analysis_small.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from convokit import Corpus, download"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "cons = Corpus(filename=\"/Users/yara/.convokit/downloads/subreddit-Conservative\")\n",
    "dems = Corpus(filename=\"/Users/yara/.convokit/downloads/subreddit-democrats\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Speakers: 141593\n",
      "Number of Utterances: 3078505\n",
      "Number of Conversations: 306539\n"
     ]
    }
   ],
   "source": [
    "cons.print_summary_stats()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Speakers: 37426\n",
      "Number of Utterances: 369011\n",
      "Number of Conversations: 84228\n"
     ]
    }
   ],
   "source": [
    "dems.print_summary_stats()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Looking at the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "utt = cons.random_utterance()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Abolish the Department of Education.'"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "utt.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'dk9awc5'"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "utt.id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'patri0t556'"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "utt.speaker.id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'6ng0g4'"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "utt.reply_to"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Utterance({'obj_type': 'utterance', 'meta': {'score': 164, 'top_level_comment': None, 'retrieved_on': 1502106180, 'gilded': 0, 'gildings': None, 'subreddit': 'Conservative', 'stickied': False, 'permalink': '/r/Conservative/comments/6ng0g4/devos_too_many_college_students_have_been_treated/', 'author_flair_text': '', 'liwc-categories': set(), 'corpus': 'Conservative'}, 'vectors': [], 'speaker': Speaker({'obj_type': 'speaker', 'meta': {'con_convos': 870, 'dem_convos': 878, 'con_utts': 888, 'dem_utts': 896, 'main': False, 'equal': False}, 'vectors': [], 'owner': <convokit.model.corpus.Corpus object at 0x2b39b4c70>, 'id': 'DGAgainstDV'}), 'conversation_id': '6ng0g4', 'reply_to': None, 'timestamp': 1500126452, 'text': '', 'owner': <convokit.model.corpus.Corpus object at 0x589ab3760>, 'id': '6ng0g4'})"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cons.get_utterance('6ng0g4')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "utt.meta['score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "convo = cons.random_conversation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ozric101\n",
      "    optionhome\n",
      "        StraightNewt\n",
      "        [deleted]\n",
      "        [deleted]\n",
      "    memberCP\n",
      "        ozric101\n",
      "            memberCP\n",
      "                ozric101\n",
      "                    memberCP\n",
      "        [deleted]\n",
      "            memberCP\n",
      "        BeachCruisin22\n",
      "    svengalus\n"
     ]
    }
   ],
   "source": [
    "convo.print_conversation_structure()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "    Apparently if you are a deep state leftist you never have to recuse yourself fro\n",
      "\n",
      "        The legal system is 100% corrupt.\n",
      "\n",
      "        [removed]\n",
      "\n",
      "        [deleted]\n",
      "\n",
      "    Prosecutors do not recuse themselves unless they have a personal connection to t\n",
      "\n",
      "        Everyone who signed off on that should be disbarred. \n",
      "\n",
      "            On what grounds?\n",
      "\n",
      "                Section 242 of Title 18\n",
      "\n",
      "                    Whose rights have been curtailed, and which ones?\n",
      "\n",
      "        [deleted]\n",
      "\n",
      "            Session was an official member of the Trump campaign. \n",
      "\n",
      "Being nominated by Trump\n",
      "\n",
      "        If a potential defense is that the FISA application was dishonest, then Rrosenst\n",
      "\n",
      "    \"I'd like to call my first witness... Me\"\n",
      "\n"
     ]
    }
   ],
   "source": [
    "convo.print_conversation_structure(lambda utt: utt.text[:80] + \"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['91qurq',\n",
       " 'e3031dz',\n",
       " 'e309rhr',\n",
       " 'e30aqra',\n",
       " 'e30hw1g',\n",
       " 'e30i4g1',\n",
       " 'e30inu5',\n",
       " 'e30it88',\n",
       " 'e30kfx9',\n",
       " 'e30nht3',\n",
       " 'e30qx1e',\n",
       " 'e30wzs4',\n",
       " 'e310dp5',\n",
       " 'e310fth']"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "convo.get_utterance_ids()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'title': \"Rep. Meadows Goes After Rosenstein For Signing Carter Page FISA Application 'He's a Witness and Should Recuse Himself Immediately'\",\n",
       " 'num_comments': 11,\n",
       " 'domain': 'thegatewaypundit.com',\n",
       " 'timestamp': 1532516643,\n",
       " 'subreddit': 'Conservative',\n",
       " 'gilded': 0,\n",
       " 'gildings': None,\n",
       " 'stickied': False,\n",
       " 'author_flair_text': 'Conservative Troublemaker'}"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "convo.meta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clean the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def check_utts(corpus, convo):\n",
    "    utts = convo.get_utterance_ids()\n",
    "    for i in range(len(utts)):\n",
    "        try:\n",
    "            utt = corpus.get_utterance(utts[i])\n",
    "            if utt.reply_to is not None:\n",
    "                corpus.get_utterance(utt.reply_to)\n",
