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회귀 분석을 통한 2017 대선 지지율 예측
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 지지율 회귀분석"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.dates as mdates\n",
"import matplotlib.font_manager as fm\n",
"import seaborn as sns\n",
"import statsmodels.api as sm\n",
"from mpl_toolkits.mplot3d import Axes3D\n",
"from collections import OrderedDict\n",
"from scipy.stats import boxcox_normplot, boxcox\n",
"\n",
"font_location = \"/Library/Fonts/NanumGothic.otf\"\n",
"font_name = fm.FontProperties(fname=font_location).get_name()\n",
"mpl.rc('font', family=font_name)\n",
"\n",
"sns.set_style(\"white\")\n",
"\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 테마주 종가"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"## http://estenpark.tistory.com/353 참고 (거의 그대로 가져옴)\n",
"\n",
"import urllib\n",
"import time\n",
"import sys\n",
"from urllib import urlopen\n",
"from bs4 import BeautifulSoup\n",
"\n",
"class NaverStockCrawler(object):\n",
" \"\"\"네이버 금융에서 일별 종가를 읽어오는 클래스\"\"\"\n",
" def __init__(self, stock_item):\n",
" self.stock_item = stock_item\n",
" self.url = 'http://finance.naver.com/item/sise_day.nhn?code='+ stock_item\n",
" self.items = OrderedDict()\n",
" \n",
" def get(self, days=40):\n",
" url = 'http://finance.naver.com/item/sise_day.nhn?code='+ self.stock_item\n",
" html = urlopen(self.url) \n",
" source = BeautifulSoup(html.read(), \"html.parser\")\n",
"\n",
" maxPage=source.find_all(\"table\", align=\"center\")\n",
" mp = maxPage[0].find_all(\"td\", class_=\"pgRR\")\n",
" mpNum = int(mp[0].a.get('href')[-3:])\n",
" pages = days//10 if days%10==0 else days//10 + 1\n",
"\n",
" for page in range(1, pages+1):\n",
" sys.stdout.write(\"\\r* crawling page \" + str(page) + \"...\")\n",
" sys.stdout.flush()\n",
" page_url = self.url +'&page='+ str(page)\n",
" html = urlopen(page_url)\n",
" source = BeautifulSoup(html.read(), \"html.parser\")\n",
" srlists=source.find_all(\"tr\")\n",
" isCheckNone = None\n",
" if((page % 1) == 0):\n",
" time.sleep(1.40)\n",
"\n",
" for i in range(1,len(srlists)-1):\n",
" if(srlists[i].span != isCheckNone):\n",
" date = srlists[i].find_all(\"td\",align=\"center\")[0].text\n",
" price = srlists[i].find_all(\"td\",class_=\"num\")[0].text\n",
" self.items[date] = float(price.replace(\",\", \"\"))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"m1 = NaverStockCrawler(\"018700\") # 바른손 (문재인 테마주 1)\n",
"m2 = NaverStockCrawler(\"118000\") # 우리들휴브레인 (문재인 테마주 2)\n",
"a1 = NaverStockCrawler(\"053800\") # 안랩 (안철수 테마주 1)\n",
"a2 = NaverStockCrawler(\"004770\") # 써니전자 (안철수 테마주 2)\n",
"h1 = NaverStockCrawler(\"013000\") # 세우글로벌 (홍준표 테마주 1)\n",
"h2 = NaverStockCrawler(\"078590\") # 두올산업 (홍준표 테마주 2)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"* crawling page 4..."
]
}
],
"source": [
"[n.get() for n in (m1, m2, a1, a2, h1, h2)];"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 지지율"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from KoPre2017 import NaverPollCrawler"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": [
"poll = NaverPollCrawler()"
]
},
{
"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>Moon</th>\n",
" <th>Ahn</th>\n",
" <th>Shim</th>\n",
" <th>You</th>\n",
" <th>Hong</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>20170430</th>\n",
" <td>42.6</td>\n",
" <td>20.9</td>\n",
" <td>7.6</td>\n",
" <td>5.2</td>\n",
" <td>16.7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170501</th>\n",
" <td>46.0</td>\n",
" <td>19.2</td>\n",
" <td>8.2</td>\n",
" <td>4.8</td>\n",
" <td>17.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170502</th>\n",
" <td>39.3</td>\n",
" <td>21.8</td>\n",
" <td>9.2</td>\n",
" <td>4.9</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170503</th>\n",
" <td>42.4</td>\n",
" <td>18.6</td>\n",
" <td>7.3</td>\n",
" <td>4.9</td>\n",
" <td>18.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170504</th>\n",
" <td>43.2</td>\n",
" <td>21.1</td>\n",
" <td>8.0</td>\n",
" <td>4.8</td>\n",
" <td>20.1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Moon Ahn Shim You Hong\n",
"20170430 42.6 20.9 7.6 5.2 16.7\n",
"20170501 46.0 19.2 8.2 4.8 17.4\n",
"20170502 39.3 21.8 9.2 4.9 16.5\n",
"20170503 42.4 18.6 7.3 4.9 18.6\n",
"20170504 43.2 21.1 8.0 4.8 20.1"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"poll_df = poll.poll_important_df[7:]\n",
"poll_df.columns = [\"Moon\", \"Ahn\", \"Shim\", \"You\", \"Hong\"]\n",
"poll_df.tail()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"m1_df = pd.DataFrame(dict(m1.items), index=[\"stock_m1\"]).T[4:]\n",
"m2_df = pd.DataFrame(dict(m2.items), index=[\"stock_m2\"]).T[4:]\n",
"a1_df = pd.DataFrame(dict(a1.items), index=[\"stock_a1\"]).T[4:]\n",
"a2_df = pd.DataFrame(dict(a2.items), index=[\"stock_a2\"]).T[4:]\n",
"h1_df = pd.DataFrame(dict(h1.items), index=[\"stock_h1\"]).T[4:]\n",
"h2_df = pd.DataFrame(dict(h2.items), index=[\"stock_h2\"]).T[4:]\n",
"for i in [m1_df, m2_df, a1_df, a2_df, h1_df, h2_df]:\n",
" i.index = [j.replace(\".\", \"\") for j in i.index]"
]
},
{
"cell_type": "code",
"execution_count": 9,
"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>Moon</th>\n",
" <th>Ahn</th>\n",
" <th>Shim</th>\n",
" <th>You</th>\n",
" <th>Hong</th>\n",
" <th>stock_m1</th>\n",
" <th>stock_m2</th>\n",
" <th>stock_a1</th>\n",
" <th>stock_a2</th>\n",
" <th>stock_h1</th>\n",
" <th>stock_h2</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>20170430</th>\n",
" <td>42.6</td>\n",
" <td>20.9</td>\n",
" <td>7.6</td>\n",
" <td>5.2</td>\n",
" <td>16.7</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170501</th>\n",
" <td>46.0</td>\n",
" <td>19.2</td>\n",
" <td>8.2</td>\n",
" <td>4.8</td>\n",
" <td>17.4</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170502</th>\n",
" <td>39.3</td>\n",
" <td>21.8</td>\n",
" <td>9.2</td>\n",
" <td>4.9</td>\n",
" <td>16.5</td>\n",
" <td>5730.0</td>\n",
" <td>4975.0</td>\n",
" <td>60200.0</td>\n",
" <td>3325.0</td>\n",
" <td>2180.0</td>\n",
" <td>2520.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170503</th>\n",
" <td>42.4</td>\n",
" <td>18.6</td>\n",
" <td>7.3</td>\n",
" <td>4.9</td>\n",
" <td>18.6</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170504</th>\n",
" <td>43.2</td>\n",
" <td>21.1</td>\n",
" <td>8.0</td>\n",
" <td>4.8</td>\n",
" <td>20.1</td>\n",
" <td>6200.0</td>\n",
" <td>4900.0</td>\n",
" <td>59900.0</td>\n",
" <td>3210.0</td>\n",
" <td>2030.0</td>\n",
" <td>2430.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Moon Ahn Shim You Hong stock_m1 stock_m2 stock_a1 stock_a2 \\\n",
"20170430 42.6 20.9 7.6 5.2 16.7 NaN NaN NaN NaN \n",
"20170501 46.0 19.2 8.2 4.8 17.4 NaN NaN NaN NaN \n",
"20170502 39.3 21.8 9.2 4.9 16.5 5730.0 4975.0 60200.0 3325.0 \n",
"20170503 42.4 18.6 7.3 4.9 18.6 NaN NaN NaN NaN \n",
"20170504 43.2 21.1 8.0 4.8 20.1 6200.0 4900.0 59900.0 3210.0 \n",
"\n",
" stock_h1 stock_h2 \n",
"20170430 NaN NaN \n",
"20170501 NaN NaN \n",
"20170502 2180.0 2520.0 \n",
"20170503 NaN NaN \n",
"20170504 2030.0 2430.0 "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.concat([poll_df, m1_df, m2_df, a1_df, a2_df, h1_df, h2_df], axis=1)\n",
"df.tail()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 구글 트렌드"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from pytrends.request import TrendReq\n",
"from pshinfo import gid, gpw\n",
"pytrend = TrendReq(gid(), gpw())"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"pytrend.build_payload([u\"문재인\", u\"안철수\", u\"홍준표\"], timeframe='today 3-m')\n",
"trend_df = pytrend.interest_over_time()\n",
"trend_df = trend_df[45:]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"trend_df.reset_index(inplace=True)\n",
"trend_df.index = trend_df.date.astype(str).str.replace(\"-\", \"\").values\n",
"del trend_df[\"date\"]"
]
},
{
"cell_type": "code",
"execution_count": 13,
"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>trend_m</th>\n",
" <th>trend_a</th>\n",
" <th>trend_h</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>20170430</th>\n",
" <td>67</td>\n",
" <td>43</td>\n",
" <td>52</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170501</th>\n",
" <td>65</td>\n",
" <td>41</td>\n",
" <td>62</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170502</th>\n",
" <td>70</td>\n",
" <td>40</td>\n",
" <td>86</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170503</th>\n",
" <td>73</td>\n",
" <td>34</td>\n",
" <td>68</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170504</th>\n",
" <td>99</td>\n",
" <td>41</td>\n",
" <td>84</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" trend_m trend_a trend_h\n",
"20170430 67 43 52\n",
"20170501 65 41 62\n",
"20170502 70 40 86\n",
"20170503 73 34 68\n",
"20170504 99 41 84"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trend_df.columns = [\"trend_m\", \"trend_a\", \"trend_h\"]\n",
"trend_df.tail()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"moon_df = pd.concat([poll_df[u\"Moon\"], m1_df, m2_df, trend_df[\"trend_m\"]], axis=1).dropna()\n",
"ahn_df = pd.concat([poll_df[u\"Ahn\"], a1_df, a2_df, trend_df[\"trend_a\"]], axis=1).dropna()\n",
"hong_df = pd.concat([poll_df[u\"Hong\"], h1_df, h2_df, trend_df[\"trend_h\"]], axis=1).dropna()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"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>Moon</th>\n",
" <th>Ahn</th>\n",
" <th>Shim</th>\n",
" <th>You</th>\n",
" <th>Hong</th>\n",
" <th>stock_m1</th>\n",
" <th>stock_m2</th>\n",
" <th>stock_a1</th>\n",
" <th>stock_a2</th>\n",
" <th>stock_h1</th>\n",
" <th>stock_h2</th>\n",
" <th>trend_m</th>\n",
" <th>trend_a</th>\n",
" <th>trend_h</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2017-04-26</th>\n",
" <td>44.3</td>\n",
" <td>26.1</td>\n",
" <td>4.3</td>\n",
" <td>4.6</td>\n",
" <td>14.8</td>\n",
" <td>7360.0</td>\n",
" <td>6870.0</td>\n",
" <td>80100.0</td>\n",
" <td>4615.0</td>\n",
" <td>2475.0</td>\n",
" <td>2730.0</td>\n",
" <td>86.0</td>\n",
" <td>39.0</td>\n",
" <td>68.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-04-27</th>\n",
" <td>44.4</td>\n",
" <td>22.8</td>\n",
" <td>7.5</td>\n",
" <td>5.4</td>\n",
" <td>13.0</td>\n",
" <td>7150.0</td>\n",
" <td>6680.0</td>\n",
" <td>74200.0</td>\n",
