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'MATURIN'): 2,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'BROWN'): 241,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'JOURNALISM'): 4,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'SOLIDARITYWITHFERGUSON'): 4,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'LUIS_FRESH'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'WHATSHOULDBEONMYTL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'IAMTRYINGTOBELIEVE'): 2,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'WEEDLORD'): 1,\n",
+       " HashtagKey(DoM='14', Hour=23, Text=u'INDY'): 4,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'THECONFIRMATION'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'REVS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'MISSISSAUGA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'COOPERATIVE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'REDSKINS'): 2,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'OLS2014'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'ALSICECHALLENGE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'SHOOTER'): 20,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'COOLDADS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'NATURALS'): 4,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'BLACKMOTHERITIS'): 3,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NEVADA'): 2,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'REPORTERS'): 8,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'JHENEBENTOBOX'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'TEARGAS'): 8,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'PRISONPLANET'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'WAKEUPAMERICA'): 8,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'DOGECOIN'): 5,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'CONSERVATIVES'): 3,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'DONTPANIC'): 2,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'NATIONAL'): 2,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'TORNADO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'COMMONGROUNDS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'LANSING'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'ARREST'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'FUKUSHIMA'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'DRKING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'UPPERS'): 4,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'HAUSARREST'): 7,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'EDLEADERSHIP'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'ONELOVE'): 2,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'ACTNOW'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'STATETROOPERS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'UWSMC'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'MILITARIZEDPOLICE'): 12,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'CHAOS'): 11,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'WEAPONS'): 30,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'SPEAKUP'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'HYPOCRITE'): 3,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'ROBINWILLIAMS'): 31,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'TOWARDSALLYSHIPNOTAWAY'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'DREAMVILLE'): 1,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'DIIME_DANIIEL'): 5,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'LEFTBANKBOOKS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'PRAYFORPEACE'): 4,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'BUTTWITTERACTIVISMAINTREALSO'): 25,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'REBELLIOUSSOULMUSICAL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'ISLAM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'POCH'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'WELFARE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'OBAMAGOLFS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'WESTFLORISSANTAVENUE'): 2,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'HARRYPOTTER'): 5,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'DAY10'): 5,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'VOTING'): 2,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'SHAQUILLE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'WORLDWIDE'): 2,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'FR'): 1,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'AMERICANSUNDERSEIGE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'HISTORY'): 4,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'TRILLTALK'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'MUFC'): 4,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'AGENDA21'): 3,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'STOPTHERACISM'): 1,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'FEAR'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'TASHIDELEK'): 3,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'UN'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'UPPERS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'PANTSUPDONTLOOT'): 1,\n",
+       " HashtagKey(DoM='14', Hour=20, Text=u'SAD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'BUTUMADATTHEPREACHER4TAKINGUR'): 2,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'BOSTON'): 4,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'BIZ'): 2,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'PROP47'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'CITIZENS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'KNOCKOUT'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'NOVIOLENCE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'BLACKLEADERSHIP'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'CITYUNDERSEIGE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'IFTHEYGUNNEDMEDOWN'): 18,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'LAMENTE_MACABRA'): 2,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'SOSVZLA'): 2,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'BROOKLYNABRIDGED'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'DETROIT'): 9,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'CBC'): 6,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'YESDATSMYNAME'): 1,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'CENSORSHIP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'\\ub3c5\\ub9bd\\uc6b4\\ub3d9\\uac00'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'EVERYONEMATTERS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'POLICING'): 2,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'TWIBDOCKET'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'WHEREISDARRENWILSON'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'USMNT'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'TACHIRA'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'GODZILLA'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'ANON'): 9,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'WHATILEARNEDTODAY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'CROWD_CONTROL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'DDHH'): 5,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'BLACKEDU'): 5,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'DISABILITY'): 3,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'FRONTPAGES'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'BACKWOODSBADASS'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'SOUTHAFRICA'): 2,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'FERGUSOM'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'WIN'): 3,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'EARLYBIRD'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'PRAYFORTHISNIGGA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'DEVOLVE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'NOWPLAYING'): 8,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'BRAINWASHEDSOCIETY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'JOHNLEGEND'): 1,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'GAZAMILLIONMARCH'): 5,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'RELIGIONPOISONSEVERYTHING'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'YAZIDIS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'NORIOTPOLICE'): 4,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'MOMMYBLOGGER'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'FERUGSON'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'IS'): 8,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'AGENDA21'): 1,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'ITALIA'): 1,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'LIES'): 3,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'ANSWER'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'JOKE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'THERUN2016'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'MURDERISTHECASE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'NOTHINGTOSEEHERE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'ALBANYSTATE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'KMOV'): 6,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'WHITEPRIVILEGE'): 94,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'TURNOUT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'GREATERST'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'MIDDLECLASS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'BRIANRUTTENBUR'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'LAWENFORCEMENT'): 4,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'\\uce74\\ub77c'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'PHOTOJOURNALISME'): 1,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'OUTFRONT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'ICC4ISRAEL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=11, Text=u'MICHAEL'): 5,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'MURICA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'ROBOCOP'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'LLWS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'NATIONALGUARD'): 22,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'DERANGEDRADIO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'CARSI'): 2,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'NDNETWORK'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'STLOUIS'): 64,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'NOMORE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'SPECIALREPORT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'NIEUWSVIDEOS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'DOBETTER'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'TWIBDOCKET'): 3,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'BEFREE'): 3,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'BEARINGWITNESS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'UK'): 20,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'RKBA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'HIGHWAYPATROL'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'WICKED'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'TEAMYAMITA'): 13,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'GREENBRIERGUESSINGGAME'): 1,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'FEMINIST'): 24,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'INNOCENTUNTILPROVENGUILTY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'SLAVERY'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'ISDSTRONG'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'PH'): 2,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'EDL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'ANCHORAGENEWS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'ALJAZEERAAMERICA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'BIBLE'): 3,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'AC360'): 7,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'NOW'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'ENDRACISM'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'NEWORLEANS'): 4,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'FERGUSONPOLICE'): 37,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'SUPERBOWL2015'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'ATHEIST'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'OSCARGRANT'): 6,\n",
+       " HashtagKey(DoM='19', Hour=11, Text=u'STLNEEDSJIMMY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'JFK'): 3,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'CYPRUS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'MARKETINGDIGITAL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'BLACKOUT'): 2,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'TKT'): 3,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'WHITES'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'KIMANIGRAY'): 3,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'MUHAMADJABAL'): 2,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'SOLOEXIGENJUSTICIA'): 2,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'IDOL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'PALESTINE'): 1177,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'KY'): 3,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'CHANGETHEMASCOT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'LISTENLIVE'): 1,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'RHEE'): 2,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'RICKPERRY'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'THATLEADERSHIPTHO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'RIGHTTOBEARWITNESS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'CHANGE'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'TWITTERREVERB'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'FUCKMSM'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'PRESSCONFERENCEPRAYERS'): 3,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'MOMSDEMAND'): 11,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'MATTHEWDUMAS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'TEACHINGMOMENT'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'ROOTS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'NEWYORK'): 11,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'LASTRT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'MARCLAMONTHILL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'SPIRITUAL'): 2,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'EFE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'CLASHDAILY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'MINORITY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'THEGUARDIAN'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'C4NEWS'): 1,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'HASHTAG'): 2,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'WEAREALLFERGUSON'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'ISRAEL'): 10,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'EQUALITY4ALL'): 14,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'JIMCAREY'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'ECONOMIC'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'CORRUPTION'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'PEACE4ALL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'CHAROBS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'WATER'): 8,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'WEARENOTSTUPID'): 7,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'RENITALAMKIN'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'BO'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'CANWELIVE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'MOREKIDSLISTENTORAPPERSTHANCNN'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'TIMEOUT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'WHATISJUSTICE'): 4,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'STOPBYOURHOUSE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'VACCINE'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'MURDER'): 4,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'ICHTHUS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'NOWPLAYING'): 5,\n",
+       " HashtagKey(DoM='14', Hour=20, Text=u'BILLIONSOFHITSPLUSHATEMAIL'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'UCWRADIO'): 3,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'WASHINGTON'): 15,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'ISRAEL'): 22,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'FASHION'): 4,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'REVALSHARPTON'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'HERRERATEAMSWAGGA'): 2,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'DEFEATOBAMA'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'KONA'): 3,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'SEANBELL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'CUBADEBATE'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'NDN'): 2,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'WIP'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'USFCAMS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'ONKOKONSAGHTHISWEEK'): 2,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'EFF'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'PEACEFUL'): 7,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'NORTHSTL'): 197,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'LAPD'): 8,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'PHOTOGRAPHY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'ANDERLIN'): 2,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'WY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'PLDEBATT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'FREEDOMEXPRESSION'): 2,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'NEWS3'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'IS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'THISISUNREAL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'WATCHWHSV'): 2,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'NL1'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NEWSNATION'): 1,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'PUFC'): 2,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'LUIS_FRESH'): 1,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'GIUSTIZIA'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'ITHASTOSTOPNOW'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'THECEOPUNDIT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'KELLYFILE'): 81,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'FERGUS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'OOH'): 2,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'FERGUSONSHOOTING'): 83,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'WRONG'): 2,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'BADCOPS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'RAMSEYORTA'): 3,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'STEPHENCOLBERT'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'MAKINGTHESITUATIONWORSE'): 2,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'PRAYCHURCH'): 2,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'SNRTG'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'POLICEOUTOFCONTROL'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'HISHERS'): 16,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'DISGUSTING'): 2,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'ICELAND'): 3,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'RONPAULREVOLUTION'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'SHOWMECIVILRIGHTS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'ELECTIONSHAVECONSEQUENCES'): 4,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'MICHAELB'): 3,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'DIGNITY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'ANTISEMITISM'): 3,\n",
+       " HashtagKey(DoM='14', Hour=19, Text=u'CIVILWAR'): 1,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'GREEN'): 1,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'FREEDOMOFPRESS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'COP'): 5,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'NJTVNEWS'): 2,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'PEOPLEOVERPOLITICS'): 3,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'MILWAUKEE'): 832,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'RELIGIOUSFREEDOM'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'NANCYGRACE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'VENEZUELA'): 18,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'VIOLENCE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'BERITA_IN'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'HTAFC'): 1,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'GUNS'): 2,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'HASHTAG'): 34,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'REPRODUCTIVEJUSTICE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'ATHEISM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'RACHELJENTEAL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'CSPANCHAT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'BREAKINGNEWS'): 14,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'PIDEBACK'): 2,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'VOTE'): 3,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'TRUTH'): 23,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'COVERAGE'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'YASSEL10'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'STANDWITHFERGUSON'): 70,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'FERGUSON_USA'): 6,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'TIMEFORCHANGE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'WHATABOUTTHEOTHERS'): 2,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'PT'): 2,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'MAYGODBLESSTHEM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'RATM'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'MISSOURI'): 74,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'WHOISINCHARGE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'REDDIT'): 11,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'KELLYFILE'): 49,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'SANFORD'): 2,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'BETRUE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'LEOYORK'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'NBC7'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'SOSAYWEALL'): 5,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'DEMOCRACYWORKS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'KIMANIGRAY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'WALKINGDEAD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'TOPPROG'): 4,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'VOTEDEMILOVATO'): 1,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'VERMONT'): 2,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'\\xc7APULCU'): 2,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'PROBLEM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'GOP'): 8,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'JUAN_STARZ'): 1,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'PATRIOTACT'): 3,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'FEARMONGERING'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'THELASTWORD'): 12,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'ATTACKING'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'PRESIDENTBARACKOBAMA'): 3,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NERF'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'FAS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'ZOMBIES'): 4,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'FITNESS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'GOTV'): 2,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'BUNDYRANCH'): 12,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'OWSINFO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'XS'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'LEOYORK'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'HUFFPOST'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'BIGDATA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'WHYNOT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'WHATAGOATROPING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'RICKPERRY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'SONG'): 2,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'LEVITY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'ETHICSINJOURNALISM'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'CINNOIR'): 6,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'BBCNEWSNIGHT'): 6,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'WE'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'JACKBOOTS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'MILESKANE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'GENERALNEWS'): 2,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'CYA'): 1,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'CONSPIRACY'): 3,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'UCWRADIO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'MRBROWN'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'MANIFENCOURS'): 9,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'CNNENESPANOL'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'ONPOINT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'KNOWLEDGEISPOWER'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'BORDERCRISIS'): 7,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'LAW'): 3,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'TEAPAY'): 4,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'FARRAKHAN'): 23,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'RIVOLTA'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'MISSOURISHOOTING'): 2,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'SHENANIGANS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'DELUXMAGAZINE'): 6,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'GLV'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'NORTHCOUNTY'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'WESTANDUNITED'): 1,\n",
+       " HashtagKey(DoM='14', Hour=22, Text=u'INNERS'): 3,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'PEOPLESMEDIA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'POLITIE'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'PHOTO'): 1,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'RICHARDSTALLMAN'): 2,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'VOTERAPATHY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'TIBETANS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'CLEOWILLIS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'DISHFEED'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'CRITICALTHINKING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'STAYUP'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'DESTACADOS'): 12,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'ITBREAKSMYHEART'): 2,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'SUSPENSE'): 3,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'FREEANTONIOFRENCH'): 72,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'BLACKPRESIDENT'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'BADIDEA'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'NY'): 2,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'BUSH'): 2,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'GOHOME'): 2,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'YAZIDIS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'PEACECHALLENGE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'VASCANDAL'): 15,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'TSA'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'JHONSONFRESZ'): 2,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'SUPPORTCAPITALISM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'IBLOCKRACISTS'): 4,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'DUOPOLY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'MURDERINMISSOURI'): 1,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'DIVINE9'): 9,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'NOTREDAME'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'VIEWGRAPHICANGRY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'UNION'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'RESTLESSAMERICA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'STOCKMARKET'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'FOX'): 4,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'MH17'): 8,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'GODBLESS'): 4,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'MAKINAHD'): 4,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'DOIGOTTHATRIGHT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'VIRUS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'RPS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'ARRESTDARRENWILSON'): 64,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'STANDTOGETHER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'AALS2015'): 3,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'BLUEWALL'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'KNOCKOUTGAME'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'DIRTYSOUTHMAFIA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'SHABAZZ'): 2,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'EMERGENCY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'PRAYER'): 2,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'JUSTICEFORMICHAEL'): 11,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'YOUTUBENATION'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'SFGIANTS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'COLONIALUCC'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'GRAMFAM'): 2,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'JAX'): 2,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'KNX'): 2,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'FRANTI'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'SOCIAL'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'JOBS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'FOOD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'TBT'): 13,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'HUMANRIGHTS'): 6,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'DARRENWILLSON'): 2,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'COPS'): 17,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'SAYFIE'): 4,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'SOLIDARITYFORFERGUSON'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'THINKINGOUTLOUD'): 2,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'HOMEOFTHEBRAVE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NEWSTICA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'MOEDCHAT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'TAKEMEOUTSA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'PEWRESEARCH'): 1,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'KOOLAID'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'DITCHMITCH'): 2,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'\\xc9MEUTES'): 1,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'VIOLENCE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'UNITEDSTATESOFOPPRESSION'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'BUSINESS'): 38,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'WTH'): 33,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'CLEOWILLIS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'DIW'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'CONSERVATIVEVIDEOS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'INTERNATIONAL'): 2,\n",
+       " ...}"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ReadAndAggregateIntervals(100000, filename, aggregateHashtags)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/.ipynb_checkpoints/Spatial_Representations-checkpoint.ipynb b/.ipynb_checkpoints/Spatial_Representations-checkpoint.ipynb
new file mode 100644
index 0000000..57ca093
--- /dev/null
+++ b/.ipynb_checkpoints/Spatial_Representations-checkpoint.ipynb
@@ -0,0 +1,338 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Mapping Twitter Data\n",
+    "This notebook provides the basis for developing spatial representations of a variety of interesting data that is presented in the Ferguson Twitter dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "% matplotlib inline\n",
+    "import json\n",
+    "import time\n",
+    "import pandas as pd\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's begin with the data. We have two datasets. The first is data from the two weeks following the initial shooting. The second is data from the two weeks following the indictment. Twitter has provided an extensive amount of data for us, and we have developed a cleaning mechanism which can be observed in a seperate script. The data is placed in a data frame:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def make_frame(filename,low_bound,high_bound):\n",
+    "    data = []\n",
+    "    i = 0\n",
+    "    #For now only want to read in a few lines of this file (about 100000 tweets)\n",
+    "    start = time.time()\n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            if i > low_bound and i < high_bound:\n",
+    "                jsonline = json.loads(tweet)\n",
+    "                data.append(jsonline)\n",
+    "            elif i > high_bound:\n",
+    "                break\n",
+    "    return data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "filename='./data/cleanedShootingTweets.json'\n",
+    "data = make_frame(filename,100000,200000)\n",
+    "df = pd.DataFrame(data=data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 9999 entries, 0 to 9998\n",
+      "Data columns (total 59 columns):\n",
+      "contributors                            0 non-null object\n",
+      "coordinates                             63 non-null object\n",
+      "created_at                              9999 non-null object\n",
+      "entities_hashtags_0_text                0 non-null float64\n",
+      "entities_hashtags_1_text                0 non-null float64\n",
+      "entities_hashtags_2_text                0 non-null float64\n",
+      "entities_hashtags_3_text                0 non-null float64\n",
+      "entities_hashtags_4_text                0 non-null float64\n",
+      "entities_hashtags_5_text                0 non-null float64\n",
+      "entities_hashtags_6_text                0 non-null float64\n",
+      "entities_hashtags_7_text                0 non-null float64\n",
+      "entities_hashtags_8_text                0 non-null float64\n",
+      "entities_hashtags_9_text                0 non-null float64\n",
+      "entities_user_mentions_0_id_str         0 non-null float64\n",
+      "entities_user_mentions_0_screen_name    0 non-null float64\n",
+      "entities_user_mentions_1_id_str         0 non-null float64\n",
+      "entities_user_mentions_1_screen_name    0 non-null float64\n",
+      "entities_user_mentions_2_id_str         0 non-null float64\n",
+      "entities_user_mentions_2_screen_name    0 non-null float64\n",
+      "entities_user_mentions_3_id_str         0 non-null float64\n",
+      "entities_user_mentions_3_screen_name    0 non-null float64\n",
+      "entities_user_mentions_4_id_str         0 non-null float64\n",
+      "entities_user_mentions_4_screen_name    0 non-null float64\n",
+      "entities_user_mentions_5_id_str         0 non-null float64\n",
+      "entities_user_mentions_5_screen_name    0 non-null float64\n",
+      "entities_user_mentions_6_id_str         0 non-null float64\n",
+      "entities_user_mentions_6_screen_name    0 non-null float64\n",
+      "entities_user_mentions_7_id_str         0 non-null float64\n",
+      "entities_user_mentions_7_screen_name    0 non-null float64\n",
+      "entities_user_mentions_8_id_str         0 non-null float64\n",
+      "entities_user_mentions_8_screen_name    0 non-null float64\n",
+      "entities_user_mentions_9_id_str         0 non-null float64\n",
+      "entities_user_mentions_9_screen_name    0 non-null float64\n",
+      "favorite_count                          9999 non-null int64\n",
+      "geo                                     63 non-null object\n",
+      "id_str                                  9999 non-null object\n",
+      "in_reply_to_status_id_str               376 non-null object\n",
+      "in_reply_to_user_id_str                 452 non-null object\n",
+      "is_quote_status                         9999 non-null bool\n",
+      "place                                   80 non-null object\n",
+      "possibly_sensitive                      6596 non-null object\n",
+      "retweet_count                           9999 non-null int64\n",
+      "retweeted                               9999 non-null bool\n",
+      "source                                  9999 non-null object\n",
+      "text                                    9999 non-null object\n",
+      "user_contributors_enabled               9999 non-null bool\n",
+      "user_created_at                         9999 non-null object\n",
+      "user_followers_count                    9999 non-null int64\n",
+      "user_friends_count                      9999 non-null int64\n",
+      "user_geo_enabled                        9999 non-null bool\n",
+      "user_id_str                             9999 non-null object\n",
+      "user_is_translation_enabled             9999 non-null bool\n",
+      "user_lang                               9999 non-null object\n",
+      "user_listed_count                       9999 non-null int64\n",
+      "user_location                           9999 non-null object\n",
+      "user_screen_name                        9999 non-null object\n",
+      "user_time_zone                          8001 non-null object\n",
+      "user_utc_offset                         8001 non-null float64\n",
+      "user_verified                           9999 non-null bool\n",
+      "dtypes: bool(6), float64(31), int64(5), object(17)\n",
+      "memory usage: 4.2+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are several fields which we find particularly interesting here, namely the time and all place related fields. To better help us process this data in this notebook, we create new columns which breaks out created_at, coordinates and place."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#time based recodes\n",
+    "df['DoW'] = df['created_at'].apply(lambda x: str(x)[0:3:])\n",
+    "df['Month'] = df['created_at'].apply(lambda x: str(x)[4:7:])\n",
+    "df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])\n",
+    "df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))\n",
+    "df['Minute'] = df['created_at'].apply(lambda x: int(str(x)[14:16:]))\n",
+    "\n",
+    "#let's grab the coordinates from the coordinates field, which is actually a dictionary\n",
+    "coords = []\n",
+    "for i in range(len(df)):\n",
+    "    location = df['coordinates'][i]\n",
+    "    try: #want to make sure that null values don't throw an exception\n",
+    "        coords.append(location.get('coordinates'))\n",
+    "    except:\n",
+    "        coords.append([0,0])\n",
+    "\n",
+    "df['Coords'] = coords\n",
+    "df['x'] = df['Coords'].apply(lambda x: x[0])\n",
+    "df['y'] = df['Coords'].apply(lambda x: x[1])\n",
+    "\n",
+    "#now, let's grab the information from place, which is similarly a very detailed dictionary of elements\n",
+    "name = []\n",
+    "country = []\n",
+    "coordinates = []\n",
+    "full_name = []\n",
+    "for i in range(len(df)):\n",
+    "    location = df['place'][i]\n",
+    "    try:\n",
+    "        coordinates.append(location.get('bounding_box').get('coordinates'))\n",
+    "        name.append(location.get('name'))\n",
+    "        full_name.append(location.get('full_name'))\n",
+    "        country.append(location.get('country'))\n",
+    "    except:\n",
+    "        coordinates.append([[[0,0],[0,0],[0,0],[0,0]]])\n",
+    "        name.append('')\n",
+    "        full_name.append('')\n",
+    "        country.append('')\n",
+    "\n",
+    "mean_coords = []\n",
+    "for box in coordinates:\n",
+    "    mean_coord_x = (box[0][0][0]+box[0][1][0]+box[0][2][0]+box[0][3][0])/4\n",
+    "    mean_coord_y = (box[0][0][1]+box[0][1][1]+box[0][2][1]+box[0][3][1])/4\n",
+    "    mean_coords.append([mean_coord_x,mean_coord_y])\n",
+    "\n",
+    "df['city'] = name\n",
+    "df['country'] = country\n",
+    "df['full_name'] = full_name\n",
+    "df['P_Coords'] = mean_coords\n",
+    "df['x_p'] = df['P_Coords'].apply(lambda x: x[0])\n",
+    "df['y_p'] = df['P_Coords'].apply(lambda x: x[1])\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that the data is all set, let's start looking at it. Using a library called [cartopy](http://scitools.org.uk/cartopy/), we can grab a really simple map to use to put everything in perspective."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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RI0egrKwMgUAAS0tLrFq1SmKqKmr+kyvSvkXGXUYs4MIg1kzsIZ4MUc8m8zfD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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f52dc4f1f10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#the cartopy map, going simple outline for now\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "\n",
+    "#straight-up coordinate data which we just finished recoding\n",
+    "plt.scatter(df.x,df.y,color='r')\n",
+    "plt.scatter(df.x_p,df.y_p,color='g')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, to add a temporal element to this, we add a slider which pulls in some of the time columns we also just pulled out of interest."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def plotLocation(Hour,Minute):\n",
+    "    plt.figure(figsize=(15,15))\n",
+    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "    ax.coastlines()\n",
+    "    plt.scatter(df.x[(df['Hour']==Hour) & (df['Minute']==Minute)],df.y[(df['Hour']==Hour) & (df['Minute']==Minute)],color='r')\n",
+    "    plt.scatter(df.x_p[(df['Hour']==Hour) & (df['Minute']==Minute)],df.y_p[(df['Hour']==Hour) &  (df['Minute']==Minute)],color='g')\n",
+    "    plt.axis([-180, 180, -75, 75])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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vv/+e2R39VDgcDhwcHKCrq4tjx4591q16VVVVDBkyBPb29rCwsEBubi7i4+MR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ZGB42JHyM+TB/QAnAZwA5BoI4GU4hQRp/s4nCccaO/QxjeBVtDeoQ3O04/fV4Yv/f9hA+1tWuDc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ERkbSt29fDh48yJUrV6hXrx4AJSUlfPTRR+zatYvjx4+Xy+sN/5es5idEDeLn58fjx49p1KgR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\nTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f52b1f62990>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "Hour = widgets.IntSlider(min=0, max=23, value=21)\n",
+    "Minute = widgets.IntSlider(min=0, max=59, value=7)\n",
+    "widgets.interact(plotLocation,Hour=Hour,Minute=Minute)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/.ipynb_checkpoints/Verified_Users-checkpoint.ipynb b/.ipynb_checkpoints/Verified_Users-checkpoint.ipynb
new file mode 100644
index 0000000..3622e6d
--- /dev/null
+++ b/.ipynb_checkpoints/Verified_Users-checkpoint.ipynb
@@ -0,0 +1,2368 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Verified Users - Do Celebs and News Outlets Go Measurably Viral?\n",
+    "This notebook provides the basis for developing spatial representations of a variety of interesting data that is presented in the Ferguson Twitter dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "% matplotlib inline\n",
+    "import json\n",
+    "import time\n",
+    "import pandas as pd\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets\n",
+    "import matplotlib.cm as cm\n",
+    "import datetime"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's begin with the data. We have two datasets. The first is data from the two weeks following the initial shooting. The second is data from the two weeks following the indictment. Twitter has provided an extensive amount of data for us, and we have developed a cleaning mechanism which can be observed in a seperate script. The data is placed in a data frame:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def ReadAndAggregate(linesAtATime,filepath, aggregationFunction):\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print i\n",
+    "                df = pd.DataFrame(data=data)\n",
+    "                #First time running through\n",
+    "                if (i == linesAtATime):\n",
+    "                    agg = aggregationFunction(df)\n",
+    "                else:\n",
+    "                    agg = aggregationFunction(df, agg)\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "        #Handle the last few tweets\n",
+    "        df = pd.DataFrame(data=data)\n",
+    "        agg = aggregationFunction(df, agg)\n",
+    "    #return the aggregation\n",
+    "    return agg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def getDateInfo (df, hashtagsDataFrame=pd.DataFrame()):\n",
+    "    \n",
+    "    #time based recodes\n",
+    "    df['DoW'] = df['created_at'].apply(lambda x: str(x)[0:3:])\n",
+    "    df['Month'] = df['created_at'].apply(lambda x: str(x)[4:7:])\n",
+    "    df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])\n",
+    "    df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))\n",
+    "    df['Minute'] = df['created_at'].apply(lambda x: int(str(x)[14:16:]))\n",
+    "\n",
+    "    \n",
+    "    hashtagsDataFrame = hashtagsDataFrame.append(df)\n",
+    "\n",
+    "    return hashtagsDataFrame"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100000\n",
+      "200000\n",
+      "300000\n",
+      "400000\n",
+      "500000\n",
+      "600000\n",
+      "700000\n",
+      "800000\n",
+      "900000\n",
+      "1000000\n",
+      "1100000\n",
+      "1200000\n",
+      "1300000\n",
+      "1400000\n",
+      "1500000\n",
+      "1600000\n",
+      "1700000\n",
+      "1800000\n",
+      "1900000\n",
+      "2000000\n",
+      "2100000\n",
+      "2200000\n",
+      "2300000\n",
+      "2400000\n",
+      "2500000\n",
+      "2600000\n",
+      "2700000\n",
+      "2800000\n",
+      "2900000\n",
+      "3000000\n",
+      "3100000\n",
+      "3200000\n",
+      "3300000\n",
+      "3400000\n",
+      "3500000\n",
+      "3600000\n",
+      "3700000\n",
+      "3800000\n",
+      "3900000\n"
+     ]
+    }
+   ],
+   "source": [
+    "filename='./data/cleanedShootingTweets.json'\n",
+    "data = ReadAndAggregate(100000,filename, getDateInfo)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>contributors</th>\n",
+       "      <th>coordinates</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>favorite_count</th>\n",
+       "      <th>geo</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>in_reply_to_status_id_str</th>\n",
+       "      <th>...</th>\n",
+       "      <th>user_location</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_time_zone</th>\n",
+       "      <th>user_utc_offset</th>\n",
+       "      <th>user_verified</th>\n",
+       "      <th>DoW</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>DoM</th>\n",
+       "      <th>Hour</th>\n",
+       "      <th>Minute</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:52:55 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064141332029440</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Estados Unidos</td>\n",
+       "      <td>20mUsa</td>\n",
+       "      <td>Athens</td>\n",
+       "      <td>7200</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>52</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:02 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[295988417]</td>\n",
+       "      <td>[NerdyNegress]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064171707170816</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>None Of Your Business</td>\n",
+       "      <td>MzDivah67</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:04 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[295988417]</td>\n",
+       "      <td>[NerdyNegress]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064180468682752</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>BrookLyn1825</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064188211765249</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Virginia Beach</td>\n",
+       "      <td>I_Mpower</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:07 +0000 2014</td>\n",
+       "      <td>[USNews]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064194309906436</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Vorarlberg1</td>\n",
+       "      <td>Vienna</td>\n",
+       "      <td>3600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[90296594]</td>\n",
+       "      <td>[Thatindianbruh]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064196642340864</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>rachel_palomera</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, MikeBrown]</td>\n",
+       "      <td>[18989941]</td>\n",
+       "      <td>[BgRs]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064196931330049</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>California</td>\n",
+       "      <td>bookishshelly</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064197396914176</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>deegerwiilen</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, tcot, uniteblue, teaparty, gop]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>mmaureen7</td>\n",
+       "      <td>Newfoundland</td>\n",
+       "      <td>-12600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, CrimeButNoTime]</td>\n",
+       "      <td>[935015863]</td>\n",
+       "      <td>[bryancrumpler]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064198009655296</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>London</td>\n",
+       "      <td>collettehodson</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[3385611074]</td>\n",
+       "      <td>[ImNotTwitFamous]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064198059597824</td>\n",
+       "      <td>499992352505610240</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>offlyniceteam</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[93963456, 573764891]</td>\n",
+       "      <td>[trymainelee, OTMBrooke]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064198513000450</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>New York</td>\n",
+       "      <td>carminemac</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064198973960192</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>SlavinOleg</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>-25200</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson, PoliceBrutality]</td>\n",
+       "      <td>[755113]</td>\n",
+       "      <td>[ShaunKing]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064199142117378</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Free2Pursue</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[20864257]</td>\n",
+       "      <td>[chrisalexander_]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064200035516416</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>summer polar vortex</td>\n",
+       "      <td>SadieODoyle</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064200186118145</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Liberal progessive in Austin,</td>\n",
+       "      <td>Ssragona</td>\n",
+       "      <td>Central Time (US &amp; Canada)</td>\n",
+       "      <td>-21600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064200316125184</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Schweizer_Kotau</td>\n",
+       "      <td>Amsterdam</td>\n",
+       "      <td>3600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[325076723]</td>\n",
+       "      <td>[zellieimani]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064201041743872</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>detroit</td>\n",
+       "      <td>bonxvivant</td>\n",
+       "      <td>Central Time (US &amp; Canada)</td>\n",
+       "      <td>-21600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[217663500]</td>\n",
+       "      <td>[locoernesto]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064201251880961</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Somewhere w/ my sister Mooder</td>\n",
+       "      <td>mickysowavy</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[279390084]</td>\n",
+       "      <td>[YourAnonNews]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064201256071168</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Enigmatic Cloud 9</td>\n",
+       "      <td>Katyria90</td>\n",
+       "      <td>Atlantic Time (Canada)</td>\n",
+       "      <td>-14400</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[MikeBrown, Ferguson]</td>\n",
+       "      <td>[97273575, 369507958]</td>\n",
+       "      <td>[Clarknt67, wethepeople]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064201503113216</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Little Rock, AR</td>\n",
+       "      <td>bennharr</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[3385611074]</td>\n",
+       "      <td>[ImNotTwitFamous]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064202245521409</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>king gio</td>\n",
+       "      <td>Jaela_mb</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>-25200</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[6273552]</td>\n",
+       "      <td>[MCHammer]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064202295848960</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Blackberryccr</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[1381926373]</td>\n",
+       "      <td>[YourAnonGlobal]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064202380115971</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>bebird</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064202794971136</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>SlavinOleg</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>-25200</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[1917731, 369534928]</td>\n",
+       "      <td>[thehill, PeterSullivan4]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064202904403970</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Columbus, Ohio</td>\n",
+       "      <td>DrJLMooreIII</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:10 +0000 2014</td>\n",
+       "      <td>[Ferguson, StandWithFerguson, HandsUpDontShoot...</td>\n",
+       "      <td>[2984310527]</td>\n",
+       "      <td>[queerdorable]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064203135102977</td>\n",
+       "      <td>501063920187346945</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>kavn</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:10 +0000 2014</td>\n",
+       "      <td>[FergusonShooting, Ferguson]</td>\n",
+       "      <td>[237606548]</td>\n",
+       "      <td>[3ChicsPolitico]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064203508412416</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Star City....till I wreck it</td>\n",
+       "      <td>ArrogantDemon</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:10 +0000 2014</td>\n",
+       "      <td>[Ferguson, BLACKMEDIA, TWIBnation]</td>\n",
+       "      <td>[1716581]</td>\n",
+       "      <td>[elonjames]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064204288540672</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>MHT &amp; NYC</td>\n",
+       "      <td>profbrady</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:10 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064204661850113</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>ahhthatswhy</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50687</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321707634688001</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>PattoFaustiano</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50688</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321707655639040</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>United States</td>\n",
+       "      <td>nanopatents</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50689</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321707676602368</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Orgelmir</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50690</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321707966025728</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Virgo Supercluster</td>\n",
+       "      <td>DeadPrecariat</td>\n",
+       "      <td>Quito</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50691</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708007559168</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Nakuru</td>\n",
+       "      <td>Swamkidd</td>\n",
+       "      <td>Quito</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50692</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[309379296]</td>\n",
+       "      <td>[LuhhNate]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708322131968</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Hilltop</td>\n",
+       "      <td>PakistanBre</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50693</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708322553856</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>JoeOKerr</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50694</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708456747008</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Syracuse, NY</td>\n",
+       "      <td>YourBlackWorld</td>\n",
+       "      <td>Central Time (US &amp; Canada)</td>\n",
+       "      <td>-21600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50695</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708465135616</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>KultureKritic</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50696</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708465143808</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>AelitaQueen</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50697</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708544847872</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Reason4Rhymes</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50698</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708645498880</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>beforeitsnews</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50699</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>5</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708900970496</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Wilkes-Barre, PA</td>\n",
+       "      <td>rcooley123</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50700</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:03 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[2320513861]</td>\n",
+       "      <td>[suddeneternity]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321710717091841</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Lethbridge AB</td>\n",
+       "      <td>UncleRee1</td>\n",
+       "      <td>Mountain Time (US &amp; Canada)</td>\n",
+       "      <td>-25200</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50701</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:03 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[2471925444]</td>\n",
+       "      <td>[YABOYYDEQUAN]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321712201859073</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Columbus, GA</td>\n",
+       "      <td>_TaeKemp</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>-25200</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50702</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:03 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[156743986, 15808218]</td>\n",
+       "      <td>[_esaliba, kgosztola]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321712386416640</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Bellingham, WA</td>\n",
+       "      <td>profjournalista</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50703</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:03 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321713431207937</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Brooklyn, NY</td>\n",
+       "      <td>LiveAndAscend</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50704</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:04 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[376109186]</td>\n",
+       "      <td>[occbaystreet]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321714236502017</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Buffalo Valley,  Tennessee</td>\n",
+       "      <td>blaha_b</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50705</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:04 +0000 2014</td>\n",
+       "      <td>[ferguson]</td>\n",
+       "      <td>[534675241]</td>\n",
+       "      <td>[Dreamdefenders]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321715574079488</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Singapore</td>\n",
+       "      <td>pjan_stellar</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50706</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:04 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[1963823209]</td>\n",
+       "      <td>[PeopIe]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321716652433408</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>ma</td>\n",
+       "      <td>a_filipiak</td>\n",
+       "      <td>Atlantic Time (Canada)</td>\n",
+       "      <td>-14400</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50707</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[HandsUpDontShoot]</td>\n",
+       "      <td>[69326792, 551947957, 373738053]</td>\n",
+       "      <td>[MaryMurrayNBC, BonBonBreak, momsnewstage]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321718443380737</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>A QUIRKY YANKEE IN THE SOUTH</td>\n",
+       "      <td>SheDoesArtWow</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50708</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[FergusonShooting, Ferguson, FergusonRiot]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321718443388928</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Florida Wig Stand</td>\n",
+       "      <td>MsBrownsWig</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50709</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[61907338]</td>\n",
+       "      <td>[joenewsman]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321718950903808</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Tryna get to a beach ✨</td>\n",
+       "      <td>hoochieuche</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50710</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[FERGUSON]</td>\n",
+       "      <td>[47856658]</td>\n",
+       "      <td>[hotwata]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321718971469824</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Elberton , Ga</td>\n",
+       "      <td>Ducedoh</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50711</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[1367531]</td>\n",
+       "      <td>[FoxNews]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321719257079808</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>America the Beautiful, Oregon</td>\n",
+       "      <td>Cate_Tweeting</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50712</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321719429050368</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Charleston, WV</td>\n",
+       "      <td>TheMaseMan</td>\n",
+       "      <td>Atlantic Time (Canada)</td>\n",
+       "      <td>-14400</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50713</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[496679549]</td>\n",
+       "      <td>[TheJarell]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321719734841344</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>getoffmylawn80</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50714</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[11740172]</td>\n",
+       "      <td>[charlesjaco1]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321719999483904</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>bitcoinmom</td>\n",
+       "      <td>Central Time (US &amp; Canada)</td>\n",
+       "      <td>-21600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50715</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321720892854273</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>syracuse</td>\n",
+       "      <td>drboycewatkins1</td>\n",
+       "      <td>Central Time (US &amp; Canada)</td>\n",
+       "      <td>-21600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50716</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321721085812736</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>yourblackgossip</td>\n",
+       "      <td>Quito</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3950717 rows × 37 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      contributors coordinates                      created_at  \\\n",
+       "0             None        None  Sun Aug 17 17:52:55 +0000 2014   \n",
+       "1             None        None  Sun Aug 17 17:53:02 +0000 2014   \n",
+       "2             None        None  Sun Aug 17 17:53:04 +0000 2014   \n",
+       "3             None        None  Sun Aug 17 17:53:06 +0000 2014   \n",
+       "4             None        None  Sun Aug 17 17:53:07 +0000 2014   \n",
+       "5             None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "6             None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "7             None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "8             None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "9             None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "10            None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "11            None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "12            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "13            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "14            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "15            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "16            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "17            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "18            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "19            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "20            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "21            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "22            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "23            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "24            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "25            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "26            None        None  Sun Aug 17 17:53:10 +0000 2014   \n",
+       "27            None        None  Sun Aug 17 17:53:10 +0000 2014   \n",
+       "28            None        None  Sun Aug 17 17:53:10 +0000 2014   \n",
+       "29            None        None  Sun Aug 17 17:53:10 +0000 2014   \n",
+       "...            ...         ...                             ...   \n",
+       "50687         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50688         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50689         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50690         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50691         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50692         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50693         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50694         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50695         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50696         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50697         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50698         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50699         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50700         None        None  Thu Aug 21 05:10:03 +0000 2014   \n",
+       "50701         None        None  Thu Aug 21 05:10:03 +0000 2014   \n",
+       "50702         None        None  Thu Aug 21 05:10:03 +0000 2014   \n",
+       "50703         None        None  Thu Aug 21 05:10:03 +0000 2014   \n",
+       "50704         None        None  Thu Aug 21 05:10:04 +0000 2014   \n",
+       "50705         None        None  Thu Aug 21 05:10:04 +0000 2014   \n",
+       "50706         None        None  Thu Aug 21 05:10:04 +0000 2014   \n",
+       "50707         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50708         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50709         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50710         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50711         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50712         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50713         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50714         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50715         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50716         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "\n",
+       "                                  entities_hashtags_text  \\\n",
+       "0                                             [Ferguson]   \n",
+       "1                                             [Ferguson]   \n",
+       "2                                             [Ferguson]   \n",
+       "3                                                     []   \n",
+       "4                                               [USNews]   \n",
+       "5                                             [Ferguson]   \n",
+       "6                                  [Ferguson, MikeBrown]   \n",
+       "7                                                     []   \n",
+       "8             [Ferguson, tcot, uniteblue, teaparty, gop]   \n",
+       "9                             [Ferguson, CrimeButNoTime]   \n",
+       "10                                            [Ferguson]   \n",
+       "11                                                    []   \n",
+       "12                                                    []   \n",
+       "13                           [Ferguson, PoliceBrutality]   \n",
+       "14                                            [Ferguson]   \n",
+       "15                                                    []   \n",
+       "16                                                    []   \n",
+       "17                                            [Ferguson]   \n",
+       "18                                            [Ferguson]   \n",
+       "19                                            [Ferguson]   \n",
+       "20                                 [MikeBrown, Ferguson]   \n",
+       "21                                            [Ferguson]   \n",
+       "22                                            [Ferguson]   \n",
+       "23                                            [Ferguson]   \n",
+       "24                                                    []   \n",
+       "25                                                    []   \n",
+       "26     [Ferguson, StandWithFerguson, HandsUpDontShoot...   \n",
+       "27                          [FergusonShooting, Ferguson]   \n",
+       "28                    [Ferguson, BLACKMEDIA, TWIBnation]   \n",
+       "29                                                    []   \n",
+       "...                                                  ...   \n",
+       "50687                                                 []   \n",
+       "50688                                                 []   \n",
+       "50689                                                 []   \n",
+       "50690                                         [Ferguson]   \n",
+       "50691                                                 []   \n",
+       "50692                                                 []   \n",
+       "50693                                                 []   \n",
+       "50694                                                 []   \n",
+       "50695                                                 []   \n",
+       "50696                                                 []   \n",
+       "50697                                                 []   \n",
+       "50698                                                 []   \n",
+       "50699                                                 []   \n",
+       "50700                                         [Ferguson]   \n",
+       "50701                                         [Ferguson]   \n",
+       "50702                                         [Ferguson]   \n",
+       "50703                                                 []   \n",
+       "50704                                         [Ferguson]   \n",
+       "50705                                         [ferguson]   \n",
+       "50706                                         [Ferguson]   \n",
+       "50707                                 [HandsUpDontShoot]   \n",
+       "50708         [FergusonShooting, Ferguson, FergusonRiot]   \n",
+       "50709                                         [Ferguson]   \n",
+       "50710                                         [FERGUSON]   \n",
+       "50711                                                 []   \n",
+       "50712                                                 []   \n",
+       "50713                                         [Ferguson]   \n",
+       "50714                                                 []   \n",
+       "50715                                                 []   \n",
+       "50716                                                 []   \n",
+       "\n",
+       "          entities_user_mentions_id_str  \\\n",
+       "0                                    []   \n",
+       "1                           [295988417]   \n",
+       "2                           [295988417]   \n",
+       "3                                    []   \n",
+       "4                                    []   \n",
+       "5                            [90296594]   \n",
+       "6                            [18989941]   \n",
+       "7                                    []   \n",
+       "8                                    []   \n",
+       "9                           [935015863]   \n",
+       "10                         [3385611074]   \n",
+       "11                [93963456, 573764891]   \n",
+       "12                                   []   \n",
+       "13                             [755113]   \n",
+       "14                           [20864257]   \n",
+       "15                                   []   \n",
+       "16                                   []   \n",
+       "17                          [325076723]   \n",
+       "18                          [217663500]   \n",
+       "19                          [279390084]   \n",
+       "20                [97273575, 369507958]   \n",
+       "21                         [3385611074]   \n",
+       "22                            [6273552]   \n",
+       "23                         [1381926373]   \n",
+       "24                                   []   \n",
+       "25                 [1917731, 369534928]   \n",
+       "26                         [2984310527]   \n",
+       "27                          [237606548]   \n",
+       "28                            [1716581]   \n",
+       "29                                   []   \n",
+       "...                                 ...   \n",
+       "50687                                []   \n",
+       "50688                                []   \n",
+       "50689                                []   \n",
+       "50690                                []   \n",
+       "50691                                []   \n",
+       "50692                       [309379296]   \n",
+       "50693                                []   \n",
+       "50694                                []   \n",
+       "50695                                []   \n",
+       "50696                                []   \n",
+       "50697                                []   \n",
+       "50698                                []   \n",
+       "50699                                []   \n",
+       "50700                      [2320513861]   \n",
+       "50701                      [2471925444]   \n",
+       "50702             [156743986, 15808218]   \n",
+       "50703                                []   \n",
+       "50704                       [376109186]   \n",
+       "50705                       [534675241]   \n",
+       "50706                      [1963823209]   \n",
+       "50707  [69326792, 551947957, 373738053]   \n",
+       "50708                                []   \n",
+       "50709                        [61907338]   \n",
+       "50710                        [47856658]   \n",
+       "50711                         [1367531]   \n",
+       "50712                                []   \n",
+       "50713                       [496679549]   \n",
+       "50714                        [11740172]   \n",
+       "50715                                []   \n",
+       "50716                                []   \n",
+       "\n",
+       "               entities_user_mentions_screen_name  favorite_count   geo  \\\n",
+       "0                                              []               0  None   \n",
+       "1                                  [NerdyNegress]               0  None   \n",
+       "2                                  [NerdyNegress]               0  None   \n",
+       "3                                              []               0  None   \n",
+       "4                                              []               0  None   \n",
+       "5                                [Thatindianbruh]               0  None   \n",
+       "6                                          [BgRs]               0  None   \n",
+       "7                                              []               0  None   \n",
+       "8                                              []               0  None   \n",
+       "9                                 [bryancrumpler]               0  None   \n",
+       "10                              [ImNotTwitFamous]               0  None   \n",
+       "11                       [trymainelee, OTMBrooke]               0  None   \n",
+       "12                                             []               0  None   \n",
+       "13                                    [ShaunKing]               0  None   \n",
+       "14                              [chrisalexander_]               0  None   \n",
+       "15                                             []               0  None   \n",
+       "16                                             []               0  None   \n",
+       "17                                  [zellieimani]               0  None   \n",
+       "18                                  [locoernesto]               0  None   \n",
+       "19                                 [YourAnonNews]               0  None   \n",
+       "20                       [Clarknt67, wethepeople]               0  None   \n",
+       "21                              [ImNotTwitFamous]               0  None   \n",
+       "22                                     [MCHammer]               0  None   \n",
+       "23                               [YourAnonGlobal]               0  None   \n",
+       "24                                             []               0  None   \n",
+       "25                      [thehill, PeterSullivan4]               0  None   \n",
+       "26                                 [queerdorable]               1  None   \n",
+       "27                               [3ChicsPolitico]               0  None   \n",
+       "28                                    [elonjames]               0  None   \n",
+       "29                                             []               0  None   \n",
+       "...                                           ...             ...   ...   \n",
+       "50687                                          []               0  None   \n",
+       "50688                                          []               0  None   \n",
+       "50689                                          []               0  None   \n",
+       "50690                                          []               0  None   \n",
+       "50691                                          []               0  None   \n",
+       "50692                                  [LuhhNate]               0  None   \n",
+       "50693                                          []               0  None   \n",
+       "50694                                          []               1  None   \n",
+       "50695                                          []               0  None   \n",
+       "50696                                          []               0  None   \n",
+       "50697                                          []               0  None   \n",
+       "50698                                          []               1  None   \n",
+       "50699                                          []               5  None   \n",
+       "50700                            [suddeneternity]               0  None   \n",
+       "50701                              [YABOYYDEQUAN]               0  None   \n",
+       "50702                       [_esaliba, kgosztola]               0  None   \n",
+       "50703                                          []               0  None   \n",
+       "50704                              [occbaystreet]               0  None   \n",
+       "50705                            [Dreamdefenders]               0  None   \n",
+       "50706                                    [PeopIe]               0  None   \n",
+       "50707  [MaryMurrayNBC, BonBonBreak, momsnewstage]               0  None   \n",
+       "50708                                          []               0  None   \n",
+       "50709                                [joenewsman]               0  None   \n",
+       "50710                                   [hotwata]               0  None   \n",
+       "50711                                   [FoxNews]               0  None   \n",
+       "50712                                          []               1  None   \n",
+       "50713                                 [TheJarell]               0  None   \n",
+       "50714                              [charlesjaco1]               0  None   \n",
+       "50715                                          []               0  None   \n",
+       "50716                                          []               0  None   \n",
+       "\n",
+       "                   id_str in_reply_to_status_id_str  ...    \\\n",
+       "0      501064141332029440                      None  ...     \n",
+       "1      501064171707170816                      None  ...     \n",
+       "2      501064180468682752                      None  ...     \n",
+       "3      501064188211765249                      None  ...     \n",
+       "4      501064194309906436                      None  ...     \n",
+       "5      501064196642340864                      None  ...     \n",
+       "6      501064196931330049                      None  ...     \n",
+       "7      501064197396914176                      None  ...     \n",
+       "8      501064197632167936                      None  ...     \n",
+       "9      501064198009655296                      None  ...     \n",
+       "10     501064198059597824        499992352505610240  ...     \n",
+       "11     501064198513000450                      None  ...     \n",
+       "12     501064198973960192                      None  ...     \n",
+       "13     501064199142117378                      None  ...     \n",
+       "14     501064200035516416                      None  ...     \n",
+       "15     501064200186118145                      None  ...     \n",
+       "16     501064200316125184                      None  ...     \n",
+       "17     501064201041743872                      None  ...     \n",
+       "18     501064201251880961                      None  ...     \n",
+       "19     501064201256071168                      None  ...     \n",
+       "20     501064201503113216                      None  ...     \n",
+       "21     501064202245521409                      None  ...     \n",
+       "22     501064202295848960                      None  ...     \n",
+       "23     501064202380115971                      None  ...     \n",
+       "24     501064202794971136                      None  ...     \n",
+       "25     501064202904403970                      None  ...     \n",
+       "26     501064203135102977        501063920187346945  ...     \n",
+       "27     501064203508412416                      None  ...     \n",
+       "28     501064204288540672                      None  ...     \n",
+       "29     501064204661850113                      None  ...     \n",
+       "...                   ...                       ...  ...     \n",
+       "50687  502321707634688001                      None  ...     \n",
+       "50688  502321707655639040                      None  ...     \n",
+       "50689  502321707676602368                      None  ...     \n",
+       "50690  502321707966025728                      None  ...     \n",
+       "50691  502321708007559168                      None  ...     \n",
+       "50692  502321708322131968                      None  ...     \n",
+       "50693  502321708322553856                      None  ...     \n",
+       "50694  502321708456747008                      None  ...     \n",
+       "50695  502321708465135616                      None  ...     \n",
+       "50696  502321708465143808                      None  ...     \n",
+       "50697  502321708544847872                      None  ...     \n",
+       "50698  502321708645498880                      None  ...     \n",
+       "50699  502321708900970496                      None  ...     \n",
+       "50700  502321710717091841                      None  ...     \n",
+       "50701  502321712201859073                      None  ...     \n",
+       "50702  502321712386416640                      None  ...     \n",
+       "50703  502321713431207937                      None  ...     \n",
+       "50704  502321714236502017                      None  ...     \n",
+       "50705  502321715574079488                      None  ...     \n",
+       "50706  502321716652433408                      None  ...     \n",
+       "50707  502321718443380737                      None  ...     \n",
+       "50708  502321718443388928                      None  ...     \n",
+       "50709  502321718950903808                      None  ...     \n",
+       "50710  502321718971469824                      None  ...     \n",
+       "50711  502321719257079808                      None  ...     \n",
+       "50712  502321719429050368                      None  ...     \n",
+       "50713  502321719734841344                      None  ...     \n",
+       "50714  502321719999483904                      None  ...     \n",
+       "50715  502321720892854273                      None  ...     \n",
+       "50716  502321721085812736                      None  ...     \n",
+       "\n",
+       "                        user_location user_screen_name  \\\n",
+       "0                      Estados Unidos           20mUsa   \n",
+       "1              None Of Your Business         MzDivah67   \n",
+       "2                                         BrookLyn1825   \n",
+       "3                      Virginia Beach         I_Mpower   \n",
+       "4                                          Vorarlberg1   \n",
+       "5                                      rachel_palomera   \n",
+       "6                          California    bookishshelly   \n",
+       "7                                         deegerwiilen   \n",
+       "8                                            mmaureen7   \n",
+       "9                             London    collettehodson   \n",
+       "10                                       offlyniceteam   \n",
+       "11                           New York       carminemac   \n",
+       "12                                          SlavinOleg   \n",
+       "13                                         Free2Pursue   \n",
+       "14                summer polar vortex      SadieODoyle   \n",
+       "15     Liberal progessive in Austin,          Ssragona   \n",
+       "16                                     Schweizer_Kotau   \n",
+       "17                           detroit        bonxvivant   \n",
+       "18      Somewhere w/ my sister Mooder      mickysowavy   \n",
+       "19                  Enigmatic Cloud 9        Katyria90   \n",
+       "20                    Little Rock, AR         bennharr   \n",
+       "21                          king gio          Jaela_mb   \n",
+       "22                                       Blackberryccr   \n",
+       "23                                              bebird   \n",
+       "24                                          SlavinOleg   \n",
+       "25                     Columbus, Ohio     DrJLMooreIII   \n",
+       "26                                                kavn   \n",
+       "27       Star City....till I wreck it    ArrogantDemon   \n",
+       "28                          MHT & NYC        profbrady   \n",
+       "29                                         ahhthatswhy   \n",
+       "...                               ...              ...   \n",
+       "50687                                   PattoFaustiano   \n",
+       "50688                   United States      nanopatents   \n",
+       "50689                                         Orgelmir   \n",
+       "50690              Virgo Supercluster    DeadPrecariat   \n",
+       "50691                          Nakuru         Swamkidd   \n",
+       "50692                         Hilltop      PakistanBre   \n",
+       "50693                                         JoeOKerr   \n",
+       "50694                    Syracuse, NY   YourBlackWorld   \n",
+       "50695                                    KultureKritic   \n",
+       "50696                                      AelitaQueen   \n",
+       "50697                                    Reason4Rhymes   \n",
+       "50698                                    beforeitsnews   \n",
+       "50699                Wilkes-Barre, PA       rcooley123   \n",
+       "50700                   Lethbridge AB        UncleRee1   \n",
+       "50701                    Columbus, GA         _TaeKemp   \n",
+       "50702                  Bellingham, WA  profjournalista   \n",
+       "50703                    Brooklyn, NY    LiveAndAscend   \n",
+       "50704      Buffalo Valley,  Tennessee          blaha_b   \n",
+       "50705                       Singapore     pjan_stellar   \n",
+       "50706                              ma       a_filipiak   \n",
+       "50707    A QUIRKY YANKEE IN THE SOUTH    SheDoesArtWow   \n",
+       "50708               Florida Wig Stand      MsBrownsWig   \n",
+       "50709          Tryna get to a beach ✨      hoochieuche   \n",
+       "50710                   Elberton , Ga          Ducedoh   \n",
+       "50711   America the Beautiful, Oregon    Cate_Tweeting   \n",
+       "50712                  Charleston, WV       TheMaseMan   \n",
+       "50713                                   getoffmylawn80   \n",
+       "50714                                       bitcoinmom   \n",
+       "50715                        syracuse  drboycewatkins1   \n",
+       "50716                                  yourblackgossip   \n",
+       "\n",
+       "                    user_time_zone user_utc_offset  user_verified  DoW Month  \\\n",
+       "0                           Athens            7200           True  Sun   Aug   \n",
+       "1       Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "2       Pacific Time (US & Canada)          -28800          False  Sun   Aug   \n",
+       "3       Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "4                           Vienna            3600          False  Sun   Aug   \n",
+       "5                             None             NaN          False  Sun   Aug   \n",
+       "6       Pacific Time (US & Canada)          -28800          False  Sun   Aug   \n",
+       "7                             None             NaN          False  Sun   Aug   \n",
+       "8                     Newfoundland          -12600          False  Sun   Aug   \n",
+       "9                             None             NaN          False  Sun   Aug   \n",
+       "10                            None             NaN          False  Sun   Aug   \n",
+       "11      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "12                         Arizona          -25200          False  Sun   Aug   \n",
+       "13                            None             NaN          False  Sun   Aug   \n",
+       "14                            None             NaN          False  Sun   Aug   \n",
+       "15      Central Time (US & Canada)          -21600          False  Sun   Aug   \n",
+       "16                       Amsterdam            3600          False  Sun   Aug   \n",
+       "17      Central Time (US & Canada)          -21600          False  Sun   Aug   \n",
+       "18      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "19          Atlantic Time (Canada)          -14400          False  Sun   Aug   \n",
+       "20                            None             NaN          False  Sun   Aug   \n",
+       "21                         Arizona          -25200          False  Sun   Aug   \n",
+       "22                            None             NaN          False  Sun   Aug   \n",
+       "23      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "24                         Arizona          -25200          False  Sun   Aug   \n",
+       "25      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "26      Pacific Time (US & Canada)          -28800          False  Sun   Aug   \n",
+       "27      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "28                            None             NaN          False  Sun   Aug   \n",
+       "29      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "...                            ...             ...            ...  ...   ...   \n",
+       "50687                         None             NaN          False  Thu   Aug   \n",
+       "50688   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50689   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50690                        Quito          -18000          False  Thu   Aug   \n",
+       "50691                        Quito          -18000          False  Thu   Aug   \n",
+       "50692   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50693                         None             NaN          False  Thu   Aug   \n",
+       "50694   Central Time (US & Canada)          -21600          False  Thu   Aug   \n",
+       "50695                         None             NaN          False  Thu   Aug   \n",
+       "50696                         None             NaN          False  Thu   Aug   \n",
+       "50697                         None             NaN          False  Thu   Aug   \n",
+       "50698   Pacific Time (US & Canada)          -28800          False  Thu   Aug   \n",
+       "50699   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50700  Mountain Time (US & Canada)          -25200          False  Thu   Aug   \n",
+       "50701                      Arizona          -25200          False  Thu   Aug   \n",
+       "50702   Pacific Time (US & Canada)          -28800          False  Thu   Aug   \n",
+       "50703   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50704                         None             NaN          False  Thu   Aug   \n",
+       "50705                         None             NaN          False  Thu   Aug   \n",
+       "50706       Atlantic Time (Canada)          -14400          False  Thu   Aug   \n",
+       "50707   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50708                         None             NaN          False  Thu   Aug   \n",
+       "50709   Pacific Time (US & Canada)          -28800          False  Thu   Aug   \n",
+       "50710   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50711                         None             NaN          False  Thu   Aug   \n",
+       "50712       Atlantic Time (Canada)          -14400          False  Thu   Aug   \n",
+       "50713                         None             NaN          False  Thu   Aug   \n",
+       "50714   Central Time (US & Canada)          -21600          False  Thu   Aug   \n",
+       "50715   Central Time (US & Canada)          -21600          False  Thu   Aug   \n",
+       "50716                        Quito          -18000          False  Thu   Aug   \n",
+       "\n",
+       "      DoM Hour Minute  \n",
+       "0      17   17     52  \n",
+       "1      17   17     53  \n",
+       "2      17   17     53  \n",
+       "3      17   17     53  \n",
+       "4      17   17     53  \n",
+       "5      17   17     53  \n",
+       "6      17   17     53  \n",
+       "7      17   17     53  \n",
+       "8      17   17     53  \n",
+       "9      17   17     53  \n",
+       "10     17   17     53  \n",
+       "11     17   17     53  \n",
+       "12     17   17     53  \n",
+       "13     17   17     53  \n",
+       "14     17   17     53  \n",
+       "15     17   17     53  \n",
+       "16     17   17     53  \n",
+       "17     17   17     53  \n",
+       "18     17   17     53  \n",
+       "19     17   17     53  \n",
+       "20     17   17     53  \n",
+       "21     17   17     53  \n",
+       "22     17   17     53  \n",
+       "23     17   17     53  \n",
+       "24     17   17     53  \n",
+       "25     17   17     53  \n",
+       "26     17   17     53  \n",
+       "27     17   17     53  \n",
+       "28     17   17     53  \n",
+       "29     17   17     53  \n",
+       "...    ..  ...    ...  \n",
+       "50687  21    5     10  \n",
+       "50688  21    5     10  \n",
+       "50689  21    5     10  \n",
+       "50690  21    5     10  \n",
+       "50691  21    5     10  \n",
+       "50692  21    5     10  \n",
+       "50693  21    5     10  \n",
+       "50694  21    5     10  \n",
+       "50695  21    5     10  \n",
+       "50696  21    5     10  \n",
+       "50697  21    5     10  \n",
+       "50698  21    5     10  \n",
+       "50699  21    5     10  \n",
+       "50700  21    5     10  \n",
+       "50701  21    5     10  \n",
+       "50702  21    5     10  \n",
+       "50703  21    5     10  \n",
+       "50704  21    5     10  \n",
+       "50705  21    5     10  \n",
+       "50706  21    5     10  \n",
+       "50707  21    5     10  \n",
+       "50708  21    5     10  \n",
+       "50709  21    5     10  \n",
+       "50710  21    5     10  \n",
+       "50711  21    5     10  \n",
+       "50712  21    5     10  \n",
+       "50713  21    5     10  \n",
+       "50714  21    5     10  \n",
+       "50715  21    5     10  \n",
+       "50716  21    5     10  \n",
+       "\n",
+       "[3950717 rows x 37 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 3950717 entries, 0 to 50716\n",
+      "Data columns (total 37 columns):\n",
+      "contributors                          object\n",
+      "coordinates                           object\n",
+      "created_at                            object\n",
+      "entities_hashtags_text                object\n",
+      "entities_user_mentions_id_str         object\n",
+      "entities_user_mentions_screen_name    object\n",
+      "favorite_count                        int64\n",
+      "geo                                   object\n",
+      "id_str                                object\n",
+      "in_reply_to_status_id_str             object\n",
+      "in_reply_to_user_id_str               object\n",
+      "is_quote_status                       bool\n",
+      "place                                 object\n",
+      "possibly_sensitive                    object\n",
+      "retweet_count                         int64\n",
+      "retweeted_status_id_str               object\n",
+      "source                                object\n",
+      "text                                  object\n",
+      "user_contributors_enabled             bool\n",
+      "user_created_at                       object\n",
+      "user_followers_count                  int64\n",
+      "user_friends_count                    int64\n",
+      "user_geo_enabled                      bool\n",
+      "user_id_str                           object\n",
+      "user_is_translation_enabled           bool\n",
+      "user_lang                             object\n",
+      "user_listed_count                     int64\n",
+      "user_location                         object\n",
+      "user_screen_name                      object\n",
+      "user_time_zone                        object\n",
+      "user_utc_offset                       float64\n",
+      "user_verified                         bool\n",
+      "DoW                                   object\n",
+      "Month                                 object\n",
+      "DoM                                   object\n",
+      "Hour                                  int64\n",
+      "Minute                                int64\n",
+      "dtypes: bool(5), float64(1), int64(7), object(24)\n",
+      "memory usage: 1013.5+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "data.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "verified = data[data.user_verified == True]\n",
+    "normal = data[data.user_verified == False]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "groupedVerified = verified.groupby(['DoM', 'Hour', 'Minute']).count().reset_index().copy()\n",
+    "groupedNormal = normal.groupby(['DoM', 'Hour', 'Minute']).count().reset_index().copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "groupedVerified['Datetime'] = groupedVerified.apply(lambda row: datetime.datetime(\n",
+    "    year = 2014, \n",
+    "    month = 8, \n",
+    "    day = int(row.DoM), \n",
+    "    hour = row.Hour, \n",
+    "    minute = row.Minute), axis=1)\n",
+    "\n",
+    "groupedNormal['Datetime'] = groupedNormal.apply(lambda row: datetime.datetime(\n",
+    "    year = 2014, \n",
+    "    month = 8, \n",
+    "    day = int(row.DoM), \n",
+    "    hour = row.Hour, \n",
+    "    minute = row.Minute), axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x344188750>"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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eRUQyTM3WIhJnsR4wo4d/EcmHLanmsVu3bhpNLhKq7Z3hcRLr5FFEpDGIc3I1\nf/78fIcgIjmmZmsRkQxTs7WIxJmSRxGRDKvcbK3R1iISJ0oeRUSyLM7N1iKy5VHyKCKSYZWbrbek\nATQiEn9KHkVEMqxKs7VqHkUkRmKdPOphX0TyQQNmRCTOYp08ioiIiEhmKXkUEckw9XEUkThT8igi\nkmFqthaRuphZUzP7t5nNNLNZZpYIyxNmtsjM3gs/R6ZtM9rM5prZbDM7PK18DzP70Mw+MbNbsx27\n3jAjIpJhlWse13y3Jk+RiEhj5e7fmdnB7r7ezAqBN83suXDxze5+c/r6ZtYLOBnoBXQBXjSzH3lw\nw7kDOMfdp5vZs2Z2hLu/kK3YVfMoIpJlV79+db5DEJFGyN3Xh1+bElTolT95VjdFw7HAI+5e6u7z\ngbnA3ma2PdDS3aeH6z0AHJe9qJU8iohknJqtRSQKMysws5nAUuBfaQngSDN738zuNrPWYVln4Iu0\nzReHZZ2BRWnli8KyrIl18qg+6yKSDxowIyJRuHuZu/cjaIbe28x6A2OAXdy9L0FSeVM+Y6yO+jyK\niIiIZNDUqVOZOnVq5PXdfY2ZTQWOrNTXcSzwVPh9MdA1bVmXsKym8qxR8igikmFqthbZsg0YMIAB\nAwakfieTySrrmFl7oMTdV5tZc+Aw4Doz297dl4arnQD8J/z+JDDBzG4haJbuAUxzdzez1Wa2NzAd\nOAP4a3bOLKDkUUQkw9RsLSIRdALGmVkBQTfCie7+rJk9YGZ9gTJgPnAugLsXm9kkoBgoAc73H242\nI4D7gWbAs+7+fDYDV/IoIpJhqnkUkbq4+yxgj2rKz6hlm2uBa6spfxf4aUYDrEWsB8yIiIiISGbF\nOnlUy5GI5IOarUUkzuKbPO41hq+Zk+8oRGQLpGZrEYmz+CaPvxzB23ZDvqMQkS2Qah5FJM7imzwC\nmG7gIiIiIpkU6+RRT/8ikg9qthaROIt18ohu4CKSB3pwFZE4i3XyqKd/ERERkcxS8igikmG694hI\nnMU6eRQRyYeXPnsp3yGIiGRNzJNHPf2LSO5d9vJl+Q5BRCRrYp08OmX5DkFEtkAaMCMicZbV5NHM\nupjZy2b2kZnNMrPfhuUJM1tkZu+FnyPTthltZnPNbLaZHb4px1e/IxHJB917RCTOmmR5/6XAJe7+\nvpltA7xrZv8Kl93s7jenr2xmvYCTgV5AF+BFM/uR6zFeRDYjZa5WDxGJr6zWPLr7Und/P/y+FpgN\ndA4XWzWH4dX7AAAgAElEQVSbHAs84u6l7j4fmAvsvQkRNHxTEZEG0vOuiMRZzvo8mtlOQF/g32HR\nSDN738zuNrPWYVln4Iu0zRbzQ7JZb+rzKCL5oGZrEYmznCSPYZP1Y8CFYQ3kGGAXd+8LLAVuysZx\ndQMXkXxQs7WIxFm2+zxiZk0IEsfx7j4ZwN2Xpa0yFngq/L4Y6Jq2rEtYVsWVV16Z+j5gwAAGDBhQ\n9dgND1tEpMGUPIpInGU9eQTuBYrd/S/lBWa2vbsvDX+eAPwn/P4kMMHMbiForu4BTKtup+nJY01U\n8ygiIiKSWVlNHs1sf+B0YJaZzSQYwXIZcJqZ9QXKgPnAuQDuXmxmk4BioAQ4f1NGWqvPo4jkgwbM\niEicZTV5dPc3gcJqFj1fyzbXAtdmLSgRkSxTs7WIxFnM3zCjp38RyT3de0QkzpQ8iohkmJqtRSTO\nYp08oj6PIpIHenAVkTiLefIoIpJ75X0ePeH8Ypdf5DkaEZHMinXyqKd/EcmH9AEz9w66N4+RiIhk\nXsyTRzVbi0jupfd5bNakGe1btM9jNCIimRXr5FFEJB/SWz0KrEBT94hIrCh5FBHJsPRk0cyUPIpI\nrMQ8eVSfRxHJrwIr0NQ9IhIrMU8eRUTyS83WIhI3Sh5FRLLIULO1iMRLrJNHTdUjIvlWYAW6F4lI\nrMQ6eRQRyTcNmBGRuFHyKCKSRerzKCJxE/PkUU1FIpJfBVbA9xu/5/737893KCIiGRHz5FFEJL8M\nA+C3z/02z5GIiGRGrJNHdVIXkXwrsOA2W55Eiohs7mKdPIqI5FsqeTQljyISD0oeRUSySEmjiMRN\nzJNHNVuLSOOgVxSKSFzEPHkUEWkc1AdbROJCyaOIiIiIRBbz5FFP+iLSOKjZWkTiItbJo27VItJY\n6C0zIhIXsU4eRURERCSzYp48qu5RRBoHDZgRkbiIefIoItI4qM+jiMSFkkcRkRxQzaOIxEXMk0fd\nrEWkcdhYtjHfIYiIZESsk0eljiLSWGx0JY8iEg+xTh6VPoqIiIhkVsyTRxERERHJJCWPIiIZtO77\ndfkOQUQkq2KdPGp0o4jk2obSDfkOQUQ2A2bW1Mz+bWYzzWyWmSXC8jZmNsXM5pjZC2bWOm2b0WY2\n18xmm9nhaeV7mNmHZvaJmd2a7dhjnTyKiOSaHlpFJAp3/w442N37AX2BgWa2NzAKeNHddwVeBkYD\nmFlv4GSgFzAQGGNmFu7uDuAcd+8J9DSzI7IZu5JHEZEM0mTgIhKVu68PvzYFmhCM9D0WGBeWjwOO\nC78PAh5x91J3nw/MBfY2s+2Blu4+PVzvgbRtsiLmyaNu4iKSW6p5FJGozKzAzGYCS4F/hQlgR3f/\nEsDdlwLbhat3Br5I23xxWNYZWJRWvigsy5pYJ4+6iYtIrt341o35DkFENhPuXhY2W3chqEXcjao1\nX40umWmS7wBEROJk2uJp+Q5BRPJs6tSpTJ06NfL67r7GzKYCRwJfmllHd/8ybJL+KlxtMdA1bbMu\nYVlN5Vmj5FFEJMsKrVBvmBHZggwYMIABAwakfieTySrrmFl7oMTdV5tZc+Aw4DrgSeDXwJ+BM4HJ\n4SZPAhPM7BaCZukewDR3dzNbHQ62mQ6cAfw1O2cWiHny2OhqekUk5qrrLlNYUMjGjUoeRaSCTsA4\nMysg6EY40d2fNbN3gElmdjawgGCENe5ebGaTgGKgBDjffxihNwK4H2gGPOvuz2cz8JgnjyIiuVXm\nZVXKCizW3ctFpAHcfRawRzXlK4Bf1LDNtcC11ZS/C/w00zHWRHc0EZEMUvIoInEX6zuaRluLSK4p\neRSRuNMdTUQkg8q7II0/fnyqrNAK8xWOiEjGKXkUEcmg8lHVzZo0S5Wp5lFE4iTmdzQ1W4tIbpU3\nWxuWKlPyKCJxojuaiEgGpZJH+yF5TP8uIrK5i3XyqAEzIpJr5X0e02se07+LiGzuYp08iojkWnmf\nx/TaxvJm6+TUqm+ZEBHZ3Ch5FBHJoOr6PJYnko9//HheYhIRyaSYJ49qthaR3Kquz+OwPYYFZWq+\nFpEYiHnyKCKSW+2atwMqJorH//j4fIUjIpJxSh5FRDJoaJ+hQPWjrTXqWkTiIObJo5qtRSS3tirc\nCqh+tLWarUUkDmKePIqI5FZ1U4RpknARiRPd0UREskDN1iISV7FOHjVJuIjkmiYJF5G4i3XyKCKS\na+UPrdVNEq4kUkTiQMmjiEgGVVvzqOZqEYmRmCeParYWkfxo1qRZ6ntqtLWSSBGJgZgnjyIiuVXe\nbJ2ePKrZWkTiJNbJowbMiEiulTdbV6h5VI2jiMRIrJNHEZFcc5yti7bmJ9v9JFWmZmsRiRMljyIi\nGfarPr+isKAw9VuThItInMT6jqZmaxHJtfJm63SpScIx3L3adURENhexTh5FRHLN8SoDY9Kbrbve\n0pWRz47MR2giIhkR6+RRvYtEJNfcvUrfxvRm68XfLObtRW/nOiwRkYyJdfKoZmsRyYcqNY9pzdbp\nv0VENkexTh7/WzA93yGIyBamuofWykmj+jyKyOYs1smjiEiu1dZsrUnCRSQOlDyKiGRQtQNm1Ewt\nIjGi5FFEJMMqJ4vq6ygicaLkUUQkg6rrz6hmaxGJkyb5DkBEJE5qa7b+z1f/Sa0jIpIvlrT+wIHA\nDsC3wH+Af3nCV0bZPqs1j2bWxcxeNrOPzGyWmV0QlrcxsylmNsfMXjCz1mnbjDazuWY228wOz2Z8\nIiKZVt2AmfJkcuWGSPdlEZGssKSdZUl7DxgNNAfmAF8BBwAvWtLGWdJ2rGs/2a55LAUucff3zWwb\n4F0zmwKcBbzo7teb2R8ITmKUmfUGTgZ6AV2AF83sR655LURkM1K55rHyu63VfC0iedIC2N8T/m11\nCy1pfYEfAQtr20lWk0d3XwosDb+vNbPZBEnhscBB4WrjgKnAKGAQ8Ii7lwLzzWwusDfw72zGKSKS\nKdXO81ipJlLN1iKSD57w2+tY/n6U/eSsz6OZ7QT0Bd4BOrr7lxAkmGa2XbhaZyD9vV2LwzIRkc1C\n8bJimhY2rVCmmkYRaUwsadcD/0fQ3/F5oA9wsSf8wSjb52S0ddhk/RhwobuvhSqP3XoMF5FYuGfm\nPYyZMaZCWeVmaxGRPDvcE74GOBqYD/QALo26cdZrHs2sCUHiON7dJ4fFX5pZR3f/0sy2J+isCUFN\nY9e0zbuEZVVceeWVqe8DBgxgwIABGY5cRCQzNL+jiDQyReGfvwQe9YSvtmT0+1Qumq3vBYrd/S9p\nZU8Cvwb+DJwJTE4rn2BmtxA0V/cAplW30/TkUUSkMVOztYg0Mk9a0j4maLY+z5LWAdgQdeNsT9Wz\nP3A6cIiZzTSz98zsSIKk8TAzmwMcClwH4O7FwCSgGHgWOF8jrUVkc1e52Vq3NRHJF0taAfAUsB/Q\n3xNeAqwnGMwcSbZHW78JFNaw+Bc1bHMtcG3WghIRyTE1W4tIY+EJL7Ok3e4J75dWtg5YF3UfsezF\nXVpWmu8QRERSanrjjIhInrxkSTvRkg27GcXy9YTPfPJMvkMQEUmp3Gxd5mV5ikREBIBzgUuAjZa0\nbwED3BPeKsrGsUweVfMoIo1J5ZrGVRtW5SkSERHwhLfclO1jmTyKiDQmlWsemxTo1isi+RM2V58O\n7OwJ/5MlrSvQyRNe7Qw3lcWyz6OISGNSuc+jRluLSJ6NAfYFTgt/rwVqfXVhulgmj+qMLiKNSeV7\nkvo8Zt5f//1X2l3fLt9hiGwufuYJH0E4t6MnfCWwVdSN60wezdjXjNvN+NCMZWYsNONZM0aY0brh\ncYuIbJlcb2TNuNcXvs6Kb1fkOwyRzUWJJa2Q8PXQ4SThkZ9qa00ezXgO+A3wAnAk0AnoDfwRaAZM\nNmNQw+IWEdkyqeYx89QVQKRe/gr8E9jOknY18AZwTdSN6+q1PdSdryuVrQXeCz83mdG+HsHmhF4F\nJiKyZVFtrkh0nvAJlrR3Cd7yZ8BxnvDZUbevteaxPHE0Y2uzYF0zepoxyCx4qXY1yWWjctSEo9SU\nISKNimrJMu+Jj5/Idwgimw1LWnfgc0/47cB/gMMsadtG3T7qgJnXgGZmdAamAEOB++sZa148N+85\n3l/6fr7DEBFJUS1Z5qkrgEi9/INggvAewF1AV+ChqBtHTR7NnfXACcAYdwYDu9U30lypPLJxQ+mG\nPEUiIlJVoRXmOwQR2bKVecJLCfK62zzhlxKMa4kkcvJoxr4EE0qWv/tvs7n76Y0zIpJLzZo0q3V5\n5UnDRWTLY2ZdzOxlM/vIzGaZ2W/D8oSZLTKz98LPkWnbjDazuWY228wOTyvfw8w+NLNPzOzWCIcv\nsaSdCpwBPB2WFUWNPeod7EJgNPBPdz4yYxfglagHybeSjSX5DkFEtiDV1Sw+cNwDPywv2GyevUUk\ne0qBS9x9N4IJu0ea2Y/DZTe7+x7h53kAM+sFnAz0AgYCY+yHptY7gHPcvSfQ08yOqOPYZ4XHvNoT\n/rklbWdgfNTA63xHlhmFwCD3H6bkcecz4IKoB8m1yqOtS8qUPIpI7lT3+sGfd/t56rsGzIiIuy8F\nlobf15rZbKBzuLi6aWOOBR5x91JgvpnNBfY2swVAS3efHq73AHAcwTSL1R874cWk5XGe8M+BP0eN\nvc7k0Z2NZhwQdYeNkW7UIpJL1dUspg+S+XzV57kMR0QaOTPbCegL/Bs4gKAWcigwA/idu68mSCzf\nTttscVhWCixKK1/ED0lo9cdL2udQdeSeJ3yXKPHWmTyGZprxJPAosC51EOfxiNvnlUY2ikguFRVU\n7Tqkh1gRqY6ZbQM8BlwY1kCOAa5ydzez/wNuInhhSyb1T/veDBgMtI26cdTksRmwHDgkrcyhcSaP\nlUdb66YtIrlUXbN15fuSiMTX1KlTmTp1ap3rmVkTgsRxvLtPBnD3ZWmrjAWeCr8vJphSp1yXsKym\n8hp5wpdXKro1nDT8ijqDJmLy6M5ZUdbLtwkfTuBX//wVk4dMrlCumkcRyaXqksdurbvlIRIRyYcB\nAwYwYMCA1O9kMlnTqvcCxe7+l/ICM9s+7A8JwVQ6/wm/PwlMMLNbCJqlewDTwhrK1Wa2NzCdYAT1\nX2uLz5K2R9rPAoKayKgVitFWNKMnwUieju78xIw+BINo/i/qgXLhgy8/qLZcNY8ikkuqecyfGUtm\n0H+H/nWvKJJnZrY/wRSIs8xsJkGL7mXAaWbWFygD5gPnArh7sZlNAoqBEuB8/yHBGUHw8pZmwLPl\nI7RrcVPa91Lgc4KR3JFEzTLHApcSzEKOOx+a8RA0ruSxfJR15dHWqnkUkVyYv2o+AO1atMtvIFuw\n5esrt8aJNE7u/ibVz5ldY+Ln7tcC11ZT/i7w08jHTvjBUdetTtR5Hlu4M61S2WYz87ZqHkUkF4b+\ncygAD50Q+S1fkmGqLBDJvqjJ49dmdCcc1m3GScB/sxZVA9XULKSbiYjkQvmDatvmkQctiohsdqI2\nW48A/g782IzFBG3jv8paVA1Uubm6nGoeRSSX9PrB/NH9XiT7oo62/gz4hRlbAwXufJPdsDZNlal6\nVPMoIjlQfq/R4Jj80f1epGaWtBNqW+4JjzQFY6THYzMuNKMVsB64xYz3zDi8ru1yrcZmaz2JikgO\n1VbzOGKvETmMRESkgmPCzznAPQSjvU8H7gbOjrqTqG0rZ7uzBjgcaAcMBa6rT7S5UGOztZ5ERSQH\nyh9Ua7oXAXTcuqPmfBSRvPCEn+UJPwsoAnp7wk/0hJ8I7BaWRRI1eSy/Ex4FPODOR1T/0u68Kq95\nrHzjLvOyfIQjIluY8gfV2moezUz3pCxoUdQCUEuTSERdPeHpA5+/BHaMunHUATPvmjEF2BkYbUZL\ngskr8+aMf57BA8c/UKGstqd9EZFcqa3Po2FqDcmC8oRc11YkkpcsaS8AD4e/TwFejLpx1JrHc4BR\nwF7urAe2gvy+snD8h+NrXFZSVlLht57yRSQXymu9aqt5bFLQRPekLPp+4/f5DkGk0fOEjwTuBHYP\nP3/3hP826vZRax4PCP/s05gHEZY/7f/l33+pUP5tybf5CEdEtlC1tYIUFhSqaTWLdG1FInsP+MYT\n/qIlrYUlraUnPNJsOlGTx0vTvjcD9gbeBQ6pX5zZVX7DXvf9ugrlLZu2zEc4IrKFidLnsdAKVfOY\nBeX3f11bkbpZ0oYB/wO0BboDnQlqIg+Nsn2kZmt3jkn7HAb8BFjZsJCzp/yGXVhQ8VWRzZs0z0c4\nIrKFqil57N2hNz/r8jP1y8siXVuRSEYA+wNrADzhc4Htom7c0NcgLAJ6NXDbrClvti60ismjnkRF\nJBdSU/XU0L/no/M/okfbHronZZGarUUi+c4TnuogbElrAtGfvCI1W5vxt7SdFgB9CdrKG5XyZovK\nT/26UYtILkS51xRYgRKcLNL9XiSSVy1plwHNLWmHAecDT0XdOGqfxxlp30uBh915M3qMuZGqeazU\nbK1mDBHJhSiJi6F5HrOh/P6vaysSySiCmXRmAecCzxK8ZSaSqO+2Hteg0HKsvOZRzdYikg+Rax71\nQJs1ut+L1M0TXgaMDT/1FrXmcbNQ/uSpZmsRyYdINY96w0xWKTEXqZklbZIn/GRL2iyq6ePoCe8T\nZT/xSh6podla/YtEJAfU5zF/NFWPSCQXhX8evSk7iVXymJqqR83WIpIH6vOYf7q2IrV6GtgD+D9P\n+NCG7qTW5NGMp6hl6LY7gxp64Gwob7Z+Zu4zFcrfWvQW5/Y/Nx8hicgWRH0e86dPxz68veht1eqK\n1G4rS9ppwH6WtBMqL/SEPx5lJ3XVPN4Y/nkCsD3wYPj7VODLiIHmTE2vBHvggwcYd9xmMeZHRDZj\nG31jneuoz2N2lHdX2qHlDnmORKRRGw6cDmwLHFNpmQObnjy68yqAGTe50z9t0VNmFabvaRRqmphX\nRCQX1Ocx/7bZapt8hyDSaHnC3wDesKTN8ITf09D9RO3zuLUZu7jzGYAZOwNbN/Sg2VJTzaOISC58\ntvKzOtdRn8fsKE/I1SVApGaWtEM84S8DK7PZbF3uYmCqGZ8BBnQjmFSyUVHNo4g0durzmD2GqVZX\npHYHAS9TtckaMtVsndqb87wZPwJ+HBZ97M53UbbNJdU8ikhjpz6P2WNmSsxFauEJT1jSCoDnPOGT\nGrqfgrpXATNaAJcCI935ANjRbNPmCMqGypODi4g0NgVWQJmX8fX6r/MdSuyo5lGkbuHbZf53U/YR\ntdn6PuBdYN/w92LgUYL5ghoNNVuLSGNX3kLy+crPad+ifZ6jiRd1CRCJ7EVL2u+BicC68kJP+Ioo\nG0etquvuzvVACYA766HxtRGr2VpEGjs95GZPSVkJhz5waL7DENkcnAKMAF4jqBx8F6LPohO15vF7\nM5oTThhuRndoHH0eZy+bTbsW7dhu6+10UxaRzYb6PWaWahxFovOE77wp20eteUwAzwNdzZgAvMQm\ntpdnSu8xvRn86GBANY8isvlQsiMi+WJJa2FJ+6Ml7e/h7x9Z0iKPZYk62vpfZrwH7EPQXH2hO42m\nt/e3Jd8ClQbMlDSHom/zFJGISO00sENE8qh8LMt+4e96jWWptebRLJiax4w9COZ2/C+whGC09R4N\nDDjjpi+ZXrWw6Fs6lPXJfTAiIhGo5lFE8qi7J/yHsSwJr9dYlrpqHi8B/ge4qZplDhwS9UC5ULkP\n0Tnff8B1zdSULSIiIpLme0vaD2NZklavsSx1JY//Cv88p/zVhI2ZOqCLyOZC96vMUjcAkXr5YSxL\n0iYA+wO/jrpxXQNmRod/Ptag0HKsRVGLH37cFXnEuYhIzm1VuFW+QxCRLZQn/F/ACQQJ48NAf0/4\n1Kjb11XzuNyMKcDOZjxZ5eDOoOihZl/TJk1/+FHaLH+BiIjUokurLrRu2jrfYcTW5I8nM2jXQZq+\nTaQSS1ox8BDwsCf8U+CZhuynrprHXwJXAF8T9Hus/Gk03B1355Cdw26YXkh6K4aaNEQk287pd06k\n9bYu2loDZrLouInHMXfF3HyHIdIYnQpsDUyxpE2zpF1sSduhvjuptebRne+Bd8zYz51lDQw0J0rK\nSnCcJgXhKS3/UYXlZV5GoRXmITIR2VJsv832XDXgqjrXM9M7mLNtY9nGfIcg0uh4wj8APgBGW9L2\nIXjTzDuWtE+BhzzhY6Psp9bk0Yxb3bkIuNes6mNyvputW1z9Qx/H+2beR7MmaU3VXkh6i4We8kUk\n29w9UlOpYbonZVjl61lSVpKnSEQ2D57wdwgSx8nALcBtwKYnj8D48M8bGx5e9nxb+sMk4OtK1jH8\nmeFV1unQogPL1i/TU76IZJ3jkd50ZWYabZ1lqnkUqZklbS+CJuwTgc+BuwgmCY+krmbrd80oBP7H\nndM3JdBsm/TRpGrLB/cezJgZY3SjFpGsq1fNox5os2ra4mn069Qv32GINCqWtGsImqpXAI8A+3vC\nF9V3P3W+29qdjUA3Mxr1vBL/XvzvKmXucPsvb2erwq3URCQiWRe15rHACnRPyrLnP30+3yGINEYb\ngCM94Xt5wm9qSOIIEd9tDXwGvBlO17OuvNCdmxty0FwrsAI95YtI1kWuedSAmazT9RWpyhNeZUSf\nJe3vnvD/qc9+oiaPn4afAqBlfQ7QGBjqXyQi2Re5z6PuSRmnZFGkwfrXd4NIyaM7SQAzWrizvr4H\nyTc1EYlILtSr5lH3JBFpHL6q7wZ19nkEMGNfM4qBj8Pfu5sxpr4HyxVPBDfl8nu4RjaKSC7Uq8+j\nasqySsm5SDSe8CPru03UZutbgSMgeEWhOx+Y8fP6HixfNLJRRHJB8zw2Hrrni9TMktYTuBToRlou\n6Ak/JMr2UZNH3Pmi0j2x0U+iVX7vULO1iORK1HkeldyISB49CtxJMCl4vfO5qMnjF2bsB7gZRcCF\nwOz6HiwXTv3JqVXK1GwtIrkQ9SFVA2ayTxUGIrUq9YTf0dCNoyaPw4G/AJ2BxcAUYERDD5pN3dt0\nr1Km/kUikgtRm63VGpJ5la+n7vkitXrKknY+8E/gu/JCT/iKKBvXOmDGjL0A3PnandPd6ejOdu78\nyp3lmxJ1tjw377kqZXrKF5FcqM/rCZXciEgenUnQ5/Et4N3wMyPqxnXVPP7djG0IXmHzkHvjbKpO\n9+5/3019Tx9trad8Eck2DZhpPA7Y8YB8hyDSaHnCd96U7et6t3U/M3YFhgD/MKMEeBh4xJ35m3Lg\nXKgwYEZP+SKSZap5bDx23naT/m0UiTVLWhFwHqRmzpkK3OUJL4myfZR3W89xJ+lOb+AMoDXwkhlv\nNizk3FOztYjkQn36POqelF2q2RWp1R3AnsCY8LNnWBZJpEnCAcwoALYDOgJbE2FGcjO7x8y+NLMP\n08oSZrbIzN4LP0emLRttZnPNbLaZHR41tghx6EYiIllXn9cT6p6UWZVrclWzK42dmXUxs5fN7CMz\nm2VmF4TlbcxsipnNMbMXzKx12jbV5klmtoeZfWhmn5jZrREOv5cn/ExP+Mvh5ywIxrlEUWfyaMaB\n4dtkFgG/B14HdnXn+Aj7v49gcvHKbnb3PcLP88FxrBdwMtALGAiMsSiP8BGo2VpEcqFeryfUPUlk\nS1cKXOLuuwH7AiPM7MfAKOBFd98VeBkYDWBmvak5T7oDOMfdewI9zay63CvdRktaanoaS9ou1GO+\nx7pGW38BXAsUA33dOcKd+9xZHWXn7v4GsLK6XVdTdizwiLuXuvt8YC6wd5Tj1EXN1iKSC6p5zK8z\ndz8z9V3XVxo7d1/q7u+H39cSzJ/dhSAfGheuNg44Lvw+iGryJDPbHmjp7tPD9R5I26YmlwKvWNKm\nWtJeJUhSfxc19rpqHg9w5wB3bnOv/4uzazHSzN43s7vTqmM7A1+krbM4LNtkmlNNRHJBfR7z6/y9\nzk99V82ubE7MbCegL/AO0NHdv4QgwSToMgg150mdCVqHyy2ijvzJE/4S8CPgAuC3wK6e8FeixltX\n8vhHM35S3QIztjbjbDNOj3qw0BhgF3fvCywFbqrn9vWmN8yISC5otHXjsb5kfb5DEInEzLYBHgMu\nDGsgK98cMnazsKT9vPwD/AzYNvz8LCyLpK55Hm8HrjDjp8B/gGVAM4JstRVwLzChPoG7+7K0n2OB\np8Lvi4Guacu6hGWbzNCNWkRyQ/M85kfl6/k/T/8Pw/YclqdoZEs3depUpk6dWud6ZtaEIHEc7+6T\nw+Ivzayju38ZNkmXt/zWlCfVJ3+6tJoyB/qE+yisM2jqnufxfeDkcKLw/kAn4FtgtjtzohyAoH9j\n6m5qZtuH1bAAJxAkpQBPAhPM7BaC6tYewLSIx6iVmq1FJBeiPqSq5lEk3gYMGMCAAQNSv5PJZE2r\n3gsUu/tf0sqeBH4N/JngTTCT08qr5Enu7ma22sz2BqYTTKv41+oO5gk/Jv23JW1/4I8ELcG/jXp+\nkd5t7c5aggkk68XMHgIGAO3MbCGQAA42s75AGTAfODc4hheb2SSCwTklwPmeoburmq1FJBeiNlur\nz2N2RLn2Io2Fme0PnA7MMrOZBDWAlxEkjZPM7GxgAcEI67rypBHA/QStw8+Wz2RT47GTdijw/8Jj\nXuMJ/1d9Yo+UPDaUu59WTfF9tax/LcHo7npp3bQ1q7+reQC4puoRkVyIOmCmZ9ueTF8ynSN61DWb\nhmyKe967h3P2OCffYYhUy93fpOZm4l/UsE21eZK7vwv8tK5jWtJ+CVwOrAb+6Al/I3LAaSJPEt6Y\nff2/X9e6XFP1iEguRK15POUnpzDxo4k5iGjLNn3J9LpXEtmyPEXQJ7IU+F9L2pPpn6g7qXfNY/im\nmW3cWVPfbbOlSUHtp6E3zIhILkStedyv636s2rCK4mXF9O7QOweRbZnUjC1SxcGZ2Emk5NGMh4Dh\nBLOPTwdamfEXd27IRBDZpmZrEcmF+vR5HNx7MBP/M5HkwTV2pJd6qO4en6GXlInEhif81UzsJ2qz\ndavXoaMAACAASURBVO+wpvE44DlgZ2BoJgLItFZNW1UpU7O1iOSCE63mEeCU3U7hkY8e0YNtBlW+\n9qp5FKnIkvaUJe0YS1pRNct2saRdZUk7u679RG22LjKjiCB5vM2dksb6QDfppElVytRsLSK54B6t\n5hFg78578/3G7/ngyw/ou33fLEe2ZSqwWHTrF8mkYcAlwK2WtBX8MH/3TsCnwG2eSM03WaOoyeNd\nBNPqfAC8ZkY3iPZ+61wrKqySTKvZWkRyoj41j2bGKbudwsT/TFTymCVqthapyBO+FPhfgsEyO/HD\n/N2feMIjv5YpavL4lPsPE06asRCos1ozH6p76leztYjkQn1qHiFouj5x0olcc+g1SnSyQM3WIjXz\nhM8nqBist6h1+v+ocMCgDfiRhhwwW+4/9n6g+pHXesOMiORCfWoeAfpu35cmBU2YsWRGFqPaMlR3\nj///7J13mBRl8se/tZFddsnskiUoGUQUDKAsKqCoIHExoqceip7nof5M5y2jZzj1xHRgPMV0CEYQ\nFBABRQFJkiUJSM45LOzO+/ujp2d7Znpmuns6TU99nmeenXm73/etnelQXfVWFSvkDGMNMZVHIrQk\nwgAAVYnQX/G6BZKP3DEe7vJwyOehHYYCUFceucIMwzB2ocfaFXRdc85H0+hcv3PwPVseGcYa4lke\nWwC4GkA1ANcoXh0hLbp0jJ7Neqq2q615JHAdWYZhrMfIdaa4bTHGrxzPD7gmQCA0rd40+JkDZhgm\nPuSj6uSj9nr6xFzzKAS+AvAVES4UAnMTks5kol0U2G3NMIxT6HVbA0DbgrbIz87H3C1z0aVRF4sk\nS03Ybc0w6pCPZgHoA0kPXARgN/noJ1EiRmjpr/WxbB8RZhBhBQAQoT0R/m5EYLNIozRkp2dHtKvm\neWS3NcMwNqA3YEaGXdfWwG5rholKVVEiDgPoD+B9USLOR5R62mpoVR7fAvAIgNMAIASWARiiU1BT\nSaM0DD17KG5od0Owbc+De0JcFrIHid3WDMPYgRHLIyApjxNWTUC5v9wCqVID+RqvVBjZ8sgwUckg\nH9UFMBjA17o7a9wvVwj8EnYelumdzGzeuOaNkM+1cmup7pdGaWx5ZBjGcoxaHlvUaoE6eXXw4x8/\noqhxkfmCpRArdq8Ivuc1jwwTFR+AqQDmiBKxgHzUFMA6rZ21nll7idAMkBYOEmEggB16JTWTI6eO\nRN3244/SX1nZ5QozDMPYgVHLI4BgwnDGOESE5buXV3xmtzXDRGOHKBHtRYkYDgCiRPwO4EWtnbUq\nj3dDqjLTkgjbANwH4E69kprJkdLoyuPCsJRpXGGGYRg7MGp5BIDBbQbjs9WfoczvuFPHM7DlkWGi\n8qrGNlU0ua2FwO8ALidCZQBpQiC65mYTeiyJXGGGYRg7SMTy2LR6UzSu1hgzN85Ej2Y9TJYsNeE1\njwwTCvnoQgAXAahNPlJGVlcBkK51HE2PZUTYQISPANwEoJEeQa1CiyUxGDDDbmuGYWwgEcsjILmu\nx61wVfGupEG1wgy7rRkmnCwAeZCMh/mK12EAA7UOojVgpjWA8wFcDOB5IrQAsEwI9NMjsZnoUQbZ\nbc0wjB0kYnkEJNd1hzc6YEz5GGSlZ5koWWrClkeGCUWUiNkAZpOP3hMlYjP5KFeUiON6x9G6IKQc\nUpqecgB+ALsDL8doVr2Z5n3Zbc0wjB0kanlsWLUhWtVqhekbppsoVeoQ/t2z5ZFholKPfLQKwG8A\nQD46m3w0WmtnrcrjYQAvAdgIYKgQuFAIDNMtqol0qt8p7j7yQydXmGEYxi4StXZxwnDz4IAZhonK\nSwB6AdgHAKJELAVwidbOWs+s6wD8AGA4gHFE8BHhMp2COgZXmGEYxg7MeEgd2HogJq2dhJNlJ02Q\nKLVhtzXDREeUiC1hTZqrFGhSHoXAV0LgQQDDAEwBcAsMZCS3i/DrBVeYYRjGDhJ1WwNA3fy66FCn\nA75d/61JUqUu7LZmmKhsIR9dBECQjzLJRw8AWK21s9Zo68+IsB7AywByAdwMoLoRae1E1hfZbc0w\njB0kGjAjw65r/agZCNjyyDBRuRNSDu/6ALYB6BD4rAmt0dajAMwVosKkSYRsHUI6CrutGYaxAzMs\njwAwoNUAPPzdwzh26hgqZ1U2QbLUhC2PDKOOKBF7AdxgtL/WNY+vKBXHAHONTmo37LZmGMYOzLI8\n1q5cG53rd8bkdZNNkCp1CP/uOWCGYdQhHzUnH80gH60IfG5PPvq71v4xzywi1CHCuQByiHAOEToG\nXkWQ3NdJAbutGYaxA7MsjwAwpO0Qdl0nCLutGSYqbwF4BFIaRogSsQzAEK2d47mte0EKjmkA4N9A\n8Kp4GMCjOgW1Hfm6wW5rhmHswCzLIwD0a9kPf5v6NxwpPYL87HxTxkw12G3NMFHJFSXiF/KFnCNl\nWjvHVB6FwFgAY4kwQAh8ZlBAx+EKMwzD2IGZlsfqOdVxcaOLMXHNRNzQ3vDSpJRBtTwhWx4ZJhp7\nyUfNAOnEIR8NBLBDa2etqXqSUnEM1rbmCjMMw9iAmZZHgKOujTD9porqPGx5ZJio3A3gDQAtyUfb\nANwHKQJbE1qjrZMaIuI1jwzDWI6ZlkcA6NuyL+755h4cPHkQ1SpVM21cr0Ig5GdVuPjZ8sgw6ogS\n8TuAy8lHlQGkiRJxRE//eAEzgwJ/mxgX0XnYbc0wjB2YbXmskl0Flza5FF/+9qVpY6YSHG3NMOqQ\njzaQjz4CcBOARnr7xzuzHgn8TUq3tQy7rRmGsQuzXaXFbYoxbsU4U8dMFdhtzTBRaQ3JbV0TwPMB\nZfILrZ3jKY/7iDANQBMiTAx/JSC0LcgGAE7VwzCMHVjh4bi6+dWYu3Uu9h7fa/rYXkL+7tsVtsND\nXR4CwG5rholBOaQ0PeUA/AB2B16aiLfm8SoAHQF8AClVT1IgXy+CATOcqodhGBsw220NAHlZebji\nzCvw+erP8edz/2zq2F4kNzMXz17+LNbsW8OWR4aJzmEAywG8COAtUSL26ekc0/IoBE4JgXkALhIC\nswEsArBICMwOfE4KuMIMwzB2YHbAjAxHXWtDqbg3qtKIPU4ME53rAPwAYDiAceQjH/noMq2dta4m\nLiTCEgArAawiwiIitNUvqzOw25phGDuwwvIIAFeeeSUW71iMXUd3mT62VyFiowHDREOUiK9EiXgQ\nwDAAUyAVhPlaa3+tyuObAEYIgTOEQCMA9wfakgJ2WzMMYwdWWR5zMnNw1VlX4dNVn5o+tld5ef7L\nGDFthNNiMIwrIR99Rj5aD+BlSOWmbwZQXWt/rXkeKwuBmfIHITCLCJV1Seog7LZmGMYOrLI8ApLr\n+vmfn8fdne+2ZHyGYVKKUQDmihJRLjeQj7K1dtZqefydCI8ToXHg9XcAv+sU1HY42pphGLuxKkij\nZ7OeWLF7BbYe3mrJ+MkOX+MZRhevKBXHAHO1dtZqefwTAB+AzyHVQfwx0OZqONqaYRg7sdLDkZ2R\njb4t+2LCygn424V/s2wehmG8C/moDoD6AHLIR+cAwafdKpDc15rQpDwKgQMA7tUrpFOEX7+5wgzD\nMHZgpdsaAIa0GYKSWSWsPEaBU/MwTFx6QQqOaQApBaN80hwG8KjWQVKjtjVXmGEYxgasCpiRubTJ\npbjxixux6eAmNK7W2LJ5GIbxJqJEjAUwlnw0QJQIw9UDU6LwJxHxehiGYSzHastjZnom+rfsj/Er\nx1s2B8Mw3icRxRHQqDwSoYuWNreSBnZbMwxjPVZbHgGguC0nDFeDr/EMYx9aLY+vamxzJRwwwzCM\nXVhdT7nbGd2w7fA2rNu3ztJ5GIbxHuSjQYG/TRIZJ6bySIQLiXA/gNpEGKF4jQSQnsjEdsKpehiG\nsQM7rjPpaekY2HogWx9VsFpxZxgP8Ejgb0Ju63gBM1kA8gL75SvaDwMYmMjEdsIBMwzD2IEdbmtA\nShg+fMpw/P2Sv1s+V7LStqAtVuxe4bQYDOM29pGPpgFoQj6aGL5RlIg+WgaJqTwKgdkAZhPhPSGw\n2ZiczsM1ThmGsQOrA2ZkujTqggMnDmDVnlVoXbu15fMlIxlpKZFMhGH0chWAjgA+gJSqxxBaz65s\nIrwJoLGyjxC41OjEVqKa55Hd1gzDWIxdlsc0SsPgNoPxyYpP4Ovus3y+ZCD8Gs/KI8NEIkrEKQDz\nyEcXiRKxh3yUF2g/qmccrQEzEwAsAfB3AA8qXkkBu60ZhrEDuyyPgOS6/mTlJ+xViQIrjwwTk0Ly\n0RIAKwGsIh8tIh+11dpZ69lVJgTGGBLPBbDbmmEYu7Cryknn+p1RWl6KZbuW4ew6Z9syp9tRfves\nPDJMTN4EMEKUiJkAQD4qCrRdpKWzVsvjJCIMJ0JdItSQX4bEdQB2WzMMYwd2PqQSEQa3HsxR11Fg\n5ZFhYlJZVhwBQJSIWQAqa+2s9ewaGvirdFULAE21TuQk7LZmGMYO7HRbA1LC8EETBuGpS5/iNDVh\nsPLIMDH5nXz0OKTAGQC4EcDvWjtrsjwKgSYqr6RQHIGA5ZHd1gzDWIxdATMy59Q5B2mUhoXbF9o2\np1sJv8az8si4HSJ6h4h2EdEyRVsJEW0losWB1xWKbY8Q0ToiWk1EPRXtHYloGRGtJaKXNE7/JwC1\nAXwOKedjrUCbJjSdXUS4Wa1dCLyvdSIn4QozDMPYgd2WRyLCkDZD8MnKT9Cpfifb5k0GCioXOC0C\nw8TjXUjV+sJ1qReFEC8qG4ioFYDBAFoBaADgOyI6S0hPTWMA3CaEWEBEU4iolxBiaqyJRYk4AOBe\no4JrXfPYSfG6GMBIAJoSSboBAvGaR4ZhbMFOyyMgua7HrxzPD8hhjOw20mkRGCYmQog5AA6obFK7\niPQFME4IUSaE2ARgHYDORFQHQL4QYkFgv/cBXGuFvEo0WR6FwF+Un4lQDcA4SyQyAdl7If9ltzXD\nMHbgxHWmbUFb5GfnY97WebiooaZASc+itPpmpWcBCCwl4PWgTHJxDxHdBGAhgPuFEIcA1AcwV7HP\ntkBbGYCtivatgXZL0Wp5DOcYgISKatsJu60ZhrEDu93WMsVtivHJCo66ViJf89nrxCQZowE0FUJ0\nALATCVSBiQX5qIuWtmhoXfM4CQiegemQfO7jtU7iFPI1nN3WDMPYgd0BMzLFbYrRfWx3vNjrRaSn\npds+vxuRr/lCCHUnIMNYyKxZszBr1izd/YQQexQf3wIwKfB+G4CGim0NAm3R2uPxKqQyhfHaVNEa\njvaC4n0ZgM1ChJhJXU0apbHlkWEYy3HK8tiiVgsUVC7AnD/moFvjbrbP7wbCDQRVs6sCkCyQ6WCF\nmrGXoqIiFBUVBT/7fFHLiBIUjzdEVEcIsTPwsT+AFYH3EwF8RESjILmlzwTwixBCENEhIuoMYAGA\nmwG8EnUyH10IKRF4bfLRCMWmKoD2E0XrmsfZRCiEFDADSAs1kwauMMMwjB04ZXkEJOvjuBXjUlZ5\nDKdqparITMtkrxPjWojoYwBFAGoS0R8ASgB0J6IOAPwANgEYBgBCiFVENB7AKgCnAQwXFYrN3QDe\nA1AJwBQhxLcxps0CkAdJ/8tXtB8GMFCr7Frd1oMBPA9gFiQN+VUiPCgEPtU6kROEBMzwBYRhGBtw\nKjijuG0xLnj7Arza+9WUzXEYrrjzenfGzQghrldpfjfG/s8AeEalfRGAdprmLBGzAcwmH70nSsRm\nrbKGo/UK8xiATkJgNwAQoTaA7wB3K48yXGGGYRg7cPIhtWn1pmhcrTFmbpyJHs16OCaHmzhVfgqH\nTh5CpbxKTovCMG4jm3z0JoDGUOiCokRcqqWz1mjrNFlxDLBPR1/HYbc1wzB24KTbGghEXXOt6xDm\n/DHHaREYxo1MALAEwN8hlZ6WX5rQann8lghTAfwv8LkYwDc6hLQVWU+UvUfstmYYxg6cCpiRGdxm\nMM554xyMvmp0MM9hqhDNQMA5HhlGlTJRIsYY7aw1YOZBIvQH0DXQ9KYQ+MLopHZDIJSLcqfFYBjG\n4zhteWxYtSFa1GqB737/Dr3P6u2YHG7Cyd8jmVm/fz1Olp1E24K2TovCWMMk8tFwAF8AKJUbRYnY\nr6VzTOWRCGcCKBQCPwmBzyEV0AYRuhKhmRDYYFxu+0ijNJT5y5wWg2EYj+O05RGocF2novKo9t3n\nZ+er7MnE48J3LsTe43shSthr51GGBv4qXdUCQFMtneNZHl8C8IhK+6HAtmu0TOIUFe5rDphhGMYe\nnLZ0DWw9ECWzSnCy7CQqZXCgyNilY3F508udFiPpsPOe+cehP3DgxAGcXeds2+ZMdUSJSKhKYDzl\nsVAILI+YVGA5ERonMrGdcIUZhmHswA2BefXy66FDnQ74dv23uLbltU6L4zhT1091WoSkxM6HoN4f\n9cbKPSvZymkj5KOb1dpFiXhfS/94EdPVYmzL0TKBG0ijNFdc1BmG8TZucFsDqRl1Hc1AwF4nY9h5\nHHNMgiN0UrwuBjASQB+tneNZHhcS4Q4h8JaykQi3A1ikT077CNcT2W3NMIwdOB0wIzOg1QA8/N3D\nOH76OHIzc50Wx1GcVky+/O1LtKzVEi1rtXRUDoZRIkrEX5SfyUfVAIzT2j+e5fE+ALcSYRYR/h14\nzQZwG4C/6pbWZuQHJ3ZbMwxjB26xPNauXBud63fG5LWTnRbFcZw2HPT7pB/++q3rb5cRuOEhiLGV\nYwA0r4OMaXkUArsAXESE7gDkeP3JQuB74/LZR0h5QnZbMwxjMW6xPAIVrutBbQY5LYptqH33TiuP\nSshH2PK3LWhQpYHTosTFDQ9BjHWQjyYBQataOoBWAMZr7a81z+NMADN1S+cS2G3NMIxduOWm269V\nP4yYNgJHSo+kdLoaN1z7lUrtlkNJojy65CGIsYwXFO/LAGwWJWKr1s6WlhgkoneIaBcRLVO0VSei\naUS0hoimElFVxbZHiGgdEa0mop5myWFnhZm3F7+N0+WnAQCbDm7C5oOG644zDJNkuGl5TI2cGuja\nqCsmrpnotCi2EM275AblUYmbjpFYuOUhiLEGUSJmA/gNQD6A6gBO6elvdX3qdwH0Cmt7GMB3QogW\nAL5HII8kEbUGMBiS6fRKAKPJpKOXYJ/l8Y5Jd2DF7hUAgJavtUT719vbMi/DMM7jJrc1AAxpMyTl\noq7DcZvyyDBugHw0GMAvAAZB0r3mk48Gau1vqfIohJgD4EBYc18AYwPvxwKQE5H1ATBOCFEmhNgE\nYB2AzmbIQUS2r3k8fvo4SstLcbj0sK3zMgzjHG4JmJHp27IvZm+ejYMnDzotimOU+zkNjBHc9BDE\nWMJjADqJEjFUlIibIelbj2vtbLXlUY0CIcQuABBC7ARQEGivD2CLYr9tgTbDyNdwO93WMs/8+Iyt\n8zEM4zxuszxWya6CS5tcii9/+9JpUWxBTXF3g+XRTQ8UWpFlnr1ptsOSMBaRJkrEbsXnfdChEzqh\nPIZjulYnGxmD5QltdFsD0kl3suxk8POvO3+1bW6GYZzFbYpCKiYMlyEQ7rvgPqfFCHmgcNPDRSxk\nOYvGFjkrCGMV35KPppKPbiEf3QJgMoBvtHbWFG1tMruIqFAIsYuI6gCQNd9tABoq9msQaFNl5MiR\nwfdFRUUoKiqKOqETqXqUN5DPV3+ODnU62Do/wzD248ZgiKubX41hXw/DvuP7UDO3ptPi2MrwTsPR\npFpCJXxNx43HCJN6iBLxIPmoP4CugaY3RYn4Qmt/O5RHCrxkJgK4BcC/AAwF8JWi/SMiGgXJXX0m\npMWcqiiVx7gC2Jyq55t13+DFuS8GP3OOSYZJDdzmtgaAvKw89GrWC5+v/hx3nHuH0+JYhppS5sSS\nJa/gNgs6Yw7kozMBFIoS8ZMoEZ8D+DzQ3pV81EyUiA1axrE6Vc/HAH4G0JyI/iCiWwE8C6AHEa0B\ncFngM4QQqyAlqFwFYAqA4cIkrcuuCjN7j+8FADz6/aOOl8RiGMZ+3BYwI5Oqrus0SnPFmsdYrN23\nFkdPHXVajAjc9hDEmMZLANQieQ8FtmnC6mjr64UQ9YQQ2UKIRkKId4UQB4QQlwshWgghegohDir2\nf0YIcaYQopUQYppZctjltn5w+oOq7QKC1z0yTArgRssjAPQ+qzcWbl+IXUd3OS2KpYR/93avd49G\nrAeKFq+1wIPT1O8dDGMBhaJELA9vDLQ11jqIGwJmLCNY29omt3U0BXXh9oU4541zLJ+fYRhncavl\nMSczB1c3vxqfrvrUaVFsxS2lab9Z903MlEFHTh2xURomxakWY1uO1kE8rTwqo63tcFtHu2mcKteV\nuJ1hmCTGjZZHIDVd10SEMn+Z02JAQOCnLT85LYYu3PgQxJjCQvJRxOJn8tHtABZpHcSJaGvbcfrp\nkxdsM0xq4AYrVzR6NuuJoV8OxbbD21C/SkIpdF2J2nc/esFonCg7gYe6PuSARNpx4z3CrQ9BTMLc\nB+AL8tENqFAWzwOQBaCf1kE8aXmMyPNIBD+sd1vzycYwqY1b3dYAkJ2Rjb4t+2LCqglOi2IbJ8pO\nAACu++w6fLFacxYS2xFCYN/xfa56+HDrccwkhigRu0SJuAiAD8CmwMsnSsSFokTs1DqOpy2P8nno\ntOWRYZjUwK0BMzLFbYrhm+1zReJsOxm3YhxOlp1Ev1aaDSumE+u4EBCo9XwtTBwyEde0uMZGqdQh\nn3uPYcYcRImYCWCm0f6etDyGY1fEnZtvGgzDWI+bLY8AcFmTy7B+/3psOrjJaVEsIdZ37+br8+S1\nkwEAu47ZGw2/YNsCHCnlYB1GP6mhPJI9ATPRmLVplmNzMwxjH263PGamZ6Jfy34Yv3K806J4ltPl\np7HxwEZMXDMxpF1WbNW8YE5FW3d+uzOe/OFJR+ZmkpuUUB7tclu72eLAMIw9uP06MKTtEE9GXccz\nENj1u4yaNwpNX2mKvuP6YuH2hcH2WKl6ZJxYXnW6/HTcfQ6XquWUZlIZTyqPEQEzLkkUyzCMt3Fj\n1Gw43c7ohm2Ht2H9/vVOi2IrdlmED508FHy/7/i+4PuisUVx+zpx/GhRqrnIBROOJ5XHcOyqb+pm\ndxXDMNbjdrc1AKSnpWNg64H4ZIX3rI9u4LS/wpKn12jxf9P/D7uP7TZbpIRh4wsTjqeVx5BUPXzw\nMwxjMW4PmJHxasJwNyjuGw5sCL4/fvp4xPZYx8eh0kMofKHQErmioeU742wlTDieVh5lCMRrHhmG\nsZxksDwCQJdGXbD/xH6s3rPaaVE8x8myk8H3X635KmK7EAKvL3wdy3Yts1OshGDjCxNOSiiPdrmt\nGYZJbZLF8phGaRjUepAnrY/RsOt3mbJuSvB9NKXrrsl3Yfjk4bbIYwasPDLhpITyaNRt/eTsJ3Hw\n5EHt88SxOJCP8Nmqz3TLwTBM8pAMlkcAKG5bjHErxnnGJan2fzj9W8S677il1rUWpZqVRyYcTyuP\nymhrIxfIf8z6B6ZtmKZ5/4y0+AV73l7ytm45GIZJDpJJETu//vk4WXYyqdyneslKzwq+d0KRVFPM\nur7b1XY5YhGej1INVh6ZcDytPMoYcVvLN4FT5ac090lPS9c1B8Mw3iJZ3NaApNh4LXAm/LtPI2dv\ncTkZOY7OH87p8tNYsXtFSNu6/evi9mPlkQnHk8pjRJ5HA27rUfNGAQDK/GWa+6RTfOUxmSwTDMPo\nI1kCZmSK20rKo1evS0qjgdVK/eaDmyOSaTutvIYzdulYtBvTTnc/Vh6ZcNx1ZFuEkQozi3YsAqBP\n2dNyceLAHYbxLslkeQSAc+qcgzRKC17vGGMcOnkIjV9ujKrPVg1pH7t0rKHxyGfNMWS0yk25iN+P\nSS08rTwmUmFGPoH0nDRaLA5arJMMwyQnyWZ5DLquPZAwXO3BfNi5w4Lvrfxddh7dqdquZ9mTHahZ\nQlvVahXyWe17dLvlsbSsFOv2xXe/M+bhaeVRhoh0W/xkpVHLk5pynngMaDVAlxwMwzBWUtymGONX\njXe9gmCEPi36BN9PWjvJsnncbm1+f+n7uPPrO4NyKvN7dq7fOWRfNcuj24+NF35+Ac1fa+60GClF\nSiiPRtzWB04cAADcOfnOiAXG0Qh/sr2o4UUR+3BQDcN4l2RzWwNA24K2qJxZGfO2znNaFNNRXvfV\nqr2kCqMXjMYbi94IWh5bj24ddV81RdHtyuOh0kPxd2JMJSWURyNu6+m/Tw++X7xjsbZ5wm4a4e4A\nhmG8TbK5rQHpujWk7RBPuK7Dv3u7lB4jv3njao1jbj/zlTMTzgs8ee1k/HfJfzF/23wAwG0Tb4vY\nZ+2+tSGfk9FtHVxmpsNTyCSGp5VH+aEz0Qoz8U6c3cd2g3wUcQFRW1/i1ahGhmGkG+/bbxOS7TQv\nblOMCasmeO7m6+YAxYsbXRxz+4YDG/DGojcSmmPY18NUFUYAeH3h6wCAuVvnhrQno+VR/p1nbJzh\nsCSpQ0ooj0ZS9dTNqxt8H++Cuv/EfgCRJ6Gq8ujiixnDMIkhhMB9fyUcPhx/XzfRolYLFFQuwJw/\n5jgtimHUHsztelg3slThg2UfxN1n+u/TLfsfJqyaoNqudq+0+ntM1FrPRhn78aTyGH4cGakwM7xT\nRd3ReBHX8sn24x8/hrTf1P4mAECljEq65mYYJjkREIBIzsuq1xKGA5EP605Z0KIFSm4+uDlu30TS\n5Ow9vjfqtmg5jJ1I1WOWUYWzmdhHcl7ldGLEbV1QuSD4Pl66hfCTbdqN03Bxo4uDSuPJspNR92UY\nxjv4hT95lce2xfhs9We6CiO4nfDr7Z5jexIe84WfX8DoBaNV54lmKMjPzldtP3LqSNz5yvxlmLJu\nSkxFMBql5aVRt0UrS5mMbmsZtyVl9zIp8U0bcVsrXdVK5U9137Cnsh7NeuCHW39Am4I2+Mcl/0CN\nnBrBbey2ZhjvkszKY9PqTdGoaiPM2jTLaVEME+4+Dr/emhEJ/+D0B/Hg9AdV54l2ryAQujfuduCg\nIgAAIABJREFUrtoejzJ/Ga76+Co88+MzBqSNzsGTB1Xb1e5Rbjd6yDJzNhP7SM6rnEaUScL1HvxK\nZfOV+a9o3ldJpYxK8HX3uS5RLMMw5iOECFEex4+PXELjdrySMFzGKqXnVPkplPnLcLr8NOZvnY+M\ntIzYckBgyg1TItrbv94+7lxKS/CJ0ydMsZ7GQu1+5vYKM/LvzG5r+/C08ihjxG19ouxE8P2Ww1ti\n7hvPqllaVuE6cPsTHMMwxhCQ0/RI1qTiYuDYMWdl0svgNoPxxW9fJOUDr6rFLNzyaFIapTJ/GTKf\nzMS5b56LC965IK5LeejZQ1Vdqlo8YuNXjgcg/S9/mvgnFLxQEKdHYiRjknAZdlvbh6e/6USircPd\nErGIF4192n+6QiZ2WzOMJ/ELf/DmdVsgO0qS5QtHo6qN0KJWC3z3+3dOi2IK4dd9sxO4L9+9HED0\n4BOZhlUaGlZshn0tlVh8Z8k7GLdinKEx4lHmL8PSnUsBqCuK8SyrTsNua/vxpPKofHA6dsxYhRkl\n9fLrxdyeLE9lDMNYh1J5/CyQ21kI4HiSFTbxUtR1+IO9VZ4fOWdiLBK1ih0utS7/08fLP0aHNzpg\n2+FtEQaOlrVaorByoWVzm4H8u7Ll0T48/U2vXg3k5RmrMKPksiaXxdwez5p4d6e7K/ZltzXDeBKl\n8ijTsSNQubJDAhlkYOuBmLRmUtxAQTcS7pbuWLdjyGerHvTVcjZ+MrBCAW9SvYkmxUaUOHN/kH/r\nBqMaRHxHzao3s9xAkuhyAtminGzVnZIZTyuPB6Ty1CAiS93Fyqfbr6/7OmL7a71fC77fc9zaxc4M\nwziDmvK4bp1DwiRAvfx6aF/YHlPXT3ValIQ5o9oZIZ/t9BI1qtoo+D6ZLGLK72hAqwEJV2jTQqLj\nn1FV+p3ZC2gfyXNEJ0Cibut4B7bygM3NzI257+MzHzcsB8Mw7qXcX55USkIsvOS6VjJz00xb5mlV\nq1XwWHjgwgfi7h+vVKHVKO+PyvdplIY0SnO9UlY9pzqA5IspIKJ3iGgXES1TtFUnomlEtIaIphJR\nVcW2R4hoHRGtJqKeivaORLSMiNYS0Ut2yO6NK10Yzz8v/ZXXRhtxWyvdHVlpWTH3VS6WdvvCYoZh\n1Fm5e2VC/f3C75kF+wNaD8CUdVNw/HTyLNjUYiBYsG2BDZIAv975K1rXbg0AuLH9jXH3H9xmsOky\nHDhxQPO+ylQ8yntlGqWBiFxf81z+7d2u5KrwLoBeYW0PA/hOCNECwPcAHgEAImoNYDCAVgCuBDCa\nKiLAxgC4TQjRHEBzIgof03Q8qTweDOQ+DSqPBtzWi3csRu3c2gCAVrVbxdxXaW1g5ZFhkg8hBNqO\naZvQzUfNbZ2sFFQuQOf6nTF57WSnRTGVWBVXzCQrPQt5WXkAgMz0zLj7W7EWXo/lWKkcCgjkZ0kV\ncdIoDV/+9iUGThhounxmIp+3yRZTIISYAyBcy+8LYGzg/VgA1wbe9wEwTghRJoTYBGAdgM5EVAdA\nvhBCfjJ6X9HHMrxxpYuDUbd1SbcS3H/h/XH3Uz61ablQMAzjLuSHS1YeK/Ci63rMwjG2zlc/vz4a\nVGkQdz8r3K16jkXlce8X/uB9zOzURlYhy69Mi5fEFAghdgGAEGInADmxZ30AyqTT2wJt9QFsVbRv\nDbRZineudCok4rYGtJ/Qyqc2tjwyTPJhhtvLa8pjv1b9MP336ThSGr/+sltwm7KzdcRWVMmuEne/\ngsr6En9Hq0ut5LVfXou7j8z2I9uD74UQyEqXlmoly/Esn7cjZ410VhBrcKU51dOajnwdMRotpvVG\nEmJ5TGPLI8MkG2x5jKRGTg10bdQVk9ZOwvXtrndaHMNc1uQyzNg4AwDQqV4nh6VRp7hNMS5vernm\n/c9+/ey4aX3kBOZaeO7n54Lv/cIfvI/ZlfomkXmEEFi7by0AYMOBDQCk8pE7juyIiLa3k1mzZmHW\nrFlGuu4iokIhxK6AS3p3oH0bgIaK/RoE2qK1W4p3rnQqKNc8GrI8BqwR8VzebHlkmORl4faFWLxj\nMYD41aJiUS68E20tk0yu62gGAl+RL/g+XsEHM5ADZfRARKiVW8s0GXp80MNw3/X71wcDvwa0GmCW\nSJbx9+//jhfnvQig4l799I9Po/HLjR2UCigqKsLIkSODrxhU1DSVmAjglsD7oQC+UrQPIaIsImoC\n4EwAvwRc24eIqHMggOZmRR/L8NaVLgoEMrTm0S/8mp6IyvxlQTM/K48Mk1x0eqsTLnj7AgCJWx7T\nyRvR1jJ9W/TFrE2zcPDkQadFMQU7onFr5tSMum3Pg3sw5fopwc/n1j0Xi/68KGSfns16hnfTTSLl\nJXt+2BPplI7HL3kcfVr0SVgWLSSy5vPpOU9HjBOv1ngibDm0BY9/b07KPSL6GMDPkCKk/yCiWwE8\nC6AHEa0BcFngM4QQqwCMB7AKwBQAw0WFYnM3gHcArAWwTgjxrSkCxsDTyqNdbmulmT+a5WHYucN0\nz88wjD3I1wflEhS9eM1tDQBVK1VF98bd8dVvlhsyLEN57U/k99VKrKCNWrm1UL9KRSzDoh2LIqrg\nNK3W1DLZtEJEeKL7E65bQxqPrYeluBErHxI+WfkJ/vnjP00ZSwhxvRCinhAiWwjRSAjxrhDigBDi\nciFECyFETyHEQcX+zwghzhRCtBJCTFO0LxJCtBNCnCWE+KspwsXBW1e6MA4dkv4adVtP/326pv2U\n7qpoJ9u959+re36GYeyF1zxGMqTtEIxbOc5pMTQRz1Nkh2J2ujx2xG/7wvYxt8v3kDp5dUyTSS9e\nPI7NQv5ulPmdUxFPHyFr1kh/9abqkffVenCU+8uD7uq6eXVV9/GaO4thvEgiax69qjxe3fxq/Lzl\nZ+w7vs9pUQwhX8//3PHPaFfYzvL5Ek0Xc1HDi5CbmetowutkrxFtZb5H+Rzv9aHlebhdjfeudCro\nTdUj7ys/IcZzeX+97ms0q9EMRY2LkJ2RrbqPVypPMIyXScSt6aXyhErysvLQq1kvfL76c6dFiUk0\nhUG+fqdRmqWVUu467y4A2qzX1SpVi7rtxvY34tijx0xTHm9qf5PuPsl+HFtZplD+bn7Z9otlcyQD\nyX2EaERvhRl53x5Ne2ha8/Hhsg+xcPtCzBwavW5qsp+MDJMKJGp59OpDYjJFXUfD6hrNJd1KAGg7\nhg48FL90oFnWs1gpgDb+daNqe7KtdQzHSsvjmr1rLBs7mUgJjeazT/W5reUAmCvPutI0GdhtzTDu\nhwNm1Ol9Vm8s3L4Qu47ucloUw6SnpVuqPBbmFQIAHun6iCnjmWU9i3XvycnIUW23+zhOJjf5+Q3O\nd1oEV+DNK10YK1bod1ub/eSlzC927NQxU8dmGMYceM2jOjmZObiq+VX4bPVnTosSE7Xrtmw4SKO0\nhB4OhBBRjw/ZZQ0Avc40Zy2cUUX3t72/hXyOtpQKiK6gJpMyJ1MluwquPFMy+Fjptq6RU8OysZMJ\nb17pwhE63dZCmH4TyEzPRHa6dBI7nbyUYRh1XvvlNcPWNS8rj0Dyu64TdVs//ePTyHhSPY/v6KtG\nAwBEidBdajAa8WQ9WXYSz855FjN+nwHyVSh7rf7TKmS/ShmVIvre0+keANHdu3Yfx2Yoe3Xy6mDr\n4a1Yv3893lr8lglSqSMr1smoYJuJJ690ffuGNQj9bmvlyWPW+gl5TCsTmDIMY5wX572I9359z1Bf\nryuPvZr1wvJdy7HtsOWVzywhUeXxo+UfAUCwIITVxLvvLN25FI/MeAQLty8MtimVSBn5f77v/PuC\nbbKLPRpqx7FyHrshH+H3A7+rbrux/Y0ApAIdy3cvR8c3OqruZzanyk/ZMo9b8eSVLvycE8KA29qC\npwuvLqZnGC9h1ArixfKESrIzstG3ZV9MWDXBaVFUifa7ye3plG5oWYJf+LH/xH6s3rsagKQ0vHn1\nmwCAyddPxvc3f29I3uI2xXi066NRtz/Z/cmY/W/56hYAFa76aEq9rISOumIUqleqHrotmtta4f6/\npvk1AIAZv8+IKY/VbDq4SbW9WrYUuS6ny7M6xdH6/esBAKXlpZbO43Y8eaWLUB79+irMCJjvtgaA\n28+53fQxGYZxB14sTxhOMrqulWsejSgWoxeMRs3nQksOtqjVAoAUSNS9SXdDco0bOA5PXfZU1O1/\nveCv6NE0eo3q8LWN0e5ZOZkVQTHhLuxoVlTlWMM7DY8qg53E++1k5fHYaWtjCu6fdr+l4ycLnlQe\n14RF0gu/fsujFcrjqCtGmT4mwzDuwOtuawC4rMllWL9/PTYf3Oy0KJqRFSajyuP2I9sj2i5ocAG+\nu8l4/WitPH7J48G18jKXnHGJrjF6NO2B1XdLVtO5t83FmnsqbpC1cmup9lF63H7d+avU5nD6nni/\n3eIdi2NuL/eX43DpYTNFSmk8eaVbuzasQVBCax618NWQ5K39yjBM4qSC8piZnol+Lfth/MrxToui\nitoyowsaXICVw1caVh7VftN0SsdlTS8zJKMeLj7jYjzX47ng5z4t+uDAidAckQ999xCA2C7olrVa\nAgDOqHYGmtdsHnc5lvJ/ll39TgeIRLuHnyw7qan/P3/4J6o+WzVY/1ovhS8UpnxJQiXevtIF0Ou2\n9gs/jp46WtFfQ1+1iDaGYZKPf/30L0P9UkF5BJLPdU1EaF27NTYf2ox/zPqH7v5qSxHs/J2VStv4\ngdGV9sETBmseM949Tbk+X071Y6XlUYtiGk1mrWsPNx3aBADo9l43zXIp2X1sN0rLUnudoxLvX+kA\n+HW6rd/79b1gfVKtJ0yqR14xjFc4ePKgoX6pojx2a9wtmBLFTcTzLkWL1o2H2m9qpwtXnmvNPWuQ\nnZGNRy9WD7L5actPEW3PXf6cyp7xUf7Pw84dZmgMs1G7hx8/fRwLti+I2e9I6REAFQrq8dPHE5LD\nyhySyYSnrnTXXguondMrlutL1RMtqisWRY2LdPdhGMY7jF4wWvUG7jUy0jIwoNUA17quoyEHVOjF\n6QcCef7mNZsDkJJha6VLoy6q7UpLX5vabaLOCSgsjxa6rbUoZGr38JfnvRwROBROlWerYPWe1abJ\nb3U0d7LgKeXxqyjLDteu0R8wo4ecjBzH14MwDOMs8W5iXmJI2yEYt2Kc02LoIjM901A/p5XH8HuL\nHkOIFtmX3rkU026cFncMpwNm1BRMrVbAAycPBP8PK+tepxKeUh6jo7/CjB4EhOMnFsMwznL/hfcD\ne1s4LYYtdGnURcp9uGe106KEEOs6bDTYwWnlMRw997JoqaMubXJp0OKYnpaOHs164C+d/xLcvmj7\noogxnDaQqBl1tKbGEsKae/T8rfNNHzNZcNdZYRU6K8yEn5zx+gohNJ9YTxQ9oVkOhmGsp11BO1PG\nyUrPAnapjzVxoilTuIY0SsOg1oOSKnBm1qZZhvo5rTyGKz163O/RFKYLG16IFcNXhLS9dMVLGNVL\nSienzJUoj+H0Wj9V5VFH4Y2g5dHE/+OCdy4wbaxkI0WUR+Nua61RYFqfavq36q9ZDoZhrOe8eueF\nfM7JyImyZ2yk64b6dSCiZKoHKG4rRV27xQ1olXLjdGWwcOW1Z7OemvvqsRamURoy06K79p1e66d2\nnGlV7EfNG4U3Fr0RdRytczutQLuJ1FAedbqt9Z4keiyP9fLroVqlarrGZxjGOvzCj8qZlYOfG1Vt\nZGgcAQGIFLmkAji//vk4cfoElu9e7rQolhJ+bbfbEmnn/LHuk1Y+JBhN1aPVbf3Z6s+C741kRpHn\nbjiqoe6+XiU1rnQ63dZ618bwmkeGSV4EBF7r/Vrws9GcrX7hB0TqXAeICIPbDMYnK5LHdW2EcGWj\nSbUmDkmiH733parZVaNuc9ryqDa/UpFWO2/V0jMdKj2ke25ZfzCaxsuLpIjyaG20tR7LI8Mw7iL8\n/F26a6nhcVLJ8ghUJAx3i+vaiuvwo99X5FWsnVsbb17zpulzxKJ+lfqG++r9Pm5of0PUbVYqj0ZT\n9SiXFNTPj/yejFaTiZib3dURpMaVTuirMNOvZT/UyKlR0T1OX7Y8MkzyIiDirvfSQqw1j16lY92O\nICIs2rEo/s4eYM6f5uDSJpfaOmfvs3rj8MPGajLrvS/Fcom7sS600m2dlZ4VsT1aNZkzXjojqeqz\nu5HUUB6hz/KYRmno0lBKrqrl5NNreXTLUzrDMJLSR0TYfv92XN38asPjpNqaR0C6Pha3KXaF69qO\n62rNnJqWz6FGfnZ+yOd6+fU09TPLEntty2vx7E/PYsbvM0wZzyhvLXoLd319V/Cz0vJYK7eW5nH+\nOPQHJq2dpLnaTKxjK3zb0C+Hgnzef4hMiStdbi7pTtWjZ1GyHssjWygZxl3ID3+1cmuhILfA8DgT\nVk0AqhsrgZfMFLcpxvhV41PiobhmrjPKo17kHI518uqYMl71StUBSMm2neSVX17B64teD35W3qcF\nBCZdN0nzWH/55i+4+uOrQT7C/hP7MWbBGExZN0V131jexy2Ht4R8fn/p+5plSGY8oTxu3w6cOBF9\ne8vm+tzWsiVCD7zmkWGSE+XDX/vC9obH+Xrt10Aj75cnDKdtQVtUzqyMeVvnOS1KTMZeOxaANzw/\n8f6HvKw8AEBhXqEp8wWrzLjsPie7rZtUa4K3rnlLt+dg5qaZAIA5f8zB8CnDcdfku1T3C/++f/pT\nxXne5399QrYNPXuoLhmSFU8oj/XrA7m5sfbQ57YWQrvlUT6o2KLIMMmJ8nwf3GawadaaVCHounZ5\nwvCb2t8EACgX5br6PXbxY1aIkxBqxpCP+38c/B/r5tc1dT6nE6XLREtbdNVZV6FlrZaGx+07TkrE\nGk1PUH7fDas0RIMqDYKfw13fRvPEJhvuOCIsRvj1perxC3+oOTzWegeOwmKYpMYv/MGbUkZahuEy\ndqlMcdtiTFg1wfF0LrEe4okImWmZKPfrUx6f+vGpRMUynYe7PAwA6FSvU7DtunbXBa1e71/7Pjbf\nZ15AiNX1rbVaNOX5S8tKAVTcf7MzsoP7jOw20rAc0e71yvZw/eBw6eGQa4ZbFG2rSY3/0kCqHvlg\njndQc5oehklulG5rVh6N0bJWS9TKrYU5f8xxWpSYnPafxtilY50WI2H+esFfIUpEMLBT5sKGF+L5\nHs8jPzvfcLJ7NdxQ35qIgvNXekrK6Sjf1x+/5HFT5tBieVTqBwCw69guPDZDsk7vP7Hf8XWhdpEa\nyqPOCjN6AmaMpOlhayXDuAflA6CsPJaWlRqqRJHKDGkzBONWjHNsfq3X1SU7llgsiX2UFJWE1GbP\nzczFAxc9YPo8oxeOBmCd5THWb3fHxDsAAIMmDIpwEfuFH7d2uBVVK0VPbq6HHUd3qMunsDyq6Qcb\nDmxAaVkpaj5XE/9b8T8AwPYj202Rya0krfJ4+jTg9wPHNUTaG3Fbaz1J9Foe2UrJMM5z4MQBjJg6\nAkDozUBWHtuMbhOxEN4sysqA0lJLhnaU4rbF+Gz1Z6633Opd8+hmqlWqhq6NujothqW8veTt4Pvd\nx3aHbNt5dCdOlMWIljXIqfJTUdPtqOkHpeWluPT90Pyfi3csNl0uN5G0yuOVVwL/+hdQuXL8fXVb\nHvUEzHCCcIZJOub8MQej5o0CEHozkJXHDQc26Ep8rTVfHADccAPQ0IMlcptWb4pGVRth1qZZTosS\nEz3K7f4T+y2UxBzq5pkbHBMLp40f4aUFH/v+sQhrt3yvz0jLMDxPuNdBqT/sPrY7Qj/4eu3X+HnL\nzyFtbn+ISpSkVR5nzADWrNG4c6DerFbrY/iahnjF4p0+oRiGMY7yHE5PSw9e9Pce36t5jMpPa3qK\nBQD8+iuwZ48+GZMFpxOGa7kW61n/3vK1igjeEReMMCST1Txy8SPY9cAu08ZTVm0JJ5kMJUaVtyU7\nluDE6VBrZvhnvuc7qDwS0SYiWkpES4jol0BbdSKaRkRriGgqEZmzkAHSj63V+qh0Y8U7WdjyyDDJ\njfIcTpVISasY3GYwvvjtC5wuP+20KFE57dcu257jFVp+69qtrRAnYTLSMlBQ2Xhy+3Bi3SeTQWm6\n4swrEvqtOr7ZEWMWjglpK3gh9PvVcp1Ihu8qEZy8UvoBFAkhzhFCdA60PQzgOyFECwDfA3gk1gBa\nlzEKISmBWp84w0PxY4/NlkeGSWZiLVOZu2WuzdIkN42qNkLzms3x3e/f2T63Vs/Srzt/NTS+l9ZK\nxkLte7ym+TUAnE/Vo4ULGlyAlcNXJjTGD5t/AAB8sfoL1e1plBZX5ms/uTYhGdyOk8ojqczfF4Cc\nR2EsgJjfvlbl0e+XfmxdbmutATNGoq09UOGAYbxC+DIVJX8c+kPfYJ+nRmmyWLg9YfhFDS4y1K97\n4+4mS+JO1CyP/Vv1B+B9a5rMjI1SDe/+4/uj01udIrZnpGW41hJtF04qjwLAdCJaQES3B9oKhRC7\nAEAIsROAKbb45culg16r5VEIgTSNX43uaGt2cTOMq4j1AFharjMsemcHEyRKbga1GYSJaybiZNlJ\np0VR5e0lb+PYqWNx9/vLlL+EfD6r5llWieR6Yq2D9DoLty+MaMtIy0j5lHtOKo9dhBAdAfQGcDcR\nXQxE/Boxf53NOhLoE2lf8xhueYxXYYYVQoZJXmI9AA79UqrYcfTUUWzYv0HDYNEvqQsj70GepF5+\nPbQvbI+p66faPrfWa7GWh4I3Fr2RqDieweoKM2r35lV7VkVNlwNAd6UgM0lPS11lWsYx5VEIsSPw\ndw+ALwF0BrCLiAoBgIjqANgdfYSR+OGHkQBGApgVdz49buuQgBmuMMMwnkN5s/pm/Tcx0/L4hR8j\npo7Ama+eqWHg6JfUTpHeL8/idte1FjLTM50WwTHC72lyyiI773Xr96+PuT3jSeOpeBIlMy0zWEc8\nVXFEeSSiXCLKC7yvDKAngOUAJgK4JbDbUABfRR9lpOJVFH9OHW7rWGugwmHLI8MkP6v3ro667ezX\nz8Zbi98CACzaHif3YwzlUWbtWl2iJSUDWg/AlHVTdOW/TBSz3Yh2yu42wu9p8ncxd6t9AWRWKKpn\n1tDwAKgBIsLDXR9GbmauKeMlI05ZHgsBzCGiJQDmAZgkhJgG4F8AehDRGgCXAXjWrAn1uK11JQk3\nYHlM9bUSDOM2Yp3DK3avCL7/cNmHsQdSKI+33x5jP49TULkAnep3wpR1U5wWRRW9QYtPdn/SIknc\nSfj5ICfcfmX+K/bJYJJR5sRjFTkam1ZvCgCok1fHlLHj8e36b22ZxwkcUR6FEBuFEB0CaXraCSGe\nDbTvF0JcLoRoIYToKYQ4aNacaZRmTaoetjwyTNKy7fA2ANrzO/qFHzM3zsSr818NtoXmNKy4FjRq\nZIqISYubXdd6H+Af6Roza5yn+Kj/R/io/0chbbLy+OjFj1o+/61f3YrMJzOx9fBWU8arlFEp+P7D\nfh/ipvY34a1r3gq21c+vj5eveNnQ2Ledc1vM7W6vtpQIKZMRl0CGU/WYWWGG10cyjHu4Y9IdALQr\nj2X+Mvxj1j9w77f3Btv+s+A/FTvEcVvrCfJLdvq36o9pG6bh6KmjTouSEE9f+nRKBUhc3+56FLct\nDmmT74fZ6dmWzKm8L/6w+QeU+ctw1+S7Eh6391m9Qz7Xyq2F9/u9H7RAAkCPZj1w7/n3hnfVxCtX\nvoJTfz8Vdfu/fvoXqjxTxZOlClNGeUyjNK4wwzAMgAq3peyNUCqPbQvaRu03euHokLQl7y99H9uP\nbFcMHPuS2rixAWGTlBo5NdC1UVdMWjPJtjnjPZxv/ZtkzdKj0Jq1Ti6Zkc+X+6beZ+nDwOgFo3VX\neaqfXz/qtsZVG4d8lu/VrWu3Rt28uujaqCsGtx4MAGhf2F6fsAHiBVYdOXUE9317n6Gx3Yxnlcdw\nfU5vhRnNATMcbc0wSUf4tUCpEMbzUMg3tzu/vhNDvxyK539+vmKjQnnkWgCS63rcynG2zXfTzcBx\nlTiXf/8bWLwYyMvKAwAM+XSI5jFll20qozS8PDH7CcvmuXvK3XGjrMO5tcOtqu0HHjqAUVeMCn5+\nt++7Idu3378dP976I64860oAwPSbpuuUVjvh5Q69gGeVx1fC1vXqcVvrCphhyyPDJB1yqbmVe6Qy\nZlqXqQAVyqNqHsAMdybGdoq+Lfpi1qZZOHjStOXrURFCYOq3wKZNkdseeAB49dWK33n+tvkxx1I+\nXFze9HIzxUxKlPfOU+XR3bSGx08giDTavbpapWrISs+Sxi8RuKXDLTHHKahcgD/u01lRSgU1JVSr\n4SqZ8KzymBsWQa/Hba2rPKGRaGs2STCMo8gJhuVF+YPbDA5ui3d+yqXLVEnz3tqmRKhaqSq6N+6O\nr36LkXXNAoiAL7803r/nBz2D7/Oz802QKPlYuLDCg3faXxEUZkVy7t/2/qZ5X1khlDHTeBNPyZPL\nNMYiVR42PKs8hqPHba1c8wiYW2GGrZQM4zyy5VFGud4poVRae1oZ7+tRnIq6XrbMeF/5ASGVlyRt\nUBRUuqb5NcH3e47vcUCaCsItn3rXSMYi3ljR1leuHL4Sj1/yePDz9e2uN00mt+JZ5TFc39NTYUaZ\nqocrzDBM8jHj9xm6Spsp1zw+UfQE/tn9nyHWSO1Icz74IHDLLQa6e5BrWlyDn7b8hH3H99kwG8Vc\na5qZpq9qDD/sS7Sq3QpjrpLW7bktet7M+2/Dqg2x4I4FUbc/3+N57H4gsvBd69qt8ejFj2L5XcsB\nAEVnFJkmk1vxrPKYkxP6mSvMMEzqsHZf7DIu4akzlEERg9oMwmOXPKZ7TlFSobU89xzneZTJy8pD\nz2Y98cVvX9gyn6w8hiuRREBOZk5khxjkZOjb38vID1xmWfqEECgtK9WdxiY8QGZIW+3BT1o4r955\nqJdfL6Stec3mAIDsjGzUrlxbtV+ljErBTA2D2gwyVSY34knlsUcPoDg0TZWrKswwDGPhut7QAAAg\nAElEQVQt8c71cLd15azKEfvcfk4Kl4gxmSFthljuupZ/czOXlMvR2UzFOWNW8MfL819Gpacq4ect\nP2vuM+fWOejeuHtIW/0q0VP1GGXNPWtCPl/a+FJd/atVqmamOK7Ek8pju3ZAelhOV71ua80BM2x5\nZBjXEe8GF+62Dl+EDwCNqrLp0Cx6n9UbC7YtwK6ju2ybU83yGLqdAxf1IJ8z4Q9eRlmyc4nmfWvm\n1MTK4SvRpVGXiAdDZQUZs8jLykOz6s0AAMcfPY5Xe78azBGqlQsbXGi6XG7Ck8pjmsp/pcdtHREw\nY2KFmXjjMQyTOFM3TAWAqOsetdwAzbCwCAE8/XTCwyQ9OZk5uKr5Vfhs9WeOyRChPGq4Dp9T9xyL\npInk+HHgj8QzxViG7F42q16zfH5NXT817r5n1zkbrWu3BhC6xvHDfh+aGjCjRF7ikJOZg4y0DN0W\nzrs73W2FWK4hZZRHCO1ua+WaR7MrzLCLm2Gs5+u1X8fcriXdSJPqTXBHxzs0zffgRQ9G3caOCQlb\noq4FRV3zGM7x08dxuPQwdh/bjZKZJbjk3Usi9pk4ZKIFQqozYgRwxhm2TacbsyyOMrLl9+k5xp6u\nhp07DDe0v8FMkUJINCVReIlHr5EyyiPpcFvzmkeG8TZaboSVMirhzWve1DRejZwaUbex8ijRq1kv\nLN+1PLScowWcfbZ6e/jvkP9MPqo+WxWFLxTiyzVf4sc/foRf+EPuE/FKz8Xj+HHgoYe07bsvEIz+\n0UcJTWka4d+X2fkd5RyrsahWqRqGnzc8xIrXs1lP3Hf+fXj96tdNlSecRJVlrZWJiGgTES0loiVE\n9EugrToRTSOiNUQ0lYiqKvZ/hIjWEdFqIuoZfWRrSRnlEUJftDVXmGGY5CVWvVsAeO6n53SNF0s5\nBGLXw2YksjOy0adFH0xYOcGS8bUaBxpUaRDRJitG6U+k49k5z5om0/LlUuS9FuTbyI03mja9qSjv\nn2asF529eXbcfe7pdA/+c9V/QpJzF+YVhpQdtAorkqFHwQ+gSAhxjhCic6DtYQDfCSFaAPgewCMA\nQEStAQwG0ArAlQBGk0MKiCeVx7Yq13GCeyrMMAxjLWfVPCvm9h1Hd+ga750+78TcfnXzq6Nu42fL\nCuxMGP7EE8ASlZiMN6+OtCYr08U8+v2jpsxPVGFNjEWtWsDkye4/TpTpa+ItCzELJ+MDvij+At/f\n/L0dUxEidbG+AMYG3o8FcG3gfR8A44QQZUKITQDWAegMB/Ck8njddWqt7qgwwzCM9ZhZS3bMVWPQ\ns1lP/LP7P2PP6b3ytaZzedPLsW7/Omw+uNn0sdW+/xUrKt7Ll+mezSI9fWouyvf6vpewTHs0FGPZ\ntw/4+Wd3B8sAwJ/O+VPw/Z+//nNCY8VK4K/kooYXadqvtBTYoe95MC7tCtuhe5Pu8XdMHAFgOhEt\nICI5P1ihEGIXAAghdgIoCLTXB7BF0XdboM12PKc8do6mgwvSl6pHDpixoMIMp4hgGGupnVuRyPfQ\nyUP4zy//CSqU4Yplr2a9Yo5153l3IjczN+TmqUZZlFzHffuqt2uxSnmNzPRM9GvZD+NXjjd97EOH\nAIRdi9Uutelp6RFtaomqta5Zi4XWS70QwLx5CU9nKUojyc6jO7Ht8DbT57ip/U0AgKrZ0hK/3mf1\n1tTv4YeBevXi72c359Y9V8tuXYQQHQH0BnA3EV0MRJhcXac0eE55nD9fvV2P21pXwAzXtmYY19G0\netPg+xFTR+Ceb+7B7mNSWbE3Fr4Rsu+3N2pLPaKWC1JJNOWxRQt9+3sdp2pdx7r0qimP17S4RmVP\nfcjKY+/eyfd7x7tVNRgVuXZUC7G8Ard0uAXf3/y9qnU4Fjt3GhLFUmbNmoVeW3ph4K6BwMzo+wkh\ndgT+7gHwJSQ39C4iKgQAIqoDQK6JuA1AQ0X3BoE22/Gc8hgVnQEzvOaRYZIXpXX/v7/+F0BF/epN\nBzcZGlPNYqUk2ZQDp+jWuBu2Ht6K9fvXmzxybONArEu6WnCEGcmn5cPwm2+ALVti75sqxLoPF1Yu\nRPcm3XUbWdxokykqKsJTTz6FO+6/A4ji/SaiXCLKC7yvDKAngOUAJgK4JbDbUABfBd5PBDCEiLKI\nqAmAMwH8Ytk/EYPUUR6hI1UPjFkeT59250HMMExFTV6j6yGj9XvsYqkOdrnO4MxUXb2SkZaBAa0G\nWOK6NopaAFVmmr40PUSRFjDlb8z3BoloUcy3dLgFbQraAPBWPuQ4/0shgDlEtATAPACThBDTAPwL\nQA8iWgPgMgDPAoAQYhWA8QBWAZgCYLhwaB1c4os6kgWDqXqICP4YK+GVlsdTp6S28nJpoXSdOomJ\nzDCMMdSWqBw5dQSn/afxwtwXDI2Zm5kb0bbirhXByhdsedROcdti/OWbv+DRi82JbI6G8rZ69Ki+\nvlqsXwcPAtnZQI5UjATbtkW/7qsNJyubyfIg8e0N3+KKj65IaIxo9+F3+74bfH9P53vQsEpD1f2S\njYMnD0bdJoTYCKCDSvt+AJdH6fMMgGfMks8oqWN5NFhhpkZODRw4eSD6sCprHl96CahbV4qgYxjG\nftQexi8deyn2HNMQ/hqFcDdm24K2aFPQJnj+s/Kona6NumLv8b34be9vts1pRfLt6tWBGxRFTiLr\nZ8fuX7eu+TJZSbVK1RIeQy2y/Y2rQ9chd23UFc/3fD7hudyAWl5RL5BCyqOxCjOFlQux86i+1bjy\n0+Thw1HGd1/gFMN4jiFth4R83nhwo2kpfJpVb4aSbiUhbaw8aieN0jC49WB8ssLkwBlhv7tz48bI\ntmXLItv0uK0XLzYuj5Wc3+D8hMdQOwcHth6Y0JhuXhJwYcML0bJWS6fFMB3PK49ZgQBJYTBgpk5e\nnZjKY6yAGbUD2ktrORjGrQgInFf3vIj2RJXHh7s8DAD4csiXETe8sjIgP197ypVkcVVaRXHbYoxb\nOc7S1GV2f8fyNf/KKyPnj6XghMvZrZu5clnFD5t/0N1H7RyMV8Ep2fHifd/zymNRkfxOu9taGTAT\nV3lUcVvLF4IrElsawjBMAqitWVPW051+03SIEn3axXn1JIVUrRxhWRlQWAicr9E4k+rK4/n1z8eJ\n0yewfPdycwakyC908mRzhtYsQtghN3p0xfvrrouuQG7YEPr56FHggw+APn0Sl2nCBKBX7FSmERAB\nkybF3+/Gz/XXUrSx7J9r8GKKPs8rj8ELtA63tXLNo1bL44kTwIkTiUrLMIwZRDvX+4yruBtf3lR1\nPbphysqADB0hiKmuPBIRBrexwHWtYOJE9fZxA8aZNodSLwjXEX79teL9Tz9FH2POnMi2jz6SFDgp\n+blxxo8Hpk3T3++DDxKbN5w1e9fgvV/fw/4T+0Pa1//F7JRN7kNr9pZkwnv/kYI+fYDBg6X3wm8s\n2jovKw9+4cfRU+qherLlsVs34FxNyeQZhrEaAWvyr+Zn50fdpld55HKGFQnD7c42Uty2GEuGLcHS\nO5eqbpeXJ9iFWpJr+fiolniMimXoqRE/cvZI3PrVrfDN9oW0N6vRzGyxXMdZNc5yWgTT8bTy+NVX\nwOWycUEYqzBDRKiTVwe7ju6Kui+BsHRpRW3Sf/+7Yvvx40alZxgmEYgI59Q5x9QxezTtgQ33blDd\nVlYGpMfOIx4CK49Ax7odAQCLd5gVIaL9gaFDnQ5oX9genep1itjWpVEX1T5ffinl81WyZElFqUk9\n3slPP4293Yg+/csvwKZN+vvpITs9O/herTJPNGSL40fLzQ97V/vev/giMoht/nxnaoiPuHCE/ZNa\njKeVxxASqDATy3Udrzzhhx+q9El1fxXDWIx8ji0epq6UGFUqiSik9KGS8nIgTccVlS8D0vdpZblC\nLd/xy1e8HNEWbV1ev37ArFmR7U88oVMwAIMGxd5u5Pg4/3ygf3/9/fTwWu/XDPX741Ck1rZk2JJE\nxYlK//6RywEuuKDCG2kn7LZ2EZn6kv9DCNKstJX5y5CRVuF/iqk86ixP6MWFswzjNpRu64MPHcS1\nLa8N2a7HYqJ5TqFPeWTLo0Rx22KMXznehIdqY/1r5taMaFPLRSjzf/8nWbquv76iTb6sm3l5nzHD\nWL8lS9QV3Iceqnh/9ChQM/LfBhDfcmn4wUvlPtmhTkR+7IS4/XZTh2NikLTKo96TVPi1u61nbpqJ\n0+UVvok6eXWw61gUt3Ucy+OOHcDJk/pkZRgmceTzsmqlqvhkYKhlq3bl2qbPJ4S+6xIrjxLtCtoh\nNzMX87fNd2R+NaUmVkSwHATzv/9Fbistlf4eOxZ7Tr2lLPXy1VeRbc89V/F+zx5gfyBuJVzWperL\nQIOcW+9c+P9RcfAeOBG9iIYSOwwn77xj+RSG4FQ9SYyePI8bD27ES/NfCn6OlShctjxGOy9GjgRq\n1dIrLcMwiRBuxQqvUzxh0AQL5tSnPLLbWkJ2XY9bYV4EtB5OloU+3bcraIdz6+mLfpR/906B5ZPx\nIqTvu0/X8KYjy/vtt0Benvq22P0rdqrxnLYcjU4oUHyOWUfKKI/wa0/VAwBPFFUsYklkzSMQ/ymU\nYRhzCY+2Dj9HrUhKrNdt/e23FZaqVKe4bTEmrJqQeAUgAxVmlEsYdj+wG8vuWqa6rnXKlOhjbNmi\nfb7ly4EVK/RIaC7HjlW4tbdujdyu5xhOBL05VmMRfgu2MlB1927A54u/n9fxjPKoXH+iRD6o9Fge\nO9TpgOY1mwc/m7nmkWEYe7B7fbHfr8/yeO+9QEEBMGAA8O67wC71lTEpQctaLVErtxbm/KGS8NBi\nlMuZYi1nuOqq6GN89pn2+dq3d7ac3n/+A9x6q/RezZ5ih/JYULnA0vFff136a4XlsW9fyaOoBy/G\nOiSt8hj+W9x1l/p+lSpJf4Vfe4WZMn8Zbr0lA5s3S5/jWR6Fn3RZELi2NcNYix4vw2OPAWPHmjGn\nPqVg1Chg/XrpZvTNN0DLllK07JNPSkEPqeZyK25TnFjCcJUKM1q+QzWjwqJFxqu7rF5trF8s5BzC\n06dLx5hWZfXttyNTAqmttb3gggorpBHl8cfNP8bdZ+WelcH3ypgCK7ByPXF4qqZUxTPKY9eu6olW\nCwuB558HhI4KM2X+Mixdko75gfXbhXmF0QNmhEBZmY5oa7ZSMozlqCUJz8nIUd336aeBp54yYc4Y\nymM0q2Lt2sDNN0tVQHbtAp55BjhwQEon0qABMGyYVGUkFfLFFrcpxqerP7UkEj4WaveFiROl7728\nXH9wy3ffxd9HbxDl4kDGqTFjpL8vR2YXUkXNQqZUDk+dkv7Ony8pzOHbtfLA9Ad07X/ab0wD8/sj\nczcCkeddhcex4q+s9KXaQ5lVJK3yWFGzuoLCQvV9GzbUV2GmzF8G+DOCTy9ywIzaRcaqShYMwyRG\nuKvo4jMuBgDc0+meiH3NuKHEUh4LNHjpsrKASy8FXnwRWLcOmDkTaNFCslDWqSO5TceMcSbJsR00\nq9EMDas0xOxNs22dV/YEKdfByr/j5ZcDl1yib7ynn46/z9y5+sYEJIXziy/09VGzwCmP0XsUp4Ks\nNIYrj1rWZxIImw9ujro9/N5pNC3T7bcDjRppkCfsPBw1Sjq/zMCDHmhDJK3y2K1bxfu6dWPvm52t\nz21d7i8H/BV5HnMyc5CTkYODJw9G7CudBHw0MYybULs5vdv3Xcy7bR5e7f2qRXOau16seXNgxAjg\n++8lhXHoUEnpOPdc4OyzJXf73LnWp32xkyFth1iWMDwaZ1Q9A5UyKmHf/+0LtskKwg8/AD//rG88\nNQ+YGYQf0rNnR3fPhlveZHbuBH77LXaf8GN427b4ss3fNh+NX24cNW1PuKVx0Z8XxR9UhQULpPR3\n8Qi39K9cqb5fIuhxjXvRwJS0yuOf/lSxKDYeWVmBPI863NbwZ4SceNHWPWqJtmYYxl7UPAL18uvh\n/Abnq+9vguVRb8CMnjmrVZNc2e+/LykAY8ZI/YcNk6ySQ4cCEybETxHjdga3GYzPV3+ewJq40B+g\nR4/4PQrzCnHisROho1iQ9DtRwo+XoiJJgYxFuILTvz/w3/+q7xtNeYz2cNKwSsOIttsm3hbRdrLs\nZMjveU+ne9CiVouoMpuBnNNS/s6Uv2Oi57rc/6efEhsn2Ula5bGgQLpwaiErC/DrcFtvObwlQnmM\ntu5Ra7S1my5CDJMKxHqo+/hjaS20zIYNwN69ic2nN2DGKOnpwEUXSe7RZcuAhQulQJt335WW6Fx2\nmeSmW7fOelnMplHVRmheszm++13DwsEIIrWCRHPsyoqTWsUWu+mgUowlltX5yBEprYySEyfU9wWi\nK49qx3SnTsB/r3k/cs5TRypk85dj8trJyHkqB7/trTB3XnHmFarzl5cDHTuqy3bgANC9e4UsQ4aE\nWlCjnXfxFMWrrpL6johSevqHH6SsCErktaFesvgbIWmVRyXxDpCg5VGD23rHkYBNXLHmEYhtedTr\ntuba1gxjLfHOsYcflsrMKUk0955dymM4Z5wBDB8u5SHcsQP461+liN9u3aQ1k/ffL62fTJYoUStr\nXWsl/HeUA1WcRO1hINZhvnGjvvGjHbtqSzEWLgQ61iiKKFUon3fl/nL0+KAHrv7f1QCA8946L7jP\nJWeoLyI9dUrKMqDGb79JCrws4yefAF9/Hf1/0Yqcu3PUKPXtb7wBvBpllUuq38aTXnkcNAi46abY\n+2Rna7c8nioPhJ/500Pd1pXVlccDJw7glF9bnp577wWqVWMTJMNYTbxANrUbYqKKn9lrHo1QubKU\nYubNN6W1av/7H1C1qlTXuKAAKC4GPvggcSurlQxqMwgT10xEaVniGdSN3uDDj4Xx4xMWxRJi/X96\n09VEWyd5xRVAv36R+7duHVkXXDbQ9P64N2ZumhllHvUTTa35ssuA3r1jy60FtWjs6dP191Oi59jy\n4tK2pFcex48PrdmphmR5JE0Wv+CP7M/Ali3SExYQaXlcvGMxyEfo/XFvrDkYpxhogFdf5TrXDGMX\nsS7YspInpypRthlBCCmwwk33CCLJDfiPfwC//CJZI3v1kiJ2mzUDunSRUgMtX+4uK0q9/HpoV9gO\nUzdMTXisBQuM9XPT7xgLIRBMKadk/nx15THcja0keOtT6aeWfmjXLuB/A0ILfMv32FjJ3nMzc6ML\ngdBj8fvvQ5U8td/F7w/9nRcpYnGEAObNUx9/w4bQdjkdkhK9yuPGjdYFTLmNpFcetZCVBfjLtbmt\ng5RWwWOPVdQqDVcel+7UpjAyDGM/8R4UZUXx7bcr2tLTjc+3YYOkpOlROq67zvh8RqhTRwo0/Pxz\nSYkoKZHc3H36AI0bA3ffLSUrd8MDrmHXdVh5wjVrTBLIZciH98KFUoLvcH7+WV252b49+pixlMdo\nVsxauaGLSsPrhKuRRrHVDjW51c4reb8ZM0ITs59X4SFHeTnw/+2dd5xU9dX/32e2sBRBUUBQQSQE\neyyPBEUFg4olFAtRjC3RWFGxE/N7bMljL6DGqCFqHnvX+Ngb2LuCLaIoIkGx0HGX3Z05vz++9+7c\nqTvlzjK7c96v17zmlu+9c+czd+4993zP95wdd0zc3ncIJe9z+zTlzJPbtFYFapNNnLe0EqgI49FP\n1ZNLt3U0FmVAjwEE4xibmlIHzKyOWlFawyhXcu22DhpKxXge/XjCbHGT/s3O74Zbf/3CP69YOnWC\nPfeEa66BL75wRuOAAc4T2bu3q3rz979nNzZKyYGbH8hjcx7jp6bis6MXUm2k3D2Pq1a59xtvdO/V\n1alt8v3e/vmfznjLdV+vLXiNaa9PKyg1jf+5p57qvOHpSI77PPBAWLw48z79QS1//3vquuOOy348\nd9zhQjzAxRF/9FGiDuk0BzdQqRKoCOPRjbbOLVVPc6yZ6kjiWbFkSarnMYx4HMMwSkcu3daJ7Qv/\nLP/S0h67rERc/NpZZ7nRpfPmudjIF16ALbd0HpnzznNdg6Us+xakd9fe7LDBDjz+2eO5b5SmPCEU\nNiq23I3HefPc+9dfu/d037HQmMd8PI8AR/ziiIT5yU9NZlXTqvw+nPh/6JprXEqqdMcWrLSk6so0\nZisHWcz5+vvfx6evucZlaAieFxtskPu+LM9jO8V1W+foedRoivHY1JRqPBZTQstqWxtGacm12zrY\nbNiwtjGOWitqsKbp2RMOOcTdLL/7zo1Era93uST79YOjjnJxk6X2sIQ16rojGo/pjq9fv8T5dN3Z\n2dh9d7ff0aNT1wVjg5O5dfyt+X1QBoL/RRHX3QyuHGG67+LnNF2dxY9TTDqdTJ5Fn0yXmHI/d8Ki\nIoxHf7R1LkZbc6yZqkhi8JMq9OrSix9++sFVn6H1uI2MqKRLR2YYRoi01m3tX+CXJhWNKtR4zHXA\niWpu5dXKhepqV57vssvg449dYuRf/MKlrunXzxka116bf1qYXNh/s/15eu7TrGxcWdR+MhkQDQ2Z\nq62EMWr+9NOL30c+5FJ5pVyZNSv1d0oe6JKMHyKSzfOYL4sXu9ypsVhqPflZs0pznrdXKsJ4rK0F\njRbebR2NQk1VDWvXrc2P9a6EVcHGI+kLuxuGES7Zuq39gRR/+Uvi8kI9FeU0WrmUDBrkUo49/bSL\nhzz2WJebb9gw2GILlxLopZfCucb17NyT4RsN59FPH81jq9TfPNNvesklsNlm6dcVM3jKp1On4veR\niWxxfmXN1fPSLt5mG5g6Nb9d/etf7v2RRzK3yfd/OX68ezhKl0Pyscdccv7W9m2exw5EbS1E8xgw\ns/qnVOMREruuE4zHK3Mo/lkiPl/8uSUdN4wkWutlyGRQFGr0pBupmYlu3Qr7jHJjrbXi5e6++cZV\nuOnUyQ0u6NMHfvtbl2dySfpyxzkRRtf1rulzUqd0u59zTtyzFIbncU3n/Cw3tu25CywbkHF9KUpr\n5pvR4KWX3Pu4ca23PfLI3PdreR7bKdXVQEyIxnLzPH6zMPGxM53xmNC1Xd8zrEPNm8HXDub1Ba34\n9w2jwsi1bGgyhXoes8WEJTNpUrhdbeVAJAJDh8KFF7p8ebNmuQo3d93lRnGPGOHKQX7ySX7eoPGb\njueFeS+wrCEHyyLDgJlZOWZVu/hid7wQjuHXAe2Foij0ga4Y8vlf5strr6VfXim/e0UYjyLOU9jU\n3PpVK6pRRFv3PPr8ZdcroLkutGMthEJGthmGkUryDax///BL09XWwqabhrvPcmPDDeGYY1zX4qJF\nrjv7yy9djOTPfua8k888k32wA0CPuh7stvFuPPJplr5Jj0Jv2unKNk6eXNi+gmTqEu+o9OrSq5UW\n2e+/wXjjYN35ciaYM/L55930vHmwxx5r7JDajIowHgEiEaGxsfVu6+ZYM6LpPY99uvbh25Xfsrp5\nNfd9fB8Ag9cp4C6Q4Qk5r11cIC3pgiY+0MbZhg2jzFGUhgbJOIigZ4bOglWB57BPP3WpUGbMiC+b\nMyceTP/1127QxVdfhXbYHZLOnV1uy+uvd1o99JDr1j7vPPd+wAGuyztTAuZ8uq7ffDP7+pdfTvV8\nBkMVVMNLLL7bbvlvk09XaFvjpwdKx8LTFvLQQQ+lXTdpq/8HwJAe26Zd79Meo69uuSU+PXNmfNqv\nyKPqrhmWqqcdk7PnMZbd87ho5SIenfMoM+bNYMLmE9hjQL6FNwtJnqrcMfsOfvzpx4TlfrqgH34q\n40K1hrEGUFX++ldJSV/is/PO6Zefe657//LL9N7BIUPgvvtc13P//s4A2njjUA65IhCBrbd28YWv\nvuqSPo8b55KUDxkCv/wl/PnPbhCOb0yMGTKGl+e/nHL9S/8BbvT3QQelX73LLvBUUtXDoNESi4Xn\nFV533dbbJHPCCeF8dikYODDzur5r9WV4/+EM3WBoyrrrDjmDIyJPctZW07LuvxTd1qXm+uvj0xde\nmLreP687IhVjPFZFhMamHD2PZIl5XPVty2CZDbtviGrpnyhum30bhz50KBPumwDAjW+7sgLBGJJl\nDcuY8+Ockh+LYbQXsgXg+yM1k7nlFhcnddJJmbd98EG4+2433W5HvZYJvXrB4YfDvfe6nJIXX+wG\n2PzmN7DRRm409wtPdWPUgD156N/pPVtBIiJMmuS6xTPh/2Z+N6lqvMvRf3golhEjoKbGTWfycqfD\nL4dbriRXHDrzzMT5N45OLLQ9cO2BsLoHvZaPbrlv+vW1Fy50v/Ec77YVdnhIW/Hww5nXrerAEWUV\nYzxGIhJazGOVOOMyIpEUV/vw4S5lBbgulORUIIVw4zvOWFxc7656Zz17FpCYCPm4x45jyHUd9BHH\nMPKktTyP2ViwwKXlaNlX0n/83ntd0mwjXGpr4Ve/gquuch7J5593Xpurr4YnrjiIKbffw9/+BvPn\nZ9qD5hT36BuN/nU9Gs3sqcyHTTZJ/QxI9E61d/wBRT5XXJHa5oKRF7RMfzopNQbAT61z223uv3b1\n1WEeYduz336Z17XHrvhcqRzjUSI0NeU22pqkmEe/LqZvPPrxNx9+92FKUuEJE1wpI3BPkb4hWQx+\niqGmWBOPf/Y4y1cvB2h5B3hm7jPFf5BhdBBU1SXkL4BBg5L3lbnt9OkFfYSRAz//OZx2mjMi5z65\nD/XrvMXzb3zHdtu5XHx/+pMb8Rrs7vSNx969M+/3sMNcfKW/XY8eUBfCmMeePePeRr86ir//XGit\nokk5kItxfu6IuPv2rjsjKdtFInDTTTBlipu/4YYwj7B8CFaS2mUXi3lst1RFhKbm1rutG6ONSLQ2\nYZnfRdWnax8WrVzEXR+6x6+n5j6V9sYSXBZGyge/qs3H33/Mvnfu27I8OO0nLzcMw+ho9OvVhXGb\n78OvTnyARYucNy8WcyO6+/Z1pRNV40bKoEGwbZbxGW++megdDCsno3/tv/TS+DKRjlMYQiS3AWKj\nB7kah88+64QN3hPnz0/07HdUgnXuO2JPRcUYj7l2WzdGGyHJeFzuOfjW7bJugpEOwHAAACAASURB\nVLcPCg3yzc+X3RhNn6xq1qIcE5gZRoXh4oHTP+1//nnbHosRDgdveTD3fHQPVVUuPOjii+GDD5wh\nOHSoqwoT9DhmKzU5dmx6j2WxpHMmiGQ3Tn/3O2cMt4fu7cbG3AaIPTrRVQVKFzpy4YUuU0ElYN3W\nHYCqSG7d1qubV0M0fV2piETo1TUxl1XyBSq56yHlAlZAV9rqaCvJ0AzDSMDFA6f/r7WWW9AoT0YP\nGs3sRbNZuCJx1MbGG8OJJ7qYybV7xH/z1uqUB9eHlW4pW8k6VRfTmczNN8Pxx8Mf/hDOMZQSv6s5\nyIsvpi6rjlTz261+22KUiyR6Y997rzTHV25kK53Y3qkY4zGSR7d1JuMRXNxjkODT62mnwdFHJ16U\nik0/sGjlIv79w7+L24lhGC1USgWIjkan6k6MHTKW+z66L6f2rXl9Crk2n3xy4vznn8Ptt2f/zOD5\nlkvFk9mz0y9/+eXWt10TpMtnKSLcvv/tCcv88K9KomWAURtkZWlrKsZ4rI60nudRLhCO+b9jaGpI\n7LYePDg+3adrn/jMW8clXIAmTHC1XYPLNtigmKOGK1+7srgdGEYF8sUXytfz3QVbBEaNiq8rJL5N\nBH6wdKprnGwJw5PL3623XvZ93Xpr/p8/IKk086BBroa3z4gRLpdkJn72s9Y/Y6ut3Ptaa8XzkW6z\njeuqL4ZOaXwiYacGEknv8bUHto5HxRiPkYjQlCXPYzDtzfKYi3Str4dTT3UxKT7rd1uf7p26s8/P\n9oXHr0swFIcNc+/Jy557rvDjXrF6RV7ttSMHWRhGjnw5L3G09fPPu/xyDQ3538iWLHHvmWrZGm3H\n7pvszpwf5zB/WcZ8PS38/Ofhf75/eV177fTrn30WXnghcVnwfDvxxMR12UIoROKjt999N7/jTEf3\n7qnLbrut+P36+NrEYm7622/j3z1TpSej/VIxxmNVKwNmPv7+45ZpxVl/dXXuaS1oj63fbX2Wr17O\nrwbuDlrVYiief368zbbbxg1JcGklCuWGd/LLY+Cn9TGMSsZPRBykTx+XkDpf49F/+Bs7tvjjMoqj\npqqG/Tbdj3s/urfVtm3p7TrzTDjjDDdop6oqc7vkrvLa2vTtLr7YvU45xVUzCuO7pMs5vOGGxe/X\nvz8GjcfHHnOj4P3jDtNILQbzgIZH5RiPVRGao5mNxwSja9N4lKsf6OzjxzxGPOmuuy5epsynX79E\nL0VCmSqNwMr1efyzx/M6/pOHnpyybMrw1Ojl5K4bw6hM0g+YmTWrfQxMMDJz0JaZu66Do3uDhsIV\nV8BRRxX3uT/+mNkwvOyyzInGg2ESTU25fdaUKa5U4bhxrtxiMfg9Z8cck7qua9fi9u0zcyb89a9u\nOhaLV/F5443M26wJwuqmzz/koeNZrZVjPLYyYMYvnZRMRuNR4sZjfjFUAvfdx5EPH5nXQJhg4lWf\ni0ZdxNyT5yYss25rwwAkfZLwOXPio0OTBz+EwTvvhL9PI5GRG49k/rL5zF08N2u7oPF4/PH5p035\n05/g8cedtxrcdf7YY1O7pbPx5JMuDtJnxx3jI5bDKCCRC+l6vhYscLXFwRl4mWIxZ87M7TNGjoz/\nn4Ixjx9/nLZ56Dz9dGKll0yf69+rf/nLwj/r5pth4sTCt+8oVJDxmH3AjO+xu2z3y2BaPBFcJJL4\nZ/AHzEhAurxd4V/vxMWjLmbc3eNY2rA0p02e+de69Ozck+EbuajpUQNHISL079HfNXj/iITvYRhG\ndrLVry6U7bYLf59GItWRag7c7MCUruvkB+dgzGOXLvkbj337wt57uxyS4K7znTs7Q2mHHWDTTVvf\nx+jRid7KqirXHQ3Zy9qFSf/+qcs22CBeBWfoUDjnnPTbBivlZCJZ12g0nhu5VCR3t++xh6s5D864\n22yz9Nv5xmO6lEO5sttumcMNKomKMR4jVVEamjKneV+8tJlf9PkFZw4/E5bE65Nl8jxGm+PSpYuv\nysTUqe79qO2OYvSg0Ux8YGJLBZmMRKu56y748pQvefqwp9HzlGcPfxZwF9JRA0fBhwdBcy2xmBmP\nhpGp2zpIrmXjjPLjoC0P4u6Psud+SfYst5b3MZnk9kEnwWOPuRCIQqmvhwsuaL1dOo47zr37ZXCT\nGTMmcX78eFi1Kj5/+ump2xx5ZGIbn0I6spqa4JNP8t8uFxYtgoULYW4Gp/OqVe67ZMI3HseNi58f\na62V2CZYozwd1rnnqBjj8aPON/Fw/RlMfnJyy7K5i+dy+SuXAzBityY0Ws0TTyRul8l4PP20uHTp\n/nSZ6Nw5Pn3lnlfSGG3kj8/9MWP7X//813D/3ahC907d6VLTJaXNs4c/C5/vDQgxO7MNI2O3dZBg\nuMnEicWPzg0OmjNKy879d+aHn37IGvrj/76+5+/gg/P7DP9SGux29qmpKc77VFdXWMqo3XeHAw5w\n0+ni9w4/PHVEt4jzvIL7LuliM/02Z58dX9atm9MuF+9jkIsuCr9aztlnu+Po3dt5hDNp36VL9p7A\nE06A3//etfHrmSfXNU8Yo5CGgm6xluex/TPtjWnIBcL8ZfO5/q3rOevZs1x3R6QZ0WoWJhYvIBJJ\nHCHXvVN3aKpDY/lLd/zxiSd2TVUN9x54L/d/fD93zL4j84axmtyemlVojtpoa8PIheB/8c474wH/\nhTBlSuKgOaO0RCTChM0ncM+H6QfOBPGNg732gnnzcv8M/7q/5Zb5H1+peOaZeO7Hvn1T1//zn66r\nPJOBM2NG9kEjl1wSn16xwhmPr76a6p3LxpVFpCbONJjtkkviMZq54ufLDGoxcSL84x9u2r+nJmuV\nXCXOJ5O3M5lKqZ5Tccajz4CpA7jq9asAuOvDu+DonZi/Ym5KKoWddnJZ4v18XCICq/q4UdN5ku4P\nvW6XdXnk4EeY/NRk3l74dsr65lgzxKpz7HIR67Y2DCCXbmuAL7+EP3qO/0I8QT7FVpIy8sdPGB6M\ndZQkt9OsWYmDmHL9nfr3TxydfP/9+RlQpcQ/T5ONnOTKNHfeWXh5PN/Aamuuvhr+7//c++uvu+Nv\nqdISMuec4/JyBllnnczffeDA1vd56KGw9dbFH1t7oGKNxyC/fdCVCFjS+APHHpu4bo893Kg4P1YR\ngJXrF+SGThe4DLBVn6246dc3sf89+/Ptym8T1s2cNxMau6YYnv/8p/Oc+C8AVIia8WgYOXVbi7i6\nyBdd5OZbq0iSjXzj6YziGbbhMFY1reLD7z4E0g8W3HprGDIkPp+r8XjSSYlpbA44oHxyBGYyHn1P\nm8/EiYXnJk3u4i8mV3E+dO0K++4Lkye7EdFjx+YfbuATvGcOG5Y6wGmddVzlqaCxt9NOmXNf+r9/\ncL/+4CefY4/N9BBaJidPiJjxmIFgQtWrroLLLyfepb1y/bw9j8uWwVlnZV6/32b7cdS2R7H/Pfuz\nujledqC+uR66/wdVWLkS/vMfl0PLv+EloBHzPBpGjiQbA1tvXXiXk3ke2x4RyVquMB3Jv1Ny1aCv\nvoKlS+G000I4wBKRHMt59dXhf0ays+KZZ5wjpVR0755fSAHEB/6syKEI2wsvZK7S8/jj7jcH972T\nc3nOnQvffx+f97VZtswlh/cZNy4eUpBriqP2TIbe/Q7O1zvCRmlqjd1zf8tkMCB30CDXhXH22V6m\n/NdOg6Ub5/WRfmkoP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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x3562ce110>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(10,10))\n",
