{
 "cells": [
  {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Disaster Tweet Prediction \n",
    "\n",
    "![image-2.png](attachment:image-2.png)\n",
    "\n",
    "### Problem Statement\n",
    "\n",
    "Twitter has become an important communication channel in times of emergency. The ubiquitousness of smartphones enables people to announce an emergency they’re observing in real-time. Because of this, more agencies are interested in programmatically monitoring Twitter (i.e. disaster relief organizations and news agencies). In this task, the goal is to predict whether a tweet is about a real disaster or not, where a real disaster will be represented as 1 and a non-disaster will be represented as 0. \n",
    "\n",
    "### Data Format \n",
    "Each sample of the train and test set has the following information: \n",
    "- The `text` of a tweet\n",
    "- A `keyword` from the tweet (may have empty values)\n",
    "- The `location` the tweet was sent from (may have empty values)\n",
    "- Train set only will have the `target` \n",
    "\n",
    "### Workflow\n",
    "Exploratory Data Analysis --> Preprocessing & Transformations --> Classification --> Evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis (EDA) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "import string\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import nltk\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from nltk.corpus import stopwords\n",
    "\n",
    "import seaborn as sns\n",
    "import plotly.graph_objs as go\n",
    "import matplotlib.pyplot as plt\n",
    "from wordcloud import WordCloud\n",
    "\n",
    "import lightgbm as lgb\n",
    "from keras.models import Model\n",
    "import gensim.downloader as api\n",
    "from tensorflow.keras.callbacks import EarlyStopping\n",
    "from tensorflow.keras.preprocessing.text import Tokenizer\n",
    "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
    "from tensorflow.keras.layers import Dense, Input, LSTM, Embedding, Dropout, Activation, Bidirectional\n",
    "from tensorflow.keras import initializers, regularizers, constraints, optimizers, layers, Sequential\n",
    "\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.linear_model import LogisticRegression, SGDClassifier\n",
    "from sklearn.metrics import classification_report, f1_score, confusion_matrix\n",
    "from sklearn.model_selection import StratifiedKFold, train_test_split, learning_curve\n",
    "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer, HashingVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# path/to/data\n",
    "TRAIN_PATH = \"../inputs/train.csv\"\n",
    "TEST_PATH = \"../inputs/test.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data shape: (7613, 5)\n",
      "Test data shape: (3263, 4)\n"
     ]
    }
   ],
   "source": [
    "# read data\n",
    "train_df = pd.read_csv(TRAIN_PATH)\n",
    "test_df = pd.read_csv(TEST_PATH)\n",
    "\n",
    "print(f\"Train data shape: {train_df.shape}\\nTest data shape: {test_df.shape}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7613 entries, 0 to 7612\n",
      "Data columns (total 5 columns):\n",
      " #   Column    Non-Null Count  Dtype \n",
      "---  ------    --------------  ----- \n",
      " 0   id        7613 non-null   int64 \n",
      " 1   keyword   7552 non-null   object\n",
      " 2   location  5080 non-null   object\n",
      " 3   text      7613 non-null   object\n",
      " 4   target    7613 non-null   int64 \n",
      "dtypes: int64(2), object(3)\n",
      "memory usage: 297.5+ KB\n",
      "None\n",
      "\n",
      "-----------------------------------------\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3263 entries, 0 to 3262\n",
      "Data columns (total 4 columns):\n",
      " #   Column    Non-Null Count  Dtype \n",
      "---  ------    --------------  ----- \n",
      " 0   id        3263 non-null   int64 \n",
      " 1   keyword   3237 non-null   object\n",
      " 2   location  2158 non-null   object\n",
      " 3   text      3263 non-null   object\n",
      "dtypes: int64(1), object(3)\n",
      "memory usage: 102.1+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "# more information about columns \n",
    "print(train_df.info())\n",
    "print(\"\\n-----------------------------------------\\n\")\n",
    "print(test_df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id             0\n",
       "keyword       61\n",
       "location    2533\n",
       "text           0\n",
       "target         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of missing values per column in train \n",
    "train_df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id             0\n",
       "keyword       26\n",
       "location    1105\n",
       "text           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of missing values per column in test\n",
    "test_df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    7613\n",
       "Name: id, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking if any id's from train are in test\n",
    "train_df[\"id\"].isin(test_df[\"id\"]).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    7486\n",
       "True      127\n",
       "Name: text, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of text that's duplicated in train and test sets\n",
    "train_df[\"text\"].isin(test_df[\"text\"]).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>keyword</th>\n",
       "      <th>location</th>\n",
       "      <th>text</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Our Deeds are the Reason of this #earthquake M...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Forest fire near La Ronge Sask. Canada</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All residents asked to 'shelter in place' are ...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13,000 people receive #wildfires evacuation or...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Just got sent this photo from Ruby #Alaska as ...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id keyword location                                               text  \\\n",
       "0   1     NaN      NaN  Our Deeds are the Reason of this #earthquake M...   \n",
       "1   4     NaN      NaN             Forest fire near La Ronge Sask. Canada   \n",
       "2   5     NaN      NaN  All residents asked to 'shelter in place' are ...   \n",
       "3   6     NaN      NaN  13,000 people receive #wildfires evacuation or...   \n",
       "4   7     NaN      NaN  Just got sent this photo from Ruby #Alaska as ...   \n",
       "\n",
       "   target  \n",
       "0     1.0  \n",
       "1     1.0  \n",
       "2     1.0  \n",
       "3     1.0  \n",
       "4     1.0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# appending the test data to train \n",
    "full_df = pd.concat(objs=[train_df, test_df], axis=0)\n",
    "full_df.head() # train data would be above the test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>keyword</th>\n",
       "      <th>location</th>\n",
       "      <th>text</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3258</th>\n",
       "      <td>10861</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EARTHQUAKE SAFETY LOS ANGELES ‰ÛÒ SAFETY FASTE...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3259</th>\n",
       "      <td>10865</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Storm in RI worse than last hurricane. My city...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3260</th>\n",
       "      <td>10868</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Green Line derailment in Chicago http://t.co/U...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3261</th>\n",
       "      <td>10874</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MEG issues Hazardous Weather Outlook (HWO) htt...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3262</th>\n",
       "      <td>10875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>#CityofCalgary has activated its Municipal Eme...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         id keyword location  \\\n",
       "3258  10861     NaN      NaN   \n",
       "3259  10865     NaN      NaN   \n",
       "3260  10868     NaN      NaN   \n",
       "3261  10874     NaN      NaN   \n",
       "3262  10875     NaN      NaN   \n",
       "\n",
       "                                                   text  target  \n",
       "3258  EARTHQUAKE SAFETY LOS ANGELES ‰ÛÒ SAFETY FASTE...     NaN  \n",
       "3259  Storm in RI worse than last hurricane. My city...     NaN  \n",
       "3260  Green Line derailment in Chicago http://t.co/U...     NaN  \n",
       "3261  MEG issues Hazardous Weather Outlook (HWO) htt...     NaN  \n",
       "3262  #CityofCalgary has activated its Municipal Eme...     NaN  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# target should be NaN if concat performed correctly\n",
    "full_df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Class Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# counting the number of positive and negative tweets\n",
    "sns.set(style=\"whitegrid\", color_codes=True)\n",
    "sns.catplot(\"target\", data=full_df, kind=\"count\", height=8)\n",
    "plt.title(\"Distribution of Target Counts\", size=20, weight=\"bold\")\n",
    "plt.xlabel(\"Target Label\", size=14, weight=\"bold\")\n",
    "plt.ylabel(\"Counts\", size=14, weight=\"bold\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Watch how bad that fool get burned in coverage this year. Dat dude is all-pro practice squad material'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# random examples of disaster tweets \n",
    "full_df[full_df[\"target\"]==1].iloc[np.random.randint(0, 3000), -2] # will give new example after each run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'New Explosion-proof Tempered Glass Screen Protector Film for Blackberry Z10 - Full read by\\x89Û_ http://t.co/tOYU16mxBO http://t.co/P10hNDc0Mm'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# random examples of non-disaster tweets \n",
    "full_df[full_df[\"target\"]==0].iloc[np.random.randint(0, 4000), -2] # will give new example after each run"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Percentage of missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# creating a new dataframe for missing values percentage\n",
    "missing_values = dict(zip([col+\"_missing_percent\" for col in full_df.columns if col != \"target\"],\n",
    "                          [round(100*full_df[col].isnull().sum()/len(full_df), 2) for col in full_df.columns\n",
    "                           if col != \"target\"]))\n",
    "missing_values_df = pd.DataFrame(missing_values, index=[0])\n",
    "missing_values_df = missing_values_df.melt(var_name= \"columns\", value_name= \"percentage\")\n",
    "\n",
    "# plotting missing values chart\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.set(style=\"whitegrid\", color_codes=True)\n",
    "seaborn_plot = sns.barplot(x=\"columns\", y=\"percentage\", data=missing_values_df)\n",
    "for p in seaborn_plot.patches:\n",
    "    seaborn_plot.annotate(format(p.get_height(), '.2f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center',\n",
    "                   va = 'center', xytext = (0, 9), textcoords = 'offset points')\n",
    "plt.title(\"Percentage of Missing Values in Columns\", size=20, weight=\"bold\")\n",
    "plt.xlabel(\"Columns\", size=14, weight=\"bold\")\n",
    "plt.ylabel(\"Percentage\", size=14, weight=\"bold\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Unique Values Per Column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# creating a new dataframe for unique value cound\n",
    "unique_values = dict(zip([col+\"_unique_values\" for col in full_df.columns if col != \"target\"],\n",
    "                          [full_df[col].nunique() for col in full_df.columns if col != \"target\"]))\n",
    "unique_values_df = pd.DataFrame(unique_values, index=[0])\n",
    "unique_values_df = unique_values_df.melt(var_name= \"columns\", value_name= \"counts\")\n",
    "\n",
    "# plotting unique values chart\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.set(style=\"whitegrid\", color_codes=True)\n",
    "seaborn_plot = sns.barplot(x=\"columns\", y=\"counts\", data=unique_values_df)\n",
    "for p in seaborn_plot.patches:\n",
    "    seaborn_plot.annotate(format(p.get_height(), '.2f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center',\n",
    "                   va = 'center', xytext = (0, 9), textcoords = 'offset points')\n",
    "plt.title(\"Number of Unique Values in Columns\", size=20, weight=\"bold\")\n",
    "plt.xlabel(\"Columns\", size=14, weight=\"bold\")\n",
    "plt.ylabel(\"Counts\", size=14, weight=\"bold\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note: 198 Tweets are not unique --> We have duplicates (Explore!)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Top Locations in Tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location</th>\n",
       "      <th>unique_counts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USA</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>New York</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>United States</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>London</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Nigeria</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Worldwide</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>India</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Los Angeles, CA</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>UK</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           location  unique_counts\n",
       "0               USA            141\n",
       "1          New York            109\n",
       "2     United States             65\n",
       "3            London             58\n",
       "4            Canada             42\n",
       "5           Nigeria             40\n",
       "6         Worldwide             35\n",
       "7             India             35\n",
       "8   Los Angeles, CA             34\n",
       "9                UK             33\n",
       "10            Kenya             32"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# creating a new dataframe with value counts of each location\n",
    "locations= full_df[\"location\"].value_counts().sort_values(ascending=False)\n",
    "locations_df= pd.DataFrame(dict(zip(locations.index, locations.values)), index=[0]).\\\n",
    "                                melt(var_name=\"location\", value_name=\"unique_counts\")\n",
    "locations_df.loc[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        require.undef(\"plotly\");\n",
       "        define('plotly', function(require, exports, module) {\n",
       "            /**\n",
       "* plotly.js v1.58.4\n",
       "* Copyright 2012-2020, Plotly, Inc.\n",
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s=e.source.column,l=e.circularLinkType,c=t.links.filter((function(t){return t.source.column==s&&t.circularLinkType==l}));\"bottom\"==e.circularLinkType?c.sort(L):c.sort(C);var u=0;c.forEach((function(t,n){t.circularLinkID==e.circularLinkID&&(e.circularPathData.leftSmallArcRadius=10+e.width/2+u,e.circularPathData.leftLargeArcRadius=10+e.width/2+n*r+u),u+=t.width})),s=e.target.column,c=t.links.filter((function(t){return t.target.column==s&&t.circularLinkType==l})),\"bottom\"==e.circularLinkType?c.sort(P):c.sort(I),u=0,c.forEach((function(t,n){t.circularLinkID==e.circularLinkID&&(e.circularPathData.rightSmallArcRadius=10+e.width/2+u,e.circularPathData.rightLargeArcRadius=10+e.width/2+n*r+u),u+=t.width})),\"bottom\"==e.circularLinkType?(e.circularPathData.verticalFullExtent=Math.max(i,e.source.y1,e.target.y1)+25+e.circularPathData.verticalBuffer,e.circularPathData.verticalLeftInnerExtent=e.circularPathData.verticalFullExtent-e.circularPathData.leftLargeArcRadius,e.circularPathData.verticalRightInnerExtent=e.circularPathData.verticalFullExtent-e.circularPathData.rightLargeArcRadius):(e.circularPathData.verticalFullExtent=o-25-e.circularPathData.verticalBuffer,e.circularPathData.verticalLeftInnerExtent=e.circularPathData.verticalFullExtent+e.circularPathData.leftLargeArcRadius,e.circularPathData.verticalRightInnerExtent=e.circularPathData.verticalFullExtent+e.circularPathData.rightLargeArcRadius)}e.circularPathData.leftInnerExtent=e.circularPathData.sourceX+e.circularPathData.leftNodeBuffer,e.circularPathData.rightInnerExtent=e.circularPathData.targetX-e.circularPathData.rightNodeBuffer,e.circularPathData.leftFullExtent=e.circularPathData.sourceX+e.circularPathData.leftLargeArcRadius+e.circularPathData.leftNodeBuffer,e.circularPathData.rightFullExtent=e.circularPathData.targetX-e.circularPathData.rightLargeArcRadius-e.circularPathData.rightNodeBuffer}if(e.circular)e.path=function(t){var 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32-Math.clz32(t)}:a.prototype._countBits=function(t){var e=t,r=0;return e>=4096&&(r+=13,e>>>=13),e>=64&&(r+=7,e>>>=7),e>=8&&(r+=4,e>>>=4),e>=2&&(r+=2,e>>>=2),r+e},a.prototype._zeroBits=function(t){if(0===t)return 26;var e=t,r=0;return 0==(8191&e)&&(r+=13,e>>>=13),0==(127&e)&&(r+=7,e>>>=7),0==(15&e)&&(r+=4,e>>>=4),0==(3&e)&&(r+=2,e>>>=2),0==(1&e)&&r++,r},a.prototype.bitLength=function(){var t=this.words[this.length-1],e=this._countBits(t);return 26*(this.length-1)+e},a.prototype.zeroBits=function(){if(this.isZero())return 0;for(var t=0,e=0;e<this.length;e++){var r=this._zeroBits(this.words[e]);if(t+=r,26!==r)break}return t},a.prototype.byteLength=function(){return Math.ceil(this.bitLength()/8)},a.prototype.toTwos=function(t){return 0!==this.negative?this.abs().inotn(t).iaddn(1):this.clone()},a.prototype.fromTwos=function(t){return this.testn(t-1)?this.notn(t).iaddn(1).ineg():this.clone()},a.prototype.isNeg=function(){return 0!==this.negative},a.prototype.neg=function(){return this.clone().ineg()},a.prototype.ineg=function(){return this.isZero()||(this.negative^=1),this},a.prototype.iuor=function(t){for(;this.length<t.length;)this.words[this.length++]=0;for(var e=0;e<t.length;e++)this.words[e]=this.words[e]|t.words[e];return this.strip()},a.prototype.ior=function(t){return n(0==(this.negative|t.negative)),this.iuor(t)},a.prototype.or=function(t){return this.length>t.length?this.clone().ior(t):t.clone().ior(this)},a.prototype.uor=function(t){return this.length>t.length?this.clone().iuor(t):t.clone().iuor(this)},a.prototype.iuand=function(t){var e;e=this.length>t.length?t:this;for(var r=0;r<e.length;r++)this.words[r]=this.words[r]&t.words[r];return this.length=e.length,this.strip()},a.prototype.iand=function(t){return n(0==(this.negative|t.negative)),this.iuand(t)},a.prototype.and=function(t){return this.length>t.length?this.clone().iand(t):t.clone().iand(this)},a.prototype.uand=function(t){return this.length>t.length?this.clone().iuand(t):t.clone().iuand(this)},a.prototype.iuxor=function(t){var e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;n<r.length;n++)this.words[n]=e.words[n]^r.words[n];if(this!==e)for(;n<e.length;n++)this.words[n]=e.words[n];return this.length=e.length,this.strip()},a.prototype.ixor=function(t){return n(0==(this.negative|t.negative)),this.iuxor(t)},a.prototype.xor=function(t){return this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},a.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},a.prototype.inotn=function(t){n(\"number\"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var i=0;i<e;i++)this.words[i]=67108863&~this.words[i];return r>0&&(this.words[i]=~this.words[i]&67108863>>26-r),this.strip()},a.prototype.notn=function(t){return this.clone().inotn(t)},a.prototype.setn=function(t,e){n(\"number\"==typeof t&&t>=0);var r=t/26|0,i=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var p=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,c=0,u=0|o[0],f=8191&u,h=u>>>13,p=0|o[1],d=8191&p,g=p>>>13,m=0|o[2],v=8191&m,y=m>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,M=0|o[5],A=8191&M,S=M>>>13,E=0|o[6],C=8191&E,L=E>>>13,I=0|o[7],P=8191&I,z=I>>>13,O=0|o[8],D=8191&O,R=O>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,q=0|s[1],H=8191&q,G=q>>>13,Y=0|s[2],W=8191&Y,X=Y>>>13,Z=0|s[3],J=8191&Z,K=Z>>>13,Q=0|s[4],$=8191&Q,tt=Q>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ct=st>>>13,ut=0|s[8],ft=8191&ut,ht=ut>>>13,pt=0|s[9],dt=8191&pt,gt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var mt=(c+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;c=((a=Math.imul(h,V))+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(g,U)|0,a=Math.imul(g,V);var vt=(c+(n=n+Math.imul(f,H)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,H)|0))<<13)|0;c=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(v,U),i=(i=Math.imul(v,V))+Math.imul(y,U)|0,a=Math.imul(y,V),n=n+Math.imul(d,H)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(g,H)|0,a=a+Math.imul(g,G)|0;var yt=(c+(n=n+Math.imul(f,W)|0)|0)+((8191&(i=(i=i+Math.imul(f,X)|0)+Math.imul(h,W)|0))<<13)|0;c=((a=a+Math.imul(h,X)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(v,H)|0,i=(i=i+Math.imul(v,G)|0)+Math.imul(y,H)|0,a=a+Math.imul(y,G)|0,n=n+Math.imul(d,W)|0,i=(i=i+Math.imul(d,X)|0)+Math.imul(g,W)|0,a=a+Math.imul(g,X)|0;var xt=(c+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;c=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,H)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,H)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(v,W)|0,i=(i=i+Math.imul(v,X)|0)+Math.imul(y,W)|0,a=a+Math.imul(y,X)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(g,J)|0,a=a+Math.imul(g,K)|0;var bt=(c+(n=n+Math.imul(f,$)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,$)|0))<<13)|0;c=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(A,U),i=(i=Math.imul(A,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,H)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,H)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,W)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,W)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(v,J)|0,i=(i=i+Math.imul(v,K)|0)+Math.imul(y,J)|0,a=a+Math.imul(y,K)|0,n=n+Math.imul(d,$)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(g,$)|0,a=a+Math.imul(g,tt)|0;var _t=(c+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;c=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(C,U),i=(i=Math.imul(C,V))+Math.imul(L,U)|0,a=Math.imul(L,V),n=n+Math.imul(A,H)|0,i=(i=i+Math.imul(A,G)|0)+Math.imul(S,H)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,W)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(k,W)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(v,$)|0,i=(i=i+Math.imul(v,tt)|0)+Math.imul(y,$)|0,a=a+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(g,rt)|0,a=a+Math.imul(g,nt)|0;var wt=(c+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;c=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(P,U),i=(i=Math.imul(P,V))+Math.imul(z,U)|0,a=Math.imul(z,V),n=n+Math.imul(C,H)|0,i=(i=i+Math.imul(C,G)|0)+Math.imul(L,H)|0,a=a+Math.imul(L,G)|0,n=n+Math.imul(A,W)|0,i=(i=i+Math.imul(A,X)|0)+Math.imul(S,W)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,$)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,$)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(v,rt)|0,i=(i=i+Math.imul(v,nt)|0)+Math.imul(y,rt)|0,a=a+Math.imul(y,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(g,at)|0,a=a+Math.imul(g,ot)|0;var Tt=(c+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ct)|0)+Math.imul(h,lt)|0))<<13)|0;c=((a=a+Math.imul(h,ct)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(D,U),i=(i=Math.imul(D,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(P,H)|0,i=(i=i+Math.imul(P,G)|0)+Math.imul(z,H)|0,a=a+Math.imul(z,G)|0,n=n+Math.imul(C,W)|0,i=(i=i+Math.imul(C,X)|0)+Math.imul(L,W)|0,a=a+Math.imul(L,X)|0,n=n+Math.imul(A,J)|0,i=(i=i+Math.imul(A,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,$)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,$)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(v,at)|0,i=(i=i+Math.imul(v,ot)|0)+Math.imul(y,at)|0,a=a+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ct)|0)+Math.imul(g,lt)|0,a=a+Math.imul(g,ct)|0;var kt=(c+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;c=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(D,H)|0,i=(i=i+Math.imul(D,G)|0)+Math.imul(R,H)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(P,W)|0,i=(i=i+Math.imul(P,X)|0)+Math.imul(z,W)|0,a=a+Math.imul(z,X)|0,n=n+Math.imul(C,J)|0,i=(i=i+Math.imul(C,K)|0)+Math.imul(L,J)|0,a=a+Math.imul(L,K)|0,n=n+Math.imul(A,$)|0,i=(i=i+Math.imul(A,tt)|0)+Math.imul(S,$)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(v,lt)|0,i=(i=i+Math.imul(v,ct)|0)+Math.imul(y,lt)|0,a=a+Math.imul(y,ct)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(g,ft)|0,a=a+Math.imul(g,ht)|0;var Mt=(c+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,gt)|0)+Math.imul(h,dt)|0))<<13)|0;c=((a=a+Math.imul(h,gt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,H),i=(i=Math.imul(B,G))+Math.imul(N,H)|0,a=Math.imul(N,G),n=n+Math.imul(D,W)|0,i=(i=i+Math.imul(D,X)|0)+Math.imul(R,W)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(P,J)|0,i=(i=i+Math.imul(P,K)|0)+Math.imul(z,J)|0,a=a+Math.imul(z,K)|0,n=n+Math.imul(C,$)|0,i=(i=i+Math.imul(C,tt)|0)+Math.imul(L,$)|0,a=a+Math.imul(L,tt)|0,n=n+Math.imul(A,rt)|0,i=(i=i+Math.imul(A,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ct)|0,n=n+Math.imul(v,ft)|0,i=(i=i+Math.imul(v,ht)|0)+Math.imul(y,ft)|0,a=a+Math.imul(y,ht)|0;var At=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,gt)|0)+Math.imul(g,dt)|0))<<13)|0;c=((a=a+Math.imul(g,gt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,W),i=(i=Math.imul(B,X))+Math.imul(N,W)|0,a=Math.imul(N,X),n=n+Math.imul(D,J)|0,i=(i=i+Math.imul(D,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(P,$)|0,i=(i=i+Math.imul(P,tt)|0)+Math.imul(z,$)|0,a=a+Math.imul(z,tt)|0,n=n+Math.imul(C,rt)|0,i=(i=i+Math.imul(C,nt)|0)+Math.imul(L,rt)|0,a=a+Math.imul(L,nt)|0,n=n+Math.imul(A,at)|0,i=(i=i+Math.imul(A,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ct)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ct)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(c+(n=n+Math.imul(v,dt)|0)|0)+((8191&(i=(i=i+Math.imul(v,gt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((a=a+Math.imul(y,gt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(D,$)|0,i=(i=i+Math.imul(D,tt)|0)+Math.imul(R,$)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(P,rt)|0,i=(i=i+Math.imul(P,nt)|0)+Math.imul(z,rt)|0,a=a+Math.imul(z,nt)|0,n=n+Math.imul(C,at)|0,i=(i=i+Math.imul(C,ot)|0)+Math.imul(L,at)|0,a=a+Math.imul(L,ot)|0,n=n+Math.imul(A,lt)|0,i=(i=i+Math.imul(A,ct)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ct)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,gt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((a=a+Math.imul(_,gt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,$),i=(i=Math.imul(B,tt))+Math.imul(N,$)|0,a=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,i=(i=i+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(P,at)|0,i=(i=i+Math.imul(P,ot)|0)+Math.imul(z,at)|0,a=a+Math.imul(z,ot)|0,n=n+Math.imul(C,lt)|0,i=(i=i+Math.imul(C,ct)|0)+Math.imul(L,lt)|0,a=a+Math.imul(L,ct)|0,n=n+Math.imul(A,ft)|0,i=(i=i+Math.imul(A,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Ct=(c+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,gt)|0)+Math.imul(k,dt)|0))<<13)|0;c=((a=a+Math.imul(k,gt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(D,at)|0,i=(i=i+Math.imul(D,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(P,lt)|0,i=(i=i+Math.imul(P,ct)|0)+Math.imul(z,lt)|0,a=a+Math.imul(z,ct)|0,n=n+Math.imul(C,ft)|0,i=(i=i+Math.imul(C,ht)|0)+Math.imul(L,ft)|0,a=a+Math.imul(L,ht)|0;var Lt=(c+(n=n+Math.imul(A,dt)|0)|0)+((8191&(i=(i=i+Math.imul(A,gt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((a=a+Math.imul(S,gt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,i=(i=i+Math.imul(D,ct)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ct)|0,n=n+Math.imul(P,ft)|0,i=(i=i+Math.imul(P,ht)|0)+Math.imul(z,ft)|0,a=a+Math.imul(z,ht)|0;var It=(c+(n=n+Math.imul(C,dt)|0)|0)+((8191&(i=(i=i+Math.imul(C,gt)|0)+Math.imul(L,dt)|0))<<13)|0;c=((a=a+Math.imul(L,gt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ct))+Math.imul(N,lt)|0,a=Math.imul(N,ct),n=n+Math.imul(D,ft)|0,i=(i=i+Math.imul(D,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var Pt=(c+(n=n+Math.imul(P,dt)|0)|0)+((8191&(i=(i=i+Math.imul(P,gt)|0)+Math.imul(z,dt)|0))<<13)|0;c=((a=a+Math.imul(z,gt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var zt=(c+(n=n+Math.imul(D,dt)|0)|0)+((8191&(i=(i=i+Math.imul(D,gt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((a=a+Math.imul(R,gt)|0)+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863;var Ot=(c+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,gt))+Math.imul(N,dt)|0))<<13)|0;return c=((a=Math.imul(N,gt))+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,l[0]=mt,l[1]=vt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=Mt,l[10]=At,l[11]=St,l[12]=Et,l[13]=Ct,l[14]=Lt,l[15]=It,l[16]=Pt,l[17]=zt,l[18]=Ot,0!==c&&(l[19]=c,r.length++),r};function d(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(p=h),a.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?p(this,t,e):r<63?h(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),c=Math.max(0,a-t.length+1);c<=l;c++){var u=a-c,f=(0|t.words[u])*(0|e.words[c]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):d(this,t,e)},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<i;u+=s)for(var f=l,h=c,p=0;p<o;p++){var d=r[u+p],g=n[u+p],m=r[u+p+o],v=n[u+p+o],y=f*m-h*v;v=f*v+h*m,m=y,r[u+p]=d+m,n[u+p]=g+v,r[u+p+o]=d-m,n[u+p+o]=g-v,p!==s&&(y=l*f-c*h,h=l*h+c*f,f=y)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,a,s,l,n,i),this.transform(c,a,u,f,n,i);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),d(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=i);c--){var f=0|this.words[c];this.words[c]=u<<26-a|f>>>a,u=f&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r)&&!!(this.words[r]&i)},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!==(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(i,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(u),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,g=1;0==(r.words[0]&g)&&d<26;++d,g<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var c=0,u=1;0==(e.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(e.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new w(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},a.prototype.redAdd=function(t){return n(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},a.prototype.redIAdd=function(t){return n(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},a.prototype.redSub=function(t){return n(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},a.prototype.redISub=function(t){return n(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},a.prototype.redShl=function(t){return n(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},a.prototype.redMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},a.prototype.redIMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},a.prototype.redSqr=function(){return n(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var m={k256:null,p224:null,p192:null,p25519:null};function v(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function y(){v.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function x(){v.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function b(){v.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function _(){v.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function w(t){if(\"string\"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function T(t){w.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}v.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},v.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},v.prototype.split=function(t,e){t.iushrn(this.n,0,e)},v.prototype.imulK=function(t){return t.imul(this.k)},i(y,v),y.prototype.split=function(t,e){for(var r=Math.min(t.length,9),n=0;n<r;n++)e.words[n]=t.words[n];if(e.length=r,t.length<=9)return t.words[0]=0,void(t.length=1);var i=t.words[9];for(e.words[e.length++]=4194303&i,n=10;n<t.length;n++){var a=0|t.words[n];t.words[n-10]=(4194303&a)<<4|i>>>22,i=a}i>>>=22,t.words[n-10]=i,0===i&&t.length>10?t.length-=10:t.length-=9},y.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(x,v),i(b,v),i(_,v),_.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(m[t])return m[t];var e;if(\"k256\"===t)e=new y;else if(\"p224\"===t)e=new x;else if(\"p192\"===t)e=new b;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new _}return m[t]=e,e},w.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},w.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},w.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},w.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},w.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},w.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},w.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},w.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},w.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},w.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},w.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},w.prototype.isqr=function(t){return this.imul(t,t.clone())},w.prototype.sqr=function(t){return this.mul(t,t)},w.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new a(1)).iushrn(2);return this.pow(t,r)}for(var i=this.m.subn(1),o=0;!i.isZero()&&0===i.andln(1);)o++,i.iushrn(1);n(!i.isZero());var s=new a(1).toRed(this),l=s.redNeg(),c=this.m.subn(1).iushrn(1),u=this.m.bitLength();for(u=new a(2*u*u).toRed(this);0!==this.pow(u,c).cmp(l);)u.redIAdd(l);for(var f=this.pow(u,i),h=this.pow(t,i.addn(1).iushrn(1)),p=this.pow(t,i),d=o;0!==p.cmp(s);){for(var g=p,m=0;0!==g.cmp(s);m++)g=g.redSqr();n(m<d);var v=this.pow(f,new a(1).iushln(d-m-1));h=h.redMul(v),f=v.redSqr(),p=p.redMul(f),d=m}return h},w.prototype.invm=function(t){var e=t._invmp(this.m);return 0!==e.negative?(e.negative=0,this.imod(e).redNeg()):this.imod(e)},w.prototype.pow=function(t,e){if(e.isZero())return new a(1).toRed(this);if(0===e.cmpn(1))return t.clone();var r=new Array(16);r[0]=new a(1).toRed(this),r[1]=t;for(var n=2;n<r.length;n++)r[n]=this.mul(r[n-1],t);var i=r[0],o=0,s=0,l=e.bitLength()%26;for(0===l&&(l=26),n=e.length-1;n>=0;n--){for(var c=e.words[n],u=l-1;u>=0;u--){var 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       "/*!\n",
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       " * @license   Licensed under MIT license\n",
       " *            See https://raw.githubusercontent.com/stefanpenner/es6-promise/master/LICENSE\n",
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a=e(t,r.key);n.push(r),a<0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new h(this,n)},l.lt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new h(this,n)},l.le=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>=0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new h(this,n)},l.find=function(t){for(var e=this._compare,r=this.root,n=[];r;){var i=e(t,r.key);if(n.push(r),0===i)return new h(this,n);r=i<=0?r.left:r.right}return new h(this,[])},l.remove=function(t){var e=this.find(t);return e?e.remove():this},l.get=function(t){for(var e=this._compare,r=this.root;r;){var n=e(t,r.key);if(0===n)return r.value;r=n<=0?r.left:r.right}};var p=h.prototype;function d(t,e){t.key=e.key,t.value=e.value,t.left=e.left,t.right=e.right,t._color=e._color,t._count=e._count}function g(t,e){return t<e?-1:t>e?1:0}Object.defineProperty(p,\"valid\",{get:function(){return this._stack.length>0}}),Object.defineProperty(p,\"node\",{get:function(){return this._stack.length>0?this._stack[this._stack.length-1]:null},enumerable:!0}),p.clone=function(){return new h(this.tree,this._stack.slice())},p.remove=function(){var t=this._stack;if(0===t.length)return this.tree;var e=new Array(t.length),r=t[t.length-1];e[e.length-1]=new n(r._color,r.key,r.value,r.left,r.right,r._count);for(var l=t.length-2;l>=0;--l){(r=t[l]).left===t[l+1]?e[l]=new n(r._color,r.key,r.value,e[l+1],r.right,r._count):e[l]=new n(r._color,r.key,r.value,r.left,e[l+1],r._count)}if((r=e[e.length-1]).left&&r.right){var c=e.length;for(r=r.left;r.right;)e.push(r),r=r.right;var u=e[c-1];e.push(new n(r._color,u.key,u.value,r.left,r.right,r._count)),e[c-1].key=r.key,e[c-1].value=r.value;for(l=e.length-2;l>=c;--l)r=e[l],e[l]=new n(r._color,r.key,r.value,r.left,e[l+1],r._count);e[c-1].left=e[c]}if(0===(r=e[e.length-1])._color){var f=e[e.length-2];f.left===r?f.left=null:f.right===r&&(f.right=null),e.pop();for(l=0;l<e.length;++l)e[l]._count--;return new s(this.tree._compare,e[0])}if(r.left||r.right){r.left?d(r,r.left):r.right&&d(r,r.right),r._color=1;for(l=0;l<e.length-1;++l)e[l]._count--;return new s(this.tree._compare,e[0])}if(1===e.length)return new s(this.tree._compare,null);for(l=0;l<e.length;++l)e[l]._count--;var h=e[e.length-2];return function(t){for(var e,r,n,s,l=t.length-1;l>=0;--l){if(e=t[l],0===l)return void(e._color=1);if((r=t[l-1]).left===e){if((n=r.right).right&&0===n.right._color){if(s=(n=r.right=i(n)).right=i(n.right),r.right=n.left,n.left=r,n.right=s,n._color=r._color,e._color=1,r._color=1,s._color=1,o(r),o(n),l>1)(c=t[l-2]).left===r?c.left=n:c.right=n;return void(t[l-1]=n)}if(n.left&&0===n.left._color){if(s=(n=r.right=i(n)).left=i(n.left),r.right=s.left,n.left=s.right,s.left=r,s.right=n,s._color=r._color,r._color=1,n._color=1,e._color=1,o(r),o(n),o(s),l>1)(c=t[l-2]).left===r?c.left=s:c.right=s;return void(t[l-1]=s)}if(1===n._color){if(0===r._color)return r._color=1,void(r.right=a(0,n));r.right=a(0,n);continue}n=i(n),r.right=n.left,n.left=r,n._color=r._color,r._color=0,o(r),o(n),l>1&&((c=t[l-2]).left===r?c.left=n:c.right=n),t[l-1]=n,t[l]=r,l+1<t.length?t[l+1]=e:t.push(e),l+=2}else{if((n=r.left).left&&0===n.left._color){if(s=(n=r.left=i(n)).left=i(n.left),r.left=n.right,n.right=r,n.left=s,n._color=r._color,e._color=1,r._color=1,s._color=1,o(r),o(n),l>1)(c=t[l-2]).right===r?c.right=n:c.left=n;return void(t[l-1]=n)}if(n.right&&0===n.right._color){if(s=(n=r.left=i(n)).right=i(n.right),r.left=s.right,n.right=s.left,s.right=r,s.left=n,s._color=r._color,r._color=1,n._color=1,e._color=1,o(r),o(n),o(s),l>1)(c=t[l-2]).right===r?c.right=s:c.left=s;return void(t[l-1]=s)}if(1===n._color){if(0===r._color)return r._color=1,void(r.left=a(0,n));r.left=a(0,n);continue}var c;n=i(n),r.left=n.right,n.right=r,n._color=r._color,r._color=0,o(r),o(n),l>1&&((c=t[l-2]).right===r?c.right=n:c.left=n),t[l-1]=n,t[l]=r,l+1<t.length?t[l+1]=e:t.push(e),l+=2}}}(e),h.left===r?h.left=null:h.right=null,new s(this.tree._compare,e[0])},Object.defineProperty(p,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(p,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(p,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),p.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(p,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),p.update=function(t){var e=this._stack;if(0===e.length)throw new Error(\"Can't update empty node!\");var r=new Array(e.length),i=e[e.length-1];r[r.length-1]=new n(i._color,i.key,t,i.left,i.right,i._count);for(var a=e.length-2;a>=0;--a)(i=e[a]).left===e[a+1]?r[a]=new n(i._color,i.key,i.value,r[a+1],i.right,i._count):r[a]=new n(i._color,i.key,i.value,i.left,r[a+1],i._count);return new s(this.tree._compare,r[0])},p.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(p,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},{}],248:[function(t,e,r){var n=[.9999999999998099,676.5203681218851,-1259.1392167224028,771.3234287776531,-176.6150291621406,12.507343278686905,-.13857109526572012,9984369578019572e-21,1.5056327351493116e-7],i=[.9999999999999971,57.15623566586292,-59.59796035547549,14.136097974741746,-.4919138160976202,3399464998481189e-20,4652362892704858e-20,-9837447530487956e-20,.0001580887032249125,-.00021026444172410488,.00021743961811521265,-.0001643181065367639,8441822398385275e-20,-26190838401581408e-21,36899182659531625e-22];function a(t){if(t<0)return Number(\"0/0\");for(var e=i[0],r=i.length-1;r>0;--r)e+=i[r]/(t+r);var n=t+607/128+.5;return.5*Math.log(2*Math.PI)+(t+.5)*Math.log(n)-n+Math.log(e)-Math.log(t)}e.exports=function t(e){if(e<.5)return Math.PI/(Math.sin(Math.PI*e)*t(1-e));if(e>100)return Math.exp(a(e));e-=1;for(var r=n[0],i=1;i<9;i++)r+=n[i]/(e+i);var o=e+7+.5;return Math.sqrt(2*Math.PI)*Math.pow(o,e+.5)*Math.exp(-o)*r},e.exports.log=a},{}],249:[function(t,e,r){e.exports=function(t,e){if(\"string\"!=typeof t)throw new TypeError(\"must specify type string\");if(e=e||{},\"undefined\"==typeof document&&!e.canvas)return null;var r=e.canvas||document.createElement(\"canvas\");\"number\"==typeof e.width&&(r.width=e.width);\"number\"==typeof e.height&&(r.height=e.height);var n,i=e;try{var a=[t];0===t.indexOf(\"webgl\")&&a.push(\"experimental-\"+t);for(var o=0;o<a.length;o++)if(n=r.getContext(a[o],i))return n}catch(t){n=null}return n||null}},{}],250:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=new u(t);return r.update(e),r};var n=t(\"./lib/text.js\"),i=t(\"./lib/lines.js\"),a=t(\"./lib/background.js\"),o=t(\"./lib/cube.js\"),s=t(\"./lib/ticks.js\"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=u.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),u=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,u=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?u=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(u=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),c(\"tickColor\");var g=l(\"labels\");l(\"labelFont\")&&(g=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),c(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),c(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),c(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),c(\"gridColor\"),o(\"zeroEnable\"),c(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),c(\"backgroundColor\"),this._text?this._text&&(g||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var f=a,h=s,p=o,d=l;c&1<<u&&(f=s,h=a,p=l,d=o),f[u]=r[0][u],h[u]=r[1][u],i[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var g=[0,0,0],m={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var v=[0,0,0],y=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||m;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,u=o(r,n,i,a,s),f=u.cubeEdges,h=u.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,M=0;M<3;++M)this.lastCubeProps.cubeEdges[M]=f[M],this.lastCubeProps.axis[M]=h[M];var A=p;for(M=0;M<3;++M)d(p[M],M,this.bounds,f,h);e=this.gl;var S,E=g;for(M=0;M<3;++M)this.backgroundEnable[M]?E[M]=h[M]:E[M]=0;this._background.draw(r,n,i,a,E,this.backgroundColor),this._lines.bind(r,n,i,this);for(M=0;M<3;++M){var C=[0,0,0];h[M]>0?C[M]=a[1][M]:C[M]=a[0][M];for(var L=0;L<2;++L){var I=(M+1+L)%3,P=(M+1+(1^L))%3;this.gridEnable[I]&&this._lines.drawGrid(I,P,this.bounds,C,this.gridColor[I],this.gridWidth[I]*this.pixelRatio)}for(L=0;L<2;++L){I=(M+1+L)%3,P=(M+1+(1^L))%3;this.zeroEnable[P]&&Math.min(a[0][P],a[1][P])<=0&&Math.max(a[0][P],a[1][P])>=0&&this._lines.drawZero(I,P,this.bounds,C,this.zeroLineColor[P],this.zeroLineWidth[P]*this.pixelRatio)}}for(M=0;M<3;++M){this.lineEnable[M]&&this._lines.drawAxisLine(M,this.bounds,A[M].primalOffset,this.lineColor[M],this.lineWidth[M]*this.pixelRatio),this.lineMirror[M]&&this._lines.drawAxisLine(M,this.bounds,A[M].mirrorOffset,this.lineColor[M],this.lineWidth[M]*this.pixelRatio);var z=c(v,A[M].primalMinor),O=c(y,A[M].mirrorMinor),D=this.lineTickLength;for(L=0;L<3;++L){var R=k/r[5*L];z[L]*=D[L]*R,O[L]*=D[L]*R}this.lineTickEnable[M]&&this._lines.drawAxisTicks(M,A[M].primalOffset,z,this.lineTickColor[M],this.lineTickWidth[M]*this.pixelRatio),this.lineTickMirror[M]&&this._lines.drawAxisTicks(M,A[M].mirrorOffset,O,this.lineTickColor[M],this.lineTickWidth[M]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(M=0;M<3;++M){var U=A[M].primalMinor,V=A[M].mirrorMinor,q=c(x,A[M].primalOffset);for(L=0;L<3;++L)this.lineTickEnable[M]&&(q[L]+=k*U[L]*Math.max(this.lineTickLength[L],0)/r[5*L]);var H=[0,0,0];if(H[M]=1,this.tickEnable[M]){-3600===this.tickAngle[M]?(this.tickAngle[M]=0,this.tickAlign[M]=\"auto\"):this.tickAlign[M]=-1,F=1,\"auto\"===(S=[this.tickAlign[M],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),B=[0,0,0],j(M,U,V);for(L=0;L<3;++L)q[L]+=k*U[L]*this.tickPad[L]/r[5*L];this._text.drawTicks(M,this.tickSize[M],this.tickAngle[M],q,this.tickColor[M],H,B,S)}if(this.labelEnable[M]){F=0,B=[0,0,0],this.labels[M].length>4&&(N(M),F=1),\"auto\"===(S=[this.labelAlign[M],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]);for(L=0;L<3;++L)q[L]+=k*U[L]*this.labelPad[L]/r[5*L];q[M]+=.5*(a[0][M]+a[1][M]),this._text.drawLabel(M,this.labelSize[M],this.labelAngle[M],q,this.labelColor[M],[0,0,0],B,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":251,\"./lib/cube.js\":252,\"./lib/lines.js\":253,\"./lib/text.js\":255,\"./lib/ticks.js\":256}],251:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[c]=d;for(var g=-1;g<=1;g+=2)f[u]=g,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var m=c;c=u,u=m}var v=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:v,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:v,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,v,x,b)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":254,\"gl-buffer\":259,\"gl-vao\":358}],252:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=a[x][2];for(var b=0;b<2;++b){u[1]=a[b][1];for(var _=0;_<2;++_)u[0]=a[_][0],h(l[y],u,s),y+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)c[x][k]=l[x][k]/T;p&&(c[x][2]*=-1),T<0&&(w<0||c[x][2]<c[w][2])&&(w=x)}if(w<0){w=0;for(var M=0;M<3;++M){for(var A=(M+2)%3,S=(M+1)%3,E=-1,C=-1,L=0;L<2;++L){var I=(z=L<<M)+(L<<A)+(1-L<<S),P=z+(1-L<<A)+(L<<S);o(c[z],c[I],c[P],f)<0||(L?E=1:C=1)}if(E<0||C<0)C>E&&(w|=1<<M);else{for(L=0;L<2;++L){I=(z=L<<M)+(L<<A)+(1-L<<S),P=z+(1-L<<A)+(L<<S);var z,O=d([l[z],l[I],l[P],l[z+(1<<A)+(1<<S)]]);L?E=O:C=O}C>E&&(w|=1<<M)}}}var D=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==D&&(R<0||c[R][1]>c[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x){if((N=R^1<<x)!==w&&N!==D)F<0&&(F=N),(S=c[N])[0]<c[F][0]&&(F=N)}var B=-1;for(x=0;x<3;++x){var N;if((N=R^1<<x)!==w&&N!==D&&N!==F)B<0&&(B=N),(S=c[N])[0]>c[B][0]&&(B=N)}var j=g;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===D?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=m,q=w;for(M=0;M<3;++M)V[M]=q&1<<M?-1:1;return v};var n=t(\"bit-twiddle\"),i=t(\"gl-mat4/multiply\"),a=t(\"split-polygon\"),o=t(\"robust-orientation\"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(c*h-u*f)}return o}var g=[1,1,1],m=[0,0,0],v={cubeEdges:g,axis:m}},{\"bit-twiddle\":97,\"gl-mat4/multiply\":295,\"robust-orientation\":548,\"split-polygon\":566}],253:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var g=+r[f][d].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var m=o.length/3|0;s[f]=h,l[f]=m-h;h=o.length/3|0;for(var v=0;v<r[f].length;++v){g=+r[f][v].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}m=o.length/3|0;c[f]=h,u[f]=m-h}var y=n(t,new Float32Array(o)),x=i(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,u=h(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var u=f(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=h(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var g=f(l);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=h(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":254,\"gl-buffer\":259,\"gl-vao\":358}],254:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.line=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n  vec3 A = project(a);\\n  vec3 B = project(b);\\n\\n  return atan(\\n    (B.y - A.y) * resolution.y,\\n    (B.x - A.x) * resolution.x\\n  );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio =       alignOpt.y;\\nbool enableAlign =    (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n  return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n  return mod_angle((a < 0.0) ?\\n    a + TWO_PI :\\n    a\\n  );\\n}\\n\\nfloat look_upwards(float a) {\\n  float b = positive_angle(a);\\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n    b - PI :\\n    b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n  // if ratio is set to 0.5 then it is 50%, 50%.\\n  // when using a higher ratio e.g. 0.75 the result would\\n  // likely be more horizontal than vertical.\\n\\n  float b = positive_angle(a);\\n\\n  return\\n    (b < (      ratio) * HALF_PI) ? 0.0 :\\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n                                    0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n  return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n  float b = positive_angle(a);\\n  float div = TWO_PI / float(n);\\n  float c = roundTo(b, div);\\n  return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n  return\\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\\n                    rawAngle;                // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n                   (axis.y == 0.0) &&\\n                   (axis.z == 0.0);\\n\\nvoid main() {\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n\\n  float beta = angle; // i.e. user defined attributes for each tick\\n\\n  float axisAngle;\\n  float clipAngle;\\n  float flip;\\n\\n  if (enableAlign) {\\n    axisAngle = (isAxisTitle) ? HALF_PI :\\n                      computeViewAngle(dataPosition, dataPosition + axis);\\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n    clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n    flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n                vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n    beta += applyAlignOption(clipAngle, flip * PI);\\n  }\\n\\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n\\n  mat2 planeXform = scale * mat2(\\n     cos(beta), sin(beta),\\n    -sin(beta), cos(beta)\\n  );\\n\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute clip position\\n  vec3 clipPosition = project(dataPosition);\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec3(viewOffset, 0.0);\\n\\n  //Done\\n  gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.text=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n  vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n  vec3 realNormal = signAxis * normal;\\n\\n  if(dot(realNormal, enable) > 0.0) {\\n    vec3 minRange = min(bounds[0], bounds[1]);\\n    vec3 maxRange = max(bounds[0], bounds[1]);\\n    vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n\\n  colorChannel = abs(realNormal);\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  gl_FragColor = colorChannel.x * colors[0] +\\n                 colorChannel.y * colors[1] +\\n                 colorChannel.z * colors[2];\\n}\"]);r.bg=function(t){return i(t,c,u,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},{\"gl-shader\":335,glslify:257}],255:[function(t,e,r){(function(r){(function(){\"use strict\";e.exports=function(t,e,r,a,s,l){var u=n(t),f=i(t,[{buffer:u,size:3}]),h=o(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,a,s,l),p};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"vectorize-text\"),o=t(\"./shaders\").text,s=window||r.global||{},l=s.__TEXT_CACHE||{};s.__TEXT_CACHE={};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}var u=c.prototype,f=[0,0];u.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,f[0]=this.gl.drawingBufferWidth,f[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=f},u.unbind=function(){this.vao.unbind()},u.update=function(t,e,r,n,i){var o=[];function s(t,e,r,n,i,s){var 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n=t(\"extract-frustum-planes\"),i=t(\"split-polygon\"),a=t(\"./lib/cube.js\"),o=t(\"gl-mat4/multiply\"),s=t(\"gl-mat4/transpose\"),l=t(\"gl-vec4/transformMat4\"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(u*u+f*f)}return t}var g=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],m=[0,0,0]},{\"./lib/cube.js\":252,\"extract-frustum-planes\":240,\"gl-mat4/multiply\":295,\"gl-mat4/transpose\":306,\"gl-vec4/transformMat4\":429,\"split-polygon\":566}],259:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),i=t(\"ndarray-ops\"),a=t(\"ndarray\"),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function c(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function u(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&\"undefined\"!=typeof t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,\"uint16\"):u(t,\"float32\"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},e.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},{ndarray:495,\"ndarray-ops\":490,\"typedarray-pool\":595}],260:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\");e.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,c=1/0,u=-1/0,f=1/0,h=-1/0,p=null,d=null,g=[],m=1/0,v=!1,y=0;y<r.length;y++){var x=r[y];s=Math.min(x[0],s),l=Math.max(x[0],l),c=Math.min(x[1],c),u=Math.max(x[1],u),f=Math.min(x[2],f),h=Math.max(x[2],h);var b=i[y];if(n.length(b)>o&&(o=n.length(b)),y){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(m=Math.min(m,_),v=!1):v=!0}v||(p=x,d=b),g.push(b)}var w=[s,c,f],T=[l,u,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(m)||(m=1),a.vectorScale=m;var M=t.coneSize||.5;t.absoluteConeSize&&(M=t.absoluteConeSize*k),a.coneScale=M;y=0;for(var A=0;y<r.length;y++)for(var S=(x=r[y])[0],E=x[1],C=x[2],L=g[y],I=n.length(L)*k,P=0;P<8;P++){a.positions.push([S,E,C,A++]),a.positions.push([S,E,C,A++]),a.positions.push([S,E,C,A++]),a.positions.push([S,E,C,A++]),a.positions.push([S,E,C,A++]),a.positions.push([S,E,C,A++]),a.vectors.push(L),a.vectors.push(L),a.vectors.push(L),a.vectors.push(L),a.vectors.push(L),a.vectors.push(L),a.vertexIntensity.push(I,I,I),a.vertexIntensity.push(I,I,I);var z=a.positions.length;a.cells.push([z-6,z-5,z-4],[z-3,z-2,z-1])}return a};var i=t(\"./lib/shaders\");e.exports.createMesh=t(\"./create_mesh\"),e.exports.createConeMesh=function(t,r){return e.exports.createMesh(t,r,{shaders:i,traceType:\"cone\"})}},{\"./create_mesh\":261,\"./lib/shaders\":262,\"gl-vec3\":377}],261:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"gl-mat4/multiply\"),l=t(\"gl-mat4/invert\"),c=t(\"ndarray\"),u=t(\"colormap\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,c,u){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=c,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=u,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;function d(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}function g(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=u({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return c(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,g=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],g=+t.vertexIntensityBounds[1];else for(var m=0;m<p.length;++m){var v=p[m];d=Math.min(d,v),g=Math.max(g,v)}else for(m=0;m<n.length;++m){v=n[m][2];d=Math.min(d,v),g=Math.max(g,v)}this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(m=0;m<n.length;++m)for(var y=n[m],x=0;x<3;++x)!isNaN(y[x])&&isFinite(y[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],y[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],y[x]));var b=0;t:for(m=0;m<r.length;++m){var _=r[m];switch(_.length){case 3:for(x=0;x<3;++x){y=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(y[w])||!isFinite(y[w]))continue t}for(x=0;x<3;++x){var T;y=n[T=_[2-x]];a.push(y[0],y[1],y[2],y[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var M,A=h;3===A.length?s.push(A[0],A[1],A[2],1):s.push(A[0],A[1],A[2],A[3]),M=p?[(p[T]-d)/(g-d),0]:[(y[2]-d)/(g-d),0],l.push(M[0],M[1]),f.push(m)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var c={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};c.inverseModel=l(c.inverseModel,c.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);s(u,c.view,c.model),s(u,c.projection,u),l(u,u);for(o=0;o<3;++o)c.eyePosition[o]=u[12+o]/u[15];var h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];c.lightPosition[o]=p/h}if(this.triangleCount>0){var g=this.triShader;g.bind(),g.uniforms=c,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},e.exports=function(t,e,r){var n=r.shaders;1===arguments.length&&(t=(e=t).gl);var s=d(t,n),l=g(t,n),u=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));u.generateMipmap(),u.minFilter=t.LINEAR_MIPMAP_LINEAR,u.magFilter=t.LINEAR;var f=i(t),p=i(t),m=i(t),v=i(t),y=i(t),x=a(t,[{buffer:f,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:m,type:t.FLOAT,size:4},{buffer:v,type:t.FLOAT,size:2},{buffer:p,type:t.FLOAT,size:4}]),b=new h(t,u,s,l,f,p,y,m,v,x,r.traceType||\"cone\");return b.update(e),b}},{colormap:131,\"gl-buffer\":259,\"gl-mat4/invert\":293,\"gl-mat4/multiply\":295,\"gl-shader\":335,\"gl-texture2d\":353,\"gl-vao\":358,ndarray:495}],262:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * conePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\\n  vec4 t_position  = view * conePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = conePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n  gl_Position = projection * view * conePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},{glslify:263}],263:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],264:[function(t,e,r){e.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\"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p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  gl_FragColor = opacity * fragColor;\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"offset\",type:\"vec3\"}])}},{\"gl-shader\":335,glslify:267}],269:[function(t,e,r){\"use strict\";var n=t(\"gl-texture2d\");e.exports=function(t,e,r,n){i||(i=t.FRAMEBUFFER_UNSUPPORTED,a=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var c=t.getExtension(\"WEBGL_draw_buffers\");!l&&c&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new 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t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function d(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var d=0;d<i;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var g=this,m=[0|e,0|r];Object.defineProperties(m,{0:{get:function(){return g._shape[0]},set:function(t){return g.width=t}},1:{get:function(){return g._shape[1]},set:function(t){return g.height=t}}}),this._shapeVector=m,function(t){var e=c(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),i=t._shape[0],a=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,g=t._useDepth,m=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var v=0;v<o;++v)t.color[v]=h(r,i,a,m,r.RGBA,r.COLOR_ATTACHMENT0+v);0===o?(t._color_rb=p(r,i,a,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var y=r.getExtension(\"WEBGL_depth_texture\");y?d?t.depth=h(r,i,a,y.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):g&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),u(r,e),f(x)}u(r,e)}(this)}var g=d.prototype;function m(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=c(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),u(n,a),f(s)),u(n,a)}}Object.defineProperties(g,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return m(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return m(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,m(this,this._shape[0],t),t},enumerable:!1}}),g.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},g.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":353}],270:[function(t,e,r){var n=t(\"sprintf-js\").sprintf,i=t(\"gl-constants/lookup\"),a=t(\"glsl-shader-name\"),o=t(\"add-line-numbers\");e.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var c=n(\"Error compiling %s shader %s:\\n\",l,s),u=n(\"%s%s\",c,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var g=parseInt(d.split(\":\")[2]);if(isNaN(g))throw new Error(n(\"Could not parse error: %s\",d));h[g]=d}}var m=o(e).split(\"\\n\");for(p=0;p<m.length;p++)if(h[p+3]||h[p+2]||h[p+1]){var v=m[p];if(c+=v+\"\\n\",h[p+1]){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),c+=n(\"^^^ %s\\n\\n\",y)}}return{long:c.trim(),short:u.trim()}}},{\"add-line-numbers\":66,\"gl-constants/lookup\":265,\"glsl-shader-name\":431,\"sprintf-js\":567}],271:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.gl,n=o(r,l.vertex,l.fragment),i=o(r,l.pickVertex,l.pickFragment),a=s(r),u=s(r),f=s(r),h=s(r),p=new c(t,n,i,a,u,f,h);return p.update(e),t.addObject(p),p};var n=t(\"binary-search-bounds\"),i=t(\"iota-array\"),a=t(\"typedarray-pool\"),o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"./lib/shaders\");function c(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var u,f=c.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(u=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],c=a[3]-a[1];u[0]=2*o/l,u[4]=2*s/c,u[6]=2*(r[0]-a[0])/l-1,u[7]=2*(r[1]-a[1])/c-1,e.bind();var f=e.uniforms;f.viewTransform=u,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,c=a[2]-a[0],u=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*c/f,t[4]=2*u/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var g=i.attributes;return this.positionBuffer.bind(),g.position.pointer(),this.weightBuffer.bind(),g.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),g.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var c,u,f,p,d=t.colorLevels||[0],g=t.colorValues||[0,0,0,1],m=d.length,v=this.bounds;l?(c=v[0]=r[0],u=v[1]=o[0],f=v[2]=r[r.length-1],p=v[3]=o[o.length-1]):(c=v[0]=r[0]+(r[1]-r[0])/2,u=v[1]=o[0]+(o[1]-o[0])/2,f=v[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=v[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var y=1/(f-c),x=1/(p-u),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),M=a.mallocUint8(2*w),A=a.mallocUint32(w),S=0,E=l?b-1:b,C=l?_-1:_,L=0;L<C;++L){var I,P;l?(I=x*(o[L]-u),P=x*(o[L+1]-u)):(I=L<_-1?x*(o[L]-(o[L+1]-o[L])/2-u):x*(o[L]-(o[L]-o[L-1])/2-u),P=L<_-1?x*(o[L]+(o[L+1]-o[L])/2-u):x*(o[L]+(o[L]-o[L-1])/2-u));for(var z=0;z<E;++z){var O,D;l?(O=y*(r[z]-c),D=y*(r[z+1]-c)):(O=z<b-1?y*(r[z]-(r[z+1]-r[z])/2-c):y*(r[z]-(r[z]-r[z-1])/2-c),D=z<b-1?y*(r[z]+(r[z+1]-r[z])/2-c):y*(r[z]+(r[z]-r[z-1])/2-c));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],q=s[l?(L+V)*b+(z+U):L*b+z],H=n.le(d,q);if(H<0)F=g[0],B=g[1],N=g[2],j=g[3];else if(H===m-1)F=g[4*m-4],B=g[4*m-3],N=g[4*m-2],j=g[4*m-1];else{var G=(q-d[H])/(d[H+1]-d[H]),Y=1-G,W=4*H,X=4*(H+1);F=Y*g[W]+G*g[X],B=Y*g[W+1]+G*g[X+1],N=Y*g[W+2]+G*g[X+2],j=Y*g[W+3]+G*g[X+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*O+.5*D,k[2*S+1]=.5*I+.5*P,M[2*S]=U,M[2*S+1]=V,A[S]=L*b+z,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(M),this.colorBuffer.update(T),this.idBuffer.update(A),a.free(k),a.free(T),a.free(M),a.free(A)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":272,\"binary-search-bounds\":96,\"gl-buffer\":259,\"gl-shader\":335,\"iota-array\":463,\"typedarray-pool\":595}],272:[function(t,e,r){\"use strict\";var n=t(\"glslify\");e.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  fragColor = color;\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n  vec2 d = step(.5, vWeight);\\n  vec4 id = fragId + pickOffset;\\n  id.x += d.x + d.y*shape.x;\\n\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n  vWeight = weight;\\n\\n  fragId = pickId;\\n\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},{glslify:273}],273:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],274:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  vec4 startPoint = project(position);\\n  vec4 endPoint   = project(nextPosition);\\n\\n  vec2 A = startPoint.xy / startPoint.w;\\n  vec2 B =   endPoint.xy /   endPoint.w;\\n\\n  float clipAngle = atan(\\n    (B.y - A.y) * screenShape.y,\\n    (B.x - A.x) * screenShape.x\\n  );\\n\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n    sin(clipAngle),\\n    -cos(clipAngle)\\n  ) / screenShape;\\n\\n  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n  float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  float e = floor(log2(av));\\n  float m = av * pow(2.0, -e) - 1.0;\\n\\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n\\n  //Unpack exponent\\n  float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0;\\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n  gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return i(t,a,o,null,l)},r.createPickShader=function(t){return i(t,a,s,null,l)}},{\"gl-shader\":335,glslify:276}],275:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),u=c(new Array(1024),[256,1,4]),p=0;p<1024;++p)u.data[p]=255;var d=a(e,u);d.wrap=e.REPEAT;var g=new v(e,r,o,s,l,d);return g.update(t),g};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"gl-texture2d\"),o=new Uint8Array(4),s=new Float32Array(o.buffer);var l=t(\"binary-search-bounds\"),c=t(\"ndarray\"),u=t(\"./lib/shaders\"),f=u.createShader,h=u.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function g(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function m(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function v(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var y=v.prototype;y.isTransparent=function(){return this.hasAlpha},y.isOpaque=function(){return!this.hasAlpha},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:g(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:g(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],s=0,u=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],g=t.lineWidth||1,m=!1;t:for(e=1;e<h.length;++e){var v,y,x,b=h[e-1],_=h[e];for(a.push(s),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&i.length>0){for(var w=0;w<24;++w)i.push(i[i.length-12]);u+=2,m=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(v=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],y=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):v=y=p,3===v.length&&(v=[v[0],v[1],v[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]),!this.hasAlpha&&v[3]<1&&(this.hasAlpha=!0),x=Array.isArray(g)?g.length>e-1?g[e-1]:g.length>0?g[g.length-1]:[0,0,0,1]:g;var 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t[0]=1-(p+g),t[1]=f+y,t[2]=h-v,t[3]=0,t[4]=f-y,t[5]=1-(u+g),t[6]=d+m,t[7]=0,t[8]=h+v,t[9]=d-m,t[10]=1-(u+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},{}],285:[function(t,e,r){e.exports=function(t,e){return t[0]=e[0],t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=e[1],t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=e[2],t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],286:[function(t,e,r){e.exports=function(t,e){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=e[0],t[13]=e[1],t[14]=e[2],t[15]=1,t}},{}],287:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=n,t[6]=r,t[7]=0,t[8]=0,t[9]=-r,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],288:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=0,t[2]=-r,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=r,t[9]=0,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],289:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=0,t[4]=-r,t[5]=n,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],290:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(r-e),l=1/(i-n),c=1/(a-o);return t[0]=2*a*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=2*a*l,t[6]=0,t[7]=0,t[8]=(r+e)*s,t[9]=(i+n)*l,t[10]=(o+a)*c,t[11]=-1,t[12]=0,t[13]=0,t[14]=o*a*2*c,t[15]=0,t}},{}],291:[function(t,e,r){e.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],292:[function(t,e,r){e.exports={create:t(\"./create\"),clone:t(\"./clone\"),copy:t(\"./copy\"),identity:t(\"./identity\"),transpose:t(\"./transpose\"),invert:t(\"./invert\"),adjoint:t(\"./adjoint\"),determinant:t(\"./determinant\"),multiply:t(\"./multiply\"),translate:t(\"./translate\"),scale:t(\"./scale\"),rotate:t(\"./rotate\"),rotateX:t(\"./rotateX\"),rotateY:t(\"./rotateY\"),rotateZ:t(\"./rotateZ\"),fromRotation:t(\"./fromRotation\"),fromRotationTranslation:t(\"./fromRotationTranslation\"),fromScaling:t(\"./fromScaling\"),fromTranslation:t(\"./fromTranslation\"),fromXRotation:t(\"./fromXRotation\"),fromYRotation:t(\"./fromYRotation\"),fromZRotation:t(\"./fromZRotation\"),fromQuat:t(\"./fromQuat\"),frustum:t(\"./frustum\"),perspective:t(\"./perspective\"),perspectiveFromFieldOfView:t(\"./perspectiveFromFieldOfView\"),ortho:t(\"./ortho\"),lookAt:t(\"./lookAt\"),str:t(\"./str\")}},{\"./adjoint\":277,\"./clone\":278,\"./copy\":279,\"./create\":280,\"./determinant\":281,\"./fromQuat\":282,\"./fromRotation\":283,\"./fromRotationTranslation\":284,\"./fromScaling\":285,\"./fromTranslation\":286,\"./fromXRotation\":287,\"./fromYRotation\":288,\"./fromZRotation\":289,\"./frustum\":290,\"./identity\":291,\"./invert\":293,\"./lookAt\":294,\"./multiply\":295,\"./ortho\":296,\"./perspective\":297,\"./perspectiveFromFieldOfView\":298,\"./rotate\":299,\"./rotateX\":300,\"./rotateY\":301,\"./rotateZ\":302,\"./scale\":303,\"./str\":304,\"./translate\":305,\"./transpose\":306}],293:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],m=e[14],v=e[15],y=r*s-n*o,x=r*l-i*o,b=r*c-a*o,_=n*l-i*s,w=n*c-a*s,T=i*c-a*l,k=u*g-f*d,M=u*m-h*d,A=u*v-p*d,S=f*m-h*g,E=f*v-p*g,C=h*v-p*m,L=y*C-x*E+b*S+_*A-w*M+T*k;if(!L)return null;return L=1/L,t[0]=(s*C-l*E+c*S)*L,t[1]=(i*E-n*C-a*S)*L,t[2]=(g*T-m*w+v*_)*L,t[3]=(h*w-f*T-p*_)*L,t[4]=(l*A-o*C-c*M)*L,t[5]=(r*C-i*A+a*M)*L,t[6]=(m*b-d*T-v*x)*L,t[7]=(u*T-h*b+p*x)*L,t[8]=(o*E-s*A+c*k)*L,t[9]=(n*A-r*E-a*k)*L,t[10]=(d*w-g*b+v*y)*L,t[11]=(f*b-u*w-p*y)*L,t[12]=(s*M-o*S-l*k)*L,t[13]=(r*S-n*M+i*k)*L,t[14]=(g*x-d*_-m*y)*L,t[15]=(u*_-f*x+h*y)*L,t}},{}],294:[function(t,e,r){var n=t(\"./identity\");e.exports=function(t,e,r,i){var a,o,s,l,c,u,f,h,p,d,g=e[0],m=e[1],v=e[2],y=i[0],x=i[1],b=i[2],_=r[0],w=r[1],T=r[2];if(Math.abs(g-_)<1e-6&&Math.abs(m-w)<1e-6&&Math.abs(v-T)<1e-6)return n(t);f=g-_,h=m-w,p=v-T,d=1/Math.sqrt(f*f+h*h+p*p),a=x*(p*=d)-b*(h*=d),o=b*(f*=d)-y*p,s=y*h-x*f,(d=Math.sqrt(a*a+o*o+s*s))?(a*=d=1/d,o*=d,s*=d):(a=0,o=0,s=0);l=h*s-p*o,c=p*a-f*s,u=f*o-h*a,(d=Math.sqrt(l*l+c*c+u*u))?(l*=d=1/d,c*=d,u*=d):(l=0,c=0,u=0);return t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=c,t[6]=h,t[7]=0,t[8]=s,t[9]=u,t[10]=p,t[11]=0,t[12]=-(a*g+o*m+s*v),t[13]=-(l*g+c*m+u*v),t[14]=-(f*g+h*m+p*v),t[15]=1,t}},{\"./identity\":291}],295:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],g=e[12],m=e[13],v=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*f+w*g,t[1]=x*i+b*l+_*h+w*m,t[2]=x*a+b*c+_*p+w*v,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*g,t[5]=x*i+b*l+_*h+w*m,t[6]=x*a+b*c+_*p+w*v,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*g,t[9]=x*i+b*l+_*h+w*m,t[10]=x*a+b*c+_*p+w*v,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*g,t[13]=x*i+b*l+_*h+w*m,t[14]=x*a+b*c+_*p+w*v,t[15]=x*o+b*u+_*d+w*y,t}},{}],296:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t}},{}],297:[function(t,e,r){e.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},{}],298:[function(t,e,r){e.exports=function(t,e,r,n){var i=Math.tan(e.upDegrees*Math.PI/180),a=Math.tan(e.downDegrees*Math.PI/180),o=Math.tan(e.leftDegrees*Math.PI/180),s=Math.tan(e.rightDegrees*Math.PI/180),l=2/(o+s),c=2/(i+a);return t[0]=l,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=c,t[6]=0,t[7]=0,t[8]=-(o-s)*l*.5,t[9]=(i-a)*c*.5,t[10]=n/(r-n),t[11]=-1,t[12]=0,t[13]=0,t[14]=n*r/(r-n),t[15]=0,t}},{}],299:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,M,A,S,E=n[0],C=n[1],L=n[2],I=Math.sqrt(E*E+C*C+L*L);if(Math.abs(I)<1e-6)return null;E*=I=1/I,C*=I,L*=I,i=Math.sin(r),a=Math.cos(r),o=1-a,s=e[0],l=e[1],c=e[2],u=e[3],f=e[4],h=e[5],p=e[6],d=e[7],g=e[8],m=e[9],v=e[10],y=e[11],x=E*E*o+a,b=C*E*o+L*i,_=L*E*o-C*i,w=E*C*o-L*i,T=C*C*o+a,k=L*C*o+E*i,M=E*L*o+C*i,A=C*L*o-E*i,S=L*L*o+a,t[0]=s*x+f*b+g*_,t[1]=l*x+h*b+m*_,t[2]=c*x+p*b+v*_,t[3]=u*x+d*b+y*_,t[4]=s*w+f*T+g*k,t[5]=l*w+h*T+m*k,t[6]=c*w+p*T+v*k,t[7]=u*w+d*T+y*k,t[8]=s*M+f*A+g*S,t[9]=l*M+h*A+m*S,t[10]=c*M+p*A+v*S,t[11]=u*M+d*A+y*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t}},{}],300:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[4]=a*i+c*n,t[5]=o*i+u*n,t[6]=s*i+f*n,t[7]=l*i+h*n,t[8]=c*i-a*n,t[9]=u*i-o*n,t[10]=f*i-s*n,t[11]=h*i-l*n,t}},{}],301:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i-c*n,t[1]=o*i-u*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+c*i,t[9]=o*n+u*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},{}],302:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[4],u=e[5],f=e[6],h=e[7];e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i+c*n,t[1]=o*i+u*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=c*i-a*n,t[5]=u*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},{}],303:[function(t,e,r){e.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},{}],304:[function(t,e,r){e.exports=function(t){return\"mat4(\"+t[0]+\", \"+t[1]+\", \"+t[2]+\", \"+t[3]+\", \"+t[4]+\", \"+t[5]+\", \"+t[6]+\", \"+t[7]+\", \"+t[8]+\", \"+t[9]+\", \"+t[10]+\", \"+t[11]+\", \"+t[12]+\", \"+t[13]+\", \"+t[14]+\", \"+t[15]+\")\"}},{}],305:[function(t,e,r){e.exports=function(t,e,r){var n,i,a,o,s,l,c,u,f,h,p,d,g=r[0],m=r[1],v=r[2];e===t?(t[12]=e[0]*g+e[4]*m+e[8]*v+e[12],t[13]=e[1]*g+e[5]*m+e[9]*v+e[13],t[14]=e[2]*g+e[6]*m+e[10]*v+e[14],t[15]=e[3]*g+e[7]*m+e[11]*v+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=c,t[7]=u,t[8]=f,t[9]=h,t[10]=p,t[11]=d,t[12]=n*g+s*m+f*v+e[12],t[13]=i*g+l*m+h*v+e[13],t[14]=a*g+c*m+p*v+e[14],t[15]=o*g+u*m+d*v+e[15]);return t}},{}],306:[function(t,e,r){e.exports=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},{}],307:[function(t,e,r){\"use strict\";var n=t(\"barycentric\"),i=t(\"polytope-closest-point/lib/closest_point_2d.js\");function a(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var i=0;i<4;++i)r[i]+=t[4*n+i]*e[n];return r}function o(t,e,r,n,i){for(var o=a(n,a(r,a(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*i[0]*(1+o[0]),.5*i[1]*(1-o[1])]}function s(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;o<3;++o)r[o]+=a*i[o];return r}e.exports=function(t,e,r,a,l,c){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),f=0;f<t.length;++f)u[f]=o(t[f],r,a,l,c);var h=0,p=1/0;for(f=0;f<u.length;++f){for(var d=0,g=0;g<2;++g)d+=Math.pow(u[f][g]-e[g],2);d<p&&(p=d,h=f)}var m=function(t,e){if(2===t.length){for(var r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return r=Math.sqrt(r),a=Math.sqrt(a),r+a<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(u,e),v=0;for(f=0;f<3;++f){if(m[f]<-.001||m[f]>1.0001)return null;v+=m[f]}if(Math.abs(v-1)>.001)return null;return[h,s(t,m),m]}},{barycentric:78,\"polytope-closest-point/lib/closest_point_2d.js\":525}],308:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection\\n           , inverseModel;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position      = project(position);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * vec4(position , 1.0);\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  f_color          = color;\\n  f_data           = position;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (f_color.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], f_data)\\n  ) discard;\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:l,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{glslify:310}],309:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),f=t(\"colormap\"),h=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./lib/shaders\"),g=t(\"./lib/closest-point\"),m=d.meshShader,v=d.wireShader,y=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,T,k,M,A,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=m,this.edgeUVs=v,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=M,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=A,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function M(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function A(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function S(t){var e=n(t,v.vertex,v.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function E(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function C(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function L(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function I(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var c=r[l],u=0;u<2;++u){var f=c[0];2===c.length&&(f=c[u]);for(var d=n[f][0],g=n[f][1],m=i[f],v=1-m,y=this.positions[d],x=this.positions[g],b=0;b<3;++b)o[s++]=m*y[b]+v*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*M(i/255,e):255*a[3]}return u(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],c=[],h=[],p=[],d=[],g=[],m=[],v=[],y=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,A=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,A)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,C=t.meshColor||[1,1,1,1],L=t.vertexUVs,I=t.vertexIntensity,P=t.cellUVs,z=t.cellIntensity,O=1/0,D=-1/0;if(!L&&!P)if(I)if(t.vertexIntensityBounds)O=+t.vertexIntensityBounds[0],D=+t.vertexIntensityBounds[1];else for(var R=0;R<I.length;++R){var F=I[R];O=Math.min(O,F),D=Math.max(D,F)}else if(z)if(t.cellIntensityBounds)O=+t.cellIntensityBounds[0],D=+t.cellIntensityBounds[1];else for(R=0;R<z.length;++R){F=z[R];O=Math.min(O,F),D=Math.max(D,F)}else for(R=0;R<n.length;++R){F=n[R][2];O=Math.min(O,F),D=Math.max(D,F)}this.intensity=I||(z||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n)),this.pickVertex=!(z||E);var B=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,q=0,H=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[W=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;v.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:C,this.opacityscale&&I?a.push(X[0],X[1],X[2],this.opacity*M((I[W]-O)/(D-O),this.opacityscale)):3===X.length?y.push(X[0],X[1],X[2],this.opacity):(y.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=L?L[W]:I?[(I[W]-O)/(D-O),0]:P?P[R]:z?[(z[R]-O)/(D-O),0]:[(j[2]-O)/(D-O),0],x.push(Z[0],Z[1]),B?b.push(B[W]):b.push(N),_.push(R),H+=1;break;case 2:for(U=0;U<2;++U){j=n[W=G[U]];for(var Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t}for(U=0;U<2;++U){j=n[W=G[U]];p.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:C,this.opacityscale&&I?a.push(X[0],X[1],X[2],this.opacity*M((I[W]-O)/(D-O),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=L?L[W]:I?[(I[W]-O)/(D-O),0]:P?P[R]:z?[(z[R]-O)/(D-O),0]:[(j[2]-O)/(D-O),0],g.push(Z[0],Z[1]),m.push(R)}q+=1;break;case 3:for(U=0;U<3;++U)for(j=n[W=G[U]],Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t;for(U=0;U<3;++U){var W,X,Z,J;j=n[W=G[2-U]];i.push(j[0],j[1],j[2]),(X=S?S[W]:E?E[R]:C)?this.opacityscale&&I?a.push(X[0],X[1],X[2],this.opacity*M((I[W]-O)/(D-O),this.opacityscale)):3===X.length?a.push(X[0],X[1],X[2],this.opacity):(a.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),Z=L?L[W]:I?[(I[W]-O)/(D-O),0]:P?P[R]:z?[(z[R]-O)/(D-O),0]:[(j[2]-O)/(D-O),0],c.push(Z[0],Z[1]),J=w?w[W]:T[R],l.push(J[0],J[1],J[2]),h.push(R)}V+=1}}this.pointCount=H,this.edgeCount=q,this.triangleCount=V,this.pointPositions.update(v),this.pointColors.update(y),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(g),this.edgeIds.update(new Uint32Array(m)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(c),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var f,h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind());this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind());this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind());this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};((s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0)&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],c=this.positions[r[1]],u=this.positions[r[2]],f=[(l[0]+c[0]+u[0])/3,(l[1]+c[1]+u[1])/3,(l[2]+c[2]+u[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=g(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\");if(!r)throw new Error(\"derivatives not supported\");var n=A(t),s=S(t),l=E(t),c=C(t),f=L(t),h=I(t),p=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),g=i(t),m=i(t),v=i(t),y=i(t),x=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:m,type:t.FLOAT,size:2},{buffer:v,type:t.FLOAT,size:3}]),b=i(t),_=i(t),w=i(t),k=i(t),M=a(t,[{buffer:b,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),P=i(t),z=i(t),O=i(t),D=i(t),R=i(t),F=a(t,[{buffer:P,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:z,type:t.FLOAT,size:4},{buffer:O,type:t.FLOAT,size:2},{buffer:D,type:t.FLOAT,size:1}]),B=i(t),N=a(t,[{buffer:B,type:t.FLOAT,size:3}]),j=new T(t,p,n,s,l,c,f,h,d,y,g,m,v,x,b,k,_,w,M,P,R,z,O,D,F,B,N);return j.update(e),j}},{\"./lib/closest-point\":307,\"./lib/shaders\":308,colormap:131,\"gl-buffer\":259,\"gl-mat4/invert\":293,\"gl-mat4/multiply\":295,\"gl-shader\":335,\"gl-texture2d\":353,\"gl-vao\":358,ndarray:495,normals:498,\"simplicial-complex-contour\":556,\"typedarray-pool\":595}],310:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],311:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[0,0,0,1,1,0,1,1]),s=i(e,a.boxVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,c=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":314,\"gl-buffer\":259,\"gl-shader\":335}],312:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,o.gridVert,o.gridFrag),l=i(e,o.tickVert,o.gridFrag);return new s(t,r,a,l)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"binary-search-bounds\"),o=t(\"./shaders\");function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var c,u,f,h,p,d=s.prototype;d.draw=(c=[0,0],u=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,g=0;g<2;++g){var m=a[g],v=a[g+2]-m,y=.5*(o[g+2]+o[g]),x=o[g+2]-o[g];u[g]=2*v/x,c[g]=2*(m-y)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=c,r.uniforms.dataScale=u;var b=0;for(g=0;g<2;++g){f[0]=f[1]=0,f[g]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[g]/(s[g+2]-s[g])*d,r.uniforms.color=h[g];var _=6*n[g].length;p[g]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,c=this.vbo,u=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,g=s.viewBox,m=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],x=v[3]-v[1],b=g[2]-g[0],_=g[3]-g[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,M=.5*(d[w+2]+d[w]),A=d[w+2]-d[w];e[w]=2*k/A,t[w]=2*(T-M)/A}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,u.bind(),c.bind(),u.attributes.dataCoord.pointer();var S=u.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,C=s.tickMarkWidth,L=s.tickMarkColor,I=6*f[0].length,P=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),z=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),O=0+6*P,D=6*Math.max(0,z-P),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=I+6*R,N=6*Math.max(0,F-R);i[0]=2*(g[0]-E[1])/y-1,i[1]=(g[3]+g[1])/x-1,o[0]=E[1]*m/y,o[1]=C[1]*m/x,N&&(S.color=L[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(g[2]+g[0])/y-1,i[1]=2*(g[1]-E[0])/x-1,o[0]=C[0]*m/y,o[1]=E[0]*m/x,D&&(S.color=L[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,O,D)),i[0]=2*(g[2]+E[3])/y-1,i[1]=(g[3]+g[1])/x-1,o[0]=E[3]*m/y,o[1]=C[3]*m/x,N&&(S.color=L[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(g[2]+g[0])/y-1,i[1]=2*(g[3]+E[2])/x-1,o[0]=C[2]*m/y,o[1]=E[2]*m/x,D&&(S.color=L[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,O,D))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],c=r[o],u=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-c)/(u-c);s.push(d);for(var g=0;g<6;++g)n[i++]=d,n[i++]=h[g],n[i++]=p[g]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":314,\"binary-search-bounds\":96,\"gl-buffer\":259,\"gl-shader\":335}],313:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[-1,-1,-1,1,1,-1,1,1]),s=i(e,a.lineVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,c=this.shader,u=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,c.uniforms.start=s,c.uniforms.end=l,c.uniforms.width=i*o.pixelRatio,c.uniforms.color=a,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":314,\"gl-buffer\":259,\"gl-shader\":335}],314:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);e.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},{glslify:316}],315:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,s.textVert,s.textFrag);return new l(t,r,a)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"text-cache\"),o=t(\"binary-search-bounds\"),s=t(\"./shaders\");function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var c,u,f,h,p,d,g=l.prototype;g.drawTicks=(c=[0,0],u=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,g=e.tickPad,m=e.tickColor,v=e.tickAngle,y=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),M=o.le(n,l[t+2]);c[0]=c[1]=0,c[t]=1,u[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var A=2/h[2+(1^t)]-h[1^t];u[1^t]=A*s[1^t]-1,d[t]&&(u[1^t]-=A*p*g[t],k<M&&i[M]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=m[t],r.uniforms.angle=v[t],a.drawArrays(a.TRIANGLES,i[k],i[M]-i[k]))),y[t]&&T&&(u[1^t]-=A*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),u[1^t]=A*s[2+(1^t)]-1,d[t+2]&&(u[1^t]+=A*p*g[t+2],k<M&&i[M]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=m[t+2],r.uniforms.angle=v[t+2],a.drawArrays(a.TRIANGLES,i[k],i[M]-i[k]))),y[t+2]&&T&&(u[1^t]+=A*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),g.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,c=r.pixelRatio;if(this.titleCount){for(var u=0;u<2;++u)e[u]=2*(o[u]*c-a[u])/(a[2+u]-a[u])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),g.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,c=.5*(n[o+2]+n[o]),u=n[o+2]-n[o],f=a[o],g=a[o+2]-f,m=i[o],v=i[o+2]-m;p[o]=2*l/u*g/v,h[o]=2*(s-c)/u*g/v}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),g.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,c=t.bounds;for(o=0;o<2;++o){var u=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,g=p.text,m=p.font||\"sans-serif\";i=p.fontSize||12;for(var v=1/(c[o+2]-c[o]),y=c[o],x=g.split(\"\\n\"),b=0;b<x.length;b++)for(n=a(m,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-y)*v);u.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=u,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},g.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":314,\"binary-search-bounds\":96,\"gl-buffer\":259,\"gl-shader\":335,\"text-cache\":575}],316:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],317:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[e.drawingBufferWidth,e.drawingBufferHeight]),c=new l(e,r);return c.grid=i(c),c.text=a(c),c.line=o(c),c.box=s(c),c.update(t),c};var n=t(\"gl-select-static\"),i=t(\"./lib/grid\"),a=t(\"./lib/text\"),o=t(\"./lib/line\"),s=t(\"./lib/box\");function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var c=l.prototype;function u(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}c.setDirty=function(){this.dirty=this.pickDirty=!0},c.setOverlayDirty=function(){this.dirty=!0},c.nextDepthValue=function(){return this._depthCounter++/65536},c.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var c=this.borderColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var u=this.backgroundColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],h[d]):o.drawLine(e[0],g,e[2],g,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var m=this.borderLineEnable,v=this.borderLineWidth,y=this.borderLineColor;for(m[1]&&o.drawLine(r[0],r[1]-.5*v[1]*i,r[0],r[3]+.5*v[3]*i,v[1],y[1]),m[0]&&o.drawLine(r[0]-.5*v[0]*i,r[1],r[2]+.5*v[2]*i,r[1],v[0],y[0]),m[3]&&o.drawLine(r[2],r[1]-.5*v[1]*i,r[2],r[3]+.5*v[3]*i,v[3],y[3]),m[2]&&o.drawLine(r[0]-.5*v[0]*i,r[3],r[2]+.5*v[2]*i,r[3],v[2],y[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},c.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},c.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),c=this.objects,u=0;u<c.length;++u){var f=c[u].pick(a,o,l);if(f)return f}return null}},c.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},c.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},c.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},c.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=u(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=u(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=u(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=u(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=u(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=u(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},c.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},c.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},c.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},c.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},c.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":311,\"./lib/grid\":312,\"./lib/line\":313,\"./lib/text\":315,\"gl-select-static\":334}],318:[function(t,e,r){\"use strict\";e.exports=function(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]);\"zoomMin\"in e&&(r[0]=e.zoomMin);\"zoomMax\"in e&&(r[1]=e.zoomMax);var c=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),u=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:c,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:c.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;c.idle(e-r),c.recalcMatrix(i),c.flush(e-(100+2*r));for(var a=!0,o=c.computedMatrix,s=0;s<16;++s)a=a&&u[s]===o[s],u[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(c.computedRadius[0]),!0)},lookAt:function(t,e,r){c.lookAt(c.lastT(),t,e,r)},rotate:function(t,e,r){c.rotate(c.lastT(),t,e,r)},pan:function(t,e,r){c.pan(c.lastT(),t,e,r)},translate:function(t,e,r){c.translate(c.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return c.computedMatrix},set:function(t){return c.setMatrix(c.lastT(),t),c.computedMatrix},enumerable:!0},mode:{get:function(){return c.getMode()},set:function(t){var e=c.computedUp.slice(),r=c.computedEye.slice(),i=c.computedCenter.slice();if(c.setMode(t),\"turntable\"===t){var a=n();c._active.lookAt(a,r,i,e),c._active.lookAt(a+500,r,i,[0,0,1]),c._active.flush(a)}return c.getMode()},enumerable:!0},center:{get:function(){return c.computedCenter},set:function(t){return c.lookAt(c.lastT(),null,t),c.computedCenter},enumerable:!0},eye:{get:function(){return c.computedEye},set:function(t){return c.lookAt(c.lastT(),t),c.computedEye},enumerable:!0},up:{get:function(){return c.computedUp},set:function(t){return c.lookAt(c.lastT(),null,null,t),c.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return c.setDistance(c.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return c.getDistanceLimits(r)},set:function(t){return c.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,u=\"zoom\"===o,h=!!a.control,p=!!a.alt,g=!!a.shift,m=!!(1&e),v=!!(2&e),y=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,M=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&m&&!h&&!p&&!g||m&&!h&&!p&&g)&&c.rotate(M,w*k*b,-T*k*_,0),(l&&m&&!h&&!p&&!g||v||m&&h&&!p&&!g)&&c.pan(M,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),u&&m&&!h&&!p&&!g||y||m&&!h&&p&&!g)){var A=-d.zoomSpeed*_/window.innerHeight*(M-c.lastT())*100;c.pan(M,0,0,f*(Math.exp(A)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener(\"touchmove\",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener(\"touchend\",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))c.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-c.lastT())/20;c.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=t(\"right-now\"),i=t(\"3d-view\"),a=t(\"mouse-change\"),o=t(\"mouse-wheel\"),s=t(\"mouse-event-offset\"),l=t(\"has-passive-events\")},{\"3d-view\":54,\"has-passive-events\":441,\"mouse-change\":483,\"mouse-event-offset\":484,\"mouse-wheel\":486,\"right-now\":542}],319:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":335,glslify:320}],320:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],321:[function(t,e,r){\"use strict\";var n=t(\"./camera.js\"),i=t(\"gl-axes3d\"),a=t(\"gl-axes3d/properties\"),o=t(\"gl-spikes3d\"),s=t(\"gl-select-static\"),l=t(\"gl-fbo\"),c=t(\"a-big-triangle\"),u=t(\"mouse-change\"),f=t(\"gl-mat4/perspective\"),h=t(\"gl-mat4/ortho\"),p=t(\"./lib/shader\"),d=t(\"is-mobile\")({tablet:!0,featureDetect:!0});function g(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function m(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function v(t){return\"boolean\"!=typeof t||t}e.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;if(!e){if(e=document.createElement(\"canvas\"),t.container)t.container.appendChild(e);else document.body.appendChild(e)}var r=t.gl;r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d}));if(!r)throw new Error(\"webgl not supported\");var y=t.bounds||[[-10,-10,-10],[10,10,10]],x=new g,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},M=i(r,k);M.enable=!k.disable;var A=t.spikes||{},S=o(r,A),E=[],C=[],L=[],I=[],P=!0,z=!0,O=new Array(16),D=new Array(16),R={view:null,projection:O,model:D,_ortho:!1},F=(z=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),B=t.cameraObject||n(e,T),N={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:B,axes:M,axesPixels:null,spikes:S,bounds:y,objects:E,shape:F,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:v(t.autoResize),autoBounds:v(t.autoBounds),autoScale:!!t.autoScale,autoCenter:v(t.autoCenter),clipToBounds:v(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:R,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,z=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},j=[r.drawingBufferWidth/N.pixelRatio|0,r.drawingBufferHeight/N.pixelRatio|0];function U(){if(!N._stopped&&N.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*N.pixelRatio),a=0|Math.ceil(n*N.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",P=!0}}}N.autoResize&&U();function V(){for(var t=E.length,e=I.length,n=0;n<e;++n)L[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(L[o]+a<255){C[n]=o,i.setPickBase(L[o]+1),L[o]+=a;continue t}var l=s(r,F);C[n]=e,I.push(l),L.push(a),i.setPickBase(1),e+=1}else C[n]=-1}for(;e>0&&0===L[e-1];)L.pop(),I.pop().dispose()}function q(){if(N.contextLost)return!0;r.isContextLost()&&(N.contextLost=!0,N.mouseListener.enabled=!1,N.selection.object=null,N.oncontextloss&&N.oncontextloss())}window.addEventListener(\"resize\",U),N.update=function(t){N._stopped||(t=t||{},P=!0,z=!0)},N.add=function(t){N._stopped||(t.axes=M,E.push(t),C.push(-1),P=!0,z=!0,V())},N.remove=function(t){if(!N._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),C.pop(),P=!0,z=!0,V())}},N.dispose=function(){if(!N._stopped&&(N._stopped=!0,window.removeEventListener(\"resize\",U),e.removeEventListener(\"webglcontextlost\",q),N.mouseListener.enabled=!1,!N.contextLost)){M.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();b.dispose();for(t=0;t<I.length;++t)I[t].dispose();_.dispose(),r=null,M=null,S=null,E=[]}},N._mouseRotating=!1,N._prevButtons=0,N.enableMouseListeners=function(){N.mouseListener=u(e,(function(t,e,r){if(!N._stopped){var n=I.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&N._prevButtons)N._mouseRotating=!0;else{N._mouseRotating&&(z=!0),N._mouseRotating=!1;for(var s=0;s<n;++s){var l=I[s].query(e,j[1]-r-1,N.pickRadius);if(l){if(l.distance>x.distance)continue;for(var c=0;c<i;++c){var u=E[c];if(C[c]===s){var f=u.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=u,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),P=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),P=!0),(o=o||x.object!==a)&&N.onselect&&N.onselect(x),1&t&&!(1&N._prevButtons)&&N.onclick&&N.onclick(x),N._prevButtons=t}}))},e.addEventListener(\"webglcontextlost\",q);var H=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],G=[H[0].slice(),H[1].slice()];function Y(){if(!q()){U();var t=N.camera.tick();R.view=N.camera.matrix,P=P||t,z=z||t,M.pixelRatio=N.pixelRatio,S.pixelRatio=N.pixelRatio;var e=E.length,n=H[0],i=H[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(L=E[o]).pixelRatio=N.pixelRatio,L.axes=N.axes,P=P||!!L.dirty,z=z||!!L.dirty;var s=L.bounds;if(s)for(var l=s[0],u=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],u[p])}var d=N.bounds;if(N.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var g=.05*(i[p]-n[p]);n[p]=n[p]-g,i[p]=i[p]+g}d[0][p]=n[p],d[1][p]=i[p]}var v=!1;for(p=0;p<3;++p)v=v||G[0][p]!==d[0][p]||G[1][p]!==d[1][p],G[0][p]=d[0][p],G[1][p]=d[1][p];if(z=z||v,P=P||v){if(v){var y=[0,0,0];for(o=0;o<3;++o)y[o]=m((d[1][o]-d[0][o])/10);M.autoTicks?M.update({bounds:d,tickSpacing:y}):M.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;F[0]=T,F[1]=k,j[0]=0|Math.max(T/N.pixelRatio,1),j[1]=0|Math.max(k/N.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,c=t.zFar,u=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,c),n._ortho=!0):(f(i,u,p,l,c),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var g=0;for(d=0;d<3;++d)g=Math.max(g,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/g,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(N,w);for(o=0;o<e;++o){(L=E[o]).axesBounds=d,N.clipToBounds&&(L.clipBounds=d)}x.object&&(N.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),z&&(z=!1,function(){if(!q()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=I.length,n=0;n<e;++n){var i=I[n];i.shape=j,i.begin();for(var a=0;a<t;++a)if(C[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(R))}i.end()}}}()),N.axesPixels=a(N.axes,R,T,k),N.onrender&&N.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),N.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var A=!1;M.enable&&(A=A||M.isTransparent(),M.draw(R)),S.axes=M,x.object&&S.draw(R),r.disable(r.CULL_FACE);for(o=0;o<e;++o){(L=E[o]).axes=M,L.pixelRatio=N.pixelRatio,L.isOpaque&&L.isOpaque()&&L.draw(R),L.isTransparent&&L.isTransparent()&&(A=!0)}if(A){b.shape=F,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),M.enable&&M.isTransparent()&&M.drawTransparent(R);for(o=0;o<e;++o){(L=E[o]).isOpaque&&L.isOpaque()&&L.draw(R)}r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),M.isTransparent()&&M.drawTransparent(R);for(o=0;o<e;++o){var L;(L=E[o]).isTransparent&&L.isTransparent()&&L.drawTransparent(R)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,c(r),r.disable(r.BLEND)}P=!1;for(o=0;o<e;++o)E[o].dirty=!1}}}return N.enableMouseListeners(),function t(){if(N._stopped||N.contextLost)return;Y(),requestAnimationFrame(t)}(),N.redraw=function(){N._stopped||(P=!0,Y())},N},createCamera:n}},{\"./camera.js\":318,\"./lib/shader\":319,\"a-big-triangle\":64,\"gl-axes3d\":250,\"gl-axes3d/properties\":258,\"gl-fbo\":269,\"gl-mat4/ortho\":296,\"gl-mat4/perspective\":297,\"gl-select-static\":334,\"gl-spikes3d\":345,\"is-mobile\":467,\"mouse-change\":483}],322:[function(t,e,r){var n=t(\"glslify\");r.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\"]),r.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\"]),r.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\"]),r.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"])},{glslify:323}],323:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],324:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"typedarray-pool\"),o=t(\"./lib/shader\");function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}e.exports=function(t,e){var r=t.gl,a=i(r),l=i(r),c=n(r,o.pointVertex,o.pointFragment),u=n(r,o.pickVertex,o.pickFragment),f=new s(t,a,l,c,u);return f.update(e),t.addObject(f),f};var l,c,u=s.prototype;u.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},u.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),c=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)c[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(c),i||a.free(l),o||a.free(c),this.pointCount=n,this.pickOffset=0},u.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],c=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),u=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=u<5,r.uniforms.pointSize=u,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(c[0]=255&t,c[1]=t>>8&255,c[2]=t>>16&255,c[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=c,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),u.draw=u.unifiedDraw,u.drawPick=u.unifiedDraw,u.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":322,\"gl-buffer\":259,\"gl-shader\":335,\"typedarray-pool\":595}],325:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c=e[0],u=e[1],f=e[2],h=e[3],p=r[0],d=r[1],g=r[2],m=r[3];(a=c*p+u*d+f*g+h*m)<0&&(a=-a,p=-p,d=-d,g=-g,m=-m);1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n);return t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*f+l*g,t[3]=s*h+l*m,t}},{}],326:[function(t,e,r){\"use strict\";e.exports=function(t){return t||0===t?t.toString():\"\"}},{}],327:[function(t,e,r){\"use strict\";var n=t(\"vectorize-text\");e.exports=function(t,e,r){var a=i[e];a||(a=i[e]={});if(t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,c,u=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(c=0;c<s.positions[l].length;++c)s.positions[l][c]/=r;for(l=0;l<u.positions.length;++l)for(c=0;c<u.positions[l].length;++c)u.positions[l][c]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=u.positions.length;for(l=0;l<h;++l){var p=u.positions[l];for(c=0;c<2;++c)f[0][c]=Math.min(f[0][c],p[c]),f[1][c]=Math.max(f[1][c],p[c])}return a[t]=[s,u,f]};var i={}},{\"vectorize-text\":600}],328:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n\\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (\\n    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n    interpColor.a * opacity == 0.\\n  ) discard;\\n  gl_FragColor = interpColor * opacity;\\n}\\n\"]),c=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n  gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),u=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:u},h={vertex:o,fragment:l,attributes:u},p={vertex:s,fragment:l,attributes:u},d={vertex:a,fragment:c,attributes:u},g={vertex:o,fragment:c,attributes:u},m={vertex:s,fragment:c,attributes:u};function v(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}r.createPerspective=function(t){return v(t,f)},r.createOrtho=function(t){return v(t,h)},r.createProject=function(t){return v(t,p)},r.createPickPerspective=function(t){return v(t,d)},r.createPickOrtho=function(t){return v(t,g)},r.createPickProject=function(t){return v(t,m)}},{\"gl-shader\":335,glslify:329}],329:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],330:[function(t,e,r){\"use strict\";var n=t(\"is-string-blank\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"typedarray-pool\"),s=t(\"gl-mat4/multiply\"),l=t(\"./lib/shaders\"),c=t(\"./lib/glyphs\"),u=t(\"./lib/get-simple-string\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function g(t){return!0===t||t>1?1:t}function m(t,e,r,n,i,a,o,s,l,c,u,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=u,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}e.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),c=l.createPickOrtho(e),u=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),g=a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new m(e,r,n,o,f,h,p,d,g,s,c,u);return v.update(t),v};var v=m.prototype;v.pickSlots=1,v.setPickBase=function(t){this.pickId=t},v.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},v.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var y=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],M=[[0,0,0],[0,0,0]];function A(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function C(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,c=r.model||f,u=r.view||f,h=r.projection||f,d=e.axesBounds,g=function(t){for(var e=M,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],y[0]=2/o.drawingBufferWidth,y[1]=2/o.drawingBufferHeight,t.bind(),l.view=u,l.projection=h,l.screenSize=y,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=g,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var m=0;m<3;++m)if(a[m]){l.scale=e.projectScale[m],l.opacity=e.projectOpacity[m];for(var v=T,C=0;C<16;++C)v[C]=0;for(C=0;C<4;++C)v[5*C]=1;v[5*m]=0,i[m]<0?v[12+m]=d[0][m]:v[12+m]=d[1][m],s(v,c,v),l.model=v;var L=(m+1)%3,I=(m+2)%3,P=A(x),z=A(b);P[L]=1,z[I]=1;var O=p(0,0,0,S(_,P)),D=p(0,0,0,S(w,z));if(Math.abs(O[1])>Math.abs(D[1])){var R=O;O=D,D=R,R=P,P=z,z=R;var F=L;L=I,I=F}O[0]<0&&(P[L]=-1),D[1]>0&&(z[I]=-1);var B=0,N=0;for(C=0;C<4;++C)B+=Math.pow(c[4*L+C],2),N+=Math.pow(c[4*I+C],2);P[L]/=Math.sqrt(B),z[I]/=Math.sqrt(N),l.axes[0]=P,l.axes[1]=z,l.fragClipBounds[0]=E(k,g[0],m,-1e8),l.fragClipBounds[1]=E(k,g[1],m,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function I(t,e,r,n,i,a,o){var s=r.gl;if((a===r.projectHasAlpha||o)&&C(e,r,n,i),a===r.hasAlpha||o){t.bind();var l=t.uniforms;l.model=n.model||f,l.view=n.view||f,l.projection=n.projection||f,y[0]=2/s.drawingBufferWidth,y[1]=2/s.drawingBufferHeight,l.screenSize=y,l.highlightId=r.highlightId,l.highlightScale=r.highlightScale,l.fragClipBounds=L,l.clipBounds=r.axes.bounds,l.opacity=r.opacity,l.pickGroup=r.pickId/255,l.pixelRatio=i,r.vao.bind(),r.vao.draw(s.TRIANGLES,r.vertexCount),r.lineWidth>0&&(s.lineWidth(r.lineWidth*i),r.vao.draw(s.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function P(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=u(a);var o=!0;n(a)&&(a=\"\\u25bc\",o=!1);var s=c(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}v.draw=function(t){I(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},v.drawTransparent=function(t){I(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},v.drawPick=function(t){I(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},v.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},v.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},v.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{r=+t.projectOpacity;this.projectOpacity=[r,r,r]}for(var n=0;n<3;++n)this.projectOpacity[n]=g(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=g(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",c=t.alignment||[0,0];if(2===c.length)i=c[0],a=c[1];else{i=[],a=[];for(n=0;n<c.length;++n)i[n]=c[n][0],a[n]=c[n][1]}var u=[1/0,1/0,1/0],f=[-1/0,-1/0,-1/0],h=t.glyph,p=t.color,d=t.size,m=t.angle,v=t.lineColor,y=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],T=0;T<3;++T)if(isNaN(w[T])||!isFinite(w[T]))continue t;var k=(N=P(h,n,l,this.pixelRatio)).mesh,M=N.lines,A=N.bounds;x+=3*k.cells.length,b+=2*M.edges.length}}var S=x+b,E=o.mallocFloat(3*S),C=o.mallocFloat(4*S),L=o.mallocFloat(2*S),I=o.mallocUint32(S);if(S>0){var z=0,O=x,D=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(v)&&Array.isArray(v[0]);t:for(n=0;n<_;++n){y+=1;for(w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T])}k=(N=P(h,n,l,this.pixelRatio)).mesh,M=N.lines,A=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(T=0;T<3;++T)D[T]=U[T];D[3]=1}else if(4===U.length){for(T=0;T<4;++T)D[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else D[0]=D[1]=D[2]=0,D[3]=1;else D=[1,1,1,0];if(j)if(Array.isArray(v)){var U;if(3===(U=B?n<v.length?v[n]:[0,0,0,0]:v).length){for(T=0;T<3;++T)R[T]=U[T];R[T]=1}else if(4===U.length){for(T=0;T<4;++T)R[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else R[0]=R[1]=R[2]=0,R[3]=1;else R=[1,1,1,0];var V=.5;j?Array.isArray(d)?V=n<d.length?+d[n]:12:d?V=+d:this.useOrtho&&(V=12):V=0;var q=0;Array.isArray(m)?q=n<m.length?+m[n]:0:m&&(q=+m);var H=Math.cos(q),G=Math.sin(q);for(w=s[n],T=0;T<3;++T)f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T]);var Y=i,W=a;Y=0;Array.isArray(i)?Y=n<i.length?i[n]:0:i&&(Y=i);W=0;Array.isArray(a)?W=n<a.length?a[n]:0:a&&(W=a);var X=[Y*=Y>0?1-A[0][0]:Y<0?1+A[1][0]:1,W*=W>0?1-A[0][1]:W<0?1+A[1][1]:1],Z=k.cells||[],J=k.positions||[];for(T=0;T<Z.length;++T)for(var K=Z[T],Q=0;Q<3;++Q){for(var $=0;$<3;++$)E[3*z+$]=w[$];for($=0;$<4;++$)C[4*z+$]=D[$];I[z]=y;var tt=J[K[Q]];L[2*z]=V*(H*tt[0]-G*tt[1]+X[0]),L[2*z+1]=V*(G*tt[0]+H*tt[1]+X[1]),z+=1}for(Z=M.edges,J=M.positions,T=0;T<Z.length;++T)for(K=Z[T],Q=0;Q<2;++Q){for($=0;$<3;++$)E[3*O+$]=w[$];for($=0;$<4;++$)C[4*O+$]=R[$];I[O]=y;tt=J[K[Q]];L[2*O]=V*(H*tt[0]-G*tt[1]+X[0]),L[2*O+1]=V*(G*tt[0]+H*tt[1]+X[1]),O+=1}}}this.bounds=[u,f],this.points=s,this.pointCount=s.length,this.vertexCount=x,this.lineVertexCount=b,this.pointBuffer.update(E),this.colorBuffer.update(C),this.glyphBuffer.update(L),this.idBuffer.update(I),o.free(E),o.free(C),o.free(L),o.free(I)},v.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/get-simple-string\":326,\"./lib/glyphs\":327,\"./lib/shaders\":328,\"gl-buffer\":259,\"gl-mat4/multiply\":295,\"gl-vao\":358,\"is-string-blank\":470,\"typedarray-pool\":595}],331:[function(t,e,r){\"use strict\";var n=t(\"glslify\");r.boxVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\"]),r.boxFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"])},{glslify:332}],332:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],333:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"./lib/shaders\");function o(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-1/0,-1/0],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}e.exports=function(t,e){var r=t.gl,s=i(r,[0,0,0,1,1,0,1,1]),l=n(r,a.boxVertex,a.boxFragment),c=new o(t,s,l);return c.update(e),t.addOverlay(c),c};var s=o.prototype;s.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,c=t.viewBox,u=t.pixelRatio,f=(e[0]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],h=(e[1]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1],p=(e[2]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],d=(e[3]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1];if(f=Math.max(f,c[0]),h=Math.max(h,c[1]),p=Math.min(p,c[2]),d=Math.min(d,c[3]),!(p<f||d<h)){o.bind();var g=s[2]-s[0],m=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,g,m,i),o.drawBox(p,h,g,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var v=r*u;o.drawBox(f-v,h-v,p+v,h+v,a),o.drawBox(f-v,d-v,p+v,d+v,a),o.drawBox(f-v,h-v,f+v,d+v,a),o.drawBox(p-v,h-v,p+v,d+v,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":331,\"gl-buffer\":259,\"gl-shader\":335}],334:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=e[0],a=e[1],o=n(t,r,a,{}),s=i.mallocUint8(r*a*4);return new l(t,o,s)};var n=t(\"gl-fbo\"),i=t(\"typedarray-pool\"),a=t(\"ndarray\"),o=t(\"bit-twiddle\").nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function 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a=[t.id,e.id,r.join(\":\"),i.join(\":\")].join(\"@\"),o=this.programs[a];return o&&this.gl.isProgram(o)||(this.programs[a]=o=function(t,e,r,i,a){var o=t.createProgram();t.attachShader(o,e),t.attachShader(o,r);for(var s=0;s<i.length;++s)t.bindAttribLocation(o,a[s],i[s]);if(t.linkProgram(o),!t.getProgramParameter(o,t.LINK_STATUS)){var l=t.getProgramInfoLog(o);throw new n(l,\"Error linking program: \"+l)}return o}(this.gl,t.shader,e.shader,r,i),t.programs.push(a),e.programs.push(a)),o}},{\"./GLError\":336,\"gl-format-compiler-error\":270,\"weakmap-shim\":605}],342:[function(t,e,r){\"use strict\";function n(t){this.plot=t,this.enable=[!0,!0,!1,!1],this.width=[1,1,1,1],this.color=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.center=[1/0,1/0]}e.exports=function(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r};var i=n.prototype;i.update=function(t){t=t||{},this.enable=(t.enable||[!0,!0,!1,!1]).slice(),this.width=(t.width||[1,1,1,1]).slice(),this.color=(t.color||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]).map((function(t){return t.slice()})),this.center=(t.center||[1/0,1/0]).slice(),this.plot.setOverlayDirty()},i.draw=function(){var t=this.enable,e=this.width,r=this.color,n=this.center,i=this.plot,a=i.line,o=i.dataBox,s=i.viewBox;if(a.bind(),o[0]<=n[0]&&n[0]<=o[2]&&o[1]<=n[1]&&n[1]<=o[3]){var l=s[0]+(n[0]-o[0])/(o[2]-o[0])*(s[2]-s[0]),c=s[1]+(n[1]-o[1])/(o[3]-o[1])*(s[3]-s[1]);t[0]&&a.drawLine(l,c,s[0],c,e[0],r[0]),t[1]&&a.drawLine(l,c,l,s[1],e[1],r[1]),t[2]&&a.drawLine(l,c,s[2],c,e[2],r[2]),t[3]&&a.drawLine(l,c,l,s[3],e[3],r[3])}},i.dispose=function(){this.plot.removeOverlay(this)}},{}],343:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],344:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, color;\\nattribute float weight;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 coordinates[3];\\nuniform vec4 colors[3];\\nuniform vec2 screenShape;\\nuniform float lineWidth;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vertexPosition = mix(coordinates[0],\\n    mix(coordinates[2], coordinates[1], 0.5 * (position + 1.0)), abs(position));\\n\\n  vec4 clipPos = projection * view * model * vec4(vertexPosition, 1.0);\\n  vec2 clipOffset = (projection * view * model * vec4(color, 0.0)).xy;\\n  vec2 delta = weight * clipOffset * screenShape;\\n  vec2 lineOffset = normalize(vec2(delta.y, -delta.x)) / screenShape;\\n\\n  gl_Position   = vec4(clipPos.xy + clipPos.w * 0.5 * lineWidth * lineOffset, clipPos.z, clipPos.w);\\n  fragColor     = color.x * colors[0] + color.y * colors[1] + color.z * colors[2];\\n}\\n\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec3\"},{name:\"weight\",type:\"float\"}])}},{\"gl-shader\":335,glslify:343}],345:[function(t,e,r){\"use strict\";var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders/index\");e.exports=function(t,e){var r=[];function o(t,e,n,i,a,o){var s=[t,e,n,0,0,0,1];s[i+3]=1,s[i]=a,r.push.apply(r,s),s[6]=-1,r.push.apply(r,s),s[i]=o,r.push.apply(r,s),r.push.apply(r,s),s[6]=1,r.push.apply(r,s),s[i]=a,r.push.apply(r,s)}o(0,0,0,0,0,1),o(0,0,0,1,0,1),o(0,0,0,2,0,1),o(1,0,0,1,-1,1),o(1,0,0,2,-1,1),o(0,1,0,0,-1,1),o(0,1,0,2,-1,1),o(0,0,1,0,-1,1),o(0,0,1,1,-1,1);var l=n(t,r),c=i(t,[{type:t.FLOAT,buffer:l,size:3,offset:0,stride:28},{type:t.FLOAT,buffer:l,size:3,offset:12,stride:28},{type:t.FLOAT,buffer:l,size:1,offset:24,stride:28}]),u=a(t);u.attributes.position.location=0,u.attributes.color.location=1,u.attributes.weight.location=2;var f=new s(t,l,c,u);return f.update(e),f};var o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n,this.pixelRatio=1,this.bounds=[[-1e3,-1e3,-1e3],[1e3,1e3,1e3]],this.position=[0,0,0],this.lineWidth=[2,2,2],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.enabled=[!0,!0,!0],this.drawSides=[!0,!0,!0],this.axes=null}var l=s.prototype,c=[0,0,0],u=[0,0,0],f=[0,0];l.isTransparent=function(){return!1},l.drawTransparent=function(t){},l.draw=function(t){var e=this.gl,r=this.vao,n=this.shader;r.bind(),n.bind();var i,a=t.model||o,s=t.view||o,l=t.projection||o;this.axes&&(i=this.axes.lastCubeProps.axis);for(var h=c,p=u,d=0;d<3;++d)i&&i[d]<0?