" <td>4240.0</td>\n",
" <td>2575.0</td>\n",
" <td>2680.0</td>\n",
" <td>69.0</td>\n",
" <td>40.0</td>\n",
" <td>53.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-04-28</th>\n",
" <td>45.5</td>\n",
" <td>23.7</td>\n",
" <td>6.8</td>\n",
" <td>3.9</td>\n",
" <td>15.3</td>\n",
" <td>6750.0</td>\n",
" <td>6100.0</td>\n",
" <td>72500.0</td>\n",
" <td>4075.0</td>\n",
" <td>2605.0</td>\n",
" <td>2685.0</td>\n",
" <td>64.0</td>\n",
" <td>46.0</td>\n",
" <td>57.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-05-02</th>\n",
" <td>39.3</td>\n",
" <td>21.8</td>\n",
" <td>9.2</td>\n",
" <td>4.9</td>\n",
" <td>16.5</td>\n",
" <td>5730.0</td>\n",
" <td>4975.0</td>\n",
" <td>60200.0</td>\n",
" <td>3325.0</td>\n",
" <td>2180.0</td>\n",
" <td>2520.0</td>\n",
" <td>70.0</td>\n",
" <td>40.0</td>\n",
" <td>86.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-05-04</th>\n",
" <td>43.2</td>\n",
" <td>21.1</td>\n",
" <td>8.0</td>\n",
" <td>4.8</td>\n",
" <td>20.1</td>\n",
" <td>6200.0</td>\n",
" <td>4900.0</td>\n",
" <td>59900.0</td>\n",
" <td>3210.0</td>\n",
" <td>2030.0</td>\n",
" <td>2430.0</td>\n",
" <td>99.0</td>\n",
" <td>41.0</td>\n",
" <td>84.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Moon Ahn Shim You Hong stock_m1 stock_m2 stock_a1 \\\n",
"2017-04-26 44.3 26.1 4.3 4.6 14.8 7360.0 6870.0 80100.0 \n",
"2017-04-27 44.4 22.8 7.5 5.4 13.0 7150.0 6680.0 74200.0 \n",
"2017-04-28 45.5 23.7 6.8 3.9 15.3 6750.0 6100.0 72500.0 \n",
"2017-05-02 39.3 21.8 9.2 4.9 16.5 5730.0 4975.0 60200.0 \n",
"2017-05-04 43.2 21.1 8.0 4.8 20.1 6200.0 4900.0 59900.0 \n",
"\n",
" stock_a2 stock_h1 stock_h2 trend_m trend_a trend_h \n",
"2017-04-26 4615.0 2475.0 2730.0 86.0 39.0 68.0 \n",
"2017-04-27 4240.0 2575.0 2680.0 69.0 40.0 53.0 \n",
"2017-04-28 4075.0 2605.0 2685.0 64.0 46.0 57.0 \n",
"2017-05-02 3325.0 2180.0 2520.0 70.0 40.0 86.0 \n",
"2017-05-04 3210.0 2030.0 2430.0 99.0 41.0 84.0 "
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df2 = pd.concat([poll_df, m1_df, m2_df, a1_df, a2_df, h1_df, h2_df, trend_df], axis=1)\n",
"df2.index = df2.index.to_datetime()\n",
"\n",
"df2.stock_m1 = np.insert(df2.stock_m1.values[1:], 0, np.nan)\n",
"df2.stock_m2 = np.insert(df2.stock_m2.values[1:], 0, np.nan)\n",
"df2.stock_a1 = np.insert(df2.stock_a1.values[1:], 0, np.nan)\n",
"df2.stock_a2 = np.insert(df2.stock_a2.values[1:], 0, np.nan)\n",
"df2.stock_h1 = np.insert(df2.stock_h1.values[1:], 0, np.nan)\n",
"df2.stock_h2 = np.insert(df2.stock_h2.values[1:], 0, np.nan)\n",
"df2.trend_m = np.insert(df2.trend_m.astype(float).values[1:], 0, np.nan)\n",
"df2.trend_a = np.insert(df2.trend_a.astype(float).values[1:], 0, np.nan)\n",
"df2.trend_h = np.insert(df2.trend_h.astype(float).values[1:], 0, np.nan)\n",
"\n",
"df3 = df2.copy()\n",
"df2 = df2.dropna()\n",
"df2.tail()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def plot_diag(df, lm, y_transform=None):\n",
" if y_transform is None:\n",
" y_transform = lambda x: x\n",
" \n",
" influence = lm.get_influence()\n",
" hat = influence.hat_matrix_diag\n",
" cooks_d2, pvals = influence.cooks_distance\n",
" fox_cr = 4. / (df.shape[0] - 2.)\n",
" leverage = np.where(cooks_d2 > fox_cr)[0]\n",
" outlier = np.abs(lm.resid)>2*np.std(lm.resid)\n",
"\n",
" fig = plt.figure(figsize=(9,9))\n",
" ax = fig.add_subplot(221)\n",
" plt.scatter(df.ix[:, 0], y_transform(lm.predict()))\n",
" plt.scatter(df.ix[:, 0][leverage], y_transform(lm.predict())[leverage], s=100, color=\"r\", alpha=.2)\n",
" plt.scatter(df.ix[:, 0][outlier], y_transform(lm.predict())[outlier], s=100, color=\"r\", alpha=.2)\n",
" plt.axis(\"equal\")\n",
" x1, x2, y1, y2 = plt.axis()\n",
" plt.plot([0, 100], [0, 100], \"k:\")\n",
" plt.xlabel(r\"$Y$\")\n",
" plt.ylabel(r\"$\\hat{Y}$\")\n",
" plt.xlim(x1, x2)\n",
" plt.ylim(y1, y2)\n",
" \n",
" ax = fig.add_subplot(222)\n",
" ax.scatter(lm.predict(), lm.resid)\n",
" plt.axhline(0, ls=\"--\", color=\"k\")\n",
" plt.axhline(2*np.std(lm.resid), ls=\":\", color=\"k\")\n",
" plt.axhline(-2*np.std(lm.resid), ls=\":\", color=\"k\")\n",
" plt.xlabel(r\"$\\hat{Y}$\")\n",
" plt.ylabel(r\"Residual\")\n",
"\n",
" ax = fig.add_subplot(223)\n",
" sm.graphics.plot_leverage_resid2(lm, ax=ax)\n",
" \n",
" ax = fig.add_subplot(224)\n",
" sm.graphics.influence_plot(lm, plot_alpha=.3, ax=ax)\n",
" plt.tight_layout();"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 문재인"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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PPJdSeltt+wMRsRn4tZTSW2tlt0TEdmAEuC6ldEUj5SmlR5upkyRJktSILD3R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\nPwl8crg9KmbUn3IxiP6N+jpQZ1Vtt3GOh3FetnFR1jaq07a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"text/plain": [
"<matplotlib.figure.Figure at 0x10228bed0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.pairplot(moon_df);"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: Moon R-squared: 0.992\n",
"Model: OLS Adj. R-squared: 0.991\n",
"Method: Least Squares F-statistic: 2871.\n",
"Date: Sat, 06 May 2017 Prob (F-statistic): 1.70e-26\n",
"Time: 23:24:53 Log-Likelihood: -67.715\n",
"No. Observations: 25 AIC: 137.4\n",
"Df Residuals: 24 BIC: 138.6\n",
"Df Model: 1 \n",
"Covariance Type: nonrobust \n",
"======================================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"--------------------------------------------------------------------------------------\n",
"I(np.log(trend_m)) 9.9620 0.186 53.586 0.000 9.578 10.346\n",
"==============================================================================\n",
"Omnibus: 0.369 Durbin-Watson: 1.278\n",
"Prob(Omnibus): 0.831 Jarque-Bera (JB): 0.486\n",
"Skew: 0.238 Prob(JB): 0.784\n",
"Kurtosis: 2.510 Cond. No. 1.00\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
]
}
],
"source": [
"res_moon = sm.OLS.from_formula(\"Moon ~ 0 + I(np.log(trend_m))\", data=moon_df).fit()\n",
"print res_moon.summary()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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UVFQwcOBArrzyyrhDKmq5fr5ki5kdB1wF/As4FbiTsBXwFuAR4DfpKMfd5wHz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NeGMYZ0epLBwTEmJz3GxsYYHx9nasojCCAIMnjeGIlElmRylKuv7mDbtnPmnf3r++08+OAoExNd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\nqJRSSilVhf4/rySLlzj4s1sAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10228a1d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_diag(moon_df, res_moon)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"## 안철수"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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8S3d+7WGefmVj3fWPHP2GCbgkSZLmKMUccEmSJKkoHAGX1JSJySkGh8YYGR2nt6eL/r5u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\nUoVMwCVJkqQK/X94v43vsVgztAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10ada0f90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.pairplot(ahn_df);"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: I(np.log(Ahn)) R-squared: 0.999\n",
"Model: OLS Adj. R-squared: 0.999\n",
"Method: Least Squares F-statistic: 8381.\n",
"Date: Sat, 06 May 2017 Prob (F-statistic): 8.82e-34\n",
"Time: 23:25:01 Log-Likelihood: 22.514\n",
"No. Observations: 25 AIC: -39.03\n",
"Df Residuals: 22 BIC: -35.37\n",
"Df Model: 3 \n",
"Covariance Type: nonrobust \n",
"=======================================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"---------------------------------------------------------------------------------------\n",
"I(np.log(stock_a2)) 0.1704 0.027 6.350 0.000 0.115 0.226\n",
"trend_a -0.0178 0.005 -3.437 0.002 -0.028 -0.007\n",
"I(np.sqrt(trend_a)) 0.3904 0.070 5.571 0.000 0.245 0.536\n",
"==============================================================================\n",
"Omnibus: 0.848 Durbin-Watson: 1.361\n",
"Prob(Omnibus): 0.655 Jarque-Bera (JB): 0.782\n",
"Skew: -0.383 Prob(JB): 0.676\n",
"Kurtosis: 2.596 Cond. No. 209.\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
]
}
],
"source": [
"res_ahn = sm.OLS.from_formula(\"I(np.log(Ahn)) ~ 0 + I(np.log(stock_a2)) + trend_a + I(np.sqrt(trend_a))\", data=ahn_df).fit()\n",
"print res_ahn.summary()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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pRDpPvRzSnDQWgdcAlwG4+zAAM+sG3Gtmi9x9cZLhJHfCMOR///d/+fjHP04Q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SQJFEKI6LwMfC7RQUxlLpeLFStmsmJFB253JYFA57DP6exsJTW1gpNP9nDooUMnYCtW5BIKjU/X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\nAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10228a190>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_diag(ahn_df, res_ahn, np.exp)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 홍준표"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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qhHGiZjScUKeU3gv8KhDAdKX4NeDaAtqlKm44L0n5sU9VI4wTNaOZEepfAH4k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\n67QPua+oFwvj5KUvOMyLGiUVYkI9Av1eQOP4Pml/nfYh9xX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SLdlDrcW8NiLOpPlX7k4W\n3B5KGoWIOIdmL+F8L8BU6/XvZ6a3xFMtGKcaN8ZsOeyhliRJkgrwokRJkiSpABNqSZIkqQATakmS\nJKkAE2pJkiSpABNqSZIkqQATakmSJKmA/w97Lc6V+kd7UwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10b398cd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.pairplot(hong_df);"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: Hong R-squared: 0.965\n",
"Model: OLS Adj. R-squared: 0.962\n",
"Method: Least Squares F-statistic: 319.6\n",
"Date: Sat, 06 May 2017 Prob (F-statistic): 1.66e-17\n",
"Time: 23:25:07 Log-Likelihood: -52.878\n",
"No. Observations: 25 AIC: 109.8\n",
"Df Residuals: 23 BIC: 112.2\n",
"Df Model: 2 \n",
"Covariance Type: nonrobust \n",
"==============================================================================\n",
" coef std err t P>|t| [95.0% Conf. Int.]\n",
"------------------------------------------------------------------------------\n",
"stock_h1 0.0014 0.000 6.638 0.000 0.001 0.002\n",
"trend_h 0.1603 0.015 10.541 0.000 0.129 0.192\n",
"==============================================================================\n",
"Omnibus: 8.766 Durbin-Watson: 2.017\n",
"Prob(Omnibus): 0.012 Jarque-Bera (JB): 8.108\n",
"Skew: -0.791 Prob(JB): 0.0174\n",