    "        except:\n",
    "            return False\n",
    "    return True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "cons_filtered = cons.filter_conversations_by(lambda x: check_utts(cons, x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Speakers: 141578\n",
      "Number of Utterances: 3077820\n",
      "Number of Conversations: 306513\n"
     ]
    }
   ],
   "source": [
    "cons.print_summary_stats()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "dems_filtered = dems.filter_conversations_by(lambda x: check_utts(dems, x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Speakers: 37426\n",
      "Number of Utterances: 368926\n",
      "Number of Conversations: 84226\n"
     ]
    }
   ],
   "source": [
    "dems_filtered.print_summary_stats()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add Metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "both = [spkr for spkr in dems_filtered.speakers if spkr in cons_filtered.speakers]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[deleted]'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "both.pop(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9134"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(both)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "for spkr in both:\n",
    "    cons_spkr = cons_filtered.get_speaker(spkr)\n",
    "    dems_spkr = dems_filtered.get_speaker(spkr)\n",
    "    cons_sprk_convo_n = len([convo for convo in cons_spkr.iter_conversations()])\n",
    "    dems_sprk_convo_n = len([convo for convo in dems_spkr.iter_conversations()])\n",
    "\n",
    "    cons_spkr.meta[\"con_convos\"] = cons_sprk_convo_n\n",
    "    cons_spkr.meta[\"dem_convos\"] = dems_sprk_convo_n\n",
    "    dems_spkr.meta[\"con_convos\"] = cons_sprk_convo_n\n",
    "    dems_spkr.meta[\"dem_convos\"] = dems_sprk_convo_n\n",
    "\n",
    "    cons_sprk_utt_n = len([utt for utt in cons_spkr.iter_utterances()])\n",
    "    dems_sprk_utt_n = len([utt for utt in dems_spkr.iter_utterances()])\n",
    "\n",
    "    cons_spkr.meta[\"con_utts\"] = cons_sprk_utt_n\n",
    "    cons_spkr.meta[\"dem_utts\"] = dems_sprk_utt_n\n",
    "    dems_spkr.meta[\"con_utts\"] = cons_sprk_utt_n\n",
    "    dems_spkr.meta[\"dem_utts\"] = dems_sprk_utt_n\n",
    "\n",
    "    cons_spkr.meta[\"main\"] = True if cons_sprk_convo_n > dems_sprk_convo_n else False\n",
    "    cons_spkr.meta[\"equal\"] = True if cons_sprk_convo_n == dems_sprk_convo_n else False\n",
    "    dems_spkr.meta[\"main\"] = True if dems_sprk_convo_n > cons_sprk_convo_n else False\n",
    "    dems_spkr.meta[\"equal\"] = True if cons_sprk_convo_n == dems_sprk_convo_n else False\n",
    "\n",
    "cons_main = [ spkr for spkr in both if cons_filtered.get_speaker(spkr).meta[\"main\"] ] \n",
    "dems_main = [ spkr for spkr in both if dems_filtered.get_speaker(spkr).meta[\"main\"] ] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "dems_filtered.dump(name=\"dems_filtered\", base_path=os.getcwd()+'/data/processed/')\n",
    "cons_filtered.dump(name=\"cons_filtered\", base_path=os.getcwd()+'/data/processed/')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate coordination scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from convokit import Coordination\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "concoord = Coordination()\n",
    "concoord.fit(cons_filtered)\n",
    "concoord.transform(cons_filtered);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "demcoord = Coordination()\n",
    "demcoord.fit(dems_filtered)\n",
    "demcoord.transform(dems_filtered);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "everyone = lambda spkr: True\n",
    "conservatives  = lambda spkr: spkr.id in cons_main \n",
    "democrats = lambda spkr: spkr.id in dems_main"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns, matplotlib.pyplot as plt\n",
    "custom_params = {\"axes.spines.right\": False, \"axes.spines.top\": False, 'figure.figsize':(16,9)}\n",
    "sns.set_theme(style=\"ticks\", font_scale=1.2, rc=custom_params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "conservatives_to_all_conservatives = concoord.summarize(cons_filtered, conservatives, everyone)\n",
    "conservatives_to_all_conservatives_scores = [ [spkr.id, score] for spkr, score in conservatives_to_all_conservatives.averages_by_speaker().items()]\n",
    "\n",
    "conservatives_to_all_democrats = demcoord.summarize(dems_filtered, conservatives, everyone)\n",
    "conservatives_to_all_democrats_scores = [ [spkr.id, score] for spkr, score in conservatives_to_all_democrats.averages_by_speaker().items()]\n",
    "\n",
    "democrats_to_all_democrats = demcoord.summarize(dems_filtered, democrats, everyone)\n",
    "democrats_to_all_democrats_scores = [ [spkr.id, score] for spkr, score in democrats_to_all_democrats.averages_by_speaker().items()]\n",
    "\n",
    "democrats_to_all_conservatives = concoord.summarize(cons_filtered, democrats, everyone)\n",
    "democrats_to_all_conservatives_scores = [ [spkr.id, score] for spkr, score in democrats_to_all_conservatives.averages_by_speaker().items()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import ttest_rel\n",
    "import pandas as pd\n",
    "\n",
    "cS = pd.DataFrame(conservatives_to_all_conservatives_scores)\n",
    "cS.columns = [\"speaker\",\"conservative\"]\n",
    "\n",
    "cSd = pd.DataFrame(conservatives_to_all_democrats_scores)\n",
    "cSd.columns = [\"speaker\",\"democrat\"]\n",
    "\n",
    "cS_cons = cSd.merge(cS, on =\"speaker\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_relResult(statistic=2.589778372688268, pvalue=0.004894067128607459)"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ttest_rel(cS_cons.conservative, cS_cons.democrat, alternative='greater')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "dS = pd.DataFrame(democrats_to_all_democrats_scores)\n",