+    "\n",
+    "\n",
+    "groupedVerified.plot(kind='line', x='Datetime', y='created_at', label='Verified Users', ax=ax)\n",
+    "groupedNormal.plot(kind='line', x='Datetime', y='created_at', ax = ax, secondary_y=True, label='Non-verified Users')\n",
+    "plt.title('Number of tweets by Users')\n",
+    "# ax2 = ax.twinx()\n",
+    "\n",
+    "ax.set_ylabel('Count of twets (Verified users)', color='b')\n",
+    "ax.right_ax.set_ylabel('Count of tweets (Non-Verified users)', color='g')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/ChangeTheWorld_Communities.ipynb b/ChangeTheWorld_Communities.ipynb
new file mode 100644
index 0000000..b4629c6
--- /dev/null
+++ b/ChangeTheWorld_Communities.ipynb
@@ -0,0 +1,1025 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Visualizing Twitter Communities Over the Ferguson Shooting\n",
+    "A popular method of visualizing data from twitter is to use community mapping techniques through node graphs. A node represents an individual - these will be represented as circles. An edge, or connecting line between nodes, represents for our data a retweet connection. In these representation one can understand information propogation during an event and the amount that differing sides/opinions interact through information promotion on social media - a potential indicator of conversation. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Imports"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Before we get started, let's get everything uploaded. We are using a few speciality packages for this visualization notebook including plotly, basemap, networkx, and cartopy. \n",
+    "\n",
+    "To download plotly using the command line, simply use the command `pip install plotly` in your terminal. Similarly, networkx can be installed with `pip install networkx`. For basemap, we recommend following the instructions [here](http://matplotlib.org/basemap/users/installing.html). And last, for cartopy, you can simply use the pre-built package for Anaconda using `conda install -c scitools cartopy`. \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"text/javascript\">require=requirejs=define=undefined;</script><script type=\"text/javascript\">/**\n",
+       "* plotly.js v1.5.2\n",
+       "* Copyright 2012-2016, Plotly, Inc.\n",
+       "* All rights reserved.\n",
+       "* Licensed under the MIT license\n",
+       "*/\n",
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3:if(t.length!==e.length)throw new Error(\"state and velocity lengths must match\");return new i(t,e,r)}}e.exports=o;var s=t(\"cubic-hermite\"),l=t(\"binary-search-bounds\"),u=i.prototype;u.flush=function(t){var e=l.gt(this._time,t)-1;0>=e||(this._time.splice(0,e),this._state.splice(0,e*this.dimension),this._velocity.splice(0,e*this.dimension))},u.curve=function(t){var e=this._time,r=e.length,i=l.le(e,t),a=this._scratch[0],o=this._state,u=this._velocity,c=this.dimension,f=this.bounds;if(0>i)for(var h=c-1,p=0;c>p;++p,--h)a[p]=o[h];else if(i>=r-1)for(var h=o.length-1,d=t-e[r-1],p=0;c>p;++p,--h)a[p]=o[h]+d*u[h];else{for(var h=c*(i+1)-1,g=e[i],v=e[i+1],m=v-g||1,y=this._scratch[1],b=this._scratch[2],x=this._scratch[3],_=this._scratch[4],w=!0,p=0;c>p;++p,--h)y[p]=o[h],x[p]=u[h]*m,b[p]=o[h+c],_[p]=u[h+c]*m,w=w&&y[p]===b[p]&&x[p]===_[p]&&0===x[p];if(w)for(var p=0;c>p;++p)a[p]=y[p];else s(y,x,b,_,(t-g)/m,a)}for(var k=f[0],A=f[1],p=0;c>p;++p)a[p]=n(k[p],A[p],a[p]);return a},u.dcurve=function(t){var e=this._time,r=e.length,n=l.le(e,t),i=this._scratch[0],a=this._state,o=this._velocity,u=this.dimension;if(n>=r-1)for(var c=a.length-1,f=(t-e[r-1],0);u>f;++f,--c)i[f]=o[c];else{for(var c=u*(n+1)-1,h=e[n],p=e[n+1],d=p-h||1,g=this._scratch[1],v=this._scratch[2],m=this._scratch[3],y=this._scratch[4],b=!0,f=0;u>f;++f,--c)g[f]=a[c],m[f]=o[c]*d,v[f]=a[c+u],y[f]=o[c+u]*d,b=b&&g[f]===v[f]&&m[f]===y[f]&&0===m[f];if(b)for(var f=0;u>f;++f)i[f]=0;else{s.derivative(g,m,v,y,(t-h)/d,i);for(var f=0;u>f;++f)i[f]/=d}}return i},u.lastT=function(){var t=this._time;return t[t.length-1]},u.stable=function(){for(var t=this._velocity,e=t.length,r=this.dimension-1;r>=0;--r)if(t[--e])return!1;return!0},u.jump=function(t){var e=this.lastT(),r=this.dimension;if(!(e>t||arguments.length!==r+1)){var i=this._state,a=this._velocity,o=i.length-this.dimension,s=this.bounds,l=s[0],u=s[1];this._time.push(e,t);for(var c=0;2>c;++c)for(var f=0;r>f;++f)i.push(i[o++]),a.push(0);this._time.push(t);for(var f=r;f>0;--f)i.push(n(l[f-1],u[f-1],arguments[f])),a.push(0)}},u.push=function(t){var e=this.lastT(),r=this.dimension;if(!(e>t||arguments.length!==r+1)){var i=this._state,a=this._velocity,o=i.length-this.dimension,s=t-e,l=this.bounds,u=l[0],c=l[1],f=s>1e-6?1/s:0;this._time.push(t);for(var h=r;h>0;--h){var p=n(u[h-1],c[h-1],arguments[h]);i.push(p),a.push((p-i[o++])*f)}}},u.set=function(t){var e=this.dimension;if(!(t<this.lastT()||arguments.length!==e+1)){var r=this._state,i=this._velocity,a=this.bounds,o=a[0],s=a[1];this._time.push(t);for(var l=e;l>0;--l)r.push(n(o[l-1],s[l-1],arguments[l])),i.push(0)}},u.move=function(t){var e=this.lastT(),r=this.dimension;if(!(e>=t||arguments.length!==r+1)){var i=this._state,a=this._velocity,o=i.length-this.dimension,s=this.bounds,l=s[0],u=s[1],c=t-e,f=c>1e-6?1/c:0;this._time.push(t);for(var h=r;h>0;--h){var p=arguments[h];i.push(n(l[h-1],u[h-1],i[o++]+p)),a.push(p*f)}}},u.idle=function(t){var e=this.lastT();if(!(e>t)){var r=this.dimension,i=this._state,a=this._velocity,o=i.length-r,s=this.bounds,l=s[0],u=s[1],c=t-e;this._time.push(t);for(var f=r-1;f>=0;--f)i.push(n(l[f],u[f],i[o]+c*a[o])),a.push(0),o+=1}}},{\"binary-search-bounds\":18,\"cubic-hermite\":19}],18:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],19:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a){var o=6*i*i-6*i,s=3*i*i-4*i+1,l=-6*i*i+6*i,u=3*i*i-2*i;if(t.length){a||(a=new Array(t.length));for(var c=t.length-1;c>=0;--c)a[c]=o*t[c]+s*e[c]+l*r[c]+u*n[c];return a}return o*t+s*e+l*r[c]+u*n}function i(t,e,r,n,i,a){var o=i-1,s=i*i,l=o*o,u=(1+2*i)*l,c=i*l,f=s*(3-2*i),h=s*o;if(t.length){a||(a=new Array(t.length));for(var p=t.length-1;p>=0;--p)a[p]=u*t[p]+c*e[p]+f*r[p]+h*n[p];return a}return u*t+c*e+f*r+h*n}e.exports=i,e.exports.derivative=n},{}],20:[function(t,e,r){\"use strict\";function n(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function i(t,e,r,n){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2)+Math.pow(n,2))}function a(t,e){var r=e[0],n=e[1],a=e[2],o=e[3],s=i(r,n,a,o);s>1e-6?(t[0]=r/s,t[1]=n/s,t[2]=a/s,t[3]=o/s):(t[0]=t[1]=t[2]=0,t[3]=1)}function o(t,e,r){this.radius=l([r]),this.center=l(e),this.rotation=l(t),this.computedRadius=this.radius.curve(0),this.computedCenter=this.center.curve(0),this.computedRotation=this.rotation.curve(0),this.computedUp=[.1,0,0],this.computedEye=[.1,0,0],this.computedMatrix=[.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],this.recalcMatrix(0)}function s(t){t=t||{};var e=t.center||[0,0,0],r=t.rotation||[0,0,0,1],n=t.radius||1;e=[].slice.call(e,0,3),r=[].slice.call(r,0,4),a(r,r);var i=new o(r,e,Math.log(n));return i.setDistanceLimits(t.zoomMin,t.zoomMax),(\"eye\"in t||\"up\"in t)&&i.lookAt(0,t.eye,t.center,t.up),i}e.exports=s;var l=t(\"filtered-vector\"),u=t(\"gl-mat4/lookAt\"),c=t(\"gl-mat4/fromQuat\"),f=t(\"gl-mat4/invert\"),h=t(\"./lib/quatFromFrame\"),p=o.prototype;p.lastT=function(){return Math.max(this.radius.lastT(),this.center.lastT(),this.rotation.lastT())},p.recalcMatrix=function(t){this.radius.curve(t),this.center.curve(t),this.rotation.curve(t);var e=this.computedRotation;a(e,e);var r=this.computedMatrix;c(r,e);var n=this.computedCenter,i=this.computedEye,o=this.computedUp,s=Math.exp(this.computedRadius[0]);i[0]=n[0]+s*r[2],i[1]=n[1]+s*r[6],i[2]=n[2]+s*r[10],o[0]=r[1],o[1]=r[5],o[2]=r[9];for(var l=0;3>l;++l){for(var u=0,f=0;3>f;++f)u+=r[l+4*f]*i[f];r[12+l]=-u}},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;16>n;++n)e[n]=r[n];return e}return r},p.idle=function(t){this.center.idle(t),this.radius.idle(t),this.rotation.idle(t)},p.flush=function(t){this.center.flush(t),this.radius.flush(t),this.rotation.flush(t)},p.pan=function(t,e,r,i){e=e||0,r=r||0,i=i||0,this.recalcMatrix(t);var a=this.computedMatrix,o=a[1],s=a[5],l=a[9],u=n(o,s,l);o/=u,s/=u,l/=u;var c=a[0],f=a[4],h=a[8],p=c*o+f*s+h*l;c-=o*p,f-=s*p,h-=l*p;var d=n(c,f,h);c/=d,f/=d,h/=d;var g=a[2],v=a[6],m=a[10],y=g*o+v*s+m*l,b=g*c+v*f+m*h;g-=y*o+b*c,v-=y*s+b*f,m-=y*l+b*h;var x=n(g,v,m);g/=x,v/=x,m/=x;var _=c*e+o*r,w=f*e+s*r,k=h*e+l*r;this.center.move(t,_,w,k);var A=Math.exp(this.computedRadius[0]);A=Math.max(1e-4,A+i),this.radius.set(t,Math.log(A))},p.rotate=function(t,e,r,a){this.recalcMatrix(t),e=e||0,r=r||0;var o=this.computedMatrix,s=o[0],l=o[4],u=o[8],c=o[1],f=o[5],h=o[9],p=o[2],d=o[6],g=o[10],v=e*s+r*c,m=e*l+r*f,y=e*u+r*h,b=-(d*y-g*m),x=-(g*v-p*y),_=-(p*m-d*v),w=Math.sqrt(Math.max(0,1-Math.pow(b,2)-Math.pow(x,2)-Math.pow(_,2))),k=i(b,x,_,w);k>1e-6?(b/=k,x/=k,_/=k,w/=k):(b=x=_=0,w=1);var A=this.computedRotation,M=A[0],T=A[1],E=A[2],L=A[3],S=M*w+L*b+T*_-E*x,C=T*w+L*x+E*b-M*_,P=E*w+L*_+M*x-T*b,z=L*w-M*b-T*x-E*_;if(a){b=p,x=d,_=g;var R=Math.sin(a)/n(b,x,_);b*=R,x*=R,_*=R,w=Math.cos(e),S=S*w+z*b+C*_-P*x,C=C*w+z*x+P*b-S*_,P=P*w+z*_+S*x-C*b,z=z*w-S*b-C*x-P*_}var O=i(S,C,P,z);O>1e-6?(S/=O,C/=O,P/=O,z/=O):(S=C=P=0,z=1),this.rotation.set(t,S,C,P,z)},p.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var i=this.computedMatrix;u(i,e,r,n);var o=this.computedRotation;h(o,i[0],i[1],i[2],i[4],i[5],i[6],i[8],i[9],i[10]),a(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var s=0,l=0;3>l;++l)s+=Math.pow(r[l]-e[l],2);this.radius.set(t,.5*Math.log(Math.max(s,1e-6))),this.center.set(t,r[0],r[1],r[2])},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e){var r=this.computedRotation;h(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),a(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var n=this.computedMatrix;f(n,e);var i=n[15];if(Math.abs(i)>1e-6){var o=n[12]/i,s=n[13]/i,l=n[14]/i;this.recalcMatrix(t);var u=Math.exp(this.computedRadius[0]);this.center.set(t,o-n[2]*u,s-n[6]*u,l-n[10]*u),this.radius.idle(t)}else this.center.idle(t),this.radius.idle(t)},p.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},p.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-(1/0),e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},p.getDistanceLimits=function(t){var e=this.radius.bounds;return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},p.toJSON=function(){return this.recalcMatrix(this.lastT()),{center:this.computedCenter.slice(),rotation:this.computedRotation.slice(),distance:Math.log(this.computedRadius[0]),zoomMin:this.radius.bounds[0][0],zoomMax:this.radius.bounds[1][0]}},p.fromJSON=function(t){var e=this.lastT(),r=t.center;r&&this.center.set(e,r[0],r[1],r[2]);var n=t.rotation;n&&this.rotation.set(e,n[0],n[1],n[2],n[3]);var i=t.distance;i&&i>0&&this.radius.set(e,Math.log(i)),this.setDistanceLimits(t.zoomMin,t.zoomMax)}},{\"./lib/quatFromFrame\":16,\"filtered-vector\":17,\"gl-mat4/fromQuat\":183,\"gl-mat4/invert\":186,\"gl-mat4/lookAt\":187}],21:[function(t,e,r){arguments[4][17][0].apply(r,arguments)},{\"binary-search-bounds\":22,\"cubic-hermite\":23,dup:17}],22:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],23:[function(t,e,r){arguments[4][19][0].apply(r,arguments)},{dup:19}],24:[function(t,e,r){arguments[4][5][0].apply(r,arguments)},{dup:5}],25:[function(t,e,r){arguments[4][6][0].apply(r,arguments)},{dup:6}],26:[function(t,e,r){arguments[4][9][0].apply(r,arguments)},{dup:9}],27:[function(t,e,r){\"use strict\";function n(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function i(t){return Math.min(1,Math.max(-1,t))}function a(t){var e=Math.abs(t[0]),r=Math.abs(t[1]),n=Math.abs(t[2]),i=[0,0,0];e>Math.max(r,n)?i[2]=1:r>Math.max(e,n)?i[0]=1:i[1]=1;for(var a=0,o=0,s=0;3>s;++s)a+=t[s]*t[s],o+=i[s]*t[s];for(var s=0;3>s;++s)i[s]-=o/a*t[s];return h(i,i),i}function o(t,e,r,n,i,a,o,s){this.center=l(r),this.up=l(n),this.right=l(i),this.radius=l([a]),this.angle=l([o,s]),this.angle.bounds=[[-(1/0),-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(t,e),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var u=0;16>u;++u)this.computedMatrix[u]=.5;this.recalcMatrix(0)}function s(t){t=t||{};var e=t.center||[0,0,0],r=t.up||[0,1,0],i=t.right||a(r),s=t.radius||1,l=t.theta||0,u=t.phi||0;if(e=[].slice.call(e,0,3),r=[].slice.call(r,0,3),h(r,r),i=[].slice.call(i,0,3),h(i,i),\"eye\"in t){var c=t.eye,d=[c[0]-e[0],c[1]-e[1],c[2]-e[2]];f(i,d,r),n(i[0],i[1],i[2])<1e-6?i=a(r):h(i,i),s=n(d[0],d[1],d[2]);var g=p(r,d)/s,v=p(i,d)/s;u=Math.acos(g),l=Math.acos(v)}return s=Math.log(s),new o(t.zoomMin,t.zoomMax,e,r,i,s,l,u)}e.exports=s;var l=t(\"filtered-vector\"),u=t(\"gl-mat4/invert\"),c=t(\"gl-mat4/rotate\"),f=t(\"gl-vec3/cross\"),h=t(\"gl-vec3/normalize\"),p=t(\"gl-vec3/dot\"),d=o.prototype;d.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-(1/0),e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},d.getDistanceLimits=function(t){var e=this.radius.bounds[0];return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},d.recalcMatrix=function(t){this.center.curve(t),this.up.curve(t),this.right.curve(t),this.radius.curve(t),this.angle.curve(t);for(var e=this.computedUp,r=this.computedRight,i=0,a=0,o=0;3>o;++o)a+=e[o]*r[o],i+=e[o]*e[o];for(var s=Math.sqrt(i),l=0,o=0;3>o;++o)r[o]-=e[o]*a/i,l+=r[o]*r[o],e[o]/=s;for(var u=Math.sqrt(l),o=0;3>o;++o)r[o]/=u;var c=this.computedToward;f(c,e,r),h(c,c);for(var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],g=this.computedAngle[1],v=Math.cos(d),m=Math.sin(d),y=Math.cos(g),b=Math.sin(g),x=this.computedCenter,_=v*y,w=m*y,k=b,A=-v*b,M=-m*b,T=y,E=this.computedEye,L=this.computedMatrix,o=0;3>o;++o){var S=_*r[o]+w*c[o]+k*e[o];L[4*o+1]=A*r[o]+M*c[o]+T*e[o],L[4*o+2]=S,L[4*o+3]=0}var C=L[1],P=L[5],z=L[9],R=L[2],O=L[6],I=L[10],j=P*I-z*O,N=z*R-C*I,F=C*O-P*R,D=n(j,N,F);j/=D,N/=D,F/=D,L[0]=j,L[4]=N,L[8]=F;for(var o=0;3>o;++o)E[o]=x[o]+L[2+4*o]*p;for(var o=0;3>o;++o){for(var l=0,B=0;3>B;++B)l+=L[o+4*B]*E[B];L[12+o]=-l}L[15]=1},d.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;16>n;++n)e[n]=r[n];return e}return r};var g=[0,0,0];d.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;g[0]=i[2],g[1]=i[6],g[2]=i[10];for(var a=this.computedUp,o=this.computedRight,s=this.computedToward,l=0;3>l;++l)i[4*l]=a[l],i[4*l+1]=o[l],i[4*l+2]=s[l];c(i,i,n,g);for(var l=0;3>l;++l)a[l]=i[4*l],o[l]=i[4*l+1];this.up.set(t,a[0],a[1],a[2]),this.right.set(t,o[0],o[1],o[2])}},d.pan=function(t,e,r,i){e=e||0,r=r||0,i=i||0,this.recalcMatrix(t);var a=this.computedMatrix,o=(Math.exp(this.computedRadius[0]),a[1]),s=a[5],l=a[9],u=n(o,s,l);o/=u,s/=u,l/=u;var c=a[0],f=a[4],h=a[8],p=c*o+f*s+h*l;c-=o*p,f-=s*p,h-=l*p;var d=n(c,f,h);c/=d,f/=d,h/=d;var g=c*e+o*r,v=f*e+s*r,m=h*e+l*r;this.center.move(t,g,v,m);var y=Math.exp(this.computedRadius[0]);y=Math.max(1e-4,y+i),this.radius.set(t,Math.log(y))},d.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},d.setMatrix=function(t,e,r,a){var o=1;\"number\"==typeof r&&(o=0|r),(0>o||o>3)&&(o=1);var s=(o+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var l=e[o],c=e[o+4],f=e[o+8];if(a){var h=Math.abs(l),p=Math.abs(c),d=Math.abs(f),g=Math.max(h,p,d);h===g?(l=0>l?-1:1,c=f=0):d===g?(f=0>f?-1:1,l=c=0):(c=0>c?-1:1,l=f=0)}else{var v=n(l,c,f);l/=v,c/=v,f/=v}var m=e[s],y=e[s+4],b=e[s+8],x=m*l+y*c+b*f;m-=l*x,y-=c*x,b-=f*x;var _=n(m,y,b);m/=_,y/=_,b/=_;var w=c*b-f*y,k=f*m-l*b,A=l*y-c*m,M=n(w,k,A);w/=M,k/=M,A/=M,this.center.jump(t,H,G,Y),this.radius.idle(t),this.up.jump(t,l,c,f),this.right.jump(t,m,y,b);var T,E;if(2===o){var L=e[1],S=e[5],C=e[9],P=L*m+S*y+C*b,z=L*w+S*k+C*A;T=0>j?-Math.PI/2:Math.PI/2,E=Math.atan2(z,P)}else{var R=e[2],O=e[6],I=e[10],j=R*l+O*c+I*f,N=R*m+O*y+I*b,F=R*w+O*k+I*A;T=Math.asin(i(j)),E=Math.atan2(F,N)}this.angle.jump(t,E,T),this.recalcMatrix(t);var D=e[2],B=e[6],U=e[10],V=this.computedMatrix;u(V,e);var q=V[15],H=V[12]/q,G=V[13]/q,Y=V[14]/q,X=Math.exp(this.computedRadius[0]);this.center.jump(t,H-D*X,G-B*X,Y-U*X)},d.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},d.idle=function(t){this.center.idle(t),this.up.idle(t),this.right.idle(t),this.radius.idle(t),this.angle.idle(t)},d.flush=function(t){this.center.flush(t),this.up.flush(t),this.right.flush(t),this.radius.flush(t),this.angle.flush(t)},d.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},d.lookAt=function(t,e,r,a){this.recalcMatrix(t),e=e||this.computedEye,r=r||this.computedCenter,a=a||this.computedUp;var o=a[0],s=a[1],l=a[2],u=n(o,s,l);if(!(1e-6>u)){o/=u,s/=u,l/=u;var c=e[0]-r[0],f=e[1]-r[1],h=e[2]-r[2],p=n(c,f,h);if(!(1e-6>p)){c/=p,f/=p,h/=p;var d=this.computedRight,g=d[0],v=d[1],m=d[2],y=o*g+s*v+l*m;g-=y*o,v-=y*s,m-=y*l;var b=n(g,v,m);if(!(.01>b&&(g=s*h-l*f,v=l*c-o*h,m=o*f-s*c,b=n(g,v,m),1e-6>b))){g/=b,v/=b,m/=b,this.up.set(t,o,s,l),this.right.set(t,g,v,m),this.center.set(t,r[0],r[1],r[2]),this.radius.set(t,Math.log(p));var x=s*m-l*v,_=l*g-o*m,w=o*v-s*g,k=n(x,_,w);x/=k,_/=k,w/=k;var A=o*c+s*f+l*h,M=g*c+v*f+m*h,T=x*c+_*f+w*h,E=Math.asin(i(A)),L=Math.atan2(T,M),S=this.angle._state,C=S[S.length-1],P=S[S.length-2];C%=2*Math.PI;var z=Math.abs(C+2*Math.PI-L),R=Math.abs(C-L),O=Math.abs(C-2*Math.PI-L);R>z&&(C+=2*Math.PI),R>O&&(C-=2*Math.PI),this.angle.jump(this.angle.lastT(),C,P),this.angle.set(t,L,E)}}}}},{\"filtered-vector\":21,\"gl-mat4/invert\":186,\"gl-mat4/rotate\":190,\"gl-vec3/cross\":24,\"gl-vec3/dot\":25,\"gl-vec3/normalize\":26}],28:[function(t,e,r){\"use strict\";function n(t,e){this._controllerNames=Object.keys(t),this._controllerList=this._controllerNames.map(function(e){return t[e]}),this._mode=e,this._active=t[e],this._active||(this._mode=\"turntable\",this._active=t.turntable),this.modes=this._controllerNames,this.computedMatrix=this._active.computedMatrix,this.computedEye=this._active.computedEye,this.computedUp=this._active.computedUp,this.computedCenter=this._active.computedCenter,this.computedRadius=this._active.computedRadius}function i(t){t=t||{};var e=t.eye||[0,0,1],r=t.center||[0,0,0],i=t.up||[0,1,0],l=t.distanceLimits||[0,1/0],u=t.mode||\"turntable\",c=a(),f=o(),h=s();return c.setDistanceLimits(l[0],l[1]),c.lookAt(0,e,r,i),f.setDistanceLimits(l[0],l[1]),f.lookAt(0,e,r,i),h.setDistanceLimits(l[0],l[1]),h.lookAt(0,e,r,i),new n({turntable:c,orbit:f,matrix:h},u)}e.exports=i;var a=t(\"turntable-camera-controller\"),o=t(\"orbit-camera-controller\"),s=t(\"matrix-camera-controller\"),l=n.prototype,u=[[\"flush\",1],[\"idle\",1],[\"lookAt\",4],[\"rotate\",4],[\"pan\",4],[\"translate\",4],[\"setMatrix\",2],[\"setDistanceLimits\",2],[\"setDistance\",2]];u.forEach(function(t){for(var e=t[0],r=[],n=0;n<t[1];++n)r.push(\"a\"+n);var i=\"var cc=this._controllerList;for(var i=0;i<cc.length;++i){cc[i].\"+t[0]+\"(\"+r.join()+\")}\";l[e]=Function.apply(null,r.concat(i))}),l.recalcMatrix=function(t){this._active.recalcMatrix(t)},l.getDistance=function(t){return this._active.getDistance(t)},l.getDistanceLimits=function(t){return this._active.getDistanceLimits(t)},l.lastT=function(){return this._active.lastT()},l.setMode=function(t){if(t!==this._mode){var e=this._controllerNames.indexOf(t);if(!(0>e)){var r=this._active,n=this._controllerList[e],i=Math.max(r.lastT(),n.lastT());r.recalcMatrix(i),n.setMatrix(i,r.computedMatrix),this._active=n,this._mode=t,this.computedMatrix=this._active.computedMatrix,this.computedEye=this._active.computedEye,this.computedUp=this._active.computedUp,this.computedCenter=this._active.computedCenter,this.computedRadius=this._active.computedRadius}}},l.getMode=function(){return this._mode}},{\"matrix-camera-controller\":3,\"orbit-camera-controller\":20,\"turntable-camera-controller\":27}],29:[function(t,e,r){e.exports=function(t,e){e||(e=[0,\"\"]),t=String(t);var r=parseFloat(t,10);\n",
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s=l.malloc(t.size,r),h=c(s,t.shape);u.assign(h,t),0>e?this.length=i(this.gl,this.type,this.length,this.usage,s,e):this.length=i(this.gl,this.type,this.length,this.usage,s.subarray(0,t.size),e),l.free(s)}}else if(Array.isArray(t)){var p;p=this.type===this.gl.ELEMENT_ARRAY_BUFFER?a(t,\"uint16\"):a(t,\"float32\"),0>e?this.length=i(this.gl,this.type,this.length,this.usage,p,e):this.length=i(this.gl,this.type,this.length,this.usage,p.subarray(0,t.length),e),l.free(p)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=i(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");t=0|t,0>=t&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},e.exports=s},{ndarray:247,\"ndarray-ops\":34,\"typedarray-pool\":41}],34:[function(t,e,r){\"use strict\";function n(t){if(!t)return s;for(var 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e=c[t];r[t]=a({args:[\"array\",\"array\",\"array\"],body:{args:[\"a\",\"b\",\"c\"],body:\"a=b\"+e+\"c\"},funcName:t}),r[t+\"s\"]=a({args:[\"array\",\"array\",\"scalar\"],body:{args:[\"a\",\"b\",\"s\"],body:\"a=b\"+e+\"s\"},funcName:t+\"s\"}),r[t+\"eq\"]=a({args:[\"array\",\"array\"],body:{args:[\"a\",\"b\"],body:\"a=a\"+e+\"b\"},rvalue:!0,count:2,funcName:t+\"eq\"}),r[t+\"seq\"]=a({args:[\"array\",\"scalar\"],body:{args:[\"a\",\"s\"],body:\"a=a\"+e+\"s\"},rvalue:!0,count:2,funcName:t+\"seq\"})}}();var f=[\"abs\",\"acos\",\"asin\",\"atan\",\"ceil\",\"cos\",\"exp\",\"floor\",\"log\",\"round\",\"sin\",\"sqrt\",\"tan\"];!function(){for(var t=0;t<f.length;++t){var 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a(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}function o(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,u=n[e],c=0;3>c;++c)if(e!==c){var f=a,h=s,p=o,d=l;u&1<<c&&(f=s,h=a,p=l,d=o),f[c]=r[0][c],h[c]=r[1][c],i[c]>0?(p[c]=-1,d[c]=0):(p[c]=0,d[c]=1)}}function s(t,e){var r=new i(t);return r.update(e),r}e.exports=s;var l=t(\"./lib/text.js\"),u=t(\"./lib/lines.js\"),c=t(\"./lib/background.js\"),f=t(\"./lib/cube.js\"),h=t(\"./lib/ticks.js\"),p=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),d=i.prototype;d.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;3>s;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,n=e.bind(this,!1,Number),i=e.bind(this,!1,Boolean),a=e.bind(this,!1,String),o=e.bind(this,!0,function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]}),s=!1,c=!1;if(\"bounds\"in t)for(var f=t.bounds,p=0;2>p;++p)for(var d=0;3>d;++d)f[p][d]!==this.bounds[p][d]&&(c=!0),this.bounds[p][d]=f[p][d];if(\"ticks\"in t){r=t.ticks,s=!0,this.autoTicks=!1;for(var p=0;3>p;++p)this.tickSpacing[p]=0}else n(\"tickSpacing\")&&(this.autoTicks=!0,c=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),c=!0,s=!0,this._firstInit=!1),c&&this.autoTicks&&(r=h.create(this.bounds,this.tickSpacing),s=!0),s){for(var p=0;3>p;++p)r[p].sort(function(t,e){return t.x-e.x});h.equal(r,this.ticks)?s=!1:this.ticks=r}i(\"tickEnable\"),a(\"tickFont\")&&(s=!0),n(\"tickSize\"),n(\"tickAngle\"),n(\"tickPad\"),o(\"tickColor\");var g=a(\"labels\");a(\"labelFont\")&&(g=!0),i(\"labelEnable\"),n(\"labelSize\"),n(\"labelPad\"),o(\"labelColor\"),i(\"lineEnable\"),i(\"lineMirror\"),n(\"lineWidth\"),o(\"lineColor\"),i(\"lineTickEnable\"),i(\"lineTickMirror\"),n(\"lineTickLength\"),n(\"lineTickWidth\"),o(\"lineTickColor\"),i(\"gridEnable\"),n(\"gridWidth\"),o(\"gridColor\"),i(\"zeroEnable\"),o(\"zeroLineColor\"),n(\"zeroLineWidth\"),i(\"backgroundEnable\"),o(\"backgroundColor\"),this._text?this._text&&(g||s)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=l(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&s&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=u(this.gl,this.bounds,this.ticks))};var g=[new a,new a,new a],v=[0,0,0],m={model:p,view:p,projection:p};d.isOpaque=function(){return!0},d.isTransparent=function(){return!1},d.drawTransparent=function(t){};var y=[0,0,0],b=[0,0,0],x=[0,0,0];d.draw=function(t){t=t||m;for(var e=this.gl,r=t.model||p,i=t.view||p,a=t.projection||p,s=this.bounds,l=f(r,i,a,s),u=l.cubeEdges,c=l.axis,h=i[12],d=i[13],_=i[14],w=i[15],k=this.pixelRatio*(a[3]*h+a[7]*d+a[11]*_+a[15]*w)/e.drawingBufferHeight,A=0;3>A;++A)this.lastCubeProps.cubeEdges[A]=u[A],this.lastCubeProps.axis[A]=c[A];for(var M=g,A=0;3>A;++A)o(g[A],A,this.bounds,u,c);for(var e=this.gl,T=v,A=0;3>A;++A)this.backgroundEnable[A]?T[A]=c[A]:T[A]=0;this._background.draw(r,i,a,s,T,this.backgroundColor),this._lines.bind(r,i,a,this);for(var A=0;3>A;++A){var E=[0,0,0];c[A]>0?E[A]=s[1][A]:E[A]=s[0][A];for(var L=0;2>L;++L){var S=(A+1+L)%3,C=(A+1+(1^L))%3;this.gridEnable[S]&&this._lines.drawGrid(S,C,this.bounds,E,this.gridColor[S],this.gridWidth[S]*this.pixelRatio)}for(var L=0;2>L;++L){var S=(A+1+L)%3,C=(A+1+(1^L))%3;this.zeroEnable[C]&&s[0][C]<=0&&s[1][C]>=0&&this._lines.drawZero(S,C,this.bounds,E,this.zeroLineColor[C],this.zeroLineWidth[C]*this.pixelRatio)}}for(var A=0;3>A;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);for(var P=n(y,M[A].primalMinor),z=n(b,M[A].mirrorMinor),R=this.lineTickLength,L=0;3>L;++L){var O=k/r[5*L];P[L]*=R[L]*O,z[L]*=R[L]*O}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,P,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}this._text.bind(r,i,a,this.pixelRatio);for(var A=0;3>A;++A){for(var I=M[A].primalMinor,j=n(x,M[A].primalOffset),L=0;3>L;++L)this.lineTickEnable[A]&&(j[L]+=k*I[L]*Math.max(this.lineTickLength[L],0)/r[5*L]);if(this.tickEnable[A]){for(var L=0;3>L;++L)j[L]+=k*I[L]*this.tickPad[L]/r[5*L];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],j,this.tickColor[A])}if(this.labelEnable[A]){for(var L=0;3>L;++L)j[L]+=k*I[L]*this.labelPad[L]/r[5*L];j[A]+=.5*(s[0][A]+s[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],j,this.labelColor[A])}}},d.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":49,\"./lib/cube.js\":50,\"./lib/lines.js\":51,\"./lib/text.js\":53,\"./lib/ticks.js\":54}],49:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}function i(t){for(var e=[],r=[],i=0,l=0;3>l;++l)for(var u=(l+1)%3,c=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;1>=p;p+=2){r.push(i,i+2,i+1,i+1,i+2,i+3),f[l]=p,h[l]=p;for(var d=-1;1>=d;d+=2){f[u]=d;for(var g=-1;1>=g;g+=2)f[c]=g,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),i+=1}var v=u;u=c,c=v}var m=a(t,new Float32Array(e)),y=a(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),b=o(t,[{buffer:m,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:m,type:t.FLOAT,size:3,offset:12,stride:24}],y),x=s(t);return x.attributes.position.location=0,x.attributes.normal.location=1,new n(t,m,b,x)}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-vao\"),s=t(\"./shaders\").bg,l=n.prototype;l.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;3>s;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),l.disable(l.POLYGON_OFFSET_FILL)}},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":52,\"gl-buffer\":58,\"gl-vao\":68}],50:[function(t,e,r){\"use strict\";function n(t,e,r){for(var n=0;4>n;++n){t[n]=r[12+n];for(var i=0;3>i;++i)t[n]+=e[i]*r[4*i+n]}}function i(t){for(var e=0;e<g.length;++e)if(t=l.positive(t,g[e]),t.length<3)return 0;for(var r=t[0],n=r[0]/r[3],i=r[1]/r[3],a=0,e=1;e+1<t.length;++e){var o=t[e],s=t[e+1],u=o[0]/o[3],c=o[1]/o[3],f=s[0]/s[3],h=s[1]/s[3],p=u-n,d=c-i,v=f-n,m=h-i;a+=Math.abs(p*m-d*v)}return a}function a(t,e,r,a){s(c,e,t),s(c,r,c);for(var l=0,g=0;2>g;++g){p[2]=a[g][2];for(var b=0;2>b;++b){p[1]=a[b][1];for(var x=0;2>x;++x)p[0]=a[x][0],n(f[l],p,c),l+=1}}for(var _=-1,g=0;8>g;++g){for(var w=f[g][3],k=0;3>k;++k)h[g][k]=f[g][k]/w;0>w&&(0>_?_=g:h[g][2]<h[_][2]&&(_=g))}if(0>_){_=0;for(var A=0;3>A;++A){for(var M=(A+2)%3,T=(A+1)%3,E=-1,L=-1,S=0;2>S;++S){var C=S<<A,P=C+(S<<M)+(1-S<<T),z=C+(1-S<<M)+(S<<T);u(h[C],h[P],h[z],d)<0||(S?E=1:L=1)}if(0>E||0>L)L>E&&(_|=1<<A);else{for(var S=0;2>S;++S){var C=S<<A,P=C+(S<<M)+(1-S<<T),z=C+(1-S<<M)+(S<<T),R=i([f[C],f[P],f[z],f[C+(1<<M)+(1<<T)]]);S?E=R:L=R}L>E&&(_|=1<<A)}}}for(var O=7^_,I=-1,g=0;8>g;++g)g!==_&&g!==O&&(0>I?I=g:h[I][1]>h[g][1]&&(I=g));for(var j=-1,g=0;3>g;++g){var N=I^1<<g;if(N!==_&&N!==O){0>j&&(j=N);var T=h[N];T[0]<h[j][0]&&(j=N)}}for(var F=-1,g=0;3>g;++g){var N=I^1<<g;if(N!==_&&N!==O&&N!==j){0>F&&(F=N);var T=h[N];T[0]>h[F][0]&&(F=N)}}var D=v;D[0]=D[1]=D[2]=0,D[o.log2(j^I)]=I&j,D[o.log2(I^F)]=I&F;var B=7^F;B===_||B===O?(B=7^j,D[o.log2(F^B)]=B&F):D[o.log2(j^B)]=B&j;for(var U=m,V=_,A=0;3>A;++A)V&1<<A?U[A]=-1:U[A]=1;return y}e.exports=a;var o=t(\"bit-twiddle\"),s=t(\"gl-mat4/multiply\"),l=(t(\"gl-mat4/invert\"),t(\"split-polygon\")),u=t(\"robust-orientation\"),c=new Array(16),f=(new Array(16),new Array(8)),h=new Array(8),p=new Array(3),d=[0,0,0];!function(){for(var t=0;8>t;++t)f[t]=[1,1,1,1],h[t]=[1,1,1]}();var g=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]],v=[1,1,1],m=[0,0,0],y={cubeEdges:v,axis:m}},{\"bit-twiddle\":55,\"gl-mat4/invert\":186,\"gl-mat4/multiply\":188,\"robust-orientation\":75,\"split-polygon\":76}],51:[function(t,e,r){\"use strict\";function n(t){return t[0]=t[1]=t[2]=0,t}function i(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function a(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}function o(t,e,r){var n=[],i=[0,0,0],o=[0,0,0],c=[0,0,0],f=[0,0,0];n.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var h=0;3>h;++h){for(var p=n.length/3|0,d=0;d<r[h].length;++d){var g=+r[h][d].x;n.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=n.length/3|0;i[h]=p,o[h]=v-p;for(var p=n.length/3|0,m=0;m<r[h].length;++m){var g=+r[h][m].x;n.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=n.length/3|0;c[h]=p,f[h]=v-p}var y=s(t,new Float32Array(n)),b=l(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),x=u(t);return x.attributes.position.location=0,new a(t,y,b,x,o,i,f,c)}e.exports=o;var s=t(\"gl-buffer\"),l=t(\"gl-vao\"),u=t(\"./shaders\").line,c=[0,0,0],f=[0,0,0],h=[0,0,0],p=[0,0,0],d=[1,1],g=a.prototype;g.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,d[0]=this.gl.drawingBufferWidth,d[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=d,this.vao.bind()},g.drawAxisLine=function(t,e,r,a,o){var s=n(f);this.shader.uniforms.majorAxis=f,s[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=s;var l=i(p,r);l[t]+=e[0][t],this.shader.uniforms.offset=l,this.shader.uniforms.lineWidth=o,this.shader.uniforms.color=a;var u=n(h);u[(t+2)%3]=1,this.shader.uniforms.screenAxis=u,this.vao.draw(this.gl.TRIANGLES,6);var u=n(h);u[(t+1)%3]=1,this.shader.uniforms.screenAxis=u,this.vao.draw(this.gl.TRIANGLES,6)},g.drawAxisTicks=function(t,e,r,i,a){var o=n(c);o[t]=1,this.shader.uniforms.majorAxis=o,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=i,this.shader.uniforms.lineWidth=a;var s=n(h);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])},g.drawGrid=function(t,e,r,a,o,s){var l=n(f);l[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=l;var u=i(p,a);u[e]+=r[0][e],this.shader.uniforms.offset=u;var d=n(c);d[t]=1,this.shader.uniforms.majorAxis=d;var g=n(h);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=s,this.shader.uniforms.color=o,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])},g.drawZero=function(t,e,r,a,o,s){var l=n(f);this.shader.uniforms.majorAxis=l,l[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=l;var u=i(p,a);u[t]+=r[0][t],this.shader.uniforms.offset=u;var c=n(h);c[e]=1,this.shader.uniforms.screenAxis=c,this.shader.uniforms.lineWidth=s,this.shader.uniforms.color=o,this.vao.draw(this.gl.TRIANGLES,6)},g.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":52,\"gl-buffer\":58,\"gl-vao\":68}],52:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) 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e?this.words[n]=this.words[n]|1<<i:this.words[n]=this.words[n]&~(1<<i),this.strip()},i.prototype.iadd=function(t){if(this.sign&&!t.sign){this.sign=!1;var e=this.isub(t);return this.sign=!this.sign,this._normSign()}if(!this.sign&&t.sign){t.sign=!1;var e=this.isub(t);return t.sign=!0,e._normSign()}var r,n;this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++){var e=r.words[a]+n.words[a]+i;this.words[a]=67108863&e,i=e>>>26}for(;0!==i&&a<r.length;a++){var e=r.words[a]+i;this.words[a]=67108863&e,i=e>>>26}if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},i.prototype.add=function(t){if(t.sign&&!this.sign){t.sign=!1;var e=this.sub(t);return t.sign=!0,e}if(!t.sign&&this.sign){this.sign=!1;var e=t.sub(this);return this.sign=!0,e}return this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},i.prototype.isub=function(t){if(t.sign){t.sign=!1;var e=this.iadd(t);return t.sign=!0,e._normSign()}if(this.sign)return this.sign=!1,this.iadd(t),this.sign=!0,this._normSign();var r=this.cmp(t);if(0===r)return this.sign=!1,this.length=1,this.words[0]=0,this;var n,i;r>0?(n=this,i=t):(n=t,i=this);for(var a=0,o=0;o<i.length;o++){var e=n.words[o]-i.words[o]+a;a=e>>26,this.words[o]=67108863&e}for(;0!==a&&o<n.length;o++){var e=n.words[o]+a;a=e>>26,this.words[o]=67108863&e}if(0===a&&o<n.length&&n!==this)for(;o<n.length;o++)this.words[o]=n.words[o];return this.length=Math.max(this.length,o),n!==this&&(this.sign=!0),this.strip()},i.prototype.sub=function(t){return this.clone().isub(t)},i.prototype._smallMulTo=function(t,e){e.sign=t.sign!==this.sign,e.length=this.length+t.length;for(var r=0,n=0;n<e.length-1;n++){for(var i=r>>>26,a=67108863&r,o=Math.min(n,t.length-1),s=Math.max(0,n-this.length+1);o>=s;s++){var l=n-s,u=0|this.words[l],c=0|t.words[s],f=u*c,h=67108863&f;i=i+(f/67108864|0)|0,h=h+a|0,a=67108863&h,i=i+(h>>>26)|0}e.words[n]=a,r=i}return 0!==r?e.words[n]=r:e.length--,e.strip()},i.prototype._bigMulTo=function(t,e){e.sign=t.sign!==this.sign,e.length=this.length+t.length;for(var r=0,n=0,i=0;i<e.length-1;i++){var a=n;n=0;for(var o=67108863&r,s=Math.min(i,t.length-1),l=Math.max(0,i-this.length+1);s>=l;l++){var u=i-l,c=0|this.words[u],f=0|t.words[l],h=c*f,p=67108863&h;a=a+(h/67108864|0)|0,p=p+o|0,o=67108863&p,a=a+(p>>>26)|0,n+=a>>>26,a&=67108863}e.words[i]=o,r=a,a=n}return 0!==r?e.words[i]=r:e.length--,e.strip()},i.prototype.mulTo=function(t,e){var r;return r=this.length+t.length<63?this._smallMulTo(t,e):this._bigMulTo(t,e)},i.prototype.mul=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},i.prototype.imul=function(t){if(0===this.cmpn(0)||0===t.cmpn(0))return this.words[0]=0,this.length=1,this;var e=this.length,r=t.length;this.sign=t.sign!==this.sign,this.length=this.length+t.length,this.words[this.length-1]=0;for(var n=this.length-2;n>=0;n--){for(var i=0,a=0,o=Math.min(n,r-1),s=Math.max(0,n-e+1);o>=s;s++){var l=n-s,u=this.words[l],c=t.words[s],f=u*c,h=67108863&f;i+=f/67108864|0,h+=a,a=67108863&h,i+=h>>>26}this.words[n]=a,this.words[n+1]+=i,i=0}for(var i=0,l=1;l<this.length;l++){var p=this.words[l]+i;this.words[l]=67108863&p,i=p>>>26}return this.strip()},i.prototype.imuln=function(t){r(\"number\"==typeof t);for(var e=0,n=0;n<this.length;n++){var i=this.words[n]*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[n]=67108863&a}return 0!==e&&(this.words[n]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.mul(this)},i.prototype.ishln=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=67108863>>>26-e<<26-e;if(0!==e){for(var a=0,o=0;o<this.length;o++){var s=this.words[o]&i,l=this.words[o]-s<<e;this.words[o]=l|a,a=s>>>26-e}a&&(this.words[o]=a,this.length++)}if(0!==n){for(var o=this.length-1;o>=0;o--)this.words[o+n]=this.words[o];for(var o=0;n>o;o++)this.words[o]=0;this.length+=n}return this.strip()},i.prototype.ishrn=function(t,e,n){r(\"number\"==typeof t&&t>=0);var i;i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=n;if(i-=o,i=Math.max(0,i),l){for(var u=0;o>u;u++)l.words[u]=this.words[u];l.length=o}if(0===o);else if(this.length>o){this.length-=o;for(var u=0;u<this.length;u++)this.words[u]=this.words[u+o]}else this.words[0]=0,this.length=1;for(var c=0,u=this.length-1;u>=0&&(0!==c||u>=i);u--){var f=this.words[u];this.words[u]=c<<26-a|f>>>a,c=f&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip(),this},i.prototype.shln=function(t){return this.clone().ishln(t)},i.prototype.shrn=function(t){return this.clone().ishrn(t)},i.prototype.testn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n)return!1;var a=this.words[n];return!!(a&i)},i.prototype.imaskn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26;if(r(!this.sign,\"imaskn works only with positive numbers\"),0!==e&&n++,this.length=Math.min(n,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return r(\"number\"==typeof t),0>t?this.isubn(-t):this.sign?1===this.length&&this.words[0]<t?(this.words[0]=t-this.words[0],\n",
+       "this.sign=!1,this):(this.sign=!1,this.isubn(t),this.sign=!0,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(r(\"number\"==typeof t),0>t)return this.iaddn(-t);if(this.sign)return this.sign=!1,this.iaddn(t),this.sign=!0,this;this.words[0]-=t;for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.sign=!1,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,n){var i,a=t.length+n;if(this.words.length<a){for(var o=new Array(a),i=0;i<this.length;i++)o[i]=this.words[i];this.words=o}else i=this.length;for(this.length=Math.max(this.length,a);i<this.length;i++)this.words[i]=0;for(var s=0,i=0;i<t.length;i++){var l=this.words[i+n]+s,u=t.words[i]*e;l-=67108863&u,s=(l>>26)-(u/67108864|0),this.words[i+n]=67108863&l}for(;i<this.length-n;i++){var l=this.words[i+n]+s;s=l>>26,this.words[i+n]=67108863&l}if(0===s)return this.strip();r(-1===s),s=0;for(var i=0;i<this.length;i++){var l=-this.words[i]+s;s=l>>26,this.words[i]=67108863&l}return this.sign=!0,this.strip()},i.prototype._wordDiv=function(t,e){var r=this.length-t.length,n=this.clone(),a=t,o=a.words[a.length-1],s=this._countBits(o);r=26-s,0!==r&&(a=a.shln(r),n.ishln(r),o=a.words[a.length-1]);var l,u=n.length-a.length;if(\"mod\"!==e){l=new i(null),l.length=u+1,l.words=new Array(l.length);for(var c=0;c<l.length;c++)l.words[c]=0}var f=n.clone()._ishlnsubmul(a,1,u);f.sign||(n=f,l&&(l.words[u]=1));for(var h=u-1;h>=0;h--){var p=67108864*n.words[a.length+h]+n.words[a.length+h-1];for(p=Math.min(p/o|0,67108863),n._ishlnsubmul(a,p,h);n.sign;)p--,n.sign=!1,n._ishlnsubmul(a,1,h),0!==n.cmpn(0)&&(n.sign=!n.sign);l&&(l.words[h]=p)}return l&&l.strip(),n.strip(),\"div\"!==e&&0!==r&&n.ishrn(r),{div:l?l:null,mod:n}},i.prototype.divmod=function(t,e){if(r(0!==t.cmpn(0)),this.sign&&!t.sign){var n,a,o=this.neg().divmod(t,e);return\"mod\"!==e&&(n=o.div.neg()),\"div\"!==e&&(a=0===o.mod.cmpn(0)?o.mod:t.sub(o.mod)),{div:n,mod:a}}if(!this.sign&&t.sign){var n,o=this.divmod(t.neg(),e);return\"mod\"!==e&&(n=o.div.neg()),{div:n,mod:o.mod}}return this.sign&&t.sign?this.neg().divmod(t.neg(),e):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e)},i.prototype.div=function(t){return this.divmod(t,\"div\").div},i.prototype.mod=function(t){return this.divmod(t,\"mod\").mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(0===e.mod.cmpn(0))return e.div;var r=e.div.sign?e.mod.isub(t):e.mod,n=t.shrn(1),i=t.andln(1),a=r.cmp(n);return 0>a||1===i&&0===a?e.div:e.div.sign?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){r(67108863>=t);for(var e=(1<<26)%t,n=0,i=this.length-1;i>=0;i--)n=(e*n+this.words[i])%t;return n},i.prototype.idivn=function(t){r(67108863>=t);for(var e=0,n=this.length-1;n>=0;n--){var i=this.words[n]+67108864*e;this.words[n]=i/t|0,e=i%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),u=0;e.isEven()&&n.isEven();)e.ishrn(1),n.ishrn(1),++u;for(var c=n.clone(),f=e.clone();0!==e.cmpn(0);){for(;e.isEven();)e.ishrn(1),a.isEven()&&o.isEven()?(a.ishrn(1),o.ishrn(1)):(a.iadd(c).ishrn(1),o.isub(f).ishrn(1));for(;n.isEven();)n.ishrn(1),s.isEven()&&l.isEven()?(s.ishrn(1),l.ishrn(1)):(s.iadd(c).ishrn(1),l.isub(f).ishrn(1));e.cmp(n)>=0?(e.isub(n),a.isub(s),o.isub(l)):(n.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:n.ishln(u)}},i.prototype._invmp=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=n.clone();e.cmpn(1)>0&&n.cmpn(1)>0;){for(;e.isEven();)e.ishrn(1),a.isEven()?a.ishrn(1):a.iadd(s).ishrn(1);for(;n.isEven();)n.ishrn(1),o.isEven()?o.ishrn(1):o.iadd(s).ishrn(1);e.cmp(n)>=0?(e.isub(n),a.isub(o)):(n.isub(e),o.isub(a))}return 0===e.cmpn(1)?a:o},i.prototype.gcd=function(t){if(0===this.cmpn(0))return t.clone();if(0===t.cmpn(0))return this.clone();var e=this.clone(),r=t.clone();e.sign=!1,r.sign=!1;for(var n=0;e.isEven()&&r.isEven();n++)e.ishrn(1),r.ishrn(1);for(;;){for(;e.isEven();)e.ishrn(1);for(;r.isEven();)r.ishrn(1);var i=e.cmp(r);if(0>i){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.ishln(n)},i.prototype.invm=function(t){return this.egcd(t).a.mod(t)},i.prototype.isEven=function(){return 0===(1&this.words[0])},i.prototype.isOdd=function(){return 1===(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){r(\"number\"==typeof t);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n){for(var a=this.length;n+1>a;a++)this.words[a]=0;return this.words[n]|=i,this.length=n+1,this}for(var o=i,a=n;0!==o&&a<this.length;a++){var s=this.words[a];s+=o,o=s>>>26,s&=67108863,this.words[a]=s}return 0!==o&&(this.words[a]=o,this.length++),this},i.prototype.cmpn=function(t){var e=0>t;if(e&&(t=-t),this.sign&&!e)return-1;if(!this.sign&&e)return 1;t&=67108863,this.strip();var r;if(this.length>1)r=1;else{var n=this.words[0];r=n===t?0:t>n?-1:1}return this.sign&&(r=-r),r},i.prototype.cmp=function(t){if(this.sign&&!t.sign)return-1;if(!this.sign&&t.sign)return 1;var e=this.ucmp(t);return this.sign?-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=this.words[r],i=t.words[r];if(n!==i){i>n?e=-1:n>i&&(e=1);break}}return e},i.red=function(t){return new h(t)},i.prototype.toRed=function(t){return r(!this.red,\"Already a number in reduction context\"),r(!this.sign,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return r(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return r(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},i.prototype.redAdd=function(t){return r(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},i.prototype.redIAdd=function(t){return r(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},i.prototype.redSub=function(t){return r(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},i.prototype.redISub=function(t){return r(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},i.prototype.redShl=function(t){return r(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},i.prototype.redMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},i.prototype.redIMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},i.prototype.redSqr=function(){return r(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},i.prototype.redISqr=function(){return r(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},i.prototype.redSqrt=function(){return r(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},i.prototype.redInvm=function(){return r(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},i.prototype.redNeg=function(){return r(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},i.prototype.redPow=function(t){return r(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var m={k256:null,p224:null,p192:null,p25519:null};s.prototype._tmp=function(){var t=new i(null);return t.words=new Array(Math.ceil(this.n/13)),t},s.prototype.ireduce=function(t){var e,r=t;do this.split(r,this.tmp),r=this.imulK(r),r=r.iadd(this.tmp),e=r.bitLength();while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},s.prototype.split=function(t,e){t.ishrn(this.n,0,e)},s.prototype.imulK=function(t){return t.imul(this.k)},n(l,s),l.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;n>i;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];e.words[e.length++]=a&r;for(var i=10;i<t.length;i++){var o=t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}t.words[i-10]=a>>>22,t.length-=9},l.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e,r=0,n=0;n<t.length;n++){var i=t.words[n];e=64*i,r+=977*i,e+=r/67108864|0,r&=67108863,t.words[n]=r,r=e}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},n(u,s),n(c,s),n(f,s),f.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*t.words[r]+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},i._prime=function 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g=p,v=0;0!==g.cmp(l);v++)g=g.redSqr();r(d>v);var m=this.pow(h,new i(1).ishln(d-v-1));a=a.redMul(m),h=m.redSqr(),p=p.redMul(h),d=v}return a},h.prototype.invm=function(t){var e=t._invmp(this.m);return e.sign?(e.sign=!1,this.imod(e).redNeg()):this.imod(e)},h.prototype.pow=function(t,e){var r=[];if(0===e.cmpn(0))return new i(1);for(var n=e.clone();0!==n.cmpn(0);)r.push(n.andln(1)),n.ishrn(1);for(var a=t,o=0;o<r.length&&0===r[o];o++,a=this.sqr(a));if(++o<r.length)for(var n=this.sqr(a);o<r.length;o++,n=this.sqr(n))0!==r[o]&&(a=this.mul(a,n));return a},h.prototype.convertTo=function(t){var e=t.mod(this.m);return e===t?e.clone():e},h.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},i.mont=function(t){return new p(t)},n(p,h),p.prototype.convertTo=function(t){return this.imod(t.shln(this.shift))},p.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},p.prototype.imul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return 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2146435072&n&&(i+=1<<20),[r,i]},e.exports.denormalized=function(t){var r=e.exports.hi(t);return!(2146435072&r)}}).call(this,t(\"buffer\").Buffer)},{buffer:300}],111:[function(t,e,r){\"use strict\";function n(t){return i(t[0])*i(t[1])}var i=t(\"./lib/bn-sign\");e.exports=n},{\"./lib/bn-sign\":101}],112:[function(t,e,r){\"use strict\";function n(t,e){return i(t[0].mul(e[1]).sub(t[1].mul(e[0])),t[1].mul(e[1]))}var i=t(\"./lib/rationalize\");e.exports=n},{\"./lib/rationalize\":106}],113:[function(t,e,r){\"use strict\";function n(t){var e=t[0],r=t[1];if(0===e.cmpn(0))return 0;var n=e.divmod(r),o=n.div,s=i(o),l=n.mod;if(0===l.cmpn(0))return s;if(s){var u=a(s)+4,c=i(l.shln(u).divRound(r));return 0>s&&(c=-c),s+c*Math.pow(2,-u)}var f=r.bitLength()-l.bitLength()+53,c=i(l.shln(f).divRound(r));return 1023>f?c*Math.pow(2,-f):(c*=Math.pow(2,-1023),c*Math.pow(2,1023-f))}var i=t(\"./lib/bn-to-num\"),a=t(\"./lib/ctz\");e.exports=n},{\"./lib/bn-to-num\":102,\"./lib/ctz\":103}],114:[function(t,e,r){\"use 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c,f=t(\"typedarray-pool\"),h=t(\"./lib/sweep\"),p=t(\"./lib/intersect\")},{\"./lib/intersect\":116,\"./lib/sweep\":120,\"typedarray-pool\":121}],115:[function(t,e,r){\"use strict\";function n(t,e,r){var n=\"bruteForce\"+(t?\"Red\":\"Blue\")+(e?\"Flip\":\"\")+(r?\"Full\":\"\"),i=[\"function \",n,\"(\",w.join(),\"){\",\"var \",u,\"=2*\",a,\";\"],l=\"for(var i=\"+c+\",\"+d+\"=\"+u+\"*\"+c+\";i<\"+f+\";++i,\"+d+\"+=\"+u+\"){var x0=\"+h+\"[\"+o+\"+\"+d+\"],x1=\"+h+\"[\"+o+\"+\"+d+\"+\"+a+\"],xi=\"+p+\"[i];\",k=\"for(var j=\"+g+\",\"+b+\"=\"+u+\"*\"+g+\";j<\"+v+\";++j,\"+b+\"+=\"+u+\"){var y0=\"+m+\"[\"+o+\"+\"+b+\"],\"+(r?\"y1=\"+m+\"[\"+o+\"+\"+b+\"+\"+a+\"],\":\"\")+\"yi=\"+y+\"[j];\";return t?i.push(l,_,\":\",k):i.push(k,_,\":\",l),r?i.push(\"if(y1<x0||x1<y0)continue;\"):e?i.push(\"if(y0<=x0||x1<y0)continue;\"):i.push(\"if(y0<x0||x1<y0)continue;\"),i.push(\"for(var k=\"+o+\"+1;k<\"+a+\";++k){var 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t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function u(t,e,r,n,i){var o=t.getParameter(t.MAX_TEXTURE_SIZE);if(0>e||e>o||0>r||r>o)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var s=l(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new a(t,s,e,r,n,i)}function c(t,e,r,n){var i=l(t);return t.texImage2D(t.TEXTURE_2D,0,r,r,n,e),new a(t,i,0|e.width,0|e.height,r,n)}function f(t,e){var r=e.dtype,n=e.shape.slice(),i=t.getParameter(t.MAX_TEXTURE_SIZE);if(n[0]<0||n[0]>i||n[1]<0||n[1]>i)throw new Error(\"gl-texture2d: Invalid texture size\");var s=o(n,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,s=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,s=!1,r=\"uint8\");var c=0;if(2===n.length)c=t.LUMINANCE,n=[n[0],n[1],1],e=p(e.data,n,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==n.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===n[2])c=t.ALPHA;else if(2===n[2])c=t.LUMINANCE_ALPHA;else if(3===n[2])c=t.RGB;else{if(4!==n[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");c=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,s=!1);var f,h,v=e.size;if(s)f=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var m=[n[2],n[2]*n[0],1];h=g.malloc(v,r);var y=p(h,n,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?d.assign(y,e):b(y,e),f=h.subarray(0,v)}var x=l(t);return t.texImage2D(t.TEXTURE_2D,0,c,n[0],n[1],0,c,u,f),s||g.free(h),new a(t,x,n[0],n[1],c,u)}function h(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");if(v||n(t),\"number\"==typeof arguments[1])return u(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return u(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1];if(e instanceof HTMLCanvasElement||e instanceof HTMLImageElement||e instanceof HTMLVideoElement||e instanceof ImageData)return c(t,e,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return f(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")}var p=t(\"ndarray\"),d=t(\"ndarray-ops\"),g=t(\"typedarray-pool\");e.exports=h;var v=null,m=null,y=null,b=function(t,e){d.muls(t,e,255)},x=a.prototype;Object.defineProperties(x,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&v.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),m.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,t),this._minFilter=t}},magFilter:{get:function(){return this._magFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&v.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),m.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,t),this._magFilter=t}},mipSamples:{get:function(){return this._anisoSamples},set:function(t){var e=this._anisoSamples;if(this._anisoSamples=0|Math.max(t,1),e!==this._anisoSamples){var r=gl.getExtension(\"EXT_texture_filter_anisotropic\");r&&this.gl.texParameterf(this.gl.TEXTURE_2D,r.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(t){if(this.bind(),y.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),y.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;2>e;++e)if(y.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return i(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return t=0|t,i(this,t,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t=0|t,i(this,this._shape[0],t),t}}}),x.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},x.dispose=function(){this.gl.deleteTexture(this.handle)},x.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},x.setPixels=function(t,e,r,n){var i=this.gl;if(this.bind(),Array.isArray(e)?(n=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),n=n||0,t instanceof HTMLCanvasElement||t instanceof ImageData||t instanceof HTMLImageElement||t instanceof HTMLVideoElement){var a=this._mipLevels.indexOf(n)<0;a?(i.texImage2D(i.TEXTURE_2D,0,this.format,this.format,this.type,t),this._mipLevels.push(n)):i.texSubImage2D(i.TEXTURE_2D,n,e,r,this.format,this.type,t)}else{if(!(t.shape&&t.stride&&t.data))throw new Error(\"gl-texture2d: Unsupported data type\");if(t.shape.length<2||e+t.shape[1]>this._shape[1]>>>n||r+t.shape[0]>this._shape[0]>>>n||0>e||0>r)throw new Error(\"gl-texture2d: Texture dimensions are out of bounds\");s(i,e,r,n,this.format,this.type,this._mipLevels,t)}}},{ndarray:247,\"ndarray-ops\":171,\"typedarray-pool\":178}],180:[function(t,e,r){function n(t){var e=new Float32Array(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e}e.exports=n},{}],181:[function(t,e,r){function n(){var t=new Float32Array(16);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],182:[function(t,e,r){function n(t){var e=t[0],r=t[1],n=t[2],i=t[3],a=t[4],o=t[5],s=t[6],l=t[7],u=t[8],c=t[9],f=t[10],h=t[11],p=t[12],d=t[13],g=t[14],v=t[15],m=e*o-r*a,y=e*s-n*a,b=e*l-i*a,x=r*s-n*o,_=r*l-i*o,w=n*l-i*s,k=u*d-c*p,A=u*g-f*p,M=u*v-h*p,T=c*g-f*d,E=c*v-h*d,L=f*v-h*g;return m*L-y*E+b*T+x*M-_*A+w*k}e.exports=n},{}],183:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,u=r*o,c=n*o,f=n*s,h=i*o,p=i*s,d=i*l,g=a*o,v=a*s,m=a*l;return t[0]=1-f-d,t[1]=c+m,t[2]=h-v,t[3]=0,t[4]=c-m,t[5]=1-u-d,t[6]=p+g,t[7]=0,t[8]=h+v,t[9]=p-g,t[10]=1-u-f,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],184:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,u=a+a,c=n*s,f=n*l,h=n*u,p=i*l,d=i*u,g=a*u,v=o*s,m=o*l,y=o*u;return t[0]=1-(p+g),t[1]=f+y,t[2]=h-m,t[3]=0,t[4]=f-y,t[5]=1-(c+g),t[6]=d+v,t[7]=0,t[8]=h+m,t[9]=d-v,t[10]=1-(c+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}e.exports=n},{}],185:[function(t,e,r){function n(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}e.exports=n},{}],186:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],v=e[14],m=e[15],y=r*s-n*o,b=r*l-i*o,x=r*u-a*o,_=n*l-i*s,w=n*u-a*s,k=i*u-a*l,A=c*g-f*d,M=c*v-h*d,T=c*m-p*d,E=f*v-h*g,L=f*m-p*g,S=h*m-p*v,C=y*S-b*L+x*E+_*T-w*M+k*A;return C?(C=1/C,t[0]=(s*S-l*L+u*E)*C,t[1]=(i*L-n*S-a*E)*C,t[2]=(g*k-v*w+m*_)*C,t[3]=(h*w-f*k-p*_)*C,t[4]=(l*T-o*S-u*M)*C,t[5]=(r*S-i*T+a*M)*C,t[6]=(v*x-d*k-m*b)*C,t[7]=(c*k-h*x+p*b)*C,t[8]=(o*L-s*T+u*A)*C,t[9]=(n*T-r*L-a*A)*C,t[10]=(d*w-g*x+m*y)*C,t[11]=(f*x-c*w-p*y)*C,t[12]=(s*M-o*E-l*A)*C,t[13]=(r*E-n*M+i*A)*C,t[14]=(g*b-d*_-v*y)*C,t[15]=(c*_-f*b+h*y)*C,t):null}e.exports=n},{}],187:[function(t,e,r){function n(t,e,r,n){var a,o,s,l,u,c,f,h,p,d,g=e[0],v=e[1],m=e[2],y=n[0],b=n[1],x=n[2],_=r[0],w=r[1],k=r[2];return Math.abs(g-_)<1e-6&&Math.abs(v-w)<1e-6&&Math.abs(m-k)<1e-6?i(t):(f=g-_,h=v-w,p=m-k,d=1/Math.sqrt(f*f+h*h+p*p),f*=d,h*=d,p*=d,a=b*p-x*h,o=x*f-y*p,s=y*h-b*f,d=Math.sqrt(a*a+o*o+s*s),d?(d=1/d,a*=d,o*=d,s*=d):(a=0,o=0,s=0),l=h*s-p*o,u=p*a-f*s,c=f*o-h*a,d=Math.sqrt(l*l+u*u+c*c),d?(d=1/d,l*=d,u*=d,c*=d):(l=0,u=0,c=0),t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=u,t[6]=h,t[7]=0,t[8]=s,t[9]=c,t[10]=p,t[11]=0,t[12]=-(a*g+o*v+s*m),t[13]=-(l*g+u*v+c*m),t[14]=-(f*g+h*v+p*m),t[15]=1,t)}var i=t(\"./identity\");e.exports=n},{\"./identity\":185}],188:[function(t,e,r){function n(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],u=e[6],c=e[7],f=e[8],h=e[9],p=e[10],d=e[11],g=e[12],v=e[13],m=e[14],y=e[15],b=r[0],x=r[1],_=r[2],w=r[3];return t[0]=b*n+x*s+_*f+w*g,t[1]=b*i+x*l+_*h+w*v,t[2]=b*a+x*u+_*p+w*m,t[3]=b*o+x*c+_*d+w*y,b=r[4],x=r[5],_=r[6],w=r[7],t[4]=b*n+x*s+_*f+w*g,t[5]=b*i+x*l+_*h+w*v,t[6]=b*a+x*u+_*p+w*m,t[7]=b*o+x*c+_*d+w*y,b=r[8],x=r[9],_=r[10],w=r[11],t[8]=b*n+x*s+_*f+w*g,t[9]=b*i+x*l+_*h+w*v,t[10]=b*a+x*u+_*p+w*m,t[11]=b*o+x*c+_*d+w*y,b=r[12],x=r[13],_=r[14],w=r[15],t[12]=b*n+x*s+_*f+w*g,t[13]=b*i+x*l+_*h+w*v,t[14]=b*a+x*u+_*p+w*m,t[15]=b*o+x*c+_*d+w*y,t}e.exports=n},{}],189:[function(t,e,r){function n(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}e.exports=n},{}],190:[function(t,e,r){function n(t,e,r,n){var i,a,o,s,l,u,c,f,h,p,d,g,v,m,y,b,x,_,w,k,A,M,T,E,L=n[0],S=n[1],C=n[2],P=Math.sqrt(L*L+S*S+C*C);return Math.abs(P)<1e-6?null:(P=1/P,L*=P,S*=P,C*=P,i=Math.sin(r),a=Math.cos(r),o=1-a,s=e[0],l=e[1],u=e[2],c=e[3],f=e[4],h=e[5],p=e[6],d=e[7],g=e[8],v=e[9],m=e[10],y=e[11],b=L*L*o+a,x=S*L*o+C*i,_=C*L*o-S*i,w=L*S*o-C*i,k=S*S*o+a,A=C*S*o+L*i,M=L*C*o+S*i,T=S*C*o-L*i,E=C*C*o+a,t[0]=s*b+f*x+g*_,t[1]=l*b+h*x+v*_,t[2]=u*b+p*x+m*_,t[3]=c*b+d*x+y*_,t[4]=s*w+f*k+g*A,t[5]=l*w+h*k+v*A,t[6]=u*w+p*k+m*A,t[7]=c*w+d*k+y*A,t[8]=s*M+f*T+g*E,t[9]=l*M+h*T+v*E,t[10]=u*M+p*T+m*E,t[11]=c*M+d*T+y*E,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t)}e.exports=n},{}],191:[function(t,e,r){function n(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],u=e[8],c=e[9],f=e[10],h=e[11];return 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u=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]],c=n.prototype;c.draw=function(){var t=[1,0,0,0,1,0,0,0,1],e=[1,1];return function(){var r=this.plot,n=this.shader,i=this.buffer,a=this.bounds,o=this.numPoints,s=(this.color,r.gl),l=r.dataBox,c=r.viewBox,f=r.pixelRatio,h=a[2]-a[0],p=a[3]-a[1],d=l[2]-l[0],g=l[3]-l[1];t[0]=2*h/d,t[4]=2*p/g,t[6]=2*(a[0]-l[0])/d-1,t[7]=2*(a[1]-l[1])/g-1;var v=c[2]-c[0],m=c[3]-c[1];e[0]=2*f/v,e[1]=2*f/m,i.bind(),n.bind(),n.uniforms.viewTransform=t,n.uniforms.pixelScale=e,n.uniforms.color=this.color,n.attributes.position.pointer(s.FLOAT,!1,16,0),n.attributes.pixelOffset.pointer(s.FLOAT,!1,16,8),s.drawArrays(s.TRIANGLES,0,o*u.length)}}(),c.drawPick=function(t){return t},c.pick=function(t,e){return null},c.update=function(t){t=t||{};var e=t.positions||[],r=t.errors||[],n=1;\"lineWidth\"in t&&(n=+t.lineWidth);var i=5;\"capSize\"in t&&(i=+t.capSize),this.color=(t.color||[0,0,0,1]).slice();for(var a=this.bounds=[1/0,1/0,-(1/0),-(1/0)],o=this.numPoints=e.length>>1,l=0;o>l;++l){var c=e[2*l],f=e[2*l+1];a[0]=Math.min(c,a[0]),a[1]=Math.min(f,a[1]),a[2]=Math.max(c,a[2]),a[3]=Math.max(f,a[3])}a[2]===a[0]&&(a[2]+=1),a[3]===a[1]&&(a[3]+=1);for(var h=1/(a[2]-a[0]),p=1/(a[3]-a[1]),d=a[0],g=a[1],v=s.mallocFloat32(o*u.length*4),m=0,l=0;o>l;++l)for(var c=e[2*l],f=e[2*l+1],y=r[4*l],b=r[4*l+1],x=r[4*l+2],_=r[4*l+3],w=0;w<u.length;++w){var k=u[w],A=k[0],M=k[1];0>A?A*=y:A>0&&(A*=b),0>M?M*=x:M>0&&(M*=_),v[m++]=h*(c-d+A),v[m++]=p*(f-g+M),v[m++]=n*k[2]+(i+n)*k[4],v[m++]=n*k[3]+(i+n)*k[5]}this.buffer.update(v),s.free(v)},c.dispose=function(){this.plot.removeObject(this),this.shader.dispose(),this.buffer.dispose()}},{\"./lib/shaders\":327,\"gl-buffer\":325,\"gl-shader\":385,\"typedarray-pool\":463}],327:[function(t,e,r){e.exports={vertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 pixelOffset;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\n\\nvoid main() {\\n  vec3 scrPosition = viewTransform * vec3(position, 1);\\n  gl_Position = vec4(\\n    scrPosition.xy + scrPosition.z * pixelScale * pixelOffset,\\n    0,\\n    scrPosition.z);\\n}\\n\",fragment:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\\n\"}},{}],328:[function(t,e,r){\"use strict\";function n(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1}function i(t,e){for(var r=0;3>r;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}function a(t,e,r,n){for(var i=h[n],a=0;a<i.length;++a){var o=i[a];t.push(e[0],e[1],e[2],r[0],r[1],r[2],r[3],o[0],o[1],o[2])}return i.length}function o(t){var e=t.gl,r=s(e),i=l(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),a=u(e);a.attributes.position.location=0,a.attributes.color.location=1,a.attributes.offset.location=2;var o=new n(e,r,i,a);return o.update(t),o}e.exports=o;var s=t(\"gl-buffer\"),l=t(\"gl-vao\"),u=t(\"./shaders/index\"),c=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],f=n.prototype;f.isOpaque=function(){return this.opacity>=1},f.isTransparent=function(){return this.opacity<1},f.drawTransparent=f.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||c,i=r.projection=t.projection||c;r.model=t.model||c,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],o=n[13],s=n[14],l=n[15],u=this.pixelRatio*(i[3]*a+i[7]*o+i[11]*s+i[15]*l)/e.drawingBufferHeight;this.vao.bind();for(var f=0;3>f;++f)e.lineWidth(this.lineWidth[f]),r.capSize=this.capSize[f]*u,e.drawArrays(e.LINES,this.lineOffset[f],this.lineCount[f]);this.vao.unbind()};var h=function(){for(var t=new Array(3),e=0;3>e;++e){for(var r=[],n=1;2>=n;++n)for(var i=-1;1>=i;i+=2){var a=(n+e)%3,o=[0,0,0];o[a]=i,r.push(o)}t[e]=r}return t}();f.update=function(t){t=t||{},\"lineWidth\"in t&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),\"capSize\"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),\"opacity\"in t&&(this.opacity=t.opacity);var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var o=[],s=r.length,l=0;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.lineCount=[0,0,0];for(var u=0;3>u;++u){this.lineOffset[u]=l;t:for(var c=0;s>c;++c){for(var f=r[c],h=0;3>h;++h)if(isNaN(f[h])||!isFinite(f[h]))continue t;var p=n[c],d=e[u];if(Array.isArray(d[0])&&(d=e[c]),3===d.length&&(d=[d[0],d[1],d[2],1]),!isNaN(p[0][u])&&!isNaN(p[1][u])){if(p[0][u]<0){var g=f.slice();g[u]+=p[0][u],o.push(f[0],f[1],f[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,d,u)}if(p[1][u]>0){var g=f.slice();g[u]+=p[1][u],o.push(f[0],f[1],f[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),i(this.bounds,g),l+=2+a(o,g,d,u)}}}this.lineCount[u]=l-this.lineOffset[u]}this.buffer.update(o)}},f.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},{\"./shaders/index\":329,\"gl-buffer\":325,\"gl-vao\":420}],329:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, offset;\\nattribute vec4 color;\\nuniform mat4 model, view, projection;\\nuniform float capSize;\\nvarying vec4 fragColor;\\nvarying vec3 fragPosition;\\n\\nvoid main() {\\n  vec4 worldPosition  = model * vec4(position, 1.0);\\n  worldPosition       = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\\n  gl_Position         = projection * view * worldPosition;\\n  fragColor           = color;\\n  fragPosition        = position;\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(fragPosition, clipBounds[0])) || any(greaterThan(fragPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = opacity * fragColor;\\n}\";e.exports=function(t){return n(t,i,a,null,[{name:\"position\",type:\"vec3\"},{name:\"offset\",type:\"vec3\"},{name:\"color\",type:\"vec4\"}])}},{\"gl-shader\":385}],330:[function(t,e,r){arguments[4][170][0].apply(r,arguments)},{dup:170,\"gl-texture2d\":416}],331:[function(t,e,r){r.lineVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat inverse_1_0(float m) {\\n  return 1.0 / m;\\n}\\n\\nmat2 inverse_1_0(mat2 m) {\\n  return mat2(m[1][1],-m[0][1],\\n             -m[1][0], m[0][0]) / (m[0][0]*m[1][1] - m[0][1]*m[1][0]);\\n}\\n\\nmat3 inverse_1_0(mat3 m) {\\n  float a00 = m[0][0], a01 = m[0][1], a02 = m[0][2];\\n  float a10 = m[1][0], a11 = m[1][1], a12 = m[1][2];\\n  float a20 = m[2][0], a21 = m[2][1], a22 = m[2][2];\\n\\n  float b01 = a22 * a11 - a12 * a21;\\n  float b11 = -a22 * a10 + a12 * a20;\\n  float b21 = a21 * a10 - a11 * a20;\\n\\n  float det = a00 * b01 + a01 * b11 + a02 * b21;\\n\\n  return mat3(b01, (-a22 * a01 + a02 * a21), (a12 * a01 - a02 * a11),\\n              b11, (a22 * a00 - a02 * a20), (-a12 * a00 + a02 * a10),\\n              b21, (-a21 * a00 + a01 * a20), (a11 * a00 - a01 * a10)) / det;\\n}\\n\\nmat4 inverse_1_0(mat4 m) {\\n  float\\n      a00 = m[0][0], a01 = m[0][1], a02 = m[0][2], a03 = m[0][3],\\n      a10 = m[1][0], a11 = m[1][1], a12 = m[1][2], a13 = m[1][3],\\n      a20 = m[2][0], a21 = m[2][1], a22 = m[2][2], a23 = m[2][3],\\n      a30 = m[3][0], a31 = m[3][1], a32 = m[3][2], a33 = m[3][3],\\n\\n      b00 = a00 * a11 - a01 * a10,\\n      b01 = a00 * a12 - a02 * a10,\\n      b02 = a00 * a13 - a03 * a10,\\n      b03 = a01 * a12 - a02 * a11,\\n      b04 = a01 * a13 - a03 * a11,\\n      b05 = a02 * a13 - a03 * a12,\\n      b06 = a20 * a31 - a21 * a30,\\n      b07 = a20 * a32 - a22 * a30,\\n      b08 = a20 * a33 - a23 * a30,\\n      b09 = a21 * a32 - a22 * a31,\\n      b10 = a21 * a33 - a23 * a31,\\n      b11 = a22 * a33 - a23 * a32,\\n\\n      det = b00 * b11 - b01 * b10 + b02 * b09 + b03 * b08 - b04 * b07 + b05 * b06;\\n\\n  return mat4(\\n      a11 * b11 - a12 * b10 + a13 * b09,\\n      a02 * b10 - a01 * b11 - a03 * b09,\\n      a31 * b05 - a32 * b04 + a33 * b03,\\n      a22 * b04 - a21 * b05 - a23 * b03,\\n      a12 * b08 - a10 * b11 - a13 * b07,\\n      a00 * b11 - a02 * b08 + a03 * b07,\\n      a32 * b02 - a30 * b05 - a33 * b01,\\n      a20 * b05 - a22 * b02 + a23 * b01,\\n      a10 * b10 - a11 * b08 + a13 * b06,\\n      a01 * b08 - a00 * b10 - a03 * b06,\\n      a30 * b04 - a31 * b02 + a33 * b00,\\n      a21 * b02 - a20 * b04 - a23 * b00,\\n      a11 * b07 - a10 * b09 - a12 * b06,\\n      a00 * b09 - a01 * b07 + a02 * b06,\\n      a31 * b01 - a30 * b03 - a32 * b00,\\n      a20 * b03 - a21 * b01 + a22 * b00) / det;\\n}\\n\\n\\n\\nattribute vec2 a, d;\\n\\nuniform mat3 matrix;\\nuniform vec2 screenShape;\\nuniform float width;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  vec2 dir = (matrix * vec3(d, 0)).xy;\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 n = 0.5 * width *\\n    normalize(screenShape.yx * vec2(dir.y, -dir.x)) / screenShape.xy;\\n  vec2 tangent = normalize(screenShape.xy * dir);\\n  if(dir.x < 0.0 || (dir.x == 0.0 && dir.y < 0.0)) {\\n    direction = -tangent;\\n  } else {\\n    direction = tangent;\\n  }\\n  gl_Position = vec4(base.xy/base.z + n, 0, 1);\\n}\\n\",r.lineFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\nuniform vec2 screenShape;\\nuniform sampler2D dashPattern;\\nuniform float dashLength;\\n\\nvarying vec2 direction;\\n\\nvoid main() {\\n  float t = fract(dot(direction, gl_FragCoord.xy) / dashLength);\\n  vec4 pcolor = color * texture2D(dashPattern, vec2(t, 0.0)).r;\\n  gl_FragColor = vec4(pcolor.rgb * pcolor.a, pcolor.a);\\n}\\n\",r.mitreVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 p;\\n\\nuniform mat3  matrix;\\nuniform vec2 screenShape;\\nuniform float radius;\\n\\nvoid main() {\\n  vec3 pp = matrix * vec3(p, 1);\\n  gl_Position  = vec4(pp.xy, 0, pp.z);\\n  gl_PointSize = radius;\\n}\\n\",r.mitreFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  if(length(gl_PointCoord.xy - 0.5) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(color.rgb, color.a);\\n}\\n\",r.pickVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 a, d;\\nattribute vec4 pick0, pick1;\\n\\nuniform mat3 matrix;\\nuniform vec2 screenShape;\\nuniform float width;\\n\\nvarying vec4 pickA, pickB;\\n\\nfloat inverse_1_0(float m) {\\n  return 1.0 / m;\\n}\\n\\nmat2 inverse_1_0(mat2 m) {\\n  return mat2(m[1][1],-m[0][1],\\n             -m[1][0], m[0][0]) / (m[0][0]*m[1][1] - m[0][1]*m[1][0]);\\n}\\n\\nmat3 inverse_1_0(mat3 m) {\\n  float a00 = m[0][0], a01 = m[0][1], a02 = m[0][2];\\n  float a10 = m[1][0], a11 = m[1][1], a12 = m[1][2];\\n  float a20 = m[2][0], a21 = m[2][1], a22 = m[2][2];\\n\\n  float b01 = a22 * a11 - a12 * a21;\\n  float b11 = -a22 * a10 + a12 * a20;\\n  float b21 = a21 * a10 - a11 * a20;\\n\\n  float det = a00 * b01 + a01 * b11 + a02 * b21;\\n\\n  return mat3(b01, (-a22 * a01 + a02 * a21), (a12 * a01 - a02 * a11),\\n              b11, (a22 * a00 - a02 * a20), (-a12 * a00 + a02 * a10),\\n              b21, (-a21 * a00 + a01 * a20), (a11 * a00 - a01 * a10)) / det;\\n}\\n\\nmat4 inverse_1_0(mat4 m) {\\n  float\\n      a00 = m[0][0], a01 = m[0][1], a02 = m[0][2], a03 = m[0][3],\\n      a10 = m[1][0], a11 = m[1][1], a12 = m[1][2], a13 = m[1][3],\\n      a20 = m[2][0], a21 = m[2][1], a22 = m[2][2], a23 = m[2][3],\\n      a30 = m[3][0], a31 = m[3][1], a32 = m[3][2], a33 = m[3][3],\\n\\n      b00 = a00 * a11 - a01 * a10,\\n      b01 = a00 * a12 - a02 * a10,\\n      b02 = a00 * a13 - a03 * a10,\\n      b03 = a01 * a12 - a02 * a11,\\n      b04 = a01 * a13 - a03 * a11,\\n      b05 = a02 * a13 - a03 * a12,\\n      b06 = a20 * a31 - a21 * a30,\\n      b07 = a20 * a32 - a22 * a30,\\n      b08 = a20 * a33 - a23 * a30,\\n      b09 = a21 * a32 - a22 * a31,\\n      b10 = a21 * a33 - a23 * a31,\\n      b11 = a22 * a33 - a23 * a32,\\n\\n      det = b00 * b11 - b01 * b10 + b02 * b09 + b03 * b08 - b04 * b07 + b05 * b06;\\n\\n  return mat4(\\n      a11 * b11 - a12 * b10 + a13 * b09,\\n      a02 * b10 - a01 * b11 - a03 * b09,\\n      a31 * b05 - a32 * b04 + a33 * b03,\\n      a22 * b04 - a21 * b05 - a23 * b03,\\n      a12 * b08 - a10 * b11 - a13 * b07,\\n      a00 * b11 - a02 * b08 + a03 * b07,\\n      a32 * b02 - a30 * b05 - a33 * b01,\\n      a20 * b05 - a22 * b02 + a23 * b01,\\n      a10 * b10 - a11 * b08 + a13 * b06,\\n      a01 * b08 - a00 * b10 - a03 * b06,\\n      a30 * b04 - a31 * b02 + a33 * b00,\\n      a21 * b02 - a20 * b04 - a23 * b00,\\n      a11 * b07 - a10 * b09 - a12 * b06,\\n      a00 * b09 - a01 * b07 + a02 * b06,\\n      a31 * b01 - a30 * b03 - a32 * b00,\\n      a20 * b03 - a21 * b01 + a22 * b00) / det;\\n}\\n\\n\\n\\nvoid main() {\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 n = width *\\n    normalize(screenShape.yx * vec2(d.y, -d.x)) / screenShape.xy;\\n  gl_Position = vec4(base.xy/base.z + n, 0, 1);\\n  pickA = pick0;\\n  pickB = pick1;\\n}\\n\",r.pickFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 pickOffset;\\n\\nvarying vec4 pickA, pickB;\\n\\nvoid main() {\\n  vec4 fragId = vec4(pickA.xyz, 0.0);\\n  if(pickB.w > pickA.w) {\\n    fragId.xyz = pickB.xyz;\\n  }\\n\\n  fragId += pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  gl_FragColor = fragId / 255.0;\\n}\\n\",r.fillVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 a, d;\\n\\nuniform mat3 matrix;\\nuniform vec2 projectAxis;\\nuniform float projectValue;\\nuniform float depth;\\n\\nvoid main() {\\n  vec3 base = matrix * vec3(a, 1);\\n  vec2 p = base.xy / base.z;\\n  if(d.y < 0.0 || (d.y == 0.0 && d.x < 0.0)) {\\n    if(dot(p, projectAxis) < projectValue) {\\n      p = p * (1.0 - abs(projectAxis)) + projectAxis * projectValue;\\n    }\\n  }\\n  gl_Position = vec4(p, depth, 1);\\n}\\n\",r.fillFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = vec4(color.rgb * color.a, color.a);\\n}\\n\"},{}],332:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){this.plot=t,this.dashPattern=e,this.lineBuffer=r,this.pickBuffer=n,this.lineShader=i,this.mitreShader=a,this.fillShader=o,this.pickShader=s,this.usingDashes=!1,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.width=1,this.color=[0,0,1,1],this.fill=[!1,!1,!1,!1],this.fillColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.data=null,this.numPoints=0,this.vertCount=0,this.pickOffset=0,this.lodBuffer=[]}function i(t){return t.map(function(t){return t.slice()})}function a(t,e){var r=t.gl,i=s(r),a=s(r),u=l(r,[1,1]),c=o(r,f.lineVertex,f.lineFragment),h=o(r,f.mitreVertex,f.mitreFragment),p=o(r,f.fillVertex,f.fillFragment),d=o(r,f.pickVertex,f.pickFragment),g=new n(t,u,i,a,c,h,p,d);return t.addObject(g),g.update(e),g}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"gl-texture2d\"),u=t(\"ndarray\"),c=t(\"typedarray-pool\"),f=t(\"./lib/shaders\"),h=n.prototype;h.draw=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0],r=[1,0],n=[-1,0],i=[0,1],a=[0,-1];return function(){var o=this.plot,s=this.color,l=this.width,u=(this.numPoints,this.bounds),c=this.vertCount,f=o.gl,h=o.viewBox,p=o.dataBox,d=o.pixelRatio,g=u[2]-u[0],v=u[3]-u[1],m=p[2]-p[0],y=p[3]-p[1],b=h[2]-h[0],x=h[3]-h[1];t[0]=2*g/m,t[4]=2*v/y,t[6]=2*(u[0]-p[0])/m-1,t[7]=2*(u[1]-p[1])/y-1,e[0]=b,e[1]=x;var _=this.lineBuffer;_.bind();var w=this.fill;if(w[0]||w[1]||w[2]||w[3]){var k=this.fillShader;k.bind();var A=k.uniforms;A.matrix=t,A.depth=o.nextDepthValue();var M=k.attributes;M.a.pointer(f.FLOAT,!1,16,0),M.d.pointer(f.FLOAT,!1,16,8),f.depthMask(!0),f.enable(f.DEPTH_TEST);var T=this.fillColor;w[0]&&(A.color=T[0],A.projectAxis=n,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[1]&&(A.color=T[1],A.projectAxis=a,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[2]&&(A.color=T[2],A.projectAxis=r,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),w[3]&&(A.color=T[3],A.projectAxis=i,A.projectValue=1,f.drawArrays(f.TRIANGLES,0,c)),f.depthMask(!1),f.disable(f.DEPTH_TEST)}var E=this.lineShader;E.bind();var L=E.uniforms;L.matrix=t,L.color=s,L.width=l*d,L.screenShape=e,L.dashPattern=this.dashPattern.bind(),L.dashLength=this.dashLength*d;var S=E.attributes;if(S.a.pointer(f.FLOAT,!1,16,0),S.d.pointer(f.FLOAT,!1,16,8),f.drawArrays(f.TRIANGLES,0,c),l>2&&!this.usingDashes){var C=this.mitreShader;C.bind();var P=C.uniforms;P.matrix=t,P.color=s,P.screenShape=e,P.radius=l*d,C.attributes.p.pointer(f.FLOAT,!1,48,0),f.drawArrays(f.POINTS,0,c/3|0)}}}(),h.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0],r=[0,0,0,0];return function(n){var i=this.plot,a=this.pickShader,o=this.lineBuffer,s=this.pickBuffer,l=this.width,u=this.numPoints,c=this.bounds,f=this.vertCount,h=i.gl,p=i.viewBox,d=i.dataBox,g=i.pickPixelRatio,v=c[2]-c[0],m=c[3]-c[1],y=d[2]-d[0],b=d[3]-d[1],x=p[2]-p[0],_=p[3]-p[1];\n",
+       "this.pickOffset=n,t[0]=2*v/y,t[4]=2*m/b,t[6]=2*(c[0]-d[0])/y-1,t[7]=2*(c[1]-d[1])/b-1,e[0]=x,e[1]=_,r[0]=255&n,r[1]=n>>>8&255,r[2]=n>>>16&255,r[3]=n>>>24,a.bind();var w=a.uniforms;w.matrix=t,w.width=l*g,w.pickOffset=r,w.screenShape=e;var k=a.attributes;return o.bind(),k.a.pointer(h.FLOAT,!1,16,0),k.d.pointer(h.FLOAT,!1,16,8),s.bind(),k.pick0.pointer(h.UNSIGNED_BYTE,!1,8,0),k.pick1.pointer(h.UNSIGNED_BYTE,!1,8,4),h.drawArrays(h.TRIANGLES,0,f),n+u}}(),h.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(n>r||r>=n+i)return null;var a=r-n,o=this.data;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},h.update=function(t){t=t||{};var e=this.plot.gl;this.color=(t.color||[0,0,1,1]).slice(),this.width=+(t.width||1),this.fill=(t.fill||[!1,!1,!1,!1]).slice(),this.fillColor=i(t.fillColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);for(var r=t.dashes||[1],n=0,a=0;a<r.length;++a)n+=r[a];for(var o=c.mallocUint8(n),s=0,f=255,a=0;a<r.length;++a){for(var h=0;h<r[a];++h)o[s++]=f;f^=255}this.dashPattern.dispose(),this.usingDashes=r.length>1,this.dashPattern=l(e,u(o,[n,1,4],[1,0,0])),this.dashPattern.minFilter=e.NEAREST,this.dashPattern.magFilter=e.NEAREST,this.dashLength=n,c.free(o);var p=t.positions;this.data=p;var d=this.bounds;d[0]=d[1]=1/0,d[2]=d[3]=-(1/0);var g=this.numPoints=p.length>>>1;if(0!==g){for(var a=0;g>a;++a){var v=p[2*a],m=p[2*a+1];d[0]=Math.min(d[0],v),d[1]=Math.min(d[1],m),d[2]=Math.max(d[2],v),d[3]=Math.max(d[3],m)}d[0]===d[2]&&(d[2]+=1),d[3]===d[1]&&(d[3]+=1);var y=c.mallocFloat32(24*(g-1)),b=c.mallocUint32(12*(g-1)),x=y.length,_=b.length,s=g;for(this.vertCount=6*(g-1);s>1;){var w=--s,v=p[2*s],m=p[2*s+1];v=(v-d[0])/(d[2]-d[0]),m=(m-d[1])/(d[3]-d[1]);var k=w-1,A=p[2*k],M=p[2*k+1];A=(A-d[0])/(d[2]-d[0]),M=(M-d[1])/(d[3]-d[1]);var T=A-v,E=M-m,L=w|1<<24,S=w-1,C=w,P=w-1|1<<24;y[--x]=-E,y[--x]=-T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S,y[--x]=E,y[--x]=T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=-E,y[--x]=-T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=E,y[--x]=T,y[--x]=M,y[--x]=A,b[--_]=C,b[--_]=P,y[--x]=-E,y[--x]=-T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S,y[--x]=E,y[--x]=T,y[--x]=m,y[--x]=v,b[--_]=L,b[--_]=S}this.lineBuffer.update(y),this.pickBuffer.update(b),c.free(y),c.free(b)}},h.dispose=function(){this.plot.removeObject(this),this.lineBuffer.dispose(),this.pickBuffer.dispose(),this.lineShader.dispose(),this.mitreShader.dispose(),this.fillShader.dispose(),this.pickShader.dispose(),this.dashPattern.dispose()}},{\"./lib/shaders\":331,\"gl-buffer\":325,\"gl-shader\":385,\"gl-texture2d\":416,ndarray:438,\"typedarray-pool\":463}],333:[function(t,e,r){var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvoid main() {\\n  vec4 projected = projection * view * model * vec4(position, 1.0);\\n  vec4 tangentClip = projection * view * model * vec4(nextPosition - position, 0.0);\\n  vec2 tangent = normalize(screenShape * tangentClip.xy);\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(tangent.y, -tangent.x) / screenShape;\\n\\n  gl_Position = vec4(projected.xy + projected.w * offset, projected.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\nlowp vec4 encode_float_1_0(highp float v) {\\n  highp float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  highp vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  highp float e = floor(log2(av));\\n  highp float m = av * pow(2.0, -e) - 1.0;\\n  \\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n  \\n  //Unpack exponent\\n  highp float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0; \\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\n\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if(any(lessThan(worldPosition, clipBounds[0])) || any(greaterThan(worldPosition, clipBounds[1]))) {\\n    discard;\\n  }\\n  gl_FragColor = vec4(pickId/255.0, encode_float_1_0(pixelArcLength).xyz);\\n}\",s=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return n(t,i,a,null,s)},r.createPickShader=function(t){return n(t,i,o,null,s)}},{\"gl-shader\":385}],334:[function(t,e,r){\"use strict\";function n(t,e){for(var r=0,n=0;3>n;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function i(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;3>r;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function a(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function o(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.dirty=!0,this.pixelRatio=1}function s(t){var e=t.gl||t.scene&&t.scene.gl,r=g(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var n=v(e);n.attributes.position.location=0,n.attributes.nextPosition.location=1,n.attributes.arcLength.location=2,n.attributes.lineWidth.location=3,n.attributes.color.location=4;for(var i=l(e),a=u(e,[{buffer:i,size:3,offset:0,stride:48},{buffer:i,size:3,offset:12,stride:48},{buffer:i,size:1,offset:24,stride:48},{buffer:i,size:1,offset:28,stride:48},{buffer:i,size:4,offset:32,stride:48}]),s=p(new Array(1024),[256,1,4]),f=0;1024>f;++f)s.data[f]=255;var h=c(e,s);h.wrap=e.REPEAT;var d=new o(e,r,n,i,a,h);return d.update(t),d}e.exports=s;var l=t(\"gl-buffer\"),u=t(\"gl-vao\"),c=t(\"gl-texture2d\"),f=t(\"glsl-read-float\"),h=t(\"binary-search-bounds\"),p=t(\"ndarray\"),d=t(\"./lib/shaders\"),g=d.createShader,v=d.createPickShader,m=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],y=o.prototype;y.isTransparent=function(){return this.opacity<1},y.isOpaque=function(){return this.opacity>=1},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||m,view:t.view||m,projection:t.projection||m,clipBounds:i(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.drawPick=function(t){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||m,view:t.view||m,projection:t.projection||m,pickId:this.pickId,clipBounds:i(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount)},y.update=function(t){this.dirty=!0,\"dashScale\"in t&&(this.dashScale=t.dashScale),\"opacity\"in t&&(this.opacity=+t.opacity);var e=t.position||t.positions;if(e){var r=t.color||t.colors||[0,0,0,1],i=t.lineWidth||1,a=[],o=[],s=[],l=0,u=0,c=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];t:for(var f=1;f<e.length;++f){var d=e[f-1],g=e[f];o.push(l),s.push(d.slice());for(var v=0;3>v;++v){if(isNaN(d[v])||isNaN(g[v])||!isFinite(d[v])||!isFinite(g[v]))continue t;c[0][v]=Math.min(c[0][v],d[v],g[v]),c[1][v]=Math.max(c[1][v],d[v],g[v])}var m,y;Array.isArray(r[0])?(m=r[f-1],y=r[f]):m=y=r,3===m.length&&(m=[m[0],m[1],m[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]);var b,x;Array.isArray(i)?(b=i[f-1],x=lineWidht[f]):b=x=i;var _=l;l+=n(d,g),a.push(d[0],d[1],d[2],g[0],g[1],g[2],_,b,m[0],m[1],m[2],m[3],d[0],d[1],d[2],g[0],g[1],g[2],_,-b,m[0],m[1],m[2],m[3],g[0],g[1],g[2],d[0],d[1],d[2],l,-b,y[0],y[1],y[2],y[3],g[0],g[1],g[2],d[0],d[1],d[2],l,b,y[0],y[1],y[2],y[3]),u+=4}if(this.buffer.update(a),o.push(l),s.push(e[e.length-1].slice()),this.bounds=c,this.vertexCount=u,this.points=s,this.arcLength=o,\"dashes\"in t){var w=t.dashes,k=w.slice();k.unshift(0);for(var f=1;f<k.length;++f)k[f]=k[f-1]+k[f];for(var A=p(new Array(1024),[256,1,4]),f=0;256>f;++f){for(var v=0;4>v;++v)A.set(f,0,v,0);1&h.le(k,k[k.length-1]*f/255)?A.set(f,0,0,0):A.set(f,0,0,255)}this.texture.setPixels(A)}}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=f(t.value[0],t.value[1],t.value[2],0),r=h.le(this.arcLength,e);if(0>r)return null;if(r===this.arcLength.length-1)return new a(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],o=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),s=1-o,l=[0,0,0],u=0;3>u;++u)l[u]=s*n[u]+o*i[u];var c=Math.min(.5>o?r:r+1,this.points.length-1);return new a(e,l,c,this.points[c])}},{\"./lib/shaders\":333,\"binary-search-bounds\":335,\"gl-buffer\":325,\"gl-texture2d\":416,\"gl-vao\":420,\"glsl-read-float\":336,ndarray:438}],335:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],336:[function(t,e,r){function n(t,e,r,n){return i[0]=n,i[1]=r,i[2]=e,i[3]=t,a[0]}e.exports=n;var i=new Uint8Array(4),a=new Float32Array(i.buffer)},{}],337:[function(t,e,r){function n(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],u=e[7],c=e[8],f=c*o-s*u,h=-c*a+s*l,p=u*a-o*l,d=r*f+n*h+i*p;return 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l=t(\"barycentric\"),u=t(\"polytope-closest-point/lib/closest_point_2d.js\");e.exports=s},{barycentric:357,\"polytope-closest-point/lib/closest_point_2d.js\":359}],355:[function(t,e,r){var n=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec4 m_position  = model * vec4(position, 1.0);\\n  vec4 t_position  = view * m_position;\\n  gl_Position      = projection * t_position;\\n  f_color          = color;\\n  f_normal         = normal;\\n  f_data           = position;\\n  f_eyeDirection   = eyePosition   - position;\\n  f_lightDirection = lightPosition - position;\\n  f_uv             = uv;\\n}\",i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat cookTorranceSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * 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h=n[f][0],p=n[f][1],d=i[f],g=1-d,v=this.positions[h],m=this.positions[p],y=0;3>y;++y)o[s++]=d*v[y]+g*m[y]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),A.free(o)},O.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"opacity\"in t&&(this.opacity=t.opacity),t.texture?(this.texture.dispose(),this.texture=m(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(i(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var s=[],l=[],u=[],c=[],f=[],h=[],p=[],d=[],g=[],v=[],b=[],x=[],_=[],w=[];this.cells=r,this.positions=n;var k=t.vertexNormals,A=t.cellNormals;t.useFacetNormals&&!A&&(A=y.faceNormals(r,n)),A||k||(k=y.vertexNormals(r,n));var M=t.vertexColors,T=t.cellColors,E=t.meshColor||[1,1,1,1],L=t.vertexUVs,S=t.vertexIntensity,C=t.cellUVs,P=t.cellIntensity,z=1/0,R=-(1/0);if(!L&&!C)if(S)for(var O=0;O<S.length;++O){var I=S[O];z=Math.min(z,I),R=Math.max(R,I)}else if(P)for(var O=0;O<P.length;++O){var I=P[O];z=Math.min(z,I),R=Math.max(R,I)}else for(var O=0;O<n.length;++O){var I=n[O][2];z=Math.min(z,I),R=Math.max(R,I)}S?this.intensity=S:P?this.intensity=a(r,n.length,P):this.intensity=o(n);var j=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]];for(var O=0;O<n.length;++O)for(var F=n[O],D=0;3>D;++D)!isNaN(F[D])&&isFinite(F[D])&&(this.bounds[0][D]=Math.min(this.bounds[0][D],F[D]),this.bounds[1][D]=Math.max(this.bounds[1][D],F[D]));var B=0,U=0,V=0;t:for(var O=0;O<r.length;++O){var q=r[O];switch(q.length){case 1:for(var H=q[0],F=n[H],D=0;3>D;++D)if(isNaN(F[D])||!isFinite(F[D]))continue t;v.push(F[0],F[1],F[2]);var 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W;W=k?k[H]:A[O],u.push(W[0],W[1],W[2]),f.push(O)}B+=1}}this.pointCount=V,this.edgeCount=U,this.triangleCount=B,this.pointPositions.update(v),this.pointColors.update(b),this.pointUVs.update(x),this.pointSizes.update(_),this.pointIds.update(new Uint32Array(w)),this.edgePositions.update(h),this.edgeColors.update(p),this.edgeUVs.update(d),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(s),this.triangleColors.update(l),this.triangleUVs.update(c),this.triangleNormals.update(u),this.triangleIds.update(new Uint32Array(f))}},O.drawTransparent=O.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;3>o;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,contourColor:this.contourColor,texture:0};this.texture.bind(0);var l=new Array(16);b(l,s.view,s.model),b(l,s.projection,l),x(l,l);for(var o=0;3>o;++o)s.eyePosition[o]=l[12+o]/l[15];for(var u=l[15],o=0;3>o;++o)u+=this.lightPosition[o]*l[4*o+3];for(var o=0;3>o;++o){for(var c=l[12+o],f=0;3>f;++f)c+=l[4*f+o]*this.lightPosition[f];s.lightPosition[o]=c/u}if(this.triangleCount>0){var h=this.triShader;h.bind(),h.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}if(this.edgeCount>0&&this.lineWidth>0){var h=this.lineShader;h.bind(),h.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()}if(this.pointCount>0){var h=this.pointShader;h.bind(),h.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}if(this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0){var h=this.contourShader;h.bind(),h.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind()}},O.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||R,n=t.view||R,i=t.projection||R,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;3>o;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255},l=this.pickShader;if(l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0){var l=this.pointPickShader;l.bind(),l.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()}},O.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=T(i,[t.coord[0],this._resolution[1]-t.coord[1]],this._model,this._view,this._projection,this._resolution);if(!o)return null;for(var s=o[2],l=0,a=0;a<r.length;++a)l+=s[a]*this.intensity[r[a]];return{position:o[1],index:r[o[0]],cell:r,cellId:e,intensity:l,dataCoordinate:this.positions[r[o[0]]]}},O.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=p},{\"./lib/closest-point\":354,\"./lib/shaders\":355,colormap:307,\"gl-buffer\":325,\"gl-mat4/invert\":344,\"gl-mat4/multiply\":346,\"gl-shader\":385,\"gl-texture2d\":416,\"gl-vao\":420,ndarray:438,normals:358,\"simplicial-complex-contour\":360,\"typedarray-pool\":463}],357:[function(t,e,r){\"use strict\";function n(t){for(var e=0,r=0;r<t.length;++r)e+=t[r];\n",
+       "return e}function i(t,e){for(var r=e.length,i=new Array(r+1),o=0;r>o;++o){for(var s=new Array(r+1),l=0;r>=l;++l)s[l]=t[l][o];i[o]=s}i[r]=new Array(r+1);for(var o=0;r>=o;++o)i[r][o]=1;for(var u=new Array(r+1),o=0;r>o;++o)u[o]=e[o];u[r]=1;var c=a(i,u),f=n(c[r+1]);0===f&&(f=1);for(var h=new Array(r+1),o=0;r>=o;++o)h[o]=n(c[o])/f;return h}e.exports=i;var a=t(\"robust-linear-solve\")},{\"robust-linear-solve\":441}],358:[function(t,e,r){var n=1e-6;r.vertexNormals=function(t,e){for(var r=e.length,i=new Array(r),a=0;r>a;++a)i[a]=[0,0,0];for(var a=0;a<t.length;++a)for(var o=t[a],s=0,l=o[o.length-1],u=o[0],c=0;c<o.length;++c){s=l,l=u,u=o[(c+1)%o.length];for(var f=e[s],h=e[l],p=e[u],d=new Array(3),g=0,v=new Array(3),m=0,y=0;3>y;++y)d[y]=f[y]-h[y],g+=d[y]*d[y],v[y]=p[y]-h[y],m+=v[y]*v[y];if(g*m>n)for(var b=i[l],x=1/Math.sqrt(g*m),y=0;3>y;++y){var _=(y+1)%3,w=(y+2)%3;b[y]+=x*(v[_]*d[w]-v[w]*d[_])}}for(var a=0;r>a;++a){for(var b=i[a],k=0,y=0;3>y;++y)k+=b[y]*b[y];if(k>n)for(var x=1/Math.sqrt(k),y=0;3>y;++y)b[y]*=x;else for(var y=0;3>y;++y)b[y]=0}return i},r.faceNormals=function(t,e){for(var r=t.length,i=new Array(r),a=0;r>a;++a){for(var o=t[a],s=new Array(3),l=0;3>l;++l)s[l]=e[o[l]];for(var u=new Array(3),c=new Array(3),l=0;3>l;++l)u[l]=s[1][l]-s[0][l],c[l]=s[2][l]-s[0][l];for(var f=new Array(3),h=0,l=0;3>l;++l){var p=(l+1)%3,d=(l+2)%3;f[l]=u[p]*c[d]-u[d]*c[p],h+=f[l]*f[l]}h=h>n?1/Math.sqrt(h):0;for(var l=0;3>l;++l)f[l]*=h;i[a]=f}return i}},{}],359:[function(t,e,r){\"use strict\";function n(t,e,r,n,s){i.length<n.length&&(i=new Float64Array(n.length),a=new Float64Array(n.length),o=new Float64Array(n.length));for(var l=0;l<n.length;++l)i[l]=t[l]-n[l],a[l]=e[l]-t[l],o[l]=r[l]-t[l];for(var u=0,c=0,f=0,h=0,p=0,d=0,l=0;l<n.length;++l){var g=a[l],v=o[l],m=i[l];u+=g*g,c+=g*v,f+=v*v,h+=m*g,p+=m*v,d+=m*m}var y,b=Math.abs(u*f-c*c),x=c*p-f*h,_=c*h-u*p;if(b>=x+_)if(0>x)0>_&&0>h?(_=0,-h>=u?(x=1,y=u+2*h+d):(x=-h/u,y=h*x+d)):(x=0,p>=0?(_=0,y=d):-p>=f?(_=1,y=f+2*p+d):(_=-p/f,y=p*_+d));else if(0>_)_=0,h>=0?(x=0,y=d):-h>=u?(x=1,y=u+2*h+d):(x=-h/u,y=h*x+d);else{var w=1/b;x*=w,_*=w,y=x*(u*x+c*_+2*h)+_*(c*x+f*_+2*p)+d}else{var k,A,M,T;0>x?(k=c+h,A=f+p,A>k?(M=A-k,T=u-2*c+f,M>=T?(x=1,_=0,y=u+2*h+d):(x=M/T,_=1-x,y=x*(u*x+c*_+2*h)+_*(c*x+f*_+2*p)+d)):(x=0,0>=A?(_=1,y=f+2*p+d):p>=0?(_=0,y=d):(_=-p/f,y=p*_+d))):0>_?(k=c+p,A=u+h,A>k?(M=A-k,T=u-2*c+f,M>=T?(_=1,x=0,y=f+2*p+d):(_=M/T,x=1-_,y=x*(u*x+c*_+2*h)+_*(c*x+f*_+2*p)+d)):(_=0,0>=A?(x=1,y=u+2*h+d):h>=0?(x=0,y=d):(x=-h/u,y=h*x+d))):(M=f+p-c-h,0>=M?(x=0,_=1,y=f+2*p+d):(T=u-2*c+f,M>=T?(x=1,_=0,y=u+2*h+d):(x=M/T,_=1-x,y=x*(u*x+c*_+2*h)+_*(c*x+f*_+2*p)+d)))}for(var E=1-x-_,l=0;l<n.length;++l)s[l]=E*t[l]+x*e[l]+_*r[l];return 0>y?0:y}var i=new Float64Array(4),a=new Float64Array(4),o=new Float64Array(4);e.exports=n},{}],360:[function(t,e,r){\"use strict\";function n(t){for(var e=t.length,r=0,n=0;e>n;++n)r=0|Math.max(r,t[n].length);return r-1}function i(t,e){for(var r=t.length,n=f.mallocUint8(r),i=0;r>i;++i)n[i]=t[i]<e|0;return n}function a(t,e){for(var r=t.length,n=e*(e+1)/2*r|0,i=f.mallocUint32(2*n),a=0,o=0;r>o;++o)for(var s=t[o],e=s.length,l=0;e>l;++l)for(var u=0;l>u;++u){var p=s[u],d=s[l];i[a++]=0|Math.min(p,d),i[a++]=0|Math.max(p,d)}var g=a/2|0;h(c(i,[g,2]));for(var v=2,o=2;a>o;o+=2)(i[o-2]!==i[o]||i[o-1]!==i[o+1])&&(i[v++]=i[o],i[v++]=i[o+1]);return c(i,[v/2|0,2])}function o(t,e,r,n){for(var i=t.data,a=t.shape[0],o=f.mallocDouble(a),s=0,l=0;a>l;++l){var u=i[2*l],h=i[2*l+1];if(r[u]!==r[h]){var p=e[u],d=e[h];i[2*s]=u,i[2*s+1]=h,o[s++]=(d-n)/(d-p)}}return t.shape[0]=s,c(o,[s])}function s(t,e){var r=f.mallocInt32(2*e),n=t.shape[0],i=t.data;r[0]=0;for(var a=0,o=0;n>o;++o){var s=i[2*o];if(s!==a){for(r[2*a+1]=o;++a<s;)r[2*a]=o,r[2*a+1]=o;r[2*a]=o}}for(r[2*a+1]=n;++a<e;)r[2*a]=r[2*a+1]=n;return r}function l(t){for(var e=0|t.shape[0],r=t.data,n=new 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t=[0,0],e=[0,0],r=[0,0];return function(){for(var n=this.plot,i=this.vbo,a=this.shader,o=this.ticks,s=n.gl,l=n._tickBounds,u=n.dataBox,c=n.viewBox,f=n.gridLineWidth,h=n.gridLineColor,p=n.gridLineEnable,d=n.pixelRatio,g=0;2>g;++g){var v=l[g],m=l[g+2],y=m-v,b=.5*(u[g+2]+u[g]),x=u[g+2]-u[g];e[g]=2*y/x,t[g]=2*(v-b)/x}a.bind(),i.bind(),a.attributes.dataCoord.pointer(),a.uniforms.dataShift=t,a.uniforms.dataScale=e;for(var _=0,g=0;2>g;++g){r[0]=r[1]=0,r[g]=1,a.uniforms.dataAxis=r,a.uniforms.lineWidth=f[g]/(c[g+2]-c[g])*d,a.uniforms.color=h[g];var w=6*o[g].length;p[g]&&s.drawArrays(s.TRIANGLES,_,w),_+=w}}}(),c.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],a=[0,0],o=[0,0];return function(){for(var s=this.plot,u=this.vbo,c=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,g=s.viewBox,v=s.pixelRatio,m=s.screenBox,y=m[2]-m[0],b=m[3]-m[1],x=g[2]-g[0],_=g[3]-g[1],w=0;2>w;++w){var k=p[w],A=p[w+2],M=A-k,T=.5*(d[w+2]+d[w]),E=d[w+2]-d[w];e[w]=2*M/E,t[w]=2*(k-T)/E}e[0]*=x/y,t[0]*=x/y,e[1]*=_/b,t[1]*=_/b,c.bind(),u.bind(),c.attributes.dataCoord.pointer();var L=c.uniforms;L.dataShift=t,L.dataScale=e;var S=s.tickMarkLength,C=s.tickMarkWidth,P=s.tickMarkColor,z=0,R=6*f[0].length,O=Math.min(l.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),i),f[0].length),I=Math.min(l.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),i),f[0].length),j=z+6*O,N=6*Math.max(0,I-O),F=Math.min(l.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),i),f[1].length),D=Math.min(l.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),i),f[1].length),B=R+6*F,U=6*Math.max(0,D-F);a[0]=2*(g[0]-S[1])/y-1,a[1]=(g[3]+g[1])/b-1,o[0]=S[1]*v/y,o[1]=C[1]*v/b,L.color=P[1],L.tickScale=o,L.dataAxis=n,L.screenOffset=a,h.drawArrays(h.TRIANGLES,B,U),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[1]-S[0])/b-1,o[0]=C[0]*v/y,o[1]=S[0]*v/b,L.color=P[0],L.tickScale=o,L.dataAxis=r,L.screenOffset=a,h.drawArrays(h.TRIANGLES,j,N),a[0]=2*(g[2]+S[3])/y-1,a[1]=(g[3]+g[1])/b-1,o[0]=S[3]*v/y,o[1]=C[3]*v/b,L.color=P[3],L.tickScale=o,L.dataAxis=n,L.screenOffset=a,h.drawArrays(h.TRIANGLES,B,U),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[3]+S[2])/b-1,o[0]=C[2]*v/y,o[1]=S[2]*v/b,L.color=P[2],L.tickScale=o,L.dataAxis=r,L.screenOffset=a,h.drawArrays(h.TRIANGLES,j,N)}}(),c.update=function(){var t=[1,1,-1,-1,1,-1],e=[1,-1,1,1,-1,-1];return function(r){for(var n=r.ticks,i=r.bounds,a=new Float32Array(18*(n[0].length+n[1].length)),o=(this.plot.zeroLineEnable,0),s=[[],[]],l=0;2>l;++l)for(var u=s[l],c=n[l],f=i[l],h=i[l+2],p=0;p<c.length;++p){var d=(c[p].x-f)/(h-f);u.push(d);for(var g=0;6>g;++g)a[o++]=d,a[o++]=t[g],a[o++]=e[g]}this.ticks=s,this.vbo.update(a)}}(),c.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":368,\"binary-search-bounds\":370,\"gl-buffer\":325,\"gl-shader\":385}],367:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r}function i(t){var e=t.gl,r=a(e,[-1,-1,-1,1,1,-1,1,1]),i=o(e,s.lineVert,s.lineFrag),l=new n(t,r,i);return l}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"./shaders\"),l=n.prototype;l.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},l.drawLine=function(){var t=[0,0],e=[0,0];return function(r,n,i,a,o,s){var l=this.plot,u=this.shader,c=l.gl;t[0]=r,t[1]=n,e[0]=i,e[1]=a,u.uniforms.start=t,u.uniforms.end=e,u.uniforms.width=o*l.pixelRatio,u.uniforms.color=s,c.drawArrays(c.TRIANGLE_STRIP,0,4)}}(),l.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":368,\"gl-buffer\":325,\"gl-shader\":385}],368:[function(t,e,r){\"use strict\";var n=\"#define GLSLIFY 1\\nprecision lowp float;\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\";e.exports={lineVert:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\",lineFrag:n,textVert:\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\",textFrag:n,gridVert:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\",gridFrag:n,boxVert:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\",tickVert:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"}},{}],369:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}function i(t){var e=t.gl,r=a(e),i=o(e,u.textVert,u.textFrag),s=new n(t,r,i);return s}e.exports=i;var a=t(\"gl-buffer\"),o=t(\"gl-shader\"),s=t(\"text-cache\"),l=t(\"binary-search-bounds\"),u=t(\"./shaders\"),c=n.prototype;c.drawTicks=function(){var t=[0,0],e=[0,0],r=[0,0];return function(n){var i=this.plot,a=this.shader,o=this.tickX[n],s=this.tickOffset[n],u=i.gl,c=i.viewBox,f=i.dataBox,h=i.screenBox,p=i.pixelRatio,d=i.tickEnable,g=i.tickPad,v=i.tickColor,m=i.tickAngle,y=(i.tickMarkLength,i.labelEnable),b=i.labelPad,x=i.labelColor,_=i.labelAngle,w=this.labelOffset[n],k=this.labelCount[n],A=l.lt(o,f[n]),M=l.le(o,f[n+2]);t[0]=t[1]=0,t[n]=1,e[n]=(c[2+n]+c[n])/(h[2+n]-h[n])-1;var T=2/h[2+(1^n)]-h[1^n];e[1^n]=T*c[1^n]-1,d[n]&&(e[1^n]-=T*p*g[n],M>A&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=v[n],a.uniforms.angle=m[n],u.drawArrays(u.TRIANGLES,s[A],s[M]-s[A]))),y[n]&&(e[1^n]-=T*p*b[n],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n],a.uniforms.angle=_[n],u.drawArrays(u.TRIANGLES,w,k)),e[1^n]=T*c[2+(1^n)]-1,d[n+2]&&(e[1^n]+=T*p*g[n+2],M>A&&(a.uniforms.dataAxis=t,a.uniforms.screenOffset=e,a.uniforms.color=v[n+2],a.uniforms.angle=m[n+2],u.drawArrays(u.TRIANGLES,s[A],s[M]-s[A]))),y[n+2]&&(e[1^n]+=T*p*b[n+2],a.uniforms.dataAxis=r,a.uniforms.screenOffset=e,a.uniforms.color=x[n+2],a.uniforms.angle=_[n+2],u.drawArrays(u.TRIANGLES,w,k))}}(),c.drawTitle=function(){var t=[0,0],e=[0,0];return function(){for(var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,o=r.titleCenter,u=r.pixelRatio,c=0;2>c;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}(),c.bind=function(){var t=[0,0],e=[0,0],r=[0,0];return function(){var n=this.plot,i=this.shader,a=n._tickBounds,o=n.dataBox,s=n.screenBox,l=n.viewBox;i.bind();for(var u=0;2>u;++u){var c=a[u],f=a[u+2],h=f-c,p=.5*(o[u+2]+o[u]),d=o[u+2]-o[u],g=l[u],v=l[u+2],m=v-g,y=s[u],b=s[u+2],x=b-y;e[u]=2*h/d*m/x,t[u]=2*(c-p)/d*m/x}r[1]=2*n.pixelRatio/(s[3]-s[1]),r[0]=r[1]*(s[3]-s[1])/(s[2]-s[0]),i.uniforms.dataScale=e,i.uniforms.dataShift=t,i.uniforms.textScale=r,this.vbo.bind(),i.attributes.textCoordinate.pointer()}}(),c.update=function(t){for(var e=[],r=t.ticks,n=t.bounds,i=0;2>i;++i){for(var a=[Math.floor(e.length/3)],o=[-(1/0)],l=r[i],u=0;u<l.length;++u){for(var c=l[u],f=c.x,h=c.text,p=c.font||\"sans-serif\",d=c.fontSize||12,g=s(p,h).data,v=1/(n[i+2]-n[i]),m=n[i],y=0;y<g.length;y+=2)e.push(g[y]*d,-g[y+1]*d,(f-m)*v);a.push(Math.floor(e.length/3)),o.push(f)}this.tickOffset[i]=a,this.tickX[i]=o}for(var i=0;2>i;++i){this.labelOffset[i]=Math.floor(e.length/3);for(var g=s(t.labelFont[i],t.labels[i]).data,d=t.labelSize[i],u=0;u<g.length;u+=2)e.push(g[u]*d,-g[u+1]*d,0);this.labelCount[i]=Math.floor(e.length/3)-this.labelOffset[i]}this.titleOffset=Math.floor(e.length/3);for(var g=s(t.titleFont,t.title).data,d=t.titleSize,u=0;u<g.length;u+=2)e.push(g[u]*d,-g[u+1]*d,0);this.titleCount=Math.floor(e.length/3)-this.titleOffset,this.vbo.update(e)},c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":368,\"binary-search-bounds\":370,\"gl-buffer\":325,\"gl-shader\":385,\"text-cache\":458}],370:[function(t,e,r){arguments[4][87][0].apply(r,arguments)},{dup:87}],371:[function(t,e,r){\"use strict\";function n(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-(1/0),-(1/0)],this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}function i(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function a(t,e){return t.x-e.x}function o(t){var e=t.gl,r=s(e,[e.drawingBufferWidth,e.drawingBufferHeight]),i=new n(e,r);return i.grid=l(i),i.text=u(i),i.line=c(i),i.box=f(i),i.update(t),i}e.exports=o;var s=t(\"gl-select-static\"),l=t(\"./lib/grid\"),u=t(\"./lib/text\"),c=t(\"./lib/line\"),f=t(\"./lib/box\"),h=n.prototype;h.setDirty=function(){this.dirty=this.pickDirty=!0},h.setOverlayDirty=function(){this.dirty=!0},h.nextDepthValue=function(){return this._depthCounter++/65536},h.draw=function(){return function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var u=this.borderColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT),t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var c=this.backgroundColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;2>d;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],h[d]):o.drawLine(e[0],g,e[2],g,p[d],h[d])}}for(var d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var v=this.borderLineEnable,m=this.borderLineWidth,y=this.borderLineColor;v[1]&&o.drawLine(r[0],r[1]-.5*m[1]*i,r[0],r[3]+.5*m[3]*i,m[1],y[1]),v[0]&&o.drawLine(r[0]-.5*m[0]*i,r[1],r[2]+.5*m[2]*i,r[1],m[0],y[0]),v[3]&&o.drawLine(r[2],r[1]-.5*m[1]*i,r[2],r[3]+.5*m[3]*i,m[3],y[3]),v[2]&&o.drawLine(r[0]-.5*m[0]*i,r[3],r[2]+.5*m[2]*i,r[3],m[2],y[2]),s.bind();for(var d=0;2>d;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();for(var b=this.overlays,d=0;d<b.length;++d)b[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}}}(),h.drawPick=function(){return function(){var t=this.pickBuffer;this.gl;this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}}(),h.pick=function(){return function(t,e){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),u=this.objects,c=0;c<u.length;++c){\n",
+       "var f=u[c].pick(a,o,l);if(f)return f}return null}}(),h.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},h.setDataBox=function(t){var e=this.dataBox,r=e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3];r&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},h.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},h.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,o=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/o,10,10/o]),this.borderColor=(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=i(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=i(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=i(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t&&!t.titleEnable),this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=i(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=i(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=i(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var s=t.ticks||[[],[]],l=this._tickBounds;l[0]=l[1]=1/0,l[2]=l[3]=-(1/0);for(var u=0;2>u;++u){var c=s[u].slice(0);0!==c.length&&(c.sort(a),l[u]=Math.min(l[u],c[0].x),l[u+2]=Math.max(l[u+2],c[c.length-1].x))}this.grid.update({bounds:l,ticks:s}),this.text.update({bounds:l,ticks:s,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.setDirty()},h.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(var t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},h.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},h.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},h.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},h.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":365,\"./lib/grid\":366,\"./lib/line\":367,\"./lib/text\":369,\"gl-select-static\":384}],372:[function(t,e,r){\"use strict\";e.exports={vertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 offset;\\nattribute vec4 color;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\n\\nvarying vec4 fragColor;\\n\\nvec4 computePosition_1_0(vec2 position, vec2 offset, mat3 view, vec2 scale) {\\n  vec3 xposition = view * vec3(position, 1.0);\\n  return vec4(\\n    xposition.xy + scale * offset * xposition.z,\\n    0,\\n    xposition.z);\\n}\\n\\n\\n\\n\\nvoid main() {\\n  fragColor = color;\\n\\n  gl_Position = computePosition_1_0(\\n    position,\\n    offset,\\n    viewTransform,\\n    pixelScale);\\n}\\n\",fragment:\"#define GLSLIFY 1\\nprecision lowp float;\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\",pickVertex:\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec2 offset;\\nattribute vec4 id;\\n\\nuniform mat3 viewTransform;\\nuniform vec2 pixelScale;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragColor;\\n\\nvec4 computePosition_1_0(vec2 position, vec2 offset, mat3 view, vec2 scale) {\\n  vec3 xposition = view * vec3(position, 1.0);\\n  return vec4(\\n    xposition.xy + scale * offset * xposition.z,\\n    0,\\n    xposition.z);\\n}\\n\\n\\n\\n\\nvoid main() {\\n  vec4 fragId = id + pickOffset;\\n\\n  fragId.y += floor(fragId.x / 256.0);\\n  fragId.x -= floor(fragId.x / 256.0) * 256.0;\\n\\n  fragId.z += floor(fragId.y / 256.0);\\n  fragId.y -= floor(fragId.y / 256.0) * 256.0;\\n\\n  fragId.w += floor(fragId.z / 256.0);\\n  fragId.z -= floor(fragId.z / 256.0) * 256.0;\\n\\n  fragColor = fragId / 255.0;\\n\\n  gl_Position = computePosition_1_0(\\n    position,\\n    offset,\\n    viewTransform,\\n    pixelScale);\\n}\\n\",pickFragment:\"#define GLSLIFY 1\\nprecision lowp float;\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\\n\"}},{}],373:[function(t,e,r){\"use strict\";function n(t){if(t in h)return h[t];var e=c(t,{polygons:!0,font:\"sans-serif\",textAlign:\"left\",textBaseline:\"alphabetic\"}),r=[],n=[];e.forEach(function(t){t.forEach(function(t){for(var e=0;e<t.length;++e){var i=t[(e+t.length-1)%t.length],a=t[e],o=t[(e+1)%t.length],s=t[(e+2)%t.length],l=a[0]-i[0],u=a[1]-i[1],c=Math.sqrt(l*l+u*u);l/=c,u/=c,r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(i[0],i[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(i[0],i[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(u,-l);var f=s[0]-o[0],h=s[1]-o[1],p=Math.sqrt(f*f+h*h);f/=p,h/=p,r.push(a[0],a[1]+1.4),n.push(u,-l),r.push(a[0],a[1]+1.4),n.push(-u,l),r.push(o[0],o[1]+1.4),n.push(-h,f),r.push(o[0],o[1]+1.4),n.push(-h,f),r.push(a[0],a[1]+1.4),n.push(h,-f),r.push(o[0],o[1]+1.4),n.push(h,-f)}})});for(var i=[1/0,1/0,-(1/0),-(1/0)],a=0;a<r.length;a+=2)for(var o=0;2>o;++o)i[o]=Math.min(i[o],r[a+o]),i[2+o]=Math.max(i[2+o],r[a+o]);return h[t]={coords:r,normals:n,bounds:i}}function i(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.offsetBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.numPoints=0,this.numVertices=0,this.pickOffset=0,this.points=null}function a(t,e){var r=t.gl,n=o(r,f.vertex,f.fragment),a=o(r,f.pickVertex,f.pickFragment),l=s(r),u=s(r),c=s(r),h=s(r),p=new i(t,n,a,l,u,c,h);return p.update(e),t.addObject(p),p}e.exports=a;var o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"text-cache\"),u=t(\"typedarray-pool\"),c=t(\"vectorize-text\"),f=t(\"./lib/shaders\"),h={},p=i.prototype;!function(){function t(){var t=this.plot,n=this.bounds,i=t.viewBox,a=t.dataBox,o=t.pixelRatio,s=n[2]-n[0],l=n[3]-n[1],u=a[2]-a[0],c=a[3]-a[1];e[0]=2*s/u,e[4]=2*l/c,e[6]=2*(n[0]-a[0])/u-1,e[7]=2*(n[1]-a[1])/c-1;var f=i[2]-i[0],h=i[3]-i[1];r[0]=2*o/f,r[1]=2*o/h}var e=[1,0,0,0,1,0,0,0,1],r=[1,1];p.draw=function(){var n=this.plot,i=this.shader,a=this.numVertices,o=n.gl;t.call(this),i.bind(),i.uniforms.pixelScale=r,i.uniforms.viewTransform=e,this.positionBuffer.bind(),i.attributes.position.pointer(),this.offsetBuffer.bind(),i.attributes.offset.pointer(),this.colorBuffer.bind(),i.attributes.color.pointer(o.UNSIGNED_BYTE,!0),o.drawArrays(o.TRIANGLES,0,a)};var n=[0,0,0,0];p.drawPick=function(i){var a=this.plot,o=this.pickShader,s=this.numVertices,l=a.gl;this.pickOffset=i;for(var u=0;4>u;++u)n[u]=i>>8*u&255;return t.call(this),o.bind(),o.uniforms.pixelScale=r,o.uniforms.viewTransform=e,o.uniforms.pickOffset=n,this.positionBuffer.bind(),o.attributes.position.pointer(),this.offsetBuffer.bind(),o.attributes.offset.pointer(),this.idBuffer.bind(),o.attributes.id.pointer(l.UNSIGNED_BYTE,!1),l.drawArrays(l.TRIANGLES,0,s),i+this.numPoints}}(),p.pick=function(t,e,r){var n=this.pickOffset,i=this.numPoints;if(n>r||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}},p.update=function(t){t=t||{};var e=t.positions||[],r=t.colors||[],i=t.glyphs||[],a=t.sizes||[],o=t.borderWidths||[],s=t.borderColors||[];this.points=e;for(var c=this.bounds=[1/0,1/0,-(1/0),-(1/0)],f=0,h=0;h<i.length;++h){f+=l(\"sans-serif\",i[h]).data.length+n(i[h]).coords.length>>1;for(var p=0;2>p;++p)c[p]=Math.min(c[p],e[2*h+p]),c[2+p]=Math.max(c[2+p],e[2*h+p])}c[0]===c[2]&&(c[2]+=1),c[3]===c[1]&&(c[3]+=1);for(var d=1/(c[2]-c[0]),g=1/(c[3]-c[1]),v=c[0],m=c[1],y=u.mallocFloat32(2*f),b=u.mallocFloat32(2*f),x=u.mallocUint8(4*f),_=u.mallocUint32(f),w=0,h=0;h<i.length;++h){for(var k=l(\"sans-serif\",i[h]),A=n(i[h]),M=d*(e[2*h]-v),T=g*(e[2*h+1]-m),E=a[h],L=255*r[4*h],S=255*r[4*h+1],C=255*r[4*h+2],P=255*r[4*h+3],z=.5*(A.bounds[0]+A.bounds[2]),R=.5*(A.bounds[1]+A.bounds[3]),p=0;p<k.data.length;p+=2)y[2*w]=M,y[2*w+1]=T,b[2*w]=-E*(k.data[p]-z),b[2*w+1]=-E*(k.data[p+1]-R),x[4*w]=L,x[4*w+1]=S,x[4*w+2]=C,x[4*w+3]=P,_[w]=h,w+=1;var O=o[h];L=255*s[4*h],S=255*s[4*h+1],C=255*s[4*h+2],P=255*s[4*h+3];for(var p=0;p<A.coords.length;p+=2)y[2*w]=M,y[2*w+1]=T,b[2*w]=-(E*(A.coords[p]-z)+O*A.normals[p]),b[2*w+1]=-(E*(A.coords[p+1]-R)+O*A.normals[p+1]),x[4*w]=L,x[4*w+1]=S,x[4*w+2]=C,x[4*w+3]=P,_[w]=h,w+=1}this.numPoints=i.length,this.numVertices=f,this.positionBuffer.update(y),this.offsetBuffer.update(b),this.colorBuffer.update(x),this.idBuffer.update(_),u.free(y),u.free(b),u.free(x),u.free(_)},p.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.offsetBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":372,\"gl-buffer\":325,\"gl-shader\":385,\"text-cache\":458,\"typedarray-pool\":463,\"vectorize-text\":465}],374:[function(t,e,r){r.pointVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute float weight;\\n\\nuniform mat3 matrix;\\nuniform float pointSize, useWeight;\\n\\nvarying float fragWeight;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n  fragWeight = mix(1.0, weight, useWeight);\\n}\\n\",r.pointFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\n\\nvarying float fragWeight;\\n\\nfloat smoothStep(float x, float y) {\\n  return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  vec4 baseColor = mix(borderColor, color, smoothStep(radius, centerFraction));\\n  float alpha = 1.0 - pow(1.0 - baseColor.a, fragWeight);\\n  gl_FragColor = vec4(baseColor.rgb * alpha, alpha);\\n}\\n\",r.pickVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\",r.pickFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0*gl_PointCoord.xy-1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"},{}],375:[function(t,e,r){arguments[4][87][0].apply(r,arguments)},{dup:87}],376:[function(t,e,r){\"use strict\";function n(t,e,r,n,a){4*h>=a?i(0,a-1,t,e,r,n):f(0,a-1,t,e,r,n)}function i(t,e,r,n,i,a){for(var o=t+1;e>=o;++o){for(var s=r[o],l=n[2*o],u=n[2*o+1],c=i[o],f=a[o],h=o;h>t;){var p=r[h-1],d=n[2*(h-1)];if((p-s||l-d)>=0)break;r[h]=p,n[2*h]=d,n[2*h+1]=n[2*h-1],i[h]=i[h-1],a[h]=a[h-1],h-=1}r[h]=s,n[2*h]=l,n[2*h+1]=u,i[h]=c,a[h]=f}}function a(t,e,r,n,i,a){var o=r[t],s=n[2*t],l=n[2*t+1],u=i[t],c=a[t];r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e],r[e]=o,n[2*e]=s,n[2*e+1]=l,i[e]=u,a[e]=c}function o(t,e,r,n,i,a){r[t]=r[e],n[2*t]=n[2*e],n[2*t+1]=n[2*e+1],i[t]=i[e],a[t]=a[e]}function s(t,e,r,n,i,a,o){var s=n[t],l=i[2*t],u=i[2*t+1],c=a[t],f=o[t];n[t]=n[e],i[2*t]=i[2*e],i[2*t+1]=i[2*e+1],a[t]=a[e],o[t]=o[e],n[e]=n[r],i[2*e]=i[2*r],i[2*e+1]=i[2*r+1],a[e]=a[r],o[e]=o[r],n[r]=s,i[2*r]=l,i[2*r+1]=u,a[r]=c,o[r]=f}function l(t,e,r,n,i,a,o,s,l,u,c){s[t]=s[e],l[2*t]=l[2*e],l[2*t+1]=l[2*e+1],u[t]=u[e],c[t]=c[e],s[e]=r,l[2*e]=n,l[2*e+1]=i,u[e]=a,c[e]=o}function u(t,e,r,n,i){return(r[t]-r[e]||n[2*e]-n[2*t]||i[t]-i[e])<0}function c(t,e,r,n,i,a,o,s){return(e-a[t]||o[2*t]-r||i-s[t])<0}function f(t,e,r,n,p,d){var g=(e-t+1)/6|0,v=t+g,m=e-g,y=t+e>>1,b=y-g,x=y+g,_=v,w=b,k=y,A=x,M=m,T=t+1,E=e-1,L=0;u(_,w,r,n,p,d)&&(L=_,_=w,w=L),u(A,M,r,n,p,d)&&(L=A,A=M,M=L),u(_,k,r,n,p,d)&&(L=_,_=k,k=L),u(w,k,r,n,p,d)&&(L=w,w=k,k=L),u(_,A,r,n,p,d)&&(L=_,_=A,A=L),u(k,A,r,n,p,d)&&(L=k,k=A,A=L),u(w,M,r,n,p,d)&&(L=w,w=M,M=L),u(w,k,r,n,p,d)&&(L=w,w=k,k=L),u(A,M,r,n,p,d)&&(L=A,A=M,M=L);var S=r[w],C=n[2*w],P=n[2*w+1],z=p[w],R=d[w],O=r[A],I=n[2*A],j=n[2*A+1],N=p[A],F=d[A],D=_,B=k,U=M,V=v,q=y,H=m,G=r[D],Y=r[B],X=r[U];r[V]=G,r[q]=Y,r[H]=X;for(var W=0;2>W;++W){var Z=n[2*D+W],$=n[2*B+W],K=n[2*U+W];n[2*V+W]=Z,n[2*q+W]=$,n[2*H+W]=K}var Q=p[D],J=p[B],tt=p[U];p[V]=Q,p[q]=J,p[H]=tt;var et=d[D],rt=d[B],nt=d[U];d[V]=et,d[q]=rt,d[H]=nt,o(b,t,r,n,p,d),o(x,e,r,n,p,d);for(var it=T;E>=it;++it)if(c(it,S,C,P,z,r,n,p))it!==T&&a(it,T,r,n,p,d),++T;else if(!c(it,O,I,j,N,r,n,p))for(;;){if(c(E,O,I,j,N,r,n,p)){c(E,S,C,P,z,r,n,p)?(s(it,T,E,r,n,p,d),++T,--E):(a(it,E,r,n,p,d),--E);break}if(--E<it)break}l(t,T-1,S,C,P,z,R,r,n,p,d),l(e,E+1,O,I,j,N,F,r,n,p,d),h>=T-2-t?i(t,T-2,r,n,p,d):f(t,T-2,r,n,p,d),h>=e-(E+2)?i(E+2,e,r,n,p,d):f(E+2,e,r,n,p,d),h>=E-T?i(T,E,r,n,p,d):f(T,E,r,n,p,d)}e.exports=n;var h=32},{}],377:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a,o,s){for(var l=r,u=r;n>u;++u){var c=t[2*u],f=t[2*u+1],h=e[u];c>=i&&o>=c&&f>=a&&s>=f&&(u===l?l+=1:(t[2*u]=t[2*l],t[2*u+1]=t[2*l+1],e[u]=e[l],t[2*l]=c,t[2*l+1]=f,e[l]=h,l+=1))}return l}function i(t,e,r){this.pixelSize=t,this.offset=e,this.count=r}function a(t,e,r,a){function l(i,a,o,s,u,c){var f=.5*o,h=s+1,p=u-s;r[_]=p,x[_++]=c;for(var d=0;2>d;++d)for(var g=0;2>g;++g){var v=i+d*f,m=a+g*f,y=n(t,e,h,u,v,m,v+f,m+f);if(y!==h){if(y-h>=Math.max(.9*p,32)){var b=u+s>>>1;l(v,m,f,h,b,c+1),h=b}l(v,m,f,h,y,c+1),h=y}}}var u=t.length>>>1;if(1>u)return[];for(var c=1/0,f=1/0,h=-(1/0),p=-(1/0),d=0;u>d;++d){var g=t[2*d],v=t[2*d+1];c=Math.min(c,g),h=Math.max(h,g),f=Math.min(f,v),p=Math.max(p,v),e[d]=d}c===h&&(h+=1+Math.abs(h)),f===p&&(p+=1+Math.abs(h));var m=1/(h-c),y=1/(p-f),b=Math.max(h-c,p-f);a=a||[0,0,0,0],a[0]=c,a[1]=f,a[2]=h,a[3]=p;var x=o.mallocInt32(u),_=0;l(c,f,b,0,u,0),s(x,t,e,r,u);for(var w=[],k=0,A=u,_=u-1;_>=0;--_){t[2*_]=(t[2*_]-c)*m,t[2*_+1]=(t[2*_+1]-f)*y;var M=x[_];M!==k&&(w.push(new i(b*Math.pow(.5,M),_+1,A-(_+1))),A=_+1,k=M)}return w.push(new i(b*Math.pow(.5,M+1),0,A)),o.free(x),w}var o=t(\"typedarray-pool\"),s=t(\"./lib/sort\");e.exports=a},{\"./lib/sort\":376,\"typedarray-pool\":463}],378:[function(t,e,r){\"use strict\";function n(t,e,r,n,i,a){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.weightBuffer=n,this.shader=i,this.pickShader=a,this.scales=[],this.size=12,this.borderSize=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.pickOffset=0,this.points=null,this.xCoords=null}function i(t,e){var r=t.gl,i=o(r),s=o(r),l=o(r),u=a(r,c.pointVertex,c.pointFragment),f=a(r,c.pickVertex,c.pickFragment),h=new n(t,i,s,l,u,f);return h.update(e),t.addObject(h),h}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"binary-search-bounds\"),l=t(\"snap-points-2d\"),u=t(\"typedarray-pool\"),c=t(\"./lib/shader\");e.exports=i;var f=n.prototype;f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.xCoords&&u.free(this.xCoords),this.plot.removeObject(this)},f.update=function(t){function e(e,r){return e in t?t[e]:r}t=t||{},this.size=e(\"size\",12),this.color=e(\"color\",[1,0,0,1]).slice(),this.borderSize=e(\"borderSize\",1),this.borderColor=e(\"borderColor\",[0,0,0,1]).slice(),this.xCoords&&u.free(this.xCoords);var r=t.positions,n=u.mallocFloat32(r.length),i=u.mallocInt32(r.length>>>1);n.set(r);var a=u.mallocFloat32(r.length);this.points=r,this.scales=l(n,i,a,this.bounds),this.offsetBuffer.update(n),this.pickBuffer.update(i),this.weightBuffer.update(a);for(var o=u.mallocFloat32(r.length>>>1),s=0,c=0;s<r.length;s+=2,++c)o[c]=n[s];u.free(i),u.free(n),u.free(a),this.xCoords=o,this.pointCount=r.length>>>1,this.pickOffset=0},f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.scales,o=this.offsetBuffer,l=this.pickBuffer,u=this.bounds,c=this.size,f=this.borderSize,h=n.gl,p=n.pickPixelRatio,d=n.viewBox,g=n.dataBox;if(0===this.pointCount)return r;var v=u[2]-u[0],m=u[3]-u[1],y=g[2]-g[0],b=g[3]-g[1],x=(d[2]-d[0])*p/n.pixelRatio,_=(d[3]-d[1])*p/n.pixelRatio,w=Math.min(y/x,b/_);t[0]=2*v/y,t[4]=2*m/b,t[6]=2*(u[0]-g[0])/y-1,t[7]=2*(u[1]-g[1])/b-1,this.pickOffset=r,e[0]=255&r,e[1]=r>>8&255,e[2]=r>>16&255,e[3]=r>>24&255,i.bind(),i.uniforms.matrix=t,i.uniforms.color=this.color,i.uniforms.borderColor=this.borderColor,i.uniforms.pointSize=p*(c+f),i.uniforms.pickOffset=e,0===this.borderSize?i.uniforms.centerFraction=2:i.uniforms.centerFraction=c/(c+f+1.25),o.bind(),i.attributes.position.pointer(),l.bind(),i.attributes.pickId.pointer(h.UNSIGNED_BYTE);for(var k=this.xCoords,A=(g[0]-u[0]-w*c*p)/v,M=(g[2]-u[0]+w*c*p)/v,T=a.length-1;T>=0;--T){var E=a[T];if(!(E.pixelSize<w&&T>1)){var L=E.offset,S=E.count+L,C=s.ge(k,A,L,S-1),P=s.lt(k,M,C,S-1)+1;h.drawArrays(h.POINTS,C,P-C)}}return r+this.pointCount}}(),f.draw=function(){var t=[1,0,0,0,1,0,0,0,1];return function(){var e=this.plot,r=this.shader,n=this.scales,i=this.offsetBuffer,a=this.bounds,o=this.size,l=this.borderSize,u=e.gl,c=e.pixelRatio,f=e.viewBox,h=e.dataBox;if(0!==this.pointCount){var p=a[2]-a[0],d=a[3]-a[1],g=h[2]-h[0],v=h[3]-h[1],m=f[2]-f[0],y=f[3]-f[1],b=Math.min(g/m,v/y);t[0]=2*p/g,t[4]=2*d/v,t[6]=2*(a[0]-h[0])/g-1,t[7]=2*(a[1]-h[1])/v-1,r.bind(),r.uniforms.matrix=t,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointSize=c*(o+l),r.uniforms.useWeight=1,0===this.borderSize?r.uniforms.centerFraction=2:r.uniforms.centerFraction=o/(o+l+1.25),i.bind(),r.attributes.position.pointer(),this.weightBuffer.bind(),r.attributes.weight.pointer();for(var x=this.xCoords,_=(h[0]-a[0]-b*o*c)/p,w=(h[2]-a[0]+b*o*c)/p,k=!0,A=n.length-1;A>=0;--A){var M=n[A];if(!(M.pixelSize<b&&A>1)){var T=M.offset,E=M.count+T,L=s.ge(x,_,T,E-1),S=s.lt(x,w,L,E-1)+1;u.drawArrays(u.POINTS,L,S-L),k&&(k=!1,r.uniforms.useWeight=0)}}}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(n>r||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":374,\"binary-search-bounds\":375,\"gl-buffer\":325,\"gl-shader\":385,\"snap-points-2d\":377,\"typedarray-pool\":463}],379:[function(t,e,r){\"use strict\";function n(t,e){var r=a[e];if(r||(r=a[e]={}),t in r)return r[t];for(var n=i(t,{textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),o=i(t,{triangles:!0,textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e}),s=[[1/0,1/0],[-(1/0),-(1/0)]],l=0;l<n.positions.length;++l)for(var u=n.positions[l],c=0;2>c;++c)s[0][c]=Math.min(s[0][c],u[c]),s[1][c]=Math.max(s[1][c],u[c]);return r[t]=[o,n,s]}var i=t(\"vectorize-text\");e.exports=n;var a={}},{\"vectorize-text\":465}],380:[function(t,e,r){function n(t,e){var r=i(t,e),n=r.attributes;return n.position.location=0,n.color.location=1,n.glyph.location=2,n.id.location=3,r}var i=t(\"gl-shader\"),a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   || \\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n    \\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0])) || any(greaterThan(position, clipBounds[1]))) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n    \\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(position, clipBounds[0]))   ||\\n     any(greaterThan(position, clipBounds[1])) ) {\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\",l=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   ||\\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = interpColor * opacity;\\n  }\\n}\\n\",u=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if(any(lessThan(dataCoordinate, fragClipBounds[0]))   || \\n     any(greaterThan(dataCoordinate, fragClipBounds[1])) ) {\\n    discard;\\n  } else {\\n    gl_FragColor = vec4(pickGroup, pickId.bgr);\\n  }\\n}\",c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},g={vertex:o,fragment:u,attributes:c},v={vertex:s,fragment:u,attributes:c};r.createPerspective=function(t){return n(t,f)},r.createOrtho=function(t){return n(t,h)},r.createProject=function(t){return n(t,p)},r.createPickPerspective=function(t){return n(t,d)},r.createPickOrtho=function(t){return n(t,g)},r.createPickProject=function(t){return n(t,v)}},{\"gl-shader\":385}],381:[function(t,e,r){\"use strict\";function n(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function i(t,e,r,i){return n(i,i,r),n(i,i,e),n(i,i,t)}function a(t,e){this.index=t,this.dataCoordinate=this.position=e}function o(t,e,r,n,i,o,s,l,u,c,f,h){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=o,this.glyphBuffer=s,this.idBuffer=l,this.vao=u,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=f,this.pickProjectShader=h,this.points=[],this._selectResult=new a(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.dirty=!0}function s(t){return t[0]=t[1]=t[2]=0,t}function l(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function u(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function c(t){for(var e=S,r=0;2>r;++r)for(var n=0;3>n;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}function f(t,e,r,n,a){var o,f=e.axesProject,h=e.gl,p=t.uniforms,d=r.model||x,g=r.view||x,v=r.projection||x,y=e.axesBounds,b=c(e.clipBounds);o=e.axes?e.axes.lastCubeProps.axis:[1,1,1],w[0]=2/h.drawingBufferWidth,w[1]=2/h.drawingBufferHeight,t.bind(),p.view=g,p.projection=v,p.screenSize=w,p.highlightId=e.highlightId,p.highlightScale=e.highlightScale,p.clipBounds=b,p.pickGroup=e.pickId/255,p.pixelRatio=e.pixelRatio;for(var _=0;3>_;++_)if(f[_]&&e.projectOpacity[_]<1===n){p.scale=e.projectScale[_],p.opacity=e.projectOpacity[_];for(var S=E,C=0;16>C;++C)S[C]=0;for(var C=0;4>C;++C)S[5*C]=1;S[5*_]=0,o[_]<0?S[12+_]=y[0][_]:S[12+_]=y[1][_],m(S,d,S),p.model=S;var P=(_+1)%3,z=(_+2)%3,R=s(k),O=s(A);R[P]=1,O[z]=1;var I=i(v,g,d,l(M,R)),j=i(v,g,d,l(T,O));if(Math.abs(I[1])>Math.abs(j[1])){var N=I;I=j,j=N,N=R,R=O,O=N;var F=P;P=z,z=F}I[0]<0&&(R[P]=-1),j[1]>0&&(O[z]=-1);for(var D=0,B=0,C=0;4>C;++C)D+=Math.pow(d[4*P+C],2),B+=Math.pow(d[4*z+C],2);R[P]/=Math.sqrt(D),O[z]/=Math.sqrt(B),p.axes[0]=R,p.axes[1]=O,p.fragClipBounds[0]=u(L,b[0],_,-1e8),p.fragClipBounds[1]=u(L,b[1],_,1e8),e.vao.draw(h.TRIANGLES,e.vertexCount),e.lineWidth>0&&(h.lineWidth(e.lineWidth),e.vao.draw(h.LINES,e.lineVertexCount,e.vertexCount))}}function h(t,e,r,n,i,a){var o=r.gl;if(r.vao.bind(),i===r.opacity<1||a){t.bind();var s=t.uniforms;s.model=n.model||x,s.view=n.view||x,s.projection=n.projection||x,w[0]=2/o.drawingBufferWidth,w[1]=2/o.drawingBufferHeight,s.screenSize=w,s.highlightId=r.highlightId,s.highlightScale=r.highlightScale,s.fragClipBounds=z,s.clipBounds=r.axes.bounds,s.opacity=r.opacity,s.pickGroup=r.pickId/255,s.pixelRatio=r.pixelRatio,r.vao.draw(o.TRIANGLES,r.vertexCount),r.lineWidth>0&&(o.lineWidth(r.lineWidth),r.vao.draw(o.LINES,r.lineVertexCount,r.vertexCount))}f(e,r,n,i,a),r.vao.unbind()}function p(t){var e=t.gl,r=y.createPerspective(e),n=y.createOrtho(e),i=y.createProject(e),a=y.createPickPerspective(e),s=y.createPickOrtho(e),l=y.createPickProject(e),u=d(e),c=d(e),f=d(e),h=d(e),p=g(e,[{buffer:u,size:3,type:e.FLOAT},{buffer:c,size:4,type:e.FLOAT},{buffer:f,size:2,type:e.FLOAT},{buffer:h,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new o(e,r,n,i,u,c,f,h,p,a,s,l);return v.update(t),v}var d=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"typedarray-pool\"),m=t(\"gl-mat4/multiply\"),y=t(\"./lib/shaders\"),b=t(\"./lib/glyphs\"),x=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];e.exports=p;var _=o.prototype;_.pickSlots=1,_.setPickBase=function(t){this.pickId=t},_.isTransparent=function(){if(this.opacity<1)return!0;for(var t=0;3>t;++t)if(this.axesProject[t]&&this.projectOpacity[t]<1)return!0;return!1},_.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;3>t;++t)if(this.axesProject[t]&&this.projectOpacity[t]>=1)return!0;return!1};var w=[0,0],k=[0,0,0],A=[0,0,0],M=[0,0,0,1],T=[0,0,0,1],E=x.slice(),L=[0,0,0],S=[[0,0,0],[0,0,0]],C=[-1e8,-1e8,-1e8],P=[1e8,1e8,1e8],z=[C,P];_.draw=function(t){var e=this.useOrtho?this.orthoShader:this.shader;h(e,this.projectShader,this,t,!1,!1)},_.drawTransparent=function(t){var e=this.useOrtho?this.orthoShader:this.shader;h(e,this.projectShader,this,t,!0,!1)},_.drawPick=function(t){var e=this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader;h(e,this.pickProjectShader,this,t,!1,!0)},_.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||0>e)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;3>i;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},_.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},_.update=function(t){if(t=t||{},\"perspective\"in t&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(\"projectOpacity\"in t)if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{var r=+t.projectOpacity;this.projectOpacity=[r,r,r]}\"opacity\"in t&&(this.opacity=t.opacity),this.dirty=!0;var n=t.position;if(n){var i=t.font||\"normal\",a=t.alignment||[0,0],o=[1/0,1/0,1/0],s=[-(1/0),-(1/0),-(1/0)],l=t.glyph,u=t.color,c=t.size,f=t.angle,h=t.lineColor,p=0,d=0,g=0,m=n.length;t:for(var y=0;m>y;++y){for(var x=n[y],_=0;3>_;++_)if(isNaN(x[_])||!isFinite(x[_]))continue t;var w;w=Array.isArray(l)?b(l[y],i):l?b(l,i):b(\"\\u25cf\",i);var k=w[0],A=w[1],M=w[2];d+=3*k.cells.length,g+=2*A.edges.length}var T=d+g,E=v.mallocFloat(3*T),L=v.mallocFloat(4*T),S=v.mallocFloat(2*T),C=v.mallocUint32(T),P=[0,a[1]],z=0,R=d,O=[0,0,0,1],I=[0,0,0,1],j=Array.isArray(u)&&Array.isArray(u[0]),N=Array.isArray(h)&&Array.isArray(h[0]);t:for(var y=0;m>y;++y){for(var x=n[y],_=0;3>_;++_){if(isNaN(x[_])||!isFinite(x[_])){p+=1;continue t}s[_]=Math.max(s[_],x[_]),o[_]=Math.min(o[_],x[_])}var w;w=Array.isArray(l)?b(l[y],i):l?b(l,i):b(\"\\u25cf\",i);var k=w[0],A=w[1],M=w[2];if(Array.isArray(u)){var F;if(F=j?u[y]:u,3===F.length){for(var _=0;3>_;++_)O[_]=F[_];O[3]=1}else if(4===F.length)for(var _=0;4>_;++_)O[_]=F[_];\n",
+       "}else O[0]=O[1]=O[2]=0,O[3]=1;if(Array.isArray(h)){var F;if(F=N?h[y]:h,3===F.length){for(var _=0;3>_;++_)I[_]=F[_];I[_]=1}else if(4===F.length)for(var _=0;4>_;++_)I[_]=F[_]}else I[0]=I[1]=I[2]=0,I[3]=1;var D=.5;Array.isArray(c)?D=+c[y]:c?D=+c:this.useOrtho&&(D=12);var B=0;Array.isArray(f)?B=+f[y]:f&&(B=+f);for(var U=Math.cos(B),V=Math.sin(B),x=n[y],_=0;3>_;++_)s[_]=Math.max(s[_],x[_]),o[_]=Math.min(o[_],x[_]);a[0]<0?P[0]=a[0]*(1+M[1][0]):a[0]>0&&(P[0]=-a[0]*(1+M[0][0]));for(var q=k.cells,H=k.positions,_=0;_<q.length;++_)for(var G=q[_],Y=0;3>Y;++Y){for(var X=0;3>X;++X)E[3*z+X]=x[X];for(var X=0;4>X;++X)L[4*z+X]=O[X];C[z]=p;var W=H[G[Y]];S[2*z]=D*(U*W[0]-V*W[1]+P[0]),S[2*z+1]=D*(V*W[0]+U*W[1]+P[1]),z+=1}for(var q=A.edges,H=A.positions,_=0;_<q.length;++_)for(var G=q[_],Y=0;2>Y;++Y){for(var X=0;3>X;++X)E[3*R+X]=x[X];for(var X=0;4>X;++X)L[4*R+X]=I[X];C[R]=p;var W=H[G[Y]];S[2*R]=D*(U*W[0]-V*W[1]+P[0]),S[2*R+1]=D*(V*W[0]+U*W[1]+P[1]),R+=1}p+=1}this.vertexCount=d,this.lineVertexCount=g,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(S),this.idBuffer.update(new Uint32Array(C)),v.free(E),v.free(L),v.free(S),v.free(C),this.bounds=[o,s],this.points=n,this.pointCount=n.length}},_.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/glyphs\":379,\"./lib/shaders\":380,\"gl-buffer\":325,\"gl-mat4/multiply\":346,\"gl-vao\":420,\"typedarray-pool\":463}],382:[function(t,e,r){\"use strict\";r.boxVertex=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\",r.boxFragment=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"},{}],383:[function(t,e,r){\"use strict\";function n(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-(1/0),-(1/0)],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}function i(t,e){var r=t.gl,i=o(r,[0,0,0,1,1,0,1,1]),l=a(r,s.boxVertex,s.boxFragment),u=new n(t,i,l);return u.update(e),t.addOverlay(u),u}var a=t(\"gl-shader\"),o=t(\"gl-buffer\"),s=t(\"./lib/shaders\");e.exports=i;var l=n.prototype;l.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,u=t.viewBox,c=t.pixelRatio,f=(e[0]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],h=(e[1]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1],p=(e[2]-l[0])*(u[2]-u[0])/(l[2]-l[0])+u[0],d=(e[3]-l[1])*(u[3]-u[1])/(l[3]-l[1])+u[1];if(f=Math.max(f,u[0]),h=Math.max(h,u[1]),p=Math.min(p,u[2]),d=Math.min(d,u[3]),!(f>p||h>d)){o.bind();var g=s[2]-s[0],v=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,g,v,i),o.drawBox(p,h,g,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var m=r*c;o.drawBox(f-m,h-m,p+m,h+m,a),o.drawBox(f-m,d-m,p+m,d+m,a),o.drawBox(f-m,h-m,f+m,d+m,a),o.drawBox(p-m,h-m,p+m,d+m,a)}}}},l.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},l.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":382,\"gl-buffer\":325,\"gl-shader\":385}],384:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function i(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}function a(t,e){var r=o(t,e),n=s.mallocUint8(e[0]*e[1]*4);return new i(t,r,n)}e.exports=a;var o=t(\"gl-fbo\"),s=t(\"typedarray-pool\"),l=t(\"ndarray\"),u=t(\"bit-twiddle\").nextPow2,c=t(\"cwise/lib/wrapper\")({args:[\"array\",{offset:[0,0,1],array:0},{offset:[0,0,2],array:0},{offset:[0,0,3],array:0},\"scalar\",\"scalar\",\"index\"],pre:{body:\"{this_closestD2=1e8,this_closestX=-1,this_closestY=-1}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},body:{body:\"{if(255>_inline_31_arg0_||255>_inline_31_arg1_||255>_inline_31_arg2_||255>_inline_31_arg3_){var _inline_31_l=_inline_31_arg4_-_inline_31_arg6_[0],_inline_31_a=_inline_31_arg5_-_inline_31_arg6_[1],_inline_31_f=_inline_31_l*_inline_31_l+_inline_31_a*_inline_31_a;_inline_31_f<this_closestD2&&(this_closestD2=_inline_31_f,this_closestX=_inline_31_arg6_[0],this_closestY=_inline_31_arg6_[1])}}\",args:[{name:\"_inline_31_arg0_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg2_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg3_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg4_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg5_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_31_arg6_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[\"_inline_31_a\",\"_inline_31_f\",\"_inline_31_l\"]},post:{body:\"{return[this_closestX,this_closestY,this_closestD2]}\",args:[],thisVars:[\"this_closestD2\",\"this_closestX\",\"this_closestY\"],localVars:[]},debug:!1,funcName:\"cwise\",blockSize:64}),f=i.prototype;Object.defineProperty(f,\"shape\",{get:function(){return this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){s.free(this.buffer);for(var n=this.buffer=s.mallocUint8(u(r*e*4)),i=0;r*e*4>i;++i)n[i]=255}return t}}}),f.begin=function(){var t=this.gl;this.shape;t&&(this.fbo.bind(),t.clearColor(1,1,1,1),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT))},f.end=function(){var t=this.gl;t&&(t.bindFramebuffer(t.FRAMEBUFFER,null),this._readTimeout||clearTimeout(this._readTimeout),this._readTimeout=setTimeout(this._readCallback,1))},f.query=function(t,e,r){if(!this.gl)return null;var i=this.fbo.shape.slice();t=0|t,e=0|e,\"number\"!=typeof r&&(r=1);var a=0|Math.min(Math.max(t-r,0),i[0]),o=0|Math.min(Math.max(t+r,0),i[0]),s=0|Math.min(Math.max(e-r,0),i[1]),u=0|Math.min(Math.max(e+r,0),i[1]);if(a>=o||s>=u)return null;var f=[o-a,u-s],h=l(this.buffer,[f[0],f[1],4],[4,4*i[0],1],4*(a+i[0]*s)),p=c(h.hi(f[0],f[1],1),r,r),d=p[0],g=p[1];if(0>d||Math.pow(this.radius,2)<p[2])return null;var v=h.get(d,g,0),m=h.get(d,g,1),y=h.get(d,g,2),b=h.get(d,g,3);return new n(d+a|0,g+s|0,v,[m,y,b],Math.sqrt(p[2]))},f.dispose=function(){this.gl&&(this.fbo.dispose(),s.free(this.buffer),this.gl=null,this._readTimeout&&clearTimeout(this._readTimeout))}},{\"bit-twiddle\":299,\"cwise/lib/wrapper\":319,\"gl-fbo\":330,ndarray:438,\"typedarray-pool\":463}],385:[function(t,e,r){arguments[4][206][0].apply(r,arguments)},{\"./lib/GLError\":386,\"./lib/create-attributes\":387,\"./lib/create-uniforms\":388,\"./lib/reflect\":389,\"./lib/runtime-reflect\":390,\"./lib/shader-cache\":391,dup:206}],386:[function(t,e,r){arguments[4][207][0].apply(r,arguments)},{dup:207}],387:[function(t,e,r){arguments[4][208][0].apply(r,arguments)},{\"./GLError\":386,dup:208}],388:[function(t,e,r){arguments[4][209][0].apply(r,arguments)},{\"./GLError\":386,\"./reflect\":389,dup:209}],389:[function(t,e,r){arguments[4][210][0].apply(r,arguments)},{dup:210}],390:[function(t,e,r){arguments[4][211][0].apply(r,arguments)},{dup:211}],391:[function(t,e,r){arguments[4][212][0].apply(r,arguments)},{\"./GLError\":386,dup:212,\"gl-format-compiler-error\":392,\"weakmap-shim\":408}],392:[function(t,e,r){arguments[4][213][0].apply(r,arguments)},{\"add-line-numbers\":393,dup:213,\"gl-constants/lookup\":397,\"glsl-shader-name\":398,\"sprintf-js\":405}],393:[function(t,e,r){arguments[4][214][0].apply(r,arguments)},{dup:214,\"pad-left\":394}],394:[function(t,e,r){arguments[4][215][0].apply(r,arguments)},{dup:215,\"repeat-string\":395}],395:[function(t,e,r){arguments[4][216][0].apply(r,arguments)},{dup:216}],396:[function(t,e,r){arguments[4][217][0].apply(r,arguments)},{dup:217}],397:[function(t,e,r){arguments[4][218][0].apply(r,arguments)},{\"./1.0/numbers\":396,dup:218}],398:[function(t,e,r){arguments[4][219][0].apply(r,arguments)},{\"atob-lite\":399,dup:219,\"glsl-tokenizer\":404}],399:[function(t,e,r){arguments[4][220][0].apply(r,arguments)},{dup:220}],400:[function(t,e,r){arguments[4][221][0].apply(r,arguments)},{\"./lib/builtins\":401,\"./lib/literals\":402,\"./lib/operators\":403,dup:221}],401:[function(t,e,r){arguments[4][222][0].apply(r,arguments)},{dup:222}],402:[function(t,e,r){arguments[4][223][0].apply(r,arguments)},{dup:223}],403:[function(t,e,r){arguments[4][224][0].apply(r,arguments)},{dup:224}],404:[function(t,e,r){arguments[4][225][0].apply(r,arguments)},{\"./index\":400,dup:225}],405:[function(t,e,r){arguments[4][226][0].apply(r,arguments)},{dup:226}],406:[function(t,e,r){arguments[4][227][0].apply(r,arguments)},{\"./hidden-store.js\":407,dup:227}],407:[function(t,e,r){arguments[4][228][0].apply(r,arguments)},{dup:228}],408:[function(t,e,r){arguments[4][229][0].apply(r,arguments)},{\"./create-store.js\":406,dup:229}],409:[function(t,e,r){\"use strict\";function n(t){this.plot=t,this.enable=[!0,!0,!1,!1],this.width=[1,1,1,1],this.color=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.center=[1/0,1/0]}function i(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r}e.exports=i;var a=n.prototype;a.update=function(t){t=t||{},this.enable=(t.enable||[!0,!0,!1,!1]).slice(),this.width=(t.width||[1,1,1,1]).slice(),this.color=(t.color||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]).map(function(t){return t.slice()}),this.center=(t.center||[1/0,1/0]).slice(),this.plot.setOverlayDirty()},a.draw=function(){var t=this.enable,e=this.width,r=this.color,n=this.center,i=this.plot,a=i.line,o=i.dataBox,s=i.viewBox;if(a.bind(),o[0]<=n[0]&&n[0]<=o[2]&&o[1]<=n[1]&&n[1]<=o[3]){var l=s[0]+(n[0]-o[0])/(o[2]-o[0])*(s[2]-s[0]),u=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&a.drawLine(l,u,s[0],u,e[0],r[0]),t[1]&&a.drawLine(l,u,l,s[1],e[1],r[1]),t[2]&&a.drawLine(l,u,s[2],u,e[2],r[2]),t[3]&&a.drawLine(l,u,l,s[3],e[3],r[3])}},a.dispose=function(){this.plot.removeOverlay(this)}},{}],410:[function(t,e,r){var n=t(\"gl-shader\"),i=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec4 uv;\\nattribute vec2 f;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  worldCoordinate = vec3(uv.zw, f.x);\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  value = f.x;\\n  kill = f.y;\\n  planeCoordinate = uv.xy;\\n  \\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\",a=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nfloat beckmannDistribution_2_0(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\n\\n\\nfloat beckmannSpecular_1_1(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution_2_0(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\n\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  if(kill > 0.0 ||\\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = beckmannSpecular_1_1(L, V, N, roughness);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  float interpValue = (value - lowerBound.z) / (upperBound.z - lowerBound.z);\\n  vec4 surfaceColor = texture2D(colormap, vec2(interpValue, interpValue));\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\",o=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nattribute vec4 uv;\\n\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  vec4 worldPosition = model * vec4(dataCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z = clipPosition.z + zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = dataCoordinate.z;\\n  kill = -1.0;\\n  worldCoordinate = dataCoordinate;\\n  planeCoordinate = uv.zw;\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\",s=\"#define GLSLIFY 1\\nprecision mediump float;\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if(kill > 0.0 || \\n    any(lessThan(worldCoordinate, clipBounds[0])) || any(greaterThan(worldCoordinate, clipBounds[1]))) {\\n    discard;\\n  }\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\";r.createShader=function(t){var e=n(t,i,a,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec2\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,i,s,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec2\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,o,a,null,[{name:\"uv\",type:\"vec4\"}]);return e.attributes.uv.location=0,e},r.createPickContourShader=function(t){var e=n(t,o,s,null,[{name:\"uv\",type:\"vec4\"}]);return e.attributes.uv.location=0,e}},{\"gl-shader\":385}],411:[function(t,e,r){arguments[4][4][0].apply(r,arguments)},{dup:4}],412:[function(t,e,r){\"use strict\";function n(t){if(t in l)return l[t];for(var e=[],r=0;t>r;++r)e.push(\"out\",r,\"s=0.5*(inp\",r,\"l-inp\",r,\"r);\");for(var n=[\"array\"],i=[\"junk\"],r=0;t>r;++r){n.push(\"array\"),i.push(\"out\"+r+\"s\");var a=o(t);a[r]=-1,n.push({array:0,offset:a.slice()}),a[r]=1,n.push({array:0,offset:a.slice()}),i.push(\"inp\"+r+\"l\",\"inp\"+r+\"r\")}return l[t]=s({args:n,pre:c,post:c,body:{body:e.join(\"\"),args:i.map(function(t){return{name:t,lvalue:0===t.indexOf(\"out\"),rvalue:0===t.indexOf(\"inp\"),count:\"junk\"!==t|0}}),thisVars:[],localVars:[]},funcName:\"fdTemplate\"+t})}function i(t){function e(e){for(var r=a-e.length,n=[],i=[],s=[],l=0;a>l;++l)e.indexOf(l+1)>=0?s.push(\"0\"):e.indexOf(-(l+1))>=0?s.push(\"s[\"+l+\"]-1\"):(s.push(\"-1\"),n.push(\"1\"),i.push(\"s[\"+l+\"]-2\"));var u=\".lo(\"+n.join()+\").hi(\"+i.join()+\")\";if(0===n.length&&(u=\"\"),r>0){o.push(\"if(1\");for(var l=0;a>l;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||o.push(\"&&s[\",l,\"]>2\");o.push(\"){grad\",r,\"(src.pick(\",s.join(),\")\",u);for(var l=0;a>l;++l)e.indexOf(l+1)>=0||e.indexOf(-(l+1))>=0||o.push(\",dst.pick(\",s.join(),\",\",l,\")\",u);o.push(\");\")}for(var l=0;l<e.length;++l){var c=Math.abs(e[l])-1,f=\"dst.pick(\"+s.join()+\",\"+c+\")\"+u;switch(t[c]){case\"clamp\":var h=s.slice(),p=s.slice();e[l]<0?h[c]=\"s[\"+c+\"]-2\":p[c]=\"1\",0===r?o.push(\"if(s[\",c,\"]>1){dst.set(\",s.join(),\",\",c,\",0.5*(src.get(\",h.join(),\")-src.get(\",p.join(),\")))}else{dst.set(\",s.join(),\",\",c,\",0)};\"):o.push(\"if(s[\",c,\"]>1){diff(\",f,\",src.pick(\",h.join(),\")\",u,\",src.pick(\",p.join(),\")\",u,\");}else{zero(\",f,\");};\");break;case\"mirror\":0===r?o.push(\"dst.set(\",s.join(),\",\",c,\",0);\"):o.push(\"zero(\",f,\");\");break;case\"wrap\":var d=s.slice(),g=s.slice();e[l]<0?(d[c]=\"s[\"+c+\"]-2\",g[c]=\"0\"):(d[c]=\"s[\"+c+\"]-1\",g[c]=\"1\"),0===r?o.push(\"if(s[\",c,\"]>2){dst.set(\",s.join(),\",\",c,\",0.5*(src.get(\",d.join(),\")-src.get(\",g.join(),\")))}else{dst.set(\",s.join(),\",\",c,\",0)};\"):o.push(\"if(s[\",c,\"]>2){diff(\",f,\",src.pick(\",d.join(),\")\",u,\",src.pick(\",g.join(),\")\",u,\");}else{zero(\",f,\");};\");break;default:throw new Error(\"ndarray-gradient: Invalid boundary condition\")}}r>0&&o.push(\"};\")}var r=t.join(),i=u[r];if(i)return i;for(var a=t.length,o=[\"function gradient(dst,src){var s=src.shape.slice();\"],s=0;1<<a>s;++s){for(var c=[],p=0;a>p;++p)s&1<<p&&c.push(p+1);for(var d=0;d<1<<c.length;++d){for(var g=c.slice(),p=0;p<c.length;++p)d&1<<p&&(g[p]=-g[p]);e(g)}}o.push(\"return dst;};return gradient\");for(var v=[\"diff\",\"zero\"],m=[f,h],s=1;a>=s;++s)v.push(\"grad\"+s),m.push(n(s));v.push(o.join(\"\"));var y=Function.apply(void 0,v),i=y.apply(void 0,m);return l[r]=i,i}function a(t,e,r){if(Array.isArray(r)){if(r.length!==e.dimension)throw new Error(\"ndarray-gradient: invalid boundary conditions\")}else r=\"string\"==typeof r?o(e.dimension,r):o(e.dimension,\"clamp\");if(t.dimension!==e.dimension+1)throw new Error(\"ndarray-gradient: output dimension must be +1 input dimension\");if(t.shape[e.dimension]!==e.dimension)throw new Error(\"ndarray-gradient: output shape must match input shape\");for(var n=0;n<e.dimension;++n)if(t.shape[n]!==e.shape[n])throw new Error(\"ndarray-gradient: shape mismatch\");if(0===e.size)return t;if(e.dimension<=0)return t.set(0),t;var a=i(r);return a(t,e)}e.exports=a;var o=t(\"dup\"),s=t(\"cwise-compiler\"),l={},u={},c={body:\"\",args:[],thisVars:[],localVars:[]},f=s({args:[\"array\",\"array\",\"array\"],pre:c,post:c,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1},{name:\"left\",lvalue:!1,rvalue:!0,count:1},{name:\"right\",lvalue:!1,rvalue:!0,count:1}],body:\"out=0.5*(left-right)\",thisVars:[],localVars:[]},funcName:\"cdiff\"}),h=s({args:[\"array\"],pre:c,post:c,body:{args:[{name:\"out\",lvalue:!0,rvalue:!1,count:1}],body:\"out=0\",thisVars:[],localVars:[]},funcName:\"zero\"})},{\"cwise-compiler\":316,dup:322}],413:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"./doConvert.js\");e.exports=function(t,e){for(var r=[],a=t,o=1;a instanceof Array;)r.push(a.length),o*=a.length,a=a[0];return 0===r.length?n():(e||(e=n(new Float64Array(o),r)),i(e,t),e)}},{\"./doConvert.js\":414,ndarray:438}],414:[function(t,e,r){e.exports=t(\"cwise-compiler\")({args:[\"array\",\"scalar\",\"index\"],pre:{body:\"{}\",args:[],thisVars:[],localVars:[]},body:{body:\"{\\nvar _inline_1_v=_inline_1_arg1_,_inline_1_i\\nfor(_inline_1_i=0;_inline_1_i<_inline_1_arg2_.length-1;++_inline_1_i) {\\n_inline_1_v=_inline_1_v[_inline_1_arg2_[_inline_1_i]]\\n}\\n_inline_1_arg0_=_inline_1_v[_inline_1_arg2_[_inline_1_arg2_.length-1]]\\n}\",args:[{name:\"_inline_1_arg0_\",lvalue:!0,rvalue:!1,count:1},{name:\"_inline_1_arg1_\",lvalue:!1,rvalue:!0,count:1},{name:\"_inline_1_arg2_\",lvalue:!1,rvalue:!0,count:4}],thisVars:[],localVars:[\"_inline_1_i\",\"_inline_1_v\"]},post:{body:\"{}\",args:[],thisVars:[],localVars:[]},funcName:\"convert\",blockSize:64})},{\"cwise-compiler\":316}],415:[function(t,e,r){\"use strict\";function n(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}function i(t){var e=x([y({colormap:t,nshades:j,format:\"rgba\"}).map(function(t){return[t[0],t[1],t[2],255*t[3]]})]);return b.divseq(e,255),e}function a(t,e,r,i,a,o,s,l,u,c,f,h,p,d){this.gl=t,this.shape=e,this.bounds=r,this._shader=i,this._pickShader=a,this._coordinateBuffer=o,this._vao=s,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=f,this._contourVAO=h,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new n([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=p,this._dynamicVAO=d,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-(1/0),-(1/0),-(1/0)]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[_(m.mallocFloat(1024),[0,0]),_(m.mallocFloat(1024),[0,0]),_(m.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-(1/0),-(1/0),-(1/0)],[1/0,1/0,1/0]],this.snapToData=!1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.dirty=!0}function o(t,e){for(var r=e.axes&&e.axes.lastCubeProps.axis||F,n=e.showSurface,i=e.showContour,a=0;3>a;++a){n=n||e.surfaceProject[a];for(var o=0;3>o;++o)i=i||e.contourProject[a][o]}for(var a=0;3>a;++a){for(var s=D.projections[a],o=0;16>o;++o)s[o]=0;for(var o=0;4>o;++o)s[5*o]=1;s[5*a]=0,s[12+a]=e.axesBounds[+(r[a]>0)][a],k(s,t.model,s);for(var l=D.clipBounds[a],u=0;2>u;++u)for(var o=0;3>o;++o)l[u][o]=t.clipBounds[u][o];l[0][a]=-1e8,l[1][a]=1e8}return D.showSurface=n,D.showContour=i,D}function s(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=B;n.model=t.model||R,n.view=t.view||R,n.projection=t.projection||R,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.contourColor=this.contourColor[0],n.inverseModel=A(n.inverseModel,n.model);for(var i=0;2>i;++i)for(var a=n.clipBounds[i],s=0;3>s;++s)a[s]=Math.min(Math.max(this.clipBounds[i][s],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.shape=n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=V;var l=U;k(l,n.view,n.model),k(l,n.projection,l),A(l,l);for(var i=0;3>i;++i)n.eyePosition[i]=l[12+i]/l[15];for(var u=l[15],i=0;3>i;++i)u+=this.lightPosition[i]*l[4*i+3];for(var i=0;3>i;++i){for(var c=l[12+i],s=0;3>s;++s)c+=l[4*s+i]*this.lightPosition[s];n.lightPosition[i]=c/u}var f=o(n,this);if(f.showSurface&&e===this.opacity<1){this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vao.draw(r.TRIANGLES,this._vertexCount);for(var i=0;3>i;++i)this.surfaceProject[i]&&(this._shader.uniforms.model=f.projections[i],this._shader.uniforms.clipBounds=f.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(f.showContour&&!e){var h=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,h.bind(),h.uniforms=n;var p=this._contourVAO;p.bind();for(var i=0;3>i;++i){h.uniforms.permutation=I[i],r.lineWidth(this.contourWidth[i]);for(var s=0;s<this.contourLevels[i].length;++s)s===this.highlightLevel[i]?(h.uniforms.contourColor=this.highlightColor[i],h.uniforms.contourTint=this.highlightTint[i]):(0===s||s-1===this.highlightLevel[i])&&(h.uniforms.contourColor=this.contourColor[i],h.uniforms.contourTint=this.contourTint[i]),h.uniforms.height=this.contourLevels[i][s],p.draw(r.LINES,this._contourCounts[i][s],this._contourOffsets[i][s])}for(var i=0;3>i;++i){h.uniforms.model=f.projections[i],h.uniforms.clipBounds=f.clipBounds[i];for(var s=0;3>s;++s)if(this.contourProject[i][s]){h.uniforms.permutation=I[s],r.lineWidth(this.contourWidth[s]);for(var d=0;d<this.contourLevels[s].length;++d)d===this.highlightLevel[s]?(h.uniforms.contourColor=this.highlightColor[s],h.uniforms.contourTint=this.highlightTint[s]):(0===d||d-1===this.highlightLevel[s])&&(h.uniforms.contourColor=this.contourColor[s],h.uniforms.contourTint=this.contourTint[s]),h.uniforms.height=this.contourLevels[s][d],p.draw(r.LINES,this._contourCounts[s][d],this._contourOffsets[s][d])}}p=this._dynamicVAO,p.bind();for(var i=0;3>i;++i)if(0!==this._dynamicCounts[i]){h.uniforms.model=n.model,h.uniforms.clipBounds=n.clipBounds,h.uniforms.permutation=I[i],r.lineWidth(this.dynamicWidth[i]),h.uniforms.contourColor=this.dynamicColor[i],h.uniforms.contourTint=this.dynamicTint[i],h.uniforms.height=this.dynamicLevel[i],p.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]);for(var s=0;3>s;++s)this.contourProject[s][i]&&(h.uniforms.model=f.projections[s],h.uniforms.clipBounds=f.clipBounds[s],p.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]))}p.unbind()}}function l(t,e){var r=e.shape.slice(),n=t.shape.slice();b.assign(t.lo(1,1).hi(r[0],r[1]),e),b.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),b.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),b.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),b.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))}function u(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function c(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function f(t){if(Array.isArray(t)){if(Array.isArray(t))return[c(t[0]),c(t[1]),c(t[2])];var e=c(t);return[e.slice(),e.slice(),e.slice()]}}function h(t){var e=t.gl,r=(t.field||t.coords&&t.coords[2]||_([],[0,0]),L(e)),n=C(e),i=S(e),o=P(e),s=d(e),l=g(e,[{buffer:s,size:4,stride:z,offset:0},{buffer:s,size:2,stride:z,offset:16},{buffer:s,size:3,stride:z,offset:24}]),u=d(e),c=g(e,[{buffer:u,size:4}]),f=d(e),h=g(e,[{buffer:f,size:2,type:e.FLOAT}]),p=v(e,1,j,e.RGBA,e.UNSIGNED_BYTE);p.minFilter=e.LINEAR,p.magFilter=e.LINEAR;var m=new a(e,[0,0],[[0,0,0],[0,0,0]],r,n,s,l,p,i,o,u,c,f,h),y={levels:[[],[],[]]};for(var b in t)y[b]=t[b];return y.colormap=y.colormap||\"jet\",m.update(y),m}e.exports=h;var p=t(\"bit-twiddle\"),d=t(\"gl-buffer\"),g=t(\"gl-vao\"),v=t(\"gl-texture2d\"),m=t(\"typedarray-pool\"),y=t(\"colormap\"),b=t(\"ndarray-ops\"),x=t(\"ndarray-pack\"),_=t(\"ndarray\"),w=t(\"surface-nets\"),k=t(\"gl-mat4/multiply\"),A=t(\"gl-mat4/invert\"),M=t(\"binary-search-bounds\"),T=t(\"ndarray-gradient\"),_=t(\"ndarray\"),E=t(\"./lib/shaders\"),L=E.createShader,S=E.createContourShader,C=E.createPickShader,P=E.createPickContourShader,z=36,R=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],O=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],I=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];!function(){for(var t=0;3>t;++t){var e=I[t],r=(t+1)%3,n=(t+2)%3;e[r+0]=1,e[n+3]=1,e[t+6]=1}}();var j=265,N=a.prototype;N.isTransparent=function(){return this.opacity<1},N.isOpaque=function(){if(this.opacity>=1)return!0;for(var t=0;3>t;++t)if(this._contourCounts[t].length>0||this._dynamicCounts[t]>0)return!0;return!1},N.pickSlots=1,N.setPickBase=function(t){this.pickId=t};var F=[0,0,0],D={showSurface:!1,showContour:!1,projections:[R.slice(),R.slice(),R.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]},B={model:R,view:R,projection:R,inverseModel:R.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1},U=R.slice(),V=[1,0,0,0,1,0,0,0,1];N.draw=function(t){return s.call(this,t,!1)},N.drawTransparent=function(t){return s.call(this,t,!0)};var q={model:R,view:R,projection:R,inverseModel:R,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};N.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=q;r.model=t.model||R,r.view=t.view||R,r.projection=t.projection||R,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.permutation=V;for(var n=0;2>n;++n)for(var i=r.clipBounds[n],a=0;3>a;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var s=o(r,this);if(s.showSurface){this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount);for(var n=0;3>n;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=s.projections[n],this._pickShader.uniforms.clipBounds=s.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(s.showContour){var l=this._contourPickShader;l.bind(),l.uniforms=r;var u=this._contourVAO;u.bind();for(var a=0;3>a;++a){e.lineWidth(this.contourWidth[a]),l.uniforms.permutation=I[a];for(var n=0;n<this.contourLevels[a].length;++n)l.uniforms.height=this.contourLevels[a][n],u.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n])}for(var n=0;3>n;++n){l.uniforms.model=s.projections[n],l.uniforms.clipBounds=s.clipBounds[n];for(var a=0;3>a;++a)if(this.contourProject[n][a]){l.uniforms.permutation=I[a],e.lineWidth(this.contourWidth[a]);for(var c=0;c<this.contourLevels[a].length;++c)l.uniforms.height=this.contourLevels[a][c],u.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c])}}u.unbind()}},N.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;2>c;++c)for(var f=c?a:1-a,h=0;2>h;++h)for(var p=h?l:1-l,d=i+c,g=s+h,v=f*p,m=0;3>m;++m)u[m]+=this._field[m].get(d,g)*v;for(var y=this._pickResult.level,b=0;3>b;++b)if(y[b]=M.le(this.contourLevels[b],u[b]),y[b]<0)this.contourLevels[b].length>0&&(y[b]=0);else if(y[b]<this.contourLevels[b].length-1){var x=this.contourLevels[b][y[b]],_=this.contourLevels[b][y[b]+1];Math.abs(x-u[b])>Math.abs(_-u[b])&&(y[b]+=1)}r.index[0]=.5>a?i:i+1,r.index[1]=.5>l?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1];for(var m=0;3>m;++m)r.dataCoordinate[m]=this._field[m].get(r.index[0],r.index[1]);return r},N.update=function(t){t=t||{},this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=u(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=u(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=u(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=f(t.contourColor)),\"contourProject\"in t&&(this.contourProject=u(t.contourProject,function(t){return u(t,Boolean)})),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=f(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=u(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=u(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\n",