(h[d]=this.bounds[0][d],p[d]=this.bounds[1][d]):(h[d]=this.bounds[1][d],p[d]=this.bounds[0][d]);f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=s,n.uniforms.projection=l,n.uniforms.coordinates=[this.position,h,p],n.uniforms.colors=this.colors,n.uniforms.screenShape=f;for(d=0;d<3;++d)n.uniforms.lineWidth=this.lineWidth[d]*this.pixelRatio,this.enabled[d]&&(r.draw(e.TRIANGLES,6,6*d),this.drawSides[d]&&r.draw(e.TRIANGLES,12,18+12*d));r.unbind()},l.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":344,\"gl-buffer\":259,\"gl-vao\":358}],346:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * tubePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(tubePosition, 1.0);\\n  vec4 t_position  = view * tubePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = tubePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  gl_Position = projection * view * tubePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},{glslify:347}],347:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],348:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),i=t(\"gl-vec4\"),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,c=0;c<l.length;c++)o=Math.max(o,n.length(l[c]));var u=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,c=[],u=[],f=[],h=[],p=[],d=[],g=0,m=0,v=i.create(),y=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),m=n.length(_)/a,v=i.create(),n.copy(v,_),v[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;c.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(y,v,v,v,y,y),d.push(g,m,m,m,g,g);var M=c.length;u.push([M-6,M-5,M-4],[M-3,M-2,M-1])}var A=h;h=p,p=A;var S=y;y=v,v=S;var E=g;g=m,m=E}return{positions:c,cells:u,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<u.length;s++){var g=u[s],m=f.length;f=f.concat(g.positions),p=p.concat(g.vectors),d=d.concat(g.vertexIntensity);for(c=0;c<g.cells.length;c++){var v=g.cells[c],y=[];h.push(y);for(var x=0;x<v.length;x++)y.push(v[x]+m)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}},s=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},l=function(t,e,r){return t<e?e:t>r?r:t},c=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};e.exports=function(t,e){var r=t.startingPositions,i=t.maxLength||1e3,u=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||\"+x+y+z\",p={};-1!==h.indexOf(\"-x\")&&(p.reversedX=!0),-1!==h.indexOf(\"-y\")&&(p.reversedY=!0),-1!==h.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,o=t[0],c=t[1],u=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=s(a[0],o),g=s(a[1],c),m=s(a[2],u),v=d+1,y=g+1,x=m+1;if(d=l(d,0,f-1),v=l(v,0,f-1),g=l(g,0,h-1),y=l(y,0,h-1),m=l(m,0,p-1),x=l(x,0,p-1),d<0||g<0||m<0||v>f-1||y>h-1||x>p-1)return n.create();var b,_,w,T,k,M,A=a[0][d],S=a[0][v],E=a[1][g],C=a[1][y],L=a[2][m],I=(o-A)/(S-A),P=(c-E)/(C-E),z=(u-L)/(a[2][x]-L);switch(isFinite(I)||(I=.5),isFinite(P)||(P=.5),isFinite(z)||(z=.5),r.reversedX&&(d=f-1-d,v=f-1-v),r.reversedY&&(g=h-1-g,y=h-1-y),r.reversedZ&&(m=p-1-m,x=p-1-x),r.filled){case 5:k=m,M=x,w=g*p,T=y*p,b=d*p*h,_=v*p*h;break;case 4:k=m,M=x,b=d*p,_=v*p,w=g*p*f,T=y*p*f;break;case 3:w=g,T=y,k=m*h,M=x*h,b=d*h*p,_=v*h*p;break;case 2:w=g,T=y,b=d*h,_=v*h,k=m*h*f,M=x*h*f;break;case 1:b=d,_=v,k=m*f,M=x*f,w=g*f*p,T=y*f*p;break;default:b=d,_=v,w=g*f,T=y*f,k=m*f*h,M=x*f*h}var O=i[b+w+k],D=i[b+w+M],R=i[b+T+k],F=i[b+T+M],B=i[_+w+k],N=i[_+w+M],j=i[_+T+k],U=i[_+T+M],V=n.create(),q=n.create(),H=n.create(),G=n.create();n.lerp(V,O,B,I),n.lerp(q,D,N,I),n.lerp(H,R,j,I),n.lerp(G,F,U,I);var Y=n.create(),W=n.create();n.lerp(Y,V,H,P),n.lerp(W,q,G,P);var X=n.create();return n.lerp(X,Y,W,z),X}(e,t,p)},g=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},m=[],v=e[0][0],y=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<v||e>b||r<y||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/i,M=k*k,A=1,S=0,E=r.length;E>1&&(A=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,l=0;l<s;l++){var u=t[l],f=u[0],h=u[1],p=u[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=c(e),g=c(r),m=c(n),v=Math.min(d,g,m);return isFinite(v)?v:1}(r));for(var C=0;C<E;C++){var L=n.create();n.copy(L,r[C]);var I=[L],P=[],z=d(L),O=L;P.push(z);var D=[],R=g(L,z),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F),m.push({points:I,velocities:P,divergences:D});for(var B=0;B<100*i&&I.length<i&&T(L);){B++;var N=n.clone(z),j=n.squaredLength(N);if(0===j)break;if(j>M&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,L),z=d(N),n.squaredDistance(O,N)-M>-1e-4*M){I.push(N),O=N,P.push(z);R=g(N,z),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F)}L=N}}var U=o(m,t.colormap,S,A);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*u*A/S),U};var u=t(\"./lib/shaders\"),f=t(\"gl-cone3d\").createMesh;e.exports.createTubeMesh=function(t,e){return f(t,e,{shaders:u,traceType:\"streamtube\"})}},{\"./lib/shaders\":346,\"gl-cone3d\":260,\"gl-vec3\":377,\"gl-vec4\":413}],349:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 localCoordinate = vec3(uv.zw, f.x);\\n  worldCoordinate = objectOffset + localCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if (\\n    kill > 0.0 ||\\n    vColor.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n  ) discard;\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color \\u2014 in vertex or in fragment\\n  vec4 surfaceColor =\\n    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n    step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  worldCoordinate = objectOffset + dataCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z += zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f + objectOffset.z;\\n  kill = -1.0;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if ((kill > 0.0) ||\\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);r.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":335,glslify:350}],350:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],351:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=y(e),n=b(e),s=x(e),l=_(e),c=i(e),u=a(e,[{buffer:c,size:4,stride:40,offset:0},{buffer:c,size:3,stride:40,offset:16},{buffer:c,size:3,stride:40,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),g=o(e,1,256,e.RGBA,e.UNSIGNED_BYTE);g.minFilter=e.LINEAR,g.magFilter=e.LINEAR;var m=new A(e,[0,0],[[0,0,0],[0,0,0]],r,n,c,u,g,s,l,f,h,p,d,[0,0,0]),v={levels:[[],[],[]]};for(var w in t)v[w]=t[w];return v.colormap=v.colormap||\"jet\",m.update(v),m};var n=t(\"bit-twiddle\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"typedarray-pool\"),l=t(\"colormap\"),c=t(\"ndarray-ops\"),u=t(\"ndarray-pack\"),f=t(\"ndarray\"),h=t(\"surface-nets\"),p=t(\"gl-mat4/multiply\"),d=t(\"gl-mat4/invert\"),g=t(\"binary-search-bounds\"),m=t(\"ndarray-gradient\"),v=t(\"./lib/shaders\"),y=v.createShader,x=v.createContourShader,b=v.createPickShader,_=v.createPickContourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],T=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],k=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=k[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();function A(t,e,r,n,i,a,o,l,c,u,h,p,d,g,m){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=m,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=c,this._contourPickShader=u,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=g,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var S=A.prototype;S.genColormap=function(t,e){var r=!1,n=u([l({colormap:t,nshades:256,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return c.divseq(n,255),this.hasAlphaScale=r,n},S.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},S.isOpaque=function(){return!this.isTransparent()},S.pickSlots=1,S.setPickBase=function(t){this.pickId=t};var E=[0,0,0],C={showSurface:!1,showContour:!1,projections:[w.slice(),w.slice(),w.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function L(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||E,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=C.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var c=C.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)c[i][n]=t.clipBounds[i][n];c[0][r]=-1e8,c[1][r]=1e8}return C.showSurface=o,C.showContour=s,C}var I={model:w,view:w,projection:w,inverseModel:w.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},P=w.slice(),z=[1,0,0,0,1,0,0,0,1];function O(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=I;n.model=t.model||w,n.view=t.view||w,n.projection=t.projection||w,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=z,n.vertexColor=this.vertexColor;var s=P;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var c=s[12+i];for(o=0;o<3;++o)c+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=c/l}var u=L(n,this);if(u.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=u.projections[i],this._shader.uniforms.clipBounds=u.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=k[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=u.projections[i],f.uniforms.clipBounds=u.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=k[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var g=0;g<this.contourLevels[o].length;++g)g===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==g&&g-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][g]&&(f.uniforms.height=this.contourLevels[o][g],h.draw(r.LINES,this._contourCounts[o][g],this._contourOffsets[o][g]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=k[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=u.projections[o],f.uniforms.clipBounds=u.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}S.draw=function(t){return O.call(this,t,!1)},S.drawTransparent=function(t){return O.call(this,t,!0)};var D={model:w,view:w,projection:w,inverseModel:w,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function R(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function F(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function B(t){if(Array.isArray(t)){if(Array.isArray(t))return[F(t[0]),F(t[1]),F(t[2])];var e=F(t);return[e.slice(),e.slice(),e.slice()]}}S.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=D;r.model=t.model||w,r.view=t.view||w,r.projection=t.projection||w,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=z;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=L(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=k[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=k[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(s.uniforms.height=this.contourLevels[a][c],l.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}l.unbind()}},S.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var f=u?a:1-a,h=0;h<2;++h)for(var p=i+u,d=s+h,m=f*(h?l:1-l),v=0;v<3;++v)c[v]+=this._field[v].get(p,d)*m;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=g.le(this.contourLevels[x],c[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-c[x])>Math.abs(_-c[x])&&(y[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],v=0;v<3;++v)r.dataCoordinate[v]=this._field[v].get(r.index[0],r.index[1]);return r},S.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},S.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=R(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=R(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=R(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=B(t.contourColor)),\"contourProject\"in t&&(this.contourProject=R(t.contourProject,(function(t){return R(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=B(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=R(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=R(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var c=l[o];for(v=0;v<2;++v)if(c.shape[v]!==a[v])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],c)}}else if(t.ticks){var u=t.ticks;if(!Array.isArray(u)||2!==u.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=u[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var g=[0,0];g[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],g,0)}this._field[0].set(0,0,0);for(var v=0;v<a[0];++v)this._field[0].set(v+1,0,v);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),v=0;v<a[1];++v)this._field[1].set(0,v+1,v);this._field[1].set(0,a[1]+1,a[1]-1)}var y=this._field,x=f(s.mallocFloat(3*y[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)m(x.pick(o),y[o],\"mirror\");var b=f(s.mallocFloat(3*y[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(v=0;v<a[1]+2;++v){var _=x.get(0,o,v,0),w=x.get(0,o,v,1),k=x.get(1,o,v,0),M=x.get(1,o,v,1),A=x.get(2,o,v,0),S=x.get(2,o,v,1),E=k*S-M*A,C=A*w-S*_,L=_*M-w*k,I=Math.sqrt(E*E+C*C+L*L);I<1e-8?(I=Math.max(Math.abs(E),Math.abs(C),Math.abs(L)))<1e-8?(L=1,C=E=0,I=1):I=1/I:I=1/Math.sqrt(I),b.set(o,v,0,E*I),b.set(o,v,1,C*I),b.set(o,v,2,L*I)}s.free(x.data);var P=[1/0,1/0,1/0],z=[-1/0,-1/0,-1/0],O=1/0,D=-1/0,F=(a[0]-1)*(a[1]-1)*6,N=s.mallocFloat(n.nextPow2(10*F)),j=0,U=0;for(o=0;o<a[0]-1;++o)t:for(v=0;v<a[1]-1;++v){for(var V=0;V<2;++V)for(var q=0;q<2;++q)for(var H=0;H<3;++H){var G=this._field[H].get(1+o+V,1+v+q);if(isNaN(G)||!isFinite(G))continue t}for(H=0;H<6;++H){var Y=o+T[H][0],W=v+T[H][1],X=this._field[0].get(Y+1,W+1),Z=this._field[1].get(Y+1,W+1);G=this._field[2].get(Y+1,W+1),E=b.get(Y+1,W+1,0),C=b.get(Y+1,W+1,1),L=b.get(Y+1,W+1,2),t.intensity&&(J=t.intensity.get(Y,W));var J=t.intensity?t.intensity.get(Y,W):G+this.objectOffset[2];N[j++]=Y,N[j++]=W,N[j++]=X,N[j++]=Z,N[j++]=G,N[j++]=0,N[j++]=J,N[j++]=E,N[j++]=C,N[j++]=L,P[0]=Math.min(P[0],X+this.objectOffset[0]),P[1]=Math.min(P[1],Z+this.objectOffset[1]),P[2]=Math.min(P[2],G+this.objectOffset[2]),O=Math.min(O,J),z[0]=Math.max(z[0],X+this.objectOffset[0]),z[1]=Math.max(z[1],Z+this.objectOffset[1]),z[2]=Math.max(z[2],G+this.objectOffset[2]),D=Math.max(D,J),U+=1}}for(t.intensityBounds&&(O=+t.intensityBounds[0],D=+t.intensityBounds[1]),o=6;o<j;o+=10)N[o]=(N[o]-O)/(D-O);this._vertexCount=U,this._coordinateBuffer.update(N.subarray(0,j)),s.freeFloat(N),s.free(b.data),this.bounds=[P,z],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===O&&this.intensityBounds[1]===D||(r=!0),this.intensityBounds=[O,D]}if(\"levels\"in t){var K=t.levels;for(K=Array.isArray(K[0])?K.slice():[[],[],K],o=0;o<3;++o)K[o]=K[o].slice(),K[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(v=0;v<K[o].length;++v)K[o][v]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(K[o].length!==this.contourLevels[o].length){r=!0;break}for(v=0;v<K[o].length;++v)if(K[o][v]!==this.contourLevels[o][v]){r=!0;break t}}this.contourLevels=K}if(r){y=this._field,a=this.shape;for(var Q=[],$=0;$<3;++$){var tt=this.contourLevels[$],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[$],tt[o]);et.push(Q.length/5|0),U=0;t:for(v=0;v<it.cells.length;++v){var at=it.cells[v];for(H=0;H<2;++H){var ot=it.positions[at[H]],st=ot[0],lt=0|Math.floor(st),ct=st-lt,ut=ot[1],ft=0|Math.floor(ut),ht=ut-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var gt=($+dt+1)%3;for(V=0;V<2;++V){var mt=V?ct:1-ct;for(Y=0|Math.min(Math.max(lt+V,0),a[0]),q=0;q<2;++q){var vt=q?ht:1-ht;if(W=0|Math.min(Math.max(ft+q,0),a[1]),G=dt<2?this._field[gt].get(Y,W):(this.intensity.get(Y,W)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var yt=mt*vt;nt[dt]+=yt*G}}}if(pt){if(H>0){for(var xt=0;xt<5;++xt)Q.pop();U-=1}continue t}Q.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[$]=et,this._contourCounts[$]=rt}var bt=s.mallocFloat(Q.length);for(o=0;o<Q.length;++o)bt[o]=Q[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},S.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},S.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,c=(o+2)%3,u=this._field[o],f=this._field[l],p=this._field[c],d=h(u,r[o]),g=d.cells,m=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<g.length;++e)for(var v=g[e],y=0;y<2;++y){var x=m[v[y]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,M=+x[1],A=0|M,S=0|Math.min(A+1,i[1]),E=M-A,C=1-E,L=k*C,I=k*E,P=T*C,z=T*E,O=L*f.get(_,A)+I*f.get(_,S)+P*f.get(w,A)+z*f.get(w,S),D=L*p.get(_,A)+I*p.get(_,S)+P*p.get(w,A)+z*p.get(w,S);if(isNaN(O)||isNaN(D)){y&&(n-=1);break}a[2*n+0]=O,a[2*n+1]=D,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},{\"./lib/shaders\":349,\"binary-search-bounds\":96,\"bit-twiddle\":97,colormap:131,\"gl-buffer\":259,\"gl-mat4/invert\":293,\"gl-mat4/multiply\":295,\"gl-texture2d\":353,\"gl-vao\":358,ndarray:495,\"ndarray-gradient\":488,\"ndarray-ops\":490,\"ndarray-pack\":491,\"surface-nets\":570,\"typedarray-pool\":595}],352:[function(t,e,r){\"use strict\";var n=t(\"css-font\"),i=t(\"pick-by-alias\"),a=t(\"regl\"),o=t(\"gl-util/context\"),s=t(\"es6-weak-map\"),l=t(\"color-normalize\"),c=t(\"font-atlas\"),u=t(\"typedarray-pool\"),f=t(\"parse-rect\"),h=t(\"is-plain-obj\"),p=t(\"parse-unit\"),d=t(\"to-px\"),g=t(\"detect-kerning\"),m=t(\"object-assign\"),v=t(\"font-measure\"),y=t(\"flatten-vertex-data\"),x=t(\"bit-twiddle\").nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement(\"div\"));w.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var T=function(t){!function(t){return\"function\"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},stencil:{enable:!1},depth:{enable:!1},count:t.prop(\"count\"),offset:t.prop(\"offset\"),attributes:{charOffset:{offset:4,stride:8,buffer:t.this(\"sizeBuffer\")},width:{offset:0,stride:8,buffer:t.this(\"sizeBuffer\")},char:t.this(\"charBuffer\"),position:t.this(\"position\")},uniforms:{atlasSize:function(t,e){return[e.atlas.width,e.atlas.height]},atlasDim:function(t,e){return[e.atlas.cols,e.atlas.rows]},atlas:function(t,e){return e.atlas.texture},charStep:function(t,e){return e.atlas.step},em:function(t,e){return e.atlas.em},color:t.prop(\"color\"),opacity:t.prop(\"opacity\"),viewport:t.this(\"viewportArray\"),scale:t.this(\"scale\"),align:t.prop(\"align\"),baseline:t.prop(\"baseline\"),translate:t.this(\"translate\"),positionOffset:t.prop(\"positionOffset\")},primitive:\"points\",viewport:t.this(\"viewport\"),vert:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tattribute float width, charOffset, char;\\n\\t\\t\\tattribute vec2 position;\\n\\t\\t\\tuniform float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\t\"+(T.normalViewport?\"\":\"vec2 positionOffset = vec2(positionOffset.x,- positionOffset.y);\")+\"\\n\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ positionOffset))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\t\"+(T.normalViewport?\"position.y = 1. - position.y;\":\"\")+\"\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 255.;\\n\\t\\t\\t}\",frag:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tuniform sampler2D atlas;\\n\\t\\t\\tuniform float fontSize, charStep, opacity;\\n\\t\\t\\tuniform vec2 atlasSize;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\n\\t\\t\\tfloat lightness(vec4 color) {\\n\\t\\t\\t\\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\\n\\t\\t\\t\\tfloat halfCharStep = floor(charStep * .5 + .5);\\n\\n\\t\\t\\t\\t// invert y and shift by 1px (FF expecially needs that)\\n\\t\\t\\t\\tuv.y = charStep - uv.y;\\n\\n\\t\\t\\t\\t// ignore points outside of character bounding box\\n\\t\\t\\t\\tfloat halfCharWidth = ceil(charWidth * .5);\\n\\t\\t\\t\\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\\n\\t\\t\\t\\t\\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map((function(t){return parseFloat(t)})):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=f(t.viewport),T.normalViewport&&(this.viewport.y=this.canvas.height-this.viewport.y-this.viewport.height),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&(\"number\"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=y(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var c=t.family.join(\", \"),u=[t.style];t.style!=t.variant&&u.push(t.variant),t.variant!=t.weight&&u.push(t.weight),_&&t.weight!=t.stretch&&u.push(t.stretch),e.font[r]={baseString:i,family:c,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:v(c,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:u.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h<s.length;h++)s[h]=t.text;t.text=s}if(null!=t.text||a){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach((function(t,n){T.atlasContext.font=t.baseString;for(var i=e.fontAtlas[n],a=0;a<e.text.length;a++){var o=e.text.charAt(a);if(null==i.ids[o]&&(i.ids[o]=i.chars.length,i.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=T.atlasContext.measureText(o).width/T.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);m(t.kerning,g(t.family,{pairs:s}))}}}))}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,k=u.mallocFloat(2*this.count),M=0,A=0;M<this.counts.length;M++){var S=this.counts[M];if(w)for(var E=0;E<S;E++)k[A++]=t.position[2*M],k[A++]=t.position[2*M+1];else for(var C=0;C<S;C++)k[A++]=t.position[M][0],k[A++]=t.position[M][1]}this.position.call?this.position({type:\"float\",data:k}):this.position=this.regl.buffer({type:\"float\",data:k}),u.freeFloat(k)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||a){var L=u.mallocUint8(this.count),I=u.mallocFloat(2*this.count);this.textWidth=[];for(var P=0,z=0;P<this.counts.length;P++){for(var O=this.counts[P],D=this.font[P]||this.font[0],R=this.fontAtlas[P]||this.fontAtlas[0],F=0;F<O;F++){var B=this.text.charAt(z),N=this.text.charAt(z-1);if(L[z]=R.ids[B],I[2*z]=D.width[B],F){var j=I[2*z-2],U=I[2*z],V=I[2*z-1]+.5*j+.5*U;if(this.kerning){var q=D.kerning[N+B];q&&(V+=.001*q)}I[2*z+1]=V}else I[2*z+1]=.5*I[2*z];z++}this.textWidth.push(I.length?.5*I[2*z-2]+I[2*z-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:L,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:I,type:\"float\",usage:\"stream\"}),u.freeUint8(L),u.freeFloat(I),r.length&&this.font.forEach((function(t,r){var n=e.fontAtlas[r],i=n.step,a=Math.floor(T.maxAtlasSize/i),o=Math.min(a,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*i),u=x(s*i);n.width=l,n.height=u,n.rows=s,n.cols=o,n.em&&n.texture({data:c({canvas:T.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,u],step:[i,i]})})}))}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map((function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,i+=\"number\"==typeof t?t-n.baseline:-n[t],T.normalViewport||(i*=-1),i}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var H;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;H=u.mallocUint8(G);for(var Y=(t.color.subarray||t.color.slice).bind(t.color),W=0;W<G;W+=4)H.set(l(Y(W,W+4),\"uint8\"),W)}else{var X=t.color.length;H=u.mallocUint8(4*X);for(var Z=0;Z<X;Z++)H.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=H}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K<this.batch.length;K++)this.batch[K]={count:this.counts.length>1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.normalViewport=!1,T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},e.exports=T},{\"bit-twiddle\":97,\"color-normalize\":125,\"css-font\":144,\"detect-kerning\":172,\"es6-weak-map\":233,\"flatten-vertex-data\":244,\"font-atlas\":245,\"font-measure\":246,\"gl-util/context\":354,\"is-plain-obj\":469,\"object-assign\":499,\"parse-rect\":504,\"parse-unit\":506,\"pick-by-alias\":511,regl:540,\"to-px\":578,\"typedarray-pool\":595}],353:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"ndarray-ops\"),a=t(\"typedarray-pool\");e.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");o||c(t);if(\"number\"==typeof arguments[1])return v(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return v(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return y(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return x(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function c(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var f=function(t,e){i.muls(t,e,255)};function h(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function p(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var d=p.prototype;function g(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function m(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function v(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=m(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new p(t,o,e,r,n,i)}function y(t,e,r,n,i,a){var o=m(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new p(t,o,r,n,i,a)}function x(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=g(o,e.stride.slice()),c=0;\"float32\"===r?c=t.FLOAT:\"float64\"===r?(c=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?c=t.UNSIGNED_BYTE:(c=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var u,h,d=0;if(2===o.length)d=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])d=t.ALPHA;else if(2===o[2])d=t.LUMINANCE_ALPHA;else if(3===o[2])d=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");d=t.RGBA}}c!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(c=t.UNSIGNED_BYTE,l=!1);var v=e.size;if(l)u=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var y=[o[2],o[2]*o[0],1];h=a.malloc(v,r);var 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strict\";e.exports=function(t,e){var r=t.length;if(0===r)throw new Error(\"Must have at least d+1 points\");var i=t[0].length;if(r<=i)throw new Error(\"Must input at least d+1 points\");var o=t.slice(0,i+1),s=n.apply(void 0,o);if(0===s)throw new Error(\"Input not in general position\");for(var l=new Array(i+1),u=0;u<=i;++u)l[u]=u;s<0&&(l[0]=1,l[1]=0);var f=new a(l,new Array(i+1),!1),h=f.adjacent,p=new Array(i+2);for(u=0;u<=i;++u){for(var d=l.slice(),g=0;g<=i;++g)g===u&&(d[g]=-1);var m=d[0];d[0]=d[1],d[1]=m;var v=new a(d,new Array(i+1),!0);h[u]=v,p[u]=v}p[i+1]=f;for(u=0;u<=i;++u){d=h[u].vertices;var y=h[u].adjacent;for(g=0;g<=i;++g){var x=d[g];if(x<0)y[g]=f;else for(var b=0;b<=i;++b)h[b].vertices.indexOf(x)<0&&(y[g]=h[b])}}var _=new c(i,o,p),w=!!e;for(u=i+1;u<r;++u)_.insert(t[u],w);return _.boundary()};var n=t(\"robust-orientation\"),i=t(\"simplicial-complex\").compareCells;function a(t,e,r){this.vertices=t,this.adjacent=e,this.boundary=r,this.lastVisited=-1}function o(t,e,r){this.vertices=t,this.cell=e,this.index=r}function s(t,e){return i(t.vertices,e.vertices)}a.prototype.flip=function(){var t=this.vertices[0];this.vertices[0]=this.vertices[1],this.vertices[1]=t;var e=this.adjacent[0];this.adjacent[0]=this.adjacent[1],this.adjacent[1]=e};var l=[];function c(t,e,r){this.dimension=t,this.vertices=e,this.simplices=r,this.interior=r.filter((function(t){return!t.boundary})),this.tuple=new Array(t+1);for(var i=0;i<=t;++i)this.tuple[i]=this.vertices[i];var a=l[t];a||(a=l[t]=function(t){for(var e=[\"function orient(){var tuple=this.tuple;return test(\"],r=0;r<=t;++r)r>0&&e.push(\",\"),e.push(\"tuple[\",r,\"]\");e.push(\")}return orient\");var i=new Function(\"test\",e.join(\"\")),a=n[t+1];return a||(a=n),i(a)}(t)),this.orient=a}var u=c.prototype;u.handleBoundaryDegeneracy=function(t,e){var r=this.dimension,n=this.vertices.length-1,i=this.tuple,a=this.vertices,o=[t];for(t.lastVisited=-n;o.length>0;){(t=o.pop()).vertices;for(var s=t.adjacent,l=0;l<=r;++l){var c=s[l];if(c.boundary&&!(c.lastVisited<=-n)){for(var u=c.vertices,f=0;f<=r;++f){var h=u[f];i[f]=h<0?e:a[h]}var p=this.orient();if(p>0)return c;c.lastVisited=-n,0===p&&o.push(c)}}}return null},u.walk=function(t,e){var r=this.vertices.length-1,n=this.dimension,i=this.vertices,a=this.tuple,o=e?this.interior.length*Math.random()|0:this.interior.length-1,s=this.interior[o];t:for(;!s.boundary;){for(var l=s.vertices,c=s.adjacent,u=0;u<=n;++u)a[u]=i[l[u]];s.lastVisited=r;for(u=0;u<=n;++u){var f=c[u];if(!(f.lastVisited>=r)){var h=a[u];a[u]=t;var p=this.orient();if(a[u]=h,p<0){s=f;continue t}f.boundary?f.lastVisited=-r:f.lastVisited=r}}return}return s},u.addPeaks=function(t,e){var r=this.vertices.length-1,n=this.dimension,i=this.vertices,l=this.tuple,c=this.interior,u=this.simplices,f=[e];e.lastVisited=r,e.vertices[e.vertices.indexOf(-1)]=r,e.boundary=!1,c.push(e);for(var h=[];f.length>0;){var p=(e=f.pop()).vertices,d=e.adjacent,g=p.indexOf(r);if(!(g<0))for(var m=0;m<=n;++m)if(m!==g){var v=d[m];if(v.boundary&&!(v.lastVisited>=r)){var y=v.vertices;if(v.lastVisited!==-r){for(var x=0,b=0;b<=n;++b)y[b]<0?(x=b,l[b]=t):l[b]=i[y[b]];if(this.orient()>0){y[x]=r,v.boundary=!1,c.push(v),f.push(v),v.lastVisited=r;continue}v.lastVisited=-r}var _=v.adjacent,w=p.slice(),T=d.slice(),k=new a(w,T,!0);u.push(k);var M=_.indexOf(e);if(!(M<0)){_[M]=k,T[g]=v,w[m]=-1,T[m]=e,d[m]=k,k.flip();for(b=0;b<=n;++b){var A=w[b];if(!(A<0||A===r)){for(var S=new Array(n-1),E=0,C=0;C<=n;++C){var L=w[C];L<0||C===b||(S[E++]=L)}h.push(new o(S,k,b))}}}}}}h.sort(s);for(m=0;m+1<h.length;m+=2){var I=h[m],P=h[m+1],z=I.index,O=P.index;z<0||O<0||(I.cell.adjacent[I.index]=P.cell,P.cell.adjacent[P.index]=I.cell)}},u.insert=function(t,e){var r=this.vertices;r.push(t);var n=this.walk(t,e);if(n){for(var i=this.dimension,a=this.tuple,o=0;o<=i;++o){var s=n.vertices[o];a[o]=s<0?t:r[s]}var l=this.orient(a);l<0||(0!==l||(n=this.handleBoundaryDegeneracy(n,t)))&&this.addPeaks(t,n)}},u.boundary=function(){for(var t=this.dimension,e=[],r=this.simplices,n=r.length,i=0;i<n;++i){var a=r[i];if(a.boundary){for(var o=new Array(t),s=a.vertices,l=0,c=0,u=0;u<=t;++u)s[u]>=0?o[l++]=s[u]:c=1&u;if(c===(1&t)){var f=o[0];o[0]=o[1],o[1]=f}e.push(o)}}return e}},{\"robust-orientation\":548,\"simplicial-complex\":558}],460:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\");function i(t,e,r,n,i){this.mid=t,this.left=e,this.right=r,this.leftPoints=n,this.rightPoints=i,this.count=(e?e.count:0)+(r?r.count:0)+n.length}e.exports=function(t){if(!t||0===t.length)return new v(null);return new v(m(t))};var a=i.prototype;function o(t,e){t.mid=e.mid,t.left=e.left,t.right=e.right,t.leftPoints=e.leftPoints,t.rightPoints=e.rightPoints,t.count=e.count}function s(t,e){var r=m(e);t.mid=r.mid,t.left=r.left,t.right=r.right,t.leftPoints=r.leftPoints,t.rightPoints=r.rightPoints,t.count=r.count}function l(t,e){var r=t.intervals([]);r.push(e),s(t,r)}function c(t,e){var r=t.intervals([]),n=r.indexOf(e);return n<0?0:(r.splice(n,1),s(t,r),1)}function u(t,e,r){for(var n=0;n<t.length&&t[n][0]<=e;++n){var i=r(t[n]);if(i)return i}}function f(t,e,r){for(var n=t.length-1;n>=0&&t[n][1]>=e;--n){var i=r(t[n]);if(i)return i}}function h(t,e){for(var r=0;r<t.length;++r){var n=e(t[r]);if(n)return n}}function p(t,e){return t-e}function d(t,e){var r=t[0]-e[0];return r||t[1]-e[1]}function g(t,e){var r=t[1]-e[1];return r||t[0]-e[0]}function m(t){if(0===t.length)return null;for(var e=[],r=0;r<t.length;++r)e.push(t[r][0],t[r][1]);e.sort(p);var n=e[e.length>>1],a=[],o=[],s=[];for(r=0;r<t.length;++r){var l=t[r];l[1]<n?a.push(l):n<l[0]?o.push(l):s.push(l)}var c=s,u=s.slice();return c.sort(d),u.sort(g),new i(n,m(a),m(o),c,u)}function v(t){this.root=t}a.intervals=function(t){return t.push.apply(t,this.leftPoints),this.left&&this.left.intervals(t),this.right&&this.right.intervals(t),t},a.insert=function(t){var e=this.count-this.leftPoints.length;if(this.count+=1,t[1]<this.mid)this.left?4*(this.left.count+1)>3*(e+1)?l(this,t):this.left.insert(t):this.left=m([t]);else if(t[0]>this.mid)this.right?4*(this.right.count+1)>3*(e+1)?l(this,t):this.right.insert(t):this.right=m([t]);else{var r=n.ge(this.leftPoints,t,d),i=n.ge(this.rightPoints,t,g);this.leftPoints.splice(r,0,t),this.rightPoints.splice(i,0,t)}},a.remove=function(t){var e=this.count-this.leftPoints;if(t[1]<this.mid)return this.left?4*(this.right?this.right.count:0)>3*(e-1)?c(this,t):2===(s=this.left.remove(t))?(this.left=null,this.count-=1,1):(1===s&&(this.count-=1),s):0;if(t[0]>this.mid)return this.right?4*(this.left?this.left.count:0)>3*(e-1)?c(this,t):2===(s=this.right.remove(t))?(this.right=null,this.count-=1,1):(1===s&&(this.count-=1),s):0;if(1===this.count)return this.leftPoints[0]===t?2:0;if(1===this.leftPoints.length&&this.leftPoints[0]===t){if(this.left&&this.right){for(var r=this,i=this.left;i.right;)r=i,i=i.right;if(r===this)i.right=this.right;else{var a=this.left,s=this.right;r.count-=i.count,r.right=i.left,i.left=a,i.right=s}o(this,i),this.count=(this.left?this.left.count:0)+(this.right?this.right.count:0)+this.leftPoints.length}else this.left?o(this,this.left):o(this,this.right);return 1}for(a=n.ge(this.leftPoints,t,d);a<this.leftPoints.length&&this.leftPoints[a][0]===t[0];++a)if(this.leftPoints[a]===t){this.count-=1,this.leftPoints.splice(a,1);for(s=n.ge(this.rightPoints,t,g);s<this.rightPoints.length&&this.rightPoints[s][1]===t[1];++s)if(this.rightPoints[s]===t)return this.rightPoints.splice(s,1),1}return 0},a.queryPoint=function(t,e){if(t<this.mid){if(this.left)if(r=this.left.queryPoint(t,e))return r;return u(this.leftPoints,t,e)}if(t>this.mid){var r;if(this.right)if(r=this.right.queryPoint(t,e))return r;return f(this.rightPoints,t,e)}return h(this.leftPoints,e)},a.queryInterval=function(t,e,r){var n;if(t<this.mid&&this.left&&(n=this.left.queryInterval(t,e,r)))return n;if(e>this.mid&&this.right&&(n=this.right.queryInterval(t,e,r)))return n;return e<this.mid?u(this.leftPoints,e,r):t>this.mid?f(this.rightPoints,t,r):h(this.leftPoints,r)};var y=v.prototype;y.insert=function(t){this.root?this.root.insert(t):this.root=new i(t[0],null,null,[t],[t])},y.remove=function(t){if(this.root){var e=this.root.remove(t);return 2===e&&(this.root=null),0!==e}return!1},y.queryPoint=function(t,e){if(this.root)return this.root.queryPoint(t,e)},y.queryInterval=function(t,e,r){if(t<=e&&this.root)return this.root.queryInterval(t,e,r)},Object.defineProperty(y,\"count\",{get:function(){return this.root?this.root.count:0}}),Object.defineProperty(y,\"intervals\",{get:function(){return this.root?this.root.intervals([]):[]}})},{\"binary-search-bounds\":461}],461:[function(t,e,r){arguments[4][243][0].apply(r,arguments)},{dup:243}],462:[function(t,e,r){\"use strict\";e.exports=function(t,e){e=e||new Array(t.length);for(var r=0;r<t.length;++r)e[t[r]]=r;return e}},{}],463:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=new Array(t),r=0;r<t;++r)e[r]=r;return e}},{}],464:[function(t,e,r){e.exports=!0},{}],465:[function(t,e,r){function n(t){return!!t.constructor&&\"function\"==typeof t.constructor.isBuffer&&t.constructor.isBuffer(t)}\n",
       "/*!\n",
       " * Determine if an object is a Buffer\n",
       " *\n",
       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
       " * @license  MIT\n",
       " */\n",
       "e.exports=function(t){return null!=t&&(n(t)||function(t){return\"function\"==typeof t.readFloatLE&&\"function\"==typeof t.slice&&n(t.slice(0,0))}(t)||!!t._isBuffer)}},{}],466:[function(t,e,r){\"use strict\";e.exports=\"undefined\"!=typeof navigator&&(/MSIE/.test(navigator.userAgent)||/Trident\\//.test(navigator.appVersion))},{}],467:[function(t,e,r){\"use strict\";e.exports=a,e.exports.isMobile=a,e.exports.default=a;var n=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i,i=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino|android|ipad|playbook|silk/i;function a(t){t||(t={});var e=t.ua;if(e||\"undefined\"==typeof navigator||(e=navigator.userAgent),e&&e.headers&&\"string\"==typeof e.headers[\"user-agent\"]&&(e=e.headers[\"user-agent\"]),\"string\"!=typeof e)return!1;var r=t.tablet?i.test(e):n.test(e);return!r&&t.tablet&&t.featureDetect&&navigator&&navigator.maxTouchPoints>1&&-1!==e.indexOf(\"Macintosh\")&&-1!==e.indexOf(\"Safari\")&&(r=!0),r}},{}],468:[function(t,e,r){\"use strict\";e.exports=function(t){var e=typeof t;return null!==t&&(\"object\"===e||\"function\"===e)}},{}],469:[function(t,e,r){\"use strict\";var n=Object.prototype.toString;e.exports=function(t){var e;return\"[object Object]\"===n.call(t)&&(null===(e=Object.getPrototypeOf(t))||e===Object.getPrototypeOf({}))}},{}],470:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e,r=t.length,n=0;n<r;n++)if(((e=t.charCodeAt(n))<9||e>13)&&32!==e&&133!==e&&160!==e&&5760!==e&&6158!==e&&(e<8192||e>8205)&&8232!==e&&8233!==e&&8239!==e&&8287!==e&&8288!==e&&12288!==e&&65279!==e)return!1;return!0}},{}],471:[function(t,e,r){\"use strict\";e.exports=function(t){return\"string\"==typeof t&&(t=t.trim(),!!(/^[mzlhvcsqta]\\s*[-+.0-9][^mlhvzcsqta]+/i.test(t)&&/[\\dz]$/i.test(t)&&t.length>4))}},{}],472:[function(t,e,r){e.exports=function(t,e,r){return t*(1-r)+e*r}},{}],473:[function(t,e,r){!function(t,n){\"object\"==typeof r&&\"undefined\"!=typeof e?e.exports=n():(t=t||self).mapboxgl=n()}(this,(function(){\"use strict\";var t,e,r;function n(n,i){if(t)if(e){var a=\"var sharedChunk = {}; (\"+t+\")(sharedChunk); (\"+e+\")(sharedChunk);\",o={};t(o),(r=i(o)).workerUrl=window.URL.createObjectURL(new Blob([a],{type:\"text/javascript\"}))}else e=i;else t=i}return n(0,(function(t){function e(t,e){return t(e={exports:{}},e.exports),e.exports}var r=n;function n(t,e,r,n){this.cx=3*t,this.bx=3*(r-t)-this.cx,this.ax=1-this.cx-this.bx,this.cy=3*e,this.by=3*(n-e)-this.cy,this.ay=1-this.cy-this.by,this.p1x=t,this.p1y=n,this.p2x=r,this.p2y=n}n.prototype.sampleCurveX=function(t){return((this.ax*t+this.bx)*t+this.cx)*t},n.prototype.sampleCurveY=function(t){return((this.ay*t+this.by)*t+this.cy)*t},n.prototype.sampleCurveDerivativeX=function(t){return(3*this.ax*t+2*this.bx)*t+this.cx},n.prototype.solveCurveX=function(t,e){var r,n,i,a,o;for(void 0===e&&(e=1e-6),i=t,o=0;o<8;o++){if(a=this.sampleCurveX(i)-t,Math.abs(a)<e)return i;var s=this.sampleCurveDerivativeX(i);if(Math.abs(s)<1e-6)break;i-=a/s}if((i=t)<(r=0))return r;if(i>(n=1))return n;for(;r<n;){if(a=this.sampleCurveX(i),Math.abs(a-t)<e)return i;t>a?r=i:n=i,i=.5*(n-r)+r}return i},n.prototype.solve=function(t,e){return this.sampleCurveY(this.solveCurveX(t,e))};var i=a;function a(t,e){this.x=t,this.y=e}function o(t,e,n,i){var a=new r(t,e,n,i);return function(t){return 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r={transparent:[0,0,0,0],aliceblue:[240,248,255,1],antiquewhite:[250,235,215,1],aqua:[0,255,255,1],aquamarine:[127,255,212,1],azure:[240,255,255,1],beige:[245,245,220,1],bisque:[255,228,196,1],black:[0,0,0,1],blanchedalmond:[255,235,205,1],blue:[0,0,255,1],blueviolet:[138,43,226,1],brown:[165,42,42,1],burlywood:[222,184,135,1],cadetblue:[95,158,160,1],chartreuse:[127,255,0,1],chocolate:[210,105,30,1],coral:[255,127,80,1],cornflowerblue:[100,149,237,1],cornsilk:[255,248,220,1],crimson:[220,20,60,1],cyan:[0,255,255,1],darkblue:[0,0,139,1],darkcyan:[0,139,139,1],darkgoldenrod:[184,134,11,1],darkgray:[169,169,169,1],darkgreen:[0,100,0,1],darkgrey:[169,169,169,1],darkkhaki:[189,183,107,1],darkmagenta:[139,0,139,1],darkolivegreen:[85,107,47,1],darkorange:[255,140,0,1],darkorchid:[153,50,204,1],darkred:[139,0,0,1],darksalmon:[233,150,122,1],darkseagreen:[143,188,143,1],darkslateblue:[72,61,139,1],darkslategray:[47,79,79,1],darkslategrey:[47,79,79,1],darkturquoise:[0,206,209,1],darkviolet:[148,0,211,1],deeppink:[255,20,147,1],deepskyblue:[0,191,255,1],dimgray:[105,105,105,1],dimgrey:[105,105,105,1],dodgerblue:[30,144,255,1],firebrick:[178,34,34,1],floralwhite:[255,250,240,1],forestgreen:[34,139,34,1],fuchsia:[255,0,255,1],gainsboro:[220,220,220,1],ghostwhite:[248,248,255,1],gold:[255,215,0,1],goldenrod:[218,165,32,1],gray:[128,128,128,1],green:[0,128,0,1],greenyellow:[173,255,47,1],grey:[128,128,128,1],honeydew:[240,255,240,1],hotpink:[255,105,180,1],indianred:[205,92,92,1],indigo:[75,0,130,1],ivory:[255,255,240,1],khaki:[240,230,140,1],lavender:[230,230,250,1],lavenderblush:[255,240,245,1],lawngreen:[124,252,0,1],lemonchiffon:[255,250,205,1],lightblue:[173,216,230,1],lightcoral:[240,128,128,1],lightcyan:[224,255,255,1],lightgoldenrodyellow:[250,250,210,1],lightgray:[211,211,211,1],lightgreen:[144,238,144,1],lightgrey:[211,211,211,1],lightpink:[255,182,193,1],lightsalmon:[255,160,122,1],lightseagreen:[32,178,170,1],lightskyblue:[135,206,250,1],lightslategray:[119,136,153,1],lightslategrey:[119,136,153,1],lightsteelblue:[176,196,222,1],lightyellow:[255,255,224,1],lime:[0,255,0,1],limegreen:[50,205,50,1],linen:[250,240,230,1],magenta:[255,0,255,1],maroon:[128,0,0,1],mediumaquamarine:[102,205,170,1],mediumblue:[0,0,205,1],mediumorchid:[186,85,211,1],mediumpurple:[147,112,219,1],mediumseagreen:[60,179,113,1],mediumslateblue:[123,104,238,1],mediumspringgreen:[0,250,154,1],mediumturquoise:[72,209,204,1],mediumvioletred:[199,21,133,1],midnightblue:[25,25,112,1],mintcream:[245,255,250,1],mistyrose:[255,228,225,1],moccasin:[255,228,181,1],navajowhite:[255,222,173,1],navy:[0,0,128,1],oldlace:[253,245,230,1],olive:[128,128,0,1],olivedrab:[107,142,35,1],orange:[255,165,0,1],orangered:[255,69,0,1],orchid:[218,112,214,1],palegoldenrod:[238,232,170,1],palegreen:[152,251,152,1],paleturquoise:[175,238,238,1],palevioletred:[219,112,147,1],papayawhip:[255,239,213,1],peachpuff:[255,218,185,1],peru:[205,133,63,1],pink:[255,192,203,1],plum:[221,160,221,1],powderblue:[176,224,230,1],purple:[128,0,128,1],rebeccapurple:[102,51,153,1],red:[255,0,0,1],rosybrown:[188,143,143,1],royalblue:[65,105,225,1],saddlebrown:[139,69,19,1],salmon:[250,128,114,1],sandybrown:[244,164,96,1],seagreen:[46,139,87,1],seashell:[255,245,238,1],sienna:[160,82,45,1],silver:[192,192,192,1],skyblue:[135,206,235,1],slateblue:[106,90,205,1],slategray:[112,128,144,1],slategrey:[112,128,144,1],snow:[255,250,250,1],springgreen:[0,255,127,1],steelblue:[70,130,180,1],tan:[210,180,140,1],teal:[0,128,128,1],thistle:[216,191,216,1],tomato:[255,99,71,1],turquoise:[64,224,208,1],violet:[238,130,238,1],wheat:[245,222,179,1],white:[255,255,255,1],whitesmoke:[245,245,245,1],yellow:[255,255,0,1],yellowgreen:[154,205,50,1]};function n(t){return(t=Math.round(t))<0?0:t>255?255:t}function i(t){return n(\"%\"===t[t.length-1]?parseFloat(t)/100*255:parseInt(t))}function a(t){return(e=\"%\"===t[t.length-1]?parseFloat(t)/100:parseFloat(t))<0?0:e>1?1:e;var e}function o(t,e,r){return r<0?r+=1:r>1&&(r-=1),6*r<1?t+(e-t)*r*6:2*r<1?e:3*r<2?t+(e-t)*(2/3-r)*6:t}try{e.parseCSSColor=function(t){var e,s=t.replace(/ /g,\"\").toLowerCase();if(s in r)return r[s].slice();if(\"#\"===s[0])return 4===s.length?(e=parseInt(s.substr(1),16))>=0&&e<=4095?[(3840&e)>>4|(3840&e)>>8,240&e|(240&e)>>4,15&e|(15&e)<<4,1]:null:7===s.length&&(e=parseInt(s.substr(1),16))>=0&&e<=16777215?[(16711680&e)>>16,(65280&e)>>8,255&e,1]:null;var l=s.indexOf(\"(\"),c=s.indexOf(\")\");if(-1!==l&&c+1===s.length){var u=s.substr(0,l),f=s.substr(l+1,c-(l+1)).split(\",\"),h=1;switch(u){case\"rgba\":if(4!==f.length)return null;h=a(f.pop());case\"rgb\":return 3!==f.length?null:[i(f[0]),i(f[1]),i(f[2]),h];case\"hsla\":if(4!==f.length)return 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Qt=function(t,e,r){this.sensitivity=t?e?\"variant\":\"case\":e?\"accent\":\"base\",this.locale=r,this.collator=new Intl.Collator(this.locale?this.locale:[],{sensitivity:this.sensitivity,usage:\"search\"})};Qt.prototype.compare=function(t,e){return this.collator.compare(t,e)},Qt.prototype.resolvedLocale=function(){return new Intl.Collator(this.locale?this.locale:[]).resolvedOptions().locale};var $t=function(t,e,r,n,i){this.text=t,this.image=e,this.scale=r,this.fontStack=n,this.textColor=i},te=function(t){this.sections=t};te.fromString=function(t){return new te([new $t(t,null,null,null,null)])},te.prototype.isEmpty=function(){return 0===this.sections.length||!this.sections.some((function(t){return 0!==t.text.length||t.image&&0!==t.image.name.length}))},te.factory=function(t){return t instanceof te?t:te.fromString(t)},te.prototype.toString=function(){return 0===this.sections.length?\"\":this.sections.map((function(t){return t.text})).join(\"\")},te.prototype.serialize=function(){for(var t=[\"format\"],e=0,r=this.sections;e<r.length;e+=1){var n=r[e];if(n.image)t.push([\"image\",n.image.name]);else{t.push(n.text);var i={};n.fontStack&&(i[\"text-font\"]=[\"literal\",n.fontStack.split(\",\")]),n.scale&&(i[\"font-scale\"]=n.scale),n.textColor&&(i[\"text-color\"]=[\"rgba\"].concat(n.textColor.toArray())),t.push(i)}}return t};var ee=function(t){this.name=t.name,this.available=t.available};function re(t,e,r,n){return\"number\"==typeof t&&t>=0&&t<=255&&\"number\"==typeof e&&e>=0&&e<=255&&\"number\"==typeof r&&r>=0&&r<=255?void 0===n||\"number\"==typeof n&&n>=0&&n<=1?null:\"Invalid rgba value [\"+[t,e,r,n].join(\", \")+\"]: 'a' must be between 0 and 1.\":\"Invalid rgba value [\"+(\"number\"==typeof n?[t,e,r,n]:[t,e,r]).join(\", \")+\"]: 'r', 'g', and 'b' must be between 0 and 255.\"}function ne(t){if(null===t)return!0;if(\"string\"==typeof t)return!0;if(\"boolean\"==typeof t)return!0;if(\"number\"==typeof t)return!0;if(t instanceof Kt)return!0;if(t instanceof Qt)return!0;if(t instanceof te)return!0;if(t instanceof ee)return!0;if(Array.isArray(t)){for(var e=0,r=t;e<r.length;e+=1)if(!ne(r[e]))return!1;return!0}if(\"object\"==typeof t){for(var n in t)if(!ne(t[n]))return!1;return!0}return!1}function ie(t){if(null===t)return Ot;if(\"string\"==typeof t)return Rt;if(\"boolean\"==typeof t)return Ft;if(\"number\"==typeof t)return Dt;if(t instanceof Kt)return Bt;if(t instanceof Qt)return Ut;if(t instanceof te)return Vt;if(t instanceof ee)return qt;if(Array.isArray(t)){for(var e,r=t.length,n=0,i=t;n<i.length;n+=1){var a=ie(i[n]);if(e){if(e===a)continue;e=jt;break}e=a}return Ht(e||jt,r)}return Nt}function ae(t){var e=typeof t;return null===t?\"\":\"string\"===e||\"number\"===e||\"boolean\"===e?String(t):t instanceof Kt||t instanceof te||t instanceof ee?t.toString():JSON.stringify(t)}ee.prototype.toString=function(){return this.name},ee.fromString=function(t){return t?new ee({name:t,available:!1}):null},ee.prototype.serialize=function(){return[\"image\",this.name]};var oe=function(t,e){this.type=t,this.value=e};oe.parse=function(t,e){if(2!==t.length)return e.error(\"'literal' expression requires exactly one argument, but found \"+(t.length-1)+\" instead.\");if(!ne(t[1]))return e.error(\"invalid value\");var r=t[1],n=ie(r),i=e.expectedType;return\"array\"!==n.kind||0!==n.N||!i||\"array\"!==i.kind||\"number\"==typeof i.N&&0!==i.N||(n=i),new oe(n,r)},oe.prototype.evaluate=function(){return this.value},oe.prototype.eachChild=function(){},oe.prototype.outputDefined=function(){return!0},oe.prototype.serialize=function(){return\"array\"===this.type.kind||\"object\"===this.type.kind?[\"literal\",this.value]:this.value instanceof Kt?[\"rgba\"].concat(this.value.toArray()):this.value instanceof te?this.value.serialize():this.value};var se=function(t){this.name=\"ExpressionEvaluationError\",this.message=t};se.prototype.toJSON=function(){return this.message};var le={string:Rt,number:Dt,boolean:Ft,object:Nt},ce=function(t,e){this.type=t,this.args=e};ce.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");var r,n=1,i=t[0];if(\"array\"===i){var a,o;if(t.length>2){var s=t[1];if(\"string\"!=typeof s||!(s in le)||\"object\"===s)return e.error('The item type argument of \"array\" must be one of string, number, boolean',1);a=le[s],n++}else a=jt;if(t.length>3){if(null!==t[2]&&(\"number\"!=typeof t[2]||t[2]<0||t[2]!==Math.floor(t[2])))return e.error('The length argument to \"array\" must be a positive integer literal',2);o=t[2],n++}r=Ht(a,o)}else r=le[i];for(var l=[];n<t.length;n++){var c=e.parse(t[n],n,jt);if(!c)return null;l.push(c)}return new ce(r,l)},ce.prototype.evaluate=function(t){for(var e=0;e<this.args.length;e++){var r=this.args[e].evaluate(t);if(!Wt(this.type,ie(r)))return r;if(e===this.args.length-1)throw new se(\"Expected value to be of type \"+Gt(this.type)+\", but found \"+Gt(ie(r))+\" instead.\")}return null},ce.prototype.eachChild=function(t){this.args.forEach(t)},ce.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},ce.prototype.serialize=function(){var t=this.type,e=[t.kind];if(\"array\"===t.kind){var r=t.itemType;if(\"string\"===r.kind||\"number\"===r.kind||\"boolean\"===r.kind){e.push(r.kind);var n=t.N;(\"number\"==typeof n||this.args.length>1)&&e.push(n)}}return e.concat(this.args.map((function(t){return t.serialize()})))};var ue=function(t){this.type=Vt,this.sections=t};ue.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");var r=t[1];if(!Array.isArray(r)&&\"object\"==typeof r)return e.error(\"First argument must be an image or text section.\");for(var n=[],i=!1,a=1;a<=t.length-1;++a){var o=t[a];if(i&&\"object\"==typeof o&&!Array.isArray(o)){i=!1;var s=null;if(o[\"font-scale\"]&&!(s=e.parse(o[\"font-scale\"],1,Dt)))return null;var l=null;if(o[\"text-font\"]&&!(l=e.parse(o[\"text-font\"],1,Ht(Rt))))return null;var c=null;if(o[\"text-color\"]&&!(c=e.parse(o[\"text-color\"],1,Bt)))return null;var u=n[n.length-1];u.scale=s,u.font=l,u.textColor=c}else{var f=e.parse(t[a],1,jt);if(!f)return null;var h=f.type.kind;if(\"string\"!==h&&\"value\"!==h&&\"null\"!==h&&\"resolvedImage\"!==h)return e.error(\"Formatted text type must be 'string', 'value', 'image' or 'null'.\");i=!0,n.push({content:f,scale:null,font:null,textColor:null})}}return new ue(n)},ue.prototype.evaluate=function(t){return new te(this.sections.map((function(e){var r=e.content.evaluate(t);return ie(r)===qt?new $t(\"\",r,null,null,null):new $t(ae(r),null,e.scale?e.scale.evaluate(t):null,e.font?e.font.evaluate(t).join(\",\"):null,e.textColor?e.textColor.evaluate(t):null)})))},ue.prototype.eachChild=function(t){for(var e=0,r=this.sections;e<r.length;e+=1){var n=r[e];t(n.content),n.scale&&t(n.scale),n.font&&t(n.font),n.textColor&&t(n.textColor)}},ue.prototype.outputDefined=function(){return!1},ue.prototype.serialize=function(){for(var t=[\"format\"],e=0,r=this.sections;e<r.length;e+=1){var n=r[e];t.push(n.content.serialize());var i={};n.scale&&(i[\"font-scale\"]=n.scale.serialize()),n.font&&(i[\"text-font\"]=n.font.serialize()),n.textColor&&(i[\"text-color\"]=n.textColor.serialize()),t.push(i)}return t};var fe=function(t){this.type=qt,this.input=t};fe.parse=function(t,e){if(2!==t.length)return e.error(\"Expected two arguments.\");var r=e.parse(t[1],1,Rt);return r?new fe(r):e.error(\"No image name provided.\")},fe.prototype.evaluate=function(t){var e=this.input.evaluate(t),r=ee.fromString(e);return r&&t.availableImages&&(r.available=t.availableImages.indexOf(e)>-1),r},fe.prototype.eachChild=function(t){t(this.input)},fe.prototype.outputDefined=function(){return!1},fe.prototype.serialize=function(){return[\"image\",this.input.serialize()]};var he={\"to-boolean\":Ft,\"to-color\":Bt,\"to-number\":Dt,\"to-string\":Rt},pe=function(t,e){this.type=t,this.args=e};pe.parse=function(t,e){if(t.length<2)return e.error(\"Expected at least one argument.\");var r=t[0];if((\"to-boolean\"===r||\"to-string\"===r)&&2!==t.length)return e.error(\"Expected one argument.\");for(var n=he[r],i=[],a=1;a<t.length;a++){var o=e.parse(t[a],a,jt);if(!o)return null;i.push(o)}return new pe(n,i)},pe.prototype.evaluate=function(t){if(\"boolean\"===this.type.kind)return Boolean(this.args[0].evaluate(t));if(\"color\"===this.type.kind){for(var e,r,n=0,i=this.args;n<i.length;n+=1){if(r=null,(e=i[n].evaluate(t))instanceof Kt)return e;if(\"string\"==typeof e){var a=t.parseColor(e);if(a)return a}else if(Array.isArray(e)&&!(r=e.length<3||e.length>4?\"Invalid rbga value \"+JSON.stringify(e)+\": expected an array containing either three or four numeric values.\":re(e[0],e[1],e[2],e[3])))return new Kt(e[0]/255,e[1]/255,e[2]/255,e[3])}throw new se(r||\"Could not parse color from value '\"+(\"string\"==typeof e?e:String(JSON.stringify(e)))+\"'\")}if(\"number\"===this.type.kind){for(var o=null,s=0,l=this.args;s<l.length;s+=1){if(null===(o=l[s].evaluate(t)))return 0;var c=Number(o);if(!isNaN(c))return c}throw new se(\"Could not convert \"+JSON.stringify(o)+\" to number.\")}return\"formatted\"===this.type.kind?te.fromString(ae(this.args[0].evaluate(t))):\"resolvedImage\"===this.type.kind?ee.fromString(ae(this.args[0].evaluate(t))):ae(this.args[0].evaluate(t))},pe.prototype.eachChild=function(t){this.args.forEach(t)},pe.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},pe.prototype.serialize=function(){if(\"formatted\"===this.type.kind)return new ue([{content:this.args[0],scale:null,font:null,textColor:null}]).serialize();if(\"resolvedImage\"===this.type.kind)return new fe(this.args[0]).serialize();var t=[\"to-\"+this.type.kind];return this.eachChild((function(e){t.push(e.serialize())})),t};var de=[\"Unknown\",\"Point\",\"LineString\",\"Polygon\"],ge=function(){this.globals=null,this.feature=null,this.featureState=null,this.formattedSection=null,this._parseColorCache={},this.availableImages=null,this.canonical=null};ge.prototype.id=function(){return this.feature&&\"id\"in this.feature?this.feature.id:null},ge.prototype.geometryType=function(){return this.feature?\"number\"==typeof this.feature.type?de[this.feature.type]:this.feature.type:null},ge.prototype.geometry=function(){return this.feature&&\"geometry\"in this.feature?this.feature.geometry:null},ge.prototype.canonicalID=function(){return this.canonical},ge.prototype.properties=function(){return this.feature&&this.feature.properties||{}},ge.prototype.parseColor=function(t){var e=this._parseColorCache[t];return e||(e=this._parseColorCache[t]=Kt.parse(t)),e};var me=function(t,e,r,n){this.name=t,this.type=e,this._evaluate=r,this.args=n};me.prototype.evaluate=function(t){return 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a=Ne(e,n),o=rr.interpolationFactor(this.interpolation,n,e[a],e[a+1]),s=r[a].evaluate(t),l=r[a+1].evaluate(t);return\"interpolate\"===this.operator?Ve[this.type.kind.toLowerCase()](s,l,o):\"interpolate-hcl\"===this.operator?tr.reverse(tr.interpolate(tr.forward(s),tr.forward(l),o)):$e.reverse($e.interpolate($e.forward(s),$e.forward(l),o))},rr.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1)t(r[e])},rr.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},rr.prototype.serialize=function(){var t;t=\"linear\"===this.interpolation.name?[\"linear\"]:\"exponential\"===this.interpolation.name?1===this.interpolation.base?[\"linear\"]:[\"exponential\",this.interpolation.base]:[\"cubic-bezier\"].concat(this.interpolation.controlPoints);for(var e=[this.operator,t,this.input.serialize()],r=0;r<this.labels.length;r++)e.push(this.labels[r],this.outputs[r].serialize());return e};var ir=function(t,e){this.type=t,this.args=e};ir.parse=function(t,e){if(t.length<2)return e.error(\"Expectected at least one argument.\");var r=null,n=e.expectedType;n&&\"value\"!==n.kind&&(r=n);for(var i=[],a=0,o=t.slice(1);a<o.length;a+=1){var s=e.parse(o[a],1+i.length,r,void 0,{typeAnnotation:\"omit\"});if(!s)return null;r=r||s.type,i.push(s)}var l=n&&i.some((function(t){return Wt(n,t.type)}));return new ir(l?jt:r,i)},ir.prototype.evaluate=function(t){for(var e,r=null,n=0,i=0,a=this.args;i<a.length&&(n++,(r=a[i].evaluate(t))&&r instanceof ee&&!r.available&&(e||(e=r.name),r=null,n===this.args.length&&(r=e)),null===r);i+=1);return r},ir.prototype.eachChild=function(t){this.args.forEach(t)},ir.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},ir.prototype.serialize=function(){var t=[\"coalesce\"];return this.eachChild((function(e){t.push(e.serialize())})),t};var ar=function(t,e){this.type=e.type,this.bindings=[].concat(t),this.result=e};ar.prototype.evaluate=function(t){return this.result.evaluate(t)},ar.prototype.eachChild=function(t){for(var e=0,r=this.bindings;e<r.length;e+=1)t(r[e][1]);t(this.result)},ar.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found \"+(t.length-1)+\" instead.\");for(var r=[],n=1;n<t.length-1;n+=2){var i=t[n];if(\"string\"!=typeof i)return e.error(\"Expected string, but found \"+typeof i+\" instead.\",n);if(/[^a-zA-Z0-9_]/.test(i))return e.error(\"Variable names must contain only alphanumeric characters or '_'.\",n);var a=e.parse(t[n+1],n+1);if(!a)return null;r.push([i,a])}var o=e.parse(t[t.length-1],t.length-1,e.expectedType,r);return o?new ar(r,o):null},ar.prototype.outputDefined=function(){return this.result.outputDefined()},ar.prototype.serialize=function(){for(var t=[\"let\"],e=0,r=this.bindings;e<r.length;e+=1){var n=r[e];t.push(n[0],n[1].serialize())}return t.push(this.result.serialize()),t};var or=function(t,e,r){this.type=t,this.index=e,this.input=r};or.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Dt),n=e.parse(t[2],2,Ht(e.expectedType||jt));return r&&n?new or(n.type.itemType,r,n):null},or.prototype.evaluate=function(t){var e=this.index.evaluate(t),r=this.input.evaluate(t);if(e<0)throw new se(\"Array index out of bounds: \"+e+\" < 0.\");if(e>=r.length)throw new se(\"Array index out of bounds: \"+e+\" > \"+(r.length-1)+\".\");if(e!==Math.floor(e))throw new se(\"Array index must be an integer, but found \"+e+\" instead.\");return r[e]},or.prototype.eachChild=function(t){t(this.index),t(this.input)},or.prototype.outputDefined=function(){return!1},or.prototype.serialize=function(){return[\"at\",this.index.serialize(),this.input.serialize()]};var sr=function(t,e){this.type=Ft,this.needle=t,this.haystack=e};sr.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,jt),n=e.parse(t[2],2,jt);return r&&n?Xt(r.type,[Ft,Rt,Dt,Ot,jt])?new sr(r,n):e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Gt(r.type)+\" instead\"):null},sr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!Zt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new se(\"Expected first argument to be of type boolean, string, number or null, but found \"+Gt(ie(e))+\" instead.\");if(!Zt(r,[\"string\",\"array\"]))throw new se(\"Expected second argument to be of type array or string, but found \"+Gt(ie(r))+\" instead.\");return r.indexOf(e)>=0},sr.prototype.eachChild=function(t){t(this.needle),t(this.haystack)},sr.prototype.outputDefined=function(){return!0},sr.prototype.serialize=function(){return[\"in\",this.needle.serialize(),this.haystack.serialize()]};var lr=function(t,e,r){this.type=Dt,this.needle=t,this.haystack=e,this.fromIndex=r};lr.parse=function(t,e){if(t.length<=2||t.length>=5)return e.error(\"Expected 3 or 4 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,jt),n=e.parse(t[2],2,jt);if(!r||!n)return null;if(!Xt(r.type,[Ft,Rt,Dt,Ot,jt]))return e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Gt(r.type)+\" instead\");if(4===t.length){var i=e.parse(t[3],3,Dt);return i?new lr(r,n,i):null}return new lr(r,n)},lr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!Zt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new se(\"Expected first argument to be of type boolean, string, number or null, but found \"+Gt(ie(e))+\" instead.\");if(!Zt(r,[\"string\",\"array\"]))throw new se(\"Expected second argument to be of type array or string, but found \"+Gt(ie(r))+\" instead.\");if(this.fromIndex){var n=this.fromIndex.evaluate(t);return r.indexOf(e,n)}return r.indexOf(e)},lr.prototype.eachChild=function(t){t(this.needle),t(this.haystack),this.fromIndex&&t(this.fromIndex)},lr.prototype.outputDefined=function(){return!1},lr.prototype.serialize=function(){if(null!=this.fromIndex&&void 0!==this.fromIndex){var t=this.fromIndex.serialize();return[\"index-of\",this.needle.serialize(),this.haystack.serialize(),t]}return[\"index-of\",this.needle.serialize(),this.haystack.serialize()]};var cr=function(t,e,r,n,i,a){this.inputType=t,this.type=e,this.input=r,this.cases=n,this.outputs=i,this.otherwise=a};cr.parse=function(t,e){if(t.length<5)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=1)return e.error(\"Expected an even number of arguments.\");var r,n;e.expectedType&&\"value\"!==e.expectedType.kind&&(n=e.expectedType);for(var i={},a=[],o=2;o<t.length-1;o+=2){var s=t[o],l=t[o+1];Array.isArray(s)||(s=[s]);var 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e=this.input.evaluate(t);return(ie(e)===this.inputType&&this.outputs[this.cases[e]]||this.otherwise).evaluate(t)},cr.prototype.eachChild=function(t){t(this.input),this.outputs.forEach(t),t(this.otherwise)},cr.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))&&this.otherwise.outputDefined()},cr.prototype.serialize=function(){for(var t=this,e=[\"match\",this.input.serialize()],r=[],n={},i=0,a=Object.keys(this.cases).sort();i<a.length;i+=1){var o=a[i];void 0===(f=n[this.cases[o]])?(n[this.cases[o]]=r.length,r.push([this.cases[o],[o]])):r[f][1].push(o)}for(var s=function(e){return\"number\"===t.inputType.kind?Number(e):e},l=0,c=r;l<c.length;l+=1){var u=c[l],f=u[0],h=u[1];e.push(1===h.length?s(h[0]):h.map(s)),e.push(this.outputs[outputIndex$1].serialize())}return e.push(this.otherwise.serialize()),e};var ur=function(t,e,r){this.type=t,this.branches=e,this.otherwise=r};ur.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 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fr=function(t,e,r,n){this.type=t,this.input=e,this.beginIndex=r,this.endIndex=n};function hr(t,e){return\"==\"===t||\"!=\"===t?\"boolean\"===e.kind||\"string\"===e.kind||\"number\"===e.kind||\"null\"===e.kind||\"value\"===e.kind:\"string\"===e.kind||\"number\"===e.kind||\"value\"===e.kind}function pr(t,e,r,n){return 0===n.compare(e,r)}function dr(t,e,r){var n=\"==\"!==t&&\"!=\"!==t;return function(){function i(t,e,r){this.type=Ft,this.lhs=t,this.rhs=e,this.collator=r,this.hasUntypedArgument=\"value\"===t.type.kind||\"value\"===e.type.kind}return i.parse=function(t,e){if(3!==t.length&&4!==t.length)return e.error(\"Expected two or three arguments.\");var r=t[0],a=e.parse(t[1],1,jt);if(!a)return null;if(!hr(r,a.type))return e.concat(1).error('\"'+r+\"\\\" comparisons are not supported for type '\"+Gt(a.type)+\"'.\");var o=e.parse(t[2],2,jt);if(!o)return null;if(!hr(r,o.type))return e.concat(2).error('\"'+r+\"\\\" comparisons are not supported for type 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0,o={}),e=e.concat(Xr({key:s+\"[0]\",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:Jr,value:h}}))}else e=e.concat(h({key:s+\"[0]\",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return Vr(It(a[1]))?e.concat([new St(s+\"[1]\",a[1],\"expressions are not allowed in function stops.\")]):e.concat(bn({key:s+\"[1]\",value:a[1],valueSpec:i,style:t.style,styleSpec:t.styleSpec}))}function h(t,n){var s=zr(t.value),l=Lt(t.value),c=null!==t.value?t.value:n;if(e){if(s!==e)return[new St(t.key,c,s+\" stop domain type must match previous stop domain type \"+e)]}else e=s;if(\"number\"!==s&&\"string\"!==s&&\"boolean\"!==s)return[new St(t.key,c,\"stop domain value must be a number, string, or boolean\")];if(\"number\"!==s&&\"categorical\"!==a){var u=\"number expected, \"+s+\" found\";return Lr(i)&&void 0===a&&(u+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new St(t.key,c,u)]}return\"categorical\"!==a||\"number\"!==s||isFinite(l)&&Math.floor(l)===l?\"categorical\"!==a&&\"number\"===s&&void 0!==r&&l<r?[new St(t.key,c,\"stop domain values must appear in ascending order\")]:(r=l,\"categorical\"===a&&l in o?[new St(t.key,c,\"stop domain values must be unique\")]:(o[l]=!0,[])):[new St(t.key,c,\"integer expected, found \"+l)]}}function Qr(t){var e=(\"property\"===t.expressionContext?Yr:qr)(It(t.value),t.valueSpec);if(\"error\"===e.result)return e.value.map((function(e){return new St(\"\"+t.key+e.key,t.value,e.message)}));var r=e.value.expression||e.value._styleExpression.expression;if(\"property\"===t.expressionContext&&\"text-font\"===t.propertyKey&&!r.outputDefined())return[new St(t.key,t.value,'Invalid data expression for \"'+t.propertyKey+'\". 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en={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function rn(t){if(null==t)return{filter:function(){return!0},needGeometry:!1};tn(t)||(t=an(t));var e=qr(t,en);if(\"error\"===e.result)throw new Error(e.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return{filter:function(t,r,n){return e.value.evaluate(t,r,{},n)},needGeometry:function t(e){if(!Array.isArray(e))return!1;if(\"within\"===e[0])return!0;for(var r=1;r<e.length;r++)if(t(e[r]))return!0;return!1}(t)}}function nn(t,e){return t<e?-1:t>e?1:0}function an(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?on(t[1],t[2],\"==\"):\"!=\"===r?cn(on(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?on(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(an))):\"all\"===r?[\"all\"].concat(t.slice(1).map(an)):\"none\"===r?[\"all\"].concat(t.slice(1).map(an).map(cn)):\"in\"===r?sn(t[1],t.slice(2)):\"!in\"===r?cn(sn(t[1],t.slice(2))):\"has\"===r?ln(t[1]):\"!has\"===r?cn(ln(t[1])):\"within\"!==r||t}function on(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function sn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(nn)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function ln(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function cn(t){return[\"!\",t]}function un(t){return tn(It(t.value))?Qr(Ct({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):function t(e){var r=e.value,n=e.key;if(\"array\"!==zr(r))return[new St(n,r,\"array expected, \"+zr(r)+\" found\")];var i,a=e.styleSpec,o=[];if(r.length<1)return[new St(n,r,\"filter array must have at least 1 element\")];switch(o=o.concat($r({key:n+\"[0]\",value:r[0],valueSpec:a.filter_operator,style:e.style,styleSpec:e.styleSpec})),Lt(r[0])){case\"<\":case\"<=\":case\">\":case\">=\":r.length>=2&&\"$type\"===Lt(r[1])&&o.push(new St(n,r,'\"$type\" cannot be use with operator \"'+r[0]+'\"'));case\"==\":case\"!=\":3!==r.length&&o.push(new St(n,r,'filter array for operator \"'+r[0]+'\" must have 3 elements'));case\"in\":case\"!in\":r.length>=2&&\"string\"!==(i=zr(r[1]))&&o.push(new St(n+\"[1]\",r[1],\"string expected, \"+i+\" found\"));for(var s=2;s<r.length;s++)i=zr(r[s]),\"$type\"===Lt(r[1])?o=o.concat($r({key:n+\"[\"+s+\"]\",value:r[s],valueSpec:a.geometry_type,style:e.style,styleSpec:e.styleSpec})):\"string\"!==i&&\"number\"!==i&&\"boolean\"!==i&&o.push(new St(n+\"[\"+s+\"]\",r[s],\"string, number, or boolean expected, \"+i+\" found\"));break;case\"any\":case\"all\":case\"none\":for(var l=1;l<r.length;l++)o=o.concat(t({key:n+\"[\"+l+\"]\",value:r[l],style:e.style,styleSpec:e.styleSpec}));break;case\"has\":case\"!has\":i=zr(r[1]),2!==r.length?o.push(new St(n,r,'filter array for \"'+r[0]+'\" operator must have 2 elements')):\"string\"!==i&&o.push(new St(n+\"[1]\",r[1],\"string expected, \"+i+\" found\"));break;case\"within\":i=zr(r[1]),2!==r.length?o.push(new St(n,r,'filter array for \"'+r[0]+'\" operator must have 2 elements')):\"object\"!==i&&o.push(new St(n+\"[1]\",r[1],\"object expected, \"+i+\" found\"))}return o}(t)}function fn(t,e){var r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return bn({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var c,u=t.valueSpec||s[o];if(!u)return[new St(r,a,'unknown property \"'+o+'\"')];if(\"string\"===zr(a)&&Lr(u)&&!u.tokens&&(c=/^{([^}]+)}$/.exec(a)))return[new St(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(c[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new St(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&Or(It(a))&&\"identity\"===Lt(a.type)&&f.push(new St(r,a,'\"text-font\" does not support identity 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h=i.sources&&i.sources[r.source],p=h&&Lt(h.type);h?\"vector\"===p&&\"raster\"===s?e.push(new St(n,r.source,'layer \"'+r.id+'\" requires a raster source')):\"raster\"===p&&\"raster\"!==s?e.push(new St(n,r.source,'layer \"'+r.id+'\" requires a vector source')):\"vector\"!==p||r[\"source-layer\"]?\"raster-dem\"===p&&\"hillshade\"!==s?e.push(new St(n,r.source,\"raster-dem source can only be used with layer type 'hillshade'.\")):\"line\"!==s||!r.paint||!r.paint[\"line-gradient\"]||\"geojson\"===p&&h.lineMetrics||e.push(new St(n,r,'layer \"'+r.id+'\" specifies a line-gradient, which requires a GeoJSON source with `lineMetrics` enabled.')):e.push(new St(n,r,'layer \"'+r.id+'\" must specify a \"source-layer\"')):e.push(new St(n,r.source,'source \"'+r.source+'\" not found'))}else e.push(new St(n,r,'missing required property \"source\"'));return e=e.concat(Xr({key:n,value:r,valueSpec:a.layer,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(){return[]},type:function(){return bn({key:n+\".type\",value:r.type,valueSpec:a.layer.type,style:t.style,styleSpec:t.styleSpec,object:r,objectKey:\"type\"})},filter:un,layout:function(t){return Xr({layer:r,key:t.key,value:t.value,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(t){return pn(Ct({layerType:s},t))}}})},paint:function(t){return Xr({layer:r,key:t.key,value:t.value,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{\"*\":function(t){return hn(Ct({layerType:s},t))}}})}}}))}function gn(t){var e=t.value,r=t.key,n=zr(e);return\"string\"!==n?[new St(r,e,\"string expected, \"+n+\" found\")]:[]}var mn={promoteId:function(t){var e=t.key,r=t.value;if(\"string\"===zr(r))return gn({key:e,value:r});var n=[];for(var i in r)n.push.apply(n,gn({key:e+\".\"+i,value:r[i]}));return n}};function vn(t){var e=t.value,r=t.key,n=t.styleSpec,i=t.style;if(!e.type)return[new St(r,e,'\"type\" is required')];var a,o=Lt(e.type);switch(o){case\"vector\":case\"raster\":case\"raster-dem\":return Xr({key:r,value:e,valueSpec:n[\"source_\"+o.replace(\"-\",\"_\")],style:t.style,styleSpec:n,objectElementValidators:mn});case\"geojson\":if(a=Xr({key:r,value:e,valueSpec:n.source_geojson,style:i,styleSpec:n,objectElementValidators:mn}),e.cluster)for(var s in e.clusterProperties){var l=e.clusterProperties[s],c=l[0],u=\"string\"==typeof c?[c,[\"accumulated\"],[\"get\",s]]:c;a.push.apply(a,Qr({key:r+\".\"+s+\".map\",value:l[1],expressionContext:\"cluster-map\"})),a.push.apply(a,Qr({key:r+\".\"+s+\".reduce\",value:u,expressionContext:\"cluster-reduce\"}))}return a;case\"video\":return Xr({key:r,value:e,valueSpec:n.source_video,style:i,styleSpec:n});case\"image\":return Xr({key:r,value:e,valueSpec:n.source_image,style:i,styleSpec:n});case\"canvas\":return[new St(r,null,\"Please use runtime APIs to add canvas sources, rather than including them in stylesheets.\",\"source.canvas\")];default:return $r({key:r+\".type\",value:e.type,valueSpec:{values:[\"vector\",\"raster\",\"raster-dem\",\"geojson\",\"video\",\"image\"]},style:i,styleSpec:n})}}function yn(t){var e=t.value,r=t.styleSpec,n=r.light,i=t.style,a=[],o=zr(e);if(void 0===e)return a;if(\"object\"!==o)return a.concat([new St(\"light\",e,\"object expected, \"+o+\" found\")]);for(var s in e){var l=s.match(/^(.*)-transition$/);a=a.concat(l&&n[l[1]]&&n[l[1]].transition?bn({key:s,value:e[s],valueSpec:r.transition,style:i,styleSpec:r}):n[s]?bn({key:s,value:e[s],valueSpec:n[s],style:i,styleSpec:r}):[new St(s,e[s],'unknown property \"'+s+'\"')])}return a}var xn={\"*\":function(){return[]},array:Zr,boolean:function(t){var e=t.value,r=t.key,n=zr(e);return\"boolean\"!==n?[new St(r,e,\"boolean expected, \"+n+\" found\")]:[]},number:Jr,color:function(t){var e=t.key,r=t.value,n=zr(r);return\"string\"!==n?[new St(e,r,\"color expected, \"+n+\" 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r=r.concat(bn({key:\"\",value:t,valueSpec:e.$root,styleSpec:e,style:t,objectElementValidators:{glyphs:_n,\"*\":function(){return[]}}})),t.constants&&(r=r.concat(Et({key:\"constants\",value:t.constants,style:t,styleSpec:e}))),Tn(r)}function Tn(t){return[].concat(t).sort((function(t,e){return t.line-e.line}))}function kn(t){return function(){for(var e=[],r=arguments.length;r--;)e[r]=arguments[r];return Tn(t.apply(this,e))}}wn.source=kn(vn),wn.light=kn(yn),wn.layer=kn(dn),wn.filter=kn(un),wn.paintProperty=kn(hn),wn.layoutProperty=kn(pn);var Mn=wn,An=Mn.light,Sn=Mn.paintProperty,En=Mn.layoutProperty;function Cn(t,e){var r=!1;if(e&&e.length)for(var n=0,i=e;n<i.length;n+=1)t.fire(new kt(new Error(i[n].message))),r=!0;return r}var Ln=In;function In(t,e,r){var n=this.cells=[];if(t instanceof ArrayBuffer){this.arrayBuffer=t;var i=new Int32Array(this.arrayBuffer);t=i[0],this.d=(e=i[1])+2*(r=i[2]);for(var a=0;a<this.d*this.d;a++){var o=i[3+a],s=i[3+a+1];n.push(o===s?null:i.subarray(o,s))}var l=i[3+n.length+1];this.keys=i.subarray(i[3+n.length],l),this.bboxes=i.subarray(l),this.insert=this._insertReadonly}else{this.d=e+2*r;for(var c=0;c<this.d*this.d;c++)n.push([]);this.keys=[],this.bboxes=[]}this.n=e,this.extent=t,this.padding=r,this.scale=e/t,this.uid=0;var u=r/e*t;this.min=-u,this.max=t+u}In.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertCell,this.uid++),this.keys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},In.prototype._insertReadonly=function(){throw\"Cannot insert into a GridIndex created from an ArrayBuffer.\"},In.prototype._insertCell=function(t,e,r,n,i,a){this.cells[i].push(a)},In.prototype.query=function(t,e,r,n,i){var a=this.min,o=this.max;if(t<=a&&e<=a&&o<=r&&o<=n&&!i)return Array.prototype.slice.call(this.keys);var s=[];return this._forEachCell(t,e,r,n,this._queryCell,s,{},i),s},In.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=this.cells[i];if(null!==l)for(var c=this.keys,u=this.bboxes,f=0;f<l.length;f++){var h=l[f];if(void 0===o[h]){var p=4*h;(s?s(u[p+0],u[p+1],u[p+2],u[p+3]):t<=u[p+2]&&e<=u[p+3]&&r>=u[p+0]&&n>=u[p+1])?(o[h]=!0,a.push(c[h])):o[h]=!1}}},In.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToCellCoord(t),c=this._convertToCellCoord(e),u=this._convertToCellCoord(r),f=this._convertToCellCoord(n),h=l;h<=u;h++)for(var p=c;p<=f;p++){var d=this.d*p+h;if((!s||s(this._convertFromCellCoord(h),this._convertFromCellCoord(p),this._convertFromCellCoord(h+1),this._convertFromCellCoord(p+1)))&&i.call(this,t,e,r,n,d,a,o,s))return}},In.prototype._convertFromCellCoord=function(t){return(t-this.padding)/this.scale},In.prototype._convertToCellCoord=function(t){return Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))},In.prototype.toArrayBuffer=function(){if(this.arrayBuffer)return this.arrayBuffer;for(var t=this.cells,e=3+this.cells.length+1+1,r=0,n=0;n<this.cells.length;n++)r+=this.cells[n].length;var i=new Int32Array(e+r+this.keys.length+this.bboxes.length);i[0]=this.extent,i[1]=this.n,i[2]=this.padding;for(var a=e,o=0;o<t.length;o++){var s=t[o];i[3+o]=a,i.set(s,a),a+=s.length}return i[3+t.length]=a,i.set(this.keys,a),i[3+t.length+1]=a+=this.keys.length,i.set(this.bboxes,a),a+=this.bboxes.length,i.buffer};var Pn=self.ImageData,zn=self.ImageBitmap,On={};function Dn(t,e,r){void 0===r&&(r={}),Object.defineProperty(e,\"_classRegistryKey\",{value:t,writeable:!1}),On[t]={klass:e,omit:r.omit||[],shallow:r.shallow||[]}}for(var Rn in Dn(\"Object\",Object),Ln.serialize=function(t,e){var r=t.toArrayBuffer();return e&&e.push(r),{buffer:r}},Ln.deserialize=function(t){return new Ln(t.buffer)},Dn(\"Grid\",Ln),Dn(\"Color\",Kt),Dn(\"Error\",Error),Dn(\"ResolvedImage\",ee),Dn(\"StylePropertyFunction\",Wr),Dn(\"StyleExpression\",Ur,{omit:[\"_evaluator\"]}),Dn(\"ZoomDependentExpression\",Gr),Dn(\"ZoomConstantExpression\",Hr),Dn(\"CompoundExpression\",me,{omit:[\"_evaluate\"]}),Tr)Tr[Rn]._classRegistryKey||Dn(\"Expression_\"+Rn,Tr[Rn]);function Fn(t){return t&&\"undefined\"!=typeof ArrayBuffer&&(t instanceof ArrayBuffer||t.constructor&&\"ArrayBuffer\"===t.constructor.name)}function Bn(t){return zn&&t instanceof zn}function Nn(t,e){if(null==t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||t instanceof Boolean||t instanceof Number||t instanceof String||t instanceof Date||t instanceof RegExp)return t;if(Fn(t)||Bn(t))return e&&e.push(t),t;if(ArrayBuffer.isView(t)){var r=t;return e&&e.push(r.buffer),r}if(t instanceof Pn)return e&&e.push(t.data.buffer),t;if(Array.isArray(t)){for(var n=[],i=0,a=t;i<a.length;i+=1)n.push(Nn(a[i],e));return n}if(\"object\"==typeof t){var o=t.constructor,s=o._classRegistryKey;if(!s)throw new Error(\"can't serialize object of unregistered class\");var l=o.serialize?o.serialize(t,e):{};if(!o.serialize){for(var c in t)if(t.hasOwnProperty(c)&&!(On[s].omit.indexOf(c)>=0)){var u=t[c];l[c]=On[s].shallow.indexOf(c)>=0?u:Nn(u,e)}t instanceof Error&&(l.message=t.message)}if(l.$name)throw new Error(\"$name property is reserved for worker serialization logic.\");return\"Object\"!==s&&(l.$name=s),l}throw new Error(\"can't serialize object of type \"+typeof t)}function jn(t){if(null==t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||t instanceof Boolean||t instanceof Number||t instanceof String||t instanceof Date||t instanceof RegExp||Fn(t)||Bn(t)||ArrayBuffer.isView(t)||t instanceof Pn)return t;if(Array.isArray(t))return t.map(jn);if(\"object\"==typeof t){var e=t.$name||\"Object\",r=On[e].klass;if(!r)throw new Error(\"can't deserialize unregistered class \"+e);if(r.deserialize)return r.deserialize(t);for(var n=Object.create(r.prototype),i=0,a=Object.keys(t);i<a.length;i+=1){var o=a[i];if(\"$name\"!==o){var s=t[o];n[o]=On[e].shallow.indexOf(o)>=0?s:jn(s)}}return n}throw new Error(\"can't deserialize object of type \"+typeof t)}var Un=function(){this.first=!0};Un.prototype.update=function(t,e){var r=Math.floor(t);return this.first?(this.first=!1,this.lastIntegerZoom=r,this.lastIntegerZoomTime=0,this.lastZoom=t,this.lastFloorZoom=r,!0):(this.lastFloorZoom>r?(this.lastIntegerZoom=r+1,this.lastIntegerZoomTime=e):this.lastFloorZoom<r&&(this.lastIntegerZoom=r,this.lastIntegerZoomTime=e),t!==this.lastZoom&&(this.lastZoom=t,this.lastFloorZoom=r,!0))};var Vn={\"Latin-1 Supplement\":function(t){return t>=128&&t<=255},Arabic:function(t){return t>=1536&&t<=1791},\"Arabic Supplement\":function(t){return t>=1872&&t<=1919},\"Arabic Extended-A\":function(t){return t>=2208&&t<=2303},\"Hangul Jamo\":function(t){return t>=4352&&t<=4607},\"Unified Canadian Aboriginal Syllabics\":function(t){return t>=5120&&t<=5759},Khmer:function(t){return t>=6016&&t<=6143},\"Unified Canadian Aboriginal Syllabics Extended\":function(t){return t>=6320&&t<=6399},\"General Punctuation\":function(t){return t>=8192&&t<=8303},\"Letterlike Symbols\":function(t){return t>=8448&&t<=8527},\"Number Forms\":function(t){return t>=8528&&t<=8591},\"Miscellaneous Technical\":function(t){return t>=8960&&t<=9215},\"Control Pictures\":function(t){return t>=9216&&t<=9279},\"Optical Character Recognition\":function(t){return t>=9280&&t<=9311},\"Enclosed Alphanumerics\":function(t){return t>=9312&&t<=9471},\"Geometric Shapes\":function(t){return t>=9632&&t<=9727},\"Miscellaneous Symbols\":function(t){return t>=9728&&t<=9983},\"Miscellaneous Symbols and Arrows\":function(t){return t>=11008&&t<=11263},\"CJK Radicals Supplement\":function(t){return t>=11904&&t<=12031},\"Kangxi Radicals\":function(t){return t>=12032&&t<=12255},\"Ideographic Description Characters\":function(t){return t>=12272&&t<=12287},\"CJK Symbols and Punctuation\":function(t){return t>=12288&&t<=12351},Hiragana:function(t){return t>=12352&&t<=12447},Katakana:function(t){return t>=12448&&t<=12543},Bopomofo:function(t){return t>=12544&&t<=12591},\"Hangul Compatibility Jamo\":function(t){return t>=12592&&t<=12687},Kanbun:function(t){return t>=12688&&t<=12703},\"Bopomofo Extended\":function(t){return t>=12704&&t<=12735},\"CJK Strokes\":function(t){return t>=12736&&t<=12783},\"Katakana Phonetic Extensions\":function(t){return t>=12784&&t<=12799},\"Enclosed CJK Letters and Months\":function(t){return t>=12800&&t<=13055},\"CJK Compatibility\":function(t){return t>=13056&&t<=13311},\"CJK Unified Ideographs Extension A\":function(t){return t>=13312&&t<=19903},\"Yijing Hexagram Symbols\":function(t){return t>=19904&&t<=19967},\"CJK Unified Ideographs\":function(t){return t>=19968&&t<=40959},\"Yi Syllables\":function(t){return t>=40960&&t<=42127},\"Yi Radicals\":function(t){return t>=42128&&t<=42191},\"Hangul Jamo Extended-A\":function(t){return t>=43360&&t<=43391},\"Hangul Syllables\":function(t){return t>=44032&&t<=55215},\"Hangul Jamo Extended-B\":function(t){return t>=55216&&t<=55295},\"Private Use Area\":function(t){return t>=57344&&t<=63743},\"CJK Compatibility Ideographs\":function(t){return t>=63744&&t<=64255},\"Arabic Presentation Forms-A\":function(t){return t>=64336&&t<=65023},\"Vertical Forms\":function(t){return t>=65040&&t<=65055},\"CJK Compatibility Forms\":function(t){return t>=65072&&t<=65103},\"Small Form Variants\":function(t){return t>=65104&&t<=65135},\"Arabic Presentation Forms-B\":function(t){return t>=65136&&t<=65279},\"Halfwidth and Fullwidth Forms\":function(t){return t>=65280&&t<=65519}};function qn(t){for(var e=0,r=t;e<r.length;e+=1)if(Hn(r[e].charCodeAt(0)))return!0;return!1}function Hn(t){return!(746!==t&&747!==t&&(t<4352||!(Vn[\"Bopomofo Extended\"](t)||Vn.Bopomofo(t)||Vn[\"CJK Compatibility 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0===this.fadeDuration?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)},ii.prototype.getCrossfadeParameters=function(){var t=this.zoom,e=t-Math.floor(t),r=this.crossFadingFactor();return t>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:e+(1-e)*r}:{fromScale:.5,toScale:1,t:1-(1-r)*e}};var ai=function(t,e){this.property=t,this.value=e,this.expression=function(t,e){if(Or(t))return new Wr(t,e);if(Vr(t)){var r=Yr(t,e);if(\"error\"===r.result)throw new Error(r.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return r.value}var n=t;return\"string\"==typeof t&&\"color\"===e.type&&(n=Kt.parse(t)),{kind:\"constant\",evaluate:function(){return n}}}(void 0===e?t.specification.default:e,t.specification)};ai.prototype.isDataDriven=function(){return\"source\"===this.expression.kind||\"composite\"===this.expression.kind},ai.prototype.possiblyEvaluate=function(t,e,r){return this.property.possiblyEvaluate(this,t,e,r)};var oi=function(t){this.property=t,this.value=new ai(t,void 0)};oi.prototype.transitioned=function(t,e){return new li(this.property,this.value,e,u({},t.transition,this.transition),t.now)},oi.prototype.untransitioned=function(){return new li(this.property,this.value,null,{},0)};var si=function(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)};si.prototype.getValue=function(t){return x(this._values[t].value.value)},si.prototype.setValue=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new oi(this._values[t].property)),this._values[t].value=new ai(this._values[t].property,null===e?void 0:x(e))},si.prototype.getTransition=function(t){return x(this._values[t].transition)},si.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new oi(this._values[t].property)),this._values[t].transition=x(e)||void 0},si.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i);var a=this.getTransition(n);void 0!==a&&(t[n+\"-transition\"]=a)}return t},si.prototype.transitioned=function(t,e){for(var r=new ci(this._properties),n=0,i=Object.keys(this._values);n<i.length;n+=1){var a=i[n];r._values[a]=this._values[a].transitioned(t,e._values[a])}return r},si.prototype.untransitioned=function(){for(var t=new ci(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var li=function(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};li.prototype.possiblyEvaluate=function(t,e,r){var n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n<this.begin)return a.possiblyEvaluate(t,e,r);var o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var ci=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};ci.prototype.possiblyEvaluate=function(t,e,r){for(var n=new hi(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},ci.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1)if(this._values[e[t]].prior)return!0;return!1};var ui=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};ui.prototype.getValue=function(t){return x(this._values[t].value)},ui.prototype.setValue=function(t,e){this._values[t]=new ai(this._values[t].property,null===e?void 0:x(e))},ui.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},ui.prototype.possiblyEvaluate=function(t,e,r){for(var n=new hi(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var fi=function(t,e,r){this.property=t,this.value=e,this.parameters=r};fi.prototype.isConstant=function(){return\"constant\"===this.value.kind},fi.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},fi.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var hi=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};hi.prototype.get=function(t){return this._values[t]};var pi=function(t){this.specification=t};pi.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},pi.prototype.interpolate=function(t,e,r){var n=Ve[this.specification.type];return n?n(t,e,r):t};var di=function(t,e){this.specification=t,this.overrides=e};di.prototype.possiblyEvaluate=function(t,e,r,n){return new fi(this,\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?{kind:\"constant\",value:t.expression.evaluate(e,null,{},r,n)}:t.expression,e)},di.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new fi(this,{kind:\"constant\",value:void 0},t.parameters);var n=Ve[this.specification.type];return n?new fi(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},di.prototype.evaluate=function(t,e,r,n,i,a){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new fi(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a=\"resolvedImage\"===t.property.specification.type&&\"string\"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new fi(this,{kind:\"constant\",value:o},e)}if(\"camera\"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new fi(this,{kind:\"constant\",value:s},e)}return new fi(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if(\"source\"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(di),mi=function(t){this.specification=t};mi.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new ii(Math.floor(e.zoom-1),e)),t.expression.evaluate(new ii(Math.floor(e.zoom),e)),t.expression.evaluate(new ii(Math.floor(e.zoom+1),e)),e)}},mi.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},mi.prototype.interpolate=function(t){return t};var vi=function(t){this.specification=t};vi.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},vi.prototype.interpolate=function(){return!1};var yi=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new ai(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new oi(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};Dn(\"DataDrivenProperty\",di),Dn(\"DataConstantProperty\",pi),Dn(\"CrossFadedDataDrivenProperty\",gi),Dn(\"CrossFadedProperty\",mi),Dn(\"ColorRampProperty\",vi);var xi=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter={filter:function(){return!0},needGeometry:!1},\"custom\"!==e.type&&(this.metadata=(e=e).metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,\"background\"!==e.type&&(this.source=e.source,this.sourceLayer=e[\"source-layer\"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new ui(r.layout)),r.paint)){for(var n in this._transitionablePaint=new si(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var i in e.layout)this.setLayoutProperty(i,e.layout[i],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new hi(r.paint)}}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){void 0===r&&(r={}),null!=e&&this._validate(En,\"layers.\"+this.id+\".layout.\"+t,t,e,r)||(\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e)},e.prototype.getPaintProperty=function(t){return m(t,\"-transition\")?this._transitionablePaint.getTransition(t.slice(0,-\"-transition\".length)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e&&this._validate(Sn,\"layers.\"+this.id+\".paint.\"+t,t,e,r))return!1;if(m(t,\"-transition\"))return this._transitionablePaint.setTransition(t.slice(0,-\"-transition\".length),e||void 0),!1;var n=this._transitionablePaint._values[t],i=\"cross-faded-data-driven\"===n.property.specification[\"property-type\"],a=n.value.isDataDriven(),o=n.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var s=this._transitionablePaint._values[t].value;return s.isDataDriven()||a||i||this._handleOverridablePaintPropertyUpdate(t,o,s)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),y(t,(function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&Cn(this,t.call(Mn,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:At,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof fi&&Lr(e.property.specification)&&(\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent)return!0}return!1},e}(Mt),bi={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},_i=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},wi=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Ti(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i=bi[t.type].BYTES_PER_ELEMENT,a=r=ki(r,Math.max(e,i)),o=t.components||1;return n=Math.max(n,i),r+=i*o,{name:t.name,type:t.type,components:o,offset:a}})),size:ki(r,Math.max(n,e)),alignment:e}}function ki(t,e){return Math.ceil(t/e)*e}wi.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},wi.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},wi.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},wi.prototype.clear=function(){this.length=0},wi.prototype.resize=function(t){this.reserve(t),this.length=t},wi.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},wi.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var Mi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(wi);Mi.prototype.bytesPerElement=4,Dn(\"StructArrayLayout2i4\",Mi);var Ai=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,this.int16[a+3]=i,t},e}(wi);Ai.prototype.bytesPerElement=8,Dn(\"StructArrayLayout4i8\",Ai);var Si=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(wi);Si.prototype.bytesPerElement=12,Dn(\"StructArrayLayout2i4i12\",Si);var Ei=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(wi);Ei.prototype.bytesPerElement=8,Dn(\"StructArrayLayout2i4ub8\",Ei);var Ci=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c){var u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,i,a,o,s,l,c)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u){var f=9*t,h=18*t;return this.uint16[f+0]=e,this.uint16[f+1]=r,this.uint16[f+2]=n,this.uint16[f+3]=i,this.uint16[f+4]=a,this.uint16[f+5]=o,this.uint16[f+6]=s,this.uint16[f+7]=l,this.uint8[h+16]=c,this.uint8[h+17]=u,t},e}(wi);Ci.prototype.bytesPerElement=18,Dn(\"StructArrayLayout8ui2ub18\",Ci);var Li=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f){var h=this.length;return this.resize(h+1),this.emplace(h,t,e,r,n,i,a,o,s,l,c,u,f)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=i,this.uint16[p+4]=a,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=c,this.int16[p+9]=u,this.int16[p+10]=f,this.int16[p+11]=h,t},e}(wi);Li.prototype.bytesPerElement=24,Dn(\"StructArrayLayout4i4ui4i24\",Li);var Ii=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t},e}(wi);Ii.prototype.bytesPerElement=12,Dn(\"StructArrayLayout3f12\",Ii);var Pi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){return this.uint32[1*t+0]=e,t},e}(wi);Pi.prototype.bytesPerElement=4,Dn(\"StructArrayLayout1ul4\",Pi);var zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l){var c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,i,a,o,s,l)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c){var u=10*t,f=5*t;return this.int16[u+0]=e,this.int16[u+1]=r,this.int16[u+2]=n,this.int16[u+3]=i,this.int16[u+4]=a,this.int16[u+5]=o,this.uint32[f+3]=s,this.uint16[u+8]=l,this.uint16[u+9]=c,t},e}(wi);zi.prototype.bytesPerElement=20,Dn(\"StructArrayLayout6i1ul2ui20\",zi);var Oi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(wi);Oi.prototype.bytesPerElement=12,Dn(\"StructArrayLayout2i2i2i12\",Oi);var Di=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(wi);Di.prototype.bytesPerElement=16,Dn(\"StructArrayLayout2f1f2i16\",Di);var Ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(wi);Ri.prototype.bytesPerElement=12,Dn(\"StructArrayLayout2ub2f12\",Ri);var Fi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.uint16[i+0]=e,this.uint16[i+1]=r,this.uint16[i+2]=n,t},e}(wi);Fi.prototype.bytesPerElement=6,Dn(\"StructArrayLayout3ui6\",Fi);var Bi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m){var v=this.length;return this.resize(v+1),this.emplace(v,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v){var y=24*t,x=12*t,b=48*t;return this.int16[y+0]=e,this.int16[y+1]=r,this.uint16[y+2]=n,this.uint16[y+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[y+10]=l,this.uint16[y+11]=c,this.uint16[y+12]=u,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=g,this.uint32[x+10]=m,this.int16[y+22]=v,t},e}(wi);Bi.prototype.bytesPerElement=48,Dn(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",Bi);var Ni=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,M,A,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,M,A,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,M,A,S,E){var C=34*t,L=17*t;return this.int16[C+0]=e,this.int16[C+1]=r,this.int16[C+2]=n,this.int16[C+3]=i,this.int16[C+4]=a,this.int16[C+5]=o,this.int16[C+6]=s,this.int16[C+7]=l,this.uint16[C+8]=c,this.uint16[C+9]=u,this.uint16[C+10]=f,this.uint16[C+11]=h,this.uint16[C+12]=p,this.uint16[C+13]=d,this.uint16[C+14]=g,this.uint16[C+15]=m,this.uint16[C+16]=v,this.uint16[C+17]=y,this.uint16[C+18]=x,this.uint16[C+19]=b,this.uint16[C+20]=_,this.uint16[C+21]=w,this.uint16[C+22]=T,this.uint32[L+12]=k,this.float32[L+13]=M,this.float32[L+14]=A,this.float32[L+15]=S,this.float32[L+16]=E,t},e}(wi);Ni.prototype.bytesPerElement=68,Dn(\"StructArrayLayout8i15ui1ul4f68\",Ni);var ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){return this.float32[1*t+0]=e,t},e}(wi);ji.prototype.bytesPerElement=4,Dn(\"StructArrayLayout1f4\",ji);var Ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(wi);Ui.prototype.bytesPerElement=6,Dn(\"StructArrayLayout3i6\",Ui);var 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a=t;a<e;a++)this.paintVertexArray.emplace(a,r);this.maxValue=Math.max(this.maxValue,Math.abs(r))}},Sa.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},Sa.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()};var Ea=function(t,e,r,n,i,a){this.expression=t,this.uniformNames=e.map((function(t){return\"u_\"+t+\"_t\"})),this.type=r,this.useIntegerZoom=n,this.zoom=i,this.maxValue=0,this.paintVertexAttributes=e.map((function(t){return{name:\"a_\"+t,type:\"Float32\",components:\"color\"===r?4:2,offset:0}})),this.paintVertexArray=new a};Ea.prototype.populatePaintArray=function(t,e,r,n,i){var a=this.expression.evaluate(new ii(this.zoom),e,{},n,[],i),o=this.expression.evaluate(new ii(this.zoom+1),e,{},n,[],i),s=this.paintVertexArray.length;this.paintVertexArray.resize(t),this._setPaintValue(s,t,a,o)},Ea.prototype.updatePaintArray=function(t,e,r,n){var i=this.expression.evaluate({zoom:this.zoom},r,n),a=this.expression.evaluate({zoom:this.zoom+1},r,n);this._setPaintValue(t,e,i,a)},Ea.prototype._setPaintValue=function(t,e,r,n){if(\"color\"===this.type)for(var i=ka(r),a=ka(n),o=t;o<e;o++)this.paintVertexArray.emplace(o,i[0],i[1],a[0],a[1]);else{for(var s=t;s<e;s++)this.paintVertexArray.emplace(s,r,n);this.maxValue=Math.max(this.maxValue,Math.abs(r),Math.abs(n))}},Ea.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},Ea.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()},Ea.prototype.setUniform=function(t,e){var r=this.useIntegerZoom?Math.floor(e.zoom):e.zoom,n=l(this.expression.interpolationFactor(r,this.zoom,this.zoom+1),0,1);t.set(n)},Ea.prototype.getBinding=function(t,e,r){return new va(t,e)};var Ca=function(t,e,r,n,i,a){this.expression=t,this.type=e,this.useIntegerZoom=r,this.zoom=n,this.layerId=a,this.zoomInPaintVertexArray=new i,this.zoomOutPaintVertexArray=new i};Ca.prototype.populatePaintArray=function(t,e,r){var n=this.zoomInPaintVertexArray.length;this.zoomInPaintVertexArray.resize(t),this.zoomOutPaintVertexArray.resize(t),this._setPaintValues(n,t,e.patterns&&e.patterns[this.layerId],r)},Ca.prototype.updatePaintArray=function(t,e,r,n,i){this._setPaintValues(t,e,r.patterns&&r.patterns[this.layerId],i)},Ca.prototype._setPaintValues=function(t,e,r,n){if(n&&r){var i=n[r.min],a=n[r.mid],o=n[r.max];if(i&&a&&o)for(var s=t;s<e;s++)this.zoomInPaintVertexArray.emplace(s,a.tl[0],a.tl[1],a.br[0],a.br[1],i.tl[0],i.tl[1],i.br[0],i.br[1],a.pixelRatio,i.pixelRatio),this.zoomOutPaintVertexArray.emplace(s,a.tl[0],a.tl[1],a.br[0],a.br[1],o.tl[0],o.tl[1],o.br[0],o.br[1],a.pixelRatio,o.pixelRatio)}},Ca.prototype.upload=function(t){this.zoomInPaintVertexArray&&this.zoomInPaintVertexArray.arrayBuffer&&this.zoomOutPaintVertexArray&&this.zoomOutPaintVertexArray.arrayBuffer&&(this.zoomInPaintVertexBuffer=t.createVertexBuffer(this.zoomInPaintVertexArray,oa.members,this.expression.isStateDependent),this.zoomOutPaintVertexBuffer=t.createVertexBuffer(this.zoomOutPaintVertexArray,oa.members,this.expression.isStateDependent))},Ca.prototype.destroy=function(){this.zoomOutPaintVertexBuffer&&this.zoomOutPaintVertexBuffer.destroy(),this.zoomInPaintVertexBuffer&&this.zoomInPaintVertexBuffer.destroy()};var La=function(t,e,r,n){this.binders={},this.layoutAttributes=n,this._buffers=[];var i=[];for(var a in t.paint._values)if(r(a)){var o=t.paint.get(a);if(o instanceof fi&&Lr(o.property.specification)){var s=Pa(a,t.type),l=o.value,c=o.property.specification.type,u=o.property.useIntegerZoom,f=o.property.specification[\"property-type\"],h=\"cross-faded\"===f||\"cross-faded-data-driven\"===f;if(\"constant\"===l.kind)this.binders[a]=h?new Aa(l.value,s):new Ma(l.value,s,c),i.push(\"/u_\"+a);else if(\"source\"===l.kind||h){var p=za(a,c,\"source\");this.binders[a]=h?new Ca(l,c,u,e,p,t.id):new Sa(l,s,c,p),i.push(\"/a_\"+a)}else{var d=za(a,c,\"composite\");this.binders[a]=new Ea(l,s,c,u,e,d),i.push(\"/z_\"+a)}}}this.cacheKey=i.sort().join(\"\")};La.prototype.getMaxValue=function(t){var e=this.binders[t];return e instanceof Sa||e instanceof Ea?e.maxValue:0},La.prototype.populatePaintArrays=function(t,e,r,n,i){for(var a in this.binders){var o=this.binders[a];(o instanceof Sa||o instanceof Ea||o instanceof Ca)&&o.populatePaintArray(t,e,r,n,i)}},La.prototype.setConstantPatternPositions=function(t,e){for(var r in this.binders){var n=this.binders[r];n instanceof Aa&&n.setConstantPatternPositions(t,e)}},La.prototype.updatePaintArrays=function(t,e,r,n,i){var a=!1;for(var o in t)for(var s=0,l=e.getPositions(o);s<l.length;s+=1){var c=l[s],u=r.feature(c.index);for(var f in this.binders){var h=this.binders[f];if((h instanceof Sa||h instanceof Ea||h instanceof Ca)&&!0===h.expression.isStateDependent){var p=n.paint.get(f);h.expression=p.value,h.updatePaintArray(c.start,c.end,u,t[o],i),a=!0}}}return a},La.prototype.defines=function(){var t=[];for(var e in this.binders){var r=this.binders[e];(r instanceof Ma||r instanceof Aa)&&t.push.apply(t,r.uniformNames.map((function(t){return\"#define HAS_UNIFORM_\"+t})))}return t},La.prototype.getPaintVertexBuffers=function(){return this._buffers},La.prototype.getUniforms=function(t,e){var r=[];for(var n in this.binders){var i=this.binders[n];if(i instanceof Ma||i instanceof Aa||i instanceof Ea)for(var a=0,o=i.uniformNames;a<o.length;a+=1){var s=o[a];if(e[s]){var l=i.getBinding(t,e[s],s);r.push({name:s,property:n,binding:l})}}}return r},La.prototype.setUniforms=function(t,e,r,n){for(var i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.name,l=o.property;this.binders[l].setUniform(o.binding,n,r.get(l),s)}},La.prototype.updatePaintBuffers=function(t){for(var e in this._buffers=[],this.binders){var r=this.binders[e];if(t&&r instanceof Ca){var n=2===t.fromScale?r.zoomInPaintVertexBuffer:r.zoomOutPaintVertexBuffer;n&&this._buffers.push(n)}else(r instanceof Sa||r instanceof Ea)&&r.paintVertexBuffer&&this._buffers.push(r.paintVertexBuffer)}},La.prototype.upload=function(t){for(var e in this.binders){var r=this.binders[e];(r instanceof Sa||r instanceof Ea||r instanceof Ca)&&r.upload(t)}this.updatePaintBuffers()},La.prototype.destroy=function(){for(var t in this.binders){var e=this.binders[t];(e instanceof Sa||e instanceof Ea||e instanceof Ca)&&e.destroy()}};var Ia=function(t,e,r,n){void 0===n&&(n=function(){return!0}),this.programConfigurations={};for(var i=0,a=e;i<a.length;i+=1){var o=a[i];this.programConfigurations[o.id]=new La(o,r,n,t)}this.needsUpload=!1,this._featureMap=new fa,this._bufferOffset=0};function Pa(t,e){return{\"text-opacity\":[\"opacity\"],\"icon-opacity\":[\"opacity\"],\"text-color\":[\"fill_color\"],\"icon-color\":[\"fill_color\"],\"text-halo-color\":[\"halo_color\"],\"icon-halo-color\":[\"halo_color\"],\"text-halo-blur\":[\"halo_blur\"],\"icon-halo-blur\":[\"halo_blur\"],\"text-halo-width\":[\"halo_width\"],\"icon-halo-width\":[\"halo_width\"],\"line-gap-width\":[\"gapwidth\"],\"line-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"],\"fill-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"],\"fill-extrusion-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"]}[t]||[t.replace(e+\"-\",\"\").replace(/-/g,\"_\")]}function za(t,e,r){var n={color:{source:Gi,composite:Yi},number:{source:ji,composite:Gi}},i=function(t){return{\"line-pattern\":{source:Ci,composite:Ci},\"fill-pattern\":{source:Ci,composite:Ci},\"fill-extrusion-pattern\":{source:Ci,composite:Ci}}[t]}(t);return i&&i[r]||n[e][r]}Ia.prototype.populatePaintArrays=function(t,e,r,n,i,a){for(var o in this.programConfigurations)this.programConfigurations[o].populatePaintArrays(t,e,n,i,a);void 0!==e.id&&this._featureMap.add(e.id,r,this._bufferOffset,t),this._bufferOffset=t,this.needsUpload=!0},Ia.prototype.updatePaintArrays=function(t,e,r,n){for(var i=0,a=r;i<a.length;i+=1){var o=a[i];this.needsUpload=this.programConfigurations[o.id].updatePaintArrays(t,this._featureMap,e,o,n)||this.needsUpload}},Ia.prototype.get=function(t){return this.programConfigurations[t]},Ia.prototype.upload=function(t){if(this.needsUpload){for(var e in this.programConfigurations)this.programConfigurations[e].upload(t);this.needsUpload=!1}},Ia.prototype.destroy=function(){for(var t in this.programConfigurations)this.programConfigurations[t].destroy()},Dn(\"ConstantBinder\",Ma),Dn(\"CrossFadedConstantBinder\",Aa),Dn(\"SourceExpressionBinder\",Sa),Dn(\"CrossFadedCompositeBinder\",Ca),Dn(\"CompositeExpressionBinder\",Ea),Dn(\"ProgramConfiguration\",La,{omit:[\"_buffers\"]}),Dn(\"ProgramConfigurationSet\",Ia);var Oa={min:-1*Math.pow(2,14),max:Math.pow(2,14)-1};function Da(t){for(var e=8192/t.extent,r=t.loadGeometry(),n=0;n<r.length;n++)for(var i=r[n],a=0;a<i.length;a++){var o=i[a];o.x=Math.round(o.x*e),o.y=Math.round(o.y*e),(o.x<Oa.min||o.x>Oa.max||o.y<Oa.min||o.y>Oa.max)&&(_(\"Geometry exceeds allowed extent, reduce your vector tile buffer size\"),o.x=l(o.x,Oa.min,Oa.max),o.y=l(o.y,Oa.min,Oa.max))}return r}function Ra(t,e,r,n,i){t.emplaceBack(2*e+(n+1)/2,2*r+(i+1)/2)}var Fa=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Mi,this.indexArray=new Fi,this.segments=new ia,this.programConfigurations=new Ia(na,t.layers,t.zoom),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function Ba(t,e){for(var r=0;r<t.length;r++)if(Wa(e,t[r]))return!0;for(var n=0;n<e.length;n++)if(Wa(t,e[n]))return!0;return!!Va(t,e)}function Na(t,e,r){return!!Wa(t,e)||!!Ha(e,t,r)}function ja(t,e){if(1===t.length)return Ya(e,t[0]);for(var r=0;r<e.length;r++)for(var n=e[r],i=0;i<n.length;i++)if(Wa(t,n[i]))return!0;for(var a=0;a<t.length;a++)if(Ya(e,t[a]))return!0;for(var o=0;o<e.length;o++)if(Va(t,e[o]))return!0;return!1}function Ua(t,e,r){if(t.length>1){if(Va(t,e))return!0;for(var n=0;n<e.length;n++)if(Ha(e[n],t,r))return!0}for(var i=0;i<t.length;i++)if(Ha(t[i],e,r))return!0;return!1}function Va(t,e){if(0===t.length||0===e.length)return!1;for(var r=0;r<t.length-1;r++)for(var n=t[r],i=t[r+1],a=0;a<e.length-1;a++)if(qa(n,i,e[a],e[a+1]))return!0;return!1}function qa(t,e,r,n){return w(t,r,n)!==w(e,r,n)&&w(t,e,r)!==w(t,e,n)}function Ha(t,e,r){var n=r*r;if(1===e.length)return t.distSqr(e[0])<n;for(var i=1;i<e.length;i++)if(Ga(t,e[i-1],e[i])<n)return!0;return!1}function Ga(t,e,r){var n=e.distSqr(r);if(0===n)return t.distSqr(e);var i=((t.x-e.x)*(r.x-e.x)+(t.y-e.y)*(r.y-e.y))/n;return t.distSqr(i<0?e:i>1?r:r.sub(e)._mult(i)._add(e))}function Ya(t,e){for(var r,n,i,a=!1,o=0;o<t.length;o++)for(var s=0,l=(r=t[o]).length-1;s<r.length;l=s++)(n=r[s]).y>e.y!=(i=r[l]).y>e.y&&e.x<(i.x-n.x)*(e.y-n.y)/(i.y-n.y)+n.x&&(a=!a);return a}function Wa(t,e){for(var r=!1,n=0,i=t.length-1;n<t.length;i=n++){var a=t[n],o=t[i];a.y>e.y!=o.y>e.y&&e.x<(o.x-a.x)*(e.y-a.y)/(o.y-a.y)+a.x&&(r=!r)}return r}function Xa(t,e,r){var n=r[0],i=r[2];if(t.x<n.x&&e.x<n.x||t.x>i.x&&e.x>i.x||t.y<n.y&&e.y<n.y||t.y>i.y&&e.y>i.y)return!1;var a=w(t,e,r[0]);return a!==w(t,e,r[1])||a!==w(t,e,r[2])||a!==w(t,e,r[3])}function Za(t,e,r){var n=e.paint.get(t).value;return\"constant\"===n.kind?n.value:r.programConfigurations.get(e.id).getMaxValue(t)}function Ja(t){return Math.sqrt(t[0]*t[0]+t[1]*t[1])}function Ka(t,e,r,n,a){if(!e[0]&&!e[1])return t;var o=i.convert(e)._mult(a);\"viewport\"===r&&o._rotate(-n);for(var s=[],l=0;l<t.length;l++)s.push(t[l].sub(o));return s}Fa.prototype.populate=function(t,e,r){var n=this.layers[0],i=[],a=null;\"circle\"===n.type&&(a=n.layout.get(\"circle-sort-key\"));for(var o=0,s=t;o<s.length;o+=1){var l=s[o],c=l.feature,u=l.id,f=l.index,h=l.sourceLayerIndex,p=this.layers[0]._featureFilter.needGeometry,d={type:c.type,id:u,properties:c.properties,geometry:p?Da(c):[]};if(this.layers[0]._featureFilter.filter(new ii(this.zoom),d,r)){p||(d.geometry=Da(c));var g=a?a.evaluate(d,{},r):void 0;i.push({id:u,properties:c.properties,type:c.type,sourceLayerIndex:h,index:f,geometry:d.geometry,patterns:{},sortKey:g})}}a&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var m=0,v=i;m<v.length;m+=1){var y=v[m],x=y.geometry,b=y.index,_=y.sourceLayerIndex,w=t[b].feature;this.addFeature(y,x,b,r),e.featureIndex.insert(w,x,b,_,this.index)}},Fa.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Fa.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Fa.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Fa.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,na),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Fa.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Fa.prototype.addFeature=function(t,e,r,n){for(var i=0,a=e;i<a.length;i+=1)for(var o=0,s=a[i];o<s.length;o+=1){var l=s[o],c=l.x,u=l.y;if(!(c<0||c>=8192||u<0||u>=8192)){var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray,t.sortKey),h=f.vertexLength;Ra(this.layoutVertexArray,c,u,-1,-1),Ra(this.layoutVertexArray,c,u,1,-1),Ra(this.layoutVertexArray,c,u,1,1),Ra(this.layoutVertexArray,c,u,-1,1),this.indexArray.emplaceBack(h,h+1,h+2),this.indexArray.emplaceBack(h,h+3,h+2),f.vertexLength+=4,f.primitiveLength+=2}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,{},n)},Dn(\"CircleBucket\",Fa,{omit:[\"layers\"]});var Qa=new yi({\"circle-sort-key\":new di(At.layout_circle[\"circle-sort-key\"])}),$a={paint:new yi({\"circle-radius\":new di(At.paint_circle[\"circle-radius\"]),\"circle-color\":new di(At.paint_circle[\"circle-color\"]),\"circle-blur\":new di(At.paint_circle[\"circle-blur\"]),\"circle-opacity\":new di(At.paint_circle[\"circle-opacity\"]),\"circle-translate\":new pi(At.paint_circle[\"circle-translate\"]),\"circle-translate-anchor\":new 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2:for(n=0;n<l.length;n++)u(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=us(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}return r&&i.push(r),i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)u(l[n][i])}1===l.length?l=l[0]:c=\"Multi\"+c;var h={type:\"Feature\",geometry:{type:c,coordinates:l},properties:this.properties};return\"id\"in this&&(h.id=this.id),h};var fs=hs;function hs(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields(ps,this,e),this.length=this._features.length}function ps(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){for(var e=null,r=t.readVarint()+t.pos;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function ds(t,e,r){if(3===t){var n=new fs(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}hs.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new ss(this._pbf,e,this.extent,this._keys,this._values)};var gs={VectorTile:function(t,e){this.layers=t.readFields(ds,{},e)},VectorTileFeature:ss,VectorTileLayer:fs},ms=gs.VectorTileFeature.types,vs=Math.pow(2,13);function ys(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*vs)+o,i*vs*2,a*vs*2,Math.round(s))}var xs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Si,this.indexArray=new Fi,this.programConfigurations=new Ia(os,t.layers,t.zoom),this.segments=new ia,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function bs(t,e){return t.x===e.x&&(t.x<0||t.x>8192)||t.y===e.y&&(t.y<0||t.y>8192)}xs.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=ts(\"fill-extrusion\",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,c=a.sourceLayerIndex,u=this.layers[0]._featureFilter.needGeometry,f={type:o.type,id:s,properties:o.properties,geometry:u?Da(o):[]};if(this.layers[0]._featureFilter.filter(new ii(this.zoom),f,r)){var h={id:s,sourceLayerIndex:c,index:l,geometry:u?f.geometry:Da(o),properties:o.properties,type:o.type,patterns:{}};void 0!==o.id&&(h.id=o.id),this.hasPattern?this.features.push(es(\"fill-extrusion\",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,c,this.index,!0)}}},xs.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},xs.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},xs.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},xs.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},xs.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,os),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},xs.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},xs.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=Qo(e,500);a<o.length;a+=1){for(var s=o[a],l=0,c=0,u=s;c<u.length;c+=1)l+=u[c].length;for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!((P=d).every((function(t){return t.x<0}))||P.every((function(t){return t.x>8192}))||P.every((function(t){return t.y<0}))||P.every((function(t){return t.y>8192}))))for(var g=0,m=0;m<d.length;m++){var v=d[m];if(m>=1){var y=d[m-1];if(!bs(v,y)){f.vertexLength+4>ia.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=v.sub(y)._perp()._unit(),b=y.dist(v);g+b>32768&&(g=0),ys(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,0,g),ys(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,1,g),ys(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,g+=b),ys(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,g);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>ia.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),\"Polygon\"===ms[t.type]){for(var w=[],T=[],k=f.vertexLength,M=0,A=s;M<A.length;M+=1){var S=A[M];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var C=S[E];ys(this.layoutVertexArray,C.x,C.y,0,0,1,1,0),w.push(C.x),w.push(C.y)}}}for(var 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a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),c=o.sub(i),u=Ts(s,s),f=Ts(s,l),h=Ts(l,l),p=Ts(c,s),d=Ts(c,l),g=u*h-f*f,m=(h*p-f*d)/g,v=(u*d-f*p)/g,y=i.z*(1-m-v)+r.z*m+a.z*v;if(isFinite(y))return y}return 1/0}for(var x=1/0,b=0,_=e;b<_.length;b+=1)x=Math.min(x,_[b].z);return x}var Ms=Ti([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,As=gs.VectorTileFeature.types,Ss=Math.cos(Math.PI/180*37.5),Es=Math.pow(2,14)/.5,Cs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new Ei,this.indexArray=new Fi,this.programConfigurations=new Ia(Ms,t.layers,t.zoom),this.segments=new ia,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return 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a=this.layers[0].layout,o=a.get(\"line-join\").evaluate(t,{}),s=a.get(\"line-cap\"),l=a.get(\"line-miter-limit\"),c=a.get(\"line-round-limit\"),u=0,f=e;u<f.length;u+=1)this.addLine(f[u],t,o,s,l,c);this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},Cs.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty(\"mapbox_clip_start\")&&e.properties.hasOwnProperty(\"mapbox_clip_end\")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance()}for(var s=\"Polygon\"===As[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var c=0;c<l-1&&t[c].equals(t[c+1]);)c++;if(!