"Kurtosis: 5.297 Cond. No. 109.\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
]
}
],
"source": [
"res_hong = sm.OLS.from_formula(\"Hong ~ 0 + stock_h1 + trend_h\", data=hong_df).fit()\n",
"print res_hong.summary()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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HuPt1wGozG8TGASb9gQuBM9w93MJhREQyTt/Yspna6WBmzRrNtGnjOeOM6XXb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ciS1ZUM6lvK5Ak7aw1jkfy5i6CPXrw6YBXBknN/aOb11gA7Egwqgbg+gs65qcBUa+1x1tqznHN/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\n2+k5/4rcBwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10ff9cfd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_diag(hong_df, res_hong)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"# 지지율 예측"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- Fitted values (모형 예측된 값)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def plot_fit(df, lm, y_transform=None):\n",
" if y_transform is None:\n",
" y_transform = lambda x: x\n",
" plt.figure(figsize=(6,5))\n",
" gs = mpl.gridspec.GridSpec(2, 1, height_ratios=[3, 1])\n",
" ax1 = plt.subplot(gs[0])\n",
" plt.plot(np.arange(df.shape[0]), df.ix[:, 0], \"o-\", label=\"real values\")\n",
" plt.plot(y_transform(lm.predict()), \"o-\", label=\"fitted values\")\n",
" plt.legend(loc=2)\n",
" plt.setp(ax1.get_xticklabels(), visible=False)\n",
" plt.ylabel(u\"지지율\", fontsize=14)\n",
"\n",
" plt.subplot(gs[1], sharex=ax1)\n",
" markerline, stemlines, baseline = \\\n",
" plt.stem(np.arange(df.shape[0]), df.ix[:, 0]-y_transform(lm.predict()))\n",
" plt.setp(baseline, 'color', 'k', 'linewidth', 1.5)\n",
" plt.setp(stemlines, 'color', 'gray', 'linewidth', 1)\n",
" plt.setp(markerline, 'color', 'k', 'markersize', 5)\n",
" plt.ylabel(r\"$Y - \\hat{Y}$\", fontsize=14)\n",
" \n",
" plt.tight_layout();"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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+Aerb+1/dOEtyrIbmNh11/Sj2HOndlJ5tDMhTB9jDcjdycJKR6aa8poVjWRUI\nqeGMSrJe9+JpTCsna6KI+SkzmRQ7FjB+C+9PUeYOtObgZN1TcOqYaEKDfdmbVkKXvqd3nK1AOjx8\n8FOlvTFIBt7vdrG4fdoNdu8rllQ1U9vYzuRR0U7vRaqUKq4TrkCn17E5e6dTYwyE2Smin9Se2RUi\nbsKA46XlVKFUwKSRjqcyXUEOTjIy3Xx3oABJGhwfPVuY2rVX2CjErW9vxFflw4erX+Wl5U97VP1W\nWN5IZKi/zfSmWqVkwZREGpo7Sev+dm1ifspMHp57l1manaCJJUDtz+6CgxwsOu6xOdvDvsIj5NVp\nuTRlJqMj7f9bm1pkTLGzvskWi4fPJdRPw9bc3bR2uta/yxpmjz0rRbL7tUf49eY/kFtbgI9STVr5\nmX7Ham3XIRbWMSo5jOBAX7fPtT9kKbnMRc+eE8V8uj0bbXkTSoUCGLqmeeEaf9QqhVVBRHNHC0UN\npUyMETziBtHjXm06ahramS7Yrn8BY2pv0/58dh8v5pJxsT0em58ys0fwzKst5Pe7XuG1g/8hxE/D\n+BjP1slYo6Ork49ObsRH5cNPJ1/v0LWm+iZn26Cb8FX7co2wlI9ObmRr7m5WjV/u0ni9seVO3rsU\noUPfaf7d1pecM3k16A3SoO83gbxykrnIMZlamv4hGySJVz4+MSiuy9ZQKhVEhQVYFURkVecCMDZ6\nlMfnYUoJDbS3MiYlnPjIIA6cLqOtw7rLgokREak8Ov8XGCQDf9n3Jtr6vg4TnuYbcTu1bfVcO2Yp\nUUERdl9nMEicyq0mOjyAuEjXFWvLRi7ER+XDp6e/Ye1n9/Pod390m8ze5LHXOzg5U4qQljM0+03g\nhcFJEIS+zVNkZDzEUJla9kdMeCB1TR106vQ9jmdWGYPT+EEJTj099WyhUCi4bEYSHZ16Dp0eWIk3\nOW4cv5x1O626Nl7c8zrVrYPnIFHbVs9/M7cS6qcx1xzZS0FZI02tOqa4sN9kyYny0+j0OgySwe11\nYD7qbsVeRU/FnjMKyvTsKnx9VIxNtT+QuwuvCk6CIIwAdguC8Gb3738XBOFNQRC+EQThliGenswF\nyFCZWvaHqa9TdX3P1F5mVS4qhZLRkSM8PofC8r6eera4bHq3as9GQW5vFg6bza1TVlHbVs+Lu1+n\nuaPF+Yk6wKenvqFD38lNk65zuOeVOaXn4n6TCU8XVKfEhdDSpqO20dgYsrmzBR+l9VSwLQVlXWM7\nheVNTBjwOvB1AAAgAElEQVQega/P4Dch9JrgJAiCGngDuA9QAYiieL8oir8Ergd+M4TTk7lAGSpT\ny/6IDe8rimjXtZNfp2VERCp+as9vTJtWTva8DgnRwYxJCSMtu4q6pvYBzwdYIVzB1WOWUNxYxl/2\nvUlnV6dL8x2Igroifsg/QEpoIkuGz3P4epMYwpniW2t4ug7M9L4uqmiisrmaZ7a/TIfe+mtsqxQh\nfQhTeuBFwQn4A/AKkGvlsQDAMyXVMhc1Q2Vq2R/Wap2ya/LRSwbGDUJKD4zBKSYi0GYL8t4s6sep\n3BoKhYLbp65mXvIMsqrP8urBdzzWylySJN5P+wIJidunrkapdOxjr0tv4ExeNUkxwUSGuseh3tZq\nJcg3iC6D3upjjmDaKzyuzeZ32/9MSVM51wqX89DsO+0yt4Vz+01DIYYALwlOgiAsARpFUTStaXsn\ndV8Enh3cWclcDCyclsS4YcZ8ulKpYFh8CI/dOmNQvMNsYerrZFnrZBJDjIv2fNBsaO6gvrljwP0m\nSxZM7d+p3BpKhZL7Z9/BhJgxHClJ5+3jn3ikW+yx0lOcrhSZFj+RyXHjHL4+R1tPW4febasmsF0H\n1tjRxP/seJmK5iqrj9tLSlwIyvByvq/5hKbOFn4+Yy23T13NpcNm8dLyp/n4xr/3W4ogSRLp2VVo\nAn0ZnmC/wa078YrgBCwDhgmC8AbwAjBPEIR1AIIgPArsEUXx4FBOUObCpbaxHU2gD1/9ecWgmVr2\nh7W+TplVuShQIER5fr/JXHzrQGozXOPP1DHRZGvrKa0a2HTUhI/Kh8fmryM1NJFtZ/fyZcYWh+fb\nH10GPR+kf4FSoeS2KT9xagyTZdFkN64geteBpYYmsm7mbVyaMpOc2gIe3/oi+woPOzW2JEmcqD2A\n76g0JIOC3156H8tGLXJojJKqZqob2pkyOgqlcnDNj014RZ2TKIpPmH4WBCEVeEoUxX8IgnAfUC+K\n4udDNzuZC5m6xnYqalu5ZFzskP0j7E1kaAAKxbm0Xpe+i+yafFJCE2y20nYnZk+9+IHFEJYsnp7E\n8axKfjhezE+vHGv3dYG+ATy56AGe2f4Sn57+hvCAMJaMcHxfyBrbcvdQ1lTJslELSQp1zjrpZG41\nCg84JPSuAwNjge6UuPG8ffwT/t/B/5BWnsHd09faLeDQG/S8ffxTtp/di1IfAHmXMG3twC4QvRkq\nyyJLvCI49UIPdAmCMBt4HNjcrd6TgGdEUawZ0tnJXFBkFRqlzGOHhQ/xTM7ho1YSGeJvXjmdrStE\np9cNSn0TWHjqOSgKmd3tVP7DsWJuXiY4JLmOCAjjd4se5JkdL/Ovo+spbSwnrTyD4sYyp3tBWfZq\nunHCtQ5da6JDpyezoJbhCaGEBHleiKJQKFg0fA5C1AhePfAOewoOkV2dx8Nz72ZkRGq/17bq2njl\nx3+TXp7BsLAkAsvmcay+kdrGdof3ys7VN/VfhO1JvC44iaJYjFGxBzBsCKcicxGQWVAHYN538hai\nwwMRtXXo9QZzfdNg7DeBUV6vVECSg8EpwE/N3Inx/HC8mGxtHYKDtTGJIXE8seA+/mfnX3u4dptq\ngMC2k4E1TL2abp2yyq5eTdbIyq9F12Vw636TPcRpYnh+6aN8cvobvs76nqe3/4WbJ6/kWuFylIq+\nuzHVrbX8ac8baBtKmBY/kV/NvZsvduRz7FQj2vImh4KTXm/gVG418ZFBZjutocBb9pxkZIaErIJa\nlEoFo5O9Z+UExn0ng0GipqHdIjh5fuUkSRKFZY3ERQbh50Rty6LumqcfjjnnsDEmagQRAdY34B2p\nAXKmV5M10l1okeEqapWaW6es4ulFD6HxC+bD9K94cffr1LU19Dgvr1bLU9v+grahhCtHLeLxS9cR\n4ONPamy3AayDNXu5xfW0tHcN2EnX03jdyklGZrDQdenJLa5nWHyI3ZLpwcKk2CuvbUasPktccDTh\nNj603UldUwfNbTomOblSmGZyKk8v4e6VE1E70C3WRE1b3/5QAIUNJfzvnteJ18SSoIkhXhNLvCaG\niIAw82piv/YIX2VsRdtglLRfkjjZ7l5N1jiZU41KqWD88KFbWU+OG8fLVz7NG4ff53jZaR7d+kcW\nD5tLWnkGRQ2lAN0y+Ru4ZswSczrVlsfeQJhTekMkITfhXf8iZWQGkbMlDei6DF6X0oNzir2sikJa\ndW3MSpo6KPctLOt2hnCyCFmlUrJgaiKb9uWTll3VxwzWHpJC4s3BxRKlQsmJsjOcKOvppO2r8iE+\nOAYftQ+5NQU9HtucvYvRkcOdcm9vadORU2RMTwb6D37jSUtC/DX8dsF9fJfzA++nfW61WWF4QEiP\nfb6E6CCUSsWAXXF7k57dLQAZ5FRmb+S0nsxFS1b3ftNYLw5OObV5AIwfxP0msN791l4uczG1Z6sG\n6ME5P+OdVS/z4uW/5YHZP2P1+KuZlzyDBE0s5c1VfQKTCWctgc7k12CQ3GdZ5CoKhYKrxiwmOsj6\nfHo/Tx+1ioSoIIoq+u+Ka0l7RxeZBbWMTBwcAUh/yCsnmYuWrIJupV6qd+03wTl/veLWQmBw9pvA\nssGg8/ZNY1LCiY8K4uAZo1O5oylT0ypnY8ZWs1rvegu13qjIIEZFDutxjSRJ3LzhAQxSX5cJZy2B\nTPY9U1xskeFuKlusm+VYe54pcRqKK5vtVuxl5NfSpTcMmSuEJXJwkrkokSSJzIJawjV+Q6pIsoUx\nOEnUG8oIDwolxsa3ZXdTWN6ISqkgITrY6TEUCgWXTU/i4+9FDp4uY/GMZIfHsFYDNNA9baUDnW0N\nfzKnGl+1EsHLvrw48jxTYkP4kTIK7VTsDWWLjN7IaT2Zi5KqujZqG9sZOyzCLS0Q3I2/r5qQCB16\nZTvjokcPyhwlSUJb3kRCdDA+atc+GlxN7TmDrXSgLWPT/mho7qCgrJHxwyOHxJG7Pxx5no6KItKz\nq/BRKxk3PNL5CboJeeUkc1FiLr4dgj419hIc1UQdMDZy5KDcr6q+jbaOLoc89Wxxzqm8krqmdsI1\njrWocIaB0oGOYHYh95L9JksceZ7mlu12iCIamjvIK21gyugop8oI3I0cnGQuSjK795u8UalnQqEx\nCjYSg/p3BnAX5/abnBdDWJIUoyFbW88df9hKalwIa5aO9rhvoaPpQFu4u0WGu7H3eSZEB6NSKuzq\nT3Yyx/icvWG/CeTgJDMAe04Us2FHDtqKJlJiNYPyATMYZBXUolYpGZk0NI7L9tCmrkDS+aDSDU5v\nKbOnnhtWTntOFLPzaBEAkmTsJPvSh8cAzov3z8mcKgL91YxKChvqqbiEj1pJQvS5rrj9pYe9ab8J\n5D0nmX7Yc6KYlz48RkFZIwaDZP6A2XNi8PYRPEF7Rxd5pY2MSgr1uv0EE9WttbRJTRiawqmp6xiU\nexa6Qalnwlabe1vHvYmqujZKq1uYOCIKlRNFxN5GSmwIre1d1DTYbgQpSRJp2ZUEB/gwItE7AvL5\n/8rLeIzz+QOmP3KK6zEYJK+sbzKR1W1ZZGgKp8KidYYn0ZY34qNWEh/puvO5Lcsce9JLQ81Js2WR\nd6b0HMUeUUR5TSuVdW1MHh2Fykvc+eXgJGOT8/kDpj/M9U1eHJxMfnr6pvAefZ08hcEgoa1oJikm\n2C2rBVsOE5ogX480FHQn58QQ3pHecpVkkyiiwrYowlssiyyRg5OMTRKirH+DTnbS2sZbMDtDeFn9\niiWZVbn4qnyRWkOosmjX7ikqalvp1OldcoawxFab+/qmDl77LI0uvWdasruKJEmk51QRGuzrtIWT\nt2HPysnUv2mozV4tkYOTjE1sVfbb+uA5HzAV38aEBzjc42awaOxoprixDCFqBEF+voOycjKJIdyx\n3wRG0cNjt85gWHwIKqWCYfEh3Ld6MqOSQtl2WMsf/n2QljadW+7lTkqrW6hpaGfyqGivaT7pKglR\nRsWerUyI3iBxMreKmPAAt6R03YWs1pOxypGMcnKK6o1pHqWCwvImlAoFD62del6orWxRWt1CU2sn\n04TEoZ6KTbIsWmRUhgdSUdsyoNLKVUxiCHetnMAYoHq/VxbPSOalD49xOKOcJ/6+j2fvnmO2avIG\nTnant7xVQu4MRsVesNljr/f7KL+kgaZWHXMmxntVQbq8cpLpQ3tnF//86hQqpYInbp/J648tYc3S\n0Rgkia4u794vGIis86C+KcuiuWBsRCBtHXqaWj27ynCHp549+Pup+d2ds7h2/nAKyhp59P/t5myx\n9RYZg82eE8W8+20GABt3nz3vVamWpMRpaG3vorq+r2LvRHYl4D0SchNycJLpw+c7cqiobWXlwpGk\nxhu/SV89bzhKpYJN+/K8fkO7PzILvN8ZIrMqF5VSxeiIYeZVhadTe4Xljfj5qsxu6J5EpVRw76pJ\n/HzlROqaOnji7/s4mlnh8fv2h6lsorW9C4CSquYLomzCREo/ooh082pRDk79IghC3FDP4WKmuLKJ\nL3blEhXqz9plgvl4VFgA8ycnUFDWyKmz1l2RzweyCmrx81UxLMF96St30qZrJ7++iFHhqfiqfc3B\nosqDwUmvN1Bc2UxyrGbQ9lkUCgUrF47kidtnYjBIPP/2Qbb8mD8o97bGhVo2YcK0Iu6ttO3Q6cnI\nr2V4QghhGr+hmJpNvCo4CYIwAtgtCMKb3b+vEARhvSAI7wuCsG6Ip3fBI0kS//zyFF16A/dcP6mP\nIGLFpSMA+GZv3lBMz2Va2nRoK5oYkxzuVIfWwSC7Jg+DZGBcjFF0YgpOlR5U7JVWt9ClN7jFGcJR\n5k1O4MX75qMJ8uWNL07y7qYzGAyDuzLPzK+loMy6zPp8L5swcc5jr+fzycyvQdflHS0yeuM1gghB\nENTAG8B9wE2CIGiAdaIoXtP9+PuCIOwQRfHC+CrjhexLKyUtp4oZY2OYO6mv/f7YYeGMSg7j0Jly\nymtaiPMiZY89iNo6JMn4PLwVU33T2Chj/yZzWq/WcysndzQYdAUhNYKXH1rI7986yBe7cimvbWXW\n+Fi++uGsx2yzJEniZE41n+3INtc1WeN8L5swkRAdjFql6BOc0rK9y7LIEm/6+vgH4BUgF1AA84Dt\nFo//F1g8BPO6KGht1/Hvr0/ho1byi1WTrap2FAoFKy4dgSTBt/uHLgXjLOdL8a0CBWOjjE7kpl5T\nntxz0pa5V0buDHGRQbz00AImjIhkf3opr3x8wiO2WZIkcTijnMde28vT//yRk7nVTBsTzdorxlg9\n/3wum7BErTIq9rS9uuKm51ShVimY4AUtMnrjFcFJEIQlQKMoipZ9hsOBWovfa7uPyXiA9VuzqG3s\nYM3SMcTbKL4FWDA1gTCNH9sOFdLW0TWIM3QdkxhCSPHOt5FOryO3Jp/UsEQCfY0rppAgX3x9VB5N\n6xUO8crJhCbQl+d/MZcgf+sJHVf2f/QGiX3pJfzqr7t5/u1DiIV1zJ4Qx/89vJDnfjGPW5aP61OX\n9ditM87rsoneJMdqaOvooqre+F5qbOnkbEkDY4dF4O9gt+LBwFtmtAwIFQThDSAEmAacpOf8IoCa\nIZjbBU9eSQOb9uYRHxXE6sX9twP3Uau4eu4wPvpeZNexIq6eN3yQZukaeoNEtraOxOhgQoO9a+PX\nxNnaQnSGLsZFn/u2rlAoiAkP8KggQlveSKC/mshQz/dcGggftYq2Tr3VxwrKGnl/cwYjE8MYkRhK\nXGRgnxV+bxf9nywehSRJbNiRQ3FlM0oFLJyayJrLxzAsvmcwtlaXdSGRGqthP8Z9tJjwQE7lViNJ\n3pnSAy8JTqIoPmH6WRCEVOAp4H3gI4ypPoDrgD8O/uwubAwGiTe/SMcgwbqfTLbLpXv53GF8tiOb\nb/bmsXzOsPOikr6ooonW9i7mTvLOVROc228aF93zC0JMeCDFlc20tusI9Pdx6z11XXpKq1oYkxLu\nNQWYKbEamwIFy9VTkL+a4YmhjEgMZWRiGHVN7by7KcP8eEFZI3/96DhglK9fMSuFG5aMdqkF/fmM\nqU+XtryJGWNjvdJPzxKvCE690ANdoig2CILwoSAInwCdQJoshnA/249oySqs49IpCUwXYuy6JjzE\nnwVTE9l1rJi0nCq7rxtKzofmgplVxrf32F7BySSKqKprIzXevcGppKoFvUEa0v2m3qxZOtrc+8mS\nB9ZMIS4iiLMlDZwtqSevpIEzeTWcPtt/QkUT6Mvffr2ImAjP13B5M7099tKzqwjy4p5VXhecRFEs\nxqjYQxTFj4GPh3ZGFy4NzR28u+kMAX4qfr5yokPXrlgwgl3Hivlmb955EZy8XQxhMBgQq/OI18QQ\n5t8z3WQpikiNd+++kLs99dyBKbW2YUcORRVNJPdS61mak7Z1dFFQ2kheST3//OoU1kTore26iz4w\nAcRHBRkVexWNlNe0UFbTwpyJcV7bs8rrgpPM4PH+5kyaWnXcfd1Eh01QRyeHM25YBEczKyipaibR\ny1MlWQW1BPmrSY7xng9hSwrqi2nramdu9Iw+j0V7sNbJ7KkX611Fyfbu/wT4qRk3PIJxwyP47mCh\n1XTghSIHdxWTYq+oosnsCuGtKT3wErWezOCTVVDL94cKGRYfwopLnRM1mIpyN+3z7qLchuYOSqtb\nEFIjvHZ/zJTSGxfVV5ASY07ruV8UYV45xZ//H+C2ZN8XihzcHaTEamjr0LP9sBbwrhYZvZGD00WI\nXm/gjS/SAfjl6slOL+vnTo4nMtSfHUe0Xtn+wIRY2N2/yUtTegCZ1d1iiJi+H6Qml4gKDxTiFpY3\