+       "\"colorBounds\"in t&&(this.colorBounds=t.colorBounds);var e=t.field||t.coords&&t.coords[2]||null;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var r=(e.shape[0]+2)*(e.shape[1]+2);r>this._field[2].data.length&&(m.freeFloat(this._field[2].data),this._field[2].data=m.mallocFloat(p.nextPow2(r))),this._field[2]=_(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),l(this._field[2],e),this.shape=e.shape.slice();for(var n=this.shape,a=0;2>a;++a)this._field[2].size>this._field[a].data.length&&(m.freeFloat(this._field[a].data),this._field[a].data=m.mallocFloat(this._field[2].size)),this._field[a]=_(this._field[a].data,[n[0]+2,n[1]+2]);if(t.coords){var o=t.coords;if(!Array.isArray(o)||3!==o.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(var a=0;2>a;++a){for(var s=o[a],c=0;2>c;++c)if(s.shape[c]!==n[c])throw new Error(\"gl-surface: coords have incorrect shape\");l(this._field[a],s)}}else if(t.ticks){var h=t.ticks;if(!Array.isArray(h)||2!==h.length)throw new Error(\"gl-surface: invalid ticks\");for(var a=0;2>a;++a){var d=h[a];if((Array.isArray(d)||d.length)&&(d=_(d)),d.shape[0]!==n[a])throw new Error(\"gl-surface: invalid tick length\");var g=_(d.data,n);g.stride[a]=d.stride[0],g.stride[1^a]=0,l(this._field[a],g)}}else{for(var a=0;2>a;++a){var v=[0,0];v[a]=1,this._field[a]=_(this._field[a].data,[n[0]+2,n[1]+2],v,0)}this._field[0].set(0,0,0);for(var c=0;c<n[0];++c)this._field[0].set(c+1,0,c);this._field[0].set(n[0]+1,0,n[0]-1),this._field[1].set(0,0,0);for(var c=0;c<n[1];++c)this._field[1].set(0,c+1,c);this._field[1].set(0,n[1]+1,n[1]-1)}for(var y=this._field,b=(y[2].size,_(m.mallocFloat(3*y[2].size*2),[3,n[0]+2,n[1]+2,2])),a=0;3>a;++a)T(b.pick(a),y[a],\"mirror\");for(var x=_(m.mallocFloat(3*y[2].size),[n[0]+2,n[1]+2,3]),a=0;a<n[0]+2;++a)for(var c=0;c<n[1]+2;++c){var k=b.get(0,a,c,0),A=b.get(0,a,c,1),M=b.get(1,a,c,0),E=b.get(1,a,c,1),L=b.get(2,a,c,0),S=b.get(2,a,c,1),C=M*S-E*L,P=L*A-S*k,z=k*E-A*M,R=Math.sqrt(C*C+P*P+z*z);1e-8>R?(R=Math.max(Math.abs(C),Math.abs(P),Math.abs(z)),1e-8>R?(z=1,P=C=0,R=1):R=1/R):R=1/Math.sqrt(R),x.set(a,c,0,C*R),x.set(a,c,1,P*R),x.set(a,c,2,z*R)}m.free(b.data);for(var I=[1/0,1/0,1/0],j=[-(1/0),-(1/0),-(1/0)],N=(n[0]-1)*(n[1]-1)*6,F=m.mallocFloat(p.nextPow2(9*N)),D=0,B=0,a=0;a<n[0]-1;++a)t:for(var c=0;c<n[1]-1;++c){for(var U=0;2>U;++U)for(var V=0;2>V;++V)for(var q=0;3>q;++q){var H=this._field[q].get(1+a+U,1+c+V);if(isNaN(H)||!isFinite(H))continue t}for(var q=0;6>q;++q){var G=a+O[q][0],Y=c+O[q][1],X=this._field[0].get(G+1,Y+1),W=this._field[1].get(G+1,Y+1),H=this._field[2].get(G+1,Y+1),C=x.get(G+1,Y+1,0),P=x.get(G+1,Y+1,1),z=x.get(G+1,Y+1,2);F[D++]=G,F[D++]=Y,F[D++]=X,F[D++]=W,F[D++]=H,F[D++]=0,F[D++]=C,F[D++]=P,F[D++]=z,I[0]=Math.min(I[0],X),I[1]=Math.min(I[1],W),I[2]=Math.min(I[2],H),j[0]=Math.max(j[0],X),j[1]=Math.max(j[1],W),j[2]=Math.max(j[2],H),B+=1}}this._vertexCount=B,this._coordinateBuffer.update(F.subarray(0,D)),m.freeFloat(F),m.free(x.data),this.bounds=[I,j]}var Z=!1;if(\"levels\"in t){var $=t.levels;$=Array.isArray($[0])?$.slice():[[],[],$];for(var a=0;3>a;++a)$[a]=$[a].slice(),$.sort(function(t,e){return t-e});t:for(var a=0;3>a;++a){if($[a].length!==this.contourLevels[a].length){Z=!0;break}for(var c=0;c<$[a].length;++c)if($[a][c]!==this.contourLevels[a][c]){Z=!0;break t}}this.contourLevels=$}if(Z){for(var y=this._field,n=this.shape,K=[],Q=0;3>Q;++Q){for(var $=this.contourLevels[Q],J=[],tt=[],et=[0,0],a=0;a<$.length;++a){var rt=w(this._field[Q],$[a]);J.push(K.length/4|0);var B=0;t:for(var c=0;c<rt.cells.length;++c)for(var nt=rt.cells[c],q=0;2>q;++q){var it=rt.positions[nt[q]],at=it[0],ot=0|Math.floor(at),st=at-ot,lt=it[1],ut=0|Math.floor(lt),ct=lt-ut,ft=!1;e:for(var ht=0;2>ht;++ht){et[ht]=0;for(var pt=(Q+ht+1)%3,U=0;2>U;++U)for(var dt=U?st:1-st,G=0|Math.min(Math.max(ot+U,0),n[0]),V=0;2>V;++V){var gt=V?ct:1-ct,Y=0|Math.min(Math.max(ut+V,0),n[1]),H=this._field[pt].get(G,Y);if(!isFinite(H)||isNaN(H)){ft=!0;break e}var vt=dt*gt;et[ht]+=vt*H}}if(ft){if(q>0){for(var mt=0;4>mt;++mt)K.pop();B-=1}continue t}K.push(et[0],et[1],it[0],it[1]),B+=1}tt.push(B)}this._contourOffsets[Q]=J,this._contourCounts[Q]=tt}for(var yt=m.mallocFloat(K.length),a=0;a<K.length;++a)yt[a]=K[a];this._contourBuffer.update(yt),m.freeFloat(yt)}t.colormap&&this._colorMap.setPixels(i(t.colormap))},N.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;3>t;++t)m.freeFloat(this._field[t].data)},N.highlight=function(t){if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(var e=0;3>e;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;var r;if(r=this.snapToData?t.dataCoordinate:t.position,this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=m.mallocFloat(12*i[0]*i[1]),o=0;3>o;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var s=(o+1)%3,l=(o+2)%3,u=this._field[o],c=this._field[s],f=this._field[l],h=w(u,r[o]),p=h.cells,d=h.positions;this._dynamicOffsets[o]=n;for(var e=0;e<p.length;++e)for(var g=p[e],v=0;2>v;++v){var y=d[g[v]],b=+y[0],x=0|b,_=0|Math.min(x+1,i[0]),k=b-x,A=1-k,M=+y[1],T=0|M,E=0|Math.min(T+1,i[1]),L=M-T,S=1-L,C=A*S,P=A*L,z=k*S,R=k*L,O=C*c.get(x,T)+P*c.get(x,E)+z*c.get(_,T)+R*c.get(_,E),I=C*f.get(x,T)+P*f.get(x,E)+z*f.get(_,T)+R*f.get(_,E);if(isNaN(O)||isNaN(I)){v&&(n-=1);break}a[2*n+0]=O,a[2*n+1]=I,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),m.freeFloat(a)}}},{\"./lib/shaders\":410,\"binary-search-bounds\":411,\"bit-twiddle\":299,colormap:307,\"gl-buffer\":325,\"gl-mat4/invert\":344,\"gl-mat4/multiply\":346,\"gl-texture2d\":416,\"gl-vao\":420,ndarray:438,\"ndarray-gradient\":412,\"ndarray-ops\":437,\"ndarray-pack\":413,\"surface-nets\":457,\"typedarray-pool\":463}],416:[function(t,e,r){arguments[4][179][0].apply(r,arguments)},{dup:179,ndarray:438,\"ndarray-ops\":437,\"typedarray-pool\":463}],417:[function(t,e,r){arguments[4][42][0].apply(r,arguments)},{dup:42}],418:[function(t,e,r){arguments[4][43][0].apply(r,arguments)},{\"./do-bind.js\":417,dup:43}],419:[function(t,e,r){arguments[4][44][0].apply(r,arguments)},{\"./do-bind.js\":417,dup:44}],420:[function(t,e,r){arguments[4][45][0].apply(r,arguments)},{\"./lib/vao-emulated.js\":418,\"./lib/vao-native.js\":419,dup:45}],421:[function(t,e,r){\"use strict\";function n(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function i(t,e,r){this.vertices=t,this.cell=e,this.index=r}function a(t,e){return c(t.vertices,e.vertices)}function o(t){for(var e=[\"function orient(){var tuple=this.tuple;return test(\"],r=0;t>=r;++r)r>0&&e.push(\",\"),e.push(\"tuple[\",r,\"]\");e.push(\")}return orient\");var n=new Function(\"test\",e.join(\"\")),i=u[t+1];return i||(i=u),n(i)}function s(t,e,r){this.dimension=t,this.vertices=e,this.simplices=r,this.interior=r.filter(function(t){return!t.boundary}),this.tuple=new Array(t+1);for(var n=0;t>=n;++n)this.tuple[n]=this.vertices[n];var i=f[t];i||(i=f[t]=o(t)),this.orient=i}function l(t,e){var r=t.length;if(0===r)throw new Error(\"Must have at least d+1 points\");var i=t[0].length;if(i>=r)throw new Error(\"Must input at least d+1 points\");var a=t.slice(0,i+1),o=u.apply(void 0,a);if(0===o)throw new Error(\"Input not in general position\");for(var l=new 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i={fontSize:parseInt(c.style(\"font-size\"),10)};a(f[2],i,function(i,a,o){p.selectAll(\"svg.\"+d).remove(),p.selectAll(\"g.\"+d+\"-group\").remove();var s=i&&i.select(\"svg\");if(!s||!s.node())return r(),void t();var l=p.append(\"g\").classed(d+\"-group\",!0).attr({\"pointer-events\":\"none\"});l.node().appendChild(s.node()),a&&a.node()&&s.node().insertBefore(a.node().cloneNode(!0),s.node().firstChild),s.attr({\"class\":d,height:o.height,preserveAspectRatio:\"xMinYMin meet\"}).style({overflow:\"visible\",\"pointer-events\":\"none\"});var u=c.style(\"fill\")||\"black\";s.select(\"g\").attr({fill:u,stroke:u});var f=n(s,\"width\"),h=n(s,\"height\"),g=+c.attr(\"x\")-f*{start:0,middle:.5,end:1}[c.attr(\"text-anchor\")||\"start\"],v=parseInt(c.style(\"font-size\"),10)||n(c,\"height\"),m=-v/4;\"y\"===d[0]?(l.attr({transform:\"rotate(\"+[-90,+c.attr(\"x\"),+c.attr(\"y\")]+\") 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t=u.select(l.Lib.getPlotDiv(o.node())),e=t.select(\".svg-container\"),n=e.append(\"div\");n.classed(\"plugin-editable editable\",!0).style({position:\"absolute\",\"font-family\":o.style(\"font-family\")||\"Arial\",\"font-size\":o.style(\"font-size\")||12,color:r.fill||o.style(\"fill\")||\"black\",opacity:1,\"background-color\":r.background||\"transparent\",outline:\"#ffffff33 1px solid\",margin:[-parseFloat(o.style(\"font-size\"))/8+1,0,0,-1].join(\"px \")+\"px\",padding:\"0\",\"box-sizing\":\"border-box\"}).attr({contenteditable:!0}).text(r.text||o.attr(\"data-unformatted\")).call(s(o,e,r)).on(\"blur\",function(){o.text(this.textContent).style({opacity:1});var t,e=u.select(this).attr(\"class\");t=e?\".\"+e.split(\" \")[0]+\"-math-group\":\"[class*=-math-group]\",t&&u.select(o.node().parentNode).select(t).style({opacity:0});var r=this.textContent;u.select(this).transition().duration(0).remove(),u.select(document).on(\"mouseup\",null),c.edit.call(o,r)}).on(\"focus\",function(){var t=this;u.select(document).on(\"mouseup\",function(){return u.event.target===t?!1:void(document.activeElement===n.node()&&n.node().blur())})}).on(\"keyup\",function(){27===u.event.which?(o.style({opacity:1}),u.select(this).style({opacity:0}).on(\"blur\",function(){return!1}).transition().remove(),c.cancel.call(o,this.textContent)):(c.input.call(o,this.textContent),u.select(this).call(s(o,e,r)))}).on(\"keydown\",function(){13===u.event.which&&this.blur()}).call(i)}r||(r={});var o=this,c=u.dispatch(\"edit\",\"input\",\"cancel\"),f=u.select(this.node()).style({\"pointer-events\":\"all\"}),h=e||f;return e&&f.style({\"pointer-events\":\"none\"}),r.immediate?n():h.on(\"click\",n),u.rebind(this,c,\"on\")}},{\"../constants/xmlns_namespaces\":567,\"../plotly\":595,d3:320}],590:[function(t,e,r){\"use strict\";var n=e.exports={},i=t(\"../constants/geo_constants\").locationmodeToLayer,a=t(\"topojson\").feature;n.getTopojsonName=function(t){return[t.scope.replace(/ /g,\"-\"),\"_\",t.resolution.toString(),\"m\"].join(\"\")},n.getTopojsonPath=function(t,e){return t+e+\".json\"},n.getTopojsonFeatures=function(t,e){var r=i[t.locationmode],n=e.objects[r];return a(e,n).features}},{\"../constants/geo_constants\":563,topojson:460}],591:[function(t,e,r){\"use strict\";function n(t){var e;if(\"string\"==typeof t){if(e=document.getElementById(t),null===e)throw new Error(\"No DOM element with id '\"+t+\"' exists on the page.\");return e}if(null===t||void 0===t)throw new Error(\"DOM element provided is null or undefined\");return t}function i(t,e){t._fullLayout._paperdiv.style(\"background\",\"white\"),P.defaultConfig.setBackground(t,e)}function a(t,e){t._context||(t._context=z.extendFlat({},P.defaultConfig));var r=t._context;e&&(Object.keys(e).forEach(function(t){t in r&&(\"setBackground\"===t&&\"opaque\"===e[t]?r[t]=i:r[t]=e[t])}),e.plot3dPixelRatio&&!r.plotGlPixelRatio&&(r.plotGlPixelRatio=r.plot3dPixelRatio)),r.staticPlot&&(r.editable=!1,r.autosizable=!1,r.scrollZoom=!1,r.doubleClick=!1,r.showTips=!1,r.showLink=!1,r.displayModeBar=!1)}function o(t,e,r){var n=L.select(t).selectAll(\".plot-container\").data([0]);n.enter().insert(\"div\",\":first-child\").classed(\"plot-container plotly\",!0);var i=n.selectAll(\".svg-container\").data([0]);i.enter().append(\"div\").classed(\"svg-container\",!0).style(\"position\",\"relative\"),i.html(\"\"),e&&(t.data=e),r&&(t.layout=r),P.micropolar.manager.fillLayout(t),\"initial\"===t._fullLayout.autosize&&t._context.autosizable&&(w(t,{}),t._fullLayout.autosize=r.autosize=!0),i.style({width:t._fullLayout.width+\"px\",height:t._fullLayout.height+\"px\"}),t.framework=P.micropolar.manager.framework(t),t.framework({data:t.data,layout:t.layout},i.node()),t.framework.setUndoPoint();var a=t.framework.svg(),o=1,s=t._fullLayout.title;\"\"!==s&&s||(o=0);var l=\"Click to enter title\",u=function(){this.call(P.util.convertToTspans)},c=a.select(\".title-group text\").call(u);if(t._context.editable){c.attr({\"data-unformatted\":s}),s&&s!==l||(o=.2,c.attr({\"data-unformatted\":l}).text(l).style({opacity:o}).on(\"mouseover.opacity\",function(){L.select(this).transition().duration(100).style(\"opacity\",1)}).on(\"mouseout.opacity\",function(){L.select(this).transition().duration(1e3).style(\"opacity\",0)}));var f=function(){this.call(P.util.makeEditable).on(\"edit\",function(e){t.framework({layout:{title:e}}),this.attr({\"data-unformatted\":e}).text(e).call(u),this.call(f)}).on(\"cancel\",function(){var t=this.attr(\"data-unformatted\");this.text(t).call(u)})};c.call(f)}return t._context.setBackground(t,t._fullLayout.paper_bgcolor),I.addLinks(t),Promise.resolve()}function s(t){var e,r;t||(t={}),t.xaxis1&&(t.xaxis||(t.xaxis=t.xaxis1),delete t.xaxis1),t.yaxis1&&(t.yaxis||(t.yaxis=t.yaxis1),delete t.yaxis1);var n=P.Axes.list({_fullLayout:t});for(e=0;e<n.length;e++){var i=n[e];i.anchor&&\"free\"!==i.anchor&&(i.anchor=P.Axes.cleanId(i.anchor)),i.overlaying&&(i.overlaying=P.Axes.cleanId(i.overlaying)),i.type||(i.isdate?i.type=\"date\":i.islog?i.type=\"log\":i.isdate===!1&&i.islog===!1&&(i.type=\"linear\")),(\"withzero\"===i.autorange||\"tozero\"===i.autorange)&&(i.autorange=!0,i.rangemode=\"tozero\"),delete i.islog,delete i.isdate,delete i.categories,f(i,\"domain\")&&delete i.domain,void 0!==i.autotick&&(void 0===i.tickmode&&(i.tickmode=i.autotick?\"auto\":\"linear\"),delete i.autotick)}void 0===t.annotations||Array.isArray(t.annotations)||(console.log(\"annotations must be an array\"),delete t.annotations);var a=(t.annotations||[]).length;for(e=0;a>e;e++){var o=t.annotations[e];o.ref&&(\"paper\"===o.ref?(o.xref=\"paper\",o.yref=\"paper\"):\"data\"===o.ref&&(o.xref=\"x\",o.yref=\"y\"),delete 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i(t){return new n(t)}var a=t(\"../../plotly\"),o=t(\"../../lib/html2unicode\"),s=t(\"../../lib/str2rgbarray\"),l=n.prototype,u=[\"xaxis\",\"yaxis\"];l.merge=function(t){this.titleEnable=!1,this.backgroundColor=s(t.plot_bgcolor);var e,r,n,i,a,l,c,f,h,p,d;for(p=0;2>p;++p){for(e=u[p],r=t[this.scene[e]._name],n=/Click to enter .+ title/.test(r.title)?\"\":r.title,d=0;2>=d;d+=2)this.labelEnable[p+d]=!1,this.labels[p+d]=o(n),this.labelColor[p+d]=s(r.titlefont.color),this.labelFont[p+d]=r.titlefont.family,this.labelSize[p+d]=r.titlefont.size,this.labelPad[p+d]=this.getLabelPad(e,r),this.tickEnable[p+d]=!1,this.tickColor[p+d]=s((r.tickfont||{}).color),this.tickAngle[p+d]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[p+d]=this.getTickPad(r),this.tickMarkLength[p+d]=0,this.tickMarkWidth[p+d]=r.tickwidth||0,this.tickMarkColor[p+d]=s(r.tickcolor),this.borderLineEnable[p+d]=!1,this.borderLineColor[p+d]=s(r.linecolor),this.borderLineWidth[p+d]=r.linewidth||0;c=this.hasSharedAxis(r),a=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,i=r.mirror||!1,f=c?-1!==String(i).indexOf(\"all\"):!!i,h=c?\"allticks\"===i:-1!==String(i).indexOf(\"ticks\"),a?this.labelEnable[p]=!0:l&&(this.labelEnable[p+2]=!0),a?this.tickEnable[p]=r.showticklabels:l&&(this.tickEnable[p+2]=r.showticklabels),(a||f)&&(this.borderLineEnable[p]=r.showline),(l||f)&&(this.borderLineEnable[p+2]=r.showline),(a||h)&&(this.tickMarkLength[p]=this.getTickMarkLength(r)),(l||h)&&(this.tickMarkLength[p+2]=this.getTickMarkLength(r)),this.gridLineEnable[p]=r.showgrid,this.gridLineColor[p]=s(r.gridcolor),this.gridLineWidth[p]=r.gridwidth,this.zeroLineEnable[p]=r.zeroline,this.zeroLineColor[p]=s(r.zerolinecolor),this.zeroLineWidth[p]=r.zerolinewidth}},l.hasSharedAxis=function(t){var e=this.scene,r=a.Plots.getSubplotIds(e.fullLayout,\"gl2d\"),n=a.Axes.findSubplotsWithAxis(r,t);return 0!==n.indexOf(e.id)},l.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},l.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},l.getLabelPad=function(t,e){var r=1.5,n=e.titlefont.size,i=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?-10+n*(r+(i?1:0)):-10+n*(r+(i?.5:0)):\"yaxis\"===t?\"right\"===e.side?10+n*(r+(i?1:.5)):10+n*(r+(i?.5:0)):void 0},l.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},l.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=i},{\"../../lib/html2unicode\":577,\"../../lib/str2rgbarray\":588,\"../../plotly\":595}],626:[function(t,e,r){\"use strict\";var n=t(\"../../plotly\"),i=t(\"./scene2d\"),a=n.Plots;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex={x:/^x([2-9]|[1-9][0-9]+)?$/,y:/^y([2-9]|[1-9][0-9]+)?$/},r.attrRegex={x:/^xaxis([2-9]|[1-9][0-9]+)?$/,y:/^yaxis([2-9]|[1-9][0-9]+)?$/},r.attributes=t(\"../cartesian/attributes\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=a.getSubplotIds(e,\"gl2d\"),o=0;o<n.length;o++){var s=n[o],l=e._plots[s],u=a.getSubplotData(r,\"gl2d\",s),c=l._scene2d;void 0===c&&(c=new i({container:t.querySelector(\".gl-container\"),id:s,staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),l._scene2d=c),c.plot(u,e,t.layout)}}},{\"../../plotly\":595,\"../cartesian/attributes\":597,\"./scene2d\":627}],627:[function(t,e,r){\"use strict\";function n(t,e){this.container=t.container,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.fullLayout=e,this.updateAxes(e),this.makeFramework(),this.glplotOptions=p(this),this.glplotOptions.merge(e),this.glplot=c(this.glplotOptions),this.camera=d(this),this.traces={},this.spikes=f(this.glplot),this.selectBox=h(this.glplot,{innerFill:!1,outerFill:!0}),this.pickResult=null,this.bounds=[1/0,1/0,-(1/0),-(1/0)],this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw()}function i(t,e){for(var r=0;2>r;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1}var a,o,s=t(\"../../plots/plots\"),l=t(\"../../plots/cartesian/axes\"),u=t(\"../../plots/cartesian/graph_interact\"),c=t(\"gl-plot2d\"),f=t(\"gl-spikes2d\"),h=t(\"gl-select-box\"),p=t(\"./convert\"),d=t(\"./camera\"),g=t(\"../../lib/html2unicode\"),v=t(\"../../lib/show_no_webgl_msg\"),m=[\"xaxis\",\"yaxis\"];e.exports=n;var y=n.prototype;y.makeFramework=function(){if(this.staticPlot){if(!o){a=document.createElement(\"canvas\");try{o=a.getContext(\"webgl\",{preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0})}catch(t){throw new Error([\"Error creating static canvas/context for image server\"].join(\" \"))}}this.canvas=a,this.gl=o}else{var e,r=document.createElement(\"canvas\"),n={premultipliedAlpha:!0};try{e=r.getContext(\"webgl\",n)}catch(t){}if(!e)try{e=r.getContext(\"experimental-webgl\",n)}catch(t){}e||v(this),this.canvas=r,this.gl=e}var i=this.canvas,s=this.pixelRatio,l=this.fullLayout;i.width=0|Math.ceil(s*l.width),i.height=0|Math.ceil(s*l.height),i.style.width=\"100%\",i.style.height=\"100%\",i.style.position=\"absolute\",i.style.top=\"0px\",i.style.left=\"0px\",i.style[\"pointer-events\"]=\"none\";var u=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");u.style.position=\"absolute\",u.style.top=u.style.left=\"0px\",u.style.width=u.style.height=\"100%\",u.style[\"z-index\"]=20,u.style[\"pointer-events\"]=\"none\";var c=this.mouseContainer=document.createElement(\"div\");c.style.position=\"absolute\";var f=this.container;f.appendChild(i),f.appendChild(u),f.appendChild(c)},y.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(a),this.glplot.setDirty(!0),this.glplot.draw();var e=this.glplot.gl,r=e.drawingBufferWidth,n=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new Uint8Array(r*n*4);e.readPixels(0,0,r,n,e.RGBA,e.UNSIGNED_BYTE,i);for(var o=0,s=n-1;s>o;++o,--s)for(var l=0;r>l;++l)for(var u=0;4>u;++u){var c=i[4*(r*o+l)+u];i[4*(r*o+l)+u]=i[4*(r*s+l)+u],i[4*(r*s+l)+u]=c}var f=document.createElement(\"canvas\");f.width=r,f.height=n;var h=f.getContext(\"2d\"),p=h.createImageData(r,n);p.data.set(i),h.putImageData(p,0,0);var d;switch(t){case\"jpeg\":d=f.toDataURL(\"image/jpeg\");break;case\"webp\":d=f.toDataURL(\"image/webp\");break;default:d=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(a),d},y.computeTickMarks=function(){\n",
+       "this.xaxis._length=this.glplot.viewBox[2]-this.glplot.viewBox[0],this.yaxis._length=this.glplot.viewBox[3]-this.glplot.viewBox[1];for(var t=[l.calcTicks(this.xaxis),l.calcTicks(this.yaxis)],e=0;2>e;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=g(t[e][r].text+\"\").replace(/\\n/g,\" \");return t},y.updateAxes=function(t){var e=l.subplotMatch,r=\"xaxis\"+this.id.match(e)[1],n=\"yaxis\"+this.id.match(e)[2];this.xaxis=t[r],this.yaxis=t[n]},y.updateFx=function(t){var e=this.fullLayout;e.dragmode=t.dragmode,e.hovermode=t.hovermode},y.cameraChanged=function(){var t=this.camera,e=this.xaxis.range,r=this.yaxis.range;this.glplot.setDataBox([e[0],r[0],e[1],r[1]]);var n=this.computeTickMarks(),a=this.glplotOptions.ticks;i(n,a)&&(this.glplotOptions.ticks=n,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions))},y.destroy=function(){this.glplot.dispose()},y.plot=function(t,e){var r,n,i=this.glplot,a=this.pixelRatio;this.fullLayout=e,this.updateAxes(e);var o=e.width,u=e.height,c=0|Math.ceil(a*o),f=0|Math.ceil(a*u),h=this.canvas;(h.width!==c||h.height!==f)&&(h.width=c,h.height=f),t?Array.isArray(t)||(t=[t]):t=[];var p,d;for(r=0;r<t.length;++r){if(p=t[r],d=this.traces[p.uid])d.update(p);else{var g=s.getModule(p.type);d=g.plot(this,p)}this.traces[p.uid]=d}var v=Object.keys(this.traces);t:for(r=0;r<v.length;++r){for(n=0;n<t.length;++n)if(t[n].uid===v[r])continue t;d=this.traces[v[r]],d.dispose(),delete this.traces[v[r]]}var y=this.glplotOptions;y.merge(e),y.screenBox=[0,0,o,u];var b=e._size,x=this.xaxis.domain,_=this.yaxis.domain;y.viewBox=[b.l+x[0]*b.w,b.b+_[0]*b.h,o-b.r-(1-x[1])*b.w,u-b.t-(1-_[1])*b.h],this.mouseContainer.style.width=b.w*(x[1]-x[0])+\"px\",this.mouseContainer.style.height=b.h*(_[1]-_[0])+\"px\",this.mouseContainer.height=b.h*(_[1]-_[0]),this.mouseContainer.style.left=b.l+x[0]*b.w+\"px\",this.mouseContainer.style.top=b.t+(1-_[1])*b.h+\"px\";var w=this.bounds;for(w[0]=w[1]=1/0,w[2]=w[3]=-(1/0),v=Object.keys(this.traces),r=0;r<v.length;++r){d=this.traces[v[r]];for(var k=0;2>k;++k)w[k]=Math.min(w[k],d.bounds[k]),w[k+2]=Math.max(w[k+2],d.bounds[k+2])}var A;for(r=0;2>r;++r)w[r]>w[r+2]&&(w[r]=-1,w[r+2]=1),A=this[m[r]],A._length=y.viewBox[r+2]-y.viewBox[r],l.doAutoRange(A);y.ticks=this.computeTickMarks();var M=this.xaxis.range,T=this.yaxis.range;y.dataBox=[M[0],T[0],M[1],T[1]],y.merge(e),i.update(y)},y.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=this.fullLayout;this.cameraChanged();var i=r.x*t.pixelRatio,a=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===n.dragmode)this.selectBox.enabled=!0,this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],t.setDirty();else{this.selectBox.enabled=!1;var o=n._size,s=this.xaxis.domain,l=this.yaxis.domain,c=t.pick(i/t.pixelRatio+o.l+s[0]*o.w,a/t.pixelRatio-(o.t+(1-l[1])*o.h));if(c&&n.hovermode){var f=c.object._trace.handlePick(c);if(f&&(!this.lastPickResult||this.lastPickResult.trace!==f.trace||this.lastPickResult.dataCoord[0]!==f.dataCoord[0]||this.lastPickResult.dataCoord[1]!==f.dataCoord[1])){var h=this.lastPickResult=f;this.spikes.update({center:c.dataCoord}),h.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(c.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(c.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio];var p=h.hoverinfo;if(\"all\"!==p){var d=p.split(\"+\");-1===d.indexOf(\"x\")&&(h.traceCoord[0]=void 0),-1===d.indexOf(\"y\")&&(h.traceCoord[1]=void 0),-1===d.indexOf(\"text\")&&(h.textLabel=void 0),-1===d.indexOf(\"name\")&&(h.name=void 0)}u.loneHover({x:h.screenCoord[0],y:h.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",h.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",h.traceCoord[1]),text:h.textLabel,name:h.name,color:h.color},{container:this.svgContainer}),this.lastPickResult={dataCoord:c.dataCoord}}}else!c&&this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,u.loneUnhover(this.svgContainer))}t.draw()}},y.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return l.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../lib/html2unicode\":577,\"../../lib/show_no_webgl_msg\":586,\"../../plots/cartesian/axes\":598,\"../../plots/cartesian/graph_interact\":603,\"../../plots/plots\":642,\"./camera\":624,\"./convert\":625,\"gl-plot2d\":371,\"gl-select-box\":383,\"gl-spikes2d\":409}],628:[function(t,e,r){\"use strict\";function n(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]),\"zoomMin\"in e&&(r[0]=e.zoomMin),\"zoomMax\"in e&&(r[1]=e.zoomMax);var n=a({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),l=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],u=0,c=t.clientWidth,f=t.clientHeight,h={keyBindingMode:\"rotate\",view:n,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:n.modes,tick:function(){var e=i(),r=this.delay,a=e-2*r;n.idle(e-r),n.recalcMatrix(a),n.flush(e-(100+2*r));for(var o=!0,s=n.computedMatrix,h=0;16>h;++h)o=o&&l[h]===s[h],l[h]=s[h];var p=t.clientWidth===c&&t.clientHeight===f;return c=t.clientWidth,f=t.clientHeight,o?!p:(u=Math.exp(n.computedRadius[0]),!0)},lookAt:function(t,e,r){n.lookAt(n.lastT(),t,e,r)},rotate:function(t,e,r){n.rotate(n.lastT(),t,e,r)},pan:function(t,e,r){n.pan(n.lastT(),t,e,r)},translate:function(t,e,r){n.translate(n.lastT(),t,e,r)}};Object.defineProperties(h,{matrix:{get:function(){return n.computedMatrix},set:function(t){return n.setMatrix(n.lastT(),t),n.computedMatrix},enumerable:!0},mode:{get:function(){return n.getMode()},set:function(t){var e=n.computedUp.slice(),r=n.computedEye.slice(),a=n.computedCenter.slice();if(n.setMode(t),\"turntable\"===t){var o=i();n._active.lookAt(o,r,a,e),n._active.lookAt(o+500,r,a,[0,0,1]),n._active.flush(o)}return n.getMode()},enumerable:!0},center:{get:function(){return n.computedCenter},set:function(t){return n.lookAt(n.lastT(),null,t),n.computedCenter},enumerable:!0},eye:{get:function(){return n.computedEye},set:function(t){return n.lookAt(n.lastT(),t),n.computedEye},enumerable:!0},up:{get:function(){return n.computedUp},set:function(t){return n.lookAt(n.lastT(),null,null,t),n.computedUp},enumerable:!0},distance:{get:function(){return u},set:function(t){return n.setDistance(n.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return n.getDistanceLimits(r)},set:function(t){return n.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",function(t){return t.preventDefault(),!1});var p=0,d=0;return o(t,function(e,r,a,o){var s=\"rotate\"===h.keyBindingMode,l=\"pan\"===h.keyBindingMode,c=\"zoom\"===h.keyBindingMode,f=!!o.control,g=!!o.alt,v=!!o.shift,m=!!(1&e),y=!!(2&e),b=!!(4&e),x=1/t.clientHeight,_=x*(r-p),w=x*(a-d),k=h.flipX?1:-1,A=h.flipY?1:-1,M=i(),T=Math.PI*h.rotateSpeed;if((s&&m&&!f&&!g&&!v||m&&!f&&!g&&v)&&n.rotate(M,k*T*_,-A*T*w,0),(l&&m&&!f&&!g&&!v||y||m&&f&&!g&&!v)&&n.pan(M,-h.translateSpeed*_*u,h.translateSpeed*w*u,0),c&&m&&!f&&!g&&!v||b||m&&!f&&g&&!v){var E=-h.zoomSpeed*w/window.innerHeight*(M-n.lastT())*100;n.pan(M,0,0,u*(Math.exp(E)-1))}return p=r,d=a,!0}),s(t,function(t,e){var r=h.flipX?1:-1,a=h.flipY?1:-1,o=i();if(Math.abs(t)>Math.abs(e))n.rotate(o,0,0,-t*r*Math.PI*h.rotateSpeed/window.innerWidth);else{var s=-h.zoomSpeed*a*e/window.innerHeight*(o-n.lastT())/100;n.pan(o,0,0,u*(Math.exp(s)-1))}},!0),h}e.exports=n;var i=t(\"right-now\"),a=t(\"3d-view\"),o=t(\"mouse-change\"),s=t(\"mouse-wheel\")},{\"3d-view\":288,\"mouse-change\":426,\"mouse-wheel\":430,\"right-now\":440}],629:[function(t,e,r){\"use strict\";var n=t(\"./scene\"),i=t(\"../plots\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attrRegex=/^scene([2-9]|[1-9][0-9]+)?$/,r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){var e=t._fullLayout,r=t._fullData,a=i.getSubplotIds(e,\"gl3d\");e._paperdiv.style({width:e.width+\"px\",height:e.height+\"px\"}),t._context.setBackground(t,e.paper_bgcolor);for(var o=0;o<a.length;o++){var s=a[o],l=i.getSubplotData(r,\"gl3d\",s),u=e[s]._scene;void 0===u&&(u=new n({container:t.querySelector(\".gl-container\"),id:s,staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),e[s]._scene=u),u.plot(l,e,t.layout)}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.setConvert=t(\"./set_convert\"),r.initAxes=function(t){var e=t._fullLayout;delete e.xaxis,delete e.yaxis;for(var r=i.getSubplotIds(e,\"gl3d\"),n=0;n<r.length;++n)for(var o=r[n],s=e[o],l=0;3>l;++l){var u=a[l],c=s[u];c._td=t}}},{\"../plots\":642,\"./layout/attributes\":630,\"./layout/defaults\":634,\"./layout/layout_attributes\":635,\"./scene\":639,\"./set_convert\":640}],630:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"sceneid\",dflt:\"scene\"}}},{}],631:[function(t,e,r){\"use strict\";var n=t(\"../../cartesian/layout_attributes\"),i=t(\"../../../lib/extend\").extendFlat;e.exports={showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:\"rgb(0,0,0)\"},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},title:n.title,titlefont:n.titlefont,type:n.type,autorange:n.autorange,rangemode:n.rangemode,range:n.range,fixedrange:n.fixedrange,tickmode:n.tickmode,nticks:n.nticks,tick0:n.tick0,dtick:n.dtick,tickvals:n.tickvals,ticktext:n.ticktext,ticks:n.ticks,mirror:n.mirror,ticklen:n.ticklen,tickwidth:n.tickwidth,tickcolor:n.tickcolor,showticklabels:n.showticklabels,tickfont:n.tickfont,tickangle:n.tickangle,tickprefix:n.tickprefix,showtickprefix:n.showtickprefix,ticksuffix:n.ticksuffix,showticksuffix:n.showticksuffix,showexponent:n.showexponent,exponentformat:n.exponentformat,tickformat:n.tickformat,hoverformat:n.hoverformat,showline:n.showline,linecolor:n.linecolor,linewidth:n.linewidth,showgrid:n.showgrid,gridcolor:i({},n.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:n.gridwidth,zeroline:n.zeroline,zerolinecolor:n.zerolinecolor,zerolinewidth:n.zerolinewidth}},{\"../../../lib/extend\":574,\"../../cartesian/layout_attributes\":605}],632:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"./axis_attributes\"),a=t(\"../../cartesian/axis_defaults\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=function(){};e.exports=function(t,e,r){function l(t,e){return n.coerce(u,c,i,t,e)}for(var u,c,f=0;f<o.length;f++){var h=o[f];u=t[h]||{},c={_id:h[0]+r.scene,_name:h},e[h]=c=a(u,c,l,{font:r.font,letter:h[0],data:r.data,showGrid:!0}),l(\"gridcolor\"),l(\"title\",h[0]),c.setScale=s,l(\"showspikes\")&&(l(\"spikesides\"),l(\"spikethickness\"),l(\"spikecolor\")),l(\"showbackground\")&&l(\"backgroundcolor\"),l(\"showaxeslabels\")}}},{\"../../../lib\":578,\"../../cartesian/axis_defaults\":599,\"./axis_attributes\":631}],633:[function(t,e,r){\"use strict\";function n(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=l(this.tickPad),this._defaultLabelPad=l(this.labelPad),this._defaultLineTickLength=l(this.lineTickLength)}function i(t){var e=new n;return e.merge(t),e}var a=t(\"arraytools\"),o=t(\"../../../lib/html2unicode\"),s=t(\"../../../lib/str2rgbarray\"),l=a.copy1D,u=[\"xaxis\",\"yaxis\",\"zaxis\"],c=n.prototype;c.merge=function(t){for(var e=this,r=0;3>r;++r){var n=t[u[r]];e.labels[r]=o(n.title),\"titlefont\"in n&&(n.titlefont.color&&(e.labelColor[r]=s(n.titlefont.color)),n.titlefont.family&&(e.labelFont[r]=n.titlefont.family),n.titlefont.size&&(e.labelSize[r]=n.titlefont.size)),\"showline\"in n&&(e.lineEnable[r]=n.showline),\"linecolor\"in n&&(e.lineColor[r]=s(n.linecolor)),\"linewidth\"in n&&(e.lineWidth[r]=n.linewidth),\"showgrid\"in n&&(e.gridEnable[r]=n.showgrid),\"gridcolor\"in n&&(e.gridColor[r]=s(n.gridcolor)),\"gridwidth\"in n&&(e.gridWidth[r]=n.gridwidth),\"log\"===n.type?e.zeroEnable[r]=!1:\"zeroline\"in n&&(e.zeroEnable[r]=n.zeroline),\"zerolinecolor\"in n&&(e.zeroLineColor[r]=s(n.zerolinecolor)),\"zerolinewidth\"in n&&(e.zeroLineWidth[r]=n.zerolinewidth),\"ticks\"in n&&n.ticks?e.lineTickEnable[r]=!0:e.lineTickEnable[r]=!1,\"ticklen\"in n&&(e.lineTickLength[r]=e._defaultLineTickLength[r]=n.ticklen),\"tickcolor\"in n&&(e.lineTickColor[r]=s(n.tickcolor)),\"tickwidth\"in n&&(e.lineTickWidth[r]=n.tickwidth),\"tickangle\"in n&&(e.tickAngle[r]=\"auto\"===n.tickangle?0:Math.PI*-n.tickangle/180),\"showticklabels\"in n&&(e.tickEnable[r]=n.showticklabels),\"tickfont\"in n&&(n.tickfont.color&&(e.tickColor[r]=s(n.tickfont.color)),n.tickfont.family&&(e.tickFont[r]=n.tickfont.family),n.tickfont.size&&(e.tickSize[r]=n.tickfont.size)),\"mirror\"in n?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(n.mirror)?(e.lineTickMirror[r]=!0,e.lineMirror[r]=!0):n.mirror===!0?(e.lineTickMirror[r]=!1,e.lineMirror[r]=!0):(e.lineTickMirror[r]=!1,e.lineMirror[r]=!1):e.lineMirror[r]=!1,\"showbackground\"in n&&n.showbackground!==!1?(e.backgroundEnable[r]=!0,e.backgroundColor[r]=s(n.backgroundcolor)):e.backgroundEnable[r]=!1}},e.exports=i},{\"../../../lib/html2unicode\":577,\"../../../lib/str2rgbarray\":588,arraytools:298}],634:[function(t,e,r){\"use strict\";var n=t(\"../../../plotly\"),i=t(\"./layout_attributes\"),a=t(\"./axis_defaults\");e.exports=function(t,e,r){function o(t,e){return n.Lib.coerce(u,c,i,t,e)}if(e._hasGL3D){var s,l=n.Plots.getSubplotIdsInData(r,\"gl3d\");delete e.xaxis,delete e.yaxis;var u,c,f=l.length;for(s=0;f>s;++s){var h=l[s];void 0!==t[h]?u=t[h]:t[h]=u={},c=e[h]||{},o(\"bgcolor\");for(var p=Object.keys(i.camera),d=0;d<p.length;d++)o(\"camera.\"+p[d]+\".x\"),o(\"camera.\"+p[d]+\".y\"),o(\"camera.\"+p[d]+\".z\");o(\"domain.x\",[s/f,(s+1)/f]),o(\"domain.y\");var g=!!o(\"aspectratio.x\")&&!!o(\"aspectratio.y\")&&!!o(\"aspectratio.z\"),v=g?\"manual\":\"auto\",m=o(\"aspectmode\",v);g||(u.aspectratio=c.aspectratio={x:1,y:1,z:1},\"manual\"===m&&(c.aspectmode=\"auto\")),a(u,c,{font:e.font,scene:h,data:r}),e[h]=c}}}},{\"../../../plotly\":595,\"./axis_defaults\":632,\"./layout_attributes\":635}],635:[function(t,e,r){\"use strict\";function n(t,e,r){return{x:{valType:\"number\",dflt:t},y:{valType:\"number\",dflt:e},z:{valType:\"number\",dflt:r}}}var i=t(\"./axis_attributes\"),a=t(\"../../../lib/extend\").extendFlat;e.exports={bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\"},camera:{up:a(n(0,0,1),{}),center:a(n(0,0,0),{}),eye:a(n(1.25,1.25,1.25),{})},domain:{x:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]},y:{valType:\"info_array\",items:[{valType:\"number\",min:0,max:1},{valType:\"number\",min:0,max:1}],dflt:[0,1]}},aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\"},aspectratio:{x:{valType:\"number\",min:0},y:{valType:\"number\",min:0},z:{valType:\"number\",min:0}},xaxis:i,yaxis:i,zaxis:i,_deprecated:{cameraposition:{valType:\"info_array\"}}}},{\"../../../lib/extend\":574,\"./axis_attributes\":631}],636:[function(t,e,r){\"use strict\";function n(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}function i(t){var e=new n;return e.merge(t),e}var a=t(\"../../../lib/str2rgbarray\"),o=[\"xaxis\",\"yaxis\",\"zaxis\"],s=n.prototype;s.merge=function(t){for(var e=0;3>e;++e){var r=t[o[e]];this.enabled[e]=r.showspikes,this.colors[e]=a(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness}},e.exports=i},{\"../../../lib/str2rgbarray\":588}],637:[function(t,e,r){\"use strict\";function n(t){for(var e=new Array(3),r=0;3>r;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}function i(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,i=t.fullSceneLayout,u=[[],[],[]],c=0;3>c;++c){var f=i[s[c]];if(f._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(f._length)===1/0)u[c]=[];else{f.range[0]=r[c].lo/t.dataScale[c],f.range[1]=r[c].hi/t.dataScale[c],f._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),f.range[0]===f.range[1]&&(f.range[0]-=1,f.range[1]+=1);var h=f.tickmode;if(\"auto\"===f.tickmode){f.tickmode=\"linear\";var p=f.nticks||a.Lib.constrain(f._length/40,4,9);a.Axes.autoTicks(f,Math.abs(f.range[1]-f.range[0])/p)}for(var d=a.Axes.calcTicks(f),g=0;g<d.length;++g)d[g].x=d[g].x*t.dataScale[c],d[g].text=o(d[g].text);u[c]=d,f.tickmode=h}}e.ticks=u;for(var c=0;3>c;++c){l[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(var g=0;2>g;++g)e.bounds[g][c]=t.glplot.bounds[g][c]}t.contourLevels=n(u)}e.exports=i;var a=t(\"../../../plotly\"),o=t(\"../../../lib/html2unicode\"),s=[\"xaxis\",\"yaxis\",\"zaxis\"],l=[0,0,0]},{\"../../../lib/html2unicode\":577,\"../../../plotly\":595}],638:[function(t,e,r){\"use strict\";function n(t,e){var r,n,i=[0,0,0,0];for(r=0;4>r;++r)for(n=0;4>n;++n)i[n]+=t[4*r+n]*e[r];return i}function i(t,e){var r=n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])));return r}e.exports=i},{}],639:[function(t,e,r){\"use strict\";function n(t){function e(e,r){if(void 0!==r){if(\"string\"==typeof r)return r;var n=t.fullSceneLayout[e];return p.tickText(n,n.c2l(r),\"hover\").text}}var r=t.svgContainer,n=t.container.getBoundingClientRect(),i=n.width,a=n.height;r.setAttributeNS(null,\"viewBox\",\"0 0 \"+i+\" \"+a),r.setAttributeNS(null,\"width\",i),r.setAttributeNS(null,\"height\",a),w(t),t.glplot.axes.update(t.axesOptions);for(var o=Object.keys(t.traces),s=null,l=t.glplot.selection,u=0;u<o.length;++u){var c=t.traces[o[u]];c.handlePick(l)&&(s=c),c.setContourLevels&&c.setContourLevels()}if(null!==s){var f=y(t.glplot.cameraParams,l.dataCoordinate),h=s.data.hoverinfo;if(\"all\"!==h){var g=h.split(\"+\");-1===g.indexOf(\"x\")&&(l.traceCoordinate[0]=void 0),-1===g.indexOf(\"y\")&&(l.traceCoordinate[1]=void 0),-1===g.indexOf(\"z\")&&(l.traceCoordinate[2]=void 0),-1===g.indexOf(\"text\")&&(l.textLabel=void 0),-1===g.indexOf(\"name\")&&(s.name=void 0)}d.loneHover({x:(.5+.5*f[0]/f[3])*i,y:(.5-.5*f[1]/f[3])*a,xLabel:e(\"xaxis\",l.traceCoordinate[0]),yLabel:e(\"yaxis\",l.traceCoordinate[1]),zLabel:e(\"zaxis\",l.traceCoordinate[2]),text:l.textLabel,name:s.name,color:s.color},{container:r})}else d.loneUnhover(r)}function i(t,e,r,i){var a={canvas:r,gl:i,container:t.container,axes:t.axesOptions,spikes:t.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1};if(t.staticMode){if(!u){l=document.createElement(\"canvas\");try{u=l.getContext(\"webgl\",{preserveDrawingBuffer:!0,premultipliedAlpha:!0})}catch(o){throw new Error(\"error creating static canvas/context for image server\")}}a.pixelRatio=t.pixelRatio,a.gl=u,a.canvas=l}try{t.glplot=c(a)}catch(o){v(t)}if(t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",function(t){console.log(\"lost context\"),t.preventDefault()}),!t.camera){var s=e.scene.camera;t.camera=m(t.container,{center:[s.center.x,s.center.y,s.center.z],eye:[s.eye.x,s.eye.y,s.eye.z],up:[s.up.x,s.up.y,s.up.z],zoomMin:.1,zoomMax:100,mode:\"orbit\"})}return t.glplot.mouseListener.enabled=!1,t.glplot.camera=t.camera,t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=n.bind(null,t),t.traces={},!0}function a(t,e){var r=document.createElement(\"div\"),n=t.container,a=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\",r.appendChild(a),this.svgContainer=a,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.plotArgs=[[],{},{}],this.axesOptions=x(e[this.id]),this.spikeOptions=_(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],!i(this,e)}function o(t,e,r,n){for(var i=0;i<e.length;++i)if(Array.isArray(e[i]))for(var a=0;a<e[i].length;++a){var o=t.d2l(e[i][a]);!isNaN(o)&&isFinite(o)&&(n[0][r]=Math.min(n[0][r],o),n[1][r]=Math.max(n[1][r],o))}else{var 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r=e._size,n=JSON.stringify(r),i=Math.max(e.margin.l||0,0),a=Math.max(e.margin.r||0,0),o=Math.max(e.margin.t||0,0),l=Math.max(e.margin.b||0,0),c=e._pushmargin;return e.margin.autoexpand!==!1&&(c.base={l:{val:0,size:i},r:{val:1,size:a},t:{val:1,size:o},b:{val:0,size:l}},Object.keys(c).forEach(function(t){var r=c[t].l||{},n=c[t].b||{},s=r.val,f=r.size,h=n.val,p=n.size;Object.keys(c).forEach(function(t){if(u(f)&&c[t].r){var r=c[t].r.val,n=c[t].r.size;if(r>s){var d=(f*r+(n-e.width)*s)/(r-s),g=(n*(1-s)+(f-e.width)*(1-r))/(r-s);d>=0&&g>=0&&d+g>i+a&&(i=d,a=g)}}if(u(p)&&c[t].t){var v=c[t].t.val,m=c[t].t.size;if(v>h){var y=(p*v+(m-e.height)*h)/(v-h),b=(m*(1-h)+(p-e.height)*(1-v))/(v-h);y>=0&&b>=0&&y+b>l+o&&(l=y,o=b)}}})})),r.l=Math.round(i),r.r=Math.round(a),r.t=Math.round(o),r.b=Math.round(l),r.p=Math.round(e.margin.pad),r.w=Math.round(e.width)-r.l-r.r,r.h=Math.round(e.height)-r.t-r.b,t._replotting||\"{}\"===n||n===JSON.stringify(e._size)?void 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i=t(\"../cartesian/layout_attributes\"),a=t(\"../../lib/extend\").extendFlat,o=a({},i.domain,{});e.exports={radialaxis:n(\"radial\",{range:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},domain:o,orientation:{valType:\"number\"}}),angularaxis:n(\"angular\",{range:{valType:\"info_array\",items:[{valType:\"number\",dflt:0},{valType:\"number\",dflt:360}]},domain:o}),layout:{direction:{valType:\"enumerated\",values:[\"clockwise\",\"counterclockwise\"]},orientation:{valType:\"angle\"}}}},{\"../../lib/extend\":574,\"../cartesian/layout_attributes\":605}],645:[function(t,e,r){var n=t(\"../../plotly\"),i=t(\"d3\"),a=e.exports={version:\"0.2.2\",manager:t(\"./micropolar_manager\")},o=n.Lib.extendDeepAll;a.Axis=function(){function t(t){r=t||r;var u=l.data,f=l.layout;return(\"string\"==typeof r||r.nodeName)&&(r=i.select(r)),r.datum(u).each(function(t,r){function l(t,e){return s(t)%360+f.orientation}var u=t.slice();c={data:a.util.cloneJson(u),layout:a.util.cloneJson(f)};var h=0;u.forEach(function(t,e){t.color||(t.color=f.defaultColorRange[h],h=(h+1)%f.defaultColorRange.length),t.strokeColor||(t.strokeColor=\"LinePlot\"===t.geometry?t.color:i.rgb(t.color).darker().toString()),c.data[e].color=t.color,c.data[e].strokeColor=t.strokeColor,c.data[e].strokeDash=t.strokeDash,c.data[e].strokeSize=t.strokeSize});var p=u.filter(function(t,e){var r=t.visible;return\"undefined\"==typeof r||r===!0}),d=!1,g=p.map(function(t,e){return d=d||\"undefined\"!=typeof t.groupId,t});if(d){var v=i.nest().key(function(t,e){return\"undefined\"!=typeof t.groupId?t.groupId:\"unstacked\"}).entries(g),m=[],y=v.map(function(t,e){if(\"unstacked\"===t.key)return t.values;var r=t.values[0].r.map(function(t,e){return 0});return t.values.forEach(function(t,e,n){t.yStack=[r],m.push(r),r=a.util.sumArrays(t.r,r)}),t.values});p=i.merge(y)}p.forEach(function(t,e){t.t=Array.isArray(t.t[0])?t.t:[t.t],t.r=Array.isArray(t.r[0])?t.r:[t.r]});var b=Math.min(f.width-f.margin.left-f.margin.right,f.height-f.margin.top-f.margin.bottom)/2;b=Math.max(10,b);var x,_=[f.margin.left+b,f.margin.top+b];if(d){var w=i.max(a.util.sumArrays(a.util.arrayLast(p).r[0],a.util.arrayLast(m)));x=[0,w]}else x=i.extent(a.util.flattenArray(p.map(function(t,e){return t.r})));f.radialAxis.domain!=a.DATAEXTENT&&(x[0]=0),n=i.scale.linear().domain(f.radialAxis.domain!=a.DATAEXTENT&&f.radialAxis.domain?f.radialAxis.domain:x).range([0,b]),c.layout.radialAxis.domain=n.domain();var k,A=a.util.flattenArray(p.map(function(t,e){return t.t})),M=\"string\"==typeof A[0];M&&(A=a.util.deduplicate(A),k=A.slice(),A=i.range(A.length),p=p.map(function(t,e){var r=t;return t.t=[A],d&&(r.yStack=t.yStack),r}));var T=p.filter(function(t,e){return\"LinePlot\"===t.geometry||\"DotPlot\"===t.geometry}).length===p.length,E=null===f.needsEndSpacing?M||!T:f.needsEndSpacing,L=f.angularAxis.domain&&f.angularAxis.domain!=a.DATAEXTENT&&!M&&f.angularAxis.domain[0]>=0,S=L?f.angularAxis.domain:i.extent(A),C=Math.abs(A[1]-A[0]);T&&!M&&(C=0);var P=S.slice();E&&M&&(P[1]+=C);var z=f.angularAxis.ticksCount||4;z>8&&(z=z/(z/8)+z%8),f.angularAxis.ticksStep&&(z=(P[1]-P[0])/z);var R=f.angularAxis.ticksStep||(P[1]-P[0])/(z*(f.minorTicks+1));k&&(R=Math.max(Math.round(R),1)),P[2]||(P[2]=R);var O=i.range.apply(this,P);if(O=O.map(function(t,e){return parseFloat(t.toPrecision(12))}),s=i.scale.linear().domain(P.slice(0,2)).range(\"clockwise\"===f.direction?[0,360]:[360,0]),c.layout.angularAxis.domain=s.domain(),c.layout.angularAxis.endPadding=E?C:0,e=i.select(this).select(\"svg.chart-root\"),\"undefined\"==typeof e||e.empty()){var I=\"<svg xmlns='http://www.w3.org/2000/svg' class='chart-root'>' + '<g class='outer-group'>' + '<g class='chart-group'>' + '<circle class='background-circle'></circle>' + '<g class='geometry-group'></g>' + '<g class='radial axis-group'>' + '<circle class='outside-circle'></circle>' + '</g>' + '<g class='angular axis-group'></g>' + '<g class='guides-group'><line></line><circle r='0'></circle></g>' + '</g>' + '<g class='legend-group'></g>' + '<g class='tooltips-group'></g>' + '<g class='title-group'><text></text></g>' + '</g>' + '</svg>\",j=(new DOMParser).parseFromString(I,\"application/xml\"),N=this.appendChild(this.ownerDocument.importNode(j.documentElement,!0));e=i.select(N)}e.select(\".guides-group\").style({\"pointer-events\":\"none\"}),e.select(\".angular.axis-group\").style({\"pointer-events\":\"none\"}),e.select(\".radial.axis-group\").style({\"pointer-events\":\"none\"});var F,D=e.select(\".chart-group\"),B={fill:\"none\",stroke:f.tickColor},U={\"font-size\":f.font.size,\"font-family\":f.font.family,fill:f.font.color,\"text-shadow\":[\"-1px 0px\",\"1px -1px\",\"-1px 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q=F.node().getBBox();b=Math.min(f.width-q.width-f.margin.left-f.margin.right,f.height-f.margin.top-f.margin.bottom)/2,b=Math.max(10,b),_=[f.margin.left+b,f.margin.top+b],n.range([0,b]),c.layout.radialAxis.domain=n.domain(),F.attr(\"transform\",\"translate(\"+[_[0]+b,_[1]-b]+\")\")}else F=e.select(\".legend-group\").style({display:\"none\"});e.attr({width:f.width,height:f.height}).style({opacity:f.opacity}),D.attr(\"transform\",\"translate(\"+_+\")\").style({cursor:\"crosshair\"});var H=[(f.width-(f.margin.left+f.margin.right+2*b+(q?q.width:0)))/2,(f.height-(f.margin.top+f.margin.bottom+2*b))/2];if(H[0]=Math.max(0,H[0]),H[1]=Math.max(0,H[1]),e.select(\".outer-group\").attr(\"transform\",\"translate(\"+H+\")\"),f.title){var G=e.select(\"g.title-group text\").style(U).text(f.title),Y=G.node().getBBox();G.attr({x:_[0]-Y.width/2,y:_[1]-b-20})}var X=e.select(\".radial.axis-group\");if(f.radialAxis.gridLinesVisible){var W=X.selectAll(\"circle.grid-circle\").data(n.ticks(5));W.enter().append(\"circle\").attr({\"class\":\"grid-circle\"}).style(B),W.attr(\"r\",n),W.exit().remove()}X.select(\"circle.outside-circle\").attr({r:b}).style(B);var Z=e.select(\"circle.background-circle\").attr({r:b}).style({fill:f.backgroundColor,stroke:f.stroke});if(f.radialAxis.visible){var $=i.svg.axis().scale(n).ticks(5).tickSize(5);X.call($).attr({transform:\"rotate(\"+f.radialAxis.orientation+\")\"}),X.selectAll(\".domain\").style(B),X.selectAll(\"g>text\").text(function(t,e){return this.textContent+f.radialAxis.ticksSuffix}).style(U).style({\"text-anchor\":\"start\"}).attr({x:0,y:0,dx:0,dy:0,transform:function(t,e){return\"horizontal\"===f.radialAxis.tickOrientation?\"rotate(\"+-f.radialAxis.orientation+\") translate(\"+[0,U[\"font-size\"]]+\")\":\"translate(\"+[0,U[\"font-size\"]]+\")\"}}),X.selectAll(\"g>line\").style({stroke:\"black\"})}var K=e.select(\".angular.axis-group\").selectAll(\"g.angular-tick\").data(O),Q=K.enter().append(\"g\").classed(\"angular-tick\",!0);K.attr({transform:function(t,e){return\"rotate(\"+l(t,e)+\")\"}}).style({display:f.angularAxis.visible?\"block\":\"none\"}),K.exit().remove(),Q.append(\"line\").classed(\"grid-line\",!0).classed(\"major\",function(t,e){return e%(f.minorTicks+1)==0}).classed(\"minor\",function(t,e){return!(e%(f.minorTicks+1)==0)}).style(B),Q.selectAll(\".minor\").style({stroke:f.minorTickColor}),K.select(\"line.grid-line\").attr({x1:f.tickLength?b-f.tickLength:0,x2:b}).style({display:f.angularAxis.gridLinesVisible?\"block\":\"none\"}),Q.append(\"text\").classed(\"axis-text\",!0).style(U);var J=K.select(\"text.axis-text\").attr({x:b+f.labelOffset,dy:\".35em\",transform:function(t,e){var r=l(t,e),n=b+f.labelOffset,i=f.angularAxis.tickOrientation;return\"horizontal\"==i?\"rotate(\"+-r+\" \"+n+\" 0)\":\"radial\"==i?270>r&&r>90?\"rotate(180 \"+n+\" 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n=i.select(this),o=n.style(\"fill\"),s=\"black\",l=n.style(\"opacity\")||1;if(n.attr({\"data-opacity\":l}),\"none\"!=o){n.attr({\"data-fill\":o}),s=i.hsl(o).darker().toString(),n.style({fill:s,opacity:1});var u={t:a.util.round(t[0]),r:a.util.round(t[1])};M&&(u.t=k[t[0]]);var c=\"t: \"+u.t+\", r: \"+u.r,f=this.getBoundingClientRect(),h=e.node().getBoundingClientRect(),p=[f.left+f.width/2-H[0]-h.left,f.top+f.height/2-H[1]-h.top];ht.config({color:s}).text(c),ht.move(p)}else o=n.style(\"stroke\"),n.attr({\"data-stroke\":o}),s=i.hsl(o).darker().toString(),n.style({stroke:s,opacity:1})}).on(\"mousemove.tooltip\",function(t,e){return 0!=i.event.which?!1:void(i.select(this).attr(\"data-fill\")&&ht.show())}).on(\"mouseout.tooltip\",function(t,e){ht.hide();var r=i.select(this),n=r.attr(\"data-fill\");n?r.style({fill:n,opacity:r.attr(\"data-opacity\")}):r.style({stroke:r.attr(\"data-stroke\"),opacity:r.attr(\"data-opacity\")})})}),h}var 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t},a.Legend=function(){function t(){var r=e.legendConfig,n=e.data.map(function(t,e){return[].concat(t).map(function(t,n){var i=o({},r.elements[e]);return i.name=t,i.color=[].concat(r.elements[e].color)[n],i})}),a=i.merge(n);a=a.filter(function(t,e){return r.elements[e]&&(r.elements[e].visibleInLegend||\"undefined\"==typeof r.elements[e].visibleInLegend)}),r.reverseOrder&&(a=a.reverse());var s=r.container;(\"string\"==typeof s||s.nodeName)&&(s=i.select(s));var l=a.map(function(t,e){return t.color}),u=r.fontSize,c=null==r.isContinuous?\"number\"==typeof a[0]:r.isContinuous,f=c?r.height:u*a.length,h=s.classed(\"legend-group\",!0),p=h.selectAll(\"svg\").data([0]),d=p.enter().append(\"svg\").attr({width:300,height:f+u,xmlns:\"http://www.w3.org/2000/svg\",\"xmlns:xlink\":\"http://www.w3.org/1999/xlink\",version:\"1.1\"});d.append(\"g\").classed(\"legend-axis\",!0),d.append(\"g\").classed(\"legend-marks\",!0);var g=i.range(a.length),v=i.scale[c?\"linear\":\"ordinal\"]().domain(g).range(l),m=i.scale[c?\"linear\":\"ordinal\"]().domain(g)[c?\"range\":\"rangePoints\"]([0,f]),y=function(t,e){var r=3*e;return\"line\"===t?\"M\"+[[-e/2,-e/12],[e/2,-e/12],[e/2,e/12],[-e/2,e/12]]+\"Z\":-1!=i.svg.symbolTypes.indexOf(t)?i.svg.symbol().type(t).size(r)():i.svg.symbol().type(\"square\").size(r)()};if(c){var b=p.select(\".legend-marks\").append(\"defs\").append(\"linearGradient\").attr({id:\"grad1\",x1:\"0%\",y1:\"0%\",x2:\"0%\",y2:\"100%\"}).selectAll(\"stop\").data(l);b.enter().append(\"stop\"),b.attr({offset:function(t,e){return e/(l.length-1)*100+\"%\"}}).style({\"stop-color\":function(t,e){return t}}),p.append(\"rect\").classed(\"legend-mark\",!0).attr({height:r.height,width:r.colorBandWidth,fill:\"url(#grad1)\"})}else{var x=p.select(\".legend-marks\").selectAll(\"path.legend-mark\").data(a);x.enter().append(\"path\").classed(\"legend-mark\",!0),x.attr({transform:function(t,e){return\"translate(\"+[u/2,m(e)+u/2]+\")\"},d:function(t,e){var r=t.symbol;return y(r,u)},fill:function(t,e){return v(e)}}),x.exit().remove()}var _=i.svg.axis().scale(m).orient(\"right\"),w=p.select(\"g.legend-axis\").attr({transform:\"translate(\"+[c?r.colorBandWidth:u,u/2]+\")\"}).call(_);return w.selectAll(\".domain\").style({fill:\"none\",stroke:\"none\"}),w.selectAll(\"line\").style({fill:\"none\",stroke:c?r.textColor:\"none\"}),w.selectAll(\"text\").style({fill:r.textColor,\"font-size\":r.fontSize}).text(function(t,e){return a[e].name}),t}var e=a.Legend.defaultConfig(),r=i.dispatch(\"hover\");return t.config=function(t){return arguments.length?(o(e,t),this):e},i.rebind(t,r,\"on\"),t},a.Legend.defaultConfig=function(t,e){var r={data:[\"a\",\"b\",\"c\"],legendConfig:{elements:[{symbol:\"line\",color:\"red\"},{symbol:\"square\",color:\"yellow\"},{symbol:\"diamond\",color:\"limegreen\"}],height:150,colorBandWidth:30,fontSize:12,container:\"body\",isContinuous:null,textColor:\"grey\",reverseOrder:!1}};return r},a.tooltipPanel=function(){var t,e,r,n={container:null,hasTick:!1,fontSize:12,color:\"white\",padding:5},s=\"tooltip-\"+a.tooltipPanel.uid++,l=10,u=function(){t=n.container.selectAll(\"g.\"+s).data([0]);var i=t.enter().append(\"g\").classed(s,!0).style({\"pointer-events\":\"none\",display:\"none\"});return r=i.append(\"path\").style({fill:\"white\",\"fill-opacity\":.9}).attr({d:\"M0 0\"}),e=i.append(\"text\").attr({dx:n.padding+l,dy:.3*+n.fontSize}),u};return u.text=function(a){var o=i.hsl(n.color).l,s=o>=.5?\"#aaa\":\"white\",c=o>=.5?\"black\":\"white\",f=a||\"\";e.style({fill:c,\"font-size\":n.fontSize+\"px\"}).text(f);var h=n.padding,p=e.node().getBBox(),d={fill:n.color,stroke:s,\"stroke-width\":\"2px\"},g=p.width+2*h+l,v=p.height+2*h;return r.attr({d:\"M\"+[[l,-v/2],[l,-v/4],[n.hasTick?0:l,0],[l,v/4],[l,v/2],[g,v/2],[g,-v/2]].join(\"L\")+\"Z\"}).style(d),t.attr({transform:\"translate(\"+[l,-v/2+2*h]+\")\"}),t.style({display:\"block\"}),u},u.move=function(e){return t?(t.attr({transform:\"translate(\"+[e[0],e[1]]+\")\"}).style({display:\"block\"}),u):void 0},u.hide=function(){return t?(t.style({display:\"none\"}),u):void 0},u.show=function(){return t?(t.style({display:\"block\"}),u):void 0},u.config=function(t){return o(n,t),u},u},a.tooltipPanel.uid=1,a.adapter={},a.adapter.plotly=function(){var t={};return t.convert=function(t,e){var r={};if(t.data&&(r.data=t.data.map(function(t,r){var n=o({},t),i=[[n,[\"marker\",\"color\"],[\"color\"]],[n,[\"marker\",\"opacity\"],[\"opacity\"]],[n,[\"marker\",\"line\",\"color\"],[\"strokeColor\"]],[n,[\"marker\",\"line\",\"dash\"],[\"strokeDash\"]],[n,[\"marker\",\"line\",\"width\"],[\"strokeSize\"]],[n,[\"marker\",\"symbol\"],[\"dotType\"]],[n,[\"marker\",\"size\"],[\"dotSize\"]],[n,[\"marker\",\"barWidth\"],[\"barWidth\"]],[n,[\"line\",\"interpolation\"],[\"lineInterpolation\"]],[n,[\"showlegend\"],[\"visibleInLegend\"]]];\n",
+       "return i.forEach(function(t,r){a.util.translator.apply(null,t.concat(e))}),e||delete n.marker,e&&delete n.groupId,e?(\"LinePlot\"===n.geometry?(n.type=\"scatter\",n.dotVisible===!0?(delete n.dotVisible,n.mode=\"lines+markers\"):n.mode=\"lines\"):\"DotPlot\"===n.geometry?(n.type=\"scatter\",n.mode=\"markers\"):\"AreaChart\"===n.geometry?n.type=\"area\":\"BarChart\"===n.geometry&&(n.type=\"bar\"),delete n.geometry):(\"scatter\"===n.type?\"lines\"===n.mode?n.geometry=\"LinePlot\":\"markers\"===n.mode?n.geometry=\"DotPlot\":\"lines+markers\"===n.mode&&(n.geometry=\"LinePlot\",n.dotVisible=!0):\"area\"===n.type?n.geometry=\"AreaChart\":\"bar\"===n.type&&(n.geometry=\"BarChart\"),delete n.mode,delete n.type),n}),!e&&t.layout&&\"stack\"===t.layout.barmode)){var n=a.util.duplicates(r.data.map(function(t,e){return t.geometry}));r.data.forEach(function(t,e){var i=n.indexOf(t.geometry);-1!=i&&(r.data[e].groupId=i)})}if(t.layout){var s=o({},t.layout),l=[[s,[\"plot_bgcolor\"],[\"backgroundColor\"]],[s,[\"showlegend\"],[\"showLegend\"]],[s,[\"radialaxis\"],[\"radialAxis\"]],[s,[\"angularaxis\"],[\"angularAxis\"]],[s.angularaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularaxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularaxis,[\"nticks\"],[\"ticksCount\"]],[s.angularaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularaxis,[\"range\"],[\"domain\"]],[s.angularaxis,[\"endpadding\"],[\"endPadding\"]],[s.radialaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialaxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularAxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularAxis,[\"nticks\"],[\"ticksCount\"]],[s.angularAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularAxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"endpadding\"],[\"endPadding\"]],[s.radialAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialAxis,[\"range\"],[\"domain\"]],[s.font,[\"outlinecolor\"],[\"outlineColor\"]],[s.legend,[\"traceorder\"],[\"reverseOrder\"]],[s,[\"labeloffset\"],[\"labelOffset\"]],[s,[\"defaultcolorrange\"],[\"defaultColorRange\"]]];if(l.forEach(function(t,r){a.util.translator.apply(null,t.concat(e))}),e?(\"undefined\"!=typeof s.tickLength&&(s.angularaxis.ticklen=s.tickLength,delete s.tickLength),s.tickColor&&(s.angularaxis.tickcolor=s.tickColor,delete s.tickColor)):(s.angularAxis&&\"undefined\"!=typeof s.angularAxis.ticklen&&(s.tickLength=s.angularAxis.ticklen),s.angularAxis&&\"undefined\"!=typeof s.angularAxis.tickcolor&&(s.tickColor=s.angularAxis.tickcolor)),s.legend&&\"boolean\"!=typeof s.legend.reverseOrder&&(s.legend.reverseOrder=\"normal\"!=s.legend.reverseOrder),s.legend&&\"boolean\"==typeof s.legend.traceorder&&(s.legend.traceorder=s.legend.traceorder?\"reversed\":\"normal\",delete s.legend.reverseOrder),s.margin&&\"undefined\"!=typeof s.margin.t){var u=[\"t\",\"r\",\"b\",\"l\",\"pad\"],c=[\"top\",\"right\",\"bottom\",\"left\",\"pad\"],f={};i.entries(s.margin).forEach(function(t,e){f[c[u.indexOf(t.key)]]=t.value}),s.margin=f}e&&(delete s.needsEndSpacing,delete s.minorTickColor,delete s.minorTicks,delete s.angularaxis.ticksCount,delete s.angularaxis.ticksCount,delete s.angularaxis.ticksStep,delete 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n=t(\"../../components/drawing\");t(\"./constants\");e.exports={x:{valType:\"data_array\"},x0:{valType:\"any\",dflt:0},dx:{valType:\"number\",dflt:1},y:{valType:\"data_array\"},y0:{valType:\"any\",dflt:0},dy:{valType:\"number\",dflt:1},text:{valType:\"string\",dflt:\"\",arrayOk:!0},mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],extras:[\"none\"]},line:{color:{valType:\"color\"},width:{valType:\"number\",\n",
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"min:0,dflt:2},shape:{valType:\"enumerated\",values:[\"linear\",\"spline\",\"hv\",\"vh\",\"hvh\",\"vhv\"],dflt:\"linear\"},smoothing:{valType:\"number\",min:0,max:1.3,dflt:1},dash:{valType:\"string\",values:[\"solid\",\"dot\",\"dash\",\"longdash\",\"dashdot\",\"longdashdot\"],dflt:\"solid\"}},connectgaps:{valType:\"boolean\",dflt:!1},fill:{valType:\"enumerated\",values:[\"none\",\"tozeroy\",\"tozerox\",\"tonexty\",\"tonextx\"],dflt:\"none\"},fillcolor:{valType:\"color\"},marker:{symbol:{valType:\"enumerated\",values:n.symbolList,dflt:\"circle\",arrayOk:!0},opacity:{valType:\"number\",min:0,max:1,arrayOk:!0},size:{valType:\"number\",min:0,dflt:6,arrayOk:!0},color:{valType:\"color\",arrayOk:!0},maxdisplayed:{valType:\"number\",min:0,dflt:0},sizeref:{valType:\"number\",dflt:1},sizemin:{valType:\"number\",min:0,dflt:0},sizemode:{valType:\"enumerated\",values:[\"diameter\",\"area\"],dflt:\"diameter\"},colorscale:{valType:\"colorscale\"},cauto:{valType:\"boolean\",dflt:!0},cmax:{valType:\"number\",dflt:null},cmin:{valType:\"number\",dflt:null},autocolorscale:{valType:\"boolean\",dflt:!0},reversescale:{valType:\"boolean\",dflt:!1},showscale:{valType:\"boolean\",dflt:!1},line:{color:{valType:\"color\",arrayOk:!0},width:{valType:\"number\",min:0,arrayOk:!0},colorscale:{valType:\"colorscale\"},cauto:{valType:\"boolean\",dflt:!0},cmax:{valType:\"number\",dflt:null},cmin:{valType:\"number\",dflt:null},autocolorscale:{valType:\"boolean\",dflt:!0},reversescale:{valType:\"boolean\",dflt:!1}}},textposition:{valType:\"enumerated\",values:[\"top 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r=e[0].trace,u=r.marker,c=\"cb\"+r.uid;if(t._fullLayout._infolayer.selectAll(\".\"+c).remove(),void 0===u||!u.showscale)return void o.autoMargin(t,c);var f=s(u.colorscale),h=u.color,p=u.cmin,d=u.cmax;i(p)||(p=a.aggNums(Math.min,null,h)),i(d)||(d=a.aggNums(Math.max,null,h));var g=e[0].t.cb=l(t,c);g.fillcolor(n.scale.linear().domain(f.map(function(t){return p+t[0]*(d-p)})).range(f.map(function(t){return t[1]}))).filllevels({start:p,end:d,size:(d-p)/254}).options(u.colorbar)(),a.markTime(\"done colorbar\")}},{\"../../components/colorbar/draw\":532,\"../../components/colorscale/get_scale\":540,\"../../lib\":578,\"../../plots/plots\":642,d3:320,\"fast-isnumeric\":324}],735:[function(t,e,r){\"use strict\";e.exports={PTS_LINESONLY:20}},{}],736:[function(t,e,r){\"use strict\";function n(t,e,r){var n=r(\"line.shape\");\"spline\"===n&&r(\"line.smoothing\")}var i=t(\"../../lib\"),a=t(\"./attributes\"),o=t(\"./constants\"),s=t(\"./subtypes\"),l=t(\"./xy_defaults\"),u=t(\"./marker_defaults\"),c=t(\"./line_defaults\"),f=t(\"./text_defaults\"),h=t(\"./fillcolor_defaults\"),p=t(\"../../components/errorbars/defaults\");e.exports=function(t,e,r,d){function g(r,n){return i.coerce(t,e,a,r,n)}var v=l(t,e,g),m=v<o.PTS_LINESONLY?\"lines+markers\":\"lines\";return v?(g(\"text\"),g(\"mode\",m),s.hasLines(e)&&(c(t,e,r,g),n(t,e,g),g(\"connectgaps\")),s.hasMarkers(e)&&u(t,e,r,d,g),s.hasText(e)&&f(t,e,d,g),(s.hasMarkers(e)||s.hasText(e))&&g(\"marker.maxdisplayed\"),g(\"fill\"),\"none\"!==e.fill&&(h(t,e,r,g),s.hasLines(e)||n(t,e,g)),p(t,e,r,{axis:\"y\"}),void 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a=o&&n.opacity(o)?o:s&&n.opacity(s)&&(e.mlw||((t.marker||{}).line||{}).width)?s:\"\",a?n.opacity(a)<.3?n.addOpacity(a,.3):a:(r=(t.line||{}).color,r&&n.opacity(r)&&i.hasLines(t)&&t.line.width?r:t.fillcolor)}},{\"../../components/color\":529,\"./subtypes\":749}],739:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/graph_interact\"),i=t(\"../../components/errorbars\"),a=t(\"./get_trace_color\");e.exports=function(t,e,r,o){var s=t.cd,l=s[0].trace,u=t.xa,c=t.ya,f=function(t){var r=Math.max(3,t.mrc||0);return Math.max(Math.abs(u.c2p(t.x)-u.c2p(e))-r,1-3/r)},h=function(t){var e=Math.max(3,t.mrc||0);return Math.max(Math.abs(c.c2p(t.y)-c.c2p(r))-e,1-3/e)},p=function(t){var n=Math.max(3,t.mrc||0),i=Math.abs(u.c2p(t.x)-u.c2p(e)),a=Math.abs(c.c2p(t.y)-c.c2p(r));return Math.max(Math.sqrt(i*i+a*a)-n,1-3/n)},d=n.getDistanceFunction(o,f,h,p);if(n.getClosest(s,d,t),t.index!==!1){var g=s[t.index],v=u.c2p(g.x,!0),m=c.c2p(g.y,!0),y=g.mrc||1;return 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h=i(l.position,l.delaunayColor,l.delaunayAxis);this.delaunayMesh?this.delaunayMesh.update(h):(h.gl=o,this.delaunayMesh=v(h),this.scene.glplot.add(this.delaunayMesh))}else this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose(),this.delaunayMesh=null)},M.dispose=function(){this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose()),this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose()),this.errorBars&&(this.scene.remove(this.errorBars),this.errorBars.dispose()),this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose()),this.delaunayMesh&&(this.scene.glplot.remove(this.textMarkers),this.delaunayMesh.dispose())},e.exports=h},{\"../../constants/gl3d_dashes\":565,\"../../constants/gl_markers\":566,\"../../lib\":578,\"../../lib/gl_format_color\":576,\"../../lib/str2rgbarray\":588,\"../scatter/make_bubble_size_func\":743,\"./calc_errors\":754,\"delaunay-triangulate\":321,\"gl-error3d\":328,\"gl-line3d\":334,\"gl-mesh3d\":356,\"gl-scatter3d\":381}],756:[function(t,e,r){\"use strict\";function n(t,e,r){var n=0,i=r(\"x\"),a=r(\"y\"),o=r(\"z\");return i&&a&&o&&(n=Math.min(i.length,a.length,o.length),n<i.length&&(e.x=i.slice(0,n)),n<a.length&&(e.y=a.slice(0,n)),n<o.length&&(e.z=o.slice(0,n))),n}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"../../components/errorbars/defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,f){function h(r,n){return i.coerce(t,e,c,r,n)}var p=n(t,e,h);if(!p)return void(e.visible=!1);h(\"text\"),h(\"mode\"),a.hasLines(e)&&s(t,e,r,h),a.hasMarkers(e)&&o(t,e,r,f,h),a.hasText(e)&&l(t,e,f,h);var d=(e.line||{}).color,g=(e.marker||{}).color;h(\"surfaceaxis\")>=0&&h(\"surfacecolor\",d||g);for(var v=[\"x\",\"y\",\"z\"],m=0;3>m;++m){var y=\"projection.\"+v[m];h(y+\".show\")&&(h(y+\".opacity\"),h(y+\".scale\"))}u(t,e,r,{axis:\"z\"}),u(t,e,r,{axis:\"y\",inherit:\"z\"}),u(t,e,r,{axis:\"x\",inherit:\"z\"})}},{\"../../components/errorbars/defaults\":552,\"../../lib\":578,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/text_defaults\":750,\"./attributes\":752}],757:[function(t,e,r){\"use strict\";var n={};n.plot=t(\"./convert\"),n.attributes=t(\"./attributes\"),n.markerSymbols=t(\"../../constants/gl_markers\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.moduleType=\"trace\",n.name=\"scatter3d\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../constants/gl_markers\":566,\"../../plots/gl3d\":629,\"../scatter/colorbar\":734,\"./attributes\":752,\"./calc\":753,\"./convert\":755,\"./defaults\":756}],758:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../lib/extend\").extendFlat,o=n.marker,s=n.line,l=o.line;e.exports={lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country names\"],dflt:\"ISO-3\"},mode:a({},n.mode,{dflt:\"markers\"}),text:a({},n.text,{}),line:{color:s.color,width:s.width,dash:s.dash},marker:{symbol:o.symbol,opacity:o.opacity,size:o.size,sizeref:o.sizeref,sizemin:o.sizemin,sizemode:o.sizemode,color:o.color,colorscale:o.colorscale,cauto:o.cauto,cmax:o.cmax,cmin:o.cmin,autocolorscale:o.autocolorscale,reversescale:o.reversescale,showscale:o.showscale,line:{color:l.color,width:l.width,colorscale:l.colorscale,cauto:l.cauto,cmax:l.cmax,cmin:l.cmin,autocolorscale:l.autocolorscale,reversescale:l.reversescale}},textfont:n.textfont,textposition:n.textposition,hoverinfo:a({},i.hoverinfo,{flags:[\"lon\",\"lat\",\"location\",\"text\",\"name\"]}),_nestedModules:{\"marker.colorbar\":\"Colorbar\"}}},{\"../../lib/extend\":574,\"../../plots/attributes\":596,\"../scatter/attributes\":731}],759:[function(t,e,r){\"use strict\";var n=t(\"../scatter/marker_colorscale_calc\");e.exports=function(t,e){var r=[{x:!1,y:!1,trace:e,t:{}}];return n(e),r}},{\"../scatter/marker_colorscale_calc\":744}],760:[function(t,e,r){\"use strict\";function n(t,e,r){var n,i,a=0,o=r(\"locations\");return o?(r(\"locationmode\"),a=o.length):(n=r(\"lon\")||[],i=r(\"lat\")||[],a=Math.min(n.length,i.length),a<n.length&&(e.lon=n.slice(0,a)),a<i.length&&(e.lat=i.slice(0,a)),a)}var i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),u=t(\"./attributes\");e.exports=function(t,e,r,c){function f(r,n){return i.coerce(t,e,u,r,n)}var h=n(t,e,f);return h?(f(\"text\"),f(\"mode\"),a.hasLines(e)&&s(t,e,r,f),a.hasMarkers(e)&&o(t,e,r,c,f),a.hasText(e)&&l(t,e,c,f),void f(\"hoverinfo\",1===c._dataLength?\"lon+lat+location+text\":void 0)):void(e.visible=!1)}},{\"../../lib\":578,\"../scatter/line_defaults\":741,\"../scatter/marker_defaults\":745,\"../scatter/subtypes\":749,\"../scatter/text_defaults\":750,\"./attributes\":758}],761:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../scatter/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./plot\").plot,n.moduleType=\"trace\",n.name=\"scattergeo\",n.basePlotModule=t(\"../../plots/geo\"),n.categories=[\"geo\",\"symbols\",\"markerColorscale\",\"showLegend\"],n.meta={},e.exports=n},{\"../../plots/geo\":614,\"../scatter/colorbar\":734,\"./attributes\":758,\"./calc\":759,\"./defaults\":760,\"./plot\":762}],762:[function(t,e,r){\"use strict\";function n(t,e,r){function n(t,n){h(t,e,n,r)}var i=t.marker;if(n(t.text,\"tx\"),n(t.textposition,\"tp\"),t.textfont&&(n(t.textfont.size,\"ts\"),n(t.textfont.color,\"tc\"),n(t.textfont.family,\"tf\")),i&&i.line){var a=i.line;n(i.opacity,\"mo\"),n(i.symbol,\"mx\"),n(i.color,\"mc\"),n(i.size,\"ms\"),n(a.color,\"mlc\"),n(a.width,\"mlw\")}}function i(t){for(var e=t.lon.length,r=new Array(e),n=0;e>n;n++)r[n]=[t.lon[n],t.lat[n]];return{type:\"LineString\",coordinates:r,trace:t}}function a(t,e){function r(e){var r=t.mockAxis;return u.tickText(r,r.c2l(e),\"hover\").text+\"\\xb0\"}var n=e.hoverinfo;if(\"none\"===n)return function(t){delete t.textLabel};var i=\"all\"===n?v.hoverinfo.flags:n.split(\"+\"),a=-1!==i.indexOf(\"location\")&&Array.isArray(e.locations),o=-1!==i.indexOf(\"lon\"),s=-1!==i.indexOf(\"lat\"),l=-1!==i.indexOf(\"text\");return function(t){var n=[];a?n.push(t.location):o&&s?n.push(\"(\"+r(t.lon)+\", \"+r(t.lat)+\")\"):o?n.push(\"lon: \"+r(t.lon)):s&&n.push(\"lat: \"+r(t.lat)),l&&n.push(t.tx||e.text),t.textLabel=n.join(\"<br>\")}}function o(t){var e=Array.isArray(t.locations);return function(r,n){return{points:[{data:t._input,fullData:t,curveNumber:t.index,pointNumber:n,lon:r.lon,lat:r.lat,location:e?r.location:null}]}}}var s=t(\"d3\"),l=t(\"../../plots/cartesian/graph_interact\"),u=t(\"../../plots/cartesian/axes\"),c=t(\"../../lib/topojson_utils\").getTopojsonFeatures,f=t(\"../../lib/geo_location_utils\").locationToFeature,h=t(\"../../lib/array_to_calc_item\"),p=t(\"../../components/color\"),d=t(\"../../components/drawing\"),g=t(\"../scatter/subtypes\"),v=t(\"./attributes\"),m=e.exports={};m.calcGeoJSON=function(t,e){var r,i,a,o,s=[],l=Array.isArray(t.locations);l?(o=t.locations,r=o.length,i=c(t,e),a=function(t,e){var r=f(t.locationmode,o[e],i);return void 0!==r?r.properties.ct:void 0}):(r=t.lon.length,a=function(t,e){return[t.lon[e],t.lat[e]]});for(var u=0;r>u;u++){var h=a(t,u);if(h){var p={lon:h[0],lat:h[1],location:l?t.locations[u]:null};n(t,p,u),s.push(p)}}return s.length>0&&(s[0].trace=t),s},m.plot=function(t,e){var r=t.framework.select(\".scattergeolayer\").selectAll(\"g.trace.scattergeo\").data(e,function(t){return t.uid});r.enter().append(\"g\").attr(\"class\",\"trace 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n=this.scene.fullSceneLayout;t.dataCoordinate=[n.xaxis.d2l(r[0])*this.scene.dataScale[0],n.yaxis.d2l(r[1])*this.scene.dataScale[1],n.zaxis.d2l(r[2])*this.scene.dataScale[2]];var i=this.data.text;return i&&i[e[1]]&&void 0!==i[e[1]][e[0]]?t.textLabel=i[e[1]][e[0]]:t.textLabel=\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}},v.setContourLevels=function(){for(var t=[[],[],[]],e=!1,r=0;3>r;++r)this.showContour[r]&&(e=!0,t[r]=this.scene.contourLevels[r]);e&&this.surface.update({levels:t})},v.update=function(t){var e,r=this.scene,n=r.fullSceneLayout,a=this.surface,s=t.opacity,l=i(t.colorscale,s),c=t.z,h=t.x,p=t.y,g=n.xaxis,v=n.yaxis,m=n.zaxis,y=r.dataScale,b=c[0].length,x=c.length,_=[u(new Float32Array(b*x),[b,x]),u(new Float32Array(b*x),[b,x]),u(new Float32Array(b*x),[b,x])],w=_[0],k=_[1],A=r.contourLevels;this.data=t,f(_[2],function(t,e){return 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t&&(a.ambientLight=t.lighting.ambient,a.diffuseLight=t.lighting.diffuse,a.specularLight=t.lighting.specular,a.roughness=t.lighting.roughness,a.fresnel=t.lighting.fresnel),s&&1>s&&(a.supportsTransparency=!0)},v.dispose=function(){this.glplot.remove(this.surface),this.surface.dispose()},e.exports=s},{\"../../lib/str2rgbarray\":588,\"gl-surface3d\":415,ndarray:438,\"ndarray-fill\":431,\"ndarray-homography\":436,\"ndarray-ops\":437,tinycolor2:459}],770:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/colorscale/defaults\"),a=t(\"./attributes\");e.exports=function(t,e,r,o){function s(r,i){return n.coerce(t,e,a,r,i)}var l,u,c=s(\"z\");if(!c)return void(e.visible=!1);var f=c[0].length,h=c.length;if(s(\"x\"),s(\"y\"),!Array.isArray(e.x))for(e.x=[],l=0;f>l;++l)e.x[l]=l;if(s(\"text\"),!Array.isArray(e.y))for(e.y=[],l=0;h>l;++l)e.y[l]=l;s(\"lighting.ambient\"),s(\"lighting.diffuse\"),s(\"lighting.specular\"),s(\"lighting.roughness\"),s(\"lighting.fresnel\"),s(\"hidesurface\"),s(\"opacity\"),s(\"colorscale\");var p=[\"x\",\"y\",\"z\"];for(l=0;3>l;++l){var d=\"contours.\"+p[l],g=s(d+\".show\"),v=s(d+\".highlight\");if(g||v)for(u=0;3>u;++u)s(d+\".project.\"+p[u]);g&&(s(d+\".color\"),s(d+\".width\"),s(d+\".usecolormap\")),v&&(s(d+\".highlightColor\"),s(d+\".highlightWidth\"))}i(t,e,o,s,{prefix:\"\",cLetter:\"z\"})}},{\"../../components/colorscale/defaults\":538,\"../../lib\":578,\"./attributes\":767}],771:[function(t,e,r){\"use strict\";var n={};n.attributes=t(\"./attributes\"),n.supplyDefaults=t(\"./defaults\"),n.colorbar=t(\"../heatmap/colorbar\"),n.calc=t(\"./calc\"),n.plot=t(\"./convert\"),n.moduleType=\"trace\",n.name=\"surface\",n.basePlotModule=t(\"../../plots/gl3d\"),n.categories=[\"gl3d\",\"noOpacity\"],n.meta={},e.exports=n},{\"../../plots/gl3d\":629,\"../heatmap/colorbar\":690,\"./attributes\":767,\"./calc\":768,\"./convert\":769,\"./defaults\":770}]},{},[262])(262)});\n",
+       "</script>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "% matplotlib inline\n",
+    "import pandas as pd\n",
+    "import json\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import time\n",
+    "from datetime import datetime\n",
+    "\n",
+    "#for matplotlib maps\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets\n",
+    "import matplotlib.cm as cm\n",
+    "\n",
+    "#for animation maps\n",
+    "from matplotlib import animation\n",
+    "from IPython.display import HTML\n",
+    "from tempfile import NamedTemporaryFile\n",
+    "\n",
+    "#for the node graphs\n",
+    "import networkx as nx\n",
+    "\n",
+    "#for the node graphs maps\n",
+    "from mpl_toolkits.basemap import Basemap\n",
+    "import plotly.plotly as py\n",
+    "from plotly.graph_objs import *\n",
+    "py.sign_in('vpreston', 'tcx2wn8rfb')\n",
+    "\n",
+    "#making the visualizations interactive\n",
+    "from plotly.offline import download_plotlyjs, init_notebook_mode, iplot\n",
+    "from plotly.offline import plot\n",
+    "from plotly.graph_objs import Scatter\n",
+    "init_notebook_mode()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## What are Communities Anyway?\n",
+    "Within the world of network analysis, the term \"communities\" is used to describe the idea that people are connected to one another in a (social) pattern with certain, quanitifiable attributes which can be mapped. There are various methodologies for determining the presence of a community analytically - these techniques often use the concepts of centrality, classifying, connectivity, and many more to identify subgroups. These communities can also be qualitatively observed through a data visualization technique called network node-edge graphs."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## The Data to Visualize\n",
+    "Let's first grab data from the first dataset, herein the \"shooting\" dataset so named because the data is the first two weeks of twitter data related to the Ferguson shooting (and not the indictment)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def ReadToDf(linesAtATime,filepath, max=-1):\n",
+    "    start = time.time()\n",
+    "    df = pd.DataFrame()\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filepath) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print \"number of tweets parsed: \", i\n",
+    "                print \"total time elapsed: \", time.time() - start\n",
+    "                df = df.append(pd.DataFrame(data=data))\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "        #Allow us to handle the last few tweets, and to truncate the data if we just want to run unit tests\n",
+    "            if (max > 0 and i >= max):\n",
+    "                break\n",
+    "        df = pd.DataFrame(data=data).append(df)\n",
+    "    #return the aggregation\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "number of tweets parsed:  100000\n",
+      "total time elapsed:  5.09561610222\n",
+      "number of tweets parsed:  200000\n",
+      "total time elapsed:  10.4655101299\n",
+      "number of tweets parsed:  300000\n",
+      "total time elapsed:  16.2270290852\n",
+      "number of tweets parsed:  400000\n",
+      "total time elapsed:  22.7011840343\n",
+      "number of tweets parsed:  500000\n",
+      "total time elapsed:  29.3895611763\n"
+     ]
+    }
+   ],
+   "source": [
+    "df = ReadToDf(100000, 'data/cleanedShootingTweets.json',max=500000)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order to later do some interesting network mapping, we will recode the `coordinate` and `place` columns into true latitude and longitude values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def get_coordinates(x):\n",
+    "    try:\n",
+    "        res = x.get('coordinates')\n",
+    "    except:\n",
+    "        res = [None,None]\n",
+    "    return res\n",
+    "\n",
+    "def get_place(x):\n",
+    "    try:\n",
+    "        box = x.get('coordinates')\n",
+    "        mean_coord_x = (box[0][0][0]+box[0][1][0]+box[0][2][0]+box[0][3][0])/4\n",
+    "        mean_coord_y = (box[0][0][1]+box[0][1][1]+box[0][2][1]+box[0][3][1])/4\n",
+    "        res = [mean_coord_x,mean_coord_y]\n",
+    "    except:\n",
+    "        res = [0,0]\n",
+    "    return res"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "df['Coords'] = df['coordinates'].apply(get_coordinates)\n",
+    "df['P_Coords'] = df['place'].apply(get_place)\n",
+    "\n",
+    "df['x'] = df['Coords'].apply(lambda x: x[0])\n",
+    "df['y'] = df['Coords'].apply(lambda x: x[1])\n",
+    "\n",
+    "df['x_p'] = df['P_Coords'].apply(lambda x: x[0])\n",
+    "df['y_p'] = df['P_Coords'].apply(lambda x: x[1])\n",
+    "\n",
+    "df['x'].fillna(df['x_p'], inplace = True)\n",
+    "df['y'].fillna(df['y_p'], inplace = True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Building Context \n",
+    "The Ferguson Shooting refers to the shooting and killing of Michael Brown, a black teenager from the St. Louis suburb, by a white police officer, Darren Wilson. The event, one amongst recent slayings of black teenage men by white police, instilled local unrest and sparked a truly international conversation virtually. \n",
+    "\n",
+    "Twitter, as a social media utility, allows users to post 140 character messages to \"followers\" which are other users of the application which have elected to receive the posts of the original user. Hashtags, a quippy phrase marked with a pound sign, are used to flag the content of these messages. Further, messages can be \"retweeted.\" In this way Twitter is an exciting social media source to analyze for networks and information propogation flow. \n",
+    "\n",
+    "Using hashtags as a means of sorting tweets to visualize them may yield compelling results. Further, understanding geographic information flow may also yield interesting patterns."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Information Propogation\n",
+    "Let's begin with a visualization that simply maps out a network of users."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For ease of data handling, we create a new dataframe which contains the information we care about including location, user identity, retweeter identity, and the hashtags used."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "creating dataframe\n"
+     ]
+    }
+   ],
+   "source": [
+    "retweetRows = []\n",
+    "for i,tweet in df.iterrows():\n",
+    "    for retweeter in tweet['entities_user_mentions_screen_name']:\n",
+    "        mappeduser = retweeter.upper()\n",
+    "        retweetRows.append({\n",
+    "                'retweeter': mappeduser,\n",
+    "                'tweetId': tweet['user_screen_name'].upper(),\n",
+    "                'x': tweet['x'],\n",
+    "                'y': tweet['y'],\n",
+    "                'retweet_count': tweet['retweet_count'],\n",
+    "                'entities_hashtags_text': tweet['entities_hashtags_text'],\n",
+    "            })\n",
+    "print \"creating dataframe\"\n",
+    "retweetDf = pd.DataFrame(retweetRows)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Using the networkx package and matplotlib, we can quickly get a sense of the tweet network."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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iei1L/rY2NQ8Pa8fOnSovL1/pbi6Ibdtyufg8FAAQ25hzBwBYNnO3EegNh1WyyhZVmXXj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UKBAMUVFSwaDBw8fJiurq7NLvKmSCaTeL1eQqEQtuUU5fdZSDyfzzM+Po7ZbKaqquoJlvTe8vk8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\nbqdQKhEdHkYRjTIyNMTOri6yev19B5tisRgzMzN0d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ZWVlYTDYUKhECaTCUmSNhVgwa1s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\nQf/3v8+XPvMZvDdukLbbeelThVTOnTtHoVBgeHAQtV5PrqICRSzGJ5cu4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fdWQE2trQNI3irq51fx6mY4tGItTImjshNqTnSu50Ol0x8FdAHTAC/KqmaeGH/NwIEAZUYEnT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\n/w3dFH82aiATDwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8ed88b1a10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,15))\n",
+    "\n",
+    "G=nx.from_pandas_dataframe(retweetDf[0:1000:], source='tweetId',target='retweeter')\n",
+    "\n",
+    "nx.draw_networkx(G,alpha=0.2,font_size=0, node_size=10)\n",
+    "plt.title('First 1000 Tweets')\n",
+    "plt.axis('equal')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Central to this graph layout is the largest connected network. Clusters imply closely related users and terminations in the transmission chain. The ring of small chains shows a disconnect from the central network. Given that this is an extremely small subset of the data, and consecutive, it perceptively makes sense that there would be a large central network - the event needs to be communicated in some way, and whomever breaks the news would be likely to be retweeted. \n",
+    "\n",
+    "Sampling thus is extremely important for drawing networks. To compare, look at this network graph of non-consecutive tweets:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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hOLeIiCxNlmVRV1uLZVkPuioiIiIRIXqBzpMPeMd8Xz/6s6YFOr+IiCwilmXhPXaMTIcD\nbyAA27bhcrkedLVERESWtIUKdzPy9a9//e7Xe/bsYc+ePQ+sLiIiEn5dfj8ZxjDY14c7NpYuv/+h\nDXeWZdHl95PsdD6090BE5GH34Ycf8uGHH865HGPb9txrAxhjioGf27b9yATbvgN8YNv2a6PfXwN2\n27Z9X8udMcYOV51ERGRx8Xg8JCQk0N7eznBdHdWXLxOXkUHuhg0UFhZSXFyM0+l80NVcEIFAAL/f\nT82RI7iNod0YCtWCKSIigDEG27bNTI8LZ8udGf0zkZ8Bvw+8Zox5HLAmCnYiIhLZdu3adffr2tpa\nEpctY/mKFRQWFob1PEuhNezgwYNse/xxWs6eJTYqivzcXC6cO8eueeqtshTuiYiIzE1YWu6MMT8A\n9gBuRsbR/QcgFrBt2/6b0X3+Evgk0A38a9u2z05SllruREQeEhcuXIBAgKKSkrAFDp/PR/2JE7iB\nNljUrWGWZXHxrbdwDg3hyMiYl7palkW910vrhQusysigJRBY1PdERERm33IXtm6Z4aJwJyLycPD5\nfFz6l38hMyqKIadzzoHjwIEDPPXUUzTducPQzZsM9fWR7HQSvWoVn/zUp8JY8/C6du0aXZ2drFi5\ncl6C3Q//4i+I7uykpbqaR3fupGdgAHvZMr7w/PNhPZeIiITPYuiWKSIiC2ipd7N7/733iL5zB5Oa\nCp2dpM1xUpWXXnoJGLkvt6Kj6WtoIKW4mMJt28JV5XmRmJiI2+0O62vo8XhwOBw0NTZSlpFBX0oK\nvW1t5KWng9u96O+JiIjMjlruRESWkOAkHLW3b3P76FHKs7PpS0xckt3sxi6HEO6ugm1tbZw+eZKK\nJXBfqqqqwh7ugsbe4yq/H9fq1eQXFi76eyIi8rBTy52IyEPgrbfeovnyZS6cPk2+w0HzihVkpKVx\no7ub57/4xQddvRlxuVywbRtdfj+FYW59dLvdZGRlzbjMB9EaOjg4SExMzLyUPfYer12iLbwiIhI6\nhTsRkSXA4/FgjKG3p4e0qCg+vWcPP3/zTTKMoXTNmiXbzc7lcs1b4HA4HAwPDxMVFTXlfoFAAIfD\n8cAWVm9rayMmKgp3Zua8nG8+77GIiCwuCnciIktAcAmBsQEk4ctfVje7KURFRREIBKYNd6+88gp7\n9uyhuamJ2NpaPA0N5Ofmcr2ri+ycHEpKSsK+VMPYQNl17RoJfj/ejz9esEApIiKRSWPuRESWmKU+\nkcpCOXbsGJkZGWSE2CJmWRbn33yT7tpa0lasoPypp+bl/lZWVhIdHU1aWhrXrlwh6c4dcjIyOPzR\nR2Rv2ULDnTv81m/9FhkZGWE/t4iILA0acyci8pCI9G52wfA6bNtEGTPjEBucdKblo4/Izs3FGx8f\neouYMQzYNoE51Hu6+u7cufPu1zk5OXdbYnfs3r0kJ8YREZHFQy13IiLywI0f99ZZU0N1VRUbt2wh\nkJIybejxeDzExMQwODiIMQZfWxsNH35IVnY2UbGxxK1eTWZ2Nps3b57wWGMMzU1NRNXU0NndjTs1\nld78/JAnqbEsi6pDh8iMiqIjKmpGIU0tsSIiMp4WMRcRkSUr2FWxq7OTrgsX8Hq9ZPf0MJCfT0pK\nCvk7d7Jl69aQympvb+dIZSVRTU04OjsZSErikU9+kuLi4imPm83SDAcPHmTfvn3U19XRfeECywsK\nuHXnDsnr1pGVnc26detIS0sL+T6IiIiAwp2IiEQAy7J442/+hviBAW5XV5OUnk5mQQHr9+1j3bp1\n0x7v8/m4+cEHRHV00OpwYLW0kJeYSGpJCcXbt08b1mbbimZZFmd/9jNyYmMZTk1dVN0r1TIoIrL0\nKNyJiEhEmGjMnTGG1NTUaY/9xc9/zqW33yYjLY0qr5ectDT2VlRQVVdHQ3w8Tz39NGVlZfNS74sX\nLxIYGqJ42bJFE6Isy6K6spLkgQF64uMp3LaN9PT0B10tERGZhsKdiIgsOgvdajS2a2WV348DyIiK\noi8hYd5b027fvk1ycvJ9s1yG6x7MpJyx4wgz2toYGhggOi6O1vR0tj3xBHl5ebMqW62AIiILQ+FO\nRERmbD4f1i3L4vbhw6QMDNCzAOFq7HmD1wQsWBiprq4mNTWV9PR0AoGR+Tb9fj/X33uPvPh4LIdj\n1vfA5/Nx/f33KUhMxDIm5HIsy+LiW2/hHBrCkZEx4XGWZXH57bcpSEzEHx094T6BQADLsqg7fpzU\n4eFJ9xMRkfDQUggiIg+huYSzYCuXy7bxGhP2BbTPnj7NYHU1l5qbSc/IoGZoiM989rNhK38y45eK\nWKgAYlkWPV1dOBwOLly4gDGGpsZGrLNnsVeu5I7Px43u7pBn4BzrwJ/+KQX9/Tz5xBPkZWfT5feH\ndF0ul4vUtWuxh4cpnKS76E/feIP2U6foWrWKdStXTlj2wYMH2bp5M/bNm1T19GBiY7nR3c36Rx6Z\ndTdXtQKKiISfwp2IyBIUCATwer18/MEH5Ccl0Z6cPONw9tGZM/ivXKG7s5OMjAz63O6QZ6QMxaOb\nN+MdHCQ1Lo7orCxWjFnfLdJYlkXDyZOsyszEW1fHI6OvhWVZHG1vJ9vtJik3l+zHHmNgYIDY2Nj7\njp8s6FiWxee2bqX1xAn6amupTkigfLRVMhSxsbEUFBSQnJw8Yb2LYmKwh4ZI8fup7e6esOyXXnoJ\ny7L4qK2NwsxM7LS0ObXcje0+6w0Ewv7BgojIw0rhTkRkiTl48CC7du3i9FtvEV1VRXNmJuTmctzr\nZXV5ORkZGZSXl09bzqbHHsM7MMBQczPdcXGsnKYFZqYtLS6XC7Zt40pKCul5eRH78P7qq6+Sm51N\nckcHXU4npq/vbuvX3Zaz7GwKMzIm7e5Ye/Qo6YA3KuqeoHPgwAHWrllDVGMjSStX4u3spK+ri+FL\nl9ixY8e0dbNtm97eXhISEibcfvDll8kcGGD71q30DgyQs3r1lK9TZ0oKyXl5rCwrm9XreeDAAZ5/\n/nmuXrlC39WruJKSqGttJaunh8ysLEpKSigsLJxxuSIiMkJj7kRElpDgYt91tbXU/epXBJqaSAWa\n8vN59LnnZtc1s6aGYdtm48aNU+83wzXgghobGxkaGqKgoGBGdRt77sXefW+q+3P27Fk2btyIw+G4\n77g///M/Z9XKlQxdv05cdDQmOprkDRvYtWdPSGVPp7GxkUsXL7J5y5YJjwm17OAi7X0NDThLSuY8\n3s6yLI69/jor3W56F3A8pojIUqExdyIiD4Hjx48DkJCQQLsx+IaHuW1ZpCQns6y9fcYPyC6Xi6Sk\nJC5fvoxt2xhz7/8j3/ve91i2bBlNjY0MXLtGhssFxpC2dm3I50pISKCpqWlG9YKRIBuckMQNtCcm\nzqn73nyExLFlFm7bRpffT+GY8oeGhnA4HBMGO4CvfvWrWJbFhZ4e0gIBcLspHBeygy2g48uejs/n\no+rQIdJ6e6kZGIAJ1vkLpewjR47QeOcOqc3N9Pf3011VNe3YwenudWJiIsmrVxNXVERGaqqCnYhI\nmCjciYgsIU888cTdr2vS04kyhk/PMazExMQQExNDT08PSUlJ92x74YUXgJGH9fMDA6TZNsbtvjsT\nZSiBKTExkaamJhLj42cUrA4fPkxbSwvRt2/TMDSEiY6mOSaGffv3z/gafT4ftUeP4goE8MbEhGWM\nV3A2ULfDgXd0BsuCoqJ79mlpaaGtpQXLsiY9n8vlwr1hAwN9fSwrLZ1wv/GTxIyvx9jX4MCBA+zd\nuxcCAbqbm+m0bfra2rjZ00NxSQlbtmwJuWyA7du339fCt3XbtinvS+3Ro2RFRU04ns6yLKqrqkhN\nTaWwuHjSckREZOYU7kRElqjiMD4Y27bNtStXKF25ctJwsWLPHq5fvcqjmzcDcOH8eepPn2Z1Zibe\nmBgCFRX3LZAdCATo7u7Gd+ECJZ2dM5qVc9euXViWxemf/pS0QIDYnBwKR889U++/9x7RNTV0dnTg\ndLlm1PI4kStXrnDl8mX6rl4lOS4OoqNpjY1l7759d/cJhhynZeEdGpryuhMSEsjNzZ31jKdjJyZ5\n6aWXfr2tp2dW3TnHm0nrYZffz9EPPuDJbdvITEq6Z/bNYH0H6+oYSE/HKirSunoiImGkcCci8pDz\n+Xx0X79O0sAA3tbWSUNaXl4eLS0tDA4O8svvfpfWqir62tro27IFh8NBZ0oKT4yb5OOb3/wmK0pL\nqa2qYpnbTXV9/YyClcvlYu3TT3Pl0iUem2TcWCj2P/UU3mPHaK+qIq209G7L43QmCxdr1qwhLy+P\nS8PDpAwOjqwh99hj9xzb5feTFx9PVnk57Z2dUy5fMDg4SExMzIyuyePxcOH8eZKamijKyyMpIeGe\nc8y2O+dkpmvhC4qOjSVv2TKcSUkjodLpvNua2NzUhKO6mpa2Nkr6+zlcWckzn/oUUVFR95VjWRY3\nP/iAwsREzagpIhIihTsRkYfY0aNHudPQQOOpU2woK6Olvp5bfX3s3bcP55gAdPDgQfbu3UtjYyPn\nz50j1RiWb9rE5VOnaLMs4t1udq9bd1/5X/va10ZaaxITyXQ4MKmpIQeroKysLBonmGlyJoJBp962\nWVdREfIC4FWHDpEXF4fXtu8LFy6Xi9wtW2hpamL1mjX3lVnX0MD1q1fJiI6mdWiI5yoqJj1XW1sb\n0Q4Hw8PDIV/nrl27eOSRR/D84AeUFRdjORz33dtQA1k42bbN8l27GHI674bKe1oTjx1j25jWxPHB\nzuPxEBMTQ1tLC7VHjtC3ejVtHR0TtoyqVU9E5F6aLVNEZBF5EA+sM5mNsbm5mRs3btBbVUVRcjK+\nQADn6tXkFxbOa/e68+fPs2bNmhm3bk1Uztq1a4mOnvyzTY/HgzGG5qYmrNOnSXY6SYiPZ7Co6L5J\nRFpbW+nu7p60i2zwuhOTk4mPjycxMfGe7cFJY0698QZrc3Jogxl1n2xtbeXQBx+wOoTXYKFcvXqV\nwsLCCdfVg9DfCxcuXKD94kVWZWTc974c+56t8vtxLaLrFxEJB82WKSKyRAWXN5jvhZ0ne6ieSfe9\nwcFBfBcusDori7quLkr37Alp7N9cW5D6+/u59fHHZM9iXNpYDofj7tpykwWMXbt2AVBTU8Nb777L\n2uRkbnV1sXncRCQAHR0dtDQ1kTrJjI/TXfc3v/lNSpcvJ9rnoys1lfq6upC6rQZDYdWhQxR1dBCo\nq4NFsD5cf38/AwMD903MM1Yo74Xh4WECgQBrnn6a/t7e+96XXX4/qcPD3K6pofbiReI7O/HW1anr\npog89BTuREQesHPnztHd3c3FCxdItyzSnE5s26betvnkpz4VlnMEg6NzaAhvdPSEXQyneij2eDyk\npKTQ19NDoLsbq7ubjpYWLl64ENaJXSare+fVq7hTUvDevj3pA3woLUJdXV1cPH+enqoqVqalTRqi\nPR4PLc3NdDscVMfFsaa0lKjRZSKCYdzn83Hn1ClSBgfxdnTMKljc7bZ67BhOh4P8lStD6rZ6+PBh\nPjp7lsLBQRJjY4muriZ5lguLh1NNTQ293d10dHTMqS7t7e2kpKSQmZl592evvPIKu3btor6+nry8\nPGpv3KCtvp762lqaYmPZHRfH7Vu32Pjoo+G4FBGRJUndMkVEFgnLsrjyzjsM3LlDwOUKuVVsOgcO\nHGDr5s10XrjAYG8viSkpbP6N37hv2v5Q6zjbBbVn60evv050bS3pTiftfj+PfelL99V9unp5PB66\nuro496tfEd/XR3dLC5t376avv587CQk8smEDmZmZrFq16p4y3//e99hWVkarbd8t89VXX2X79u20\n+3zE1tQQ7XDQ2N5O3KpVFBUX37fUQChm0211tq/FfHX9tSyLU2+8wfLUVHrmuDD5tWvXyM3NJTU1\ndcrz1Xu9+K9dY5nTya3OTtbs3//AA66ISDjMtlumwp2IyCIQbA2qqanh/e9/n00lJUS53WELT8Eg\n0FNXB+nprNq3b1EtBj7d+aYLblEOB81HjpCanMygbbP22WfvCYDf+ta3aLxzh/K4OPLS0rhw9iy7\n9+8nJiNjynt86NAhlpeUkDJBt8sHEXTHm+lrYVkWNUeOkDI4SHdc3KR1nkm5wTGKBAK0njpFjttN\nR1cX3bmL77KQAAAgAElEQVS5Uy50PpmGhgYuX7rE5i1bSEtLC+maNLGKiEQahTsRkSXswIEDPPvs\ns3x88ybcukVORgatlsVwcTFbKyooDMN4KsuyqLp5k7iEBNZNMLPlQgv1oTzYQgNMOGnGwMAAlmVx\n8ic/Ia6nh8T8fNY+9dSUYaza7w9pIpizZ8+yadOmkfAyh2tYDCorK+mwLPouXyYlLo7Wri7aUlLY\ntWcPGzduvLufZVnc8njIjI7GGl2cPdTgONew6/P5OPvzn5MTG8uw00nx9u1h+3BjqbxOIiKgCVVE\nRJa04FTxJSUldx+QU/Pywtoa5HK5WLt+PTdu3AhLeXPh8/moP3Fi0sljxk8y4wbaYMJJQ2JjY4mN\njSUuJgaGhnBMcs6xE8eUh+khf7YTxcw1bMzm+J07d2JZFh9ZFpnR0eS5XPe8vzweDwCXLl4k/s4d\nhoaGyMvOpj8jg1SXixUrVkwacmHu6+oFxzk6mpuJSU3FamgIyzhCy7K48f77xHR3czUQoCxM3Z1F\nRBYjhTsRkUVkLg/IoTzwx8fHEx0dTXd395QzGs63//jKK+wpKKAnNZUmy7pvhsiDBw+yatUqWpqb\ncbW3k+FyMTQ8jGuC9eSuXLnC9atXabpxgxX5+dy6fp0GY8jKzqagoIBly5bd3XemYayzs5O62toJ\nu2XOlmVZVFdWkhkVhdeYkCZiCYbd4PGznVXV5XKRtGoV0cnJ5OTl3XNccJbQ4Np5jxQU0BkTQ+HK\nlTMqf7b3adeuXfe1/rnHTKgyW69+4xvk9PWR2NdHd0cHUUDKZz9Lenr6nMsWEVls1C1TRGSJC06L\nP/ahOL+iYtKH16tXr9Ll97Ny1aoH1kUtuED4QGMjyUVFU479OveLX5DhcGCnpU25X7jHv1mWhecH\nP+CxkhJ8xkx5T2fif/+jP2JLejoO2yYmIYFASQlfeP75KY8JjmtzuVxcv3YN79GjrFm2jNqmJpbv\n3cvadevIycmZ9tyBQIDz58+zYcOGu2FxvN7eXs6ePUtxYeED6cYY7i6Up06d4vXvfIcn4uLoCgSI\nKijAuXEj6W43HR0dfPKTnwxDrUVEwktj7kREHjLBB/6CggKqPv6Y1hMncKWk0Dc0RGZFBQHbZufO\nnXf3H7s2WmJfH0NO5wOZBCSovb2dE8eOsaWiArfbPel+t27dorGhgTXr1s3rQukAZ86coaenh7S0\nNK5fu0ZMbS2bVq3izLVrZFVU0NHZyTPPPDOrssfW8/g//zO0t5NSVDTh+MDpjj/82mvE9/WRkJc3\no+O9Xi9VN2+y8dFHJz3m+vXrWD4fq8rLI2J82p07d7h69Sq1R45QUVb2wN/3IiKh0Jg7EXmoPYwT\nJgS70QGkpaVxtaODKMsiIT+fwgmC0OHDh2lvayPq9m2WFxTw8eXLNAB7nnySuLi4Ba79SJ1Lli+f\n9tzZ2dn09/dP+7rOdaF0gMcee+zu1wUFBXiPHSPG4aB0zZoJ7+lsOYD42NhJxwdOJzA8THx09IyO\nD7aWugFvf/+E4xz9fj8tH31EXnw8NT4fTDKhyVL6fWtubsbpdLL7d36HmKioJVFnEZHZUrgTkSXP\nsixqjx4lKypqxmOQpipzqTy8wkiwWb1vH6dPnqRow4YJ6zx2TFO6w8GKtWsp3LbtgQS7oISEBHp7\ne0lOTp50n7i4OPr7+xewViPmOkHIRL73ve9RUlTExzdusK60lHNnzhBVWMjWxx8P6XiPx4O/o4NA\nby8xGRm01tfT5fdPW7fKykpampuxGxogNZWEoaF7jrtw4QIdHR0jE5rU12OnptLR2UlrXBz79u+/\npyzLsrj5wQfkxcfjhbD8vs0Xv99Pa2sry5cvv2fspYhIpFK4E5ElqbKykg8//JC9e/fS2tzMtXff\npbSgAHdaGhd9PoqKi9mxY8esyg6O8ypNTw95wovFIC0tjTXr1jE8PDzpPvMRWKYyXUgeGBigsaGB\nmJiYSesSHR1NZ2cnt2/dwpWevqCvRThaA8d64YUXqK2tJW33bjIdDtIKCihcvTrk4+8G9OhoMh0O\nErOySHY6pz0uOFOmNzHx7rjEscc98sgjwARjFzdvvrtPZWUlK1as4Mjhw3SdO8eVmBjSnE4SV6xY\nlK17lmVx8vhxBoaGKBq36L2ISKTSmDsRWdIsy+LKO+/Q6PGQ4naTuG7djMcwBVVWVhIdHU1DfT09\nFy9SmJ1Ne08PrU4nX/m3/3Yeah9+fX193Lhxg/Xr1085bf1CCM4KmTo8POGC2ZZlcf2993BYFrE5\nOZOuaWZZFmd/9jNWut1YDkdEjJd6EEshhHrcdPtcu3aNEz/6EdvXrKE3IWHC1yP42rsCAer7+0kr\nL592TcFwsiyLjz/8kKpTpyjatIny/fvnfbymiEg4aUIVEXko1dXWYi5dwgwP09bRgWPDBtauXz+n\nMoOLOPfU1ZFYUMDyXbuW1APfyZMnSU5MJK+gYMb1DudD7o9ef52Y2loGe3vZvnkzw2vWUDDaghJc\n0yzq9m3SU1OJj43lVGcnq1avZv9oN8AjR44QCARGugrevo07NZVWy8JRWspzn//8nOomMxcIBO6u\nGWdbFv6oKFY/+eTdNeMOHDjAV77yFVpaWrh54wbDN2/i8/movnqV8k2bwOnkc1/5yrz+LgUnGWq8\nc4fTP/kJa5YtIzsnh66cHLJzcigqKrpvjTvLsqg5coTs6OiwzbQqIjJXCnci8lB68cUX2ZiXR0xf\nHyYlhdyNG6moqJhzuZZlcfP6deITE1k/x7C4kCzL4vybb5IyOEhMdnZID6rjFwxPs23ajZnzQ26w\nvN66Ouz0dFbt23dfy10oyxfMxzIHMjPB0DQ0MEB8bS2DQ0P4/H6Gi4tZXV7O2rVr79k/+Jp9++/+\njs0ZGWx44gkKcnIYKi+/G/Dng2VZ+FpbuVlVRde1a6zNy2MwOXnC90zwmpqbmkhtaiItJYVGn4+B\nwkLcmZlER0fzxBNPzEsd1UooItNRuBORh1JHRwe2bc/Lw9LQ0BCXL1+mvLyc2NjYKfddLA9sP3r9\ndaJqanAlJZGUmEje3r1TPkx7PB4KCwtpb2+n3efDOnOG23V1lJaUEF1WRkZmJkNDQ3Mav3j2zBkM\nsOmxxybsvhfKfVss9/dhN5OgbVkW9V4v/mvXWOZ0znswD06s1FtfT29CAj3p6awuKyM9I2PKc7a2\ntnLktdfYUFg4smh7mOsY/PAk2PJZf+IEbqAN9EGFiExK4U5EZB7U19fT1tZGuss1YbCwLIu62lq8\nJ06woaDgnge2BxFI5tLKFTzWf/s2Cfn5YemOalkW1959l9iurpBbEmVxm+n7er5/Dw4fPkxZWRme\nQ4dIbGggIT6ehqYmqm2b/+53fofS0tIpj6+pqaGzsxOX0zkvdTxw4AB79+4FwNfaSuupU6xZuZLz\nN27w+Je+xMZHHw3r+UQkMijciYjMg+bmZo69/jqbiovpiIq6J5wEx+a9/eabONrb2fWJT7CsoICh\n8nKSnc4F60o4/uF5Lg/TlmVx5dIlsnNzp30ono7H46G7s5Pzb73F9o0baevowC4pwZ2ZSXx8PFu3\nbp1T+ZEuklsrg9c2bNtEGTPnawy24HuPHSO2p4czJ06wfMUKEvLzJ52oB6C7u5uqqirWrl1LVFTU\nrK8jlPrbts3JkycZun2bUpdLXYxFZEpaxFxEJEyCn7QbY2hracHR38+t+nqsri7ONTfT0dnJhg0b\naG5qIqmhgYoNG7h05gyVZ8+SnJdHodPJe+++y9E33mDXhg3k5+aGtBbZWDPprhgMkWPX+JvtA6PL\n5SInL4879fW43e45tcwEp+0vcDjIdDhw5efrYTZEY1/XmqEh2L4dp9OJwzHbZc8Xh+BC6dWVlfQ2\nNuKtrmbTo4/SnpQ07ZIjU/1OpKamAvDnhw9Ttnw5CS4XA8bgaG2d8nfP6/WSn58/42AXvI4b779P\nZlQUNdHRky74HtTY2Eh6ejqZq1Yt2FIkIvLwUbgTERnnpZdeuvu1ZVl44+MnbIEb+wAel5mJa/Xq\nu9O979u/n+VxcXR7vcS63SGtRRbk8/moP3GCDGOoGR6e8sG+y++HtjbSS0vB759xiBwr+MBqXbpE\nanc33q4uAhUVpKenT3rM2JkGvYHAffsv9Lp6S1lwgo/s7GwuXbxIgteLPymJ+IQE3v3Vr6h4/HGy\nsrJCXnR+Mbb8HT9+nKY7dzDV1bS2tVF7/jyxKSlsWrduyvducGmF7OjoKRdOf+WVV+7rmjzR755l\nWdTevk3fwACrZ7DOYNDBgwcpKSrC99FH5GRkkJCYSD3wqU9/esL9+/r6aG5uvjt+d7G8HiISedQt\nU0RkGlM9JE+37ezp06wqLyc/P3/a8wQf7ttaWmg4cYLE6GicLhdx5eUsLy2lvLz87r6VlZUAdHZ2\nUnvqFHGDgzhcLrZ++tP37DcTBw4cINXppHh4mLKiIm7U1pJVUcFjW7bcEygOHjzI7t27ARjo78d7\n6BArSkro7O6mJy+P57/4xVmdfykLd5CyLIsTP/4xy10u+hITQ27xDAb0eq+XxnPnKHO78dn2lF0T\nF5plWbz13e8S09fHxzdusOXRR6nr7eW5f/NvJqxjZWUlTY2NDF29SlZmJqUFBURt2DDlREHT/V56\njx1jsKmJ4dRUVu7dO+29majr85V33qHx0CGSMzJImmJ9Tdu2uX79Om63m8zMzBDvkog87DTmTkRk\nEbp48SJDAwMsKy2d8cQmg01NdMfFsf6ZZ6Y8tqmpidMnT/LYli3k5OTMqb4znZDFsiyOvf46ZW43\nPZMsaB3pgi2t4R5feeTIEbKzssjIzAy5vDfffJOWy5dpvXWLAZ+PdVu3kpuZSVdBAes3bCAjIyPk\n889ny59lWdyprycxOTmkMXdVVVXceP99NhUVzfkeB2eUHR4eprSggNbMTJ56+ul79hk7w6XP5+Py\n22+zKiPj7rn//NVXGayr44m1awkEAqz6zGcmXF/Tsiyqq6oYtm02b94cUv0WY4uriCw8jbkTEVlk\nfD4f1qVL4PPhbW6edkxRULArY2NDA/0dHdMek52dzarycmJiYoC5PRzOtBuly+WiZMcOfJ2drCwr\ne2geRj0eD7dv3wYgMz0d39mzxEVF4Xa7+aipiaTkZHbs3El2dvasym9ra6Ozo4M1a9aEfE+//e1v\nk52VhSsqisyyMk4ePcrg0BDxWVmsnGAZiskEW/9ueTzkxcVRMzREYNu2KbvnzlQo40KD7+OklBR6\ne3tZ98lPMmTbc+7eu/+pp+75AGPLBBP7HD9+nOHhYdxuNz9+/XXWxMbi6O3F19HBxz09fOaznyXZ\nsu6WkV9YOGH9vceOEWhqwqSlYa1YMWW9g/c92M05ONbyYfmdEpHwUMudiMy7xfxJ9HzVzePxkBAX\nx61336WtuZmC4mIGi4r49Gc+Q3x8fMjlXL58meLiYpKTk6fcr6Ojgzt37pCTk0PNkSNkRUXRatsL\n0pLm9/u5fv06udnZi/I1DqdAIACAw+GgpqaGm++/T3IgQF1NzUi4TksjKjaWzcXFs25h8vl83D58\nmBi/H9zuWS1nkelwUO334xwzDjQUHo+HpqYmsG26z5+ndNky2jo6yH78cbZt3z6j65itYMgJXkeV\nZRG7fDlbtmwJ2zlC/b3v6enhzJkzpHR0kBMTc89rOlkZwS7TQwMDdJ4/j8PhwAB2aSmlK1YQFxfH\n8uXL7zvXq6++yorSUuwbNyjIyaHFsnBt3syOnTvDdt0isnSoW6aILCrBbk3Bh80MYxYsbIRqvutm\nWRaHX3uNodZWhlJS2P/CCzMuv7m5mYaGBjLS06d8EK2srOTixYt0dnQQV1/P9s2bafX7GSgs5LnP\nfz4clzOh4MLMh3/4Q7YsXz5v9zHUAD7fHyR4PB6io6Opr6+n/cYN4mtq+OGxY5SsXElDezvLsrIY\nbm9n15NPMjQwwEBRES98+cszOscfv/giW91u0lNTCQQCdObm8pnPfjbk48NxDz7++GOqKytZn5e3\n4FP2V1ZW8tGZM2R1dxMFVNXWsvfLX6Zi27YFOf9Y169fJz09nZiYmBnf07FBu7anhxW7d0/b+nnz\n5s273U+1yLnIw03dMkVkUTl48CD79u2jv7eXnuvXudzRQV5uLtX9/aRnZLBjx44HVrejR48yPDyM\nAerOnCEKiElI4EZ3N8tLS9m0aVNYzhMIBAgMD5PpcuHt7aW7u3tGXeMcDgdRUVG0njtHTm7uhLNR\nBvdbu3Ytpr4ef3c33amppDmdxGZmUjyPrS3BJSPa29oI9PZy0+vF39WFc/XqsDyQjm3Bievupnpw\nkPyKCmKjo+8+ZAevHyZfFiKcdu3aRSAQoKGujj97/XUygU+vXUttXBzrEhJYtXw5ddeuUX3xIltX\nryY6KQnLsmZUj69+7Wv3dBvcMMNQM5elMIJs22bl3r0MORwLPsvpzp07Wb9+Ped/+Uuq33uPFfHx\n9FRVYZWXL1g9LMvCW1tLT28vZWVlGGPm1MW5LIR72N3dTU9PD5s/9zkG+/s1u6yIzIpa7kRkXgUf\nuB2WRW1XF49/8YukpaU96GoBo9OhHz1KX309g04naz/xibA9TL388svs27sX36lTJCcmUtfYyEB+\nPk8//XRIn/4HZ85sbmoizuvFmZyMz+8nq6KCJ8YE4+rqaiorK3E5nSTU15OflcXZa9foychg67Zt\ndHZ2snOeu3VNNAkLMOfWo5dffpmC/Hy6rl6lrLCQ67dvk+Ry8emKirvnuXXrFrdu3SI7Oxt7eJiP\n332XnIwMahobydq8mcSkJJ555plwXi5Hjx4lEAhQc+oUg21ttPb10ZGQQNetW5Tl5tLY1UVvZycF\neXmU5ufTV1Aw4xlEH2RX5ra2Nk6fPMmWaZbBmA/B931aWho3rl/nTmUl68rKuNnQQE5FBRs2biQq\nKoq8vLx5q0NweY/uujqiMjJYtW/fvL4GlmVh+XzU37nD2rVrFehEBFC3TBFZxIIPqk0tLeTk5IS0\nLMBCsSyLqps3uXz5Mhs3biQ1LS2k2ftCLbvmyBEyHQ5ud3bS3NpKxfLlNA8Phzw1faizV850lstw\nGxtGOjo6OP3Tn1LkdBKfnT2nuty4cYMjP/kJaVFR3GprY0N+Pm2dnSTExTFYVMSOnTvJysq6W4fT\nP/0pBQkJDKakzOs98Pv9Iy2LlkVjczOXLl3i5o0brFmzhuKSEpx+/31jtBa7YEvp5bffJr63l9hZ\nvHbhDKVTvafnc6xsS3MzeaPvsaHhYbyJiTz7uc/NeKHzUASvcaCpiQ6Hg0effXZJvFdEZP4p3InI\nojc0NMSVK1coKSnBOYNFveeTZVmc/+UvaTx2jIHeXgIpKWx54gmGk5PJD0PLxZtvvklfby/dXV24\nfD7SnE5aLYtASUnIrTmhPsiG+8F6NmVZlsVXv/IVyoeHScnJITk/n4wtW+6ban42dRm2bfxXrkwZ\nYC9dusRgf/+Mlp6Yq9bWVv7xG9/A9/HH7H3+eTZ+5jPA3FsuF9qNGzf4+7/7O1bFxFBWUkJXXx/r\nnntuyvXkxgoGlXSgNRAIy9p649+HwTGeEy09MbaL7lzPOd8flARbKFubm6G6mpTERBLj42lISWHd\n+vWzWlhdRCKLwp2ILAmdnZ1UV1eTm5tLf2/vA3349Xg8fPuv/opVKSmcOXmSnIQEEmJiSC4tpSg3\nl9VPPcXeffvCcq4H3bIWqmBLZv2pU2wtLQ25rh6Ph3PnzkEgQG5vL47mZgIDA/SWlPDsV74yo8Xf\np6vfVMdduXKFvp4elk8z7fxc6jBeXW0tnu9+l1hj2LFlC0Pl5SEHosXG5/Ph+cEP2FJaio/QJ/R4\n+eWX2bB+PcMffzzyIQmwYv9+VoZxnNy3vvUtNm3aRJffT8vJk2SkpTEwPEzUihXgcLBt27YZreM3\nlYXqFrtU/l0QkYWncCci8ybcDzrXrl2j6tAhHi0ufuAzaFqWxeVf/Yqha9cY7O+nLRBg42OPMZCY\n+EBnfVxogUCAt956C+v6dWquXiWht5eKPXuIj49nYPlyHn/iiZDKCT6sJvT2UtvZSemePRQXF99z\nnrHT3IfzgdayLM794hdkOBzYaWlTlmtZFlWHDpE4MEBdTw9l4+o50/PePnyYhqtXicnMpGzv3lmX\n9aC1t7ePjGHMzJxV8PYeOwYdHRyvrGT7zp0Mp6aG/feosbGREz/+MY+WlGA5HEs+EC3mfxdE5MHR\nbJkiMi/Gz0DYsWbNrMeknTlzhu7ubm7fukV/dTVJgQAdPT20xsZSunIlRQ+gtcPlcrH2qaeoH+0G\ntdLpJMoYsufhQSscsxjOl+PHj9PW2kpWdDSFW7dy/vhxUuLjwe1m+Zo1IZczdobARye4h9/85jdZ\nUVqK/9w5VpaUYHV2khamSSS6/H6KU1LITk/H39NDl99/t9xgNzgYmQmypbmZ9jNnGG5vJzEQ4PL1\n65Tt2MGyZcsoLy+f0XmdTidp69dz4fx5NsfH479yBSs1ddG+1lNpb2+nuLh4Vi1gwdf+tR/8gJSc\nHIaA2mvXsHNzcW3cGLY6+v1+1jz9NCYuLiJmlFzM/y6IyNKjljsRmdSBAwfY+MgjBKqqCAwM0NTW\nRiApiVK3m/yVK2f9ibllWdzyeOhraMCRkcHq/fv1cLMIjA3yVX4/rhkugD2T8xz/0Y9YkZ5Ob0LC\nnFtegsFtcHCQmtOniRscZCA2lux16yacKdOyLOq9Xo795Ces7ugg2e3GFBQwsGLFjLsRjp3V1NnU\nRHFuLjdqatj4/PNLrmumz+fj1IkTPLZly5y6N85nV8O2tjaam5tZvXr13bAuIhKJ1C1TRObFiy++\nyOr0dBIDAa56vbgTEthUXk7/wAD+7GyKly1jw4YNMy7XsiwaGxpo9fmoqKggJiZmHmovM7VQXcSO\nHDlCl2Wxet26sHRh9Pv9OJ3Oaesf/GAhsb+ff6qspK2lhc2lpTQ2NvL0k09CauqsJgJZqmOngpOQ\nWJbF5XfeIdbvJz4/f871n4/3UWtrK2dPn2bdI4/M61IIIiKLgcKdiMybmcxWOFN37tyhs7OTlStX\nzusn8ZE6ruVBzKQ5Vz6fj4tvvYXbGIZDDFPhqH9lZSXNTU3Yt26RlZTEn/3jP7Ly0UdJSEwkq7eX\nZ3bupL2ri6bUVD7//PMzLn8x3eNQVVdX4/V66enqIr2lBYD6lhaGi4vJLyhg2wwXUJ8vlmVx4sc/\nJi8uDtzuJROeRURmS+FORBZEuB9gbdvm5s2bJCcnz9un8T6fj1seD65AICzdABeLma6Bl2HMA5/A\n5uDBg6wpL8fV3Ex9SwspSUkkrV/PuvXryc3NvW9/y7Koqa7mzkcfsTE/f84fKgTvRaC9naOHDjFs\n26QsW0ZxYSGrMzOXVKtbOC3WlsfDhw9j2za3qqpIa2rC6XJhdXWRt307K1etIi0t7UFXUURkXijc\niciSNTg4yNWrV3G5XDggbMHR4/EQExNDQ309d06cID0xkSSnk+GSEr4wi5aZxcDj8QAjLZ5RDgfe\no0fJdbnwtrSQvXkz0bGxFBUVsWPHDiorK3G5XNyurmbg+nWc0dF0DQ9jli8nIyuLHTt2THmu+WqJ\nCjVI+Hw+bn7wAcfef5/a6mo+9/nPU1ZUNOelBizL4sf/9E/E1tfjjImhz+FgID+fvXv3LqlWt3Bb\nrC2Pg4ODnDhxgtjmZoqSkhZV+BQRmS8KdyKypHm9Xi6+9RaPFheH/eEtGCai/X6qOzrY9qUv3f3E\nf7E+0IbC5/Nx5Z13aK6sxJmZScLatax96qkJ15TzHjtGT10dpKezat++kLpBeo8dww20Efp6Z6EK\n5b7/6PXXia6pwZmQQHx7O/HFxcRkZISlLou1pUruZVkWly5eJN3tJi8vb9L3zIP+PZ7ruo3Dtj3r\nWYjncn4RWby0FIKILFkej4ejR47whNtNXXMzTW1tOFevDttDytjp+XNaW+np6SEtLe2eAOMFWGIP\n+H/5l39J2cqV+JKSSEhPp6+ujjOnT7Nv//579gte/7mzZxkaHp62XI/HQ0tzM46bN/FnZdFqWaSs\nWhXWexPK9O/7n3rqbgCr9vuJC+PsnWPfE5Ewnf5iNdvQ4fF4+PDDDylPT4eODm7FxVGydSu7du2a\n8ByX336bouRkvA4HgYoK0tPTw3kZExo7Gc3tw4fJiYnBGwiE/O9I8Djj93Pz2jXWr19Pe3LyjP8d\n8vl81J84cXe5mqX275iIhJda7kRkUViolpShoSG+//3vk5KSwofvv88yh4MvPP00527cYLi4mJzc\n3Gm7Ky4mMxl3V3XoELGdnSFNSGFZFu99//tkxcTgcLsnbBFcCGqRWFxm8npYlkV1ZSW5sbGz+p2u\nq60l+upVcjIyaGxtvac7bmVl5a/383qxzp5l68aN1DU1kVlRgTszk1WrVs3uIkNw4MABfvd3f5er\nV69iBwLUfPghxYWF5LrdVMfH8/wXvzjhcR6Ph7i4OP76r/+a5cuW0X79Ov6ODuI7Onhk2zYSkpOx\nXC5Wl5ezf9yHNONVVlZiWRYOYxi8fp3inBxqGxtxrFjBtu3b57SchYg8eOqWKSJL3kI9yNfW1nLk\ntdfIiInB39bGhk2bFnSilXB1xRpf3lTl/PGLL7I9OxtncjKtloV782Z27t49ZZmn3ngD58AAgfR0\nyh9QuJOpTfXah/v3KfgBQX58/LRhLdj6G3XzJsuKimjv6iJr+3bWrFs3o/OF8sHFqVOn6L15kzK3\ne8G62A4MDAAQExPDiRMn/n/27jQ6zus88Py/VgAFoFDY930jdhIkuJMSRa1eIkuU03Z3u/MhPWd6\nTp84yXHmzMQzySSUppOOv8zYTo5POomnMx88iRzFji05NiWRLHCnwAUkQBA7CnsVquqtQm1AbfNB\nKhqSuGCpAgrg8/ukBfW+963lfe9z73OfS3higlqTidHFRZpXuW9n7Pr0Ph/3+/pobm195H3oSZ+z\npKPxE5wAACAASURBVBgLsfNIcCeEeOqstfMa23DapSgsDQxQkpfH6NQUtSdOsKu1NWEdolj6VqzN\n995/n6xQiMF796hvaUFRqTA2NFBeWZmwNqylAxjrmBcqCqhUEI2ib21l/8GDCWmbWDtFUZicmGDx\n/n0KtFps4TDGFWmriqJw5xe/oCYrC4dKFZeN4j+6fp3U6WlePH6cjLS0Jxa2uXv3Ljd++lMO7dpF\nwGBYVxue9BtfWFhgYWGBwsJCvIuL6wpkNxIET09PEwgEyM3Njfuau5Vpn0Nnz1KUkoKiUlH6kLRT\nmeEWYueR4E4I8dTo7u5mcXGRyZ4eKjIziRqNHH799VV3ajZ7pDsWVIZCId77+c9JVxR8Hg/LVivR\nnBwiPh979+1DlZXFq//xPyY0wFtLSp3MBiQnRVF48ZlnON7SgtrjIauggHy1Gl1REdqsLPJbWpid\nniY0OEhjXR2hUIjFoiK6DhzY0HYjg4ODTFy8SFtJyRO/E4qi8NFPf0pWNIqiUtHw7LNx2ax+JZvN\nxs2eHto6Oh66jcaTKIrC9OQkC3fu0LiOWb+pqSnu9fWxu7OT/Pz8NZ//SWL3jenJSRw9PTTU1BBY\nXiZUWUmqwcDLL78c93MKIZKHBHdCiKfKlMXC8o0bhAMBUo1GVK2tayqPv9kj3Sv3V+u9eZN3fvlL\nitLT0RkM5Gdm8uKXv8yM04m2vp4vv/pqwtuzGht5j2QmIXH67txh6dYtXE4ni1NTBPV6tEtL7D95\nEpVKha+2lunZWQwOx6pSKFdDURR6rl+nqKSErMzMx36uFy9eZG52Fp3FgtvrpaKoiJqXXtrQ9hUP\na8+tn/+cPJWKaE7Omq9PURT6f/UrnCMjuKemeOG11wiFw6veZkNRFK698w7VWVkPZiWNRuODGfp4\nCYfDXLt2Df/wMHXZ2bg0GhloEeIpIdUyhRBPlQyjkcmUFFQ+HyMzMxw8fPjB/1tNYLGaao0bFRt5\nBwj4/dz8xS8YnpggFAxSXl2N1e0mNzOTaw4HzwF1LS2UHzqU0DatxXrfI0VRGDWbyVWpmFCr4cgR\n6YzGiaIo2G7fxt/by4jNxrhaTSgzE5WikD8zw9m+PnQFBXTu3UvbM8/EpRqooijc/+ADMhwOIqEQ\nGU8ILo4cOfK5md8Mo3Hd5/+sB+v55udRZWYy0NdHFfDSK6+s6rUqlYq//P73ebW9nd7791lyOLj/\nD/9AXVMTOeEwd/v7Hzordu7cORSHg1AkggpIcbmYi0TwTk/z0ewsbe3tBAKBuBVkikajjI6OUlZW\nRmZTk1R2FUKsiszcCSG2LUVRmLJYGBsfp6m5mbq6uqRNJ5yYmODmD39IyfIy151OUouKSPP7UbRa\nqg4fpr21ddvPcr311ls888wz2G02PHfu4PZ4qCgpwdDWhkNReOMRFQTF6pjNZs6dPUvR8jKpwJjF\ngkWj4atf+xptbW0MDQ7i7O+nRK8nrbSUisOHN/R9unDhAtFoFMfCAgvXr1OYm0sIyOzo+Nx2Gw+T\nyNnbjf7OFUWh//33qcnMZMzt/tR6xUf9/cTFi2SFwziA3I4O3P39pC8vs6jVUhnHAYzY++Z0uUhN\nTaWuru7BIJEQ4ukhaZlCiKdKJBLB7XZjuXSJvhs3+NmVK3zx619n2mIhY2GBjuZmrE4nkaoqauvq\n2L1795a0MzZTYJ2fp8DhoPfePULhMEulpaTo9czbbLz4/PPs7uzc1oHdSrGqistzc2RUVCRNgL0T\nxIKMVJ+Psx98wOzCAg1dXVQcPszf/s3fcLK6mtqKCoLBILWvvBKXVEi73U73j37EvpoanHEozhIv\nGw0eV/v6ixcv4rTbmb5wgerycsLRKNpdu+javz/uwWssaNW63Yw4nRz66lfJzc2Ny7Fjx5d0aSG2\nB0nLFEJse2vpeFy8eBGb1Up4aIhMvZ5/e/gwgzdu0F5SgislhcLsbIwlJVveEY1tuhzrtJ2qrGQu\nGCSzqYmBgQF6fvYzUiormVxa2jGbD5tMJmqfeYYPzpyhfh2FLsSj9fb2EtDpsHq9mCoqwGikKCOD\nmakp/v03voHWZqMmJyeuqZBOp5PUmhpc5eWUx2kT+Xh4WNrwau8ha7nXHDlyhIGBATTz87RXVHw8\nU7h/f0JSuz1uN8N9faRqtQSWlvB7vbDB4G5l1c37H3xASVoaE9GopEsLsUNJcCeESAor06wmI5En\nBjrt7e1Eo1EmDQbyVCr+9O/+jraKClxLS+zeuxdncTH1TU1JUXkSPu6IcugQf/n977Ons5MKv5+A\n38/Jw4fpm5igPBhk0Otl95491NbWJqTNm01ns2FMSWFydnbHBK5b7bODBbG0xL2fvL+x72W81mYp\nisL4hQvUG414LBYoL9/wMRMhNpMfe08mQiE4cuRzRU5WzvjnwKqCHK/Xy9LSEvu+8hWW/P6ErnvL\nMBqpa2mJ61rFCxcuoFKpmJyYYOjsWVoaGtBptQz5fITCYb72ta/FoeVCiGQhaZlCiKTw47ffRjM+\njsPp5MWjR1dd/XLlPlHu/v6ErbWLnceQkYFarY7Lur5Y4RHf1BQZFRVUHT26rQOg7u5usrKyuHbt\nGh63m2ybDa3BQH52Nqr6eopKSmhra9vqZm65eKXGJTLF7vTp05w4cYKlQABPby+5WVmEQiEceXmc\nSrK1k2azmf7+fiKhEOHRUTqbmnB4PCyVlVFUXExXVxcpKSkAjI2N8fOf/QyTw4EhJQW1Tsd8ejrt\nHR3s2bOHtLS0Tx3b4XBws6eH2vp6qqqqNtzW1Xxmifhcl5aWuH79OprZWaqNxqRajyyEeDhZcyeE\nSJjNWKcRm4lQKQoTbjeHvvrVz23Uu1XtVBSFse5uinQ6/rW3l7TycjJnZwHY29Ky6vLpjzp23507\nFBYXU1dXF7c2bxVFUbBcuoR1aAjFaqV9zx6W0tOlI/mJZC348yjbob2xNvomJxkaGmLv/v2EMjIe\n2lZFURgdHube2bMca2p65NYCsRm+np/+lBxAnZe34aIpsVnQIp1uU9/LUCjEwMAAhYWF6HQ6WXMn\nxDYha+6EEHEVC5RCkQjK3bsU6XSrSpdcr1jaosftJqIoOBwOVCoV3sXFNaU+xrttZrMZtUrFwKVL\nRICMjAzaWlvx6PVE7faPO2kbSJ0ymUy0795NX18fqXp9XNcKbSaz2cyFCxdINxioCIWYslrJyczk\n/MIC7Um0TmurxD63s2fPEh0dpayoiOaaGjxud1K/Nyt/l8lahj+2Ti3PZCIlJwdPWdmnUrIjkQjA\ng7TN8MwM2VlZLFZWPnQNYWzW8kZPD5XBIH6dDhwORgIBDh0+vK4N0998801qq6tZ7O3lQEcHU1Yr\noYIC9uzdu/E34DEikQjDw8NkZ2c/2Gg9GT9DIUT8yMydEOJzFEXhf/ud36GzvJyB2VlqcnMxZWdj\nSE0ld/9+jh47ltDzR6NRbty4gfPuXVqLirZ8xsBisbBw6xaBmRk0+fk0njwJwI2PPqK+sZHyDa5D\nUhSFy2+/TWtJCYpa/chrjc2K5apUOCCpZ1GSeaZns8UqXBpDIWaWl5myWDhQX8+iTvfUvj/xHKRY\nua3Bw75zZrMZtVqN3WYjOjpKdkYGiz4fKS0ttLa1PTJYi/d3+fbt21hv3KCtpGRTfhtOp5O+u3fJ\nNBrp6OhI2HmEEIkhaZlCiLj58dtvo7VYyExLY8HlQpuRwZGGhk3pkLz11lu8+uqr3L93D9XYGGmp\nqSgeD6m7dvH6qVMJO++TKIrCzNQUTpeLAwcOoNVqsdlsTE9Pk5eTs+ZO6uXLlwmFQng8HkaGh2lU\nq2msqqLn3j1UNTXU1NXhcrmYn5+nqKiIaDTK7Vu30E1PU5STg1avx6LXs6+ri66urgRe+dol6+zi\nZovNANmsVtJnZnA6HKj0enoXF3nj1Cly8vLQqFRP3fsUG6Qo0GhWtcfcao+5mrVsaw3W4vVdttls\n2Gw2ioqK8Hk8Cf/MHQ4HY93dROx2UoqK1rTnofx+hUgOEtwJIeLms50gY3PzpndCk3UGaHJykoWF\nBXKzs5m32bBcusSRXbs2XFhlNdeqKAr33n8fndtNSnFx0rwn4vEerCd1OumdmiK9vp7a+nqsN27Q\nXFiYVN/vzTBlsXDuhz8kU68nfXGRnKYmdHl5m/IebHbgoigK1rk55m02urq6SE1NTfg5AX7yzjtM\nXr7MvuZmlMVF2r7ylceuCz59+jQvvPACCwsLjFy+TLpKRUp2NiW7d/P8KjasF0LEnwR3Qoi4SobR\n281qw1rO43Q6ufgP/0D60hLff/ddXj14kBeOHEEFGy6sspo2zM/P03v7Nl2f7LMltgdFUbh6+TLd\nP/kJJmDE6eRYaytavR69TkduVxeoVA+qOu7fv39rG5xAsbTvPSUl+Obnadi7l+VgkM433ojLpuvJ\nIlaIyT8zgyonh6YXXkjqwbFIJEL3+fOYpqfpaGpibmFhQ/c0IcTGSEEVIURcxbs4yXoCtUQUSHlY\nu8YvXCBfo2ESHlsw5s///M+pr6tD4/EQTU/n9WPHIC0NFcSlsMpqSqMXFBSQkpqKW1EevG47SYZB\ng61gMpnw+/3sa2ggJzOTUqsVVWYmx2Ozvu3tT837YTKZ+D+/9z2mJydRBgao/aQ0f7w2XU8G3d3d\n2KxWyj0evKEQXosF9+XLvPTKK5vWBnVZGXZY1cbzDwqv5OaiCgSYW1jY8D1NCLE1ZOZOCJEwkUgE\ntVq9pSmWjwsm3nzzTXZ3dGC/fp2sjAzSDAZaX331sSPVm52yGjtfVjiMS6PB2NzM7XffpaO8HLdW\nu23S+ex2O/cHBrD39tJVU/PUpSJCcqQ7J5udGOxvdO/Njb4nCwsLDH74ITVZWas6bzQaZXh4GK1W\nS1VVFS6Xa8d9JkJsR5KWKYRIOqdPn0alUtHS3EzG7CxerxeNTsdyeTnFJSUcPHgQjUbz0Nc+rIOz\n1k7Pys70fCj00H2qLBYL9tu3mR8cJGw00vrii1RWVj7xuInu/JjNZlQqFZMTE9x9/30ioRB5eXmM\nLS3RkpZGU2MjLo8HdW0t1bW1Sbs5eCQS4b333mP65k2U6WlSvF7SKyqoKSsjY/duDhw6tNVN3FQ7\nMZgRnx7IGr9wgUKtFms4jKm1dU0BvKIo3PnFL6g2GnE+pnLu49rxve9+F5PdTnN9PeWFhY9MrVQU\nhUWXiwWHA6PRSE1NDSrVmvuRQogEkbRMIUTS+eM//mPg19XxlufmUNRqjj9h7Uns7/VeL470dDh8\nmEgkwlh3N6WpqU/cb+/NN99k7969KHY7yq1bNDU04PJ4mNdoePHllz/1txUVFUSjUSzj4+QGg7j7\n+1Gysh7bvs1IFz169ChutxvN7CxVtbVYFQVtQwMvHDzI7PXrNJWXb4vZr7feeovd7e1EfT7UKSm0\nFxeTX1sLubmUNzVtdfM23WZ8d8Tm+8EPfkBbWxuOhQU8t25hLyhgdGaGiMXCiZMnSUlLe+Ixvv3t\nb5NlNJIyMwPt7Vjm5ljQ6znxydYrTxKNRhkZGeHEc8+hmp7+9YzhQ1IrYwNfYZuN+eVlqk6dksBO\niB1CZu6EEJtCURRcTidzVivl5eWUlJQ88m9//PbbqMfH0UWjFOXmchdwKQpMTnKks5NIJELpc889\nMn0y1nFxWSwMDwxw9NgxvCkpD5256+7u5qc/+Qm/0diISq1mQVHQNTbypS9/OZ6Xv2qxGTuA4aEh\nUqanWfJ68S8v4ysu5sD+/WRmZa1r+4WtsnIGdcTtxhSH0vdCJKN79+4xfuECu8vLWYhG15SKee/M\nGXxTU7gVheb2dpYNhlW/PhqNMjY2RjQapaam5omple/80z+hHh8nOyMD/9ISpn37OHj48KraKTPP\nQmwOScsUQmwLoVCI+/fvk5+fT0FBwUP/JhYM5KlU9ExMMDs3R1lqKj6vl9aOjsd2enp6ehgbHcXa\n00OWXo87GCSQm8tvvPYatbW1jz1fsm27EGtXmt/PtdFRXE4npQYDFR0dVB09mhRtXC3pFIqd4FHf\nY0VRPi4Q43bT2NhIwOdb9Xf99OnTHDp4EM/t25iMRjxeL/rGRg48ZDDqUW0a6O9Hq9fT2dmJWq1e\n1WvWes9bWFhg+Nw5qh6xWbwQIr4kuBNCbBvLy8vcv3+fjIwMdBrNQztBiqLw/pkz+LxeUqanyc3O\nxuZwkN7czPHnnntiWuft997DMTpKQWMjLasoQZ6swce7776L3WbDYbczfvkyh9vb0RkMWLRaXj91\nivLy8q1uohA7Wmw2fWRkhNvnz3O8uRklGiWvqYns7GxaW1sZOX+ewMwMusJCGp5wf3qY9Q4wORwO\nRs6fB7sdXVHRmgZ91nLP+/DDDzl/9iw1QH11NTank9Ljx9nX1bWqcwkh1k6COyHEtjI7O8v1f/5n\n9lRWojymcMB6Oj2KotD3y1/iHBoit7FxU/eXirdYgQbX2Bhjo6McPHKEYHq6jJoLscmuXbmCdmCA\nzrY25hYWuOB24/P78Xm9FHm91JWVMTozQ6iyktdPnVrz8dczwPTjt99Ga7FQmp//2OIpG7G8vMzg\n4CBarZbg2FjSZTgIsVNJcCeESApP6qD09PTg9Xq509tLSSBAnsmEPxBgIBTim7/3e+s6Zszp06c5\nceIE0XAY+/XrGFJTCSwvE6qspK29nYaGhrhdZyLFKu8BWMbH0d67R4pGg9PjwVlcTH1Tk3SqhNhE\niqLQ19dHutNJkU73qeBmq7d6SeS5l5aWGBwcpKCggMLCwqTNcBBiJ5LgTgix5RwOB9NXr6JxuVjU\n6Wg8efKxG3MnqlOSrGvoVuvatWtoNBocDgfBYJDlyUmii4sEdDqMdXUYjUaOHTu21c0UYsdTFAXH\nwgLTs7N0dnYSDAYfueZuq4KeRJxbURRsVivzViu7du0iLy8vKdolxNNEgjshxJYaHx/n1o0bZFmt\npOp03OjrI2ffPg4cPEhNTc1DX5PIh/9271gsLy8DoNfrt/21CLEdxQaJAjMz+NPSaP/CF3b87y8S\niaAoCmPd3SzNzhLNzqblpZdWfd0r9/vbzgNsQiQDCe6EEFvOYrHg6usjX61mzO0mXFxMbW0t4WBw\nxwQmEmgJ8XT41/feI3T/PuWFhdhdLpSCAnbv2fPIwaqdwGw24/N4yLZa8QcCOD0eVDU1fOX111f9\nepVKhcNux3b1Kk11dfQODdF16pQUXxFijSS4E0IkhVjwY8jIwO12M/D+++zeJhtuP0lsNDrV6yUg\nRU2E2NG2ei3dVg0izczMMNLdTb3JtK7rDgaD9PT04Ll/n5bCwjXt9yeE+DUJ7oQQCbeWDsd3vvMd\ndjU24r59m4riYvJNJjL27497JbfN0N3djVarxbO4iLe3l4DXS1ilIqOtjV3NzTQ2Nm51E4UQCbCZ\nQVYspdHhcDB87hwV6elbNii23uv2+/0MDw+Tn59PamqqZDkIsQES3AkhHipenRNFURg1m9F7PERM\nJsoOHiQnJ+dTlR0/a2ZmBtvNmxRqtTtq5i4zGOTy/fvseu45qmtrt/U1CSGSw/nz57HNzzM2Pk7e\n4iL6lBQy0tIIVVZy6o031nSszZ75UxSFuZkZbHY7LS0t5OTkJPycQux06w3utIlojBBi6ymKwvTk\nJMrAALVGI5ORCKwjuOrv72dhYQHHwgLRkREiwSDOxUWGvF5q6upITU2lqanpoa8tKSnBYDDgcbsp\nX0UnI9nXs5lMJiIHDjA9OYlxfh7D6CiTVuu63lchhIhRFAWTx0O6x4MuPZ3cqirqsrIeDIqt5TjT\nk5M4792jLitr3ff9tbZ9+Nw5lmZn0RcUoG5rS9i5hBBPJsGdEDuQw+HAcukS8319KJOTVLz8Mvk6\nHR63e80P+ebmZuCTWau0NPJUKvrm5lDl5JCdlYXpCSO0JpNpVedcub5lMzok63X37l2cdjtar5ex\nQIBUvZ45jYajx46Rlpa21c0TQmwz165dY9JigdFR9Go1FcXF6JuaCGVlrWpQLMbhcPC/f/ObNOXm\n4pyaYun558n8ZHAtkffS98+cQWuxsKuqCsXtTvj5hBCPJ2mZQuwgf/Znf8bJkyf5g299iy90dBAK\nBpkfH6e2pYWsoiIKW1t59tlnMRgM6zq+w+HA5/EQjkYZ6+4mT60mmp29oXTLmZkZxsfHmZ2ZwXf3\nLqaMDFLT0sg/dIjdnZ3rOmaiKYpC//vvU5OZyZjHQ9Nj9vMTWyPZZ4GFWGkjxVtiFSqt8/NoxsYY\nHB2lTKMhmJtL58GDCU+Hj6Xsm6JRFiIRGk6ckN+cEHEga+6EEA+s7CiMud0Yd+2itLx8ww/cwcFB\nrFYrc7OzaC0WGioq+PD6dVpeeona+noqNlAsJdZBWJ6bI2AwUH3sGBqVas2d883q1EvwkJxi+3RN\nXLxIVjiMNyVl26/1FE+Hjd5TEnXfX+255X4oRHxJcCeE+JREbxCeiBLhiqJgt9kYGRsjxWajPicH\nO6z6+LEAsSQlZdM7NyI5/P3f/z3pBgPlXi8LVitLKhX6Xbs4cvTolnU+peMrNot814TYOSS4E0Js\nqkR1Ii5dusT1a9fItNt58dAh+kZHqftkZvBhRkdH0Wq1jI+PY52bIzQ4yILNRtBup6S5mfrWVmqO\nH39oG6UjtDPFBh/mBwfJLCujaN8+nHfuUKTTbWrV1kgkgtvtZuLixQcVY0sPHJBKgiJpyD1QiOQl\nwZ0QYsdYz8yg2WzG4/Fg6+9n2WZDmZnBlZLCiwcO4C8r46VXXvncOe6dOUOZwYADqDxyRDo3O4ii\nKPzd3/4tkUiEcCRCidfL3rY2Bi0W9n31q5uy3+K7777LR1ev0mIwEA2FKMjPx11cTHZODkePHpWO\ntdgSse1rYvfZPJVKNhoXIgnJVghCiB3DZDLBoUOr3kIB4Pjx4wAohw9/agsIWyRC+2dKiV+9epXl\npSU8U1NMejxkZmUx7PeveS8pkbwikQhHq6tZnpvDm5JCenU1OUYjtc3NZBiNCT0vfBxcFiwv82pj\nIyMDA+Tk5mIqK6Pjk0EERVEY/PBDStPSmISkrQ4rdp6PPvqIpaUlAn4/7jt3+MngILWVlajLyuQ7\nKMQOIDN3Qogd6UmzIoqiYLl0iaWZGazRKFUHD8r6vG3urbfe4vXXX0ev13Pr5k20FsuDWQp1bS3B\nUIiTzz+f0M/YbDaTlpaGZWKC8OAgmampjM7NMRWN0nXoEEVFRYTDYebn57Fevkx2djYZ6emo6+sx\nZmVx7NixhLVNiJhYynDfmTPMXbxIRloawZoaGp55hqqqKvR6/VY3UYinnqRlCiGSUizICkej66p+\nmUgOh4OxkREGz5/nYH09Hr1eUpN2iEQV/Vnr+b0zM1y/dIn2jg5y6uspP3SIcDjMBbOZVIeDjrKy\nLWmfeLoNDg4yPz+P4nQyd+ECB3fvZmR2Fk1dHWnp6Tz//PNb0i5JVRbi1yS4E+IplcwPw1gH1zU2\nxkB/P50HDqDLy9vyjmx3d/eDf7ZZrejGx/H5fCxFItSePMmRo0e3rG0ifrb6t6EoCv/4ox8RGh5G\nr1ZTVVKCv6aGkMVCTXY2npQUTFLRVaxDvL7bWz0IAr9eA+hwOLj97rs05OXhYPVVkoXYqSS4E+Ip\npCgKY93dmKJRPDpdUj0MT58+TUtzMwMffogmEmF5bg4KCmhraMBfXMy//Xf/bqubCPy6c7M8N8fc\n8jJVhw9LZ1vEzcrO85m7dwlkZmK026krLyfHaES3e/emFHcRO4fD4WD66tW4FUJZb6AYrwBzbGyM\n8+fPMzw0RA3Q2dLC2MwMkaoqnjt5kuzs7HUfW4jtTII7IZ4iZrMZg8HA+NgY4aEhMnQ6HD4fisnE\nf/6d30GtVm9qex71kI91bNP8fvrv3qWxpYVlgyGpgtAH5erHxhi5eJFDdXVSOU7E1crfB7DlMyVi\ne7pw4QLRaBTHwgKBvj4MqamEVSq0DQ3U1tXR1NS0aW1xOp0MfPAB1ZmZG/oeK4rC1OQkTkWhpKQE\n3+Cg/DaE+IQEd0I8hWLBkzEUondqisojR2hra0OlWvO9YENtuP/BBxTp9bi12s89kJN5zV13dzda\nrZaUlBTGx8bQjI+TazIRjUYJVlWRajBw+PDhrW7mjrHVaZLJQt4HsRH9/f2MdXfTUV6OU6VacxC0\n0e/fn/7pn5KTnY1hfp7GmhrCoRCh2lpOrmGd3oOCLr/8JSpFQVdQQP2JEwDy2xDiExLcCfGUij2o\n09LTURSFYDBITU0NPp8v4Q/Jy5cvMzM9zfyVKxhSUznQ0UHmgQMJSTNLdId4Zfrc6OIizQmuqvg0\niXXk7p05Q3FKCotJlkIsxHagKArDQ0OEwmHq6uoI+Hxruh+azWYWFxcx/8u/0JCby1wgQNeLL7L/\n4MFVH2N5eZmhoSGi0SgRi4UCjWZds2xms5n33n2XA/n5ZGdmEgqH2fWlL0mKshArSHAnhABgbm6O\n4eFhdPPzVGZkbDi95UlB1cTEBFd+8APKwmHsGRm0feMbVFdXb/QyPteGwQ8/JF+rTejaQplRSQyz\n2YzNasV18yZ15eWkZ2RQePy4dOSEWCVFURg6e5bIwgL6oiKqjx3DaDSuOQV/ymJB3ddH0O+n58MP\nKe3sxFBc/Nh7auy+qNZqWVhYoLCwkMLCwg3fL5OhmIsQyUw2MRdCYDabsVgsqKJRIiMjqGtq8Pn9\nZLe0bPjhOxmJfG6j5e7ubuw2GzOBANWtrYTtdm7euMHS0hK7du3a0LWcPn2arq4uvB4PdrudyNAQ\n6ampZGZnM+j1JmS/MpPJJJ2LBDh+/DiKomC2WtFGIiynpCR0I3EhdgKz2YzL5aKpqYnbt26hmZig\nIDubicFBpoHKqipyc3MpKSlZ9TEzjEYmgR++/TbV6emkejwUhUJ43O5H7gc6efkyBr+fu7OzdHzx\nixQWFgIbv1+aTCY4dAiP2025DKgJETcS3Amxgxw/fhz4/IjoejrSb775JgcPHMBx6xbqcJhALYKE\nlgAAIABJREFUKMTl8XF+8+tff/AQPnbsGIqiUJuWRlY4jDY/n5rjx+PykP7mN7/JxMWLaEIhesfH\nMajVRFwujA0N7JWUyW0pHI0SiEZJ2eqGCLENxO7nAHl5eQ/u6ZlPmGl7nFhA9dtlZSgDA9QajR+n\noT/iGeFWFPLVatRpabSVlqJdxUzhWmb0ZEBNiPiTtEwhdqh4pBjGgkT/9DS3b97k4LFjkJX1yKIp\n8UhnNJvN6HQ6pqemGDh7Fo+ioLXbWUhNhWiUL/72b/PlV1/d0DnE5vkv/+W/cPz4ceZmZ3HfvMm+\ntjZGpqcxtLTw0iuvbHXzhNg24p02/qTjnT59mn379jF/9y7ZGg3OcJjMmhreeOONxx7TcunSutfi\nCSF+TdbcCSHirqenh7m5OW719FAcDFJSUIB/aYn59HRaWlvR6/UcOHAgIedeuY3CzZ4ecgsLmXC5\ncGVm8vzJk5TJXnTbQqwD6VAUbv7Lv9BVV0f4IQMEQojktJag8k5vL/6rV+nas4d5u53lxkYqqqo2\np6FC7DAS3AkhEmarFr5/dhsFxe3m0ttvU56WRk59PUX79iXd9griY5FIBEVRGDWbUS8uMnzvHprU\nVIwVFTScOEFlZeVWN1GILbHTCjcpisKbp09z6PBh7HY7qS4X2qUlounptJ08SUdHx1Y3UYhtSYI7\nIXaIZH3wb2W7uru7AbDOz5M+M0Ou0ciVW7dwhMMcbW5mLhCg44UXaG1t3dR2bXeJ2oOwt7cXl8uF\nS1FYvnePD69cQeNw0L5/P7vb26VSpngqxbYEmbh4kUKtlhG3G9OuXZRu4ywERVEY6+4mND/P9NIS\nR37zN9HpdEn5DBNiu5FqmUJsc7EH/6jZjDEUwpmW9rnqlE+rY8eOAR93JP7k93+fE62thNPSaDWZ\n0Gm1pEcijI+NUVlZSWZm5ha3NjlFIpFPlU2PrY1J9fnov3uXxpYWJgFjHDqb7e3tD84xqdXSUlvL\n/b4+mltb8aelSaVM8VS6cOEC1rk5HD09FBcWYhsZQdPbS+Tw4W13r79w4QLRaBS7zYZhZgadWk1+\nairdZjMlpaUcPHhwq5soxFNLZu6ESBL9/f3c6+8nY2qK6ZkZMkwmdI2NvHbq1FY37UEgkK9WsxCN\nfiotc7Nn9FbONrn7+2WPpFXq7e1FURRsNhtZWVmMDg3Rd+4cBp0Oz9QUKSUltGZloSospPPAgbi9\nn4maHRRiO7p37x6/+Pu/x2Wz4Z+d5aUvfpFFv5+qEyfY3dm51c1bM9mrTojEkbRMIXaAiYkJzN/9\nLvU6HVaDgY7f+q3PrU3azGDKbDajUqkYHhoi1+nE7/PhD4Vo/dKX2NfV9eDBnhUO49JoNv3Bnqwp\nrMnM4XAwffUqeo+HGzdu8LPr16nNy6O+pobRgQH2HT1KKBolZ+9eUKspKyujpqZmq5stxLa3vLxM\nf38/arWakaEhMhcXaS0uTnhQlOgBFrkPC5EYEtwJsY3FgqhoOIz75k38gQDLoRB5+/Z9qlx8bH1D\nsV6/6YVNJi9fRut2889XrlDV1UV5eTnzc3MwMoJepSKs0aCpqyMnL4+jR48mvE1ifX789ttoxseZ\nnp2lLD8fT3ExUY2GgMdDmsdDV00NFo+HhmeflaInQsSJoijc7OnBFwjQ0NBAVVUVXq83IUHRyhRs\nh8PB8LlzBGZmuH/vHoePHydiNMoMmxDbgAR3QuwAj0txURSF3/vmN+kwGulsb6equBhNR8emFaaI\njc5q9XoURUGtVhMMBpm6coXMYBC3VsuBU6fIzs7elPaI9VEUhXtnzmDw+bD4fATy8hh4/312V1QQ\nzMoiGg7TXlZGwGCQDqDYtpJpNsnhcHD/gw+YuXuXvIYGOr74xYS2yWw2c//+fZqamvh/fvhDMvx+\nDtTV0XP1Km0HDzI8Pc0z/+bfsP/AAYzbbP1rMn2uQiSaBHdC7BCffXitLLTiHB/HZbfT2tbGUnp6\n3NdFrfaBGY1GGRwc5N6ZM+TqdNhDIYxNTRQWFpKVmSkP3iQUG813OBzc+dd/5W/++3+nqqYGdX4+\nvjt3mFAU8rOzWVxcpL21lV0VFYQqK/nK669vddOFWDVFUZienMTR30+9ybSl68AuXLhAVlYWfXfu\n4OjpwZSdTa7JhKeoiFOP2Qg8nlbuFxornLT8ycCNSqUiKytr09qx0aAsllIu6/vE00KCOyF2ILPZ\njFqtZikQwH3rFlXFxdwbG8Obl8dvvPYahYWFGz6HoigMvP8+BVot3pSUVT8w/+Bb36IM2FNXx/DE\nBJm7d+MdGqKrtpZodjalBw6Qk5Oz4faJ+Lh27RpLS0tY5+fRjI+TYTAwY7MxoVKxKyuLY7t2MeJ2\nowaqjUbpPO1AO33Ww+Fw8JP/9t9QezxMj4xgLCigtLQUi0ZDbm4uX3711U2/bofDwcXubtRWK3sr\nKrbkd7XVRY0cDgeTly9TqNWu+/rNZjNTk5PYrl+nrbER/9ISgbIyjh0/TkFBwZqOtdN/B2LnkOBO\niB0sERXJYoHj/NwcocFBQoEAYZWK5377t1eV6hlr03BfH9H0dPwZGaRNTZGbk4Nlfp70lhby8vNR\nq9WyBi+JxD43vc/H/b4+0jMzISeHos5OSsvLAaTjswPFKt4WaDTMh0JUHjmyoz7fb3/721SWlcHY\nGBnp6bh7e8lITcUeDFJbXk6a0UhaSwstL7ywadftcDgYOX8evdeLLyUlLtuMbIWNBENmsxmb1Urq\n9DRZqamMWa0U7dtH1xqeYdFolLm5OYaHh1HPzFC7gRlZRVEYv3CBfI0GB8gAlkhqEtwJscMlarQx\n1tk3RSLcnZmhoLOTiooKlvz+J55rZZsA7n3wAdUZGTLrk6RihXsMBgM9165hdDgoKSggVa9nMj2d\ngsJCamtrKSkp2eqmijiIfd7p6el0m81k2e201dVhsdnIaG+nrLycpqamrW7mhsXuYd/5/vdx2e20\n1ddjGxvDn5qK1ulkxOnkaFMTkbw86o4c4dRv/mbC7k2x91ytVhMJhXDduEFWZiaRSITF4mIOHT5M\nbm5uQs6dCIqiMHzuHIV6PRavd12brsc+H2VigqH+fo4cO8ZyRsaqnhGBQICxsTG0Wm1citD87je/\nSXNqKsX5+ehTUmj9ylc2bd26EGslwZ0QYt1iQVp6ZubHI6TnzrGvuvpze9qt9jgbDUAlbSbxZH+q\np8vExATmH/2IqpwcTOXlO+bzPn36NJ179pAyOYnb6SQE9DgcqOx2nmlpoa+3lyKtlqhGg1Ol4uWX\nX36w5izR179df2OnT5/mxIkTRKNRFIeDxd5e/F4vPpuN/KoqWru61px2/+677zJtsVDgdlNYUIAK\nKH3uOcofUpE3dv/3Ly3h8/koKSkhPz9/Q9cUDoeZnp7GYrGgmp7e0OyfEJtFgjshxIbFUmhUY2OU\n5OdjSEkh58iRTR3ZVBSFiYsXKdBo1hxcJrNkDFiTsU0i/mKFKOb6+yE7m4aTJykvL39QLn+7i1WA\njVitTPr9pDc2cre3l4zMTFxuN96JCZadTvJ0Ohr37CESjXLw61/flPvadv+NvffeezgGBrCOjeGd\nnOTEF7+I3e3GuHs3J06eXNOxVhPsxtbnYbczHQiw99VX1722PPbeL4dCeDweTCYTpaWlLC4ubuvP\nRDw91hvcaRPRGCHE9nT8+PHPPYAzNrlU9o2PPmLhzh2sqaloU1OZVal48eWXN7UN8eRwOJidnsY9\nMEC10chkJAJJErCaTKakaIdIDLPZDEDv7dtUhcMsBQKoHQ7+8vvf57XXX8dgMNDR0bHFrYyPCBAE\nloNB5i9cwHvvHsGiInpmZ6nW6+lobGTu+nWMMzP4cnIIb9Ig8nb/jX3hC19gqL6eu729mHw+6goK\nyIpEKN+7d83HMplMcOgQHreb8kcEVmc//JD0mRlS9HqWPR6CS0vranfsORax25nyetn9pS9RWlr6\noB3b+TMR4klk5k4I8TlbOdo8MTHB4LlzpPp8BFJT6XrttW31II5tORAryX7+nXdwWa3oHA66jh2j\nqLAQd0kJ9U1N2+q6xPalKAqjZjP+6WmMVVU7ZjYc4Dvf+Q411dXkORy4FxcZGx9nQVGY6++nqb2d\nzMOHUYaGCLndzA8Pc/DoUSYdDtpeeYWXXnllq5uf1JxOJ0P37xMBOjs78fl8CX8uxCuV9SfvvANj\nY2RlZKC43USqqzdt+wkh4kXSMoUQa5ZsKUOx9DGVojDp8aCtqqK6uppUvX7LynivldlsRqPR0Pvh\nh0TdbgKzs2RXVGAdH6ekpobxyUmOHjxI3g7rZIvkNjw8zNVLlzj6zDNUPmSd03a2MiB458oVUKmw\njo5CWhrH3niDpaUlJq9do3hpibz0dFSNjTRtYtXM7ShWSEXldKLJz6fq6NFNe7/i8VzarusdhVhp\nS4M7lUr1MvB/AWrgb6PR6H/9zP9/BvgpMPrJf3onGo2+9YhjSXAnxCZY+fBLhtLo3d3dOBYWUI2N\nUZydze3793Hm5JDt89FYVMTk2Bh7OjsJGY1J/aCOrVs0TE0xNTvLxP37HNi7F3dqKpm1teRZrbQ0\nNOAPBgk1NUmlNpFwK2fuMioqtvy3nggrAwKXy8Wf/cEf0FRUxKTXS3lrKwVeL3m5uUxMT6Orq6O2\nvp6ampptURl2swbhuru7GRgYoL29nbmZGbIXFtBqNFidTrQNDVTX1NDS0pKw88dbsg1eCrFWWxbc\nqVQqNTAInARmgOvA16LR6MCKv3kG+FY0Gv2NVRxPgjshEuj06dOcPHmS2ZkZtBYLGXo9wVCIUG0t\nwWCQ8ooKurq6EnLuJz1sPzva+v+ZzWhtNlK0WiIzMxw4cQJPOExGWxumnJyEtXOjFEWh78wZ9D4f\nP71yhXG3m5LSUoqLi/FOTNBWXo4zEqGorY3i4uIds+5JJKc/+Na3yF9eprawkLSMDEqOHSM/P39H\ndnpPnz7NoYMH8d6+jUalYrK3l5qODpa9XhpbWjatUmY8RCIR3G43995/n3y1Gn9aWsLbvnLDc3d/\nv8x8CbGFtjK4Owj8H9Fo9JVP/v1/BaIrZ+8+Ce7+IBqNfnkVx5PgTohNEAuksqNResbG8Pr9HKqv\nx6PXx/1BHlt/5rp3j2qj8UEVTKPR+LmKfZ8dgXf39z/YcLu5tXVTOjjrEVtrBx9fw/V//mcC09N4\nUlJQV1Rw6+c/54WuLlKLishqatqWmxmL7Sn2W1+0WFjOyIBolIr0dLypqUn5W9qo2PV+dPEirpkZ\n6tvbMaSkkLF797Za62o2m7FMTGC7fJmioiKysrIIlJXx+qlTCTmfoij0/+pXlBkMuDQajM3NcUmF\nlxk0IdZnK6tllgKTK/59Ctj/kL87pFKpbgHTwP8cjUb743BuIcQ6mUwmLgODPh/e9HT0isLo9DSL\nfj8+k4nlUIhjx45t+DyKovDPf/3XOKemiMzNsdDVRUStxp+dTU1dHXl5eZ9rV6wDYDKZULKy8Ljd\ndOzbh0alIi9JOwjDw8PMz89jMpkYGRoiurDAhNOJ1+9ntL+fxsxMtGlp+O12DMFgUl6D2JliVQrv\nZmTQ39tLxvw8nqwsFgMBPpqe5rU33thR38fY9arLylAGBqg1Gj+efdpGgR1ARUUFU9eu0ZqXRxqg\nKSmhaY3bD6zGt7/9bTr37GF6epq0mRnUTU3MORzowmHUGg2vbKDwTCzQTvF6GV5aIr+9XQa2hEiw\nzdoKoQeoiEajPpVK9QrwE6Bhk84txLa30ZHPR70+9tCO7S2XGQrh1evj2gn64P33ydZoKK2vp29x\nkdK8PPRFRZTv2rWqc2yXstUNDQ00NHx8WysvL2cyLY1D7e3YIhFsKSnYb96kJDf345nHmpotbq14\nWqz87efm5VFZUYHL76e6vJy+W7c4lpPz8b5imziDtzL1L1FFkmL3DaW8/LGl95ORoii880//xPj4\nONXhMI6MDDw+H/l6PYfifA2KonDqwAFCVisajYbcPXuoyskhvahow7O6d+/e5f7AANaPPiIzJYWR\nO3couX2bgydOJM12MELsRPEI7qaBlRUByj75bw9Eo1HPin/+hUql+iuVSpUTjUYdDzvgn/zJnzz4\n52effZZnn302Ds0UYnvp6en5uPS0x8PM7dvgdqMxmajYt4+0tDQOHTq0quPEKlDmq9WP3GPNZDLB\nkSN43G5y4twJOvn88w/W0aUXFZG6a9eOH7lduZ9TRjiM+9o1GoqLGVtcpGHv3h197SJ5rEy9vuV0\n4vf58Fks3LPZuGOzUbq8jM3lQpmaIlxYyO7Ozk1rk97no6+3l/qGBpw5OQnr7G+XwaGY2PtTtbhI\nRnY2OXl5tBYWPlj3Fg8rU8g9bje5KhVZNTVUhkLYS0oIZWXFJRh2OBykZ2RQUFGBMjNDSX4+pSUl\njPT3M+j1squpiV27dqHRaNZ0XEnzFDvVuXPnOHfu3IaPE481dxrgPh8XVJkFrgFfj0aj91b8TWE0\nGp3/5J/3A/8YjUarHnE8WXMnxApTFgua/n70ajUDIyMsNzZSW1ODcRWdFrPZjM/jwXXrFsUmEzaP\nhwNf+9qmV2h82h7Gvb29DAwMUFxcjHV+Hs3EBDlGI0MWC/r6er7xH/7DVjdRPAX+6cc/RjMxwZLX\ni9Xh4MbAAM3l5WTn59P11a+inpvblIIZZrOZtLQ0gsEgtvl5LBcuEIlGuffRR+RWVaHR6Qjm5fG/\n/OEfPhX3h0cxm82Eg0GW792jJD+f6fl5rEYjtXV1tLS2xu29+au/+iva2trQ6XQsLy8ze+sW2Wo1\ns4EANQcOAMQlJR/A5/MRCASYnZ7GPTBAdSxFdp3fN7vdTv+vfkV9To4UehE7XjJshfB/8+utEP5c\npVL9j3xcWOWvVSrVfwb+JyAI+IHfj0ajVx9xLAnuhFghljJZqNVy327H6XDQXlaGNyWF0gMHyMnJ\nWdXrNYrCqMtF+xe+QFVV1eY0Xsh+S2LLrPzujbjdqIFCnY6rQ0PUHT9OQVHRpu8dqSgKt37+c3Re\nL/f7+mhsamJocJCDR44QTE9/6n8fW3G/cDgc2G028gsLN6US53q/b3/4h39IUWEhjdEoaenpOBcX\nUdXU8OprryWgtUJsPdnEXIgd7I/+6I8oKizE7XZzODcXlVqNw+0mXFlJQWHhE0dZYw9VlUaDoiik\npaVhNBoJ+Hxx6dg9bTNzayXvj9gqK797ANOTk0x99BEVBsOm7xkZa8vZ8+exWa3k5OYyNTFBS0oK\naWlp9A4OUnLwIK+fOoXBYNiUNiUjuV98LPY+aPV6FhcXCQaDGI1GnHfuyGCZeCpIcCfEUyAeo7qR\nSISBgQGGz52jpagI3wa3Foi1KdXnQ1GrqT9xQh62QiSpH7/9NqlTU9SUlTExO0u4upovffmJuxSt\nW2x9l8PhYNRsRqUoBNLSmFap8LjdFJeWEp6YIDIwgDE3F92uXbS88ILcQ55ysYwTldPJmMtF0wsv\nUF9fj0qlkuBXPDW2cisEIcQTxOthtLJQx3oXvF+8eJEFq5VlRWEcUKvV6y6mcOnSJbweD/rJSZaW\nlrja20vvwgK7mpupLC+Xh68QSeb5F15g8vJlctRqwhkZcSvS8ShXrlxhcnISnVZL5vw8S34/M/Pz\n3LVYaM3NJRqJ0O9ykaHT0ZiXR3hhAY/bLfeNJJfIACu2Vtxz9y6aaJSwSsXdO3ceVCPebkVyhNhs\nMnMnRALERqsVRWGgvx9nXx97KiqSJo0knus6Vh5rZmkJV2YmvsFB2svKUNTqpLheIcSvbcXMR+w+\n8f/+6Ec0NDQQ8fmoKynBFwyS2tJCYTgsqXZJbGWFTUVRsFy6RJ5KhR0S8nnJWmUhJC1TiKRy7tw5\nBgcHic7PY7dYyAgGySgrIyc7m1BFBRqtlte2eBF4PDt4sWP91Q9+wN7OToyzs+hTUvAFAglP+xJC\nbA8r97eb7+kBu520srIHs4eSape8rl+/jt/vZ3JykuVAAEZHqa2qwuF2E6mqoqm5maamprieU9Iv\nxdNOgjshksB3vvMdXn75ZTQaDR9+8AHtqam4vF7G79zBVFqKR6fj67/zO5vyoNqqB6OMuAohnsRu\nt3P96lUOHj4s94c4SPT9XlEUHAsLOBSFSCSCZnaW0tTUNd/jN/O5JMGh2O4kuBMiyXy2DLlpEzfv\n3uoASx6qQognuXjxIsWFheTk5cl9YgMURWHk/PkHwdZqtshZrUgkgtvtZvLyZYLz87i1Wjq++EVU\nnxTEWc09PpbSubCwwMTFixTr9QlL54yZn5/n/gcf0JCbK4OMYtuSgipCJJmVxU9aNjnI8bjd6BYX\nCaWkYNLpNr1AgSx4F0J81mfXbbn7+8mdnmYyMxOk870u58+fZ3hwkKWBAZobGohGoygGA8eeeSYu\nxx8eHqb39m20FgvN1dVYxsbwLi5SVlGx6s/rwoULBINBbt26RaHHw1J5OZd6e6n2ejn1xhtxaSd8\nXIglEomwvLzMndu3yfd4UJWXY3e5GPR6qauvp7i4mIKCgridU4hkJDN3QuxA7777Lra+PlSLi5iK\nimh56SXq6uq2ullCiKfYX/zFX3DixAlCoRB+rxfbtWtElpdJMRhQ1dZSWFzM7t27MRgMMvv/BIqi\nYLfZsDudqNVq1DMzlKSkJGSWaj2ZILHPT6PTsbi4SCgUStgedYqi4HI68QUCLC8vk5ubS2pqKrPX\nr8vyALGtSVqmEOJTJiYm0KhUaHQ6XC4XKpUKo9FIOBiUDpMQYkvFAgaD38/d2Vlqn3kGk9FIhtFI\nJBJh6soVCjQa6Zg/ROy9809PEzAYaP/CF4DEFqRZS7Ada1/UbmfM5aLlpZeora2N6x51kUgEALfb\nzcj58/impggYDLS98gpFRUVrbrMQyUiCOyHEYw0PD9P3y19SazIRNpmoPHIEo9H4IE1KCCE2U6zz\nrbjdDJ09S5nBgC0c5rbNRnBsjJOHDhEKhah95RXKKiq2urlJwWw2s2CzoZ2YoDA3l7mFBfZ+9atb\n/v6YzWbS0tIIhUI47HbCg4MUmkxYXS6Wy8vJLyjA5/Px8ssvx+V8p0+f5sSJEyhOJ+GhIcoLCrg5\nOEjzSy9x+OjRuJxDiK0mwZ0Q4qG6u7tRq9XMzszA2BiNpaWMTE7iKS1l9549tLa2bnUThRBPIbPZ\njE6nY2Z6mpTpaXQqFc7FRfxFRewtLpaZu0fY6oJZT7KZ7Uv290KIjZDgTgjxWLGHYIrfjz0cJlxc\nTEVFBaWlpWg0mq1unhDiKfWwDjrIvnePk0wphw9ri2x5IMTGSXAnxDaxlQ+ilefOzMxkamoKt9uN\n0WhEo1LJw1EIsSWkg749fTYwj+c2DEI87SS4EyLJrdwvKCscxqXRJEUKyeTkJDd/9jPay8pwaTRU\nHjmy5W0SQgiRvN58802effZZZqencd26RXpGBr6lJVnzJkQcSXAnRJIzm83YrFbU4+OEAgECS0s4\n8/L45u/+7pa0p7+/n1AoxLkPP6QiFCI/Oxur04lFq+U3Xn2V6urqLWmXEEKI5BSbYU3PzGR5eZnB\nwUHCExM05uWxEI0mxYClEDuFBHdCbAOxFJY8lYoRRYGyMsrLyykpKUGn0216e9xuN5FIZN17GIWj\nUUnnFEKIp0Ds+ZURDNI/O0v+nj10dHTg9/slpVaIBJDgToht4rPr3mZnZ7Hb7RQWFpKSkoJ3cfGh\nD8lErklZ6x5Gw+fOoff7Gbp3j4aGBsjNlRFbIYTYgcxmM2q1Guv8PJrxcXRqNb5AAN2uXdQ1NNDS\n0pLwNqzn+SfrOMV2J8GdENvY0tIS/f39TF6+THNREf60NMoPHXqwD53D4WDqyhU0Lhcho5HyQ4dW\nvWg9ng+4733ve9wfGCBVUYgEgzSkpKArLiaq15O9ezd7OjtRFIXOzs4NnUcIIURy2aptB+x2O0Nn\nz1KVmfnE8yqKwoLNhtVmwzMwQHtpqWyRILat9QZ32kQ0RgixNikpKeTn5jJgtzMTjZKeno5jYQGr\n1co//uM/0rRrF8b5eVThMIM9PZgUhY7dux87YrqygIsxHGZSo4ENPuC+8Y1v0Pvee3hv3GDB60UJ\nhagtLKSouRljczMalYqampp1H18IIURyMplMcOgQHreb8gTPhpnNZrKzs5mZmWF8dJTo+DjB+noc\nLhc2nQ6jycS+ffs+9ZqJiQn6f/UrxgYGcCwvU5aTQ0txMcN9fQTz8+n8zN8LsVPJzJ0QSWLlerz7\nCwtoKitpaGigoKAAl8v1YMR01OUiXFxMXV0dS0tL2GZnKSgpobKy8lPHM5vNOBYW0E9O4nI6CYRC\nBEtL6ezq+txD8UlOnz7NiRMn6L19m4y5OcLBIPfGxoiUldG0axdVVVX4R0epy84mZDRKOWwhhHjK\nrTdrJDb7prhcGAwGsrKycPT2PnQfxNt37qBWq1lYWGDR7aY2HMZgMGC127k9Ocm/f+45lj7JhJGZ\nO7HdSFqmEDvAyodhamoqFouFcDhMRUUFCwsLWGdmKCgpoaSkhL/8y7/E8uGHdBUUkF5RQcdv/dbn\nArxYwBh1OLh66RL7jxxBnZ295gddbBaw78wZRs+cIRwIEK6thbIy/vEHP+BgQwMp4TBHnnsOh9tN\npKqK10+dQqVa8z1JCCHENrfWFM5IJIJarUZRFEbNZvzT04Szsmh75RWys7M/9WwEmLx8GY3bzbDd\nTnFXFw0NDUSj0U+dM5ZNImvuxHYlaZlC7AAmk+lTD6GGhgYcDgc3b95keXSU5sJCbIpCVlYWI0ND\nHMzPZ8ZuJ2Npiflf/IL/4T/9p08d77vf/S779u1j1uslr6oKt89HyO1mOholPTOTY8eOPbFN/f39\n2O12xkZGsN64wYTFwrLXi9NqJb2oiP0tLXzluee4bDYzbLGgycri/2fvzoPjuu4D3397RzcavQBo\n7I19JwFwpyguImNZi8eSIzupeckr25mqZN6kJvljqiapes6rZB7lVM24Mkmscs1M/CYefEC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YNIMMjCxAR6k4kKmw1VUxOqTIanenqYXFx87O0hhBBivbjdbr73J3+CORIhbrXiPHqUopkZqsrL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\nhMz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ZzPXr18lIT6eipmbDnn2qlZlCiNQiRyEIsU0oisKN997D6PejLyhgfn4e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\njgrEFwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8ebb708050>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,15))\n",
+    "\n",
+    "G=nx.from_pandas_dataframe(retweetDf[0:500000:500], source='tweetId',target='retweeter')\n",
+    "\n",
+    "nx.draw_networkx(G,alpha=0.2,font_size=0, node_size=10)\n",
+    "plt.title('Extended 1000 Tweets')\n",
+    "plt.axis('equal')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here we see more distinctly that there are more dense communities which may persistently communicate over the event, with central or breaking information being more widely shared, as indicated in the first visualization. This is also an important consideration when developing more intensive network visualizations."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Individual Impact and Visualizing Centrality\n",
+    "There are clear leaders in any conversation, and this is observable in the network by simply allowing certain parameters of the visualization to be leveraged. Size and color are two of these features. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Helper Functions for Node Visualizations\n",
+    "We'll be using plotly as the way to visualize the rest of these graphs, for its extremely versatile and interactive interface. As part of this, we'll need to create special graphing features for the interface. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#create empty scatter objects for nodes and edges\n",
+    "\n",
+    "def init_edge():\n",
+    "    edge_trace = Scatter(\n",
+    "    x=[], \n",
+    "    y=[], \n",
+    "    line=Line(width=0.5,color='#888'),\n",
+    "    hoverinfo='none',\n",
+    "    mode='lines')\n",
+    "    return edge_trace\n",
+    "\n",
+    "def init_node(size=[],color=[]):\n",
+    "    node_trace = Scatter(\n",
+    "    x=[], \n",
+    "    y=[], \n",
+    "    text=[],\n",
+    "    mode='markers', \n",
+    "    hoverinfo='text',\n",
+    "    marker=Marker(\n",
+    "        color=color, \n",
+    "        size=size,         \n",
+    "        line=dict(width=0.5)))\n",
+    "    return node_trace\n",
+    "\n",
+    "def make_figure(data1, data2, title):\n",
+    "    fig = Figure(data=Data([data1, data2]),\n",
+    "             layout=Layout(\n",
+    "                title=title,\n",
+    "                titlefont=dict(size=16),\n",
+    "                showlegend=False, \n",
+    "                hovermode='closest',\n",
+    "                margin=dict(b=20,l=5,r=5,t=40),\n",
+    "                annotations=[ dict(\n",
+    "                    text=\"\",\n",
+    "                    showarrow=False,\n",
+    "                    xref=\"paper\", yref=\"paper\",\n",
+    "                    x=0.005, y=-0.002 ) ],\n",
+    "                xaxis=XAxis(showgrid=False, zeroline=False, showticklabels=False),\n",
+    "                yaxis=YAxis(showgrid=False, zeroline=False, showticklabels=False)))\n",
+    "    return fig"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Size as Centrality Visualization"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#create the graphing node from the dataframe\n",
+    "G=nx.from_pandas_dataframe(retweetDf[0:300000:100], source='tweetId',target='retweeter')\n",
+    "\n",
+    "#select a layout model\n",
+    "pos = nx.spring_layout(G)\n",
+    "\n",
+    "#using the layout model, assign positions of each user in the visualization\n",
+    "for n,p in pos.iteritems():\n",
+    "    G.node[n]['pos'] = p\n",
+    "\n",
+    "#create an empty scatter object to populated with edge information\n",
+    "edge_trace = init_edge()\n",
+    "\n",
+    "#populate the edge scatter object\n",
+    "for edge in G.edges():\n",
+    "    x0, y0 = G.node[edge[0]]['pos']\n",
+    "    x1, y1 = G.node[edge[1]]['pos']\n",
+    "    edge_trace['x'] += [x0, x1, None]\n",
+    "    edge_trace['y'] += [y0, y1, None]\n",
+    "\n",
+    "#create an empty scatter object to populate with node information\n",
+    "node_trace = init_node(color='blue')\n",
+    "\n",
+    "#populate the node scatter object\n",
+    "for node in G.nodes():\n",
+    "    x, y = G.node[node]['pos']\n",
+    "    node_trace['x'].append(x)\n",
+    "    node_trace['y'].append(y)\n",
+    "    node_trace['text'].append(str(node))\n",
+    "\n",
+    "#use the adjacency attribute to count the number of connections a node has, then map that to the size\n",
+    "for node, adjacencies in enumerate(G.adjacency_list()):\n",
+    "    node_trace['marker']['size'].append(len(adjacencies))\n",
+    "\n",
+    "#create the figure object\n",
+    "fig = make_figure(edge_trace, node_trace, '<br>The Network: Size as Centrality')\n",
+    "\n",
+    "#plot using the offline plotly system\n",
+    "iplot(fig)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Strikingly, Antonio French immediately stands out. This figure happens to be critical in the events that unfolded following Michael Brown's death. He is an Alderman in St. Louis, and in the 2014 unrest that followed the shooting, was an outspoken advocate, and was arrested during his time covering events in Ferguson. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Color as a Measure of Centrality"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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Color as Centrality\", \"titlefont\": {\"size\": 16}, \"xaxis\": {\"zeroline\": false, \"showticklabels\": false, \"showgrid\": false}, \"hovermode\": \"closest\", \"margin\": {\"r\": 5, \"b\": 20, \"t\": 40, \"l\": 5}, \"annotations\": [{\"xref\": \"paper\", \"yref\": \"paper\", \"text\": \"\", \"y\": -0.002, \"x\": 0.005, \"showarrow\": false}]}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})</script>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#create the graphing node from the dataframe\n",
+    "G=nx.from_pandas_dataframe(retweetDf[0:300000:100], source='tweetId',target='retweeter')\n",
+    "\n",
+    "#select a layout model\n",
+    "pos = nx.spring_layout(G)\n",
+    "\n",
+    "#using the layout model, assign positions of each user in the visualization\n",
+    "for n,p in pos.iteritems():\n",
+    "    G.node[n]['pos'] = p\n",
+    "\n",
+    "#create an empty scatter object to populated with edge information\n",
+    "edge_trace = init_edge()\n",
+    "\n",
+    "#populate the edge scatter object\n",
+    "for edge in G.edges():\n",
+    "    x0, y0 = G.node[edge[0]]['pos']\n",
+    "    x1, y1 = G.node[edge[1]]['pos']\n",
+    "    edge_trace['x'] += [x0, x1, None]\n",
+    "    edge_trace['y'] += [y0, y1, None]\n",
+    "\n",
+    "#create an empty scatter object to populate with node information\n",
+    "node_trace = init_node(size=10)\n",
+    "\n",
+    "#populate the node scatter object\n",
+    "for node in G.nodes():\n",
+    "    x, y = G.node[node]['pos']\n",
+    "    node_trace['x'].append(x)\n",
+    "    node_trace['y'].append(y)\n",
+    "    node_trace['text'].append(str(node))\n",
+    "\n",
+    "#use the adjacency attribute to count the number of connections a node has, then map that to the size\n",
+    "for node, adjacencies in enumerate(G.adjacency_list()):\n",
+    "    node_trace['marker']['color'].append(len(adjacencies))\n",
+    "\n",
+    "#create the figure object\n",
+    "fig = make_figure(edge_trace, node_trace, '<br>The Network: Color as Centrality')\n",
+    "\n",
+    "#plot using the offline plotly system\n",
+    "iplot(fig)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is still clear that Antonio French is still the center of information, but the extent to which he has impacted the network is lost. This is further an important consideration in visualization. Color is a great sorting metric, and in the next section we explore that quality by looking at hashtag networks."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Identifying Communities\n",
+    "Through color coding of hashtags, we can determine whether there are community relationships or discussions which exist primarily between certain aligning perspectives, or whether there was an even amount of cross-pollination between groups."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To begin, let's create a mapping of popular hashtags that align with supporters of Michael Brown and family, and supporters of Darren Wilson and the police. Then using this mapping, let's create a new data frame we can manipulate."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "hashtagMapBlue = ['MIKEBROWN','JUSTICEFORMIKEBROWN','HANDSUPDONTSHOOT',\n",
+    "                  'DONTSHOOT','CRIMEBUTNOTIME','POLICEBRUTALITY',\n",
+    "                  'P2','BEFREE','MIKEBROWNRALLY',\n",
+    "                  'STANDWITHFERGUSON','BLACKLIVESMATTER','OCCUPYFERGUSON',\n",
+    "                  'POLICESTATE','WHITEPRIVILEGE','IFTHEYGUNNEDMEDOWN',\n",
+    "                  'HANDSUP','NOJUSTICENOPEACE','WEGOTYOUSIS',\n",
+    "                  'RACISM','CIVILRIGHTS','FERGUSONCOVERUP',\n",
+    "                  'MIKEBROWNBHEARD','BLACKTWITTER','TRAYVONMARTIN',\n",
+    "                  'NMOS14','COPSLIE','NOJUSTICENOSLEEP',\n",
+    "                  'FTP','WHEREISDARRENWILSON','ARRESTDARRENWILSON','UNITEBLUE', 'TLOT']\n",
+    "\n",
+    "hashtagMapRed = ['TCOT','DARRENWILSON',\n",
+    "                 'GOP','WARONWHITES','REDNATIONRISING',\n",
+    "                 'TGDN','PJNET','2A',\n",
+    "                 'FOXNEWS','CAPTRONJOHNSON','BUNDYRANCH',\n",
+    "                 'CCOT','LNYHBT','NRA']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "creating dataframe\n"
+     ]
+    }
+   ],
+   "source": [
+    "#set up for data frame\n",
+    "retweetHT_Rows = []\n",
+    "tally_red = 0\n",
+    "tally_blue = 0\n",
+    "\n",
+    "#want to count the number of hashtags someone has used, and whatever type of hashtags are most prevalent, that person will get that designation\n",
+    "for i,tweet in retweetDf.iterrows():\n",
+    "    #look at the hashtags and sort them\n",
+    "    for hashtag in tweet['entities_hashtags_text']:\n",
+    "        mappedhashtag = hashtag.upper()\n",
+    "        if (mappedhashtag in hashtagMapRed):\n",
+    "            tally_red += 1\n",
+    "        if (mappedhashtag in hashtagMapBlue):\n",
+    "            tally_blue += 1\n",
+    "    #determine person's alignment\n",
+    "    if tally_red > tally_blue:\n",
+    "        mappedhashtag = 'red' #we use colors for the mapping\n",
+    "    elif tally_blue > tally_red:\n",
+    "        mappedhashtag = 'blue' \n",
+    "    else:\n",
+    "        mappedhashtag = 'green'\n",
+    "    #reset the tallies\n",
+    "    tally_red = 0\n",
+    "    tally_blue = 0\n",
+    "    #make a dataframe row\n",
+    "    retweetHT_Rows.append({\n",
+    "            'hashtag': mappedhashtag,\n",
+    "            'tweetId': tweet['tweetId'],\n",
+    "            'x': tweet['x'],\n",
+    "            'y': tweet['y'],\n",
+    "            'retweeter': tweet['retweeter'],\n",
+    "        })\n",
+    "            \n",
+    "print \"creating dataframe\"\n",
+    "retweetHashtagsDf = pd.DataFrame(retweetHT_Rows)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's visualize the network now with this coloration."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[]\n"
+     ]
+    },
+    {
+     "data": {
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-0.8375489711761475, 0.03651510924100876, -0.5296018719673157, 0.177965447306633], \"type\": \"scatter\"}], {\"showlegend\": false, \"yaxis\": {\"zeroline\": false, \"showticklabels\": false, \"showgrid\": false}, \"title\": \"<br>The Network: Hashtag Communities\", \"titlefont\": {\"size\": 16}, \"xaxis\": {\"zeroline\": false, \"showticklabels\": false, \"showgrid\": false}, \"hovermode\": \"closest\", \"margin\": {\"r\": 5, \"b\": 20, \"t\": 40, \"l\": 5}, \"annotations\": [{\"xref\": \"paper\", \"yref\": \"paper\", \"text\": \"\", \"y\": -0.002, \"x\": 0.005, \"showarrow\": false}]}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})</script>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#create the graphing node from the dataframe\n",
+    "G=nx.from_pandas_dataframe(retweetHashtagsDf[0:300000:100], source='tweetId',target='retweeter')\n",
+    "\n",
+    "#select a layout model\n",
+    "pos = nx.spring_layout(G)\n",
+    "\n",
+    "#using the layout model, assign positions of each user in the visualization\n",
+    "for n,p in pos.iteritems():\n",
+    "    G.node[n]['pos'] = p\n",
+    "\n",
+    "#create an empty scatter object to populated with edge information\n",
+    "edge_tracer = init_edge()\n",
+    "\n",
+    "#populate the edge scatter object\n",
+    "for edge in G.edges():\n",
+    "    x0, y0 = G.node[edge[0]]['pos']\n",
+    "    x1, y1 = G.node[edge[1]]['pos']\n",
+    "    edge_tracer['x'] += [x0, x1, None]\n",
+    "    edge_tracer['y'] += [y0, y1, None]\n",
+    "\n",
+    "#create a dictionary for color look-up to plot\n",
+    "color = {}\n",
+    "for i,tweet in retweetHashtagsDf.iterrows():\n",
+    "    color[tweet['tweetId'].upper()] = tweet['hashtag']\n",
+    "    color[tweet['retweeter'].upper()] = tweet['hashtag']\n",
+    "\n",
+    "#create an empty scatter object to populate with node information\n",
+    "node_tracer = init_node(color=[],size=[])\n",
+    "\n",
+    "#populate the node scatter object\n",
+    "for node in G.nodes():\n",
+    "    x, y = G.node[node]['pos']\n",
+    "    node_tracer['x'].append(x)\n",
+    "    node_tracer['y'].append(y)\n",
+    "    node_tracer['text'].append(str(node))\n",
+    "    node_tracer['marker']['color'].append(color.get(node))\n",
+    "\n",
+    "#use the adjacency attribute to count the number of connections a node has, then map that to the size\n",
+    "for node, adjacencies in enumerate(G.adjacency_list()):\n",
+    "    node_tracer['marker']['size'].append(len(adjacencies))\n",
+    "\n",
+    "#create the figure object\n",
+    "fig = make_figure(edge_tracer, node_tracer, '<br>The Network: Hashtag Communities')\n",
+    "\n",
+    "#plot using the offline plotly system\n",
+    "iplot(fig)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this we see that the more supportive of Michael Brown and family, or even neutral, parties are seeing more traction. But we also see that there are very few non-supporters in that network. Rather, it appears that there are more individual communities of these Darren Wilson supporters, implying that there might not be significant cross talk between these groups."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Mapping Networks\n",
+    "The placement of nodes in these previous graphs was based upon a spring model - there is some attraction between nodes which are \"closer together\" and no attraction between those that are further apart. This dataset also has an explicit position mapping through geographic coordinates. Mapping these networks physically could further yield insight about communities. \n",
+    "\n",
+    "To do this, we simply replace our position model layout with a dictionary of position coordinates from the data frame. First, we'll make a new dataframe with only populated coordinate data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "latLonPopulated_RTHT = retweetHashtagsDf[(retweetHashtagsDf['x'] != 0) & (retweetHashtagsDf['y'] != 0)]\n",
+    "\n",
+    "pos = {}\n",
+    "for i,tweet in latLonPopulated_RTHT.iterrows():\n",
+    "    pos[tweet['tweetId'].upper()] = np.asarray([tweet['x'],tweet['y']])\n",
+    "#     pos[tweet['retweeter'].upper()] = np.asarray([tweet['x'],tweet['y']])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We'll also need to set-up a map for reference behind the frame. Code for this is adapted from tutorials provided by matplotlib, plotly, and basemap."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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8qc5aJC1Gxo8fjxEjRkjdzypVqmDdunVYsmQJDh06lK/ZWEBAAJYvXy7z2JMn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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f8eb8bfa410>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#again, code adapted from https://plot.ly/ipython-notebooks/basemap-maps/\n",
+    "\n",
+    "#just rename the module for ease\n",
+    "m = Basemap()\n",
+    "\n",
+    "#just like before, we need to make a scatter frame\n",
+    "def make_scatter(x,y):\n",
+    "    return Scatter(x=x,\n",
+    "                   y=y,\n",
+    "                   mode='lines',\n",
+    "                   line=Line(color='black'),\n",
+    "                   name=' ')\n",
+    "\n",
+    "#this breaks down attributes of the baseline map and allows us to convert it to a scatter object for plotting\n",
+    "def polygons_to_traces(poly_paths, num_paths):\n",
+    "    #polypaths - the data to trace\n",
+    "    #num_paths - the number of contours to actually trace (since there are a lot)\n",
+    "    traces = []  \n",
+    "\n",
+    "    for i in range(num_paths):\n",
+    "        poly_path = poly_paths[i]\n",
+    "        \n",
+    "        # get the Basemap coordinates of each segment\n",
+    "        coords_cc = np.array(\n",
+    "            [(vertex[0],vertex[1]) \n",
+    "             for (vertex,code) in poly_path.iter_segments(simplify=False)])\n",
+    "        \n",
+    "        # convert coordinates to lon/lat by 'inverting' the Basemap projection\n",
+    "        lon_cc, lat_cc = m(coords_cc[:,0],coords_cc[:,1], inverse=True)\n",
+    "        \n",
+    "        # make the plotly data\n",
+    "        traces.append(make_scatter(lon_cc,lat_cc))\n",
+    "     \n",
+    "    return traces\n",
+    "\n",
+    "def get_coastline_traces():\n",
+    "    poly_paths = m.drawcoastlines().get_paths() # coastline polygon paths\n",
+    "    N_poly = 91  # use only the 91st biggest coastlines (i.e. no rivers)\n",
+    "    return polygons_to_traces(poly_paths, N_poly)\n",
+    "\n",
+    "#actually create the contour traces for the map\n",
+    "traces_cc = get_coastline_traces()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Further, given the scale of the map, we will plot the log-normalized sizes in order to have an opportunity to more closely examine locations of opinion (should they exist)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "G=nx.from_pandas_dataframe(latLonPopulated_RTHT, source='tweetId',target='retweeter')\n",