(l<(s?3:2))){\"bevel\"===r&&(i=1.05);var u,f=this.overscaling<=16?122880/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 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o=e.y*n-e.x,s=-e.y-e.x*n;this.addHalfVertex(t,e.x+e.y*r,e.y-e.x*r,a,!1,r,i),this.addHalfVertex(t,o,s,a,!0,-n,i),this.distance>Es/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,i,a))},Cs.prototype.addHalfVertex=function(t,e,r,n,i,a,o){var s=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((t.x<<1)+(n?1:0),(t.y<<1)+(i?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===a?0:a<0?-1:1)|(63&s)<<2,s>>6);var l=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,l),o.primitiveLength++),i?this.e2=l:this.e1=l},Cs.prototype.updateScaledDistance=function(){this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(Es-1):this.distance},Cs.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},Dn(\"LineBucket\",Cs,{omit:[\"layers\",\"patternFeatures\"]});var Ls=new yi({\"line-cap\":new 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n,i,a=0;a<e.length;a++){if((n=e.charCodeAt(a))>55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else i&&(t[r++]=239,t[r++]=191,t[r++]=189,i=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&Zs(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),qs(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),qs(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&Zs(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,Gs.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,Js,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,Ks,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,tl,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,Qs,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,$s,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,el,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,rl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,nl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,il,e)},writeBytesField:function(t,e){this.writeTag(t,Gs.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,Gs.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,Gs.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,Gs.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,Gs.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,Gs.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,Gs.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,Gs.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,Gs.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,Gs.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};var hl=function(t,e){var r=e.pixelRatio,n=e.version,i=e.stretchX,a=e.stretchY,o=e.content;this.paddedRect=t,this.pixelRatio=r,this.stretchX=i,this.stretchY=a,this.content=o,this.version=n},pl={tl:{configurable:!0},br:{configurable:!0},tlbr:{configurable:!0},displaySize:{configurable:!0}};pl.tl.get=function(){return[this.paddedRect.x+1,this.paddedRect.y+1]},pl.br.get=function(){return[this.paddedRect.x+this.paddedRect.w-1,this.paddedRect.y+this.paddedRect.h-1]},pl.tlbr.get=function(){return this.tl.concat(this.br)},pl.displaySize.get=function(){return[(this.paddedRect.w-2)/this.pixelRatio,(this.paddedRect.h-2)/this.pixelRatio]},Object.defineProperties(hl.prototype,pl);var dl=function(t,e){var r={},n={};this.haveRenderCallbacks=[];var i=[];this.addImages(t,r,i),this.addImages(e,n,i);var a=fl(i),o=new po({width:a.w||1,height:a.h||1});for(var s in t){var l=t[s],c=r[s].paddedRect;po.copy(l.data,o,{x:0,y:0},{x:c.x+1,y:c.y+1},l.data)}for(var u in e){var f=e[u],h=n[u].paddedRect,p=h.x+1,d=h.y+1,g=f.data.width,m=f.data.height;po.copy(f.data,o,{x:0,y:0},{x:p,y:d},f.data),po.copy(f.data,o,{x:0,y:m-1},{x:p,y:d-1},{width:g,height:1}),po.copy(f.data,o,{x:0,y:0},{x:p,y:d+m},{width:g,height:1}),po.copy(f.data,o,{x:g-1,y:0},{x:p-1,y:d},{width:1,height:m}),po.copy(f.data,o,{x:0,y:0},{x:p+g,y:d},{width:1,height:m})}this.image=o,this.iconPositions=r,this.patternPositions=n};dl.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2,h:i.data.height+2};r.push(a),e[n]=new hl(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},dl.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},dl.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl;r.update(e.data,void 0,{x:n[0],y:n[1]})}},Dn(\"ImagePosition\",hl),Dn(\"ImageAtlas\",dl);var gl={horizontal:1,vertical:2,horizontalOnly:3},ml=function(){this.scale=1,this.fontStack=\"\",this.imageName=null};ml.forText=function(t,e){var r=new ml;return r.scale=t||1,r.fontStack=e,r},ml.forImage=function(t){var e=new ml;return e.imageName=t,e};var vl=function(){this.text=\"\",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function yl(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g){var m,v=vl.fromFeature(t,i);f===gl.vertical&&v.verticalizePunctuation();var y=ni.processBidirectionalText,x=ni.processStyledBidirectionalText;if(y&&1===v.sections.length){m=[];for(var b=0,_=y(v.toString(),Ml(v,c,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new vl;T.text=w,T.sections=v.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);m.push(T)}}else if(x){m=[];for(var M=0,A=x(v.text,v.sectionIndex,Ml(v,c,a,e,n,p,d));M<A.length;M+=1){var S=A[M],E=new vl;E.text=S[0],E.sectionIndex=S[1],E.sections=v.sections,m.push(E)}}else m=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(v,Ml(v,c,a,e,n,p,d));var C=[],L={positionedLines:C,text:v.toString(),top:u[1],bottom:u[1],left:u[0],right:u[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=0,p=-17,d=0,g=0,m=\"right\"===s?1:\"left\"===s?0:.5,v=0,y=0,x=i;y<x.length;y+=1){var b=x[y];b.trim();var _=b.getMaxScale(),w=24*(_-1),T={positionedGlyphs:[],lineOffset:0};t.positionedLines[v]=T;var k=T.positionedGlyphs,M=0;if(b.length()){for(var A=0;A<b.length();A++){var S=b.getSection(A),E=b.getSectionIndex(A),C=b.getCharCode(A),L=0,I=null,P=null,z=null,O=24,D=!(l===gl.horizontal||!u&&!Hn(C)||u&&(xl[C]||(H=C,Vn.Arabic(H)||Vn[\"Arabic Supplement\"](H)||Vn[\"Arabic Extended-A\"](H)||Vn[\"Arabic Presentation Forms-A\"](H)||Vn[\"Arabic Presentation Forms-B\"](H))));if(S.imageName){var R=n[S.imageName];if(!R)continue;z=S.imageName,t.iconsInText=t.iconsInText||!0,P=R.paddedRect;var F=R.displaySize;S.scale=24*S.scale/f,L=w+(24-F[1]*S.scale),O=(I={width:F[0],height:F[1],left:1,top:-3,advance:D?F[1]:F[0]}).advance;var B=D?F[0]*S.scale-24*_:F[1]*S.scale-24*_;B>0&&B>M&&(M=B)}else{var N=r[S.fontStack],j=N&&N[C];if(j&&j.rect)P=j.rect,I=j.metrics;else{var U=e[S.fontStack],V=U&&U[C];if(!V)continue;I=V.metrics}L=24*(_-S.scale)}D?(t.verticalizable=!0,k.push({glyph:C,imageName:z,x:h,y:p+L,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:I,rect:P}),h+=O*S.scale+c):(k.push({glyph:C,imageName:z,x:h,y:p+L,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:I,rect:P}),h+=I.advance*S.scale+c)}0!==k.length&&(d=Math.max(h-c,d),Sl(k,0,k.length-1,m,M)),h=0;var q=a*_+M;T.lineOffset=Math.max(M,w),p+=q,g=Math.max(q,g),++v}else p+=a,++v}var H,G=p- -17,Y=Al(o),W=Y.horizontalAlign,X=Y.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var c,u=(e-r)*i;c=a!==o?-s*n- -17:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=0,d=h[f].positionedGlyphs;p<d.length;p+=1){var g=d[p];g.x+=u,g.y+=c}})(t.positionedLines,m,W,X,d,g,a,G,i.length),t.top+=-X*G,t.bottom=t.top+G,t.left+=-W*d,t.right=t.left+d}(L,e,r,n,m,o,s,l,f,c,h,g),!function(t){for(var e=0,r=t;e<r.length;e+=1)if(0!==r[e].positionedGlyphs.length)return!1;return!0}(C)&&L}vl.fromFeature=function(t,e){for(var r=new vl,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},vl.prototype.length=function(){return this.text.length},vl.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},vl.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},vl.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},vl.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;e+=n&&Gn(n)&&!Us[t[r+1]]||i&&Gn(i)&&!Us[t[r-1]]||!Us[t[r]]?t[r]:Us[t[r]]}return e}(this.text)},vl.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&xl[this.text.charCodeAt(e)];e++)t++;for(var r=this.text.length,n=this.text.length-1;n>=0&&n>=t&&xl[this.text.charCodeAt(n)];n--)r--;this.text=this.text.substring(t,r),this.sectionIndex=this.sectionIndex.slice(t,r)},vl.prototype.substring=function(t,e){var r=new vl;return r.text=this.text.substring(t,e),r.sectionIndex=this.sectionIndex.slice(t,e),r.sections=this.sections,r},vl.prototype.toString=function(){return this.text},vl.prototype.getMaxScale=function(){var t=this;return this.sectionIndex.reduce((function(e,r){return Math.max(e,t.sections[r].scale)}),0)},vl.prototype.addTextSection=function(t,e){this.text+=t.text,this.sections.push(ml.forText(t.scale,t.fontStack||e));for(var r=this.sections.length-1,n=0;n<t.text.length;++n)this.sectionIndex.push(r)},vl.prototype.addImageSection=function(t){var e=t.image?t.image.name:\"\";if(0!==e.length){var r=this.getNextImageSectionCharCode();r?(this.text+=String.fromCharCode(r),this.sections.push(ml.forImage(e)),this.sectionIndex.push(this.sections.length-1)):_(\"Reached maximum number of images 6401\")}else _(\"Can't add FormattedSection with an empty image.\")},vl.prototype.getNextImageSectionCharCode=function(){return this.imageSectionID?this.imageSectionID>=63743?null:++this.imageSectionID:(this.imageSectionID=57344,this.imageSectionID)};var xl={9:!0,10:!0,11:!0,12:!0,13:!0,32:!0},bl={};function _l(t,e,r,n,i,a){if(e.imageName){var o=n[e.imageName];return o?o.displaySize[0]*e.scale*24/a+i:0}var s=r[e.fontStack],l=s&&s[t];return l?l.metrics.advance*e.scale+i:0}function wl(t,e,r,n){var i=Math.pow(t-e,2);return n?t<e?i/2:2*i:i+Math.abs(r)*r}function Tl(t,e,r){var n=0;return 10===t&&(n-=1e4),r&&(n+=150),40!==t&&65288!==t||(n+=50),41!==e&&65289!==e||(n+=50),n}function kl(t,e,r,n,i,a){for(var o=null,s=wl(e,r,i,a),l=0,c=n;l<c.length;l+=1){var u=c[l],f=wl(e-u.x,r,i,a)+u.badness;f<=s&&(o=u,s=f)}return{index:t,x:e,priorBreak:o,badness:s}}function Ml(t,e,r,n,i,a,o){if(\"point\"!==a)return[];if(!t)return[];for(var s,l=[],c=function(t,e,r,n,i,a){for(var o=0,s=0;s<t.length();s++){var l=t.getSection(s);o+=_l(t.getCharCode(s),l,n,i,e,a)}return o/Math.max(1,Math.ceil(o/r))}(t,e,r,n,i,o),u=t.text.indexOf(\"\\u200b\")>=0,f=0,h=0;h<t.length();h++){var p=t.getSection(h),d=t.getCharCode(h);if(xl[d]||(f+=_l(d,p,n,i,e,o)),h<t.length()-1){var g=!((s=d)<11904||!(Vn[\"Bopomofo Extended\"](s)||Vn.Bopomofo(s)||Vn[\"CJK Compatibility Forms\"](s)||Vn[\"CJK Compatibility Ideographs\"](s)||Vn[\"CJK Compatibility\"](s)||Vn[\"CJK Radicals Supplement\"](s)||Vn[\"CJK Strokes\"](s)||Vn[\"CJK Symbols and Punctuation\"](s)||Vn[\"CJK Unified Ideographs Extension A\"](s)||Vn[\"CJK Unified 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o,s=t.image;if(s.content){var l=s.content,c=s.pixelRatio||1;o=[l[0]/c,l[1]/c,s.displaySize[0]-l[2]/c,s.displaySize[1]-l[3]/c]}var u,f,h,p,d=e.left*a,g=e.right*a;\"width\"===r||\"both\"===r?(p=i[0]+d-n[3],f=i[0]+g+n[1]):f=(p=i[0]+(d+g-s.displaySize[0])/2)+s.displaySize[0];var m=e.top*a,v=e.bottom*a;return\"height\"===r||\"both\"===r?(u=i[1]+m-n[0],h=i[1]+v+n[2]):h=(u=i[1]+(m+v-s.displaySize[1])/2)+s.displaySize[1],{image:s,top:u,right:f,bottom:h,left:p,collisionPadding:o}}bl[10]=!0,bl[32]=!0,bl[38]=!0,bl[40]=!0,bl[41]=!0,bl[43]=!0,bl[45]=!0,bl[47]=!0,bl[173]=!0,bl[183]=!0,bl[8203]=!0,bl[8208]=!0,bl[8211]=!0,bl[8231]=!0;var Cl=function(t){function e(e,r,n,i){t.call(this,e,r),this.angle=n,void 0!==i&&(this.segment=i)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.clone=function(){return new e(this.x,this.y,this.angle,this.segment)},e}(i);function Ll(t,e){var r=e.expression;if(\"constant\"===r.kind)return{kind:\"constant\",layoutSize:r.evaluate(new ii(t+1))};if(\"source\"===r.kind)return{kind:\"source\"};for(var n=r.zoomStops,i=r.interpolationType,a=0;a<n.length&&n[a]<=t;)a++;for(var o=a=Math.max(0,a-1);o<n.length&&n[o]<t+1;)o++;o=Math.min(n.length-1,o);var s=n[a],l=n[o];return\"composite\"===r.kind?{kind:\"composite\",minZoom:s,maxZoom:l,interpolationType:i}:{kind:\"camera\",minZoom:s,maxZoom:l,minSize:r.evaluate(new ii(s)),maxSize:r.evaluate(new ii(l)),interpolationType:i}}function Il(t,e,r){var n=e.uSize,i=r.lowerSize;return\"source\"===t.kind?i/128:\"composite\"===t.kind?Ue(i/128,r.upperSize/128,e.uSizeT):n}function Pl(t,e){var r=0,n=0;if(\"constant\"===t.kind)n=t.layoutSize;else if(\"source\"!==t.kind){var i=t.interpolationType,a=i?l(rr.interpolationFactor(i,e,t.minZoom,t.maxZoom),0,1):0;\"camera\"===t.kind?n=Ue(t.minSize,t.maxSize,a):r=a}return{uSizeT:r,uSize:n}}Dn(\"Anchor\",Cl);var 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h=Hl(n.stretch-x,b,u,t.left),p=Gl(n.fixed-T,k,n.stretch,g),d=Hl(a.stretch-_,w,f,t.top),v=Gl(a.fixed-M,A,a.stretch,m),y=Hl(l.stretch-x,b,u,t.left),S=Gl(l.fixed-T,k,l.stretch,g),E=Hl(c.stretch-_,w,f,t.top),C=Gl(c.fixed-M,A,c.stretch,m),L=new i(h,d),I=new i(y,d),P=new i(y,E),z=new i(h,E),O=new i(p/s,v/s),D=new i(S/s,C/s),R=e*Math.PI/180;if(R){var F=Math.sin(R),B=Math.cos(R),N=[B,-F,F,B];L._matMult(N),I._matMult(N),z._matMult(N),P._matMult(N)}var j=n.stretch+n.fixed,U=a.stretch+a.fixed;return{tl:L,tr:I,bl:z,br:P,tex:{x:o.paddedRect.x+1+j,y:o.paddedRect.y+1+U,w:l.stretch+l.fixed-j,h:c.stretch+c.fixed-U},writingMode:void 0,glyphOffset:[0,0],sectionIndex:0,pixelOffsetTL:O,pixelOffsetBR:D,minFontScaleX:k/s/u,minFontScaleY:A/s/f,isSDF:r}};if(n&&(o.stretchX||o.stretchY))for(var C=ql(h,v,g),L=ql(p,y,m),I=0;I<C.length-1;I++)for(var P=C[I],z=C[I+1],O=0;O<L.length-1;O++)a.push(E(P,L[O],z,L[O+1]));else 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k=s[m.imageName];x=k.sdf,y=1/(b=k.pixelRatio)}var M=a?[m.x+T,m.y]:[0,0],A=a?[0,0]:[m.x+T+r[0],m.y+r[1]-_],S=[0,0];w&&(S=A,A=[0,0]);var E=(m.metrics.left-y)*m.scale-T+A[0],C=(-m.metrics.top-y)*m.scale+A[1],L=E+v.w*m.scale/b,I=C+v.h*m.scale/b,P=new i(E,C),z=new i(L,C),O=new i(E,I),D=new i(L,I);if(w){var R=new i(-T,T- -17),F=-Math.PI/2,B=12-T,N=new i(22-B,-(m.imageName?B:0)),j=new(Function.prototype.bind.apply(i,[null].concat(S)));P._rotateAround(F,R)._add(N)._add(j),z._rotateAround(F,R)._add(N)._add(j),O._rotateAround(F,R)._add(N)._add(j),D._rotateAround(F,R)._add(N)._add(j)}if(c){var U=Math.sin(c),V=Math.cos(c),q=[V,-U,U,V];P._matMult(q),z._matMult(q),O._matMult(q),D._matMult(q)}var H=new i(0,0),G=new i(0,0);u.push({tl:P,tr:z,bl:O,br:D,tex:v,writingMode:e.writingMode,glyphOffset:M,sectionIndex:m.sectionIndex,isSDF:x,pixelOffsetTL:H,pixelOffsetBR:G,minFontScaleX:0,minFontScaleY:0})}}return u}(0,r,l,a,o,s,n,t.allowVerticalPlacement),v=t.textSizeData,y=null;\"source\"===v.kind?(y=[128*a.layout.get(\"text-size\").evaluate(s,{})])[0]>32640&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. 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Fi,this.programConfigurations=t,this.segments=new ia,this.dynamicLayoutVertexArray=new Ii,this.opacityVertexArray=new Pi,this.placedSymbolArray=new Ji};cc.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length&&0===this.indexArray.length&&0===this.dynamicLayoutVertexArray.length&&0===this.opacityVertexArray.length},cc.prototype.upload=function(t,e,r,n){this.isEmpty()||(r&&(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Ds.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,Rs.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,ac,!0),this.opacityVertexBuffer.itemSize=1),(r||n)&&this.programConfigurations.upload(t))},cc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},Dn(\"SymbolBuffers\",cc);var uc=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new ia,this.collisionVertexArray=new Ri};uc.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,Fs.members,!0)},uc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},Dn(\"CollisionBuffers\",uc);var fc=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=eo([]),this.placementViewportMatrix=eo([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Ll(this.zoom,e[\"text-size\"]),this.iconSizeData=Ll(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),i=r.get(\"symbol-z-order\");this.sortFeaturesByKey=\"viewport-y\"!==i&&void 0!==n.constantOr(1),this.sortFeaturesByY=(\"viewport-y\"===i||\"auto\"===i&&!this.sortFeaturesByKey)&&(r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\")),\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map((function(t){return gl[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};fc.prototype.createArrays=function(){this.text=new cc(new Ia(Ds.members,this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new cc(new Ia(Ds.members,this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new $i,this.lineVertexArray=new ta,this.symbolInstances=new Qi},fc.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=Us[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},fc.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get(\"text-font\"),o=i.get(\"text-field\"),s=i.get(\"icon-image\"),l=(\"constant\"!==o.value.kind||o.value.value instanceof te&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),c=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,u=i.get(\"symbol-sort-key\");if(this.features=[],l||c){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new ii(this.zoom),g=0,m=t;g<m.length;g+=1){var v=m[g],y=v.feature,x=v.id,b=v.index,_=v.sourceLayerIndex,w=n._featureFilter.needGeometry,T={type:y.type,id:x,properties:y.properties,geometry:w?Da(y):[]};if(n._featureFilter.filter(d,T,r)){w||(T.geometry=Da(y));var k=void 0;if(l){var M=n.getValueAndResolveTokens(\"text-field\",T,r,p),A=te.factory(M);lc(A)&&(this.hasRTLText=!0),(!this.hasRTLText||\"unavailable\"===ei()||this.hasRTLText&&ni.isParsed())&&(k=js(A,n,T))}var S=void 0;if(c){var E=n.getValueAndResolveTokens(\"icon-image\",T,r,p);S=E instanceof ee?E:ee.fromString(E)}if(k||S){var C=this.sortFeaturesByKey?u.evaluate(T,{},r):void 0,L={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:Da(y),properties:y.properties,type:ic[y.type],sortKey:C};if(this.features.push(L),S&&(f[S.name]=!0),k){var I=a.evaluate(T,{},r).join(\",\"),P=\"map\"===i.get(\"text-rotation-alignment\")&&\"point\"!==i.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(gl.vertical)>=0;for(var z=0,O=k.sections;z<O.length;z+=1){var D=O[z];if(D.image)f[D.image.name]=!0;else{var R=qn(k.toString()),F=D.fontStack||I,B=h[F]=h[F]||{};this.calculateGlyphDependencies(D.text,B,P,this.allowVerticalPlacement,R)}}}}}}\"line\"===i.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var c=0;c<t.length;c++){var u=t[c],f=u.geometry,h=u.text?u.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var g=s(p,d,f),m=o(p,d,n[g].geometry);delete e[p],delete r[d],r[l(h,n[m].geometry,!0)]=m,n[g].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(c),e[p]=i-1,r[d]=i-1)}else a(c)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},fc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},fc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},fc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},fc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},fc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},fc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},fc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var c=a[l];this.lineVertexArray.emplaceBack(c.x,c.y,c.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},fc.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,a.sortKey),g=this.glyphOffsetArray.length,m=d.vertexLength,v=this.allowVerticalPlacement&&o===gl.vertical?Math.PI/2:0,y=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,M=b.tex,A=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,C=b.minFontScaleY,L=b.glyphOffset,I=b.isSDF,P=b.sectionIndex,z=d.vertexLength,O=L[1];oc(p,s.x,s.y,_.x,O+_.y,M.x,M.y,r,I,A.x,A.y,E,C),oc(p,s.x,s.y,w.x,O+w.y,M.x+M.w,M.y,r,I,S.x,A.y,E,C),oc(p,s.x,s.y,T.x,O+T.y,M.x,M.y+M.h,r,I,A.x,S.y,E,C),oc(p,s.x,s.y,k.x,O+k.y,M.x+M.w,M.y+M.h,r,I,S.x,S.y,E,C),sc(t.dynamicLayoutVertexArray,s,v),h.emplaceBack(z,z+1,z+2),h.emplaceBack(z+1,z+2,z+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(L[0]),x!==e.length-1&&P===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,y&&y[P])}t.placedSymbolArray.emplaceBack(s.x,s.y,g,this.glyphOffsetArray.length-g,m,l,c,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,u)},fc.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},fc.prototype.addCollisionDebugVertices=function(t,e,r,n,a,o,s){var l=a.segments.prepareSegment(4,a.layoutVertexArray,a.indexArray),c=l.vertexLength,u=a.layoutVertexArray,f=a.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(u,f,o,h,p,new i(t,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,n)),this._addCollisionDebugVertex(u,f,o,h,p,new i(t,n)),l.vertexLength+=4;var d=a.indexArray;d.emplaceBack(c,c+1),d.emplaceBack(c+1,c+2),d.emplaceBack(c+2,c+3),d.emplaceBack(c+3,c),l.primitiveLength+=4},fc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i);this.addCollisionDebugVertices(a.x1,a.y1,a.x2,a.y2,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},fc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new uc(Oi,Bs.members,qi),this.iconCollisionBox=new uc(Oi,Bs.members,qi);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},fc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var c={},u=e;u<r;u++){var f=t.get(u);c.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},c.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);c.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},c.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var g=t.get(d);c.iconBox={x1:g.x1,y1:g.y1,x2:g.x2,y2:g.y2,anchorPointX:g.anchorPointX,anchorPointY:g.anchorPointY},c.iconFeatureIndex=g.featureIndex;break}for(var m=s;m<l;m++){var v=t.get(m);c.verticalIconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},c.verticalIconFeatureIndex=v.featureIndex;break}return c},fc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},fc.prototype.hasTextData=function(){return this.text.segments.get().length>0},fc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},fc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},fc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},fc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},fc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},fc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},fc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},fc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=this.symbolInstances.get(n[r]);this.featureSortOrder.push(i.featureIndex),[i.rightJustifiedTextSymbolIndex,i.centerJustifiedTextSymbolIndex,i.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),i.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,i.verticalPlacedTextSymbolIndex),i.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,i.placedIconSymbolIndex),i.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,i.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},Dn(\"SymbolBucket\",fc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),fc.MAX_GLYPHS=65535,fc.addDynamicAttributes=sc;var hc=new yi({\"symbol-placement\":new pi(At.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new pi(At.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new pi(At.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new di(At.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new pi(At.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new pi(At.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new pi(At.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new pi(At.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new pi(At.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new di(At.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new pi(At.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new pi(At.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new di(At.layout_symbol[\"icon-image\"]),\"icon-rotate\":new di(At.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new pi(At.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new pi(At.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new di(At.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new di(At.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new pi(At.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new pi(At.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new pi(At.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new di(At.layout_symbol[\"text-field\"]),\"text-font\":new di(At.layout_symbol[\"text-font\"]),\"text-size\":new di(At.layout_symbol[\"text-size\"]),\"text-max-width\":new di(At.layout_symbol[\"text-max-width\"]),\"text-line-height\":new pi(At.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new di(At.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new di(At.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new di(At.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new pi(At.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new di(At.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new pi(At.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new pi(At.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new di(At.layout_symbol[\"text-rotate\"]),\"text-padding\":new pi(At.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new pi(At.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new di(At.layout_symbol[\"text-transform\"]),\"text-offset\":new di(At.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new pi(At.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new pi(At.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new pi(At.layout_symbol[\"text-optional\"])}),pc={paint:new yi({\"icon-opacity\":new di(At.paint_symbol[\"icon-opacity\"]),\"icon-color\":new di(At.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new di(At.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new di(At.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new di(At.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new pi(At.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new pi(At.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new di(At.paint_symbol[\"text-opacity\"]),\"text-color\":new di(At.paint_symbol[\"text-color\"],{runtimeType:Bt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new di(At.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new di(At.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new di(At.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new pi(At.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new pi(At.paint_symbol[\"text-translate-anchor\"])}),layout:hc},dc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Ot,this.defaultValue=t};dc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},dc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},dc.prototype.outputDefined=function(){return!1},dc.prototype.serialize=function(){return null},Dn(\"FormatSectionOverride\",dc,{omit:[\"defaultValue\"]});var gc=function(t){function e(e){t.call(this,e,pc)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(this.layout._values[\"icon-rotation-alignment\"]=\"point\"!==this.layout.get(\"symbol-placement\")?\"map\":\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(this.layout._values[\"text-rotation-alignment\"]=\"point\"!==this.layout.get(\"symbol-placement\")?\"map\":\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values[\"text-writing-mode\"]=i}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||Vr(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):\"\"}))}(e.properties,i)},e.prototype.createBucket=function(t){return new fc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=pc.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i,a=this.paint.get(n),o=new dc(a),s=new Ur(o,a.property.specification);i=\"constant\"===a.value.kind||\"source\"===a.value.kind?new Hr(\"source\",s):new Gr(\"composite\",s,a.value.zoomStops,a.value._interpolationType),this.paint._values[n]=new fi(a.property,i,a.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=pc.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1)if(n.overrides&&n.overrides.hasOverride(r[e]))return void(i=!0)};if(\"constant\"===r.value.kind&&r.value.value instanceof te)a(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){i||(t instanceof oe&&ie(t.value)===Vt?a(t.value.sections):t instanceof ue?a(t.sections):t.eachChild(o))},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(xi),mc={paint:new yi({\"background-color\":new pi(At.paint_background[\"background-color\"]),\"background-pattern\":new mi(At.paint_background[\"background-pattern\"]),\"background-opacity\":new pi(At.paint_background[\"background-opacity\"])})},vc=function(t){function e(e){t.call(this,e,mc)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e}(xi),yc={paint:new yi({\"raster-opacity\":new pi(At.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new pi(At.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new pi(At.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new pi(At.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new pi(At.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new pi(At.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new pi(At.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new pi(At.paint_raster[\"raster-fade-duration\"])})},xc=function(t){function e(e){t.call(this,e,yc)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e}(xi),bc=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(xi),_c={circle:oo,heatmap:vo,hillshade:xo,fill:as,\"fill-extrusion\":ws,line:zs,symbol:gc,background:vc,raster:xc},wc=self.HTMLImageElement,Tc=self.HTMLCanvasElement,kc=self.HTMLVideoElement,Mc=self.ImageData,Ac=self.ImageBitmap,Sc=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Sc.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof wc||t instanceof Tc||t instanceof kc||t instanceof Mc||Ac&&t instanceof Ac?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},c=l.x,u=l.y;t instanceof wc||t instanceof Tc||t instanceof kc||t instanceof Mc||Ac&&t instanceof Ac?s.texSubImage2D(s.TEXTURE_2D,0,c,u,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,c,u,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Sc.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Sc.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Sc.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var Ec=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};Ec.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},Ec.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Cc=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},g([\"receive\",\"process\"],this),this.invoker=new Ec(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=k()?t:self};function Lc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}Cc.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=S(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:Nn(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},Cc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else k()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Cc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Cc.prototype.processTask=function(t,e){var r=this;if(\"<response>\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(jn(e.error)):n(null,jn(e.data)))}else{var i=!1,a=S(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"<response>\",sourceMapId:r.mapId,error:e?Nn(e):null,data:Nn(n,a)},a)}:function(t){i=!0},s=null,l=jn(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var c=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,c[0],l.source)[c[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Cc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Ic=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Ic.prototype.setNorthEast=function(t){return this._ne=t instanceof Pc?new Pc(t.lng,t.lat):Pc.convert(t),this},Ic.prototype.setSouthWest=function(t){return this._sw=t instanceof Pc?new Pc(t.lng,t.lat):Pc.convert(t),this},Ic.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Pc)e=t,r=t;else{if(!(t instanceof Ic))return Array.isArray(t)?4===t.length||t.every(Array.isArray)?this.extend(Ic.convert(t)):this.extend(Pc.convert(t)):this;if(r=t._ne,!(e=t._sw)||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Pc(e.lng,e.lat),this._ne=new Pc(r.lng,r.lat)),this},Ic.prototype.getCenter=function(){return new Pc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Ic.prototype.getSouthWest=function(){return this._sw},Ic.prototype.getNorthEast=function(){return this._ne},Ic.prototype.getNorthWest=function(){return new Pc(this.getWest(),this.getNorth())},Ic.prototype.getSouthEast=function(){return new Pc(this.getEast(),this.getSouth())},Ic.prototype.getWest=function(){return this._sw.lng},Ic.prototype.getSouth=function(){return this._sw.lat},Ic.prototype.getEast=function(){return this._ne.lng},Ic.prototype.getNorth=function(){return this._ne.lat},Ic.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Ic.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Ic.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Ic.prototype.contains=function(t){var e=Pc.convert(t),r=e.lng,n=e.lat,i=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(i=this._sw.lng>=r&&r>=this._ne.lng),this._sw.lat<=n&&n<=this._ne.lat&&i},Ic.convert=function(t){return!t||t instanceof Ic?t:new Ic(t)};var Pc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Pc.prototype.wrap=function(){return new Pc(c(this.lng,-180,180),this.lat)},Pc.prototype.toArray=function(){return[this.lng,this.lat]},Pc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Pc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return 6371008.8*Math.acos(Math.min(i,1))},Pc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Ic(new Pc(this.lng-r,this.lat-e),new Pc(this.lng+r,this.lat+e))},Pc.convert=function(t){if(t instanceof Pc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Pc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Pc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var zc=2*Math.PI*6371008.8;function Oc(t){return zc*Math.cos(t*Math.PI/180)}function Dc(t){return(180+t)/360}function Rc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Fc(t,e){return t/Oc(e)}function Bc(t){return 360/Math.PI*Math.atan(Math.exp((180-360*t)*Math.PI/180))-90}var Nc=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Nc.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Pc.convert(t);return new Nc(Dc(r.lng),Rc(r.lat),Fc(e,r.lat))},Nc.prototype.toLngLat=function(){return new Pc(360*this.x-180,Bc(this.y))},Nc.prototype.toAltitude=function(){return this.z*Oc(Bc(this.y))},Nc.prototype.meterInMercatorCoordinateUnits=function(){return 1/zc*(t=Bc(this.y),1/Math.cos(t*Math.PI/180));var t};var jc=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=qc(0,t,t,e,r)};jc.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},jc.prototype.url=function(t,e){var r,n,i,a,o,s=(n=this.y,i=this.z,a=Lc(256*(r=this.x),256*(n=Math.pow(2,i)-n-1),i),o=Lc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},jc.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new i(8192*(t.x*e-this.x),8192*(t.y*e-this.y))},jc.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var Uc=function(t,e){this.wrap=t,this.canonical=e,this.key=qc(t,e.z,e.z,e.x,e.y)},Vc=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new jc(r,+n,+i),this.key=qc(e,t,r,n,i)};function qc(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}Vc.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},Vc.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new Vc(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Vc(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Vc.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?qc(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):qc(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Vc.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},Vc.prototype.children=function(t){if(this.overscaledZ>=t)return[new Vc(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Vc(e,this.wrap,e,r,n),new Vc(e,this.wrap,e,r+1,n),new Vc(e,this.wrap,e,r,n+1),new Vc(e,this.wrap,e,r+1,n+1)]},Vc.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},Vc.prototype.wrapped=function(){return new Vc(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},Vc.prototype.unwrapTo=function(t){return new Vc(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},Vc.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},Vc.prototype.toUnwrapped=function(){return new Uc(this.wrap,this.canonical)},Vc.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},Vc.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new Nc(t.x-this.wrap,t.y))},Dn(\"CanonicalTileID\",jc),Dn(\"OverscaledTileID\",Vc,{omit:[\"posMatrix\"]});var Hc=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return _('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||\"mapbox\";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};Hc.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return(\"terrarium\"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},Hc.prototype.getUnpackVector=function(){return\"terrarium\"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},Hc.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},Hc.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Hc.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Hc.prototype.getPixels=function(){return new po({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Hc.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,c=a;c<o;c++)for(var u=n;u<i;u++)this.data[this._idx(u,c)]=t.data[this._idx(u+s,c+l)]},Dn(\"DEMData\",Hc);var Gc=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};Gc.prototype.encode=function(t){return this._stringToNumber[t]},Gc.prototype.decode=function(t){return this._numberToString[t]};var Yc=function(t,e,r,n,i){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},Wc={geometry:{configurable:!0}};Wc.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},Wc.geometry.set=function(t){this._geometry=t},Yc.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(Yc.prototype,Wc);var Xc=function(){this.state={},this.stateChanges={},this.deletedStates={}};Xc.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},u(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r)this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]},Xc.prototype.removeFeatureState=function(t,e,r){if(null!==this.deletedStates[t]){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e)if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null;else this.deletedStates[t]=null}},Xc.prototype.getState=function(t,e){var r=String(e),n=u({},(this.state[t]||{})[r],(this.stateChanges[t]||{})[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var i=this.deletedStates[t][e];if(null===i)return{};for(var a in i)delete n[a]}return n},Xc.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},Xc.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),u(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var c in this.deletedStates[o]){if(null===this.deletedStates[o][c])this.state[o][c]={};else for(var f=0,h=Object.keys(this.deletedStates[o][c]);f<h.length;f+=1)delete this.state[o][c][h[f]];s[c]=this.state[o][c]}r[o]=r[o]||{},u(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var p in t)t[p].setFeatureState(r,e)};var Zc=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new Ln(8192,16,0),this.grid3D=new Ln(8192,16,0),this.featureIndexArray=new ra,this.promoteId=e};function Jc(t,e,r,n,i){return v(t,(function(t,a){var o=e instanceof hi?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function Kc(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function Qc(t,e){return e-t}Zc.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var c=e[l],u=[1/0,1/0,-1/0,-1/0],f=0;f<c.length;f++){var h=c[f];u[0]=Math.min(u[0],h.x),u[1]=Math.min(u[1],h.y),u[2]=Math.max(u[2],h.x),u[3]=Math.max(u[3],h.y)}u[0]<8192&&u[1]<8192&&u[2]>=0&&u[3]>=0&&s.insert(o,u[0],u[1],u[2],u[3])}},Zc.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new gs.VectorTile(new Hs(this.rawTileData)).layers,this.sourceLayerCoder=new Gc(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},Zc.prototype.query=function(t,e,r,n){var a=this;this.loadVTLayers();for(var o=t.params||{},s=8192/t.tileSize/t.scale,l=rn(o.filter),c=t.queryGeometry,u=t.queryPadding*s,f=Kc(c),h=this.grid.query(f.minX-u,f.minY-u,f.maxX+u,f.maxY+u),p=Kc(t.cameraQueryGeometry),d=0,g=this.grid3D.query(p.minX-u,p.minY-u,p.maxX+u,p.maxY+u,(function(e,r,n,a){return function(t,e,r,n,a){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&a>=l.y)return!0}var c=[new i(e,r),new i(e,a),new i(n,a),new i(n,r)];if(t.length>2)for(var u=0,f=c;u<f.length;u+=1)if(Wa(t,f[u]))return!0;for(var h=0;h<t.length-1;h++)if(Xa(t[h],t[h+1],c))return!0;return!1}(t.cameraQueryGeometry,e-u,r-u,n+u,a+u)}));d<g.length;d+=1)h.push(g[d]);h.sort(Qc);for(var m,v={},y=function(i){var u=h[i];if(u!==m){m=u;var f=a.featureIndexArray.get(u),p=null;a.loadMatchingFeature(v,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=Da(e)),r.queryIntersectsFeature(c,e,n,p,a.z,t.transform,s,t.pixelPosMatrix)}))}},x=0;x<h.length;x++)y(x);return v},Zc.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,c,u){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new ii(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),g=0;g<f.length;g++){var m=f[g];if(!(a&&a.indexOf(m)<0)){var v=s[m];if(v){var y={};void 0!==d&&c&&(y=c.getState(v.sourceLayer||\"_geojsonTileLayer\",d));var x=l[m];x.paint=Jc(x.paint,v.paint,p,y,o),x.layout=Jc(x.layout,v.layout,p,y,o);var b=!u||u(p,v,y);if(b){var _=new Yc(p,this.z,this.x,this.y,d);_.layer=x;var w=t[m];void 0===w&&(w=t[m]=[]),w.push({featureIndex:n,feature:_,intersectionZ:b})}}}}}},Zc.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var c=rn(i),u=0,f=t;u<f.length;u+=1)this.loadMatchingFeature(l,r,n,f[u],c,a,o,s,e);return l},Zc.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1)if(t===i[n])return!0;return!1},Zc.prototype.getId=function(t,e){var r=t.id;return this.promoteId&&\"boolean\"==typeof(r=t.properties[\"string\"==typeof this.promoteId?this.promoteId:this.promoteId[e]])&&(r=Number(r)),r},Dn(\"FeatureIndex\",Zc,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var $c=function(t,e){this.tileID=t,this.uid=h(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};$c.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<R.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},$c.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},$c.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1)r[s[o].id]=t}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof fc){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof fc&&o.hasRTLText){this.hasRTLText=!0,ni.isLoading()||ni.isLoaded()||\"deferred\"!==ei()||ri();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new Xi},$c.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},$c.prototype.getBucket=function(t){return this.buckets[t.id]},$c.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Sc(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Sc(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},$c.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},$c.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,c){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:c,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},$c.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=rn(e&&e.filter),s=this.tileID.canonical,l=s.z,c=s.x,u=s.y,f={z:l,x:c,y:u},h=0;h<a.length;h++){var p=a.feature(h);if(o.filter(new ii(this.tileID.overscaledZ),p)){var d=r.getId(p,i),g=new Yc(p,l,c,u,d);g.tile=f,t.push(g)}}}},$c.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},$c.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},$c.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=M(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},$c.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},$c.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},$c.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},$c.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<R.now()},$c.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},$c.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=R.now()+t},$c.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1)r[i[n]]=!0;this.dependencies[t]=r},$c.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=this.dependencies[n[r]];if(i)for(var a=0,o=e;a<o.length;a+=1)if(i[o[a]])return!0}return!1};var tu=self.performance,eu=function(t){this._marks={start:[t.url,\"start\"].join(\"#\"),end:[t.url,\"end\"].join(\"#\"),measure:t.url.toString()},tu.mark(this._marks.start)};eu.prototype.finish=function(){tu.mark(this._marks.end);var t=tu.getEntriesByName(this._marks.measure);return 0===t.length&&(tu.measure(this._marks.measure,this._marks.start,this._marks.end),t=tu.getEntriesByName(this._marks.measure),tu.clearMarks(this._marks.start),tu.clearMarks(this._marks.end),tu.clearMeasures(this._marks.measure)),t},t.Actor=Cc,t.AlphaImage=ho,t.CanonicalTileID=jc,t.CollisionBoxArray=Xi,t.Color=Kt,t.DEMData=Hc,t.DataConstantProperty=pi,t.DictionaryCoder=Gc,t.EXTENT=8192,t.ErrorEvent=kt,t.EvaluationParameters=ii,t.Event=Tt,t.Evented=Mt,t.FeatureIndex=Zc,t.FillBucket=rs,t.FillExtrusionBucket=xs,t.ImageAtlas=dl,t.ImagePosition=hl,t.LineBucket=Cs,t.LngLat=Pc,t.LngLatBounds=Ic,t.MercatorCoordinate=Nc,t.ONE_EM=24,t.OverscaledTileID=Vc,t.Point=i,t.Point$1=i,t.Properties=yi,t.Protobuf=Hs,t.RGBAImage=po,t.RequestManager=q,t.RequestPerformance=eu,t.ResourceType=ht,t.SegmentVector=ia,t.SourceFeatureState=Xc,t.StructArrayLayout1ui2=Hi,t.StructArrayLayout2f1f2i16=Di,t.StructArrayLayout2i4=Mi,t.StructArrayLayout3ui6=Fi,t.StructArrayLayout4i8=Ai,t.SymbolBucket=fc,t.Texture=Sc,t.Tile=$c,t.Transitionable=si,t.Uniform1f=va,t.Uniform1i=ma,t.Uniform2f=ya,t.Uniform3f=xa,t.Uniform4f=ba,t.UniformColor=_a,t.UniformMatrix4f=Ta,t.UnwrappedTileID=Uc,t.ValidationError=St,t.WritingMode=gl,t.ZoomHistory=Un,t.add=function(t,e,r){return t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t},t.addDynamicAttributes=sc,t.asyncAll=function(t,e,r){if(!t.length)return r(null,[]);var n=t.length,i=new Array(t.length),a=null;t.forEach((function(t,o){e(t,(function(t,e){t&&(a=t),i[o]=e,0==--n&&r(a,i)}))}))},t.bezier=o,t.bindAll=g,t.browser=R,t.cacheEntryPossiblyAdded=function(t){++ut>ot&&(t.getActor().send(\"enforceCacheSizeLimit\",at),ut=0)},t.clamp=l,t.clearTileCache=function(t){var e=self.caches.delete(\"mapbox-tiles\");t&&e.catch(t).then((function(){return t()}))},t.clipLine=jl,t.clone=function(t){var e=new to(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=x,t.clone$2=function(t){var e=new to(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=Ns,t.config=F,t.create=function(){var t=new to(16);return to!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0),t[0]=1,t[5]=1,t[10]=1,t[15]=1,t},t.create$1=function(){var t=new to(9);return to!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[5]=0,t[6]=0,t[7]=0),t[0]=1,t[4]=1,t[8]=1,t},t.create$2=function(){var t=new to(4);return to!=Float32Array&&(t[1]=0,t[2]=0),t[0]=1,t[3]=1,t},t.createCommonjsModule=e,t.createExpression=qr,t.createLayout=Ti,t.createStyleLayer=function(t){return\"custom\"===t.type?new bc(t):new _c[t.type](t)},t.cross=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=r[0],s=r[1],l=r[2];return t[0]=i*l-a*s,t[1]=a*o-n*l,t[2]=n*s-i*o,t},t.deepEqual=function t(e,r){if(Array.isArray(e)){if(!Array.isArray(r)||e.length!==r.length)return!1;for(var n=0;n<e.length;n++)if(!t(e[n],r[n]))return!1;return!0}if(\"object\"==typeof e&&null!==e&&null!==r){if(\"object\"!=typeof r)return!1;if(Object.keys(e).length!==Object.keys(r).length)return!1;for(var i in e)if(!t(e[i],r[i]))return!1;return!0}return e===r},t.dot=function(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]},t.dot$1=function(t,e){return t[0]*e[0]+t[1]*e[1]+t[2]*e[2]+t[3]*e[3]},t.ease=s,t.emitValidationErrors=Cn,t.endsWith=m,t.enforceCacheSizeLimit=function(t){st(),Q&&Q.then((function(e){e.keys().then((function(r){for(var n=0;n<r.length-t;n++)e.delete(r[n])}))}))},t.evaluateSizeForFeature=Il,t.evaluateSizeForZoom=Pl,t.evaluateVariableOffset=$l,t.evented=ti,t.extend=u,t.featureFilter=rn,t.filterObject=y,t.fromRotation=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=-r,t[4]=n,t[5]=0,t[6]=0,t[7]=0,t[8]=1,t},t.getAnchorAlignment=Al,t.getAnchorJustification=tc,t.getArrayBuffer=yt,t.getImage=bt,t.getJSON=function(t,e){return vt(u(t,{type:\"json\"}),e)},t.getRTLTextPluginStatus=ei,t.getReferrer=mt,t.getVideo=function(t,e){var r,n,i=self.document.createElement(\"video\");i.muted=!0,i.onloadstart=function(){e(null,i)};for(var a=0;a<t.length;a++){var o=self.document.createElement(\"source\");r=t[a],n=void 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r}function ft(t,e){var r=[];r.size=t.size,void 0!==t.start&&(r.start=t.start,r.end=t.end);for(var n=0;n<t.length;n+=3)r.push(t[n]+e,t[n+1],t[n+2]);return r}function ht(t,e){if(t.transformed)return t;var r,n,i,a=1<<t.z,o=t.x,s=t.y;for(r=0;r<t.features.length;r++){var l=t.features[r],c=l.geometry,u=l.type;if(l.geometry=[],1===u)for(n=0;n<c.length;n+=2)l.geometry.push(pt(c[n],c[n+1],e,a,o,s));else for(n=0;n<c.length;n++){var f=[];for(i=0;i<c[n].length;i+=2)f.push(pt(c[n][i],c[n][i+1],e,a,o,s));l.geometry.push(f)}}return t.transformed=!0,t}function pt(t,e,r,n,i,a){return[Math.round(r*(t*n-i)),Math.round(r*(e*n-a))]}function dt(t,e,r,n,i){for(var a=e===i.maxZoom?0:i.tolerance/((1<<e)*i.extent),o={features:[],numPoints:0,numSimplified:0,numFeatures:0,source:null,x:r,y:n,z:e,transformed:!1,minX:2,minY:1,maxX:-1,maxY:0},s=0;s<t.length;s++){o.numFeatures++,gt(o,t[s],a,i);var l=t[s].minX,c=t[s].minY,u=t[s].maxX,f=t[s].maxY;l<o.minX&&(o.minX=l),c<o.minY&&(o.minY=c),u>o.maxX&&(o.maxX=u),f>o.maxY&&(o.maxY=f)}return o}function gt(t,e,r,n){var i=e.geometry,a=e.type,o=[];if(\"Point\"===a||\"MultiPoint\"===a)for(var s=0;s<i.length;s+=3)o.push(i[s]),o.push(i[s+1]),t.numPoints++,t.numSimplified++;else if(\"LineString\"===a)mt(o,i,t,r,!1,!1);else if(\"MultiLineString\"===a||\"Polygon\"===a)for(s=0;s<i.length;s++)mt(o,i[s],t,r,\"Polygon\"===a,0===s);else if(\"MultiPolygon\"===a)for(var l=0;l<i.length;l++){var c=i[l];for(s=0;s<c.length;s++)mt(o,c[s],t,r,!0,0===s)}if(o.length){var u=e.tags||null;if(\"LineString\"===a&&n.lineMetrics){for(var f in u={},e.tags)u[f]=e.tags[f];u.mapbox_clip_start=i.start/i.size,u.mapbox_clip_end=i.end/i.size}var h={geometry:o,type:\"Polygon\"===a||\"MultiPolygon\"===a?3:\"LineString\"===a||\"MultiLineString\"===a?2:1,tags:u};null!==e.id&&(h.id=e.id),t.features.push(h)}}function mt(t,e,r,n,i,a){var o=n*n;if(n>0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n<i;a=n,n+=2)r+=(t[n]-t[a])*(t[n+1]+t[a+1]);if(r>0===e)for(n=0,i=t.length;n<i/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[i-2-n],t[n+1]=t[i-1-n],t[i-2-n]=o,t[i-1-n]=s}}(s,a),t.push(s)}}function vt(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time(\"preprocess data\"),e.maxZoom<0||e.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)J(r,t.features[n],e,n);else J(r,\"Feature\"===t.type?t:{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=rt(t,1,-1-r,r,0,-1,2,e),a=rt(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=rt(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=ut(i,1).concat(n)),a&&(n=n.concat(ut(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function yt(t,e,r){return 32*((1<<t)*r+e)+t}function xt(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new g(n.features),a=b(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}F.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(N(t[l],l));this.trees[i+1]=new D(s,G,Y,a,Float32Array),r&&console.timeEnd(o);for(var c=i;c>=n;c--){var u=+Date.now();s=this._cluster(s,c),this.trees[c]=new D(s,G,Y,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",c,s.length,+Date.now()-u)}return r&&console.timeEnd(\"total time\"),this},F.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],c=[],u=0,f=l.range(V(r),q(a),V(i),q(n));u<f.length;u+=1){var h=l.points[f[u]];c.push(h.numPoints?j(h):this.points[h.index])}return c},F.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n=\"No cluster with the specified id.\",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,c=i.within(a.x,a.y,o);l<c.length;l+=1){var u=i.points[c[l]];u.parentId===t&&s.push(u.numPoints?j(u):this.points[u.index])}if(0===s.length)throw new Error(n);return s},F.prototype.getLeaves=function(t,e,r){var n=[];return this._appendLeaves(n,t,e=e||10,r=r||0,0),n},F.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.radius/a.extent,s=(r-o)/i,l=(r+1+o)/i,c={features:[]};return this._addTileFeatures(n.range((e-o)/i,s,(e+1+o)/i,l),n.points,e,r,i,c),0===e&&this._addTileFeatures(n.range(1-o/i,s,1,l),n.points,i,r,i,c),e===i-1&&this._addTileFeatures(n.range(0,s,o/i,l),n.points,-1,r,i,c),c.features.length?c:null},F.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},F.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},F.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],c=l.numPoints,u={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:c?U(l):this.points[l.index].properties},f=void 0;c?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(u.id=f),a.features.push(u)}},F.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},F.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.reduce,a=n.radius/(n.extent*Math.pow(2,e)),o=0;o<t.length;o++){var s=t[o];if(!(s.zoom<=e)){s.zoom=e;for(var l=this.trees[e+1],c=l.within(s.x,s.y,a),u=s.numPoints||1,f=s.x*u,h=s.y*u,p=i&&u>1?this._map(s,!0):null,d=(o<<5)+(e+1)+this.points.length,g=0,m=c;g<m.length;g+=1){var v=l.points[m[g]];if(!(v.zoom<=e)){v.zoom=e;var y=v.numPoints||1;f+=v.x*y,h+=v.y*y,u+=y,v.parentId=d,i&&(p||(p=this._map(s,!0)),i(p,this._map(v)))}}1===u?r.push(s):(s.parentId=d,r.push(B(f/u,h/u,d,u,p)))}}return r},F.prototype._getOriginId=function(t){return t-this.points.length>>5},F.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},F.prototype._map=function(t,e){if(t.numPoints)return e?H({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?H({},n):n},vt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},vt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<<e,f=yt(e,r,n),h=this.tiles[f];if(!h&&(c>1&&console.time(\"creation\"),h=this.tiles[f]=dt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){c>1&&console.time(\"clipping\");var g,m,v,y,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;g=m=v=y=null,x=rt(t,u,r-_,r+T,0,h.minX,h.maxX,l),b=rt(t,u,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(g=rt(x,u,n-_,n+T,1,h.minY,h.maxY,l),m=rt(x,u,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(v=rt(b,u,n-_,n+T,1,h.minY,h.maxY,l),y=rt(b,u,n+w,n+k,1,h.minY,h.maxY,l),b=null),c>1&&console.timeEnd(\"clipping\"),s.push(g||[],e+1,2*r,2*n),s.push(m||[],e+1,2*r,2*n+1),s.push(v||[],e+1,2*r+1,2*n),s.push(y||[],e+1,2*r+1,2*n+1)}}},vt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=yt(t,e=(e%o+o)%o,r);if(this.tiles[s])return ht(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,c=t,u=e,f=r;!l&&c>0;)c--,u=Math.floor(u/2),f=Math.floor(f/2),l=this.tiles[yt(c,u,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",c,u,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,c,u,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?ht(this.tiles[s],i):null):null};var bt=function(e){function r(t,r,n,i){e.call(this,t,r,n,xt),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));!function t(e,r){var n,i=e&&e.type;if(\"FeatureCollection\"===i)for(n=0;n<e.features.length;n++)t(e.features[n],r);else if(\"GeometryCollection\"===i)for(n=0;n<e.geometries.length;n++)t(e.geometries[n],r);else if(\"Feature\"===i)t(e.geometry,r);else if(\"Polygon\"===i)f(e.coordinates,r);else if(\"MultiPolygon\"===i)for(n=0;n<e.coordinates.length;n++)f(e.coordinates[n],r);return e}(o,!0);try{e._geoJSONIndex=n.cluster?new F(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),c=0,u=l;c<u.length;c+=1){var f=u[c],h=n[f],p=h[0],d=t.createExpression(h[1]),g=t.createExpression(\"string\"==typeof p?[p,[\"accumulated\"],[\"get\",f]]:p);i[f]=d.value,a[f]=g.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var a=n[r];e[a]=i[a].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new vt(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var s={};if(i){var l=i.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)}))}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded;return n&&n[t.uid]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"))}}},r.prototype.removeSource=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),e()},r.prototype.getClusterExpansionZoom=function(t,e){try{e(null,this._geoJSONIndex.getClusterExpansionZoom(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterChildren=function(t,e){try{e(null,this._geoJSONIndex.getChildren(t.clusterId))}catch(t){e(t)}},r.prototype.getClusterLeaves=function(t,e){try{e(null,this._geoJSONIndex.getLeaves(t.clusterId,t.limit,t.offset))}catch(t){e(t)}},r}(l),_t=function(e){var r=this;this.self=e,this.actor=new t.Actor(e,this),this.layerIndexes={},this.availableImages={},this.workerSourceTypes={vector:l,geojson:bt},this.workerSources={},this.demWorkerSources={},this.self.registerWorkerSource=function(t,e){if(r.workerSourceTypes[t])throw new Error('Worker source with name \"'+t+'\" already registered.');r.workerSourceTypes[t]=e},this.self.registerRTLTextPlugin=function(e){if(t.plugin.isParsed())throw new Error(\"RTL text plugin already registered.\");t.plugin.applyArabicShaping=e.applyArabicShaping,t.plugin.processBidirectionalText=e.processBidirectionalText,t.plugin.processStyledBidirectionalText=e.processStyledBidirectionalText}};return _t.prototype.setReferrer=function(t,e){this.referrer=e},_t.prototype.setImages=function(t,e,r){for(var n in this.availableImages[t]=e,this.workerSources[t]){var i=this.workerSources[t][n];for(var a in i)i[a].availableImages=e}r()},_t.prototype.setLayers=function(t,e,r){this.getLayerIndex(t).replace(e),r()},_t.prototype.updateLayers=function(t,e,r){this.getLayerIndex(t).update(e.layers,e.removedIds),r()},_t.prototype.loadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).loadTile(e,r)},_t.prototype.loadDEMTile=function(t,e,r){this.getDEMWorkerSource(t,e.source).loadTile(e,r)},_t.prototype.reloadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).reloadTile(e,r)},_t.prototype.abortTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).abortTile(e,r)},_t.prototype.removeTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).removeTile(e,r)},_t.prototype.removeDEMTile=function(t,e){this.getDEMWorkerSource(t,e.source).removeTile(e)},_t.prototype.removeSource=function(t,e,r){if(this.workerSources[t]&&this.workerSources[t][e.type]&&this.workerSources[t][e.type][e.source]){var n=this.workerSources[t][e.type][e.source];delete this.workerSources[t][e.type][e.source],void 0!==n.removeSource?n.removeSource(e,r):r()}},_t.prototype.loadWorkerSource=function(t,e,r){try{this.self.importScripts(e.url),r()}catch(t){r(t.toString())}},_t.prototype.syncRTLPluginState=function(e,r,n){try{t.plugin.setState(r);var i=t.plugin.getPluginURL();if(t.plugin.isLoaded()&&!t.plugin.isParsed()&&null!=i){this.self.importScripts(i);var a=t.plugin.isParsed();n(a?void 0:new Error(\"RTL Text Plugin failed to import scripts from \"+i),a)}}catch(t){n(t.toString())}},_t.prototype.getAvailableImages=function(t){var e=this.availableImages[t];return e||(e=[]),e},_t.prototype.getLayerIndex=function(t){var e=this.layerIndexes[t];return e||(e=this.layerIndexes[t]=new n),e},_t.prototype.getWorkerSource=function(t,e,r){var n=this;return this.workerSources[t]||(this.workerSources[t]={}),this.workerSources[t][e]||(this.workerSources[t][e]={}),this.workerSources[t][e][r]||(this.workerSources[t][e][r]=new this.workerSourceTypes[e]({send:function(e,r,i){n.actor.send(e,r,i,t)}},this.getLayerIndex(t),this.getAvailableImages(t))),this.workerSources[t][e][r]},_t.prototype.getDEMWorkerSource=function(t,e){return this.demWorkerSources[t]||(this.demWorkerSources[t]={}),this.demWorkerSources[t][e]||(this.demWorkerSources[t][e]=new u),this.demWorkerSources[t][e]},_t.prototype.enforceCacheSizeLimit=function(e,r){t.enforceCacheSizeLimit(r)},\"undefined\"!=typeof WorkerGlobalScope&&void 0!==t.window&&t.window instanceof WorkerGlobalScope&&(t.window.worker=new _t(t.window)),_t})),n(0,(function(t){var e=t.createCommonjsModule((function(t){function e(t){return!r(t)}function r(t){return\"undefined\"==typeof window||\"undefined\"==typeof document?\"not a browser\":Array.prototype&&Array.prototype.every&&Array.prototype.filter&&Array.prototype.forEach&&Array.prototype.indexOf&&Array.prototype.lastIndexOf&&Array.prototype.map&&Array.prototype.some&&Array.prototype.reduce&&Array.prototype.reduceRight&&Array.isArray?Function.prototype&&Function.prototype.bind?Object.keys&&Object.create&&Object.getPrototypeOf&&Object.getOwnPropertyNames&&Object.isSealed&&Object.isFrozen&&Object.isExtensible&&Object.getOwnPropertyDescriptor&&Object.defineProperty&&Object.defineProperties&&Object.seal&&Object.freeze&&Object.preventExtensions?\"JSON\"in window&&\"parse\"in JSON&&\"stringify\"in JSON?function(){if(!(\"Worker\"in window&&\"Blob\"in window&&\"URL\"in window))return!1;var t,e,r=new Blob([\"\"],{type:\"text/javascript\"}),n=URL.createObjectURL(r);try{e=new Worker(n),t=!0}catch(e){t=!1}return e&&e.terminate(),URL.revokeObjectURL(n),t}()?\"Uint8ClampedArray\"in window?ArrayBuffer.isView?function(){var t=document.createElement(\"canvas\");t.width=t.height=1;var e=t.getContext(\"2d\");if(!e)return!1;var r=e.getImageData(0,0,1,1);return r&&r.width===t.width}()?(void 0===n[r=t&&t.failIfMajorPerformanceCaveat]&&(n[r]=function(t){var r=function(t){var r=document.createElement(\"canvas\"),n=Object.create(e.webGLContextAttributes);return n.failIfMajorPerformanceCaveat=t,r.probablySupportsContext?r.probablySupportsContext(\"webgl\",n)||r.probablySupportsContext(\"experimental-webgl\",n):r.supportsContext?r.supportsContext(\"webgl\",n)||r.supportsContext(\"experimental-webgl\",n):r.getContext(\"webgl\",n)||r.getContext(\"experimental-webgl\",n)}(t);if(!r)return!1;var n=r.createShader(r.VERTEX_SHADER);return!(!n||r.isContextLost())&&(r.shaderSource(n,\"void main() {}\"),r.compileShader(n),!0===r.getShaderParameter(n,r.COMPILE_STATUS))}(r)),n[r]?void 0:\"insufficient WebGL support\"):\"insufficient Canvas/getImageData support\":\"insufficient ArrayBuffer support\":\"insufficient Uint8ClampedArray support\":\"insufficient worker support\":\"insufficient JSON support\":\"insufficient Object support\":\"insufficient Function support\":\"insufficent Array support\";var r}t.exports?t.exports=e:window&&(window.mapboxgl=window.mapboxgl||{},window.mapboxgl.supported=e,window.mapboxgl.notSupportedReason=r);var n={};e.webGLContextAttributes={antialias:!1,alpha:!0,stencil:!0,depth:!0}})),r={create:function(e,r,n){var i=t.window.document.createElement(e);return void 0!==r&&(i.className=r),n&&n.appendChild(i),i},createNS:function(e,r){return t.window.document.createElementNS(e,r)}},n=t.window.document.documentElement.style;function i(t){if(!n)return t[0];for(var e=0;e<t.length;e++)if(t[e]in n)return t[e];return t[0]}var a,o=i([\"userSelect\",\"MozUserSelect\",\"WebkitUserSelect\",\"msUserSelect\"]);r.disableDrag=function(){n&&o&&(a=n[o],n[o]=\"none\")},r.enableDrag=function(){n&&o&&(n[o]=a)};var s=i([\"transform\",\"WebkitTransform\"]);r.setTransform=function(t,e){t.style[s]=e};var l=!1;try{var c=Object.defineProperty({},\"passive\",{get:function(){l=!0}});t.window.addEventListener(\"test\",c,c),t.window.removeEventListener(\"test\",c,c)}catch(t){l=!1}r.addEventListener=function(t,e,r,n){void 0===n&&(n={}),t.addEventListener(e,r,\"passive\"in n&&l?n:n.capture)},r.removeEventListener=function(t,e,r,n){void 0===n&&(n={}),t.removeEventListener(e,r,\"passive\"in n&&l?n:n.capture)};var u=function(e){e.preventDefault(),e.stopPropagation(),t.window.removeEventListener(\"click\",u,!0)};function f(t){var e=t.userImage;return!!(e&&e.render&&e.render())&&(t.data.replace(new Uint8Array(e.data.buffer)),!0)}r.suppressClick=function(){t.window.addEventListener(\"click\",u,!0),t.window.setTimeout((function(){t.window.removeEventListener(\"click\",u,!0)}),0)},r.mousePos=function(e,r){var n=e.getBoundingClientRect();return new t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),i=[],a=0;a<r.length;a++)i.push(new t.Point(r[a].clientX-n.left-e.clientLeft,r[a].clientY-n.top-e.clientTop));return i},r.mouseButton=function(e){return void 0!==t.window.InstallTrigger&&2===e.button&&e.ctrlKey&&t.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e];this._notify(n.ids,n.callback)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchX\" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchY\" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"content\" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];if(a[0]<r||a[1]<a[0]||e<a[1])return!1;r=a[1]}return!0},r.prototype._validateContent=function(t,e){return!(t&&(4!==t.length||t[0]<0||e.data.width<t[0]||t[1]<0||e.data.height<t[1]||t[2]<0||e.data.width<t[2]||t[3]<0||e.data.height<t[3]||t[2]<t[0]||t[3]<t[1]))},r.prototype.updateImage=function(t,e){e.version=this.images[t].version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1)this.images[i[n]]||(r=!1);this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i];this.images[o]||this.fire(new t.Event(\"styleimagemissing\",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. 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o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,c=l.x+1,u=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:c,y:u-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:c-1,y:u},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c+h,y:u},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented),p=m,d=m,g=1e20;function m(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function v(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(y(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(y(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function y(t,e,r,n,i){r[0]=0,n[0]=-g,n[1]=+g;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+g}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}m.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?g:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?g:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(v(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),v(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++)r[n]=Math.max(0,Math.min(255,Math.round(255-255*((this.gridOuter[n]-this.gridInner[n])/this.radius+this.cutoff))));return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1)i.push({stack:a,id:s[o]});t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1)(0,o[i])(t,e);delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,c=o.glyph;(n[s]||(n[s]={}))[l]=c&&{id:c.id,bitmap:c.bitmap.clone(),metrics:c.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,\"-transition\")?this._transitionable.setTransition(n.slice(0,-\"-transition\".length),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),T=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};T.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},T.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){var c=t[l];n.push({left:i=s*r,right:a=(s+=c)*r,isDash:o=!o,zeroLength:0===c})}return n},T.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.width*(this.nextRow+r+i),o=0,s=t[o],l=0;l<this.width;l++){l/s.right>1&&(s=t[++o]);var c=Math.abs(l-s.left),u=Math.abs(l-s.right),f=Math.min(c,u),h=void 0,p=i/r*(n+1);if(s.isDash){var d=n-Math.abs(p);h=Math.sqrt(f*f+d*d)}else h=n-Math.sqrt(f*f+p*p);this.data[a+l]=Math.max(0,Math.min(255,h+128))}},T.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f);this.data[o+c]=Math.max(0,Math.min(255,(l.isDash?h:-h)+128))}},T.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var c={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,c},T.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var k=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=new e.Actor(i[a],n,this.id);o.name=\"Worker \"+a,this.actors.push(o)}};function M(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}k.prototype.broadcast=function(e,r,n){t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n=n||function(){})},k.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},k.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},k.Actor=t.Actor;var A=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};A.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},A.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var S=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new A(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),E=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=M(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new A(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(i)e.state=\"errored\",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),C=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(E),L=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor,e.request=this.actor.send(i,{type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId},(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),I=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),P=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var c=Math.max(i-r,a-n),u=Math.max(0,Math.floor(-Math.log(c)/Math.LN2)),f=Math.pow(2,u);return new t.CanonicalTileID(u,Math.floor((r+i)/2*f),Math.floor((n+a)/2*f))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,I.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented),z=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1)this.urls.push(this.map._requestManager.transformRequest(i[n],t.ResourceType.Source).url);t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,I.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(P),O=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,I.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var r=e[t];if(isNaN(r)||r<=0)return!0}return!1},r}(P),D={vector:S,raster:E,\"raster-dem\":C,geojson:L,video:z,image:P,canvas:O};function R(e,r){var n=t.identity([]);return t.translate(n,n,[1,1,0]),t.scale(n,n,[.5*e.width,.5*e.height,1]),t.multiply(n,n,e.calculatePosMatrix(r.toUnwrapped()))}function F(t,e,r,n,i,a){var o=function(t,e,r){if(t)for(var n=0,i=t;n<i.length;n+=1){var a=e[i[n]];if(a&&a.source===r&&\"fill-extrusion\"===a.type)return!0}else for(var o in e){var s=e[o];if(s.source===r&&\"fill-extrusion\"===s.type)return!0}return!1}(i&&i.layers,e,t.id),s=a.maxPitchScaleFactor(),l=t.tilesIn(n,s,o);l.sort(B);for(var c=[],u=0,f=l;u<f.length;u+=1){var h=f[u];c.push({wrappedTileID:h.tileID.wrapped().key,queryResults:h.tile.queryRenderedFeatures(e,r,t._state,h.queryGeometry,h.cameraQueryGeometry,h.scale,i,a,s,R(t.transform,h.tileID))})}var p=function(t){for(var e={},r={},n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.queryResults,s=a.wrappedTileID,l=r[s]=r[s]||{};for(var c in o)for(var u=o[c],f=l[c]=l[c]||{},h=e[c]=e[c]||[],p=0,d=u;p<d.length;p+=1){var g=d[p];f[g.featureIndex]||(f[g.featureIndex]=!0,h.push(g))}}return e}(c);for(var d in p)p[d].forEach((function(e){var r=e.feature,n=t.getFeatureState(r.layer[\"source-layer\"],r.id);r.source=r.layer.source,r.layer[\"source-layer\"]&&(r.sourceLayer=r.layer[\"source-layer\"]),r.state=n}));return p}function B(t,e){var r=t.tileID,n=e.tileID;return r.overscaledZ-n.overscaledZ||r.canonical.y-n.canonical.y||r.wrap-n.wrap||r.canonical.x-n.canonical.x}var N=function(t,e){this.max=t,this.onRemove=e,this.reset()};N.prototype.reset=function(){for(var t in this.data)for(var e=0,r=this.data[t];e<r.length;e+=1){var n=r[e];n.timeout&&clearTimeout(n.timeout),this.onRemove(n.value)}return this.data={},this.order=[],this},N.prototype.add=function(t,e,r){var n=this,i=t.wrapped().key;void 0===this.data[i]&&(this.data[i]=[]);var a={value:e,timeout:void 0};if(void 0!==r&&(a.timeout=setTimeout((function(){n.remove(t,a)}),r)),this.data[i].push(a),this.order.push(i),this.order.length>this.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},N.prototype.has=function(t){return t.wrapped().key in this.data},N.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},N.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},N.prototype.getByKey=function(t){var e=this.data[t];return e?e[0].value:null},N.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},N.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),i=this.data[r][n];return this.data[r].splice(n,1),i.timeout&&clearTimeout(i.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(i.value),this.order.splice(this.order.indexOf(r),1),this},N.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this},N.prototype.filter=function(t){var e=[];for(var r in this.data)for(var n=0,i=this.data[r];n<i.length;n+=1){var a=i[n];t(a.value)||e.push(a)}for(var o=0,s=e;o<s.length;o+=1){var l=s[o];this.remove(l.value.tileID,l)}};var j=function(t,e,r){this.context=t;var n=t.gl;this.buffer=n.createBuffer(),this.dynamicDraw=Boolean(r),this.context.unbindVAO(),t.bindElementBuffer.set(this.buffer),n.bufferData(n.ELEMENT_ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?n.DYNAMIC_DRAW:n.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};j.prototype.bind=function(){this.context.bindElementBuffer.set(this.buffer)},j.prototype.updateData=function(t){var e=this.context.gl;this.context.unbindVAO(),this.bind(),e.bufferSubData(e.ELEMENT_ARRAY_BUFFER,0,t.arrayBuffer)},j.prototype.destroy=function(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)};var U={Int8:\"BYTE\",Uint8:\"UNSIGNED_BYTE\",Int16:\"SHORT\",Uint16:\"UNSIGNED_SHORT\",Int32:\"INT\",Uint32:\"UNSIGNED_INT\",Float32:\"FLOAT\"},V=function(t,e,r,n){this.length=e.length,this.attributes=r,this.itemSize=e.bytesPerElement,this.dynamicDraw=n,this.context=t;var i=t.gl;this.buffer=i.createBuffer(),t.bindVertexBuffer.set(this.buffer),i.bufferData(i.ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?i.DYNAMIC_DRAW:i.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};V.prototype.bind=function(){this.context.bindVertexBuffer.set(this.buffer)},V.prototype.updateData=function(t){var e=this.context.gl;this.bind(),e.bufferSubData(e.ARRAY_BUFFER,0,t.arrayBuffer)},V.prototype.enableAttributes=function(t,e){for(var r=0;r<this.attributes.length;r++){var n=e.attributes[this.attributes[r].name];void 0!==n&&t.enableVertexAttribArray(n)}},V.prototype.setVertexAttribPointers=function(t,e,r){for(var n=0;n<this.attributes.length;n++){var i=this.attributes[n],a=e.attributes[i.name];void 0!==a&&t.vertexAttribPointer(a,i.components,t[U[i.type]],!1,this.itemSize,i.offset+this.itemSize*(r||0))}},V.prototype.destroy=function(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)};var q=function(t){this.gl=t.gl,this.default=this.getDefault(),this.current=this.default,this.dirty=!1};q.prototype.get=function(){return this.current},q.prototype.set=function(t){},q.prototype.getDefault=function(){return this.default},q.prototype.setDefault=function(){this.set(this.default)};var H=function(e){function r(){e.apply(this,arguments)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.getDefault=function(){return t.Color.transparent},r.prototype.set=function(t){var 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e=this.gl;e.bindFramebuffer(e.FRAMEBUFFER,t),this.current=t,this.dirty=!1}},e}(q),pt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindRenderbuffer(e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(q),dt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.bindTexture(e.TEXTURE_2D,t),this.current=t,this.dirty=!1}},e}(q),gt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return null},e.prototype.set=function(t){if(t!==this.current||this.dirty){var 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e=this.gl;e.pixelStorei(e.UNPACK_ALIGNMENT,t),this.current=t,this.dirty=!1}},e}(q),xt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_PREMULTIPLY_ALPHA_WEBGL,t),this.current=t,this.dirty=!1}},e}(q),bt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return!1},e.prototype.set=function(t){if(t!==this.current||this.dirty){var e=this.gl;e.pixelStorei(e.UNPACK_FLIP_Y_WEBGL,t),this.current=t,this.dirty=!1}},e}(q),_t=function(t){function e(e,r){t.call(this,e),this.context=e,this.parent=r}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return null},e}(q),wt=function(t){function 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t=this.context.gl,e=this.colorAttachment.get();if(e&&t.deleteTexture(e),this.depthAttachment){var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r)}t.deleteFramebuffer(this.framebuffer)};var Mt=function(t,e,r){this.func=t,this.mask=e,this.range=r};Mt.ReadOnly=!1,Mt.ReadWrite=!0,Mt.disabled=new Mt(519,Mt.ReadOnly,[0,1]);var At=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};At.disabled=new At({func:519,mask:0},0,0,7680,7680,7680);var St=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};St.disabled=new St(St.Replace=[1,0],t.Color.transparent,[!1,!1,!1,!1]),St.unblended=new St(St.Replace,t.Color.transparent,[!0,!0,!0,!0]),St.alphaBlended=new St([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Et=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Et.disabled=new Et(!1,1029,2305),Et.backCCW=new Et(!0,1029,2305);var Ct=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new H(this),this.clearDepth=new G(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new X(this),this.stencilMask=new Z(this),this.stencilFunc=new J(this),this.stencilOp=new K(this),this.stencilTest=new Q(this),this.depthRange=new $(this),this.depthTest=new tt(this),this.depthFunc=new et(this),this.blend=new rt(this),this.blendFunc=new nt(this),this.blendColor=new it(this),this.blendEquation=new at(this),this.cullFace=new ot(this),this.cullFaceSide=new st(this),this.frontFace=new lt(this),this.program=new ct(this),this.activeTexture=new ut(this),this.viewport=new ft(this),this.bindFramebuffer=new ht(this),this.bindRenderbuffer=new pt(this),this.bindTexture=new dt(this),this.bindVertexBuffer=new gt(this),this.bindElementBuffer=new mt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new vt(this),this.pixelStoreUnpack=new yt(this),this.pixelStoreUnpackPremultiplyAlpha=new xt(this),this.pixelStoreUnpackFlipY=new bt(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(t.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=t.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=t.getExtension(\"EXT_disjoint_timer_query\")};Ct.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Ct.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Ct.prototype.createIndexBuffer=function(t,e){return new j(this,t,e)},Ct.prototype.createVertexBuffer=function(t,e,r){return new V(this,t,e,r)},Ct.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Ct.prototype.createFramebuffer=function(t,e,r){return new kt(this,t,e,r)},Ct.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Ct.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Ct.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Ct.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Ct.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,St.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Ct.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Lt=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on(\"data\",(function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on(\"error\",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new D[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a}(r,n,i,this),this._tiles={},this._cache=new N(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(It).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=Math.ceil(t.width/this._source.tileSize)+1,r=Math.ceil(t.height/this._source.tileSize)+1,n=Math.floor(e*r*5),i=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,n):n;this._cache.setMaxSize(i)},r.prototype.handleWrapJump=function(t){var e=Math.round((t-(void 0===this._prevLng?t:this._prevLng))/360);if(this._prevLng=t,e){var r={};for(var n in this._tiles){var i=this._tiles[n];i.tileID=i.tileID.unwrapTo(i.tileID.wrap+e),r[i.tileID.key]=i}for(var a in this._tiles=r,this._timers)clearTimeout(this._timers[a]),delete this._timers[a];for(var o in this._tiles)this._setTileReloadTimer(o,this._tiles[o])}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(Pt(this._source.type)){for(var c={},u={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],g=this._tiles[p];if(g&&!(g.fadeEndTime&&g.fadeEndTime<=t.browser.now())){var m=this.findLoadedParent(d,o);m&&(this._addTile(m.tileID),c[m.tileID.key]=m.tileID),u[p]=d}}for(var v in this._retainLoadedChildren(u,a,s,l),c)l[v]||(this._coveredTiles[v]=!0,l[v]=c[v])}for(var y in l)this._tiles[y].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,c=t;l<c.length;l+=1){var u=c[l],f=this._addTile(u);n[u.key]=u,f.hasData()||e<this._source.maxzoom&&(s[u.key]=u)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],g=this._tiles[d.key];if(!g.hasData()){if(e+1>this._source.maxzoom){var m=d.children(this._source.maxzoom)[0],v=this.getTile(m);if(v&&v.hasData()){n[m.key]=m;continue}}else{var y=d.children(this._source.maxzoom);if(n[y[0].key]&&n[y[1].key]&&n[y[2].key]&&n[y[3].key])continue}for(var x=g.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(g=this.getTile(_))&&x&&(g=this._addTile(_)),g&&(n[_.key]=_,x=g.wasRequested(),g.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1)this._loadedParentTiles[o[a]]=r}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,\"expired\"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),c=s.map((function(t){return o.pointCoordinate(t)})),u=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,g=0,m=c;g<m.length;g+=1){var v=m[g];f=Math.min(f,v.x),h=Math.min(h,v.y),p=Math.max(p,v.x),d=Math.max(d,v.y)}for(var y=function(e){var n=i._tiles[u[e]];if(!n.holdingForFade()){var s=n.tileID,g=Math.pow(2,o.zoom-n.tileID.overscaledZ),m=r*n.queryPadding*t.EXTENT/n.tileSize/g,v=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(v[0].x-m<t.EXTENT&&v[0].y-m<t.EXTENT&&v[1].x+m>=0&&v[1].y+m>=0){var y=l.map((function(t){return s.getTilePoint(t)})),x=c.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:y,cameraQueryGeometry:x,scale:g})}}},x=0;x<u.length;x++)y(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(Pt(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){this._state.updateState(t=t||\"_geojsonTileLayer\",e,r)},r.prototype.removeFeatureState=function(t,e,r){this._state.removeFeatureState(t=t||\"_geojsonTileLayer\",e,r)},r.prototype.getFeatureState=function(t,e){return this._state.getState(t=t||\"_geojsonTileLayer\",e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function It(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function Pt(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function zt(){return new t.window.Worker(Yi.workerUrl)}Lt.maxOverzooming=10,Lt.maxUnderzooming=3;var Ot=\"mapboxgl_preloaded_worker_pool\",Dt=function(){this.active={}};Dt.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Dt.workerCount;)this.workers.push(new zt);return this.active[t]=!0,this.workers.slice()},Dt.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Dt.prototype.isPreloaded=function(){return!!this.active[Ot]},Dt.prototype.numActive=function(){return Object.keys(this.active).length};var Rt,Ft=Math.floor(t.browser.hardwareConcurrency/2);function Bt(){return Rt||(Rt=new Dt),Rt}function Nt(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function jt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Nt(t[n],e[t[n].ref]));return t}Dt.workerCount=Math.max(Math.min(Ft,6),1);var Ut={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function Vt(t,e,r){r.push({command:Ut.addSource,args:[t,e[t]]})}function qt(t,e,r){e.push({command:Ut.removeSource,args:[t]}),r[t]=!0}function Ht(t,e,r,n){qt(t,r,n),Vt(t,e,r)}function Gt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Yt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Wt(t){return t.id}function Xt(t,e){return t[e.id]=e,t}var Zt=function(t,e){this.reset(t,e)};Zt.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},Zt.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Jt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function Kt(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function Qt(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function $t(e,r){var n=[e.x,e.y,0,1];ue(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function te(t,e){return.5+t/e*.5}function ee(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function re(e,r,n,i,a,o,s,l){var c=i?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,g=n.transform.width/n.transform.height,m=!1,v=0;v<d.length;v++){var y=d.get(v);if(y.hidden||y.writingMode===t.WritingMode.vertical&&!m)ce(y.numGlyphs,h);else{m=!1;var x=[y.anchorX,y.anchorY,0,1];if(t.transformMat4(x,x,r),ee(x,f)){var b=te(n.transform.cameraToCenterDistance,x[3]),_=t.evaluateSizeForFeature(c,u,y),w=s?_/b:_*b,T=new t.Point(y.anchorX,y.anchorY),k=$t(T,a).point,M={},A=ae(y,w,!1,l,r,a,o,e.glyphOffsetArray,p,h,k,T,M,g);m=A.useVertical,(A.notEnoughRoom||m||A.needsFlipping&&ae(y,w,!0,l,r,a,o,e.glyphOffsetArray,p,h,k,T,M,g).notEnoughRoom)&&ce(y.numGlyphs,h)}else ce(y.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function ne(t,e,r,n,i,a,o,s,l,c,u){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),g=e.getoffsetX(f-1),m=se(t*d,r,n,i,a,o,s.segment,h,p,l,c,u);if(!m)return null;var v=se(t*g,r,n,i,a,o,s.segment,h,p,l,c,u);return v?{first:m,last:v}:null}function ie(e,r,n,i){return e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function ae(e,r,n,i,a,o,s,l,c,u,f,h,p,d){var g,m=r/24,v=e.lineOffsetX*m,y=e.lineOffsetY*m;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=ne(m,l,v,y,n,f,h,e,c,o,p);if(!w)return{notEnoughRoom:!0};var T=$t(w.first.point,s).point,k=$t(w.last.point,s).point;if(i&&!n){var M=ie(e.writingMode,T,k,d);if(M)return M}g=[w.first];for(var A=e.glyphStartIndex+1;A<x-1;A++)g.push(se(m*l.getoffsetX(A),v,y,n,f,h,e.segment,b,_,c,o,p));g.push(w.last)}else{if(i&&!n){var S=$t(h,a).point,E=e.lineStartIndex+e.segment+1,C=new t.Point(c.getx(E),c.gety(E)),L=$t(C,a),I=L.signedDistanceFromCamera>0?L.point:oe(h,C,S,1,a),P=ie(e.writingMode,S,I,d);if(P)return P}var z=se(m*l.getoffsetX(e.glyphStartIndex),v,y,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p);if(!z)return{notEnoughRoom:!0};g=[z]}for(var O=0,D=g;O<D.length;O+=1){var R=D[O];t.addDynamicAttributes(u,R.point,R.angle)}return{}}function oe(t,e,r,n,i){var a=$t(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function se(e,r,n,i,a,o,s,l,c,u,f,h){var p=i?e-r:e+r,d=p>0?1:-1,g=0;i&&(d*=-1,g=Math.PI),d<0&&(g+=Math.PI);for(var m=d>0?l+s:l+s+1,v=a,y=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((m+=d)<l||m>=c)return null;if(y=v,w.push(v),void 0===(v=h[m])){var T=new t.Point(u.getx(m),u.gety(m)),k=$t(T,f);if(k.signedDistanceFromCamera>0)v=h[m]=k.point;else{var M=m-d;v=oe(0===x?o:new t.Point(u.getx(M),u.gety(M)),T,y,_-x+1,f)}}x+=b,b=y.dist(v)}var A=(_-x)/b,S=v.sub(y),E=S.mult(A)._add(y);E._add(S._unit()._perp()._mult(n*d));var C=g+Math.atan2(v.y-y.y,v.x-y.x);return w.push(E),{point:E,angle:C,path:w}}Jt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Jt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Jt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Jt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Jt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Jt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var c=this.circles[3*l],u=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:c-f,y1:u-f,x2:c+f,y2:u+f})}return a?o.filter(a):o}return this._forEachCell(t,e,r,n,this._queryCell,o,{hitTest:i,seenUids:{box:{},circle:{}}},a),i?o.length>0:o},Jt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var c=[];return this._forEachCell(a,s,o,l,this._queryCellCircle,c,{hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}},i),n?c.length>0:c},Jt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Jt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Jt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Jt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,c=this.boxCells[i];if(null!==c)for(var u=this.bboxes,f=0,h=c;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=u[d+2]&&e<=u[d+3]&&r>=u[d+0]&&n>=u[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:u[d],y1:u[d+1],x2:u[d+2],y2:u[d+3]})}}}var g=this.circleCells[i];if(null!==g)for(var m=this.circles,v=0,y=g;v<y.length;v+=1){var x=y[v];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(m[b],m[b+1],m[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=m[b],w=m[b+1],T=m[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Jt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,c=o.seenUids,u=this.boxCells[i];if(null!==u)for(var f=this.bboxes,h=0,p=u;h<p.length;h+=1){var d=p[h];if(!c.box[d]){c.box[d]=!0;var g=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[g+0],f[g+1],f[g+2],f[g+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var m=this.circleCells[i];if(null!==m)for(var v=this.circles,y=0,x=m;y<x.length;y+=1){var b=x[y];if(!c.circle[b]){c.circle[b]=!0;var _=3*b;if(this._circlesCollide(v[_],v[_+1],v[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Jt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),c=this._convertToYCellCoord(e),u=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=u;h++)for(var p=c;p<=f;p++)if(i.call(this,t,e,r,n,this.xCellCount*p+h,a,o,s))return},Jt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Jt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Jt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Jt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-i)/2,u=Math.abs(e-(i+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var f=l-s,h=u-c;return f*f+h*h<=r*r};var le=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ce(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(le,3*n)}}function ue(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var fe=function(t,e,r){void 0===e&&(e=new Jt(t.width+200,t.height+200,25)),void 0===r&&(r=new Jt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+100,this.screenBottomBoundary=t.height+100,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function he(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}fe.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,c=t.x2*o+a.point.x,u=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,c,u)||!e&&this.grid.hitTest(s,l,c,u,i)?{box:[],offscreen:!1}:{box:[s,l,c,u],offscreen:this.isOffscreen(s,l,c,u)}},fe.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,c,u,f,h,p){var d=[],g=new t.Point(r.anchorX,r.anchorY),m=$t(g,o),v=te(this.transform.cameraToCenterDistance,m.signedDistanceFromCamera),y=(u?a/v:a*v)/t.ONE_EM,x=$t(g,s).point,b=ne(y,i,r.lineOffsetX*y,r.lineOffsetY*y,!1,x,g,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*v+p,M=new t.Point(-100,-100),A=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new Zt,E=b.first,C=b.last,L=[],I=E.path.length-1;I>=1;I--)L.push(E.path[I]);for(var P=1;P<C.path.length;P++)L.push(C.path[P]);var z=2.5*k;if(l){var O=L.map((function(t){return $t(t,l)}));L=O.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:O.map((function(t){return t.point}))}var D=[];if(L.length>0){for(var R=L[0].clone(),F=L[0].clone(),B=1;B<L.length;B++)R.x=Math.min(R.x,L[B].x),R.y=Math.min(R.y,L[B].y),F.x=Math.max(F.x,L[B].x),F.y=Math.max(F.y,L[B].y);D=R.x>=M.x&&F.x<=A.x&&R.y>=M.y&&F.y<=A.y?[L]:F.x<M.x||R.x>A.x||F.y<M.y||R.y>A.y?[]:t.clipLine([L],M.x,M.y,A.x,A.y)}for(var N=0,j=D;N<j.length;N+=1){var U;S.reset(j[N],.25*k),U=S.length<=.5*k?1:Math.ceil(S.paddedLength/z)+1;for(var V=0;V<U;V++){var q=V/Math.max(U-1,1),H=S.lerp(q),G=H.x+100,Y=H.y+100;d.push(G,Y,k,0);var W=G-k,X=Y-k,Z=G+k,J=Y+k;if(T=T&&this.isOffscreen(W,X,Z,J),w=w||this.isInsideGrid(W,X,Z,J),!e&&this.grid.hitTestCircle(G,Y,k,f)&&(_=!0,!c))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!c&&_||!w?[]:d,offscreen:T,collisionDetected:_}},fe.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var c=l[s],u=new t.Point(c.x+100,c.y+100);n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y),r.push(u)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var g=d[p],m=g.key;if(void 0===f[m.bucketInstanceId]&&(f[m.bucketInstanceId]={}),!f[m.bucketInstanceId][m.featureIndex]){var v=[new t.Point(g.x1,g.y1),new t.Point(g.x2,g.y1),new t.Point(g.x2,g.y2),new t.Point(g.x1,g.y2)];t.polygonIntersectsPolygon(r,v)&&(f[m.bucketInstanceId][m.featureIndex]=!0,void 0===h[m.bucketInstanceId]&&(h[m.bucketInstanceId]=[]),h[m.bucketInstanceId].push(m.featureIndex))}}return h},fe.prototype.insertCollisionBox=function(t,e,r,n,i){(e?this.ignoredGrid:this.grid).insert({bucketInstanceId:r,featureIndex:n,collisionGroupID:i},t[0],t[1],t[2],t[3])},fe.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},fe.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return ue(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+100,(-i[1]/i[3]+1)/2*this.transform.height+100),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},fe.prototype.isOffscreen=function(t,e,r,n){return r<100||t>=this.screenRightBoundary||n<100||e>this.screenBottomBoundary},fe.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},fe.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var pe=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};pe.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var de=function(t,e,r,n,i){this.text=new pe(t?t.text:null,e,r,i),this.icon=new pe(t?t.icon:null,e,n,i)};de.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var ge=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},me=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},ve=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},ye=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function xe(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point(s+c[0]*a,l+c[1]*a)}function be(e,r,n,i,a,o){var s=e.x1,l=e.x2,c=e.y1,u=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:c+p.y,x2:l+p.x,y2:u+p.y,anchorPointX:f,anchorPointY:h}}ye.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var _e=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new fe(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new ye(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function we(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}_e.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,c=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),u=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h=\"map\"===l.get(\"text-pitch-alignment\"),p=\"map\"===l.get(\"text-rotation-alignment\"),d=he(n,1,this.transform.zoom),g=Kt(f,h,p,this.transform,d),m=null;if(h){var v=Qt(f,h,p,this.transform,d);m=t.multiply([],this.transform.labelPlaneMatrix,v)}this.retainedQueryData[a.bucketInstanceId]=new ve(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var y={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:g,labelToScreenMatrix:m,scale:c,textPixelRatio:u,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x];e.push({sortKey:_.sortKey,symbolInstanceStart:_.symbolInstanceStart,symbolInstanceEnd:_.symbolInstanceEnd,parameters:y})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:y})}},_e.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d){var g,m=[f.textOffset0,f.textOffset1],v=xe(t,r,n,m,i),y=this.collisionIndex.placeCollisionBox(be(e,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate);if(!d||0!==this.collisionIndex.placeCollisionBox(be(d,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate).box.length)return y.box.length>0?(this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(g=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:m,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:g},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:v,placedGlyphBoxes:y}):void 0},_e.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,c=a.textLabelPlaneMatrix,u=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,g=a.collisionGroup,m=s.get(\"text-optional\"),v=s.get(\"icon-optional\"),y=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=y&&(x||!o.hasIconData()||v),M=x&&(y||!o.hasTextData()||m);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var A=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new ge(!1,!1,!1);else{var p,T=!1,A=!1,S=!0,E=null,C={box:null,offscreen:null},L={box:null,offscreen:null},I=null,P=null,z=0,O=0,D=0;a.textFeatureIndex?z=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(z=e.featureIndex),a.verticalTextFeatureIndex&&(O=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,i.markUsedOrientation(o,n=a,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length&&(s[i]===t.WritingMode.vertical?(C=n(),L=C):C=r(),!(C&&C.box&&C.box.length));i+=1);else C=r()};if(s.get(\"text-variable-anchor\")){var N=s.get(\"text-variable-anchor\");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,c=e.textBoxScale,u=w&&!x?r:null,h={box:[],offscreen:!1},p=y?2*N.length:N.length,d=0;d<p;++d){var m=i.attemptAnchorPlacement(N[d%N.length],t,a,s,c,b,_,f,l,g,d>=N.length,e,o,n,u);if(m&&(h=m.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=m.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&!(C&&C.box&&C.box.length)&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),C&&(T=C.box,S=C.offscreen);var V=F(C&&C.box);if(!T&&i.prevPlacement){var q=i.prevPlacement.variableOffsets[e.crossTileID];q&&(i.variableOffsets[e.crossTileID]=q,i.markUsedJustification(o,q.anchor,e,V))}}else{var H=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,y,f,l,g.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return H(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?H(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(C&&C.box&&C.box.length)}}if(T=(p=C)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Y=t.evaluateSizeForFeature(o.textSizeData,d,G),W=s.get(\"text-padding\");I=i.collisionIndex.placeCollisionCircles(y,G,o.lineVertexArray,o.glyphOffsetArray,Y,l,c,u,n,_,g.predicate,e.collisionCircleDiameter,W),T=y||I.circles.length>0&&!I.collisionDetected,S=S&&I.offscreen}if(a.iconFeatureIndex&&(D=a.iconFeatureIndex),a.iconBox){var X=function(t){var e=w&&E?be(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,g.predicate)};A=L&&L.box&&L.box.length&&a.verticalIconBox?(P=X(a.verticalIconBox)).box.length>0:(P=X(a.iconBox)).box.length>0,S=S&&P.offscreen}var Z=m||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,J=v||0===e.numIconVertices;if(Z||J?J?Z||(A=A&&T):T=A&&T:A=T=A&&T,T&&p&&p.box&&i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,L&&L.box&&O?O:z,g.ID),A&&P&&i.collisionIndex.insertCollisionBox(P.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,D,g.ID),I&&(T&&i.collisionIndex.insertCollisionCircles(I.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,z,g.ID),n)){var K=o.bucketInstanceId,Q=i.collisionCircleArrays[K];void 0===Q&&(Q=i.collisionCircleArrays[K]=new me);for(var $=0;$<I.circles.length;$+=4)Q.circles.push(I.circles[$+0]),Q.circles.push(I.circles[$+1]),Q.circles.push(I.circles[$+2]),Q.circles.push(I.collisionDetected?1:0)}i.placements[e.crossTileID]=new ge(T||k,A||M,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var C=S[E];A(o.symbolInstances.get(C),o.collisionArrays[C])}else for(var L=e.symbolInstanceStart;L<e.symbolInstanceEnd;L++)A(o.symbolInstances.get(L),o.collisionArrays[L]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var I=this.collisionCircleArrays[o.bucketInstanceId];t.invert(I.invProjMatrix,l),I.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},_e.prototype.markUsedJustification=function(e,r,n,i){var a;a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:{left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex}[t.getAnchorJustification(r)];for(var o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];o<s.length;o+=1){var l=s[o];l>=0&&(e.text.placedSymbolArray.get(l).crossTileID=a>=0&&l!==a?0:n.crossTileID)}},_e.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1)e.text.placedSymbolArray.get(s[o]).placedOrientation=i;n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},_e.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],c=i[s];c?(this.opacities[s]=new de(c,n,l.text,l.icon),r=r||l.text!==c.text.placed||l.icon!==c.icon.placed):(this.opacities[s]=new de(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var u in i){var f=i[u];if(!this.opacities[u]){var h=new de(f,n,!1,!1);h.isHidden()||(this.opacities[u]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},_e.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},_e.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new de(null,0,!1,!1,!0),s=a.get(\"text-allow-overlap\"),l=a.get(\"icon-allow-overlap\"),c=a.get(\"text-variable-anchor\"),u=\"map\"===a.get(\"text-rotation-alignment\"),f=\"map\"===a.get(\"text-pitch-alignment\"),h=\"none\"!==a.get(\"icon-text-fit\"),p=new de(null,0,s&&(l||!e.hasIconData()||a.get(\"icon-optional\")),l&&(s||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},g=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,g=a.crossTileID,m=i.opacities[g];r[g]?m=o:m||(i.opacities[g]=m=p),r[g]=!0;var v=a.numIconVertices>0,y=i.placedOrientations[a.crossTileID],x=y===t.WritingMode.vertical,b=y===t.WritingMode.horizontal||y===t.WritingMode.horizontalOnly;if(s>0||l>0){var _=Le(m.text);d(e.text,s,x?Ie:_),d(e.text,l,b?Ie:_);var w=m.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=w||x?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=w||b?1:0);var T=i.variableOffsets[a.crossTileID];T&&i.markUsedJustification(e,T.anchor,a,y);var k=i.placedOrientations[a.crossTileID];k&&(i.markUsedJustification(e,\"left\",a,k),i.markUsedOrientation(e,k,a))}if(v){var M=Le(m.icon),A=!(h&&a.verticalPlacedIconSymbolIndex&&x);a.placedIconSymbolIndex>=0&&(d(e.icon,a.numIconVertices,A?M:Ie),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=m.icon.isHidden()),a.verticalPlacedIconSymbolIndex>=0&&(d(e.icon,a.numVerticalIconVertices,A?Ie:M),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=m.icon.isHidden())}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var S=e.collisionArrays[n];if(S){var E=new t.Point(0,0);if(S.textBox||S.verticalTextBox){var C=!0;if(c){var L=i.variableOffsets[g];L?(E=xe(L.anchor,L.width,L.height,L.textOffset,L.textBoxScale),u&&E._rotate(f?i.transform.angle:-i.transform.angle)):C=!1}S.textBox&&we(e.textCollisionBox.collisionVertexArray,m.text.placed,!C||x,E.x,E.y),S.verticalTextBox&&we(e.textCollisionBox.collisionVertexArray,m.text.placed,!C||b,E.x,E.y)}var I=Boolean(!b&&S.verticalIconBox);S.iconBox&&we(e.iconCollisionBox.collisionVertexArray,m.icon.placed,I,h?E.x:0,h?E.y:0),S.verticalIconBox&&we(e.iconCollisionBox.collisionVertexArray,m.icon.placed,!I,h?E.x:0,h?E.y:0)}}},m=0;m<e.symbolInstances.length;m++)g(m);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var v=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=v.invProjMatrix,e.placementViewportMatrix=v.viewportMatrix,e.collisionCircleArray=v.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},_e.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},_e.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},_e.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},_e.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},_e.prototype.setStale=function(){this.stale=!0};var Te=Math.pow(2,25),ke=Math.pow(2,24),Me=Math.pow(2,17),Ae=Math.pow(2,16),Se=Math.pow(2,9),Ee=Math.pow(2,8),Ce=Math.pow(2,1);function Le(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Te+e*ke+r*Me+e*Ae+r*Se+e*Ee+r*Ce+e}var Ie=0,Pe=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Pe.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;)if(e.getBucketParts(a,n,t[this._currentTileIndex],this._sortAcrossTiles),this._currentTileIndex++,i())return!0;for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;)if(e.placeLayerBucketPart(a[this._currentPartIndex],this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0;return!1};var ze=function(t,e,r,n,i,a,o){this.placement=new _e(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};ze.prototype.isDone=function(){return this._done},ze.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Pe(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},ze.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Oe=512/t.EXTENT/2,De=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};De.prototype.getScaledCoordinates=function(e,r){var n=Oe/Math.pow(2,r.canonical.z-this.tileID.canonical.z);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*n),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*n)}},De.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,c=o;l<c.length;l+=1){var u=c[l];if(Math.abs(u.coord.x-s.x)<=n&&Math.abs(u.coord.y-s.y)<=n&&!r[u.crossTileID]){r[u.crossTileID]=!0,a.crossTileID=u.crossTileID;break}}}}};var Re=function(){this.maxCrossTileID=0};Re.prototype.generate=function(){return++this.maxCrossTileID};var Fe=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Fe.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Fe.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++)e.symbolInstances.get(n).crossTileID=0;this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var c=o[t.scaledTo(Number(a)).key];c&&c.findMatches(e.symbolInstances,t,i)}}for(var u=0;u<e.symbolInstances.length;u++){var f=e.symbolInstances.get(u);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new De(t,e.symbolInstances,e.bucketInstanceId),!0},Fe.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1)delete this.usedCrossTileIDs[t][i[n].crossTileID]},Fe.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Be=function(){this.layerIndexes={},this.crossTileIDs=new Re,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Be.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Fe);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.getBucket(t);c&&t.id===c.layerIds[0]&&(c.bucketInstanceId||(c.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,c,this.crossTileIDs)&&(i=!0),a[c.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Be.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var Ne=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return\"source.canvas\"!==t.identifier})))},je=t.pick(Ut,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Ue=t.pick(Ut,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),Ve=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i,a=t.styleSpec.$root[n];a.required&&null!=(i=\"version\"===n?r:\"array\"===a.type?[]:{})&&(e[n]=i)}return e}(),qe=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new k(Bt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new T(256,512),this.crossTileSymbolIndex=new Be,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){o.dispatcher.broadcast(\"syncRTLPluginState\",{pluginStatus:e.pluginStatus,pluginURL:e.pluginURL},(function(e,r){if(t.triggerPluginCompletionEvent(e),r&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on(\"data\",(function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._load(Ve,!1)},r.prototype._load=function(e,r){if(!r||!Ne(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=jt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new w(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,u())})),c=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){c=null,o||(o=t,a=e,u())}));function u(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],c=l.width,u=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,g=l.stretchX,m=l.stretchY,v=l.content,y=new t.RGBAImage({width:c,height:u});t.RGBAImage.copy(e,y,{x:f,y:h},{x:0,y:0},{width:c,height:u}),r[s]={data:y,pixelRatio:d,sdf:p,stretchX:g,stretchY:m,content:v}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),c&&(c.cancel(),c=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=this._layers[n[r]];\"custom\"!==i.type&&e.push(i.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];\"reload\"===o?this._reloadSource(a):\"clear\"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var c=0,u=this._order;c<u.length;c+=1){var f=this._layers[u[c]];f.recalculate(e,this._availableImages),!f.isHidden(e.zoom)&&f.source&&(this.sourceCaches[f.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies([\"icons\",\"patterns\"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),Ne(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=jt(e.layers);var n=function(e,r){if(!e)return[{command:Ut.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Ut.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Ut.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Ut.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Ut.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Ut.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Ut.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Ut.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Ut.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Ut.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||qt(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&Gt(e,r,a)?n.push({command:Ut.setGeoJSONSourceData,args:[a,r[a].data]}):Ht(a,r,n,i)):Vt(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:Ut.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,c,u,f=(e=e||[]).map(Wt),h=r.map(Wt),p=e.reduce(Xt,{}),d=r.reduce(Xt,{}),g=f.slice(),m=Object.create(null);for(i=0,a=0;i<f.length;i++)d.hasOwnProperty(o=f[i])?a++:(n.push({command:Ut.removeLayer,args:[o]}),g.splice(g.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)g[g.length-1-i]!==(o=h[h.length-1-i])&&(p.hasOwnProperty(o)?(n.push({command:Ut.removeLayer,args:[o]}),g.splice(g.lastIndexOf(o,g.length-a),1)):a++,n.push({command:Ut.addLayer,args:[d[o],c=g[g.length-i]]}),g.splice(g.length-i,0,o),m[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!m[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(u in Yt(s.layout,l.layout,n,o,null,Ut.setLayoutProperty),Yt(s.paint,l.paint,n,o,null,Ut.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Ut.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Ut.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}));for(u in l)l.hasOwnProperty(u)&&!s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}))}else n.push({command:Ut.removeLayer,args:[o]}),c=g[g.lastIndexOf(o)+1],n.push({command:Ut.addLayer,args:[l,c]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:Ut.setStyle,args:[r]}]}return n}(this.serialize(),e).filter((function(t){return!(t.command in Ue)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in je)}));if(i.length>0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Lt(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(Ne(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var c=l[s][o];if(c)for(var u=0,f=c;u<f.length;u+=1)i.push(f[u])}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var h=[],p=this._order.length-1;p>=0;p--){var d=this._order[p];if(r(d))for(var g=i.length-1;g>=0;g--){var m=i[g].feature;if(n[m.layer.id]<p)break;h.push(m),i.pop()}else for(var v=0,y=t;v<y.length;v+=1){var x=y[v][d];if(x)for(var b=0,_=x;b<_.length;b+=1)h.push(_[b].feature)}}return h},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var c=[];for(var u in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[u]||c.push(F(this.sourceCaches[u],this._layers,this._serializedLayers,e,r,n));return this.placement&&c.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),c=[],u=0,f=Object.keys(l).map(Number);u<f.length;u+=1)c.push(o[f[u]]);c.sort(B);for(var h=function(){var r=d[p],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],c=n[a];c.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var u=0,f=c;u<f.length;u+=1)o.push(f[u])}},p=0,d=c;p<d.length;p+=1)h();var g=function(e){s[e].forEach((function(n){var i=n.feature,a=r[t[e].source].getFeatureState(i.layer[\"source-layer\"],i.id);i.source=i.layer.source,i.layer[\"source-layer\"]&&(i.sourceLayer=i.layer[\"source-layer\"]),i.state=a}))};for(var m in s)g(m);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(c)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&Ne(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback),this._layers)this._layers[e].setEventedParent(null);for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},c=0,u=this._order;c<u.length;c+=1){var f=this._layers[u[c]];if(\"symbol\"===f.type){if(!l[f.source]){var h=this.sourceCaches[f.source];l[f.source]=h.getRenderableIds(!0).map((function(t){return h.