noQn0JcxLFYyOYK1Nx4UmB3cVkygiq7COqFB/r854yGm9i5BN+/PJL23kilkpjHeh+E6tUnL1vOF8\nsCWTHUe0XLdwpBtn6T7Omb16p1JPkiSyqnKJDAgnOrBvAA0P8UelVLi96WCHTk95TQsTRkR6jVLP\nVS50ObirNLd1mn9u79SzN63Ea18veeV0kVHT0Mb67zLRBPpwxzXjXR7vyjmp+KqVbNqXj36QPdHs\nJbOgFoUCBC8NTqVNFTR2NDMuepTVIKFSKogOD3C7S4Sxv4/tluoyFxZ7ThTz9Z5zKfjmNp1XO6/L\nweki4+2vz9DWoeeOa8a7pRg1NNiPRdOTKKtp4VjW0LY9sEaX3kBOUT2pcSFurxFyF+b9pmjbeyMx\n4YHUNXXQqbNeoOoMJkmxuxWAMt7J+ea8Lqf1LgLMVfPljRgkiI8M4opZqW4bf8WCEWw7rOWbPXnM\nGu9dHU/ySxvo1Om9e7/JRvGtJaZap+r6NrcVkZrFEPLK6aLAVpt2b3Ved9vKSRCEo+4aS8Z9mJqo\nFZQZAxNAWU0L+9JL3HaP4QmhTBoZRVpOlfkDz1s4V3zrnSk9MAYnjV8wiSG2A7snRBGF5u638srp\nYsDWlxBvldq7FJwEQbDMCwX1eizY4uclrtxHxnkGaym/YoFRjv7NPu9yK88q8G6lXlVLDdWttYyN\nGtmvKMETfZ205Y2Ea/wICfJ125gy3sv5JrV3KjgJghAjCEIGUCwIwt1WHk8DREEQ3us+9DcX5ijj\nAoO1lJ81IZ6Y8AB2Hi2iubVz4AsGiazCWkKDfYn30t5T51J6/X9AxES4t9aptV1HZV3bkDuRywwe\n55vU3tk9p2eBLd3/3yYIwkcAgiA8hLEXk0EUxURBEEwGWReGTvU8xJaJpruX8iqlgmvmj+A/m87w\n/aFCfrJ46L+NVde3UVXXxuwJcV4rlc6yY78JLFdO7glOpi8n3mRbJON5ziepvbNpvcXAB6IotgDf\nY2wMCBAPWCbOvfMT4SJiMJfyy2an4OerYtP+fPR6g9vHd5SsQu/20wPjyslf7cewsP4/MCJDA1Ao\n3JfW08r7TTJejrPBKRko6v5ZC6QAkiiKT4qi+KRbZibjFhZOS2LuJOP3BaXCs0v54EBflsxIpqqu\njUNnyt0+vqOY9pu81Ym8ob2RkqZyhKgRqJT9tyrxUSuJCPF328rJ7Kknr5xkvBRn03q+QEv3z22A\n93pgyNDYokOpgPXPX0VwgGO1Pvu1R/gqYyvFjWUkhcSzavyVzE+ZafP8FQtGsOVAAV/vzWPe5AQX\nZ+4aWQW1qJQKRiV7X0uA/dojrE/fCBhNX/drj/T7uoIxtSdq69DrDS47SXujG7mMjCXOvsOrMK6W\nABKBagBBEJK7mwXKeAmdOj3Z2jqGJ4Y6FZhePfAO2oYSDJIBbUMJrx54h/3aIzavSY7VMG1MNGfy\nasgraXB1+k7TodNztqSeEYmh+NnRQHEwMb2u1a3GtGNDe9OArysYg5PBIFHT0O7yHArLm4gKC/Da\nwmQZGWeD0yHA5O0/EziMcX/pW2CTlfO909fmIkAsrEPXZWDiiCiHr/0qY6vV4xttHDexYoHRrfyb\nvUPnVp5bVE+XXvLKlJ6zr6tJsedqaq+5tZPaxnY5pSfj1Tib1vsbsEEQhGsAnSiKJYIgIIriZABB\nEE50nxcqCML/Iqf9hozTZ6sBmDjScYPX4sYyh46bmDE2ljCNH9uPaNl5rIiUXs3iBgPRJIZI9b7g\nVNxYauN4/69rtJsUe3Lxrcz5gFMrJ1EU9wFXAV8Dpjony9XR893/vwOjcOJ2Zyco4xqn82pQKGDC\nCMeDU0yQ9dWWQZL4x5EPyavVWn18X3oJ9U0dxnMNEgVljYNuMJnphZ1vW3VtvHP8UwyS9URCUkh8\nv9eb+jq5qtgz1b7JKycZb8Zpbz1RFNOANItDCovHvuz+/z5gn9Ozk3EJXZeerIJahsWHoAl0zAWg\ny6BHL1k3GQ32C2Jn3n525u1nVMQwrhi5gHkpl+CnNt7DlvvEZzuyB2X1JEkSWQXGfjUmT7qhRJIk\nDhWf4D8nPqOurYEw/xDq2/vWnl0//sp+xzHXOrloYaQtk8UQMt6PO41f73LjWDJuIFtbT2eXgYkj\nHd9v+jrre6paahgXNYpWXZtZrXf9+CuZmzSDtPIMvj+7hxOlp8mtLeD9tM9ZNHwuy0YuQFvRhCqi\nDHXCWRQBLUhtQXSVjqSwDP618RRXzEpheEKoB56xkYraVuqbO5g/ZWjVggCVzdW8ffxTTpSdxkep\n5saJ17Jy7DIOl6Sx0UIFef0AKkg4Z/7qal8nbUUTCgVe27JeRgbcGJxEUTzgyvWCILwG+ACxwAlR\nFJ8TBOEBYDLGlKEOeFQURdelShcJ5v0mB1N6RQ2lfH5mM+H+oTy2YB3Bvn2tf6YnTGR6wkSqWmrY\nkbePHXk/sjl7J5uzdxI4OQS977mVgSKwGd9R6ejOwjd7jUKJUUmhXDE7lYXTkhxWEQ7EObPXoUvp\ndRn0bBK38/mZb+nU65gUK/DzGT8lXhMDwPyUmQMGo974+6oJDfZ1w55TI7ERgfj7yU0JZLwXp96d\ngiDcjDGQ2ItOFMWP+ztBFMUHLcb/jyAIk4Hloihe233scYzOFFucmPJFyemzNYBj+016g543D39A\nl6GLey652WpgsiQ6KJK1k1Zyw/hrOFySzrazezhTmW313LhxZdw+aiXbDhdyLLOCN784ydv/Pc28\nKQksm5XKxJGR7E0rMbb3qGhyWkgx1MEpqyqXt45+RFFjGaF+GtbNvJX5KTPdYqEUHR5IQWkjBoOE\nUun4ePVNHTQ0d3qlUERGxhJnvzrNwViIay+dQL/ByYQgCBFANFAAVAuCMA8oB6YArzs2zQsLRwpi\nu/QGMgtrSYnTONRU8NvsHeTWFnBpykwuSZxi93VqlZp5KTOYlzKDtZ/dZ3XTv15XzdxJ8cydFE9N\nQxs7jxax/bCWH44V88OxYsKC/ahv7jCfbxJSAA4FKLGgDl+10qOpQxOWf5METSyhfhrOVBmD8+Uj\nF/DTySsHDPCOEBMeQG5RPfXNHUSE+Dt8vbZC3m+SOT9wKjiJoviwuyciCMJI4FXgEuB6URQbBUH4\nK0bZugS8Joqie/tUn0eYCjdNmApiAasBKreono5OvUMpvdLGcj499Q2hfhrunH6j03NNCklA29C3\nX5SlGi0yNIA1S8dww5LRnMmrYdthLbuOFvW5BowCC3uDU2u7joKyBsYOi8BH7dlGz73/JsWNZRRT\nRmRAOL+e93PGRI1w+z0tDWCdCk6yjFzmPMHt/3oFQVAKgvCWIAgOvftFUTzbncJLAn4tCMIC4Hei\nKC4RRXEpMNFae46LBUcLN0917zdNGmWfGMJgMPDm4Q/QGbq4e8ZaNH7Ol6atsqE6s6ZGUygUTBwZ\nxa9vno7CRpqqoKyRdzed4fTZaroGMJTN0dZjkAYnpWfrbxLkG+iRwATnglNVrXOiCNlTT+Z8wekd\nUUEQ1gABwOe9VjT/BqpEUXSqJaooil2CIKiAVCDL4qEDwCJn53u+42hBrKP7TVtydiHW5DEneTpz\nkqc7N8luTCu5jRlbKWosxSBJTIubMKAAwFZ7DwXwxa5cvtiVS5C/mqlCDJeMjWXG2BjCLVYPe04U\n89bG0wDsTSthRGKoR6Xrtl77kgGKaV3BVOtU4YQoYs+JYvPq9OX1x7jp8jHnTfsEmYsPV+Q6zwGn\ngJcFQfgX8AbwFnBWFMXfOjKQIAjTgN8CzRj3mz4VRfEjQRCeFwThC6AdY2rvARfme16TFBKHtqGv\ns0CilcJNvd5AZkENSTHBhGsGTv2UN1Xy8an/ovEL5u7pN7llviY1mk6v48FvnyWjKoemjuZ+V2Rr\nlo427zFZ8vDaaYQE+XI0s4KjmRXsTy9lf7rxtRiVFMqMcbGoVQrWfyear6msa3Nqv8oRYoOjKWuq\n6HN8oGJaV4iJcM4lYs+J4h6vrba8yeOvj4yMK7gSnLpEUbyxW8DwBJAHvCeK4kOODiSK4glgrZXj\nz7gwvwuK6QmTrAYnX5UPnXodvqpz4smzJQ20dejtqm8ySAbePPIhnXodv5x1G6H+7t2L8FH5sEK4\nnPfSPmdLzi5unLjC5rmmD8kNO3IoqmgiuZdab+b4OCRJoriy2RyozuTVkFts22DWkf0qR9H4BmJt\njWBwCEEAACAASURBVDRQMa0rmCyMHKl1kiSJj7aKVh/z5OsjI+MKrgQnCUAUxVrgcUEQNgCfCoJw\nhSiK29wyOxnAGEDSyzMAiA+OobKlmgRNLAZJIre2gBd2v8bjl64jyNf4weVIfdP3uXvIrMphZuIU\n5iVf4pH5Lx15KV9mfseW7F1cK1xOoI9t14aBOnUqFAqSYzUkx2pYddkoWtt1pOdU8b/vHrHqLuzu\ndvQm8mq1ZNfkExMUib/anxIHimld4XhWBQoFHM2s4MGXd/WR2usNEiWVTeSVNHC2pMH8/5Y2ndXx\nPPX6yMi4ijuLcI8IgnAlsEkQhDtFUfzRXWNf7BwsOk5+XRGXpszkobnnjDg69TpeP/QuB4uO8+zO\n/+N3Cx8gMjCcU937TQOZvVY2V7P+5EaCfAO5Z8bNHmtl7q/245oxS/jk1Ndsy93LynHL3DZ2oL8P\ncyclkBofQlGH2MeVItlPcNu9LPn41H8BuPeSW5gcN84j9+hN79ScSWqfnlONSqUgr6SBgrJGOjp7\n2k4lRAUhSRKt7V19xkyOlYURMt6JK8GpzyeZKIo5giCsBr4UBGGRKIqe2xm+SOgy6Pnk1NeoFEpu\nnNQzJear8uFXc+/mPf9QtuTs4untL/HbBfeTkV9DQlQQkaG2VyiSJPHPox/S0dXBPbN/RliAZ2uC\nrhy1iP9mfc+m7B1cNfoyfNWOef0NxJSZnVSUp5t/N7lSTIkb7tb7AJyuEEkvz2BSrDBogQlsexZ+\nf6gQAKVSQUqshhGJoYxMCmVkYhjDE0II9PfpE9hMrFk62qNzlpFxFleC0xprB0VRPC0IwpPAKowi\nCRkX2JX3I+XNVSwbtZC44Og+jysVSn42bQ0RAWGsP/kVz+54mXb1ZCaOnNbvuDvy9nGqQmR6/EQW\npM7y1PTNBPkGcuWoRWzM3MrO/B9ZPvoyt46f1Wa9UZ/YdgRw3x6QJEl8fNLYwfbmSde7bVx70NpI\nwSkV8PLDC0mNC8HXRmPFgfbzZGS8DVdcybP6eewLZ8eVOUdHVyefn/kWP5Uvq8dfbfM8hULBynHL\nCA8I5e+H3sd37FECY21/6FS31PJB2pcE+gRw7yW3eCyd15trxixhc/ZOvs7axuUjF6BWuq9DrbO9\npxzlSEk6ObUFzE6axqjIYW4deyBsSe1T4kIYnRw+4PUD7efJyHgTznrrzcVxbz2XjGEvRrbk7KKu\nvYFV45YTbkfabeGw2Xy7u4Q8n518X/4ViTk+fVYoxnTeetq62lk38zYiAsM8NPu+hPqHsHTEpWzJ\n2cW+wsNcNnyu28b2V/vRquurYHOnrFtv0PPxqf+iUChYO+k6t41rL7ak9nJqTuZCxNmV0xM47q23\n0sl7XZQ0d7bw38ytBPkGct3YK+y6xmCQ0Ob4Exy2EPWoo7xz/FPq2hpYO+k68+roh/wDpJdnMCVu\nPIvdGBzsZcXYy/k+dzcbM7eyMHU2SqXrJiU/ao9ZDUwA1wqXuzy+iT0FhyhpLGfJiPkkhsS5bVx7\nkVNzMhcTznrryYHGw3ydtY0WXRu3TvmJWSI+EIXljTS36ZgzcTQ3Xb6YF3e/xleZ35FVdZZmXQsl\njeVIkoSP0odfDGI6z5KowAgWDpvDrvwfOVyS5rIbRW1bPW8d+wg/lS83TVrB7vyDFDeWEegTQFNn\nC3l1WhYNn+PyvDv1Oj47swkfpZo1E65xeTxnkVNzMhcLHnHGFAThKUEQZI2qk9S21bM5eycRAWEs\nH2W/Y9Op3O76ppGRxAVH8/zSR4kJiiKzOoeihlIMkgEJCZ1Bh1hz1lPTH5Drx12JQqHgq4zvkGy0\nLLcHSZJ48/AHtHS2ctvUn3CtcDkvLX+aj2/8O2+ueJFETRxbcnZxsjzT5Tl/n7uHmtY6lo++jMjA\ngfd3ZGRkXMPp4CQIwgJBEBZaOf4HYKwoinJ1n5N8cWYznXodayZc45Dk+nSeqb7J6AwR6h+Cn8r6\n1qAtw9jBIF4Tw9yk6eTXF5FWfsbpcb7P3UN6eQZT48Zzxcieb0VftS8PzPkZKoWSNw9/QHNni9P3\nadW18VXGFgJ8/Ll+nOfcH2RkZM7hysrpHxh99c4KgvBzQRB8BUF4E2Pn2jvdM72Lj7KmSnbk7Sde\nE+OQYMBgkDh9tobo8ABiI86lAUuseL+B+1VsjnL9uOUAfJXxnVPXlzZV8EH6FwT7BrFu1m1WU5Qj\nI1JZPeFqatrqeOfYp07PdZO4nabOFlaOXeaSW7uMjIz9uBKcDKIozgJWAFcAlYAG+Ikoin1L0WXs\n4tPT32CQDNw8aSUqB6TWRRVNNLV29rEssqVW86Q5qT0MC09iesIksqrPklllvbjUFnqDntcPvkun\nXsfPZ9xMRIBtxeGqccsZFTGMfdoj/Kjtq3QbiIb2Rr4RdxDqH8LVoxc7fL2MjIxzuBKcTN56GaIo\n3gTcBcwHJrljYhcj+XVF/Kg9yojwFGYn9V9E2xuzn14vs1dHeisNNj/pXj196eDq6avMrcZuvamz\nmJcyo99zVUoVD8z5Gb4qH9469hG1bfUO3evLjO/o6Opg9fir8PdxvLmfjIyMc7hNECGK4pfATzFa\nF41117gXEybngZ9Ovt5hJZ3JT29Sr+A0P2UmD8+9i9TQRFQKJamhiTw89y6PmpPay5ioEUyIGUN6\neQZ5tYV2XXO2tpDPz3xLZEC43e09EjSx3DZlNS2drbx5+AO7RRiVLTV8f3YPMUGRXD7i/7d351FS\n1ne+x9+9sm/drLI1DfQXEFCCkAnGJkKiMYtioscF40TnzkRJnMlMlrm5mXicJXNOrnMz1+tEPTOj\nZFSMjlEwahIXYmwVDWjYly/QgKwN3TT72kvdP6qqaaCru6uqu+upqs/rHI48T9XveX5dPl1fnuf3\n/X1/n25XGxHpGB1dW+/9yGq1z5vZLCVFtN/6A5tZlWC9tlAoxPptBynu152hxRennUfXVgqiGyd+\nnvUHNrN442t858q/aPW9Z+vP8m8f/JzGUCMLPnlnu1PsAa4ZV86He9ewumoDb1RWcE07siD/e93L\nNDQ2cMvk68nP67AaySLSDsncOX27pZ3u/jbhZIl7kjh2VgmFQjyzejGQWL223QeOc/j4GSaXDkzJ\n3KVkTBkygbFFo1m+e1WbSRqL1ixhz7Eqrht/NVOGxHdznpOTw70zv0avwp48ueoF9sZIFInaeXgP\n7+xYzuh+w7lydOcsJSIisSUcnNx9aSuv/czdH0z02Nkm2Xpt58ab2rcke5Dk5OTwlUnXESLEko2x\n09vXVG3kN1veYnifocyfmljB1aIe/fnz6beHlxr54Oc0NDbEfO+za39FiBC3Tb2B3JxOmQ4oIq3Q\nb12KNTY2Jl2vbV07128KqumXTGFk32G8+/EKDpw4eNHrx8+e4JHlT5KXkxtObkhiuY1Zo6bz6VEz\n2Fq7g8UxgqHXVPLh3jVMGDiWacMmJ3wuEUmcglOKVXwcrtd2dcmnEqrXFgqFWFtZw4A+3Rg+KD3n\n4OTm5DJv4udpDDXyq42vX/T6Ex89R+2pw3z10i8ytmh00ue7e/otFPXozwvrX70oESMUCvFMU2LK\njWn3mFQkUyg4pdDZhjr+e124XttNkxOr17a35gSHjp1h8tj0G29qbtao6QzpNZC3ti/j0KkjTfuX\n7fyQd3euYHxRCTd2UHWG3oW9WDDzThpCjTz8wc85W3+26bVVVevZWL2V6ZdMYcKgsR1yPhGJX2CC\nk5k9bGaPmdliM7s/sm9oZP9DZvaEmXV9KehO9MbWCmpO1nLt+M8wsGdRQsdI5/Gm5vJy87hh4jXU\nNdbz6ubwcGbtycP8x0e/oDCvgG/+ydfjmpTclqlDJ3Ld+KvZc6yKRZE7pcZQI8+seYkccrhtimob\ni6RSYPJj3f2+6N/NbKGZlQE/BL6VaSnp7+1cwQvrf8Puo/vIIYdL+gxJ+FhN402l6R2cAGaX/AmL\nVi/m5U1v8oovpTCvgNP1Z/izT9ya1GcUy/yp85oSLT7au4bqE7WECDFh4DhG9R/e4ecTkfYLzJ1T\nlJkVAYOAvsAe4H4ze8rM7k5tzzrGeztX8ND7TzSlTYcI8e8fLuK9nS0vM96aUCjEusoa+vUuZOSQ\n9C8Cv3zPKk7UnSJEiMZQI6frzwDENZ8pHoX5hVxVEl6i/sCJg4TCRU/YVLM1of8fItJxAhOczGys\nmb0CbAD+CRgDTAB+4O5fA64wsytT2ceOsDhGNfBEqoTvrz1JzZHTXFpanNbjTVGxPpuXWkkxT1as\nenuprNouIgEKTu5e6e5fAkYAf014Gfg3mhWRfRlovZBaGog10TSRKuHR9ZsuLFmUrjryswnyOUWk\nbYEJTlGRYJQHvAPMbfbSTGBNSjrVgTqySviF6zelu1RUUA9q1XaRbBeI4GRm08zsWTP7TzN7CXjR\n3XcBvzazJ83scaDe3X+f2p4m7/oJn2txfyJVwtdV1tCnZwGjMmC8CVJTQT3IVdtFslkgsvXcfSVw\nawv7nwCe6PoedZ4hvcN3Ob0Le3Gq7hQj+g5j3qRr4y7MeqD2JAcOneJPJg8lNzf9x5uAps9gyYbX\n2H10X8KfTdDPKSJtC0RwyiZr928C4Bsz5se9ZlNz67a1vH5TuktFBfUgV20XyVaBeKyXTdbu30QO\nOVw6uCy542zNnPlNIiIXUnDqQqfrTrO5ZhulRaPoXdgrqWOt21ZDrx4FlFzSr4N6JyISHApOXWhD\n9VYaQo1xr0V0oZrDp6g6eJJLxxSTlyHjTSIizWnMKUEVK3fz/NIt7Nx/jFFD+nDz3PGUTxvRapvo\neNPUJINTptTTExGJRcEpARUrd/Pg0+cqC+zYd7Rpu7UAtW7/JgryCigbmFy163PzmxScRCQz6bFe\nAp5fuiWu/QCHTx/l4yN7mDhwHIV5BUmdf+3WGnp0y6dU400ikqEUnBKwc3/LRdJ3xdgPsG6/AzB5\niCV17tqjp9lbc4JLS4vJy9P/PhHJTPp2S0CsigytVQbviPGmipW7+c5DFQBU7j5MxcrdCR9LRCTI\nFJwScH15aYv7b547vsX9oVCINfs30ruwFyX9RyZ0zug4V83hUwAcOnaGB5/+SAFKRDKSglMCjp0I\nL+vdv083AHJzc/ju/OkxkyGqjldz8OQhJg82cnMT+8gTGecSEUlXCk5xOlvXwJK3K+nRLY9Hvz+H\n2dNG0NgYonR47OSEtfs3AiQ1vymRcS4RkXSl4BSn3324i0PHznDdp8bQu2dhUzp3NL27JWsi401T\nhiYenBIZ5xIRSVcKTnFoaGjkxbe2kp+Xyw2zw3OVmoJTZGLshRobG1m/3xnUq5ghvRIv0hprPCvW\nfhGRdKbgFIdla/ax7+AJ5s4YSVHf7gAMH9Sb/n26sa6yhlAodFGbbYd2cqLuFFOGTEhqKfWrLh9O\n7x4F5ObmkJebQ8mwvnzvjtjjXCIi6SzjKkQ88B/vc+e8T3X4l3YoFOL5320mNwe+cvW4pv05OTlM\nLi3m3dV72VdzgksG9T6vXUeVLNp94DjHT9Vx1eXD+f7XrkjqWCIiQZdxd067DxzvlBTrjzYdYPve\no1x52XAuGXh+AIquqbS28uJxp2hwmjw4ucm3q7dUA3DZ+EFJHUdEJB1kXHCK6ugU61/+Lny8m+Zc\nPMZzLini/HGnM/Vn2VRTSUn/EfTtnlziwqrN4eB0eZmCk4hkvowNTh2ZYr1xey3rtx1k+oTBLaaM\njxrSh769CllXefC8cSevqaS+sT7pJTIaGhpZW1nDsOJeDCnqmdSxRETSQVoEJzMbGm+bjkyxbu2u\nCSLjTmOLqTl8iv21J5v2Rx/pTRkyManzb9l9mJOn67lMd00ikiUCE5zM7GEze8zMFpvZ/c32lwJv\nm9mj8RxvxqQhHdKvj/cdZfmGKiaWFHFpK0uiTy4Njzs1Tylfu38T+bn5TBiU3BIZq6OP9DTeJCJZ\nIjDByd3vc/d73P1GYIyZjTezfOARYAGQ157jDB7Qk9wceGP5Tg4dO510v5rfNbWWCh4dd4omRRw7\nc5zth3ZhA0vpnt8tqT6s2lJNTg5MGZf4PCkRkXQSmOAUZWZFwCBgP/D3wL8CW9vbvvelK7n6s3kc\nPnaGnz7zRxobL5571F5VB09QsWoPo4f24YqJrd+JjR7alz49C5oqRaw/sJkQoaTHm06fqWfTjlrG\nDu9H316FSR1LRCRdBCY4mdlYM3sF2AD8E3AFcNTdX4u8pV0zWPceq2LZkVcZP/UkqzZX88JbiWft\nLf79VhobQ9w0Zzy5ua2fPjc3h0ljijlQe5IDh06eK1mUZHBav/0g9Q0hpZCLSFYJTHBy90p3/xIw\nAvhr4GagJDLW9GNglpnd0+4DDtpKcb/uPP3bTaxvpe5dLIeOnebN5TsZXNSTqy4f3q420cdu6yoP\nsnb/JnoW9KB0wKi4z91cNIV8WtngpI4jIpJOAhOcoty9nvD40o/d/V53vxf4IfCeuz/W3uPsO17F\n9+64AkIh/uXpDzkaWeaivV5+Zxtn6xv5ymfGtXvF2cmRhIkPK7ex/3g1lw4uIy+3XUNlMa3eUk1h\nfi4TxxQldRwRkXQSiOBkZtPM7Fkz+08zewl40d2bl3hoAOrjOeaIvsO4tLSY26+dQM2R0zz07MoW\na9+15MSpOl59bzv9e3fjszPbf+dTckk/enXPZ/2BzUDyj/QOHzvD9r1HmTSmmMKC5IKciEg6CURt\nPXdfCdzayuu7CWfstdu8SdcCcNPcMtZW1rB8QxW/emcbN5S3ndb9m/d3cPJ0PTd9YTzd4ggKebk5\nTCotZtWZD8kn+Xp6a7ZGShZpfpOIZJlA3Dl1pIK8AgAGdO8PhAPGd26fTv/e3fj5K+vZsutQq+3P\n1DXwUkUlPbvn84VZY+I+/6Vjisnre5Be+X0Y1ie5uVarNL9JRLJUxgWnv/rU3QD818rnaWxsBGBA\n3+78ze2foKExxP9+6kNOnKqL2X7pip0cPnaG6z5VQq8eBXGff+Cws+QU1NG7flhSS2SEQiFWbamm\nT88CxrSyyq6ISCbKuOBU0n8kV42eyfbDu/j9jg+a9k+zwdw0ZzxVB0/yb8+vanH8KbqYYEF+brse\n/7XkcGgPAMcPJBdQ9h08QfWhU0wdN4i8NtLYRUQyTcYFJ4Dbp86jW14hv1j7EqfqzlWJmH/tBCaW\nFPHu6r289sHHF7V7Z/Ve9tee5LMzRzEgsphgvNZVOwA1e3pRezTxChXRkkUabxKRbJSRwam45wBu\nmHgNR04fZfHG3zbtz8vL5Xt3XEGfngX8x5K17Nh3tOm1UCjEC7/bEl5M8DPjWjpsm+oa6thYvYW+\necVQ1531Lazv1F6rtmi8SUSyV0YGJ4Av2+co7jGAV30pB46fK8Y6aEAP/uqWaZytb+QnT67g9Jlw\nhvqHG/ezY99Rrrp8BEOLeyV0zs0Ht3O2oY5Jg8ILC669YH2n9mpoDLFmSw2Di3oytFhLZIhI9snY\n4NQtv5D5l82jrrGep9csPu+1T04exvXlpew+cJzHFq8Bzi1O+NU5id01wbklMj5dOpXuhXmsS/DO\naduewxw/Vcfl4wcllVQhIpKuMjY4AVw5agbji8fwwa4/srH6/Bp7X//iJMaN6MfSFbu4/Ue/ZuOO\nWnp0y09qkcK1+zeRm5PLlKHGhJIidu0/xuFjZ+I+jlLIRSTbZXRwysnJ4U8vvwmAn698nsZQY9Nr\nBfl5fGb6SACOnQynlp86U8+DT39ExcrdFx+sDSfPnmJr7Q7GF4+hR0F3powN19lLpK7f6sh409Tx\nWiJDRLJTRgcngLKBpXx69Ey2H9pFxY4/nPfam8t3ttgm+ogvHuurNxMKnVsiI7q+U/PFB9vjTF0D\nG7bXUnpJP/r1Tm4dKBGRdJXxwQng9qk3UJhXwDNrlnC6WWr5zhiP8BJ5tLe2KjzeFC1ZNH7kAAoL\n8prWd2qvjdsPUlffqBRyEclqWRGcBvYs4voJ13D49FGWbHqtaf+oIX1afP/IGPtbs3b/Jrrnd2Nc\ncbjkUUF+LhNGD2DHvqNxVUTXeJOISJYEJ4DrJ3yOoh79eXnTm1SfCN/N3Dx3fIvvjbU/loMnD7Hn\nWBWTBo0nv9kSGZMTGHdavaWa/LxcJmmJDBHJYlkTnLrnd+P2qeHU8kWrw6nl5dNG8L07plMyrC95\nuTmUDOvL9+6YTvm0EXEde22MVW/jHXc6euIslXuOMLGkiO7dAlEwXkQkJbLqG/DTo2fw2y2/Z9mu\nj/h89WeYMGgc5dNGxB2MLhQrONmoARTk57Z7vtParTWEQnBZmbL0RCS7Zc2dE0BuTi5fn3YzcHFq\neaJCoRBr92+iX/e+jOx3yXmvFRbkYaMHsH3fEY6fbHvcSSWLRETCsio4QSS1fNQMth3aeVFqeSJ2\nH93H4dNHmTJkQovVHCaXDiQUgg3ba9s81urN1fTqns+4Ef2T7peISDrLuuAEcPtl8yjMK+AXa146\nL7U8EdFHerFWvY2OO61tY9yp6uAJ9h08wZRxA8nLy8r/LSIiTbLyWzCcWv45Dp0+wpJNryd1rDWR\n4DR5iLX4uo0eQH5eTptJEau3hF/XIz0RkQAlRJjZw0ABMARY6e7/YGY/IxxARwDPuvuijjrf9ROu\nYem293hp4+t8sOuPVB2vZkTfYdw46VquHDWjzfbv7VzBixt+y64je8nPzcdrKhk46uL07+6F+Ywf\nOQD/uJYTp+pirq4bLVmkybciIgEKTu5+X/TvZrbQzMa7+zcj23nACqDDglP3/G7MGH4Zr2+tYO+x\n/QDsPLKHh95/AqDVAPXezhVN7wOob6xvtd2UcQPZuKOWjTtquWLikIteb2wMsXpLNQP7dWf4oN5J\n/VwiIpkgMMEpysyKgEHA/ma7ewCJLY7Uik3VW1vc/9SqFzlVF7ua+C/Xv9ri/iUbXmsxOE0uLea/\nCc93aik4bd97hKMnzjJ3xkgtkSEiQoCCk5mNBR4CrgDmufvRZi//M3B/R59z99GqFvfXnjrMv38Y\n/03a7qP7Wtw/saSIvNycmPOdViuFXETkPIEJTu5eCXzJzPKBRWZ2n7sfMLPvAhXu/kFHn3NE32Hs\nPLLnov3FPQdw+5R5Mds9s2YJB08davF4LeneLZ9xI/uzZddhTp6uo2f388edovX0LlNwEhEBAhSc\noty9PjLGVGhmC4DD7v7LzjjXjZOuPW/sKOqOy25sdcwpNzenxXbzJl0bs83k0mL840Ns2nGIT0wY\n3LT/bF0D67fXMnpoHwb07R7nTyAikpkCEZzMbBrwt8AJYCDwHDAc+D7wazN7FAgBP3L3xNY+b0E0\nAC3Z8Bq7j+5jRN9hzGtHtl4i7SaPHcgLb21l3baa84LTpo9rOVvXoCw9EZFmAhGc3H0lcGsLL5V0\n9rmvHDWjXanjybabNKaI3BbGnbREhojIxbJyEm4q9OxewNjh/diy6xCnz9Y37V+9pZq83BwuLS1O\nYe9ERIJFwakLTR47kPqGEL4jnExx/ORZtu46jI0ecFGShIhINlNw6kIX1tlbW1lDYwguLxvcWjMR\nkayj4NSFJo0pJicH1kVWxtV4k4hIyxSculDvHgWMuaQf/vEhztQ1sHpLNT265TN+lJbIEBFpTsGp\ni00ZO5D6hkbeW72XPdUnmDJ2IPlaIkNE5Dz6Vuxi0XGnZ193QEuyi4i0RMGpi0VTxvcdPAHAq+9u\np2Ll7lR2SUQkcBScuthKP3De9t6aEzz49EcKUCIizSg4dbHnl26Ja7+ISDZScOpiO/cfa3H/rhj7\nRUSykYJTFxs1pE+L+0fG2C8iko0UnLrYzXPHx7VfRCQbBaIqeTYpnzYCCI8x7dp/jJFD+nDz3PFN\n+0VERMEpJcqnjVAwEhFphR7riYhI4Cg4iYhI4Cg4iYhI4Cg4iYhI4Cg4iYhI4AQmW8/MHgYKgCHA\nSnf/BzP7MnAr0AAsc/fHUtlHERHpGoEJTu5+X/TvZrbQzKYC97j7FyP7njSzpe6uInQiIhkucI/1\nzKwIGARMAN5s9tJLwNUp6ZSIiHSpwNw5mdlY4CHgCmAeMAaobfaWWmBcK4fIA6iqquqsLoqISAKa\nfS/ntbdNYIKTu1cCXzKzfGAR8ApQ1OwtRcDBVg4xDGD+/Pmd1kcREUnKMKCyPW8MTHCKcvd6M8sD\nfg88Cvxr5KXrgX9qpekK4CpgH+EEChERCYY8woFpRXsb5IRCoc7rTjuZ2TTgb4HjhMebnnP3Z8zs\nVsKP+M4Cq9z9pynspoiIdJFABCcREZHmApetJyIiouAkIiKBo+AkIiKBo+AkIiKBo+AkIiKBo+Ak\nIiKBo+AkIiKBo+AkIiKBo+AkIiKBo+AkIiKBo+AkIiKBo+AkIiKBo+AkIiKBE7j1nC5kZt8CpgIh\noA74rrufTm2vRESkMwX6zsnMegKfd/e/cPdvADuBq1PcLRER6WSBDk7ufhKoMbNZZlYKXAa8neJu\niYhIJwv8Yz3gp8D/JfxY7+FIwLqImXUDZqBl2kVEgqZpmXZ3P9OeBoEOTmY2Bfhf7j4nsv13Zlbs\n7o+38PYZwDtd2kEREYnHVcC77XljoIMTMBTY1Gz7fWB2jPfuA1i0aBFDhw7t7H6JJOWWW25h+fLl\nTdszZ87kueeeS2GPRDpPVVUV8+fPh8j3dHsEOji5+xtmVm5mLwCnCT/a+1aMtzcADB06lBEjRnRV\nF0USsnz5curr61mwYAGPPPIIy5cv13Ur2aDdQy6BDk4A7v6jVPdBJJZt27Zx1113sWzZMmbNmsXC\nhQspLS1ts92sWbOoqKhg8ODBTdsick6gs/VEgu6uu+6ioqKC+vp6KioquOuuu9rVbuHChZSXlwNQ\nXl7OwoULO7ObImkn8MHJzIaa2cNm9pCZPWFmGlCSwFi2bBkACxYsOG+7LaWlpbz9dnhWxNtvv92u\nuy2RbBL44AT8hHDG3l+5+93uXpXqDklm2bZtG7Nnz6agoIDZs2ezbdu2dreNPo7T4zmRjhXo2Nl0\nqAAADNBJREFU4GRmM4A9wP1m9pSZ3Z3qPknmSfTRHOjxnEhnCXRwAkqACcAP3P1rwBVmdmVquySZ\nJtFHc6DHcyKdJejB6STwhrvXR7ZfBqansD+SgfRoTiR4gh6cPgLmNNueCaxJUV8kQ+nRnEjwBDo4\nRZIffmNmT5rZ40C9u/8+xd2SDKNHcyLBkw6TcJ8Ankh1P0REpOsE+s6pOc1vEhHJHmkRnCJrOb1t\nZo+mui8iItL5Ah+czCwfeARYQHhNEBERyXCBD07A3wP/CmxNdUdERIIgmaom6SLQwcnM5gBH3f21\nyK6cVPZHRCQIkqlqki4CHZyAa4ASM3sE+DEwy8zuSXGfRERSKpmqJuki0Knk7v4/o383s9HAD939\nsRR2SUQk5bJhPbCg3zk11wDUt/muLpINz3xFJJiyoapJ2gQnd9/t7gtS3Y+obHjmKyLBlA1VTdod\nnMzsus7sSLrJhme+IiKpEs+d032d1os0pErWIiKdJ57gNN3Mbu+0nsRgZj8zs0fN7GUzm9/V548l\nG575gsbWRCQ12gxOkSw5gC8A+8zsts7t0vnc/Zvufi8wD/hOV567Nen0zDeZANPVY2sKhpItdK23\nrtXgZGY3ApcCuPtH7v4WsNXM/qwrOneBHkBNCs6b9pIJMF09tqZEE8kWutZbFzM4mdlA4AZ3/3Xz\n/e6+AnjPzO674P3DOqeLTf4ZuL+Tz5GRkgkwXT22pkQTyRa61lsXMzi5ew3wipl9HsDMhjd7uRCY\nbWavm9m9ZmbANzqrk2b2XaDC3T/orHNksmQCTFePrSnRRLKFrvXWtfpYz91/CWyObP6jmX3DzFYA\nK4ExhJdRvxlYBfxdZ3TQzBYAhyN9kQQkE2C6emwtWxJNRHStt67NhAh3j47SfZ3wo7U/ANPdfbq7\n/8Dd5wDFwHMd3Tkz+yTwfeATkYy9R8ysuKPPk+nSKXkjnfoqkgxd662Lp7beEuA2dz9z4QvuftLM\nfttx3Wo67h+Ako4+bnPbtm3jrrvuYtmyZcyaNYuFCxfqIhERSbF45jk93FJginL3pzqgP0m75ZZb\nAp0qLSIibWt3cIqkkXc5M/uymS0ysyfbs1zG8uXLA50qLSIibQt04Vcz6wPc4+7z3f1Owus5jW+r\nXZBTpbNFKiYYalKjSOYIdHACZgFvNtt+Cbi6zUYBTpXOFql4XKpHtJIK+kdR58gJhUIJNzazW9y9\nw7P0mh3/NqDQ3f8rsn01MNPdf9LCe0uA7dXV1ZSVldG9e/e4zrVjxw5KSkri7mOi7VIhmb7G2zaa\nhXTJJZewd+9eAGbPnt1p50vVOZNtm07Xj7Rs1apVHDlypGm7X79+XH755e1un4rrLlF33303d955\nZ9ztdu/ezdy5cwHGuPuO9rRJ9s5pepLt23IQKGq2XRTZF9OkSZPiDkwAhYWFcbdJph3Q9AXaVe2S\n6Wu8bfv169fqdkefL1XnTLZtou0SvQaSadvV7dLlnM0DU0vbbUnFdZfo57N06dKE2iUkFAol/Kes\nrOzBZNq34/j9y8rKXmm2/V9lZWXjY7y3pKysLLRr165QunjggQe6tF1XqqysDJWXl4fy8/ND5eXl\nocrKyow8Z6okcw3E2zb6uT7wwAMJfa5d2ddUnLO8vDwENP0pLy9P+Nxdpas/1127doXKyspCZWVl\nJaF2fv/HM8+pxdiWfHiMzd0Pm9nTZvYscBZY5e5bOvOc0jGaTzDM5HNmg+hY3pw5c5rG8vQ5n7Nw\n4cKL5kpK8pINTp3O3Z8Fnk11P0SyVTT79cCBA+dtS5j+UdQ5gp6tJyIpFs1+feSRR87bFulMKQtO\nZvZDM3vLzH7X7M9bZlYRef0OM3ss8ljvcTPLS1VfRbJZdLpFfn5+l023iKZnA3GlZyfaToIn2eCU\nk0TbI8C/uPuc6B/gz4ENAO7+tLvf4+53ANXA55Lsq4gkIPrYqq6uLq4CpckEiug4FxDXnLVE20nw\nJBuckvlnyV5gg5l9FsDMRgGTgddbeO8gYEcS5xKRLpZMoEh0nEvjY5mj3cHJzK67cJ+7P5rMyd19\nO7DLzL4KfNLdl3DB3ZiZfQaodfdNyZxLRLpWMoEi0XEujY9ljnjunO5r+y0JqSG8cOFFs8LMbALw\nNcJrOolIGkkmUCQ6zpWK8THpHPEEp+lmdntHntzM+gJfdPd/AU6Z2Uwic6fMbBzwA+Bed+/U+VQi\n0vGSCRSJjnMl2k5al4pEk3iC0xeAfZF6dx2hF3Czuz8J4O5/BPI4VxLppch/H4qsgPulDjqviHQB\nBYrMkYpEk3jWc/oosqbTVjP7sw4499XAnc1TyQkvA3935HyXuvufuvu97r7A3V/pgHOmNaXJinSe\nbPj9SvRnTEWiSdzZeu6+AnjPzM4bgzKzYXEe5253n908ldzdr3b3845jZsVmFvhKFl1BabIinScb\nfr8S/RlTkWjS7i99Mxvu7nsim4XAbDP7MrAY+B1wG/BAHMf7IfBZzq/PlwPkuXt5s32PA58ARrX3\n2JlKabIinScbfr8S/RlTUT8wnjuSfzSzPwD/g3CwWEV4TtLNwE+BAuIITpybhPtqdEckCeK7zbb/\nEngH6BnHcTPWrFmzqKioUJqsSCfIht+vRH/GVNQPjOex3tcJjwn9AZju7tPd/QeRyg7FQLyLDrY6\nCdfMpgKXu/v/IblKFBlDabIinScbfr/S6WeM585pCXCbu5+58AV3P2lmv4335O6+3cwKI5Nwc939\neTP7ipn1IJxGnnkPfZOg6scinScbfr/S6WeM587p4ZYCU5S7P5VgHy6chJsDXBHp20/N7FFggpn9\nzMz0eE9EJAu0+84pkkbeoZpPwjWzT0Qn4br7O4THmqLvG+vu3+zo84uISDClcj2ntibhNhfzjk1E\nRDJPKoNTq5Nwm3P3L3d57zpRNkz2ExFJRsomt7r7RUEoW0Qnws2ZM6dpIly6DFKKiHQFLdOeAtkw\n2U86h+66JVuk7M6prQoRZpYD/A3hyhDdgKXu/nzX97TjZcNkP+kcuuuWbJHKmnVtVYj4NrAiMgk3\no6SiFIhkBt11S7ZIZXBqqhDh7m+2sEz7FCBkZl8DTgL3u/uRFPW1Q6XTRDgJFt11S7ZI6ZhTjGXa\no64Bfu3ufw48CzyYij6KBEk6lZ8RSUYQlqKIVoh4/4L9a9x9M4C7v29mD3R1x0SCRnfdki1SeucU\nY5n2qJNmNjjyvrHA7lT0USRTKNNP0kmQK0T8LfD/IrX17idcCFZEEpQNi+lJ5kjlY72rgbFmNr/Z\nvhxgAvBDd68Ebk1Jz0QykDL9JJ2oQoRIllCmn6STIE/CnQJ8BzgN9AAecfc/dH1PRTKD5tdJOgny\nJNy/A77l7tWRxIiHgVu6vpsimUGZfpJOUpkQ0eoy7YTnNn07ssDgt4HHU9JLERHpcimd5xRjmfav\nRl5+E/gi8BRwAHi3jcPlAVRVVXVaf0VEJH7Nvpfz2tsmiJNwo2NQLwG3u3uVmY0HlhCuGhHLMID5\n8+e38hYREUmhYUBle96Y0uAUY5n2qFzgYOTvHwOFbRxuBXAVsA9o6PDOiohIovIIB6YV7W2QyuAU\nnYT7OIQn4ZrZpwhPwn0R+EfgRTOrAYqAH7d2MHc/Q9uP/kREJDXadccUlRMKhdp+VycwsyeAsZx/\nl5MDTHD3YSnplIiIBELKgpOIiEgsWqZdREQCR8FJREQCJwip5B3CzL5MuFBsA7DM3R9LcZcCw8z+\nCHwQ2ax3979MZX+CwsxygX8Aprv7dZF9uo6I+dnoOmrGzH5G+B/4I4Bn3X2Rrp+wCz6bX7j7M/Fe\nPxkRnMysD3CPu38xsv2kmS119y0p7lpQ1Lj7glR3IoC+ACwGZoKuowuc99lE6Dpqxt2/CWBmecAK\nM/sVun6Aiz8b4BngYDzXT0YEJ2AW4YoSUS8RXpIj6y6KGPLM7CeE5xn80t1/leoOBYG7vwJgZtFd\nuo4iWvhsQNdRLD0IFxPQ9XOx6GcDkBvP9ZMpwakIqG22XQuMS1FfAsfd5wKYWT7wvJmtj6yXJefT\nddQKXUcx/TPhBVHHoOvnQtHPJu7rJ1MSIg4S/mKJKuJcdQmJcPd64A1gUqr7ElC6jtpB19E5ZvZd\noMLdP0DXz3ku+GyatPf6yZTgtByY22z7ekBrA7TsU8DqVHciYHIi/9V1dLGcGPuz/joyswXAYXf/\nZWSXrp+IFj6bC7V5/WTMJFwzuxWYB5wFVrn7T1PcpcAws0XAMaAnsNjdF6e4S4FiZq82G8TWddTM\nBZ+NrqMIM/sk8Bzwa8IBPAT8CPgcWX79xPhs7gceIo7rJ2OCk4iIZI5MeawnIiIZRMFJREQCR8FJ\nREQCR8FJREQCR8FJREQCR8FJREQCR8FJREQCR8FJREQC5/8D7m8sUFLpYPwAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x110efbdd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_fit(moon_df, res_moon)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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q+MUt8bg6qfnnlpOUVJpOFgvdG23/9tkJ8ksbuDIpgsvnhZm9tq9lPVN72y0I\nfsLFzf7fTYQx1W8hxBBvvgaDgW9S8lEqFaywo4wQg5kXHIODSkOKNm3YZct35R1ErsplQWgc8cEx\no9RD20oI6Z7aG+q5k5GftzP33ziXtg4dL3+YZnb67bvDWnakFhIV5sU9q6Mt7k9kqCcRQR6kZpYN\n+9mWcHERwUnoZ0de90KI5RZM6WUX1pFXXM/8WQFM8jRfp8meOGmciA+KobixjII6y/fcNLQ18v6J\nz3FSO3Jn3E2j2EPbcumpXFxYXzIgjZI5i+NCuSw+lLPaOj7efnbA+ZyiOv7++QncXTT8+vZENGrL\ncygqFAqWJYbRpTOw51iRxfcJFx8RnIReFU1VHC/LYoZvJKGeQy+EMGaEWGXnCyHOlxyeAMDBQsv3\nPP37+Kc0d7SwNuZafFzGPnnsSBhX7VkytWf0fz+cg5+3Mx9tkzmTX9N7vLGlgz++l0qXTs8jtyZY\ntTpzSXwoSqWCHali1Z5gnghOQq8dPQshlkdeOuS1Ta2d7M0oxt/Hhbjp/qPdNZuKC4rGSe1o8dTe\nqXKZvfmHmeIdxko7qQk1HPOC56BWqocVnNycNTxySzwG4OUP02hp60SvN/DKh+lU1LRw83LJ6gUw\n3u5OJM4MIK+4nnMlpiv0CoIITgIAXXodu84dxFXjbNFCiN1phbR36Fi1cDJKG2a0HguOagfmBc+h\nvLmK3JqCQa/t1HXyVtpGFCi4J+FWVCMooz5eXBycmRM4k4L6YkoaLd9kGx3pyw1Lp1FW3cLdz2xj\n9a++5GhWORGB7qxdIY2oT8sSuxdQiIwRgjkiOAlAd8aDurYGFlu4EOLblHxUSgXL54ePTQdt7Pup\nvcFX7X1xZhsljeWsjFpC1KSIMejZ6BjOqr2+wnvqLzW1dmIcZOaXNXLg+Mhy5M2bGYiHqwO704ro\n7BJ7noSBRHASANieuw+AZVOHzgiRlV9DQVkjSTFBvck9J5q5gbNw0TiTUpiG3mD6zbG0sYLPM7/B\n28mTtTHXjnEPbWteyBwUCgWfnv6GtR8/wKPfPjNoRWOjz3bnoPIpxTF6P06JW3GM3o/Kp9RsGXZL\nadRKLosPpaG5g6NZ1qVMEi5sIjgJVDRXc7wsC2nSVJPlFc7XmxEiOWJU+zWaNCoN80NiqW6pJbv6\n3IDzBoOBt9M20anv4o64Nbg4TIzViOZklJ3GYDDQqe9Eb9CjrS/m1ZR32F8weIAq6pBxiDqO0qUJ\nhcKA0qUCgDdyAAAgAElEQVQJh6jjFHfII+6TcdS9Q0ztCSaIek4Xgb3HinrLc4cHuLNm2bR+Rd92\n5h3AgIFlkUMvH29o7uDA8RJC/FyJifQdzW6PuuTwBHbnp3BAexTJt3+y0gPao5wozyI2cFZv+YmJ\nzFztqdcOvcNfj/wbtUqNRqlGrez5U9Xz9RTTmSWcwvJH3KcpwZ5MDfbkaFY5dY3teLk7jrhN4cIh\nRk4XuL3Hinjx/TTySxvQ6w3klzbw4vtp7O3ZY6LT69iVdxAXjTNJYQlDtrfzqJbOLj2rkiLMJvic\nKKIDZuDu4MqhwnT0+u+n9po7Wngv4xM0Kg13J6yd8N8nmK89BTDZKxR/V1/cHdzQKNV06rtoaG+i\norkKlKZrPOkdGm3Sr2WJYej0Bnaniz1PQn9i5HSBM/dsYPOObBbHhZJWcpLatnpWRV02ZDoe40II\njVrJ5fMm5kKIvtRKFQtC49iet5+sqhxm+08HYOOJL6hva2BtzLUEuPmNcy9tI9QjCG39wEUMkz1D\neO6Kx83e9+i3z5i8z99tkomrh29JfCj/+u9pdqRquW7x1Avig4BgG2LkdIHTlpv+hGs83psRwoIp\nvZO5VRRXNrNobjAervafV84SxlV7B3qKEGZXn2Nb7j5CPAK5VrpiPLtmU9ebqTE1VO0pc/dVNlez\n59yhEffL082RxFmB5Jc2kFss9jwJ3xPB6QJnXAp8Pr3ewJ827SGjNJNpk6ZYthDiYD5g/6UxhmOW\n33Q8nTw4XHSMDl0n/zj6IQYM3JNwK2rVhTOxsCg8kYeT7hp27SlT910rrcBR7cgbR97j3fSP6dKP\nrLx7b50nsTBC6OPC+dcnmLRm2TRefH/gXh5fL2cOl6SiCTHg2hxJS1vnoLV4ahvbSDlZyuRAd2ZG\n+Ixml8eUUtn9hnuiPIvbPnkIgJl+05jlP22ce2Z7i8ITrao3Zeq+ZZGLeGH/X/lf9i4K6ov5RdJP\n8HAy/UFoKPEz/PFyc2RPehF3XTN7WLn6hAuXGDld4BbHhfLzm7/P+BAR5MFjtyXw9/WX4xleDjo1\nKfsV/N8fd/BNSj46M1motx/RotMbLoiFEH0d0KZyojyr37GsymyL9gBdzILc/Xlu+eMkhszldMVZ\nfr3tT5yrtS5Xnlql5LKEUBpbOjmSKfY8Cd1EcLoITAvvTlS6cuFkXn90KYvjQjlRfpoWXRPLo5K4\n9YrZtHV08eYnx3nw5d0czSrvl3NOrzfw7aECHB1ULE2wrG7PRGFuifUWM8eF7zlrnPjlonu5Kfoa\nqlpq+P2OF9lfcMSqtpbZaGrvgDaVR799ZlgbjQX7JKb1LgIVta1Ad60eo+253QshVkxbTIR3KCsX\nTubDrWfYdriAJ986xNxpvtx1TTRFFY28978sKmpacHPWkHamvN8eqYnO3BJrayvlXmyUCiU3zr6K\nCK9QXj/0L1479C/yagtZN2f1sPIQRgR5EBXqSdqZCmob2vD2GH7mkQPaVF5Neaf378aNxoBV05nC\n+BIjp4tARW0LAAHe3eUNqpprOFZ2mmk+EUR4dwcaHw8nfrYmltd+uZSEGf4cz67i4Vd28+L7aVTU\ndN/f1NrZb4/UhSDUw3RpEHPHBdPmhczhuSseJ9g9gP/K23lu719obDdfSdeU5Ynh6PUGdqVZ9/sl\nRsEXFhGcLgLG4OLfU3tn57mDGAwGlpkojTE5yIM/3JPEU/cmoVGb/vUYaV41e2LtEmthoBCPQJ5b\n/jjxwTGcLD/DL755koe+/n8WT7Etjg9FrVKyPVU77CrFIEbBFxoRnC4Cxmk9f2+X3owQzmqn3j0+\npsRJ/uj0pt8gCs3snZqIrF1iLZjm4uDMry65jwWhsTS0N1HWVNEvl99gAcrdxYEF0YEUljeSXVg3\n7NcWo+ALi3jmdBGoqGlBrVLg7eFERtkpqltrWRG5GCf14LnMwgPcyS9tGHA8zMzeqYnK2iXWgmlK\nhZLSxkqT57Zkbh30Z708MZwDx0vYkaplerj3sF73+lkr+z1zMooNih5WO4J9ECOni0BFbQt+Xi6o\nlIre0hiWZIRYs8z0Xh9zxwXByNoptrjpfvh4OLLnWDEdncPb3JscNg93B1eUKFAplAS6+aFUKNl5\n7gDVLbXDaksYfyI4XeDaO3XUNrbj5+1MVUsN6aWniPSZTIT30EvCF8eF8thtCUQEeaBSKnr3SF1I\nq/WE0WHtFJtKpWRpQhjNrZ0cPl02rNcsrC+hsaOZheEJbLzpDV77wVPcGXcTje1N/Dnl7RFnshDG\nlt1M60mS9DqgAQKAY7IsPyVJ0jXAWkAHHJRl+W/j2ceJqLK2BZVPKcU+R3jgqw8wYCDCy/Lgsjgu\nVAQjYdjMTbFZstBkWWI4n+7K4bWPj/HSB2kmy7yYcrTkBADzgmN6j62IWkxWZTYHC9PYdPJLbpt7\n/TC/E2G82E1wkmX5QePXkiT9S5KkOcB9siz/oOfYvyVJ2iHL8oWzVGwM7M47gkPUcVr6HNuRd4Do\nAEk8ZxFGjfF3a0vmVgobStAbDCSGzLXod+5cSXcC2Lb27pGOscwLMGiASi85hUKhIDZwdu8xhULB\nvYnrOFdbyJdnvmOmXxQJfYKXYL/sblpPkiQfwA+YAWzvc+oLYOm4dGoC21eyx+RxsfdDGG2LwhN5\ncdXvePeHG9CoNJQ2Vlh032BlXsypb2sgu/ocM3wjcXN07XfORePML5J/gkap5o3D71HVXGP5NyGM\nG7sJTpIkRUqS9F8gE3gGUAF9f4tqgOEt3xGo66wyeVzs/RDGipPakbkBMylqKKWkYejnSIOVeTG3\n/+lY6WkMGMyOiiK8w7gz/iaaOprZkPIWXbouy78BYVzYTXCSZTlXluWrgVDgF3RPOfZNf+0DVI9H\n3yYyJ4OXyeNi74cwluaHxgJwpPj4kNcOVublkVf3siutkM6u/gmK00tOARA/yJTdsqmXcEl4ItnV\n5/jwxBZLuy6ME7sJTkayLHfRPWraDSzrc+pawPQclWCWa8NMk8dFBgRhLCUEx6BUKDlSlDHktea2\nKkSFepJbVMcrH6Zz9zPfsXHrGWob2+jSdXG8LJMAV19C3APNtqtQKLh33q3dKZbO7iD1vEC591gR\nD760i+se+5IHX9p1QaXpmojsYkGEJElxwONAE93Pmz6SZblQkqT3JUnaBHQAGWIxxPA1l/qjMUyh\n0+scChSEewazetZKsRhCGFPujm7M8pvGqQqZmpY6fFxMj+jh+0UPm3dkU1jeSFif1Xpl1c18feAc\n2w4X8OF3Mh/vyGZOHLQq21g6JYl9GcVs3pGNtrzR5Co/J40TjyTfw2+2P8+bh9/j+RW/wc91ElsP\nFfDGJ98HK0sXYQijR2FNDit7JElSBHBux44dhIaKXyaAzi4dN/z6v/jFZNPolMvzK37DFAv2NwnC\naPg2ezfvpH/EXfE3s2raZSNqq7W9i51HC/lqXx4VzqmoAwtwK72EykK3Adc+ui6BOVG+VNS2UFHT\nSkVtCxnV6cj63ajbvek4s4D2dtOvExHkweuPinVYI1VUVMSyZcsApsiynG/JPXYxchJGR2VdKwYD\ndDpW4qJxZrLn0KXYBWG0JIbM5Z30jzhSlDHi4OTsqOYHi6awauFkfvrlDhraNVQWuZi89uUP0hj4\nEdwJzZRg8CvBLTKX9sxIk/deSHkkJxqbBSdJko7KsjzPVu0JI1dR0wKaNtoUDcT7RqNU2t0jRuEi\nMsnFmyifCDIrs2lsb8LdceAoZ7hKm8up66hlYVg8e46q0JsIQwYgeU4Q/t4u+Hu7EODjgr+PC57u\ny3h63ysUkU3gVF/K8jwH3Huh5ZGcSEb0biVJUt/Moa7nnXPr8/XlI3kdwToVta2o3Ltzis30E/nw\nhPE3PzQWvUFPWslJm7SXVtzdTnxwNOGBpgNJRJAH6++Yz93XRnPNpVOZPzuQiCAPvN3ceCT5HhxV\nDrT6p6NwbBlwr8gjOX6sCk6SJPlLkpQJFEmSdLeJ8xmALEnSez2H/jyCPgpWqqhpQdkbnKLGuTeC\nAPND5gKWLSm3RHrpSRQoiA+KtipRcahnEPfMu5UOfTt+Ccdxiz2IU+JWHKP3s3CRXiyGGEfWjpye\nAL4BIoC7JUlyBpAk6SFJkh4G9LIshwDGXPWKkXZUGL7y2haU7jU4KDVM9Q4f7+4IAsEegYR4BHK8\nLJO2LjOrECzU1N7Mmapcpk2agoeTu9WJihdHLGC233Qau+rROTSgUBhQujRxvPO7IQskCqPH2mdO\nS4F1siw3S5L0HZDcc/z8nZ0iKI2jsro6lJOamOYroVaJtS+CfVgQGstnmd+SUXqahWHxVrdzrPQ0\nBoOB+ODv6zVZm6i4od30wodNGf8T2y7GibUjpzCgsOdrLRAOGGRZXi/L8nqb9EwYsbK27k2Es/3F\nvLlgP+aHWJ4tYjBppd3Pm+YFzxlxn4oby00eL28xfVwYfdYGJweguefrVsSSdLvTpdPTrOrOYyYW\nQwj2ZIp3OL4uPqSXnLQ6x12XXsfx0tP4uvgQ5hk84j6ZS+elb3VDWzawGrQw+qwNTpV0j5YAQoAq\nAEmSwiRJmmyLjgkjU1XXitKtFoVByTSfiPHujiD0UigUJIbMpaWzlVMVZ61qQ67KpbmzlfjgaBSK\nkT89uN5MOq+ukql8vjt3xO0Lw2dtcDoMJPR8nQgcofv50tfAf01cf2GkoZhACqtqUbg24K0OwEHt\nMN7dEYR+FvQmgh06154pxqXotpjSg+7yHg8n3UWQmz8AzhonHlpwF4GqaexOL6S6vtUmryNYztrg\n9GfgFUmS3gc6ZVkuBpBleY4syzF8vxDCU5KkPwIj320nDMup0mwUCgNhrhHj3RVBGGCGbxTujm4c\nLT6O3qAf+obzpJWcwFHtyCz/6Tbr06LwRP581R8IcQ+kS68jISSGHy6Noktn4Iu9eTZ7HcEyVgUn\nWZb3A1cCXwLGfU59R0dP9/x5B90LJ263toOCdXLrzgEww890WhZBGE9KpZJ5wXOo6ykSOBwljeWU\nNlYwJ2AGDiqNTfulUChICk+gU9dJWskJliaE4uPhyLcp+TS1dtr0tYTBWZ0hQpblDFmWP5Zl2bhZ\nQdHn3Gc9f+6XZfnNnmAmjKHSNi0GA8SFSuPdFUEwyVjj6bAFZTT6MtZuGq1y68nh3U8sDmrT0KhV\nXHtpJK3tXXxzcHhBVBgZWyZbu8uGbQkj0NHVQSOVGFo8CPMVxYMF+xQTMAMntSOpRRlmK9yaklZy\nAoC4oOghrrROqEcQ4Z4hZJRl0tzRwqqkCJwd1Xy1L4+OTt2ovKYwkM2CkyzLKbZqSxiZnJp8UOjR\ntPuhUavGuzuCYJKDSkNcUDTlzVVo64stuqe5o4UzlTlE+kzG23lgolZbSQ5PoEvfRWrxcVydNVyZ\nFEFtYzu70gqHvlmwCav2J0mSdAswnMneTlmWN1rzWsLwnS7vrsnooxz5/g9BGE3zQ+eSUpjGkaIM\nJnsNndnheFkmOoN+1Kb0jJLCEth08ktSCtO4bEoS1y6eypf7cvl8dw7L509GpRTJb0abtZtnF9K9\nEddSHYAITmPkRJkMQIiryKcn2Le4oGjUSjVHijJYE331kNcbl5DHB41ucApy92eKVxgnyrJoam9m\nkqcrSxPC2HZEy+FTpSTPER/8RptVwUmW5Ydt3RHBNrr0OvLq8tG3uBEa4DPe3RGEQblonIkJmMGx\n0lOUN1US4OZn9lq9Xs+x0tN4O3uOSUXnpPAEzp0o5EhxBpdPXcT1l0Wx7YiWT3dlkxQTZJPNv4J5\nNq8+J0mSUpKkf0qS5GHrtoWhnavV0qnvRN/og7+36cqggmBPestoFA2ea+9sdR5NHc0kBMWMSWBI\nDvt+1R50Fx5cMDuQs9o6TuVVj/rrX+ysDk6SJK2RJOl2SZLOfwd8C6iRZVkkpBoHWZXdz5v0jd4i\nOAkTwryQOSgUiiGzRfRO6Y3y8yYjfzdfonwiOFUh09DWnbX8xsu781R+titnTPpwMRvJyOkp4Gog\nX5KkZyRJCpYk6WugSZblx23TPWG4Miu7/9HoGr3x93Ee594IwtA8nTyY4RvJ2ao86lrrzV6XXnIS\njUpDTMCMMetbcngCeoOeQ0XHAJgR4cOsKT4czSonv1R8/h5NIwlOXbIs3wTMoHtxRB5QJMvyQzbp\nmTBser2eM5U5aHTu0OmEnxg5CRPE/JBYDBhILT5h8nxFUxWFDaXE+Es4jmGuSGO9qZTCtN5jN/SO\nnrLHrB8Xo5EEJwOALMs1siz/CrgUuEKSpCts0jNh2LT1xbR0tqJonoSXuyOOGrHHSZgYEodIBGuc\n0kuwUaJXS/m6+CBNmkpmRXbvqG7ejADCAtzZe6yYitqWMe3PxcSWm3BTgZXAXyRJSh7qesH2Mnue\nN7VUuxMgRk3CBOLvOokpXmGcqpBp7hj4hv/986bRyQoxmKTwBAwYeqf2lEoFP7wsCp3ewBd7RTmN\n0TKS4DRguYwsy9nADcC7kiSZrt4ljJqsnudNXfXe+PuI4CRMLImhsej0ut7ceUatnW2crjxLhFco\nk1zGPh3XwrB4FCg4qD3ae2xJfCiTPJ347lABjS0dY96ni8FIgtMaUwdlWT4FrAeuH0HbwjAZDAay\nKrPxcPDA0OGMv7dYDCFMLOZqPJ0oz0Kn1435lJ6Rj7MXM/2iOFOVS3VLLQAatZLrFkfS1qHjfwdE\nQtjRMJKs5GcGOfepLMtvWtu2MHwljeU0tDcR4BAGKMTISZhwQj2CCHLzJ6P0NB1d349G0oqNz5vG\nZgm5KUk9e55SCtN7j61cOBlXJzVf7c+jXSSEtTlrc+slMfzceiIx7Cgy7m9yMwQAiD1OwoSjUChI\nDI3lyzPfcaI8i3khc9Eb9KSXnsTTyYOpPuOXjmtBWBzvHPuIlMI0rpaWAeDipOGqRVPYvCObHala\nrkqeMm79uxBZm1vv1ww/t951Vr6WYAHj/iZViy/QIKb1hAlpfshcvjzzHYeLMpgXMpfcmgIa2ptY\nOiUZpcLmCW0s5uXkQbT/dE6Wy1Q2V+PnOgmAay6Zyme7cvjnlpP8/fOThAe4s2bZNBbHDZ3EVhic\ntbn1RKCxIwaDgayKbNwd3Wgo7/7MIEZOwkQUNSkCb2dP0kpOotPrems3jeeUnlFS2DxOlsukFKZx\n7YwVAJzMrUKn/74WVX5pAy++370nSgSokRmVjyKSJP1WkiT30WhbGKiypYbq1lpm+kVRWdOKh6sD\nTo7WDooFYfwoFUoSQ+bS1NFMVmU2aSWnUCvVzBnDrBDmLAiNRaVQ9ubaA9i8w/RGXHPHBctZ/Q4m\nSdKlgEKW5b3nHX8SmCrLcuNIOydYJqui+x/CDN8oDta1MDlI5NwVJq75IbF8l7OX/53dRUFdEXMD\nZ+GkcRrvbuHu6EZMwAwyyjIpa6wg0N0fbbnpt7lCM8dt5YA2lc8zt1LUUEqoRxDXz1rJovDEUX3N\nsTaSkdPfgJckScqVJOknkiQ5SJL0V2AOcKdtuidYwrgYItRlMp1derEBV5jQZvlPx1HlwNGeKT1t\nXTEHtKnj3KtuxlV7B3vSGYUHmJ4gCjNz3BYOaFN5NeUdtPXF6A16tPXFvJryjt38jGxlJMFJL8vy\nfOAa4AqgAnAHfijLcpctOidYJqsyBxeNMw5dXgD4icUQwgR2uCiddt33S8lr2+rt5s03MXQuKqWq\nd0n5mmXTTF5n7rgtfJ651eTxLWaOT1S2yK2XKcvyzcBdwCJg/J9cXkRqW+spbapghm8kVXVtAASI\nPU7CBGbPb75uDq7MDZxFQV0RJQ1lLI4L5bHbEogI8kDZU7o92NeVS2NDRq0PRQ0lZo6Xjtprjgdb\n5tb7DLgV+EySpPF/enmRMKYsmuk3jfKa7pxkYgOuMJGZe5O1lzff5POm9hbHhfL6o0v54sVrmT8r\nkJKqZk7kVI3Ka5c0lKEYmDkO6N7EfCGxdW69FOBuYPNwV+tJkvSGJEl/lSTpK0mSbu05li5J0ps9\n/702gr5esDIrzwJ0r9SrbQXEMnJhYjP3Jmsvb77zQuagUar7rdozuvmK6QBs2ibb/HVLGst5ctef\n0Rn0Js+vnrXS5q85nkYSnH5u6qAsy3voXixx33Aak2X5AVmWfwqsBh7tOVwty/L9Pf+JOlEmZFXm\n4KhyYKp3OOU96fvFBlxhIrvezJusvbz5umiciQ2aTVFDKdq64n7npod7kzDDn1O51ZzKtd3oqbSx\ngid3baC2rZ47Ym/k4aS7mOwZ0rsx2c91EgtD4232evbA6qXksizvGOTcG9a2CzgDxv+rSkmSngeC\ngE9kWf5yBO1ecBrbmyisLyEmQEKtUlNR04K7iwYXp+FklhIE+2JcEr2lz1Lp1Xa2VDo5PIHU4uOk\nFKYT7tX/+dLaKyTSzlTw0bazREf6jvi1yoyBqbWe22Nv5Ac96ZOMP4+/HHqXvQWH2Zqzh6umXz7i\n17MX9rhT8zngCQBZlpcBSJKkpnuq8LQsy6KASo8zVd0/ipl+0zAYDFTUthLq7zbOvRKEkVsUnmhX\nweh8CUExOKg0HCw8yk3RV6NQfP+UY0aED7HT/MjIruRMfg0zInysfp2yxgr+sGsDNa113B57Q29e\nv75uj72B9NJTbDr5JQtC48alrMhoGL9kVSZIkvQosFeW5UN9j/csTd8GzBqXjtkp4+bbmX7TqG/q\noKNTJ1bqCcIYcNI4ER8cQ2ljBQV1RQPO2