+    "\n",
+    "#create the specialized position matrix\n",
+    "pos = {}\n",
+    "color = {}\n",
+    "for i,tweet in latLonPopulated_RTHT.iterrows():\n",
+    "    pos[tweet['tweetId'].upper()] = np.asarray([tweet['x'],tweet['y']])\n",
+    "    pos[tweet['retweeter'].upper()] = np.asarray([tweet['x'],tweet['y']])\n",
+    "    color[tweet['tweetId'].upper()] = tweet['hashtag']\n",
+    "    color[tweet['retweeter'].upper()] = tweet['hashtag']\n",
+    "\n",
+    "for n,p in pos.iteritems():\n",
+    "    G.node[n]['pos'] = p\n",
+    "\n",
+    "pos = nx.get_node_attributes(G,'pos')\n",
+    "\n",
+    "edges = init_edge()\n",
+    "\n",
+    "for edge in G.edges():\n",
+    "    x0, y0 = G.node[edge[0]]['pos']\n",
+    "    x1, y1 = G.node[edge[1]]['pos']\n",
+    "    edges['x'] += [x0, x1, None]\n",
+    "    edges['y'] += [y0, y1, None]\n",
+    "\n",
+    "nodes = init_node(color=[],size=[])\n",
+    "\n",
+    "for node in G.nodes():\n",
+    "    x, y = G.node[node]['pos']\n",
+    "    nodes['x'].append(x)\n",
+    "    nodes['y'].append(y)\n",
+    "    nodes['marker']['color'].append(color.get(node))\n",
+    "    nodes['text'].append(str(node))\n",
+    "\n",
+    "for node, adjacencies in enumerate(G.adjacency_list()):\n",
+    "    nodes['marker']['size'].append(np.log(len(adjacencies))*10) #making the log normal sizing here\n",
+    "\n",
+    "\n",
+    "fig = Figure(data=Data([edges, nodes]+traces_cc), #not using specialized function here because of map tracing\n",
+    "             layout=Layout(\n",
+    "                title='<br> A Physical Mapping of the Network',\n",
+    "                titlefont=dict(size=16),\n",
+    "                showlegend=False, \n",
+    "                hovermode='closest',\n",
+    "                margin=dict(b=20,l=5,r=5,t=40),\n",
+    "                annotations=[ dict(\n",
+    "                    text=\"\",\n",
+    "                    showarrow=False,\n",
+    "                    xref=\"paper\", yref=\"paper\",\n",
+    "                    x=0.005, y=-0.002 ) ],\n",
+    "                xaxis=XAxis(range=[-180,180],showgrid=False, zeroline=False, showticklabels=False),\n",
+    "                yaxis=YAxis(range=[-75,75],showgrid=False, zeroline=False, showticklabels=False)))\n",
+    "\n",
+    "iplot(fig)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "What is striking about the map of the world is the spread of information outside of the United States. Zooming in to the country, we see immediately three nodes of officer-based support - Baltimore, a site of frequent white officer-black teen altercations and killings, being amongst these. A mapping like this allows us to immediately see the epicenter of the tweets - Ferguson - and the relationship of opinion, politics, and location. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Conclusions and Future Work in Networking\n",
+    "There is some obvious power in the various ways to visualize and leverage the attributes of a network graph to discuss social media, information spread. With further work - particularly in starting to develop analytical methods of defining communities and classifying information flow, adding external event data, etc - it may be possible to use network theory to start to analyze present versus virtual activism in social justice movements. This has far reaching impacts from informing groups like BlackLivesMatter on how to reach previously untapped communities, to mobilizing groups across the country. Even at the time of Ferguson, Twitter became a venue for memoralizing other young people who's lives were taken by police shootings, for supporting rallies in Los Angeles, and for truly real-time international reporting. In an increasingly connected world, we should learn what that means; we see potential here to begin that process."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/Change_The_World_Writeup.ipynb b/Change_The_World_Writeup.ipynb
new file mode 100644
index 0000000..1428f8a
--- /dev/null
+++ b/Change_The_World_Writeup.ipynb
@@ -0,0 +1,5296 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Ferguson - 2014\n",
+    "**Sophia and Victoria**\n",
+    "\n",
+    "In Ferguson Missouri the Summer 2014, an unarmed black teenager was shot 6 times and subsequently died from his wounds. The white officer was not indicted by a grand jury 3 months later. \n",
+    "\n",
+    "The initial incident and the following decision incited both a physical firestorm as the streets of Ferguson were filled with flame and protests, and virtually through social media as people from around the world weighed in. \n",
+    "\n",
+    "This project explores the phenomenon of social media activism, news sharing, and the relationship between the virtual and physical world through analysis of 13 million tweets over the two weeks following the shooting, and 15 million tweets about the indictment decision in the two weeks following.\n",
+    "\n",
+    "Specifically, we are interested in the kinds of visualizations helpful for understanding social justice-related events over twitter. Using spatial, temporal, and aggregate type graphs, we present a variety of graphs to highlight the various traits which could make the study of twitter data compelling."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Getting a dataset\n",
+    "To get the dataset of tweets mentioning Ferguson in the time after the shooting and around the time of the indictment, we found the following [list of tweet ids](https://archive.org/details/ferguson-tweet-ids). Since the Twitter API terms of service do not allow posting actual tweet content on the internet, we have to \"hydrate\" these tweets from their ids. \n",
+    "\n",
+    "We did this using a tool called twarc.py. [Documentation Here.](https://github.com/edsu/twarc). This tool allows us to point twarc.py at a file containing tweet ids. Then twarc hydrates the tweets by querying the twitter api for those ids, 100 at a time. In all it took the two of us about a week and a half to collect all the data. \n",
+    "\n",
+    "Unfortunately, as [this blog post](http://inkdroid.org/2014/08/30/a-ferguson-twitter-archive/) mentions, there are some gaps in the dataset containing the tweets after the time of the shooting. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Importing everthing!\n",
+    "Let's get ready to do some cool data things! Admittedly, we are using a specil package called [cartopy](http://scitools.org.uk/cartopy/) for mapping. To install, there is a pre-built binary/package for Anaconda which you can get through the command line: `conda install -c scitools cartopy`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/Sophia/anaconda/lib/python2.7/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n",
+      "  warnings.warn(self.msg_depr % (key, alt_key))\n"
+     ]
+    }
+   ],
+   "source": [
+    "% matplotlib inline\n",
+    "import pandas as pd\n",
+    "import json\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import time\n",
+    "from datetime import datetime\n",
+    "from datetime import date\n",
+    "from datetime import timedelta\n",
+    "\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets\n",
+    "import matplotlib.cm as cm\n",
+    "import seaborn as sns\n",
+    "\n",
+    "from matplotlib import animation\n",
+    "from IPython.display import HTML\n",
+    "from tempfile import NamedTemporaryFile"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Reading in Data\n",
+    "Here, we're using a function that we've developed to read in the data, a certain number of lines at a time. This function will take a while to read in all the tweets. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def ReadToDf(linesAtATime,filepath, max=-1):\n",
+    "    '''Read in the .json file of all of the tweets and convert them into a dataframe\n",
+    "    \n",
+    "    This function also has an optional argument max that can be used to speficy if only a certain number of tweets \n",
+    "    are desired.'''\n",
+    "    start = time.time()\n",
+    "    df = pd.DataFrame()\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filepath) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print \"number of tweets parsed: \", i\n",
+    "                print \"total time elapsed: \", time.time() - start\n",
+    "                df = pd.DataFrame(data=data).append(df)\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "        #Allow us to handle the last few tweets, and to truncate the data if we just want to run unit tests\n",
+    "            if (max > 0 and i >= max):\n",
+    "                break\n",
+    "        df = pd.DataFrame(data=data).append(df)\n",
+    "    #return the aggregation\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "number of tweets parsed:  500000\n",
+      "total time elapsed:  8.42842698097\n",
+      "number of tweets parsed:  1000000\n",
+      "total time elapsed:  18.3847298622\n",
+      "number of tweets parsed:  1500000\n",
+      "total time elapsed:  29.5955348015\n",
+      "number of tweets parsed:  2000000\n",
+      "total time elapsed:  42.0361249447\n",
+      "number of tweets parsed:  2500000\n",
+      "total time elapsed:  54.7786529064\n",
+      "number of tweets parsed:  3000000\n",
+      "total time elapsed:  68.3164279461\n",
+      "number of tweets parsed:  3500000\n",
+      "total time elapsed:  83.3426258564\n",
+      "number of tweets parsed:  4000000\n",
+      "total time elapsed:  97.4800388813\n",
+      "number of tweets parsed:  4500000\n",
+      "total time elapsed:  114.210583925\n",
+      "number of tweets parsed:  5000000\n",
+      "total time elapsed:  132.300080776\n",
+      "number of tweets parsed:  5500000\n",
+      "total time elapsed:  148.048592806\n",
+      "number of tweets parsed:  6000000\n",
+      "total time elapsed:  168.449382782\n",
+      "number of tweets parsed:  6500000\n",
+      "total time elapsed:  187.605800867\n",
+      "number of tweets parsed:  7000000\n",
+      "total time elapsed:  211.799097776\n",
+      "number of tweets parsed:  7500000\n",
+      "total time elapsed:  234.145410776\n",
+      "number of tweets parsed:  8000000\n",
+      "total time elapsed:  258.229158878\n",
+      "number of tweets parsed:  8500000\n",
+      "total time elapsed:  286.702250957\n",
+      "number of tweets parsed:  9000000\n",
+      "total time elapsed:  313.91174984\n",
+      "number of tweets parsed:  9500000\n",
+      "total time elapsed:  345.321898937\n",
+      "number of tweets parsed:  10000000\n",
+      "total time elapsed:  387.382420778\n",
+      "number of tweets parsed:  10500000\n",
+      "total time elapsed:  427.470818996\n",
+      "number of tweets parsed:  11000000\n",
+      "total time elapsed:  472.723701954\n"
+     ]
+    }
+   ],
+   "source": [
+    "shooting_df = ReadToDf(500000, 'data/cleanedShootingTweets.json')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>coordinates_x</th>\n",
+       "      <th>coordinates_y</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>retweet_count</th>\n",
+       "      <th>retweeted_status_id_str</th>\n",
+       "      <th>user_id_str</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_verified</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>499906559254986752</td>\n",
+       "      <td>33</td>\n",
+       "      <td>None</td>\n",
+       "      <td>1241255414</td>\n",
+       "      <td>Baris_DR</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[760827962]</td>\n",
+       "      <td>[VistoHLK]</td>\n",
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+       "      <td>8</td>\n",
+       "      <td>499905751163604993</td>\n",
+       "      <td>762556028</td>\n",
+       "      <td>FrantasticRadio</td>\n",
+       "      <td>False</td>\n",
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+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[1670129570]</td>\n",
+       "      <td>[SMBoucher_]</td>\n",
+       "      <td>499906559585951746</td>\n",
+       "      <td>1318</td>\n",
+       "      <td>499797954627403776</td>\n",
+       "      <td>983639826</td>\n",
+       "      <td>arisandhraaal</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[93292598]</td>\n",
+       "      <td>[TuckOnTheRise]</td>\n",
+       "      <td>499906559628288000</td>\n",
+       "      <td>34</td>\n",
+       "      <td>499739127949316096</td>\n",
+       "      <td>1676578380</td>\n",
+       "      <td>Jupvcx</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>499906559653449729</td>\n",
+       "      <td>2</td>\n",
+       "      <td>None</td>\n",
+       "      <td>117810285</td>\n",
+       "      <td>annemariemingo</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[63004503]</td>\n",
+       "      <td>[mlcalderone]</td>\n",
+       "      <td>499906559661854720</td>\n",
+       "      <td>2977</td>\n",
+       "      <td>499906107926917121</td>\n",
+       "      <td>1588428578</td>\n",
+       "      <td>TiniDo</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[1178700896]</td>\n",
+       "      <td>[ajam]</td>\n",
+       "      <td>499906560026370048</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>156824708</td>\n",
+       "      <td>HiRhy</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[18197912]</td>\n",
+       "      <td>[jackfrombkln]</td>\n",
+       "      <td>499906560190324736</td>\n",
+       "      <td>48078</td>\n",
+       "      <td>499531968229683200</td>\n",
+       "      <td>315935087</td>\n",
+       "      <td>_FlightToAsia</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson, SisterPatriots]</td>\n",
+       "      <td>[347627434]</td>\n",
+       "      <td>[LindaSuhler]</td>\n",
+       "      <td>499906560328749057</td>\n",
+       "      <td>60</td>\n",
+       "      <td>499763033414328320</td>\n",
+       "      <td>732980827</td>\n",
+       "      <td>ChristiChat</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[11771512]</td>\n",
+       "      <td>[OKnox]</td>\n",
+       "      <td>499906561222139904</td>\n",
+       "      <td>110</td>\n",
+       "      <td>499906334796812288</td>\n",
+       "      <td>18237351</td>\n",
+       "      <td>uplift17</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   coordinates_x  coordinates_y                      created_at  \\\n",
+       "0            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "1            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "2            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "3            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "4            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "5            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "6            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "7            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "8            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "9            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "\n",
+       "       entities_hashtags_text entities_user_mentions_id_str  \\\n",
+       "0                          []                            []   \n",
+       "1                  [Ferguson]                   [760827962]   \n",
+       "2                  [Ferguson]                  [1670129570]   \n",
+       "3                          []                    [93292598]   \n",
+       "4                  [Ferguson]                            []   \n",
+       "5                          []                    [63004503]   \n",
+       "6                          []                  [1178700896]   \n",
+       "7                  [Ferguson]                    [18197912]   \n",
+       "8  [Ferguson, SisterPatriots]                   [347627434]   \n",
+       "9                  [Ferguson]                    [11771512]   \n",
+       "\n",
+       "  entities_user_mentions_screen_name              id_str  retweet_count  \\\n",
+       "0                                 []  499906559254986752             33   \n",
+       "1                         [VistoHLK]  499906559552802816              8   \n",
+       "2                       [SMBoucher_]  499906559585951746           1318   \n",
+       "3                    [TuckOnTheRise]  499906559628288000             34   \n",
+       "4                                 []  499906559653449729              2   \n",
+       "5                      [mlcalderone]  499906559661854720           2977   \n",
+       "6                             [ajam]  499906560026370048              0   \n",
+       "7                     [jackfrombkln]  499906560190324736          48078   \n",
+       "8                      [LindaSuhler]  499906560328749057             60   \n",
+       "9                            [OKnox]  499906561222139904            110   \n",
+       "\n",
+       "  retweeted_status_id_str user_id_str user_screen_name user_verified  \n",
+       "0                    None  1241255414         Baris_DR         False  \n",
+       "1      499905751163604993   762556028  FrantasticRadio         False  \n",
+       "2      499797954627403776   983639826    arisandhraaal         False  \n",
+       "3      499739127949316096  1676578380           Jupvcx         False  \n",
+       "4                    None   117810285   annemariemingo         False  \n",
+       "5      499906107926917121  1588428578           TiniDo         False  \n",
+       "6                    None   156824708            HiRhy         False  \n",
+       "7      499531968229683200   315935087    _FlightToAsia         False  \n",
+       "8      499763033414328320   732980827      ChristiChat         False  \n",
+       "9      499906334796812288    18237351         uplift17         False  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shooting_df.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "number of tweets parsed:  500000\n",
+      "total time elapsed:  18.6331429482\n",
+      "number of tweets parsed:  1000000\n",
+      "total time elapsed:  28.0015799999\n",
+      "number of tweets parsed:  1500000\n",
+      "total time elapsed:  38.5282449722\n",
+      "number of tweets parsed:  2000000\n",
+      "total time elapsed:  50.155023098\n",
+      "number of tweets parsed:  2500000\n",
+      "total time elapsed:  61.9974660873\n",
+      "number of tweets parsed:  3000000\n",
+      "total time elapsed:  89.0536670685\n",
+      "number of tweets parsed:  3500000\n",
+      "total time elapsed:  105.817389965\n",
+      "number of tweets parsed:  4000000\n",
+      "total time elapsed:  120.09651494\n",
+      "number of tweets parsed:  4500000\n",
+      "total time elapsed:  134.684483051\n",
+      "number of tweets parsed:  5000000\n",
+      "total time elapsed:  150.199685097\n",
+      "number of tweets parsed:  5500000\n",
+      "total time elapsed:  220.092925072\n",
+      "number of tweets parsed:  6000000\n",
+      "total time elapsed:  252.059778929\n",
+      "number of tweets parsed:  6500000\n",
+      "total time elapsed:  270.389688969\n",
+      "number of tweets parsed:  7000000\n",
+      "total time elapsed:  289.102723122\n",
+      "number of tweets parsed:  7500000\n",
+      "total time elapsed:  313.567158937\n",
+      "number of tweets parsed:  8000000\n",
+      "total time elapsed:  340.885793924\n"
+     ]
+    }
+   ],
+   "source": [
+    "indictment_df = ReadToDf(500000, 'data/cleanedIndTweets.json')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>coordinates_x</th>\n",
+       "      <th>coordinates_y</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>retweet_count</th>\n",
+       "      <th>retweeted_status_id_str</th>\n",
+       "      <th>user_id_str</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_verified</th>\n",
+       "    </tr>\n",
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+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:14 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>541719359513980928</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>555589804</td>\n",
+       "      <td>wallyworkswell</td>\n",
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+       "    <tr>\n",
+       "      <th>1</th>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:14 +0000 2014</td>\n",
+       "      <td>[EricGarner, BlackLivesMatter, Ferguson]</td>\n",
+       "      <td>[1241761556, 125412208]</td>\n",
+       "      <td>[StatenStories, rockwitlili]</td>\n",
+       "      <td>541719360960995328</td>\n",
+       "      <td>11</td>\n",
+       "      <td>541718719156989953</td>\n",
+       "      <td>2251226729</td>\n",
+       "      <td>Iluvthewayymmf</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:16 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[11131522]</td>\n",
+       "      <td>[stimulator]</td>\n",
+       "      <td>541719365561745408</td>\n",
+       "      <td>52</td>\n",
+       "      <td>541683660483608576</td>\n",
+       "      <td>30693810</td>\n",
+       "      <td>Peta_de_Aztlan</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:16 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[11131522]</td>\n",
+       "      <td>[stimulator]</td>\n",
+       "      <td>541719365700173824</td>\n",
+       "      <td>52</td>\n",
+       "      <td>541683660483608576</td>\n",
+       "      <td>98631494</td>\n",
+       "      <td>Humane_Being</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:16 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[959596692]</td>\n",
+       "      <td>[KennettDems]</td>\n",
+       "      <td>541719368993087488</td>\n",
+       "      <td>11</td>\n",
+       "      <td>541717992925827074</td>\n",
+       "      <td>2904274533</td>\n",
+       "      <td>_forwardhope</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:17 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[14116807]</td>\n",
+       "      <td>[ShareThis]</td>\n",
+       "      <td>541719371194716160</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>64157934</td>\n",
+       "      <td>HauteLifestyle</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:18 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[407754987]</td>\n",
+       "      <td>[Ignacio_RT]</td>\n",
+       "      <td>541719374357606400</td>\n",
+       "      <td>84</td>\n",
+       "      <td>541714248511291392</td>\n",
+       "      <td>965597011</td>\n",
+       "      <td>martinezarcaya</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:18 +0000 2014</td>\n",
+       "      <td>[Alaska, EricGarner, Ferguson, BlackLivesMatter]</td>\n",
+       "      <td>[487600344]</td>\n",
+       "      <td>[Bipartisanism]</td>\n",
+       "      <td>541719375821025280</td>\n",
+       "      <td>722</td>\n",
+       "      <td>541464022613516289</td>\n",
+       "      <td>165341521</td>\n",
+       "      <td>VanessaHrndzzz</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Dec 07 22:22:19 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[407754987]</td>\n",
+       "      <td>[Ignacio_RT]</td>\n",
+       "      <td>541719379218825217</td>\n",
+       "      <td>84</td>\n",
+       "      <td>541714248511291392</td>\n",
+       "      <td>438948938</td>\n",
+       "      <td>harrysotopo</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>-122.46199</td>\n",
+       "      <td>38.290648</td>\n",
+       "      <td>Sun Dec 07 22:22:21 +0000 2014</td>\n",
+       "      <td>[ICantBreathe, Ferguson]</td>\n",
+       "      <td>[21879831]</td>\n",
+       "      <td>[ZerlinaMaxwell]</td>\n",
+       "      <td>541719388324253696</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>73267550</td>\n",
+       "      <td>SofieRKarasek</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   coordinates_x  coordinates_y                      created_at  \\\n",
+       "0            NaN            NaN  Sun Dec 07 22:22:14 +0000 2014   \n",
+       "1            NaN            NaN  Sun Dec 07 22:22:14 +0000 2014   \n",
+       "2            NaN            NaN  Sun Dec 07 22:22:16 +0000 2014   \n",
+       "3            NaN            NaN  Sun Dec 07 22:22:16 +0000 2014   \n",
+       "4            NaN            NaN  Sun Dec 07 22:22:16 +0000 2014   \n",
+       "5            NaN            NaN  Sun Dec 07 22:22:17 +0000 2014   \n",
+       "6            NaN            NaN  Sun Dec 07 22:22:18 +0000 2014   \n",
+       "7            NaN            NaN  Sun Dec 07 22:22:18 +0000 2014   \n",
+       "8            NaN            NaN  Sun Dec 07 22:22:19 +0000 2014   \n",
+       "9     -122.46199      38.290648  Sun Dec 07 22:22:21 +0000 2014   \n",
+       "\n",
+       "                             entities_hashtags_text  \\\n",
+       "0                                                []   \n",
+       "1          [EricGarner, BlackLivesMatter, Ferguson]   \n",
+       "2                                        [Ferguson]   \n",
+       "3                                        [Ferguson]   \n",
+       "4                                        [Ferguson]   \n",
+       "5                                                []   \n",
+       "6                                        [Ferguson]   \n",
+       "7  [Alaska, EricGarner, Ferguson, BlackLivesMatter]   \n",
+       "8                                        [Ferguson]   \n",
+       "9                          [ICantBreathe, Ferguson]   \n",
+       "\n",
+       "  entities_user_mentions_id_str entities_user_mentions_screen_name  \\\n",
+       "0                            []                                 []   \n",
+       "1       [1241761556, 125412208]       [StatenStories, rockwitlili]   \n",
+       "2                    [11131522]                       [stimulator]   \n",
+       "3                    [11131522]                       [stimulator]   \n",
+       "4                   [959596692]                      [KennettDems]   \n",
+       "5                    [14116807]                        [ShareThis]   \n",
+       "6                   [407754987]                       [Ignacio_RT]   \n",
+       "7                   [487600344]                    [Bipartisanism]   \n",
+       "8                   [407754987]                       [Ignacio_RT]   \n",
+       "9                    [21879831]                   [ZerlinaMaxwell]   \n",
+       "\n",
+       "               id_str  retweet_count retweeted_status_id_str user_id_str  \\\n",
+       "0  541719359513980928              0                    None   555589804   \n",
+       "1  541719360960995328             11      541718719156989953  2251226729   \n",
+       "2  541719365561745408             52      541683660483608576    30693810   \n",
+       "3  541719365700173824             52      541683660483608576    98631494   \n",
+       "4  541719368993087488             11      541717992925827074  2904274533   \n",
+       "5  541719371194716160              0                    None    64157934   \n",
+       "6  541719374357606400             84      541714248511291392   965597011   \n",
+       "7  541719375821025280            722      541464022613516289   165341521   \n",
+       "8  541719379218825217             84      541714248511291392   438948938   \n",
+       "9  541719388324253696              0                    None    73267550   \n",
+       "\n",
+       "  user_screen_name user_verified  \n",
+       "0   wallyworkswell         False  \n",
+       "1   Iluvthewayymmf         False  \n",
+       "2   Peta_de_Aztlan         False  \n",
+       "3     Humane_Being         False  \n",
+       "4     _forwardhope         False  \n",
+       "5   HauteLifestyle         False  \n",
+       "6   martinezarcaya         False  \n",
+       "7   VanessaHrndzzz         False  \n",
+       "8      harrysotopo         False  \n",
+       "9    SofieRKarasek         False  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "indictment_df.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cleaning Data\n",
+    "This is where we're going to clean data that we've read in. The only cleaning that we need to do is that we need to convert the \"created_at\" column to a datetime object. The rest of the cleaning data is done in the script `development_scripts/clean_json_data.py`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def recodeData (dataframe):\n",
+    "    # Creating a parseable dataset    \n",
+    "    dataframe['createdDatetime'] =  pd.to_datetime(\n",
+    "        dataframe['created_at'], \n",
+    "        format = '%a %b %d %H:%M:%S +0000 %Y')\n",
+    "    \n",
+    "    # Pull out hour and date data since we use these a lot and it takes a long time to get to them\n",
+    "    dataframe['createdDatetime_Date'] = dataframe['createdDatetime'].dt.date\n",
+    "    dataframe['createdDatetime_Hour'] = dataframe['createdDatetime'].dt.hour"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's recode the dates for the shooting data and the indictment data! These opperations are done in place, so we don't actually have to return anything"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "recoding shooting dataset\n",
+      "recoding indictment dataset\n",
+      "recoded all datasets\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('recoding shooting dataset')\n",
+    "recodeData(shooting_df)\n",
+    "print('recoding indictment dataset')\n",
+    "recodeData(indictment_df)\n",
+    "print('recoded all datasets')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Getting a Subset of the Data\n",
+    "Here, we are going to get a subset of the data. We are doing this because there is too much data to analyze in a timely manner. If we were going to tell the story of how the twitter world reacted to Ferguson, we would re-run our analysis on the entire dataset. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "shootingSubset = shooting_df[shooting_df.createdDatetime_Date.isin([date(2014,8,14),date(2014,8,15),date(2014,8,16)])]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>coordinates_x</th>\n",
+       "      <th>coordinates_y</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>retweet_count</th>\n",
+       "      <th>retweeted_status_id_str</th>\n",
+       "      <th>user_id_str</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_verified</th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>createdDatetime_Date</th>\n",
+       "      <th>createdDatetime_Hour</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>499906559254986752</td>\n",
+       "      <td>33</td>\n",
+       "      <td>None</td>\n",
+       "      <td>1241255414</td>\n",
+       "      <td>Baris_DR</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[760827962]</td>\n",
+       "      <td>[VistoHLK]</td>\n",
+       "      <td>499906559552802816</td>\n",
+       "      <td>8</td>\n",
+       "      <td>499905751163604993</td>\n",
+       "      <td>762556028</td>\n",
+       "      <td>FrantasticRadio</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[1670129570]</td>\n",
+       "      <td>[SMBoucher_]</td>\n",
+       "      <td>499906559585951746</td>\n",
+       "      <td>1318</td>\n",
+       "      <td>499797954627403776</td>\n",
+       "      <td>983639826</td>\n",
+       "      <td>arisandhraaal</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[93292598]</td>\n",
+       "      <td>[TuckOnTheRise]</td>\n",
+       "      <td>499906559628288000</td>\n",
+       "      <td>34</td>\n",
+       "      <td>499739127949316096</td>\n",
+       "      <td>1676578380</td>\n",
+       "      <td>Jupvcx</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>499906559653449729</td>\n",
+       "      <td>2</td>\n",
+       "      <td>None</td>\n",
+       "      <td>117810285</td>\n",
+       "      <td>annemariemingo</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[63004503]</td>\n",
+       "      <td>[mlcalderone]</td>\n",
+       "      <td>499906559661854720</td>\n",
+       "      <td>2977</td>\n",
+       "      <td>499906107926917121</td>\n",
+       "      <td>1588428578</td>\n",
+       "      <td>TiniDo</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[1178700896]</td>\n",
+       "      <td>[ajam]</td>\n",
+       "      <td>499906560026370048</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>156824708</td>\n",
+       "      <td>HiRhy</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[18197912]</td>\n",
+       "      <td>[jackfrombkln]</td>\n",
+       "      <td>499906560190324736</td>\n",
+       "      <td>48078</td>\n",
+       "      <td>499531968229683200</td>\n",
+       "      <td>315935087</td>\n",
+       "      <td>_FlightToAsia</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson, SisterPatriots]</td>\n",
+       "      <td>[347627434]</td>\n",
+       "      <td>[LindaSuhler]</td>\n",
+       "      <td>499906560328749057</td>\n",
+       "      <td>60</td>\n",
+       "      <td>499763033414328320</td>\n",
+       "      <td>732980827</td>\n",
+       "      <td>ChristiChat</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Thu Aug 14 13:13:06 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[11771512]</td>\n",
+       "      <td>[OKnox]</td>\n",
+       "      <td>499906561222139904</td>\n",
+       "      <td>110</td>\n",
+       "      <td>499906334796812288</td>\n",
+       "      <td>18237351</td>\n",
+       "      <td>uplift17</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   coordinates_x  coordinates_y                      created_at  \\\n",
+       "0            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "1            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "2            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "3            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "4            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "5            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "6            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "7            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "8            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "9            NaN            NaN  Thu Aug 14 13:13:06 +0000 2014   \n",
+       "\n",
+       "       entities_hashtags_text entities_user_mentions_id_str  \\\n",
+       "0                          []                            []   \n",
+       "1                  [Ferguson]                   [760827962]   \n",
+       "2                  [Ferguson]                  [1670129570]   \n",
+       "3                          []                    [93292598]   \n",
+       "4                  [Ferguson]                            []   \n",
+       "5                          []                    [63004503]   \n",
+       "6                          []                  [1178700896]   \n",
+       "7                  [Ferguson]                    [18197912]   \n",
+       "8  [Ferguson, SisterPatriots]                   [347627434]   \n",
+       "9                  [Ferguson]                    [11771512]   \n",
+       "\n",
+       "  entities_user_mentions_screen_name              id_str  retweet_count  \\\n",
+       "0                                 []  499906559254986752             33   \n",
+       "1                         [VistoHLK]  499906559552802816              8   \n",
+       "2                       [SMBoucher_]  499906559585951746           1318   \n",
+       "3                    [TuckOnTheRise]  499906559628288000             34   \n",
+       "4                                 []  499906559653449729              2   \n",
+       "5                      [mlcalderone]  499906559661854720           2977   \n",
+       "6                             [ajam]  499906560026370048              0   \n",
+       "7                     [jackfrombkln]  499906560190324736          48078   \n",
+       "8                      [LindaSuhler]  499906560328749057             60   \n",
+       "9                            [OKnox]  499906561222139904            110   \n",
+       "\n",
+       "  retweeted_status_id_str user_id_str user_screen_name user_verified  \\\n",
+       "0                    None  1241255414         Baris_DR         False   \n",
+       "1      499905751163604993   762556028  FrantasticRadio         False   \n",
+       "2      499797954627403776   983639826    arisandhraaal         False   \n",
+       "3      499739127949316096  1676578380           Jupvcx         False   \n",
+       "4                    None   117810285   annemariemingo         False   \n",
+       "5      499906107926917121  1588428578           TiniDo         False   \n",
+       "6                    None   156824708            HiRhy         False   \n",
+       "7      499531968229683200   315935087    _FlightToAsia         False   \n",
+       "8      499763033414328320   732980827      ChristiChat         False   \n",
+       "9      499906334796812288    18237351         uplift17         False   \n",
+       "\n",
+       "      createdDatetime createdDatetime_Date  createdDatetime_Hour  \n",
+       "0 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "1 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "2 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "3 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "4 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "5 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "6 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "7 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "8 2014-08-14 13:13:06           2014-08-14                    13  \n",
+       "9 2014-08-14 13:13:06           2014-08-14                    13  "
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shootingSubset.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "indictmentSubset = indictment_df[indictment_df.createdDatetime_Date.isin([date(2014,11,23),date(2014,11,24),date(2014,11,25)])]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>coordinates_x</th>\n",
+       "      <th>coordinates_y</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>retweet_count</th>\n",
+       "      <th>retweeted_status_id_str</th>\n",
+       "      <th>user_id_str</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_verified</th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>createdDatetime_Date</th>\n",
+       "      <th>createdDatetime_Hour</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[Atlanta, Ferguson, cnn]</td>\n",
+       "      <td>[16252233]</td>\n",
+       "      <td>[sgallman]</td>\n",
+       "      <td>537368500663508992</td>\n",
+       "      <td>269</td>\n",
+       "      <td>537356966684033025</td>\n",
+       "      <td>2526260324</td>\n",
+       "      <td>infinate_words</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[edshow, Ferguson]</td>\n",
+       "      <td>[26379293]</td>\n",
+       "      <td>[ahuntre]</td>\n",
+       "      <td>537368500671889408</td>\n",
+       "      <td>4</td>\n",
+       "      <td>537366422583009280</td>\n",
+       "      <td>1197490142</td>\n",
+       "      <td>SexyLiberal317</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[34643610, 52419540]</td>\n",
+       "      <td>[EricBoehlert, NBCFirstRead]</td>\n",
+       "      <td>537368500739002369</td>\n",
+       "      <td>42</td>\n",
+       "      <td>537310708493725696</td>\n",
+       "      <td>408855841</td>\n",
+       "      <td>LaDow</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[148116121]</td>\n",
+       "      <td>[scottbix]</td>\n",
+       "      <td>537368500814491648</td>\n",
+       "      <td>2558</td>\n",
+       "      <td>536965701337382912</td>\n",
+       "      <td>187314413</td>\n",
+       "      <td>SwAgOnALLMaDDeN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[1496971]</td>\n",
+       "      <td>[GlobalGrind]</td>\n",
+       "      <td>537368501791772672</td>\n",
+       "      <td>204</td>\n",
+       "      <td>537289646708113408</td>\n",
+       "      <td>419066409</td>\n",
+       "      <td>CerezaChampagne</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[8839632]</td>\n",
+       "      <td>[NBCNightlyNews]</td>\n",
+       "      <td>537368501804343296</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>23618466</td>\n",
+       "      <td>wbaltv11</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[569467464]</td>\n",
+       "      <td>[RealLucasNeff]</td>\n",
+       "      <td>537368501959548928</td>\n",
+       "      <td>18</td>\n",
+       "      <td>537358807371100160</td>\n",
+       "      <td>257448308</td>\n",
+       "      <td>Sara_Laylaa</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[102817657]</td>\n",
+       "      <td>[CubanRendezvous]</td>\n",
+       "      <td>537368501997277184</td>\n",
+       "      <td>4348</td>\n",
+       "      <td>537320870902263808</td>\n",
+       "      <td>387339834</td>\n",
+       "      <td>chanelyousif</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[46343528]</td>\n",
+       "      <td>[Gia_Nova]</td>\n",
+       "      <td>537368502081159170</td>\n",
+       "      <td>43</td>\n",
+       "      <td>537358089888870401</td>\n",
+       "      <td>1660502162</td>\n",
+       "      <td>ealxpatcarvalho</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Tue Nov 25 22:13:29 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[214622133, 2538201518]</td>\n",
+       "      <td>[iSmashFizzle, fergusonlibrary]</td>\n",
+       "      <td>537368502152462336</td>\n",
+       "      <td>1011</td>\n",
+       "      <td>537113989407571969</td>\n",
+       "      <td>2364576554</td>\n",
+       "      <td>RuthAnnAngle1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2014-11-25 22:13:29</td>\n",
+       "      <td>2014-11-25</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   coordinates_x  coordinates_y                      created_at  \\\n",
+       "0            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "1            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "2            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "3            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "4            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "5            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "6            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "7            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "8            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "9            NaN            NaN  Tue Nov 25 22:13:29 +0000 2014   \n",
+       "\n",
+       "     entities_hashtags_text entities_user_mentions_id_str  \\\n",
+       "0  [Atlanta, Ferguson, cnn]                    [16252233]   \n",
+       "1        [edshow, Ferguson]                    [26379293]   \n",
+       "2                        []          [34643610, 52419540]   \n",
+       "3                        []                   [148116121]   \n",
+       "4                        []                     [1496971]   \n",
+       "5                [Ferguson]                     [8839632]   \n",
+       "6                [Ferguson]                   [569467464]   \n",
+       "7                        []                   [102817657]   \n",
+       "8                [Ferguson]                    [46343528]   \n",
+       "9                        []       [214622133, 2538201518]   \n",
+       "\n",
+       "  entities_user_mentions_screen_name              id_str  retweet_count  \\\n",
+       "0                         [sgallman]  537368500663508992            269   \n",
+       "1                          [ahuntre]  537368500671889408              4   \n",
+       "2       [EricBoehlert, NBCFirstRead]  537368500739002369             42   \n",
+       "3                         [scottbix]  537368500814491648           2558   \n",
+       "4                      [GlobalGrind]  537368501791772672            204   \n",
+       "5                   [NBCNightlyNews]  537368501804343296              0   \n",
+       "6                    [RealLucasNeff]  537368501959548928             18   \n",
+       "7                  [CubanRendezvous]  537368501997277184           4348   \n",
+       "8                         [Gia_Nova]  537368502081159170             43   \n",
+       "9    [iSmashFizzle, fergusonlibrary]  537368502152462336           1011   \n",
+       "\n",
+       "  retweeted_status_id_str user_id_str user_screen_name user_verified  \\\n",
+       "0      537356966684033025  2526260324   infinate_words         False   \n",
+       "1      537366422583009280  1197490142   SexyLiberal317         False   \n",
+       "2      537310708493725696   408855841            LaDow         False   \n",
+       "3      536965701337382912   187314413  SwAgOnALLMaDDeN         False   \n",
+       "4      537289646708113408   419066409  CerezaChampagne         False   \n",
+       "5                    None    23618466         wbaltv11          True   \n",
+       "6      537358807371100160   257448308      Sara_Laylaa         False   \n",
+       "7      537320870902263808   387339834     chanelyousif         False   \n",
+       "8      537358089888870401  1660502162  ealxpatcarvalho         False   \n",
+       "9      537113989407571969  2364576554    RuthAnnAngle1         False   \n",
+       "\n",
+       "      createdDatetime createdDatetime_Date  createdDatetime_Hour  \n",
+       "0 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "1 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "2 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "3 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "4 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "5 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "6 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "7 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "8 2014-11-25 22:13:29           2014-11-25                    22  \n",
+       "9 2014-11-25 22:13:29           2014-11-25                    22  "
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "indictmentSubset.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Understanding The Dataset\n",
+    "In this section, we mostly want to explore broadly the data we have -- both the shooting and indictment-related tweets. We will do this for large scale temporal and spatial visualizations first, followed by more specifically aggregated comparisons amongst different axes of data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Visualizing the Number of Tweets Over Time\n",
+    "One of the first things we sought to visualize was the number of tweets over time, expecially as people reacted to important events related to the shooting and indictment. We were interested in seeing whether there were dectectable spikes in the number of tweets mentioning Ferguson as people reacted to these events. \n",
+    "\n",
+    "In the dataset related to the shooting, we have approximately 11 million tweets worth of data. Over the course of the first week, statements from police, from the family of Michael Brown, statements from the police officer Darren Wilson, and unrest from the streets were recorded and shared wildly across the web. To get a general understanding of the data, we are going to plot the number of tweets over time and annotate this plot with important events that happened over the course of the two weeks. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First, we will group the tweets by minute, and then count the number of tweets that happened each minute. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def plotWithEvents(df,eventlist):\n",
+    "    '''Given a dataframe of tweets, this function will plot those tweets, grouped by minute, and annotate the graph \n",
+    "    with any events that we would like.'''\n",
+    "    groupedTime = (df.set_index('createdDatetime')\n",
+    "                      .groupby([pd.TimeGrouper('Min')])\n",
+    "                      .count()\n",
+    "                      .reset_index())\n",
+    "    fig, ax = plt.subplots(figsize=(10,10))\n",
+    "\n",
+    "    groupedTime.plot(kind='line', x='createdDatetime', y='created_at', ax=ax)\n",
+    "    plt.title('Number of Tweets by Users')\n",
+    "\n",
+    "    ax.set_ylabel('Count of tweets')\n",
+    "    ax.set_xlabel('Date/Time')\n",
+    "    \n",
+    "    for i,event in enumerate(eventlist):\n",
+    "        plt.axvline(x=eventlist.get(event).get('date'),ymin=0, ymax=4000, linewidth=4,color='g',label=event)\n",
+    "        plt.text(eventlist.get(event).get('date'),2500 - (eventlist.get(event).get('offset'))*500,event)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To put the data in context, we map for a variety of calendar dates and times, as called out by [this](http://www.nytimes.com/interactive/2014/08/13/us/ferguson-missouri-town-under-siege-after-police-shooting.html?_r=0) article."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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YDx8+RK9efQEAjRs3KTTgOTk54fr1qzh//izs7MogOzu7yM9JXxjwiIiIyCjVrFkL169f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\nRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x491256e50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#calendar dates learned from a variety of news sources, especially http://www.nytimes.com/interactive/2014/08/13/us/ferguson-missouri-town-under-siege-after-police-shooting.html?_r=0\n",
+    "calendar_dates = {'AntonioFrench': {'date': datetime(2014,8,14,7,0,0), 'offset': 0},\n",
+    "                 'Obama2': {'date': datetime(2014,8,14,11,40,0), 'offset': 1},\n",
+    "                 'SilentVigils': {'date': datetime(2014,8,14,18,0,0), 'offset': 0},\n",
+    "                 'DarrenWilsonNamed': {'date': datetime(2014,8,15,8,45,0), 'offset': 0},\n",
+    "                 'CharacterAssassination': {'date': datetime(2014,8,15,12,30,0), 'offset': 1},\n",
+    "                 'StateOfEmergency': {'date': datetime(2014,8,16,15,0,0), 'offset': 0}}\n",
+    "\n",
+    "plotWithEvents(shootingSubset, calendar_dates)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's do the same thing for the data regarding the tweets after the indictment!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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b9MOfhdypbCQ0AhoAAPCbwlq4Cn1vM9d5SWfOu3NYqUZAAwAAflPUtyydd2pK\np846D2ylFQENAAD4T1GbuAppenti7jp3DitVCGgAAMBvnOWnr9f9rV/2nPT4vLKKgAYAAPzHSdL6\nfNW+Ip1X4LAy0oRGQAMAAH5jLWKAcvesshHPCGgAAKAUcLtlrIwkNAIaAADwm6J2QZazfEZAAwAA\n/lPUIWJun8YYNAAAAM8UOT6VkeDlLgIaAADwH14ScAsBDQAA+E1hKwIU5lKuy7EWfoWy0tBmLukC\nAABAOZIvQFltNr352XbXp11MXr/9meSLqgyHFjQAAOA3+d/iTDmbqd/+ch26Nu06IUk6n5Xj0fVL\nKwIaAADwmdSMbGXmClX545PJ5N51lm84cOH8spG/XKKLEwAAeNXG348rNSNbbRpV1Zg31uTZ99fh\nM2p6dRX7Z5O7Ce0im4vXAMpKgKMFDQAAeNW8r3Zq4fd/KOn0+QL7lq37O8/nlHOZnl28jAQwVwho\nAADAJ9xpHPt81V6Prukqn7lqYSstCGgAAMAnAtxIaFarZ4HK5WLrZSOfEdAAAEDpUU7yGQENAAB4\nT1b25Tc2PRz/7x4XCY2ABgAAkM/oWSvtP7vzhqbnXZwuDigjr3ES0AAAgE+404Lm6dJPriaiLRvx\njIAGAAB8xFU+y7bk6K/DZzy6pssAVkYSGgENAAB4RYHWLRdNaF+u+bsI9/D4lFKJgAYAALzi7S93\nenT8n4dPe3T8idMZdHECAAB4YvPuE3k+uwpTmS4WPs8v22J1Pc1GGWliI6ABAIBicxiMXGSlHA/D\nVICp7KwU4AoBDQAAFFuOg/kvnM36/+z8jR63nkkXp+1w2YLm8WUNiYAGAACKzZOuxcSkNG3fl+zx\nPVLOntcfhwoft1ZG8pnMJV0AAAAo/RxNIJtyLtPp8YEBni8zMPPj31wfVEaa0GhBAwAAxeZoRYDX\nP93m9PjAQF+sA1V2WtAIaAAAoNg8fXsyMIAIUhieDgAAKDYPl9RUQBG6ON1SRprQCGgAAKDYnL2x\n6UyASUo8mVbs+zaLrZLncxnJZwQ0AABQfDZPm9AK8ew9rTX7kZvdOrbelZF56ygjLwn47C1Oi8Wi\nZ555RomJicrOztbo0aNVv359PfXUUwoICFCDBg00adIkSdKSJUu0ePFiBQUFafTo0erUqZMyMzM1\nbtw4JScnKyIiQi+99JIqVarkq3IBAEAxeDGfKSQoUJFhQW4dm51j9d6NDcRnLWhfffWVKlWqpIUL\nF2r+/PkwmFqBAAAgAElEQVSaOnWqpk+frrFjx+qjjz6S1WrVihUrlJSUpAULFmjx4sWaP3++Zs2a\npezsbC1atEgNGzbUwoUL1atXL82dO9dXpQIAgCLKys7Rz1sSlXY+26Pzvll/wOk+k0lyd4Rao7p5\nG2/KSAOa71rQevTooe7du0uScnJyFBgYqN9//12tW7eWJMXFxWnt2rUKCAhQq1atZDabFRERoXr1\n6mn37t1KSEjQAw88YD+WgAYAgPEsW/e3vll/QPVrVfTovB37TxW632QqPKJFRwTrdGqWmlxVRdfW\nidbug54tvG50PgtoFSpUkCSlpqbqscce0+OPP64ZM2bY94eHhys1NVVpaWmKjLzcfxwWFmbfHhER\nkedYd8XERLo+CF7FM/c/nrn/8cz9/wx45v7nyTPfc+CUvSXs76PnvFZDpUrhLut4Kb6DrqwcpsDA\nANWoGmkPaNHRYWXi341PVxI4evSo4uPjNXToUN1+++2aOXOmfV9aWpqioqIUERGRJ3zl3p6Wlmbf\nljvEuXLypPf+kcC1mJhInrmf8cz9j2d+gT+fAc/c/zx95k+8sdr+s8WLY8FSUtIUGiDd0KiqNu06\n4fSY4IvvbGbm6l5NOZ2mk6GBXqvF15yFSZ+NQUtKStLIkSM1btw49enTR5LUqFEjbd68WZK0atUq\ntWrVSk2bNlVCQoKysrJ07tw57du3Tw0aNFDLli21cuVKSdLKlSvtXaMAAKDkJZ3OKNH7m5x8YAya\nC/PmzdPZs2c1d+5cvfXWWzKZTJowYYKmTZum7OxsxcbGqnv37jKZTBo2bJgGDx4sm82msWPHKjg4\nWIMGDdL48eM1ePBgBQcHa9asWb4qFQAAeOjJt9eX6P1zj1Ezuf1KQenhs4A2YcIETZgwocD2BQsW\nFNjWv39/9e/fP8+20NBQvf76674qDwAA+NGdN9XTV2v/9tr1nEWystKCxkS1AADA53p3uFpRbs5t\n5o48b3nm7uIsI2sJENAAAIBfuJo6I/9xhbWGOclnPl3r6XyWRSf8NPaOgAYAANxmybHq2Xc3Fulc\nN/OZm9e6fDFz4OU448v2s2fnb9RTb69X+nmLD+9yAQENAAC47WhyepEXOQ8I8CyhuRu2bruhtufF\nFEHy2UxJ8njVhKIgoAEAALe5sxh597Z1HG4PcLMJLceNhT1zXyqiQvDlD2VjCBoBDQAAuM+dtyQj\nKxTvZQCLxfWkt3mm2TDwSwKnzp5X/OxVmrHwV7fC7SUENAAA4FVhoY5n8XK3BS370qoEhQSa3Fcy\nGXii2lmLf1N6pkV7Dp1WthvB8xICGgAAcJs7LVQtG8YotkZUge0mN8eguRNk8rzF6c23D7zsaHK6\n/WdPyiSgAQAAt7nTQhViDtTdXeoX2B7p5jxoocEX1tIs7Fa5Q1lAnhY0gzWh5eJJaQQ0AADgNndC\nRmCgyeFxg29t4NY9rqp+sfWtkHtZ87xIYNwWtNw8iY4ENAAA4DZ3WqgCA0wOj4uOCPFaHc7e9HTj\nBdCSQwsaAADwBVcZo/U1MTKZTA6DUoSHb3cWdq/c3aW5x3bNXLRFCXtOFnrdY6fStXrbEY9q8QYr\nb3ECAABfcNWCdql70tFx5sAADXQwNk2Set18lds1NKhVMc/qAYH5Xj74fNVe+8+bdh3X95sP5dn/\nzDsb9P7y3UpMKtqEu/5AQAMAAG5z1QjUosEVhR7X7YaCk9jGNa/u5F6OL5I/kJlMpjwBL/d0Hm9/\nuVOLfvjT4XUyMn2/ZFNuzIMGAAB8wlXIqFY57MJxHgy4GtGjkUfhxdG0Gnmn3XDzQn4er+bJ7RzP\nJAcAAFAEl7JRw1rR9m1Nrq7s8rzOLWvqlz0nnXaB5uZoTc/8oS0j06LjKekFjitJnkyzQUADAABu\ncxUyLgWl4KBAvTmmg77/5bBuaVXL5XUrRoRo2v1t3aohfxdn/m2HT6bp4dmr3LqWP3nSSkhAAwAA\nbvMkZISFBnk0+N9djpaMKspiAv5et5OJagEAgE94O9JcUTHU+b2c3MxbKzvlv37CnpM+nX6DiWoB\nAIBPZGblePV6lSKdT17b9OLYtfo1K+bZ7mgMmjtsNpsys53X/9bS7Xp/+e4iXdvd+7uLLk4AAOCW\ns+lZmvP5dqf7zYHuBafXH71Zj72xRpLj8WSXdGpZUw1qRevKKmF695td2vj7cUlFXxz9o+//0E+/\nJhbpXG+gixMAAHjdkZOFT+xaOdJ5d2VukWHB9p8LC1smk0m1qkbIHBigUXdep2qVKkjKuzi6J0oy\nnEnMgwYAAHzAVcDwZCmjSzxpDLt0/aJ2cZYmBDQAAOAWq4v9nuSzkKBASZfnTXPr/hcLcPQWZ1He\nXsgdOLMtrr5d8bEWJwAA8D6X+cL9ANK+yZWSpJoxEW6fY29B89ZrnLm8uvg3r1+zACaqBQAA3uZq\n3rDm9a9w+1p3d45VvSsj1bZxNbfPudzF6fYpbttz6LT3L5qPJ210BDQAAOCWwnroHurdxL5QujtC\ng82Ka17Ds/tbfdeC5hd0cQIAAG/77c8kp/vq16ooc6BvY8XFfFYiLwmcTc8q9jWYZgMAAHiVzWbT\nT1ucT1Phj8hUu+qF8Wox0RUK7PP1ok0Z5y3FvoYnNdLFCQAAXDrvagUBP3Q7jup1nX7ZfcLjrlFn\nPGnR8kYAZB40AADgVa6yhT9a0KLCgtXl+lo+70r93+ZDOpOamWebJ+HKGbo4AQCAV7l6g9MvCc3L\nt3f2jT7+4U+9tXRHccrx6H6OENAAAIBLOdbC40WpfbPSicMnU/N8fvebXcW+Zv5WuMJa5QhoAADA\nJauLgFbSXFXnKAzN+Wyb1u885vD4/Hlz35GzRawsdxGXf/y/jQc1csZPTg8loAEAAJdcBbTS2IB2\nPitH/172u5O93v9CuZd6WvLTX4UeS0ADAAAuueriLOl8FmQuPNJ42v5X0t+HgAYAAFxy3YJWspEm\nrnkNtb/uSucHeLGHtqiX4i1OAADgVa5a0EpaSFCgHujZ2GvX80XedPkmbC4ENAAA4NKuAymF7jf6\nGDRPwpHrixXtWrSgAQAAr1r4/R+F7jeV+KitwllyPAtVJpNJJ05n6Exa8dfgvGT11iNuH0tAAwAA\nxWfsfKb42as8Puept9fr8TlrCmwvanfvz78R0AAAAOw8DVWFddku+uHPYlbjGgENAAAUyq11KI39\nDoHHCmsQ3LHvlM/v71FAS01N1Z9/+j41AgAA41i3w/Fs+5J0VfVISZLZbPA+Tk+V8FsPZlcHfPLJ\nJ/r11181btw49e7dW+Hh4erWrZsef/xxf9QHAABK2O6Dzt/gnDC8tbItVgUGGKNTrmJ4sMcD+x2t\nJnDWiy8HFIXLp7lo0SKNHz9eX3/9tW655RYtW7ZMq1ev9kdtAADAAAoLXwEmk0KCAv1YTeFmPnSj\nx+c4W4+zJLkVd6Ojo7Vy5Up16tRJZrNZmZmZvq4LAAAYRGBA6em+NAd6vyXvfJbF6b6ftiTq+fc3\ny5Jjdbg/Jjq0wLbUjGyX93T5LerXr69Ro0bp8OHDat++vR577DE1adLE5YUBAEDZEFCKApovPPSq\n8yk6Fny3RweOn9OhE6nKtuTo1NnzefZXja5Q4JyUc64bulyOQXvxxRe1ZcsWNWjQQMHBwerVq5fa\ntWvn8sIAAKBsKE0taP7y5+HTWrPtqP1zgMmkye9v1tHkdL05poPCQoMkSfln9/jj0GkFB7lu5XN5\nxJAhQ9SmTRtFR0dLkjp27KgBAwZ48h0AAEAplp7pvIuvvJr+0a9anSugSdLR5HRJ0rl0512YyWfO\nu7WqgdMWtOHDh2vTpk2SpEaNGtnnQDGbzerSpYvrygEAQKn2/S+HFGwOyNNSlNuY/s39XJFx5Z6V\nI/fPBeaQM0k5Tsar5eY0oH344YeSpGnTpmnixImeVQkAAEo1S45Vi1Y4n/v0kX5N1Sy2ih8r8r0q\nUaFKzjeGzF0BuVKZKdfPjub43XPwtOvruTpg4sSJWrZsmWbPnq2MjAx98cUXbpYKAABKq2kf/lLS\nJRTZsNuuKdJ5xRprl+vU3GEtfz5LOp2hL9bsd3k5lwHtlVde0cqVK/W///1PFotFn332mV566SW3\n6wUAAKXPweOphe43GXh19PBQl+9AOhQYWPTvZMrTgpZrR74mtNOp7k2A6zKgrVmzRjNnzlRISIgi\nIyP1/vvva9Uqz1eEBwAA8AdTEZdpKk4LWu4zTSaTduxL1her9yn/aDO31jWVG9NsBFycPfjSl83K\nyrJvAwAA5ZRxG9CKXFpx5nvLnwlfXbJVknRl5bA82zOzc9y6nsuA1r17d40ZM0ZnzpzRBx98oK++\n+kp33HGHm+UCAAD4V1HXOS/OeqIf/e8Pt45bv/O4W8e5DGgPPvigVq9erRo1aujo0aN65JFH1Llz\nZ7cuDgAAypYH7mis7zYfVKO6lUq6FKdKootz14HLC8rn7sZ0r0OzILdG0YWFhalOnTrq27evtm3b\nVsRbAQCA0q59kyvVvsmVJV1GoYraguatJa227Uu2/2y1up7zzGEtrg74z3/+o9dee00ffPCBMjIy\n9Nxzz+ndd98t0s0AAAB8LXcLWt+4q/1+/w//b4/9Z2v+tZ7c5DKgLV26VO+++64qVKig6Ohoffrp\np/rss8+KdDMAAABfy90O1vraqm6fF1khSJ2vr+nVWoqYz1wHtICAAAUHB9s/h4SEKDAwsGh3AwAA\npdYNjdwPOyUpdwua2YO5zUwBJg3rVrRJbp3JsdoUEuR5bnIZ0G644QbNmDFDGRkZWrFihf75z3+q\nXbt2RSoSAACUXlnZRRtP5W+5h5KZA91/M9NLQ9DysFptMpmkPh52tbqs+sknn1TdunV1zTXX6Isv\nvlDHjh01fvz4IhcKAABKJ3cnWS1puVvQPBn4H1DUtwsKkZqRLZNJsnnY1+nyLc5p06apU6dOeuWV\nV/J0dQIAABhRVPiFvBISFKggD1rQrD4KoCaZPL62y4DWunVrLV++XFOmTFHDhg3VuXNndezYUVWr\nlo5+aAAAUL7Urhqhf/ZuoqurR6lCiPvrcv72Z5JP6jGZPH9ZwGXV//jHP/SPf/xDFotFn376qebM\nmaPnnntOu3btKmqdAACgFCodHZwXtPHg7c1Lcor6yqULaectHncPuwxo8+fP1+bNm/Xnn3+qUaNG\nuv/++3lJAAAAwANe7+L84YcflJiYqDvvvFPt2rVTq1atVKFChSIXCAAAjOvwyVR9u+FASZdR5tg8\nfAHWZUBbtGiR0tPTtXnzZq1fv14vvviioqKi9PHHHxe1RgAAYFCzPv5NZ9KyHO4LC3V/PBfyctSC\nNnF4a6fHu3y14VI4W7dundauXauoqCjFxcUVr0oAAGBIqRnZTvf1vLGe/wrxgU4tvbtKgCfyB7Qn\nB7XU1TWinB7vMgrfeuutat++veLi4jRq1ChVrly5+FUCAIBSJyw0qKRLKJabml6pn7cklsi98zeg\nXVMnutDjXbagDR8+XLNmzVKvXr3s4ezVV18teoUAAMCwChvL7oOJ9v3ithtqS5JqVAkvsRryt6CZ\nXEyK67QF7ZVXXlFycrJ+/PFHHThwebCgxWLRtm3bNHbs2GKWCgAAjMZXk7WWpAFdGujuzvVdhiJf\nsnprJYFu3bpp79692rBhg2644Qb79sDAQD388MNFrxAAAMDPSjKcSZ4vk+U0oDVr1kzNmjXTrbfe\nqsjIyGIXBgAASrey17bmP1YPp9lwOQatuOFs69atGjZsmCRp165diouL0/DhwzV8+HB9++23kqQl\nS5aoX79+GjhwoH7++WdJUmZmph599FENGTJEo0aNUkpKSrHqAAAAxWMOLK2j0Dxzb49rFRoc6NVr\nxjWv4dHxTlvQ0tPTFRYWVqxi5s+fry+//FLh4RcG5e3YsUP33XefRowYYT8mKSlJCxYs0NKlS3X+\n/HkNGjRIN910kxYtWqSGDRsqPj5ey5cv19y5czVhwoRi1QMAAIrm3h7XKryUv8Xprg7Na+jqmhX1\n7PyNXrtm/VoVPTreaQvapVavyZMnF7mYunXr6q233rJ/3rlzp37++WcNHTpUEydOVFpamrZt26ZW\nrVrJbDYrIiJC9erV0+7du5WQkGCfby0uLk7r168vch0AAKB4OnjYAlQWje51nd/uVWgL2hNPPKHV\nq1crMzOzwP7p06e7vHjXrl2VmHh5vpHmzZvr7rvvVuPGjTVv3jy9+eabatSoUZ5u1LCwMKWmpiot\nLU0RERGSpPDwcKWmprr9pWJiGDPnbzxz/+OZ+x/P3P/PgGduHOXhd2EyXf6eGTkFR9zdHldfb3+5\ns0jXzv/8XD1PpwHtvffe08aNG5WQkJDnLc7iyP3Cwa233qpp06bphhtuyBO+0tLSFBUVpYiICKWl\npdm3eTIW7uTJc16pF+6JiYnkmfsZz9z/eOYX+PMZ8Mz9z1FoaFCroqpUDC0zv4tJI9ro+Q82O9wX\nGRZs/56nUtIL7C/qM3jjsQ4Fzr302VlQcxrQqlevrt69e+vaa69VbGys9u/fr5ycHDVo0EBmc9HW\n4ho5cqSeffZZNW3aVOvXr9d1112npk2bavbs2crKylJmZqb27dunBg0aqGXLllq5cqWaNm2qlStX\nqnVr5+tVAQAA33h6aKuSLsGr6l4Zqdvb19U36wsuCF+tUgWf3DOigudj91wmrezsbN12222Kjo6W\n1WpVUlKS3nrrLTVv3tzjm02ePFlTp05VUFCQYmJiNGXKFIWHh2vYsGEaPHiwbDabxo4dq+DgYA0a\nNEjjx4/X4MGDFRwcrFmzZnl8PwAAgPxKek40d7gMaC+88IJmz55tD2S//fabpk6dqk8//dStG9Ss\nWVMff/yxJKlx48ZatGhRgWP69++v/v3759kWGhqq119/3a17AAAAuCvIfOEdyZDgQGVm5ZRwNY65\nnActPT09T2tZixYtHL40AAAAUBrccn0ttWxwhZ4c1FKdWvjv7dQRPa51+1iXAa1ixYpasWKF/fOK\nFSsUHV34CuwAAABGFRZq1iP9mumq6lEa3v1aNaztu1zTqG4l+8+XWu7c4bKLc+rUqRo3bpx9ktja\ntWtr5syZRSgRAADAeGpXjdAfh06rVkyE16757vjOOnQiVdUqX570P8CDsW8uA1q9evX0ySefKD09\nXVar1T43GQAAKFu+WbOvpEsoEXd1jFWdahG64dpq9m3uRqmBXerr4x//KrDdZDKpTrXIfNvcr8nt\n+TKKu+wTAAAwtreXbi/pEkpESHCgOjTzfCxaSHCgut1QRzHRFTTnc9fPzpO3R93vDAUAAIBdozoX\nxpeZAtwLXp5M7uEyoP35558Ftv32228e3AIAAKB0iY4IcXmMJccqKe/YskqRzs/zpAXNaRdnQkKC\nrFarJk6cqBdeeEE224U1qSwWiyZPnqzvvvvO7ZsAAACUJmGhZs0Z00GPvLba6TH2gJaruWvG6PbK\nyrY6PN7NhjZJhQS0devWadOmTTpx4kSeCWPNZrMGDBjg/h0AAABKofDQwpdoqhByIUblbkEzBwbI\nHOi4g9LdrlCpkID2yCOPSJK++OIL9e7d2+0LAgAAlAdDu10jSQp0M3hdV6+yGterpC7X13J5rMu3\nONu0aaMZM2bozJkz9m5OSZo+fbpbxQAAAJR2111VucC2S+PN3B1bFmQO0BMDW7p1rMuANmbMGLVu\n3VqtW7cuFYuLAgCA4ru1VS11aO6/ZZCM7vH+zZ3uC/BkcJmbXAY0i8Wi8ePHe/3GAADAuO7uUt/p\nWKryKH8Iy/3JkxUC3L6fqwNatWqlH3/8UVlZWV6/OQAAMCY6zRy7vX3dCz/kej6erLHpLpctaP/3\nf/+njz76KM82k8mkXbt2eb0YAABgDL5oFSpLTLkSWq2YcN1yfS01b1DFa9d3GdDWrFnjtZsBAIDS\ngXHnF7z26M0y5+reDL7YWhZe4XKEMplMGtKtoVfv6zKgvfnmmw63x8fHe7UQAAAAo4kKC87z+ZZW\ntXU0OV092tX16X096jTNzs7Wjz/+qOTkZF/VAwAAYFhhoWY9eOd1ql01wqf3cdmClr+l7OGHH9Z9\n993ns4IAAADKO49fO0hLS9ORI0d8UQsAACghVqvN9UHwG5ctaF26dLEPFLTZbDp79qxGjhzp88IA\nAID/nMvILukSkIvLgLZgwQL7zyaTSVFRUYqI8G2/KwAA8K8tf54s6RKQi8uAVqNGDS1atEgbNmyQ\nxWJRu3btNHToUAUEMLswAABlwbn0LH34f3vsn3veWK/kioEkNwLayy+/rAMHDqhfv36y2Wz6/PPP\ndejQIU2YMMEf9QEAAB/LtljzfDb7YGZ8eMZlQFu7dq2++OILe4tZp06d1LNnT58XBgAA/CMw35qb\nPlj7Gx5yGZFzcnJksVjyfA4MDPRpUQAAoOTUqRZZ0iWUey5b0Hr27Knhw4fr9ttvlyR98803uuOO\nO3xeGAAA8A+bLe8UG02uqlxCleASlwFt9OjRatSokTZs2CCbzabRo0erU6dOfigNAAD4Q758xjqc\nBlBoQDtz5oxycnLUsWNHdezYURs3blSDBg38VRsAAPCD/C1oKHlOx6D9/vvvuv3227Vjxw77tnXr\n1qlXr17avXu3X4oDAAC+ZyWgGY7TgDZjxgzNmjVLcXFx9m2PP/64XnzxRb300kt+KQ4AAPge+cx4\nnAa0s2fPqm3btgW2d+jQQSkpKT4tCgAA+A9dnMbjNKBZLBZZrdYC261Wq7KzWa8LAICygnxmPE4D\nWps2bfTmm28W2D537lw1adLEp0UBAAD/YQya8Th9i3Ps2LF68MEHtWzZMjVt2lQ2m02///67Kleu\nrH/961/+rBEAAPgQ+cx4nAa0iIgILVy4UBs2bNCuXbsUEBCgIUOGqHXr1v6sDwAA+Bhj0Iyn0HnQ\nTCaT2rdvr/bt2/urHgAA4GfkM+NxuZIAAAAou/7zf7u18rcjJV0G8nG5WDoAACi7CGfGREADAKCU\nysi0aO32o8q25Hjtmre2quW1a6Ho6OIEAKCUWvj9H1q345hOns5Q7w5Xe+Wat7YmoBkBLWgAAJRS\nB46dkyQlJqUV6fykMxneLAdeREADAKC0Ml34n8Mn04rUzTn+X+u9XBC8hYAGAHAb82UZy8V8puOn\n0jXqlZX6fNVel+d8ve5vTfj3BmVm5cjRb7NyVKhXa0TRENAAAG5jSSBjOXwyb9fm1+sOuDzn81X7\ndDQ5XY+9sbrAvofvai5zINHACPgtAADcRj4rO7IsVgfbvPc2KIqHgAYAcBsBrfR449NtWvLjXx6d\nw+/XOJhmAwDgNsagGcexU+kOt2dbrHppYYL2H73whufdXeq7fU2rld+vUdCCBgBwG/nMOKZ8sNnh\n9s27j9vDmadyCGiGQUADALjN5vC9P5SE81mOx4u586KAM7SQGgcBDQDgNv5+G5+zrk930MVpHAQ0\nAIDbaGEp2whoxkFAAwC4jT/fZRtj0IyDgAYAcBsNaGUbExEbBwENAOA2/oCXbXRxGgcBDQDgNvJZ\n2UY+Mw4CGgDAfSQ0w4gKD/b6NXOsBZd/QskgoAEA3EYLi3EEm73/J5wuTuMgoAEA3MY0G8ZxLiPb\n69ckoBkHAQ0AUCTLNxzQX4lnnO7Ptlg157Nt2rn/lB+rKj9ycjwLU1arTZ/8VPji6c3qxxSnJHgR\nAQ0A4LbjKRmSpMSTqfr05716cUGC02N/+ytJW/5M0qzFv/mrPBRi295kfbvxoNP90+5vqxubVfdj\nRSgMAQ0A4LbV245Ikp59d5PLY3N3l/1v8yGf1QT3ZGRZCt1f44pwmUwmP1UDV8wlXQAAoPTYsPO4\n/jrsvFvTmY9/+FPd2tT2QUVwF+MHSxda0AAAHkk6cz7P55RzmSVUCdxx/mLLGfmsdCGgAQCK5dip\ndIfb6S3zNfcSV0ZmzoWjCWilCgENAFAsP/56mAlODexSUKaLs3QhoAEAiiVhz0lt2nWiwPaNvx8v\ngWqQ36WB/8Sz0oWABgAotjQHk6Zu+TOpBCopfyYOb13oflrQSicCGgAApVRsjShdXSOq0GMuDQUk\nn5UuBDQAQLExf5b/uRu4Lh1GC1rpQkADAKC0ciMXX8plhS2z2Ty2infqgdcwUS0AwOustNYYx8Xf\nhbMWtOHdr1Fc8xr+rAhuoAUNAOB11sKaa+BXl7s4He8PCzErgC5qwyGgAQC8zlFA2/n3KWVbmC/N\n3174MEHHU9KdTrNBmDYmujgBAF6X4+CP/qyPf9PNTavLbA5Q19a1VL1KeAlUVv4knz2vJT/+pYa1\nox3ud/S7QskjoAEAvM7ZeKc1249KkrbvTdbMh270Z0nlnrMuzsBAujeNyOddnFu3btWwYcMkSQcP\nHtTgwYM1dOhQPf/88/ZjlixZon79+mngwIH6+eefJUmZmZl69NFHNWTIEI0aNUopKSm+LhUA4CWu\nWmXOpLHAujeYLr7GeXfn+qoUGVLosbZcnZwVQi63z7S+pqpvikOx+DSgzZ8/XxMnTlR29oUZpqdP\nn66xY8fqo48+ktVq1YoVK5SUlKQFCxZo8eLFmj9/vmbNmqXs7GwtWrRIDRs21MKFC9WrVy/NnTvX\nl6UCAIoh/1ubZ9MLriyQF6023tS9bR3Nevgmp/tNJlOeFwGuqh4pSeobd7XMgQxHNyKf/lbq1q2r\nt956y/55586dat36wpIUcXFxWrdunbZt26ZWrVrJbDYrIiJC9erV0+7du5WQkKC4uDj7sevXr/dl\nqQCA4sjXYPbvr3aWTB3l3IM9GzvdlzsSj+7VRAO61FePdnV8XxSKxKdj0Lp27arExET759xjEsLD\nw5Wamqq0tDRFRkbat4eFhdm3R0RE5DnWXTExka4PglfxzP2PZ+5/PHPnwsJD8jyfgycK/2+2yeTe\n8+SZFy4oKDDPM2rZWNKy3wscFxJiVmiFYEnSyDub6Ko6lXVVncoOr8kzNwa/viQQEHC5wS4tLU1R\nUU11mj4AACAASURBVFGKiIjIE75yb09LS7Nvyx3iXDl58pz3ioZLMTGRPHM/45n7H8+8cOfOnc/z\nfAIDTIWOQ7PZbC6fJ8+8cDablJ2dk+cZZaZnOTw2K9Oi5JR0SVLFCoFOnyvP3P+cBWK/djw3btxY\nmzdvliStWrVKrVq1UtOmTZWQkKCsrCydO3dO+/btU4MGDdSyZUutXLlSkrRy5Up71ygAwHhs+fo4\nXc17aslhagevyPecIyoEOTws4Y+TWrbub0lSYABjzkoDv7agjR8/Xs8++6yys7MVGxur7t27y2Qy\nadiwYRo8eLBsNpvGjh2r4OBgDRo0SOPHj9fgwYMVHBysWbNm+bNUAIAH1m0/ppOnz2v4bddIcr2Q\nd3REsB+qKn8CAly/fBHoxjEoeT4PaDVr1tTHH38sSapXr54WLFhQ4Jj+/furf//+ebaFhobq9ddf\n93V5AAAvSExKU2JSmu7uHKvQYNd/WoKDAv1QVfnUtnE1bfz9uNP9zHtWOtDOCQDwGnfXSHc2kS2K\nr7A3OSXJTBdnqcBvCQDgNZfmQ8s9EarD41heyGdMJpPGDmjudD9dnKUDAQ0A4DWXglera2IKPc5C\nQCu2/C9m5NbkqipOX9Sgi7N0IKABALzGUe5qFlulwLYc3uL0isKiltO1N2lBKxUIaACAIul8fc0C\n2y61oOXuwhzStaFeybcwOl2cJcjVHCgwBAIaAKBIalQJ17BuDfNsy7FaJeUNYFHhwQXm57JcPA6+\n07FFDYfb+cNfOvB7AgAUSZYlp8B0GV+s3i8p7+LpIUGBBcY90YLme8Nvu0Y3Nrmy4A4a0EoFAhoA\noEga1o4u8Lbmuh3HJMm+zNO9Pa6VJAXk61ZjDJoXuHiEJpNJUeEFJwQOc/GGLYyBgAYA8Nhrj96s\n2BoVFWx2/GfkUgtZ8/pXSLoQFnIjnvlH/mAsSWGhjpeDgrEQ0AAAHosKu9AyY3LyRuClHkx3lh5C\n0bl6ulYmBC61CGgAgCJz9kfkUgta7hacuOaOB63Dd2pXjSjpElBEBDQAQB6FLcP0QM/G6t851v7Z\nWQvZb38lSco759aIi+PR4D9tG1cr6RJQRAQ0AIDdrMW/afzb653ub3/dlerRtq79c/6xZVLegJd/\n2cepI2+QJFWKDClmpXBHgMmkKRefuSTd3r5uIUfDSHiVAwBgt3P/KY+OdzQI3ZonoOXdXzMmQldW\nDlP6+eyiFQg7d0eX1YqJ0MBbGuj3v0+pb9zVPq0J3kNAAwAUmaNJ6fcdOWv/2VGACwww2afhQDG5\nuSpAtza11a1NbR8XA2+iixMAUGSOxqC99slW+8+OukAJaIBrBDQAQJE5asDJyMwp9JzAQAIa4AoB\nDQBQZI66MF0JDAhgJQHABQIaAMChzOzCW8KKKjDAJKvNVuh0HkB5R0ADADh04Ng5l8c4GmPm+pyi\nVAOULwQ0AEABVptNgYGukxRZq2Tx/MsuAhoAQPuPntX+o5enx7DZbDK58ec/vMKFhbevrRPts9qA\n8oh50AAAmvqfX/J8ttncW2i7UmSIJt/bRlUqhuqR11Z7dE+baAECnCGgAQAKsHkwiL9OtUiH21s2\nuMKbJQHlCl2cAIACrNYLrWjF8Q/WffQZ3oAt+whoAIACvDENhjn/Sun5kTGKjTdiyy66OAGgnLLk\nWHU6NVNpGZYC+2w2m46nZBTr+s7CQ1Gm5gDKGwIaAJRTr3+6TTv3n1JYSME/BT9tSdRnK/dJUe5f\nL6JCkFIzsu2fHa3TCcA9dHECQDm1c/8pSVJ6ZsEWtIQ9Jz2+3uR72+T5TDwDio6ABgAooCjDzypH\nhWrq/W3tn10tiG5jEFqR8eTKPgIaAKCAor4gUPOKcPvPFhZEB4qMgAYA5VyAg0H73ohWlhyrF64C\nlE8ENAAo5xy1lhVnio1Rd16nRnUr6eoahb9hwFRegHO8xQkA5ZyjnORi+Fih2jaupraNqxX9AgBo\nQQP+f3v3HdgEmf8P/J206UzbdLfQSWmBsilLlgxFRRRwncKJCiegpxyuE085ORc4QE8Oz/HTLzJO\nQMa5OZVVVhmlzNJSOmnp3ulKm+T3R5o0SZM2LWmSJu/XP9A0TZ6mT5J3nvF5iKi9nqxUzzJoRJ1j\nQCMionYKy+ut3QTqCKeH7R4DGhERUS/FUxnsFwMaERFZFCMFUecY0IiIiIhsDAMaERERkY1hQCMi\nIqtgHbTu4zFZ9o8BjYiILIsL24k6xYBGREREZGMY0IiIyEo4TUdkDAMaERFZFCc4iTrHgEZERERk\nYxjQiIiIehnugLV/DGhERGQVDBlExjGgERE5IIU10xEXoZkNK5bYLwY0IiIHdC2/utPr9A/zsUBL\niMgQBjQiIgcjVyiwdtvZdpdPHhaq87UpIe5mcIaTyDgGNCIiB2NsdnPWLZF4eu4QyzaGiAxiQCMi\ncjDGApqLsxOEwp5f1CTgIjSiTjGgERE5nPYJbdKwUPh6uULIVee9Cv9a9osBjYjIwRgaQVs0axAA\nwNPd2YINsdxdEfU2DGhERA6mowobvl6uPX7/HKQj6hwDGhGRg1F2MHQlEfd8QCOizjGgERE5GP0R\ntNcfH6P5v7MT3xZ6A57CYP/4TCQicjD6b+6RIV4Gr+fUwzs6OxrJI3J0DGhERA7HtGDE0bRegAv6\n7BaffUREDkY7nrmKnIxez9mJb/5E1sKARkTkYLSnOF/54yij1+vpETSuoyIyjgGNiMjBKFuTUUJc\nICKCDa8/AwBFDyUojssRdY4BjYjIwahjV2fLl5beO7jH20LdxeFHe8eARkTkYJQmJrT4KL+ebwzd\nFI5G2i8GNCIiR9Oa0Iy9uU8ZHorwILHl2kNE7Vjw0DUiIrIFnQ2gPX7XoB69fwFLQxB1iiNoREQO\nRj3FyaBEZLsY0IiIHIyykylOy7XDyg3oxfjY2T8GNCIiB1NW3QiA+wCJbBkDGhGRg3l321kAwKkr\nxVZuCd00aw+DUo9hQCMiciBKZdsR5ZwmI7JdDGhERA7kxxO51m6CFiZEImMY0IiIHMixC4XWbkKn\nJxgQEQMaEZFDEQqZjuwBxx7tHwMaEZEDYUCzLwLuErBbVjlJ4L777oNYrDpGJCwsDMuWLcPKlSsh\nFAoRGxuL119/HQCwc+dO7NixAyKRCMuWLcPUqVOt0VwiIrsh1Jpf9Pd2s2JLOApE1BGLBzSZTAYA\n2Lx5s+ayp556Cs8//zxGjx6N119/Hb///jtGjBiBLVu2YO/evWhsbMQjjzyCiRMnQiQSWbrJRER2\nw0lrBE3IORQim2XxgJaWlob6+nosXrwYcrkczz33HFJTUzF69GgAwJQpU3Ds2DEIhUIkJCTA2dkZ\nYrEYUVFRSE9Px5AhQyzdZCIiu6EdynjUE5HtsnhAc3Nzw+LFi/Hggw8iJycHTz75pObYEQDw9PSE\nVCpFXV0dvLy8NJd7eHigtrbWpPsIDPTq/EpkVnzMLY+PueXZw2Pu4tL2si9ydury72SOx8DVVdUG\nf38xvDxcevz+7FFjUwsAwMWl63/DzvAxtw0WD2hRUVGIjIzU/F8ikSA1NVXz/bq6Onh7e0MsFkMq\nlba73BSlpaYFOTKPwEAvPuYWxsfc8uzlMVfIFZr/K5XKLv9O5ngMmlrDRVmZFI3uxpet2Mtj3hOa\nZHIAgEwmN+tjxMfc8owFYouvQNi9ezfWrl0LACguLoZUKsXEiRNx6tQpAEBiYiISEhIwdOhQJCcn\nQyaToba2FllZWYiNjbV0c4mI7Ir2JgFrzXByatV8+FDaL4uPoD3wwAN45ZVXMH/+fAiFQqxduxYS\niQSvvfYampubERMTgzvvvBMCgQCPPvoo5s+fD6VSieeffx4uLh0PhRMRUce0y2ywRAOR7bJ4QBOJ\nRPjggw/aXb5ly5Z2lz344IN48MEHLdEsIiKHIOQuTqJegU9PIiIHol1mw9PNOmWLOG5H1DkGNCIi\nB+Ls1PayL3LmW0BvpWSZX7vHZycRkQOxpVCmXWKJiHTZzjOViIh6nLdW3bFBkb5WbAkRdcQqZ3ES\nEZF1qMsyLLg9DtNG9rVSI6xzt0S9CUfQiIgciHpWsX9fH50dnURkWxjQiIgciHrdly0UOOUKtO7j\n8j37x4BGRORAWlqPetLezWlpNpANiWweAxoRkQORtagCmosN7eak7mPYtV98hhIROZDm1oBmS+U2\niKg9PkOJiBzI6bQSAIDI2cnKLQEXoRF1gAGNiMgBuYis+PJvCzsUiGwcAxoRkQNyYokNIpvGgEZE\n5CDKqxs1/xfYwCgWZziJjGNAIyJyEGevllq7CWRmthC0qWcwoBEROQhb2bnJSEHUOdt4thIRUY8L\n9HUHAESHelu5JUTUGQY0IiIHIZerVn2Niguwckta8byibuNDZ/8Y0IiIHIRcoSpS6yS07ks/l00R\ndY4BjYjIQahH0JycmJCIbB0DGhGRg5ArWgOajdRA4ywdkXEMaEREDkLZunBJyDlGIpvHgEZE5CAU\n6oBmIyNoRGQcAxoRkYNQ7/zjAJo94ASxvWNAIyJyEAqFbU1xslQEkXEMaEREDkJhI2vQeDyR+fCh\ntF8MaEREDkIzxclXfiKbx6cpEZEdO5dRhu37MwDYzggaEXXO2doNICKinvPx7gsAgLvGRdjcGjTq\nPi7fs38cQSMicgQCgdYuTiuvQbPqvRP1DgxoRFakUCix9dd0XMuvtnZTyM4JBdpTnFZuDBF1igGN\nyIqu5FXiwNkCvLM12dpNITunVLYFNIGNJDQl62wQGcWARmRFcrnC2k0gB6FUKjVTnDaSz4ioAwxo\nNiKvuBZV0iZrN4MszNprgchxKJQ2VKiW3Z6oUwxoNqBFrsDq/zuN5/91zNpNIQuz9vskOQ7VCJpt\nTXFS93F22P4xoNkAuZzPNEdl9ZEMchgKhRIK9RSndZtCRCbg89QGyBVch+SoGNDIUhTQmuK08gga\ne735cJmE/WJAswEtCo6gOSq+tpKlKJVKKFvLm/JNncj2MaCZQYtcgezCGs0W9q7iFKfj4hslWYpC\noYR6sN5WRm65jorIOAY0M9hzOAtvfn0GiedvmPwz5dWNqKxV7dpkqQXHdTNvlC1yRbc/FJDj0a2D\nZuXGEFGn+DQ1g5RrZQCAtNxKk66vUCjx0r+P44WNql2bxZUNPdY2sm0380a55P1DWP3VafM1huxa\nWXUjzqSVALCFETRr3z+R7WNAMwP1eluFiWvJNrQeXgwA1XUyrNtxTvO1rFlu1raRbcnIr8LGPRfR\n1Pp3FnTzjaq5RTXqml8qNVvbyL599O15lFU3ArCFgEbmwr+k/WJA66aaOhn2JGahvrFZsyPKlNmm\n5hY5zmeWa77+9VSezvcvZlWYtZ1kW9ZsPYvkq6U4cbkIADSLtruqvrHZnM2iXkipVKK5peMPdMbO\neLWVfNbd/k/kCBjQumnz/9Lx4/Ec7DqUqRkFMWU9UF1ji87Xgb7uOl9v3HsRLVyTZveU6tHWbr4/\nqUfQyHFt3HsJSz84jOoOTiDJKqwxeDlH0IhsHwNaN5VVqdaNVUllmilOU0bQ9F8YN+9Lb3eder0Q\nR3ZIYPqoqyEyvZGTRlkLvjua3eGbdVeVVNbzw4INO3u1FADw+Q+pmssqaho1rx91jc04faXY4M9a\n+yQB5kOizjlbuwG9lfb7anW9DABwrnWzgDEnU4txvpPrAEBBWR28PV1upnlWo1AqsX1/BkbFBmJg\npK+1m2Oz1G9Q3Z3i0R5BO3L+Booq6/FLUh6u5VfhhYdH3nT7KmoasfKzJADAk7PjERXqhRA/D5YF\nsZCsGzXIKarB9FFhBr+vPVp/RWtz0oufHIfIWYjPXpyKT/97CZk3DI+gOTvZyN+RM5zdpuQObrvH\nEbRuUj83BAKgWioz6Wc++/4yklINf6LV9v43KTfTNKvKLarF72fy8V4v/h2q62So6+E1XkIjI2iq\n43g6f+F9b8sZzf8TL9xAVWvJlpIq8+wI/n8/to3KfPFjKl794iSS00vNctvUubc2n8HWX69qSvHo\nSzynW9JHu9+ow/vlHOO7yr3cRWZqKRH1FAa0bmt7ExX3wItdfknv3J1nD3W5nttwFM9+dMQi96X9\nKVipVOJP7x3En949iEZZx9PceUW1mv9nFtTgUnZF620A5zLK8NOJHOQV1+r8jEKpREpGKRqaWnD4\nXAF+OpEDuUKBlIxSfPlTqs510/Kq2t3nxazydpdRz5I1y6FQKvHLyVyUVNZrLt/8P92lEWu2Juvs\nIs8t0v3b63N3te7kiY2M39kHPph2i1OcXaBQKNt2bLZeJhQIMHl4KH5JyjP+gwA2/XKlS/d1vVSK\nsCBxd5ppVaaWGnF0AgPrFrXDbVFFPaJCvE2+vdp61YhfWXUjPm4t47L7cBa+Wjldc50Tl4rw5U9X\nMCouULN+affhLM33j10swucvTUWjzPDOQP5tLa9FocSew1n4OSkX3x7MxMMzYjFtZN9218u8UQO5\n1t/nH5tOIz7KF6lGRtE4VU1k+ziCZqLcolr86b2D+HpfGkqqGlBQWgcAkCuUcHF26vTnE88Xdvh9\nXy9Xna+drLyIt7t4bJVpNFOcWpdpP3YtLeZ5HDf9koaaOhla5Ap8+ZPqQ4I6nBny9b40o7X4jl0q\nglzBTQOWVFJZj5+TcjVfb9+fgaUfHDJ4Xf3nXm94BeGrBZFxDhPQfknKxbGLHYekjqh/9vC5G1j5\n6QnN5XkltWZZrLno7kE6X/fWbfA99YKbcrVUZzG0OckVCtTUmbaOsKs6m/LV7jvaIyCNzebZyZt4\n/gZWbDiqCWedOXaxCCeN7PwDgOX/PGqWdjkCpVKJDbsv4Lcz17t9G1evt59qNiYlQzd4d7QGjXo/\nhlv75zAB7dtDmfjypyuQKxTdKkVg7I1W1tz5iIIpNauiQ7x0vv7kv5fQZGSqyZb11M6iDXsudnvz\nhHoEyZhtv2VgxYajKDBzVf6Kmkb86d2D+PF4Trvvte3ibPPW5raF/9L6jjcpBPl5dKktJ03YnKL2\n7cFMo99raGIJmGppk0kjiY0yOVIyyvDN7xndvq//nTI93Jkawm1C7/z8SWRRDhPQ1P656wKe+9cx\nXC+R4rfT19HULEdZdQPe2ZKMyzkVaJErkF1Yg7e3nEFFTaPm54ytvxkW4w9D39IOKgfO5nfYpplj\nwuHhJkJCXKDO5aXVve+MTkt/qlM/ztV1MryzNRkZ+VWob2zGpl/SUFxZj4amFqzYcBRL3j+EL39M\nNXgbh1IKAKhKG5hzk4N64f6exKx23xMYSGiF5W2LwD//IdVo2ZbfTl9HSUW9we9ZQk5RDfYn52PR\n2gOo0vuwo1Ao8dG3529qtNqWlVU34Ll/HcPHuy722H0ktZ4yQWQKZl375XCbBC61HqX07razqG9q\nQU29DBU1TbhWUI11288hNswH2YW1aJEr8OInxzGknx8mDQ1FtZEpsNzi2nbrx3KLavGPTaeREBeI\n8CCxZgG3vltH9MGC2+Pg7GQ4J/fGJ15P1+Y5cv4GJg/vA0B1TNb2A9ewaNYgfPWzavRgzdazmuue\nzyzDyvmjNF8fu1SE6QlhOH6pCI/MiNVs+FCTNjZrwhqg+l16ajF12yYB44/Xx7su6CzyV/tmf/dH\nZLrq7SfH4dUvTupc9samtpG+45eKsOuQasTt85emoqiiHhcyy3EhsxwjYwPg4WZf5RxulKnWnvbE\njtb8Uik2/y+9xwtVh/p3bfS1J6hPX/nih1TER/liYIQvYvp6Q2TCel4iR2G3Aa2usRlJl4sxZXio\nwSd9fetUTXFlA86klWguz9A7u+5SVgUuZVUgpq/hHXUFpXWIDNadnjx8TvUmn3y1FMlXSxEf1b5g\n6wdPT4Cvl6tOANB/q+6VO616IJ8Vltdp/v9/v6RhaIw/JGJXbD9wDQA04UxftVSGVz5P0rnsza9V\n4SIy2AuhAR6I6eOj+Z7+1F5esRSRelPPaupg1dAkx+7DmbhjXAQkni44cqEQ4wcHw7OTYGLq8WCZ\nN6pRUyfDyNjADq/XExLiAhHq74nxg4ORdNnwFOnPJ9oWsF8vkUKk9WFj9+EszJkcDW+P3ll0+WYZ\n+ts2NLXg+KUiTBgSolPqQqlU4v9+voLswo7LY5jDC38Y0eP30ZlbhoQgr7gWmQXVuFZQje+P5cDZ\nSYB+fXwwMEKCARG+iOlj+i5mIntkdwHt659SUVhai2MXVdMEtfUyzJ3c76ZvN7PAcEVuQDWKoKZQ\nKHFcb4pCf6v7+mcmQiLWHXUD2o+mdPTW3SJXQNasgIebbf0JzVmJIa+4Fj5iV2TpVUPfsPsiVj02\n+qZuWx3q3lky3uh1/rHpNL58eVq7oLw3MQs/tK4rGx8fjKTUYlwrqMaI/gH44XgO0q9X4em5Qzq8\n/8PnCjAuPhjNnezWfHtzsqq9BkbSnJ2EWLt0PF785HiHt9Fd00epyjksuWew0YBWr7Um7c2vz+Af\ni8Zqvj6YUoCDKQW4/9Z+uPuWqB5po6V1NkCsPeqqfd3mFjmOXCjEtfxqJKUWY9tvV7FhxWR4uonw\n04kc7EnM6vaxX53pE+CpGfkDAD9vt565oy4YFOmL1YvGoq6xGVevVyE9rwppeZXIuF6l2hjRGtgG\nRPohJtQLA8IliOnrAxcRR9jIcdjWu7sZ7DqgO/2jnq40xtxTcn/99HiHGwfiwiUGw5kh8g7a/dr/\nO4mSygaDAcK6uv94KpVKXMquQFpuJeZMisbq/zsNAFist8M1u7AG1wqqDd1El/1Nb4RNX4tcCZFz\n2+N77lqZJpwB0JwMUVLZgIx81Y47Q0WGa+plOuUt0vKqUFMnQ76JGxOOXijEpGGhem1TwM/bDe8s\nGd/p79GZof38203bDYryu6nbVNt9OKvXBDSlUomM/GpEh3ppRt7zS6Tw8nRBYGDHvfvctTJ8vOsC\nXls4Gv36eOusW913Mg97j2TrXP/Zj47g2fuG6tSi66q7xkXgl5Md12Bc/cQYLHn/EABg5YJRHV7X\n0jzdRBgZG6gZIdYObOl5VUjNLsfl1n7p7CRAv1BvDIjwxcAIBjZu47R/dhfQ9F3MKte8OBli7uNr\nKmo63iH61/nGz0l8YGqMTo21PYlZWPHgcIPXLalUbSCQK5S2c64edEfQurqGa+fBa5pdawMiJJrL\nRc7t1+i9syW5+43sgqUfHMKMhDBMGhoKXy9XbDeyI6+pWa6pvl/UuoBfO/yv+Lh9eYoVG0wvWfHV\nz1fwv1N5kBo4giqkCzs6b0sIw4nLRajTW+c0c2y4WdZVGfvA0ySTw9XFCSs/PYF+fb2x5J7BN31f\nPeHklWJ8/n0qJg4NweK749EiV+DvX50CAPywbk6HP7ujdW3gr6fzsGzOEDRonQahH87UNuzp/maD\nuZOiMTY+uMOAdsfYcDg7CREWKEZ+qRR9Ajy7fX+WoB/Y3MVuOJGSj7S8SqTnVSEjvxpX86vxw3FV\nYIvWC2yujhzYyO7YfUAzt3lT+mGvgV15puqovlmovyfeXDwOi9YeAABcyCzHTydyOhx9UCiUgA29\nJmm/Qdc3tXS6Fuv8tTL4e7shLEisU1JAexSys9voafuT87E/ueOduPq2788weaTUVAVa01RA92rl\nzb89Dr8b+F1CfM2zcDyr0PBSgI17L+LOcREoqWpASVVDjwe0hqYWlFY1ICLY8BpCY7JalzIcu1iE\neZP7dWkJgbrrCwUCXMmpwPvbz3Xpvo0J8HFDWXWjzmXDYvwxe2JUuz7w8V8m473/pGhGZtVrKF9b\nmICaelmPHEvXk8TuIoyIDcCI2AAAQH1jM67mVyM9rxJpeVW4VlCNjPxq/HhcVdy7Xx8HDGw2NYNC\n5sSA1kW3xAd3O6A91cm6JLVlcwbj0+8uA1BND3m4OmPaqDCD15Xb2vE7Ws05k1aCW0eo1jF9+t0l\nVNQ24W9/TNB8X6FU4p+7VMcS6a+x0j6sfN0O87zRWdKvp7tfnNRUzlpTrw9P74/tB65h9oQoVEub\ncOSCqszFknvjkZpTCX9vN4wZGGTwdtYuuwX+Pm64d2IUvj+WAwCICNY9ZizYzwPFJpT22Lwv3eDl\nl7IrNGVH1M5dK8OxC4VYNncwnITmrfizZmsy8kvrsHbpeAR1M3y++Mlx/GvFZN0LO3i6KdXfFKDd\nOtTuWnB7HMYMDGo32vrErEGacDYyNgApGWVYuWAUxO4ivLF4rOZDXnPrBx0XkRMCfNzN0iZr8nAT\nYUT/AIzorxvYrrauYdMPbNF9vDWbDvr38YGriwMENrIbDGhd5O/T/QW2+nXOjBkzMEgT0ABgy69X\nERXqjfAg1TSF9q5RWwto2s359fR1TUA7dUW1U3b5P49g5phwZBfWYOLQtjVVT753UOd2vjbyRk9t\ntI/2mTk2AtMTwjQlW9QBbXx8CMbHh+j83KN3DMCW1sO2H79rIIIkqjdu7RG/hXcM1PmZ1Y+PQX6Z\nVLNpwRw+bg3nV69XY1Bk+53ONyO/dZlAaXVjlwKa/rOpSWskV6lUIqfI+Gahlta/hwBAjpl2Y85I\nUH0wGx7jj/OZqinoGaPC4OPZtjN22ZwhqK5r0glgXh4i1NY3230gaR/YWpCR37bpILOgGtfyq/Hj\n8VxNYBsQLsHACF/078vARraNAa0Dby4ei1VfntK5TCAQ4KuV05GcXoqNe7u2fkS/7pYxhtZtvfn1\nGcwYFYb9Z/MR5Nv2QmxrAU37La6wvB75JbqHvksbmjWFW1My2gqx3szv4SQUQCgU6JzY8MHTE+Dl\nIcLSDw7rXDfY1x3Fle0LAM9ICOvyNGZPeWhaf+w8eK3T6+k/Ztr19GaNj0SAxPCHiUlDQ5F1oxpT\nR/bVKTMyeXgopA3NmDwsFD5607OuLk6ICBLr31S3bfqlrTRKVzfqNDXLTZ+66mq30rt+k9a5pIfO\n5mtGGPWVVjWgsla1/jSvWNpuOvpm3TU+Euczy/HIbbG4LUF3NF3kLGw3Ova3PyYgKbUYCQMshHdf\niAAAHX9JREFUX57FmjzcnDG8fwCGawW2awVVSMurQrpWYPvpRGtgC/XGgAgGNrJNDGgd6Bsoxp/n\nDcHGvZfg4+mC5x5qW7CfMCAQE4eE4Nilnqn6PTjaD5f1poT2t55IUKIVMDra6WkN+u+1n/9wGW8s\nHmeW21712GjsOHCt3fmEX/x1GgBVvbQ9iVl4eHos/LzdDB7Hs2bpLXj1iySdqv1v/mkc+vh7WC2g\n+Xu7oVzr1Ipx8cEQOQux7berELuLIG3Q3RhgLGRqe2BqjNHviZyFWHx3fLvLnYRCzJ4QZfTnnLQC\n4LP3DdVZ4O4kFHQpZCee1z1p4I1Np5FTVItn7huKUR2MNJdUNWDlpycwfVRf/HHmgE7vp6vhT6GX\n0LSPW7to5GQHAEjPa+uTpoazIF93eLmL8NxDw/HMR0fafV97x2VcuASfvXiryYVcg/08MGdStEnX\ntWcebs4YFhOAYTGqwNbQpD3CVoWsG6od4erAFhXqhYERvhgQIUH/vj5wc7Hdt0hb+2hO5me7vc9K\n9NfaJAwIwhuLxiLYz6PdbsJFdw8yGNDcXZ0wYXAojl8u0pxd+HIHuzcN+fO8IXh6fWKn17O1ETT9\n1rTIlSadRWqKsEAxXnx4hM6u3PefmqD5f6i/J/48b6jma/0F1C89rCrQ+dafxmHxu21Tqn1bd7at\nXXYL3EROcHd1xs9JufjuqOGdd+agXZvq8VkDsennNE1I8/YUYfqovpg2si+EQoFmPZHasjlD8PHu\nC3hkRmyPtc8QoUCAR2fGIcjPA/1CvSFyFmr+trePCce+Tso9GFNZ24ScItWU4Ma9F/Hly+1rvm3c\ncxHOzkIM7acq/XHgbIFJAa3LT48ORtCMqa2XGS2W3JG1S28xeLmPpwueuX+ozugmAFbZNwN3V0OB\nrW3TQfaNWmQW1LQPbOES9A+z7cBG9oe9DarprdEDAuHm4gy5Qom3Np/BaK2pgTAjUzvaU5EJAwI1\nJTv+tWIKBAIBpif0xatfnMRd4yIwIKJra2xMfSE4daUYs8ZH2kwtNP0Ri6KKeiz94NBN325ksJcm\nIM8cE45fT1/H7AlRHa4J1H5MtDchCAQCvLF4LPYmZmG61uYL9VosAJgzKRq/JOVC1qJATB9veLiJ\ndMpQ3H9rP1TVyrD/bD5efHgEPmjdsbf6iTHw9nTB8/861uHv8+bisa011lS/02sLE5BbXKt541C1\nU/XvIzNi8cvJXDw0vT9kzQpEhnhh8+o7UVra81Xn9WlvVvnsxama8Hj76HDEhUs068q6QvuQb2MD\nXsmtNeTUAc1UXR1Ba78GrS2g6d/UW5vPIOtGDR69o/OgqE/7FAFtImchPnx2Updvj7pHFdj8MSzG\nH4AqsF0rqNaU9WgX2EK8NLtEbSWw2cYrP/UE6/euHmRKAc//9/K0diMtb/5pnM6bdUdeemQk8opr\nEeznoQlo6mAQ6u+Jz1+aCicT1551x+7DWZCIXXUW3FuTOev+xoX54Grr0Vvurm2jBw9MjcG4+GBE\nGTmGSVtEsNjg9cICxXj2/mEd/uyHz07CxaxyjBkYhKZmuWZE82+PJqB/Xx8olEr8YUZ/ODsJdQKg\nseObQvw8UFRRj8nDQiEQCHQK4PqIXTHMSFmO28eE4/Yx4Z3+rtbw6qMJaGhqga+XK3y9XPHVyuk4\ndK4AO/ZfM2n0yZB3t51F+vUqPDwjFmMGBt1UMekuD6ApjU9xtuhNmatPuPj9TNd37N47MUrn60fv\nGICDZwuw5J72U89kOe6uzhjazx9D++kGtvTWNWzZhbXIvFGDn5NyIRSoRti017AZC95E3WF3vWnr\nP+7E/45lYdIww2dwerg66xxPY6iWVN8uFHMcFOmLQZG+7dZFqRk7CN0Uy+8fho93dz4iob9GyZrM\ndTLD03OHwN/HTXN2pvqAdED1mEaHmnZO3+onxnZ+JSPcXZ0xdlAwANWIpn4pEKFAAKGBIsFCgQDv\nLbsFf/30hM7lM8eEIyLYq10Ji94spq9Pu8umjuiLqa27d/WnZ02R3vpc2r4/A9v1Doavlsq6dFtd\nHkHTD2jamwSMrFHUXs9ozPj4YNwzMUpz8Lz+0oRpI1VT2mRbDAW2zIJqzaaD7MJaZN2owS9JeQxs\nZHZ213t8xK460zD/WDQWr7dWAlfXRFqx4Shq6mRmLWIYG+aD2RMizXqotbo4Y2fUI3RyhcLs9aS6\nqrvxbPTAIJ1D60e31uz6aPkkVNY0GT203FYFSNzx+UtTAQDPfJQIWbMCfQI80c/BDoCeNzlap4r+\n8w8Nx/qd57t9e98eyuz8SlrUeauiphHHLhUh1M8De49k4f5bY1Ba1YCZY8KhUCrhJBRCoVSiSC9s\nGSrqa4o5k6J11jAuuVdVmFd9NJO5y4qQZbi7OmNIP38MaQ1sjbK2Eba0vErk6AW2yBAvTR222DAz\nB7aeOryVbIbdBTR94Vrrx9T1kD58ZiISz9/ACDOGKYFAgPumGN8515Myb9RgYlML/vxhIiYNC8Wi\nWaqzKy9llaNRJteEHUtobB2dlIhdUGXiaMez9w/F0H7+mDA4BL+duY55U9oOt/f2cIG3h0sHP227\n1KOnby4eh9yiWsSFSzr5Cftzz8RonLpSotnZOKSfP75aOb1bI2vdoR4R27j3ErK1Tjn4V+sO1B0H\nVOVM/v3CrfjxeI5mSl0tt8j0dX4fPD0Bf/s8CZOH98GcSdEoLK/DqSsl+MsDbVPpD0yNwaxbIq1+\nOgaZh5uLM4ZE+2NIdPvAlp5XhezCGmQX1uCXk22BTTXCJkFsmIQjbNQhh+wdAoFAU0DVHpxMLUZY\noGpa9uiFQiyaNQgtcoVmpEJ/aq4nbfn1KgDVCIKxYrMj+gdg/m2xOHiuANNG9EVA63o/7SNd7Emg\nxB2BJq5ptEcvPTKyXSX8NUvG4xW99aExfb2RWWC8EKw+9VmvzS1yXM6uxJB+fu2WFKgHGYoqOi59\nUSVtwpHzN0y+b0PcXZ3x6YtTNV8/MWsQ7hoXqTP6KxAIGM7smH5ga5LJdTcdtAa2fSfzIBBAZ9NB\ndwObjewPox7gEAFtyvA+Nn9IsDEvzx+JS9kV8PZ0wTdGDuoGVJsF1L78MVWn/Ed2YY3Ja7b0KZTK\nbp35WFnb1K5Wltry1hGFB6f271abqHdRv+lor70L9vPAly9P05Q78XB1hoGydR26lF2B/n198Mam\n0yiubMC8Kf1wz4Qo1fm0elRT/x1sWlACNfU3t5ZTvwyPq8ip103Nk3m5ujhhcLQfBkerdh83yeS4\ndkO7rEcNsgtrNYEtMritDltsmKRLZ8GS/XGIv/7jdw3s/Eo2akCEr6ZER4CPG1JzKjF1RB98/kMq\nrpdIDf6Mfm22N78+g/HxwfjjzAFwEgpMrpZdLW3Cc/86hpGxAUZ3PF7KLkfR2QJMGRqis/B5aIy/\nzpFUE4eG4NjFom6FPerdRM5CfPyXyXDT63faZVDuviUSN8rqdKYhO/Oh3lq2vYlZmDk6XOfAdoVS\nia2/pne6kUZ/NM8YQ4WD1XpytzbZB1cXJwyO8sPgqPaBLb21cG5OUS32ndINbHEREsQxsDkc/rV7\nkZGxgZpNCKufGIM1287imt6aGWOSUouRlFoMTzdnbFgxRXO5eppIW3peJQCguk61hiwlo8zgSFpJ\nVQPW71C9Sf7n17bpzHHxwZoim/Nvi0VesRSP3TXAYPV6cgxid8PTequfGIOM/GpMH9UXtfXNOHap\nCIESNwyJ9sfptJIu71B++sPDuHNchObrovJ6HDhbcFNtV7tlaCiUcgWSUos1lz04NQaTh/eBp5uz\nzdQipN6jXWBrluvsEtUPbBHBbZsOgn0dd9mEoxAozVUXwYZYo4CnNTS0bgzojohgMSYP64Ntv6nW\njP37+VtxKbsCMX29jRZZjQuXwMPVGf3DfPBLUi6a5QrImg3PS1ly3ZsjCgz0coh+bqnNBMa89MhI\nuIiEaJLJMWV0BPLyK3HsYhFGxAbgXEYZpo7s225q094EfaK7PKLkadNHOW+Wo/RzY5qa5cjSCmyZ\nN2ralWgZOygIy+YMMdt9Ovpjbg2BgYaXQnAErRdzd3XGM/cNxfFLRTjbWmndVHnFUk04A4Cn1h/u\n4Noq6lpv5zo4kxBoX4STqLv6h/mYPEpsbs89NFynHIZAIICHm0hTNNhWiweT/XAVOWFQlB8GaY2w\naQLb9SrkFNYgIpjrHO0VA1ovNyouEL5erjh7tRR3jA1HQ1MLvD1dMXdyNIor6jWFMS2JhzSTuax4\nYDhulNWhX19vzRT7x7su6HxIEKBr9ffCAj1RJZUhLlxi9IPNv5+/1eS1mkSWoh/YDC1RIfth0wFN\nqVRi9erVSE9Ph4uLC95++22Eh/NTq77oUG+s+/NE+IhddNaJhfp7YszAIFTWNuFaQc+NQtw+NgK/\nncpDRLAYy+8fxhcMMhsPN9WUujb1LuDrJVK4uTghUOKO6joZntMr5WHIly9P0/RPpVKJyzkVCJS4\nI0jirrm8uzuXiSyNr7X2zaYD2u+//w6ZTIbt27fj/PnzWLNmDT755BNrN8sm+XoZPsfxqblDcK2g\nGu9sSQYAPDwjFsWV9Th5uVjnyCu1If38cNfYCEi8XPHD8RwkXVYtiL5nQhSKK+tx6oqq2v/G56bg\n6vUq9A30xKD+QXhkOktmkGVpF6H28XTBZy/eimc/OgKBUACRkxDDY/wxZUQf7Dx4DZkFNRC7i3Te\n0AQCgaZelTaGMyKyBTa9SWDt2rUYNmwYZs2aBQCYMmUKEhM7XxTPBY66FEoltvwvHaMHBGnq8WhL\nz6tEblEtJg0LhUc3imhyUanl8THvmpp6GVychXBz6f5nUkd9zLlJwLHwMbe8XrlJQCqVwsurreHO\nzs5QKBQQdnLepLFf1pG9+OgYo98LDPTCpJu8fT7mlsfH3HTmOtTNER9z5evW/QzviI+5tfExtw02\nvT9cLBajrq7tiBZTwhkRERFRb2fTaWfUqFE4fFhV/uHcuXOIi4uzcouIiIiIep5Nr0HT3sUJAGvW\nrEF0NEs4EBERkX2z6YBGRERE5IhseoqTiIiIyBExoBERERHZGAY0IiIiIhvDgEZERERkY3pdQKuu\n7rkzJYlsBfs5OQL2cyLjnFavXr3a2o0whVwuxz//+U9s27YN169fh6enJ4KCgqzdLLvX3NyMPXv2\noL6+HkFBQXBycrJ2k+wa+7l1sJ9bFvu5dbCf9y69JqAdPHgQZ86cwRtvvIGsrCycOHECfn5+CA4O\nhlKp1DkEmcwjKysLS5YsgUgkwoULF5CTk4PIyEh4eHjwMe8h7OeWx35ueeznlsd+3vvY9BRnZmYm\nZDIZACA9PR3jx4+Hv78/Zs+ejf79++P7778HAHasHlJSUoI77rgDq1atwqJFiyCTybB9+3YAfMzN\nif3cutjPLYP93LrYz3sfmxxBk0qleO+997BlyxZkZ2ejoqICw4YNw7p167BgwQJ4enrCxcUFqamp\nCAwMRGCguY5CdmylpaVYv3496urq4O7ujsLCQuzbtw9z5syBt7c33NzckJSUhPDwcAQEBFi7ub0e\n+7l1sJ9bFvu5dbCf9342OYJ29uxZVFRUYPfu3Vi4cCHWr1+PqKgoREdH44svvgAAREZGor6+HmKx\n2MqttQ+ZmZn461//iqCgINTX12P58uWYMWMGysrKsH//fohEIoSGhsLPzw8VFRXWbq5dYD+3PPZz\ny2M/tzz2c/vgbO0GqCmVSiiVSgiFQgiFQgQEBKCmpgbh4eG47777sGbNGqxevRrz589HQkICKioq\nUFBQgJaWFms3vVdTKBQQCoVQKBTw8/PD0qVLAQCJiYn44osvsGrVKrz++uuYMWMGQkJCUFRUBDc3\nNyu3uvdiP7cO9nPLYj+3DvZz+2L1EbTy8nIAqjlwoVAIqVQKkUgEpVKJ/Px8AMCKFSuQkpKCmpoa\nvPbaazh69Ci2b9+OF154gYen3yShUNUFpFIpAgMDcfXqVQDA66+/jq1bt2LgwIEYO3Ys3nrrLSxa\ntAhyuRyhoaHWbHKvxH5uXeznlsF+bl3s5/bFamvQ1OsS9uzZg/Lycs3Q9rp16zBv3jycPHkSTU1N\nCAwMhFgsRk1NDby8vDB58mSMGzcO9957L4KDg63R9F6tpqYGu3fvhrOzM3x8fODk5IRvv/0WAwcO\nRFJSEjw8PBAUFARfX1+UlJQgLy8PzzzzDKKjoxEWFoann36a0xBdwH5uHeznlsV+bh3s5/bNagFt\n9+7dKCsrw8qVK3H58mUcOXIE48aNw9133w0XFxdIJBKcPXsWp0+fRm5uLr7//ns89NBDkEgk1miu\nXUhOTsby5cvh7e2N06dP48aNGxgxYgTy8vIwatQoNDU1ISUlBc3NzYiNjUViYiJGjx6NyMhISCQS\n9OvXz9q/Qq/Dfm557OeWx35ueezn9s+iAS0jIwMSiQRCoRB79uzBbbfdhoEDByI0NBT5+flISUnB\n+PHjAQDBwcGIi4tDRUUFCgsL8fLLLyMyMtJSTbVLKSkpiI+Px9KlSxEYGIiUlBRcv34d8+bNAwD0\n798fTU1NOHjwILZt24aWlhbcf//9cHd3t3LLexf2c+tiP7cM9nPrYj+3fxYJaCUlJVi9ejV++OEH\npKamQiQSwd/fH5s2bcJ9990HT09PODs74/Lly4iOjoaTkxO++eYbTJgwAcOGDcPEiRPh4+PT0820\nO5mZmfjoo48gl8shkUhw/vx5XLhwAbfddht8fHzg7OyMo0ePYujQoRCLxaiqqkJ8fDxGjx6NhIQE\nLFiwgE/mLmA/tw72c8tiP7cO9nPHY5FNAkeOHIFYLMa2bdtw11134e9//ztmzpyJhoYG7Nu3D0Kh\nEH379kV9fT0kEgnEYjHCwsIs0TS7dfbsWaxevRoDBgxAbm4uXnrpJSxYsAAnT55Eeno63NzcEBYW\nBrFYjPLyckilUrz77rsoKSmBRCJBbGystX+FXof93PLYzy2P/dzy2M8dU48FNIVCAYVCAQCaNQhN\nTU0YM2YMRo0ahU8//RSrV6/Gxo0bkZaWhqNHj6K0tBRNTU0AgBkzZvRU0+ya+jFvampCdHQ0FixY\ngMWLF6Ourg6//fYb/vKXv+Ctt94CAERFRaGwsBAeHh4Qi8V44403eB5eF7GfWwf7uWWxn1sH+7lj\nM3tAKy0tVd1wa/0bqVQKFxcXtLS0aLZZ//3vf8eePXsQHh6OZcuW4bvvvsOBAwfwyiuvsKLxTVJv\ns5bJZJBIJMjNzQUAvPrqq1i3bh3mzp0LPz8/rF27Fo8++ih8fX3h6+sLpVIJkUhkzab3Kuzn1sV+\nbhns59bFfu7YzLYGraioCGvWrMFPP/2EhoYGeHt7o6ysDFu3bsXs2bNx+PBhiEQihISEwNvbGwUF\nBQgPD8eECRNwyy23YPbs2fD19TVHUxxKYWEhNm7cqHkB9fb2xu7duxEXF4djx44hICAAQUFBCAsL\nw/nz5yEQCPDkk08iJCQEgwcPxmOPPQY3NzeexWYi9nPrYD+3LPZz62A/J21mC2hfffUVxGIxlixZ\nguTkZCQlJeHOO+/ElClT4O7uDhcXF5w5cwYpKSm4cOECTpw4gYcffhju7u6aTwnUNT///DPWrFmD\nmJgY3LhxA2fPnsWkSZOQk5ODcePGobS0FFeuXIFAIEBUVBQOHz6MadOmISgoCAEBAYiIiLD2r9Dr\nsJ9bHvu55bGfWx77Oem7qYC2Z88e/PTTT2hsbERKSgoWLlyIiIgIBAcHIy0tDdnZ2RgxYgQAICIi\nArGxscjNzYVMJsOrr74KPz8/c/0eDiUtLQ0BAQHYvXs3nnjiCcydOxctLS0oLCzEhAkTNAtCY2Nj\nUVtbi59//hn/+c9/IJFIcM8998DZ2WZO+OoV2M+tg/3cstjPrYP9nIzp1l9WqVRi48aNuHr1KmbP\nno1Dhw7hu+++Q2hoKFasWIGQkBBMmDABR44cQUVFhaYWy/z587FkyRJz/w4OJScnB88//zx27twJ\nX19feHp6AlBVlM7Ly9O5rlQqxd13343Ro0ejqamJn7C6iP3cetjPLYf93HrYz6kj3RqLFggEqKur\nw5w5czBz5kwsWbIEPj4+2LJlC3Jzc+Hq6gp/f380NjbCz88PHh4eiIqKMnPTHY9CocCuXbtQV1eH\njRs3YunSpYiLi4NcLsf+/fsxZ84cAKoFpeXl5Vi/fj2kUimCg4P5ZO4G9nPrYD+3LPZz62A/p850\nK6ApFAqIxWJIpVJIpVKEhYVh0aJFqKurw4YNG5CZmYnjx4+juroa9fX18PHxwYQJE8zddoejVCrh\n4eGBrVu3Ij09HSdOnAAAVFZWwtPTE9OmTcOmTZvwwQcfQCKR4O233+Y5azeB/dw62M8ti/3cOtjP\nqTPdWoMmEAjg5OSEU6dOISIiAn5+fhg0aBAuXryIgQMH4tSpUygsLMTKlSt51poZCYVC9OvXDyEh\nIZDJZNi1axfuvfdeXLt2DR9++CGSkpIgl8vx1FNP8YlsBuzn1sF+blns59bBfk6d6fbqwlGjRuHA\ngQM4ePAg/Pz8kJ+fj5iYGCxfvhwymQwuLi7mbCe18vf3BwDMnj0bR44cwX//+1+EhIRAIpHgxRdf\nxKBBg6zcQvvCfm4d7OeWxX5uHezn1BGBUqlUdveHKyoqsGvXLiQnJ6O2thYPPfQQ5s6da872UQcO\nHTqE//znP/jss89Y96YHsZ9bF/u5ZbCfWxf7Oem7qYCmdvnyZcTFxbFysRW0tLRwm7WFsJ9bD/u5\n5bCfWw/7OWkzS0AjIiIiIvNhyWciIiIiG8OARkRERGRjGNCIiIiIbAwDGhEREZGNYUAjIiIisjEM\naEREREQ2hgVXiKjXKygowB133IHY2FgolUo0NTVhwIABWLVqlaZauyELFy7E5s2bO739f//734iL\ni8OGDRsAALm5uQgMDISnpyfCwsKwatUqrFq1Cp999pnZficicmysg0ZEvV5BQQEWLlyI/fv3ay5b\nv349kpOTsW3bNqM/N3DgQKSlpXV6+48//jg+++wzuLq6AlAFu+XLl2P06NE333giIgM4gkZEdunZ\nZ5/FpEmTkJ6ejq1btyIjIwPl5eWIjo7Ghg0b8P777wMA/vCHP2DHjh1ITEzEhg0bIJfLERYWhjff\nfBM+Pj6oqamBq6urJpwBgFKphPZn24KCAjz66KM4cOAAXnnlFbi7u2uOTPrb3/6G7777Dunp6Zgx\nYwZefvllKBQKvPfeezh16hQUCgXmzZuHxx57zOKPERHZLq5BIyK7JBKJEBERgf3798PFxQXbt2/H\nr7/+ioaGBiQmJuK1114DAOzYsQMVFRVYv349vvrqK+zZswcTJ07UBLijR49i4sSJnd6f9vmJpaWl\n+O6777B8+XK88soreOONN7B3717s3LkTUqkUO3fuhEAgwJ49e7Bz5078/vvvSE5O7pkHgoh6JY6g\nEZHdEggEiI+PR1hYGLZt24bs7Gzk5eWhrq5O830AuHDhAgoLC7Fw4UIolUooFApIJBIAwJEjR7B0\n6dIu3e+UKVMAAH369EFcXBx8fX0BABKJBDU1NTh+/DjS09Nx4sQJAEBDQwOuXr2KhIQEs/zeRNT7\nMaARkV1qbm7WBLKPPvoIjz32GO6//35UVla2u65cLkdCQgI++eQTAIBMJtOEuJycHERFRXXpvrUP\nGndycmr3fYVCgZdeegm33XYbAKCyshKenp5dug8ism+c4iQiu6C9JkypVGLDhg0YMWIErl+/jlmz\nZmHevHnw8/PD6dOnIZfLAajCk0KhwPDhw3Hu3Dnk5OQAADZu3Ij33nsPqampiI+PN3sbx48fjx07\ndqClpQV1dXWYP38+zp8/b7b7IaLejyNoRGQXSktLMW/ePM0UZXx8PNatW4eioiK88MIL2LdvH1xc\nXDBixAjk5+cDAKZPn445c+Zg9+7deOedd7BixQooFAqEhITg/fffxzfffKOZrtSmvd6sK9Q/9/DD\nDyM3Nxfz5s2DXC7HAw88gDFjxnT/lyciu8MyG0REREQ2hlOcRERERDaGAY2IiIjIxjCgEREREdkY\nBjQiIiIiG8OARkRERGRjGNCIiIiIbAwDGhEREZGN+f+OV7LTySapvgAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x47f98fa10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "calendar_dates = {'IndictmentDecision': {'date': datetime(2014,11,24,20,15,0), 'offset': 0}}\n",
+    "plotWithEvents(indictmentSubset, calendar_dates)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our Thougts on this type of Visualization:**\n",
+    "\n",
+    "On the bright side, this type of visualization makes it immediately obvious if there are any gaps in the data, which, unfortunately there are. Additionally, we can see how the number of tweets mentioning Ferguson reacts after important events unfold. One thing that we find expecially interesting is how some events seem to cause a spike in the number of tweets, while some events cause a decrease in the number of tweets. \n",
+    "\n",
+    "However, while this visualization tells us about how many people are interacting in the twitter discussion about Ferguson, it does not tell us *who* is interacting or how they interact."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Visualizing the Location of Tweets \n",
+    "To start to understand who is interacting in the twitter discussion about Ferguson, we decided to start visualizing some of the location-based data that we had. Although many of the tweets are not geo-coded we, wanted to use the tweets that were to get a sense of who was engaging in this dataset, by understanding where people were engaging from. \n",
+    "\n",
+    "To do this, we first created a heatmap of the number of tweets origininating across the world. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Before we get there, though, we have to filter out only the tweets that have location data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "latLonPopulatedShooting = shootingSubset.dropna(subset=['coordinates_x','coordinates_y'])\n",
+    "latLonPopulatedIndictment = indictmentSubset.dropna(subset=['coordinates_x','coordinates_y'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we are going to define a function that plots a heatmap of the number of tweets origininating across the world, or at least a heatmap simulant called hexbin. Further, we should note that this will be a log scale graph, which will allow more clearly for ALL tweets to be visualized, but the density of certain locations to be still visible."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def createTweetHeatmap(tweetDf):\n",
+    "    #create a simple cartopy map\n",
+    "    plt.figure(figsize=(15,5))\n",
+    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "    ax.coastlines()\n",
+    "\n",
+    "    #straight-up coordinate data which we just finished recoding\n",
+    "    plt.hexbin(tweetDf.coordinates_x,tweetDf.coordinates_y,cmap=cm.Reds, bins='log') #add bins='log' to see a log based chart\n",
+    "    cb = plt.colorbar()\n",
+    "    cb.set_label('log10(counts)')\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And now, let's create some plots!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/Sophia/anaconda/lib/python2.7/site-packages/matplotlib/artist.py:221: MatplotlibDeprecationWarning: This has been deprecated in mpl 1.5, please use the\n",
+      "axes property.  A removal date has not been set.\n",
+      "  warnings.warn(_get_axes_msg, mplDeprecation, stacklevel=1)\n"
+     ]
+    },
+    {
+     "data": {
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a2WFV6POdu1jz3Crs9ogQ9SOAjt0xOOOs//ef8MnTPE5QvKAooPpAksFg1P+3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\nH+/Ywqwpz2FTLKxeOp93fvVLZldV0N2G1pMW8CPzC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lskypdeW8hAcGlNGaAo\nz0L17WuUlJaDUMCeF2wB6Zx+1hoUGGjb0gqt18Dn4eypE1T06gul3cFibykVmS8JWTHLJMqX6Wcu\n2by552f69ElGP7M+06dPMnmz18+EiFWfCWw2CxUV3VrOL6icF5zD4EH6POCux1dfS0G3nngKS7C7\nili2+BkURXDl6lX+9e//Lq4CF8VFRUyfOoWuXbsC2uprdY+q2b5rF4X5TnqUF1PXUE9+SQnf/95q\nrDa7obboUVlJj8oebcoMqOqP0+ngg42bsNvzCAT8BAIqFkv4pFYt/4IX5/HmO2tY/dpKFEXhxRdm\n88HGzZQUF7fZW0G/fpHTvF4f+w9+zvhxT7N1x0eMH/c0Nptdx3V2pJ9lCZ7sCcnJzDkwYSL9kE31\nwR18IRAIsHHHLpYvmKclusoRObSecDbhzp27HDh0iOWLF3W0KiZMmDDRBpEaKt569z3u3b/PcxOe\n5c7duyxZuKBNr6psauDtd99l5ZIFbNu9l3GjR9CzUtsPIZvfFfX19azbsIkVSxfjcmm712/etp2z\n5y7wZ//+3xoi461338Pv93Przh1GDh9GWWkpUyY9Zwh3MsipOQfv/39JlbO88gODNUkPdPYc6IWe\nlpdUeDPBZ5SszmoLo/mSlKFYwGoH1Y8FcDjyaHB7KCgsTIIvli5Pjp/dvn2Hzw5+zivLlxqoX6yy\nOeBnGX+GTVuYtk2VL1bZ3LaFiMD3nVWv8uDBQ/Z8uo+Hjx61TnoOQkVw9dZdtuzay7CB/bXAQLEE\n52upJLcXbPpt63IVsvq1lWz7cGebtBHDhvLeuvVMGD8uylKp+mV9Z9WreL1eVFVy4PMv8Pv9+Hw+\nbLZEFrgw2hY5gk4+rEjnJmgmTGQntGUTffh8frZ8tJvlS8wW72Rw6/ZtDn5xmBVLF3e0KiZMmDBh\nOFqW2AWwWBPcJ8ZYHP7qa1RVZeKz4xMqJ6Vkz9591NbVMnvGdAoLCw3T6cGDh/z6rXeQUhrWM5Eo\ncmoTtHX/I6lylhX/zmBN0gODew5MmMgcVJ8XGmvB24RVCFwWycP79ynv2rWjVcspNL9wvrPq1Y5W\nxYQJEybSAiGEtqu8TmjBhBf8Af7lrbfxBVR69OjJ/BfnYbWm9ul0/caNpIITIQSzZkxLSXY0dOlS\nzp/+uz9KC3enhNK5ew7i9Kd17os3kbtQH9yAa2fg/jV4fA9q7jJ7aC92rX0L6fd2tHo5hT179/HC\nrJkdrYYJExEhpSRKB7cJE2mBVFWofxRsfGrgt19ejEX1M3P8KN57bw0f7tzNN2e+pb6+Hp/Px7nz\nF/ji8Je6uC9dvkJVv36UlpRw6fKV9F5IziGHvjmFktxfjsDsOTCRmxAKWCzgD7SeEoI+PXtw6fIV\nBgzK/m7JjoIEUFUA7t5/QJOniW7dzN4WE9mJtes3IqUM7jZrwkQGIMAfUNm2czeqqqIoCt26lFOQ\nX8BrK5bhDsC16zfYt/8gXp+XgVVV2G02Dn5xKO5yoF8fPRZcehvWbdhEVf9+6b8eE8ajk8850LEJ\nmgkT2QelvAeyrDvS3QDuOi1YcLp4bsBTvPPeWqoGtt9580mH9DSBpxHctaAGuP+wml0HDvH6a6uQ\nagChWDpaRRMm2sHhyGNA//4cP3GSMaNHdbQ6Jp4ACKGw9qO9LHpxPgV5dm3icnARDKEo5ANDhwxm\n6JDWRqhdH3/C6JEj4nJ7va09290runH9xg169+qVjsvIQeTQN2cO9QIkg859dSY6NYRQUPILUcp7\noJR1R3G6EELw4gtz+HDn7o5WDwApVaSvCelxa3szdCRUv7b8qxpAVVU27d7LyvlzEF5PTtXJJp4c\nHDl6jH59+jBi+DAuXLrU0eqYeEJQXV2D3+/HVVSMyHMiHAUIuyPqsqcbt2ylsNDVZp+GaCgsdLX8\nnjD+GU6dPmOY3iYyCEUk95cjiN1zYLa8mshBlJWVUltX16E6SJ+n5UNcWy4P8AikYgGHC5HAxDij\nIJwupNMFUuX4kWPMWbwca69+IEQujfQ08YTgn/75VwwdPIhpU6cApDwJ1ISJUJy/cJHTZ85gs9l4\n8YU5wd2HtX1zNm/bzurXVurm8np9Ca88BKAoCl6fOUeuBbn0zflE9xyYrYkmchRWq4VAR7bUqwEI\n+FoDAwCk1nrfgZ/iAq3HRSoKdocDYQYGJkIgZXZU+6qqUlxU1BIYANisNnw+XwdqZaIzwO12879/\n+S9cuHiJJQsXMOW5ifzmrXdoaGgA4MNdu1m2eGFLsBAPn362nwnjx+mWHzq53mKx0NDQyLvvr2Pj\nlq2JXUgHQVXV+JmSRTZUPiaAuMOK9NypeJ8WsdIjpaXyqWL0Z06ifKnYwoj8RpU1gq9jbfHCrJm8\n9e57NDY2RimbZtvanZBfAnkFYHOANQ/sBeAs0iZSp6RL6rbNdzppbHQnKT+0zJPtZ/HLZv8zLH0e\n1Poa1Ae3kFdPIq99i1p9F7WxLs4qQcnaNna5Bw8e8uY7a3hp3gttyo4cMYwjx44nKDOeLkblN/0s\neb7M2ba2tpZ331/H6lWv8uLcOQAUFxfz3ddXsWX7h2zZ/iGnTp/B7W7SLe3a9Rv07dNHty7hH9ev\nLF/KypeXM3rkSDZv2xFHWsf72Seffsb//uW/JLGCmB5dcig6ECK5vxyBAf208W5mrPRIaak4h9GO\nlShfKrYwIr9RZY3g61hbFBYW8vrKV9iweSv9+vZh/LinU5SfWNmWNbWtNqQaACkRlmiPW2K6SKlq\nfFFbtuLzOZ0Oamubh14lYwsZ9t8o5JafxS+b/c+wrLkHj++HnPHBw0btRdZ/NIhoE9WTtW30clev\nXeOrI0f57uur2iwo4PN5uXHzFnfv3UtQZjxdjMpv+lnyfJmx7aNH1Wz78CO+t/r1dr0CFouFlS8v\nB2Dh/HkJSZs1YxpvvP0uL8yaSffuFTF1idTq3jxcrqp/P06ePh1HWsf7WXFxEa6CAq5dvx4jKDJa\nlyyEzp6lXEWc4EDQfvvr0ONoW2Mnsp12LD49W7Mny0cU3SNdS3PeZGwRjTObbKF32/tssa0+W1it\nVl5etoSz587z9pq1vDBrBl27dkmaLxH9VHc91D4EXxN4PYCKtOWBPQ+KuqE4CxKyhQz4tDkMUtV2\n+ZRSm79gsYDViYi43X103evrGygoKMiILaLzRUNu+Vl28EGythBde0NZDwj4tbkyQiBseWCx6nwB\npqa7293I3n37cTe5KS4qZvmSJe34Ll66zMEvDjNl0sS4fKafZaef6ZMVKU/qutfXN7DvwAG+s+rV\nkKDTGNv2qKxk9WsrOfD5F+z9bD8zpz0ftjR0a96DXxxm8sSJUfjQ2RrfsX427qmx3Lx5iy+/PhoM\nDoz8hhDtSmQtcqgXIBno6DkIv8EyRlqs8zJKWiy+aGXSwRcNeviicUZ7QNJhi0iysoWPFPgSldU+\nbcjgQQweNJCdu/fQ0NjAiy/Mwel0Js2nSz93PdQ9aHva0wieRkRJeOuSDr6ATws0QqH6tT+bk8iI\nrvvlq1d5ad7cyLIilmk+Z7RfREJu+ll28UVDez4BWpBpsYA9L8br2fj6bMPmzRTkF/D8lEnBYLU5\nra2sIYMHce7ChZBJn6afZQdfNKTy3ox2PnHdHz16xKlvvuHipcuUlBSHLW9tnC2EEEyZ9BxSSrZ/\ntJPKigqefmpsu7z37t8LCXDb85WWlPDw4SPKy8uamZPUT7/usdMi1BdCMGPaVH7wF/+FEcOGMmzo\nkCh8qeieA3iiJyS33KzQSDv04RJhadEQnpYMnx7+dPOFp4WfD0+L5OxG2yJcllG2iMcXnqaXL1a+\n9PmZEApz58xiwYvz2LVnLxu3bKOpqUmn7knoV1iitcYWloOjAOz54CqF0u5IGela4tjWatfmLNic\n2m/FGpzHkA8RW5ti27Z5Y5+O97PI+kVPi8fXsX6WnfVZrHwCGQggPW7U2kfIe9dQH9xErX+M9HlC\nwweMtq2UEp/PzwuzZ4UEBpH97Mix4/TtHTqEoaP8LN11u9F82eNn0c+nxxZ+v7bq0L37D2hobGTp\nokUp8emxhRCCl+bNRVEsrN+0mUNfft2Sz+fzYbFYYvJNmjiRTVu3haRlp58VFRXzj//zv4cEBrHq\n4kT0y6EAwZxzAMlFgdHyhR5HOx9PVjT+dPM1nzPaFonyJdM6kC5bxNMvFoywRTy+tuftdjuLXnoR\nj8fDr996h+995zXy8vIS5I9vW8WWB2XdY3CF88S2hVAs4MiPwxeNO/TY9LMnrz6LlU8ib1+EmrsR\nc4phz2nDixLgi32+9fe+/QeY8fzUiGnhx7du32bh/Bcj5Mu0n6W7bo/HF+t8dvtZZm0Bu/d8wivL\nlxIIBLh85WocWcbaYuyYUYwdM4ovDn/J+k2bGNC/P0eOHWfpogUxZdlsVoYPG8qt27foUVkZhb2j\nbavJaru0cGp+dvnKZb78+ijXrt9g0YpXYnBlEZ7sOQfNaHa8cAeMF93KKHmi8cWTFetBjaZPJvnC\n80YqYyRfJN2zxbbxdO9YW+TlOVi5YhnrNmxm0sTx9O/XTwdfLH1yx7Z3796lID9aS20kPiN1zy5b\ndK5nTj+f+vAW0l0HTW5oqtfShND+F5cj8vK1yfTuOi04EBawWBE2O0bZVgiBzWbVpbuqxrpm08+y\n1c/08YXnjVRGL19rmtfnIz9fa1AZPWpkmnSPzTfx2WeRUnLh4kW+t/r14LCm2LYYPHAgp775Jiw4\n6Dx+JqUK3iaQanBorMqhA/tZ+OI8Dh89EaFcliINvQBSSsRtjUUAACAASURBVH70ox9x9uxZ7HY7\nP/7xj+ndu3dL+ubNm/n1r3+NxWJh2bJlrFq1ynAdmhEn9Al3rvAbLiOcC02LlicaXzxZkX7H0yeT\nfJEepPAyqfCFlwn9He9exZMVjS+WPtlqi3h82rni4mJeX/kyp898y81bt3TwxdInd/zs4KFDzJox\nLUbeSPoa5ReRfqfCl/1+FrtMtHLR9DGGT966CHevwuN7LXNhaGoARz5KURkiz4GwWBCqPzipviHk\nZWiMbQdU9ef8xUtRdG/1s5qaGgpdBQnKivQ7tj6mn3UUXzxbJMKnnTt77nyEb7eOsYUQMGjggJD5\nDrFtIaUM2aMnl/0sxrvC0wjeRvB7QfUzf8Zk9u/fx4O7t8gZCCW5vxjYvXs3Xq+XNWvW8IMf/ICf\n/OQnbdJ/+tOf8pvf/IZ33nmHX/3qV9SlcbNXHf0i4Tc4VrSkJy0WXyKy9JSJlhaJN5m0eNcb7cFM\nhy1kknzReCPxxdInnv2i8SVr23jQb4vpU6fy7dnzhvFlws8kIKXUxov7mpABP1KqLdWvlCoy4EP6\nfVoeKVu80WKxhq3YEVtWe8lG+lmiaen0s0zVP0bzJeFnxV2hqAvkBSez253a/Jg8p7Yvh8XW+iJr\nnt8SdSWV5Gzbs0cPrl2/HoWz9T7u//wLpkx6Li5f5PPR9ImX9qT5mR5ZmXpvxkuLbQspJcdPngoO\nQ8vkMxetjB5ZrefLy8uoq6/ny6+PkBt+lug3hABbXnDunFbHFBYV88LsWYwePVqHjlmCNMw5+Prr\nr5k6dSoAY8aM4dSpU23Shw4dyuPHj/F4PEEV9NzT5BBnWFGsKDVa/nhpiUTfsfj0lDEiIo6V1llt\noUdmtto2Wp7otnC5CmhobDCMLyO2qK8BNcJusUIJfsRFKJNfjLTY8PtDy5l+Fl9WLGQDX+K2sPQZ\nqv2SKtLTpPUUhLVqSamCqoJiifMSSt62eni9Xi92u10Xn+lnyfLpkdXRdXt8vjt37vDR7o9ZvGC+\nDr5oMjvezxa9NJ/LV66wZu0HPD12DIMHDdSpR7bUP9FlCgE4XVqqlME6RkEIoQ1nzBWkYbWi+vp6\nCgsLW46tVmvI4iEwaNAgli9fTn5+PnPmzMHlchmuQ4vs1CmaW1E6IxK9tnj5s8FWyepgtC2eXEgp\nIeAFf0Abc6koICzapmlxP8QABDgLIBAAn0fjUmzaHgpK8JFuXvpUDXZPCwU8jWze+QlTJ4xHBvwx\nNmXrSGTCzzLtm9nyLLTXQwgFEWWiuxAWsMR6Aab/um7fvkP3ikhL/6aKzlifZYuOmXtver1etmzf\ngd1ux+/3072igu+sejW4KlA2IHlb9O/Xj/79+nHoy69Yv2kzi16aHzYJOP24fuMGXx89xguzZrbM\n3zDyG0IIoS2hnItQjG+1d7lcNDS0NlSGBgZnz55l79697Nmzh/z8fP70T/+Ujz76iLlz5xquB+ja\nBC0esqEyShcSvbZ4+bPBVsnqYLQtsgvp7J5rB3cd+D3tz3uAwi46CCTCYtOGftgdLZZucwVWGzIv\nH+qrtQBEqnx95AR9Ksro4sqDpjpkQamuJzyzyISfZdo3s+VZyK767Oq1a3Tr2jVmni++/JLFC15K\nSU5kdMb6LFt0TJ+fPXjwkM8PH8aiWGh0u3EVFDBn5gyKiooS1jIzSN0WE8Y/Q0NDA+++v47Vr600\nRi2dKHS58Hp97Ni5i6p+/Xhq7JiIOuqDnnLZ90aKijT0HDz99NN88sknzJs3j2PHjjF48OCWtMLC\nQpxOJ3a7HSEEZWVl1NbWGq5DM7Kx6dCEic4NxaK18Kv+kJMiuGSkJLSCbKlOVVU7LRTdI0kFaLso\nI0ENcPn6dVYseFGr1ESOttaY6BTw+Xzs2Lmbf/V7vxM3r9LJlww0ER+BQID1m7ZQXlbKS/Pm0tjY\nmNYhFdmGgoICSktLuHHzJr169syY3JKSEp4aM5qLly6jSslHuz5m7pxZGZP/pGHOnDkcOHCAlSu1\nIPAnP/kJW7duxe128/LLL/PKK6/w2muvYbfb6dOnD0uXLk2bLjrmHJgw0fmhb9t6YyAcBUiZrw35\n8Xu1j3Wbvf2Yb58HPO6wuQUCacsDZ6G+6WX5RdrqF14PDlcxOIvAas9sT4kJE2HYsn0Hq15eHjNP\n+oYUmcgFeL1e/H4/Xxz+krv37rN4wfyWoS1PUmDQjAUvzmPD5i0ZDQ5AW2nJarXwxeGveG7CeN56\n9z1eXrYkbH8go5BD35xpeIcKIfirv/qrNuf69+/f8nvlypUtgUO6YfYcmDDRAdDGWlojbjAlpQo+\nL/jcbXoXpJRIrxse3QWrFeEqQxSVIRSLNrG0sQ4aHms9EwUlCEc+Qgju3LnLnk/3MWv6NIQtHRW6\niUxA+r3IukfaPJO8fISrNC3zRrRJggHw+wCpjQm2GBtQWiwWiouLY+Y59NVXLHppfsw8Jjov1q7f\nyJFjx/mLP/0TunQp72h1sgJWq5VNW7cxa/q0jAZI/fv1o7J7dzZv20GPyu78/J/+L3/yb/8wY/Kz\nEmkYVpRNMGDOgQkTuY1AIJA1QxdkQw0E/LRtQRGoDTVw56rWkyBVLS8g7U4oKNY+3HxNbcpIuwPZ\nbyS79nzC6tdWmr0FOQqpBpCXTmjBYsv65yAtNmSXHihd+xgny+cFT0PYkDdAKEhnIcJqN0SOHl+U\nUmbNc2ki83A6HSxfssgMDEIwZ+YMPB4Pa9dvZPSokYx7amzGZDscDl5ZvpTbt+/Qr2/fNEnJnXdU\nZ3+fmj0HJp543Lh5k94Z7qqNCqkSccm4QEDrTQgGBi3wurVVjiwW3E0eDp78lvpGNwCKxYqsvMkL\ns2Z2+ooMglaTEoTIoVeMDkiprT4VEhgA2jmZ+JVqI+jUiPNXaO41aHdebX8uBRQXFXH//gO6do08\nAd/tduN0OA2VaSK3oCgKkyZO6Gg1sgoOhwOHw8H3Vr/Olu07MhocNKOysnvGZWYlnuyegxwa/2Ui\nzciWZfKMx8VLl3n2mXEdrYaGgtLWZU6l9gGH1YJS2AUq+iOr7yKb6uDaOWish+qHuOse89nVezQ6\nCpk1fQpFVcMgLx9cpSj2zj+MSPq0XTZblm4VCtLm1IImqy3nAwVhscKgccj6x8GVrrzaJkL5RYh8\nfau0yIAfvE3aX1MdqBLsTqSzAPIKEMHlBIU9D2m1BXcuDWjBgmKJOgQuWTw/ZTKbt22PuhLR54cO\nM/HZZwyTZyKb0f7dcunyFXO+SQwIIWhq8nD37j0qKrp1tDoGIoe+MZ7s4MCEiWbk0EObIOobGtI2\nfrNl/LaU0GZn4sgQQmi70UZ6Mm12RLfeAAQunePU0WOcvX0fl8POhH49KClwQr4LUVmV8x/ECcHb\nqLWiN0Oq4G0ACrQAoRNAKBZEURkUlSVcVkoJjXXQUE2bXY69jdpfiYJ05LdMiBeKAnaHUapHhBAi\n5pCh6poaSkpK0qqDiWxB+3fLydOn07SEbefBy8uWsHnbdgYNGMCwQVXB90vn/mDNKqRhn4NsgsFz\nDppbACK1MsdKyxRfeNlEZSUjI1ttYdq2bZlouiRnC+nztrZkN4/fViza0qL2/ODY7eRs4ff72fAI\nqmauZMWQAUhPI8LuQOS7tJWIUtI9B/2soET76JWq1iKuiOByrSKCLZKRkUO2CDknPY1aL1Rwnwvy\nC8PyBn/73OD3aL5psYLDFaHmN94WTU2e5lFgbfD4cS1FhUUJ85n1Wbr4wssmKitxGWWlZVy7fp0+\nvXvrlBVP505o26Z6Fs2YzN7PDuCtuceYEcORFou2/02GnmHjbZFDH9ydPBAzuOdAhv3Xm5YpvvCy\nicpKRka22iLTto1WSXRG26JNKg7f6EwNaH95BXFkRU4RgJSSd99fx7LFCykoKAimlsYoFZs3sTLZ\nwBdeNvg6EQKEJdia8wT5WSy+gE8bHhQxb5idpAoBVduhO6YM42wx4/mprF2/ge4V3Zg6eRInTp7i\nwqVLWK1WXpo3N2E+Y/ULLxt+zvQz/bISlzFl0kTeW7c+LDjIBltkkZ8FfKD6mT7pWfYePMT5S5cZ\nVNUPiDCXKK5+2WSLHEEnn8enc85BrOgvWoSYbIuCnogzEVmJyEyELxZPJm2RTJlM2Da8XLgvGWUL\nI/iiIQVb2PO0ykOqwZZbtCUh22w+FptP+nxITyPSXQ91D8FmZ+vnR5k1aQL5TmeC+pl+lpheydg2\n2Ra0NNVneflaT4BUke5GqH2IrH6IvHMdGmqhVxWirAJR3g3hLNB802IJac1Pb33WpUs5ryxfyp07\nd/lg42ZGjRjO8iWLY5ZJ2hYJ8cXXPf1+lkiZRGV2BF9i17Vn7z4aGhv55sy3DB82LGW++MhBP3MU\ngN8PMsD0qVNYv/0jBg0brvVQSxkcwpprfpaIrToYZs8BxL5hMkqeaOeT5YtVPpkyqfLF4smkLZIp\nkwnbZsoWqfFJqcaYB9BellbpxqANlhGKBfLirbYS27bqjbPw6Fbbc7cuUfGwHHr3BsIrJ9PP9PGl\ny88STYumjzG2FSGTiOXpI6i71rbNdv6UlvP1f4dSFmkFkszYtnv3ClYsDQ8K9MhKRGYifInokS4/\nS6RMouU7gi+x6zpy7DjFxUXcuHmL4cOGpswXH7nnZ8Jqh+DSwlJKrE4XIq8gbrn4emWbn2Upnuye\nA2htWZUhx5FuZKx84b/TmS9cp0T5Ih1HO59MPr06hfPp0d1oWyTLFy1fIrIy42fV1TWUlYZO8myf\nT3rdrUOC1ABSCFCsWstBXvNETuP9TOk7HHoORHrcyKZ6VASidy3K6OnauFJDbBEuNxm+9rpnhi9a\nvkRkPRn1mXhqCpahTyNrHyEf3tFaHEu7IkrKEa6iKOVC5aZ6jUbwhXOky7bxdDf9LPI1JXONkfNN\nmTSRurp6Xpg9M0Gd9MrN/W8I9etPkfduQc19eFyNvHibgKhGdKlEjJ+JaDNhNlf8LIfwZPccRHLc\nSDc59HxzGRkhLVL5VPJFe7BS5Yt3jdGO9fDp1Umv3HTbIhm+SPkyaQv9+e7cvUv3NkvBRcjn97Yf\nux3wA0Lr2k3KvyMdtz3fvGqMsDugsBQLIPKcCJs9rLzpZ9nuZx1j29ZjoShQ4EIUuKAy2qZpZn0W\n/Tgan+ln0Y+TzSd4bsKzvL3m/ZDhMbnmZ8bZIpqfyWMH4OHdlrOBB3fg9JfIgaNQJoR/bCdri0z7\nWQ4GCZ0UcUKfWDcW2t/IZmcQYWnRfutNi8QXKiuWTtEQiy+WTkbyZdIWetOy3bahx6nb9srVa/So\nrIzBJ7SuW5tDa60XitZrYM0Du5M2S0PG1T2UPzlbtF2qrjP5WaaeOb18ocfRbBGrTDJ8Rj9z0WQl\ny2f6WW75WaTf2exnzceafkOHDObW7dtR5MbSKVJa5/MzMWI8DB0H3ftAvotxw4aw32MHVyFq7SOk\npwkZCIR8xXWULaKViYR479MsgiKS+8sRpLhaUbToMdnWBqP5YiHVFh8j+DJpi2RaBLLRtqHHqV2v\nlJKGxkacTkfMMsLeOndABoMB/TsOG2eLc+cv0L9vaKuv6Wfp4ws9zhbbxkI22Nb0s8T5Qo9NW4Ta\nYvjQIbz/wQa++/qqsOHdpp8BKBPntJwJ3LxIH/djjuzZj6gaBPeutJQS/UcFh6Hmki1yAE/2sKJm\nhEaB4Tc30jkj+MLT9MhJhC9ZZJIvGVlG88WT1YxM2cI4vv0HDzJtyhQApFTB522dW4DUeggUBWx5\nrRtEtVkBQq+sZNCW79Gjag5/9TXfWfWqIXz60zLFF09WM3LPz5K3RWp8MhDQhsPJQMvO0SgW7c9q\nj7iaiVQDyAe34PFDZGNwN+b8QkR+MXTrheIMn/AYTWfTz54UP0tMhn4+p9PJhPHPcOr0N4waOSIB\nvifPz5SKPkifB0vJOXAUgkWB/GJtUYw2K+Tp1S+TftaMHAscnuwJyc0XHy3ijHYuHvTwJRNxJsKX\nLDLJl4wso/n0yDIKmfWz2ro6ysuDewR43NpusW0QnGdgtYf1hmbWz2pra9n+0U5eX/mKIXyJpWWK\nT48so5AN9VkivEnyeRra77XRjMIuEfnk7SvIUwciShUFhRA3ODD9rD1fJ/ezhGQkxjd0yGDefX9d\nhODA9LNQPmG14ZcgCooQvQbpHsgUja/tf71penljncuhD+5O3nOQpquLdINTuekdzZfLumcDn5H5\n45XVz9eta1fu3buvHQRbU1FCHgmhaOfizitITT8JSCm18aFqACnVNlXmtg938tqrL8cZypSLfpEu\nP8tF3dPAZ7G2zpNpOR3sPQj42/kZAAXFUN4zZDdltPk2xV1BVTOne1bzZVJWLvMZI8vlKmh3LhW+\n2OeyiS8xWQe+OMSkCRO0FfXUgPZOSYFPP4zmyxEIkdxfjkDnJmiJwqiWkmzhy2Xds4HPyPzxyurn\nq62tI3+gNp9A2B1gd2hzCgI+jcdiT2BuQXL6SZ9Ha+FVA22zCQWZX8LREycZM2okihIvjs9Fv0iX\nn+Wi7sbzibx8yMvXhsw11YPPA1LVsjfWaNmCfiYs2tADpaQLPDNLCxxqa6CpHlHeXVtTPYO6Zzdf\nJmXlMp8xsqwWKx6Ph7y8PEP4Yp/LJj79sqTXTfXt65SPGQL1j1oTFAuyoCRsIYtstoXRvSpphNlz\nYMJE58Tj2scUFxe3OSeEQFjtCGteS2AgpUT6fciGx8jaB8i6R9rOxUn3KIRAsYI9v2Uzm1C4ax5y\n7tszDBs0wBhZJp5ICKGAvUAbixzqZ4pFW3ErQgAshIJSXIZS0SckMDBhIjOQnkbUy6cJHN3L5CLY\n+f47SJ83fsEnFRYbit2pPdPNUOzB59v8zEsLFCW5vxyBzjkHJkx0PlgsOidqVd8FTyPtWjUsNmTX\n3in1LgiLBSwWrdcCtFYfNUB1dTVbdu7htWULtVZemwPpLDSfSBNJoZ2fSQlCmP5kIuugHtmLvHRK\n6+kCCgDP8TO47XU4F/4OIt+VVvn19fVcu36D2ro66urqKSx0MWH8Myn2IqcXwmJFWqzgKmt5tiEX\nv+ByR+Ns9gcjkOJSpiZMPAkIjhUMb71vPmdQJaGt5SA4eeYs5y5eZvXLS1oroM5dD5nIIATk1NhX\nE08YFEWbL+NrnUw/c1h/Pr94gxnSDxhbHUopOXHyFJevXgXAVeCiX98+VPXrR2Ghi4ePHrF2/Uby\n8uw4HU6mPz8Fuz27etPOnb9Avz59zGc7k+jkPTJpmnNgwkRuoHUHzugQZRVINQBNDeD3ay8vuyO4\nxKmxFfHpq7epCygsX75CGx8uFLDaQLGY8YEJEyY6PZSxzyNHTETevYa8fxO8bgpdxTQc/QZR+xDq\na5DOQnAWIWy2hPnv3r3HvgMHsdmsWCwWVFVl1IgRLFm4IGL+Xj178srypQA0NDSw7cOPAJg/94UU\n50EYAyllistcZxNy6JuzkwdhZs+BiScOUlWRtQ/x37uJbGoAR0H8AEGxQH5R2nU7c/YcLy9bknY5\nJnIPUkpkzX14dA+69kQUlugKTqWqavsVKMKASfYmTKQfwmaHnlWIsm5QX83N6zfo1b27lqgGtAn2\nzgJAf3Cw/+DnPHj4kPKyMlYsXZzUc1BQUMDSRQs5+MUhvj56jEkTJ7TL8/mhwwwdPJjS0pKE+aOh\n5RkWImSPErh37z47Nq5n/sBeqHeuIbr1QuTQuPacxpPdc9BZXyKJbuCRzIYfmeRLBR19bZmzhdrk\nRp74THuxuOvh+lnk/s3I/ELoOwxLr4EGS9R/bVJKNm3dzrinxnaI/PTjyfEzoyEDAdQDW6HhsfYn\nZXAVkmLoOxTLsPFEujbZ1AgBDwQCrelC0cYmOwoN/IjIJtuafpY+ZMYW0uPW9ucI+AHJI7eXPUdP\n88K0KVDeC6zWhHtSGxoaePjoUdTegUQxaeJEDn35JV9+fYTx455uOX/s+Amu37iJzWbjmdKnEmCM\nbCvNFk0Rn+HA9vf4eNdeXutbirh7FPXzbVBcDv0GY3npOznaCJCLOndOPKE9B5lcbjMTfKmgo68t\ng7bwe7TJxUiu3HtI766loPqhvtrwOklKCQI8TU18tPtjFi94KWb+rTs+5Llnx1NR0c1ILQzkShVP\nkJ8ZjYAfHt1pMwYbNQB1zUsWRrk21Rf8wAqBDGmBNAzZZFvTz9KHDNlC9QeXk9aw74svWb1isbac\ns9UWMai9d+8++z//HJvN1m5lNyEEbncTy5csSk6fiJBMGP8Mm7dtp7a2FpfLxYbNW6isqMBqtTB4\n4ICE+SIiEP0ZvvLNaXrgQQSCy2CrKlTfh649Er4aE0kgJ4Mv/UhwzkGk6DZe60Cs9GT4YiETfKnI\n6my2SPR6UimbOp8oKIaJL8Kju3z17TaWT50E+UXa+fLKGNz69JNetzZMyV0PNfcgz0mNR3Lm5Ek8\nHh82m4VePXuGtDQJPJ4mPtz1MT17VEYJDEw/yy4/i4X08Al7HmLGCrh7HVlXrc19yS9EFJZCZd/o\nxZ2F4PNqgYQa0F5mikWb7GmI7rlvW/18zWnR8jxJtkiGLwFZjgJt876g3z47fjwbdu6ja0VXnn9+\nWpuSd+/eZ//nB1EUhaWLFgZbyzNniz69e3Pk84N4G2qZ0qOcUvU+2+9fY/N777DytdewFhQnxAcC\nGfBp1+73tu5w3jyEpXkRDKnydeUQVsyai6x+CPW1iMJSRHkFVA0N6TXoeL/44vCXNDY2MnP6dB18\nORRcd/LhWwn2HES6cfFuZqz0ZPgSlWU0XyqyOpstEr2eVMqmzieEQBR3ocHqxDVkDNanZ8bhTEw/\nefcKPL7fesrXRDdg5YQhfHaniRdmzaPm8WM2bN6Coigtk6Hnzp6Fw+FISFbi+qXCl6iszuxnicoy\nhk8pLteGDCQAbX+DaH4VXVbsc3rTc8e2+vhknDxPki2S4dMvK9xve1YVsaJqEDdu3uT9DzaQn+9E\nSonX66OkuJhlixeFDaHJnC3GDB/KhYtfcfHaNcrLh/M/N+6iKN9Jzy6lHP5kN5MWLEuIDyS467Te\nkzanVVpWyxOC+oYGSiq6o4war53LL0FYI82/6Hi/yHc6uXP3Lm+veY+pk5+jT+/eKfFlDdLQcyCl\n5Ec/+hFnz57Fbrfz4x//mN5t7KXhhz/8ISUlJfzJn/yJ4To0Q8ecg/DILvRYbytKsxHj5Y3FF15e\nj+xousfii6V7IrYwmi9S+UjH4XlTsYXRfOmwReJ+9vHefcydHSkwSM0WotcQqBwAfg/S6wVFQdgd\n9B1uo49QeH/dela+vIJ+ffvG0d30s87gZ52rPoumZy75WbLPVSJ8xEgz/Swx3duW6dWzF6+u6JkC\nH2H5wq9FD1+YLaw2Bi7+LgN9Xrx1NUz2uhgzdizrd36CJa+Ix48fU1xcop8PCa5SkKrWe9BQC74m\nbchQwE9z79/GrR/y6spVkO/SWrAj9hRkh5+NHjWSs+cvMG/ObG2VKKuNysruUfQQ5AzSMCF59+7d\neL1e1qxZw/Hjx/nJT37CL37xizZ51qxZw7lz53j22WcNlx8KHVcX7gwyRlqsMnryxsoTSw+9fDLk\nf6y0aLITsUWkSjEVvkjlQ48jPVSp2CIdfJFtIWPyRUqLpUP0vM0pPp83yhJ0qfmZtruyDeFwoRSV\nobhKEHYHQrGgCEFtXR2qGtCh+5PkZ9FkJ8uXLltE44uVtzPVZ5D7fpbocxWLz/Sz9mnRZBttCyP9\nLJ7s2LYQgFAsiDwneV0qmTjnRZxdK1m1aiVjRo1i/+dfcOTo0Zh8MkwfAQihIJqHVnmbtCFGwYDh\n+rVrDO5dia3AhbBYtPdOwrYIP06Hn7VqtWLpYrbu+JDZM6Zx6KuvQq45ll5ZDiGS+4uBr7/+mqlT\npwIwZswYTp061Sb96NGjnDx5kpUrV6btspoRJzhovsGhUWnoxUX7Hek4UlokPhGWRw9i6ZSq7qnw\nhdsvEpLRLxKaH6xUbRuthSXS70RtoR1LCdLvQ21qQH38APnoLmpDLdLn0ZZsM9DPpJTIgB/paYL6\nx5z++kuGVfXXzsUt354v+u/4tnh1+TI2bN5iGF/sexVNd6P9LNLvRPwsnh5G2MKIOiEWnqT6LBJ/\nJFmmn2Wfn6XLFpngC0dHPXOxyremK4qF7t0reGneXC5duRoySVrLp00bCCD9PvA0Ir1NyIAPKdW2\n7yVnIRSUgsMFVjvY8jhy4SrjJ00JumA2+1nINUuV15cu5N03foNSfZdP173DyYOfojbWaXsItXDn\nUoAgkvyLjvr6egoLC1uOrVYrqqoCcP/+ff7hH/6BH/7wh+0m3acDOuYchDp1Mi0vsTijlUnUSaLp\nYYTuqfLFu45YrVB6OSKVS9a2yVxXYraVtQ/g/rXIknsMQuQXRkrRISsCY90jaKgB4NK1G+w/eJjf\nX7kM7l2Fbn2jTM6MwRfzd+z72NDYQFlpqWF8xj5z8cpH44v2u+P9LHH9OuqZi8YX7XdH1meRjiOl\nmX4WXb9cqdtNPzPCtsOGDObipcsMHFDVer6pThsuFAmFXVq+IUWeE/KcbZIVVwlKUfP8o9zwM3nl\nDOL8EWa4vNytecjabUeZMLgvw2qvoExahCgqjciU1UjDnAOXy0VDQ0PLsaqq2ipdwIcffkhNTQ3f\n//73uX//Ph6Ph6qqKpYsSc++SDq/jJqdIZJTREsLPY7mTLH4YuWNJiuTfEbaIlndwyP0eGUzZYtQ\nvdqniaJyyC9Eej3gaQS/T9uILM8JNnsSsmLYtrAUnEUQ8HJq/5f8/u/+NtidYLHrWLVF+y09jcGu\n3eASe4pFW2vbYgNn83rxsW3r9/v5+JN9rH7t1XZpke9jNj1zuelnqT1znbU+IwlZpp+16pUpP8tm\nW5h+Fl+/VlnDhg7hX954i349KrAIgqsw+bX3iJSoTY1w6QzU1cDjam1uQUkXRHE5DBiB0qWS2to6\n6hvquXHzFqoaSZfs9jPRdyh0682AxjpOrF/Pz/7tQRBKcQAACRtJREFU73LuXjUbz9/5/9u796eo\nzjuO459zdpeFgKuCAkq8EsH7BWLtRGlsDPHStGkqKMyUZKb5pT/1h/4D+hv5vamddtKZNJ22RhNJ\nopmxkQq2YzMJoph4CaAiKhcDGMptYXE5/WFhFRVYll3ZXd6vmR3hPOc8z3eX4+757vOc59GejKuK\nnz1X52pvqOpKvfL3Fj+h/ggUhuQgJydHFRUV2rVrl2pqapSVleUvKykpUUlJiSSprKxMDQ0NYUsM\npIAXQbMe+fdhY5VZY/w81j6T2Xestp5mfYGUjfwnCddrMdYbabD1Pfzzo7FP9W//oD7DMCSHU4bD\nKSW6Rr1FhaatBwzDlBym5HD4VjielTLB4jBPqK/nf5Knb/RuA5IM86FVk8d+bXt6enTkozIVFe4d\no62ZfJ6N19ZEZYGct4HGE0xbk6lvvO28nz1ePtPPs7Hqmqi+8baH67WYSn3BtjXe9smcZ6Go70n7\nPGjLNE3t3/u6PjhyRHNcSdq8YZ3mpSQ/+By6WauvPvyHTtXf0W/z1ivBYZdab8mSVNXRpzsDllKS\n58rlciktdb5+8HxuELFPx3n20Ge+zS4jabaUNFv2jOWyz03R6tlztHTRAlV88aUGBgeVvfhZqatj\nnHgiTeiTg/z8fJ09e9Z/T0FpaalOnDght9utwsLCkLc3HsMaY/BSXV2d5O5R1ornNP6btp5QFsg+\nAYUX4raCrS+QbzYiMb5wtBWt9Um1dfXyer1avWrlhPs+XGZ1f+/rAr7vGe45MH3jP20OyTVP/QMe\nxcU5ZLPZZFmW2tvvqbmlWU3NLeof6FdSYpJezNs6fBM051ls1zeeSI89UuqLpNgjNb7xRMrfMdLr\ne3ptWZak/m4N9Lt17vwFtXfckyXJEefUQEeblg92Sd2dut7QqMWueG1amaWy+matzX9Vq7fnhz2+\nwI6fzL6j2xrZyxryquyTT/V6brZvDZbBft/IAbtTcibodx8c1+5fvjXqG/NIZTXVBnWckZEd4kjC\nY4LkoHs4OQCin2VZ+vj4Cb3+s58GfbzueySbXYZp82//81/eV3pamrxer0zTVEpyshYuSNeC9HTF\nxcWFKnwAQJSzLEvyeiWbTR6PR263W3PmzPGVuXtVd+WSqq/d0qu7d8rlck1QW3SwPH1qrK/XF9Xn\ntf2FLUpPne/bPjQkyxGvzyrOqn9gQM8kJChr/aboSA6ag0wOFkZHcjDJRdCA6HX5ylUtXbw46ONH\nhkM9KmPBQr2Yt00JCYEuOAVg5pjMt7GIdYZh+O5Zk+R0OkdNq20kJCo7d4uyc7dMV3jhYXeqzzLl\niH9GnV09Sk9N9Q0ttsfp4uVvtWpltlY8l6m6+mvTHSmGTTCVaejHVAHTpe7aNW3auCHk9fYP9JMY\nABgDiQFmNsO0afXadSrYt1/9tnhV1lyVkTBLhsOp201Nmj9vZPalaLrmNIJ8RIfQL/EGRCi7feod\nZW1t7ers7By17e53bf65iAEAmKzTlWf0z1P/Ul/fg8kvWlvv6vyFmlHTW0aT9vYOvfve+7p2/YYk\nybKGtOa5ZWptapI15NW3tXVKS031D6uKKmFYBC2STHC1xDceiA3d3d1KSkycUh2WZans+AllLlum\nru4u2Ww2eb1e7dmZ75+LGACAyfq+s1N7dr6iM/85K3e/W6ZpKj0tTRkLF+jkqXLt/flr0x3ipJ08\nVa633izRn/5wSF963TK776m3t0+/2JajtpN/14X6Zu3/9W8eOiKKrjmj6EI/GNxzgBnhm8tXtG7N\nminVYRiGFqSnacePXwxRVAAASIsXLdKt23e065WXHyu7cPHraYhoaj4vP63cTRtlGIZ+VbxP5r0W\nlX30oQryntfH/z2vhanzVLjz8ecaPWZ0chDbTx4zR3tHh1ZkZuq9v/5N23+0TUuXLAmqHtM0deyT\nT9Vx73vtfuVlPZuREeJIAQAzzebcHB375FNlZ60Ytb2lpVX2Jy7YGbmuflureSnJWrXSNzOPY+58\nXb17T2lbd2n25ly9+VKhZB89659PFF1zxnjPAWMhMGN8VV2t4n0FU/oW5ie7dmr50qWal5Ks5pbW\nEEYHAJjJ4uLiRt1zMDg4qC/PndPunfnTGNXkNN66pat1ddq0cb1/kNCdpiZdb2hQ3tYXZMQ5fY/H\nEoNoE9s3JI+bjtZdq1dUjQEDnshQzdffaGjIks1mU7wzPqgp0yzLUnlFpRZlLNSaVaskianXAEQA\npkuNBcuXLdXv//iuXnt1j/rcffrs5Ody2O1R8Tnj9Q7p32cqFG+36YdrslT3RaVkd+pGa5tutnyn\nHS+9NOHzaLjZqGWr1j6dgKcqxnsOxlwETRpeCA0AAAAIs8zMTNlskd+rYLU1BnWcMT+4Ic1P27jJ\nAQAAAIAHrLZbQR1nzA9+IdanKbrucgEAAACmkRHjw4pIDgAAAIBAxXhywGxFAAAAACTRcwAAAABM\nQmz3HJAcAAAAAIGK8WFFJAcAAABAoEgOAAAAAPiQHAAAAACQ6DkAAAAAMCy2cwOSAwAAACBwsZ0d\nkBwAAAAAgWJYEQAAAABJJAcAAAAARpAcAAAAAJBivufAnO4AAAAAgJnMsiwdOHBARUVFeuONN3T7\n9u1R5adPn1ZBQYGKiop09OjRsMZCzwEAAAAQqDD0HJSXl8vj8ejw4cO6ePGiSktLdejQIUnS/fv3\n9fbbb+vYsWNyOp0qLi7Wjh07lJycHPI4JHoOAAAAgEkwgnyMrbq6Wnl5eZKkDRs26NKlS/6y69ev\na8mSJUpKSpLD4VBubq6qqqpC/aT86DkAAAAAApU4J+RV9vT0aNasWf7f7Xa7hoaGZJrmY2WJiYnq\n7u4OeQwj6DkAAAAAplFSUpJ6e3v9v48kBiNlPT09/rLe3l65XK6wxUJyAAAAAEyjnJwcnTlzRpJU\nU1OjrKwsf1lmZqYaGxvV1dUlj8ejqqoqbdy4MWyxGJZlWWGrHQAAAMC4LMvSwYMHVVtbK0kqLS3V\n5cuX5Xa7VVhYqMrKSr3zzjuyLEsFBQUqLi4OWywkBwAAAAAkMawIAAAAwDCSAwAAAACSSA4AAAAA\nDCM5AAAAACCJ5AAAAADAMJIDAAAAAJJIDgAAAAAM+z/MwGRA/exqLQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x49c6f9850>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "createTweetHeatmap(latLonPopulatedShooting)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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7LLpnAceOH+fy1asAlI4fz/33LU2akW3H6/XwwOpVKfcBhEIhTpw6zZGvvsKy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\n6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9j+8v9Q43RhUARZaXamlmg7WWLkPSi5PZuESdRw4MODnP7sDI89srwVn+/KRTw/eIYK\nl4cb9W7MikKqyUCu1YzhkS9hHDUuuCCOnCY+FImI5D3XfnwdiUSXPWlnbeFTqyvg0snghT0HaVHb\nOgR3vp2tXb+B++9bHHj/2po3eOiBpe3SV9fi68i+ouc7dfoM2FK7xOSg/tEZMbWzvrIrnmK0GyLk\nFW+Y0XXUClq0fNHMYCPxNZTFY8Wr83WRnp7O+LFjGDNqJJu3bcfj8TBz+jQcDoc/q7BXcwRWDGAy\naTkQmp2BjV4XjQ/p8dGtktmNeUuXIZ01UFelRR6yObRQrUJ7WG/0e9DajBszmnFjRgfpC5SsXAzz\nHyC77AZZN64ia6oQ2XmIvB6I1HSw2LVVPX/UJED7X1OJtNjAoOmptWNPR64aJZadtQ9fW3UR7xU5\nvf2GQ7zHM70yJe2sve1MImnMYu/V/jfsOiqKv5YAmx2y88HtAk+9FiTCYtVy04QcO5N2FrleaxgD\nO72R+LqOnUWvs3jIHgrtbWddAF3A5+C73/1u0Os/+clPIraNMDmA1l9WqC8vXL1Qr2PtVy9fuHp6\n+dqTo/11YTAYWLRgPl6vl13vvk/11QsoXjejSgfRs3u3xoqKAj0GNN7LUfULUqpNHprjo1vFmgJF\no1r0ofeMbmtdCKsN0wNPNtZQ1SB5HUB63HD9XKvrAGR0g9SMMDLolenOsrP48rX1M8bKF+56Iug2\naWfx5YuTnbmc4KwKLpo9S1t8QaIYzZDXq7F1i13P6GQPhaSdBatnNBriyheeIzme6ePTK3uCogv4\nHIwb13gawuv1smPHDvr166errY7JATTO6ILN7EKVhZstB6sT7lpH8zX9TIQpa3mdMGXtIbv+WbnR\naGT2zHuQPi/S62Hvnj3s/XQv3Xv0YNz4cVhSUkEIrl+/yd4DWka9tNQ0pk6ehNlsCvBJKTWHYVX1\n+wb4QDHw0mtrmT9zBmr5VW1lzO2krraO8joXmTm5eCx2srrnR9BFeDvTJgbx022wiQEIMJmhez//\n7kq9tsNi9q/wGUwh+ZJ2ppcvWJ1YxxjClLVFF505nunRRax8xNDXnWpnLfuK0c4sNi3HjOoDn0cb\nG40Nu7EtfZUa2wV/tkg0O4vmu+88O9N+l+pAlfzvn1ei+nxacAtF4d19H5KVmYsAu6AAACAASURB\nVBlBvmB9hrsWSb742Jn0ujX/FLXJbrZi9GcgtyCaJTuNl+zx5ovlu098RBsatDNw//33N3u/bNky\nVqxYoatthMlBS8MO9uWFKpMhXoeqE03d9uaL1+dtMPj2kj3UQBqaTxgMCIOByffMRAK3ym6xY88B\nXC4XQgiyMjNZsuhehFC4fbuSdRvfpGhAf4YPG9pIU18LUg28VT0uPM4admx5E6OrDpPRiBDazZOf\nm83xw4cwFvTn5nt7mTJpAj0LCgLyRP5ckcrir1sB2o+70QQWW7MhPha+0HXuXDuL3Hei66IzxzM9\nuog3n56ypJ0F04WAxlwvJnM7jhfx5ov3eBsvO9PTV4vrPg84awDIdqSyaM494HZy+ep1DIqBKVOn\nRJAhXD+dqFt3fSB6XyPc2r90W4vriWZnLccLvWNMEu2FM2fOcOPGDV11dewcxGPVKNYVvs5YQQvG\nF4vs4drEyhfqemy6EEhycnK4d/78oHKkp6fz0ANL2b1vP/v27WPcsFKoq0E6qxBmi7ZaZjCgGM18\n6ckntOM4zmrwuLStdqn6V9ytkJmHkpLOu++/z+Ejx1g4f2476CIedgZaxCQVvB4tAonXizCbtcgj\nRlOT6E9JO4vMF0S3UgWv178q5kYYzf5dGWMbdRvu84Yr6xw7028XSTuLzNeRuoVwuhBJO2uD7KF4\nI/AJA5hTQPWhAj5VxaCqHDl0iGmjh6PevIywO8CSAgZD4JtKeDszmrVrqk/zhRNoOweKodG3Ja73\nXGfbWRdCF/A5GDx4MEKIQHbkrKwsvvnNb+pqq8MhOdigGOx1qDqR2ugpC9aPnr47ik9v+/bg01s3\ndl1M7JHOgTdf5529m5lWOqBZDTF+IaRlIYQ/JV5GrlauqiBVLRxoE95pUybz+hvropAvlIzRtolC\nF+561OP7m2VtDtwJvUowZPeIji+szNHIp7d9e/DprRtBFz4v8uxhzbm8ZYtufRBZ3aPjiyiPXvnC\ncSbHs9jaJOZ41na+SG2iLYs3391nZ8JggBQtIt+sBYv44799D3NdFZOKenNy4wmG9+qhtXJkocx5\nFO1MVyLpInhbYbZqC2yghcxFtDjOEu97rrPtLNz9lljoCseKTpw4EXPbOPgctKzTVj49fUXTdyx8\nevrqCL626CJefCDy+zHu0a9x/PAhVh3Yz+z+3cnOzkSYzMgzh5D2DIQtBRy5CJMZvC5/HG8VaTRr\n5/Rtdm2FGPB4vKF60iFfB+jCbEUMHA1uf8bTq+eg3qmt3hzdiy/FgbCnQ0YOonsvf5jTpJ3pKjMY\nEb0GI1312jGA2kpIy9bsw9Jym7wt8sUqe8s6beW708ezcKuJiTmexdZXe/FpZdLn0ybMqk/zdRLC\nH+3IACaL3z+q8+xM+rzI8qvgrEY66zQ5bXaExQ5Z3VFC3rttkS82vrQ0B3Of/Crbtm2l78yprHnt\nNS5cdeG1pZGVks4MKTGEjDjX8XYmpdR82/z5fVBV7Xs3GMBoDiywtQ7GEY18d8t41oFox52DTz75\nhJ/+9Ke8/PLLza4fPnyYf//3fwcgJyeH559/HrPZHJLH6XTywgsvsHfvXnw+HxMmTODZZ59tkRAw\nOOLgc4COslB1o5nB6uGLtq9Y0JF8bdFFvPhAmMyIjBxKp81m0MRpvPe7n3P71FlcHi/52RmU9s4n\n3Z4C2T0Q/p2DRtRq/yy9Afj80iUGDgiVOyMx7EwAIiUVUlIhIw/f2U/h1pXGChU3tFYmC2LBUzr6\nigV3pp0JAEuKlhXbkYWkl47N5M7QbXI8i669Hr7EGM9i66u9+PxlrjrNoTYYTLnN63aCnclr55EX\nP21epdL/WJeWqTll6+qrY8YzS0YWqj2d9SevYhg6mZ49C+hdWIiiKPzP7/+Xv/ryF6PiC10WC1rw\nuZ3acdxgSM2Kni9sHT3ozPEs8VfjA2innYPf/e53rFu3Drvd3qrse9/7Hr/61a8oLCxk9erVXLly\nhT59+oTk+tGPfoTNZuNf//VfAXj11Vf5/ve/z/PPPx9Rjhh8DvTUTdRVo7byhVol6wqyx4fPYDQy\nbcY94KqFuhquXLvGB2evUuMDg/0Ghy9eY/6UCYwtLQKpBmJ946xFCoWzZ88xrKlzc6s+20/2WPlE\nTgHSYICa21q+BZMF7OmQmo70+YJEPUramV6+4Oez9fBF31ei66Lzx7P27CvR+Tr+npMAPh/S60K6\n6hA+j3aGvOGIpmLU3ssE0G1qppajob4W6mvAp4I1Bax2fxSdxLKzjVu2UpCfz7XrN/jSU0/wwcGP\n2LB5M3179yYnO5vy8gqysrJ088VPviB2ppi0o0M+f44dZKNfQcjv/k6454LxdR2Idto56N27Ny++\n+CLf+c53ml0/d+4cGRkZ/OEPf+D06dPMmDEj7MQA4NixY6xfvz7w/nvf+x4LFy7UJUcMPgeR6jf9\nr7esq/C1LNNTN1Fkjw+fEAqGYi12rvR5KairpmeKIxBSLW/ffi5dv87Y7n3h2rnGEGzVZVBdRjec\nXD97ioxR41oMBfGRXVV9KIoStCwWPpAoxaO1V6qKrC5H2FK1s6Ax8oUua1kn1Pt49tVV+TqyrzuV\nryvLHm++jr/n1LNH4PbNQN1Ai7QsRN+hWlLKoLljIiH+ulXSsyE9W5Pb5QSvB5GSplO+jpf96ccf\n48+rXiUrU8tJM3b0KMaOHsXRY59y7sIF3tj4Jv369GbggP4U5Od3oHyt7UyYTGBK1941hAhvlmwz\nUe6RjuCLpn4no512DubMmcPly5dbXa+oqODQoUN8//vfp7CwkK997WsMGTKE8ePHh+SSUlJVVaUl\nvwWqqqowNAt/Gxo6fQ7CIZqZYVvadAZvtHyR6sebryPRWhZhMGpbyn5IKZk4ahhHDn3MlnVrmT9x\nNEhFG+wEYE3ldFkN00pHBeWLtv+WOHvuPO/v2YvbVc8XH1hEZdl1Ll64yLDSEm1lJsWBMJoa40ZL\nVTvXKZqe6w0jgaIg0nNikD0SknbWiK6jC6mqWmQu2RBJRNFW+4yhMmlHi8SyM+1stNufRbzJuXij\nEQxmHZ+3LZ8nsXQRDz7RvQ8yIwdqKrVJgs0B6bkIW6pmP1GwtQ3Rya5YbM2OEUmpNrGLWO6DeOtW\nS/45f85s9h440Oz6kNISSkuK2b5jJznZ2bzz3m6WP3i/P6NybH2FR3R8omGnPU58XXtsT3B0cLSi\njIwMevXqRd++fQGYOnUqR48eDTs5ePrpp1m2bBkzZ84E4O233+arX/2qrv50+hyEQyxfdnsZSLx5\no+WLVD/efB0JHbLUVMLtGwzNz0bUVPLO3v1MH+fPcJxTiLCk4BIG0rNz9PHp7N/n87Fx8xbSHQ4W\nL1zA+pd+B1fPsHnLThRFobfDQorVgslqg9yezRt7Gl44dJybjSxLbEjaWSO6kC5qK7X46i2hGMCR\nE2W/bZSlXfha1HdWB4m57ocjV8dKWls+T4LpIg58SkqaFmEnqwdSHRRxcaL90Ebd1lVrDrXBkJ4X\nh/5jky8vL5cli+7l5VdWYbVasVotTJ8yGYfDwdjRo9i8bTvTpkzi0OEjjBk1sk19hUbn21niQI8s\nXedoUXtHK2oIP9qAwsJC6urq+PzzzyksLOTgwYMsW7YsLMeDDz7I0KFD+eCDD1BVlRdeeIGioiJd\n/cdh5yAYwp1BS1S+eNZvT77O1kUYmMzaGVSPmyFF/Tl59gKb3t3LwpnTtbj2JhW3p+XDVHT9S6ni\nrXeyZftb3LhVTk5OLm6Pl/lzZpNqs/Dcv/0Hc4f0Y+3OPVjMZuZOGMXBE59x+cp1hvcuZPBQI8Lh\nQEmxafF/G4hdTm3FxqCd9RSgReior0N6PShmK1is/shEepG0s/i0jQdfO+jCYNJe+ryN5Q3nxGPh\nS/TxzGDU4q77vASSIDZE1IkZna2LePPF1n/zaERt5wvdth10azCCDGYXfn+JuD1ERZb9N7/7PU89\ntgKbzaY9XKkq6akp3Dt/Hh8dOcaVa9c5feYs7+/Zi9VqZe/+D6ipqWkyOYifLO3Ll+h2cYftEgRD\nO+8cNEw+Nm7ciNPp5KGHHuK5554L5CkYOXIk06dPD8tx8uRJfvOb3/Dzn/+cM2fO8L3vfY8f//jH\n9OvXL3L/suX0xI9Tp06Bs5qigQOi/UxJ3OXQUtnXI6tv8eJLq/jGF58IlG3Z+R4TJk0mo1uPqNcI\nfJdO475+gT9veptH5kzBZrFoW9iWNCi/BreusOGDo9S63DwyaQQYjNRfuY1z1258V6/xWlklBWYj\nEoEzKwvbA0uZN3kUNrP2kLfvyHFuVlYhjWbUWzf4+JNPGJCbSZrVjE+VPDBpFIybi6FHn/gpK4ku\nD6mqWhhKxRCn40SJjcDxIgWdx4mSuBsQOF6kKGAwdbhdlJXdYsv2t+jXtw8Ti/trO3uqjzfeegez\nyciHR45TUefCa7LwtS88zZ79Bxg+dAhjR4/SfQ47ifbFqdOfgS1N9+p2Z8L7N4tjamf81YY4SxIa\ny5cv5xvf+AbTpk0DYPfu3bzwwgusXLkyYtt22jm4U3AXzH7bAUII7YiOkkt+YS/q3V4qKsrplmZj\n1qBCXvq//8WT9y/C6MhG5ORr/gBet7bypPq0HxfFBKbmDx7Ckc3Hx06wYOZ0bBaj1i6rB8JsA0cm\nano2lXsO0xj1V2CwgHX4YDwZqTxw6ixOgwnzpMlkjRuPcfhw3tixA4vXhbu2hm55OSxecj9YbBzY\ns5vM7vl8uOd98rMcVGCBwWMQ/kQ7SSQhVRVZUwHV5cj6Oi3Hhz1dOzduNHW2eO0GIQSYLc2uSSnB\n5wZv03vY6L+HO+u4TBIdCSGUQMKujoaqqry8chXpqSmMGNRP8wMyWcFTz9TRIzCYTNSoBnK7def8\ntZsMHVLK/g8PIoRIsIlB8pmjy6ALLIo4nc7AxABg8uTJusKYQlx8Du5kJG/StkCYLBQPGcZ/r97A\nxY8P8Hdzx5GXbufhob358x//yPIpo7Da7IgR0wLRjs5e+JxPT33GnGmTsaQ6kPb0gBUqjizKvAYm\nTp6nTSSaRfOAG4ZUes1fjmf/Nm6V3SI7NQWTVcHUJxdbn1zSFs3CMPdRLTqEHw8/+QUtRoLXizA0\n8k1YuJR9Bz6gmyGV8856HnrwfgwZGR2luiS6ANRP90B1eeB9w2ghUxwow6bfXSvqNRXB/S8MJmRa\n1l3/SxINtm7fQU5ONqNHjuhsUboEVFXljy//CYOnnqeXPogQ/qNNJhOYTGRn9WDVhi3c98AyDnx4\nkAVzZgPw5aefZNe773Hok8OMGD6sEz9BU9ztzxzJkSKeyMrKYuXKldx3330AbNq0iezsbF1tk0s6\nSbQrigcP4pmvfJF/++unOH6tjA0fHCPFYmbFtLGs2n2IMqcbPG7OXPic1zdt4/MrVykZ2J+t7+5m\n9YY3OXzkKKCtTL625g1SU1NpjP3cfCjt1r0b5y9e4GxFDdl53Wk20FjtiNR0LTpRE0jQImyoXs0v\noskpu/HjxvLEikf44lOPs37T5rt+2E6iBcw2sDTPNCkRyDon8nY50uPuJME6AYrS2vdABLmWREQ4\n650YFIX39+ztbFESHm63m9/87vfcrqrhC48ub+0T5o/+c9/C+fz5L69RVV1Njx7dAaitreXylauY\nTCa279jZCdIn0aUhRGx/HYif/OQn7Nq1iylTpjBz5kx27drFc889p6utjjwHSSQRG3xnjsDVs1BX\nhQJMH9SbVe99iDTbMKXbmTtjCgfPfY7zs1fokZPF0pHDWXXgU7CmcsvpZcVDD3L46DHWv7mZiooK\n7p01jWy7FW7faOxEKEiTFZDgcfH04jmI++b6cxJUQE0NIjMHkVfY6qiH7+YlKL+qJTbDb+1Gsz/T\nczeEpx6kigKkGyXrX1vF5GkzyOnWvYM0mEQiw1A0GilVZE0Vvn3bUQ/uR148rx2t4beaA/uQUZge\n+yuUVEdni9uuEPYM/9EirxYqWDG0OhaYRGRUV1eTak9lxPBhbNy8hYqKSjIzkzuWofDTX/yK3oWF\nPPLQgxgMhiZhVdVmoVTtZnjqsRXsevd9ampqEELw0iurmDhuLKUlxXx29mxnf5QkgC71zNlp0cUi\nw+VyYbFYyM/P57e//W3YOqGQ9DlIov1gs0NGnhb+0OsBo4l5Cxay9sRFzlw+xsC8THJsNuaNH4kb\nhd9s2sXS5Svo2bsPk9xuXvjNf/PNZ74RoJPues03wVMPUmrRhG6Xa5mLFQH2dIQjCwwGLQdDXiH0\ntCFCRY9pyHTcwCsU7b3Z1hin2+MGJIvnzgKTlW3v7cPlPci98+c1iY2dRCJBe0Bw+WOui0CUnXAP\nqoEHW59He7BQGnNfSFXVMoK76zUbMVvBYkMIRftLy0AOHAleBdWjIi+dQ4tjn4/Sqz93ywatEEK7\nZ+5gf4v2hJQqe/fsYdLokcj6GhbcM501m7by0ANLO1u0hISUkgVzZjNyxPDAtVB+Dx99fIjTZ84y\neeJ41m3cRGZGBl966gnMZrO/XXISm0SUSGCb+bu/+zumTp3KwoULtdMWTVBTU8O6devYs2cPL774\nYkiOpM9BEu0GQ34/yO+HVMcjvW6E0USOYuChSf6HMSHYv28///3BYR5YsoSUvEvkdu8BgNlspldh\nYTM+YbaC2YrEgXr8AHx+ulV8bWmxwaTFWvbOSPJl5EJGLrJgoN+HQWmxLZ2irWOoqpYADZg/fx61\ntbW8/MoqnnxsRYI5syUh66r8icnU5gWKgkzNDhpLXnpcWgx/1de8wCmQXrc2KWhZphiReb0Cu1GG\nPgMw9BmAnP8AuFyA1HYOEvgHJInEgayvAZcTu6LirLqF3ShRAKvqoq62hhR7akSOuw1CiGYTg1Co\nqqri2vUbPPTAUj44+BFWq4X5c2ejJPDK792LLjReJvDY/otf/IKVK1eybNkyHA4H3bt3x2AwcPny\nZSorK3nyySf5xS9+EZYjufSZRLtDKIr2YN/0WoPj74TxjBkzmt+/9Ce6d8vD1MRZuLR4MLvefY8Z\n06YGIw2+red3Um5520rw+yoALcoDK57BZIdW/djtdpY9sJRNW7exaME8EEpXGtK6NBomaw3nN1vp\nPeQXEbxAi4XuQ/of/kWzMlXLf6GqIFowhPhhEEKAtXMitiTRxSGgT2EB5z+/TE5WFgDd8nIpr6hI\nTg7agLd27iLFlsKadRvo16c3o0eOYPvbu5g76x5c9fW8unYd3XJzcTqd2Gx6E2EmcdcjgScHiqLw\n2GOP8dhjj3HixAnOnz+Poij06tWLwYMH6+JI+hwk0ekwGo189YtPt7pePHgQVdXVfHbmLAP699OO\nFXnqweNG6V6IzMtHVlVC7W2wpCCyeyDSc5qtDkuv5vCM29kkQY+CNGnOpNFmJZVeD3hcpKr1eG7f\nYtv6tcydMQ1ptvr5kjsJ7QHpcWk7Ak13BRSDpndrauDBXdgcSKs/Dr/Po00im5w9boBaW6VF2Kkq\n0468ARiMyBQH8nYF3LoK1z/XdpSEAhnZyB59UPoUa07I5uSuQBLxg7CmIi12uvdNZd+RE4yxpYLB\nxLXqesYW9IxMcJfhyNFjHD56DCEEK5YvC3svTp00iXpXPYU9eyKlyvp165g7eSLcvsEb6zaRl+7g\n83OfYb1nWkiOJDoKXeiZM8F3nqqqqti5cyfXr19HCEFeXh5Z/kUHPUjsT5fEXY9xY0Zz7NNPkS4n\n1FdrD4f+AUQoBpSsPJQBw7W/zLzWD/tSajGvmw46UrY+dqIXEq2tVLl/wRwG9u3N6g2bUb1eALxe\nL1evXqOs7BZSSqTHjaypQFaXI93OVinRk9CJgN5bfo+t9SmEQJgtCFsqwpqCMDYmZJJSIt0ucFZB\nfY0/u7GfzuNCll3RnOjLrzWWSRV8KqSkgyMbYbE18qk+1MqbqJdOo978/O6KUJREXCGEwGCxYUpJ\n5fDJs7yxaSsmY8cnE0t01NXV8emJkzz2yHJmTJvCnn37w9bPzc2hsKd/giVh1pTJ/GXdelRVZVjJ\nILrlZNO7IL8DJE/ijkICRyvavn07Dz74IAcOHKCuro7a2loOHDjAihUr2LBBXxK2CBmSayga2D+u\nQieRhF5Ir4easqvsfHcPi+fe01ggFLDaNcfhYEdLgnGBdjwENN+CtsrWhK+88jZ79u1DSkldnZP+\n/fpSf7ucsksXkT4PuZkZTBw5VPNPMJohswfCkjx6EgsajxUR9XEuWVOhPfA3mRhKQNbchkufgbde\nc2JugMEIhYNRevQLGnnHd/IDbffB3cTvxWACezpKycTkQ10SMcHn83Hy1GmKBw/qcBuqr6/HYrEk\nrO3eulXOm1u28tgjy/3RiSRvbtmKy+WitLiYwYP0ZdYtr6hkx85d3Lh5k6WL7yU/Pz95NDQBcOr0\nGbCldo0Myf/wSEztjP+2Ks6StMb8+fN55ZVXWu0UlJeX89hjj7F58+aIHEmfgyQSEtpDoA/p9ZJi\na/4gLVUV3G6ESf/RjmC+A21BU77srEwWL1zQXMaaShjcG1SVG7fKWb31bYr79WHY4CK61NZpgqFN\n36N/x6cln2Zr3uYTA9Ac0e0OhDlEuDevG9yu5td8Hu3P73CfxN2FgG+TzkWLYDAYDJQU6zsXHG88\n///9kuFDhwDaTkZ9vYv771uUEJHZ3t29h8rKSh5/9BEU/70lhGDRgvl4vV62bH+L21VVjB87JiJX\nVmYGDz2wFCllwk6EkkhwJLDdCCFIS0trdd1ut+sOopL0OUgioSC9Hm111+0En4e0VDvVtbUgFNTz\np5E3LsPJw3D7FtgdiJIx0HcwysAhCbXyI1IzkClpUF9LXloWD/fuz/5PjvHW8QvMLhjY2eLdnUjN\nagxX6vNpkwyjESU9D3r0Q1begOpKLbKWLRUy8xC21gNsA5SSSci6aqi6iayt1mYalhRESpp2zWgG\nkzUQEjWJOxPS59Mmil43eF3a5EAxIM02MFkD2d+7AooHDWLyhAlkZ2srjk6nkz+vepUnH1vRKQ/R\nUlWRbhevvv46E0aUMrW0P1Tf0nyNTLaAbt/Y8Cbdu+UxSkf0oqZITgwSDV3omTOBx/SHHnqIhx9+\nmDlz5pCbmwtAWVkZ27ZtY9myZbo4EvfTJXF3wufVYsr7NCdRl8t/hlsxQuUt+PSgNjEAqK1CHt6r\nOY4m4JgiFAMixYFIz0Vk5DFh+j2YLFbe3vVuZ4t2V0IIofkf+B/ghdWOMGpHKITBiJKdj9KnBMOA\nESgFA1BSHGEfHoQQKHYHSo/+KL0Go+QWoqSmN04EvG5w1XXQp0ui0yB9/kAJ9Y0+MKpPW+AgRt+m\nTsKDS+9j87btVFVpiSFtNhuLFy7gz6teRVVVpM+HWn4N9fpFLUhAe0P1seHNjcyaOLrRL6BBt/5d\nwN179wEwZtTIZtHukkiiXZHAPgdf/OIX+eEPf4jP5+Pw4cMcPnwYr9fLD37wA55++mldHHepz0Hg\nMEE71b+b0XbdBrbmpYqUkhd++3/5m69/TaupquCsQ9bXasc9bKmIBNjyDo7gujj26XEASkuKddVP\nIhgS7x5uardal0qbjpfoR+Lp4s6Bfl01HIXUmnXUdx9/qKrKX1avYeL4sfTp3RuAirMnWbvyTzw8\nZQTWhgmPwaSNv/2Ho2TkBmFqu53t3X+AVLudIUNK/T5eKghDQLdnz53n+o0bTBw/rk39dD6S9zB0\nMZ+Df3o8pnbGf/lTnCVpH9ylOwfR3lR33k3Yfmi7bgX+VV7FwMeHjzJz+tTGUJWKgrCnomR3Q6Rl\nJPDEAELporSkmFOffaa7fhLBkHj3cFO7FSHybbQPEk8Xdw7060rzke/o7z7+UBSFFcuX8dmZc5w4\neQqAdLPCoxNLeWPXXi6VlWsVfR7NIV+IEFqK3c7KyyvYvHU7UkqGDin161ZBKMZmut29d98dMDGA\n5D3cBZHAOwfxQNLnIImEhM/nY9PWbQCtnH3vBEgpk85wSSSRRMJi9swZrHx1NYOKBiIKBmDOzGPF\nwNGsXPsGC7oXkp6RARarlivEXY+0pYLZFtqBXwe2bt+Bs95JdlYWE8ePJSMjI2z98WPHsHvvPiZP\nnBBzn0kkErrQM2cC/3YvWrQIp9PZ6nrDM8eOHTsiciTysmsSdzG2bt/BzOnTsNvtnS1Ku2BISQmf\nHj8R5GhREkkkkURiYMHc2fxp5V9YtGA+mZkZYE9nxTe+xf/+14v0zsvCaDQwdmgxNiGQ9dVIYUBk\ndUfY0nQtfEgpUVU1EJbUWe9k6eJFuuUrGjiAgx8fYtKE+C20HPrkMCOGD4sLVxJ3LhI5yMTPfvYz\nvvKVr/Cf//mf9OjRIyaOCJODaG+2hnNwwc7DxXJGTg9fW3ij7SuWPu40XcSbr/U1j8fD8ZMnWTh/\nboQ+uq5uiwYOZM26dVTX1DBh3Ngw9fX20XV1cffcw+Ha3m26SNpZdHydo4uMjAweX/Ewr/zlNRYt\nmE96ugNFUXjq//lrnLW1uOvref3Pf2B6/3wKHFZwOZGKQdtFSHEgSsajWGxBuaWU/HnVq9hsWkhq\nKSVjRo3SIXtzWCxmbt4sIy8vnN9D67aXLl8hLdVOenpGoOzK1au88upq6pxOxowaidlsDqGZzv6u\n7iw7a96uiyCBdw4GDRrEN7/5TV566SV++ctfxsRxlzokJ5GoUFWVLdveIicnm7FjRneloSImrH9z\nE/fdu7CzxUgiCYCwR90afuqjLUui68Pn8/HGho08uHRJ67JDu1i9dj2zhg8iMzWlWZky8xGEsXUE\nIQns3PUOpcXFdOuW1ybZpJSsf3MTA/r1C+zE1tfXs3b9RjLS05kyaUKrmO8733mXU5+doWTwIKZO\nnhS4vnHzFhbMnUNZ2S0+OvQJC+bNaZNsSUSHruSQ7PvRF2NqZ/je7+MsSWjU1NSQmpoaU1udPged\nsYKW6Hyx9BWuPKmLo8eO8+mnx5g9aRwZViPy7BGk0QSpmWC1IaypMW7lmCshbQAAIABJREFUdbYu\nguO93Xvo16dPDHyh+tDTd9LO7ozxLH4rfLKuCllVgbx9Ey6fAYsduvdCOLIR6dlaM3/CN2kyg9GM\nRGjnzF21UF0OdTWQlYewObTwvSZLGNljQWfr9u62M4PBgKIoyIbkfj4P+FTNLgr68+Bjj/Py2g08\nPmsSisWm5QdJz24SC14gfV4tmpPPA24nNbdukJcxTsttYzTFNLmUEl59fS0pKTaO+Y9plpdXsHHz\nFh59+CFcLhcHPjxITW1tkzaSPr16kZVZ3mxiAKCqEkVR6NYtD6/PG0Y/epG0M318Df9j5e4EJPDO\nQQNinRiAbp8D2eJ/sLJY0JX5YukrXHlSF5evXGHuyGIcVVegyn/RBdRWajfigNExJh7pbF20xuUr\nVyivqPD/OMVLt3r6TtpZOD7pcYGzFtIyYjjD3Nm6iI1PPfkxnD0MTTeRr55FGowwfWnzCbnbCW4n\n8vYtuHkJmib4unpO66H/SIQp2HGMpJ3p54u1r3jzNZaNHjmC9/fsZcqkiVB7OxC2VTGZIa+A+1c8\nxur3DjB2wgQG9O/Xms9VB+7GvB/S5wGnf6BPz4vqYUv6QwbvPfAhkyeOp2dBQaBs61s7MBgMbNq6\nrXFC09AGbXf6/MWLPLj0vla8/fr0Zt+BDzh1+rMm/mBJO2t/vi40KWhAAvscNGD69OncuHEDh8OB\nlJLq6mocDgc9e/bkX/7lXyguDu3zqMPnoOVsr+n7cGXBuILNbmPlC1VHD1+sK/ixfN5wZV1NF7Hy\nRS6TEm5XVZE+YJaWvdbnQXrcgECYzVpM7SarUF1dtwX5BRw/cYr1b25CCIHL5Wb82DEU9iyIUr6u\nr4v421m4PlrzqeU3kO++qT3wVtwApxMysiErD2XEJJRBwbKutkW3HaGLUHyt2ykjpsKQicj6Wqj3\nr7CmOBBWm5Z8EAmqD/XCcbhyHuqqtT8BWFO0LNAl4xAZOdqOgcEYpO+knXV1XfQq7MW58xf46NAn\njBo5AqSq5R5QfaAYSE/PZcQYldrAKn0LOVLSwJba2MaahkzLRhiMrfoKJbN0Vmm/D6oPVC9ll84z\ncUiRlqk8JQ2P28Pnly5z/32LGDigfwS+1n2WFA/mb771HX70T/+vP0t0cF0cPnKMnJws8oM6e8ai\n96Sdae9FBPkSCF1g52Ds2LHMnz+f2bNnA/DOO++wZcsWnnjiCX74wx+yatWqkG117By0/NKlzrJQ\nPPHi09MmVJkeOfW0i5YnGr5odRHsBo23LmLlk/4hJLRu9x04wNjRI7WhwWDQ/szWEEPFnWFns2fO\nCLyrqKhk13vvsfOdd3E40jAYDEwaP97/A5W0M3184X6owujixhXkkX3NL5ddhbKryJGTI8icqLoI\n1Ua71vR+FEKAyYQwZSDTMoLcc0J74L91Ha6db17k0TKYKxl52mQiatlD4Q60M11yhEJi6GL61Cm8\n+/5uzp49R/9+fcGgNJkMwuEjR5kyaUKrduB/7BMiML5PnDCBXe/tZuaM6WH6biGH1w2B4z5QWVmp\nXVNUBNpRzaWL7+XY8eMMHNCfqqrbfHDwY2rrarl1q5zU1FQeemBpyM+uKAoL583h5ZWr+D/f+Hqg\nzOl0snvvfuqcdXg8HkoGD+bS5Ssc+PAg9fUuFi+c3ySyXix6T9qZPvkSCF1gcnD69Gl++tOfBt5P\nnz6dX/ziF5SUlOByhc9wHoc8B5FmsLGtJHfMClqoMj184Xg6Y3Wg5fto9R5Knth1IasrkNWVyIob\nUHYFsnsgsvIQjmxITQ88nEgpOXLsUyaOH490OZF11cjqCii/pp1FzewGqRmI1HT/KlMoXYT6LA03\ncVttpv3szG5P4cbNMr76xacRQuD1etm9dx/lFRXYU+xMnzoZi8XSql1i2lk0feqRPRxatovmPvC/\n61+MsuhxZNl1ZPkNqK9DZOZAZi4iLT2Kz9KR91x0fFLKwGorXg+oPqTRDEZTY32fBzxupKKA0QyK\nEVlbDdUVyPLrcPkcqGix7Q0GSM/Rjl/Z05GBxFRJO4tOrmhWd8O1IYwcobhj0+20KZP5y+o19O/X\nrxXfw8se4P09+3hv914eeejBEJwa8vJyqdpfzeUrVynI76FPPmsq+Ly46+t4ff0mxo0dC1Y7KAak\nhKrqKooGzsBqtfA/f/gj2VmZzJ01k0uXr3DUfZzBRQMj6mLhvLnIuc0/s5SS8xcv8ujyZaSkNHe6\ndrvdbH97F/c2i67XlewsXs9uoeSJRhfR6KqT0QUmBw6Hg1WrVnHfffehqiobNmwgPT2dM2fOoKpq\n2LYRohVVUzRwQLsIncSdD9/rv4bqytYFpRMwjJ3Z7FJD1B7fx7vgwomgfMqCpxEWaztIqh9SqoDo\n0ORlNTU1rFm3gQVz55Cbm9Nh/SZx50C66sBZHbxQMWqThiBQt70GlTdbF/QfimHWsjhKmERXwslT\np6mrq2PkiGBH7mDt+g3cd+9CDE19UoJASslLf17JiuXLwoQNbY3NW7czferkVg/qTaO/+Xw+Kitv\ns/Pd98jNyWb61Cm6+YOhurqa/R8c5MLnF3n8kYebLNYEjzpXU1PD9rd3YjQa8fl8ZKSnM23KZJQu\ncFa9s3Dq9GdgS+sa0Yr+4+sxtTN859dxliQ0rl+/znPPPcfu3bsxGo1MmjSJ7373u2zdupXevXsz\nbdq0kG3bmAQt3AwRms9MoW0z2Fj49Mrekq9lX+3F15G60FsWP10oS76inWOurkTW1SBsqdpKo83u\nZ9fq+SpucuXMKU7us+Nzexg8arq2gunxNO4yWO1gCrZyHk9dBOeTNRXgrte2r70eUBSk0QJGIziy\nEUq4H8C26zY1NZUnHn2EV19fy333LuTY8eOUFg/GZktpwnH32ln78DV9fweMZ5YUMNv85729IFXN\nj0co2gqY38ETn1d7rxhBUVAe+BrSWavtHtRWI2x2cGQibGnN7uHwn7c9dJG0s860s0FFA1n12usM\nGzoUg0Fp1dfse+7hf/7wR0YMG8q4MaNDPhALoTBqxHAuX7lC3z59W8jXUvbG116fF5vN1qzs3Pnz\n9OjePcBtMBgQQmAyGZk+dWqMumh8nZaWxuyZ9+By1fPq62tJTU3lZlkZRQHfhka9v/X2Tupd9Sxe\nuACj0QRIyspusXb9BiwWC2NGjqRbt7wWi0xts7OGdd5Gzq5sZ0nEA926deNnP/sZZ8+exefzUVRU\nhNFo5IknnojYto1J0Fp+yTLC9VjLYuULh1Ac8eQLdiO0ly7i1ZdevnDwD1JGEyI1A1IzwvIprhru\nGVnKqdOfUVNXR3G/XmCxIjLyENnBHL462M6cNeBqDIWHijZREAqkB0u8o6ff6HQrhOB2VRXvvr+b\n0pLBvPPebupd9QDk5uQCEpfLRUZ6uuYs2GXsLFKbcGgfu239vmPsTPspbZ/xTABNz3u3ghBA8/Pj\ngHasLy0D0sLfw8FlTdpZZL6m77vW7+bihfNZs269/wx/8/Zpaal87Utf4Oq1a6xZt4Fl97fOj9DA\nV9izgHd376F3r16BZGitJxPNZVdVtclDsFa278CHrFiu7WYd+uQwe/Yf4Otf/TI9Cwo4cvQoQ4eU\nhuRrCq/Xw6at2wKyFBYUMHzYUL9MkqqqajweD0ajgZHDh5GTncWJk6e5cPECvXv14v09eyjsWcCg\nwBEmjT8nJ5sHly6hvr6eT44cZf+HH+L1esnv0YMJ48a2OKUSvZ39+r9/h9NZz5yZMxg+bGiYdoly\nDwdDpGfOBEIXOFZ05MgRnn32WTIyMlBVlbKyMl588UWGDw++49cUMeQ5aHmdJmWhvvj2nnF2FF/L\nspbXW/YVjD8eugjG15bvKtxNHG++ILKnZlI0dDiHz37OvbNmamdIDWYwWfzsnWxn9nQwW8Dj0SYF\nBoN2VttgBim1SUJUuogkX8sy7fpXv/h0oK4Wuk8rKyu7hRACi8XMjZtlrHrtdUaNGNEigWGi2llb\n5IvSztrUV7z5BBIJdTXI2tvIyjKordJ2ytKzEakZTY7QtVW38ZK9vXTbEeNPJPlaliXS2N4Wvva7\n5+x2OyOGDWX7jp3MmXVPK24hIL9HDwwGhYb0CMH6Sk/PoLCggE1btwOSW7fK6d2rkIrKSurrXYwe\nOYKeBQWkpNia8beU1WQyUV/vwmq1cv7iRQp79gS0EKyv/OU1hg4ZElQXJ0+d5uDHn2AyGRlaWsrp\nM2fISE/HbDZTW1vHtes3OfSnV5g3Zzb5PbqTk5NNz4ICHA4HY0drGZ379unD7r2ar0VBfg8GFRWF\n0C1YrTbGjx0T0OWly5dZs249QiiMHD6Mvn16E4udff2rX2HfgQ94fd16jn56nEceWuY/1tVZdhbL\nPaxnDEsQtOPk4JNPPuGnP/0pL7/8crPrGzdu5KWXXsJoNFJUVMQPfvCDsDzPPfccP//5zwOTgUOH\nDvHjH/+Y1atXR5QhijwHkX6Iw32podpFMqZwHJ3B13At3rroyrqNVBYOWj3VlsZra95g/PSZOPr0\njbKvcP3GRxciJQ1Ia3U9Vr7I8jVc02cXOTnZgSupqan069uHgx8f4i+r17Ds/iVNfiCC9XX32Fnz\n9wlwz9VWoa5+sVn0lQDThAUYSsZEx6cLna2LSGWh+DtqbI8k3900tkfmGzigP3V1dXxw8KPAg3LL\netrxntB8QsDIEcMD/gvl5RUAZGVlIqXk2KfHWf/mJsaOHsWt8nIOHz1Gt7zcQPsGzJ11Dy/+9r95\n5ut/haIo2FNsHD9xkuLBgwDweNyYTK2zNffv15ePPzmM1+tFCJgzcwZlt25hNplJSbFx5eo1autq\nWbNuPd/4q68ihGDu7JmsWbee05+dYdd77zNu9CgmT5zA5InBIzUF16H2v2dBAT0LCpBS8snhI6xd\nvwGAEcOG0rdPnzDtm74XCCGZOH4sQ0uLeemVVfzX//yOr3zhKb9vRFezsy6AdvId+d3vfse6deua\nRL/S4HK5+OUvf8nGjRsxm81861vfYufOndxzT8uJeSPq6uqa7RKMGDEiYpSiBuiYHLSc3TW8bigL\n9QXHe8UikoyhZAole6j2sfLFootY+cKhvVargr2ORfbWZW9s2MjihQv8N0PSzoLxSZ9XS0Al/THC\nVVU7AqIYwGhBmEzNOEaPHMGggQN46c8reeShZf7zuZ1hZ03LgrUP9j4R77l2sDO7A2X5M8jaKi3H\nQm0VwpGl7RzYHSFkCiV7MHmCve9M3TYtS/x7Ljm265N9+LChbN66nU+Pn6SkeFCIeuFkb/46Kysz\n8F4IGFJawpDSEjZt2caQ0mKGlpbgdnuaySpVL2kmhXvvmcKZY58g66q5Z/ok1m7ZRrYjlQeWLOaV\nv7zGU48/2korRqORRx5a1kyOxqRqgqKBaf7ALM1lH1xUxMXPL/GVLzzF0WPHeeUvrzFn5j3k5GQj\nhBK1boVQGDF8GCOGDwME777/PmfPXWDWPdPRa2dSSv606lWys7KQUrJtx9ssXrggTPtg6Ew760Jo\np52D3r178+KLL/Kd73yn2XWz2cyqVasCjvter7eZU3wwpKen89ZbbwXyHGzfvp2MjAxdcujwOWj6\nJbc0hmBlDW3CGaJs8T8cnx75QrXTyxdOdr18segiWr5waNlXrHwdqQvttapK7PaUGGXvinYWDYf/\ntdfd3O8BGiPMGC3N6/rR4Mi86rXXGTl8mD/j591oZ3rl61g7EwA2u+bkmxMslGM4jnays7BlnTme\nheO4k+wsHBL1noMF8+bwkX+3csmihVit1hb1opE9uG4XNgkV2uiM7K+j+sBVS3XFLbrl5CCkCl4X\nfbvnsXXHTs5+fokxo0ayZ99+Jk0Y34Q1dl2UFA+mpHgwAENKiykpHsSefQfYe+AAbreHngX5jB87\nJoQvQWRdTJsymXPnLwSNhBSqTWVlJbk52ZhMJhRFoTAwyekqY3sXmiS00+Rgzpw5XL58OUh3gqys\nLABefvllnE4nkyZNCsv14x//mG9/+9v84z/+IwCFhYU8//zzuuTQ4XMQyywwmnqhoIdPRqgXjDOS\nTLGuGsWDLxRi1UUkzsTQhZSyyZlUPbLqkekOszOjCSx27UfQ59XKFUNjBtsQfEajkcdXPMKJkydZ\ns34DBqHg9Xq4f+FcbXXLoEWlQSiImHURDoljZ8H5wsmqh+MOs7PkeNZOfOFk1cOR+HY2auRIhg4p\nZeWrq7l3/nyyszNb1IuOL/LnaALFAJYUzl25wZhRIzl0/AQYzYwYNYoR4ybw0qtrmDR+PPsOfKBD\nF+EQXA6fT0VRFH8COI3v80ufs3rtOuwpdhbMm+13oI7Ozvr26c2Jk6dxudxYLOZAmctVj5QSq9XG\nwY8/5uNPDjN10kSOHT/O0sWLWL12HQ8vezDAJyV893s/4Cc/+n4QOWLRRTzsLJwuugA6wSFZSsl/\n/Md/cOHCBV544YWQ9Z544omAw77VaqVnz55IKbHZbHz/+9/npZdeithXHDMkx1qvPfsNx9nWz9Ee\nfKEQb93q5egYXZQMHsSRo0cZNnRIlLJG01codA07EwYj2FK1d61C1kXmGzyoiEGFPcBdx8XLV/hg\nz27GjRzWWMWRG+QM5Z1lZ8HL4tlvOHQNO4svXyjc2eNZ8LJ49hsOnWtnJpOJJx59hJWvriY3Jwef\nz8eNmzc5euxT0tJS6ZaXF2RXIVr5WssqFAPY0hg7cRKrt79HVnYPRGpmoHzs6FEc+PAg8+bM0sUX\nGsHbvfr6GhyONO6dPy9wvbBnTwp79uTK1au88977zJg2NYrP1fh6xrTJbN62DSklpcXFFA0cwJbt\nb3H12nXye3THarEycvgwqqqrURSFN7dsZeG8Oc04hIBBAwew8tXVPPrwQ7r61a8HfZ8jurIugHbO\nVxEsBdk///M/Y7Va+fWvw+dK+Ju/+Zs29x9lnoNgM7uGa3pnxHr5wtUN1VdH8nWkLqLh6wxdBOND\nt+ynz5xhQL9+EXiTdhYoCZxnjVIXtlSwpNCrKIOPTqzXdiKMpkBM+65nZ+HadeQ9p4cvXN3O1K0e\n2SPrQrrrtWNuqg98Pv+ulv/PbGvhkJrodpaoY7sevnB1O0a3QiisWP4QdXW1+K5fYs2nH2G9cpKK\nykoO3bqNC4VhI0YwaPy0Znbh86n+nAl6+gouZ98+fegbCGrRWKYdASpucp246UJKLVJSc0fPRr78\nHj14f88+pJQtVu312YXNZmPp4sWA5MjRY6xeu45l9y/h4MeHuHDxInVqHXWX6vB6fUyeMJ4ePboH\n5Rs8qAin08nqtet4cOmSJgvfiWhnXQDtvHPQsPi3ceNGnE4npaWlrFmzhtGjRwd2Bp588smAP0FT\njBs3rs39R5nnINiXKEOUyRCv9fKFux6qr47k01PWYPht1YUe3bbs6/9v772j5LiyO83vRZpKU97A\nVMEUPEGQ8JYASIAkSJAASYAkQJBssrsltbTaPZrZ1fRKM2d32mhWS61mjnZG3aJGZ7QaTYvdBL0B\nSNCDJEgQ3tuCB0jCFIDyLk28/SOysqqy0kRmRrrC+86pU1UR8X73xs0bkfHiuXRjkWm9vn1rH32E\nI0ePhW5aj8a45lSexd5nLs9E/3nunW5jUbqYvsby3eq8iPw/Gb1o5bJ5zSWjF297LvMsnm4Sse3p\nGDDrEsHQgFGbHVEU0T887/Ms3+7tyejF2569PBPCmOr0b/7+V8wbX0dNsJ1xw4q5c1gxUko2Hz5I\nw412ADRNo6urm66uLkpLSxBCMGL4cObNmd1vvQMrY5vqZx99uxCCDz7+hL/9T/9PTL0pkyZy7vwF\nxo+rT9KPvjxramrm4OEj4YfGObNmMmfWzBi+DdZbtGA+b2/azI2bNzlx8iSvvvkWf/on/wslJbFm\n4svFM0RmH7gtJYOVg7q6OjZu3AjA6tWrw9uPHTuWMZuRmJytSMb4P9NvSqx+k9O/DDF8j3Yuvccm\nG4tYsUlFL5OxiKUXzfdUYxs/FndMm0ZdbS2vvPEWTz2xNrSSa9A4xmb0iUf09YqP7eetmmfRygzc\nJ8F4qxvw40KnvfEK3rIKY9yBzRYqkc1YZD/P8v9+Fs92HueZvchogQqGWg96Ww1s9lCpXF5z+Z5n\nhX5vj4Zx7B//3g9pvPw9Gz//ijUL7qS6ZhjCXcwj4+5AG3s7AoGuB+nu7sbj8YRLX/r2Oz746JMB\ng5Dz+d7+3/7ubyO6eQ60M3rUKLZ++SXjx40zpddH3/9lZaW43S6eWLOm377kfF/zyGpaWlopKytl\n6V2L+Fc//XN++X/+O3w+P+VlZVRXV6cYC6vyrIAQme1WlGuEjNaxCWhoaICuttAUXgpFdtj22adM\nHDWcEcOirDxcVhPqUqNIBf3qBbh5GYDN23ayctFc7HYbIBATZ4emQ1UoUkdKCVIHocV5WFLcanR2\ndrJ3926ut7QhhJEnNpstvALxrJkzBuXLjl27udbYCICu6yycN48RI4bnwv202Lf/ANcar7PivuWh\nNWfi09TUzLbt2wkGg2iaxuKFC8Nr2Rw4eIjzFy/y6KqHo6winTwdHR24XC6OHD3Gf/+X37LkrkWs\nWvlAv9mgskvDqdPgLmHy5Mk5sZ8Mwf/6b1MqZ/uf/spiTzKDycpBKjXEuGZN6KWja5VePBvZ0EvF\nVqZiG8tWL9bo6cEA//wvL/GDJ9fikEHQhPFW0mYHuyPJdwsqz/rryYAP6euCni7eefsdHluxDIrL\nociDKPIYg/pukTxT97Nc6N169zOVZ4n1zl+4wP6Dh/oenKWkxO1CSB094GfBnNm4i718+c0uLly+\nyuqVK6mqqkLXgzQ3t/DWpk1UVlRQUV7OsruX0tLSyvYdO9GlZMW9ywgGg3z+5VdcvXaNHz337CDP\nWltbuXK1kbPnzjF2zBim3hb5YJpeLP7zr19k+d1LudZ4nabmZlwuF/VjRjP9zjsH6X2x7St6enzc\nu+xu7HY7gUCA7Tt20tXVHR5M3dzczMeffc66x3tbEKzJs+vXb/D+hx+x/+Bh/uP//Rd8tX0Hc2bN\niOh2lNk8U5WD/MHkmAMZ8bs/qdw4zOilo2uVXjwb2dBLxVamYhvPllVINJuNDevX8dEXX7LqoZVp\nNjSqPOuvJ+wOhN0BnlKorkUbFXkDvnXyLLauup9lTu/Wu5/F1lV51kv92LHUjx0b/l9vb6Gt6Xr4\n/y+2fUlXdw9CCOpG1lFSUgxI3nxnEyOGD+OuBQs4d/4Ce/cfYM6smbz17iaqqiqpqa7mV3//D1y8\n9C0L589jXP3YAXYPHT7CqTNnqKyowO8PcPnKFWoHDOZN7LsZHlv9MHa7nbra2nALwJ59+/nyq6+4\ne8niAce2tLYOWNPAbrdz95LFfPjxp9y4cZOqqkrKy8sZP66ekw2nmDJ5UgL/zPtcXV3F888+zawZ\n0/H5fDRev87Hn23l8ccejaKXqTwroNbGId6LIYUxB2aOzde3Rtl+C5XPvueL3uB9Ho+Hnp4e9GBw\nQDOslBKCAaSvC+nzIex2RJHHmHEnPB6hkGORCsnb+vKrr5lxR6xpYwslFunnmXkbQ00vH95a57te\nZNlM2hqqeqnZEg4npRVVoZXgAzx07z3GeJbQdM4itLaLy1XEzaYmir1e7lt+Dw+vfIDOzk7mzZnN\n+HH1XGtsZPVDDzFhfD12uyPsw/ETJzl24gTDaoZRVFTEzaZmxowexYr7lpvoCpf8+Y6rrx+kMnf2\nLI4eO867772PEIJgMEgwGMRu7/9I1qf3wP338i+/28hjqx+mrKyMObNm8cFHH7Nt+zf8wY+eNx1b\nM763trWxa89eZk6/k3/8599w14IFMbpzZSLPCogh3m1SjTlQ5CXNzc3s3rufFfctD28LHvgCGi9B\nZMrWTkC7465Cu7XkhGPHT9B4/Tr3LF2Sa1cUCoUiJr0vgxACNFvCB/eTDaf4Ly/+V37yo+c5cuw4\nK1fcT01N9YBjWltb+fTzL3hs9Sr+x0u/4+n1T0asu5C/6LrOa2++zcL5cxk7ZgxgjEF478OP+MmP\nfsiwaOP0UuDlV1/Hbrezd/8Bnlz7GIePHOXHz//AEu1EFFS3on/89ymVs/3Bf7DYk8xgQeXAqjeg\n+Uiy55bo+EKOldWxSEzf1KYCEOgtjcj2Frh5Ba5/B6VVUDMaUVqBKK8p4MpBdvLsyNFjXGts5N5l\n9yTnXlbJ9TWXiWs0VU2rfcl1bPMJFYs+MpdnUg+C3xdqBeg3i5XdYSzsaMq+ef98Ph9bPvoYXddx\nFbl46MEVA/Zven8LgUCArq5uVj/0IKWlpcmeXJJYn2efff45be3tCCHQNA2vx0NTczNej7ffIm/p\n0d7eTltbOx2dnZw9dz48BiI9EseioCoH/9/PUipn+/2/sNiTzJDkOgfRKNQbohmSPbdExxdyrKyO\nRWLuWbKYrV98GXqYlWhl1VBWDXUTjC8dzVbAFYL+ZD7PDh85yvUbN/K8YgC5v+YycY2mqmm1L7mO\nbT6hYtFHBvOsvSk0JXUEDjfSWxq6f1sXW6fTyWOrV8Xcb6xgjCUz/ZjDnO8HDh7C5XJx25RED8Vy\nwD08GAxy4NBhmltacLmK0vBzIMXFxRQXF+P3+3n5tdd5+bXX+Ydf/WecTmcaqmZiUUDf6GrMgVWk\n83Yi39+gZdp+orJDK7a9zclVpR6uX7uGv6cHe1HRgNuGMbOOFfatKmuFXmbsNzU1c/7iRR55+KE0\nfVGxtUYv177k2n6isiq21ujl2hdhjBNAGKtn96LZU3wGTD8WAysFqelt+3o75y9coqKijAfuuzfN\nB2aDhtNn0DTNROWgF8N3m81mcjE0c3qROBwO/v2//bOUyg55hviYgwRVHys/8HS08v0NWqbtJyo7\ndGIbvP4d+rHt6Ie/RB77hgfr3Gz5x/+CfnI3sv8KrJbZt6qsFXqZsf/Rp5+F35il54uKrTV6ufYl\n1/YTlVWxtUYv175IhLccSiqhpAo8ZcbvkkqEpzSF+kF+5NnC+fOZAewPAAAgAElEQVQoKnIyeeJE\nXnvzbb7ZuSs8oBiMl1stLS34fD5TeseOn2D6HdPQNEFzc7NJL3L92VpVNpNaGUbTUvspELLYcqBQ\nJEZ4y5DD66H1BrTeoLikBN1TRoe3kmIiV0hWQKilJeCH7g4I+IwbkN0JLi9HTzQwccL4LDajK/IF\nqet0nTlLy7Zv6L5wEZvXg2fyRMruXoKjsiJuOQI9oX7iEmw2sDnAZs/awmZ+v59f/f0/8HvP/4Dy\n8vKs2FRkBiFCLQi2wn7cOH3mLIeOHMFms6HrOl6vh2c3rOfKlau898GHBINBAoEgQgg8bjeN16/z\nwx88k1D36PETrHt8DZMnTeTtTZsjpg5V5C1DvOXAgjEHCoV1aO5icBdDdZ0xrkAIVt++mNffeocN\n6ybk2r38pPkadLQQ+dbl+2s3OPd9E4/E6YOrGLqc+d/+LTc++Bj8/gHbbSUlzNz2EfbSkkFlpK8L\nOtuI+gbPWw4O6/o1x+PzL7/iJz/+Ie9sfp8fPP1UVmwqFLHYuXsPwWAw6oP7iBHDB6xN0Msrr79p\nStsfuj41TcNms9HS0kJZWVl6DhcsBfTMOcTHHAzts1MUNEKzIYSG3W7nzmm3s//AwVy7lFdIQq0G\nvW/m+nG44Sx7jp9i9coHcuOcIuc4htVQVFcLDkd4m62khKIxo5GBGF30hK2vn3h/tOy+9W28fp3i\n4mKmTb2NM2fPZdW2QhHJyYZT3LVwgaljb95s4je/fZn5c2cnPFZKidvdN5XqinuXs2vPvpT9VGQR\nTaT2UyAkuOMXUP8vxZBm2u1T2fjaG8yaOSPXruQFsrsTfJ19M4G4PKDrgACXm9Mtx3n82R/m1EdF\nbhn7f/zvjPl3/8boWvTVDhwVZQm7FAmHExyV/boWSWORwSx1Kbp46RIffbqV+XNmI4Rg5ozpvPve\n+0wYPy7jthW3LlJKjp84ybCamvAqxr28vWkzC+bNNa317XffsWDe3KiLn0Vy7VojI0f0rcrscrno\n6u4ybWvoUUDPnEO85aCwOwEqbikKrd+8DAaR1y/DtUvGQ3zFcMTIMQgrumZowugHLnWQ0rhRuVzg\ndIOjCEdRdrp/KPIboWl4Jk3EE7FeTXicSk8nBP1GLoVWGxdCIDTNyKUs4/cHmD1jOtPvNFbw7p3L\nXaHIFK+9+TbXGhu5f/ky9uzbj9PpCE8XevzEScaMGsWUyZNM6x05dpyn1z9p6tjq6ip27+trKdA0\njZ4eH7v27EXTNObOnpXcySgUFqHGHCgKhhl33sFnn39RAHP1g376EPLQduhsHbBdFnkQy9ai1dSl\npS+cbnC6jfcsug6apq5WhXmuXQR/DwPf1AnwliIrRuQkl65da2THrt08u2H9gO29s8AoFFbS2trK\n5i0fsnD+POrHjkHTNKZMnkTDqdO8+c67TJk0iaPHT/Dg/fea1ty5ew8L5s1NqpVN1/UB/0+/Yxo2\nm43vL19mz779BVNBeP2td1iyaCEjRgxPQ6WAvsWG+IBk9UpGUTBMmTyJUXV1bHztDdPTxOUOEbp5\nRNxAYtxQpJTI7m707i6jS4d5KwhVMVCYJDxORcZovpe5yaSDhw6ze98+nnlq3YDtgUCA8fX1nDjZ\nkBO/FEMTn88XmuTiCcaPqx/QOjV50kSW3303LpeL2pEjCATMV07Hjh7Nzt176O7uNnW8pmmDKr9T\nJk9i4oTx3L1kcUGNt3E6HWzb/k2u3cgeQkvtp0BQYw4UBcXkSRMZPaqOdza/z5jRo5LqC5pNtIl3\nIsdPQ968ClcvQjAAVSMRw0cj7H0DRPXGy8jTR5AnDhjHSQnFZYjb5yLm3INWXpmSfRnr4U9xSyKD\nfvD7wNdldHFzuSHoNFqd7A5jFiKXB2yOrFY0T5xs4PDRYwwfVhN1LY5XXn+TC5cu8cNnn86iV4qh\nztub3uMHTz8Vs8taRUU5FRXlSY91GTFiOOseX8PmLR8ghGDFvcvxer0xj9+1Zy/z5sQeuFxUlP4C\na9nC6/Fy+szZNFUK6HurgAYXp4Iac6AoONxuN+seX8PpM2f57cZXuW/ZPWk2ZWYGoWmI6pFQPXLQ\nPiklsr0Zef4o8swhuPF939vc7k5kyw2ENN+C0LuqNAEfCA2pB5FSZm1e+qGADAaMtSL0oNHf3uka\nOvGT9I1P6cVmMyoJrlKELdaK49Zz82YTW7/8EiEEkyZMYN3ja2IeW1zs5fFHH6GutjZr/imGJoFA\nAJvNxksvv4KU0pKVjaPhcDhY++gj+P1+Nm/5gPoxY2JOpHHl6tW4L7gqKyq4ebOJyjiTCOQL9y2/\nh737D/DeBx+msOhmATJUvhtioMYcKAqWiRPGM2H8OL7Y9hVffr2d5XcvpaamOtduJSR4+oBRGeju\nBCRi9BgYUw8IxJ13I0rKBrQuJEJ2t4OvB/S+6SllZyu03UQWVxiDSxUxkT1d0HzVGKDbv0JmcyDL\nahCewesBFBrC7gC7A+kuCVUSAKHl5Pttx67dPPLwQ6YezjRNY9JEtb6JIj2CwSC/+vt/oKK8nJnT\n72TG9DszbrO3krBv/wE2vvYGC+bNGTCDka7rBGJNKRxi4fx5vPbm24PG4eQrf/T7P+LNdzah63qK\nEwkU0DNnAXURSoWhfXaKIY8QgmV3L2Xd42s4fPQor77xVhJL0OcIfw/0dDOgCVXqYLMlXTEAjOkm\n+1UMmppbqCgr65vmVBEfqRutLpEtNUE/BfVlZQIBCKEZrVoRpyYJzbCVxJiXZNF1neaWFlMVA13X\naWpqxpbFVg3F0OTNdzbxh7/3IxwOB+cvXsxqi+DsWTNZ/8RabjY1s+XDj8Pbv/zqa+5evDhuWafT\nyai6Wi5fvpJpNy2hrKyMHz//g1tjhjG1zoFCkf8IIbh32T1IKXnp5Vd47pkNuXYpJtpt85FjO6Dp\nCrKrHWGzg7cMUTk8+YoBGCtKF7mNN9/BAMfOH2PazFlQWq1aDUwgXF7kiPFGlyJ/T18/fJcH7IXT\n5zdV9PZmZNtNuHkF2m6AZoOKkVBWhaiqQ7Pw4bypqZkxo0eZOra5uYXx4+ots624dSkqcuL1enP2\nBl7TNObMmknDqdO89e4mAoEgI0cMN9XSvXTxXWx6fwuP3RIr3RfQM+cQbzlQYw4UQwqjJWEJL7/6\nOvPnzsnLxZOEEAhPMXgmJj44Ail1ZGc7BHwIr9HKIHpXSA6tknzu+6ssWbbcareHNELTwFMCFH4X\nomSRHS1w9QJ0tRkbggG48S34uhFV1vb1r6gop8lky97xkyeZNEF1KVKkR1tbW95M0DB50kQmT0ru\nvn9LvIUvRNSYg6GIILkaarLHZ1svHXJ9btbHYvSoUTy9/kne2fxejisH1sVC72yFxu/A122sXAtI\nzYZ0uqBmNFpxOQCdnZ3UjhyZUC/7DL08yx/Si4Vt+FjksDEQDCADfuMIR5HRzc1i+5qmJexn3cvV\na9dYvGihqWNT8SUzeirPUj/eer329nbeenczP3j6KQv9SM2XdPR8Pn+G7ecLBfTMOcRbDob22cUk\n2YvK6oswny7qXJ9b5mKR+5lmLIxFTxd0toQrBoAxpqC7A6QeLnnu/AXG1Y9N0X4mGbp5lnvSj4UQ\nAmF3oLk8aC4PwnTFIHn7QoiE65T0ziyTPCrPMkeuY5G83rvvbeGZp9Zl4O17ds9t7uyZvPrGWxw7\nfiJD9hVJM8THHCS4YlQCKlKlcC6CfEXv7kBvukrw0knktyeRPZ3GFKiaHalpSCGQAR/yzAH0U/sJ\nNl7i6KH9jBqV3urLhYXKM/PkR6wmT5zIhYuX4h7z1fZvWLJoUZY8UlhLbvMsEAiwfcdOXn71dZYu\nXoTdXvi9p8fV17P+ibUEg0F+u/FV2tracuhNJj/fAnrmvLUXQVMoUiX3F3nuWw7iE16bQAjQbIP8\nlU1X4drFgbMO9XSGFqzyQlsT4Ti33+TY4YPUlZThcKQwqLlgyX2eFQ75EauTp04lnAf9ZlMTVVWp\nLQCoyDXZzTMpJceOn2DPvv2Ul5dht9uZN3s2dy1ckFU/ssGdd0zj9qm3sen9LdRUV6fQ7c4KJP/9\nNy9RXV3Fww8+oGYTG6JYPOagtx9ctP5w8fZlSy+ybLK2UrGRTT0V2/77hBAm51vObixktzGgGD3Y\n9+Cv2ZE2O7hLwjMM2UaORw6vh6Af6feBEKG+4HajQhEMGi0HAR8tHZ2cPNfKE6vW9rtq8yHP4vky\nNPJMXXPm9W7ebMJV5MLpLIqp19XVjavIlaafZn23Wk/lWfzjzdqIr3f8xElOnjpFIGAs9jhz+p08\n98yGKPf6fImFdXo2m401jzzC/3jptyxaMD+JLlPWxWJUXR3Dhw3jd6+8xv3LlzNyZOQipKnGIr9f\n6A0gz18+povFbRwy4rfZfdnSiyybrK1UbGRTT8W2/z6vx0NnZ6dleskTQy/o76sc9KIHwN896IYj\nNA3hKEJ4StDcxeHZiQQgbDa0Ijc2bxnbdu3jibVrIm6t+ZBn8XwZGnmWO73IsgO3yYS2UrGRul5P\nTw8vv/Y6y+5eEldv29fbuXvJXWn6GW2byrNCj0VPTw+/3fgqgUCANY+s5sm1j7Hu8TVMmjghxkNy\nvsTCaj3J2kdX8/pb76RgI33fV9y3nPMXL3DXwgXsPbCfg4cOp6VXkGhaaj9xkFLy85//nA0bNvD8\n889z6dLA7pfvvvsujz/+OOvWrePll1/O5NmZXefA6rcD8cpmSq+w35Qkj4pFT48v1MUmz2LrKgZ7\nkVE5CAb63Tj6X44CGQwYc+4H/eDrNFoW7E6wGavd9q8IaJqWoBuVyrP09MzYyW1sJRj5pAeNyqe/\nG+lwGTmj2Y31NHIY261ffMWPn3sWt9sdV6Gjs4Pi4mITvgzFPEtGNxt6uY9tW1sbPT0+tu/cid/v\nZ93ja+K2PA3lWPSntLSU6qpKmptbKC8vS1tvMPH1Hl31MFu/+JJir5dgMMj7H3zEwysfSFGv93cB\nVSYy0HLwySef4PP52LhxIwcPHuSFF17gxRdfDO//67/+a7Zs2YLL5WLVqlWsXr2akpLMTL9tcsyB\n1W8H4pXNlF5hvilJHRULn99HUVHvl0j6evHLxvZdSh0k4e5Cot+aBDEtSB3ZdgOk3vfQrwfB32NU\nGtylCE8JnZ2dvP/hxyYWllJ5lp6eGTs5jq2U0NE8eIxKTycUFYPbm5yexbHt8XXj8Xjilvb5fDHG\nzNwqeZaMbjb0ch/bt97dzO59+/jr/+sv+lUs1f0MjAXS/uZXf8e82TNZdvfdUVpPMptny++5m0vf\nfstX23fgchXx9qbNrHlkdQp6BVQp6CUDg4v37t3L0qVLAZgxYwZHjhwZsP+2226jpaUl/EyQyXGV\nJsYcRNb2+v8fb180rWi1ZTN6ZnQzqUcavsezYZXv+RZb4mjGsmF9bAdeONmNhfT7wN/V1zogpfHm\n32YDpyfKSsiGr8Fzh4zpSbs7jOlLnUVIpxv8AWi+CZ2t0N4Kfh/BknLeO3yWx577Mc6xk+LGQuVZ\n5vIsP2IhjTdZpdVGa5PUjdzTbEarVPiLLJf3M5BShq7L6GW279jJ4oULo5RPMhZx/UxWjziasWwM\n4TwzhXV5VlJSzE9+9EPcbk8aeoV4P4tvQ3a1Yg8G+Vc/WM/5i+f52//3b/jXf/QHxosndzEiS3k2\netRonl4/inPnzzN2zJgYumb1+n9n5zkZeDBvb28f0BJgt9sHjJucNGkSTzzxBB6PhxUrVkRpYbUO\nEy0HkckkTe6LpZOKnhndXOrF2hfrYrQ6FrFspROLbOjFK5d+ng1cFTPLeRH0g69r4Oag3/gpivb2\nNKRx87Kx0FkvPV3Q04W/qZntX2+npdNY58B4vhKMKy/BHnN2okLIMyv9I4Z/8coNnftZ+KtK0wAN\nabNH+arN3f1s7uxZfLNzV2gWmehlmltaqKgoj2FL5Vlyetn83oynn14shBBMv/OOOH6kcz+zUi9R\nmVT8i5Nnfh/oAVxOG7dNnMDJM+dC6+DI3qp4Ar/M+GHe93H19RH7U72GC4QMrFxdXFxMR0dH+P/+\nFYOTJ0/y+eef89lnn+HxePjpT3/Khx9+yIMPxp/5LVVMjjmIR76/nTTztsOKNyXRykX6m8z5xtsX\nLRbp2EpVLx6pxCIZvXi+998XbXs6eiZ9dxQZv/WgMdhYD4bK6dDRiixyg81hVGB6OqGjDdl6Azo7\nwOEwxhVoNgI2BzuOn+b7a9dZsXwFFQ5hHCOB0gpESTkU9Ta1p/JmKNlYpJvT0bTNlomnk+s8y9b9\nLDYSIBg0Wg50v9EFzeEy3iRqGkKLNuYgHolia6ZMH3W1dezaszfKvshYgLnPUeVZ5vSSOYd09WL7\n3nDqFKPq6pK0la3YRjsmmTLxdEzkmcvbN8ZIBpl+53Q2f/ENq1c+iJSEXmznMs9SuUZSycMckYGW\ng9mzZ7N161ZWrlzJgQMHmDx5cnhfSUkJbrcbp9OJEILKykpaW1st96EXC9Y5kBG/I7fH2xctETKl\nF49k9MzoWHG+ZvSsspWqXjxSiUU6egP/9vv9OMKL32QnFlLX+40rsIHNaCGQUkLrdZC9fcF16DIW\nsZFXLsLFEwOFuuD05UYOdNrxFHuZe8dU7l5aNfCY2okILXJ+6XgxzYc8i6Vttkw8ndzkWWJbWbzm\npIT2myD1vm2B0ErERV5wR2+C7nuQGLQngX/JlDG2GQtSRdc7dvwEUyZNTErPvD/JlImno/LMer3Y\nvh8/eZLHVq9K0tatcT8TTteAI8bfXklReRW/e2sTTz35eMS1Vsh5lqdkYMzBihUr+Prrr9mwYQMA\nL7zwAps3b6arq4t169axfv16nnnmGZxOJ2PGjGHt2rWW+9CLicqB2dpy/zc+sd7+RNMzW4ON1DNj\nK5G/6erF0zajl+qbiEi9/rZixTaRv4USC3N6Z86eZ8L4cXE0zORgfFtSDyJP7kV2tUFHq9EC4C4G\nbxmiYgTa2ClGOYHRF1zqENTRvz8NzY3GuIKuDnC6jL7hgD5mKpt3HmDYuLmsX7zYMNU79anQwO4I\nvQm2mY6FyrPM5Vlq97NUbSXwNyLP0APGDFg2LZxfvWVkVzvIYKilIYjUbKG8soPLg8hQbDVNo6Oj\nA6+3eJDeiYYGHn/ssQhbKs+i6+Uwz7IYW1eRi+vXb1BdXZ2Cr/3/vzXuZ3W1tax9dDW/+e3LPP/s\nM9jt/a/7eHr99+UyzwqIDLQcCCH45S9/OWDbuHF9zzEbNmwIVxwyjYkByfGSWpr424p9qepFYsbf\nZPQSaUeLXzxb8ewmikUiW/H0U/E9HpmMhbnP6uy5c6y4b3nS5ZKyFfAjL57oezsLxhiB5kZkSWX4\nOAHGjUTYjIe05ka4eoFovLbjEA+vfIjy8vK+jTabUYEYxFDIs3i2EpH7PLNmnzX3s0F5RpxZf/zd\nA2c1CoamzHW6Q1/RmYntA/fdy2tvvk1d7UjuXrIYv9/Hx59txe/3M2XSpCRsxTgv038n0kukfevm\nWfp65rXvv3cZb76ziXWPrzGprZ4hPB4PT69/kpde3siPnns2Sf+szLNUruECqiBkoOUgn0hhnYPI\n7fTbF+uDt6I2H498ezvQ+3c0/UzFIp3PKt5FnK5eZCzMvIlIP88CwQAOhzNNvcH6EhkaR6Ajg34Y\nMxm6OqGnA3q6wVMKnlKEyxsuE3m+om4C0l0MnW3Gj80BnhK27D3MkmVLKS+viPAv0vehlGfR9llx\nzWUyz2L5ni/3s8H7ZMCPbG1G3riG/v1FaGtG1AxHVNUgyisRTqdxaMCH7OkMj3lB0xCDYhvNV3O+\nOxwOnnlqPdeuXePNd97FbrfzwH33Rln7QOVZbN+tjoV1eWZ1LHbs2k0gEOD8hYvUj+0/E06hxDba\n3/31Im1Zc293u90sWrCAI0ePc8e0qQl8jaWfi2cIsz7mAZpIfEwBk8Q6B/E+/Mi/o5WP9n+iZDJL\nKnpm/Y32t9WxSEcvlr7VsUjGv3T2WRNbY7rEDORZdwd0t4dLi5H1fbtLqo2xBjF86v1bq66D6rqB\nR0lJ4PxNxtTXJ/AvU9dcIr1Y+tm65uLZSmVfrq85q/Xin29w28cEX/lvUa3Z/vjPsI0d17chNB4G\ngLJhfd/hcX2N/D++f8OG1fDEmsdIjMqzwcdm696efJ7F35d8LL7ZuZuSkmL2HTgQUTm41e5n8exG\nj+2UyRN5e9PmUOUgH2Jh1f0xT7i1Ww4g+ZquGfKt1m92X6qxyPe3S9HKJ/Ld6lhkPs+k1I1xAXow\n/Paf3r7WNgfCWRRVRfq6Q7NCBIw+2r39t/XQwE/NZtjpaEJqoX7bdhvC6TYdi+vXbzKspibNWFj9\nljAeKs8G27I6tol9l0F/XxehYNDYp4XGpNiLEKEVwm1LV6DNnG+0HFy+BG1NiOpQy0FZRb8xCRhT\n7fa2HAxYkyCaf9mKxVDLMzO+xzqX7OdZbq45wcgRwxlVV8uSuxbF8F09Q0T6rvd0wamDyI4WOLSd\noO0mFJdBcRli5Hi0kZFrEUSSyzxT5AtJjjmITIZ4++IhI37nQi+VfcmW6Y2fmXLpxiLSVqp6Zn23\nOhZZyLNgIPzWP4weMOaGdpfFlvF1DRxXMABhaIT1gkAPaL0LmZg7r+rqSr7e0ZhUmfixjSRf8yxR\nuQLMM8v0TPzt7zFas/oTDOVjeJyKRNjtiIoqqKjCNnEqsvX6wDEHvX873YhB63CoPBv89y2WZ2nt\nS13P6Dv/CvcsXRKjnHqGGOT7jSvII9uNLa03oPcHYNgoEpOpazieRv/zLRAyuDpxPmBizIHZtzKZ\nfCOXqi2r9bIZi1h6sTSyHQur9ayLrZSSYLDfdI692GzGW1E9NJOL1Pvesoav8yi2HEXGMb1rFgjN\nKBduVpR9802H5pTvu3GY811KsNlsUcqkF4vU9WJpqDzLq/uZwwnS29eqhQyNFbAbSRVLz+ECGexr\ncdBsxvWh2UNeqDxTeWaVXuqx0DSN+rFjaG5uoby8LEoZs3pmzyNZ/fyIrQTjOg76kUUuYyxcdxdd\ntnPoRR600gooLgcROctdPB8SkclYFACqW1G8D0ua+DvRPrO2U7FltV42Y5GKRjZjYbWedbH9/Mtt\nLF64YJCKEBq4+5Ymjz6/+2D9/m9Se1ddFlHeGpjVi+Z7w6lTTBw/Puq+VPRUnpkpk4p2Mnqp6CcX\nC2FzgNuYlSh6bkbXE/3WPEgnb1WemSmTinYyeqnoF04spk2dyvYdO3l45QNp6Jmzlbp+jmPbdBU6\nmgHQAMYY64U8OGwMn19pZcV99yenZ4pMxiL/ifYMMJRIchG0yFpg7zbJ4FqfmdpotO2p6MUqY9Z2\nMnrxuNViYeYtQDzfY5F6LKTUabx+g5qa6kHHyGAA2XAA2XwDWm8a3TGKyxFlVVBbj1Y7bpBepK2B\nq04SsS+12Oq6ZMeu3fzwB89EjUZsTZVnucqz5H3PTGxlMGh0LeodR4M01izQbGB3IOzOBHrEzelb\nK8/icavFIpXrx0xsE8dCBgPg94VbaiuLBC5NcunsaUaNHRcx6UMhxjYeKeZZWbXRMuD3Gd1ghQCn\nm4phY+m6uDVJvWzFQoR+JxOfPOLWbjkQEf9H+xBljH0yxt+Z0ItVxqztZPTiEVmu92LIRiwibaUb\ni3T0+u+LF4tEZePpRTtWous6Hk/0aRFl603ktk0Dd129ZOwtfTyqnjkfYm1LrNfT08PLr77O2kdX\nJ/EmYijlWSIf4ulFK5edPDNXJpN6Ifzdg8fR9NJvrY3YerF8iFZuqOdZPHIZi0RlzNq26ppLRS+e\nbkS5nk7jAbcfS2ffwRvvfcRT9eMHFi3I2MYjtTwTvS8EHEVIT0n4ye3ChQuMrq2N41+yvlv5DBFN\ny+x3YB4wxCsHJs4u8sMSJvfF0klFL5qu1XqxECnagtgXUiZiIS3UI009s7FINbaxfbfZ7Oi6HrWM\n8JTClNlQNwGKK8DuhIphMPY2hBbL73T9E+Hbo9R1o/XC32P81nXeeW8Lzzy1jrKy8hRtQWHnWTTy\nP8/yRs/mBKfbyGWhhbY5jG3SXCwkIINBZE83ensLekerkaO6HhFNlWd93GJ5Fv5tNr5pxMIeymmb\nMdMWQsPu8uD0eBk4jiZZ36P5mIJ/MfViYXWexfND9Nsi2H/wEDNnTE9QJr5e9L8T6UHq13CBoInU\nfgoEEwOSU6lxxtJKVCaXb+RiYfZ8U9HM91jka2zjx8Loez24jChyYbvHmFtd6kHo7gK3t98b+wzF\nVkpouzFwdhjg5OmzjBtRg9PpJPVYxKNQ8iyWnWzqJWsrP2IrHA5w9BtzICVCi/fOZ7CevHwOmq8O\nPkoIxKQ5xiD7uORHLGLrxULlWfp6sUg9FsLpCs+0JXXdqB8IDbunGClE6HWLFb7nUyyS0YtXbrCt\nwd9v+fwMkWwccsgQbzkwOeag/5ucyA8v2jYr9NLRtUovno1sxiIVshXbXvIjticbTjFh3LiEekKz\ng6c4vE9KHXw9IKPMFy8E9HRB0A8Bf2hmFwc4i8DVW7mI47sQ4C03KgcBH/h70G1O9jac45mnnspY\nLDKrF6+suobN7TOra05PCEHy0+sJRHUdsrTKWOW7tcmobHjLwOkZuP5BUj6rPBuqeZYaqcWif0V3\n1ozp7N67jwXz5qasZ95Ps75nWy+ejdB3ma4jWxqhvRlx9QLBEzuhyINweaFiOJrLm5Sedb5nIxZZ\n5NYekJxMjTMZUqnBJqNrlV48G9mMRSpkM7ZWkX4sTjQ08Oiqh5PQC/3u7jD6ug6gJ/Sryxj0GYnQ\noHZiQlsCQgut2cFRhO4qZuMrr7Hq4YejrKgcw7+o+5JhKORZIV/D+RsL4XAiHE7wliIrR6bZuK/y\nzJzerZdniW3FZ/SoUWzfsStUOVB5FktPtjYiT+zE5w9g62gyZjIK7RVFbkhYOchlnhXQA7dqOUgG\nq2uc+aKXD2958l0vsmyytlKxMbhsXW0t31++TF1tXUJdCWK3HEEAABh5SURBVCAlyH4rHctQK0Iv\nwaCxhkFoH1I3pkS1O8HuIHIeSKkHIRBABnwgBMJRZFQKhAAp8XV38/Jrr/HoqlWUlZWFzyITsciP\nvBiaeTZUYxH7qznfY5H/sU1sQ8Vi0FtwMO6xoVbXeXdOZdfOHcybNz9B97lk/Bu8T9d19h88xKVv\nv0UL2RFCEAgEKSku5r7ly6K8OM6T2BYVQ+VIvvlmFwumTTa2Od3g9oJeCHlWINzaLQfJfqhW1zjz\nRS+V5M4X37OlF1k2WVup2Bhcdsqkiezeu4+62trEMp2tg2bFAIzKwM2r0VdFrhkNFcMRUfphB79t\ngOvf9VU2ej10uBBjpnDu3Hl2HTjEUw/ej8sWgJZrxroL4XUUVJ4lr5usrVRsqFjkfyxUbDOnF1k2\nWVup2DB+y45WuHwm3HJbDxzc9w1zywRy9FQ0b2lSetH2NTY2smP3bsrLymhra8fn9yGEYNaM6cyZ\nNXNQqevXb/D2pk3YbDb8fj/3L19GWVlZAluJsC62mtsLU+Zx4+h31NyzEtnTjfCW9qtM5XOeFVBF\nQrUc3MokW+sthFpyqj5mIxbpx08IQbC7C/3kfmi8jGxrAncxorwGxk1BlFb2DdAq8hgtAP4eCPSA\nsEGR22glKCo2Kg5tN5EtN5DXLkNLM/TsQpRVIyqHwcRpiOoRYT1RVYv0lBmL0TRdNQbVVQxHuEvA\n7WXP8dNseGKtUelwOMHuMlofLI9tIeRhLIbiNZcbpK6HpoXsgaDPyG+7w8h7h9PE1Lkqz1I/Phfk\ni48WxtblhRHjjTxuvY7s6UIUl8PICcaYrxSRUnLk6DGOn2ygprqKhx98gLa2NtxuN0VF8XWrq6tY\n++gjAASDQT7+dCtSSh56cEVy5xYV88fLYMDoDhvwGePhbA6wOZBFbt77+DNmzZiOcLqMAd6Wki95\npsgkSa5zcKsxFGu9qfqYjVikH7/tO3ax8PJh5PFPBisfHon4wZ+Gt4necQBOV9iyCP3gKALKkJUj\n0P/pr+H8yQFaEsBbgu2n/yk8m4vmLgZ3MVQOR9ZNAqGFWx537t7DrDlzEcUVSCKvLKtjWwh5GIuh\neM3liKYr0NUWfV/tJBPN4irPUj8+F+SLj9bFVrPZoLgMisuQVSMJ+Hpwnm9GK6uOWSYR3d3d/NNv\nXuLB++9j3eNrwpXk8vLypLVsNhsPrriP373yGhcvXWLM6NED9l+9epV/ful3/Pm/+V9NKiYRu8ZL\nUVu3f/v+Vh56Yj3VVZVRCllBJvOsgJ45C2ha0lTIYrtIOoG0+kNIVi/X9jNJrs/NWvudXV1468ZC\n9Ujj7TwYzX/l1VBeQ+Tc7xKMMQaBAOjBQbc9AYgRY2DkGKNVoXer22tUKq5+j+zsCE2f2q+cpoW/\ndL7ZuQufz8fkSRMTnHGuP4tMkutzy7X95MtKKZG+HvTmG+jNN5A9XeE8k737gwGkHjT+7l8uGDD+\n0ewDm79tdijyDroO0kPlWf7Yt6qsFXrW2m9oOM1b777HXQvnmzo+GAzS3Nw8aPum9z/gh88+zYTx\n45JYeDKSvnJCCJ7dsJ5de/Zx82ZTePuVK1fZ+uU2Jowfl5SeafsOF9iLwmUlcOT4SWaOHUklAWR3\n96DvJevsW1W2gBFaaj8FgsVjDjKlZXVNNddvjfLlDQ/k/tyss+/z+dA0ge2B9QDobc1w8TTU1Brd\nfyIGsMneGYr6D0AGpMMF3rLwLc/28AZje3srwXd+gzy8Czo6+Kt9Z/hxQwPDvS4YNgrbH/4ZWnn/\nN1qS8xcu0NPTw7K7l5o4g1x/Fpkk1+eWa/vJldXPHkPu+wIuXwznp0RAZQ2sfBrN4RiUt2gOYyB8\nV9vgfS4vFFdCkTuNB6JYqDzLH/tWlbVCz1r7DadPsXD+3Lhv+Juamnnvgw8pKytFCEFJcTEtra0A\n4bxfMG8OXm+iGXsSMfjcnljzKG+8/S5Prn2ML7Z9RTAYZOH8uVz69ruU9BIdL6pGGg//AT/6zk8I\n7vicvd/s4we3j0H/6h3QNKgbj+25f41wm52hKBXy5Tkxy9zaA5IVivxEhmew8BsDiIXgk08/5957\n7g4fo5WUw7S5sUVsof7Xvi5DS2jGOAGbc7CtYAAcdrQlK9BH1SPPNVB35ipbLl2natRofM4ebtv+\nJfbyampGjaFs2HA++nQrDrsjRl9UhSIOlcNg6lwoqYBzx4xZs0ZPgvopCKcbilzg6wznPo5Q3joc\nRutAZ4uxz+YATxm4PMY0hgpFgbL6oZXs2befr7/Zyf3LlzFsWE1437nz59m1Zx9ut4tnN6zPQAU4\nMUIIpJR88/VXNH13kUeX3cVrH3zMgnnz+du/+3v+5I//CNnRAh0tSH+PMZOdtwzhLYs585LsN1MT\nwaBxrWs2o9urCA3Y7mgGp51v9CLunz8LOpuN+8CUWYjxtyE1W96925dS8tZbb9Pe1srTax/B7iwC\nux0pZd75GpMCagVIBSFjtDs1NDRAVzuTJ03Itk8KRUJkV9ugdQneeO9Dnli1EkqrEEks3iSB3ilJ\no92YZHuzMWA5crvfz6dbNhMIBHhw0VwaLnwLQGNTC02aiwceewKXy+rBYIpbDRkMGi0BNvuAh554\neSsBdB00rXC+bBUKE0gp+XTrF3R2Gfd/XdeprqpiyV2LcuwZ6N820HDkMGNH1rDn2Ck+2L6bmVMm\nokt4ctmC6DPgDRuLrW7i4O2AjDWjHgL98lljQHKI1z/bzpP33gXecrTx0xF2h0VnZS1SSmi7weXL\nl9lz8AgdXV2UeL2sXL6UM5e+R1SPZvLkybl2MyH60W0pldOmmelFkHtUy4GiMBGa0Z9aN/pW7z10\nhNl33m4MEtJ1pNBiPuwPkoL4TYRa6G2NHhxYyunivqWLeeejrQBMHjvK+D1hPFSMQFMVA4UFGAvl\nDa7sxstbAUa3AoViiCGE4P57l+XajejYnUyeOAH83cybNpm7ZtyOsNn5jy+9yabt+5h323hGlHr6\njndEnxkpXPFHGt91g7oQCuP7z+EEv48dRxqYPrHemI3M6Q7NgpfHaBojR4yg9Ox5JtSPoaa6km07\n9zCyqrJwXmYM8ZaDLI45UCisQ7i8yCKP8cDu6+LCt98zZ/odxtvS9pvGQTYH0lOCsKV3oxSesr6u\nRQGf8dBlLzIWxymrxjH6W075nEwaNQJcXoS7xOQCPQqFQqEYKmgj6o0JAbo7cXa2gM2BKC7nz//D\nPKSUvLflAyaVljGptgZcxYiS8kGt3LK7o6+r6wB6H5sl6Dra8NFIqSO7u7h88CyL7lmJKKmIugZP\nPiGEgOJKpJTcc98DbNr4Lzgr3Vw7eJgR9XVQNynXLppjiH/HD+2zUwx9gkG6OrsGd98RIjTFqEXv\nIaQOPV2hn24I+MMzQax++CH2HD+NVlWLFqf/qEKhUCiGNkIINLfX+D4orwl37xFCsPrhhzhy4Tu0\n4WPRyvq6vxozk3Uh225Ce5OxNkm4x7cwWhh6p8ru9/AvNDtBbznuYaMMW3leMehFSonsakdeOc+q\nKXVs37WPccMq2XroRK5dM40QIqWfQkGtc6AoSGR3O/R0cfXaNd5470N+/NQTxg6hQXG58cbGKls3\nvjfGN0S+ybE7kcPGoktZUBe9QqFQKHKDvXfgbeg7Q3a2QWujMblGfzQNKkYai3j22yyLPEbFQUrQ\nNM6cOMmkSQXyth1j8TZ95xbobAt/p66ZM5WtR05zpak9x94lwRDvVjS0z04x5Pn28hUee/B+3O5Q\ny4HAWHwsG8ZDfULfeGcTj656KBsWFQqFQlHALJw3j7fe3ZTwOBnUkV0dgyoNAmhvb+f8xYscO3ac\nXXv2UlWZqQXPskOxuwgdnafvX5JrV8wjRGo/BYIac6AoSISrGFnkpap2DDeam6hzeY1BWDan5W/x\nRVUtUg9CV2hdhKAfNI2ALnn/9Ve4Y/w4vDaQejCpWZIUCoVCcWsxfPgwFsybyyuvv0l5WRkL5s2h\nbPg48HdDTxf6oR3s27GDz7/ZxbrbRjO6ugLGT4M75nFB87Bv/0HKSksZMXwYbreb557ZYIx/KxCE\nzY62aLUx4+D1y8iWRtA0tEttaCPrc+2eeYZ4y0FhdFBTKKIghGB0/Ti2fHSaGa5iy/X9fj92uzF9\npNBsdAo73zU28+2F8zTdvI5N01gybw6VFRXhWZMUCoVCoYhHXW0tTz35OB0dHezZt5+m5maklLhd\nbnqOH2FkZwerJtSy9/vrXGjuYElpJV/v2oN/xFieXPtYrt1PGyEEwlMKY0qRHSOhsxVpO5Jrt3KO\nlJJf/OIXnDx5EqfTyV/+5V8yevToQcf97Gc/o7y8nD/90z/NmC9qzIGioLHb7QQCmXkw/6ffvETt\nyBHhgcdul5u62pHMXrCI0rIyY2YkUHPJKxQKhSJpvF4v9yzt60rT2dlJ5+xZVFVVQk83t/m6+a7x\nBq/s2c/8uXOYOGF8Dr3NDDe7A2z5dDvz7loeZYamPCYDXYQ++eQTfD4fGzdu5ODBg7zwwgu8+OKL\nA47ZuHEjDQ0NzJ8/33L7/VEtB4qCpqOjA13XEx+YAqPqallx73KcTmf0AwqoKVehUCgU+Y3H48Hj\nCa2D4HIjXG5Gl1bwzIToi6QNBZpbWtCEwONx09U1eLHRvCUD3/979+5l6VJjkbQZM2Zw5MjA1pT9\n+/dz+PBhNmzYwNmzZy23358EZ6fGHCjym48/28pjq1dlRNvv98euGCgUCoVCoUiLCePH8fT6J7l8\n5Srbvt6ea3fMk4EBye3t7ZSUlIT/t9vt4ZefjY2N/PrXv+ZnP/tZuDdDJlEtB4qCRtM07Pb009jv\n9+NwDFwsra2tfcCUcwqFQqFQZIMTJxuw2WxMnDB+wHdQV5exrk8hfy/5fD5eef1NVty7nBEjhiOE\nYP7cOXz5VSFVDqxvOSguLqajoyP8v67r4cHmH3zwAc3NzfzkJz+hsbGRnp4exo8fz5o1ayz3A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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x4539d6b90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "createTweetHeatmap(latLonPopulatedIndictment)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our thoughts on this type of visualization:**\n",