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var p=this.crossTileSymbolIndex.addLayer(f,l[f.source],e.center.lng);o=o||p}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new ze(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var d=0,g=this._order;d<g.length;d+=1){var m=this._layers[g[d]];\"symbol\"===m.type&&this.placement.updateLayerOpacities(m,l[m.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);qe.getSourceType=function(t){return D[t]},qe.setSourceType=function(t,e){D[t]=e},qe.registerForPluginStateChange=t.registerForPluginStateChange;var He=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Ge=vr(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),Ye=vr(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),We=vr(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),Xe=vr(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Ze=vr(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Je=vr(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),Ke=vr(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),Qe=vr(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),$e=vr(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),tr=vr(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),er=vr(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),rr=vr(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),nr=vr(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ir=vr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),ar=vr(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),or=vr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),sr=vr(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),lr=vr(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),cr=vr(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),ur=vr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),fr=vr(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),hr=vr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),pr=vr(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),dr=vr(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),gr=vr(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),mr=vr(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function vr(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o=\"float\"===i?\"vec2\":\"vec4\",s=a.match(/color/)?\"color\":o;return n[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}))}}var yr=Object.freeze({__proto__:null,prelude:Ge,background:Ye,backgroundPattern:We,circle:Xe,clippingMask:Ze,heatmap:Je,heatmapTexture:Ke,collisionBox:Qe,collisionCircle:$e,debug:tr,fill:er,fillOutline:rr,fillOutlinePattern:nr,fillPattern:ir,fillExtrusion:ar,fillExtrusionPattern:or,hillshadePrepare:sr,hillshade:lr,line:cr,lineGradient:ur,linePattern:fr,lineSDF:hr,raster:pr,symbolIcon:dr,symbolSDF:gr,symbolTextAndIcon:mr}),xr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};xr.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,c=0;!l&&c<n.length;c++)this.boundPaintVertexBuffers[c]!==n[c]&&(l=!0);t.extVertexArrayObject&&this.vao&&this.boundProgram===e&&this.boundLayoutVertexBuffer===r&&!l&&this.boundIndexBuffer===i&&this.boundVertexOffset===a&&this.boundDynamicVertexBuffer===o&&this.boundDynamicVertexBuffer2===s?(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind()):this.freshBind(e,r,n,i,a,o,s)},xr.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,c=this.context,u=c.gl;if(c.extVertexArrayObject)this.vao&&this.destroy(),this.vao=c.extVertexArrayObject.createVertexArrayOES(),c.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=c.currentNumAttributes||0;for(var f=l;f<s;f++)u.disableVertexAttribArray(f)}e.enableAttributes(u,t);for(var h=0,p=r;h<p.length;h+=1)p[h].enableAttributes(u,t);a&&a.enableAttributes(u,t),o&&o.enableAttributes(u,t),e.bind(),e.setVertexAttribPointers(u,t,i);for(var d=0,g=r;d<g.length;d+=1){var m=g[d];m.bind(),m.setVertexAttribPointers(u,t,i)}a&&(a.bind(),a.setVertexAttribPointers(u,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(u,t,i)),c.currentNumAttributes=l},xr.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var br=function(t,e,r,n,i){var a=t.gl;this.program=a.createProgram();var o=r?r.defines():[];i&&o.push(\"#define OVERDRAW_INSPECTOR;\");var s=o.concat(Ge.fragmentSource,e.fragmentSource).join(\"\\n\"),l=o.concat(Ge.vertexSource,e.vertexSource).join(\"\\n\"),c=a.createShader(a.FRAGMENT_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(c,s),a.compileShader(c),a.attachShader(this.program,c);var u=a.createShader(a.VERTEX_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(u,l),a.compileShader(u),a.attachShader(this.program,u);for(var f=r?r.layoutAttributes:[],h=0;h<f.length;h++)a.bindAttribLocation(this.program,h,f[h].name);a.linkProgram(this.program),a.deleteShader(u),a.deleteShader(c),this.numAttributes=a.getProgramParameter(this.program,a.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var g=a.getActiveAttrib(this.program,d);g&&(this.attributes[g.name]=a.getAttribLocation(this.program,g.name))}for(var m=a.getProgramParameter(this.program,a.ACTIVE_UNIFORMS),v=0;v<m;v++){var y=a.getActiveUniform(this.program,v);y&&(p[y.name]=a.getUniformLocation(this.program,y.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r?r.getUniforms(t,p):[]}}};function _r(t,e,r){var n=1/he(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}br.prototype.draw=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g){var m,v=t.gl;if(!this.failedToCreate){for(var y in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[y].set(o[y]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(m={},m[v.LINES]=2,m[v.TRIANGLES]=3,m[v.LINE_STRIP]=1,m)[e],b=0,_=u.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new xr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],c,w.vertexOffset,d,g),v.drawElements(e,w.primitiveLength*x,v.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var wr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var c=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[c.r,c.g,c.b],u_vertical_gradient:+n,u_opacity:i}},Tr=function(e,r,n,i,a,o,s){return t.extend(wr(e,r,n,i),_r(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},kr=function(t){return{u_matrix:t}},Mr=function(e,r,n,i){return t.extend(kr(e),_r(n,r,i))},Ar=function(t,e){return{u_matrix:t,u_world:e}},Sr=function(e,r,n,i,a){return t.extend(Mr(e,r,n,i),{u_world:a})},Er=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=he(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Cr=function(t,e,r){var n=he(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Lr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Ir=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Pr=function(t){return{u_matrix:t}},zr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:he(e,1,r),u_intensity:n}},Or=function(e,r,n){var i=e.transform;return{u_matrix:Nr(e,r,n),u_ratio:1/he(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Dr=function(e,r,n){return t.extend(Or(e,r,n),{u_image:0})},Rr=function(e,r,n,i){var a=e.transform,o=Br(r,a);return{u_matrix:Nr(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/he(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Fr=function(e,r,n,i,a){var o=e.lineAtlas,s=Br(r,e.transform),l=\"round\"===n.layout.get(\"line-cap\"),c=o.getDash(i.from,l),u=o.getDash(i.to,l),f=c.width*a.fromScale,h=u.width*a.toScale;return t.extend(Or(e,r,n),{u_patternscale_a:[s/f,-c.height/2],u_patternscale_b:[s/h,-u.height/2],u_sdfgamma:o.width/(256*Math.min(f,h)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:c.y,u_tex_y_b:u.y,u_mix:a.t})};function Br(t,e){return 1/he(t,1,e.tileZoom)}function Nr(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var jr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:Ur(i.paint.get(\"raster-hue-rotate\"))};var a,o};function Ur(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Vr,qr=function(t,e,r,n,i,a,o,s,l,c){var u=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:u.cameraToCenterDistance,u_pitch:u.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:u.width/u.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:c,u_texture:0}},Hr=function(e,r,n,i,a,o,s,l,c,u,f){var h=a.transform;return t.extend(qr(e,r,n,i,a,o,s,l,c,u),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},Gr=function(e,r,n,i,a,o,s,l,c,u){return t.extend(Hr(e,r,n,i,a,o,s,l,!0,c,!0),{u_texsize_icon:u,u_texture_icon:1})},Yr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},Wr=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,c=Math.pow(2,n.tileID.overscaledZ),u=n.tileSize*Math.pow(2,r.transform.tileZoom)/c,f=u*(n.tileID.canonical.x+n.tileID.wrap*c),h=u*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/he(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},Xr={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function Zr(e,r,n,i,a,o,s){for(var l=e.context,c=l.gl,u=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d<i.length;d++){var g=i[d],m=r.getTile(g),v=m.getBucket(n);if(v){var y=g.posMatrix;0===a[0]&&0===a[1]||(y=e.translatePosMatrix(g.posMatrix,m,a,o));var x=s?v.textCollisionBox:v.iconCollisionBox,b=v.collisionCircleArray;if(b.length>0){var _=t.create(),w=y;t.mul(_,v.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,v.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&u.draw(l,c.LINES,Mt.disabled,At.disabled,e.colorModeForRenderPass(),Et.disabled,Cr(y,e.transform,m),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var M=0,A=0,S=f;A<S.length;A+=1)for(var E=S[A],C=0;C<E.circleArray.length/4;C++){var L=4*C,I=E.circleArray[L+0],P=E.circleArray[L+1],z=E.circleArray[L+2],O=E.circleArray[L+3];k.emplace(M++,I,P,z,O,0),k.emplace(M++,I,P,z,O,1),k.emplace(M++,I,P,z,O,2),k.emplace(M++,I,P,z,O,3)}(!Vr||Vr.length<2*h)&&(Vr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var D=l.createIndexBuffer(Vr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=Lr(N.transform,N.invTransform,e.transform);T.draw(l,c.TRIANGLES,Mt.disabled,At.disabled,e.colorModeForRenderPass(),Et.disabled,j,n.id,R,D,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),D.destroy()}}var Jr=t.identity(new Float32Array(16));function Kr(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,c=-(s.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point((l/a+u[0])*o,(c/a+u[1])*o)}function Qr(e,r,n,i,a,o,s,l,c,u,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,g={};p.clear();for(var m=0;m<h.length;m++){var v=h.get(m),y=v.hidden||!v.crossTileID||e.allowVerticalPlacement&&!v.placedOrientation?null:i[v.crossTileID];if(y){var x=new t.Point(v.anchorX,v.anchorY),b=$t(x,n?l:s),_=te(o.cameraToCenterDistance,b.signedDistanceFromCamera),w=a.evaluateSizeForFeature(e.textSizeData,u,v)*_/t.ONE_EM;n&&(w*=e.tilePixelRatio/c);for(var T=Kr(y.anchor,y.width,y.height,y.textOffset,y.textBoxScale,w),k=n?$t(x.add(T),s).point:b.point.add(r?T.rotate(-o.angle):T),M=e.allowVerticalPlacement&&v.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,A=0;A<v.numGlyphs;A++)t.addDynamicAttributes(p,k,M);f&&v.associatedIconIndex>=0&&(g[v.associatedIconIndex]={shiftedAnchor:k,angle:M})}else ce(v.numGlyphs,p)}if(f){d.clear();for(var S=e.icon.placedSymbolArray,E=0;E<S.length;E++){var C=S.get(E);if(C.hidden)ce(C.numGlyphs,d);else{var L=g[E];if(L)for(var I=0;I<C.numGlyphs;I++)t.addDynamicAttributes(d,L.shiftedAnchor,L.angle);else ce(C.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function $r(t,e,r){return r.iconsInText&&e?\"symbolTextAndIcon\":t?\"symbolSDF\":\"symbolIcon\"}function tn(e,r,n,i,a,o,s,l,c,u,f,h){for(var p=e.context,d=p.gl,g=e.transform,m=\"map\"===l,v=\"map\"===c,y=m&&\"point\"!==n.layout.get(\"symbol-placement\"),x=m&&!v&&!y,b=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),_=e.depthModeForSublayer(0,Mt.ReadOnly),w=n.layout.get(\"text-variable-anchor\"),T=[],k=0,M=i;k<M.length;k+=1){var A=M[k],S=r.getTile(A),E=S.getBucket(n);if(E){var C=a?E.text:E.icon;if(C&&C.segments.get().length){var L=C.programConfigurations.get(n.id),I=a||E.sdfIcons,P=a?E.textSizeData:E.iconSizeData,z=v||0!==g.pitch,O=e.useProgram($r(I,a,E),L),D=t.evaluateSizeForZoom(P,g.zoom),R=void 0,F=[0,0],B=void 0,N=void 0,j=null,U=void 0;if(a)B=S.glyphAtlasTexture,N=d.LINEAR,R=S.glyphAtlasTexture.size,E.iconsInText&&(F=S.imageAtlasTexture.size,j=S.imageAtlasTexture,U=z||e.options.rotating||e.options.zooming||\"composite\"===P.kind||\"camera\"===P.kind?d.LINEAR:d.NEAREST);else{var V=1!==n.layout.get(\"icon-size\").constantOr(0)||E.iconsNeedLinear;B=S.imageAtlasTexture,N=I||e.options.rotating||e.options.zooming||V||z?d.LINEAR:d.NEAREST,R=S.imageAtlasTexture.size}var q=he(S,1,e.transform.zoom),H=Kt(A.posMatrix,v,m,e.transform,q),G=Qt(A.posMatrix,v,m,e.transform,q),Y=w&&E.hasTextData(),W=\"none\"!==n.layout.get(\"icon-text-fit\")&&Y&&E.hasIconData();y&&re(E,A.posMatrix,e,a,H,G,v,u);var X=e.translatePosMatrix(A.posMatrix,S,o,s),Z=y||a&&w||W?Jr:H,J=e.translatePosMatrix(G,S,o,s,!0),K=I&&0!==n.paint.get(a?\"text-halo-width\":\"icon-halo-width\").constantOr(1),Q={program:O,buffers:C,uniformValues:I?E.iconsInText?Gr(P.kind,D,x,v,e,X,Z,J,R,F):Hr(P.kind,D,x,v,e,X,Z,J,a,R,!0):qr(P.kind,D,x,v,e,X,Z,J,a,R),atlasTexture:B,atlasTextureIcon:j,atlasInterpolation:N,atlasInterpolationIcon:U,isSDF:I,hasHalo:K};if(b)for(var $=0,tt=C.segments.get();$<tt.length;$+=1){var et=tt[$];T.push({segments:new t.SegmentVector([et]),sortKey:et.sortKey,state:Q})}else T.push({segments:C.segments,sortKey:0,state:Q})}}}b&&T.sort((function(t,e){return t.sortKey-e.sortKey}));for(var rt=0,nt=T;rt<nt.length;rt+=1){var it=nt[rt],at=it.state;if(p.activeTexture.set(d.TEXTURE0),at.atlasTexture.bind(at.atlasInterpolation,d.CLAMP_TO_EDGE),at.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),at.atlasTextureIcon&&at.atlasTextureIcon.bind(at.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),at.isSDF){var ot=at.uniformValues;at.hasHalo&&(ot.u_is_halo=1,en(at.buffers,it.segments,n,e,at.program,_,f,h,ot)),ot.u_is_halo=0}en(at.buffers,it.segments,n,e,at.program,_,f,h,at.uniformValues)}}function en(t,e,r,n,i,a,o,s,l){var c=n.context;i.draw(c,c.gl.TRIANGLES,a,o,s,Et.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function rn(t,e,r,n,i,a,o){var s,l,c,u,f,h=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),g=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=h.LINES):(l=d?\"fillPattern\":\"fill\",s=h.TRIANGLES);for(var m=0,v=n;m<v.length;m+=1){var y=v[m],x=e.getTile(y);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(g));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,M=k.patternPositions[T.to.toString()],A=k.patternPositions[T.from.toString()];M&&A&&_.setConstantPatternPositions(M,A)}var S=t.translatePosMatrix(y.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){u=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];c=\"fillOutlinePattern\"===l&&d?Sr(S,t,g,x,E):Ar(S,E)}else u=b.indexBuffer,f=b.segments,c=d?Mr(S,t,g,x):kr(S);w.draw(t.context,s,i,t.stencilModeForClipping(y),a,Et.disabled,c,r.id,b.layoutVertexBuffer,u,f,r.paint,t.transform.zoom,_)}}}}function nn(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,c=r.paint.get(\"fill-extrusion-pattern\"),u=c.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var g=d[p],m=e.getTile(g),v=m.getBucket(r);if(v){var y=v.programConfigurations.get(r.id),x=t.useProgram(u?\"fillExtrusionPattern\":\"fillExtrusion\",y);u&&(t.context.activeTexture.set(l.TEXTURE0),m.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),y.updatePaintBuffers(f));var b=c.constantOr(null);if(b&&m.imageAtlas){var _=m.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&y.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(g.posMatrix,m,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),M=r.paint.get(\"fill-extrusion-vertical-gradient\"),A=u?Tr(k,t,M,h,g,f,m):wr(k,t,M,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Et.backCCW,A,r.id,v.layoutVertexBuffer,v.indexBuffer,v.segments,r.paint,t.transform.zoom,y)}}}function an(e,r,n,i,a,o){var s=e.context,l=s.gl,c=r.fbo;if(c){var u=e.useProgram(\"hillshade\");s.activeTexture.set(l.TEXTURE0),l.bindTexture(l.TEXTURE_2D,c.colorAttachment.get());var f=function(e,r,n){var i=n.paint.get(\"hillshade-shadow-color\"),a=n.paint.get(\"hillshade-highlight-color\"),o=n.paint.get(\"hillshade-accent-color\"),s=n.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===n.paint.get(\"hillshade-illumination-anchor\")&&(s-=e.transform.angle);var l,c,u,f=!e.options.moving;return{u_matrix:e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),f),u_image:0,u_latrange:(l=r.tileID,c=Math.pow(2,l.canonical.z),u=l.canonical.y,[new t.MercatorCoordinate(0,u/c).toLngLat().lat,new t.MercatorCoordinate(0,(u+1)/c).toLngLat().lat]),u_light:[n.paint.get(\"hillshade-exaggeration\"),s],u_shadow:i,u_highlight:a,u_accent:o}}(e,r,n);u.draw(s,l.TRIANGLES,i,a,o,Et.disabled,f,n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments)}}function on(e,r,n,i,a,o,s){var l=e.context,c=l.gl,u=r.dem;if(u&&u.data){var f=u.dim,h=u.stride,p=u.getPixels();if(l.activeTexture.set(c.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(h),r.demTexture){var d=r.demTexture;d.update(p,{premultiply:!1}),d.bind(c.NEAREST,c.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,p,c.RGBA,{premultiply:!1}),r.demTexture.bind(c.NEAREST,c.CLAMP_TO_EDGE);l.activeTexture.set(c.TEXTURE0);var g=r.fbo;if(!g){var m=new t.Texture(l,{width:f,height:f,data:null},c.RGBA);m.bind(c.LINEAR,c.CLAMP_TO_EDGE),(g=r.fbo=l.createFramebuffer(f,f,!0)).colorAttachment.set(m.texture)}l.bindFramebuffer.set(g.framebuffer),l.viewport.set([0,0,f,f]),e.useProgram(\"hillshadePrepare\").draw(l,c.TRIANGLES,a,o,s,Et.disabled,function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}}(r.tileID,u,i),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function sn(e,r,n,i,a){var o=i.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,c=r?(s-r.timeAdded)/o:-1,u=n.getSource(),f=a.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-c,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var ln=new t.Color(1,0,0,1),cn=new t.Color(0,1,0,1),un=new t.Color(0,0,1,1),fn=new t.Color(1,0,1,1),hn=new t.Color(0,1,1,1);function pn(t,e,r,n){gn(t,0,e+r/2,t.transform.width,r,n)}function dn(t,e,r,n){gn(t,e-r/2,0,r,t.transform.height,n)}function gn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function mn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=Mt.disabled,c=At.disabled,u=e.colorModeForRenderPass();i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,c,u,Et.disabled,Ir(o,t.Color.red),\"$debug\",e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var f=r.getTileByID(n.key).latestRawTileData,h=Math.floor((f&&f.byteLength||0)/1024),p=r.getTile(n).tileSize,d=512/Math.min(p,512)*(n.overscaledZ/e.transform.zoom)*.5,g=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(g+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,g+\" \"+h+\"kb\"),s.draw(i,a.TRIANGLES,l,c,St.alphaBlended,Et.disabled,Ir(o,t.Color.transparent,d),\"$debug\",e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var vn={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=At.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,c=\"map\"===a,u=\"map\"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),g=d.getBucket(n);if(g&&g.text&&g.text.segments.get().length){var m=t.evaluateSizeForZoom(g.textSizeData,l.zoom),v=he(d,1,r.transform.zoom),y=Kt(p.posMatrix,u,c,r.transform,v),x=\"none\"!==n.layout.get(\"icon-text-fit\")&&g.hasIconData();if(m){var b=Math.pow(2,l.zoom-d.tileID.overscaledZ);Qr(g,c,u,s,t.symbolSize,l,y,p.posMatrix,b,m,x)}}}}(i,e,n,r,n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),a),0!==n.paint.get(\"icon-opacity\").constantOr(1)&&tn(e,r,n,i,!1,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),n.layout.get(\"icon-rotation-alignment\"),n.layout.get(\"icon-pitch-alignment\"),n.layout.get(\"icon-keep-upright\"),o,s),0!==n.paint.get(\"text-opacity\").constantOr(1)&&tn(e,r,n,i,!0,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),n.layout.get(\"text-keep-upright\"),o,s),r.map.showCollisionBoxes&&(Zr(e,r,n,i,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),!0),Zr(e,r,n,i,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),!1))}},circle:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var c=e.context,u=c.gl,f=e.depthModeForSublayer(0,Mt.ReadOnly),h=At.disabled,p=e.colorModeForRenderPass(),d=[],g=0;g<i.length;g++){var m=i[g],v=r.getTile(m),y=v.getBucket(n);if(y){var x=y.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:y.layoutVertexBuffer,indexBuffer:y.indexBuffer,uniformValues:Er(e,m,v,n)};if(l)for(var _=0,w=y.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:y.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,M=d;k<M.length;k+=1){var A=M[k],S=A.state;S.program.draw(c,u.TRIANGLES,f,h,p,Et.disabled,S.uniformValues,n.id,S.layoutVertexBuffer,S.indexBuffer,A.segments,n.paint,e.transform.zoom,S.programConfiguration)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var a=e.context,o=a.gl,s=At.disabled,l=new St([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);!function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE,null),n.colorAttachment.set(r)}(t,e,a,i)}}(a,e,n),a.clear({color:t.Color.transparent});for(var c=0;c<i.length;c++){var u=i[c];if(!r.hasRenderableParent(u)){var f=r.getTile(u),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id);e.useProgram(\"heatmap\",p).draw(a,o.TRIANGLES,Mt.disabled,s,l,Et.disabled,zr(u.posMatrix,f,e.transform.zoom,n.paint.get(\"heatmap-intensity\")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(a){n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA)),o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,i.TRIANGLES,Mt.disabled,At.disabled,e.colorModeForRenderPass(),Et.disabled,function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:0,u_color_ramp:1,u_opacity:r.paint.get(\"heatmap-opacity\")}}(e,r),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}}(e,n))},line:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==a.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,Mt.ReadOnly),l=e.colorModeForRenderPass(),c=n.paint.get(\"line-dasharray\"),u=n.paint.get(\"line-pattern\"),f=u.constantOr(1),h=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=f?\"linePattern\":c?\"lineSDF\":h?\"lineGradient\":\"line\",g=e.context,m=g.gl,v=!0;if(h){g.activeTexture.set(m.TEXTURE0);var y=n.gradientTexture;if(!n.gradient)return;y||(y=n.gradientTexture=new t.Texture(g,n.gradient,m.RGBA)),y.bind(m.LINEAR,m.CLAMP_TO_EDGE)}for(var x=0,b=i;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!f||w.patternsLoaded()){var T=w.getBucket(n);if(T){var k=T.programConfigurations.get(n.id),M=e.context.program.get(),A=e.useProgram(d,k),S=v||A.program!==M,E=u.constantOr(null);if(E&&w.imageAtlas){var C=w.imageAtlas,L=C.patternPositions[E.to.toString()],I=C.patternPositions[E.from.toString()];L&&I&&k.setConstantPatternPositions(L,I)}var P=f?Rr(e,w,n,p):c?Fr(e,w,n,c,p):h?Dr(e,w,n):Or(e,w,n);f?(g.activeTexture.set(m.TEXTURE0),w.imageAtlasTexture.bind(m.LINEAR,m.CLAMP_TO_EDGE),k.updatePaintBuffers(p)):c&&(S||e.lineAtlas.dirty)&&(g.activeTexture.set(m.TEXTURE0),e.lineAtlas.bind(g)),A.draw(g,m.TRIANGLES,s,e.stencilModeForClipping(_),l,Et.disabled,P,n.id,T.layoutVertexBuffer,T.indexBuffer,T.segments,n.paint,e.transform.zoom,k),v=!1}}}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),c=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===c){var u=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?Mt.ReadWrite:Mt.ReadOnly);rn(e,r,n,i,u,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var f=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,Mt.ReadOnly);rn(e,r,n,i,f,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var i=r.paint.get(\"fill-extrusion-opacity\");if(0!==i&&\"translucent\"===t.renderPass){var a=new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))nn(t,e,r,n,a,At.disabled,St.disabled),nn(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();nn(t,e,r,n,a,At.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var i=t.context,a=e.getSource().maxzoom,o=t.depthModeForSublayer(0,Mt.ReadOnly),s=t.colorModeForRenderPass(),l=\"translucent\"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],c=l[0],u=0,f=l[1];u<f.length;u+=1){var h=f[u],p=e.getTile(h);p.needsHillshadePrepare&&\"offscreen\"===t.renderPass?on(t,p,r,a,o,At.disabled,s):\"translucent\"===t.renderPass&&an(t,p,r,o,c[h.overscaledZ],s)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=t.colorModeForRenderPass(),c=o instanceof P?[{},n]:t.stencilConfigForOverlap(n),u=c[0],f=c[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,g=f;d<g.length;d+=1){var m=g[d],v=t.depthModeForSublayer(m.overscaledZ-h,1===r.paint.get(\"raster-opacity\")?Mt.ReadWrite:Mt.ReadOnly,a.LESS),y=e.getTile(m),x=t.transform.calculatePosMatrix(m.toUnwrapped(),p);y.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var b=e.findLoadedParent(m,0),_=sn(y,b,e,r,t.transform),w=void 0,T=void 0,k=\"nearest\"===r.paint.get(\"raster-resampling\")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-y.tileID.overscaledZ),T=[y.tileID.canonical.x*w%1,y.tileID.canonical.y*w%1]):y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var M=jr(x,T||[0,0],w||1,_,r);o instanceof P?s.draw(i,a.TRIANGLES,v,At.disabled,l,Et.disabled,M,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,v,u[m.overscaledZ],l,Et.disabled,M,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,c=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(c)){var u=!c&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===u){var f=At.disabled,h=t.depthModeForSublayer(0,\"opaque\"===u?Mt.ReadWrite:Mt.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(c?\"backgroundPattern\":\"background\"),g=s.coveringTiles({tileSize:l});c&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var m=r.getCrossfadeParameters(),v=0,y=g;v<y.length;v+=1){var x=y[v],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=c?Wr(b,i,t,c,{tileID:x,tileSize:l},m):Yr(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Et.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)mn(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if(\"offscreen\"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(At.disabled);var o=\"3d\"===i.renderingMode?new Mt(t.context.gl.LEQUAL,Mt.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,Mt.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},yn=function(t,e){this.context=new Ct(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Lt.maxUnderzooming+Lt.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Be,this.gpuTimers={}};yn.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1)this.style._layers[i[n]].resize()},yn.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,He.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,He.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,I.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,He.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new At({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},yn.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,Mt.disabled,this.stencilClearMode,St.disabled,Et.disabled,Pr(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},yn.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(St.disabled),r.setDepthMode(Mt.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,Mt.disabled,new At({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),St.disabled,Et.disabled,Pr(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},yn.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new At({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},yn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new At({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},yn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new At({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=At.disabled,e),n]},yn.prototype.colorModeForRenderPass=function(){var e=this.context.gl;return this._showOverdrawInspector?new St([e.CONSTANT_COLOR,e.ONE],new t.Color(1/8,1/8,1/8,0),[!0,!0,!0,!0]):\"opaque\"===this.renderPass?St.unblended:St.alphaBlended},yn.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return Mt.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new Mt(r||this.context.gl.LEQUAL,e,[n,n])},yn.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},yn.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,c,u={},f={},h={};for(var p in a){var d=a[p];u[p]=d.getVisibleCoordinates(),f[p]=u[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var g=0;g<i.length;g++)if(this.style._layers[i[g]].is3D()){this.opaquePassCutoff=g;break}this.renderPass=\"offscreen\";for(var m=0,v=i;m<v.length;m+=1){var y=this.style._layers[v[m]];if(y.hasOffscreenPass()&&!y.isHidden(this.transform.zoom)){var x=f[y.source];(\"custom\"===y.type||x.length)&&this.renderLayer(this,a[y.source],y,x)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var b=this.style._layers[i[this.currentLayer]],_=a[b.source],w=u[b.source];this._renderTileClippingMasks(b,w),this.renderLayer(this,_,b,w)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var T=this.style._layers[i[this.currentLayer]],k=a[T.source],M=(\"symbol\"===T.type?h:f)[T.source];this._renderTileClippingMasks(T,u[T.source]),this.renderLayer(this,k,T,M)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(c&&c.id)&&(c=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<c.getSource().maxzoom)&&(l=c))})),l&&vn.debug(this,l,l.getVisibleCoordinates())),this.options.showPadding&&function(t){var e=t.transform.padding;pn(t,t.transform.height-(e.top||0),3,ln),pn(t,e.bottom||0,3,cn),dn(t,e.left||0,3,un),dn(t,t.transform.width-(e.right||0),3,fn);var r=t.transform.centerPoint;!function(t,e,r,n){gn(t,e-1,r-10,2,20,n),gn(t,e-10,r-1,20,2,n)}(t,r.x,t.transform.height-r.y,hn)}(this),this.context.setDefault()},yn.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),vn[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},yn.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},yn.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},yn.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},yn.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},yn.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var c=[a?n[0]:he(r,n[0],this.transform.zoom),a?n[1]:he(r,n[1],this.transform.zoom),0],u=new Float32Array(16);return t.translate(u,e,c),u},yn.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},yn.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},yn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},yn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new br(this.context,yr[t],e,Xr[t],this._showOverdrawInspector)),this.cache[r]},yn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},yn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},yn.prototype.initDebugOverlayCanvas=function(){null==this.debugOverlayCanvas&&(this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512,this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,this.context.gl.RGBA))},yn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var xn=function(t,e){this.points=t,this.planes=e};xn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new xn(a,o)};var bn=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};bn.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new bn(n,i)},bn.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},bn.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},bn.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var c=Number.MAX_VALUE,u=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];c=Math.min(c,h),u=Math.max(u,h)}if(u<0||c>this.max[l]-this.min[l])return 0}return 1};var _n=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};_n.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},_n.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},_n.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},_n.prototype.clone=function(){return new _n(this.top,this.bottom,this.left,this.right)},_n.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var wn=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new _n,this._posMatrixCache={},this._alignedPosMatrixCache={}},Tn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};wn.prototype.clone=function(){var t=new wn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Tn.minZoom.get=function(){return this._minZoom},Tn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Tn.maxZoom.get=function(){return this._maxZoom},Tn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Tn.minPitch.get=function(){return this._minPitch},Tn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Tn.maxPitch.get=function(){return this._maxPitch},Tn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Tn.renderWorldCopies.get=function(){return this._renderWorldCopies},Tn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Tn.worldSize.get=function(){return this.tileSize*this.scale},Tn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Tn.size.get=function(){return new t.Point(this.width,this.height)},Tn.bearing.get=function(){return-this.angle/Math.PI*180},Tn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Tn.pitch.get=function(){return this._pitch/Math.PI*180},Tn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Tn.fov.get=function(){return this._fov/Math.PI*180},Tn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Tn.zoom.get=function(){return this._zoom},Tn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Tn.center.get=function(){return this._center},Tn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Tn.padding.get=function(){return this._edgeInsets.toJSON()},Tn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Tn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},wn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},wn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},wn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},wn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),c=s-1;c<=l+1;c++)0!==c&&r.push(new t.UnwrappedTileID(c,e));return r},wn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=xn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var c=function(t){return{aabb:new bn([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},u=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)u.push(c(-d)),u.push(c(d));for(u.push(c(0));u.length>0;){var g=u.pop(),m=g.x,v=g.y,y=g.fullyVisible;if(!y){var x=g.aabb.intersects(s);if(0===x)continue;y=2===x}var b=g.aabb.distanceX(o),_=g.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_));if(g.zoom===h||w>3+(1<<h-g.zoom)-2&&g.zoom>=l)f.push({tileID:new t.OverscaledTileID(g.zoom===h?p:g.zoom,g.wrap,g.zoom,m,v),distanceSq:t.sqrLen([o[0]-.5-m,o[1]-.5-v])});else for(var T=0;T<4;T++){var k=(m<<1)+T%2,M=(v<<1)+(T>>1);u.push({aabb:g.aabb.quadrant(T),zoom:g.zoom+1,x:k,y:M,wrap:g.wrap,fullyVisible:y})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},wn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Tn.unmodified.get=function(){return this._unmodified},wn.prototype.zoomScale=function(t){return Math.pow(2,t)},wn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},wn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},wn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Tn.point.get=function(){return this.project(this.center)},wn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},wn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},wn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},wn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},wn.prototype.coordinateLocation=function(t){return t.toLngLat()},wn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[1]/i,s=n[1]/a,l=r[2]/i,c=n[2]/a,u=l===c?0:(0-l)/(c-l);return new t.MercatorCoordinate(t.number(r[0]/i,n[0]/a,u)/this.worldSize,t.number(o,s,u)/this.worldSize)},wn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},wn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},wn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},wn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},wn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},wn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},wn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<c.y?c.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<c.x?c.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=u,void(this._constraining=!1);if(this.latRange){var g=p.y,m=c.y/2;g-m<a&&(i=a+m),g+m>o&&(i=o-m)}if(this.lngRange){var v=p.x,y=c.x/2;v-y<s&&(n=s+y),v+y>l&&(n=l-y)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=u,this._constraining=!1}},wn.prototype._calcMatrices=function(){if(this.height){var e=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(this._fov/2)*this.height;var r=Math.PI/2+this._pitch,n=this._fov*(.5+e.y/this.height),i=Math.sin(n)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-r-n,.01,Math.PI-.01)),a=this.point,o=a.x,s=a.y,l=1.01*(Math.cos(Math.PI/2-this._pitch)*i+this.cameraToCenterDistance),c=this.height/50,u=new Float64Array(16);t.perspective(u,this._fov,this.width/this.height,c,l),u[8]=2*-e.x/this.width,u[9]=2*e.y/this.height,t.scale(u,u,[1,-1,1]),t.translate(u,u,[0,0,-this.cameraToCenterDistance]),t.rotateX(u,u,this._pitch),t.rotateZ(u,u,this.angle),t.translate(u,u,[-o,-s,0]),this.mercatorMatrix=t.scale([],u,[this.worldSize,this.worldSize,this.worldSize]),t.scale(u,u,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=u,this.invProjMatrix=t.invert([],this.projMatrix);var f=this.width%2/2,h=this.height%2/2,p=Math.cos(this.angle),d=Math.sin(this.angle),g=o-Math.round(o)+p*f+d*h,m=s-Math.round(s)+p*h+d*f,v=new Float64Array(u);if(t.translate(v,v,[g>.5?g-1:g,m>.5?m-1:m,0]),this.alignedProjMatrix=v,u=t.create(),t.scale(u,u,[this.width/2,-this.height/2,1]),t.translate(u,u,[1,-1,0]),this.labelPlaneMatrix=u,u=t.create(),t.scale(u,u,[1,-1,1]),t.translate(u,u,[-1,-1,0]),t.scale(u,u,[2/this.width,2/this.height,1]),this.glCoordMatrix=u,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(u=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=u,this._posMatrixCache={},this._alignedPosMatrixCache={}}},wn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},wn.prototype.getCameraPoint=function(){var e=Math.tan(this._pitch)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,e))},wn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var c=l[s];n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(wn.prototype,Tn);var kn=function(e){var r,n,i,a;this._hashName=e&&encodeURIComponent(e),t.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=!1,i=null,a=function(){i=null,n&&(r(),i=setTimeout(a,300),n=!1)},function(){return n=!0,i||a(),i})};kn.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},kn.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},kn.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),c=this._map.getPitch(),u=\"\";if(u+=e?\"/\"+o+\"/\"+s+\"/\"+n:n+\"/\"+s+\"/\"+o,(l||c)&&(u+=\"/\"+Math.round(10*l)/10),c&&(u+=\"/\"+Math.round(c)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split(\"&\").map((function(t){var e=t.split(\"=\")[0];return e===f?(h=!0,e+\"=\"+u):t})).filter((function(t){return t}));return h||p.push(f+\"=\"+u),\"#\"+p.join(\"&\")}return\"#\"+u},kn.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace(\"#\",\"\");return this._hashName?(n.split(\"&\").map((function(t){return t.split(\"=\")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||\"\").split(\"/\")):n.split(\"/\")},kn.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},kn.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var Mn={linearity:.3,easing:t.bezier(0,0,.3,1)},An=t.extend({deceleration:2500,maxSpeed:1400},Mn),Sn=t.extend({deceleration:20,maxSpeed:1400},Mn),En=t.extend({deceleration:1e3,maxSpeed:360},Mn),Cn=t.extend({deceleration:1e3,maxSpeed:90},Mn),Ln=function(t){this._map=t,this.clear()};function In(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function Pn(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}Ln.prototype.clear=function(){this._inertiaBuffer=[]},Ln.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},Ln.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},Ln.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=Pn(r.pan.mag(),o,t.extend({},An,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,In(s,l)}if(r.zoom){var c=Pn(r.zoom,o,Sn);s.zoom=this._map.transform.zoom+c.amount,In(s,c)}if(r.bearing){var u=Pn(r.bearing,o,En);s.bearing=this._map.transform.bearing+t.clamp(u.amount,-179,179),In(s,u)}if(r.pitch){var f=Pn(r.pitch,o,Cn);s.pitch=this._map.transform.pitch+f.amount,In(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var zn=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),On=function(e){function n(n,i,a){var o=\"touchend\"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),c=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),u=i.unproject(c);e.call(this,n,{points:s,point:c,lngLats:l,lngLat:u,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Dn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),Rn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};Rn.prototype.reset=function(){delete this._mousedownPos},Rn.prototype.wheel=function(t){return this._firePreventable(new Dn(t.type,this._map,t))},Rn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new zn(t.type,this._map,t))},Rn.prototype.mouseup=function(t){this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.dblclick=function(t){return this._firePreventable(new zn(t.type,this._map,t))},Rn.prototype.mouseover=function(t){this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.mouseout=function(t){this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.touchstart=function(t){return this._firePreventable(new On(t.type,this._map,t))},Rn.prototype.touchmove=function(t){this._map.fire(new On(t.type,this._map,t))},Rn.prototype.touchend=function(t){this._map.fire(new On(t.type,this._map,t))},Rn.prototype.touchcancel=function(t){this._map.fire(new On(t.type,this._map,t))},Rn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Rn.prototype.isEnabled=function(){return!0},Rn.prototype.isActive=function(){return!1},Rn.prototype.enable=function(){},Rn.prototype.disable=function(){};var Fn=function(t){this._map=t};Fn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Fn.prototype.mousemove=function(t){this._map.fire(new zn(t.type,this._map,t))},Fn.prototype.mousedown=function(){this._delayContextMenu=!0},Fn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new zn(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Fn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new zn(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},Fn.prototype.isEnabled=function(){return!0},Fn.prototype.isActive=function(){return!1},Fn.prototype.enable=function(){},Fn.prototype.disable=function(){};var Bn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Nn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Bn.prototype.isEnabled=function(){return!!this._enabled},Bn.prototype.isActive=function(){return!!this._active},Bn.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Bn.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Bn.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Bn.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+s+\"px)\"),this._box.style.width=o-a+\"px\",this._box.style.height=l-s+\"px\"}}},Bn.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event(\"boxzoomend\",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent(\"boxzoomcancel\",e)}},Bn.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent(\"boxzoomcancel\",t))},Bn.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Bn.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var jn=function(t){this.reset(),this.numTouches=t.numTouches};jn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},jn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1)r._add(i[n]);return r.div(e.length)}(r),this.touches=Nn(n,r)))},jn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Nn(r,e);for(var i in this.touches){var a=n[i];(!a||a.dist(this.touches[i])>30)&&(this.aborted=!0)}}},jn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Un=function(t){this.singleTap=new jn(t),this.numTaps=t.numTaps,this.reset()};Un.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Un.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Un.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Un.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Vn=function(){this._zoomIn=new Un({numTouches:1,numTaps:2}),this._zoomOut=new Un({numTouches:2,numTaps:1}),this.reset()};Vn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Vn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Vn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Vn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Vn.prototype.touchcancel=function(){this.reset()},Vn.prototype.enable=function(){this._enabled=!0},Vn.prototype.disable=function(){this._enabled=!1,this.reset()},Vn.prototype.isEnabled=function(){return this._enabled},Vn.prototype.isActive=function(){return this._active};var qn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};qn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},qn.prototype._correctButton=function(t,e){return!1},qn.prototype._move=function(t,e){return{}},qn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},qn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)<this._clickTolerance)))return this._moved=!0,this._lastPoint=e,this._move(r,e)},qn.prototype.mouseupWindow=function(t){r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},qn.prototype.enable=function(){this._enabled=!0},qn.prototype.disable=function(){this._enabled=!1,this.reset()},qn.prototype.isEnabled=function(){return this._enabled},qn.prototype.isActive=function(){return this._active};var Hn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(qn),Gn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(qn),Yn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(qn),Wn=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};Wn.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},Wn.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},Wn.prototype.touchmove=function(t,e,r){if(this._active)return t.preventDefault(),this._calculateTransform(t,e,r)},Wn.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},Wn.prototype.touchcancel=function(){this.reset()},Wn.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Nn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var c=i[l],u=this._touches[l];u&&(a._add(c),o._add(c.sub(u)),s++,i[l]=c)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},Wn.prototype.enable=function(){this._enabled=!0},Wn.prototype.disable=function(){this._enabled=!1,this.reset()},Wn.prototype.isEnabled=function(){return this._enabled},Wn.prototype.isActive=function(){return this._active};var Xn=function(){this.reset()};function Zn(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}function Jn(t,e){return Math.log(t/e)/Math.LN2}Xn.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},Xn.prototype._start=function(t){},Xn.prototype._move=function(t,e,r){return{}},Xn.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},Xn.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[1],a=Zn(r,e,n[0]),o=Zn(r,e,i);if(a&&o){var s=this._aroundCenter?null:a.add(o).div(2);return this._move([a,o],s,t)}}},Xn.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[1],o=Zn(n,e,i[0]),s=Zn(n,e,a);o&&s||(this._active&&r.suppressClick(),this.reset())}},Xn.prototype.touchcancel=function(){this.reset()},Xn.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around},Xn.prototype.disable=function(){this._enabled=!1,this.reset()},Xn.prototype.isEnabled=function(){return this._enabled},Xn.prototype.isActive=function(){return this._active};var Kn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs(Jn(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:Jn(this._distance,r),pinchAround:e}},e}(Xn);function Qn(t,e){return 180*t.angleWith(e)/Math.PI}var $n=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:Qn(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=Qn(t,this._startVector);return Math.abs(r)<e},e}(Xn);function ti(t){return Math.abs(t.y)>Math.abs(t.x)}var ei=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ti(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return ti(t)&&ti(e)&&a}},e}(Xn),ri={panStep:100,bearingStep:15,pitchStep:10},ni=function(){var t=ri;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function ii(t){return t*(2-t)}ni.prototype.reset=function(){this._active=!1},ni.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:ii,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},ni.prototype.enable=function(){this._enabled=!0},ni.prototype.disable=function(){this._enabled=!1,this.reset()},ni.prototype.isEnabled=function(){return this._enabled},ni.prototype.isActive=function(){return this._active};var ai=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=1/450,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};ai.prototype.setZoomRate=function(t){this._defaultZoomRate=t},ai.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},ai.prototype.isEnabled=function(){return!!this._enabled},ai.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},ai.prototype.isZooming=function(){return!!this._zooming},ai.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},ai.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},ai.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%4.000244140625==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},ai.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},ai.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},ai.prototype.renderFrame=function(){return this._onScrollFrame()},ai.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>4.000244140625?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,c=this._easing,u=!1;if(\"wheel\"===this._type&&l&&c){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=c(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):u=!0}else o=s,u=!0;return this._active=!0,u&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!u,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},ai.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},ai.prototype.reset=function(){this._active=!1};var oi=function(t,e){this._clickZoom=t,this._tapZoom=e};oi.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},oi.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},oi.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},oi.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var si=function(){this.reset()};si.prototype.reset=function(){this._active=!1},si.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},si.prototype.enable=function(){this._enabled=!0},si.prototype.disable=function(){this._enabled=!1,this.reset()},si.prototype.isEnabled=function(){return this._enabled},si.prototype.isActive=function(){return this._active};var li=function(){this._tap=new Un({numTouches:1,numTaps:1}),this.reset()};li.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},li.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},li.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},li.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},li.prototype.touchcancel=function(){this.reset()},li.prototype.enable=function(){this._enabled=!0},li.prototype.disable=function(){this._enabled=!1,this.reset()},li.prototype.isEnabled=function(){return this._enabled},li.prototype.isActive=function(){return this._active};var ci=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};ci.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},ci.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},ci.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},ci.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var ui=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};ui.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},ui.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},ui.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},ui.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var fi=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};fi.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},fi.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},fi.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},fi.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},fi.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},fi.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var hi=function(t){return t.zoom||t.drag||t.pitch||t.rotate},pi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e}(t.Event);function di(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var gi=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Ln(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!1}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0];r.addEventListener(l,s[1],l===t.window.document?this.handleWindowEvent:this.handleEvent,s[2])}};gi.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0];r.removeEventListener(a,i[1],a===t.window.document?this.handleWindowEvent:this.handleEvent,i[2])}},gi.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add(\"mapEvent\",new Rn(e,t));var n=e.boxZoom=new Bn(e,t);this._add(\"boxZoom\",n);var i=new Vn,a=new si;e.doubleClickZoom=new oi(a,i),this._add(\"tapZoom\",i),this._add(\"clickZoom\",a);var o=new li;this._add(\"tapDragZoom\",o);var s=e.touchPitch=new ei;this._add(\"touchPitch\",s);var l=new Gn(t),c=new Yn(t);e.dragRotate=new ui(t,l,c),this._add(\"mouseRotate\",l,[\"mousePitch\"]),this._add(\"mousePitch\",c,[\"mouseRotate\"]);var u=new Hn(t),f=new Wn(t);e.dragPan=new ci(r,u,f),this._add(\"mousePan\",u),this._add(\"touchPan\",f,[\"touchZoom\",\"touchRotate\"]);var h=new $n,p=new Kn;e.touchZoomRotate=new fi(r,p,h,o),this._add(\"touchRotate\",h,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",p,[\"touchPan\",\"touchRotate\"]);var d=e.scrollZoom=new ai(e,this);this._add(\"scrollZoom\",d,[\"mousePan\"]);var g=e.keyboard=new ni;this._add(\"keyboard\",g),this._add(\"blockableMapEvent\",new Fn(e));for(var m=0,v=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];m<v.length;m+=1){var y=v[m];t.interactive&&t[y]&&e[y].enable(t[y])}},gi.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},gi.prototype.stop=function(){if(!this._updatingCamera){for(var t=0,e=this._handlers;t<e.length;t+=1)e[t].handler.reset();this._inertia.clear(),this._fireEvents({},{}),this._changes=[]}},gi.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1)if(e[t].handler.isActive())return!0;return!1},gi.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},gi.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},gi.prototype.isMoving=function(){return Boolean(hi(this._eventsInProgress))||this.isZooming()},gi.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},gi.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+\"Window\")},gi.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r];this._el.contains(i.target)&&e.push(i)}return e},gi.prototype.handleEvent=function(t,e){if(\"blur\"!==t.type){this._updatingCamera=!0;for(var n=\"renderFrame\"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),c=0,u=this._handlers;c<u.length;c+=1){var f=u[c],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var g=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(g=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,g,h,n),g&&g.needsRenderFrame&&this._triggerRenderFrame()),(g||p.isActive())&&(o[h]=p)}}var m={};for(var v in this._previousActiveHandlers)o[v]||(m[v]=n);this._previousActiveHandlers=o,(Object.keys(m).length||di(i))&&(this._changes.push([i,a,m]),this._triggerRenderFrame()),(Object.keys(o).length||di(i))&&this._map._stop(!0),this._updatingCamera=!1;var y=i.cameraAnimation;y&&(this._inertia.clear(),this._fireEvents({},{}),this._changes=[],y(this._map))}else this.stop()},gi.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},gi.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],c=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,c)}this._updateMapTransform(e,r,n),this._changes=[]},gi.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!di(t))return this._fireEvents(e,r);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,c=t.around,u=t.pinchAround;void 0!==u&&(c=u),n._stop(!0),c=c||n.transform.centerPoint;var f=i.pointLocation(a?c.sub(a):c);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,c),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r)},gi.prototype._fireEvents=function(e,r){var n=this,i=hi(this._eventsInProgress),a=hi(e),o={};for(var s in e)this._eventsInProgress[s]||(o[s+\"start\"]=e[s].originalEvent),this._eventsInProgress[s]=e[s];for(var l in!i&&a&&this._fireEvent(\"movestart\",a.originalEvent),o)this._fireEvent(l,o[l]);for(var c in e.rotate&&(this._bearingChanged=!0),a&&this._fireEvent(\"move\",a.originalEvent),e)this._fireEvent(c,e[c].originalEvent);var u,f={};for(var h in this._eventsInProgress){var p=this._eventsInProgress[h],d=p.handlerName,g=p.originalEvent;this._handlersById[d].isActive()||(delete this._eventsInProgress[h],f[h+\"end\"]=u=r[d]||g)}for(var m in f)this._fireEvent(m,f[m]);var v=hi(this._eventsInProgress);if((i||a)&&!v){this._updatingCamera=!0;var y=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),x=function(t){return 0!==t&&-n._bearingSnap<t&&t<n._bearingSnap};y?(x(y.bearing||this._map.getBearing())&&(y.bearing=0),this._map.easeTo(y,{originalEvent:u})):(this._map.fire(new t.Event(\"moveend\",{originalEvent:u})),x(this._map.getBearing())&&this._map.resetNorth()),this._bearingChanged=!1,this._updatingCamera=!1}},gi.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},gi.prototype._triggerRenderFrame=function(){var t=this;void 0===this._frameId&&(this._frameId=this._map._requestRenderFrame((function(e){delete t._frameId,t.handleEvent(new pi(\"renderFrame\",{timeStamp:e})),t._applyChanges()})))};var mi=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if(\"number\"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,c=s.project(t.LngLat.convert(e)),u=s.project(t.LngLat.convert(r)),f=c.rotate(-n*Math.PI/180),h=u.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),g=p.sub(d),m=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/g.x,v=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/g.y;if(!(v<0||m<0)){var y=Math.min(s.scaleZoom(s.scale*Math.min(m,v)),i.maxZoom),x=t.Point.convert(i.offset),b=new t.Point(x.x+(i.padding.left-i.padding.right)/2,x.y+(i.padding.top-i.padding.bottom)/2).mult(s.scale/s.zoomScale(y));return{center:s.unproject(c.add(u).div(2).sub(b)),zoom:y,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),c=\"zoom\"in e?+e.zoom:a,u=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,f=\"pitch\"in e?+e.pitch:s,h=\"padding\"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),g=i.pointLocation(d),m=t.LngLat.convert(e.center||g);this._normalizeCenter(m);var v,y,x=i.project(g),b=i.project(m).sub(x),_=i.zoomScale(c-a);e.around&&(v=t.LngLat.convert(e.around),y=i.locationPoint(v));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||c!==a,this._rotating=this._rotating||o!==u,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),clearTimeout(this._easeEndTimeoutID),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,c,e)),n._rotating&&(i.bearing=t.number(o,u,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),v)i.setLocationAtPoint(v,y);else{var g=i.zoomScale(i.zoom-a),m=c>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(m,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(g));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),c=this.getPadding(),u=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(u-o),g=t.Point.convert(e.offset),m=a.centerPoint.add(g),v=a.pointLocation(m),y=t.LngLat.convert(e.center||v);this._normalizeCenter(y);var x=a.project(v),b=a.project(y).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var M=t.clamp(Math.min(e.minZoom,o,u),a.minZoom,a.maxZoom),A=w/a.zoomScale(M-o);_=Math.sqrt(A/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function C(t){return(Math.exp(t)-Math.exp(-t))/2}function L(t){return(Math.exp(t)+Math.exp(-t))/2}var I=E(0),P=function(t){return L(I)/L(I+_*t)},z=function(t){return w*((L(I)*(C(e=I+_*t)/L(e))-C(I))/S)/k;var e},O=(E(1)-I)/_;if(Math.abs(k)<1e-6||!isFinite(O)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var D=T<w?-1:1;O=Math.abs(Math.log(T/w))/_,z=function(){return 0},P=function(t){return Math.exp(D*_*t)}}return e.duration=\"duration\"in e?+e.duration:1e3*O/(\"screenSpeed\"in e?+e.screenSpeed/_:+e.speed),e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*O,d=1/P(i);a.zoom=1===e?u:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(c,p,e),m=a.centerPoint.add(g));var v=1===e?y:a.unproject(x.add(b.mult(z(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?v.wrap():v,m),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),vi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};vi.prototype.getDefaultPosition=function(){return\"bottom-right\"},vi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},vi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},vi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t}),\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\"}},vi.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},vi.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return\"string\"!=typeof t?\"\":t}))):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},vi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var yi=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};yi.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},yi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},yi.prototype.getDefaultPosition=function(){return\"bottom-left\"},yi.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},yi.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},yi.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var xi=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};xi.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},xi.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},xi.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},xi.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var bi={\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},_i=t.window.HTMLImageElement,wi=t.window.HTMLElement,Ti=t.window.ImageBitmap,ki={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:60,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Mi=function(n){function i(e){var r=this;if(null!=(e=t.extend({},ki,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>60)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new wn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new xi,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},bi,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof wi))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),this.handlers=new gi(this,e),this._hash=e.hash&&new kn(\"string\"==typeof e.hash&&e.hash||void 0).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new vi({customAttribution:e.customAttribution})),this.addControl(new yi,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),(i.prototype=Object.create(n&&n.prototype)).constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?60:t)>60)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new zn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new zn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new zn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;return void 0===r?n.prototype.off.call(this,t,e):(this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this)},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error(\"Missing UI string '\"+t+\"'\");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new qe(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new qe(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else\"object\"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\".  Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;if(this._lazyInitEmptyStyle(),r instanceof _i||Ti&&r instanceof Ti){var c=t.browser.getImageData(r);this.style.addImage(e,{data:new t.RGBAImage({width:c.width,height:c.height},c.data),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var u=r;this.style.addImage(e,{data:new t.RGBAImage({width:r.width,height:r.height},new Uint8Array(r.data)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:u}),u.onAdd&&u.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var i=r instanceof _i||Ti&&r instanceof Ti?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;return void 0===a||void 0===o?this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\"))):a!==n.data.width||o!==n.data.height?this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\"))):(n.data.replace(s,!(r instanceof _i||Ti&&r instanceof Ti)),void this.style.updateImage(e,n))},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),a=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach((function(t){a[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,i)}))},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new yn(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var c=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),u=c.crossFadingFactor();1===u&&u===this._crossFadingFactor||(o=!0,this._crossFadingFactor=u),this.style.update(c)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event(\"gpu-timing-frame\",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens(\"gpu-timing-layer\")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event(\"gpu-timing-layer\",{layerTimes:e}))}),50)}return this._sourcesDirty||this._styleDirty||this._placementDirty||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&(this._fullyLoaded||(this._fullyLoaded=!0),this.fire(new t.Event(\"idle\"))),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1)r[e].onRemove(this);this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext(),Ai(this._canvasContainer),Ai(this._controlContainer),Ai(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new t.Event(\"remove\"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(mi);function Ai(t){t.parentNode&&t.parentNode.removeChild(t)}var Si={showCompass:!0,showZoom:!0,visualizePitch:!1},Ei=function(e){var n=this;this.options=t.extend({},Si,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};Ei.prototype._updateZoomButtons=function(){var t=this._map.getZoom();this._zoomInButton.disabled=t===this._map.getMaxZoom(),this._zoomOutButton.disabled=t===this._map.getMinZoom()},Ei.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=t},Ei.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ci(this._map,this._compass,this.options.visualizePitch)),this._container},Ei.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Ei.prototype._createButton=function(t,e){var n=r.create(\"button\",t,this._container);return n.type=\"button\",n.addEventListener(\"click\",e),n},Ei.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString(\"NavigationControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)};var Ci=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new Gn({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new Yn({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),r.addEventListener(n,\"mousedown\",this.mousedown),r.addEventListener(n,\"touchstart\",this.touchstart,{passive:!1}),r.addEventListener(n,\"touchmove\",this.touchmove),r.addEventListener(n,\"touchend\",this.touchend),r.addEventListener(n,\"touchcancel\",this.reset)};function Li(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ci.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ci.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ci.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ci.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ci.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ci.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ci.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ci.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ci.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ci.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ci.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var Ii={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Pi(t,e,r){var n=t.classList;for(var i in Ii)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var zi,Oi=function(e){function n(n,i){var a=this;if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._draggable=n&&n.draggable||!1,this._state=\"inactive\",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||\"auto\",this._pitchAlignment=n&&n.pitchAlignment&&\"auto\"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");o.setAttributeNS(null,\"display\",\"block\"),o.setAttributeNS(null,\"height\",\"41px\"),o.setAttributeNS(null,\"width\",\"27px\"),o.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"stroke\",\"none\"),s.setAttributeNS(null,\"stroke-width\",\"1\"),s.setAttributeNS(null,\"fill\",\"none\"),s.setAttributeNS(null,\"fill-rule\",\"evenodd\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"fill-rule\",\"nonzero\");var c=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");c.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),c.setAttributeNS(null,\"fill\",\"#000000\");for(var u=0,f=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];u<f.length;u+=1){var h=f[u],p=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");p.setAttributeNS(null,\"opacity\",\"0.04\"),p.setAttributeNS(null,\"cx\",\"10.5\"),p.setAttributeNS(null,\"cy\",\"5.80029008\"),p.setAttributeNS(null,\"rx\",h.rx),p.setAttributeNS(null,\"ry\",h.ry),c.appendChild(p)}var d=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");d.setAttributeNS(null,\"fill\",this._color);var g=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");g.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),d.appendChild(g);var m=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");m.setAttributeNS(null,\"opacity\",\"0.25\"),m.setAttributeNS(null,\"fill\",\"#000000\");var v=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");v.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),m.appendChild(v);var y=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");y.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),y.setAttributeNS(null,\"fill\",\"#FFFFFF\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");x.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#000000\"),b.setAttributeNS(null,\"opacity\",\"0.25\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\");var _=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");_.setAttributeNS(null,\"fill\",\"#FFFFFF\"),_.setAttributeNS(null,\"cx\",\"5.5\"),_.setAttributeNS(null,\"cy\",\"5.5\"),_.setAttributeNS(null,\"r\",\"5.4999962\"),x.appendChild(b),x.appendChild(_),l.appendChild(c),l.appendChild(d),l.appendChild(m),l.appendChild(y),l.appendChild(x),o.appendChild(l),this._element.appendChild(o),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",(function(t){t.preventDefault()})),this._element.addEventListener(\"mousedown\",(function(t){t.preventDefault()})),this._element.addEventListener(\"focus\",(function(){var t=a._map.getContainer();t.scrollTop=0,t.scrollLeft=0})),Pi(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),t){if(!(\"offset\"in t.options)){var e=Math.sqrt(Math.pow(13.5,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[e,-1*(24.6+e)],\"bottom-right\":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;\"Space\"!==e&&\"Enter\"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=Li(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e=\"\";\"viewport\"===this._rotationAlignment||\"auto\"===this._rotationAlignment?e=\"rotateZ(\"+this._rotation+\"deg)\":\"map\"===this._rotationAlignment&&(e=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var n=\"\";\"viewport\"===this._pitchAlignment||\"auto\"===this._pitchAlignment?n=\"rotateX(0deg)\":\"map\"===this._pitchAlignment&&(n=\"rotateX(\"+this._map.getPitch()+\"deg)\"),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,Ii[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+n+\" \"+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\"))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Di={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},Ri=0,Fi=!1,Bi=function(e){function n(r){e.call(this),this.options=t.extend({},Di,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n,n.prototype.onAdd=function(e){var n;return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==zi?n(zi):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){n(zi=\"denied\"!==t.state)})):n(zi=!!t.window.navigator.geolocation),this._container},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Ri=0,Fi=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Fi)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Oi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Oi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||e.originalEvent&&\"resize\"===e.originalEvent.type||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Ri--,Fi=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Ri>1?(e={maximumAge:6e5,timeout:0},Fi=!0):(e=this.options.positionOptions,Fi=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Ni={maxWidth:100,unit:\"metric\"},ji=function(e){this.options=t.extend({},Ni,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Ui(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;l>5280?Vi(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\")):Vi(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else r&&\"nautical\"===r.unit?Vi(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\")):s>=1e3?Vi(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):Vi(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function Vi(t,e,r,n){var i,a,o,s=(i=r,(a=Math.pow(10,(\"\"+Math.floor(i)).length-1))*(o=(o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o)));t.style.width=e*(s/r)+\"px\",t.innerHTML=s+\"&nbsp;\"+n}ji.prototype.getDefaultPosition=function(){return\"bottom-left\"},ji.prototype._onMove=function(){Ui(this._map,this._container,this.options)},ji.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},ji.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},ji.prototype.setUnit=function(t){this.options.unit=t,Ui(this._map,this._container,this.options)};var qi=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};qi.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},qi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},qi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},qi.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},qi.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},qi.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},qi.prototype._isFullscreen=function(){return this._fullscreen},qi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},qi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Hi={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},Gi=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(Hi),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(e){var n=this;if(this._map&&(this._lngLat||this._trackPointer)&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return n._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Li(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||e)){var i=this._pos=this._trackPointer&&e?e:this._map.project(this._lngLat),a=this.options.anchor,o=function e(r){if(r){if(\"number\"==typeof r){var n=Math.round(Math.sqrt(.5*Math.pow(r,2)));return{center:new t.Point(0,0),top:new t.Point(0,r),\"top-left\":new t.Point(n,n),\"top-right\":new t.Point(-n,n),bottom:new t.Point(0,-r),\"bottom-left\":new t.Point(n,-n),\"bottom-right\":new t.Point(-n,-n),left:new t.Point(r,0),right:new t.Point(-r,0)}}if(r instanceof t.Point||Array.isArray(r)){var i=t.Point.convert(r);return{center:i,top:i,\"top-left\":i,\"top-right\":i,bottom:i,\"bottom-left\":i,\"bottom-right\":i,left:i,right:i}}return{center:t.Point.convert(r.center||[0,0]),top:t.Point.convert(r.top||[0,0]),\"top-left\":t.Point.convert(r[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(r[\"top-right\"]||[0,0]),bottom:t.Point.convert(r.bottom||[0,0]),\"bottom-left\":t.Point.convert(r[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(r[\"bottom-right\"]||[0,0]),left:t.Point.convert(r.left||[0,0]),right:t.Point.convert(r.right||[0,0])}}return e(new t.Point(0,0))}(this.options.offset);if(!a){var s,l=this._container.offsetWidth,c=this._container.offsetHeight;s=i.y+o.bottom.y<c?[\"top\"]:i.y>this._map.transform.height-c?[\"bottom\"]:[],i.x<l/2?s.push(\"left\"):i.x>this._map.transform.width-l/2&&s.push(\"right\"),a=0===s.length?\"bottom\":s.join(\"-\")}var u=i.add(o[a]).round();r.setTransform(this._container,Ii[a]+\" translate(\"+u.x+\"px,\"+u.y+\"px)\"),Pi(this._container,a,\"popup\")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented),Yi={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Mi,NavigationControl:Ei,GeolocateControl:Bi,AttributionControl:vi,ScaleControl:ji,FullscreenControl:qi,Popup:Gi,Marker:Oi,Style:qe,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){Bt().acquire(Ot)},clearPrewarmedResources:function(){var t=Rt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(Ot),Rt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))},get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return Dt.workerCount},set workerCount(t){Dt.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:\"\"};return Yi})),r}))},{}],474:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=1<<t+1,r=new Array(e),n=0;n<e;++n)r[n]=a(t,n);return r};var n=t(\"convex-hull\");function i(t,e,r){for(var n=new Array(t),i=0;i<t;++i)n[i]=0,i===e&&(n[i]+=.5),i===r&&(n[i]+=.5);return n}function a(t,e){if(0===e||e===(1<<t+1)-1)return[];for(var r=[],a=[],o=0;o<=t;++o)if(e&1<<o){r.push(i(t,o-1,o-1)),a.push(null);for(var s=0;s<=t;++s)~e&1<<s&&(r.push(i(t,o-1,s-1)),a.push([o,s]))}var l=n(r),c=[];t:for(o=0;o<l.length;++o){var u=l[o],f=[];for(s=0;s<u.length;++s){if(!a[u[s]])continue t;f.push(a[u[s]].slice())}c.push(f)}return c}},{\"convex-hull\":135}],475:[function(t,e,r){var n=t(\"./normalize\"),i=t(\"gl-mat4/create\"),a=t(\"gl-mat4/clone\"),o=t(\"gl-mat4/determinant\"),s=t(\"gl-mat4/invert\"),l=t(\"gl-mat4/transpose\"),c={length:t(\"gl-vec3/length\"),normalize:t(\"gl-vec3/normalize\"),dot:t(\"gl-vec3/dot\"),cross:t(\"gl-vec3/cross\")},u=i(),f=i(),h=[0,0,0,0],p=[[0,0,0],[0,0,0],[0,0,0]],d=[0,0,0];function g(t,e,r,n,i){t[0]=e[0]*n+r[0]*i,t[1]=e[1]*n+r[1]*i,t[2]=e[2]*n+r[2]*i}e.exports=function(t,e,r,i,m,v){if(e||(e=[0,0,0]),r||(r=[0,0,0]),i||(i=[0,0,0]),m||(m=[0,0,0,1]),v||(v=[0,0,0,1]),!n(u,t))return!1;if(a(f,u),f[3]=0,f[7]=0,f[11]=0,f[15]=1,Math.abs(o(f)<1e-8))return!1;var y,x,b,_,w,T,k,M=u[3],A=u[7],S=u[11],E=u[12],C=u[13],L=u[14],I=u[15];if(0!==M||0!==A||0!==S){if(h[0]=M,h[1]=A,h[2]=S,h[3]=I,!s(f,f))return!1;l(f,f),y=m,b=f,_=(x=h)[0],w=x[1],T=x[2],k=x[3],y[0]=b[0]*_+b[4]*w+b[8]*T+b[12]*k,y[1]=b[1]*_+b[5]*w+b[9]*T+b[13]*k,y[2]=b[2]*_+b[6]*w+b[10]*T+b[14]*k,y[3]=b[3]*_+b[7]*w+b[11]*T+b[15]*k}else m[0]=m[1]=m[2]=0,m[3]=1;if(e[0]=E,e[1]=C,e[2]=L,function(t,e){t[0][0]=e[0],t[0][1]=e[1],t[0][2]=e[2],t[1][0]=e[4],t[1][1]=e[5],t[1][2]=e[6],t[2][0]=e[8],t[2][1]=e[9],t[2][2]=e[10]}(p,u),r[0]=c.length(p[0]),c.normalize(p[0],p[0]),i[0]=c.dot(p[0],p[1]),g(p[1],p[1],p[0],1,-i[0]),r[1]=c.length(p[1]),c.normalize(p[1],p[1]),i[0]/=r[1],i[1]=c.dot(p[0],p[2]),g(p[2],p[2],p[0],1,-i[1]),i[2]=c.dot(p[1],p[2]),g(p[2],p[2],p[1],1,-i[2]),r[2]=c.length(p[2]),c.normalize(p[2],p[2]),i[1]/=r[2],i[2]/=r[2],c.cross(d,p[1],p[2]),c.dot(p[0],d)<0)for(var P=0;P<3;P++)r[P]*=-1,p[P][0]*=-1,p[P][1]*=-1,p[P][2]*=-1;return v[0]=.5*Math.sqrt(Math.max(1+p[0][0]-p[1][1]-p[2][2],0)),v[1]=.5*Math.sqrt(Math.max(1-p[0][0]+p[1][1]-p[2][2],0)),v[2]=.5*Math.sqrt(Math.max(1-p[0][0]-p[1][1]+p[2][2],0)),v[3]=.5*Math.sqrt(Math.max(1+p[0][0]+p[1][1]+p[2][2],0)),p[2][1]>p[1][2]&&(v[0]=-v[0]),p[0][2]>p[2][0]&&(v[1]=-v[1]),p[1][0]>p[0][1]&&(v[2]=-v[2]),!0}},{\"./normalize\":476,\"gl-mat4/clone\":278,\"gl-mat4/create\":280,\"gl-mat4/determinant\":281,\"gl-mat4/invert\":293,\"gl-mat4/transpose\":306,\"gl-vec3/cross\":365,\"gl-vec3/dot\":370,\"gl-vec3/length\":380,\"gl-vec3/normalize\":387}],476:[function(t,e,r){e.exports=function(t,e){var r=e[15];if(0===r)return!1;for(var n=1/r,i=0;i<16;i++)t[i]=e[i]*n;return!0}},{}],477:[function(t,e,r){var n=t(\"gl-vec3/lerp\"),i=t(\"mat4-recompose\"),a=t(\"mat4-decompose\"),o=t(\"gl-mat4/determinant\"),s=t(\"quat-slerp\"),l=f(),c=f(),u=f();function f(){return{translate:h(),scale:h(1),skew:h(),perspective:[0,0,0,1],quaternion:[0,0,0,1]}}function h(t){return[t||0,t||0,t||0]}e.exports=function(t,e,r,f){if(0===o(e)||0===o(r))return!1;var h=a(e,l.translate,l.scale,l.skew,l.perspective,l.quaternion),p=a(r,c.translate,c.scale,c.skew,c.perspective,c.quaternion);return!(!h||!p)&&(n(u.translate,l.translate,c.translate,f),n(u.skew,l.skew,c.skew,f),n(u.scale,l.scale,c.scale,f),n(u.perspective,l.perspective,c.perspective,f),s(u.quaternion,l.quaternion,c.quaternion,f),i(t,u.translate,u.scale,u.skew,u.perspective,u.quaternion),!0)}},{\"gl-mat4/determinant\":281,\"gl-vec3/lerp\":381,\"mat4-decompose\":475,\"mat4-recompose\":478,\"quat-slerp\":527}],478:[function(t,e,r){var n={identity:t(\"gl-mat4/identity\"),translate:t(\"gl-mat4/translate\"),multiply:t(\"gl-mat4/multiply\"),create:t(\"gl-mat4/create\"),scale:t(\"gl-mat4/scale\"),fromRotationTranslation:t(\"gl-mat4/fromRotationTranslation\")},i=(n.create(),n.create());e.exports=function(t,e,r,a,o,s){return n.identity(t),n.fromRotationTranslation(t,s,e),t[3]=o[0],t[7]=o[1],t[11]=o[2],t[15]=o[3],n.identity(i),0!==a[2]&&(i[9]=a[2],n.multiply(t,t,i)),0!==a[1]&&(i[9]=0,i[8]=a[1],n.multiply(t,t,i)),0!==a[0]&&(i[8]=0,i[4]=a[0],n.multiply(t,t,i)),n.scale(t,t,r),t}},{\"gl-mat4/create\":280,\"gl-mat4/fromRotationTranslation\":284,\"gl-mat4/identity\":291,\"gl-mat4/multiply\":295,\"gl-mat4/scale\":303,\"gl-mat4/translate\":305}],479:[function(t,e,r){\"use strict\";e.exports=Math.log2||function(t){return Math.log(t)*Math.LOG2E}},{}],480:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\"),i=t(\"mat4-interpolate\"),a=t(\"gl-mat4/invert\"),o=t(\"gl-mat4/rotateX\"),s=t(\"gl-mat4/rotateY\"),l=t(\"gl-mat4/rotateZ\"),c=t(\"gl-mat4/lookAt\"),u=t(\"gl-mat4/translate\"),f=(t(\"gl-mat4/scale\"),t(\"gl-vec3/normalize\")),h=[0,0,0];function p(t){this._components=t.slice(),this._time=[0],this.prevMatrix=t.slice(),this.nextMatrix=t.slice(),this.computedMatrix=t.slice(),this.computedInverse=t.slice(),this.computedEye=[0,0,0],this.computedUp=[0,0,0],this.computedCenter=[0,0,0],this.computedRadius=[0],this._limits=[-1/0,1/0]}e.exports=function(t){return new p((t=t||{}).matrix||[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1])};var d=p.prototype;d.recalcMatrix=function(t){var e=this._time,r=n.le(e,t),o=this.computedMatrix;if(!(r<0)){var s=this._components;if(r===e.length-1)for(var l=16*r,c=0;c<16;++c)o[c]=s[l++];else{var u=e[r+1]-e[r],h=(l=16*r,this.prevMatrix),p=!0;for(c=0;c<16;++c)h[c]=s[l++];var d=this.nextMatrix;for(c=0;c<16;++c)d[c]=s[l++],p=p&&h[c]===d[c];if(u<1e-6||p)for(c=0;c<16;++c)o[c]=h[c];else i(o,h,d,(t-e[r])/u)}var g=this.computedUp;g[0]=o[1],g[1]=o[5],g[2]=o[9],f(g,g);var m=this.computedInverse;a(m,o);var v=this.computedEye,y=m[15];v[0]=m[12]/y,v[1]=m[13]/y,v[2]=m[14]/y;var 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\"+r+\"(data,\"+o.map((function(t){return\"shape[\"+t+\"]\"})).join(\",\")+\",\"+o.map((function(t){return\"stride[\"+t+\"]\"})).join(\",\")+\",offset)}\"),new Function(\"CTOR_LIST\",\"ORDER\",a.join(\"\\n\"))(c[t],s)}var c={float32:[],float64:[],int8:[],int16:[],int32:[],uint8:[],uint16:[],uint32:[],array:[],uint8_clamped:[],bigint64:[],biguint64:[],buffer:[],generic:[]};e.exports=function(t,e,r,n){if(void 0===t)return(0,c.array[0])([]);\"number\"==typeof t&&(t=[t]),void 0===e&&(e=[t.length]);var o=e.length;if(void 0===r){r=new Array(o);for(var s=o-1,u=1;s>=0;--s)r[s]=u,u*=e[s]}if(void 0===n){n=0;for(s=0;s<o;++s)r[s]<0&&(n-=(e[s]-1)*r[s])}for(var f=function(t){if(i(t))return\"buffer\";if(a)switch(Object.prototype.toString.call(t)){case\"[object Float64Array]\":return\"float64\";case\"[object Float32Array]\":return\"float32\";case\"[object Int8Array]\":return\"int8\";case\"[object Int16Array]\":return\"int16\";case\"[object Int32Array]\":return\"int32\";case\"[object Uint8Array]\":return\"uint8\";case\"[object Uint16Array]\":return\"uint16\";case\"[object Uint32Array]\":return\"uint32\";case\"[object Uint8ClampedArray]\":return\"uint8_clamped\";case\"[object BigInt64Array]\":return\"bigint64\";case\"[object BigUint64Array]\":return\"biguint64\"}return Array.isArray(t)?\"array\":\"generic\"}(t),h=c[f];h.length<=o+1;)h.push(l(f,h.length-1));return(0,h[o+1])(t,e,r,n)}},{\"iota-array\":463,\"is-buffer\":465}],496:[function(t,e,r){\"use strict\";var n=t(\"double-bits\"),i=Math.pow(2,-1074);e.exports=function(t,e){if(isNaN(t)||isNaN(e))return NaN;if(t===e)return t;if(0===t)return e<0?-i:i;var r=n.hi(t),a=n.lo(t);e>t==t>0?a===-1>>>0?(r+=1,a=0):a+=1:0===a?(a=-1>>>0,r-=1):a-=1;return n.pack(a,r)}},{\"double-bits\":173}],497:[function(t,e,r){var n=Math.PI,i=c(120);function a(t,e,r,n){return[\"C\",t,e,r,n,r,n]}function o(t,e,r,n,i,a){return[\"C\",t/3+2/3*r,e/3+2/3*n,i/3+2/3*r,a/3+2/3*n,i,a]}function 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h=e[l],p=e[c],d=e[u],g=new Array(3),m=0,v=new Array(3),y=0,x=0;x<3;++x)g[x]=h[x]-p[x],m+=g[x]*g[x],v[x]=d[x]-p[x],y+=v[x]*v[x];if(m*y>a){var b=i[c],_=1/Math.sqrt(m*y);for(x=0;x<3;++x){var w=(x+1)%3,T=(x+2)%3;b[x]+=_*(v[w]*g[T]-v[T]*g[w])}}}for(o=0;o<n;++o){b=i[o];var k=0;for(x=0;x<3;++x)k+=b[x]*b[x];if(k>a)for(_=1/Math.sqrt(k),x=0;x<3;++x)b[x]*=_;else for(x=0;x<3;++x)b[x]=0}return i},r.faceNormals=function(t,e,r){for(var n=t.length,i=new Array(n),a=void 0===r?1e-6:r,o=0;o<n;++o){for(var s=t[o],l=new Array(3),c=0;c<3;++c)l[c]=e[s[c]];var u=new Array(3),f=new Array(3);for(c=0;c<3;++c)u[c]=l[1][c]-l[0][c],f[c]=l[2][c]-l[0][c];var h=new Array(3),p=0;for(c=0;c<3;++c){var d=(c+1)%3,g=(c+2)%3;h[c]=u[d]*f[g]-u[g]*f[d],p+=h[c]*h[c]}p=p>a?1/Math.sqrt(p):0;for(c=0;c<3;++c)h[c]*=p;i[o]=h}return i}},{}],499:[function(t,e,r){\n",
       "/*\n",
       "object-assign\n",
       "(c) Sindre Sorhus\n",
       "@license MIT\n",
       "*/\n",
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       "/*\n",
       " * @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc\n",
       " * @license MIT\n",
       " * @preserve Project Home: https://github.com/voidqk/polybooljs\n",
       " */\n",
       "var n,i=t(\"./lib/build-log\"),a=t(\"./lib/epsilon\"),o=t(\"./lib/intersecter\"),s=t(\"./lib/segment-chainer\"),l=t(\"./lib/segment-selector\"),c=t(\"./lib/geojson\"),u=!1,f=a();function h(t,e,r){var i=n.segments(t),a=n.segments(e),o=r(n.combine(i,a));return n.polygon(o)}n={buildLog:function(t){return!0===t?u=i():!1===t&&(u=!1),!1!==u&&u.list},epsilon:function(t){return f.epsilon(t)},segments:function(t){var e=o(!0,f,u);return 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h=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]]},{\"array-bounds\":70,\"color-normalize\":125,\"flatten-vertex-data\":244,\"object-assign\":499,\"pick-by-alias\":511,\"to-float32\":577,\"update-diff\":599}],535:[function(t,e,r){\"use strict\";var n=t(\"color-normalize\"),i=t(\"array-bounds\"),a=t(\"object-assign\"),o=t(\"glslify\"),s=t(\"pick-by-alias\"),l=t(\"flatten-vertex-data\"),c=t(\"earcut\"),u=t(\"array-normalize\"),f=t(\"to-float32\"),h=f.float32,p=f.fract32,d=t(\"es6-weak-map\"),g=t(\"parse-rect\");function m(t,e){if(!(this instanceof m))return new m(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=m.shaders.has(t)?m.shaders.get(t):m.shaders.set(t,m.createShaders(t)).get(t),this.update(e)}e.exports=m,m.dashMult=2,m.maxPatternLength=256,m.precisionThreshold=3e6,m.maxPoints=1e4,m.maxLines=2048,m.shaders=new d,m.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashPattern:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashSize:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},i=t(a({vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\n\\nuniform float dashSize, pixelRatio, thickness, opacity, id;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:\"back\"},vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n  vec2 adjustedScale;\\n  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n  vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\nuniform float dashSize, pixelRatio, thickness, opacity, id, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=i}return{fill:t({primitive:\"triangle\",elements:function(t,e){return e.triangles},offset:0,vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position, positionFract;\\n\\nuniform vec4 color;\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio, id;\\nuniform vec4 viewport;\\nuniform float opacity;\\n\\nvarying vec4 fragColor;\\n\\nconst float MAX_LINES = 256.;\\n\\nvoid main() {\\n\\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\\n\\n\\tvec2 position = position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n\\tfragColor.a *= opacity;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n\\tgl_FragColor = fragColor;\\n}\\n\"]),uniforms:{scale:t.prop(\"scale\"),color:t.prop(\"fill\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]}},attributes:{position:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8},positionFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8}},blend:n.blend,depth:{enable:!1},scissor:n.scissor,stencil:n.stencil,viewport:n.viewport}),rect:i,miter:e}},m.defaults={dashes:null,join:\"miter\",miterLimit:1,thickness:10,cap:\"square\",color:\"black\",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null},m.prototype.render=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];e.length&&(t=this).update.apply(t,e),this.draw()},m.prototype.draw=function(){for(var t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach((function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);\"number\"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>m.precisionThreshold||e.scale[1]*e.viewport.height>m.precisionThreshold||\"rect\"===e.join||!e.join&&(e.thickness<=2||e.count>=m.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))})),this},m.prototype.update=function(t){var e=this;if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach((function(t,f){var d=e.passes[f];if(void 0!==t)if(null!==t){if(\"number\"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin 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Uint8Array})},t=a({},m.defaults,t)),null!=t.thickness&&(d.thickness=parseFloat(t.thickness)),null!=t.opacity&&(d.opacity=parseFloat(t.opacity)),null!=t.miterLimit&&(d.miterLimit=parseFloat(t.miterLimit)),null!=t.overlay&&(d.overlay=!!t.overlay,f<m.maxLines&&(d.depth=2*(m.maxLines-1-f%m.maxLines)/m.maxLines-1)),null!=t.join&&(d.join=t.join),null!=t.hole&&(d.hole=t.hole),null!=t.fill&&(d.fill=t.fill?n(t.fill,\"uint8\"):null),null!=t.viewport&&(d.viewport=g(t.viewport)),d.viewport||(d.viewport=g([o.drawingBufferWidth,o.drawingBufferHeight])),null!=t.close&&(d.close=t.close),null===t.positions&&(t.positions=[]),t.positions){var v,y;if(t.positions.x&&t.positions.y){var x=t.positions.x,b=t.positions.y;y=d.count=Math.max(x.length,b.length),v=new Float64Array(2*y);for(var _=0;_<y;_++)v[2*_]=x[_],v[2*_+1]=b[_]}else v=l(t.positions,\"float64\"),y=d.count=Math.floor(v.length/2);var w=d.bounds=i(v,2);if(d.fill){for(var T=[],k={},M=0,A=0,S=0,E=d.count;A<E;A++){var C=v[2*A],L=v[2*A+1];isNaN(C)||isNaN(L)||null==C||null==L?(C=v[2*M],L=v[2*M+1],k[A]=M):M=A,T[S++]=C,T[S++]=L}for(var I=c(T,d.hole||[]),P=0,z=I.length;P<z;P++)null!=k[I[P]]&&(I[P]=k[I[P]]);d.triangles=I}var O=new Float64Array(v);u(O,2,w);var D=new Float64Array(2*y+6);d.close?v[0]===v[2*y-2]&&v[1]===v[2*y-1]?(D[0]=O[2*y-4],D[1]=O[2*y-3]):(D[0]=O[2*y-2],D[1]=O[2*y-1]):(D[0]=O[0],D[1]=O[1]),D.set(O,2),d.close?v[0]===v[2*y-2]&&v[1]===v[2*y-1]?(D[2*y+2]=O[2],D[2*y+3]=O[3],d.count-=1):(D[2*y+2]=O[0],D[2*y+3]=O[1],D[2*y+4]=O[2],D[2*y+5]=O[3]):(D[2*y+2]=O[2*y-2],D[2*y+3]=O[2*y-1],D[2*y+4]=O[2*y-2],D[2*y+5]=O[2*y-1]),d.positionBuffer(h(D)),d.positionFractBuffer(p(D))}if(t.range?d.range=t.range:d.range||(d.range=d.bounds),(t.range||t.positions)&&d.count){var R=d.bounds,F=R[2]-R[0],B=R[3]-R[1],N=d.range[2]-d.range[0],j=d.range[3]-d.range[1];d.scale=[F/N,B/j],d.translate=[-d.range[0]/N+R[0]/N||0,-d.range[1]/j+R[1]/j||0],d.scaleFract=p(d.scale),d.translateFract=p(d.translate)}if(t.dashes){var U,V=0;if(!t.dashes||t.dashes.length<2)V=1,U=new Uint8Array([255,255,255,255,255,255,255,255]);else{V=0;for(var q=0;q<t.dashes.length;++q)V+=t.dashes[q];U=new Uint8Array(V*m.dashMult);for(var H=0,G=255,Y=0;Y<2;Y++)for(var W=0;W<t.dashes.length;++W){for(var X=0,Z=t.dashes[W]*m.dashMult*.5;X<Z;++X)U[H++]=G;G^=255}}d.dashLength=V,d.dashTexture({channels:1,data:U,width:U.length,height:1,mag:\"linear\",min:\"linear\"},0,0)}if(t.color){var J=d.count,K=t.color;K||(K=\"transparent\");var Q=new Uint8Array(4*J+4);if(Array.isArray(K)&&\"number\"!=typeof K[0]){for(var $=0;$<J;$++){var tt=n(K[$],\"uint8\");Q.set(tt,4*$)}Q.set(n(K[0],\"uint8\"),4*J)}else for(var et=n(K,\"uint8\"),rt=0;rt<J+1;rt++)Q.set(et,4*rt);d.colorBuffer({usage:\"dynamic\",type:\"uint8\",data:Q})}}else e.passes[f]=null})),t.length<this.passes.length){for(var f=t.length;f<this.passes.length;f++){var d=this.passes[f];d&&(d.colorBuffer.destroy(),d.positionBuffer.destroy(),d.dashTexture.destroy())}this.passes.length=t.length}for(var v=[],y=0;y<this.passes.length;y++)null!==this.passes[y]&&v.push(this.passes[y]);return this.passes=v,this}},m.prototype.destroy=function(){return this.passes.forEach((function(t){t.colorBuffer.destroy(),t.positionBuffer.destroy(),t.dashTexture.destroy()})),this.passes.length=0,this}},{\"array-bounds\":70,\"array-normalize\":71,\"color-normalize\":125,earcut:177,\"es6-weak-map\":233,\"flatten-vertex-data\":244,glslify:536,\"object-assign\":499,\"parse-rect\":504,\"pick-by-alias\":511,\"to-float32\":577}],536:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],537:[function(t,e,r){\"use strict\";function n(t,e){return function(t){if(Array.isArray(t))return t}(t)||function(t,e){if(\"undefined\"==typeof Symbol||!(Symbol.iterator in Object(t)))return;var r=[],n=!0,i=!1,a=void 0;try{for(var o,s=t[Symbol.iterator]();!(n=(o=s.next()).done)&&(r.push(o.value),!e||r.length!==e);n=!0);}catch(t){i=!0,a=t}finally{try{n||null==s.return||s.return()}finally{if(i)throw a}}return r}(t,e)||a(t,e)||function(){throw new TypeError(\"Invalid attempt to destructure non-iterable instance.\\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.\")}()}function i(t){return function(t){if(Array.isArray(t))return o(t)}(t)||function(t){if(\"undefined\"!=typeof Symbol&&Symbol.iterator in Object(t))return Array.from(t)}(t)||a(t)||function(){throw new TypeError(\"Invalid attempt to spread non-iterable instance.\\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.\")}()}function a(t,e){if(t){if(\"string\"==typeof t)return o(t,e);var r=Object.prototype.toString.call(t).slice(8,-1);return\"Object\"===r&&t.constructor&&(r=t.constructor.name),\"Map\"===r||\"Set\"===r?Array.from(t):\"Arguments\"===r||/^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(r)?o(t,e):void 0}}function o(t,e){(null==e||e>t.length)&&(e=t.length);for(var r=0,n=new Array(e);r<e;r++)n[r]=t[r];return n}var s=t(\"color-normalize\"),l=t(\"array-bounds\"),c=t(\"color-id\"),u=t(\"@plotly/point-cluster\"),f=t(\"object-assign\"),h=t(\"glslify\"),p=t(\"pick-by-alias\"),d=t(\"update-diff\"),g=t(\"flatten-vertex-data\"),m=t(\"is-iexplorer\"),v=t(\"to-float32\"),y=t(\"parse-rect\"),x=b;function b(t,e){var r=this;if(!(this instanceof b))return new b(t,e);\"function\"==typeof t?(e||(e={}),e.regl=t):(e=t,t=null),e&&e.length&&(e.positions=e);var n,i=(t=e.regl)._gl,a=[];this.tooManyColors=m,n=t.texture({data:new Uint8Array(1020),width:255,height:1,type:\"uint8\",format:\"rgba\",wrapS:\"clamp\",wrapT:\"clamp\",mag:\"nearest\",min:\"nearest\"}),f(this,{regl:t,gl:i,groups:[],markerCache:[null],markerTextures:[null],palette:a,paletteIds:{},paletteTexture:n,maxColors:255,maxSize:100,canvas:i.canvas}),this.update(e);var o={uniforms:{constPointSize:!!e.constPointSize,pixelRatio:t.context(\"pixelRatio\"),palette:n,paletteSize:function(t,e){return[r.tooManyColors?0:255,n.height]},scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translate:t.prop(\"translate\"),translateFract:t.prop(\"translateFract\"),opacity:t.prop(\"opacity\"),marker:t.prop(\"markerTexture\")},attributes:{x:function(t,e){return e.xAttr||{buffer:e.positionBuffer,stride:8,offset:0}},y:function(t,e){return e.yAttr||{buffer:e.positionBuffer,stride:8,offset:4}},xFract:function(t,e){return e.xAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:0}},yFract:function(t,e){return e.yAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:4}},size:function(t,e){return e.size.length?{buffer:e.sizeBuffer,stride:2,offset:0}:{constant:[Math.round(255*e.size/r.maxSize)]}},borderSize:function(t,e){return e.borderSize.length?{buffer:e.sizeBuffer,stride:2,offset:1}:{constant:[Math.round(255*e.borderSize/r.maxSize)]}},colorId:function(t,e){return e.color.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:0}:{constant:r.tooManyColors?a.slice(4*e.color,4*e.color+4):[e.color]}},borderColorId:function(t,e){return e.borderColor.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:r.tooManyColors?4:2}:{constant:r.tooManyColors?a.slice(4*e.borderColor,4*e.borderColor+4):[e.borderColor]}},isActive:function(t,e){return!0===e.activation?{constant:[1]}:e.activation?e.activation:{constant:[0]}}},blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\"),stencil:{enable:!1},depth:{enable:!1},elements:t.prop(\"elements\"),count:t.prop(\"count\"),offset:t.prop(\"offset\"),primitive:\"points\"},s=f({},o);s.frag=h([\"precision 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fragColor, colorAmt);\\n    color.a *= opacity;\\n\\n    gl_FragColor = color;\\n  }\\n\\n}\\n\"]),s.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\\nuniform float pixelRatio;\\nuniform bool constPointSize;\\nuniform sampler2D palette;\\n\\nconst float maxSize = 100.;\\nconst float borderLevel = .5;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(palette,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = 2. * size * pointSizeScale;\\n  fragPointSize = size * pixelRatio;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragColor = color;\\n  fragBorderColor = borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n\\n  fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\\n  fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\\n}\"]),this.drawMarker=t(s);var l=f({},o);l.frag=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\n\\nuniform float opacity;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio;\\nuniform bool constPointSize;\\nuniform sampler2D palette;\\nuniform vec2 paletteSize;\\n\\nconst float maxSize = 100.;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n  return isDirect ? id / 255. : texture2D(palette,\\n    vec2(\\n      (id.x + .5) / paletteSize.x,\\n      (id.y + .5) / paletteSize.y\\n    )\\n  );\\n}\\n\\nvoid main() {\\n  // ignore inactive points\\n  if (isActive == 0.) return;\\n\\n  vec2 position = vec2(x, y);\\n  vec2 positionFract = vec2(xFract, yFract);\\n\\n  vec4 color = getColor(colorId);\\n  vec4 borderColor = getColor(borderColorId);\\n\\n  float size = size * maxSize / 255.;\\n  float borderSize = borderSize * maxSize / 255.;\\n\\n  gl_PointSize = (size + borderSize) * pointSizeScale;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n  fragColor = color;\\n  fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n}\\n\"]),m&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}b.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},b.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},b.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var i=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach((function(e,r){t.drawItem(r)}));return this},b.prototype.drawItem=function(t,e){var r=this.groups,n=r[t];if(\"number\"==typeof e&&(t=e,n=r[e],e=null),n&&n.count&&n.opacity){n.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,n,e));for(var a=[],o=1;o<n.activation.length;o++)n.activation[o]&&(!0===n.activation[o]||n.activation[o].data.length)&&a.push.apply(a,i(this.getMarkerDrawOptions(o,n,e)));a.length&&this.drawMarker(a)}},b.prototype.getMarkerDrawOptions=function(t,e,r){var i=e.range,a=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,c=e.count;this.regl;if(!a)return r?[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var u=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(c),g=0;g<r.length;g++){var m=r[g];d[m]=p?p[m]:1}l.subdata(d)}for(var v=h.length;v--;){var y=n(h[v],2),x=y[0],b=y[1];u.push(f({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return u},b.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,s=this.maxSize,c=this.maxColors,h=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=p(e,{positions:\"positions data points\",snap:\"snap cluster lod tree\",size:\"sizes size radius\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",color:\"colors color fill fill-color fillColor\",borderColor:\"borderColors borderColor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range dataBox databox\",viewport:\"viewport viewPort viewBox viewbox\",opacity:\"opacity alpha transparency\",bounds:\"bound bounds boundaries limits\",tooManyColors:\"tooManyColors palette paletteMode optimizePalette enablePalette\"})).positions&&(e.positions=[]),null!=e.tooManyColors&&(t.tooManyColors=e.tooManyColors),n||(i[r]=n={id:r,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:o.buffer({data:new Uint8Array(0),usage:\"stream\",type:\"uint8\"}),sizeBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),colorBuffer:o.buffer({data:new 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t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=g(t,\"float64\");var c=e.count=Math.floor(t.length/2),f=e.bounds=c?l(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=o.elements(h)}return i({data:v.float(t),usage:\"dynamic\"}),a({data:v.fract(t),usage:\"dynamic\"}),s({data:new Uint8Array(c),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var i=r.activation;if(i.forEach((function(t){return t&&t.destroy&&t.destroy()})),i.length=0,e&&\"number\"!=typeof e[0]){for(var a=[],s=0,l=Math.min(e.length,r.count);s<l;s++){var c=t.addMarker(e[s]);a[c]||(a[c]=new Uint8Array(r.count)),a[c][s]=1}for(var u=0;u<a.length;u++)if(a[u]){var f={data:a[u],type:\"uint8\",usage:\"static\"};i[u]?i[u](f):i[u]=o.buffer(f),i[u].data=a[u]}}else{i[t.addMarker(e)]=!0}return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=v.fract(e.scale),e.translateFract=v.fract(e.translate),t},viewport:function(t){return y(t||[a.drawingBufferWidth,a.drawingBufferHeight])}}]),m){var _=n,w=_.count,T=_.size,k=_.borderSize,M=_.sizeBuffer,A=new Uint8Array(2*w);if(T.length||k.length)for(var S=0;S<w;S++)A[2*S]=Math.round(255*(null==T[S]?T:T[S])/s),A[2*S+1]=Math.round(255*(null==k[S]?k:k[S])/s);M({data:A,usage:\"dynamic\"})}if(x){var E,C=n,L=C.count,I=C.color,P=C.borderColor,z=C.colorBuffer;if(t.tooManyColors){if(I.length||P.length){E=new Uint8Array(8*L);for(var O=0;O<L;O++){var D=I[O];E[8*O]=h[4*D],E[8*O+1]=h[4*D+1],E[8*O+2]=h[4*D+2],E[8*O+3]=h[4*D+3];var R=P[O];E[8*O+4]=h[4*R],E[8*O+5]=h[4*R+1],E[8*O+6]=h[4*R+2],E[8*O+7]=h[4*R+3]}}}else if(I.length||P.length){E=new Uint8Array(4*L+2);for(var F=0;F<L;F++)null!=I[F]&&(E[4*F]=I[F]%c,E[4*F+1]=Math.floor(I[F]/c)),null!=P[F]&&(E[4*F+2]=P[F]%c,E[4*F+3]=Math.floor(P[F]/c))}z({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n}))}},b.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return a=r.length,i.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:\"linear\",min:\"linear\"})),a},b.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var i=[];if(\"number\"==typeof t[0]){var a=[];if(Array.isArray(t))for(var o=0;o<t.length;o+=4)a.push(t.slice(o,o+4));else for(var l=0;l<t.length;l+=4)a.push(t.subarray(l,l+4));t=a}for(var u=0;u<t.length;u++){var f=t[u];f=s(f,\"uint8\");var h=c(f,!1);if(null==e[h]){var p=r.length;e[h]=Math.floor(p/4),r[p]=f[0],r[p+1]=f[1],r[p+2]=f[2],r[p+3]=f[3]}i[u]=e[h]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===i.length?i[0]:i},b.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},b.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var _=t(\"object-assign\");e.exports=function(t,e){var r=new x(t,e),n=r.render.bind(r);return _(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},{\"@plotly/point-cluster\":57,\"array-bounds\":70,\"color-id\":123,\"color-normalize\":125,\"flatten-vertex-data\":244,glslify:538,\"is-iexplorer\":466,\"object-assign\":499,\"parse-rect\":504,\"pick-by-alias\":511,\"to-float32\":577,\"update-diff\":599}],538:[function(t,e,r){arguments[4][257][0].apply(r,arguments)},{dup:257}],539:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"pick-by-alias\"),a=t(\"array-bounds\"),o=t(\"raf\"),s=t(\"array-range\"),l=t(\"parse-rect\"),c=t(\"flatten-vertex-data\");function u(t,e){if(!(this instanceof u))return new u(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function f(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function h(t,e,r){var n,i,a,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x+s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y+l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}e.exports=u,u.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},u.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var 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u=0;u<s.columns;u++)s.bounds[u]=a(o.data[u],1)}o.range&&(s.range=o.range,n=s.range&&\"number\"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&\"number\"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var g=s.columns,m=s.count,v=s.viewport.width,y=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=v/g,w=y/g;s.passes=[];for(var T=0;T<g;T++)for(var k=0;k<g;k++)if((s.diagonal||k!==T)&&(s.upper||!(T>k))&&(s.lower||!(T<k))){var M=f(s.id,T,k),A=this.passes[M]||(this.passes[M]={});if(o.data&&(o.transpose?A.positions={x:{buffer:s.buffer,offset:k,count:m,stride:g},y:{buffer:s.buffer,offset:T,count:m,stride:g}}:A.positions={x:{buffer:s.buffer,offset:k*m,count:m},y:{buffer:s.buffer,offset:T*m,count:m}},A.bounds=h(s.bounds,T,k)),o.domain||o.viewport||o.data){var S=d?h(s.padding,T,k):s.padding;if(s.domain){var E=h(s.domain,T,k),C=E[0],L=E[1],I=E[2],P=E[3];A.viewport=[x+C*v+S[0],b+L*y+S[1],x+I*v-S[2],b+P*y-S[3]]}else A.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(A.color=s.color),o.size&&(A.size=s.size),o.marker&&(A.marker=s.marker),o.borderSize&&(A.borderSize=s.borderSize),o.borderColor&&(A.borderColor=s.borderColor),o.opacity&&(A.opacity=s.opacity),o.range&&(A.range=n?h(s.range,T,k):s.range||A.bounds),s.passes.push(M)}return this},u.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],i=0;i<e.length;i++)if(\"number\"==typeof e[i]){var a=this.traces[e[i]],o=a.passes,l=a.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[i].length){var c=e[i],u=this.traces[i],f=u.passes,h=u.passOffset;f=f.map((function(t,e){n[h+e]=c}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},u.prototype.destroy=function(){return this.traces.forEach((function(t){t.buffer&&t.buffer.destroy&&t.buffer.destroy()})),this.traces=null,this.passes=null,this.scatter.destroy(),this}},{\"array-bounds\":70,\"array-range\":72,\"flatten-vertex-data\":244,\"parse-rect\":504,\"pick-by-alias\":511,raf:528,\"regl-scatter2d\":537}],540:[function(t,e,r){!function(t,n){\"object\"==typeof r&&\"undefined\"!=typeof e?e.exports=n():t.createREGL=n()}(this,(function(){function t(t,e){this.id=V++,this.type=t,this.data=e}function e(t){return\"[\"+function t(e){if(0===e.length)return[];var r=e.charAt(0),n=e.charAt(e.length-1);if(1<e.length&&r===n&&('\"'===r||\"'\"===r))return['\"'+e.substr(1,e.length-2).replace(/\\\\/g,\"\\\\\\\\\").replace(/\"/g,'\\\\\"')+'\"'];if(r=/\\[(false|true|null|\\d+|'[^']*'|\"[^\"]*\")\\]/.exec(e))return 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r,n=parseInt(e);if(isNaN(n))\"\\u95f0\"===e[0]&&(r=!0,e=e.substring(1)),\"\\u6708\"===e[e.length-1]&&(e=e.substring(0,e.length-1)),n=1+[\"\\u4e00\",\"\\u4e8c\",\"\\u4e09\",\"\\u56db\",\"\\u4e94\",\"\\u516d\",\"\\u4e03\",\"\\u516b\",\"\\u4e5d\",\"\\u5341\",\"\\u5341\\u4e00\",\"\\u5341\\u4e8c\"].indexOf(e);else{var i=e[e.length-1];r=\"i\"===i||\"I\"===i}return this.toMonthIndex(t,n,r)},dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:1,isRTL:!1}},_validateYear:function(t,e){if(t.year&&(t=t.year()),\"number\"!=typeof t||t<1888||t>2111)throw e.replace(/\\{0\\}/,this.local.name);return t},toMonthIndex:function(t,e,r){var i=this.intercalaryMonth(t);if(r&&e!==i||e<1||e>12)throw n.local.invalidMonth.replace(/\\{0\\}/,this.local.name);return i?!r&&e<=i?e-1:e:e-1},toChineseMonth:function(t,e){t.year&&(e=(t=t.year()).month());var r=this.intercalaryMonth(t);if(e<0||e>(r?12:11))throw n.local.invalidMonth.replace(/\\{0\\}/,this.local.name);return r?e<r?e+1:e:e+1},intercalaryMonth:function(t){return t=this._validateYear(t),f[t-f[0]]>>13},isIntercalaryMonth:function(t,e){t.year&&(e=(t=t.year()).month());var r=this.intercalaryMonth(t);return!!r&&r===e},leapYear:function(t){return 0!==this.intercalaryMonth(t)},weekOfYear:function(t,e,r){var i,o=this._validateYear(t,n.local.invalidyear),s=h[o-h[0]],l=s>>9&4095,c=s>>5&15,u=31&s;(i=a.newDate(l,c,u)).add(4-(i.dayOfWeek()||7),\"d\");var f=this.toJD(t,e,r)-i.toJD();return 1+Math.floor(f/7)},monthsInYear:function(t){return this.leapYear(t)?13:12},daysInMonth:function(t,e){t.year&&(e=t.month(),t=t.year()),t=this._validateYear(t);var r=f[t-f[0]];if(e>(r>>13?12:11))throw n.local.invalidMonth.replace(/\\{0\\}/,this.local.name);return r&1<<12-e?30:29},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,s,r,n.local.invalidDate);t=this._validateYear(i.year()),e=i.month(),r=i.day();var o=this.isIntercalaryMonth(t,e),s=this.toChineseMonth(t,e),l=function(t,e,r,n,i){var a,o,s;if(\"object\"==typeof t)o=t,a=e||{};else{var l;if(!(\"number\"==typeof t&&t>=1888&&t<=2111))throw new Error(\"Lunar year outside range 1888-2111\");if(!(\"number\"==typeof e&&e>=1&&e<=12))throw new Error(\"Lunar month outside range 1 - 12\");if(!(\"number\"==typeof r&&r>=1&&r<=30))throw new Error(\"Lunar day outside range 1 - 30\");\"object\"==typeof n?(l=!1,a=n):(l=!!n,a=i||{}),o={year:t,month:e,day:r,isIntercalary:l}}s=o.day-1;var c,u=f[o.year-f[0]],p=u>>13;c=p&&(o.month>p||o.isIntercalary)?o.month:o.month-1;for(var d=0;d<c;d++){s+=u&1<<12-d?30:29}var g=h[o.year-h[0]],m=new Date(g>>9&4095,(g>>5&15)-1,(31&g)+s);return a.year=m.getFullYear(),a.month=1+m.getMonth(),a.day=m.getDate(),a}(t,s,r,o);return a.toJD(l.year,l.month,l.day)},fromJD:function(t){var e=a.fromJD(t),r=function(t,e,r,n){var i,a;if(\"object\"==typeof t)i=t,a=e||{};else{if(!(\"number\"==typeof t&&t>=1888&&t<=2111))throw new Error(\"Solar year outside range 1888-2111\");if(!(\"number\"==typeof e&&e>=1&&e<=12))throw new Error(\"Solar month outside range 1 - 12\");if(!(\"number\"==typeof r&&r>=1&&r<=31))throw new Error(\"Solar day outside range 1 - 31\");i={year:t,month:e,day:r},a=n||{}}var o=h[i.year-h[0]],s=i.year<<9|i.month<<5|i.day;a.year=s>=o?i.year:i.year-1,o=h[a.year-h[0]];var l,c=new Date(o>>9&4095,(o>>5&15)-1,31&o),u=new Date(i.year,i.month-1,i.day);l=Math.round((u-c)/864e5);var p,d=f[a.year-f[0]];for(p=0;p<13;p++){var g=d&1<<12-p?30:29;if(l<g)break;l-=g}var m=d>>13;!m||p<m?(a.isIntercalary=!1,a.month=1+p):p===m?(a.isIntercalary=!0,a.month=p):(a.isIntercalary=!1,a.month=p);return 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n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Coptic\",jdEpoch:1825029.5,daysPerMonth:[30,30,30,30,30,30,30,30,30,30,30,30,5],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Coptic\",epochs:[\"BAM\",\"AM\"],monthNames:[\"Thout\",\"Paopi\",\"Hathor\",\"Koiak\",\"Tobi\",\"Meshir\",\"Paremhat\",\"Paremoude\",\"Pashons\",\"Paoni\",\"Epip\",\"Mesori\",\"Pi Kogi Enavot\"],monthNamesShort:[\"Tho\",\"Pao\",\"Hath\",\"Koi\",\"Tob\",\"Mesh\",\"Pat\",\"Pad\",\"Pash\",\"Pao\",\"Epi\",\"Meso\",\"PiK\"],dayNames:[\"Tkyriaka\",\"Pesnau\",\"Pshoment\",\"Peftoou\",\"Ptiou\",\"Psoou\",\"Psabbaton\"],dayNamesShort:[\"Tky\",\"Pes\",\"Psh\",\"Pef\",\"Pti\",\"Pso\",\"Psa\"],dayNamesMin:[\"Tk\",\"Pes\",\"Psh\",\"Pef\",\"Pt\",\"Pso\",\"Psa\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return this.newDate(r,n,i)}}),n.calendars.coptic=a},{\"../main\":621,\"object-assign\":499}],609:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Discworld\",jdEpoch:1721425.5,daysPerMonth:[16,32,32,32,32,32,32,32,32,32,32,32,32],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Discworld\",epochs:[\"BUC\",\"UC\"],monthNames:[\"Ick\",\"Offle\",\"February\",\"March\",\"April\",\"May\",\"June\",\"Grune\",\"August\",\"Spune\",\"Sektober\",\"Ember\",\"December\"],monthNamesShort:[\"Ick\",\"Off\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Gru\",\"Aug\",\"Spu\",\"Sek\",\"Emb\",\"Dec\"],dayNames:[\"Sunday\",\"Octeday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Oct\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Oc\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:2,isRTL:!1}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),13},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),400},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/8)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]},daysInWeek:function(){return 8},dayOfWeek:function(t,e,r){return(this._validate(t,e,r,n.local.invalidDate).day()+1)%8},weekDay:function(t,e,r){var n=this.dayOfWeek(t,e,r);return n>=2&&n<=6},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{century:o[Math.floor((i.year()-1)/100)+1]||\"\"}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year()+(i.year()<0?1:0),e=i.month(),(r=i.day())+(e>1?16:0)+(e>2?32*(e-2):0)+400*(t-1)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t+.5)-Math.floor(this.jdEpoch)-1;var e=Math.floor(t/400)+1;t-=400*(e-1),t+=t>15?16:0;var r=Math.floor(t/32)+1,n=t-32*(r-1)+1;return this.newDate(e<=0?e-1:e,r,n)}});var o={20:\"Fruitbat\",21:\"Anchovy\"};n.calendars.discworld=a},{\"../main\":621,\"object-assign\":499}],610:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return this.newDate(r,n,i)}}),n.calendars.ethiopian=a},{\"../main\":621,\"object-assign\":499}],611:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Hebrew\",jdEpoch:347995.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29,29],hasYearZero:!1,minMonth:1,firstMonth:7,minDay:1,regionalOptions:{\"\":{name:\"Hebrew\",epochs:[\"BAM\",\"AM\"],monthNames:[\"Nisan\",\"Iyar\",\"Sivan\",\"Tammuz\",\"Av\",\"Elul\",\"Tishrei\",\"Cheshvan\",\"Kislev\",\"Tevet\",\"Shevat\",\"Adar\",\"Adar II\"],monthNamesShort:[\"Nis\",\"Iya\",\"Siv\",\"Tam\",\"Av\",\"Elu\",\"Tis\",\"Che\",\"Kis\",\"Tev\",\"She\",\"Ada\",\"Ad2\"],dayNames:[\"Yom Rishon\",\"Yom Sheni\",\"Yom Shlishi\",\"Yom Revi'i\",\"Yom Chamishi\",\"Yom Shishi\",\"Yom Shabbat\"],dayNamesShort:[\"Ris\",\"She\",\"Shl\",\"Rev\",\"Cha\",\"Shi\",\"Sha\"],dayNamesMin:[\"Ri\",\"She\",\"Shl\",\"Re\",\"Ch\",\"Shi\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return this._leapYear(e.year())},_leapYear:function(t){return o(7*(t=t<0?t+1:t)+1,19)<7},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),this._leapYear(t.year?t.year():t)?13:12},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),this.toJD(-1===t?1:t+1,7,1)-this.toJD(t,7,1)},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),12===e&&this.leapYear(t)||8===e&&5===o(this.daysInYear(t),10)?30:9===e&&3===o(this.daysInYear(t),10)?29:this.daysPerMonth[e-1]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(i)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(i)%10-3]}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t<=0?t+1:t,o=this.jdEpoch+this._delay1(a)+this._delay2(a)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.hebrew=a},{\"../main\":621,\"object-assign\":499}],612:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Islamic\",jdEpoch:1948439.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Islamic\",epochs:[\"BH\",\"AH\"],monthNames:[\"Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' al-thani\",\"Jumada al-awwal\",\"Jumada al-thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-ahad\",\"Yawm al-ithnayn\",\"Yawm ath-thulaathaa'\",\"Yawm al-arbi'aa'\",\"Yawm al-kham\\u012bs\",\"Yawm al-jum'a\",\"Yawm as-sabt\"],dayNamesShort:[\"Aha\",\"Ith\",\"Thu\",\"Arb\",\"Kha\",\"Jum\",\"Sab\"],dayNamesMin:[\"Ah\",\"It\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!1}},leapYear:function(t){return(11*this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year()+14)%30<11},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return this.leapYear(t)?355:354},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),t=t<=0?t+1:t,(r=i.day())+Math.ceil(29.5*(e-1))+354*(t-1)+Math.floor((3+11*t)/30)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t)+.5;var e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=a},{\"../main\":621,\"object-assign\":499}],613:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Julian\",jdEpoch:1721423.5,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Julian\",epochs:[\"BC\",\"AD\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"mm/dd/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()<0?e.year()+1:e.year())%4==0},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),r=i.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),i=Math.floor((e-n)/30.6001),a=i-Math.floor(i<14?1:13),o=r-Math.floor(a>2?4716:4715),s=e-n-Math.floor(30.6001*i);return o<=0&&o--,this.newDate(o,a,s)}}),n.calendars.julian=a},{\"../main\":621,\"object-assign\":499}],614:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Mayan\",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{\"\":{name:\"Mayan\",epochs:[\"\",\"\"],monthNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],monthNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],dayNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesMin:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],digits:null,dateFormat:\"YYYY.m.d\",firstDay:0,isRTL:!1,haabMonths:[\"Pop\",\"Uo\",\"Zip\",\"Zotz\",\"Tzec\",\"Xul\",\"Yaxkin\",\"Mol\",\"Chen\",\"Yax\",\"Zac\",\"Ceh\",\"Mac\",\"Kankin\",\"Muan\",\"Pax\",\"Kayab\",\"Cumku\",\"Uayeb\"],tzolkinMonths:[\"Imix\",\"Ik\",\"Akbal\",\"Kan\",\"Chicchan\",\"Cimi\",\"Manik\",\"Lamat\",\"Muluc\",\"Oc\",\"Chuen\",\"Eb\",\"Ben\",\"Ix\",\"Men\",\"Cib\",\"Caban\",\"Etznab\",\"Cauac\",\"Ahau\"]}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate).toJD(),a=this._toHaab(i),o=this._toTzolkin(i);return{haabMonthName:this.local.haabMonths[a[0]-1],haabMonth:a[0],haabDay:a[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(t){var e=o((t-=this.jdEpoch)+8+340,365);return[Math.floor(e/20)+1,o(e,20)]},_toTzolkin:function(t){return[s((t-=this.jdEpoch)+20,20),s(t+4,13)]},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return i.day()+20*i.month()+360*i.year()+this.jdEpoch},fromJD:function(t){t=Math.floor(t)+.5-this.jdEpoch;var e=Math.floor(t/360);t%=360,t+=t<0?360:0;var r=Math.floor(t/20),n=t%20;return this.newDate(e,r,n)}}),n.calendars.mayan=a},{\"../main\":621,\"object-assign\":499}],615:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar;var o=n.instance(\"gregorian\");i(a.prototype,{name:\"Nanakshahi\",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidMonth);(t=i.year())<0&&t++;for(var a=i.day(),s=1;s<i.month();s++)a+=this.daysPerMonth[s-1];return a+o.toJD(t+1468,3,13)},fromJD:function(t){t=Math.floor(t+.5);for(var e=Math.floor((t-(this.jdEpoch-1))/366);t>=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=a},{\"../main\":621,\"object-assign\":499}],616:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Nepali\",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(t){return 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c=t-(s>9||9===s&&r>=this.NEPALI_CALENDAR_DATA[l][0]?56:57);for(9!==e&&(o=r,s--);9!==s;)s<=0&&(s=12,l--),o+=this.NEPALI_CALENDAR_DATA[l][s],s--;return 9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=a.daysInYear(c)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],a.newDate(c,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),i=e.dayOfYear(),a=r+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)++o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var c=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,c)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)\"undefined\"==typeof 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},{\"../main\":621,\"object-assign\":499}],619:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\"),a=n.instance();function 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(e.year());return a.leapYear(t)},weekOfYear:function(t,e,r){var i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)},_g2tYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)}}),n.calendars.thai=o},{\"../main\":621,\"object-assign\":499}],620:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thal\\u0101th\\u0101\\u2019\",\"Yawm al-Arba\\u2018\\u0101\\u2019\",\"Yawm al-Kham\\u012bs\",\"Yawm al-Jum\\u2018a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;a<o.length;a++){if(o[a]>r)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;n<o.length&&!(o[n]>e);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,c=e-o[r-1]+1;return this.newDate(s,l,c)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=t(\"object-assign\");function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(c.local.differentCalendars||c.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day();\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(!function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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r,s,l=o(t,e),c=l.on,u=l.off.concat(l.explicitOff),f={},h=t._fullLayout.annotations;if(!c.length&&!u.length)return;for(r=0;r<c.length;r++)(s=a(t.layout,\"annotations\",h[c[r]])).modifyItem(\"visible\",!0),n.extendFlat(f,s.getUpdateObj());for(r=0;r<u.length;r++)(s=a(t.layout,\"annotations\",h[u[r]])).modifyItem(\"visible\",!1),n.extendFlat(f,s.getUpdateObj());return i.call(\"update\",t,{},f)}}},{\"../../lib\":778,\"../../plot_api/plot_template\":817,\"../../registry\":911}],629:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../color\");e.exports=function(t,e,r,a){a(\"opacity\");var o=a(\"bgcolor\"),s=a(\"bordercolor\"),l=i.opacity(s);a(\"borderpad\");var c=a(\"borderwidth\"),u=a(\"showarrow\");if(a(\"text\",u?\" \":r._dfltTitle.annotation),a(\"textangle\"),n.coerceFont(a,\"font\",r.font),a(\"width\"),a(\"align\"),a(\"height\")&&a(\"valign\"),u){var f,h,p=a(\"arrowside\");-1!==p.indexOf(\"end\")&&(f=a(\"arrowhead\"),h=a(\"arrowsize\")),-1!==p.indexOf(\"start\")&&(a(\"startarrowhead\",f),a(\"startarrowsize\",h)),a(\"arrowcolor\",l?e.bordercolor:i.defaultLine),a(\"arrowwidth\",2*(l&&c||1)),a(\"standoff\"),a(\"startstandoff\")}var d=a(\"hovertext\"),g=r.hoverlabel||{};if(d){var m=a(\"hoverlabel.bgcolor\",g.bgcolor||(i.opacity(o)?i.rgb(o):i.defaultLine)),v=a(\"hoverlabel.bordercolor\",g.bordercolor||i.contrast(m));n.coerceFont(a,\"hoverlabel.font\",{family:g.font.family,size:g.font.size,color:g.font.color||v})}a(\"captureevents\",!!d)}},{\"../../lib\":778,\"../color\":643}],630:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib/to_log_range\");e.exports=function(t,e,r,a){e=e||{};var o=\"log\"===r&&\"linear\"===e.type,s=\"linear\"===r&&\"log\"===e.type;if(o||s)for(var l,c,u=t._fullLayout.annotations,f=e._id.charAt(0),h=0;h<u.length;h++)l=u[h],c=\"annotations[\"+h+\"].\",l[f+\"ref\"]===e._id&&p(f),l[\"a\"+f+\"ref\"]===e._id&&p(\"a\"+f);function p(t){var r=l[t],s=null;s=o?i(r,e.range):Math.pow(10,r),n(s)||(s=null),a(c+t,s)}}},{\"../../lib/to_log_range\":805,\"fast-isnumeric\":241}],631:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../plots/array_container_defaults\"),o=t(\"./common_defaults\"),s=t(\"./attributes\");function l(t,e,r){function a(r,i){return n.coerce(t,e,s,r,i)}var l=a(\"visible\"),c=a(\"clicktoshow\");if(l||c){o(t,e,r,a);for(var u=e.showarrow,f=[\"x\",\"y\"],h=[-10,-30],p={_fullLayout:r},d=0;d<2;d++){var g=f[d],m=i.coerceRef(t,e,p,g,\"\",\"paper\");if(\"paper\"!==m)i.getFromId(p,m)._annIndices.push(e._index);if(i.coercePosition(e,p,a,m,g,.5),u){var v=\"a\"+g,y=i.coerceRef(t,e,p,v,\"pixel\",[\"pixel\",\"paper\"]);\"pixel\"!==y&&y!==m&&(y=e[v]=\"pixel\");var x=\"pixel\"===y?h[d]:.4;i.coercePosition(e,p,a,y,v,x)}a(g+\"anchor\"),a(g+\"shift\")}if(n.noneOrAll(t,e,[\"x\",\"y\"]),u&&n.noneOrAll(t,e,[\"ax\",\"ay\"]),c){var b=a(\"xclick\"),_=a(\"yclick\");e._xclick=void 0===b?e.x:i.cleanPosition(b,p,e.xref),e._yclick=void 0===_?e.y:i.cleanPosition(_,p,e.yref)}}}e.exports=function(t,e){a(t,e,{name:\"annotations\",handleItemDefaults:l})}},{\"../../lib\":778,\"../../plots/array_container_defaults\":823,\"../../plots/cartesian/axes\":828,\"./attributes\":626,\"./common_defaults\":629}],632:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../registry\"),a=t(\"../../plots/plots\"),o=t(\"../../lib\"),s=o.strTranslate,l=t(\"../../plots/cartesian/axes\"),c=t(\"../color\"),u=t(\"../drawing\"),f=t(\"../fx\"),h=t(\"../../lib/svg_text_utils\"),p=t(\"../../lib/setcursor\"),d=t(\"../dragelement\"),g=t(\"../../plot_api/plot_template\").arrayEditor,m=t(\"./draw_arrow_head\");function v(t,e){var r=t._fullLayout.annotations[e]||{},n=l.getFromId(t,r.xref),i=l.getFromId(t,r.yref);n&&n.setScale(),i&&i.setScale(),x(t,r,e,!1,n,i)}function y(t,e,r,n,i){var a=i[r],o=i[r+\"ref\"],s=-1!==r.indexOf(\"y\"),c=\"domain\"===l.getRefType(o),u=s?n.h:n.w;return t?c?a+(s?-e:e)/t._length:t.p2r(t.r2p(a)+e):a+(s?-e:e)/u}function x(t,e,r,a,v,x){var b,_,w=t._fullLayout,T=t._fullLayout._size,k=t._context.edits;a?(b=\"annotation-\"+a,_=a+\".annotations\"):(b=\"annotation\",_=\"annotations\");var M=g(t.layout,_,e),A=M.modifyBase,S=M.modifyItem,E=M.getUpdateObj;w._infolayer.selectAll(\".\"+b+'[data-index=\"'+r+'\"]').remove();var C=\"clip\"+w._uid+\"_ann\"+r;if(e._input&&!1!==e.visible){var L={x:{},y:{}},I=+e.textangle||0,P=w._infolayer.append(\"g\").classed(b,!0).attr(\"data-index\",String(r)).style(\"opacity\",e.opacity),z=P.append(\"g\").classed(\"annotation-text-g\",!0),O=k[e.showarrow?\"annotationTail\":\"annotationPosition\"],D=e.captureevents||k.annotationText||O,R=z.append(\"g\").style(\"pointer-events\",D?\"all\":null).call(p,\"pointer\").on(\"click\",(function(){t._dragging=!1,t.emit(\"plotly_clickannotation\",Y(n.event))}));e.hovertext&&R.on(\"mouseover\",(function(){var r=e.hoverlabel,n=r.font,i=this.getBoundingClientRect(),a=t.getBoundingClientRect();f.loneHover({x0:i.left-a.left,x1:i.right-a.left,y:(i.top+i.bottom)/2-a.top,text:e.hovertext,color:r.bgcolor,borderColor:r.bordercolor,fontFamily:n.family,fontSize:n.size,fontColor:n.color},{container:w._hoverlayer.node(),outerContainer:w._paper.node(),gd:t})})).on(\"mouseout\",(function(){f.loneUnhover(w._hoverlayer.node())}));var F=e.borderwidth,B=e.borderpad,N=F+B,j=R.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",F+\"px\").call(c.stroke,e.bordercolor).call(c.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll(\"#\"+C).data(U?[0]:[]);V.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",C).append(\"rect\"),V.exit().remove();var q=e.font,H=w._meta?o.templateString(e.text,w._meta):e.text,G=R.append(\"text\").classed(\"annotation-text\",!0).text(H);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(W).on(\"edit\",(function(r){e.text=r,this.call(W),S(\"text\",r),v&&v.autorange&&A(v._name+\".autorange\",!0),x&&x.autorange&&A(x._name+\".autorange\",!0),i.call(\"_guiRelayout\",t,E())})):G.call(W)}else n.selectAll(\"#\"+C).remove();function Y(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return a&&(n.subplotId=a),n}function W(r){return r.call(u.font,q).attr({\"text-anchor\":{left:\"start\",right:\"end\"}[e.align]||\"middle\"}),h.convertToTspans(r,t,X),r}function X(){var r=G.selectAll(\"a\");1===r.size()&&r.text()===G.text()&&R.insert(\"a\",\":first-child\").attr({\"xlink:xlink:href\":r.attr(\"xlink:href\"),\"xlink:xlink:show\":r.attr(\"xlink:show\")}).style({cursor:\"pointer\"}).node().appendChild(j.node());var n=R.select(\".annotation-text-math-group\"),f=!n.empty(),g=u.bBox((f?n:G).node()),b=g.width,_=g.height,M=e.width||b,D=e.height||_,B=Math.round(M+2*N),q=Math.round(D+2*N);function H(t,e){return\"auto\"===e&&(e=t<1/3?\"left\":t>2/3?\"right\":\"center\"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var W=!1,X=[\"x\",\"y\"],Z=0;Z<X.length;Z++){var J,K,Q,$,tt,et=X[Z],rt=e[et+\"ref\"]||et,nt=e[\"a\"+et+\"ref\"],it={x:v,y:x}[et],at=(I+(\"x\"===et?0:-90))*Math.PI/180,ot=B*Math.cos(at),st=q*Math.sin(at),lt=Math.abs(ot)+Math.abs(st),ct=e[et+\"anchor\"],ut=e[et+\"shift\"]*(\"x\"===et?1:-1),ft=L[et],ht=l.getRefType(rt);if(it&&\"domain\"!==ht){var pt=it.r2fraction(e[et]);(pt<0||pt>1)&&(nt===rt?((pt=it.r2fraction(e[\"a\"+et]))<0||pt>1)&&(W=!0):W=!0),J=it._offset+it.r2p(e[et]),$=.5}else{var dt=\"domain\"===ht;\"x\"===et?(Q=e[et],J=dt?it._offset+it._length*Q:J=T.l+T.w*Q):(Q=1-e[et],J=dt?it._offset+it._length*Q:J=T.t+T.h*Q),$=e.showarrow?.5:Q}if(e.showarrow){ft.head=J;var gt=e[\"a\"+et];if(tt=ot*H(.5,e.xanchor)-st*H(.5,e.yanchor),nt===rt){var mt=l.getRefType(nt);\"domain\"===mt?(\"y\"===et&&(gt=1-gt),ft.tail=it._offset+it._length*gt):\"paper\"===mt?\"y\"===et?(gt=1-gt,ft.tail=T.t+T.h*gt):ft.tail=T.l+T.w*gt:ft.tail=it._offset+it.r2p(gt),K=tt}else ft.tail=J+gt,K=tt+gt;ft.text=ft.tail+tt;var vt=w[\"x\"===et?\"width\":\"height\"];if(\"paper\"===rt&&(ft.head=o.constrain(ft.head,1,vt-1)),\"pixel\"===nt){var yt=-Math.max(ft.tail-3,ft.text),xt=Math.min(ft.tail+3,ft.text)-vt;yt>0?(ft.tail+=yt,ft.text+=yt):xt>0&&(ft.tail-=xt,ft.text-=xt)}ft.tail+=ut,ft.head+=ut}else K=tt=lt*H($,ct),ft.text=J+tt;ft.text+=ut,tt+=ut,K+=ut,e[\"_\"+et+\"padplus\"]=lt/2+K,e[\"_\"+et+\"padminus\"]=lt/2-K,e[\"_\"+et+\"size\"]=lt,e[\"_\"+et+\"shift\"]=tt}if(W)R.remove();else{var bt=0,_t=0;if(\"left\"!==e.align&&(bt=(M-b)*(\"center\"===e.align?.5:1)),\"top\"!==e.valign&&(_t=(D-_)*(\"middle\"===e.valign?.5:1)),f)n.select(\"svg\").attr({x:N+bt-1,y:N+_t}).call(u.setClipUrl,U?C:null,t);else{var wt=N+_t-g.top,Tt=N+bt-g.left;G.call(h.positionText,Tt,wt).call(u.setClipUrl,U?C:null,t)}V.select(\"rect\").call(u.setRect,N,N,M,D),j.call(u.setRect,F/2,F/2,B-F,q-F),R.call(u.setTranslate,Math.round(L.x.text-B/2),Math.round(L.y.text-q/2)),z.attr({transform:\"rotate(\"+I+\",\"+L.x.text+\",\"+L.y.text+\")\"});var kt,Mt=function(r,n){P.selectAll(\".annotation-arrow-g\").remove();var l=L.x.head,f=L.y.head,h=L.x.tail+r,p=L.y.tail+n,g=L.x.text+r,b=L.y.text+n,_=o.rotationXYMatrix(I,g,b),w=o.apply2DTransform(_),M=o.apply2DTransform2(_),C=+j.attr(\"width\"),O=+j.attr(\"height\"),D=g-.5*C,F=D+C,B=b-.5*O,N=B+O,U=[[D,B,D,N],[D,N,F,N],[F,N,F,B],[F,B,D,B]].map(M);if(!U.reduce((function(t,e){return t^!!o.segmentsIntersect(l,f,l+1e6,f+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=o.segmentsIntersect(h,p,l,f,t[0],t[1],t[2],t[3]);e&&(h=e.x,p=e.y)}));var V=e.arrowwidth,q=e.arrowcolor,H=e.arrowside,G=P.append(\"g\").style({opacity:c.opacity(q)}).classed(\"annotation-arrow-g\",!0),Y=G.append(\"path\").attr(\"d\",\"M\"+h+\",\"+p+\"L\"+l+\",\"+f).style(\"stroke-width\",V+\"px\").call(c.stroke,c.rgb(q));if(m(Y,H,e),k.annotationPosition&&Y.node().parentNode&&!a){var W=l,X=f;if(e.standoff){var Z=Math.sqrt(Math.pow(l-h,2)+Math.pow(f-p,2));W+=e.standoff*(h-l)/Z,X+=e.standoff*(p-f)/Z}var 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n=t(\"../annotations/attributes\"),i=t(\"../../plot_api/edit_types\").overrideAll,a=t(\"../../plot_api/plot_template\").templatedArray;e.exports=i(a(\"annotation\",{visible:n.visible,x:{valType:\"any\"},y:{valType:\"any\"},z:{valType:\"any\"},ax:{valType:\"number\"},ay:{valType:\"number\"},xanchor:n.xanchor,xshift:n.xshift,yanchor:n.yanchor,yshift:n.yshift,text:n.text,textangle:n.textangle,font:n.font,width:n.width,height:n.height,opacity:n.opacity,align:n.align,valign:n.valign,bgcolor:n.bgcolor,bordercolor:n.bordercolor,borderpad:n.borderpad,borderwidth:n.borderwidth,showarrow:n.showarrow,arrowcolor:n.arrowcolor,arrowhead:n.arrowhead,startarrowhead:n.startarrowhead,arrowside:n.arrowside,arrowsize:n.arrowsize,startarrowsize:n.startarrowsize,arrowwidth:n.arrowwidth,standoff:n.standoff,startstandoff:n.startstandoff,hovertext:n.hovertext,hoverlabel:n.hoverlabel,captureevents:n.captureevents}),\"calc\",\"from-root\")},{\"../../plot_api/edit_types\":810,\"../../plot_api/plot_template\":817,\"../annotations/attributes\":626}],636:[function(t,e,r){\"use 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n.coerce(t,e,s,r,i)}function c(t){var n=t+\"axis\",a={_fullLayout:{}};return a._fullLayout[n]=r[n],i.coercePosition(e,a,l,t,t,.5)}l(\"visible\")&&(o(t,e,a.fullLayout,l),c(\"x\"),c(\"y\"),c(\"z\"),n.noneOrAll(t,e,[\"x\",\"y\",\"z\"]),e.xref=\"x\",e.yref=\"y\",e.zref=\"z\",l(\"xanchor\"),l(\"yanchor\"),l(\"xshift\"),l(\"yshift\"),e.showarrow&&(e.axref=\"pixel\",e.ayref=\"pixel\",l(\"ax\",-10),l(\"ay\",-30),n.noneOrAll(t,e,[\"ax\",\"ay\"])))}e.exports=function(t,e,r){a(t,e,{name:\"annotations\",handleItemDefaults:l,fullLayout:r.fullLayout})}},{\"../../lib\":778,\"../../plots/array_container_defaults\":823,\"../../plots/cartesian/axes\":828,\"../annotations/common_defaults\":629,\"./attributes\":635}],638:[function(t,e,r){\"use strict\";var n=t(\"../annotations/draw\").drawRaw,i=t(\"../../plots/gl3d/project\"),a=[\"x\",\"y\",\"z\"];e.exports=function(t){for(var e=t.fullSceneLayout,r=t.dataScale,o=e.annotations,s=0;s<o.length;s++){for(var l=o[s],c=!1,u=0;u<3;u++){var 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If `target` is a string (eg *x*) we use the\",\"corresponding trace attribute (eg `xcalendar`) if it exists,\",\"even if `targetcalendar` is provided.\"].join(\" \"))}}},layoutAttributes:l,handleDefaults:c,handleTraceDefaults:function(t,e,r,n){for(var i=0;i<r.length;i++)c(t,e,r[i]+\"calendar\",n.calendar)},CANONICAL_SUNDAY:{chinese:\"2000-01-02\",coptic:\"2000-01-03\",discworld:\"2000-01-03\",ethiopian:\"2000-01-05\",hebrew:\"5000-01-01\",islamic:\"1000-01-02\",julian:\"2000-01-03\",mayan:\"5000-01-01\",nanakshahi:\"1000-01-05\",nepali:\"2000-01-05\",persian:\"1000-01-01\",jalali:\"1000-01-01\",taiwan:\"1000-01-04\",thai:\"2000-01-04\",ummalqura:\"1400-01-06\"},CANONICAL_TICK:{chinese:\"2000-01-01\",coptic:\"2000-01-01\",discworld:\"2000-01-01\",ethiopian:\"2000-01-01\",hebrew:\"5000-01-01\",islamic:\"1000-01-01\",julian:\"2000-01-01\",mayan:\"5000-01-01\",nanakshahi:\"1000-01-01\",nepali:\"2000-01-01\",persian:\"1000-01-01\",jalali:\"1000-01-01\",taiwan:\"1000-01-01\",thai:\"2000-01-01\",ummalqura:\"1400-01-01\"},DFLTRANGE:{chinese:[\"2000-01-01\",\"2001-01-01\"],coptic:[\"1700-01-01\",\"1701-01-01\"],discworld:[\"1800-01-01\",\"1801-01-01\"],ethiopian:[\"2000-01-01\",\"2001-01-01\"],hebrew:[\"5700-01-01\",\"5701-01-01\"],islamic:[\"1400-01-01\",\"1401-01-01\"],julian:[\"2000-01-01\",\"2001-01-01\"],mayan:[\"5200-01-01\",\"5201-01-01\"],nanakshahi:[\"0500-01-01\",\"0501-01-01\"],nepali:[\"2000-01-01\",\"2001-01-01\"],persian:[\"1400-01-01\",\"1401-01-01\"],jalali:[\"1400-01-01\",\"1401-01-01\"],taiwan:[\"0100-01-01\",\"0101-01-01\"],thai:[\"2500-01-01\",\"2501-01-01\"],ummalqura:[\"1400-01-01\",\"1401-01-01\"]},getCal:h,worldCalFmt:function(t,e,r){for(var 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T={y:e.y,b:u.height*g[w],t:u.height*d[w]};\"fraction\"===e.lenmode?(T.l=0,T.xl=e.x-e.len*d[b],T.r=0,T.xr=e.x+e.len*g[b]):(T.x=e.x,T.l=u.outerLength*d[b],T.r=u.outerLength*g[b]),i.autoMargin(t,m(e),T)}function x(t,e,r){if(e.currentvalue.visible){var n,i,a=e._dims;switch(e.currentvalue.xanchor){case\"right\":n=a.inputAreaLength-f.currentValueInset-a.currentValueMaxWidth,i=\"left\";break;case\"center\":n=.5*a.inputAreaLength,i=\"middle\";break;default:n=f.currentValueInset,i=\"left\"}var l=s.ensureSingle(t,\"text\",f.labelClass,(function(t){t.attr({\"text-anchor\":i,\"data-notex\":1})})),u=e.currentvalue.prefix?e.currentvalue.prefix:\"\";if(\"string\"==typeof r)u+=r;else{var h=e.steps[e.active].label,d=e._gd._fullLayout._meta;d&&(h=s.templateString(h,d)),u+=h}e.currentvalue.suffix&&(u+=e.currentvalue.suffix),l.call(o.font,e.currentvalue.font).text(u).call(c.convertToTspans,e._gd);var g=c.lineCount(l),m=(a.currentValueMaxLines+1-g)*e.currentvalue.font.size*p;return 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r=t[e[n]],s=(r._extremes||{})[o];if(!0===r.visible&&s){for(i=0;i<s.min.length;i++)a=s.min[i],d(u,a.val,a.pad,{extrapad:a.extrapad});for(i=0;i<s.max.length;i++)a=s.max[i],g(f,a.val,a.pad,{extrapad:a.extrapad})}}}if(h(s,e._traceIndices),h(c.annotations||[],e._annIndices||[]),h(c.shapes||[],e._shapeIndices||[]),e._matchGroup&&!r)for(var m in e._matchGroup)if(m!==e._id){var v=l(t,m),y=p(t,v,!0),x=e._length/v._length;for(i=0;i<y.min.length;i++)a=y.min[i],d(u,a.val,a.pad*x,{extrapad:a.extrapad});for(i=0;i<y.max.length;i++)a=y.max[i],g(f,a.val,a.pad*x,{extrapad:a.extrapad})}return{min:u,max:f}}function d(t,e,r,n){m(t,e,r,n,y)}function g(t,e,r,n){m(t,e,r,n,x)}function m(t,e,r,n,i){for(var a=n.tozero,o=n.extrapad,s=!0,l=0;l<t.length&&s;l++){var c=t[l];if(i(c.val,e)&&c.pad>=r&&(c.extrapad||!o)){s=!1;break}i(e,c.val)&&c.pad<=r&&(o||!c.extrapad)&&(t.splice(l,1),l--)}if(s){var u=a&&0===e;t.push({val:e,pad:u?0:r,extrapad:!u&&o})}}function v(t){return n(t)&&Math.abs(t)<a}function y(t,e){return 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n,a=t.nticks;a||(\"category\"===t.type||\"multicategory\"===t.type?(n=t.tickfont?1.2*(t.tickfont.size||12):15,a=t._length/n):(n=\"y\"===t._id.charAt(0)?40:80,a=s.constrain(t._length/n,4,9)+1),\"radialaxis\"===t._name&&(a*=2)),\"array\"===t.tickmode&&(a*=100),t._roughDTick=Math.abs(r[1]-r[0])/a,B.autoTicks(t,t._roughDTick),t._minDtick>0&&t.dtick<2*t._minDtick&&(t.dtick=t._minDtick,t.tick0=t.l2r(t._forceTick0))}\"period\"===t.ticklabelmode&&function(t){var e;function r(){return!(i(t.dtick)||\"M\"!==t.dtick.charAt(0))}var n=r(),a=B.getTickFormat(t);if(a){var 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c=\"category\"===t.type?t.d2l_noadd:t.d2l;\"log\"===t.type&&\"L\"!==String(t.dtick).charAt(0)&&(t.dtick=\"L\"+Math.pow(10,Math.floor(Math.min(t.range[0],t.range[1]))-1));for(var u=0;u<e.length;u++){var f=c(e[u]);f>a&&f<o&&(void 0===r[u]?n[l]=B.tickText(t,f):n[l]=it(t,f,String(r[u])),l++)}l<e.length&&n.splice(l,e.length-l);t.rangebreaks&&(n=n.filter((function(e){return t.maskBreaks(e.x)!==P})));return n}(t);var n=H(r),a=n[0],o=n[1],l=r[1]<r[0],c=Math.min(r[0],r[1]),u=Math.max(r[0],r[1]),f=\"log\"===t.type&&!(i(t.dtick)||\"L\"===t.dtick.charAt(0)),h=\"period\"===t.ticklabelmode;if(t._tmin=B.tickFirst(t,e),t._tmin<a!==l)return[];\"category\"!==t.type&&\"multicategory\"!==t.type||(o=l?Math.max(-.5,o):Math.min(t._categories.length-.5,o));var p=t._tmin;t.rangebreaks&&t._tick0Init!==t.tick0&&(p=wt(p,t),l||(p=B.tickIncrement(p,t.dtick,!l,t.calendar))),h&&(p=B.tickIncrement(p,t.dtick,!l,t.calendar));for(var d,g=Math.max(1e3,t._length||0),C=[],L=null;l?p>=o:p<=o;p=B.tickIncrement(p,t.dtick,l,t.calendar)){if(t.rangebreaks&&!l){if(p<a)continue;if(t.maskBreaks(p)===P&&wt(p,t)>=u)break}if(C.length>g||p===L)break;L=p;var I=!1;f&&p!==(0|p)&&(I=!0),C.push({minor:I,value:p})}if(h&&function(t,e,r){for(var n=0;n<t.length;n++){var i=t[n].value,a=n,o=n+1;n<t.length-1?(a=n,o=n+1):n>0?(a=n-1,o=n):(a=n,o=n);var s,l=t[a].value,c=t[o].value,u=Math.abs(c-l),f=r||u,h=0;f>=y?h=u>=y&&u<=m?u:v:r===b&&f>=_?h=u>=_&&u<=x?u:b:f>=k?h=u>=k&&u<=w?u:T:r===M&&f>=M?h=M:f>=A?h=A:r===S&&f>=S?h=S:r===E&&f>=E&&(h=E),h>=u&&(h=u,s=!0);var p=i+h;if(e.rangebreaks&&h>0){for(var d=0,g=0;g<84;g++){var C=(g+.5)/84;e.maskBreaks(i*(1-C)+C*p)!==P&&d++}(h*=d/84)||(t[n].drop=!0),s&&u>M&&(h=u)}(h>0||0===n)&&(t[n].periodX=i+h/2)}}(C,t,t._definedDelta),t.rangebreaks){var z=\"y\"===t._id.charAt(0),O=1;\"auto\"===t.tickmode&&(O=t.tickfont?t.tickfont.size:12);var 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w=e._anchorAxis;w&&w.autorange&&-1!==(e.ticklabelposition||\"\").indexOf(\"inside\")&&!V(a,e._id)&&(a._insideTickLabelsAutorange||(a._insideTickLabelsAutorange={}),a._insideTickLabelsAutorange[w._name+\".autorange\"]=w.autorange,_.push((function(){v.each((function(t,r){var n=dt(this);e._vals[r].bb=h.bBox(n.node())}))})));var T=s.syncOrAsync(_);return T&&T.then&&t._promises.push(T),T},B.getPxPosition=function(t,e){var r,n=t._fullLayout._size,i=e._id.charAt(0),a=e.side;return\"free\"!==e.anchor?r=e._anchorAxis:\"x\"===i?r={_offset:n.t+(1-(e.position||0))*n.h,_length:0}:\"y\"===i&&(r={_offset:n.l+(e.position||0)*n.w,_length:0}),\"top\"===a||\"left\"===a?r._offset:\"bottom\"===a||\"right\"===a?r._offset+r._length:void 0},B.shouldShowZeroLine=function(t,e,r){var n=s.simpleMap(e.range,e.r2l);return n[0]*n[1]<=0&&e.zeroline&&(\"linear\"===e.type||\"-\"===e.type)&&!(e.rangebreaks&&e.maskBreaks(0)===P)&&(pt(e,0)||!function(t,e,r,n){var i=r._mainAxis;if(!i)return;var 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r=a(t.changedTouches[0],e);f(0,r[0],r[1]),f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener(\"touchmove\",(function(t){t.preventDefault();var r=a(t.changedTouches[0],e);f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener(\"touchend\",(function(t){f(0,c.lastPos[0],c.lastPos[1]),t.preventDefault()}),!!s&&{passive:!1}),c.wheelListener=i(e,(function(e,n){if(!t.scrollZoom)return!1;var i=t.calcDataBox(),a=r.viewBox,o=c.lastPos[0],s=c.lastPos[1],l=Math.exp(5*n/(a[3]-a[1])),f=o/(a[2]-a[0])*(i[2]-i[0])+i[0],h=s/(a[3]-a[1])*(i[3]-i[1])+i[1];return i[0]=(i[0]-f)*l+f,i[2]=(i[2]-f)*l+f,i[1]=(i[1]-h)*l+h,i[3]=(i[3]-h)*l+h,t.setRanges(i),c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations(),t.relayoutCallback(),!0}),!0),c}},{\"../cartesian/constants\":834,\"has-passive-events\":441,\"mouse-change\":483,\"mouse-event-offset\":484,\"mouse-wheel\":486}],867:[function(t,e,r){\"use strict\";var n=t(\"../cartesian/axes\"),i=t(\"../../lib/str2rgbarray\");function a(t){this.scene=t,this.gl=t.gl,this.pixelRatio=t.pixelRatio,this.screenBox=[0,0,1,1],this.viewBox=[0,0,1,1],this.dataBox=[-1,-1,1,1],this.borderLineEnable=[!1,!1,!1,!1],this.borderLineWidth=[1,1,1,1],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.ticks=[[],[]],this.tickEnable=[!0,!0,!1,!1],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labels=[\"x\",\"y\"],this.labelEnable=[!0,!0,!1,!1],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelPad=[15,15,15,15],this.labelSize=[12,12],this.labelFont=[\"sans-serif\",\"sans-serif\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.title=\"\",this.titleEnable=!0,this.titleCenter=[0,0,0,0],this.titleAngle=0,this.titleColor=[0,0,0,1],this.titleFont=\"sans-serif\",this.titleSize=18,this.gridLineEnable=[!0,!0],this.gridLineColor=[[0,0,0,.5],[0,0,0,.5]],this.gridLineWidth=[1,1],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[1,1],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.static=this.scene.staticPlot}var o=a.prototype,s=[\"xaxis\",\"yaxis\"];o.merge=function(t){var e,r,n,a,o,l,c,u,f,h,p;for(this.titleEnable=!1,this.backgroundColor=i(t.plot_bgcolor),h=0;h<2;++h){var d=(e=s[h]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?\"\":r.title.text,p=0;p<=2;p+=2)this.labelEnable[h+p]=!1,this.labels[h+p]=n,this.labelColor[h+p]=i(r.title.font.color),this.labelFont[h+p]=r.title.font.family,this.labelSize[h+p]=r.title.font.size,this.labelPad[h+p]=this.getLabelPad(e,r),this.tickEnable[h+p]=!1,this.tickColor[h+p]=i((r.tickfont||{}).color),this.tickAngle[h+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[h+p]=this.getTickPad(r),this.tickMarkLength[h+p]=0,this.tickMarkWidth[h+p]=r.tickwidth||0,this.tickMarkColor[h+p]=i(r.tickcolor),this.borderLineEnable[h+p]=!1,this.borderLineColor[h+p]=i(r.linecolor),this.borderLineWidth[h+p]=r.linewidth||0;c=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,a=r.mirror||!1,u=c?-1!==String(a).indexOf(\"all\"):!!a,f=c?\"allticks\"===a:-1!==String(a).indexOf(\"ticks\"),o?this.labelEnable[h]=!0:l&&(this.labelEnable[h+2]=!0),o?this.tickEnable[h]=r.showticklabels:l&&(this.tickEnable[h+2]=r.showticklabels),(o||u)&&(this.borderLineEnable[h]=r.showline),(l||u)&&(this.borderLineEnable[h+2]=r.showline),(o||f)&&(this.tickMarkLength[h]=this.getTickMarkLength(r)),(l||f)&&(this.tickMarkLength[h+2]=this.getTickMarkLength(r)),this.gridLineEnable[h]=r.showgrid,this.gridLineColor[h]=i(r.gridcolor),this.gridLineWidth[h]=r.gridwidth,this.zeroLineEnable[h]=r.zeroline,this.zeroLineColor[h]=i(r.zerolinecolor),this.zeroLineWidth[h]=r.zerolinewidth}},o.hasSharedAxis=function(t){var e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},o.getLabelPad=function(t,e){var r=e.title.font.size,n=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?r*(1.5+(n?1:0))-10:r*(1.5+(n?.5:0))-10:\"yaxis\"===t?\"right\"===e.side?10+r*(1.5+(n?1:.5)):10+r*(1.5+(n?.5:0)):void 0},o.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=function(t){return new a(t)}},{\"../../lib/str2rgbarray\":802,\"../cartesian/axes\":828}],868:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"./scene2d\"),a=t(\"../layout_attributes\"),o=t(\"../../constants/xmlns_namespaces\"),s=t(\"../cartesian/constants\"),l=t(\"../cartesian\"),c=t(\"../../components/fx/layout_attributes\"),u=t(\"../get_data\").getSubplotData;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex=s.idRegex,r.attrRegex=s.attrRegex,r.attributes=t(\"../cartesian/attributes\"),r.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},r.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),r.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:c.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=u(r,\"gl2d\",o),c=s._scene2d;void 0===c&&(c=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=c),c.plot(l,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];if(s._scene2d){var c=u(t,\"gl2d\",o);0===c.length&&(s._scene2d.destroy(),delete n._plots[o])}}l.clean.apply(this,arguments)},r.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){e._plots[r[n]]._scene2d.updateFx(e.dragmode)}}},{\"../../components/fx/layout_attributes\":684,\"../../constants/xmlns_namespaces\":754,\"../../plot_api/edit_types\":810,\"../cartesian\":841,\"../cartesian/attributes\":826,\"../cartesian/constants\":834,\"../get_data\":865,\"../layout_attributes\":882,\"./scene2d\":869}],869:[function(t,e,r){\"use strict\";var n,i,a=t(\"../../registry\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../../components/fx\"),l=t(\"gl-plot2d\"),c=t(\"gl-spikes2d\"),u=t(\"gl-select-box\"),f=t(\"webgl-context\"),h=t(\"./convert\"),p=t(\"./camera\"),d=t(\"../../lib/show_no_webgl_msg\"),g=t(\"../cartesian/constraints\"),m=g.enforce,v=g.clean,y=t(\"../cartesian/autorange\").doAutoRange,x=t(\"../../components/dragelement/helpers\"),b=x.drawMode,_=x.selectMode,w=[\"xaxis\",\"yaxis\"],T=t(\"../cartesian/constants\").SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=c(this.glplot),this.selectBox=u(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}e.exports=k;var M=k.prototype;M.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r);var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener(\"mouseover\",(function(){l.isMouseOver=!0}))},M.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=a[4*(r*o+l)+c];a[4*(r*o+l)+c]=a[4*(r*s+l)+c],a[4*(r*s+l)+c]=u}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\"),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},M.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},M.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},M.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},M.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var c=n[r._name];c.range=s,c.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},M.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},M.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},M.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},M.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:this.graphDiv._fullLayout._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis}};v(s,this.xaxis),v(s,this.yaxis);var l,c,u=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[u.l+f[0]*u.w,u.b+h[0]*u.h,i-u.r-(1-f[1])*u.w,a-u.t-(1-h[1])*u.h],this.mouseContainer.style.width=u.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=u.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=u.h*(h[1]-h[0]),this.mouseContainer.style.left=u.l+f[0]*u.w+\"px\",this.mouseContainer.style.top=u.t+(1-h[1])*u.h+\"px\",c=0;c<2;++c)(l=this[w[c]])._length=o.viewBox[c+2]-o.viewBox[c],y(this.graphDiv,l),l.setScale();m(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},M.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},M.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},M.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],c=this.traces[i.uid];c?c.update(i,l):(c=i._module.plot(this,i,l),this.traces[i.uid]=c)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},M.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},M.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},M.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var c=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],u=0;u<2;u++)e.boxStart[u]===e.boxEnd[u]&&(c[u]=t.dataBox[u],c[u+2]=t.dataBox[u+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var g=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),g.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var m=this.fullData[g.trace.index]||{},v=g.pointIndex,y=s.castHoverinfo(m,i,v);if(y&&\"all\"!==y){var x=y.split(\"+\");-1===x.indexOf(\"x\")&&(g.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(g.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(g.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(g.textLabel=void 0),-1===x.indexOf(\"name\")&&(g.name=void 0)}s.loneHover({x:g.screenCoord[0],y:g.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",g.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",g.traceCoord[1]),zLabel:g.traceCoord[2],text:g.textLabel,name:g.name,color:s.castHoverOption(m,v,\"bgcolor\")||g.color,borderColor:s.castHoverOption(m,v,\"bordercolor\"),fontFamily:s.castHoverOption(m,v,\"font.family\"),fontSize:s.castHoverOption(m,v,\"font.size\"),fontColor:s.castHoverOption(m,v,\"font.color\"),nameLength:s.castHoverOption(m,v,\"namelength\"),textAlign:s.castHoverOption(m,v,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},M.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},M.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../components/dragelement/helpers\":661,\"../../components/fx\":683,\"../../lib/show_no_webgl_msg\":800,\"../../plots/cartesian/axes\":828,\"../../registry\":911,\"../cartesian/autorange\":827,\"../cartesian/constants\":834,\"../cartesian/constraints\":835,\"./camera\":866,\"./convert\":867,\"gl-plot2d\":317,\"gl-select-box\":333,\"gl-spikes2d\":342,\"webgl-context\":606}],870:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"../../components/fx/layout_attributes\"),a=t(\"./scene\"),o=t(\"../get_data\").getSubplotData,s=t(\"../../lib\"),l=t(\"../../constants/xmlns_namespaces\");r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=r.attrRegex=s.counterRegex(\"scene\"),r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl3d,i=0;i<n.length;i++){var s=n[i],l=o(r,\"gl3d\",s),c=e[s],u=c.camera,f=c._scene;f||(f=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},e),c._scene=f),f.viewInitial||(f.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),f.plot(l,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl3d||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}}},{\"../../components/fx/layout_attributes\":684,\"../../constants/xmlns_namespaces\":754,\"../../lib\":778,\"../../plot_api/edit_types\":810,\"../get_data\":865,\"./layout/attributes\":871,\"./layout/defaults\":875,\"./layout/layout_attributes\":876,\"./scene\":880}],871:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},{}],872:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../plot_api/edit_types\").overrideAll;e.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,rangemode:i.rangemode,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},{\"../../../components/color\":643,\"../../../lib/extend\":768,\"../../../plot_api/edit_types\":810,\"../../cartesian/layout_attributes\":842}],873:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"../../../plot_api/plot_template\"),o=t(\"./axis_attributes\"),s=t(\"../../cartesian/type_defaults\"),l=t(\"../../cartesian/axis_defaults\"),c=[\"xaxis\",\"yaxis\",\"zaxis\"];e.exports=function(t,e,r){var u,f;function h(t,e){return i.coerce(u,f,o,t,e)}for(var p=0;p<c.length;p++){var d=c[p];u=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(u,f,h,r),l(u,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelposition:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,13600/187).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},{\"../../../lib\":778,\"../../../plot_api/plot_template\":817,\"../../cartesian/axis_defaults\":830,\"../../cartesian/type_defaults\":853,\"./axis_attributes\":872,tinycolor2:576}],874:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=0;r<3;++r){var o=e[a[r]];o.visible?(this.labels[r]=t._meta?i.templateString(o.title.text,t._meta):o.title.text,\"font\"in o.title&&(o.title.font.color&&(this.labelColor[r]=n(o.title.font.color)),o.title.font.family&&(this.labelFont[r]=o.title.font.family),o.title.font.size&&(this.labelSize[r]=o.title.font.size)),\"showline\"in o&&(this.lineEnable[r]=o.showline),\"linecolor\"in o&&(this.lineColor[r]=n(o.linecolor)),\"linewidth\"in o&&(this.lineWidth[r]=o.linewidth),\"showgrid\"in o&&(this.gridEnable[r]=o.showgrid),\"gridcolor\"in o&&(this.gridColor[r]=n(o.gridcolor)),\"gridwidth\"in o&&(this.gridWidth[r]=o.gridwidth),\"log\"===o.type?this.zeroEnable[r]=!1:\"zeroline\"in o&&(this.zeroEnable[r]=o.zeroline),\"zerolinecolor\"in o&&(this.zeroLineColor[r]=n(o.zerolinecolor)),\"zerolinewidth\"in o&&(this.zeroLineWidth[r]=o.zerolinewidth),\"ticks\"in o&&o.ticks?this.lineTickEnable[r]=!0:this.lineTickEnable[r]=!1,\"ticklen\"in o&&(this.lineTickLength[r]=this._defaultLineTickLength[r]=o.ticklen),\"tickcolor\"in o&&(this.lineTickColor[r]=n(o.tickcolor)),\"tickwidth\"in o&&(this.lineTickWidth[r]=o.tickwidth),\"tickangle\"in o&&(this.tickAngle[r]=\"auto\"===o.tickangle?-3600:Math.PI*-o.tickangle/180),\"showticklabels\"in o&&(this.tickEnable[r]=o.showticklabels),\"tickfont\"in o&&(o.tickfont.color&&(this.tickColor[r]=n(o.tickfont.color)),o.tickfont.family&&(this.tickFont[r]=o.tickfont.family),o.tickfont.size&&(this.tickSize[r]=o.tickfont.size)),\"mirror\"in o?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(o.mirror)?(this.lineTickMirror[r]=!0,this.lineMirror[r]=!0):!0===o.mirror?(this.lineTickMirror[r]=!1,this.lineMirror[r]=!0):(this.lineTickMirror[r]=!1,this.lineMirror[r]=!1):this.lineMirror[r]=!1,\"showbackground\"in o&&!1!==o.showbackground?(this.backgroundEnable[r]=!0,this.backgroundColor[r]=n(o.backgroundcolor)):this.backgroundEnable[r]=!1):(this.tickEnable[r]=!1,this.labelEnable[r]=!1,this.lineEnable[r]=!1,this.lineTickEnable[r]=!1,this.gridEnable[r]=!1,this.zeroEnable[r]=!1,this.backgroundEnable[r]=!1)}},e.exports=function(t,e){var r=new o;return r.merge(t,e),r}},{\"../../../lib\":778,\"../../../lib/str2rgbarray\":802}],875:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"../../../components/color\"),a=t(\"../../../registry\"),o=t(\"../../subplot_defaults\"),s=t(\"./axis_defaults\"),l=t(\"./layout_attributes\"),c=t(\"../../get_data\").getSubplotData;function u(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),u=[\"up\",\"center\",\"eye\"],f=0;f<u.length;f++)r(\"camera.\"+u[f]+\".x\"),r(\"camera.\"+u[f]+\".y\"),r(\"camera.\"+u[f]+\".z\");r(\"camera.projection.type\");var h=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),p=r(\"aspectmode\",h?\"manual\":\"auto\");h||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===p&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var d=c(n.fullData,\"gl3d\",n.id);s(t,e,{font:n.font,scene:n.id,data:d,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var g=n.getDfltFromLayout(\"dragmode\");if(!1!==g&&!g)if(g=\"orbit\",t.camera&&t.camera.up){var m=t.camera.up.x,v=t.camera.up.y,y=t.camera.up.z;0!==y&&(m&&v&&y?y/Math.sqrt(m*m+v*v+y*y)>.999&&(g=\"turntable\"):g=\"turntable\")}else g=\"turntable\";r(\"dragmode\",g),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}e.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:\"gl3d\",attributes:l,handleDefaults:u,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{\"../../../components/color\":643,\"../../../lib\":778,\"../../../registry\":911,\"../../get_data\":865,\"../../subplot_defaults\":905,\"./axis_defaults\":873,\"./layout_attributes\":876}],876:[function(t,e,r){\"use strict\";var n=t(\"./axis_attributes\"),i=t(\"../../domain\").attributes,a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../lib\").counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}e.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},{\"../../../lib\":778,\"../../../lib/extend\":768,\"../../domain\":855,\"./axis_attributes\":872}],877:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=function(t){var e=new a;return e.merge(t),e}},{\"../../../lib/str2rgbarray\":802}],878:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],c=0;c<3;++c){var u=s[a[c]];if(u._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(u._length)===1/0||isNaN(u._length))l[c]=[];else{u._input_range=u.range.slice(),u.range[0]=r[c].lo/t.dataScale[c],u.range[1]=r[c].hi/t.dataScale[c],u._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),u.range[0]===u.range[1]&&(u.range[0]-=1,u.range[1]+=1);var f=u.tickmode;if(\"auto\"===u.tickmode){u.tickmode=\"linear\";var h=u.nticks||i.constrain(u._length/40,4,9);n.autoTicks(u,Math.abs(u.range[1]-u.range[0])/h)}for(var p=n.calcTicks(u,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[c],\"date\"===u.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[c]=p,u.tickmode=f}}e.ticks=l;for(c=0;c<3;++c){o[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(d=0;d<2;++d)e.bounds[d][c]=t.glplot.bounds[d][c]}t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=t(\"../../cartesian/axes\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},{\"../../../lib\":778,\"../../cartesian/axes\":828}],879:[function(t,e,r){\"use strict\";function n(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}e.exports=function(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}},{}],880:[function(t,e,r){\"use strict\";var n,i,a=t(\"gl-plot3d\"),o=a.createCamera,s=a.createScene,l=t(\"webgl-context\"),c=t(\"has-passive-events\"),u=t(\"../../registry\"),f=t(\"../../lib\"),h=f.preserveDrawingBuffer(),p=t(\"../../plots/cartesian/axes\"),d=t(\"../../components/fx\"),g=t(\"../../lib/str2rgbarray\"),m=t(\"../../lib/show_no_webgl_msg\"),v=t(\"./project\"),y=t(\"./layout/convert\"),x=t(\"./layout/spikes\"),b=t(\"./layout/tick_marks\");function _(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=y(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=u.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=u.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var w=_.prototype;w.prepareOptions=function(){var t={canvas:this.canvas,gl:this.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:this.container,axes:this.axesOptions,spikes:this.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:this.camera,pixelRatio:this.pixelRatio};if(this.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");t.gl=i,t.canvas=n}return t};var T=!0;w.tryCreatePlot=function(){var t=this.prepareOptions(),e=!0;try{this.glplot=s(t)}catch(r){if(this.staticMode||!T||h)e=!1;else{f.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{h=t.glOptions.preserveDrawingBuffer=!0,this.glplot=s(t)}catch(r){h=t.glOptions.preserveDrawingBuffer=!1,e=!1}}}return T=!1,e},w.initializeGLCamera=function(){var t=this.fullSceneLayout.camera,e=\"orthographic\"===t.projection.type;this.camera=o(this.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:e,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},w.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return m(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio(),\"manual\"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+\".aspectmode\"]=\"manual\")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener(\"mouseup\",(function(){i(t)})),t.glplot.canvas.addEventListener(\"wheel\",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!c&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}})),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",(function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},w.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var c,u=Object.keys(e.traces),h=null,g=e.glplot.selection,m=0;m<u.length;++m)\"skip\"!==(t=e.traces[u[m]]).data.hoverinfo&&t.handlePick(g)&&(h=t),t.setContourLevels&&t.setContourLevels();function y(t,r){var n=e.fullSceneLayout[t];return p.tickText(n,n.d2l(r),\"hover\").text}if(null!==h){var x=v(e.glplot.cameraParams,g.dataCoordinate);t=h.data;var _,w=r._fullData[t.index],T=g.index,k={xLabel:y(\"xaxis\",g.traceCoordinate[0]),yLabel:y(\"yaxis\",g.traceCoordinate[1]),zLabel:y(\"zaxis\",g.traceCoordinate[2])},M=d.castHoverinfo(w,e.fullLayout,T),A=(M||\"\").split(\"+\"),S=M&&\"all\"===M;w.hovertemplate||S||(-1===A.indexOf(\"x\")&&(k.xLabel=void 0),-1===A.indexOf(\"y\")&&(k.yLabel=void 0),-1===A.indexOf(\"z\")&&(k.zLabel=void 0),-1===A.indexOf(\"text\")&&(g.textLabel=void 0),-1===A.indexOf(\"name\")&&(h.name=void 0));var E=[];\"cone\"===t.type||\"streamtube\"===t.type?(k.uLabel=y(\"xaxis\",g.traceCoordinate[3]),(S||-1!==A.indexOf(\"u\"))&&E.push(\"u: \"+k.uLabel),k.vLabel=y(\"yaxis\",g.traceCoordinate[4]),(S||-1!==A.indexOf(\"v\"))&&E.push(\"v: \"+k.vLabel),k.wLabel=y(\"zaxis\",g.traceCoordinate[5]),(S||-1!==A.indexOf(\"w\"))&&E.push(\"w: \"+k.wLabel),k.normLabel=g.traceCoordinate[6].toPrecision(3),(S||-1!==A.indexOf(\"norm\"))&&E.push(\"norm: \"+k.normLabel),\"streamtube\"===t.type&&(k.divergenceLabel=g.traceCoordinate[7].toPrecision(3),(S||-1!==A.indexOf(\"divergence\"))&&E.push(\"divergence: \"+k.divergenceLabel)),g.textLabel&&E.push(g.textLabel),_=E.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(k.valueLabel=p.tickText(e._mockAxis,e._mockAxis.d2l(g.traceCoordinate[3]),\"hover\").text,E.push(\"value: \"+k.valueLabel),g.textLabel&&E.push(g.textLabel),_=E.join(\"<br>\")):_=g.textLabel;var C={x:g.traceCoordinate[0],y:g.traceCoordinate[1],z:g.traceCoordinate[2],data:w._input,fullData:w,curveNumber:w.index,pointNumber:T};d.appendArrayPointValue(C,w,T),t._module.eventData&&(C=w._module.eventData(C,g,w,{},T));var L={points:[C]};e.fullSceneLayout.hovermode&&d.loneHover({trace:w,x:(.5+.5*x[0]/x[3])*s,y:(.5-.5*x[1]/x[3])*l,xLabel:k.xLabel,yLabel:k.yLabel,zLabel:k.zLabel,text:_,name:h.name,color:d.castHoverOption(w,T,\"bgcolor\")||h.color,borderColor:d.castHoverOption(w,T,\"bordercolor\"),fontFamily:d.castHoverOption(w,T,\"font.family\"),fontSize:d.castHoverOption(w,T,\"font.size\"),fontColor:d.castHoverOption(w,T,\"font.color\"),nameLength:d.castHoverOption(w,T,\"namelength\"),textAlign:d.castHoverOption(w,T,\"align\"),hovertemplate:f.castOption(w,T,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},C,k),eventData:[C]},{container:n,gd:r}),g.buttons&&g.distance<5?r.emit(\"plotly_click\",L):r.emit(\"plotly_hover\",L),c=L}else d.loneUnhover(n),r.emit(\"plotly_unhover\",c);e.drawAnnotations(e)},w.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var k=[\"xaxis\",\"yaxis\",\"zaxis\"];function M(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=k[i],o=a.charAt(0),s=n[a],l=e[o],c=e[o+\"calendar\"],u=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(u||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)h=s.d2l(l[p][d],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else h=s.d2l(l[p],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],u-1)}}w.plot=function(t,e,r){if(this.plotArgs=[t,e,r],!this.glplot.contextLost){var n,i,a,o,s,l,c=e[this.id],u=r[this.id];this.fullLayout=e,this.fullSceneLayout=c,this.axesOptions.merge(e,c),this.spikeOptions.merge(c),this.setViewport(c),this.updateFx(c.dragmode,c.hovermode),this.camera.enableWheel=this.graphDiv._context._scrollZoom.gl3d,this.glplot.setClearColor(g(c.bgcolor)),this.setConvert(s),t?Array.isArray(t)||(t=[t]):t=[];var f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&M(this,n,f);!function(t,e){for(var r=t.fullSceneLayout,n=r.annotations||[],i=0;i<3;i++)for(var a=k[i],o=a.charAt(0),s=r[a],l=0;l<n.length;l++){var c=n[l];if(c.visible){var u=s.r2l(c[o]);!isNaN(u)&&isFinite(u)&&(e[0][i]=Math.min(e[0][i],u),e[1][i]=Math.max(e[1][i],u))}}}(this,f);var h=[1,1,1];for(o=0;o<3;++o)f[1][o]===f[0][o]?h[o]=1:h[o]=1/(f[1][o]-f[0][o]);for(this.dataScale=h,this.convertAnnotations(this),a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&((i=this.traces[n.uid])?i.data.type===n.type?i.update(n):(i.dispose(),i=n._module.plot(this,n),this.traces[n.uid]=i):(i=n._module.plot(this,n),this.traces[n.uid]=i),i.name=n.name);var p=Object.keys(this.traces);t:for(a=0;a<p.length;++a){for(o=0;o<t.length;++o)if(t[o].uid===p[a]&&!0===t[o].visible&&0!==t[o]._length)continue t;(i=this.traces[p[a]]).dispose(),delete this.traces[p[a]]}this.glplot.objects.sort((function(t,e){return t._trace.data.index-e._trace.data.index}));var d,m=[[0,0,0],[0,0,0]],v=[],y={};for(a=0;a<3;++a){if((l=(s=c[k[a]]).type)in y?(y[l].acc*=h[a],y[l].count+=1):y[l]={acc:h[a],count:1},s.autorange){m[0][a]=1/0,m[1][a]=-1/0;var x=this.glplot.objects,b=this.fullSceneLayout.annotations||[],_=s._name.charAt(0);for(o=0;o<x.length;o++){var w=x[o],T=w.bounds,A=w._trace.data._pad||0;\"ErrorBars\"===w.constructor.name&&s._lowerLogErrorBound?m[0][a]=Math.min(m[0][a],s._lowerLogErrorBound):m[0][a]=Math.min(m[0][a],T[0][a]/h[a]-A),m[1][a]=Math.max(m[1][a],T[1][a]/h[a]+A)}for(o=0;o<b.length;o++){var S=b[o];if(S.visible){var E=s.r2l(S[_]);m[0][a]=Math.min(m[0][a],E),m[1][a]=Math.max(m[1][a],E)}}if(\"rangemode\"in s&&\"tozero\"===s.rangemode&&(m[0][a]=Math.min(m[0][a],0),m[1][a]=Math.max(m[1][a],0)),m[0][a]>m[1][a])m[0][a]=-1,m[1][a]=1;else{var C=m[1][a]-m[0][a];m[0][a]-=C/32,m[1][a]+=C/32}if(\"reversed\"===s.autorange){var L=m[0][a];m[0][a]=m[1][a],m[1][a]=L}}else{var I=s.range;m[0][a]=s.r2l(I[0]),m[1][a]=s.r2l(I[1])}m[0][a]===m[1][a]&&(m[0][a]-=1,m[1][a]+=1),v[a]=m[1][a]-m[0][a],this.glplot.setBounds(a,{min:m[0][a]*h[a],max:m[1][a]*h[a]})}var P=c.aspectmode;if(\"cube\"===P)d=[1,1,1];else if(\"manual\"===P){var z=c.aspectratio;d=[z.x,z.y,z.z]}else{if(\"auto\"!==P&&\"data\"!==P)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var O=[1,1,1];for(a=0;a<3;++a){var D=y[l=(s=c[k[a]]).type];O[a]=Math.pow(D.acc,1/D.count)/h[a]}d=\"data\"===P||Math.max.apply(null,O)/Math.min.apply(null,O)<=4?O:[1,1,1]}c.aspectratio.x=u.aspectratio.x=d[0],c.aspectratio.y=u.aspectratio.y=d[1],c.aspectratio.z=u.aspectratio.z=d[2],this.glplot.setAspectratio(c.aspectratio),this.viewInitial.aspectratio||(this.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),this.viewInitial.aspectmode||(this.viewInitial.aspectmode=c.aspectmode);var R=c.domain||null,F=e._size||null;if(R&&F){var B=this.container.style;B.position=\"absolute\",B.left=F.l+R.x[0]*F.w+\"px\",B.top=F.t+(1-R.y[1])*F.h+\"px\",B.width=F.w*(R.x[1]-R.x[0])+\"px\",B.height=F.h*(R.y[1]-R.y[0])+\"px\"}this.glplot.redraw()}},w.destroy=function(){this.glplot&&(this.camera.mouseListener.enabled=!1,this.container.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null,this.glplot.dispose(),this.container.parentNode.removeChild(this.container),this.glplot=null)},w.getCamera=function(){var t;return this.camera.view.recalcMatrix(this.camera.view.lastT()),{up:{x:(t=this.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},w.setViewport=function(t){var e,r=t.camera;this.camera.lookAt.apply(this,[[(e=r).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),this.glplot.setAspectratio(t.aspectratio),\"orthographic\"===r.projection.type!==this.camera._ortho&&(this.glplot.redraw(),this.glplot.clearRGBA(),this.glplot.dispose(),this.initializeGLPlot())},w.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}var i=!1;if(void 0===r)i=!0;else{for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!n(e,r,a,o)){i=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(i=!0)}return i},w.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=f.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},w.saveLayout=function(t){var e,r,n,i,a,o,s=this.fullLayout,l=this.isCameraChanged(t),c=this.isAspectChanged(t),h=l||c;if(h){var p={};if(l&&(e=this.getCamera(),n=(r=f.nestedProperty(t,this.id+\".camera\")).get(),p[this.id+\".camera\"]=n),c&&(i=this.glplot.getAspectratio(),o=(a=f.nestedProperty(t,this.id+\".aspectratio\")).get(),p[this.id+\".aspectratio\"]=o),u.call(\"_storeDirectGUIEdit\",t,s._preGUI,p),l)r.set(e),f.nestedProperty(s,this.id+\".camera\").set(e);if(c)a.set(i),f.nestedProperty(s,this.id+\".aspectratio\").set(i),this.glplot.redraw()}return h},w.updateFx=function(t,e){var r=this.camera;if(r)if(\"orbit\"===t)r.mode=\"orbit\",r.keyBindingMode=\"rotate\";else if(\"turntable\"===t){r.up=[0,0,1],r.mode=\"turntable\",r.keyBindingMode=\"rotate\";var n=this.graphDiv,i=n._fullLayout,a=this.fullSceneLayout.camera,o=a.up.x,s=a.up.y,l=a.up.z;if(l/Math.sqrt(o*o+s*s+l*l)<.999){var c=this.id+\".camera.up\",h={x:0,y:0,z:1},p={};p[c]=h;var 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r=t.visible;return\"undefined\"==typeof r||!0===r})),d=!1,g=p.map((function(t,e){return d=d||\"undefined\"!=typeof t.groupId,t}));if(d){var m=n.nest().key((function(t,e){return\"undefined\"!=typeof t.groupId?t.groupId:\"unstacked\"})).entries(g),v=[],y=m.map((function(t,e){if(\"unstacked\"===t.key)return t.values;var r=t.values[0].r.map((function(t,e){return 0}));return t.values.forEach((function(t,e,n){t.yStack=[r],v.push(r),r=o.util.sumArrays(t.r,r)})),t.values}));p=n.merge(y)}p.forEach((function(t,e){t.t=Array.isArray(t.t[0])?t.t:[t.t],t.r=Array.isArray(t.r[0])?t.r:[t.r]}));var x=Math.min(h.width-h.margin.left-h.margin.right,h.height-h.margin.top-h.margin.bottom)/2;x=Math.max(10,x);var b,_=[h.margin.left+x,h.margin.top+x];d?b=[0,n.max(o.util.sumArrays(o.util.arrayLast(p).r[0],o.util.arrayLast(v)))]:b=n.extent(o.util.flattenArray(p.map((function(t,e){return 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P=n.range.apply(this,C);if(P=P.map((function(t,e){return parseFloat(t.toPrecision(12))})),s=n.scale.linear().domain(C.slice(0,2)).range(\"clockwise\"===h.direction?[0,360]:[360,0]),u.layout.angularAxis.domain=s.domain(),u.layout.angularAxis.endPadding=A?E:0,\"undefined\"==typeof(t=n.select(this).select(\"svg.chart-root\"))||t.empty()){var z=(new DOMParser).parseFromString(\"<svg xmlns='http://www.w3.org/2000/svg' class='chart-root'>' + '<g class='outer-group'>' + '<g class='chart-group'>' + '<circle class='background-circle'></circle>' + '<g class='geometry-group'></g>' + '<g class='radial axis-group'>' + '<circle class='outside-circle'></circle>' + '</g>' + '<g class='angular axis-group'></g>' + '<g class='guides-group'><line></line><circle r='0'></circle></g>' + '</g>' + '<g class='legend-group'></g>' + '<g class='tooltips-group'></g>' + '<g class='title-group'><text></text></g>' + '</g>' + 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o=n.hsl(a.color).l,s=o>=.5?\"#aaa\":\"white\",u=o>=.5?\"black\":\"white\",f=i||\"\";e.style({fill:u,\"font-size\":a.fontSize+\"px\"}).text(f);var h=a.padding,p=e.node().getBBox(),d={fill:a.color,stroke:s,\"stroke-width\":\"2px\"},g=p.width+2*h+l,m=p.height+2*h;return r.attr({d:\"M\"+[[l,-m/2],[l,-m/4],[a.hasTick?0:l,0],[l,m/4],[l,m/2],[g,m/2],[g,-m/2]].join(\"L\")+\"Z\"}).style(d),t.attr({transform:\"translate(\"+[l,-m/2+2*h]+\")\"}),t.style({display:\"block\"}),c},c.move=function(e){if(t)return t.attr({transform:\"translate(\"+[e[0],e[1]]+\")\"}).style({display:\"block\"}),c},c.hide=function(){if(t)return t.style({display:\"none\"}),c},c.show=function(){if(t)return t.style({display:\"block\"}),c},c.config=function(t){return i(a,t),c},c},o.tooltipPanel.uid=1,o.adapter={},o.adapter.plotly=function(){var t={convert:function(t,e){var r={};if(t.data&&(r.data=t.data.map((function(t,r){var 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s=i({},t.layout);if([[s,[\"plot_bgcolor\"],[\"backgroundColor\"]],[s,[\"showlegend\"],[\"showLegend\"]],[s,[\"radialaxis\"],[\"radialAxis\"]],[s,[\"angularaxis\"],[\"angularAxis\"]],[s.angularaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularaxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularaxis,[\"nticks\"],[\"ticksCount\"]],[s.angularaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularaxis,[\"range\"],[\"domain\"]],[s.angularaxis,[\"endpadding\"],[\"endPadding\"]],[s.radialaxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialaxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialaxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialaxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.angularAxis,[\"showticklabels\"],[\"labelsVisible\"]],[s.angularAxis,[\"nticks\"],[\"ticksCount\"]],[s.angularAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.angularAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.angularAxis,[\"range\"],[\"domain\"]],[s.angularAxis,[\"endpadding\"],[\"endPadding\"]],[s.radialAxis,[\"showline\"],[\"gridLinesVisible\"]],[s.radialAxis,[\"tickorientation\"],[\"tickOrientation\"]],[s.radialAxis,[\"ticksuffix\"],[\"ticksSuffix\"]],[s.radialAxis,[\"range\"],[\"domain\"]],[s.font,[\"outlinecolor\"],[\"outlineColor\"]],[s.legend,[\"traceorder\"],[\"reverseOrder\"]],[s,[\"labeloffset\"],[\"labelOffset\"]],[s,[\"defaultcolorrange\"],[\"defaultColorRange\"]]].forEach((function(t,r){o.util.translator.apply(null,t.concat(e))})),e?(\"undefined\"!=typeof 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n=t(\"d3\"),i=t(\"tinycolor2\"),a=t(\"../../registry\"),o=t(\"../../lib\"),s=o.strRotate,l=o.strTranslate,c=t(\"../../components/color\"),u=t(\"../../components/drawing\"),f=t(\"../plots\"),h=t(\"../../plots/cartesian/axes\"),p=t(\"../cartesian/set_convert\"),d=t(\"./set_convert\"),g=t(\"../cartesian/autorange\").doAutoRange,m=t(\"../cartesian/dragbox\"),v=t(\"../../components/dragelement\"),y=t(\"../../components/fx\"),x=t(\"../../components/titles\"),b=t(\"../cartesian/select\").prepSelect,_=t(\"../cartesian/select\").selectOnClick,w=t(\"../cartesian/select\").clearSelect,T=t(\"../../lib/setcursor\"),k=t(\"../../lib/clear_gl_canvases\"),M=t(\"../../plot_api/subroutines\").redrawReglTraces,A=t(\"../../constants/alignment\").MID_SHIFT,S=t(\"./constants\"),E=t(\"./helpers\"),C=o._,L=o.mod,I=o.deg2rad,P=o.rad2deg;function 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e,r,n,i,a=t[0],o=t[1]-a,s=L(a,360),l=s+o,c=Math.cos(I(s)),u=Math.sin(I(s)),f=Math.cos(I(l)),h=Math.sin(I(l));i=s<=90&&l>=90||s>90&&l>=450?1:u<=0&&h<=0?0:Math.max(u,h);e=s<=180&&l>=180||s>180&&l>=540?-1:c>=0&&f>=0?0:Math.min(c,f);r=s<=270&&l>=270||s>270&&l>=630?-1:u>=0&&h>=0?0:Math.min(u,h);n=l>=360?1:c<=0&&f<=0?0:Math.max(c,f);return[e,r,n,i]}(p),b=x[2]-x[0],_=x[3]-x[1],w=h/f,T=Math.abs(_/b);w>T?(d=f,y=(h-(g=f*T))/n.h/2,m=[o[0],o[1]],v=[s[0]+y,s[1]-y]):(g=h,y=(f-(d=h/T))/n.w/2,m=[o[0]+y,o[1]-y],v=[s[0],s[1]]),this.xLength2=d,this.yLength2=g,this.xDomain2=m,this.yDomain2=v;var 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e=m(t),r=Math.cos(e),n=Math.sin(e);return\"M\"+[f+u*r,p-u*n]+\"L\"+[f+a*r,p-a*n]},transFn:o.noop,crisp:!1}),h.drawLabels(n,g,{vals:w,layer:i[\"angular-axis\"],repositionOnUpdate:!0,transFn:function(t){return v(m(t))},labelFns:x})}F(i[\"angular-line\"].select(\"path\"),d.showline,{d:r.pathSubplot(),transform:l(f,p)}).attr(\"stroke-width\",d.linewidth).call(c.stroke,d.linecolor)},O.updateFx=function(t,e){this.gd._context.staticPlot||(this.updateAngularDrag(t),this.updateRadialDrag(t,e,0),this.updateRadialDrag(t,e,1),this.updateMainDrag(t))},O.updateMainDrag=function(t){var e,r,s=this,c=s.gd,u=s.layers,f=t._zoomlayer,h=S.MINZOOM,p=S.OFFEDGE,d=s.radius,g=s.innerRadius,x=s.cx,T=s.cy,k=s.cxx,M=s.cyy,A=s.sectorInRad,C=s.vangles,L=s.radialAxis,I=E.clampTiny,P=E.findXYatLength,z=E.findEnclosingVertexAngles,O=S.cornerHalfWidth,D=S.cornerLen/2,R=m.makeDragger(u,\"path\",\"maindrag\",\"crosshair\");n.select(R).attr(\"d\",s.pathSubplot()).attr(\"transform\",l(x,T));var F,B,N,j,U,V,q,H,G,Y={element:R,gd:c,subplot:s.id,plotinfo:{id:s.id,xaxis:s.xaxis,yaxis:s.yaxis},xaxes:[s.xaxis],yaxes:[s.yaxis]};function W(t,e){return Math.sqrt(t*t+e*e)}function X(t,e){return W(t-k,e-M)}function Z(t,e){return Math.atan2(M-e,t-k)}function J(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function K(t,e){if(0===t)return s.pathSector(2*O);var r=D/t,n=e-r,i=e+r,a=Math.max(0,Math.min(t,d)),o=a-O,l=a+O;return\"M\"+J(o,n)+\"A\"+[o,o]+\" 0,0,0 \"+J(o,i)+\"L\"+J(l,i)+\"A\"+[l,l]+\" 0,0,1 \"+J(l,n)+\"Z\"}function Q(t,e,r){if(0===t)return s.pathSector(2*O);var n,i,a=J(t,e),o=J(t,r),l=I((a[0]+o[0])/2),c=I((a[1]+o[1])/2);if(l&&c){var u=c/l,f=-1/u,h=P(O,u,l,c);n=P(D,f,h[0][0],h[0][1]),i=P(D,f,h[1][0],h[1][1])}else{var p,d;c?(p=D,d=O):(p=O,d=D),n=[[l-p,c-d],[l+p,c-d]],i=[[l-p,c+d],[l+p,c+d]]}return\"M\"+n.join(\"L\")+\"L\"+i.reverse().join(\"L\")+\"Z\"}function $(t,e){return 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e=L._rl,r=(e[1]-e[0])/(1-g/d)/d,n=[e[0]+(N-g)*r,e[0]+(j-g)*r];t[s.id+\".radialaxis.range\"]=n}function ot(t,e){var r=c._fullLayout.clickmode;if(m.removeZoombox(c),2===t){var n={};for(var i in s.viewInitial)n[s.id+\".\"+i]=s.viewInitial[i];c.emit(\"plotly_doubleclick\",null),a.call(\"_guiRelayout\",c,n)}r.indexOf(\"select\")>-1&&1===t&&_(e,c,[s.xaxis],[s.yaxis],s.id,Y),r.indexOf(\"event\")>-1&&y.click(c,e,s.id)}Y.prepFn=function(t,n,a){var l=c._fullLayout.dragmode,u=R.getBoundingClientRect();c._fullLayout._calcInverseTransform(c);var h=c._fullLayout._invTransform;e=c._fullLayout._invScaleX,r=c._fullLayout._invScaleY;var p=o.apply3DTransform(h)(n-u.left,a-u.top);if(F=p[0],B=p[1],C){var g=E.findPolygonOffset(d,A[0],A[1],C);F+=k+g[0],B+=M+g[1]}switch(l){case\"zoom\":Y.moveFn=C?nt:et,Y.clickFn=ot,Y.doneFn=it,function(){N=null,j=null,U=s.pathSubplot(),V=!1;var t=c._fullLayout[s.id];q=i(t.bgcolor).getLuminance(),(H=m.makeZoombox(f,q,x,T,U)).attr(\"fill-rule\",\"evenodd\"),G=m.makeCorners(f,x,T),w(c)}();break;case\"select\":case\"lasso\":b(t,n,a,Y,l)}},R.onmousemove=function(t){y.hover(c,t,s.id),c._fullLayout._lasthover=R,c._fullLayout._hoversubplot=s.id},R.onmouseout=function(t){c._dragging||v.unhover(c,t)},v.init(Y)},O.updateRadialDrag=function(t,e,r){var i=this,c=i.gd,u=i.layers,f=i.radius,h=i.innerRadius,p=i.cx,d=i.cy,g=i.radialAxis,y=S.radialDragBoxSize,x=y/2;if(g.visible){var b,_,T,A=I(i.radialAxisAngle),E=g._rl,C=E[0],L=E[1],z=E[r],O=.75*(E[1]-E[0])/(1-e.hole)/f;r?(b=p+(f+x)*Math.cos(A),_=d-(f+x)*Math.sin(A),T=\"radialdrag\"):(b=p+(h-x)*Math.cos(A),_=d-(h-x)*Math.sin(A),T=\"radialdrag-inner\");var D,B,N,j=m.makeRectDragger(u,T,\"crosshair\",-x,-x,y,y),U={element:j,gd:c};F(n.select(j),g.visible&&h<f,{transform:l(b,_)}),U.prepFn=function(){D=null,B=null,N=null,U.moveFn=V,U.doneFn=q,w(c)},U.clampFn=function(t,e){return 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v=e.gd._fullLayout,y=v[e.id],x=_(A+c*t._invScaleX,E+m*t._invScaleY),b=P(x-z);if(L=C+b,i.frontplot.attr(\"transform\",l(e.xOffset2,e.yOffset2)+s([-b,d,g])),e.vangles){I=e.radialAxisAngle+b;var w=l(h,p)+s(-b),T=l(h,p)+s(-I);i.bg.attr(\"transform\",w),i[\"radial-grid\"].attr(\"transform\",w),i[\"radial-axis\"].attr(\"transform\",T),i[\"radial-line\"].select(\"line\").attr(\"transform\",T),e.updateRadialAxisTitle(v,y,I)}else e.clipPaths.forTraces.select(\"path\").attr(\"transform\",l(d,g)+s(b));D.each((function(){var t=n.select(this),e=u.getTranslate(t);t.attr(\"transform\",l(e.x,e.y)+s([b]))})),R.each((function(){var t=n.select(this),e=t.select(\"text\"),r=u.getTranslate(t);t.attr(\"transform\",s([b,e.attr(\"x\"),e.attr(\"y\")])+l(r.x,r.y))})),f.rotation=o.modHalf(L,360),e.updateAngularAxis(v,y),e._hasClipOnAxisFalse&&!o.isFullCircle(e.sectorInRad)&&O.call(u.hideOutsideRangePoints,e);var S=!1;for(var F in e.traceHash)if(a.traceIs(F,\"gl\")){var 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x={};x[h]=[v/d,(v+1)/d],a(l,e,m,x),o.id=y,f(s,l,m,o)}}},{\"../lib\":778,\"../plot_api/plot_template\":817,\"./domain\":855}],906:[function(t,e,r){\"use strict\";['Variables are inserted using %{variable}, for example \"y: %{y}\".','Numbers are formatted using d3-format\\'s syntax %{variable:d3-format}, for example \"Price: %{y:$.2f}\".',t(\"../constants/docs\").FORMAT_LINK,\"for details on the formatting syntax.\",'Dates are formatted using d3-time-format\\'s syntax %{variable|d3-time-format}, for example \"Day: %{2019-01-01|%A}\".',t(\"../constants/docs\").DATE_FORMAT_LINK,\"for details on the date formatting syntax.\"].join(\" \");function n(t){var e=t.description?\" \"+t.description:\"\",r=t.keys||[];if(r.length>0){for(var n=[],i=0;i<r.length;i++)n[i]=\"`\"+r[i]+\"`\";e+=\"Finally, the template string has access to \",e=1===r.length?\"variable \"+n[0]:\"variables \"+n.slice(0,-1).join(\", \")+\" and \"+n.slice(-1)+\".\"}return e}r.hovertemplateAttrs=function(t,e){t=t||{};n(e=e||{});var r={valType:\"string\",dflt:\"\",editType:t.editType||\"none\"};return!1!==t.arrayOk&&(r.arrayOk=!0),r},r.texttemplateAttrs=function(t,e){t=t||{};n(e=e||{});var r={valType:\"string\",dflt:\"\",editType:t.editType||\"calc\"};return!1!==t.arrayOk&&(r.arrayOk=!0),r}},{\"../constants/docs\":748}],907:[function(t,e,r){\"use strict\";var n=t(\"./ternary\"),i=t(\"../../plots/get_data\").getSubplotCalcData,a=t(\"../../lib\").counterRegex;r.name=\"ternary\";var o=r.attr=\"subplot\";r.idRoot=\"ternary\",r.idRegex=r.attrRegex=a(\"ternary\"),(r.attributes={})[o]={valType:\"subplotid\",dflt:\"ternary\",editType:\"calc\"},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t.calcdata,a=e._subplots.ternary,o=0;o<a.length;o++){var s=a[o],l=i(r,\"ternary\",s),c=e[s]._subplot;c||(c=new 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n=t(\"../../components/color/attributes\"),i=t(\"../domain\").attributes,a=t(\"../cartesian/layout_attributes\"),o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../lib/extend\").extendFlat,l={title:{text:a.title.text,font:a.title.font},color:a.color,tickmode:a.tickmode,nticks:s({},a.nticks,{dflt:6,min:1}),tick0:a.tick0,dtick:a.dtick,tickvals:a.tickvals,ticktext:a.ticktext,ticks:a.ticks,ticklen:a.ticklen,tickwidth:a.tickwidth,tickcolor:a.tickcolor,showticklabels:a.showticklabels,showtickprefix:a.showtickprefix,tickprefix:a.tickprefix,showticksuffix:a.showticksuffix,ticksuffix:a.ticksuffix,showexponent:a.showexponent,exponentformat:a.exponentformat,minexponent:a.minexponent,separatethousands:a.separatethousands,tickfont:a.tickfont,tickangle:a.tickangle,tickformat:a.tickformat,tickformatstops:a.tickformatstops,hoverformat:a.hoverformat,showline:s({},a.showline,{dflt:!0}),linecolor:a.linecolor,linewidth:a.linewidth,showgrid:s({},a.showgrid,{dflt:!0}),gridcolor:a.gridcolor,gridwidth:a.gridwidth,layer:a.layer,min:{valType:\"number\",dflt:0,min:0},_deprecated:{title:a._deprecated.title,titlefont:a._deprecated.titlefont}},c=e.exports=o({domain:i({name:\"ternary\"}),bgcolor:{valType:\"color\",dflt:n.background},sum:{valType:\"number\",dflt:1,min:0},aaxis:l,baxis:l,caxis:l},\"plot\",\"from-root\");c.uirevision={valType:\"any\",editType:\"none\"},c.aaxis.uirevision=c.baxis.uirevision=c.caxis.uirevision={valType:\"any\",editType:\"none\"}},{\"../../components/color/attributes\":642,\"../../lib/extend\":768,\"../../plot_api/edit_types\":810,\"../cartesian/layout_attributes\":842,\"../domain\":855}],909:[function(t,e,r){\"use 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n=t(\"d3\"),i=t(\"tinycolor2\"),a=t(\"../../registry\"),o=t(\"../../lib\"),s=o.strTranslate,l=o._,c=t(\"../../components/color\"),u=t(\"../../components/drawing\"),f=t(\"../cartesian/set_convert\"),h=t(\"../../lib/extend\").extendFlat,p=t(\"../plots\"),d=t(\"../cartesian/axes\"),g=t(\"../../components/dragelement\"),m=t(\"../../components/fx\"),v=t(\"../../components/dragelement/helpers\"),y=v.freeMode,x=v.rectMode,b=t(\"../../components/titles\"),_=t(\"../cartesian/select\").prepSelect,w=t(\"../cartesian/select\").selectOnClick,T=t(\"../cartesian/select\").clearSelect,k=t(\"../cartesian/select\").clearSelectionsCache,M=t(\"../cartesian/constants\");function A(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework(e),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}e.exports=A;var S=A.prototype;S.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={},this.layers={}},S.plot=function(t,e){var r=e[this.id],n=e._size;this._hasClipOnAxisFalse=!1;for(var i=0;i<t.length;i++){if(!1===t[i][0].trace.cliponaxis){this._hasClipOnAxisFalse=!0;break}}this.updateLayers(r),this.adjustLayout(r,n),p.generalUpdatePerTraceModule(this.graphDiv,this,t,r),this.layers.plotbg.select(\"path\").call(c.fill,r.bgcolor)},S.makeFramework=function(t){var e=this.graphDiv,r=t[this.id],n=this.clipId=\"clip\"+this.layoutId+this.id,i=this.clipIdRelative=\"clip-relative\"+this.layoutId+this.id;this.clipDef=o.ensureSingleById(t._clips,\"clipPath\",n,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.clipDefRelative=o.ensureSingleById(t._clips,\"clipPath\",i,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.plotContainer=o.ensureSingle(this.container,\"g\",this.id),this.updateLayers(r),u.setClipUrl(this.layers.backplot,n,e),u.setClipUrl(this.layers.grids,n,e)},S.updateLayers=function(t){var e=this.layers,r=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\"];\"below 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E=Math.sqrt(4/3);S.adjustLayout=function(t,e){var r,n,i,a,o,l,p=this,d=t.domain,g=(d.x[0]+d.x[1])/2,m=(d.y[0]+d.y[1])/2,v=d.x[1]-d.x[0],y=d.y[1]-d.y[0],x=v*e.w,b=y*e.h,_=t.sum,w=t.aaxis.min,T=t.baxis.min,k=t.caxis.min;x>E*b?i=(a=b)*E:a=(i=x)/E,o=v*i/x,l=y*a/b,r=e.l+e.w*g-i/2,n=e.t+e.h*(1-m)-a/2,p.x0=r,p.y0=n,p.w=i,p.h=a,p.sum=_,p.xaxis={type:\"linear\",range:[w+2*k-_,_-w-2*T],domain:[g-o/2,g+o/2],_id:\"x\"},f(p.xaxis,p.graphDiv._fullLayout),p.xaxis.setScale(),p.xaxis.isPtWithinRange=function(t){return t.a>=p.aaxis.range[0]&&t.a<=p.aaxis.range[1]&&t.b>=p.baxis.range[1]&&t.b<=p.baxis.range[0]&&t.c>=p.caxis.range[1]&&t.c<=p.caxis.range[0]},p.yaxis={type:\"linear\",range:[w,_-T-k],domain:[m-l/2,m+l/2],_id:\"y\"},f(p.yaxis,p.graphDiv._fullLayout),p.yaxis.setScale(),p.yaxis.isPtWithinRange=function(){return!0};var M=p.yaxis.domain[0],A=p.aaxis=h({},t.aaxis,{range:[w,_-T-k],side:\"left\",tickangle:(+t.aaxis.tickangle||0)-30,domain:[M,M+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(A,p.graphDiv._fullLayout),A.setScale();var S=p.baxis=h({},t.baxis,{range:[_-w-k,T],side:\"bottom\",domain:p.xaxis.domain,anchor:\"free\",position:0,_id:\"x\",_length:i});f(S,p.graphDiv._fullLayout),S.setScale();var C=p.caxis=h({},t.caxis,{range:[_-w-T,k],side:\"right\",tickangle:(+t.caxis.tickangle||0)+30,domain:[M,M+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(C,p.graphDiv._fullLayout),C.setScale();var L=\"M\"+r+\",\"+(n+a)+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDef.select(\"path\").attr(\"d\",L),p.layers.plotbg.select(\"path\").attr(\"d\",L);var I=\"M0,\"+a+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDefRelative.select(\"path\").attr(\"d\",I);var P=s(r,n);p.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",P),p.clipDefRelative.select(\"path\").attr(\"transform\",null);var z=s(r-S._offset,n+a);p.layers.baxis.attr(\"transform\",z),p.layers.bgrid.attr(\"transform\",z);var O=s(r+i/2,n)+\"rotate(30)\"+s(0,-A._offset);p.layers.aaxis.attr(\"transform\",O),p.layers.agrid.attr(\"transform\",O);var D=s(r+i/2,n)+\"rotate(-30)\"+s(0,-C._offset);p.layers.caxis.attr(\"transform\",D),p.layers.cgrid.attr(\"transform\",D),p.drawAxes(!0),p.layers.aline.select(\"path\").attr(\"d\",A.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(c.stroke,A.linecolor||\"#000\").style(\"stroke-width\",(A.linewidth||0)+\"px\"),p.layers.bline.select(\"path\").attr(\"d\",S.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(c.stroke,S.linecolor||\"#000\").style(\"stroke-width\",(S.linewidth||0)+\"px\"),p.layers.cline.select(\"path\").attr(\"d\",C.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(c.stroke,C.linecolor||\"#000\").style(\"stroke-width\",(C.linewidth||0)+\"px\"),p.graphDiv._context.staticPlot||p.initInteractions(),u.setClipUrl(p.layers.frontplot,p._hasClipOnAxisFalse?null:p.clipId,p.graphDiv)},S.drawAxes=function(t){var 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n=t(\"../pie/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/domain\").attributes,o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/template_attributes\").texttemplateAttrs,l=t(\"../../lib/extend\").extendFlat;e.exports={labels:n.labels,label0:n.label0,dlabel:n.dlabel,values:n.values,marker:{colors:n.marker.colors,line:{color:l({},n.marker.line.color,{dflt:null}),width:l({},n.marker.line.width,{dflt:1}),editType:\"calc\"},editType:\"calc\"},text:n.text,hovertext:n.hovertext,scalegroup:l({},n.scalegroup,{}),textinfo:l({},n.textinfo,{flags:[\"label\",\"text\",\"value\",\"percent\"]}),texttemplate:s({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),hoverinfo:l({},i.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:o({},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),textposition:l({},n.textposition,{values:[\"inside\",\"none\"],dflt:\"inside\"}),textfont:n.textfont,insidetextfont:n.insidetextfont,title:{text:n.title.text,font:n.title.font,position:l({},n.title.position,{values:[\"top 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n=t(\"../../lib\"),i=t(\"./attributes\"),a=t(\"../../plots/domain\").defaults,o=t(\"../bar/defaults\").handleText,s=t(\"../pie/defaults\").handleLabelsAndValues;e.exports=function(t,e,r,l){function c(r,a){return n.coerce(t,e,i,r,a)}var u=c(\"labels\"),f=c(\"values\"),h=s(u,f),p=h.len;if(e._hasLabels=h.hasLabels,e._hasValues=h.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),p){e._length=p,c(\"marker.line.width\")&&c(\"marker.line.color\",l.paper_bgcolor),c(\"marker.colors\"),c(\"scalegroup\");var d,g=c(\"text\"),m=c(\"texttemplate\");if(m||(d=c(\"textinfo\",Array.isArray(g)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),m||d&&\"none\"!==d){var v=c(\"textposition\");o(t,e,l,c,v,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1})}a(e,l,c),c(\"title.text\")&&(c(\"title.position\"),n.coerceFont(c,\"title.font\",l.font)),c(\"aspectratio\"),c(\"baseratio\")}else 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n=t(\"../pie/layout_attributes\").hiddenlabels;e.exports={hiddenlabels:n,funnelareacolorway:{valType:\"colorlist\",editType:\"calc\"},extendfunnelareacolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{\"../pie/layout_attributes\":1168}],1062:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"funnelareacolorway\",e.colorway),r(\"extendfunnelareacolors\")}},{\"../../lib\":778,\"./layout_attributes\":1061}],1063:[function(t,e,r){\"use strict\";var 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0===d._deltaLastValue&&(d._deltaLastValue=a(r[0]));var l=C.select(\"text.delta\");function p(){l.text(o(a(r[0]),i)).call(m.fill,s(r[0])).call(f.convertToTspans,t)}return l.call(c.font,d.delta.font).call(m.fill,s({delta:d._deltaLastValue})),b(S)?l.transition().duration(S.duration).ease(S.easing).tween(\"text\",(function(){var t=n.select(this),e=a(r[0]),l=d._deltaLastValue,c=P(d.delta.valueformat,i,l,e),u=n.interpolateNumber(l,e);return d._deltaLastValue=e,function(e){t.text(o(u(e),c)),t.call(m.fill,s({delta:u(e)}))}})).each(\"end\",(function(){p(),E&&E()})).each(\"interrupt\",(function(){p(),E&&E()})):p(),u=k(o(a(r[0]),i),d.delta.font,A,t),l}(),O+=d.delta.position+d.delta.font.size+d.delta.font.family+d.delta.valueformat,O+=d.delta.increasing.symbol+d.delta.decreasing.symbol,p=u);d._hasNumber&&(!function(){var e=w(t,{tickformat:d.number.valueformat},d._range);e.setScale(),h.prepTicks(e);var i=function(t){return h.tickText(e,t).text},a=d.number.suffix,o=d.number.prefix,s=C.select(\"text.number\");function u(){var e=\"number\"==typeof r[0].y?o+i(r[0].y)+a:\"-\";s.text(e).call(c.font,d.number.font).call(f.convertToTspans,t)}b(S)?s.transition().duration(S.duration).ease(S.easing).each(\"end\",(function(){u(),E&&E()})).each(\"interrupt\",(function(){u(),E&&E()})).attrTween(\"text\",(function(){var t=n.select(this),e=n.interpolateNumber(r[0].lastY,r[0].y);d._lastValue=r[0].y;var s=P(d.number.valueformat,i,r[0].lastY,r[0].y);return function(r){t.text(o+s(e(r))+a)}})):u(),l=k(o+i(r[0].y)+a,d.number.font,A,t)}(),O+=d.number.font.size+d.number.font.family+d.number.valueformat+d.number.suffix+d.number.prefix,p=l);if(d._hasDelta&&d._hasNumber){var D,R,F=[(l.left+l.right)/2,(l.top+l.bottom)/2],B=[(u.left+u.right)/2,(u.top+u.bottom)/2],N=.75*d.delta.font.size;\"left\"===d.delta.position&&(D=M(d,\"deltaPos\",0,-1*(l.width*y[d.align]+u.width*(1-y[d.align])+N),O,Math.min),R=F[1]-B[1],p={width:l.width+u.width+N,height:Math.max(l.height,u.height),left:u.left+D,right:l.right,top:Math.min(l.top,u.top+R),bottom:Math.max(l.bottom,u.bottom+R)}),\"right\"===d.delta.position&&(D=M(d,\"deltaPos\",0,l.width*(1-y[d.align])+u.width*y[d.align]+N,O,Math.max),R=F[1]-B[1],p={width:l.width+u.width+N,height:Math.max(l.height,u.height),left:l.left,right:u.right+D,top:Math.min(l.top,u.top+R),bottom:Math.max(l.bottom,u.bottom+R)}),\"bottom\"===d.delta.position&&(D=null,R=u.height,p={width:Math.max(l.width,u.width),height:l.height+u.height,left:Math.min(l.left,u.left),right:Math.max(l.right,u.right),top:l.bottom-l.height,bottom:l.bottom+u.height}),\"top\"===d.delta.position&&(D=null,R=l.top,p={width:Math.max(l.width,u.width),height:l.height+u.height,left:Math.min(l.left,u.left),right:Math.max(l.right,u.right),top:l.bottom-l.height-u.height,bottom:l.bottom}),z.attr({dx:D,dy:R})}(d._hasNumber||d._hasDelta)&&C.attr(\"transform\",(function(){var t=s.numbersScaler(p);O+=t[2];var e,r=M(d,\"numbersScale\",1,t[0],O,Math.min);d._scaleNumbers||(r=1),e=d._isAngular?_-r*p.bottom:_-r*(p.top+p.bottom)/2,d._numbersTop=r*p.top+e;var n=p[T];\"center\"===T&&(n=(p.left+p.right)/2);var i=g-r*n;return i=M(d,\"numbersTranslate\",0,i,O,Math.max),o(i,e)+a(r)}))}(t,I,e,{numbersX:p,numbersY:A,numbersScaler:S,transitionOpts:r,onComplete:d}),P&&(E={range:L.gauge.axis.range,color:L.gauge.bgcolor,line:{color:L.gauge.bordercolor,width:0},thickness:1},C={range:L.gauge.axis.range,color:\"rgba(0, 0, 0, 0)\",line:{color:L.gauge.bordercolor,width:L.gauge.borderwidth},thickness:1});var H=I.selectAll(\"g.angular\").data(z?e:[]);H.exit().remove();var G=I.selectAll(\"g.angularaxis\").data(z?e:[]);G.exit().remove(),z&&function(t,e,r,i){var a,c,u,f,p=r[0].trace,d=i.size,g=i.radius,m=i.innerRadius,v=i.gaugeBg,y=i.gaugeOutline,x=[d.l+d.w/2,d.t+d.h/2+g/2],T=i.gauge,k=i.layer,M=i.transitionOpts,A=i.onComplete,S=Math.PI/2;function E(t){var e=p.gauge.axis.range[0],r=(t-e)/(p.gauge.axis.range[1]-e)*Math.PI-S;return r<-S?-S:r>S?S:r}function C(t){return n.svg.arc().innerRadius((m+g)/2-t/2*(g-m)).outerRadius((m+g)/2+t/2*(g-m)).startAngle(-S)}function L(t){t.attr(\"d\",(function(t){return C(t.thickness).startAngle(E(t.range[0])).endAngle(E(t.range[1]))()}))}T.enter().append(\"g\").classed(\"angular\",!0),T.attr(\"transform\",o(x[0],x[1])),k.enter().append(\"g\").classed(\"angularaxis\",!0).classed(\"crisp\",!0),k.selectAll(\"g.xangularaxistick,path,text\").remove(),(a=w(t,p.gauge.axis)).type=\"linear\",a.range=p.gauge.axis.range,a._id=\"xangularaxis\",a.setScale();var I=function(t){return(a.range[0]-t.x)/(a.range[1]-a.range[0])*Math.PI+Math.PI},P={},z=h.makeLabelFns(a,0).labelStandoff;P.xFn=function(t){var e=I(t);return Math.cos(e)*z},P.yFn=function(t){var e=I(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(z+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*l)},P.anchorFn=function(t){var e=I(t),r=Math.cos(e);return Math.abs(r)<.1?\"middle\":r>0?\"start\":\"end\"},P.heightFn=function(t,e,r){var n=I(t);return-.5*(1+Math.sin(n))*r};var O=function(t){return o(x[0]+g*Math.cos(t),x[1]-g*Math.sin(t))};u=function(t){return O(I(t))};if(c=h.calcTicks(a),f=h.getTickSigns(a)[2],a.visible){f=\"inside\"===a.ticks?-1:1;var D=(a.linewidth||1)/2;h.drawTicks(t,a,{vals:c,layer:k,path:\"M\"+f*D+\",0h\"+f*a.ticklen,transFn:function(t){var e=I(t);return O(e)+\"rotate(\"+-s(e)+\")\"}}),h.drawLabels(t,a,{vals:c,layer:k,transFn:u,labelFns:P})}var R=[v].concat(p.gauge.steps),F=T.selectAll(\"g.bg-arc\").data(R);F.enter().append(\"g\").classed(\"bg-arc\",!0).append(\"path\"),F.select(\"path\").call(L).call(_),F.exit().remove();var B=C(p.gauge.bar.thickness),N=T.selectAll(\"g.value-arc\").data([p.gauge.bar]);N.enter().append(\"g\").classed(\"value-arc\",!0).append(\"path\");var j=N.select(\"path\");b(M)?(j.transition().duration(M.duration).ease(M.easing).each(\"end\",(function(){A&&A()})).each(\"interrupt\",(function(){A&&A()})).attrTween(\"d\",(U=B,V=E(r[0].lastY),q=E(r[0].y),function(){var t=n.interpolate(V,q);return function(e){return U.endAngle(t(e))()}})),p._lastValue=r[0].y):j.attr(\"d\",\"number\"==typeof r[0].y?B.endAngle(E(r[0].y)):\"M0,0Z\");var U,V,q;j.call(_),N.exit().remove(),R=[];var H=p.gauge.threshold.value;H&&R.push({range:[H,H],color:p.gauge.threshold.color,line:{color:p.gauge.threshold.line.color,width:p.gauge.threshold.line.width},thickness:p.gauge.threshold.thickness});var G=T.selectAll(\"g.threshold-arc\").data(R);G.enter().append(\"g\").classed(\"threshold-arc\",!0).append(\"path\"),G.select(\"path\").call(L).call(_),G.exit().remove();var Y=T.selectAll(\"g.gauge-outline\").data([y]);Y.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),Y.select(\"path\").call(L).call(_),Y.exit().remove()}(t,0,e,{radius:N,innerRadius:j,gauge:H,layer:G,size:R,gaugeBg:E,gaugeOutline:C,transitionOpts:r,onComplete:d});var Y=I.selectAll(\"g.bullet\").data(O?e:[]);Y.exit().remove();var W=I.selectAll(\"g.bulletaxis\").data(O?e:[]);W.exit().remove(),O&&function(t,e,r,n){var i,a,s,l,c,f=r[0].trace,p=n.gauge,d=n.layer,g=n.gaugeBg,v=n.gaugeOutline,y=n.size,x=f.domain,T=n.transitionOpts,k=n.onComplete;p.enter().append(\"g\").classed(\"bullet\",!0),p.attr(\"transform\",o(y.l,y.t)),d.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),d.selectAll(\"g.xbulletaxistick,path,text\").remove();var M=y.h,A=f.gauge.bar.thickness*M,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(f._hasNumber||f._hasDelta?1-u.bulletNumberDomainSize:1);(i=w(t,f.gauge.axis))._id=\"xbulletaxis\",i.domain=[S,E],i.setScale(),a=h.calcTicks(i),s=h.makeTransTickFn(i),l=h.getTickSigns(i)[2],c=y.t+y.h,i.visible&&(h.drawTicks(t,i,{vals:\"inside\"===i.ticks?h.clipEnds(i,a):a,layer:d,path:h.makeTickPath(i,c,l),transFn:s}),h.drawLabels(t,i,{vals:a,layer:d,transFn:s,labelFns:h.makeLabelFns(i,c)}));function C(t){t.attr(\"width\",(function(t){return Math.max(0,i.c2p(t.range[1])-i.c2p(t.range[0]))})).attr(\"x\",(function(t){return i.c2p(t.range[0])})).attr(\"y\",(function(t){return.5*(1-t.thickness)*M})).attr(\"height\",(function(t){return t.thickness*M}))}var L=[g].concat(f.gauge.steps),I=p.selectAll(\"g.bg-bullet\").data(L);I.enter().append(\"g\").classed(\"bg-bullet\",!0).append(\"rect\"),I.select(\"rect\").call(C).call(_),I.exit().remove();var P=p.selectAll(\"g.value-bullet\").data([f.gauge.bar]);P.enter().append(\"g\").classed(\"value-bullet\",!0).append(\"rect\"),P.select(\"rect\").attr(\"height\",A).attr(\"y\",(M-A)/2).call(_),b(T)?P.select(\"rect\").transition().duration(T.duration).ease(T.easing).each(\"end\",(function(){k&&k()})).each(\"interrupt\",(function(){k&&k()})).attr(\"width\",Math.max(0,i.c2p(Math.min(f.gauge.axis.range[1],r[0].y)))):P.select(\"rect\").attr(\"width\",\"number\"==typeof r[0].y?Math.max(0,i.c2p(Math.min(f.gauge.axis.range[1],r[0].y))):0);P.exit().remove();var z=r.filter((function(){return f.gauge.threshold.value})),O=p.selectAll(\"g.threshold-bullet\").data(z);O.enter().append(\"g\").classed(\"threshold-bullet\",!0).append(\"line\"),O.select(\"line\").attr(\"x1\",i.c2p(f.gauge.threshold.value)).attr(\"x2\",i.c2p(f.gauge.threshold.value)).attr(\"y1\",(1-f.gauge.threshold.thickness)/2*M).attr(\"y2\",(1-(1-f.gauge.threshold.thickness)/2)*M).call(m.stroke,f.gauge.threshold.line.color).style(\"stroke-width\",f.gauge.threshold.line.width),O.exit().remove();var D=p.selectAll(\"g.gauge-outline\").data([v]);D.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"rect\"),D.select(\"rect\").call(C).call(_),D.exit().remove()}(t,0,e,{gauge:Y,layer:W,size:R,gaugeBg:E,gaugeOutline:C,transitionOpts:r,onComplete:d});var X=I.selectAll(\"text.title\").data(e);X.exit().remove(),X.enter().append(\"text\").classed(\"title\",!0),X.attr(\"text-anchor\",(function(){return O?v.right:v[L.title.align]})).text(L.title.text).call(c.font,L.title.font).call(f.convertToTspans,t),X.attr(\"transform\",(function(){var t,e=R.l+R.w*y[L.title.align],r=u.titlePadding,n=c.bBox(X.node());if(P){if(z)if(L.gauge.axis.visible)t=c.bBox(G.node()).top-r-n.bottom;else t=R.t+R.h/2-N/2-n.bottom-r;O&&(t=A-(n.top+n.bottom)/2,e=R.l-u.bulletPadding*R.w)}else t=L._numbersTop-r-n.bottom;return o(e,t)}))}))}},{\"../../components/color\":643,\"../../components/drawing\":665,\"../../constants/alignment\":745,\"../../lib\":778,\"../../lib/svg_text_utils\":803,\"../../plots/cartesian/axes\":828,\"../../plots/cartesian/axis_defaults\":830,\"../../plots/cartesian/layout_attributes\":842,\"../../plots/cartesian/position_defaults\":845,\"./constants\":1119,d3:169}],1123:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/template_attributes\").hovertemplateAttrs,a=t(\"../mesh3d/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/edit_types\").overrideAll;var c=e.exports=l(s({x:{valType:\"data_array\"},y:{valType:\"data_array\"},z:{valType:\"data_array\"},value:{valType:\"data_array\"},isomin:{valType:\"number\"},isomax:{valType:\"number\"},surface:{show:{valType:\"boolean\",dflt:!0},count:{valType:\"integer\",dflt:2,min:1},fill:{valType:\"number\",min:0,max:1,dflt:1},pattern:{valType:\"flaglist\",flags:[\"A\",\"B\",\"C\",\"D\",\"E\"],extras:[\"all\",\"odd\",\"even\"],dflt:\"all\"}},spaceframe:{show:{valType:\"boolean\",dflt:!1},fill:{valType:\"number\",min:0,max:1,dflt:.15}},slices:{x:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}},y:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}},z:{show:{valType:\"boolean\",dflt:!1},locations:{valType:\"data_array\",dflt:[]},fill:{valType:\"number\",min:0,max:1,dflt:1}}},caps:{x:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}},y:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}},z:{show:{valType:\"boolean\",dflt:!0},fill:{valType:\"number\",min:0,max:1,dflt:1}}},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:i(),showlegend:s({},o.showlegend,{dflt:!1})},n(\"\",{colorAttr:\"`value`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{opacity:a.opacity,lightposition:a.lightposition,lighting:a.lighting,flatshading:a.flatshading,contour:a.contour,hoverinfo:s({},o.hoverinfo)}),\"calc\",\"nested\");c.flatshading.dflt=!0,c.lighting.facenormalsepsilon.dflt=0,c.x.editType=c.y.editType=c.z.editType=c.value.editType=\"calc+clearAxisTypes\",c.transforms=void 0},{\"../../components/colorscale/attributes\":650,\"../../lib/extend\":768,\"../../plot_api/edit_types\":810,\"../../plots/attributes\":824,\"../../plots/template_attributes\":906,\"../mesh3d/attributes\":1128}],1124:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\"),i=t(\"../streamtube/calc\").processGrid,a=t(\"../streamtube/calc\").filter;e.exports=function(t,e){e._len=Math.min(e.x.length,e.y.length,e.z.length,e.value.length),e._x=a(e.x,e._len),e._y=a(e.y,e._len),e._z=a(e.z,e._len),e._value=a(e.value,e._len);var r=i(e);e._gridFill=r.fill,e._Xs=r.Xs,e._Ys=r.Ys,e._Zs=r.Zs,e._len=r.len;for(var o=1/0,s=-1/0,l=0;l<e._len;l++){var c=e._value[l];o=Math.min(o,c),s=Math.max(s,c)}e._minValues=o,e._maxValues=s,e._vMin=void 0===e.isomin||null===e.isomin?o:e.isomin,e._vMax=void 0===e.isomax||null===e.isomin?s:e.isomax,n(t,e,{vals:[e._vMin,e._vMax],containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":651,\"../streamtube/calc\":1295}],1125:[function(t,e,r){\"use strict\";var n=t(\"gl-mesh3d\"),i=t(\"../../lib/gl_format_color\").parseColorScale,a=t(\"../../lib/str2rgbarray\"),o=t(\"../../components/colorscale\").extractOpts,s=t(\"../../plots/gl3d/zip3\"),l=function(t,e){for(var r=e.length-1;r>0;r--){var n=Math.min(e[r],e[r-1]),i=Math.max(e[r],e[r-1]);if(i>n&&n<t&&t<=i)return{id:r,distRatio:(i-t)/(i-n)}}return{id:0,distRatio:0}};function c(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.data=null,this.showContour=!1}var u=c.prototype;u.handlePick=function(t){if(t.object===this.mesh){var e=t.data.index,r=this.data._meshX[e],n=this.data._meshY[e],i=this.data._meshZ[e],a=this.data._Ys.length,o=this.data._Zs.length,s=l(r,this.data._Xs).id,c=l(n,this.data._Ys).id,u=l(i,this.data._Zs).id,f=t.index=u+o*c+o*a*s;t.traceCoordinate=[this.data._meshX[f],this.data._meshY[f],this.data._meshZ[f],this.data._value[f]];var h=this.data.hovertext||this.data.text;return Array.isArray(h)&&void 0!==h[f]?t.textLabel=h[f]:h&&(t.textLabel=h),!0}},u.update=function(t){var e=this.scene,r=e.fullSceneLayout;function n(t,e,r,n){return e.map((function(e){return t.d2l(e,0,n)*r}))}this.data=h(t);var 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0),\"category descending\"===t.categoryorder&&(e=e.reverse())}return function(t,e){e=null==e?[]:e.map((function(t){return t}));var r={},n={},i=[];e.forEach((function(t,e){r[t]=0,n[t]=e}));for(var a=0;a<t.length;a++){var o,s=t[a];void 0===r[s]?(r[s]=1,o=e.push(s)-1,n[s]=o):(r[s]++,o=n[s]),i.push(o)}var l=e.map((function(t){return r[t]}));return{uniqueValues:e,uniqueCounts:l,inds:i}}(t.values,e)}));p=l.isArrayOrTypedArray(e.counts)?e.counts:[e.counts],function(t){var e;if(function(t){for(var e=new Array(t.length),r=0;r<t.length;r++){if(t[r]<0||t[r]>=t.length)return!1;if(void 0!==e[t[r]])return!1;e[t[r]]=!0}return!0}(t.map((function(t){return t.displayindex}))))for(e=0;e<t.length;e++)t[e]._displayindex=t[e].displayindex;else for(e=0;e<t.length;e++)t[e]._displayindex=e}(r),r.forEach((function(t,e){!function(t,e){t._categoryarray=e.uniqueValues,null===t.ticktext||void 0===t.ticktext?t._ticktext=[]:t._ticktext=t.ticktext.slice();for(var r=t._ticktext.length;r<e.uniqueValues.length;r++)t._ticktext.push(e.uniqueValues[r])}(t,m[e])}));var v,y=e.line;y?(i(e,\"line\")&&a(t,e,{vals:e.line.color,containerStr:\"line\",cLetter:\"c\"}),v=s.tryColorscale(y)):v=l.identity;var x,b,_,w,T,k=r[0].values.length,M={},A=m.map((function(t){return t.inds}));for(g=0,x=0;x<k;x++){var S=[];for(b=0;b<A.length;b++)S.push(A[b][x]);d=p[x%p.length],g+=d;var E=(_=x,w=void 0,T=void 0,l.isArrayOrTypedArray(y.color)?T=w=y.color[_%y.color.length]:w=y.color,{color:v(w),rawColor:T}),C=S+\"-\"+E.rawColor;void 0===M[C]&&(M[C]=f(S,E.color,E.rawColor)),h(M[C],x,d)}var L,I=r.map((function(t,e){return function(t,e,r,n,i){return{dimensionInd:t,containerInd:e,displayInd:r,dimensionLabel:n,count:i,categories:[],dragX:null}}(e,t._index,t._displayindex,t.label,g)}));for(x=0;x<k;x++)for(d=p[x%p.length],b=0;b<I.length;b++){var P=I[b].containerInd,z=m[b].inds[x],O=I[b].categories;if(void 0===O[z]){var D=e.dimensions[P]._categoryarray[z],R=e.dimensions[P]._ticktext[z];O[z]={dimensionInd:b,categoryInd:L=z,categoryValue:D,displayInd:L,categoryLabel:R,valueInds:[],count:0,dragY:null}}u(O[z],x,d)}return n(function(t,e,r){var n=t.map((function(t){return t.categories.length})).reduce((function(t,e){return Math.max(t,e)}));return{dimensions:t,paths:e,trace:void 0,maxCats:n,count:r}}(I,M,g))}},{\"../../components/colorscale/calc\":651,\"../../components/colorscale/helpers\":654,\"../../components/drawing\":665,\"../../lib\":778,\"../../lib/filter_unique.js\":769,\"../../lib/gup\":775,\"fast-isnumeric\":241}],1145:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/colorscale/helpers\").hasColorscale,a=t(\"../../components/colorscale/defaults\"),o=t(\"../../plots/domain\").defaults,s=t(\"../../plots/array_container_defaults\"),l=t(\"./attributes\"),c=t(\"../parcoords/merge_length\");function u(t,e){function r(r,i){return n.coerce(t,e,l.dimensions,r,i)}var i=r(\"values\"),a=r(\"visible\");if(i&&i.length||(a=e.visible=!1),a){r(\"label\"),r(\"displayindex\",e._index);var o,s=t.categoryarray,c=Array.isArray(s)&&s.length>0;c&&(o=\"array\");var u=r(\"categoryorder\",o);\"array\"===u?(r(\"categoryarray\"),r(\"ticktext\")):(delete t.categoryarray,delete t.ticktext),c||\"array\"!==u||(e.categoryorder=\"trace\")}}e.exports=function(t,e,r,f){function h(r,i){return n.coerce(t,e,l,r,i)}var p=s(t,e,{name:\"dimensions\",handleItemDefaults:u}),d=function(t,e,r,o,s){s(\"line.shape\"),s(\"line.hovertemplate\");var l=s(\"line.color\",o.colorway[0]);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,f,h);o(e,f,h),Array.isArray(p)&&p.length||(e.visible=!1),c(e,p,\"values\",d),h(\"hoveron\"),h(\"hovertemplate\"),h(\"arrangement\"),h(\"bundlecolors\"),h(\"sortpaths\"),h(\"counts\");var g={family:f.font.family,size:Math.round(f.font.size),color:f.font.color};n.coerceFont(h,\"labelfont\",g);var m={family:f.font.family,size:Math.round(f.font.size/1.2),color:f.font.color};n.coerceFont(h,\"tickfont\",m)}},{\"../../components/colorscale/defaults\":653,\"../../components/colorscale/helpers\":654,\"../../lib\":778,\"../../plots/array_container_defaults\":823,\"../../plots/domain\":855,\"../parcoords/merge_length\":1158,\"./attributes\":1142}],1146:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcats\",basePlotModule:t(\"./base_plot\"),categories:[\"noOpacity\"],meta:{}}},{\"./attributes\":1142,\"./base_plot\":1143,\"./calc\":1144,\"./defaults\":1145,\"./plot\":1148}],1147:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../plot_api/plot_api\"),a=t(\"../../components/fx\"),o=t(\"../../lib\"),s=o.strTranslate,l=t(\"../../components/drawing\"),c=t(\"tinycolor2\"),u=t(\"../../lib/svg_text_utils\");function f(t,e,r,i){var a=t.map(R.bind(0,e,r)),c=i.selectAll(\"g.parcatslayer\").data([null]);c.enter().append(\"g\").attr(\"class\",\"parcatslayer\").style(\"pointer-events\",\"all\");var f=c.selectAll(\"g.trace.parcats\").data(a,h),v=f.enter().append(\"g\").attr(\"class\",\"trace parcats\");f.attr(\"transform\",(function(t){return s(t.x,t.y)})),v.append(\"g\").attr(\"class\",\"paths\");var y=f.select(\"g.paths\").selectAll(\"path.path\").data((function(t){return t.paths}),h);y.attr(\"fill\",(function(t){return t.model.color}));var _=y.enter().append(\"path\").attr(\"class\",\"path\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",0);b(_),y.attr(\"d\",(function(t){return t.svgD})),_.empty()||y.sort(d),y.exit().remove(),y.on(\"mouseover\",g).on(\"mouseout\",m).on(\"click\",x),v.append(\"g\").attr(\"class\",\"dimensions\");var k=f.select(\"g.dimensions\").selectAll(\"g.dimension\").data((function(t){return t.dimensions}),h);k.enter().append(\"g\").attr(\"class\",\"dimension\"),k.attr(\"transform\",(function(t){return s(t.x,0)})),k.exit().remove();var M=k.selectAll(\"g.category\").data((function(t){return t.categories}),h),A=M.enter().append(\"g\").attr(\"class\",\"category\");M.attr(\"transform\",(function(t){return s(0,t.y)})),A.append(\"rect\").attr(\"class\",\"catrect\").attr(\"pointer-events\",\"none\"),M.select(\"rect.catrect\").attr(\"fill\",\"none\").attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})),w(A);var S=M.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),h);S.each((function(){o.raiseToTop(this)})),S.attr(\"fill\",(function(t){return t.color}));var z=S.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);S.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),T(z),S.exit().remove(),A.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var O=e._fullLayout.paper_bgcolor;M.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return p(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",O+\" -1px  1px 2px, \"+O+\" 1px  1px 2px, \"+O+\"  1px -1px 2px, \"+O+\" -1px -1px 2px\").style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return p(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){l.font(n.select(this),t.parcatsViewModel.categorylabelfont),u.convertToTspans(n.select(this),e)})),A.append(\"text\").attr(\"class\",\"dimlabel\"),M.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){l.font(n.select(this),t.parcatsViewModel.labelfont)})),M.selectAll(\"rect.bandrect\").on(\"mouseover\",E).on(\"mouseout\",C),M.exit().remove(),k.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",L).on(\"drag\",I).on(\"dragend\",P)),f.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),f.exit().remove()}function h(t){return t.key}function p(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function d(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function g(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){o.raiseToTop(this),_(n.select(this));var e=v(t),r=y(t);if(t.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")){var i,s,l,u=n.mouse(this)[0],f=t.parcatsViewModel.graphDiv,h=t.parcatsViewModel.trace,p=f._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),g=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(l=0;l<t.leftXs.length-1;l++)if(t.leftXs[l]+t.dimWidths[l]-2<=u&&u<=t.leftXs[l+1]+2){var m=t.parcatsViewModel.dimensions[l],x=t.parcatsViewModel.dimensions[l+1];i=(m.x+m.width+x.x)/2,s=(t.topYs[l]+t.topYs[l+1]+t.height)/2;break}var b=t.parcatsViewModel.x+i,w=t.parcatsViewModel.y+s,T=c.mostReadable(t.model.color,[\"black\",\"white\"]),k=t.model.count,M=k/t.parcatsViewModel.model.count,A={countLabel:k,probabilityLabel:M.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&S.push([\"Count:\",A.countLabel].join(\" \")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&S.push([\"P:\",A.probabilityLabel].join(\" \"));var E=S.join(\"<br>\"),C=n.mouse(f)[0];a.loneHover({trace:h,x:b-d.left+g.left,y:w-d.top+g.top,text:E,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:T,idealAlign:C<b?\"right\":\"left\",hovertemplate:(h.line||{}).hovertemplate,hovertemplateLabels:A,eventData:[{data:h._input,fullData:h,count:k,probability:M}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:f})}}}function m(t){if(!t.parcatsViewModel.dragDimension&&(b(n.select(this)),a.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(d),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=v(t),r=y(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event,constraints:r})}}function v(t){for(var e=[],r=z(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function y(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[t.model.categoryInds[n]];e[i.containerInd]=a.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function x(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=v(t),r=y(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event,constraints:r})}}function b(t){t.attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function _(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",(function(t){return c.mostReadable(t.model.color,[\"black\",\"white\"])})).attr(\"stroke-width\",.3)}function w(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function T(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function k(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function M(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll(\"rect.bandrect\"),l=[];s.each((function(t){k(t).each((function(t){Array.prototype.push.apply(l,v(t))}))}));var c={};c[a.dimensionInd]=a.categoryValue,o.emit(e,{points:l,event:r,constraints:c})}function A(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=k(i),l=[];s.each((function(t){Array.prototype.push.apply(l,v(t))}));var c={};c[a.dimensionInd]=a.categoryValue,void 0!==i.rawColor&&(c.color=i.rawColor),o.emit(e,{points:l,event:r,constraints:c})}function S(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=n.select(r.parentNode).select(\"rect.catrect\"),c=l.node().getBoundingClientRect(),u=l.datum(),f=u.parcatsViewModel,h=f.model.dimensions[u.model.dimensionInd],p=f.trace,d=c.top+c.height/2;f.dimensions.length>1&&h.displayInd===f.dimensions.length-1?(i=c.left,a=\"left\"):(i=c.left+c.width,a=\"right\");var g=u.model.count,m=u.model.categoryLabel,v=g/u.parcatsViewModel.model.count,y={countLabel:g,categoryLabel:m,probabilityLabel:v.toFixed(3)},x=[];-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&x.push([\"Count:\",y.countLabel].join(\" \")),-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&x.push([\"P(\"+y.categoryLabel+\"):\",y.probabilityLabel].join(\" \"));var b=x.join(\"<br>\");return{trace:p,x:o*(i-e.left),y:s*(d-e.top),text:b,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", 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e=k(t);_(e),e.each((function(){o.raiseToTop(this)}))})),n.select(t.parentNode).select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}(this),M(this,\"plotly_hover\",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\"))\"category\"===l?e=S(r,s,this):\"color\"===l?e=function(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=r.getBoundingClientRect(),u=n.select(r).datum(),f=u.categoryViewModel,h=f.parcatsViewModel,p=h.model.dimensions[f.model.dimensionInd],d=h.trace,g=l.y+l.height/2;h.dimensions.length>1&&p.displayInd===h.dimensions.length-1?(i=l.left,a=\"left\"):(i=l.left+l.width,a=\"right\");var m=f.model.categoryLabel,v=u.parcatsViewModel.model.count,y=0;u.categoryViewModel.bands.forEach((function(t){t.color===u.color&&(y+=t.count)}));var x=f.model.count,b=0;h.pathSelection.each((function(t){t.model.color===u.color&&(b+=t.model.count)}));var _=y/v,w=y/b,T=y/x,k={countLabel:v,categoryLabel:m,probabilityLabel:_.toFixed(3)},M=[];-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&M.push([\"Count:\",k.countLabel].join(\" \")),-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&(M.push(\"P(color \\u2229 \"+m+\"): \"+k.probabilityLabel),M.push(\"P(\"+m+\" | color): \"+w.toFixed(3)),M.push(\"P(color | \"+m+\"): \"+T.toFixed(3)));var A=M.join(\"<br>\"),S=c.mostReadable(u.color,[\"black\",\"white\"]);return{trace:d,x:o*(i-e.left),y:s*(g-e.top),text:A,color:u.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:S,fontSize:10,idealAlign:a,hovertemplate:d.hovertemplate,hovertemplateLabels:k,eventData:[{data:d._input,fullData:d,category:m,count:v,probability:_,categorycount:x,colorcount:b,bandcolorcount:y}]}}(r,s,this):\"dimension\"===l&&(e=function(t,e,r){var i=[];return n.select(r.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each((function(){i.push(S(t,e,this))})),i}(r,s,this)),e&&a.loneHover(e,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r})}}function C(t){var e=t.parcatsViewModel;if(!e.dragDimension&&(b(e.pathSelection),w(e.dimensionSelection.selectAll(\"g.category\")),T(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),a.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(d),-1===e.hoverinfoItems.indexOf(\"skip\"))){\"color\"===t.parcatsViewModel.hoveron?A(this,\"plotly_unhover\",n.event):M(this,\"plotly_unhover\",n.event)}}function L(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each((function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,o.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each((function(e){e.y<i&&i<=e.y+e.height&&(t.potentialClickBand=this)})))})),t.parcatsViewModel.dragDimension=t,a.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function I(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,i=e+1,a=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=a.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,c=a.categories,u=c[l-1],f=c[l+1];void 0!==u&&s<u.y+u.height/2&&(o.model.displayInd=u.model.displayInd,u.model.displayInd=l),void 0!==f&&s+o.height>f.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragX<h.x+h.width&&(a.model.displayInd=h.model.displayInd,h.model.displayInd=e),void 0!==p&&a.model.dragX+a.width>p.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}N(t.parcatsViewModel),B(t.parcatsViewModel),D(t.parcatsViewModel),O(t.parcatsViewModel)}}function P(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=z(t.parcatsViewModel),a=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==a[e]}));o&&a.forEach((function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+i+\"].displayindex\"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var c=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),u=c.map((function(t){return t.categoryValue})),f=c.map((function(t){return t.categoryLabel}));e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[u],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[f],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?A(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):M(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd)t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null;t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,N(t.parcatsViewModel),B(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each((function(){D(t.parcatsViewModel,!0),O(t.parcatsViewModel,!0)})).each(\"end\",(function(){(o||s)&&i.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function z(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function O(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data((function(t){return t.paths}),h),(r=t.pathSelection,e?r.transition():r).attr(\"d\",(function(t){return t.svgD}))}function D(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data((function(t){return t.dimensions}),h);var i=t.dimensionSelection.selectAll(\"g.category\").data((function(t){return t.categories}),h);r(t.dimensionSelection).attr(\"transform\",(function(t){return s(t.x,0)})),r(i).attr(\"transform\",(function(t){return s(0,t.y)})),i.select(\".dimlabel\").text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})),i.select(\".catlabel\").attr(\"text-anchor\",(function(t){return p(t)?\"start\":\"end\"})).attr(\"x\",(function(t){return p(t)?t.width+5:-5})).each((function(t){var e,r;p(t)?(e=t.width+5,r=\"start\"):(e=-5,r=\"end\"),n.select(this).selectAll(\"tspan\").attr(\"x\",e).attr(\"text-anchor\",r)}));var a=i.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),h),l=a.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);a.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})),T(l),a.each((function(){o.raiseToTop(this)})),a.exit().remove()}function R(t,e,r){var n,i=r[0],a=e.margin||{l:80,r:80,t:100,b:80},o=i.trace,s=o.domain,l=e.width,c=e.height,u=Math.floor(l*(s.x[1]-s.x[0])),f=Math.floor(c*(s.y[1]-s.y[0])),h=s.x[0]*l+a.l,p=e.height-s.y[1]*e.height+a.t,d=o.line.shape;n=\"all\"===o.hoverinfo?[\"count\",\"probability\"]:(o.hoverinfo||\"\").split(\"+\");var g={trace:o,key:o.uid,model:i,x:h,y:p,width:u,height:f,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:a,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};return i.dimensions&&(N(g),B(g)),g}function F(t,e,r,i,a){var o,s,l=[],c=[];for(s=0;s<r.length-1;s++)o=n.interpolateNumber(r[s]+t[s],t[s+1]),l.push(o(a)),c.push(o(1-a));var u=\"M \"+t[0]+\",\"+e[0];for(u+=\"l\"+r[0]+\",0 \",s=1;s<r.length;s++)u+=\"C\"+l[s-1]+\",\"+e[s-1]+\" \"+c[s-1]+\",\"+e[s]+\" \"+t[s]+\",\"+e[s],u+=\"l\"+r[s]+\",0 \";for(u+=\"l0,\"+i+\" \",u+=\"l -\"+r[r.length-1]+\",0 \",s=r.length-2;s>=0;s--)u+=\"C\"+c[s]+\",\"+(e[s+1]+i)+\" \"+l[s]+\",\"+(e[s]+i)+\" \"+(t[s]+r[s])+\",\"+(e[s]+i),u+=\"l-\"+r[s]+\",0 \";return u+=\"Z\"}function B(t){var e=t.dimensions,r=t.model,n=e.map((function(t){return t.categories.map((function(t){return t.y}))})),i=t.model.dimensions.map((function(t){return t.categories.map((function(t){return t.displayInd}))})),a=t.model.dimensions.map((function(t){return t.displayInd})),o=t.dimensions.map((function(t){return t.model.dimensionInd})),s=e.map((function(t){return t.x})),l=e.map((function(t){return t.width})),c=[];for(var u in r.paths)r.paths.hasOwnProperty(u)&&c.push(r.paths[u]);function f(t){var e=t.categoryInds.map((function(t,e){return i[e][t]}));return o.map((function(t){return e[t]}))}c.sort((function(e,r){var n=f(e),i=f(r);return\"backward\"===t.sortpaths&&(n.reverse(),i.reverse()),n.push(e.valueInds[0]),i.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),i.unshift(r.rawColor)),n<i?-1:n>i?1:0}));for(var h=new Array(c.length),p=e[0].model.count,d=e[0].categories.map((function(t){return t.height})).reduce((function(t,e){return t+e})),g=0;g<c.length;g++){var m,v=c[g];m=p>0?d*(v.count/p):0;for(var y,x=new Array(n.length),b=0;b<v.categoryInds.length;b++){var _=v.categoryInds[b],w=i[b][_],T=a[b];x[T]=n[T][w],n[T][w]+=m;var k=t.dimensions[T].categories[w],M=k.bands.length,A=k.bands[M-1];if(void 0===A||v.rawColor!