+LZU1lTJU/u+jM1rXX8aO4NXC0tN3mdh5M7t829nrau\ndv517GOrX8/e2E1wkiTpfqBOluVPzFySBBwfwy7ZvazKHFRKFdN8InrLRYvFEIIwNs5ftddXdKQv\n0ZGTSDtTwVlt7bDbLmuq5MmdG6hureW2uT/kmhmmA5PRZVOSmOEbyZGiDI4Wnxj269kjuwhOkiQt\nAH4FxPes2HtTkiRfSZI+kCTpb5Ik/Rv4TJZl7Th31W60draRV6clyicCB7VDn+AkFkMIwliIC4rG\nUe3IQe1RDAbDgPNrr5AA+Hj72WG1W95UyZO7jIHpeq6dccWQ9ygVSu6ZdysqhZJ30j+irat9WK9p\nj+zimZMsy4eBCBOn1o1xVyYMuSoPg8HATL8oACrEHidBGFOOagfmBcdwQHuUvFotkT6T+52fE+XL\nzAgfDp8uI7eojshQryHbLG+q5A+7NlDdUsu6Odf3Zj+3RJhnMNfOWMHnWd+y+dR/+VHsDcP+nuyJ\nXYychOEz5tOb5dedJsW4AVc8cxKEsZMcPg+Ag9qjA84pFIre0dNHFoyeKpqqeHLXn6luqeXWOau5\nbqblgcnohllXEuDqy9dnd5JfO/BZ2ERiFyMnYfiyKrNRKBRM950KQEXPBlw/8cxJEMZMbOAsNCoN\n/zu7i6/P7hyQITxO8mN6uBcpJ0spKG3oVzGgb2bxQDc/GtubaOxo5tY5q1k907o9XQ5qB+5OuIXn\n9r7OP9M+5Ollj45rkcaRmJi9vsh1dHWQU1PAFK8wXDTdz5gqaltwdVLj5iz2OAnCWDlSnEGnrhOd\nQWcyQ7hCoeBmE6On8zOLlzSW09jRTHJYgtWBySg2aBbJYQlkV59je+7+EbU1nsTIaQLKqcmnS9/F\nzJ4pPYPBQEVNC4GTXMe5Z4JwcTGXpPbttI/Irs5HpVCiUqjwm1FISmUO7x4pxsfDma/lnSbvK24o\ns0m/7ohbQ0ZZJh+e2ML8kLl4OXvapN2xJILTBJTZm+y1ezFEY0snbR1ij5MgjDVzyWibOpr539k+\nAcgDNB7wv3M5VrU3XN7Ontw65zreStvEuxmf8POku23S7lgSwWkCMi6GECv1BGF8hXoEoa0vHnA8\nyM2fnyf/BJ1eh86go0un49WP06mobeKBNXP5PGcLVS01JtuzxN5jRWzekY22vJHwAHfWLJvG4rjQ\nftcsj7yUPecOcVB7lKVTkpgbOLFyGIhnThNMl17H2ao8wjyDcXfsTlUkEr4Kwvgwl6T2ppirmeId\nRtSkCCTfSGYHTOf2xZeiq/cj87iadXNXm7zPkuS2e48V8eL7aeSXNqDXG8gvbeDF99PYe6z/6rzu\nvU/rUCqUvHV0Ix1dHWZatE8iOE0weTUFtOs6ekdNAJUiO4QgjItF4Ym9GcJVCiWTPUN4OOkuk3kB\nk2OCCQtwZ2daIZGusyy+73zmNvVu3pE94FiEdyg/mH455c1VfJb1zfC/wXEkpvUmkAPaVN471p3d\nKb3kJAf8olgUniiKDArCOLI0Sa1SqeCm5dN5+YM0PtmZzc/WDC+5rcFgYH9GCQVljSbPF5abPr4m\n+mpSCtP54sw2LgmfT6infdTFGooYOU0QxqWndW0NAFS11PYuWa2oEUUGBWEiuDQ2hBA/V3akantT\njlnidF41j722jxfeH7jZ1ygswHR9Vye1I3fF34xOr+OfaR+iN1OscDAHtKk8+u0zrP34AR799pne\npfKjSYyc7FxNax1Zldm8nfaRyfNbMrfSVrsIZ0cV7i5ij5Mg2DOVUsGaZdP586ZjfLozm5/eMHfQ\n60sqm3j360xSTnav4ls0N5iZET689cWpAdeuSpo84JjRvJA5zA+J5UhxBvd/9Vvq2hoGbBg2x/jB\n2Mi4lwsY1bImIjiNg747w/v+ghgMBiqbq8mszCarMoesymzKmioHbauooRR9bQv+3i79asoIgmCf\nlsSHsmmbzHeHtdy0fDqTPAcuZGpo7uCjbTJfHziHTm9gxmRv7r42urc2lLe7I5t3ZFNY3oiHqwO1\nje1sP6Jl2bxwnBxNv61HB0gcKc6gprUO+D7ItHW1I02KpLatntrWnv/a6qnr+TO7+pzJ9rZkbhXB\n6UJi7lPIt2d3U9VSS3Xr9+n1XTTOxAdFM9NvGtvz9lHeNLDsc5B7INltXSJtkSBMEGqVkjXLpvP6\nxxl8tiuHe1bH9J7r7NLx1b5zfLxdprmti8BJLvz4B7NJnhPU78Pn4rjQ3qXjBoOB1z/OYNsRLS9/\nmNC7iLQAABzLSURBVMb6O+ajVA78oGouW8TfUz8w21eFQmEy4zrYbk+WOSI4jTFzO8rl6jw8HN1Y\nEBrHTL8oZvlNI9wzBKWy+7Ggr6t3v6BmdGnQErKpFRtwBWECWZoQxrtfn+arfXn8d/85wgLdmBPp\nx+HMMipqWnBz1nD3tdH8YFEEGrVq0LYUCgU/vWEu5TUtHDpVxntfZ3LnNbMHXDdYMFkeeSneTh54\nO3vi7eyFt5MHXs6eeDq68/h3fzS5l8vSPVnWEsFpjJn7BVEqlPzzuhfMTs0Zh89b+kwHrp61EmV9\nKHBELIYQhAkk5WQJjc2dQPfIp6C0kYLSRpQKWL0kkpuWT8fdxcHi9jRqJevvSOTR1/bx2e4cgv1c\nWbkwot815jYMT/YM4d55t5pt+/pZK01+MLZkT9ZIiOA0xsz9goR5BA35zMjUktUv9+YC4O8jNuAK\nwkRhak8SQLCfG3dfG21Vm24uDvy/nyzkl6/u5a+fniDAx4XY6f69560NMuY+GI/m8yYQwWnMrZ65\nktcO2e5TSLnYgCsIE47WzJ6k0qrmEbUb5OvKb++cz+/+dpA/vZfKCw9eSnhgd5mOkQQZS/dy2ZII\nTmMsqqdapovGmfau9hF/CqkQRQYFYcIJD3Anv7RhwHFze5WGY/bUSTx8cywvf5jOU28f5qWHFuPl\n7giMT5CxlghOY+xMVfc03E3RV3PV9MtH3F5FbSsOGhUerpbPTwuCML7WLJvGi++nmTxuC5clhFFS\n1czG72Se/ddhnv3pIhw0gy+ssDciQ8QYMwanGb6RNmmvoqaFAB9nscdJECaQxXGhPHZbAhFBHqiU\nCiKCPHjstoQBmcVH4pYVEkviQjlTUMurm46ZXRJur8TIaYzJVbk4qh2Z7DXyX8KWtk6aWjuRJnvb\noGeCIIylvnuVRoNCoeChm2OpqG1hb0YxwX5urFs1Y9Rez9bEyGkMNbY3UdxQxvRJU1ApRz7ErqgV\nOfUEQTDPQaPit3fOJ3CSC5u2yew8WjjeXbKYGDmNIbkqDwDJhlN6ILKRC4JgnqebI0/cvZDHXtvL\nq5vS2bj1DBV1rWaLFNoLMXIaQ7Z+3tRbKkMUGRQEYRBhAe784JKp6A1QVtMyaJFCeyGC0xiSq3JR\nKBRMmzTFJu0ZU+6LkZMgCEM5crrM5HFzG4LHmwhOY6RD10luTQERXqE4a5xs0qYxOAWIZ06CIAzB\n3MbfgtIGMs9V291qPhGcxkhejZYufZfNnjdB9zMnjVqJp5ujzdoUBOHCFG5mg68BePwv+3nkz3vY\nebSQzi7d2HbMDBGcxsiZqhwAZvhG2azNitpW/L2dTabHFwRB6MvcBt+br5hOUkwQecX1bNiYzl3P\nbOPDrWeobWgb4x72J1brjRFbL4Zobe+iobmDyBBPm7QnCMKFzbgqz1ikMOy81XrlNS18feAc3x0u\nYON3Mpt3nOWS2BCuvXQqpVXNbN6Rjba8ccxW+YngNAb0Bj1nq/Lwc52Ej4uXTdoUiyEEQRiuwTb+\nBvi4cNc1s7l1hcSutEK+2p/H7rQidqf1X81nXOVnbG+0iGm9MVDSUE5TR7NNnzf9//buPUyuur7j\n+Ht2djfs5rJkc+luLuS+3xS5KCmBxJpIorWAF9RS0QCPEUEIavtYtbW0GLXlqbVaqSXY2poWjIZL\n5SJ4IylmgYCEkASU+iVkg9lkcyFXyMVkL9M/ZmYzu9nN7lzPmZnP63nywDl75vy+M8+Z+Z7fOd/z\n+72mB3BFJA/OGFLJpXOncMfnFvDlG+ZQ08+07/mu8lNyKoBcX9KDlGec1HMSkTyIRCK8xcZyvL3v\nAonWfqr/ckXJqQBOFkPktlIP9ACuiORXf1V+uZje43SUnArA97YwtKqGCXWNOdtn9zNO6jmJSB71\nV+WXq+k9+qOCiDw7eOwQuw+/xlsaz6EikrtzgT0HjlIZjTByeG4e6BUR6ctAVX75ouSUZ8n7TTZ6\nak73u2f/McacWatnnEQk7/I9vUdfdFkvz04WQ+Tu4dvj7Z0cPHycsfW63yQipSk0PSczu4N4spwA\nrHT3FWb2HuAqoBNY6+7fDjLGTPjeLUQrokyvn5SzfZ4shtD9JhEpTaFJTu5+M4CZRYF1ZvYwcKO7\nX55Yf5eZrXb3cA6h24ffdRxn64FWptVPorqyOmf77X7GScUQIlKiwnhZrwbYC8wFVqWsfwi4JJCI\nMvTKvlfpinXl9OFbgN0H1HMSkdIWxuR0G3ArUA/sT1m/HxgZSEQZysfDt3Dysp7KyEWkVIUqOZnZ\nZ4Fmd38G2Ec8QSXVJ9YVDc9XpV6i5zRGD+CKSIkKTXIysyXAQXe/P7HqWWBhyibvBdYUPLAMdXXF\nB3ttHD6WujNG5HTfe/YfJVoRYdQIPeMkIqUpFAURZnYR8Hngx2Z2J/H5r/4W+J6ZrQROABuLqRhi\n26E2jnX8jotHX5Dzfe85cJRRZ9YQjYbm3EJEJKdCkZzc/ZfA5D7+tDLxr+gkx9PLdTFEe0cn+18/\nzrnTRud0vyIiYaJT7zzpLoYYk9vkdLKMXPebRKR0KTnlie/dwoghw2gcNjan+92tB3BFpAyE4rJe\nqdl7ZD/7jh7gwvHnE4mcOvZd84btGU95vEeTDIpIGVByyoOTg72eekmvecP27imOIf0pjzVVhoiU\nA13Wy4PTTS5476qX+3zNvz/4Ik9s3MH2PW/Q2RXrc5vmDdt59MmtANxx/yaaN2zPUcQiIuGinlMe\n+N4WqqJVTB15Vo/1XV0xtu3qe2rjQ4dP8I93PwfAkOookxtGMGV8HVPGjWDquDq27znM7fds6N5+\nx2uH0+pxiYgUEyWnHDt64hjbDu5g5pjpVEZPfrxdXTHuuH8TffeJoKG+lsv/cAotOw6xte11Xtl+\nEN92YMD27lu9WclJREqOklOOvbxvKzFiPYYs6uyK8a/3bmTVum2Mra9hz/5jp7zumst+v0eSae/o\npHX3Yba2HaKl7RAPN7f02V7r7r57YiIixUzJKcdO3m+KTy7Y2RXjX+7ZwP8+18r0iWfylRvm8Lzv\nGXDK46rKKFPH1zF1fB0LgRc27+XVna+f0t7E3xue9/ckIlJoSk455nu3ECFC0+gpdHbF+ObK5/nF\n+u00nXUmX7phLsNqqjKa8vjKhTN6VPmlrhcRKTVKTjnU0dXJ5n1bmVDXSE20hm98fz3NG3Zgk0by\npevnMLSmKuN9J5PZQD0uEZFSoOSUQ68eaOVEZzs2aipf//7zPLFxB78/uZ6l119M7RmZJ6akTHpc\nIiLFSMkph5IP327+TQW/2biDs6fU88WP5yYxiYiUEyWnHPq/1+LFEP4SvGnqKL748YupGaKPWEQk\nXSU3QsTS7zwdyMgJJ9o72dD6G2InhnDOWRNZqsQkIpKxkktO2/fER04oZIJq7+jkS3evpqPid4yg\ngVuvu5gzlJhERDJWsr+g+R45IXVk8SFVUU4M/y3VU+F9f3AhZ1SX7McqIlIQJfsrms+RE3qPLH7s\neAdVjfGhhs75PT13JCKSrZK7rJfUFYvxUPMWOju7cr7vvkYWrxh+gEhXJZPOHJ/z9kREyk3JJqch\nVVH+46Ff8ZlvNuO/3Z+TfXZ2xXhiww5+23tk8coTVNQcofNwHdGKaE7aEhEpZyV3WW/C2GFce8Us\nzp8xhv965CVWrdvG5771BH88ZzLXXnY2wzIYpaGzK8YTG3dw7yqndffhU/5eMewgAMNjDVnHLyIi\nJZicll4/hwkT4oUQf3bVW1h44USW/c8mfrL2VZ5+cSfXvfcc5r9lfJ/Tp/fW2dnFmg3xpLTjtSNU\nVER45+yzmNQ4nP946Nfd21UMi99vesfZ5+fnTYmIlJmSS069nTNtNLd/5hIeXPMKKx97ma+vWM+q\nZ3/LTR88n/FjhvX5mo7OLn6xfjv3rn6ZnXuPEK2I8K6LJ/EnC2bQMGooACOHn9E9zl3tqDfoIMIH\nLrqwkG9NRKRklXxyAqiqrODKhU287c3j+bcHXuS5/9vNJ7/2OFcunEHDqFoe+MUWtu1+g4ljh2GT\n6tm0+TV27z9KZTTCpXMm8ycLZjC2vrbHPpPj3J3obOejP3yMyXUTqKk6I6B3KCJSWsoiOSU1jBrK\nrdddxNoXd/LvD7zID37uROt3UjluC9UTjrDr2FC2b55G7MA4Ln/rFD54yQzGjKw57T5b9m+jo6uj\ne/4mERHJXslV69225l95atu6fv8eiUR463njWPb5S6gdv4vq6ZuoqD1MJBKjovYw1dM3MXryfm78\nwHkDJiY4ObmgjZ6Ws/cgIlLuSq7n1PbGLm5/+rs8u30To2tHcuTEUY60H+No+1GOnDjWvXyk/Six\n8bE+93Fo2K8G3Z4nRiKfqeQkIpIzJZeckp5uPXXW2CHRamqraxh5xgjGj2jAX9sCfRTtVdQc4S9/\ndhuzxp/LrHHnMWXkRCoip3Yyu2Jd+N4WxgwdRX3tmfl4GyIiZalkk1NFpIK/W/g5aqtrGFZVS21V\nDZXRnm/3pge+yL4Te055bVWkmm2vt7H1YCv3//rHjKypY1bjucwafx7njjWqK6t5ats67v3VIxw+\ncYSuWBdPbVvHW89StZ6ISC6UbHKaOKKR6aMmn3abq2e9m9uf/u4p65dcfDUXNJ7Lpl0v8VzbC2xo\n+xWrWp5kVcuTVEermDCikZYD27q3P9p+rHs/SlAiItkr2eR0xdnvGnCbZCJ58KWfsf31nUwY0cgV\nZ7+re/3FEy/g4okX0NXVxcv7tvJc2wusb3uhR2JK9eBLP1NyEhHJgZJLTuOHN/CROR8cdJJ461kX\nDrhtRUUFM8dMY+aYaVx9/vu56t6b6YqdOqDs9td3ZhSziIj0VHKl5F+Y/8m8914mjGhMa72IiKSn\n5JJTIby/n0uGg7mUKCIiAyu5y3qFMNC9KhERyY6SU4YGc69KREQyE5rkZGYVwJeBWe5+aWLd88Az\niU063P3TQcUnIiKFE5rkBFwGPADMTlm3192XBBSPiIgEJDTJyd0fATCz1NVRM/sq0Ajc7+4PBxGb\niIgUVmiSU1/cfSGAmVUC95nZr919Sz+bRwF27dpVqPBERGQQUn6Xo4N9TaiTU5K7d5jZY8DZQH/J\nqRFg0aJFBYtLRETS0kj/v+E9hDE59TFOOABzgEdO87p1wNuAnUBnroMSEZGMRYknpv4n2+sljMnp\nRPJ/zGwF8AZQC/zQ3fse1A5w9+PAk/kPT0REMjCoHlNSJBbre8I9ERGRoGj4IhERCR0lJxERCR0l\nJxERCR0lJxERCR0lJxERCR0lJxERCR0lJxERCR0lJxERCR0lJxERCR0lJxERCR0lJxERCR0lJxER\nCR0lJxERCZ0wTpnRg5k1ALcAXcBw4K/dXdPdioiUsNAnJ+CrwCfd/Y2gAxERkcII9XxOZnYh8H6g\nCmgAHnf37wYblYiI5FvYe06TgZnAn7p7h5ktMzN396d6b2hmQ4AL0TTtIiJh0z1Ne2LW8gGFPTkd\nBR5z947E8o+AWcApyYl4YnqiUIGJiEja3gY8OZgNw56c1gMfBe5MLM8G1vSz7U6AFStW0NDQkP/I\npGTMmDGDjo4OrrnmGu6++24qKyvZvHlz0GGJlIxdu3axaNEiSPxOD0aok5O77zKzn5jZXUA70OLu\nv+hn806AhoYGJkyYUKgQpQTMnj2b5uZmJk2aREdHB3PnztUxJJIfg77lEurkBJAogFARhOTN8uXL\nWbx4MQDz5s1j+fLlAUckInoIV8re1KlTWbMmfrV4zZo1TJ06NeCIRETJSUREQkfJSUREQqdoklNi\nGCMRKQMtLS3Mnz+fqqoq5s+fT0tLS9AhSYEVRXIys6nAGjO7c8CNRaToLV68mObmZjo6Omhubu4u\nWJHyEfrkZGaVwDJgCfGnjEWkxK1duxaAJUuW9FiW8hH65AR8Cfhn4JWgAxGRwpg7dy4AY8eO7bEs\n5SPUycnMFgCvu/vPEqsiQcYjIoWxfPly5s2bB+jZs3IV6uQE/BEw2cyWAX8PzDWzGwOOSUQGIZui\nBj17JqEeIcLd/yr5/2Y2CbjF3b8dYEgiMkjJogagu6ghmXBEBhL2nlOqTqBjwK1EJBRU1CDZKJrk\n5O7b3X1J0HGIyOCoqEGyUTTJSUSKi4oaJBtKTiKSFypqkGwoOYmISOgoOYlkoZjGgCumWEVCn5zM\n7A4zu9PMfmRmi4KORyRVMY0BV0yxioQ+Obn7ze5+E3AF8BdBxyOSKtNy6SB6MSrtlmIy6ORkZpfm\nM5BBqAH2BhyDSA+ZlksH0YtRabcUk3R6Tp/KWxSDcxtwa8AxiPSQabl0EL0YlXbnh+7l5Uc6yWmW\nmX0kb5Gchpl9Fmh292eCaL/Y6cuTP5mWSwfRi1Fpd37oXl5+DJicEmPaAVwG7DSzD+c3pFPaXwIc\ndPf7C9luKdGXJ3zUiykdupeXH6dNTmb2fuBNAO6+3t0fB14xs+sKEZyZXQR8HrggUbG3zMxGFaLt\ngRRTb0RfnvBRL6Z06F5efvSbnMxsNPA+d/9x6np3Xwc8ZWaf6rV9Y66Dc/dfuvtkd1/i7jcl/rsv\n1+1koph6I/ryiOSPesH50W9ycve9wCNm9scAZjY+5c/VwHwz+7mZ3WRmBnwiv6EOzoc+9CGV5fai\nL49I/qgXnB+nvayXuM/zcmLxK2b2CTNbB2wApgDrgSuBjcDf5DPQwXr22WdVlttLuXx5iulSq4ic\n3oAFEe6e/IZ/lHg59y+BWe4+y92/4O4LgFHAPXmLMk0qyy1PxXSpVcJHJzfhkk4p+YPAOHf/pLtv\nTP2Dux8FfprTyLKgstzyVEyXWiV8dHITLukkp2+5+/H+/ujud+cgnqzNnj1bvZgyVUyXWiV8dHIT\nLoNOToky8oIzs/eY2Qozu8vMbhxo+3vuuUe9mDJVDpdag7j0VC6Xu3RyEy6hHvjVzIYDN7r7Ine/\nFphrZjNy2Ua5fPHKQTlcag3i0lO5XO4qh5ObYhLq5ATMBValLD8EXJLLBsrliyelIYhLT+Vyuasc\nTm6KSWU2LzazD7l7Pqv06oH9Kcv7gemne8FVV11FZeXg31ZzczMA48aNo62tjebmZt7+9rcP+vWv\nvvoqjz8eyBXPtBVTrNnI9H1m8/kUqs2hQ4dy6NAhHn300e7ldI7XINoM4nPNRhDHT7H42Mc+xrXX\nXluQtrLtOc3KSRT920c8QSXVJ9blTF1d3WmXB1JdXZ1x221tbQV9XTHFmunrIPP3mc3nU6g2Z86c\nSV1dHe3t7dTV1TFz5szQtxnE51pMx082sRb6+7V69eqMXpeRWCyW8b+mpqavZfP6Qez/zKampkdS\nlv+7qalpRj/bTm5qaoq1trbG0rFly5bYvHnzYpWVlbF58+bFtmzZktbrs7F06dKCvi4bhY41iPco\npaOYjp9sYi2W72Vra2usqakp1tTUNDk2yN//rC7rAbGcZMh+uPtBM/uema0ETgAb3X1zLttIvc4s\nIiLhkG1yyjt3XwmsDDoOEREpnLBX64mISBlSchIRkdDJNjlFchKFiEiZSQ4AABR8tI9CtpmpbJNT\neN+ZiEiIJQcAAAo+2kch28zUoAsizOxSd/9J6jp3vzPThs3sFuAd9Kz4iwBRd59nZlcDfwgMA44D\nN7h7Z6btiUjpa2lpYfHixSxYsID58+ezfPny0I70kBxpY8+ePT2WS63NTKXTc/