+    "\n",
+    "First of all, the reason that we used a log-based color scale in these plots is because it makes it easier to see where people are interacting -- otherwise it appears that all of the tweets are coming from Ferguson. We think that this visualization helps us better understand who is interacting in the twitter dataset, as we can begin to see that the Eastern half of the U.S. as well as the West Coast of the U.S tend to be the ones that interact most. There is, however, additionally, a dark point in the middle of the coutry that represents Ferguson. Beyond that, it looks like people all over the world, especially Europe, are talking about Ferguson in our dataset. \n",
+    "\n",
+    "After looking at this visualization, one of our thoughts is that it would be interesting to see how many people interact at a given time -- a combination of the first two visualizations. We pursue some variety of this in the following section."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "### Plotting tweets based on location and time\n",
+    "As we saw in the last visualization, it would be interesting to create an animation of the number of number of people tweeting from various locations across the world. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First lets declare some functions that every animation needs, courtesy of and adapted from [this blog](http://jakevdp.github.io/blog/2013/05/12/embedding-matplotlib-animations/)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#Note, the animation code courtesy of and adapted from http://jakevdp.github.io/blog/2013/05/12/embedding-matplotlib-animations/\n",
+    "VIDEO_TAG = \"\"\"<video controls>\n",
+    " <source src=\"data:video/x-m4v;base64,{0}\" type=\"video/mp4\">\n",
+    " Your browser does not support the video tag.\n",
+    "</video>\"\"\"\n",
+    "\n",
+    "def anim_to_html(anim):\n",
+    "    if not hasattr(anim, '_encoded_video'):\n",
+    "        with NamedTemporaryFile(suffix='.mp4') as f:\n",
+    "            anim.save(f.name, fps=20, extra_args=['-vcodec', 'libx264', '-pix_fmt', 'yuv420p'])\n",
+    "            video = open(f.name, \"rb\").read()\n",
+    "        anim._encoded_video = video.encode(\"base64\")\n",
+    "    \n",
+    "    return VIDEO_TAG.format(anim._encoded_video)\n",
+    "\n",
+    "def display_animation(anim):\n",
+    "    plt.close(anim._fig)\n",
+    "    return HTML(anim_to_html(anim))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Unfortunately, it's not as easy as we'd like to create functions that create animations for us (the output gets lost), so there will be some copy-and-paste-coding here!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<video controls>\n",
+       " <source src=\"data:video/x-m4v;base64,AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAA5nBtZGF0AAACrwYF//+r\n",
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+       "Jal0b28AAAAdZGF0YQAAAAEAAAAATGF2ZjU3LjI1LjEwMA==\n",
+       "\" type=\"video/mp4\">\n",
+       " Your browser does not support the video tag.\n",
+       "</video>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# First set up the figure, the axis, and the plot element we want to animate\n",
+    "fig = plt.figure(figsize=(10,10))\n",
+    "ax = plt.axes(xlim=(-180, 180), ylim=(-75, 75))\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "scat, = plt.plot([], [],'o', alpha=0.2)\n",
+    "\n",
+    "# animation function.  This is called sequentially by the animator\n",
+    "def animateShooting(i):\n",
+    "    startDate = date(2014,8,14)\n",
+    "    queryDate = startDate + timedelta(days = round(i/24)) \n",
+    "    hour = i % 24\n",
+    "    subset = []\n",
+    "    subset = latLonPopulatedShooting[\n",
+    "        (latLonPopulatedShooting['createdDatetime_Date'] == queryDate) & \n",
+    "        (latLonPopulatedShooting['createdDatetime_Hour'] == hour)]\n",
+    "\n",
+    "    scat.set_data(subset.coordinates_x,subset.coordinates_y)\n",
+    "    \n",
+    "    return scat,\n",
+    "\n",
+    "# animation.Animation._repr_html_ = anim_to_html #this yields a depreciation warning, heads up\n",
+    "# call the animator.  blit=True means only re-draw the parts that have changed.\n",
+    "anim = animation.FuncAnimation(fig, animateShooting, frames=72, interval=5000, blit=True)\n",
+    "\n",
+    "# call our new function to display the animation\n",
+    "display_animation(anim)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And now, the same for the indictment data!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
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+       "AAEAAAAATGF2ZjU3LjI1LjEwMA==\n",
+       "\" type=\"video/mp4\">\n",
+       " Your browser does not support the video tag.\n",
+       "</video>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# First set up the figure, the axis, and the plot element we want to animate\n",
+    "fig = plt.figure(figsize=(10,10))\n",
+    "ax = plt.axes(xlim=(-180, 180), ylim=(-75, 75))\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "scat, = plt.plot([], [],'o', alpha=0.2)\n",
+    "\n",
+    "# animation function.  This is called sequentially by the animator\n",
+    "def animateInd(i):\n",
+    "    startDate = date(2014,11,23)\n",
+    "    queryDate = startDate + timedelta(days = round(i/24)) \n",
+    "    hour = i % 24\n",
+    "    subset = []\n",
+    "    subset = latLonPopulatedIndictment[\n",
+    "        (latLonPopulatedIndictment['createdDatetime_Date'] == queryDate) & \n",
+    "        (latLonPopulatedIndictment['createdDatetime_Hour'] == hour)]\n",
+    "\n",
+    "    scat.set_data(subset.coordinates_x,subset.coordinates_y)\n",
+    "    \n",
+    "    return scat,\n",
+    "\n",
+    "# animation.Animation._repr_html_ = anim_to_html #this yields a depreciation warning, heads up\n",
+    "# call the animator.  blit=True means only re-draw the parts that have changed.\n",
+    "anim = animation.FuncAnimation(fig, animateInd, frames=72, interval=5000, blit=True)\n",
+    "\n",
+    "# call our new function to display the animation\n",
+    "display_animation(anim)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our Thoughts on this type of visualization**\n",
+    "\n",
+    "We really like this visualization -- it's super cool to see how the world talks about Ferguson, and see when various parts of the world are engaged in the coversation. One insight these plots appear to give us, is that while the rest of the world has some periods in which they talk about Ferguson less, the twitter users in Ferguson are *always* talking about Ferguson. Improvements to such a visualization may stem from incorporating labels for events, over time, allowing a viewer to immediately understand a particular ebb or rise in tweets.\n",
+    "\n",
+    "Although now we know where people are engaging, and when they are engaging, this plot still does not tell us *how* users engage in the conversation."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hashtags\n",
+    "To get at the question of how users are engaging with the dataset, we decided to look at one of twitters unique features: the hashtag. This is a quippy oneword statement often indicated by a pound sign in a post by a user - which twitter has handily aggregated for us already. \n",
+    "\n",
+    "To do this exploration, we first have to do a little bit of data re-ordering. Now that we've seen what sorts of visualizations are helpful for understanding the dataset on a very high level, let's explore different methods of visualizing hashtags in the dataset. To do this, let's create a dataframe that has one row per hasthag,tweet combination. So, a tweet using two hashtags would translate into a dataframe with two rows. \n",
+    "\n",
+    "In this case, these visualizations take a long time to make and the data takes a long time to reprocess, so we will transition to using only the shooting data here. We are doing this because it seems we learn similar things about how helpful a given visualization is whether or not we are using the shooting or indictment dataset. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will create this dataframe by looping over the rows in the dataframe, and looping over the hashtags in each tweet. For each tweet, we will create a json object that represents the row that should be added to our new dataframe. \n",
+    "\n",
+    "**Warning:** This is super slow, so don't run this unless you have to"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def convertToHashtagDf (df):\n",
+    "    '''convert a tweet dataframe to a dataframe of hashtags'''\n",
+    "    numprocessed = 0\n",
+    "    hashtagRows = []\n",
+    "    hashtagMap = {'MICHAELBROWN': 'MIKEBROWN'}\n",
+    "    for i,tweet in df.iterrows():\n",
+    "        numprocessed += 1\n",
+    "        if (numprocessed%500000 == 0):\n",
+    "                print('processed {} tweets'.format(numprocessed))\n",
+    "        for hashtag in tweet['entities_hashtags_text']:\n",
+    "            mappedhashtag = hashtag.upper()\n",
+    "            if (mappedhashtag in hashtagMap):\n",
+    "                mappedhashtag = hashtagMap[mappedhashtag]\n",
+    "\n",
+    "            hashtagRows.append({\n",
+    "                    'createdDatetime': tweet['createdDatetime'],\n",
+    "                    'hashtag': mappedhashtag,\n",
+    "                    'tweetId': tweet['id_str'],\n",
+    "                    'x': tweet['coordinates_x'],\n",
+    "                    'y': tweet['coordinates_y'],\n",
+    "                    'date': tweet['createdDatetime_Date'],\n",
+    "                    'hour': tweet['createdDatetime_Hour']})\n",
+    "    print \"creating dataframe\"\n",
+    "    hashtagsDf = pd.DataFrame(hashtagRows)\n",
+    "    return hashtagsDf"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "processed 500000 tweets\n",
+      "processed 1000000 tweets\n",
+      "processed 1500000 tweets\n",
+      "processed 2000000 tweets\n",
+      "processed 2500000 tweets\n",
+      "processed 3000000 tweets\n",
+      "processed 3500000 tweets\n",
+      "creating dataframe\n"
+     ]
+    }
+   ],
+   "source": [
+    "shootingHashtagsDf = convertToHashtagDf(shootingSubset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559552802816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559585951746</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559653449729</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906560190324736</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906560328749057</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>SISTERPATRIOTS</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906560328749057</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561222139904</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561251504129</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561264062464</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>CUBA</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561645367297</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      createdDatetime        date         hashtag  hour             tweetId  \\\n",
+       "0 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906559552802816   \n",
+       "1 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906559585951746   \n",
+       "2 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906559653449729   \n",
+       "3 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906560190324736   \n",
+       "4 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906560328749057   \n",
+       "5 2014-08-14 13:13:06  2014-08-14  SISTERPATRIOTS    13  499906560328749057   \n",
+       "6 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906561222139904   \n",
+       "7 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906561251504129   \n",
+       "8 2014-08-14 13:13:06  2014-08-14        FERGUSON    13  499906561264062464   \n",
+       "9 2014-08-14 13:13:06  2014-08-14            CUBA    13  499906561645367297   \n",
+       "\n",
+       "    x   y  \n",
+       "0 NaN NaN  \n",
+       "1 NaN NaN  \n",
+       "2 NaN NaN  \n",
+       "3 NaN NaN  \n",
+       "4 NaN NaN  \n",
+       "5 NaN NaN  \n",
+       "6 NaN NaN  \n",
+       "7 NaN NaN  \n",
+       "8 NaN NaN  \n",
+       "9 NaN NaN  "
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shootingHashtagsDf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that we have a dataframe, let's look at the tweets that use hashtags the top 10 hashtags (to get a feel for what people are tweeting)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[u'FERGUSON', u'MIKEBROWN', u'GAZA', u'MEDIABLACKOUT', u'JUSTICEFORMIKEBROWN', u'NMOS14', u'DONTSHOOT', u'PALESTINE', u'STL', u'TCOT']\n"
+     ]
+    }
+   ],
+   "source": [
+    "numTopHashtags = 10\n",
+    "popularHashtagsList = (shootingHashtagsDf\n",
+    "                   .groupby('hashtag')\n",
+    "                   .count()\n",
+    "                   .reset_index()\n",
+    "                   .sort_values(by='createdDatetime', ascending=False)['hashtag']\n",
+    "                   .tolist())[0:numTopHashtags]\n",
+    "\n",
+    "print(popularHashtagsList)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For framing, these hashtags had/have the following connotations on twitter:\n",
+    "\n",
+    "*Ferguson* - a flag for simply talking about the shooting and current events\n",
+    "\n",
+    "*MikeBrown* - used often to memorialize the teen\n",
+    "\n",
+    "*Gaza* - used to reference other unrest in the world\n",
+    "\n",
+    "*MediaBlackout* - initially in reference to reporter arrests, then carried on to imply that reporting in Ferguson failed to tell the whole story or was limited in detail\n",
+    "\n",
+    "*JusticeForMikeBrown* - this not only memorialized the teen, but took a stance of decidely PRO-Mike Brown\n",
+    "\n",
+    "*NMOS14* - a call for a national moment of silence, peaked during a night of silent vigils both physically, and as the data will show, virtually\n",
+    "\n",
+    "*DontShoot* - an allied with Mike Brown or BlackLivesMatter hashtag\n",
+    "\n",
+    "*Palestine* - similar to Gaza in purpose\n",
+    "\n",
+    "*STL* - used as a flag for the greater metropolitan area, St. Louis\n",
+    "\n",
+    "*TCOT* - used as a unifier for Top Conservatives on Twitter\n",
+    "\n",
+    "Now that we have the most popular hashtags, let's filter the hashtags dataframe for just those hashtags. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559552802816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559585951746</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906559653449729</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906560190324736</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906560328749057</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561222139904</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561251504129</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561264062464</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2014-08-14 13:13:06</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906561704460288</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2014-08-14 13:13:07</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906562589478912</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       createdDatetime        date   hashtag  hour             tweetId   x   y\n",
+       "0  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906559552802816 NaN NaN\n",
+       "1  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906559585951746 NaN NaN\n",
+       "2  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906559653449729 NaN NaN\n",
+       "3  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906560190324736 NaN NaN\n",
+       "4  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906560328749057 NaN NaN\n",
+       "6  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906561222139904 NaN NaN\n",
+       "7  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906561251504129 NaN NaN\n",
+       "8  2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906561264062464 NaN NaN\n",
+       "10 2014-08-14 13:13:06  2014-08-14  FERGUSON    13  499906561704460288 NaN NaN\n",
+       "11 2014-08-14 13:13:07  2014-08-14  FERGUSON    13  499906562589478912 NaN NaN"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "popularShootingHashtagsDf = shootingHashtagsDf[shootingHashtagsDf.hashtag.isin(popularHashtagsList)]\n",
+    "popularShootingHashtagsDf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's count the number of times each hashtag was used in a given minute. To do this, we will group the dataframe by datetime.minute and hashtag and then aggregate by count."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>DONTSHOOT</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>289</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>25745</td>\n",
+       "      <td>25745</td>\n",
+       "      <td>25745</td>\n",
+       "      <td>173</td>\n",
+       "      <td>173</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>GAZA</td>\n",
+       "      <td>130</td>\n",
+       "      <td>130</td>\n",
+       "      <td>130</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>JUSTICEFORMIKEBROWN</td>\n",
+       "      <td>286</td>\n",
+       "      <td>286</td>\n",
+       "      <td>286</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>MIKEBROWN</td>\n",
+       "      <td>3236</td>\n",
+       "      <td>3236</td>\n",
+       "      <td>3236</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>NMOS14</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>PALESTINE</td>\n",
+       "      <td>28</td>\n",
+       "      <td>28</td>\n",
+       "      <td>28</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>STL</td>\n",
+       "      <td>993</td>\n",
+       "      <td>993</td>\n",
+       "      <td>993</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>TCOT</td>\n",
+       "      <td>106</td>\n",
+       "      <td>106</td>\n",
+       "      <td>106</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-14 00:15:00</td>\n",
+       "      <td>DONTSHOOT</td>\n",
+       "      <td>102</td>\n",
+       "      <td>102</td>\n",
+       "      <td>102</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      createdDatetime              hashtag   date   hour  tweetId    x    y\n",
+       "0 2014-08-14 00:00:00            DONTSHOOT    289    289      289    0    0\n",
+       "1 2014-08-14 00:00:00             FERGUSON  25745  25745    25745  173  173\n",
+       "2 2014-08-14 00:00:00                 GAZA    130    130      130    0    0\n",
+       "3 2014-08-14 00:00:00  JUSTICEFORMIKEBROWN    286    286      286    0    0\n",
+       "4 2014-08-14 00:00:00            MIKEBROWN   3236   3236     3236   16   16\n",
+       "5 2014-08-14 00:00:00               NMOS14     18     18       18    0    0\n",
+       "6 2014-08-14 00:00:00            PALESTINE     28     28       28    0    0\n",
+       "7 2014-08-14 00:00:00                  STL    993    993      993    0    0\n",
+       "8 2014-08-14 00:00:00                 TCOT    106    106      106    0    0\n",
+       "9 2014-08-14 00:15:00            DONTSHOOT    102    102      102    2    2"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hashtagTimeCounts = (popularShootingHashtagsDf\n",
+    "                     .set_index('createdDatetime')\n",
+    "                     .groupby([pd.TimeGrouper(freq=(15,'Min')), 'hashtag'])\n",
+    "                     .count()\n",
+    "                     .reset_index())\n",
+    "hashtagTimeCounts.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that we've gotten the counts for a particular hashtag every 15 minutes, let's plot this over time as a line graph."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x5821df450>"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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JiQmzZ8/G1taWjz/+mMzMTKpWrYq7uzsqlYoBAwbg5eWFwWDAz88PtVpN3759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\nBEEQhBHv/we8UY1hH9a4wQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x58098f650>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "\n",
+    "for hashtag in popularHashtagsList:\n",
+    "    filteredHashtagTimeCounts = hashtagTimeCounts[hashtagTimeCounts.hashtag == hashtag]\n",
+    "    filteredHashtagTimeCounts.plot(kind = 'line', x = 'createdDatetime', y = 'tweetId', label = hashtag, ax = ax)\n",
+    "    \n",
+    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
+    "plt.xlabel('Time')\n",
+    "plt.ylabel('Number of Tweets over Time')\n",
+    "plt.title('Hashtag useage over Time')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Since the number of tweets using the \"ferguson\" hashtag is so high, let's also make this plot and remove that line from the dataset. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x4ba6a67d0>"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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p06hZsyYvvPBCtjXfq1Spwrp16wgJCeHdd9/ls88+U85NnDiRdu3aPXRP5hSCxMREBg8e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Chyk6oCTSe82ZGulDGJQCcEkqKlDGlwCRxUTYdWxNAE1Xr/2NIFrE6MLyYMUi8lXrjMaAZ6awan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\nK8N14YUMJUZwSg7cFhcBeykVj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FCyH13XcJhN+Sr0WCYG6KzzGUU128svAKB19BQXlxsB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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x527f45110>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "\n",
+    "for hashtag in popularHashtagsList:\n",
+    "    if (hashtag == 'FERGUSON'):\n",
+    "        continue\n",
+    "    filteredHashtagTimeCounts = hashtagTimeCounts[hashtagTimeCounts.hashtag == hashtag]\n",
+    "    filteredHashtagTimeCounts.plot(kind = 'line', x = 'createdDatetime', y = 'tweetId', label = hashtag, ax = ax)\n",
+    "    \n",
+    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
+    "plt.xlabel('Time')\n",
+    "plt.ylabel('Number of Tweets over Time')\n",
+    "plt.title('Hashtag useage over Time')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our thoughts on this visualization**\n",
+    "From this visualization, we can very breifly see trends in hashtags - as they pick up steam, as they persist, or as they die. What's useful about this, is that hashtags serve as both a method of labeling one's own post, or calling out other groups (that perhaps don't share the views in the post). Ferguson and MikeBrown persist because they are general tags which immediately capture, on either side, what is going on. MediaBlackout is more short lived though wildly popular, and was triggered after some arrests of reporters during the unrest in Ferguson.\n",
+    "\n",
+    "Since hashtags can be 'polarizing' in the sense that many label what could be perceived as 'sides' of an argument, it would further be interesting to understand who is actually tweeting certain hashtags across the US, thus exploring - are there communities that only tweet certain hashtags? Are they geo-located by stance?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Hashtags by Location"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Thus, to explore geo-located information, we create a new dataframe primarily of populated coordinate information."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "latLonPopulatedHashtags = popularShootingHashtagsDf.dropna(subset=['x','y'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>2014-08-14 13:13:07</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906566502776832</td>\n",
+       "      <td>-82.729054</td>\n",
+       "      <td>28.031176</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>370</th>\n",
+       "      <td>2014-08-14 13:13:23</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906630168088576</td>\n",
+       "      <td>10.711095</td>\n",
+       "      <td>59.927393</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>638</th>\n",
+       "      <td>2014-08-14 13:13:33</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906675026198528</td>\n",
+       "      <td>-77.034159</td>\n",
+       "      <td>38.926960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>816</th>\n",
+       "      <td>2014-08-14 13:13:41</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906705330036736</td>\n",
+       "      <td>-77.036776</td>\n",
+       "      <td>38.903024</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>822</th>\n",
+       "      <td>2014-08-14 13:13:41</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906707519471617</td>\n",
+       "      <td>-80.503679</td>\n",
+       "      <td>43.414038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>919</th>\n",
+       "      <td>2014-08-14 13:13:45</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906723331981312</td>\n",
+       "      <td>-88.143910</td>\n",
+       "      <td>42.086162</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1233</th>\n",
+       "      <td>2014-08-14 13:13:58</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906779070087168</td>\n",
+       "      <td>-73.838375</td>\n",
+       "      <td>45.476223</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1307</th>\n",
+       "      <td>2014-08-14 13:14:01</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906790557904898</td>\n",
+       "      <td>-90.273212</td>\n",
+       "      <td>38.568488</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1500</th>\n",
+       "      <td>2014-08-14 13:14:09</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906825593319424</td>\n",
+       "      <td>18.378632</td>\n",
+       "      <td>-33.930716</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1608</th>\n",
+       "      <td>2014-08-14 13:14:14</td>\n",
+       "      <td>2014-08-14</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>13</td>\n",
+       "      <td>499906846472540160</td>\n",
+       "      <td>-73.986029</td>\n",
+       "      <td>40.757285</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         createdDatetime        date   hashtag  hour             tweetId  \\\n",
+       "35   2014-08-14 13:13:07  2014-08-14  FERGUSON    13  499906566502776832   \n",
+       "370  2014-08-14 13:13:23  2014-08-14  FERGUSON    13  499906630168088576   \n",
+       "638  2014-08-14 13:13:33  2014-08-14  FERGUSON    13  499906675026198528   \n",
+       "816  2014-08-14 13:13:41  2014-08-14  FERGUSON    13  499906705330036736   \n",
+       "822  2014-08-14 13:13:41  2014-08-14  FERGUSON    13  499906707519471617   \n",
+       "919  2014-08-14 13:13:45  2014-08-14  FERGUSON    13  499906723331981312   \n",
+       "1233 2014-08-14 13:13:58  2014-08-14  FERGUSON    13  499906779070087168   \n",
+       "1307 2014-08-14 13:14:01  2014-08-14  FERGUSON    13  499906790557904898   \n",
+       "1500 2014-08-14 13:14:09  2014-08-14  FERGUSON    13  499906825593319424   \n",
+       "1608 2014-08-14 13:14:14  2014-08-14  FERGUSON    13  499906846472540160   \n",
+       "\n",
+       "              x          y  \n",
+       "35   -82.729054  28.031176  \n",
+       "370   10.711095  59.927393  \n",
+       "638  -77.034159  38.926960  \n",
+       "816  -77.036776  38.903024  \n",
+       "822  -80.503679  43.414038  \n",
+       "919  -88.143910  42.086162  \n",
+       "1233 -73.838375  45.476223  \n",
+       "1307 -90.273212  38.568488  \n",
+       "1500  18.378632 -33.930716  \n",
+       "1608 -73.986029  40.757285  "
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "latLonPopulatedHashtags.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def createHashtagHeatmap(hashtag):\n",
+    "    plt.figure(figsize=(10,7))\n",
+    "    subset = latLonPopulatedHashtags[(latLonPopulatedHashtags['hashtag'] == hashtag)]\n",
+    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "    ax.coastlines()\n",
+    "    plt.hexbin(subset.x,subset.y,cmap=cm.Reds,bins='log')\n",
+    "    plt.title(hashtag)\n",
+    "    plt.axis([-180, 0, -75, 75])\n",
+    "    plt.colorbar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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V1ZGbm4vFYkEURZ555hmSkpJ8lj948CDjxo0jOjqa69ev895776HRaNBqtUydOrVdo6ms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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x5285738d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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48WP5c39/f4KDgwkKCiIyMtLhioCu0lqLISQkhDlz5ijxEQodcDXgs7eorq52\nexroq1evotFomDBhQpf2u3fvHidOnOA73/mOS9/J/v375SFvs9nM2LFjbVahtHL06FEGDRrUYelr\nTykuLubUqVMkJycTHh6Ov78/fn5+bj2eN2/e5Ouvv+a1115zWy6ZvuDevXtcvXqVV199tc9XNb0I\neNqJ+MjPvfeIv9NXu7U/Z7h1iefWrVuJiopi3LhxREZGIkkSOp2OhoYG6uvrefr0KbW1tcyYMcNu\nql9XMBgM3Lhxg8bGRvz9/Zk0aRLZ2dnU1NSQmpqqeOEKLxWNjY1YLBa7cQXl5eXk5OQgSRIJCQlM\nnDjRbXL1er385hsTE+O2fttz9+5d6urqaG5uJj8/n1mzZrlt1AOsiaUOHDgwIKczioqKyM3NZciQ\nIU5jbfoTpaWlAPIoYn/LxuppJ+JjrXudiL/RedaJcMltbXUGnCWHWblyJVlZWRQXF8vLpVpPlKio\nKHlOOi8vj7y8PCZOnNhpJcjWWvY3b95EFEU5GGvy5MkEBweTmZnJxIkTmTFjBiaTiYMHDzJs2DCP\n1l1QUOhL9u7dS0xMDHV1dR1ygoSHh7N69Wq3j8bU19eTmZnJm2++2eU33ydPnnDlyhVZJ51Ox5Il\nSxwGM7a9P1RUVJCcnNx9xe1w9uxZlzOL9gcePnwoV1MdOnQor776qkemdO/cucP9+/dlWa1ZWmfP\nnm1T00WSJHJzcykrKyM4OFhO6nX79m3y8/MBiI6ORqVSybFM+fn5LiU1UuifdHoHOH36NLdv36ah\noQEvLy/efPPNTjsLDAxk9erVToXOmDGDhIQEfve73/HGG2+QkJAgt7VNOSwIAnFxcaSnp9v1VseN\nG0dubq4c4DZ+/Pg+j/RWUPAEkiSxZ88exowZw7BhwzwaNJeZmcnmzZu75ZxcvXqV1atX2zg7hw8f\nBmDZsmV2baiurubgwYPMmzfP7TZGR0dz9OjRLseX9DYVFRV8/fXXNDc32yxLjo+PZ82aNR6NBbt+\n/Tq1tbUdasFIksT58+fJyckhODhYzpo6Y8YMZs2aRX19PRcvXqShoYFx48bZrUrb0tJCU1OTp0zp\nlwzsaBwn0xl1dXU8ePCAdevWkZmZKedRFwRBni+Niopi+vTpnQq5c+cOBQUF8t+iKMqBmO0v3Hv3\n7nH69GmmT59OUlJST+1TUHjhsFgsfPHFFyxdupSjR48yatQobt26xfLly2lpaSEuLq7bfVdUVMgr\nXVpzaRiospxyAAAgAElEQVQMBurq6mhsbASstSfefvvtbi25vnv3LteuXWP+/Pk2uSJqamo4cuQI\nMTExpKSkyPeFrKwsDAYD6enpvfbgbGpqYu/evUybNq3PMvTm5uZSXl4u/x0REcHEiRP7RazX7t27\nO4w4DR8+nEmTJsl/NzQ0dDveLTc3lydPnsh5UfoaT09n/NbfvdMZ7zf3o5iIrKwsli1b1ulN6ezZ\ns0RGRnb6hXelGFFb+ZcuXSItLU2Jc1BQaMPWrVtZvXo1ZWVl1NfXk5yczOPHjykrK0OtVvP48WP8\n/PxITU3t0o390qVLVFVVERsbi0qlQq1Wo1Kp8PHxITQ0lICAALc8yCVJ4tSpU9TU1DBixAiSkpLk\nfisqKsjJyUEURXQ6HfPmzfPY9X/48GEmTJjg0fuN0Whk586dTJ06tV+XGHj69ClPnjyhutr6gGpu\nbmbjxo1u67+xsZFf/epX/OIXv3Bbn91FcSK6Ro8DK1sT9rTWeBAEgQULFth40N1xIlo5cOAAFosF\nLy8vEhISiI+Pp6mpiaqqKiorK4mKiiIuLo6CggJu374NwP3799Hr9fzkJz9RloAqvDC0ZpFMTk5m\n1KhRZGZmkpGRYfccby0i1TrEPHLkSCZMmODwenjw4AG3bt3qtHx5XV0dhw4dYtGiRW5LB11YWCjX\nVlm6dGmfvnnr9Xqys7M7LGPtTXbv3i3nNOnPHDlyhOLiYsLCwvDy8mLSpEkMHTq0x/dXSZI4efIk\n9fX1rFixok+ru7biaSfid/6uJ2xzhe83V7m1P2f0eD2QIAjMnDlT/ttkMnH8+HE5XbHFYunROvnW\ndL4mk4mCggKOHj1KYGAg4eHhjBo1ipKSEvbs2UNUVBQZGRmYTCYKCwtZtGiR4kAoDGgkSUKv19PU\n1MS1a9fQ6/WsXbtWHlpuG0jZHl9fX1JSUuTh4QcPHnDw4EFWrFghz7G3Zfjw4Tx8+JCdO3fa3Mhb\n3zEEQcBkMrFgwQLy8/M5e/YsarWalJSULmWtbE98fDzx8fFyUa4NGzag1Wq73V9P8PPzk8u/ewq1\nWt3vHQjApsBhU1MTn3zyCYmJiU7TuNujsbFRznxqNptJSUl56epztEU1wB9THq3iWVBQgFarJTo6\nmrq6OoKDg3vtQf8///M/fPOb31QcCYUBhdls5siRIxgMBnx8fNBqtfj7+5OQkCCvYDAajRw4cICY\nmBhmzJjRoY/WNM5eXl4EBQWxZMkSADkBl9FoRKVSkZGR0aNgQovFwrlz56iqqkKj0TBv3jyHLwwm\nk4mqqiqioqI6tX3Hjh1uHSbvKlevXgVw+yoQe9TV1ZGVlcW6det6XZY7+eSTTxg6dKicKdXb25vY\n2FiGDh1qd/qsvLycy5cvywXwAgMDmT59er/NOuzpkYh/D3DvSMR3mzw7EuFRJ2LLli3U19dz9+5d\nYmNjGTt2LJIkoVKpGDRoEJMnT+7WiSVJEseOHUOn06FWq2lpaWH06NE2gT8KCgOB7du3k56e3ul1\n8Kc//QkfHx98fX0pKSlh3bp1hIWFyQ/0wYMHy3kDiouLuXz5sryvJElYLBZCQ0Pdutphy5YtTJgw\nweHDV5IkPvvsMy5cuMCSJUuYNGmS3XoNt27dwmQy9WlQ9enTpwGYO3dur8m4d+8eeXl5bNq0acC/\n6BgMBoqLiykqKrJJYQ7W4x4ZGcmUKVP6xVSFK3jaifgPNzsRf/UiOxEWi4XKykpCQkKoqanhwoUL\n8jKx6upqFi5c6DSyvDUyvTW3viRJGAwGFi5c2KNhVQWFvkKSJKqqquQH/jvvvNOlfT///HOCg4NJ\nSUmRYxXMZjN3796Vq6GGhIR0OgrQUwwGA1lZWej1ejmxlaPlmkeOHJEr8gLExsYyefJkvL29OXXq\nFOPHj+/zEtyFhYXk5OSwbt06t64YuHPnDl9//TWjR49WVp/1UzztRPxXoHufW99pfIGdiJ4iiiJ/\n+tOfWLduXb9Y+qSg0FOys7MpLS0lNjaW2NhYhgwZ0uMUzNeuXePu3btMnz4dQRDIy8vDbDazefNm\np/taLBYuX75MWFgY8fHxDqc77MVVtFJQUMCtW7cA65z/9OnTO5T+vnLlCvn5+SxbtgydTseNGzfk\nOiSulDX3BGazmV27djFhwgQSExN73N+2bdtITEx0a+ZQBfejOBFdY8A4EY8ePeLcuXNkZGT027k0\nBQVXqaur48CBA6SkpPQor4M9/vd//5dBgwbJBcKmTZvWoejWpUuXKCwsRKfTsX79erRaLffv3yc3\nN5f58+dTX19PYWGhXMSsNTdMa+ZYsDoSISEhzJ0716GzYTKZuHjxIhUVFfKooyAIDB06lJEjR3L2\n7Fmio6P79Vv5uXPnCAwM7PH06NmzZxkxYkSvpglX6Dmefvb9PtC9o27fbqx0vpEbGRDVWpqamrh4\n8SKbNm3qa1UUFHpMaWkpZ86c4c033+yV+XB7Zcnbc/PmTRYuXEhWVpYcIBcVFUVUVBQxMTHExMS4\n9PZdU1PDnj178Pb2ZunSpR3mvTUaDbNnz7b5TBRFnj59Ko+QVFZ69qbXVVJSUti2bRujR492qey6\nI1JTU/nqq6/YsGGDG7VTGOgM9NUZA8KJyM7Odlq+uC8wmUxIkjRgAoYU+p7KykrOnDnD66+/3qd6\nbN68mRs3brBq1Sp5hCAgIKDLKYjDwsJ49dVX0el07Nmzh6SkJKdvcCqVimHDhnUr42VfsXbtWrZs\n2cKmTZu67UhkZWUpdX0UXjgGhBOxbNky8vPz2bVrV8+XQ0kSiNYhWlRqaP8m6EJ7dXUVp7KyuFfw\nAFEU+clPf2q7iWgBox5JUFNZ10BERIRtnQGXdBBBEkGtBsFOdnVJBIvF2qZSdcsOa7sEKi/77UhW\nGWo1IPRARl/bKQKicztVKqucXrKzrraGY0eP8MabdkbUJAksZo/Z6aVWd6yG2SrDYu6ynVqtlg3r\n13P86FHyb9+Sv8umpibb5FSSBKIZ6CU74fk548bj6e3tzTe+8Q0OHDhAgL8/yUmTQRQRvLxAUMnB\nq/LIUjs7zRYLtbW17b6H/mdnh3ZJtOrh8Pr04PHs8b3ORTslyb4evcQAH4gYGE4EwJgxY+TMdl0u\n/GMxgcloPVEksU2DYB1LkoTnR1IUgTZhIoKqzcUjsf/AQSoqKvD29ubVFUutxcMMTUgtOjAawGyk\nsb6OLzMPEBk+iPDwQeTUNCCqVCSMn8TE8eMQJBzIePZZ60ltVwcc2KGy7i4Indv57M/O7bQjw+Ym\n5UhGGx0QQZS6aafUBRl9Zaf0rJ9O7JQkqw7P7Dx2+CBvrF2NYGjqhp1tZXT1vHXdTl8VNFaVERgY\n1C07F82ZZdN+8/YdGqvKiAjU9is7O+jQFgcyvIG16Yuprqri3q0bz2NDELCIIiUlpSSOG8ekCYkd\nZBw5cpRlc1PB0OzYTtpcGw7tdHDOtNrZ6T3ANTuffZFuuj67a2erGt2xU8Dm0dxVO1uawddzgfvK\ndEYvsWXLFjQaDVqtFkEQqKqqIj09nczMTERRZNmyZU5Lk8tYLM+85fZIz05ybM4x202sJ6kkSeze\nu49pU5LJvahn/bo1bfqwWB0IvbVAUYCfLxFhoWQsbjN06e1HQUUd+/YfkG8+0VFRJE2aiEqlor6+\ngbr6ekKCgwkLC7Wrg2PaeNp27Whjp6NtnMmQRMffkUs6uCpjINnpoJ+2Mp71VVlZRfigMOubqjvt\n7NF33fHjhfPnsvfAQdatzuiWne3bzcYWvAK0nVx/tnbevHWbvEuX+cabG62rVHrJTrs6dNrHcxmD\nwkJ5ZWbHJF8At+/c5cvtXzF96hQCAwJo1jXT1NSMydhCgL+fk/tQD66NtnY6PGe6ZmeX210+b3vb\nzk4PuAsynOyvYEO/dSJef/11jh8/jtFoBKzBWMHBwaxduxaTycShQ4fkmhqAnIXPbv51L29br9Xy\nbBjf+vrUTnLbz6wR6WeysymvqGTenFR8fHwIlrOyCc9kt5B96bq1yuGz4bkhw0dAUPizYUA1qFSM\nChpEwqiRsozikhKOnTgJQHBwEMFBQRSXlFBbVw+AJImEBIeQNGkiwcFB7XSkjQ2tvzvCuZ0d+3Am\no/1nzmQ40stVGX1lp70+um7njZu3eGXm9B7o4Az32Onl5UVdXT3uOp5jx4zm1Jlshg0d6lSHYydO\nMigslE0bN7B1+w6+8eZGO4Gnnj5nHO1jX0biuLEkjhvHtes3qKquRutnzTi6Mn1ZJ/11TYZr7fb6\n683r05X+eirDXfcAe+1tZXh2aEA1wCc0+q0T4e3tzfLly+22aTQau4WCzp07R3FxcccgTJUKVG3y\n05uNYNTj4PVJ/u3K1avk3y9gftoc5s6xZgDU6/VIkkRFRSU3bt6ivqEejUbD3NQUOQGWc6wyYqKj\niYmO7mQ7gbq6Wq5ev05tXR0AyxYvapf8xpWLtnM7O293dGNo/5kr2/RERl/Z2ZU+HOul0+vw89N2\nU0dX6LmdkiSyc89e5s+d46QPZzo8l+Hr64uhxeBUx3PnLzAkcjATJ4wHYGX6Mrbt2MXG9a92okN3\nj6ej/jr7rCsyJJIm9zQXxMCws2v9dSbD0f59cQ/o7jXYPZTpjH5EVVUVKSkpgLV0bU5ODsnJyWjU\nKuJiY7COREjykGLR02ICAwIICWl9+Nt6umNGJ5B//wGNTU0MwZosx8/PD0mSeFBYyCszp9uZUml/\nwdnz1l3927oOf17aHMA62nL42HFrxcNFC9s4E8KzPaRngYoW62iLxWRt89I8CyiyBiYJDj3+rtxo\numpn+31s7XSNnnyXjvSm3Tb27HKHnXA86yTDhsYyNDbGSZEpT9n5/G+z2cKfv9zGimVLCQ8f1A0Z\nnR/PM9nnmJCY2G6qzrrPrdu3kSSJiRMmyH2EhYUyPy2NbTt2seHVtc9GJHpup2fOW3feAxz1Sbtt\nXnQ7O5PREzvb/u1Z5+FF4YVyIkaPHi3HTERFRbF+/Xq2b9+Or1rFuVNZRISHU11Tg4+PNyqVinPn\nc/mnn/2kTQ+2J5FWq8XHRyNPqbSybMmiTrRw5p139e/neHt7k7FiOS0tLRw5fgJRFJk9cyaDBz+L\n+NY3QXOdY9UEAQbFOJDR1QuoO3b09I3bHd+lq29f7pJh/X3V8nSam5t5WlxCzoU8Hhc94Z233/KQ\nDs5l1NfX2ySScufxXLNqJbW1ddy8fZvCR49Zv24Nfn5+3Lx1i/z79xkcEcGclNkd+oiMjGDB3DS2\nbt/BGxtecxAw3zfHs3dl9p/ztndl9r6dZWVlnLtwAW9vbznLakVlJcuXLCEqaoiDPjxLF5cJ9DsG\nTMbKHmEx09LcSG1NLUMiI0ASyTp1molyjv6OXu2Dh4Vk55xn9crlhISE4tqJ5siL7uqcnDNP3Npu\nNBq5ePkKlVVVgIBKJWCN+RCRLGYE0YQkQcrs2QwaPNg6GqH2ejYS4UzP/mOn/c8dzY8606Gzz7uq\ng6NtnNtZ8OAh9Q0NTE1OdiLDc3ZKksSxEycxmU0sX7oEoe1KGjcdT7PZzK7MfXh5qUkcO5axY8bg\nzM7q6mqOHD/BGxvWO3AkXD2Xuns8XenDmS6uHE9wXc/OZPeHa6Pv7ayqqub4yVM2U2JPi4u5ePkK\nazMyHMq4d78A/AI99uz7ImSwW/t7s67Crf054+VwItpjbmHv7l1krLCNuairqyP7/AVaWloYER+P\nTqej/Fm6XpVKhU6nZ/XK5W4tyNObSACS5GBuWaGv+fKrnf3yuFRVVXM2J4e1Gav6WhWZqqpqTp45\n22ZVlIKCYyRJ4rM/fcHbm59nhS0uKeFMdg5TkiZTU1uLIAj4a7VyHE4rnnYitrrZiXjDw07EQB9J\ncQ1JssYImFqoLS9hx/btDG5TJTD/3n12Ze7lyrXrLF4wn2WLF5Odc56R8SNYtzqDNatWMnvmTCwW\nC4+fFPHcA7b7WuRCuyv0XIYACILA5IkTuHb9Ri/I6B929r6M3tEhLXU2J0+fAcBiEXn0+DEFDx7i\nwK/vlozutIeHhzMmIYGcC7l9oIN9wsMHMWvGNPYdPOQGGV2R3b/Omf4noz/o0JHci5dYvHB+m9U9\nAk+KnhIWGoogCIwaMYIRcXFcle+L7rCje6gEwa0/nuaFiolwiNmIWd9E1qkz6A161mWsRKVSIUkS\n167fIP9+gc0boY+PNao8IEDL9RtfU/DwIcFBwbz5+vpnJ6WjeWPafd6TuTb3yRg3dgxHj2dx8vQZ\n5s9Nc6OM/mVn78noHR2io6J48LCQvQcOWlNBx8aiVqvZd/CQ7EhEDRnCtCnJLiZYc5+diePGsnvv\nPhdkulsHxwyNjUWvN3AmO5u01JQeyOiK7P51zvQ/Gf1Bh46UlpUxa8Z0mz7a5/Ywm81tls67w46X\nkxfeiaipqeHUieOoJAvz56QSHBzErdt3uFdQAEDSpIl2h5S/uflNjp04ScKokby6ZrWn1XY7SxYt\n4GlxMX/+cjvz0lKdLC1V8BTWgEJbxieOk38vLikhc/8BRFFk5vRpxL7kFSAfPyliUrvhZwUFsE5h\nSEY96Box1ZRTmX+DQRGDQRuI4OMHCNbVayYD5pYWPt+2gzdeW4NkNIDG+1kMkOfx/NiBe3lhYyIk\nSeLKlSuUlJSwfPlya6liSeJx4UMe3s9n/pyUvlaxz/j8z1sdJPJR6K9Yk56do76hgZXpy7qe+r2L\nlJdXcPHKlW4kSepdWkdpFs2f52SZrMLLhNhYB+WF1hxAWK+XLw6dZNPyBdYNvHwgNAJBArPZxJZd\n+9iYkY5fazE1QQVB4Qgab4/HRHwVGunW/tbXlru1P2e8MCMRFouFI0eO0NLSglqtRhAEhg4dytSp\nUwHIzc2lpLiYQH9/Fs2d6yD97MtBWupsrl67zpTkpL5WRcFFBEFg7pxU6uvrn8UFWImOimLalGS3\nOoQPCx+Rd+kyr7/Ww2J3vcCq5em0tLRw4uRpmnU6liyc34UkbwovLNYAMFpXZgiCQFCAlsLiMuqb\nmkkaP84aG4dAbX0DIUGBHM++QG19PZvWrESteTnCA3uDAT8SUVNTQ3Z2NkajkaVLl2I2m8nOzsZs\nNuPr60t4eDjlJU9JHp9ITPQQ5x2+JHy1aw9+fr7MTU0hMDCwr9VR6CaPnzzh0pWrCIKA1k+Ln58v\nWq0WP19fQkNDGBwRYa1B4QJGo5G9Bw4REx3lsDZEf0IURQ4eOYqfrx/z587p9dEZhf6NdTrDALpG\nMBnYkbmfoMAACkvK+cvNr9ueHyo1aHxpMrRw6NRZ1r/2muyIe3okYoebRyJe8/BIxIB0IkwmE8eP\nH0ev1zNo0CCmT59OdnY2TU1NhIaGkpqaanvjNLWAyeC4w5eUlpYWjp88hcZLw5JFC/paHYUeIEkS\nJpMJvV6PXm9Ab9BTU1tHRUUlT0tK+PZfvG13P71eT86FPBqbGhEEgaWLFuLbOsQ7QCgrK+filSty\nMKooiiRPnsTwYcP6WDMFT1D46BG5Fy/j769FkiSam3XMnjGNYWEBNNfXknkkizfXrLDdSe0FwREI\nKjW379ylobFRDsT0tBOxM8y9L7ev1pS5tT9nDDgn4vjx4+Tl5REfHy+nnBYEgXnz5jl+o26tWS+a\nsSZjMj8b2nIUidvT5DWu9tMZribI6bmMg4ePMX9uqp38Fy+Wnb2XSMiTOnRdxt4DB5/lRLFtz845\nz5Vr1/nm5jcJCmpf4G3g2dm2/UJeHlXVNaxMX9pNGT3Xof+ct67I6A86dE2GXq/nwOGjRA2JJOWV\nWTZ7nDt/gbr6epYvW8rNmzd5WFgIEhhajKxIX4p/QIBNQOOpM9nUN9QTN2w4fn6+ihPRBQZcTMSM\nGTOIj48nLi7OGizpCoJgrab5LLgSwehkZMLZxeDqcqD+texp74GDRISHo9fraWpuZtXydARBYHzi\nGPYeOMTajJXtKqD2Dzutt4/+8F32Bx26LkMURbvtqbNfQaVScevO3XbTFwPTzrbts2ZMJ+vUaaqq\nqp/VAnE3/cNO98noDzq4JkOSJI5nnaJZ18zqlcvRaDSyi9GKSqViRFwcAjBxwgQmTpiABIgWC3/+\ncjsr05fZ1HGZl5YqZ2wNDg4i1M9zU7wDPbx9wDkRQUFB7d6aXMBiArMJuQCXTS35tt5td73trrTT\nzT6c4VwHi8XCiLg4AgICOH7ypDwHOHzYMCIHD2bvgUNERw1h9qxZ3dTRPXZKFhOYjNb5zRY9NNUh\n+fmDbwB4+yJofBA0Pk76b/+7o23s0d+Opz0Z7rFz9qyZ7N6734kOrsjoSzvtMy9tDv+z5U9EhEcw\nJWkSsTGxDvbvL3aC+2T0tp3dvTZ6bue2HbuYn5bK4PAwsFiQdAZoMSCpVaDxAS8Njx89YtaaVYjN\nDWDSP4uTMCIEhPB6+kIOnT5JxuJFYGhCamqA+kqoKGZBRCy/23eAFX/xbpf16i4DPZJnwDkR3UKu\naGkPycHv9rbprXZXt+kM5zoIgkCzTkdk5OAOWRF9fX15be1q8i5d5t79+4xOGNUtGZ23u7aNVP4E\nGqpsP2xpBqzpXKXwWIRwR/kSunI8u6tj/zie9n/vuI23xhu9Xm9nusraPmxoLI+fPLETQ+COa8MZ\n7rDTPiqVinfefgtRFDlx8jT19Q02OTi6JqP/2uleGa7a2dN7oSsy7LN4wXyuXsxl4bR25dYtgFEP\ngI+pGanwa0DCaDLxhz2HiY20ZiluaNKxcEYS0rm90FBj04VQV0Fk/dNu6TUQMJvNfPjhhxQXF2My\nmXj33XdZsMA2Hk6v1/Otb32LX/7yl8THxzvt8+VwIryeBVm2KwXe0Vu25z131Vtuv70zGd3RoXsy\n1qxayZnsc1RV19DUpLOr97Qpyew/dNiBE9Fx+67q4IpdQtQIGDwMLCYk47OgWLUGNL4IGo01KMpt\nMp3hjuNnr8+eH09X7Vy0YB579h1gw6tr7WozJWkymfsPMnzY8B7KdIYnro2O8lQqFYsXzmffwUOM\nT0x0g0xneNpORzr0VKYrMjx9r4NBg8KobjZAWLT1nt76kigAag06g5EWn0CEhKkgmjl/6jSvb3qb\nMElnvf8LgCQiWcIRRBHJbIIWAwgC+AcxZfCYLnwHPceT6Xr27t1LaGgov/nNb6ivr2fNmjU2TsTN\nmzf5h3/4B8rLXV/hMdBHUlxDpQZvX/DRgq8/eLe+kUl09IzbX0Rd9Zbt7d+ZjM7+dnRhd19GWmoK\nzc1NmExGTpw83aFPlUpFYEAAu/fu4+TpM5hMjvJp9NTOtn3Y2ikIAoKXBsFHiyowFFVYFKrgcFTa\nAOtUhkrtoM+eHE9HV3JPjp8jGe47no5lPv/b29ubhJEjuHnrNvbsFAQBi8XsBplyjw4+7107O+pg\nr603jqc9Ge6W2R/OW3sy3C3Tud1GoxGT0YigUiGovRC8fRD8AhB8A5DUGrbvzmT9urUIajWCxoeJ\nyVM5duk6kiSCucW6Ws9sQpBEEEDQaBACAhGGjUYVHoXg5+/A3t5BcPO/zkhPT+f9998HrLFSXl62\n4wgmk4lPP/2UESNGuKz/yzESIYpWT1USn6/ScEj7eUOwPZHbz+l11t6+P2fy2n/mLhm2zJ+bxrXr\nX3P42HGGRA7u8HZmra8hUFdXx5+2fslfvPUNN+jgie/SkVxPH8/eluFIrmM7k5OS+GrXbsLCQomO\nirZpb2pqwsfH104fA89ORzo0NDRQX9/gog6ePmfs4W4dPCHDM3bu2J3Zppqr9bOmpkbOZOdQV1/P\nq2syUKnVSJJEZUUF53PzaNE1U95oYMigYLBYnweS2fR8JMKgh8ZGpIBgJF2zk0fxwKV1SrOpqYn3\n33+fH/zgBzbtycnJAF0qAvhyOBFmo9UDdYn2nnJP2h1t46zd3TI6kjR5IkmTW+cU7csICQl+VqBm\n4Nr5shxPV2SsX7eGrFOnuXLtOsuXLpGT7xw5foLVK1e40IczHfuHnW1/b2xs5FjWSSQJkidPoqXF\ngI+PT5f66Fm7o22c4W4dPCGj9+18WlxMY1MTR46fAKxv06IoEuAfwIJ5aXKOE8lihtpyLp05w+ih\nMYx5Jckmq6skSXDmAFJ5UUeJlXUwynPZfD3tsJSWlvK9732PzZs3s3z58h7393I4EWo1iF6ACGLr\nG35XaPWWHXnaztq7IqO7Orjajys6PO/DZDJjMpmeJe/qGzslswmprAhKHyM11kJDHXh5IwSHQtAg\nGDYSISS8C6mfX4Tj6YpuHWUsmDeXuro6vvxqJ2GhYTTrmhiTMLrDsKbruMvOnvBchihauHe/gHsF\nBUiSRE1NLf7+/gQHBXHuQi6BgQEMGzq0RzJ675zpDzr072sjNiaG77zzF/J2kiTav+6fJZNKz1hD\nbl4e2w8e48yFi4SEhvE33/8rwsIjYf46aKxFqquGpw+g5BFotaAO6KZd3cOTTkRVVRXvvPMOP/vZ\nz5g1a5bzHVzgJXEiNNYfAEl6Nifm6sgEPD+RHZ34ztq7IqO7Orjaj+syLBYLGSvS2bZjF6+tXd0m\nk6Fn7ZTOHUa6mOW4p2EJCOv/qhs6DOTj2ZU3TdttQ0JCePP19dTX17uh7oS77OyZDvX19Rw8coyA\nAH9GjxrFyvRl3L5zF18fX5YuXsit23d64EBYZdj+39V2d+DJ83ZgXBuOXhwEAI01541fcBjqoDr+\n5ZNP0LZZoSSEDYawwTAcmDybhpzDGKuKaWyqIsQFKwYi//Vf/0VDQwOffvop//7v/44gCGzYsAG9\nXs/69evl7bpSi2fAZazsNpIEosWarVK0WH8cnqTuepvozbcSd+BYP6PRyK8/+TcmTRhPQ2MjDx4W\nMjgigsER4Wj9tMxJnU2AVmuNMREEUKlAcBbW0z3EGxeQbl2EhlporHuus5c3BAbB4FhU6W+AygtU\nKjs69N7xlAA5IyrI30X3v4fefMPzdD+9JcN23zPZ56irr7epblpeXsHlq9dYvmwJVVXVnLtw4dmU\njbGOFNYAACAASURBVKfpD8fTEzL6n52iKLJ77z5GxMWRnJQESEiSxJFjJ2hobMTbWyMnLJQkCb+6\ncnxaGnlU9JRZ7/yNx559B8Oj3Nrf8qpSt/bnjJdjJKLLtTPcdUL3ZwcCOtPPGtE/krSUFEJDQ7BY\nrMPEjx8+oKq0iN//398xcewoFqbMeu61qtRIfgHgF+hWZ0I1aRZMmoVksSBVlSE9ugMqASEyBvz8\nrfLrKp7r4O0HASFtdHD/8ZTMZjA0WdelixbbzQQVkrcv+IcgdLkoVG++4Xm6H+cyDh05htliDXSW\npOdvlhaLiEolyH+3fddp+5ZkNpuZmpzUYYThWNZJNm3cgCiKfPr7/8f4cWO5ees24xPHubXiqXP6\nw/H0hIz+Z+evP/430lJnk3+/gEdPnqBWqzEaTcyZ/QqRkYMd7hd5926v6OOI3nn18hwvx0iEqcUa\nXGmTqVLBGSaTiZwLudQ3NNDY2MQbG15DsJjA1EL22bPodc3U1jcQGT6IOdOSrNklLWbw8UfwD0II\nDEFQu1ZBsitIZhMYDdYfsxH5JiQI1tEJbz/wC+jVS1OyWKz2mg3W86vtZaT2Bh8/8PXvhhPxciCK\nIlu372BeWiox0dE2bcezTvHV7j0sWTgfjUaDKIokTZpI3PDhLvV96sxZRo0cQWxMDHfu5lNZVUVa\nagr/8m+/493/7y8ICAjAYrG4njZfYUAiSRL37hcwOmGUy46jJEnk3/oaVUikx559h8KjnW/UBdKr\nStzanzNeDicCng85i88Sk3S6zFOhPQ0NDRzLOomXlxfz0+YQGBTE5StXefj1VSIwUF5RSVRYECkT\nxjy/YNUa8NGiGjcToRdu2PJUQuspLKg8mrjFRo+20xm9NK3zIvDgYSHXv/4aSZJYumghWq2W+voG\nauvqqK2rIyw0hPi4OJqbmzl6IguVSoW/1h+1WkVNbS0Tx4/vNBFaXV0d2ecvsDJ9WYe2k6fPUN/Q\ngNlsQaUSUKlUSJLEimVL29WMUXgZsTy6BfVV3HvwEPWM5R579h12sxOxzMNOxMsxnQFt5u3pOPys\n4JSgoCBeXbMas9nMF9u+YtGCeUydkkxyTBg3zxyn1GImbkgEX57IYdb4BOKjBludNaMBaC2i1RHZ\nEXDw4JUf0HbiDASQH9p9iQDWc0vBITqdjq927SFp0kTWZqzi2vUbHD2RhZeXF2GhoYSGhBA1JJKS\n0jLyLl1hftoc1masAqxr2vMuXbYWWupk/XrBg4dcvHyF119bZ7fdmv/Elt179ykjEgpWzEbr9GQX\nciS4gz6+ffWYl2MkwmyyrsboUHxLoatIFjOisYVLly9TUvQEvU5HeGgwlWWlxA0ZzKxxo9h17CTr\nFqZaPQC1CkHlZc0UGhBizRqq8bFmi2u9aEXRGhTp7WeNqFaprJ+1tlvMIKjAxxe8fKzLO73cP02i\n0DvU1tbJ5cjPnDuHxWIhadIkRsTHddhWkiQOHjlKaEgIs2fNdFnG1WvXKXz8mHWrM7qk27/+7t8Z\nFBbGzOnTGDM6oUv7KrxYSJKE1KLj3rUrqGJHe+zZdyTCvSMRSyuVkQj3I6/GUOgxLXpU+kZmjB0B\nY0fw+607EACL2psKnYmHRSWozWZEBNRez97wJBH0jdYftQbCYzoWRBPNYGiElmdxDWaj7RuBJIJB\nB+jAP+R5PRSFfk1JaSlnsnMYER9HTm4uy5cueZZzpCOSJPHHz7eQsXw5ERHhXZITFBTE4ycdEwc5\n4wff/y6SJLF77z7FiXjJEQQBwdcf1SD3rpZwKtej0tzPy+FEaHysyUcsZuSCLQ7XIrdPs9qdoa22\nyVIcyZDs/N5ZX65+7qqMbtqpDbT+iCJIFmaMjEe4kUuivwYqa9i28xYTBgVR8PQeo+KGQVAI6ozN\nCP7B4OVlrWMiCM9jVFpTkatUz6ab1HKztWCaxXq8BJV132dLSXvdzg59eOp4dleGK3Z2JclPd3Sw\n3Tb/3j3u3ruHt7eGwRERzEmZ3akMQRAICw1r40C4buf+Q4eZNyeVr2/ewstLg5eXGkEQaGxspKGx\nkdCQECaMT3y2BFTg+o0blJaVs2zJ4mczYgJGo/FZbMSLdjx7IsOZrBfNTs/TkwXh/YGXw4kQBKsT\n0Vr9sXWY3C6Sg9+7grNkKV2R4Uof3ZHhqg62F518uqtUgIqJWg07c8+TOGIIAEtiwtj1oIwxOj2j\nBCP4ahGCwzsGVgqCNZMo9uejBQGr44DqeaIwu/SOnfb76Lzdeovq6fHs7jnjip3ObqLuOm8FTp89\ni9Fooq6unv+fvfeOkurK8zw/973wJi1JAgkk3iNAIIMQTggZQAiJkkqmVNXdNVt1pme2p7e7t2b7\nzJmZ7tndmd2a6tnT09M7p3eqT1eVquRKSAIh771BCIGE9ySQpHeR4ePd/eNGREZmhs2MiMwk4ntO\nQMa79/3Me/e9+N3f/d3fb+f2bVRXVw05L/n5g9eHs9fzxz96Iho0GSYcjhAORzCMMHV1k5g7Zzbt\nHZ389//xj8xqnEk4HGbm9On4A/44DafDic/nixoR+Xw+C30/0yFfz0Y2MlwvepaRK0rDiIhEIBKM\nRtAbA5H0w5CNFcuQPpnaU9FNxyNXGRJ5pGrPJE8qHnJQu0wsYhYJw8IlmFetJTJ/Brq3j+ruTjbV\nTmPe3LmI6jqorkNGIlEjYuLomYmHBDWuZLS4WzgEEqTZHE16pYOuR/eAj0bPVHqk6puJR256pkdy\nGv/P3/03pJTMamzk8Ue+j8k09N6nln1KfT2Xmpp49/0PuXnNapYsXpS0byAQ4PkX9/L4I98HwOVy\n4XK5k/BQfK+1tHLxUhNVlVXce9ed1NRUc+S7o/FAzZ7e3jTZO4vxDsjUNx8yZMN3tDzy7TVIx6PQ\nehYHE9sPQYkEVgb9Oaa5Tobx4AYrhgzpecj+HhXbkIBvT5zC6bAzZ+YMMFkRVXUFlSE/GB0PGQpA\nT1v6TjXTMuSJGP96jgSJSaNylUFKya9/+xQOhwO73YaUErPJjCENNKFx791bMQyDX//2KSoq3Oze\ndX/OPGI4feYsR48fB2DdrbfmHIcxHNfL/Rzp0kYxZSgcTp0+A3Z30X773qlryCu9LW1X8kovE0rD\nE6GbATnOPRH5ss5z5Zctj+gxRwXYXNFg1TBGdxuzelr47IMjNM6aAn09atmoqhZRWYOorIVVt6PF\n15qz4DHuZ3RCxdlUT416IsJRTxeQ6ImIrr+PmMcY6Gn4vHD+GNLbC/3RD4CzApyVCKcbps9D6EKV\nVDbCIGVUX/UxAl6E14MM+tSyYTCgrpfFhrDawFmNVpU87kEIwfJlS/nm8BHa2zuYOrUel9NJZ1c3\nU+rrAXjm93vYvWsnl5ou89yeF9l+z904nY6c9ASYP28u8+fNJfOzc72M22LwuJ70LA4m+hbPEjEi\ndNAHCq+kjolINhjlKNvTHS8Uj1z4ZTo/9hCqYyIWy6DrgAXOnsJx4F28Z65CqH3gtCvn1Vk2O/rq\nDUnoFupaZuqbnZ6ZZBAwENNhMgP2Qa+kkcmQ6bxUyKOeF08gD74znFyHyscvhYaorQctzZuv9TLS\n0zX4WNR7JQFmL09oGC776lUrWb1qJd9+d5TTZ8/SfO0aNpuNzq5O9r3yKnds3EBFRQVOp4NQKMS1\nlhbmzpmdm56DMNpxOZb3MxcZisHjetOz8JjgNkSJGBFSRtfwY2vYEdJb0rHjI3WpZVqzy3Xmk0yG\nYvAYTldCNIdDCBn0I91uaJwH7X5wV4HXo0zrihrljaiqRYbD0bwOmfQYP3qORAYxRAYppTJYfV5k\nXw8yFEDYHAhXJdjsoJsTZiEj01MqRgPZWJHxXS6xBFiDX1IZ9KybBnOXR70QPdDfp+6nww2uCnBU\nKk+T2RL1wISjPHXlgdF1cNeAxQYBr1pKDAWUoWW1g8WOihMRnDt/nqbLl+np6yOWw8UIh2lva+OP\nHn+EZQvmsmzxokHF3cLhCAcOfs2Hn3wajbl4OIUu2c5OU42ZdO3ZoFjjNhsZisGjGO+6TDKMhkcZ\nI0VpGBE5lf7O1dJNR6NQM59i8Uhy1sXjyIvHozUr1CMZnNaAua0PVi4FqwOx7Ha0ypoh6+Kj1aO4\neuZDhsie/w/OHR+UoyTearagPfavEFNnjpiHlFIVHhuacyMGIaCqfmBXUkZItNopcNu2OH3p6QYE\nwlWZtP6ANKJbcE3meLvurhloj0SQ/n6EzT6ojophRHj2+Rf4Fz/9Z7hkkOCVs7zx8eeEQiF233wj\nXDqm/AhScvpKC8f7NYQmMJlMrFm1irW33JSlTsn1TP53tu258BgP47YYPIrxrsskw2h4jB0mepL8\n0jAiYuu15YyVo8fkGQhHBbK/G9qboa+Ti+1dNDY2IiZNA6sd4etFhgNImx1hd4OUyJ426G5H+jwQ\nDiNsTrXOXjsVbA4I+ZQXIxRU8QW6WSWdcrgRVkeRKy/mB9qtW5ELVij3/snD4OmBmimIBTdA3VRw\np9oNkIg0MychVOItI6wM5aBfjW/dpDKD6mbUNtkBSMNAdrXB+VPIzmvQ3QV2B6KqFmbOQ0xrBE2o\nmIhArPqtQAa8SKsd4XAjEowSEXu2EnlIqQybUBCMCMKIgN+L1HQCEclbH35MIBDkxz96goqKCt7/\n4AM6W65x1/adOIwg+Hrp6Orhg8PHwWRh0fx57LxpBZrZonhZbEmCN68HlMosuVT0zA7pVgYnAkrD\niDCZ1SdmRMR+qMrIGZrdBXYX1DUgG5ciO69w4eI+1i9diLBaAQk9rfH+hgQun1EVLxMQf4XoJsSs\nxWkXBuXUuYjK0UbOFx/a9DkwfQ4AcsuDatyZrTn++KV+2QoAixWwgs05sNSUpM5IDMaL/4T85lO1\nJTUZlxW3oN14S8oMr1IzwbxV6Xed9HZEjQ8Fn9/Pp199Q6/Hg8Vs5o4778ZZO3A/+/q9PPiw2qoZ\nCoXYu3cfFSaDXffvHKhrEfIn0BRQM0Ut2VxXKJUf1lLRszRQGkYEJKwbh8veiDwgviKvW/CGItgd\njuE/PJppYFaMUGvkidBNyiDRdJXNMpRQ1jsGs5ViF8QpBITQVJzACBA3DoxoLI+uKXqJfSIR5Ykw\nDLBYkCbLIGNFeQfCSKsFXJXKK5JoSAgBTrfiIaXyYAx9ToQGGBD0Ic020PRBkeUy+ozJqJyffvU1\nbR2d2KxW1t64gsoKtxoTDvsgsr29fXzw0cdomsbV5mvsuOtOHBE/yMjwnVRCKBoTf0iUUQZQDqyc\nGAgForUYysbDaCFDAXU9A95oGnGJYXVC1eSBehdWJ9idCJsLTddh7gpkJIzs7YCuNmUsuCoQtdHl\nDyHU+nvQD94+Fb9isoCjAmGxXYdu6+xgBLzg6VYff//A+BUa0u5GOtxw5QJca4ILJ6K1RVQ7tVNg\nzhKYOUcZC10tEPQhJk9C1t0JPi90dYKnV/V3ucDlQmga8spZdczmVEXPBODzQaBfLU1djra7q2HS\nNERFjfI09XfHDZPPvz2O02bntttvhspahNWhgjF187D7+dj3H6Knpwe/PxBNjQ1QqRKbhYJRmjIa\n0GlVSyhllHGdYKK/3UrDiICyAZEvGBLC4fgM8cDh77hpxTLl3ra51MfhGvZgCN2EqK6H6vqkZIUQ\nCKtdRfBf55CRCNLXp7YZW2wI++A4A2lEkD0dyKZTamuk3QnmAc+CNCLQ0w7tV+HscehqHzAgVAdk\nSxPy8kWYNBXq6hC1tYho4SshBDicajeNrkPAr/gkzvqj5dmJBUn6rwzyCEkjgrx6iciBr5C6Bb1x\nBvq0aQizmbaubnr6+rll6QJkZ7MyDGumIKrrEabhr0whBFVVVUmOR703I/TglFHGSCCNyIT/YS8m\nSsOIMKvy0RgRNXuOV/VM5RPNV+DPeA8gyl0+YbWB1RZ3sTvqu/CaTFDbEN+GN/4wPu6n0XIBfB6V\nfMkIx49LXUeabMjuDrXbor9P9YtBN4HVjrRY1TbLSER5g6QBtbXqo6lHOfLZp0iPB7xe5R24eEnR\ncLrBXYG2dj164xwGJV2zOaCyVgVU2t2ISdMR0aJ1ccNl3kqIhDH8Prz/7n9FdnZidHYpAwSiO0Gq\n0WpquDSnkcUzp0HTmegSFcizR5BmizIyZy1Bb0xMZ13G2GF8PBuFR2b5jLYm6O9BNp1FLLq1OGIx\n8XdnpMvJe30hVoTLbI1Gk6cbUPl6GMbzQwWjkU8AQtNYvnw5x0+dVp6E/AmWE6SUGcImxv5+Sona\nfeLvH2RAAMooCPSDp0vteEk0IEAZvt4+pKdH7W4J+oZ71owwGGGk1wtdHcMCWenvg2tXlFFghIfH\nGqDiGYTVgbC7EKbByw5CCHXMYsO4chWjuXnAgIgp2NWJcfYM8yZV8PXR47z65WFauhNSpIeC0Nc5\n8VP0XVcY+2ejOMhCvoBPPZ+RcOa+eYSqIpu/T7FRGp6I2HYzjOh2gVwHfC4JkUb6MGWbUCWXxCsj\nlSE3Pc3mdFU2c5Uvs54yEkYG/GpbqL9fxQwA0lWjYjHMVrAPX1LJnkd+7qfR3Q7eXmRvJ7Rego4W\ncFeAqwpsToTNEd01FE2AVluvPAZ+H0TChDs7CTa3EeroIXC1Bc+3p8FsxrVqKdbpUzDXVWOfXo8w\nRcvch0Poa29FdnYjvT7w+5BdnWq3RrRQmPz8XYwpDTBlBlRWIaonIdzV0VLs0W3QXdeQVjvoFqV9\nb5eaoXW1QdMZ7JtXY3R6MHxBDF8A6fcj3C40qxnNbSMQ6KPGrPG7L49is9mpb5wNFbUIuwtcVYhJ\nU9Nc85Fd6+I9G4WUYTy9Awopw3jSc4CGmDpHGel9yXcmlZEcJWJERIbP/nJCtglVRmONZ5tQJZfE\nKyOVITc9U9Rwy0BjpDKA7GqB9svDG7qaoUstD4h5q1Oa5VIa8TX/5EGb+bmf8ut34+miB2RsVx9A\nLroRwYBHQGgaOFRMCUD/dxdp+R/PI0ODx27XGx8BoDnszP1Pf4pI2K4sbDbEtCkDUly4CFfOq3el\nSSiDpbkJmpuUB2fDveh1DYNLtUc9HwCysxU+f3PQtdSddnSnnYhh8MnpJppDJoK9PVTarNDXh8Nq\nRtc0/vN9t+G2WRELVqPVz8h4vUaOYj4bhZRhPL0DCinD2OupqhGHQRtYshO6CeGqQquaPGK6I8FE\nXw4oDSPCZFEvQWkQL5iUEonWbWK6VJIcy9Q+lF62yIVHsvZseeRHT8MwKKSeRn90h0JsZ0goEC1y\npUV9eBpMmo6wWEG3qGDB+I+ekkt6eweMyUg0JkbXkXq0WJbFgYgH8OV6P5Prrm3aDaEgMuBVyxG9\nnWDS1U4FkzlaeyN6bkw2oUWTRAmqHtpNxc77MPr6CXV0EmppA38f5tpqTFUVaE4bmsmkdlQYsUJg\nETXedU1dgmmzEZENyGAQ6evHOHoYea1ZFc8K+GHv7zHefBVRXYuorAa3G62+Dvo9ypDo71PXymIF\n3YyUkm/eOcSJa518cKEJf7+PDn8As93KY/Pn0TilhvmP7qD6xhvB6VZJxcyWHK5lJhTj+Rwv74DR\nyJCMxvWqZyp6g48ZbU3R3T4BCAbV82ayIM1WNUYr69Ds7gQ+xcEYrEDkFaVhRGgaaNaB7ykLcMHg\nAZhssObSnqpPJmR6KDPJkAuPVDSyk8EwDDRNG6EcWerZ3wtd14Y3xybxdjdaRc3w9kQaAd/w9NDx\n2g+obakjvp/JdReaBtZo5cqKGqTDlWTcRc/VdRWvE/eYqeO61YJutWCeVI2cMyNJ+XGpskLGaFjt\nA9uZZfQFpWsIuw1ht6lQiOYhpYIDfmR3h3pNT58OXUm8PEEV/2BEIvz63S+41udhpm5iutDYoluw\nhCBy7AznjsHCf/tXaFMbs7hOoxkzqc7P5dnJRKOQPDJhtDLkQmOkPIqpZ7b009Do7VATkETEKs0C\noqo+2nc0npzSQ2kYEUZE7TWPubHjL+pklnTi99ixXAbV0P6ZeKT7nuohziePVDRJ0icRA/07Ojrx\n+fzY7fYRypCBh7ta5YYNRvN9BAPKMDRboyWmrdHViTQ8bM5Bu3Ok34fh8SB7ujFaWzH6vWiT6tGn\nNiBqatEqqxDx8uUju9YyHEIGAxDoR/b3QV8HmCwqFiKaMwGBitOJhCHSr4J/Y4WsJGrcBnxIr0fF\nJgT6we4Gm20gC2s4hPT2qzLswSC4K1TJbqtNZRE1WaJ0NbQb1iCrapHdXcjuThWEKQRYreoahw2k\niOZj0DWVoMowkIZABoJEPF5umTEZt2k6LnR8Hh9hNBzTG3BOm4pj+rSEa5Difo7gWib/nowmQ/qM\n9tlJRyPzs5Edj0LpmW8eQ1FMPfPAo3pK1JMZVP9HQgPvELMFiYz3LiYmeh6c0jAiwqEUBbhGPstM\njUw0c/1eCJr501PTNJ547BFe2PsyD+9+YJQypOARS7UdO5qybkJqHiLhfADvv/8ZkW++SsnZ+r/8\nJdZNW7OQO/V345OX1W6EVD1mLVZBkSkgr16CE9+kbpcS+jwqEDMFD/GDP0FUVMeP6/MXw/zF8e+R\nL96HAx8AgQHPTsvVOI2IP0To7FVChoFZ05BS4jO87KpzqL51Duz/8Ax6TSpPUDKp8vU91bFC8yg0\nz/GiZyZMLD21mimDW8ZJ/ZWxl2B0KA0jQjcR90LE4iLiyLRumO54tv1ix9OtXZLQJ9eHOVse+ddT\nBgNo545hPn+UyOsB6O1UMQYV1Srqv24qYvaihGRKiXKOTE/13Oemp9HboQqABfrB78Ny+xrkigUY\n3b0YrW0Yza3oq25GmzUHrX4a2rTpg/WU0RgCIzzg0YilYNZ0pKYhL19ANJ1H9rQjYwGUVitYLGAx\nqUJXmqboRiLw7VdIezQrpNVKPyaOHj5Hy+UWOq910HW5GYswqK5yUuO2MnOKm4W334JWPx0qqhAO\nl6Lj7Vc5JlouQ18vYu4Sdd0rJyFq6lRK8Ug4OgPzg9kGZjNoJrTNu2D1JmR3O7S3ED56iNYD3+Dx\nRvD7DVo7e3BLwa9bW1hT6SIQCbD9jnWY121AmzYDra4e4XaT+X6O5tkY7bjNNOZy4VFIPSF7OdPx\nLuuZjZ4D75FUMpaRDUrHiIj9iEmpim8FY3vcEwdQqoGb7Y9dpvOzoT+SH9Z88chdT3nkM+T7e6m9\n1MKZjvPMq60Y3MtqQ/zx/5GDnNnyzk1PeewL8PbGv2s6UOVCr3LBrGmIFZtUGexUtPz90N+TWqxg\nEPnk3yJ9/an7zF80qDAVAF0Df7713ineevXzlKfPWrmUpf/63w5vqKyGqdNh8QqonjIo+2UcJrNK\nWEXloFekMFvUbpAp0wG4dKado2/8CoAL4RDHwyHutTlYEg5xpL2HNQ4nM//qP6Pbh2aRzHUGOfR4\nIcdtPnmU9Rzd+RNBz5G+m0aGiW6ylIYRMbT4ViRMems3W0t3tNZ8OkwEHgLqGmDectZNbuDlz7/G\nbtZpqHAiTRYMdIywhn7qBFrNJERlJcI6tIplkfSsrFPpk/390RTRUlkSVodKKz2IV5LzdQtY7ANe\niIQ6FspItcDcJdDXrTwQvd2KltWmskFWT0LU1KhYDk+3KoAVCavvVjtYrMyYNYWla1fS2dZFV0s7\n/j5lkFTUT6J6aj1T588iHAyiW2JBwmoNV0bjIlR+CZB2ZzzuQgihNDKiHjjDQGqakjta7TN+vs+L\ne3Ilk1ctxtfVh9HcQrhH5eBYNHkyfRYTS1asIBwIJDEisr1f42Hc5gPXi575mvVfT3oWF+NhSWU0\nEDLFJv9Tp04BsGDBgqIKVBCEAsNngGXkHdLv4/lf/F/M/uITGn1+tY0wEWYz+oJFVP7f/wXd6UxO\npNAyGoba7tnfqxIg2Rw5P8TSiBaGEkR/qIdU1AyHkM2XoKsDMXuhKjY2qKKmgeztQn72utp1opsY\nmtPC0+flbFuQitmzmbFwFmarhcEQanvq6aNw9bwKNh3ULKB6MuKOBxEmPXlpb6FhNDfBkc9VPouE\nLJan23v4py+P4w0JVm3ZRsPKG1i0fCmNM2fmdK3KKGOi4dTpM2B3F+237+C0xrzSW331Yl7pZUJp\neCJiuQTKRbgKAhmJYFxtwjjxLfdNquDX/QHm1dcQ7uiOJ0oSbheWpQsxNUxFnv0Go2qSqu7oqh6c\n6KjAEJqGcFWprJGjoIF1+Ew8Xom0rwNEBFnpBk8nEAFnJULT4waIMFtgyWoVi9DdBh3XlDdA06Gq\nDtfSWaysnqwKZfmiKbHDA0mliG2rraxWOzlaryoPh5SqFkbjQqifof42W9Q2tmiVVWlE1G6PgFdV\n93S5gMnKgxJWXrr5Mxv4j6tXs+/4JU76epkd8TGjrnrcBKOVUcb1Am2CP06lYUSYLOojpZqRhQKj\nzGBZRgyhD98m9OJvVVnp6Gx3baWZI33drGmoAocL845tCKsZEXMntjch25sAkBY7YtVmNGdFKhYT\nAtKIYHz3qfqxTpj1x1dezVbE1DnKeIgas8LhUsGR02apfhY7wlExqPAVAJV1SNmI9Hvg8ql4siwB\nUFunPo1zFc0Zi1Xq76Hlsu0uNfxPfQWtTYP3y7uc6jN1ujI4rPa4jOHTV/F1NLFhih357SdIix1t\n+brkcRdllFFGzhAT3IqY6Bk3yxg3GFgVm+e2c9EbIGwAVgvCahnx7FWVzfYiQ8Ec02uPM0RCyIBP\nlfFOAoFAxPI5pLpWhkxf+0XTo9k6Uz3Wscqdaa6jEd3FFEV1hYu7b1o50C6l8makplBGGeMKUkr1\nHgmHJ/Y7ZJyiNKYT4eBA6eQy8grzhjsxrduMcfUSxomjGFcuIXta2H6ziTeb29i1+VYEKnuiCkA0\nQ+1UhLMy5XKGcfUCsqUJLp+HiydVIKSuw+QZMHcJYuZ8tGmzxkTfVBCajrb89oHlDL8Pef642hHS\n3aFiMOQXSJMZObkB6qYhpjYibC6Q0bL03h710c1Iq1299Dw90N8FrZfV8gOo6+ioUIGiJrPyVkkE\nMgAAIABJREFUfAS8KolWd5vyulVOAle1CrAMhxVdXx9CSGTt1GjulLDaitrRBt2d0HJFJasSAtyV\nMG0mm2ZO4eVLnVA3Hax2VdysuwU0DWmxK14We3TrahlljA/ISATZ3aIKanW1qCVBpPK0VU0GZxWi\nZipamjwtxcJEXx0c+ytYDMTyQ5RREAhdR58xG33GbAxPN/L0ISp72pmi6Xx3qZnlsxpURyMCFjva\nzEXJXe5RyGtN8PWH6sc3NueNRKD5AnS3IasmQQojQspo0KOUKuvikB83FbfgBX8gWvFz5F6SYddB\nCITVjjRNRXa2wJVzynhIRDgEVy9Abxdy2lz1Ahk6OYqEkG1dhL/5Cvw9aNVVKjgy3h5W8Q9ON5iq\nVBbLxNLe4SB0XIXedmR1PSLoH7TEIjQNabZAMEjk2DHE1QsIPaEYmZRqd4nfp+5XRTWaeyBhFaD4\n+ftBD6hdK2WUMZ5ghJAd11Sq68Sl61AQ2q+ApwdRXT928iWgbERMBJgsKilQ4hZPmcYtXN7iOeJ2\nzVUFqzYjjQjr1oZ45513OKZbWbponroHAvD1gq9P7S6IzqqFyRKnod+4HrnqdggGkL5+ZMCnKuw5\noqmch3guZDgC3m71Q2mEB35QhRYvsCX7uqL5QYID2UuFhjRb1Q9qzVQ0Z9UIrwPIiIHxwQuqYJWn\nG7we1Vc3qeJVmglWbYh6H5yDt19GtyCHP/uA8EdvIzs7kJ0d0dmTUGmsKythcj3W7/8gWmhMHyQZ\nEjBUimoRW9YYJLH6K/zRuxgnvkN2d0NPJwQCavnD6QSbHW3WXMx33qtyR1iVERZ+7S3VR4ioPNWD\nCqANfgdOhHGbD1wvel6fWzyF2Ya+4MZoYboQMqSCkoVuVt47TR/y4z12WzwnOkrDiBBCvVR1Xb2w\ntcRkU8kgh/yf7/ZsMBF4pG4Xmg5WnS333Mube/fgutrCrBkNg8+NhNTH7h5GQwgxULwqoxqh5AXV\npDGwo8HvGV58RxoDBXhqG0akZxxGWG21DAyRIxIGX3SHypSZwwqFCYiPT+PSeYxvDw3n3deD7OtB\n6Bqa3TGMtYj9o5sQJjEopiHeHpVdXr2MPHV8CAsDPH3g6UOsWI2orYs3Nbe0YTLFMr5GD5rSeW8m\nwrjNB64XPTOdO7H1FNHii8JszdCzGGMmOSb6bqfSMCIi4fj2tnLa62zkzJbX8OMSGS9yRTgEQT93\nrV/L3rfeY1ZjIwCR9jZVAKqthUjTJYzLTejLV6PPmIk2eQpi2nQ0R6o8Ekn0NFnBXTvANxJWx6Mp\nqdF1sFeouIFYfEw4pNZHTdEywCZzCh6ZrlP0b5MZccdD0H5VxTF4ehQfZwXCVQkVNSqGIQEyFEIG\nfRDwIr0etHkzMG3bhuz1IPs8yN5uVVvD5UJz2BBVlUQunkC4qsFmVx4JQ6pZls8z4AGprgOHW5Uc\nt1iVkRIJQyiAfstaRP1kZE8v9PUqHjYHVFQg3G7E1KlITw9+CZ8cOkpHby/ff2CXuoaxwmAp70c2\nM9os7mema5017WxlzIVHIfWE7OVMx7usZ/70vD5x+PBhfvGLX/Dkk08OOr5v3z5+9atfoes6Dz74\nII8++mhGWqVjRAwtAx2HTPF3qj7pMNoZfS68CsEjD3oG/dDbPqylyu1i7+tvomkaFXufZ03YO6g9\nfPIYsZVL21//DdqS5Sl5qFwFA0eU1yL9urwASNhGqqp+puo9nEeydsV7QAYxbVbKWI1kMJpOQPtA\n2W0N0BbMS+ggB6XqBqCnXX1QZdgJhRBDx3a06JcE5OylaPpAXIjmcqAtS7i2Jsug/BOBYJBnX9xH\nTaWbtcuXUFm7GFE5KY0W2c7gCvls5Gs2nU2fsp6jO3+i6Vl4FNsR8ctf/pK9e/fiTJLw7+c//zmv\nvfYaNpuN7du3s2PHDtxud1p6pWFExGaZE64UeDqaheaRCSlksNigZlr8OsuAn9C+57mlox3Z0YHR\n2c7ZgJ+X+oMITeP+6ZPRGqagz2hAuFwImxUufUOk4yw43Kp6p2ZChINIb5+KOfD1qV0eTjfY3QhX\nJWL+yoRAzeF6Sp9nUClwjAhS06MlsnU1mw/5B8oEhwJI3RwvE4zJgrDHyonHCnCh+mia8njYXGll\nGApt1lKYsSBaLtyH7GlXyy66Hj3PQNTUKcdZJITh6SPy5RdIrx/6PRg9vRAJKw+Cy4mw2zD8AWQg\njNHnRfb2Ir37EdXVaDU1aFWVmFatwrR4ibp+8aBTQV+fh++OH+fEmfM8/vgTWFwVCJMVdFN0vjaS\nMZXlmCnouB3ts5MNjWx4puNRKD3zzSPfPEeqZ6F5FBfFXs5obGzk7//+7/nZz342rG3RokX09PTE\nZcpGttIwIjQdLAlu2HAwuoY+dCAlG1i5DrZMNHP5Hhvs+aSZ7HuqY4kyZOov473jP066DsEQwdf2\ngccT7zkHmOPQafIF2Xf0FHMWLuCm+lj0v6ECH3sC8Rk3ugXp6R4uQm+H4lzXgLbwxvR6+vuHe6OM\nyMAs3Ns3fNYfDqqdDwCOStRWzCGIJBik9or0Mgy5loPWa50VGJEgBDzDUlQLUNeyv5/IZ58NE0F2\ndsSphrEiOwZ7gmRHe7zKt+mW24atDx/89juarl5j3ZpVrF2/Cc2dLJvnSMbtaGhk8z3VsUQZCsEj\n8QfqetZzKI9M/QspQzF4jC/jolDYunUrV65cSdo2f/58du/ejcPhYOvWrbhcroz0SsOIiEboxuMh\nIskT/igMXU+DwQNr6Jpeuvah9LJFLjyymQGm4lEEPa02LHdux+how2hrQba1Ir0ehMNJo83KLLOJ\no10dvHPIx5ZVS6I5YGV89o/JrOIXrHb1fyiADAYQMbnCBrKtlcjRg4iqWoS7CuzR4lOJclntELEo\nL1Q046MKto3OyIWuvCgxT0Q4qGIALNG4CYtVBYAmxF3IUAijvx/Z3Y3R3gauM2g1tWg1dYjKCoTV\nFrXkk19LKaWiEwxA0Ivs71Wy6WaVpV0m9JYGuFzoq9cgvT5kXx+ypwfCIYTbhXA4wWZB93hhSh1G\nvxfZ24f0+9GqaxCTJqNNii5LaKa4DG1t7TQ1t7FrxzZ1PL6VNNn9zLTWPLIxI5WCA0XCYoaZbiJW\nKGxgF0gxxu14eQeMRoZkNK5XPVPRGymP4noGxktc5cmTJ3n//fd59913cTgc/MVf/AVvvPEGd999\nd9rzSsOICCds68sImeLvkbSn6lNoGYrBIzs9hcmE9Uc/GegVChH+L3+J6G6NHgmzyujjzeNn6e2+\ngttigi3bEO6KgafLOiSy+tIF5NFDJO5CkEe/HpDA4UL/819ElwXUUeFIjIeQxIIi4m67BIM79uM+\nLP10AsInjuL52Z+oLZLJYDLhfnofesVQ78TA38apr+HK6aSnSwCzFZmwo0QDtFVLB/oEg3C1CTHI\nQzKw+0MaEtZuQ6ufMlgPI0w4HOaVdz/EUT2J+x95LEmyqNGOiRzGjM8D/Uk8TYmobWB4Uo1Cjdvr\n5R2QTz3Gs56ZZMiVx0jfqSODNkZWxNDsnW63G7vdjsWidl/V1NTQ29ub4uwBlIYRoetgmFBpf0cy\nSGIvr1SWdqb2XHiMVIZs6WQjQ+H0FGYL+g//FbKrDdquIk99C61X2HDPjbzb4Wf7jh2I2nrQNaS/\nH/q6VKCmzQFVkxF2F2Lejcibt0JnG1y7hDxxSHkPGhqhsgacLowzh8DuQlhs4K4Csx38fSrwMxTd\nWmqyqBwRVgfC7o7nnxBCi8bRDOgZL5cdDoIRQZtUg/Pf/HuMtjYiTZcIH/gS6enBtGwJWsN0tNoa\nuPQdEXcVwmIHVyUiWoQrdi21mYuQddNVVdGedlWEy2JTOtidCN2CFKikT7HMe+GgKjuu6yrfhMWq\nvBc+L/R2qR/aGQugrgGtshZRPUl5W8IhCKuYj0vX2vjwq2/Ydd8OXJVVUZnGcNxaHcrrZISVJyi2\nXddiVx4pLU0q8Gx5ZCVrOhTj+RxP74BCyjCe9CyNJYxkiE0s9u/fj8/n46GHHuLhhx/msccew2Kx\nMHPmTB544IHMdEqiFHgipIy6q7P1TJRRSMRm/cJkZs9Le3nw/p3DZv/SMEDTUjoZIz0dcPLLtHxE\n1eT0RddmLkZzpC4CJjPMlo2Igbx0YohXYIgMN6xHs6VeY5SeLqS/P6WehrcPzhwh3UtPu+0+ZVyk\nwKkzZzl95gzb70nvohxLDHU8l1FGMVHsUuAn58/NK72Fp8/mlV4mlIYnAohX8IytaY/KUs4W493K\nHXs9hRDx3TO3r13L+x9+xOaNG+Ltr7/5Nr19fZjNJibV1nL7bWuHGRnCYkO6ayAYULPYxDwgFruK\nhzBbQVqU8ZgYuKib1WzXSC6/jI4bGY+jUboOkkAzIXRNlRcPBYZV8sRsVTIYyVOvq6x6YWRYZduU\n0aWFYau3QgO7M5rzIThYz2icg+zpUidYhmf27Ovr45vDR3h4d6bZxdiO27LxUEyM/TugOBi/8pWT\nTU0EhAJq+17WyNdgG5+DdgDjS8/6+sl8+MmnhEIhzGZlWHh9Xh56cBdCCJqbr/Gb3z3Nrvu2U1lZ\nGT9Pszth8S2qLkbApwpgRQxwV6ty2wlVLWU4hPT1qh9hq0MtjySp4WF4etTuj/6uhB0YMYY60lmF\nqJmiDATdpNY1qycroyMUQPZ2KB6uaoTTnZRHpLNZLWH0tg/hIcBsQ7oqlDHi6U4INtRVoKFuUpe9\nuQl6VMEvAHnskLobVjvMXIC4bRuaU3k/3vvwI773wP1Z3InxPm7LyB/G1zugcBjv8k1clIYRAWoW\nVy7CNe6x49672f/a6zyw8z4A5s2Zw/kLF5kzexZTp05hzY2raGltG2RExCCEUNkXbcNTQ8f7mMwI\nd21mQXRNxRsELNHdPDLGJFqLRVfjyYiov2OziUgY2XIFzp9CBryISVNg3lKkq1LVypAS6e2B9mvQ\nclHFaAgBpoF1fxnwQ2sz9HvUcVelyigZ8yzEkmuZrRDwK6OirVnFPcQV1cDfh7x6GqOqDtw1GIZE\nK1fbLKOMcQUxwR/J0jAizNZo4JYR3eIXTr8+XsaYwW6343Q46ezsoqammrlzZvPZFweYM3sWAEsW\nL+L5F/eyYP68tHRGC82uElnJSQ3KUPB5VFxE4lJGLK+E0DCkxHj6H1RRq95u4gGZoHaXVNYilq4A\nq1kV1ko0aIUAiw3Z3g6t11RCrWAATzDMx5fbCBsSabWBuwLnjbfi9ftBSiIRg5uXLaRh8UpYvEot\nhfT3KJox+l3XkF3XQGjIC0eJdN+CXpUuA2UZZZRRTJSXMyYKhIjuNzenXJsuY3xg65bNPPv8Czzy\n0G6cTidXrl6NpqFWWzKrKitpa2unrq7wP4YC1PKFricv2w0gDbXdsrsd+nqGtwcC0NGK9HQjIqp+\nRkyf6BflUQiFVCGs6LbO3x69yB8un4U1mrtB1jfgX7EYR3QLlpSSTw8f45uTZ9m+/hYutnbw5aHD\naOEga5ctYGptQvluaTCtyknTlSs0Vk0qxx2UUUYZeUFp7M4Ih1RAXawAVxnjHke+/Y5rLa1s3bKZ\nnp4eXn71dR5/5GE0TUNKyZNPPcMTjz1SVCteGhH1Ax+JIANeZOtl5Y3oaFXbVYN+CAQhFAFDEmlr\nQwbDGH39nL9yjSNd/QinA/OUeqTLhayfgrlmMlit9GtW7rx3G5MdVuT5k8iOFl5+70PuXbMCc20d\nTG1ENMwGk0l5RALeeHDlueYWDh47TeO8Bdy0Zg0i4OHZp5/lzptXUmONFs3STUiLlRff+Yjv7bh3\nYPukyYLQx8NcYvwGvhUPpXINxreexd6dcXbJ/LzSm3ssee6ZQqE0jIigv7ylcwKitbWNN95+hzs3\nb8LlcrLnpX384NHvYzKZ6Ozs4tDhI2zZvHFMZDM6W5Dv7VHpspPBaidw6grGsW/5rK2bsCFZPylh\nC6nFiu2vfoFprnq+pJS8+sabBAIBzGYzPp+fYDDI7FmNrFt7a87ySSn5zT/9mvsWzaWycRpaNGHX\n3jff5Z6Nt2O1WlRHd42q9llGGWUAxTcizi3NL585R0/llV4mlIYRESu6FYkwkPY6pvZQ9YemQB2J\nxZyYyCQVD5nk71xkKAaPTBitDENpJG9/6eWXWbF8OfWTJ/Pcnhf4gyceB+C3Tz/L7l33Y7fbhtAa\nSj8mW/70lBDNORJE+r3KmBAiuuPDAWYrvX19vPrKa9wwu5GFtVUYfj+6ywXVNWhON5jNCZ6U/NzP\n1r/9rwTOniPU3Iz36lXea27hnsaZmOonY66fjP2+Hbzb3c33Htg1JJ10PmTIBuNp3KbjUSp65otH\nMd51mWQYDY8BlI2I3DAe/JiFhxAqH4AereYZTsiKNwwyxd+5IJWBki2PbGQoBg9I/9CNVobsaOy6\nbwd7XtrL7l33s/aWm9n3yqvs3L6NRx7aHTUkdkbL1RZPTwHRgEgrwmKFioH4g/b2Dt778A0q3G4e\nevh7mEzZPGb5uZ+eDz8meFq5M03Ro5GODiIdHQSOHafqsUex+P2EDQOzPnTbaT7uJxR2zORThtHy\nSIdi6ZmNDMXgUYx3XSYZRsNj7DDB4ypLxIiIRCASjAZUGmkCK7OxYhnSJ1N7KrqpUCwe2eopM7Tn\nIsPQGcNQGsN5eL39XLnazKRatS1z4YIFnDx9mkgkgslk4oePP8pze17E4bBzy5o11NdPHlM9z1+4\nwNffHOF7D+yKvhzydT+H85SgclKEghDwIn0eardvIHBpHqGuPkJtHVjOnMM+ZyYmtwOzwwLHPqPO\nXkXLkYNMmzMX4axQqcFz1DO9HvkcM5n65luG8fIOKLQM17Oe+eJRHIxV7Yx8oUSMiNBAyee0SGfF\npno48mFJj1aGYvAo5oxhQIZf/O3fsf62tQlZLCWb1t/O7555jiceewRN03jkod1IKXlh7z5277o/\nCb30PHKTMd1x+PKrr/n+9x4cpQzJzkvSz4hgfPvxoLHtWjYH17I58e81L77C9HkJhpXRw0193ez9\n9ds8sGI+cv396AtWZClDuvbrZdyOhMb1pmcmHuNdz2x5ZNNeRiaUhhGhmwE5jj0RmdbscuFRaOu8\nuHr+5V/8GU8/9zzfHT3GsqVLAEFFRQX33nUXL738Cg/s3KHOFAK3y82Vq1dpmDatwHomh8/no7qq\nakR65j5rBDQdbfnt0VLiPrVrI+QHe4VKumW1M81r52JtFbOq3cieDmg6gxYJIK55icxahN56gYin\nA2xOhM1BT0Sjat6SLHe9FEnPpH2z5THy+5lfHrl66Qr9DkglQzoepaZncTDBHRElElg5FGljIsoY\njFzck4XDiZOn+PTzL6ivn8y2u+9CCEHT5ct8/OnnPPrw9+L9XnvjLSorK7jt1lty5DB6PT0eDwcO\nfj2o9kexkfhajOF3zzzH4488DEDk2Bdw7Tznr7XT6/OzYvZ0Pj9xjrYetcvkq9Z+enUbf/TED1i5\n4oYRSjEexsx4kKGMiYhiB1Y2rViUV3ozDp/IK71MmOAJN7NEtFIkQb/aXx8MoF4yyUzAxOMjNRET\nz0/FI9nf6WhlezxbHtnqmY1nofB6Llq4kB/94DFuvekmnnr291y8dIkZ06ezetUqvv3uaLzvvXdv\nZdrUKfzumeeSyJY/PSWoFNaRCDIYwPD2YiOCp6cbGQmrthHomd39Tn0/RZL2jbfewjv7XyF8+hTh\nS5eJdHkI+INYooXP3C6XKsftrmHXXZtZf9ttnD1/YQQyxJDMlBl63kjHTDb3M1uPWDoe6dpT9U12\nvNB6ZivbaN91paJnGbmiNJYzcir9neuaWzoaI12bTNU3m+PZ8phoekp0Xae2tobHH3mYDz/+hM7O\nLlatXMELe/exfNnSeN9ZjY18c+TbEciQSbaB86WvH66eUgmfotAAz4XjyNP1oJsQc1aoQllJaWXm\nkfq87O+n97/9De5336DlSisXK5xMsih5Lvf0M89lJ/znP2P5Iz/hhnhwJfg++ZTOrq4RyJCqb7Lj\n+dUzO9755JGtDGU9Ry/DeHjXFQ4TfTmjNDwRmh4tklQa6pYCNty+jotNTQC4XW6uXWsZ1B4Khfnm\n8JHCCWCxQf1smNwIrup4ES6T3Ql1M2DKXOQ4mPVY7r4P27/8c3b9Tz/hU81CczCMmFRH+w2rafiz\nv8S0ZFXC7gyF9etu4/4d28dI4jLKKC0Ikd9P0eUvqZiIWNrrUFBt+SxjQuPlV1/jvm33IqXkqWd/\nH1/3j+H0mbN8/uUB7t+xjYqKihRU8gMpJV8f+oaq6mrmzp5VUF4jhRGJ8Ktf/Yaq2lomTaplw+3r\nBrW/894HSCm5845NYyJfGWWMBxQ7JuLKqvzGRDQcKm5MRGksZ8CAARHLWlnGhEdbWzsejweXy8Wq\nFTdw7PgJliweeCDnz5vL3Dmz+c3vnuZHP3isoHU2hBBcvnqV1TeuKhiP0ULTdf7ox3+Ysr2ntweH\n3RG/pmWUUUbhIbSx91iOBqXh3w8FwO9Rn5CvXAb8OsEPH3+U9z78iLfeeY8F8+fx6htvcTgeC6Gg\naRoP7NzBr3/7FH19KepclAGoJaBFC+fz/kcfj7UoZZRRMpjoyxmlYURA2ftwHcJkMnHftntZtmQx\nv3vmOf7FT/8Z/kBgWCxEZWUlP3z8UV57821OnipchTtNm9iP0/e/9yAHDh7CSJlHpYwyyihjMCb2\nWy9bmK1grwCrE0xWEDrpt/rky5wb726qiaRnah5Tp07h8Uce5vcvvMSCefNovtbClatXB52raRoP\n736AS02XOXvufN5lyB9Gw2P08t2wbCk3rlw5ajqZMbZ6Fg/jXc/x8A6YSHrmH5oQef0UG6UTEyGE\n2m6nRYsOpd3yma9tQONvO9FgTCQ90/MwmUw88dgjvLB3H8uWLOHc+QsJmSsHzt26ZTMv7N2H2+Vi\n8uS6vMkQiUTy5IkYzbUcODcUCnH42+9ovnaNUCiE2WwmFkMtpWT+3LmD4kdiWLhg/ij4j0zW4p5b\nbIx3PcfDO2Ai6VnGUJSGEREJRffzG2BIRpYmVSb8n2t7LjxGKkO2dLKRYWLqKYRgxvTptLa1sX7d\nbSnPfGDnTp586mkeffghzOZkj0Duel5tbmZqfX1a+UbLIxt0dHTy7gcfYrVaWLJoEU2XL2MymXE6\nHNyxaWO83/ETJ9nz0j5mNc5k9apVo5Ch0GMmm/OKOW4LyWM8yFDWs9iY6HkiSsKIOHPyFDphZs+a\nlbRdRsIgJSKawS9JjyH/59qeDbJNqDLSpDC5yDBx9bx5zeqMEggBDz24i1def51d9+0YhQwDaG1r\nZ3LdpIzyjYZHJoRCIV55/Q3u23YvZ86d49DhIzywcwdXm5t55vcvsGTRIiZPrkPTNBYvWsjiRQv5\n6utD7HvlFQC8Xh8L589j1cpUBblGosdo9czmvGKO20LyGA8ylPUsNgq5a6wYKAkj4rMDX+F2Opg9\nbwEYBobfg7x0Avxe8PerjwRsDrA5weZAzFyMZrVHKSQONJFwTGRoj33P1XOQeGykPHLhm4lHvvRM\nRmO0emZCch52u51IJIKUsYd4dHquWnEDL728nxnTZ2SgURg9W1vb+av/+J/YvGE9b7z9DrfefBM3\nrb4RgJkzZvDTH/8hJ0+f4atDh4hEDMLhMHds3MCaG1cBq+IyHD5yhD0v7eWBnTvR0m49K8aYScU3\nn+M2G36j5TFe9Sz2O6AYMuSDx8T+US82SivZFGq29lc/+zPummLj9qXzUvbTNuxO45koFsbe1VYc\nGcZGz+7ubj785FN2bt+WFxneeOsd1ty4itramhQ9cuMhpeTCxYscPX6CxMfU7w+waf3t1A3yfEAw\nGETXdXRdT0NVyRAIBPj8ywN09/SgaRqaprH9nrsB6O3tZe/+V7lz8yamTp2StbxDeYwtrt9xW3wZ\nxoOexYDSs9jJptpvXZpXepM+P5q5Ux5REp4IGQ5Cfw+EQ5giQbZvvA1vSxNPfnmSr4+f5Md33c6S\nxgY0p1uVRLY6kJFI1IjI9QEa2j+ZtZ7ueyKNVBb+aHlk8gokIpXuE1/PqqoqgsFQkj4M6Z8dj61b\nNrP/tTeiRkm6a5lez4uXmjh46Bs0TTBn1izuveuuqGGg+kgJL728P14GPSaDxWJJSXOoDFarlY3r\nb48fff3Nd+jq6qa6uoqKigqeeOxR3nnvfb48eJBIJMLmDRuorq5Ocx1y13Psxu1oeabjm6ytEHoO\nfXaSyTBanqQ5lkqm0fLMNGaSyTBanqQ5VniUlzMmAvp7oKc1/nXtjTcAqszxfd09/Nd/+h3Pn+3i\nf/93/ybJybkOrKH9c/2eDxr54JkJE1/P1tY2qquqkvQZGQ9N0wgGgyn4Zk/ziwNf8fDuB1L2+ebw\nYWY3zkxDL9Wx1Lh76x289PJ+TCYTVouVO+/YxJbNGwG4cvUqL+57mZqaalbesJxZjY1Z0r9ex20m\nvsXQc3RjLHd6heAxUfQsIx1KI0+E1QHOqmieCAsgVAElRxU1jfP4i5/9jD/9l/+cDz76hOSrO2LI\n/6NpHymNTMhWhmz6lIaeL+x7mRuWJXMljlzP1atW8Pqbb2dBIzmklNhs1pQ8zl+4QEdnFytXJAY/\nZnMt0rULhBA8sPM+7tt2L5PrJvHam2/F2xumNfBHP/ohu+7bQfO1Fl56eX9SGiNDpjGTzf3MhUe6\n9mz6FFLPXHiku1bF0HOk74Bc9czEI117Nn3G3gsw0TNWloQnQticKmAS9ZIm6EckFOByV1p5/8OP\ncDqdPP3c86xft5YZ06cnUJBD/h+K0bZn2ycdspUhmz6loeetN63hWkvLsNiC0eg5e9YsPJ5+Dhw8\nGA1szE3Prq5uqiorU/I4dPgID96/k9zuZyoM53Hu/AV++8xzbFy/jpdffXWYUS2lZGb02bh85QoH\nDn6Nrus47A6m1E/m9Nmz6LrOpNpa1t5ycxau2nzcz0woxrNRDBlS9c8nj2z1HO07Ihsb0ub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ehmkqesZ3bt2UBw6803sWD+PL73wP0IIfjyq68BwbIlS/D6fOx5aR/HT5ykra2N5/a8yJvvvMem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\nL2AQXJImSbAAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x4b7971510>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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PsmrVKpefY1RUFBcuXOh3vMpQU1dXx/379+no6HBYIh0XF8fOnTvdGlt29+5d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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x52c884b10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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UqcM9vUlGRgalpaV4enoyePBgFAoFKpWKsLAw6buMfXrasHjXyYbFD/urYdGC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CDL4bdDQnT3gWqZ9ZyKhh75ktHI9UC1VMpOzvP4cWNo+KKBPR9+FGVxrVja+f585Zdnr9fDlavX\n2LZzF8OGDKGmtpb9hw4BUOgqZM6sh3A6nWouoaAoSvh+GHUiPz0bJIMRWKSDz62+bmpg0I2Y9/Ac\nqgYO4Oq167m20mNxOBz833/8R1GPNTU18dm+L/EH/ABIkkQgEEAIweOPPoLdbs+mVYNcE+fVze6I\nEVikgxz+xicUOs++KdE58o38HLm/4/Fk0kY7nmxaLeKlScdzrPNO1rOWj2jpk/GcyLkkc37J+oiV\nNr3n69btWxw8/BUb169N03My19CoE/f3FxcX8+jyZUReD5/Pyzu79+B0OHhk2RIkSU7Rcz7WiVQ9\nR0P/OhHbc4bJk+4LPel5oVI2sdrV2TdtTjr3zWk100YSr0kwXlqtMpJJq0WqzZHR0mhdDz08J9Ok\nmYxnrf2JeE61STbRtKk/X18dPcqx419HBBWxtJPxEcuPUSdi+xDYbDbWrl7JjGlT+feXXsHjcSeo\nlaiPXNaJZMrIbp2I79kgWYzAIh18bvC2qj/GQ2mQ5/j9fq5ev87jKx7JtRWDGJSXl/HcM5v43Zat\n1Nbey7Udg0zTAwdvGoGFQS8gPypbrtn74ccsX7I41zYMEsBsNvPcM5v4dN8+Tp85m4ESjDqRN/TA\nwMIYY5EONnVUN0oIvG0YrRb5inFfACaMH8uJk6d4ePasXFsxSABJkli/5kmOHT/Blm3bMZvNyLJM\n/379dJjgzKgTBpnDCCzSwe9VgwqhkNhgIz0GjqUzyCwVjWQHJqZanh4ahudY931QdTX7Dx5GCBFl\nRcX89Jy8hh4DEJP1nNnna8rkSUyZPKn986lvzvDF/gMxFpHLvef0NPLl+coSPfCtkJ53RtlEhNTX\nTTu9ERI1YcRvrePpaCSil4qG1qAovT3roWF4jn2c9tcak9dIJG1mPCenkeqgwXw57/iMHzeGmtra\nNMsz6kTe0AO7QozAIh1sBeAoBIsDo8/SIN8RQuD3+zlz9lyurRjogMYyTwYGOccILNIh6FeXTg8F\nwjs6BhdSh9/R9qOxT+u4ll66Gsl41iojnkY2PMfy0d09J3qvYnuWJInf+85z+Hw+3t6+o8M/Jr3O\nOxXPiepFO95768SYUaM4c/Z8Gj6y7zn6dr56ziJGi4VBJwJ+NbhQgqhNa9GaZLX2o7FP67iWXroa\nyXjWKiOeRjY8x/LR3T0neq8S8zx1ymTmzp7Ny6+9EQ4u9DrvVDwnqhfteO+tE6NHjeTchfNp+Mi+\n5+jb+eo5ixiBhUEn7E61G8RsJedRr4FBElRWVrB44Xz2HzyUaysGKdB18K2BQf5gBBbpoGhFwx3R\n4w9ApEYmNDOtn4pmJs470+Xl+l4lXl7VwIFcvnKVrl31veX5iqeZaf3Uny+v14vNaktRI/nytD9n\nSyOfy0sTWdb3Jw/IDxfdFb8HAl61O0QzwNCjmS1SIxOamdZPRTMT553p8nJ9r5Ir7/FHl7N567a0\nNKLTHZ6veJqZ1k/9+Tr81VFmTJuaokby5Wl/zpZGPpeXJkZXiEEnrDa1G8RkpusgIa0bHG0wUrTj\nyWpkuzw9NJIZsKVHeXpodEfP2holJSUM6N+fGzdvZqW87Gp0d8/az9e9/7+9Ow2K4k7/AP7tuTgc\nGDwQUZDDFRUwilETb/GKJ0YjRrPRNbGSF/tqa4/aStXWxrxQ8iK1m6rN3xebvNhy1yhRE69EURLB\niAkqCgIeKHKjBEFQGJiz/y9YZ0VngIGme6b5fqqmdLqnf/30TDfzzO/qpiaMGjVSgv25W+9tGeq6\nJmjgmFgMhEYHaPVd/wLoW4cgd52R3K33tgy59ydFGd502JJif1KU4Y8x91zGnFdm4ad8d30tfDfm\nvpXh7zG7P7/MZjOczufnzvHtmKXdnxJlDCLWWFA3FjNgae9qDvH16jYiDwRBwMgRw3nDKz8giiIO\nf3MM69euUToUkgoTC+pGq+t6uDrM9Fal9vwyb6oV3fG2CrK3mAYr5ufX91TGQGLurYz+xtxbGYKH\n5Z7K872YFy9cgJwfL/RQni+cX8+/z+74Wsx93Ufv14Qoivgy8xDWrV4FrVbbx5iVPL962rYv+1b6\nOqb+4r1CBkIfAIiGrvuFWMzovUrNU6eivlQruuNtFWRvMQ1WzAOpNu1PeVLH3FsZ/h+zRqNBiNGI\n1tZWmEymAcbsaZnU77M7vhazt/twH7PT6fxvUrHymc/Hm/J4TfRehjK1zoKPjOSQkvqOSE4WM9Dx\npKs5hE0h5OeWL01FVvYPSodBz3E6nfjPgUykrVnlIakgv8amEOpGEACNXB+kb5wwpBYvnk9arRbh\no0biwYMGBeIZ6jxf398cP4ENaWsRGhoqYzxDEf/GSoWJxUAYgoDAkK7HoJ+UrBEhKbk/n572teDZ\nJjf373h1TQ0ix4xBSEiIzPEMRQqd9ayxoG6sHUBnW9ejTydlXzo09fZab04cb/YnRRl9jbk/ZXhj\nIPuTogz//KzEznaILb8gZpgWd3JPwdFQDefj5h7uoql8zN7vV66YvemA6DmOiz9fwtxXX+3Ta3vG\na6L3MhT6UmZiQd2Izq6Omy8kFW4+XE8fuMcToac/Vs8tc1uGBPsTPJwe3py87l7r8QLwsNyr987T\nKe2pDHfL3JTR00U74Pffy/d5wO+R++XO+nKI5UWYHSYg/3wOcO86xHvXu87zFwvwbn9D7pro4YdG\nH6+JH3JyMXvmy30vo2uFm2WDeE14855KcR3LfE1Q/3BUyEAEDANEEXDYu/7Vav93AYpOwOHoOlm1\nuq5/RbErEXE6AI226/F0ucPW9bdIp+sqQxQBp7PrzqnPv9ZVxn+HugpC1/7s9q7rXKvvfX9Oe9e9\nTnwmZpmOW6qYIeNn9ez5pdF2/f/pZ6URusqW4Li1yQsgOhwQWxuROjwOPzxowbIlayEMNGafOL/8\n65q4VliIkFFjEJ80rQ8xO4fgNeEmZtHZdd5pNAO7JnQBg/aV4ZYKR4UwsRgoQQB0ejfL/3sSP//a\np3NfvFCGwc1rtV2PPpWhAfTuyvCwP60eeGEovK/EPIjH7Zcx619cNkiflaDVQhgxBlEjxqDw5Em0\ntLRg+PDhA4+5q3AfOb98+5r49sxZDB8+HHPnzu1nzEPhmnDzWqk+q+fjIK+pL1UiIkmsWbMGp0+f\nVjqMIcXhcMBqtf4vqSD1e9oMJtXDB7DGgojccjgcCAiQuVp4iKusrMTEiROVDoPk5CPJgJRYY0FE\nbul0OoiiCIfDoXQoQ0ZAQACsVqvSYRANCBMLIvJo2bJl2L9/P+xPO+fRoAoODkZHR4fSYZCcVNgU\nwsSCiDwymUzYtGkT9u/fj4YGzsg52IKCgmA2m5UOg+Sk0Uj78AG+EQUR+azg4GBs374dxcXFOH78\nOJtGBlFgYCA6OzuVDoNoQHpMLK5evSpXHETkwwRBwLJly7B48WIcOnQIRUVFSoekSvfv38eYMWOU\nDoPkNNSaQhobG+WKg4j8QGhoKLZs2QKtVosDBw6grq5O6ZBUpbS0FElJSUqHQXIaaonFwoUL5YqD\niPxIcnIytmzZgoqKCmRmZuL+/ftKh6QKHR0dCA4OVjoMogHpcR6LoKAgueIgIj8jCALmz58PURRx\n/vx5nD9/HqmpqRg9erTSofktzzd8I9XykQ6XUlLfERGRrARBwKJFi7B582bk5uYqHY5fE3ykKptk\nNNSaQoiI+koQBCQmJuLAgQNoampSOhy/c+PGDYwbN07pMIgGjFN6E5FkkpKSkJiYiFOnTiE2NhaJ\niYlKh+Q3bt68iTfeeEPpMEhuMtYyiKKIXbt24fbt2zAYDNi9ezeio6NfeN1f//pXhIWF4fe//z0A\nYOPGjTAajQCAqKgo7Nmzp8f9MLEgIkkJgoBVq1bhxIkTTCy8YDDwrppDkoyJRXZ2NqxWKw4ePIii\noiJkZGRg79693V5z8OBBlJWVYfbs2QDgmmJ+3759fd4Pm0KISHLsK+Adq9UKvd7NreaJJFRQUIAF\nCxYAAKZNm4aSkpJu669du4bi4mJs2bLFtezWrVswm83YuXMnduzY0ac5bFhjQUSDgiMc+u769etI\nSEhQOgxSgoyjQtra2hASEuJ6rtPp4HQ6odFo0NjYiM8++wx79+7Fd99953pNYGAgdu7cifT0dFRW\nVuK9995DVlYWND3EzcSCiAYFay365vHjx7h37x5mzpypdCikBBmvE6PRiPb2dtfzp0kFAJw+fRot\nLS1477330NjYCIvFgvj4eKxevRoxMTEAgNjYWISFhaGxsREREREe98PEgogGBROL3omiiK+//hrb\nt29XOhQaAmbMmIFz585h5cqVKCws7FZLtm3bNmzbtg0A8M0336CiogKvv/46Dhw4gLKyMnz44Ydo\naGhAe3s7wsPDe9wPEwsiIoWcOHECaWlpPVYrk8rJmIAvX74ceXl5rj4UGRkZOHnyJDo6OpCenu52\nm02bNuGDDz7AW2+9BY1Ggz179vR6vjKxICJS0IgRI5QOgZQkyJdUCoKAjz76qNuyuLi4F163YcMG\n1//1ej0++eQTr/bDNJmIBgU7b/ZMFEU2F5EqscaCiEhmZrMZJ0+edM0VQEOYRn3JJRMLIhoU/DXu\nXlVVFS5duoQNGzZw7gqStSlELkwsiIgGkSiKqKqqwqNHjwB0TUL0zjvvMPEi1WJiQUSSs9ls0OmG\n7p+XhoYG/PTTT67nsbGxCA8PhyiK2LBhA5MK+h8VngtD98onokFTVVXlmlRnKLFarcjKykJQUBDW\nr1/PBIJ6p8KhxkwsiEhyd+/eRWpqqtJhyKKzsxOnT5+GIAjQ6/VYtGgRQkNDlQ6LSDFMLIhIclar\nFQEBAUqHMegKCwtx584dvP766+yISf2jwlot9dXBEBENsqdTcWu1WqSnpzOpIHoGayyIiLx0/Phx\nzJs3r8cbMRH1CYebEhENbT/++CMmTZrEpIKkwaYQIqKeWSwWVfev+OWXXzB58mSlwyDyWayxICJJ\n/fLLL6r9Nd/Y2IjIyEilwyA14XBTIqKePXjwAFFRUUqHMSj0ej2sVqvSYZCasCmEiKhnjY2NCA8P\nVzqMQREWFobW1lalwyDyaayxICJJWSwW1U7nbbfbVXtspBCOCiEi8sxut0MURaXDGDRlZWWYOHGi\n0mGQmqjwtunqS5WISDHZ2dlYtmyZ0mEMmtLSUiYWRL1gjQURScZsNqvyPhmiKOLkyZOYPHkybyxG\n0mJTCBGRZ2qd2vrw4cNYuHChaofRkoJUmKiqL1UiIpLQtWvXkJSUxKSCqI+YWBCRZJxOp9IhSMpm\ns6GsrAyJiYlKh0JqJWikffgANoUQkSScTiccDofSYUjqxIkTSEtLUzoMUjOOCiEicq+goACzZs1S\nOgzJ3LlzBxEREQgKClI6FCK/whoLIpJEcHCwaqa7Li0tRU1NDVauXKl0KKR27LxJROTer371K9y9\ne1fpMAYsLy8PTU1NTCpIHirsY+EbURCR3wsICIDFYlE6jH6zWCz48ssvMWrUKCxcuFDpcIj8FptC\niEgy/jydd1ZWFt544w0EBAQoHQoNJSrsvMnEgogk0draipCQEKXD6BebzQan08mkguTnI80XUlLf\nERGRIi5evIi5c+cqHYbXnE4nvvzyS6xYsULpUIhUgTUWRCQJi8WCwMBARWNwOp3QaPr+e8nhcGDf\nvn1IT09HcHDwIEZG5AFHhRARvchsNvvEfUL+85//4PTp031+/dGjR7F582YYjcZBjIqoByocFcIa\nCyIasO+//94nmhLCw8MBAEeOHIFer4fFYkFqaipGjRrV7XUNDQ04f/48kpKSMGzYMCVCJVItJhZE\nNCCiKMJisfhEx8dVq1bh8uXLaG9vx5o1ayAIAnJycvDkyRPXa+x2O0aNGoVNmzbxFuikPI4KISLq\nLi8vD/PmzVM6DJdZs2YhMTER+/btwzvvvIMlS5YoHRKRZz7SfCEl9R0REcnqwYMHiIyMVDqMboYN\nG4aRI0cqHQbRkMTEgoj6rbm52We/wEVRRGlpqdJhEPVMEKR9+AAmFkTUb+fPn7D9DX4AABd6SURB\nVPfZ6a/Xr1+Pa9euqe5W7kS+jn0siKhfzGYzHA4HtFqt0qF4ZDAYfDo+Ingx74q/UN8REdGgs9ls\n+Mc//oGlS5cqHYpHxcXFiI+PVzoMop6xKYSICNDr9UhMTERYWJjSobj1+PFjlJWVYebMmUqHQjTk\nsCmEiFSlrKwMeXl5+M1vfqN0KES9k3G4qSiK2LVrF27fvg2DwYDdu3cjOjratT4rKwuff/45NBoN\n1q5di+3bt/e6jTtMLIioX3ylU6TdbkddXR2uXbsGp9OJhIQEvPPOO0qHRdQ3MjZfZGdnw2q14uDB\ngygqKkJGRgb27t0LoOs+O3/729/w9ddfIygoCKtXr0ZaWhouX77scRtPmFgQUb8IguD1Tb/6q62t\nDf/3f/+HKVOmvLBOp9MhMjIS69atY0dNoh4UFBRgwYIFAIBp06ahpKTEtU6j0eDUqVPQaDRoamqC\nKIrQ6/U9buMJEwsi6pegoCA8evRIlnksjEYjEhISkJaWNuj7IpKVjKNC2traEBIS4nqu0+m6/TjQ\naDQ4e/YsPvroI6SmpiIoKKjXbdxh500i8tqTJ09gNptlnRxLjpoRItnJOCrEaDSivb3d9dxdgrB8\n+XJcuHABVqsVR48eRUhISK/bPI9XKhF5LScnB+vWrZNtfy0tLQgNDZVtf0RqNGPGDOTm5gIACgsL\nkZCQ4FrX1taGbdu2wWq1AuiqkdRoND1u4wmbQojIa06nU9b+DCaTCQ8ePJBtf0SykXFUyPLly5GX\nl4ctW7YAADIyMnDy5El0dHQgPT0daWlpePvtt6HX6zFp0iSsX78eAHDhwoVu2/RGEEVRdLeirKwM\nAPqUnRDR0HLs2DHXHx2pOJ1O7N+/H8HBwa5fSo2Njbh//z7a2tqwePFin7vZGamP3N99jnNfSlqe\nNvUtScvrD9ZYEJFPEAQBJpMJaWlpcDgcuH79OsaOHYsZM2awfwWRH2FiQUReuX//PsaMGSN5ucIz\nHc+0Wi1SUlIk3weRz5GxKUQuTCyIyCtFRUVITU3Fd999BwBYsmQJAgMDJSk7MDAQx48fh8FgQGVl\nJd5//33WVpC6aXzj/h5S4hVLRF6xWCwICAiAzWbDnDlz8P3330tW9ooVK7BixQpMmTIFRqMR169f\nl6xsIpIHayyIyGuNjY0YNWoUiouLMWfOHMnKtdvtOHbsGEaOHIn09HQEBARIVjaRT1JhU4j6joiI\nBlVAQACOHTuGmTNnorm5GSNGjJCk3NbWVuzfvx/r1q3DsmXLmFTQ0KDC26azxoKIvLJy5cpBKffi\nxYvYunUrDAbDoJRPRPJgYkFEfWa32/HPf/4T0dHRSElJkazTJgDYbDYmFTT0qLAphIkFEfXZzZs3\nsWrVKkRFRSEvLw/z58+XrGybzSZZWUT+QvCR5gspMbEgoj6rqKjAunXrIAgCFi9ePKCyRFFEdnY2\nOjs74XA4EB0dLU2QRKQoJhZE1GeiKEryC6umpgbnz5/HqlWrJOv8SeSX2BRCREPVw4cPJZusKj8/\nH7/+9a8lKYvIr6kwsVDfERGR5Gpra3Hu3DmsXbt2wGU9efKEQ0mJVIyJBRH1qKOjA3//+9+RkJAA\nu90+4PKMRiO0Wi3y8/MliI7Iz2kEaR8+gIkFEfUoKCgIn3zyCUwmE06cOIGMjIwBlScIAlavXo3Q\n0FBkZmbizJkzePjwoUTREvkZQSPtwwf4RhRE5NMEQUBnZydsNhv++Mc/SlLmlClT8Oabb2L+/PnY\nv3+/JGUSkfLYeZOIelVdXY2qqiq8+eabkpcdGBiI8ePHS14ukV/gPBZENBTl5+dj06ZNkpdbVVWF\nCxcuYMWKFZKXTUTKYGJBRD2yWq0ICAiQdIbAlpYWnD59GnFxcRx2SkObj/SLkBITCyLqkVarhVar\nlbTMrKwsbN68WbJ5MYj8lgqbQnhVE1GPtFotHA6HZOXdu3cPsbGxTCqIVIpXNhH1SqpmkJqaGvz4\n44945ZVXJCmPyO+pcLgpm0KIqFeiKA5o+6amJmRlZSEuLg7bt2+XKCoiFfCRSa2kxMSCiHoVFBSE\nuro6jBs3zuttRVHE8ePHsWPHDlXeIpqIuvONehMi8mnLly9HTk5Ov7YVBAFhYWGDklQ82/fDYrEg\nKytL0v4gRIOOTSFENBSZzWaEhYUpHYZLZ2cnsrKyYLfbodFoIIoiHA4HlixZgiNHjmDKlCmYOnWq\n0mES9U6FtXi+kd4QkU+z2+0DGnKanJyMH374QZJY7t27hy+++AKvvfYaxo8fD5PJhI0bN2LDhg2o\nrq6GxWLxqSSIaKhhjQUR9So0NBQAcO3aNaSkpPR5u/v37yM/Px9arRZlZWWoq6vDtm3bBhRLfHw8\n4uLicOzYMcyaNQsRERE4fPgwgoKCMHXqVLz99tvsy0H+w0eaL6QkiB66e5eVlQEAEhISZA2IiHxX\naWkpbty4gdGjR2PhwoVuv8BFUURBQQFu376NyspKTJ48GXq9HoIgYN26dQpETdR3cn/3OUt/lLQ8\nTdICScvrD9ZYEFGfXb16FYWFhZgyZQquXr2KtWvXYuLEid1ec/bsWURHR6OzsxN/+tOfYDAYAAC1\ntbU4c+YM7wtCpHJMLIioz7Zt24ZXXnkF169fR0pKCg4fPgy9Xo+1a9di0qRJrtur3759G2+//bYr\nqQCAqKgolJeXo7q6mnczJXpKhU0hTCyIyCsJCQkYPXo0jh49ivfffx8NDQ3Izs7Gvn37YDQaYbfb\nsWbNGgQEBLyw7aJFi/DVV1+hubkZ06dPVyB6Ih+jwqnt2ceCiPpFFEVkZ2ejpaUFK1euREhICJqb\nm9HR0dHrRFplZWW4fv06Ro8ejTlz5kCv18sUNVHPZO9jcesnScvTTJ4jaXn9wRoLIuoXQRCwfPly\n2O12nD17Fm1tbZg3b16fZudMSEhAQkICfvnlF5w9exY2mw2dnZ1ISkpCcnKyDNET+QY1jmBiYkFE\nA6LT6bBq1SqIooiffvoJP//8M7RaLQRBwPTp0932p3j48CEyMzMRExOD2NhYPHnyBDdv3sTkyZMV\nOAIiBbGPBRGRe4IgYO7cua7noiji8uXLuHz5MvR6PTQaDQwGA9ra2hAYGIjf/va3aG1tRXNzMyIi\nIjB79uwBTcJFRL6BiQURDQpBEDB79mzMnj0bAOB0OtHZ2Yng4GDXa8LCwjhLJg1tbAohIuofjUbT\nLakgIqiyKUR9R0RERESKYY0FERGRUtgUQkRERJKRcYIsURSxa9cu3L59GwaDAbt370Z0dHS313R0\ndODdd9/Fnj17EBcXBwDYuHEjjEYjgK4ZdPfs2dPjfphYEBERDQHZ2dmwWq04ePAgioqKkJGRgb17\n97rWl5SU4MMPP0RDQ4NrmdVqBQDs27evz/thHwsiIiKlCIK0jx4UFBRgwYKuu59OmzYNJSUl3dbb\nbDbs3bsX8fHxrmW3bt2C2WzGzp07sWPHDhQVFfV6SKyxICIiUoqMo0La2toQEhLieq7T6eB0OqH5\nb3NMSkoKgK4mk6cCAwOxc+dOpKeno7KyEu+99x6ysrJc27jDxIKIiGgIMBqNaG9vdz1/NqnwJDY2\nFjExMa7/h4WFobGxERERER63YVMIERGRUmRsCpkxYwZyc3MBAIWFhX260dqRI0fw8ccfAwAaGhrQ\n3t6O8PDwHrdhjQUREZFi5Btuunz5cuTl5WHLli0AgIyMDJw8eRIdHR1IT0//X0TPJCibNm3CBx98\ngLfeegsajQZ79uzptZaDt00nIiL6L7m/+8TqUknLE8YnSVpef7DGgoiISCkqnCCLfSyIiIhIMqyx\nICIiUooKayyYWBARESlGfYkFm0KIiIhIMqyxICIiUgqbQoiIfJfD4UBlZSW0Wi1iY2OVDoeod+rL\nK9gUQkT+r6mpCZmZmfj222/R0dGBpqambndtJCL5sMaCiPxObW0tioqK4HA4YLfbMWLECKSnp6Oi\nogLFxcWwWq148803lQ6TqA/UV2XBxIKI/ILNZsPp06dx//59VFdXIyUlBXq9HjqdDq2trThy5Agm\nTpyI9evXd5uSmMinqfBcZWJBRD6pvr4eP/30E3Q6HQRBwIULFzB16lRMnjwZO3fuhFarVTpEInKD\niQUR+RSn04nDhw9j7Nix2LhxIwRBwKFDh/C73/0OY8eOVTo8ImmxxoKIaPBUVVUhOzsb6enpCA0N\ndS3X6/VMKkilmFgQEUnK6XQiJycHjx49QkxMDN59990X+kjYbDZUVVUhJiZGoSiJqK+YWBCRYvLz\n81FRUYFly5Zh1KhR3daVlpaisrISDocDWq0WtbW1TCxIfdgUQkQ0cBUVFcjPz8esWbPwyiuvdFtX\nV1eH3NxcpKSkYOXKleykSSrHxIKIaEBKS0tRX1+PLVu2dFtutVpx/PhxjBkzBlu3buWQUSI/xcSC\niGR19+5drF27ttuytrY2HD58GFu3bkVAQIBCkREpQIUJNKf0JiJZLVy4EOfOneu2LD8/H6+99hqT\nChp6BEHahw9gYkFEsjIYDLDZbN2WLVmyBDk5OSgvL1coKiKSCptCiEhSnZ2duHXrFux2O2bOnNlt\nndVqxVdffYVt27Z1Wy4IArZu3Yr8/HwUFxdDEATMnz8fI0eOlDN0IgX4Ri2DlJhYEJEkns6YGRoa\nisTERFitVmRmZmLz5s0QBAGNjY04ffo03nrrLeh07v/0PB0h4nA4cOHCBTQ0NGDx4sUYPXq0nIdC\nJBs1dlJmYkFEkjhx4gRee+01mEwm17KQkBCcOnUKq1evRl5e3gs1FZ5otVosWrQIoigiMzMTK1eu\nRFhY2GCFTkQSYh8LIpKERqPpllQAQEREBKKionDx4kUAgCiKXpUpCAI2b96Mb7/9VrI4iXwKO28S\nEbnnKWl46aWXYLPZMG7cuH4lCBqNBnPmzMHRo0e9TkyIfJ8g8UN5TCyISBKdnZ0e1y1atAhlZWWI\njIzE1atXvS47Pj4e8+bNw5dffjmQEEnl7ty5g1u3buHRo0dMQhXEPhZE5JXy8nKUlJRAEATXo729\nHfPnz+9xu6lTp8JoNKKiogLl5eWYMGGCV/sNDw/HggULcOnSJcyePXsgh0B+RhRFFBQUoL6+HoIg\nQKPR4NVXX+02aujEiROIjIyEyWRCSUkJ7t69i82bNyM4OBiCIKCzsxMVFRWorKx0DXd+tuOk0+lE\nUlKS7MfmK80XUmJiQdSD5uZmFBUVITw8HFFRUTCZTKrsxd0XP//8M+rr6xEfH4+0tDSv3weLxQKT\nyYSlS5di//79iI2N9fo+IOPHj0dRUZFX25B/u3PnDq5cuYK5c+e6hi87HA5kZWXBYrG4RhgJguBa\nP3HiRCQnJyM/Px9msxlOpxOBgYGIjY3F0qVLYTAY3O7rzJkzuHPnDpYvXy7PwXUFLt++ZMLEgsiD\niooKfPHFF/jzn/+Mhw8fori4GI8ePXJ9oQqC4Kpufbbata2tDatXr1bdKIYHDx4gJSUFcXFxrmXt\n7e2oqalBTU0NJkyYgPj4+Be2czgcqK+vx927dzFr1iwAwMyZM3Hz5k0kJyd7HYfZbO7/QZDfEEUR\n586dg91ux9atW7ut02q1WL16dY/bDx8+HEuWLPFqnytWrEBsbKy3odJzBNFDQ1RZWRkAICEhQdaA\niJRkt9u7zbFQW1uLS5cuQavVuqr9eyOKIk6dOoVPPvkEw4YNG1A8Dx8+fOF24koRRRHXrl1DVVWV\n6z0KCgrCuHHj8Omnn2LZsmUIDAx8oW1bp9MhMjISycnJ0Ov1sNls2LdvH3bs2NGvO5fevXsXjx49\nciUppC41NTUoKCiAzWZDamqq7Oe/7N99jx5IW97wMdKW1w9MLIie8dlnnyE6OtqVRDy9PJ4mFM9f\nLtOmTUNMTIzkcTidTmRmZmL48OFoaWlBamoqIiIiJN+PHERRRGNjI4qKimA2m+FwOLBy5UoEBwf3\nu8wDBw688CuW/I/dbsetW7dcU7mLoohx48bh5ZdfhkajzNgCJhYDx8SC+uTu3bsoKSmBwWDAyy+/\n3OOXXHt7OwoKCpCQkICIiAi/6pPQ1NSEwsJCLF26tNfXOp1OFBYWorq6GjqdDmvWrPF4rFarFffu\n3UNFRUW3jmNOpxMAEBkZidDQULS2tqK1tRV1dXXYuHEjTCYTRFHExYsX0dzcDFEUuyU9VqsVISEh\nWLp0aZ9//dfV1SEnJwdGoxGpqakIDQ0F0PVH3m63IzAwsE/lAEBHRwfu3LmDuro62O32buue/dMS\nHh7u6rwphStXrsBkMmHixImSlEfysVgsOHPmDBwOB/R6PSZNmoT4+HjFEonnyf7d19IgbXlhyv8A\nYWJBvTKbzfj000+RlJQEq9WKGzduwG63Y9SoURgzZgxSU1O7Tbn8+eefY9q0aQC62uWf/eX/tLy8\nvDz85S9/6dOvcFEUUVJSgmHDhrltw5faoUOHsGrVKq++BJuamnDu3DnX3TmfJgBP/28wGBAXF4e4\nuDi3Hcfq6+vR1tYGk8kEk8nk1Zd7S0sLfvzxR9fz5/cNANHR0YiKisL58+dhMpmwbNky2Gw25Obm\noqOjA0BXu7VWq0VnZydEUcSYMWPw6quvdttXQ0MDCgsLXUNLAwMDMWnSJIwdO9Zjh7jB8NVXX+H1\n11+XdZ80cO3t7cjMzMTWrVsRFBSkdDhuyf7d1ypxYmFiYkF+qLOzE01NTWhqasL9+/eRk5ODXbt2\ndftSvX79OsrLy6HX613bOZ1OiKKIgIAALF68GDdu3EB9fb1rnSAIiImJQXR0NCorK1FbW+vaZurU\nqWhtbcXt27exceNGr754veVwOHD8+HFXrCaTCVFRUX7bqUsURdTW1qKyshJz5szxeJ+O51VXV+PK\nlSuuz1AURYSHh2P69OmKfSlYLBYcO3YMycnJSExMVCQG6r/Kykpcu3YNWq0W48ePx/Tp05UO6QVM\nLAaOiYUKWCwWFBcXo66uzrXMXZX88zUHnpZ7qs73tP3znv3F/PxzURThdDqh1+sxffp0REZGuqpA\nnU4nqqurUVNTg7i4OIwdO/aF6lGbzYZDhw4hKSkJkydPxsWLF9HS0oKAgADMnz/fVa0vFYfDgceP\nH6OsrAzV1dVIS0tzJVA0+KqqqlBaWgq73Q5RFOFwOLBmzRp+Bn6spaUF3377LRYuXIjo6Gilw3mB\n/InFL9KWZ1L+hn09JhZlZWVMLHyExWJBS0sLHj16hKamJld1NQBXO6W/9WcYiPLyctTW1mL69Okw\nmUywWCy4evUq2traoNFoXO+D0WhEcnKy246CNpsN9fX1rkl39Ho9DAYDgoODERERgWHDhnV7P5+2\nDU+YMIG/lgeZKIrIzc2F0WjESy+9xCYPP2c2m5Gfnw+bzYbQ0FDMmDHDZz/TiooKxMXFyffd97hR\n2vJCw6Utrx88JhbA/zI3IiKioWLChAn9GgrdL0MtsSAiIqJB9OShtOWFKD/vDWfeJCIiUoz6mq99\nY+AwERERqQJrLIiIiJSiwg73TCyIiIiUImNiIYoidu3ahdu3b8NgMGD37t3dhvz+8MMP2Lt3L3Q6\nHd544w2kp6f3uo07bAohIiIaArKzs2G1WnHw4EH84Q9/QEZGhmud3W7Hxx9/jH/961/497//jczM\nTDQ3N/e4jSessSAiIlKMfDUWBQUFWLBgAYCuGyiWlJS41pWXlyMmJsZ1K4OZM2fi0qVLKCws9LiN\nJ0wsiIiIlCJjU0hbWxtCQkJcz3U6HZxOJzQazQvrgoOD8eTJE7S3t3vcxhMmFkREREoJNsm2K6PR\niPb2dtfzZxMEo9GItrY217r29naYTKYet/GEfSyIiIiGgBkzZiA3NxcAUFhY2G3a8gkTJqCqqgqP\nHz+G1WrFlStXMH36dKSkpHjcxhPOvElERDQEPDvCAwAyMjJQWlqKjo4OpKenIycnB5999hlEUcSm\nTZuwdetWt9vExcX1uB8mFkRERCQZNoUQERGRZJhYEBERkWSYWBAREZFkmFgQERGRZJhYEBERkWSY\nWBAREZFkmFgQERGRZJhYEBERkWT+HyFYB52uOe5jAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x52cb89f50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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i7Nixcq//zp07XLt2rdkpjcbo9XrKysqa3Ov5+flUVlY6+GSYzWY++eQTnn76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\nZKJTK0L1iATuXRECTBUVUFGBeew4WLCQ0BYftDZx4e4DPj5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2gGstHr6914QGzK0uo2be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IIIYeSIaE84Fa8/MXJaUWRkl6g8Wn3JbFMOyiH7DrHHRhTWdcgVh+s3blAzaFCX5ZsL8TpkzyED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\nEUFERERhYRFBREREYWERQURERGH5/2bUW206RDV2AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x585537910>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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auX37Nvn5+XJZaGgoM2fOdBobQpIk9u7dy4svvijbNFgsFnx8fAgPD2fs2LGdmnF3tq2X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AJiqy0eEKwUG9tQocWkSdP+A0160TTphTctXvTCC9Ob9qJp08OKJq3WaI0p0ArtEtClgEVguxyW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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x5760ba190>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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mzZrFsGHDWi1Teno6M2bMQK1WM2PGDN566y3UajVOTk4sXLiQ2NjYNjsTlUpldznDHkOH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\nJMPEgoiIiCTDxIKIiIgkw8SCiIiIJPN/3KmppvlwnF8AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x587c87490>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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CEyZM6OKKMBgMXL58mS+//JKmpiYEQSA0NJRly5bZ1a8vSRIHDhxg//79Vj9gJEkiIyOD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\nMwwWREREFDMMFkRERBQzDBZEREQUM/8D/T0jQGse+9cAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x59042ecd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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esHnzZg4cOCDPAQuCIM+nxMXFMWPGjG4refDgAUVFRfJnURRlR8yXb9xHjx5x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\nIiKKCEMEERERRYQhgoiIiCLyP49MvYZ+D3P+AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x594928a50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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aa+ONN97oU/p3dnY2mZmZrFq1qk0ti5qaGs6dO8fYsWNZunSpdl5ISkrCbDaz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\nLIiIiEgyTCyIiIhIMv8//cbxthKiiUwAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x528d6d4d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for hashtag in popularHashtagsList:\n",
+    "    createHashtagHeatmap(hashtag)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our Thoughts on this Visualization**\n",
+    "\n",
+    "It becomes immediately obvious that certain locations tend to favor certain hashtags - in example, STL appears only to be used within Ferguson and Missouri, whereas Ferguson, as a more general hashtag, it broadly used. Further, the NMOS14 and MediaBlackout flags have clear aggregations within the US, potentially implying geo-located communities spreading information. \n",
+    "\n",
+    "To further our understanding, aggregating hashtags explicitly in support of Mike Brown or the officer Darren Wilson, could also yield more information about the relationship between hashtag users and their perceptions - beyond that of where they may be located."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Hashtags by Alignment\n",
+    "We start by creating alignment dataframes of different hashtags, then plot the total yield of tweets in these alignments in order to determine whether conclusions can be drawn about the distinctive populations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "mikeBrown = ['MIKEBROWN', 'HANDSUPDONTSHOOT','JUSTICEFORMIKEBROWN',\n",
+    "             'DONTSHOOT','POLICESTATE','RIPMIKEBROWN',\n",
+    "             'IFTHEYGUNNEDMEDOWN']\n",
+    "darrenWilson = ['TCOT', 'DARRENWILSON', 'UNITEBLUE','TEAPARTY',\n",
+    "                'SUPPORTDARENWILSON', 'GOP']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "mikeBrownDf = (shootingHashtagsDf[shootingHashtagsDf.hashtag.isin(mikeBrown)]\n",
+    "               .set_index('createdDatetime')\n",
+    "               .groupby(pd.TimeGrouper('Min'))\n",
+    "               .count()\n",
+    "               .reset_index())\n",
+    "darrenWilsonDf = (shootingHashtagsDf[shootingHashtagsDf.hashtag.isin(darrenWilson)]\n",
+    "                  .set_index('createdDatetime')\n",
+    "                  .groupby(pd.TimeGrouper('Min'))\n",
+    "                  .count()\n",
+    "                  .reset_index())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>384</td>\n",
+       "      <td>384</td>\n",
+       "      <td>384</td>\n",
+       "      <td>384</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-14 00:01:00</td>\n",
+       "      <td>284</td>\n",
+       "      <td>284</td>\n",
+       "      <td>284</td>\n",
+       "      <td>284</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-14 00:02:00</td>\n",
+       "      <td>220</td>\n",
+       "      <td>220</td>\n",
+       "      <td>220</td>\n",
+       "      <td>220</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-14 00:03:00</td>\n",
+       "      <td>236</td>\n",
+       "      <td>236</td>\n",
+       "      <td>236</td>\n",
+       "      <td>236</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-14 00:04:00</td>\n",
+       "      <td>290</td>\n",
+       "      <td>290</td>\n",
+       "      <td>290</td>\n",
+       "      <td>290</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-14 00:05:00</td>\n",
+       "      <td>348</td>\n",
+       "      <td>348</td>\n",
+       "      <td>348</td>\n",
+       "      <td>348</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-14 00:06:00</td>\n",
+       "      <td>270</td>\n",
+       "      <td>270</td>\n",
+       "      <td>270</td>\n",
+       "      <td>270</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-14 00:07:00</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-14 00:08:00</td>\n",
+       "      <td>274</td>\n",
+       "      <td>274</td>\n",
+       "      <td>274</td>\n",
+       "      <td>274</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-14 00:09:00</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>260</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      createdDatetime  date  hashtag  hour  tweetId  x  y\n",
+       "0 2014-08-14 00:00:00   384      384   384      384  2  2\n",
+       "1 2014-08-14 00:01:00   284      284   284      284  4  4\n",
+       "2 2014-08-14 00:02:00   220      220   220      220  0  0\n",
+       "3 2014-08-14 00:03:00   236      236   236      236  2  2\n",
+       "4 2014-08-14 00:04:00   290      290   290      290  0  0\n",
+       "5 2014-08-14 00:05:00   348      348   348      348  0  0\n",
+       "6 2014-08-14 00:06:00   270      270   270      270  2  2\n",
+       "7 2014-08-14 00:07:00   260      260   260      260  2  2\n",
+       "8 2014-08-14 00:08:00   274      274   274      274  0  0\n",
+       "9 2014-08-14 00:09:00   260      260   260      260  2  2"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mikeBrownDf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>date</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-14 00:00:00</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-14 00:01:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-14 00:02:00</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-14 00:03:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-14 00:04:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-14 00:05:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-14 00:06:00</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-14 00:07:00</td>\n",
+       "      <td>20</td>\n",
+       "      <td>20</td>\n",
+       "      <td>20</td>\n",
+       "      <td>20</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-14 00:08:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-14 00:09:00</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      createdDatetime  date  hashtag  hour  tweetId  x  y\n",
+       "0 2014-08-14 00:00:00     2        2     2        2  0  0\n",
+       "1 2014-08-14 00:01:00     6        6     6        6  0  0\n",
+       "2 2014-08-14 00:02:00    10       10    10       10  0  0\n",
+       "3 2014-08-14 00:03:00     6        6     6        6  0  0\n",
+       "4 2014-08-14 00:04:00     6        6     6        6  0  0\n",
+       "5 2014-08-14 00:05:00     6        6     6        6  0  0\n",
+       "6 2014-08-14 00:06:00    10       10    10       10  0  0\n",
+       "7 2014-08-14 00:07:00    20       20    20       20  0  0\n",
+       "8 2014-08-14 00:08:00     6        6     6        6  0  0\n",
+       "9 2014-08-14 00:09:00    10       10    10       10  0  0"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "darrenWilsonDf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x408960ad0>"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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2traAdkRTf39/JkyYgIODg26dmJiYdKOoOjo6Eh1tug4WBbbqpEQJR5RKW0uH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\nQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x407f4aa10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "\n",
+    "mikeBrownDf.plot(kind='line', x='createdDatetime', y='hashtag', label='Mike Brown Supporters', ax=ax)\n",
+    "darrenWilsonDf.plot(kind='line', x='createdDatetime', y='hashtag', ax = ax, secondary_y=True, label='Darren Wilson Supporters')\n",
+    "plt.title('Number of tweets by Users')\n",
+    "\n",
+    "ax.set_ylabel('Count of twets (Mike Brown Supporters)', color='b')\n",
+    "ax.right_ax.set_ylabel('Count of tweets (Darren Wilson Supporters)', color='g')\n",
+    "\n",
+    "plt.xlabel('Time')\n",
+    "plt.ylabel('Number of Tweets over Time')\n",
+    "plt.title('Hashtag useage over Time')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Our Thoughts on this Visualization**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are certainly similar ebbs and peaks in the data, but what is immediately striking is the gain of Darren Wilson aligned tweets with time, as compared to the ebb of Mike Brown aligned tweets. Several relationships with more time could be explored here through detailed network analysis including: did people change their minds as more information was aligned? Did Mike Brown aligned tweeters begin to aggresively parody Darren Wilson aligned tweeters?\n",
+    "\n",
+    "A visualization like this of the aggregated, sorted data provides a powerful way of framing the different sides of an 'argument' being played out over social media on a grand scale"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Conclusions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "The union of spatial and temporal data visualization, coupled with contextual information, we find a compelling way of presenting large amounts of data. Further, aggregation of data metrics based upon research yields opportunity to tell compelling stories and reduce the complexity of the visualization. Opportunities that we were not able to implement - namely selecting other axes to which to aggregate data - may be worthwhile for a person interested in pursuing this particular project in the future. There may also be filtering techniques for the data that could also yield more clean or parseable visualizations. \n",
+    "\n",
+    "On the whole, it is clear that making compelling visualizations is a matter of creativity. The opportunity to build interactive graphs is truly an area in which we see strong potential for complex data being shown in a way that a human can interact with fully. \n",
+    "\n",
+    "When working with large datasets, it is also critical to understand how long it will take to collect and plot. We went through many iterations of our functions simply so that the time to run each was within a reasonable period of time (on the order of tens of minutes). Using ipython notebooks proved useful for this aspect, as once the data was read in, there was no need to do it again each time something was to be built.\n",
+    "\n",
+    "As for understanding social media and it's role in activism, there are clearly some relationships between present activism (physically acting) and virtual activism (voicing support remotely) - namely in observed patterns in Ferguson and Los Angeles, a site of protest during the events. What we were unable to capture here was whether one incited or caused the other, or if the relationship between the media and the actions was primarily active reporting/information spread (reactionary to events). Further work on this project could ask this question and dive more deeply into classifying tweets as action based or support based, triggering or reporting, etc. As a first pass, we are pleased with what these visualizations, and the others we developed along the way through our hypotheses, tell us about the data and have found them compelling with potential to improve."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/Hashtags_Over_Time.ipynb b/Hashtags_Over_Time.ipynb
new file mode 100644
index 0000000..078fa84
--- /dev/null
+++ b/Hashtags_Over_Time.ipynb
@@ -0,0 +1,2692 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Mapping Twitter Data\n",
+    "This notebook provides the basis for developing spatial representations of a variety of interesting data that is presented in the Ferguson Twitter dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/Sophia/anaconda/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
+      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "% matplotlib inline\n",
+    "import json\n",
+    "import time\n",
+    "import pandas as pd\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets\n",
+    "import matplotlib.cm as cm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's begin with the data. We have two datasets. The first is data from the two weeks following the initial shooting. The second is data from the two weeks following the indictment. Twitter has provided an extensive amount of data for us, and we have developed a cleaning mechanism which can be observed in a seperate script. The data is placed in a data frame:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def ReadAndAggregate(linesAtATime,filepath,aggregationFunction):\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of lines\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print i\n",
+    "                df = pd.DataFrame(data=data)\n",
+    "#                 print df.info()\n",
+    "                #First time running through\n",
+    "                if (i == linesAtATime):\n",
+    "                    agg = aggregationFunction(df)\n",
+    "                else:\n",
+    "                    agg = aggregationFunction(df, agg)\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "            if (i >= 300000):\n",
+    "                break\n",
+    "        #Handle the last few tweets\n",
+    "#         df = pd.DataFrame(data=data)\n",
+    "#         print df.info()\n",
+    "#         agg = aggregationFunction(df, agg)\n",
+    "    #return the aggregation\n",
+    "    return agg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def createHashtagsDf (df, hashtagsDataFrame=pd.DataFrame()):\n",
+    "    \n",
+    "    #time based recodes\n",
+    "    df['DoW'] = df['created_at'].apply(lambda x: str(x)[0:3:])\n",
+    "    df['Month'] = df['created_at'].apply(lambda x: str(x)[4:7:])\n",
+    "    df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])\n",
+    "    df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))\n",
+    "    df['Minute'] = df['created_at'].apply(lambda x: int(str(x)[14:16:]))\n",
+    "\n",
+    "    #let's grab the coordinates from the coordinates field, which is actually a dictionary\n",
+    "    coords = []\n",
+    "    for i in range(len(df)):\n",
+    "        location = df['coordinates'][i]\n",
+    "        try: #want to make sure that null values don't throw an exception\n",
+    "            coords.append(location.get('coordinates'))\n",
+    "        except:\n",
+    "            coords.append([None,None])\n",
+    "\n",
+    "    df['Coords'] = coords\n",
+    "    df['x'] = df['Coords'].apply(lambda x: x[0])\n",
+    "    df['y'] = df['Coords'].apply(lambda x: x[1])\n",
+    "\n",
+    "    #now, let's grab the information from place, which is similarly a very detailed dictionary of elements\n",
+    "    name = []\n",
+    "    country = []\n",
+    "    coordinates = []\n",
+    "    full_name = []\n",
+    "    for i in range(len(df)):\n",
+    "        location = df['place'][i]\n",
+    "        try:\n",
+    "            coordinates.append(location.get('bounding_box').get('coordinates'))\n",
+    "            name.append(location.get('name'))\n",
+    "            full_name.append(location.get('full_name'))\n",
+    "            country.append(location.get('country'))\n",
+    "        except:\n",
+    "            coordinates.append([[[0,0],[0,0],[0,0],[0,0]]])\n",
+    "            name.append('')\n",
+    "            full_name.append('')\n",
+    "            country.append('')\n",
+    "\n",
+    "    mean_coords = []\n",
+    "    for box in coordinates:\n",
+    "        mean_coord_x = (box[0][0][0]+box[0][1][0]+box[0][2][0]+box[0][3][0])/4\n",
+    "        mean_coord_y = (box[0][0][1]+box[0][1][1]+box[0][2][1]+box[0][3][1])/4\n",
+    "        mean_coords.append([mean_coord_x,mean_coord_y])\n",
+    "\n",
+    "#     df['city'] = name\n",
+    "#     df['country'] = country\n",
+    "#     df['full_name'] = full_name\n",
+    "    df['P_Coords'] = mean_coords\n",
+    "    df['x_p'] = df['P_Coords'].apply(lambda x: x[0])\n",
+    "    df['y_p'] = df['P_Coords'].apply(lambda x: x[1])\n",
+    "    \n",
+    "    rowsToAdd = []\n",
+    "    for index,tweet in df.iterrows():\n",
+    "        for hashtag in tweet['entities_hashtags_text']:\n",
+    "            rowsToAdd.append({\n",
+    "                    'DoW': tweet['DoW'],\n",
+    "                    'Month': tweet['Month'],\n",
+    "                    'DoM': tweet['DoM'],\n",
+    "                    'Hour': tweet['Hour'],\n",
+    "                    'Minute': tweet['Minute'],\n",
+    "                    'Hashtag': hashtag.upper(),\n",
+    "                    'x': tweet['x'],\n",
+    "                    'y': tweet['y'],\n",
+    "                    'x_p': tweet['x_p'],\n",
+    "                    'y_p': tweet['y_p'],\n",
+    "                    'tweetId': tweet['id_str']\n",
+    "                })\n",
+    "    tempDf = pd.DataFrame(rowsToAdd)\n",
+    "    hashtagsDataFrame = hashtagsDataFrame.append(tempDf)\n",
+    "\n",
+    "    return hashtagsDataFrame"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100000\n",
+      "200000\n",
+      "300000\n",
+      "400000\n",
+      "500000\n",
+      "600000\n",
+      "700000\n",
+      "800000\n",
+      "900000\n",
+      "1000000\n",
+      "1100000\n",
+      "1200000\n",
+      "1300000\n",
+      "1400000\n",
+      "1500000\n",
+      "1600000\n",
+      "1700000\n",
+      "1800000\n",
+      "1900000\n",
+      "2000000\n",
+      "2100000\n",
+      "2200000\n",
+      "2300000\n",
+      "2400000\n",
+      "2500000\n",
+      "2600000\n",
+      "2700000\n",
+      "2800000\n",
+      "2900000\n",
+      "3000000\n",
+      "3100000\n",
+      "3200000\n",
+      "3300000\n",
+      "3400000\n",
+      "3500000\n",
+      "3600000\n",
+      "3700000\n",
+      "3800000\n",
+      "3900000\n"
+     ]
+    }
+   ],
+   "source": [
+    "filename='data/cleanedShootingTweets.json'\n",
+    "data = ReadAndAggregate(100000,filename, createHashtagsDf)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "data['x'].fillna(value = data['x_p'], inplace = True)\n",
+    "data['y'].fillna(value = data['y_p'], inplace = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>DoM</th>\n",
+       "      <th>DoW</th>\n",
+       "      <th>Hashtag</th>\n",
+       "      <th>Hour</th>\n",
+       "      <th>Minute</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>x_p</th>\n",
+       "      <th>y</th>\n",
+       "      <th>y_p</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>52</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064141332029440</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "    <tr>\n",
+       "      <th>2</th>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>USNEWS</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064194309906436</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064196642340864</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064196931330049</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>MIKEBROWN</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
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+       "      <td>501064196931330049</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>TCOT</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>UNITEBLUE</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>17</td>\n",
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+       "      <td>TEAPARTY</td>\n",
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+       "      <td>501064197632167936</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>GOP</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064198009655296</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>CRIMEBUTNOTIME</td>\n",
+       "      <td>17</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>17</td>\n",
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+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
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+       "      <td>Aug</td>\n",
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+       "      <td>0</td>\n",
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+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>POLICEBRUTALITY</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064199142117378</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064200035516416</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064201041743872</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064201251880961</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064201256071168</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>MIKEBROWN</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064201503113216</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064201503113216</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064202245521409</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064202295848960</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064202380115971</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064203135102977</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>STANDWITHFERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064203135102977</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>HANDSUPDONTSHOOT</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064203135102977</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>JUSTICEFORMIKEBROWN</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064203135102977</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58829</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>RUSSIA</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321699904188416</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58830</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321699904188416</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58831</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321702525628416</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58832</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321703121219585</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58833</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>GAZA</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321703138385922</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58834</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>ISRAEL</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321703138385922</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58835</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321703138385922</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58836</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>ISIS</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321703138385922</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58837</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321703880359936</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58838</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321704379891712</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58839</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321705394900992</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58840</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>SAFESPACE</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321705394900992</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58841</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321705747230720</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58842</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>HANNITY</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321705747230720</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58843</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321706963566592</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58844</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321707588517888</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58845</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321707966025728</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58846</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321710717091841</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58847</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321712201859073</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58848</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321712386416640</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58849</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321714236502017</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58850</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321715574079488</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58851</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321716652433408</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58852</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>HANDSUPDONTSHOOT</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321718443380737</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58853</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSONSHOOTING</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321718443388928</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58854</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321718443388928</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58855</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSONRIOT</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321718443388928</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58856</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321718950903808</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58857</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321718971469824</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58858</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321719734841344</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4159744 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      DoM  DoW              Hashtag  Hour  Minute Month             tweetId  \\\n",
+       "0      17  Sun             FERGUSON    17      52   Aug  501064141332029440   \n",
+       "1      17  Sun             FERGUSON    17      53   Aug  501064171707170816   \n",
+       "2      17  Sun             FERGUSON    17      53   Aug  501064180468682752   \n",
+       "3      17  Sun               USNEWS    17      53   Aug  501064194309906436   \n",
+       "4      17  Sun             FERGUSON    17      53   Aug  501064196642340864   \n",
+       "5      17  Sun             FERGUSON    17      53   Aug  501064196931330049   \n",
+       "6      17  Sun            MIKEBROWN    17      53   Aug  501064196931330049   \n",
+       "7      17  Sun             FERGUSON    17      53   Aug  501064197632167936   \n",
+       "8      17  Sun                 TCOT    17      53   Aug  501064197632167936   \n",
+       "9      17  Sun            UNITEBLUE    17      53   Aug  501064197632167936   \n",
+       "10     17  Sun             TEAPARTY    17      53   Aug  501064197632167936   \n",
+       "11     17  Sun                  GOP    17      53   Aug  501064197632167936   \n",
+       "12     17  Sun             FERGUSON    17      53   Aug  501064198009655296   \n",
+       "13     17  Sun       CRIMEBUTNOTIME    17      53   Aug  501064198009655296   \n",
+       "14     17  Sun             FERGUSON    17      53   Aug  501064198059597824   \n",
+       "15     17  Sun             FERGUSON    17      53   Aug  501064199142117378   \n",
+       "16     17  Sun      POLICEBRUTALITY    17      53   Aug  501064199142117378   \n",
+       "17     17  Sun             FERGUSON    17      53   Aug  501064200035516416   \n",
+       "18     17  Sun             FERGUSON    17      53   Aug  501064201041743872   \n",
+       "19     17  Sun             FERGUSON    17      53   Aug  501064201251880961   \n",
+       "20     17  Sun             FERGUSON    17      53   Aug  501064201256071168   \n",
+       "21     17  Sun            MIKEBROWN    17      53   Aug  501064201503113216   \n",
+       "22     17  Sun             FERGUSON    17      53   Aug  501064201503113216   \n",
+       "23     17  Sun             FERGUSON    17      53   Aug  501064202245521409   \n",
+       "24     17  Sun             FERGUSON    17      53   Aug  501064202295848960   \n",
+       "25     17  Sun             FERGUSON    17      53   Aug  501064202380115971   \n",
+       "26     17  Sun             FERGUSON    17      53   Aug  501064203135102977   \n",
+       "27     17  Sun    STANDWITHFERGUSON    17      53   Aug  501064203135102977   \n",
+       "28     17  Sun     HANDSUPDONTSHOOT    17      53   Aug  501064203135102977   \n",
+       "29     17  Sun  JUSTICEFORMIKEBROWN    17      53   Aug  501064203135102977   \n",
+       "...    ..  ...                  ...   ...     ...   ...                 ...   \n",
+       "58829  21  Thu               RUSSIA     5      10   Aug  502321699904188416   \n",
+       "58830  21  Thu             FERGUSON     5      10   Aug  502321699904188416   \n",
+       "58831  21  Thu             FERGUSON     5      10   Aug  502321702525628416   \n",
+       "58832  21  Thu             FERGUSON     5      10   Aug  502321703121219585   \n",
+       "58833  21  Thu                 GAZA     5      10   Aug  502321703138385922   \n",
+       "58834  21  Thu               ISRAEL     5      10   Aug  502321703138385922   \n",
+       "58835  21  Thu             FERGUSON     5      10   Aug  502321703138385922   \n",
+       "58836  21  Thu                 ISIS     5      10   Aug  502321703138385922   \n",
+       "58837  21  Thu             FERGUSON     5      10   Aug  502321703880359936   \n",
+       "58838  21  Thu             FERGUSON     5      10   Aug  502321704379891712   \n",
+       "58839  21  Thu             FERGUSON     5      10   Aug  502321705394900992   \n",
+       "58840  21  Thu            SAFESPACE     5      10   Aug  502321705394900992   \n",
+       "58841  21  Thu             FERGUSON     5      10   Aug  502321705747230720   \n",
+       "58842  21  Thu              HANNITY     5      10   Aug  502321705747230720   \n",
+       "58843  21  Thu             FERGUSON     5      10   Aug  502321706963566592   \n",
+       "58844  21  Thu             FERGUSON     5      10   Aug  502321707588517888   \n",
+       "58845  21  Thu             FERGUSON     5      10   Aug  502321707966025728   \n",
+       "58846  21  Thu             FERGUSON     5      10   Aug  502321710717091841   \n",
+       "58847  21  Thu             FERGUSON     5      10   Aug  502321712201859073   \n",
+       "58848  21  Thu             FERGUSON     5      10   Aug  502321712386416640   \n",
+       "58849  21  Thu             FERGUSON     5      10   Aug  502321714236502017   \n",
+       "58850  21  Thu             FERGUSON     5      10   Aug  502321715574079488   \n",
+       "58851  21  Thu             FERGUSON     5      10   Aug  502321716652433408   \n",
+       "58852  21  Thu     HANDSUPDONTSHOOT     5      10   Aug  502321718443380737   \n",
+       "58853  21  Thu     FERGUSONSHOOTING     5      10   Aug  502321718443388928   \n",
+       "58854  21  Thu             FERGUSON     5      10   Aug  502321718443388928   \n",
+       "58855  21  Thu         FERGUSONRIOT     5      10   Aug  502321718443388928   \n",
+       "58856  21  Thu             FERGUSON     5      10   Aug  502321718950903808   \n",
+       "58857  21  Thu             FERGUSON     5      10   Aug  502321718971469824   \n",
+       "58858  21  Thu             FERGUSON     5      10   Aug  502321719734841344   \n",
+       "\n",
+       "       x  x_p  y  y_p  \n",
+       "0      0    0  0    0  \n",
+       "1      0    0  0    0  \n",
+       "2      0    0  0    0  \n",
+       "3      0    0  0    0  \n",
+       "4      0    0  0    0  \n",
+       "5      0    0  0    0  \n",
+       "6      0    0  0    0  \n",
+       "7      0    0  0    0  \n",
+       "8      0    0  0    0  \n",
+       "9      0    0  0    0  \n",
+       "10     0    0  0    0  \n",
+       "11     0    0  0    0  \n",
+       "12     0    0  0    0  \n",
+       "13     0    0  0    0  \n",
+       "14     0    0  0    0  \n",
+       "15     0    0  0    0  \n",
+       "16     0    0  0    0  \n",
+       "17     0    0  0    0  \n",
+       "18     0    0  0    0  \n",
+       "19     0    0  0    0  \n",
+       "20     0    0  0    0  \n",
+       "21     0    0  0    0  \n",
+       "22     0    0  0    0  \n",
+       "23     0    0  0    0  \n",
+       "24     0    0  0    0  \n",
+       "25     0    0  0    0  \n",
+       "26     0    0  0    0  \n",
+       "27     0    0  0    0  \n",
+       "28     0    0  0    0  \n",
+       "29     0    0  0    0  \n",
+       "...   ..  ... ..  ...  \n",
+       "58829  0    0  0    0  \n",
+       "58830  0    0  0    0  \n",
+       "58831  0    0  0    0  \n",
+       "58832  0    0  0    0  \n",
+       "58833  0    0  0    0  \n",
+       "58834  0    0  0    0  \n",
+       "58835  0    0  0    0  \n",
+       "58836  0    0  0    0  \n",
+       "58837  0    0  0    0  \n",
+       "58838  0    0  0    0  \n",
+       "58839  0    0  0    0  \n",
+       "58840  0    0  0    0  \n",
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+       "58842  0    0  0    0  \n",
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+       "58844  0    0  0    0  \n",
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+       "58848  0    0  0    0  \n",
+       "58849  0    0  0    0  \n",
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+       "58851  0    0  0    0  \n",
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+       "58856  0    0  0    0  \n",
+       "58857  0    0  0    0  \n",
+       "58858  0    0  0    0  \n",
+       "\n",
+       "[4159744 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0        0\n",
+       "1        0\n",
+       "2        0\n",
+       "3        0\n",
+       "4        0\n",
+       "5        0\n",
+       "6        0\n",
+       "7        0\n",
+       "8        0\n",
+       "9        0\n",
+       "10       0\n",
+       "11       0\n",
+       "12       0\n",
+       "13       0\n",
+       "14       0\n",
+       "15       0\n",
+       "16       0\n",
+       "17       0\n",
+       "18       0\n",
+       "19       0\n",
+       "20       0\n",
+       "21       0\n",
+       "22       0\n",
+       "23       0\n",
+       "24       0\n",
+       "25       0\n",
+       "26       0\n",
+       "27       0\n",
+       "28       0\n",
+       "29       0\n",
+       "        ..\n",
+       "58829    0\n",
+       "58830    0\n",
+       "58831    0\n",
+       "58832    0\n",
+       "58833    0\n",
+       "58834    0\n",
+       "58835    0\n",
+       "58836    0\n",
+       "58837    0\n",
+       "58838    0\n",
+       "58839    0\n",
+       "58840    0\n",
+       "58841    0\n",
+       "58842    0\n",
+       "58843    0\n",
+       "58844    0\n",
+       "58845    0\n",
+       "58846    0\n",
+       "58847    0\n",
+       "58848    0\n",
+       "58849    0\n",
+       "58850    0\n",
+       "58851    0\n",
+       "58852    0\n",
+       "58853    0\n",
+       "58854    0\n",
+       "58855    0\n",
+       "58856    0\n",
+       "58857    0\n",
+       "58858    0\n",
+       "Name: x, dtype: float64"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data['x']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 4159744 entries, 0 to 58858\n",
+      "Data columns (total 11 columns):\n",
+      "DoM        object\n",
+      "DoW        object\n",
+      "Hashtag    object\n",
+      "Hour       int64\n",
+      "Minute     int64\n",
+      "Month      object\n",
+      "tweetId    object\n",
+      "x          float64\n",
+      "x_p        float64\n",
+      "y          float64\n",
+      "y_p        float64\n",
+      "dtypes: float64(4), int64(2), object(5)\n",
+      "memory usage: 380.8+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "data.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/Sophia/anaconda/lib/python2.7/site-packages/matplotlib/artist.py:221: MatplotlibDeprecationWarning: This has been deprecated in mpl 1.5, please use the\n",
+      "axes property.  A removal date has not been set.\n",
+      "  warnings.warn(_get_axes_msg, mplDeprecation, stacklevel=1)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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OTowbNw57e3vkcjk7d+5k7ty52NraEhMTQ926dRFCYG5ujrW1NVevXiUsLAwr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\nIYQQQgghauD/A8Chy1Xhi5niAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x178633d90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#the cartopy map, going simple outline for now\n",
+    "plt.figure(figsize=(15,15))\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "\n",
+    "#straight-up coordinate data which we just finished recoding\n",
+    "plt.scatter(data.x,data.y,color='r')\n",
+    "plt.scatter(data.x_p,data.y_p,color='g')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, to add a temporal element to this, we add a slider which pulls in some of the time columns we also just pulled out of interest."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "latLonPopulated = data[(data['x'] != 0) & (data['y'] != 0)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>DoM</th>\n",
+       "      <th>DoW</th>\n",
+       "      <th>Hashtag</th>\n",
+       "      <th>Hour</th>\n",
+       "      <th>Minute</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>x_p</th>\n",
+       "      <th>y</th>\n",
+       "      <th>y_p</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>420</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>RACISM</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064361788862465</td>\n",
+       "      <td>-80.670740</td>\n",
+       "      <td>-80.649699</td>\n",
+       "      <td>28.139480</td>\n",
+       "      <td>28.117874</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>421</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>SMH</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064361788862465</td>\n",
+       "      <td>-80.670740</td>\n",
+       "      <td>-80.649699</td>\n",
+       "      <td>28.139480</td>\n",
+       "      <td>28.117874</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>422</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>LUKEBRYAN</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064361788862465</td>\n",
+       "      <td>-80.670740</td>\n",
+       "      <td>-80.649699</td>\n",
+       "      <td>28.139480</td>\n",
+       "      <td>28.117874</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>423</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064361788862465</td>\n",
+       "      <td>-80.670740</td>\n",
+       "      <td>-80.649699</td>\n",
+       "      <td>28.139480</td>\n",
+       "      <td>28.117874</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>559</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064409679421440</td>\n",
+       "      <td>9.003542</td>\n",
+       "      <td>9.003542</td>\n",
+       "      <td>48.661709</td>\n",
+       "      <td>48.661709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>714</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>54</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064473965510656</td>\n",
+       "      <td>-122.251715</td>\n",
+       "      <td>-122.330602</td>\n",
+       "      <td>47.672935</td>\n",
+       "      <td>47.614817</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>991</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>54</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064579946790912</td>\n",
+       "      <td>-94.484954</td>\n",
+       "      <td>-94.498228</td>\n",
+       "      <td>37.048930</td>\n",
+       "      <td>37.096519</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1252</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>BALTIMORE</td>\n",
+       "      <td>17</td>\n",
+       "      <td>55</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064692165783553</td>\n",
+       "      <td>-76.620482</td>\n",
+       "      <td>-76.620482</td>\n",
+       "      <td>39.284713</td>\n",
+       "      <td>39.284713</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1253</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>55</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064692165783553</td>\n",
+       "      <td>-76.620482</td>\n",
+       "      <td>-76.620482</td>\n",
+       "      <td>39.284713</td>\n",
+       "      <td>39.284713</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1447</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>SADTRAILS</td>\n",
+       "      <td>17</td>\n",
+       "      <td>55</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064755596242944</td>\n",
+       "      <td>-124.414311</td>\n",
+       "      <td>-124.415765</td>\n",
+       "      <td>43.109538</td>\n",
+       "      <td>43.111422</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1570</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>55</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064800969822208</td>\n",
+       "      <td>-122.435979</td>\n",
+       "      <td>-122.435979</td>\n",
+       "      <td>37.770657</td>\n",
+       "      <td>37.770657</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1583</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>55</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064805306748929</td>\n",
+       "      <td>-90.243462</td>\n",
+       "      <td>-90.243462</td>\n",
+       "      <td>38.653099</td>\n",
+       "      <td>38.653099</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1997</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>56</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501064956989952000</td>\n",
+       "      <td>-122.923516</td>\n",
+       "      <td>-122.923516</td>\n",
+       "      <td>47.064528</td>\n",
+       "      <td>47.064528</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2124</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>56</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065004477472768</td>\n",
+       "      <td>-122.435979</td>\n",
+       "      <td>-122.435979</td>\n",
+       "      <td>37.770657</td>\n",
+       "      <td>37.770657</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2125</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>USA</td>\n",
+       "      <td>17</td>\n",
+       "      <td>56</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065004477472768</td>\n",
+       "      <td>-122.435979</td>\n",
+       "      <td>-122.435979</td>\n",
+       "      <td>37.770657</td>\n",
+       "      <td>37.770657</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2203</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>56</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065028146323457</td>\n",
+       "      <td>-116.583728</td>\n",
+       "      <td>-119.306608</td>\n",
+       "      <td>34.811688</td>\n",
+       "      <td>37.269176</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2204</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>DETROIT</td>\n",
+       "      <td>17</td>\n",
+       "      <td>56</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065028146323457</td>\n",
+       "      <td>-116.583728</td>\n",
+       "      <td>-119.306608</td>\n",
+       "      <td>34.811688</td>\n",
+       "      <td>37.269176</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2609</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>57</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065191430565889</td>\n",
+       "      <td>-78.643892</td>\n",
+       "      <td>-78.657837</td>\n",
+       "      <td>35.777026</td>\n",
+       "      <td>35.843981</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2610</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSONSHOOTING</td>\n",
+       "      <td>17</td>\n",
+       "      <td>57</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065191430565889</td>\n",
+       "      <td>-78.643892</td>\n",
+       "      <td>-78.657837</td>\n",
+       "      <td>35.777026</td>\n",
+       "      <td>35.843981</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2655</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>57</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065208350388224</td>\n",
+       "      <td>-77.014398</td>\n",
+       "      <td>-77.014398</td>\n",
+       "      <td>38.898603</td>\n",
+       "      <td>38.898603</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3024</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>57</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065344338100224</td>\n",
+       "      <td>-87.732013</td>\n",
+       "      <td>-87.732013</td>\n",
+       "      <td>41.833584</td>\n",
+       "      <td>41.833584</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3078</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>57</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065358594543616</td>\n",
+       "      <td>-82.407653</td>\n",
+       "      <td>-82.407653</td>\n",
+       "      <td>40.079697</td>\n",
+       "      <td>40.079697</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3714</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>58</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065604678561792</td>\n",
+       "      <td>-118.387101</td>\n",
+       "      <td>-118.411907</td>\n",
+       "      <td>34.279363</td>\n",
+       "      <td>34.020789</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3781</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>58</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065635452157952</td>\n",
+       "      <td>-0.668641</td>\n",
+       "      <td>-0.668641</td>\n",
+       "      <td>52.256827</td>\n",
+       "      <td>52.256827</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3824</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSONSYLLABUS</td>\n",
+       "      <td>17</td>\n",
+       "      <td>58</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065653353480192</td>\n",
+       "      <td>-77.014398</td>\n",
+       "      <td>-77.014398</td>\n",
+       "      <td>38.898603</td>\n",
+       "      <td>38.898603</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3901</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>MIKEBROWN</td>\n",
+       "      <td>17</td>\n",
+       "      <td>59</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065680695726082</td>\n",
+       "      <td>-90.294906</td>\n",
+       "      <td>-90.329325</td>\n",
+       "      <td>38.804851</td>\n",
+       "      <td>38.799436</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3902</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>59</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065680695726082</td>\n",
+       "      <td>-90.294906</td>\n",
+       "      <td>-90.329325</td>\n",
+       "      <td>38.804851</td>\n",
+       "      <td>38.799436</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3925</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>17</td>\n",
+       "      <td>59</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501065697976647680</td>\n",
+       "      <td>-97.049856</td>\n",
+       "      <td>-97.011168</td>\n",
+       "      <td>32.653455</td>\n",
+       "      <td>32.655678</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4763</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>18</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501066006341898242</td>\n",
+       "      <td>-86.850496</td>\n",
+       "      <td>-86.680738</td>\n",
+       "      <td>33.247880</td>\n",
+       "      <td>32.576227</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5017</th>\n",
+       "      <td>17</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>18</td>\n",
+       "      <td>0</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>501066092635492352</td>\n",
+       "      <td>-87.646291</td>\n",
+       "      <td>-87.732013</td>\n",
+       "      <td>41.951363</td>\n",
+       "      <td>41.833584</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57369</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502320986768035840</td>\n",
+       "      <td>-112.383763</td>\n",
+       "      <td>-112.424976</td>\n",
+       "      <td>33.448569</td>\n",
+       "      <td>33.412872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57466</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>BENZINO</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321028677525504</td>\n",
+       "      <td>-90.305300</td>\n",
+       "      <td>-90.276813</td>\n",
+       "      <td>38.744200</td>\n",
+       "      <td>38.755407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57467</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321028677525504</td>\n",
+       "      <td>-90.305300</td>\n",
+       "      <td>-90.276813</td>\n",
+       "      <td>38.744200</td>\n",
+       "      <td>38.755407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57468</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>STL</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321028677525504</td>\n",
+       "      <td>-90.305300</td>\n",
+       "      <td>-90.276813</td>\n",
+       "      <td>38.744200</td>\n",
+       "      <td>38.755407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57469</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>STLOUIS</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321028677525504</td>\n",
+       "      <td>-90.305300</td>\n",
+       "      <td>-90.276813</td>\n",
+       "      <td>38.744200</td>\n",
+       "      <td>38.755407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57470</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>MISSOURI</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321028677525504</td>\n",
+       "      <td>-90.305300</td>\n",
+       "      <td>-90.276813</td>\n",
+       "      <td>38.744200</td>\n",
+       "      <td>38.755407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57471</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>RIPMIKEBROWN</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321028677525504</td>\n",
+       "      <td>-90.305300</td>\n",
+       "      <td>-90.276813</td>\n",
+       "      <td>38.744200</td>\n",
+       "      <td>38.755407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57472</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>GROUNDZERO</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321028677525504</td>\n",
+       "      <td>-90.305300</td>\n",
+       "      <td>-90.276813</td>\n",
+       "      <td>38.744200</td>\n",
+       "      <td>38.755407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57473</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>CNN</td>\n",
+       "      <td>5</td>\n",
+       "      <td>7</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321028677525504</td>\n",
+       "      <td>-90.305300</td>\n",
+       "      <td>-90.276813</td>\n",
+       "      <td>38.744200</td>\n",
+       "      <td>38.755407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57750</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321204611809280</td>\n",
+       "      <td>-117.714228</td>\n",
+       "      <td>-117.688769</td>\n",
+       "      <td>33.489561</td>\n",
+       "      <td>33.469634</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57904</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUBITCHES</td>\n",
+       "      <td>5</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321282168283136</td>\n",
+       "      <td>-118.375100</td>\n",
+       "      <td>-118.408990</td>\n",
+       "      <td>34.015540</td>\n",
+       "      <td>34.006013</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57953</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321309561679873</td>\n",
+       "      <td>-85.864032</td>\n",
+       "      <td>-85.922362</td>\n",
+       "      <td>39.223454</td>\n",
+       "      <td>39.211432</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58043</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321323759390720</td>\n",
+       "      <td>-71.125213</td>\n",
+       "      <td>-71.142156</td>\n",
+       "      <td>42.331736</td>\n",
+       "      <td>42.323239</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58310</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321472883269633</td>\n",
+       "      <td>-121.036209</td>\n",
+       "      <td>-121.058188</td>\n",
+       "      <td>39.228261</td>\n",
+       "      <td>39.215572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58311</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>CNN</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321472883269633</td>\n",
+       "      <td>-121.036209</td>\n",
+       "      <td>-121.058188</td>\n",
+       "      <td>39.228261</td>\n",
+       "      <td>39.215572</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58360</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321496681754624</td>\n",
+       "      <td>-122.141444</td>\n",
+       "      <td>-122.149768</td>\n",
+       "      <td>47.601725</td>\n",
+       "      <td>47.597856</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58484</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321560607543296</td>\n",
+       "      <td>-90.277155</td>\n",
+       "      <td>-90.265822</td>\n",
+       "      <td>38.734562</td>\n",
+       "      <td>38.721618</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58485</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FREEDOM</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321560607543296</td>\n",
+       "      <td>-90.277155</td>\n",
+       "      <td>-90.265822</td>\n",
+       "      <td>38.734562</td>\n",
+       "      <td>38.721618</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58491</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321562393927680</td>\n",
+       "      <td>-83.134390</td>\n",
+       "      <td>-83.099288</td>\n",
+       "      <td>42.364129</td>\n",
+       "      <td>42.352787</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58689</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSONSHOOTING</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321633584242689</td>\n",
+       "      <td>-84.178042</td>\n",
+       "      <td>-84.175549</td>\n",
+       "      <td>39.721481</td>\n",
+       "      <td>39.719631</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58764</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321668560130048</td>\n",
+       "      <td>-90.389746</td>\n",
+       "      <td>-90.427646</td>\n",
+       "      <td>38.737716</td>\n",
+       "      <td>38.759510</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58765</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>BEYONDTODAY</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321668560130048</td>\n",
+       "      <td>-90.389746</td>\n",
+       "      <td>-90.427646</td>\n",
+       "      <td>38.737716</td>\n",
+       "      <td>38.759510</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58766</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>MIKEBROWN</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321668560130048</td>\n",
+       "      <td>-90.389746</td>\n",
+       "      <td>-90.427646</td>\n",
+       "      <td>38.737716</td>\n",
+       "      <td>38.759510</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58767</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>JUSTICEFORMIKEBROWN</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321668560130048</td>\n",
+       "      <td>-90.389746</td>\n",
+       "      <td>-90.427646</td>\n",
+       "      <td>38.737716</td>\n",
+       "      <td>38.759510</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58778</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321673153286144</td>\n",
+       "      <td>-79.272570</td>\n",
+       "      <td>-79.272570</td>\n",
+       "      <td>43.629311</td>\n",
+       "      <td>43.629311</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58779</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321673618857984</td>\n",
+       "      <td>-118.062700</td>\n",
+       "      <td>-118.018856</td>\n",
+       "      <td>33.985845</td>\n",
+       "      <td>33.975918</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58818</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>SOLIDARITY</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321695697276928</td>\n",
+       "      <td>-73.977142</td>\n",
+       "      <td>-73.977142</td>\n",
+       "      <td>40.780881</td>\n",
+       "      <td>40.780881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58819</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>KNOWJUSTICE</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321695697276928</td>\n",
+       "      <td>-73.977142</td>\n",
+       "      <td>-73.977142</td>\n",
+       "      <td>40.780881</td>\n",
+       "      <td>40.780881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58820</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>KNOWPEACE</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321695697276928</td>\n",
+       "      <td>-73.977142</td>\n",
+       "      <td>-73.977142</td>\n",
+       "      <td>40.780881</td>\n",
+       "      <td>40.780881</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58821</th>\n",
+       "      <td>21</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>5</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>502321695697276928</td>\n",
+       "      <td>-73.977142</td>\n",
+       "      <td>-73.977142</td>\n",
+       "      <td>40.780881</td>\n",
+       "      <td>40.780881</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>37851 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      DoM  DoW              Hashtag  Hour  Minute Month             tweetId  \\\n",
+       "420    17  Sun               RACISM    17      53   Aug  501064361788862465   \n",
+       "421    17  Sun                  SMH    17      53   Aug  501064361788862465   \n",
+       "422    17  Sun            LUKEBRYAN    17      53   Aug  501064361788862465   \n",
+       "423    17  Sun             FERGUSON    17      53   Aug  501064361788862465   \n",
+       "559    17  Sun             FERGUSON    17      53   Aug  501064409679421440   \n",
+       "714    17  Sun             FERGUSON    17      54   Aug  501064473965510656   \n",
+       "991    17  Sun             FERGUSON    17      54   Aug  501064579946790912   \n",
+       "1252   17  Sun            BALTIMORE    17      55   Aug  501064692165783553   \n",
+       "1253   17  Sun             FERGUSON    17      55   Aug  501064692165783553   \n",
+       "1447   17  Sun            SADTRAILS    17      55   Aug  501064755596242944   \n",
+       "1570   17  Sun             FERGUSON    17      55   Aug  501064800969822208   \n",
+       "1583   17  Sun             FERGUSON    17      55   Aug  501064805306748929   \n",
+       "1997   17  Sun             FERGUSON    17      56   Aug  501064956989952000   \n",
+       "2124   17  Sun             FERGUSON    17      56   Aug  501065004477472768   \n",
+       "2125   17  Sun                  USA    17      56   Aug  501065004477472768   \n",
+       "2203   17  Sun             FERGUSON    17      56   Aug  501065028146323457   \n",
+       "2204   17  Sun              DETROIT    17      56   Aug  501065028146323457   \n",
+       "2609   17  Sun             FERGUSON    17      57   Aug  501065191430565889   \n",
+       "2610   17  Sun     FERGUSONSHOOTING    17      57   Aug  501065191430565889   \n",
+       "2655   17  Sun             FERGUSON    17      57   Aug  501065208350388224   \n",
+       "3024   17  Sun             FERGUSON    17      57   Aug  501065344338100224   \n",
+       "3078   17  Sun             FERGUSON    17      57   Aug  501065358594543616   \n",
+       "3714   17  Sun             FERGUSON    17      58   Aug  501065604678561792   \n",
+       "3781   17  Sun             FERGUSON    17      58   Aug  501065635452157952   \n",
+       "3824   17  Sun     FERGUSONSYLLABUS    17      58   Aug  501065653353480192   \n",
+       "3901   17  Sun            MIKEBROWN    17      59   Aug  501065680695726082   \n",
+       "3902   17  Sun             FERGUSON    17      59   Aug  501065680695726082   \n",
+       "3925   17  Sun             FERGUSON    17      59   Aug  501065697976647680   \n",
+       "4763   17  Sun             FERGUSON    18       0   Aug  501066006341898242   \n",
+       "5017   17  Sun             FERGUSON    18       0   Aug  501066092635492352   \n",
+       "...    ..  ...                  ...   ...     ...   ...                 ...   \n",
+       "57369  21  Thu             FERGUSON     5       7   Aug  502320986768035840   \n",
+       "57466  21  Thu              BENZINO     5       7   Aug  502321028677525504   \n",
+       "57467  21  Thu             FERGUSON     5       7   Aug  502321028677525504   \n",
+       "57468  21  Thu                  STL     5       7   Aug  502321028677525504   \n",
+       "57469  21  Thu              STLOUIS     5       7   Aug  502321028677525504   \n",
+       "57470  21  Thu             MISSOURI     5       7   Aug  502321028677525504   \n",
+       "57471  21  Thu         RIPMIKEBROWN     5       7   Aug  502321028677525504   \n",
+       "57472  21  Thu           GROUNDZERO     5       7   Aug  502321028677525504   \n",
+       "57473  21  Thu                  CNN     5       7   Aug  502321028677525504   \n",
+       "57750  21  Thu             FERGUSON     5       8   Aug  502321204611809280   \n",
+       "57904  21  Thu         FERGUBITCHES     5       8   Aug  502321282168283136   \n",
+       "57953  21  Thu             FERGUSON     5       8   Aug  502321309561679873   \n",
+       "58043  21  Thu             FERGUSON     5       8   Aug  502321323759390720   \n",
+       "58310  21  Thu             FERGUSON     5       9   Aug  502321472883269633   \n",
+       "58311  21  Thu                  CNN     5       9   Aug  502321472883269633   \n",
+       "58360  21  Thu             FERGUSON     5       9   Aug  502321496681754624   \n",
+       "58484  21  Thu             FERGUSON     5       9   Aug  502321560607543296   \n",
+       "58485  21  Thu              FREEDOM     5       9   Aug  502321560607543296   \n",
+       "58491  21  Thu             FERGUSON     5       9   Aug  502321562393927680   \n",
+       "58689  21  Thu     FERGUSONSHOOTING     5       9   Aug  502321633584242689   \n",
+       "58764  21  Thu             FERGUSON     5       9   Aug  502321668560130048   \n",
+       "58765  21  Thu          BEYONDTODAY     5       9   Aug  502321668560130048   \n",
+       "58766  21  Thu            MIKEBROWN     5       9   Aug  502321668560130048   \n",
+       "58767  21  Thu  JUSTICEFORMIKEBROWN     5       9   Aug  502321668560130048   \n",
+       "58778  21  Thu             FERGUSON     5       9   Aug  502321673153286144   \n",
+       "58779  21  Thu             FERGUSON     5       9   Aug  502321673618857984   \n",
+       "58818  21  Thu           SOLIDARITY     5       9   Aug  502321695697276928   \n",
+       "58819  21  Thu          KNOWJUSTICE     5       9   Aug  502321695697276928   \n",
+       "58820  21  Thu            KNOWPEACE     5       9   Aug  502321695697276928   \n",
+       "58821  21  Thu             FERGUSON     5       9   Aug  502321695697276928   \n",
+       "\n",
+       "                x         x_p          y        y_p  \n",
+       "420    -80.670740  -80.649699  28.139480  28.117874  \n",
+       "421    -80.670740  -80.649699  28.139480  28.117874  \n",
+       "422    -80.670740  -80.649699  28.139480  28.117874  \n",
+       "423    -80.670740  -80.649699  28.139480  28.117874  \n",
+       "559      9.003542    9.003542  48.661709  48.661709  \n",
+       "714   -122.251715 -122.330602  47.672935  47.614817  \n",
+       "991    -94.484954  -94.498228  37.048930  37.096519  \n",
+       "1252   -76.620482  -76.620482  39.284713  39.284713  \n",
+       "1253   -76.620482  -76.620482  39.284713  39.284713  \n",
+       "1447  -124.414311 -124.415765  43.109538  43.111422  \n",
+       "1570  -122.435979 -122.435979  37.770657  37.770657  \n",
+       "1583   -90.243462  -90.243462  38.653099  38.653099  \n",
+       "1997  -122.923516 -122.923516  47.064528  47.064528  \n",
+       "2124  -122.435979 -122.435979  37.770657  37.770657  \n",
+       "2125  -122.435979 -122.435979  37.770657  37.770657  \n",
+       "2203  -116.583728 -119.306608  34.811688  37.269176  \n",
+       "2204  -116.583728 -119.306608  34.811688  37.269176  \n",
+       "2609   -78.643892  -78.657837  35.777026  35.843981  \n",
+       "2610   -78.643892  -78.657837  35.777026  35.843981  \n",
+       "2655   -77.014398  -77.014398  38.898603  38.898603  \n",
+       "3024   -87.732013  -87.732013  41.833584  41.833584  \n",
+       "3078   -82.407653  -82.407653  40.079697  40.079697  \n",
+       "3714  -118.387101 -118.411907  34.279363  34.020789  \n",
+       "3781    -0.668641   -0.668641  52.256827  52.256827  \n",
+       "3824   -77.014398  -77.014398  38.898603  38.898603  \n",
+       "3901   -90.294906  -90.329325  38.804851  38.799436  \n",
+       "3902   -90.294906  -90.329325  38.804851  38.799436  \n",
+       "3925   -97.049856  -97.011168  32.653455  32.655678  \n",
+       "4763   -86.850496  -86.680738  33.247880  32.576227  \n",
+       "5017   -87.646291  -87.732013  41.951363  41.833584  \n",
+       "...           ...         ...        ...        ...  \n",
+       "57369 -112.383763 -112.424976  33.448569  33.412872  \n",
+       "57466  -90.305300  -90.276813  38.744200  38.755407  \n",
+       "57467  -90.305300  -90.276813  38.744200  38.755407  \n",
+       "57468  -90.305300  -90.276813  38.744200  38.755407  \n",
+       "57469  -90.305300  -90.276813  38.744200  38.755407  \n",
+       "57470  -90.305300  -90.276813  38.744200  38.755407  \n",
+       "57471  -90.305300  -90.276813  38.744200  38.755407  \n",
+       "57472  -90.305300  -90.276813  38.744200  38.755407  \n",
+       "57473  -90.305300  -90.276813  38.744200  38.755407  \n",
+       "57750 -117.714228 -117.688769  33.489561  33.469634  \n",
+       "57904 -118.375100 -118.408990  34.015540  34.006013  \n",
+       "57953  -85.864032  -85.922362  39.223454  39.211432  \n",
+       "58043  -71.125213  -71.142156  42.331736  42.323239  \n",
+       "58310 -121.036209 -121.058188  39.228261  39.215572  \n",
+       "58311 -121.036209 -121.058188  39.228261  39.215572  \n",
+       "58360 -122.141444 -122.149768  47.601725  47.597856  \n",
+       "58484  -90.277155  -90.265822  38.734562  38.721618  \n",
+       "58485  -90.277155  -90.265822  38.734562  38.721618  \n",
+       "58491  -83.134390  -83.099288  42.364129  42.352787  \n",
+       "58689  -84.178042  -84.175549  39.721481  39.719631  \n",
+       "58764  -90.389746  -90.427646  38.737716  38.759510  \n",
+       "58765  -90.389746  -90.427646  38.737716  38.759510  \n",
+       "58766  -90.389746  -90.427646  38.737716  38.759510  \n",
+       "58767  -90.389746  -90.427646  38.737716  38.759510  \n",
+       "58778  -79.272570  -79.272570  43.629311  43.629311  \n",
+       "58779 -118.062700 -118.018856  33.985845  33.975918  \n",
+       "58818  -73.977142  -73.977142  40.780881  40.780881  \n",
+       "58819  -73.977142  -73.977142  40.780881  40.780881  \n",
+       "58820  -73.977142  -73.977142  40.780881  40.780881  \n",
+       "58821  -73.977142  -73.977142  40.780881  40.780881  \n",
+       "\n",
+       "[37851 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "latLonPopulated"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "hashtagGrouped = latLonPopulated.groupby('Hashtag').count().reset_index().sort_values(by = 'DoM', ascending = False)\n",
+    "sortedHashtags = hashtagGrouped['Hashtag'].tolist()\n",
+    "topHashtags = sortedHashtags[0:10]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[u'FERGUSON',\n",
+       " u'MIKEBROWN',\n",
+       " u'MICHAELBROWN',\n",
+       " u'FERGUSONSHOOTING',\n",
+       " u'JUSTICEFORMIKEBROWN',\n",
+       " u'CNN',\n",
+       " u'HANDSUPDONTSHOOT',\n",
+       " u'TCOT',\n",
+       " u'GAZA',\n",
+       " u'STL']"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "topHashtags"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def plotHashtagLocation(DoM, Hour):\n",
+    "    plt.figure(figsize=(15,15))\n",
+    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "    ax.coastlines()\n",
+    "    \n",
+    "    for i,hashtag in enumerate(topHashtags):\n",
+    "        subset = latLonPopulated[\n",
+    "            (latLonPopulated['DoM'] == str(DoM)) & \n",
+    "            (latLonPopulated['Hour']==Hour) & \n",
+    "            (latLonPopulated['Hashtag'] == hashtag)]\n",
+    "        if (len(subset) == 0):\n",
+    "            continue\n",
+    "        \n",
+    "        plt.scatter(subset.x,subset.y, color= cm.jet(i/float(len(topHashtags))), label = hashtag)\n",
+    "#         plt.scatter(subset.x_p,subset.y_p, color= cm.jet(i/float(len(topHashtags))), label = hashtag)\n",
+    "#     plt.axis([-180, 180, -75, 75])\n",
+    "    plt.axis([-180, 0, -75, 75])\n",
+    "    plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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fCgkBoqL/G6H+/ntTrFgRgbq6CtTX8yEtLYZFi3oz/+88Hh/5+ZUCefD5hKSk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\nFBERERERUTP8P5ACtX6ruzDFAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x15e2af890>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "DoM = widgets.IntSlider(min=10, max=27, value=17)\n",
+    "Hour = widgets.IntSlider(min=0, max=23, value=17)\n",
+    "widgets.interact(plotHashtagLocation,DoM = DoM, Hour=Hour)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "Since sliders aren't the most conducive, we actually animate this function..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "from matplotlib import animation\n",
+    "from IPython.display import HTML\n",
+    "from tempfile import NamedTemporaryFile\n",
+    "\n",
+    "def plotAnimationProperly(list_functions, data_to_plot, colors_to_plot):\n",
+    "    for i in range(len(list_functions)):\n",
+    "        list_functions[i].set_data(data_to_plot[i].x,data_to_plot[i].y)\n",
+    "        list_functions[i].set_color(colors_to_plot[i])\n",
+    "\n",
+    "#Note, the animation code courtesy of and adapted from http://jakevdp.github.io/blog/2013/05/12/embedding-matplotlib-animations/\n",
+    "VIDEO_TAG = \"\"\"<video controls>\n",
+    " <source src=\"data:video/x-m4v;base64,{0}\" type=\"video/mp4\">\n",
+    " Your browser does not support the video tag.\n",
+    "</video>\"\"\"\n",
+    "\n",
+    "def anim_to_html(anim):\n",
+    "    if not hasattr(anim, '_encoded_video'):\n",
+    "        with NamedTemporaryFile(suffix='.mp4') as f:\n",
+    "            anim.save(f.name, fps=20, extra_args=['-vcodec', 'libx264', '-pix_fmt', 'yuv420p'])\n",
+    "            video = open(f.name, \"rb\").read()\n",
+    "        anim._encoded_video = video.encode(\"base64\")\n",
+    "    \n",
+    "    return VIDEO_TAG.format(anim._encoded_video)\n",
+    "\n",
+    "def display_animation(anim):\n",
+    "    plt.close(anim._fig)\n",
+    "    return HTML(anim_to_html(anim))\n",
+    "\n",
+    "# First set up the figure, the axis, and the plot element we want to animate\n",
+    "# First set up the figure, the axis, and the plot element we want to animate\n",
+    "fig = plt.figure(figsize=(10,10))\n",
+    "ax = plt.axes(xlim=(-180, 180), ylim=(-75, 75))\n",
+    "# plt.axis([-180, 180, -75, 75])\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "scat, = plt.plot([], [],'o')\n",
+    "scat_top_1, = plt.plot([], [],'o')\n",
+    "scat_top_2, = plt.plot([], [],'o')\n",
+    "scat_top_3, = plt.plot([], [],'o')\n",
+    "scat_top_4, = plt.plot([], [],'o')\n",
+    "scat_top_5, = plt.plot([], [],'o')\n",
+    "scat_top_6, = plt.plot([], [],'o')\n",
+    "scat_top_7, = plt.plot([], [],'o')\n",
+    "scat_top_8, = plt.plot([], [],'o')\n",
+    "scat_top_9, = plt.plot([], [],'o')\n",
+    "\n",
+    "# initialization function: plot the background of each frame\n",
+    "def init():\n",
+    "    scat.set_data([], [])\n",
+    "    scat_top_1.set_data([],[])\n",
+    "    return scat,scat_top_1,scat_top_2,scat_top_3,scat_top_4,scat_top_5,scat_top_6,scat_top_7,scat_top_8,scat_top_9,\n",
+    "\n",
+    "\n",
+    "# animation function.  This is called sequentially\n",
+    "def animate(i):\n",
+    "    day = round(i/24) + 17\n",
+    "    hour = i - (day-17)*24\n",
+    "    subset = []\n",
+    "    color = []\n",
+    "    label = []\n",
+    "    for j,hashtag in enumerate(topHashtags):\n",
+    "        subset.append(latLonPopulated[\n",
+    "            (latLonPopulated['DoM'] == str(int(day))) & \n",
+    "            (latLonPopulated['Hour']==hour) & \n",
+    "            (latLonPopulated['Hashtag'] == hashtag)])\n",
+    "        color.append(cm.jet(j/float(len(topHashtags))))\n",
+    "\n",
+    "    plotAnimationProperly([scat,scat_top_1,scat_top_2,scat_top_3,scat_top_4,scat_top_5,scat_top_6,scat_top_7,scat_top_8,scat_top_9],subset,color)\n",
+    "    \n",
+    "    return scat,scat_top_1,scat_top_2,scat_top_3,scat_top_4,scat_top_5,scat_top_6,scat_top_7,scat_top_8,scat_top_9,\n",
+    "\n",
+    "animation.Animation._repr_html_ = anim_to_html\n",
+    "# call the animator.  blit=True means only re-draw the parts that have changed.\n",
+    "anim = animation.FuncAnimation(fig, animate, frames=48, interval=5000, blit=False)\n",
+    "\n",
+    "# call our new function to display the animation\n",
+    "display_animation(anim)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/Most_Popular_Hashtags.ipynb b/Most_Popular_Hashtags.ipynb
new file mode 100644
index 0000000..9fffa13
--- /dev/null
+++ b/Most_Popular_Hashtags.ipynb
@@ -0,0 +1,1599 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Most Popular Hashtags\n",
+    "**Sophia and Victoria**\n",
+    "This notebook will explore the most popular hashtags over time. In addition, we are also using this notebook to start developing functions that will allow us to read in/aggregate our data bit by bit -- we don't think reading in millions of tweets and converting them to a dataframe is a sustainable method once our tweet counts gets to be in the 10s of millions. We will be prototyping this functionality using the popularity of hashtags. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First, let's start by importing everything we need!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import time\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np \n",
+    "import pandas as pd\n",
+    "from collections import namedtuple\n",
+    "from ipywidgets import widgets  \n",
+    "from IPython.display import display\n",
+    "% matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the path to the json file containing the cleaned tweets. We can't push this to github, because Twitter's API terms of service do not allow this"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "filename = './data/cleanedShootingTweets.json'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the read and aggregate function. This is a first pass at creating a function that reads through the data bit by bit, and aggregates. This function takes in the number of lines to read at a time and a filepath, and returns a dictionary of hashtags and counts of those hashtags. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#This works if we don't care about time stuff. \n",
+    "def ReadAndAggregate(linesAtATime,filepath):\n",
+    "    i = 0\n",
+    "    data = []\n",
+    "    hashtagsDict = {}\n",
+    "    \n",
+    "    #Open the file     \n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        # Loop through all the tweets        \n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate after we've read through the right number of lines\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print i\n",
+    "                df = pd.DataFrame(data=data)\n",
+    "                allHashtags = df.entities_hashtags_text.tolist()\n",
+    "                #                 \n",
+    "                for tweet in allHashtags:\n",
+    "                    for hashtag in tweet:\n",
+    "                        hashtagsDict[hashtag.upper()] = hashtagsDict.get(hashtag.upper(), 0) + 1\n",
+    "                \n",
+    "                data = []\n",
+    "    return hashtagsDict"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's try out this function!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100000\n",
+      "200000\n",
+      "300000\n",
+      "400000\n",
+      "500000\n",
+      "600000\n",
+      "700000\n",
+      "800000\n",
+      "900000\n",
+      "1000000\n",
+      "1100000\n",
+      "1200000\n",
+      "1300000\n",
+      "1400000\n",
+      "1500000\n",
+      "1600000\n",
+      "1700000\n",
+      "1800000\n",
+      "1900000\n",
+      "2000000\n",
+      "2100000\n",
+      "2200000\n",
+      "2300000\n",
+      "2400000\n",
+      "2500000\n",
+      "2600000\n",
+      "2700000\n",
+      "2800000\n",
+      "2900000\n",
+      "3000000\n",
+      "3100000\n",
+      "3200000\n",
+      "3300000\n",
+      "3400000\n",
+      "3500000\n",
+      "3600000\n",
+      "3700000\n",
+      "3800000\n",
+      "3900000\n"
+     ]
+    }
+   ],
+   "source": [
+    "hashtagsDict = ReadAndAggregate(100000, filename)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we want to actually plot the top hashtags. First we need to get the hashtags and counts sorted by the number of counts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "sortedByCount = sorted(hashtagsDict.items(), key=lambda x: (x[1],x[0]), reverse=True)\n",
+    "\n",
+    "splitintoTwoLists = [list(t) for t in zip(*sortedByCount)]\n",
+    "hashtags = splitintoTwoLists[0]\n",
+    "counts = splitintoTwoLists[1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now for the plotting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([<matplotlib.axis.XTick at 0x11d0357d0>,\n",
+       "  <matplotlib.axis.XTick at 0x124488850>,\n",
+       "  <matplotlib.axis.XTick at 0x151a7d390>,\n",
+       "  <matplotlib.axis.XTick at 0x1225390d0>,\n",
+       "  <matplotlib.axis.XTick at 0x1143398d0>,\n",
+       "  <matplotlib.axis.XTick at 0x114339490>,\n",
+       "  <matplotlib.axis.XTick at 0x136282ed0>,\n",
+       "  <matplotlib.axis.XTick at 0x136282910>,\n",
+       "  <matplotlib.axis.XTick at 0x129607d10>,\n",
+       "  <matplotlib.axis.XTick at 0x11fac6d90>,\n",
+       "  <matplotlib.axis.XTick at 0x152186490>,\n",
+       "  <matplotlib.axis.XTick at 0x15056f790>,\n",
+       "  <matplotlib.axis.XTick at 0x1369b1290>,\n",
+       "  <matplotlib.axis.XTick at 0x11d039290>,\n",
+       "  <matplotlib.axis.XTick at 0x11d0293d0>,\n",
+       "  <matplotlib.axis.XTick at 0x11fac6190>,\n",
+       "  <matplotlib.axis.XTick at 0x1192eb890>,\n",
+       "  <matplotlib.axis.XTick at 0x1192eb950>,\n",
+       "  <matplotlib.axis.XTick at 0x11faf6fd0>,\n",
+       "  <matplotlib.axis.XTick at 0x11faf6710>],\n",
+       " <a list of 20 Text xticklabel objects>)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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mlEYQBEFQTCiNIAiCoJhQGkEQBEExoTSCIAiCYkJpBEEQBMWE0giCIAiKCaURBEEQFNNW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\n1PaKEx7cBJmoTT9PrD5NXZQ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vsQTjCZ9GMGi2IKWLuB64Pm/kiplMcIvtPw56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\nRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x11d035810>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.bar(range(len(counts[0:20])), counts[0:20], width = 1)\n",
+    "plt.xticks([x+0.5 for x in range(len(counts[0:20]))], hashtags[0:20], rotation='vertical')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we also want to aggregate over time, so that we can understand how popular hashtags develop over time. To do this, we'll need to define another function for aggregation.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "#This works if we don't care about time stuff. \n",
+    "def ReadAndAggregateIntervals(linesAtATime,filepath):\n",
+    "    i = 0\n",
+    "    data = []\n",
+    "    hashtagsDict = {}\n",
+    "    #Create a named tuple that we'll be using as our dictionary key\n",
+    "    HashtagKey = namedtuple(\"HashtagKey\", [\"DoM\", \"Hour\", \"Text\"])\n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print i\n",
+    "\n",
+    "                #Recode some of the data\n",
+    "                df = pd.DataFrame(data=data)\n",
+    "                df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])\n",
+    "                df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))\n",
+    "                \n",
+    "                #loop over all the tweets\n",
+    "                for index,tweet in df.iterrows():\n",
+    "                    #Loop over the hashtags in the tweet\n",
+    "                    for hashtag in tweet['entities_hashtags_text']:\n",
+    "                        hashtagsDict[HashtagKey(\n",
+    "                                tweet[\"DoM\"], \n",
+    "                                tweet[\"Hour\"], \n",
+    "                                hashtag.upper())] = hashtagsDict.get((tweet[\"DoM\"],\n",
+    "                                                             tweet[\"Hour\"],\n",
+    "                                                             hashtag.upper()), 0) + 1\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "    #return the aggregation\n",
+    "    return hashtagsDict"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's create a plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100000\n",
+      "200000\n",
+      "300000\n",
+      "400000\n",
+      "500000\n",
+      "600000\n",
+      "700000\n",
+      "800000\n",
+      "900000\n",
+      "1000000\n",
+      "1100000\n",
+      "1200000\n",
+      "1300000\n",
+      "1400000\n",
+      "1500000\n",
+      "1600000\n",
+      "1700000\n",
+      "1800000\n",
+      "1900000\n",
+      "2000000\n",
+      "2100000\n",
+      "2200000\n",
+      "2300000\n",
+      "2400000\n",
+      "2500000\n",
+      "2600000\n",
+      "2700000\n",
+      "2800000\n",
+      "2900000\n",
+      "3000000\n",
+      "3100000\n",
+      "3200000\n",
+      "3300000\n",
+      "3400000\n",
+      "3500000\n",
+      "3600000\n",
+      "3700000\n",
+      "3800000\n",
+      "3900000\n"
+     ]
+    }
+   ],
+   "source": [
+    "aggDict = ReadAndAggregateIntervals(100000,filename)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's create a plot of the most popular hashtags, allowing the user to input time and the number of hashtags they'd like to visualize"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def plotHashtags(DoM, Hour,nHashTags=20):\n",
+    "    #Filter the hashtags, so that we only get the tweets of the appropriate day of month and hour\n",
+    "    timeHashtags = {key: value for key,value in aggDict.items() if (key.DoM == str(DoM) and key.Hour == Hour)}\n",
+    "\n",
+    "    #Sort the hashtags by count\n",
+    "    sortedByCount = sorted(timeHashtags.items(), key=lambda x: (x[1],x[0].Text), reverse=True)\n",
+    "\n",
+    "    #Split them up into hashtags and counts\n",
+    "    dictList = [list(t) for t in zip(*sortedByCount)]\n",
+    "    hashtags = [x.Text for x in dictList[0]]\n",
+    "    counts = dictList[1]\n",
+    "    \n",
+    "    #Plot\n",
+    "    plt.title('Hashtag Distribution (Dec {0} at {1})'.format(DoM, Hour))\n",
+    "    plt.ylabel('Number of Tweets')\n",
+    "    plt.bar(range(len(counts[0:nHashTags])), counts[0:nHashTags], width = 1)\n",
+    "    plt.xticks([x+0.5 for x in range(len(counts[0:nHashTags]))], hashtags[0:nHashTags], rotation='vertical')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we're going to create the sliders!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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QdL2k70taNpdNBu4pnHNvLpsMzC6Uz85lI+rYfg54VNIKXcoWBEEQlKBMMMWd\nCrsTgNcB/+7imicAX7JtSV8BjgH27qK9Ig19lYc5rLA9NX+CIAiCGkNDQwwNDZU6t4wXVjEvyDzg\nLpLpqBK2Hyzsfo8UpBHSiGO1wrFVc1mz8mKd+yRNBJaxPbf51Q+rKnYQBMG4YOrUqUydOnX+/uGH\nH9703LYKxPYHu5RHFEYGklaxfX/e3Ym0UBHgPOBHkr5BMk2tDVyVRyqPSZpCyoS4B/CtQp09gStJ\nmRIv7lLWIAiCoCStUtr+d4t6tv3ldo1L+jHJTvRiSf8grSnZUtLGpLhadwEfzQ3OlHQmMBN4FtjH\nw3FD9gVOAZYEzq95bpHCzJ8uaRbwMDCtnUxBEARBb2gaC0vSpxsUL01ynX2x7Rf1U7BeE7GwgiAI\nOqdVLKxSKW0lTQL2JymPM4FjbD/QUyn7TCiQIAiCzqkczj27xB4IvJ+03mJT243WdQRBEATjjFZz\nIF8nTXJ/F9jQ9pMDkyoIgiAY87SaA3meFH13HiNtPyJNoi/Tf/F6R5iwgiAIOqeSCct2R6vUgyAI\ngvFFKIkgCIKgEqFAgiAIgkqEAgmCIAgqEQokCIIgqEQokCAIgqASoUCCIAiCSoQCCYIgCCoRCiQI\ngiCoRCiQIAiCoBKhQIIgCIJKhAIJgiAIKtFXBSLpZElzJN1YKFte0oWSbpf0W0nLFo4dImmWpFsl\nbVUo31TSjZLukHRcoXxxSWfkOpdLWr2f9xMEQRAM0+8RyA+BrevKDgYusv1KUg7zQwAkrQ/sAqwH\nbAucIKkWAfJEYLrtdYF1JdXanA7Mtb0OcBxwVD9vJgiCIBimrwrE9qVAfQKqHUjJqch/d8zb2wNn\n2J5n+y5gFjBF0irAJNtX5/NOK9QptnUW8Lae30QQBEHQkNGYA1nJ9hwA2/cDK+XyycA9hfPuzWWT\ngdmF8tm5bEQd288Bj+YsikEQBEGfaZnSdkD0MkNTw6QnwxxW2J6aP0EQBEGNoaEhhoaGSp07Ggpk\njqSVbc/J5qkHcvm9wGqF81bNZc3Ki3XukzQRWMb23OaXPqwX8gdBECyyTJ06lalTp87fP/zww5ue\nOwgTlhg5MjgP2Ctv7wmcWyiflj2r1gTWBq7KZq7HJE3Jk+p71NXZM2/vTJqUD4IgCAZA05zoPWlc\n+jHJTvRiYA4wAzgH+Blp5HA3sIvtR/P5h5A8q54F9rd9YS5/LXAKsCRwvu39c/kSwOnAJsDDwLQ8\nAd9IlsiqaWcMAAAgAElEQVSJHgRB0CGtcqL3VYGMJUKBBEEQdE4rBRIr0YMgCIJKhAIJgiAIKhEK\nJAiCIKhEKJAgCIKgEqFAgiAIgkqEAgmCIAgqEQokCIIgqEQokCAIgqASoUCCIAiCSoQCCYIgCCoR\nCiQIgiCoRCiQIAiCoBKhQIIgCIJKhAIJgiAIKhEKJAiCIKhEKJAgCIKgEqOmQCTdJekGSddJuiqX\nLS/pQkm3S/qtpGUL5x8iaZakWyVtVSjfVNKNku6QdNxo3EsQBMF4ZDRHIM8DU21vYntKLjsYuMj2\nK0n5zQ8BkLQ+sAuwHrAtcELOjw5wIjDd9rrAupK2HuRNBEEQjFdGU4GowfV3AE7N26cCO+bt7YEz\nbM/LOc9nAVMkrQJMsn11Pu+0Qp0gCIKgj4ymAjHwO0lXS9o7l61sew6A7fuBlXL5ZOCeQt17c9lk\nYHahfHYuC4IgCPrMYqN47c1t/1PSisCFkm4nKZUi9ftdclhhe2r+BEEQBDWGhoYYGhoqda7sHr+j\nKyBpBvAksDdpXmRONk9dYns9SQcDtn1kPv8CYAZwd+2cXD4N2ML2xxtcw93rIzEWnlcQBMGgkIRt\nNTo2KiYsSS+U9KK8vTSwFXATcB6wVz5tT+DcvH0eME3S4pLWBNYGrspmrsckTcmT6nsU6gRBEAR9\nZLRMWCsDZ6dRAYsBP7J9oaRrgDMlfYg0utgFwPZMSWcCM4FngX08PBTYFzgFWBI43/YFg72VIAiC\n8cmYMGENgjBhBUEQdM6YM2EFQRAECz+hQIIgCIJKhAIJgiAIKhEKJAiCIKhEKJAgCIKgEqFAgiAI\ngkqEAgmCIAgqEQqkI5ZAUlefVVZZY7RvIgiCoCfEQsLOWiEWIwZBMJ6IhYRBEARBzwkFEgRBEFQi\nFEgQBEFQiVAgQRAEQSVCgQRBEASVCAUSBEEQVGKRUCCStpF0m6Q7JH1utOVpTXdrSWIdSRAEY4WF\nXoFImgAcD2wNvBrYVdKrOm9pqAfSlGnjGdJakmafS1oenzPn/r4vZhwaKnMfrVlU2hgLMoyVNsaC\nDGOljbEgw1hoY6FXIMAUYJbtu20/C5wB7NB5M0M9EGUQbbRTQAZmtDzeTgltueWWbZXQxIlLd93G\nwqDIxoIMY6WNsSDDWGljLMgwJtqwvVB/gPcA3y3sfwD4VoPzDG7xmdHmuD022mhXvxdtDOpZLNFO\nE7b8TJjwwq7qj5U2xoIMY6WNsSAD4JVXfrlbMWPGjJbHy7CwtAHYzd6/zQ4sLB9CgfShjXgWi959\nxLPorI3uOjeLkjJtpUAW+lhYkt4IHGZ7m7x/MOmGj6w7b+G+0SAIglHCTWJhLQoKZCJwO/A24J/A\nVcCutm8dVcGCIAgWcRYbbQG6xfZzkj4BXEhyCjg5lEcQBEH/WehHIEEQBMHosCi48QZBEASjQCiQ\nUULSEaMtQxB0iqTlR1uGYOwQCmT02Ga0BVhYkPT6NsefkPR4/jxR2H9K0rwOrnNh99LOb2tFSStW\nrPvWwvaadcd26la2Etf/fpPy1YA/9fv6QWPyXG+/2l65Sr2FfhK9CpL+u8Vh2/5yiTZWb3Xc9j/a\nNDEx9+YausfZnttOhizHHm3kOK1N/be0qf/HfsvQpM31gV3z51HgdS3an1RX90XAvsBHgbM7uGyl\nF37huiKFAfgEqXOmrMD+1/aXOmjqaGDTvP3zwjbAF4BflJDlBuCy/Pmz7Ts7uP5ikv4P2MP287m9\n9YBfA6XvQ9IlpHUEjbDtt7Wpf2dd/WJOadt+RUk5um4nh0eaDFxp+8lC+Ta2LyhRfzqwgu2v5/17\ngUlZls/aPqnErXyIFLapJ0hajrSObjdgPeBlnbYxLhUI8K8GZS8E9gZeDLRVIKQfkxmpAEx6Ca0E\nTGxT/1XAX2isQAysVUIGgGa98+1JX/h2L+/PNrn+RsBqtL+PXsgAgKQ1GFYazwIvB15n+66S9ZcD\nDgD2AH4MvN72w2XqZpZt1cO33e7F/Slg83zdO7NMawEnSvqU7W+UlENNthvtN+P9wGbAO4AZkpYG\nLmdYoVzZou4Hge8AP5U0DXgD8FPg47Z/VfL6AJ9pUPZG4CDggRL16zsNE4BdcrvXdSBHV+1I2o/U\nIbkVOFnS/rbPzYePANoqEOBjjLQ6PGB7sqQlgd8CZRRI10haihTqaTdgE5IS2xFo21FsyGivJB/t\nT36AXwDuBI4EVqrYzhrAicAs4JMlzr+uD/ci0kr8m0g/+I0qtLE58BvgCuDdg5KB9HK7BfgisE4u\nu7Nk3ZcAXwP+nv+Xy1Z8fg8DPwB+2ODzgzL/U+AlDcpX7OT/DVzbaLvRfgdtvoQ0Mvor8FzJOt8i\nmaz+Abyxy+/mFsBFwKXAth3WnQDsCdwM/B+wfkUZKrWTv8svyttrANcA+9f+5yXbuKZu/9DC9lUl\n25gHPN7g8wTweIn6PwbuAU4mdSwmlv2NNfuM1xEIklYADiT11E4FNrX9SIV21gE+T+qlHQPs5xTU\ncWBIWgzYi9SjugJ4r+3bO2zjbaSXt4EjbP9uwDLMIY1WVia9cGfR3PxRz93Ag6QX/VPA9GRNStg+\ntmw7tj9UVuAGvMD2Q/WFth+U9IIO2llL0nkkZVzbJu+v2bzaMHmB7SakUcjmwCuAe4Hvk5R1q7r/\ny/Doen3gWmA3Sbvl+9mv7I1I2pqk1J8Bvmr7kg7qvoBktvkUSfHsaPuvZev3sJ0JzmYr23dJmgqc\nJenllB8RLlfcsX1Elm0CSbmX4Sbbm5Q8txHrA4+QRlK3Oq2h62odx7hUIJK+DuwEfBfY0AWbZgdt\nbEBSHK8GjgKm236ugya+WWjrRQAV5dgX2B/4PbCNS5p7CvW3I93HY8AXbF86aBkAbO8oaVnS/+Ww\nrJiXkzTF9lVtqn+dYWUzqdWJbSj7MmjGfyoeq6cYTfroumP1+814ApgJfBs42J3NgVzTZLsjJF1N\n6gx8nay0JM2fz7F9bZsm7iT1uo8jjYI2krRRoX7buaAetTNH0sa2r8/nPynpXaTR6oYlZbhQ0lds\nf6Gu/EukRdB9x/bGeS5nV+AiSQ8BkyStbHtOlTbH5UJCSc+TekTzaDC5ZnuZEm08RxoO/hpYQHGU\n6aVJ2gc4GFg6X/sJ4EjbJ5S4jVobz5PsyQ/S+F42alhxZP3ZwA006PHb3r7fMjRpc2WSnXoasLrt\n1Vqcu3yV0WODdjawfXOD8gmk8Dg/alP/ORrPrwlY0nYno5CukLQr8P+A15K+n1eTXuKX2763Td3F\nbJf2XmvRzhCtJ9Hf2uRYrf4pbeqXGi12246kVYFnG71kJW1u+7ISMixNGv29nvRbA3gNSUHvXabz\nKOnQ2silF0h6LUmZ7ALMtr1Zx22MRwXSCyTt2eq47VPb1P88ybTwCdt/z2VrkUYmV9r+Skk5Xt5G\njrvb1N+iTf0/9FuGFu0uT/LAWr1VG5IeAB4iTxADl9m+o8L1liFNlk4GzgN+R5o3+DRwg+0KeWY6\nR9JNjHzhmXR/lwBH2/53h+29kJQ3ZzPSBPnitpv+zyRda3vTvP2/tj/Z4S0sUuSJ7o8Ba5PmQ06u\nqmDzb/zVeXem7b91WH9b4BCSOQrSvOGRts+vIk9uU8CbXcLjcoG641mBSNqS4X/mzbaHOqi7Meml\nUukBSrodeE39yyB7Sdxge92S7RxAemle202vMf9I1s67f+30JdUt2bX6TNu3SVqC5NnyGtIocTfb\nF7Wpvy7pBVn7rEiai7nM9lElZTiXZCO+nBSccyXS6GH/mvmiKpL+Ybul63fh3EYv9xVIE8BL2/5w\nyXaWJs3N1eZBXk8aNV9mu+maAknX1WztRWVSBUkrkZRy7Xd2C/Bt2229sNq4h9v26R3IsQHJ47Ao\nx9G2bypR96ckr8A/AduS5sr2L3vt3Ea3bv9I2pukyA5i2LT4OuB/gO/b/m6b+v8kTd7/sMGxSv/n\ncalAJE0m+dL/m+RKC2movxTwX+2G+LmNa0iutn8h93pJ5oEnSspwm+2GqXdbHWtw7tGkF8SrSL2j\nWi/8zy6xliRPfh9BmmS8m/TCXI00If35Mg4Bkp6gsYmgE5PgLcAGti3pI6Sh9duBdYFTbU9p10ah\nrVcA7yTNy0y2vVTJejfZ3jBvTyRFd169F8pU0j2tzHAdtDP/5d7uPNL/8Rry9wG4oqSppDgCqaxA\nJG1O8vw5hZG/sz2B97cz/eTJ/EZsT/q/lprDlbQDae7oa4x88R4CfMbDLrnN6he/F4uRvKY6eiaF\nUWVDt3/bbd3lJc0E3lT/u5b0YuBS2+u1qX8naQ7oAZLZ7LHCsVLfqwVwFy5cC+uHtLhsrwblewDn\ndtDOC4GpwKHAr0ieRDcAJ5So+3vgbQ3K3wpcUuGeFicpks+QFp/dRxoit6v3DZJtdlKhbBmSg8E3\nB/g/ua6w/XPgo42ONalbvO+rSGmNDyCtOVi8Axl64jLbpO1/9KidG0qetxG5g1jhGk8DN5I6JE/l\n7dr+jR20cwWwSYPyjUlm2k5kquyinn+TazQoX6PM8+zH94IO3f5znVurHCvKnZ/jF0gu71O7vadx\n6YVF8v/+r/pC26fluYlS2H4KGMreJleSzAR7UC5MyX7AuZIuZbh39rrcRhVb+1KkF/+y+XMf6cfW\njncB6zp/iwBsPy7p48BtpF58x2TzyX+RJp+3K1HlmWxmmANsychFaO1GEJeSfhzfAM7O/5cqvEbS\n43lbwFJ5v9RIStKBzQ4BLyorRNFTqcDypBdoKTu17RslTcwOBg/ldhcnuVp/yq17q6+ivAt1K5ax\nvcBCPdvXSyrlLaceuKgDi7mBZ6CTS24Zx4auvhdF1J3b/+OSXmP7hmKhpNeQHHDakn/nX1EK23O6\npLNJCqUS41WBNIwBlr1tyqy8RsknfjNSb+oZkpfLlaQh5v3t6tu+Jb8wd2PYLvtHUs+7tMlE0ndz\n/Sfy9f8MHOvyXkkuKo9CYcc+4vkFtR3pnrYmjQjKrrDdHziLNKQ/1sMrud9J+9XCL2N47uOj+aVz\nLcNeR38vI4BLmBHa0Oql+M0Wx+o5pm7fpEWOQ6QV4m1RWkH+HeBfkmYBXyW5nV5NWvvUiptprkCe\nkfQ3knnz9+3FWNBDTmkNVts4fOqBe3hmnqTVXTfPkOea2s4b9uB70Qu3f0jOHOdJ+iEjO517kjoX\nbcWobdi+KnthfYv03nhxh7KkBhu8OxZ5JH2D1CM8wPa/ctnSpB7sv13OBfcJUibEk4A/ukOvH0lr\nAyu7zg6c7cb3u6R3hqQLSAuRbiYpj8tJDgGl/rGSzgF+4bp4VZI+AOzicm68W5HmLLYieQr9lBT/\naY0yMuQ2DmT4C26GPY8udWdrGGpeRx8imbHW7MULoFskLV37rnXZznts/7zEeTeTF8zlEc3lpN77\nL7u8/kRgA+BHtjdoc+5HgA+TRg+1NR+vJUV8+IHtlspQzd3DAXBJ93BJO5Je2kcw8sV7MPA52+eU\naacb1AO3/9zOKsA+FDy5SE4JbTutkn7gBi7Lkt4LfMUl511H1B2nCuQFpAm1vRg5cXwqyUuh7aKv\n/EN6DcM931eSJl1rvd6L29T/FXCI67xAJG1IWgn+7g7uR6QvVE2WDYC5WY4ZberWHAqeZuSPqxOH\ngudJHip7FUYOf7ddNp4XkhrJuQJpJHOY7TNa1F2WtOahdv+bkGzLl5M8js4qK0e35Of5UtJcwX+y\nF9IBpGfTcbC6Bu2X8uaqn/yWdHO7F36Hcny0nQLI572L5DVU9H76ehlFls09K5NevEVWI3WySq8m\nz2aeT9fJcUy9OahfSNqLFmZBt3H7r2urpx6Tub132/5Zx3XHowKpoeQyW/tH/K0L2zlKC992pmSv\nV9LVthsGISx6fXQow6qkOZTNSHMbL7a9XOta8+u+lZH+6e3ME8W6G5MW/O1Mmpw7A/hvt1hr0EHb\nKwAXuYXXi6QHyYqb5IV2te2nu712pyi5VH+eFG9qCeAEUm/7NOAo2//swTVKeXNJmg0UQ7gcWNx3\n+fAuo0YvO1kN2l4eeLTsSH0sUPCY/CDJm6pjj8lCWxNJnbOa5eBPtt/bsUwL0fPrGUr5Je6pDfuU\n/M3fQxqNHOZy7q8bMXLdweIMm5Aus90yBISkWbbXaXLsr7bXbnSswbn7FWR4lmGXzT+TYuc836b+\nCq2Ol3kWde1tRvpSvofk/XK22/inl2iztIuhuggL0y1FN0slv/87gM1t/6VN1U6uUXYE0nLkafvw\nXsnUQoZaTK1mMrQ02/Sqk6UF1xj9hjR3WWqNUS+Q9EtaP4sypuJvkObZPuW8XEBp8evRwNMusTZF\naeHwbiQ396tIHc61qnaex6sCuRZ4e/6hv4XUY/4k6Uu1XhlNnNsornxuuxCorv5PgIttf6+ufG/g\nHbbfV7KdYxkO0d1xD1fDuRKKORKo7XdihqprdwJpHcf7bE+v0kZuZ0vgi24f9uLjJL/+ymFhuqWB\n2egG26+p0E79SvT5h0gec0t0IebAUPfRGnrVyapfY7QbaaFox2uMqqLeRHyYRZ3HZC6fCNzW7FkV\nzptNGrmcCJxj+wlJd9ouFaCzEePVC2tioWf9PuC7eWLy55JKrTj28EKrJYG1s5dFJ/bIg0j5Ft7P\nyLmHxUnur6WwfWCWY0tJ78nFt7h81NOprhhqpI1cz0u6C2g5AqrR5KW5AskduWXCKklfII3Aprou\nLIykFVwyLEwPWFXStwr7Ly3ul50oJZkfu6JOjgXoQJZueKXtQ7uof42kDzfpZHUyqvtP4aW7NfAT\nJw+oW7NZaBB80PZeXbbhRiY3l/eYPIuU++N9wHNKkRe6GkGM1xHIzcDGtudJug34iHMcmLKTjepy\nBXett1o393BLu8n3Bu28jLQwstKq+vpecxWyOe9okjvtOaQIsMeTfd1dIpGSFgzfYeBhl/BcUo/C\nwnRLtz3uNm2/hPQ8ynrXFWU5nJQpsSeylKXb71aeVzybFMl4gU6WS3ge5XauICWLm0PynHxtwdnj\ndtuvrCpjWXr0O+uFx6RIi593JZmxlgOmA7+uYvYdrwrk86SH9xCwOikXiJVca0+1vXmJNrqyR3Zi\n12/Tztmk1fOn1JXvAbzHbQIA9kIOSVeShsWXkxZRHkryaPvvDkZk3Vy/J2FheixTNyH630iKbzSX\nlB3zdJKr9gRSmtkyGfCK7fXku9YpSml1p0LXaZu3JHkWQrVO1htI38cVgeOcU1YrrTHa3faunbRX\nhdxR3ZXmz6JdaPueeEzWtfcChifSt7ZdNi/JcBvjUYHA/B/pS4ELPbwWZF1S5rEy/8xe2CObesK4\npJdMqx5Umd6VUiTbpi6yZUwdkq63vXFhvyMX3m6R9HuSV87v68rfSpo/2XKAshTnYgCepPMQ/deQ\nlPCypJAy29q+QimXw086VQa96P1WQdIzpCRWDdM2D/I70gyVXFfTg+s8QVrE2exZtJzjq2urksek\nUkywVW1/O+9fSQoYCqmzVzo4ZY1xOQeSPY/uyJ8llFZQP+rOFgN2a4+cSFrM2G0So25X1Rd7M1VZ\nUtImDN/LM8X9Mgq5S3odFqYSPZyLWcz2hbn+l2xfAeDkRdQP0fvFzNEY+XTIN0gRE/rNXztREo3Q\nsMfk9fkzorzEiO4gkrt9jSVIv5OlSab3UCAl+QvDk0e1X+SL8pB7b5cLmTBT0h5N7JG3laj/T9tf\nKitwC34l6Xs0XlVfJkfAwz2wh9/PyNFUcd+kAJF9wz0KC9MDdqduLsb23yXtQnJpLqtAio4H9etZ\nys6BFCMkv1AjYznZHcRvWsRZmDRy7b0lkvXkvlxe86BsN6Jb3HZxUealth8GHs7vjI4Zlwqkmdua\npJ1IoUnKBEPcF/iFpA/RwB5Zon6vvrgHkVbV3y2p5k21OnlVfYn6naRabYjtqd220QMZ/k2K9TQf\nSRMkvd9tMgn2VowFFZbtp5VW65elFryvGLiPvL9kSUG6Se3bKxrG/1IXK5/7wKBs+J+DYa/NXNbR\nKvLie6vivNbyde0Vc8Ks2GFbSY7xOgfSjE7txV3YI1coO4lYsr1erqp/Bak3P832q0ucv1Or4y6f\nu7oSGplJ8Fzgorz/GQabSXDMzMWMNdSjlc8Vrz3q62ryhPVX6SLvTl17Hc9rSfoRMOQF3aI/SjK7\nduxMEAqkQPacubQ4IVyhjeWAfW1/tXeSVZLjHcBBtt9R8vyXkfzDdwM2JI1qfuFyGduKGc7eDRTj\nHNklc1dXRX3MJNihHOuTUuE2nIuxfUvJdt5a8zSStKYLwSQl7dRvhdxL1OOVzxVl6EvK5Q5l6HoV\neV17VRTISiQ3+2cYGdxyCVLgzQVyvrdtczwqEDXO27A8KdPZ8fUaukkbqwFfZHjtw0+AL5EWvf24\n0y9EVXLv9qSCHEeSejUCvtruZaPh7H+TgTPz59xmZr4S8gzcZVR9zCTYoRwHkJTYa0irnAFuJUWu\n7SREf9OMgKPlUVUF9WHl88JKt16b+dzie2tEbDPoyHOzq7VnRcblHAgL5m0waeL3A2V63JnTgD+Q\nPDi2IaXKvB7Y0CUXOPWIY4CPkF5c2+a/B9s+vmT943Od3Zzjd5X0ImvGaPRI5g//sxfc7EErj8yq\nJOeF9UgZ/C4jLV57IWmhZ1nUZLvR/lim5yufq6AepFzuAd16bcLI99b3aJ1/ppUgFwOVlUaRcTkC\n6QWqi3OUe1uru03wwj7IUd9D7WhlrVI+5Z1Jo5BVSCOQvVwxf/do9JCVci3UVqyL5MjwFKPkcZTd\nwl9Hcun9f/nzqO31S9ZfJEYgQKOVz8uSVj6f71EIeDlaqAeryMci43IEIulNJDvsaXn/LFLcJUiJ\nVUppZ6WQ0LUe4cPAsvkH03EU2y5Yrm4Se7HifjsTVnbjOwk4SSkc/PuAOZJuJUXSbevJpZGRRteS\ndF7dNfr64/AYSBhVR9X0wjVqz1CMfJ4CFirzT+51XwJckieStyGtRTiBtLq+70g6jjQavMz2fe3O\n7xPdem0i6cOkSfBZ+T1zMsNRxPd0g/TB/WZcjkCyt8wnbc/M+zeRkkstTUoo1daNV8OBAkd1lW3d\nBHYjOSpNYCsl89m1zFoV9SDSaC9Ryki4PnCXcz7wAV23Pr3wFcAVLp9euNbOmHqevUDSigC2H8z7\nS3lAOVskfYLhlAcwnO7gMpKX3sCsBlW9NnPdm4FNbD+rlFL70ySPtk2AGbbf3HOB2zAuRyDAMjXl\nkZnlnLNB0tfKNOAO0rX2E9sf7KZ+HkLLC4YxeCMpMVIZGRq+0LKjwTTSXFHfkLQ9KbfzXOALpGCO\nc4A1JH3OAwgcmFmd5NEyixTCYzbwaIV2ehG5ddTJveQZwCfIUREkzSOlO+7FItpS5PnA4/P1X8aw\nMjmA5LE3SBNnLV0zlIxUXWBewd33XcBp2YJwkaSjeiVgJ4zXEUiv8gwsBjxn2/ll+QbS4qCBuY5m\nObYAHrF9o9Kq57cAfwNOsP1Mm7pXAm+rt0crrUz9o+3XdijLigzPqbyMZAb7TCdtdIpSBIGdSeai\nS4CNnFaArwT83hWyO3YhS+X0woU2Fqp5jmZkr6FtSdGua9Fv1yJ5ZV3gElGaeyiLSO7pm5Fcidcn\n5Vq/3INJrlULhFgpanZu41pgO5LL+t3AW2uu4ZJutb1eP2RvxXgdgdwmaTvbvy4WKuVvvr1MA9ke\neSTwpKQvA58l+VZvopS8/sheC91Ejm8DG5HiUd1Oiq91AelH8gPg/W2aeEGjyUzb/8o26zIyTAJ2\nIvn7r0v6oaxpe9XSN9IdzzvHMctuon8HsP1A7vEOjGzzv1nSo8Bj+fMuYAp1IdVb8EKNjC1Wf41+\nxxbrFbuTkqPNNyNmxf4B4EKSx1rfkfQ70ijjepJZ8Qjbtw7i2gWOB05046jZJ1AuZtsXSd6eE4Hz\nCspjC1Iq6YEzXhXIp4BfS3ovIxfU1HKJl+EA4BUkV7pbgZfbfijb368mKZdBsKXt9ZVCJNwLrJRd\nA79DciVtx1KSlnZd3o2sFBYvKcMDpEViXyAtxLSk0kmxesCE7NAwAXi+zrmhYbDJfqDm6YV/QGeT\n6JNJ7tkN59foc2yxHvKCRnNQth8s2znpEX8ndbLWITm7PCTpwUHOjwHr217gN2H7NKX0EmV4GHg5\nMKluXu0akvPLwBmXCsT2X5WSIL2fkcH3PtbB+oH/5H/iI9ns9VBu+ylJXceX6oB/5+v+W9LdTpnW\nyC/xMuERTgbOkvQx5xW5ktYgzSOcXFKGQxj2rPmJpJ92dgtdsyzJLFB74RZ76IO00a4B/Iy02rjj\n9MIFuo7cOkZo9TsY2G/E9kdh/srvN5IU/L7Z3Hqz7ZaJwHpEt1GzIZmkNyWZsOZT3/kbJONSgQDk\nuYFugu8tlc0ME4DFCyaH0gHvesRK2daswjZ5v22ANNtHS3oS+KNSKJdaPvH/sX1iGQFsHwccl+3b\n00gr4l8m6XOkOZBOwuR3zBhyaGgU4WA8UwsKWc+gfyM1niGtD3o6b69K+VF2t3QbNXtMMl4n0bsO\nvidpiBa9Ww8ocJ6klnb1TiYIs9kK51g9XcpVC6++S1mnhC6u9QHb/5e3N7d9WeHYJ1x+Vf6YQNI7\nbP9utOVYVFCKQ7UZyYR1HSnywmWkCfQqXnJVZHgBKb7cXowMpngqaelA2xFZnlf7Y7Pj/V5v1Yjx\nqkDGRPC9fiPpgDw6aHVOfa/ZpFS/l7oQxK/CtTvK4d0NWoRWbsP8dUmtQm9sNGCRKqHhBEgN8YAW\n2+a5qcuA62sm3tFCXUTNVoqntXez46OxPmi8mrDW8nDwve9TIfiepINsH5W3d3Yht4GkI1xiBfcA\nOBBoqUBoHE9nDeDzkg6z3TTdbQ21yOGtlHSroxzeFVhUYkfVKOvIMdYpJkCqp0wCpF5xTv47WQ0y\nOtr+R78FUOOUB+vU5HG5CMtPjoaSaMV4VSC9CL43Dagt3jmENHlaYxvKJXPqN21fns1MXLn3eBEt\n8huVCNcAABRUSURBVKUXOJ7hHN4XU5fDm+RW3E/cZLvR/pjHAwgvPgg8dqLu/poFFZlJc4QrUX4S\nuxveXbc9IuUByfW9HZUtAv1ivCqQ4uReMetbJ8H3FoZeb+WXp+25atRda8xo5/B+laQbSc/9FXmb\nvD+oXm7PkHQnI/93Kuzb9isGL1XnSGppOhzUepb6haTZy/BzwNuBIwYkw/yIEUopD6pEkPimpLe0\nuEbT+ZF+MS4ViHsTfG9M9HrVOlT1Ul20uyV17oIt6DqHd5e0WoE7sHUgPeR1dfsTgF1ITh4DD5jX\nBdcAN5Pm1GDBEcBAXZWV4rt9nhQx4hhgP3eYCbBHVP1NNIroYNIal9UYzEhqBONSgag3Gd+6zlvd\nC9xl7usmE7YrkCLI7lGymdF+FlPdIN6VUqiZ00lhVRYanOIb1dYI7E6KcnA9sJ1HxnAb6xwIvJfU\nqTiD5NI98BDu2SPw86Q1X0cB00d7Mr0KtotmMCRtTlq8ez/wydGQabx6YfXVa0fSEm4Tg6pXdKsM\ntWC6T5O8p0ZtcVKnKMUIOsn2dwtlSwNnA/fYnj5qwlUgu3x+iBQx4VLSmpxSgS3HIoX1QTuQXFiP\nGKS3o1K+mHtIcyELKA7b+w1AhmLKg7dQ547biQuupLeRwpqY9CxHzeV7XI5A6MH8haT/doOIonmN\nyXmkJDqD4GigpvB+XtiG1Dtplw+ktvp8Q+BVufhWkulhYeHtwAWSlrT9rbzC+HxSIMWDR1m2KtwJ\nzCN50P0D2ChHTgBKe+yMGZziX51LMqnuToqXNkh3+emMvjPF0YXtY6o0IGk70kjqMeALti/thWDd\nMF4VSC/mL94k6au258exkbQy8FtSz3dQdKUMJS1LWky5Gil2loANJf0D2MF2o5XEY4o84f924DdK\n4bp3II1IvjnKolWl1qPcKH9g+H9Z1mNn1KkbedxDMmMd4QHlAanhugCGRbKZcxAyjHC/zaPMDYB7\nbT9QsplfklIEPAwcJOmgumvEQsJBUFjRKeDNDA8nBbzJ9vIl2liSlPP5DtsH5gm63wBH2z6pP5I3\nlKMrc5ykb5HiEh3knFgn297/B1jK9qjYVjuh4GM/CTgW+D0F9+OFrccu6dOMdDs1KfR4V4s7B42k\n50mdknOBx6nrnNk+dkByXGr7TXn7dNu7F44NZKGppJNIeVBuyZ22y0nmtBWAz9j+SYk2xlyisfGq\nQHryj8i9iJ+S4upsRopzM8jRR9fKUNJMUv6MeXXliwE3eRRyDHSK+pSVcbRoEp5mBWBroNTizrGA\npMNoHe6n73k4shzX2d4kb9d3suYf67MMt9h+dd4+gOT4saOkVYDfdCJD7rzWVrP/tcIatp4xXk1Y\nd3a7+rQQAuRK4CDgT8CatfJB9a4YmUfg6Lpj9fuN+E+98gCwPU/SQBwBuqWiT/2YpUeLO0cd24eN\ntgyZVr3kQfWgi7Gu3kFeeGz7/rJrpXKn7giSg8X8eFq5A/X50XBJHq8K5BzyZLOkn9t+T4U2iu6z\n32pQNhCajZZUPp3skmqcvEik9KxjngbxvEYwQGXeVzpc3DnqSPpfWo9A+u79lFlOKT/NhLxdM3mK\nFD1hEDyqlLDuXlKyt+kwXymUXa/1ddI7Zk3ngKfZaefo/Nm/10K3Y7wqkOKPsNJK5UENv/9/e2cf\nLGdZnvHflYgaQqiEiqW0QGgVtRgi2BELLQMpakus1DpCBERIS+uABVFLB6dQodBipFrDt8XSAIII\n9QOkTACF+IGtCSQCMSVowMZBCxSEBoUhXv3jeTZnz2bPnnf37L7vvnvu30xm3o+zz95Jds/9PO9z\n39fVDWpjJ1vgZT8m7RtMdK8OlJ64q6DL5s5hYFXVAWTuAv6o6bi5n6Ks7u0/J000f4X0qLvx3VpI\nKi8uwiLgVW7ad7D9tKT3AeupIIFM1z2QCTeeuxjjU53ulzW7Uns72SNdnp1s0Gcma+60vb78qLpH\nwyMqOhJIetD2q7q9N0im6wqkU+d0US2s1QOLrjumZCereqgKd2RYknkfaVXjrV1zZ2ZYREWRNBPY\nydk5VNKLSd4cHyijUETSmR1u2/Y5BYZZp6Ruvbxl7GNIK5DSmZYrkFEiV3QcBcwmKd9+DrjNdqFH\nc4Puyi8DJQvh+4HrSbP0cfsE7WROgsEjaS2pobbtvo3L8wM5CrgM2AxsAM4luZF+BzjHJYg65tLs\nVrYn+XvsbHuHAmPsRnrC8DPGJrBvIO2h/LHtH/Up3MJEAukRSV/udL/spp6mpq3FJOe1syhgJ9tS\n4jiupLGsEsepImln0t7PkaQO7s8BN7gkt7mgPbmK70e0TyAuOsnpQxz3A0fYfkhJIfhu4J22b5rk\npYOKZw5pv2IJadJzQRfNhEg6lKTrBbDO9h39j7IY0/URVj94E6m79lpSKW+l1TG2f0Aq8TtPY3ay\ntzBWLz7hSyc4bnc+lDiJD14KXCrp10iJdJ2k021fVW1005p1QzIBeb6hJWb7HkkbqkgeuQz7NOBo\nkpXtfrZ7KYp4jLECl5/0KbyeiBVIj+RnqoeRZvzzSZUU19p+oNLAuiQLzW2GrfLvDYtNAS+1vV1V\nsXVLnl0uJv2/rCbN7OqkXjtSDMsKVtImxlcantZ8XkaZt6SlpGKXy4GL3IMq8USyQyS9tEpkhyKB\n9AFJLyH94loKfNT2hSW+dyc/kKIFAbVG0tnA4SQRyOuAW9s1RwblIum9nXSoSoyjXWf/Vsooyc+y\nLs+RHrFuYxZW5Hs6jLJDkUCmQE4ch5OSx54kFd7PVLGZleMZihlf2eQv50bGVk+ND3Xjyzm/7QuD\ngZI7pCf6BWMPgcy+pNl1qW4bRtmh2APpEUnLSWqat5BWHcMgfz5dZwPD4r0djOfmNtd+neRzUqp7\nXq5g2hX4ru3nJe0CnEoq5f3VEuM4hLEN8Ptt39nFy4dOdihWID2SZ72NmUtPS9IBxFSLstuyyMv7\nxbavqTqW6U6uEjyDZKb0CeAK2893flXf3vtUko/GQyR5nouB84HlwMdsP1pCDI0S3J8zVoK7P12U\n4EpaT3ra0U526OoqViCRQGpOk64PJD2ccb7JrpmUeS9kPaCTgN1IjxFvA04GPgistf32Di8PBoik\nV5OaXF9P2iO8uuz9qfzo56CsJbY78CBwoO3SmoElfQH4UuuekKT3AH9S5DMq6U46a4sdMsUwuyYS\nSM0ZNSnzXlByu3uSVN+/ENiFNCs7xSVapwbjkfR50iz7AlK/wzg72RIbCVsbZNfa3reM9256z/+y\nvXe394adSCBB7ZF0n+3X5eOZwKPA7q7QJyEASQ8zNmNuNsiCchsJ/4fxEvhHMd5wrAxP9A22X9nm\n+gySKd1k/VoomdYtJfV23UcyoqqkYKdBbKLXnCxl/lPbV7RcXwLMsf3JaiIrla0+CLa3SNoUyaN6\nbO9ZdQyZD7ecV6Fjd7OkT5OUeDdDqgAj7QfdUnCMz5D2bVaS1IWXkXpLKiNWIDVH0mrgALeYyWSx\nuFXToYS1pRkSxhoip00vzDCSGzsnpAwNqk4oOfu9rVlAdIDvtR3w96Sqr61mUKSO9DOKFBRIWmN7\nQdN55UUzsQKpPy9qTR4AuVSxNuZDU8F2qSWhQWEu6HDPwKFlBdIgP+J8C6ma6c0kJ9GBJ5D8Hf2Q\npL9hTF7o+7af7fCyVlrN32Y1n1eRkGMFUnOyd8Tv2/5Jy/VXALc39gamA1OssQ9GGEkHk/Th/pBk\nf3AgsFeXv8Cn8v6/Dfy3s5FUo/qKtBr52yIFBZNUYdl2+Qk5Eki9yR/EvySVrDZmIPuTNtsunA5S\n5v2osQ8GQ27YO4mxxP4ASQuqsPpsH2LYRNKLugT4ou1nJG20XVoDqqR7SBO9/5X0e6RN/PcDC4DX\n2H5nWbH0k3iEVXNsL5f0GHA2qTMekjfGmbb/vbrISuVC4JIJauwvBqIPpAIkHQh8FriStPkLKbH/\np6SjbX+zpFBuAI4gyf1vyWXfZc+cZzatMo4ELrd9I3CjpEKl5i09X5D+Do8Da5w90ssmViBB7RnV\nGvu6I+nbwPts39tyfQFwme03lhiLSOZWi0mPsX6J5MdxSy/KuD28//3Agiw7sh440fbKxj3b+3Qe\nYcKer7kkNfAltr/a16ALECuQmiNpGZ27U+tm59oLM9pdzDX2scFeHTu2Jg8A22uyqVJpOM2UvwZ8\nLVdEvZXUD3Ix8MslhHAtcJekx0mOgl8HkPSbwE+LDGD7+HbXJe1BatQsLSE3iARSf1ZVHcAQ0I8a\n+6D/SNJObjFNysZKbZN+CQG9HMDJUOomSbPKeF/b50q6gyTouMJjj35mkPZCpjL2Izkplk48wgpq\nT5sae4Dd6aLGPug/kk4E/oykz9Zc4HE+yfbgspLiEMni+WTGVqQvAMtsn11SDHNbLhl4yn34BSxp\nb+BK22+a6lhdv3ckkHqjIfNmr5I8m+y1xj4YAJIWAX/F+CqspS7RUjarNfwBad9hY762F6kq61bb\nnyghho2M96kB2AFYC/yp7YcLjHET2z6unkta1Rxj++7+RFucSCA1J1dgTejNbvuuKuIqE0nn2T4j\nHx9m+7aqYwqGB0n3AofZfrzl+stJj5MqM2HLlVUn2n5rgZ89uOWSgSeADVWtsiOB1ByNiDf7VGiW\ndBgGeYcgIenMDrdt+5yS4piwyqloBdQg6fUzK2lnkr/KI1XJwlSykRX0D9tbbN9q+zjgAJJpzp2S\nTq44tCDY3OYPpPLZ00uMo9PsvNL9MUk7UPD3sKSbJe2Tj3cl9XudAFydTbNKJ6qwRgBt683+KeAL\nVcZUMrvk59xqOt6K7X+sJqzpje2tWli5bPcU4HhSF3Ynnax+s6+kp9tcF/DSMgJo/UxmdiKp6l5Y\ncJh5HrPOPh64zfZ78r/tN4HSlbcjgdQcDac3e9l8GpjT5jiomFx9dBpwNKkqbr/Wst5BMyRim62f\nSQM/Jm1+31dwjGbR1IWkzzpZmuUXUw+xe2IPpOZoCL3ZgwBA0lKSX8XlJP2rgXd8jzK5CmsFsInk\nDTLP9lO5+nCV7d/qOMAgYooEEtQdSdfbflc+Pt/26U33Vth+c3XRTV/y5OY5Us/FtJ7cSDqIpP67\nPJ/fQCrBBfi7IjIkWZjybFLZ7kW2V+TrhwD72/74QILvFFMkkKDuSLq3UYrZWtHSfC8IqiJ3ob/f\n9rp8fh+p8XU2qdl10jLeYSSqsIJRoNMsKGZIwTCwYyN5ZDbYXp0FFQvv2Uk6TtJqSZvzn1VZdboS\nYhM9GAW2z85sMxjv0iaSJ0gQVM3Lmk9sN0uzv6LIAJKOA04lFSXcQ/p87wcslWTbV/Up1sLEI6yg\n9kzi1IbtQ8qLJgi2JW+AX2r7Ky3XF5Ek7w8vMMa3gaNaZU8k7QlcZ/uAvgVckEggQRAEAybLtn8F\n+BbjhSV/B1hk+8ECY6yz/dpu7w2S2AMJao+kYyQd2+b6sZLeXUVMQdCM7YdIUkNfJzX77gmsBOYX\nSR6Zn/V4b2DECiSoPZL+A1jY2meQPUFW2t6/msiCoDPZ9Gyx7WsK/OyzJKmibW6RSoRn9zu+yYhN\n9GAU2K5dk5rtzVUZ7QRBM5J2BE4CdgO+BNyezz9EknSfNIEArxlYgD0SCSQYBWZJmt1wI2yQNYJe\nXFFMQdDMVcCTwN0kk62PkFYOR9heU2QA249M/lPlEgkkGAWuAG6Q9BeNL1muTLko3wuCqtnL9usA\nJP0z8Ciwu+2fFx2gxZQKckd/Prbt3+hXsEWJBBLUHtsfl/R/wMosjy3gGeAfbF9SbXRBADQJIdre\nImlTN8kj84aW8xnAu0iPwe6dYnw9EZvowUiRH1th+5mqYwmCBpK2MCZ62mhwfZYedMHyxvuxwIeB\nNcB5LV3upRErkKD2tPNakMacfcMPJKiafkjK54KQE4APAN8g7Z+0q8oqjUggwSgQ/h/BUCPp0Ibi\nrqR5tjc23XuH7X8rMMxGkrLxJ4EfAvMlzW/cLDhGX4lHWEHtkXSy7aKubkFQOs0q0W0Uowt5oku6\nkokle2z7hL4E2wWxAglGgRMobgsaBFWgCY7bnbfF9nsnHFwqJMjYb0LKJAiCYPB4guN254WQ9DJJ\nS7LXSFRhBUEvSHqBVNGyzS2mmfNdMJxIeoqkfSXgd/Mx+fwg2zsVHGcW8Hbg3cDrSft/R5Ake0r3\nRY8EEtSecB0Mhh1JB3e6b/uuAmN8lpR8VgDXAV8FHrI9ry9B9kDsgQRBEAyejbZ/OMUxXkuSQ/ke\n8L3ckFjpCiD2QIJR4PNVBxAEk/DFxoGkG3sZwPYCUuf5HOB2Sd8A5lS1gQ6RQILR4DFJrwRQ4l8k\nPS3pu5ImLY8MghJorrTaq9dBbK+3fZbtVwOnAMuB70j61lQD7IVIIMEocArwcD5eTDLumUfyjv6n\nimIKgmY6VWH1NqC92vYHgT2Av+7HmN0SeyDBKPCC7YZY3SJgue0nSMv8j1UYVxA02FfS02QdrHwM\nXVQKSlpG5+SzssO9gRAJJBgFfiFpV9IG40Lg3KZ7s6oJKQjG6IcWFrCq6fijwFl9GHNKRAIJRoEz\nSV+umcCXbT8AW0snf1BlYEHQL2z/a+NY0qnN51URfSDBSCDpRcAc2082XZtN+oxvY3cbBHWmqH7W\noIkVSFB7JL2j6RjSc+LHgTXhCxIEgyMSSDAKvK3NtbkkueslDRntIKgzkp5hbBN9+1424vseUzzC\nCkYVSXsA19t+Y9WxBMEoEn0gwchi+xFgu6rjCIJRJRJIMLJI2ht4ruo4gmBUiT2QoPZIuoltG6zm\nArsCx5YfURBMD2IPJKg9ud+jVSriCWBDU4d6EAR9JhJIUHuaqlOaBesaH+zngO8DH7F9R9mxBcEo\nEwkkGGkkzQT2Aa6xvU/V8QTBKBGb6MFIY3uL7bXAsqpjCYJRI1YgQRAEQU/ECiQIgiDoiUggQRAE\nQU9EAgmCIAh6IhJIEARB0BORQIIgCIKe+H8ZG2Yo/2ok6QAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x13be03ed0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "DoM = widgets.IntSlider(min=10, max=27, value=15)\n",
+    "Hour = widgets.IntSlider(min=0, max=23, value=10)\n",
+    "nHashTags = widgets.IntSlider(min=0, max=40, value=50)\n",
+    "widgets.interact(plotHashtags, DoM=DoM, Hour=Hour, nHashTags=nHashTags)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this plot, we don't have data for all the days, so there are some days/hour combinations that will error due to lack of data. \n",
+    "\n",
+    "This potential method of aggregation works pretty well, but it would be really ideal if we could use different kinds of aggregation functions and have this ReadAndAggregateIntervals function work with many different kinds of aggregation functions that we might want. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#This works if we don't care about time stuff. \n",
+    "def ReadAndAggregateIntervals(linesAtATime,filepath, aggregationFunction):\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print i\n",
+    "                \n",
+    "                #First time running through\n",
+    "                if (i == linesAtATime):\n",
+    "                    agg = aggregationFunction(data)\n",
+    "                else:\n",
+    "                    agg = aggregationFunction(data, agg)\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "    #return the aggregation\n",
+    "    return hashtagsDict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def aggregateHashtags(df, hashtagsDict):\n",
+    "    #Create a named tuple that we'll be using as our dictionary key\n",
+    "    HashtagKey = namedtuple(\"HashtagKey\", [\"DoM\", \"Hour\", \"Text\"])\n",
+    "               \n",
+    "    df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])\n",
+    "    df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))\n",
+    "\n",
+    "    #loop over all the tweets\n",
+    "    for index,tweet in df.iterrows():\n",
+    "        #Loop over the hashtags in the tweet\n",
+    "        for hashtag in tweet['entities_hashtags_text']:\n",
+    "            hashtagsDict[HashtagKey(\n",
+    "                    tweet[\"DoM\"], \n",
+    "                    tweet[\"Hour\"], \n",
+    "                    hashtag.upper())] = hashtagsDict.get((tweet[\"DoM\"],\n",
+    "                                                 tweet[\"Hour\"],\n",
+    "                                                 hashtag.upper()), 0) + 1\n",
+    "            \n",
+    "    return hashtagsDict\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100000\n",
+      "200000\n",
+      "300000\n",
+      "400000\n",
+      "500000\n",
+      "600000\n",
+      "700000\n",
+      "800000\n",
+      "900000\n",
+      "1000000\n",
+      "1100000\n",
+      "1200000\n",
+      "1300000\n",
+      "1400000\n",
+      "1500000\n",
+      "1600000\n",
+      "1700000\n",
+      "1800000\n",
+      "1900000\n",
+      "2000000\n",
+      "2100000\n",
+      "2200000\n",
+      "2300000\n",
+      "2400000\n",
+      "2500000\n",
+      "2600000\n",
+      "2700000\n",
+      "2800000\n",
+      "2900000\n",
+      "3000000\n",
+      "3100000\n",
+      "3200000\n",
+      "3300000\n",
+      "3400000\n",
+      "3500000\n",
+      "3600000\n",
+      "3700000\n",
+      "3800000\n",
+      "3900000\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{HashtagKey(DoM='14', Hour=15, Text=u'DEVELOPMENTS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'SHARPTON'): 8,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'KABARI'): 5,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'ROBERTMCCULLOCH'): 3,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'JOHNHOTZ'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'NO'): 2,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'ILLEGAL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'ITSTIME'): 2,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'DOESNTLOOKPEACEFULTOME'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'FERGUSONMISSOURI'): 4,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'TEACHERS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'BOUFFON'): 2,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'KITDANIELS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'FLASHBACK'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'RCFEED'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'HELLINAHANDBASKET'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'LHHATL'): 8,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'BULLION'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'MUSLIMS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'PHX'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'FAILMEDIA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'FREEOCELOT2014'): 2,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'LEGALIZE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'ECUADOR'): 3,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'THEREALNEWS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'MURDERER'): 3,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'SCREENWRITING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'ODINFEELS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'RENISHAMCBRIDE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'NEXTBIGCHARITYCHALLENGE'): 3,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'TLOT'): 60,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'SOCIOPATH'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'RISINGSTAR'): 2,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'JUSTICEFORDARRENWILSON'): 2,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'SIMONSAYS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'SOPOWERFUL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'BURNINGMAN'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'AM\\xc9RIQUES'): 1,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'FLASHBANG'): 1,\n",
+       " HashtagKey(DoM='17', Hour=17, Text=u'BOSTONFORFERGUSON'): 1,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'\\u0130YIDEBENBUSAATTENSONRA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'ISRAELUNDERFIRE'): 3,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'PRESS'): 4,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'NIXON'): 2,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'ASSHOLES'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'NOCOMMENTARYNEEDED'): 1,\n",
+       " HashtagKey(DoM='19', Hour=11, Text=u'NLG'): 2,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'NEWJIMCROW'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'OAKWOOD'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'PSF2014'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'SBOT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'HOTEP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'THOMASJACKSON'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'WAGEPEACE'): 3,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'DREDSCOTT'): 8,\n",
+       " HashtagKey(DoM='14', Hour=22, Text=u'JUSTICE'): 5,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'DJKINGASSASSIN'): 3,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'VOTEORDIE'): 1,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'HISPANIC'): 4,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'NOVOTENOGOPPROBLEMS'): 3,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'XDA'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'OURLIVESMATTER'): 4,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'SGF'): 2,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'YOUGOGRANDMA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'REPUBLICAN'): 1,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'LOZTELETOBIIZ'): 12,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'INTERNACIONAL'): 4,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'OLIVERCROW'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'AMERICANCHEESE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'ACAB'): 7,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'MAKEAMERICAABETTERPLACE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'EXECUTIVEORDERS'): 14,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'EVIINSONTEAMA'): 2,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'CNN'): 89,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'OBSTRUCTIONOFJUSTICE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'RIPJAMESFOLEY'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'C2GTHR'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'EE'): 4,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'COMBAT'): 1,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'LOCALGOV'): 2,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'NEWWORLDORDER'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'GOP'): 54,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'LEVIN'): 1,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'THUGS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'AND'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'BRAZIL'): 8,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'SECURITY'): 2,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'LETUSHOPEITENDSWELL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'VFP'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'TANKS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'CAPTRONJOHNSON'): 3,\n",
+       " HashtagKey(DoM='14', Hour=23, Text=u'MYAWHITE'): 11,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'JIHAD'): 2,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'SMART'): 6,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'STEPUP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'SARCASM'): 3,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'PAULCALLAN'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'MAIL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'LOVEMYCHURCH'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'CHARLIERIEDEL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'SAIDNOONEEVER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'DISASTER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'INSANITYCHECK'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'BREAKINNEWS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'CNNFAIL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'RETURNTHESERVE'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'SOLIDARIDAD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'ALQAEDA'): 1,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'RICKPERRY'): 2,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'CAREYGILLAM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'STANDUPORFALLDOWN'): 3,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'THEBLACE'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'FOCUSPLEASE'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'YOU'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'LIBERIA'): 3,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'GADGETS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'SHAKEITOFF'): 8,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'OPINIONJOURNAL'): 2,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'MEDIABLACKOUT'): 9,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'I'): 2,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'CANADA'): 2,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'YOUPEOPLE'): 1,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'RESPONSE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'SERIOUSLY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'DJ'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'FEATHER'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'PHOTOGRAPHY'): 14,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'CLEOWILLIS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'GODISGOOD'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'BLACKBOYS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'AFRIQUE'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'BB4SP'): 8,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'FRANCE'): 14,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'STOPPOLICEBRUTALITY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'BELGIQUE'): 1,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'SOMEGOODNEWS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'ASBURYPARK'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'UNDESIRABLES'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'LAW'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'\\ub3c5\\ub9bd\\uc6b4\\ub3d9'): 2,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'IDFGIRLS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'BORDERCRISIS'): 5,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'TWIBDOCKET'): 11,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'THEWHOLEWORLDISWATCHING'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'REVALSAIDSO'): 2,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'RACIALLYPROFILED'): 2,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'SCOTTOLSON'): 5,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'STANDFORSOMETHINGORNOTHINGATALL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'TRECASMENA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'VOLVIOCAYENDOYCORRIENDO'): 4,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'LIVE'): 12,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'URGENTE'): 4,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'GLOBAL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'NOTODOEST\\xc1DICHO'): 2,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'SEANBELL'): 1,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'SHOUTOUT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'MIKEBROWNLAW'): 3,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'BORED'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'CORRUPTOFFICERS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'JEZEBEL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'DEMANDJUSTICE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'CHICFILA'): 3,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'CV'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'CNET'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'BANKERS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NIEUWSVIDEOS'): 5,\n",
+       " HashtagKey(DoM='14', Hour=19, Text=u'GUN'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'JERK'): 5,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'HOPEFUL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'REPRORIGHTS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'MAGOP'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'YOKELCHANG'): 3,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'INTERNATIONAL'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'TEAMLOVE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'HOWCONVENIENT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'PERFECTTIMING'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'NOT'): 3,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'THEGOSPEL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'STLOUIS'): 15,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'OMAHA'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'BLACKAMERICA'): 2,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'SOCIALJUSTICE'): 4,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'NORTHKOREA'): 2,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'FOCUS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'LIBERTY'): 9,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'CHILLING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'NDAWAY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'DNC'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'PROBLACK'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'CARDS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'WALGREENS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'GUN'): 7,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'HELLO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'KNOCKOUTGAME'): 1,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'MUNDO'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'EMERGENCY'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'NBCNEWS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'OURTAXDOLLARSATWORK'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'LAVERDADOBRERA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'SALINGFOLLOW'): 4,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'NEWORLEANS'): 17,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'GEEK'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'AR2'): 3,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'EDUCATEKCPT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'PETITION'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'KABARI'): 6,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'INSTITUTIONALRACISM'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'LABORDAY'): 3,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'INVALID'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'LITTLEBLACKBOYS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'HUFFINGTONPOST'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'COLLAGE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'COPPEDNEWS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'SPSU'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'MYDU'): 2,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'DBENEWS'): 4,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'FILISTIN'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'RIOTING'): 2,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'SUPPORTGOOD'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'NOM\\xc1SRACISMO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'MEDIAINGERMANY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'HANNITY'): 2,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'THEPSHOW'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'BIAS4COP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'PAIESTINA'): 2,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'WRONGFULARREST'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'UAREAGREATSENATORMARIA'): 5,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'MORELIES'): 2,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'MEDIA'): 6,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'WECOMING'): 4,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'STLCITY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'MILITARIZED'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'QUERY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'WELLACTUALLY'): 2,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'YOURESOLOVEDHARRY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=22, Text=u'RIP'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'RACES'): 2,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'HANDSUPDONTSHOOT'): 203,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'JORDANDAVIS'): 3,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'DC'): 28,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'NIOWA'): 2,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'BLOGGING'): 2,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'HANDSUPTURNUP'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'ABD'): 3,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'DMSANTANA_21'): 2,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'LAW'): 6,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'FML'): 2,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'REDACTED'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'20H'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'DOTHERIGHTTHING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'FREEGAZAMOVEMENT'): 3,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'DONTSHOOT'): 98,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'UNEMPLOYMENT'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'WESTERNAFRICA'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'I'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'FERGUSONPD'): 66,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'HALLOFFAME'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'CONSPIRACYTHEORIES'): 6,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'NBC'): 6,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'NATIONOFTROLLS'): 2,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'AMWRITING'): 2,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'WELLDONE'): 2,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'STARTUPNEWS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'THEOLIVIAFOXSHOW'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'2NDAMENDMENT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'IPROTEST'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'EDITEDVIDEO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'COUPLE'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'GOVJAYNIXON'): 4,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'MOSAIC'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'PRAYINGWITHOURFEET'): 2,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'PIGS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'MS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'REAL'): 14,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'UNCLETOM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'CITIZENJOURNALISTS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'ERICHOLDER'): 20,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'NOVAYAISGRACIAS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'LIMBAUGH'): 2,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'BLUE2014'): 12,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'THELASTWORD'): 3,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'HAIKUFIGHTCLUB'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'TITULARESEU'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'REVOLUTIONNOWORNEVER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'SERVICE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'USA'): 112,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'RHYMES'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'NBA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'FASCIST'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'INROCKS'): 4,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'CIVILREVOLT'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'MOUTHHUGSFORTIM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'CHANGE'): 4,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'PHOTOS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'HIDDENNEWS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'POSH'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'7CI'): 2,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'MYCOUNTRY'): 6,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'UNITEDNATIONS'): 13,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'MIDDLEEAST'): 3,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'TNTWEETERS'): 8,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'WESTERWELLE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'BOISE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'AGENTPROVOCATEUR'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'SM'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'BECAUSEITSGOINGTORAIN'): 1,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'EZELLFORD'): 7,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'MAYORBILL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'STATENISLAND'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'POLITIE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'ABD'): 3,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'JAYNIXON'): 8,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'TROOPS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'POLMTL'): 7,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'BUNDYRANCH'): 35,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'HISTORYSHOULDNOTREPEAT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'CURRENTAFFAIRS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'NOTALLCOPS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'MIZ'): 1,\n",
+       " HashtagKey(DoM='19', Hour=11, Text=u'INFONEWS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'NATIONOFCOWARDS'): 5,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'NBA'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'KONDOBYJAYMONI'): 6,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'JUSTICEFORFERGUSON'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'PHX'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'DEAROBAMA'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'LETSGETFREE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'\\u0623\\u062e\\u0628\\u0627\\u0631'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'FREGUSON'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'MP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'ROSARY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'SATIRE'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'DONTSHOOTMEBRO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'IDOTHINKTHISISTHEBEGINNINGOFSOMETHINGMUCHBIGGER'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'SOUTHDAKOTA'): 8,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'TYRANNY'): 17,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'FIRSTAID'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'BETTERLATETHANNEVER'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'JONSWAINEISAHACK'): 11,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'CT'): 4,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'METAMEDIO'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'BLACKLIVESDONTMATTERIN'): 2,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'PHLED'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'STARTUPS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'OHPOL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'LIBERALDREAMS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'CHAMAKOSERIOO'): 2,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'MIFF2014'): 2,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'STOPSHOOTINGATNEWSVANS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'OPENSEASON'): 5,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'OOGOMOOG'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'BRAZIL'): 6,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'RICHMOND'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'FBI'): 27,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'NIEUWSVIDEOS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'UGH'): 1,\n",
+       " HashtagKey(DoM='14', Hour=20, Text=u'ICANT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'MADDOW'): 58,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'ISTANBUL'): 4,\n",
+       " HashtagKey(DoM='14', Hour=23, Text=u'THEFIVE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'DAVIDLETTERMAN'): 2,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'FREEDOM'): 2,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'CANADA'): 2,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'VIEWHOLDER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'MILITARIZATIONOFPOLICE'): 7,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'USNEWS'): 3,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'NEVERFEARHOLDERSHERE'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'HELPINGORHURTING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'GOVERNORS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'MARTHAVINEYARD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'ERICHOLDER'): 65,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'AFFRONTEMENTS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'DATOS'): 2,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'BLOODCUZZ'): 5,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'A19'): 1,\n",
+       " HashtagKey(DoM='14', Hour=23, Text=u'WILDWEST'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'KENTUCKY'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'CBTU'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'TERRIBLE'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'PHOTOJOURNALISM'): 13,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'SHARPTON'): 14,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'DISARMTHECOPS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'REFORMJO'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'DIREITOSHUMANOS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'WELLACTUALLY'): 10,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'PAKISTAN'): 2,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'INSPIRINGED'): 2,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'FINANCENEWS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'YOUTUBE'): 3,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'NOTICIAS'): 11,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'LOUISCOUNTYPOLICE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'NATIONALACTIONNETWORK'): 2,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NFLF'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'MINI_SWAG1'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'SOSEEUU'): 6,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'JUSTICEFORMIKEBROW'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'HUFFPO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'AUTOFOLLOW'): 7,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'ARTONFIRE'): 3,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'FREEGAZA'): 5,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'BOYCOTTSTL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'KIWANECARRINGTON'): 2,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'STLSHOOTING'): 1,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'SPREADCAM'): 2,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'HARLEYDAVIDSON'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'MOVEORYOURENEXT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'HARASSMENT'): 2,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'FRESNO'): 2,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'ROBERTCOHEN'): 3,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'TEFPOE'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'MADRID'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'OTTAWA'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'SOUTHERNDEMOCRATS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'VOTEBLUE2014'): 3,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'NOS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'THINK'): 3,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'NORMSTAMPER'): 3,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'FPD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'TALIBKWELI'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'AMIDFERGUSON'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'TELMI'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'HOWMANYMORE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'LIVESMATTER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'BLATANTDOMESTICTERRORISM'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'FUCKTHENRA'): 1,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'HSV'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'IRACK'): 2,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'ULTIMAHORA'): 3,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'STFU'): 2,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'GROWUP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'STLRIOTS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'ANOTHERSHOOTING'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'WESTBOROBAPTISTCHURCH'): 4,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'SHAME'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'KEEPTHEPEACE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'TYRANNY'): 8,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'APPRECIATEYOUMYBROTHA'): 2,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'TGDN'): 24,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'CCSS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'SORRYFORYOURLOSS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'SHAWSHANKREDEMPTION'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'DMEDIISON_21'): 12,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'CONSTANTCONTACT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'AUDRELORDE'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'CLASSACT'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'PEACENOW'): 1,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'M5S'): 4,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'PAYATTENTION'): 4,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'INTERNACIONALES'): 3,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'DONTSHOOT'): 60,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'HANDSUPHOUSTON'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'COUNTRY'): 3,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'KILLING'): 2,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'CROOKEDSYSTEM'): 3,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'MIKEBROW'): 3,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'FERGUSONPROTESTS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'GUNSENSE'): 2,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'YEREMIITO21'): 3,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'CROWDFUNDING'): 3,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'REDLINE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'PEOPLEAREAWESOME'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'MISSISSIPPI'): 2,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'LOUISVILLE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'CAUSEYOUSHOULDBE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'POLICEMILTARYBRUTALITY'): 9,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'ODD'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'MA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'PUPPET'): 2,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'NCAT18'): 8,\n",
+       " HashtagKey(DoM='14', Hour=23, Text=u'WASHINGTON'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'JAMESPARROTT'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'PARIS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'TRGGRRADIO'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'DICTATORSHIP'): 3,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'COMMANDPYCHOSIS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'PLANKPROTESTING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'CLUSTERFUCK'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'APPALLING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'TIMESSQUARE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'CRITICALMEDIA'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'RIPROBINWILLIAMS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'DOWNTOWN'): 4,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'MINORITIES'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'N4TM'): 3,\n",
+       " HashtagKey(DoM='14', Hour=22, Text=u'WELLDONE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'ECIG'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'DEMOCRATICPARTY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'RW16'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'POLAND'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'CORRUPT'): 1,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'UNCATEGORIZED'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'TULSACOCAINBUST'): 1,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'COP'): 3,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'P3'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'SECONDHOME'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'SWAT'): 2,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'BLUMOB'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'CHRISTIE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'SIXPACK'): 1,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'BNEWS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'EVERY28HOURS'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'TRIGGERHAPPY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'FREEDOMOFPRESS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'DENVERMARCHFORJUSTICE'): 3,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'BIAS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'MAKINAHD'): 3,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'SPEAKUP'): 7,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'AMERIKKKA'): 3,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'NOTSPORTS'): 36,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'STANDUPFORYOURRIGHTS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'FUCKYOU'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'GOFUNDME'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'ORDERNO'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'REPORTERSARRESTED'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'CCOT'): 10,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'GOTV'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'MATURIN'): 2,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'BROWN'): 241,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'JOURNALISM'): 4,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'SOLIDARITYWITHFERGUSON'): 4,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'LUIS_FRESH'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'WHATSHOULDBEONMYTL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'IAMTRYINGTOBELIEVE'): 2,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'WEEDLORD'): 1,\n",
+       " HashtagKey(DoM='14', Hour=23, Text=u'INDY'): 4,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'THECONFIRMATION'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'REVS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'MISSISSAUGA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'COOPERATIVE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'REDSKINS'): 2,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'OLS2014'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'ALSICECHALLENGE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'SHOOTER'): 20,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'COOLDADS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'NATURALS'): 4,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'BLACKMOTHERITIS'): 3,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NEVADA'): 2,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'REPORTERS'): 8,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'JHENEBENTOBOX'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'TEARGAS'): 8,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'PRISONPLANET'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'WAKEUPAMERICA'): 8,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'DOGECOIN'): 5,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'CONSERVATIVES'): 3,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'DONTPANIC'): 2,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'NATIONAL'): 2,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'TORNADO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'COMMONGROUNDS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'LANSING'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'ARREST'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'FUKUSHIMA'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'DRKING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'UPPERS'): 4,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'HAUSARREST'): 7,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'EDLEADERSHIP'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'ONELOVE'): 2,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'ACTNOW'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'STATETROOPERS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'UWSMC'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'MILITARIZEDPOLICE'): 12,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'CHAOS'): 11,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'WEAPONS'): 30,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'SPEAKUP'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'HYPOCRITE'): 3,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'ROBINWILLIAMS'): 31,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'TOWARDSALLYSHIPNOTAWAY'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'DREAMVILLE'): 1,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'DIIME_DANIIEL'): 5,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'LEFTBANKBOOKS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'PRAYFORPEACE'): 4,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'BUTTWITTERACTIVISMAINTREALSO'): 25,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'REBELLIOUSSOULMUSICAL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'ISLAM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'POCH'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'WELFARE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'OBAMAGOLFS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'WESTFLORISSANTAVENUE'): 2,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'HARRYPOTTER'): 5,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'DAY10'): 5,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'VOTING'): 2,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'SHAQUILLE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'WORLDWIDE'): 2,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'FR'): 1,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'AMERICANSUNDERSEIGE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'HISTORY'): 4,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'TRILLTALK'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'MUFC'): 4,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'AGENDA21'): 3,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'STOPTHERACISM'): 1,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'FEAR'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'TASHIDELEK'): 3,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'UN'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'UPPERS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'PANTSUPDONTLOOT'): 1,\n",
+       " HashtagKey(DoM='14', Hour=20, Text=u'SAD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'BUTUMADATTHEPREACHER4TAKINGUR'): 2,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'BOSTON'): 4,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'BIZ'): 2,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'PROP47'): 1,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'CITIZENS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'KNOCKOUT'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'NOVIOLENCE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'BLACKLEADERSHIP'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'CITYUNDERSEIGE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'IFTHEYGUNNEDMEDOWN'): 18,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'LAMENTE_MACABRA'): 2,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'SOSVZLA'): 2,\n",
+       " HashtagKey(DoM='20', Hour=15, Text=u'BROOKLYNABRIDGED'): 2,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'DETROIT'): 9,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'CBC'): 6,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'YESDATSMYNAME'): 1,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'CENSORSHIP'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'\\ub3c5\\ub9bd\\uc6b4\\ub3d9\\uac00'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'EVERYONEMATTERS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'POLICING'): 2,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'TWIBDOCKET'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'WHEREISDARRENWILSON'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'USMNT'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'TACHIRA'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'GODZILLA'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'ANON'): 9,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'WHATILEARNEDTODAY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'CROWD_CONTROL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'DDHH'): 5,\n",
+       " HashtagKey(DoM='21', Hour=0, Text=u'BLACKEDU'): 5,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'DISABILITY'): 3,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'FRONTPAGES'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'BACKWOODSBADASS'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'SOUTHAFRICA'): 2,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'FERGUSOM'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'WIN'): 3,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'EARLYBIRD'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'PRAYFORTHISNIGGA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'DEVOLVE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'NOWPLAYING'): 8,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'BRAINWASHEDSOCIETY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'JOHNLEGEND'): 1,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'GAZAMILLIONMARCH'): 5,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'RELIGIONPOISONSEVERYTHING'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'YAZIDIS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'NORIOTPOLICE'): 4,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'MOMMYBLOGGER'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'FERUGSON'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'IS'): 8,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'AGENDA21'): 1,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'ITALIA'): 1,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'LIES'): 3,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'ANSWER'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'JOKE'): 2,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'THERUN2016'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'MURDERISTHECASE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'NOTHINGTOSEEHERE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'ALBANYSTATE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'KMOV'): 6,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'WHITEPRIVILEGE'): 94,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'TURNOUT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'GREATERST'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'MIDDLECLASS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'BRIANRUTTENBUR'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'LAWENFORCEMENT'): 4,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'\\uce74\\ub77c'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'PHOTOJOURNALISME'): 1,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'OUTFRONT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'ICC4ISRAEL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=11, Text=u'MICHAEL'): 5,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'MURICA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'ROBOCOP'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'LLWS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'NATIONALGUARD'): 22,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'DERANGEDRADIO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'CARSI'): 2,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'NDNETWORK'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'STLOUIS'): 64,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'NOMORE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'SPECIALREPORT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'NIEUWSVIDEOS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'DOBETTER'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'TWIBDOCKET'): 3,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'BEFREE'): 3,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'BEARINGWITNESS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'UK'): 20,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'RKBA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'HIGHWAYPATROL'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'WICKED'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'TEAMYAMITA'): 13,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'GREENBRIERGUESSINGGAME'): 1,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'FEMINIST'): 24,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'INNOCENTUNTILPROVENGUILTY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'SLAVERY'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'ISDSTRONG'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'PH'): 2,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'EDL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'ANCHORAGENEWS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'ALJAZEERAAMERICA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'BIBLE'): 3,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'AC360'): 7,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'NOW'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'ENDRACISM'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'NEWORLEANS'): 4,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'FERGUSONPOLICE'): 37,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'SUPERBOWL2015'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'ATHEIST'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'OSCARGRANT'): 6,\n",
+       " HashtagKey(DoM='19', Hour=11, Text=u'STLNEEDSJIMMY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'JFK'): 3,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'CYPRUS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'MARKETINGDIGITAL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'BLACKOUT'): 2,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'TKT'): 3,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'WHITES'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'KIMANIGRAY'): 3,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'MUHAMADJABAL'): 2,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'SOLOEXIGENJUSTICIA'): 2,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'IDOL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'PALESTINE'): 1177,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'KY'): 3,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'CHANGETHEMASCOT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'LISTENLIVE'): 1,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'RHEE'): 2,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'RICKPERRY'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'THATLEADERSHIPTHO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'RIGHTTOBEARWITNESS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'CHANGE'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'TWITTERREVERB'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'FUCKMSM'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'PRESSCONFERENCEPRAYERS'): 3,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'MOMSDEMAND'): 11,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'MATTHEWDUMAS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'TEACHINGMOMENT'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'ROOTS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=8, Text=u'NEWYORK'): 11,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'LASTRT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'MARCLAMONTHILL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'SPIRITUAL'): 2,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'EFE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'CLASHDAILY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'MINORITY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'THEGUARDIAN'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'C4NEWS'): 1,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'HASHTAG'): 2,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'WEAREALLFERGUSON'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'ISRAEL'): 10,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'EQUALITY4ALL'): 14,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'JIMCAREY'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'ECONOMIC'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'CORRUPTION'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'PEACE4ALL'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'CHAROBS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'WATER'): 8,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'WEARENOTSTUPID'): 7,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'RENITALAMKIN'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'BO'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'CANWELIVE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'MOREKIDSLISTENTORAPPERSTHANCNN'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'TIMEOUT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'WHATISJUSTICE'): 4,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'STOPBYOURHOUSE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'VACCINE'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'MURDER'): 4,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'ICHTHUS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'NOWPLAYING'): 5,\n",
+       " HashtagKey(DoM='14', Hour=20, Text=u'BILLIONSOFHITSPLUSHATEMAIL'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'UCWRADIO'): 3,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'WASHINGTON'): 15,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'ISRAEL'): 22,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'FASHION'): 4,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'REVALSHARPTON'): 1,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'HERRERATEAMSWAGGA'): 2,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'DEFEATOBAMA'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'KONA'): 3,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'SEANBELL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'CUBADEBATE'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'NDN'): 2,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'WIP'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'USFCAMS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'ONKOKONSAGHTHISWEEK'): 2,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'EFF'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'PEACEFUL'): 7,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'NORTHSTL'): 197,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'LAPD'): 8,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'PHOTOGRAPHY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'ANDERLIN'): 2,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'WY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'PLDEBATT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'FREEDOMEXPRESSION'): 2,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'NEWS3'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'IS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'THISISUNREAL'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'WATCHWHSV'): 2,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'NL1'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NEWSNATION'): 1,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'PUFC'): 2,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'LUIS_FRESH'): 1,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'GIUSTIZIA'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'ITHASTOSTOPNOW'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'THECEOPUNDIT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'KELLYFILE'): 81,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'FERGUS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'OOH'): 2,\n",
+       " HashtagKey(DoM='20', Hour=17, Text=u'FERGUSONSHOOTING'): 83,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'WRONG'): 2,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'BADCOPS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'RAMSEYORTA'): 3,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'STEPHENCOLBERT'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'MAKINGTHESITUATIONWORSE'): 2,\n",
+       " HashtagKey(DoM='19', Hour=23, Text=u'PRAYCHURCH'): 2,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'SNRTG'): 1,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'POLICEOUTOFCONTROL'): 1,\n",
+       " HashtagKey(DoM='14', Hour=21, Text=u'HISHERS'): 16,\n",
+       " HashtagKey(DoM='19', Hour=13, Text=u'DISGUSTING'): 2,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'ICELAND'): 3,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'RONPAULREVOLUTION'): 1,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'SHOWMECIVILRIGHTS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'ELECTIONSHAVECONSEQUENCES'): 4,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'MICHAELB'): 3,\n",
+       " HashtagKey(DoM='20', Hour=4, Text=u'DIGNITY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'ANTISEMITISM'): 3,\n",
+       " HashtagKey(DoM='14', Hour=19, Text=u'CIVILWAR'): 1,\n",
+       " HashtagKey(DoM='17', Hour=19, Text=u'GREEN'): 1,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'FREEDOMOFPRESS'): 2,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'COP'): 5,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'NJTVNEWS'): 2,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'PEOPLEOVERPOLITICS'): 3,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'MILWAUKEE'): 832,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'RELIGIOUSFREEDOM'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'NANCYGRACE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'VENEZUELA'): 18,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'VIOLENCE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'BERITA_IN'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'HTAFC'): 1,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'GUNS'): 2,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'HASHTAG'): 34,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'REPRODUCTIVEJUSTICE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=18, Text=u'ATHEISM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'RACHELJENTEAL'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'CSPANCHAT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=20, Text=u'BREAKINGNEWS'): 14,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'PIDEBACK'): 2,\n",
+       " HashtagKey(DoM='19', Hour=7, Text=u'VOTE'): 3,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'TRUTH'): 23,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'COVERAGE'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'YASSEL10'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'STANDWITHFERGUSON'): 70,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'FERGUSON_USA'): 6,\n",
+       " HashtagKey(DoM='15', Hour=0, Text=u'TIMEFORCHANGE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'WHATABOUTTHEOTHERS'): 2,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'PT'): 2,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'MAYGODBLESSTHEM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'RATM'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'MISSOURI'): 74,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'WHOISINCHARGE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=20, Text=u'REDDIT'): 11,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'KELLYFILE'): 49,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'SANFORD'): 2,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'BETRUE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'LEOYORK'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'NBC7'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'SOSAYWEALL'): 5,\n",
+       " HashtagKey(DoM='20', Hour=16, Text=u'DEMOCRACYWORKS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'KIMANIGRAY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'WALKINGDEAD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'TOPPROG'): 4,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'VOTEDEMILOVATO'): 1,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'VERMONT'): 2,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'\\xc7APULCU'): 2,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'PROBLEM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'GOP'): 8,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'JUAN_STARZ'): 1,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'PATRIOTACT'): 3,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'FEARMONGERING'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'THELASTWORD'): 12,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'ATTACKING'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'PRESIDENTBARACKOBAMA'): 3,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NERF'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'FAS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'ZOMBIES'): 4,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'FITNESS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=2, Text=u'GOTV'): 2,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'BUNDYRANCH'): 12,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'OWSINFO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=8, Text=u'XS'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'LEOYORK'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'HUFFPOST'): 1,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'BIGDATA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'WHYNOT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'WHATAGOATROPING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'RICKPERRY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'SONG'): 2,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'LEVITY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'ETHICSINJOURNALISM'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'CINNOIR'): 6,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'BBCNEWSNIGHT'): 6,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'WE'): 1,\n",
+       " HashtagKey(DoM='15', Hour=2, Text=u'JACKBOOTS'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'MILESKANE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'GENERALNEWS'): 2,\n",
+       " HashtagKey(DoM='17', Hour=21, Text=u'CYA'): 1,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'CONSPIRACY'): 3,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'UCWRADIO'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'MRBROWN'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'MANIFENCOURS'): 9,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'CNNENESPANOL'): 1,\n",
+       " HashtagKey(DoM='21', Hour=1, Text=u'ONPOINT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=12, Text=u'KNOWLEDGEISPOWER'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'BORDERCRISIS'): 7,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'LAW'): 3,\n",
+       " HashtagKey(DoM='19', Hour=10, Text=u'TEAPAY'): 4,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'FARRAKHAN'): 23,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'RIVOLTA'): 1,\n",
+       " HashtagKey(DoM='18', Hour=0, Text=u'MISSOURISHOOTING'): 2,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'SHENANIGANS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'DELUXMAGAZINE'): 6,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'GLV'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'NORTHCOUNTY'): 1,\n",
+       " HashtagKey(DoM='15', Hour=3, Text=u'WESTANDUNITED'): 1,\n",
+       " HashtagKey(DoM='14', Hour=22, Text=u'INNERS'): 3,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'PEOPLESMEDIA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'POLITIE'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'PHOTO'): 1,\n",
+       " HashtagKey(DoM='21', Hour=3, Text=u'RICHARDSTALLMAN'): 2,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'VOTERAPATHY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'TIBETANS'): 1,\n",
+       " HashtagKey(DoM='17', Hour=23, Text=u'CLEOWILLIS'): 1,\n",
+       " HashtagKey(DoM='14', Hour=16, Text=u'DISHFEED'): 1,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'CRITICALTHINKING'): 1,\n",
+       " HashtagKey(DoM='19', Hour=5, Text=u'STAYUP'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'DESTACADOS'): 12,\n",
+       " HashtagKey(DoM='14', Hour=17, Text=u'ITBREAKSMYHEART'): 2,\n",
+       " HashtagKey(DoM='20', Hour=10, Text=u'SUSPENSE'): 3,\n",
+       " HashtagKey(DoM='14', Hour=14, Text=u'FREEANTONIOFRENCH'): 72,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'BLACKPRESIDENT'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'BADIDEA'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'NY'): 2,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'BUSH'): 2,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'GOHOME'): 2,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'YAZIDIS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'PEACECHALLENGE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'VASCANDAL'): 15,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'TSA'): 1,\n",
+       " HashtagKey(DoM='18', Hour=1, Text=u'JHONSONFRESZ'): 2,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'SUPPORTCAPITALISM'): 1,\n",
+       " HashtagKey(DoM='20', Hour=0, Text=u'IBLOCKRACISTS'): 4,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'DUOPOLY'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'MURDERINMISSOURI'): 1,\n",
+       " HashtagKey(DoM='17', Hour=20, Text=u'DIVINE9'): 9,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'NOTREDAME'): 1,\n",
+       " HashtagKey(DoM='19', Hour=18, Text=u'VIEWGRAPHICANGRY'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'UNION'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'RESTLESSAMERICA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=14, Text=u'STOCKMARKET'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'FOX'): 4,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'MH17'): 8,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'GODBLESS'): 4,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'MAKINAHD'): 4,\n",
+       " HashtagKey(DoM='20', Hour=3, Text=u'DOIGOTTHATRIGHT'): 1,\n",
+       " HashtagKey(DoM='20', Hour=1, Text=u'VIRUS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'RPS'): 1,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'ARRESTDARRENWILSON'): 64,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'STANDTOGETHER'): 1,\n",
+       " HashtagKey(DoM='20', Hour=13, Text=u'AALS2015'): 3,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'BLUEWALL'): 1,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'KNOCKOUTGAME'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'DIRTYSOUTHMAFIA'): 1,\n",
+       " HashtagKey(DoM='20', Hour=5, Text=u'SHABAZZ'): 2,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'EMERGENCY'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'PRAYER'): 2,\n",
+       " HashtagKey(DoM='15', Hour=7, Text=u'JUSTICEFORMICHAEL'): 11,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'YOUTUBENATION'): 1,\n",
+       " HashtagKey(DoM='20', Hour=23, Text=u'SFGIANTS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'COLONIALUCC'): 1,\n",
+       " HashtagKey(DoM='17', Hour=22, Text=u'GRAMFAM'): 2,\n",
+       " HashtagKey(DoM='20', Hour=19, Text=u'JAX'): 2,\n",
+       " HashtagKey(DoM='20', Hour=22, Text=u'KNX'): 2,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'FRANTI'): 1,\n",
+       " HashtagKey(DoM='18', Hour=3, Text=u'SOCIAL'): 1,\n",
+       " HashtagKey(DoM='14', Hour=15, Text=u'JOBS'): 2,\n",
+       " HashtagKey(DoM='19', Hour=6, Text=u'FOOD'): 1,\n",
+       " HashtagKey(DoM='20', Hour=21, Text=u'TBT'): 13,\n",
+       " HashtagKey(DoM='20', Hour=11, Text=u'HUMANRIGHTS'): 6,\n",
+       " HashtagKey(DoM='20', Hour=6, Text=u'DARRENWILLSON'): 2,\n",
+       " HashtagKey(DoM='21', Hour=2, Text=u'COPS'): 17,\n",
+       " HashtagKey(DoM='19', Hour=14, Text=u'SAYFIE'): 4,\n",
+       " HashtagKey(DoM='15', Hour=1, Text=u'SOLIDARITYFORFERGUSON'): 1,\n",
+       " HashtagKey(DoM='18', Hour=4, Text=u'THINKINGOUTLOUD'): 2,\n",
+       " HashtagKey(DoM='20', Hour=2, Text=u'HOMEOFTHEBRAVE'): 1,\n",
+       " HashtagKey(DoM='19', Hour=19, Text=u'NEWSTICA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=12, Text=u'MOEDCHAT'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'TAKEMEOUTSA'): 1,\n",
+       " HashtagKey(DoM='19', Hour=22, Text=u'PEWRESEARCH'): 1,\n",
+       " HashtagKey(DoM='19', Hour=9, Text=u'KOOLAID'): 1,\n",
+       " HashtagKey(DoM='19', Hour=16, Text=u'DITCHMITCH'): 2,\n",
+       " HashtagKey(DoM='19', Hour=21, Text=u'\\xc9MEUTES'): 1,\n",
+       " HashtagKey(DoM='20', Hour=9, Text=u'VIOLENCE'): 1,\n",
+       " HashtagKey(DoM='20', Hour=7, Text=u'UNITEDSTATESOFOPPRESSION'): 1,\n",
+       " HashtagKey(DoM='19', Hour=15, Text=u'BUSINESS'): 38,\n",
+       " HashtagKey(DoM='19', Hour=8, Text=u'WTH'): 33,\n",
+       " HashtagKey(DoM='19', Hour=17, Text=u'CLEOWILLIS'): 1,\n",
+       " HashtagKey(DoM='15', Hour=9, Text=u'DIW'): 1,\n",
+       " HashtagKey(DoM='17', Hour=18, Text=u'CONSERVATIVEVIDEOS'): 1,\n",
+       " HashtagKey(DoM='18', Hour=5, Text=u'INTERNATIONAL'): 2,\n",
+       " ...}"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ReadAndAggregateIntervals(100000, filename, aggregateHashtags)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/Popular_Hashtags_Over_Time.ipynb b/Popular_Hashtags_Over_Time.ipynb
new file mode 100644
index 0000000..f836717
--- /dev/null
+++ b/Popular_Hashtags_Over_Time.ipynb
@@ -0,0 +1,2304 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Popular Hashtags Over Time\n",
+    "**Sophia and Victoria**\n",
+    "\n",
+    "In this notebook, we're going to be exploring how to visualize information about the hashtags people use in tweets! In this notebook, we'll be using a subset of the data!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Importing everthing!\n",
+    "Let's get ready to do some cool data things!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "% matplotlib inline\n",
+    "import pandas as pd\n",
+    "import json\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import time\n",
+    "from datetime import datetime, date, timedelta\n",
+    "\n",
+    "\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets\n",
+    "import matplotlib.cm as cm\n",
+    "\n",
+    "from matplotlib import animation\n",
+    "from IPython.display import HTML\n",
+    "from tempfile import NamedTemporaryFile\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Reading in Data\n",
+    "Here, we're using a function that we've developed to read in the data, a certain number of lines at a time. This uses a file of cleaned tweets that can be found..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def ReadToDf(linesAtATime,filepath, max=-1):\n",
+    "    start = time.time()\n",
+    "    df = pd.DataFrame()\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filepath) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print \"number of tweets parsed: \", i\n",
+    "                print \"total time elapsed: \", time.time() - start\n",
+    "                df = df.append(pd.DataFrame(data=data))\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "        #Allow us to handle the last few tweets, and to truncate the data if we just want to run unit tests\n",
+    "            if (max > 0 and i >= max):\n",
+    "                break\n",
+    "        df = pd.DataFrame(data=data).append(df)\n",
+    "    #return the aggregation\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "number of tweets parsed:  100000\n",
+      "total time elapsed:  1.75667119026\n",
+      "number of tweets parsed:  200000\n",
+      "total time elapsed:  4.05197715759\n"
+     ]
+    }
+   ],
+   "source": [
+    "shooting_df = ReadToDf(100000, 'data/cleanedShootingTweets.json', 200000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>coordinates_x</th>\n",
+       "      <th>coordinates_y</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>retweet_count</th>\n",
+       "      <th>retweeted_status_id_str</th>\n",
+       "      <th>user_id_str</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_verified</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:52:55 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>501064141332029440</td>\n",
+       "      <td>3</td>\n",
+       "      <td>None</td>\n",
+       "      <td>851336634</td>\n",
+       "      <td>20mUsa</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:02 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[295988417]</td>\n",
+       "      <td>[NerdyNegress]</td>\n",
+       "      <td>501064171707170816</td>\n",
+       "      <td>10</td>\n",
+       "      <td>501064110696857600</td>\n",
+       "      <td>53158947</td>\n",
+       "      <td>MzDivah67</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:04 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[295988417]</td>\n",
+       "      <td>[NerdyNegress]</td>\n",
+       "      <td>501064180468682752</td>\n",
+       "      <td>10</td>\n",
+       "      <td>501064110696857600</td>\n",
+       "      <td>619587350</td>\n",
+       "      <td>BrookLyn1825</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>501064188211765249</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>374346913</td>\n",
+       "      <td>I_Mpower</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:07 +0000 2014</td>\n",
+       "      <td>[USNews]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>501064194309906436</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>2272978051</td>\n",
+       "      <td>Vorarlberg1</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[90296594]</td>\n",
+       "      <td>[Thatindianbruh]</td>\n",
+       "      <td>501064196642340864</td>\n",
+       "      <td>10479</td>\n",
+       "      <td>501051914218668032</td>\n",
+       "      <td>1458086762</td>\n",
+       "      <td>rachel_palomera</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, MikeBrown]</td>\n",
+       "      <td>[18989941]</td>\n",
+       "      <td>[BgRs]</td>\n",
+       "      <td>501064196931330049</td>\n",
+       "      <td>228</td>\n",
+       "      <td>501017032486178818</td>\n",
+       "      <td>278298244</td>\n",
+       "      <td>bookishshelly</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>501064197396914176</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>1112443196</td>\n",
+       "      <td>deegerwiilen</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, tcot, uniteblue, teaparty, gop]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>134</td>\n",
+       "      <td>501062167303450626</td>\n",
+       "      <td>21811025</td>\n",
+       "      <td>mmaureen7</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, CrimeButNoTime]</td>\n",
+       "      <td>[935015863]</td>\n",
+       "      <td>[bryancrumpler]</td>\n",
+       "      <td>501064198009655296</td>\n",
+       "      <td>5493</td>\n",
+       "      <td>501011628448841728</td>\n",
+       "      <td>2743004644</td>\n",
+       "      <td>collettehodson</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   coordinates_x  coordinates_y                      created_at  \\\n",
+       "0            NaN            NaN  Sun Aug 17 17:52:55 +0000 2014   \n",
+       "1            NaN            NaN  Sun Aug 17 17:53:02 +0000 2014   \n",
+       "2            NaN            NaN  Sun Aug 17 17:53:04 +0000 2014   \n",
+       "3            NaN            NaN  Sun Aug 17 17:53:06 +0000 2014   \n",
+       "4            NaN            NaN  Sun Aug 17 17:53:07 +0000 2014   \n",
+       "5            NaN            NaN  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "6            NaN            NaN  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "7            NaN            NaN  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "8            NaN            NaN  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "9            NaN            NaN  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "\n",
+       "                       entities_hashtags_text entities_user_mentions_id_str  \\\n",
+       "0                                  [Ferguson]                            []   \n",
+       "1                                  [Ferguson]                   [295988417]   \n",
+       "2                                  [Ferguson]                   [295988417]   \n",
+       "3                                          []                            []   \n",
+       "4                                    [USNews]                            []   \n",
+       "5                                  [Ferguson]                    [90296594]   \n",
+       "6                       [Ferguson, MikeBrown]                    [18989941]   \n",
+       "7                                          []                            []   \n",
+       "8  [Ferguson, tcot, uniteblue, teaparty, gop]                            []   \n",
+       "9                  [Ferguson, CrimeButNoTime]                   [935015863]   \n",
+       "\n",
+       "  entities_user_mentions_screen_name              id_str  retweet_count  \\\n",
+       "0                                 []  501064141332029440              3   \n",
+       "1                     [NerdyNegress]  501064171707170816             10   \n",
+       "2                     [NerdyNegress]  501064180468682752             10   \n",
+       "3                                 []  501064188211765249              0   \n",
+       "4                                 []  501064194309906436              0   \n",
+       "5                   [Thatindianbruh]  501064196642340864          10479   \n",
+       "6                             [BgRs]  501064196931330049            228   \n",
+       "7                                 []  501064197396914176              0   \n",
+       "8                                 []  501064197632167936            134   \n",
+       "9                    [bryancrumpler]  501064198009655296           5493   \n",
+       "\n",
+       "  retweeted_status_id_str user_id_str user_screen_name user_verified  \n",
+       "0                    None   851336634           20mUsa          True  \n",
+       "1      501064110696857600    53158947        MzDivah67         False  \n",
+       "2      501064110696857600   619587350     BrookLyn1825         False  \n",
+       "3                    None   374346913         I_Mpower         False  \n",
+       "4                    None  2272978051      Vorarlberg1         False  \n",
+       "5      501051914218668032  1458086762  rachel_palomera         False  \n",
+       "6      501017032486178818   278298244    bookishshelly         False  \n",
+       "7                    None  1112443196     deegerwiilen         False  \n",
+       "8      501062167303450626    21811025        mmaureen7         False  \n",
+       "9      501011628448841728  2743004644   collettehodson         False  "
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shooting_df.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cleaning Data\n",
+    "This is where we're going to clean data that we've read in. The only cleaning that we need to do is that we need to convert the \"created_at\" column to a datetime object. The rest of the cleaning data is done in the script `development_scripts/clean_json_data.py`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def recodeData (dataframe):\n",
+    "    # Creating a parseable dataset    \n",
+    "    dataframe['createdDatetime'] =  pd.to_datetime(\n",
+    "        dataframe['created_at'], \n",
+    "        format = '%a %b %d %H:%M:%S +0000 %Y')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's recode the dates for the shooting data and the indictment data! These opperations are done in place, so we don't actually have to return anything"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "recoding shooting dataset\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('recoding shooting dataset')\n",
+    "recodeData(shooting_df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Number of Tweets over Time\n",
+    "In this section, we mostly want to explore broadly the data we have -- both the shooting and indictment-related tweets. First, we want to understand the volume of tweets that we have, and when there are spikes in the data. We will do this for both the shooting and the indictment tweets."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hashtags - Sophia\n",
+    "Now, let's explore the different hashtags used by users. First, let's create a dataframe that has one row per tweet-hashtag combination. So, a tweet using two hashtags would translate into a dataframe with two rows. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will create this dataframe by looping over the rows in the dataframe, and looping over the hashtags in each tweet. For each tweet, we will create a json object that represents the row that should be added to our new dataframe. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "creating dataframe\n"
+     ]
+    }
+   ],
+   "source": [
+    "hashtagRows = []\n",
+    "hashtagMap = {'MICHAELBROWN': 'MIKEBROWN'}\n",
+    "for i,tweet in shooting_df.iterrows():\n",
+    "    for hashtag in tweet['entities_hashtags_text']:\n",
+    "        \n",
+    "        mappedhashtag = hashtag.upper()\n",
+    "        if (mappedhashtag in hashtagMap):\n",
+    "            mappedhashtag = hashtagMap[mappedhashtag]\n",
+    "        #Do we want to map michael brown to mike brown and similar stuff?\n",
+    "        hashtagRows.append({\n",
+    "                'createdDatetime': tweet['createdDatetime'],\n",
+    "                'hashtag': mappedhashtag,\n",
+    "                'tweetId': tweet['id_str'],\n",
+    "                'x': tweet['coordinates_x'],\n",
+    "                'y': tweet['coordinates_y'],\n",
+    "                'createdDatetime_date': tweet['createdDatetime'].date(),\n",
+    "                'createdDatetime_hour': tweet['createdDatetime'].hour\n",
+    "            })\n",
+    "print \"creating dataframe\"\n",
+    "hashtagsDf = pd.DataFrame(hashtagRows)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>createdDatetime_date</th>\n",
+       "      <th>createdDatetime_hour</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-17 17:52:55</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064141332029440</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-17 17:53:02</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064171707170816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-17 17:53:04</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064180468682752</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-17 17:53:07</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>USNEWS</td>\n",
+       "      <td>501064194309906436</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064196642340864</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064196931330049</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>MIKEBROWN</td>\n",
+       "      <td>501064196931330049</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>TCOT</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>UNITEBLUE</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      createdDatetime createdDatetime_date  createdDatetime_hour    hashtag  \\\n",
+       "0 2014-08-17 17:52:55           2014-08-17                    17   FERGUSON   \n",
+       "1 2014-08-17 17:53:02           2014-08-17                    17   FERGUSON   \n",
+       "2 2014-08-17 17:53:04           2014-08-17                    17   FERGUSON   \n",
+       "3 2014-08-17 17:53:07           2014-08-17                    17     USNEWS   \n",
+       "4 2014-08-17 17:53:08           2014-08-17                    17   FERGUSON   \n",
+       "5 2014-08-17 17:53:08           2014-08-17                    17   FERGUSON   \n",
+       "6 2014-08-17 17:53:08           2014-08-17                    17  MIKEBROWN   \n",
+       "7 2014-08-17 17:53:08           2014-08-17                    17   FERGUSON   \n",
+       "8 2014-08-17 17:53:08           2014-08-17                    17       TCOT   \n",
+       "9 2014-08-17 17:53:08           2014-08-17                    17  UNITEBLUE   \n",
+       "\n",
+       "              tweetId   x   y  \n",
+       "0  501064141332029440 NaN NaN  \n",
+       "1  501064171707170816 NaN NaN  \n",
+       "2  501064180468682752 NaN NaN  \n",
+       "3  501064194309906436 NaN NaN  \n",
+       "4  501064196642340864 NaN NaN  \n",
+       "5  501064196931330049 NaN NaN  \n",
+       "6  501064196931330049 NaN NaN  \n",
+       "7  501064197632167936 NaN NaN  \n",
+       "8  501064197632167936 NaN NaN  \n",
+       "9  501064197632167936 NaN NaN  "
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hashtagsDf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that we have a dataframe, let's get the most popular tweets! We will do this by grouping the dataframe by hashtag and then aggregating by count. We'll sort by count, and then transform that information to a list that we can use later. Right now, we'll start by getting the top 10 hashtags and plotting those over time. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[u'FERGUSON', u'MIKEBROWN', u'JUSTICEFORMIKEBROWN', u'TCOT', u'UNITEBLUE', u'CRIMEBUTNOTIME', u'POLICEBRUTALITY', u'FERGUSONSHOOTING', u'DONTSHOOT', u'HANDSUPDONTSHOOT']\n"
+     ]
+    }
+   ],
+   "source": [
+    "numTopHashtags = 10\n",
+    "popularHashtagsList = (hashtagsDf\n",
+    "                   .groupby('hashtag')\n",
+    "                   .count()\n",
+    "                   .reset_index()\n",
+    "                   .sort_values(by='createdDatetime', ascending=False)['hashtag']\n",
+    "                   .tolist())[0:numTopHashtags]\n",
+    "\n",
+    "print(popularHashtagsList)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that we have the most popular hashtags, let's filter the hashtags dataframe for just those hashtags. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>createdDatetime_date</th>\n",
+       "      <th>createdDatetime_hour</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-17 17:52:55</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064141332029440</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-17 17:53:02</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064171707170816</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-17 17:53:04</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064180468682752</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064196642340864</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064196931330049</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>MIKEBROWN</td>\n",
+       "      <td>501064196931330049</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>TCOT</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>UNITEBLUE</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2014-08-17 17:53:08</td>\n",
+       "      <td>2014-08-17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>501064198009655296</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       createdDatetime createdDatetime_date  createdDatetime_hour    hashtag  \\\n",
+       "0  2014-08-17 17:52:55           2014-08-17                    17   FERGUSON   \n",
+       "1  2014-08-17 17:53:02           2014-08-17                    17   FERGUSON   \n",
+       "2  2014-08-17 17:53:04           2014-08-17                    17   FERGUSON   \n",
+       "4  2014-08-17 17:53:08           2014-08-17                    17   FERGUSON   \n",
+       "5  2014-08-17 17:53:08           2014-08-17                    17   FERGUSON   \n",
+       "6  2014-08-17 17:53:08           2014-08-17                    17  MIKEBROWN   \n",
+       "7  2014-08-17 17:53:08           2014-08-17                    17   FERGUSON   \n",
+       "8  2014-08-17 17:53:08           2014-08-17                    17       TCOT   \n",
+       "9  2014-08-17 17:53:08           2014-08-17                    17  UNITEBLUE   \n",
+       "12 2014-08-17 17:53:08           2014-08-17                    17   FERGUSON   \n",
+       "\n",
+       "               tweetId   x   y  \n",
+       "0   501064141332029440 NaN NaN  \n",
+       "1   501064171707170816 NaN NaN  \n",
+       "2   501064180468682752 NaN NaN  \n",
+       "4   501064196642340864 NaN NaN  \n",
+       "5   501064196931330049 NaN NaN  \n",
+       "6   501064196931330049 NaN NaN  \n",
+       "7   501064197632167936 NaN NaN  \n",
+       "8   501064197632167936 NaN NaN  \n",
+       "9   501064197632167936 NaN NaN  \n",
+       "12  501064198009655296 NaN NaN  "
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "popularHashtagsDf = hashtagsDf[hashtagsDf.hashtag.isin(popularHashtagsList)]\n",
+    "popularHashtagsDf.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's count the number of times each hashtag was used in a given minute. To do this, we will group the dataframe by datetime.minute and hashtag and then aggregate by count."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>createdDatetime</th>\n",
+       "      <th>hashtag</th>\n",
+       "      <th>createdDatetime_date</th>\n",
+       "      <th>createdDatetime_hour</th>\n",
+       "      <th>tweetId</th>\n",
+       "      <th>x</th>\n",
+       "      <th>y</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2014-08-17 17:00:00</td>\n",
+       "      <td>CRIMEBUTNOTIME</td>\n",
+       "      <td>78</td>\n",
+       "      <td>78</td>\n",
+       "      <td>78</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2014-08-17 17:00:00</td>\n",
+       "      <td>DONTSHOOT</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2014-08-17 17:00:00</td>\n",
+       "      <td>FERGUSON</td>\n",
+       "      <td>2537</td>\n",
+       "      <td>2537</td>\n",
+       "      <td>2537</td>\n",
+       "      <td>18</td>\n",
+       "      <td>18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2014-08-17 17:00:00</td>\n",
+       "      <td>FERGUSONSHOOTING</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>16</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2014-08-17 17:00:00</td>\n",
+       "      <td>HANDSUPDONTSHOOT</td>\n",
+       "      <td>53</td>\n",
+       "      <td>53</td>\n",
+       "      <td>53</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2014-08-17 17:00:00</td>\n",
+       "      <td>JUSTICEFORMIKEBROWN</td>\n",
+       "      <td>74</td>\n",
+       "      <td>74</td>\n",
+       "      <td>74</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2014-08-17 17:00:00</td>\n",
+       "      <td>MIKEBROWN</td>\n",
+       "      <td>434</td>\n",
+       "      <td>434</td>\n",
+       "      <td>434</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2014-08-17 17:00:00</td>\n",
+       "      <td>POLICEBRUTALITY</td>\n",
+       "      <td>19</td>\n",
+       "      <td>19</td>\n",
+       "      <td>19</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2014-08-17 17:00:00</td>\n",
+       "      <td>TCOT</td>\n",
+       "      <td>92</td>\n",
+       "      <td>92</td>\n",
+       "      <td>92</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2014-08-17 17:00:00</td>\n",
+       "      <td>UNITEBLUE</td>\n",
+       "      <td>15</td>\n",
+       "      <td>15</td>\n",
+       "      <td>15</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      createdDatetime              hashtag  createdDatetime_date  \\\n",
+       "0 2014-08-17 17:00:00       CRIMEBUTNOTIME                    78   \n",
+       "1 2014-08-17 17:00:00            DONTSHOOT                    10   \n",
+       "2 2014-08-17 17:00:00             FERGUSON                  2537   \n",
+       "3 2014-08-17 17:00:00     FERGUSONSHOOTING                    16   \n",
+       "4 2014-08-17 17:00:00     HANDSUPDONTSHOOT                    53   \n",
+       "5 2014-08-17 17:00:00  JUSTICEFORMIKEBROWN                    74   \n",
+       "6 2014-08-17 17:00:00            MIKEBROWN                   434   \n",
+       "7 2014-08-17 17:00:00      POLICEBRUTALITY                    19   \n",
+       "8 2014-08-17 17:00:00                 TCOT                    92   \n",
+       "9 2014-08-17 17:00:00            UNITEBLUE                    15   \n",
+       "\n",
+       "   createdDatetime_hour  tweetId   x   y  \n",
+       "0                    78       78   0   0  \n",
+       "1                    10       10   0   0  \n",
+       "2                  2537     2537  18  18  \n",
+       "3                    16       16   1   1  \n",
+       "4                    53       53   0   0  \n",
+       "5                    74       74   0   0  \n",
+       "6                   434      434   1   1  \n",
+       "7                    19       19   0   0  \n",
+       "8                    92       92   0   0  \n",
+       "9                    15       15   0   0  "
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hashtagTimeCounts = (popularHashtagsDf\n",
+    "                     .set_index('createdDatetime')\n",
+    "                     .groupby([pd.TimeGrouper('H'), 'hashtag'])\n",
+    "                     .count()\n",
+    "                     .reset_index())\n",
+    "hashtagTimeCounts.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that we've gotten the counts for a particular hashtag every minute, let's plot this over time as a line graph."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x10fa73610>"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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CVi/e8uW6ur3KnIz2JezSpQuVK1fm0KFDxMXFMXnyZG666SYiIyNJTEzE6XSy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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x10fdcdd10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "\n",
+    "for hashtag in popularHashtagsList:\n",
+    "    filteredHashtagTimeCounts = hashtagTimeCounts[hashtagTimeCounts.hashtag == hashtag]\n",
+    "    filteredHashtagTimeCounts.plot(kind = 'line', x = 'createdDatetime', y = 'tweetId', label = hashtag, ax = ax)\n",
+    "    \n",
+    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
+    "plt.xlabel('Time')\n",
+    "plt.ylabel('Number of Tweets over Time')\n",