==A.rawColor){var S=void 0===A?0:A.y+A.height;k.bands.push({key:S,color:v.color,rawColor:v.rawColor,height:m,width:k.width,count:v.count,y:S,categoryViewModel:k,parcatsViewModel:t})}else{var E=k.bands[M-1];E.height+=m,E.count+=v.count}}y=\"hspline\"===t.pathShape?F(s,x,l,m,.5):F(s,x,l,m,0),h[g]={key:v.valueInds[0],model:v,height:m,leftXs:s,topYs:x,dimWidths:l,svgD:y,parcatsViewModel:t}}t.paths=h}function N(t){var e=t.model.dimensions.map((function(t){return{displayInd:t.displayInd,dimensionInd:t.dimensionInd}}));e.sort((function(t,e){return t.displayInd-e.displayInd}));var r=[];for(var n in e){var i=e[n].dimensionInd,a=t.model.dimensions[i];r.push(j(t,a))}t.dimensions=r}function j(t,e){var r,n=t.model.dimensions.length,i=e.displayInd;r=40+(n>1?(t.width-80-16)/(n-1):0)*i;var a,o,s,l,c,u=[],f=t.model.maxCats,h=e.categories.length,p=e.count,d=t.height-8*(f-1),g=8*(f-h)/2,m=e.categories.map((function(t){return{displayInd:t.displayInd,categoryInd:t.categoryInd}}));for(m.sort((function(t,e){return t.displayInd-e.displayInd})),c=0;c<h;c++)l=m[c].categoryInd,o=e.categories[l],a=p>0?o.count/p*d:0,s={key:o.valueInds[0],model:o,width:16,height:a,y:null!==o.dragY?o.dragY:g,bands:[],parcatsViewModel:t},g=g+a+8,u.push(s);return{key:e.dimensionInd,x:null!==e.dragX?e.dragX:r,y:0,width:16,model:e,categories:u,parcatsViewModel:t,dragCategoryDisplayInd:null,dragDimensionDisplayInd:null,initialDragDimensionDisplayInds:null,initialDragCategoryDisplayInds:null,dragHasMoved:null,potentialClickBand:null}}e.exports=function(t,e,r,n){f(r,t,n,e)}},{\"../../components/drawing\":665,\"../../components/fx\":683,\"../../lib\":778,\"../../lib/svg_text_utils\":803,\"../../plot_api/plot_api\":814,d3:169,tinycolor2:576}],1148:[function(t,e,r){\"use strict\";var n=t(\"./parcats\");e.exports=function(t,e,r,i){var a=t._fullLayout,o=a._paper,s=a._size;n(t,o,e,{width:s.w,height:s.h,margin:{t:s.t,r:s.r,b:s.b,l:s.l}},r,i)}},{\"./parcats\":1147}],1149:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/layout_attributes\"),a=t(\"../../plots/font_attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/plot_template\").templatedArray;e.exports={domain:o({name:\"parcoords\",trace:!0,editType:\"plot\"}),labelangle:{valType:\"angle\",dflt:0,editType:\"plot\"},labelside:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},labelfont:a({editType:\"plot\"}),tickfont:a({editType:\"plot\"}),rangefont:a({editType:\"plot\"}),dimensions:l(\"dimension\",{label:{valType:\"string\",editType:\"plot\"},tickvals:s({},i.tickvals,{editType:\"plot\"}),ticktext:s({},i.ticktext,{editType:\"plot\"}),tickformat:s({},i.tickformat,{editType:\"plot\"}),visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},range:{valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},constraintrange:{valType:\"info_array\",freeLength:!0,dimensions:\"1-2\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},multiselect:{valType:\"boolean\",dflt:!0,editType:\"plot\"},values:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"}),line:s({editType:\"calc\"},n(\"line\",{colorscaleDflt:\"Viridis\",autoColorDflt:!1,editTypeOverride:\"calc\"}))}},{\"../../components/colorscale/attributes\":650,\"../../lib/extend\":768,\"../../plot_api/plot_template\":817,\"../../plots/cartesian/layout_attributes\":842,\"../../plots/domain\":855,\"../../plots/font_attributes\":856}],1150:[function(t,e,r){\"use strict\";var n=t(\"./constants\"),i=t(\"d3\"),a=t(\"../../lib/gup\").keyFun,o=t(\"../../lib/gup\").repeat,s=t(\"../../lib\").sorterAsc,l=t(\"../../lib\").strTranslate,c=n.bar.snapRatio;function u(t,e){return t*(1-c)+e*c}var f=n.bar.snapClose;function h(t,e){return t*(1-f)+e*f}function p(t,e,r,n){if(function(t,e){for(var r=0;r<e.length;r++)if(t>=e[r][0]&&t<=e[r][1])return!0;return!1}(r,n))return r;var i=t?-1:1,a=0,o=e.length-1;if(i<0){var s=a;a=o,o=s}for(var l=e[a],c=l,f=a;i*f<i*o;f+=i){var p=f+i,d=e[p];if(i*r<i*h(l,d))return u(l,c);if(i*r<i*d||p===o)return u(d,l);c=l,l=d}}function d(t){t.attr(\"x\",-n.bar.captureWidth/2).attr(\"width\",n.bar.captureWidth)}function g(t){t.attr(\"visibility\",\"visible\").style(\"visibility\",\"visible\").attr(\"fill\",\"yellow\").attr(\"opacity\",0)}function m(t){if(!t.brush.filterSpecified)return\"0,\"+t.height;for(var 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k(t){t.on(\"mousemove\",(function(t){i.event.preventDefault(),t.parent.inBrushDrag||T(this,t)})).on(\"mouseleave\",(function(t){t.parent.inBrushDrag||y()})).call(i.behavior.drag().on(\"dragstart\",(function(t){!function(t,e){i.event.sourceEvent.stopPropagation();var r=e.height-i.mouse(t)[1]-2*n.verticalPadding,a=e.unitToPaddedPx.invert(r),o=e.brush,s=_(e,r),l=s.interval,c=o.svgBrush;if(c.wasDragged=!1,c.grabbingBar=\"ns\"===s.region,c.grabbingBar){var u=l.map(e.unitToPaddedPx);c.grabPoint=r-u[0]-n.verticalPadding,c.barLength=u[1]-u[0]}c.clickableOrdinalRange=s.clickableOrdinalRange,c.stayingIntervals=e.multiselect&&o.filterSpecified?o.filter.getConsolidated():[],l&&(c.stayingIntervals=c.stayingIntervals.filter((function(t){return t[0]!==l[0]&&t[1]!==l[1]}))),c.startExtent=s.region?l[\"s\"===s.region?1:0]:a,e.parent.inBrushDrag=!0,c.brushStartCallback()}(this,t)})).on(\"drag\",(function(t){w(this,t)})).on(\"dragend\",(function(t){!function(t,e){var r=e.brush,n=r.filter,a=r.svgBrush;a._dragging||(T(t,e),w(t,e),e.brush.svgBrush.wasDragged=!1),a._dragging=!1,i.event.sourceEvent.stopPropagation();var o=a.grabbingBar;if(a.grabbingBar=!1,a.grabLocation=void 0,e.parent.inBrushDrag=!1,y(),!a.wasDragged)return a.wasDragged=void 0,a.clickableOrdinalRange?r.filterSpecified&&e.multiselect?a.extent.push(a.clickableOrdinalRange):(a.extent=[a.clickableOrdinalRange],r.filterSpecified=!0):o?(a.extent=a.stayingIntervals,0===a.extent.length&&A(r)):A(r),a.brushCallback(e),b(t.parentNode),void a.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);var s=function(){n.set(n.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]<l[0]&&l.reverse(),a.newExtent=[p(0,l,a.newExtent[0],a.stayingIntervals),p(1,l,a.newExtent[1],a.stayingIntervals)];var c=a.newExtent[1]>a.newExtent[0];a.extent=a.stayingIntervals.concat(c?[a.newExtent]:[]),a.extent.length||A(r),a.brushCallback(e),c?b(t.parentNode,s):(s(),b(t.parentNode))}else s();a.brushEndCallback(r.filterSpecified?n.getConsolidated():[])}(this,t)})))}function M(t,e){return t[0]-e[0]}function A(t){t.filterSpecified=!1,t.svgBrush.extent=[[-1/0,1/0]]}function S(t){for(var e,r=t.slice(),n=[],i=r.shift();i;){for(e=i.slice();(i=r.shift())&&i[0]<=e[1];)e[1]=Math.max(e[1],i[1]);n.push(e)}return 1===n.length&&n[0][0]>n[0][1]&&(n=[]),n}e.exports={makeBrush:function(t,e,r,n,i,a){var o,l=function(){var t,e,r=[];return{set:function(n){1===(r=n.map((function(t){return t.slice().sort(s)})).sort(M)).length&&r[0][0]===-1/0&&r[0][1]===1/0&&(r=[[0,-1]]),t=S(r),e=r.reduce((function(t,e){return[Math.min(t[0],e[0]),Math.max(t[1],e[1])]}),[1/0,-1/0])},get:function(){return r.slice()},getConsolidated:function(){return t},getBounds:function(){return e}}}();return l.set(r),{filter:l,filterSpecified:e,svgBrush:{extent:[],brushStartCallback:n,brushCallback:(o=i,function(t){var e=t.brush,r=function(t){return t.svgBrush.extent.map((function(t){return t.slice()}))}(e).slice();e.filter.set(r),o()}),brushEndCallback:a}}},ensureAxisBrush:function(t){var e=t.selectAll(\".\"+n.cn.axisBrush).data(o,a);e.enter().append(\"g\").classed(n.cn.axisBrush,!0),function(t){var e=t.selectAll(\".background\").data(o);e.enter().append(\"rect\").classed(\"background\",!0).call(d).call(g).style(\"pointer-events\",\"auto\").attr(\"transform\",l(0,n.verticalPadding)),e.call(k).attr(\"height\",(function(t){return t.height-n.verticalPadding}));var r=t.selectAll(\".highlight-shadow\").data(o);r.enter().append(\"line\").classed(\"highlight-shadow\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width+n.bar.strokeWidth).attr(\"stroke\",n.bar.strokeColor).attr(\"opacity\",n.bar.strokeOpacity).attr(\"stroke-linecap\",\"butt\"),r.attr(\"y1\",(function(t){return t.height})).call(x);var i=t.selectAll(\".highlight\").data(o);i.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width-n.bar.strokeWidth).attr(\"stroke\",n.bar.fillColor).attr(\"opacity\",n.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),i.attr(\"y1\",(function(t){return t.height})).call(x)}(e)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(s)})),t=e.multiselect?S(t.sort(M)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map((function(t){var e=[p(0,r,t[0],[]),p(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}},{\"../../lib\":778,\"../../lib/gup\":775,\"./constants\":1153,d3:169}],1151:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../plots/get_data\").getModuleCalcData,a=t(\"./plot\"),o=t(\"../../constants/xmlns_namespaces\");r.name=\"parcoords\",r.plot=function(t){var e=i(t.calcdata,\"parcoords\")[0];e.length&&a(t,e)},r.clean=function(t,e,r,n){var i=n._has&&n._has(\"parcoords\"),a=e._has&&e._has(\"parcoords\");i&&!a&&(n._paperdiv.selectAll(\".parcoords\").remove(),n._glimages.selectAll(\"*\").remove())},r.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter((function(t,e){return e===r.size()-1})).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each((function(){var t=this.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":t,preserveAspectRatio:\"none\",x:0,y:0,width:this.width,height:this.height})})),window.setTimeout((function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")}),60)}},{\"../../constants/xmlns_namespaces\":754,\"../../plots/get_data\":865,\"./plot\":1160,d3:169}],1152:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray,i=t(\"../../components/colorscale\"),a=t(\"../../lib/gup\").wrap;e.exports=function(t,e){var r,o;return i.hasColorscale(e,\"line\")&&n(e.line.color)?(r=e.line.color,o=i.extractOpts(e.line).colorscale,i.calc(t,e,{vals:r,containerStr:\"line\",cLetter:\"c\"})):(r=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),o=[[0,e.line.color],[1,e.line.color]]),a({lineColor:r,cscale:o})}},{\"../../components/colorscale\":655,\"../../lib\":778,\"../../lib/gup\":775}],1153:[function(t,e,r){\"use strict\";e.exports={maxDimensionCount:60,overdrag:45,verticalPadding:2,tickDistance:50,canvasPixelRatio:1,blockLineCount:5e3,layers:[\"contextLineLayer\",\"focusLineLayer\",\"pickLineLayer\"],axisTitleOffset:28,axisExtentOffset:10,deselectedLineColor:\"#777\",bar:{width:4,captureWidth:10,fillColor:\"magenta\",fillOpacity:1,snapDuration:150,snapRatio:.25,snapClose:.01,strokeColor:\"white\",strokeOpacity:1,strokeWidth:1,handleHeight:8,handleOpacity:1,handleOverlap:0},cn:{axisExtentText:\"axis-extent-text\",parcoordsLineLayers:\"parcoords-line-layers\",parcoordsLineLayer:\"parcoords-lines\",parcoords:\"parcoords\",parcoordsControlView:\"parcoords-control-view\",yAxis:\"y-axis\",axisOverlays:\"axis-overlays\",axis:\"axis\",axisHeading:\"axis-heading\",axisTitle:\"axis-title\",axisExtent:\"axis-extent\",axisExtentTop:\"axis-extent-top\",axisExtentTopText:\"axis-extent-top-text\",axisExtentBottom:\"axis-extent-bottom\",axisExtentBottomText:\"axis-extent-bottom-text\",axisBrush:\"axis-brush\"},id:{filterBarPattern:\"filter-bar-pattern\"}}},{}],1154:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/colorscale/helpers\").hasColorscale,a=t(\"../../components/colorscale/defaults\"),o=t(\"../../plots/domain\").defaults,s=t(\"../../plots/array_container_defaults\"),l=t(\"../../plots/cartesian/axes\"),c=t(\"./attributes\"),u=t(\"./axisbrush\"),f=t(\"./constants\").maxDimensionCount,h=t(\"./merge_length\");function p(t,e,r,i){function a(r,i){return n.coerce(t,e,c.dimensions,r,i)}var o=a(\"values\"),s=a(\"visible\");if(o&&o.length||(s=e.visible=!1),s){a(\"label\"),a(\"tickvals\"),a(\"ticktext\"),a(\"tickformat\");var f=a(\"range\");e._ax={_id:\"y\",type:\"linear\",showexponent:\"all\",exponentformat:\"B\",range:f},l.setConvert(e._ax,i.layout),a(\"multiselect\");var h=a(\"constraintrange\");h&&(e.constraintrange=u.cleanRanges(h,e))}}e.exports=function(t,e,r,l){function u(r,i){return n.coerce(t,e,c,r,i)}var d=t.dimensions;Array.isArray(d)&&d.length>f&&(n.log(\"parcoords traces support up to \"+f+\" dimensions at the moment\"),d.splice(f));var g=s(t,e,{name:\"dimensions\",layout:l,handleItemDefaults:p}),m=function(t,e,r,o,s){var l=s(\"line.color\",r);if(i(t,\"line\")&&n.isArrayOrTypedArray(l)){if(l.length)return s(\"line.colorscale\"),a(t,e,o,s,{prefix:\"line.\",cLetter:\"c\"}),l.length;e.line.color=r}return 1/0}(t,e,r,l,u);o(e,l,u),Array.isArray(g)&&g.length||(e.visible=!1),h(e,g,\"values\",m);var v={family:l.font.family,size:Math.round(l.font.size/1.2),color:l.font.color};n.coerceFont(u,\"labelfont\",v),n.coerceFont(u,\"tickfont\",v),n.coerceFont(u,\"rangefont\",v),u(\"labelangle\"),u(\"labelside\")}},{\"../../components/colorscale/defaults\":653,\"../../components/colorscale/helpers\":654,\"../../lib\":778,\"../../plots/array_container_defaults\":823,\"../../plots/cartesian/axes\":828,\"../../plots/domain\":855,\"./attributes\":1149,\"./axisbrush\":1150,\"./constants\":1153,\"./merge_length\":1158}],1155:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isTypedArray;r.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},r.isOrdinal=function(t){return!!t.tickvals},r.isVisible=function(t){return t.visible||!(\"visible\"in t)}},{\"../../lib\":778}],1156:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcoords\",basePlotModule:t(\"./base_plot\"),categories:[\"gl\",\"regl\",\"noOpacity\",\"noHover\"],meta:{}}},{\"./attributes\":1149,\"./base_plot\":1151,\"./calc\":1152,\"./defaults\":1154,\"./plot\":1160}],1157:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\\n               p17_20, p21_24, p25_28, p29_32,\\n               p33_36, p37_40, p41_44, p45_48,\\n               p49_52, p53_56, p57_60, colors;\\n\\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\\n             loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\\nuniform sampler2D mask, palette;\\nuniform float maskHeight;\\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\\nuniform vec4 contextColor;\\n\\nbool isPick    = (drwLayer > 1.5);\\nbool isContext = (drwLayer < 0.5);\\n\\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\\n\\nfloat val(mat4 p, mat4 v) {\\n    return dot(matrixCompMult(p, v) * UNITS, UNITS);\\n}\\n\\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\\n    float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\\n    return y1 * (1.0 - ratio) + y2 * ratio;\\n}\\n\\nint iMod(int a, int b) {\\n    return a - b * (a / b);\\n}\\n\\nbool fOutside(float p, float lo, float hi) {\\n    return (lo < hi) && (lo > p || p > hi);\\n}\\n\\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\\n    return (\\n        fOutside(p[0], lo[0], hi[0]) ||\\n        fOutside(p[1], lo[1], hi[1]) ||\\n        fOutside(p[2], lo[2], hi[2]) ||\\n        fOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n    return (\\n        vOutside(p[0], lo[0], hi[0]) ||\\n        vOutside(p[1], lo[1], hi[1]) ||\\n        vOutside(p[2], lo[2], hi[2]) ||\\n        vOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    return mOutside(A, loA, hiA) ||\\n           mOutside(B, loB, hiB) ||\\n           mOutside(C, loC, hiC) ||\\n           mOutside(D, loD, hiD);\\n}\\n\\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    mat4 pnts[4];\\n    pnts[0] = A;\\n    pnts[1] = B;\\n    pnts[2] = C;\\n    pnts[3] = D;\\n\\n    for(int i = 0; i < 4; ++i) {\\n        for(int j = 0; j < 4; ++j) {\\n            for(int k = 0; k < 4; ++k) {\\n                if(0 == iMod(\\n                    int(255.0 * texture2D(mask,\\n                        vec2(\\n                            (float(i * 2 + j / 2) + 0.5) / 8.0,\\n                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\\n                        ))[3]\\n                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\\n                    2\\n                )) return true;\\n            }\\n        }\\n    }\\n    return false;\\n}\\n\\nvec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float x = 0.5 * sign(v) + 0.5;\\n    float y = axisY(x, A, B, C, D);\\n    float z = 1.0 - abs(v);\\n\\n    z += isContext ? 0.0 : 2.0 * float(\\n        outsideBoundingBox(A, B, C, D) ||\\n        outsideRasterMask(A, B, C, D)\\n    );\\n\\n    return vec4(\\n        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\\n        z,\\n        1.0\\n    );\\n}\\n\\nvoid main() {\\n    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\\n    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\\n    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\\n    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\\n\\n    float v = colors[3];\\n\\n    gl_Position = position(isContext, v, A, B, C, D);\\n\\n    fragColor =\\n        isContext ? vec4(contextColor) :\\n        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\\n}\\n\"]),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n    gl_FragColor = fragColor;\\n}\\n\"]),o=t(\"./constants\").maxDimensionCount,s=t(\"../../lib\"),l=new Uint8Array(4),c=new Uint8Array(4),u={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function f(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function h(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(!function(t){t.read({x:0,y:0,width:1,height:1,data:l})}(t),r.drawCompleted=!0),function s(l){var c=Math.min(n,i-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],f(t,a.scissorX,a.scissorY,a.scissorWidth,a.viewBoxSize[1])),r.clearOnly||(a.count=2*c,a.offset=2*l*n,e(a),l*n+c<i&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function p(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function d(t,e){return(t>>>8*e)%256/255}function g(t,e,r){for(var n=new Array(8*e),i=0,a=0;a<e;a++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,c=r[64*a+l];63===l&&0===o&&(c*=-1),n[i++]=c}return n}function m(t){var e=\"0\"+t;return e.substr(e.length-2)}function v(t){return t<o?\"p\"+m(t+1)+\"_\"+m(t+4):\"colors\"}function y(t,e,r,n,i,a,o,l,c,u,f,h,p){for(var d=[[],[]],g=0;g<64;g++)d[0][g]=g===i?1:0,d[1][g]=g===a?1:0;var m=t.lines.canvasOverdrag,v=t.domain,y=t.canvasWidth,x=t.canvasHeight,b=t.deselectedLines.color;return s.extendFlat({key:f,resolution:[y,x],viewBoxPos:[o+m,l],viewBoxSize:[c,u],i0:i,i1:a,dim0A:d[0].slice(0,16),dim0B:d[0].slice(16,32),dim0C:d[0].slice(32,48),dim0D:d[0].slice(48,64),dim1A:d[1].slice(0,16),dim1B:d[1].slice(16,32),dim1C:d[1].slice(32,48),dim1D:d[1].slice(48,64),drwLayer:h,contextColor:[b[0]/255,b[1]/255,b[2]/255,b[3]<1?b[3]:Math.max(1/255,Math.pow(1/t.lines.color.length,1/3))],scissorX:(n===e?0:o+m)+(t.pad.l-m)+t.layoutWidth*v.x[0],scissorWidth:(n===r?y-o+m:c+.5)+(n===e?o+m:0),scissorY:l+t.pad.b+t.layoutHeight*v.y[0],scissorHeight:u,viewportX:t.pad.l-m+t.layoutWidth*v.x[0],viewportY:t.pad.b+t.layoutHeight*v.y[0],viewportWidth:y,viewportHeight:x},p)}function x(t){var e=Math.max(0,Math.floor(2047*t[0]),0),r=Math.min(2047,Math.ceil(2047*t[1]),2047);return[Math.min(e,r),Math.max(e,r)]}e.exports=function(t,e){var r,n,l,m,b,_=e.context,w=e.pick,T=e.regl,k={currentRafs:{},drawCompleted:!0,clearOnly:!1},M=function(t){for(var e={},r=0;r<=o;r+=4)e[v(r)]=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)});return e}(T),A=T.texture(u),S=[];C(e);var E=T({profile:!1,blend:{enable:_,func:{srcRGB:\"src alpha\",dstRGB:\"one minus src 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r=t._fullLayout;if(i(t)){var s={},l={},c={},u={},f=r._size;e.forEach((function(e,r){var n=e[0].trace;c[r]=n.index;var i=u[r]=n._fullInput.index;s[r]=t.data[i].dimensions,l[r]=t.data[i].dimensions.slice()}));n(t,e,{width:f.w,height:f.h,margin:{t:f.t,r:f.r,b:f.b,l:f.l}},{filterChanged:function(e,n,i){var a=l[e][n],o=i.map((function(t){return t.slice()})),s=\"dimensions[\"+n+\"].constraintrange\",f=r._tracePreGUI[t._fullData[c[e]]._fullInput.uid];if(void 0===f[s]){var h=a.constraintrange;f[s]=h||null}var p=t._fullData[c[e]].dimensions[n];o.length?(1===o.length&&(o=o[0]),a.constraintrange=o,p.constraintrange=o.slice(),o=[o]):(delete a.constraintrange,delete p.constraintrange,o=null);var d={};d[s]=o,t.emit(\"plotly_restyle\",[d,[u[e]]])},hover:function(e){t.emit(\"plotly_hover\",e)},unhover:function(e){t.emit(\"plotly_unhover\",e)},axesMoved:function(e,r){var n=function(t,e){return function(r,n){return 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n=t(\"../../plots/attributes\"),i=t(\"../../plots/domain\").attributes,a=t(\"../../plots/font_attributes\"),o=t(\"../../components/color/attributes\"),s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/template_attributes\").texttemplateAttrs,c=t(\"../../lib/extend\").extendFlat,u=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});e.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:c({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:c({},u,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:c({},u,{}),outsidetextfont:c({},u,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:c({},u,{}),position:{valType:\"enumerated\",values:[\"top left\",\"top center\",\"top right\",\"middle center\",\"bottom left\",\"bottom center\",\"bottom right\"],editType:\"plot\"},editType:\"plot\"},domain:i({name:\"pie\",trace:!0,editType:\"calc\"}),hole:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},sort:{valType:\"boolean\",dflt:!0,editType:\"calc\"},direction:{valType:\"enumerated\",values:[\"clockwise\",\"counterclockwise\"],dflt:\"counterclockwise\",editType:\"calc\"},rotation:{valType:\"number\",min:-360,max:360,dflt:0,editType:\"calc\"},pull:{valType:\"number\",min:0,max:1,dflt:0,arrayOk:!0,editType:\"calc\"},_deprecated:{title:{valType:\"string\",dflt:\"\",editType:\"calc\"},titlefont:c({},u,{}),titleposition:{valType:\"enumerated\",values:[\"top left\",\"top center\",\"top right\",\"middle center\",\"bottom left\",\"bottom center\",\"bottom right\"],editType:\"calc\"}}}},{\"../../components/color/attributes\":642,\"../../lib/extend\":768,\"../../plots/attributes\":824,\"../../plots/domain\":855,\"../../plots/font_attributes\":856,\"../../plots/template_attributes\":906}],1162:[function(t,e,r){\"use strict\";var n=t(\"../../plots/plots\");r.name=\"pie\",r.plot=function(t,e,i,a){n.plotBasePlot(r.name,t,e,i,a)},r.clean=function(t,e,i,a){n.cleanBasePlot(r.name,t,e,i,a)}},{\"../../plots/plots\":891}],1163:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"tinycolor2\"),a=t(\"../../components/color\"),o={};function s(t){return function(e,r){return!!e&&(!!(e=i(e)).isValid()&&(e=a.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e))}}function l(t,e){var r,n=JSON.stringify(t),a=e[n];if(!a){for(a=t.slice(),r=0;r<t.length;r++)a.push(i(t[r]).lighten(20).toHexString());for(r=0;r<t.length;r++)a.push(i(t[r]).darken(20).toHexString());e[n]=a}return a}e.exports={calc:function(t,e){var r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],c=e.labels,u=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(c=new Array(h),r=0;r<h;r++)c[r]=String(e.label0+r*e.dlabel);var d={},g=s(o[\"_\"+e.type+\"colormap\"]),m=0,v=!1;for(r=0;r<h;r++){var y,x,b;if(p){if(y=f[r],!n(y))continue;if((y=+y)<0)continue}else y=1;void 0!==(x=c[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=a.length,(b=-1!==l.indexOf(x))||(m+=y),a.push({v:y,label:x,color:g(u[r],x),i:r,pts:[r],hidden:b})):(v=!0,(i=a[_]).v+=y,i.pts.push(r),i.hidden||(m+=y),!1===i.color&&u[r]&&(i.color=g(u[r],x)))}return(\"funnelarea\"===e.type?v:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=m),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var c=0,u=0;u<i.length;u++){var f=i[u];if(f[0].trace.type===r)for(var h=0;h<f.length;h++){var p=f[h];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=a[c%a.length],c++))}}},makePullColorFn:s,generateExtendedColors:l}},{\"../../components/color\":643,\"fast-isnumeric\":241,tinycolor2:576}],1164:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"./attributes\"),o=t(\"../../plots/domain\").defaults,s=t(\"../bar/defaults\").handleText;function l(t,e){var r=Array.isArray(t),a=i.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,a?e.length:1/0);if(isFinite(o)||(o=0),o&&a){for(var s,l=0;l<o;l++){var c=e[l];if(n(c)&&c>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}e.exports={handleLabelsAndValues:l,supplyDefaults:function(t,e,r,n){function c(r,n){return i.coerce(t,e,a,r,n)}var u=l(c(\"labels\"),c(\"values\")),f=u.len;if(e._hasLabels=u.hasLabels,e._hasValues=u.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),f){e._length=f,c(\"marker.line.width\")&&c(\"marker.line.color\"),c(\"marker.colors\"),c(\"scalegroup\");var h,p=c(\"text\"),d=c(\"texttemplate\");if(d||(h=c(\"textinfo\",Array.isArray(p)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),d||h&&\"none\"!==h){var g=c(\"textposition\");s(t,e,n,c,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||\"auto\"===g||\"outside\"===g)&&c(\"automargin\"),(\"inside\"===g||\"auto\"===g||Array.isArray(g))&&c(\"insidetextorientation\")}o(e,n,c);var m=c(\"hole\");if(c(\"title.text\")){var v=c(\"title.position\",m?\"middle center\":\"top center\");m||\"middle center\"!==v||(e.title.position=\"top center\"),i.coerceFont(c,\"title.font\",n.font)}c(\"sort\"),c(\"direction\"),c(\"rotation\"),c(\"pull\")}else e.visible=!1}}},{\"../../lib\":778,\"../../plots/domain\":855,\"../bar/defaults\":925,\"./attributes\":1161,\"fast-isnumeric\":241}],1165:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/helpers\").appendArrayMultiPointValues;e.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},{\"../../components/fx/helpers\":679}],1166:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}r.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},r.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},r.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||\"\"===n)return n}},r.castOption=function(t,e){return Array.isArray(t)?r.getFirstFilled(t,e):t||void 0},r.getRotationAngle=function(t){return(\"auto\"===t?0:t)*Math.PI/180}},{\"../../lib\":778}],1167:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),layoutAttributes:t(\"./layout_attributes\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\"),styleOne:t(\"./style_one\"),moduleType:\"trace\",name:\"pie\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},{\"./attributes\":1161,\"./base_plot\":1162,\"./calc\":1163,\"./defaults\":1164,\"./layout_attributes\":1168,\"./layout_defaults\":1169,\"./plot\":1170,\"./style\":1171,\"./style_one\":1172}],1168:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],1169:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},{\"../../lib\":778,\"./layout_attributes\":1168}],1170:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../plots/plots\"),a=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=t(\"../../components/drawing\"),l=t(\"../../lib\"),c=l.strScale,u=l.strTranslate,f=t(\"../../lib/svg_text_utils\"),h=t(\"../bar/uniform_text\"),p=h.recordMinTextSize,d=h.clearMinTextSize,g=t(\"../bar/constants\").TEXTPAD,m=t(\"./helpers\"),v=t(\"./event_data\"),y=t(\"../../lib\").isValidTextValue;function x(t,e,r){var i=r[0],o=i.trace,s=i.cx,c=i.cy;\"_hasHoverLabel\"in o||(o._hasHoverLabel=!1),\"_hasHoverEvent\"in o||(o._hasHoverEvent=!1),t.on(\"mouseover\",(function(t){var r=e._fullLayout,u=e._fullData[o.index];if(!e._dragging&&!1!==r.hovermode){var f=u.hoverinfo;if(Array.isArray(f)&&(f=a.castHoverinfo({hoverinfo:[m.castOption(f,t.pts)],_module:o._module},r,0)),\"all\"===f&&(f=\"label+text+value+percent+name\"),u.hovertemplate||\"none\"!==f&&\"skip\"!==f&&f){var h=t.rInscribed||0,p=s+t.pxmid[0]*(1-h),d=c+t.pxmid[1]*(1-h),g=r.separators,y=[];if(f&&-1!==f.indexOf(\"label\")&&y.push(t.label),t.text=m.castOption(u.hovertext||u.text,t.pts),f&&-1!==f.indexOf(\"text\")){var x=t.text;l.isValidTextValue(x)&&y.push(x)}t.value=t.v,t.valueLabel=m.formatPieValue(t.v,g),f&&-1!==f.indexOf(\"value\")&&y.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=m.formatPiePercent(t.percent,g),f&&-1!==f.indexOf(\"percent\")&&y.push(t.percentLabel);var b=u.hoverlabel,_=b.font;a.loneHover({trace:o,x0:p-h*i.r,x1:p+h*i.r,y:d,text:y.join(\"<br>\"),name:u.hovertemplate||-1!==f.indexOf(\"name\")?u.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:m.castOption(b.bgcolor,t.pts)||t.color,borderColor:m.castOption(b.bordercolor,t.pts),fontFamily:m.castOption(_.family,t.pts),fontSize:m.castOption(_.size,t.pts),fontColor:m.castOption(_.color,t.pts),nameLength:m.castOption(b.namelength,t.pts),textAlign:m.castOption(b.align,t.pts),hovertemplate:m.castOption(u.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[v(t,u)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e}),o._hasHoverLabel=!0}o._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[v(t,u)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[o.index],s=n.select(this).datum();o._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[v(s,i)],event:n.event}),o._hasHoverEvent=!1),o._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),o._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[o.index];e._dragging||!1===r.hovermode||(e._hoverdata=[v(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=m.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=m.castOption(t._input.textfont.color,e.pts));var i=m.castOption(t.insidetextfont.family,e.pts)||m.castOption(t.textfont.family,e.pts)||r.family,a=m.castOption(t.insidetextfont.size,e.pts)||m.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var o=s.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(s.font,n.title.font).call(f.convertToTspans,e),c=s.bBox(o.node(),!0);r.titleBox={width:c.width,height:c.height},o.remove()}}function w(t,e,r){var n=r.r||e.rpx1,i=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var a,o=e.ring,s=1===o&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,l=e.halfangle,c=e.midangle,u=r.trace.insidetextorientation,f=\"horizontal\"===u,h=\"tangential\"===u,p=\"radial\"===u,d=\"auto\"===u,g=[];if(!d){var m,v=function(r,i){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var s=Math.abs(r-e.startangle),l=Math.abs(r-e.stopangle),c=s<l?s:l;(a=\"tan\"===i?k(t,n,o,c,0):T(t,n,o,c,Math.PI/2)).textPosAngle=r,g.push(a)}};if(f||h){for(m=4;m>=-4;m-=2)v(Math.PI*m,\"tan\");for(m=4;m>=-4;m-=2)v(Math.PI*(m+1),\"tan\")}if(f||p){for(m=4;m>=-4;m-=2)v(Math.PI*(m+1.5),\"rad\");for(m=4;m>=-4;m-=2)v(Math.PI*(m+.5),\"rad\")}}if(s||d||f){var y=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/y,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;g.push(a)}(d||p)&&((a=T(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,g.push(a)),(d||h)&&((a=k(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,g.push(a));for(var x=0,b=0,_=0;_<g.length;_++){var w=g[_].scale;if(b<w&&(b=w,x=_),!d&&b>=1)break}return g[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*g);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:M(a,o/e),rotate:A(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*g);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:M(a,o/e),rotate:A(i+Math.PI/2)}}function M(t,e){return Math.cos(e)-t*e}function A(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function C(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function L(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=P(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,c,u=(l=t.r,c=t.trace.aspectratio,l/(void 0===c?1:c)),f=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(f+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?f*=2:-1!==a.title.position.indexOf(\"right\")&&(f+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=f/t.titleBox.width,n=I(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function I(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function P(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function z(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=I(i,e));var c=s/2,u=l/2;\"funnelarea\"!==a.type||a.scalegroup||(u/=a.aspectratio),i.r=Math.min(c,u)/(1+P(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=I(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var c,u;i.aspectratio>1?(c=r.r,u=c/i.aspectratio):(u=r.r,c=u*i.aspectratio),c*=(1+i.baseratio)/2,l=c*u}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function O(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function D(t,e,r){var n=t._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&\"none\"!==o){var s,c=o.split(\"+\"),u=function(t){return-1!==c.indexOf(t)},f=u(\"label\"),h=u(\"text\"),p=u(\"value\"),d=u(\"percent\"),g=n.separators;if(s=f?[e.label]:[],h){var v=m.getFirstFilled(i.text,e.pts);y(v)&&s.push(v)}p&&s.push(m.formatPieValue(e.v,g)),d&&s.push(m.formatPiePercent(e.v/r.vTotal,g)),e.text=s.join(\"<br>\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:m.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:m.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=m.getFirstFilled(i.text,e.pts);(y(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}e.exports={plot:function(t,e){var r=t._fullLayout,a=r._size;d(\"pie\",r),_(e,t),z(e,a);var h=l.makeTraceGroups(r._pielayer,e,\"trace\").each((function(e){var h=n.select(this),d=e[0],g=d.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=m.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,c=\"px0\",u=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,c=\"px1\",u=\"px0\"}for(n=O(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[c]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=O(a,s),r.midangle=s,s+=l*r.v/2,n=O(a,s),r.stopangle=s,r[u]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),h.attr(\"stroke-linejoin\",\"round\"),h.each((function(){var v=n.select(this).selectAll(\"g.slice\").data(e);v.enter().append(\"g\").classed(\"slice\",!0),v.exit().remove();var y=[[[],[]],[[],[]]],_=!1;v.each((function(i,a){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=g.index,y[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var o=d.cx,c=d.cy,u=n.select(this),h=u.selectAll(\"path.surface\").data([i]);if(h.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),u.call(x,t,e),g.pull){var v=+m.castOption(g.pull,i.pts)||0;v>0&&(o+=v*i.pxmid[0],c+=v*i.pxmid[1])}i.cxFinal=o,i.cyFinal=c;var T=g.hole;if(i.v===d.vTotal){var k=\"M\"+(o+i.px0[0])+\",\"+(c+i.px0[1])+L(i.px0,i.pxmid,!0,1)+L(i.pxmid,i.px0,!0,1)+\"Z\";T?h.attr(\"d\",\"M\"+(o+T*i.px0[0])+\",\"+(c+T*i.px0[1])+L(i.px0,i.pxmid,!1,T)+L(i.pxmid,i.px0,!1,T)+\"Z\"+k):h.attr(\"d\",k)}else{var M=L(i.px0,i.px1,!0,1);if(T){var A=1-T;h.attr(\"d\",\"M\"+(o+T*i.px1[0])+\",\"+(c+T*i.px1[1])+L(i.px1,i.px0,!1,T)+\"l\"+A*i.px0[0]+\",\"+A*i.px0[1]+M+\"Z\")}else h.attr(\"d\",\"M\"+o+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+M+\"Z\")}D(t,i,d);var S=m.castOption(g.textposition,i.pts),E=u.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==S?[0]:[]);E.enter().append(\"g\").classed(\"slicetext\",!0),E.exit().remove(),E.each((function(){var u=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===S?function(t,e,r){var n=m.castOption(t.outsidetextfont.color,e.pts)||m.castOption(t.textfont.color,e.pts)||r.color,i=m.castOption(t.outsidetextfont.family,e.pts)||m.castOption(t.textfont.family,e.pts)||r.family,a=m.castOption(t.outsidetextfont.size,e.pts)||m.castOption(t.textfont.size,e.pts)||r.size;return{color:n,family:i,size:a}}(g,i,r.font):b(g,i,r.font));u.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var v,y=s.bBox(u.node());if(\"outside\"===S)v=C(y,i);else if(v=w(y,i,d),\"auto\"===S&&v.scale<1){var x=l.ensureUniformFontSize(t,g.outsidetextfont);u.call(s.font,x),v=C(y=s.bBox(u.node()),i)}var T=v.textPosAngle,k=void 0===T?i.pxmid:O(d.r,T);if(v.targetX=o+k[0]*v.rCenter+(v.x||0),v.targetY=c+k[1]*v.rCenter+(v.y||0),R(v,y),v.outside){var M=v.targetY;i.yLabelMin=M-y.height/2,i.yLabelMid=M,i.yLabelMax=M+y.height/2,i.labelExtraX=0,i.labelExtraY=0,_=!0}v.fontSize=h.size,p(g.type,v,r),e[a].transform=v,u.attr(\"transform\",l.getTextTransform(v))}))}function L(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*d.r+\",\"+n*d.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var T=n.select(this).selectAll(\"g.titletext\").data(g.title.text?[0]:[]);if(T.enter().append(\"g\").classed(\"titletext\",!0),T.exit().remove(),T.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=g.title.text;g._meta&&(i=l.templateString(i,g._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,g.title.font).call(f.convertToTspans,t),e=\"middle center\"===g.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(d):L(d,a),r.attr(\"transform\",u(e.x,e.y)+c(Math.min(1,e.scale))+u(e.tx,e.ty))})),_&&function(t,e){var r,n,i,a,o,s,l,c,u,f,h,p,d;function g(t,e){return t.pxmid[1]-e.pxmid[1]}function v(t,e){return e.pxmid[1]-t.pxmid[1]}function y(t,r){r||(r={});var i,c,u,h,p=r.labelExtraY+(n?r.yLabelMax:r.yLabelMin),d=n?t.yLabelMin:t.yLabelMax,g=n?t.yLabelMax:t.yLabelMin,v=t.cyFinal+o(t.px0[1],t.px1[1]),y=p-d;if(y*l>0&&(t.labelExtraY=y),Array.isArray(e.pull))for(c=0;c<f.length;c++)(u=f[c])===t||(m.castOption(e.pull,t.pts)||0)>=(m.castOption(e.pull,u.pts)||0)||((t.pxmid[1]-u.pxmid[1])*l>0?(y=u.cyFinal+o(u.px0[1],u.px1[1])-d-t.labelExtraY)*l>0&&(t.labelExtraY+=y):(g+t.labelExtraY-v)*l>0&&(i=3*s*Math.abs(c-f.indexOf(t)),(h=u.cxFinal+a(u.px0[0],u.px1[0])+i-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*s>0&&(t.labelExtraX+=h)))}for(n=0;n<2;n++)for(i=n?g:v,o=n?Math.max:Math.min,l=n?1:-1,r=0;r<2;r++){for(a=r?Math.max:Math.min,s=r?1:-1,(c=t[n][r]).sort(i),u=t[1-n][r],f=u.concat(c),p=[],h=0;h<c.length;h++)void 0!==c[h].yLabelMid&&p.push(c[h]);for(d=!1,h=0;n&&h<u.length;h++)if(void 0!==u[h].yLabelMid){d=u[h];break}for(h=0;h<p.length;h++){var x=h&&p[h-1];d&&!h&&(x=d),y(p[h],x)}}}(y,g),function(t,e){t.each((function(t){var r=n.select(this);if(t.labelExtraX||t.labelExtraY){var i=r.select(\"g.slicetext text\");t.transform.targetX+=t.labelExtraX,t.transform.targetY+=t.labelExtraY,i.attr(\"transform\",l.getTextTransform(t.transform));var a=t.cxFinal+t.pxmid[0],s=\"M\"+a+\",\"+(t.cyFinal+t.pxmid[1]),c=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var u=t.labelExtraX*t.pxmid[1]/t.pxmid[0],f=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);Math.abs(u)>Math.abs(f)?s+=\"l\"+f*t.pxmid[0]/t.pxmid[1]+\",\"+f+\"H\"+(a+t.labelExtraX+c):s+=\"l\"+t.labelExtraX+\",\"+u+\"v\"+(f-u)+\"h\"+c}else s+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+c;l.ensureSingle(r,\"path\",\"textline\").call(o.stroke,e.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,e.outsidetextfont.size/8),d:s,fill:\"none\"})}else r.select(\"path.textline\").remove()}))}(v,g),_&&g.automargin){var k=s.bBox(h.node()),M=g.domain,A=a.w*(M.x[1]-M.x[0]),S=a.h*(M.y[1]-M.y[0]),E=(.5*A-d.r)/a.w,I=(.5*S-d.r)/a.h;i.autoMargin(t,\"pie.\"+g.uid+\".automargin\",{xl:M.x[0]-E,xr:M.x[1]+E,yb:M.y[0]-I,yt:M.y[1]+I,l:Math.max(d.cx-d.r-k.left,0),r:Math.max(k.right-(d.cx+d.r),0),b:Math.max(k.bottom-(d.cy+d.r),0),t:Math.max(d.cy-d.r-k.top,0),pad:5})}}))}));setTimeout((function(){h.selectAll(\"tspan\").each((function(){var t=n.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))}))}),0)},formatSliceLabel:D,transformInsideText:w,determineInsideTextFont:b,positionTitleOutside:L,prerenderTitles:_,layoutAreas:z,attachFxHandlers:x,computeTransform:R}},{\"../../components/color\":643,\"../../components/drawing\":665,\"../../components/fx\":683,\"../../lib\":778,\"../../lib/svg_text_utils\":803,\"../../plots/plots\":891,\"../bar/constants\":923,\"../bar/uniform_text\":937,\"./event_data\":1165,\"./helpers\":1166,d3:169}],1171:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"./style_one\"),a=t(\"../bar/uniform_text\").resizeText;e.exports=function(t){var e=t._fullLayout._pielayer.selectAll(\".trace\");a(t,e,\"pie\"),e.each((function(t){var e=t[0].trace,r=n.select(this);r.style({opacity:e.opacity}),r.selectAll(\"path.surface\").each((function(t){n.select(this).call(i,t,e)}))}))}},{\"../bar/uniform_text\":937,\"./style_one\":1172,d3:169}],1172:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"./helpers\").castOption;e.exports=function(t,e,r){var a=r.marker.line,o=i(a.color,e.pts)||n.defaultLine,s=i(a.width,e.pts)||0;t.style(\"stroke-width\",s).call(n.fill,e.color).call(n.stroke,o)}},{\"../../components/color\":643,\"./helpers\":1166}],1173:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\");e.exports={x:n.x,y:n.y,xy:{valType:\"data_array\",editType:\"calc\"},indices:{valType:\"data_array\",editType:\"calc\"},xbounds:{valType:\"data_array\",editType:\"calc\"},ybounds:{valType:\"data_array\",editType:\"calc\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1,editType:\"calc\"},blend:{valType:\"boolean\",dflt:null,editType:\"calc\"},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5,editType:\"calc\"},sizemax:{valType:\"number\",min:.1,dflt:20,editType:\"calc\"},border:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},arearatio:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},transforms:void 0}},{\"../scatter/attributes\":1187}],1174:[function(t,e,r){\"use strict\";var n=t(\"gl-pointcloud2d\"),i=t(\"../../lib/str2rgbarray\"),a=t(\"../../plots/cartesian/autorange\").findExtremes,o=t(\"../scatter/get_trace_color\");function s(t,e){this.scene=t,this.uid=e,this.type=\"pointcloud\",this.pickXData=[],this.pickYData=[],this.xData=[],this.yData=[],this.textLabels=[],this.color=\"rgb(0, 0, 0)\",this.name=\"\",this.hoverinfo=\"all\",this.idToIndex=new Int32Array(0),this.bounds=[0,0,0,0],this.pointcloudOptions={positions:new Float32Array(0),idToIndex:this.idToIndex,sizemin:.5,sizemax:12,color:[0,0,0,1],areaRatio:1,borderColor:[0,0,0,1]},this.pointcloud=n(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}var l=s.prototype;l.handlePick=function(t){var e=this.idToIndex[t.pointId];return{trace:this,dataCoord:t.dataCoord,traceCoord:this.pickXYData?[this.pickXYData[2*e],this.pickXYData[2*e+1]]:[this.pickXData[e],this.pickYData[e]],textLabel:Array.isArray(this.textLabels)?this.textLabels[e]:this.textLabels,color:this.color,name:this.name,pointIndex:e,hoverinfo:this.hoverinfo}},l.update=function(t){this.index=t.index,this.textLabels=t.text,this.name=t.name,this.hoverinfo=t.hoverinfo,this.bounds=[1/0,1/0,-1/0,-1/0],this.updateFast(t),this.color=o(t,{})},l.updateFast=function(t){var e,r,n,o,s,l,c=this.xData=this.pickXData=t.x,u=this.yData=this.pickYData=t.y,f=this.pickXYData=t.xy,h=t.xbounds&&t.ybounds,p=t.indices,d=this.bounds;if(f){if(n=f,e=f.length>>>1,h)d[0]=t.xbounds[0],d[2]=t.xbounds[1],d[1]=t.ybounds[0],d[3]=t.ybounds[1];else for(l=0;l<e;l++)o=n[2*l],s=n[2*l+1],o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);if(p)r=p;else for(r=new Int32Array(e),l=0;l<e;l++)r[l]=l}else for(e=c.length,n=new Float32Array(2*e),r=new Int32Array(e),l=0;l<e;l++)o=c[l],s=u[l],r[l]=l,n[2*l]=o,n[2*l+1]=s,o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);this.idToIndex=r,this.pointcloudOptions.idToIndex=r,this.pointcloudOptions.positions=n;var g=i(t.marker.color),m=i(t.marker.border.color),v=t.opacity*t.marker.opacity;g[3]*=v,this.pointcloudOptions.color=g;var y=t.marker.blend;if(null===y){y=c.length<100||u.length<100}this.pointcloudOptions.blend=y,m[3]*=v,this.pointcloudOptions.borderColor=m;var x=t.marker.sizemin,b=Math.max(t.marker.sizemax,t.marker.sizemin);this.pointcloudOptions.sizeMin=x,this.pointcloudOptions.sizeMax=b,this.pointcloudOptions.areaRatio=t.marker.border.arearatio,this.pointcloud.update(this.pointcloudOptions);var _=this.scene.xaxis,w=this.scene.yaxis,T=b/2||.5;t._extremes[_._id]=a(_,[d[0],d[2]],{ppad:T}),t._extremes[w._id]=a(w,[d[1],d[3]],{ppad:T})},l.dispose=function(){this.pointcloud.dispose()},e.exports=function(t,e){var r=new s(t,e.uid);return r.update(e),r}},{\"../../lib/str2rgbarray\":802,\"../../plots/cartesian/autorange\":827,\"../scatter/get_trace_color\":1197,\"gl-pointcloud2d\":324}],1175:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./attributes\");e.exports=function(t,e,r){function a(r,a){return n.coerce(t,e,i,r,a)}a(\"x\"),a(\"y\"),a(\"xbounds\"),a(\"ybounds\"),t.xy&&t.xy instanceof Float32Array&&(e.xy=t.xy),t.indices&&t.indices instanceof Int32Array&&(e.indices=t.indices),a(\"text\"),a(\"marker.color\",r),a(\"marker.opacity\"),a(\"marker.blend\"),a(\"marker.sizemin\"),a(\"marker.sizemax\"),a(\"marker.border.color\",r),a(\"marker.border.arearatio\"),e._length=null}},{\"../../lib\":778,\"./attributes\":1173}],1176:[function(t,e,r){\"use 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n=t(\"../../plots/font_attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../components/color/attributes\"),o=t(\"../../components/fx/attributes\"),s=t(\"../../plots/domain\").attributes,l=t(\"../../plots/template_attributes\").hovertemplateAttrs,c=t(\"../../components/colorscale/attributes\"),u=t(\"../../plot_api/plot_template\").templatedArray,f=t(\"../../lib/extend\").extendFlat,h=t(\"../../plot_api/edit_types\").overrideAll;t(\"../../constants/docs\").FORMAT_LINK;(e.exports=h({hoverinfo:f({},i.hoverinfo,{flags:[],arrayOk:!1}),hoverlabel:o.hoverlabel,domain:s({name:\"sankey\",trace:!0}),orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],dflt:\"h\"},valueformat:{valType:\"string\",dflt:\".3s\"},valuesuffix:{valType:\"string\",dflt:\"\"},arrangement:{valType:\"enumerated\",values:[\"snap\",\"perpendicular\",\"freeform\",\"fixed\"],dflt:\"snap\"},textfont:n({}),customdata:void 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o=n[t=i[w]],s=0,l={};for(T=0;T<o.length;T++)l[(e=o[T]).label]||(l[e.label]=0),l[e.label]+=e.value,s+=e.value;for(T=0;T<o.length;T++)(e=o[T]).flow={value:s,labelConcentration:l[e.label]/s,concentration:e.value/s,links:o},e.concentrationscale&&(e.color=a(e.concentrationscale(e.flow.labelConcentration)))}var c=0;for(w=0;w<r.sourceLinks.length;w++)c+=r.sourceLinks[w].value;for(w=0;w<r.sourceLinks.length;w++)(e=r.sourceLinks[w]).concentrationOut=e.value/c;var u=0;for(w=0;w<r.targetLinks.length;w++)u+=r.targetLinks[w].value;for(w=0;w<r.targetLinks.length;w++)(e=r.targetLinks[w]).concenrationIn=e.value/u}}(),s.node.x.length&&s.node.y.length){for(_=0;_<Math.min(s.node.x.length,s.node.y.length,k.nodes.length);_++)if(s.node.x[_]&&s.node.y[_]){var C=[s.node.x[_]*g,s.node.y[_]*v];k.nodes[_].x0=C[0]-d/2,k.nodes[_].x1=C[0]+d/2;var L=k.nodes[_].y1-k.nodes[_].y0;k.nodes[_].y0=C[1]-L/2,k.nodes[_].y1=C[1]+L/2}if(\"snap\"===s.arrangement)!function(t){t.forEach((function(t){var e,r,n,i=0,a=t.length;for(t.sort((function(t,e){return t.y0-e.y0})),n=0;n<a;++n)(e=t[n]).y0>=i||(r=i-e.y0)>1e-6&&(e.y0+=r,e.y1+=r),i=e.y1+p}))}(function(t){var e,r,n=t.map((function(t,e){return{x0:t.x0,index:e}})).sort((function(t,e){return t.x0-e.x0})),i=[],a=-1,o=-1/0;for(_=0;_<n.length;_++){var s=t[n[_].index];s.x0>o+d&&(a+=1,e=s.x0),o=s.x0,i[a]||(i[a]=[]),i[a].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return i}(y=k.nodes));i.update(k)}return{circular:b,key:r,trace:s,guid:f.randstr(),horizontal:h,width:g,height:v,nodePad:s.node.pad,nodeLineColor:s.node.line.color,nodeLineWidth:s.node.line.width,linkLineColor:s.link.line.color,linkLineWidth:s.link.line.width,valueFormat:s.valueformat,valueSuffix:s.valuesuffix,textFont:s.textfont,translateX:u.x[0]*t.width+t.margin.l,translateY:t.height-u.y[1]*t.height+t.margin.t,dragParallel:h?v:g,dragPerpendicular:h?g:v,arrangement:s.arrangement,sankey:i,graph:k,forceLayouts:{},interactionState:{dragInProgress:!1,hovered:!1}}}function b(t,e,r){var n=a(e.color),i=e.source.label+\"|\"+e.target.label+\"__\"+r;return e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:i,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:o.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:_,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function _(){return function(t){if(t.link.circular)return e=t.link,r=e.width/2,n=e.circularPathData,\"top\"===e.circularLinkType?\"M \"+n.targetX+\" \"+(n.targetY+r)+\" L\"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 1 \"+(n.rightFullExtent-r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 1 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 0 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 0 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 0 \"+n.rightInnerExtent+\" \"+(n.targetY-r)+\"L\"+n.targetX+\" \"+(n.targetY-r)+\"Z\":\"M \"+n.targetX+\" \"+(n.targetY-r)+\" L\"+n.rightInnerExtent+\" \"+(n.targetY-r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 0 \"+(n.rightFullExtent-r)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 0 \"+n.rightInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 0 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 1 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 1 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"L\"+n.targetX+\" \"+(n.targetY+r)+\"Z\";var e,r,n,i=t.link.source.x1,a=t.link.target.x0,o=v(i,a),s=o(.5),l=o(.5),c=t.link.y0-t.link.width/2,u=t.link.y0+t.link.width/2,f=t.link.y1-t.link.width/2,h=t.link.y1+t.link.width/2;return\"M\"+i+\",\"+c+\"C\"+s+\",\"+c+\" \"+l+\",\"+f+\" \"+a+\",\"+f+\"L\"+a+\",\"+h+\"C\"+l+\",\"+h+\" \"+s+\",\"+u+\" \"+i+\",\"+u+\"Z\"}}function w(t,e){var r=a(e.color),i=n.nodePadAcross,s=t.nodePad/2;e.dx=e.x1-e.x0,e.dy=e.y1-e.y0;var l=e.dx,c=Math.max(.5,e.dy),u=\"node_\"+e.pointNumber;return e.group&&(u=f.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:u,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(l),visibleHeight:c,zoneX:-i,zoneY:-s,zoneWidth:l+2*i,zoneHeight:c+2*s,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:o.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,u].join(\"_\"),interactionState:t.interactionState,figure:t}}function T(t){t.attr(\"transform\",(function(t){return h(t.node.x0.toFixed(3),t.node.y0.toFixed(3))}))}function k(t){t.call(T)}function M(t,e){t.call(k),e.attr(\"d\",_())}function A(t){t.attr(\"width\",(function(t){return t.node.x1-t.node.x0})).attr(\"height\",(function(t){return t.visibleHeight}))}function S(t){return t.link.width>1||t.linkLineWidth>0}function E(t){return h(t.translateX,t.translateY)+(t.horizontal?\"matrix(1 0 0 1 0 0)\":\"matrix(0 1 1 0 0 0)\")}function C(t){return h(t.horizontal?0:t.labelY,t.horizontal?t.labelY:0)}function L(t){return i.svg.line()([[t.horizontal?t.left?-t.sizeAcross:t.visibleWidth+n.nodeTextOffsetHorizontal:n.nodeTextOffsetHorizontal,0],[t.horizontal?t.left?-n.nodeTextOffsetHorizontal:t.sizeAcross:t.visibleHeight-n.nodeTextOffsetHorizontal,0]])}function I(t){return t.horizontal?\"matrix(1 0 0 1 0 0)\":\"matrix(0 1 1 0 0 0)\"}function P(t){return t.horizontal?\"scale(1 1)\":\"scale(-1 1)\"}function z(t){return t.darkBackground&&!t.horizontal?\"rgb(255,255,255)\":\"rgb(0,0,0)\"}function O(t){return t.horizontal&&t.left?\"100%\":\"0%\"}function D(t,e,r){t.on(\".basic\",null).on(\"mouseover.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.hover(this,t,e),t.interactionState.hovered=[this,t])})).on(\"mousemove.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.follow(this,t),t.interactionState.hovered=[this,t])})).on(\"mouseout.basic\",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.unhover(this,t,e),t.interactionState.hovered=!1)})).on(\"click.basic\",(function(t){t.interactionState.hovered&&(r.unhover(this,t,e),t.interactionState.hovered=!1),t.interactionState.dragInProgress||t.partOfGroup||r.select(this,t,e)}))}function R(t,e,r,a){var o=i.behavior.drag().origin((function(t){return{x:t.node.x0+t.visibleWidth/2,y:t.node.y0+t.visibleHeight/2}})).on(\"dragstart\",(function(i){if(\"fixed\"!==i.arrangement&&(f.ensureSingle(a._fullLayout._infolayer,\"g\",\"dragcover\",(function(t){a._fullLayout._dragCover=t})),f.raiseToTop(this),i.interactionState.dragInProgress=i.node,B(i.node),i.interactionState.hovered&&(r.nodeEvents.unhover.apply(0,i.interactionState.hovered),i.interactionState.hovered=!1),\"snap\"===i.arrangement)){var o=i.traceId+\"|\"+i.key;i.forceLayouts[o]?i.forceLayouts[o].alpha(1):function(t,e,r,i){!function(t){for(var e=0;e<t.length;e++)t[e].y=(t[e].y0+t[e].y1)/2,t[e].x=(t[e].x0+t[e].x1)/2}(r.graph.nodes);var a=r.graph.nodes.filter((function(t){return t.originalX===r.node.originalX})).filter((function(t){return!t.partOfGroup}));r.forceLayouts[e]=u.forceSimulation(a).alphaDecay(0).force(\"collide\",u.forceCollide().radius((function(t){return t.dy/2+r.nodePad/2})).strength(1).iterations(n.forceIterations)).force(\"constrain\",function(t,e,r,i){return function(){for(var t=0,a=0;a<r.length;a++){var o=r[a];o===i.interactionState.dragInProgress?(o.x=o.lastDraggedX,o.y=o.lastDraggedY):(o.vx=(o.originalX-o.x)/n.forceTicksPerFrame,o.y=Math.min(i.size-o.dy/2,Math.max(o.dy/2,o.y))),t=Math.max(t,Math.abs(o.vx),Math.abs(o.vy))}!i.interactionState.dragInProgress&&t<.1&&i.forceLayouts[e].alpha()>0&&i.forceLayouts[e].alpha(0)}}(0,e,a,r)).stop()}(0,o,i),function(t,e,r,i,a){window.requestAnimationFrame((function o(){var s;for(s=0;s<n.forceTicksPerFrame;s++)r.forceLayouts[i].tick();if(function(t){for(var e=0;e<t.length;e++)t[e].y0=t[e].y-t[e].dy/2,t[e].y1=t[e].y0+t[e].dy,t[e].x0=t[e].x-t[e].dx/2,t[e].x1=t[e].x0+t[e].dx}(r.graph.nodes),r.sankey.update(r.graph),M(t.filter(N(r)),e),r.forceLayouts[i].alpha()>0)window.requestAnimationFrame(o);else{var l=r.node.originalX;r.node.x0=l-r.visibleWidth/2,r.node.x1=l+r.visibleWidth/2,F(r,a)}}))}(t,e,i,o,a)}})).on(\"drag\",(function(r){if(\"fixed\"!==r.arrangement){var n=i.event.x,a=i.event.y;\"snap\"===r.arrangement?(r.node.x0=n-r.visibleWidth/2,r.node.x1=n+r.visibleWidth/2,r.node.y0=a-r.visibleHeight/2,r.node.y1=a+r.visibleHeight/2):(\"freeform\"===r.arrangement&&(r.node.x0=n-r.visibleWidth/2,r.node.x1=n+r.visibleWidth/2),a=Math.max(0,Math.min(r.size-r.visibleHeight/2,a)),r.node.y0=a-r.visibleHeight/2,r.node.y1=a+r.visibleHeight/2),B(r.node),\"snap\"!==r.arrangement&&(r.sankey.update(r.graph),M(t.filter(N(r)),e))}})).on(\"dragend\",(function(t){if(\"fixed\"!==t.arrangement){t.interactionState.dragInProgress=!1;for(var e=0;e<t.node.childrenNodes.length;e++)t.node.childrenNodes[e].x=t.node.x,t.node.childrenNodes[e].y=t.node.y;\"snap\"!==t.arrangement&&F(t,a)}}));t.on(\".drag\",null).call(o)}function F(t,e){for(var r=[],n=[],i=0;i<t.graph.nodes.length;i++){var a=(t.graph.nodes[i].x0+t.graph.nodes[i].x1)/2,o=(t.graph.nodes[i].y0+t.graph.nodes[i].y1)/2;r.push(a/t.figure.width),n.push(o/t.figure.height)}y.call(\"_guiRestyle\",e,{\"node.x\":[r],\"node.y\":[n]},t.trace.index).then((function(){e._fullLayout._dragCover&&e._fullLayout._dragCover.remove()}))}function B(t){t.lastDraggedX=t.x0+t.dx/2,t.lastDraggedY=t.y0+t.dy/2}function N(t){return function(e){return e.node.originalX===t.node.originalX}}e.exports=function(t,e,r,l,c){var u=!1;f.ensureSingle(t._fullLayout._infolayer,\"g\",\"first-render\",(function(){u=!0}));var h=t._fullLayout._dragCover,p=r.filter((function(t){return m(t).trace.visible})).map(x.bind(null,l)),v=e.selectAll(\".\"+n.cn.sankey).data(p,d);v.exit().remove(),v.enter().append(\"g\").classed(n.cn.sankey,!0).style(\"box-sizing\",\"content-box\").style(\"position\",\"absolute\").style(\"left\",0).style(\"shape-rendering\",\"geometricPrecision\").style(\"pointer-events\",\"auto\").attr(\"transform\",E),v.each((function(e,r){t._fullData[r]._sankey=e;var n=\"bgsankey-\"+e.trace.uid+\"-\"+r;f.ensureSingle(t._fullLayout._draggers,\"rect\",n),t._fullData[r]._bgRect=i.select(\".\"+n),t._fullData[r]._bgRect.style(\"pointer-events\",\"all\").attr(\"width\",e.width).attr(\"height\",e.height).attr(\"x\",e.translateX).attr(\"y\",e.translateY).classed(\"bgsankey\",!0).style({fill:\"transparent\",\"stroke-width\":0})})),v.transition().ease(n.ease).duration(n.duration).attr(\"transform\",E);var y=v.selectAll(\".\"+n.cn.sankeyLinks).data(g,d);y.enter().append(\"g\").classed(n.cn.sankeyLinks,!0).style(\"fill\",\"none\");var k=y.selectAll(\".\"+n.cn.sankeyLink).data((function(t){return t.graph.links.filter((function(t){return t.value})).map(b.bind(null,t))}),d);k.enter().append(\"path\").classed(n.cn.sankeyLink,!0).call(D,v,c.linkEvents),k.style(\"stroke\",(function(t){return S(t)?o.tinyRGB(a(t.linkLineColor)):t.tinyColorHue})).style(\"stroke-opacity\",(function(t){return S(t)?o.opacity(t.linkLineColor):t.tinyColorAlpha})).style(\"fill\",(function(t){return t.tinyColorHue})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})).style(\"stroke-width\",(function(t){return S(t)?t.linkLineWidth:1})).attr(\"d\",_()),k.style(\"opacity\",(function(){return t._context.staticPlot||u||h?1:0})).transition().ease(n.ease).duration(n.duration).style(\"opacity\",1),k.exit().transition().ease(n.ease).duration(n.duration).style(\"opacity\",0).remove();var M=v.selectAll(\".\"+n.cn.sankeyNodeSet).data(g,d);M.enter().append(\"g\").classed(n.cn.sankeyNodeSet,!0),M.style(\"cursor\",(function(t){switch(t.arrangement){case\"fixed\":return\"default\";case\"perpendicular\":return\"ns-resize\";default:return\"move\"}}));var F=M.selectAll(\".\"+n.cn.sankeyNode).data((function(t){var e=t.graph.nodes;return function(t){var e,r=[];for(e=0;e<t.length;e++)t[e].originalX=(t[e].x0+t[e].x1)/2,t[e].originalY=(t[e].y0+t[e].y1)/2,-1===r.indexOf(t[e].originalX)&&r.push(t[e].originalX);for(r.sort((function(t,e){return t-e})),e=0;e<t.length;e++)t[e].originalLayerIndex=r.indexOf(t[e].originalX),t[e].originalLayer=t[e].originalLayerIndex/(r.length-1)}(e),e.map(w.bind(null,t))}),d);F.enter().append(\"g\").classed(n.cn.sankeyNode,!0).call(T).style(\"opacity\",(function(e){return!t._context.staticPlot&&!u||e.partOfGroup?0:1})),F.call(D,v,c.nodeEvents).call(R,k,c,t),F.transition().ease(n.ease).duration(n.duration).call(T).style(\"opacity\",(function(t){return t.partOfGroup?0:1})),F.exit().transition().ease(n.ease).duration(n.duration).style(\"opacity\",0).remove();var B=F.selectAll(\".\"+n.cn.nodeRect).data(g);B.enter().append(\"rect\").classed(n.cn.nodeRect,!0).call(A),B.style(\"stroke-width\",(function(t){return t.nodeLineWidth})).style(\"stroke\",(function(t){return o.tinyRGB(a(t.nodeLineColor))})).style(\"stroke-opacity\",(function(t){return o.opacity(t.nodeLineColor)})).style(\"fill\",(function(t){return t.tinyColorHue})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),B.transition().ease(n.ease).duration(n.duration).call(A);var N=F.selectAll(\".\"+n.cn.nodeCapture).data(g);N.enter().append(\"rect\").classed(n.cn.nodeCapture,!0).style(\"fill-opacity\",0),N.attr(\"x\",(function(t){return t.zoneX})).attr(\"y\",(function(t){return t.zoneY})).attr(\"width\",(function(t){return t.zoneWidth})).attr(\"height\",(function(t){return t.zoneHeight}));var 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/line_shape_defaults\"),c=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}p(\"carpet\"),e.xaxis=\"x\",e.yaxis=\"y\";var d=p(\"a\"),g=p(\"b\"),m=Math.min(d.length,g.length);if(m){e._length=m,p(\"text\"),p(\"texttemplate\"),p(\"hovertext\"),p(\"mode\",m<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&(s(t,e,r,h,p),l(t,e,p),p(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,p,{gradient:!0}),a.hasText(e)&&c(t,e,h,p);var v=[];(a.hasMarkers(e)||a.hasText(e))&&(p(\"marker.maxdisplayed\"),v.push(\"points\")),p(\"fill\"),\"none\"!==e.fill&&(u(t,e,r,p),a.hasLines(e)||l(t,e,p)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||v.push(\"fills\"),\"fills\"!==p(\"hoveron\",v.join(\"+\")||\"points\")&&p(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,p)}else e.visible=!1}},{\"../../lib\":778,\"../scatter/constants\":1191,\"../scatter/fillcolor_defaults\":1195,\"../scatter/line_defaults\":1200,\"../scatter/line_shape_defaults\":1202,\"../scatter/marker_defaults\":1206,\"../scatter/subtypes\":1212,\"../scatter/text_defaults\":1213,\"./attributes\":1221}],1224:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){var a=n[i];return t.a=a.a,t.b=a.b,t.y=a.y,t}},{}],1225:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r={},n=e._carpet,i=n.ab2ij([t.a,t.b]),a=Math.floor(i[0]),o=i[0]-a,s=Math.floor(i[1]),l=i[1]-s,c=n.evalxy([],a,s,o,l);return r.yLabel=c[1].toFixed(3),r}},{}],1226:[function(t,e,r){\"use 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n=t(\"../scatter/plot\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../components/drawing\");e.exports=function(t,e,r,o){var s,l,c,u=r[0][0].carpet,f={xaxis:i.getFromId(t,u.xaxis||\"x\"),yaxis:i.getFromId(t,u.yaxis||\"y\"),plot:e.plot};for(n(t,f,r,o),s=0;s<r.length;s++)l=r[s][0].trace,c=o.selectAll(\"g.trace\"+l.uid+\" .js-line\"),a.setClipUrl(c,r[s][0].carpet._clipPathId,t)}},{\"../../components/drawing\":665,\"../../plots/cartesian/axes\":828,\"../scatter/plot\":1208}],1229:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scatter/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../components/colorscale/attributes\"),l=t(\"../../components/drawing/attributes\").dash,c=t(\"../../lib/extend\").extendFlat,u=t(\"../../plot_api/edit_types\").overrideAll,f=a.marker,h=a.line,p=f.line;e.exports=u({lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/text_defaults\"),l=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,i){return n.coerce(t,e,c,r,i)}var h,p=f(\"locations\");if(p&&p.length){var d,g=f(\"geojson\");(\"string\"==typeof g&&\"\"!==g||n.isPlainObject(g))&&(d=\"geojson-id\"),\"geojson-id\"===f(\"locationmode\",d)&&f(\"featureidkey\"),h=p.length}else{var m=f(\"lon\")||[],v=f(\"lat\")||[];h=Math.min(m.length,v.length)}h?(e._length=h,f(\"text\"),f(\"hovertext\"),f(\"hovertemplate\"),f(\"mode\"),i.hasLines(e)&&(o(t,e,r,u,f),f(\"connectgaps\")),i.hasMarkers(e)&&a(t,e,r,u,f,{gradient:!0}),i.hasText(e)&&(f(\"texttemplate\"),s(t,e,u,f)),f(\"fill\"),\"none\"!==e.fill&&l(t,e,r,f),n.coerceSelectionMarkerOpacity(e,f)):e.visible=!1}},{\"../../lib\":778,\"../scatter/fillcolor_defaults\":1195,\"../scatter/line_defaults\":1200,\"../scatter/marker_defaults\":1206,\"../scatter/subtypes\":1212,\"../scatter/text_defaults\":1213,\"./attributes\":1229}],1232:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){t.lon=e.lon,t.lat=e.lat,t.location=e.loc?e.loc:null;var a=n[i];return a.fIn&&a.fIn.properties&&(t.properties=a.fIn.properties),t}},{}],1233:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var i={},a=r[e.geo]._subplot.mockAxis,o=t.lonlat;return i.lonLabel=n.tickText(a,a.c2l(o[0]),!0).text,i.latLabel=n.tickText(a,a.c2l(o[1]),!0).text,i}},{\"../../plots/cartesian/axes\":828}],1234:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx\"),i=t(\"../../constants/numerical\").BADNUM,a=t(\"../scatter/get_trace_color\"),o=t(\"../../lib\").fillText,s=t(\"./attributes\");e.exports=function(t,e,r){var l=t.cd,c=l[0].trace,u=t.xa,f=t.ya,h=t.subplot,p=h.projection.isLonLatOverEdges,d=h.project;if(n.getClosest(l,(function(t){var n=t.lonlat;if(n[0]===i)return 1/0;if(p(n))return 1/0;var a=d(n),o=d([e,r]),s=Math.abs(a[0]-o[0]),l=Math.abs(a[1]-o[1]),c=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(s*s+l*l)-c,1-3/c)}),t),!1!==t.index){var g=l[t.index],m=g.lonlat,v=[u.c2p(m),f.c2p(m)],y=g.mrc||1;t.x0=v[0]-y,t.x1=v[0]+y,t.y0=v[1]-y,t.y1=v[1]+y,t.loc=g.loc,t.lon=m[0],t.lat=m[1];var x={};x[c.geo]={_subplot:h};var b=c._module.formatLabels(g,c,x);return 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T=y-_,k=y+w;p[v+u[0]]=x-i.c2l(T),p[v+u[1]]=i.c2l(k)-x,p[v+u[2]]=0,p[v+u[3]]=0,d=Math.min(d,y-_),g=Math.max(g,y+w)}}}h[a]={positions:r,errors:p,_bnds:[d,g]}}}return p(i,l),p(a,u),h},textPosition:function(t,e,r,n){var i,a=e._length,o={};if(f.hasMarkers(e)){var s=r.font,l=r.align,c=r.baseline;for(o.offset=new Array(a),i=0;i<a;i++){var u=n.sizes?n.sizes[i]:n.size,h=Array.isArray(s)?s[i].size:s.size,p=Array.isArray(l)?l.length>1?l[i]:l[0]:l,d=Array.isArray(c)?c.length>1?c[i]:c[0]:c,g=m[p],v=m[d],y=u?u/.8+1:0,x=-v*y-.5*v;o.offset[i]=[g*y/h,x/h]}}return o}}},{\"../../components/drawing\":665,\"../../components/fx/helpers\":679,\"../../constants/interactions\":752,\"../../lib\":778,\"../../lib/gl_format_color\":774,\"../../plots/cartesian/axis_ids\":831,\"../../registry\":911,\"../scatter/make_bubble_size_func\":1204,\"../scatter/subtypes\":1212,\"./constants\":1241,\"./helpers\":1246,\"color-normalize\":125,\"fast-isnumeric\":241,\"svg-path-sdf\":574}],1243:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../registry\"),a=t(\"./helpers\"),o=t(\"./attributes\"),s=t(\"../scatter/constants\"),l=t(\"../scatter/subtypes\"),c=t(\"../scatter/xy_defaults\"),u=t(\"../scatter/period_defaults\"),f=t(\"../scatter/marker_defaults\"),h=t(\"../scatter/line_defaults\"),p=t(\"../scatter/fillcolor_defaults\"),d=t(\"../scatter/text_defaults\");e.exports=function(t,e,r,g){function m(r,i){return n.coerce(t,e,o,r,i)}var v=!!t.marker&&a.isOpenSymbol(t.marker.symbol),y=l.isBubble(t),x=c(t,e,g,m);if(x){u(t,e,g,m);var b=x<s.PTS_LINESONLY?\"lines+markers\":\"lines\";m(\"text\"),m(\"hovertext\"),m(\"hovertemplate\"),m(\"mode\",b),l.hasLines(e)&&(m(\"connectgaps\"),h(t,e,r,g,m),m(\"line.shape\")),l.hasMarkers(e)&&(f(t,e,r,g,m),m(\"marker.line.width\",v||y?1:0)),l.hasText(e)&&(m(\"texttemplate\"),d(t,e,g,m));var _=(e.line||{}).color,w=(e.marker||{}).color;m(\"fill\"),\"none\"!==e.fill&&p(t,e,r,m);var T=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");T(t,e,_||w||r,{axis:\"y\"}),T(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,m)}else e.visible=!1}},{\"../../lib\":778,\"../../registry\":911,\"../scatter/constants\":1191,\"../scatter/fillcolor_defaults\":1195,\"../scatter/line_defaults\":1200,\"../scatter/marker_defaults\":1206,\"../scatter/period_defaults\":1207,\"../scatter/subtypes\":1212,\"../scatter/text_defaults\":1213,\"../scatter/xy_defaults\":1214,\"./attributes\":1239,\"./helpers\":1246}],1244:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\"),a=t(\"../../constants/interactions\").DESELECTDIM;e.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,c=l._scene,u=l.index,f=c.selectBatch[u],h=c.unselectBatch[u],p=c.textOptions[u],d=c.textSelectedOptions[u]||{},g=c.textUnselectedOptions[u]||{},m=n.extendFlat({},p);if(f.length||h.length){var v=d.color,y=g.color,x=p.color,b=Array.isArray(x);for(m.color=new Array(s._length),e=0;e<f.length;e++)r=f[e],m.color[r]=v||(b?x[r]:x);for(e=0;e<h.length;e++){r=h[e];var _=b?x[r]:x;m.color[r]=y||(v?_:i.addOpacity(_,a))}}c.glText[u].update(m)}}},{\"../../components/color\":643,\"../../constants/interactions\":752,\"../../lib\":778}],1245:[function(t,e,r){\"use strict\";var n=t(\"../scatter/format_labels\");e.exports=function(t,e,r){var i=t.i;return\"x\"in t||(t.x=e._x[i]),\"y\"in t||(t.y=e._y[i]),n(t,e,r)}},{\"../scatter/format_labels\":1196}],1246:[function(t,e,r){\"use strict\";var n=t(\"./constants\");r.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},r.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},{\"./constants\":1241}],1247:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../scatter/get_trace_color\");function o(t,e,r,o){var s=t.xa,l=t.ya,c=t.distance,u=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=Array.isArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=Array.isArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var g=d&&d.line;g&&(h.mlc=Array.isArray(g.color)?g.color[f]:g.color,h.mlw=i.isArrayOrTypedArray(g.width)?g.width[f]:g.width);var m=d&&d.gradient;m&&\"none\"!==m.type&&(h.mgt=Array.isArray(m.type)?m.type[f]:m.type,h.mgc=Array.isArray(m.color)?m.color[f]:m.color);var v=s.c2p(h.x,!0),y=l.c2p(h.y,!0),x=h.mrc||1,b=o.hoverlabel;b&&(h.hbg=Array.isArray(b.bgcolor)?b.bgcolor[f]:b.bgcolor,h.hbc=Array.isArray(b.bordercolor)?b.bordercolor[f]:b.bordercolor,h.hts=i.isArrayOrTypedArray(b.font.size)?b.font.size[f]:b.font.size,h.htc=Array.isArray(b.font.color)?b.font.color[f]:b.font.color,h.htf=Array.isArray(b.font.family)?b.font.family[f]:b.font.family,h.hnl=i.isArrayOrTypedArray(b.namelength)?b.namelength[f]:b.namelength);var _=o.hoverinfo;_&&(h.hi=Array.isArray(_)?_[f]:_);var w=o.hovertemplate;w&&(h.ht=Array.isArray(w)?w[f]:w);var T={};T[t.index]=h;var k=o._origX,M=o._origY,A=i.extendFlat({},t,{color:a(o,h),x0:v-x,x1:v+x,xLabelVal:k?k[f]:h.x,y0:y-x,y1:y+x,yLabelVal:M?M[f]:h.y,cd:T,distance:c,spikeDistance:u,hovertemplate:h.ht});return h.htx?A.text=h.htx:h.tx?A.text=h.tx:o.text&&(A.text=o.text),i.fillText(h,o,A),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(h,o,A),A}e.exports={hoverPoints:function(t,e,r,n){var i,a,s,l,c,u,f,h,p,d=t.cd,g=d[0].t,m=d[0].trace,v=t.xa,y=t.ya,x=g.x,b=g.y,_=v.c2p(e),w=y.c2p(r),T=t.distance;if(g.tree){var k=v.p2c(_-T),M=v.p2c(_+T),A=y.p2c(w-T),S=y.p2c(w+T);i=\"x\"===n?g.tree.range(Math.min(k,M),Math.min(y._rl[0],y._rl[1]),Math.max(k,M),Math.max(y._rl[0],y._rl[1])):g.tree.range(Math.min(k,M),Math.min(A,S),Math.max(k,M),Math.max(A,S))}else i=g.ids;var E=T;if(\"x\"===n)for(c=0;c<i.length;c++)s=x[i[c]],(u=Math.abs(v.c2p(s)-_))<E&&(E=u,f=y.c2p(b[i[c]])-w,p=Math.sqrt(u*u+f*f),a=i[c]);else for(c=i.length-1;c>-1;c--)s=x[i[c]],l=b[i[c]],u=v.c2p(s)-_,f=y.c2p(l)-w,(h=Math.sqrt(u*u+f*f))<E&&(E=p=h,a=i[c]);return t.index=a,t.distance=E,t.dxy=p,void 0===a?[t]:[o(t,x,b,m)]},calcHover:o}},{\"../../lib\":778,\"../../registry\":911,\"../scatter/get_trace_color\":1197}],1248:[function(t,e,r){\"use strict\";var n=t(\"./hover\");e.exports={moduleType:\"trace\",name:\"scattergl\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"gl\",\"regl\",\"cartesian\",\"symbols\",\"errorBarsOK\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../scatter/cross_trace_defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),hoverPoints:n.hoverPoints,selectPoints:t(\"./select\"),meta:{}}},{\"../../plots/cartesian\":841,\"../scatter/cross_trace_defaults\":1193,\"../scatter/marker_colorbar\":1205,\"./attributes\":1239,\"./calc\":1240,\"./defaults\":1243,\"./format_labels\":1245,\"./hover\":1247,\"./plot\":1249,\"./select\":1251}],1249:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"regl-line2d\"),a=t(\"regl-error2d\"),o=t(\"gl-text\"),s=t(\"../../lib\"),l=t(\"../../components/dragelement/helpers\").selectMode,c=t(\"../../lib/prepare_regl\"),u=t(\"../scatter/subtypes\"),f=t(\"../scatter/link_traces\"),h=t(\"./edit_style\").styleTextSelection;function p(t,e,r){var n=t._size,i=t.width,a=t.height;return[n.l+e.domain[0]*n.w,n.b+r.domain[0]*n.h,i-n.r-(1-e.domain[1])*n.w,a-n.t-(1-r.domain[1])*n.h]}e.exports=function(t,e,r){if(r.length){var d,g,m=t._fullLayout,v=e._scene,y=e.xaxis,x=e.yaxis;if(v)if(c(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"])){var b=v.count,_=m._glcanvas.data()[0].regl;if(f(t,e,r),v.dirty){if(!0===v.error2d&&(v.error2d=a(_)),!0===v.line2d&&(v.line2d=i(_)),!0===v.scatter2d&&(v.scatter2d=n(_,{constPointSize:!0})),!0===v.fill2d&&(v.fill2d=i(_)),!0===v.glText)for(v.glText=new Array(b),d=0;d<b;d++)v.glText[d]=new o(_);if(v.glText){if(b>v.glText.length){var w=b-v.glText.length;for(d=0;d<w;d++)v.glText.push(new o(_))}else if(b<v.glText.length){var T=v.glText.length-b;v.glText.splice(b,T).forEach((function(t){t.destroy()}))}for(d=0;d<b;d++)v.glText[d].update(v.textOptions[d])}if(v.line2d&&(v.line2d.update(v.lineOptions),v.lineOptions=v.lineOptions.map((function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t})),v.line2d.update(v.lineOptions)),v.error2d){var k=(v.errorXOptions||[]).concat(v.errorYOptions||[]);v.error2d.update(k)}v.scatter2d&&v.scatter2d.update(v.markerOptions),v.fillOrder=s.repeat(null,b),v.fill2d&&(v.fillOptions=v.fillOptions.map((function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var i,a,o=n[0],s=o.trace,l=o.t,c=v.lineOptions[e],u=[];s._ownfill&&u.push(e),s._nexttrace&&u.push(e+1),u.length&&(v.fillOrder[e]=u);var f,h,p=[],d=c&&c.positions||l.positions;if(\"tozeroy\"===s.fill){for(f=0;f<d.length&&isNaN(d[f+1]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h+1]);)h-=2;0!==d[f+1]&&(p=[d[f],0]),p=p.concat(d.slice(f,h+2)),0!==d[h+1]&&(p=p.concat([d[h],0]))}else if(\"tozerox\"===s.fill){for(f=0;f<d.length&&isNaN(d[f]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h]);)h-=2;0!==d[f]&&(p=[0,d[f+1]]),p=p.concat(d.slice(f,h+2)),0!==d[h]&&(p=p.concat([0,d[h+1]]))}else if(\"toself\"===s.fill||\"tonext\"===s.fill){for(p=[],i=0,a=0;a<d.length;a+=2)(isNaN(d[a])||isNaN(d[a+1]))&&((p=p.concat(d.slice(i,a))).push(d[i],d[i+1]),i=a+2);p=p.concat(d.slice(i)),i&&p.push(d[i],d[i+1])}else{var g=s._nexttrace;if(g){var m=v.lineOptions[e+1];if(m){var y=m.positions;if(\"tonexty\"===s.fill){for(p=d.slice(),e=Math.floor(y.length/2);e--;){var x=y[2*e],b=y[2*e+1];isNaN(x)||isNaN(b)||p.push(x,b)}t.fill=g.fillcolor}}}}if(s._prevtrace&&\"tonext\"===s._prevtrace.fill){var _=v.lineOptions[e-1].positions,w=p.length/2,T=[i=w];for(a=0;a<_.length;a+=2)(isNaN(_[a])||isNaN(_[a+1]))&&(T.push(a/2+w+1),i=a+2);p=p.concat(_),t.hole=T}return t.fillmode=s.fill,t.opacity=s.opacity,t.positions=p,t}})),v.fill2d.update(v.fillOptions))}var M=m.dragmode,A=l(M),S=m.clickmode.indexOf(\"select\")>-1;for(d=0;d<b;d++){var E=r[d][0],C=E.trace,L=E.t,I=L.index,P=C._length,z=L.x,O=L.y;if(C.selectedpoints||A||S){if(A||(A=!0),C.selectedpoints){var D=v.selectBatch[I]=s.selIndices2selPoints(C),R={};for(g=0;g<D.length;g++)R[D[g]]=1;var F=[];for(g=0;g<P;g++)R[g]||F.push(g);v.unselectBatch[I]=F}var B=L.xpx=new Array(P),N=L.ypx=new Array(P);for(g=0;g<P;g++)B[g]=y.c2p(z[g]),N[g]=x.c2p(O[g])}else L.xpx=L.ypx=null}if(A){if(v.select2d||(v.select2d=n(m._glcanvas.data()[1].regl)),v.scatter2d){var j=new Array(b);for(d=0;d<b;d++)j[d]=v.selectBatch[d].length||v.unselectBatch[d].length?v.markerUnselectedOptions[d]:{};v.scatter2d.update(j)}v.select2d&&(v.select2d.update(v.markerOptions),v.select2d.update(v.markerSelectedOptions)),v.glText&&r.forEach((function(t){var e=((t||[])[0]||{}).trace||{};u.hasText(e)&&h(t)}))}else v.scatter2d&&v.scatter2d.update(v.markerOptions);var U={viewport:p(m,y,x),range:[(y._rl||y.range)[0],(x._rl||x.range)[0],(y._rl||y.range)[1],(x._rl||x.range)[1]]},V=s.repeat(U,v.count);v.fill2d&&v.fill2d.update(V),v.line2d&&v.line2d.update(V),v.error2d&&v.error2d.update(V.concat(V)),v.scatter2d&&v.scatter2d.update(V),v.select2d&&v.select2d.update(V),v.glText&&v.glText.forEach((function(t){t.update(U)}))}else v.init()}}},{\"../../components/dragelement/helpers\":661,\"../../lib\":778,\"../../lib/prepare_regl\":791,\"../scatter/link_traces\":1203,\"../scatter/subtypes\":1212,\"./edit_style\":1244,\"gl-text\":352,\"regl-error2d\":534,\"regl-line2d\":535,\"regl-scatter2d\":537}],1250:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=e._scene,i={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},a={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,a,i)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var i=0;i<r.count;i++)r.glText[i].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,i=r.error2d,a=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,c=r.selectBatch,u=r.unselectBatch,f=0;f<t;f++){if(e&&r.fillOrder[f]&&e.draw(r.fillOrder[f]),a&&r.lineOptions[f]&&a.draw(f),i&&(r.errorXOptions[f]&&i.draw(f),r.errorYOptions[f]&&i.draw(f+t)),o&&r.markerOptions[f])if(u[f].length){var h=n.repeat([],r.count);h[f]=u[f],o.draw(h)}else 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n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scattergeo/attributes\"),o=t(\"../scatter/attributes\"),s=t(\"../../plots/mapbox/layout_attributes\"),l=t(\"../../plots/attributes\"),c=t(\"../../components/colorscale/attributes\"),u=t(\"../../lib/extend\").extendFlat,f=t(\"../../plot_api/edit_types\").overrideAll,h=a.line,p=a.marker;e.exports=f({lon:a.lon,lat:a.lat,mode:u({},o.mode,{dflt:\"markers\"}),text:u({},o.text,{}),texttemplate:i({editType:\"plot\"},{keys:[\"lat\",\"lon\",\"text\"]}),hovertext:u({},o.hovertext,{}),line:{color:h.color,width:h.width},connectgaps:o.connectgaps,marker:u({symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},angle:{valType:\"number\",dflt:\"auto\",arrayOk:!0},allowoverlap:{valType:\"boolean\",dflt:!1},opacity:p.opacity,size:p.size,sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode},c(\"marker\")),fill:a.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:\"string\"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:u({},l.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":650,\"../../lib/extend\":768,\"../../plot_api/edit_types\":810,\"../../plots/attributes\":824,\"../../plots/mapbox/layout_attributes\":887,\"../../plots/template_attributes\":906,\"../scatter/attributes\":1187,\"../scattergeo/attributes\":1229}],1253:[function(t,e,r){\"use 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e,r,i,a,s,l,c,u,f,h,p,d,g=t._x,m=t._y,v=t._z,y=t._len,x=-1/0,b=1/0,_=-1/0,w=1/0,T=-1/0,k=1/0,M=\"\";for(y&&(c=g[0],f=m[0],p=v[0]),y>1&&(u=g[y-1],h=m[y-1],d=v[y-1]),e=0;e<y;e++)x=Math.max(x,g[e]),b=Math.min(b,g[e]),_=Math.max(_,m[e]),w=Math.min(w,m[e]),T=Math.max(T,v[e]),k=Math.min(k,v[e]),a||g[e]===c||(a=!0,M+=\"x\"),s||m[e]===f||(s=!0,M+=\"y\"),l||v[e]===p||(l=!0,M+=\"z\");a||(M+=\"x\"),s||(M+=\"y\"),l||(M+=\"z\");var A=o(t._x),S=o(t._y),E=o(t._z);M=(M=(M=M.replace(\"x\",(c>u?\"-\":\"+\")+\"x\")).replace(\"y\",(f>h?\"-\":\"+\")+\"y\")).replace(\"z\",(p>d?\"-\":\"+\")+\"z\");var C=function(){y=0,A=[],S=[],E=[]};(!y||y<A.length*S.length*E.length)&&C();var L=function(t){return\"x\"===t?g:\"y\"===t?m:v},I=function(t){return\"x\"===t?A:\"y\"===t?S:E},P=function(t){return t[y-1]<t[0]?-1:1},z=L(M[1]),O=L(M[3]),D=L(M[5]),R=I(M[1]).length,F=I(M[3]).length,B=I(M[5]).length,N=!1,j=function(t,e,r){return 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M={};u.label&&(M.label=u.label),u.hasOwnProperty(\"v\")&&(M.value=u.v,M.valueLabel=x.formatValue(u.v,l)),M.currentPath=x.getPath(t.data),h||(M.percentParent=d/x.getValue(p),M.percentParentLabel=x.formatPercent(M.percentParent,l),M.parent=x.getPtLabel(p)),M.percentEntry=d/x.getValue(e),M.percentEntryLabel=x.formatPercent(M.percentEntry,l),M.entry=x.getPtLabel(e),M.percentRoot=d/x.getValue(f),M.percentRootLabel=x.formatPercent(M.percentRoot,l),M.root=x.getPtLabel(f),u.hasOwnProperty(\"color\")&&(M.color=u.color);var A=o.castOption(r,u.i,\"text\");return(o.isValidTextValue(A)||\"\"===A)&&(M.text=A),M.customdata=o.castOption(r,u.i,\"customdata\"),o.texttemplateString(k,M,i._d3locale,M,r._meta||{})}},{\"../../components/drawing\":665,\"../../lib\":778,\"../../lib/svg_text_utils\":803,\"../bar/style\":935,\"../bar/uniform_text\":937,\"../pie/helpers\":1166,\"../pie/plot\":1170,\"./constants\":1302,\"./fx\":1304,\"./helpers\":1305,\"./style\":1310,d3:169,\"d3-hierarchy\":161}],1310:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../components/color\"),a=t(\"../../lib\"),o=t(\"../bar/uniform_text\").resizeText;function s(t,e,r){var n=e.data.data,o=!e.children,s=n.i,l=a.castOption(r,s,\"marker.line.color\")||i.defaultLine,c=a.castOption(r,s,\"marker.line.width\")||0;t.style(\"stroke-width\",c).call(i.fill,n.color).call(i.stroke,l).style(\"opacity\",o?r.leaf.opacity:null)}e.exports={style:function(t){var e=t._fullLayout._sunburstlayer.selectAll(\".trace\");o(t,e,\"sunburst\"),e.each((function(t){var e=n.select(this),r=t[0].trace;e.style(\"opacity\",r.opacity),e.selectAll(\"path.surface\").each((function(t){n.select(this).call(s,t,r)}))}))},styleOne:s}},{\"../../components/color\":643,\"../../lib\":778,\"../bar/uniform_text\":937,d3:169}],1311:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/edit_types\").overrideAll;function c(t){return{show:{valType:\"boolean\",dflt:!1},start:{valType:\"number\",dflt:null,editType:\"plot\"},end:{valType:\"number\",dflt:null,editType:\"plot\"},size:{valType:\"number\",dflt:null,min:0,editType:\"plot\"},project:{x:{valType:\"boolean\",dflt:!1},y:{valType:\"boolean\",dflt:!1},z:{valType:\"boolean\",dflt:!1}},color:{valType:\"color\",dflt:n.defaultLine},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!0},highlightcolor:{valType:\"color\",dflt:n.defaultLine},highlightwidth:{valType:\"number\",min:1,max:16,dflt:2}}}var u=e.exports=l(s({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:a(),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},i(\"\",{colorAttr:\"z or surfacecolor\",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:\"calc\"}),{contours:{x:c(),y:c(),z:c()},hidesurface:{valType:\"boolean\",dflt:!1},lightposition:{x:{valType:\"number\",min:-1e5,max:1e5,dflt:10},y:{valType:\"number\",min:-1e5,max:1e5,dflt:1e4},z:{valType:\"number\",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},opacityscale:{valType:\"any\",editType:\"calc\"},_deprecated:{zauto:s({},i.zauto,{}),zmin:s({},i.zmin,{}),zmax:s({},i.zmax,{})},hoverinfo:s({},o.hoverinfo),showlegend:s({},o.showlegend,{dflt:!1})}),\"calc\",\"nested\");u.x.editType=u.y.editType=u.z.editType=\"calc+clearAxisTypes\",u.transforms=void 0},{\"../../components/color\":643,\"../../components/colorscale/attributes\":650,\"../../lib/extend\":768,\"../../plot_api/edit_types\":810,\"../../plots/attributes\":824,\"../../plots/template_attributes\":906}],1312:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":651}],1313:[function(t,e,r){\"use strict\";var n=t(\"gl-surface3d\"),i=t(\"ndarray\"),a=t(\"ndarray-linear-interpolate\").d2,o=t(\"../heatmap/interp2d\"),s=t(\"../heatmap/find_empties\"),l=t(\"../../lib\").isArrayOrTypedArray,c=t(\"../../lib/gl_format_color\").parseColorScale,u=t(\"../../lib/str2rgbarray\"),f=t(\"../../components/colorscale\").extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){var o=t.dataCoordinate[a];null!=o&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var s=this.data.hovertext||this.data.text;return Array.isArray(s)&&s[i]&&void 0!==s[i][n]?t.textLabel=s[i][n]:t.textLabel=s||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var d=[2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97,101,103,107,109,113,127,131,137,139,149,151,157,163,167,173,179,181,191,193,197,199,211,223,227,229,233,239,241,251,257,263,269,271,277,281,283,293,307,311,313,317,331,337,347,349,353,359,367,373,379,383,389,397,401,409,419,421,431,433,439,443,449,457,461,463,467,479,487,491,499,503,509,521,523,541,547,557,563,569,571,577,587,593,599,601,607,613,617,619,631,641,643,647,653,659,661,673,677,683,691,701,709,719,727,733,739,743,751,757,761,769,773,787,797,809,811,821,823,827,829,839,853,857,859,863,877,881,883,887,907,911,919,929,937,941,947,953,967,971,977,983,991,997,1009,1013,1019,1021,1031,1033,1039,1049,1051,1061,1063,1069,1087,1091,1093,1097,1103,1109,1117,1123,1129,1151,1153,1163,1171,1181,1187,1193,1201,1213,1217,1223,1229,1231,1237,1249,1259,1277,1279,1283,1289,1291,1297,1301,1303,1307,1319,1321,1327,1361,1367,1373,1381,1399,1409,1423,1427,1429,1433,1439,1447,1451,1453,1459,1471,1481,1483,1487,1489,1493,1499,1511,1523,1531,1543,1549,1553,1559,1567,1571,1579,1583,1597,1601,1607,1609,1613,1619,1621,1627,1637,1657,1663,1667,1669,1693,1697,1699,1709,1721,1723,1733,1741,1747,1753,1759,1777,1783,1787,1789,1801,1811,1823,1831,1847,1861,1867,1871,1873,1877,1879,1889,1901,1907,1913,1931,1933,1949,1951,1973,1979,1987,1993,1997,1999,2003,2011,2017,2027,2029,2039,2053,2063,2069,2081,2083,2087,2089,2099,2111,2113,2129,2131,2137,2141,2143,2153,2161,2179,2203,2207,2213,2221,2237,2239,2243,2251,2267,2269,2273,2281,2287,2293,2297,2309,2311,2333,2339,2341,2347,2351,2357,2371,2377,2381,2383,2389,2393,2399,2411,2417,2423,2437,2441,2447,2459,2467,2473,2477,2503,2521,2531,2539,2543,2549,2551,2557,2579,2591,2593,2609,2617,2621,2633,2647,2657,2659,2663,2671,2677,2683,2687,2689,2693,2699,2707,2711,2713,2719,2729,2731,2741,2749,2753,2767,2777,2789,2791,2797,2801,2803,2819,2833,2837,2843,2851,2857,2861,2879,2887,2897,2903,2909,2917,2927,2939,2953,2957,2963,2969,2971,2999];function g(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function m(t){for(var e=[],r=0;r<d.length;r++){var n=d[r];e.push(g(t,n))}return e}function v(t){for(var e=m(t),r=t,n=0;n<d.length;n++)if(e[n]>0){r=d[n];break}return r}function y(t,e){if(!(t<1||e<1)){for(var r=m(t),n=m(e),i=1,a=0;a<d.length;a++)i*=Math.pow(d[a],Math.max(r[a],n[a]));return i}}p.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),i=this.getXat(e,0);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r},p.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),i=this.getYat(0,e);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r};var x=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],b=x[9],_=x[13];function w(t,e,r){var n=r[8]+r[2]*e[0]+r[5]*e[1];return t[0]=(r[6]+r[0]*e[0]+r[3]*e[1])/n,t[1]=(r[7]+r[1]*e[0]+r[4]*e[1])/n,t}function T(t,e,r){return function(t,e,r,n){for(var i=[0,0],o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var c=0;c<s;c++)r(i,[l,c],n),t.set(l,c,a(e,i[0],i[1]))}(t,e,w,r),t}function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}p.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=y(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<b;)r*=2;for(;r>_;)r--,r/=v(r),++r<b&&(r=_);var n=Math.round(r/t);return n>1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,c=1+a+1,u=i(new Float32Array(l*c),[l,c]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h<t.length;++h){this.surface.padField(u,t[h]);var p=i(new Float32Array(o*s),[o,s]);T(p,u,f),t[h]=p}},p.setContourLevels=function(){var t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,a,l=this.scene,h=l.fullSceneLayout,p=this.surface,d=c(t),g=l.dataScale,m=t.z[0].length,v=t._ylength,y=l.contourLevels;this.data=t;var x=[];for(e=0;e<3;e++)for(x[e]=[],r=0;r<m;r++)x[e][r]=[];for(r=0;r<m;r++)for(n=0;n<v;n++)x[0][r][n]=this.getXat(r,n,t.xcalendar,h.xaxis),x[1][r][n]=this.getYat(r,n,t.ycalendar,h.yaxis),x[2][r][n]=this.getZat(r,n,t.zcalendar,h.zaxis);if(t.connectgaps)for(t._emptypoints=s(x[2]),o(x[2],t._emptypoints),t._interpolatedZ=[],r=0;r<m;r++)for(t._interpolatedZ[r]=[],n=0;n<v;n++)t._interpolatedZ[r][n]=x[2][r][n];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null==(a=x[e][r][n])?x[e][r][n]=NaN:a=x[e][r][n]*=g[e];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(this.minValues[e]>a&&(this.minValues[e]=a),this.maxValues[e]<a&&(this.maxValues[e]=a));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(x[e][r][n]-=this.objectOffset[e]);var b=[i(new Float32Array(m*v),[m,v]),i(new Float32Array(m*v),[m,v]),i(new Float32Array(m*v),[m,v])];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)b[e].set(r,n,x[e][r][n]);x=[];var w={colormap:d,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacityscale:t.opacityscale,opacity:t.opacity},T=f(t);if(w.intensityBounds=[T.min,T.max],t.surfacecolor){var k=i(new Float32Array(m*v),[m,v]);for(r=0;r<m;r++)for(n=0;n<v;n++)k.set(r,n,t.surfacecolor[n][r]);b.push(k)}else w.intensityBounds[0]*=g[2],w.intensityBounds[1]*=g[2];(_<b[0].shape[0]||_<b[0].shape[1])&&(this.refineData=!1),!0===this.refineData&&(this.dataScaleX=this.estimateScale(b[0].shape[0],0),this.dataScaleY=this.estimateScale(b[0].shape[1],1),1===this.dataScaleX&&1===this.dataScaleY||this.refineCoords(b)),t.surfacecolor&&(w.intensity=b.pop());var M=[!0,!0,!0],A=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var S=t.contours[A[e]];M[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=y[e],p.highlightColor[e]=w.contourColor[e]=u(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=u(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=M,p.enableHighlight=M,p.snapToData=!0,\"lighting\"in t&&(p.ambientLight=t.lighting.ambient,p.diffuseLight=t.lighting.diffuse,p.specularLight=t.lighting.specular,p.roughness=t.lighting.roughness,p.fresnel=t.lighting.fresnel),\"lightposition\"in t&&(p.lightPosition=[t.lightposition.x,t.lightposition.y,t.lightposition.z])},p.dispose=function(){this.scene.glplot.remove(this.surface),this.surface.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new h(t,i,e.uid);return i._trace=a,a.update(e),t.glplot.add(i),a}},{\"../../components/colorscale\":655,\"../../lib\":778,\"../../lib/gl_format_color\":774,\"../../lib/str2rgbarray\":802,\"../heatmap/find_empties\":1071,\"../heatmap/interp2d\":1074,\"gl-surface3d\":351,ndarray:495,\"ndarray-linear-interpolate\":489}],1314:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),o=t(\"./attributes\");function s(t,e,r,n){var 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d=i.ensureSingle(h,\"g\",\"slicetext\"),T=i.ensureSingle(d,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),E=i.ensureUniformFontSize(t,u.determineTextFont(C,s,S.font,{onPathbar:!0}));T.text(s._text||\" \").classed(\"slicetext\",!0).attr(\"text-anchor\",\"start\").call(a.font,E).call(o.convertToTspans,t),s.textBB=a.bBox(T.node()),s.transform=b(s,{fontSize:E.size,onPathbar:!0}),s.transform.fontSize=E.size,w?T.transition().attrTween(\"transform\",(function(t){var e=M(t,!0,A,[g,m]);return function(t){return _(e(t))}})):T.attr(\"transform\",_(s))}))}},{\"../../components/drawing\":665,\"../../lib\":778,\"../../lib/svg_text_utils\":803,\"../sunburst/fx\":1304,\"../sunburst/helpers\":1305,\"./constants\":1328,\"./partition\":1335,\"./style\":1337,d3:169}],1331:[function(t,e,r){\"use strict\";var n=t(\"d3\"),i=t(\"../../lib\"),a=t(\"../../components/drawing\"),o=t(\"../../lib/svg_text_utils\"),s=t(\"./partition\"),l=t(\"./style\").styleOne,c=t(\"./constants\"),u=t(\"../sunburst/helpers\"),f=t(\"../sunburst/fx\"),h=t(\"../sunburst/plot\").formatSliceLabel;e.exports=function(t,e,r,p,d){var 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strict\";e.exports={attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../box/defaults\").crossTraceDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\"),crossTraceCalc:t(\"./cross_trace_calc\"),plot:t(\"./plot\"),style:t(\"./style\"),styleOnSelect:t(\"../scatter/style\").styleOnSelect,hoverPoints:t(\"./hover\"),selectPoints:t(\"../box/select\"),moduleType:\"trace\",name:\"violin\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"cartesian\",\"svg\",\"symbols\",\"oriented\",\"box-violin\",\"showLegend\",\"violinLayout\",\"zoomScale\"],meta:{}}},{\"../../plots/cartesian\":841,\"../box/defaults\":949,\"../box/select\":956,\"../scatter/style\":1211,\"./attributes\":1338,\"./calc\":1339,\"./cross_trace_calc\":1340,\"./defaults\":1341,\"./hover\":1343,\"./layout_attributes\":1345,\"./layout_defaults\":1346,\"./plot\":1347,\"./style\":1348}],1345:[function(t,e,r){\"use strict\";var 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f={\"stroke-width\":u+\"px\",\"stroke-dasharray\":2*u+\"px,\"+u+\"px\"};o.selectAll(\"path.mean\").style(f).call(i.stroke,c.color),o.selectAll(\"path.meanline\").style(f).call(i.stroke,c.color),a(o,r,t)}))}},{\"../../components/color\":643,\"../scatter/style\":1211,d3:169}],1349:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/attributes\"),i=t(\"../isosurface/attributes\"),a=t(\"../surface/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/edit_types\").overrideAll,c=e.exports=l(s({x:i.x,y:i.y,z:i.z,value:i.value,isomin:i.isomin,isomax:i.isomax,surface:i.surface,spaceframe:{show:{valType:\"boolean\",dflt:!1},fill:{valType:\"number\",min:0,max:1,dflt:1}},slices:i.slices,caps:i.caps,text:i.text,hovertext:i.hovertext,hovertemplate:i.hovertemplate},n(\"\",{colorAttr:\"`value`\",showScaleDflt:!0,editTypeOverride:\"calc\"}),{colorbar:i.colorbar,opacity:i.opacity,opacityscale:a.opacityscale,lightposition:i.lightposition,lighting:i.lighting,flatshading:i.flatshading,contour:i.contour,hoverinfo:s({},o.hoverinfo),showlegend:s({},o.showlegend,{dflt:!1})}),\"calc\",\"nested\");c.x.editType=c.y.editType=c.z.editType=c.value.editType=\"calc+clearAxisTypes\",c.transforms=void 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     "metadata": {},
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   ],
   "source": [
    "# plotting in a graph \n",
    "data = {\n",
    "    \"values\": locations_df[\"unique_counts\"].loc[:10],\n",
    "    \"labels\": locations_df[\"location\"].loc[:10],\n",
    "    \"domain\": {\"column\": 0},\n",
    "    \"hoverinfo\": \"label + percent\",\n",
    "    \"type\": \"pie\"\n",
    "}\n",
    "layout = go.Layout(title= \"<b>Top 10 Locations from Tweets</b>\",\n",
    "                   legend= dict(x=0.1, y=1.1, orientation=\"h\"))\n",
    "\n",
    "fig = go.Figure(data=[data], layout=layout)\n",
    "fig.update_layout(title_x=0.5)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>unique_counts</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>United States</td>\n",
       "      <td>627</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>UK</td>\n",
       "      <td>117</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Worldwide</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>India</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Canada</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Nigeria</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Kenya</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Australia</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Ireland</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Seattle, WA</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          country  unique_counts\n",
       "0   United States            627\n",
       "1              UK            117\n",
       "2       Worldwide             64\n",
       "3           India             63\n",
       "4          Canada             58\n",
       "5         Nigeria             40\n",
       "6           Kenya             32\n",
       "7       Australia             25\n",
       "8         Ireland             15\n",
       "9       Indonesia             15\n",
       "10    Seattle, WA             14"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# replacing some names from locations to be all countries\n",
    "replace_names= {\n",
    "    \"USA\":\"United States\",\n",
    "    \"New York\":\"United States\",\n",
    "    \"Los Angeles\": \"United States\",\n",
    "    \"Los Angeles, CA\":\"United States\",\n",
    "    \"Washington, DC\": \"United States\",\n",
    "    \"San Francisco\": \"United States\",\n",
    "    \"San Francisco, CA\": \"United States\",\n",
    "    \"Chicago, IL\": \"United States\",\n",
    "    \"Chicago\": \"United States\",\n",
    "    \"New York, NY\": \"United States\",\n",
    "    \"NYC\": \"United States\",\n",
    "    \"Florida\": \"United States\",\n",
    "    \"London\": \"UK\",\n",
    "    \"United Kingdom\": \"UK\",\n",
    "    \"Mumbai\": \"India\",\n",
    "    \"California\": \"United States\",\n",
    "    \"California, USA\": \"United States\",\n",
    "    \"Toronto\": \"Canada\",\n",
    "    \"Washington, D.C.\": \"United States\",\n",
    "    \"Everywhere\": \"Worldwide\",\n",
    "    \"Seattle\": \"United States\",\n",
    "    \"ss\": \"Worldwide\"\n",
    "}\n",
    "\n",
    "countries = full_df[\"location\"].replace(replace_names).value_counts().sort_values(ascending=False)\n",
    "countries_df= pd.DataFrame(dict(zip(countries.index, countries.values)), index=[0]).\\\n",
    "                                melt(var_name=\"country\", value_name=\"unique_counts\")\n",
    "# Note: Counts may not be accurate because not all area's have been replaced! \n",
    "countries_df.loc[:10]"
   ]
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[0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"<b>Tweet Locations of Top 10 Countries</b>\", \"x\": 0.5}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('876ccf35-1359-4984-833c-492656d2d9f4');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A world plot with each of these locations highlighted with a heatmap displaying area's with higher unique counts\n",
    "data = {\n",
    "    \"locations\": countries_df.loc[:10, \"country\"],\n",
    "    \"locationmode\": \"country names\",\n",
    "    \"z\": countries_df.loc[:10, \"unique_counts\"],\n",
    "    \"colorscale\": \"Rainbow\",\n",
    "    \"text\": countries_df.loc[:10, \"country\"],\n",
    "    \"type\": \"choropleth\",\n",
    "    \"colorbar\": {\"title\": \"Unique Counts\", \"len\": 200, \"lenmode\":\"pixels\"}\n",
    "}\n",
    "\n",
    "layout = go.Layout(title_text= \"<b>Tweet Locations of Top 10 Countries</b>\",\n",
    "                   geo= dict(scope= \"world\"))\n",
    "\n",
    "fig = go.Figure(data=[data], layout=layout)\n",
    "fig.update_layout(title_x=0.5)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Number of Disaster tweets in each location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# creating new dataframe to replace the names we changed\n",
    "df2 = full_df.copy()\n",
    "df2[\"location\"].replace(replace_names, inplace=True)\n",
    "\n",
    "# count the number of disaster tweets in each location\n",
    "country_disaster_tweets = df2[df2[\"location\"].isin(countries_df.loc[:10, \"country\"])].groupby(\"location\")[\"target\"].sum()\n",
    "country_disaster_tweets_df = pd.merge(left=countries_df, right=country_disaster_tweets, left_on=\"country\", right_on=\"location\")\n",
    "\n",
    "# renaming target column\n",
    "country_disaster_tweets_df.rename(columns={\"target\":\"disaster_tweets\"}, inplace=True)\n",
    "country_disaster_tweets_df[\"percent_disaster_tweets\"] = round(100 * country_disaster_tweets_df[\"disaster_tweets\"]\\\n",
    "                                                              / country_disaster_tweets_df[\"unique_counts\"], 2)\n",
    "\n",
    "# plotting the percentages\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.set(style=\"whitegrid\", color_codes=True)\n",
    "seaborn_plot = sns.barplot(x=\"country\", y=\"percent_disaster_tweets\", data=country_disaster_tweets_df)\n",
    "for p in seaborn_plot.patches:\n",
    "    seaborn_plot.annotate(format(p.get_height(), '.2f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center',\n",
    "                   va = 'center', xytext = (0, 9), textcoords = 'offset points')\n",
    "plt.title(\"Percentage of Disaster tweets per Country\", size=20, weight=\"bold\")\n",
    "plt.xlabel(\"Countries\", size=14, weight=\"bold\")\n",
    "plt.ylabel(\"Percentage\", size=14, weight=\"bold\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Duplicate Tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Duplicated Tweets in Train & Test: 198\n",
      "Number of Duplicated Tweets in Train: 110\n",
      "Number of Duplicated Tweets in Test: 88\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# all duplicate tweets\n",
    "duplicated_df = full_df[full_df[\"text\"].duplicated()]\n",
    "\n",
    "print(f\"Number of Duplicated Tweets in Train & Test: {len(duplicated_df)}\\n\\\n",
    "Number of Duplicated Tweets in Train: {duplicated_df['target'].notna().sum()}\\n\\\n",
    "Number of Duplicated Tweets in Test: {duplicated_df['target'].isna().sum()}\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Duplicated Tweets with different target labels in train: 12\n"
     ]
    }
   ],
   "source": [
    "# add all the tweets with duplicates\n",
    "train_duplicates = train_df[train_df[\"text\"].duplicated()].groupby([\"text\"])[[\"target\"]].agg(list)\n",
    "\n",
    "diff_label_idx = []\n",
    "for idx, val in enumerate(train_duplicates[\"target\"]):\n",
    "    for ele in val: \n",
    "        if ele != val[0]:\n",
    "            diff_label_idx.append(idx)\n",
    "                \n",
    "print(f\"Number of Duplicated Tweets with different target labels in train: {len(diff_label_idx)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>text</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>#Allah describes piling up #wealth thinking it would last #forever as the description of the people of #Hellfire in Surah Humaza. #Reflect</th>\n",
       "      <td>[0, 1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#foodscare #offers2go #NestleIndia slips into loss after #Magginoodle #ban unsafe and hazardous for #humanconsumption</th>\n",
       "      <td>[1, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>.POTUS #StrategicPatience is a strategy for #Genocide; refugees; IDP Internally displaced people; horror; etc. https://t.co/rqWuoy1fm4</th>\n",
       "      <td>[1, 0, 1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CLEARED:incident with injury:I-495  inner loop Exit 31 - MD 97/Georgia Ave Silver Spring</th>\n",
       "      <td>[1, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>He came to a land which was engulfed in tribal war and turned it into a land of peace i.e. Madinah. #ProphetMuhammad #islam</th>\n",
       "      <td>[1, 1, 0, 0, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>He came to a land which was engulfed in tribal war and turned it into a land of peace i.e. Madinah. #ProphetMuhammad #islam</th>\n",
       "      <td>[1, 1, 0, 0, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>He came to a land which was engulfed in tribal war and turned it into a land of peace i.e. Madinah. #ProphetMuhammad #islam</th>\n",
       "      <td>[1, 1, 0, 0, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hellfire is surrounded by desires so be careful and don‰Ûªt let your desires control you! #Afterlife</th>\n",
       "      <td>[1, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Prophet (peace be upon him) said 'Save yourself from Hellfire even if it is by giving half a date in charity.'</th>\n",
       "      <td>[0, 1, 0, 0, 1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Prophet (peace be upon him) said 'Save yourself from Hellfire even if it is by giving half a date in charity.'</th>\n",
       "      <td>[0, 1, 0, 0, 1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>To fight bioterrorism sir.</th>\n",
       "      <td>[0, 1, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>that horrible sinking feeling when you‰Ûªve been at home on your phone for a while and you realise its been on 3G this whole time</th>\n",
       "      <td>[0, 0, 1]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                             target\n",
       "text                                                               \n",
       "#Allah describes piling up #wealth thinking it ...           [0, 1]\n",
       "#foodscare #offers2go #NestleIndia slips into l...           [1, 0]\n",
       ".POTUS #StrategicPatience is a strategy for #Ge...        [1, 0, 1]\n",
       "CLEARED:incident with injury:I-495  inner loop ...           [1, 0]\n",
       "He came to a land which was engulfed in tribal ...  [1, 1, 0, 0, 0]\n",
       "He came to a land which was engulfed in tribal ...  [1, 1, 0, 0, 0]\n",
       "He came to a land which was engulfed in tribal ...  [1, 1, 0, 0, 0]\n",
       "Hellfire is surrounded by desires so be careful...           [1, 0]\n",
       "The Prophet (peace be upon him) said 'Save your...  [0, 1, 0, 0, 1]\n",
       "The Prophet (peace be upon him) said 'Save your...  [0, 1, 0, 0, 1]\n",
       "To fight bioterrorism sir.                                [0, 1, 0]\n",
       "that horrible sinking feeling when you‰Ûªve bee...        [0, 0, 1]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# tweets with different labels\n",
    "train_duplicates.iloc[diff_label_idx]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Keywords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# getting all the keywords from keyword column\n",
    "all_keywords = \" \".join([keyword for keyword in full_df[\"keyword\"].dropna()])\n",
    "\n",
    "# visualizing keywords\n",
    "word_cloud= WordCloud(width=800,\n",
    "                      height=500,\n",
    "                      max_font_size=112,\n",
    "                      random_state=24).generate(all_keywords)\n",
    "\n",
    "# plotting \n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.title(\"All keywords\", size=20, weight=\"bold\")\n",
    "plt.imshow(word_cloud, interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# all keywords from tweets associated to a disaster \n",
    "all_disaster_keywords = \" \".join([keyword for keyword in full_df[full_df[\"target\"]==1][\"keyword\"].dropna()])\n",
    "\n",
    "# visualizing keywords\n",
    "word_cloud= WordCloud(width=800,\n",
    "                      height=500,\n",
    "                      max_font_size=112,\n",
    "                      random_state=24).generate(all_disaster_keywords)\n",
    "\n",
    "# plotting \n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.title(\"All keywords associated to Disasters\", size=20, weight=\"bold\")\n",