rUwJuk5RDwT+6+\nIPkPuB54CcDdv+fuN7r71cBrwDtz3L6IlJhi6hkkB5ZdtmxZj+VSazNT6SSnWWb2kRy23Qa8ZGbv\nADCzs4BzgJ/3se0Y4NUcti0hVUzXxCV8iqlnkBxotrKyMu2BZjP9nmTTZqGlk5wuA3aa2Ydz1bi7\nbwVazeyDwEXu/iC9iizM7O3Afnf/Ta7alfAqpjNfCZ9i6hkkBwBob29Pe6DZTL8nmbYZxEljOvM5\nrU/M6fSKmV2Xwxj2AlOI96R6MLOZwDXA53PYnoRYMZ35SvgUU88gG4X+ngRx0ph2tZ67rwOeMrMe\n96DMrDHdfZnZCOByd/8n4JiZzSZRIGFm04EvADe5e16HSZLwKKYzXwmfbHojxaTQ35MgThoHnZzM\nbHzKYjUw38x+bmY3mZkBn0iz7aHAle5+F4C7Pw9EOTnS+UOJ/95uZsvM7N1p7l+KULmc+Ypko9Df\nkyBOGtMZW+8rZvZL4OPABcBG4sULVwLfAKqApWns7xJgmpktSlkXAWYCt7j7m9LYl5QIDcQrMrBC\nf0+WL1/O4sWLWbt2LXPnzi3ISWM6yemjwPuAHwDXu/vG5B/MrBb4TjoNu/vH0tleRESCEcRJYzrJ\n6UHgw+5+vPcf3P2omf00d2GJiEg5S6cg4lt9JaYkd787B/FIyOi5IxEJQjql5I/nM5D+mNkoMwv9\nvFOlSs8diUgQAvvRH2hsvZR1/0m8AOOsAoYnCXruSESCEGSPJDm23qPJFYlnmz6bsvxp4AmgtvDh\nCcRLRpubm/XckYgUVJCTDZ52bD0zOw94s7t/nRKbN6qY7uNk+jxFMb1HEQmfQGfC7WdsPcyshvjo\nEEuCjC9fiuk+TqZP3BfTexSR8AnDNO29x9aLAH9APLZvmNmdwEwzuyPxPFXRK4f7OOXwHkUkfwKt\ngksdW8/MLkiOrefuTxC/15Tcbpq73xxYoDlWDvdxyuE9ikj+BNlzGmhsvVT9Pl9VjMph/LhyeI8i\nkj9B9pxOO7Ze6obu/p5CBpZvmQ4FUkxTUGuMPBHJRmDJSWPrpS9ZZLBgwYLuIgMlABEpRWEoiJBB\nUpGBiJQLJacioon4RKRcKDkVERUZiEi50ICqRURFBiJSLkI78KuZRYDPEB/wdQiw2t3vK3ykIiJS\naGEe+PXPgXWJsfVERKSMhHbgV+Bc4AIz+46Z3W5mdQHFKSIiBRboPSd332pm1YmBXyvc/T4z+0Di\nz38E/IO7f9PM5gBfA244ze6iALt27cpv0CIikpaU3+XoYF8ThoKI5MCvT/da/4K7vwzg7k+b2dIB\n9tMIsGjRogE2ExGRgDQCWwazYRgHfk06amZj3X2PmU0Dtg+wu3XA24CdQGeeQhYRkfRFiSemdYN9\nQSQWiw28VR6Y2TVAtbv/Z8q6OcC73f2WREL6e+AA8ZlwP+fuewIJVkRECirI5PRdYBo9ezkRYKa7\nNwYSlIiIhEJgyUlERKQ/Gr5IRERCR8lJRERCJwyl5DlhZu8BriJ+D2utu3874JBCw8yeB55JLHa4\n+6eDjCcszKwC+DIwy90vTazTcUS/n42OoxRmdgfxE/wJwEp3X6HjJ67XZ/MDd/9+usdPSSQnMxsO\n3OjulyeW7zKz1e6+OeDQwmKvuy8JOogQugx4AJgNOo566fHZJOg4SuHuNwOYWRRYZ2YPo+MHOPWz\nAb4P7Evn+CmJ5ATMBValLD9EfBr4sjso+hE1s68Sf87gfnd/OOiAwsDdHwEws+QqHUcJfXw2oOOo\nPzXEBxPQ8XOq5GcDUJHO8VMqyake2J+yvB+YHlAsoePuCwHMrBK4z8x+7e6Dekq7zOg4Og0dR/26\nDbiV+Eg3On56Sn42aR8/pVIQsY/4D0tSfWKdpHD3DuAx4OygYwkpHUeDoOPoJDP7LNDs7s+g46eH\nXp9Nt8EeP6WSnJ4FFqYsvxfQrHx9mwNsCjqIkIkk/qvj6FSRftaX/XFkZkuAg+5+f2KVjp+EPj6b\n3gY8fkrmIVwzuwq4AjgBbHT3bwQcUmiY2QrgDeLDQD3g7g8EHFKomNmjKTexdRyl6PXZ6DhKMLOL\ngHuAHxNP4DHgb4F3UubHTz+fza3A7aRx/JRMchIRkdJRKpf1RESkhCg5iYhI6Cg5iYhI6Cg5iYhI\n6Cg5iYhI6Cg5iYhI6Cg5iYhI6Cg5iYhI6Pw/yLjVLc+yYDEAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10e9f0790>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_fit(ahn_df, res_ahn, np.exp)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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Phx0O6JvcULvVsHaX3OeMIkG4HG3J+ZH6tkbumLICVwfDnYu6xjYKyhqYPtEf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\ngg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10f78fa50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_fit(hong_df, res_hong)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* NA 포함한 데이터프레임 생성"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def predict_votes(index):\n",
" index = str(index - 1)\n",
" _date = pd.concat([poll_df_today, a2_df_today, h1_df_today, trend_df_today],\n",
" axis=1).loc[index]\n",
" info_m = pd.DataFrame([_date[\"trend_m\"]], index=[\"trend_m\"]).T\n",
" info_a = pd.DataFrame([_date[\"stock_a2\"], _date[\"trend_a\"]],\n",
" index=[\"stock_a2\", \"trend_a\"]).T\n",
" info_h = pd.DataFrame([_date[\"stock_h1\"], _date[\"trend_h\"]],\n",
" index=[\"stock_h1\", \"trend_h\"]).T\n",
"\n",
" try:\n",
" m = res_moon.predict(info_m)[0]\n",
" a = np.exp(res_ahn.predict(info_a))[0]\n",
" h = res_hong.predict(info_h)[0]\n",
" print u\"문재인: {}%\".format(m),\n",
" try: print \"|| (real: {}%)\".format(poll_df_today.ix[str(int(index)+1), \"Moon\"])\n",
" except: print\n",
" print u\"안철수: {}%\".format(a),\n",
" try: print \"|| (real: {}%)\".format(poll_df_today.ix[str(int(index)+1), \"Ahn\"])\n",
" except: print\n",
" print u\"홍준표: {}%\".format(h),\n",
" try: print \"|| (real: {}%)\".format(poll_df_today.ix[str(int(index)+1), \"Hong\"])\n",
" except: print\n",
" \n",
" return m, a, h\n",
" except IndexError:\n",
" raise IndexError(\"Not enough data provided for prediction\")"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"* crawling page 4..."
]
}
],
"source": [
"poll_df_today = poll.poll_important_df[7:]\n",
"poll_df_today.columns = [\"Moon\", \"Ahn\", \"Shim\", \"You\", \"Hong\"]\n",
"\n",
"a2.get(); h1.get();\n",
"a2_df_today = pd.DataFrame(dict(a2.items), index=[\"stock_a2\"]).T[4:]\n",
"h1_df_today = pd.DataFrame(dict(h1.items), index=[\"stock_h1\"]).T[4:]\n",
"for i in [a2_df_today, h1_df_today]:\n",
" i.index = [j.replace(\".\", \"\") for j in i.index]"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"pytrend2 = TrendReq(gid(), gpw())\n",
"pytrend2.build_payload([u\"문재인\", u\"안철수\", u\"홍준표\"], timeframe='today 3-m')\n",
"trend_df_today = pytrend2.interest_over_time()\n",
"#trend_df_today = trend_df_today.resample('D').max()\n",
"trend_df_today.reset_index(inplace=True)\n",
"trend_df_today.index = trend_df_today.date.astype(str).str.replace(\"-\", \"\").values\n",
"del trend_df_today[\"date\"]\n",
"trend_df_today.columns = [\"trend_m\", \"trend_a\", \"trend_h\"]"
]
},
{
"cell_type": "code",
"execution_count": 33,
"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>Moon</th>\n",
" <th>Ahn</th>\n",
" <th>Shim</th>\n",
" <th>You</th>\n",
" <th>Hong</th>\n",
" <th>stock_a2</th>\n",
" <th>stock_h1</th>\n",
" <th>trend_m</th>\n",
" <th>trend_a</th>\n",
" <th>trend_h</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>20170428</th>\n",
" <td>45.5</td>\n",
" <td>23.7</td>\n",
" <td>6.8</td>\n",
" <td>3.9</td>\n",
" <td>15.3</td>\n",
" <td>4075</td>\n",
" <td>2605</td>\n",
" <td>64</td>\n",
" <td>46</td>\n",
" <td>57</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170429</th>\n",
" <td>.</td>\n",
" <td>.</td>\n",
" <td>.</td>\n",
" <td>.</td>\n",
" <td>.</td>\n",
" <td>.</td>\n",
" <td>.</td>\n",
" <td>60</td>\n",
" <td>33</td>\n",
" <td>50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170430</th>\n",
" <td>42.6</td>\n",
" <td>20.9</td>\n",
" <td>7.6</td>\n",
" <td>5.2</td>\n",
" <td>16.7</td>\n",
" <td>.</td>\n",
" <td>.</td>\n",
" <td>67</td>\n",
" <td>43</td>\n",
" <td>52</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170501</th>\n",
" <td>46</td>\n",
" <td>19.2</td>\n",
" <td>8.2</td>\n",
" <td>4.8</td>\n",
" <td>17.4</td>\n",
" <td>.</td>\n",
" <td>.</td>\n",
" <td>65</td>\n",
" <td>41</td>\n",
" <td>62</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170502</th>\n",
" <td>39.3</td>\n",
" <td>21.8</td>\n",
" <td>9.2</td>\n",
" <td>4.9</td>\n",
" <td>16.5</td>\n",
" <td>3325</td>\n",
" <td>2180</td>\n",
" <td>70</td>\n",
" <td>40</td>\n",
" <td>86</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170503</th>\n",
" <td>42.4</td>\n",
" <td>18.6</td>\n",
" <td>7.3</td>\n",
" <td>4.9</td>\n",
" <td>18.6</td>\n",
" <td>.</td>\n",
" <td>.</td>\n",
" <td>73</td>\n",
" <td>34</td>\n",
" <td>68</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20170504</th>\n",
" <td>43.2</td>\n",
" <td>21.1</td>\n",
" <td>8</td>\n",
" <td>4.8</td>\n",
" <td>20.1</td>\n",
" <td>3210</td>\n",
" <td>2030</td>\n",
" <td>99</td>\n",
" <td>41</td>\n",
" <td>84</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Moon Ahn Shim You Hong stock_a2 stock_h1 trend_m trend_a \\\n",
"20170428 45.5 23.7 6.8 3.9 15.3 4075 2605 64 46 \n",
"20170429 . . . . . . . 60 33 \n",
"20170430 42.6 20.9 7.6 5.2 16.7 . . 67 43 \n",
"20170501 46 19.2 8.2 4.8 17.4 . . 65 41 \n",
"20170502 39.3 21.8 9.2 4.9 16.5 3325 2180 70 40 \n",
"20170503 42.4 18.6 7.3 4.9 18.6 . . 73 34 \n",
"20170504 43.2 21.1 8 4.8 20.1 3210 2030 99 41 \n",
"\n",
" trend_h \n",
"20170428 57 \n",
"20170429 50 \n",
"20170430 52 \n",
"20170501 62 \n",
"20170502 86 \n",
"20170503 68 \n",
"20170504 84 "
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.concat([poll_df_today, a2_df_today, h1_df_today, trend_df_today],\n",
" axis=1).tail(7).fillna(\".\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"* 지지율 예측"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"문재인: 42.3235531919% || (real: 42.4%)\n",
"안철수: 23.1095658307% || (real: 18.6%)\n",
"홍준표: 16.9263891115% || (real: 18.6%)\n"
]
},
{
"data": {
"text/plain": [
"(42.323553191853854, 23.109565830744803, 16.926389111539116)"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"predict_votes(20170503)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"문재인: 45.776631094%\n",
"안철수: 23.269674707%\n",
"홍준표: 16.3895555256%\n"
]
},
{
"data": {
"text/plain": [
"(45.776631094048739, 23.269674706990912, 16.389555525555679)"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"predict_votes(20170505)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"문재인: 45.776631094%\n",
"안철수: 23.269674707%\n",
"홍준표: 16.3895555256%\n"
]
},
{
"data": {
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pqbceaWkQEFBy+5AQMQnu2hXatYO2bcWjtLKxnTtX3/47kRvpmT/6SEyUSppE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\nCCGEaEIk8QshhBBNyP8D8uJSi/Kv/J0AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10fe97210>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(7,4))\n",
"plt.plot(res_moon.predict())\n",
"plt.plot(np.exp(res_ahn.predict()))\n",
"plt.plot(res_hong.predict())\n",
"rr = len(res_moon.predict())\n",
"plt.plot(np.arange(rr), df2.Moon, \"b--\")\n",
"plt.plot(np.arange(rr), df2.Ahn, \"g--\")\n",
"plt.plot(np.arange(rr), df2.Hong, \"r--\")\n",
"plt.xlim(0, 25.5)\n",
"\n",
"m, a, h = predict_votes(20170505)\n",
"plt.scatter([rr], [m], s=30, color=\"b\")\n",
"plt.scatter([rr], [a], s=30, color=\"g\")\n",
"plt.scatter([rr], [h], s=30, color=\"r\")\n",
"\n",
"handles, labels = plt.gca().get_legend_handles_labels()\n",
"simArtist = plt.Line2D((0,1),(0,0), color='k', marker='o', linestyle='')\n",
"simArtist2 = plt.Line2D((0,1),(0,0), color='k', linestyle='--')\n",
"anyArtist = plt.Line2D((0,1),(0,0), color='k')\n",
"plt.legend([simArtist, anyArtist, simArtist2], ['prediction', \"prediction\", 'real value'],\n",
" bbox_to_anchor=(1.01, 1), loc=2, borderaxespad=0)\n",
"plt.title(u\"지지율 예측\", fontsize=14);"
]
},
{
"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": "2.7.12"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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