+    "plt.title('Hashtag useage over Time')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we can see the number of times each hashtag was used in a tweet in this dataset. Unfortunately, it appears that the hashtag \"Ferguson\" was used much more than any of the other hashtags, so this plot is a little hard to read. To adjust for that, let's \"normalize\" each hashtag line on this graph. To do this, we will divide the number of times that hashtag was used in any given minute by the maxiumum times that hashtag was used in any minute. This will mean that we can see all the lines on the same set of axes. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/Sophia/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:7: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x10fdcd2d0>"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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hAQYDTJyYyupkZ2nJy/VWEh56iP3XZ+WF2M8F0YHxDHoplo87h9B4SrJovjdu\nwJkzkIP0C23baoYaz3afPbTW5BFRcVF0X9GdF0u9yJdtvwS01bj33tNCDxQK8NJiM128CCdPgnnb\ndEh0CCd9TtK6fOusTeTsDH/9BW+/DeYt2gNrDSQiLoJ1l1LGv1n71jdUKlOYxp+/TWjo07vl32Bp\nwHmwM35L/PJbFB0dnaeYrChOC4EjSqnzSqmTSqlTSqmTeS3Ys4aI4Hd9K3HhJmrWrZvlfr179+af\nf/4hOjoa+vbVvnSTJX8EqGxXHKcqqwi6+yXXH+zKZcmffRKiE/i44X3sHWD8+mIpKxctgkGDwNr6\nscdXCt59F75ZVQHc3SGPYrDEJcTRd01fShlLMfeluSiliI/XxP/kE6jruwUaNdKCTG3YAMUeXuuu\nm7toWqYphQoUyvqE9etrfls9e8L9+1gYLPim/Td8uvNT4k0P4zhZGCw4/OFyKHUMt/e+J+EpzrNb\nYkgJPaaTjo5OhmQ1cvhwtB11if5NffJSqGeRiIiLnDodQ/OqNTAYsp4i0MXFhbp167J582YtONCE\nCZrV6RE6l2yEV/FZnL/gTljUndwU/ZnGFG9iY9cbLPMuzu97C2EwJIuNEh8PixfDiJzHzBo4UMt5\nd2PAJE0Zu3cvx2MmxyQmhv49FBHhtx6/YVDae+z//g9sreN5P3CSFoPKw0PToh55D26+tjlz/6a0\ncHfXNLPevSE2lk6VOlHKWIqFJxemaGa0KcyRceu57vwdr3yy4bGvM6+xrWmLdSlrgnboMZ10dHTS\nJivf4AEislZErorI9cQjzyV7xjjnu479x+3o9vLL2e6btFwHMGAA3LoFnp6p2r1d/TX+LTiAbSd1\nZ/GsICJceuMqk4+X5MuZBipUeiSg3ObNWr7AF17I8VwFC8LIkTDLo6S2O+/LL3M8ZiIiwphNY7gb\nepfVfVZTwELLk3X4MKz+wYcN0R1QRw5rodBbtUqzf4r8dNll2jSwt4fRo1HAjPYz+Hzv50TERqRo\n5upYjn8Gr2WT5XAmzDn7eHM9AXQncR0dnQxJz/lJHjoFzgOWolmZuicemfXL7YP/uHPiX3sbSlH7\nQnLp4sVs971//74YjUYJT4wD9OuvIp06pdk2ODZWvt3bVtafcNedxTPh+qfXZVyZO9KqRYIkJKTR\noHt3kYULc22+u3e1gJjB1x6IODikCiT5uEzcOVHq/1JfQqJDkspCQ0UGuuyUSHsXkc8+E4mPT7f/\nOb9zUm6TBnZEAAAgAElEQVRWuZy9X0JCNA/4efNERKTfmn4ybc+0NJvO2rFcDB+Uk+XrfdOsz2+e\ntZhO6M7hOjrZJqPnJisWpyJouem6o4cjeCzi40MJ9voXQ5yiSrLs3FnFyckJNzc3Nm7cqBUMGaJl\nrT96NFXbIgUK0LnucgJDj3Poxvc5Ff2ZxWuWFyc9wlkWUZqFiw2PrlxpS2n79ml+ZblEqVLQpQss\n/NsR3nknxXb+x+W7g9/x58U/2TJwC0Zro1ZoMrG91RfMCx5IQY8lWqqUDMJfJFqbcpTCwWjUwht8\n8QXs2sX0ttOZc2QO9yPup2o6rl1/htQZwmubenL89NNnGU2M6XR/ZWrZdZ4+ypcvj42NDYGBgSnK\n69Wrh4WFBXfu3GHYsGFMmTIF0JLwGgwGTOY4ZABjxoyhRo0a+Pj4sGTJEiwtLTEajSnStfj6+ibN\nV6hQIYxGI8WKFaNbt27cvfsw8fqwYcOwtrbGaDTi6OhIp06duHz5cgrZvL29GTRoEI6OjhQuXDjl\n5zvw5ptv8vbbbyedx8fHY2dnxzvvvJOq7OjRo0nX1DUp1ojG4MGDmTZt2uPeWp10yFRxEpHBaRxZ\n3xamg4//VjadLEGH2nUe+8spxXKdlZXmp5KGrxNATaMzRSsv54HXdG4+2Pm4Yj+z+C715fb3d/ne\n4QWmfKaoVCmNRr/9Bn36gJ1drs797rswdy4kjPsANm7Udrc9JotOLWLu0blsG7QNJ1snrfDBA3zr\ndaHMxe0UOHMCOnTIdJwt17fQxbXLY8uRRKVK2ta9AQOoGKTtsvtib9rv0QWDPqOha1lafT8cH5+n\nzxG7xDB9ue6/glKKChUqsGLFiqSyc+fOERUVlWEf0FZcRo0axb59+9i3bx8uLtqO2qZNmxIaGkpo\naChhYWGEhoZSokSJpL4bN24kNDQUHx8fihcvzpgxY1KMP378eEJDQ/H29qZkyZKMSOYnGRQURPPm\nzbGxseHixYv4+/szbtw4BgwYwNq1awFo2bIl+/fvT+pz/PhxypYtm6Ls2LFjKKVo0KBBUtmRI0c4\nfPhwtu+hTvZIV3FSSn1g/vt9WseTE/G/z0XfdZw/nECHHGxpf+WVV9ixYwdhYWFawfDh2nbyU6fS\nbN+jVGOuOc3i3IV+RETefux5nzX8//Hn+sfXOTi4PhY2BkaPTqORyQQLF2pOSblM48bg4gLr9xaB\nDz/UMu0+BmsurGHSrklsG7yNMkXKaIWensTXqY/H1fqwaxe2lUtmOk54bDiH7x6mbYW2jyVHKtq2\n1YK19ujBpPrjWHFuBdcCr6VqZlAGdo39DftK12j0wZdERubO9LmFfQd7Yu7EEHExIvPGOvnO4MGD\nWbJkSdL5kiVLGDJkSIZ9EhISGDp0KCdPnmTv3r04OjpmeT4xh4SxsrKid+/eXEznB5C1tTV9+/bl\nzJkzSWXff/89hQsXZsGCBTg5OWFtbU2/fv2YOHEi77//PqApThcvXkyyou3fv59+/foRERGRVHbg\nwAGaNGmSIpjyxx9/zIQJE7J8HTqPR0YWp0QH8PPpHDpZQESID9rC3TMBtHn11ccex97enhYtWrB+\n/XqtwMYGPvooQyfjcTVe47jNQLaf6kpCQvq/vp4Xgg8Ec3nYZWx/rM2MX61ZtCjV5jKNPXs0S1PD\nhnkix7hxMHs2MHo0HDiQrvKbHtuub+OdTe+waeAmqhSrosX1+vZb5NVXmVTsZyInf0WjJpZZGmvP\nrT00LNmQwtaFH+NK0uGdd8DNDac33uO9F8cxcdfENJsVLFCQo+/9TVDF/9F2zCqSrZzkO4kxnXyX\n6Fan/wJubm6EhYVx+fJlTCYTHh4eDBo0KN32IsKAAQO4evUqu3fvpmjRoo81b2RkJB4eHjRJJ4VW\nREQEy5cvx9X1YRqjHTt20KtXr1Rt+/bty507d7h69SqlS5dOYWHat28fLVu2pGnTpqnKElFK8fbb\nb3PlyhV27dLD0uQlGSlODQBEZGFaxxOS7z9PePgZLt62xM7SigoVKuRorBTLdQCjRmm7686dS7O9\nhVKMrTeDKwkl2Hp2SNKvpOeR8LPhnO91nqrLqjNubmE+/VRLh5ImCxZoW/dz4vOTAa++qgWlPHnZ\nFj79FCZPznLfg14HGbR2EGv7rqVuiboQGAg9esCaNfw87CiHHF7m44+zLsvmq5tzZ5kuOYlpWQIC\nGLcznAN3DnDM+1iaTUsaXdg18m9OlHiH4ZPSbpNflBhSAr9lfnpMpyygPle5cuSERKvT9u3bqV69\nOiVLlszwM2/79u306dOHwoVT/2g4dOgQDg4OODg4YG9vT+VHPix69uyJg4MDRYsWZceOHXz44Ycp\n6mfOnImDgwNGo5GDBw+ybNmypDp/f/+kJcHkJJb5+/sD0KpVK/bt24eIcPToUdzc3GjevHlSmaen\nJ60e2SVbsGBBJk6cyKRJkzK5Wzo5Ij2vceBkenX5cfAf3dVx4upU6TC6lgxt1y7HY4WEhIjRaJSg\noKCHhd98I9KvX4b9TgX7yuLdleTItRk5luG/SOSNSPEs5Sl+K/3kxx9F3Nwy2GTm7y9SpIhIQECe\nyvT11yKvvSYi0dFa6pKDBzPtc8b3jBSfWVw2X92sFRw5IlK+vMi4cXLiUIw4OYncvp11GUwmk1SY\nXUHO+J55vIvIDD8/kbJl5ddfRknr31pnuGtvyZG/xOKjUjLzF6+8keUxOd74uPhv9s9vMXIEz/iu\nuvLly8vOnTvl9u3bUq5cOenXr5/8/vvvEh8fLwaDQW7fvi1Dhw6VyeZ0R7du3RKDwSD79+8Xo9Eo\nixYtSjHeb7/9Ji1atMhwvl27domI9gytXbtWHBwcxM/PT0QkxVxeXl5Ss2ZNWbNmTVJ/Nzc3mTp1\naqpxb968KUopuXLlioiILFq0SBo2bChnzpyRJk2aiIjIuXPnpEGDBnLmzBkpWLCgxMTEpLimhIQE\niY2NlYoVK8qGDRtk0KBB8vnnnz/WfX3eyei5ycjiZKGUKqyUMqZ15LlG94zg82ADXvuCaZsLu7OM\nRiNt27Zl3bpkKS3eegt27oRHdm0kp24RZwpVWo6P19fc8d+RYzn+S8T6xXK241nKTShH5IvFmTJF\niz+Z7iaz33/XsuA6OOSpXCNHwvr14BtkDVOmaOl0MuBa4DW6/NGFuV3m0rlSJ83DvGtX+O47Ir6c\nRf8hVsydq4WdyirXAq8RkxBDreK1cng16VC8OKxbx7BJf+Lrf4vN1zan2/S1xj15t8kYPj3bnU07\nnh6/Ij2m03+HsmXLUqFCBTZv3syrWXCLaNq0KRs2bGDcuHEpHMuzgpgtWUopXnnlFSwsLDhw4ECq\ndqVLl2b27NmMHTuWmJgYANq3b5/kBJ4cDw8PypYtm2TdatmyJadPn2bjxo20aNECgJo1a+Ll5cXG\njRtp1KgRVlZWqcYpUKAAn332GZOzYcnWyR4ZKU7VSO3XdC7ZX51MiIsLwBB5Ae8rD2jz0ku5Mmaq\n5brChWHsWC1EdAb0LdOY847fc/Z8fyKibuWKLE878SHxnO18FudBzpR8qxQjR2r+2NWrp9NB5OEy\nXR7j4AD9+sHPP6OFl7h7V1OA08A71JsOyzowtdVU+pbupIVIWLwYDh2CV1/l/fe1lHPu7tmTITFa\n+KM7PSMSEjgaGsqCe/cYe/Uq/S9cYF9w8ONdaL16WM6bz9frwhm/5QMSTOnnW/m258e0rVmbV5YN\n4uKlp8PhqXi/4gRuCSQuKC6/RdHJAosWLWLXrl0ULFgQeKjgPEpiecuWLfnzzz954403Uigz6fVL\ni7///pvg4GBq1KiRZn379u0pVaoUv/zyCwDvvfceISEhjBgxAj8/P2JiYlixYgVfffUV3377bVK/\nSpUq4ezszJw5c5IUJ4AXX3yROXPmpPBvelTmQYMGER0drWWc0Ml1MlKcLohIWREpk+xIPM/G79rn\nl/sBW9h2wxXHQoUoXbp0rozZtWtXDh48mLQODsCYMdrW9hs3Muz7cY3BHLQezM6Tz76zeEJ0Av/2\n+BdjMyPlppRjwQIIDtYUp3Q5ehSio9OMrp0XjB2rKU4xCZZaTKeJE1MkcAbwj/Snw7IOvNXwLUZa\nNNIc1p2c4OBBqFSJdetg+3bNAJVdNl/bQv2ybfnb358vbt2i97lzVDlyBEdPT964coX9ISGUs7Gh\nmdHIsEuXaH3qFLuCgrLvK9e3L91bv0GR694sO7k43WZKKdaP/IVy1QNoOnkiyd/i+UUB+wI4dHLg\nvoce0+lpJbniX6FCBerXr59mXXp92rdvz8qVKxk6dGhSLKXDhw+niuN04sSJpD7dunXDaDRSpEgR\nJk+ezNKlS6lWrVq6c3744YfMnDmTuLg4HBwcOHDgAFFRUdSoUQNHR0dmz57N77//Tu/eKUMktmzZ\nkoCAAJo1a5ZU1qJFCx48eJBKcUo+r8FgYNq0aQQFBeUsPptOmqj0PgSVUqdEpN4TliddlFKS7Q/s\nfGb3GXc+m3OT6v4l+CVxN1wu0LdvX9q3b8+oUaMeFk6ZAj4+8L//ZdjXLyaGhUe607CwkQ51Vz2T\nD5Up3sT53ucx2BiosbwGXncVDRrA7t2ZZE95/XVwddViZD0hOneG/v1hyGAT1K0L06dDt24AhMaE\n0m5pO9qXb8dXtyppeQp/+EHrgBajs359+OsvSGdTTxKh8fH8GxHB2fBwzkZEcCrEnyNb2+PS4i/q\n2rtQx86O2ra21Lazo0rBghR4ZLthvMnE8vv3mX77No4FCjClfHk62ttn/f1jMnFwcGv6VTzJ5cn3\nKWiVfjJh/0h/Kn/zIk4Xp/DvsiE5ya+cKwRsDuDW57docLhB5o2fQpRSiEiOHvT/4uevjk5OyOi5\nyUhxGiFP0e65/9qDK5LA9n1OjBthy5SpX9Evg62x2eXPP/9k/vz57Ey+tBMYqG0TO3UqU0eXo8G+\nnD/dktplRtCg0vhck+tpQES4/PplYu7GUGtDLVQBA126QPPmWnihdAkL0+7bxYtgDnT3JNiyRdtY\nd/IkqPV/awrwqVNEm2Lp8kcX6hSqxKz1MajTp2H1ajD/qjWZNKWrWbOUoaASRLgeFZWkICX+9YuN\npaatbZJyFO1/mLUnZnF4ROqchxmRIMKq+/f54vZt7CwsmFKuHC8XK5Y1BSosjFffL4VblbZ8/NG6\nDJue87tAw3mtaeW7li2/Ns+rDY5ZwhRv4nC5w9TZUQfb6rb5J8hjoitOOjrZ57EUp6eN/9qDGxp6\nhPVH3Xn7ZR+u3rmDs7Nzro0dFRWFi4sLly9fTjnuJ59oCsCPP2Y6xtI7xyhyowsNXlhOaceOuSZb\nfnP9k+sE7wmmzo46WNpZsnixtox15AgUKJBBxwULtOXOv/56YrKCpgDVqAG//AKtWgq4uRE/biy9\n1Cqq+MYx49dbKDc3mDcPCj200syaBcv/ieObVRGcj3qoJJ2PiMDJyipJQapta0sdOzsqFSyIRTLt\n470t7+FYyJGJLTN2Sk9XbhH+fPCAL27fxlIpppQrR3dHRwyZaDiXT+2guUdHLrdZi0Onnhm2XXd+\nC31/H8Y7BT2ZNaXiY8mZW1z/5DoIVPomrTDzTze64qSjk30yfG7S2273tB08xdth0+LslU+l34/t\npYazc56MP2DAAJlnTqiahJ+flkXW2ztLY0w5u0T+2VNMIiJzJ9lsfnPn2ztypPoRifXXkrPevSvi\n5CRy+nQWOr/4osg//+StgOkwf77IK69orxO2bpF7JQvLd6NqicnRUWTRIolLSJDz4eGywtdXPrl+\nXZrvPyOG1QfFds8+aXLihLx5+bLMv3tXDgQHS3BcXJbmrDq3qhz3Pp5j2RNMJvnr/n2pd+yY1Dp6\nVFb5+UlCJsmC3/i5q3zQs6DI9euZjv/l9h+kwLs1ZMGy4BzLmhPCL4SLp4unJMSllQ366YZnPByB\njk5ekNFzk2GuOqWUhVJqbC4rcs8F9wI24rUjnDZt2uTJ+Kl214G2/XvoUJg5M0tjTKw5iN1WQ9l1\nqisJCU9Zzots4rvEl7s/3KX21toUKFYAEXjzTS1aQ506mXT+919tV1unTk9E1kd57TUtn/D168Lb\nEZuITbCg5lVHhq1fT/1atTAeOEDPc+dY8+ABlgkGbv3owozYuoS2bM7B+vX5qUoV3ipVimZFilDE\nMvOI4TeDbhIUHUQ9l5y7MBqUoqeTEycaNOCrihX51suLWseOsdzPj4R0LBSfDfiVxfUUt/t11iyk\nGTCh3Wheqd+Kt3b1Y9+B+BzL+7jYVrfFuqw1QduD8k0GHR2dp4MMFScRSQByzznnOSEmxheibxJy\n+BZtH9klkVt06tSJc+fO4e3tnbLio49gyRLw88t0DCuDgffqfcmp+LLsPjs4+7ulnhL8N/hzffx1\nam+tjU0ZGwD++ANu3840PJLGggVa7r8sKB25RYzJxJnwcJb5+jLV9zqFu92nxvhbrLBqzzdvjKXh\n5cu0KFGCn6pU4UGzZlx58UXWvPACwT+UpzlOvN+/YKbLYumx5doWOlXqhEFlmuM7yyileLlYMQ7X\nr8/3rq786O1NjaNHWerrS/wjuVRcCrvwTvP3mdxGYNAgMsq1opTi94FzqFkrni6zP8hs42ieosd0\n0tHRgUwUJzMHlFKzlVJNlFK1E4+sTqCU6qyUuqSUuqKUSuWJbA6ouV4pdVop9a9Samh2LuBpJCBw\nM0dj63DbP4BWrVvnyRzW1tZ0796d1atXp6xwcYGBA+G777I0TikbG1q/sIjboec5ffPrPJA0bwne\nF8zl4Zeptb4WttU0x11fX/jgAy3UURrx4VISHa1pWcOH54l8IsK9mBi2BAQw484dBl64QK1jxyh6\n4AD9L1xgU2AgDpaW9KywmIJ/FeH8+RvMnzqVYnXqMGLjRl40GrE1R+vctEkLmvnTTznLBrPl+hY6\nu3bOpStMiVKKTg4OHKhXj5+qVGGRjw/Vjh5loY8PsckUpI+afcw2pzDOxN7RHOIzoIBFAXa/tZrC\ndbfS7N2fedyQUjmluHtxArfqMZ10dJ570lvDk4dr2/vTOPZl1s/c1wBcA8oBBYDTQLVH2nwKfGV+\n7QgEAJZpjJXHK5q5x75TPaXrzF5Sp0yZPJ1n8+bN4ubmlrrizh0RBweRBw+yPNYvN4/Iuj3FxPvB\n5lyUMG8JOx0mB5wOSMD2h+lRTCbNX+jTT7M4yB9/iHTokCvyRMbHy7GQEFl47568e+WKtDl1Sort\n3y+OBw5Iu1On5L2rV2XxvXtyIjRUohJzvkRHy4W+beWmo6V0a+0tP/xgHuzECREXF5GICBER8fUV\nKVFCZM+enMkYEx8jxq+M8iAi6++NnLI3KEjanz4t5Q4elJ+9vSU6QfMTmntkrnRa2EakXDmRlSsz\nHedqwFUpNMVZ6vXaLrGxeSx0OpxzPyd359/Nn8kfE3QfJx2dbJPRc5PXDt1uwOZk558A4x9p8wkw\nz/y6AnAlnbHy7AblJgkJsbJ9r1Fatmok740YkadzxcbGiqOjo9y6dSt15ahRIhMnZnksk8kkH59e\nIhv3FJOIiGu5KGXeEHk9UjxLeorfKr8U5StXitSooaWAyxJt2oh4eDy2HCdCQ+W1Cxek2pEjYrN3\nr9Q+elQGXbggM27fli0BAeITHZ1+jrYbNySwZiX5p5a1XLl+TDw9RSpVEklI9D/u1Uvkm2/EZBJ5\n6aVsKIMZsPPGTmn8v8Y5H+gxOBgcLF3OnJHSBw/KXC8vCYmJlEpzKsmObT+LODpqymIm7Li2W6wm\nOknvNy9JJj7oeYL/Zn853jjnTvVPEl1x0tHJPjlSnAAn4BfgH/N5DWBoZv3MbXsBvyY7HwT88Egb\nO2AXcA8IBbqkM1Ye36bcIShoj/y+u6rUc3KS9evX5/l8I0eOlBkz0kjee+OGSLFiIskTAmdCZHy8\njPX8UDZ5VpP4+PBclDJ3ifaJlkOVDsndn1L+8vfzE3F21nLfZomrV7Vtd1nWsh5yKDhYXj5zRkp6\nesq3d+7I2bAwiUnIxo6rdeskxqGoTOhuKye9NYXBZBJp2FAk6W1z/ryIk5P8OjNYGjYUMefzzBEf\nbftIpuyakvOBcsDRkBDpdvasuHh6ymt7fpS6P9eXBI+VWrJjX99M+8/zXCBWH7rK1BlPPvmuKd4k\nniU9Jfz80/t8PIquOOnoZJ+Mnpus+Dj9BuwFypjPrwIfZKFfVukEnBKRkkA94EellF1aDadOnZp0\n7NmzJxdFyD3uPfiHPdH1uRocnCokfl6Q5u46gAoVtAjUP/yQ5bEKWljwXr1pHImryL6zgxI/MJ8q\n4oLjONv5LCWGlKDUm6VS1I0ere1Qa9w4i4MtWgSDB5Od0NR7g4Npf/o07hcu8HKxYlx/8UU+KFOG\nWnZ2WBmy8DjFxcEHHxDzzpt07y90/mEz9UpqKSKUgnHjYM4cc9saNQh260zQlFn88UcW/LWywOZr\nm+lSuUvOB8oBjYxG1teqxcZatQhzaMG5yCgGFb9P+PDh0KsXmJOhpsc7TUcw1K0H/3etN6v+jH1C\nUmsoC4XzYOen2kl8z549KT4rnwfatGnDokWLWLJkSYq8bolUqFCBXbt2AeDt7U3v3r1xcnLC3t6e\n2rVrs3TpUg4cOJCUXsXOzg6DwZAi5crdu3eT5kkkLCyMcePGUa5cOYxGI5UrV+b9998nMDAQgPLl\ny1OoUKEU44wdq21UX7JkCZaWlmnWARw8eJB27dphNBqxt7enR48eXLx4Mal+7969WFhYJKV+qV69\nOr/99luK6zYYDJQoUQJTMv/C+Ph4ihcvjkWyTOfJr2vv3r2UKVMmqS4uLo5XX32VFi1aEB4ezuef\nf46VlVWKlDQOyZKiGwyGpOspXrw4AwcOJDQ0NKm+devWFCxYMKm+V69e+D2ymenChQv06NGDokWL\nUqRIEdq1a8ehQ4eS6jt37szMZLvH7927h8FgSLPs/v377N27F4PBwOjRo1PM06JFC5YuXUq2SU+j\nkoe/NI6Z/55KVnYms37ycKluS7LztJbq/gGaJTvfCTRMY6y8Uy1zke0Hq0uXSYOkkavrE5kvLi5O\nnJ2d5erVq6krr1zRlkBCQrI15vYH3vK/PdXlzLUvcknK3CE+Ml5OtjgpV0ZfSbX8tWaNSJUqIpGR\nWRwsNlbzITp/PtOmJpNJtgYESIuTJ6XSoUOy8N697FmXErlzR6RJEwlp10KqTnWUjVc2pmoSEyNS\nsqTI2bOaIaxL1esSZVdMxD/n1hWvEC9x+MZB4hPiczxWbrLwwiaxnVlanPbtkunTp0vIm29KZutw\n8Qnx0nx+V7Hu87ocO/Zk1+zCL4aLZ4n/TkwnngOLU+vWrWXhwoXy22+/SYsWLVLVly9fXnbu3Cki\nIm3atJH3339foqKiJCEhQU6fPi1btmxJ0f7WrVtiMBhSfc4kziOiuUo0bNhQOnbsKJcuXRIRkQcP\nHsj06dNl8+bNSfPu2rUrTZnTk1VE5ODBg2JnZydz586V8PBwCQoKkkmTJom9vb3cvHlTRET27Nkj\nZZL50W7atEksLS3lypUrSWVKKalWrZr8kyxG3fr166Vq1apiMBjSvK7k48bExMjLL78s7dq1k6io\nKBERmTp1qgwePDhNuUVEDAaD3LihxQYMCwuTzp07y3vvvZdirkWLFomISEhIiHTs2FEGDRqUVH/t\n2jWxt7eXyZMnS1BQkISHh8sPP/wgdnZ2cvjwYRERmT59unTt2jWpz4oVK6RGjRqpyqpWrZp0TXZ2\ndmI0GuX27dtJbZo3by5LlixJ8zoyem6yYnGKUEo5AAKglGqEtqSWFY4BrkqpckopK6Af8GjStttA\ne/PYzkAVIB83HT8+0dF3iI/1xfT3Kdq89NITmdPS0pJevXqxatWq1JWVK0PHjjB/frbGbO9YkvAy\ni7l5dw6+/ptySdKcYYo3caHfBaxLW+M6xzVFig9/f83atHgxmJOiZ86mTZpVLp2M5qD9qNjg74/b\nyZOMu3aNN0qW5FLjxgx3ccmadSk5mzdDo0YEdGhOjc7X+LzXPF6qnPo9YmWlxZ6aM0dLTWdToyLW\nA/vAN99kb7402HptKx0rdcTCYJF54yfI8OpdaFWyNq/LMS507Uqll15i2qpVBMelv3vNwmDBpuHL\nKdHgKO0mz8LL68nJa1vNFpvyNgRt02M6/Rc5duwYQ4YMwcbGBoPBQJ06deiUTgw3ycDqvmTJEu7e\nvcu6deuoWrUqAI6OjkyYMIHOnR/uWs1ojPQYP348Q4cOZfTo0dja2lK0aFG++OIL3Nzc0rUidunS\nBQcHB86ePZuifPDgwSxZsiTpfOnSpQwZMiRTGaKioujatSsiwsaNG7GxscmS7PJQ2cbOzo7u3btz\n4cKFVG0AjEYjPXv25PTp00l1U6dOpWnTpkybNo2iRYtia2vLmDFjGDx4MOPHaxvzW7Zsiafnw3RR\n+/fvZ9y4cRw/fjxFWfJVn6JFizJ06NBcscJm5dP/I2ADUFEptRdYAYzJyuCixYEaDWwDzgMrReSi\nUuoNpVRihtovgaZKqbPAduBjEQnM5nU8FQQEbOKEqQEB3j60fUKKE2SwXAdaIKNZsyAiIltjvluh\nMbuN33HqwmtERl7NBSkfHxHhysgrmGJMVPutGsqQci/+u+9Cv37QtGk2Bl2wAEaOTLPKJMKa+/ep\nd/w4k2/e5KMyZTjXqBEDnZ2xzK7CFB+vJckbORL/3+bTyGENk1t/hvsL7ul2eeMN8PCA5cu1nM1q\n8iRYuFBL4pwDNl/bTOdKeROGIKd83e5rFh79jh+rlONg1arcvHgR1wMHmHzzJgHpKFCFrQuz9431\nSJNvaTXyn8xiaeYqekyn/y5NmjTh7bffxsPDA68caNw7d+6kc+fOFMzyr7WsERUVxcGDB+mdRgzA\nvn37sn379lTlIsL69esJCAjA1dU1qVwpRc+ePdm3bx+hoaEEBwdz4MABevTokaEM0dHRdOnShUKF\nCvOv5SsAACAASURBVLFu3TqsHzPTdlBQEOvWraNJOlnIAwICWLt2LZUrV04q27FjB3369EnVtm/f\nvnh6ehITE0Pjxo2Jjo7mzJkzAOzbt48OHTrg6uqaoiy54qSUYuLEifz5559cvZqz77RMvwVE5BjQ\nBmgFvAvUEJHTGfdK0X+LiFQVkcoi8rW57BcR+dX82kdEOolIbfOx4vEuJf+5/WADJ8JqcTEsjGbN\nmj2xeZs3b46/vz+XLl1KXVmjBrRsqSVDywZKKb6sNYANliPYd7ob8fHhuSRt9rkx/gaRlyJ54c8X\nMFilfMuuX6/loZs+PRsDenuDpyc88nDGm0z84efHC8eOMcPLiy8qVOBUw4b0Ll788YJN+vhAhw5w\n5AiBB3bQ6sZkRjUYxRsN38iwm8HwMIlvsWJAqVJaRPhsXWRK4hLi2HlzJ51c8yc6embUcq7FS5Vf\nYobnDCpXqcLi1q05OnYsvv7+VDlyhE+uX+dBbGp/pnJFy7F12Fp8Gg/j5eFnSUh4MvI6uTsRuC2Q\nuEA9phOgOejlxvEEWL16NS1btuTLL7+kYsWK1K9fP4WlIqsEBATg4uKSabuePXvi4OCAvb09Dg4O\nLFy4MKnu0KFDKeqOHj1KYGAgJpMpzbFdXFzw9/dPOvf29sbBwYGCBQvSq1cvvv/+e+o8kirBxsaG\n7t27s3LlSjw8POjevXumilBYWBiHDx9myJAhFEgjyaeHhwcODg5JR7t27VLU169fH3t7e4oXL46X\nlxejRo1KUT927Fjs7e1xcnIiICCAH5L54vr7+6d77SaTicDAQKysrHjxxRfZt28fQUFBhIaGUr58\neZo3b55UduHCBVq1apVijOLFi/Pmm28yJZPYcZnx/+ydd3hUVRPG35sAQkJLg9ASakABqdLR0ItY\n4AMiLYiCgtJUlC5VpYOKICDSO6ggvYc0AoQAIQmkhxDSN73tZvf9/rhhSdmabAq4v+e5D+y5c86Z\nu7s3O3fOnBmthpMgCHchGkwpJO+RLNtozJcEuTwbWSk3ID8Th/YtW6J6dZXx7aWCiYkJRo0apd7r\ntGgRsG4dkJWl17jVK1XCV+2+h7usBdwfjiuXYPEna58g8Uwi2p5pC1PzgktMSUnistbOnQXq32pn\n1y5g9GjAXEyYKVMo8Gd0NF6/fRu/P3uGTc2bw6tjR7xnbV1gSVAvrl4FOnUCHB2RdvIYBl9yxrAW\nwzCv1zyN3UjRETZyJHDxIqC0FebNAw4dAsLDi6XOzac30aR2E9hWty1W/7JgueNy/O79O6JSowBH\nRzSdNg07Pv4Yd1u2RKpcjpa3bmFOcDBiCgWPd2/UDdtG/Izbzd/H1DnaM+Ybgsq1K8NqiBXiDseV\nyXwVHnGLdsmPElKpUiXIVHgoZTKZ0gCoVasWfvzxR/j6+iI2Nhbt2rXD8OHD9Z7LysoK0Tp4gU+e\nPAmJRIKkpCRIJBJ8+umnynPdu3cvcK5Lly6wsLCAiYmJyrGjo6NhbW2tfN2gQQNIJBKkpaVh5syZ\nygD45zz/mz1hwgTs3bsX+/btg7Ozs1adbWxscPjwYTg7O+PixYtFzjs5OUEikSiPK1euFDjv4+OD\npKQkZGdnY+rUqejVqxek+R58fvnlFyQlJcHX1xdJSUl4+vSp8py1tbXaazcxMYGFhQUAcbnuxo0b\ncHV1VToqevXqBRcXF7i6usLOzq5AkPtz5s6diwsXLhRZ0tQHXdYdRkFMXnlSEARPQRBmC4JQv9gz\nvqKkpNxAtNAUlS55oM+wYWU+v5OTEw4fPqzauGnXDnjrLdHC0JMW5ubo9sY2BKUEwy90hQE01Z3o\nXdGI+i1KrD9nWfSp56uvgBEjgEIPFZpRKMT3YcoUZMvl2BoVhRZeXjgYG4s/WrbEjfbtMdDSsvgG\nk0IBrFghZm/fuxfZC+fig2Mj0MG2A1b1156ZfedOIDQU2L4daNUKUCaGt7EBvvgCWL68WGqdDy69\nbOGGolGtRpjcYTKWXl8qNkybBvTuDftPP8WW5s3xoHNnSEm8cfs2ZgUFISqfAeXcfixmvO2MA7nD\nsWlzdpnoa1yuq3jY2dkhIiKiQFtmZibi4uJgb29fRN7S0hJz5szBs2fPkJSkX8xa//79ceHCBWRp\neSDV94HTzMwM3bt3L1oVAsDRo0fRv3//Iu2VK1fGqlWr8ODBA5w6VTiMWNw9Fh0djbi4OJ1XQz78\n8EPs2LEDo0aN0nsX+/NrNjU1xeTJkxEWFoaHDx8WkWvdujUWLlyIL774QtnWv39/ldd+5MgRdO/e\nXRlr9dxwunHjhnInZc+ePeHu7l5kmS4/lpaWmD17NhYvXlz8v/PqosZVHQBeB7AXQK4+/QxxoILv\n6gh4PJOTrn7KtywslLs3yhKFQkE7Ozvev39ftcDt22TDhsXKWUSSPwV58uR1G8bE/1sCLXUn/p94\nutu6M+NRhsrzp0+TTZqQaWl6DnzpEuXt23NjRATru7tz6P379EhOLrnCJBkXRw4cSL79NhkVRZlc\nxg8OfUCnY0467WR7/FjcBPl8o9+pU2JeJ+XGnqQkUSBvB48+dNzWkTfCb+jdr6yRZEpos8aGfnF5\nb0JODtm7N7lggVLmWXY2vw4KooWrK794/JgRebt95Ao5h+4axarjxvLsWd132hVngySZL6fTw4qd\n0wn/oV11OTk5bNq0KVetWsXs7Gymp6dzxowZ7NGjh1J27ty5fPjwIXNzc5mamsovvviCDg4OBcYL\nDw+nIAiUF/py5N99lpOTwy5dunDIkCF89OgRFQoFExIS+OOPPxbYVafu90DTrjo3Nzflrrq0tDRK\nJBIuXLiQFhYWDAkJIVl0Vx1Jbt68mR07dlS+FgRBKe/v709/f3+S4s41QRBUXlfhcffs2cOaNWvS\n3d2dpPZddfnnlMvl/PXXX2lubs6kvJyC+ecixd2JDRo0UOY9DAoKooWFBRctWkSJRMK0tDTlrjpP\nT09lv4yMDFapUoW2trb09fVVtrdt25Z169blH3/8oWwrfE2pqam0tramtbV1qe2qgyAIDQVB+Bpi\nTqfWAHQpnfqfIjrhDBKf2SMgM1NtIFxpIggCRo8erX65rnNnoE0boFCeD135rllXnKuxDj7+H5d6\nsHiySzIeT3mMNv+2gVnLomtwKSnA1KlifLc+K6JpubkI+OUXLOzTBzdSU/Fv27Y48+ab6F6rVsmV\ndnMDOnYUl+euXIGini0+PfUppHIp9g7fq3Unm1QKjB0LLFv2YqPfu++Ky5HK9CW1awNffw0sWaKX\najHpMQiRhKBbw27FuLCyxaKaBeb2nIv5V+aLDVWqACdOiJHyed/teq+9hvXNm+NRly6oYWqK9nfu\n4LPHjxGRnYNj43ajcadAjPzlB/j6ap9v3Tqgd2+NdYbVIpgKsHW2Rcweo9epIiAIAqpUqYIzZ87g\n2rVraNiwIZo3b46YmJgCu44zMzMxfPhwWFhYoHnz5oiMjFTppVHljcjfVqVKFVy+fBmtWrXCgAED\nUKtWLXTr1g2JiYno2rWrUu69995T5jyqWbMm/ve//2m9lp49e+LChQs4ceIE6tWrhyZNmuD+/ftw\nd3dH06ZN1fb75JNPEBkZiTNnzhTR9/XXX8frr7+u8lo0eV6cnZ2xfv16DBs2TBkLduTIkQJ5nGrW\nrKmMvRIEAe3atUPNmjVhaWmJffv24Z9//kHt2rVVzlW5cmXMnDkTK1aIKxrNmzeHm5sb7t27h8aN\nG6N+/fr4+++/cfHiRXTr9uJvmJmZGTp16gSZTIY2bdoo23v37o34+HiNeRRr1KiB7777TplvS2/U\nWVR88aThAeABgMUAWmiTL60DFfiJJyMjkOdc6nD8Bx/QsXPnctPj9u3bbNasmfoSHx4eZOPGLG6h\nr2SZjJ+6zeUFdwfKZKkl0FQ9qT6pdLNxo+SyRK3Mp5+Sn3+u+5hJUimXh4XR4fRppteowYdPnhhA\n03ysX0/WqUOeEfMyKRQKzjw7kz139mSGVLXHrDDz55Pvvls0fdHPP5OjRuVrSE8Xi9bdu6ezenvu\n7eGIIyN0li9vsmRZtN9oT9cI1xeN9+6pLcsSn5PDhSEhtHJ15ccBAXSLC6fVyka0fucoo6PVz+Pu\nLn5sb75J7ttXPF1fhpxO+A94nDp27MiTJ0+WtxpGXiE03Te63DCttcmUxVGRb9zIyE1ceX0Yx9er\nx+XLlpWbHgqFgk2bNuWdOxpqafXrR+YlHysOfunpXODyPm/cHUaFwrA/FpnBefXnjsWqlblwQazM\noUtOz/w/qBP9/Rm7ahWpwcVcLH76iXz9dTJfUrUl15aw/e/tmZSlW7mb69fFXJyxKi47NVWs15xv\neHLTJvK993RW8aPjH3GH9w6d5SsCe+/tZbc/uhV8CDh+XGNZFolUyqVhYbRydeVQbzdWXf0m3xhw\n+3md5AIkJIhDnTpFurmRjRpRpZwueHfzZsLpsi//oiuvuuH08OFDmpmZ8YmhH4iM/KcpqeFUA8Aa\nADfzjtUAamjrZ+ijIt+4N+/259DLS9jJwoKurq7aO5Qi8+fP57fffqte4Pp1snlzUiYr9hzHYyK5\n/XobPgxeUuwxCpP9LJueTT0ZtS1KrUxqKmlvTxZK8luE6OxsfpMXA/PZo0cMycwUXTlvvEG6uBhM\nZ27dKgZaPX1RM2+T5ya2+KUFY9K011wjSYlE/AE/e1a9zFdfkd99l68hK0v8pc+33q+OXHkurVZb\nMTIlUid9KgpyhZzttrbjCf8TBU98/z3Zo4fGWL1kmYw/hIez5vUrND38I3tNDS4Qx6RQiHZnvmTG\nHDmSXLmyeLpG/R7FhyMfFq9zGfAqG05z585lw4YNuXnz5vJWxcgrRkkNp2MAfoCY0dsBwAoAx7X1\nM/RRUW/c3Nx0XrluTqefV7H6a68xxxCVWEvA/fv3aW9vr365jhSDbffvL9E83wd68uT1OoyNK7l7\nXJok5a03bzF8ZbhGualTyU8+UX/+SVYWZwQG0sLVlTMCA/kkL2iYpLhM2aKF1lIeOnPwoFgbJThY\n2bTbZzftNtoxIjlCQ8cXKBTk6NHkjBma5UJCxHrN6fljkLdvJ/v21TrHzcibbLOljU76VDTOB52n\nw68OlObmW1qWy8nhw8UvgpbPMlUm48BruymcO8nmh+/RJ1VcXt64kXzrrYJFk4ODxfdY09KeOqRJ\nUt6odYPShOItgZc2r7LhZMRIaVFSw+meLm2lfVTUGzc+/hT3uXXlzB49OFDNDomyRKFQsFWrVgV2\nHxTh4kVxeam424lI5ioU/PjOXp53sWRGhv67vJTjZOTybq+7DJxVtP5cfq5cETcFJqlY/QrNzORn\njx7RwtWVc4KDGa3KGzFpErl6dbH1LMDp02JwzIMHyqa/A/6m7TpbBsQH6DzMnj1k69a61df78ENy\ny5Z8DVIp2ayZ+MZoYMm1JZxzYY7OOlUkFAoF++3px623txY8kZZGtm0rBoDpMMaIw5+wyprlrHXJ\nnb0PBtHCWs68UloF+OYbcsqU4unqN8aPTzc/1S5YDhgNJyNG9KekhtNNAN3yve4G4Ka2foY+KuqN\nG/DoMzpfm8bJNjb86aefylsdkuSSJUs4e/Zs9QIKBdm1K3n0aInmSZBK6ew6n5fcW1Am06+QMEnK\npXI+GPaAfuP8qJCrN5rS0sQVsXx1KkmSjzIyONHfn5aurlwQEsJ4dd6+lBSyVi21sTF64eJC2tgU\nWCa7HHKZNmts6P2saOCyOoKDxVhnddkjCnP9OtmqVSFbd/9+sls3jZ6Xrju68nLIZZ31qmjcibrD\neuvqMS2nUN6J0FCybl3y0iWtY2TLstlpcy9WfXcFa9aT0fKHRxyiIg1FUlIRe1hnEi8k8k5nDbGF\n5YjRcDJiRH9Kajh1hFhnLhhACABfAO219TP0URFvXIVCwWtuDTnw7Fa2tbSkl5dXeatEUszX0aBB\ngyI5SApw+rS4nagEXieS9ElN5TyXD+nmM1SvYHGFXEF/Z3/eH3KfcqnmftOnk87OL177pqXxIz8/\nWru5cVlYGCXadglu20aOMMCusjt3RKPp8gtD5H7MfdqssaFLuO6xUzKZaO9s3Kj71AoF2b49mZce\nRiQ3V3RZ/as6t1Z8Rjxr/lST2bLi5e6qKIw5PobLrqvYdHHtmmjpBAVpHSM2LY5V25xl5XoBfBAg\n59anT2nn4cH+9+7xTuqLHaK//EIOGKD/iq4iV0H3Bu5M89U3sVjpYzScjBjRnxIZTnxx41gCsNRV\n3tBHRbxx09J8efZGQ05ftJC1zMwoK0HAtaFp27Ytb9zQkPBQoSA7diT/+afEc+2PfsJt19vRP3ix\nTvIKhYJB3wTRu7s3c9M1J4Z0cRFDiRITSe/UVA739WVdNzeuiohgqq7v91tvaY6+1oWAADENwF9/\nKZui06Jpt9GOh30P6zXUkiVinkx9bdZdu8hBgwo1/vUX2a6dysEOPjjI9w7qvvuuohIqCaXVaivG\npqvYdrhli7jsrGWb5W+/ka3aZLL64oas382V8fFkjlzO36OiWNfNjYl5xrdUSjo4FO/rEjI/hMFz\ngrULljFGw8mIEf0xiOFU3kdFvHEjIlbzB7eR/N7Bge8OHFje6hRg5cqV/PLLLzUL/fUX2amTQQKm\nvwtw50mXuoyN+1urbMSqCHq19qI0UbOnKCND3AC46kA6h96/z/ru7tz45AkzcrVn4VZy7564A02f\nPoUJDxfH2L1b2ZQpzWSXHV1Ue0I04O4urjA9e6a/GllZYt+85L8iCoWYXvzIkSLyzn87c8utLUXa\nX0ZmnZvF6Wemqz45dSo5bJjaz9jHR1wWDQwkzwWdo/kSW3buH6rcmPfF48ec+vixUv7kSXEDpr7P\nQRmPMipkTiej4WTEiP4YDadS4pb32+xz7Sd+VqcO169fX97qFCAoKIh169ZlriaDQS4n27QpuTeG\npFQu59hbe3nBxYrp6f5q5Z798YyejT2Z/VTz8pFCoeDIaVmsO1hCOw8Pbnn6lFnFMX6mTxddPMUl\nJkbcjbdpk7JJrpBz9LHRHHtirObdi4VISRFjtUri5FuyRLQTCnDhAtmyZYFferlCzjpr6zBEElL8\nySoQ8RnxtFptxaBEFctyOTlimZv584ucSk0VP76DB1+0bfL8mTXnteboCSlUKMQEqfXc3emV57VS\nKMg+fcjff9dfT+/uFS+nk9FwMmJEf4yGUykgkyXzikt1fnhsP1tZWfHu3bvlrVIROnbsqL1u3uHD\nZPfuBvE6xeTkcKzrAl52b0aZrGj9t7i/4sT6c4/VZxpUKBS8kJjIN3c9pqlVDjf5RjOnuHFYmZli\n9sjw8OL1l0jEZbClSws0L766mN3/6M4sWZaajqqZMEG/jOeqiI4ma9cWly6VKBSi4bBrl7LJ+5k3\nHX51KNL/ZeaHGz9w9LHRqk/GxYlZ8fNZSAoFOWYMOXlyQVGFQsHJf09lrS+GcMky0djcFx3Njrdv\nMzfvPrh7V1yZ1SXRan6itkXR93++2gXLkFfZcKpevTpr1KjBGjVq0MTEhNWqVVO2Hcz7Ljx+/Jij\nRo2itbU1a9euzXbt2nHDhg3Kh56cnBzOmzePdnZ2NDMzo4ODA9euXauco3Xr1so5TE1NWbVqVeUc\nFWVDkBHDU9Lg8BHPE14CmAfgqDE4nIyNPcp97r25csoUWtSooTkQu5xYvXo1P/vsM81Cubmit+Ky\nYXZeeaWkcK7LCHr4DCkQLC65JqGbjRtT76gu1aJQKHgqPp5d7txhS5dbrNdcxsNHSvie7tunIihI\nR9LTRYNy1qwCRuX++/vZZFMT1fE2Gjh4UHyb0w1QD9bZWUVmBVdX0XDI21m40mUlZ52bVfLJKhAZ\n0gw2WN+At57eUi1w/764JpeXOX/HDtGhqiojuDRXyt47+rHGqFk8dEj8/r1z9y5/jXyRKHTiRJVO\nLI1Ik6S8UbNi5XR6lQ2n/DRp0oRXr14t0BYcHEwLCwvOmTOHMXm7agMDAzl+/Him5FnF7733Hrt2\n7Up/f3/K5XJ6eXmxRYsWnDlzZpE5HB0d+WcJKi8YeXkoqeH0IO/fHgBuAPjAmI6A9Pf/mBNdZnN9\n3boc/v775a2OSsLCwmhtbU2ptl1ne/eKHgsDseNpOLe7dOCj4IUkydS7efXnrhatPydXKHgsNpbt\nbt1iu1u3eCw2lt9+q+DIkQZQ5J13yGPH9O+XnS1Gb3/8cYGga7cIN9qsseHDWP2yRIeHi5vxNFXC\n0QdvbzHkqsjHOniwGAVNstefvXgu6FzRzi852+9sp+NuR/VLpCdOkI0a0fdaPK2tC8WDFUKSKaH9\nWgdWf2cbo6PFckLWbm7KPGBPnxbPYek3xo+Rv1acTO3/FcOpcePGRTzs48eP57Bhw9T2uXz5MqtV\nq8aoqIIVC7y8vGhqasqQkIJL3Y6Ojty5c6fhlDZSYdF035hAO/K8f4cB2EbyJIDXdOj3ykIqEJd4\nFo9yO8Hf1BR9+vcvb5VU0rhxYzRr1gxXrlzRLDhmDBAVBdy4YZB5Jzewh6/1ZgRG7cSzwCN4+P5D\nOGx1gEUfC6VMrkKBA7GxaHP7NtZERmJFkybw6dwZduF1sHevgN9+K6ESgYFAQADw/vv69ZPLgfHj\nAXNzYMcOwES8RUKTQjHy2EjsHb4Xreu01mu4CROAb74BOnXSTxV1dOwING4M/P13oRMrVwI//IBk\nyTPci7mHd+zfMcyEFYhJHSYhJj0G54LPqRYYMQIZE6Zi9NA0rPtJhnzF4ItgUc0CFyf9C7njAnw2\nLxhvmJvjU1tbzAkJAQA0aABMnw4sWKCfjraTbBGzO0a/TkZKhcuXL2PkyJEaz3ft2hX169cv0N6l\nSxc0bNhQ+99OI/9JKukgEy0Iwm8ABgPoLAhCFUAng+uVJT3dB5lCDXQKy8H57Gx81bdveaukFicn\nJxw5cgSDBw9WL1SpkvjrsGIFcOmSQeZd26obJnitgXngVDSYcQQ2/7MBAEgVCuyPjcVPT57AtkoV\nbGreHAMsLCAIAnJygEmTgE2bgDp1SqjAn38Czs5AlSq69yGBzz8HkpOB06fF9wVASnYK3jv0Hhb1\nXoTBzTW8jypYvRowNQXmzNGrm1ZmzwbWrQNGj87X2KkT0K0bnvw0D73a90K1ytUMO2kFoJJJJazq\ntwpzL8/FoGaDYGpiWkRmetR8vGXjgokeK4BPdwKCoHY8BysHfN9nAZYenoyLl65icd/GeOPWLVxL\nSkIfCwt8+y3QsiVw6xbQpYtuOlr0tYAsVoZ033RUb1u9uJf6UiFcv26QcejoaJBxnpOYmIh69eqp\nPZ+QkKD2fL169ZCQkGBQfYy8IqhzRfGFi7Y6gNEAWuW9rg9giLZ+hj5QgVzFYWHL+aPHeO54913W\nsbTUa2dVWRMZGUkLCwtmayiKSlJc97G316lwrK74fBnAXV/M5xX3JoxNuMJtEQ9o7+HBfj4+vCaR\nFHnfFiwQS4uU+O2USsV9+wG6lz+hQkF+/bWYmTLtRRJDmVzGgfsGqt8KrwEvL3GJrjSKtufmiiFN\nRXKuPnzIlFpVueXyKsNPWkFQKBTsubMnd/nsKnJuzx4xw3padJqY4DXfbkh15Mpz2XJtV9oM3cqs\nLPLvuDi28vJSbkrYuZPs2VO/72XIghAGfaM9MWdZgP/wUp2trS1350sjUph58+bR0dFR5Tl7e3tu\n3769QJtxqe6/g6b7RhfP0WaSR0k+yrt7ngFwMrgF9xIRn3gap3M6INfdHY79+kHQ8ERb3jRs2BCt\nW7fGxYsXNQtWrgzMmyd6nQxAzP4Y5FxIQdPvvsb+3KH45+Es2IX1xG75e1jLWagXNx9RUb9AIrmE\n7OynuHOH+OMPYOtWjQ4C3Th9GnBwAFq10r3PDz8AFy8CZ84A1UUvAUnMOjcLJoIJNg7eqJcK6enA\nuHHAb78BjRrp1VUnTE2BGTOAn38u2M433sCl5gJGXYoy/KQVBEEQsGbAGnx/7XtkybKU7Y8eiUui\nR44A1W2rAydPAqtWafWimpqY4oTzTqR0XIwFqyPxgbU1mlWtig2RkQCAiRPFz/PECd11tJ1oi9j9\nsVDIFMW6RiOGoX///jih4YPr378/vLy8EBVV8H7x8vLC06dP0bcCryYYKUfUWVR88aRxt9BrEwB+\n2voZ+kAFeeLJyYnjVZca7HfuJJ3t7fl7cZK9lDG//vorx40bp10wO1uspFvCKOZUn1S6Wbsx7YHo\nuTmXkMA7qalUKBTMzn5GieQyIyN/5ePH0+jj48hr1xqyaVNfLlu2hAEBHzMiYjXj4/9lZmYwFYpi\n5G4aOlR0PejKr7+KBXMLZaX85eYvbP1bayZnFU2toI3Jk8XY8tIkKYm0sBCDmJ/zIOYB31nUkAor\nq0I5C149hh8eztVu4vbCzEyx7u+2bYWErl8Xy7IEBmodb86pFaz88RA+fqxgaGYmrVxdGZ4lppy4\nfJls2pTU5rjNj3cPb8b/G697h1IC/2GPU0hICK2srPjdd98pd9UFBQUV2FU3bNgwdu3alX5+fpTL\n5fT09GSLFi04Y8aMInMYPU7/HTTdN5pulLkAkgDkApDk/T8p7/9r1fUrraOi3LjR0fu437M/f1q9\nmg0tLPg4X8bhikp0dDRr1arFzMxM7cI//yyulxUTaaKUnk08GXNI94K6S5aQQ4fmMCnJjVFR2xkU\n9BXv3RtEDw87urhU461b7ejnN4ZhYcsZF3ec6el+lMvVFPR98kS0JlTtQVfFvn2isRgWVqD5bOBZ\n1ltXj6GSUJ2v4zknToh2WKrqzAsGZfp0cuHCF6/XuK3hF6e/ID/7jJw7t/QVKEcexT+i9RprJmYm\n8vPPyY8+UrOctnWrWJYlWbMBLM2Vsv7ydnxj7B4qFOTK8HC+n6/i77Bh5Lp1uusXtb1i5HT6rxhO\nTZo0UZm3LjAwkKNGjaKVlRVr167N9u3b8+effy6Sx6lRo0Y0MzNjixYtuGbNGpVz9OnTx2g4DeAk\nQQAAIABJREFU/UcoruEkQAweXwvA9PmhTr60j4py4/r5jeEkt3k82a4dG9StW6Hjm/LTt29fnjhx\nQrtgZqaY+e/+fb3nUOQqeG/QPQZ9rXtsx717YhxQfq9JfmSyNKak3GZ09B6GhMzjgwfv8+bNFnRx\nqUovr1b09R3OkJCFjInZz9TUu5QvWUROm6bb5CdPirFQfn4Fmn1jfWmzxobuT9x1vo7nPH0qOjgM\nGCqmkcBA8f17bhP32d2Hpx6dIiMjxb300dFlo0g58fm/n/PdX75hs2ZaklVOm0a++67W0jteT7xZ\naV4dbtkbzWy5nA43b/JkvOg1CggQ00TF6+hEkiXLeKNW+ed0+q8YTkaMGJJiGU58ccMIAD4CsCDv\ndUMAnbT1M/RREW5chSKXLq6WbHXtGH+3suL48ePLWyWd2bZtG0ePVpN1uTBr15K6yuYjZGEIfRx9\ndK7VJZWSHTqIwbf6kpubxbS0B4yNPcLQ0CV8+HA0b3m2ZlZd8P7u+rx/fyiDg+fw2bOdTE72LJrJ\n/OpV0eK4VTCZYkxaDO032vPAgwN66ySXk/36kcuX6389JeHdd8Vkj6nZqaz+Y3Wm5eQFt8+eLbqk\nXmHcHzyjMM+Sp13DNQtKpaSjIzlvntYxJ+6dz6rO/2NSEnkpMZH2Hh7K+ohffkmqWMFRi99YP0b+\nUr45nYyGkxEj+lNSw2kzgG0AAvJeWwK4ra2foY+KcOMmJ7vxnPsbdD5xgh81bfpSuWzj4+NZs2ZN\npuuSujotTXSbaMoeWIi4v+Po0ciDObFqltBUsHKlmNjbYE67Cxeo6NiBGRmPGR//D8PDf6S//wTe\nvt2JLi7mdHevTx+ffgx0HcWnY80pubaROTmxSq9hpjST3f7oxu+vfl+s6detE3df6VsctqRcuiRm\nyP474B/229PvxYnY2JKVnKngZGeTHTuSg1cv5oS/JmjvEB8vFgs8oNkozpJlsfaiVhz0lZg89SM/\nPy7IS4QYF0daWZGPHummY+LFRN7ueFs34VLCaDgZMaI/JTWc7ub965Ov7b62foY+KsKNGxKygKtv\nfsr933zDurVqMaxQXExFZ9CgQTx8+LBuwj/8QOroUct4lEE3GzemeOle2MvXV1z2iIjQuYt2Ro0i\nt2xReUqhkDMrK5wJd3/nk0nV+ejCQHp796CrqwVdXS3p7d2LW8415Q+nOzAh4Ryzsp7otQzr4yM6\nsMrjK6FQkK1bk8N+n8q17msLnlywgPzkk7JXqgyYMYMcMYJMyUpl3bV1eS/6nvZOz8uy3NZszJzz\nc6fJt7a86JrAqOxsWrm6MiDvoWPNGlLXYgGKXAU9Gnow7X6aduFSwmg4GTGiPyU1nLzydtI9N6Cs\n8htRZXVUhBv31q327Oqyma5167KxnV15q6M3f/75J4cPH66bcEqK+AMTpDleSZYqo9frXozaEaVR\nrkAfGdm5s4odUCUhLo6sVUtzAHBoqBgIvn+/skmhUDAnJ4Ybrzlz9tHG9A/4nD4+fenubssbN6rz\nzp236O/vzIiIVYyPP8mMjKAiO/0yMsTY43zDljnbtytYbX7jouVgJBLRRfISbGLQh7/+EvNYJSWJ\nr3/1+pWD9ulYl/Cvv8TvQaFdlIUZuHEmLT6dQJmM3BQZyb4+PlQoFMzKEue+dk236UIWhugV92do\njIaTESP6U1LDyRnA3wAiASwDEADgI239DH2U942bnf2U125YsMu1y9zcsCE/eQmf4iUSCWvWrKnc\nhquVJUvISZPUnlYoFPQd4ctHU3Rct8hj1SoxFsigcfXr1olVWdXx7Jm4nzyvllt+Djw4QPuN9oxJ\nK7gTUCqVMDnZnc+e/cGgoK95//4QenjY08WlKm/dasuHD50YGrqUy5ef4LhxZbw+VwifyACafNOQ\njx+reFNXrhS3nL0ihIWJ3r2bN1+05eTmsNnPzXg5RMdi1cuWiclONeQXSMtOZ9W5TThlzRnK5HK2\nv32bB/O2tB85Isbn6VLbOyMwg2513SiXlk8hcKPhZMSI/pTIcBL7ozWAWQBmA2ijSx9DH+V94z57\n9gcPeg3jwt27+T8HB+7bt69c9Skuw4YN0113iUSMkVGz/hSxKoJ3utyhPFv3H4SAANEBYtAlLYVC\nTBft6qr6fGKiGAS0cmWRUx5PPGizxoYPYh6o6Kia3Nx0pqZ688mTfdy0aQF37erGW7d6MisrvLhX\nUGI2em5k+8VTVAcup6WJuweLsVOyopGTQ3bpojotwJGHR9hxW0fKFTp8H+Vy8n//E5NtabDgd12/\nTJNvGtE/JIWeycms7+7OZJmMCgXZvTupISl1Abx7ejP+VPnkdDIaTkaM6I8hDKduAJzz/m8FwE6X\nfoY8yvvG9fUdwckey+gyZgytatbkU3X75ys4+/bt01gtvAgLFpCff16kOfFiIt3ruTMrMkvnoXJz\nxYf8zZt1n14n3NzIli1V/wCmpZFdu5Jz5hQ5H5YUxnrr6vFM4Bm9p3z2TPwBHz2aTE+XMyJiFd3c\nbBgbe6y4V1EiBu4byO2uJ2hh8WL5qgAbNugemFOBmTNHzKek6qNWKBR8a/tbPPjgoG6DpaeT7dqR\nq1drFOuwZDKbzBDvgSmPHnFGXjJNDw9xxU+X/RZRO6LoO6J8cjoZDScjRvSnpEt1iwCcAxCY97oB\nADdt/Qx9lOeNK5fn0OVGLdq7nORtc3M6tGhRbrqUlJSUFNasWZMSiUS3DvHxotcp8sWW6sywTLrV\ndaPkmo5j5LF+PfnOO7otb+jFxIliCoXCZGWJa4KTJxf5pU3JTmHr31rz55s/6z3d7dviD+aKFQWH\nTUnxoqdnUz56NIW5uTom4DQAGdIMVv+xOpOzkjlmjPg+FyErS1Q6//rWS8bp02SjRmRCgnqZa2HX\n2GRTE2bLdEzxHRFBOjiQ332n9osZk5xM028b8seDV5kglbKOmxu987KbOjmJq37aeJ7TKSde912n\nhsJoOBkxoj8lNZzu5eVyyr+r7oG2foY+yvPGlUiu8LxnB464dIkbmjfn5yo8MC8Tw4cP559//ql7\nhzlzlMlrcjNzebvDbT7ZoF/l2sBAcYlOS6y5/iQni0HhsbEF22UyMQP6qFFFkh7K5DIO3j+Y005P\n0zuB6aFDYsz8X3+pPi+TpdDPbxy9vF5nWpoOu7wMwJnAM3x719skxaK/jRuryfO4bRvZv3+Z6GRo\nIiPF1UZ1q7H5GXpgKDd5ai/uqyQhQcwj4eQkGpgqWHb4X1b6uinjktK589kzdrlzh3KFgqGh4nNF\nlA57I/zGlU9OJ6PhZMSI/mi6b3Qp8pvzfBAAEATBTIc+rxSJiWfx0LQHBj18iGuVKqFPnz7lrVKJ\ncHJywpEjR3Tv8M03wP79YHQ0AqcGwqyVGRrObqhzd4UC+PRTYNEioHnzYiisiUOHgAEDgDp1ik6Y\nlQXs3y9WxM3H1xe+hoIK/DLkF50LNCsUwMKFwPz5wOXLwPDhquUqVaqJN97YDzu7+bh/vz+ePv31\n+Q9PqXE++DwGNxsMAOjSBahXDzh1SoXgpElAWBhw/Xqp6mNocnOBMWOAWbOAXr20y6/qtwo/uv2I\nlOwU3SawshI/VIVC/C5JJEVEvncahgbshnfXL8bHtraoJAj4IzoaTZoAkycDixdrn8b2Y1vE7IrR\nTScjOmNiYoLQ0NACbcuWLYOzszMAwMXFBSYmJpg+fXoBmd69e2Pv3r0AgD179qB3794AgBo1aqBm\nzZqoWbMmTE1NYWZmpmw7dOgQli1bhipVqihlatSoAUtLywL6PJevU6cOxo0bh9TUVOX5Pn364M8/\n/yxyHS4uLmikoiJ4fnltcxspG3QxnP4SBOE3ALUEQZgE4CKAop/6K4xEchbHs9uj34kTcI2KgqOj\nY3mrVCKGDRsGT09PxMfH69bB1haYMAHPJhxHuk86Wu5oqbPBAQCbNwNyOTBjRjEV1sSOHeIv13NI\n4KuvgJAQsZx9lSoFxH+79Rsuh17GkZFHUMmkkk5TpKUBI0YArq6AlxfQrp32Pra2E9ChgwdiYvbg\n4cMPIJUm6HNVenE++DyGtBiifD1rFrBpkwrBypWBpUtFC7CUjTlDsmQJYGYGzJ2rm3zbum0xtMVQ\nrHFfo/skVasChw8D3boBPXoAhX6IAeD0jJ9xJ+cQDrt6YauDAxaFhSFeKsWCBcCZM8D9+5qnsOhj\nAVmCDOn303XXy4hWdPlbZG5ujn379uHJkydax0lLS0NqaipSU1Nhb2+PM2fOKNvGjBkDAPjoo4+U\nMmlpaZDkM7YFQcCDBw+QmpqK0NBQSCQSLF261GDXomluI2WDVsOJ5GoApwGcAtAOwA8kVf1ZVokg\nCIMFQXgkCEKgIAgq//QJguAoCIKPIAgPBUG4puvYZUFWVhiypAlIMWkFyb17aGBnh7p165a3WiXC\n3NwcgwcPxl9//aVzn5S+MxB+tRHa/FEfpuam2jvkcf8+sGIFsGtXEcdPybl7F0hIAPr3f9G2bBlw\n4wZw+jRgbl5A/Hzweax0XYnTY0+jdtXaOk0RFib+jtrYiE6J/I4tbZiZtUDHjh4wM2uJO3faIynp\nqu6ddSREEoI0aRra1X1hzY0YIf7u+/io6DBmDJCcDJw7Z3BdSoOLF4Hdu4F9+wATXR7z8ljuuBy/\ne/+OqNQo3TuZmABr14oWfq9ewO3bBU63aWKNSbY/Y/LpT+DwWmWMr1sXc0NDUasW8P33omNWkz0q\nmAqo61wXMXuMXidDootHt3bt2vj44491NmDyj62vxzh/n+rVq+P999+Hv7+/XmMYqdho/VMkCMJE\nAI9IfkVyNkmd/+IKgmACsWTLIIgpDcYIgtCqkEwtAL8BGEayDYBR+lxAaSORnEVs1bcxMCkZ1+zt\n0bdv3/JWySDos1yXE50Dvy/j0GrwA1T75zed50hPB0aPBjZuBBwciqupBnbuFJfknltkP/8MHDwI\nnD8P1C5oGPnF+cH5b2ccH3UcTS2a6jS8i4toNE2ZAmzfXsR5pRMmJlXQrNlatGq1EwEB4xEaugAK\nhUz/gdRwPvg8BjUbVOBJtXJlYPp08e0ogqmpaMkuWiQuTVVgoqOBiRPF1VZ9DFYAaFSrESZ3mIyl\n15fqP/GXXwK//w4MHVpkzXPbzFF4La0lRm1egWWNG+OiRAK35GR89hkQFQWcPat5aNuJtog9EAuF\nrGK/968agiBg4cKFOHHiBIKCgsps3qSkJPzzzz/o3r17mc1ppPTR5RnOAcAeQRCCBUE4JAjCNEEQ\n2ug4fhcAQSQjSMoAHAbwQSGZsQBOkIwCAJKlt6ZRDBITz+Ka/C0M9vTENfKlj296zpAhQ3D37l3E\nxGh++lVIFfAb5Yf6n9eH1daJwLZtKmNACkMC06aJD+7jxxtK63xkZopLK5Mmia937wY2bBDdQoU8\ngnEZcRh2aBg2DNqAnnY9dRp++3bR6Nu7F5g5E9BjZVIllpaD0LmzD9LTfeDj0xtZWUWXgorDueBz\nGNJ8SJH2KVOAkycBlR/v8OGid0UPj2NZI5cD48YBn38OFPeWm9drHk4+Pgn/+GI87b//vmgFTZ0K\n/PbiYaFSJQGHx2/BmZjt8A5+iI3Nm2NaUBBoosC6dcCcOYBMg11s1sIMZg5mkJx7tZZXrgvXDXKU\nJnXq1MHUqVPx/fffl3isI0eOwNLSUnn069evwPmOHTvCwsICderUQWRkJD777LMSz6nr3EZKH12W\n6haSfBtAWwCeAOYD0LKar6QBxIzjz3ma15YfBwCWgiBcEwThtiAIE3Qcu9SRy7OQnHIDf+e0RfdD\nh+AeEYF33nmnvNUyCNWqVcN7772H48ePa5QL+SYElS0rw36hPWBvD3z4IfDLL1rH371bXEnTQbR4\nHD8OdO0KNGokGgDz5wMXLgB2dgXEsnOzMfzIcIxvOx7j39Ruwclk4krNhg1iTNOAAYZTuUqVumjb\n9gzq1BmNu3e7Ijb2UInGy87Nxo2IGxjQrKiSlpaAk5PoOCmCIAArV4rrS3J5iXQoLVauFI1vXYKu\n1WFRzQJze87F/CvzizfAW28B7u7Ar7+KFlGeh25Qz3rop1iDkfs+wQeWtVG/ShX8EhWFoUOBBg3E\nsDtN2H5si5jdr9ZynSMdDXIUB1NTU8gKWasymQyVK1cuIjt37lxcuHABDx48KNZcz3FycoJEIlEe\nV65cKXDex8cHSUlJyM7OxtSpU9GrVy9IpVKNY1aqVKnIdai6Fm1zGyl9dFmqmycIwmkAlwG0AjAP\nQGMD6lAJQEcAQwAMBrBYEARD770qFsnJ15HzWhu8Wak2/DIy0NzB4ZXawaBtuS5mbwwkFyR4fd/r\nEEzyXC7z54tP4Pl2iRTG3x/47jvg6NEiYUaG448/xKDwy5dFr8DZs0CrAqvAIIlPT32KBjUaYFmf\nZVqHlEiAIUOA4GDg5s3SWV4UBBM0avQ13nzzAsLDl+DRo0nIzS1esLDbEze0qdMGltVUfydnzhQN\np5wcFScHDRJ3kx04UKy5S5Nr10S9DxwoeVzcl12+xP2Y+3B74la8AZo0ATw8gFu3gI8+ArKzAQDH\nF01EemwdzDi8HptbtMBPERGIysnG+vVimF2Khg19NqNskHQ1CdJ4zT+kRnTDzs4O4eHhBdrCwsJg\nb29fRNbS0hKzZ8/G4sWL9drgoi/PY5xMTU0xefJkhIWF4eHDhxr72NnZISEhAZmZmQXaIyIiVF6L\nkfJDl6W6sQDqADgL4CCAYyQjNXdREgUgvwugYV5bfp4CuEAym2QigBsQg9CLsHTpUuVxvQy2VEsk\nZ+Fn2hODIyJwtUGDV2aZ7jkDBw6Ev78/nj59WuRcmk8aQr4JQeu/WqNSrXy7z5o3BwYPFrfKqSAz\nU1ziWr0aaN26lBR//BgIDBQDX8aMEXfPdehQRGzljZUIlgRjz4d7YCJo/qoHBIgOrHbtxLjy2rrF\njhebGjU6olOnuwAEeHt3RFraXb3HOBd0DoObD1Z7/o03gPbtxRXNIggC8MMP4i47LU/CZUlcHDBh\nArBnD1C/fsnHq1qpKlb0WYFvL31b/LQQlpZilLqpKdCvH5CQgFq1BGzosw07/dcjKyUCXzZogK9C\nQtCuHTBsGPDjj+qHq1SzEqzfs0bcobji6aOF69evF/hb+arj5OSElStXIioqCiRx+fJlnD59GiNH\njlQp/9VXX8HDwwMBAQGlrptCocCff/4JMzMzNG36IrZSJpMhJydHeeTm5qJRo0bo2rUr5s6di4yM\nDEilUqxZswZVqlRBt27dSl1XI3qgLsFT/gOABYD3AKwG8BjAdR37mQIIBmAPoArEZJqvF5JpBeBS\nnqwZAF8Ab6gYyzBZrXREoVDQ07MJe7nv48NJk9i3dWuePn26THUoCyZNmsQNGzYUaJMmSOnZ2JOx\nR2JVdwoIEKuspqUVOfXpp+S4cQYu4FuYb78Va4zVqUOeUV0u5bDvYdpttGN0WrTW4c6cES9n1y4D\n66kjMTEH6eZmzSdP1lOhS521PN747Q16PfXSKHP2LNm+vYbPY+BAcutWPbQtPeRyUZ358w08rkLO\ndlvb8YT/iRIOJCfnzSNbtCCDg6lQkK9P3Ey75d2ZJs1hU09PnktIYFSUmBQzNFT9UJLLEt7ucLtk\n+ugIXvEEmFlZWfzuu+/YuHFj1q5dm506dSrwt/r69ets1KhRgT5r1qyhiYkJ9+zZQ5LcvXs3e/fu\nXWTsJk2a8MqVKwXali5dyipVqrBGjRqsUaMGq1evzho1ajA+XqxFaGJiomyrVasWu3TpwkuXLin7\nOzo60sTEpMAxYcIEkmRkZCRHjRpFW1tb2tjYcPDgwQwICNB5biOGQ9N9o8sN0wrAFAD7AQQCcAXw\no7Z++foPzjO2ggDMy2v7HMBn+WTmAPAD8ADADDXjlPoblZ/09AC6uDdgQzc3Ztasyerm5kxJSSlT\nHcqC8+fPs2vXrsrXilwF7w24x+BvgzV3HD2aXLOmQNP+/WL1irxqFKVDTo6YgrxOHfLwYZUinpGe\ntF5jzfsxmovaKhTiJdSrR7q7l4ayupOZGUpv7268f38wc3JitMpHJEfQeo211oK2crlYxs/FRY3A\nrVtk/fpkZmYxtDYsP/0kJvCWyQw/9vmg83T41YHSXGnJB/v9d9LWlvT0ZGCQnJWm9Ob3ZzbxbEIC\nm3l6Mis3l8uWiYnI1aGQK+hh58G0e0UfPgzNq244GTFSGpTUcDoPYAGAtwG8pk2+tI6yvnGfPFnP\n497j+OmNG7zWpAm7dOlSpvOXFVKplNbW1gwLCyNJhswPoU9fH8plWjwfDx6IPx4ZYk22x4/FUiQ+\nPqWs8LZt5Guvkdu3qzwdnhTOeuvq8d/H/2ocJiuLnDCB7NCBfKJf9ZhSQy6XMiRkAd3d6zEx8YJG\n2W13tnHsibE6jbtlCzl8uAaBDz8k163TQ1PD4+oq2sKl9VkoFAr229OPW28byLt2+rSy9s7sFYGs\nvNCKwYkhHOHry6VhYUxPF0sDenioHyJ0USiDZhu6BlFRjIaTESP6UyzDCcBudefK4yjrG9fHpx9n\n3N7Eo1u28PuuXTlv3rwynb8s+eyzz7h69WrGnYijh50Hc+J0LEQ6fDi5aROzssQi81u2lK6ejI8n\nzc3VPsqnZKewzZY23OCxQeX55zx7RnbrJpax06WyfVkjkVyhu3sDBgfPoVyu+rMYfng4993fp9N4\n6emik07t0pGvr2i1lKqrUD0JCWLx3n8127ol5k7UHdZbV49pOQby8ty5Q9avT9m6TbT5cA3bruvL\niMxMWrm6Migjg7t3i98zdcukGUEZdLNxozzH0FWvC2I0nIwY0R9N942miNk3tUdIvZrk5qYhNc0L\nhzNbof/Jk7ianv7KBYbnx8nJCYf2HELg1EC0PtEaVWx0zPS4aBGwdi2+mZ0LBwdxc1upkZoK9O0r\nbp/ftavIablCjjEnxqBno56Y3W222mG8vcUg8CFDgCNHSnHXXwmwsOiLzp3vITPzMe7e7YHMzIIJ\n+6RyKa6GXcXAZgN1Gs/cHPjkE7Xx/ECbNmL2dZV1WkoXEvj4Y3FDwbBhpTtXp/qd4NjYERs8Nxho\nwE6Ahwcq7dyGO6ZPERiSgpM++zHPzg7Tg4IwfjyRkwMcO6a6u1lzM5i1fPVyOhkx8sqjzqIC8AhA\nB4ipAooc6vqV1oEyfOKJi/ubV247svutW8wwM6O5uTnTK6JrwkBkS7JpaWpJ95/0D/Q51vFHNrVO\nZnJyKSj2nMxM8p13yE6dyC++UCky69ws9t/bX2MMy+HD4urK8eOlpKeBUSgUjIz8lW5u1oyO3kNF\nnuvieth1dtrWSa+xIiLEgGW1TqWgINEtlZhYQq31Y/16sksXMXStLAiVhNJqtRVj09VsfCgOEgnp\n6Ej3xv1oMd+KoclP2NrLi8diY3n1Ktm4sbg0rIpnfzyj74e+htNFBTB6nIwY0RtN940mj1MDAOvV\nHOtKwYarMEgkZxBg2gODk5Ph3qwZOnToAPOK6JowAFQQQZ8EYUirIbgm169MYGgo8EXYHBwxHYda\n1UppS7tMJrojbG3FveoqMvBuvb0VF0Iu4NioY6hsWjTpnUIhJlKcOxe4dAn43/9KR1VDIwgCGjac\njnbtruDJk1UICBiP3NxUtdnCNWFnJ+6k371bjUDz5mJG8bVrS6y3rty6BaxaJaZLKE45m+LQxKIJ\nxr85HstdlhtuUAsL4Px5dOxYF+e2VsPM7Z9gS4sW+CokBJ175+LNN8UcmqqwGW2DpGvGnE5GjLxU\nqLOoAPioO1ceB8roiUehUNDdvT773DzGmytWcF7v3ly8eHGZzF0ehP8YTu9u3rx++Trbtm2rc7/s\nbLJzZ3LTJpIDBpB//GF45eRycuxY8t13xQCYzp2LiFwIvsC6a+syOFH1LsC0NDEUq2dPMtaAToay\nJjc3g48efUZPz6Zs+1sLukW46T2GmxvZvLn4tqrkyRPRLRWtPYVDSUlKEj0xJ0qYIaA4xGfE02q1\nFQMTAg07sELBO0PmMah2Ff59ch0n+vvzm6AgPnokOvPi4lR385/gz8hNkYbVJR8wepyMGNEbTfeN\nHvXG/xtkZDwAhaq4L62LzidO4JpE8soU9i2M5KIEUb9GofXx1ujdpzckEonOVbznzRPLS8ycCdGd\n89NPQG6u4ZQjxdonT5+KQSK7d4uZwvPhH++P8X+Nx7FRx9DMslmRIcLDxSK9FhbAlSv6F4qtSJia\nmqFly20wt52H8KRg1FO4gNSvUGyPHmJiT7WFaBs1ErNP/vRTyRXWACnWZh42DBgxolSnUom1mTW+\n7v41Fl5daNiBBQEdTv+EA/XnoPu47zD/WSj2xsZC2iAdY8eKGcVV8SqWYDFi5JVGnUUFYKC6c+Vx\noIyeeMLDf+Q/Pp/QydubKTVr0tzcnFnqAhReYjJDM+lWx41JLknKttmzZ/P777/X2vfkSdLevlA4\nzDvvkHv3Gk7BhQvFmKaUFDImhqxdW/x/HnHpcWz6c1Pu9tmtsruLi5gtYdOmUk7GWcb8efdPjjj0\nLu/e7cV79/ozO/uZXv337yf79dMgEBMjep0iIkqmqAY2byY7dhS9luVFhjSDDdY30JpAtDjcv09+\n0HUkk2q8xq3//sue3t6Mi1fQ2pr09y8q/zynU6pP6exqhNHjZMSI3mi6b9R6nEheLAvDraIhkZyF\nK7tiUGQkXF9/HV26dEHVqlXLWy2DIs+Uw2+EH+wX2qP22y9qizyvXSd+Z1QTEQFMmQIcOiRWolCy\neLFYwsMQRWPXrRPLqJw/D9SsCezdK8bf1KwJAMjJzcHwI8Ph1NoJE9tPLNL9jz+AkSNFJ9WsWWJ1\nkVeF8yHn8W7LEWjX7hpq1eoFb++OSEw8o3P/UaPEWoK+vmoE6tYFPv8cWLHCMAoX4u5dscrLkSPA\na6+VyhQ6YVbZDEsdl+K7S99p/L4XhzffBBr33otho+pg/JRJkEZH44wsBvPmiTUcCyOMrGH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8/Oj88PlpIgqwxyc0knp3Tq6a0p0O9QqJP69ckLF4q+n5JCtmhBlpX/Lz2dmQY67PiDPZNeJpEk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\n39D07ez6dSNp6tULPvtMJ03awwk4E8C4P8YR9HJQ3o21bCUmJnLs2LEsC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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x10f35c790>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "\n",
+    "for hashtag in popularHashtagsList:\n",
+    "    filteredHashtagTimeCounts = hashtagTimeCounts[hashtagTimeCounts.hashtag == hashtag]\n",
+    "    maxCount = filteredHashtagTimeCounts['tweetId'].max()\n",
+    "    filteredHashtagTimeCounts['normalizedCounts'] = filteredHashtagTimeCounts['tweetId']/maxCount\n",
+    "    filteredHashtagTimeCounts.plot(kind = 'line', x = 'createdDatetime', y = 'normalizedCounts', label = hashtag, ax = ax)\n",
+    "    \n",
+    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
+    "plt.xlabel('Time')\n",
+    "plt.ylabel('Normalized Number of Tweets over Time')\n",
+    "plt.title('Hashtag useage over Time')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Hmmm, this isn't the most helpful graph -- it looks like 10 lines is too many but we can  see that a lot of the hashtags follow similar patterns"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can even see where these hashtags are most popular over time!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "latLonPopulated_HT = hashtagsDf.dropna(subset=['x','y'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To make our lives easier, let's declare a vector that has the date bins we want to animate. This will allow us to filter our dataframe intelligently. (by indexing this date_list vector)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "startDate = latLonPopulated_HT.createdDatetime.min()\n",
+    "#We've loaded in about 1 day of data\n",
+    "numFrames = 96\n",
+    "date_list = [startDate + timedelta(minutes = 15*x) for x in range(numFrames)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#Note, the animation code courtesy of and adapted from http://jakevdp.github.io/blog/2013/05/12/embedding-matplotlib-animations/\n",
+    "VIDEO_TAG = \"\"\"<video controls>\n",
+    " <source src=\"data:video/x-m4v;base64,{0}\" type=\"video/mp4\">\n",
+    " Your browser does not support the video tag.\n",
+    "</video>\"\"\"\n",
+    "\n",
+    "def anim_to_html(anim):\n",
+    "    if not hasattr(anim, '_encoded_video'):\n",
+    "        with NamedTemporaryFile(suffix='.mp4') as f:\n",
+    "            anim.save(f.name, fps=20, extra_args=['-vcodec', 'libx264', '-pix_fmt', 'yuv420p'])\n",
+    "            video = open(f.name, \"rb\").read()\n",
+    "        anim._encoded_video = video.encode(\"base64\")\n",
+    "    \n",
+    "    return VIDEO_TAG.format(anim._encoded_video)\n",
+    "\n",
+    "def display_animation(anim):\n",
+    "    plt.close(anim._fig)\n",
+    "    return HTML(anim_to_html(anim))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def plotAnimationProperly(list_functions, data_to_plot, colors_to_plot):\n",
+    "    for i in range(len(list_functions)):\n",
+    "        list_functions[i].set_data(data_to_plot[i].x,data_to_plot[i].y)\n",
+    "        list_functions[i].set_color(colors_to_plot[i])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
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+       "<video controls>\n",
+       " <source src=\"data:video/x-m4v;base64,AAAAIGZ0eXBpc29tAAACAGlzb21pc28yYXZjMW1wNDEAAAAIZnJlZQAAv6VtZGF0AAACrwYF//+r\n",
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+       "YXZmNTcuMjUuMTAw\n",
+       "\" type=\"video/mp4\">\n",
+       " Your browser does not support the video tag.\n",
+       "</video>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import matplotlib.patches as mpatches\n",
+    "# First set up the figure, the axis, and the plot element we want to animate\n",
+    "fig = plt.figure(figsize=(10,10))\n",
+    "ax = plt.axes(xlim=(-180, 180), ylim=(-75, 75))\n",
+    "# plt.axis([-180, 180, -75, 75])\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "scat, = plt.plot([], [],'o')\n",
+    "scat_top_1, = plt.plot([], [],'o')\n",
+    "scat_top_2, = plt.plot([], [],'o')\n",
+    "scat_top_3, = plt.plot([], [],'o')\n",
+    "scat_top_4, = plt.plot([], [],'o')\n",
+    "scat_top_5, = plt.plot([], [],'o')\n",
+    "scat_top_6, = plt.plot([], [],'o')\n",
+    "scat_top_7, = plt.plot([], [],'o')\n",
+    "scat_top_8, = plt.plot([], [],'o')\n",
+    "scat_top_9, = plt.plot([], [],'o')\n",
+    "\n",
+    "# animation function.  This is called sequentially\n",
+    "patches = []\n",
+    "def animate(i):\n",
+    "    subset = []\n",
+    "    color = []\n",
+    "    for j,hashtag in enumerate(popularHashtagsList):\n",
+    "        subset.append(latLonPopulated_HT[\n",
+    "            (latLonPopulated_HT['createdDatetime'] >= date_list[i]) & \n",
+    "            (latLonPopulated_HT['createdDatetime'] < date_list[i+1]) & \n",
+    "            (latLonPopulated_HT['hashtag'] == hashtag)])\n",
+    "        color.append(cm.jet(j/float(len(popularHashtagsList))))\n",
+    "\n",
+    "    plotAnimationProperly([scat,scat_top_1,scat_top_2,scat_top_3,scat_top_4,scat_top_5,scat_top_6,scat_top_7,scat_top_8,scat_top_9],subset,color)\n",
+    "    \n",
+    "    return scat,scat_top_1,scat_top_2,scat_top_3,scat_top_4,scat_top_5,scat_top_6,scat_top_7,scat_top_8,scat_top_9,\n",
+    "\n",
+    "# animation.Animation._repr_html_ = anim_to_html\n",
+    "#set up the legend\n",
+    "for j, hashtag in enumerate(popularHashtagsList):\n",
+    "    patches.append(mpatches.Patch(color=cm.jet(j/float(len(popularHashtagsList))), label=hashtag))\n",
+    "plt.legend(handles=patches, loc='best')\n",
+    "\n",
+    "# call the animator.  blit=True means only re-draw the parts that have changed.\n",
+    "anim = animation.FuncAnimation(fig, animate, frames=numFrames-1, interval=5000, blit=False)\n",
+    "\n",
+    "# call our new function to display the animation\n",
+    "display_animation(anim)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also plot the hashtags by location! this is currently just a simple scatterplot. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Qhg8fTpqamtSjRw+6e/cuky+VSikhIYF27txJ7du3p23btlF0dDSZm5uTsbEx6erqkry8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g5LqsKK6lphiWJvfVVIJNDSGvqWhnKmWefY66aNXhnLoLQR7K0D5bMZlx+yi3I7Ojpy4cIFHj58\nSOXKlbGwsKB79+7UqVMHMzMzAHbt2kXz5s1p3bo1ZmZmfPXVV3h6erJ48eJ8rSEiko6o5ieSLRkq\nfIfRbrgb65338HDEz69/oa/7vn2hCrtB79vqgXnZk5OCYPfuNVmzpjZZyxQFtM6W9q6vQiFFZe2i\nTe3T1UzdhifZOVOZuc6qVWZ07FhR97z9/f+mS5cd/OR5mRHt9mp7kZqASiFh/AoDfvZ9e7PaEaj6\nxsYaQE3Wr5cxYEDh9/sR+Xfy22+/cfTo0XwpzuXnva6tmXJ482gvcBCp9DIazTOgDtAMpdIo3wqR\nwcHB3L9/n1mzZiGRSDh//ryeQiVoHYiVK1cydepUAFxcXNiyZYtemt2RI0eYPXs2wcHBDBgwgGHD\nhundyW7ZsiXff/89bdu2zdMm0NYX3bx5k5IlS2Jra4uhoaFu8zZ+/B581x+miMlqbr4RLnUqBcXM\n4XVKVWq6VebSpUuUL1+e2bNn4+rqmstK2sL8DRs2sG7dOp48eUKLFi1o1aoVhoaGPHjwgPDwcCws\nLDAyMmLTpk3Y2dkxdepUWrZsma/nkh2JiYm0b9+eOnXqMHfu3GzHXLlyhTp16hAbG4uBgQEDBw7k\nwYMH7N+/XydtLfLx+Vyb9oqIfCjeRc1PdKZEsiXDKVgFuAEVMTaW07t3VQYNctXJaRcm7yujnr45\n0/ZHUjNsWG2WLWtXKHalO2hArs5abs+hSZPz3LlTB32nKEMqXSKB5cvbM3z4IdQyJSirQ1JtSFWj\nTfF725nSf9y580V27/bQvRaDB+/D3iaJ4Jk/IQnQDo9NgSKrs3uWTsBF3pZaDwoyxMXlHW8Xivzn\nOHv2LN9//z2XLl3KdVxB3uv16h3g8uUYYDi//jqPZ8+MWbjwPgYGRfJ1gyMzbdq04dq1awwaNIiz\nZ8/StGlTZs2ale1YtVrN8+fPWbduHQsXLqRDhw74+Pjg6JjRp+3evXssW7aMrVu38tVXXzFt2jTM\nzMyoUKECe/bsoVKlStnO/eLFC4oWLcq2bdv46aefePjwIZUqVSIyMpLHjx/TtGlT/Pz8mDlzJjNn\nzqeSgwOuznf58xrYWsK26fD8Naw+1JoWvfpTpkwZGjfW3vA6d+4R/v4hem0PciIiIoJjx45x/Phx\nBEHA0dGR0qVL8/LlS16+fEnXrl0LpZEvQHR0NK6urvzwww906NABZ2fnLGNsbGxQq9U0a9aMR48e\nER4ezo4dO3TPTeTjIzpTIv81RGdKpNCIjk7Azu5nkpN/RCvfXTxXxya9/5Gbm9k7b77fpS9UuqNj\nampArVor9TZnALa2JkREjM722oKS36hZbtGsMWPOsmBBGGAMPCY9IgXQtKk9zZrZM336abTRQH3Z\n9KzRqLedK3+iotpy8eILOvQ7DtZGjGh2kV8VvyB5c+nJCGh+AAZ+AfWrgYuTCaNW7ePq1fv06dOI\nrVtLkrnn1ZIljoiI5JfJkyeTlJTEggULch1XkPd6YGAgbdq0YerUqQwdOhR49wj0unXrOHz4ML//\n/jvh4eE4OzuTmJiYZwrP/fv3WbVqFUePHmXVqlXUrl0bQRD44osvOHXqlE45zN7enuDgYFq3bk23\nbt3w9vbOMverV6+wsLCgb9++jBgxgg4dOjB69GjGjh0LaCNHlStXxsDAgMePHwNgqDDD2iIOUyVs\nnQo1ymsV0X49MoORMyfr5vbw2MTRow8yPf4wGQTvyqpVq3S/w9u3b+s5m5GRkTg5OXH58mWuXr2K\ntbU17u7uyOWi6PCnRHSmRP5riH2mRAoNa2sT1q7txIAB51Grd2BgMIw1a7rqNi7BwdGsWBFEeDgk\nJxfj0CFbtH9OKXh7R73TJtzBoWgWZyg5OS3HGqXMzk1ychoajVZEQWZlgMLBGFVoIk+eJLBlS6Ce\nfPm7EB2dwODB+0lOTtPZOGTIPlq2LJtlM9eyZVn69KmCkd8VuiUdYOfYZJ0zNXhwBezsFNy/H8OS\nJfoF3adOhXHqVNibR5lFIdJJBa6ibYDbmbeRy6Po0OEqryyN+epXuCitRoo0Bs5mjClrDpZGsGog\nyMtAokpD2CN7vLwkLFtWhUmTMjvFoiMlkn8EQcDPzy9fimz5rUcUBIGhQ4cyffp0vv76a93xzC0I\nCkJ61EW7ngobG5t81UI4Ozszd+5cLCwsaNu2LTt37iQsLIzg4GCioqK4desWQ4YM4cmTJ2g0GhYu\nXEjv3r158OBBltopAwMDDA0NCQwMpH79+pibm+tJOFtaWrJ48WJ69uxJvXptCAioRU93Fet95vK2\nqbVqZnzhnzv3SM+RAq3q6rlzj2jY0I4tW+6zY0c4PXqUpm/frFGhj8GRI0cYPHgw9evXx8HBQe/c\n8+fPsbGxoUqVKty+fZuKFSt+EhtFRERECoroTInkiLZB7u906NCOb7+tonMIRow4zOZtT7GtUpEn\niSV5dUe/H8PSpUXw8op/pwiVIGhyfZxOZqGHzA6YWS9bbNe4IqQKSAwkPBl8gx07br+3MzV8+CGS\nk/UdvczNh9PvlF+79pRhww7x2GgeZiQCUCPhL8KVi5j79e+ZmiHnRSxZ9WGkQCAGBimkpl5HW9eU\nznWk0mT62G9ihPVquKotudrp0JY/HkHnIxDQBYadBq/KkKxRIlXB4GXLUcjvsGxZewBcXEzFtD6R\nd2LMmDFIpVLq16+f59j89oA7c+YML1++ZNCgQYVio1KpJCkpiZcvX7J///4C9TSSSCRMmDABZ2dn\nhg0bxubNm3FycsLNzY2rV68SEBBAaGgoJiYm1K5dm8OHD1OtWjW8vb316qmMjY0ZPXo0/v7+PHv2\nDGtr6ywO3bx58+jevTv/+998Gjdez8Wg7JX0bJ3ddf/39w/Jdoy/fwi9et0iPLwuUJT9+6VMmHCI\nR4/ePwW6IKjVas6fP8/58+cpW7ZslvOVKlXi0KFD1K9fP9vzIiIiIp8ropqfSK5YW5vQtGldgoO1\nDXI7ddrK/Zh9HH68lOV+ozh8rhseR85Ao8x+uYZLl/Kv6JVOaOgrjI31JYGUSoNslbqyky03LGGE\n7RpXpMZyZEUVSI3l2K51pWL9EgW2JTPBwdH8/ntwluOpqdo76elS6O7uGxk27BDDS8swI1FP/NyM\nRIS9udeR6JOEtm9UJtl0/DEwSCU1VUOGSqDfm39P0aiywAjr1UjUIFHBxPPw7eTDOFvKSNVAzZ3g\nagk+teV0XvJ/2PfYQodODXjypP17vT4iIgD79+9n7dq1GBsb52t8flomGBkZER8fz6tXhSPRb2dn\nx507d6hWrRq+vr60atWqQNdr05/rUaJEKfbt20efPn14+vQpRkZGFC1aVE/8wdnZmWnTptG1a1di\nY/UVUbt168a1a9c4f/58tpGx2bNn4+d3HHf3iSgUEu4+smbxTjcEAd3PqXsdcKraUHeNh4cTVkUT\nqF0xAquiGeqIgmD0xpFSAIaAgseP67FlS/YtLz4EarWa7777DicnpywRqcwYGRlRpUoVypcvz+nT\npz+afSIiIiLvgxiZEskTT09PmjRpwty5D3EtV4t1G44jiZOisdb++UyrM5lLo4/yKtAAYgVAipub\nWYHXKYgUeXZj5Q5KhFRBW470BkElkGjxltR4PkmPNgUEhGd7fuDA6gC6CJkWZ7olzct2fLekvSyj\nD/lvrHsPbV2VOdpIVRKpqZnPJ6OVNU9GqZTjaHxFr4xq1wN4kQJHq3/NxNurWX9Xw4IGBgw45sml\n6Ce51qKJiBQUjUZDUFAQzs7OKBQ5NazWJ690PQMDA1JSUjh9+jSdO2dNbS0odnZ2BAQE8Pfff9Om\nTcHaKKSnFSsUGmJjzxMbm4YgxLJ27doc63rGjh1LWFgY3bt310mMp9tRv3591q1bR506dbJEyGxt\nnYiNTUH73tem8o35rT1l60/AQhGIrbM7zQY31Lvm3vmlhO38mdQ0GQZyNYNnd+SlrCN//ZVM1pRh\nDTt2hH+0dL/bt2+zd+9erl+/nmtaZdmyZTl79iy9evXi/v37NGnS5KPYJyIiIvI+iM6USJ6UK1eO\nWrW+54TfFEY93YF9ZykSlUDU/5UkoUcRVIIcW6MIXtnYQayGpk1DcXGpVeB18pv6k9NY787V2Wug\n/0UtUUho51pw5UH9eqzs27K3a1ee69efIpVmXrMCO5XdqJHwV5bxO5Xd0G6O8utMgUSSxK+/NsXH\n50/02/dUAFqRLhaRlOTPmb+fwpsb405b4cGbm+GTf0shLrQ81kaWOG5pTkyyDKUy935ZIiIFZenS\npXh7e+Pv78/KlSvfez6VSoWHhwdLliwpFEcqHWdn52yV5DKzefNmdu/ejZWVFcWKFePJk0i2bDmP\nRvOKpKTXQApXr17i4sUA3Nyq5jiPRCJh8eLFNGvWjO3bt9O3b18AihUrxooVK1i/fj3Vq1fn8ePH\nen2cfv55MTKZBWp1Rgq1UqmgpGMd6tTplGWde7eD6VnzZ4yN0jBGe2Nn7YR9hJf4kcs35OzfnzVl\nuEeP0oXeSiInihcvTmJiYr6jlhEREWLTVBERkX8MYpqfSL4IumDIAaMkRiTAhVcapEkCNsOeIo1O\nQyFJ40lySYgSADWnTjlgabn3ndbp3bsKV68OZfHi1ly9OjRXyeO304TmjG2K1S9P0CSmoX6tQpOY\nhtUvT2hd16FANrzdeDclRYM0m3dKhw6+tGmzhYSEzM7WXZaFjyAOYwTQ/cRhzLLw4WgjTFrMzPK+\nez9jRnN69apCWlrmO8tKtI5URtoOeHA30o7F4W4IMrjUA1qW1o5+8WA9RibJvNB4kGpgjFIpz9FJ\nFRF5V1q3bs22bdu4fDm/dYE5ExgYiI+PD+XKlaN3796FYF3BWLJkCUqlkpo1a1KkSBFsbStgZFQP\nbZsIBVAapfJLJJJiec4ll8vp06cPfn5+esebNm3KihUrePnyJfHx8Xrnxo8fgyCYAWvRpvnm3jD8\n3s1rpKbpR+BVaTLu3bxG377OlCkTQOaU4TJlApBKk7G3/4VWrTZhb/8Lvr638vPSvBPFixencePG\nTJkyheDgYJ1YUE4kJCRgaGj4wewRERERKUxEZ0okX9QonoyrkZSvZLDrTXadoJAgPIBpl6fzaoER\nxMpI39y/eNGY5cuz/3J2d7+AoeEN3N0vZDnn63uTWrVW8t13R6hVa2WeX/DW1ibUqVNK5xicndiR\nX25a47EtmV9uWnN2YscCP9fs6rFMTQ1ZtChrfcXbewJDwxAgljLJT/Cx+pHrJtXxsfqRMslP8PD4\nm6CgQaxf35HNmzsTF5d9xCszXbu6ADBxYmOMjGSYmxsilRYhu7QdMGfkvra47BzO9391JyRpuO5s\nXFxnxo1rlGt9iojI+/Lq1SvMzc1JS0sjJSUFf39/7t27R1paWt4Xv2HRokW0bt2a+Ph4li9f/s62\nREREsGXLFjZu3MjGjRuJjo7WHZ87dy7Vq1enZs2ajB49mtjYWAIDA3XXDho0iOvXrzN//nySk5Np\n2rQuGo0j2tRaJ+BroEq+o7tdunTh4MGDREVFAdrU6bi4OAYNGsT+/fuxstIX8SlXrhSbNm1HJrPG\nwOBcnjdAyletiYFcP+1ZIVdTvmpNAB49asfmzS/48stbbN78Al/fqgwYsFd3wygpKY0hQ/YRHZ2Q\n3fSFwpw5c3j27Bnt2rWjXLlynDt3LsexjRo1EmumRERE/jGIfaZE8oVbhTX4R3vyOlHALQV2GEB1\nEwnNqx/nxrWnENsKrSOVTgqNG1/m9Om2evNIJOk1QOnEIghlgPdr2nvucgz+Z5/j0ciShnWschyX\nn7SWnOyYO7cl//vfkRznNjFRsHt3Dw4cuM/SpQlAbUAG3Ofs2ao0bGitGzt16glmzMh9s2BkJMPH\npzE//XRW19tq4sTGxMdLmTvXhcw9qKyKPsOhxDZCn6UR8yrdEUwE5gHVgC4oFFIiIr4XI1IiH4yl\nS5cyYsQIlEolFhYWlCxZkhcvXhAbG8uNGzcoXVobLk1LS+OPP/4gKSkJhUKBIBwPxC4AACAASURB\nVAio1Wru3r3LqlWrOHv2LGXKlMkyf1xcHIGBgUREROh+YmJiiI+PJy4ujvj4eJycnEhMTOTPP//E\n3d0dpVJJYmIix48fR6FQoFKp6NatG/379yc+Pp4vv/wStVrriGT+vhMEgWvXrrFlyxZOnDjBo0dP\nePXKCqlUjkLRo0DNggGGDRtGdHQ0S5cuZeHChahUKn799ddcr7l16wGNG9dhxozZFC9eFENDQ9q2\nbaurSQsJCeHq1asYGRlx5ehOxnfyRZUmQyFXs/3q9wwaO5fHjx+zePFiatWqRc2aNRk/fi979sSj\n/WzKIK+efoXJgQMH8PT0pFKlStjb22Nvb4+RkRFBQUHcvn2bO3fusG7dOnr06PHBbRHJnc+5z5RU\nKuXvv//Wa6Q9ffp0QkJC2LhxI6dOnaJ58+Z4eXmxdOlS3ZjGjRvj6enJV199xYYNG1i9ejVnzpzB\nzMxMV9OXHh2VyWRIJBJWrFjBvXv3mDVrFkZGRoD2M0KhUPDixQudPSYmJkgkEoyMjGjVqhXLly/H\n3Fy752nevDn9+/dn8ODBes/j1KlT9OvXT9dXLp3M46dPn57r2iKFh9hnSuSDcenuEKY3usZ3QcuZ\nbACjEwXaunhz4+QzIJzsZLzbt9dX0dNGoiqh32zWHHf3Cxw/Xl8XEcrsxGSWH88Jj0HXORpZBQRT\nZhyV4VH8On7ramQZl9+muznVbrm6Fs/1NdJoBGrUKMmBAxKgKNoEPwne3g56jhRolbfycqYAfvrp\nrJ78+08/nWH2SBe+Kn+Ii5Ffcvd1eXq13Mua8SNITVNgIFcxePYQth+3QqvEMQQ4BIBcLs3ztRQR\neR8GDx5Mp06dMDU1JTQ0lOrVqyORSBgzZgw+Pj6sX7+eK1euMGjQIMzMzChdujQqlQqJRIJMJsPQ\n0BA/Pz89R0oQBPbt28fq1as5ffo0Li4ulClTBltbW0qVKkWlSpUwMzPD1NQUExMTbt26hVQqZe3a\ntbpNDGibwgqCgJWVlU4IQqVS4ePjw4wZM9iyZYvec5FIJNSqVYtatbT1n1evXmXWrDl8+eUA2rVr\nXuD30dy5c/nxxx+pUqUKZcqUITw8PE9nqkoVR1au/D98fX2Ry+U8ffqUMWPGMGvWLKytrfH09KRC\nhQpIJBJu3rzJ9Qdf0LWtB/blK1G9ZTF27drF//73P7p06YKvr2+mlMnv0b+plXsaYWHToUMHbt++\nzbVr1wgLCyM0NJSYmBiaNWvG8OHDdb9TkX82agSS0GDKu4lA5UV+esSZmJiwadMmxo4di51d9vXT\n6fPEZSpMdnR0ZM2aNTRv3lx3bPr06fTq1YuNGzfmOE9gYCBly5YlPj6e7t27M23aNBYtWlQozyW3\ntUU+LaIzJZJvpp5dhottZSoVTeDW/dVcOX+dtm3dOHw4Xcbbg3RBBPCnefMMJabo6AROncp+83Hm\njLavUUHU/NI5dzlG60jJFaRHavwjq3DucoxehCq7vlQ5Nd0FbePdvXt7AlCjRkndmMGDa7B27fUs\n442MZKxZ05GYGIGlSy1If2tZEsP5ZQ9pcfo+f/71hW58w4Z2NG1qn6lJbwZKpRxBEPDxacKCBef1\nnMs5Na8w4sUkaA4wh1X3+tFv/C6MjZIwfiNssXbCGo5fHf0mQmUNPCddEUwUnRD5kBgbG+tEBjLL\nhPv4+NCgQQOkb4oPfX196dmzZ44biMTERAIDAwkODmbv3r3cv3+fSZMmsWXLFooUKZKrDTkpwBUv\nnvVmiEKhoGfPnqxevZp27XLvu1SrVi127/491zG5UaRIERYsWMCoUaO4c+cOlpaWqFQq5HJ5rhup\n7t270717d93jo0ePMnXqVKRSKf3792fKlCmA9jWbNGkS/5swiSJFimBpaYmVlRUrVqygfXtt+4Ov\nv57OmjVLASO9NRQK6Uevo7S0tCywNL3I54UaASkgIevf7y5i+JFwNAiUxpBVlKMUBlkneQ/yEzEr\nWrQoXbp0Ydq0aaxdu7ZAcxc0Ipf5GlNTU7788kv27dtXoDlE/pmINVMiBSL4iRczdw1k4a+rqFjx\nFa6uwQwZUgOtjPcaYBewBqXygW7jnt6HSa1+nO2c1appHaj0iJBSKcfc3DBfQgkLlwdpu9NmRlDj\nf/a53qHs6qDSo15vk25vjx476dRpO8eOPdSdK1s260bOxETBvn296N27Cnv2PCc9faar9HduGVZh\nr0EXtt7tTFeZfv3H/PmtMDbO/n6GRCLB2tpEz7msUCSVEVX2IpGg+/Esv5m0F/pvY1WanK7tLN+I\nZsjePNcUUXRC5JNRpEgRvUjD5s2bOXbsGL///ju7du0iLCxMl+q3YsUKHB0d8fb25sSJE7i7u3P9\n+nX69OmTpyP1LlSoUIF69eoxbdq0Qp87O0qVKoW7uzuurq40a9aMFi1asGXLFn777TfWrFnD8ePH\nswhSZKZVq1acP3+es2fP6hwp0DqyixYt4sWLF2zduhUfHx8sLS3p0KGDbtxXX3VFK4KTojfniRMD\nxDpKkXyTgobveIArN3DlLxbzFIEMxyOIRGYRTioCacAjUviWrE2lrxDP//GMncSQmqUOuHCQSCT4\n+Piwa9cu7t//eL3VXr58yd69e/PVxFzkn48YmRIpMC4u1ri4WNOjxwmaNWvGuHEVqVixFRMnHkcq\njSHFsDhJNhWxKXeOqvbPuXv3PqmpAnAbaIh+mp/AH39U0z3q3bsKLVuWzZdcb3R0Aod+vwyN3/qw\nksjwaGSpdyi/Ua/cIligTbt7G7VaQ40aJfWOWRLDUsUIjCVJpEuhL1P8QLt6jhwK+EJnU9YbXxYk\nJZUAnvHdd38wc2YLpkw5gUwmpW6p7HOjDWNTwTbjsUKexqBvPZi+sDS9evVGo2nF77/7YGNjmu31\nIiIfmsOHD/P69WvS0tJQq9XMnDmTWbNm6aIz3t7epKWlIZfLKV++PIcPH6ZmzZofxTaZTIaTkxNF\ni37cqG18fDwhISFERkZy8uRJQNu0Njk5GYDw8PAs/afyYu7cufj6+hISEkKzZs04ePAgrVu3ZvLk\nyQAkJz/B1rYCT55kOLbe3m40bFjw9hEi/13mEM5pYlGjjU5tIIqyGNIBrbplIIl64zVACMmoEZC9\n+f7fQQxz3jhcBkjYRgxbKY/BB7jHb2Njw7Bhw5gyZQq+vr7vNdf27ds5ePCg7nGNGjU4fvy47nHN\nmjWRSCTEx8fj7OzM0KFD32u9gqwt8ukQnSmRd8bKyopx48axadMmOnUaR1paGkKjnjDCBdIAOdxc\nnASpl4BTaJ2KP9CmA0oACVu3mmBtnfHhWZC+J6Ghr1DKVKT+tQ+qd9RGqCQy6hpdoWEdfQcrvz2s\nsqvbksmkHD58n5IlTbOcA/DxaaKbp3NnS3x8VNhLwlChIHNPKRVyoq++ztYmqVRCQkJDdI2igJSU\n60yceJwlS9piZCRj9qTsPzTHH5rKLIdZqNIUKOQqOk4YRYrRLKKirmBlZcXRo0f1etiIiHxM4uLi\nGD58OKtXr0YmkyGTyZgxY4beGEEQePbsGYmJiTg6OuarfqCwuHz5Mr6+vqxbt+6jrQnaNKCnT58S\nHR3Nvn372Lx5MyVKlEAikVC5cmVKlCiR9yRvkZaWRmhoKN26dePQoUPUr1+f9evX6wQrbGxsMDFJ\nJijIi0uXInBzK4WLi3Ues4qI6HOeOFIyRaKS0HCaWJ0zVRwFUiSQaYwZMp0jJSAwh3CS35xPRiCU\nFP7kNa2xyLcdMpkMlUpfFVelUmXbNHzcuHGUK1dOT7XzXejZs2eudUvXr1+nbNmyqNVqli1bRqNG\njQgODsbAIOcUR7lcnuV5QNbnktfaIp8O0ZkSeS++/PJLtm37neHDOwFJkHIL7nqDYw0wLAr/U0Jg\nTYgNBF4C95DLwzl06Ftq1DDWc6R8fW8y+rvN2NqrCVVXokfrSiz7qV6Oa+uiTa9vQ8xDUBbFQB3L\ngQfDsh2fn6hXdhGs+PhURoz4g9RU9Vv9nrT1Td98k9Gg2MXFlD59buG3tRQK9D8cFaRhXSsjTenc\nuUfcuRPNjh3dWb8+lF27XAEJtrWeUL7Z39w76cSTq0UYNeoIV68O5W60hsVxXvzP7DfdHIvjvPjl\n0DdsPtEbhxJh3Am7THzSAqTS+hw5sgp394a6OhURkY+NWq1m9OjRNG/enJYtW+Y4TiKRULJkyRzP\nfyiioqJo3rw5GzZsyNW+D4VEIsHGxgZPT088PT3fe75x48ZRoUIF7t+/z8SJE7M0J543bx4eHh66\n7AIRkXfBCgWPSdU9ViChZCZ12aaY44Ypl4hHgjZ6NRd73XkNkIp+WoYGgTjeStnPAzs7O0JDQ6lQ\noYLu2MOHD/Uep1OsWDFGjhzJ5MmTP+jNmvSaKZlMxtdff83IkSO5detWrpF2Ozs7YmJisjS2DgsL\nw97ePsfrRD4fRGdK5L0oUqQI06Yt588/15Fs6wolz8OGsSBowHMx2DUARzkE1YFUfwCk0hRq1JBk\niUjtXzud+9sPkio3woBUBr9ag20vY55sq5bt2vrRJjWq1Kg864KsrU3yPJ8+p0QCiYkKwJy4uFjI\n9OVhYCBDJpNku96WLVXoI/zB8O0/s0wxChVyFKQxXLVQl+Ln4bGJo0cfZLpK65AN3biGX8pNIE2i\nQN5Vxcj7M9n4Ddy8GQkpiYw82ZzltYZR1+ASF1PduHv1IaSmEZO6gphX29/MtR+l8gJFizqKjpTI\nJ0EQBA4fPszEiRMpUqQIe/e+WxPvD02xYsUwMTHh0KFDODg46JT7/qnI5XK6deuW7blDhw5x7do1\nrl279pGtEvm3MZnS9Oc+agQkSCiKjMFkCLxIkbAMRy4Qx3PSqIYJ9plap8iQUAMTAknQu+VYh4Kl\novfs2ZOZM2dSpUoVbG1tOX78OAcPHsTHxyfb8aNGjdKTUf+QaDQa1q5di7Gxsd6aKpWKlJSMmkWZ\nTEaZMmWoW7cu48aNY86cOSgUCn755RcMDAyoVy/nG8oinw/iTkvkvdHVHcU8hb6zYO55qNMBFvaB\n3VPA3gjc64Gt9kveyEieRfhh17aTrBm/H2ODFIpKX2MsTWKtxRBU3Uuw5UBEjmv37l2FsLCRhdqM\ntnfvKvTuXYXERCe00uJd3/xbXjcmNVXN0aP9c1xv69Y2zLzVhQ62m+miXsUQ1z3sUn8LaCNS+o6U\nFttaT/il3ASUmhTM1PEoNSn84jyJYpUtiYx800zzyW3u+h1h4zENd/2OwJPrQG/gErAZCAAeotEk\nflTlvujoBC5fjvigTT9F/hls3bqVKlWq4OPjw9SpUzl16hTFihX71GZli1wu5/Dhw5QsWZJBgwYR\nEpK1SP7fwoIFC5g2bZrenW8RkXehIsYcwAUfyjCNMuzHhaJv3ZuXIKEB5nSgmJ4jlc4SHKmDGUZI\nKIGCpTji8JbKZF5MmTKFBg0a0KhRI4oVK8b48ePZunUrlSpVyna8mZkZY8eOzVdvppyiV9u3b8fc\n3Bxzc3PMzMwwNzcnJiZGd0316tUxNzenWLFibNq0ib179+rVY3p5eelUT42NjXU9p7Zt20ZkZCTl\nypWjdOnSnDhxgkOHDumlB+a2tsinRWzaK1Io+Preon//3ajr94H/OWlrppKiYEI7sOoLTqMgTYDj\nqzGUPOPxY/3msVNGzeP7ttMpapxRuPpaY07LqKM8nC8nJuDjFKMDBAdHU6nSOrQOVObcaxVaxUJt\nHdT69R1p29Y53zVe6WTfsLcmzX6QsL9bb8zUGUpecTITvtz5K30ruuLpefCta+KQSo8hCKF06bKC\n/ftfY2CQgEaTWOCGou9Dfvt3ifz7mTt3LuvWrWPp0qW4u7t/1Nqn90EQBCZPnszKlSspXrw47dq1\nw97ensTERGrUqIGbmxumpu8m4KLRaPjrr7+4fv06pqamVKhQAWdn54/q1Bw/flznLGZXTyIikhOf\nc9NeEZEPwbs07RUjUyKFQu/eVXj69Ae2j0iGr+/CvCQ4YAPlFsHjdSAI2lpUpQMDB9bI4ng0atkE\nA+lbNUYSFaE48DzYgWnTLua49k7fi/zwzXJ2+uY8Jieyi6js2ROMtqHl21KtGjI3uoyOTsDe/hda\ntdqEvf0v+PreyteaHh5Obx1RAg24d7IcciHjNdC8AmlwKtHH4vDyOvTWNdcwNFxJv34NCQm5y86d\nPYmI6MuJEz0KLUKXHzKrH75+nUJSUhpDhuwTI1T/Qfbu3cvKlSs5fvw4LVu2/Mc4UqD9kpw5cyZP\nnz5l5cqVyOVyrly5QmhoKJMnT8bW1pauXbuyfft2EhMT857wDXfu3KFJkyb06NGDEydOsH37dvr2\n7YulpaWerPmHZtWqVUyePFl0pEREREQ+AGJkSuSDUL7KCe7bNQOZACcqQbX/g6JN4fhqgm50yrb4\neezgQUzr74tKbogCFYNfrWH7vI5wNgG5fA9PnvTN4oQN7zGW+d8sJTVNjoE8jTErvVm2fV6+bPT1\nvcmgQXt1dyHWretM795V+OmnM/j4XCC3yNTgwa74+t7SU/ZTKuWEhY3MV4Tqiy824e+fnupXHG0q\noSFDN6zlF+fxqI4LsCCVJIkRQpKE4aoh7NakNyE+hkRyhzNnjtCw4aet8bh8OYJWrTbx+nVGDri5\nuSHHjvWnTp2CyTqL/LPp06cPLVq04Ouvv/7UphQ6L168YO/evWzevBm1Ws3JkyfzdBbv379P/fr1\nmTZtGl5eXnr1i9HR0dSpU4e0tDR69uxJ5cqVcXJyokmTJoXuhKamplKqVCmuXr2KnZ0ogS5SMMTI\nlMh/jXeJTInOlMgHw65eBI+L2cKjlRC5FwwW4N3lEUuWtKFnz55ERkbSuXNnateuTcOGDQFYsug4\nG7cKhGqciAmxglgBUGFispETJ3robdB3+l6krU1zjI0y5McTk5UcjjpBt951c7UtOjqBEiUWoMkU\nfJJK4dmz0WzYcIMxY46hrZHyQBuRkmFgcIqVK8vi5laK+PjULE6EiUURfpjchl4dS+PimLdDde7c\nI/z9QyhRwhovr5KkO26Vq9/iREhzDNMyBC8SBSVVUkbznBvABczMvuX48W8+ucOSHp17V6dS5N/B\n8+fPKVeuHHfu3KF48eJ5X/APRa1WU7VqVRYsWEDbtm1zHTto0CDKli2bYwQqOTmZkJAQduzYQVhY\nGKdPn6ZZs2Y4ODigVqsxNTWlefPm1KxZM1shmVu3bhEcHExUVBSlSpWibt262Soizp8/n927d3Ph\nwoV3e9Ii/2lEZ0rkv4aY5ifyWfEooBSbBz2niVMjzFJvsnpGMEuWtAHg4MGDdOrUieDgYPr27UuX\nLl1QqVSM+N4dUzMTYq6bQ2wy2miQf7aCChdOXiM1Tb/oVZUm58LJvNWqTpx4qOdIAWg0sG/fHSZN\nCkAbLXqMtj+WDFBjlloJ33F/In0Zk1VC3bYyCfWGM8PfnkojDBgx5xGQkUYYHBydJZ2wYUM7vL3d\nqF3bgurV7wBqQMAwMIVklX4hrgo5diQD/kBP0tIMP6rARE6kqx8qlXLMzQ1RKuV5KiqK/PtYvXo1\nnTp1+lc7UqBV3po3bx49evSgUaNGjBs3jlOnTmXbI6ZChQpER0fnOJeRkRGVK1dm+vTprF+/nlOn\nTlGqVClUKhVSqZTHjx8zYMAAihcvTv/+/dm+fTuxsbGEhIQwfPhwWrVqxfbt27l58yarV6/GycmJ\ntm3bMn36dM6dO8fDhw/5448/mDRpEuPHj/+QL4uIiIjIfxpRGl3kg9K3uxV9u1uxZ88SJk+ezIAB\nnZDL5TRv3pxSpUoxcuRIkpOTKVOmDBERETg4OHDiRH2mTbvIrFl/YWiYIajw9ga9frOaGMj1G+gq\n5GnUb5a3WIVOHe8tli2LJSVlINpolBRtc2E5XaV7WKrwRvNKhrTFBPa0GMmaNf21DXeNTEio3hHk\nCtKjS0vPlGTHsgCiwm2AO8BllEoZINEJNKQLN6SkOKHRtELrTEkJE+yz7VH1gNeAGRSpTqnSks/G\nYclP/y6RfzexsbH/mRSy9u3b8+TJEy5fvsyZM2f44YcfePDgAa1bt8bLy4tGjRohCAKRkZGEhYXl\ne94yZcrw448/Zjn+6NEjDh8+zIYNG/D09MTQ0JCBAwdy8+ZNrKysdOM8PT0JCQkhPj6eUaNGERUV\nhYWFBTt27KBjx46F8txFRERERLIipvmJfBQEQaBFixb06NGDb7/9lgkTJmBqaqrrB9GrVy/c3Nz4\n/vvvdddERyfkuUEf3nMs84cuRZUmR1GAmimtYt9vbx1VAl+jf49BwJLnBBtWxFCS4eCkCApe/PkX\nxZztmLviIQvPlQNFpmiSSgMXEuG1Gm106yBwDhCQySwYOrQ+K1eeQK2OB9qgrc+y163ZRbqTZYoR\nmXpUDWG3lTPELoCmd0Eqp2u5e+xcXDnP5yoi8qHZvXs3a9eu5eDBtxUn/xs8ffqU3bt3s2jRIkqU\nKIGhoSGxsbEcOXJEz+F5X2JjYzEwMMDIKKuEtCAIn63oR2JiIkuWLKFnz56ULFmShISEz1YuX0Qf\nMc1P5L+GWDMl8llz48YNvvjiC4KDgzl79ixjxowhICAACwsLrl27RocOHbh9+7ZeT4b8sNP3IhdO\nXqN+s5p51kplZsSIP1i69JLucYkSLXj2rBraaFQ6As0lf7LHoAuZ9ykaDXRWjGX8rhbcvKthzB/u\noDAAdQrIDN/IwMdDajJgAwwASgIhGBrG07p1Gfz9o0lKKok2CrYTrbjFC2AJ8DcmuFNBUp4wwYDn\nBtbQ4hs46Qj1joKZC6hVBC1JzVd9lojIh+TGjRu0b9+e8PDwT23KJyUtLY3du3eTlJREnz59Prp6\nXnBwMHFxcbi5uX3UdXPi0aNHfP311zx79gxzc3OCg4NJS0vD2tqa27dvY2iYtf+QyOeF6EyJ/NcQ\nnSmRzx4vLy/u3r3L/Pnz2bJlCydPnuTIkSNYW1vj7e1NTEwMvr6+H+0Oa3BwNJcuRWBpaUmHDsbo\nq/cBqGkuOalzpl4KMC0NjqjhFVY0dK/O3bv3CH+apM0KVL2AMoNB9RM8M0TrHPVAG/FqCWxCqZRz\n9epQatVaSVKSAm1U6hzwFeACeAE3gLVAY6APFGkN9c3h/nhAApXmgiqZ9cNiGdDR5mO8VCIi2RIZ\nGUmLFi3o1asXkydP/tTm/Kfp1asX27dvJzU1Vc+R27hxI9WqVcPV1fWj2pOYmIitrS2zZ8/G09OT\nuLg41Go1AwYMoFWrVowcOfKj2iNScERnSuS/hihAIfLZs3DhQjp06EDbtm2pWLEibdu2pXHjxjx/\n/pz58+dz/vx5AgMDP5o9Li7WDBjgyvPncrL2lRKACwQKRqSi4J4G3FO17tY+Azm2RbZx7NgxHj0K\nY/6cNRgYDMfQZjFEhMGzykAToCZwGbgA3NEJNLi4WL8RblAhkRwFGgL30KYDyjE3t0ahGIBMdh5Q\nQJIMJBKwGwKP14PqFUgUuFUVo1Iin44///yTpk2b0r17d9GR+gwYM2YMoHWe0gkODmbAgAEcPXr0\no9tjbGyMmZkZDRo0QC6XY2FhgZWVFfPmzeOnn37i5cuXH90mERERkUJHEIQcf7SnRUQKn3v37gkO\nDg7CkiVLhNGjRwvOzs5CXFycMH36dKFOnTrCq1evPqo9QUFxAsQI8DrTT4wgl88XWrdeJTjzhVAM\nhEVyA+GZoZHQRbpaCAqK05sjKipeuHQpXIiKihfgsgAnBbgrwBMBonTnsrvmwIFHwpQpQcLZs1FC\nVFS84Od3X4DHAmwVZIqKQu1WJwWrWqECbTQCZYYKlPlGwDZBGD368sd8mUT+5WT+G84NtVotjB07\nVrC3txe2bdv2kawTyQ9o7wIJKpVKEARBmDFjhgAI9+7d+yT2TJo0SfDy8spyfOjQocLQoUM/gUUi\nBeFz3gfa29sLSqVSMDMzE0qUKCEMHDhQSEhIEARBEA4cOCC4ubkJJiYmgpWVldCvXz8hPDxcd+36\n9euFRo0aZTtvs2bNhDVr1ugex8bGCt99951gZ2cnmJmZCeXKlRNGjRolPH/+PIsdpqamgpmZmTBi\nxAjdOjKZTDAzMxPMzMwEJycnYfny5bq5Q0NDBYlEojtftmxZYc6cOXr2SCQSISQkRO/YtGnThH79\n+glbtmzRralUKgWpVKpnR2aaNm0qWFhYCKmpqXrHBw4cKEyePDnb1yJ97WHDhunmNDAwEBQKhc7m\nFi1aCM7OzsKGDRv0rp0+fXqOr/HnTE5/82+OZ+8v5XRCEJ0pkQ/M3r17BXd3d0Gj0Qiurq5Cnz59\nBI1GI4wYMUKoUaOG8PTp049qj7d3yBuHKkqAGEEi2Sp06jRUsLCwECpU6C8U5ahQU3JUsOSO4O0d\nkud8VateESSSB0LVqlcKZMfWrYEC+ArwSmjfb65gVRThxSlzIeG0Uug5Yr2A2QMBTAV4JUilv+e5\n8RURyQ9btwYKSuVMoUiR2YJSOVPYuvWm3vm0tDTBz89PWL58udChQwehUaNGQkxMzCeyViQnDh8+\nLADCV199JaSlpQlFixYVAOHcuXOfxJ6IiAjBwsJCt/FM59WrV4KDg4Owf//+T2KXSP54n32gRkgT\n0oS4vAe+Iw4ODsKff/4pCIIgPHnyRKhSpYowYcIEYefOnYK5ubmwbds2ITk5WYiMjBQGDx4sODg4\n6G7Url+/XmjcuHG282Z2plJTU4XatWsLHh4ewp07dwRBEITo6Ghh1qxZwh9//JHFjrd5e53r168L\nZmZmwo0bNwRB0DpTUqlU0Gg0giAIwpUrVwQTExPh2LFjumukUmm2zlT//v31jp08eVIoU6ZMtnaE\nhoYKMplMsLS0FHbu3Kl3LjdnKr9rnz59WrC2thaioqIEQRCEoKAgoWjRop/sJs778C7OlJjmJ/LR\niYiI4IsvvmDUqFF069YNiUTCgQMH+OOPP4iIiODXX3+lU6dOODg40KBBr1Yk6gAAIABJREFUg2x7\nuHwIlixxJCjIkMWLE9i+/RXffHOBp0//4s6dO9y5s5HzQfX437rKnAkqxZIljnnOFxhYC42mLIGB\ntfJtQ3R0AkOG7AecsSr9nPZlJtGkOljIYjGWJrG2+7dYmqvRJhuGYmgYRWjoq3d+ziIikPF3l5SU\nxuvXKSQlpTFkyD5dX7QXL17Qpk0bxo0bx7Vr12jSpAlHjx7F0tLyE1su8jZt2rTBw8ODjRs3Ur9+\nfQwMDOjSpQudO3fmxIkTH90eW1tbOnbsyMyZM/U+y4sUKcKmTZsYNGgQXl5eHD58GLVanctMIp8b\nAmoEsq+nimEXf1GLQBoQRFtSifgwNrypbSlZsiRt2rQhMDCQH374gSlTptCzZ08MDQ2xsbFh9erV\nmJqa8vPPPxdo/g0bNhAeHs7evXupUKECAFZWVkycOJHWrVtnsSMvXF1dcXFxITg4ONvnUatWLSpX\nrsyNGzcKPHdupH8eDBw4kPXr1+f7uvyu3bhxY3r27Im3tzegbdUwceJEnJ2d38XcfxyiMyXy0VEo\nFPj7+2Nvb88333wDQOnSpRk3bhytWrUiNTWVKVOm8Pr1awRBwM/P76PZ5uJiyogRDjRubMyOHVs4\ndOgQNjY2unMDBpTExcX0g60fGvoKAwMZcBcHl8fUrW7E6b/g+WvteRUKylaKAHoB84CXn0XzXpF/\nNhl/dxkoFDKdoz58+HDs7e25fPkyK1euZPTo0dnKc4t8HqxatQoDAwOqV69OQEAAu3btYtOmTfTv\n35/IyMiPbs/UqVO5du0aDRs2RJOpW3qjRo04d+4cZcuWZdKkSbRu3ZqoqKgc54mJiRHrrD4DNKTw\ngO+4gSt/4cpTFus5VYkEEc4sBFKBNFJ4RAjfZpknnis84/+IYScaUt/LpsePH3P48GFMTEx4/Pgx\n3bp10zsvkUjo2rVrgWsHjx8/TuvWrVEqle9lXzqXL1/m/v371K5dW+94utMSEBDA7du3KVeuXKGs\nl87GjRvp168fffr0wc/PL9eG4u/KnDlzuHTpEl27diU1NZXRo0cX+hqfK6IzJfLRsbGx4fHjx7x+\n/ZoKFSrw/+ydd3xN9//HnzdT9pAgQ2ITo7aIXYISfpGYQcxGoyhVVXvUXqVGUTNWjMaOJESIGiE1\n0i+xooLEypIlO5/fH6nLlaQSktzgPB+P+2jvZ53XuTnuPe/zeY/ly5fz/PlzJk6cSMOGDencuTNR\nUVFoamry/fff4+7uzqVLl969cBESGvoPpqbmZGeX7A1jpUqGpKdnAXcJv2lEDfNM+tvD5HU5/epk\nEH4zGRWV8sBR+vRphImJNitWrGDSpEk4ODhQoUIFHj16VKK6JT5uXl93r8nIyKJSJUOOHz9OUFAQ\nv/76K2pqUp33jwErKysGDRqEmZkZlStXBqBTp04MHjyYgQMHlvgOUE4x9lPo6Ojg4ODAP//8I++r\nWbMmP/74I5cuXaJZs2Y0btyYPXv28OJFjiGfkJDA4sWLsbGxoWrVqlSuXJkFCxaUqH4JRSJYSAJn\ngCwEGTzHgzhe15h7ydtJpLJJ5R6C19ddNHsJYwRPWE0E87lD//cyqHr06IGxsTFt2rThyy+/ZMyY\nMUDOTtXbmJmZER0dXaj1Y2Ji8lwrPx1GRkYYGxuzadMmed+FCxcwNjZGX1+f5s2b4+rqqmAsCSEw\nNTVFW1ubli1b8u233xZpoe2zZ8/y8OFD+vTpQ6NGjahWrRq7du0qsvVfoaOjw5o1azhw4ACbN28u\ntXXvigPJmJJQCpaWlly+fJnff/+d8ePHU6NGDbZv38727dtp0qQJLi4uAPTp04c1a9bQtWtXBg4c\nWCIuf56e/8PBYRd370Zjbb0CT8/rxX7MV5ia6vyb5U+NpOjDDNs9kUnDynD0goyAEA3c/hhFRmIa\n2dmjgQw8POqirz+D77//nkWLFnHs2DGePXuGlZUVT58+LTHdEh83b153+vqaaGmpsWFDNw4e3IWr\nqyu//fYb2traypYpUQgmTZrEb7/9Rnx8vLxt9uzZZGRksGLFihLXI5PJ8PPzw9bWlp49e+bqV1NT\nY968eWzYsIHNmzdTsWJFmjdvTtWqVbl27Rpbt25l9+7d+Pr6snTpUtLS0kr8HCRySOQ8gteffzYp\n/xpXOahTHtlbt5eq6CEjZ/dbIIhgIYJUIBtBKmmEE09AobUcOnSI2NhY7t+/z6pVqzA1NQVyCmm/\nzZMnTwpdRLts2bJ5rpWfjri4OGJjYxk+fLi8z87OjtjYWBISEnj69CnXr19n6tSp8n6ZTEZMTAzJ\nycksW7aM06dPk5mZKe9XVVXNde+TkZFR4Dp227Zto1OnThgZGQHg4uKCh4dHgeYWljp16iCTyahd\nu3axrF9akYwpCaUhk8lo164dQggCAgL45Zdf6N69OzNmzODq1avy3RVHR0cuX77MgQMHil3Tq9iR\ntDQdsrPjSElJVIgdKQlcXOry4ME4zpwZyszRo1gUuB3z2n0ZMNec5tX6Ex/f5t+RGYA+SUmDcHae\nwP79+7l+/Tpdu3YFkOJZJArFq+vO39+VBw/GERq6l40bN3L06FG6dOmibHkShaRq1ap06dKFJUuW\nyNvU1NRYt24dCxculO/8lCQaGhr0799f7q7n6urK+vXrFcZ89dVXcjekBQsWcOHCBXbt2sXDhw/p\n2rUrZ8+epXbt2iXq/i2hiDqKBokMddR5vXujT1t0aYYK2qigg4wyWLPojRnZ/7oAvkaQTRaJhdby\ndkxPzZo1sbS0ZN++fbnGeXl5YW9vX6j17e3t8fPzIyUlpVA68sPU1JSePXty5MiRXPNlMhnjxo1D\nU1OT3377Td5nZWVFeHi4wvj79+9jbW39zuOlpqayd+9eAgMDMTMzw8zMjBUrVhASEsL//ve/AmmW\neDeSMSVRKmjUqBHBwcFER0cTFBREr169FL5MUlJS0NbW5urVq8Wq43XsiDagCzxTiB0pKUxNdWja\n1AIbG1NWLOxF8OldtG1jy6RJzkA8cB2wBmSAIVFRX+Lk5ESdOnUYPXo0M2bMKPBTKwmJV7y67tLT\nX7B+/XoOHDhA06ZNlS1L4j1ZuHAhv//+u8L3Zq1atejTpw/dunV75w1icZCVlUV2djaTJ08mOTmZ\nyZMn5+mWXKZMGb788kuqVavG7t275e5bbdu2ZejQoQwZMoSWLVvi4uLC/Pnz8ff3f+94qpcvXxIW\nFkZycsk9NPuYsWS63EhSQQs1TCjPMHm/DBWqsIbKrKQiM7DhAAa0faNfFR0akpNI6TW6FM13zZIl\nS5g7dy67d+8mLS2Np0+fMnz4cBITExUKRWdnZ5OWlqbwehtXV1cqVqxIz549uX37NkIIYmJiWLBg\nAb6+vgXS86ahFRMTw4EDB6hbt26e/ZCzq7xo0SLS03MMzr59+zJ37lwiIyMRQuDv78/Ro0dzxYXl\nxYEDB1BTU+PmzZuEhIQQEhLCzZs3adWqlUI9uszMTIXP4UO8gIoiYcbHhuQAL1FqUFdXx9bWltDQ\nUGbOnEmDBg1wcXHhiy++oFatWixZsoTevXtTvXp1duzYQYUKFYpcw+vYkQfklGuxkseOKBOZTIan\npycNGrTn779/AOIAl397VXBxsSIoKIjff/+d1atXSzsJEh9EWFgYderUwdzcXNlSJD4ACwsL5s+f\nz3fffceZM2fkMQyrVq2iR48erFmzpsSDxG1sbHBycmLNmjX8+eefhIaGEh8fT8WKFXONFUKwYsUK\nli5dyokTJ3B2dkZXV5ehQ4fSoUMHHj58yIMHDwgJCWHOnDlcuXIFXV1dbGxssLGxoUaNGqSkpPD4\n8WOePHlCYmKi3JjLzMwkKiqKx48fk5aWhqmpKXp6egQEBFC+fPkS/Uw+NrSphQ1HSOQcMjQwoD2q\nKBaQlyFDnxb5rlGFVYQzgSSuoIYhVsylDJUKpSO/mJw+ffqgpaXFnDlzcHNzQ1NTk86dO3Pu3Dm5\nqxvkxDK9cl9+tTOUkZGhsK6Ghgb+/v7MnDmTjh078uLFC8qXL4+joyO2trbycd27d0dV9XUSn44d\nO+Ll5QXkJJXQ19cHcgpZ29vbK7javn0eDg4OGBsbs2HDBkaNGsWMGTOYOXMmrVq14sWLF1StWpVd\nu3YVyJVu27ZtDBs2DAsLC4X20aNHM3bsWBYtytkxXLRokfz/AVq2bKnwnVEYPqdYqVfI/suClMlk\n4nO0MCWUh5ubG/r6+ixevJj169fj7e2Nt7e3vD89PZ2pU6dy6dIl/P39i2X3xdPzOq6ug1FTM0NF\nxY5Nmxxxcan77oklQGRkJNWr/0RKijXgBuhhbPwn0dGOmJmZ8fLlS5YuXcqIESOULVXiI2bq1Kkk\nJCSwatUqZUuR+ECysrJo2bIlTk5O/PTTT/L27du3s2fPHo4ePfofs4uHly9foqOjw9y5c/nll1+I\njIzMlR1SCMH333/PyZMn8fb2xsrKChcXFxo1asSPP/6Y57pCCCIiIrh58yY3b97kzp076OjoyN2b\nDAwMUFFRQVVVFTU1NUxMTDA3N8fIyAiZTMbPP/+Mp6cnZ86ckcfefO7IZLLPcqdB4vMlv2v+3/Y8\nLUXJmJIoVVy9epVvv/2WjIwMZs2ahaurK5MnT2bs2LFoamoCOTcHzs7OvHz5kl27dhXLj16VKtWY\nN28d9vZ2mJrqvHtCCbN27XU8PR/i4mLFyJF1ycjIoFKlStSvX5+nT59y5coVZUuU+AgRQjBjxgzW\nrl3LxYsXqVq1qrIlSRQBERER2NrasmHDBnlMZWxsLLVq1WLFihX06tULDQ2NEtV0/fp14uLiaN++\nPX5+fujq6vLixQvKlCmDjo4OGzdu5Nq1a/j6+mJgYADA3bt3sbOzIyAggC+++KJYdH3zzTcYGxtL\nGQP/RTKmJD43JGNK4pNACMGmTZuYNGkSVatWRV9fn3LlyrFjxw759nFmZibTpk3D09OTP/74o0jj\nOoQQqKurk5KS8lHFHT169AgrKyvg8/RZlvhwli5dyrZt2zh58qT0ZP4TIyAggA4dOhAdHS1PThMQ\nEMDs2bOJiYnh8OHDVKny7mLkRY2DgwPHjh2jfv36mJqakpKSwsuXL7GysmLbtm1y96hXeHp6MmbM\nGPr370+TJk1o27ZtgQLxC8qdO3ews7NjxowZ9OvX77N3+ZOMKYnPDcmYkvikuH37Nl27dsXV1RUf\nHx+cnJyYNGmSwpj9+/czcuRIAgICqFOnTpEcNzk5mXLlyn2Uwcg///wzjx49YsOGDcqWIvGRcffu\nXVq0aMHVq1extLRUthyJIubUqVOMGTOGkJAQhdgOIQTLly9n8+bNufpKAiEEGRkZhdoZe/DgATt3\n7iQkJISAgABsbW05cOBAkT38On36NFu3buXYsWOsXLmSfv36Fcm6HyOSMSXxuSEZUxKfHI8fP6Z2\n7dp07tyZmJgY/P39c43ZsWMHU6dO5fz587mCLN+HJ0+e0KhRowLVligu0tPT8fb25vTp04SFhREY\nGIiuri5ly5ZFXV2d8uXL07dvX3r16pXrya2ExPswYsQILCwsmDlzprKlSBQDf/31Fz179uTixYu5\nkvcIIWjRooV8x+djIjMzE0dHR6pXr17k9bOuXLmCi4sLLVq0YNWqVejq6hbp+iWJEILo6Gh0dHTQ\n0tIqcJIAyZiS+Nx4H2NKSo0uUaoxNzdn7NixPH36VCGN55sMHDgQd3d3nJ2dFQrdvS8PHjxQahaz\nAwcOULVqVZYvX46Pjw/Hjh0jOTkZmUzGnj172LJlC25ubhw5coSqVavi5eXF0aNH2b59u1JSHUt8\nGjx48AAbGxtly5AoJho1asTQoUNp3LgxZ86cUeiTyWTMmzePmTNnfnQ3zmpqauzYsQNvb2/c3Nx4\n+fJlka3dqFEjLl++TGpqKi4uLh/dZ/Mm+/fvx8zMjLJly9KoUSPpt0JCogj5JI2p58+fU6dOHYWi\naDdvRuHhcY2bN6OUqEzifZg9ezaBgYH/aeBMmjQJXV1dtmzZ8sHHS0hIQEtL64PXeR98fX1xc3Oj\nfv36qKuro6Ojw6lTp1BTU+Pp06ds3ryZwMBAdHR02L9/P3v27GHBggWsWbOG7du307Bhw2KvxSXx\n6eHt7c3//vc/OnbsqGwpEsWEiooKs2bNYtOmTfTu3ZtNmzYp9Ldu3Zr79+8rSd2HYWRkxOnTp9m4\ncSN///13ka6tq6uLpaUl//vf/z46A+TSpUv8/fffBAcHExUVRfv27Xn58iW1atVi6tSpypYnIfHJ\n8Em6+YWFhVG9enWGDx/Oxo0b6dPnV/btCwJqAjJGj27GqlVSHZ5PDU9PT1avXs2ZM2c+yO8/NTUV\nCwsL/vzzzwLVcSgomZmZZGdno66uTnx8PJmZmZiYvK4kf+XKFRo3bgxA/fr1mTBhAr1790ZTU5OM\njAyOHj3KvXv3ePDgAWfOnEFTUxNnZ2datGiBTCajVatWeHp6MnbsWKZPn86YMWM+y3oPEoUjODiY\nbt268ccff9C6dWtly5EoAe7evUuTJk2IiIhAT08PyElXbmxsTHJyconHTRUFv/32G3v37uXUqVNF\n/r3XvXt3ZDIZe/fuzZXCvbSQmZnJ3bt3uXHjBjdv3iQlJYV169ahr6/PgwcPkMlkBAQE0K5dO549\ne0bNmjV5+PDhO93EJTc/ic8NKWYqD27ejKJ27RZAGNCGnIrbDQgN/QkbGylb1adEVlYWbdu2xc3N\njcGDB3/QWqtXr+bYsWMcO3bsvdcQQhAcHMzevXu5cOEC165dIyMjg6ysLLS0tNDQ0OD06dMKKX4j\nIiJISEigVq1aqKjkv3GcmZnJiRMn8PHx4a+//iI8PJzly5fTt29f7t27J89C5eTkhL29fZFmu5L4\ntNi2bRt+fn7s3LlT2VIkSpCuXbsyaNAgheQK1tbW+Pn5UatWLSUqKzz+/v7069eP06dPU7du0dcE\nTE9Px9XVlejoaA4ePCg3QNPT0zl48CDe3t6sX79eqYbWlClT2LJlC7a2ttSuXRtdXV2qVKlC3759\nycrKIjExUaFgbbNmzfj111+xs7P7z3UlY0ric0OKmcqDS5ciAUegMyCAk8Cv9OnjSExMjFK1SRQt\nKioqRRIzBTB48GDOnDnz3m4dQgh69eqFi4sLurq6zJkzh6dPn5Kenk5qaiqJiYnY2tpy7949hXmW\nlpbUrl37Pw0pyIkT6NKlCytXruT8+fOsWbOGadOmcfz4cVRVVTl37hytWrUiICCASpUqMXbsWG7f\nvv1e5yLxaZOUlERERESRxppIlH4sLS0JCgpSaBsyZAjjx4//qG6e7927R9++fdm3b1+xGFIAGhoa\n7Nq1i2rVqtGmTRsWL17MtGnTqFSpEr/99huBgYFKr+2nrq7ON998w8GDB5k/fz5TpkyhX79+yGQy\n1NTUFAwpADs7O/744w8lqZWQ+MQQQuT7yun+uAkNfS5g1huvGQIqCkD4+/srW55EEXLw4EEBiOjo\n6CJZr3379mLhwoXvNTc8PFyUK1dOpKen59n/+++/iypVqhSZViGEWL9+vWjTpo0wMTERo0aNkrcv\nW7ZMfPHFF8Lc3Fw4ODiI0NDQIjumxMfPy5cvxcCBA0WHDh1Edna2suVIlBDNmzcXJ0+eVGhLT08X\njRs3FgsXLsz3u6u0kJqaKkaPHi3q168vfv755xI5ZnZ2tvD09BTff/+9GD9+vLhx44YQQgh3d3ex\nYsWKEtGQFzExMaJ27drCw8OjwHOePn0qypUr9877oNJ8H2htbS20tLSEnp6e0NXVFXp6euL8+fNC\nJpMJPT09hfa9e/cKIYQYPHiw0NDQEHp6eqJs2bKiU6dO4tatWwrrPnnyRLi5uQlzc3Ohp6cnqlat\nKoYOHSpu374thBDi9OnTwtLSMpeedu3aiU2bNgkhhHjx4oUYNmyYqFChgtDX1xc1a9YUixYtUhi/\nePFiUb16daGtrS2sra3F5MmTRVpamrx/8ODBQiaTieDgYHlbWFiY+NdrTAghxI0bN0SnTp2EsbGx\nMDIyEk2aNBE+Pj4F1vlKq7u7u6hQoYLQ0dERX3zxhdiyZUuueVu2bBH16tUT2trawszMTIwcOVK8\nePFCCJHzb+DVZ62hoSHU1dXlf4OuXbuK8PBwIZPJRFZWVoHPTQghjh8/Lr788kuhp6cnTExMRMOG\nDcXixYsVPqeiJr9r/t/2PO2lT35nysbGlNGjm73RosKoUes4ePAg9vb2tG3btsgDViWUw/Pnz2nc\nuDHGxsZFst7WrVtZs2YNnp6ehZ4bGRlJ5cqV86x78vTpUyZOnIivr6+8eGZRMGLECLZt20aFChU4\nceIEa9as4ddff8XKyoqpU6cybtw4vL29Wbx4MUIIjh49ysGDB7l27RqJiYns37+fP/74Q9rB+szQ\n0tJi69atREZGEhgYqGw5EiVEtWrVePTokUKburo6u3bt4siRI9StWzdXf2liw4YNhIaGMn78eCZM\nmFAix5TJZPTr149ffvmFZcuWyWNqzc3NiY6OLhENb5KRkYGHhwd2dnZ06dKFQYMGFXhu+fLl2bt3\nLy4uLpw7d47s7OyiFyiyIDOh6Nf9F5lMhre3NwkJCSQmJpKQkIC5uTkymYz4+HiF9t69e8vn/PTT\nTyQkJBAZGYm5uTnDhw+XrxkbG0uLFi1ISUnh3LlzJCQkcOXKFdq2bcuJEycUjv1fjBs3juTkZG7f\nvk18fDyHDx+mWrVq8v4xY8awceNGduzYQWJiIj4+Ppw8eZI+ffooHKNs2bJMmzYt13m/onv37nTu\n3Jlnz57x/PlzVq5cqRAH9y6dGRkZdOjQgUePHnHx4kXi4+NZvHgxkyZNUig1sGzZMiZPnsyyZctI\nSEggKCiIBw8e0LFjRzIzM1m7dq38s361K5qQkEBCQgLe3t65tBTk3Pbt20fv3r0ZOHAgDx8+JCoq\nij179hAREVH6vpvys7LEJ7Iz9YrQ0Odi69arIjT0uRBCiJEjR4qhQ4eKdevWibJly4rY2FglK5T4\nUNLS0kT9+vXFypUri2zNq1evChMTE5GSklKoecuWLRNDhgzJs2/dunWidevWRSEvF/v37xedOnUS\n/fr1EyNHjhRjxowRTk5OomfPnuLbb78Va9euFVFRUeKPP/4Q5Pi9ijp16ghAtG/fXjg5OYny5csL\nW1tbsXnz5mLRKFE6adCggbh48aKyZUiUEPPmzRNjx47Nt3/p0qWiatWqIjIysgRVFRxnZ2exfft2\nZcsQQggxe/ZsMW3atBI7XlZWlli5cqWoWLGi6NChgzhx4sR77yrv2bNHVKpUSdjY2OTZ/5/3gdmZ\nQuR33KebhDinKcQ5NSH+qiFESvh76fsvKlWqlGt3NTw8XKioqMh3QN5myJAhYvr06fL3x44dE7q6\nuvL3U6dOFQ0aNPjP454+fVpUrFgxV/ubOz5169YVhw4dynP+3bt3haqqqvjrr78U2h89eiQ0NTXF\nqVOn5Fp/+OEHYWZmJs6cOSOEyNm9UVFREUIIER0dLVRUVER8fPx769y4caMoX758rnucPXv2CF1d\nXZGYmCgSEhKErq6u+OOPPxTGJCUlCVNT01y7WLNmzRKurq4KbW//Xd51bkIIUbFiRbF8+fI8z604\nye+a5z92ptSUZ8aVLDY2pgoJJ5o2bcqiRYuIjIxEXV2dlJSUXD7FEh8XGhoaHDhwgBYtWnDnzh2m\nTZtG+fLlP2jNBg0a0LRpU1asWMGkSZMKNOfEiRMsWbKE/fv359lvaGhYbPEpTk5OODk5vXNc+/bt\nWbVqFePHj+fatWsIIeS7aGlpafj4+DBo0CCGDRvGhg0bGDp0aK4MX1FRyYSHv6BSJUMA+f+bmuoU\n/YlJFDtGRkbExcUpW4ZECdG1a1d69erF8uXL83x6/cMPP/Dw4UOWL1/OkiVLlKAwf+Lj41FVVVVq\nYfU3kclkxbOzkwdCCMaOHculS5fw8vKiadOmH7Renz59sLa2pnfv3qSlpaGpqfnuSdmpcHsAxB4C\nmSpY/ARWs+HVdZR0Ff4ZAyIt531qGNx0gIbXFdeJ/xMSzoB6eSjnCioFOHYBEQWI+0tOTpbHwr3i\n5MmTBfoNfRfNmzdnypQpxMbG0qpVq1zHqFixojx77yssLS1p3rw5J06coF27dgBoa2szZcoUpkyZ\nwp9//qkwvmzZslSrVo0BAwbw9ddfY2dnR7ly5Qql09/fny5duuRKntKzZ08GDBjAhQsXyM7OJi0t\nLdfnoqOjQ9euXTlx4gRDhgwp1HHfdW63bt0iMjISZ2fnQq+rDD55N7/8aNOmDZmZmXTu3FnpRVol\nio7KlSsTEhKCmpoatWvXZs2aNR+85vr16/n111/p2bMnq1atIjw8XN4nhODZs2ccO3aMSZMm0aRJ\nE9zc3Ni8eXOeWZJiYmIIDAwsli8IIQRPnz4lISF/twp/f388PDy4desWvXr1on379gwYMEDBHVFT\nU5MePXrw7NkzJkyYwJw5c+jcuTOxsbEAxMXFsWKFD1ZWP2Nv74Gl5XIsLJbRseN2rK1X4Ol5Pb/D\nS5RiGjduLLk8f0bUr1+fjIwMQkJC8h3j5ubG7t27iyyxz4eSnZ3N0qVLqVKlCkFBQQo3qMqkZs2a\nXL9eMt97U6dO5fz58xw/fvyDDalXNGvWjKZNmzJjxoyCTfhnPMT5AFkg0uHxLxC163V/4kVQMGay\n4WVojtvfK57+DqFfwcMZcH8s/N0CstMLrb1Hjx4YGxtjbGws/10VQmBqaoqxsTFGRkYYGxsruK8v\nWbIEY2Nj9PX1OX/+PNu3b5f3RUdHU6FCBfn7I0eOYGRkhL6+Pl999VWBda1evZqBAweyZs0a6tSp\nQ/Xq1fH19ZUfw8zMLM95ZmZmuVxGR4wYwcOHD/Hz88s1/tSpU1SuXJkJEyZgbm5Ou3btCAsLk/dH\nRkbKP59Xn8e5c+cUzjcvLaqqqpiYmBAdHU10dDQmJiZ5JsbKS28C3vnkAAAgAElEQVRhyO/cXiWI\ne/Nv4eLigpGRETo6OqUu++xna0xVrVqVsLAwxo8fj4aGhrLlSBQh5cqVY/ny5QQHB7N06VImTpxI\nSEjIe2eoqlixIteuXcPZ2ZmQkBBsbW1ZsmQJXbp0QU9Pjzp16rB06VI0NTVZvnw5d+/epUuX3HXM\nEhISMDExYe3atfTs2fNDTzMX3bp1o2LFipiZmWFqasqAAQO4deuWwpgxY8YwadIkWrRogZmZGX5+\nfuzfv5///e9/CCGYOnUqtra2fP3119StW5d9+/ZRr149Lly4IE/bbmFhwfjx/UlN/Y2EhKmkp18h\nI0MQH59GSkomw4cfIioqucjPT6J4sbCwKH1+6BLFhkwmY8qUKXTq1Ilt27bl+f1Yt25datSowapV\nq5SgMDdnz55l3bp1BAUF8fDhwyLZQSgKWrZsWXxxR/8ihGDmzJkcOnQIPz8/DAwMimxtmUzGunXr\n2LZtGxcuXHj3hBd+IN7IdJudDHFvlBHRtMjZsXoTVYPXbULA/e8h+yWQnfPflDs5O12F5NChQ8TG\nxhIbGyv3BpHJZMTExBAbG0tcXByxsbHUrFlTPufHH38kNjaWBw8eoKWlpWBolS1bVmHHs3v37sTF\nxbF8+XLS03OMPTU1NTIyMnJpycjIkD+Y1NTUZNKkSQQHBxMTE0OfPn3o06cPL168wMTEJN9d1SdP\nnijUn4Qcr5vp06czffr0XOPNzc1ZuXIld+/e5cGDB2hrayuUhrGwsJB/Pq8+j5YtW8r789OSlZUl\nN6JeGVV5Xd956S0M+Z3bq3jyN7V5enoSFxdHo0aNyMrKojTx2RpTEp8+VapUISAggMzMTJycnLC0\ntKRt27a50gEXhPLlyzNgwAA2btzI5s2buX79OkOHDiUiIoLo6GgCAgKYPXs2rVu3zjPpBIC+vj4G\nBga4u7srfLEXFVWrVsXY2JhZs2YxcOBAdu3ahY2NjcKYpUuXYmBggJ2dHQMGDKBLly706dOHr776\ninbt2uHl5YWzszPly5fn4MGD+Pv74+DgwOHDh/niiy9QVVUlMzMLmUwFePVjqfg0UV1dlfDwF0V+\nfhLFi76+PvHx8cqWIVGCfPPNN/j5+bFkyRLmzJmT55h169Yxb948rl27VsLqchBCsGvXLlxcXBg7\ndiz9+/enevXqStGSHxYWFujp6RVb8p7U1FRcXV05duwYJ0+e/KCb1/wwNTVl0qRJbNq06d2DNd7a\nyZCpg2bF1++NHMDgS1DRBVU9UNGGGjvemJCd4yqoQDZkFv53I7+HpAV5eGppacmKFSv47rvvSEvL\ncUns0KEDBw8e/M95VlZWREdH53LXf/DgQZ41HXV1dZkyZQpJSUncv3+f9u3b8+jRI/766y+FcY8e\nPSIoKAh7e/tcawwdOpQXL17kGz4AOdfhqFGjCrVLam9vj4+PT64yMH/88QdlypShefPm2NnZoamp\nmevYSUlJ+Pj45Km3MOR1bjVr1sTCwuI/z7dUkV8wlfjEElBIfN5kZ2eLf/75R2zbtk0YGxuLKVOm\niMTExBLVkJmZWaSp2/Pi7Nmzwt3dXbi6ugoPDw95itR38ddffwk1NTVx/Pjxd44NCgoRmprfCxgn\nYPxbpQdmCS2tueL586QPPRWJEmbGjBkKgdkSnw/h4eHC2NhYREVF5dm/e/duYWJiIo4ePVrCyl6n\nd96yZYvw8vISmZmZJa6hILi4uOSZTvpDCQoKErVr1xZ9+/YVycnJRb7+m1y5ckXUrl1boS3P+8Ck\na0Jc0BPivLYQ53WECLYSIj1GcUx2thBxJ4R4tkOIl3dzrxHSWohz6kKcJed1XluIl7cLpTe/BBQy\nmSzf6+TtBBRCCNG0aVPx66+/CiFykjpYW1uLgQMHinv37gkhhEhISBCjR48WX375pXxOy5YtxejR\no0VSUpJIS0sTixYtElWqVJGn7J4zZ44IDg4W6enpIjU1VcydO1cYGxvL/4bffvutqFGjhggKChJZ\nWVni+vXrolmzZqJ79+75at25c6coW7asPElDXFycmDlzpggLCxPZ2dkiKipKODs7i86dOwshCpaA\nIi0tTTRu3Fg4ODiI8PBwkZGRIXx9fUX58uXFsmXL5HMWL14sKlSoIHx9fUVGRoa4f/++6Nq1q2jS\npEmuMgr5JaB4MzX6u85NiJwkGAYGBmLjxo0iLi5OCCHEnTt3RPXq1QtVBqCw5Gf78DmnRpeQgJxt\n/8qVK+Pq6kpISAgPHz6kSpUqTJw4kX/++adENLxyEXgzbWlR07JlS9auXcu2bdsYNGhQgX28Gzdu\nTEZGBh07dnznWFvbL9iyZRhaWibo65uioaGKuroMfX1NtLTU2LTJUUpC8RFy4cIFatWqpWwZEkrA\n2tqaXr168csvv+TZ37dvX+bPn8+vv/5aIu419+/fZ9SoUXzzzTeMHz8eR0dHhgwZgrOzc65EOKUF\nW1tbLl68WKRrrl69GkdHR2bMmIGnpyfa2tpFuv7bmJiY8OzZs3cP1KkPDUOhyiqouh4aXAf1t0qS\nyGRgaA/lBoBWHrFtNgdB/8ucXSsNy5z3WjUKpTe/tN8ymUwe56Snp4e+vr5Cmu+3mTBhAkuWLCEj\nI4OyZcsSFBREmTJlaNWqFfr6+jRq1IikpCTWrl0rn7Nnzx6ePXtGtWrVsLS05NSpU3h7e8vDRmQy\nGUOHDsXU1BQLCwtOnjzJsWPH5H/DNWvW8PXXXzNw4ED09PTo2rUr7du3Vyik/Pb5ubi4YGZmJm/X\n0NAgPDycjh07YmBgwBdffEGZMmXYsmVLgT83DQ0N/P39qVixIra2thgYGDBhwgQWLFjA+PHj5eN+\n/PFH5s+fz4QJE+TeLdbW1vj7++frjfNfx32bt88NcpKj7N27l+3bt2NlZYWpqSn9+vXD3d1dnuq+\ntCAT/7EV+m/xrBKUIyFRcty9e5f169ezdetWLCwsaNiwIW5ubgr+xEV9vLZt2xIZGfnO2g8fA1I2\nv0+Hq1ev4ujoyN27dwuWzUvik+P+/fs0adKEZ8+eoaaWO9Hvy5cv6dixI4MHD2bEiBFFfvxr166x\nadMmAgICePr0KSNHjqRChQqUK1eOXr165Rn8Xpq4cOECo0aN4sqVK0WyXnx8PB06dGD69Ok4OjoW\nyZrvYsuWLfj4+LB37155m0wme+94YwmJj5H8rvl/2/O8eftsUqNLSLxN9erVWbp0KfPmzeP69euc\nO3cOV1dXKlWqxODBg2nfvj0VK+b4gQsh8PPzY9++fTx79ozWrVvTq1cvqlatWqBjPXz4EHt7e9zc\n3HIZUrdv3yYrKwtjY2Pi4uKoVavWR2FsmZrqKBhOkhH18VKmTBk0NDQkQ+ozpnLlylhbW3Pu3Dna\ntm2bq19bWxt3d3eOHDlS5MbUvXv3aN++PWPHjmXnzp3UqFGj2HdhipqGDRty+/ZtXr58+d7ak5KS\nuHHjBh4eHuzZswcHBwfat29fxErzx8/Pj1atWgE5v3keHh4ldmwJiY8ZyZiS+OzR1NSkcePGNG7c\nmJEjR7J7926OHDnChAkTqFGjBs2aNSMgIIDs7GxGjBiBmZkZJ0+exM7Ojv79+7Nw4cJcNRreZu/e\nvTx8+JDdu3ezaNEiypQpQ7169cjIyCA0NBQTExNiYmLQ1dVFJpMxd+5cBg8e/FEYVRIfP4GBgZKL\nnwQuLi5MnDgRb2/vPJMcZGdnF0uNvJ07d+Li4sLMmTOLfO2S4pVb2IYNGxg7dmyh5z969Ih69eph\naWlJnz59CAkJwdLSshiU5k+9evWYNWsWnp6eZGdnl7qMaRISpRXJzU9CIh8yMjLw9fXlxo0bNGvW\njC+//FLBuImOjsbNzY3k5GQOHDiAjk7+OzNZWVkcPnyY1NRUeW2QR48eoaamRqNGjeRzhRBcvnyZ\nIUOGUK5cOdatW0eNGoXzI5eQKAxPnz6lQYMGHDlypMjq1kh8nIh/yyPs3r2b7du353J5HjZsGPHx\n8Xh5eX3wseLj4/Hx8WHt2rWEhYWxc+dOeaHSj5W7d+9iZ2f3XjWwfv75Z54+fcpvv/1WTOoKxsuX\nLwkODiYuLo5u3bqhrq4uuflJfFa8j5ufZExJSHwAmZmZfP3119y7d4+jR48WWe2P9PR0vvnmG27e\nvPleqdwlJArCxYsXGTNmDJ06dWLu3LnKliNRSjh06BDu7u4MGTKEWbNmyd0/X6XOjoqKeq91IyMj\n2bVrF8eOHeOvv/6iVatWDB06FCcnpwIHsZd2li9fzsGDBzl16lSh4rwcHR0ZOHBg6Qusl2KmJD4z\n3seYKt0RnRISpRw1NTU2b95M/fr1adu2bZFlBtTQ0KBt27Z51qyQkCgqDh8+zPXr1xk4cKCypUiU\nIhwdHQkJCSE0NBQ7OzueP38OwKxZs0hPTyc6OrrQax4/fpzGjRtz9+5dfvjhB549e4aPjw99+vT5\nZAwpgO+++47k5GSOHDlSqHnVq1cvscyyEhISRYsUMyUh8YGoqKiwatUqVq9eTbNmzeRJLGrUqEGH\nDh3kqVILy+3bt9HS0ipitRISr5k3bx46Ojr88MMPeHt7K1uORCmiXLlyHDx4kOnTp9OxY0dOnTqF\nsbExbdq04dixYwwaNOidaxw7doxjx46RlJTE8ePH2bNnT57JLT4lVFVVcXFxwcfHp1BZ+GxsbPjz\nzz+LUZmEhERxIbn5SUgUIffv32fbtm3ExMRw+fJlnjx5wqhRo2jcuDFt27ZFJpMRERFBhQoV8kw/\n/Cbm5uacOXOm0L73EhKFIS0tjRo1auDl5UWTJk2ULUeilCGEYOLEiZw5cwZ/f398fHzYtGkTfn5+\nucZFREQQGxvLP//8w759+zh//jwjR45EV1cXJycnzM3NlXQWJculS5cYMWIE165dK/Cc06dPM2PG\nDM6cOVOMygqP5OYn8bkhpUaXkFAylStXVshI5e3tjb+/Pxs3bkQmk1G7dm158HZGRka+BlVqairR\n0dEFTr0uIfG+aGpqoqqqKu2CSuSJTCZj8eLFfPPNN/To0YNvv/1WXoD8Fffu3aNfv35ERERgamqK\nubk5X331Fb/99huGhoZKUq48vvjiC+7cuUNqauo7M72+wtjYmBcvXhSzMgkJieJAMqYkJIoRBwcH\nHBwcWLZsGZcvXyY8PJy4uDgCAgJ48uSJvI7V22hoaKChoUFiYiL6+volrFric0NLS4u0tDRlyygR\nbt5M4tKlRJo108PGRlfZcj4KZDIZa9eu5ZtvvmHEiBHExsaycuVKMjIyuHbtGr6+vowZM4bp06dL\n5RzISZNeo0YNeZKNgnDnzh2MjIyKWZmEhERxICWgkJAoAVRUVGjatCm9e/fGx8eH/v374+zsTHh4\neJ7jHz16RHJyMhkZGcWuLT4+nnbt2lGxYkV8fX0BePLkiRQM/RnRvHlzTp06pWwZxc6YMfeoXTuN\nIUPUqF07jTFjpGu8oKiqqrJx40ZWrFgBwI0bN7h9+zbt27fHy8uLGTNmFMqQysrKKpHvN2UxfPjw\nQmXI/OWXXxgzZkwxKvr0qFSpEtra2hgYGGBsbEyrVq1Yv369govW+fPn6dChA/r6+hgZGeHo6MjN\nmzfl/YGBgaioqDB69GiFtVu3bs22bdtYsGABenp66Ovro6WlhZqaGvr6+ujp6VGvXj0gJ/tlw4YN\nMTQ0pFy5ctjb2/PgwQMAZs+ejauray7tKioqCr+xoaGhODo6YmhoiIGBAR06dODChQsKc9LT05k8\neTLW1tbo6OhQs2ZNli5dKu+vW7cu+vr66Ovro6amhpaWllz7woULP+CTlngnQoh8XzndEhISRU12\ndraYO3euaNiwoUhMTMzVv2HDBtG3b99i13H27FlRr1498e2334pJkyaJHj16iOjoaGFhYSHq1asn\nsrKyil2DhPI5f/680NHREcHBwcqWUmyEhiYKiBYQ/8YrWoSG5v73J5E3ERERwtXVVTRs2PC910hI\nSBCenp7CxMREAOLly5dFqLD0kJaWJqpVqyZ8fX3fOTYiIkIYGxuLzMzMElBWOD7oPjArU4iX8UUn\n5i0qVaokAgIChBA519WRI0dE5cqVxbBhw4QQOd9rurq6YtWqVSIpKUnExcWJadOmCSMjI3H//n0h\nhBCnT58Wurq6Ql9fXzx48EC+dqtWrYSHh4fC8bZu3Spat26t0BYWFiYMDAzEqVOnhBBCJCUlif37\n94tHjx4JIYSYNWuWcHV1zaVdRUVF3Lt3T76GkZGRmD59uoiLixNJSUli5cqVQldXVwQFBcnndO/e\nXdja2orQ0FCRlZUlLl68KKpXry6+++67XOu3a9dObN68uTAfp8S/5HfN/9uep70k7UxJSCgBmUzG\nlClT5Ikpnj59qtAfFhZWLO598fHx7Nu3jzNnzjBy5Ej69OnDTz/9RGJiIosWLeLbb7/lr7/+4sWL\nF6iqqtK+fXsGDBggf8om8WliZ2fH/Pnz6datG25ubiQkJChbUpFz6VIikP1Wa/a/7RIF4Z9//uHQ\noUM0atSI1NTUd47PzMwkMDCQCRMm8PXXX9O6dWsqVKjAypUrOXDgQIHjiT5GNDQ0WLVqFV9//TUx\nMTH/OTYjIwM9PT1UVVVLSF0RkZ0F+SWnOLcZxurAhLIwsybEFM9viPj3+Hp6enTr1o09e/bg4eHB\njRs3+OmnnxgyZAijR49GR0cHQ0ND5syZQ/PmzZk1a5Z8DUNDQ3lNtcJy7do1qlSpIi84raOjg5OT\nE5aWlgXSDTklB1q0aMHPP/+MoaEhOjo6jBkzBldXV3766ScATp48ib+/P/v378fGxgYVFRWaNWvG\njh07WLNmTZ6eJEJKHFJiSMaUhISSkMlk/P7775QrVy5Xxr579+4VafKJa9euYWtrS4UKFfjhhx+Y\nNGkSMpmMGzdu0L9/fx4/fowQghEjRjBq1CjGjRuHt7c3P/74IzVr1qRFixaEhIS89/HDwsLw9PTk\n3r17RXZOEkXLd999x6lTp1BVVaVp06acPXtW2ZKKlGbN9Mj9k6fyb7tEQWjdujU3b97k3r17LF++\nPFd/YmIiN2/eZMuWLdjb26Orq4u7uztGRkY0a9aMadOmERsby/nz57GysqJs2bKfdOKTr776ik6d\nOrF27dr/HPfR3fRmpML6njBGE8aUgSMzFI2qR1dhzxjITIPsTIgKgzUOude5+yf4zIOzGyGjaGI2\nmzZtiqWlJYGBgZw/f55evXrlGtOnTx9OnDghfy+TyZg6dSpeXl7cvXu3UMdr1KgRt27dYvz48Zw+\nfZrk5ORCa/b398+zWHOfPn04d+4caWlp+Pv7Y2trmysjZrNmzbC0tOTkyZOFPq5E0SEloJCQUCIy\nmYx+/frh6+uLEEIeczBnzhxat27NyJEjP3iH6u+//6Zjx44sW7aM1q1bY2VllesJqJubGydPnmTu\n3Ln0799frsPc3BwHBwfU1dXp378/LVu2JD09nSdPnhATE8O4cePkBV+DgoLo168fWVlZJCUl5cpM\nVbZsWXr16sW6des+6Hwkig8bGxvWrVuHl5cXTk5OhIeHo6Ojo2xZRYKNjS6jRz9n9WoDcnaoVBg9\nOh4bmyrKlvZRYW5uzrp162jTpg0qKiro6elx6tQpTp8+zcuXL7G0tKRu3bq4u7tz+PBhtLW181wn\nLi4OTU3NElZf8ri7u+Pi4sLUqVPzjSmLj4//uBJ3/DEebvjk7EyRBf6/QPma0GxATv/9i8AbxpXI\nhqehOeNV/v3t+fN32Pc9ZKaCehk4sxYmXgC196vL+CZmZmZER0cjhMDMzCzf/jcpV64c7u7uzJgx\nA09PzwIfq3Llypw+fZpffvmFvn37kpiYSN++fVmzZo382t+zZw9Hjx6Vz3nztx4gOjo6X53Z2dnE\nxsbmOya/85EoWaSdKQkJJWNubk7z5s2JjIxkz549CCGoVasWzs7O9O/fP1ca4sLi7e2Nq6srgwYN\nonLlyrkMqaysLNavXw9AQkJCnj/qI0aMYPz48TRp0oS2bdsybtw45s+fz+zZs2nXrh3u7u44Ozvj\n7OzMuXPnuHfvHlOnTsXY2Jj/+7//A3KeGH4qN+afOj179qR27dqsWLGCzMxMZcv5IKKikgkOjiQq\nKplVq6oQGqrJ1q2ZhIZqsmqVZEi9DzVr1uTkyZOEhoZy+fJlunXrxtWrV0lKSuL27dt4eXnRq1ev\nfA0pgNWrVxeo8O/HTpMmTShTpgznzp3Ls3/VqlW0bt2aRo0albCyDyDUDzJSXr9PT4brx16/N7R4\nbTS9oozB6zYhcgypjJc5hlb6S3h+B0IOFYm8yMhITE1NUVFR4cmTJ7n6nzx5gomJSa72n376CT8/\nP/7+++9CHa9Zs2bs3r2bZ8+e8eeff3LmzBnmzZsn7+/bty+xsbHyV1xcnMJupImJSZ46Hz9+jIqK\nCkZGRvmO+a/zkSg5pJ0pCQkl06xZM9LS0uRp0lNSUhg8eDCrV6+mb9++ODg4cODAAXR1c6dx9vb2\nJjExkXbt2lGhQoU81w8ODqZv3775Hj8gIIAHDx5w9uxZHBwccHd3z2VQlS1bluHDh+eae+XKFf78\n80/u3LlDz54DMDSsgpaWIcbGOkyfPp2bN28SGBiIqqoq6enpDBkypBCfjIQy2bRpE4MHD+bs2bMf\nbXyLp+f/GD78MBoaqqSnZ7FpkyMuLnWllOhFQN26dfHw8HivuUII/Pz8FFytPlVkMhl9+/Zl3759\nudKkP3nyhNmzZ3P58mXOnTuHi4sL69evL/3lMPTNIPqNGB1VdTB6o8xHXQeo8SXcOQXIQGTB0B2v\n+0V2zo7Um4hsSPnwOlvBwcE8fvyYNm3a0Lx5c/bt20fbtm0Vxuzduxd7e/tcc42NjRk3btwHpfhv\n3Lgxzs7OXL9+vcBz7O3t2bdvH4MHD86l087OjjJlymBvb8+vv/5KZGQkFhYW8jEXL14kIiKC9u3b\nv5deiaJB2pmSkFAyBgYGXLlyhfnz5zNt2jQWLVqEra0t9+/fZ+/evTRp0oSuXbvK6wAJIfD19aVf\nv358//33jB49GjMzM6ysrFixYoX8iVdqairDhg3Dz8+P6tWr53v8Vq1akZyczJEjR2jUqFGhfkT0\n9PTo2rUr5ct3wNHxDB07bsfaegWentfR1NTEy8uL6Oho/vnnHzQ0NN4rwFdCOVSrVo3AwEC0tbUZ\nOXKksuUUmqioZIYPP0xKSibx8WmkpGQyfPghoqIKH9MgUbSEhYWRnZ1NjRo1lC2lROjVqxdeXl5k\nZysmQAkKCkIIgZ6eHjt37uThw4c0b96cqKgoJSktIC5roIweaGiDhg4YmEGnia/7VVRg5CH45gD0\nXwtTQ6DeGzFTKqpQtWWOEfYm1RWNnsKQmJjI0aNHcXFxwdXVlTp16rBw4UI8PDxYvXo1SUlJxMXF\nMW3aNIKCgpg5c2ae63z//fecP39eIX36f3Hu3Dk2btwo/5vdunWLw4cPY2dnV2DtM2fO5Pz580yf\nPp24uDiSkpJYtWoVO3bsYPHixQB06NCBDh060LNnT0JDQ8nOziYoKAhXV1e+/fbbIo2xlig8kjEl\nIVFKmDx5MnPmzOHGjRt07dqVr7/+GjU1NebNm8fFixcpU6YMvXv3pkWLFkycOBE7Ozvq1q1Leno6\nLi4ueHh44OHhweDBgzl//jzdunUjMTGRiIiI/3Qh0dLSYtGiRZw7d06eOagwFOSm1crKip07d3Li\nxAlevHjx8QVcf6aoqanh4eHBhQsX8Pb2VracQhEe/gINDUVXI3V1VcLDP/zpt8SHsW3bNnr06PFx\nxQl9ADY2NhgZGbF//34g54GYo6MjI0aMwNHRkdTUVC5evIivry9dunTJVfOo1GFZH2aEQt9VMGA9\nTL8OOsaKY2QysLHPiaMqVy33Gu4Hc3avNLTB0DLnffnCG9fdu3fHwMAAKysrFixYwIQJE9i8eTMA\nLVu2xM/PDy8vL8zMzKhcuTIhISGcO3eOKlXydvHV09Nj4sSJxMbGFuj4hoaGHD58mHr16qGvr0/X\nrl3p2bMnP/7443/Oe/Par1atGmfPnuXatWtUqlQJc3NzDhw4wPHjx2nevLl8nJeXF19++SVfffUV\nenp6DBo0CDc3N1auXPmf60sUP7L/uqmRyWRCuumRkCh5fHx86N69O8uXL8fAwABra2ssLS05fPgw\nVapUwcLCgsWLFxMeHs6hQ4eYOXMmV65cYdeuXezevZsDBw7Qpk0bfvnll2JPtxscHEnHjtuJj3+d\njUlfXxN/f1eaNrVQGNu4cWNu3bpFw4YNWbly5ccVJ/AZM3/+fOLj41m0aJGypRSYqKhkrK1XkJLy\nOuZLS0uNBw/GYWoqxe4pi9TUVKytrQkMDKRWrVrKllNiBAUF8X//939s3rwZFRUVfvzxR0JCQlBT\nU8Pb25slS5Zw+vRpUlJSqF+/PqtXr6ZTp07Klo1MJpMefkl8VuR3zf/bnqeVKsVMSUiUQrp06cLh\nw4dxdHQkMzMTGxsbIiIi8PX1pUqVKnTu3BlLS0tOnz6NtrY2CxYswMTEhOTkZGbMmMGMGTNKTGul\nSoakp2cptGVkZFGpkmGusZcvXyY7O5vNmzfj4OBAjx49WL169cdXX+Uzo0GDBvz888+5slCVZkxN\nddi0yZHhww+hrq5KRkZOzJRkSCmXXbt20bBhw8/KkAJo3rw5R48epXv37mRnZ7Nt2zbU1HJuwUJC\nQmjSpAmQ4ykwbdo0Fi5cWCqMKQkJiXcj7UxJSJRisrOzSU9Pp0yZMnh4eMgTOKxZs4ZRo0YRFxeH\noaEh2dnZVKtWjc2bN8uLB5Yknp7Xc920urjU/c85CQkJODs7Y2VlxcaNG1FRkbyOSytZWVk0adIE\nJyenEjXUi4KoqGTCw19QqZKhZEgpmaysLGrVqsWGDRuU8j1VGggNDQWgdu3a8ratW7dy8uRJtm/f\nDuQU8TUzM+PSpUv5uqOVFNLOlMTnhrQzJSHxiaGioiLPolcbf+YAACAASURBVDZ48GAcHByoU6cO\n48ePl1d1fzVu5cqVzJkzB0NDQxo0aFCiOl1c6mJvX7lQN636+vocPHiQBg0acOnSJQXfcInShaqq\nKr6+vrRr146bN2+ycOFCrK2tlS2rQJia6khGVClh7969lC9fPld2tc+JN42oV1SqVIkHDx7I36ur\nq2NjY8OdO3eUbkxJSEi8G+lRsITER4SJiQk3b94kOjqaVatWoa7+OhtSt27dGD58OL179/7g2lTv\ng6mpDk2bWhTqxlVXV5dGjRrRrVs39u7dW4zqJD6U8uXLExwcTM2aNalfvz5Dhw4lIyOjWI/5Zo0o\niY+bjIwM5syZw7Rp0z4aV9GSonLlyty6dUvhe/vhw4efTbZDCYmPHcnNT0LiE6Nu3bps376dhg0b\nKltKgcjMzOTq1as4OTnx008/MWbMGHmfEIKEhAT09fWlG7BSRHJyMv369UNFRYVdu3YVSzHmvGpE\n9epVk4sXL3LlyhXCwsJISEgActxhhRCMGzeOxo0bF7kWiQ9n5cqVHDlyhOPHj0v/lt9CCEH37t1p\n3rw57dq1Y+fOnfj4+BAWFiaPq1IWkpufxOfG+7j5ScaUhMQnRo8ePXB2dmbQoEHKllIowsPD6dKl\nC+np6dSpU4fnz58THBxMmTJl0NXVpW3btnTo0AFHR8d8CxRLlBzp6em4u7tz6tQp1q1bR+fOnYts\nbcVMfNnAP6iq/o22djjVqlWlefPmVKtWDWPjnHTMKioqxMTEsGDBAvbu3fvZxuOUVqKioqhduzaB\ngYF5urlJwL1792jQoAHVq1enc+fO/Pjjj/LrW5lIxpTE54ZkTElIfOZkZWWhpaXFrVu38vS1L+3B\n+JmZmYSFhXHjxg0eP36Mq6srhoaGhIeHExgYiK+vLz4+PtSrV4/FixcXqjCiRPHg5+fHiBEj6N+/\nP/PmzStQIpHk5GRevHiBpqYmJiYmufqDgyOxt99AQkIAcA3Qo0yZxhw6NJdOnb7Id91Tp07Rq1cv\n7t27h6Fh7mySEsrBzc0NXV1dli9frmwppZqsrKxSkdn0/v379OvXDx0dHU6dOiUZUxKfFZIxJSEh\nQb169di0aRPNmjVTaM/LbepdGfdKI6mpqezfv59x48Yxd+5cRowYoWxJnz1RUVE4OztjamrKxo0b\ncz1Rj4qKYtOmTfj5+XHnzh3i4uIwMjIiOTmZihUrUqNGDSwsLHBycsLExITt23ezZMkqoBrQHChf\n4BpRAwcOpE6dOkyePDlXnxCCmJiYPA04ieLBy8uLCRMmcPXqVcnA/Uh49OgRNjY27Ny5kx49ekjG\nlMRnhWRMSUhIMGjQIFq0aIG7u7u87VMsYHrnzh25S+PcuXOVLeezJy0tjQkTJrBz504GDRpE7969\niYqKYseOHfj7++Ps7Ezfvn2xsbHB0tISFRUVsrKyuHz5Mg8fPuTOnTvs37+f2NhYevTogYlJc+bO\nvVuodPuQc120atWK/fv306pVK0JDQzlz5gyPHj1iy5YtPHnyhNjYWIyMjErgU/m8uXv3Li1atMDH\nx0deR0mi9COEYNiwYTx+/Jjjx49LxpTEZ8X7GFMIIfJ95XRLSEh8TFStWlWcOHFCoe3SpQhhYLBA\nwCz5S19/gbh0KUJJKouGZ8+eCQMDAzFu3DiRnZ2tbDkSQoiIiAgxYcIE0bRpU9GuXTvx+++/i7i4\nuPda6/nzJHHpUoR4/jypUPN8fX2FlpaW0NLSEmXLlhWDBw8WEydOFFeuXBFDhgwRPXv2fC89EgUn\nPj5e1KtXT6xZs0bZUiTeg4yMDNGzZ09Rmu8DK1WqJE6ePKnQtnXrVtGqVSuFtrZt2wojIyORnp6u\n0D548GAhk8lEcHCwvC0sLEz8u5Egn1umTBmhr68vDAwMRJMmTcTChQtFWlqafMyLFy/EsGHDRIUK\nFYS+vr6oWbOmWLRokRBCiPDwcCGTyURWVpbCsYcMGSKmT58u16yqqir09PSEgYHB/7N353E1pv8f\nx1+nUlqFLC2UFiNblmzZt8gYskV+9n0GYxtkZ76WwTCWwdiXQbIU2VPWspYlYUhUhiyhUlpP9++P\n+U7fMVmiU3edrufj4fGYzn3f1/W+M+p8znXd1yXVrl1bOnTokCRJknT69GlJQ0NDMjQ0lAwNDaUK\nFSpIbm5u72T+26JFiyQ7OztJT09PsrS0lKZMmfJOzk/db7Vq1bL60dTUlIoXLy4ZGBhIhoaG0oIF\nC6S0tDRp/PjxkoWFhWRoaChVqlRJGjdu3Gf/fWzevFmqUaOGpKenJ5mamkrffvutFBcX9845t27d\nkjp16iSVKFFCMjIyklq1aiWdP39ekiRJOnfuXFYufX19SaFQSIaGhlmvPXr0KNv35nN86P/5/77+\n3npJLI0uCGrGycmJ2bNnv/OalZUxaWnKd15LT1diZVW4p92ULVuWc+fOERAQwOHDh+WOIwDm5uYs\nXryYy5cvc+rUKYYOHfrF07u+ZLl9gHbt2pGQkMDz5895/PgxW7ZsYeHChdSuXZuVK1cSFhZG3bp1\niY2N/aJcwsdlZGTQs2dPnJyc+Pbbb+WOI3wBLS0tdu7cmas2JKUS6b8rbuanf64WGRUVRWBgIBoa\nGvj6+mY7r3Tp0kyfPv2D1ysUClavXk18fDwxMTEsWbKEXbt20aFDh6xzxo0bR1JSEnfv3iU+Ph5f\nX19sbW3f296HODk5kZCQQFxcHIMGDcLNzY34+Hjgr5+pCQkJJCQkcPHiRapUqULTpk05depU1vWj\nR49mw4YNbN++nTdv3nD06FECAgJwc3PL8f2GhYVl9dO0aVNWr17NmzdvSEhIwMPDg/nz53P16lWC\ng4NJSEjg9OnT1KlT55P39s/7X7JkCVOmTGHJkiVZ9xMVFUXbtm3JyPhr5kxERARNmjTBwcGByMhI\nnjx5gqurK87Ozly6dIkmTZpk5bp16xYKhYL4+Pis1ywsLD6ZSdVEMSUIaiQ2NpaAgAB+/PHHd14v\nU0afjRs7o6urhZGRDrq6Wmzc2LnQTvH7pxo1ajBmzBi2bdsmdxShANHS0sLAwAAdHZ13XjcwMOD2\n7ds0aNAg25sKIfckSWLUqFEA/Prrr2IZ9EJMW1v7o8clpfKDUwDTtm7iTWl93piX5k2Nr8j8x6bE\n+Wnbtm00atSIAQMGsGXLlmzH+/fvT2hoKOfOnftgG3/fo66uLs2aNcPX15cLFy5w5MgRAK5cuULv\n3r0xMjICoHLlynTt2vWLMw8aNIjk5GQiIiKyHTMzM2POnDkMGTKEyZMnA39Np12zZg07d+6kfv36\naGhoYG9vz759+zh27BinT5/+rPv9933/LTg4mC5dulCuXDkAKlasSJ8+fXJ8X2/evGH27Nn8+uuv\ntG3bFk1NTSpWrMju3buJjIxk+/btAMyePRsnJyd+/PFHjI2N0dfXZ/To0fTt2zfrnj+VNb+JYkoQ\n1IAkSVy9epUhQ4bQq1cvWrVqle0cd/fqREWNxd+/L1FRYwvl4hMf0qlTJ44fP05ycrLcUYRCQEND\ngx9++IF9+/bJHUWtZGZmMnPmTC5cuICXl5fseyQJeUNKSeFtr268KaHDG+PipPw48503s8rr10gZ\nNxpSUyEjA+nBfd52/TpbOxmB50hdOI+0zRuQUlNVk+1fb6q3bdtGnz596N27N8ePH+fFixfvHNfT\n02Pq1KlMnTo1x31UqFABR0fHrIKkYcOGTJ06lS1btnD//v1c5c/IyGD9+vUYGhpiZ2f3wfO6du3K\n1atXSU5O5uTJk1SoUCHbHnsWFhY0bNiQEydOZL32Jff7t4YNG7JkyRLWrFlDWFhYjq75599HUFAQ\nqampdOnS5Z1z9PX16dChQ1ZOf39/evToka0tNze3rDYKGlFMCYIa2LFjBx07dqRUqVIfXYzhS6dN\nFXRlypShTp06+Pn5yR1FKCQePnwo9jxSocTERNzc3PD39+fYsWNZn9IL6idl0ngyjh8FpRLS0khb\nvpR0r/9NCVReuQT8o6jJzCTzzm0k5f+mmqduXMfbTu1J/XEmKT+MIamlE1Ja2mdncXV1pVSpUll/\nRo4cmXUsMDCQ6Oho3NzcqFOnDra2tu+dujhs2DCio6M5fvx4jvs1MzPj1atXwF8jsH369GHVqlVU\nq1aNypUrc+zYsc+6jwsXLlCqVCnMzMzw8vJi//79GBoafrR/SZKIi4sjNjYWU1PT955namqabTrz\nl9wvwNSpU/Hw8GDnzp3Uq1cPCwuLbDNCPvb38fdKqu/bPuOfOT90P6ampmRmZmZ93wsSUUwJQiEn\nSRI+Pj4sWLCATZs2oaurK3ckWXTr1o3Vq1fz4MEDuaMIhcCZM2do2LCh3DHUQkhICA0aNKBEiRKc\nPn36g2/sBPWQ4X8cUv4xC+BtEhnHjmR9qTAzB41/7ZdVogSK/+6hJUkSqRPHQfJbyMyEt2/JDL9H\nxsEDn53lwIEDvHr1KuvP6tWrs45t3boVZ2fnrJU73d3d2bp1a7Y2tLW1mTFjBjNmzMhxv48fP87a\nAkJHRwcPDw+uXLnCy5cv6dGjBz169CAuLi5rdDY9Pf2d69PT0ylWrFjW140aNeLVq1c8f/6c8+fP\n07Jly0/2r1AoMDY2xsTEhJiYmPeeFxMTk20riC+5X/jr2advv/2Wc+fOERcXx9SpUxk0aBB3797N\nOudjfx8mJibExsaSmZn50Zwfup+YmBg0NDQK5EqsopgShEJu9+7deHt7Y25uLncUWfXt25dKlSpR\nq1atrAdZBeFDfH196dSpk9wxCrXU1FSmT5+Oi4sLHh4ebNiwIdszaoL60Sj/r2K5WDE0LCpkfanl\n8jVazVuCvgEYGIKuHrqbtv/v/MxMSE15tw1lJlJ83Gdn+dCzMikpKezZs4czZ85gamqKqakpy5Yt\n48aNG9y8eTPb+QMHDiQuLg5vb+9P9vno0SNCQkJo1qxZtmMGBgZMnTqVpKQkHj58iKmpKcWKFSMy\nMvKd8x4+fIilpWXObvI9vL29qVOnDrq6urRq1YpHjx4RHBycLefFixdp06ZNtus/537fR0dHh+++\n+46SJUty+/btrNc/9uxSo0aN0NHRydZnYmIiR48ezcrZpk0b9uzZk+16Ly8vGjVqRPHixb8oc14S\nxZQgFFIZGRn4+Pgwc+ZMBg4c+N4fmEVJiRIlWL16NRkZGSQlJckdR1CRoKBoZs06RVBQtMrafP36\nNTdu3KB6dfV5bjC/3bx5E0dHR8LCwrhx4wZ9+/YVi00UEcWXrQJDQ9DTA319FOVN0Rk/Keu4QkMD\n3b0H0Nvtg+6KNRhcuUExl/89M6XQ1ESzUWP4x8gMCtBs2lxlGffv34+WlhZ37tzhxo0b3Lhxgzt3\n7tCkSZP3LlakqanJ7NmzWbhw4QfbTE5O5syZM7i6utKwYUNcXFwAmDt3LsHBwaSnp5OamsqyZcso\nWbIkX331FRoaGnTr1o1p06bx6tUrMjIy8PT05M6dO1nXf8o/C5QnT54wZ84cNm3axIIFCwCws7Nj\n+PDh/N///R+XLl0iMzOTW7du0b17d5ydnd87ypWT+/235cuXc+bMGVJSUlAqlWzdupXExMQcregH\nYGRkxMyZMxk9ejTHjx8nIyODyMhIevbs+c5iFrNmzeL8+fPMmDGD169fk5iYyMqVK9m+fTuLFi36\n6PdHLuLpUEEohCRJokqVKpQuXZqlS5fy9dfZH+4taiRJYuzYsdSvX/+jc82FwsPZ+XdOnPhr2uaP\nP57F2dma48f75rpdY2Nj9PT0ePLkCSVKlMh1e0XNvn37GDFiBEuWLBFFVBGkWdMBg6u3yQjwQ6Gt\ng1bHTij+9TNXoVCg1erDH/Dp7d7P2/7uKM8HoihZCt21m9C0q/xZOT72/922bdsYNGhQthkbo0aN\nYsyYMe8tItzd3VmwYAFxcXHZrhk3bhwAtra29OjRg/Hjx7+TY+DAgTx69AgtLS1q1qzJkSNH0NPT\nA2D16tVMnDiRmjVrkpycTNWqVTly5AhlypTJ0X3GxMRgZGSEJEmUKFECJycnzpw5Q7169bLOWbVq\nFYsXL6ZPnz48efIEExMTevfuzZw5cz74/frQ/b7vXPhr8YoJEyYQERGBQqGgcuXKeHt7Z42w5eTn\nwMSJEzExMeGHH37gwYMHGBkZ0aVLF3bu3Jk17dHW1pbAwEAmT56MlZUVkiTh6OiIn5/fe6dmF4Sf\nP4qPVXT/3cgrH+MIgpATqamplClThnv37lG+fHm54xQIK1asYN26dQQGBn7xvkZCwREUFE2TJpuz\nvR4YOJDGjSvmqu379+/TrFmzrOcOhJxbunQpy5Ytw8fHJ9vqYYL6USgUBeKTf0HILx/6f/6/r7/3\nF4YYmRKEQmjZsmW0bNlSFFL/YGtry+PHj2nRogVly5alXLlymJubM3PmzKxPCIXCw88v+x4rf7+e\n22LK29ubTp06iULqM23ZsoUVK1Zw/vx5WTbGFARBKIjEyJQgFDKSJFGpUiUOHDiAg4OD3HEKlNjY\nWB49esSzZ8949uwZU6ZMYf369Xh5eVG9enVcXFyoXr26eBNdCOTVyFRycjI1a9Zk/fr1tGjRIhcJ\ni5bDhw8zePBgTp8+TZUqVeSOI+QTMTIlFDVfMjIlFqAQhEJm6NChFC9enJo1a8odpcAxMTGhdu3a\ntG/fnv79+2Nubo6bmxsWFhZERUXRuXNnLC0t8fDweGcFIqHgady4Is7O1u+85uxsnetRqYCAAMqX\nLy8Kqc8QExND//792b9/vyikBEEQ/kWMTAlCIWNtbc3evXtzvIJOUTZ79mxq1aqFq6sr8NeoXlhY\nGL///jvbt2/H3NycMWPGZK0iJBQ8QUHR+PlF4Oxsk+tCCuDevXs0btyYW7duUbZsWRUkVG+SJPH9\n99+TmZnJqlWr5I4j5DMxMiUUNV8yMiWKKUEoZFxdXenduzdubm5yRynUlEol/v7+DB8+nIULF9Kz\nZ0+5Iwn5ZMKECcTFxbFx40a5oxRot27dYsyYMcTGxnLixIkcrz4mqA9RTAlFjZjmJwhqLjMzk3Pn\nzvHixQvatWvH+fPn5Y5UaGlqatKuXTvWrVvHtGnTuHDhAj/99BM7d+7k+fPncscT8tDMmTM5fvw4\nhw8fljtKgRUeHk7btm3p1KkTwcHBopASBEH4ADEyJQiFjK+vLwMHDiQlJYXu3buzdetWuSMVar//\n/jv9+vXDwcGB5s2bExUVxenTp7G2tqZt27bUq1cPpVJJamoqGRkZuLi4YGpqKndsIZeCgoLo0qUL\ngYGBVK78efvbqLtr167RsmVLJkyYwIwZM+SOI8hIjEwJRY2Y5icIRcSdO3do1qwZvr6+NGrUSO44\nhVpaWhoJCQmYmJhkvZaens7ly5fx8/MjNDSUYsWKoaOjQ3p6OidOnGDs2LFMmDBBLLleyG3YsIF5\n8+Zx6tQprKys5I5TYKxYsYKwsDDWrVsndxRBZlZWVkRFRckdQxDyjaWlJZGRkdle/1gxhSRJH/zz\n12FBEAqSsLAwyc7OTpo/f77cUYqkBw8eSG5ubpKFhYW0Z88eueMIubRixQrJ0tJSioiIkDtKgRAT\nEyOVL19eOn36tNxRhEIoOTlZatGihTRmzJiPnnfgwAGpXbt2OW43MzNTyszMlLZs2SKVLVtWcnNz\nk37//Xdp5MiRkqGhoaStrS1t3rxZUiqVUkBAgGRubi6NGjUqWzuvX7+WypUrJ5UvX15KSEiQNDU1\npc6dO0vLli2TJEmS1qxZI7Vu3fqjWQYOHChVqFBBqlOnjmRsbCydOHFCsre3lypWrCjVrl1bqlu3\nrlSuXDmpVKlSkoGBgfTy5cusa/38/CQ7OzspJiZGatWqlXTw4EFJkiTp2rVrkru7u3Tv3r0cf0/+\n7erVq9Lo0aMlCwsLyc7OTvrhhx+kc+fOSUql8ovbfPbsmdSiRQsJkEqWLCk9e/bsi9sq7P5bE72/\nXvrQAUkUU4JQ4Fy4cEEyMTGRNm/eLHeUIi8oKEiytLSU/vOf/0iZmZlyxxFyYfXq1VLFihWlmJgY\nuaPIbunSpdLAgQPljiEUYnFxcZKVlZXk4+PzwXNmzpwpTZs2TWV9hoaGSiYmJpKtra1UvXp1CZC2\nbNny3nPT0tKkatWqSVevXpWMjY2lQ4cOSeXLl5eWLVsmPX36VLKwsJB8fX0/2NfLly+lpUuXSiNG\njJDOnz//3nMyMzOl48ePS23btpWCgoKyXk9ISJDKli0r1a1bV+revbtkZ2cnubq6SlFRUbn7Bvyr\n75CQEGnmzJmSvb291KpVqy/+2RYdHS2tXr1acnV1lQDJ1tY2V8VZYSaKKUFQE+3bt5fWr18vdwzh\nv548eSLVqVNHGjJkiJSWliZ3HCEXZs6cKbVo0UJKT0+XO4pswsPDJWtra+nQoUNyRxEKufPnz0tl\nypSRJk2aJCUlJWU73q1bN2nXrl0q7fPw4cPShQsXpMzMTOnp06cf/ZCra9eukqenp1ShQgUpMjJS\n8vf3l+zs7KTw8HCpZcuWEiCFh4erNN/fLly4IP3+++9SSkqKlJycLM2ZM0cqXbq01KtXL2nChAnS\nsWPHVPYBXXp6ujRz5kzJzMxMCgkJ+ezrf/vtN8na2lqys7OTzMzMJEC6ffu2SrIVNh8rpsQzU4JQ\nSKSnp6Ovr09kZCRmZmZyxxH+KzExkZ49e/L06VOGDx+Ok5MTBgYGVKhQAU1NTbnjCTmkVCrp0KED\ntWrVYuHChXLHkUWTJk3o3LkzEydOlDuKoAaePXvG2LFjuXLlChs3bqR58+ZZxzp06MCoUaPo0KFD\nvueSJInKlSvj5eVFr169OHjwIDo6Ojg6OvL27VtSUlJo27Yt1apVY+nSpfmS6eHDh5w/f57o6Gi8\nvLxIS0tjzJgx9O3bVyXP5vr4+DB8+PBPLrgjSRK7du3CxcUFSZIYMWIEGRkZpKenY2BgwKtXr/Dx\n8UFXV5eEhAQePnyIg4NDrvMVBmJpdEFQA8WKFaN///5i48wCxsDAAF9fX3788UdOnDhBz549adSo\nEa1bt+bNmzdyxxNySFNTkx07drB27VpevHghd5x8Fx4ezv379xk7dqzcUQQ1Ua5cOTw9PVm2bBk9\nevTg4MGDWcdSU1PR1taWJVd4eDixsbFUrVoVTU1NUlNTsbKy4t69e/zwww+0aNECCwsLFIr3rzWg\nShkZGZw4cYJKlSrxf//3f0yZMoVr166xevVqjh49iqWlJfPnz891P126dKFnz55s2rSJzMzMd44F\nBATg4+PDnTt38Pb2pnfv3sybN4927dqhUCjo3LkzFy9eZNWqVRw7dgxdXV0Afv75Z2rVqiUWKEGs\n5icIhcq1a9do1aoVr1+/ljuK8BFKpZJOnTrh6urK0KFD5Y4jfIbevXvj5OTEqFGj5I6Sr6ZPn05y\ncjJLliyRO4qghi5fvkzHjh0ZNWoU+vr6rFy5koEDB+Lg4IChoSH29vb5NuMiKSmJrl27curUKezs\n7PDz88Pc3ByAqKgoOnfuTPny5Vm9ejXW1tZ5mmXFihWMGTOGgwcP0rFjx2zHIyIicHZ2Zu3atbRp\n0yZXfd24cYP+/fvz+vVr+vbtS//+/bGzs6NixYo8efIEKysrDAwMqFixIqmpqVhYWHD06FGsrKwY\nP3483bt3f6e9kydP0rp1aywtLQkJCaF06dK5ylfQiaXRBUFNjB49mkuXLnHmzJmsT4eEgmnLli0c\nPXoULy8vuaMIn8HLy4tffvmFixcvyh0lX3Xq1In+/fvTrVs3uaMIauratWts3rwZLS0tAgIC0NTU\npEKFCrx584br16/TrVs3+vXrR5MmTbKNCmVmZqKhobrJVJIkkZSUhIGBgcra/BLm5uZYWFjQu3dv\nxowZ895zfHx8mDlzJqGhoSoZLbtx4wbbtm1jx44dTJgwga+++opZs2YRFxeHu7s7lSpVwt/fH39/\nf6ZPn87YsWPf229aWhpVqlRBR0cHMzMz9u7dS8mSJXOdr6ASxZQgqInIyEgmTpxIcHAwPj4+1KpV\nS+5Iwgc8evSI2rVr8/z5c5W+CRDy1r1796hfvz7nz5+natWqcsfJN1OmTOHkyZP89ttv1K5dW+44\nghrbs2cPEyZM4ObNm5QoUQKAly9fsmLFChYsWMD48eNxdnbGyMgIQ0NDTp06xfjx42ncuDGtW7em\nVatW1KlTBy0tLZnvJPf+LlLu37+PjY3Ne8+RJAkrKyv8/Pz46quvct1nZmYmK1eu5NSpUwQFBfHi\nxQskSeLGjRt4eXnx4sULqlevzuDBgzE0NPxoW2fPnqVr165YWlqiVCpp27Ytzs7OtG3bNtc5CxpR\nTAmCmtm9ezcjR45k8+bN750aIBQM9vb27Nixgzp16sgdRfgMmzZtYu3atVy6dEnuKPlGqVTy22+/\nMXfuXGJiYuSOI6ixESNGsHfvXhISEvDx8eHrr7/OOhYZGcm4ceN4/fo1b9684c2bN6SlpbF+/XqS\nk5M5efIkJ0+e5Pnz54SEhGRNzyus/h6JGzZs2EfP69OnDy1atGDIkCG57jM9PZ3SpUszZswYmjVr\nluvCZ8+ePXz33XeMHz+eRYsWERcXl/Xf6rQIkyimBEENnT9/ni5duhAVFUXx4sXljiO8R//+/XFy\ncmL48OFyRxE+Q0ZGBuXLl+fq1atUrFhR7jj5ZteuXaxZs4YzZ87IHUUoAnx8fBg4cCBNmzbFyckJ\nJycnbG1tuXXrFmZmZtjZ2aGjo/Pea6dMmcKtW7cYMWIElpaWWFpayj5lL6/s2rWLadOm0a9fP2bN\nmvVZ10ZFRREZGYmTkxPFihXLer1fv35IksS6detU+shAQkIC33zzDWfPnmXv3r2MGjWKp0+f4ufn\nV+hHq8RqfoKghpycnKhTpw4bN26UO4rwATdv3qRmzZpyxxA+k5aWFh07dsTX11fuKPnq+PHjuLm5\nyR1DKCK6dOnCrVu36N+/Py9evMDDw4MaNWowb948mh7inAAAIABJREFUevToQbly5XB3d2ffvn28\nevXqnWunTJmCpaUly5cvp1u3bpQtW5aWLVsSEBDA+wYB/vzzT96+fZujXOnp6dy/f18l95hbd+/e\nZfTo0axfv57JkycTGhpKamrqR6+RJIk9e/bQsGFDHB0dGT9+PGZmZgwdOpQrV64A8Ouvv6JUKqlf\nvz7h4eEqy2tkZMSZM2d4+fIlXbt2ZcWKFQA4OzvToUOHbH+P6kKMTAlCIRYWFkarVq3w8fGhcePG\ncscR/iE+Ph4LCwtevnwp2xLAwpfbv38/K1euJCAgQO4o+WbIkCHUq1dPjKQKBcKzZ8/Yv38/+/bt\n4+LFi5QsWRIbGxtKly6NoaEh6enpKBQKOnbsiIuLC/v27WPs2LFUrVqVY8eOYWRkxK1btzh58iTz\n5s3j7du31KlTBxcXFyZPnszq1avx9fUlKioKd3d3atasSUhICJs2baJ48eJERES8kycjI4MrV64Q\nHBzM06dPCQ4O5vnz55w8eTLPFl74v//7P0JDQ2ndujWXL18mKiqK169f4+DgwObNm6lSpUq2a6ZP\nn46vry/z58+nXbt2FCtWjMjISHbv3s2iRYsICwujfPnySJLE0qVL8fT05NKlS3k2Je/evXsMHDiQ\n8+fPA389ZzVmzBjWrVuHo6NjnvSZF8Q0P0FQYzt37mT16tUEBgbKHUX4h6NHj7J48WJOnjwpdxTh\nC3h7e+Ph4cG9e/fkjpJvJk6cSHJyMr/++qvcUQThHZmZmURERBAVFcWrV69ISEhAW1ub5ORk9u7d\nS0hICMWLF8fExISePXsyefJk0tLSqFq1Kvb29piYmKBUKvH39+fVq1e8ePGCsmXLUqVKFWrWrImv\nry+JiYlZ/Y0YMYI1a9ZkfX337l1at26NiYkJDg4OBAUFERERQcmSJYmOjs6zKYbe3t5ERESgra2N\nkZERffr0IT09ne3btzNr1ix8fX2pV6/eO9fMmDEDDQ0N5syZk629SZMm8ezZM7Zu3Qr8NYrVsmVL\nunfvnqfbQUiShK+vL6tWrWLWrFk0adKEdu3acezYsTzrU9VEMSUIakypVFKlShU2bdpE06ZN5Y4j\n8NffiYuLC+3atWPChAlyxxG+QL169Zg6dSpdunSRO0q+iY2NpUqVKgQHB2NlZSV3HEHIsb+n8VWu\nXDnrtaCgIL755hu0tLSoWbMmDg4O1KhRAwcHB0qVKsXmzZuRJIlnz54RGxuLtbU1tWvXplatWlSu\nXBlNTU0uXrzItGnTuHnzJi1btsTY2Jh9+/bRoEEDRo4cSfv27WVbrdXX15f+/ftTrlw59PX1sbOz\nw9zcnG3btjFx4kQmTZqU7Zo3b97g6OhI3759mT59OgB37tyhQYMGZGRkcPjwYVq2bJkneS9evEhA\nQADNmjVj5MiR3Lx5k1OnTtGiRYs86U/VRDElCGpu/fr1eHt7c/ToUbmjFHmSJDF58mSCg4Px8/NT\ni+V7i6Lhw4djYWHBjBkz5I6SryZMmICWlhYLFy6UO4ogqFx8fDxVq1bl+fPn2NjYUKJECbZv346d\nnV22c58/f46DgwPz5s1DQ0ODadOmMWbMGHr27ImlpaUM6bOLjY3lxYsXJCUlcf36dR4+fMiAAQPe\nez9/i4mJoW3btrRs2ZJffvkFLS0tEhMTcXNzIyQkhGbNmrF7926V7Gn1T6NHj2bXrl3Ex8fTtGnT\nrFkbhaXOEMWUIKi51NRUrK2tOXTokNgjRkaSJGXNVz958iRlypSRO5LwhUJDQ+nQoQMPHz58ZxUs\ndXf//n0aNWrEuXPn3vs8hiAUdj4+PkybNo3SpUsjSRKPHj0iKioq23ljxowhOjqaNm3aMGfOHAIC\nAqhRo4YMiVXv7w16U1JS6N27N5UrV6ZChQqMHTuWgwcPMnPmTIYOHYqFhYXK+rx+/ToeHh5cu3aN\n58+f4+3tzfnz51m8eLHK+shLopgShCJg6dKlBAYG4u3tLXeUIkmSJDw8PDh27BgBAQGYmJjIHUnI\npTZt2tCuXTsmTpwod5R89dtvvzFt2jSioqLUdrlpoWhTKpX8/vvv7Nmzh0qVKr33OcEJEyawZs0a\nXF1d+f7772nYsKEMSXPu9evXZGRk5PhDPKVSydq1awkODubu3btEREQQHx9P/fr1uXHjBvXr18fP\nzy/P8rq6unLgwAG6d+/OkiVLCvw2FKKYEoQi4O/54t7e3tSvX1/uOEXO5MmT8fPzw9/fn9KlS8sd\nR1CBqKgo7O3tefnypUr3YikMWrRogYeHB+3bt5c7iiCohbS0NB49eoS1tbXKp9C9fPmSJk2aYGxs\nzPnz57+4/b+XqNfW1qZfv340atRIpTn/6eXLl9jY2BAfH0/79u0L/GMKYp8pQSgC9PT0mDVrFh4e\nHoVmDrK6OHv2LLt27SIgIEAUUmrE0tKSUqVK8eLFC7mj5DstLa08WypZEIqaBw8eoKOjg62tLfb2\n9nh5eam0/UOHDmFjY8Pr16+z9pL6EmXKlGHjxo2sWbMmTwspgNKlSxMTE8PTp08L/YwaUUwJghoZ\nOHAgjx8/ztOheeFdmZmZjB8/np9++olSpUrJHUdQIaVSycuXL4vklM3k5GSVjsZJkoRSqVRZe4JQ\nmFSqVImdO3dia2tL8+bNmT59Ou7u7vj6+nL58mVevHiBJEncuHEDf39/zp0791ntHz58mE6dOlG9\nenWOHDmSR3eherq6upQrV67Qj/yLZaYEQY1oaWkxb948PDw8aNOmjfhkOR+sXbsWLS0tevXqJXcU\nQcWOHj2KpaUlenp6ckfJd2XKlOHZs2cqa2/EiBHcuXMHf39/sYm1UGRER0fz448/Zi2fnpiYiKOj\nI4sWLWLTpk0sW7aMp0+f8vTpU6ysrIiNjUVbW5uEhAQOHDiQo9Ghx48f4+/vz9q1a2nWrBk1a9Zk\nxowZ4vd/PhIjU4KgZrp160bJkiVZvny53FHUXkBAAHPmzGHbtm0qnwMvyCs8PJwhQ4awdu1auaPI\nwsbGhvv376ukrTt37nDw4EH09PT48ccfVdKmIBR0ly5dok6dOpiZmVG9enVq1KjBoUOHGDRoECVK\nlGDcuHGcPHmS27dvExoayty5c3n48CH379+nRYsWnD9/Pkf93Lp1C0tLS0qWLEmVKlVo3LgxS5cu\nzeO7E/5JjEwJgppRKBSsW7eOhg0b0rlzZ2xsbOSOpJZ+/vlnFi5cyN69e9/ZKFIo/F6/fo2Liws/\n/vgjzZs3lzuOLEqWLElCQoJK2vrzzz+xsrJiy5Yt2NvbM2rUKMqXL6+StgWhIMrIyMDNzY0NGzbg\n6ur6yfMtLCywsLAgOTkZb29vAgMDWbduXY76+uOPPzA1Nc36et26dTg5ORW5VUjlJEamBEEN2dra\nMmnSJMaNGyd3FLUUFxfHnDlzOHToUJF9s63O5syZQ6tWrRg2bJjcUWSjo6NDampqrtqIjY3l8uXL\njBkzhsGDB1O+fHlcXV3ZsWOHilIKQsG0Z88eoqOjcXBw+Kzrvv/+e6ZMmcKhQ4cwNjbO0TWXL1/G\nzc0t62tbW1sSEhJ4+/btZ/UtfDlRTAmCmipdujRpaWlyx1BLJ06coFmzZjRo0EDuKIKKJScns3Xr\nVmbPni13FFlpa2vn+ufH7t27adCgAc7OzgwePBiAtm3bcvnyZVVEFARZPH/+nNmzZ+Po6Ejjxo0J\nCQl55/jt27f5/vvvuXz5MpUqVfqstlNTUxkxYgR16tTJ8TWxsbHZFj/S0tIiPj6epKQksbpvPhDF\nlCCoqfbt23P58mWeP38udxS1VNhXHxLe7+DBg9SrVw8zMzO5o8jK2NiYmJiYXLWRkJCAm5sby5Yt\ny3rNxsaGBw8e5DaeIOS7zMxMRo8eTbly5Th58iRLlixh6NChfP3116xevTrrvAkTJjBjxgzq1av3\nWe2fO3eOEydO8N13333WdZUrV+bu3btZXysUCgYOHIi7uztmZmZMmjTps9orqApyUSiKKUFQU+bm\n5vTv3x93d3devnwpdxy1oqenR3JystwxhDxw4cIF2rZtK3cM2TVt2pSAgIAvulaSJJYtW8bSpUuZ\nN2/eO8dsbGwIDw/P9RRCQchP6enpNGzYkNOnT+Pp6cnBgwdp3rw5AwYM4OLFi/z00098//33zJ07\nlxs3bmBubv7ZfYwcOZJVq1bleHrf31JTUylWrNg7r02cOJGKFSty9OhRDhw4wMSJEwt0MZIT+/bt\no1KlSpw9e1buKNmIYkoQ1NjixYupW7cu9erVIygoSO44akNPT0/MR1dDkiTh5+dHw4YN5Y4iu8OH\nD39RUZmamoqbmxs7duzg4sWL2NravnM8LS2Npk2bsnHjRlVFFYQ8lZGRwfDhwzExMSE0NJRevXpR\nokSJrONWVlZZG7YnJSXRvHnzL1qWvG7duvz888+fvYqmtbX1OyNT8NeG49u2bcPJyYkLFy6wZs0a\nHj169NmZCpLk5GTS0tIYM2aM3FGyEav5CYIa09LSYtGiRTRs2JCePXvSrl07Fi5cWCQ3IVWl4sWL\ni5EpNRQcHExqaipNmjSRO4qskpOTWbJkCTt37szxNfHx8Rw5coTt27ejo6NDYGAgOjo675zz8OFD\nrK2tMTQ0FKN/QqExbdo0Hj9+zL59+z64BYadnR2zZs3KVT8bN25k5cqVNGzYEDc3N0aNGkXVqlU/\ned2ePXuYP3/+B48bGxuTnp5e6DeVt7Gx4cmTJzx58oSUlBSKFy8ud6QsnxyZio2NzY8cgiDkoa5d\nu3L79m2MjIyoWrUq69evJzMzU+5Yhdbjx4/F0s5qyM/Pjy5duhT5PcPmzZtHnTp1cHJy+uh5f/75\nJ2vWrGHIkCFUqlSJXbt2Ubt2bXbt2pWtkIK/VsEEePPmDV26dMmT7IKgKpmZmcyZM4cDBw4wdepU\nDAwM8rQ/DQ0NxowZQ2hoKGXLlqVly5ZMmTKF9PT0D14THR3No0ePaN269QfP0dTUpEGDBly4cCEv\nYucbJycnrl27BvBZH/TkVlpa2jvPxL3PJ4spIyMjlQUSBEE+RkZG/PLLL/j5+bF582Zq167N/v37\nC/08ajncuHGDmjVryh1DULE//viDatWqyR1DNpmZmcybNw8vLy9Wrlz5yfOXLl2Kl5cX9vb2hIaG\ncuDAAebOnYu2tvZ7z3dwcMDAwIA///yTChUqqDq+IKhEfHw8zZs3Z9iwYezZswdjY+N8/XlvZmbG\n7NmzCQ0N5caNGzg7O39wYMPPz4+mTZt+clphq1at8PPzy4u4+ap69ero6OgwePBgTpw4kad93b59\nGzc3NwwMDBg5cuRHz/1kMfWhH4qCIBROtWrVIigoiP/85z/MmTOHunXrcvDgQVFUfYbQ0FBRTKmh\nhIQEDA0N5Y6R716/fs3SpUv56quvOHDgAGfOnPnkA/RKpRI/Pz9mz57NhAkTsLCw+GQ/58+fR0ND\ng3LlyqkquiColFKppHfv3rx8+ZKNGzeipaXF2bNnKVmyZL5nKVeuHAcPHqRBgwaUK1eOxo0bv7Ot\ngCRJrFy5kuHDh3+yrW7durFx40ZOnjyZl5HznJaWFnfu3GHNmjU0btw4T/s6duwYe/bsIT09/ZPT\nksUCFIJQBCkUCjp16kRISAgzZsxg2rRpNG7cWOxLlUM3b96kRo0acscQVMzW1paIiAi5Y+Sbu3fv\n8t1332FtbU1ISAhbt27l0qVLOVoWfsOGDZQuXfqzNq2eNWsWy5cvR0tLPK4tFEw7duzg9evXXLp0\nCSsrK9n3a9TU1OSnn34iLS2NAQMG0LVrV7Zv3058fDy//fYb8fHxH53i97caNWrw008/sXbt2nxI\nnbcqVarEiBEj0NPTU3nbSqWSefPmMWDAAK5cucKiRYt48uTJJ0f1RDElCEWYhoYGXbp04fr16yQm\nJrJixQqUSqXcsQq0+Ph4YmJisLGxkTuKoGLly5fn2bNncsfIF0ePHqVJkyaUKVOG27dvs2PHDpyc\nnHL8vNiDBw9wcXH5rOfLYmNjqVWr1pdGFoQ89/jxY5o1a4a+vj737t0jICAgz5+VyglNTU2GDh3K\nsmXL8PT0pEyZMuzatYu9e/eioZGzt/KdO3fmyJEjYhbKR/z0008cPXqUatWqkZKSwu3btzE1Nf3k\ndaKYEgQBDQ0NduzYwcGDB6lTp07WQ55Cdt9//z19+vQRn66rIVtbW/z9/dV+2ft9+/YxYMAAfH19\nmTNnTo7eLPxb2bJlP2tD8MTERCIjI7G0tPzsvgQhPyiVSi5cuJD17+HfezcVBN27d+fw4cPEx8dz\n+vRpHB0dc3zt27dvMTIyKvIL7HxMyZIlefr0KWFhYQQHB9O0adMcXaf4WIWqUCgkUcEKQtEhSRJz\n587l9u3beHp6yh2nQDIxMSEsLEys5qeGJEmib9++ZGRk4OnpqXZvOhITE/n5559Zu3YtR44coXbt\n2l/c1tGjR1mwYEGON9DctWsXW7du5ejRo1/cpyDkFUmS6NatG2/evGHfvn1qufjamzdvsLa25sKF\nC9n2fxP+olQqOXPmDPfv36dWrVrUq1cv6/eAQqFAkqT3/lIQI1OCIGRRKBQ4OzsTHh4ud5QCKT4+\nnuTkZPEAvZpSKBRs2LCByMhIVq1aJXcclUpMTKR9+/bcvHmToKCgXBVSAC1btuTmzZtER0fn6Hwv\nLy969uyZqz4FIa8cPnyY+/fvc+TIEbUspAAMDQ0ZM2YMHTt2ZMeOHWRkZMgdqcDR1NSkVatWDBs2\njPr16+f4AzVRTAmC8A47Ozvu3bsn5lW/R3h4ONbW1mo3YiH8T/HixVm0aBHr1q2TO4rKRERE4OLi\nQpUqVdizZw/W1ta5brN48eL069ePDRs2fPLc169fc/LkSVxdXXPdryCoUnJyMtu3b2fgwIH8/PPP\nBXJqnypNmzaN5cuXs3btWuzt7fH395c7kloQxZQgCO8oVaoUGhoavH79Wu4oBUp6ejrjxo2jV69e\nckcR8liTJk1ITEzk4sWLckdRiSZNmtC+fXvWrVuX44fVc0JTUzNHS8nv3buXtm3bYmxsrLK+BeFL\nJCUlMXHiRNzc3Gjbti1ly5Zl3bp1HD58GGdnZ7nj5TmFQkG7du04e/YsK1asYNCgQXz77bckJCTI\nHS3Lq1ev8PHx4cGDB3JHyTFRTAmCkI2hoSGJiYlyxyhQPDw8MDQ0ZMqUKXJHEfKYhoYGo0ePZvny\n5XJHybX4+HjevHnD1KlTVVpIvXr1Ck9Pzxwty7xjxw769Omjsr4FIafevn1LUlISp0+fpnv37tjZ\n2fHgwQO6devG6NGj+fPPPzl79iz169eXO2q+c3Fx4ebNmyiVSszNzXM8ZTevnTt3jq5du+Lo6Mis\nWbMKxXREsQCFIAjZ2Nvbs2/fPqpWrSp3lALBx8eH8ePHExISQqlSpeSOI+SD+Ph4KlWqxLVr1wr1\nCnQpKSnY2tri6emZ45WpcmLUqFEoFApWrlz50fOePHlC9erViYmJQUdHR2X9C8LHnDp1ivnz5xMY\nGIiGhgbm5ub88MMPtGnThkqVKomp2v9ibGzMli1bCsRU3LS0NNq2bUupUqVITk4mNTWVffv2yf67\nVyxAIQjCZ9HX1ycpKUnuGAXG1q1bWbBggew/zIX8U6JECUaPHs348ePljpIrxYsXZ/ny5QwfPpzM\nzEyVtOnp6YmXlxd9+/b95Lk+Pj58/fXXopAS8oVSqWTUqFEMGTKE3r17Ex8fz6NHj7hz5w7Dhg0T\nz7x+gK+vL8OGDeOPP/6QOwra2tocPHiQR48eYWlpSe3atXF0dOTq1atyR/sgUUwJgpBNWloampqa\ncscoMG7fvo2Dg4PcMYR8NmXKFEJDQ9mzZ4/cUXKla9euaGpqcuHChVy3pVQq+fbbb9m+fXuOpkbt\n27eP7t2757pfQfiQyMhILly4wMKFC7G1tSUiIoKrV68ycOBAtLW1KVWqlPh99gnNmjVjxIgRrF27\nVu4oABgZGREQEMCff/5JSEgIQ4cOpV27dmzatEnuaO8liilBEN4hSRIRERHY2NjIHUV2jx8/ZujQ\noSQmJop9OYqg4sWL4+npyciRIwv1RtYKhYLGjRvTv3//XLd169YtypUrR7t27T557osXL7h69WqR\neLBfkIckSfTp04dmzZpx/Phxdu/ezdGjRylRooTc0QqdPn364OnpyaRJk3j8+LHccShRogS+vr64\nuLjw888/4+zszA8//MAvv/wid7RsRDElCMI7nj59ir6+vlr+Mjp06AVDhtzn0KEXnzw3NTWVevXq\nUbp0aW7duqX2S+YK7+fo6Mjw4cPZu3ev3FFypWvXripZHUtPT4+0tLQcnXvw4EGcnZ3R1dXNdb+C\n8D4BAQFcvXoVfX19du7cSb169eSOVGhVrlyZVq1acf/+fSwsLFTy4UtuaWpq4uHhwZUrV9DU1ERP\nT69APsOqJXcAQRAKlvv376vlKEyNGncICzMDyrBxI9jZ3eHePXvgr6lLoaGhnD17lkuXLpGamsrr\n16+pUqUKP/30k7zBBdnZ29vj6+srd4xcMTc3x97ePtftVKxYkVevXvHkyRPMzMw+eu6xY8fo0KFD\nrvsUhA/R19fH3t6e/fv3U758ebnjFHo7d+4EYOHChWzdulXmNP9jbW3Ntm3b5I7xQWJkShCEd0RE\nRKhdMXXo0Iv/FlKKrD/h4WY4O19g6NChmJiY0Lt3b+7cuUO7du1wd3fnu+++4/fff5c5uVAQFCtW\njPT0dLlj5EpISIhK/l1ra2vTt29fVq1a9dHzlEolAQEBtG3bNtd9CsKHvH37Fm1tbSpUqCB3FLXy\n3XffERkZyZs3b+SOUiiIkSlBEN4RHh6udsXU/v3xQJn/fhUPBAJnOHHCh379evDHH39Qrlw5+QIK\nBVqxYsVyPLWtoNLT0+P27dsqaatfv34MHTqUefPmffCcS5cuYWpqirm5uUr6FIT3mTVrltjDLA8Y\nGhoyaNAgmjZtyuHDh8W/408QI1OCILzjjz/+4Kuvvsr3fl+8SOLKlce8eKH6JdldXUsAErAFqAWs\nB8oD3rRqNU0UUsJHWVtbEx4eLneML5aWlsbhw4epW7euStozNTUlNjb2o+ds3boVd3d3lfQnCO8T\nFxfH9evXGTFihNxR1NLKlSvp1asXDRo04MqVK3LHKdBEMSUIwjvu3r1LlSpV8rVPT8+bWFouo23b\n37G0XIanZ5hK269dOw09vW+ATcBhYD8wHqhC/fqGKu1LUD/VqlXj8ePHvHr1Su4on+XPP/9k6tSp\nVKxYkTdv3rB+/XqVtFu2bFlSUlK4f//+e48nJSWxZ88eBgwYoJL+BOF9NDU1KVGihEqW/BeyUygU\neHh48Ouvv/L111+L7/NHiGJKEIQsSqWSiIgI7Ozs8q3PFy+SGDzYl+TkDOLjU0lOzmDw4AMqG6GK\njY2lRYsWjB/fAheX34GvgDQgnVGj4rG3N1BJP4L60tTUxNHRkcuXL8sdJUeuX79Onz59qFmzJklJ\nSZw+fZq9e/diaKiaDw50dHSYOHEiLi4urF+/npSUFACCg4MZPHgwtra2dOzYUUwNEvKUoaEhHh4e\nLFmyRO4oas3V1ZWtW7fSuXPnAr1xrpxEMSUIQpbIyEjKli2Lnp5ePvYZh7b2uxsqFiumSWRkXK7b\nTk1NpUuXLnTt2pX//Oc/HDlSg9u3i7FlSzq3b+uwcqV1rvsQigYnJyfOnDkjd4xPWrRoES4uLjg4\nOPDgwQOWL1+eJyPNkydPZu3atezfvx9LS0tatGhBly5dsLe359y5cwV65S1BfSgUCgIDAzl8+LDc\nUdSai4sL8+fPZ9KkSXJHKZAUkiR9+KBCIX3suCAI6sXf35/58+dz8uTJfOvzxYskLC2XkZyckfWa\nrq4WUVFjKVNGP1dtz549m+vXr+Pt7Y2GhvjsSPhyISEh9OzZk/DwcBQKhdxx3isjIwNdXV2uXr1K\njRo18q3fO3fuEBoaiqurKzo6OvnWr1C0JSUlYWDw18wCMzOzArHRrDpLTk7GzMyM27dvY2pqKnec\nfKdQKJAk6b0//MW7C0EQsjx9+jTff0iWKaPPxo2d0dXVwshIB11dLTZu7JzrQgrg7NmzfPvtt6KQ\nEnKtTp06pKamfvA5oYJAS0uLxo0bM2vWrHzt197enp49e4pCSshXd+/ezfpvsYR33tPV1aVatRp4\ne5/Jk4WiCjOxNLogCFmePn0qy8aH7u7VadOmEpGRcVhZGaukkAJ4/vw5pUqVUklbQtGmUCho3Lgx\nFy5cyNdnCj9X69atiY+PlzuGIOS52rVrA1CzZk2uX78ucxr15+l5kwsXnnDtmh8TJ0awcWNn3N2r\nyx2rQBAf1wqCkEWuYgr+GqGqV89cZYUUQJMmTQgMDFRZe0LR1rJlS7y9veWO8VHe3t507NhR7hiC\nkOcUCgV3797l8ePH74xSCar390JRmZlvePtWU+ULRRV2opgSBCHLgwcP1Gou9PPnzzEzM5M7hqAm\n+vXrR0hICEFBQXJHea/nz58TGRlJ06ZN5Y4iCPmicuXKuLu7c+jQIbmjqLX/LRRlA/y1op+qFopS\nB6KYEgQBgKioKM6cOcPXX38tdxSVkCSJa9eu4eDgIHcUQU3o6uqyfPlyevTowR9//CF3nGzCw8P5\n6quv0NTU/PTJgqAmqlevzqlTp8jMzJQ7itqysjImLU0JNAP+AF6Rnq7EyspY5mQFgyimBEEAYPHi\nxQwdOpSSJUvKHUUlAgICKFasGJUrV5Y7iqBGunbtyoIFC2jTpk2BWz1s9+7dNGrUSO4YgpCv3N3d\nSUxMZOrUqXJHUVv/WyjKEA0NY3R00lW2UJQ6EEujC4KAJEno6+vz4MED2Z6ZUiUvLy9GjRrFli1b\n1GakTShYpkyZQkxMDFu2bJE7CmlpaUyePBkfHx+uXLlCmTJl5I4kCPkqODiYHj16cOfOHYoXLy53\nHLX14kUSNWt+xYEDR6lfP/+2XygIxNLogiCQAWcYAAAgAElEQVR8lEKhQFdXVy2mB/n7+zNhwgRO\nnDghCikhz0yZMoVjx45x48YNWXMkJCTQtGlTHjx4wNWrV0UhJRRJjo6O1K5dm6VLl8odRa09fx6J\nhoZE3bpV5Y5SoIhiShAEAExNTYmJiZE7Rq4kJyczYsQI1q1bR61ateSOI6gxIyMjZsyYwQ8//IBc\nMzgkSaJ3797UqVOH/fv3i20AhCKtY8eO3Lt3T+4Yam3fvn24ubmpxQevqiSKKUEQgL/emKWmpsod\nI1f+85//4OjoSIcOHeSOIhQBw4YN48mTJ+zfv1+W/vfv38+jR49YsWIFCsV7Z58IQpFRrFgxkpLE\nUt156dChQ3zzzTdyxyhwxDNTgiBw69Yt2rdvT1RUFBoahfMzlps3b9K6dWtCQ0PV4rkvoXA4efIk\ngwYNIiwsDAMDg3zr9/Hjx9SrV48dO3bQsmXLfOtXEAqqmJgYqlWrRmRkJEZGRnLHUUumpqYEBwdj\nbm4ud5R8J56ZEgThoy5evEjz5s0LbSEVFRVFjx49WLBggSikhHzVqlUrWrRowfjx4/Otz/j4eLp2\n7cro0aNFISUI/2VqakrHjh355ZdfiI2J5Palw8TGRMqcSn0olUqSk5PR1taWO0qBUzjfOQmCoFKV\nKlUiOjpa7hhf5ObNmzRp0oRvv/2WwYMHyx1HKIJWrFjBiRMnOHz4cJ739fTpU5o3b069evXw8PDI\n8/4EoTCZPXs2vyxZROolO8zju6F3uzJBBxblS9/JycmcOHGCSZMm4ebmhouLC40bN6ZGjRq4ublx\n8+bNfMmRV65cuUKFChXEIjfvoSV3AEEQ5GdiUoFbt+7w4kVSodk3QpIkVq9ezaxZs/j111/p1auX\n3JGEIsrIyIixY8dy5MiRPF1BMiIiAmdnZwYMGMD06dPFc1KC8C9GuhrUrZzM9XCJr50yAKjNdGJj\n3DAxtVJJH+np6URHR1OyZEni4uI4cuQIhw8fJjAwkJo1a+Ls7Ey3bt0wNDTEyMgIQ0ND/P39adu2\nLfb29piYmNC8eXMGDRqEnp6eSjLlh9WrV+Pu7i53jAJJFFOCUMR5et5k0KADpKTEU7HiT2za1BN3\n9+pyx/qkDRs2sHbtWoKCgvjqq6/kjiMUYZIk8fDhQ9LS0vKsj6CgILp3787s2bMZPnx4nvUjCIXZ\n8+hblCul4Ens/573T1dq8Dz6Vq6LqZcvX7J8+XLWrVuHUqlEqVSira1N+/btGTRoEJ6enhgbG7/3\nWgcHB0aMGMGZM2eIj4/Hy8uLuXPnMnr0aMaNG1fgi6rbt29z5MgRVq5cKXeUAkkUU4JQhL14kcTg\nwb6kpLwEipGSosHgwQdo06ZSgR6hysjIYMGCBWzfvl0UUoLskpKS+O233zh+/LjK205NTWXJkiUs\nW7aMbdu20b59e5X3IQjqomzFakT8KfGt6/9eK6aZSdmK1b64zTVr1uDj48OlS5dwc3MjMDAQW1vb\nz25HX18/a6VZd3d3wsLCqFGjBpaWlvTp0+e91wQHBxMfH0/r1q2/OH9uSJLEunXrmD59OosXL6ZE\niRKy5CjoxDNTglCERUbGoa2tCdwHbAANihXTJDIyTuZkHyZJEjNmzMDS0hInJye54wgCBgYGDBky\nhBMnTqiszcePH/PTTz9RtWpVLl++zKVLl0QhJQifoFeiLE/iSqGh0CI+SYe3KcW4ljj3i0elbty4\nwdy5cxk5ciRRUVGsX7/+iwqp96levTpLly5l3LhxnD9/PtvxkJAQWrduzZo1a1TS35c4c+YMCxYs\n4MyZMwwcOFC2HAWdGJkShCLMysqYtDQlEA789clderoSK6v3T1XICy9fvkRfX5/ixYt/8lxJkhg8\neDBhYWEcPHgwH9IJQs7UrVuX06dPf/K8yMhIbt68iSRJ3LlzB0tLS2rUqMGzZ88ICwvj5cuX7Nix\ng1evXtG9e3d+//138aGBIORASEgILVq0oE2bNlTqsJDHT8MpW7EajT9QSL1+/Zrnz5/z559/EhER\ngbm5OXXr1iU5OZknT56QkpLC9OnTGTt2LJ07d86TzOPGjaNKlSp069aNwMBAbGxskCSJ48ePM2DA\nAL7++muePHmSJ33nxPz585kxYwZVq1aVLUNhIIopQSjCypTRZ/nyFgwbNhcDgx4olVps3Ng5X6f4\njRgxgujoaA4fPkypUqU+ujz7xo0buX79OoGBgQV+jrlQtFhaWrJt2zZ69uz5zqbRqamp3Lp1i5CQ\nELy8vLh+/TqOjo4oFAqqVKnClStXmDlzJvr6+jg6OhIWFsb27dupXbs2Ojo6Mt6RIBQu9+7do1q1\naixbtgwzS0vMLCt/8NzffvuNSZMmYWpqiqmpKTY2NkRHR3P16lX09fWxsLBAV1eXli1b8sMPP+Rp\nbhcXF4YOHcrixYv57bffGDx4MEFBQaxcuZLvv/+erVu3kpaWlu9Lku/evZtHjx59cAqi8D+imBKE\nIu716yB69OjCxIkjsLIyzvdnpd6+fcvly5ezlltt2LAhkydPpkaNGrx8+ZLatWsTGRnJ/PnzOXTo\nEKdPnxaFlFDgtGzZkp07d9KnTx/Kli3L+vXriYqKYvLkyZQqVQoHBweGDRtGp06dcjQKKwjC52nX\nrh1nz56lbt26DBw4kJkzZ2JoaJh1PDExkQULFrBp0yYMDAy4du0aNjY2Mib+n0qVKrFv3z42bdrE\nsWPHiIiI4OjRo9SoUYP169dz4MABVq1alW95JEli9uzZrF69utB/qHP27Fl69+7NN998w6pVq/Jk\nP02FJEkfPqhQSB87LghC4ZaRkYGNjQ3e3t7UrVtXlgxxcXGMHTsWf39/tm3bxqtXr1i8eDFPnjzB\n2NiY6OhotLW1GT16NN9///0HV0sShIJAqVTi6enJjz/+iJmZGQsWLKBRo0ZyxxKEIuPZs2dMnjyZ\ngICArM3oDQwMOHbsGI0aNWLatGlYWVkVqA/lMjIy2Lp1K3PmzGHChAm4urrSpEkTDAwMSE9PJyEh\ngZiYGDQ1NfMlT2hoKJ06deL/27vP8CrK9f373zRSCSmkkCzSCAk9tIQSESGUUAMWwEIRQXQroiiK\nwgYLoDQLAlKkCiJdRWGLIERKjAgJEAikt5W+UkjPav8XPq5ns0F+kEIiuT7H4Zs1a+65Jockc87c\nc93Jycn/+CUYsrOzadOmDTY2NvTp04cZM2YwaNAgzMzM7mkcIyMj9Hr9bX8YEqaEaMIOHDjAxx9/\nzOnTpxu6FA4dOsQTTzxBZmYmDg4Ohs/z8vKwsLC46Q6jEEIIcSfnzp3j+vXraLVaSktLadeuXYN1\nxbtbf11zr1y5kv379xMYGIifnx8LFiwgNjYWZ2fneg83Go2GwYMHM3To0AdmYfDPP/+czz//nGee\neYb9+/czZMgQli9ffk9jSJgSQtxWaGgoEydO5Omnn27oUigoKEChUFBSUnLf7r4JIYQQjdmXX37J\nmjVrSE5OpkuXLuzbtw9nZ+d6O96OHTtYv349J0+efGD+Fuv1embMmEFqaipLly5l9OjRpKam3lMw\nlTAlhLhFeno6AQEBKJVKLC0tG7ocqqqqePjhh7Gzs2Pfvn3yJEoIIYT4/+h0OubNm8fJkyc5e/Zs\nvT2hGjlyJE8++WSjuMlalzQaDY8//jhqtZrLly+zevVqBgwYcNfXGncKU7LOlBBN1F+dxxpDkAIw\nNzfn9OnTZGRkEB0d3dDlCCGEEI2GsbExixYtQqVSce7cuXo5hlarJTw8/KaOpA8KU1NT9u7dS3l5\nOe3ateOJJ57A1taWN998s9ZjS5gSogl64403+PjjjxvdInyXLl0iLy+Pdu3aNXQpQgghRKNiYmLC\nqFGj6nSB8P+WmpqKnZ0d9vb29TJ+QzMzM2Px4sVcvXqVAQMGAH+2yS8oKKjVuBKmhGiCDh06xIYN\nGwgKCmroUgyKi4sZN24ca9asMbRJF0IIIcT/b8SIEaxbt474+Pg6GS8xMZE//viDU6dOsXTp0ge+\nY27fvn3p2bMnY8eO5fTp03Tv3p358+eTkpICQFJSEs899xzvvvsuJSUldzWmhCkhmiBHR0dcXV0b\nugyDsrIypk6dSmhoKE888URDlyOEEEI0SgMHDmThwoU88sgjLFu2jKtXr3K7/gYajYYlS5bQvn17\njh49etM2vV7P/v37CQ4Opl+/frzwwgu8/fbbNGvWjPDw8Pt1Kg3Gx8eHkpISgoOD2bp1K+bm5vTo\n0QNXV1cCAwPx8PDgo48+Ijs7+67Gk0V7hWiC3NzcSE1NJTg4uMFqUKvVnDhxgq+++opDhw4xaNAg\nVq5c2WD1CCGEEP8E06ZNw9/fn127dhEaGkpRURHt27dn0KBBjB49Gl9fXyZMmICxsTFKpZJvv/0W\nHx8ffH19qaioYNq0aVy5coV///vfjBkz5oHp2ne3UlJSDDNzvLy8+OSTT1i5ciU5OTkYGxujUqnY\nvHkzvr6+dzWedPMTogn64osviIiIYPv27fV6nEWLFnHixAlcXFywsbEhOzsbpVJJZmYm+fn5dO3a\nlYkTJzJ+/HhcXFzqtRYhhBDiQVRUVMTFixc5cuQI33//PfHx8cycOZNly5Zx7tw59u3bx7Zt2xg7\ndixnz56la9eufPnll42mAdX9UlVVxdatW5k7dy7R0dF4enretL26uprq6mrmzp2LhYUFK1asMGyT\n1uhCiJtER0czcuRIMjIy6vU4ixcv5vjx40ydOpXS0lJcXV1xd3fHzc0NFxcXTE3l4bgQQghRl1Qq\nFY6Ojrd89tlnn+Hv789TTz1V74v/NkazZ8/m999/Z/ny5fTp0+embRkZGfTt25f8/Hzs7OyIjo6+\naT2vO4UpuZIRoonR6/UsWrTovqwh4ebmhrOzM88880y9H0sIIYQQ3BKk/vrs/fffb4BqGg9XV1di\nYmJYu3YtwE2B6vTp03To0IH//Oc/9zyuNKAQoolJSEjgzJkzvPfee/V+rBMnThjajwohhBBCNJQ3\n33yT+Ph4evbsyahRo0hKSjJs++WXX1AoFDUaV8KUEE1MdHQ0vXr1wsLCos7GrK6uJjMz85bPHR0d\nuX79ep0dRwghhBB3p7i4mC+//JKff/6ZsrKym7YVFBSQnJxMeXl5A1VX//R6PRs2bKBHjx4UFxcD\n4OTkxKxZswgJCWHHjh0AfP/99xw7doyPP/64RseRaX5CNDEXL14kICCgzsYrKSnhoYceIjExkR49\nejBmzBgKCgq4evUqp0+fZs2aNXV2LCGEEELcnVOnTvHuu+/Spk0bLl68yIgRI3BwcODkyZOkpaVh\na2tLaWkpBQUFD+Q7VLNmzSIiIgJXV1feeecdysrKqK6u5l//+hfh4eF89tlnKJVKnn/+efbv34+t\nrW2NjiNPpoRoYqKjo+natWudjVdQUEBOTg4FBQXMmjWL69evY2pqypgxY7h69SqPP/54nR1LCCGE\nEHfH29sbtVrN7t27iYuLo2/fvnh4eLBp0yZUKhXp6emUl5dTWVnZ0KXWudzcXHbt2sX+/fv54osv\n2LdvH61ateLixYssX74cgI0bN9K7d29effXVWi0VI938hGhiFAoFx48fx93dHRsbm1qPp9Vqsba2\nJjc3FysrKy5cuGBYv0EIIYQQDWfevHnExsZy4MCB2253cXHh4sWLuLq63ufK6k9xcTGdO3dm0qRJ\nLFq0CPhzyp9arSYwMJAPP/wQlUrF3r17mT9//l1ds9ypm588mRKiCcnIyKCqqooDBw7g7OzM1KlT\nqaqqqtWYJiYmPPPMM7Rt25aOHTvy0EMPcebMmTqqWAghhBA1tWDBAk6ePEl2dvYt2/bu3YuJiQnW\n1tYNUFn9WbhwIUOHDjUEqb+89NJLeHl5ERoaysSJE/n+++/r5OavhCkhmpDIyEh69+7N8ePHWbZs\nGTt37kSr1dZ63C+//JL169cDYGNjw7Fjx2o9phBCCCFqx9zcnKCgIH766aebPk9PT2f16tWsXbuW\n5s2bN1B1dUuv17NkyRIOHjzIkiVLbtr2wQcfcOHCBXbu3Imxcd3GHwlTQjQhv//+O2q1msjISFxc\nXAgKCsLKyqrW4+7cuZPp06fzzDPPcO7cORYuXFgH1QohhBCithYuXMibb76JUqkEICIigs6dO/Pr\nr7/Srl27Bq6ubiQlJTFy5Ej2799PREQETk5OAGg0Gl555RV27NjBjz/+WCevN/wv6eYnRBMybtw4\nysvLadeuHRcuXKiTNaAOHz7MvHnzOH78OF26dKmDKoUQQghRV/r06cPMmTMJCgrCy8uLK1eusGvX\nLszNzfH392/o8mqlqKiIZcuWsWHDBubMmcNrr71Gs2bNDNujo6NZvXo158+fr7f3wiRMCdGE5OXl\n0adPH0aMGEFoaCiLFy+u9Zjnzp3j6aefliAlhBBCNFLz5s0jLCyMvLw8HB0d63SJlIZw5swZVq9e\nzdGjRxkzZgxRUVG0bt0a+HO63759+/j444+JjY3Fzc2NiIgIunXrVi+1SDc/IZqQoKAgTE1NiYmJ\nQaPRoFKpsLS0rNWYTz75JEOHDmXKlCl1U6QQQgghxG3o9Xo+/fRTli5dynvvvceoUaNwc3O76Ts/\n/PADs2bNYsWKFYwePRoTE5NaH/dO3fwkTAnRRFRXV2NnZ0deXh46nY7U1FQ6depUo7FSUlI4deoU\nOp2O1157jUuXLqFQKOq4YiGEEEKIP5WWljJt2jQSEhLYv38/np6et/3e0KFDeeqpp5g8eXKdHftO\nYUqm+QnRRFy+fJk2bdoYWqDWJEjpdDpWrVrFokWLGDRoEGZmZixatEiClBBCCCHqjV6vZ/LkyZib\nm3P69GksLCxu+73jx48THx/PhAkT7lttEqaEaCIOHz5MYGBgrcbYtWsXmzZtIiIigrZt29ZRZUII\nIYQQf2/r1q0kJSXx22+/YW5uftvvVFRU8Prrr7Ns2bK//U59kNboQjQBq1atYuPGjbz11lu1GmfT\npk3Mnz9fgpQQQggh7puMjAzMzc1ZsGABS5cuJT4+3rBNr9fzzTff0K5dOwICAnjsscfua23yZEqI\nB9y6deuYNWsWn332GRYWFuj1eoyMbjvt9//Upk0bFi1aRJcuXWjfvn0dVyqEEEIIcavZs2fj6uqK\nSqUiMzOTvn370rNnT1q0aEFSUhIajYavvvqKhx9++L7XJg0ohHjAXbx4kT179nDhwgV++uknxo4d\ny/79+2s0ll6vZ/PmzcydO5exY8fSq1cvRo4ciYuLSx1XLYQQQghxe0VFRZw4cYKqqipsbGwYNmxY\nnXTt+zvSzU+IJi4/P58pU6aQl5fHrl278PHxqdV4CQkJHDlyhFWrVjF58mTmz59fR5UKIYQQQjQu\nEqaEaOKGDx+Oj48Pn3zyCWZmZnUyZnV1Na1bt+bMmTP4+vrWyZhCCCGEEI3NncKUNKAQ4gEXGxvL\nhQsXWLFiRZ0EKbVazbZt2wgICODhhx+WICWEEEKIJkvClBAPuG3btvHss8/+7ZoM96KkpITOnTuz\nfft2Vq9ezZ49e+qgQiGEaJxWrFiBjY0NO3bsIDY2loqKioYuSQjRyEiYEuIBZ2xsjI2NTZ2MtXz5\ncgIDAzl+/DghISE17goohBCNnU6nY+XKlbz//vvs3r2bMWPGYGVlRWJiYkOXJoRoRKQ1uhAPOEdH\nR5RKZa3HUSqVrFmzhqioqDqoSgghGje9Xk9OTg62trYMGjSIbt26sX79ehwcHBq6NCFEIyJPpoR4\nwDk6OqJSqWq8f05ODvPnz6d79+68/vrreHh41GF1QgjROJmYmDBr1iwiIiJITExErVazb98+7O3t\nG7o0IUQjIk+mhHjAubu7ExUVhVqtvucGFLm5uQQHBzNo0CB+/fVX/P3966lKIYRofD755JOGLkEI\n0cjJkykhHnAhISF4enrWaC2orVu30qNHD9atW1dvQeratWtotdp6GVsIIYQQoj5JmBLiAWdsbMyY\nMWO4fPnyPe/br18/rl69Wme1xMfHM3nyZDp27Mirr77KuHHjCAwMpEePHoSHh9fZcYQQQggh7gcJ\nU0I0Ad9//z1hYWH3vF+vXr3Iy8vj119/rXUNEydOJCgoCFtbW3r27ImZmRkdO3bk1KlTODk5MXfu\n3FofQwghhBDifpIwJUQTMHHiRHbu3El8fPxd7/PHH3+waNEivL296d+/P1u2bKlVDVeuXMHZ2Zmv\nv/4apVLJzp07WbVqFWFhYbRs2ZKvv/66VuMLIYQQQtxv0oBCiCbg0UcfJScnh169ejFgwADefvtt\nevbsecv31Go13377LZ988gmXLl1Cp9Nha2uLr68ver2+VjVERkaydetWBg8ejJeXF1FRUbi4uODm\n5larcYUQQgghGorRnS6QjIyM9LW9gBJCNA6lpaU0b94cAGtra4YPH86aNWtwcnIyfGfhwoV88803\nZGZm8vLLL/P888+Tk5PDU089xYcffsj48eMbqnwhhBBCiAZhZGSEXq83uu02CVNCNB2//PILISEh\nmJubA3/+cpgyZQrPPvssPXv2ZPjw4eTm5jJjxgxmzJhh2O/ChQuEhoYSHR0tT5KEEEII0aRImBJC\nGCQnJxMWFoZCocDGxoYjR45QWVmJsbExarWarl27cvbsWSwsLG7ab+HChRw8eJB3332XsLAwTExM\nGugMhBBCCCHuHwlTQoiblJaW8t5777Fp0yaee+45RowYwenTp8nLy+PDDz/Eysrqln10Oh0HDx5k\n6dKlFBcXM23aNHr06EHnzp1vmioohBBCCPEgkTAlhLgtpVLJ4sWL2bVrF2PHjmXWrFl06dIFI6Pb\n/r4AIDY2lh9++IGUlBQuX77MhQsX6NatG6dOnbqPlQshhBBC3B93ClPSGl2IJszd3Z21a9cSHx9P\nmzZtGDVqFDY2NnTu3JkXX3yRixcvGrr4abVajh8/zpAhQ1i2bBmZmZnY29tjY2PDK6+80sBnIoQQ\nQghx/8mTKSHETW7cuEFiYiI//PADGzdupLi4GIVCQWFhIa1atWL27NkMGjSIY8eOYW1tjaenJ926\ndWvosoUQQggh6oVM8xNC1FhhYSEZGRlYWlri6+vb0OUIIYQQQtxXEqaEEEIIIYQQogbknSkhhBBC\nCCGEqGMSpoQQQgghhBCiBiRMCSGEEEIIIUQNSJgSQgghhBBCiBqQMCWEEEIIIYQQNSBhSgghhBBC\nCCFqQMKUEEIIIYQQQtSAhCkhhBBCCCGEqAEJU0IIIYQQQghRAxKmhBBCCCGEEKIGJEwJIYQQQggh\nRA1ImBJCCCGEEEKIGpAwJYQQQgghhBA1IGFKCCGEEEIIIWpAwpQQQgghhBBC1ICEKSFEgzl16hRh\nYWH4+vri4eHBokWL0Gq1DV2WEEIIIcRdMdLr9X+/0chIf6ftQghxL3Jycrh27RrR0dHs3r2bzMxM\n5s6dC8CePXtIT0/n4sWLWFlZNXClQgghhBB/MjIyQq/XG912m4QpIUR9KioqYtWqVXzwwQdoNBrD\n505OTjzxxBPs2rWLtm3bMmzYMF566SWcnJwasFohhBBCiJvdKUyZ3u9ihBAPtuTkZNavX8/PP/9M\nVlYWWVlZhm0vvfQSvXv3plWrViQlJZGens6FCxfw8vJquIKFEEIIIWpInkwJIepEZWUlM2fO5ODB\ng0yePJlHHnmE0aNHExISwttvv80jjzyCiYlJQ5cphBBCNCqZmZnY29tjaWnZ0KWIv3GnJ1PSgEII\nUSt6vZ6oqCgeffRRCgsLiY+PZ+XKleTk5DBu3DiOHTtGSEiIBCkhxF3T6/VUVFQgN3T/mYqLi1m4\ncCELFy7k2LFjN03xFrd6/PHH8fDwYPPmzQ1diqgBCVNCiBpRq9V89dVXdO/enbFjxxIYGMjOnTux\nt7cHwNnZmfPnz3P16tUGrlQI0Vjp9XquXbvGxo0b+de//sXAgQPx8PDA0tISOzs7mjVrhrOzMwEB\nAYwYMYKVK1eSnp7e0GU3Wnq9npKSkgY7vk6nY/v27bRv35709HQ0Gg3vvPMOCoWC+fPnU1RUVOOx\nq6qqOHz4MDt27ODLL7/kjTfeoHPnzvTr148FCxaQk5NTh2dyf6jVamJiYrh+/Tpff/01c+bM4caN\nGw1dlrhH8s6UEOKe6PV6jhw5wuzZs2nVqhUffvghQ4YMwdjYmJKSEtavX096ejpKpZK0tDS2bt3K\nsmXLGrpsIUQjkpeXx9KlS9m/fz9arZb+/fsTGBjI2LFj8fX1xcXFBSsrK6qrqykoKCArK4uUlBR+\n/PFHOnfuTExMDAqFoqFPo9FZunQpixcvZsuWLTz++OP37biVlZVs27aNL774gmbNmvHtt98SFBQE\nwOLFi4mLi2PZsmX4+fnx8ssv8/LLL+Pg4PB/jvvXzIc9e/awdetW/P39USgUWFpa4uHhwaZNmygu\nLua7776jU6dOzJo1ixkzZmBtbU1FRQW2traYmZnd9Xmkp6fz66+/kpubi1arpW3btvj6+tKqVSvs\n7e3Jzs7m6tWrhsBja2uLQqFAoVBgbW2NXq8nKSmJy5cvExcXR0JCAoWFhZSXl6NWqw3nlJ+fT0ZG\nBkVFRTg6OvLvf/+bwYMHM378eJ566in27t0rU/7+QeSdKSHEXUtLS2PKlClkZmaycuVKhg8fjpGR\nEVqtlp07dzJv3jz69u1L9+7dcXFxISQkhNatWzd02UKIBlZSUoJarcbY2Jhz587x0Ucf4eLiwty5\nc+ncuTNGRrd9FeG2nn32WSIjI3nuueeYMmUKjo6O9Vh541VaWopOp8PGxoYbN26wfft2lixZwsaN\nG5kxYwZvvPEGjz76KJ6enjf9fNVqNaamprf8zP/u8/+l1+vR6XSYmJig1+v55ZdfmDlzJp6enrz6\n6qsMHjwYY+PbT3yKi4tj6dKlHDx4kIkTJ+Lt7Y2ZmZlhrOLiYpRKJenp6SQnJ5OSkkLLli0ZN24c\nkyZNon379n9bV2xsLCtWrODrr78GwJ5PPt8AABhqSURBVNLSEhMTE8aNG0dISAhBQUG4u7vfcn56\nvZ5z586xdu1aDh06xKBBg3BzczPUm5SURFZWFqWlpdjZ2dGhQwccHR3R6/XcuHHDcPOwWbNmADRv\n3pyAgAD8/Pxo27Ytjo6OWFlZYWZmZji2o6Mj7u7uODk53TQFvrq6milTpnDu3DkGDx6Mn58fFRUV\nlJSUUFlZiVarRaPRUFZWRmFhIRUVFYZ9tVotarUanU6Hubk5FhYWWFpaYm9vj4ODA8HBwYwYMUKm\n3NeQtEYXQtRaTk4OQUFBvPDCC8yZMwdT0z8fbF+9epVJkyZhbm7OsmXLCA4ObuBKhRCNgU6nIzw8\nnC+++IIjR45gZmaGWq2mU6dOjBgxgtmzZ9doTTmdTsepU6fYvHkzhw4dYtiwYXh7e9OqVSt69uxJ\nUFDQ3wYCjUbD8ePHcXd3p0OHDn970d+Q9Ho9V65c4ccffyQiIoLs7GxcXV1xcHAgNzeXjIwM0tLS\nqKysxNTUlLKyMiwsLBgxYgRz586le/fuXL16lQULFnDmzBkqKytxdnbGxsYGpVKJSqXCyMgIR0dH\nmjdvTrNmzSgrK0OpVKLX63F0dCQ4OJjAwEBDqNFqtYYnKnFxcVRXV6NQKLCyskKtVrNkyRIeffTR\nuw7FaWlpbN68mcLCQkMAgD+DSOvWrVEoFHh5eeHt7Y2dnd09he3/lpyczDfffMOZM2eIjIwEwNXV\nlZYtW2JtbW146mlsbMz06dOZMWOGYar6/6qurjYEpv+l1+spLCxEp9PRsmXLGtX632P99ttvREZG\nkpiYiLW1Nc2bN8fS0hJTU1NMTEywsrIyNKz462djbGyMmZkZxsbGVFVVUVVVRVlZGUVFReTn5/Pt\nt99y48YNoqOjsbCwqFWNTZGEKSFErcXGxhISEkJGRobhAiQxMZGgoCA+/PBDpk+fXuM/eEKIf66K\nigrCw8P56aefOHbsGABeXl7ExsZiaWnJ888/z+TJk7G1ta3zY2dnZ/PDDz+QmZlJVlYWP//8M82b\nN+fpp59mzJgxtG7dmmbNmpGQkMB//vMfPvnkExwdHQ0XmP7+/nh6euLl5YWnpyetW7fGyckJR0dH\nw1MaDw+P+xK6NBoN58+fZ/78+Vy/fp2wsDAeeughFAoFOTk5FBQU4OzsjLu7O56enjg6OmJkZIRO\np0Oj0dz2Ql+v16NSqcjLy6O0tBR3d3dcXV1Rq9Xk5+dTWlqKWq3GwsICLy8v9Ho92dnZnDx5kqio\nKDw9PfHx8TGMbW9vj5+fH1ZWVqSmppKXl0dQUJDh5lpj9te55eXlkZ+fT1lZGfb29rRs2RI/P79G\nGazrUnh4OEOGDGHbtm0MGzaMFi1aNHRJ/ygSpoQQtabX6wkMDOT9999n+PDhAOzcuZMVK1YQGRn5\nt3fshBAPloKCAq5cucIff/zB0aNHOXPmDAEBAYSGhjJkyBCaNWtGcnIybm5uBAYG3tebLDqdjl9+\n+YXdu3dz+PBhcnNzMTIywsXFhUceeYQZM2bw0EMPAZCbm0t8fDypqamkpKSQmppKeno6+fn5qFQq\ndDodZWVlhIWFsXHjxnqpNyYmhiNHjnD8+HHOnj2LQqFg+vTpzJw58x8RUMQ/h06n49ChQ3z++ef8\n9ttveHl50bt3b4KDg+nbty++vr4yBfAOJEwJIWqtuLiYrl27smvXLnr37g38OUd7woQJxMfH8+67\n7zJ48GCsra0buFIhmja9Xs++fftYvXo1rVq1ws/Pj6lTp9ZocezCwkJ++OEHTpw4QUJCAvHx8ZSV\nldGhQwe6du3K4MGDGThw4N9OjWpoer2eyspKLCwsahTqSktL6dWrF7NmzeL555+vs7rS09OZPXs2\nZ8+eZezYsYSEhPDwww832fe/xP2lVqu5fPkyZ8+eJSIigrNnz5KVlWV4Eunl5YWHhwceHh74+Pjg\n7+9vaBii1+s5fvw4e/fupV+/fowYMaLR/vuvSxKmhBD/p5iYGFauXElMTAzl5eWsXr2aAQMGAH9O\npRkzZgyBgYGsWrXqposSvV7Pnj17WLduHX/88QeDBg3ixRdfZPDgwTLtT4j7TKfTMWPGDH777Tfe\ne+89ysvLOX/+PLt37+aNN95g0KBBWFtbo1KpcHBwwNfX95YxTpw4waFDhzh//jxRUVEMHDiQ0NBQ\n2rVrR5s2bVAoFE3q33ZcXBzBwcGcPXuWtm3b1no8lUpF//79GT16NPPnz6/Re2NC1LXKykqSk5NJ\nTEwkNTWVtLQ0UlNTSUxM5Nq1axgZGdGsWTOMjIxwcHDg2WefJSIigvDwcIYPH87UqVPp168f5ubm\nDX0q9ULClBDijk6cOMG4ceN488036devH3l5eUybNo0DBw7Qp08f2rZtyzPPPMPChQvvOK+8uLiY\n3bt38+mnn9K3b1/Wr18v0waEqGd6vZ6ioiJOnz7N2rVrKS0t5ciRI9jY2Bi+Ex4ezq5du/jll19Q\nq9W0bNmStLQ0HnnkEV5++WWCg4NRqVQcPnyYN998k9dee43u3bvTt2/fm8Zpqtq0acOhQ4fo0KHD\nPe9748YNUlNTiY+P5/r162zcuJHx48ezZMmSJhVKxT/XX50WNRoNarUaZ2dnw9/2wsJCtm/fztdf\nf83Vq1fp1q0brq6uODk54ezsjJubG+7u7gwYMOAf3e5dwpQQ4o5efPFF2rRpwxtvvGH47Ntvv2Xm\nzJns3LmTCRMmkJmZedfjlZaWMnjwYJ566ilmzpxZHyULcddu3LjBunXr8Pb2ZujQoahUKlJTUwkI\nCPjb6SklJSWEh4dTUFCAtbU1NjY29OrVCzs7O65du8alS5fIyMggJyeHiooKQ9tiMzMzLCwscHV1\nxd3dHWdnZ2xtbWnZsmWdPNXQ6/VER0dz5MgRzp8/z6VLl0hPT8fCwoIuXbrw9NNPM3HixLt62lFW\nVsb69evZunUraWlpAPTu3Zt58+bRr1+/Wtf6T/f777+zbds2jh07hpmZGZcvX75j+MnNzeXtt9/m\n0qVLqFQqKioqKC0tRa/X4+Hhga+vL/7+/gwcOJBhw4bdxzMR4v4oLCwkKiqK3Nxc8vPzyc7OJisr\ni9jYWKqqqvj444/p0aPHP/IGjYQpIcQdzZo1C29vb1599dWbPl+zZg2rVq0iNzeXX3/9lc6dO9/1\nmFeuXOGRRx7h2LFjBAQE1HXJQvyt6upqUlJSuHz5MuHh4ezbt4/+/fuTn59PeHg4rq6uuLm5kZaW\nxqpVq3jssccMF8lpaWk899xz/PbbbwQFBeHm5kZZWRn5+fnk5ubi6enJ5cuXCQ4Oxt3d3bC4rKWl\nJcbGxmg0GioqKsjOziYjI4O8vDxKSkpITk4mNDSUjz76CFdXV0Ob6aKiIioqKqiqqjLUr9PpUKvV\nVFdXk56ebph2k56eTlxcHBYWFowaNYpevXoREBCAp6dnraeKZWVl3XS3uSkrLy8nLCyMuLg4Xnzx\nRUJDQ+nSpcsdn8pnZmYyYMAARo0axWOPPYaLiwuWlpZYWVlha2srT6BEk6bX61mzZg07duzg8uXL\n+Pr6Mn36dKZOnfqPmeYqYUoIcUejR49m/PjxPP3007dsmzp1KikpKSiVSiIjI7Gzs7vrcffu3cuL\nL77I2rVrGTduXF2WLP4hVCoVarX6lsUp64JGo0GpVJKamsq1a9c4c+YMERERpKamolAoaN++PQ8/\n/DDDhg0z3AjQ6/WGC9vTp08zbdo0/Pz86Nq1KzExMZw+fZo5c+bw0ksv3fJHfvv27ej1ep588sl7\n7l5ZWlrK/Pnz2bZtG35+fsTHxxvW9LG0tMTc3NxQl5GREWZmZpiZmeHu7o6vry9eXl60bt0ab29v\nfHx85OK8HlVXV+Pq6krXrl0xMjKif//+LFiw4G+/HxUVxQsvvMCwYcN4991371+hQvwDVVdXExkZ\nySeffMLRo0fx8fGhTZs2tGjRArVajVarNdyEsLCwQKPRoNFosLCwwM7ODgcHB8PyAN7e3vet6ZWE\nKSEE8OfF56lTp/j1119JTEzE1NQUU1NTfvjhB65du3bbdWAKCwtp06YNjz76KElJSRw5cuSeXjC9\ndOkSISEhREVFoVAo6vJ0RAOrrq7m6NGj3Lhxg+bNm+Pk5ESvXr0MF/p79uzhxRdfxMTEhMLCQgYM\nGMC3335rWGiyuLiYxMREkpKSyMrKIjs7m/z8fCwtLWnevDnBwcGEhoaiVquJiIjgwoULxMTEEBcX\nR2pqKllZWbi4uODp6Ymvry99+vShb9+++Pv733XYqaqqYvXq1RQVFdG5c2e6d+9+26YMdSU/P5+r\nV6/Srl07nJycJBQ1UteuXSMmJoZ58+YxevRoli9ffst3UlJSeP3114mMjOT111/nlVdekSd7QtyD\nkpISEhMTSUhIoLS01LAocXl5OTdu3KCyshIzMzNMTEyorKyksLCQgoICMjIyDE0y/P396dOnDz17\n9qRr16507NixXpZqkTAlBH/ekU5ISODatWu0atUKhUKBs7PzA79QH/z5bsQ777zDN998g0KhIDQ0\nFF9fX7RaLRUVFYZfRH+nW7duLF++nNWrV6NQKFi9evU9HX/EiBHMmDGD0aNH1/ZURCOxZcsW3nrr\nLdq1a4e7uzslJSVcv34dPz8/QkJCsLCw4PXXX+fs2bN069YNjUbDuHHjOHz4sOEuI/z5Yr+3tzfu\n7u60atUKR0dHKisrKSkpYcOGDXTt2pWzZ8/i7e1Nnz596NSpk2GhVYVCIeubiXqRmprK8OHDCQoK\nYvXq1bfc/U5KSqJ///48//zzzJkzx/D/sxDi/qmqqiIqKoqzZ88SFRVleF/r2WefZcGCBXX61ErC\nlBD8+f7Pyy+/zJAhQ8jNzUWpVKJSqbC2tsbW1pYWLVrQunVrvLy8sLS0NGz/4IMP6Nu3b0OXXyvx\n8fEEBARw8OBBhg4dilarJSsri7S0NBITE1Eqlbz11ls33SWvrq4mIyODo0ePsmLFCmJjYyktLaV1\n69bk5eXdU1ee1157DTs7OxYuXFgfpyfuo6KiIpYtW8bOnTv58ccf6dSpk2FbdXU169atIyUlhcrK\nSuzt7Vm8ePEtY6jVaioqKmjevPkdn8wkJydz8uRJhgwZgru7e72cjxC38/jjj3Pq1Ck+++wzfH19\ncXZ2RqfTERcXR1RUFCtXrmTRokV1uvaUEKL2oqKi6Nu3L9HR0fj7+9fZuBKmRJOVkpKChYUFLi4u\nZGVlMWHCBJKSkujRowf+/v5UVlaSnZ1Nbm4uZWVl5OXloVQq0Wg0mJubY25ujlar5cSJEwQGBtao\nhuLiYmJiYujbt2+DTenR6XTMmzePTZs2YWFhQU5ODg4ODnh6ehIZGQnA22+/jUajITY2lsuXL5OV\nlYWbmxuenp6sWLGCHj16sGXLFj788ENiY2MxNTW96+NfvXqV/v37c+HCBVq3bl1fpynqSXV1NeHh\n4Xz33Xd88803jBw5kkWLFsm0TfHAqqysZN++fezevZvMzExyc3MB8PPzw9/fn+nTp9OtW7cGrlII\n8d8uXrzImDFjGDJkCOvWravTay4JU6LJCgkJ4eTJk4YnT9bW1hgZGVFUVERZWRk6nQ4HBwdcXFxo\n1aoVfn5+hi5MlpaWaDQasrKyGD16dI060qWnpzNs2DAKCgrw8/Njzpw5dOzYEQ8PD4yMjCgpKaGo\nqAiFQnHP0w3/+0X6u1VdXU1aWhoKhQILCwu0Wi0fffQRxsbG6HQ6jI2N8ff3x9/fH3Nzc7Kzs0lK\nSiIyMpKTJ0/SrFkzNmzYUKNgOX78eHr27MmcOXPueV9x/2i1WhISEoiKiuL8+fNERkYSFRVFx44d\nCQsLY9y4cbRp06ahyxRCCCEMLl68yNChQ/n000+ZMGFCnY8vYUrc0fXr11mwYAEFBQUEBATw0EMP\n8fDDD+Pg4HDLdy9evMjXX3+Nr68vbdu2xcfHBzc3N8NTisLCQpKSkujevXujeLF67969rFixgh9/\n/JHS0lJKS0upqKjAysoKa2trTE1NycjIICkpifPnz3PkyBGKiorYtGkTgwcPNpzXX6FKqVQaXpaM\nj48nIyODrKwsQ8vk4OBgfHx8uHHjBsXFxRw4cIBXXnmFV199lc2bN7N7926uX7+OSqVCq9Vibm6O\nlZUVzs7OzJkzh3bt2mFubo6FhQVOTk7Y29vf8nMsKChg3LhxXLt2jWeffZYxY8ZQWVmJSqWivLyc\njh070qFDhzu+CK1Wqw0Xyn+1XP7rPPLy8igrK6NVq1aGjjmBgYH07t2b3r171/gds7i4ODp37syN\nGzce2BXS/8kqKytZtWoVn376KZaWlnTr1o1u3brRq1cvAgMDadGiRUOXKIQQQtwiMjKSsLAwPv/8\nc5544ol6OYaEKXFHe/bsYfz48bfdZm9vz4YNG3j88ceBPxd0jIyMpEePHlhaWpKcnExeXh4uLi6k\np6cb9isuLr5tZ7i/VFVV8fPPP3Po0CF69uzJpEmT6uUCW6vV0r17dyZNmsTs2bPvKuCFh4czadIk\nlEolJiYmWFpaUlZWhpOTE+7u7vj4+NC2bVvatm2Lh4eHYaXvxMREzpw5Q1paGi1atKBFixZ07dqV\ngQMH3nKMsrIyTExMsLCwQK/X89NPP7F69Wpyc3OprKykoqKCvLw8KioqcHNzo2PHjgQEBFBVVcWW\nLVuYMmUKkyZNYsuWLRw7dgxbW1scHBywtLTk8uXLKJVKxo4dy6uvvoqZmRkqlYqcnByio6P5/fff\nOXfuHD4+PgQHBxtaLru5ueHs7IyzszN2dnZ13phj//79vPXWWyQkJNTpuKJuTJgwgfT0dL744gu6\ndOnS0OUIIYQQt5WYmMiOHTtITU0lNTWVS5cusXXrVkaMGFFvx5Qw9YCpqqoiNjaW9PR07OzscHZ2\nRqFQUFFRQU5ODtnZ2VRXV+Pt7Y2Xl9dNXYb0ej2FhYUolUry8vKwsbHB0dERBwcHqquriYqKMrQc\nPnLkCL///juTJk1i27ZtACQkJLBp0yZ27dpFVlYWtra2WFpaGmoJDQ3F2dmZ5ORkkpOTUSqVeHh4\n0KlTJ3x8fFAqlcTFxRETE0OXLl0YOXIkx48fJzU1lePHj+Pm5gb8+Y4PUCcX9NeuXeOZZ56hqqoK\nDw8P7OzsaN++PXPmzLljgNPr9VRVVVFeXo6tre09vSNUV8rLy1EqlcTExHDp0iUqKip44YUX8PLy\nuuN+KpWKdevWsWXLFszNzXF0dKRly5YEBAQQGBhIr169cHR0vC/noFKpWLhwId999x27du3ioYce\nui/HFXdPq9Uybtw4Tp48SfPmzTlw4ADdu3dv6LKEEEIISkpK+OOPP7hy5QoXL17k4MGDTJ48mfbt\n2xuuMf+6fqwvEqb+wQoKCoiJiSE6Opo//viDCxcukJiYiI+PD56enhQXF5OTk0NGRgZWVla4uLjg\n6uqKqakpKSkppKWl0bx5c3Q6HRqNhqqqKiwtLQ1PIcrKylCpVKhUKsrKymjevDn29vZYWFhQVVVF\nVVUVGo0GY2NjTExMMDExMawDYGJigk6no6KigurqakpKSujQoQPDhw+na9eueHt74+bmRmpqKjEx\nMSQlJdG6dWvatm1Lx44dcXJyMpzn8uXLWbZsGdOmTSM9PZ2jR49iZGTEyJEjCQsLo0uXLjg7O9d4\npWyNRkNkZCSFhYUUFxezf/9+4uPjWbZsGaGhoY1iSuKDIjMzk7feeou4uDhDR8TnnnuO9957774F\nOHFvioqKOHToEAcOHODSpUtcuHBBpvUJIYRocJcuXWLUqFEoFAo6depEx44dGTt27H1vZiVhqoEU\nFxeTkpKCv7//LWtQZGVlERERQUxMDFVVVWi1WjQaDcXFxYZwk5CQQElJCZ06dSIgIIAePXrQvXt3\nOnTocNdrWmi1WgoKCgwhyMzM7G9bWmu1WoqKiigsLKSqqsrQzc7MzAytVnvTfxqNBq1Wi16vN7zj\n81eTh5qKj49n3bp1+Pn5ERoaik6n47vvvuP7778nMTGRnJwczMzMaNeuHf369aNPnz6YmZlRXl5O\nWVkZmZmZJCQkkJiYSGVlJebm5jRr1gwrKytatWqFm5sbbm5ueHl54e3tzeHDh3njjTf48ccfGT58\neI3rFn9Sq9Vs27aNf//730yfPp3hw4fj5uaGq6urrAXUCP31O2jfvn0cPnyY/v37M3bsWMLCwrC3\nt2/o8oQQQjRh6enpfPTRR+zevZtVq1bx1FNPNWg9tQpT9VaVEEIIIYQQQjR+qXq93ut2G+4YpoQQ\nQgghhBBC3F7dtusSQgghhBBCiCZCwpQQQgghhBBC1ICEKSGEEEIIIYSoAQlTQgghhBBCCFEDEqaE\nEEIIIYQQogb+HyINWSR6uFugAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x117cd99d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#the cartopy map, going simple outline for now\n",
+    "plt.figure(figsize=(15,15))\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "\n",
+    "for j,hashtag in enumerate(popularHashtagsList):\n",
+    "    subset = latLonPopulated_HT[(latLonPopulated_HT['hashtag'] == hashtag)]\n",
+    "    if len(subset.x) == 0:\n",
+    "        pass\n",
+    "    else:\n",
+    "        plt.scatter(subset.x,subset.y,color=cm.jet(j/float(len(popularHashtagsList))),label=hashtag)\n",
+    "\n",
+    "handles, labels = ax.get_legend_handles_labels()\n",
+    "ax.legend(handles,labels, loc='best')\n",
+    "plt.axis([-180, 180, -75, 75])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Although in theory we like this visualization, it's a little hard to tell what hashtags originate where -- there are too many colors. And the points are too much -- let's try doing a heatmap of hashtag distribution. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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lT3qH/nxJSUl8++23rF27lt27d5OTk1NkDhQYGEhISEi+LKhWrVqFMpu0tLR8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pgpaKDx7oMaipgoqSpsu0rn08a3lCwRPKnr+/i1lR1bCaaQGBht/9ASq37CDEY+IYHAVG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\nJvMsJETtWEIIIYQQQggh0jCNRkOTJk1o164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4eM38ao540oH7CQrK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\nAQAAA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ll63aCerZsyfjxo1j0qRJmM1mq4wphBBCCCGEEEIIIS7ucp2gYcOGMX/+fEaN\nGkVAQAA//fQTra2t13xdGxsb5syZw3vvvcfRo0eveTwhxKXJJo9CCHGLaGlpwdHR8ZLPSUtL4403\n3iA9PZ3hw4czefJkq9x4Cw4OZtGiRYwZM4bvvvvumscTQgghhBBCCCGEEJfW0tKCk5PTRX/fycmJ\nb775hnXr1pGamspbb71FVlaWVa79z3/+k/r6esaNG0ddXZ1VxhRCCCGEEEIIIYQQF3YlnaARI0Yw\nc+ZM3nzzTW677Taefvppq3SCwsPDmT9/Pvfeey/r16+/5vGEEEIIIYQQQgghxKVdrhPk4uLCt99+\ny9dff83IkSN5+eWXyc7Otsq1Z8+eTVFREY899hgNDQ1WGVMIIYQQQgghhBBCXNjlciCA+++/n7//\n/e+89957JCcn8/zzz1vl2tHR0Xz88ceMHDmSLVu2WGVMIcSFySaPQghxi9ixYwfJycmXfd6UKVPo\n2LEj4eHhZGdn8/7771vl+sOHD2fNmjW8+OKL/Pvf/7bKmELcrCoqKiguLkan07X3VIQQQgghhBBC\n/AE1NzeTkZFBUlLSJZ/n7e3N0qVL+fe//80777zD/fffT21t7TVf38HBga1btxIUFETv3r2pqqq6\n5jGFuFnp9XpycnKora21yuYYQgghhBBCCCHE1brSTtCzzz6Ll5cXiYmJZGRkMG/ePKtc//7772fV\nqlU89dRTfPTRR1YZU4ibVVlZGSUlJbS1tbX3VIQQQgghhBBC/AHV19eTmZlJQkLCJZ/n5+fHkiVL\n+O9//8vrr7/OfffdZ5VNGZ2dndm5cyfu7u7069dPDn8Vt7S2tjZycnKoq6uTTpAQQgghhBBCiHZx\npZ2g9PR0bGxsGDhwIFu3bmXRokVWuf64ceP46quv+Mtf/sKCBQusMqYQNyuVSkVpaWm7dIJsLhU+\n2djYmCWcEkKIm4fJZOLs2bOcOHGCkpISnJyccHZ2xsnJiWnTprF9+/bLLu4HKCgooHv37hw6dIih\nQ4fy4YcfMmbMGKvMUaVS0adPH1atWkVKSopVxhTiejObzWi1WlxcXLCxsbnk8z7//HNeeuklXF1d\nqaysxM3Njb59+7J27dpL7pJvMpmora2loqJCeQB06NABDw8PvL296datGzY2NtjY2GA2my8+ESGE\nEEKI60SyICGEuLnU19dz4sQJTp06RVtbGy4uLri4uLB9+3Z0Oh1Lly69onEee+wxkpOTqaqqYu/e\nvWzbtg0XFxerzDE9PZ2srCzWr19vlfGEuBF0Oh12dnbY29tf8nmlpaU89NBDFBcX09zcjFarJTAw\nkI8//pjRo0df8rVarRa1Wq3kQPX19bi5ueHh4UGHDh2IjY3F399fciAhhBBCtBvJgYQQ4uZiNBrJ\ny8vjxIkTqFQqpRPk4ODAtGnT2LdvH507d77sOGfOnCElJYV9+/aRmprKggULuOeee6wyx8LCQvr3\n78+6devo06ePVcYU4nozmUzodDqcnZ0v2wmaO3cur732Gi4uLlRVVeHm5kZKSgrff/89Dg4Ol7xG\nTU2NkgOp1WpsbGzw8PDAw8MDHx8fkpOTpRMkhBBCiHYlWZAQQtxc6urqlE6QwWDA2dkZFxcXNm7c\niJOTEwsXLryiccaOHcuQIUPIzs7m5MmTyuutYfr06ahUKlatWmWV8YS4EVpbW7G3t79sJ6iwsJCx\nY8dSUVFBY2Mjra2tBAUFMX/+fO6+++5LvralpcWiE9TQ0IC7u7uSBcXFxeHr6ys5kBBCCCHajeRA\nQghxczEajeTm5iqdoHM5kK2tLc888wyHDx8mMjLysuMcPXqU4cOHs337doYOHcpXX33FsGHDrDLH\n3NxcUlJS2LZt2xVtOinEzeBqOkHvv/8+b7/9Ns7OzlRVVeHh4UFqaiqrVq3Czs7ukteorq626ATZ\n2toq+wT5+vqSmJh42U6QbPIohBA3ObPZzJEjR1i6dCnffvstZrOZnj170rFjR/R6PVqtFq1Wy6BB\ng5g2bdoVj9urVy/mzJmDh4cHw4YNY8OGDVYrYP/jH//Azs6O119/3SrjCXG9lJSUsGTJEhYvXkxJ\nSQkGgwF3d3fc3d3p06cPc+fOJSwsTHn+vHnz+Pjjj/nuu+/o0qULJpOJuro6Jk6cSGtrK8nJycpN\nOZPJRH5+PmfPnuXs2bMUFhbi5uZGUFAQwcHBBAYGYmNjQ2NjI01NTRQUFHDnnXcyb948HB0d5Uae\nEEIIIdqFZEFCCNH+GhoaWL16NUuXLiUjI4PExEQSEhJwdnZWciCA//73v4SGhl7RmN9//z3z58/n\nxx9/5LHHHsNoNPL1119f8gbGldJqtfj4+NDc3HzJmxpCtDej0ciGDRtYvHgxmzZtQqfT4ejoiLu7\nO97e3syaNYsnnnhC+Xuh0+mIioriqaeeYubMmdja2tLa2srevXt55JFHeOSRR5QcyNXVFbVareRA\nZ8+epbGxkaCgIOXh5eWFRqOhqamJxsZGioqK+PHHH+nRo4fkQEIIIYRoF5IDCSFE+zObzRw6dEjp\nBDk4ONC9e3c6duyITqdDq9XS2trKHXfcweTJk6943ISEBJYsWYLJZGLkyJFs27aNbt26WWXOL7zw\nAn5+frz00ktWGU+I66WoqIhFixaxZMkSysrKLDpBAwYM4OOPPyY4OFh5/vvvv8+SJUv47rvviI6O\nVg5zfeyxx7C3tychIUFZrG80Gi06QUVFRbi7uys5UGBgIABNTU00NTVx9uxZRo8ezQcffCCdICGE\nEEK0G8mChBCi/dXV1bFq1SqWLVvGkSNHSEpKIj4+HicnJ6UTZGtry/vvv6+8t7yc5cuXs2rVKr79\n9lseeughPDw8WLRokVU6QfX19YSHh9PY2GiV8YS4XgwGA+vWrWPRokVs3bqVtrY2pRPk6+vLa6+9\nxrhx45Tv4+bmZmJiYpgxYwbPPvssNjY2aLVaduzYwV/+8hfGjRundILc3NwoLy+36AQ1NzdbdII6\ndOhg0QkqKSlhy5YtJCYmSg4khBBCiHYhOZAQQrQ/s9nMgQMHWLp0KatWrcLDw4Pk5GTCwsKUTpBW\nq2XkyJH8+c9/vuJxo6KiWLduHXV1dTzwwAPs2rWLrl27WmXOTz31FLGxsTzzzDNWGU+I6yU/P1/p\nBKnVaqUT5OHhwW233cZHH31EQECA8vy3336b77//ntWrVxMREaEc5vrwww/j6elJXFyckgUZDAaL\nHKi4uBgPDw+LTpDZbFZyoLy8PMaPH8+//vWvS3aCLn0ciRBCXEB+fj6bN2+mrq6OsLAwQkNDCQ0N\nJTg4GA8PD2xtbdt7ireMoqIi7r77btra2pgwYQLbt2+nc+fO1zxuc3MzRUVFhIaGEhUVxYIFCxgz\nZgx5eXmXPHX8SsXFxbFhw4ZrHkeI62nnzp089NBDjBkzhq+//prevXtjNBqVG2uLFy+mZ8+e9O7d\nW9kN//Dhw7zwwgt06dIFAFtbW3x9ffniiy/4+uuvlQ0bKysrgZ/fJN15551ER0fTqVMnXF1dLzqf\n5uZmRo8ejZeX1w35/IUQQgghhBDiSmi1Wnbv3s3Bgwfx8fGxyIJ8fX2tdvK7+Nmrr77Khx9+SFpa\nGk899RQjRozA2dn5msc9fvw4HTt2xNbWloULFzJo0CAWLVrEk08+ec1ju7i4EBgYSGFhIdHR0dc8\nnhDXQ2trKw8//DClpaVMnTqVxYsX4+HhQWtrK01NTeTl5TF16lQ++eQTgoODcXFxwWQy4eDgQHp6\nujKOs7MzaWlpLF26lKysLJqamlCr1Wg0GgICArjrrruIiooiOjqaoKCgSy5yWL16NUOGDLkRn74Q\nQgghhBBCXLG8vDw2b95MY2MjoaGhShYUFBQknSAry8vLY8SIEdjY2PDoo4+ye/duYmJirnnc+vp6\nysvLCQ4OJjQ0lI8//pgxY8aQnZ1tlT+/uLg49u/ff83jCHE9bdmyhUcffZTx48ezevVqevTogdFo\npLm5maamJj7//HO6d+9Or169cHFxwdnZmYyMDF5//XUl47S1tcXPz4+lS5eyYsUKi06QjY0NsbGx\n3H333URFRdGpUydcXFwuOp+GhgZGjRolnSAhhBBCCCHETaWltm/TBwAAIABJREFUpYVdu3Zx6NAh\nfH19LTpBPj4+0gmyspkzZ/LZZ59x11138dxzzzF8+HAcHR2vedysrCw6duyInZ0dX375JQMGDGDF\nihWMHz/+msf28vLC1dWV8vJyQkJCrnk8Ia6HlpYWHnzwQWpra5k6dSrLly/Hzc0NrVZLc3Mz2dnZ\nTJkyhQ8//JCAgABcXFzQ6/V4e3vz3HPPKeO4uLgwYsQIvvjiC06dOkVzc7PSCQoMDGT48OFER0cT\nFRVFYGDgJTtBy5cvp3///jfi0xdCCCGEEEKIK2I2m8nNzWXz5s1oNJrzOkHu7u7SCbKiU6dOcc89\n9+Do6MiECRM4ePAgnTp1uuZxq6qqqKurw9/fn4SEBGbPns3YsWPJysqyygEdnTt3Jjs7+5rHEeJ6\nWrduHU8++SQTJkxg3bp1dOvWDb1ej0ajobGxkU8//ZTk5GR69uypdIL27dvHe++9R0REBPBzJ8jf\n358VK1bwzTffKH2iiooK7OzsiIuLY8SIEURHRxMZGXnJtZ21tbUMHz4cb2/vS87b5lI7cMsO3UKI\nX9u4cSMjRoxg/PjxdOzYEZVKRWlpKSqVioqKCjQaDW5ubnh4eNChQwd8fX2JjIxUHkajkdLSUkpL\nS2loaOCdd95RNksT5ztz5gx33nknubm5F/1H32AwUFZWRllZGT179ryim3xPP/009fX1fPXVV8rH\nevXqxQcffMDgwYOved4ZGRlMnDiRY8eOyWlt4qZjNBpZtmwZL7zwAitXriQ1NfWiz83NzSUnJ4fW\n1la0Wi06nY777rsPX1/f6zI3vV5PdXU1ISEhclqbEEIIIdqFZEFCiF+zsbHBxcWFadOm0djYaJEF\n1dbWYmNjQ4cOHZRHWFiYkgP5+/ujVquVLKh379689NJLkhVcwoMPPsiwYcOYPHnyBX/fbDbT0NBA\ncXEx7u7uREVFXXbM3NxcBg4cyN69e5XDQ77//ns+++wzNm/ebJV5Dxs2jKeeeop7773XKuMJYU0F\nBQX89a9/xdvbm6VLl140P21ra2PXrl20tLQoWVB4eDhpaWnXbW4VFRUEBwdLDiSEEEKIdiE5kBDi\n17755hvGjRvHhAkTCAkJOa8T1NLSgpubm5ID/boTpNfrlec3NjYye/Zsq2xaeKvKzMxk7NixnDx5\n8qKbJuj1esrKyigvL6dXr15XdHDrxIkTsbW1ZcGCBcrH4uPjWbJkCX369Lnmee/atYsZM2Zw8ODB\nax5LCGszGAwsXryYl19+me+//56BAwde9LnZ2dnk5eVZdIIefPDB67YRY1tbG7W1tZIFCSGEEKLd\nSBYkhPg1GxsbvLy8mDJlCvX19ed1gmxtbZUcyNPT06IT5OfnR0VFhdIJSklJ4bnnnpNO0CWMHDmS\nhx9+mMcff/yCv282m6mvr6ekpIQOHToQGRl52TFPnjxJamoqGRkZykYBy5cvZ+XKlfzwww9Wmfeg\nQYN49dVXufPOO60ynhDWlJeXx1/+8hc6duzIokWLsLe3v+DzWltb+emnn2hpaUGr1dLa2kpkZOQl\n15Ndq3Obo0oOJIQQQoj2IDmQEOLXFixYwOTJk/nTn/6Ev7//eZ0grVaLu7u7sk+Qn58fkZGRdOrU\niYiICHQ6nfJ8jUbDf//7X2WzNHG+ffv2MWnSJDIzMy+6fkWv16NSqVCr1fTu3Rs7O7tLjmk2m5kw\nYQJ+fn58+OGHyseioqJYt24diYmJ1zzvTZs28e6777Jz585rHksIa9Pr9Xz++ee88cYbrF+//pI9\nuFOnTlFQUKDkQG1tbYwdOxYPD4/rMjedTkd9fT1BQUEXzYIunFoJIcRF9O/fn5EjR1JQUEBaWhoP\nPfQQCQkJStnYZDJRU1OjlLubm5tRqVQUFhayb98+ZTfbxMREtFott99+O5s3byYpKamdP7ObU3R0\nNN27dycsLIzx48eTlJREUVERhYWFFBUVUVxcTEVFBXq9Hg8PD44ePaos7m9qauLEiRNkZWVx5swZ\niouLlYeHhweHDh1SrqPT6aipqbHKKXAA3bt3x9bWlrlz5/L0009bZUwhrpVOp2P16tW89dZbeHt7\ns2HDhssuYIiNjSU2NvYGzRAcHBwIDg6+YdcTQgghhBBCiMtZuXIlf/vb37C3t2fUqFH06NHD4n1L\nS0sLFRUV1NbWotPpqK6uVrKLzMxM/Pz88PPzIyEhgc8++4yKigrmzJkjpe6LmDBhAlOnTmXZsmU8\n9NBDtLS0nJcFaTQaTCYT06dP54MPPgB+zuQKCgrIysrixIkT5OfnKzlQSUkJH3zwgbLBI0BZWZnV\nciCAP/3pT7zwwgsMGTIET09Pq40rxLXIycnhP//5D9999x1PP/00r7zyykXL3ACOjo43fFFCUFDQ\nDb2eEEIIIYQQQlxKWloaw4YNo6ioiKFDhzJ+/Hji4+OVDMFoNFJTU4NarUar1SoHghQWFrJnzx7s\n7e3x9/cnKSmJxsZGUlNT2bZtmxz+ehFdu3YlJiaGsLAwHn30Ubp27XpeDqRWq9Hr9Xh5eZGVlUVY\nWBgAjY2NSifo9OnTSgZUXFyMn58fBw4cUK5z7pTyK9kg8kr07duXpqYmPv/8cyZNmmSVMYW4Vlqt\nllWrVvHWW28RHBzM5s2b6d69+yVfExcXR1xc3A2a4c/Zk2RBQgghhBBCiJvJV199xbPPPoujoyOj\nR4+mR48eBAYGAj8vEG9paUGtVlNXV0draytVVVVKdnHkyBH8/f0JCAggKSmJjz76iKqqKv71r39J\nJ+giHnvsMaZNm8aiRYsYM2YMzc3N52VBLS0tmEwm0tPTeeedd4CfM7n8/HxOnDhxXieotLSUefPm\nKRs8wvXpBE2fPp2DBw/i7u5utXGFuBanT59m9uzZrF+/nmeffZb09HRsbW0v+nxnZ+cb3gmStWFC\nCCGEEEKIm8no0aNZsWIFRUVFDBkyhEcffZT4+HilS2I0Gqmurr5gJ2j37t04Ojri7+9Pt27dqK6u\nZsiQIWzbtk0Of72Ibt26ERQURHh4OI899hgxMTHn5UCVlZXo9Xp8fX05deoUAQEBANTX1190n6Cw\nsDD27t2rXKepqQmtVnvJdTJXIyUlBZVKxdKlS5kwYYJVxhTiWrW0tLBixQr++c9/0qlTJ7Zv337Z\nTU3j4+OJj4+/QTMEJycnJVu/GJtL7cAtO3QL8cfW0tLCokWLiImJISkpieDgYGxsbDCZTCxevJid\nO3eSmZnJ2bNn8fLyorm5mZaWFmxtbXF1dcVoNKLVaoGf/0EymUzodDocHBxwdnZWdrsNCAigvLz8\nkmH6b7Vt2zZ27NjB9OnT8ff3t/r4N0phYSFLliyhuLiYyMhIIiIiiIiIIDIyEpVKRUpKCs7Oznh5\neWFvb4/JZKKuro6uXbuSlJREfHw8kZGRdOzYkY4dOxIYGKjs5J2VlcWLL76Ii4sL33//vdXmfObM\nGW677TaqqqrkJq1oN1VVVWzatIk1a9awdetWevbsSXp6OnfeeedN/X1pY2Mjp7UJIYQQol1IFiTE\nH9uOHTsoKSkhOTmZLl264OzsDEB2djYLFy4kMzOTzMzMc+9Z0Gg0tLW14erqir29vZL1ODo6Ym9v\nj06nw2Qy4eLigo2NjVJE/uyzz5g8ebLV56/RaHjzzTcZMmQIw4cPv6nf912KXq9nw4YNrF27Fm9v\nbyIjI5VcJyIigoceeoitW7fi7++Pg4MDdnZ21NbW4uPjQ1JSEomJicTGxio5UHh4OG5ubsDPp5J/\n+umnvP322/zvf/+jW7duVpv3mDFjuOOOO5gyZYrVxhTiahgMBg4fPsyaNWtYs2YNNTU1TJw4keee\new4fH5/2nt5FSQ4khBBCiPYiOZAQf2xNTU18+eWXxMbGkpycTGBgIDY2NhiNRv7f//t/7N69m8zM\nTAoKCi7YCTIYDGi1WmxsbCw6QY6Ojjg5OaHVatHr9YSFhVFcXHxdcpqNGzeyb98+nn322Zv6fd/l\n5Ofns3jxYsrKyiw6QREREZw9e5a0tDRcXFzw9PTE3t4eo9FIQ0MD8fHxJCUl0bVr1/M6Qec6WJmZ\nmTz//PMEBQWxfPlyq8356NGjjBo1itLSUquNKcTVUqvVSido+/bt9O3bl1mzZpGamnpTZ8OSBQkh\nhBCivUgWJMQf29atW1Gr1SQnJxMXF4eTkxMAJ0+eZNGiRUonyM7ODpPJZNEJsrOzQ6fTWXSCWltb\nMZvN53WClixZwuOPP271+Tc2NvLWW28xbNiwG75RmzW1tbWxbt061q9fj5+fn7Iu7FwnaNSoUezZ\ns0fpBNnb21NdXY2fnx9JSUkkJSURExNj0QlydXUFfl4DOHfuXGbPns2ePXvo2rWrVeZsNpsZNWoU\nDz30EE888YRVxhTiaun1eg4dOsTatWtZs2YNDQ0NTJ48mWeeeQYvL6/2nt5FSQ4khBBCiPYiOZAQ\nf2z19fUsW7aMuLg4kpKSCAgIwMbGBoPBwIIFC9izZw+ZmZkUFRXh6elJc3MzWq0WOzs7XFxcLDpB\nzs7OGAwGJRf6ZScoNjaWnJyc6/I5rF27liNHjjB9+vSb+n3f5eTm5rJ48WIqKyvP2yfo+PHjjBo1\nCldXVzp06IC9vT0Gg4GmpialExQfH09ERISSBQUEBCidoEOHDvH8888TExPDF198YbU579+/n8cf\nf5zc3FyrjSnE1SovL2fjxo2sWbOGHTt2MHDgQGbNmsXgwYPbe2qXdKksSDZ5FEJcVH19PaGhoURH\nR1NeXk5NTQ2urq64ubnh7u6Oo6MjLS0tNDc3o9Fo0Ol0+Pn5ERUVRVRUFNHR0QwePJiBAwcCYGdn\nh5OTk/JDg8lkoqamhpaWFiIiIqw+/yVLljBz5kxGjhzJmjVrmDlzJk8++SS+vr5Wv1Z7q62txWAw\nKA+A0NBQZSPHc3Q6HaWlpWRmZnLgwAH2799PXl4e6enpTJ06VblRay0RERF88cUXpKWlWXVcIS6k\nsbGRY8eOcfjwYQ4ePMjBgwepra0lNTWV0aNHM3LkSGUH+5ud3MgTQgghRHuRLEiIP7aXXnqJhQsX\nEhgYSE5ODra2tri5uSkPg8GARqNRTvpycHAgIiJCyYISExO56667CAkJQa/X4+zsjL29vbKgVqvV\nUl5eTlBQkFIwtpbKykpGjRpFWFgYp06dIjw8nLfffpsePXooJ8vdKlpbW2lubrbIgry8vM67cWk2\nm6mpqSE3N1fJgXbv3k3fvn155513Lntq1dX6/PPPWbFiBVu3br0uh7kI8Usmk4mzZ8+SmZlJRkYG\nBw8eJDMzk06dOjFq1Cjuvfde+vXr97v4XpQcSAghhBDtRXIgIf7YqqqqCA8PJy4ujtLSUurq6nB1\ndcXd3R03NzccHR3RaDRoNBqam5vR6/VKJyg6Opro6GiGDBnCgAEDMJlMF+wEVVdXo9PpCA8Pt/r8\n58+fz+uvv87dd9/Nhg0bmDVrFo8//vjverPHCzGbzdTV1V1RJ6i1tZXS0lKOHDmiZEGFhYW88sor\nTJo0CUdHR6vOKygoiO+//17phQlxPTU0NHDs2DH+7//+T+kENTQ0MHToUKUT5Ofn197TvCKSBQkh\nhBCivUgWJMQf2zPPPMPXX3+Nr68vubm52NnZKWvD3Nzc0Ov1NDc3K4v6HRwciIyMVDpBycnJDBs2\njKCgIKUT9Ms+TktLC2VlZYSFhSmHylpLeXk5I0aMIDY2liNHjhAXF8dbb71FcnIy9vb2Vr1We9Nq\ntWg0GossyNvbG09PT4vnmc1mqqurycnJsegEDRo0iLfffpsuXbpYdV4fffQRmzdvZv369Tf1wQri\n1mA0GsnLy7PoBB09epSYmBhGjRrF6NGj6d27t3SChBBCCCEuQXIgIf7YVCoVkZGRJCYmUlRURH19\nvbIuzN3dHQcHB6UPpNFo0Ov1+Pv7Ex0drfSCUlNT6d+/PwaDAXt7+/M6QVVVVcrhr9b20UcfMXv2\nbNLS0tiyZQv/+Mc/eOSRR/D29rb6tdqT2WymtrYWo9Go5EA2NjaEhoae955Xq9VSUlKidIL27duH\nSqXi1Vdf5cknn7Tqujmj0Yi/vz9bt26lV69eVhtXiIupq6uz6ARlZGTQ1NREWloao0ePZsSIEb+b\nTqBs8ij+8PR6PXv37sXOzo4+ffpc1Q0jk8lEW1ub1W8y/V48++yz2Nra8t5772E0Gi02dWxra7P4\nYc7JyYnKykry8/PJz88nOzub7du3k5WVRWpqKpMnT2bkyJFXdX29Xk9BQQFFRUVUVFRQXl5ORUUF\nOp2Ovn37kpKSQnR0tHKTyGQy0dTUxNy5c1m4cCEbN26kS5cuZGdnk56ezvbt27G3tycuLo64uDgA\nqqurlUd0dDQzZ8685hO9jxw5wuzZs7nnnnt48MEHcXFx+c1jXYnGxkZKSkooLS1FrVZTWVlJVVUV\nVVVVVFZWolKpUKlUNDQ0EBQURLdu3ejfvz/9+/enX79+uLm5XZd5bd26lccff5wzZ86cd1NRCGs4\ncuQIc+bMYd++fZSXl5OUlESPHj3o168f/fr1Iy4u7ndx4+7X5EaeEEIIIdqLZEHiVlFSUkJmZibd\nu3enY8eOV/VarVaLs7PzH7KQWlZWRmJiIjk5Ofj6+qLT6SwW8zs4OCjlbjc3N9ra2igsLFSyoEOH\nDrFp0yb8/f0ZNWoUs2bNuqo84NymhGfPnqWsrEzJgdRqNeHh4aSkpNC3b1+LHEOn05Gbm8v999/P\nuHHjePPNNzEYDMyfP58PP/yQkpISIiMjiYuLIzg4mLq6OiUH0mq1PP744/z973+/ppt9BoOBV155\nBb1ez8SJE+natetvHutKr1deXk5JSQllZWVK/nMuC6qoqKC0tBSVSoWrqytRUVH069eP/v37M2DA\nAGJiYq7LvPR6PXfccQejRo3ixRdfvC7XEH9sGo2Gzz//nFWrVnH8+HF8fX3p3r07ffv2pW/fvvTp\n0+d3mUFKDiSEEEKI9iI5kLhVtLW1sXfvXhwdHendu/dVHW5pMpnQ6/VWPxDz92LKlCn4+fnxz3/+\nE6PRqORAv+wEncuCnJycUKvV5Ofnc/bsWbKzs9m2bRunT5/m9ttvZ+rUqQwbNuyqrt/W1mbRCTrX\nC9Lr9fTr14+UlBQ6dep0XifovffeY/ny5WzatImYmBhOnjxJeno6O3fuxMnJibi4ODp37qxsNFlT\nU0N1dTWdO3fmpZdeYtCgQdf0dTtw4AAffPAB9913H/fff/9175Q1NDRYdIJ+2Qf6ZSeosbGRkJCQ\n8zpB16uztG7dOqZOnUp2dvZ16x2JP7ZDhw4xZ84c9u/fT2VlJcnJyRadoNjYWOkECSGEEEJcBcmC\nxK2iqKiIY8eO0bNnz6teRP5H7gQVFhbSq1cv8vPz6dChAzqdTlkbptFocHR0VLIgV1dXdDqdRSfo\n4MGDbN68meDgYO655x5mzZqFu7v7FV//3KaEF+oERUZGctttt9GnTx+LHKO1tZXTp0/zwAMPMHHi\nRGbNmoVer+eTTz5h7ty5qFQqOnXqRFxcHEFBQdTW1iqdoLa2Nv70pz8xderUa+oR6PV60tPTsbW1\nZeLEiXTu3Pk3j3UlDAYDZWVlFp2gX2ZB5zpBZWVluLm5ERUVpeRAAwcOpFOnTtdlXjqdjiFDhjBh\nwgSeeuqp63IN8cfW1NTEggUL+Pbbb8nKyiIgIIDu3bvTp08f+vXrR+/evenQoUN7T/OqSQ4khBBC\niPYiOZC4Veh0Ovbs2YOrqyu9evW6qsMtz22c90ftBD3xxBN07tyZl19+GYPBQEtLi8VBr+dyoHOb\nPqrVas6ePUt+fj5nzpxh27Zt5OTkcMcdd/C3v/2N22+//aqur9PpKCgooLi4WMmBysvLMRqN9O/f\nn5SUFCIiIiw6QY2NjbzzzjusW7eOjRs3EhkZybFjx5g1axa7d+/GxcVF6QQZjUaLfYLi4+NJT09n\nwIAB1/R1++mnn/jkk0944IEHGD169HX9/jGbzRftBFVVVaFWq5VOUFNTE6GhoXTv3l3Jgvr27Xvd\nOkvffvstL7zwAjk5OVY9VFaIc/bv389HH33E/v37qampITk5mZ49eyqdoJiYmN9lji+bPIo/tFGj\nRrFhwwYAunbtSnFxMd27d2fQoEEMHTqUlJSUixZNzWYzY8eOZc2aNYSGhtK5c2c6d+5MVFQUERER\nysPLy4uioiJycnLYunUr9vb2/Oc//7mRn+Z1U1paSrdu3Thx4gTBwcG/aYyamho2bdpEeno6jzzy\nCGlpaRYbAhgMBuWHC5VKRUlJCWfPniU3N5fS0lLCwsKIjIwkODiY4OBggoKCsLOz48CBA+zduxed\nToeLiwv19fU0Nzfj5uZG9+7d+eabb86bs9lsprKykuzsbHJycrC1tcXPzw8/Pz98fX3Zv38///rX\nv/Dx8WHgwIE4Ozvj5OSEs7Mz7u7uBAUFKXMIDg4+74ceg8HAsmXLePHFF5k+fTp79uwhIyODhx9+\nmMDAQGpra6mpqaG2thadTmexCPmXP4ReSlVVFbt372bnzp3s2bOH/Px8DAYD4eHhhIeHExQUhL+/\nPwEBAcqvISEhhIWF4e/vf0PLra2trfj7+6NSqX6XN1PEzau2tpYJEyZw/Phxnn32WUaMGEHnzp2x\ns7Nr76lZhdzIE0IIIUR7kSxI/N7V1NTg5+cHQFRUFE1NTTg7OzNo0CCGDBnC7bffbnFYxK8dPHiQ\n1NRUHBwc6Ny5M7GxscTGxhIZGankQOHh4Wg0GnJycsjOzuarr77ik08+UQ6T+L2bPHkyXl5ezJ49\n+ze93mQy8X//93/Mnz+fffv28e677+Ll5aVkQc7OzlRXVyubEKpUKgoKCsjLyyMvLw+AmJgYQkND\nlQwmICCA/Px89uzZw/HjxwkKCqK5uZmGhgbMZjPe3t688cYbTJ48+bz5tLa2kpeXR05ODhUVFfj4\n+ODn54e/vz8Gg4GPP/6YdevW8cADD+Dj42ORBfn5+VnkQL6+vud97+Tm5vLMM89gNBrp1asXixcv\nJioqiuHDh9Pc3KzkQLW1tQQGBtKvXz/69u1Ljx49rmiBvcFg4OjRo+zcuZOdO3dy7Ngx1Go1fn5+\nhIeHExoaapEB+fv7ExQURFhYGCEhIbi6uv6mP8ff6pVXXsFsNvP222/f0OuKW9/ixYuZMWMGgwcP\nZvLkyfTu3fuWOYlRciAhhBBCtBfJgcStIDU1lV27dgHQpUsXSkpK6Nmzp9IJGjhw4EXfG5vNZkaN\nGsWWLVsIDw8nNjb2gp0gT09PCgsLycnJ4ccff8THx4e33nrrRn6a101+fj59+/blzJkzSqZ2taqq\nqti4cSOzZs3iySefZPDgwRYHxur1elQqlZIF/bITpFKpCA8PVzpB5zIYQOkEGY1GHB0daWhoQKPR\n4ObmRq9evVixYgUBAQEWczGbzVRUVJCdnU1ubi52dnb4+/srnaBdu3Yxe/ZsgoKC6NevH87OzkoW\n5OHhQVBQkDKH4ODg84rabW1tfPnll6Snp/P888/zv//9j8zMTMaPH4+vr6+SAdXU1KDX6+nRo4fS\nCbrSg2gqKyvZtWuX0gkqKCjAZDIpnaDAwMDzsqDQ0FDCwsLw8/O7oZ2gpqYmgoODqaqquu6H34o/\nlqqqKh555BGys7N57rnnGD58ODExMdIJEkIIIYS4RpIFid+70tJSwsPDgZ97JfX19bi7u3Pbbbcp\nnaBfHhbxa7t27WLYsGE4Ozsra8NiY2MtcqDw8HCamprIycnh9OnTLF++nPnz5xMdHX0jP9Xr5vHH\nHycqKorXX3/9N73eaDRy6NAhPvnkE44ePco777yDp6enkgU5OztTVVV1wU7Quazm150gf39/8vLy\n2LNnDydOnCAoKIimpiYaGhoA8PHx4d133+WJJ544bz5arZa8vDyys7OprKzE19dXWR/W1tbGhx9+\nyKZNm3jggQfw9vZWsqBznaBf5kA+Pj7nfe+cOXOGp59+GmdnZ7p27cqSJUvo2rUrd955J01NTRbr\nw0JCQpROUPfu3a9ogb3BYODIkSNKJ+j48eNUVlbi7+9PeHg4ISEhBAYG4u/vrzyCg4OVTtCNzmOe\nf/55vL29eeWVV27odcWtb8GCBbz88sukpaXx17/+lZ49e+Ll5dXe07IKyYGEEEII0V4kBxK3gt69\ne3P48GEA4uLiKC0tpXfv3konaMCAARd9b2wymRg2bBi7du2iY8eOSg70606Qh4cHBQUF5Obmsm7d\nOiIiIpg1a9aN/DSvm9OnTzNkyBBycnJ+83sstVrNhg0beOWVV5g6dSoDBgywODC2ra3tvE7QubVh\n5eXlF+wEmUwm9u/fz969ewFwcHCgvr4ejUaDu7s7/fv35+uvv8bHx8diLmazmfLycqUT5ODgoKwN\n8/HxYfv27fz73/8mIiKCXr16WeRAv+4EBQUFndcJ0ul0fPHFF7z22mu88MILbN68maysLB555BG8\nvb0tciCDwaAcUNm3b98rPoimoqJC6QTt3buXgoICgAt2gs71gn7ZCbqRG97V1NQQFRVFdXU1Dg4O\nN+y64tZXXl7O+PHjKSoq4vnnn2fYsGHExMT8Lg95vRDZ5FH8oS1atIh169ahUqk4ceIEvr6+NDY2\nKjd8zunWrRsvv/wyY8eOVT6m1WpxdXVl8uTJDB06FA8PD3JycpRT5M89GhsbMZlMnPv7MmHCBL76\n6qurnmtRURGrV6/mf//7H/fffz+PPfbYTbGr8UsvvcTx48dZtmzZNS2cVavVvPjii6hUKuW0N41G\ng52dHaGhocojLCyM6OhoZROFy30NVCoVBoMBT09PPDw8rrnQaTQaWb9+PXl5ebS2tqLT6WhtbaWx\nsRG1Wk15eTnl5eXKiXHJyckkJyfj4uLC3LlziYiIYPbs2fTr1w+A4uJili1bRktLC76+vvj4+ODj\n44O9vT2ZmZkcPHiQAwcO0KlTJ/7xj38wfPhwDAaDUv68EfOuAAAgAElEQVSurKzk2LFjHDp0iIyM\nDCoqKkhJSSE1NZXBgwfTuXNnvL29b7pdiM1mM7Nnz2bdunXKD9lCWENbWxt33XUX8fHxvP/++7fk\nCQpyI08IIYQQ7UWyIPF719LSwsMPPwzA0aNHaW5uxt3dndLSUovnOTk5MXbsWObNm2dxqvzTTz/N\n3Llzef/990lMTEStVpOTk2ORA6lUKmxtbdHpdMrriouLlSL5ldLpdGzfvp1vv/0WOzs7Xnzxxet+\n2vuVKCsrIykpiaVLlzJ8+PBrGmvRokWsXLlSOe1No9Gg1WqVxefnHhEREcqGmhcqTf+SVqultLSU\nDh064OnpaZVTxwoLC1m7di1arVbJgrRaLdXV1UoOVFZWho2NjZIDJSQksGPHDrZv385TTz1Feno6\njo6O6PV6fvzxR/bu3Yu3tzc+Pj74+vri7e1NaWkpBw8eJCMjg/z8fCZPnsxzzz2Hn5+fRfk7Pz+f\nQ4cOcejQIQ4fPkx4eDipqamkpqbSu3dvQkNDb4rM8NcKCgq44447WLhwIUOHDm3v6YhbyPr165k4\ncSJbt24lKSmpvadjdZIDCSGEEKK9SA4kbgXz589ny5YtlJSUcOLECfz9/amvr6exsdHieT179uTV\nV19l9OjRyseampro0KEDf//73xkyZAiurq4X7AQ1NTVhNBqV102ZMoV58+Zd9Vzz8/NZvXo1u3bt\nYuzYsTzyyCM3RQn2mWeeobi4mMWLF+Pp6fmbxykrK2PGjBmUl5dbdILs7e3P6wTFxMQQExNDZGTk\nJb8GZrOZ0tJSTCaT1TpBBoOBtWvXUlBQQGtrq5IFNTY2UlFRoWRBlZWVdOrUScmCHB0d+fjjj4mL\ni+Pdd9+lV69ewM95yPLly9HpdEoOdC7f+mUnqEuXLrzyyivceeedSieopqaGyspKjh49qnSCqqqq\nuO2225ROUGxsLF5eXjddJ8hkMvHGG2+wd+9etm3b1t7TEbeQ1tZWbr/9dvr378+77757U+ag10qy\nICGEEEK0F8mCxO9dY2Mj48ePV95zn1vvpVKpLJ7n6urKQw89xCeffGJx+McTTzzBl19+yZw5c4iP\nj6e8vJzc3NwLdoLa2tqU15WVlSmHUlyp1tZWtm7dyurVq3F2dubFF1+8KTaKLCwspFevXqxcuZK0\ntLTfPI7ZbGb+/Pn88MMPFjlQa2vrZTtBl9LS0oJKpbJqJ+js2bNs2LBB6QS1trZesBNkZ2en5EDx\n8fFs2bKFn376ienTpzNjxgzs7e1pa2tj/fr1HDhwAG9vbyUH8vb2pri4mIyMDA4ePEhRURF///vf\neeaZZ/Dx8aGpqYmamhqlE5SRkcGhQ4fIzMwkIiJC6QT16tWL0NDQmyIz/LXc3FzS0tJYuXIl/fv3\nb+/piFvIt99+yzPPPMP27dvp0qVLe0/H6iQHEkIIIUR7kRxI3Ao++ugjdu3aRVFREadOncLf35+6\nujqamposntenTx9ef/11RowYoXysvr4eb29vpk+fzm233YaTk5NFJ6iwsJCioiJaWlowGAzK655/\n/nn++9//XvVcc3NzWb16NXv27GH8+PE8/PDD2Nvb//ZP3kr++te/0tjYyMKFCy3Wzl2t4uJiZs6c\nSWVlpbI2TKPR4ODgQFhY2AU7QREREZftBJWUlAAonaBr3eRNr9fzww8/UFRUpOwRdG6foF92gqqq\nqoiOjlayIBsbG+bOnUtSUhLvvvsu3bp1AyAvL4+vv/4ag8Gg7BHk6+uL2WzmyJEjZGRkcODAAZKS\nknjllVcYOnQoer3eohOUmZmpdIJqa2sZPHgwqampDBo0iJiYGDw9PW/KTlB6ejonT55k/fr17T0d\ncQtpaWlh8ODBDBs2jDfffPOm+HfS2mSTRyH+f3q9npMnT5KXl0dNTQ3V1dUUFxezdu1aKioq8PHx\noaamxuI1Z86cYfny5SxfvhyAqKgo5YZRhw4dlJtvjY2N3H333bz66qu0tbUpP+QVFBRQUlJCaGgo\niYmJJCYmkpCQgMFgICcnh9zcXLKzs9m2bRuFhYWMHj2awYMHs2zZMk6fPs3SpUsZPHhwe3y5FFqt\nlhkzZvDdd98xffp0AgMD8fT0xNPTk+DgYOLi4tp1fu1Fr9eTnZ3NsWPHOH78OFVVVUyaNIkBAwZc\n9VhGo5Fvv/2Wf/7zn+Tn59PW1qZsBODn50diYiJ9+vShT58+xMfH3/T/s1Kr1fztb3+jqKiIlStX\nEhUV1d5TErcQlUrF8OHDyc/Pp2fPngwYMIAZM2bg6+vb3lOzGrmRJ4QQQoj2IlmQuNWo1WqOHj2K\nWq2murqampoa9u/fz44dOwDYsWMHqampyvNbWlpYv349y5YtY+fOnSQnJ+Pl5aXkQO7u7hw9epT9\n+/eTkJDAX/7yFx544AGysrKUHCg/Px+9Xk9CQoKSBYWHh1NUVEROTg45OTlkZmayceNG4uPjGTNm\nDI2NjXz88cfcf//9fPrpp+3+vn/nzp38+c9/JiUlhcGDB+Pp6al8HRITE6/p5t7vmVqtJisri+PH\nj5OVlUVCQgKTJ0/Gw8PjqscqLCxk9uzZLF26FJ1Oh6OjI76+vvj6+hIeHq7kQL17977p3++azWa+\n+eYbpk2bxssvv8y0adNuupuM4vftjTfeYM6cOfj4+NC/f3/GjRvHPffc097TshrJgYQQQgjRXiQH\nEreatra2C3aC1qxZQ2VlJR07dqSoqMjiNSdPnlQ6QQ4ODkRGRio5kKenJy0tLWzZsoWWlhaGDx/O\nq6++ikajITc3V8mBVCoVYWFhFp2gc72hc48tW7agUqm47777SElJYfHixRQUFPD111+3+6JojUbD\nc889x8aNG5k+fTp+fn5KFhQSEkJsbGy7zq+9tLW1cebMGY4fP87x48epqalhypQp9OnT56rHMhgM\nfPPNN7z99tsUFRUpnSBfX1/8/PxISkpSsqCuXbte80aW11tZWRmTJ0+mqqqKb775hoiIiPaekriF\nFBYWMnLkSIqLi+nVqxcDBw5k5syZ17QJ7c1GsiAhhBBCtBfJgsStpry8nGPHjqFWq5UsaO/eveze\nvRuAvXv3MnDgQOX5Go2GtWvXsmzZMn766Se6deuGl5eXkgO5ublx5MgRDh48SHJyMpMmTeKee+7h\n+PHj5OfnK70go9Go5ECJiYmEhoZSUFCgrA87cuQImzZtIjk5mQcffJDq6mo+/fRTxo8fz5w5c9r9\nff+WLVuYOHEiaWlpDBw4UFkb5uXlRWJiIm5ubu06v/ZSUVGh5EBZWVn06NGDSZMm/aavx9mzZ/nX\nv/7FihUr0Ol0ODs7K52gjh070rt3b/r27UuvXr0uu/FlezObzXz11Vc8//zzvPnmm0yZMkU6QcKq\n0tPTmTdvHv7+/vTv359HH32Uu+++u72nZTWSAwkhhBCivUgOJG41Op2OEydOcPbsWeUghYKCAn74\n4Qdqa2tJSEjgxIkTFq85fvy40glydXUlIiLCYp+g5uZmNm/ejF6vZ8SIEbz66qvU19crnaCCggLK\nysro2LGj0gdKSEigtbVV6QNlZ2ezefNm1Go1DzzwAP369WPhwoVUVFTwzTff0LNnz3b6iv2ssbGR\n6dOns2PHDqZNm6Z0gjw9PQkLC7spDiVpDzqdjjNnzij7BDU0NDB16tTf9Oel1+tZvnw577zzDqWl\npbS1tSmbQfr5+ZGcnKx0guLi4to9G7yckpISJk2ahEajYcWKFYSGhrb3lMQtJCcnh3vvvZeysjJ6\n9+5NSkoKM2bM+E3rMm9WssmjaHcNDQ0WC6BPnz6tLFz29/cnPDyckJAQmpqaqKiooKKiArVaTVVV\nFQEBAXTq1ImoqCiioqIICAjAaDRiMBgwGo3o9XpqampQqVTKo6mpyeJULF9fX7y9vZWHl5cX3t7e\n2NjYoNPplIder8fW1hY7Ozvs7Oywt7dXfrW1tSUnJ4fq6mqam5upra2lrq4Ok8lE9+7dAdi0aRMb\nN27ExcWF+Ph4OnXqRKdOnQgLC0OlUnHixAlOnDjByZMnsbe3p3PnzspjwIABpKamWizi37RpE48/\n/jiffvopDz74oHIjpLKykp9++onExMQbusHiTz/9xMqVK2loaKC+vp76+npycnJ44IEHeO+993Bx\ncblhc7lVmUwmmpqarLLT+I2k1WopLy9HpVKxe/duPvjgA5588kneeustnJyc2nt64hbV0NDAwoUL\nee211zh58uQttXBAbuQJIYQQor1IFiSswWg0cvbsWSUHOn78ONXV1cpBBiEhIYSHh+Pi4qJkQOfy\nIJPJZJEDnTu565dZUEtLC2VlZUoOVF5ejpOTk0UOdO6U9F/mQO7u7rS1tVlkQSaT6bwM6Fwu1NTU\nRHZ2NhqNhvr6eurq6qivryc8PJwuXbpw+PBhfvzxR44dO0Z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5SbmwtfX1/s2LEDI0eOxMWLFwVd0meF5UAMwzAMwwgKy4GYb8WzZ8+wcOFCiImJ4dq1a5/kptLk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VBO3bt4+cnBz8/f2pWbMmFy5cwMXFhcmTJ1dorJfVBBUXF9O0aVOOHz9eJmfLycmh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DMzM/z9/b9r8XtBEH5Mnzd9HT16NLNnz1Z0OXkilUoZO3YsR44coVSpUnh4eNCtWzfZ8wcP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\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p4+vry9y5c9m8eTPXrl3j0qVL+Pv7k5ycTLVq1cjKyuL58+dUr16d77//nlGjRr32d1ch\nyrJnz55x69YtEhISSExMJCUlBaBQL0hDQwMDA4OCPpChoeFrX6KjVCpJSEggNjaWv/76i0WLFuHm\n5oabm1uhG3hKpRI7Ozu6dOnCnDlzAPjss8/Izc1l+/bt8n0qPmjZ2dnMnz+fnTt34uXlRXx8PCEh\nIdStW5e6dety6tQpvL29+eqrrzhy5AhxcXGv9IEaNmxYsNCF9IGEEEIIoSrSBxKlUePGjXFxcaF2\n7dpcunSJgIAALl++jL6+PmpqaqSkpJCSkoK9vT0rV67E2NhY1ZFfT6mEvBzIy4X83Jf/LUQJUCqV\nBF+7zrNnz0lITCQxKYmcnJxXZ4IqV8bYyAgjQwOMDA3R0an62n5NZmYmcU+fEhX9kK8XfUd2dg5b\n1/9EYwvzQnVnzp5j5NgJ3Lh0AR0dHUJCb9C930DOHPN7pVaID83Fy1cYOdaFTu3bMWPKZHbt2UsV\nbW3q1qlN+fLlmDXPgy4dO2BkaIDvwcPUMjamsbkZFuZmWJg1wsLMjOrVqxWcT1FJR3pBQgghhFAJ\n6QWJ0mbnzp0sWbKEdevWcfXqVYKCgvD39yc9PR09Pb2CmSADAwOWLl2Ko6OjzBoI8R/i4uIICwsj\nMTGRhIQEUlJSUCgUhXpBmpqar8wEve4lOkqlkvj4eGJjYzl27BhLlizB3d2dadOmoa6uXlCXn59P\nt27dGDRoENOnT0epVOLk5ESVKlXw9PQsycsX4r+WmZnJ3Llz+f3339m2bRsxMTGEhYUVzAQdO3aM\nffv2MXv2bA4ePEh8fHyheaDGjRtTv359mQkSQgghhMpJH0iURiYmJsyaNYvq1asXzAQFBwdjYGCA\nQqEgOTmZ1NRUHB0dWb58+Ztf/JGRCsq8kg0vxAcgPz+/YCYoMSmpYCbo7x7Q3/2gKtraGBsZYmRo\niJGhAVWrvnkmKDYujsioaNwXLkJDQ50t636ikWnDQnXH/zzBpGkzCL14gcqVK3M5+Cp97B24cPIP\nGjaoX1KXL8Q7OR8QyKhxE7Dr1RPX8WPZtWcvOlWrUrdObTQ0NHBzn08f215UrVKFg0eOUqdWrZez\nQOZmL2eDzMzQ09MtOF9RM0GyyKP46Fy5cgU7Ozs2btxI8+bNqVevHjk5OVy7do2oqCgePnzI8ePH\nuXv3LsnJybi5uTFt2jQqVKig6uhCqFxOTg6TJk3ir7/+wtzcHF1dXXR1ddHS0kKpVJKXl8ezZ88A\nUFdXJy4ujsePH/PkyROysrIKbupVqFCB2NhYYmNjSUlJwcDAAENDQxwdHZkxY8YrK+RnZWXRsmVL\nPDw8GDZsGOnp6VhbW3Pv3j0aNWrEwIEDGTlyJI0aNVLFxyJEkbKzs9HX16dmzZr06dMHLy8vRo8e\nTbly5YiKiuLx48dMnjyZ4cOHv/U55UaeEEIIIVRFekGitFEqlQwcOBB9fX3Gjx9P06ZNqVy5MlFR\nUYSFhfHw4UOioqJYt24d1apVo2bNmqxevVpeJiDE/3f+/HmGDh2Kqakpenp66Orqoq2tjUKhID8/\nn7S0NBISEqhcuTLJyck8efKEJ0+eEBcXR9WqVTE2NkZfX5+UlJSC7RUrVsTQ0BAzMzOWLFmCufmr\nD+pv376dH3/8kaCgIDQ1Ndm2bRtjx47FyMiITp06YW9vz9ChQwsNgQvxofjhhx9wd3dn9uzZ/PHH\nH5QrV45+/frx8OFDIiMjMTAwYNWqVVSvXv2tzid9ICGEEEKoivSBRGl0/vx5hgwZwqZNm7C0tKRu\n3bpkZWVx7do1oqOjefjwIUeOHCE6OvrlW5TnzmXKlCmUK1dO1dGLlpMNORmqTiE+cllZWYyfPJVz\nAYGYmZqiq6ODjk5VtDQ1UaIkNzePZ8+fvxzqVqgR9+wpT2LjePwklpycHAwN9DE2MqKclhaxT58S\nGxdHWlo6Bvr6GBroM8JxKFNdJ77Sz8nIyMDSuj0rf1jMgL59SElJoVXHrjyKeYyZaUMG9e/LqOHD\nqG9STyWfixBFycjIoHqdBpg2qE/XTh3Z7v0bziNHoK6uTtTDh8TGxTH9c1fsB/R/63PKIo9CCCGE\nUBXpBYnSJj8/n969e9OwYUOcnZ1p0qQJFStWJDIykvDw8IL7s+vXr6datWqYmJjw448/0rRpU1VH\nF+KDcPr0aYYNG1bwbJienh7a2trAy++v1NRUEhMTqVy5Mi9evCiYCXr69Ck6OjoYGRmhr69PcnIy\nsbGxxMXFUalSJQwNDbGwsGDp0qU0bNjwlf/vpk2b2LZtG+fPn0ddXZ3169fz+eefU7NmTTp37szg\nwYOxt7dHTU2tpD8SIYrl4eHBokWLmDt3LocOHaJq1ar07t2b6OhoIiMjqVWrFitXrkRXV7f4kyEz\nQUIIIYRQHekDidLo5MmTjB49mo0bN2JpaUmdOnXIyMgoNBN08OBBYmNjSUpKwsPDg4kTJ6KlpVX4\nRJlpL1+4KkQZkpGRwZgJrgRfu07D+vXR1dFBV1cHTQ0NlCjJycnj2fNnL2d6lBTMBD2JjSMnJ6fg\nJbDltLR4EhdHbFwc6ekZGOjrY2RowJiRTkwaP/aVfk5KSgrN2rTD86fV9OrRjcTEJFq278Sz5/GY\nNzLFfkA/Rg5zoF7duir6ZIR4s+TkZGrUbYhVs6ZYt/4Eb5/fGTt6FEqlksjoaJ4+e8as6V/Qz673\nW59TFnkUZY63tzc7duzgxo0bJCYmYmtry+7duwuGSPPy8nB2dubu3btUr16d4OBg5syZg4uLC+XL\nl1dxeiFUIykpiaFDh1KhQgW8vb2pXLnyKzXz5s3j+++/B6BChQpYWFjQokUL2rZtS9++fUlPT+fJ\nkydkZGRgaGiIkZERenp6xd58W7hwIVevXmX//v0oFAoWLFiAp6cn8+fPp1mzZgwfPpwOHTqwZ8+e\nf+TahfhfRUdHs2PHDp4+fcrs2bOpWbNmkfU5OTnMnj2b4cOHY21tXbA9Pz+fgIAAOnToIDfyhBBC\nCKES0gsSpdGzZ8+YM2cO165dIywsDCMjIzw9PenevXtBTUBAAAMHDmTIkCHs37+fDh06sGDBAhns\nFmXab7/9xhdffMGOHTuwtbV9Zb9SqSzo6VSoUAE9PT2aN29OixYt6Nu3LyYmJgULO1apUgUjIyMM\nDAyKfZlOXFwclpaWHDt2jBYtWpCUlFTw4oSZM2fi7e3N+vXrCQkJoXHjxv/ItQvxv8jJyeHYsWP4\n+vrSt29fhgwZ8to3F/67/fv3ExUVxdixYwsemoCXP8P09fWlDySEEEIIlZA+kCittm/fjre3N6Gh\noSQnJ9OvXz9+/fXXgt9hc3JyGDlyJE+ePEFbW5vQ0FDmzZvH2LFjXx3sVhWlEvJyXw6V5+WCMl/V\nicRHLj4+AXunkejXqMH2zRupWLHiKzWTp3/Jhs1bgZe9oCYW5rSwssSmTWvsbHuSmprGk9hYsrKy\nMTTQx8jQEF1dnWJngr6av4Cohw/57RcvAGbP82DXnr18PWcWjRo2wPHTz+jTqye/bN74/i9ciPcg\nMiqKX3Z68+JFMrNnTMPQ0KDI+oyMDOZ6fMMop2G0atmiYHt+fj7nAwLp1KuP9IKEEEIIoRLSCxKl\n0ZMnT3B3d+f69euEh4djbGzMzz//TIcOHQpqzpw5w5AhQ3BwcMDX15du3bqxYMGC176QUoiy4pdf\nfmH27Nl4e3vTrVu3V/b/50xQtWrVaNGiBS1atKB///7UqlWrYMHHqlWrFswEFffM5aNHj2jRogWn\nT5+mSZMmPH36lLp162Jvb88XX3zBtm3b2LZtG2FhYTRo0OAfuXYh/hfZ2dkcOXKE/fv3Y29vz4AB\nA4qdCfLx8eHp06c4OztTqVKlgu1xcXEYGhpKH0gIIYQQKiF9IFFabdmyBR8fH0JDQ0lLS2Pw4MF4\neXkV/Ls8OzsbBwcHkpOT0dTU5Pbt23z99dd8+umnaGpqvjxJZirk56nwKoQoWU+fPmOAoxMNTEzw\n2rj2tS9DHuE8Hm+fvQBUrFiRpo0taG7ZjHbWbejdswfJKSk8iY0lO/vlgo+GBgbo6ekW+zvxF26z\nSUlJZdum9QBM/XIWB/2OsmDuV9SpXRvHT51xHGzPxjX/ev8XLsR7cO/+A37ZuYuMjExmz5hGjRrV\ni6xPSUnBY9H3jBnpRHMry4LteXl5nD1/ga52/WWRR1F2JSUlMWjQIKpWrcrUqVPp1q0bampq5OXl\nMXHiREJCQhgzZgxHjx7l+vXruLu7M3bs2Nf+4BLiYxQTE8Pu3bvZsGEDffr0YdWqVQULov6ntLQ0\nNmzYwPLly2nTpg1t2rShQoUKBAYGcuLECRwcHHB1daVFixavPf51QkND6datG9euXStYGC8hIYEK\nFSpQoUIFLl68iLW1NQMHDmTkyJFkZmaybNkyateuzcCBAxkwYABGRkbv5bMQoqTk5uZSo0YNAJo2\nbcr48eO5du0aPj4+6OjocPPmTbmRJ4QQQgiVkF6QKO3y8vI4cOAAkydP5ssvv+TTTz/FwODlA5eX\nLl2iX79+TJw4ETU1NTZs2EDXrl1ZsGABFhYWKk4uRMnIzc3lxIkT/Prrr/j7+3P48GGaNWv2xvqL\nFy+yYMECbt26hYODA/r6+iQlJeHt7U21atWYNGkSTk5OhQZUi+Pg4ICpqWnBi0SUSiWPHz8u6AvZ\n2toSGhrK559/TocOHdi6dSuXL1/Gzs6OgQMH0q5dOzQ0NP63D0KIErZs2TIWL16MlpYWLi4umJiY\n4OPjw8WLF0lOTpY+kBBCCCFUQvpA4mOQkJBA3759MTY2ZsqUKXTu3Bk1NTVyc3NxdnbmwYMHjBw5\nkkOHDhEWFsb8+fMZM2bM/w12q0p+3suhciH+YQ8fPeI3H1/Wb96C42B7fvh2wRsXZUxNTWXtxs2s\n+mkd7W2s+aRFc8ppleNCUBBnzp1n+NAhuL4C/70AACAASURBVI4fS7OmTd76/385+Cp9BzsSevEC\n+vovZyTi4xOoVKki5cuXx//ceTrb9mWo/UCcHIbw4kUyK9aspX69ugzs15f+dr0xMNB/L5+FECUl\nKysLvVomlCunhVWzpnw2aiSXr15l776DVK+mR+jNW9ILEkIIIYRKSC9IlHa5ubn4+Pjg5uaGm5sb\no0ePpnr1lw9cnj9/Hnt7e6ZMmUJubi4bN27E1tYWDw8PTE1NVZxciJKRk5PDn3/+yY4dOwgKCsLP\nz6/ImbgLFy6wYMEC7t69y9ChQ6lRowYJCQns2rULY2NjJk2axLBhw4p92evflEol/fv3p02bNnh4\neBRse/LkCcbGxgB06tSJBw8e8Pnnn2NjY8OmTZsICQmhT58+DBw4kLZt277xeTYhPlTffPMNq1at\nQktLi0mTJmFsbIyPjw/BwcG8ePFC+kBCCCGEUAnpA4mPQXx8PD179qRRo0ZMnjyZjh07olAoyM7O\nZuTIkTx79gxHR0d8fX158OABX3/9NaNGjUIjJ0NetirKhMioKH7z8WXDlq04jxrBwnlz37goY3Jy\nMms2bGL1+o106dgBq2ZN0dLU4uyFC1wIusjIYQ5MGjeWxhZv/+Kc8wGBOIxy5salAPT0dAF4/jwe\nbe3KlCtXjuN/nqD3oCE4OQxl2FB74p4+48d1GzBtUJ+BffvQv49dsQvqCfGhSUtLQ6+WCZUqVeST\n5s35dMRwAi9d5vf9BzEyNOBaSKgs8ijKtuTkZHbs2MHmzZt58eIFq1evZsCAAeTn5+Pl5cVPP/1E\nRkYGffr0ISwsjPDwcObPn8/IkSNf++ZyIUq7zMxMfvnlF7y9vQkJCWHQoEGMGjWK1q1b4+PjQ1hY\nGImJiYX+tGvXjgULFqCvr09qaiobNmzg4MGDXL16laZNm2JqakpQUBB37tzh+PHj9OrVq9gcqamp\ndOvWDRcXF1xcXN5YFxMTw8GDBzlw4ABZWVm4u7uTkJDAgQMH8PPzY/HixUydOvV9fkRC/OMcHBzo\n3bs32tra7Nixg1atWuHg4EDjxo1RKBRyI08IIYQQKiG9IPGxCAwMxNPTE19fX/r06cPWrVupUKEC\nERERLFu2DF9fX3r16oW+vj67d++mV69ezJ07t+Df40J8bIKDg9m6dSt79+7FxMQEJycnRo4cSWRk\nJIcPH+b58+eF+kDq6urMmTOHvn37olAouHDhAuvWrePMmTPk5+fTvn170tLSOHr0KBYWFty6deut\ncuzcuZNvv/2W69evU758+dfW5OTk4O/vz4EDBzh16hRDhgzBzs6Oo0ePsm/fPp4/f050dLQMdYtS\n5fr16wwdOpTjx4/z448/8uzZM4YOHYqdnR2VKlWSPpAQQgghVEL6QOJjkZSUxPbt29m8eTMZGRms\nXbuW3r17k5eXh6enJ+vWrSMvL4/evXsTEhJSMNg9fPjwt35A+b2TRR7FPyg9PZ2ff92Ft8/v3AoP\nZ/CA/ox2GoZVs6bs8d1PxO07JCYlFfxJSnpB5w7tmf/VLKpXr0ZycjLrNm3h8LHjXA+9gWXTJtSv\nV4+Aixe5/yAS/z+O0LF9u2JzvHjxgk69+jBr+heMchr2xrrohw856HeUA4ePoFQqmes2k6fPnnHA\n7whHjv/Jyh8W4/LZmPf5EQnxj+s3ZBhODkNQKBTs2rMX69af4GA/CHOzRigq6UgvSAghhBAqIb0g\n8bE4d+4cnp6eHDx4kIEDB+Lp6Um5cuW4desWS5cu5cCBA9jZ2aGnp8eePXvo27cvc+bMwczMTGaC\nxEfp0qVLbN26ld9//x1TU9OCmaDbt29z5MgR4uPjC80ElStXDnd3d2xtbQHw9/dnw4YNnDlzBjU1\nNdq1a0dycjLHjx+ndevWXLx48a1ybNmyhTVr1nD58mW0tLReW5Odnc3p06c5cOAA/v7+DBs2jB49\nenDkyBF8fX1JT0/n/v377+2zEaIkBAYG4uLigq+vLz/++CNJSUk4ODhga2tLxYoVpQ8khBBCCJWQ\nPpD4WCQkJPDzzz+zZcsW8vLyWL9+Pd27dyc3N5cNGzawfv161NXV6dmzJ8HBwTx+/JgFc2czdNCA\nNz6vIkRplpqayrYdO/H2+Z079+4xdNBARjsNo7G5Gb/t9eXO3XuFZoJevEime5fOzJvthq6uDklJ\nSazdtBm/Y38QevMWzS2bUa9OHc4FBBAV/ZCL/idp/UnLYnMkJibRrnsvFnvMY8iggW+si4yK4qDf\nUfYf8kNLS4s5X07nUcxjDvgd4difJ1j/rxWMHjH8fX5EQvzjevQdyKTxY0lPT2f37/tob2ONg/0g\nTBs2KHImSBZ5FGWKUqnk7NmzDBkyhFWrVtGvXz90dXVRKpUEBASwaNEiqlSpwrRp0/jmm284efIk\njx49wsDAQNXRhXhvXrx4wYABL38xcXV1xc7OjtDQUDw9PfHx8aFz587Y2Nigq6uLnp4eurq6VKlS\nhV27drFjxw5mzJjBl19+WfCLTUZGBhcvXsTf35/w8HA0NDSYNWsWTZs2LTLHpUuXGDFiBF27dmXT\npk3vdMNcqVRiYWGBp6cnnTp1eqfPQ4h/QnZ2Nrdv3+bmzZvcvHmTsLAwqlSpgrm5OWZmZpiZmXHq\n1CnOnDmDt7f3K8fLIo9CCCGEUBXpBYmPTXJyMhMmTCAzM5MFCxZgZWWFmpoaCQkJ/PLLL3z//fcF\nC8ktWrSIWbNmsWjRIlXHFuK92rVrFzNmzOCLL75g+PDhVK9enV27duHp6UlSUhLDhg3D2NgYXV3d\ngn5QbGws8+fPx8DAgFWrVtGiRQvgZS8mMjISf39/zp8/T1paGlZWVsyePbvIDFlZWcyZM4e9e/ey\nf/9+Pvnkk3e6ll9//ZXt27fzxx9/vNPxQvwTlEolT58+5ebNm9y4cYObN2/y/PlzTE1NC/pAZmZm\nNG3alLNnz9KwYcNCx0sfSAghhBCqIn0g8bFRKpWcOHECJycn1qxZg52dHTo6OgWzQt9++y21atVi\n3LhxLFy4kPPnz/P48WP09PRUERZysiA/9+WCj0K8JwkJifQbOgxdHR1cXcbSq3s3gq9dZ/O2X/j9\nwEG6d+mMdatW6OrqoKvz8o+2dmW27/qN3b/7MmvaF0yf4lrwIH56ejpBly7jf/4Ct+/cQ1NTg7lu\nMzFrZFpkjguBQYwaN4G+vXuxZsWyd5oJysvLw9SyJb/94kWbVu/WSxLin5CVlUXE7TvcDAvnZlg4\n4bdvo6ujg5mpKWaNGmLeqBF+x44TcuMmXhvXvXK8LPIohBBCCFWRXpD42CQlJfHZZ5+hqanJ/Pnz\nadasGQqFgufPn+Pl5cXy5cvx8/Pj6NGjfPfddyxcuBB3d3dVxxbivdq2bRtz585l+vTpDB8+nKpV\nq/Lrr7+yefNm0tPTcXR0xMjIqGAmSFdXl0ePHjF//nzq1avHypUradasGfCyv3r//n38/f25cOEC\n6enptGrVihkzZhSZISMjAzc3N/z8/Dh06FDB+f5bmzdv5vDhwxw4cOCdjhfin6BUKomNjS14Nuzm\nzZskJCQUzASZm5vTsGFDzMzMCAkJoWbNmoWOl5kgIYQQQqiK9IHEx0apVHL06FGcnZ1Zt24dvXr1\nomrVqiiVSk6fPs3ChQtp3Lgxjo6OLPh6PleuXiP2fgTa2tqqji7Ee/P06TP6DHagVk1jJo79jB7d\nunDx8hU8vX7mgN8RbHt055PmzdHT00VXpyq6OjpUqlQJr+2/su/gYea6zWDKpAloamoCkJaWRuDF\ny/ifP8+du/fR0tLEY+5X1DepV2SOM2fPMXr8JIYPHcyy7759p2vJycmhnoUlR/f5YNms6HWJhChJ\nmZmZhWaCIu7cQU9XFzPThpibNcLM1JS9+w7wMCaGdf9a8crxssijEP/h1KlTrFixgrNnz9K4cWNs\nbW2xtbWladOmWFlZMXfuXCZMmICLiwsmJiZyI098NOLi4ujduzcdOnRg0aJFeHt7FzzQ7+LigrOz\nM8bGxm88/qeffmLatGmcOnWKzp07v3OOtWvX8u2337Ju3TocHBze+TwnTpzA1taWli1bkpKSwq1b\nt+TtikLlUlJSMDQ0pHbt2jRp0oQmTZpgYWFBcnIyERERhIeHExERQVRUFDVr1iQqKuqVc8iNPCGE\nEEKoivSCxMcoMzOTefPmcfjwYZKSkujVqxe2trb07NmT3bt3s379eoKDg4mNjcXa2pro6GgqVKig\n6thCvBc//fQTy5Yt4+jRo6SmpuLp6Ymvry89evRgwoQJ9OjRAzU1tdce+/z5c1q3bo25uTlHjx59\n5wyPHj2iX79+NGjQAE9PT6pVq/bO57KxsSEhIYHk5GRWrlzJiBEj3vlcQrwvc+fOZcOGDVhaWhb0\ngmrUqMHdu3cL+kAREREkJyezfft2Ro8eXeh46QMJIYQQQlWkDyQ+Vn/++SerVq3i/PnzNGvWrKAX\n9Pfi60uWLGH06NGMGjWKli1bMnPmTNUGViohJxtyM1WbQ5R6MY8fYztgCHa9euA+60t27t6Dp9fP\npGdk4OI8BudRIzAw0H/j8ctWrWbugm+4cPIPrFu3euccK378iRWrf2LjmlUM6t/vnc/jd+w49sNH\nYdm0CXl5eVwNOPvO5xLifXn+PJ465k2pV7cOTSzMaWxuhnmjRrxITiY84jYRd+4ScecO0Q8f0bBB\nfcKvXnrlHLLIoxBCCCFURXpB4mOUlpaGu7s7fn5+pKWlFZoJ8vLyYufOnVy6dIn79+/TrVs3oqKi\nCl5sIERpt3z5ctatW8fx48d5/vw5np6eHDhwgN69ezNhwgS6dOnyxpmg2NhYWrduTatWrdi3b987\nZ4iMjKRv375YWlqyYcMGdHR03vlczZs3Jysri4SEBDZs2MDgwYPf+VxCvC8zZszg559/xsrKqmAm\nSE9Pjzt37hTMA4WHh5OamoqPjw9Dhw4tdLzMBAkhhBBCVaQPJD5Wfn5+rF69moCAAJo3b16wTpCJ\niQmNGzdm/fr1DO1nx5DhTvTo2gVXl3GqjizEexEVHU2vAYNxHDyI6Z9PZof3b3hu+4W8vDxcnMcw\nZqQTNWpUf+Px33y/hMVLV3DJ/yTNrSzfOcd3y1awbtMWtq7/CTvbnu98nr37DjB6/EQszBpRrlw5\nAk79+c7nEuJ9iXn8mIbNWlLfpB5NLMxpYmGOmakpCYmJRNy+Q8Sdu4Tfvs3DRzFYNm3y2lm2omaC\nNP7pCxDiQ9S1a1e6du1KVlYWJ0+exMXFhRUrVpCRkUGtWrXIzHw5OO3q6sqgQYOYPXs2Ghry7SJK\nt/v379OrVy+GDx/+/9i78zid6v6P469rNmY1Y5mxLzO2sQwh3Cjr2BIhS/ZUIpJEpVX2QklJJRTZ\nhSyhGRnGLiGyj33MGNvs+3Wd3x/uptsvCTPmzJj38/GYR3fnus457/O4Z5q5PudzPl8SEhIoV64c\nLVq04MMPP7zjA/1wc2W1kSNHsmbNmkwPeISbNwTt7Ozw9v7n5vG7UaRIEUaPHs3jjz9O7969OXHi\nBJUqVcrUMUUyy9XVFZvNxr59+3B1df3H9yUnJxMXF5eNyURERERE8qb8+fMzdepUpk6dypkzZxgz\nZgwDBw4kNTUVe3t7/vOf/5CUlISvry9169ZlyZIl9OvXz+zYIpliGAajR49m0aJFTJgwgR49epCY\nmMgLL7zA8ePH8fHxueP+W7ZsoU+fPrRv356PPvooU1ni4+OJiYnB1dUVLy+vTB2rc+fOFC1alDNn\nzrBhwwYNeZQcwdnZmcGDBzN+/Ph/fI9hGFy+fJnChf/5xrmIiIiIiGSNwMBAAgMDSU5O5ueff+bF\nF1/ko48+IikpidKlS5OYmAjA4MGD6dOnD8OGDbtjv8QDYRhgs4I1HWzpN/+3SCacOHmKlu070r9P\nLy5HXaFc1QBaB7Zg2kcTafL4Y3f8Hk9ISODVN94ieHMIoUHrMzXgESAiMhJ7e3t8MtkTVMzHh9Fv\nv8njDRvQuUcfzl+4QOlSpTJ1TJHM8vBwx2q1cnDXNhwdHf/xfUlJSSQkJGZjMhERERGRvMnV1ZVP\nP/2UTz/9lLCwMN577z0GDBiQ0RP02GOPkZycjL+/P/7+/qxYsYLu3bubHVskUwzD4I033mDdunWM\nGTOGTp06kZ6ezoABA5gyZQpFihS54/7BwcH069ePbt26MWHChExliY2NJS4uDjc3NwoUKJCpY3Xr\n1o0yZcpw9OhRNm7cqCGPkiPkz5+f1157jXfeeecf3/NnT9C//eyJiIiIiEjmPfHEEzzxxBMkJiay\nYcMGBg0axMSJE0lKSqJs2bLEx8eDYWPwgOd5ZeQoBj7fH4tFc9cld/vjyFFaP/U0gwc8z+mzZ/Gr\nXpN2rVszc9pUHm/U8I7f47GxsQwd8QY7du9h5+agTA14BLgUcbMn6E4DJe9GqZIleO/N13m8UQOe\n6NyVqKgreHvrc7WYy8PdHYvFwqE9O/51/lZiYtI9H19T6yRPy5cvHzVq1CA6Opqvv/6aY8eOsWvX\nLt555x2+++47NmzYgKenJ/v27aNevXpmxxW5b7///jtt27blueeeIzg4GB8fH44dO/avD/T/6YUX\nXiAuLo4DBw5k+mH88+fP8/vvv+Pi4nLHZte7ERAQQEDAzT8kW7ZsyZIlS3jvvfcydUyRzLKzs6Ns\n2bJ8++23PP300//4c5Y/f37y58+fzelERERERPK2cuXK4ejoyJNPPkmzZs3Yvn07O3bsoHz58owd\nO5a+ffsyf/58DXmUXM1qtfLyyy+ze/du+vTpw4gRI/jqq69o3779XQ2t+OOPP+jQoQMLFy6kbdu2\nmc6zZcsWEhMTcf/vzY7MGDFiBABnzpyhXr16xMXF4e7unumMIpnh5+fHF198wd69e3nkkUduu2CU\nxWKhaNGiJqQTEREREcm78ufPT/Xq1YmPj2f27NkcOnSIXbt2MWLECObMmcPGjRuxWCwcPnw4o+8g\n2xg2SEnI3nPKQ2vf/gO069yNwS8+z49rf8LPtxwnD/521w3VfV4YiJ2dHQd2huLh4ZGpLKfPnOXI\nseO4urpkekHlWo/UpNYjNQEIbNaUJctXMvLVoZk6pkhmOTk5UayoD98tWESHJ9r+48+Zs7Mzzs7O\n2ZxORERERCRv8/Pzw87Ojs6dO9OgQYOMniBfX18mTZpE3759NeRRcr0