    "dS.columns = [\"speaker\",\"democrat\"]\n",
    "\n",
    "dSc = pd.DataFrame(democrats_to_all_conservatives_scores)\n",
    "dSc.columns = [\"speaker\",\"conservative\"]\n",
    "\n",
    "cS_dems = dSc.merge(dS, on =\"speaker\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_relResult(statistic=3.561291807833982, pvalue=0.0002008173358550846)"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ttest_rel(cS_dems.democrat, cS_dems.conservative, alternative='greater')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot( cS_cons.conservative, label='conservatives to conservatives', kde=True, color = \"#d62728\");\n",
    "sns.histplot( cS_cons.democrat, label='conservatives to democrats', kde=True, color = \"#9467bd\");\n",
    "plt.legend()\n",
    "plt.title(\"Linguistic coordination of r/Conservative users to users in r/Conservative and r/democrats\")\n",
    "plt.xlabel(\"Linguistic coordination\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot( cS_dems.democrat, label='democrats to democrats', kde=True, color =   \"#1f77b4\" );\n",
    "sns.histplot( cS_dems.conservative, label='democrats to conservatives', kde=True, color = \"#9467bd\");\n",
    "plt.legend()\n",
    "plt.title(\"Linguistic coordination of r/democrats users to users in r/Conservative and r/democrats\")\n",
    "plt.xlabel(\"Linguistic coordination\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### More in-depth linguistic coordination analysis \n",
    "code for make_chart function from \"https://github.com/CornellNLP/ConvoKit/blob/master/examples/coordination/examples.ipynb\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import matplotlib.patches as mpatches\n",
    "def make_chart(a_scores, b_scores, a_description, b_description, a_color=\"b\", b_color=\"g\"):\n",
    "    # get scores by marker and on aggregate\n",
    "    a_score_by_marker = a_scores[\"marker_agg2\"]\n",
    "    a_agg1, a_agg2, a_agg3 = a_scores[\"agg1\"], a_scores[\"agg2\"], a_scores[\"agg3\"]\n",
    "    b_score_by_marker = b_scores[\"marker_agg2\"]\n",
    "    b_agg1, b_agg2, b_agg3 = b_scores[\"agg1\"], b_scores[\"agg2\"], b_scores[\"agg3\"]\n",
    "\n",
    "    # the rest plots this data as a double bar graph\n",
    "    a_data_points = sorted(a_score_by_marker.items())\n",
    "    b_data_points = sorted(b_score_by_marker.items())\n",
    "    a_data_points, b_data_points = zip(*sorted(zip(a_data_points, b_data_points),\n",
    "        key=lambda x: x[0][1], reverse=True))\n",
    "    labels, a_data_points = zip(*a_data_points)\n",
    "    _, b_data_points = zip(*b_data_points)\n",
    "\n",
    "    labels = [\"aggregate 1\", \"aggregate 2\", \"aggregate 3\"] + list(labels)\n",
    "    a_data_points = [a_agg1, a_agg2, a_agg3] + list(a_data_points)\n",
    "    b_data_points = [b_agg1, b_agg2, b_agg3] + list(b_data_points)\n",
    "\n",
    "    fig, ax = plt.subplots()\n",
    "    ax.set_xticks(np.arange(len(a_data_points)) + 0.35)\n",
    "    ax.set_xticklabels(labels, rotation=\"vertical\")\n",
    "\n",
    "    ax.bar(np.arange(len(a_data_points)), a_data_points, 0.35, color=a_color)\n",
    "    ax.bar(np.arange(len(b_data_points)) + 0.35, b_data_points, 0.35, color=b_color)\n",
    "\n",
    "    b_patch = mpatches.Patch(color=\"b\",\n",
    "                             label=a_description + \" (total: \" +\n",
    "                             str(a_scores[\"count_agg1\"]) + \", \" +\n",
    "                             str(a_scores[\"count_agg2\"]) + \")\")\n",
    "    g_patch = mpatches.Patch(color=\"g\",\n",
    "                             label=b_description + \" (total: \"  +\n",
    "                             str(b_scores[\"count_agg1\"]) + \", \" +\n",
    "                             str(b_scores[\"count_agg2\"]) + \")\")\n",
    "    plt.legend(handles=[b_patch, g_patch])\n",
    "\n",
    "    filename = str(a_description) + \" vs \" + str(b_description) + \".png\"\n",
    "    plt.savefig(filename, bbox_inches=\"tight\")\n",
    "    print('Created chart \"' + filename + '\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Created chart \"Conservative-coservative vs Conservative-democrat.png\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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o6CiTyaSnnnpKr7/+uiIjIy2rE/KTyWTS888/r4YNG0q68UHPokWL9OOPP6pIkSK6cuWKOnbseNv3tm/fXj4+PpKkIUOGaNGiRTp58qQl6JYpU0Y7d+78V2vOM7geP35cVapUsTrm7e2tY8eOWR07ceKEvLy8rIKpt7e3ZVnx77//ruzsbL366qs6d+6cnnjiCY0cOTLHuaUbN8LfOuUuybLWHwAAAPbn6+urwoULa/v27Tl2P/3oo4/0559/asGCBTKZTDp//rzKlCkj6cZ9i2azWaVKldLJkydve/74+HiVLFlS4eHhSklJ0YYNGzR8+HDVq1dPHh4e6tixowYPHmxpf/r0aauwcmswcnJyUlBQkL7//nudOXPGMtsaFxdn+aH72WeflSSNHz8+xwY1ualSpYp8fHy0efNm/fDDD1q6dKmkG6HwySef1LfffmtpGxcXJwcHB3l4eGj//v1W5ylbtqzVz7mXLl3SwoUL1aBBA8XHx8tsNlt2Zz179qxKly6tjIwMnTx5UmPHjpWLi4t+//13DRkyRF9++aX8/PxUqlQp7dixw3LOm4Ext7GRpJYtW6pt27aqU6eOqlatagmQ7733nipXrqzZs2fL2dlZv//+uyIiIvIcG+lGsP/+++/l6empoKAgOTo6qnjx4nJxcdGyZcvk7e0t6cbqzrNnz6pSpUo5zuHo6Gi5b/LvSpcufcevrb8bOHCgWrdurS+//FKOjo764YcfLLPMdyslJUUzZsxQly5dLF9r6enpcnZ21pEjR3TmzBn169dPkixLr2vVqqU5c+YoKytLkydPtnwocPPab72nND95e3tbbQwl/X/N69at08GDB1W7dm1JN677p59+0qFDh/T555/L29vbKqtlZWXl+BAgKytLTk5O/2rNeS4Vvn79ugoXLmx1zNXVNccSgWvXruXa7uY/EkdHRz311FOaOXOmtm7dqscee0zdu3fPdanBwoUL1bhxY6tf7OAGAABgHCaTSUOGDNGYMWMUGRmpjIwMXb9+XQsWLNCqVavUt29fy2xeaGioLl++rOTkZE2YMEG+vr6qWLHiHc9/4sQJdevWTceOHZOrq6tKlSolk8kkV1dXhYSEaPny5Tpw4ICys7O1a9cuBQUF6dChQ7c9X8uWLbVp0ybt27fPcv/hzaWsN3+G3bVrl1avXm3ZmdVkMslsNistLfedlkNCQjR16lQ98sgjliBWv359nTlzRitWrFBGRobOnj2rt956yyrI3qpFixZatGiRTp06JbPZrJkzZ+r333/X008/rbJlyyo0NFRpaWk6c+aMPvvsM7Vo0UJOTk4aOXKkwsPDlZmZKU9PTzk6OqpYsWJ6+umn5ebmptmzZ8tsNishIUF9+vTRp59+etuxqVKliipXrqzp06crODjYcvzmzLmjo6Pi4+MVGhoqSZbxcXFxUVJSUq7nbN68uX755Rdt2rTJ8kHBzQ8QPv74Y125ckVms1kffvjhbe8n9fT0tFrOezPAJyUl5fm1dWtb6cbfdeHCheXo6Kg///xTs2fPtvkZr66urtq5c6emTp2q1NRUy5i0bNlStWrV0sGDBxUdHa3o6Gh98803kqTo6GjVqlVLjz32mOLi4rRgwQJlZmZq3759+u6773Js4pRfQkJCtH//fq1evdpyj/bRo0fVuHFjzZ8/X/v377dcS/369dWjRw99/vnnkm5sfPX111/ryJEjMpvN+vjjj+Xj46NHH33Ucv74+Hh5enr+qzXnGVyLFCmS4x9rSkpKjiW/ebXr3r27Pv74Y3l6esrV1VWDBw/W1atXcyR9SerYsaMiIyOtfn399dc2XxwAAADunTZt2mjUqFH6/PPPVbduXdWvX1/btm3T/PnzLc9xHTFihKpUqaLg4GA1aNBATk5OmjlzZp7nDggIUM+ePdWzZ0/VqFFDkydP1rRp01S8eHHVrl1bo0aN0qhRo/Tss8/q/fff19ixY62Wx/6dj4+PypYtq3r16llmuapUqaIBAwaoa9euql27tqZNm6Z27drpxIkTlmfSPvbYY/L397d6HudNzZs318WLFy3BTLqxMc28efO0cuVKBQQEqF27dgoMDFSfPn1yrat169Zq27atunbtqrp16yo2NlaTJk2Si4uLPv/8c506dUrPP/+83njjDTVp0kT9+/eXg4ODPvnkE23evFm1a9dWs2bNVKdOHbVp00Ymk0lz587VwYMH9fzzz6tZs2by8fHRmDFj7jjeLVu21MWLF602FXr33Xe1Y8cO1axZU23btlXt2rVVokQJy8rLVq1a6YMPPrBsmnWrYsWKqW7duipXrpzVCsuRI0fK09NTwcHBqlu3rk6fPq2wsLBcZ+cCAgL03//+1/LnMmXKqGHDhmrWrJm2bdt2x6+tv7edMGGCFi1aJF9fX/Xo0UNBQUFKT0+37Mfz97/X2+0qPHPmTCUkJOj5559XixYtVK1aNb3zzjt3HFvpxrLiuXPnatOmTfLz89OYMWM0fvz4u3recUxMjHx9ff/VR0xVr15dYWFhWrhwoWrVqqXZs2drxowZ8vLyyvO9b7zxhnr37q23335b/v7++uOPPzRr1iyrmfwDBw7oueee+9fqlSSH7DwWd//0008aPXq0tm3bZjnWrl07hYSEqE2bNpZjJ0+eVFBQkKKjoy2fWg0ZMkTlypXToEGDFB4erieffNKy3j8jI0M1a9bUV199ddubrm917tw5NW7cWJGRkapQocI/uVYAAADDO3z4sB577DGrYx3e35Bvz3ItXrSQvnr/5XzpC7iT2NhYBQcHa8uWLZbHxjyoQkND1aRJk7vKTfaWkJCgZs2aadOmTbddCp3b97m85HmPq7+/v7KzsxUeHq727dtr06ZNOnr0qJo0aWLVztvbW9WrV9e0adM0ePBg7du3T5GRkZZlEefPn9eaNWs0Z84cubu76+OPP1blypX1xBNP2FQwANwNc3qmTC7/7r0V9uwHwIONIIkHkaenp5o3b66VK1fqzTfftHc5dnPt2jUlJCTkeNyNUS1dulTt2rX71+/fzXPGVZKOHTum9957T0eOHFGFChU0cuRIBQQEaM2aNXrvvfcsN5nf3A56//79KlGihAYNGmRZbpCWlqbJkydr06ZNun79uvz8/PTee+/d9QN2mXEFYKsWg1ff8z7Whgbn3QgAbPBPZiKAgiopKUmdO3dWeHj4P35cDPJPQkKCevfurS+//FKFChW6bbt/8n3uroKrERBcAdiK4ArgfkRwBVDQ/ZPvc3luzgQAAAAAgD0RXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAIDbOHv2rL1LuK9kZmbqwoULd90+MTFRiYmJ/3pbFDzO9i4AAAAAd9Z99Tv6KzV/fmAvVthdYcEf3nX7n376SfPnz9fhw4eVnZ2tatWqqX///vLz87uHVeaPw4cPq0uXLtq1a5ckqVu3bmrYsKHat29/z/q8+QjIvXv3yt3d/Z71c68MGjRIvr6+6tSpU66vZ2ZmqlOnTvrwww9Vrlw5vfTSS/riiy/u6lrvtq0tY3jx4kW9//772rNnjxwcHNSgQQONHj1aRYsWtWp34MABvfHGG9q4caMqVKig6Ohode/e3aqN2WxWhQoVtHHjxjv2OWbMGK1du9bq2PXr1zVw4ED16tVLhw8f1vjx43X48GF5eHiob9++atGiRY7zfPHFF1q0aJG2bNkiSbpy5Yr69u2r8PBwmUymO9ZwP2LGFQAAwODyK7Ta2tfy5cs1bNgwvfnmm/rpp5+0Y8cOBQUFqUePHoqOjr6HVeaPxMREpaenW/48b968expaC4KEhIQ7vh4eHq5nn31W5cqVu6v2tpz7nxg1apTc3d31008/acuWLbp48aI++eQTqzbXrl3TsGHDlJGRYTlWq1Yt7d+/3/Jr/fr1Kl68uEaPHp1nn2PHjrV679ChQ+Xj46M333xTycnJ6t69u5555hnt2rVLM2fOVGhoqH7++Wercxw5ciRHnSVKlFBgYKBmzZr1P4yIcRFcAQAAYLOUlBRNnjxZ48aNU2BgoEwmk0wmk1577TX17NlTp06dknTjh/6xY8eqXr16qlu3roYOHWoJICtWrFDnzp01YsQI1axZU4GBgVqyZImlj7lz5+qFF16Qv7+/2rdvr4MHD1pei4yMVFBQkGrVqqW2bdvq999/t7xWrVo1jR07Vn5+fpo0aZKeeeYZHT582Oq9jRo1UnZ2to4ePaouXbqoXr16euaZZ9SxY0fFxMTo8uXL6t69u5KSkuTr66u4uDh16NBB4eHh+vnnn1WnTh2rIDNp0iQNHz5cknT8+HF16tRJtWvX1ssvv5xjdu1WWVlZmjp1qvz9/fXcc89pxYoVVq/f6VwdOnTQZ599ppCQENWoUUM9evTQwYMH9eqrr8rX11fdunVTcnKyJOnSpUsaMmSI6tSpo+eff17jx49XSkqKJCk7O1thYWFq0KCBatasqW7duik2NlaS1KhRI40ZM0Z16tTRsGHDlJ2drZkzZ6pp06by9fXVCy+8oPDwcEnShAkTFB0drY8//lhjx47Nca2pqamaP3++Xn/9dUlSq1atJElt27bV+vXrlZGRoU8//VT169eXv7+/evXqpXPnzuXa1mw2a/z48XrxxRdVo0YNNWnSROvWrct1jLt166YxY8bk+tqMGTP0wQcfqHDhwkpKSlJKSoqKFy9u1eZmP3cycuRIBQUFqV69ends93dnzpzRRx99pNDQULm5uemXX35RZmamhgwZokKFCsnHx0dvvPGGvv32W8t7UlNTNXTo0Fw/RGnVqpUWL16sq1ev2lTH/YDgCgAAAJvt379fZrNZ9evXz/Fa79699dprr0m6sSzyjz/+0KpVq7Rp0yalpaVp6NChlrY7d+7UM888o6ioKPXs2VMTJkxQYmKiDh06pPnz52vp0qXatWuX/Pz8NHXqVEnSr7/+qiFDhmjEiBHavXu32rVrpy5duljd/5icnKwdO3aof//+CgwMtAp8ERERCg4OloODgwYMGKC6devqxx9/1E8//aSsrCyFhYWpVKlSCgsLU9GiRbV//36VLVvW8v6AgAAVKlTIMguWlZWl9evXKzg4WNeuXVPnzp31/PPPa+fOnZoyZYomTZp02xnoxYsXKyIiQsuWLdPGjRv122+/WV67m3N98803mjFjhrZt26YjR47oP//5j6ZOnaqtW7fqzJkzWrlypSSpX79+ysjI0ObNm7Vy5UodPnxYkyZNkiQtXbpUX3/9tebOnavdu3erXLlyGjlypKWP06dPa+vWrRo9erQiIiK0evVqhYeHa9++fXrvvfc0ZcoUxcfH691331WtWrU0ZMiQXINiZGSkKlasqPLly0uSJaQvWbJEzZo104wZM7Rp0yYtWrRIP/74oypUqKBevXopPT09R9svvvhChw4d0rJly7Rv3z699dZbGjNmjNWHCTfNmzcv1yAtyfKBy6BBg9SwYUMlJyfrjTfesLy+YcMGnTlzRl27ds31/ZK0efNmHT9+XG+//fZt29zO5MmT9frrr6t69eqSbnyIUKhQITk6/n9Mc3Jy0unTpy1/njJliho1aqRnn302x/mKFy+up5566rYh/n5GcAUAAIDNEhISVKxYMbm4uNy2TVpamjZu3KghQ4aodOnScnNz0+jRo7Vjxw7FxcVJksqUKaO2bdvK2dlZISEhMpvNunDhgh566CFdu3ZNK1as0IkTJ9S/f3/LzN7y5csVFBSkgIAAOTs7Kzg4WJUrV9aGDRssfTdr1kwmk0lubm4KCQnR+vXrlZ2dreTkZG3dulUhISGSpLCwMHXq1Enp6emKjY1ViRIlFB8ff8drd3R0VFBQkCUMR0VFycnJSXXq1NH27dvl5uamrl27ysXFRU8//bRat26txYsX53qu9evX680331SlSpXk5uam//znP5bX7uZcrVq1UsWKFVW8eHE9/vjjaty4sSpVqqTixYurRo0aOnfunM6cOaP9+/dr1KhRcnNzU+nSpTV06FCtXLlSWVlZWrt2rd58801VrVpVLi4uGjp0qNWHCy+99JJcXV1VtGhRNWzYUF9//bXKli2rS5cuycXFRZmZmXe1jDcqKkpPPfXUbV9ftWqV+vTpo4oVK6pQoUIaNmyYYmJirGbab2rbtq1mz54td3d3xcfHy9XVVcnJyZZZZFtNmjRJe/bs0cMPP6z+/ftLkuLi4jRlyhR9+OGHVkHy7z777DP16NFDhQsXtqnPY8eOaefOnVb3ytasWVPp6emaO3euzGazjh8/rm+//VZpaWmSbnxNHDhwQP369bvteZ955hnt3bvXplruB2zOBAAAAJuVKVNGV69eVXp6eo7wmpSUpEKFCumvv/5Senq65X7Gm+8zmUyWnWdLlSplee3mebKysvTII49o1qxZWrBggT777DOVKlVKffv21WuvvaaYmBhFRUVZzSplZGQoJibG8mcPDw/L7+vWravMzExFR0fr/Pnzql69uipXrixJOnTokHr27KmkpCQ9+uijSklJUcmSJfO8/pCQEL366qtKSUnRmjVrLDO458+f15kzZ1SrVi1L28zMTD3xxBM5NvQJCwvTpUuX5OnpaTlWoUIFy+/vdK6bSpQoYfm9o6Oj1WZEjo6OysrK0uXLl2UymVS6dGnLa+XLl5fZbNbly5d16dIlq7+jokWL6rHHHst1LDMyMjRp0iTt3LlTHh4eevrppyXdmCnMS2xsrNW1/N3ly5et6jCZTPLw8LAsW75VcnKyxo4dqwMHDqh8+fJ65JFH7rqO3BQqVEiFChXS0KFD9eKLL+rKlSsaNmyYBgwYoAoVKtx2N+MjR47o+PHjatmypc19fvfdd2rcuLHV30vRokUVFhamiRMnav78+apatapCQkK0detWXb58WR988IHCwsLu+IFRmTJltHPnTpvrMTqCKwAAAGzm6+urwoULa/v27QoMDLR67aOPPtKff/6pBQsWyGQy6fz58ypTpoykG7NYZrNZpUqV0smTJ297/vj4eJUsWVLh4eFKSUnRhg0bNHz4cNWrV08eHh7q2LGjBg8ebGl/+vRpqwDg4OBg+b2Tk5OCgoL0/fff68yZM5bZ1ri4OA0ZMkSLFi2yLLscP368VQC+nSpVqsjHx0ebN2/WDz/8oKVLl0q6EfKefPJJq3sS4+Li5ODgIA8PD+3fv9/qPB4eHjp//rxV21tfu925bFGuXDmZzWZdvHjR8vdw9uxZubi4qFixYipbtqxVOLx06ZIWLlyogQMHSrIey6lTpyotLU3bt29X4cKF9ddff2n58uV3VYejo+Mdg2W5cuV0/vx51ahRQ9KNXXrj4uKsPty46b333lPlypU1e/ZsOTs76/fff1dERMRd1XGr1q1ba+jQoapTp46lT2dnZ12/fl379u3Tb7/9pvHjx1vqDgoK0gcffGDZ5TcyMlIvvPCC3NzcbO47MjLSakn2zf4zMzO1aNEiy7HQ0FA98cQT2rFjhy5fvqw2bdpIuvEhQmpqqmrVqqU1a9ZYQn9WVpacnJxsrsfoWCoMAAAAm5lMJsu9jJGRkcrIyND169e1YMECrVq1Sn379rUsqQ0NDdXly5eVnJysCRMmyNfXVxUrVrzj+U+cOKFu3brp2LFjcnV1ValSpWQymeTq6qqQkBAtX75cBw4cUHZ2tnbt2qWgoCAdOnTotudr2bKlNm3apH379qlZs2aSbszaZWdnW5Z47tq1S6tXr7bsJGwymWQ2my3LNP8uJCREU6dO1SOPPCJvb29JUv369XXmzBmtWLFCGRkZOnv2rN566y2r8HmrVq1aadGiRTpx4oSuXbum6dOnW16z9Vy3U7ZsWQUEBGjixIlKTk7WpUuXFBoaqpdeekkmk0ktWrTQokWLdOrUKZnNZs2cOVO///57rstjb86mOzk56a+//tLEiRMlyWrMbm4I9Xeenp45lmG7uLgoKSnJMp6fffaZzp49q7S0NE2ZMkUlSpSwfKhwa9ubdTg6Oio+Pl6hoaFWddytJ554QjNmzNDVq1d15coVffjhhwoODlb58uX166+/Kjo6WtHR0dq6daskac2aNVaPpjlw4ECu95rmJSEhQWfPns3x3szMTHXs2FEbN25UVlaWoqKitHTpUrVt21bBwcE6cOCApaaPP/5Y5cqVU3R0tNVMdXx8vNUsfkFBcAUAAMA/0qZNG40aNUqff/656tatq/r162vbtm2aP3++5TmuI0aMUJUqVRQcHKwGDRrIyclJM2fOzPPcAQEB6tmzp3r27KkaNWpo8uTJmjZtmooXL67atWtr1KhRGjVqlJ599lm9//77Gjt2rGXWLDc+Pj4qW7as6tWrZ1lOW6VKFQ0YMEBdu3ZV7dq1NW3aNLVr104nTpywPJP2sccek7+/v44ePZrjnM2bN9fFixctM7jSjc1x5s2bp5UrVyogIEDt2rVTYGCg+vTpk2tdLVu21BtvvKEOHTqoUaNGlk16/sm57uTjjz+Wo6OjmjRpoubNm8vHx8eyYVHr1q3Vtm1bde3aVXXr1lVsbKxl46a/e/vtt3XhwgX5+fmpRYsWKlGihKpVq6Zjx45Jklq0aKEvvvjCajb8poCAgBwzzq+++qq6d++ub775Rt27d1dgYKDeeustBQQE6PTp05ZZ+7+3fffdd7Vjxw7VrFlTbdu2Ve3atVWiRAlLHbe6067Cw4cPV5UqVdS0aVO1aNFCDz/88F090uam8+fPWy2lvmnNmjXy9fW97fvOnTsnk8mUYwdjV1dXzZgxQzNnzlTNmjU1ceJETZkyxerrIi8HDhzQc889d9ft7xcO2f90IXg+u/kg4cjISKu1/wBwOy0Gr77nfawNDb7nfQB4sBw+fNjq/kJJ6r76nXx7lmuxwu4KC/4wX/rCgyUlJUWNGzfWt99+m+eMe0HQqVMny4Zi+SUhIUHNmjXTpk2brO53Nprcvs/lhXtcAQAADI4giYLA1dVVXbt21TfffKN33nnH3uXcU/v371eDBg3yvd+lS5eqXbt2hg6t/xRLhQEAAADki44dO+rAgQNWG1IVRL6+vurUqVO+9pmQkKCtW7eqV69e+dpvfmHGFQAAAEC+cHZ21jfffGPvMgqkkiVL2rxx1/2EGVcAAAAAgKERXAEAAAzmPtk7EwBs9k+/vxFcAQAADMTFxUUpKSn2LgMA7omUlBS5uLjY/D6CKwAAgIF4eHjo/Pnzun79OjOvAAqM7OxsXb9+/bbPvs0LmzMBAAAYyM3HWMTExCg9Pd3O1QDAv8fFxUVly5b9R4/rIbgCAAAYjLu7e4F8DiMA/FMsFQYAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwBAAAAAIZGcAUAAAAAGBrBFQAAAABgaARXAAAAAIChEVwB4H9gzkwvkH0BAAAYibO9CwCA+5nJyUWvf9s7X/pa2uazfOkHAADAaJhxBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAY2l0F1yNHjqhNmzaqUaOGWrRooYMHD+baLiYmRp07d5avr68CAwO1ffv2XNt98cUXatSo0T+vGgAAAADwwMgzuJrNZvXp00dNmzbV3r171atXL3Xt2lXJyck52g4aNEjVqlVTVFSUxo0bp4EDB+rs2bNWbY4cOaJPPvnk37sCAAAAAECBlmdw3bNnj9LT09WpUye5uLioefPm8vHx0fr1663anTp1SocOHdKAAQNkMpkUEBCgRo0aafny5ZY2qampGjp0qNq3b//vXwkAAAAAoEByzqvB8ePHVaVKFatj3t7eOnbsmNWxEydOyMvLS0WKFLFqd+uy4ilTpqhRo0Z66qmntGHDhtv2mZiYqMTERKtjsbGxeZUKAAAAACiA8gyu169fV+HCha2Oubq6KiUlxerYtWvXcm2XmpoqSdq+fbsOHDigJUuW3Pbe15sWLlyomTNn3tUFAAAAAAAKtjyDa5EiRZSWlmZ1LCUlxWpmNa92ly9f1gcffKCwsDC5uLjkWVTHjh3VsmVLq2OxsbEsMQYAAACAB1CewbVKlSoKDw+3Onby5EmFhITkaBcTE6PU1FTLzOvJkyfl4+OjHTt26PLly2rTpo0kKSMjQ6mpqapVq5bWrFmjcuXKWZ3L3d1d7u7u/8NlAQAAAAAKijw3Z/L391d2drbCw8OVnp6udevW6ejRo2rSpIlVO29vb1WvXl3Tpk2T2WzW7t27FRkZqVdeeUXBwcE6cOCAoqOjFR0drY8//ljlypVTdHR0jtAKAAAAAMCt8gyuJpNJYWFh2rhxo/z8/DRnzhzNmjVLJUuW1Jo1a+Tr62tpO2PGDJ04cUIBAQEaNWqUJkyYoKpVq97TCwAAAAAAFGx5LhWWpKpVq2rx4sU5jgcFBSkoKMjyZy8vL82bNy/P8wUGBiowMNCGMgEAAAAAD6o8Z1wBAAAAALAngisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAAAAADA0gisAAAAAwNAIrgAAAAAAQyO4AgAAAAAMjeAKAJA5PbNA9QMAAAoWZ3sXAACwP5OLk1oMXn3P+1kbGnzP+wAAAAUPM64AAAAAAEMjuAIAAAAADO2uguuRI0fUpk0b1ahRQy1atNDBgwdzbRcTE6POnTvL19dXgYGB2r59u+W1a9euacSIEfL391fNmjXVp08fxcbG/jtXAQAAAAAosPIMrmazWX369FHTpk21d+9e9erVS127dlVycnKOtoMGDVK1atUUFRWlcePGaeDAgTp79qwkKTQ0VPHx8frhhx+0c+dOFS1aVO+///6/fkEAAAAAgIIlz+C6Z88epaenq1OnTnJxcVHz5s3l4+Oj9evXW7U7deqUDh06pAEDBshkMikgIECNGjXS8uXLJUkjR47UrFmz5O7urmvXrunatWsqUaLEvbkqAAAAAECBkeeuwsePH1eVKlWsjnl7e+vYsWNWx06cOCEvLy8VKVLEqt3NZcXOzs5ydnZWaGiowsLC5OHhoa+++irXPhMTE5WYmGh1jGXFAAAAAPBgyjO4Xr9+XYULF7Y65urqqpSUFKtj165dy7Vdamqq1bF+/fqpT58++uijj9S1a1d9//33cnFxsWqzcOFCzZw506YLAQAAAAAUTHkG1yJFiigtLc3qWEpKitXMqi3tChUqJEl65513tGTJEh07dkxPPPGEVZuOHTuqZcuWVsdiY2PVvn37vMoFAAAAABQwed7jWqVKFZ06dcrq2MmTJ+Xj45OjXUxMjNUM663t+vXrp1WrVlleS09PV3Z2ttzd3XP06e7urgoVKlj98vT0tOnCAAAAAAAFQ57B1d/fX9nZ2QoPD1d6errWrVuno0ePqkmTJlbtvL29Vb16dU2bNk1ms1m7d+9WZGSkXnnlFUnS008/rc8//1wXLlzQ9evXNWHCBPn5+alixYr35soAAAAAAAVCnsHVZDIpLCxMGzdulJ+fn+bMmaNZs2apZMmSWrNmjXx9fS1tZ8yYoRMnTiggIECjRo3ShAkTVLVqVUlS165d9eKLL+r1119X48aNlZmZqenTp9+zCwMAAAAAFAx53uMqSVWrVtXixYtzHA8KClJQUJDlz15eXpo3b16u53ByctLAgQM1cODAf1gqAAAAAOBBlOeMKwAAAAAA9kRwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXP9F5vTMAtkXAAAAANiTs70LKEhMLk5qMXh1vvS1NjQ4X/oBAAAAAHtjxhUAABuwugYAgPzHjCsAADZgdQ0AAPmPGVcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQDkG3NmeoHsCwAA3FvO9i4AAPDgMDm56PVve+dLX0vbfJYv/QAAgHuPGVcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsH1PmXOTC9Q/QAAAADA7TjbuwD8MyYnF73+be973s/SNp/d8z4AAPg3mDPTZXJyKTD9AAD+H8EVAAAUCHyoCwAFF0uFAQAAAACGRnAFAAAAABgawRUAAAAAYGgEV9iNOT2zQPYFAAAA4N/F5kywG5OLk1oMXp0vfa0NDc6XfgAAAAD8+5hxBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhnZXwfXIkSNq06aNatSooRYtWujgwYO5touJiVHnzp3l6+urwMBAbd++3fJaSkqKxowZo3r16snPz0+9e/dWTEzMv3MVAAAAAIACK8/gajab1adPHzVt2lR79+5Vr1691LVrVyUnJ+doO2jQIFWrVk1RUVEaN26cBg4cqLNnz0qSQkNDdebMGa1du1Y//vijSpcurUGDBv37VwQAAAAAKFDyDK579uxRenq6OnXqJBcXFzVv3lw+Pj5av369VbtTp07p0KFDGjBggEwmkwICAtSoUSMtX75ckpSWlqZ+/fqpRIkSKly4sNq3b68DBw4oIyPj3lwZAAAAAKBAcM6rwfHjx1WlShWrY97e3jp27JjVsRMnTsjLy0tFihSxandzWfG4ceOs2m/evFmPPvqonJ1zlpCYmKjExESrY7GxsXmVCgAAAAAogPIMrtevX1fhwoWtjrm6uiolJcXq2LVr13Jtl5qamuOc69at0/z58zV37txc+1y4cKFmzpyZZ/EAAMDYzOmZMrk42bsMAMB9Ls/gWqRIEaWlpVkdS0lJsZpZvdt22dnZmjVrlhYuXKhZs2apdu3aufbZsWNHtWzZ0upYbGys2rdvn1e5AADAQEwuTmoxeHW+9LU2NDhf+gEA5L88g2uVKlUUHh5udezkyZMKCQnJ0S4mJkapqamWmdeTJ0/Kx8dHkpSenq5hw4bp119/1TfffKNHH330tn26u7vL3d3dxksBAAAAABREeW7O5O/vr+zsbIWHhys9PV3r1q3T0aNH1aRJE6t23t7eql69uqZNmyaz2azdu3crMjJSr7zyiiRp4sSJOnLkiJYuXXrH0AoAAAAAwK3yDK4mk0lhYWHauHGj/Pz8NGfOHM2aNUslS5bUmjVr5Ovra2k7Y8YMnThxQgEBARo1apQmTJigqlWrKjExUUuWLNHZs2fVuHFj+fr6Wn4lJSXd0wsEAAAAANzf8lwqLElVq1bV4sWLcxwPCgpSUFCQ5c9eXl6aN29ejnbu7u46fPjw/1AmAABAwZefm1mxcRaA+8ldBVcAAADce2xmZVzmzHSZnFwKTD/A/YbgCgAAAOTB5OSi17/tfc/7Wdrms3veB3A/yvMeVwAAAAAA7IngCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrcJ8wp2cWqH4AAACAu+Vs7wIA3B2Ti5NaDF59z/tZGxp8z/sAAAAAbMGMKx4I5sz0AtUPAAAA8CBhxhUPBJOTi17/tvc972dpm8/ueR8AAADAg4YZVwAAAACAoRFcAQAAcF9iQ0HgwcFSYQAAANyX8mvjQonNCwF7Y8YVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAMChzZnqB7AsAAFs527sAAACQO5OTi17/tne+9LW0zWf50g8AAP8EM64AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAADAA8icmV6g+gFQsDnbuwAAAADkP5OTi17/tvc972dpm8/ueR8ACj5mXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBFcAAAAAgKERXAEAAAAAhkZwBWDFnJleIPsCAADA/cvZ3gUAMBaTk4te/7Z3vvS1tM1n+dIPAAAA7m/MuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAPAHN6ZoHqBw8WZ3sXAAAAAODeM7k4qcXg1fe8n7Whwfe8Dzx4mHEFAAAAABgawRUAAAAAYGh3FVyPHDmiNm3aqEaNGmrRooUOHjyYa7uYmBh17txZvr6+CgwM1Pbt23O0ycrKUt++fRUeHv4/FQ4AAAAAeDDkGVzNZrP69Omjpk2bau/everVq5e6du2q5OTkHG0HDRqkatWqKSoqSuPGjdPAgQN19uxZy+vnzp1Tr169tHnz5n/3KgAAAAAABVaewXXPnj1KT09Xp06d5OLioubNm8vHx0fr16+3anfq1CkdOnRIAwYMkMlkUkBAgBo1aqTly5dLkq5du6bWrVurevXq8vX1vTdXAwAAAAAocPLcVfj48eOqUqWK1TFvb28dO3bM6tiJEyfk5eWlIkWKWLW7uay4UKFCWr9+vUqVKqUOHTrcsc/ExEQlJiZaHYuNjc2rVAAAAABAAZRncL1+/boKFy5sdczV1VUpKSlWx65du5Zru9TU1BsdOTurVKlSd1XUwoULNXPmzLtqCwAAAAAo2PIMrkWKFFFaWprVsZSUFKuZVVva3Y2OHTuqZcuWVsdiY2PVvn17m88FAAAAALi/5Rlcq1SpkmMH4JMnTyokJCRHu5iYGKWmplpmXk+ePCkfHx+bi3J3d5e7u7vN7wMAAAAAFDx5bs7k7++v7OxshYeHKz09XevWrdPRo0fVpEkTq3be3t6qXr26pk2bJrPZrN27dysyMlKvvPLKPSseAAAAAFDw5RlcTSaTwsLCtHHjRvn5+WnOnDmaNWuWSpYsqTVr1ljtEDxjxgydOHFCAQEBGjVqlCZMmKCqVave0wsAAAAAABRseS4VlqSqVatq8eLFOY4HBQUpKCjI8mcvLy/Nmzcvz/N99dVXNpQIAAAAAHiQ5TnjCgAAAACAPRFcAQAAAACGRnAFAAAAABgawRUAAAAAYGgEVwAAAACAoRFcAQAAAACGRnAFAAAAABgawRUAAAAAYGgEVwAAAACAoRFcAQAAAOBvzOmZBaqf+52zvQsAAAAAAKMxuTipxeDV97yftaHB97yPgoAZVwAAAACAoRFcAQAAAACGRnAFAAAAABgawRUAAAAAYGgEVwAAAACAoRFcAQAAAACGRnAFAAAAABgawRUAAAAAYGgEVwAAAACAoRFcAQAAAACGRnAFAAAAABgawRUAAAAAYGgEVwAAAACAoRFcAQAAAACGRnAFAAAAABgawRUAAAAAYGgEVwAAAACAoRFcAQAAAACGRnAFAAAAABgawRUAAAAAYGgEVwAAAACAoRFcAQAAAACGRnAFAAAAABgawRUAAAAAYGgEVwAAAACAoRFcAQAAAACGRnAFAAAAABgawRUAAAAAYGgEVwAAAAD/GnNmeoHsC/blbO8CAAAAABQcJicXvf5t73zpa2mbz/KlH9gfM64AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwNIIrAAAAAMDQCK4AAAAAAEMjuAIAAAAADI3gCgAAAAAwtLsKrkeOHFGbNm1Uo0YNtWjRQgcPHsy1XUxMjDp37ixfX18FBgZq+/btlteys7M1bdo0BQQEqFatWpo4caIyMjL+nasAAAAAABRYeQZXs9msPn36qGnTptq7d6969eqlrl27Kjk5OUfbQYMGqVq1aoqKitK4ceM0cOBAnT17VpL07bff6ocfftDKlSu1adMm/frrr5ozZ86/f0UAAAAAgAIlz+C6Z88epaenq1OnTnJxcVHz5s3l4+Oj9evXW7U7deqUDh06pAEDBshkMikgIECNGjXS8uXLJUmrVq1Sx44d5enpqZIlS6p///769ttv781VAQAAAAAKDOe8Ghw/flxVqlSxOubt7a1jx45ZHTtx4oS8vLxUpEgRq3Y3lxX//Tze3t6Kj4/X1atXVbx4catzJSYmKjEx0epYbGzs3V0RAAAAAKBAccjOzs6+U4PZs2fr4MGDVst6x48fr5SUFE2YMMFybPXq1Zo3b57Wrl1rObZgwQJt375d4eHhevzxx7Vs2TI98cQTkqSrV6/K399f27dvl6enp1WfM2bM0MyZM3OtJzIyUhUqVLD9SvOBOT1TJhen/OkrwyyTs+ne95OZLpOTy705N+Nl27nzabzya6wkxsvmvhgv2/q6R+NVEL93SYyXTf0UgH+LEuNlc1+M1933UwC+d0mMl9HkOeNapEgRpaWlWR1LSUmxmlm9m3aurq5KTU21vHbz938/jyR17NhRLVu2tDoWGxur9u3b51WuXeXXN05J+fbFfS+/sBkvG8+dT+OVX2MlMV4298V42dbXPRqvgvi9S2K8bOqnAPxblBgvm/tivO6+nwLwvUvKx68vB4f86ec+l+c9rlWqVNGpU6esjp08eVI+Pj452sXExFiF01vb+fj4WJ3n5MmTKlOmjNzd3XP06e7urgoVKlj9+vusLAAAAADc7/JzBvR+nW2V7iK4+vv7Kzs7W+Hh4UpPT9e6det09OhRNWnSxKqdt7e3qlevrmnTpslsNmv37t2KjIzUK6+8IkkKCgrSF198ofPnzyshIUEzZsxQcHDwvbkqAAAAAECBkWdwNZlMCgsL08aNG+Xn56c5c+Zo1qxZKlmypNasWSNfX19L2xkzZujEiRMKCAjQqFGjNGHCBFWtWlWS1K5dO7388stq27atXnrpJfn4+Ojtt9++d1cGAAAAACgQ8tycySjOnTunxo0bG3pzJgAAAADAvy/PGVcAAAAAAOyJ4AoAAAAAMDSCKwAAAADA0AiuAAAAAABDI7gCAAAAAAyN4AoAAAAAMDSCKwAAAADA0AiuAAAAAABDI7gCAAAAAAyN4AoAAAAAMDSCKwAAAADA0AiuAAAAAABDI7gCAAAAAAyN4AoAAAAAMDSCKwAAAADA0AiuAAAAAABDc7Z3AXcrMzNTkhQbG2vnSgAAAAAA94Knp6ecnXPG1PsmuF68eFGS1L59eztXAgAAAAC4FyIjI1WhQoUcxx2ys7Oz7VCPzVJTU3Xo0CGVKVNGTk5O9i7nvhMbG6v27dvr66+/lqenp73LMTzGyzaMl20Yr7vHWNmG8bIN42Ubxss2jJdtGC/bFOTxuu9nXAsXLqxatWrZu4z7nqenZ66fYCB3jJdtGC/bMF53j7GyDeNlG8bLNoyXbRgv2zBetnmQxovNmQAAAAAAhkZwBQAAAAAYGsEVAAAAAGBoBNcHhLu7u/r16yd3d3d7l3JfYLxsw3jZhvG6e4yVbRgv2zBetmG8bMN42Ybxss2DOF73za7CAAAAAIAHEzOuAAAAAABDI7gCAAAAAAyN4AoAAAAAMDSCKx54y5Yt0/Dhw/Xll1/KbDZbvTZ48GA7VWVcmzdv1t69eyVJn376qYKDg9WhQwetXbvWzpXdf5KTk+1dAgAAwH3B2d4F4N91Nz8Iu7m55UMl94dZs2Zp5cqVCgwM1JIlS7RmzRotWLBARYsWlSRt3brVzhUay+zZs/XNN98oOztbAQEBOnTokLp27Sqz2azp06fr+vXratOmjb3LNBw/Pz/t2bPH6lh2drbq16+vX375xU5V3R8yMjLk7Mx/VbnZvn276tevr8jIyNu2cXJyUsmSJfXUU0/JwcEhH6u7P5jNZplMJnuXgQIkNTVVq1at0p9//qmsrCyr10aMGGGnqowtOjpatWrV0sWLF/Xpp5+qWLFi6tOnj4oUKWLv0gznt99+07p16xQfH6/y5csrODhY3t7e9i4r37CrcAHj5+enpKSkXF/Lzs6Wg4ODDh8+nM9VGVejRo20YMECVa5cWWazWYMHD9aVK1cUHh4uZ2dn+fr6av/+/fYu0zAaNGigr776SleuXFGbNm20ceNGVapUSZJ0/Phx9e3bVxs3brRzlcZw7tw5DRgwQNnZ2Tp69KiqVatm9fq1a9fk5OSk77//3k4VGldKSopCQ0MVERGhv/76S6VLl9arr76qPn36yMXFxd7lGcYrr7yiiIgINWrU6I7tEhISVK9ePc2cOTOfKjO2rKwsff7551q8eLGSkpK0Zs0avfvuu5o+fbpKlixp7/IMZ//+/Zo8eXKuQezvH8hBGjhwoH755Rf5+fnl+H41adIkO1VlXFOmTNH69eu1bds29e7dW0lJSXJxcVHZsmU1efJke5dnKKtWrdL777+vwMBAeXl5KSYmRlu2bNG0adPUoEEDe5eXL/gYu4D57rvv1L59e/Xv319169a1dzmGl5SUZAleJpNJoaGheuuttzR69Gj+g8lFUlKSKlasqIoVK6p06dLy9PS0vPbwww8rISHBjtUZS4UKFTRgwAAlJCTo/fff11tvvWX1uslkUu3ate1UnbFNmDBBp06d0tSpU+Xp6anz589r1qxZun79OjMWt4iIiJAkbdmy5Y7tYmNj1bRp0/wo6b7wySefaM+ePZo4caIGDhyokiVLqlixYho7dqymT59u7/IMZ9y4cXrsscf09ttvs/rhLuzcuVMrV65UuXLl7F3KfWHz5s369ttvde3aNf3000+KiIhQmTJl8vxA7kE0Z84czZs3T7Vq1bIc27lzpyZMmEBwxf2pYsWKGjNmjD766CO9+uqrLA3LQ7Vq1bR48WK98cYbkm6EiRkzZui1117TlClT7Fyd8fj4+GjZsmV67bXX9NNPP1mOp6amavr06apRo4b9ijOgm/+RPProo3rqqafsW8x9ZMuWLdqwYYPloere3t56/PHHFRQURHC9jZMnT+rMmTPKzMy0HHNwcFCjRo3k4eGhBQsW2LE6Y1mzZo2WLVum0qVLy8HBQQ899JAmTZqkxo0b27s0Qzp16pSWLFnCkuq75ObmZvnehbxdvXpVZcuWVWRkpMqWLauHH35Y6enpOWb3cWPy4JlnnrE6VqtWLV24cMFOFeU/gmsBFBgYqL/++ktXrlxh2VMehg8frl69emnXrl2aMWOGJKlMmTKaN2+eunTpotTUVDtXaCzDhw9X79691bx5c6t7T4KCglSoUCHNnj3bjtUZ16OPPqolS5Zwz9NdKlGihK5fv271w19mZiY/ON/GzJkzNWvWLJUpU8ZqRuxmcHV0dORDpVukp6dbvn/dvFvK0dGR2cTbePLJJ3Xs2DE9+eST9i7lvtCpUycNHDhQnTt3zvEzWPXq1e1UlXFVq1ZN06ZNU1RUlBo3bqzk5GRNnz6dD3tz8eqrr2rq1KkaNGiQXFxclJWVpblz5yo4ONjepeUb7nHFAy81NVUXLlzQI488YnU8MTFRq1evVocOHexUmTHltpnJn3/+qUqVKjHDfxvc83R3bm4ytGfPHv3888/q2bOnvLy8dOnSJc2dO1fPPfccO33nokGDBpowYYKee+45e5dyXxgxYoRSU1M1evRovfzyy9qxY4cmTpyo5ORkffzxx/Yuz3DGjRunVatWqUGDBipdurTVa3zwltPtwil7jOTuzJkzmjhxoooWLar33ntPR44c0bRp0zR58mRVrFjR3uUZQu3ateXg4KCsrCwlJyfL1dVVpUuX1pUrV5ScnKyKFSvqhx9+sHeZ+YLgCgD3mL+/P/c83YW87mlycHC44w66Dyp/f3/t3LlTTk5O9i7lvpCYmKhhw4Zp27Ztkm7svOzn56fQ0FBWKeXiTuGUD97wb2KX79zdzSZofn5++VCJ/RFcAeAea9y4sVavXs2jqO5Sbrsw4/Y++ugjmUwm9e7dmx/6bHD58mWdP39eZcuWVdmyZe1dDgqQs2fPav369bpw4YJKly6tpk2bqkqVKvYuy5BSUlL04Ycfat26dUpOTlbx4sXVsmVLDRw4kF3k/+att97S7NmzH+ifJQiuAHCPffXVV/rxxx+55+ku1alTR5GRkXrooYfsXcp94ZVXXtHx48fl6OiY4wcaHlfy/+5mtp4NmnLKysrSvHnz9N133yk2NlalSpVSUFCQ+vfvzyx/Lvbs2aOePXuqZs2aKl++vM6dO6fo6GjNnj2b5fy5GD58uM6ePat+/fqpbNmyll3kn3rqKb377rv2Ls9Q6tWrpw0bNhBc7V0EABRk3PNkm3bt2qlfv378kHeX7hROH5TlY3eDpej/zMyZM/X999+rb9++Kl++vM6cOaM5c+boxRdf1Ntvv23v8gzn9ddfV6dOndSsWTPLsXXr1mn+/PlasWKFHSszptq1a2vz5s0qVqyY5djly5fVrFkzRUVF2bEy4xkxYoQOHjyoBg0ayMPDw2pfkb8/cq+gIrgWYGvWrNHixYt18eJFLVq0SJ988onee+89FS5c2N6lGRLjZRvGC/dKu3bt9N///lclSpTI8Z/zypUr7ViZcWVmZurgwYOWpYnPPvssu+TepezsbDaWu4PGjRsrPDzcaqOcM2fOqH379laPRcMNtWvXVlRUlBwdHS3HsrKyVKtWLe3bt8+OlRlT48aN9eWXX6p8+fKWYxcvXtSbb76pjRs32rEy47ndZqEODg768ssv87ka++B/tQIqPDxc3377rTp16qSPPvpIhQsX1unTpzVx4kSNHTvW3uUZDuNlG8bLdpcuXdLly5ctj99IT0/XH3/8oVatWtm5MuN5/fXX9frrr9u7jPvG+fPn1atXL8XExMjDw0NxcXEqWbKkFixYwK6cuYiLi9PIkSM1dOhQVa9eXdOmTdPvv/+uDz/8UKVKlbJ3eYaTnJwsT09Pq2Oenp4ym812qsjYPD099csvv6h27dqWY9HR0WzOdxutW7dWt27d1KtXL1WqVElxcXGaO3eu/P39rVZAsIz/xm1HDzpmXAuoF198UfPmzVOlSpXk5+enPXv2KCEhQa+88op27txp7/IMh/GyDeNlm4ULF2rKlCmWZ7jenOGpVq2aVq1aZd/iDCw9PV0xMTGqVKmSJDErdht9+vRR+fLlNWzYMLm4uMhsNmvKlCk6c+aM5s6da+/yDKdHjx7y9PTUsGHD5ObmpsuXL2vGjBmKj4/nWdS56NWrlx555BENGTJETk5OysjIUGhoqE6ePKnPP//c3uUZzrp16zR69GgFBwerXLlyOn/+vNauXatx48ZZLR/GDXkt4ZdYxn+rX375RUuWLFFcXJymTp2qJUuWqG/fvg/M/4/MuBZQiYmJ8vLykvT/D1h3c3Oz/OAMa4yXbRgv2yxYsEAzZsyQs7OzNm3apGHDhmnChAk8euM2UlNTNW7cOK1cuVImk0nfffed+vTpo3nz5jGDmIt9+/Zp+vTplh04TSaThg4dyj3Ct7F//37t3r3bsrFQqVKlNHLkSNWrV8/OlRnTyJEj1aVLFy1fvlxlypRRfHy8ypYtqzlz5ti7NENq3ry5ihUrpjVr1mj37t0qV66cPv/8c9WqVcvepRnSli1b7F3CfSMiIkKTJ09Wq1attGXLFmVlZWnt2rUym80aNGiQvcvLF455N8H9qFatWvr444+VlZVl+RRm/vz5qlGjhn0LMyjGyzaMl20SExPVqFEjPf744/r111/l7u6ukSNH6vvvv7d3aYY0ceJEJSYmKiIiQi4uLqpUqZLq1aunDz74wN6lGVLhwoV18eJFq2Px8fFyd3e3U0XG5ubmptOnT1sdi4mJUdGiRe1TkMGlpqZq/fr1+vTTT9W3b1/NnTtXq1ev5kOk23jrrbdUo0YNTZkyRfPnz9e4ceMIrXk4e/aspk+frhEjRuivv/5iJdJtzJ49W3PmzNGgQYPk6OgoDw8PzZs374Ha+4EZ1wJq9OjR6tWrl/z8/HT9+nW98MILcnNzY1nPbTBetmG8bOPp6amLFy+qTJkyio2Nldls1kMPPaTExER7l2ZIW7ZssWz57+DgIBcXF73zzjvMiN1Gq1at1KtXL/Xt21flypXTuXPn9NlnnykkJMTepRnSG2+8oe7du+vNN9+Ul5eX4uLitGjRIrVr187epRnSW2+9pcjISAUEBNi7lPvCyZMn7V3CfWXXrl0aMGCAXnjhBW3dulX9+vXThx9+qKtXr6pTp072Ls9QLl26pMcff1zS/986U65cOaWlpdmzrHxFcC2gypYtq++++06//vqrZcOOp59+moc53wbjZRvGyzbNmjXTm2++qa+//lrPPfecBg0apEKFCqlq1ar2Ls2QnJ2dLRu/3FyKfv36dbm6utqzLMPq27evLly4oDFjxiglJUXZ2dnq27evevToYe/SDKl79+5yd3dXRESELl26pLJly6p3795q3bq1vUszpEceeUT//e9/WXp+l55//nm1adPmgX5kiS0++ugjffLJJ6pbt65q166t8uXL64svvlDfvn0Jrn/zxBNP6Msvv7QalzVr1qhatWr2KyqfsTlTARUSEpLrUouGDRtq69at+V+QwTFetmG8bBcREaGGDRtaNjZJTk7W22+/rcqVK9u7NMOZNGmSfv/9dw0dOlRdu3bVsmXL9NFHH8nLy0ujRo2yd3mG88MPP2jIkCFavHixHn/8cYWHh2vmzJkKDQ1V/fr17V0e7nM8nso2PLLENrVq1dKePXvk6Oho2ewxOztbtWvXVnR0tL3LM5Tjx4+rS5cuKlq0qP788089+eSTOnv2rObNm6fHHnvM3uXlC4JrAXLu3Dl9+OGHys7O1rZt29SgQQOr15OSknT69Glt377dPgUaDONlG8YL+eXmrrjLly9XamqqTCaTgoKCNHLkSBUpUsTe5RlO06ZNNWbMGKulnLt27dKECRMUERFhx8qMZfDgwQoNDb3jDpwzZ87M56qM707htGXLlvlYCQqiNm3aqGPHjmrWrJkluP7444+aMWOGli1bZu/yDOf69evatm2bZbVb/fr1VaxYMXuXlW9YKlyAVKhQQQEBAUpISNC2bdtUvXp1q9dNJpPeffddO1VnPIyXbRivfy4kJOS2PygzY5FTZmamRo0apVGjRikhIUHFixeXoyN7Cd5ObGys/P39rY75+/srNjbWThUZ082l+Q/KzMS/5WY4/euvv3T58mV5eHjIzc3NzlUZ2/r167Vu3TpdunRJnp6eatWqFasfbmPYsGHq0aOHVq1apZSUFA0ePFg//vijPv30U3uXZjgjRoxQy5YtH+jHKjHjWkBt2rRJL774or3LuG8wXrZhvGzz93B65coVrVy5UsHBwerWrZudqjIuX19fvfzyywoODladOnXsXY7htW3bViEhIWrbtq3l2Hfffadly5ZpyZIldqzMmL7//ns1bdo0x/ElS5ZYjSFuSEhI0DvvvKOff/5ZWVlZcnZ2VuPGjTVhwgQCbC7mzp2rhQsX6rXXXpOnp6diYmK0bNkyDRw4UK+//rq9yzOk2NhYrV271jKL2KxZM26jycWkSZP0/fffy9nZWUFBQQoJCdHDDz9s77LyFcG1gMrMzNTmzZsVHx9v2dwkPT1df/zxhyZPnmzn6oyH8bIN4/W/i4mJUZ8+fdj2PxdHjx5VRESE1q1bp+zsbAUFBSk4OFje3t72Ls2Q9u/frx49esjT01NeXl6KjY1VXFycwsLC9PTTT9u7PENISkrS+fPnJd24Z3PJkiW69cef5ORkde/eXfv377dXiYbVu3dvmUwmDR48WJ6enjp37pymTp2qIkWKaMqUKfYuz3Dq1aunL774wmrzvcOHD6tv3748szQXb731lmbPns2HIHcpOztbu3fv1tq1a/XDDz/I29tbISEhD8yu6CwVLqDGjBmjLVu2qESJEkpLS5Obm5uOHj2qV155xd6lGRLjZRvG639XtGhRnTt3zt5lGFK1atVUrVo1DR48WNHR0YqIiFCHDh1Uvnx5LV261N7lGY6vr682btyobdu2WXbJrV+/vooXL27v0gylS5cuSkhIkCQFBwdbvebi4qJXX33VHmUZ3p49e/Tzzz+rcOHCkiRvb29NnjxZDRs2tHNlxpSenp7jGbdVqlSx7JQOazw+yDYODg4KCAjQs88+q7p162rq1KmaNGkSwRX3t82bN2vZsmW6fPmywsPD9cknn+irr77Snj177F2aITFetmG8bPP3nSTT09P1ww8/qEaNGvYp6D5x/fp1nT9/3vLsWy8vL3uXZFglS5ZUq1at7F2GYRUtWlQ7d+6UdOO5tytWrLBzRfcPLy8vnT592mpfg5v3biKn7t27a9iwYXr33Xfl6emphIQEffzxxwoKClJycrKlHTOMN/D4oLuXlZWlHTt2KCIiQpGRkfLx8VG3bt3UvHlze5eWbwiuBVilSpVUsmRJHT58WNKN+6DmzJlj56qMi/GyDeN193744QerPzs5Oal69erq06ePnSoytsjISEVERGjr1q2qXr26goODNWXKFLm7u9u7NBQAbm5uSk5OJjjcpQYNGqhr16564403VLlyZcXFxenrr7/Ws88+a/WhHCHjhk8//VRms1k//PCDnJ2dlZGRYXltwYIFys7OloODg+X/zgfduXPnVLJkSf3666+WYzfHiK8pa88995wKFy6sFi1aaNmyZQ/k7TME1wKqYsWK2r9/v3x9fZWSkqJLly7J2dlZaWlp9i7NkBgv2zBetgkMDLR8inzzP2RJ2rBhg1U7/pO+Yfz48QoKCtLKlSv1yCOP2LscFDAsTbTNgQMH5O3traioKEVFRUmSypcvr7i4OMuHcoQMWT4MudPtDEWLFs3Hiu4PX331ldavX6+IiAhdunRJXl5eatmyZY5H7kEKDQ1VQEBAjqcUpKamWpbyF3QE1wKqe/fu6tKliyIiItS6dWu1a9dOjo6Oev755+1dmiExXrZhvGyzd+9ebdmyRdWqVVPFihV18eJF7d+/X48//rgeeughSfzgd6stW7bc9vFBwP+KpYm2IVjcnRdeeEH79u3L9fFnzLLeXlhYmBYuXKhXX31VL7zwgmJiYjRy5Ej95z//YRfmv/nqq6/0+OOPW+1fsH//fg0fPlwbN260X2H5iF2FC7Cb24o7OzsrIiJCycnJatmypQoVKmTv0gyJ8bIN43X3BgwYoICAAKvNEzZs2KCIiAjNnDnTjpUZy52ed3sTz73F/6pDhw65HndwcMhxPzqsg8XNx7ssX76cYPE3Fy5ckJeXl2X36tyUL18+Hyu6P7AL8937z3/+o19++UUffvih/Pz89Omnn+rLL79Ut27d1K9fP3uXly8IrgVUTExMrsddXFxUrFgxmUymfK7I2Bgv2zBetvH19VV0dLScnJwsxzIzM1W3bl3L0jv8fyg9dOiQtm/frg4dOqhChQqKjY3Vl19+qYYNG2r48OF2rhL3u4yMDG3evFkXL160PBLHbDbr+PHjPM4rFwQL3Ev+/v7atm2bXF1dLcfMZrMaNWqkHTt22LEyY1qzZo0mTpyohx56SGXKlNH48ePl4+Nj77LyDUuFC6gmTZooKytLkvU9dZLk6OgoPz8/ffjhh/Lw8LBXiYbCeNmG8bJNxYoVtXbtWoWEhFiOLVmyRFWqVLFfUQbUsmVLSTdmeBYsWGD1SIn69eurU6dOBFf8z9577z1t2bJFJUuWVGpqqtzc3HTs2LEHamdOW/B4F9xL7MJsmytXrigjI0Ourq5KSkqyGqMHATOuBdSCBQu0d+9eDRs2TOXKldOFCxc0bdo0Va5cWUFBQQoLC1NSUpJmzZpl71INgfGyDeNlm127dqlfv34qX768ZaldUlKS5s2bp0cffdTe5RlOzZo1tWPHDqtP4BMTE9WwYUP98ssvdqwMBYG/v/9tH+c1Y8YMe5dnOPPmzdOBAwdyBIvixYtb7YxOsMA/8fTTT8tsNsvBwUFOTk7KzMy0rIRwcHDg/uBbvPbaa7p8+bImT54sPz8/y/evV199Ve+++669y8sXBNcCqmHDhlq3bp2KFCliOXb9+nU1a9ZM27ZtU2pqqp5//nnt3bvXjlUaB+NlG8bLdgkJCdq6dasSEhJUvnx5NWjQwGr88P/69++v9PR0vf322ypbtqzOnz+v6dOnq1SpUpoyZYq9y8N9zt/fX1FRUUpOTlarVq20adMmpaenq0GDBvr555/tXZ7hECxwL93pnuBbcX+wNGLECL377rtWHxKdOHFC77zzjpYvX27HyvIPS4ULqLS0NF26dEmVKlWyHLt48aJSUlIk3bi/zsXFxV7lGQ7jZRvGy3YlS5ZU69at7V3GfWH8+PEaM2aMXnvtNWVmZspkMql58+YaPXq0vUtDAcDjvGzz/fff27sEFGAE0rs3adKkHMeqVKlyx0cwFTQE1wLqjTfeUOfOndWhQweVLVtWsbGx+vrrr9WuXTtdvHhRQ4cOVePGje1dpmEwXrZhvHAvubm5qVmzZqpZs6ZSUlLk6OgoR0dHffDBB2yeg/8Zj/OyDcECMIY77bz/oOy4z1LhAmz58uVau3at4uLi5OXlpVatWqlFixY6cuSIfvzxR3Xq1IndX2/BeNmG8cK9MnLkSG3dujXXzXM+/vhje5eHAuDWx3mtW7dOSUlJPM4LgKH9PZxevXpVK1asUHBwsLp162anqvIXwbWAS09P1/nz51WpUiU5ODjk+YzEBx3jZRvGC/cCm+cAAJC3mJgY9enTR6tWrbJ3KfnC0d4F4N5ISUnRqFGj9MwzzygkJESnT5/Wyy+/rLNnz9q7NENivGzDeOFeq1Spkh599FHLhi9t27bVvn377FwVAADGUbRoUZ07d87eZeQbgmsBNXnyZP3111+KiIiQi4uLKlasqHr16umDDz6wd2mGxHjZhvHCvXRz8xw3NzfL5jnXrl1j8xwAwAPryy+/tPo1f/58de/eXTVq1LB3afmGzZkKqMjISG3YsEFubm5ycHCQi4uL3nnnHdWrV8/epRkS42Ubxgv3EpvnAABg7YcffrD6s5OTk6pXr271POWCjuBaQDk7O8tsNkuS5Xlr169fl6urqz3LMizGyzaMF+6ll156SU899ZQ8PDz0n//8R48++qhl8xwAAB5ECxYs0ObNm3Xx4kXLz17p6emaOnXqA7PjPsG1gHrppZf09ttva+jQoZKk06dP66OPPlKTJk3sXJkxMV62Ybxwr5UrV87y++bNm9uxEgAA7O+9997Tli1bct1x/0HBrsIFlNls1pQpU7R8+XKlpqbKZDIpKChII0eOVJEiRexdnuEwXrZhvAAAAPIPO+4TXAusH3/8UXXq1JHJZFJCQoKKFy8uR0f24rodxss2jBcAAED+8ff3V1RUlJKTk9WqVStt2rRJ6enpatCggX7++Wd7l5cv+EmzgLq5hFOSSpYsSajIA+NlG8YLAAAg/7DjPsG1wHr22We1evVqpaSk2LuU+wLjZRvGCwAAIP/c3HH//Pnzlh3327Rp80DtuM9S4QLqpZde0p9//ikHBwfLI0tu2rNnjx0rMybGyzaMFwAAQP6KiYmRh4eHnJ2dtW7dOsuO+4UKFbJ3afmC4FpA3Sk8+Pn55WMl9wfGyzaMFwAAAPITwRUAAAAAYGg8x7WAql69utXyzZucnZ1VokQJvfDCCxo+fLjc3NzsUJ3xMF62YbwAAACQn5hxLaDmzZunzZs3q3///vLy8lJsbKw+++wzPfnkkwoICNDChQvl4eGhSZMm2btUQ2C8bMN4AQAAID8RXAuoF198UUuWLFHJkiUtx65cuaI2bdpo06ZNSkxMVJMmTRQVFWXHKo2D8bIN4wUAAID8xONwCqirV6/q759JZGZm6vLly5KkwoUL26Msw2K8bMN4AQAAID9xj2sB9corr6hHjx7q3bu3PDw8FBsbq7lz56p58+ZKSkrSuHHj5O/vb+8yDYPxsg3jBQAAgPzEUuECKiMjQ7NmzdLatWsVFxcnLy8vtWrVSl27dtXhw4f13XffadCgQSpWrJi9SzUExss2jBcAAADyE8EVAAAAAGBoLBUuoDp06JDr40pcXFwsjysJCgqyQ2XGxHjZhvECAABAfmJzpgLqySef1LFjx+Tr66tmzZrp2Wef1cmTJ1WiRAl5enoqNDRUc+bMsXeZhsF42YbxAgAAQH5iqXAB9dprr+mDDz7Q448/bjl27NgxjRo1SkuXLtXp06fVqVMnbdu2zX5FGgjjZRvGCwAAAPmJGdcC6uTJk3r00Uetjj388MM6fvy45fdJSUn2KM2QGC/bMF4AAADITwTXAsrX11cffPCBEhMTJd147ub48eP19NNPKysrS998802O4PEgY7xsw3gBAAAgP7FUuICKj4/XwIED9csvv6hw4cJKS0tT3bp1NWHCBJ06dUpjx47V1KlT9dhjj9m7VENgvGzDeAEAACA/EVwLuAsXLlies1m2bFl7l2N4jJdtGC8AAADkB4JrAZWZmanNmzcrPj5eN/+K09PT9ccff2jy5Ml2rs54GC/bMF4AAADITzzHtYAaPXq0tm7dqhIlSigtLU1ubm46evSoXnnlFXuXZkiMl20YLwAAAOQngmsBFRkZqWXLluny5csKDw/XJ598oq+++kp79uyxd2mGxHjZhvECAABAfmJX4QKsUqVKevTRR3X48GFJUtu2bbVv3z47V2VcjJdtGC8AAADkF4JrAVWxYkXt379fbm5uSklJ0aVLl3Tt2jWlpaXZuzRDYrxsw3gBAAAgP7FUuIDq3r27unTpooiICLVu3Vrt2rWTo6Ojnn/+eXuXZkiMl20YLwAAAOQndhUuwGJiYuTh4SFnZ2etW7dOSUlJatmypQoVKmTv0gyJ8bIN4wUAAID8QnAFAAAAABga97gCAAAAAAyN4AoAAAAAMDSCKwAAAADA0AiuAAAAAABDI7gCAAAAAAzt/wAdHaGE5kPZLgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# do speakers on the whole coordinate more to admins or nonadmins?\n",
    "make_chart(\n",
    "    concoord.summarize(cons_filtered, conservatives, everyone,focus=\"targets\", summary_report=True),\n",
    "    demcoord.summarize(dems_filtered, conservatives, everyone,focus=\"targets\", summary_report=True),\n",
    "    \"Conservative-coservative\", \"Conservative-democrat\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Created chart \"Democrat-coservative vs Democrat-democrat.png\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "make_chart(\n",
    "    concoord.summarize(cons_filtered, democrats, everyone,focus=\"targets\", summary_report=True),\n",
    "    demcoord.summarize(dems_filtered, democrats, everyone,focus=\"targets\", summary_report=True),\n",
    "    \"Democrat-coservative\", \"Democrat-democrat\"\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.7 ('ml')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "db00b3a626384bec78137815b78dbfa3868ae3c424ba9ba9cfb25bba6eee4913"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}