/hzkeOXKELl268PrrrzN7\n9mzatm17Vz05+/bto1u3bixevJjAwMBMZTEMg5CQEJKTk7Okd2fUqFEAHD16lObNmzNt2jR9thbT\n+fn58f3339OmTRtq1qyJvb39396jniARERERkezn4uKCv78/ycnJzJkzhwMHDrBr1y6GDBnCrK++\nZMOq5cTExnLyVBgVK5Q3O67Ifdu5ew8du/di2OBBLF7+AzWqVyPs0AEKFSp4V/t37/scBb28+G37\nFtzc3DKV5eSpMI6fOImbmysOt/l8fC/qPVonYxHaFk2bsHTFSoYMHJCpY4pklru7O+5ubixYvJQ2\nLQMpXLjQbd93vz1BFsMw/vlFi8W40+siD4tRo0YRHh7OvHnzgJs3PYYOHYrFYiElJYXatWszaNAg\nk1OK3J+goCB69erFs88+y8KFC+nfvz/vvffeXT3U/6fXX3+d/PnzM2bMmEznmTt3Lu+//z5TpkzB\n1dUVBweHW77S09OJjY0lJiaGhIQEqlSpQr169XBycso4xo4dOxg9ejTdu3enf//+AJw4cYKGDRty\n6tSpTK8AJ5JZa9asYdasWYSGhlK8eHGaNGlCkyZNaNu2La6urv+6v8ViwTAMLQ0hIiIi2U61IMkL\nwsPDqVmzJjt37qR8+Zs3644dO0bDhg1ZvXo1Xbt2JTw83OSUIvcnPj6evn37cuXKFcqWLcvevXtZ\nvXo1FSpUuOtjXL9+nbJlyxIVFZXpxQkMw6BEiRI888wzNGnS5G91IDs7O+Lj44mNjSU2NhZnZ2ca\nN25MiRIlMo6RlJTEqFGjuH79OhMmTKBkyZIA9OjRg4CAAN58881MZRTJrJiYGN599102b97MhQsX\naNSoEU2aNKF169ZUq1btX/dXHUhERETMojqQ5BXDhg0jKSmJr776CoC0tDQGDBhAoUKFiIyMpEWL\nFtm/4IfNCsnx2XtOeSit27CRZ18czPP9+jBv4WIGD3ieN0e8ek8Lbbz82kiKFy3GqJHDM53ni6+/\nYer0z5k0ZjQuLs442P9ZB7LHwcGBtLQ0YuPiiI2NIyExkepVq/Bo7Vq3LBIbsjWUCZM/pk+P7vR6\nphsAhw7/QeCTHQk7vP+uei5EHqQVP65mzrwFbNu5k1IlStLk8YY0ffwxWge2wMXF5V/3t7h6qhYk\nIiIiplAtSPKCs2fPUqdOHX777TdKly4NwKFDh2jatCk//PADzz33HKdOnTI5pcj9iYmJoVevXiQk\nJODj48Phw4dZvXo15cqVu+tjREREUKVKFaKiom6px9yP9PR0ihYtygsvvECDBg3u2BMUExODm5sb\njRs3plixYhnHSEhI4PXXXycpKYkJEyZkDMrr2LEjTZo04ZVXXslURpHMunbtGu+99x6bN28mIiKC\nxx57jCZNmtCmTRv8/f3/dX/1BImIiIhZVAeSvOLFF1/E2dmZadOmAZCamkrfXj0p71uWI8eO06Xj\nU3Tv0tnklCL3Z8WPqxk4dDgvPNuXOfO+Z+Swl3n15cH31BP0/EsvU62KP8OGvJTpPFM//YxZ385j\n/Pvv4Jzf+ZZ+IAcHB1JTU4mNiyMmJpbEpCRqVK9GnVqP3LJIbNCmzUyeNp3n+vam29OdAPj1t/10\n7N6LU4d+I1++fJnOKZIZS5av4LsFi9i+azdlS5eiyWONaNr4Zk/Q3TxjeaeeIA15FAGio6MpW7Ys\np0+fpmDBmxOLr127RuXKlencuTNWq5VZs2aZnFLk3hiGwZQpU/j444/p2LEjy5YtY+bMmTz99NP3\nfKwtW7YwfPhw9u3bl+lcKSkpvPzyy1y+fJn09PS/fdnb21OgQAE8PDxwdnbmwIEDHD9+nPr16zN1\n6lTWr1/Pxx9/TM+ePVm/fj1Hjx7NOHatWrUYN24cbdu2zXROkaxgtVo5cOAAmzdv5ueffyYsLIzv\nvvuORo0a3XE/3cgTERERs6gWJHnFyJEjcXR0ZMKECRnb3nrrLcLDw1m1ahUnT57E29vbxIQi9y4s\nLIynnnqK8uXLExUVhaenJwsXLryvxTAee+wx3n77bVq3bp3pXGvXrmX27Nm3rQNZrVbc3Nzw8PDA\nw8OD6Ohotm7dSsGCBenVqxfdunWja9eu+Pv7c/jwYcaMGUOnTjdv5K1YsYIpU6awY8eOTGcUySpR\nUVFs3bqVzZs3s2LFCp555hnGjx9/x1XaVAcSERERs6gOJHnFlStXqFChAhcuXMDd3R2AyMhIqlWr\nRufOncmXLx/Tp0/P3lCGAWnJYE0Hw5a955aHgs1mY8LkqXz5zVyebNuaH1atZvbMz3iybZt7PtaG\nn4MZ99EUtgVvyHSupKQkhgwfydVr10hPt/5VB7Kmk55uxd7ejgIeHni4e5A/fz5+O3CQsDNnaVCv\nLh9PGs/yVT8yc9YcunZ6itAdO/ltx9aMY/vXqssXn0yhaePHM51TJCukp6ez/+DvbN4SysbgTVy8\ndIl5s76k3qN17rifhjyKiIiIWVQLkrxiyJAh+Pj48O6772ZsGz58OHFxcSxYsICIiIj76qMQMdOx\nY8d46qmnqFatGhcuXKB48eLMmzcvo955L+rUqcPUqVNp3LhxpnOtWLGC+fPn37En6M/nw65du8bW\nrVvx9vamX79+PPnkk3Tt2pXatWuza9cupk2blvEs2IIFC5gzZw6bNm3KdEaRrHL58mVCQkIICQlh\n5cqV9OvXjw8++OCOAyjUEyQiIiJmUR1I8orw8HCqV69OeHh4Rr/+hZPHqVn/P3R8sh2FChbkw3Ef\nmJxS5N7YbDbeGzuB+YsW0zqwBStXr2X+N1/RKrD5PR9r1Zq1zPjqG4LWrsp0rri4OF5+7XVuREff\ntifIwcE+oyfIycmRffsPcPb8BRrWr8e0jyYyb+Fi5s5fQMf27dh/8He2b9oI3JyL5Fu1Bou+nU39\nuo9mOqdIVkhLS+O3AwfZvCWU9UFBXL12nXmzvqT2IzXvuJ+GPIrche7du9O4cWMGDRqUse2TTz5h\n+PDhzJ07l379+pkXTuQeJSQk8Pzzz7Nz504ee+wxQkNDWbVqFTVr3vkXxj9JS0vDx8eHP/74g0KF\nCnHlyhVKlChxV/umpKRw6dKle1od7n+dOXOGnj17EhUVhaurK66urixevJilS5dy5swZZsyYAcCv\nv/5Kx44dCQsLw8nJ6b7OJfKg/fjjjwwcOJB+/foxfvx47Ozsbvs+3cgTERERs6gWJHnF4cOHadOm\nDWfPnsXe3h64ebOhQoUKFClShD179txxIJdITrNhwwZ69uxJq1at2LVrF127dmX8+PEZ39/3atKk\nSVy8eJHPP//8lprM3Th58iS+vr73dW6bzcbnn3/OO++8Q40aNTh27Bjjxo3j2WefpUiRIpw+fZpC\nhQoB0KZNGzp16sQLL7xwz+cRyQ7Xrl1j0KBBHD58mGXLllG1atXbvk91IBERETGL6kCSl3To0IGO\nHTve0vszceJE3nrrLRYuXMgzzzxjXjjDgLQUSE8xL4PkKnFxcfQdMIjfD/9B3dq12bNvHz8uWUjV\nKv73dbzk5GR8ylXk9OEDuLq6cONGNMWKFb2rfZOSkrgcFUXZMmXu69ynwk7zTL/niI6JIX++/BQs\n6MnCud8wd/4CoqNjmDJxHACh23fQ78WXOH7gVxwcHO7rXCIP2rIVqxgyfCSDXujP+2+9icVy+3KP\nhjyKiIiIWVQLkrxi79699OjRgxMnTmT8XX7jxg3Kly9PmTJl2L17N46OjianFLl7a9asoU+fPrRr\n146tW7fSr18/3n///X98FuXfvP/+2tnVsAAAIABJREFU+yQmJjJ58uR77gk6ceIE5cuXv69zW61W\nPvnkE8aMGZPRE/TRRx/RrVs3vL29iYiIyBha2aRJE55//nl69ep1z+cRyQ5RUVG8+OKLhIWFsXz5\ncipWrHjb96knSERERMyiOpDkJS1btuS5556jW7duNzckx/PeB2MY9+EUflg4j47tnzQ3oMg9iI6O\nptdzL3Lq9GlqVK/GwUOHWb10ERUrlL+v48XHx1O8vD/hJ49gb29PXFw8Pj7ed7VvYmIiV69do3Sp\nUvd17mPHT9C9b3+SkpNxdHCkWFEfvp/9NdNnfoWdnYWx770DQPAvIQwd+QaH9+6873qXyINkGAaL\nli5n2OujeHXIS7w54tX76gnSd7fIf/Xu3ZtFixbdsm3IkCGEhIRowKPkKoZh0LhxYxYvXkx0dDQJ\nCQns2bPnvgc8Ajg6OtKuXTu++eYbmjdvTsmSJVm4cOG/7me1WunZs+dfH4ruQ+/evdm5cyfh4eG0\nbt2aLVu2ULp0aTZv3kxKSgphYWEkJCQwbtw4Ro4cqQGPkqN16NCB33//ndDQUAYPHoyKZCIiIiIi\n5qhWrRqFCxdm+/btGdvc3d3ZuHEjv/zyiwY8Sq6yfPly2rZty40bN9i/fz9jx45l0qRJ9z3gEeCp\np55i+fLlfPPNN/j4+BAQEEBKyr8Pm9i2bRvVq1dn06ZN93Xen3/+mVdeeYXU1FQuX75MUFAQL774\nIvv27cPBwYF9+/aRkJDAtm3bOHToEH369Lmv84hkh0KFCrFkyRJGjBhBixYtOHLkiNmRRERERETy\nrNv1BA0fPpwtW7aYN+DRZoX0VEhN0oBHuWtWq5UGzVqxcvVart+4gdVmZc+WX+57wCNA/vz5adm8\nKbO/m0+T1u0oXr4yK1ev+df90tPT6dKrH31eGHjf5+7W51l+/W0/4ZcieOrJtmxat5oSxYuzeUso\niUlJnD13jvj4eMZ/NJU3hg/TgEfJ0bp0eoqDu7bx08Yghr/xlnqCRERERERMUqdOHezt7fn1118z\ntnl5eREUFERQUJAGPEqusmDBAtq3b09sbCz79+9n6tSpfPDBB5l64L1jx44sWbKEL7/8Eh8fH+rX\nr09aWtq/7rdp0yaqVat2S7/dvVi9ejUjR44kNTWV69evExISwrPPPsuuXbtwc3Nj9+7dJCYmEhwc\nzPnz5+nevft9nUckO3h7e7NixQpeeuklmjVrxsmTJ82OJCIiIiKSZ/2tJ8gwGDViOFt//kkDHiVX\nSU1NpX7TQNZt2MjVa9dwsHdgd0jwfQ94BHBzc+Pxhg2Y/e18GrVoTVHfiqzfGHRXWTp07cELg1+5\n73N37tmHg4cOczH8Et27dGLDjz/g4+PN5q2hxMcncP7ChZs9QZOnMOq1VzXgUXIsi8VCj25d+G3H\nFpb8sIK3R4+9r54gy5120oRuyUuioqLw9/fn2rVrZkcRybTQ0FBKlixJ2bJl/3EC8L3avXs3nTp1\nIjo6mm+++YaXX36Zp556iho1alC8eHFSUlJITk6mZs2a1KpVC8MwGDp0KKGhoVy9epWLFy/e13kN\nwyAxMZHU1FS8vLwytoeEhDBv3jzWr19PdHQ0VapUITQ0FBcXlyy5XpEHKTY2llatWlGnTh2mT5/+\nt59TrdYmIiIiZlEtSPKSAQMG8MgjjzBo0CCzo4hkSnh4OOfPnycgIABXV9csO26LFi2Ii4sjICCA\nqKgorl69StOmTalatSr29vYkJydjZ2dH165dcXJy4siRIzRt2pTChQszcuTI+144Jy0tjdjYWNzd\n3TMW84iNjeWzzz5j/fr17NmzBw8PD6ZMmaLFeSTX+P7773njjTfYtGkTlStXvuU11YFERETELKoD\nSV5y7tw5GjZseN99C1nOZoXkeLNTSC61JXQbZcuUpnSpUlnWExSyNZRnBw7mytVrfDX9E4a9MYqn\n2j1BzYDqFPXxJiUlleTkZOrUeoSA6tUwDIMBQ15h777fSEhM5OTvv93XeQ3DICEhgbS0dLy8PDO2\nB23azPeLl7AhaBNx8fEEVKvKlo3ryJcvX5Zcr8iDdONGNC3adaBZ48f5aPyYv/cEuXqqFiQiIiKm\nUC1I8pLevXvTvHlz9RRIrnf+/HkuXbpEQEBAlj4r1ahRI5KTk6lfvz4nT54kOTmZxo0bU6VKFSwW\nCykpKdjb29OtWzccHBw4ePAggYGBFCpUiNGjR9OtW7f7Om9aWhoxMTEUKFAgY+DqjRs3MnqCfv31\nVzw9Pfnss8805FFyjdmzZ/PBBx+wefNm/Pz8bnlNPUEiIiJiFtWBJC85fvw4TzzxBKdOnbq5ISkO\nDJu5oUTug2EYhGwNxc+3HKVKlsyynqD1G4N4ZeSbXL4SxYyPpzD8zbfp2L4dNapXw8e7CMnJKaSk\npFDv0TpUreKPzWajz/MDOXzkCFarjUN7d9z39SQkJJCeno6n5189Qes3BrFw6TI2BG8iMTGJWjVr\n8MtPq7U4j+QKV69eo1nbJ+nYvh0fvPPW316/U0+QhjyK/JdhGHh4eHDhwoVbfkGIyF/q16+Pi4sL\n+/btw8HBgaJFi1K+fHns7Ow4e/YsBw4c4IsvvmDQoEFMmjSJhQsXsmnTJsqVK8eMGTPo3bt3lk/Q\n/vP3VFb9kSqSXWJiYggMDKRhw4Z8/PHHt3wP60aeiIiImEW1IMlLPvzwQ65evcrkyZP/2mi1Qsrd\nPWBvs9m4djGcguUrY+/g8IBSiphnzZo1vPLKKzg6OhIREYGLiwuVKlWicOHCGIbBunXrKFu2LPv3\n7+fGjRs0bNiQsWPHcuLECXbt2sXs2bMpXbp0lucyDEN1IMmVvvvuO95++202b95MhQoVMrarDiQi\nIiJmUR1I8hKr1Yqrqys3btzA2dnZ7Dga8ig5jmEYPPKfxyhY0It9+w/g4OBA8aLF8PO9ubhs2Okz\nHPrjCHNmfs6zfXoxevxE1q7fyNrlSygfUIuvP5tG9y6dH0hPkOpAkhtdv36D5k+0p03LQMaPfvfW\nniANeRQRERGTqBYkecno0aOxWq2MHTvW7CgiOdKyZct4662bDyFfvnwZNzc3KlasSMGCBTEMg7Vr\n11KxYkX279/PpUuXaNSoEZ988gl79uzhyJEjfP3115QoUSLLc6kWJLnV119/zfjx4wkJCaFcuXIZ\n29UTJCIiImZRHUjykpSUFDw8PEhISMDBwQGSE8CWbnYskRzDZrNRpXY9ShQrxq+/7cfB0YESxYrh\nW+5mT9CJU2EcPXacBXNm8UzXp3njnfcJ3bGTpfPn4l+rHnNmfs7THTtkec1GdSDJraKirtC07ZN0\nf7oT7775+i2v3aknKGu76kRyMYvFgq+vL6dPnzY7ikiOtWjRIgICAnB0dKREiRJ4eXmxZcsW9u3b\nx4kTJxg+fDiOjo689tprzJw5k/Xr11OkSBGCg4P55JNPePTRR4mLi8vSTBaLRX+8Sa5UoEABfv75\nZzZu3MiaNWvMjiMiIiIikuf4+voSFhZ268aUpLve32KxULhUSUhLy+JkIjlDu3btGD16NN7e3jg5\nOVGxYkWioqLYsmULmzZtonr16owYMYKvv/6a1q1bM2jQIHr37s2bb75JvXr18Pf3Z968eVmeS3Ug\nya369u3LqFGj6Nmzp9lRRERERETyHHt7e0qXLs3Zs2fNjnKTxQ7sHAB9xpWcwWKxsHzBPKr6V8bB\nwYGSxUvg4eHO5q2h7Nt/gDNnz/H68FdIt1p5ZcQbzF+0hHU/LKVoUR/Wr1zG+MlTadi8FUlJd19f\nvdtcIrlRwYJeBK1ZxdIVKwn+JcTsOCIiIiIieY6eDRO5s86dOzNq1CiKFClC/vz5KV++PBEREYSG\nhrJp0yZq167Nq6++yowZM2jdujWvv/46Xbp04d1336VatWpUqlSJJUuWZHku1YIktxowYABDhw6l\nX79+ZkcREREREclz8uXLh4+PDxcuXDA7ikiOZGdnx49LFlKxQnns7O0oXbIU7m5u/LIllF9/28+F\ni+G8NXI4cfHxDH51BD+u+4k1yxZTskQJVi9dyDtjxtG4VVtSU1OzNJfqQJJbeXsX4Zd1q/nm23mE\nbt9x1/tpyKPI//Dz8/v7w/0ikqFcuXJMmzaN8PBw3n33Xdzd3UlLSyM9PR1/f3+OHz/Ozp07cXJy\nIjg4mBIlSnDt2jV++OEHzp8/T2BgIC4uLmZfhkiO4enpSbly5fQhRERERETEBH5+frdp6L771Qr/\nXHTA3sEha4OJ5BAWi4U+ffoQGhrKjh07aNCgAXFxcdhsNooWLYq7uzubNm3i9OnTDBs2jNdffx3D\nMNi6dStr166latWqVK1a1ezLEMlRatWqpTqQiIiIiIhJclRPkMUC+V3BxQOc3cHByexEIpT38+Wz\nqZMJP3mUUSNexdXFhfR0K1arlcqVKnLk6DF27dmLq6srwWtX4ePjTVTUFX5YtZrIy5cJbNaEfPny\nmX0ZIjlG4cKFKFOqlGpBIiIiIiImyFF1IJEcyM7Ojv79+7Njxw5CQkKoV68ecXFxWK1WihcvjouL\nC5s2beLs2bOMGjWKoUOHYhgGISEhrFu3jho1auDv72/2ZYjkKI888ojqQCIiIiIiJrnl+TDDZm4Y\nkRyoUsUKzPz0Y8JPHmXEK0PIly8fVqsVm2FQqUIFfj/8B3t+3YdngQIErVlJoUIFiYy8zPJVq7l6\n7RqBzZri6Oho9mWI5Bg+Pt6UKF78nmpBegJZ5H+4u7sTFxdndgwR08TGxnLx4kUuXrxIeHg4SUlJ\npKamkpaWlvHVrl07ateuTZcuXejSpcttj2MYBkeOHOGDDz7gs88+o0uXLhw+fJjixYtn8xWJ5HyR\nkZEUK1bM7BgiIiIiInmOu7s7sbGxZscQMU16ejoREREZtaBr167dUgNKTU3Fzc2NV199lYoVKzJp\n0iQmTZp022PFxsby448/8vHHH3P16lXGjx/PU089pcZVkf8nIiJCdSAREREREZPkuJ4gwwBbOlit\nYE03O4085AzDuNkTFH6Ji+GXuBQRQWJS0n/rQOmkpd+sBz3V7glqBFSne5fOdO/S+R+PdfiPI7w7\nZhxfzJpNz25dOPLrbnx8vLP5qkRyvojLlylW1MfsGCIiIiIieU6OqwOJZLO0tLRbeoKuX79+Sz9Q\nWloaXl5eDBkyhCpVqjB58mQmT55822NFR0ezYsUKpkyZQlxcHBMnTqRdu3bqCRL5f/RsmIiIiIiI\neW55PswwzA0jks0MwyAmJuaWnqCk5OS/9QR16fgUVfwr07N7V3p273rbY9lsNg4d/oMvvp7N13O/\npW+PZzj2216KFCmczVclkvNFREZSrGjRu36/hjyK/I8zZ87Qr18/s2OImGLs2LGMGzcOX19fSpYs\nmbH6mp2dHWvXruX8+fPUrFmTNm3a3Hb/iIgIgoODM76cnJxo3bo1O3fupEKFCtl8NSK5R0REBEXv\n4Y83ERERERHJGmfOnKFcuXJmxxAxRXx8PN7e3nh4eFCmTBlKlixJoUKFcHJy4uLFi6xevZr8+fMz\nePBgDMP4W2N2Wloau3fvJjg4mKCgIH7//Xfq169P//796dWrFw4OuvUgcjuRkZGqA4mIiIiImCRH\n1YJsNkjWoAHJPm+PHsvU6Z/j51uOksWLU6yoD66urlgsFlavW8/F8HDq1HqE9m1v3xMUfukSwb+E\nEPRLCMGbQ3Bzc6V1YAt+Dd1MubJls/diRHKRyMuXKeqjIY8iIiIiItktR9WBRLLZ9evXKV68OF5e\nXrf0BDk6OnLu3DnWrVuHi4sLw4YNu+3+qamp7Nq1i6CgIIKDgzl8+DANGjTgpZde4plnnsHe3j6b\nr0gkd9CzYSIiIiIi5rmlFmRnBzaruYFEstFrb77NF7Nm39IT5OLiAsCqNeuIiIykft1H6dT+ydvu\nf+HixYyeoE0hWyhQwIM2gS3Yv2MrpUuVys5LEck1DMMg8nIURe9hUWQ9aSnyP06fPo2vr6/ZMUSy\n3dWrVzl//jylSpXi6NGjAKSkpDBv3jw+/PBDSpcuzVdffUWrVq0yHuo3DINt27axcuVKgoKCCA8P\np2nTpgQGBvLee+/h6+urldlE/oXVauXKlSv4qKFbRERERCTbqQ4keZVhGOzcuRNnZ2emTZtG9+7d\nATh8+DCTJk1i27ZtvP322wwdOpQiRYpk7Hft2jUWL17Mxo0b2bJlC35+fgQGBvLBBx/QsGFDnJ2d\nzbokkVwjIiKCYsWKmR1DRERERCRPylm1IMPsAJKHREVdIfzSJSqWL8+hvTsASE5OZu78BXz0yadU\n8PNlzszPadGsyS09QVtCt7Fy9VqCNodwOSqK5k0a06JpE8a+95YGO4rcheTkZBISEilY0MvsKCIi\nIiIieU7OqgOJZB/DMNi9ezdOTk58+eWXdOjQAYCDBw8yceJEdu3axfvvv8+QIUMoVKhQxn5Xrlxh\n0aJFbNy4kdDQUCpWrEhgYCDjx4+nQYMG5M+f36xLEsk1IiMj1RMkIiIiImICwzD+Xy1I800k74iI\niORSZCTVq1Zhb+hmABITE5n93XwmT/uMalX8WTh3Fo0fa5TRE2Sz2di8JZRVa9cS9EsI165fp3mT\nxgQ2a8LEMe9RpnRpE69IJHeIiYnB0dERV1fXu95HQx5F/is5OZmrV69SsmRJs6OIZJtjx47x2Wef\nsXDhQjp37syaNWsAOHnyJE2bNiUgIIC5c+fy2GOPZewTExPD/Pnz+fLLL7FarfTs2ZPZs2dTu3Zt\nrcgmco+uXr2Kp6cnjo6OZkcREREREclzbt/QrQfs5eGVlJTE8uXLmTJlCunp6UyZMoVOnToB8Oqr\nr7J48WKGDRvGF198gYeHB/DXQMgvv/yS1atX88QTT9CjRw9mz559ywBIEbk7kZGR1KlTx+wYIiIi\nIiJ5TkxMDCkpKTnns6zFAnb2YLOanUQeYn8cOcr0mV+xdMVKunXuxA8L52VsD3yyI3Vq1WTh3G/4\nT726GfvcuBHNdwsW8uXsuTjYO9Cj29PMm/Ulj9QIUE+QyD26HBWFj7e3FkkWERERETHB6dOn8fPz\nMzuGSLZJSEhg6dKlTJ06FQcHB2bMmEHbtm0BGDRoEKtXr2b48OHMmjULd3d34GZP0LZt25g5cybr\n16+nffv29OvXj3nz5t0yAFJE7k5ERATVq1c3O4aIiIiISJ5z+fJlnJ2dM56B0XNh8rAzDIPfDx1m\n+syvWLlmLT26dmH8++8CsP/AQdp07EKD+nX5YeE8Hq1dK2O/a9eu8+33C/hy9lxcnJ3p0bULC+fM\nomaNAOzs7My6HJFcKfJyFEV9vO9pHw15FPmvM2fOULp0aTWkykPv5MmTLFu2jKVLl3L58mX69+/P\n0aNHKVq0aMZ7Tpw4QZUqVfjpp58ythmGwZw5cxg1ahRNmzbl888/p3HjxmpEFckErdQmIiIiImKe\nsLAwunXrZnYMkQcqOTmZDRs2sHTpUn766Sfq1avHhx9+SKtWrW6p6YSEhLB69WoeffTRjG1nz55l\n4MCBnDp1ikGDBvHJJ5+oiVskk1QLEhERERExR1hYGH5+fjmnv8FiB/ndwDDAsEF66s0vkUw6fuIk\nS1esZOkPq7h+4wbP9+vN8f2/4u3914DTYydO8GjtR/hx6aKMbTabja9mz+XdseNp1bw5sz7/lEYN\n/pNzfmZEcqH7aegWEREREZGsERYWRsuWLc2OIfJAJSYmsn79epYuXcqGDRto2LAh06ZNo3nz5rfU\ndDZv3syGDRtuGT4XFhbGgAEDCA8PZ9CgQcyYMQMvLy8zLkPkoaGeIBERERERc/xtsQ9DQx7l4WMY\nBkePHb/ZE7RiFXFx8Qzo35eTB3+jUKGCGe/74+gxmjzeiMXfzcnYZrVamfHVLMZM+oi2LQOZN+tL\n6td9VD1BIpkQefkyxYr63NM+GvIo8l+nT5/G19fX7BgiWS4pKYmQkBA2bNjAxo0biY6OpnPnznz6\n6ac0atTotoNN3dzcSE5Ozvj3P2/gxcbGEhQURI0aNbLzEkRMd/bsWaKioqhQoUKW3bw2DIPPP/+c\n2rVrZ8nxRERERETk3vztRp7IQ+LEiRNs2LCBDRs2sG3bNmrXrk23bt2YNm0a3t63f6j4f2tBVquV\nzz//nLFjx/Laa6+xZs0aHB0ds/MSREyVlpbGrl27KF68OGXKlMHBIWtupR06dIhdu3Yxbdq0LDme\niIiIiIjcvRzZE/TngEebFWzpZqeRXCohIYHNW0PZGLyJDUGbSEhI5OmO7Zn56VQa1K+HnZ3d3/Zx\ndXElOTkl49+PnzjJC0OGkp5uZevGn6jiXzk7L0HEdGGnz3D9xg0q+Pni6emZJcc0DIMZX82i9iM1\ns+R4IiIiIiJyb3JkLUgkCxw7diyjJ2j79u3Ur1+frl27MmPGDAoXLnzbff63Jyg9PZ1p06YxadIk\nRo0axSuvvJJlPREiuUFqaiq7d++mRIkSlClT5rbPVN6Pffv2cfDgQSpXVm1VRERERCS76dkweVjF\nx8fzy5atbAjaxMbgTaSkpNKlYwdmf/EZ9R6tc9ueIDc311vmBP1x5CjPDx6Kk5MjOzb9TMUK5bPz\nEkRMd/JUGDGxsVTw86VAgQJZckybzcYXs2ZTu+a99QSpCivyX7t27aJq1apmxxDJUleuXKFRo0Z4\ne3vTpk0bFi5cSM2aNW/7B9v/8vLyYt++fTRv3pxChQrxyy+/6Aae5Elnz55l7Nix/Pjjj5QuXZqT\nJ0+SP39+KlasiI+PD4ZhYLPZMAwDOzs7ypQpg7+/P/7+/hQrVozY2Fiio6NJTU3F0dERR0dHnJyc\ncHR0ZN26dfz6669s3brV7MsUEREREclzoqOjOX36NBUqVDA7ikiW+uSTT5g0aRJPPvkkzz77LAsW\nLLirxQq8vLwYOHAgFSpU4OLFi7i4uLB9+3YqVaqUDalFcgar1cqCBQsYM2YMLi4uxMTEcPnyZcqV\nK4evry9OTk4YhpHx5eHhQeXKlfH396dy5coYhkF0dDSxsbHY2dll1IAcHR2xWq306NGD6dOnq4lE\nRERERMQEOa4nyGaD5DizU0guFxERSaPA1pQqWYI2gYEsm/8tAdWr3UVPkCc7du+hxRMd8PLyZPPW\nUN4f9QYvDXg+yx5qFskNwk6fYczED/np5yBKFi/OybDTuLq4UKG8H0UKF7qlDmRnZ0fZ0qXxr1yJ\nKpUr4ePtTWxcHDduRJOWlvbffiDHjFrQytVrOX7yFJvXrzH7MkVERERE8pyoqCgiIiI05FEeOhMm\nTGD69Om0b9+eAQMGsGTJkrt6MNnLy4v+/fvj5+fHuXPnKFiwILt371bvguQpaWlpzJ8/n7Fjx1Kg\nQAGuX79OVFQUvr6++Pr64ujoeEstqECBAhnPhlWqVAmr1Up0dDRxcXHY29vf8nxYSkoKPXr04Ouv\nv6ZUqVJmX6qIiIiISJ7zt54gi93NRVdFcrELFy/SqEVr/MqVo03LQFYtXkC1qlWwWCx33M/L05Nf\ntoTS4okOeHoWYMu27Yx77x1eeLbvv/YTiTxMjp84yQcTPiR4cwjFixXlZNhp3N3cqFjBj8KFCmXM\nCPqzJ8i3bFn8K1fCv1JFvIsUISY2lujomNv2BC1aupyIyMvMm/XlPWWyGIbxzy9aLMadXhd5WKSm\nplK2bFmCgoJyVlO3SCYkJCTQrFkzmjdvzoQJE+5pX8MwOHr0KOHh4URGRtKwYUPd5JY85cKFC4wf\nP55ly5bx0ksvMXz4cLy8vDAMg8jISE6ePMmVK1ews7PDYrFgsViwWq2cOXOGI0eOcPToUaKiovD0\n9MTT0xNHR0fS0tIyvlJTU3Fzc2PBggWUKFHib+e3WCwYhnHnT1kiIiIiD4BqQZJXTJs2jT179rBw\n4cJbX0iMBe7xZ8DRBRwdsyybyP1avHgxI0eOZPv27ZQuXfqe9r1x4wbHjh0jIiICOzs72rdvrxt4\nkmfYbDaWLl3K6NGjKVKkCGPHjqVJkyYAJCUlERYWxunTp0lPT8+oA1ksFm7cuMHRo0c5evQoJ06c\nwMHBAU9PT9zd3bHZbBk1oD//2bdvX4YNG/a386sOJCIiImZRHUjyiqSkJEqXLs2uXbtyzoPLNisk\nx5udQnKx2NhYGrd6gk4dnuTdN1+/p30Nw+DI0WOEX4rgclQUjzdqQJl7rCWJ5Gbnzp9n7KTJrFq7\njpcHDmDY4EEUKFAAwzCIiIzkxMlTXLt+/ZaeoPT0dE6fOcfR48c5evwEV65exbNAATwLFPirJyg9\njbS0dFJTUyng4cHCud/g4+P9t/NbXD1VCxIRERFTqBYkecXEiRM5deoUs2fPNjuKSJb59ttvGT16\nNDt27KB48eL3tO+1a9c4fvw4ERERODk50a5du38dCCDysLBarSxcuJAPPviAMmXK8MEHH9CoUSMA\nEhMTOXXqFGfOnMFqtd7SE3T9+vVbeoIcHR1v6Qn6sx/oz56gAQMGMGjQoL+dXz1BIiIiYhbVgSSv\niI+Pp0yZMhw8eJCSJUve3JicALZ0c4OJZEJ0dDSNWrShb89nGPnq0Hva1zAMDv9xhEsRkURduUKz\nJo9T4h5rSSK5WdjpM4yd9BHrNv7Mq0Ne4uWBA3B3d8cwDC5FRHD8xEluREf/rSco7PTZjJ6gq9eu\n4eXpSQEPj1t6glJTb9aCCnp5sXDuNxQuXOhv579TT5CGPIoAS5cu5YsvviAkJMTsKCJZpnv37jg5\nOfHdd9/pBpzIPdi/fz/169dnyJAhjBo1isKFC2d7Bt3IExEREbOoFiR5gc1mo3LlysyZMyejYS+D\nhjxKLrVv3z5at27Npk2bCAgIMDuOSK7SuXNnjhw5wvTp02nRokW211JVBxIRERGzqA4kecW8efNY\ntGgR69evNzvKXwzbzSGP+hmU+2AYBh2796RI4cJ8/fmn6gkSuQe79/7KY4FteG3oEF5/9RW8vDyz\nPYOGPIqIiIhZVAuSvMBqteL/n7oTAAAgAElEQVTr68uKFSuoXbu22XFEssSOHTvo2LEjW7ZsoXLl\nymbHEclV2rZty8WLF5k+fXrGgq/ZST1BIiIiYhbVgSSv+Oqrr9i4cSMrVqz4a2NSPBhW80KJZILN\nZqNtxy5UrODHp5M/VE+QyD3YErqNwCc7MmrEqwx/eTAFChTI9gx36glyyO4wIjnRqlWr6Ny5s9kx\nRLJMTEwMa9as4erVq/rDTeQeVa1alebNm3P16lVTBjyKiIiIiMiDdezYMWJiYmjYsKHZUUSyzNy5\ncxk+fLgGPIrchwEDBtCnTx+KFi2qWqqIiIiIyEMoR/YEWezA2ePmkEdbOqSl3vynyF24fDmKLdu2\nc/nMSX2OFblHNapX4/GGDbh+44YpAx5FREREROTBOnDgABaLRQMe5aEye/ZsRo0apQGPIvdh4MCB\nDBgwgKJFi5odRUREREREHoBVq1bRs2fPWzcaNnPCiGSBc+fPc+D3Q6z9YYl6gkTu0aO1a1Hv0TrE\nxMSaMuDx39iZHUAkJ2jdujVr1641O4ZIlklJSSFfvnw4OzubHUUk13FycmL58uXMnz+f9HQ9SCMi\nIiIi8rCpVKkSzs7O/Prrr2ZHEckyqampeHrqoWSR+9GqVSt69ep16wqeIiIiIiLy0MjZPUEGGGZn\nkNwmJTUFF2cXnJyczI4ikuvkz5+fZd9/x9z5CzAM/QdYRERERORhExAQQGpqKocOHTI7ikiWUU+Q\nyP1r3749nTp14scffzQ7ioiIiIiIPACtW7dm3bp1t260szcnjEgWSElJxc3NFQcHB7OjiOQ6Li4u\nLJk3hznzF5gd5bY05FEE6Nq1K/v37+fkyZNmRxHJEgULFsTb25tVq1ZRt25d5s2bZ3YkkVwlPT0d\nNzc3fQASEREREXkI2dvbM2jQIGbMmHGbV/VQp+RODRs2ZO7cufz0008EBAQQExNjdiSRXCU1NRUv\nLy+zY4iIiIiIyAPQs2dPQkNDOX/+vNlR/mLYIDEWkuIgNRFsWnxQ7l5RHx/y58/Hhp+DqVbnPyxf\nqQeURe5FamoqXp6eWCwWs6OIiIiIiEgWc3R0ZMCAAXzxxRdmRxHJMg0bNmTOnDmsXLmSOnXqEB8f\nb3YkkVwlNTWVggULmh1DREREREQegL59+7JhwwYiIyPNjiKSJUqXKklqahohW0PxrVqDnzb8bHYk\nkVwlNTWVgl45c8EcDXkU4eYKzS1btmT79u1mRxHJEg4ODnz55Ze8+OKL7N27l759+5KWlmZ2LJFc\nIy4uDldXV7NjiIiIiIjIA9KhQwfVgeSh0qdPH/Lnz8+gQYM4dOjQPwwxFZF/olqQiIiIiMjDy9XV\nlSZNmrBz506zo/zFMNBiI3K/8uXLx4yPp/DswMH8cfQoXXr1xWazmR1LJNeIi4/H1dXF7BgiIiIi\nIvKAdOjQgW3btpkdQyTLvPDCCyQnJzN06FD27dvHrFmzzI4kkquoJ0hERERE5OHl6enJf/7zH/bs\n2fM/W9WPI7mXi4sLn06eSM/+Azhz9hxPdO5qdiSRXCUuLj7H1oEczA4gklO4u7uTmJhodgyR+5aU\nlMT+/fvZtm0bBw8exNHRkaSkJAAaN26Mo6OjyQlFcg9vb2+io6O5fv26VmwTEREREXkIubu7k5CQ\nYHYMkftms9m4ePEi27dvZ9u2bURHR+Pq6sr58+cBaNGihckJRXKXEiVKcPz4cbNjiIiIiIjIA+Lh\n4ZGzeoIsFrMTSC6TmJjIbwcOErp9J4ePHMXJyZHomBgA2rZqiZ2d1voWuVvFivpwOeoKsbGxeHh4\nmB1HRERERESymJ4Nk9zOZrNx/vx5tm/fzvbt24mNjaVAgQLs3bsXgGbNmpmcUCR3KVmypHqCRERE\nREQeYn/rCTI05FFyl4SEBPbtP0Dojp38ceQY+fI5cTkqCoAunZ4yOZ1I7lKieHEuXAwnISEhxw17\nVHefyH+5urrqRp7kGhEREUydOpUKFSpgsViwWCy4uLgwZMgQwsPDadmyJY0bN+b777/n6tWrhISE\nmB1ZJFdxdHSkX79+TJo0yewoIiIiIiLyAKgOJLmJ1WolODiYzp074+joiMViwd7enrp167J06VL8\n/Pxo06YNXbt25eDBg1itVurWrWt2bJFcpX///syZM4dr166ZHUVERERERB4AFxeXnFULstiBswfk\ndwMnZ7CzNzuR5CDhly7x4dRp+FatgcXVE4urJ65FijPs9VFEXblCqxbNeKzBf1j2/bdcv3iWdSuW\nmh1ZJFdxdXWlS8cOTJ3+udlRRERERETkAVBPkOQm6enpbNy4kQ4dOmBnZ5fRE9SgQQNWrFhBxYoV\nadWqFT179uTQoUNYrVZq1KhhdmyRXOX555/niy++IDY21uwoIiIiIiLyAOS4niCRO7hw8SITJk+l\nTOVqGT1Bbt4lGPHWu1y/foPWgc1p1KA+q5cu4kb4WZbO/9bsyCK5SsGCXrRp2YLPZn5tdpS/cTA7\ngEhOce7cOQICAsyOIXJHqampBAQE/OMKUrt27cLJySmbU4k8nDp27MjkyZPNjiEiIiIiIg/AuXPn\n8PHxMTuGyB0ZhsGePXuoX7/+bV+fOHEizz77bDanEnk4+fn5Ua5cOcLCwihUqJDZcUREREREJIud\nP3+eJk2amB3jVhYLYAcW4+bQR6xmJ5JsYthsWOz+vjZ3SkoKZf0DiLx8+bb77d6yCXt7DQQVyQod\n27dj9nfzzY4hIiIiIiIPwLlz5/D29jY7hsgdGYbBtm3bePzxx2/7+tSpU3nmmWeyOZXIw8nf35+i\nRYty7tw5qlevbnYcERERERHJYufPn7+1FmSxA8NmXiCR20hOTqZgyXIkJSXd9vXdWzZhsViyOZXI\nw6njk+1YuWat2TH+RkMeRQCbzcYvv/zCtGnTzI4i8o/2799PrVq1APD29sZisZCWlka9evWoV68e\n9evX14BHkSwUHR2No6Oj2TFEREREROQBCA4Opnnz5mbHEPlHNpuNqlWrcuzYMeDmALqIiAjKly9P\nvXr1eOSRR2jXrp3JKUUeHoZhEBMTo1qQiIiIiMhDKC0tja1btzJ37lyzo/zFsEFygprK8whbWhpG\nWhpY7Ig/fpLEsNPYOTnh8UgA+Xy8IT2N3fsP0iCwDQBFC3phA2wWC/Xq1Kbuo3VoUK+eBjyKZKGY\nmFjVgUREREREHlLBwcG0aNHC7Bgi/8hqtVKqVCkiIiKAv3qCKlasmNET1LJlS5NTijw81BMkIiIi\nIvLwSkpKYvfu3f+4iIJITrAldBtNWt98/qt4sWKkpaVhsVio92ht6j1ahwb16mrAo0gWiomNxdEh\n59WBNORRBDhy5Aj58uWjWLFiZkcR+UebN28GYMKECdStW5cyZcrg5+enP9hEHpClS5fSsWNHs2OI\niIiIiMgDsHXrVtq3b292DJF/dOPGjYwBj8HBwTg7OxMQEICbm5vJyUQeTgcPHiQtLY2aNWuaHUVE\nRERERLLYgQMHKFSoEIUKFTI7yl8MQwMe85BzM2cR9eNPJJ4+c/P/+/9h7+JC3edaExS0FYApDfyp\nXsidsh4ulHN3xlLKF/shw7HkwMZTkdxs6YpVdH+6k9kxRERERETkAdi6dSv9+vUzO4Y8LNLSID09\n04cxbGlYnN3Azo6oqCgiIiJwcXFh9erVuLi4UKNGDVxcXLIgsIj8f7t27cLV1ZVKlSqZHUVERERE\nRLLY3r17KVWqFO7u7n9tVD+O5DAbg38BYOanH1PBzw8/37KUKV1ac4JEHpClP6zkpQHPZft5jf/X\nF/j/We70BovFYvzbAUQeBklJSQQGBhIQEMCMGTP0y1BypOjoaEqXLk1kZKRu3ok8YFarlQIFCnDu\n3Llsf9jn559/plWrVhiGoV9GIiIiku1UC5K8YtmyZbzyyits2rQJf3//v15IjLn3gzm6gFZ5lgfg\n1VdfpWDBgrz77rtmRxF56I0fP57r168zderUbD2vYRjY2dmpDiQiIiKmUB1I8or4+HiaNWtGo0aN\nmDp1as7oCbLZIDnO7BSSTWzp6diSU4g/eozrW7aRcOo0dvnz4VW/Lp71HsW5dEmizp2h0n8aE/HZ\naBwTYrB4FMRSsTqWshXBzSNnfN+KPCRSU1PxLF6Gy2dO3PqwTzZYve4nOnTtoVqQiIiImEK1IMkr\n5s+fz6hRowgJCaF8+fJmx5HczGqFlPhMH8aw2TAA0q3YeRYGYODAgZQvX54RI0Zk+vgicmfvvPMO\nAOPGjcvW89psNuzt7VUHEhEREVOoDiR5RUxMDI0bN+aJJ55g3LhxN3srEmMBff9LznH+wgVqNWxM\n5OkTODg4mB1H5KEWHx+PT7mKXD0fhrOzc7aee8nyFXTv2/8fa0H66RcBnJ2d+emnn2jRogWfffYZ\nQ4cONTuSyN8sX76cxx9/XAMeRbJBcHAw3t7e2T7gEbL/xqGIiIiISF7UpUsXkpOTadmyJadPn8ZR\nQxolh0lKSmLVqlWsXLnS7CgiD72UlBR++uknBg8enO3nDgoKyvZzioiIiIjkNW5ubmzcuJFmzZrx\nzTff8MILL5gdCezswNkDbFawpoM1DQyb2ankAbFzcMDOzQHPR2tT4JGaYGfBsFqxODhkDG9cunET\nLVo0J3+nfmDvANZ0LA6qWYo8COt/DqJc2TLZPuDRMAzGfTglW88pIiIiIpIX9e7dm+TkZAIDAwkL\nC8POzs7sSJJbZdFAFIudHRgG1tQU7Lj5oPHq1avZvHlzlhxfRP5ZYmIiGzdu5K233sr2c69Zsybb\nzykiIiIiktcUKFCAoKAgmjRpQuXKlenduzfY2YMt3exoIhkWL1tBm8AWGvAokg3Wrt+If6WK2T7g\n0TAMxn90554g3akQ+S8PDw9GjBihmySSY1gsFhYtWgRASEgIb731Fu+//77JqUQefps3b6Z3797M\nmjUr28+9fft2Ll68mO3nFRERERHJi3r37o2zszMnT540O4oIM2fOpESJEsTFxZGamkrnzp1p1KgR\nNWrUMDuayEPNZrPRrl07ihcvTufOnbP9/BMnTvw/9u47Oqqya+Pwb1IhoSbSeyihF+lNOhLpoEgR\nGwpI70Wkg/SOCpEqShNQUJqA9N4hhF4CSE8gJECSKef7g/fNKx89JDmE3NdaWcucmfM891Ais2ef\nfeJ9TxERERGRxCh16tR06dLl9eoJslgeNpa7uD0c6idvFOMpQwAsLs5YnJxwTpWGFStXAbB23QaG\njhzDN716YHFxxWKxaMCjSBxZ89d6WnfowrRJ4+N97783bSEsPDze9xURERERSYy+/PJLbDYbFy5c\nMDuKJGSxNORx3KQp5CpUjEiLhYiICBo0aMB7772Hr69vrKwvIk9ms9moVasWvr6+1KlTJ173NgxD\nPUEiIiIiIvEkTZo0dOzYkU2bNpkdRQS73Y7FMxV/rf8bgBUrVzF+ynf07dHN5GQib77lf66kS6++\nfDch/m/AunLN2ufecEpDHkX+pWDBghw7dszsGJKItWnThqCgIADSpk1L8+bNSZ48OU2aNGHRokWU\nLFnS5IQib75FixbRr18/qlWrFu97nz9/nrfeeive9xURERERSawKFixIQECA2TEkkdq5cyeDBw8G\noHDhwly5coU0adKQIUMG3N3dmT17NhaLxeSUIm+2f/75hyNHjrBw4ULc3d3jff/z58/H+54iIiIi\nIonVa9UTZBgQEQ4P7kJEGNiizE4kr8BwODAiIzCsVox7YTjOHcc4dxwj9DaGzYZhjcIwDD5r046r\nV68B4O7uToMPW5AyQ1ZaftGG3xb+TNEihU1+JSJvvgW/LmHogH5ULF8u3vc+HxREmre8431fERER\nEZHE6rWqBUnCFIOenf/e+GPz1m2MHDsBgEIFCnDu/AW8s/iQOXNmvL29mT59eqxGFZHHnTt3jqCg\nIH766SdcXeP/pjoaNCwiIiIiEn8erQPFzk0bRF7GR5+35tatYJydnQF4t34jUmfKxhftOvHHkoXk\nz5fX5IQib75fFv3KmOFDKF2yRLzvff5CEGmeMydIQx5F/iV37tzcvn2bdevWmR1FEqHjx4/j7+/P\nli1bAJg/fz5p06YlPDycH3/8kSpVqpicUCRxCAoKIleuXKbs3bx5czw9PU3ZW0REREQkMSpTpgwz\nZszAarWaHUUSoY8++ohBgwYBUK5cOcqXL09kZCTp06dn4cKFuLi4mBtQJBEICgrCx8cn+sP0+Obv\n72/KviIiIiIiiVG+fPm4fPkymzdvNjsKGA5w2M1OIbHECDqNY9F07N92xj6wDY7vh+L4YRj2oe2x\nD/4K42wghw4fYc7P89m5Zw8AS+f/RNo0abh79y4/z/SnfNkyJr8KkcQh6NIlcubIYcren37UHKvV\nZsreIiIiIiKJUZkyZfD398dm07/DJYaMlx8KYRgGDoeDBk1b0Hfgwxu/1qhWhbeLFiEyMpJs2bIx\nb94803oURBKToKAgcubMiZNT/F9Cb7FY1BMkIiIiIhKPChUqxKlTp9i1a1eM3s+LuR6E3mXfsj8J\nXL+ZC/sOcXTNBiLCws2O9cJ27t7DL4sWs//gIQCW/DKXtGnScOdOKEt+mUvJ4m+bnFAkcQi6eImc\nPub0BLVp9RnBISHPfI6GPIr8i6urK8uWLaNFixbs3r3b7DiSyBw9ehSAy5cvA1CtWjU6duxIp06d\nqF+/vpnRRBKVtGnTsmPHDlP2Pnv2LMHBwabsLSIiIiKSGHXt2pUkSZLw6aef4nA4HnnM4XDgcDii\n77AuEtvCwx9+6GgYBhaLhbVr15IkSRJ27dqFu7u7yelEEgdvb2/OnTvHzZs3431vh8PBnv8M9xAR\nERERkbjn4eHB4sWL+eCDDzh48KDJaSwm7y+xyZIpO06NP8ep2VdY3nkPsuWBLD5YytXAqWlbLD55\nORxwDHjYTApQu9a7fPHpx/Tu1oWa1auaGV8kUUmbJk30sNX4dvrMWe6Ehpqyt4iIiIhIYtSnTx8i\nIyNp06aNen8kZiwvX8OzWCw4OTlx7979R45tWvMnTk5O7Nq1Czc3t9hMKSJP8dZbb3HixAnu3LkT\n73vb7Xb27t0b7/uKiIiIiCRWKVOm5Oeff6Z+/foEHAs0O468JGtEJDNafsXk+h8xslJdfmjSCotz\nwhmHdvhoAADng4IAaNygPi0+/ICBX/fmnQrlzYwmkqikTfMWO3eb0xN04uQpwsKfPZw24fxUE4kn\nFStWZPbs2dSvX59jx46ZHUcSibp16zJhwgQAZsyYwZUrV7DZbGzdupUMGTKYnE4kcRk5ciRz5szB\nx8eH3377Ld72vXjxIuXLl+err76Ktz1FRERERBI7V1dXFi1axKVLl+jcufMjTd1m3MFZEofdu3eT\nPHlyvL29gYe1IMMw2LlzJylSpMDV1dXkhCKJR758+fjiiy/w8fGhbt262O32eNu7c+fOrFmzJt72\nExERERGRhzfbnDZtGrVr1+bUqVPmBXFygiTJwc0DXNzQ0MeEzeLmjsUzOU55CuFUuynOX32Dc4fB\nONX7CKcCxaneoAnTZ84GYNZPv3D9+g2sVivbd+0iQ/p0JqcXSVzGDB/ClB/8yVWoGKvW/BVv+545\ne4533n2Pnp07xtueIiIiIiKJnbu7O8uWLePYsWP07t1bgx7l5cXgz8z2nbtIljYTPjmyA/DLwsUA\nbN2+k3Rp02KJweBIEYmZYsWK0bRpU7JmzUrjxo3j9f8Dbdq0Yfv27fG2n4iIiIiIwHvvvceECROo\nVb8R5y9cMDuOvIQU6dIw7d4lpt27xA/hF/n+7gXcPTzMjvVCylWtydxfFgAw66efuXUrmMjISHbu\n2UuG9OlNTieSuEwYNYIR4yaQu/DbrP97U7zteyzwONXq1GfQ132e+TzLs4pTFovF0IcYklgtWLCA\nzp0788MPP9C4cWOz48gbrm/fvowcORKAkiVLcunSJcqWLcvdu3dZs2YNLi4uJicUSVwcDgffffcd\nO3bsYMGCBfGy5+jRozl79izTp0/HYrFgGIY+wRcREZF4p1qQJFahoaG8++67ZEj7FjO/n4qXV+oX\nP9nVAzSUT17C1atXyZgxY/T3+fPnJ3/+/GzZsoVFixZRuXJl88KJJFJ37tyhUKFCbN68GR8fnzjf\nLyIigvTp03PixAkyZMigOpCIiIiYQnUgScxmz55Nnz59mDFjBnXr1jU3jGGANRJskebmkDjTpWcf\nJn0/DYByZUpzIegixYsVweEwWL54Ps7OziYnFElc7HY74yZN5cSpU8ya9l287Dn425Hcvn2HiWNG\nYvFMpVqQiIiImEK1IEmsgoODqVGjBrlz5+bHH38kRYoUZkeShMJmg6h7L3VK0MWLZM9XOPr7PLlz\n8XaRImzYtJnli+dTtkqN2E4pIs9x+/Zt8uTJw5EjR8iQIUOc7xceHk6mTJk4f/483t7eqgOJiIiI\nKVQHksTsh3GjGTJmPHOmf8+7NaqZHUfecK07dObH2XMBqFSxPOfOB1GoQH6SJk3C4nlzcHJyMjmh\nSOJit9sZPnos12/c5LsJY+Nlzz79B2GxWBgxZOAze4L000DkKZo1a8bKlStp1qwZYWFhZseRN9yI\nESOw2+00bdqUxo0bc+3aNX777Tfmz5+vAY8iJnBycqJUqVKcOnUqzve6cuUK8+bNw9/fnyZNmsT5\nfiIiIiIi8riUKVOyefNmrFE2Rk+c9HIn6wMXeUn/GegW3TjasGFDlixZQufOnTXgUcQkqVKlIm/e\nvJw8eTJO97FarWzbto3u3btTrFgx0uvujCIiIiIipvjss8/47bffaNSoEZGRJgxXNAyIvA8P7j78\n0oDHN9rEMSOx3Q2mfp33aFi3DleuXmXV2nX89OM0DXgUMYGzszOlSrzNqTNn43yvy//8w9yf5zPr\np59p0rhhnO8nIiIiIiKP8/b2Zvv27YSHhzNx4kSz40hCEoOBKNmyZsW4d4fdmzfgkyM7td+tycIl\nS+nboytlS5eK/Ywi8lypU6fG19c3znuCoqKi2LJlC127dqV8+fJ4eXnF6X4iIiIiIvJkrfN689Mn\nftRv0gyHw2F2HHnD+U+dhO1uMLVqVKdBndpcunyZrTt2MuuHqRrwKGICZ2dnSr79NqdOn4nzvS5e\nusTsn35m3oJFfNCw/nOfr58IIs9QsmRJsmXLxo4dO8yOIomAk5MTmTNnZujQoQCsXLmStGnTmpxK\nJPEKDg7G29s7ztY3DIPOnTtTsGBBfv/9d/r06UOVKlXibD8REREREXk2d3d3PmjWjO279mAYToDz\nE76c/vP1n++dk4AuxJYYypIlCzdv3mT48OGkS5eO3r17mx1JJFG7detWnNaCAgICyJIlC507d8bT\n05Np06bF2V4iIiIiIvJ8ZcqUIUOGDOzatSv+NzccYLfG6EJxSZicnZ3JnCkT3wwZBsDa5cvw8kpt\nciqRxCs4JATvOPw7aBgGrTt0pmjZivy5Zi2D+/XVMA8RERERERMlTZqUunXrsm3bNgzVY+RFWSwx\nPjVr5sxcvXadCVO/J3eunHRu/1UsBhORlxXXPUEHDx4kc+bMdO/enbfeeospU6bE2V4iIiIiIvJs\nTpXfp1LXgXilTs2efftVC5I45+zsTMYM6ene9xsAVv/2KylSpDA5lUjiFRwSgrd33N18w+Fw8MmX\nbSleoTJrN/zNqKGDKFa0yHPPc4mzRCJviIkTJ9KxY0eOHj2Ku7u72XHkDefp6cm9e/do164d7733\nntlxRBK1AwcO4OXlxYIFCyhSpAiurq706dMHgPz581OgQAHq1auHh4dHjNYfNGgQ27Zt48KFC3qj\nJiIiIiLymvjoo4+YPHky839fQYsWLcyOI284T09PbDYbWbJkYcuWLThrYKiIaSIjIwkMDOTy5cvc\nunWL8uXLM3v2bFasWIGvry/58+fnnXfeoUiR53/w9iTnz5+nVq1aTJgwgWbNmsVyehERERERiQkn\nJyfGjx9Phw4dOHDgAK6urmZHkjecp4cHkZGRdOvYnmpVKpkdRyRRO3DoCClTpGDB4iUUK1IYgD4D\nBuHi4kKBfHkpkC8f9Wr7kSRJkhit3/ubgRw9FkjQ8aN4enrGZnQREREREYmhVq1aMXXqVJYtW0bj\nxo3NjiMJwSsMgfD09ODBgwdky5qFjav/wMnJKRaDicjLCAsL49y5c5w7d47Lly9Trlw5/P39WbNm\nDb6+vhQoUIBKlSpRsGDBGK1/6tQpateuzbRp02jUqFEspxcRERERkZdlcXbBLUVqRg0bTIduPdm9\neYOu1ZE4l8zTE4fDwdc9u1O+bBmz44gkagcOHSZ5smQsWLyE4sWKEhkZydeDhpA0aVLy5/WlYP78\n1Kvth5ub20uvbRgGnXv25sLFi1w8EUDSpElf+FwNeRR5jtq1azN9+nTGjx9P3759zY4jb7iqVauy\nZMmSGA+NE5HYExoaysGDB4mKiuLrr7/m5s2bDBo0iCxZsnDs2DEmTZrEzp07mTRp0mPnXrx4kU2b\nNuHi4oKrqysuLi44HA5sNht2u52jR4+ydOlStm3bpgGPIiIiIiKvEWdnZ6ZOnUrjxo2pW7eu/r0u\nccrV1ZXPP/+cpUuXkipVKrPjiCRqwcHBpE6dmu+++w6Hw0GjRo0oU6YM3bt358KFCxw7doyBAwcS\nGBhI+vTpHznX4XCwcuVKQkNDcXV1jR4MY7fbsdvt2Gw2Bg8eTJ8+fTTgUURERETkNdO4cWOmT5/O\nd999R5cuXeJvY4sTJEkGdtvDL4ct/vYW09SoWoXlK1fh6ameIBGz3Q27y94DBwkLD6d3/0HcCQ1l\nyDd9SZc2LYEnTjBm4mT2HzzEqGGDHzv3/IULbN2+ExcXF9zc3HB2dsJud0TXgg4cOsyadRvY8tcq\nDXgUEREREXmNuLq6MnXqVD755BNq1aqlf6/L81ksMT7V09OTls0+5M81a0mVMmUshhKRl3Xz5k28\nvLyYOnUqUVFR7Nq1iyM3NL0AACAASURBVHfeeYcuXbpw/vx5jhw5woABAzh9+jReXl6PnGu32/nz\nzz8JCwt7Yk+Q1WplwIABDB06VAMeRUREREReMx81+xD/2XOZMecn2rT6zOw48oZ7t3o1Vv21jmSq\nOYqY7m5YGDv37OVWcDA9+w0g/F44wwZ8g1fq1ASeOMm3Y8YREBjIoH6Pz5A7c/YcO3btjq4D/f+e\noF1797Jtxy42rfnzpQY8AliMZ9xVyGKxGM96XCSxOHfuHKVKleLAgQNkzZrV7Djyhjt48CDNmzfn\n+PHjZkcRkf8wDAOr1frINO5r166RP39+AgICyJgxIwDh4eGMGDGCadOmUaNGDSwWC1arFZvNhrOz\nc/RX0qRJGTBgANmzZ3/ifhaLBcMwYt4VICIiIhJDqgWJPPT555+TKlUqxo8fb3YUSQTee+89vvji\nCzV6irxGoqKicHV1xfKvizY6duyIm5sb48aNiz62efNmunbtirOzM3ny5MFqtWK1WoGHg4NdXFxw\ndnamYsWKtG3b9ol7qQ4kIiIiZlEdSOShEydOULFiRY4cOUKGDBniP4BhgC0KrBHxv7fEGcMwHnlP\n+V87du2mQ7eeHNixxYRUIvIkT+oJunjpEsXKvcOJA3tJk+Yt4OHNYoePHsfMn+ZRs2pVAKKsUdjt\n9v/1BDk54+GRlCH9vybTf3qJ/j+LZyrVgkRERMQUqgWJPNSsWTN8fHwYPny42VHkdWe1gvX+Ky1R\nxa8Ovbp0xu/dGg8PeGjgo4jZntQT9OWXX5IuXTqGDRsWfWzDhg107doVT09PfHx8HukJ+m8/kLOz\nM1WrVqVVq1ZP3Es9QSIiImIW1YEkUYsIB4cdgMNHjlKzXiOO7dvFW295mxxM3nQbNm5mwLBv2b5h\nrdlRROQ/ntQTdObsOcpWrcHpw/tJlSoVALdv32HIiFHMW7iImlWr4jAcWK3WR3qCXJxd8PT0YNiA\nb0iXLu0T93tWT5CGPIq8oMGDB7Nv3z5+//13nJ2dzY4jb7DIyEhSpkxJeHg4Li4uZscRkWcYPnw4\n8+fPZ8mSJaRLl46aNWuSK1cuxo4dS+bMmWO0ps1mw9XVVR/kiYiIiClUCxJ56MaNGxQsWJCVK1dS\nsmRJs+PIG653796kSpWKvn0fvwOUiLw+rly5QunSpenatStt2rRhwYIFDBw4kPHjx9OkSZM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3I49evUjpM9NORRREREzKJakMjTGYbBkSNHonuCVq9ezYULF6hbty65cuWiZcuWODk5mR1TXkOG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\nmxv58+fH2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FtbU716dYKDg+nYsSOjR49GR0eHbt260a5dO6ZPn57q3Jo1azJr1ixsbGz+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\n1gEAgNyVP39+ZWZmWmdAUmJiomrVq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iIiIiUqjc3FwMHTr0iQs8JiUloVOnTpg2bRpOnjwJdXV1JcyQiP5K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\nEREREREREREREREREREREbnA/wAtp7Gtz9m1SwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x117c503d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#each hashtag, hexbin\n",
+    "plt.figure(figsize=(100,20))\n",
+    "\n",
+    "for j,hashtag in enumerate(popularHashtagsList):\n",
+    "    subset = latLonPopulated_HT[(latLonPopulated_HT['hashtag'] == hashtag)]\n",
+    "    ax = plt.subplot(2,5,j+1,projection=ccrs.PlateCarree())\n",
+    "    ax.coastlines()\n",
+    "    ax.hexbin(subset.x,subset.y,cmap=cm.Reds,bins='log')\n",
+    "    plt.title(hashtag)\n",
+    "    plt.axis([-180, 0, -75, 75])\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "This makes it much easier to see where certain hashtags are centered! (Note: because we're using a subset of the data, there aren't hashtags that are geo-located for all the top hashtags. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/README.md b/README.md
index a8435e9..c0ad21c 100644
--- a/README.md
+++ b/README.md
@@ -1,2 +1,21 @@
-# DataScience16CTW
-This is the base repo for the "Change the World" project for Data Science at Olin College, Spring 2016.
+# DataScience16CTW - Political/Social Justice Tweet Visualization
+A project done as part of Olin College of Engineering's Data Science Course, 2016
+Students: Sophia Seitz and Victoria Preston
+Instructor: Paul Ruvolo
+
+## Project Goals
+Using data from the Twitter API, we would like to visualize how during political or social justice events information propogates through the Twitter network. In particular, we would like to look at: who is engaging, how many are engaging, how certain hashtags gain momentum (virality), and where conversations tend to happen on certain topics. Our minimum viable product will be a series of static visualizations of these questions with an intended reach goal of building an interactive visualizer. Overall, we want to inform people looking at our project on how information spreads, and perhaps discuss the implications of this knowledge.
+
+## Changing the World through Social Media
+With the advent of Twitter and other social media platforms, the ability for people to get informed and engage in social justice or political movements is more easily accessible (lower activation energy) - something that was not as easy only 10 years ago. We would like to visualize information spread in this way to have a formative discussion on the use of social media as a platform for justice and awareness which could have serious impacts on small local communities to larger politics. 
+
+## Project Development
+Initially, we will explore the dataset, familiarizing ourselves with the data objects and engage in exploration. Further, we will incrementally add complexity to this exploration in order to develop interesting visual insights on the data. We will start with Python as our visualizer then, time allowing, potentially move to Javscript/D3 visualizations. By mid-project we will be familiar with our dataset and have a firm picture on what visualizations we will want to create with it sketched out or roughly prototyped. All of our development plans currently hinge on the ability to get data from Twitter on Ferguson, with a back-up plan being getting data about the recent GOP Debate.
+
+## Assessing this Project
+We wish to be assessed in the ease of use (given interactive visualizations) of our project, in addition to the clarity of the story (is there a coherent story or message being presented), clarity of data presentation (are all figures legible, accessible, and appropriately labeled), and documentation/style of our code. In particular, our learning goals for this project tend towards exploring how to make good visualizations/figures of merit, and so wish to be assessed more critically on these. Our standard is: would someone who is non-technical be able to use our product effectively and understand the story; for someone who is technical, would they be able to re-create our work from our documentation.
+
+### Updated Assessment Plan (3/10)
+Over the course of this project, we have slightly shifted our goal from creating a set of visualizations that tell a story about the events in Ferguson to an investigation of what kinds of visualizations are helpful in telling these stories. As a result, we would like to be evaluated in terms of how well we analyze the merits of the types of visualizations that we have created, rathter than how *good* our visualizations are at telling stories. 
+
+
diff --git a/Reflection.md b/Reflection.md
new file mode 100644
index 0000000..4bbc469
--- /dev/null
+++ b/Reflection.md
@@ -0,0 +1,26 @@
+# Project Reflection
+
+**Sophia and Victoria**
+
+## Assessment Evidence and Interpretation
+When we set out to do this project, our project goals were
+
+*"Using data from the Twitter API, we would like to visualize how during political or social justice events information propogates through the Twitter network. In particular, we would like to look at: who is engaging, how many are engaging, how certain hashtags gain momentum (virality), and where conversations tend to happen on certain topics. Our minimum viable product will be a series of static visualizations of these questions with an intended reach goal of building an interactive visualizer. Overall, we want to inform people looking at our project on how information spreads, and perhaps discuss the implications of this knowledge."*
+
+We feel that we have started to accomplish these goals, although we did not necessarily get as far as we would have liked. (Our final writeup can be found in the `Change_The_World_Writeup` and the `ChangeTheWorld_Communites` ipython notebooks. (These files are in two different notebooks because they require, at least for some macs, different versions of the same library)  In an ideal world, our visualizations would have been interactive -- and potentially in the form of a web page rather than an Ipython notebook. That being said, we feel that we have produced some visualizations that help us understand with whom people were interacting on twitter, and have started to look into how users use hashtags to engage with certain causes. If you would like to see all of the visualizations that we created, please take a look at the other ipython notebooks in the folder. These contain code for creating all the visualizations we made of the course of this project, including those that did not make it into our final writeup. 
+
+## Changing the World
+We believe that our product has potential to change the world, albeit with some UI changes. Understanding how social change/protest happens, or is organized, over social media is important; as more and more information about social justice happens over social media like twitter. 
+
+Further, if we look at the recent political debates and how social justice groups like BlackLivesMatter are choosing to engage, there is a duality: present activism, and virtual activism. Present activism encapsulates the idea that a person is physically attending, acting, or rallying for a cause. Virtual activism is the shared support and shared knowledge for those causes online, often on social media platforms. The beauty of realtime social media sites like twitter, is the opportunity to unite these aspects of the social justice movement into a more powerful, impactful, and broader statement. Virtual activism serves as a way of organizing, sharing, and promoting causes. Communities can rally from across the world, and those that would otherwise not be exposed to certain movements now have that benefit.  
+
+In balance, there is concern that virtual activism could replace present activism - the ease of retweeting trumps that of actually attending a rally. Of the millions of tweeters, how many were presently active? This is a hot topic within social justice circles, and an extension of our project easily lends itself to mapping, measuring, and starting a conversation about the dichotomy. Ideally, virtual activism will lead to present activism, and the study of motivations, communities, and networks could only lead to more insights about how to make this a reality. 
+
+And with any social justice movement, the end goal is truly change for a community and thus for the world as people are asked to check their assumptions, and take a side. 
+
+## Learning Goals
+When we started out this project, we did not realize how large of a dataset we were dealing with. In other words, we might not have realized how ambitious our project really was. 
+
+That being said, we learned a TON about how to handle large, text-based dataset. While this was not necessarily one of our learning goals, we feel that this is something that we really appreciated learning. This dataset forced us to make decisions about what functions to use, and how to process the dataset. For example, we learned about the relative speed differences between looping over all the rows in a dataframe, using the apply function, and using a pandas built-in function such as `to_datetime`. Had we not had such an unweildy dataset, we would not have learned about how to interact with a dataframe in a speedy matter. 
+
+Additionally, we feel that, through a process of trial and error, we are starting to understand what kinds of visualizations are helpful for understanding twitter data and how users rally around a cause on twitter. Particularly relevant was a cursory exploration of node-graphs and node theory, which we started in the project, and think would be a great launching off point for someone to work on in the future.
\ No newline at end of file
diff --git a/Time_and_Location_Visualizations.ipynb b/Time_and_Location_Visualizations.ipynb
new file mode 100644
index 0000000..8e64c51
--- /dev/null
+++ b/Time_and_Location_Visualizations.ipynb
@@ -0,0 +1,1873 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Time and Location Visualizations\n",
+    "**Sophia and Victoria**\n",
+    "\n",
+    "In this notebook, we're going to explpore plotting tweets based on time and location!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Importing everthing!\n",
+    "Let's get ready to do some cool data things!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/Sophia/anaconda/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
+      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
+     ]
+    }
+   ],
+   "source": [
+    "% matplotlib inline\n",
+    "import pandas as pd\n",
+    "import json\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import time\n",
+    "from datetime import datetime\n",
+    "\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets\n",
+    "import matplotlib.cm as cm\n",
+    "\n",
+    "from matplotlib import animation\n",
+    "from IPython.display import HTML\n",
+    "from tempfile import NamedTemporaryFile\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Reading in Data\n",
+    "Here, we're using a function that we've developed to read in the data, a certain number of lines at a time. This uses a file of cleaned tweets that we have created but cannot push to github. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def ReadToDf(linesAtATime,filepath, max=-1):\n",
+    "    start = time.time()\n",
+    "    df = pd.DataFrame()\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filepath) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print \"number of tweets parsed: \", i\n",
+    "                print \"total time elapsed: \", time.time() - start\n",
+    "                df = df.append(pd.DataFrame(data=data))\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "        #Allow us to handle the last few tweets, and to truncate the data if we just want to run unit tests\n",
+    "            if (max > 0 and i >= max):\n",
+    "                break\n",
+    "        df = pd.DataFrame(data=data).append(df)\n",
+    "    #return the aggregation\n",
+    "    return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "number of tweets parsed:  100000\n",
+      "total time elapsed:  1.7647562027\n",
+      "number of tweets parsed:  200000\n",
+      "total time elapsed:  3.98646521568\n"
+     ]
+    }
+   ],
+   "source": [
+    "shooting_df = ReadToDf(100000, 'data/cleanedShootingTweets.json', 200000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>coordinates_x</th>\n",
+       "      <th>coordinates_y</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>retweet_count</th>\n",
+       "      <th>retweeted_status_id_str</th>\n",
+       "      <th>user_id_str</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_verified</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:52:55 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>501064141332029440</td>\n",
+       "      <td>3</td>\n",
+       "      <td>None</td>\n",
+       "      <td>851336634</td>\n",
+       "      <td>20mUsa</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:02 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[295988417]</td>\n",
+       "      <td>[NerdyNegress]</td>\n",
+       "      <td>501064171707170816</td>\n",
+       "      <td>10</td>\n",
+       "      <td>501064110696857600</td>\n",
+       "      <td>53158947</td>\n",
+       "      <td>MzDivah67</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:04 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[295988417]</td>\n",
+       "      <td>[NerdyNegress]</td>\n",
+       "      <td>501064180468682752</td>\n",
+       "      <td>10</td>\n",
+       "      <td>501064110696857600</td>\n",
+       "      <td>619587350</td>\n",
+       "      <td>BrookLyn1825</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>501064188211765249</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>374346913</td>\n",
+       "      <td>I_Mpower</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:07 +0000 2014</td>\n",
+       "      <td>[USNews]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>501064194309906436</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>2272978051</td>\n",
+       "      <td>Vorarlberg1</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[90296594]</td>\n",
+       "      <td>[Thatindianbruh]</td>\n",
+       "      <td>501064196642340864</td>\n",
+       "      <td>10479</td>\n",
+       "      <td>501051914218668032</td>\n",
+       "      <td>1458086762</td>\n",
+       "      <td>rachel_palomera</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, MikeBrown]</td>\n",
+       "      <td>[18989941]</td>\n",
+       "      <td>[BgRs]</td>\n",
+       "      <td>501064196931330049</td>\n",
+       "      <td>228</td>\n",
+       "      <td>501017032486178818</td>\n",
+       "      <td>278298244</td>\n",
+       "      <td>bookishshelly</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>501064197396914176</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>1112443196</td>\n",
+       "      <td>deegerwiilen</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, tcot, uniteblue, teaparty, gop]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>134</td>\n",
+       "      <td>501062167303450626</td>\n",
+       "      <td>21811025</td>\n",
+       "      <td>mmaureen7</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, CrimeButNoTime]</td>\n",
+       "      <td>[935015863]</td>\n",
+       "      <td>[bryancrumpler]</td>\n",
+       "      <td>501064198009655296</td>\n",
+       "      <td>5493</td>\n",
+       "      <td>501011628448841728</td>\n",
+       "      <td>2743004644</td>\n",
+       "      <td>collettehodson</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   coordinates_x  coordinates_y                      created_at  \\\n",
+       "0            NaN            NaN  Sun Aug 17 17:52:55 +0000 2014   \n",
+       "1            NaN            NaN  Sun Aug 17 17:53:02 +0000 2014   \n",
+       "2            NaN            NaN  Sun Aug 17 17:53:04 +0000 2014   \n",
+       "3            NaN            NaN  Sun Aug 17 17:53:06 +0000 2014   \n",
+       "4            NaN            NaN  Sun Aug 17 17:53:07 +0000 2014   \n",
+       "5            NaN            NaN  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "6            NaN            NaN  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "7            NaN            NaN  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "8            NaN            NaN  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "9            NaN            NaN  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "\n",
+       "                       entities_hashtags_text entities_user_mentions_id_str  \\\n",
+       "0                                  [Ferguson]                            []   \n",
+       "1                                  [Ferguson]                   [295988417]   \n",
+       "2                                  [Ferguson]                   [295988417]   \n",
+       "3                                          []                            []   \n",
+       "4                                    [USNews]                            []   \n",
+       "5                                  [Ferguson]                    [90296594]   \n",
+       "6                       [Ferguson, MikeBrown]                    [18989941]   \n",
+       "7                                          []                            []   \n",
+       "8  [Ferguson, tcot, uniteblue, teaparty, gop]                            []   \n",
+       "9                  [Ferguson, CrimeButNoTime]                   [935015863]   \n",
+       "\n",
+       "  entities_user_mentions_screen_name              id_str  retweet_count  \\\n",
+       "0                                 []  501064141332029440              3   \n",
+       "1                     [NerdyNegress]  501064171707170816             10   \n",
+       "2                     [NerdyNegress]  501064180468682752             10   \n",
+       "3                                 []  501064188211765249              0   \n",
+       "4                                 []  501064194309906436              0   \n",
+       "5                   [Thatindianbruh]  501064196642340864          10479   \n",
+       "6                             [BgRs]  501064196931330049            228   \n",
+       "7                                 []  501064197396914176              0   \n",
+       "8                                 []  501064197632167936            134   \n",
+       "9                    [bryancrumpler]  501064198009655296           5493   \n",
+       "\n",
+       "  retweeted_status_id_str user_id_str user_screen_name user_verified  \n",
+       "0                    None   851336634           20mUsa          True  \n",
+       "1      501064110696857600    53158947        MzDivah67         False  \n",
+       "2      501064110696857600   619587350     BrookLyn1825         False  \n",
+       "3                    None   374346913         I_Mpower         False  \n",
+       "4                    None  2272978051      Vorarlberg1         False  \n",
+       "5      501051914218668032  1458086762  rachel_palomera         False  \n",
+       "6      501017032486178818   278298244    bookishshelly         False  \n",
+       "7                    None  1112443196     deegerwiilen         False  \n",
+       "8      501062167303450626    21811025        mmaureen7         False  \n",
+       "9      501011628448841728  2743004644   collettehodson         False  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shooting_df.head(10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cleaning Data\n",
+    "This is where we're going to clean data that we've read in. The only cleaning that we need to do is that we need to convert the \"created_at\" column to a datetime object. The rest of the cleaning data is done in the script `development_scripts/clean_json_data.py`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def recodeData (dataframe):\n",
+    "    # Creating a parseable dataset    \n",
+    "    dataframe['createdDatetime'] =  pd.to_datetime(\n",
+    "        dataframe['created_at'], \n",
+    "        format = '%a %b %d %H:%M:%S +0000 %Y')\n",
+    "    dataframe['createdDatetime_day'] = dataframe['createdDatetime'].dt.day\n",
+    "    dataframe['createdDatetime_hour'] = dataframe['createdDatetime'].dt.hour"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, let's recode the dates for the shooting data and the indictment data! These opperations are done in place, so we don't actually have to return anything"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "recoding shooting dataset\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('recoding shooting dataset')\n",
+    "recodeData(shooting_df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Tweets after the Mike Brown Shooting\n",
+    "In the dataset related to the shooting, we have approximately 11 million tweets worth of data. Over the course of the first week, statements from police, from the family of Michael Brown, statements from the police officer Darren Wilson, and unrest from the streets were recorded and shared wildly across the web. To get a general understanding of the data, we are going to plot the number of tweets over time and annotate this plot with important events that happened over the course of the two weeks. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "First, we will group the tweets by minute, and then count the number of tweets that happened each minute. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#Raw numbers of tweets over time\n",
+    "shootingTweetsGroupedTime = (shooting_df\n",
+    "                                 .set_index('createdDatetime')\n",
+    "                                 .groupby([pd.TimeGrouper('Min')])\n",
+    "                                 .count()\n",
+    "                                 .reset_index())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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5WEVFwHPP6cdeK2g2oO3Z47xPNqBNmqSTJmwFrbVVN4SvqwPWrfN+X0TpwoBG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\nN+Lf05gx+QOalG5zlro5dbTHaPZSFvEK2ujRmeN0Ro1KV1NyVdDiG27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kC2PQ0Kc1NEjX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\nrkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x11230ccd0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(10,10))\n",
+    "\n",
+    "shootingTweetsGroupedTime.plot(kind='line', x='createdDatetime', y='created_at', ax=ax)\n",
+    "plt.title('Number of Tweets by Users')\n",
+    "\n",
+    "ax.set_ylabel('Count of tweets')\n",
+    "ax.set_xlabel('Date/Time')\n",
+    "\n",
+    "#Overlaying Special Events\n",
+    "#August 11, 10AM - first police department demonstration\n",
+    "#August 11, 4PM - parents ask for stop to violence\n",
+    "#August 11, 8PM - tear gas used at protest\n",
+    "#August 12, 10AM - protest in St. Louis\n",
+    "#August 12, 12PM - Al Sharpton addresses crowds\n",
+    "#August 12, 4PM - Obama makes a statement\n",
+    "#August 13, 6PM - Reporters detained\n",
+    "#August 13, 9PM - Tear gas used again, and at reporters\n",
+    "#August 14, 7AM - Antonio French released from jail\n",
+    "#August 14, 11:40AM - Obama Address\n",
+    "#August 14, 6PM - Silent Vigils, first peaceful night\n",
+    "#August 15, 8:45AM - Darren Wilson names\n",
+    "#August 15, 12:30PM - Assassination statement by family\n",
+    "#August 15 Evening - Huge amounts of protest\n",
+    "#August 16, 3PM - State of emergency issued, curfew issued\n",
+    "#August 17 - Afternoon - Federal Autopsy Ordered\n",
+    "#August 18 - 2AM - Federal Gaurd Ordered into town\n",
+    "#August 18 - 3:30PM - third Obama address\n",
+    "#August 18 - Trayvon Martin's mother published letter\n",
+    "#August 19 - 7AM - family on the Today Show\n",
+    "#August 19 - 1PM - another man is shot\n",
+    "#August 22 - 12PM - national gaurd ordered to withdraw\n",
+    "#August 23 - Online fundraisers for officer surpass that of Brown\n",
+    "#August 23 - 7PM - Obama address\n",
+    "#August 24 - 12PM - Private Viewing, Requests for no Violence\n",
+    "#August 25 - Funeral\n",
+    "\n",
+    "calendar_dates = {'FirstDemo':datetime(2014,8,11,10,0,0),\n",
+    "                 'ParentReq':datetime(2014,8,11,16,0,0),\n",
+    "                 'TearGas':datetime(2014,8,11,20,0,0),\n",
+    "                 'StLouisProtest':datetime(2014,8,12,10,0,0),\n",
+    "                 'AlSharpton':datetime(2014,8,12,12,0,0),\n",
+    "                 'Obama':datetime(2014,8,12,16,0,0),\n",
+    "                 'Reporters':datetime(2014,8,13,18,0,0),\n",
+    "                 'TearGas2':datetime(2014,8,13,21,0,0),\n",
+    "                 'AntonioFrench':datetime(2014,8,14,7,0,0),\n",
+    "                 'Obama2':datetime(2014,8,14,11,40,0),\n",
+    "                 'SilentVigils':datetime(2014,8,14,18,0,0),\n",
+    "                 'DarrenWilson':datetime(2014,8,15,8,45,0),\n",
+    "                 'CharacterAssassination':datetime(2014,8,15,12,30,0),\n",
+    "                 'StateOfEmergency':datetime(2014,8,16,15,0,0),\n",
+    "                 'FederalGaurd':datetime(2014,8,18,2,0,0),\n",
+    "                 'Obama3':datetime(2014,8,18,15,30,0),\n",
+    "                 'TodayShow':datetime(2014,8,19,7,0,0),\n",
+    "                 'AnotherShot':datetime(2014,8,19,13,0,0),\n",
+    "                 'GaurdWithdrawn':datetime(2014,8,22,12,0,0),\n",
+    "                 'Obama4':datetime(2014,8,23,19,0,0),\n",
+    "                 'Viewing':datetime(2014,8,24,12,0,0)}\n",
+    "\n",
+    "for event in calendar_dates:\n",
+    "    plt.axvline(x=calendar_dates.get(event),ymin=0, ymax=4000, linewidth=4,color='g',label=event)\n",
+    "#     plt.text(calendar_dates.get(event),600,event)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Further, a certain percentage of users have place or geoencoding available on their tweets. Spatially we can see how tweets were generated following the shooting."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "latLonPopulated = shooting_df.dropna(subset=['coordinates_x','coordinates_y'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#Note, the animation code courtesy of and adapted from http://jakevdp.github.io/blog/2013/05/12/embedding-matplotlib-animations/\n",
+    "VIDEO_TAG = \"\"\"<video controls>\n",
+    " <source src=\"data:video/x-m4v;base64,{0}\" type=\"video/mp4\">\n",
+    " Your browser does not support the video tag.\n",
+    "</video>\"\"\"\n",
+    "\n",
+    "def anim_to_html(anim):\n",
+    "    if not hasattr(anim, '_encoded_video'):\n",
+    "        with NamedTemporaryFile(suffix='.mp4') as f:\n",
+    "            anim.save(f.name, fps=20, extra_args=['-vcodec', 'libx264', '-pix_fmt', 'yuv420p'])\n",
+    "            video = open(f.name, \"rb\").read()\n",
+    "        anim._encoded_video = video.encode(\"base64\")\n",
+    "    \n",
+    "    return VIDEO_TAG.format(anim._encoded_video)\n",
+    "\n",
+    "def display_animation(anim):\n",
+    "    plt.close(anim._fig)\n",
+    "    return HTML(anim_to_html(anim))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
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+       "\" type=\"video/mp4\">\n",
+       " Your browser does not support the video tag.\n",
+       "</video>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# First set up the figure, the axis, and the plot element we want to animate\n",
+    "fig = plt.figure(figsize=(10,10))\n",
+    "ax = plt.axes(xlim=(-180, 180), ylim=(-75, 75))\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "scat, = plt.plot([], [],'o')\n",
+    "\n",
+    "# initialization function: plot the background of each frame\n",
+    "def init():\n",
+    "    scat.set_data([], [])\n",
+    "    return scat,\n",
+    "\n",
+    "# animation function.  This is called sequentially by the animator\n",
+    "def animate(i):\n",
+    "    day = round(i/24) + 17\n",
+    "    hour = i - (day-17)*24\n",
+    "    subset = []\n",
+    "    subset = latLonPopulated[\n",
+    "        (latLonPopulated['createdDatetime_day'] == day) & \n",
+    "        (latLonPopulated['createdDatetime_hour'] == hour)]\n",
+    "\n",
+    "    scat.set_data(subset.coordinates_x,subset.coordinates_y)\n",
+    "    \n",
+    "    return scat,\n",
+    "\n",
+    "# animation.Animation._repr_html_ = anim_to_html #this yields a depreciation warning, heads up\n",
+    "# call the animator.  blit=True means only re-draw the parts that have changed.\n",
+    "anim = animation.FuncAnimation(fig, animate, frames=336, interval=5000, blit=True)\n",
+    "\n",
+    "# call our new function to display the animation\n",
+    "display_animation(anim)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And over all time, statically, this looks like:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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f5TPi5+dHkpKSZGZmRgsXLqRTp05RRkZGmwPwfv360cqVK+nly5ekoaFBLi4uVFRU1CGD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\n8m9ppwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x110849c90>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#the cartopy map, going simple outline for now\n",
+    "plt.figure(figsize=(15,15))\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "\n",
+    "#straight-up coordinate data which we just finished recoding\n",
+    "plt.scatter(latLonPopulated.coordinates_x,latLonPopulated.coordinates_y,color='r')\n",
+    "plt.axis([-180, 180, -75, 75])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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ZsJFJU37l+k1PIiMjATA3N8c+S2YcHRyY8/s0ShQv9sZ+7j94yI7de1ixZh06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\nHB3p066FMukVicXICIHKwwspmzfC77ElcmBpymYyIT/xRRgMCZ2Qnx0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SWnEabFTKOWoN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\nbBAiOv6bT5YkSRL69OqpcTSGSyXyv6Wq6lBVHTmzZ9M6JP38uB2hEwwZn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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x114b42b50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#as a hexbin instead\n",
+    "#the cartopy map, going simple outline for now\n",
+    "plt.figure(figsize=(15,5))\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "\n",
+    "#straight-up coordinate data which we just finished recoding\n",
+    "plt.hexbin(latLonPopulated.coordinates_x,latLonPopulated.coordinates_y,cmap=cm.Reds, bins='log') #add bins='log' to see a log based chart\n",
+    "cb = plt.colorbar()\n",
+    "cb.set_label('counts')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So, we can see that most of the tweets are coming from the US, expecially the East coast and Ferguson."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/Verified_Users.ipynb b/Verified_Users.ipynb
new file mode 100644
index 0000000..59de14f
--- /dev/null
+++ b/Verified_Users.ipynb
@@ -0,0 +1,2348 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Verified Users - Do Celebs and News Outlets Go Measurably Viral?\n",
+    "This notebook provides the basis for developing spatial representations of a variety of interesting data that is presented in the Ferguson Twitter dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/Sophia/anaconda/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
+      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "% matplotlib inline\n",
+    "import json\n",
+    "import time\n",
+    "import pandas as pd\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets\n",
+    "import matplotlib.cm as cm\n",
+    "import datetime"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's begin with the data. We have two datasets. The first is data from the two weeks following the initial shooting. The second is data from the two weeks following the indictment. Twitter has provided an extensive amount of data for us, and we have developed a cleaning mechanism which can be observed in a seperate script. The data is placed in a data frame:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def ReadAndAggregate(linesAtATime,filepath, aggregationFunction):\n",
+    "    i = 0\n",
+    "    data = [] \n",
+    "    \n",
+    "    #Open and read in the file\n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            jsonline = json.loads(tweet)\n",
+    "            data.append(jsonline)\n",
+    "            #aggregate once we've read in the appropriate number of liens\n",
+    "            if (i % linesAtATime == 0):\n",
+    "                print i\n",
+    "                df = pd.DataFrame(data=data)\n",
+    "                #First time running through\n",
+    "                if (i == linesAtATime):\n",
+    "                    agg = aggregationFunction(df)\n",
+    "                else:\n",
+    "                    agg = aggregationFunction(df, agg)\n",
+    "                #reset the data\n",
+    "                data = []\n",
+    "        #Handle the last few tweets\n",
+    "        df = pd.DataFrame(data=data)\n",
+    "        agg = aggregationFunction(df, agg)\n",
+    "    #return the aggregation\n",
+    "    return agg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def getDateInfo (df, hashtagsDataFrame=pd.DataFrame()):\n",
+    "    \n",
+    "    #time based recodes\n",
+    "    df['DoW'] = df['created_at'].apply(lambda x: str(x)[0:3:])\n",
+    "    df['Month'] = df['created_at'].apply(lambda x: str(x)[4:7:])\n",
+    "    df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])\n",
+    "    df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))\n",
+    "    df['Minute'] = df['created_at'].apply(lambda x: int(str(x)[14:16:]))\n",
+    "\n",
+    "    \n",
+    "    hashtagsDataFrame = hashtagsDataFrame.append(df)\n",
+    "\n",
+    "    return hashtagsDataFrame"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100000\n",
+      "200000\n",
+      "300000\n",
+      "400000\n",
+      "500000\n",
+      "600000\n",
+      "700000\n",
+      "800000\n",
+      "900000\n",
+      "1000000\n",
+      "1100000"
+     ]
+    }
+   ],
+   "source": [
+    "filename='./data/cleanedShootingTweets.json'\n",
+    "data = ReadAndAggregate(100000,filename, getDateInfo)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>contributors</th>\n",
+       "      <th>coordinates</th>\n",
+       "      <th>created_at</th>\n",
+       "      <th>entities_hashtags_text</th>\n",
+       "      <th>entities_user_mentions_id_str</th>\n",
+       "      <th>entities_user_mentions_screen_name</th>\n",
+       "      <th>favorite_count</th>\n",
+       "      <th>geo</th>\n",
+       "      <th>id_str</th>\n",
+       "      <th>in_reply_to_status_id_str</th>\n",
+       "      <th>...</th>\n",
+       "      <th>user_location</th>\n",
+       "      <th>user_screen_name</th>\n",
+       "      <th>user_time_zone</th>\n",
+       "      <th>user_utc_offset</th>\n",
+       "      <th>user_verified</th>\n",
+       "      <th>DoW</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>DoM</th>\n",
+       "      <th>Hour</th>\n",
+       "      <th>Minute</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:52:55 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064141332029440</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Estados Unidos</td>\n",
+       "      <td>20mUsa</td>\n",
+       "      <td>Athens</td>\n",
+       "      <td>7200</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>52</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:02 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[295988417]</td>\n",
+       "      <td>[NerdyNegress]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064171707170816</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>None Of Your Business</td>\n",
+       "      <td>MzDivah67</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:04 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[295988417]</td>\n",
+       "      <td>[NerdyNegress]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064180468682752</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>BrookLyn1825</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:06 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064188211765249</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Virginia Beach</td>\n",
+       "      <td>I_Mpower</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:07 +0000 2014</td>\n",
+       "      <td>[USNews]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064194309906436</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Vorarlberg1</td>\n",
+       "      <td>Vienna</td>\n",
+       "      <td>3600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[90296594]</td>\n",
+       "      <td>[Thatindianbruh]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064196642340864</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>rachel_palomera</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, MikeBrown]</td>\n",
+       "      <td>[18989941]</td>\n",
+       "      <td>[BgRs]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064196931330049</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>California</td>\n",
+       "      <td>bookishshelly</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064197396914176</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>deegerwiilen</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, tcot, uniteblue, teaparty, gop]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064197632167936</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>mmaureen7</td>\n",
+       "      <td>Newfoundland</td>\n",
+       "      <td>-12600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson, CrimeButNoTime]</td>\n",
+       "      <td>[935015863]</td>\n",
+       "      <td>[bryancrumpler]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064198009655296</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>London</td>\n",
+       "      <td>collettehodson</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[3385611074]</td>\n",
+       "      <td>[ImNotTwitFamous]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064198059597824</td>\n",
+       "      <td>499992352505610240</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>offlyniceteam</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:08 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[93963456, 573764891]</td>\n",
+       "      <td>[trymainelee, OTMBrooke]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064198513000450</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>New York</td>\n",
+       "      <td>carminemac</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064198973960192</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>SlavinOleg</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>-25200</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson, PoliceBrutality]</td>\n",
+       "      <td>[755113]</td>\n",
+       "      <td>[ShaunKing]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064199142117378</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Free2Pursue</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[20864257]</td>\n",
+       "      <td>[chrisalexander_]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064200035516416</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>summer polar vortex</td>\n",
+       "      <td>SadieODoyle</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064200186118145</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Liberal progessive in Austin,</td>\n",
+       "      <td>Ssragona</td>\n",
+       "      <td>Central Time (US &amp; Canada)</td>\n",
+       "      <td>-21600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064200316125184</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Schweizer_Kotau</td>\n",
+       "      <td>Amsterdam</td>\n",
+       "      <td>3600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[325076723]</td>\n",
+       "      <td>[zellieimani]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064201041743872</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>detroit</td>\n",
+       "      <td>bonxvivant</td>\n",
+       "      <td>Central Time (US &amp; Canada)</td>\n",
+       "      <td>-21600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[217663500]</td>\n",
+       "      <td>[locoernesto]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064201251880961</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Somewhere w/ my sister Mooder</td>\n",
+       "      <td>mickysowavy</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[279390084]</td>\n",
+       "      <td>[YourAnonNews]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064201256071168</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Enigmatic Cloud 9</td>\n",
+       "      <td>Katyria90</td>\n",
+       "      <td>Atlantic Time (Canada)</td>\n",
+       "      <td>-14400</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[MikeBrown, Ferguson]</td>\n",
+       "      <td>[97273575, 369507958]</td>\n",
+       "      <td>[Clarknt67, wethepeople]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064201503113216</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Little Rock, AR</td>\n",
+       "      <td>bennharr</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[3385611074]</td>\n",
+       "      <td>[ImNotTwitFamous]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064202245521409</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>king gio</td>\n",
+       "      <td>Jaela_mb</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>-25200</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[6273552]</td>\n",
+       "      <td>[MCHammer]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064202295848960</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Blackberryccr</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[1381926373]</td>\n",
+       "      <td>[YourAnonGlobal]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064202380115971</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>bebird</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064202794971136</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>SlavinOleg</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>-25200</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:09 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[1917731, 369534928]</td>\n",
+       "      <td>[thehill, PeterSullivan4]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064202904403970</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Columbus, Ohio</td>\n",
+       "      <td>DrJLMooreIII</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:10 +0000 2014</td>\n",
+       "      <td>[Ferguson, StandWithFerguson, HandsUpDontShoot...</td>\n",
+       "      <td>[2984310527]</td>\n",
+       "      <td>[queerdorable]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064203135102977</td>\n",
+       "      <td>501063920187346945</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>kavn</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:10 +0000 2014</td>\n",
+       "      <td>[FergusonShooting, Ferguson]</td>\n",
+       "      <td>[237606548]</td>\n",
+       "      <td>[3ChicsPolitico]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064203508412416</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Star City....till I wreck it</td>\n",
+       "      <td>ArrogantDemon</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:10 +0000 2014</td>\n",
+       "      <td>[Ferguson, BLACKMEDIA, TWIBnation]</td>\n",
+       "      <td>[1716581]</td>\n",
+       "      <td>[elonjames]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064204288540672</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>MHT &amp; NYC</td>\n",
+       "      <td>profbrady</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Sun Aug 17 17:53:10 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>501064204661850113</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>ahhthatswhy</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Sun</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>17</td>\n",
+       "      <td>17</td>\n",
+       "      <td>53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50687</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321707634688001</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>PattoFaustiano</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50688</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321707655639040</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>United States</td>\n",
+       "      <td>nanopatents</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50689</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321707676602368</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Orgelmir</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50690</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321707966025728</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Virgo Supercluster</td>\n",
+       "      <td>DeadPrecariat</td>\n",
+       "      <td>Quito</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50691</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708007559168</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Nakuru</td>\n",
+       "      <td>Swamkidd</td>\n",
+       "      <td>Quito</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50692</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[309379296]</td>\n",
+       "      <td>[LuhhNate]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708322131968</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Hilltop</td>\n",
+       "      <td>PakistanBre</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50693</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708322553856</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>JoeOKerr</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50694</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708456747008</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Syracuse, NY</td>\n",
+       "      <td>YourBlackWorld</td>\n",
+       "      <td>Central Time (US &amp; Canada)</td>\n",
+       "      <td>-21600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50695</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708465135616</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>KultureKritic</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50696</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708465143808</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>AelitaQueen</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50697</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708544847872</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>Reason4Rhymes</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50698</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708645498880</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>beforeitsnews</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50699</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:02 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>5</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321708900970496</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Wilkes-Barre, PA</td>\n",
+       "      <td>rcooley123</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50700</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:03 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[2320513861]</td>\n",
+       "      <td>[suddeneternity]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321710717091841</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Lethbridge AB</td>\n",
+       "      <td>UncleRee1</td>\n",
+       "      <td>Mountain Time (US &amp; Canada)</td>\n",
+       "      <td>-25200</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50701</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:03 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[2471925444]</td>\n",
+       "      <td>[YABOYYDEQUAN]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321712201859073</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Columbus, GA</td>\n",
+       "      <td>_TaeKemp</td>\n",
+       "      <td>Arizona</td>\n",
+       "      <td>-25200</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50702</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:03 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[156743986, 15808218]</td>\n",
+       "      <td>[_esaliba, kgosztola]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321712386416640</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Bellingham, WA</td>\n",
+       "      <td>profjournalista</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50703</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:03 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321713431207937</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Brooklyn, NY</td>\n",
+       "      <td>LiveAndAscend</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50704</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:04 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[376109186]</td>\n",
+       "      <td>[occbaystreet]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321714236502017</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Buffalo Valley,  Tennessee</td>\n",
+       "      <td>blaha_b</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50705</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:04 +0000 2014</td>\n",
+       "      <td>[ferguson]</td>\n",
+       "      <td>[534675241]</td>\n",
+       "      <td>[Dreamdefenders]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321715574079488</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Singapore</td>\n",
+       "      <td>pjan_stellar</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50706</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:04 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[1963823209]</td>\n",
+       "      <td>[PeopIe]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321716652433408</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>ma</td>\n",
+       "      <td>a_filipiak</td>\n",
+       "      <td>Atlantic Time (Canada)</td>\n",
+       "      <td>-14400</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50707</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[HandsUpDontShoot]</td>\n",
+       "      <td>[69326792, 551947957, 373738053]</td>\n",
+       "      <td>[MaryMurrayNBC, BonBonBreak, momsnewstage]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321718443380737</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>A QUIRKY YANKEE IN THE SOUTH</td>\n",
+       "      <td>SheDoesArtWow</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50708</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[FergusonShooting, Ferguson, FergusonRiot]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321718443388928</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Florida Wig Stand</td>\n",
+       "      <td>MsBrownsWig</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50709</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[61907338]</td>\n",
+       "      <td>[joenewsman]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321718950903808</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Tryna get to a beach ✨</td>\n",
+       "      <td>hoochieuche</td>\n",
+       "      <td>Pacific Time (US &amp; Canada)</td>\n",
+       "      <td>-28800</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50710</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[FERGUSON]</td>\n",
+       "      <td>[47856658]</td>\n",
+       "      <td>[hotwata]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321718971469824</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Elberton , Ga</td>\n",
+       "      <td>Ducedoh</td>\n",
+       "      <td>Eastern Time (US &amp; Canada)</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50711</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[1367531]</td>\n",
+       "      <td>[FoxNews]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321719257079808</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>America the Beautiful, Oregon</td>\n",
+       "      <td>Cate_Tweeting</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50712</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321719429050368</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Charleston, WV</td>\n",
+       "      <td>TheMaseMan</td>\n",
+       "      <td>Atlantic Time (Canada)</td>\n",
+       "      <td>-14400</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50713</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[Ferguson]</td>\n",
+       "      <td>[496679549]</td>\n",
+       "      <td>[TheJarell]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321719734841344</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>getoffmylawn80</td>\n",
+       "      <td>None</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50714</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[11740172]</td>\n",
+       "      <td>[charlesjaco1]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321719999483904</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>bitcoinmom</td>\n",
+       "      <td>Central Time (US &amp; Canada)</td>\n",
+       "      <td>-21600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50715</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321720892854273</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>syracuse</td>\n",
+       "      <td>drboycewatkins1</td>\n",
+       "      <td>Central Time (US &amp; Canada)</td>\n",
+       "      <td>-21600</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50716</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>Thu Aug 21 05:10:05 +0000 2014</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>[]</td>\n",
+       "      <td>0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>502321721085812736</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td></td>\n",
+       "      <td>yourblackgossip</td>\n",
+       "      <td>Quito</td>\n",
+       "      <td>-18000</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Thu</td>\n",
+       "      <td>Aug</td>\n",
+       "      <td>21</td>\n",
+       "      <td>5</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3950717 rows × 37 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      contributors coordinates                      created_at  \\\n",
+       "0             None        None  Sun Aug 17 17:52:55 +0000 2014   \n",
+       "1             None        None  Sun Aug 17 17:53:02 +0000 2014   \n",
+       "2             None        None  Sun Aug 17 17:53:04 +0000 2014   \n",
+       "3             None        None  Sun Aug 17 17:53:06 +0000 2014   \n",
+       "4             None        None  Sun Aug 17 17:53:07 +0000 2014   \n",
+       "5             None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "6             None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "7             None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "8             None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "9             None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "10            None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "11            None        None  Sun Aug 17 17:53:08 +0000 2014   \n",
+       "12            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "13            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "14            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "15            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "16            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "17            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "18            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "19            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "20            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "21            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "22            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "23            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "24            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "25            None        None  Sun Aug 17 17:53:09 +0000 2014   \n",
+       "26            None        None  Sun Aug 17 17:53:10 +0000 2014   \n",
+       "27            None        None  Sun Aug 17 17:53:10 +0000 2014   \n",
+       "28            None        None  Sun Aug 17 17:53:10 +0000 2014   \n",
+       "29            None        None  Sun Aug 17 17:53:10 +0000 2014   \n",
+       "...            ...         ...                             ...   \n",
+       "50687         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50688         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50689         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50690         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50691         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50692         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50693         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50694         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50695         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50696         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50697         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50698         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50699         None        None  Thu Aug 21 05:10:02 +0000 2014   \n",
+       "50700         None        None  Thu Aug 21 05:10:03 +0000 2014   \n",
+       "50701         None        None  Thu Aug 21 05:10:03 +0000 2014   \n",
+       "50702         None        None  Thu Aug 21 05:10:03 +0000 2014   \n",
+       "50703         None        None  Thu Aug 21 05:10:03 +0000 2014   \n",
+       "50704         None        None  Thu Aug 21 05:10:04 +0000 2014   \n",
+       "50705         None        None  Thu Aug 21 05:10:04 +0000 2014   \n",
+       "50706         None        None  Thu Aug 21 05:10:04 +0000 2014   \n",
+       "50707         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50708         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50709         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50710         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50711         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50712         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50713         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50714         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50715         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "50716         None        None  Thu Aug 21 05:10:05 +0000 2014   \n",
+       "\n",
+       "                                  entities_hashtags_text  \\\n",
+       "0                                             [Ferguson]   \n",
+       "1                                             [Ferguson]   \n",
+       "2                                             [Ferguson]   \n",
+       "3                                                     []   \n",
+       "4                                               [USNews]   \n",
+       "5                                             [Ferguson]   \n",
+       "6                                  [Ferguson, MikeBrown]   \n",
+       "7                                                     []   \n",
+       "8             [Ferguson, tcot, uniteblue, teaparty, gop]   \n",
+       "9                             [Ferguson, CrimeButNoTime]   \n",
+       "10                                            [Ferguson]   \n",
+       "11                                                    []   \n",
+       "12                                                    []   \n",
+       "13                           [Ferguson, PoliceBrutality]   \n",
+       "14                                            [Ferguson]   \n",
+       "15                                                    []   \n",
+       "16                                                    []   \n",
+       "17                                            [Ferguson]   \n",
+       "18                                            [Ferguson]   \n",
+       "19                                            [Ferguson]   \n",
+       "20                                 [MikeBrown, Ferguson]   \n",
+       "21                                            [Ferguson]   \n",
+       "22                                            [Ferguson]   \n",
+       "23                                            [Ferguson]   \n",
+       "24                                                    []   \n",
+       "25                                                    []   \n",
+       "26     [Ferguson, StandWithFerguson, HandsUpDontShoot...   \n",
+       "27                          [FergusonShooting, Ferguson]   \n",
+       "28                    [Ferguson, BLACKMEDIA, TWIBnation]   \n",
+       "29                                                    []   \n",
+       "...                                                  ...   \n",
+       "50687                                                 []   \n",
+       "50688                                                 []   \n",
+       "50689                                                 []   \n",
+       "50690                                         [Ferguson]   \n",
+       "50691                                                 []   \n",
+       "50692                                                 []   \n",
+       "50693                                                 []   \n",
+       "50694                                                 []   \n",
+       "50695                                                 []   \n",
+       "50696                                                 []   \n",
+       "50697                                                 []   \n",
+       "50698                                                 []   \n",
+       "50699                                                 []   \n",
+       "50700                                         [Ferguson]   \n",
+       "50701                                         [Ferguson]   \n",
+       "50702                                         [Ferguson]   \n",
+       "50703                                                 []   \n",
+       "50704                                         [Ferguson]   \n",
+       "50705                                         [ferguson]   \n",
+       "50706                                         [Ferguson]   \n",
+       "50707                                 [HandsUpDontShoot]   \n",
+       "50708         [FergusonShooting, Ferguson, FergusonRiot]   \n",
+       "50709                                         [Ferguson]   \n",
+       "50710                                         [FERGUSON]   \n",
+       "50711                                                 []   \n",
+       "50712                                                 []   \n",
+       "50713                                         [Ferguson]   \n",
+       "50714                                                 []   \n",
+       "50715                                                 []   \n",
+       "50716                                                 []   \n",
+       "\n",
+       "          entities_user_mentions_id_str  \\\n",
+       "0                                    []   \n",
+       "1                           [295988417]   \n",
+       "2                           [295988417]   \n",
+       "3                                    []   \n",
+       "4                                    []   \n",
+       "5                            [90296594]   \n",
+       "6                            [18989941]   \n",
+       "7                                    []   \n",
+       "8                                    []   \n",
+       "9                           [935015863]   \n",
+       "10                         [3385611074]   \n",
+       "11                [93963456, 573764891]   \n",
+       "12                                   []   \n",
+       "13                             [755113]   \n",
+       "14                           [20864257]   \n",
+       "15                                   []   \n",
+       "16                                   []   \n",
+       "17                          [325076723]   \n",
+       "18                          [217663500]   \n",
+       "19                          [279390084]   \n",
+       "20                [97273575, 369507958]   \n",
+       "21                         [3385611074]   \n",
+       "22                            [6273552]   \n",
+       "23                         [1381926373]   \n",
+       "24                                   []   \n",
+       "25                 [1917731, 369534928]   \n",
+       "26                         [2984310527]   \n",
+       "27                          [237606548]   \n",
+       "28                            [1716581]   \n",
+       "29                                   []   \n",
+       "...                                 ...   \n",
+       "50687                                []   \n",
+       "50688                                []   \n",
+       "50689                                []   \n",
+       "50690                                []   \n",
+       "50691                                []   \n",
+       "50692                       [309379296]   \n",
+       "50693                                []   \n",
+       "50694                                []   \n",
+       "50695                                []   \n",
+       "50696                                []   \n",
+       "50697                                []   \n",
+       "50698                                []   \n",
+       "50699                                []   \n",
+       "50700                      [2320513861]   \n",
+       "50701                      [2471925444]   \n",
+       "50702             [156743986, 15808218]   \n",
+       "50703                                []   \n",
+       "50704                       [376109186]   \n",
+       "50705                       [534675241]   \n",
+       "50706                      [1963823209]   \n",
+       "50707  [69326792, 551947957, 373738053]   \n",
+       "50708                                []   \n",
+       "50709                        [61907338]   \n",
+       "50710                        [47856658]   \n",
+       "50711                         [1367531]   \n",
+       "50712                                []   \n",
+       "50713                       [496679549]   \n",
+       "50714                        [11740172]   \n",
+       "50715                                []   \n",
+       "50716                                []   \n",
+       "\n",
+       "               entities_user_mentions_screen_name  favorite_count   geo  \\\n",
+       "0                                              []               0  None   \n",
+       "1                                  [NerdyNegress]               0  None   \n",
+       "2                                  [NerdyNegress]               0  None   \n",
+       "3                                              []               0  None   \n",
+       "4                                              []               0  None   \n",
+       "5                                [Thatindianbruh]               0  None   \n",
+       "6                                          [BgRs]               0  None   \n",
+       "7                                              []               0  None   \n",
+       "8                                              []               0  None   \n",
+       "9                                 [bryancrumpler]               0  None   \n",
+       "10                              [ImNotTwitFamous]               0  None   \n",
+       "11                       [trymainelee, OTMBrooke]               0  None   \n",
+       "12                                             []               0  None   \n",
+       "13                                    [ShaunKing]               0  None   \n",
+       "14                              [chrisalexander_]               0  None   \n",
+       "15                                             []               0  None   \n",
+       "16                                             []               0  None   \n",
+       "17                                  [zellieimani]               0  None   \n",
+       "18                                  [locoernesto]               0  None   \n",
+       "19                                 [YourAnonNews]               0  None   \n",
+       "20                       [Clarknt67, wethepeople]               0  None   \n",
+       "21                              [ImNotTwitFamous]               0  None   \n",
+       "22                                     [MCHammer]               0  None   \n",
+       "23                               [YourAnonGlobal]               0  None   \n",
+       "24                                             []               0  None   \n",
+       "25                      [thehill, PeterSullivan4]               0  None   \n",
+       "26                                 [queerdorable]               1  None   \n",
+       "27                               [3ChicsPolitico]               0  None   \n",
+       "28                                    [elonjames]               0  None   \n",
+       "29                                             []               0  None   \n",
+       "...                                           ...             ...   ...   \n",
+       "50687                                          []               0  None   \n",
+       "50688                                          []               0  None   \n",
+       "50689                                          []               0  None   \n",
+       "50690                                          []               0  None   \n",
+       "50691                                          []               0  None   \n",
+       "50692                                  [LuhhNate]               0  None   \n",
+       "50693                                          []               0  None   \n",
+       "50694                                          []               1  None   \n",
+       "50695                                          []               0  None   \n",
+       "50696                                          []               0  None   \n",
+       "50697                                          []               0  None   \n",
+       "50698                                          []               1  None   \n",
+       "50699                                          []               5  None   \n",
+       "50700                            [suddeneternity]               0  None   \n",
+       "50701                              [YABOYYDEQUAN]               0  None   \n",
+       "50702                       [_esaliba, kgosztola]               0  None   \n",
+       "50703                                          []               0  None   \n",
+       "50704                              [occbaystreet]               0  None   \n",
+       "50705                            [Dreamdefenders]               0  None   \n",
+       "50706                                    [PeopIe]               0  None   \n",
+       "50707  [MaryMurrayNBC, BonBonBreak, momsnewstage]               0  None   \n",
+       "50708                                          []               0  None   \n",
+       "50709                                [joenewsman]               0  None   \n",
+       "50710                                   [hotwata]               0  None   \n",
+       "50711                                   [FoxNews]               0  None   \n",
+       "50712                                          []               1  None   \n",
+       "50713                                 [TheJarell]               0  None   \n",
+       "50714                              [charlesjaco1]               0  None   \n",
+       "50715                                          []               0  None   \n",
+       "50716                                          []               0  None   \n",
+       "\n",
+       "                   id_str in_reply_to_status_id_str  ...    \\\n",
+       "0      501064141332029440                      None  ...     \n",
+       "1      501064171707170816                      None  ...     \n",
+       "2      501064180468682752                      None  ...     \n",
+       "3      501064188211765249                      None  ...     \n",
+       "4      501064194309906436                      None  ...     \n",
+       "5      501064196642340864                      None  ...     \n",
+       "6      501064196931330049                      None  ...     \n",
+       "7      501064197396914176                      None  ...     \n",
+       "8      501064197632167936                      None  ...     \n",
+       "9      501064198009655296                      None  ...     \n",
+       "10     501064198059597824        499992352505610240  ...     \n",
+       "11     501064198513000450                      None  ...     \n",
+       "12     501064198973960192                      None  ...     \n",
+       "13     501064199142117378                      None  ...     \n",
+       "14     501064200035516416                      None  ...     \n",
+       "15     501064200186118145                      None  ...     \n",
+       "16     501064200316125184                      None  ...     \n",
+       "17     501064201041743872                      None  ...     \n",
+       "18     501064201251880961                      None  ...     \n",
+       "19     501064201256071168                      None  ...     \n",
+       "20     501064201503113216                      None  ...     \n",
+       "21     501064202245521409                      None  ...     \n",
+       "22     501064202295848960                      None  ...     \n",
+       "23     501064202380115971                      None  ...     \n",
+       "24     501064202794971136                      None  ...     \n",
+       "25     501064202904403970                      None  ...     \n",
+       "26     501064203135102977        501063920187346945  ...     \n",
+       "27     501064203508412416                      None  ...     \n",
+       "28     501064204288540672                      None  ...     \n",
+       "29     501064204661850113                      None  ...     \n",
+       "...                   ...                       ...  ...     \n",
+       "50687  502321707634688001                      None  ...     \n",
+       "50688  502321707655639040                      None  ...     \n",
+       "50689  502321707676602368                      None  ...     \n",
+       "50690  502321707966025728                      None  ...     \n",
+       "50691  502321708007559168                      None  ...     \n",
+       "50692  502321708322131968                      None  ...     \n",
+       "50693  502321708322553856                      None  ...     \n",
+       "50694  502321708456747008                      None  ...     \n",
+       "50695  502321708465135616                      None  ...     \n",
+       "50696  502321708465143808                      None  ...     \n",
+       "50697  502321708544847872                      None  ...     \n",
+       "50698  502321708645498880                      None  ...     \n",
+       "50699  502321708900970496                      None  ...     \n",
+       "50700  502321710717091841                      None  ...     \n",
+       "50701  502321712201859073                      None  ...     \n",
+       "50702  502321712386416640                      None  ...     \n",
+       "50703  502321713431207937                      None  ...     \n",
+       "50704  502321714236502017                      None  ...     \n",
+       "50705  502321715574079488                      None  ...     \n",
+       "50706  502321716652433408                      None  ...     \n",
+       "50707  502321718443380737                      None  ...     \n",
+       "50708  502321718443388928                      None  ...     \n",
+       "50709  502321718950903808                      None  ...     \n",
+       "50710  502321718971469824                      None  ...     \n",
+       "50711  502321719257079808                      None  ...     \n",
+       "50712  502321719429050368                      None  ...     \n",
+       "50713  502321719734841344                      None  ...     \n",
+       "50714  502321719999483904                      None  ...     \n",
+       "50715  502321720892854273                      None  ...     \n",
+       "50716  502321721085812736                      None  ...     \n",
+       "\n",
+       "                        user_location user_screen_name  \\\n",
+       "0                      Estados Unidos           20mUsa   \n",
+       "1              None Of Your Business         MzDivah67   \n",
+       "2                                         BrookLyn1825   \n",
+       "3                      Virginia Beach         I_Mpower   \n",
+       "4                                          Vorarlberg1   \n",
+       "5                                      rachel_palomera   \n",
+       "6                          California    bookishshelly   \n",
+       "7                                         deegerwiilen   \n",
+       "8                                            mmaureen7   \n",
+       "9                             London    collettehodson   \n",
+       "10                                       offlyniceteam   \n",
+       "11                           New York       carminemac   \n",
+       "12                                          SlavinOleg   \n",
+       "13                                         Free2Pursue   \n",
+       "14                summer polar vortex      SadieODoyle   \n",
+       "15     Liberal progessive in Austin,          Ssragona   \n",
+       "16                                     Schweizer_Kotau   \n",
+       "17                           detroit        bonxvivant   \n",
+       "18      Somewhere w/ my sister Mooder      mickysowavy   \n",
+       "19                  Enigmatic Cloud 9        Katyria90   \n",
+       "20                    Little Rock, AR         bennharr   \n",
+       "21                          king gio          Jaela_mb   \n",
+       "22                                       Blackberryccr   \n",
+       "23                                              bebird   \n",
+       "24                                          SlavinOleg   \n",
+       "25                     Columbus, Ohio     DrJLMooreIII   \n",
+       "26                                                kavn   \n",
+       "27       Star City....till I wreck it    ArrogantDemon   \n",
+       "28                          MHT & NYC        profbrady   \n",
+       "29                                         ahhthatswhy   \n",
+       "...                               ...              ...   \n",
+       "50687                                   PattoFaustiano   \n",
+       "50688                   United States      nanopatents   \n",
+       "50689                                         Orgelmir   \n",
+       "50690              Virgo Supercluster    DeadPrecariat   \n",
+       "50691                          Nakuru         Swamkidd   \n",
+       "50692                         Hilltop      PakistanBre   \n",
+       "50693                                         JoeOKerr   \n",
+       "50694                    Syracuse, NY   YourBlackWorld   \n",
+       "50695                                    KultureKritic   \n",
+       "50696                                      AelitaQueen   \n",
+       "50697                                    Reason4Rhymes   \n",
+       "50698                                    beforeitsnews   \n",
+       "50699                Wilkes-Barre, PA       rcooley123   \n",
+       "50700                   Lethbridge AB        UncleRee1   \n",
+       "50701                    Columbus, GA         _TaeKemp   \n",
+       "50702                  Bellingham, WA  profjournalista   \n",
+       "50703                    Brooklyn, NY    LiveAndAscend   \n",
+       "50704      Buffalo Valley,  Tennessee          blaha_b   \n",
+       "50705                       Singapore     pjan_stellar   \n",
+       "50706                              ma       a_filipiak   \n",
+       "50707    A QUIRKY YANKEE IN THE SOUTH    SheDoesArtWow   \n",
+       "50708               Florida Wig Stand      MsBrownsWig   \n",
+       "50709          Tryna get to a beach ✨      hoochieuche   \n",
+       "50710                   Elberton , Ga          Ducedoh   \n",
+       "50711   America the Beautiful, Oregon    Cate_Tweeting   \n",
+       "50712                  Charleston, WV       TheMaseMan   \n",
+       "50713                                   getoffmylawn80   \n",
+       "50714                                       bitcoinmom   \n",
+       "50715                        syracuse  drboycewatkins1   \n",
+       "50716                                  yourblackgossip   \n",
+       "\n",
+       "                    user_time_zone user_utc_offset  user_verified  DoW Month  \\\n",
+       "0                           Athens            7200           True  Sun   Aug   \n",
+       "1       Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "2       Pacific Time (US & Canada)          -28800          False  Sun   Aug   \n",
+       "3       Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "4                           Vienna            3600          False  Sun   Aug   \n",
+       "5                             None             NaN          False  Sun   Aug   \n",
+       "6       Pacific Time (US & Canada)          -28800          False  Sun   Aug   \n",
+       "7                             None             NaN          False  Sun   Aug   \n",
+       "8                     Newfoundland          -12600          False  Sun   Aug   \n",
+       "9                             None             NaN          False  Sun   Aug   \n",
+       "10                            None             NaN          False  Sun   Aug   \n",
+       "11      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "12                         Arizona          -25200          False  Sun   Aug   \n",
+       "13                            None             NaN          False  Sun   Aug   \n",
+       "14                            None             NaN          False  Sun   Aug   \n",
+       "15      Central Time (US & Canada)          -21600          False  Sun   Aug   \n",
+       "16                       Amsterdam            3600          False  Sun   Aug   \n",
+       "17      Central Time (US & Canada)          -21600          False  Sun   Aug   \n",
+       "18      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "19          Atlantic Time (Canada)          -14400          False  Sun   Aug   \n",
+       "20                            None             NaN          False  Sun   Aug   \n",
+       "21                         Arizona          -25200          False  Sun   Aug   \n",
+       "22                            None             NaN          False  Sun   Aug   \n",
+       "23      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "24                         Arizona          -25200          False  Sun   Aug   \n",
+       "25      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "26      Pacific Time (US & Canada)          -28800          False  Sun   Aug   \n",
+       "27      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "28                            None             NaN          False  Sun   Aug   \n",
+       "29      Eastern Time (US & Canada)          -18000          False  Sun   Aug   \n",
+       "...                            ...             ...            ...  ...   ...   \n",
+       "50687                         None             NaN          False  Thu   Aug   \n",
+       "50688   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50689   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50690                        Quito          -18000          False  Thu   Aug   \n",
+       "50691                        Quito          -18000          False  Thu   Aug   \n",
+       "50692   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50693                         None             NaN          False  Thu   Aug   \n",
+       "50694   Central Time (US & Canada)          -21600          False  Thu   Aug   \n",
+       "50695                         None             NaN          False  Thu   Aug   \n",
+       "50696                         None             NaN          False  Thu   Aug   \n",
+       "50697                         None             NaN          False  Thu   Aug   \n",
+       "50698   Pacific Time (US & Canada)          -28800          False  Thu   Aug   \n",
+       "50699   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50700  Mountain Time (US & Canada)          -25200          False  Thu   Aug   \n",
+       "50701                      Arizona          -25200          False  Thu   Aug   \n",
+       "50702   Pacific Time (US & Canada)          -28800          False  Thu   Aug   \n",
+       "50703   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50704                         None             NaN          False  Thu   Aug   \n",
+       "50705                         None             NaN          False  Thu   Aug   \n",
+       "50706       Atlantic Time (Canada)          -14400          False  Thu   Aug   \n",
+       "50707   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50708                         None             NaN          False  Thu   Aug   \n",
+       "50709   Pacific Time (US & Canada)          -28800          False  Thu   Aug   \n",
+       "50710   Eastern Time (US & Canada)          -18000          False  Thu   Aug   \n",
+       "50711                         None             NaN          False  Thu   Aug   \n",
+       "50712       Atlantic Time (Canada)          -14400          False  Thu   Aug   \n",
+       "50713                         None             NaN          False  Thu   Aug   \n",
+       "50714   Central Time (US & Canada)          -21600          False  Thu   Aug   \n",
+       "50715   Central Time (US & Canada)          -21600          False  Thu   Aug   \n",
+       "50716                        Quito          -18000          False  Thu   Aug   \n",
+       "\n",
+       "      DoM Hour Minute  \n",
+       "0      17   17     52  \n",
+       "1      17   17     53  \n",
+       "2      17   17     53  \n",
+       "3      17   17     53  \n",
+       "4      17   17     53  \n",
+       "5      17   17     53  \n",
+       "6      17   17     53  \n",
+       "7      17   17     53  \n",
+       "8      17   17     53  \n",
+       "9      17   17     53  \n",
+       "10     17   17     53  \n",
+       "11     17   17     53  \n",
+       "12     17   17     53  \n",
+       "13     17   17     53  \n",
+       "14     17   17     53  \n",
+       "15     17   17     53  \n",
+       "16     17   17     53  \n",
+       "17     17   17     53  \n",
+       "18     17   17     53  \n",
+       "19     17   17     53  \n",
+       "20     17   17     53  \n",
+       "21     17   17     53  \n",
+       "22     17   17     53  \n",
+       "23     17   17     53  \n",
+       "24     17   17     53  \n",
+       "25     17   17     53  \n",
+       "26     17   17     53  \n",
+       "27     17   17     53  \n",
+       "28     17   17     53  \n",
+       "29     17   17     53  \n",
+       "...    ..  ...    ...  \n",
+       "50687  21    5     10  \n",
+       "50688  21    5     10  \n",
+       "50689  21    5     10  \n",
+       "50690  21    5     10  \n",
+       "50691  21    5     10  \n",
+       "50692  21    5     10  \n",
+       "50693  21    5     10  \n",
+       "50694  21    5     10  \n",
+       "50695  21    5     10  \n",
+       "50696  21    5     10  \n",
+       "50697  21    5     10  \n",
+       "50698  21    5     10  \n",
+       "50699  21    5     10  \n",
+       "50700  21    5     10  \n",
+       "50701  21    5     10  \n",
+       "50702  21    5     10  \n",
+       "50703  21    5     10  \n",
+       "50704  21    5     10  \n",
+       "50705  21    5     10  \n",
+       "50706  21    5     10  \n",
+       "50707  21    5     10  \n",
+       "50708  21    5     10  \n",
+       "50709  21    5     10  \n",
+       "50710  21    5     10  \n",
+       "50711  21    5     10  \n",
+       "50712  21    5     10  \n",
+       "50713  21    5     10  \n",
+       "50714  21    5     10  \n",
+       "50715  21    5     10  \n",
+       "50716  21    5     10  \n",
+       "\n",
+       "[3950717 rows x 37 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 3950717 entries, 0 to 50716\n",
+      "Data columns (total 37 columns):\n",
+      "contributors                          object\n",
+      "coordinates                           object\n",
+      "created_at                            object\n",
+      "entities_hashtags_text                object\n",
+      "entities_user_mentions_id_str         object\n",
+      "entities_user_mentions_screen_name    object\n",
+      "favorite_count                        int64\n",
+      "geo                                   object\n",
+      "id_str                                object\n",
+      "in_reply_to_status_id_str             object\n",
+      "in_reply_to_user_id_str               object\n",
+      "is_quote_status                       bool\n",
+      "place                                 object\n",
+      "possibly_sensitive                    object\n",
+      "retweet_count                         int64\n",
+      "retweeted_status_id_str               object\n",
+      "source                                object\n",
+      "text                                  object\n",
+      "user_contributors_enabled             bool\n",
+      "user_created_at                       object\n",
+      "user_followers_count                  int64\n",
+      "user_friends_count                    int64\n",
+      "user_geo_enabled                      bool\n",
+      "user_id_str                           object\n",
+      "user_is_translation_enabled           bool\n",
+      "user_lang                             object\n",
+      "user_listed_count                     int64\n",
+      "user_location                         object\n",
+      "user_screen_name                      object\n",
+      "user_time_zone                        object\n",
+      "user_utc_offset                       float64\n",
+      "user_verified                         bool\n",
+      "DoW                                   object\n",
+      "Month                                 object\n",
+      "DoM                                   object\n",
+      "Hour                                  int64\n",
+      "Minute                                int64\n",
+      "dtypes: bool(5), float64(1), int64(7), object(24)\n",
+      "memory usage: 1013.5+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "data.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "verified = data[data.user_verified == True]\n",
+    "normal = data[data.user_verified == False]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "groupedVerified = verified.groupby(['DoM', 'Hour', 'Minute']).count().reset_index().copy()\n",
+    "groupedNormal = normal.groupby(['DoM', 'Hour', 'Minute']).count().reset_index().copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "groupedVerified['Datetime'] = groupedVerified.apply(lambda row: datetime.datetime(\n",
+    "    year = 2014, \n",
+    "    month = 8, \n",
+    "    day = int(row.DoM), \n",
+    "    hour = row.Hour, \n",
+    "    minute = row.Minute), axis=1)\n",
+    "\n",
+    "groupedNormal['Datetime'] = groupedNormal.apply(lambda row: datetime.datetime(\n",
+    "    year = 2014, \n",
+    "    month = 8, \n",
+    "    day = int(row.DoM), \n",
+    "    hour = row.Hour, \n",
+    "    minute = row.Minute), axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x344188750>"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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eRUQyTM3WIhJnsR4wo4d/EcmHLanmsVu3bhpNLhKq7Z3hcRLr5FFEpDGIc3I1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\nwzAMI2f+P7sbyYe4QCEZAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x3562ce110>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(10,10))\n",
+    "\n",
+    "\n",
+    "groupedVerified.plot(kind='line', x='Datetime', y='created_at', label='Verified Users', ax=ax)\n",
+    "groupedNormal.plot(kind='line', x='Datetime', y='created_at', ax = ax, secondary_y=True, label='Non-verified Users')\n",
+    "plt.title('Number of tweets by Users')\n",
+    "\n",
+    "ax.set_ylabel('Count of twets (Verified users)', color='b')\n",
+    "ax.right_ax.set_ylabel('Count of tweets (Non-Verified users)', color='g')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/development_scripts/Spatial_Representations.ipynb b/development_scripts/Spatial_Representations.ipynb
new file mode 100644
index 0000000..57ca093
--- /dev/null
+++ b/development_scripts/Spatial_Representations.ipynb
@@ -0,0 +1,338 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Mapping Twitter Data\n",
+    "This notebook provides the basis for developing spatial representations of a variety of interesting data that is presented in the Ferguson Twitter dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "% matplotlib inline\n",
+    "import json\n",
+    "import time\n",
+    "import pandas as pd\n",
+    "import cartopy.crs as ccrs\n",
+    "from ipywidgets import widgets"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's begin with the data. We have two datasets. The first is data from the two weeks following the initial shooting. The second is data from the two weeks following the indictment. Twitter has provided an extensive amount of data for us, and we have developed a cleaning mechanism which can be observed in a seperate script. The data is placed in a data frame:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def make_frame(filename,low_bound,high_bound):\n",
+    "    data = []\n",
+    "    i = 0\n",
+    "    #For now only want to read in a few lines of this file (about 100000 tweets)\n",
+    "    start = time.time()\n",
+    "    with open(filename) as cleanedTweets:\n",
+    "        for tweet in cleanedTweets:\n",
+    "            i += 1\n",
+    "            if i > low_bound and i < high_bound:\n",
+    "                jsonline = json.loads(tweet)\n",
+    "                data.append(jsonline)\n",
+    "            elif i > high_bound:\n",
+    "                break\n",
+    "    return data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "filename='./data/cleanedShootingTweets.json'\n",
+    "data = make_frame(filename,100000,200000)\n",
+    "df = pd.DataFrame(data=data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 9999 entries, 0 to 9998\n",
+      "Data columns (total 59 columns):\n",
+      "contributors                            0 non-null object\n",
+      "coordinates                             63 non-null object\n",
+      "created_at                              9999 non-null object\n",
+      "entities_hashtags_0_text                0 non-null float64\n",
+      "entities_hashtags_1_text                0 non-null float64\n",
+      "entities_hashtags_2_text                0 non-null float64\n",
+      "entities_hashtags_3_text                0 non-null float64\n",
+      "entities_hashtags_4_text                0 non-null float64\n",
+      "entities_hashtags_5_text                0 non-null float64\n",
+      "entities_hashtags_6_text                0 non-null float64\n",
+      "entities_hashtags_7_text                0 non-null float64\n",
+      "entities_hashtags_8_text                0 non-null float64\n",
+      "entities_hashtags_9_text                0 non-null float64\n",
+      "entities_user_mentions_0_id_str         0 non-null float64\n",
+      "entities_user_mentions_0_screen_name    0 non-null float64\n",
+      "entities_user_mentions_1_id_str         0 non-null float64\n",
+      "entities_user_mentions_1_screen_name    0 non-null float64\n",
+      "entities_user_mentions_2_id_str         0 non-null float64\n",
+      "entities_user_mentions_2_screen_name    0 non-null float64\n",
+      "entities_user_mentions_3_id_str         0 non-null float64\n",
+      "entities_user_mentions_3_screen_name    0 non-null float64\n",
+      "entities_user_mentions_4_id_str         0 non-null float64\n",
+      "entities_user_mentions_4_screen_name    0 non-null float64\n",
+      "entities_user_mentions_5_id_str         0 non-null float64\n",
+      "entities_user_mentions_5_screen_name    0 non-null float64\n",
+      "entities_user_mentions_6_id_str         0 non-null float64\n",
+      "entities_user_mentions_6_screen_name    0 non-null float64\n",
+      "entities_user_mentions_7_id_str         0 non-null float64\n",
+      "entities_user_mentions_7_screen_name    0 non-null float64\n",
+      "entities_user_mentions_8_id_str         0 non-null float64\n",
+      "entities_user_mentions_8_screen_name    0 non-null float64\n",
+      "entities_user_mentions_9_id_str         0 non-null float64\n",
+      "entities_user_mentions_9_screen_name    0 non-null float64\n",
+      "favorite_count                          9999 non-null int64\n",
+      "geo                                     63 non-null object\n",
+      "id_str                                  9999 non-null object\n",
+      "in_reply_to_status_id_str               376 non-null object\n",
+      "in_reply_to_user_id_str                 452 non-null object\n",
+      "is_quote_status                         9999 non-null bool\n",
+      "place                                   80 non-null object\n",
+      "possibly_sensitive                      6596 non-null object\n",
+      "retweet_count                           9999 non-null int64\n",
+      "retweeted                               9999 non-null bool\n",
+      "source                                  9999 non-null object\n",
+      "text                                    9999 non-null object\n",
+      "user_contributors_enabled               9999 non-null bool\n",
+      "user_created_at                         9999 non-null object\n",
+      "user_followers_count                    9999 non-null int64\n",
+      "user_friends_count                      9999 non-null int64\n",
+      "user_geo_enabled                        9999 non-null bool\n",
+      "user_id_str                             9999 non-null object\n",
+      "user_is_translation_enabled             9999 non-null bool\n",
+      "user_lang                               9999 non-null object\n",
+      "user_listed_count                       9999 non-null int64\n",
+      "user_location                           9999 non-null object\n",
+      "user_screen_name                        9999 non-null object\n",
+      "user_time_zone                          8001 non-null object\n",
+      "user_utc_offset                         8001 non-null float64\n",
+      "user_verified                           9999 non-null bool\n",
+      "dtypes: bool(6), float64(31), int64(5), object(17)\n",
+      "memory usage: 4.2+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are several fields which we find particularly interesting here, namely the time and all place related fields. To better help us process this data in this notebook, we create new columns which breaks out created_at, coordinates and place."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "#time based recodes\n",
+    "df['DoW'] = df['created_at'].apply(lambda x: str(x)[0:3:])\n",
+    "df['Month'] = df['created_at'].apply(lambda x: str(x)[4:7:])\n",
+    "df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])\n",
+    "df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))\n",
+    "df['Minute'] = df['created_at'].apply(lambda x: int(str(x)[14:16:]))\n",
+    "\n",
+    "#let's grab the coordinates from the coordinates field, which is actually a dictionary\n",
+    "coords = []\n",
+    "for i in range(len(df)):\n",
+    "    location = df['coordinates'][i]\n",
+    "    try: #want to make sure that null values don't throw an exception\n",
+    "        coords.append(location.get('coordinates'))\n",
+    "    except:\n",
+    "        coords.append([0,0])\n",
+    "\n",
+    "df['Coords'] = coords\n",
+    "df['x'] = df['Coords'].apply(lambda x: x[0])\n",
+    "df['y'] = df['Coords'].apply(lambda x: x[1])\n",
+    "\n",
+    "#now, let's grab the information from place, which is similarly a very detailed dictionary of elements\n",
+    "name = []\n",
+    "country = []\n",
+    "coordinates = []\n",
+    "full_name = []\n",
+    "for i in range(len(df)):\n",
+    "    location = df['place'][i]\n",
+    "    try:\n",
+    "        coordinates.append(location.get('bounding_box').get('coordinates'))\n",
+    "        name.append(location.get('name'))\n",
+    "        full_name.append(location.get('full_name'))\n",
+    "        country.append(location.get('country'))\n",
+    "    except:\n",
+    "        coordinates.append([[[0,0],[0,0],[0,0],[0,0]]])\n",
+    "        name.append('')\n",
+    "        full_name.append('')\n",
+    "        country.append('')\n",
+    "\n",
+    "mean_coords = []\n",
+    "for box in coordinates:\n",
+    "    mean_coord_x = (box[0][0][0]+box[0][1][0]+box[0][2][0]+box[0][3][0])/4\n",
+    "    mean_coord_y = (box[0][0][1]+box[0][1][1]+box[0][2][1]+box[0][3][1])/4\n",
+    "    mean_coords.append([mean_coord_x,mean_coord_y])\n",
+    "\n",
+    "df['city'] = name\n",
+    "df['country'] = country\n",
+    "df['full_name'] = full_name\n",
+    "df['P_Coords'] = mean_coords\n",
+    "df['x_p'] = df['P_Coords'].apply(lambda x: x[0])\n",
+    "df['y_p'] = df['P_Coords'].apply(lambda x: x[1])\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that the data is all set, let's start looking at it. Using a library called [cartopy](http://scitools.org.uk/cartopy/), we can grab a really simple map to use to put everything in perspective."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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4T47/9zxy9+5dXLt2Da6urihfvjySk5Nx9OhRPH78WPJQ9Pb2Rt++fXOtJzQ0FKdOncKR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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f52dc4f1f10>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#the cartopy map, going simple outline for now\n",
+    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "ax.coastlines()\n",
+    "\n",
+    "#straight-up coordinate data which we just finished recoding\n",
+    "plt.scatter(df.x,df.y,color='r')\n",
+    "plt.scatter(df.x_p,df.y_p,color='g')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, to add a temporal element to this, we add a slider which pulls in some of the time columns we also just pulled out of interest."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def plotLocation(Hour,Minute):\n",
+    "    plt.figure(figsize=(15,15))\n",
+    "    ax = plt.axes(projection=ccrs.PlateCarree())\n",
+    "    ax.coastlines()\n",
+    "    plt.scatter(df.x[(df['Hour']==Hour) & (df['Minute']==Minute)],df.y[(df['Hour']==Hour) & (df['Minute']==Minute)],color='r')\n",
+    "    plt.scatter(df.x_p[(df['Hour']==Hour) & (df['Minute']==Minute)],df.y_p[(df['Hour']==Hour) &  (df['Minute']==Minute)],color='g')\n",
+    "    plt.axis([-180, 180, -75, 75])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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vv/+e2R39VDgcDhwcHKCrq4tjx4591q16VVVVDBkyBPb29rCwsEBubi7i4+MR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ZGB42JHyM+TB/QAnAZwA5BoI4GU4hQRp/s4nCccaO/QxjeBVtDeoQ3O04/fV4Yv/f9hA+1tWuDc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ERkbSt29fDh48yJUrV6hXrx4AJSUlfPTRR+zatYvjx4+Xy+sN/5es5idEDeLn58fjx49p1KgR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\nTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f52b1f62990>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "Hour = widgets.IntSlider(min=0, max=23, value=21)\n",
+    "Minute = widgets.IntSlider(min=0, max=59, value=7)\n",
+    "widgets.interact(plotLocation,Hour=Hour,Minute=Minute)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/development_scripts/clean_json_data.py b/development_scripts/clean_json_data.py
new file mode 100644
index 0000000..e353fc8
--- /dev/null
+++ b/development_scripts/clean_json_data.py
@@ -0,0 +1,128 @@
+import json
+import time
+import os
+
+data = []
+baseFolderPath = './../data/shooting_tweets/raw tweet data/'
+files = ['tweets.json', 'rest_tweets.json', 
+	'rest_tweets2.json', 'rest_tweets3.json', 
+	'rest_tweets4.json', 'rest_tweets5.json',
+	'rest_tweets6.json', 'rest_tweets7.json',
+	'rest_tweets8.json', 'rest_tweets9.json',
+	'rest_tweets10.json', 'rest_tweets11.json',
+	'rest_tweets12.json', 'rest_tweets13.json',
+	'rest_tweets14.json', 'rest_tweets15.json',
+	'rest_tweets16.json', 'rest_tweets17.json',
+	'rest_tweets18.json',]
+i = 0
+
+
+#Just the ones we're keeping
+#For a complete list
+#https://dev.twitter.com/overview/api/tweets
+toKeep = {
+	'contributors': 1, 
+	'text': 1, 
+	'id_str': 1, 
+	'is_quote_status': 1, 
+	'in_reply_to_status_id_str': 1, 
+	'favorite_count': 1, 
+	'source': 1, 
+	'coordinates': 1, 
+	'entities': {
+		'hashtags': {
+			'text': 1
+		},
+		'user_mentions': {
+			'id_str': 1,
+			'screen_name': 1,
+		},
+	},
+	'retweet_count': 1,
+	'in_reply_to_user_id_str': 1,
+	'user': {
+		'id_str': 1,
+		'verified': 1,
+		'followers_count': 1,
+		'listed_count': 1,
+		'is_translation_enabled': 1,
+		'utc_offset': 1,
+		'friends_count': 1,
+		'location': 1,
+		'geo_enabled': 1,
+		'screen_name': 1,
+		'lang': 1,
+		'created_at': 1,
+		'contributors_enabled': 1,
+		'time_zone': 1,
+	},
+	'geo': 1,
+	'possibly_sensitive': 1,
+	'created_at': 1,
+	'place': 1,
+	'retweeted_status': {
+		"id_str": 1,
+	},
+}
+
+#Takes about 1.8 Seconds per 10000 json objects. 
+start = time.time()
+with open("./../cleanedShootingTweets.json", "a") as cleanedTweets:
+	for tweetFile in files:
+		filepath = os.path.abspath(baseFolderPath + tweetFile)
+		with open(filepath) as f:
+		    for line in f:
+		    	i += 1
+		    	jsonline = json.loads(line)
+		    	newJson = {}
+		    	for key in toKeep.keys():
+		    		#This is not a nested hash
+		    		if (toKeep[key] == 1):
+		    			jsonVal = jsonline.get(key,None)
+		    			newJson[key] = jsonVal
+		    		#This is a nested hash
+		    		else :
+		    			jsonVal = jsonline.get(key,{})
+		    			for key2 in toKeep[key].keys():
+		    				if (toKeep[key][key2] == 1):
+		    					subJson = jsonVal.get(key2, None)
+		    					newKey = key + '_' + key2
+				    			newJson[newKey] = subJson
+				    		#handle user mentions separately because that's a list
+				    		elif (key2 in ['user_mentions', 'hashtags']):
+				    			subJson = jsonVal.get(key2, {})
+				    			for key3 in toKeep[key][key2].keys():
+									newKey = key + '_' + key2 + '_' + key3
+									newJson[newKey] = []
+									for j, jsonElem in enumerate(subJson):
+
+				    				# print(jsonElem)
+										newJson[newKey].append(jsonElem.get(key3,None))
+						    			# print(newKey, newJson[newKey])
+
+				    		#This is a twice-nested hash (we currently don't have 
+				    		#this case, but it's here for completeness/in case we 
+				    		#decide to add something)
+				    		else :
+				    			subJson = jsonVal.get(key2, {})
+				    			for key3 in toKeep[key][key2].keys():
+				    				newKey = key + '_' + key2 + '_' + key3
+			    					subsubJson = subJson.get(key,None)
+					    			newJson[newKey] = subsubJson.get(key3,None)
+		    	# jsonKeeping = {key: jsonline.get(key,None) for key in toKeep}
+		    	
+
+		   #  	print newJson
+		   #  	if (i > 5):
+					# break	
+		    	#Add a new line so we aren't just appending to the file. 
+		    	cleanedTweets.write(json.dumps(newJson) + "\n")
+
+					    
+		        if (i % 100000 == 0):
+		        	print "number of tweets parsed: ", i
+		        	print "total time elapsed: ", time.time() - start
+		print "finished file: ", tweetFile	
+
+
+
diff --git a/development_scripts/initial_tweet_exploration.py b/development_scripts/initial_tweet_exploration.py
new file mode 100644
index 0000000..582ced7
--- /dev/null
+++ b/development_scripts/initial_tweet_exploration.py
@@ -0,0 +1,90 @@
+import json
+import time
+import matplotlib.pyplot as plt
+import numpy as np 
+import pandas as pd
+import cartopy.crs as ccrs
+from ipywidgets import widgets
+
+data = []
+filename='./data/cleanedShootingTweets.json'
+i = 0
+
+#For now only want to read in a few lines of this file (about 100000 tweets)
+start = time.time()
+with open(filename) as cleanedTweets:
+    for tweet in cleanedTweets:
+    	i += 1
+    	if i > 100000 and i < 300000:
+    		jsonline = json.loads(tweet)
+    		data.append(jsonline)
+    	elif i > 300000:
+    		break
+
+df = pd.DataFrame(data=data)
+df['retweet'] = df['text'].apply(lambda x: 'RT @' in x)
+# df['DoW'] = df['created_at'].apply(lambda x: str(x)[0:3:])
+# df['Month'] = df['created_at'].apply(lambda x: str(x)[4:7:])
+# df['DoM'] = df['created_at'].apply(lambda x: str(x)[8:10:])
+df['Hour'] = df['created_at'].apply(lambda x: int(str(x)[11:13:]))
+df['Minute'] = df['created_at'].apply(lambda x: int(str(x)[14:16:]))
+df['Minute'] = df['Minute'] + (df['Hour']-17)*60
+# df['HMS'] = df['created_at'].apply(lambda x: str(x)[11:19:])
+
+coords = []
+for i in range(len(df)):
+	location = df['coordinates'][i]
+	try:
+		coords.append(location.get('coordinates'))
+	except:
+		coords.append([0,0])
+
+df['coords'] = coords
+df['x'] = df['coords'].apply(lambda x: x[0])
+df['y'] = df['coords'].apply(lambda x: x[1])
+
+name = []
+country = []
+coordinates = []
+full_name = []
+for i in range(len(df)):
+	location = df['place'][i]
+	try:
+		coordinates.append(location.get('bounding_box').get('coordinates'))
+		name.append(location.get('name'))
+		full_name.append(location.get('full_name'))
+		country.append(location.get('country'))
+	except:
+		coordinates.append([[[0,0],[0,0],[0,0],[0,0]]])
+		name.append('')
+		full_name.append('')
+		country.append('')
+
+act_coords = []
+for box in coordinates:
+	actual_coord_x = (box[0][0][0]+box[0][1][0]+box[0][2][0]+box[0][3][0])/4
+	actual_coord_y = (box[0][0][1]+box[0][1][1]+box[0][2][1]+box[0][3][1])/4
+	act_coords.append([actual_coord_x,actual_coord_y])
+
+df['city'] = name
+df['country'] = country
+df['full_name'] = full_name
+df['coordinates'] = act_coords
+df['x_p'] = df['coordinates'].apply(lambda x: x[0])
+df['y_p'] = df['coordinates'].apply(lambda x: x[1])
+
+ax = plt.axes(projection=ccrs.PlateCarree())
+# shapename = 'admin_1_states_provinces_lakes_shp'
+# states_shp = shpreader.natural_earth(resolution='110m',category='cultural', name=shapename)
+ax.coastlines()
+
+def plotLocation(Hour):
+	plt.scatter(df.x[df['Hour']==Hour],df.y[df['Hour']==Hour],color='r')
+	plt.scatter(df.x_p[df['Hour']==Hour],df.y_p[df['Hour']==Hour],color='g')
+
+Hour = widgets.IntSlider(min=0, max=23, value=10)
+widgets.interact(plotLocation,Hour=Hour)
+
+plt.show()
+
+
diff --git a/development_scripts/nodes_for_notebook.py b/development_scripts/nodes_for_notebook.py
new file mode 100644
index 0000000..6a2825e
--- /dev/null
+++ b/development_scripts/nodes_for_notebook.py
@@ -0,0 +1,123 @@
+import networkx as nx
+
+from mpl_toolkits.basemap import Basemap
+import plotly.plotly as py
+from plotly.graph_objs import *
+py.sign_in('vpreston', 'tcx2wn8rfb')
+
+from plotly.offline import download_plotlyjs, init_notebook_mode, iplot
+from plotly.offline import plot
+from plotly.graph_objs import Scatter
+init_notebook_mode()
+
+
+############### Imports above to be added to the beginning
+
+m = Basemap()
+def make_scatter(x,y):
+    return Scatter(x=x,y=y,mode='lines',line=Line(color='black'),name=' ')
+
+def polygons_to_traces(poly_paths, N_poly):
+    ''' 
+    pos arg 1. (poly_paths): paths to polygons
+    pos arg 2. (N_poly): number of polygon to convert
+    '''
+    traces = []  # init. plotting list 
+
+    for i_poly in range(N_poly):
+        poly_path = poly_paths[i_poly]
+        
+        # get the Basemap coordinates of each segment
+        coords_cc = np.array(
+            [(vertex[0],vertex[1]) 
+             for (vertex,code) in poly_path.iter_segments(simplify=False)]
+        )
+        
+        # convert coordinates to lon/lat by 'inverting' the Basemap projection
+        lon_cc, lat_cc = m(coords_cc[:,0],coords_cc[:,1], inverse=True)
+        
+        # add plot.ly plotting options
+        traces.append(make_scatter(lon_cc,lat_cc))
+     
+    return traces
+
+def get_coastline_traces():
+    poly_paths = m.drawcoastlines().get_paths() # coastline polygon paths
+    N_poly = 91  # use only the 91st biggest coastlines (i.e. no rivers)
+    return polygons_to_traces(poly_paths, N_poly)
+
+traces_cc = get_coastline_traces()
+
+
+############################## FRAME ABOVE FOR MAP, FRAME BELOW FOR NODES
+
+G=nx.from_pandas_dataframe(latLonPopulated_RT, source='tweetId',target='retweeter')
+
+pos = {}
+color = {}
+for i,tweet in latLonPopulated_RT.iterrows():
+    pos[tweet['tweetId'].upper()] = np.asarray([tweet['x'],tweet['y']])
+    pos[tweet['retweeter'].upper()] = np.asarray([tweet['x'],tweet['y']])
+    color[tweet['tweetId'].upper()] = tweet['node_color']
+    color[tweet['retweeter'].upper()] = tweet['node_color']
+
+for n,p in pos.iteritems():
+    G.node[n]['pos'] = p
+
+for n,c in color.iteritems():
+    G.node[n]['color'] = c
+    
+pos = nx.get_node_attributes(G,'pos')
+
+edge_trace = Scatter(
+    x=[], 
+    y=[], 
+    line=Line(width=0.5,color='#888'),
+    hoverinfo='none',
+    mode='lines')
+
+for edge in G.edges():
+    x0, y0 = G.node[edge[0]]['pos']
+    x1, y1 = G.node[edge[1]]['pos']
+    edge_trace['x'] += [x0, x1, None]
+    edge_trace['y'] += [y0, y1, None]
+
+node_trace = Scatter(
+    x=[], 
+    y=[], 
+    text=[],
+    mode='markers', 
+    hoverinfo='text',
+    marker=Marker(
+        color=[], 
+        size=[],         
+        line=dict(width=2)))
+
+for node in G.nodes():
+    x, y = G.node[node]['pos']
+    node_trace['x'].append(x)
+    node_trace['y'].append(y)
+    c = G.node[node]['color']
+    node_trace['marker']['color'].append(c)
+
+for node, adjacencies in enumerate(G.adjacency_list()):
+    node_trace['marker']['size'].append(len(adjacencies))
+    node_info = '# of connections: '+str(len(adjacencies))
+    node_trace['text'].append(node_info)
+
+fig = Figure(data=Data([edge_trace, node_trace]+traces_cc),
+             layout=Layout(
+                title='<br>',
+                titlefont=dict(size=16),
+                showlegend=False, 
+                hovermode='closest',
+                margin=dict(b=20,l=5,r=5,t=40),
+                annotations=[ dict(
+                    text="",
+                    showarrow=False,
+                    xref="paper", yref="paper",
+                    x=0.005, y=-0.002 ) ],
+                xaxis=XAxis(range=[-180,180],showgrid=False, zeroline=False, showticklabels=False),
+                yaxis=YAxis(range=[-75,75],showgrid=False, zeroline=False, showticklabels=False)))
+
+iplot(fig)
\ No newline at end of file
diff --git a/mid_project_checkin.md b/mid_project_checkin.md
new file mode 100644
index 0000000..c9ad848
--- /dev/null
+++ b/mid_project_checkin.md
@@ -0,0 +1,26 @@
+# Mid Project Checkin
+### By Sophia and Victoria
+
+## Goals
+Our goals for this mid-project checkin were to 
+* Have Data
+* Have an understanding of what information the dataset contains and how to access that information
+* Have plans for our final visualizations and preliminary visualizations. 
+
+We believe that we have accomplised these goals, although the documentation for code produced in accomplishing these goals is not entirely to our standard. 
+
+## Accomplishments Thus Far
+Thus far, we have:
+* Found a sustainable method of downloading tweets, using twarc.py [documentation](https://github.com/edsu/twarc). This library allows us to query the twitter API and download tweets from a list of tweets ids. 
+
+* We have looked through the tweets, and the twitter API [documentation](https://dev.twitter.com/rest/reference/get/statuses/lookup) as well as the [documentation on tweet objects](https://dev.twitter.com/overview/api/tweets) to decide what information in each tweet that we want to keep. Most fields of interest like retweet/friend count are populated. On the otherhand, fields contanint location data are the least likely to be populated. We have chosen to keep approximately half of the indicators given to us by the twitter API. 
+
+* We have created a cleaning function that, given a file of raw tweet data, cleans the tweets, keeping only the information we want and flattening the json, so that there is no nested json. This code van be found in the development_scripts/clean_json_data.py. 
+
+* We have started exploring the data and created preliminary plots of our data. These plots include a visualization of how the most popular hashtags over time and a location-based visualization of the tweets that occurred. These explorations can be found in Most_Popular_Hashtags.ipynb and Spatial_Representations.ipynb. 
+
+* We have also started to plan out our final visualization(s).
+	* Our minumum viable product product will be a map-based, temporal visualization of the number of tweets mentioning Ferguson over time. We are planning on producing similar visualizations for both the tweets related to the shooting and the tweets shortly after the (lack of) indictment. 
+	* Additionally, a stretch goal would be a visualization depicting how the most re-tweeted tweets spread over time, or how a tweet goes viral over time.
+	* Another thing that we are interested in investigating if the time allows is when celebrities and/or public organizations (verified twitter accounts) get involved -- how do celebrities/public figures play a role in the conversation about Ferguson over social media.
+