    "plt.imshow(word_cloud, interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4xz8GvB3WRz/60eJLfKLx9NNPF/+uqqoatEht3bq1+PeqVauGLKPXbkNVVS6++GLuvPNO9uzZw/79+6mvry9KTqZPn860adMAqK6uZvr06ezatYsXXniBD3zgA6xbtw6AM844g+eee46NGzdi23ZRnVVSUlJUUaxZswaAYDA4KG7Ru971ruICt27dukGEZ8GCBYPUCv13+f1tkHw+H2eccQb33HPPgOsvuOACfvWrX2FZFjfeeCOxWIwlS5awdOlSzjrrLOrq6obsq/6ora2ltraWRCLB008/zaZNm9iwYcMAyVAvqbv44ovZsGEDLS0tXHTRRYwfP76oGjzzzDOJxWLFey6++GIefPBBcrkc73jHO6ioqGDJkiUsW7aMs846q0gw+vcjwDXXXDNgnq1atYqqqipaWlqKMVS2bdtWPH/aaacNaM//+3//75htBohGo6xatYoVK1awadMmHnjgATZu3DigLr3tHg7ZbLa4WTh48GBRinE0Nm3axCmnnDLs+AqCwLnnnjsqwjMSNm3aRKFQADzy0Et2wJO2nH322TzwwAPkcjm2b9/OggULRlVuSUkJn/70p4sq5ltuuYXPf/7zg647dOhQUeq2cuXKAQut3+/nsssu4+c//zmO47B+/XouvvjiAfefeuqpxb9VVaWqqor9+/cPsPvZt28fBw4cGHCfz+cbNA+GQ/+yRvLYU1WVc889l0cffZTnnnuOlStXMmPGDBYvXszKlStZtmzZAMJ4st6j4XDgwIEiYVu9evUAW5/+2LRp0yDCc7QR//G2dQwnB2OE5yTDMIwBuvbeHefRaGxs5OWXX2bFihUnvU5r1qzh2WefHUBsRhMsrr94+u1vf3vRbffRRx/lzDPP5PDhwwCDiMeZZ57Jrl27eOWVV9i/fz9NTU2A1xcvvPACmUyG7du3F9UWq1atKqrael2dKyoqBpHB/qLzZDI5qL4lJSWDjvWqg3w+36CPcWlp6aDrZ86cya9+9Su+973vsXXrVhKJBE888QRPPPFEUbV26623jvhhz2Qy3HLLLTz88MPFD/LEiROZMGFC0ei2V7r23ve+F0EQ+OUvf0lzczMNDQ00NDRw3333oWkaN954Y1ESeOaZZ/LDH/6Q22+/nf3799PW1sbDDz/Mww8/zH//939z9dVX85WvfAVRFIv9CAwgQv2PtbS0oOs6+XyedDo9Yj+OFj/72c/4zW9+UyyvrKyMKVOmFI00j2Us278eI6F3bva3Zzq63kON7/FiNP3Yi6Hm5Eh4xzvewV//+lc2bdo0rAFz/+cPZefT//n9r+1Ff4IGDLnIPvzww0X1di9qa2t56qmnjtUEgAFS0l5103D49re/TUVFBffeey/ZbJbt27ezfft2/vCHP1BWVsbXv/71orT3ZL1Hw2G04zeU2m6od+Z42jqGk4MxwnOS8dRTTw354RkK99xzz0kjPKIo8sUvfpHvfe975PN5vve97xXVM+BJUMCze7jtttuGlDT1X9TnzZtHfX09+/fv57HHHivqzgVBGJLw/M///A+FQoH/+Z//Abzd8IIFC5gxYwbbt2/njjvuKNrK9NrvgLdItbS00NbWhuu6A+rV/0MzlFqlv8quF706/EKhQC6XIxAIFM91dnYO2XcrVqzgnnvuoaGhgZdeeokNGzbwwgsv0NHRwaOPPsq4ceMGeaH1x9e//nUeeOABJEniS1/6EhdffDHxeJwf/ehHg4wYwbMVuvbaa9m2bRsvv/wy69evZ/Xq1eTzeW6//Xbmzp1bJKsXXXQRF110EXv37i3W7cUXXySVSvGnP/2JadOm8Z73vGdA//R6R/VH7zG/34/f7x8QC+fo+dvV1UU2m2XcuHEjSiTvueeeol3CNddcww033MCECRNYvXo173//+4e9rz965yV4tmX9bWv6o6amBmBAvbu6ugaQnOHG93jQv7yR+hGOnygKgsBXvvIVrr76ahzH4cknnxzx+UMttP2fP9Q70buROJnYsmVL8e9jGeEGAgG+9KUv8Z//+Z+sW7eOtWvX8sorr7B+/Xo6Ojr41Kc+xVNPPUU8Hj+p79FQ6G/0vWLFCt773vcOeV19ff2gY0N9e46nrWM4ORgzWj7J6O8Cee211/Kxj31s0E/vLuvxxx8f9Y72ePGBD3yA9773vUV32927dw+oW6+qwLZtSkpKOOecczjnnHOor6/nySef5PDhw0Sj0QFl9tq/bN++nbvvvhuApUuXDrIbmDdvXvFD3RumvzfAWu/vXq8ORVEGiM57VQLZbHaQV8qf//zn4t9Lly4d1OahFuP+3lz9bY5yuRzPPPPMoOvvvvtuvvjFL/LBD36QiooK3vnOd3LrrbfywAMPFK/ZuHHjoPv64/HHHwc8VeJ1111X/KAdrV7J5XL87Gc/41Of+hRf+9rXmDNnDjfccAM///nPBwRG27BhA67r8utf/5rPfvaz3HzzzUyePJnrr7+eH/3oR/z6178eVLf+Xky9Nii9ePbZZ4tqkt5+nDVrVvH8888/P0AS84tf/IJzzjmHRYsWjehO29tugJtuuqnozdJrS3Q0eser/7PC4XDRGLitrY1ly5YV56Zt27z00ku0tbUVycVw4+s4zoihB45G70bg6PrMmjULRVEAz0i2//va0dFRJCnhcHhY9dtImD179rD2O+BJWnrtsl588UWOHDlSPKfrenFeSpI0wA7pePDxj3+cXbt2DfgZrXTnmWeeKYaTWLRo0SBVT38cOHCA73//+3zkIx/h/vvvZ+XKlXzyk5/kzjvvLPZBPp9n586dwMl5j3ox1Nyrr68vEpeWlhZWrVpVnHvt7e2sXbuW7u7uIYnt0d+e423rGE4OxiQ8JxGdnZ1FQ+Hy8nK+/OUvD/iQ9mL37t089thjFAoF/v73v4/4wXut6BV/33DDDfzpT38imUzy4x//mIsvvhhN07jqqquKBnqf+MQnuOGGG4jH4/zmN78pein86Ec/Ys6cOcUyL7vsMn70ox/hOE5xtzmUe70oiqxatYp777236E3TS3SWL1/O7373u+Lx5cuXD9hZXXvttTz66KO4rsvnPvc5du/ezaRJk3jqqaeKHkD19fVFr61j4e1vf3vRTudrX/sabW1tlJaW8n//939DSgB27drFX//612LfXXnllYiiOGAx712Qh0MoFCKbzdLY2MjXvvY1Fi5cyBNPPDGAYBmGQSAQ4JFHHin2t2EYnHrqqWQymQFxZHolK+vWrSvaZn384x/nvPPOw7KsATZjvXVbuXIlEydO5ODBg0WX3QsvvJDGxsYiQRIEgZtuugnwFpXTTjuNF154ge3bt3PDDTdw6aWX0tDQUFS1hEKhosfVcO3uxZe+9CWuuuoqdu7cOcBlvL93Xa8EMZvNcueddxIKhbj88su58sor+fGPf0wikeB973sf1157LYVCgdtvv51kMomiKEVVwKWXXsrPfvYzLMvi5z//OYZhMGnSJB588MGiB+Bo0H+HvmbNGv72t79RX1/PvHnzuPTSS7n33nvp7Ozkne98J9ddd13RmLjX5uNDH/pQkRgdLz75yU/yyCOPDAiF0AtJknjXu95VjAF17bXX8qEPfQi/38+f/vSnovHxlVdeOaJr+4nA9u3biyqybDbL1q1bi5sQQRD4xCc+MeL9oVCI3/72t5imyerVq2ltbaW+vp6mpqYBoQxqa2uL15/o96gXfr+fXC5HQ0MD99xzD9FolHPOOYeLL76Ye+65hwMHDvChD32IK6+8kra2tmL/x+PxEXMivta2juHkYIzwnEQ8+OCDRV3zBRdcMCTZAY8k9O5G77nnnpNCeHoRiUS44YYb+P73v09zczN33HEHH/7wh1myZAnve9/7+P3vf09nZ+eg3D4XXHDBoECD1dXVLF++vOjKrKrqkMEIwfNO6+/62kt4li5diiiKRcJztA57+fLlfOpTn+KHP/whhmEUVWK9qKioOK6YJ8uWLeNd73oXf/rTn8hms3z/+98fUMejpTwf+9jHWLNmDbt372bt2rWDPMxisdgxbQGuuuqqYkLMO++8s2j7pChKURXY+wH85je/yfve9z4ymQx//etfi2SrF/PmzePyyy8HvES027dvL+Yw6k/CwPMuet/73gd4nk+33XYbN9xwA+3t7cXYO70QBIHPfe5zA4wtb7nlFt797nfT1tbGCy+8UDQq7y3vO9/5zogqkquuuoqHHnoI13VZvXp1cZ70JwL9Y/zMnDmzGI/ma1/7GhMnTuTyyy/nQx/6EM8//zwbN25k+/btfOlLXxrwnM997nNFqWJdXR0333wz3//+9zFNc8B8GWp8h0N9fT2apqHrOrt37+azn/0sn/zkJ5k3bx5f/OIX2bdvH5s2bWLfvn2Dgneef/75A+IZHS8ikQif+cxnhjRaBvi3f/s3tm3bxlNPPUVra+ugtAiLFy/mC1/4wmt+/mjxhz/8gT/84Q+DjguCwGc+85ljqufLy8v5r//6L7785S8X1UxH4/rrry9KBk/WewTe3Fu/fj25XI4vfOELrFy5knPOOYf/9//+H+vXr+fgwYPFmGS9kGWZr3/966NKpXK8bR3DycGYSuskov9O+8ILLxz2ulWrVhV3Sps3bx51vJDXiuuvv74oFv/FL35RtNH4whe+wHe/+10WLVpEMBgkEAgwY8aMou3PUIStf7v6t+NorFy5srjQlZeXF/XeR4v++9vv9OLGG2/kj3/8IxdeeCHl5eUoisK4ceO4/vrr+dvf/nZMt/Cj8dWvfpXPf/7zTJgwAVVVmTlzJrfddtuQRDMWi3HXXXfxH//xH8yYMYNwOFx8/jXXXMN99913zI/URz/6UT796U8zceJENE2jrq6OK6+8kj/96U9F0XevymDOnDn87W9/413vehcTJ07E5/Ph8/mYNm0aH//4x7njjjuKKtDx48dzzz338KEPfYgpU6YQCARQVZVJkybxgQ98gLvvvnuAuH3GjBk88MAD3HTTTcUFPRaL8ba3vY077rhjkF3NuHHjuOeee7j22muprq5GURSqq6s577zzuPvuu4+5oK1YsYKf/OQnzJ49G7/fT0VFBatWreKuu+4qBpXs7z34yU9+kpUrV6JpGpFIpDiuPp+P3/3ud9x8881MnToVn89HLBZj2bJl/O///u8g24obb7yRW2+9lWnTphX746tf/Sqf/vSnR6xvfwSDQb797W9TV1dXbHfvOxMKhbjrrrv4r//6L+bPn08oFCIQCLBgwQK+8Y1vcNttt71uW5krrriCRYsWDXlOlmV+/vOf853vfIfly5cTjUbx+XzMmDGDz33uc/zud78bYJv2RqC3jy666CLuuusuPvShD43qvmuuuYY777yTs88+m5qaGhRFIRwOs2TJEm699dYBxO1kvUcA//Vf/8WCBQtQFIVYLFacn/F4nL/85S988IMfLH4vSktLWbVqFXfcccdxpcs4nraO4eRAcE9UTPEx/P8Sn//854uSm9tuu40LLrjgTa7RGMYwhjGMYQyDMabSGsNxY+vWrbS3t7Np06ai4XNJScmYS+UYxjCGMYzhLYsxwjOG48YLL7zAD3/4wwHHPv7xj48FzhrDGMYwhjG8ZTFGeMZw3Jg8eTKxWAxd1xk/fjzvec97Tqqh9RjGMIYxjGEMrxdjNjxjGMMYxjCGMYzhXx5jXlpjGMMYxjCGMYzhXx4jqrR6Xf0UQUMUJHQnD4wJhN4qiMUEbBvSaReBkzMy4ZCALEN34tilS7EoamUljmliNDXj9iRZfEtCEFEjcYxkx6iv1+IVuKaBkfICwimhGFY+g2tbIPTsHVyn71wujevYx101JVyCXcjimMaxLwbkYAQ5EKbQ2QyOg+QLguti67meqkvFekj+EDg2tp4fqcgTCjleglJRgVPQMZqacI3RtWsMYxjDGI4XIymtjinhERCIyZWUKrUowphR6smA3ydQUy2hKlBaKlJWKiIIUFYqEokIBIMCmgp+v0DALzCuVkJVYXytzMQJMooCixYqTJwgEfB71wYCAlK/0dVUqK2W0DQoiYlUlIuIIsRLREpiAoGAgNpzn88nUFsj4dOgvFxk+nQFRYF5cxSmTZXx+wV8Pq8+ck+4EUFRKLnwAio++H4q3ncdoSVHhbUXRBAEEHt+D/kjDvN3z08/iD4/Wnk1kj+EVlaFqPpAEBEkCa28GkFWBpdVrIqEpPmJTJ4LgoAgSiBKIIoIotT3vyAgSD3HBQFfaTWB2snFc6LmK5bvK61CKykvPlPS/EUSJIiSV07PswRJ9p5xNAQRUVEJT5yBEor11UXoq5cg9iunpwxJ9RGtn4uoaF7fqJrXfgQkf5BAzSSv3wFJ6T1HT3/JPf3j/S1IMjB8fqzjhejzUXLpJVR88P2UX/8eAvPmHPumYRAKi8iKV7dgWKSmTqanW/EHvOMjpPYahP7XSjL4/MfXbn9AKN6jqFA7QUbzCcVzvXU7nu7srVP/No3hKIzwXTgpzxr23DDHxbFxe6vimEbLLmC6BqIr4Y5Jd044NA2WLlHRdZdszqF+gszcOQr3P5RnxTKVQw02JSUiTc02sahIKu2waqXGE0/rmKaLpnnEZnK9jGFYKLJAaamIqgisXqNjO95at2iBiqwIZHMOEydILFmo8tAjBRbMU+jsclAUgbY2m/IykfYOh+VLVbZsM+nqdoo8ZUKdRFu7g15wqa6WCAYEnn9JB9uT7mgTJyCoKpKq4p8ymfRLq8FxUCIlaOU1uI6N5Avg6HkQBBzDAFzsfA45GPIkEbgICD3ndVzb7pGggGMY2IU8dj6DaxoIokigbjJGdzuhyTOxcxmsbBo5EMLOZ1FipYiygiBIWPkshbYjSIpGbLpHxiSfn2D1JHxlNTiWgSDJiD2LvmMa6Il2tFg5jlEgdXAHRqIDNerlBFMjpUQnz6Nr62oESSY2bSGubZHYswnXsYhMnkvn5hcR/AGi9XPBddGTHWixcgRJwrFMkntexS54UhgEkUj9bJRQFDVahpHoIDR+KiBg63kkzY/kC+A6Nrnmg/jLa3Fti2zTAYxkJ1bBS2kgKhqxKfPItR3BMQpEJs4iUD0RQRApdDYTnTqfXMsh7EKeSP0cZH8QK5cG10ErqcCxbTINuyl0NJ2Q+S3H42gT6hBVFaGkBF99PdkNr0JPZO1jQRChtFzCslymzdZIdjs0HTaRZZg+RyOddBBFKK2QaThgMnuhRmuTRWebTSQmYlku+axLtETCMBxMAyJRkVTCZuJUlUzaobnBIl4uIcvQfMT72yh4Xzt/QCSXcUgne+orQDQmomoCZZUyPr/A4f0m2YxD7QQFSRZobbQYN0mh6bBJ9TgFBGg8aKJqAooqkOy2CUclRBGyaYdIiUQ+5xAKi5RVyuzboSMrAqWVMof2GkRi3rWFvEsgKOA40N1p8xqEh//8EAW0mjiiXwXbBUnEaO32FipBQJBEHMNEkERc00GQRVzLRlAkcFyPwDguyCKuaSMIAi4uruUgAI5hgguipiCoMlptKXpTF65pIfTs7gRZwikYyCUhjJYEUlArnncdF9/ECvTD7diZt7CE+yRBElVEQcJxHVQlgG6kkSQFx7HR1DAFI4mmRDDMDJKo4LgWntzFxbK9/pIlL62LIIiIgoRl6wiChADIsh/DzKAqQQwziyjKOI5V/G07I0uPR+Wl5WDTaTZiuebr6YsxDAFBEPBpAq4DJVGRuXMUaqslDNMlEBCpnySQSDgsnK+SzbqMHycxaaJCIGAQj4uUxUX27LNIpV1UFXbssli2NMDhwzam1fsM0HwCkigQConMm6MybpyM47gossDUKTJ791nMm+N9nONxicn1CgcO2YgiTKlX2LbdJJlyURWB5habxYtU8nmXXu2Ea5hg93yBXRenUIAe0aIciiIHgri2jaAoSJoP13Vw9AJmOoGVS+OrGoedz6GEIzi67qlzBAG1pIxC2xEEUcZXWUtmv5coUA6XoJVVY2WSyIEQki+IYxookRJE1YcSNlCCEeRQhEJbE6KmIQgiaqwMW8+RObKXsvmnE6ydjG3oKIEIkj9IvvUwCAK+smpc1yG1fwuB6kloJRUe8eqBkezAzmdBELGyKXKth7EySfQuL1WCXcghiCL+shr0RBuFjmbKF67CzGdI7d1CqG4aciBcJDyyL4ASiJDav53o5Dn4y8ch+QIYqW4C1RPJNu33iJhl4K+qI998CDOTIFI/h65kXw4wx9QpdLUiCAKOZZBvawDXJdPg5ZHSu1oBATUSR5Rlunetp3T2clzHId/RhJVL4y+vPWGExzEMsHvIguN4as7j8JMYP0lhwmTVIzWVEtG4Q/V4ma2vFLBtj4jH4hLj6xVamyxmztcQBIFwVGT2Ih+4sG+nwdRZGhvX5NHzLktO89PWbFFRJdPZbtPdblNZKyPLAr6ASPU4BVmGQEgkn3VAEHj+sSym4RIrkZi7xIfruJRXyxi6S0mZxO6tBnrBRVY8qU/9dJXuDpsJUxQkScA2XWYu8OHzC+zfZTBpqsrubTptzRZzl/iQJEh2OUyYotDaaKH5BerqFQo5h8kzPMldtETE0F1ESWDd8zk62954xuOLVRIZN51U424K3S3HvuFEw3Gx0nl8sSCiX8PO5Iksm4ZrOwiShKCIuLr3ntp5HSuZx9ENtJo4uC6ipuA6LnY675GjvIHZlUYKedLa/L4WXMvGN7kKO5lFrYohajJySQhB9KS5oiqT29OEFPaD6yJHAljJLNq4MpyC6c3vYdIIvVHwxSqI1M4g3bSHfHcLb5QpSshfieva6GYGnxpDljRkyYfjWPh9cUwrj1+LIYkyPjXaQ2pkTDtPV2o/oqgQCdRQMFMASKKC3xdHQMRxLXxKhO7MIXxqDE0JIwoykqQhihLZfAeZ/MhzclSER0AgIpeRstoHkR5ZE/HHVDIdOq49sFPVgESkKoBtOiSbczjWwPOBEhVLdzByFiNBUgQCcR/ZrgKO+foGTvFLaCGFbKeO6wwsSwvJhCv8WIZDqjmHc1R7AnENM29h5kf+0EiqSKBEI9tZGNTmo6HrLmvW6QQCAomky8OP5pEkgXze5ZnnC1iWd01JTCSbdxEFeGWDQUeHQ2Ozp77SdZeX1+hIkoAoQqLbYfPWPqZr29490YhIV7fDI4/nURSB7oTD6rU6ggDpjEtjo41uuNgObNpikEg4CCK0tTvk8y4bNxn4NAEEyGZdXt3c7xmpFMlnnye8bAlWMkXqxZeKC1uhrRGjux3XcXrUMC4g4DoWruMgSjK2nse1TTJ7tuFYpneN66J3tIDrIvkDmOkkjqF7z8ulyRzchWuaCJKEXcjjWiZmOokgybi2hZHsBEHA7bGFcW0LxzQRFQ0l4KXAsPUcdiFHvrUbX3ktjt2z67MsXNtGDkYRJbkonZI0P5Kq4To2ouZD9gc8WxnXRQ6EPbWSICCpPo+EWSayP4QSimLrBU9q5Vg9euY+0XevjY0SDCMqKlYuA4KA3t2KlU977XBscBwcXUfyB3EdB1svIGp+JNWH7Atg2haSFsC1LURZ7amnJx1yLBPJ5wdR8qQ6gogaiuE6Do5p4JgGruOc0I+11d1N6rnnCC5ahNneTnrN2uMiPPFyia52T+qiaSK7DumMm6QQCIsEQiI+v0g+7+APCLiuS2uTRWuTRWWthKm7dHXYmKZ3vGG/yeKVfoyCQzAk0tZi0dFiUSi4FHIOVeMUNE2gtcmirl5B8wmsebbA0tMD9GogAyEBx3HpareZMc/Hlg0FJMkjI8GQJ1HqbZ7mF+hotXEdb8arqkB7i00245DNOmx/VWfmfA1ZFlA1gVTSpLlBIJWwCSPi8wuUVsgUcg6G4TJ5pspLT2SpqJHxB0Sgxy5L6dlAWCffNqp06lIqZq1E8Ydp3vhYz7t64uG1ycWx9AHHBUUiMKUa13ZwdBNRU7CzBVzdk7AIsjd3XcvG0U2M1m6kgIYgS9jJnHdfwcTsTKGWR4vXSwENO6fjmjY9AmZEv4rZlcbqziKF/dgFr62i6qmEpaAPKaAhagpS2I8giYiajCBLyBE/dio3uE24OObANp0MlE5ZQvns0+nYEaVpw6MnbW4c3SbHtcjr3UiigiL7cRwLAQHLLmCaWURBKhKgvJ4g4IsjSQp6D8EBMO0CBT1BwFeGKgdxXO+bbBhZZFFFEmQU2Y9p5ckbCaKhcQgIOKMQyByT8EiChCyouDgIQ5j8lE+JsuTaep76wVaynQMHMlzpZ+HVk6icEeWBL7xCqqXPUFIQYdE1k2ja0s3+l9pGrEOkKsAZH5vFs7dvJ3EkO+i8Z6IhDCIoQ6F6dgmzLhzHs7dvJ58YOAmiNQEWvmMS8boQD315Pem2PpGkIAosubaegy+3c/iVkQ1dS8YHWfnh6Tz1w22kWwcbhwqS4IlPbe/jmEy5JFNe3fP5vja0tvWJ/TPZfiSrZ0Of63dtIukCLvG4yLoNRrG84v0Zl0zGHvSM9o6+ZxzpR+T6J2pOpbzjpumSTrtEIgKbtxoD7sV1yaxdR+aV9d6C1k9l4Vom9ggfRts0yB3e66mvBl3X8yLZFkainyTD0MHom2+OXvBUrsdQlRjJDrRYGWo0Tq75IIWuVgKV45H9QYxkh0cEELAKWaxcBn95LWY2hZnuRo3EAQElVAKuRxLUcBwjnUDvaiNQPQElFEWQZGxTR43Gybc1Iml+tFgFyX2bkXwBbNNA72rBLvTNZVvPk2trQI2WYiQ7ybU24CutQglGsPJZrHwGO5/FdWysfBZ/eS1KOEb68E7USBzHKKBGyzxSKcsIoogcDGNmktiFLL7SaoxUF4IoI6keedK72/CV15JrPoRjmx7psUz0zhO4c7dtUi+8ROqllwfNi9Fg91aDuYs10imH7a8WKCmTaTxkIQC25RKKiCCAYbgEwyL7dxlU1Eg07DfRNJFU0qazzaaQc3Edl0zSQZbwJDsdNrUTFSIxm0BQxLZdDu4zmDBZpb3ZovGQSy7jcGivgd2zcWlvsYmXO0RKRF56OkusxCNWiS6beLmMonjSJcf21GGNh0wmTlUptLgc2GMgyQLdHTaCYOK6eOQnZdOWdWlttIpqLdUnYBqQ6LIpq5BQNYF1z+Xo6rCxLMj0vJOirFI5923oqQ669m98TUbyxwPbLODYFpaeG9E49PXAa9Mq9HQ3XfvWD2iTa9qkN+wffNPRXhsC3nxzQVQkjOZu7FwB/Uind53rojd0euRGEhEkEbMrU7wnu/1IX5mu69034Bku+f3eZgxBABfyQsuA80e3qWLOGZjZJJ17Xzn542QUcG2zZ5yO750bLURZ8dqUS9G5Zx2uY5PONQNg2QXaunfQu7kFl2yhE3B7jgO4GFaWoK8Mu6c/HMcknfOky5l8C5l8f3sol7ze7f02ksVjAgKKHGBUxnLuCABcEcktkavdiFTmSshuTwuKPzVzS9zLb13qBku1QecA1xdV3at+uNyNVvsHnYvXBd1AiTrkff1/SuqC7hXfW+aWjA8OeX7cwlJ34inlriAJxyxrwrJy96KvLnT9saGfG6nyu1f9YLkbrhyivhNDri+qHPMZ5VMi7hXfW+ZGqgaXAbgTlpa5dUvLXISRyxn7GfsZ+3kNP8fzXr0R7+BJfIYaKnFnX/1Zt3rR+a4gDv4+n+gf2R92Q1WTXdkXOrltuuo/3ZrFF7iCdGLaJCjy8OMg4CKJJ7XflGDMnXXlZ9zaJRedsDaNPE4hb5z84ZPXpkDUa9PSi19Xm0RBcuHYa/fIZfQ9fyQcU8Lj4AAusqiC4zHZoyEAVbNiSLJIojFL+94URVI5xC5AUkUmLC1H8Us0b+0ecC5aE6CsPozil8CFroYstmF7XktTIpTVh8mnTFp2JLAKNjXzSph7yXgEUSAQ00gcydKyMzGiKkmUBGrmlCApIl2HM3TsTxfb1dtr/SH7JCYuLUdUBJq2WECfFCI2PkjZpDCyJoILnQfTngRHgIppUSpnxMh16bTuTGBbDrXz4sy9tA5TtwmWaHQ3ZGndnRykDhzDGMbwGnE8r9Ib8dqdxGf44zXIvtDJe8BRsPJpMvn0SX3GyWiTa45gNuHSZ2d2kuCPV6P4wyf1Gf1h5TNk8pmT+gx/vAbZ//rHyXFfv7TLM34+No5JeARAEhRGemvjE0LULSrDMmxmnlfLmj/spWV7YsQyVb/EgqsnIcki2x85AkCwTGPpeyaTbM4RKvMxYUkZT/5gKznTIVoTYPLKSlLNOSqmR9n5eBM7H29EC8oESjQcx8UfVch2yT3xg4avb1l9hHELCzi2y4xza3npV7s80jNcfQVQgzLzr5iA6+xnzzOe2C5c6WPptZPpOpShpC5IzewSnvj+FmzdITYuSP3KCjJtBSouGsfWhxrY90IralAhENfQ0yb+qEqmo3DSYugUIYpIoRDahDqUykqkSBhRVnAdG6dQwEoksdraMJqbsfMFsI49eQRFYYDfe3+44Nr2qMoZBElCUGSvDNMsqkAERUGpKMdXX49cWoqgqbimiZ1MYTQ3ox8+jJMZrO4cXHEBUdNQa2rQJtQhl5SALOHqOmZXN8ahwxgtLaOKFVPsAxdcvUe9JssopaX4JtejlJcjaiquZWGl0hhHGr165vNDbgTecEgSUjjcMy8qkEJhREXGtW2cXB4rkcBsbcVobcXJF/qM0kfAMeeFZY2qnEHlyjLI0uB5oaooVZX4Jk1CLo0jKAquYWInExiNzegNh3Fyo4g5JAiIfh/quHFo48cjx6IgSd770dmJfvAwZnubZ5x/rKJU1XNNdtziPBJkGaWyAm3SJJSyUkRVxemZv3rDEYwjR7x5MQoowRjhqnp8sUrC1VM8z8O62Wih+AD1Rdu258l3NRGfshh/vIbO3WspJFoBkP1hquafjSCKdOxYTb67uXi8YuZKzHyKjl1rcR2LcO00SibM7QlZ4CFxcAvJIzthBHWJ7AsSqp5MoHQcshYA18XMp8l3t5BtO4iZ67Pb6GtThdcm1Ud0/GzUYMmANrVvf4FcZ+NRHS6gBmNEaqbiK6lGkGSsXIp0yz5yHQ1D2hnFJswhWDGRzt1rMbIJghUTCFXVo/hC2KZOrrOR1JEd2MZr97RSglHCVZMHtCkyfiZKIDqwTTteJNdxhJL6hQTLxtGxZ13RIFz2haiafzaiJNO+czX5Lk/dI/tDlM9ciVXI0rHrZVzbIlwzhZKJ8weO06GtpI7s8GzzhoGkBQhXTyZQNn7AOBUSrWRaDwwcp0CUcPVkfNEKwtWTkVQ/0XEzUfyRo9r0ErmOhoEP6hmncM1U/CVVCJKClU+Tbu4dp8Hf3Oj4WYSq6uncsw4j002wvI5Q1WQUfwjbNMh3NZJs2D7qcRqVWzq4KKLPcxceAkbOZuvfG+huyHLK+6dSf2rFiITHMhx2PdVE3ZKyAccjlX78UZU1v9+D4peJjQvSeSCNFlawTYftjx6haXMXcy+to3pWjJ2PN3JwTTs1c+KYus2r9x7CNo/N1Aspky0PHCbVmue0D0+n/tSKEQmPmbfZ8VgjE5YNrG+sNogWlNn+yBEilX5CpT66D2UJlfuwTYetf2+gdWeSRddMonpWjL3PtXBgdRt1i8tIteTYeM/BQYbTJxpiOERo4UJCSxcjl5QgqKq3eAgCvTYVrmXhGiZWOkV+5y5Sz72AnUyOWG7JxRcSmDWTofSmrmWRXv0yqedfOL7KSiLhZUuJnvk2nEKB7of/QX7nLqSSGJHTVhJcMB8pGPQWVVEE1/XqrutkNr5K90MPj0hUBEXGN3ky4VNXoE2YgOjzeeRKELx+ME2cXJ7Cvn2kXnwJ/dDhEYlJ/Iq3458yGTudov2P/4frOIRXnEJo8UKkcHhQPR1dx2hsIvn0MxT27D1ue5YTCSkaJbR0McGFC5FjUW9e9AaO6TcvHN3ATqXI79hJ8tnncLIjk8rSq67AV18/5DnHNEg98xyZda8cZ2UlIqvOILx8GXYuR9ffHkA/eBC5NE5k1RkE585FDPi9/u5xO3ZtC7egk375ZRKPP+mRpGEgqCr+aVMJn7oCdVytNy/kgfPCzmbJ79xFevXLGI1Nw88LSaLsmneg1Y3H6uqi7Y4/Ivr9RFauIDBvHlJo8Px1CgX0Q4dJPvMs+oGDx5wX/ng18cmLkLQAaigGguhJD+JHVUX13HvVYIz45EXkOxuLhCdQWkvp1CVeuIJEa5Hw+KLlxCcvJNmwsy9YpayihuJImh81GEMJRNBTHaQadw9rH+KLVlCz5CKCFXXeWNi25+EkKwiiROeedT1Gz9776i+p6mtTMAaCgOIPQbz6qDb5jx49IuNmULPgPJRg1CvPdREVlbIZK+jcvZbWrc8MWhD9pbVen3Q3U1K/kNIpizy3dkFElFUKyTYyrftfF+Hxl1QP0abwsG1SAxHikxeR62ouEh5/aQ2lU5cgSjKFZFuR8Pgi3jilGvcUx0mUBo+Tkekm1bgLGHqctGg5tYsvJFg5cchx6tq33jN67jFKPnqcBEFA9ofwD2qT76gnCURqp1O94FzUcAmOaYLrIMoqZdNPoXPPOlq3PINtDCT9/ng18SmLyHe3UDJxHvGpixEEsW+cUpNIt4x+nEaZPFRAFlTEYeIU5rp18kkDS7dJt+epmBIZValHfzOSTTn0rMXy90/DdVxaticopEy0sEKmQyfdmsfSHQopE7leLJbh9vwxWiO6bFeBQsrAKthkOgqEyo8enOEqPPDfrsMZbMvh1A9NQxAFGrd0oWdMQuU+0m15Mu0FbMNBT5uEynw99fWUZu5x1Pe1QgwEKLnwAsJLl3gfWa8CHtu3bU+aIsvex93nQ4qEESSZzLr1xyQ8UiSCXF5ejMbdH45pIgaDr6HGAmIggFJRjmtZSLEYUkmM0iveTmDWTK+eAy4XEFQVVxRxsrmRyY4sE1qyhNj55yJFo8V69+8L0edD9PkIlixGHT+OrvsfJL9r97ALkByNIJeXIQYC+KZOxjdpEqEli4t97dp2X9mqiqiqSNOnIZfG6fzzXyns3fsa+uj1Q4qEiV9+KcF5c/v6tP+86JkTgiwj+nzI0QiIIumX1xyT8MixKHJ52dDzQtcR/UcvWMeGIAhIoSBKRTmSaSJFwsjl5ZReeTn+adM8ojaggQKCpOIgYGcyxyQ74VNXEDv7TMRQaNC8ECQJoWdeyCtOQauro+v+Byns2zck6REEASkWRakoR1BVfFOnEJw/j+D8ecV6urbnbYco9s2LObO9efGXv6IfPDRif2Sa95HvbAQEKmefTvms0+jav5H27S/i9AudYOneWOUTLQiCgBoqKRLaQOk4bCOPIEgE4rXFe9RQHEGSKSRb6f3gJQ5tJXF4G6KsUb3gHCrnnNHT2GH6VFIombyQ6PiZdB/YRNeeVzALGURJRg3FCZTVkm7ai2P3jUumZX/PYi5QMfs0KmadTveBTbRte37INvXCH69h3NJLkFQf7TteJN28D9e20KLlVMw6jYrZp2EWMnTsfGmQlENUVMpnnIogCLTvWkO+qwnXsVECUURJwsymeD0Y0KZZK6mYfYbXpq3PHdUmz5srn/Scd7Rw/3Gq9QzFLQl/af9xKkGUFPREa3EeJhu2kzyywxun+WdRMedtI9ZPkGTikxYQrZtN4uAWOvesxcz3G6fSGtIt+wdIXjKt+3vIsUD5zFOpnHMG3Qc307bl2SHb1At/vJrapRcja0Hat79EpmUfjmV44zTzNCpmnYalZ2nf/uIgg25JVimfsQJBEOncvY5cZ2O/cVIwsyOvVf0xKsJTcDLoTr7HnmcwQmUawbiGnjGJVgfIdPTz1hIG/dF36qgopPmUia3btO5K0rIjQbotX/S8ch13EOHwToBjOih+GVmVsFz7mN5a4XI/gRINU7eJVPlJ9fOkEvr9DK7wUfXtNrB0h8bNXbTvTR9VX4atr226qAEZWRVxLHdU3mWvBcHFCwktXACyjJ3Nktu6jdz2HVhdXWA7CIqMHCtBHVeDNnEicmkp+R07sDo7j1l26tnnyO/chRgIIAUCiIEAwflzkcInSE8tSShlpfgmnkdg5gysRJLCvn3oBw9hp9K4gFJaglbnqaUK+4bw3OiFIBCYO4fY+echRSO4pknh4CGyr76K0diEa1mIfj/apEmEFi1AqaxEqawkftmldPzpL+iHRl6ARJ9G9JxzkKMRHN0gv3kLua1bMds9rwQ5FiO4YB7+WbOQAgGU0lKiZ67CbG/DTr6+j+prQWj5cgJz5oAkYafTZDdvIb9zF1Z3AhwHQVGQ43HU8bX4Jk5ELomR27IFK3XsunY/9gTKxk3FOSEGA55kLhA4IXUXZBm1qorgwgX4p0zB6uwiv3cv+qHD2OmM551WFkebMAEpFEQ/eHiEwgSCixYQO+8cRL8f1zDI791HdvMWzBYvHksvmQ0uWIBSVopaW0v88kvp+L8/YzSNHKtIDAYouehC5JIYdi5Hftv2nvfPs1uUS+OEFi7AP2M6os+HWlVF9G1vo+Puv45ILB3LKC5Ctlno+a1jZJO4zmA1cqG7Fccy0SJliLKKYxkESmsodLXg4qJFSpFUP7apo0VKAaEndks/uC6OWRjoJj7MZ0uUJE8V5TgkG3aQatpdPJdtP0zi0Fbv5n6EcUCbjALgYpsFjFxyQPyrAc+RVcqmLUUNRmne9BRtW58rtj/X2YhVyDBx1bspnbKY1JGd6KmB3rWipKCGYhx+8R5SjTsHEiJBHL6Bo8RQbXJMfdg2eeNkoIVLkWQN29IJxGspJNq88QuXIml+bENHC5ciCOKw42Sb+jHrL4iSR4Jd1xunxqPHaUuxzL42mUUVoW0UPGHwCG0Cb5xKpy5BC5XQsvkZWrc+U7w219mElffGKT55McmGHejJ9oH1lBTUUAmHV99LqmHHQEJ0nOM0KsIjCyqKoKE7QxtB2abDnB7D4WCpxku/2o0oC0xYWk7NnBLidSEWXDWB5m0J9j7XQumkMHVLyqicEcMXUdGCMruebMLI2/hLVCqmRQmUqKTaChx8eWSXdYCWnQkWXjWJFR+YypFNXRxc0z6iast1Xea9fQKSLOKLKmz460EkVWTisnJq58eJ1wVZcNVEmrZ2s/e5FipnRBm/qIyKaVEkWSQY19j5eCO26RAoUamcESNc6SfVnOfgmvZhn9uLpq1dzLtsAuoHZRo2dnL4lY5jxus5XgiqSmDGDASfDxyH9Mtr6H74kUH2E/qhw2Q3bQJZRq2uwinoI+6I+9+nHxq4mKjjak8Y4REEgdDiRYh+P/l9+0n84xH0ww0DXr5emiqFQ56NyTBQysuInrkKKRoB2ya9eg2Jxx4ftKgU9u0nv3MnZe+4CnX8eJSqSiJvO4OOu/40cp9IEkp5GU42S/c/HvVizfSzXzKONJLfs4fY2QmiZ5+JIEn4pk5Braoi/wYTHkHTCMycgaDIuKZJ8tnnST799CCjTf3QIbIbNyKoCkpVNU4mMyqbLH3/AfT9B/oOyDK+SZNOHOERBMKnLEcMBMjt2k3iH494KqbBFyKFQtj53OBzPVCqKom+bVWR7KSefZ7k088MsqUp7NtHftcuyq6+GqWqEnVcLZHTT6PjL3ePqPIUZBmlohw7maTroYfJbnx1wPtnHDlCYc8eTwq78lQvUOXM6SjlZejHkKQdD8x8GjObQIuUISkasupHCcbIth3E1vPEJs5Di5ShpzrwRcqwzQKFxLG/Y8NJeBzL9GyH6hdQPvNUcB3SzfuwCt76MRQpey1QAhFCVfVYep7k4W1HleuSaT2IVcjiL6lGCUQHER4QSDfvI9O6f7CNy0ly5R4JZj6N0TNOoupDVDXUUIxcxxHMXJqSyQvQIuXoyTa0SDm2qVNIHnt9HA6ubZHraiI+eRHlM1d4buUt+7y4X3DCXOcVf5hQ1WQso+CNk33UOLUd9EJtxCpRg7FBhAcg07KPTPO+wXU6znEaldFy3kmDKAwp4ek8kOYf//0qkuIF20u35uluyAAC6bY8TVtcmrZ2g+upvlzXpZAy6NiX4oX/3QmAbdjYhkPd4lLyCYP2vUkc22X8wlJ8YYVtDzfw4i92km73FrXD6zto3d0nxmrY0Emu28AfUUi15EeUmLTuTPDoNzchaxL+mEqqOUfiSBZRFEi15nHWd9CwoRNcl2yXt5vprdNzP/UmgqXbOJbDpBUVpFvzdB7wjk86pRxZE9nzbAsv/mJn8f79L7XRsLFPanJwTTuZjgK+kEKiKXdSPLREvx8xEPDiEzkOhQMHRzYWtSyMhiOv86knth1SLIZxpJGu+x/AbB4+NoydHsEbQZIIzJuLUl2NIAjkDxwk9dzzQ++gXRfjSCOpF1cTv7wcKeDHN2ki2oQ6Cnv3DfsIQRBwHYfM+o1k129AwEEMetFxnYKJazu4ukFm40YCc2aj1lQjqipqbQ35N9iWRwoGEf0+b16YJvrBgyN6qLiGiXF4BCnJsXAS1LZSSQx9/wG6H3gIs22YD77rYqdH8CaSZYKLFqKUeeq33J69pF54cWjDYcdBP3CI9Np1lFxwXo+qajJqbQ3GkcbB1/egd16kX15LbtPmId8/J5cn88oG/DOmo5R7ajC1puaYaq3jgevY5LtbiNbNRlJ8KMEokqJRSLRiFXLEpy5Bi5Ri5dNF4uOYo7CJGGZoXcem++AmfNFyonWzGX/K2ymk2kk37SXZsL1HYvH6A+FJqs9Ta8gqdadeNUClAt7apYXiiLIyhE2J1wAj041tnPxAgKOC65DvaiE2aS6SoqH4w0iqn0KiDSOXoFRehi9ShplLokW9cXo9dXcdm8TBzfii5cQmzOkbp+a9JA9vp5BsOyFBEkVFQ+2Zc+NXXDFonAC0iKdKHWyj5cHIJl+XPVUvjkl4ZEEjIEbRpAA5e7CuTM9Y6JmhFhyXjn1pOvYN/uik2woDgvoBiLJA1cwSUi15dj/djKRKxMYFe6Ix27Tt7tsJZzv1AUEObcOhbdfo9HiFlEkhNXi37tgu7XtStO8ZfE+qJT8gaCKApIjUzovTdSjD7qebUQMypZPC+KMqZt4aUN9M+8C22oZD647R6x1fC1zbojfZjiAIqJWV5Ldtf2t4B40Wrktm/foRyc6xIIWCBGbNQpA976Pc5i1Y3d3D3+C65Hfuwjk7jRTwIwWD+OonjUh4AOxkktzWrTiFAmppiOj88bi2Q2p7E0a79w7YiSRGaytqjWfgJ5eUeMarbyDh8SJI93g4STJKZaWnDvwnmheuYZBet254sjMKyLEogenTQZJwbZvsq6+OTJAch/yOnUTPOB1Z05AiEbSJE0ckPABWZxe5bdtHlBCaHR2YnV0o5eVe3eIlr6lNw8F1HPLdzZTNOAXZH8IXLUeUVfJdzVhG3ktvE62gkGxHC5eOaIw8ACPEeTOzSY6se4jE4a3EJswlWDGByjmrKJ22lO79m2jf8SJGZoT3cBQQBNHLfSd4c1kaIiFvr8rHHmbh9iQGb42577reOJXPOhXZH/YkPYpKvrsJI5f2CFy0gnx3C75IKR27hpB4HCfMXIrGdX8neXgbsYnzCJbXUTn7DEqnLiVxYBNt21/EyHQdu6ARIIgiouTZNYqSMmTi5Hy3Z0zvGS0P9lv2pEKvf5yOSXhMt4Dl6kiOjMPJiw7pWC6H1rYx+6LxvO3jsxFEz/tr8/2H3gzp4jFhWw77Xmhlxrk1VE6PIYhQyFjse7H1LVFfJ5vDaGlFmzgRJInwilNwDIPcps3Ymcyb6iE0WjiFgufN9DoghcOotTUIgoCVyWA0Nx+z7XYmg5VKo1RUeG7m5eWeu/Nwi5brYnZ2YrZ6C7DRmaHQlkYtCRTJBXh5pZxcn4pF8PlOfkiCo2BnMphtbag11QiaSuSM0zwiuHWbV7d/gnlhZ7MU9o5gszUKyNEYSlUlgiBgJpPe2B2D9NmpFHYmg1wSK4ZJEGTZc7UfCq6L0dLi2cyNAKdQ8HKM9UD0jdKJYrRwHQrJdlzbxl9S5alDjDx6uhPXsTEyCXyxSnyJNiTNT767eUQ35r5yRz7tmDqpI7tIN+3FF60gVDWpJzXFaYiySuMrf39dEgTHtrDNAq5t07D6vmIC3aFgFYYjs28NsgOA61JItvWNU6gE29AppDpxLAM9040/VkE+Wo6kBbxxOhExbCyDVONu0s370KLlhCrrKZu6hPKZpyIqGo3rHnpd0hXXtr1xchwa1vwNMzf8xsJTe568MRmFSktAFf0IgohPDJK1TU5W1vSmbQm6G7IofhnXdTGyFoX0WzRhqQtHNnbSsT+N4vOy5OpZCz0zuvoKiPSm63CPUhUKeAnVbHdose9I90qCguPauK5D5pUN+CbXo1ZVIZfGiV98IaGF88lu3ERh/wHMzg7cwltEnDsErK4u7NzwNhijQa+aAADb9kjMMXJFCaLYlxlZEBD9fs8bbBjC4+Kp1ex+kk5REhAVCdfq90FynAGEQngzEgw6Dpm16zxj5HgJSkUF8csuJbR4oTcvDh7E6ugcVRyiNwtWZ5eXnPa1QhBQKsoRez0XLQu1uvqYHmSipnnxdejxxgoERiQ8Lp7kzxnBjsi70B1IMI5jXvR6fQqCOLLEJZ/GyHbjj9eiBqPku5pxLAPXhVxXI+GqKfhLa7D1PEa6i1EtOqOI5A+9KrVm8olW8l3NTDrzOqLjZ9Ky+akhCY/reiuMIEgjPsQqZCkk2vCXVCNrgcFxX95C8Lxy6RnbEdqUz2BkugnEa1D8YQpdzT057mzynY1EaqcTiNdi63n0dNcJlcy6jk2hu4VCwnN/rz/zvUTGzaBl05PDEJ5+c2+kNulZColWL1ChFiDbduLUtceLUcXhERDQBD+6kGUocdNQ0DSB088LsGV9gdamgSw0FBG5/N1hwlGRR+7LcHCPt5C4tkuu24Du1/axLS2XWHSqjxefzJHLDF3H2gky02arrH46TyE/8JopM1TOvixId4fN3+/OkE2PvMtxbJdc17EJw/S5KqXlEmufsfHJUSynQEgtI220E1LLyBqdSKKK7ZhIoowoyMiiStboxrBzgItPDiOLKi6gSgF0K4NPiZDVO1AkP6adR5ECqJKfgpXGdArohw/T/fAjlFxwHkpVFYKm4auvR5s0Caujg8Le/eS2bye/Z++AHeZbBV6wu9cncZAifSES5HicsmuuPu4yBEUZ7BLfH67r2X70X7QkESmkISqDxbdvNgp799H18D8oOe8c5PJyRL8P/9Sp+CZPxmxvp7BnL7lt2yns2/+WJD6D+vp4IQhIkXCPmygoFRWUX/uu4y9GVeFol/j+cBxvDh93rK1RMgko5rTyxSqRFA1rGE8Zu5BDT3XiL6lE9oVJNe7yctfhku9somzacgLxavR054iSklHVXpTRIqWeBKl/fVwH2zLAdXpUZkP3i214kkZfrAJJUbHsoTcaZj5N8shOguV1lM9aiZ7uHGSYLGkBZC2Inu58UwyRe2EbOXAdfNHecRq6TZaRp5DqwBerRPYF6di5uifZsEOuq4myGSu8ccp0HWOcjj2HBFHybLbSXbj96+M6OJbeM0YjEZmeNsVGbpOZz5Bs2OGN08yVFFIdgwyTJTWA7A+ip07uOI3KaFlA8l4MOzNIojAcFE3g1LMCNDVYgwhPIeew9vk87/94jHETlSLheb2IlYqsPDvAxpcL5DJDi/qqamVOWRVgw+rCIMLT0mTx6ssFrnp/hKf/kSV7giKo109TqZ+u8urzLiGtlIKZRhKVHoKjIIkqQaUEVQqQt5IUrDRhdRymrWPYWQRE/EqUgFJCWm9HEmUc10ISZFQ5REiNIwoKqYIXPCzmq6E9tx96VBVmSyuhJYsJzJ/rBR9UFJTycuTSUgJzZ2M0NpFes9azXXmdEpUTCsd+3TsY0d+nHnBfQ/LKnhuPef7oXb7ZlfUC4FlvPRWRa1lkN76K2dREaOlSArNnIZXEEBUFtbISpbycwLx5GEcaSK9eQ2HvvlFHAX4j4Nqvc14IwgC10euaFyOtK0PMixONbNtBjGyCSO00xq+4kmz7YU/6pPro3Lu+uLBYeg491UF8yhLAs23ptdPRUx24tkWwfALJxl0DYqiIsooWKUWUNSRFwxetBAR8sUoiNdOwjbznEp/pLgaNkzQ/45Zf5tkJdTZiZLpxXQclECVSMxVJ9dO140Vsfeg5lW09hJFNEK6ZSt2KK8n0tknx0bVvQ59nkuvQuWcd/pIqYhPmMPmcD5BtO4SZSyFIMmowhi9WQbppL00bHnlDsskPh0zrIYxMN+HqKdSdeiWZtkN9bdq/sRgQ0tZz6Kl2QlOXAT3j1GOnUxynigmkmnYXvd5giHGKVRRtsyK107H1XE/oggR2z/hKqo9xyy5FUnzkuhox0l094xQhXD3Vi5mzc/WgmDq9yLYdwsgkCFdP7tcmkBT/gDbhOnTuXY+vpJqSiXOZfPb7ybYfxswme8Ypii9WSbplH02v/OOkjtMoJDwuGbsLzQ1ijzJfRd+9Q8Oy4NA+k1TiBC8Go/wGDndZJuVwcK+JaZxYlV3ft9klbybRrQy2a+K6Ljkjgeu66HYO3c4WgxF25Q9huza9X1TbMckYnehWGhcHyzEoWGlwXXJmAtd1EAQRw86Rt1KIQs/QOg5mWxvd/3iE9Jq1BObOITBzBtqEOgRNQwqF8E+fhm9yPZlX1pN49DEvHstbASdiGPqVYScSZF/dhD2aVAP9YHUdnwpFiQVQy8P4KiNk94/CvffNgG1jNDXT9cCDpF9+mcCcOfhnTEerG4+gqsiRMPKsWfjq68mse4XEE0++KTGD3ghYHR1kN2/BOU71rtXehqsf6+N8cm1ECok2ml75BxWzTydSO52SifNwbBMjmyB5eDu9LXIdi0KyHUGSMFKdA9IFmPk0eqqTQNk49GT7APVFsGICk8/5AJKi0p/dlU5ZTOmUxZ43nKnT8PLf6NyzznuWZXrql3EziU9ZhKR45NJzo26nZfOTdOxaO+zCVki20bT+ESpmn064dhqx/m06snPAtbae48jaBykkWomOn0V0wmzP08d1sApZ8t2tZDsOn/Ts5MeC3tumOacTrplKbMJcHNvEzCZINu4qXuc6tjdOooiR6cLI9Tm3mPkMhVQHwbLxPR5afeMUKBvPlPM+NGic4pMXEp+8sG+c1txP5+61gGcDletsJDp+JvH6hT2ebAK2WUBPttOy5Wk6dr08rJ1VIdlO4/p/UDnnjEFtSvVrE3jj1Lj2QQqJFmJ1c4iOn4Wk9Y1TIdFGtr3hpI/TqOLw5J2055p+nFAUOPUsP+dfESKfdXjoz2mOHBqeNMkKrDgzwKIVPkQBNq4p8OKTOWwLps1RWXVBkHBU5MBug6ceytLd6VBZI3H5uyOEoiLphI2qHVuUF4mKvOMDEUrLJXZvM/jHPZlB0p7+KCkVOeeyEBOnKCS7HZ59NMuebQaSDKefG2D+Mh+ODetfKvDyszkcG+Yt8bHqggCW5bXLsSFnJsBMAHhkBcgYPQviCEIuF5eU3lr8X7c9UWZaPw4vFdfF6uwk9exzZDe+ilpTRWDuXPwzpiNHoz2RiBcD0PXQ30eXl+qfAP0lE3YmS3r1mtfl3TMa2AUTO1MgncgdW7IsSwiiMDBHU296B4Aee6L+5wVN8WyDetV9/a8HBLXn/KgMT13M1jaS7c+QWb8BtbaG4IL5+KdMQYpGEH0+QqcsB6D74UfeUpKe14xeFWQP7FSa9IsvFQMC/jPBdWwSh7eR6zyC4o8gSBKu43hB+9IDA4h2H9xEvqvJM4Dtd87IJDj04t1Iqs+zC+lH0nIdR9j72K+GjJxdrIProif7VEm2WaB505N07FmHrPqLuZ1c28IsZDGziREXtuNpE3iLadvW5+g+sAnZF0KUFW+BtwysfAYznx6kJuncvY50097X7YE0WriuQ6Jhu9emQARBknEdB8cs9PR5HxIHt1DobvHGKdXXXjOb4PCLf0VS/T390C8mWVfT6Mapn8rPMXVaNj1F595XkFQ/Yr9xsgrZEYMJehd6gSXznY3HbBN4Hlht214gcWALsr9vnBzLwBxmnLr2bSDTegAjkxi+HseBUREeVfAjChK6kz0ug+VITEIULR6+O81ZFwc5/8oQd/wkwXDOLrPma7ztgiCP3JvGMFwufWeYXMZl3y6Dq98fZePqPHt3GJx/RYjz3h7iz79Oce7lIfxBgYfvTrN8lZ942bFtJmrqZJ54MMtLT+Z5xwcitDVbvPjk8B/ycy8LUVkrc///pZkyU+VdN0T56Te7mDRVYcWZAf5+dwZZhguvDpNOOTQdMrniujBrn8uzf7fBtTfG6O58c3cYRbgudjJJPpmksHc/6vhxRN+2isBsz3U7uGC+F3l3+443u6YnBFYiUfxb7In+e7LhFExAQA77PNXWcBBFtEm1CIqEcbgFRMFz4Qz4sLqSCJoKjotSXUphuxfMT1BkAgtnoB9swjUtXMNCLothdyVBFHFtB6WqFKujG7vrOCQyjoOdSHjzYs9efJMmEnnbKvzTpyEqCqEli8lufJVC/6CC/6xwXaxE385ZDIVOvGfUGwnXwch0H9PNe7gM2q5jFXM0HQ3byJNpOX6POMfU0ZPtvGaXiGO0Sa0tRSkJkd3RALZnEzSaPuiFkekaNdkRfSqBGbXoTd2YbYnRtmAwXAcjm8DIjlyGVciQKQw1TvaJHydLHzLQ36jR0ybLyRGcVUfhQBtW9whx0VwHI9uNkR3tOA0xpoKAVleGHA6Q23UE1xz92npMdwABgahcTlypRhbUURcMkE46rH8pz66tBi89lWPCZAVJGZqBCiJMm6Nx5KDJpnU6W9fr7NtpMmexRmWNjD8gsPqZnrKezjNjnoaieobGLz2VY+cWg1deKJAYBbFoOGDx6toC2zfp7N6uM2OeNuy1sgLT52qsfibH7q0Ga57J4/MLVI2TmbXQx/5dJlvWF9i8TufIAZOZ81Ti5RI+v8ArL+bZsclg8yuFE64mOxFwTdML4Pb3h70oxngusdr48SMbY/4TwWxvx8n26KwjYZTysqKx6smE67r4x8ePfaEo4OQKyJVxfDMmIZWEkeIR5PISfNMnIgb9PYksB5aN46BNrEGdUIVcFkUMB1DrKtEmjwPXHZxfavQV91Is7NpN998fLsZAEv1+1Lrxr63MtxpcF7OtrZhFXS6JIcfjb8i8OGkQBIJzJ+CfWvNm1+R1wzepktCiySNeE5w5ntjb5ha9KU8mpGiA8qtOJTCj9tgX94NSHiGyYsYbUseTCTHoI3rGbKTI8JtFKRKg9JKlqNWj+Oa9TgiSSGTZNEovWYroOz5OckzC4wKmq2O5xrC5tEa83+37PWyOqp7jkjTQFtF1XVxn8NrrOp6Ln+u5kBUl97bjjt72sPc57nA54D1IouB5Eva2o7dNbm993QHH+z+/ty32CU4bcaJhdXYNyAvUG4n3XwF2Ko1+8CCu6yLIMoHZsxBDryWx6fFB1GSsZH5klZbjYHclsZNeDignm8NOZnFyOqKm4mTzCIoEkoig9iQkNS2sVk/M7RomTq6A3Z1GEEXvvTBNBEVC8KnH4+wzJMy2dsz2vt2f6Dv+xJ9vVVjdCfSGBm9eKAqBObMRfcNvfN7qEGSR6Gmz0GpL3+yqvG6EF08hOGPciNckX9xOyx1P4upv0bAlgH9qDeElU0F6E8JPnECo5RFKzpyHFBj+/TA7Uhy57QHyu0cOxPlmY1QqLReHbrPluI2Ww1GRBct8tLfYLD3dT1ODhWW5CALIsheSQJY94mDbsHeHwSXvDDNtjopRcJkyU+WJB7O0Nlk4tsuiU3zs2qqzfJWffTsMLBMaDpgsO8NPW7PF3MU+SkqPzabHT5KZOV+j8ZDJ1Fkqzz3mqR1EEaRivTyio+su+3cbLDvDT2uTxbTZGpbp0tpksWuLzlkXB5kyU0WWBerqFR76S5pEl41jw5zFPvbuMJi9UCObfhNIz1G2HcNe5tOQwiHAI3B2ps94+p8dTi5HdvNmtPp6z/16+jSC8+eTfmn1sW1ceknfa+gLvSWJlS7gGCO/M1Z7AteysNr7xLZW28iiduNgc891r8Hm5DjaJPp9RRWg67pePq1/EdipFLktW9EmTvDyzs2ZTWHfPjLrN57UeXGiIcgigTkTCM2eQHjxFNSKGL76KgC6H9+I3tABokBoYT0AZluS8NKpSAGN/P4W0uv24Jo2UshHcN5EfHUVnoq1pZv0uj1YiSwIEJpfj1IaJvnCdhzdBEkkvKAeKewntWYXofmTcAoGWl05Tt4gu/UQ4cVTcAomyZd2eCQ+oBGcXYdvYiWiX8XsSJJetxez3VMv+qdUE5w/iejps3Et2yPtQGbjPjIbPXWNVldO7IzZiJqC0Zak8++vDBovtbaU8IJ65HgIp2BSONhKdsshnIJnJC36FIJzJ3rSMNclt6OB7JZDfUFCJYHQ3IkEZtXhFAyvD49j96BURAkvmUp0xQyU8ihV15+FazvoRzrofmyjd01ZhPCSKaRe3kVw9gR8EytwCgaJ57dhtiURJBH/5Gr8M2qRoyGcgk52yyFyO48U74+cMp30hn0YTV19x1bMILVmNzgOwXkTsbM6vvFlpNfvRY6HCUytIfXyTgoH20AU8NWVE5xVh1waxjVtstsPk91yCFwXKeInvHgqoQWT8E+tofwdK7GzOnYqR8eDa3B1C9GvEj19Ntq4MgRRoOsf69EbB9pZiX6V0IJ6fBMqECQRsyNFZvNBjOa+75w2vozwkqlIIR9GW8Kbe1193xulIkpk2TTkWJDC4Q5EdVTUZRBGfVdYLiVltWO5o2PUju2y5ZUC6aTDuz8cQS+4/O2uNKYBi0/18bYLglRUS5xzaYiZ8zXu/m2KLet1oiUSF1wRQhThlRcLbFhdwDJd/vzrFG+7MMjS0/0c3m/yyH1eZzxyb4ar31/C9f8xnv3butm41rt+OGQzDs8+mmPabJUzLwywe5vO2uc8NdX5V4SYu1gjEBT50CdjbN2gc/+daR7+a4bz3x7ivR+JkUk53P3bFJ3tDq9ukAnHLC5/dxjHhRefzLFlfQHHhr/dlWbV+QHmLNTYvd3gjXYS0OonEZw7h8L+AxgtrTi5nOdp1C+fj6DISOEwwQUL8E+dCnhRX/WGhhHzbgmq6qlMRBFBEkGUECQRQfakEAICYsCPHI97LsSOg+vY3gfFtnDNk+uqOwCuS27rdvxTpxJctBDB5yN27tlIoZDnsZVK4Zqex5wgigiKjKj5kCJhtEmTkPw+uh99fOQ8ZEdB1GTCs2pxdBMz8RZy8wfPI2/qVAp792K2d3jzQtePmhcKUjRCaOkStAl1gJfzSW8YIbCbIHjxio6aF6Kq9KnXBAExGESOl3hzwXG8WDCOA5Z10l24B8B1ybz6Kr7p0zzpTjBIyYUXIoUj5LZuw06n+wJNiiKCoiD6NKRIFF/9JARJJPHYE29cfUeC7WClvHlmJXOYLR4RdnqkH4IoEpg+Dn99FVYii5XIIsgiakUMtydGkK++isiy6ZhdXgqD2Jnz8E+qouWPT+MUDALTavHVV5Jauxt0E0ESCcwYh1IRI7NxP8HZE9DqytEb2gnOriM0byJWKo9/Wg2OYZJ8bhvauDKiK2ZgpfO4pkVk2TSCsybQ9MtHsJM5XMfFTnsxlpycXmyHnenzRrLTefL7W4meNgvfpCq6Hlk/wM5VG1dK1QfOwU7l0Zu7kUuChCITye9rxikYiJpC6aXLCc4aT/5AK4IiUf6O01Cr43Q95pHd6IqZlF66jML+FhxFJnj+IpSK6HENiZPTcXQT17QwWxO4lj3AtkWOhYidNR+1phRRlbFSOdTKmPfe0KNGOn02gipjJbJotaWEF06m5Y6nyO08ghwNEl05C/1we5Hw9B7L72nCtR3KrzyV7NaDKGVRQgvrMRo7kaJBtNpSjtz2AIIiETllBkp5BLMzjRIPUfneM2n703NkNuzrmUNGsf/NjhR2Moed64st5Vo2ekMHcthP2eWnkH5l70DCI4mUXryU0MJ6cjsaAIHAjHGYnaki4QnMGEf5O1ZidqSxUznCi6YQmjeJlt89idmeRCmPUHPD+SAKFPa3EF5Yj29SJUbL8W/4jkl4JEFGFfw4PZF9R4tc1uXXP0oMeW79SwXWvzS0m+9Tf8/y1N8HG3pu3aCzdcNgE7jGQxY//Z5OyfQ5dG5uPKYP/87NBjs3D33N/Xeluf+uwd5onW02d/1iYO4rQVbx1S3g6af38Mg9g3M9rXk2z5pn3zyPFikQILR0KZEzTsfq6sZobsbq7MTO5nAtC0GWkSNh1PHj0MaP78s19eomjBEWNjEYJHr2mciRKIKqIGgqoqohqKpnHwMgS4QWLsA3aRKuYeAYRvG32dRM6oUXR5WR/UTByeXofvwJxHAY/7SpyNEosfPPJbR4IfqRRi/5qGN7C30ohByPe5F4NY38zl1eEsjjeZ5ukdp6BCuVf8vF4ZFCISKnnkL0bWdgtndgtrRgdnbh5PPevFBk5GgUrW48am2t5yFjWWReeQWjpXX4ciNhYuec7SWsVVUEVUVUVURNQy6JAV728PCK5QRmzfDUcb3zQjcwGhpIvfDiGyo1cTJednspHEabUIccL6HkkosILV+K0dhUTMEiqCpSOIwSjyOXlyEoCrnNW96weo4E13LIbjlEfn8LsVVzyGw6QOLpzUNe659SzeHv3ENu++D3O7e9gdy2w0UpR2TlTCquOR3RrxYlI8eC1ZWm+bdPMP6Tl+O60HrnM1Rdf5anZhMF8vuaafzZw8Xo48E5Exh382XIkQB2MkdhfwuFg62EFtRjdiTpfPiVwc/ozpB6aQdqRZTQwsF2PkpZBLUyxpG7niO/z5OEIvZJun0TKwgv6iEOO7x+KLt8ObHTZ5N5dT92Tid6xhxyuxpp+a1HaKMrZ1L53jNH1QfgSdES7VtQKmMgQOejG4ZUvUkBDRyH5t8+Mei8nc7RcsdT3ibABTHkY8Ln3oF/Wm1RynNMuC7dT29BCmiM+8SlNP/6ceRIgPKrVyL6FOxMgfZ7XvLGw3VBFKj77NUEZ9eR2bAPO5Un9dJOnIJJZOlUEk9vGUQyXNMmt6MBK5Wj5NyFg6ogiAKB6bXkdjXS9qfnvWcJFKWkYkAjfsEiCofaaf3D0+C6aOPLqP3YJYQXTabr0Q0EZ09ArS7h8PfuRT/UjhwLMu6Tbx9dHxyFY8fhcR1M18B2TZwTkLfjWBBlleiUeSiREhzTwNbzZA7vJjxhBpIvQKGzGSPZiRqJkz60k0j9HKx8BiUUJT7vVAC6d7yCGokTqJ6IAGSO7CVQWYccjOCYOlY2TXL/Flyrb5KFJ8zEV1oFeGHek3s346uoxVdSgV3Ikz60E39lHZmG3fhKqxBlBVFRiU2dj+PMJn1gJ3YhS3jSLERZIddyCDkQQYuV4fZIOJJ7XsUaIY/IiYTnwWNAMIBSXlYkI8Uga4Lg7coFwVNj5fLkt20j8dgTRWPOoSD6fIQWL0KODr/jEQQBKRxGCocHnSvs20/65ZffUMIDYLV30HXf34iedRaBWTMQg0GU8vJiwsaj4boujmF4BPE4F2FRk4nMrsUxLNI7m0f21HqD4ZgmjmEi+XyoVZWoVZV97XOcYloDL9O3i53JkN20meRTT+Pqw/vciIEgoWVLvfQLw0AQReRIBLlf9Ote5EJBUi++9IariczmZjr/cjfRc8/BP20qYiCAWlmJWlk55PVuj1H3WypA5yhRONhWlAYcDSmoEV46Dd/ECkSfgloRQwpqx5X+xOxKg+NipXK4hifJdQoGoiJ73oc+hfDiKfjqq5ACGnI8jBTyvXYD+yFQaOggv6+FyuveRnbrYdKv7EFv6sLtUS37plSjVESpuOa0ogRMjgYQVAXRryEoMkppmMQzW4pzsXC4fWTPo9cIJ2+Q3XZ4SDIkyBKBGeMIzp2AHA0g+jS0mvhxqXLsbAEnp3tqpM40Tq6Ao8meU4MiI0iiZyC+sB6lJISoyvgmVhZVjCcCru2QenkX8QsXIwU1Umv3UNjbjJXyvolyNIivrgJtfDlajWfwLCgSUsiHHPNsLX0TKyk0tGN19iRhzunk9zUXrz8eHLP3PMkOyKIKjnCy42iBKCIqGmYmiSgpiJKMqGoY6W5kyyRUO5nW5gOE6qYht0dQI3Hy7Y04tk1i53pi0xbii1cSrpuOkU4gh6MEKsYjyCpWNuWJ1TUfoqJh9yM8ks+PlUsj+YLYhRxarAw7n6Fg20SnzCe5fwuSz48aLsEXryLXehhBFEk37EZSffjKPL25GophZBKEaidjmwZmNoXsC+AYBZRwyRtGePQjR0g88SS+qVNQysqQwiEvJ1SP8ZRr27gFHTuVwmhtJb9jJ7ktW48ZZ8UpFMiu3zgggvHxwGzvGJhfqj9cF6OpifTqlwE8VdyJIkY98WY6772P3LZpBOfNRamqQo5FvUW6R5LhFArY6QxWRwf64QZy27YNq87K79zlqcRcF/3AweJxR7fIHepEVKQeF/U+FA4cLKapKBw+PLqs1CcQ+v4DJJ98Ct/keuTSUqRQyDNS750XloVb0LFSScyWVnJbtpLbueuYqUecXI7M2nUjp+AYAUZzy7Bkx3Uc9EOHi/NCb2gYOT7I8cB1MZqa6fzLX/HPmklg9izUqkqkaBSxJ3WEa1k4+Tx2Ko3Z0YF+6DD5bduHrWtu+3as9nav3sfIpt5bh8KevUVCqe9/fYlRh4OdKwz57olBjfJ3no42rozuJzdhtiXw11cTv3jJiKYrwtHGuL02MI5blBS5rosAiJpC2dtPITh7At1Pb0Y/0oFaGcNfX/m6jev7w+pM0/KbxwkvnUZoQT2RU6aTfH47XY9txMl7zgBWMkfiuW3YuT4C7xomZlsCpSLmxb3qp3Z3TctTzZ9guLaNnR36vQrNm0Tl9WeRWrub1OqdOIaFWnkMtZooDOxLxy2+U65l9zn69BzzT62h6oPnkt/dSGrtbuxUrkgyThgcl8RzW9GbuoieOoOKa07D7EjRfveLFA62IsgigqaQXrOL/K7GPnrhukVpkqjJuKZdVL/iukWyerwYVWoJWfA8Pt4ovx3XsXEMHVe2EWUVX1kNWrQUI5NAkGUc06DQ2ULJrKVkG/fjOjZ2Potj6DiWCYLoBbZyHfKtDZjZFP7yWmyjgCCIngpm0ENdbLOAIEk4toUciqJGSsm3NXgfcRdyjfsJT5qNme7GzKZw9AJ2IY8gSEg+z13MdR2sbIp8awO+8hoco4AtevURBNGz0O4xJhYEASQJtbrac5PN5z17gR6py9G/e+tZNNLrvzMSBERNQ6mowGhqwsnlSK9dR3bzFuRIBDEY9OwpehImuq6Lky/gpNNYiW6qSk0ufaePI4d9rH1JR1Vh4mSZ3dtN+m/snWyWrgceHNU4Tposc+oqjQN7LV55WScQFBlfJ7HTNRlyuXIc8jt2kt+xc6izJwSubpDbvIX8zl3IJSVIkXDR9sS1bVxdx87mepI+jkz+Us+/MOw5pSSAWhbC6Mpg53pUAq5LdsNGshs2Hne9qwJT8ctRDqVfxTlO54Fe1AZn4xNDHH5hHZl1ryBFIojBAKKmebtsQfCkkbqOncniz8qMk+s5bGnkGZnw2Mkknffc95rqdUw4DtlXN5F9ddNx31rqq6PEV8vB1AYsZ3gJlZPPk12/gdy27cglMaRQyFPNiSKVWj0RJ8yBltVku5pGJn+Og/nsBmqji2hIbyVvdgx/bS9cl/Tql4uE7jWhZzEQxBG+0sNsVpV4mOCsOjr/vo7ks1tBEFCr4n154FxwDBNRlYskR1Bk5NKBEtyR9sJS2E9o3iSSa3bR/eQmsB1En4rY433YV4i3Kr+exLpWMkf3E6+SenknkeXTKX/n6WS3Hya/pwmzI4lrWhQOt1HY188UoSdFpBTWcXIF1H42O1LIf9zuz7iA4yXWFF6DnCA4dwJmR4quh1/B6s4gRQMDpDtOjxpK8PX1n1IaHnDNsZ4ZmDke17ToeHAtZmvC8+4cyoW+n0bgtcC1PLVXfk8T2vgyqt53FrGz5tHym8dx8gZWVxonp3v2YUNseszuDMHaUqSAVpRYKa+RmI0qeaiLiyJovBGUx3VsjHQ3jqkjSDKiJGHrBdRwHFFSyLUcBscjFaKiYiQ7cG0bPdnuqd/S3ZiZBMm9mwnW1KNG4hjJToxUl6fCEkDUVZyjdohmJukRLcvAtTwjVkn1oQSj5FsbcG2zmPvDTHfjGAX0VBeOqWML3ttiJDu93CDhOFY+i5n0zvdmu7WNPFptLa7jIPp8iD4fVjKJUuapm+xk0svurSiePYWq4uo6gqbh5PMIoojZ2YnV2YmgKGjjx+MUCkjhMIIkYedynqrJcbAzGZTSUq8My/LK1HUQJex0GlFVMZubsdNpYiUiF1waQBC8fGKu41JZ7U2NXm41aYqMKIKiCOzdZRKNidSMkygUXA7uswYGkxQgHhc57xI/hbxLS7Ont62qkXAcb05LEkyo98qUJIHdO0zKKkSqayQyGZdDByz6D5EsaiMuWKNFSCsjZ3R79kStrTjtXTiug/s61bWaHEIQBAqmJ8HLN3Th5E2c4wiKNTwEYloNEbWcxsw2jNdEeAQiahlBJc6RzFbMfPaYhC7un0xVZCrtuX3krRMn5j4WVCWEJod6/nPJFjpfM8mLqBVU+OtpzGwf1fxxCwXM5pYBgc/FaICAT8Pp7MK1jp1iRJODVAem05U/QmY0hOcEwLUd7FQO35RqtD1NnkSzI4WTP7b9jaOb2NkCamUMtboEJR4mesr0vqztrove3EX8/EUE50ygcLgd36RK/FOqye8dbL84ZP1MCyudQy2LeKoZv0bs9NmDXbZdz05HrY7jq6/ENSzsdAEr2eNJ61cRNQUx6ENUJOSSME5Ox87rYDuoVTHUmlKsrnSPVMMdIOnIbW+g5Mx5xM9dSLfwKk7BRAr7PeeGPU2YXWny+1oIL5tGfl8LjmERXjoVOXr8C2wvUfFPqcHszngGzG2je4+sRJbAzPFoNXGkkI/wkqnIsVDf+e40dsEgvHAyZlsS0acSWT4d0T/60Ap2MoeoKmi1pYiKRHB2HUpljMLhgYEI7awOrot/Wk3RHspo7vYIl+wFSpWjAQRJRIr4kWNB7LzhqeokkfD8SVjpPE5e96Rndt94mN0ZUut2e8bWB1qLxEsuCZHf24ydynljdtZ8Isumkd12GKUihn9a7WtSvY1S/uwiC8pxGS2/VriWSebwrkHHcy19KeXVaBnhCTPItzZ4GWMdh9Q+z4gwfahPOlDobO4roP/fQyDbNFiMnGs+WPxb0gKEJ87AMQoUOltwbYv0gW3AwKwQ3TvWDv8QUUSLTsBsbcU/daonrcrlsLq6EAC1qgopGsU1TRxdR/T5cCUJUVVxDQNBFJECAazOTk/94LpYiQRqVRWOaWKn09BDpqRwGCkQwDFNBEnypFSKAqKIk8t5XieBAHY6japCrEQkmeyLY1QzTmLmHJWD+yxs2+WSKwPs22XS1eng8wucc6GfbNZhXJ3MU48U2L2zX+oDQPMJRGMihbznoi8IUDdJYlydzP69FoIAl10dYOc2k64OG39A4LyL/XR3OtRNkvnH/XkOHfAWOUlUqSmZSyrfTM5IEPZVYDkGupkh4q8ip3chSyqSqFEwU6iSH0GQSBdaCfkqcF2bvJEk7Csn5CunsXsLjm0hIFIenoKLSyJ7BE0JI0saWb2ToFqK41rYjokmB9GtLKIgoch+sgUvu72mhEgXWgmqcQJaKVm9o0h4jPY0RvuJUl+6NGW30573YzhvXFb7hNHCzu5nSb9Bi7YHAUlQiIXGY1hZVDmIYeXQzdfWl225fWTMTnTrjXOpz5rdbO96mm596Ki4JwOuadP12EbKLltOzb9diJMzaL3rGQr7ewiJ7eBazpBaQ6szTdejGym9cDH+KTXY2QKFw+2IfrWPKOw4QvqVPZRethxXNzE702Q3H0TUFFzcHm/MHvWJ7fS5eNveM610nq5HvfpV33A+Tl5Hb+z06ndUpZLPbaXs6pXU3HghTkEn8cQmEi9sR+jx+PFPqfaIQNhPzY3nY3Vn6Pz7OgoH21DKo1S8Y6X3fTQsXMeh44E1Rc8hszNN6/89R9klS6n50Lk4PQl+06/s8bybdIvOf6yn4prTvLKTOfJ7mrz7jzPrfWbTfgIzaqm8/kycvEl26yHa7+6RCruuFyF4mDJTa3cTmD6Oive8DSenY7R0k9l8sNivdipP9+OvUnrxEmpuuhA7VyC/u8nzJnNdLyZXjxoLxD6S4bo4PY4U6U37CcwcR8U1p2Fndcy2BJlXDwxSexpNXXQ/tZnSi5bgGhZ6Y2fR0NpXX0XZ209BDvkRAxqlFy8lumIm6Y37SDy9BQSB6Blz0WpKPKmU42I0d9H91Kbi/Eg8uRlRUSi/coV3zHGxElmMxk7sVI783iY6/76O2JlziZw2C7MtSW57A3JJiOOF4I5gkekFnxMISTEERPJOGst98zLOFuslK0haAFvPDTA8PqkQRWR/CNcyh83yOxoUpTc95MM1jKLRniDLKJWViKqKncthdXbi2nbRUwZRLEbCRRA8z6oeSRDgBZ3rUU0IsoxWUwOiiJVIYKVSnseJJBWvcx2naDx86VUBWptt1r7k7YJr6yRWne3jwXtyZDMuH/xoiAf/mqe12aa0XOTjn4nQ0mQjSfDskwW2vjp4HK56d4C9uy02rffmzKQpMstO1bj/7hyCAO/5UJC//TlHR5tDZbXEJ/4zwoF9Jooi8OQjeXbv8AiPgMC4+EJaU7uQBJl4aCKtqV3IokbEX4VPCWNaBbJGJ6WhiWT1LkwrRzRYi2XrPXYEAulCKxF/FS3JnZi2Z3RaEZmObmXIFjqojM6gK3sIyzYI+8oJaqW4QCrfTMRfheu6pPLNxEMTsB0LxzGRJT9ZvQNRkDDtAolcA6ImI4d8IICZzA8b+lwVA2hSAFGQcFwH0yl4CWT7BfgMyDFU0UvqZ7kGGXNgriMBAb8cw3YNbNfCL4URBQnLMcjbqX6OBgIzS84gqMTZ0vlYMR+bJgXxSSFyVhKzh0ypoh+/HEVAwMUhY3ZhHxWOQpOCSIKCbufwySFkQcFxbfJ2epAkRRIU/HIYSVDpH+bTcnWyZmJAe3sRD9fj4uBTInSl96Ob/WJyiL6e58s4roPl6uhWFoe+fvZJYTQpiICA7VpkzM6jniPglyOeCtrR8clhJEHGdk3yVnpAeydHl1Hmm8CWzsfJWYmeOvgJyFHyVgrD8eaSLGgElZJiGzNW16C+UEQ/muQnb6XRpBCKqOK4DgU7g+kM/K6IgoRfiiCLvf3Wk0jYNcla3YOcSCSfHzUeRVBEHMvC6s6C5eI4FmpJBEQBo7MbAckLdOk4qL4wpp5BVBSkqA9HdLyduQ5y2I/RmfK+MYKIFPQjhjUkWcVKZ7FNA8nnw04VEEMqqhYm19KMWhrFtgzMriRS1IvjZCdzIIkosRCCT+mR3OSRQj6sZLb4jsQrZGxHIGupiEGNUESiMm6zf303esFFKY8MUi+5tuOpRQpe0M26BXG6ulz0gourm1jJLIrkUFal0HTQ+3aqUR+Tl8bparfoaipgp/MDpGFS2O9JfmwHK5lDDGqEAw4UdLrbRy9tlMJ+pJDfi6ieLXhxjQBBlZFjQaxEtmhQPQCC0HOvD1zPEFzoicxrp3vmiSQix4KIPgXXsLFSOeSIHyvZMx+jQex0gfiilTiCTtfLqxEkETkaxOz0NsdSyOdFUHY9zzAQEGSxWM/iXPSpnhRHlrxwG50pz3vMr6KUDXZCsDNeW/01E4gtWEznhqcRJAHXcrAz+QGhBvr3h6DIPWEJDKx0rk9VWzwv4WR1HNNC9KmeMflRpHEkJ5NRSXhkQUUVfejOW8PbxLVMrH4idkFTkEuj2KksUsjvRavN93xoFMkzphsFOxf8GkLPxBxwXJVxDcszen69de8hGK7R93K5PWIV1zTRDx1C1LQB2bmHrLnr9pXVz8imWJZhkN+/v0+VdVRZI8U8CQQFlq/UmDlHofGwxtrVOo4DZk98o1TSYfMGA0EAveBy5NCx1TahsMCK0zWmz1I4tF9lxzYTx4ZevtrdZbN5o4Ghu+TzLk1H+sp0cbFsnYAaw7DyWHYB29YpDU7Cr0Z7bKEgoJbguA6a7C2GppVHElXyZk9gMzWKKMoDetS0cp4ER0pjOyamlSegxYn6a3BcG0EQCKpxBEREUSSoxbEdq1hGVu9AlQM9hMf7EEkBleiCOs9La1czRttg6URMq2ZSZDEhxYuMKyKSt1Ns63qKrNnn+lkVmEKpfyIhpYS8leaV1nsHbDpkUWV6yUosR8dxHWJaNYrow3QKHE5vpjGzbQAR6A+/FGF6yWmoUoAdXc8WCU9ErWBiZBF+OYImBVjXeh9Jo091ISBRE5xJmX8CSb2VUn8diqAhCiKtuX3sTa4pLt6SoDAxspgK/yQc10aTQz0EK0Frbi8HUuuHVDVlC+1UlswiW+jAtPvOh5RS6iNLiWgVXrwnRHQnz46uZwbUscxXR3VwBgElhuNarG39a5HkefWSmRxZiiyq6HaOEl8tiqjhuA6N2e0cTG0YVo2miD6mxVYQVavY0f0Mhu4tMAElypTYcnxSmJBSyob2B2jP9889JlDun8jE8ELaCwcp9dWhij5EQaar0MCexGrydqpnPkiMD82jOjgN13VRpV6ClaYtv5/9qXUYdj9PMUEkGq9HlDUsPYelZ1EDQRRfBNex0HMJJFkDzcEXKkOUZGyzgOILU8h24Q9XYhSSJJt3I8kaJdWzAFAjYRzHQhAEVH/My6Sd6kZTY5hOGpUocqkfI5/EJ5VCxMXvryCfbsck6RGdXtiOt1D2Q6/LuyTB5LkB6qb5aDqggwupRJZEs0W8PkxHqWdHmU5kiAcVVJ9ArEzmyD6deIWCGZPpbHGpm6oxaZbLs/d3Y3TZCALUTNKomaQRjkmoPhHVJ3J4dwEhmSAmuNiSSRqbkgkqrg21kzW6Wk30QpaScpnDe2yqai3GT/HRcpjjIjx2Ot9HUPrBNY6h3nJd7FQOOzWCN6DtFD2XemG2m/3+TiLICqKkYXanPGmb7QxQBdmZwiDyMRScgoExRHgCJ98bmHFoiLKKYMsDggwOhWP1x1DnnezxmziMwmhZIO9kAOE1pZZ4I+BanhTEN2MCdncauSKOWzCwUxmUmjLsZLYv6rAo4pqWpw9VJArbDuLkCig1Zai15SAIFPY0IJeEERQZqyOJNnUchZ2HsBNvgFjcdQeQndeFHgPU0eCFpwtFQmMYLutfNtj2qkkq5WAYLg/dkyOV8MbfNODxh/OUVfx/7P3Xkx1ZluaL/bbro0VoDS0ykQKZWamrqqu6ulqP4G32vUPeV77R+KeQRvKBTySNvDS7Y5yZnts9PdNToitLp5YAEhoBILQ4Wrjemw9+4kScUIgIIKvLmvOZZSLixHH37e5brL3Wt76lI4Bud/9+8d5PvH4Vet9XvP8rn08+CGjUJZ225O//pkurlRwb+PBf/85laFhDysSQ2onN9oOeUeETxi4KRbXzCMO10DSDnDNKy1un41dJmXla/gZB1MbUU0gVI2WEqTt942kLTXcV00gRRi6V9jyxDOj4m4RRNzEg0lN4YYMgcsmnJugEFfyw2TOADMLYw9RtQOsbPGGti7fawB7No8K9z8bUbGZzL6EJg2uVHxPJAEOzSRt5gnhwcnzcusZy5xbni2+RMfdPwxToDKdOsdy5zfXKT1Ao5nIvM5t7kUawSjPYWx3e0XOcK76Jodncrv1qIGxV9ZdoVTYZSZ3mQvGdfa8JULDGiGXA7eovCaXHcGqOmewLNIMNljpJuHfImWU8fY6Hzc+o+ovYepZLpW/TDesHGjsA2dQYYeRiGRkMzSaQIbowmco+R8rMc7P6c/y4gy5MMmYJPx4cmyvdO2x4j5jLvcRo+uC6TGVnhrXuPb6u/oxYRkxlLzOZuUTDX6XiPd7zfUtLc6bwGllziJu1X1D3t0PlrWCT65WfUrDGeGnkzw68ZsYqEyqfu/X3CeIOBXucM/nXmMhc4kEzCYkX7HGmspdZ7txmrXsXU3M4X3wbgeB+40PCfZ6bjCNkHBH6Lex0iSj0kjlPaGiGhVKJsWPaWeIoMZADr4VSEhkHRD3DTaGQcUgUuCgVoelWL3FCJunlhgVC4GSH0U0HKSPiOCL0E+9kHPnE4fG84NPnHDJ5Hd+VXHg5TbcZI4TNZ79sEQUKJ60xPmsz/7XLi+9kaTdiLFuQyetk8omH/OzzKZYf+j01/8QblsnrzF5waNUizr2QwjAFMgYpFYEn0XXB7AWHR7c9Lr+Swe3EFIYMUmmNTF4njhWnL6dYfezjdSRPwaU+HoTASGfRLAelJHG3gww8dCcNAmK3m3iB0llkkHBsNDspCaSZdl9+ZTc0O4VmmkTtFofRmjXLQU9nEEJDBh5Rt92jVGST80qJZiXZnXG3jZHJJdxUu+eR6rT2RF+ErqNncsTdzrEiM/ZI9tB6ZFHbI2odbZ17osFjCIu0lsfSUnTj3w1xUegGztmzSdbOvbtP/L6WcbBmRokb7URLwTISr0wYIrs+aBp6NtX31Hh3F7AmhxCO3X+QxlABFcUYoyWs6VG0tAMookqjl5a4nRmVOn0Goet0b39z2UTW5CTW2Dida1/9ThRoa9XthTkK6fNntrC+Orhwt5qKVvPwdlU3t48JA5i/d/g5G3VJo76/8RTuMARkHPY+6xLG3SQkJEO8sIWumQRRp8fZUMRye2Dtt7jGKiTuecri3nljGeLKpK833BXCuIuUMaDwovY2wXnrH7l356NZScHPLY/brr+iC5NYhnhRC6+3WNf34XxEyieKfSIZHDg9CcCL2jxqfo4XJ5PcYvsGV0dO4+g5mmwbPFJJbD3DXO4lHCPHndqvaQSDgoJSRfhxNOhB2AcKxePWV1T9RAjNjzuMpc+Rt0f7Bk/WLCNVzKb3CD/u4EZNOmG950052DMYxS4pq5BkjvU3Wgm/R6oYP273wnsMeHa2EKuQOA77XqsDryMDHjY/oxMlXrWFdsxo6iwZszxg8CgUhmYxk71C2Znmdu3X1PzBlHOFxI87A56k/aAJncXWdSpewkt0oxajqTMU7G3tn4xZQhMGm+5D3KiJS5NmsM6wM9t7brt6g5LU1+/Q63R0GivJV3oJFYJepufOTJutAocKuvXlfihARgHVla8HuTVi638Hn6vbTPg4ybmOtzmWElIZDdMWxJHCMAUrjwIsR2NsxqTdjEhndc5eSQjGQ+NmIm640KUwZLCxFKKbiQGka9tZrUqBaQlSWZ04ShIk2o2ITjPmzHNJbbjAV5x/MU2uqOO5kpnzDu//qEG2aBC5ktVNHyetYVgasnLYXTw72ENjlF/7Tj9DqnXnGu2Hdyg8/wpCN6h89HM0y2H4zT+kff8mMvAYfvP7hM06wjARhkHlw/cIapv9nqKncwx96zuErTr1Lz84MNVemBblV9/FzBcBQdCoUvvsVxjZAiPv/jHrP//PhM0a2bOXcUYnWf/lPzD63T9Hhkm40EhlaD24RfPrT4Fk7CAE2fNXyMycpfLxLwjrR3+QU/+rV3DGkrCZWUyhWyZBrYMwdcyszeP/+WM2f3PvSOd6osETKo9IBRjKPNA1DiQ3WiiSvnwZe2oaoesEqyu0v/qSqDaozqg5KTLPP49zOqnv4j2cp3PjBtJNJlhhmRTefAsZhkcyeIgk3v0llOsnIawohq1B2RuY0aaezAVRhOz6uDcfITQtkckG/IcraI5FsLgOin5nUF6A/2C5Lw6lmSa51xKBtW/S4Emfv0j+rbdw79wh/h0SLp8lHKdENjMGCOqNh0TRN6M8LVXcD1tF0n8m2Vxb8MJtI98Nj27wqyhGd8y9WiVAJD1Wu3c5nX+VK0M/oOItsOHO0w0bh4+xg66FwovbfWMHIJBuIsEgBq8vhOBU7ip5e5Rb1V/S2Mf7c1RE0h8Iv4XSR6oYXWxPK37cQQiNjFkmkiGmZmPrqYSrdMii6IcdwmgeXbOQPaM1ViHr3fucL77N5dL3qPlLrLn36YS1E2dx+bJDd0d4PIyT+UAXu3eUgumesXO/8SFV74hqt/sgllHfWAN6/KsQU9vWtgriLkpJsmYZL0oM+ZSRI5DewYbiVlXj/s/b/6rdn/eP2fp4rwG193tPOteWkXF8sbaVhz4yVmgatBsxmbyO15UEnuTaB22a1ZiNpZBURqNdjymNmfhu0sYvft0mCiRuV1IaMVme9+n2PMfddszNTzo4GY1Ht1yEJhACWvWYh7c8lIJuK6Y4bLC+GDB5xubTn7colA0++XkT29FoViPyZQNdP14462lglYbRTIvND/4xkT/x3eSdCH07e04kXhOhJSnjRq5I5eNf4K2vMPzm98nMniOobYJS6E6a8ivvELYaNK5/cqiukG6nsEcmadz4BG9jGWQiwgoCoRl9Q1doWo8zCprtENQ2qX3xPunp0+TOX6F99zqQeNvyl14mNT5D9ZNfHsvYAVj6j5+jmTpm3mHsh89T++wR3cdVNFNn6K0zB2wq98eRQlqW5iCERkrL0o5r2x1+B7R0hvKf/TlGLk+wtoqKY7JXX8WenmHzb/9jItMOoOvk33qb7Esv4y08BqUofucPMAoFaj9/71g1i7Ygux6ye7wwUFwbdPfJVhfZOmBH6z67BfT/nxAEbeLUEJrQf6+rrzt2iVx6bGDHGkUe9eajfQm1R0HYdBEr9X1LSygUa527eFGT8fQFxtLnmMhcYrl9k8X29RMlBuwmFR/kDipYY8kCKkwcI9cjJp9MTTRW0cDz2e88m94jhlOnuFT6Ng1/HUtPCNhL7ZsHPltNMyhlZ/GCJraZJYjaPU+douItEFT/kfH0BYacGcbS51jt3uNx68s9pN8j3cMOPtZB9wCQNUvowkRDJ20UEUI7sWik3PPc9r6umr9MzV/hbOENhlNzyfvSc8w3Pz3wuaVTI2RSwwOfBUGbRntxnyv8fiEKFUsPtufZnYZFsza4JqQyGmc1gabDwj2PZnX7761d31USNpb3D590mtvfrW9GfVmz0pjJw1selZXt49qNveuSaaQp5ucGPovjgGZ7iSh+OlpCd/kRzvg05Vfexa+u07r9FdLfe86d82pYrxBUN5C+S9RuJuGl5Evkzj6HjCJWf/o3SQjsEESdFq2718idv0J6+jTt+VsH8Fe3ry19H3d1kdjtELbqoG0ZZgKzOETp5bepffk+Qe34LjK/x4FUcQHN1GlcWyKsuyAgPVsmPTdE5f2jiXUeSYdHIDCFg0uTvg909/fCgPbnnxFWK4Tr68lDfuU1hv/yX2BNTOLevQOANTZO9oUX6Fz7MjFwgMLb75B75TU6X98gWNmVPr5lRdILD+xnEOlJ1sEWT2erYOWh39txgyqOnlwhed8HI3rKsiIROtyvbUL0rGANOKRtu+9z92lMc//77x2X1Fz5/ZrUpIxQKsa0sr2Q0O8nhovnOX/6T9C1bRGvZnuZT2/8P4jj4xu71lCW1GQRs5Sh+2Bj3+9IYmr+MnV/laxZZiJziVP5V+hEtV1E1yPiiK/ei9vcrv+aIWeW2dxLuFFzX67Ks7pmEHfphFUMYdIM1gilRyvYpNPLdtoPAkEsA3TNxAvqhNFOAr+kGazTCjZIGQXG0+eZy1/FjRosd24drVHHvQkgiF3uNz4gY5aYyb5AJ6yy2j2C9/mE1w2lRyeskDEKNIN1wtinHVYGPEM7IYTG+NAVzsx+f+Dzjeotrt35//a9ZEeBZtoUp59Dt1O01+Zxa6tkRufIDM/Q2XhMZ+PxE9u/G05hDN206Ww+7rc3N3kew8lSf3QdGR19nLkdyfUPn73XO47hwdcufH00wzmTHuXFi/9mwOjouJtcv/PvaHWeTpIg7rbZfP+nWKURCs+/RuGF16l89B4qjtBtOxGaNUz09HZqtoyjHd61HZmcQsNdeYyKI4ovvUnlo/eQ3iH3qCTN21/RXbhPZvYcpZffIWw2+uuL0JJMYCOTS37uHdNXP1e7BJ89l8atL8ievoi/sYy/cTTtpj3PpFe0dvIvXqR9bwM9ZTH0xmk2f3u0cBYcUWlZoCNQeLJ74O5CBQHdmzvk1pUiWE9KA+ysqWRNTKBlMnS+3pbs7966RfblV0idPjNg8GiWRf6NN0lfuozmpPAXF2h+8D7hxrYb3hwdI//Gm1jj4wjTQgU+7r17ND/5CNneHhRGuUzuW29gT0wkxQCzWVCKsFKh+dvfHC10tvO5WCa5198gc+k5tHSaYGWZ5gfvE6yu7PiORebyc2ReeBE9m0X6Ad1bX9P+4ot++A5Az+XJv/46qbPnUUrizc+j2dsaGMK2Gf4X/4q43ab2jz9F7bDQsy+8SPbqK9R++hP8xUOqWT/pfoSOaaQxDQddtxJVaBKiopQhUeQRRN1jTZxCCAzdRggdTdOP7bwzdAfTzGDoNpqm99oTE8cBYeQShgf3x39KhE2XoNLBW23suywINAzNIpQ+Ckkr3ETr3mM0dZqUsTfF81kiiLu9hbOCo2c4k38NP+7QDr8ZcoKppyg7Myx3vmax/TVHWShjGeIFDbKpUTLOEF2/ThAliROmZhHJEIXsZ3qNZy6Q7qfRfzNGfyg92mGVmr+MrWc5lX8FN2ru4T89KxjCYjg1R8VbZKF1/Xfaz5WM6VaX0K0UhZnL+O0q+YnzVOe/oHzqJfzmZiLA6rYw7AxKRmiGhW4mvEe/Xd1T+sPKFHCKY8RRQOS2iPwOQadBujyFZpjIyMdM5TCcLHHgJar3QkMzTOLQRzdtlJTodgoQhJ06cfi706T6XSM9dRqrPNL36mwRk/3NVdJX36Zw+SpGNo+R2VuvcA+UxK9t0Jm/zdAb36Nw+Sr1rz46sDyLmS+Snj2PikKElRCglYyQUYT0XfKXXiJs1UlNzBB1n5y5HbtdmrcS3Z3S1XepfPTescNakEh8LPz7Txn9znlGvnseGcRUPpyn8sHRN4hH8PAoWnGFQKX3us2fAD2dRpgmcaMXI9d1zFIJ6fvbIS4gqlVBxhjDOwo5CoE9PYMKQ7o3biAsi9xr30LP5dj82/+I7GwVH0tk4Lu3byE7XayxMQrvvItSksavfwVxjLBtit/5A+zpGRq/+TWy2yF79RVS5y9Q+8mPT2QoWOMTpD2P7q2vwTDJvfIq5UKBjb/594kAIJB9+SqlP/ge3Vu36N68iV4skH/zbfRcjvrP30s0eCyLwrvvkn3pKq3PPiGqVLBn58hcvrzNI4oigtVVCu+8Q+uTjwg3NvrPM33pcjL5VE62YJlGmkJ+lmJulmx6nJRTwjIz6FqSmRHLiCjq4vp12t01ao15qo0HR+LjGIaD5zfxgzZxfPQwjW0VGC6dp5Q/RSY1im3nMfRkVyPjED9s43oV6q0FNqu36XTXjrzQ6VaKOPT3chSeIVQYI3SBXS4QNfc+J1tPc6bwLYLY7RFcBWVnCiF0mv62MW9oNhmjhKFZpIwCpmYzlJoliF28qNVPYT4J/LjDg+YnPFf+PmcLb3Cz+l7C+0Ena5YxdYe8NYYmdErOJLpmEsYurWMaRlJGSBUxkblEyij2dW8awSp1f/XAhbztbeIFTYbyZ3vGbpLddib/GhKFF7VQSArWGJbm0AjW+udKMrfKmJpNxixjCJMhZwY3ahPEnT5B+SQIpcd88xOeL/8h54tvc6Pyj7hxE4EgY5axtBQ5awSBSLLYVEQkfdpB5VhZrhJJJANG06cxNBOpJLEKaQbrVL3Fb9QAUnGE11gnP3WRsNvETOWQUYDf3EDGIXZhlOzoKTbvfEBx5jKB2yI7MkvodTDtNM3lO7TXHw6cU+g6Tn4EFUcITWfj9vvEoYeUyaKrmQ7lM68Q+S5mKkvQqaGkJF2epFtdws6P9jgsiSKR21in/vj6751X+1khctvYxgSmU8ZbW6Tz8A4qCukuziMME2dknLBRY+PXPyKoVxIh3NtfJcRhoLv0CM0wUDKm/fAOsdcl6rSofPxL0tOneqV09jd4Yt9HhQFmoYwMA6qf/IqoWQdg86P3yMyeRzNMqp/9OgldSUXzzrW+ERO1GzRvf4kMA4L6Js2710BJWnevo+IIzTxmmY4tSEXn/gbz9zcOCjQ9EUfS4fFkG08ez4WopdJkrrxAsLJMsJks0ELX0ZxUUotmhy6OiiJUFKE59kB9KOl2qf7kx4lHRwik26X0R3+MMzNL99ZNANwH9/AXHvdddFo6jVEu48zM0rJtZLeLnkqROnuW1mef0bn2ZUJcDgIyz19Bet6J0sBVEFD9yY8I19ZACOJmg6E/+3OcM2fpfPkFei5P7pXX6N69S+VH/5Ckh+s6cbtN+Qc/pHvzJv7CY4xikcwLL9H67BPq7/0MFYa49+9jDg9jDiUaLcQx3vx98m++SerMub7BY42OYY6O0bl+bcBj9GQIHLvASOkiY8MvkE4NYxqpnldnEIZuYegWjl2kmJtjbOgF2p0VFlY/otq4f2jIx7GLZLOTeH4dIXTYv4LW9rWMFKPly0yNvUYmPYqhWww6R0EzdAzDIe0MUS6cZXL0Kmsb11hc+xg/eLIBYGfLyDgi6NaR4TfIzRICezRP595eD0AkQ9yoScmZxhAWCokbNblZfY9mvJ0enjXLzOWuYmo2hmYjVcRs9kUkko3uAxba11BK4UbNwc2IpiGJaYdVol4GmdA1fNlFi4w+96QdVrnf+JBT+VcYSZ1mqfN1L2X+RVJGHl0YuFGD0dQZhpw5PNXm5uZ7SQmX2O2J3w0uvN2oidcj2Qs0ivYEkBDLU0ayG7W0FJPZSzxofNILC+2dudJ2mZRVJJZhX0ZAqohO1GAkdYqSPQk9svbX1Z9T8bY3LY6R41TuKpaewtAsAukxlX0eqWLq/goPGh/3id5ql6mskHSi2oA8QBC7dKNGPzvPjzvcb3zIueJbjKbP8rj1JZowmMxcJmcNowuDTlij7MxQtCfw4y53ar/Cl25i/ITVPcRjL2oRa1ubAkHeGkUXJpEMcHrPzRA2E5mLLLSusdj+Br0+QpAZmsbOlqk9uoamG73aVgKhaaieLg+A0IzEsyYlreXb2PkRzHRhD8dJSUW3ukx94QbD519HtwaLD1vpPChJ9cFnlM9c7XuLEBpWtkzktdEMsxdOA6c4hhA66oRk9d93BJV1gkqy+RGajulkwUoRBy6d+Vt0H95Jeu4Og6/VamDYGWIR4a1uj4fuwv3+z1GrTvPmF4deW/ouzdv7163b2S7dsNGtFJpu0L7/db+tCQfoOgBho0rUamBYaaLApXXn2vEfxhY0Qf7iOGM/fA4VSR78339N7uIYUcOl8/BoG7GTlTZ+YsM0si+9jDN3iuqP/ytxc3shEr2Uwd078qRIpjYQD43q9e3wlVK4D+cp6zrmyAjcuZ1wYaRES6dwTp9Gz2TQbAc9k03UhPu1YEDFciCXf0u18qQ7hKjZSIydXtu8Rw9BgTU6SkfXscbH0VIpvPkH21o4cYz/+BEohT01hb+4gDU6itC0pAJ0Lz06ajXxFxe2DR4g2NjAm58n/fzztD79GBXH2DMz6KkU3TtHzxbTNIPh0kVmxt+kkJtGHINQLITAMlOUCmfIZiZYXPmAx6sfHOjtabVXcL0aqqeDcxhMI82pqW8zNf6tvnfpSW0RwiBll5mbepdcdoJ7j35Cu3t4iEHGEenSBDIOCb5hgyes7+/ujZTPfPMzHjY/Y9ugUyghsE/P4j94CEDdX6Hh738/qkd1jVTArdov+qNJS6cxhsq4C4t8tPrv+ouiOTXBw40bKNfdMfYUFe9xz2PQ02CSXb6u/ozdhiaAffYUskcmXex8zVLn6z3mwo3KT/qfpI0C5wpvsure5VHzC7YMG1NzeH7oDxlOzbHpPtyXpG1oFrX2I9L2UN8Qj1XEYvsaS+3rg89t11zSVQ2uN/5xj0S+sExUmITDlJLca3zYO0vveEMnUiGfrf/dwDkX2td7Bsb2Z414g89r/xkZJqTnWAXcrf+mX7tuj/pr7z1sBI/YrCwkRY53/PVO/Tf9O7L1NOcLb9EIVrnf+KifgSbQuFz+A0ZSp1jr3usrPD9r2LlhRi+/S2dzAac4SreyhJKS8pmrSVilVUFMXqQwcxmnOErQbaAZJrnxcxhOhtbqg72ZWgKc/AiFqUtJvUIpyY3PkSqMJdygzQUQGsW5K5ipPM3l25ROvYhbWyE9NIXf3MRI5ZIizJq+RS79vYSeyWIXp0EIgo31I2uhHXg+02F47hUCr8Xm/CcAZMrTBG6LoLvTWykYOfUqlYWvCLr1p7rmUWBnhxiae5nqwld0qknWYn7sHM3VuwPGrp0pUZy8xPr9j4/F1doNM59i7IfP4a03yZ0dRWgCeyhL9szIP6HBo2mkL10m/8abtL/4LPHE7EiRlEGAZpqDC5oQCN1ARkntE7H13V0dRUURKgzQHCfZaShF9uWr5N94Cxn4RPU69DxF8Y5qlnG3Q+f6NTJXroBSxJ0u6YsXce/fI9jYn1T6JOzXNhn4ifiTpiVtFIK42937Pc9DzyRkM81J9T1O2w2O93idlO/TvXWT0g/+CHt6hmB9jdT5C/jLi0TVw1Ust2CZWWYn3mZi9GUsM7vHqEgMUZkUUe11WE0kAnvb3p8krdM0UsxOvg1C8Hj5t/tmJWTSo1h2DsvKUqveIwj39xIaRopT099heuxb6LrJzplMKZVktcgYhUIT+kB7tgyfoeJ5QHBn/h/oegcrf+qmg9BNNP2bsfWTRiW1g6QXIveTjQe284ES2QRzbBRzfAyjWEz0oAp5wvUN9GKiJC3DhFgvzKTdSR20NsrzMcdGCNbW0Rwbo1xGRSHBQhL20LJZnNNzGGOjeOI+5lCZcLMCSmEUi0n4Vdd6i4hEOD3hsI0K5tQEstUi7nYxR0YwyiW8+w92tX//uwIwdQfHyNIJa7u8ESIx1w4JK+q6RSEziWPm8cNBz92Wsbf/sxfoxRwyCMHzk/IrYULmNMdLhKsVkCKpZK1ryb0LkYiRlvNJxqfrJ2rnQZj0L9NIFIF3GDF6IeEAiraLMI2kbpGUmGNFws06aut96TpoAqGZqCBEK2YT7mIzmae22qZZJtIPIY7RhUXaLLLcuUmstrPItsZr8iy/uVBO5HfYuPMhMg6TwsdxRHX+c6xMidbqfWK/S+XB5xhOGre2Rhx0SRXHCLoNOhuP8Rrre9rX3Vgg6rawbI20bKGJAFNuULnf7ClDd6k9/BIzladbWSJoVZBRQOi1CZpLBJ02SjORgQcCgk79wNRqTYOxcY21VUk2K2g2n/ys9J4N9SxyK1Qcow8XQcZozQbxIQaPkx8lP3IGw3KQMqa1+QgZBeRHzwCC+vLX+J0a7eoCpp2sGXamzOi5N4n8Lo2V27Q2H1GeuYJhpbGzQwhNozj5HE5umNBr4bcrCE3HShfx2xXs7FASmsyUEUKjsXaPbm1QZqEwcZFUfjRJAlKS2uIN0sUJnPwoodeitngdt7WO19wgWRN0ssOzjJ9/h1R+lNpSouNUmnqu560D085QmHsZTbfo1pfRzRR+p0pu5DStjQekChPoptVTwxdsPvyUKNjBdU2ZCE1Q+fV90tPlxJERxegpk6Pimc/6zqlTlL73h3gP52l88H7fawHJYh81m2ipVFJLqgc9nUmqfbea2xlMQgx8B3rscCMRFFRKYeQLFL79HcL1Nao/+hFxp4MwDYb+/C8xsttkLhWGtK99RercOazJKeJ2C2/+Ae1r14ibJxNT3Ns2Lcmk6rVNBkFvIrN2fU9HWGafjLbliRI7QnlJ5tXeV+M+uE/B/w6pCxeRUYgzPUPtZz/dY3ztB8NIcXr6D5gcvYqmDRqcSimi2KPdXaPTXafrVQjDpKNZZpZsZpxCbpqUXd52ZQuBbtjMjL9B162wurnXBeoHjcRYUfJQnZSxoSv7GjtR5NFoL9FoLeD5NaSMsawsufQ4hfwsKbu4w/DRKBfOcGrqXe48+tGBXqc46BJ57YTH8w1BswzSp0eIuwF+5cmhYGEYmKMjhMsr6IU85nCZYHkV4Ti9AoCS9PPPEXe6SS0b18W79wDn3NmkRk+rg3P2DHG9Tri+PuAZtCYniOoNtGwGPZtBxTFxo4F9+hTB4hLZb73aG6NJhqO/sIAwTdIvXiFqNjFGRjCkxHswj54/AkFyB4LYxY2aTGQuIlVEJEMMzaTszJAzh7jbeZ/oAF5gs7vCSP48QdQlPIZ+kzANrNOThCubmGen0TIO0vUJFtdxLp/qqcGaxK0u5lgZo1wgqtQJljawT08SPF7DnBjGPjNFtF5FIdBzadwv7hA3ex47TWDPTRDVWlhTo+jFLCoI8R+t4jx/BnXjAXrGIVyvYc1NoKdtZMfDf7iMfWqCaKOOXsjiXDpFVG0guz7mxDDu57eJKo2evlGFsfQ5AukSxC66MCjYY5ScqV4K/jfXf2O/S3ttMM037DYJu9uGZ9CuELSTXbXQTdz6Kp2Nx0Te/v09Djpkiy7TkzqTUzqaBNtep7IUcfq0jpcTNOoNpkbaVKuSQFdMTFRZX5NcvBjR7Sru3e1SHNfQddhY95k6nYz9xcW4X6KmXNaYnNK4eMnk/d8ElMqCm19HzM7pKAWVTcnEpE6nI2m3FNMzOhvrkukZHcuCWzcj0mlBKi1YWZaMjCbXW16KOaqjRnkesiMxhob2eBl3wzAT8UMlJXHgkilNYtoZQr+LaafJlKfxu4NrVNBt0K2v4jbWaG0+xM6UsFIF1u9/yORz38dKF0nlR9h8+Bml6SukS1PIyCddmkI3LDTDRtMNurVEbDJTnMBtrCSZxj2YdpY49DCsNHHgkxs+RW70NI3Ve+RG5ujWlvA62xttpWI61UW8doXKoy+IQ4/i5CUCt0lQXaQ4fpF0aRIlJbXVG5RnXiAJkepkh2YJ3SamncZKF1m78xvKMy9gZcoDBo/0I1SsyF0ax8hYZM+NkL8yReOro2tiPVODx5qYoPT9HxBublB772d9YnEfShGur6OiGHtisi9IaE1NIQyDYHkwlc/IF9Dz+X5IzBobRQiNsFqFOMYoFtEsG/fBfEJ8BjTHxhweRnk7eqemkTp1ChVFVP7uf0k8QU8JI5dHLxT6hGxzdDQhD1crEEXJfYYB9tQUnZtfJ7s6ITCGh9GcFMFqokoaVDbB0DGHh5NMsV61c3NkZM81ZbeLe/s2qQsXkkrrbjchXB8hpV7JmCBsD8bVe4ZOpXaX9coNGu3FfXkwQugUcjPMTrzFcOlCPwwmEBhGiunx16k15/ccG0Uehu4kWVZ7hNwSZFIjzIy/ga5vG4ZKKTy/xqPl37JeubHHM6QJg3xuirnJdxguXewbPZpmMDL0HPXWY1Y2vtjXg7A1OUf+N1cXTvoRnTtrRG2P2H8y0T8p4hphzUwnIl9+kHj4/AD71BxCE4SbmwhNR4WJN0K2O6gwQEUxmmMTrqyi53OYo6MD3kHZ6WJOjqHZDlFYRQUh0vWgFxKNavWEwKgUmm0hO120dIq41UJzHKKNTdA17NnpYzsV3KjBvcYHzGRf5ELx22yFn/y4zb3Gh730+/1PmnGG8cJEh8fQbYIjqo2rOEZ2XLS0DaaB+/U8qRfPEW3WkV0PYRpo+QwAWiGDQuHemAddQ3a9RLV9cpi4kfS5uNpAS1kIa8cGR0Hc7KBlHIRj4d1dwLkwi2x3iZsdhKGj5TPoHQ+jmEVFMe6tR6ggIG510dI2xlAB2eqAVEkNwGIWYSfXCKTLvcaHzGZf5Fzhzd4lFaH0eNT8nJXO7d+r7EQVhzQWvj70O5ms4OorJlEIjiPI5QRDwxory4J3v2PzyccBvi84e87gsgUb65LZOZ2fv+czPqmzsR4zNa1z9RUTTYcH92LOntP54P2gv0VyHHjpqomUilRKkErD1LTOg/sR737b4vatiHZLMXdKZ2jIZP5BxJUXTH76E5/hEQ3dgOERjVdeszANePQwZu6UzqefhMcLnwnQbLsvXfIkxJGHkjFR6GEbBRB6kkreXKPbWE3KRWgGQjeSOUDGyHg7NEtv/lOq9/tWoLYXLQn9Dk52iNBrY6VLeM11NMsm9NvJ3Jku7G2nUkSBCwhklBSb3pr3m+sPCP1O0iZNT7zlvYQSJeMkUqAUoIGKe975pF2KxGMkhMBrVUgXJ+nWlkgXJ2htPkToJmHQJY78frLCFsKGy+av7zL6/Uukp0vM/m9ep3FtidpnR5fVeGYGj1EsUv7jP0XPZGi+/z56Jo2eTirlqjAkrCRhBn9pCX9pkdwbb/VcfYrCW28TNxu484O7Cj2XpfD2O3S+voEwTPJvvUOwvoa/lFh0UauJikKcuVmCpUXQBJkrL2DkC4TeoIKsMAz0bBbnzFmiRiOpyOp5hJXNgUKeR4WWSlF459t0rl9D6DqFt98latQTLg8Q1Wt0b35N5soLhJUK/soKRja5n+6d2/309ahaxZufJ/fKa8SNBmGthjMzgzMzu2/B0+6dW2RfeZXM81fw5h8Qbh4cvtmJWAYsrHyAbeWZHH0lqfzdXmZh5QOqjfuE0cF8AKVi6s2HeF5ioI6UL7E1qIQQZNOjDBXPs7z+6a4jBY5TSmqwGDaEuyrwagYTo1dJp4YGPveDFvcf/yNrlRvbZRx2QKqIevMRQZhkOCVGWDLoDd1hcvRVqo0HeH59n5uRpIem6VYXCdonz9Y5DJptkL04TuyFtG+vEAZP4FrEMd79B8miGktUHPd1lbzbHiCSjIodpHIV+HS++CoJzZhm0oeNhFy606sarK4SNeqJ+7fXz1UY4t6+2+e0bGlECaEhwySM4z9KPD1b7RCWdWxRUIWi4i3SDDYwRFJ/SSlFrEKiXkr+QRBC63sHjwMt7STGhBcgu15SU6/W6i8+sp14dvTJNFG1wVa6h55JoQ8VoNEmWN7EmhwmWK8mE71pwE7+n21hjBSTZIVWF+X6xPV2Un5GkCi+K7BOjRPVWskzljFaysYYLkIcEyxvYs+NE2/UEZpAM42eplfy5Or+Cp2wmlSYF1oSilcRofR+r4ydo8LQwTQFtWpMqSxAQHlIQ9Ph4cOYi5dMxick+bxAaLCxIZmZ1RkfT4yddlthmElS0Ma6pNGQNBoa9+9t90ldF9i2YH1NIqVCKSiVNCxLcP9ezOkzBtmsxsiIhmkmoa52RzE9rVOtSJyUQNMEliXY3JRUK5LhEY17d6PjdX2VpGJrqRRP2iXEoUfotRGannCb4ohg4wG50TPY6RLd2gp2pkymPI2mm2RK07Srj+nWlsiPngOlaFceE/odRk6/Rui18FobGKbDyJnXiPwOzfX7GHYmMSxK03idKjYl4tBHCEHoNvdwWUO/nRguvfpsceQRBS6p/AhR4KGUpDT1HOniOHZuiCjo4ndqdOsrjJx+lerCNbqNFcrTV0gVxgj9Np3qIuWZFxg+/SpufZV25RF2tkx16TrlmZdwm2sYVhqUJHCbe2QHVCxpXF/C32hjZG2UUoQNF3WEwuBbeGYGjzUxSfryc8hul6G/+MuBBxisrrL6//5/AknmVf2XP6f0/R8w8ld/nVigmxtUf/qTAY+QimPa16+jZTKM/Hd/jZZKEfU8R1EvBTuqVml+8D75t95h9N+cQoUh3uPHtD77BGd6tn+uLfKynk5T/qMfJhOTpoGMaX3+OfWf/+zYk3nn6xtotsXIf/dXSdtqNeq/eC8RXQRQisb7vwVNp/Dt76JZJkoqvPkH1H/xXj8tX3a71H/+M0o/+CHD//JfI30PfyUpyZG+dGnPdcNKBX95ifSFhIO0c3F7EqLY4+HiL7DMNFHk8Wj5N3Tco3OYvKDBo6Vfk89O4diF/ueG4VDKn2K9cn2gMKcQAsNIdjqp1DBB0BnI6ko5Q4yUL/VitluPTbKy8Tnr1Zv7Gjs70XU3mV/8OZn0KCm71OPzCHLZCcqFs/sYYEn1Xt2wellj3wykH9F9tImRdZDB0fqVCoJ9DW/ZPTics+XF7B8Xhnun1zhGtvd6s/a73m7Jsp1/P8mmYOtsofQIOV4mpOfXsa08LXftUGN8N2SrS/tXXwx85t54gDU3nhgNzS6dD67vOS5utGn//LP+7/7d7SwXf35pYN1Snr/nHO6N+5hTo2imQdx2CT/e6/FQQUTnt1/1fw/mtz3aweO1vYuO9An556Hy3mop7t2NKJU1bt2MUAo21iQpR9BoSKpViecquh1Ft6vwfcWjRzHraxL/sWJmTmdtVXLjeoSSsL4uCYLBuc91FbdvhUxM6nx9I1FOXl2JSaUFnY7i7t2IZkPieTq+r3BdxeJCzPJyTLOhOH1Gp9WSfPFZgGUJ1tclYRQeW5N2q4aev7z0RA+P21zDbe5NTOjWBwV4l278dOD3duUx7cq2Z2PjwUcDf68t3Rj4ff3e+/3jdCuV6PeIxAsf1Zews+WERqJpSbmN5hqGkyH2u4mUR+AikXRqi4RuC6EbdJqr+EEbFYdY+SHs4iit6qNe9qtA03U2H3+RrAOpbJKN2q0QdutJX9cN6msJwbm+egthWHQaywhNp758c88z0VMm43/yPJkzg9GPyvsPqPz2/p7v74dnZvB48w9Y/D//n/b9mwoHJ8tgeZmN//gf0LM5BBB3OsSd7bCF9Dwq//nvE56LlOj5Qq/uVQfV7qIJo88JaX78Md07d9BsK+EnNJsgBK10uk8YzrzwIpkrL7D5t/8LwepqkhGmaWSef57s1Vfo3rqZeIiOAOn7VH/0DwnJOI7R83lMxyDuuvjVXeXre8ZM67NP0CwLFcXE7RbSHVzEgpUVGv/lb6hbGZSCuN1GRTGtTz9OquLufJZRhOx0iOo13PtHe8k74QUNbj34T0gpieLjS/G33XU2a3eYHn+NnX7ebGYM00gPGDxKKaLIx3FKfdXlLQihUcrPkXaGBr7f7q6xtnntyAKHzfYy65UbzE2+02+PJgzGhp5nrXJ9wMDaUgjVrfTRSMtPofFhFtOYpQzeSp24889j0fpdIu0M4wWNnsryCUU3thBLoo1awsnxT2C49S4tTB1zKIcwdKJaGxnGSeZnLDFKGTRTEG9sgozQUsl4V2HS5zXHxJkZJlhvIMMYFcd93p6RddCzDmGtTdz1EZqWEJiPsXP9fUccJ/yY/bC6o4jwndvbnz+c354vNjaS72xubH+3ssu5LSXMP4iZf7B93N07yc+rK9vH7fQKPXq4/XO1V0B553dPIm+WlG8UWNOzuHe/uXqLJ8UWD9MpTaDiEKUkmm7S2VwgPTRF5HXQdAPTyaJ6QpCp8UlQkk4UgJt4TA078cYopTDsNHHgkR6aJvaTNSsOvSQ05nfRdJNUaTxJjNAMDDvVE5l0SY2fTbw6nQaGnUZGwb6ikkbOIXd+jPX3buNXO/35OagdfUN06Kwv0MjaQxiaQ8tfJ2uPIGVIy9/Y41aVnkewvLTveSw9s+cz2ens5fhsQak+J2fr3FtwjBwZa4iau5gYPXFEVN3bK3caFanzF4jbbbr37g6kCPrLy2RfuoruJCxyyxGUxy18V2LZGlGkEAJCX6EbAt0UBK4kjprYeR3T1gj9OhPTDhuLPmubknReJ182cdsR6ZyB14kx7Tbddkw6pxObCs9MjjUdrf/SZi7o3PxoA7e9PQD3k//Wszmc06fp3r49YCQeB0F4cv5KHPs024tIeXXAM2NbBXTdHviuEEk2jutVabeXB1LTtV5m1U7tH6Uk9eajY3mdQLFeucHk6CtY5nY/S6dHyGcmqDUfbl/TsLAzZUK3mRTBe8J5n0a1t3N/HaucJXaPJ9b535AgiNrk0xNIGVFpPXi62kRKIdtPX7g2dXoUs5zDKGVRfkiw0UTP2MRtD3M4T1hrY+QcdHsaYWj4K3X8hU2EZZC5NIU5nMeZG0FFMcFGE3MoR7jRxBrJI2OJUcwknKyURefGAnH7WSgJn1x647/hZBACNMdBM43tQp+/R5BxROS2k/lYKTTDIuw0iLw2XmMdGYXopk0c+cSBS+R1MDMFNE3ve8Z1ywEFodtEMyzc2iqaYSHjMAmB60bC/dGSskoyCpFRF820ExVtTSMO3ESsMl1E0xORRL+1yUGEqbgbEDZcRv7gAv5mu78hqH+5SP2IRs+hs75CEcYeGWs4UboFhJ4I1DlmgSBqE8Y+eWeMtr+JJCZnj9Bwl7GNHIZm0gnrjGcvUuk+IpIeWXsEL2wSyYCcPUrb36AdJKa6beQoOEl17TD26IY1LD2NVMl5u0ENL2ph6jaGZpGxxrGNLA13hbRVQtdMmt4ahdQ4QeTS8FaQKiJutbDOnMWemCTsiSBqmSzZq1cTNcjeZ5mCQXHEolWPuPhKlnYjIvBUz2gRrD32mTqXQsaKqXMpfDcmjhRuO0Y3k5c0PGkhNEFhyGH8tENjI8SwNFq1CCGgXY8ojpgMT9pkCjqBK/vHHzY2tEwGoRtkr15Fs2y6O0pz/K4RhB3iOBgweAzd2kMy2/pc9MpC7IRt5cmmxwY+i2KfWmP+2LwNz6/TbC8yXLoIJIaWbWbJZaeoNR+xtUWPAxe3voqVKRI/QQ9id9q0EDqWmSaTHqOQnSbllDGNpKhuFAf4foNWd5VmewnfbxA1PaLms5O+F0LH0G1MM00mNUwmNYpjF/qkcIRAyogocvGDFh2vQqe7huc3iGLvxIUuD4Ou29hWjlx6gmxmDMcqYBg9OYY4JIi6dLsbyTM5QJJgN6QMCcIOYeSxXr+NZaaP3HZds/rPJ50aIe2UMY1Ur1SKjpRhr10dPL+O69XoupuEkUsU+08MoQpNQ8Uy8dT6IcJMUs6VlET1NsoP8eodzHIW6YXoaQtEL6qhacggQugaccdHzySbrLjjEadtZBgRVtpYo3lUJNHT9jMxeLakJragCSPJdMyMk89M4ThFDN1BIIhiH9ev0+os02wvE4StJ+pnnQxJyRnLypHLTJBNb/dlITSkDPGDNl2vQrO9RNetEMXuN9KHIclgTdllCrkZMukRbDOLphlIGSVjyV2n0VrA9WqDhvcBhqRSEDWbCN0c+I5AYJoZNG0wwzeKvSMp1x8NAmufa8Sx3w8Nyyigvb5/OQa/mazFIcCOgEV79QG6ne4ne0Rem9bq0WtYHTbbtte2z73lHdoPesrEHslSv7ZEUNnetAfVo2/gn7DNTdSdpIqIZUgsg6SjGmm0ngz+WPY8UsVk7WHa/gZKKcrpOYK4S81dIIoDgrhLy19nJHOGprtKKT1NGHuJWmuw7cmx9BRSSaSMKKdnCNseaauILiw6QYWWv4GuWSgUlp4ma48Qxh45Z5Qw9kjp+Z7hY9Hw7vfVTNuff4Y1OsrQv/iXiedHKTQnhfQ86r/4eT8LLPQlm8s+bitm5aFHqxqhaWA6GnEksFMagRfjZHRW5l28rkTTwHK0vmfGbcd4HYnlaCCgsRmSyuoITWD0jCJNF7idmGYlxG3HmI6WeJTC/QeQsGyG/uTPsKemwDBp/PbXSXz4nwhSxXuUYg+yyhUKY1caPEAuM943orcQRS7Nzq7isUdAGHk020sMFS/sSJvXyWUmMHR7YJJSStKtLh2apaWU6rlqkwnWMrOMlC8zPvIiufT4Dh2gHeJ3SiFVTBC02KjeZHXzK1onuJfd0HWbXHqcfG6KUv40+ewkum73RDo1RK/a3Y7W97M1ojig1Vlmo3qTzdqdIylRHwWaZlLMzTI2fIVy4SymmcwHe54JCiV7kgRH9DJUm/PcfvD3lHOn8MMWlpGm2ponlgeHopKsvWlGypcZKpzFtgv99iT9Yffz6T0jJFHk0uqs0mgt0Gg9ptVZOzDU27m70uMDbuuKIQRKquQ6vewUf6lCPwynEk5X+6tHoCXf2Smap2KJv1IDmRwbrNWSc8ZPv7j377PXjx2rwNjwC4yPvEjKLh3QjyVSxnh+nbXKNdYqN+i6R0uMOAp03aaUP8VI+TnKhdOJAdDry4P6W0m7YxnQ6qywtnmdSv3uM+vDkCRNlPKnmBh5mVLhTGJwaRqCQa/zlrJ4tX6f1c2vqDcfImXU65N7FRCNbBZBI0k02NHvdcPh3NwPk8zSHd9f3bzGvUc/PrSPHxWOnef5839FNjW6fQ8oHi//lsfLvz1UHuQwRH6HyO/yVKHlpzy3ihVRJ9jWozqB5/JQg8fQbMZzF4mkjxc2k5CWiumGVZSe7Mb8qEPGKtMJqhRSEwihE0TdRDfCmaDhrRHJgLwzRih9CqlJZK+eTqyigd1H0rGSLIQgdik6E+iaRTeokbNH+gM3bZaTQpYqRBMaYRySd8ZRJOlvYeQNLMjB6gob//E/YI2N95jzCb8m3NxIMrZ6D65dj2nXk+Nuftg69sME2Fjc7rSVlafvwAAqCml9/hndu3eIm038pcVjkZWfNTSh70kzj2W4ZwemlELJuC8ktROZ9BiaPqhR5Pp1whOE25SK6bgV4jhISNJsZY+NYRjOgMGj6QZ2eRK3vkbQOThLK9nZKrLpMU5P/wFDpfOJp2Bfwy4RY9TQMVJDzE6+Q6lwhodLv2KzdutEu2RNMxkuXWR06DkKuRkcK79v6Y/929Ij6esWlnW+t8Bc5uHiL6i3FniaScsyM8yMv8XE6EvYVuEQRezek9J1dI4hDKbbgCAI20gZ0nY3Bqql74ZjFZieeIOxoSs4dvEIquGixyPV+9dz7CLDpQv4QYvVzS+ZX/zl/iVTYnmgITKgN70P9+YwPZad+ifHyTg5CpIFTlDIzXBm+g8oFk4noYkD+3EiNJo1xkinhikXzvFw6ZdUGw+e6AE7HIJMapiZibcYKV/CsrIHtKH3baEDOrpuMlQ8RzE3S60xz+OV9xOD46naknh1ZsbfZGrsNWwrd2C/2dmOxDA6zfLaJyysfoSUMXEc9uec/jGmCfFWFfHtz6PIpdFaYLT83MAxw6XzLK19/ESV+KMgmx6nkJ0e8L77QZNmZ/nExs42vsnQ6JPPHfsR3cdVrHIGI++wZTpEbR8eH01891CDJ5YBS83rvZTIkG7YABSxDBGigkJRcxdo+mtIGdHwVhEkHoCkA2nEMmCjfT9Ri1URurCSdNN9Uis7QbXf8TpBNVlUe+mYumYmxFd6tYNkSNNfR5Ckrzb9tb4q734DKW42cZvPbnfwO4WUeA+OT1D+prAVJtiJIGwTx7uNMEWj+Yhma3GgeKgQGimntMdocr3NE7utfb9BGHUHJpKUU8LQB2v2xKGPnRvGcDKHGjyxjEinRjh/6k8o5U/vG647CEIIcpkJLpz6Ewzd7mkCHW+CtswMc5PvkM9OHtHQOaAtCHTdYqh4DtNIc3v+72m2T+YdtMwsZ2f/kLHhF9F3eO22avqEkUscBwkJUjMwDOdIZUJg2xsRxwGxDAiiDh2vgmMVkvDCPoUObavA+VN/zHAv0++wBfRJEELDtnLEcfiUC/szgq5j5AtIz+0nSBwfCikjCrkZLpz602P3JU3TKeZnuWj9OXcf/YiN6t7MmaOimJ/j3OwPyGeTIrnHfVe6bjFUOk8qNcTDxV+yVrl24nCbaaQ5Pf0dJkZfxTScJx/QgxACxyowO/kOhpFiffMGUezuMXiiRh1R0BIph123WanfZWb8DbLGdjjfMrMMFc8/A4MnkegYzHpVtDprtE445n+fEHd9Vn/8NVYxlYSTe3hmpOWEw7Pt3t1pVW8tTFLFyK3v7FRN3WGwxSro/y7VIWm2yG0PoIrZOcR3Tnj9n9X+f/9v+OagCT0xVnYNqj3x7R6SSWnw3RhGCsvM7FkIXa9xYo2RIOzsub6h29h2jnZ3dbutcUQcdHfVMtoLQ7c5O/M9SoUzaELruU8VXtCk090gjLpIGWHoDpn0CGlnqBdCgWSnnBRoPT39XYKwxWbtzrHvp9aYJ5+dTNrdC4/07oIwcul6FYKgnWTGKYWuW6SdIdKp4f772Q7xaeSzk5ya+g63HvynA8t8HIapsVeZGL3aN1S3nknXrbBWuUGrs0IYdpAqRtctHKtAMT/LSPkyppHepe4t8fwGrl/D95t4QRM/aNLpriNliG3m0TSTjF3el7Ss6zZzk28zUr68py+Cwg9adN3NxBDvFbvUNRvLypCyy73+N7j4e36TWmP+G+KtHA/W6CjO3BxRs0m4tkZ4gnQhpRS2lePszPf7xs4WpyfhL1WIIhepYkwjRTY9Rsopse0FE73NSZmzM3+I7zdpdo6/cOYyk1w49SfkMpP7hCMUrl/vjakOSsme161EJj2CriUbq0RyQiOdGuLc3B8BsLr51bGNU00YTI29xtTYt3Zt2hLdnjj2aXfXcP0aUkbomoVjF8ikRjCMJDpgGilmxt/A0O39PU1KoaUyaKaJNTaB5z/se+Q9v0G1cZ9MerT/LDTNpFw8x/LG5yfycG/BtnIU86cGPpMypNq4j6ZbTI28mMxFldvP3KjXNJNy6SxpZ4iV9c/7Sv3P9BqWwch3z1N6ZS7R4YmSEiuLf/M5tU8eHekcx0tL1zSMYgkVBkkNnv0gBEahgJZOMmbiRuPE2UTHapqTQs9mieq1RCztKSEsCyNfIGrUDwwfCdPEKJUTwTApCTbWv3kisRBJvaWtFPzfMQwjRSE3u+tTRauzvKcEQMoZIpdLFuxa/X5/EJi6s8fzAuCHzRPFZQHCqDuQEr8FxyoO/G5lS1jZMqF7eMgyl50gxySa0IjjkGZ7kaX1T2m2FoliD9mv7aUlzyQ7zdT4t/a4kx27yNzku3TdCl3v6IuWlCEbtZuMDj1HyikRRi6uV6Peekyt8YCuVyWO/X66vyKpe6brNmlniMnRVxgqXRjYwQqhMVQ6TzE/x3rla47joi5kp5kYubqH37BZu8WDhZ/TcTf2nUTXq1+zWbvNudkfkk4NDyx4G9WbPF55nyjyeiHR7eObnSUK2Rm6QZ1gH0JnITvN+MhLA89ayphGe5HltU9ptBZ67ynqZ9tt1YXTNQvbLlDMzVLMz5FODWMZaRrthWfCu3oWELqBAoxi6UTGDmxJP5zp872iOKDWnGdp9WM67gZR5Pf6TlKjzjRSlAqnmRr7FrnM+EAZmUx6hFPT3+HWg78nCI8e7k87iYGSy0wMGLxSRjTaCyyvfUazvdijISRhZCF0dM0kZRcZG36B0aHn+7X/BALLzHJm5nuEYYfN+vE2EqXCGabHv7VH2T2OfdarN1le/wzXqyaeSiQCDV03sa08o+XnGBt+AcdOvI7jwy/t7zFTELdbiXzBnvVIsV69ycToVcyeASWEIJceo5CdYbN28jT2cuEstjVY/sUP21RqdwjDLr5fp1g4TaV695kbPFJGNFtLvc1N6hsxeMxCisLzk6z/4y2G3jrD4t98xuj39mrVHYZjGTyak2Loz/+SYGmR+i9+npCydkHoBqlzF8g8fwVn7hS1n/2Uxq9/eaxGnQSp8+cpvP1tNv7m321XWH8K2JNTDP3pX7Dxt39zYLq9ns2Sf/1NnNk5jEKBpf/b//WZlK04DJptU/7hnxHVa1R/+qPfeaZWJjVMPjs18FkQdmk0H+8ZRJ5fw3bye8jJum5j7HElq94gOZnBE8V+khK5i0S4ewLQdHMPQXI3hBDoIuGdxDJkdfNL7i/8jCDYO9HH0DNGqtRbC5yb+yPGhq4MLBbF/ByjQ1d4vPybY8XRm+1lVje/wjTTVGr3qDXn9+eW7GqL59dptBeZm3yH2cm3B56/rpmMlp9js3r7yG3RhMHo0POJavaORavVWeHe458eSmqNY5+N6m00YXDxzJ9jmb2iuZrOcPkiS2uf4MX1Pcel7BKmkUKpGF0zBnSZNGFQLp4dkCFQSlFvPeLm/b/F9faP5+/snV2vQq3xoEduH6eQm6XTXXsmxNFngajVxOiWiTsd9HQGmc32xUqPCiFErz5dMj4WVz/i4dKv9s0ISvpOl65XodFe4kIvlLvTQzhcushQ8RYrG19wlHG65U0pF84O9Js4Dlha/5SHi7880NMY4eIHTRrtJSr1+5yf2zaYE+9pkVPT36Htru+vqL4PTCPD9Pjr2FZh4PMo9nm09EsWVj8cCL1v/93DD1o028tUm/Ocn/tjcpnx/rPdg15aOohER23XJq7TXafWmGd06Ln+Z5aVZah4jlrjwYn6oK7blItn9mwkq/V7eH6jl/nWYud7S6eGKeTnEEKj3nxEGLTJZsapNR6gaUkiQNfdxLGL5LKTxHFAtXZQEWhFELSI4qB/BV23KRXPYFs5PK9Oo/mYTGYMz6vhB82el0sjCNqUS2fRdZtWe5lma4n9+pfQtSQBYH6DwpVJvLUmjS8XyJ0fPbKH5ylEAg5IyYtC2l98zuZ/+tt+Cvg/V0T1OtWf/IjG+79JqjP/M4cmdMZHXh5YQJVSdNx16q299UyUUr0dko3cQczUNRN9V9qklJL4iGKD+0GpmFgGe5KBTCO93X4jKW8go2CAKHrIWanW7/Ng4b19jZ3d8PwaDxd/QaO9MOCpEkJjfOQFbLtwyNH7XF3FPF7+Lfce/pjN2q1DjZ3diGOfhZUPqTUe7OFFZTPj+xicB8OyshRys2g7drNSxqxufoXrHaU8h2Kzdodme2nguThWgXLx3L5HGLoNSpGyy3u4XkLTyaXHBz6LY5+1ja/2NXYcI0feHidtlsjbY5h6Cl2Y6MKkYI/Rai+zvPopjdYiurAGrrf1PUOzen8z0IW569/tz7f+E0Lv/12gHVvZ2xweQbMsrIkJtHQaa3LyWMfvhFQxa5vXeXSAsbMb7c4qDxbeo+tuDrwvTdOZGH35yH2nkJthdIfxD4knYHXzGvOLvzhSWFWpmM3abe4//unA9xNF9cleMeSj7NsFpcIcxfzsrtCqYm3zKxZXP97X2NnVGqr1+8wv/vxwLTNNSxJi6rV9xSPDyKVSv0u0i4w/VDo/oGB/HKSdJK1+572FkUelfu/AeVUInVgGCAGT468iVcRQ+SK2lcexCwyVLyZzuNCJIg/HLjA68sKR27Tl/Ypjn9GRZMOUSY9QLMyhaSajw1eSRBBNR8oYKUMmxl7ds0HeQuyFBPUuum0SdQJm/vo1ht46S1A7ekr/yZSWNR17dg6jUER6Lt7C48GyEFGI7HZQB3kfhMAcGcUaG0f0Ooe/ujLgrdCzWaypafR0hrjdwl9cGBATFJaFPT2DkS8khQ6t7YdkFIrYs3N079waEBq0Z+cQhnFkArAiKUeRvnQZzXH6ZR367VQK5Xs9gcADUsptG3tqOiEgBgHB0mJS26j/LDWs0THM0VEQgmhjA39tdeBZGMUS9tQUwjB7x6reYxTYp88kMua9Gl5b10yfv4i/uJAMumeEUuEsQ8VzDKaPxqxXbuzL39naYeo9jZ6tW9I0Y88ktVuJ+SSI9/Hw7JycddMhDj1kFDxR8h22dsUfHysVtt1dZ3ntMzKp0YFwkmOXKBfOsHSMsFbShpNrsYRRh7XKDYr5U333OST1xlJ28cg8HsvMkEkND3yW7HiXjvzOYhlQazyiXDjXX/yF0CnlT7Gw8v6e79faj8mnJ5L72GXoCcSAIZucP6Tr79/Xw9jDMfLkrBG6UZ3RzDm8sIkbNTE0G0N3KNoTaJpBLEPC2KXhr2JoNsPp0ygkhmYnpOpe2CWWQVLFXDOx9DRKqZ6hlGiXCSGIZJBkoiqJQNAKjr4BlJ02MpfD0DQ00+zVHTwZgqDN0trHx6g6r2g0H7NWuc7c5LsDnoxsapRibpbN2u1Djk/G+NjwC9j2oIe1427yePm3x+SqKCr1eyyvf87c5Dv9BAJNJGGltc3rTxQrNXSboeKFPR4Qz6+xtPbpMcZZYvRsVG8yOfrKviEtzbIxsyPouWxC59gjIJvcz/T462T17dChY+UpF84eU3h1i583TcouDVyj3V2l1Vlm/7VJkM9NYfU84CmnRBwHtNpLlEvJJqTdWU1I7/lZQGGamWNtlBy7QD47SRh5OHYRXTepNx4xPvoSnt8EAa5bJZ+bIp0eIY4DUk4p0W3bZ1qJmi7Lf/cVUdtj4xe3Gf3+JdzlOpX3j57QcyKDJ3X2HNboGEpJzFIZf3mJ6k/+68HKyTshBOnLz1F48x1UFKFkjJ7O0PrsE1qffQJSYpSHKH3/BxiFYuLSzWYI19eo/fw94mYDYRjkX3+L7EsvE1arSfE9y+5Lteu5HKXv/xHS83DvJgNTc1IUv/MHhBvrRzZ4dMch/8bbqDhGs220dJrmb39N+8vPj3S8lk5T/M73cGZnidttNNtBei61936aVEsXgszzL5B//c2k8rVU6Ok0zY8/pP3FZ6AU5vAwpT/6E/RslrjRQFg25tBwP3SWOnMWe2qG9X//b5G9Uhr21DSlH/yQjb/5d8/M4Em4KG9jW/kBHkaj9fjAyc+ysgRBB8+rE0fbuydN25vWfpJCkbshZYhCDQSrdnqS4tDHsFLIOOqFvw5Hs7U0QHg+GhJuyvT46xg7eAu6ZlAunGF5/bPfaRZQkiHnDxg8mqZjWdkjn8M00n3C5haCsH1s4nPX3dijXm1b+Z5W0taCLsjYZRyrgAIyTpmuX8XftUvdTRbVhI5l7FV0B8jZI9h6hkj6WHoaTRiJAJ+extJTpI0CumZi6inqwRKG1pM2QKAJnWiHMa4Lk0h6KAWdoEYxNZlkHImt8hcCL2pRcCaQSuJHbUqpaaru0UrXbCFqtTDHxomaDeJ6o19s+CSoNefpuscztBWS9coNJkZeJqVvL6SGkaKUP02ldvfQBIO0M0wxPzswzpVKVNGPw2XbQiwD1is3GC1fHghtpZwypcKZJxoJppmmlD+1hzi/Wb97bAMjij02q7cZKV8eCKtuQVg2elok3p0DZAY8v0618aAnvrqtHTZcusDy+mfHCmvpmjVQQBmSLNNa42FiWJAYoLpu97InbeJYUMjPsLTyCaaZIpdJPKat9jJTE99C00weLvwS03DIpId58OhnjAxdPsRLnYhJapqBoTtJwkF6lFiGVKq3KeZnQSlcr4JUEcNDl2i3V4lin2LhFPXGQ/ygRalw6sD7VLEibHTRUxZBvcvD/9f7CEP7HRQPFRq1n/2EqNHAnp1l5F/8a9w7t+l8vbco354LFork33gLf2mBxm9+hVKKzHNXyL36LfzFBcLNDbIvX8Uolqj8578jqtcwh4YZ+ot/Seb5KzQ/+gBjaJjsSy/T+vRj2l99gWZaDP35X6L1qrMHG+v4C4/IPPc87r07oBTWxCRGoXg8PpGuE6yt0vzgtwAUv/s9cq9+C/f+PeL2k0McqXPnSZ2/QPVH/wV/YQHNsSn/0Z+Sf/MdKv/wn9EzafKvv4n38AHND99HKUX2yovkX38Df+ExYa1K+vLzGIUim3/7N0T1Gvb0DKN/9T8AvXDSza9JX7iEMzNH93aSNpq+eJlgbfWZcJkgYeBPj79OcceEoZQiCNssrHzYH1S7YRhpMpkRPK/es9q3OCNij4dF9UTbngZyl6gbMBBK0C2HoNvAyhQx7QxB+2DtBqUkzfbSibKZwqhLo/WYXGZix6fJ5OzYhQM5Jt8Ewsjt7bB2tkSgadbBBw1A9BRwB99XLIN9ZAie0JbYY+duUwjRm4idvsEjhIauWz2drQhDt/bRd5J4QR3YJs/rhs1I+RLVxgPCaHDjlchXbPSM4UTF3YtaRNKjFWyglKQdJGKBUkX9ew2lx1r7Tv+4/vUTHe4kQ1WGBErihg2CuJuILSqJF7V696P3/na87BtrbBxhGGi2Tbi2NlBe5zhQStJoLuxL6H8SthTMk8ytBEJoZNOjmGb6kLEhyGbGBurkQZJ5+DR6Pu3uGs3OMunUENtGQpKKvbT2yaHnzaZH9xj5UeRRbzw8ct2+nai3FvCD1p7sQ4C400KmnaSsxCGe5I3qTSZHrmKa297KTHqMQm6GauPoXotManjXXANh2KFSu8PWeMtlpygXz6BpJiNDz7O+cY1K9S4jQ5cTNWl/ieywg9do0XUriSZe0EZoAjdcYWr8WwRhm1Z7ec/1nbyJaWQoOpfRNI3hoYRI3PFWyRVGGBl6jlZ7hSDsopSkWrvPUPkCzdYiUoZsVm5RLp0jCDs0mgsHZkkKXaP0yixjf/QcKo65+3/5GYUXpgibHq1bR9uYnsjg8RceEVY2UWFIsLRIsL6OPTt3JIPHHB3FKJao/ugf+iS8ztfXyb36LZzTZ4iaTVJnz+PevU2wtgYyJlhZwZt/QPr8RVqffYo9OYWKItx7d5HdLpIu7v17ZK++CoDyfbq3b1J497sYpTJRo45z+jRxu5Wc84iQnof7YNu46d65hXP6DObIyNEMnrPnCdfX8R7Oo4IA6Xbp3LxB+Yd/gpHLYY6OoudytK9/tf0srl8j99q3cE6dIu60cWZm8R49JNzcSJ73yjL+6nanCzc3CdbXSJ0/j/vgPpptYU9N07n25Z4ipSeBQGNs6HkmR18Z0KKRKmJ148telsT+hkqns4bn1RINph2deCtrZBDPQtRq745T21GvI/I6RF4Hv1V9YvHQOA7ouCfXBaq3HjM9/kb/dyEEtpUl7ZR/pwaPQu3l/gixryv+QJxc3uaJpxG9FP4tKBXT7K5gGRmyqdEkG23XbleqiEZrgbGhF7ZTe0VCgg6jLo9X3u9xi1T/+zvR8te3vRP7LJI77e5YHb4Y1r0VNKHv+V7c6zdCxdS9lf71jNFhrLnpZCFUCu/2PWRzr+EQ1evJ+D91+mBqwBEQhl26XpWTjK9YRjTaiwM8HCEEjlPCtnIHGjy6ZpLPTO4JW7e7a0cmGO8HpWIarceMlC9j7MiySqeGn7iRyGYmBr1NKIKoS6tzXA9ugjDq4HrVPeVxIBGZDNZW0TOZfeshbqHT3aDWfMRI+VLfY2X3yMv11qMjyyMMFc8PGE0AzfbKgHe60XxEozlI7N2ofM1G5WsQMH6xwJkrwyx8USVK30LTBdOTeZprHkH6Fq1Nj+yQTdAIGL9coLXu0an46JbG2bdHkt9r1/Di6zhlk1xW4ncjqsEHGL2qA86opJAuUHm4zPyjhX476s1H1He1bT+YhRTD756j/uUCxZdmQAj0tE16dujIBs+JSMvS9/qzggojpOeiOaknHNW7YC/0tBV+gV6hTynR02mEpqGnUkml8x6xVMURsdtFz2SS8JXjgJLIYHsij3slI7bg3r+HCgLSFy9hZHOkz56ne+tW0vYj36gc4ADF3S4IMcAXOgx6Oo0MPFSwPWHHnTZaKoUwdDS7VwOpuz0oElY/aKk0aBqa4yS7u57bTsXxwG5PhQGdmzdwTp3BKBZxTp9BGDrdu8dL19wfglLhNKemvzvAmVBKUq0/YGH1w0MHZTYzRqEwx/Dwc5jmzv7xTRU03Luk7vQaKRmhZISM/ENLS0DC33mayTnZJQ0uVIaewrbyJz7nifDUnjPVS18eNPx0zdojPvkkmGZm0FPSEwrdz/uQz0ximznymck9RWmVktQaD+m46wP3Zug2k2Ov8uKF/4G5yXfIpsf21BRK7ujZ1WRSyEONIoUcuF7caEIUEdcbvUKh+8+bWsohde48ejq979+PiiDqnshLCYmBsbXb3wnbzO7hUO2Ephlk0qMDn6leOONp05VbnVXUrjnH0O19DY+dyPR0srYblCgfewfwvo6Cg0NhirjVJFhdOVQRP4xcNmq3Bgz6LekIxzoodDQIy8xRzM+hiUF5ho3q18RH1ZNS4LdDGstd0iWb8YsFpq6UGDmbI1UwyY7YDJ/KgoDz3x5j4nKB0nTy/mUocRshnapPaTrNzMslxs7nGTqdxckaZIZsilNpnJzJubdHGL2Qw8kdXXl9JzQ7ucfGtSVkmMytQoBmHN2MOZGHR3NSfVdd4nZ1jpyOLX0PFUXo2UyfX6Knk8U97nRQMk54O5kM6DrEMcIw0DMZok4bJVWy4OsGmpPqa9FojjPgPpSeR/fObdIXLiJdF2HbeI8fgjzGZKdpA4acnkqBHDS0DkPcaaM5KYRlJUaPEBjZHLLbRUVRz5CR6JkMcSu5Dz2TASF6Bp8kdr3es9ASIpemDxpcSuEvLiK7HdIXLmEODxOsrAwSo0+IbHqMM7PfHyCsKqVodzeYX3zviQZB160kGQK9+mg7z7F7Ed7a4TwN9jt+92StGRaaYaKkIg4OnnyljJ6qqnwU+wRhG8cubl9bN3pp2Vt8j5MjKWaaxTIzPeVrE02Y/YrGCTFcx9CdE2d+bCEI24RhdyAkYFt5HCuHeww+RjY9tsfFHwTtPdkqAH7YwjHzgNo3o67jrrO4+hHnZv9okJiumeSyE2Qz40yNv8Zm7Q6V2j0arcdPV3H9GUH5AeHaJsbYMJppoA7I7hSmlZS/2dgY2BAdF1HkPSXx3SWMXOwd71437AFO2G5omkHKLg98tiU0+bTlDXy/QSQDTLYNLl2zdhF2ByGEhmXl2b0h8oPmU5Wo8PzGvp8buTzOUJIRGqytHBKOVNSbD+m6Gz2pj6R9mdQohdzMkbhOucw42R2aSQBdd5NGa5HjzDGdWkAUSFIFk80HLRAgY4XXSopfe62QTjUxzFSsaKwkfVIpqDxqE3kx3VqA2whRsULGkjhU6JaiW/MJvZjAjYkDSbdxMumH2A1QkWTojdNYxRSlV2YpvXaK9feOrl10IoPHmTuFNT5BVKtiz8xijY7R/KiXaSEEwjAQtg1CS362rMQtG8cEq6uEm5tkXrpK3GqjpCRz5QVA4c0/6Iej0s89j3vvHlG1gjkyQur0WVqffYIKQ/ylRYSmkb50mbbrIgyD1JmzfdLyFtz7d8m+fJXcK6/hLy8eO01eS6VIXbhAWNlASUX60nPEnQ7heo8bo/Xuz0w6t7BshGkm9yol3Vu3KP3gh6TOXcB//AjNcchceQH3/j2iVgsZhET1GtmXrtJwXVCS7Asvo6IQ/+E8MgjwFx6RffkVrIlJos1NrKkprImJARJj3GrSvXeXzIsvIYSg9o8/fmp9npRd5szM98hnBjV3PL/B/OLPaLWfTKKUMkTKKJGSHyAvyj2GSPL3pzN4kmKIg+fY7YFy8sNY2TJefe1wg0dFT7VQKBURRu6AwSMQGEYKTejHnvgN3cG28uSzUxRy033lV10z0TQTTdsqJtoLFwrR+3l38czjIwhbtDorlM1z/edrW1lKhdM02ktH4kBYZpZy4cwe4cJEzmDvxNzqruEHLaSK930PSklWNr7ENNLMTLy5h0shhCDtDDEzntTZ6rqbVOr3qNTvHqgK/ruCdF30XDapuXSQvEcYoBcK6IUCUa16pBD6vteS4RHSrZ90vA9sGzxbWXKJcvPeDaSh23vKLUgVEUQn30BsnycmDLukdm4knkDCN3RnoBTKFp5mQwP0q4/vaWPgoxXToGRSXuIQ/pXr1ag25sn2ihJD0ndHh55jbfP6ofOEppm9DMxB73ulcb/HcTs6gk5E0Ilore9ta21h+z67tb19qbGcGD9bBtFBaK4+3ZgLmx4r//U6o9+/hJ62GPvDS1Q+nKfx1dHVv49v8EhFWK1Q/O73QGgY+Rydm9fxHiUxOL1QIP+tNzFyecyhYTKXn0fP5QlWlmlf+5K41aTxm19R/PZ3Gfmr/x6kRFgmzQ8/SJSKpaT91RcYxRJDf/rnSN9Dcxy8Rw/p3LgGMiasbNL67BPyr71O6uz5hB/juXti3WG1ir+0SOa552l+8uGxC27KbhfNdhj+y3+NME2EadL49S+SVENNI3X+IunzFzBHRtGzOUp/8IfE7Sbt69fwHz/Cnb+Pde1Liu9+JxkEpkXUbNB4/9co3yf2fRq/+TWFd7/N6F/9NSiFMEwa7/+WsJKIuXW+vo49Oc3wX/xLokYDFQZ7DTel6N78mvxrbxC1msfiKe0Hy8xyevq7SVXfHW7gMPJ4vPwbNqq3jxQWEGhk0iNomoFlZfupqFJGSBUCOzKH+tW2T44kfLGLQLhrso98F6g/sRSJ2uWVOi62qpXvhr4lfHjEzZeuWZQKSXXpoeLZnuJsIpz4tB6xoyII2lQa9ynm5/phrERb6GUarUUq9buHHq9rFlNjr5HNjA+8Hj9sHXKseuICGcc+j5d/S9erMD3+OoXszJ6aZ1s1siwzSyE3w/T461Tq99io3qLefPhPYvhYUxPIroteMJMFcR+oKEIFPsIwE/LrCSFV/FReDCnjfXVckn6wf/8zdGdPraytOmlPi2Rc7X5nSYbQQQaYppn7zC3qRETunTjofpQfIF2FMTRyaNHYrXZsVG8yMfLSQLg7l5kkl52g0Vo48EjLSDNUPDcwDwRhh2r97u9FeZRnDqlo312n87CC0DVQKgltfVNZWtL3qP/iZ0StJno6nejw+D7B6kqfIKv8AH/hMYGu0b39df/YuN3uex28hw/YrNcwR0YSyfN6jWBzox9uiptNav/441518zSy2yFYW912DcYxrU8+wl9cQM8kWgdRLcnmihrbbkYVBkS1KlG9jjf/AAwde3YaEInct6Gj53KEi0sY5RLCcYibrWT3pRs0PvwN2AZ6o4KeyyEDn7BVxz57Gj2bJm508ebvJ/8tP+oZRRp6IUf6tZeJ1jbozt9FFDMoL0CYJmFlAxlHOM9dSPhPMqD76F5CcGt10ApZgrVtizWqVqn817/HGh1D6AbB5kbyshED4bmoUSfudvDm7xO1Tl5ywtAd5qbeZWz4Sn/xUCrRHVlc/eh4hTAFCM1AaDq2XcD3GkRxUkZg9yS6nzbP8SD6dXd2Yk8NJiuFlSkkWjyHQamnSh9Xin2P14R+JA0g6HkoJt5kdOgylrl/Reet2lFbXrOtQp5qB09KN5wB0cBj3wuK9cr1pHJ7dlvcLGUXOTf3Q2wr1xdSkyqpbyPQkvduZpkYfYWpsdcGBMViGbKy/jmdfVSaNWH0+l4S+ksMx/0ntVgGrG1eo9VeZrh8ifHhF0mnhvYULU1CpgaOXWBy9BVGyhepNx+zvP4Ztcb871RhOVxeQ6RsNNs6cBOmp9NEtRrG0PAez/XxoOAp5B6S+oZ7jxe9iuv7Krxoe/u4UmpAfPTk2HuerTpbBxo8+yZJ7PX+HhcHGpKiR/tAgfbksd7pblBvPmJ0+ErfULTMDMOliz2tq/3fXz47NZAJp5Si626ip1d46XKa6x91j+3oT2c1Zs5a3P/a4wnlBvsYnTIZmza59uHx+Vn5ks7opMn8Le+JbdXTFoXnJ2lcXyZ2TzZej7fCxDH+YmJxxo0GwcresIZ0u3Rvfb3n8wEolRgitYNZ9dJ18R7OH3yKMMRfGFT33e321dKZRIDw7m3iTgdhGlgz0wjTAE0gPR/V9TCnJ5HtDnougzFcJni8iF7II3IO3S9vkLpyiWizQ/BoEWt2GtlsoaKIYHUZ30t2CSlTYAyVEk7TUAHV6WJOjhMurSSGWSFPtLpE3GyRe+d1ul/eQMuksSbH8e7NY44OE9XqGH4ZuWsSPEqld3t6BgR079w+cThL1yxmJt7sZWRtE8uUkolS6/Kvj7UjVkoRRR6WmSZU20rKcRzs2R0JoR2rcvHetps978nhbmsVhygpj6i0/LQelJMfn02PcX7uh5QKp3shwUGyb0K4bOCHLfygRRC2CCOPOPaJ48SglDJECI0Lp/60l8p7cnh+g8fLv+Xi6b/o8zmSFOUxLpz6U9ruqzTbS0kYSkb9QqaF7BSOXRoQr5MyZrN2h+X1z/YJhwkyzjDl/GniOETXDFZq159IvO16FRZWPmCjepPh0kWGSxfJZcZ6OimD70GIpB7TSPkShdwMa5XrLK5+1NOq+SbI9Ltg6NinZonqjX3HaiKv0duUIY7tmf6dQPX/9zvHsUfVN+QJPTCDUyX8TWFZR/I+RLHPRvUWw6VL/XEihE6pcBpnvXhA9plgqHRhV3kLxWbtNqYdcu75LIGv2FgOUQo8VyIE2CmNVFpDNyDwFUpCrqAjpWLxQUBxSEfJXlhtSqdQMohjxeJ8wOikSaGs021LHt3x+/vtTE7j/BUH35VsrkRoBnSaEssRaBrkisn85bsSoUE2rxMFiuVHyfWkVGi6YGzaIJPXCQPFyuOAsWmTfFGnWY95fDfAzDsMvX2W5hEzsvbDEw2eXl1MpOxnUm49735/73++1a9UwjculJPGxtHepBxNA6HtkGbZga3z7bzezp+LZQ3fU7jd/TuTnsvhzJ1OlJhzeWo//XHvJhLCs5AmiN5EYuioToh1ajYJrxk65vgYSkriZgv79CzEceKmbHdAJNlaztnThOubRD2DR7kuKswlpOZ2Bz2XJVzbwDo1i7BMhK5jFItotkO4toExXE5qg3gecbuNMVROsjYyacyxUeJq/UmvBgB7bg6znOgS+YuLfYP0+BBMjF5ldvLtPiFxq7LyZu0284s/P5Is/cAZe0TkVnuVbne7uGQUe/sSVS0zg0A7URaNYTj7enj8XYUOdSuFYWfQzCdk2h2wKzwqhBB7xBUhWeyflKFmmhnOzHyP8i539Zb20Ub1JpX6PTrdDbygcSiHxjRSz8x7sVm7jWmkOT393b4ApRACw3CSQpx7isoOItnlR6xXv2Z+8RcHkN4VLXcVx8rjBU0yqeEB3s/h549xvSoLK++zuvEVxfwM5eI5horncKzCDoXn7fpQtpVjZvwNsqlR7j3+Cc328auBHxfGUAlQmCNDRJtVaAz2UaEbmCPDvcQGNwlrnRi9ifaEEELbtx9vFazdD1LunfAPGg8naFHiQRpoS6KJdJABog4Yc8ct97H3+AOea2/IhutriCN4eEDRaCcip/nsdH9c5TIT5DOTAxILW0g7QwnReVc4q1K/T2Es8ZyMTJicv+LgdiSP7vroumB8xuTURZvrH3WpV2POX3EwLEEcKlLpJH38uVfTrC2FvPadLLohUFJRKOtcfDlNHElCX7HwIEAGW4r/yVo/Nm1y8aUUvie5/YXH8ISB7Wg890qKT3/Vod2MefGNNN22xLQEuikoDetMzllU1yPe+eMcrUaM7WgUh3QuX02jaVBZj3h8N0CGkrgboKdNoo6//UiOkYV6qMFjmPDmd9OsLIYsP44YnzLotCSepxgZ16luxGTzGumMxtKjiHRWkC/qLD0KmZw1mD1tcv1zn2xeo9WQbK5tp5KdvWQxOqHz2Qce5WEdwxCsr0SMjBtEkSIMFPmiTrsZ02kppk8bLD+OSKUFz1+1eXA7JIoUmgYLD6MBr62ezZF54SVUEFD98T8QrCUWoQpDul9eH+gkQtdRYUSwuAxKYc1MIV2PaGMTFUYIx0aFESiJCkLcL66DUrQ3qwPZE/6DRwSPl0DQV2aWQUjwaAE0DT2fwygWCJZWkJ0uwraS0IPsnbd9C1BElepAKvyTYE/Pkpo7TbCyTPOjD46Xhbb1DITO2NDznJp6d0B6XfVk1O89/smJU7R1zcJO5/G8an9hDiOXIOr26rTsLPRZ6Fm2x7+OaWT2SV9WezIp4sA7lKy8BSE0dM3kpHvrLQG93Yjj4FBtHyE0xodeoFw8O7CVVUrRbC/xYOFn1FuPj1VX61lByoiV9c/x/Dpzk+8k6bBHCENuhUS7boXVzS9Z3fjqiR6btrtOOX+aIOyeiGcTRh02qreoNh6wuPIhpcIZRsuXyWbG9yE4a5QKpzk784fcmv/7b1QnSaQcZMdFTI6j4mhAnmMLcatJsLKCls4kSRBPISugaTq6Zpy4vyThxb0GVxT7By40UeTu2bQIoe0hMp8EyXn2eoIPG1exDPcNPx1Us+mo2F0PcAu9KDP29ExfDPZJ8Pwa1caDXlV5o3/+4fIlNut397y/Yn4uKcPAthBstX4fz69TACprEZ//us2f/29LRKFC0wSmlXw38BVffdhFKZics1hdCDAtjdKowc3PXE5dTJ6j25EsPghIZTUKZR3TBK+ruPZRlzjcIfehYH0p5JNfdPir/12ZzVWF0Ohfz+1Kvny/g53SOHvZ5uYXHuPTJtm8xsrjkPJI8hw7LcmNT1ymz9ikMhqWI2jVYq5/nIyRJEsrZu5/fJP2vXVkkLzT9r112nePJrJ76GylJDgpge8pLjxvYVqCqTmDelUyNKpTWY957iWbWCY3XShrXLnq8OEvXQolDSet8dxLNu2WZGLGoNXw8L0er0BP1uZ8QePMBQtNB8uGubMW1z71uXjFBhQy1qlVY17/doovP/YplDRMS2Ns0kA3wLIFjZqkUdvu7MHKMuv/8/+0/z15PkLA+JjOyur2LkX5PoYBrK0QdgOU5zM2qpFJSxpNSaGg8XhBEvWMnFRK4MY7XnoYDrieY7+Xwrf19yCAOETLWqjAR885RJUGKkhcXFuEa+Vtd2y9lCNutA91izZ/8yuav/nVYa/xCRAMl85zdu6PBjKKIBGruvfox4dWwz7C6Xf/kFTu9etJjaEdu6yUXerF4Y8fkrOt7J6QWBi5BMHgwmqmC5ipPP4hKsuQcG0Mw4Fg/9TTJ0ET+h6tEqUUYdQ9lERqmTlGh5/fMxl7fp17j35MrXlwmHd/iAGNjqfFluhfvfWYfHYKTTP6nhuposTLJgQyDohiHz9o0ulu0Ggn5OajGs62le8PnqTG1QlTWeOAjrtBx91gdeNLysWzTIy8TLlwdiAcIIRGqXiGiZGXebj0y2+M9Kln0tjn5pCeh2aaaOk0srWXnO0vLWGNjgLiqRTTk0K9FnCyjCRdM/cYKlv9+CBPbCxDwsjtSTAk0ISBuU8ZhuNC03SsXeNKqsMlJKLYT8rODGywBNYusb7jYne5lS0IAVo6BZp+ZMK5UrJHXn55QEailJ8j7ZRpdbbpI4buUC6cGZgjothPeHSxB1gMjRq8+6d56pWIZi3myrdSIGBzJUKpJJKqaSClIo7BUGCaggsvOpy+ZLP80EEIiGWiXm8YAk0X1DZi0lkNodHX7BQi4fF89y/yrDwOiULFS2+lyWQ1HvZCX1v78DhO0t2VAietceFFhzPP2awtBfSSm3vPViBE4t3JFXqeWUNDxpKw7mIPb9do89eOzlk9dCaMY6hXYwplnepmzOnzFt2upNWQdFqSTltS2ZDUKhG6LiiVddyupFmPGR1PGrmxGjMyrtNqSqKeVagUNBuSiWmDOIYoUqQsjXZTsfQopLoR0WkZbK5H5AsapSGdKEosTssWlIYEC/OSQilJu/Xco++ACgWN5y+ZnD5l8KvfeuRzGo4jaLckpbKOJgI++NgnBnxfceaUzqWLJqtrMeOjNnGsWFqJef01m2vXA0oljShUWJbA8xRzswZr6zEffDw4QSs/IKrUsaZHsV48S7RWI/PqpV6YzSdYXEcv5hCmjux4aGkHc6xMVG2ipIQoRgZRIliYspGeD1IRLK6j/BBrdgxrYohwo47mWMRdH80xieptjEKWcKNOXN3dMQTlwhnOzvxgIM1TKUmjtci9xz+h3T35ZKuUIgrdntdo8B21uxtIGQ5k1aRTw2iacSKp95RT2qMN0vUqezIxZBQQh94TOTy6bvYm7JNlvBmGs2dClTLsTcwH91fHLpDLDFbGTjhU12i0j1ePCXpkcP1pQiKDsMwsZ2a+z9jwCxiGg1Qx7c4qD5d+Rder9sjRAtXLDorjgDByj+1h2No9p+wSje6zCTNFscd65UZCEB16nlNT38G2tsngmtAZG7rCyvrnuE8hSHdoGzarBAsroIlEX+sgSJnU23tKGIaTLMwnvB/TTO/xqESxd2ghUikjum6FTGqk/5kQGo5V6I3vkxuTjlXYE7qO47AX9tkfSsX4YRt21Z1JwrL7E52P1pbcvp8rBVGt1svGPPra1O6uU289ZtzerkhuGgl5eafB49gFSoXTO66n6Lob1FtJpvTGcsh/+bd1DFPQrEXEETy6GxBHim5bcu3jLnGkiIEvftsl9CVCEyw+EFi2YGk+oNWQxJHCcyW6LtD0FKYVUK9EXHgpxZ2vPPzehn/pYcA//Ns6uiGob0YIAfmyjoyh3Yy5/WXiofVdyUfvtXE7ktpGhNAE6YzGvRserXrM/G0fty1pVCMuX02z+CBIfn4lxc3PXaKmx6P/z4f7P/Aj4olbv8/e9xKuTQzLC0noaOv8SsFn77v93+/fThb5OIaVxQhUYrHdvpH8u7NfrSxErC9HxDHUNt3+catLyXm/+Njb5ghp8NGvXOIo+VkT2xbq1nFHRTEvSKcEji04f8akVNJotiSWCa2WJJUS/fuZmzEYHtLwfUUuKzBNQcrReLwQEfiKUlHDsQXTZwxu3AxpNhXlkkYYHcAtKmQwJ4aIW120lI2WTpSWtWwKJRXmSJFgeYO442KOlhCGjjU9QtxykV2XYGmB9NULyTGehXd3AeUnxoGWdtByaUyjV0C1mEtIj7FCz2eQXrDL4BEUstOcm/vhHlXUVmeVe49+fGhK5NGgaDQXaDQX2L3ItzrLRDLAYHsytcyk9MJxeRS6bpFNj+2JyXe6a3t4R53Nx3Qqj584SHTdTmoInczBQyY1sqc9YeQ+sfJ6yi7tcZWHkUu99fhEhqBt5Z8RdyJ5zqemvs3E6MtoIvHstNrL3Hrwn3oS/c+OxNpy1xKlWBXvy/d6GgRhm+W1TwE4N/uDgQXdtvNk0qPfmMED4M8/xpqZIHI9oso3dx0Ay8hgW1n2cSI9EULoSaHOXRyqIGgdqpgcy5B2d42R8qUd5xKkU0OYRgb/hF5T6JWI2BVGjWOfjnv4xsz1Kj2P8va9mEYaxyqc+F2nnP0TAYx8HiF64/wYQ0LKiPXK14yWL/fvUdMMSoXTLK19StDjIxbzcwPeM6Vi6s2H/fB94CvWFgfnim57fw9pq761eCrcA/uI4u51l1wxw9CowY2Pu4TB9o35rmJ1YfB67eb2Yt9uyN79QaMa99s4eP1tBL7i3g2PF99IUx41+PKDpGHC1HFGcvibrX44yx7NIYOIsH40fukTDR4p6Zco2o9gvJMysvPvB/28BaUg6n2+02DpG1M7zqvifpWJ5Gf2HndUrK1L4jjk3oOIMFToBriuQojEo2NZ2wbPxqakUgsIfIVpClxPYdvQbCk++zLAdRWplODu/YhWWxJH8JP3PIJg/14u/RDv3iLS89FMg2B1E6FpvTRiQbhWRXZcpB/iP1zpKU3LXlV5hXR93Gv3Ex+iVMSd7ZccLKwTbdb7HBgV94h6CsKNGioe3MXkMuOcnfujXsx4Ow7cdTe4//inPUG4Z4H9n4Xr1XDdCs4O7QnDsCnm5o5t8JhGhkJuhp28jDgOaHVW9gmFqCNNQrpmkUmNognjROqwhdzM4FV7hOPuofwQgWnuLUYYRe6JRdLy2cljl4A4+FxTTIy+3DfIothnYeXDgd3ns4BAkHVG6fpVMnYZQ3cIopOVRzgIUkWsbV5jcvSVgTEghLYntPvMEUUE84dvJrRMBuf0aaJKlahR35frcxQYhkPaGUaIe8f2ZOiaSaFHot2CUgrXr/cX3/0gZUizvUwU+wNhl2x6jJRdPLHBI4ROMTe7x+BxveqhHh7olaTYcf9CJGMtm5k4kcGjaSbZXRvFHSeHOEZG0TGfuaLVXqLVWRkgL2dTo+Qy41TqLUBjqHh+4Kgo8tio3j72PRwHnabkV//lZOKXJ0FtI+IXfz+4OTQLKcb/7AqL/+EzZNAFAbmL4xhpi9Uf3TjSeZ9dcP+fGOVJBzujs3L38IXB8xWLy4dZStur4fLqwd/rdJO/1eqDny8ubR+jG4KJ8xka6z6tSohsdZGtZOJ60jCIKvt7AuLG/vcnOy6yczQrN+UMcXb2DynmZgcmM9ercu/xT3uVer/ZlNNYhlQb9ykWTvWJd1sieysbnx/qMt+NfHaK9I7yFwB+0OrJq58MQggKuWksK3fsejtbIneDUHTdyhEm+73PPdHYOb51r+s2pfzpA8mVx0W5cBZD3w4bRpH7DLyAe6HrNmmnTMoqEMbuiTxbR0EYdXsL92BV+2f1vJ4G1ugoeiqNPpmEg4MTGjwJIfsUKxtfHKgMfBBSdnHf8Gq7s0bwhJpY7e4ane4Ghdx2yQTTSFMunqXRXjxRf86mx3pVwQc3BJX6vSeer91dIwg7pHYY/6aRopifo1K/c+wwWy4zcWBdvLjZRJQsNMc5tjioFzSp1O4OkJdNM0MhN0utOY9jlwZChQCN9sIhdb3++UAzdcxCChVueT9IEo2GD1bZ3o1/NgbP+TeKjJ1O83f/xwf/1E3pw0rrvPPfT/LlTze59evfXYXsw2Bbec7N/oBy4dyAsGAYdXiw+HM2qkm22DcNpWKqjXmmgzZ2LxaeGBkzFHKzbNYOrsK+E7puMzHy0gAxVylJq7NC5yn4RwDZzDiF3EyPaHvUZyIYKV/qEbB3eJx6Bt7hOz7VM/QGuQa6bu3JQDtKO0r5UxTzc0+tYL2F3Z4PIbQnVp0/CaLYo9VZIeWUeiToZ9P+3Ugy6XZl/Kh9qss/QxhjI9inZvqyHt6tu8SNvTvnqFbHHB7u64UNaoIcD4XcLLnMRG8jczQIoTE6fAXLGuQZhVGXWvMBTxoPSdbRfbKZsb4BmZRMeJ71ytcDlbyPAl2zGBt6npRTHhhXnt880n0FQZt66xGOXRzw5g2XLrCy/vmx2qMJg5HSxURGY1+DRqE5DpplYY1P4j2aP7KWklIxm/U7TIxe7bdViKSI8+LqRxRzMz219eS6UkZsVu8cOew790KO0JdMnE2zuegm2VkTDnEoufnbOmdezlGasFm81cFOa5QnHAIv5uZv6py5mic3ZLJ4q0M6bzA0ZRP6kq9/XaNTTwzGVN5g6nyadN6kVQ2SZKYRi0zRZP7LJjJWnHkpj9eNWJt3mb6cxbQ0HnzRRAiYfS5Lux5RXfaYeS6LZWvMX2uxeLODDGM0Qyc9N0T73jqaqZM9O4K3fnTP0zczk/w3/F7CNFKcnv4DRsqXBoydIGzzYOE91is3+F0YO1vouBtU64NGgGlkmB5/fYBEfRCE0JkYeZlifm7g8zgOWK/ceOpChbpmMj32rYTLc0Rk02NMjr6yx0BxvSq1xpMzrBLhvsHdqmlmeru6o+8Ws+lR5qbeHYj1Py12T6qmkWZm/E2y6bFeOYFnN510/AqNzhL7eVx03R6QTzgpCtkZUrsKqyoVH6lo40kR1+pI3yeq1JBBgHD2vw8tk05q7dXq2HNzWBMT+37vKDCNFNPjrx+jLwiKuTlGh57bk+HX7q4dyXO6RbTfneKfdoaYnXz7mP1SJNl1o1cHkhykjFmvXO8JRh6OKPbZrN3Zk8SQdspMjr1yrBT1Qn6W0R1K9HugksoC0vcIq5WegOTR0eqs7gnrZ1MjZFLD5LNTAyHqrluh0V44snZZacxi7FSKuStZnv92mamLGZyMTipncOblHK1qiNuKOf1SjslzGVrVkDhUvPWvx8gNmdz7uMHz75aYvpShuZn8bfrS9ru0bI3J8xlGT6W48p0yM5cyTF3I0K6FXHqrSBQoaus+pQmHuRdyZEuJIfTS94c4/VKO1XkXO61x+e0S2ZLJgy9anHslGaNhw6X2+WNm/tevcu5//z3O/x++j1VKU/344ZGf7T+th0fAmasFzr5aQCl4fL3Fwy8bTJzLMDSTIpUzWLnXYepilvkvGix+3SZTNHj+u8OUJmxW7na4+ZsqoTf4sstTDhfeKHLtvQqdWsjE+QyX3ymjlOLOh3WWbh3OB3AyOpe/XWb0VBqvE3Pz1xValZBTL+XJD1tEgcRrxwxNO3z2D+u0qyHj59JceruMYWncfr/Gwo1dYmICzr5WxMno3PhlBd3QOP9GkZnLWRobAV//qkpr85uTt09KRnw78YbsiIHHMuDR8m9YWvv0qUopnARR5LKy8QXl4tkBL0+5cIZT09/h/uOfHcgVEGi9TJtv78nOqrUeUT12+vb+KOSmOTv7A+4/+skTY/2OXeL09HfJ56YHaglJGbO68dUTCcuQVIN2veoAkVzXTMaGX6BSv3ek8FouM8HZ2R/sCVk+LZJJeNv7pGkGU2OvUiqcotVewQ9bB4QGFFJKYplkbLlela67cSgvyTIyZJxhhBB7+uVQ4SxDxXPU2wtU6w9OxAlJp0Y4tUNAcQuuV9233MWzggpCorUNzPHRRGMn2H/M6+kMejpN6tw5ujduYBRLBMvLJ7qmEBpDxXOcmfkeDxbee6IGUjYzzumZ7/UIyzv7caLDdNQaVB13g6W1Tzk/98MdJNwkEy6OAx4u/fKJY0IInaHiOc7N/mAXUTfhGy6tf3pEyQJFrTFPs71IuXB2wMszMfIyvt9kcfWjJ54rn53i7Mz3STvlg78kQLPtJGnHc4/tmVMqZq1yg5Hy5X7ig6abDJXO9ZIztjiXshfOOnp/ra8FXHq7yPojl5lLWaJAIoRg+W4HrxNz/rUCfjcmnTfo1CO6jRDT0ciVTRobAbU1Hyul0amH1FZ8ckMmdmrb8At8iZ3RaVdChiZt3HZEOm+gabB8t8u5V/MYlkYmbxD5MaEbU18LcDI63aZGqxKQHzIxbY2NBY/qio9pJxspFcas/+Mt2vc3SE0WkV5I6/YqYfPoSQ3/pAbP8LTDt//NFF/9bDPJ9TcFQhNcfLtMYcRCxoqLb5V4fL3Fm/9qgh9vPOKdv55ENwVLtzpcfrdMtmzx23+3PRGMnkrzzl9PsPB1m6AbM3Iqxbf/zRTzXzTQNMF3/8cpfvE/LbF0e/9BLzS4/G6Zy+8Ocf29TdKFpAK3k9V541+N///Ye+8wya67zvtzY93KXZ1zT/fkPJqgnCUrWI6y5RzAxsbYL2ZhF3aBfTeRFtgFDMvaOGFjg7GNZAVbkiVZOYwmaXLu6ZxD5aqbz/vHre6enu4eTZJZ9uX7PHo0XXXrnnPPPfee3/mF75ehYwU6r0ow2l0iktTIT9qMdBe57ZNtDBzJU8w43PzRFl7+3hDjfUEFm6pKrL2pmvW31LDzoVGED+turmbN9dWc2JmmsTPCbZ9s5emv9lPOvxX8HxJ11Wtpbbx6QQKrLMk01KynpmrFFWkpXxyhb+jlC84XSOd6GZs8TFvTNbOhF1lWaKzbjBFKMTS2m1xFkVsIgSyrhPQEDTUbaKjdMI+zQgiBaWcZHNl13iqSN8MMr4wkyciySn31Wgw9yfD4XjK5PhzXDLxHQiDJCqpikIy1BAKW8bZ5i4QQPplcb8Xj9OYGpWXnmcqeIRyunad/VRVvY0XH2+gbepmyOV1ZdGaYThUURUdXI9RVr6GpfmvAUCzJeL6L59mXzTkCkM6dIZ3rIZXonL1XkiQTDdctyCs4G2frffm+i+tZ2E6RdLaHsanD5IsjC4waVQlRKI+ha9EF46ZpURpqN9JQuxHTzgblvNlecsVhHLdUIaHzKrlPohIWUAIRWy1KKtlFY+1GYtHGeeE+z3cYnTw4K3L7VsG3bOR4DElfKHY7A3tkGBQFZ3oKWQ9dEhdPMI8dZFlFUXSa6q8ibFQzNLabfHG0on3mAaLCOxUmleyktWFHkENyzjyemD52Ufl9gZfnILFoA021m2f10RRFo7l+K9FIHSPj+8jmB3HcctAXIWZJOw09SUNt8JyfqyXnuEX6hl+hWLrw3BXbKTA4tptYpH5e/o2qGCxrvZlopI7h8Tcom1N4noPArzBNq+hajJrUSprrtszmC7quubgGoKzgTAX6i5cahswVBsmXRkjGWoFKLlaia5632XHLTE6fuKiN6kR/mVXXJBk6UUSSJAaOFli2KU60SiM9aiMrErIqUUg7aCGZ9TdVk520eeXBUVZsT3LTB5s4sz+HrEg4lo9V8vDP4qOzSx7ZcZtC2mH4VJGhkyXqOxySdTrlQhnH9olXaxQzDo4laFkd5fr7Gzj6ShohYNPtNZh5jzP7c6i6jPAFhfT8cGCxe4Ji9wRKWLvogMQ/q8HjOgLfF1Q16JzcmWHkVBFFDSZ178Ec5ZzL6utSHHt5mls+2kJNq0HL6hiP/M9uJvrKZEZNbvuFNl5/eCSIFTaEuOuz7Rx5YYr9T00gBKy+JkVNq8HUYBlZkajriNC2PrakwYMA2/Qxogp6WOb4K9Nkxm2qGkN4ruDAMxOkmkKc2pWhpsUgXqNjxFXKOZfdj47hmB6JGp11N9cw+fdD+K5g5TUpYtUaT3+1j9HuYCG+6q46HFtQ3RTCiKusujbFqz8YfksMHkmSCBupRd22kqSSqDxUV6QtpIsSARXCo3/kNeLRpkq+icRMGKM62UUq0UHZTGNaGXzhoWtRIuHaRUManmczNLrrCiRdC0YnD2LoCaqrliPLKsl4G4lYS4VIbxzLKSCEj6oalQW/lkDzav6ZymaGvuGXL7gSxPNtRicOUFu1cl6+glThiKmKt5PO9VIqT+C6FpKkoKkGkYq7OxRKBMKdkoTve4xNHKRoTrCi/a7L9vaYVpaTPT+lq+1WalOrLvg+z9zTGQNSVQ1CeoJ4tIn6mnX0j7zG8Pi+ebkzIS3w+EVC1Vh2fnGFbDVEVAkRDdfTULMeIXwsO0/ZSuM4JTzfxvc9ZFlBVUKE9CSRcE3lOZivNi+Ez3TmNKOThy5LXfxCoLc04hdLKHqyYvQshByNoVVVgapSPnUSZ+zi+aA8z2J4/I3ZuRs8U8tJJTopW9MUS5M4bhEhgrBXLFpfEaOU5s1jIQSF4hi9Qy9ddLWg7RTp6X8OXY1Qm1oze15ZVkklOkklllG20hRLEzhOEV/4qEoII1RFLFI/Gxqeb+yU6Rt69ZJC8FPpUwxH9tHecsO83CJNNWiqu4q66nUUSqOYZgZPuKiyjq7HiEUaKp7kYN64nkX/yGvUVK0kGZ///pR1HS1WEwhb5/PAxUnyQLDxmZg+TjzShCwrSMiBlMRZCLh3Lq6atph1efobgwgBvQfzCAF9hwMvuhDMrot6WGbz7TUcfy3D0IlgjkwOmIGSgM+ctFTf/PN7rmDXjwPjXKqcs+dALvjdWTJRCGjfEMN1fPY8PjFblX16b5ZZ3ePKcTsfDua+EtVJbW0ne3AIJaLT8q7NeLbL8CMHsKcvbF7+sxo8mTGLn32jnxU7qrjloy0MHC2w9ydj+J7AcwS+J3AsH88NRiMUURAwG8IyC15gkcrBf9VNBuW8ixFTkRUJzxUYcRXb9MlO2Pie4KXvDS0IN50NIeDUrjSO6bF8exVrb6rhlR8MkxkxcW0f3xP4Pjimh+8LVF3GiCrYpj/LIGmWPKIpDSTQDJnqlI7nCUIRZTb30IipTJ8qkp2wyU7Y9B7MkZ/++YsEXsmQR3DCi/+JaWU41fdTVi27h0S8dZY3ZkbhOhqpIxo5vwfB820Gx3ZfkdCcV3Hde77NKlklmWhHlhQkSSFspC4op2fG29Qz+DzTF5C7czbyxWH6R15jedsdqKoxm7gIAelYU93mShvBm2exe+h6FuNTRzgz8CyhUBLbKc6Kfl4KZnSn4tHGWYPhcjCruG6k6Gq7HVlW6R9+dfbe5UsjJKOtuJ6Fcx5pibOZcyVJvuD7MwMhxGwC/ZmB5y4o7Hi5sAdHkSNhpJC+dEgrHMZJp9Hq6i5ZLd1xywyO7WYyfZyVy+6phENkJEl5U6/cDITwKZlTdA88e8n0A6ad5XTf0/jCp7ZqJbKszbtvEaNmnur30n0RWHaO/pHXGBrbMytGfDHwfYeB0dfRtAiNdZvP2gQGRp6mGqQSy2DxAqxKzmOJwdFdDI/tJRxKLTB4pFAIJTZzzy5t4yWERzpzBrPuqgWJ2jP9mJg+sehGIK7VYHtlLL9Y0SYMPKwz6vZCCHQ58PjaogwisCwSWi2mV8T2S0hOmFO7ipSKFgohVEXH8gqVY/05jjwk4lodppfH9stBezPaGhWLRQgISVF8ycPx5zSwrKEEPeMFhA8hJYrtlRG+jyYbyJKC7ZdmrxVAixlUb19G/uQ4tdcvx3c88AXVO5b9yyhLD8dVSjmXvY+PMzVocs17Gjn+2tLVTMW0g2v5tK6L4dg+XVuTpEctHMsPcoCO5Nn18Ag3f7SV3JTNsZemGe8p0bwqysCRPPkpGyOqUsqe50GRAmNk9EyJsZ4yN32kheXbkuz/6TnMyZWb5vuC9JDFpjtjVLcamHmXxuVBe74n8D3Y9egokgLXP9BMKdfPRF+Z4VNFPMfn9O5MQDoYUnCsS2P8/JePQCfqZM/jLGu9hZqqFRfFHWNaaQbH9jA8tveiS28XQ6k8SdnKYNlZTvY+QWfrLVRXrUCR9QsyEIUQ5IvD9A6+xGT64lzOwe99RicOoMgqrU3XVoQvF7a7WPVV8EIuMjK+j/6R14J8DUmiVJ68ZINHVQzqatbS0rCdWGSm6kZiRrTRdcv4vrtE4qQ06/VTFH3RMdRUg7bGq8kXRpjOng7aVA1kWUORdGRJ4ewRtJ0CtlNAUS7sfpwPlp1lbOoIQ6O739Jk5bMh6Rqhzja8dHZJ2Rg3m0FNpQLh4iWMojdDoTSGbecpm1Oc6HmcztZbqEosqxjvbz5uvh/IiPQMvngJkibzUSxPcLLncUoNOyrh6qqLunee75DLDzEwupOp9MlLMnZmYDsFuvufxXFNmuu3nqfaaj4Cbb4Mg6O7GBzbje87lMypcyQrAi003zBAvTzCz3xxhFxhqGLAz++fZedI53oXqfoUyCioso7tl4mqgVyP61uElAiOb+EJlyq9Acsrovo6qqSRd6aRJRVV1nB8iZAUIz+RQZZCVOl1BOKvMiE5StFNY/vlSmsCRVJRJA0Ji5hWE4STEWiygeUF7+OU3kjBTaPLDhIyRXcauyhTcn0kZMJKHMe30OUISa0eV9ionoYuR8k7k7jCChiHBagRnUhHDUM/2ofRlCTaWcuF4i03eGbYkBfTtKxuCnH1e5oIRYKJcfy1aYppB8/xg/9cgWP6CC8IM+WnHHY/NsrmO+vYCNiQQAABAABJREFUdEcdvid45ftDyDIIz8csuAyfKrL7sTGueU8jUwNlTu1KU9NmcMcvtuP7guy4xa6HR7FK3qLhVVmW6NySZN1N1bPfH31xCtf2scvenHen4oUCnzP7stS2Gdzxi22ARHrE5PDzQV6SXfYo5Rx69ueIV+vseGcDz3yjn12PjHLDB5p5xxc78TzBwJE8e348hr0ES/Plwvfdi+K2uVR4ns2l7WoEueIwx8/8mPqatTTWbiIWaQzcuRW5gtkjhY8QPo5bYjpzmpHJA2Ry/Zfs2fGFG+QzyEE4MZPrnWVozhdHgj5Vr6OhbiPxSCOyrC7RJ6/iij7G6OSBCvvwpcH1TPpHdlIojdNUt4VUsgtVDQU79HnVUKLipQiSgtPZHkYm9pPO9swmYNp2nnxxmFi0ITi3a17wWGlqmGUtN9PcsG02OVwIn7I5zUT6BPnCEJZTqChkL27wIAUGj6oYGKEk1cnO4HrOCrGG9ARNdZvJFQZxPRNDryJXGiIWrg9CZ2d1dzrTzXHvUVLJLlLJTqLhWmRp7p7MhNDmozJO+Ajfw7SyTGW7mUyfIJvrv+yKvouBmkqCEKh1NTiT04uyeSvxBKHWNoS3+HtqMXjnPOPpXA+e78zmkR3rztBQs4HGuk2EjeqK4XP2PBYVI9bFNDOMTh5ifOoIJfPKJHFbdo6ewReYzp6hvmY9NamVhLRYJRQ8/54Jgmfc9xwKpXHGpw4zmT55xRiwHbdIz+DzZPMDNNdvoSqxDEXRK97lhf1wXZOpzGlGJ/aTyfXNhj1L5hSWnZvdoHmehfBcrNERlEgEv3zp71xfuIxPH6UmtWqeTqAQohLWXvy+SJKEjIwuh4lrtehymJKbwcdDVUKosoYvPKTKMTG1mpKbDTYmyAggJEew5BIxNfCWSkhU6y2ocgjXt2cNnpnvZEkmpERJaHVISDh+GVe4RNQEmhwK2pMkQnIUQ4lR8s5uTxCSo6hSloRWi8BHkVSqQ62oko7lFXE9C69k4zseHR+9hmLfFKWBNLEV9bhLsEgvOjbiPFK8l7t7kiTo6lJQFYkTJxe+UFav1cibMpYTyNMXsw4ygjXrQxw75lQ8HzJW0SOcUClmHCRZIlaloYbkwJjIOrS2KNQ2qJzq9slPO8iKRKxao5xzaW6UKFkSDgqKImGbHmbepatT4cSJxV9yoagym6zsmN4sx0AkoVLKu4RjKlbZQ1UlkILQmh6WiSY1JFmilHUwix6SBJEqDbvs4Zg+uiETiqkUpm0QYMRVwrHA5iwX3CB/5y2qCleV8AJxzbcCnu/iOMULK5NUZJRYDK9QnEebLUkKuhYlFqknEWsjEq5GU8IgyXi+jWXnKBTHyBUGMa3MBVeNLAUtXhUkxxaD3chiWkHz+9RKxKhBU8NIsozr2VhWhnxxlGxhEMvKzu5AJQmqEnJFYFegyBLZvE8kLOFWLtmylr7pmioBBmGjmkSslVikHk2Loso6Aj9o285TKk+QKwxj2Rl8UcY9x3DW1AiqEkJRJaoSEqMTeVz3/C8KWVJpb7mBjuYb5hk7k+mT9Ay+QLE0ftGinpIkV6gHttPRfNM8Ac9iaYJDJ39AoTRKOJQiZtTjehbZ4uCiBoksa6iKQUiPEQnXEg6lCOlxNDUSLF6VJFnfd3A9G9ctUzKnKJYmKJlTs3k+P0/IkXDAxbN8GXguxT0H8fML8wmNzi7U6mr8cglrcBAv9+ahtnOfcdstLeAUkiUVXY8RjzaRiLUQDqUq0hoSnmdSNjPkikPkC8MBRcJbZAgqik5ISxCPNRGPNGKEqmbDt57nYDkFSuUp8sUhSuUpHLf8FlWRSmhqmIhRQzLeRjRSh67FkGUF33ex7DyF0jjZ/EClWGB+CEmR9YAdvWIk+cLHdgpXrK9GKMmWtZ+Yx+rsuGVO9jzOyMT+Ra5GpjrUgoRMyc2S0IOwZdnNYftlNDkUhDSVKopuGh+PuFrLpNVHQqtH4JO1x6gx2jHdPJ5wiGk1OL6JJ1zCSpxpaxCrEm6SUagx2vB8F8svktDq8ISD7ZuBB0kKxGujaoqcM4YsqUSUJJNWHym9Bcc3yTuT1BnLKDhTIMnE1GpMLwfIGEqUSbMfRwT5Q0ZTkkhLivypMZxsmfiaRty8SXkwMzsG5zFpLs/gCYVg61U6+bxPNivwPEEsLhMOSyQTEsePu4QjEmvXqDzzM4urtmg4LvT3eaxbp7JhvcaLL1k0Niqc7nbRVFi5QiVVLfO9fwwWHEWBrVdpOA5MTvoIBGEjEB2rTkmcOhWov151lc5zz1usXKGih+DECZcN6zXWrdXYs88mmZAYHPKxbcGqlSrt7Qp/+63LD3/8Ky4dkqah1tfiTkwi7J9//tIMlFRVYLhMXXlySEUONNk6WlWQJFxXMJX2WLVcp6fPQQgYHnWprlJIZz3q6xSyOUE0IpHJ+mxcq3PqjEM0KmNZPqGQRD4vGBh20TRYs0LHsgWmFfxGCGioU+jpD+ROaqsVdA2mMz7VKZnxCZ9tm0P87MUSzpusZYlYCxtWPkAkPJdfkS+OcvT0Q5ctJxExali/8n3zGKl932X/se8yne0mFesgXx5bJEfhXzaUmhSRjWvxTQtJ1zBPnMYdW7hTV2tqiG3eghQKUXzjDezRKyvf8a/4l4F4tInNaz4yj/SzUBxj39Fvn1fe4//POJ/Bc1khrS2bNbq6FBRF5dBhh7vvMnj5ZYvaOpneHo9rrtbZvdfG92H9Og1FkYhGYcu7DI4dc7AswXXX6RQKgs5Og/Fxj5ERj1T1nMt+7RqV1atVhJA4ccLhhutDHDzkkEhIdJ9xueYanRdfsnE9QecyhaoqCcsSfOgDEY4cdcgXfK7ZoZPL+3R1qWSzPt3dLm2tV0ZQMdUUIpIIPD6FMRVVClO2M6hKGNczUWQ9cM0KB5AQCGRkwqEURXMySEhFDkogkQMXND5hPQUILKeArsWwnQK6GsXx5nseZEkhpCcomVNnnStIUHP9ufCSqktUtxhoukx+yiF3mZw/4U0b0Joa8AtFyoePYqxagXn6DGpVEknX8UtlQiu6AtXn4WEQIMky1sAgkY3rMU+cRm9vQW9pJv/Sa8jRKKGuZZQOHCa8ZhVePo+kKOidQeVW8Y2DeOcYJEoyQfSa7eD7mN09CNNEa2ygdOgo0W1bKB85RvSqzQHxl6JgnjhFaFk7pcNHCbW3IVwXN50hum0L9sAQbiaLsXolfr6Al8tjrF6B1d2DsXYVcjiMOz5J6dCRxeOz56C6xSAcV3BKHolEcEcMXUKWYPP6EIVCYLxUJQKx2RWdGiNjMp3tKmVToKoS+w5YhMMSjQ0KG9eGKBR9Rsc9hkaCXXvYkGhuVHA90FRoqFM5dMwmEpZZ0alRLPl0tWvsO2yRiMusW6UTjwWGkqZJOG7gQa1uMVA1ieyETWF6xjOlkEosm5cA7PsuE9PHKZQuTUH+bJh2lpI5Pc/gkSRlVshTkmQaU+sDwrjc6Ys3fC6DmXj+eSr/v4BTRVc1krq6i5GH9+IVFvc6elNp7KERJEVBjkaWPK+aSATPgGleWOOX0N8rea6aW9egGDrjPz348+Qu/b8cEnXV6xaQNE5lT/+rsXOJuCyDx7LBCEn09lV0pdI+sZhEIi7T0gKyAm1tCu3tKrmcQ3W1jK4HLvy6OoWQIVEs+kQiEt3dDlUpmbr6c5V5QdclBgc9HAfyBR/DgHhCor0tqMZqaVZY1qGSzQjicZl4HEplQU2tTCQiYdmByGdPj0csLtHQqFwxtvr7fnUZV7+rkTP7svzDvx9BKtegKREEPmVbEFJjCOEjyxqGnsT1TEwnRyRUgyrrKIqOpoQr1ShlCuVxXN9CV6PoagRdjaLIGp5nEQmlMB0FQ0uiqWEc18R2C8SNehRJJaTFkWUN1zOx3SKF8visS7q6xeCXvrSexq4IT399gMf+4vKSECVNxc8XsIdHEI6LEo8haSqSYSAbIYTvI0mQ37kLYdmodbVENm3AdxzkcBgvl8Pq8ytVKDJeJouaqkJrqEdrasCZmCR23dV402nkVBK9pYnydHr+IlYRV3Ump3AnplBrUsjRIAFRScQri0qU0oGDOCNjIEmE161Ba2xAb22hdPAw3nQaZ3g0IArzPPxyGb21GTedAUlCqa1Gb23F6u1DX9aOeaZn0RDEuXjff1jO5jtrOfXqNIe+c4bJCQffA1WF6YxHJCyTL/ioqkShKOgbcDFCEn2DLqWSAAk8X9Db71Is+bxxyCSXF1iWIF8IDC7LglNnHBRForZaIZO1GRlz8X2B7QiScZlTZxyGR1xqqxX6BgOvj6ZKhEISpbKgcXmET/3ZOmpaDB798x6e+WagjaXIGvFY87zEaNezyBeHLlqEcjH4vrtAIytIjFQBiXx5nFxpBEXWLlpLS6uOYjRVUTg5Oqe7c4kwWqqRdZVS78SSCcYzUMIaofpEIAh8Hlhn+tBbm/AKxSXV0r1CAb9sEursPO+O9VyE22uRJCj1Xn7eTWxlEC4wRzJveqyWjKBEdObqlf8VlwsjlKSmasUs+SAEz+B08RQN17Thlh2mD48h3mReno1YWxLh+RSH5xtMejxEzeZGZEVm4sAITt6ialUt0eYE6aPjWDmTeHsV6WP/sjW7LsvgOXrUIZP2MU2B40BfX5mqKolwWKKv32V42EfTID1tMjbuk0rJCB9yeZ+aGpkjRx1yWUFVlUQmK1AViMak4IVfQfcZF9MSuI7AtAJxzrAB27frDI94DA4GL7Rnn7WYmPCIxiRURSKdCdoAyGUFyaREvhCUyCUTEkeOXLkQykzkz/ddTHMSTQ2jyiF0JYLnu8iygqYYSEgokoosKQGRHsGu1vUsPN+lbKdx/WBn6Pk2RatMSIuhKgaqYuD6dpBJr+hBulclodf17dnkQ9cLKmZK1vSC+LvElStDt870ojXUE9m4nsLruxEClHgctSoZKLUDXrGIqCSqeNkcvmUS3bKJwu59gECJhJGMEHIkgpcvYPX0Ebv+aqwzvfiFAsI08W0bt7sXe2h4wY7dzxcwT3ejNTUS3rgOu28AOWygVCVRYsGuSHguXiU3ByEwu88Q3bENd3wCL5tD0rWgRFhRkHQNd3yCUNcyjNpq8q/uQonH8C0Tv1CgPD6BX744T4NlCV7ZZWKVllp4g3k4sIRA/NBI5Xd9C7+zbMGZvuAenzozN59Hxha2lS+49PTPzIdF5v45eb6SJKOr83eWvvBwnCuT+K7I+gJeKCF8XN9CkiQSkUZKVppIKEW+NLZQLV2R0OJh5JCG8HzcXBnfdlHjBomNbSQ2tuKVbJxcGSddBF+gJsPBMVEDJHCyJYTtISkyaiKMrCt4ZQc3b4IQaFURqq9fiaRI+LaLVzBxsqXAW1kRMpQUBd92cXPlmYFDq4qghDU80wk+F4AsoSXCyCEV33KxB4bBF0iqjJIMI1wfNRoKSm21KMbyFUiyjBwOL3hmJU1BS4SRVAXfCdoWro+WilJz0yp80wn6VLBw8+WgT4kwvuWixA2E6+NmSwjPR9ZV1IQRhHSLFl4xqIbRq6PU3bmewqkxhBC4BXPWayUbGmrcQJKlufECJFVGr4khydLcuSqfq8kIslpp46zzyKoCsoQS1vFK1uy5Lgiygqxq+PYF/kaWK95ZCTkUwrftJRLtzx5sGVnX8W3rwjyGs22ArBsI10H4l2J0S9QklxON1J3FrCxIZ3spFMapVqupWlVL+vgEwvHQYiGUkIJbdvDKLmpEwynYqBEN3/GQZBktqlGzqRFrukxxJD/PLhWAnbUI10ZovmkZYzsHaNjRyvTRcZpv6WTk5V4adrRSHi/i2R5O3kKNaKjh4Pmz8xaqoSGHggR0O2ciBOgxHUlT8G0PO2f+s9vCl2Xw2Daz3p0ZFArBvJjxyADMcGbl83PHZrNz/54XqTiHUNTzoL9/fhuKAgcOOAyPeFgVz/HkZDDJMtm5Ec3lFm9j8i1ijrecPAXTmSNaQyJm1GG7JYpmYBnP9K5gTgQDNfMyq1SQcPb3QNlOB2eSZEJajLKboWTNlc8KBAVzvEJ7sPi53groLU2oNdU4Y+N4uQJWTy+hjjbwBfbIKKJs4vr+7EtC2HbwkkfCHR8HRUVrCZSYtZYm3Ok0zsgY7sQUztAwfrFE6Y2DhJZ3olansAcXWgRyJExoWQfC97F7+3Gn0/jFEsbqldhDwwjHwRkZmyfc545P4E5MYA8OI2wbrbkRJZEASUKtqcEZG8MZGsFPxPGmpvELBexkErW6GpfpecnV/7djwUJ7kaSS50M4lCJyDg+M45RwnBKKrBPWqwhpcRy3vDCxWAq8D/V3bQio0RGMP3GIwqkREhvbqL11DeGWFLKmUOqbYvypw/imTccv3kR5MI1eG5Aajv/0EOX+KZLblpG6ZjmSLONbDhNPHaJ4ZoLUtcupvnY5SBCqS5A/NszUC8cRQlD/tg3EN7QiXA97Is/YEwcACDUkaHzXVci6ivAFwz/chTmSIb62mdpb1yJpgVdy4mdHyB8dxmhM0vaJGymcHMVoTmFPFRj98X7cyUmE6yBpeuAqn7l0Rab6uhUkt3SALOEVLUYf2Yc9VaD6+pWkru7Ctz2MpipyhwaZevkkaixE5+fvIH9kCKOtBjdfZvSxN/AKFrW3ryW2qikwANNFRh97A9/xqLtjPckt7RhNVcRWNZJ+vZvMnh60qggN77gKozHwFJR6Jhj/6SEAYisa0D4YRomEsKcLDP/TbryiTfX1K0hsCWROvILJ2OMHMUcyJDe3UX3dSqzJfDC+R4aY+NkRhHdh7y49WU20bQWZY3sRzpsk4OsGRl0TpaEeZD1Eat0OsqcO4hbOL0uiRmIkVm4mc2w3vnV+w0pSVCJNHRQHu5FUjao1V1EY6MZOXzxLdkiP01C7MRDPrcDzLCamj2GVC5TGdIyagEsnVBWm/e5VCM/Hdz3Gdg3SdF07Zx49RuttXWS7p4m1JQnXRok2xxnbvVALzclbTB0epem6DiTVxaiNYOdtpo+Mk1pdh54wiDbFab65Ey2qc+aRIyQ6q6laWUO4LkbvT47TdEMHiq6ghFTGdg3gmi6N17SjRjWcos3p7x/Es/55359XvCzdtqGn5629KM+Dnt7/8xaeGYKnGRe0AArm+PmZW5e0eCvnEMFZET650vAlnuvKo3z42Ly/7d5+7N5zWD/PSfWw+/qx++aOKe3dP+97Ydvkn39p9m9nbBxnbOmXhZfNkX/h5XmfFV59/Zx+Hj2nDYfCyzvn2hgexRmeXz5uHj85d7xlUzpwaMk+/N8KIXxsdz57qaoYxKONTGffXC37fFCUEPW164mG5/gzhBAUy5NYdg7XM0kX+ijbWTQlXHmu5iDJMtGVDQhfMPLQ6yDAyQSel+mdp5EUieTWZfR940W8kjXrSVHjYeRQgaHvvx4sDpaDlopQd/s6pl89RfHMOHW3raP2jvUUzzzPxNNH0Gti+JbL6KOBIYAQxNY2U7Wjk8Hvvoo5lkPWFdycidGSQo3oTL10glLPJK0fvpbklnbcXJm629dROD1G7tAAqauXU3fXRvLHRkCRCTUmmXj2KOM/PQwygZdDGkdvbkFSFOyxufkph1SSW9op9UwE16rK2OkiwvMZf/IgocYk9niOsScOILwKZa0Eem0cJ28y8XcvB+HSgkV0VSOJTe2MP3EQJ1ui+X3bSV27gvEnDjL84B7CbdVMvXKKzK4ziIrXourqLoymJIN//xpuvhyEoy1n9r6MPLQXSZVp/ch1RJbV4UwXqLl5NeNPHsIczdL4ji3U3LyaoR+8jqQqhNtrGHv8AOXhTDAPLsDY0eIpYp1rUI1owAMTMoh2rUcxIpiTw5RHB4h3rkVLpLCzUxT7T5FYsZF413r0ZA2FgdMo4ShVa7YiPHdRw0eJxEgs34ASMpB1A1kLEW1dgRavwk5PUOg7SaxzDaFUHU4hR6HvONG2FaTW7UBP1VHoPY4cCpNcuQnfscj3HsdOX2g4SKK+Zh3JRPs8706+NMZU5hTnPnuxtiRuyabnx8dY8f6NRJviKCEVSQLF0NATIaJNCfp+epL6bS2LP7oSVK2uJdwQY+CZ08RaEvO+AyhPlTnzoyOs+vBmoo1xVEPFLTnEWhJo8RCKrjDyaj9GTRijNkp5oogSUjAnimROT/2zGzvwzy0e+v8DXDmaevGWU97/K/4VM/B9l0JxnPrqOVI1WVapr1nPdPbMJVdpaWqEpvqraG3YMc9b5AuPdPbMLNNxWE8hhCAWriNbHMI6K49HeD7ZN/oJt1bTdP92CidGSb/eHTD4+yLIaRAiWDzPym/wbZfCiZEgxFWB0hAitqYJWVNIXd2FbOhYo5kKhb4fkMr6lXNVNjLh9mrsiTzF7sAYP/upLA+lKfdN4ebKWJN51JiBHFKJrW1Gr4mRWN+CrKu4RWt2IXGmixS7x4PwUwVuJoNXqjDNnkU86JUdJp8/Tu2tazGaqsge7MeZLgZbLd+fvf6gv3P9cvNlCidH5kJvQKg+QWxlA5K8GeF6KFFj9jfCD8hcmTlXBeHWaoqnxzCHF+YeFbvHMUezKBEdN28GWkdVUWIrGuAugW+7Fe/P3PiXB6YpD07jlS6wiEKWCTe245kl7MwkkZZOjNpmjPpWzIkhom0rsdKTOKU8vmMTX76B/JljmBNDGDWN5HuOgRBIikpx6BhGXTOh6vpzDB6JcG0zIFEcPENi5Ub0VC2Rlk7Kw31EWpdjTg7jlQtYvk98xQaK/Scxx4dxWtPkTh9GeC6yolIa6UMOGRi1zdjZqTcteAg0s5bR2njNPKX6QHJmf8D5Y6jE25NEGmJEGuPYOQstqlO9th5FUyiPF6nd1ETV6joijTFyPdN4tkuyq5pwbQRnkYT6REeKzvvWML53GD0ewkqX0aIa1RsaEJ7AzploEY3UmjoUQ0UAqXX15PsyuGUHBHimi+94gaFdge/6FEfymFOl/yPSuy7c4JHmNDAWhDKls6Ipi9zPmbzHc79b7PMFnGGLtbdY9y7xd296HirnuZwbdfb4vNm5zjo2+MFFXsc5vz+7vbdirs2O1yL9PHssL3penHO+c+/Lhd6Tt2xeiErz/xfMi8XgC5dsvh/bKc4y0UqSRCLWyoqOu+gberlCwHYhPC0SqmKQSnbSWLuRmqqVqOpc/k6gfD3J6OSh2YTokjVNrOIBWowrxxycpv8bLxBd2UjjO7YgqXIQWvFnvBrz9aBm2vHPrcUXAmssy+A/7qQ8WFnE/TljQQiBJEvz557pIhsaKBJ48wfRt9y5JFIBMxpC9mSe4R/tpXBydGaAZ40x3/UW9WwsyrAsBLmDA5TOjBNf10r93RvwTIfc/v7Z7yX5rIdy5meeWJDALVyPYvc4fd98cTZ3ZibnrqJBwLmDKGwXJawvWgU34+mZhSQhfB9zOEP/372CPVWo9MWb7ZrvuBeVdCshIakqXrmIZ5bAF8iqhhIyEL5PabgXNRon1rYCc3IUJRwBBJ5t4nsOnllC1g08s4RbyOLFksiKOv96JJBUFd+18MpFhO8jKxpKKAyyPBsWi3WsxpwcQTEiIIFvm/iei2cWkVUNzzJxChlUP44aic9KOywFRdapq17DspabiRg187w7mVwfE9PHAZA1GeEJ8n0ZtIhGtmeayYMjRBpijO0aIN+fYWzXAEZNhPG9Q+R60pTGCiSX15DtnibXM73g2Re+IH088ECFqgyy3VOM7R4k2pRg6IUzWFmTkVf6CDfEGN89SL43jRbW0BIhhl7spTSSY8LzMafLeKaLmi4Tb6/CzpmE66LE2qvoefQYbvHiq4Mb716PVhWZvTfnInd4iOzh4YVfLIILNniuf18jN3+khRM7Mzz+171YxeDBkGS49eOtXPveRgAe/O+nOfl6ZnZAI0mVj//RGhK1Ot/7TycZPB5M+vYNcd7/OyvIjFn8/e+eQAhBx6YEG2+roWVVFCMWyE6MnSmx58dj9B5cvAwvHFdZtinO2huraVkdJRxXsUoeYz1ljr44Rfe+7Cxx4FJQNInaVoMVO6rouioRlBRHVVzHJzdpM9pd4tSuDN17s9jmxeXGhOMqt3yshc131mIVPV7+wTB7frwwTKMZMs0ro6y7qZplmxLEajQ822dq0OT4a2lO7cowPWItuUhJUqAUv+G2GlbuSBKv0TGLHn2Hchx8ZhKr7OO/BSzOt32ylavf3cDBn03xzNf7Z8dHViTu/XwHm+4IFq1/+H9P0Hdo7h5WN4f4yO+txogqfPvfH2eiL9h5rrqminf9eicjp0v88A9OIckSXVsSbLy9lsblEUJhhWLWYfhkkT0/GWfw2OIVU5GkSufmBOtuqqZ5VZRQRMEsegyfKnLspWnO7A/Eac8HVZOo6wiz8poqOjcnSDUZGBEFx/bJTdgMnypyYmeG3oM53IuUBYkkVd72S+2svTFFYdrhxX8Y4uDPFkobhCIKLWtirLspRfv6ONGUhmv5TPSVOfZqmtO7M2THl36JyIpE4/IIG26tYcW2JLFqjWLWpWd/joM/m0SWpXlqx2cjWxhkfPooLfVbkSq7TUmSqE52EYvUky+OkMn1UyxPYNuFs4wfCVXR0bRoRQSygXi0kZCeQFMj54h2CmynQO/gi/OkHSRJQldjlKyphYa0IpPY3IaWjOCVHXzLQbhz4+9kSmhVEVJXd1EeygQVVktYh/ZUgcLxUWpuXkPh2DCSrmCP58gfDV6g1liWqm2dVG3vwhzJUB6cInd4kKqru2h+3w7K/dNIskT+6BJZ54BXMMkdGKDmxlVBsq8i42RK5A5cnPAjgBLRqdq2bE7axnbnjC5BkC+0roWq7Z1YoxnKQ4tXgQEUT41RtaOL2lvWUB6YQja0wHszGFRD2uM5kpvb8B0XczCNNZYls6+X5vfvoOHtm7Cng1Ba7sDAkm2YQ2nKQ2lqb1lDsXsM2dAoD0xT6r74vBYgYMkeHyTRtSFgW89nKI8NoERi6IkUlufiTRcBCS2WwJocASGCwgPXpXrjdeS6D+MWcwjPw7PKCNeZ/14VAnNyhKo1W9FWJHDzGczJEdRKG04hiztSDIhxY1VY02MBI7bv4xbz1Gy9heyJN3BLeXzXxbctPFlBIKhNrSYZb8NxihVFdg9F1jFCVSTirUTDdfOeESEEZXOKvuFXZoVbnbzN0AtzVbaSBNnj40wfmRvTqcNBPoGmgeOAlS5THFqavDLfnyHfn5n3WebEJJkTcwmv43uHZtuTZZg8OD8VwMqYaBqU8hbSpISRChNvTeK7HrneNJ51aSSWwvcDo1OVia9pQjgexd4pZEMl1llL/viFM9pfsMFjlTyqmw2WbY4TS2mzBk8kqbFiW5LWNUFFR9eWBN17sxXZhWARblsXxyy6uM7cSykUUWhaESGSUKlqDLHpjlre9uk2olXz1YPX3VjNZH+Z3kP5BYt9vEbjns91cO39jRhRFSEqOzIJVl6d4pp3N/DGUxP85K96mRpcPOFMN2S2v7OB2z7RSuPyCLK80ITcfGewEH/rN48FirEXiHBc5a7PtHPzR5pxHcEz3+zn0LMLM6aNmMINDzRx2ydaSTUZ865j+bYqtt3XwKndGR77ix76DuYW9bB1bU3y3t/sonNLEmA2j2jNdSm2vb2e1x4cxS5f+URmu+xR1xama0uiItQaLL7xGo2uq+bmxbLNiXkGT+PyKK1rYmQnbLyz5oURV2laEQVJItVosOOd9dz2iVaM2PypuvraFKPdpUUNnpoWg7s/1872+xoCwdmzxnPVNSmuu7+RvT8Z5/G/7iUztrixEIoqXPveRm75WAv1HQsrZQC23FVH55Zpvvs7x5c8z2KIpjTu+3+Wcd39jZhFj1d/OMKxlxcuTJGkyq0fa+GmD7eQqNXnXceK7VXseGcDx16Z5rG/6GHoZHGhMSzB2htTvOvfdNG6tlK1VpkX626sZuvddex+bGxJI97zLPqHXiYcSlKTWjXLJhsIiSYI6QlqU6tnzxt4Z0RFoPLNeR+EEJStNGcGnmV8+ihnX0DUqMPzHWLhBormNJ5vzfudV7SJrmhA1hQyb/SR2d0z6zEpnh5n/MlDRLvqEZ6gPDCFb7ukX+vGGpv/0vdKNkM/fJ3U9i4iXXW4eXPeYpx+vRskiWhXHb7tYg5NY08VGPjOK6SuWU50RT3mSAbh+lhjOdKvd+NXPB2FEyNIihzkAD2+n6qrlhFZVotvu5QHgyoKN1tm+pVTeOULmz++6+GZLtEVAfPu+NOHyR+bM7amXj6J8AWxlQ34loM5nMEzHaZePhGE0c6CNZ5j8B9eI7W9k+jKBuyx3Dz+oLEnD5K6dkVQnp4tY41lyR8fYfB7O0lu6SBaFaF4ehwhfAonR5E1JTAuHJfM3l7M4TROpsTAd4Oxiq1sxJ4u4BWCd2h5cBrh+XNepQuENTXGxNT8BMH0wdfm/T3x+tPz/vbMEpO7npn9O3N0DwBu/+IbaSeXZmLXz+Z9NvObGUzunv89wNS+F2b/nT3xRnCu7JwhH4820dF8wwUn/ztumb7hV8hke1lqtxsKSSSTEmNjC5/jLVs0jhxxZyufq6slyiXBRRabzkMkIhGJSExMLGxv21adPXttXFcwvmcIv3eEXM7nEuXgABh7OsgXDdXF0auj9P/jbuypIkhQd8tqwq0pMvuXNrrPxgUbPGM9Zcp5l1SjQbRKmzUg4tUaDV0RsuMW4YRK69o4qibjVdyn9cvChCIKA0fzFDMLy2GNqMKtH29h3U3VDJ0scPyVNFODJpIM9Z0Rlm1K0L0vu+BeR6tU7vmVDq57XxPFjMMrPxjh9J4s5ZxLOKmy6uoqtt5bx/b76hECHvzD05TO2dFLMlzznkbu+9VlRKs00iMWJ19P03coTzHtoIcV6jvDdGyMc2ZfjunhC5cwCCdU7vpsOzd9sBmz6PHU1/rZ+dAoVmn+JNFCMtfd38Tdn+sAEQiNHnlhmsy4jR6WWbYxwfZ31LNye5L3//ZyvvM7Jxg7M58hun5ZmHd8cRkdGxNkJ2x2PTLKydczeK5PQ2eEbW+v55aPNKNoV4h86CyMdpcwix41rQbhmEpuIpjZVQ0hqptDZMctIkmN9vWxeV7jhq4IelhhtLuIWVj4wosmVe74VBtrb0jRcyDH8VfTpEcsVF2ioStC86ooPfsXVlgkanXe/qvL2HpPHfkpm+e/O0733hx22SNapbHuxhSb7qzlmvc04nmCh/579wLRVkWTuPGDTdzzuWWEIgqTA4GXbeBonnLWJRRVaOiM0LExztEXp2ev+UIQS2nc+4UOrru/kdykzRNf7mPf4+ML+hCKKNz6sVZu/4VWHNvnlR8Oc/yVNLmKAG7X1gTb3l7PupuqUVSZf/yvJxcY9a1rYrz9C8toXhUlPWKy80ejnN4bPEtNK6Nsv6+eWz7egh5amoSzbKU51ftTbKdEbWrVAg/NDIKQ14WReQY6aGUyuT4GRnaSyS/UQcsVh0jG2jArSczz4AsKJ0YonFg8j8i3XdKvdwfGylmYeunEosd7BYvJ548t/l3JZvLZows+t0azjD6yb95nbsHEGp2bk/kjc4aIX3aYfvUU06+eQjXieE4ZLZwgEmlm6oVTCP/Cdr8hoxp/QGVo985Fv/eKFhNPH573mUqUqedPohlxok3LyI3MjYM9nmPs8QOLnsueLJB/dQJJVilOVgwMX1A8NUbx1HyDo3BsLqQgbG/e2LvZMhNPze8TQLlvinLfz0ew9V8aZjyffcOvBKHes6pu43GJq7YEjoGpaZ94XAYBsZjHmlUajisYHPRY3qXS3qEgAV1dKnv22mzfpmOagjf2O3QuU5FlOHHSZctmjWw2OFfIAMsUPPushWVDTY3M2jUqiiIxMurR2KCQy/nU1cl0daqUy4LRsaC91lYFzxe0tSq8sd/hlptDjI15HDnqsmqlim0Lens9tmzRmJryqUrJaCoUS4Knn36T9VWW0JJh9OoovuUiqTKhutib8mOdjQs2eCb7yxQzDi2rY8Rr5rwwyYYQNa0GR16YpqEzTNOKCEZUCXhHJGhYFkEPy0z0lSllFz7UyfoQV7+zgVd+OMLT3+inlHEDF7sUuONVTVqwA5VkWH1dimvf24hVcHnwj05z5IVpHNufjZsfe2maycEy7/3N5Wy4pYZjL02z5yfz3ajNK6Pc+vEWYtUafYfyPPbnPXTvy+K5fpBXMtMHXUaSWNL1D8yLQ0erNO7+5Xauf38T5YLL4/+rl70/GV90J928KuiDbsg8+ZV+nvv2IHZ5TjDwxKtp+o/k+fB/XUXHxgRXv7Oex77UO/t7RZPYeGsNy7dXYRZcnvjfvbz+o9HZtk7tynBiZ4aP/LdVLN+WfFPaiYvFWE8Js+BS0xomWlWZTlJAdJio0znywjSta2M0rYyiGTJ2OSAkbOiMoGoSo2cCg+lc1LSFiVXrPP+dQZ77u0HMYiUZ7jzzQlElNt5ew9a768hPOfzg905z/NU0rh0cJ0lw/JVppkcs3v6FDjbfWcuh56Y4+uJ8Buf29XFu+UgLkYTKqd0ZHvkfZxg4XsB3KomclT5oeiC0d748xLO/S9Tp3Pv5Dq55VwPZCZtH//wMB56ZnPWGzuvDxjg3f6QZJPjp3/Tx6g9HAiHdyqHHXplm+GSRB/7jSlZsT7L1njqe/vrcLkczZK66u4729XGKGYfH/qKHfU9OzBpWJ1/P0L03w4f/62ra1sXOO7eL5QlO9PyE6Ww3DTUbScSa0LX4RXM6uZ5F2ZwmXxxhYvo46WzPogzKuhpFVUKUzCnCoSpkWf25a169VdCjVdR27aA0PYRdzhGpagLALqaDHBPXBiHQo1VIsoqi6tilDK5VIpxsQI+mQAiMRD1aOIFVmML3HIxYDUIIzPwknj2zIZIIxWuo7dxKfrwHz7GIVrcE4apSOgjB2GVkRUE14iiqjqzoWIVJfNfBSNZjJOpxSlnCVU1oRpRydhxJktAiVSB8zNwEnvN/l/zHPzc83yGbH2BwdBeT6ZMLiDcNQ2LLFg3fh+5ul2PHXVYuV5Ekhckpn+pqiRtvDPHccyZVKQlZkTBNgWlCJuNz5oxLdbVMqeTjC9i4QSUel3jqaZsPPBBmbNxnWUegPQmCaFTiqquCNV8Iwfi4R0ODjCRJDA15dHUptLXpPPecRU2NjCxLWBaUSoJMxufwEYf2NpXxcY/qapnVq1Q0DQ4cdHjPu8NMTHi0NCtvSo7u5soUTk/Q/pGr8QpWQPHgCwZ+uGfpH52DCzZ4zKLHRF+Z9g1x6trCKGqQgNWyKooWkunel8X3BSt3VAUenwkbI6pQ02rg2j5jPSW8RXJIJBkGjhZ44btD5CfPurEiYJpdbDHQDYVt99ZjRFWOvjTNoWen5p9bgGP5HH1hmhs/0ExDV4TV16XY//Tk7OInK7Dh1hpq28KU8y4/+9sBTr6enr94zfbhzV2utukjfEEkqXLP59q54QPNZCcsHvuLHg4+O7VkjseWt9WSbAgxejpQeT+XoM5zBaf3ZOg7mGPTnbWsuaGap742MHtcKKKw/pYaZBmGTxfZ8+P5hpXvwXhviV2PjrF8W/JNr+NiUc67TPSXaVwepbY9TM/+HKou07IqiixLnNqdQQ/LtKyOUd8RYfB4gXBCJdUUwir7TPSWF11sZRm692V56R+H5xvK55kX4YTK1nvqUHSZE6+lOfry9Ly8JSGCeXz4+SmufU8jNa0Gq6+p4sRr6dnzyYrE5jtrqWoIUcw4PPXVfnoO5s6J8V/EvCh7CCFINoR4+xc6uPqdDUwNmjz8P7s59kp60esA2HpPHdEqje69WfY9PrEgHOk5ghOvpRk6VmDVtVWsuT7FC38/NHtcNKmx7qZqJAn6DuXZ/8zkPC+S7wmGThTZ98Q4bevmEwwuBs+zGJ04wFT6NNFIHbFIPbFIA0YoRUgPyDHlCl+MED6e5+B6FrZTxLKzlMpTlMwpymaaspVekj1ZkhQiRk2FYdkL2MPP4zmKxQKi0xkIEZA95vM//3KQcFgiFpUwz9u+hKyoARmdEChaCEmSSTavwbXLmLlxhOdS1bYBhKAw2U+yeS12KYui6UiSgqzqJJtXY5eyhBP12KUM4WQD2ZGTCyoAJElGks9qTw0hSRJVLetx7RLFqUG0UIRY3TIkWaEw0UtV63ocs4AEyIqGFkkSitdiF9NUtazFcyxUPUxhsu+iWKDPhaJAIiEFIswVCAHZrI9z5XhhLwiSBMmkhKJI5POXF4I5H7L5fkYmDhAxqtG0CIqszwqm2k6BQmmMbH6ATL4f08oseg7bFkxM+JUQN3QuU+noUOgb8Ojv8zAMmYlJj02bNXRdwrYFtbUyLc0K4+M+K1ZoDAx6tLUqyDIMDHj4Isj1KRQEhbxPqSTPvvLMsmBqysf3QVEkurpUamtlxsY8MhmPUknBdX22bdOQpOD5a2qSaWhQGJ/wWbNaY3zcp7Mz8Cj19Xl4ftCvQsEnnxdUJd98Hnllh6FHDxA9NIheFcF3PEoD6QVh6vPhosrSh04W2XpvEI5QNAlEsBv2HEH/4TyRuMq6m6ppWR3j5OsZolUa1S0GZt5jrGdxoU7hB16I9OiFh4uiVSotq6MAuLbPmhtSix+X1PAcgSxLVDUEmlczGlLhuErrmhiKJjF8oEjvwfyFSCQtCavkEUlo3PihZq69v4nMmMUjf3aGI89P4S6xqOlhhbZ1cVRNwix6dGyM07g8suA4VZORlKBKJprUSDaEGK+MZ7RKo649jPBh4EghUFw/B8KHoRNB6CgUuTIaYjPwvWBebLytlsauCJIsoRkybWvj2KZH38Ec9R1hurYmaVoVZfB4gWSdTrJep5h2mBxYnLnX9wQnXk2Tn7rwN0+iRqd5ZTQoy/UFa5eYF4laHc/1kRWJ6maDUESZNapiKY3mVVFkVaL3YC5Isr+MtdMqe8RrdO7+bDvb3l7PxECZh//0DMdfTS/pVQlFFdrWxZDkwGDq2ppYEPICCIWDeylJErFqnUStPptjFqvRgs2GI+g/kp/NuTsbniMYOl7AKnlooQsLdzpukUyuSDbfjyyryJJ6Vs7OzMIVlIAFeT0evvDxffeCFKSF8MiXRpAlBV2LMZ0vLKmjJUnwK5+L8sADc8+M5wuefMLkv/63n6/WkKrCe95j8GtfjPHTpyz+839e/CXsWiXsYpZydizQlitmKEz2YSQbZsdQqijI26UMxck+IqnAu1KaHkJSVBKNK1H1cMAi7poIBGZhilL63MRpgWMWsIsZytkx1FAUqzBFYbKXaE175b7NtWcVpoPvajsQnkdhohc9ZhNJNaOF4/iujWcHzM3l3ASl9IVVxiyFjg6FP/iDJMu75pahUknwH347y86dP1+PXnW1zB/+YYLly1V+//fyPP/Cha9HF4N0rpdsYeis52YuOVkIH9938HyH8710cjnBI49WqupEsDnc90ZgsDi2oK8/eCeEQoGH2XGg54xLqSzwfTjd7VIuC3p7XCSJinZfcO6nn7HwPMGhwy6mGfRhcsrn0R87yEYEz3XRdA1JuLi+jlWWmCzoCN8nHNVwLBur4NLb62F6IWRVJaRD2YT+UR+BhFmWUHUVX9N59jUFu1jiwEHzwqqx5WAdtDMlCifHUONGwGpevjAL+eIMnuMFhBA0dEZQNBlFlWheFWV62CQ7YTHeV8L3RLBgKMHiUd0copR3F+SdzMA2PdKj1nld6ueiqjGEXlm4d7yzgR3vbDjv8UIIdENGPeulrkcUkg3Bbmd6xKIwffkP2M0faeaGDzSjqBJ7Hx/nyAtLGzsAsWqNSJWGJEms2J5kxfbze2CEEMiqhBGdM1riNRpaSEYIwfTw0q5lq+RSSDtX3uDxxey8aFweQZIDY7JxZYSpQZPcpM1YTwlZlmheGUWSg9BOsi7E1GCZiSWSwK2SR2bMuqgQXKophBpSUFSJ6x9o4voHms57vBCCUERB1efmRTiuEK8Jdl2TA+abVnK9GRRF4s5PtwVzVIJdD49xYufSxg5AslYnHFORJIl1N1ez7ubqN70OVZPm3dtErY6iSviuID2y9Mu7nPco5VySdfqSxyzepo/n2Xhc+YXJ8x0SsWbCoVRFF65UWQTO7QPsfN1GAFVVMluv0tiwQSOVuvK5am8GSYJYTKalRaH6PO2LiuGXbFpNKTuK77kgBMJ3ce0yiYbl+J6L8H18z0Mg8D0Xp5QjXt8VEEIW09ilLMJzsQrpwGO0RJK479lIskKyaTVWYTo4tyBYWB2TRNNKJFmpVMIE3kjfs3HMPInGFUiKhpmfwrUDyRqrmEaPJi/IeH0zpNM+jz1WZlmHSl2dzJ13GlRVSRihKyN/czGQZairVWhqVDDCb137wXNj4XHpBpUQzJNfOhcB84KgfNZe8ux/O5U1yTlrbZrxqM2c17LmvvN9MEWEcGpZEK4q5HGLOUK1jSh6Hk9VUSMxyq6DL1mUJ3oomxBurEetqsGxLXxvirKioxhh5LCP7/vEmmuws1P4fgFz8hyW2kUgh1Qa71pHascyEIJjf/gEVVe145sOU6+dedPfw0UaPJODJsWMS01rUJ5b3WoQS2n0HshRznuM9wZ5PjWtBvEanURdsOscOpGeVWE+F8JjNsx0odDDymw11Xhf+YKSRodPFua1oyjS7K7WsbzzGiYXghU7kmghGd8XqLLEVXfVcXJnmlN7FiZcz0ALBUYjQHbcZmrQxH+TBKz8lD0v7KWF5FmqjMW8ADPwXXHe7y8ZgsAwyLvUtoXRDYWmFVEiCZWTr2ewSh4jp0uYRZf6ZWFiKS3wtiVVTr5uLprIPtNfz73IeREJRGGFgPGeEvkl5tzZGDldnFclpmjyrAFkl72L7sO5WHdTNXpYwfcEmiGz/b56Tu3OzKtYOxeaISNX5sX0sEVm1HxT72N6xJwX9grmhYTwz3/fPdfHu8jn7+eBGa+RoSeRWNqAePllm507bSIRic9+JsqGDdqSx/6fAOF7TPcfRFY0PMfCzI7juSZTZ/bi+x7FyT6EqBgfvofnWkyd2RMQQU4NAD6+64AkIas6vutUEp4XX6SF5zLVuxdJVvAcm3J2FN+1mezehe97qJoReBcq7fmuE3znuShaGBB4joVc0a3yHDsIu12SPtR8pNOC73+/jKpCfb3CunUanZ1XdkP2r7gyUEJhhO8ioeDm0niWiW+WkNTgefMdByeXRlJn6CtkZD2EcB18q4yTmUKLVyHroYAhSpJwzRJOLoOkXJgZoiXDRDtrGfzhXhrvXh9wkbke0Y6at8bgMfMuYz0lGroiVLcYNK+MohsKQyeLlPMu431l8lMOqcYgkbm+I4wsSwyfKC7prroUM8Mp+7OGwQvfHeKF7y7NgbEUfE/MGkBaSEFVJezL4KkJx1UOPzfF8VfT3PzRFlrXxHjHr3Xyvf90ktElvFuuNceNc+i5KR7+0+5FE3jPB9cSs2N7vrCEJEuzxtWVRjHjMNFfJpbSSTWFaFkdRVHl2XDJaHeRUtalrj1MqsmgriMIwQ0vVkp9Ni7ydjjlINnctX2e/sYAOx+6cH6GGXiumKVP0AwFWZHxL1DbZzGEogr7n5qk/3COWz7WSuu6YF78w386QXqJqj/H8plZT/b+ZJzH/3cvzkXyP7lWkMAvSRLaeXbMkiIhqz9/j8ibIVPox/FMPM9aIHFxNkQl96BUEtj2zz9v51Lg2WU85ody3Uqise0unBMz3/nu/I2dZ1+YkKtrLXz/zHxmO4u0Zy1szwfeAmcenhf8Vyr6b7rZ+5eE298W4sQxl6HB+e9zTYf3vj9CXZ3Mz54yOX7s8jzIPy9YU2NY51ABlAaWNjKE51PsPTnvMzs9cRHyGgshVZwcdqYUFAlJoMaMQPLlAnFxBk/RY7S7ROuaGHXtYRo6I7iOz2h3Cd8VlHMuE70lmlfWUdMSpq4jghDMkg1eKaTHzNny7qblkUuirLZK3ixhW6opRKxGZ3ro0qsNRk4Veewve5joK5OdsPnA/7uSZZsT3PfFZTz8p2eYWuTchbRDIeMEYoTLwugVcryLQW7SxrH8gBCuxVjyuFBEIZZ6a3a/pZzLeE+Z6maDurYwDV0RzKLLeG8Z34NiNkhsXn1diuqmEHXtYTzXZ+jElZ0X0yMmjuURCms0di3MhboQlPMuhanAM1TXHiaSVC+q7Pxc9B/K89iXeshP2hTSLvf/1nJW7qjivv9nGY/9Rc+ipIG5CZtyzq2Ej8OounzRBk92wsZ1fXRDobp56XkRjqlEEku/BmKxgOMjpEv4AkpFQTqzMKlUU6GpWUFVYXraJ5NZ+EDGYhL19TK+B8MjHrYdJK7W18loelDxIUmQSslEowDjlMsCZ1q8JUmsihKEwmIxCUUOQgG5nE8uJ86bTxAKQXVKxghL+D4U8oJiyX/Td5AsB4mx8biMqoLrQj7vk82Ky8ofXAoz1xeNSqhqYBjmckF75yKRkKitkXE9GB31FiTtyjLU1QVjlc/PJc2Gw9DQoFDIC6amfcJhiVRKRtcDQ2amvcvIbV4S4bAUhMCMYCEsl4OqIPM8r3FJCq41kQjKoW0nCK3Bmy8hoVAwnuFwwOJtmYJ0RlAuz/+lJMHb7jYoFsoLDB7PhWNHHK77bJThIY0Tx923ZGwWg6bBtTeEuOkWnVBI4vWdNj97ysQyobZW5j3vD9OxTKG3x+ORh8pMLsKz888JJ29iTRZoeecmIu0p2j6wHaMxwcAP9l7wOS7K4LHLHmNnSkgytKyOUtNiUMq6jJ6Z24ENHCuw9e31NHRFaOgMY5seY2eW3qFdCgrTDgNH8tR3hFm+vYraVuOiCAEhWNgGjubZeFsNrWtidG5OBKGDS/TU2mWfUtZF+EHJ8E/+qof3/LvlbL6jlsK0w4//sndB+MYqBUm9K3dU0bomRtvaGEcmppdoYXEUsw7jvSVSTSE6NsSJJNUF5f+SHPCuRJLqFS9LBzALgXGz4ZYaWtZEqW4yyI7bTA5WdqAiqMTbdEctjcuj1LWHMQtBCPRKIjthM3iswLqbqlm5o4pUc2hJL8pSKEw7DJ0ssPq6KpZtjgf3ZHIhFfuFwip5lHMunis48LNJIkmVd/5aJzve2UB+yuHJr/QtSCg2ix69B3N0bIzTvjFO88oo3XsXcg6dD/lpm4n+Mh3r47RviGPElAV8R4oW5OAZMWVBTpGiBKRl998f5tprdBobFSxLcPq0y+OPmzz6mMn09NxkSiRlfue349x4Y4gHHyzzp/8jT6Eg5p3v05+O8rlfjrJnr81/+A85hoY8qqpk/vN/SbBypcoXvpBh/XqN970vzNo1KrIs0dvn8vCPyjz4UJlc7sqtDImExL33Gtx7r8H6dRqRiEQ67bNvn81DPyrz8ss27iKb7/p6mQ98IMy99xh0dKiYpuDQYYeHHy4vFVUCIBqRuPW2EO96p8GmTRqJhEwu57P/gMNDD5V58UUL6wrmySYSEnffZXDffQZr12rEYhKZjM+ePTbf/0GZ3bvteUbk2rUaf/LHScJhid/+nSzPPmvNW4jb2hT+x58mWb1a5X9/ucg3vlHEcWDzZo0/+59VPPMzi+99r8T97w1z2+0hGuoViiXBnj02//i9EjtfX3w8LxWrVqm8971hbrlZp6U14Jrp6/N4/gWLBx8s09fnLTAkJAm2b9f4yIcjXHONTjIpMzHh8cILNo8/YZ43r66jQ+Hd7zK44w6D9nYFTZMYHPR44UWLH/6wTHf3hRkuvg/HjzqMjvz8dRFDRmAgPvm4CQI+9dkovWdcThxzue1tBk3NCv/wdyXe/b4wd7zN4MEflK7oPbtceEWb4UcPUH1NJ34l1WDo4f0Uey7ca3RRBo8QMDlQxip6tK2Po4cVspPBi3UGg8eLuLageUWE+o4IE/1liovw71wOHMtnz4/HWH19irqOMPf9aidPfqWP9LBZycUJ9GRUTUY3ZGpaDcZ7y/OIB30PDr8wxY53NNC4IsIdn2qlnHc580YWx/IrLrMgDKQbMpqhUJh2LijfyHME+56YIFGnc88vd7DjXQ3kp2ye+ebAgvLi/U9NsuWuOho6I9z1mXbKeZehE8UKp1Ag3KhoQb5RTatBbtIhc1ZFm1UKyqxX7qiiaUWUa9/byGsPjlIuuCCCRa2uPcy172m8YuN/LoQflL67js+yzQli1RrjvaV5ybIDR/MIH1rWBIby8KniohVll4NyzmXPT8bp3JKkeXWUt//KMn761T6y43aFtiCo2FM0GT0cjOfI6dI8g8P3BAefmWTL2+qoaw9z12fbsUoeg8cKOHYwL6TKvNDCClpIJj9lL1lefjZcy+f1h0dJ1unc+el2bnigidykzcv/OLwgz2bfE+NsflstyTqdez7XwWN/cYaxnhKOLWb1koK5GVA/pEeteZ6oUtbl6IvTtK2N07Exwfb76tnz4/FZD6KqS7SsjrH9HfUL+ilJcPttIX7rt+K0tSmcOuXyzDMm8YTMpo0av/VbcVasUPnzPy8wVTF6pqd9vvHNImvWqLznPQb79tn85HET1w3Od+MNOh/6YJh8XvDtb5cYqbzwJQlCukRDvcKv/mqMDRs0Jic8XnzJorZWYfMmjd/8zTjV1TJ/89XiPCPqUpFISPzaF2N86MMRrIrBks34NDer3H67wbbtOv/rrwo89FAZ6yxPR1WVxL/9jTjve1+YbM5n1y6bclnQ2any7/5tnMGhxRexaFTik5+M8NnPRBHA0SMuk5M2zc0KN90YYvs2nT//izwPPli+IkZPVZXE538lxoc/HMay4MhRh0zGp71N5W13GezYofOHf5TnySfN2QVt716bBx8q8Ru/Huezn41y4oTLYMU7YRjwsY9G2LFD52fPWjz0UHnWWJLlgBbgqi0aq1YmaG1VOHHS5dixgGjunrtDXLVF47d/O8uLL11+TEySAiPrP/5unE2bNAYHPV59JTjvmjUan/mlKFu3avzBH+Q5etSd97vt2zV+778lWblS5UyPyxv7LYyQxB13hli/XqW5efH8oRUrFH77txPceIPOyKjP6xXjbd06lU9/KsLmTRr/7fdy89pTFNh+jc7Nt4WwLMFjD5fpPbPQCJuBrMBVWzVuuc3ACEvs2WXz/M9M3n1/mL27bVRV4u63G/zT90s0NCo0NinEYhKeB8s6VTQdXnjOYs/rNt4StlQhL3js4cAxoKpQLAhSqcDbuG69ykvPWxw76lJbb3HH2wwMQ+KWO0Lks4IXn7dIJCTe96EIzz5tUlUls36jRjgs0dSssH+fzZM/Md9aA0mSkEMq1lgOJxOEXbWEQbi5ivJQ5oJOcdFq6VODQaJp88oonivY/9QE9lnswdNDZfKTNh2bEsRSGqf2ZC46TPNmEH5AnPb8dwa5/Rda2XpPHU0rIpx4Lc3kQGCpG3GV2laDtvVB2fe3fuvYAqbl4ZNFXvj7Ie771WW0rYvzkd9bxendWQaOBeXdmi6TagrRvDqKU/b5pz86fd6Kl7PhWD6v/tMoidoQN3ygiZs+3EJu0mbnj0Zxz8o1GOku8tTX+nnXb3TSeVWCT/7JWo6/kmb4VGD0hMJKJS8mRkNXhO//t5PzDB7PERx+YZoNt9aw8poUd/9yB3XtYU7vzeI5PjUtYTbfWUuiTic9YlHVEFqsu5eN8d4yVsmjfX0cIWDkdGleGGZywKSYtunckiScUBk5VbziUhe+Jzj83BSta2Lc8IEmdryrgebV0YCledQKeJISGrVtBm3rYnie4Ju/fnSBh6XvcJ6X/nGYez7XTtdVST7xx2s4tSvL0IkCZtFDN2RSjQata6PkJh1+9Cfds3QHbwa77PPiPwyTrA+x4x313PGLreQnbd746cQ8LqmBowWe+foA9/xKB6uvraLmT9dx/LU0o91FXEdgRINQVeuaGMkGnX/8zyfnGTyO6fPGTydYc32KZZsS3Pery2joitLzRhZfQH1HMC9m2LFj1XPhzmXLFD7/+RjNzQpf+UqR7/+gRD4vUBXYuFHjP/2nBO97X5ijRx1+8MMyblBoxL59Dt/+donf+q04v/RLUY4ddzl50qW1VeFzn4uRqpb58peLvPyytSCEk0xK3HC9zl/9VYFHHzMplwWhkMRtt4X43d+J8/GPR9i92+all+3LCgHIMrzrnWE+8IEIY2Mev//7efbtCxaJUEjirrtC/Mavx/k3vx7n1GmXPXvm3CBve5vB299uMDXl8Z//S47XXrPxfUgkZD71qQgf/cjiYdQbb9T59Kej5POCP/7jPC+/YuG6QXvvepfBb/xGnM//SowjR1wOHLj82N3b7jT4xCci9PZ6/Pc/zvHGGw6+F+zwP/LhMF/8YpzPfz7K0aMOZ84Ec9914Yc/LHPVFp3rr9f5xMcj/MWXCpim4LZbQ9x/f5jBIY+vfKWwqKTAxo0a+/c7fPHXMnR3u/h+wND7xV+N8f73h/mlX4qy7w3nsg3W6mqZz38+ytatOg/9qMxf/3WBycmgP42NCp//fJR33GfwK5+L8Tu/m53lQ0omJT75ySirV6s89ZTJn/xpnvHxgAR17VqN3/4PcVpblQX8SfG4xKd+McrNN+k884zFX3ypwMhIYLg0Nir85m/GuP02g099Ksp/+S+52euLxWVqagQ/eazMdTeEeOCDEf76LwsUl7j+ruUqH/pYlOeeMZmY8Hnv+8M4jqAqJbNiVeChW7NOZflKlbY2lVJZcNU2nWhM4h+/W6K9Q+GDH4lw5rTLxPibv1fXrtdQFOjt8ZBliURSng3tZdKCRFJGUWD5CnU2tKWHJDZu0ti7y6auXubd94f55teKHDvq8MCHIoyOeOzZ9dYRKOmpCJ2fugGvZOOW5t51wvXfQoNn2CQ35dC0Mopj+fQfmV9tYha9gK/nnjqELxjtLi3KAXK5MIsez317EKvocctHW2haEaVlTWxO3FdUBIk9weDR/KKVKsKH1x8ZxXV8bvloC43LAxmGs3e9wg9Kr7v3XFxIAaCYdnj66/0kajS23FXHXZ/tIDthc+i5qdkQiecI3nhyAtfyuf0X2mhdG+P6B5o4u8pU+MF1FDPOAmJCgIn+Mo99qYd3/4ZE11VJbvxQMzd9qDlgQ/EEI6eL/OSvell3UzXb71u4o78SGO8vUcwGFXrlXBAuPBvlnMvI6RKrr0vh+4KR0yVs88rPi1LO5amv9VPMONzwgWZa18Zo3xCfPy8q43nmjeyiHjvPEbzy/WEc0+PmD7dQ1xHm6nc1IMlz9Acz8+LwC1MXTb6Wm7R5/H/3Eq/RWHdTDff8Sge5KXue6K5j+bz20AhWyePWj7fQuCLKTR9qXnReTA2bWIsYjyOngvv+ji8uo219nFs/3sJtH28J2KE9EeQX/UUPV7+rYbb0XVXhjtsNNm7UeOkli299uzgvH+ell20eeaTMr/96nHe8I8xPn7KYmgra9jx4+JEyGzdpvPtdYX7xFyL89z/O88EPhrn++mDB+Pu/Ly2aYyFJsHu3w0M/KpNOB+0VCoIf/ajMTTfqvO99Ye64w2DXLhvzMrwg9fUy73yngabBt79d4oUXrNkdcT4veOihMitXqHzmM1He//4IeyrPfTQq8bY7Q8TjEt/9rslzz82FoPJ5j299q8SNN4RYt27+KzUSkXjf/WFSVTLf+Eaep542Z/NjCgXBww+Xuf46nTvvNLjnbuOyDZ5YTOKBB8LousTffqvISy/N7fjzBcEPfljm1ltDbNigcfvtBmfOSjcYGfH5X39doKurive/P8zevTZnejx++ZdjhAyJv/yrAvv3O4sanKoKf//3Jd54Y+77fN7j298uce21Ohs3amy9SrtsL8/27Ro33hCit9flb75SpKdn7h2Sz7t85StF1q/TuOkmnWuv1WflCjo7VW66USeT8fnq14p0d8/9bvdum+99r8TatYkF7a1YofKOd4SZnAzG5sQJd1573/52iS2bNW68QWfNGnXWQC4VfV55yWLvLodySfD5L8aJRqVFDR5JghWrVPJ5nxeesygWBJ1dKtdeH2L/Ppu2doV4XOLwIZeOZSqNjQpPPWmy5SqNIzsddr5qMzqicOMtISKRNy9MqW+Qed8Hw7z0osXYqIemzXABMft/SWLxEO1Zn53pdtn5ikU+J9i2Q2fTVfpbavAAOJkyk692Ux5Kz6ob+BfIwQOXYPBYRY9Tr2dQVAnX8heomNtlj+OvTpOs07FNj/7D+UVjo+W8S8+BHBIS+UvkwDELHi/+Q6AxtOLqKjo2xEnWB/wjZsFjctCk71COvkP5JXM57LLPrkfGOLU7y4rtSTo3J6hqDBEKKziWT3bCYvhkoIq9WILpRF+Z7n1Zhk8VFmWSzk3Y/OR/9eJ7guoWgzXXp+g9kCM/NXeTHMtn/9OT9B3O03VVguXbklQ3G7NSDJkRi4HjBXoP5BbnMxLQdzDPd3/3BOtvqmb59iSxah2z4NJ3KM+h56aY6CsTjgcMx+fj67lUmHmPE69lcMwgl2ng6PyE5HLB5ejL06i6jFUKjOLF8omKGYeeAzk8R1xyKLQw7fDstwc5/PwUq65N0bEhTqxGQ1EkSjmXyQGTvsM5+g7mKaQXf1hmRD1PvJZm5dVVdGyMk6wPoRsKjumRqeQLHX81vWhp/diZEmf25RjpLi1afZIetvjxl3pwbZ9Ytc7aG6oZOl6gmJm7Zrvss/uxMbr3ZVm+LUnXlkSFa0jGKvpMD5sMHMvTeyDPRN/CeSEEnNyZ5u+GTdbfVE3X1iTRKo1izqHnjRyHn59ietiitj2MEVPJjFnEYhLbtmkIIdi92140+XjfGw62LVi7VqWqSp41eAAyGcHXv15kxQqVe+81kBW47VaDvn6PL39lbjd+LhwHjh51FrTnefDyKzbve1+YzZs1ND1gMr5UdHSorFqlMjbms3PnQve/acLzL1h84hNRtm3VqKqSyGQETU0K7e0q2azPG/vtBaGn6Wmf/QfsBQZPR4fCihUqk5M++/Y5C5KBi0XBgQMO994bGJkz6taXilWrVDo6VAYHPQ4dchZcXybjc+iwy44dOhs2BLv8s4/Zv9/hm98s8u//fZwvfjFGb5/Hpk0aDz9c5sEHy0v2LZ0WHDm60BgaGHQ5fMThzjsM1q2/fIPn2mtDhMMSO1+3GRlduGHq7nY5dMjh/e8Pc9VVOs8/b+E4sH69RjQms3evTW/v/N/5Phw77jA66lNbO79icetWnWRSYudOh/7+he2dPOkyNu6zaaNGR4fK3r3BAAnBbD6o7zG34VoMEuiaRIUMGwDXDUSC+3o9brktxMSEz+nDNmvXaTS1KPT2uLgeZDP+7DUgSedvB4gnJD740Qh9PR5PPxl4GhVFkMv5JKuCa08mJYoFH88LzjuzyVJViJzFUeT7c/31PVDe4mJP4fmosRBtH9yOV7RmN4cTL59m8qVTF3SOizZ4AJ78Sh9PfqUPAFmV6NgQY/lVCTRDofdQntceHOWVH4zQ2BUmWR9i423VtK6K0nu4QP+RPMs2xonXaOz8pxFs06eu1WCwRqNlZZRy0aX/cAEhoGVVhOpmg6Mvpxc1JgBiKZVlm2JEojKnXp/m8AtpCmkHVZPYdHsNY71lNt1ajVnyOPz8NMl6nbo2IwirnC7RvDJK36E8+bSDXXL5pz88jWP5hCIym26v4fAL05TzS3sifvo3/fz0b/rPO17jvWW+/e+Pn/cY3xNMDZpMDZrsfmz8vMcuBiGCcOOL3xvmxe8tzoD64j8M8eI/XHwJ/4Xikf+5dJmiY/o8840BnvnG+VVtu/dk+V+fPnjZfXFMn6ETRYZOXHrCvOsIxnrKjPWUefn7iwtVLoVH/7znTY8ZPF7k67+2UJjybHiuYKKvzERf+ZLK7H0/mH/jvUM8953F7/1TX+3nqa8Gc7i5SaajoqOzbZvOv/u3C9+g9fUKuh58nkrN/14IOHrU5WtfK/L7v5/kox+Jksv5fOlLefbvX3olt6xAo2cx70F/v1tpV8YwpMuSjahOydTUyAwNOwwPL/5cT0/5TE/7xBMSLS0KmYxLKhUkfOYqFUrnwnUEI8MLP29sVEilZGQ5YGK+8Yb5BI+SHISDJEkiHpeIRqVFjcwLRVtbkNshy/DhD0dmF8QZyDJs2KAhy0H1XTgszQszzXjpNm3SeOCBMJs36xw54vA3f3P+/KmpKW9RMrx8XjA+7qPrEg31wThcakWaJEFHu4KmQX+fN8sEfDZcFwaHPFw3ODYSkchmBS0tCooMQ4PeovQF09OCXH6hwbN8eSC/0Nys8IUvxBbwtWm6RH1dQGtSXS3PGpDRmMy2q3VOnnTZtkNnesqf119JmvOiCB96e1zedk9gFI6OemzZqrP7dZuJcY9klczwkMdgv8dNt4TwXEE+JwIemouYKpGIxMc+GcUwJL7/96Ugfy4UjNmJYy7XXq9zptvl2htCnD7lYpmCTNqnq0uloVFm0xad9mVzJsPKVSpr1mpMTPgsX6ny2I+ubBHKuZD1gCCz52svUR6Zi7iIi+BKuySD52xIQLxaJ592QTjc+EBj4Fk4UqCxK8LbPtXK64+OM9pTxjE9IgmV6+9vpP9onuVbkwydLJKs1clO2Ki6xMbbqhnvKeNYPtvfXv+mLMyaoaBqMqM9ZVbtSBJJaLz4j8OomsytH23mxOsZRk4HOl6yAmuvr6K62cB1fNbdkKLvcIHr7m/ghX8YZuMt1aRHLHoO5Fm+Lcmaa1O88fTk5Q7RmyJkVNG+7FYmxw+Tnj696DGqFqGl9VriiRY0Pcqp449SyF8etfulQJJkNC2KohqAwLGLuO78iS7LGroeQ5bVQE/JLizQ+HkrIcuweZuOosCet4CivqlFYfM2neefKs8Lz7S0KWzcovPkY1f+wdc0uOsdYV57yWJ6CS/JlYCiSkSjMpoG11+vs3374lQGhYJPoSCWLEzav99haNCjplpmYnIu0XMpCDHDELsQM2MsK8waWpcCSYKQEZCOei6LLpgQLACmKQiH53S6NC3QfCqX/XkstDPwRUDRfy6MkISmScTiEu+4L4y3xLtsctIjnxezgo2Xikg4KEGvrZV5z7vDS3LbTE56lIoCeZFdeaEg2Pm6zX33GcRiEnv32gwtYRzOYCaP61x4HthW4K3QdQlFuXSDR1WDc0iSRNkUSybnlssC3w/un1LJQw4b0qyMwmLt27bAXcQej0WDAVq9WqW9XV0yfD056eF5glhcxnEEJ084ZDOCz34+iiRJPPiDEoW8YNNmjXe+N8zKVSodnSorV6v843dLHD/q8OhDJd75njB6CI4ccnj2aRMJ6D7t0t/vMT7h43gSZ44GHZ0YD+aMHpIIR2VGhhfSCZyNmjqZbTs0PA9+83cSeJ5g56s2D/9TmWefNnngwxG+8MUYw8MeTz0ReMaef9Zi7Xqdf/fbCQb6XV58zpx9bsZHPW69M0Rtrczhg0Fo7a2E73hIikzHx6/FzZuzIa3pXT1M7XzzDSZcAYPH8wQj3SU6NsSIJFSMqEJdW5i+I0FIIzflsO+pydnQQU1zCMf22ffTSWpbw5zYmaF5RYRYtcaRF6bZeEsNdR1hCmmH+o4wOx8eO68Vm5+ymRw0SdbryIpEw7JwoGItglDRsVcznNkf6NpoFQbd3kN58lMO629KcfjFaW7/eDO26TNwtMDKHUlGz5RYd32K7n1Z3Mtwn18oZFklGq0noy3NHeO5JqMj+ygVJ1i55t0oyluTfHw+SJJMXcMmGho3V0QIVcqlCfrOPEu5PAUExk5z69XU1m8ABJ7nMNT/KunpU4ifo9FTlZJZuUYjFpfp6XYZHXLZtE0nEZfp63U5fcLlqh06iWSwuL/wjElHl0pbh0qxIDiwz6KhSaG6RiGZlDlx1KFU8tm4Rae+SSFZJSOfszgZYYnV6zVMU5DN+Lyx22bNeo3mVoVM2ufQfpvWdpW2DoVYXGb3a0Hp77qNGgg4fNDBdQQr1wSif9mMz+kTDus26tTUyyxfqbFn51uj8TMD3xOYZsAt8u2/K7F3z9IvMdeF090LVx1Ng/e822D5coVSyaepUeaDHwySYIvFxZ8nWQ6SeBfDDM+K73FZ5IJCgGUG7yxFCYwRZ5HqOlUN+uJ5ArPCseK6IvidKs3mPJwNSWJWj+hs2I7AdQVDgz5f+ZviecuRs1lBPn95z4hlBYZAd7fL175eZHpq6fNNTvqLemVaWhTe//4w4bBEqeRz990GT/7U5MUXl54Lekha1HhSlOA7IcC2WdJIuRC4bnD/hRAYRsCd5C5yvrAhIcsS5fKcUWRVCFpD+uJhH0Vh0f6blcKLZ5+zeOQRM6iSXAJnej02XW1gW4K/+rMgSqEowbxzPUDAoUMOx47Ot6xmjMVnnrJ47mcWksRsOAngz/8kjxDQsVzjxBnBT34QbKi+8TdFfAFdq3XWbQ3xJ3+QwzvPpmKw3+NXPp2e99lMG+NjPl/5q8KsB25m3CYnfY6eFjz3eJGxYXf2N+0dCiMjPl/96yAR++z+vlVwizZDD72BVImdzdwJe+rC+dwu2+CpbTG493Pt9B8tMDlQxjb9WVp8gPyUE1TrnDVPXNvHcwS+J7DLgQqrLENuyqb3cJ51N6TITdqkR615Je+L4aYPNhGv1ujelyM/bVNVp88SETqWH8gLzCZjCfyKlIVXkVrwHIFAwnMFp/bmuO1jzXRsiFPTYvDKgxcfQrgcSJKEpkWQZBXfd3GdMjOdF8LHMjMUZQ1fLD2rFSWEouqAFGgducH2WNOieJ6F77vBMYoeeF4QqGoYITw87/wWeqDZFGZ89ACF/AiaHmPZ8jtoaN5Kb/fTAFSlOqlr2Mxg/8sUC2PU1q2ho+s2SqUJzPI0sqKjyBqOU5q9trM/kyQJVQ3jeRaKoi86FhcCPRTs7iQJbr7d4JEfBqzOqiZx9zvCnD6RJ5/zWbNeQ1XnXMyuK7j1bQbDg25gaNTKHHrDxnEFm7fpNLco5HKC5pbFF71IVGJ60ufmOwy6T7mz57zjnjADvS6loo+mqazdoPHGbruykMLyVRohQ+L0CZdb7zJ44WmTfM6nuVXl6ht09r5uE4m+9RpDZVMwOOjR2akwMe7x9DMXZ2DJMtxwg85HPhJhYsLn239X4kMfDPPBD0bYf8DhiScWl8nQ9YCUUJIWegra2oJt+sTk4t6Vi8F02mNqyicWl2lsUsifWvgsVaVkqqtl+vpcRkaDzmazglwuUJ2urVm4MqpKUFp/LibGPbJZgabBsWPOvKqvtwJDwx7FYuBR2b/fmZdkeyEIheCTn4iwbavOU0+ZdHd7fPrTEX7lczFOn8owPLL4qlZTLRNdJGE2FpOor5OxbcH4hHdZi6IQ0Nfv4jgh2loVQoaEe44BrShB+ElVYWjImyUFHBkN2m5qmgnHzv9dMhmQKp6L3r7gd7YFL75onTespyiwbE2ITdsN2js1Du+zKJV86htVDu4xufbWMG/sNLn+9gieG+jfvf5CmetuC2NEgnDYU48USFUrbLnGAAlefTaQ3rj21gjxROA9miF+nzFKFBk6V+nc/7EEE2Mu+1832XK1wcs/K7HjxjADZxxal2kkUzLxKoWdz5do79JoW6YhK7D3NZOJUY/rbw8TicocO2DRe9rhlrsjxBIyNfVK0O4ixqXrXl7O2cVAuB5u2SaxuhE1FgruoIDcMR976sJSFy47zShRUb4+9mqasd4y6jm7nzerYBFnTTwh4PiraZpXRtl8Ry0nd2ff9AHp2BCnZ3+e0/uy+K5A0c4uYyHwNZ/T4lIY7S5Ryrpsu6eO3JR9wSXoVwSSTCLZwfLV72Dthg+yZt37SVUv57xsZucgGm2ga+U9rFn3AGvWf4DlK+8lFm9GljWWr7qPVM1KJEmmqfVqNl71C4QjNciyxrLld1Y8Mm8GwejQbsbGDlAsjpFJn6FYGCMSqQMCT1Uy1YlZniI9dZJScYyJ8aNIskosFvAA1datY+WadxMKzVVE1NVvYOXa96DrMYxwNavX3U9z67VnjcX7SFYtu6ixsCxB90mXE0cdNA1a21U2btFJ1cg0NClIUuAxMMuCJx4po6gSm7fp1DcqNLUEL1OA3jMuh/Y75DI+iYTMQL/H6RMO9iILrxAwPOBx8A2bYsGnrl5myzadmrrgnFoo2HWGIzKP/LDE5LjH6rUanctV6uoVkikZJJgc8zly0GGgzyOekMjnBEcO2uSyb72HLJ8X7N1nI8sS118fIlV1cUZWe5vC5345RnW1zPe/X+I73ynyzb8tYhjwuV+O0tW1ONeJpsG6tQuFPxUFrrs2yHs5dNC5bPmI/n6PEydc6utkrt6hz4Y8ZhAKwQ03hDAMOHLEmSVXHBnxGBwMiBI3btLQz9FajSckNm5cGP7r6fU4c8alvl5hxw59we+uNE6ccBkYcOnoUNmyWVtwfeeDosA9dxu85z1h+gdcvvyVIt/+uyLPPmuxdavGL/xilOgSRnciIbF+g7bAe9LaorB2rUYu53Ps2OWvjDt32hRLgh1X6zQ0LFy+OjsV1q9XyecFBw/NJYkfOxYohK9erdLaMn9QJCmoxmpoWDhYe/fa5POCq67SWLbszf0DsgK9p2wO7Da56lqD+iaFhuYgx6elQ0MPSbS0q/SfcXjhySICaF+usfP5EsKHzpU6N94VDegOkjIbtobYsNVgbMhl/y5zwfoaXADkMj5PP1qgc6VOQ4tKS0eQp9XYqhJNyNQ3qzgOPPlQgelJj47lGv09DmdOOKxap7Nxe4i2To1SwWfb9Qar1uvEkzLPP1HEXSR/dnzU59gR57I1KC8GWiJM2we2k9reQf3ta4i2V1N74wq0xNJM8ufisg2e6eEg0fauT7dy4wON5Ked2RLwGS/K2UaP8IOE0pmQk++B6/izAzc9YpEes4gklAWVPovhxOsZtt5by72/3E68Riczbs0mc9mmv8DecW2B5wbepRmCQcf0ZkUWj72apm1djFO7s1ecP+h8kGWZaKyB8dGD9HY/jW3nae+8bZ5hcD4oikHbslsQQtDX8yx9Z55BllXal92CpkXwPJtwpBZFNYhEapFkhWisAUlWMMIpHPvC3IK+PxesV7Uwuh6bC2cpOuFwDeXSVHAc4DolLDNLJFpfuU4VVQsjnVVfLSsamhquCEYqhIwkqeoVjI8coLf7GRynTEfnbeh69ILH07EFliUquzNBKCxRVS3j+zA96aOH4L0fitDUorD9uhCxmER1TbD7S0/5OHYQipipxnFdGOx32bxV58ZbDRxnoSfC86BcCRHYdpCPkaqVUdXA6yN8eNu9YTZu0di8TaexWSFRJRONypRLPvlc0N+z8wxGh4OkxXc/ECVUCQ28lXAcePppi2PHHK67TucLX4jR3q4QDksYRpD4WFsrc8vNOpvPWVBDIfj4JyJcfbXOSy9Z/OCHQY7TT35i8vjjJmvWqHzmMzGqljCirr5a513vMkgmJEKhoBT87rtC3HpriExG8OyzC9mIJSnwKqkqs4LCkjwXojh3AR4d9Xn0scDL9MlPRrh6h044HLQXi0ncfbfBe95tMJ0W/NM/lWfHO5cTvPCChWkK3nd/mGuu0TGMGbkBifvvD7N69cIFMZ8XPPhQmULB5+Mfj3D//WFSKYlwOCD0i0Yl2loV7r3HoKXl8stcMhnBPz1YxvcFn/lMlHvvNUgmg3tnGBCLSixbFrR3boLuiuUqX/hCDMOQ+Na3Shw86DAy4vOVrxQZHfX48Ici3HpraNHQD8BHPhxhwwZtdlwaGmQ+9OEIHR0Kx4+7sxVMZ0Ou3CtVDXJzABR16fu3e7fDq69YrFyh8qlPRWlslAmFgvZaWhR+8RejrFypsXu3zatn5ZScPu2yZ49NTY3ML34qQnPT3O9WrVT5wANhEomF8/LYMZcnnjRpbFT4t78RY8sWjWg0GM9wWCKRkNi8SeP224LqsZnwlesKJDmQkjDCMpFYwHUDgSTF2LBHsSAQviCb9smmfYpFH02X0NRgDHpPO/ScDMbM8wSuI5bMyfJ9MRtu870gmTockahKKZWwmmB82KWQ8/HcikTMpEch5yPJoFVCtYW8z77XTDw3CAE69uKenYMHHB76Yfm8Mh5XGkpER1ZlBr6/h/yJUbq/+hLjPztGqDZ2wee47JBWdtzm0b/sJRxXcUw/MF7sIIP85K4MvQfz8wjoMhM2j3+ln2LG5adfG6Bc9BjvLSFEYAwJPyg3P7Ezu2TJ8Nl4/eExjr40HcTnS0GVx4yh8uCfnJl3DtcRvP7oOJ4nEJ5g6ESBcsHj8S/3z5YWl/Iu6VGL05fAu3M5EL5PeuoU05NBNZfve6xc/U7iyVas8TfvSzzRQjRWz/Dgrtm3RLk0RV3DRoxINeXSBEa4Bl2PoagGhdwQkUgdpeIEEhLl8sVJWkiSTE3tavRQkv7eF2Y/U1Qdz7NnjVwhPHzPRlUv3Ar3fY/pqVNMT52ofCJYvuo+YvGWsz473+9h367gZWfbgkcfLGGWBYN9gfSH6wUu6u9+vYAvAkMlm/b5wXeKaBo883iZ9LTP5IQ/r1T06KEgEVci8CCZ52joDPW7PDERzL3HHixRKgm+9y0PRYHnflomnfZ59qcmLz9n4ougpHTqaZNYbE6nyrYFTzzszXqQJid8vv93RVQtMLpymbfey9Pd7fKXf1XgN/9dnI99LMIddxr09LiYZUEiIdHcHFQe/e//XeDo0aD0WVHg3nsN3vPuMAMDHl/7epHxCgFaJiP46leLrF6t8c53GBw8aPODH8wvcS6VAtmKX/p0lLfdadDb51JbK7Nju04kIvHd75bYs3c+6eCyZQpr1qjE4zLJpMT27TqSBCtXqPzCJyMUioJiUdDX53L4cED9LwT8+Mdlli9X+NAHI/zZnyXZv99hOu3T0qywebOG78NXvlxgzzkL9E8eN9lxtc699xj8yR8n2bPHoVDw6exUqauX2fm6ze23L8yte/55i69+rcgvfTrK7/5Ogo99LMLQkIfwoaZWpqkxWJR+7d9kGBq6/Pv7xBMmyzpUPvjBCH/w+wl6e73ZEu76OoWmJplSSfD5L2RmaQJiMYnPfDYg5nvoR2UeeaQ8m2R+6LDDt75V4nd+J87nfjnKiRMOp0+fQ9bZ52EYEn/1l1UcOhSMy5o1GuvWqYyO+nz9G8V51XWqCtu2aTQ0KJWwl0JtrYymBUZuS4tCsSDI5nwOHXIYGwv6mU77fPkrRaprZN53f5irtmgcPeYifMH69Rpdy1WOH3f48pcL86RP0mmfv/1Wkc5OlXfcZ7C8S+XYMRdNg/UbNKYmfU53uwvCkvl8MHerUzI33KCzbn2KM90u02mfsCHR1BT0e98+mzcOOEyNe6zdHOLqm8Ic3G0y2OeyZmOIW++NMjbs4tiC0WF3NnfMdWFsyMV1BdPjHlPjLi/81GPLNQaNLSrdx22OH7S47rYwvg/Dfe4C+aNSwadU9HnHB+MM9jr0nLJZtV7nnvtj2JYIdM7GPQqFimaYpDI5FoTXZVlicszjzAmbaFymqVWlmPc5dcxl5eYQd75bZmps8cq280FSVMT5EoogYE7WQ/iOfUEJQMLzA6FQKeCXiy2vC9JAqi98I3zZBo8QUMy48/hDZmCV/FmRzxn4rpjloMlPB/+fEQjWDZnGFRGaV0R47rsL6fYXg236TA0tHnrKniv6KJjHtmxXDLH8lIOiSiTqVDbfXkvPgTyZRTh33koIfEwzM/u3ZWXxfIdQKHlBvw+Hq9H1OPWNmxFnPRHF4hieZ1MsTlCV6iIcqUFCIpvtJxZvIRqtx/NsrLPavhAkU500texgZGgXhXylZFsECYXSvG1ZkBxzMQnLQvhY1lx/TDOD73uEjAsbC5jztADkKmKJE2Pz+zA2Ov/vTHr+3+e6ch0HJs/DYuo4zL7IZtpMn5M0mp6e/7dtCUrn5CHkz3ITC7HwN281fB+efdZifMzngQ8EWlo33hAIDpZKQY7Pc89b7N03x/OyvEvlC5+PEYtJfPkrRfbunc/JcvSYyzf/tsjv/16CX/p0wCp8dpm6bcM/PVgmFJK4/70GD7w/jCRJ9Pe7/O3flvnOd0sLtLTe/e4wv/5vYguSiDdv1tm8eS529NiPy/zqr2ZmDaxcTvClLxXo7fF417sMbrkl2J1nMj4HDwXaVk8+aS7wJk1M+PzRH+UZGfG4622BTpVpCo4ccfjrvy4yPe2zfdvCmFWhIPjmN4ucOePynneH2XKVxto1gXcsk/Hp7fXYtctmYODKeJTTacGX/jIgybvvPoONmzQ2btSQ5YAvqPuMyysv20xUjHNFgXe+0+Dt9xp0d7t84xvFeQKjrguPPFrm6qt17rrL4DOfifGHf5ibd0w67fOlLxW4+26Dm27Sqa9oae183eY73wkIHs9GLCbxX/9LctEw4Ec/OreAZbM+//H/zfLQQ4ErQQh44w2H3/3dHB/+UITbbgvx3v+Pvf8Okyu7zrvR3z65cuqcGzljECZnznBIDoekSEuiJEqWZUXbkm3J9nd9/fiz9Pg+9v0sB9lXVg62ZVGkRFFiEDnDyTlhAjDIaKTOuXI6+f5xqqu7gQ6FGZAWJb7Pg+lBo6rOObv2Xnvttd71ru8LATAx4fLlL9f4kz+pcu7c6v3I8+Cllyx++VcK/N0fi3DkiBq0MVnwePFFkz/8wwqf+1yYxx4LrXqf78PIiMO/+TcFPv2ZEA99yGDffpV4LCC8z84Gc+ZbT5pUyh7vvl7n3ddXhz0+/zurD6xPfXWZb1IqeDz99eDvrz2/zFe9eHb1/nP14vqH/4mrDl/8veKq333jS6sj9mOXlt8vdw3yyrOXmie5pc/+2heWNfWEpvHN59JYczM4peXPlsMRPMfG36gcDDD6BqhPTeDbG7xOktB7+nAKOezs4vKvdQOEwKuv5u86ZZP8u+O4dYfq6CLDP3E3nu0w/qWb2DxUSLDn1ihdAxqVgssbTxW+LWF1WRXsfzDDnrtTnH45d52C87cb7YMhHviRbupll2PfuHEdnA8OgSQtfx1CSAjEKudlI3i+g2kWuTzyBPX6Cia+7+M4dcKRdhASsXgf9XqOQn6UVHob8eRgw6FoldwoSCQH6R+4h4W5M8zNnMD3g3v0PAfLLKFqUYSQ8H03SFepEQrm1aUbWvqYJmTp2k1CIEnLhjAYC27gHr+HDwrXhRPv2Vy86JBpCzpuy3Kw+VUqQVfqcnm5C/bklMsv/lIe14XxcXfNEvSvf73GqVM2QgSE0pWQpCBq9md/VuVb36oRjwffebniMzvrrtlj6gtfqPLMM/VNxdYKBf+6+ykWff7kC1WefKpOKikhK4HTlcsFGjzrHTgnJlz+y38p88d/XCUSDnoZ5fIeCwseui74wc8urlmJVq/Dt75l8sYbFqlUoCckRHDNcjm45s1sHlqp+PzlV2o8/4JJKiWaFXCW6VMs+eRyXpPf4nlBFOrUyUWKJf+67wYCnZpf/pUiv/GbZapV/7rqLk0XjFx0eOPNIu3tEiFD4LiwuOixuOhdt2eUSj4//wt5Qqv9i+vguqypl3T+vMOv/scS/+N/Vpq8okrFZ2HBW7cS0PPghRcsTp50yGSC6sx6PdBVKhZ9fv2/l/njz1fXfP7JKY/f+Z0KX/5yMDdVNfi8Ws2nUAjWw7e7SumDQmvvRO/qQU2kwfdRk2nMmSmURAIhydSnJzG6evAcB3NqAvCRDANFlohs3Yk5N4OWaQd8amNX0do7kVSN6ugl3IZTpKYyGL0DqKk0CAk1ncGam0bSdORIlNrEGHpbBwhBfXIM33WRQ2G8qEVkxx7s7AJyKIwci1O7PIISTyJHY9RGL+MUciy8egnf9Zh7cYTi+Vl8x6U+U9zwuVdiU4dHkgWZLpXjL5cwq9dP3JsF1/Z5+4l53vnW/HdSsqWJmUtV/vTfXbphMaebBSEkorGehqPgEYl0Iis6lUprztdSlCUcaadUDCZr8Lkyvu/i2DU8zyYS6WBx/hyWVcZ1LWLxPman32n5PmPxXgaHP0Qud4mpiTfwvOWTg+talEuTtHXsQ1FDWKaNYaTQjQTlcnB/jl1DUQwUJQTkkCSFWLx31TUkSSYW62F+9r1gLKJdSLJCrdJ6V9zv4eagUvWprKEwe93rKj6nTm3skNbrASdiTTSq5GwbJie9NVM7kqJhZLqoLUzhuw5zc14zbfZ+4Lown9Moy71UZ8fw3dZItdWqf51a79LvRxe7cM0asHjdv/s+FGth6kqK2pWpm6ZNpUYSqJEE1YWJVakBz1tyODZ+v+8HbSWmGxVYka5hKMzj1FZHCTYa76XqulLJp7SGUKusSqQGIhRnalgVB9cNeDWrniOskOqPMn8h35INrlZ9Rkc3npvxnjC+61OarTWfdckJW0Ln7iSVepGZGY+ZmY0juCvH6bsKQkJr66A2egX1lgx6Vy9OMY+SSOLbFr7kYvT0YS3Oo8TiKIkEvucFaSdVwymXUNNtOOUSTiGHUBSUWBy3VkWJxJoOj9bRRX1qHDkaw+jpx84vosRTOOUiwjTR2ztxq0FES2vrwG+EiCXdwC2XUFMZ7FwWp1zCcxy0tg6cchElkcQp5FAiOslD/eD5LLx6Cb0thhzRcIqtkYk2dXh8z6de9Tj6YJzFWZu3ny2+P4dASA1PYoM3b+BsyIqO5znLEQ8hoaghfM9tll63dBsNh2LNy28yj4WQkWQF11k+ikmKhiRruFb1A+vMhCPtDG/7CI5dI5XZRqk4QaXhKGhajGi8JyAeyxrJ9FYURadaXaBWXaRamWd+9hQ9fbcRDmew7SqqFsN16kyMvYzt1HDsKvHEIJXKLJ5rYVkVUpntVFt0JDQ9zuCWh1C1gCTW1X0YAMc1yWUvYltlsosjpDLbGd76CNXKHInkEIXcFarlwHErl2dwXZOBoQcoFSfQjQS6EQ8W1/JIE0v0MbztERy7Tjqzg0J+jEpl9n2PrRCw7d5Obv+R4SAH7MM7Xxrl7DM3pqC8GSRZcOQHBtn5YFCVVi87vP6/LjHxXm6Td64NIWD/fgXfh5MnlzeIvj6Jjz1q8PWv1ZmZ8chkJHp6JM6cCTYTSQq6L5dL/g2XJq9EIiG4806NJ55YnvOGAY99wmB21uPVV4L2DIcPq5w7Z1NtdLhIZwRHj2g8+eTNC1v4notTq1wzVz4YFCNKYngf9ewM7hoOj2xE0GIpagutOSjR3m2Y+Tms4tpehu86uPUKH0Rc8FpoiTYiXUPUszN43vUpBDWaRNZC1LOtzfX44G7yl+3rHJ4PAjUkIykS+MFWoEfV4O9ArWAhyQIjpgZtDCSBqkoNGREfRZdxTBctElSBLRWaSLLArrmoYQXP9nDt1d+PrEmohoxZCr5XNaygGkGFplm2cW0fPRbchxACWZWQNQmr4qBHFayqixZRAmK8LGFWbGRVwq46yJqEkILrrwUhwcFP9rPvY8Fhzq67vPmFK1x5/eYK2cqq4J6f2k7/LUEvvErW5KXfHWHhyjXfne/jVMqEhrbimSZOqYCk65gzU0i6gZbpwJqbRm/vwsfHrVbQ2jpxdQMkCSUWxymXccsltPZOrIU5/IZSo1NejrA4pSJG/xD4HnYuhxyOYM5MgRAoyTTW3DRKIglCws4uoHd249sWsm2jptK41SputYLe2YVvmbi1CkJWcPI55LBGzycOEOpPIxsq2bdGie/pBt9n7rnNuZ3QCoenUe3kuj6qJpoaNzeKSKIbq17CrrceflqCJKuk+w5Qzo5RKwabnqzotA8ewXXqzF15s+XPiaT6KC1cueF7ADBibcQyg6uuF0n2kuzaxfzVt6iX318EwnVMFubOUMhfIZEcxDDSZBcuMDdzAsepI0kKoXCGjo4D+HhkF84TCqUwjCS57EVc18K2ykxNvE61Ok8iOUgo3IZtVSgWxvE8F3DILV7EcSzqtRy+75HPXUKWNarVzRehEBKKrGPWC7hOnXA4AwiEkLGsEtXKHJ5rU6/luHrxKdo692GEUuRyl5ifPdlUY67XclweeYK29j2EI+2US1MszJ0mnhzEdS1kxcDzbOZnTyHJKoaeZGH+LHOzJzbVCdr4ASDRZbD17qBazPd8Lr1y81OXQoK2LVG23hVcp5ozOfn1iTVfq+lBZYymC/ChVPKomz6zMx5DQzKFgs/AYEDMnZx0GwRdweioy/S0h2MH+jWSFLRdWDosdHRIDAzI7Nuvcv6cw86dCvG44OJFp9mYE4I+T/G4QFYCPkK50TYhnZYwLZ+uTolUWmJ4i0Jnl01fb9BN+soVh6kpj3g8SMtkMhK6IfA80LSg+3QmIxgckunskhrtGTxGr7rvW3hOUjVCbX0A2JUCvuthpLsRioIajmOXctSyM4Tbe6llZ/Adh1BbD2ZxESPVEWgwhSLUc4EzokaThDI9CEVFAEKSMNLdaPE0nm1SnZ9ACInU9kPoiTbK0YtUZ8ewa2X0ZDt6PI1Tr1JbCNp1hNp6kTUDJRTFzK09r2Q9TKi9F9esQ7kAAkLtfQhE8L78PGZxgXDHANXZUYSiYiQ7sEpZ9FQngoDkWZufxKmX0RPtaPEMWjQZzD1FIZzpQgnFcOoV6guTSHqY9M5bkVSNyvRlytNX8B0bI9ODGo5hl/PUsjNIskK4ox+EhKTefFHTjl1JttzVybt/dhmpInH0c9swSzaRNoMTf3EFz/HYcncX0Q6DwmSFvsNtWBWH4kyVoTs7GXtjjn2fGqQwWaWyUCc3XqZ7X5pTXxtl90f7GH1jnsLkai2WaLvBrkf6GH9ngVrBYufDvSR7w3iuz9z5AuPvLjBwtI2hOzp4/Q/Po8c0uvakOP2NMfZ+YpDzT02y75OD1IsWnu0x9tY8w3d2cv6ZSXr2p7FrLmPH1rb5QgjSA5GmHTDLNmefvrmHKwAhCbp2JZrXKUxXORa7usYrfeoTo4HzEXQ+BlnGd1yEJFGfHMd3HYSsAD6+62LNzy07+ZIErofveVjZeXzHwS3n8T0fz1y2y+bMJNZC8D7f8xCyjO+6CCEw56bxHQfRKO30XRensIhnO8H9SDJ4Lr7rYucX8R0Ha2EeJAnfsdE7YujtMSb/4h16P3VL0AjadAgPplserxY4PIJwXObtZ4vsvyvoOn2j/o4eSdO17W6sepH87AUq2QlSPXsa/+qTnThFvH0LoXgHZjVPafEq0fQApYWrhGKBxouihUn37sdpGyY/ewGzkqW0eJVQvFHuLGskOrejhRLUirMU5y+tugdJVkl17yYzcAgj2k528iSheAdaKImqhSjMXcRzHZKdO0BIFBcuBZu8GqJamCbWvgXXrhNO9NC59S7Mao789Fmq+WnCia4mUTcU7ySWGcL3PXLTZ3HMjU9JQsjYTo2JsZcQQqJUnGz8PiD6SpKCpsWp13IBQbg8g+taqGoISVKw7SqJ5BB1SaFWyzUrvTQtiu/7WFa5Ue4tmJ87zeLCOaLRHiyrRHbhPNmF8yxxZgIujmhee+n/Pc9FUcI4Tp256Xeo1wsN0UIwjASmWcQwksTj/eRyl6hWF4LKLd8nFEpjW5XGNWR836NcmqJWXSAeHyCbvQBAPhf04dIaZfhmPc/C/MZ9pr7bEY9J3H2PRjIpUch7yIpgesrl6adNPvaowfi4iySC181rHo9+3OD0KZuJicBxsFeQqjs7JQYHFUbHXO6+R8dzfWIxQV+/xJ69CnOzHgMDMl/+8nI09LbbVJIpCUUWJJKCsTGXF1+0uPXWQMMjmRTMznooMgFp2RCcfC841Vmmj+8Fc16S4M47NUYuOLS1Sxw5qpJd9IjFJB54QMes+9xyi8rj36x/gHSAQAlFiA/spp6bxfU80rtuxbNN6rk50nvuYO74c6R338HsW0/ieGVSO46QPfsGHbc8SGk8mGeRrmHmTrxAZs8d2OUCkqIi64EkghqJo4SiaB0DKEaU0uQFZM1AUrTAkxUCI9VBcssB7EqBaO92JEVDCEG0dxu1xWm0aIqqtI74jQA90YYeb8PMzeL7Hu0H7qM6O4Znm0R7tjJ7/Dna9t3N2OwoihEhteMI+Yvv0nn4IfIXT6CGoxipTgpXTpHZeyf1hSm0WArwEZKCGkmi6GFifTvIeR52pYCshxrKmgEvMNyzlXB7H069QrRvO/65Y4Qy3WixFGZ+HjWSuKbw4INj7lyeju0JhLysdHzm8XG23ttFtM1g/O0FRp6fZt9jA8vRFjVQM9dCMkIWuJbHhWcmqeUtFF2i71CG9h0JhCQoTl/fPLcwWWV+pNjUZlM0ifG3FzDLNt370rimy4VnpkgNRBFCIMkCxQi4Y1pYQUiB1MHEOwssXg44pfWiRduWOJGMwdU3/k9wPT8APA/fWhFxbZw+VvJEfd9CqMGz+66NUGRwlxykhgyz7yJkgdGfwi3VMecc/CXJa8/Dd6zgffjgOQhZBI6V8Bv/7yBUGUmVCG/JUJ/I4hRr+NZyJHqJFO3jQfP2lvifAiSBZCjoHTGccutR5E0dHtf1uXq6xq4jEWbHrfdFzLJrRerlBSr5Kar5KYQkE050k508iVnJoYXiRFK9LIyfIN2zB8/pIRzvpJKbRI+k8T0HSZKp5CYRkkQsM4RVXc18D8U7iLUNUc6Ok+jYRrU4g2Mue/ye61DJTxPLDJGfPoPrmBiRNJKskp06g+daJLt2YZsVHKtCsmM7ZjWPrIWolRcIx7uo5CbwHIvc1Ck6hm+nkh3HW1F6Jyka6d59WNUCeiRFNNVLfuYC67mIQsikUlvQtBiWXUFRjMDR8P3AmXFq1GtZIpEuqtU5YrFejFCacmkKTYvhuhaWVcb3XGRZQ9djZDK7qNWyqFoEWdYo5K8SjrSjKCGqlXl0PYFhJMhml7vLGkaCdHondTOPImsgZHzPRohAqrhcmiQUymCaRXQ9QSTShWkVqVYWiMV6sazzOI5JOKwhSTLJ5DCaFqNcnqGtfTeLixfwfZd4vD+IELkWuh6/oVL1v6ko5H0cx2N2xmNwKGhUqKpBO4VoVHDsTZtaLdDYeO01i4MHVKam3FWOg+cFJOCOThldE0TC8NprNkKC/gGZjg6Jet1fVaYLQXn+UsPLcDgwBbIURI0ScYmJiaCcu6db4s1jNvfdpzE0pFxXkjw/v8yJyKQlxsddLl9y2LVbYds2mYV5j2qNNYnMluVz5oyN58Ps7PrhH882qc6OEene0vydkGRKExeoTF8h1NaLaizpcTR2VLHUksKhcOUkCEHnoQ+hx9Oo4Rizbz0VRGtSHUiK2vipoUYSeLaJe6lKdWES17Yojp7B91wi3cNEerZQm59EUjVkPYQWT1NdmKBw+VQQTVpnvbv1KtW5cdRGRGbpyyuOnsat1wjd2o2iX8PibXSYdOtVCpffQ0tkSO84gp5oA98ne+FtYv07iXQOIOsh9GQ7+D5aPIMSilCdG6OencH3XIpXTyMkmWjXEEa6G6u0iCQrKKEI4Y5+sufforYwFYxxi6faQiHok1Yoeuv2JgNI9ESIthskeyMsXi1h1xw818NzvGY37iX4vo9Td0n2RVDDClo4KGBw6i6uFcwzx/KYPVtgz8f6Ofut8WZfpZWIZHQSPWHsuoMR1wLJFDOQAwhkM1Y7dVbVIZzU6dyVJJIJbJPneliV5Yk7/vYiBz4zxMKlIpX576AIzXcIWnuc+IEBamMLIASh/jSVi7PIukp4SzvFUxPEdvVg5SrIYR11eyd2oUbh7Su4VQskQWRbJ0Z3kurlefSeJEKRqIzMEtnSjhzWqVyaI35wgOrFWUJ9aUK9KczZAoV3Rze8N7tQpzqWpeexA0SG2xj68TuRVJmxP2ktwwObODyyIoilZPSwRDHv0jOkceF45YY5PJ7n4LoWjl3DtevIagjXrmNWsjhWFUUL4fs+dr2I77lIsoIQcjPC4ljVYBFYVSRZRtUiKxSpGqdMWUXRwgghKC1eXUMDwMd16nieg70i6lKvZLHrRSRJQZIVrFoR26oiKWpA2JIUJElGUZcWgI1VK4HvIyQZmpVDIrhfLYxr16mV5qlXsmxkORTFCJSmhSAS6SCXu0QolMEwEszPnyGZ3NJoEOojhETdLFCrLhAOt1OpzGE0yrSXFq+qRrCsMroexzSLVO15fN9H0+JYVpF4vI9CYRzfd1he7AJFDWNZJSKRDsx6gVJxgu7uw+TzV7DtGrqRwjRLKIqB5znkcpeJJ/rxPDuoxJKkxnP6q55JkhTqtRyl4gSdnQcDXpEaRlEMCoVRUqlta4zKJjyvv2HwfR/PC3R4sose/QMyH37EQFGCrtn33KsRjQrOnXUwQkGgoatbpm7Cnr0q9VogkHj4iMa+fSpXLjsUij733qeTTkuMjDjUqkHp+3UET78hRO7TbMb44IM6Xd0Sp085bN2mkExJhEKB2KDvQ2eXRFe3xKEjKulU4NwgYM8ehYV5jYkJlyNHA32VatVnbMwlZAimp901q2eKRZ//+J9a5IqsjDo0/tc1l8qVvWDe+R6yEcbHQw3Hghd5Lq5VR9YMfN8PTrRCQtZDQQRHVlGjKYxUF9OvfZ307tubYXc8D0lWWCJ+ebZJdW6c2befav4utfMIih4OokVa6Hq1vNUPsfzDD+7bNevB/ft+c+OW9XAQcTLCjUdw8BwLvKAyznedxvV0ZN1AyApGugtZ1Zk78TxaPN28lu95gT1rjJNr1SmNnyd7/k2EouF7LrG+HShGBElRkTS9ZVHz06cdfu4f5Dd9nR5VWLhcQlIkPMdn7Ng8dtVl5kwesxJEDYUU/HFtj+kzOWRdxvd8Lr44TWXRZOyteRyrMYd9MCs2ds2hNLN2+yEjrlFZDJpMKrrMzOkc9YKF5/r47/l4jS7bkiLhuT7lhSpTJ7NEO0NcfGEas+wwdmy+yQECMMsWnuORH69cxxnaEN/+rjA3BYGjMkf16jzx/f3UxrOYs0Wi2ztx6zZGdxIr2+Cg+T6lM1OEBjLIIQ23aiHpClomRvHUBE6xRmR7F4V3r4IAz/FQdRU5rGFnyyBLuDWL0qkJEkeHN6XLeHWb6W+eJLGvl/KleTzbIX98gtpkvuXn29Dh8b1AlTjVrrA455Bse/+yPdX8NMnOHUiySjk7jm2WmyRfs5LFqhXo3nE/jlWltDiKJOu0Dx5GklXq5QWEJBPv2IJAkJs5h2bESHbtRNHCmO1bqRZnKS+OoodTmJUcrnM938N1LByrRtf2e5m/+haOVcNrEJA9z6G8OEayezdCSBQXLmPXSnQM30rbwCGsegnXCQxTz877sGoFbLNCumcP4XgXkqSyMH6cxYn3iGWG0MNJSosbe6ySrGIYKXzfw7bKOHYdR6lhCQnHMXGcGoaRxDCSuK6JbVUaon4u4Ug7qhLCMNKEw204Tg3Pd9H0GLZVwTSLRKKdVCtz2HYFIWTyhVEi4XYkSW0SgIUQaFoUTY/h2DVsO7iGaZaw7Squa6EoIcKRdgRS49/rOHYdXY9jGClCoTaEkDCMFJZdbT6T6wbPkEgOUa0tEIv2UqnOBS0oEkM47vWhyHoty/nTX8aybx5h8q8rcjmPJ580kaRG9ENAJByE/J9/3qRS9kkkAvXWSsUnEhGcPOmQzXpIAn7ntyuYdZ9CweOF501ef90in/M4e9YhHg/eVywGXaN1A0rX6Ng8+6zZjNi+/nrQLDMaDbg4xWKQEkMEarGO4zM/51Gr+ZQrHk88Hnx3+byHAH7rNytUq4FQ3Nyci09Q1WLWfTq6ZMrF1X2wGoGLlgqVJAmi3b2Ee/ahRVO07b2L/KUT2JU8XoNo7FSLeLZF4epp0rtuxa2Vqefm8FwHq5QLNKIaKR67WqY4epbOww9h18rUFqewyjnsSoGOww/h2RZmIeBm1BaniHQN0X3bR8ief4vKzFWUSIKuWz+K77ksnnmd0tg5UjuP0nHLg3iOuS7ZN9KzlcTQHtRoivTuO8hfPI5VyjWjunalgOdYlMbP03XrR3BqJWqL03iOhV0OSO+ea2NXC9Tz89QWp+g8/HBweMzNYeZmiXQM0L7/Plyz1ryP6twomd230337o8yffIn8pRMkt91C9x2P4Zo1Fs68Su7C26S2Hybc3o9dzuPaN7etzthbC8AyV7CyEDiqC5eKyJrEtge6adsWZ+FSCbvuYtdcLjw9ueozpgvLNj09FGXLPV2Mv71AvbA2t2/xSonFK2vLm1SzJp27kgzf1YFZsqnlTVzL48orqwsjpk8tFxuEkhrbH+yhNFdj8coNclG/S85w5nyJ+IF+hCrj1izcmoWkSGidSYQssHNVJE1BTYSwizXciolTquM1Gnx5poNTqhE/0E/18hx2voxnuyhxA70jEaS+fJqf4VZM3LqNU6xtPkaSQCgy2bdH4djV9/V8wt+g2ZUQgcGLJmTKeZdMl8rizHeoU9j3cBPwPhnmNx3/5+9DSHDk+wf5+P99EAic+Sf/02le/9+Xb+p1ZFXwyL/Yy20/HKReqjmTr/2bE5x//jvbiPbbiXSHQtegxuyYhR6WqBRdInGFWsUlEpVxbB9ZCZwdIyzRv03n5BsVFBkK2SAi1LdVD6TsC0G1jVnzCEUlzJpPOCZRr3roukS14tLWpRJPKZx5q4KqieAzvofv4a8xJFnwwD/ayb0/vQMISMvf/PcneW+dAob3C0WX+Du/eoRdH+oGAtLyn//zt993Vei6WGnCxVJ4ssXXr/cZN5gq0jIRuh/dz9RXT2AX128qvlH/zk1DNkZYYvfRCCPHqwztCZFfsDdsQf89/HXCXwdnB/763Mf3cLMQSyp4LoGTE5cZ3mWgagLPC/qAhSISjuWTnbMJR4N/d2yfYi5oI6OqgnBMJpKQmR2zaOtW6d0SkK09L/h3SRH4ns/CtE2iTWHrvhClnPs9h+d7+B6+01hpwltxVNZ6yY1+xjWQVBktHdm0IflG2NThiacUugZ0dENicca+ro/H9/A9fA9/u1ApueQXbKolj9y8TSypUMg6xFMyqiZRzjtk5xxqZRc9JDE7bhFLyYyN1JsptPxicGqybZ/cvEM8rbA4Y5NqV8CHhRkb2/KxLQ/dkBi7UKdvq86l0+uf7L6H7+F7+JsLp2xSny6Q2NtD+fI8foODFaTeWss8berwzE9ZnDlWJt2pomibM69kVUILy6T6I3Rsi5EeiBBOaqiGjGt7mBWH4kyd+cslZs8XqOYt3BtsMa+FZRQtIBXadRe7vuyFKbpEoifMwC1p2rbGiKSCtgVm2aYwXWN2pMjshSKVRfM6/oCiS2ghJSjnrrq4todqyAzf0caW29vRowr5qSojL80xc76A17hvWZXoPZBk290dxDoMagWb8XezXD22QK2w+RchJFANmUhap2N7nLbhKPFOIxC9QmDVHao5i+xYhemzBfKT1eCZ34ejK8mCUFKja1eCrp1x4l0htLCMa3nkp2pcPbZAbqKK764nz+5jluyWHHRFl4h1hOg7mKJja4xom46kSNg1h8JMnemzeabPFKjlAyLh+4GiS6QHIgwcztA2HMWIqXiuT2ku+PyJEzkqOSsgnL7/imi0sEL7ligDhzOk+yNoERmn7pGfqjJ5MsfU2UJzXD6I/qSiS8TaDXoPpOjYFiOa0ZE1CbvuUpiuM3Muz9TpGxszWZPQG1VYru1hVp2mAFwoodG9O0HPviSJrhCqIWObHtWsydzFEpMncxTn6s3qGACz5nP+3WXHo1ywmB61SGRkEmmFctElO7scBlY0QVuXsup32Vln1d8vngw+r7NPRTMksnM2leLyNcNRifyiQ61yvbicHlbIDEdp3xoj1RcmnNBQdAnHCuxNYarK7EiJ+YtFakUbz7mxuaZHFWRFCnhJNQdnRY8/NSST7o/QfyhNZjBKKKGCD/WSTW6yyuz5AnMXS1Tz1nXrVQ3JqLqM7/uYFQfP8dHCMtvv62To1jZkRWJxrMyFF2ZZvFJuft+KLjF4NMPWOzsIJVQqWZPRtxYZezeLWd48/C5kgWbIRNsNOnfEyQxFiLYZ6GEZH7CqLpVFk8XRMjNnCxRn66ts7I1AUgSRlE733gRdOxNE23VUQ8GuOeQmqlw9tkhxprrumvFcj3qptZSCGpJJdIfoO5imbThKJKUF6dKqS36qyvTpPLPni9RK9rr2rZVrtA0HdiAzGEGPKDiWR3GmxuSpPFOn89QKVlB6sVpLtXUIMKIqnTvj9N+SJtkTRjUk7JpLbqrK+LtZZs4XsapOs+H2+4VqBGPWeyBF+5Yo4ZSOrAqsSjBmU2fyzJwrUr+BMVMMGc0I9mfHcrFqDd6OLAinNHr3J+nenSTWYaBoElbdpbJgMnOhwNSpAuXFenNvXTUsikxsVxft923HylaapPP5Fy8w//yF1u5tsxdIsmB4T5hqySXZpnL6jTL+GnNfC8u0b40xfHs7W+9sJzMURQ3JKJoUKFk2hJZ918e1PWzTpTBZ4+Tjk5x6fILyfOskuQf+4S52PxzkLN/60lVe+YOLDWG5EIc+PcDej/YQbTNQDRlJDnhI3tJ1ay6zF4p85V+/S2l2uaxQUgQHHuvj3p/egVVzeeG3znPxlTnu/LtbOPz9g0TSOpIkcCyP/Y/18fx/P8epJ6ZQNIlbvm+AO398K/FOA7nB+D/4yX7OPjXF8795nvLC2s8mJEGiJ0Tf/hTb7+2g90CKUMNYy6qEJC1VWfi4ro9retSKFlfeWOD4V8aYPJm/IUdBjynsfqibQ58eWP5+1EAx1PfBtTxu/9wwjuWt60wVpqt86Z+9RSW7vghgIL4XY/+jfex6qKvxXUjIitQkqrq2h1VzyI5WePcvxzj37DS1/I3xw9IDEQ59eoA9j/QQyegoeqDbgb/0+S7zF0sc++IVRl6ew667+J6PkFq3PpIs6NwZ5+hnh9h6VwehuIqiN8as8Rxm2WbyZJ5jX7zC6NuLwXWua6K6MYQkyAxFOPiJfnY91E0kExwSAhXY5TGzaw4Ll8u8+9UxLjw/SzW3sRijkGDn/Z18+J/tBWDseJan/uNpzIrDljvbOfrZIbp3J9DCCrLaWKdeUFFhmy7FmTqnHp/k+FfHNl2jhUWXUt69LgrsWD6z4605ybOTNpK4vnlyrRJ0hF6al3pMoWNrjK13dbD1rvZgUwjJyFqw5peew/d8HCsoR164XOLkNyY5+/R04IC0iI//3wfoP5jGsVxe+6PLvPPnowgBqf4IRz87xK4PdRFOaSiajKQE88/zfFwrmIOjxxb4+r89gbli41Z0iTt/fCuHvm+AesnmW796irmREnf/5DYOfqKfUDKoEnVMlz2P9PDcr5/j4stz6BGF2z63hSM/MEg0oyPJAtcJ7M2Jr43z0u+PrLrOSkiyINUfYeBQmm33dNC9J4kRU1B0GVkRzXWxVKzimC7VnMXFV+Y4/tVxZs4VbuiQFcno7Hmkh4Of6CPVFwm+n8Z1lr4Xs+IE1U7rfO7sSJEv/4u3N3S4JEXQtTPBwU/2se3eTsJJrflMiOU5YFddZs4XOP6VMUZenlt3nNaCkKB9a4wjPzDIjvu7gmtoUqArs2TPqg7TZwu89adXufza/Go70OK4SYqgd1+K2z43zNDRDHpEbag6B/PZsVzqRZvRtxY59sWrTJ7K4Vg3bm9Wjdk9ncH81Vfa6GDMrGqwXx7/yhgXX5qjXtrYRkuK4NCn+7nrx4MK3AsvzvLcr5/Fc312PtjNrZ8dIjMcbcyF5edynWBvzo1XOPH1CU49PnHdfuCU61z5w1eus992ofWo7+atJVyfi+9VCUUkVH39Ae07mOYTv3yQRHdoeeEsWbhG6asAhCKQFBktrBBJ6bRvj9G9O8HTv3aG0lxrugbhlEayNyjXbN8SlJ6mByI8/E/3sOP+TuSGLPlKSLJAVhS0kIJre9d5kEIEcufJ3jC+59OxLYasCO74sa3o0SDMjgg84nR/hHt+agcz54qkByLc9zM7iLbrzddIiiCc1Nj/WB/5ySqv/s9LazomoaTKgz+/i90PdaMay2Jlq8aN4ESmyAJVlzHiKqm+CL0HUjzza2cYeXmupcUUSqrc9fe2cfQHh4LnoZFG9QL5dkRwWo4Y+nULZ+X9uI6HkDdYWAK23tXBfT+3g979qWWnzfeX54EUGHzV0AknNTp3xOndl+TF3x2huE6J6bVo2xLlw7+0l233dqy+RgOyKhHSgpNw+7YYr//RJfLTNWzTRQu1Xm04eCTDh//5Xrp2xhuO4fJYCBE8h6Lr7Hywi47tcV787fNY1eC0LqutGSBJEWy5o50H/uFOuvckkGTp+rWzYswGjuh07U4wcEuaF393hPzk9aJryxBoYaW5XjzXI9ZlsGtvivt+bgfRthWquiuuJWsSii4TimukByK0b43x1H8+va7zvoT1Ut4tp92XSuU3eL+QBdvu6uCRf7GXWLuxvr0Rgb3RFBk9ohBJ63TtSdK+PcYLv3m+pegrQDSjk+wN49oemcGgk3fnzjgf+b/2MXAojaRcY28EyEqweWhhJdj4rhkXIQShuNpU/m3bEqNjW+BYq4bctCVaSKF7V4J7fmo7i1fL9B9Kc/dPbEWLLNskWRVE2wyO/MAQi6MVjn9lbM1TfySj85H/ay9b7mwPNjZWr5nr7I0hE0popAcj9O5P8a1fPcXEidbIsLEOg/v/wU72f7y3GTUPop9+ECkQoOgyakje0N5UsubG0REBux/u5v6f20nbcPS6NRrM5+BZtJDCljvb6dmX5PhfjvPyH4xsemBYQu/+FB/+xT30H0qvnm+r7IDGtrs76NoZ58XfuYBdC5y5pWzEZhCSYPt9nXz4F/eQHow0BGBX2xvVkFENmf0f76Nje5xnf/0sZsXBd32E0pq9kTWJ3Q91c+/PbKdtSwxpkzGL3tlO3/4k7/zFGC//3siGhwXRiE4t2Zu+AyliHSF2PtDFXT+xFSO+3BR6lW3TJFRdJpzUaNsSI90f5oXfvkC9uLxGfcejNpn7QJTQlix/PC3TO2xQq7jrGq7SXB2vcXr2XJ9a0aKatSjN1ylM1aiXbRRdJtUbbqZsJCV4yD2P9FCYrvL8b51fM5S1EWIdBtF2gw/9wi523N+JEFCcq1HNWdTyFnbdRY+ohJIa4ZSGEVMZfzdLvbRRhELQsy/J9vs6MSsOF1+ew6w49B0Mwn6SLJEZinDkBwZp3xZHjypMnMgxe6FIOKkxdFtbM42388Euzjw1TXasct116kWbetFGkoMJZ9dcKlmTStYiP1Gl2khbRDM6bVuipPojaOHAQHRsjXHvz+4gP1Vj/tLGneUlRXD4M4Pc9iPDgfHxfBbHKpx9aoqrxxapZE0UTaJzZ4K9j/TQfygdRDEaJ8z8VJXibJ3CdI25keK6YXMhC7be1c6Hf2lP4IiKQCCsOFtj8WqZ/GQV1/GDST0cJdUXJhTX0MIKBz/VjyRLPP1fz2xqhGKdBg/+/C623t3eXKxWxWFxtML85RK1go0RU0j3R0gPRomkNW7/0S1MncrfUCi7fVuMD/3jXXTtijeNT61gs3ilzPzloHw2nNLIDEVJ9UVI9oa492d3kBuvrCmEtuaYSbD17g4e+aU9ZIYDxdellFx2rExuoopdczHiKm1DUVL9YUKJYMz2P9aHHlN5+r+cITexkdOzjHhXmAMf72PvR3uJtunYteD7XbhcpjxfB0mQ6A7RvjVGojuErAT9iPY80kNuvMILv33+/0hz35XwXZ/SfL1pmF3Ho5a3qOYsirM1ijN1zKqD1kg3ZYaixDoCx0gPK9zyyX4KUzVe+6NLN2Q8hSSItRsk+8I8/It7GDySwXN9CtPVwN4UbRzTxYgF9iaS0tGjCqNvLWKbG0QoZMGWO9poG45RyVqMvbOIa3sMHgnSp0ISdO9JcPBTA2y/N+g0ffXYAguXyiR7wwwcTqNHVfSowt5Hehh5aXbNaFw1Z2JVnKa9MSsO1axFZdEkPxXYG9+HeIcR2JveSKA8LAQ9e5M88A938vVfOUFheuNDiRZRuOPHtnDwE30oDS2d2ZEip5+YYuJEllrBRgsrdO9NsOfDPfTuTzadAqvmkJ+oBvvGdI2p0/l19W4kRbD74W4e+ie7mxtskPqtsni1QmGmhu8F9jMzHKxRPawQimsc+cFBAJ777+c2TdelByN86Bd20XdLuulQ1UsOi1fLzF0sYtdcQnE1sAP9ESIZnXt+cjuzI8U1syHroe9Aig/9wi4yg9GGxJNPecFk8UqZxdEyju0RSeu0DUdJNygjH/qF3VgVp+UDhZAEez/Sw8P/dDfRdgMhgvVTnKmRHa2Qn6rimB7htEbbUJRkXwQjpqBHVY7+wBBaWOH53zzXckYmMxjh0GcGOPTpAfSogll2yE1WWbxSprJoIqmCZG+Y9i0x4l0hJEmgRxRu+dQA+ckqb/zJleYaVaI6qSOD5N4ZwynVg6zO/j5826V4trW2HZu3lpAFyTaVN58pUK966xq73ESF009Msu2eDq4eW2Ts7UUmT+eDqM01p7OePQnu+nvb2PVQdyDnrUnseaSHE1+bYPHqjemvJHvD3PP3t7HjgS7Mss3pb01x9ulpps7kmyFLISDaZtC9J0HX7gSXX5/flDe09e4OyvN1/urfnuDiK/P4rk/PviSf/neHaNsSQ9FkDn16AIAzT03xzK+dpbxoIimC+39uJ/f97A6EEAGvoD+8psPjOT4n/2qCgUNpsmMVrry5wMSJLAtXyqt4AhCczvY/2ss9P7mdSEZHSEHoc+td7WTHNhbBygxGOfTpgWZkY+FqmW/+u5OMvrWw6vucPJnn3DPTPPxLezjwWB+yIjArDs/9xnnOPjW16UaXGYjw4D/aRce2RnuIis3xr4zz9p+PsnC5tOr9oYTK7od7uOvvbSU9GEHRZPZ8tIeFKyVe/9+X103VyarEng/3BJG8xim1vGDyyh9e5OQ3J6iuSLUphsy2u9u55ye307M3cGBbhR5RuPWHhujem2w6OwtXyrz0eyNceG4Gc4X6ajilseuh7uBZBiKk+yMtX6dtOMoD/2Bn09lxTJeRl+Z4/Y8vM/ledtU81aPBCfWuH99K74EUiiaz68EuqlmLp//rmZb4G4omcduPbEFIUJiu8eYXrnDq8cnV61RA964Ed/3ENnZ/uBtZkVA0iX0f6+W9b0xQKgnsfGXNUIykKXjWJvchS4GOR/b6NYEAoSqrZObXwsz5IhdemKVrd4Irb8wz9m6W6dP5Bl9rxf0ogsHDGe79me0M3dqGkARaRGHvR3uWn7tFCAkyQ1Hu/7mdDN3aRnnB5OQ3Jjj7zDRzI0Wsqtt4nSDeadCzN0nnzjjjJ3KbOto7H+wmO1bmq//6XcbeWcT3YNs9HXzy395CrN1ACync/rlhhIB3/vwqL/7uCPWijR5T+PAv7uHIDwwFjsm+JNE2Y80NybV9jn91nO49ScZPZBk9tsjEe1myY9XV9kNAvCvE0e8f5NYfHsaIqUiyYOi2NvoPpSnOTG64wXbvTnDgscDZCb6rAl//lRNMn1mtjj9+PMu5p6f52L/a3yyrruUtHv9/TnL12OKmzmj3rgQP/qNdpPqC9VbJmrz9pVGOf22M/Hh11T1G23X2P9rHHT+6hVhnMJ63fF8/M+cLnPzG5LoHFDUkc/gzAwwczjQdxfxklZd+/yJnn5xaleIx4io77uvkrr+/jY5twQa+ckw3QjilcfuPDtM2HGumlKbO5Hnxdy5w+bX5VftBrMNg36O93PGjW+jYHruhVFbP3gT3/eyOprNjVR3OPDXFsS9cZfpcYdU8DSU1dj3Yxe0/OkznjgRqSOaWT/VTmqvz8u+PtCS8qEUUbv/cFiRZMH+5xGv/6xLnn59ZZaeFgP5D6WBd3daGJAv0mML+j/dx9pmZZtRfiRmkjg6Se3cseKMPaiJEqDd58xwe3/OpV1xuezjB4rTFsWfW7pbumB5vfP4Kx78yTnG2dt2G3fw812fyZJ7nfuMckYzOwOE0QgTEtr4DqRt2eBLdIW759ADVrMXzv3mOM09Nr5IChyAcXpqvU3qhzsVXWksBSZJg5KVZLr0635wEcxeKnH9hlrZGGk2PquQmK7zxx5cpLzYEDB2f88/PcOsPDQUn8YhCojsc5HrXMHrTZ/N8+f/1NpWsRa1wPbFxCZVFk2N/ehU1pPDAP9yJJAe9XwaOZDj+1fENJ9/WO9uJdQRK0Xbd5eRfTTSN6rWo5iyO/ckVhm9rI9kTJpzU2PlAF5dfm18VXrwWQhYc/juDdO0MnB275vDG56/w+h9dWjN1UCvYHP/qGNW8xcf+1T7iHSG0UBCqvfjKPHMjawt7xbsNDn26fxVp/eXfH+HtPx9dRayFQIr+/HMzlOZNHvu/D9C5M96ycejcFWffR3ubTlVprs6z/+0s51+Yve57rOYsjn9ljGrW5GP/aj/xztBaH3kdtLDMoc8MNu/Lc33OPjPNU//pNKU1Niyz7HD2qWmKMzUe/VcH6N6bQFIk9jzSzdW3Fjj9xFRL1xVSsB6e/W9nOfP09HXjhg/TZws8/xvniLbrDB7JBP2i2g2Gbm3jyoSKUzHxTBvRUEuVwzrWfJHorh4qIzOo6Si+4yLpakN4WOBUTaqX5pBUmfj+AczZQhBKF+BbDkKRcWs24YEMlYuzaB1x3JqFEjWCf9cVzJkC5nQeq+Lw0u9dQFIlijO1dYnInuNz5dgCVs3hE79yS3ODSHSF6NqVuDGHRwg6tsdo2xIlN1Hl6f96hsuvzl8XIfA9n8J0jcJ0jQsvzLRU2eq5Pmefnl61LidO5Lj8+jwHP9EPBA7v3IUib3z+SnMtmiWH88/Psu9jvehRFSOuEu80mDlbWPM6V99a5Iv/5E1Ks/X1+Rg+FKdrvPq/LqGGFW7/kWGEJJAViaGjbZx5cgp/A+L3jvs6MeLLxSLv/PkYM+fXXs/F2TpvfP4KQ7e2YcRU4p0htt3TyeTJ/LqdyCFYO0c/O0S6kWI0yzYv/e4F3v3LsabjuRLleZNjX7iCXXP50D/eRSihYcRVDn9mkNG3FylMrR21ahuOBoe/Rj+uWt7iud84z+nHJ687lNWLNqcen6Q4V+eTv3KQ1MqDzwZ7jpCC1PnWuzsCDiKwOFrmW//hNBPvZa+z06W5Om9+/gr1ks2Hf2kPocZYb4ZQQuXWHx4m1Rd0JLBNl+NfHeOF37qwZlS9lrc4/rVxCtM1Pvov99G2JYqsShz8VD+jby9w9c3FTa8phADJJzdR4cn/eDrYT69xLn0fxt7N8vSvneFT/59b6NgR2MNUf4Te/cllmoPvIyQJSZWXPhzZULkRSJu/JGgUWK+4ASdhg/2ismiSHaus6+ysxMKVMiMvzjZfq4ZkMkOtn4yXsHT6PPbF4KR6rbNzLTzHb5noO/rW4ipD6tgekydzq/Les+eKLI6uPqnW8lYz7CuEINauI6/De3Ftn4XLZWprVHFc91rL49wz06uMdNtQFEVf/2uUVYmOHXHUUDBJagWLq8cWNqxUyU9VmTqdD+5fEgweSRNObryo2rdE2X5/Z+DY+T4TJ/O8/aXRDXkSnuNz4fkZrrweKLAKIWjfFmPo1kxA/lwDw7cFBFUAfBh9a4EzT01dv2k34HsweTLHyW9MBGTsFiAkwfZ7O5fzzT6cfXqay6/Pr1+95vhcenWe88+1LjCY6o+w5+HuplNVmK7y2v+6tKazsxJTp/O88fnLzbENJTQOPNaHHmmNm+TaPmefnObcczPrjhvA4liFCy/MNjceLSTTsTWGwMerWUS2dCBpCnpHAi0drF3fdpFDGlomFvTU6UwgRwxCAxm0dLRpP5xyHdlQMbqTqLEQaiqKloniWw6+66Emw+jtcSLbOtHSEdS2KHpnAjURbt5fcbZOfqK6edWVH4zZyvVsxFRSveGN37cGFE1GAK/+z4tceH5m03SIa/stpTddy2Xs7dWHELPqMHU6v4pfMXk6f11KqTxfbx64hBDEO4x17bRTD4j8m5FPIdjAzz09HfBoGmjfGm1y5taCokt07og3+WvFuTpjx7MbRriyo2VmLwQOkZAEw7e1oYU3nsvde5JsubM9iL56PhdfnuPk45NrOjtLcCyP009OMd7gIQkh6DuYondfat1uINvu6SCSafDc/ICEO/Li7Lp7iOf6jL61yOmnWjt8AKghhW33diyvXx/e+/oEEydz60bVXdvj/LMzXHljYe0XrIGO7XF23N+FJAf2Zm6kyBt/fGVDCoHv+lw9tsBbf3a1ObaJToP9j/at4p1uBMf0ePcvx7jy5sL6a8GH6XMFLr++vDctpfGXOFNOxcStWvQ8doD0bUO037ed9K2DlM63bnM3dXiECATC3nutHFT03KyeIH4w4EsOiqQIjNiNeWtLmDlX4OzT0y05Wq3Ccz2y49eE3H2oZq1VRm7uYqlZHrcEx/KorYiG6BH1hiqDNkKtYLGwQi7diKnNDXMtqKGAeLgU2bBNl8LMxqfapTLLJUTbjCbReU0IGL69nURXKDg51F0uvTLXEgHZc31GXpptGnVZkeg/lF6TWCwpgTFUG8bQrjuMvDxHZRMiLT6MvDTXMkFRDckM39bWHLNa0WLkpdkNjSkEY3vhhdmWS3iHb28j0iAN+77PhRdmWbiyeYTT9+DiK3PMXSwG1RmSoHNnUFreCqo5k9NPTm14gg4uBNOn8830nZAE4bSGNTFPfTpP4Z2r1KfyVC5MUz43jVuxqFyaxc5XqYxMU7k0h1u38Eyb/LFLlM9OBiR5y6FycYbKlTlKZyapXl2gcmmWysVZ7GKNyqU5rIUSpTMTWHNF3JqFtVCm+M5VqlfnW3rGtcZs5nyh6fTKmrTxnN4A48dzjLw4e1O5TI7lkbuGfO67PpVFs+mU+r7P3Mj1fD2r7q5KZ+pR9abZ6eJcbRUp3oirGxYtGDEVLao0145ZdgJu2Aawau6qQ1ysw0ALrb+ZCgm239tBJB2snXrZ5sILs6vSJOvBLNtcfnVu2d6oEgOH02sesGRNYvj29qbtrlfsliqVfM/nwnOzWLXWqsDCSbUZRYUgNXfxlblN06C1ghUEDazN7c0SvzLUOMT5ns/Zp6Y35WNBYKPPPDVFYSqYB1LDRmeGopu8M5izhekq557Z+HAVvDg4nC6tUUkSRNt0FC3Y35yyydTXTyAkiY4Hd5E+Osjiq5conGrdudx0xXuuz+SlOtv2h5m+ar5/LZM1UCvauA1nQQgRlGLL4oZKrT3PZ+zdLIXp1kibrcIsO9hrbHCu4+HUlyt9SnO168bEc33cFZNQ1qUWY2mbw7G8VQtOyKIZbl0LsiJWVws1So43hA/uylOzCCb5etCjCj17Es1Ik11zGXs3u/E1VmDxagXH8lAbOf/ORkTqWsMSzegkukNIS4YhZzF9ptASYa+SNZm/WCLRtXm6KdkTXj7VAYujldZIwX4QHcuNV+jYHt/wpULAwKF001k1yw4TJ3KbOyENVHMWk+/l6TuQRtEE0YxO954EV48tbLoRF6ZrzF1orRdQJWutmi9aSMGv1nErFm5lDZ5Idfl31nwJa76IV7eDTspL8HycZinp9QbXqi2/1s5VkCM6TrmO34Jh3wi1gtXcRIQQyJrcLIttFZ7rcfmN+Zad51ZRL9nY9etvxDE9HMsLyL8+lGavHy/P8Zp2FGhyZ24GHNNbxVeT5EAyY715KqvSqgOY720eUfd9v9mLCRrVdRs4VeGUTueORNNJqRXsllspeI7P4mhlVfVU9+5EcL1reJ2JzhCxdh3RCJcVpmvMXym1RIkozgWFGt27k42HWv+16f4oocRyBH3mQqGlVKvvBbazNG9uGq2UVcHAoXTz79WCxeTJXMsNUMsLJlOn8027luoLio9mzm8uVZAdq7DQIlWlvGiuigJpEWXZGfWhOpZl9AtvIGkKeD5uzbqhQpRNt2FZEUTiMm8/VyQUlZBucOMWUlCFICnBH1ld+iNdF/V4P6cSuxboa9yoeOFmMCvOKiOyhGsXcK1oX0/evEbkTpLEZpy11RDBafr6cZMaJffXvHyDD7fNQN9g5YkmtEl6SlJFU7ARglSaVV3/tLJUodCMItVdyvN1ZE1q6Y/v+atSkeGkhrJGuDTWYRBOac2eLPWSTb7F6iTH8shNrEGSXQOZgchyhMkPnNpWTo8QcCqKLRirUEILuF2NNVDNWeSnbsxpn7tYbBosWZVoG46htlByv3g1qPhoBY7lrnIIpBV6LZvBdz3sbGW1s3OD8EwHO1tp2dlZ294E60YIsco2L3GLbgT1ksPiaPmGDmWtwCw7qzb9JfjeipSYz6rI8fJrVjtt0kayEWtgycFYGjd5xbhd91liY3tjVR0cc9neqIa8aeRe0eRVNsmuexs6/tE2nUS30bQ3VsWhkjVbtjdLemxLCKc0FPV6e5PsC6NH1aa9qSyalOdaq06yq+5qXtAG0yUzFGlGMfAhN15d5WRuhErWpJrb/J4iaZ3YCm5hcWY5DdoSfJppRwi+s7bh6PJ9r/c2Lyj2aNUpWTl3IIj4N3mXkkCJG3iWi1u1MDrjhPvTN7SEN7WObT0qe26L0jmgUVhcvyy9CRFUuMQ6DBLdIdqGYiR6QgFJLKaiGoG+h6JJGHG1GZZ8v3Asd0MRvPcL11q/Iu261232oha+EFmViLbpxDoMMoONcuqUhhHXAmXpxphpIYVET2ukWAgM0OJoGdf2UTSBEVfp258KStnXufFISqd7d6L59/lLJcwNwrhaSGmSoiFIgf3Ib93R8qagqNIqfQYhCYw10g1GTG0qBvsEatgr+QUbwbW9TTVklhDJaMgNVXEfn2rOxqy0ptli1ZyWTv+RNh0tvGxk6yW75WdZQmGqtmqM452B2OZmPLbSvNkSrwT4QJoX3xGIwOEO7E2Yti1R4p0hQnG1YW/kQCNFkwmntJZ5TuvBrjnUW9TvuRE4VmvK6a3y0DaDoktE2wzinQaZwSipgQiRpIaRUNFCSmPMAh2hRE/rXKd60SY7XqHvYAohB/pAXbsSgTO/zvPFOww6ty1HROdGihumhUNxlXBqed/IDEX5yT++t+WpqhryqnSmpEhoUeW6iHKkIcYHgR2oF+01Hc61YJsu5RbXc7RNbzqWPkEpeqtp8XrJbqk6M95QNV5CJWu2xONaiWv1vhLdIWRV2pBK4nvckKjwRtCSYXo/dQvTj58k1Jei57EDeKbD5NdOUDzdWlpr09U/O2bx9vNFZEmQnbM3dAIUQ2LrnR3seqiLgcMZkj3hGz5t3Ch813/fsucbwfP8lpqUea1uHOtASEElwN6P9DJ8RxvduxItndJbhg8XX5rj4Cf7iXeG0KMKBz/Zz9i72TUr4hRd4sBjfWSGg/ysa3tcfGVuQ7EpWZNWneIUTaKthfzuehCCNU8Oii4jr/i9U3dbdqp8z285p66FlCaxz/cDrlCraQ+voVC7GfSIsioV6Vgbn2rXQr1sr3JcjLjaktih1Wgt8d0OLSyz44Eudj3YRd8taeKdy6f+bxdc279pTsdK+K7fUmr2g0aWhCzo3hVnz0d6Gb6tjY5tsZuaAvN9uPD8LLs+1I0Rk4hkNA5/ZoCp0/k1OX1aOCgPXyrhdkyXkZdnN4woqyFlFalZNQKV//cLIYk17c2SGnDwYDSV2luB5/otr2ctrKxSubZrra9P1/Y258YAekxdRUuw625L71uJax2kUEJraX83N/gubwSSrqAmQ/iOR/rIILNPnUGoMom9PTfP4ZFkGNxpUCt7dPRrvP6t/Jpllqm+MPf81HZ23N8Z6MQ0tEvsuotVcbDNoDeVawcbgl13UXWZju0fbMH5/tJ/vvugGIG2ye2f20LbcKy56FzHC8as7uJYHp7j4ZgedmODzwxGVyvkboLpswXOPjXN0c8OIasSfQdTfOKXD/DuV8aZOpXHrrsICRJdYfZ9rIfdH+4JUmeez+SpPKcen9rQi5ek1Twi1wlk3N9vV9t6yV7TsMuqWLXAWiHrLSGQZW9tgct6IHkevM9vOc8NgaFrJV0UtD9Yfhbfbb16cAnXGqxV4d+N7nEzDtdfdwjo2Bbj7p/czra7O5oVhEEPPKeRVgl4La7t4dQ9rLpDKKbRtjW6Icl/c7TmmNz4p377oYVkDn3/ILf90DCJnkBU0vf9Zo/DpU3QdTzchr3x/UAFerMqzZUYfXuRkRdn2fuRHiRFYsud7Tz2bw7w7l+MMX+phGN5zTYXBz7ey84Hu4AGP+r1eS6+NLdh5d1S6m0JS20d3i/Mkr2mIxO0dFhSVeaG7MCN2A1Fl5tZAN+9hj+5CVzHb+n1srK64MhzvBu2N9faT0kRm9ob37959sZ3PHwfkrf0I4c1CqemSB7s21j5/xpsrsPjQznv0tatUcqvfdI14ioP/sIu9n6kFyEFhMB6yWbsnUXGjwcKxPnJKtWCFahCej74MHA4w/f9+0PE2m/eCeO7BZIi2PuRXh76x7ubDqLreCxcLnPlzQWmTuXIjlUoL5rUS06TBB1KaDz6rw+wq2EkWoFdd3n9jy8T7wqx/b5OFE1i4HCG3gNprIpNvewgKxKhpBqU3UoEpbxn8jz/G+dWVYWtBZ9gw6YR5MlPBuXV79cIuba3JknYc/xVEbUb2rg2VlS47vpL81wI0Yz23MzreO7qcuUlDsWNQL7mVOo5rW3G353Hg2UkewKl4613dzSN+FIDzfETWeYvlijM1Kjl7aDBYqMFwO5Henj0X+1Hjt2kCoLvIiiaxKG/M8j9P7sjqLQSQV/AmXMFRt9eZPpMnux4hcqihVm2m5t1vDPEJ37lIEO3trV8rWrO4uU/uEgkozN4NIOsSmy7u4Ph29uol2ysiouiS4QS2or+bT5Xjy3y/G+c37RyyPdXr525i0Ve/6PL7/uAtdQs9VqskhRotAx639jgre7K3oXSjXGwWqWhuQ1nYQmSvAY/axNcGwUL7M13zprYxRrlkVlSRwaZe/48drGOUCQqo60XyGzo8Gi6YNfRCF2DOvG0gmV6TQLXEoQE+z7W26jvD6I6uYkqL//+COefn1lzIi1hLVLw3xak+iLc/RPbiLY1BAFNl1PfmOT1P77EwpXyuicc1/LWbja0CfKTVZ741VMUpqsc/v5BtJCCrIKR0ALCoN8Iw9ZdavmgDPvdv2wIhm2mD9TowL1ENHZMN2jQeJMrWWxzdfhWNVqvspEkNtX2WIJVXU6VLXWyv3berwdZES3pU5hlZ9WzKJrUsq7FEvSI0oxEQZDi8m7gFPrdCEkWHPrMQKDI2pD5n79U4oXfPs+lVzcWx/yuj2x9AHTuinPHj25pVgPVyzbvfHmMt790ldxEdV1SqWN57yuiNXexyOP/z0nu+vFt7H+0t9HMUyKS0omkl07+QfqmvGhy7plpjn91vCVZhqVo91KVlVl2OPnNiZve8sSuu007LARBFWmLdkCSRVP7DDZ+T9D13F9+3w3YAVmTNiUOQ8CtWjn/1ZC8YXXvWtCjq8nn9ZL9gSkdNwLPdJh58gwLL41gl03wfXJvj+GarR+sN9wBbMvn0skaqXaVt54tsPNQhGsbv0bSOtvv62wSMK2ay1tfusqJr22s/gs0uk63fK9/ozB0a4b0wLLQ4sSJHC/+3oVNq46ELDYUGtwQno9iBIbHrrtMvJelNFtH0WUcy6Oat1i4XGLiZI7ceLVlroddcykvmE0CuhHX0GPqTXd4ltJ8AAKBGg40hlq5jiSvJkZvhFrBWpZLQDSInPKmOjwQVC9caxjWQnnRbEYfhBDoUYVwSm+5JxYEpMGV0afSfH3Dnk1/E5DoCbHl9ramka8VbV75wxHOPjW9aYheNeSbpyP2XYSl5rQrix0uvTLHK384smn1oayszW/ZFH7wRzVkJEXCrNiMvp3FLNlBWXs96MQ+f7nExIkc+cnqDRF1awW7qTAcSga95Voh794I6gWrkTZXEQj0mIoRVai30GVdVlfzGjeKwlTzVtNxEIhm5/JWdOW0kNySg1Saq6/6vKW+kq0WcgAkrymWKc7Wb7j35QeFb7vY9vI8uZFO6bCJw+P7UCu7zE1aDO8OUche36QsktZp37JcklxdNDn71FRL+ctoRl+zHPBvA3r2JZshRc/zOf/sDMUWRKAUXSL8PirbIhmdB35+F/sf7QUB73x5lFf/50WKm4gQtoJ6ySY7VmnK9mshmc7tMXJr9A/7ICjN16nmrKB3jghOHInuUEsOj6xJzQaDmyE3XgkIhwlAQKzdIJzUsKqbfz96bHXF2nqoFSzyUzW69yRBBJVxie4Qkydb0xMBaN8aa5KUPdcnO1rBukHi882CaJQre17w80aiArIcvA9/c/860R0m0RNucgQLU1XOP7e+8u1KRNv0DfWk/qZCViR6Gj3hoCEk9+Q0tRbWjRZWWj4orESyJ8xD/2Q32+/rxPd8Xv+jy6vUwT8IKosmxZlas0VCKK7SviXWshZPq8hNBuXh0TYaa1Qj0mZQL20ehdLCConuFQ7CBtNzcbQcRHtDwXWSvWG0iIJjbv79hNN6INWxCSrZYMyWDtmJrhCRtN5SRG0JK7XFPMcL5C0+oDbWdxqbrn7Pg5HjVU6+Vub06+XrwoaKvlpnoVqwNqzoaV5YCdRh1fDfTocnktKXZfZNl+JcrSWjHWs3yAzcWAsOIWDgcJp9H+1F0WTmLpZ458ujN8XZgeCUPXUm39RC0sIKW+5ob6li6EZQmq9TnK03w7+RlEbXrkRLOWwjptCxrbVKjux4NWj10UBmMNKysxRtM0j3t/BaP2hdsnQw0KMKfQdTq8PgG8CIq/QdSDXD0tWcycw1zf++XZBkSKclkglBPC5IJgR9vTIH9qlEwoL+PhlNg3RKIhIWpNMSWsMm6zq0ZSRiMUEqJRGPCY4c0sikJbq7ZZIJQTQqSCRE4zVilfaXFl5doVPJWi2V18qaROfOxA2H8f8mQEisKuO2ag7lhXpLEiOJ3tDqjbsFSIpg270dbLunA1mRmDyV492vjN0UZwcCOzA3Umzay1BSY/j2tpteEVyYqlHJWk2eSqI7HHQybwHhpEbb8IrXbnBri1crq3R3unbGiWZaO9Qme0LE2jc/YLmOz9W3lhuyhpMaPfuSLa+HcFpbpeRemAmEFW92GvHbjZae1rF9ygUX27p+hfj+aiJpq6JkmcEow7e1fcCKie9erHRuhGhRzE3Aroe6W0qZrHqbLOjalWiGPq2Ks6lWy43Ad30uvzZPaS6IgMiqxNa7Oujdn7pp14CAvzT27mIz9K1FlFVy6Ruh90BquQfXJjArziql6EhGZ/i2tk1TiZLS6DuWas1YXXlzgVJDdl9Igh33d5Lqa+EeRdCWomN7fLmT+9XKTT/hrodwSHD0sMqtR3XuuE3n4AENTRMYhiAcEfT2yOzaqdLTI3PLQZVHHjLYMhw4KYMDCvv3qTx4n8He3Sq7dwXCbooCXZ0S7e0yB/artLfJPHi/zsMPGsSiK6rZvNWE1VaFUHv2JOjZm/y2y2T8dcW19qYVaGGFXQ92r9nmZSOoukzXrkSTY1Mv2jcsubARPMdn5KW5pgOl6jK7H+lZ7WDcBNh1d1Uz11BSZeudbav0s9bDwJE00cwKR2QD57KSM1et3XhXiMGjmU0PclpYbjZd3QxLNrpaCA5yQhLsfri7pWpfIWDnA13NQ5/v+UydLjB/eeNilr+OaMlcGBGJdKdKInP9xLeqzqpeRtGMvqkXHG3Xuf1zw7S3eOL+m4jCdLV5wlJ0qaGHsXET0N0Pd7Pvo703fjE/IPYtnVS69yR44B/tYtdDXXTvSdC+LbbqT9uWKOnBCPFOo2Wi78y5AhdenG1yX5J9Ye772R107Yq3xtMSQdQi1mlseOq49Mr8spMgBNvu7mD7/Z0bVlAke8Mc/sxgy2RA3w2amjZ7SAnBvo/30X9Lev1nEdC1K8GBx/paugYERPKT35hsRnlSfRHu+LGtm4aoO7bFuONHtzRfZ1UcTj8xedM5U+tBlgXJhBQ0EfV8hATJpEQqJZGIS6TTEoYhiIQFngf5gkexGMw9wxBEIwLH9ZEkUFRIJSTa22SiUYm2NglNFYTDgnrdZ37Bw14RGKgXrVXib7HO0KbRt1R/mDt/fNt1HIS/LfBcn+KK1jtaSKZje3xD529Jj2vH/Z03fr2GcvqSvRk82sYD/3An2+7poGvXOvZmIEKsw2h5jY4fzwbNfBvX6Nwe556f3k56INKSvREicGBiHcaG43DhhdlmBFEIwe4P9zB0W9uGdiAzHOWW7xu47vfrwaq4jKzowSeE4PBnBoMU0jrvExL0H0qz++Hu9T/4GsxdKnL26akmeblrV4Lbfnh4w5SlkILD4q0/NNwU7axkTU4/MXnTOVPfCbSkw3PwnhiqKqgUXY6/VFoVCi0vmMxcKNK+LeBvhFM6t/3IMM/81zOUrpHhlmRB5844t/3wMHs/2tussvh2i4X9dcTYu1mOfnYISZODDfVjvcEifnX+ep5URmfPh7u588e3Ee8y8D3/hpqReq7P1TcXyE9USfUHbRMOPNbH/kd71wxrL+kAFaZrTJ3Jc+nlOS6/sbDhKc1zfN764lX69gfdhyVJMHx7O4/98kHe/tIoo28vBp2tV5w0ZVUinNZI9YZp3xpj4HAGWRU89Z/OUFin8WhuosJ7X5/gvp/dgaxKaBGFB/7BToQQnH9uZlWVjqQIevYmuesntjF4JDgxtTrfpk7nOf/sNPse7Qs0Q3qDUugXfvs8V64ZCy0sM3Akw70/tZ3MUKxphDe7jl13OfG1cQYOpxk4kkFIsPejPUiK4M0/ucLMucKqaj01JNN/S5q7//62wPlqdIq+9No8Z56a3vSZbhYsy+fESYeRiw1Se4Ozs1TAcvlKwPVb4vIscXsAFhc9Zmdd5ua9dbk+S8N26nTwc2Wblux4lexYhWRP0Kg22RPmth8Z5qXfu0AtvzplIqsSPXsT3Pnj29j5QGczGva3zd64js/Y8Sz7Pt4XtLmRBIc+PcD0mTyTp/LXRR8S3SH2f7yP235kmHBKu+Exs+sul16bY9/Heol1GOgRhaM/OMTh7x9cM9Lh2h5m2SY3WWXyZJ6Rl2YZeye7oTCeWXZ4448v07M7QdtwDEkW7PlwD7E2g7e/PMrEiSyF6dqqlIuiS0QyOqm+CO1bowzd2oZZsnn6v55d97AwN1Lk9BOTHPmBQSQ5UMN/6B/vRtEkLr4yvypSrhgS/QeD9dm1I77aDmwQ4fE9nytvLnDlzQW239OBkAQd22N85F/s5aXfvcD4idyqsdBjClvv6uDen95OrN1o2d6YJYdjX7hK774UnTvjKLrE4R8YRDFk3v7SKPOXS6tS4npUYcud7dz141uDg2vD3px9ZpqLr8xteK2/rtjU4RFCoGqCiYsm1dL1rSXqJZtzz0yz5fY2Ipmgs+nuh7uJdxhcfmOB3HgFIQJyc9euBL0HUqT7I3iez3t/NUH37sSmjRb/JmLyZJ7x4zmGjmYQkiDdH+Fj/3I/l16bZ/psHqvioEdUMoMReven6NwVx4ipzI2UmD1fYM8jPTck2LhwtcyLv3uBB//RLmKdBkJaP40mq0ELi2ibQc++JLsf6ubU45O89HsjG0YRFscqPPvr5/jwL+1pniB79iZpG4qSHa9SmqtTL1l4jh/Iu8cC+f9IWifWriNrEmPvZDc8DTmmx6lvTjJ4JBOUJsuCZG+YR/75Xg58vI/ZkSL1oo0Wlkn1RejcESc1EKGWtxh9e5Gho5mWUk61gs2xL15tnkiFJOjek+Dj//oA02eCcK5dczHiKm3DUTq2x4l3GOQmq8xdKLLlrvaWUgHZ8Qov/u4FPvIv9tKxLY4WUtj/aB+9+5LMjpSaBGojptA2HKNjR5xYR/D9ea7HxIkcL//+SEv9dG4W6nWfi1POsiPir/rRtBHX/gSYnglsyNKftbARt6SaNbnw/Aw9exOE4hqqIXP4MwNkBiNcPbZIcbaGkASxNp3uPckgldkdwrE8Tj8xydBtbQHp/W8RfNdn7O0sM2cLdO9JIISga2ecT/zKLVx6dY65kRJ23cGIqbRvjQX2ZkccRZcZP56lmrPYfm9n6/wnH6ZO5Xntf1/inr+/jXBKR0gCeSN7E1aIdYToP5hm90PdHP/qOG98/vKGMgMz5wo8++vneOif7iY9EEFWJQZvzdCxI05+skppvk69GIgKqqGAaxqKq0QyOpGMjqxKnH92ZsNHMcsO73x5lN59Sbr3JBGSoH1bjI/9v/czfabA3MUiVtVFjypkhgI7kOwOUZyrM/lejq13tS/349oApbk6x75whfYtUVJ9ESRZYvi2NpK9YWbOFlgcLeNYHuGERvvWwA6EkxpzI0XKiyaDRzPNFOJGmB0p8uLvXeCRf7aXRFcII6py5PsHGTyaYW6kSH6yhmO6hFMabVuidG6PE0kv68RdenWeN/748k1NUX4nsbnwoOdTLbnc+lCcycsm85PWaoPkw8iLs7x3IMWtnx1GDcloIYWhW9voO5huhs+ELFBUCSEL7JrLqScmefn3Rjj62aG/lQ5Paa7Gq//jItE2nbahaOD0NMixjtXfPFUtNfHzPZi/WOKZ/3YGx/QYPJoh0d0aJyXeFWLXh7rY/2gv4XSQBnEb6s2rSK6NpqVBs8VARVMIQSSjc+gzg1g1l1f+YGTd8mzfDU4qT/6n09zzU9sZOJxulml370rQtSveOHE1Toxi9anE9/1AYn8TbYfcRIXnf+s8Dxsy/QdTCEkQTmoM39HG4NFMkGYRy8rDtZLF218a5eLLc6QHIi1zbCZP5Xjxdy/woV/YTao/qAiJdRjE2g223t2O7wcq05IcjFNhpsqr/+Mi+akqvQdSrXEfGuTlp/7zGe7/BzsDIqEikRmKkh6M4jUEw4QImjouOamO5XH12AIv/NZ5Zs4VvqNqgr4P7vu0d94HJDn6Ppx6fJLOnXEOfLwPRQ/m17Z7Oxm+ra0ZQZTkoBu6JAtqRYt3vjzGO18eDaJ1f8scHggaxr7yPy7y4V/cQ6InhKRIdGyPkRmKBkKbvt9UTJeU4CQ/fjzLs/+/s0QyOgOHWuemZYYi7H6oh70f7UFv8Etc2wsaQ678/sVyW4clZ0pIgkRPiNt/dBiz4vDWn15Ztzzbc3zOPz+D7/nc+zM76NwRD6LGSY1wQsPHXyEgypr2xmuhpcfshSIv/E5gB5YqUaNtBtvu0Rm+o231+hSCSs7kjf99mamzebr3JAOHp4X1eeXNBV75g4vc93M7iXUETmKqL0yyN9y0A5IUqEwLBPNXSrz4uyOohkzPvmRLDg8+jDw/iyQJ7vmp7XRsC8asY1uM9i0xPPea6zTGyzFdLrwwy3O/cY7F0ZtbffudxOYWWQQPf/qNMsl2NRB6u8bYOabHK394kVrB5tD39RPrDJqKKboEuhSI2nmBBHZhvMq7fzHKia9PUFk0ufrWIoc+M4gQQZfcVmDX3WZe1ao4N6dzsR8sypWfuxYD3XN9zIqDogev85zra2l9v9FksPFZTv36yJjvwaXX5nniP5zizr+7lf6DKRQ9MNBLpDjfC+TWawWbS6/M8cbnrzB1Jo8RVVgcq6BH1XXvEwAB7VtiPPjzu9h2bweKJlGcrXP+2Rmmz+apl5zrqnqEHFTeRdI6/QdTbL27I2jaGVE49OkBRl6Y3ZAcu+T05Car7P1ID3s/0kNmMBooqsqikfsOQry+B67rBc+Ytxh9J8uZb01tWuXn+0EO//H/70lu+5FhdtzXiR5Vmx2yJQS+G/Q8Wrxa5s0vXOHMk1NIsiA3XiHZE25K6m94HQ/OPj1NLW9z2+eGGTySCXRF5EYrjca8tmoO02cKvPH5y1x8aY5QUqM0V0c15EBgcBPBO88JCIXF2TqHPj3Anke6Caf1Rtfq5V4+nufjWR6FqSonvznJyW9MkJtcvynj0htXzmtoseFtc6yD+b70frvWQgPhbzOqOYvnf/M85XmTg5/sI5IOys2XhC+XxsqxXHLjFY598SqnHp/ErrmMvp1l54PdIJZak2z+MFZt2d6YlevXzPuB7/s45vL3sl4rFs8J2j4IKThhr3Vt3/exqyvszRqlwp7rc+6ZaXzX566/t5WO7fGge7gikNXV9qayaHHu2Rne/MIVFi6XiLUbFKZrSIrU4Oas/UxCBHyPB39+F4NHMwghyE9WOf/cDDMXClhlZ02HRzWCRqaDRzNsub0NNaQQimsc/cFBLr40u2Hp9JLTszhaZt+jfex+uDtoaqlIjfYtS4PUaPfgeniOTyVrcuXNRU59cwJrk8bAvhf0I6wXbW77kS1suaMNLaws2wGWRVvnRoq8+YUrnHtmBj2iUJypEkqoWFVnU3vjWh4nvj5OacHkjh/dQu/+JLImLbfuaYjDmmWHsXcWeePzV7j65gId22NUFi2EEJgt7IeO5XHmySnyk1UOfXqAHfd3EUoEvbZW2RvHx7VdsuMVTv7VBCe/OUlpbuPKXt8PPn9pLgbtpG6sNY9ZdpqO1lJ7k5sF4W/waYHXCocfiLM4bdM1qPP6E/l1T2mKLpHqjzB0NEP37kQjxSVj1RyKs3VmzhYYezdLYbra9NoVXQpC9AjMit1S5/NIWkOPBCcHz/MpL9ZxWnSWNoIRU5s9Y1zHozRfv07xWNYkYu0GUuOkXVqoXxfeE1LAu9GMwJ+sl+1gE1+Lr9B4be++FAOH0qT6Ag0Gz/Wp5iwWr5YZeyfL3KViUJXQ+IxYh4Giy/ieT3G2tqYyczip8dF/uY89H+lBliUWR8s88R9OMfZONmikucE8kmRBKKFy9LND3PszO5p9d771q6c59oUrLTmZsiYRa9Pp3Jmgd1+SVH+kIWsfnBhqBZv8VI350Sqz5wtUF03qRbP1UkcBRlShc2eCodvaaB+OYsRVPCcYk8lTea6+tRB0FXcCkkk0o6OFFHx8anmrJRGxpbLenr0JBo9kSA9E0SMKdt0lN1ll/N0s48ezlBdNfDcg8cY7Aqff8wLj2nojQZlkX4TBw2m6diWIthvIahAVLUzXmD6TZ/xEjuJMrSVhMgiq2aIrtJuq+dZKuSHgQcU6DOSGwKFVd6gsWq13W/82Qg3JZIaCas/OHXHCqaCZoVV1KczUmD6dZ+x4ltJsbYVkgkwkYyCAWtFqqVQ61mEEKrsEdqG8aN5w48XrICCc0JoVNrYZiHdeO65qKDh8SJLAx6c4W7/u2pIsiLTpqI0T/kbPJcmCaLtB/y0p+g+mSXSH0MIyru1TXjRZuFxi9J0sC5dLTVKqEAE5XFElXMejOFtbc40mukN88t/ewtCtgQr2xMksT/3nM0yfLWw6/yVFEG3Tuecnt3PkB4aQZIFjuXztl09w8q8mWhpS1ZCJdRh0707QvSdBsjeCEVVABI56NW+Rm6gyd7HI/KUS1ZwVFCa0OpUb31nXngRDRzNkBqMYMRXbDNbmxPEsY+9mKc3V8dwgyhzrMFA0Gd/3qWStVe12InKSipu//jISRNsN+g4Ee0KyN4waUrCrDtmJCqNvLTJxIketYOF7wdjFOwwkWcJ1PcoLrc9PPaqQGYwwcDhD5444kYyOpAjMskN+qsbUqRyTJ/OU5q+fd+vBiKuEG4rePj5WTuBWBXVvc82fa/dXs+pQzZo3dMjayEHa1OEBiKVkBnYEDUQvn6l99zfj+VuC7fd28Ol/f5hQUsOuuzz3G+d4439fvqGIWM/eJD/4a7c2tTiOffEK3/rV0zfktW8GbbgH37RwKzW8wndvuPR7+B7+NuPAJ/r41L+9JVBWLtt849+d5NQNtnzYdk8H3/fvDhFJ63iOx0u/P8Lzv3H+pt6nhIQuRTC9Ch43ZscUoaEIlbr3weyUQGJv5F7OVF7G49vHh1GFjiQUzBu+X4EhhXF8G8f/YNWfaaWHlNrFpdo7H+hzWsVGDs+GLDRFFbT3qmw7ECaaVNh9a4QbKA76Hv4Po/9QuilkV1k0mTiRu+H038r0IQQnzpa7cLYI37JRuzPvq0fYzYJxYAfh2w8Esr8bQRJE7j1M+I6Da/+7EETuP4qxa8vNv8lvB4Qg+qHb0bcNbv7SkEHiMw+jDfas/QJJEH/0PpTO1htN3mwoQmNb6CgROfm+3i+Q6Nd306FuPh7rQRdhInKKkBRDrDCxEjJhKU5ESqKIILKjCYPtoVsJS99+HqNAMBy6BV1qjft3oxhsFGAA5KdqzJ4v3LAwnVlxlqMgQtyQBpBAYEgRInISQwp4WqrQiUgJwlIcGQWBRFxpp1ffQUzJoAoDEI3vLLnqO9NEiIicICTFkJCRhUqHNkiHNkhYSiAhIyGjiRAhKdb8nUDCkKJE5ASKCCKrughjSBHCUgJFaI3Ha9yvlEBtvE5GISzFm/e7HmShBnNJTqIIrXHN5WcXCBSh0akN0a4OEJYSCCQkZEJSjIicRBOBTpCE1PydLgK557AUo0ffQVLpaI6lIjR0ESYsJZpzSBEaYSnRHDcJGUOKEpJijXGTGverEJLi141vWEo073c9hKU4Q9o+duq3EpMyzfdGpeSG71sLG84mx/EpLDrEkg6LMzY9W/T/4/n776F1RBvhSQhC5rXCjXvqakhepdNg3UgIuAUIQwuMpOcjNnM2vo1wC2X8Wr2FTqQCORHDt9ZJhfg+7nwetwX5+b8e8HHms7jlzU+AQpZQ2lIIYx2dIB/smQW8+s1R8H4/EAhCcmzDzWKz9+tS+IZP/ksIywkG9D1IQkYRKnPWKDPWFQSCbn0babUb3/epekWu1t5DCJmQHEMS3/657wNVN4/rf3v0U6JtRvMwZFWdVerBrUKPrlDS9n3MTfg1K5FSumjTBnB8C9OrMGWOEJMzJNVOZKFSdQvMWldIqZ0k1U58fBaZpOQsklK7CctxVKEzZ41ScfMMGnvx8bF9k1nrCrJQyai9jY1dYcocwZAj9Oo7qbvBep80R4grGVJqV2OcfSbrF9gaPkzdqyAh4eExWjuFIlS69C3IQsX1HUZrJ+nSt6BJYWRkal6ZKXME/5q5qAiVXn0nmmTg+S5z1hh1r0Kb2o8mhdGFwZh5BgmJtNqLj4csZKbMERSh0aENoggdSUhcqZ0grrTRrvZj+xYVN8+8NUZcaSOtdDUiWhoz1mW69a1E5CSmV6XmlliwJ+nTdyILFSEEJWeBmltmS+gQeWcWXQqzaE/g4xOTM3Rpw4TlOFPmRSyvSoc+hECgCYNJ8wIl9/qu54aIsMu4HQUFVRjk3DlK3iIxKc2Atpsz9Vcw/db7aW1sFfyggWi54FJYdIjE11+UqTaZRz4do7tPxbJ8XnyizJl36/jAvsMGdz8cIRSVmBl3+NZfFMlnXT71uQQLMw5b9+iEIxLPfL3E+fdMuvoUHvx4jI4ehblph2e/XmJ20qGjW+FDn4zR1atQLXu8+K0yYxct7vtolLYuhVBYYmrMZmCrxitPlTn1dp1te3TufSRCPCWzMOfwxJ+XmJ9efyHqhuCBR6Ps3G/gAyfeqPHasxVs22dgi8b9H43Q3q1QzHs8+ZdFxi/b3PFgmGRaIRKX6BtWOfZilVeeqhBPStz/aIwtOzSKeZeXn6pw6ayJHhI89IkYW3bpuI7PO6/VeOulKrfcEWLHPp14QubKiEn/sMalcybPf6NMe7fCQ5+M0dGtUK95PPWVEpfPWRs6oHbdC/ZvOVAjXeqU3CpkVdC3P9VU4/R9P+jkfjPbF7jBYvbqFn6LpT9CVRC6BpKEUBX8Wh2v2hAj1FSkcAhkCd+28UpV8H2kSAh8P3ifEHjlatNpkRJR/EoNe762OsokBFIkFLzH9/EqNXx79dwRuobQ1eA6gJyM4cwv4haXHQihqQhVAVkO7te08MoNIThZRo6FQVECXRrbwS2W1412iZCOaDw3khTcU6PnjjB0pLABQiyPSeMZms/uebjlKjguCIGcimNPL+Bd66DJElI0HFzHcYP3XAMpHAIBXqUWPEcqhnV1Mvh7836NoM+Wpgb3W63j183l7yoSCsYF8JbG5SacqhShYkgRPN/D9uv4DS99yYD7vofl15ubiSxUVKERuDzBCVRCQRYKtt+YW0ioQsPyTdbz+m2vzrh5FtOrkFQ66dF3sGhPogqDtNrDaO0Uda/E9vCtJJR2ql6peV+GFMXzXSy/DviN6+lIQr7ufhWhNk/24GP7Fo5vISGjSjoSDc6R72D5dSQkNClEwZlf5fAsRRtkFIQQ2J6Ji9P8nSLpzVO641vY/vryByubf2phpSlU1yrUkMzAoTShRIOf6fosXG794JBR+5i3xsg50wgCzpMsVHzfQxISCaWNSfM889YEstAYq5/G9k0UoSELBd/30OQgqlN2c3i42L5F3pnF8up4VMjaU3h4TJsXATCI4OExYZ7H9k1koZBRe5g2L1FyF9kSuoWonEIgMW+NUXULbA/fiiFFcX2HafMSnu8yHDpIWE7QpW2l7OaQhIwkFBShNedfc2xFmLCc4FL1ncZcAV2EEELC910iShC9yTkz5OxpLL/OrHUleJ0UBgSe75BUepFR8HwHH5+Km6fgzOPhsmhPElXSTJsXV/CMBBU3z0T9HD4Qk1PoUpiR6jHCcpwefTuu72L7JuP1MyTVLhJyOyU3S9UtMFo/TZc+TEROEJbjpJRuym4OXYoQluNrOjxtSh+ub3O2/hq7jNubvzf9KopQkIUKN83hARJphcMPxLlyukpbr8bsuIm7hr+w/6jBtj06f/b7eUJhQXbexfOhZ0Dl+38yxUuPl7l8wUTTBPVaQOga3qGxY5/B179QwDJ9cgsOobDgkc/EqVc9vvHFAnc9HOWxH0rwP35tEdP0uHTG5M3nKxy4LcTHvj/BF347y/5bQ4xetEi3SezYpzN22eK2+yOMX7b56PfHmbhq8+xflUlmZKrljU9ufVtU7no4yp/+XpD+8bxAuCuZkvnsTycZv2zzlT8uoOmCYj74rPZulfs+GuVLf5Dj3deq1KrB7+/+cJTeQYVvfqnItt06n/nxJL/7qwtUSh5T4zZnj9fp7ld56BMxxi5ZDG7VaOtUmJmwuf9jMZ79eomj90Y4/nqN2+4L09Gt8PUvFIgnZQrZzatlsuMVXNtDVgPBrW13dTB9toDTQldiSQmEA4/+0FCz/Ud5vs7kqfxNJaz6toMwdJBEyzXL2pY+og/ejpsvIsejeKUKhW+8iFeuoG3tJ3LrPlAVhCRR/NYr2GPTxD9+X+B4SBJS2MC8PEH5+WP4lk348F7Ch3dRP3eF4pOvgu2AEOhb+4ncfQihKniWQ+3YSernry6PUdgg+uDt4HuUnn0DXI/I3YcI3bKL0tOvU339BAD6ziEidx7Eq9SQQga+7VD4qxdw80VCB3Zg7N2G0FT0rX3U3j1H8Rsv4tXWjpJE7jyINtCDb9lIsQj2xAylZ17HdzxCh3Zj7BgM7rdSo/jNl/Btm9QPfQyvUkPoGlI4ROW149SOn0PoGtF7j2Ds20bxiZepvX2m8WAS4cN7CB3cGZTuVmqUX3gLr7TkxAnkTILYQ3diT8xQee0EcixC/JG70Qa6yf3pE1hXAqJp9N7DqN3t+K6HFDZw5nOUnnwF33aI3HsEtasNKRpG6+uk+OSrVF8/cZ1TeaNQhEqnvgWBhCwUxuunyTtzhKUE/cauRprBY9GeZs66iiQkBo39hKU4tm8SkuNUrSJxJUOPvp2R6lvYfp2k0kmXvoULlTeaTsG1sH0T2w2cAqexkQAYcgTPd6h5JWy/Ts0rEVMyVK0SqtDp1rchISEJhdHaSYruAiEpRp+xC0WoSEJmzhpl3hpFFioDxl5UoROSY+gizKXaO+TsaTr1YeJyG4qkEZMzTJkjTNTPokkhBoy9xJQ0ZyqvUHULAAwYe9BFGB9QJY2yk2PcPIPv+/QZuzGkKLoUOAFXaieYta5eF3FYQna03BSiTPaGGTySYfFquUkY3wiyJrHzwS4OfrIfqUGQL0zXmD5XuIFv3l+R4hAoKHRqg4zU3iahtJNRe1e9bum1YSlOXM5wuX6CHrEdgcDxLcbr54jISXr1nUz65ym6C/j4TWdyCbZXx2tEc/CDb1wIiSXn2cdHALKQaXbZxcfzPUyvFjhbeAjA8qqM189i+3UE0roOplj1U5BQ2puRkiCdKxpPuny/AolObZiSs0jZzRNX2gEouTnq9SpptYcBYy8Xqm+uuM5yStb3PWzfbM7ppZ8rxxJ8JCEQQgp+J4LXWH4dDwfPdxvRTJ+8M8tE/RwgcFk7+2BIYSpekZpfXhV1XZqDNzWlBcEelJ+3UTSJ0XP1NZ0dgOlxB1kR3PVQhLderrIwG6Q+dh80KOZcnvn6aoVmWQkOsaffqXHm3WXjnm6Xue2+MPPTDt39Kuk2GT0kIUlBzjPVJrPvqEFnr0osLqHpAsf2OfeeiWUGFxi7ZNH5IRXPh5HTJgdvC+HYPm+9XKVW2XhTzS245BYcHvh4lLdfrvLesRqeBz2DKtF4EIVaGSFaknW4fM7kxBs16rXlh7zt/jChsMSjPygRjkoM79CIRCWqZY9QSGLfh0MkMzLpdplYXMJ1fcYuWVw6a9I3rHH2RJ2Dt4fQdMH4FZtDd4a5/f4Ib75YJZ/d3Gm5emyB8oJJekAJBNq+fwC77vDeNyaoFewgUuMHFkqIQCtJViUyAxF2fqiLvR/tJdW7XMJ96ompG+qu2wrkdBy1J4NXrHItOUhoGkJeDm97lgmeh5BllLYUpadexV3Ikfj0Q4QO7qTy0ts4U/OUnn0D33aIPXwHxs5h7LFppEgYPI/C155D7Woj9shdVN85i7uQo/zcG+B7yKl4Uy1YioaJPnQ75vmrVN8+E0RNljZi30eoCtEHbkXIEqXnjuHXgwVb/MaLyLEIQlk2ikKRUToy5L/4OPZcluT3PYSxc4jaexcIHdhJ7cQ5zJFRUp97jPqZS+s6OwBCVZGiYXJ/8g2kaJjEY/ejDfRgjoxiXRoLHA0hSH7qQ2iDPZiXxpBTcazJOSqvvEP4lt2E9u+gdmoEv25S+NpzSInoqvtVOzOE7zhI+fk3sS5PgBJE0YSmguehpOOEbtmJM71A9a3TQRovXyT3xcdp+7kfBHnZSApdRU5EyX7+G0hhg8SnPoTS1YZXrWPsGKLw1WfxanXSP/YJ6qcvXh9BUzWEcv0c2AgSMiVnkTnrKl36Vrq0rRScBXr0bdi+yZXaCSJykqHQfkrOAiE5RliOc7l6HICdkTsAqLpFZKEQlZPknVkyag8VN7+us7MSMgHfI2tPYfsmEnKgC9Mw1K7vNKMrkpDJ27Ms2pP06Nvp0rdQrC5g+lWmzREc3yat9tCu9pOzp4nKKcJSjHPVN4jICQaMveSdWVRJp03tZ7R+kppbZlfkTrL2JC6Bo3Wh+gYHYw+v2iQUoaFIGiPVY2gizNbwLczbYw2uS4aL1bcRCLaHbyNrT63r7ABcfm2eo58dIhTX0CMKd/zdrQCcfWYas+ysaW8UTaJ9a4w9j/Sw++FuYh2BcvCSCnlxHcX1tTBnj9GhDZLRe6lRYaZ+EVMy6Q/vaUSvLIQsYwkTX/gMRQ4y74xTdwNHvk/fgaZGyDtVNCVMr7EjiIAIF1dyQciUKdCrbsdQo0yY5/Eb3+WS1XdxmLdGaVcHaFcHsP06ZTcHCNrUftq1QWpukbpXxvVtAmvjNyNxC84kvcZOfN8l78yx6E1eJ0VgehWKziKDoX34vse8M47pV8mIXnr0bYhGBAeg7Obo1rZiSBEmzfNU3AIpo4eInWzct09CbiOl9iAhNcjNPp5wqbtl+vSd5J05ZqxLeLh4KzRpam6JqltgS+gWfCBrT2N7JpoIMaDvRpEM5q1RQDSjip7v4uGSd2bp0rcy0EgbTprncf3r9xbTq5GQ2xr8qyUXUiYqpfAb43Yj2NThKecdqmWXzn6NZJvC5KW1u+xeOmfye7+6wIFbQ3zfjyU49mKVZ79eQpaD0OSaPr4PpcI1JZYSmHWfV56uMHYx2ERM08dx4bEfihOOSDz9tRJ9QxoPfyoWhNTdpaaC4DaiMoKg6emzXy9x6azJkXvC/P1fyvCF385y6ez6XJbsvMsf/XqWXQcM7vxQhF0HDP7s93NIUkMddp3oRrnkrWmH33m1yvHXgkXr+TA37XD3hyMcuTvMX32xgCQJfvhnU015fs+lGVVaSh35Ppx6q8bCjMOhO0P82M+nefxLBd54oboh5WRxtMI7Xx7l3p/Zjh5RibYZ3PPTO9j/8T5mzhcoTNewai6SJFANmWi7QWYwQqI7RCipoWiBcJ9re1x8eY43P3/5pjYdBXCLFdxsCTkZDdInDQhVpe3BjxLZvT94XaXE/Df/kvrkOADOfBZnLotXqmBPL6B2pEGRUYd7MHYMIxQZrb8brxI4D75tY41O4+aKwXU8f9Umfy2ksIEUCWNeHFsR2aDZrdLYtx0cl9yffKOZzmpijSniTM9jT8/jVeu4+SJSJITvBOkrbaA7cBI8L0hnbQJ7ag43V8Sr1fHKVeRkDKFr6DuHUXvaEbKM3JZEhINUpFepYV0exytWsOcW0XcMBjLx69yv3J7CNy2syxOr01NaoBgbuesQXrlK6fGXr+EyrfHgPlijU7iLeXwzjF8zkTQVN1vAM0307QN4po1bKOPVVp9mhaKQvv9hYvsOBc9RqzD/xFepjV7ZeHx8i7Kbw/LrFJ0FUkZXQJqUY0yZI0FqyM3h+R6aFMaQotS9CrVGeqniBjpTll8nb8+SUrux/DphOcFMbeNrQ5AK6jN24vteM5Ww8jQc/JSazoPt1am4OSy/RsGZp9/YDUBEStChDSILBV2KEChMiUYaQ5BWu9FFmLpXxvNdXAS2Vycut2NI0XVSUKu/I8/3KDoL1L0KvuQHJ3BkbL+O53sklaAlh+lVcTbZXKbPFjjxlXGO/OAQqiGT6gvzoX+8m8OfGQzszWwNp+4hKQEZOdYR2Jt4V4hQQmuKndo1hzPfmuL4V8Zbll4AKDrz1NwiRl8nIqqhWBkW2mr4BRMMCTtbxAj34Js2U7UJ9LYUfiiFKKtcunAcSVbQhzpxzDpKpINCyMMrFvBkH7dqYMghbElmLH8Jo68DXe3HHJ1ncvY83gonOO/MUnELSELC9i1838MnmAu2bzbThhdr7zScCI/R+ikc32LWvEJWTCFEEGUK7+jCXizh1m0800Y2VJAl5pxxNC2MZzqITpX6fJEx7Ty+64E0ihOxUeUIFbfMGOcQkoRt2cxZV7G3y9RnsnjWKI7qUDHKWMoYvu3hKg4SKmomxuz8VfL6Io5koRghFplFqBKKtdQUVTBVuYiC1oz+xOQ0Va/EpHkBH5qRqpK7CMCiPUkQ0bEZq59GESo+YHlrO7YLziQZpZsd+q2EpBhppYu4nCGtdDNjX26m9FpFC720BB19OoUFm7YeDUlaW2W1Z0BFlgVvvVIlmZEZ2qGhaIKRMyYPPhbj6N0hroxYRCISC3Mu5jq6ObWKz+hFi64+hZNv1VA1ERTO+NDZo3Llgkl+0eWuhzV0Yylst0LGfsVn6YagZ0ClmHd57q9KDO/U6O5XN3R42jsVYkmJsyfqCAEf/nSMcFRiZsLG9+COByO89lwFw5CoVjzyi+71F27g3Ik6fUMqrz5TwbF9ojEJ34eOLoVaxWNm3OHofWFiyes33pUfJ8mC3iENz/N57bkqfcMag9s0jr1UXaLArAmn7vLOl0dRQwq3/tAQoYSKFg4aB26mbr1U2lcrWJx6fJLX/ugS+anWT1stw3FBEviuh9bfTr1WxzdtQCBHomjpgJXvKApCWSZPS4aGaEQSJF3Dtx3kSJjY/bdRfv4YtdMXiX/07mWnxvdpdqFsJSPX8F6b0YWVkCScmQXcUpXIvUco/tXzTQ7RevAte8Uk9YOIUd3CujpJ+OhevGqd0vPHsKfnN701yQgcGSFJCEXBd1zU3g4itx8g96dPYE/Okv5730czrO26+M6KebpJzx3fdhqco+uLOIWiUD9/FSWTJHRkL+WX3w5SgOt+GI3vc+WHCNxcEWdmAa2/G2t8huKTrwak8Wtep4Qjy3OgrK2aA+tBalSLAM10ge8HKQQZtfEaGSEkXN/Bw2ucIAMnUBJL37nPgj3BtvAR2tQ+bK/egpaIoEMbIiKnuFx7p1nSa3v1ZlUPwP+fvf8Os+PK7zvhT+W6+d6+nRMaGUQiCKZhmBlych5pRhpFS5ZkS3KUtLbfZ7376rHX9j7rddDKfmVZclhJo5E1UZrASRxyOMwJJAEQAJEajc7h5li5zvtHXXSj0d1ANwhOkPV9HhJAd9WpqlOnzvmeX/j+DDlG3S92HlNZDlpWJW3ZdD9k7qUd1JiwTpDR+hgx9gLQCmp4wiGjdtP0q0zbk8u770ZQJq3mqfshU/YZ7HBt7NVqiJW0aLHyaVhhEztskVbzNIMKk/apVYv6enCaPs/+8UUUXebwR0fQ4wpGUqX/tgz9t2Wufxedb6NZtHn1L6Y49rnLy0WCNwuBiOKVDA+/UEHrzhAmZLy2g2KYSD1x5CAkCAKkoQT0JqKNj2fjCgsJBVlysRcLJI/uwhMevuqgJEy0VAavWEdO6EhpEzGYQGpaoElr0raj+1iRb7li3fOEsyqdfSU2RywTU0GAI1bERFNdCZSYhpqJ0x5fJL6jF7fUJHQ8pJiON10m1p1GDT3k7jjuUh1jIEsslyR0fITno2biCM/HeqlO0HYROQlFTaCnTMRkkfhYN26xAYFA02L40y56bxpXCKScjii5JAb70bJxAiuKG1VTJqHlUn15HMdZnfAQimBVILG4yjJ0tXXU78SdXQ+WaDDunGBI200gfLJKL3bYYtY9z4I3seWU/hsSnsAXnHm5Sf+ITrsRbJg53NOv8vBHkmiaRLUU8PhXGzhWRF6+8pkq7/hAknd/XGZu0uUbn69jW7A059Oorb7hdivkL/6kyrs+muJv/kYe1wl55jstJsc9vvOVBu/5eIq/sVNnfsrj+AsWriMozPvY7ZBqOSAMBFYrpLDgI0lw2+0Gew+bIODiaYfXj11/0U6kZN77YylyfTqtqs8jn61TKUWS6J/9rxUe/nCKv31XjGop4JtfrFMtBdTKQWSRuaZzHv3LBu/6aIqf+bUcYQinXrGYmfJ59gmLj/50ir/1j/PMXPZ4+akWjidRLYfR/bdDluZ8PFewOOsReIKhPTr3vSuBokBpKQqA3si9eDWshs/znx5n+rUSt398hIHbMsQyOlpMiWTk5ajEgwgiJWzfCXBaPq2yw/RrZc4+Ps/C2fpNZVxsFsL2kLMp3GJt0/EbaneO+D2HCBsttJE+Go8+jwhDhOuidGeJH9mHsXvbcizJRpAMHbUnh9qdQ04n0Eb68RdLBNUGzvnLJN95F1Y+AwKCUhV3egGEwJsv0HrhJOkPvZ3EA0dpPnUMSVVQ8lmUbBLVyaEN9+MvlTa+uCyjdGUIyjWcS9NRXI6h35A86dsGid97GCWdAE3Bm1lAihmIIEAb6EYfG0DtznIjZicn46j5LEo6idqbRxvuw18s4U3NE9RbpN97P874NCgy3tQ8oeUgghDn4iTtV06R/sDbidWbWK+dQUknUXIZ5EQcbaCHsGVd/9lVFSWfxZ1ewL08CwgkXds4+20LUCSNHn1k2cVT8RYJ8Cl5M/ToI1GRYzmNHURWndD36daGGDB2EeKTULLLZMQKG7SDOv36Tibt1284Qee1QQaNPSy6E8tpzo2gTDus4QqLQWMXjrDRJIOyPw9IqJJGjzaKISfo0UapeHMABMJDk0xyWj89+ujy21QkBUOOMe+MY4etjuUnIqcxJUUrqFH3i1F2DioBHoacwJTjaJJBUskhRLgcML0eovTiOGVvnmZQWXYl3GiBaRYcnvi9s1x6ocjhjw7TuyuFmdbQY2pUeqFTmTwMRKfcRKQk3SraTLxU5Ox3FyiMN95UrSZnagkRhAT1Ns5MAeF2CHxUMyHasStl7AuzkWfA86HzpzU+h3B9mq9cAEAEIZKmROZ5WYJZgaTKWOdmIhJt3TjzNSRg3HptQyvG9eCWmwRNByVhYPRnQYCzUEXWFPyGTWA5KDEdNWkiqypKwkTWNQhCvFIDFBlJU/Dr1nKZJ7fYwG85xOI6Rn8WEQichRpKXMdzfELXR4nrKAkDWddQkyaSpkTf/lIdNWkSyBJetbXG3dYMKly2Tm75Oa+HRljmgvNKJ0hfIiDAvyqWaCu4sdKyAve8Lyo416oHnHy2sa5L668aYrsHcBerBPW1g1TNxAnaDsLb+kepZhNo+RTW+OqidfF9Q9hTRcL22iA1NZsgaFqIG5QoWA9abwZZV3FmosUnNxJVJs/0xzBTWlSAVIpkze2GR7PkUJ1pU7rcfEtJztUw944imTru5QWCWrSDljSdvo/+BOkjdwHg12vMf+FPsSYvYe7fSeLBozgXp4hlu2mfH6d1+hxIERkwD+4mbNv48wWE5+FcmCJxxwG8Yhl3eh45ESNx+37ar59FMnXidx1ETsYx5DiO06D1yim86QWMWBrt4A6U4Tyh7WK/fh5vdglj7xgEIc6FSZRcmsTBfbROnEHOpojdvhc1FkeIkMC2aT37GrKhkxgcoX7yFKHnYu7bgQh8vLkCqffej9qTI3Rc5JiBv1ii9uXvbthXqfc/gJJLExQrSIaOfeoi7uQcqArmbTswdgzjLVUIGy2Cah1/qUzsyD6ci1ME5Rpqdw59+xDtV8+gbxskdmhP5KpCEFoOzadfIaw1kTMp4kf2onRlCWoNrFffIGxbxI7sw700g1+soA33ow33Yb16BmP3Nsx92zsuP4FfqdN65lX0sSEIBc75y0i6RuzwHtyp+eVnuZIFJsdjWCfP0Xru+PKzSppG7wd/jMxd90VjoNlg4Ut/Rnv8/Ib9I6PSrQ0REJBWu3HCNkvuZXzhIiHTpQ2QUXvxQpslbxKnYwHJqr3ktEHc0MIOW3ihQz2IrG15bZjt5mHOtJ6hHdavO5bz2hA5dWBZtDXKxLmIFTYwpHiUEiwbFNxJmkEFVdLoUgcRhKTUPFbYYsmZIMAnJifp1cc6LoEyIKh6iySULCPmbR2XWESYZuyztIIaY7FDqJJOSIAq6dT8Jabts+S1oWX3FAisoMGcc5Gc1o8vXGp+ISKK2igVfwG1Exh9JdtJlXQW3QmW3MvXff6rIckS+W0JurcnSQ/EMBJqNN+ISGn9ynxTnm5RutzaVDLFX+OvPjQM4nLqhscJoBlW1pDwN6W0rKgS930ww9yEQ7sesDB1Y0YryRBLqpFPliiWpl1fu3iaie7I9+c0CIM3v7O7FVDSMRIHRjGG8rTPzaL3pHHnK4SejznaQ+vsLMnD2wgaFq03Zojt7IdQ4C7VMIfy+E0L4QfY00XM0R4IBfpADmeqgJKKo/WmCeoW9RejSVvLp4jvHUIf7KL9xgx6fxZ7qhDFoPSkaZ+fI333bpyFCtbFBeJ7hwhtB7/cwhjpxq82EV6AM1vC3NYbtdmdwr5cQOtJo/dmsKeLtE5N/SC79brQR/siglJtRi4uNkF47juC/6UXibdNXGEhEPjCxQ1tVElHkww8Ef3dDptk1F7qfglDjhEIn5iSwgoaUYoyIQJBTE5R8KYIhEdS6SKldF3VtocbWp229eV01tVtmwQiIKYksYLmmraL3hS+WBnn+q5RUg/fQ/WLjxJaNvrYEKl3v43Sf/nChpauiCRo1L/+vR9dxXNZIvHAUdSeHI1Hn0P4AYl7D6EN91P57DeWpQpuhvDc8ltFYcS8DU0yGLdeu27Q7vfrfnbF76QZlFl0J1FQGTX34wobO2yR1wYZb79KQECPNkJeG+JM69kt3beEzKi5H4BZJ+rrQWM3uhRj3HrlpnbWf42/xmaRVwbZaawIu14J7r8SZH0l+9ITNq9bT2OL1S616xGeTVVLb9UD7n53hpmLNovT19d+AdB0mbHbU4zsS9IouUiyxLNfXFhzXLprG129e7FaJerlCZrVWTz3B1taIDbWi1eso8R0EnuHcAs1tL4s7mIV4foI1yNsOViXFgktFzWboPbsWZIHR7Gni8R29hO0bLL330bQslBzSYK6ReLAKM5CBWe6iJpLLl/PHOvFmSuj5hLE9w7iFeoYg114xTqh6xPaHkHTwr60SOh6qOkYlWMXSd+zm/b5OZKHtuHXWqTftpfQdlGzSfx6m+Qd27EvL+HMlZfVT39YISdMJFXpWLE2qcWDFOmW4JBUuvCEjRPKxNQUvnDR5RiaMJCQsDsS8leCPwUhgfCRJYWkmsMX3nLGxJWQ0picJCS4qm2LmJq8qm2z03b7mrYFgfBWtR0uZ2Osfg9hR28ncd8RhO+j9XfjjE/f2K33Q/o6dUNCllmVqbguQoFfrGDu2Ubi/iMgSWhDvVjHz3HdoLTvM+Jyhj5jjIScZdI+9QMnOwAhIU2/QlrtQTGiMgeGHKfgTEcxSprGgLEbECSULBV/ccv3LQhpB3V69FEGjd3IyCSULAvuxP8UZEdPavTu7yLRHcN3AgpvlKnP/dUreSNJkB5K0r0nh2Iq2BWHueMFfOv7Y9nfCPWwzHnnFSBSqB7W91AJFqkHRQIRoEsm3epQZIm9ji7Uergh4ZEkUFSJ156q0z2or1st/Vq4dsiFl2vEUyrTZ5uMHYqyqa79VopzJ2nVF0jnRugePEzfyN00qzNUChewWkXC4M3V8LgZ+NUWsZ0DKAkTd6mKmklgTSwSOh5qPoWWT+OVGpijPViuT9CwEZ6PV6wT29kXPf9SjfjeIdoX5gAJJWliXV5E60qhpuN45ZXAR7/WJra9D0lVIqKViWONLyC8gNiuLO5CFb/axhzrxb68hN+ISIFXbpC4bZjQcfFKDeJ7Bqk+fYaYpiJrCtb4Alp3GllXsadWAmEliQ0Dz28GihLF9960m1OCsGUjqQqSIm9qOnVnFqh/9wXkZh3Zl6gTxSt4wsWQYvjCQ5U0oryVKKiw4ZcIRUgoigREVbKFELihRdghPxIygYh+Vw9KKKjXtB3HF+512vajtkWUgLy27dUTiV+sUPv6k2gD3SAruJdnl909G8E6cS6KJfghW3eGt6ncdlhnaSHg1KvODceXc2ES0bZR8lkA7Dcu4c0uvvU3ugUE+LT8KoVwupNa/MMAwaI7QTuso8sxbBGwFFymFdaRkLhsvx7J90tQ8RZu+r5L3iyOsDDlRCQ46s0uZ6/9VYasSuz/+E52vXeU2nQjqkJfdf5KEp5Eb5wHfvMOtIRGc7FNu2hROFf+gRMeT9hUgyiOcUTbSyuoMeGcXEW2rbDJTuN2NMlcN519I2xOClNEivsiZNMTre+GVBYc9t6TZfpsc93zwsCjVZvFtao4dp3ugYPk+vaSyo1itYosTh/Dat44a+VWwp4pLROS0PWRDZXQjWZvr1AntKOq57KhEdgu/muXEF6ANVnAXaohghAtl8SaWMRdquHMlZH1SLhOUhUkWSJ0VwaUPbGIu1ABAaF35Xo+kiThLlYJLTey0mgKoe3hv3oJAOviPM5sCeGH6L1Z2hfn8Qp1vGIdSZUJHR95YjFSFb4qS2agT+HQAY1Xjrt4nqA7r1Crh8gypJIy5UqI60bCkPkuGVWVCAJBrS7o7ZFZKoRUOoKLqgIP3GewVAiYnAroyskoClSqIT3dCq12iOtCvRHSk1cwO1l1li2QJTAMidmShD7US+i4+MXNiYyF9RZuff0JqN1xGbnXqG9eCTZ1rx2H4po/O1iv2F5b1G5J28sIBf5CEX+huMEBa7GVY7+f0LQrquzh5sivH0SxR5Nzb/m93SycsMXSmywS+VYgwKfqryWHAkEzKNNcR7F2qwgJqPsF6nx/598fNIy0zuDRHiafm+fkn59FCAicv5qxRbntaWJ5kxd+7wSF8xUIwbN+OEJLrkCX48thAVdDINBlMxJz3MLmb1PCg/OXHZJZhdlxe7NiuCiqRH7IpFH2SKS1dS08qhYn17ubbPdukCQalSlmLnyPUAR0Dxykb/RuLp/5xuaf5lZAgCT0qK6T4qEoJoFXRtFNgkYbWTeRNQ2/1ew8kIyayuI3qgTNSMpfhCHW+TlCy0NP5whcB9UwEWFIYLWjVGJ8lHgKEXjReYCsm0iBhnCikhzYK4NPdEiS6Jj8hR8SNGyQJULPo31+bhWxAQjWCarOZmQO3KZx7oLHyLDGQJ/Ci8ccUimZt91lYNuCU2+4qKrEh94XY2rGJ98l8+3HbY4c0mk0Q77+LSvKJldg324NWYJSOeQD74nx6gkXx4VDB3RyGZlqPeTJZ2w+8dF4pLHkCirVkMtTPrcf1Hn6eZvxC9ORpWerGTrLqqWr31+04t4CE8h67dNp/62O3F/32W7yule3tVEb115vsx96B5VyyOhOyOTk76/LbaMxwC16R389Bn44IEFmOMXo2/pJ9MUJvZDi+QqTz80jyRK737eN5mKLmZcXEYFAi6vsfv826jNNZl5eRDEUdjw0TGM+Up8fvW8A1VCYe22J2WOL6Emd7e8comdfF917u1BNFT1xELvmcvpLFwg6dQiTfXG2PTBIeiiJVba5/Mwc1ak63Xty9N7WxYVvTxJ4AUd+bh/VqQYTT86S7I8z9uAg5755Gbdx4zlOVmWG7uyl71A3WkzBrrpMvTBPebxKaiDJ9ncMcfGxKVqFaOOVHUsz+rZ+xr87Q2upTbIvut7EU7MM3N5Dfk8W3/I5/+1JGnMtevblGL1/kP6DeZK9cfZ9ZAdjdYeFE0UmnppFhCGyKtN7oIvhu/pQDZXyRI3LT8/iNj32fWQ7tZkm88cL5Hdl2PfRHZz87Hka8y22PTCIrMlMfO/62bGbRTOoMGYcYCjcTS0oEhJgSgkGtO0Ewl8VE7kZ3JDwxFMK2w/EuHiizbZ9MWYvbay2fDUkSYqCl1MqRjxcd/3pHjhIPNVLYe4krfo8nttc/hALsyfoG717Sw9zM5AUFbNnkND3kLVOcJRtoRgxvHoZNZkhcG30TDeB3cLI9SKpGqHnEjrW8jnNRhVZNzC7BwgcG9WIofSkowjuzkSiqBqSoqIYkXCTkeslDHxEGBC6NooRx7ea+O2N00XXIBS4c5s3NZcqAfMLAfWGQAi4MO7TaAruv1fH8wVdOZm+XgVdl4jHJWbnAvI5mUP7dRQZMikZSQYCcF2YWwgolEI8DxqtkJOnXe44rJNJScRiEkEoMTqskM/LTM34NJuCgb6o/SCMCJiqZlHSceyzkwT2ddyYnbEhmzGMvgFi23dhDg6jJtNRnSbHxq9XsWensSYv4RaXEN4WPghJQoknUTMZjIEhjL5B9K5u5FgcSVEQvkdo27jlIs78LPbsFF65hPC39tHpvf3Imo4IA7xqhdBqL19fzWSJDW8jtn0ner4XORaDUBC0W3jlIvbsNPbsFG7hmh2+JKFlu1DiCUTg45YKCM9H7+4hdeQu4mM7QZJwFudpnHwVa/rysl9TTWdIHTpKYvc+ZN3Ar1dpXjhL69xpgubmxmIqLaMoEl09SkdsdEtdsnlc0TYxTPS+AeLbd2EOjqCkUkiyQug6nTEwgzU5jltYQnhbcI1LEko8gZrOYAwMY/QPoHV1o8Ti0UbF8wltC69Swr56DGzlGlw9BkL8WoWgvWJJUjNZzJFtxMd2onX3opjxSM3aanfGwBT27DTu0iKrJlZJQs3mUOPJzhgoIjwXLd9N+shdxMd2gyzjLs3TeP01rMkJRGcyV5Ip0oeOEt9zG4pp4tfrtC68QevcGfzGVso7vDUYuL2He//OYaySTeVyDS2u0bOvi8vPzKGZKmNvH6TwRpnZV5YQgUA1Vba/Y4i51woR4dFkRu7pQzFVAjugWWijmgqJnljHeyFw6i7NxTa+5WNVbGrTTdyWR+BHfZwdTXHPrx0iDAS16Qb5PVm2PTjI8793HCOps+u9o0w+N4cWi7Hng9spX6wy++oS+Z0Zhu/p5+J3bpw4osYUDv/UXrY9MEjxbBm74ZLdlqI0XqV0sUqiJ8au944y+8riMuFJDSTY9Z5R5l4r0FpqE+8y2fuR7WTH0iiqjFVxSA0klksE+W5Iu2jRLtn4TkBjvkW7bNOu2FHArwS73jPKvo9sp3yphu8E7Pvodnr3d/H8752ge2+O9FCSxVMlhu7sY//Hd7J0pkxjvsXYO4aoTW1h/boBiv4McTnNsL6HYbE3qjcoIlHQS87JLRUOhU0QnlhCJp5UGN1rsjTrborsAPheSHHG5vaH80ycXL8DCnMnCAMPsY5csGvXmbv07LrndXXLvOsDMU684nLhjesvNnfcY3D03kiozWqHfPXzLZqNlUlCUjXUeAq3VkKNJQAJSVZQjBiha6PGk/iNKno6S2CYCBFipHP4Vgticfz2iv9Q0U1k3ST0XGTDRDHjiMAnVFSEEMvkSEvnAIkw8NGzeQKrBbEEvtVaJfsuK3D4qM72XRrf/mqbdus60ecafPxTCbJdkYDZudMuzzxhryGatbpgaiagOy8zPevjOJGS9cysj6pKlMouvT0Kti147AmbS5M+rbbA9wXZTOTyujo+48Qpl5FBlQU54NQZjzCEYilkbiHAsnwazZDhQZWXXnFYWApwXZid99G1SF5+di4g1B2UdPy60fVCCELfQ+/uJXf/O0keuB3FjK27+04dvhO/VqH+2stUX3xm1WKyLjoLRWL3fhK79xEb2RaRnA0E+hKdP91ykcbJV6m9/Bx+4/rpyivXkhn4iZ/H6B8ksCwK3/oK9ddeAlkhsXMPube/i9jodiR5rejfFTROn2D+859etUuXdYP8u95P+va78Fst5j7zXwldh96P/sSq9mIjYyR27mXpW1+h9cYp1GyO3g9+nMSe/VdVqx8lsec26kOjFB/7BkH7xj7yIIyyMd9So0BnDGhd3eTuewepQ3egxOLrj4FDR/HrNeqvvUT1pWcImjd+hmgM3EZi923RGIgnNhwDV+BVyjRef43qy8/i16qbfpT+T/wM5uAIoWNTePQRai8/F9UwG9tJ1zveQ2xs5wZjYC/wAM2zp5j//KcR/lVlbjSd/DvfS+bovQTtFnN//kf4zQa9H/kk8e27rhoD24jv2kfh0a/RfP04ajpDzwc+SvK2QyulXIYgsXsfjZExCt95ZNPE962AJEsc+tQemottnv53r+DUO+RyHa/BjdC1PcN3fvs5yuOrSZxTd7n0xAzJvjjDd/Uxe2yJM18eX/69osnseHgEWZN56t++jF11iOUM3v3P38au94xy4VtRCQUzrZPdlqY+20QxFOJdJsm+OK2Chb8J11jX9gwHP7GL537vOBcfvfnMWj2hIUJ49j+8tibdv3KpRuVSDbflkRlJcv7bl6lOrrzfRG+MvR8a4+J3JjnzlSiEYuiuXh74jTvo3d9FdbJB7/4u9IRGajDB4qkSuW3p5ee9/PTsTd/3tQjwmXBfZ8GbICGnkSUFVzg0gwr+BvW3rocbEp7SosfchINhyohALDOsG8GIK3QPmbz09SWc1kqHp3Pb6B0+Gv1DklBUPbJyiBBZ0XDtOtMXvkvgO/je+iqh3b0KP/PLKRyncUPCI0mQSEocPKKzbYfGE9+2aDZW7id0baz5SYQIO5YVCUQY7RZ9j8CxCD2H1uwlhO8jKSr20iyIEBEESIqK6GxnvXYTsTQbaay06lypG7PsYpFkRBjgtxuIMLqGtTAZlasQIZKiEl61U1QUuPNeg/d8JM4z37Vpt67/wSiqRC4v876PxHnyMYtnv7e2DIhtC559YW1k+9PPX/2z1X16aWJjljs1HTA9HSCAYjla7SYmfSYmV845cer67yh2KKb2Wu4AAQAASURBVBYV9lxecNeBCNEyXWTuvJf4zj1IsowQAuF5iDCIitVpGkiRPL2W7SL3wMPI8QTF7zyCcDf+OCRZIbn3IPl3fQDZMFYWOSEileIgQIiwo2ysRb+XJPSubnIPPISayVL8zte3vChIqoKaTCGpKqmDR8g//AHUbC4q+yDEiktBllctvM7C3HU/QiUWQ+8fJDY0Smx4G8L3EEhIWnTvajZH7v534lfLpG+/k8Tu2wBBYNvImgqygqRqpA4dwZqZpH785eu6NyQJCgtR7TxZBv+tinkUAjWVoeuBh0ns3hdZ3daMARWkqL+0TJbcAw+hJFMUH32E0L7OblBRSOzeR/d7P4xsmKvHQBgpVQsRLo+zK2NAy3WRve8dqNkcxUe/hl/fojVEVlCTaSRFIbn/MPl3fxAtl19nDEidgpQRnIU5xHXeiRyLo/cNkDp4hPi2HZ0x0KlNJkmo6Qy5t70dr1Qguf8wyX2HACkaA6oaVbBXVZIHDmPPTlE99vwPzMUV6zJI9sY4+8jECtmBm/JaL71RprlwI/XptVBNld79XeR3ZXnXb9+LCAWSLJHqT9AuRdYRu2aTHU3TtSNDebxKZjRNqj9BdiRF5XKdwL0B4ZEguy2N2/JYOv3m4rC8ts/88aWb0jbKjqbJjCTZ++EdbHswKriqmsoyoSlfqjF63wCpgTiJ7hjTLy6Q35UhPZhA0WQqlze5+ds0BJZoYAWr59dIVDNKMtksblxaQpYYGDNolH12HoozdcG+YZaWqksM7koQz6jk+gyaFY/CVBSn4tg1KoWo6Foi1U881U+9MknguySzQ9Hkcgt946+97PD6aw6f+Nkkv/z31pGlFwLf2nj3F7p2589NpL91yMwND9taJt2m4Hvwpc80UTWJQ0f0W3+B6+DNvi1vsUJoe4jrpPbIhkn2bQ8S27YDALe4hDV9GbewSGjbSJqGnu8hNrYTvacvqoqu66QPHcWZnaJ+/NjG9x/4OAuzhLaFYpqEroNbLOCWlvDLZfxmndDzkHUDPd+NObodo38QSZKQNZ3U/sO4S4tUnvveluIrJEVFSaWI79hN/qH3o2ZzhI6NszCHVy5GlqlQIMdiqJksencfajKJNXnp+u3KMulDR9F7+2hfukD70nmQJFIHj2AOjSJJEubQKNm77yex9wB+o07zjddxi0sY/YOkDh1FicWQdIPkbQdpnT11XStZMiWRzSv0Daj0DSoszvts0cOzKUi6Tvbu+4mNbQck3HIRa2oCd2mR0LaQVBUt30Ns2w6MvoFoDGg6qQNHcOZnqR17fuP3EwQ4C/OE7TaKGSP0XNxiAa+4hFcp4TeujAEdvaszBgaGOmNAI7nvAG5hkfJTj21xDCgoqRSxbTvIP/wBtFye0HVw5q8eAyGyaaJmcug9vajJdFRP7LokVCJ14Ah6dw/ty+O0x88hhCB14HbM4aiWmjkwHI2BXfvwW02ab5zEXVpE7+0nffgoSjyBpOkkbjtE48zJH5iVRzXUqLaUvXkmLUmsK8fhNlzCm5A+kGTQYiqFM2XGn5heVi0GaBdt2iWb5lKb/O4s6aEkFx+bQo2p5HdlSfTGmX5pkdC//riQJAktpuA7wXKs5mYgr/OcoR/iNG7uI1QNhdAXXPreNPXZlbUx9AWli1UkJVLM7t0flXyZen6egdu76T/cjWf7tEtvQQmia6CgMqzvYdGbXKPDcz1cl/BIUqStsTTjMnZbLCocuon3EAZQXXJQzkbChYnMymUcq4pjVYGI8BRmj1NePANAvTzByO53oSjaDVPSRScwMZ6QMGMSYRjV4XKca6K5w6iE0o1ccboOZlzmSukk1xW0m6tN9KYpEU9KayzogQ+N+mpXj6JCIiGhap17awsc+yapgQBVhUxWRlHB8wStplgTJxEEUfT6RuU/IHqnsbiEYUjISnSObYlV2imSBMm0hK6v/ZBsK7r21TBNiVg8itnyvKjfNpv2Lukaxo4hhOfjL20ciySbMWJjOxG+R/PM61Sefwp3aWF1/IwsY/QPkX/ofcsWADkWI3ngCK2L5wmaG+887Llpmm+8jqzrtC6exV1axKtW1sZmyDJG3yBd73g3yX0HkRQFSTdI7LmNxqnXtuTWQJIwh8cwh0ZR0xmsyUtUX3oOe+Yyfr2+EgjTiSvRcnm0XB5n6fqp6wCxbdtpj59n8ZEv4Vej3aKzME//J38WNZlCVlVSh+8kdGxK3/s2jZOvIQIf2YwhKQrpo/ciSRLGwDByLH5dwuO64NqC4pKP1Q7fsvgd2TCJbd+J8H1a505Tee57OIvzq+O0ZBmjb4Cud7xn+f3IpknytkO0zp2+rgXGWZilceYESjwZjYHF+Y3HQG8/ube/m9T+yA0kaXrkBjxxDL+6hfRtScIcGkHv6UPL5rBnJqm++AzW1ETkJg2uGgOxeDQGuvI4Czd2G8S2jWFNjLP0yJfwylF2nzM3w8BP/DxqOhNZFg8dJXQdyk98i/prLyN8H9kwI2vDPQ9GxKh/CCWe+IERHrvmEPghmZEUkiKtKWcgQkHgBKgxdXlu1pMasZy5pq2b3UwHXkhjoYViKMy8vLja0tRBbarJyD39CCGoTtZJ9sboO9iNaqqbIgFCCFoFi3h3DDNr0FjHEnUlY0w1V9bUZG8MWdvYBb5VtMs2TtOlVbCYePKqcdZxIcZyBnbFoe9AnuZSm+pkHbflMXxXH82F9g2J3a2AIqnklD5K/tyty9LSdIk9dyTYeSiGawu6+rVNubTCQNAse+y7L4vdCoin1XXPC0OfZHYIq1VEiIBkehBFNTYnbiVg23aN3/jfDPbs1xACnvmuzV/+eZNKaWsMPpmS+OhPJnjgIZNsl4IQsDjv88XPNHnhqRVzzL1vN/nULyaJxVeIQDojszAX8G//WYXJSxGrisUlHn5/jPd+JE53r4JjC15+zubLn22xOL/11UBRJN79oTh3vs0g3ytTLoZ88U+bPP+kvWU9nV17NT71i0l27tUwdAnXFbz6osMX/rTJwlzUWCIp8Ut/N82Ru43l81RVItcl85XPt/jj368vuy2GRhU+/lNJ7nqbgaZLFBYDvvGXLZ56zGIzRjHh+XiLJSQgdK7jduqY+FsXzlJ8/JvLi/gqhCHO3DSlJx9F7+lDz3dHE/bgMFo2d13CI1yX0ne/FcWJeO7GgzwMceZnKD3x7egaPZFcv9bVjZbLb4nwRLvsIYQQtC9doPDo16Jg5GuvLQRBq0nQamLPTm3KghC6Do1Tx1f1kz0/gzV1idT+SMVU0jTsSxdonnl9OXg1tC3aExdJHjyCYpgohomazuCVNk5PdmxBvRYihBxVhn6L5rsrY6B96QLFx76xvIivQhjizM9S+t6jGL39y+/H6B+K3s91CI/wPMpPfidqxr3BGFiYo/y9R9G7e5etfVq2C727d0uER5IkjL4BCAXW5CUK3/4qzuICa3aWIgpcD9ot7LnpTY4Bj8aZk6v6yVmYoz05TvpQFFYgaRrO1ASN148vxwOFjo01MU769rtQzBiyYaCms7hLa8Vjvx9wmx4zLy8w9uAQlYk65YkasiKjmgqFs2V8x6c23WDgSC99B7txmy4jbxsgPZS4ceObhG/7XH5mjnt//RA73z3C/IkCsiKT6IlRvVynPteiOlnn4E/spnC2jNPwqE412PWebXiWR6u4iUKoAsrjNeqzTQ5+cjdnvjyOa/kYSQ276lCbbtBcahMGgrEHB/HaPkZaZ/SBQVRjcwozm0FlokbxXIW9HxqjXbaxyjaaqWJkdOZeXcKzA9oli9G3DXDyCxcIA0F9rsXeD47x2mfOriGkW4UpJUgpXZT8eRJymoScWXOMJumYcnKds6+P6/aS6whOvdAklVM5/1qL/Xcnb5hyqpgx1FgKv1GgOG3TrHqo2vqCcqX5Uwxuf4Dt+z8ERLo8hdnjBN6NB4duSrzrAzEe+VKL55+02bVP48d/OoHvCT77x41NLbZXoKoSmazMS886zE77mDGJj3wywa/9VoaLZ4sUl6LJ5/QJh//6HwKUTgG8TE7ml/9umloloFbpyOFL8PAHYvzy303z2DfaPPJFj94BhY99KkE2J/Of/m1tVdD0ZtA7oHD3/QaPPtLGcwXv/UicX/9HGUqFgDde31qGUDwp4Xvwlc+1qNdCtm1X+YmfT+K6gj/6T3VcN7LifP0v2jz7hL38TEfuNvjpX0oyO+UvW726umX+9m9k6BtQ+PJnW1hWyN33m/zqb2bwXMGT39nMRy5QUnHUfAa/1rxullbQbEQBwuuRnavgLs5jTV1Cz3cDUQaKmsnCDchC6Gy+OrO7tIA9PYneE4lNKokESvLG9V+uhaQo+JUy5ace29yCskk2EbpOtDBe/TPLwl1aRNwmIvLg+9izU2ue26/XCS0ryiaUJdRU+obXGxhWOXTUQNVgYbZ189bMGyBoNakdew6vcp3CpIBbWKQ9eWnV+9GyOayp6+/YQmfzE4dbWMSevhwRlo4FRr2ZMSAreM0a5acei+KzboRNjgHhudgzqwNfQ8fGXVxAHIzGAEEQjYFr4pv8Rp2g495D2twYeCtx5i/GUTSFwz+1B4g21eVLNcrjUfDt+W9PkhlOcd/fvx2v7VOZrDP/WmHF2iCiQtjheouxJK8QzM5xy9m1nb4WQmLm5SXM1Dl2vX+UPR8YAyHw7IBX/vsp6vMtqtMNZEWiXbJxmy7VqQaKLlObtrGrm5tbGgstXvi94xz+mX08+I+OEvohQki8/oXz1GabtEs2Z758kQOf2M3AHb04dZfiuTJ6QovumchSFHhh9Eiy0hHRW53NF8WmRcdduzj7dsBrnznLoZ/czT2/eig6VkD5YpX51woEjk9tuonxAYPypRpCQHWqgZk1qFyuRzGp6+Hqfr4O4nKaIS1KQx/QdjCg7cAVq/tPRkaXY5vq06txYx2eQDBxus3YbSaT56wbxq2ZPcOktu+l/PI3WLjURtVk8sPaumYnu11m6vxjaHoSJInAt/Gc5rpZW2tuXIUXn3b43KebtBqCV16w6crLvP9jcb71lTZLC5s3fVQrIZ/+wwauI/D9aDy4juBX/kGabTs0ikvRJFhcCikuRQuyGZP4ub+VwrJC/uy/Nah2CE8yJfHxTyV47ns2f/IHDay2QNejYM6/+XfSfPlzLc6d3rq40xc+3VwOQr580eef/04XD70vxtlT3pZ21KdeizLbrHY0iBNJiZ17NPYd1IknZdxyiO/D+LmrxAqHFf7Gr6b41lciEhSGUR8dusPgrrcZ/B//pMyx5x2EiGKm/q//X573fTTO80/aXCdWeBl+qWN5uY4vTgiBPTOFPX9jU74IQ5z5Obgj+rckSSiJJJsyT24BTiGqnI4kISnqchbeVtE8dxp7Ey6KrSB0nLWZYyKMXFNBAKoapS4Xl9ae6zpXuQolZN1Yc8y1KCwGnDvtYrdDPO+tITtCiEgOYGYTVq7OsVcgSRJyInlrZcYBZ2khiqWR5SjQdxN9tR7a589gz90a7ZIrCF13bUp5x1IkAh9J1RBhgFtYOwaE565yF8v6+mM7pffghTZuYGGqSSyvRkzL4PgtJEleDvRWJA1NMbG8GqrcqTHXUSQHgYSCHzoIQtJ6L07Qwg8djE6bNGK89sfnuPDVWWQdEDJBC3QvTSDVsWYEL/w/pzFSOkIIrKqNZmg4TkTkPMvj5f/6OiIUq7Kl1ESKxM7bqJ16BcLIcvHCf5/GHLkNs8/CXojeiZ7NI2k65789yfRLCyS3jeDVqjjVBlbFARHF8nz9Hz2F2/QI3JDWksWj/9/nCJxgXTeP0T+Mszi7aiyLEBZOlaj+m2MYKR01ESe+/QBLr1aXLScXHp1i9pUlVEPBtwOcusu5b8+h9u1FTZ6ifKnGd//Fi3i+Qf7ed+IUF2leOA2AkkihZbuw56aYfmmBykyA1TaA1e7K+kyTl/7wdWI5A1mVCX2B03CX++7i41PMvbZEY76F0dPP5AtFvvg3H6U+v7HrO3PwKO2pcbza9S2g1WCJll3F65CcSfc0C97lVcfokslu887rtrMeblxLS8DsJYfZS5vb+SixOHo8RrpbZ8eRNK4VkB82ufDy+qbkWLKXXO8eJEmhVZ+nsnSOwL8xG/Y9uPCGR6tjLWnUBadOuB03krwlwgNRhtNdR3WGt6kkkjLbdqiYZhQftB7ufdDgQz8e5w9+p8bZq7KQRrdr9A+qtJqCv/GrK7u9sZ0q8YTE4LC6ZcJTr4VcPLdCbC6e86iUQsZ2apgxCau9+QVGiCjLbd9Bje4ehURKZnBUxXUE6yVJpdISv/CrUWmQT/9Bg3otInaaDvsORtd/x3ti3HFPNNFLEuTyCiCRySkUFm/8HiRdxS/WNt4ZACIIcBbmCG+UYt55yGtTqRXDXF9A7k3g6l2xJElRltkWSVXoe1iXL143i+ym7s1qr7uwC7+T0YQKQbhuOr0Ig5UMICnKJrsRNA3yPQp2W2L68luUphUGOIvzBK1NSMl33IBXQ9Gj7KtbSceEbXcKGr6ZMeDTvjy+JQvjptq1WusmAgjfi3QE1Ghz4K/j6hVBsJx9Go2B9ZcKQ0lgKHEc2UJXYth+k5iaQQhBUs+jSCpuYOGFNmmjH4h254IQU80ghI8ia0iSQqk9iRfamGoKTYnhBm10JY7tN4irGVpegFLJRqnJQZsg9MgYfQgh0GQDv+EiWekoPELOIfkyTWsiep4wIiTIMvHRnWiZLpzCAn6rgdHdS+bAHfjNOu2pcUqnJ8iIbJT1CSiJJEbfIG6lROiHuF4cue8IKEv4jQsIsdBpM4dTWMCuzhAf2x3JAGg61tJZzIERjO4+AtuiPTWO3tVD/m0P0bz4Bq3LFwhdl/joDmRdx5q5jNNqofaMIpkp7LaBb68YAUIvpLnQxuwfxujtR4vVaBYWyI2mSO45RNBu0po4T+iUUVJzy2RV0nRig6PLCTihMJF79pPZlqA1fpbWxHmMviHMvkG8WoX29CUUkUeRTdSuFH7lHFouRWxoGyIMaUyOIye76LrnnThLc9Fz+G3i23ahpTLYhXmcpXliw9vRMjmM3kGs2cs3HrcEy/o6jbBCO6yvCUwO8JcV7reCLTn+Bt/zk+jZ7ut+zGo8jbU0TWXe4Y1WBbsdkB9aGzwGkO4ao3/0HlqNBcLAI9u9AyOWYf7y8zesnu77a4OAHUsQBIJEcmsBXLv2afzqb6bJ5mQmJ3wqxbCTlrr+Ajm2U+VnfinFo19r88x3V6tPpzJRYHEmKzO2c3X3Pv4Ni1Jh67tLuy1W1VSMgqBDdENCNzZPeGQZPvqTCX78ZxKUiyEzkz5WO5IaWO9JNR3e/7E4t99l8O//RXUViVQUiXQ2UtUdHFFw7JU+P3/GZfKSj7em1sL6EF6A1psjqG+cLio8F6+y+bIKayZ6Wd66bIeiIGs6kqoiyUrUhixdSQGJBA/fJIJmc/MaPltp17HXjYWLJBA6fxchYj0XzrVKvNKNv6d0VsZzBemsgqLeUiPKMkLPXz9uZwOsHQM3QXhvMAaUVHqVdtbNIGg1t57Ovpl2HWfduXrFskLkrtiIaF196gZjwAttvMBGV+Josokqa4QiQJU1JCK3kCwrSKGMG7SQJQVF0pAlGT+0CYWPriQIhLdc5NQJ2vihjSqbaLKJImmEBKhyJBkhSRKypBBKPm7QRpE1FFlHFhG5AtCVqO7dtUHKer4Xs2+Y1sR5Ejv3YU2Nd6RG5knuug2vXsW9Zp4JHQdJVTG6e3EWZwmsFoFt4ZaX8Os19K4e4mO7cRZnSe7ej1evkNi2k/bUJeyl+UhY1nPxm3USu/bjFJfw61VCx8FenCN0HeIjO9C7egjsNsndB3CW5tHzvVizk+jdvWv6XUmkiI/tpn35ArGR7QDImo5bKWJ092H2D9OeHF91jgh8hO9h9AzQnr4UiXS2GgjfxyktIZsxUnsPYc9NER/bhd+sERscJXAsrLlpQjfqB7/ZIDa4jdC2seYmCR0reqZGHb27l/i2XThLcyR3H4iKI2/bSf3sSWIDI2xVhn3Ru7zuPOYLl3HnBFa4+TpasEXCo6e7cEqLeM2NP06zZxBFEXQNGugxhYwE+SGThfG1i1m2ZzflpbMU514HwIhnGd39HhTFuCHhUVQJw1zdeYYpoSgS7S1YPMyYxIc/EWfXXo1/8U/KnDoeVYN/4OEY+29fa8btysv8yj9IUy4FfPaPmmvIRrsVYluCr32xxSNfusYaIW5uITBjEspV840sgxmTaTfDTZMKgL5BhU/9YpLzp13+47+uUa+FGIZEvifL8OjaoXDkboOPfSrJF/60yclXVi+MYQitpqBUCPjdf1Vjfm71rl6Em39Wb2YJb65wfZdWEBC0t66fsWXIMlouHwU653vR890oyRSKaUb6LKoaZeWoHRfWm7QahY4TBcjeYgg/2BS7E5tVEr0BluYDevpUZqY8tig8vXmEwY1FJG8FZBkt24UxOIze3Yve1Y2SSkdjQDeRtJUxIGka65pGtwDhupuTvdhqu4HPZgaBeBPCSTUnijtr+zUkZx5Z1hAipO3VaLolOkpk0V1sOMzlVRvMmnMlC1Gi7iygyDphGNByyzTd4uo21z4NEp33sc63GQnKOjjFRRLb9yCb0b/d0hLh6M513bfC9whaLZRYFDMSOnakel2tELSbGN296Lk8frOOWy52Eh887KV5glYDWTdIbN8TqV6ns8iKjNNqEDg2brmACEPUVBot20VY9HArJWTdILBa0e/XmR9kwwAR4pSWMHoHlkVuvUoJxYwvZ9qtQhjiNxtoufxVz9VE+B5+vYqazqJnu/BbDfxaFeH7iDDELS7hlpaQFIX46A4UM46aTiOXdULbIrAsvFqZwGph9g8t94VXLkZq4kGAW1wksNsbvrWNELL+IiIQNMMtZEN2sCXC4zVrlE88i1PeuKpxauchBu44SGLEJPCiOJFkbh39GyLTuaxoyIoaBa8qBrC5CqWaBjv3asQTEu1WlJ6+94BGuRRQXNo8q9B1ib4BhYW5gImLPr4fWTZ27VVJJFaPGNOMsrlGt6v8379doVZdG2s0NeFTr4XsP6zz+DfaNOrRs0hS1O7NEJ50Vmb7Lo2F+WgR27ZDJdclc+60uyV3Vr4nKulw9rS3nMmW7JbZsVvDvSadf3S7ys/+cooTxxwe/Vqbays0eK7g/BmXj/9UgrFdKrPTK8HMqspy+YlN4Ur17+uZYK5kT71VkGX0nn4yR+4itmMXWq4bxdwgrfXKf7fARSZC/60RdNuMfkSnYvybhRmTiCdkJi56DI+qyPJb9EjfjzHQ3RuVYdixOyopYa4NjLz1YyC4rgbVTeMqa97GF7/5VO1rGxJAEHrUnIVla03nEtdF3VlAkmTCNQJvV9p0t9SmIOgQMQlxzSTklpYw+4fouufthI6DWy4SG95O9o63IasqXr1KbHgMc3AUrasHv15F0nTiY7uQVRW3XMBenMMtFUjtOYisaTjFRayZy5EIbeATOHbknrzqI7iiYO03aoSdHYHfrJM7ej+Nc6/Tnp5A1o1I8Nax8Jt1MgN3kzlwB2Hgr/me/VqVwGqTO3ofCLBmJ9EyOVJ7DyHrOvU3TqDne4lv24mkqHjVSE8suXs/WiZHYtsu2lPj+M06qeHDJPd4NC+eoTVxHjkWR/g+gdXuxHJdpeYtK8i6QWhZHQIDbrlAat9hWpfOYi/No89NRX3hezilRWIjY+TuerAj0ntrJgYJmYzS3VFc3vwOa0uEp/z683iN67Mqv1mhMjFD9XSdeFqla8Bg8tT6+g2VwnkGxu4jnughDH3MRJ56eRLfv/Fux3OjshEf+WSCi2c9du7VeMd7YnzrK+3ljClNg94BFdOMMp1UFbbv0jAMiVZTUFgMcBzB9GTA/tsN7nunyfyMz869Gvc/tHaiu+t+g4/+ZIKnH7eQZIl9ByMi53swOx25h+rVkEe+2OIXfi3Fz/xyitdeip4l36OQTMl866stmvWtTTBBIPjEzyZQtUgf6P0fSyAr8PRj1rLFOp2RyXbJxGJRDatsVmbXHg3HERSXAtotQWEhoN0KOXqPwcWzHrIM73xvjFxeZnFuZWJIJCV+6heTDI2qfP0vWoyMrQyTRj1kbjogDOHkKy6vPG/zC7+WIhaXKS4FGKbE0IjCzFTAC09tLiZB6+9GeB6h5RA2N9CruFp19lZDUUjuPUDXO9+L0dO3HK8gwpCg1cBvNAhti9Bzo/v0PESnzEVsbOebu7ZY/t/3H7fosgPDKj39CiKMxvnpE2+BsiZ0xsBb1FdypLScf+h96H39yGr0bUdjoInfbBBa7eV3f2UsaF3dxLfvepPE5wf0/mGrHoZN4Cp32VbOuI6a7ZXA5q21uf5cEVgtqideWl6QReBTfuEJrrD00HWwHRu3sBANN9dGkiRKzz+BJK3IFTQvnqE1eSGygvge1ZMvI19R3Q9DqidfXg76Dl2H6qtR6RBYyQatvPpcdI7vEwY+1XoNZHnlvl56MhpXYbiG6IvAp37meDRXdX5fefW5KIZMiMj9JMur7luIMDpGkgh9HxEE2EtzuNVSNLeGIfU3jiOpWqcNl/obJ5ZjuUQQrFxTgPCje2qcex1J06L79n2qx1+MCF4YELoOlVefX3VftwKqpDGs7WFCvI4fbt4dvCXCY81P3viYpTns0iKKLNh2MIndCsj1G8ycXWuKblZnmL30NOnsKLKiU5g9Tr18Odr1XgdhCDOTPk9+x+LIPQY//rMJFEXiqcciHZ4rInp9Qwa/9b+nyGRlunpkFE3h7/2veVp1n7OvO/zOv6ziOPCNv7To7ZP5xb+TwvNgYcbnc3/S4OOfSq4SUbv3QZNMTub+h2Lcdf/K7r9SCvhP/6bGudNRLalvfdUiCKL4l3d/KIZE5P753qPWpjbekqyslKvw4PknXS6NC37h1zNkcxKNesif/GGTUydX+umd74vxwY/HiSUk8j0KqYzMP/0/czi24NP/pcHzT9oszgf82X9r8qlfSPCP/lkWuy048YrDl/6sxV33GVyZ/VJpmXvfbhKLR3o8V68xx56z+f1/V8NzYWkh4A9+p84nfjbBL/x6Cl2P3s3spM/n/mTzvlXZ1FAG8jgXb22WymYRG91O93s/jJ7vATpZXkvzNF8/jj03He2m2q1O9tJKn2fueSBSfr7FwdDfN9yi25665DE94ZFKy1w6z1vn0gLeKnJgDo/S/d4PY/RGgbUiDHELizRef21lDLSaa8ZA+ui9xLbtuG7tsx9q/AC51lsBSVKWg8ivmIyjf1/JGJPADwg9LyoTIsmErrtcqkaSIuITWFYUrI0cLdTXpO2LwEfT4qT79mI1lxAiJJ7qo1GZwvE88AO40h4R6ZEkhatN2cL3CIMQ3UzhWjVCz0VCWr5P4UYxSNHYWmv+jgjGyscmPJeri4dHZXFWhwFc/RxqKkvQalz1M6lD4HxAWi6xEthXXaNzTdkwO263duQ6lSQUM47frHfuY4WgCc9bdudtRHjURJrAjtqSkJC5vptYQ0eXzC3Hz906taIrECHCD5GMKLjPagQburQAfKdFqz4faVE4LcIbkB2AyUse/8c/KVOtBDz6SJtkSiYMBNVqSLujAqylsniZPfzuv3p1Od4u3j9Kattt1C6eoDYbBaYZ2R4WKxL/z79aIpmWSfQNU5lZolKwOHHMpVFbYSh/9Pt1vvCnaxfyIBDLWj0gIRJDfP1L0zzzXWtZpNB1IuvIjVxQaiJNats+KmdewnPhy59rkRzIofbu5/EnThPU53FsQVvkUZMp/HLkQ3/5RI7XT1aXS2FcjXJxhbV995ttXnvJxjBlgkBQq0RCcY8+0sbRhoApiksBv/lLBWRl7WCy2uGqBW1qwue//G6dz/5xE02TCAKB1Rar+u16kFSFoN5C0rVbZu7cCiRNJ3vvgyt+7TCgdeEspce/iVNYvK4P8s0Gq/7AcYsWuyCA0R0q+w8ZSDI8/vXWpuQIflggaRrZex5YDg4VYRiJG37nkUjN+3pj4EeV7F7Bj/jtXw0znifTsxPfs1DUTiyOCHHtBkY8S6s2j25mAIHVLJDKjSLJCu3GEol0H54Tbcqjmo4NhAjQ9CSe08T3LEAQhgF2K1o7PLeNY1Uw49HcYTdLpHKjJNIesqLRqEyRykVlPFq1OZLZ4eUqA+36IvF0H67TJJ7soepapHIjyIqO1SxEZZZESLuxSCa/g0ZlilZtblOSLZvur76hKF6nXomSMOJJvGYNPdMVES1FRTZMvGoJv1lDy3QROjah7xPrH+4EM0+BCFHMGLGh7bilRbx6BTWVjYhQGKImM/hWk1jfCEplCa9eRdI01FgCt1pGjacw+4ZoTZ4jsHy61SF2G3cSbmClg4iImlJ8y89804RHiSdJ7ziAls6tKmoHYC3N0po4iSxJ3PWhHiZOrJ+FEk/2MrTrnWh6fJldF+ZOUpxbMaOthyvWBQDXCamWo8KbyeG95EZSWIVZQs9BTvfTcI7gNau0ZseRpqfJ1nqwCmAXAtREhljPEFZxjnodHLkbZd8DCH8G1TtPoVgiMbSbXCyJVZilUl7CjUdVjCVFpX7pFPGB7RjZHnSpjjc/Qax7kPztb6c+cYrq5DmqTUFyaCeSoeA1xoHVfSEpKomhnWiJNHZxHt9uYXb1k9t3F16rRn12nEZjjix92GUZa9FHTaRJDA4SlBcBCSPbjbrt7TSLczRLF3AqSyQGd6AlM1jFOezmPMnRqOCmrGgUJk4R7xvGyPWiqE1ac5eQRB/dRx5CTZ+iOXWe+aWAxNAuZEWlNXcJr1nd8H20W+KGhU03gqSpKNkUcsxAUr7/u2SjfxBzYGh5h+5VK5SfenxTAnAbaZP8yOAWLnaSJCEkiMcl9h3SOX/aw36LxAdvNfTefszBkeUx4NeqkQjgJjSfZN340eYMPxqvaBnmUBeJfUPo3UlQFELLxZmv0Hh9ikRmkDDwUBQdTY9jNQokc8MoWgzXqqEZCVTNpLxwBlnRUDQTu1UknurF9+wOSZKoFcfpHjqM3S5TK1wkDH26B28nDD1qxZXMJ0mS0Y00VqtILNGF57aIy/04VhVNTxBP9aGoOr5noeoJhAipFcdJpAfoGbmDZmUaz2lAqgfNTCKrOrXCRRKZQWRZJfCdKAXfub61XFJk4jv7iO/uR01HJCBo2rQnlmidn0e46xsRJFlBjSdRjBiKYRJ6Lko8SXx4B26lgKQoBFYbs3eQMNeNns3j1asgSZG0haKuGJ4kCUlWMLoHOtmrUY052YihJlK45QJKLIHqZ5GNOHpXN7KmI+szUSKAqnJlQlLRcYTFkje1YdCyJukMaFsPJ7gpwiNrBt13PkRiZBfC81CTGdxKAT3TFemKLM0gKxKJrMrihEWwgRBZfuAA7cYihdkTCBGSSPXRO3In1aVzeO7WsjFi3YPo2R5acxMkR/bQXrgMSFgLk2T2HMGtFvHta3L5HQtJ1TAy3TjlRfx2Hd9pYxfn8Js1zPwAiYEx7OI86e0HqDgWiaGdNKfO4ZYWoOPj9RoV0tv3Y5fmcOtlAteivTCJCDzS2w+i6CYCQWpkL9ULr67aMZr5fsyuPpozF6P7np8AWaa9OEVm1+24tVJUef2a+5ZVFSPbg12ax7eaBHYbuziP16xidvWTGNqBXZwjPbYfv90gMbSD5vQF7PLisi/Va1Q79z3fuW+b9sIkoe+R2rYXNZ5G+F5kcTp77JZl9FyN0HI61cjFlgrm3SpouTxyLJokhBC4hUWc+c251tRc14+uOwtu6WJXLQdcOueiqBJL8/5bJj74VkDL5lASURkCIQRuqYA9c2P3PYCazd1cuvsPC35Ebl1SZLL37WHgp+5H70l3KslHY8yZr9C6uEC7sUg6vx2nXSUMfXzPwm6VI4uPZmLVCtE8I65oiSUJPBurGZEeu10GJILAwbGqhIFLpmcXjfIUvmchKxreVeQjmR0inu7D99p4bpts727a9QWQZHQzTbM6g2YkEGGA5zSQ5chN4zpRTKtj1zHiOcx4F3arggRkundht8tRsHbgEYQesqKimxla9bUlR2RDo+/H7yb/nsOoKTOaQztxgbVjl7Amlgg2IDyh66DEEni1UuSiS2VxSou41SJupYiaSHUCjQPcaik6tlmPyqHke3Hs9orExVU137x6FT3XgwhDvHqV0LHxW3Vk3UDRTfxGFb9eRYkn8Ro1zLwZhXF0ni3Ap+TPMetd2JDw6JJJRlmbrn8j3Bzh0Q1ifaMsPf8ownfJ7LmDxWceQYkl6Ln3vVEUekeqwnfDDQmPEAKrWcS1o6CjtiTje9ZNzcOyYRI4bdxqAUZ2RZHkroNTLSCCIEohvobwCN8luOpngWNFBKZeIXAsVDOBns7jNWvYlchPG3o2dnmBwGohGzFSo3vxrSZaMgOSjN+uE7o2brWIpGhoiTRqLIlTK+E2ymsWGVk3CRwLp1ogObJn5b4rBULfQ9bWT5P0rdZy5H/gWASuhduoENhtlN7h5ft2KkvLQW12aYHAaiLrJsnRvQR2Cy2ZQZJlvEbjqvtW0eIZtFQOp1rArRWuq730ZiCn42gDefzFCsJ7iwTrrnd9w1jux2UV2k2k6cpmDGNg6C2+ux8dJJIy9z0UY3HO5+JZ9y3R4XmrIOvGirCeEATWVsbA8KZ0in5o8SPCS9Vcgv5P3os5kqf60kWqz58ntFzkeKTN45WbeGEDq1m46pkE9fIkIJbLGrTrUYZxFG8ziaxo2K0i9fLEqgSC4uyJqAlJ7lh+BI3KahJcL01QL11ePqdenowIiSTRqESunmZ1tmMFidxoAJ7TZG78GUDgtKFVnQMErdpcR7Qy7BCn6Dy7Wexk0q19WYk9A/R88A5kU6P0xGmap6YRQYiajuGVGgStjYOEW5fPrS730BHMtBdnV64lScv94paXltcBa35qFfkK2k3qZ1/rdLvArRRW9efyOUid8+aWn8+rlZbPg0hpuR6UNiQ7AIHwKftzeFsUH7w5l5YkQRjgtxtR4JeqgizjVovYS7MkhnZgTZ/Fagak8zrt+srkEUv0kMlHQkmKatC/7R7iqd6okGh6EMeub6jBs8wChegE9q6ksNulBbJd/XQdug+/1cCrlWFgO923vz3SJ2jVSQ7vIt47jJZIE1gNlFiSxOCOSLK+VsSpLOFUC2T3HKE+eRanvIhVmImEx6wWoecSOPZKpogQUTVmTcdtVCJhp1Dgt1t0H3kH1fPHaU5fIDmyG1nVCFx7javOKS8Syw+QP/QAgd3ErZVIDOyg+/YHAYHXrJEY2kG8bwQtlcNv1VDMOImhnUiSFPV5eQG3XCC763YaU2exi/O0FyaRVQ0/DAg8h8CxrhqgAllREJqB26guW278doPuI++kdvE4zdmLJId3I6tqJGL3FpXAFl6AsD307YP45fp1a2m9Jdf3vU5Vci0SSdONGyvlyjLJ2w6h53t+9GM4bhFsK+SV56P4sVsYZvB9gehkrKARjQFtE2NAkkns3Y/R0/ujPQZ+RG5dy8QxR7vx6xZzf/YM9uQGxWzXvLMrc/XqQdmqzaGZKcLA71htNnjXIkSEPs3qDK69XraxWHXsyj2Ild+v27RY5+9XC36uFghdFxIYAzm0riSN09PM/elT1yU46+Lqtq++9pqfXfv3de5po2NX/Wydfrnm2GvrZq2HAJ8Z78KG2Xgb4eYITxgQ+h5qLIlXL6HGEsR6R7ALs8tmMEWViKVUygsOydyKr09RDcxEV6chCbtVRNXigMDz2oS+s8E3KBHLDhD6Dk6zQiI/jNMs41mRu8dv1SmfeiFK6wt8RBhQeOWJZX+j8D2aMxdpz18mlu2P6sxYCyy+/BiIKGIeIahdOLFsxovnBmlOnCPwLGLZAWRZpfLG1emGNsXjTy2z4Ch1UFA68TTIMqHn4FsNFFnHrhcInLXCeX67Qfn0i8iaTuh7hL5L4dUnkNROuqLn0JqbwFqcjqxBnoPfbrD08uMRWfZckCTqE6dXnj3wKZ95CVlRQIrSHKP77lRDdh1Kp16IPmYRWX8kWaF08lmQJELPxWs1CBwLEQbLegvLWK8gHXT8uCriBqKRV0NYDsLzCCoNlFyKoNGOMhy+T/DrNULHjoS6IKp6nu/GK24woUoS8bGd5O5/J/I6Gi3/syIMQdMl6tW3rlr6WwW/USe0rWXNHS0XVT13CxvrjcW2bafr/oeQ47euIvcPBD8i70pJGEiqjN+08KtvXnwyDH2c9uaE68LAw93CnPb9giTLKAkdJPCrra2TnR9xaJKOJ9wtkZ6bIjyB69CauRi5Qpo17OI8vfd/gKDdRE2kKL78OJIM5XmbgR1x5i+t+PqatRmatevHSGjxLKmu3diNErKiopoJWsVpQKAnctiNEpKsoMXSCBGS6tuJ0ywtB6JZtUW0WApVi9EqzRDrHgYETqNMLNtPLNuHUy8RuBYisDBS3Zi9vTj1AooeR9H06HoCVD2O0ygiCVCNOLKskBgaw24UUDUTWdFpV+cxU91RxH9ljnjXEKHv4rZrxLP9GOkerMr8WiuJFPn9wtDHSPURuDZevUwYeGhmnOBKJVMhCDwHNZHBSOdpzo0jPGeZRKrxZKRE7FpRAHmH+KBqxHqGaU6fi0iaJAFROQgj24PXquO3akiSjJbM4rXqUTCaHKVwqmYCSVFptxuR6VO68n5SBK5N6HtRsGoYggRqLImR7aU1e3FL40n4IdpglqC6vl7TWwlnYQ6vUkZJZZAkCb27l9z9D1N+6jGCZqfyrxQFKMqxGMm9B6KMnt5+hOeBpv1o7/BvEbp7FfYf1rEswcykx1sgHPyWwV1awCuXUDM5JElCy3eTe/u7KD/xKH6jtnoMmDESe24je+8D6P2D0XelqmsSN/4abw6yqZG+Yzuxbd2omTjmcB5JkdHzKUZ//b2E3spcWnrsJI2Tq6vCI0UkKXV4G4m9g6hJk6Dt0h5foH78Mn6tvZbsyRJqKkZi9wDxXX1o3WkkWcJv2FgTizRen8IrN9eGJcR0et5/O1o+xfznnye0XRL7BknfPoaWTRA6HtZ0kforE7iFN1dGRk3Hydy7C6Mvg5ZNEN/dD5JEYs8gY//LR5aPC5o2S19/FWe2vOYZ9e4U6Tu2Y452o5gaXrVN88wMzdPThPZaYicpMlpXkuT+YWJjPaiZeOTJqDRpnZ+neWZmXbKl96Tp+dAd+LU2i19+GSVpkr59G4k9AygJE79p0764QO3VCcL21iYMFY1R/TZm3QtYYvMSKDdFeITvUXn9hSgAzPcovvI93FoJLZGlPX8Zv3yZPfdkGdqbIAwEub7NVxCWZJVYthe3XUWEPnq6G6dZJtk7htMoQUeE6gp5kOXIGpPsGYsC0MpzpHq3E3g2YeBjZnoxU92IMMBM99IuzxJ4KyYzWdWJZXqxG1HsiqKbBK5FvHuEwGlHmRsiSkeEKBIdEZLu3YnnNLHrBVJ9O6IifE6LeG4APZ4FwMz00i7NoMUz6z6rke3FyHRH1zViSLKMb7ewlqaJ94/Rmh3HyPVi5vpoL00RujZyJo/Z1Y+eyiEpGk5lMQperiwS6xlGjSUJXYvQ99AS6UhEqoNY9yBaIoOkaqhmglh+AM9qYJcWSPSNUp86h9nVj5ZI016cJPQc9FiSWM8IWjyJpGrYpQVi+QGswgx6rjfqL6cNQkRBzjeTWh6GeLNL+MXa99W6A1Edo/qp4+h9AyhmDFnTSN9+J+bgMNbUBEGzAYqClsli9A+hdeWRDRO/UaP20nNk7r4fLZP9vt7zDyMW5wMWZgOKhYA3UangB4Kg3aL++msY/YMo8QSyqpE6eASjbxB76hJ+owGKjJbujIF8dxQz2KhTfflZ0nfci96V/0E/xl8pyDGd9J07SOwZQFZl5FjkZpQNjfiu/lUJDrVjq2tGIUF8ex/9P30fqQMjkSi2FyDrCvn3HKJ1dpa5P3uG9vjiKiu1OdTFyK+9l/iO3sgz4PoIIVBiOghoXZhn9o+/R/vS4irSI2sKqSNjJHYPUH7qDJk7d9D93tuRzSjUQ9ZVgqaNM19984QnGyd3/x707jSSKi9nZampGIk9A8vH+bV2dN9Xd4sqk75jOwM/dR/GUD4KJwhDZEOj+32Hqb5wgYXPP7/6HiWJ1JFtDP/yu9DzSUQgCD0/qmcW0xGeT+2lcWY/8xRe6ZpivSmT7H178OsWlefPM/hzD5I+uiPa5ysykq5iXVqidX4Od4uER5YUknIORVK3ZKW86bT0sOMCgki9svL6C6t+f+4FFzOpcPFYnb1vy1y/bMDqlkEIzHQvTquMrGjE0r0EvkMs04cWS2LXi5jZvsiFlO7GSHZ0AyQJM9sfxezYTVJ9O7HKc8iKiuu2EU4LM9WNoq6IBopOkFks04dnNVD1OKoex7ObxLL9kT5Qu04s24+iGSiaiRZLIUkSKgnMtETouwSeQyI/jFVdQNF0nGYU8W+me5EVfV2fpqIbmPn+yO0U+DRnLqBn8iArBK6NpEYEzK4s4lSW0BKZyC1oxDDzAyDJONUlPKuBrJkoukFrbpzs7jvwWjVaC5MkBnesXO/KebJM6Do0ps8T6xmKitsFfkS8zDhWYQa3XkbPdAOgmvHl86zCLL7TRtYNZEWjNT9Bbt9dOKUFrMUpzJ6tB/KGlgO2S2j/YMwCjZOvoud7ydx5T5QqqWmYg8OYg8NrjhVC4FXKlB7/BtblSxiDI39NeIBGLeS73/w+1Dp7i9A8fRy9u4fs3Q8g6zqyqmEODGGuE5guhMCvVSg+/k3aly6gd/f9NeG5xQjqFotffAHZjDZs8d0DbPv7H8BdqnH5P36ToLmyaXWLqy3DWleKoV98J+k7d1B59iyVp8/i1y3UbJyud+4nc+cOZENj4ncewbvqXL9pEzQsqi9coHVuDnepjghDzOE8vR+5k/QdY7hLdzDz358gWGeBlk2N3g8fJXlghOqLF2idn4us110J9O401tTmC99uBGehysx/fwJJlZFkma6H9tP3iXtpnplh5o+eWD5O+OEachXfNcDIr70XNR2j+J2TNE5OEtoexkCW7vcfoeeDdyC8gJn//t0VQikEfsPGq7Sov3qJ9sVFvGoLSZFJ3jZEz4ePkn/3QVrjCxQeeXXtDUug55MM/eI7MYe6KHztFey5MkgSRl+0nl37/lJyF/3a9uv2gyJpJOXslvvvpgiPEk/S//aPYi1M0ZoZx2usFbzz3JC5C23GDiWZu7CO+XADiDCkWZhE1eMEno1TLyDJGoFnIas6kiQTeDa1mTc6AcwhkqIjKwrxrmGsyhye1YiCqJuVKEW8PItAEPouih6LIsPtiI2KwKexMI6sGQSejV0vIsnRNexOhlTgOVSmTi4H90qKiqIZxLIDtMszeHYTWVaxa4ud680tkwhVjyFEQOBHLqiR+4Y4/PMHePr/eh671sKtlwGBpGgErhVlhxlxzGx3VNzNcyJ5c1lBz/agp3NYBatzXmShMrO9BJ5L6DlR/E2zQuh5JPrHCJ0VZU2vVV8+D0kidG0Cx0KLp6OsrladwG5FripFw8j1oicyUaZWPRqkihHruMP0zvUc3FoJIQSx3hF8K+pXLa5x9G8fRgSCl35vnQ/hKsgxA7/aXF02QAi8WgVnIdJC8VutzRfZFILQtpfPBQiajQ1jS0KrTemJb+GVCqRuvxMt1xVl7ijKcoB+6HmEVhtrepLqS89iz0wBgvbFs2i5LiQJAmsz4zxKe75yoFcqvKnijSuPHOJVV/rLq5bXDSwMrDbO0jyyphG02+teW/hedI8ijFylre9Dwc71IARevbb8TEG7vSVp+tBZOwY2ej+hbVN+8jG8Uon0HXdHY8Aw1xkDFvbsFNUXn8GamQQhaI+fR+/tj8bAJvvKLRaWdX/cUnGVYu5NQ4T4tepVY6C0bp2s0LJwF+eRdZ3AtjccA16p0EkaEgStrVWlfrMQQYizUF3+t5KOAYLQ9bGnivj1DUrQSBL5dx0geXCE2svjzPy/T+AurpQeaF+YR03FSB4YJnffHpa+9sry7/xqm6k/+A6h6xNaK3NN4/UpAsth2999P6nD21ASxoaEJ3lwlLk/e5rqc+cJnc47lUDWNUL3zb9j4frYM52sJkUmWYkCrv2WjXV5g7hDQNJVej92J0Z/hoXPPc/8F19YfsbGySmchSrb/5ePkr1/D5XnztE8Nb18rnVpicv//mv4LWeVpk/zjVkkVaH/U/eRvmP7+oQH0HszGLWob1vn5yEIkQ2VxPZutEyc7OFhGucWCKyofxJyln5tjFZQ27BMiSwpkXVni7hpl5ZbXiK96zD52x+kvThNa+pch/zUiFxOMHuuxey5rU+Woe/i+msXt/Cqn4Wrft+OsraCAM+qX5XP3zn2qoCzcJ12A89ednOFOOsee+15vqISei6uVQcRrj7PWrmee3VdMAmMtE7X7iyqoeLWS7j10qp23U6KXntxrQ5Ia/biuvEx1x5bvXB8zTFAlIVWWVr1syuCgutdr3H5zLrtWEvTq/5dPb92oEuKRHooRejf2MUVtmzUTIKw2V5OTRe+R+nxb1J6/Js3PH89tMfPMfn75zZ9fGi1qb74NI1Tr2IOb0PP9yDH4lHdGcfBq1dx5udwi4uranrVjj1P7djzm78xIZj/3J9s5VE216zrrumvnmGDXUcznHyyRqsW9WvrjddpvfH6ddvySkXmP/vHW7q+JIFhSkgSWypoez0I36f8vUcpf+/RmzrfujzO5O//+00fH9oWtWPP0ThzgtjQKFpPL8qVMeC6eLUqzsIcbmFh1RioH3+Z+vGXN2z3tntTqLrM6edqy6VqFr74mZt6putBeB6lJ75N6YlvX/e41vkztM6v/21fgVcpM//5T9/K2/u+QMvGSd+xHUJB5Zk3VpEdALfQoHZsnOSBYTJ372TpkVdWZQv5tXWslKGgeXqGwHJRM3EkfYNlMxS0z89RefoNxNXznmCF/PyAYA53kdw/jFduUX7m7CpChxBYl5Zonp0l+7bdpA5vW0V4hB/gVdau46Hl0jwzA6FAyyU39OIIP6Dy9FlaZ+eWPR3JXb103bMda6aCECbSeAE6RUAlYMG7zCXnBAHrbwZ1KcZ+874t98NNEZ7QdSgce4Lq2VcwuvpIjO4hd/BeMvvuxCnOU7twEmthc8JdtwoiDHDb1e/f9QL/+3q9v6qQDA1tpA/heUiLm8uaeCsRtFq0zp3hB2TTuHWQYPfRJJ/8zWGK0w4XXntrd+ij21VuO2wwP+tz6lXnR0qH51qE7RatC2/AhTfedFuyIvHwT/dhxGQunWzSqv0Id8yPALTuNHpPmsByCL0Aoz+7+gBZQnTiBLVcAiWmE7RXb2YlVUE2NWRdjdTfJQmtKwmhQJIlpA2EJoUf0Lq4uJrs/JAgtq0HJabjzFdRYvqafpE0BeH6UWB4dyr6t7d6rEq6imJqSJoSWSdlCSVpIsIw6pMNpBz8ho11eWnN79qXS1RPTCOEWPUOGmEFR7Svq8MTiqBzzPcjLR1AhHiNKl6jSmtmHC2ZIXPbnWT23IGejONfLGAm1WjH1/Ajt9Y1kBUtqp11TUdIkhyZst5kfque1OjanSPWFUOSwKm7VCdrtBY79yLB4F39NBdaODWH/J4uzJyJ23Qpnitjl20UXaH/jl6cmkvx7Io1xsgYjNw/yOyL81hle7m9eHeM3M4cRkoncAOskkX1cg23eVUBNgFqTKX/SC/x7hiBG1Aer9KYW5sBsBlIMiT7k2THMmhJjdANaBUtKuNVfCtiyLEuk5793SwcX8TsMsltzyKrMq3FFsVzZUIvJNEbp/dQD/OvLGBXVyxT3fvzmFmDmedWyi3Imkxue4bkYBJZlfHbPvXZBvWZBiJY/RCJ3jj5PTnUmIZVsiieK+O1ov4Qjod7eQ7h+lEsz1/j1kDA7EWLZ/6ySGH2re9XSQbXEVgt8SOXlv5WIgwEJ75XQdVl7NYP30L4Vw1KTEeJ6ajZOGP/8IPrqrdLqoIkSZGGmqGtLLayRGx7byeTaBC9L4OaNJENFUlXUZPmullMVyCEwG9u4Gr7AUPLxJE0hfiOXnb9859cd22VjSjjVDZUJHWF8EiGSmLPIOkjY8R39qHnk8hxA1lXo3PUSEFakqR1XVDCC/CvyeLyWw7JPX2YgxlCP2Tx0dN4lWhdbobVK2du+Dw+LpecE7hiq9ldbwJXglzjg2MkRvZgdvXi1cu0ZsaJqxKj+5MsXGrTN5Zal/D0DN6O1Srguxa2VSEMPFLZEXqG7yAMPBYmX+zIfW8dqcEkR/7mQXoP9uC7nRcnS5z+/FkuPDK+/O87fukQS6eKIEv0HsijmioihJd//1XmyzZ6UuPorxym8EZpFeFJD6d4+F+8nUd+/dsR4ZGge1+eo3/rMPGeOIEToMZURBDy8u+/xuxL8ys3JwT7f3IPqYEksiJjZA0ac01e+o+vUDq/NSuHrMqMPjjE/k/tI5Y1cdsemqnSXGzx4n84Rm0qCgjL7shy3z++mxN/fIqRB4cwUgZ6Sqd4tsSLv3sMx3PpuS3Pg//0bXz7tx5fITwS7PnQTnoPdS8THlmV2f/JPex4z9iyrL4WVylfqPDs//3iKnKXHEhw72/eSaIngRZTUQyFie9OcuLTp5dJj5JKoGQS2OenCW6Bn3vDvlJAN2UUNdJNCgKB5wgC/1o9IdANGVWXrgif4rkhnrNynG7K0SJvhehmdKwQ4DmrjwPQTBmt05bvCVxrrVaNZkioukwnKRDfFbj2ymStx+Tl71/VJBwr+p0Rlwl9gW2Fy7/XDAk9plCac3n00wtYzbU7pSv377sCzZRRlMhL41rhmv6QFTBiCrLCqhR83wtx2tGzVEoh7jZBPCHdUMxO1SU0o/OsIfi+wHPCNSFHq94XEPhr31csqeA5IWEolu8xDMCxAq5WgZBkMEwZReu8JzvEc6/ZaMnRe1c06UrYDq59VX9IYMYVfDdEM2QE4LYDVD16/9e2GUsqKKrEiSdr+N7afpWk6P35HSV63ei8kw3GiKpL6KaMfJWFQYhonFw75v6nhRT9F1guzVMzBK2NRezcYmMlvV1iuXSFOdSFPVumfWEBr9wgaLtIhkr/j99z/Xp/gtVxiD+E8Cotmmfnrqtq33xjdpkoyoZKz4fvpPfjd6GYGu1LSzROz0S6P7aH0Z+l98NHr3tNgVjTL/ZcjcITZ9HzSezFOn7DXnXGtZCQkVGu1JknIMARWyeXN0V4JEUhPrid5Oge4oNjIMAuL1I49gR2YY7AblFXQ7qHY/heGE3c6/j3EplBeobvwHfbVAsXWJh+mfzAQaxmAUU16R48zMzF7235/vSkxqGf20/3/m6O/eFxim+UEKEg1hXDrq7+ABRdYeyhUd74y/M89S+fJ/ACtLiGXbmx2uOqdjSFsXeOEO+O8ey/eZHmfAtFl0kNJqlN1aNn78xTRsbASBs89+9exipbdO/Lc88/OMrOD2zfMuHp2p3jjl85THWixou/e4x2yUY1FIy0TquwekDEumJse+cIr/+PM1QnasiajKIpeO2tkYzUUJLt79rG4usFTv35G4hQoKd0zKyBZ131IUkRMZx8eoaXf+81RCjY/5N72fHuMWZemGPhtSieSHg+Igjf0mrpRkzmjnfnuOt9OTLdGrIsUSt5PP2lIieerCwvjooqMXYgzgM/1sPovhiyIuHZguNPVnj8z5Zw7RBJgvf8fB9d/TrPfbXI2z/Zw/CuGJIs8fRfFHjyCyvBgyN7Yrz9kz1sP5RAViSWphye+sISZ19eCaLuHtJ56FO97DqSxEgohL5g/ESTx/98icXL0Tj88N8aQNNlZFVi5+1JnvriErIscf/HuqkWXL70uzMsTUck9dCDWd71M70ksyqyIvGH/59xZi+sjAVVk3j4p3sZ3Blj/HiTIw9nyfXpuHbIc18t8txXS3hO9C50U+au9+W4631dmAmFZE4lllBoVDxef7rGt/4oIlSZXETqevqViDxtYI3uGtB54OPd7Ls7hZlQCHzB4qTN1//rPAuXV765WFLhyENZ7v5AF5keDQmoFT2++9klXn+6tvwcv/J/bueV71QQAu75YBfZXo1a0eMr/2mWy6ejTZamSxx8MMP9H+uma0An8AXnXmrw5BeWKM5Fu3tZgT13pnj7J3ro22aiaBLtus+rj1V47mslrEZAIq3wC/9sjPETLfbdnULVJR79k0UOPphh99Ekrz1e4dt/srjcdx/5tUF2HE6Q6da4dLLFp//FZVxrZYwnsio/+09HmXqjjWbI3HZvmkRGYWHC5jt/usilk83lUKGufp13fqqH7QeT6KZMtkdDkmBp2uGpLy7x8rdvjTtYUSXC4PpWOkWVEEJs+I5vBFmJSP31FLmvkOs1m5EbILBcAstFcnwWv/Iy7QvzGx4rQkHYUXbXezP0fewuYiN5Ct88ztJXj+HV25F7KgjRulP0fvjomlTvHxX4dQvhR4Hgc595KtIT2gDCD5eDkxN7Bun96FHUuMHMHz1B5blzhLYXEaJQkD66/YaEZz2YfWmyR0bwmy6JsTxetY1bXj+QIC6nGVC3k1F7UVCxwxYFf5qiP4PP1taum8vSiiXpe+DDeI0K1TdepTV7CbdaXDWCfQGNssvIbUnGX6uvH8wUBsyOP0WzNsfI7nchSQqqFmNp5lXCwGN45ztv5vZID6cYuX+Is1+5wOSTK8FX7eJaRigpEu2SxcR3J1dcXdycWVIAiqGgaDJW2QIBzfm1L1GSJc5/bZzSuch6NddcoHKpRtfO3JavOfrgMJIs8fqfv7GKLDXWKfatxVTmji0wd2xha66za3fsInoGLaYSeAF21Vm3b5GgMdfk3JcvLLv9Lj02yZ6P7CLeE18+TE7FULJJJE3Zwk1tDbuPpvjxfzDEyadqHHu0gqpJ9I+ZaKa0MrlLMHYgwS/9y+3Uii7PfLmI3Qzp6tepFb1VGS+JjMqB+9PEkgpz4xbnXmqQ6lIpXuU+6h7S+eRvjSAr8OyXi4QB3PGuLJ/6J6P8v789wfTZaLzFUirJrMprT1SpFT2yPRrv/tk+VF3mc/9mCscKSXdp7LkrxfNfK1Kac/ixvz/EuWMNTjxV5f6PdXP7Q1m+86eRMvD5VxtUCy5HHs7y8Kd6UbXVL1CSIJFWuPM9OQZ3xnj522VaVZ9D78jw0V8bpDjrcPq5KKV1z50pPvyrgxz/boVTz9bp327yoV8ZYO6izVNfLGC3o1XPcyOp+PZ1XFq6KfPwT/Vy9N05nvpigWrBJZXT6N9urhpjiirxjk/28N6/0cepZ2u88p1I4qFrQF9trZKiwOy3f7KHwrTD8Ser+G5IPKXSbqwcd+CBDD/xWyO88WKd409USGY1HvzxiPz8j389RavqI8sSuX4dux3wzF8WsFshe+9K8cnfGqFa8Hj18QqyLDGyJ04irXL6+Tr3fyzPJ/7hEGePNRg/0eTuD+R5/Zkak2ei9/rkF5c4/oTGT/zWCOm8tqbOrCxD77DJvrvTnH+lwfNfKyIrEu/6mV4+8Q+H+W//2yXKCy6aIfHQp3q46/1dfOO/zVOcdbjrvV287SN5Xvovc5x54QbaLpuUBJFkSOc1WnV/FTG7FoM7Y9itgMLM6oSMTV1DgmROw7PDdS2PV5AfNDBjMtPntzYXe8UGbqFOYlc/ej5J4/jmXB7mYA5jMIdbqFN64tSqDDEANRNH1t6UQ+QHCmuyQNB2MAaySJqyaVXm+O5+1Eyc1tk5Ks+fx69e5amRpSiI+3pWrw2g5eK0JkuUX5pg4EOHUOI6rEN4dCnGbuMommRQDZYIhI8pJ9luHEKXTWbc89eN9bkWN6e03G4y8+0/J7CaBLbFeiNd1WX6tsepLDj0bosxdWZtfIrnNFFVE8NMo5sp8v370YwEimoQBv6GKWk3gpkziffEI1fVJtCYa6zE4dwkAjfg8ncn6dmX575/dA/lixUmHp9k6VRxjbXI68S7LJ/rBAROgJne+u4hO5bGrjmRFWkTKJ1fW8D0hrjm+MZcg4vfmmDvx3bx3n/7MLMvzDH59AzVyzUCJ1h1Xrtorepbt+kiySBf9ZH4pc69v4Xm4O4hHd8RvPpYObKuhJGLAFZ4uhGTefsnugm8kD//11PMdCZbWYkI3rVFcFNdGmeer/PC10sEvojEqDuLmqzAne/JkR/U+cN/PM7MxYgAn3+1wW/+5z3c/b4uZi+0CQOYOd/mc/92GrsdIMLo3K5+nW0HEqTzGoUZB0kGqxnw2GcWGTuY4O73d/HqYxVOPVNj+8EE/WMr2lLNik+z4tMzYly3S1VN4vH/schL3ywRBnDxeIN/+Ht72HtXapnw7L4ziWuFPPHZyBpy/pUGt78jix6TqZW8K7USKS4GnPYdNEPacOevGRK9IwYLl21e/GaJ6pKHJEUuvytWEYCBHSb3fSzPiaeqfOHfTy/HviiaFKkeX/0Mukw8BY//j0WmOgTyigUBIpL10Kd6uXyqxV/8hxnajQBFlbBaAT//v2/je59f4sKrTXxPcOzbZV79TmXZXXjp9SY7bk+w/WCCE09Wl5/h/CsNHv8fi2TyGrc/nOXbf7xAMqNy4L4MuV59mfAsTTosTTrUSx5GfP1FQVYjy9VX//Msc5ei7yTwBD//29vo6tc7hEdm371pzjxf5+VvlXGskGbF594Pd+F7gnZ9/Q6XJNi2P87YgQSXO/dUXXTp3xEjkVEIXIFjhyxO2nT16TSrPmMHE4wfb5LOqxRnXYZ3x1A0iVSXxvS5Nr0jBvlBg7Mvrcw3/dtNDj6QYfx4E1mJrE4je+OR61KXsRoBhVmHeErBtUOG98SZeqPF4E6TxUmHbfvjiBDygzqzFywyPRpd/Trzl2y2uvn0qi1qr1wisXuA/HsO0R5fxJosropZkRQZJR0jbLvL2VPLv5bl5ZiUK1DiBvmHDyDHtDWBvOt1euK2YULXw6+1CS032ihd8YrKUpTSLkDrSaN1JQltF9nUcZdqyKaGX24hqTIiFAjPj2KOlEh8UTZU3EJ9VXr4ZmDPlGiemqbrof10v/cw8597bjV5IQpKVhNGZA1a1uGJ/rui+3M1jN4MXe+4bUv3cQVuqUn3g7uJDeaQNBm/uf7626OOABKvW0/jChtBiIJKjzrCiL6PJW8a+y1XWg4D3GvSm69FGAjqRZf8sEll3ll3kS0tnmFox4PkBw9RL18mnuqj3Viib+QuJFmJqsfeBGRVRlak1YvvdRC4AaG3NXfKepH6pfMVvvfPn2H07cOMvn2EB//Xt7FwfIljf/Aa9ekVghN6AeJaU60QrNkC3ghypPIZqV9u7v59a2sfiiStzUoIfcEbf3GexZNLjD00ysiDw+z52C5OffYsZz5/diUVXXDDdyBpKlpvDuEHaxazW4mJUy2EEHz87w3R/40yp5+rUZhxVpnVdVNmz50pTjxVZXFy5QMMAyBYe2/tms+p52rLZnexEkaDGVfYfiiJEVO4+wNd3NEhS5IMsYRC76iBGVdoNwKEiFw4++5Nk+vVMGIy/dtjUWxQxzojBDSrPnY7pFn1sZoB9ZKHY4d4bhRHtFU0az7njzWWCUpxzsVzQuLplWnBdyMipxpR+4oqoWgSYXtlEk9lZLp7FQaGVHoHFL7+pea6pSXsdsi5Yw0++muDfPI3hnn1uxXOH2usyVzqGTHoHjT4wu9Mrwr0vZZwQvTJXD7dYn7imvd1pa1hg95Rg7Im8e6f61v+efegjh6T6R01oww2EZ3XP2YyvDtGMqeS6rjvzISy/Gn6rqBW9HCtkFbdp1HysBoBqiohyyskerMQIcxNWNHi3nm8hcs2saSCZnTa6sR06YaMpEQ/U42IXYfrjMur4TkRIdJNmURGwWkH9I4YiFDw4jfKJLMqRx7OUl5wWbhs47TDTmyRwpGHs7QbAZm8SrXosf++NBdebeA54aqpKvAFzaqPoklkezXqZZ/eURPPCTn5ZJUwFNzzgTy1osfF401aNR9VlwGJez/URbXg0dWvU1l02XU0yfTZNtPnIjfflhEKyt89RXLvINn797LtH3yAyrPnIpIQCtSkid6XIbGzn4UvvbBcksKZr+Au1Ynv6qf3w0cpmRp+w0brSkap2rdvI2i7yDewQkuKjNadwp4soPdm8Gvtzp8tzKE8SBK1ly8SWi5+3ULvSWOOdOPMlomN9qDlk1hTRZSYjvAD/LoVFU1tWAjHJ7atm6YQOHNbc2GGjs/iV48R39FHzweOoHenqR+/HIkIyhJqOo451IXWlWDmv313WQywdXGeoO2Q2D1AzwePUDt2CSFCjP4c+Yf2Y450r6tJdCNYs1UWvnkKrSuOV7Pw6usTnpicpB3WccQKOQvwaYRlJCQUSfl+KC1LmD2D5A6/DT3d1Sm3EFUwDwOfxsQZaqeeJQwFiYxKo7y+n81qFpg8+x1kRcN16gghkGWFZHYEVTNplG8utd1turhNl/RQkqXXNxZj2gxEGNmZlGsGerx7/cKRdtXh/CPjTD09w+Bd/dz9946y/V3bOPXnZwi2SKpuiBCskkV8T45Y3lzXfbal5gKBrKxm8lpMxVjH8iRCQel8hcqlGhe/NcFtP7GHPR/ZyfwrC8uuus1ABCFh2yZ0PMRbGLA8c97ij//5ZR788W7e9TO9vP0T3Zx4ssYTn12kXopIoKpJxJIKzaq/7uJ6LXxf0K6vTyAVTSKeVtEMidHbEqsWpovHm0yeaRGGAkmC2x/K8r5f6EcIWJqyadd9NEOKvDxXFhYhVsaPiBaZq0Oebqacl90K8a8ak1cI29VtnXiyyuF3ZPmpfzzCuWMNeoYNklmVJ7+wtBxsa7VDapXoz8V5ecPSEoEneP6REu1GwP0f6+aTvzFCedHlmS8VeO17VbxOkLYZU1B1iUZ5c+TcagT47vrfVjytoOkyqbzG2IHVhT5f+U6F6pILHcL5np/v48hDWaoFj9KcE2WsqNeQ/VCsvEvBch/cLFUPQ4HVDFa5AaNx0Ym+BRwr5MVvlPjQrwzwiX84RHHWZd89KSZONjtEfv22rzSRzqu0mwFmQmHXkSTtuo/nhohQ0Kh4hEFEWGJJhf7tJu2GT6PsMbgzxsSzNXYdTaGqMhdeadK3zUQ35RV3lhS55hIZBauhIMsS++5O4bQDWjWfwBe0GwGuHeC0AxQ1suBpusTipIMek5k+20aSJYyYwqWTLbqHDDRDYu7izYUWeJUWs3/yJH7NInP3TgZ++oHlVPQr7he/Ya1KH3cLdZa+doyBn36A7L27SR4cIXR8JEUiaLssfOF5Uoe2kb1313WvLfwAd74SEZ2eNEiRRcddrKH3ZAhdfzlWMb6jFzUTx6+1UTNx3MValPItgbtYRVIV9P5slCJvewSuj9+wkQ3tuvewEazxRSb/07fo/9R9JA+OkDo8GllyJCnqlzCkfWlplXZa+8IChW+8Rs+Hj9L7sbvoevgAwg+RVBlntszsnz5F70fv3FI9QdlQIRQIBG65Rfb2ERpvzOMU11pqnLBNTu1Hl0w84SAQyCgk5EwkJiy2Fkh2U4RHNky673wnshHDbzUwuvpozVzEyPWixBK4pXniaZVMj84LX17Eaa8/GUmSjB5LY5hZktIgEIkE1kqXonT1m0RzvkXpXIUd7xlj7pUF2p3gXUWXkXUFr7n5hdVre/htj9RwkliXiVW20eIqow+slpyXZIl4dwy77hDYUVxL4UwJq2xjZo0NtRveLOaOLTB07wBj7xzhjb+8EFlUpEjpeKuWK7tmI6sSuZ1Zlk4VEKGga3eO/N6uVYHNWkJDNVWsikXoh9Rn6hTPlBi6ZwAjtUW3XBiComBs7yaoNQnsTaopbxGBL7h4vMnUG236tpnc9f4u7v9YHk2X+Op/nlvOxnGdEDOuIKsSoXuDZew6gZdhIHCsgNmLFn/025fWpCSHgcD3BOm8ynt+rg8hBH/yzy9TWXQRIfzY3x/iwP2Zay93S7EZi9rcuMWpZ2rc8a4s/WMmjYrP5//d1CpdH88F2xKYsSjz6nqwGgEvfaPEyaeq7Lw9yYM/1s3P/NNR2o2AU8/WOu2FhEFEQjb1HNdRsHCsEMcKeekbpeUYp6txhfCNHUzwrp/u5ckvFnjsM4s47YBsr86Ow29xNfRNqG8EvuD0czXufn8XPUMmsixx/liD175boTC98e46DGFhwqIw7RD4Ino30ooF7Ipl8pm/LBKGUezVY59ZIAwi0jU/YeN7gsq3y8hyRFinzkabqitEDwGFGYenv1RcduvKEgQhy8Qc4IVvlKPNYwhPfbFAGEbfwHf+dJHAE5TmXWQlOn7ydCvKtLrKCu6Xm5QeO4VXaa4qHLpRn9ozZab/y2P/f/b+O9qSLDvvA3/hr/fP+/SuvK9qA3QD6G6YBgiSAgECEsghR6I0mtGaWTPUcFF/kEvSaCQOZ7goUkORFEnBkgAJgnBtqrvRXV3eZaW3z/vrXfiIM3/EzZvv5bvv5XtZVQ1wab7V1ZkZ7pyIG3HOPnt/+9tUv3uN9LlJjLEiIvDx2xbOeg3zbgVreUeUIhTUv38Te61O5uk59FIaWY9hLW3RfO8O7laToOsTdO0+/0XSdYTrEro+rQ+jwqDOeq1Xa0vQvriIkkgSmF1EENLq1fy6Fy7q3troS9dIEohA4JZ7xWpFlOXibt8XTozekx31v4TAXqpQ+eZlzFsPj4aIIKRzbZXF/9fvk7owReL4KFo2HmWFNrpYy1U611fxm/cXzqHtsfU779C9uU76sWnUTJzAcrEWy7Q+XCSwHNSk0dPj2f0iB22bxuu3QJF2KWOnjg+BJJF/Zga/Y5M+NYq5tFuA9x4q/hpD2iRnYy9RDzYJhE9cTlFQx9j2lo+cqfVoBo+mo6aybL/1DRCC3JlnKL/zLSRZZvilLxEvFcmPVVB1mbknM3QbPtdf3+uCyw2dZGTqWTyn0y/xHng2rfoSfAyDp7ttcuVfXueZ//0TfO5vvkz9biMqfZCPsf7BVj8t/TAI3JCl11Z5/JfO88pff4HWSptEKU68GMfboaisGArnf+4MqbEUZtkkcAOy01m0REQUDtxPR3Bs/d0Nll8b4syfOUXpTJHOVhc9paNoMpd+/RrNxcMXq2uvdVh7e53z/8EZCidyBE5AeixF4AS7PBT5uSwXfv4snuVj1x3UmMLwhSEaiy1qd46eLRKaNkHr063DdC+zxLVDVm6abMxbFEY05h5Lkcwq/dTe5esmJ55KkRvSqKzdN77kAzKPBsHuhizfMHn5qyVyw3rELxG7+wIRgTOVU7n5bpvt5WggNeIyEyfi/GkowJ3Oq5x9Ic23f3Ob7/+bMvsl0g2PqVx4ykCWYWnexxkUapFAVaPMG7MVcPm1Jo1tl//07AlmLyS5+kYTIaC26dIou5x7McOdDzv9iU/qaZsdJZmvvOLQrnlMnU6gGXJfcfpeX+4ZrKXxKHvr7sUOnUZ0TCqvMjRpsHDlT1aGMuLiJEnlVf7xX59n7Qiej8CHwN+tPP8g/B3ezJ3p7X7P4A88cV+1fkD6exiAO0DvZlc/HtaGL+hV7hkYprNXayz9/aOproeuT+fyMt1r6xjjk/jNBlo2j292UBMp1FQGEQRRGRlNj0r5tGUa319FBD56cRhz6S5Bp42cSGDebdG9to2SKCICDS1fwKvXEL5H8611WsoWgeMSG5+OynVIEnq+QOfmVYC9mkBBeF/k+d6fu6gOYi/1YdcNClofLND6YOHwD0VEGVuNN27ReOPWoU4Jbe/AdnaW59gJt9xi7X/97p7t3aUqseEMzStrWKt1AssncAbP95Zoc8f+kHH9OKPqHIoUZWmtubfZ8paORFiGj6HDI4IQ4UUTvqwbyKqGb7ZxatsY+TFW3n8f3xMoqkQ8PbiZdH6a6tY1aps7FU1FVHfqY0CEgtU317HqNrM/NM3Q6eN4VofG4ib1u40dB0p01hOEto6RKvQKfu7F3a8v4Ns+48+OkRhOUL/b4Nq/vsmZnzmF04z6GnoBGx9sMfWySmokQzw3Qm1+hWu//S5bH22j6ClUPYZZsVl7e2OXx0QIQfV2nW756JO+03K5/Gt36Wzo5I9LZCbTeJZP9UYNp+GgxdIkChPoRoLVN7dw2vt7UKy6zdt//wNOfPkY2ek0btvlztfmkTWF4ulC/7j2Rof6XY/h82PoySqBE7D4nWU237dxu9EHGvohlRvVPYOXb/msvb2BueNehR/gbVT6budPA0/8UI5EWqGy5uC5gnReZfxEnJUbZt/74pgBb/xehV/4v8/wE391nHf+qIrnCBIZBVWXufxa49B6J4Ev+PBbdc6/mOGn/9MJvvfbZbpNP+KNTBksXjVZvNqlU/do132mzyY4/VyawBecezHDyEwM1znCzN6DrEjkhjT0mExhVEdRJYanYtjdAMcKaWwfLWwoyRJaTObY40k6dQ/fjzRiKmsu1Y37HKjtTZ8bV8A2xR59m3tIpBVe/IkirYpHsxr14/iTKWJJhfKK3R/01+5YXPpeg+e/XKDT9FnsGRyZkkaz7HHnCKrRVifg9d+t8JP/8Thf+uXRXnmH6PfPDeu887UanbpPZc1BViTOvJCm2/Ix4gqf/bMlZOXRPLNGQiZdUNF0mXhKQY/JjM3FMNsBnbq/K4vsoZBAlqV+ZmBpwiAMo1DR5oL1/1dvfigEajKNhIQIA9R0FuG5yEYcJR5HSaYJrC7u9haJ46cgDBFhgAiCfqhGkmTUdAbiCXyzi5JMggA1nUGSJPTSMM72JhISxug4wnOjWnV/wnf+pxFB18VcrsJyDRGEbH/nxoG6QK2wStdu9mpnSQgR4uP1nSRHwaORlgOf0HPQUlnsyjqKESd97DzmxiKx4QkCyyTwBXOPp2mWXfR4JKj1oPvfd6NJLwjcj62q/CBCP6R8pUL5SoWZF2Zprq/QWLmy+z6E4IP/+Q6l48+SnTxP+dYbiAHLeLfjcfsP5rn9B/O7tm9fvp8FFvqCldfXWHl9DS2eYfq5n2bjygJmbROA7MQUifwoGx++xvp7D2hDCLj8awfXtjkIslSguzzFjd/5fXxn92rUSKdJFCeJJU7w6n/5m3jmAR4fAc2lFu//o4t7ds1/c7H/d6tqs/zHHpVLPivvfS/aKMlMP/dV9HgT2yvjWz4f/i97azaZFYtv/83Xdvc/pqFk04Tm6qHv+ahIZhR+5BdHSeVUwkAQhoLbH3T45q9s9dNjwxCuvN7kt//uCp/7c8P85f/6GGEQCd198K06V9+I6sQB/e0HYfWWxb/+e6t88RdG+Av/tylkJUqBX71lMn85+p1aVZ9Xf22LL/+lUX75b83iWCFrtyy+/ZvbPP/lQv+zCIPoHYOeMKF3P/079O97n7IllZ/7v05RHDfIFCMC9M/85xOYLZ/VWxa/9t8uRfpoYS9ksOsWonvaaaQmsyqeHfLYZ3KceDINRLo2lTWH3/57qyxciu4jHpcZm1BxbMH6qs+gsUiSYOJEnC/98ljk6QkEVsfn27+xzZXvN/t9ccyQr/+zbRxT8LmfHeJH/+IIQkC77vNH/8vub8d/oL87Wuv/Vu98rYYkS7zy00We/0oBiUhQ8PKONheudPn2b27x4o8XeeLzeRwr4PL3mrxr1vrXF+zmTkVhmfvE4sC//5ucfjbNj/7SCMmsyvBUDEmGX/5bczhWyPd/p8z3/20FkAiDvcTjSHgy7HsBFUXCiEfuvi/8/AieG6IoErIicfWNJv/m76/SbfxgjJ7isQynvjzNtd9bpLlygOEpwZmvzDB8No8kS3TLFu//rzc/1cSEnUiPJjjzEzPc/KNl2tsOXqNG6NiEjo1sxNAKJbx6VLQ1sCwCs0NgdrCWF6JSCYoSFdi1IzKtCEP8Zp3QcQhsCyUWQ02msTfLKLE49sYqfrNB6PuwNE/ousi6DkiIMCQzluDMT86y+NoG2zcO9oLPfWaMqRdGkGQJp+3ywa/cwu3+YGpxxXI6F37mGAvf36B6p/nwEx4RxnAGSZWxVuokpgvYm038AcRlpWeiBPgEwt+1XZY0vCMqLUtiUDndezv3ISJJikL62HkCq4u5sUT+/PPkzj8PQOjabL/5dazNBYrjMVw7IJHR2Jzf670ojJ5j4thnMdtbeE4HhMD3bTaX3yUMPjkux8wLP0tz/SaNlasDbkZm7MIPE3juvgbPUXHf4Pk2Zi2qXCyrBrKi7jFIPgmkR45TOv4sK+/vNXii/mSZef5nWHr3d/E+ofpfxWPPkCiMs/Le7+1oJ4PvdI/8DCVNQdK1qLTEpzQg6nGZdF6NFIYlicCPUnu7A1J6ZQXSeY14WkHuqSN3mr1Vea97maJKLKn0w1D7QZIi4mwqp6LcC+e0I0LnvcckK5H+STylEAbQaXh4jiBb0qhvufieIDekISsStU0XVZcoTRjUNlxcOyQ/ooGA+raHqkX7FHXvt+s5YZSZRhSqiqcij9eurKYpA9cOaZY9ShM6f/FvzLA+b/O9375PUs4N6/z8X5/m1vtt/u0/WMO1QmaPqwyPqSSSEm/8sTUwS+ves0hmVVRNBgSOFdKqertVrOU4E4kz+FoHM77Uz0BzrJB2bcexEgxPGdjdoE88B1AkjdH4Ccr2Em4YjTuKKvXvGSkKq3SbPlb3/m+qx2QyJQ1Nl/rZWEYiyvhsVjxkCUqTRt9DM1wqMFs8y92lRRr+OsVxnVbNx+4EJDJKTxxw7+/Qrnu0qj4xLc6ZudMs129S2yESqhmRF7Cy5uBYIU/+cI6v/OUxvvOb29z9qBORmmWJsy+k+cpfGuM3//tlLn3v05ucdmLuM2N88b96lj/6G2+x9v7BCSEzL40ycr7A3OfGUQ2F3/iFbzw0q+yTwtQLI/zE//Mlvv5fvc3Ca7uNZElRUBIpArODeMSib5KmIxsGQaf98IOB0QsFvvTfvMib//AKt76+fOCxY48XmXx2mKnnR8hNp/iX/+GrdCsfTzblsCidyvGz/9Pn+f7fu8T1P1jcUybok4AS1yi+dBwlodO6vknh+Tkq37uJtdbYc+yIOktOGeam886u7Vl5iGn9DDed93Af4PEcYNI8qocnoHX7Uv/ftctvYZXXUONp7Oo6odkgXdAwkgrZYZ3CuDHQ4Ak8i8r6bi9AGDh88vRMCSNdYvj0K4SBT3PtOp61w9MxoDk1liI7cQbNSNKtrtLZXkCIEFnVSY+eIJ4ZxunUaG3cIvBsJEkhPXqCRGEM3zF3pbrkph8jnh2hW12hvXkHEQYoepz08BxCCGLZYTyzRXPtOoFnI6s62fEzxDIlJFkh8Bzqy5dxuwesDGSF3NR5VCNJt7pMe3N+x40NSOeVZZKlGZKlaXzHpLVxC8+MBs1YdpjM6ElAor09j1WPCHF6Mk92/EwkOKXfz1LT4hlKx58l9D1qSxfxrGgQSA3PIUkyRrqErOp0tu5i1jcAQSw7Qmb0BErvOmZtjZZ1C3HEmOxh4VohVetwRnQYRNoozcr+q6pW1d81ye4HIaDbDA4MO4QBNLa9PeGmncJujfL9fb4r2NyRhl3f2rHPE7sUi/dDu+YPzILaSYIdnooxfTbJ1/75JltL97fb3YD6lksiHZVyANhcD8gVFMpbAd4Dj62gTxBX0phBi267jmOmKXsVEmoGAE1AKT5MKAJqzipuaNH0yhhBgmrdRZE0SsY0MUnFDcpIskVOH0WRNNxNk5a7SlzJkNNHEULQ8DaJKylGYnP4wqViL0MoobfHCdsyDXcdJ9w9HskoZMUkWjVGx6/jBF1icppWrUJaLRKXXTQ5hloukApdHGmF7UoNOhtIQiXwBY1VmYI+hxSTaXQ3qHUhqw0jSwqm36TpbZFU82S1aWIxj5a3jbkZJ+bNMBxzqTrLqJJBXhrDWw0JnFXA5fSzUajz8vcbu96j9aIWyQikPz3Bzo+DpTc3WX5rEyOtMf3i6A+07dp8izf+wZWB3hQRBPjtj2cgCs8l8D6dBIuNS1U2LlcJvZDc9MlPpY390N7s8uY/vML6h+VPxdgBUNMx4pN59FwCJa7jVju49cF0jpSSG6jHF+ARk5OokrbH4Dmw7UfuNb1aWkYcEYZYm8t9unmUqSFRGDdoVbx9PUXN6gLN6m4ilKolCINHJywPgqzpJIuTNFavkyiME0sX2bjybQJv8MSg6AlGzn6OwDVxuw0Kc0+haAbNtRvkZx4nkZ+gW1kiNTSDnsqzfeP7fS9Lc+MmeiJHPHtf88NubBLPjpCbOBMZTmGAaiQYf/xHaW3ewayvkx0/jaLplG+/TXbyHKmhWZrrNygdewanU9u3r/eQyI1i1dfxnQ5DJ19CBAGd8uK+x6eHj5OfeZz29jx6IsfYhS+w/tE3UDSD4dOvYNXXEUIwcuYVtm68jtttMHru8wSejd0qkxw/0/cWBZ5Ne3uB8cd+hPb2fN/gyYydIlWaorZ0CUmSGD3/w6xe/CNEGDB85hU62wsEvsPQiRdorF5DHKQ1fxRIElrGQE0aIIHfdvDazh7xMT2fQImpBI6PWzd/oFWOk7MFJn/mCdb+3WU684MFMo2hFFN/5kkSU3lkXeH633kVp/zpVj3fCbMTYHUCzr2UobIWZfqomsT5l7NMn03wB/94A9cWJFMS6azM1kbA1KzKyoLHzkcZCB8nNBmJHeNu5z0KxiROaFEypqk5a/h4uKFFQR/HCU0a7t5yAF7oICsKw7FjlJ1F8voE6+Z1RuLHaXsVxuInqbvruKFNKAIUSccKtkipBTLaEIaSRJE0QKJoTLFh3d7DAfCFiyQURmPHmO98SCk2i9ltUYrNsGHeiio0hybDxiwdv4YZ7J40BQIvtEmoWUrGNGbQIqMNUXGWKBqT2EGn73nyw0iQTpFUTL9B0ZjECbrk9BG80CGhZAlCj6q7Sn3b48JnVE4/m2bhqokIBamcyis/U0KSpSOrEX9cCBFxxZKlGFpCJfBCrLqDbz/aYkVPaRhpDUVXEKHA7XrYDXdX+CueM4jl9maA+nZAp2z1J2ctoZIaioMEK+9u4bT3LlqMtIaWULEbLrGsjhpTCAOBVXfwzN1zj6LJxAsGakzdrT3khnS2zX6Y+VCIEq+IFwyMlLZvm4eFllCJZXQUPZKF8Swfs+7sMlSMjEY8F9uTABE4AZ2K3c/iVQyFzGgCJFh9fxtzgBCvllCJZXWsmtN/hiIU2E0Xp+PtWlfLqkQ8Z6Al1F0ZyoEX0i13Wf93F5EUGbfaPVClW0IaSEyOHqWM9LDCfQ/gkQ0eNZEmd/55UpMnojpab3+DwHXIHDuHXd2kVS1z7bU6YSDo1g8ffxyfe5mNxTfx3E8u9COCgE5lgdrih1iNDSae/DKqkdjXiDBSBTIjx2msXkPR46h6nMz4adpb8+SnHsPp1CLPhCSRmzhD5fbbZEZP0K0uU51/HyNdIjN23zK3W2Xs1jZabG5XO4HvUl+6RLe6iiTJJApRar6RzOOZTTqbd0nkxhBhQOgfvJpwzSa1xYu4ZhMtniU9euJAgyc3fQFZ1VG0GLKikh45jhbPkCxOYqSK2K0yMhJGqkCqNE1HhBipIsvv/S5Op4oWz6InohV66Lt0y0sDyOYCs7FJ5e57aPE0ydI0WixF6LuoWpxuZYUw8MhPXYg8bp8Ej0uWyD85ycRXzqMXk8iqjFPpsPDr79G5W+6rhg69fIyJn3wMSZMRXsj616+x/d3bPzCjR4nrpI+VUJL7p/G7DYv1P7pK4dlpZv7CsyjGD1bafu22yXd/e5uXf6rEE5/P4ZiRwKEIBW/9fpUPv1Un9AVDoxqlYYUwFGRy8q6JQZfjFIyJyGOipAhFQMerMRo7Tih83NCiaEyjSCqGkkKV9mqMJNQseX2MQHgYciJKOw7atP0qJTGDqsRQJZ22V8MXDqpk4IU2Hb+GKuuoskFMSaNJOlbQxgn2ji0xNU1eH8cLbQwliS9crKDFZOIcTmAS4DNszBGKgJiSQpYe/C0k0lqJjDaEImmEIkT4DcygScevk9PH0GQDBZW2V0EQYsgJnMCk7VdJa0U02SCuZFAlB084+D1+wnvfqDF5Ms7P/p+msM2A0BfEEpFe1O/9o/V+vbUfGARMvzjKU3/xFJnxFCIU3H51hY9+8/ZAA+MgpIbjPPvLZ5h4ZjgSI5Qk6ostPvz1W6y8cz9t/OSPTXHup2b7wouSFBlc2zfqfPNvvYvZC/kMnc7xwl89T7IUIzOe5N/9F99n9b3715EUiRNfnOL0V6ZZemODuVfGSRRjIMP8d9f54FduYlaja8mazLmvznLqSzP9CTw5FKdbsVh+a5O3/+drWPUjcEiEYPR8gZNfmCQ/m0aSJRa+t86Hv37ryCGreN7gqV84xczLo+gJFSSJzrbJxd+8zd1vr/WPm3lpjCd+7gRq7L4XMFmM0Vjp8OrffpfGcrSAyk4k+dz/+UkShRi56RTf/FvvcufVlV1D8tSzwzz3V85x+9UVpp8bIT2WQFZl1j4o884/uUZrPfquZEXixBcmOffVObSEipHWyIwlMesOK+9s8e4/vY7jyX1NpORcCWe7jd/Z+yzNsM2IOoMuxfueHAmJjFIExC5ez2HwaMVDVY3C4y+RmDyO32lhFIYjsToRkpw6SWpkiFj3XWKp6PL5MYPKb0XkXc1IYcSydFubxJJFjHju/nWBRGaUTzofV4gwMm6EIPTdyCo8oA1Z1ZAUldB3EYFHc+16lMElyah6HMuzEYGHVV+ns71AGHjIqk7g3mvDe6hHBsB3THzPBgRh4CNJ0UvZ2Z5n7MIX0RNZwsCnuvD+Q3kxgedEnjEhCDwbPZ458HjVSBK4FiLwcLt1tq79Ma7VJKOfBAQi8AjDgOr8+3QqK8iy2uunF3Gt3C5aPHXwDQoRhclElPWACJEkGadTw+3WGH/8R/Bdi+b6zU+O2yTAKKZoXFmneXUDOaYx+wvPMvnTj3Prf/wuoeOTnCkw+wvPsfGN69Q+WCH32DhTf+ZJzNUG7ZtbSJqCGtfwu+79qsG6ghLrbRMCLWUQ2B6yriLrCsIP8bvOkd3AsiKjZWJIqkzo+Pim21/tCC/AXKljlFL7G2JSZDwpMTUizloege2BLKGljai/foia1JFUBa9pgSShpgxC2ztQ08RzBH/8m9vceLtFfiTK+PKckPq2x/ay3efSLC94rC975IoKq0v+HuFBVdLwJBUraCOEoOltMxSbYdtewBMuiqREx4QWfuiSULIU9UkUScP0m0iAKmv4gYsddAgJCUS0AAiESxB6tLwyk4lzBMKl4qzgCzf67oVPKHyqzgp5fQxJknFDe493R0JClXQ8XKygAwha7jbH08+x2L0YeY1QkSQZO+wSCp+0NkReH0MgsIM2CjKqpOMLDzewCEVAIKLvJRAeXujQ9RvMJJ/ADU1q7hq+cIkGbg8vtCk7S6TUAhISbhiV7altuPyrv7PM2LE4yWw0plqdgMqaQ33TPVKa/icBPaUx/kSJS791h862xdgTJZ74uROYVZsrvzN/JEZCGIR0yhbv/OOrmDWHWEbn6V86zVO/eJrK7WbfoLj77VU2Pup5QiUoHsvy/F85x9aVGu4OI2v7ep3v/D/eZ/ypEl/4G88O1D+TVYnR8wVkWeLSb93BrNpMPDPEua/O0VrvcOlfRbIloxcKPP7nT3DrmyssfG+dRDHGS//JBcy6w7v/9Dp282ghLTWuMvX8CBd/4zYf/sYthk7leOoXT+N2Pd7/lZsE+4hn7vfcrIbDh792i/aWiRZXefzPH+fZ/+gMm5dr/cLRK+9sUZtvRs9BgvRIghf/2gUqtxp9ww6gudrhO//d+xSPZ/nKf/tSJLj5gOdFUiRKJ7JIElz+7bs0VjsMnc7x9C+epr1l8vY/ijiyxeNZnvrF02xcrHDt9xcxUhrP/e/OosVV3v2n1+lsmaTPT6DENOzNJpkzYzTcYKDBU/XXGVFnOB97hWawTYBPQs6QVUpseUu44miG4qMVDzXixMdmqX7wPUQYUHzqc9EOIfDadXITRfyWoL7hIAQ9GfEIsXie/MhprG6VkamniSeH7nsGJDBi2QEt7kU8XiSZGN67Q4R0rQqWdV/ISFZU4rlRVCNJLDNMGPjRxA331Wx3fBe+Y+JZLczGBmZtDVnRojTF0MdqbeM5XRqr1yOFSklGhCFut0EsO4xqJDFShX0Mjgc+vn0U08LAx7PbbN38Pr7djQyph8BI5TFSBRCCWHoIq7G5o9megMmO5u3mFrKq01y/hQgDZFUn9BycTpXAnaS9vYhntSJDzrPRYpFxE0uXEIFPPDsSKWw/5B4HEcjCwAdJprFylfb2Qt8YfRCqGieTnkCW9676PbdDq7OOeFBpUwi2v3srEjnzQ5CgcXmd0guzyKqM8CQyp0YI3YDy9+9ib7fxWjZDrxwje26Uzp0y2TMjTP/5p7nzj1/HXIk4ALnHJ5j8qce480/fwO84nPrPPk/r5hbJqTyx0QyhG7D+h1eovL14aC+RpCoUn5th4icfQy8kcCpdln/rA9q3Dy7b0ocskTk9wsRXzmOMpJEkifbtbVZ+9yMQcOr/8HmWfuM9OncrzP3SC6SOl7j8t/4QWVM4+dc+y9ofXKHx0dqBTXiuYOWmxcrN/cMmYQDjsxqnL+goCrz6B90+adkNLRY6F+8fi48b+txuvRUZIwSsWzeRiQxqX0Tf5WI3OicQPkKEdP0mkTZrSCgC7CDi4K2ZNwmEz7a90AtZRddYM28QCJ+qHRUPFoR0/QYSUmSEPADTb7DQ+YD7+VhgBk2uN1+LjCdCVswrSPSUeoWLFMjMB5EGSRB6mH6ThrsNCAIChAhp+RVC4ff7s2HdRpFVhBAEwu1v37LnCXsh3Za7DUg9YyhCpxFw+4NoNa5oEqWZBJ4HRkrF7vi7MmBjRo5UcnSg/LZl1eiaewUYjwJFlbn96gq3v7VK6IXU5lsMn8lx6semuP57i0dSlDerDh/++q1osu+FfLKTSU59aZrkULxv8HQrdt8LEs8bPPkXTlK53eTyv5nH31G+xrcDGisdkkPxAw0v1VC49u8WuP3qCiKE2mKLyWeHGXus2Dd4SidyyIrMnVdXqS+14U6T4z80QfF4FqfrHTnjTFYklt7Y5ObXlvDtgMqtBoXZDCd+ZIqrv7twJC+P0/K49Ft3CP0w+u0l0JMqz/3lc2Qnkn2Dx6o7/WeopzTO/vgsZsXm4m/cxu3eX5kEbkhztYuiRZ7afZ9bTOHWN1a48UdLBG5I5VaD8SdKjD9Z6h+TnUwRzxnc/c4alVsNkGD8/RKnvzyNa0bK3oHlkjo2RP7ZWbRcfN+FlyNMbjsfMKWfIqeMIEkygfBY8+6w4c7/gHR4ehO9320ha8aefd2mz9a1DsMzcSbPpKiu3f8h240V2s1VEAIRhizd+Dpmp9w/99j5n2TnmyrFNLShHPpYAfv2Gn69gyQpDJcucGLux/Z0LQg8Fpa/w9LKfcGjwHOQVYPxJ76EFkvSWLmKb3eIZYcpzD5JeuQEQgRoRpLqwgc47SrVhQ8ozj1NYfYpQt+hvnSJTnmJyt13KR1/jsmnfwIRBrS37lJfukRj9Sqj53+YqWd+Es8xIx6LEOiJHIW5p0gNz6LF0ow/8WPUly7j2x1E6N+/1572A4CsaMQyw4yc+Syh79Lemqe1cbt3/F4IERlchZknUGNJQt+jsXYNSVEpTD9OauQYscwQ44/9CJ3yItW771Nd+JDhUy8x8eSXESLEbm1Tuf0Orc07xDJDjJ77IYQI8OwO1bvv4ZoNmms3GD71Ep7dQZJlAt8FJLKTZ8iMniSeGWbk7GfpVleo3H67ZyTefyHDwO+XD1E0g/z0Y6SG53DNJvXFj3AfyCBLJoY4e+pniRl7jeBq/TbXbvw2rreX0xLuEHmUDZXYUAp7q40IIkn0xFQea6MZeVOAwHIx15oke1wZWVfQsnEk9b6hLutqtK1XekPPxhn+3EmWf+sD3IbJ0EvHmPulFzDXGnQXD1daQ03qJKbyrP3BFUQQMvnVx5n9+We59t9/M/LSPASx4TRzv/g8nbtlNr55HUlTmPlzTzP9555m9d9+hKzIGMUUTq1LbDiNmjJITOXxWhZGMUlgfnKky1BESr6xuMT5Jw2uX3Kxrejd9gekju5MJw2ET8Dud9sLHyi4+8BKLujN8PeMl5Bgl8z8vf07B0RfOCBFK9UHx0mB2JPiGm2zd5zvPbA/IHzA8/qg1L3Y009/l4r8ve07XfMPS7WdeTzL+Jk0ZsPDc0Nuv1nF3lF5vJA/wemTP408wIu9vPY6t+/+4YHXfxh8x6e+2O7zP6ymQ/Vuk9NfniGWM/qT7WEgyZAaSjDx9BDp0QRaQmXoVA41pqJoe/uvGgrnvjpL8ViWP/4fPjxSWzvhWT5b12p9Q9FuuHimj568v7hye4r8iWKM5loHNRaFZzzbP1gQcB8EbkhtsdXnOrldn/LtBse/MEGiGDtaWEuCeCHGxFMlshMp9KRKbiqNFldRjb0LUUmWOPGFCaZfGuW1v3uRxuqjcQEDN2DrWq3vjXK7PlbDJTN2X5Hcs3xCPyRRiiGrEoquEMvp+HZA2Mv0NJdqaJk4xlCa5uU13Or+/emEda7bb6NJBjIKvnD3jBeHxaNlafkevt0hPjqN321HNWf0OLFUlsTYLO35qyiazNiJJIuX2sw9kWbhUntH0lD0l7WF13uhH9HfXt+63ptII0iqgj5eREkYSNqj2Wfrl74JIkTR4ggR4tntqABqt0F1/n1qCxd7zYd4VgsR+pGBs7WArGqEgY9vR27ubmUZp11F0WKAiNKwRYjdqrD64R+i6DFCz+3ts0CC2tJH/ZR4gcC32oSBx8oHf9C7LjQ3btEuLyDJKvmZxynffgunXUWNpykdfxaruY3bGSy/bVZXWXrnd5AkGVkzCByzFyKSaG3eoVtdZetapJcT+NHzdtoV1i+/impEL2rg2QRelCG3ffMN1Fgqqo3muz3jLKBy912a6zd6xzu9FWTvmbSqlG+9BUTlQcLQp3z77f6A7zsmaxe/RuDZpEdPEPoe9eUrhIFLZuwUxePPsHHl25+4HlP23BjZ82PM/4u3CZwAWVdQkzqB7fXDVSKMVhyxofShS4AIoHF5jfJrdxChwGvaZM+PkbswfmiDJ7A8tr9/l+rbi0BUCHbul14gOVekdX3z4JOB/OMT6PkEnYVq5NFyfLorNfJPTrH5zRtYGy1ioxnchokIQqzVBsnpPPaWSmB5uLVPTt26WQ+5c8NFUSQ2Vn3cQwo0/qBh5OPkTg9jbXdwGhZO3frUpBA+LSSyGmbDIzOk49rhkeoYfRIIvHC3F0fQn8S1+BEyxqSIC/T8XzmH2/Go3GliViys4TjJUmyPQxwJpl8Y4eSPTPPRb95i+/rha/Y9CM8Kdt1Df9jZ8SxX3t3i+BcmeOX/+DjrH5aJ5Qyykyk+/LVbj1QXMQzCPYr7vhMgwogQfGhIUer6S3/tAkLQD0/pSW2w10mCkfMFLvyZ41z9nXlW399+5ERo3w53h97uRSl2/FZb12usf1jm2V8+w+iFAmpMZfRCgSu/M9+vTqAmdSRFxmtZqOkYsq7umvcH4aiaO4PwSBZE4Ng0r3/A0PNfjC6SyjHyyo9jFIext9doz19DBAK76zN5NonV8Qc+4Gj1v3tHvXwbSVKiUJEICTs29vwGwvUIH6EqK9A3Knxn9wAf+i5Oe7ARIcJgj8ch2iHw7U7/mjt27LMd3H0UnO+lgUd9cQh9B0VPYKQKlG+/jWc2SMgykqwcOKiFgdcP0bFrwSPwrNbuFPwdCFyLwN27Qgp9d2Cfw8AbqEbt2118ey8HZxcvp2dMIskYqQJB4GLWVkGSyYye3Cc89vGQmMoz+3PPsP3dO9Q+WO6PaiIUyOru1aMky0d2Udtb7X7Izq2beE2b2MjB3KmdCL0AZ+u+joe13gRJwigern5TYjKHUUox8VOP7ep7Z6GCbzp0l2uk5or4HRvfdLE3WySmCihxHafSwW1+ctk9iaTEZ34kwfqyx50bj8YrURSdRLyIYeQw9DSKovfCmRF3zPNtXLeFadew7fojZfU59cjIGfv8cexKl+btMo3rhwwhPgSqGieZGCJm5ND1FIqsgSQRhj6+b2M7TUyrim3X+TjSG+s325x6uUg8o7Fxu4H7iNlRjwpFV1B20BTu1e4DdoVJHoZYVufCzx4D4NW//W7fw/Hkz5+kMLf3OyrMZnjqF0+z/NYmt19dPVqG1IM4xMKqW7FZfb/M6S9N98M3V/713YcKB+4HWZNRH0g80OJRFpN7hPqOWlzl3FfnSBRi/OF/+Sa1+Wh8P/nFScafGtpzfHokwfN/5RzVu02u/Nv5I3GF9mIwDWMn7IbLyrvbFI5no2y2cptb31hm83L1fuhVkaOiqLpC+tQo3YXKJ+px3g+P5jIRIZ2lm3jdFqmZ0xj5IYTvUXnvGp3lW/hmG1WXyI0YDE3F2VwYvJIcmX4W12riexad5jq+Z0b1tSafIQx91hdex3KrJM5NIyky3Yvz+LXDCT39+4rAtagtXmTkzGf6HpbK3fdwu40/6a59MhAhzfUbFI89y+RTPwGA061TvfvuJ+rdSc4WOPbLL9G+W2b1dz8itKOBWAQhTqVD5vQIsq4QWB6yqqDn4ri1bhQT73EJdhqZSkzdw4mQ9ftGmiRLIPPwwoY7IUlIO9z2kiJHod5DcoDCHqn59v/0PZwdOhYiCPHbDvZWi/yTk6TmSnRX6nTmK0z8xAW0TAxztf6JZqQ5luD73zJRemrSh4EkKRh6ilRyjGLhJOnUBLqWRFF0FEXvL3xARIufMCAI3ch4sOvUmwtUa7cwrSpheLgJwygkUOIqq9+4SWD7xErJA9NiHwZNTZBKjTFUPEc2M4mupVAUA0XRen2PpPBD4RMELp5nYVplKtUb1Bp3cd32kQ03RZW58VoFxwzIj8d77+kPzkulGgrDZwusfVDGtwOSpTjDZ3I0VztHIvJqMZVYWqe10aXbI9DqKY2R84XdBhVRWOmZXz6DWbO59Nt3dvF2Pi3oKY25z45x51srfPgbtz+2Lo2iygyfzXP7VQ234xHL6oxeKNDeNHcRiB96HV0mnjfobFt0tqJFixpTGLlQjDK2dsBIa1GWliHzwa/dfOQU+KNAi6sc+/w46x+WeesfXRlomPptm/b1jchYzsY/teLaD+LRa2mFAfb2KnZ5jb4/SwjufXiSLCFJsHi5TbcxeDCKJQoUhs/gOm1S2QnW5l+jMHyGyuZVVC1GcewxVpe/i/AC1GwyKsP7CaJwPEPoCRrLj25EZSaSjD1eonq3SfV2oz/Y52fS+G5Ae2OwsRcvGOSm02xcfFCDRVBb/Ij6ck+QUYj+gFg6lcPterTWHj2jKTedYvTxEttXa9QWW/1xsnAsg9vx6GwPXvUnh+KkRxNsXh7sETsKnHaV9Uvf7BsUQgj2LTv+CIiPZZj9hedw6yZL//J9/O79QVgEIe07ZUa+cBq9kMRr2uj5OMmZArX3lwl72QKyIqMXEjAfGSLpk8OR3sUOpE8MI2sKoRsQG81glFJ0F68/2J19ocQ0UseGqH2wAqEgfWIIIQTmeuNQ57dubTP8uZNouTjtXso9UhQGFkGIU+6gxDWMoRS1D1dwyh0kRSY5nafy5vxDr38kSFAsKdSqwSGmXolkYohS4TRDpQukU6N942CwJzPiDMqyioqBrqVIxEsU8ieYHH+Rre1LbGx9eCgyrqIrOHUL3/SIFRM0bj6ae1+SFLKZKSbGXqBUOIWi6Pv2X5IUZBRUJep7MjFEsXCKTmeTtY13KVeu4geHm/BSBY3Hf2yY+rpNs+ww91SO+oaF/7FW7UeDa3oc/+EJAi+gtdZl/KkhRs4X+O7fuUjYM6K1pEp2IoUWV0mNJNDiKuNPlnBNH7Nq09m2sFsujeUO40+XOPOVGTzLZ/zJUuTdeeB2zv7EDDMvjvDhr90iP5MmPx2VOfF65F/fCZAUiexEEiOjUzqVQ5KhdDKLZ3q4XZ/6Ecd5EQhCXzD90mhUjsULozqF8y3K1+tHVo32nYCJp4d48udPUr3bZPhMnukXR3nvn9/A7mWaqYZCdiqFnlDJTKZQdYXRx4p0tiyspkNrrYtn+tTmW5z+8jRnfnya9pbF8Nk8E0+X9vTp2A9NcOrHprnxh0ukhxOkSpHQq+8GVO80I4+cBJnxJPGcQX4mjaxIFGYzjF4o4po+jeX2kbxCIhT4TsjYEyWe/IVTBE6A7wTUlzpsXakSeCHGUJrSKyciD6jj4bV/MNIKj2zwSIqKURhBz5WQtd1ZNG6zildZQpYlhqZiqNpgQ0WEPiu3v023tcHMmS8hKxqyqmN1tgl8h6mTXyC0HKwbKzjJGEH7kxXYGn9yCLfj0VhpP/ICybcD0uNJ9JRGbb7VXzW7lt8n9Q1CejTJ8R+eHGDwAIiBaegTzwzT2TQ/lsHjWT6F2QwIqC+3+6sW1/QPXDVlp1JMvzj6iRg8QJSq/iksStV0jJmff5bM6RE2vnmDoc+cAAGh59O4vI692aJ9a5vO7TJzf/F5mlc3yJwdwa50aFxZByEw1xrY5Q7Tf/YpUsdK6Nk46RNDPEgqSE7nOf6XX8apdsk9Po690aR5ba9o3r6QIP/4OEpcRXghxRdmqV9cxVprggSxkQzJqTyZs6MocY3Cs9PExrJ0F2s45TbNaxvUP1pl5ueeIXNqhMByMYbSmGsNNr5+DafajYoZFhJY6038joPwA7RsvJ999kkhX1SYO6ExOqmyeMfDHfgqSRh6mpHhxxgZepJUcrgnd3A03DcqJGJGlunJV8jn5lhee51y5fqB3h5JlcnMFQhsP+JTPMI7qCgG46PPMDX+ErFYrmesHa3viqSRzUyRiBfJZqZZXn0N06rysA6FgcBzQlRDxkgo3Hmnhmv+4EJagSvYvNjg9reXmHlhjHNfOo1jRSnJi9/fQJY1wtCjOJfh+b9yHi2pEs9FiS0v/rULBF7I0usbfPCrt/BMnw9/4xZIgsf/gxP4TkD5ZoO3/8k1zv3E7K7xc+hMHs8KOP1jxzjxhShzT1UM2lsm3/k779DZMomnEzz186fJz6XRkxpm1eH0V6Y59rlx2psm3/u7F3E6Hp7p0ylbezwPVt3pj0mSTKSVI0EsrTPTU4rWEhGZ+oNfvcntb64eOgweeCHb1+vc+c4qE08NMfvKGCIUXPz1W9z8o6X+vaZGE7z01y5gpDViWQPP9nnmPzyNbwdsXa3x+v94mcANufI786iGwpmvzBD4gvpiizf/v1d57GeP4e/4+IZO5QgDmHl5nMln72c1mzWbN/7BZWrzLRRV5vxPzzH2eBEtpmLVHeY+O8b4UyXslstr/++PaK118Z2Azra1h79kt9z7Hqqe8aTGFFRdYfr5ERACNa6iJVSu/pt5rvzOPG69y9a3rhNYLqHj/8D0zx5Nh0dRyZ17jsLjLxG6zp56JJ2VW9S3F7G6Ab4ndmUQ7IRjNUmkR1FUAz2WYWT6OYxYBk3vcRgUCTWfQi2k0YZzCM/H2/x4A7WsShSPZzGyBsliDLfjoagy+bkMiWJUzby13iU1miCe1XG7HlpCo3q3iQhCSidzqHGV6t0m3W0Ls2rTWGoRy97PVkuNJCieyFK72+PoSFExu/xsBhEKqrej7UZKY/ypISRFonKzPlC0S9ZkSiey6CmNRMGgs2lG93Ait8OtaZIeTRDL3OuvSuVWA0mWKJ3MIWsy1btNzIpNt2zTWLnPPUGCzFiSwlyG8u1GtEmC9HiS3HSaMBBUe9tjGZ2JZ4ZAwPbNOt4R4vU/KMiajNdyaN8pk5jIkpiIMrwCy6O7VMPebOHWTe7+szcZ/eJpUseKmCsNtr57C3s7WgEGXZf5f/4WIz98isREDmuzxcKvvkP+yUmCnrdIAspvzBPYHonJHO07Fba+cxPngGyDnfDbNlvfvkn9wxWKz89ijKbZ/t5tNr99M8omkyVScyWGXp5DUhWal9coPTeDd9ph89s3ccpt/LbDwq+8Q+nFWdKnRpC1NG7VpHO3jAhCvLZN9f0l1FSszzeqfbiKU+1iH0GxWdYV1JiK23b2nY83131Wlnyq5QB/gL0hSQr57BzTk6+Qzc6gyPonRraVJJl0aoITc19B11Ksb7xHEA4OrdjlLqnpPLFSksqHB6fkD4KqxpmeeIWJ8efRtcNxrR52vbGRpzD0FHcXv0mnezBZ3Wz6XPrGFome6rDvhp+kc/Sh2LzU5K2VZWqVNVa+32BuOs9m+RbVyipSqJGKl2ibm5RvNXnzf1jAchu7stKAXQur2nyL7/3dj/qZRZ7tE7gha++X8cz7L9J3/rsPUDSZTGIMy23i+xYjxfMokoFVjX5r1c/y3j+5Q4CDriWRJRXbjcZaEQictosI4c63Vll6c3NX+E2Egu/93Yv9fydKcV78Ty5Qvdvig1+92ScbawmVz/1fnuT4D02w9OYWTutwIbzq3Sav/u138Syf+T9eRzUiVWnP8nd5T1prHb7137w38NsIdoTLW2td3viHl9EMNVKTdwJ822frahXPun/cW//oKh/99iaJ4Uns+jZus4IIw+h5dHpZql7IB79yc48H+95zsXv3uPreNv/6P/5jnPaO5ybg/X9xo8+JNNI6z/6lM3imzx/89Tf6z0dSJF7+zx5j7vPj3P3uOspQDllXaVxcOdTz+6TwyDo82ZOP07r1Ea35K4QPFM8JPRdZkUikI42Iwrgx8DrVzauMTj9PMjNKZf0jZEWntnWD4cmnUVSDRu0OAMIP8BsdwkOk6j4MpZM5Tn15hsqtBtnJFK0Nk9HHS4w+VsRuusy8PMbqu1tMPDOM03bJTKToli0SxVhPhlzFaTqMPV7iw1+9MZCkJ6sSc5+bwEhpdLaWUWMqJ390GoBu2aKVjDw0mYkUmYkk+Zk0yWKM299c2bNiGDlf4NjnJqjeaZKdSFG53WTy2RFKp3I4bY+Zl0ZZeXebyWeHcbseqeFIu8JI62TGkyBJeKbH6GNFLv76rYExXFmVOf7FKWRNZn57DT2lcfrLM/h2QLdq0YpHr0luOk16NEnxZA49rbH42voPdLA9DNyayd1/8vpDj7O3Wiz++rv77u8uVpn/Z2/u2nZPs8YopRCA2zBZ+73LR/YSyJqMtdli6TffQ5IlWje3QESDQuhHhSElRaL69gLVdxf7WlGlx0exyl06qxFJUVIk/K7D1rdvsvHNG5HUkiwR+mFfxXTlX1+837AEm9+8HmWnSRKyJhMGoifT1DtPlZGAMBRRdfdQoCU0io+NUL64GQkZhqKfsi/RE0GzJV7/roMIQmRVRpJE33t4b1KPPCL5hxg69yqOi55R3guR90Je0f8GhY0kYkaG2anPI8KAtc13B3JjYqUkiqHSWW0ejW8FyLLG5NgLTE28hKrGBvf+HjGenWHae6GuvSEvSZKQJIVi4RQCwe27f4hlH5x9VJpOMH46TaqoY7U83vxXq/suKj8OZEmlmD0e3asQdO0KsqwiOQlCX9BpNKio61imE9V9So+ia0k61jZJbYii9iQNe5lq8y7Z1DiGlqHZXUUTIfnCCKHw8XyTIPBo1zcpZo9Ts+cRQuC0XDLJCeKZHLKsEQQOrfY6spzHblRxPIut7iLZ9DQiEBh6hlR8lErjFgiFoaEzaEqMTfMyAkEuOYGXtWm0lygkjyNEQCwZCTu2zU3iRgHfdbCc6NnHczrDZ3Jc+3cLUZmF3jce+CFOO+LfHMVeD33RX9CGvr8vlyb0BVbtcMk5vhXgW7t/d6e1e450Ox6+2yDwU6jxInphGKuyjtPa2jXXRH07eH4N3BBrQFXgnXOgnlQZOV/g0r+8Q2fT7IfYJDnqW3ZCRpIhsD3iE3niUwWEH+BUOogjfo+PgkcLaUXFsuis3Map7o2by4pEZlSnVXGZPBOlpg+C63RYvfu9SNPHj8TnJEkmnhpCUXXM9hah5BOYDpIs9dOIHxWSLJGfzdBc7XDza0skCjGkXorfyPkizdUOWlzFSOu4HY/NS1W0uMrmpSqlUzkSRYOPfuM2rfUuz//V8+RmMmxf2zs4tda6VG7X+y9U6Ie0N00KxzJ4to/b9TDSOo3lNre/sczksyMUjmWQNZlgx+onUrbMUb3T5ObXl0iPJ5FliYmnh8hOp2lvmn1tCLvlUr5eQ3qsRPlWg8KxLKnhOO/98+s4LZdn/9I5slMpKjcbuzsroLHcjjxYvf4Gbkh7yyQzlsRb9XF7H2dtocXtbyzjOwHJoUiTRvygZV7/lEDa8f9HgawrjL00hawp+JaHGtfw2g6+7RMfSmJutJFUmVg+Tv1WhdRkllgxwdY7qwRugJbUyZ8uYZa75E4WUWMakixhbrbRczHUuEbt6jaF88NIssT2e2vYtSgUHC8lGXt5GqvcRdYUZFXGqnRR4xqKodJarJOZzeObHu2VBqUnRvE6LrWr25GmT9YgM5PDKncpXhiJ3hchaC7UGHpijPZKE7fpULwwglXusvX+GlKgMTv1eSbGnkNRjH2NHSEEYejhuC0cp4Vl1bDdFmHgIssaup4ikSgRjxUw9AzyPll9mpZkavIVTLtGrX6HQdaoJEmEXnBEDobEUPEck+MvHGDshLhuB9Oq0jW3cdwWIgxR1RiJeJFEYoh4LN/j+zzYJ5li/iTu1Oe4s/B1fH//8H0ip7E138X3QhRN+tQIn5KsYOgZVMXA9TokYkVa3XUyyfHIAH3g8blel0xyDAkJx+tgOXVa3TWCwMb1uiiyQSY5ge/bKLJKvbkASAzlzxCGHoq8+7nEjRyKrKEoBoaWotq8iyJrqIqO88Dc7HldFEVDVQxsp4ntNLAAy2mgqQkct00yMYzrdUgnRlndfpcgdClmTxKEHnEjT7N73+Pndnxa690oHLZh4lpen08z/kQpCst0P/4C/AcBEQZ4VgclnkSLZ0hNnkBP52gtXvvE27on/Dj94kgkM1C3UVSZ4oksMy+PsvDaerQgN+IYIxmK+ahUzNar1/D2KSD6SeKRdXg8s42eLWJtrezJrlFUicJ4jOGZOBt3TPIjgz08hZEzmK1NfM/qE55jyQKlsccIAxfbrKFNFTFmRiAIMG+s4m0+uvaCEALfCUiPJlANBb1nKLimz/Lbm1z9nXkUQ45qpgzHI0VINyT0o/9EELnsFN1CT2qHfuHDIGT5rU02LlU4+1NzxHMxyjfrfXdmGIT3Fq8PnCjwHR89raEaCkbqfurn0usb3PiDRbS4QqIUJ1m619+A0A8JvAAhovhz4ARocfXQIajAD1n43jqxjMbZrx5Di2t0tk3crkfgRc9CYqCQ6/9m8Kj0IyNrENgBsXwCIxdn8+0VRp+bQAhYfvUux37qNJ31NtsfrIMUeVgkSSJeSvQNUq/jMv3F43TWWlG48vIWI89N0JyvIckSmdlcZEh1HNS4xj2tAj1jYNcs0tM5nLpF9coWc189w/b767SXGkx8bpb6zQpb762SmsjgtV3iQ5FHRAhBYPtoKZ3MXL5vpDkNi8xsvm9U5U6X8C0XJaYgKxIKOpn0xL5GAkRiofXmPNXaTZqtZbpmeU8YBCIPSzo1xsjQ44wOP442IKQkSRKJeJHpiZfpdDb2CFN6HQc9H4lK+qaLUzkcHy6RKDE9+TK6nh58D6FHpXqDjc0PaLSWCIIHV8JRv4aKZxkfe454rLDH+JNlldHhJ2m2ltnY+mDfvmzc6uC7Icm8hqrLBN6nl6EVCh8/ELi+iaoY+IG7R1zxHoLw/r4g8KKsNN9C15Lk0jMEgdu7ho3ttXG96Nm7Xpt8Zo56e3GXV04AXmATihBJk6NMt9Ab+O2FIuiX1glFgB9EmmICQSEzC0hoahxJUvBDpx/q6toVEkb0W9jOfZmQ9pbJO//0Ok//4mm+9F+/EI15koRrelz/g0Wu//7ix0uL/wFCS6RJjc1hlddo3r2MGkuSGJ35VNqymw7v/4sbPPvLZ/ni33w2IrFLUdhs4fsbXPpXdwjcEHO5xvKvvvWp9OEgHMngSR87j5pIRQOx5zL03BdIjM3i1LcROyqcO40Ki5cWyJR0Kqs2o8cTA1M/s4U5xmZfIvBsKhuXKa99xPDEkwSBj6onGBp/gq3yRYTrE5g2QetjWoACNi5VyM+keeaXzyLJEt2ySfVui5M/OsXL//njuF2f+T9exao5UfXZmo1n+rQ3uqy9v83c58c59aUpNq9Uaa52OP7Dk0y/MIpiKAReyN1vrTLzmTHGHi9FRDRJYvXdLU78yBS5qTS+7bN9vRZVja1Ek4Rn+j3C3O4HJASsvLvN2Z+c5Zn/6CxhENKtWqxfLHPyx6Z55b94Arvhsvj9yGr27BC7FeCZAZ1tl+2rK5z+iePIqsT6xS1aG11O/tg0408N9RPqFr+/zuxnJxh9bJjCXBZF11m/uM2pL02RncrjtEyqdxoomtwnprldD0WT/9SFs3ZCUQ3CMECWlQFFTSP0S4bsCJ3sgSRF1wp8JFmONIoaJjf/P9/uVWAHkJAVNYqN7zMZ3IOa1ElOpAndAFVXGHlmArtm4Zke4y9P07gTGS3Dz0xgVU1SExlEGEZ6FVNZAiegcmkTWZWxaxb5oSTDz0zQ3WiDJBEvJqndKKPn4oR+GPFuoi4SKyaIDyfwbQ8jF2PoyTEqH22ixlSyJwpsv7dGejrHyLMTIEskRlNR6nYhTmoii7Xdxa6apKeyNO5UKV0YxcjGaC01SIymSAyn6Kw2yR4r0FqsE3ohvt9ifulbnNaSJBPD9zPzEAS+Q7O1zOrGO7RaK70JcP9JJAw9mq1lOt0tmu0Vjs18gXisONBrlMvOUsifYHP74q7tWjqG8EMCx0c7oHDrTiiyztjIU6SSY3vaEkLg+zbLa99nffM9XHc/bpTAtCosr71Bo7nI8bkvkcvODjR6JsdfoN6Yx3Yag68k4OxnSyQLekRYftSFhyyhxjRCL0BSZYTf83oJEf0MIsTzLWRJwQ9cJEmmVDpGQi+SS89gu01SiSFimRRiKyCTGicRK5JNT9FoLxOEHqXcKVrdNSRJjgwG38T3bYIdxHLTqpKKD+8xTv3ARogQEUY1+FLxYZKxUqTRRkg2PU0yXiKTmsQPHBLxYnRew8XxOgzlTuMHDoEIMLQkrtclCNy+oQXQMbfIp2eotxfZ+e6JQLD0xiblWw3iWR1ZkQmDEKOYonqrht3yQIroAKEfIslRqEZN6GgpHXOzvSuNPT2bx9ru4PeE9/rnKVGxXS1toBgq1nbnY6e/PwjfNmnOX8a3Osh6jMCzaa/cfOh5upIAwA0OP++KEDYuVnj1b79LPG+g9MLmXtejW7X7ApXJ40PImkL7xiaFF47Rmd/G3YdXmJAzDKvT6FKcDW+edlhFl+Joko4ZtqLw8SEhiUHFju7tfOBjHPvCn8Uo7KxfNVj/obN0i8q73yJT0hg9lmBryaK5tZfcNXf+J2lVF+k015g4/lkWrv0hxy98lfWF1wnDgInjn+Xu1d9F0lTUbJKgYxF2bSRJYXryM4cuLbH3xnb0XOzY1tt4T4eFnX+y+7gd4fm+p6M/bx6wbdfcKu3z90P2V9F11GSW0PcJXRs1lUXPFnCbNfRcEXt7HTWeAARep4Os6XjtOogAJZFG0Yz+uYmJOXy7i6xohEGA16oSH57A2lxF7qlH+2brcP39hJDNTHPh7F84cmkJVU+QHz9HqzxPPD1MqzKPHssQ+C6KovWLvcbTQ9jdGr5romgxROAjECiKjt2tIsIAI1kgM3SMdmURI5GnU19BM1IEvoOiGgS+g2ak0WJJPLuLazXRYikCz4kK6iLhdGu7HpYkSwghGH56nNZSA7tqRrtl+um4ktzz7vSO7b+LQGYmR3I8Q/1GmezxItVr21HqvRyxW0Qo+jpCuzhhvW1qQqNwdpjq1S1807s/Ye7QHxJC9P+8t13WFEqPR2Eur+uiZwwat6rRhKlI0TchRCQfce+8XsOlwilOnfgpYkYOAMuusbr+FptbH+IdEL7ZHxJDxbOcPvlVjAFeFyEE1dotLl37tV1GqFFMMPzCNIqhUruySev2oCzJ3cikJnns3M8Ti+X27AsCl+XV77O08tq+ROlBSKfGOXfqz5JKje7pdxj6LK78MUsrrw00oJ/68REamw5bd7qEocDp+ruc7OOjzx6qtIRiqKRm86iJSKE39EIQAq/jIHp6VKETRAa3pqAYKvHRNO35Gr7pEjg+eibGyCtzVC+uoaUNuqtNjEIC33JR4zp+192lEfUgdC1JITOH7ztUmrcP8eQGDMj7DkoHD1KypJJNTZCMD7Ne/mBfz9VOjH1mFhGEmBtREkB8KEl3o01mNh+Rhy2feDGBud2hemmz//1NfH6OwPHprreRFIlYMUF3o032eCEywP0QIxPD2u5QvbK1h8v5cRAfnkKNp2gvXSd/6hnM8ipOfTcVRZNje+b7fHyKIPSpmEeTsJBllVRqrOfVlfA8k3Z7tb9fL6YY/dJ51EwMc7lGcqbI2u9exB4gxxGTkpyLv4SKhibFuO18wLa/RFGZYFo/yzX7dRyxe/w4wKQ5moen/NY3kJSHnxKVVoBWxaNVae57nO92CUMfSZLR9CSZwiyqFkeWI5lpWVPRR/Lo40XUfArz6hJu9xPI1xcDPoN7hs6Of+/684Djdv47O5WiW7HxLf/g8x689kHv9z79lY0kSiwJro0ST2IURwg9l1hpDAHohWECq4skqySnjiPJCu15k8A20dIFQtdGy2YJHQs9P0xYXscojuDUttGzpajwaypLfHQKr9Wgs9ja1f6fVogwIHBtPLtNIjtKLFlE0eKkEjlcq4Eey+I5HWRFR9UTyLKCFssAIio/Evo4VqNfC8xzuviuRSxVIp6JCtilk7PY3Srp1ByuWUdWNLRYCkkCVU+ipA0kWcV3TVyzvusjvDeY1W6UI87WvV07Fdt7x+wa+Hp/tes2ds3C7bgE17b7q0bCHWsdMeDD723zTY/azvP2vM+9tsXutkUQ0l5q4DZthAC70u0Tf3etSvcM1oJq/TZLK99lbuYLdDpbLK18l0Zr+aEesf0RGTRb2x8xNfHKQDJwIlEimRim070vFSDJEqEbYG20SY5H8gytOwcZPRLDQ+cHhrIEgnpjgdWNd45k7AB0upssrX6Pk8d+HE1L9vsvSRKKojFUPMd2+QqmtbdvjhUw91SO7IiBa4XcerOK7zxaqQNFV5AVGd/10DPGfaJ5QsfcbJGazSEhoWViNG9tY+TiyCdLVC5GfJfQD/C6Dk7TIjWbJ3Ajz5kaV8meHsbcaOG8v7/BE4Y+7e5mP8T0cBxlED14kBKEOF4H067tMXZkGTRd6hfmvF8qJRqM46MptKSO23JITWTIHCtgbrTR0wa+FWk8qQkNr5cJFS2iI6+pljLwOm503lyBzkoTI67htp2IVB/XdmmHfRzomQK5E0+ipXIkx44hKyqdjYXd9yqpnCx+do+nJK5mWG9fPXKbQoQEgUsqNUa3u0UiMbTL4AkdD3uzidq2sdYadO5s45QH83xL6iSB8Lluv8WZ2Av97Y4wUSU1KhgsDr9gOpLB45u7OyWpGlo6hxJLQBjidZv43faAmX0w6uU7jM08j6zq2N0axZGz+J5JaewxBAK7VcErN/BrbSRD/USytD5t5KbSZMaSWA2HxnK778L7NBD6Hl67Qeh76PkhQscm9D2C0EJSFEK3V+9KknBbdQiDvjEa2F38bjsiVSYzuK1aVE6jUUH0jpNULSJi1it47candh+fNILAw+qU+5XsI7d4gGPWEWGIYzUAged2o3dVknHMeiRspycJd3gnfNfC6VSj0hMiJPRd5L4HKMTuRNopoWv2NGUk7G4VI5HDSBQO/Bb8RyQ9us37Rr/3CAOjCMWjnRcIrPL9cMAhxY2jc0XI5vYlHLdD19zGsnZ7vR4FofDZKl9iZPiJgV4eXUuSTo3uMnj0TAwtbZCaztFerJMYS9O6W9m3K7FYjnzu+ECtncB3WNt8B9c9unCpECHl6nVKhTMMD13gwbhUKjlKLjszUJtn63aXwnic4lSC9ZvtR/YG6GkDNaljV7ooMQ1ruxuFj2QJ3/RwqiZ6OnpeTsNESxmYm21800XWI8HNwPbprjZ6BnHkFbS2OoRBiJpsYG4d/Gz8wOnxbX7wECLEtAfriqWzMo8/G8N1BJ12yI3LDoEPVrlLfCiJvW1il7skxzO0lyMJEKtqoiU01KQOIoi8pz1YlS6xQhyrbGLXLZJjGdqLdSRVxtruoqV01IRG4PgE1ic3z7ntBvVbH6AYcezqOiIMCb0Hn7eg7ZbZaN/YtbUQnzyU1+tBCBFiWTXi8WJPl2n3WON3HKpv3gVJemg5iZicoBu2sESHkJ38rujvgzI2D8IjCw/quRLFJz5DbGQCWY9BGOJbXdp3LlO//j7iIYXAADqNFZadDqoWw+pG+gCyopEfPoWmJ6iXbyEZOpIsoebT+PUOwYP0/IH4k3M/1JdaFI9nSRRjtNa77CnL/AkiMDv9q1vW0cQI3Xq0cnTdMm693N+eycnMHddoNUKW7kbP+k9mODocJFmJiI5CRH8PAxAhVity2TY2bzzkCjuuJclRTTJJ6pMnw8DFake1lpr24Sc2z27ju1ZUIf4TfB+NE1MIx8VdebiqsJyMgxCE5ierYirFDWKnZ7BvLCHsh78dSjFLUG0SBA6V6uGVqA8Dy67Taq0wVDrLg0aDohjEYwV2hjbsqom51sTaaKMkNPzOweNULjNNPL6XYCyEoN5coNVaHXieohioioEkyftycYLAZWP7IoXCSTQ1vmufLCuUimfZKl8mCHb3MTtiYLU8Ghs2mZKOqsm7NFoOxI5X0albbL+1fODhjRsH1xkToaA9HyWSlN/Zfa1q/ZMViv1BIghAVqAwpGCZYZ+i0LhZoXHzvteteTe69/ZS48Dr1a/tfo7N25Gh1V4++LyPDRFiVzd64e0ARY9H4+QOzm0oAjbbN/DD3eNEw15/9GZFQBC4xON52q2919GyCWRDRS8kSUwX2P7WdfzO3rHECS0yShEZlZ6wAzIKSTkX8QDF0bTgHsngkfUYpac/j54fpnnzIm6jiqQoxEenyZ17jsCxaN66eKhrBX7khdCNaIUmREh14yogkFMG8VOTEISohTTm9WWC5sMn9oNieJ82JFlCT2lRBXn18Aqsf1pQHFKQJLDMP8WM5B3ITpzBrG/gdmrk556ksXxlwArmcBAixGrfM/4+pvch8DBbmw8Qrx4dcjqBms9gnJjC2ygjleuopRwg4Vfq0TcylEfSVPx6C+F6JJ45C0Jg31jEL9dRhwsRz0dR8DYqKOkESi5N6LgEtRZyKkHQ6iBpKrKhEzQ7uz1UioI2UkDJpjBmx3EX1iERQ8kkCdpdgmoTJZ9GyaQQno9frqPk0qR/+Dm6b13C26pG104mkHSVsNkhtJyo36qCX40UppFkwo4Z9c20Ec7+Ronv23TMLUri7J6sQUmS0LQUsqz21ZdlTcHc6tBdaSDrSi+1fvC1FVknm5lBVfZmmIWhR61+dxcBdicMLUUyMYzl1A9cMbQ763Q6G+Rzx/bsSyVHiccKe8QIkzmN5rZDZdniwheGkNXDr3IfpeDq/1bhOYJK2+f2NXegmOa/D1CMBCIMUOMpAFITx+msz+M2d4dKvXDvokhCfmRxUFlWiccLeG6XeKJIu7Nb5NMYSqEXU+jFJJIso2biAw2eir9GUR3ntPEscTlNXh0loxQoKONs+gu44miLuUc0eAyM0hjlt75JZ/k+27s9fw3pFZnE+NyhDJ54aoiJY5/FiOdACGRFp9NcZfnWqwS+Q9Cx6V68C0GIpKuH1OERB/ICJGRisXxU1TiWQ1XjKLKKECF+4OK67Z6OxtaeldVhUJjLsHW1Rn42g5HSsBsf3z+iqQkSO6owq4qB3PNsBIGH63WwnSZdc/uR3Os7YVshT71goGmwvfHo3ilJkonHir3q0VlULUoJFSLA9x0cp4lpVeia5X1/r4MMVwmJeH6M3MzjpEaOEbgmip6guXz0mPMDrX7M83de6hO6lqqQfOExRBCgDhfwqw3i546hFLJImoq3USGot0h95kmchXVC10NIEtpoEZDwtmr41SbpH3oWb6NM0DYJmh2SLzxGaDsouTTWlTvEjk9hXrqNNlxA0hTMi7d23YM2WiT18hN4lTpyJomcTpB44hR+rUX8iZO0vvEWqc8+TWg5+FtV/HoLJZdCmxhCHSni11oYxyYwTk7hrZVxgxB1uEDs3DGCdhd9bgJvbRt9aoTO6x+RfPExuq9/RHCAwRNp33QRIkCS9g5nqqojy0rf4FGTGsUnxnuhiDrmWmvPOf371RJkMlMDB33X69BsLTHofZFljVgsH5XKGdCnnfA9i1pjfqDBo6kJctnZPQbP+s0Ox5/NMzybpLJk4lqH/04PNniiUh3JxDCxWA5NS0RhWhGlnLtuB8uu0eluHagT9IOCoWeIxfLEYjl0LdkbF6OwshABQa9Kvet1cJwmllXD8w+XcaRpoGoS1UqAbe39jVOpiN8zMiKzsRliDTjm4Osne2NjDk1LoqoGsqRGifShj+fb0VxkVzHNyqGL4z4IIzeEpChkZs7hmS3ipQnM7b1eSV1J7AkPFeKT+KGL7R99TgnDAMduEI8XB/LQAtsjfWaU5kerPaNnsGFliTbzzkUm9FMEIqCgjGCHXda822x684RHjKA8WkgrDAmsTuT+f3CX7w2sAzUIxdFzmJ1tAt+m3VhFllViydL9A4RANnQyL59DG8nR/M5HuOsP1+EJH2hfkmRiRo5C/jil4lkS8RKqGkORtT0VmYMw0o9w3S71xl3Klat0zO0BuhqDUb7ZYORcgTAMsR7R2JEkhZiRJZuZplg4TSo5EhlmioYsq8iSwj03fVRFOtKn8H2LrhlVYm40F7Gd5pFJoZomcfem90jaHpKkEI/lKeRPUiqeIREroPSecyQUF/U50szw8AMHx2lRqd2gUr2BZdUId7gow9Df12gQCNxunc7mHdxuA89q47s2wQ7vjq6nOX3ip3phjd0IQ5+bd36XducIta8eAfFYntMnfhpdT+3Z53pd7i58nXbnYNexHDeQkzE63/sQQoGkyOjTY0jJGKFpIxsabqONM7+Gkksj6xruRgV3aYPQ9XBuLYEsETou1tV5gloTdSgPqoz53jXij59EyaRwljbQp0eRVAVnYQ0eEJVUCxm8zQrW5TuohSxqIYtxbBIhrSEpMnLMwL52F+P4FEomCUGIu7COv1XDfPe+IeqtV+i+exWEIPn8BdylDdzlDVKvPIXTtRBegHF6Fr/WJGg9vARG0NOGkQcMZxI9heYe7O0OncU6gesT2Ae7w3U9RTI+tGe7EALHadHtDg73iDCqjC5E+NAVcih8Op0NPN/aE9ZSFI10ary/UOhv1yRuv1PD6QYUJo9WLT3cEwKQMIwMucwMw0MXorFGie1Trd7vp3U3W0tsV67R7qwf2vjRpBiCMPr+jzhR3ROfTMaHyGVnyKSnMIxIFPGeYSnLMlGqI70+R4vf++Ojg2VVqDXu0mguYtm1fRe1ritYuuuRLQz20j/1hIZhSJw9o/GHX7O4O3/w/ewc00uFM6RSO56zrOwY0wFCwjAkDD38wCUInEfyzFl2jfmVb+Ph0rj7EW6zgjtWJXB3/16ypHK69Hn8B4yquJZhvfXoC0hJVlAUHUXZq8PXXayy8fuX8FoWkiThH8DlaYU1uvZ7qJKOhERIgCecR6IKPJLBEzgW3bUFMief6BGP2kiyilEcIT4ySePmB+j53kAhwGvX9tTbAlDUGJ3qPAiB71m06yvMnv0ysqL1tVMkWcZe2gJZPpSHRyB2WcOKYjAydIHJ8RdJJUcZJO8e4X5FZk2NY+gZ0qkxxkefZnP7Euub79LpPpw3Ec8ZrL63FRVQMxTcztEsc8PIMjr8BKPDT5JM3C9Y+fAq0rFeFekhhopn6ZplNrc+ZKt8eV8OwSBUygHprDxwVXMQ7pUPmBh7jkRvktivz4oko8gampYgZuTIZqaZGHue9Y332Nj6AMeNVt0P+9AD16a2+FGUTj7gONdt4/s2qeToQA7GUOnCp27w5HPHyWVnBqrr1psLDy0jABBaDqHlkHjyFOpYCefWEs7CGkoxS9ixcBY3+uR0hECfHYuMHcvBODEVHXN3JTJg/GjCC1pd8AMSz55DLWTovncNb6NC9sdfwa808cv1Pf3w621iZ4+BJCEZGn6tiTO/RlBr4pk2QbONNjlM2LHQpkeRPrpNaFoIIPniY1iXe6ViPD+an0OBX64TO38ctZAh6Jj41SZyKk7imXO0vnk4YTJZlnuGzV4Eobfr3VCTBuljRazNFqEX4FT3X/GnkqP7FjdtdzYGGA8RBALbaVDMn3pobSyIeEi23UBLxR/YI5GIlzCMDLYd/R7pks4TXx6hsW7TKrvMPJmltmoeulp6uIO7IcsapcJpJsdfJJed4TBjo6rG0PU0qeQoo8NPUq5eZ23jHZqtg7lAqqQzGjuOE3RxhU3De/hzgWhcyWWmKeRPkM8dJxEv7SKQ729QSr0QZzTpaoDQBcnEEKXiWRy3TblylfXN93rj+m75hmxOoTikEE9K9+VEdqBSDTl+TOW733Podg8eK3Utxcjw430tp4f3XUFRFBQlGiMfFbKkIIXgdmvQ7nGNVm4OUMcXVMxFNtq7+XWF+PTHCmkpisHG5od7SMsASlwjczYqoGouVxGbLfweD03DIC4PFvi8h5iUAgSdsHEk4/mRQ1rJiWPEhiZIjs9GmT+SjBqP4nHFx1+5H44QgrVX/yVec+/AbnXKaHqSbnuT0thjpLITPTG4+z9IYDmI1Sp+vUvYOcRKQtBXaY0ZeWamPsvI0GOoavxIP969YzUtycTY82TSkyytvEa1fnOgCiyAntKYeGaI0ceL+E5At3L4yVSWNYr5E0xNvEwmPRXVrDniy7azinQqOcLczBcoFE6ysvo6tcb8Q92iqgaTMxrZvEIqLbh783DGWjIxwuz05ykVzvRWhkd/zvFYntnpz5PNTLGw/Me026v4gf3QLIFEcQLP6pAemQNJonr3/V2EvO3yFUaGHkdRtD3nFvMnWV17Y18exseFLKkU86cGTppCCCrV64cLm/oB3bcuo+bS2HdWCOothOejlvJImkLYtRBBgLdexlvdirgwgH17maDRJrQcCAXdNy8R9GQdhOPSffsKSi6NfWuJoNpETkSifO7KFgxYXHibFTqvX4wWITcW8WtNOuZHKJkkwvV7BkyDsG1i31km7JoQCtqvvo0cNxCejzO/CpLc9x45PcNsJ4dHjhl4mxXC9uHCD4pi9Fb3e59xZDTv8I7EFEAQKyXxH5L1uVMo8YEr0zUPJvOqioFplTmM58V1W7huGyF2G+aSFHlfDD3dN3h8N8Rq+veSC7n+vQpO9/AD/j3BP11PMTn+EuOjz6BrqUf6ZlU1xujwE6RT46ysvs5WZS/B+h5kSUFCjvRexMPb0tQEQ6VzPa9TVKPrKFXpD+o3QMzIMDH2PPnsHEurr7FduXp/fBTQqAUMjyl022KXsSNJcOqkyksvGCgKjI0ofP3V/XgkEpn0BLNTnyefO37ksfGTgKwZKMZ9Qzo5NodV2cDr3F/QhCJgu3N3z7kt5+EL/P0QURdsstlpfN+mXr+za39isoAc01BTBrKuEpgefjt6jhmlyHHjif6xqtQrlCt8QES0ZUnFEzaXrdewxeHH70cyeELPpXblbeRDaPIgBIE1eOCqbV0HJILAwYjnSKZH2V75gMC//wIZEyW0kTwIgbO8TWg/bIIQBKGLoWc4PvcjDJce66t8PipkWSGTnuTk8a+gLOlsbX802KPQ9Vh6cxOr7iDJHNq7oyoxxkefYWryFQw984l9FIqik88eIxEvsbTyGhtb7x84wfoebK75NGoBsdjh+pBKjnHy2JfJ54597AFJUXSKhVPoeoo781+j2V7Z17i8ByNdRDWSSLKKokXu7WCHwdPubtBqr+zhSEiSRDxWIJ8/wdb2Rx+r3/shlRrtCcvtfZaO06TeWDi0qzpsdXFb0Yct6ZHxEFTbhE5Ugw5ZxluvIDwPJZVCMgyE5eAu319J+5VG9BdJQtJ1glY3IiYDkqETOzuHX67hrZcfbL53gQBvbfdEH9RahG0rEkk0jMgz1PPmSoaBcF2CZhdheQg3+m/PNdfL0T35XsT3Keawrs/vPXYAJElB11IwwMMjRIjjtHa9Q17LIXQDtLSBXbk/LkmahnigCHIisTecBZEHxzQPFiz0A5d0aqJn9BwMz7d7ZQ12qEv2oGup3v1FsFo+l1/dpjidoLFp45r+kZI0wtBF05LMTv0Q46PPIMvaxxpvJEkmmRjm+LEvo6gGaxvvDPxm/dCl7VdQJI1u0HjYVclmZzgx96UjL1SPAllWSCZHODH3JSRJYXP7Yt84NmISsYTMxqq/W+lHwN15n+kplWotZGRIRh8o2C2RzUxz8tiPk0mPf+yx8VGRO/4Eut/oLzDiQ5O47ToP6rUGIpoXElqObGwcWZIJRUjdWsUPj0bNiLyBGpZVjeqgGXu9NaEfIGsKseEMIggJvR1jdljjthOVVtGlOFP6KerBNs2gQih8dClOSZ3ACjt44mh9e+RaWt3lW4PG8Wh/KOAQPB7fs6KJStGpbV6nun6ZIPDYuSoKbZfQcgi6FsEhVnwCgSxrzEx9jqHS+V1FBu8LqgWRNsuuasZydKwkHVCNOcexmS8SBC6V6vW9k5WAZDGG2/HITCRpb3TpbB3slVLVGFPjLzM1+fKeGP6uSwvR63Owq93ImJN78fbB/Tb0DMdmvoCqGKyuv4Uf7M9sT6Yljp/SqVcf/vsl4iVOzP0YuYcYO0IIQuH3PHfiXseiVZ+ksLMCtiTJpFPjHJ/7MW7f/cOoqOwB8MwmqeFj1JcukxqZ2+N79rwu5eoNMumpPV4eVY1Ryp+iWrv1iZMwJUkmn50jZmT3TWmOtGgeOE/XUVJpgnYbORYDWSa0zOjvAoJuBy2fx61WMKan8atV/E4bWdWQYzG8WhU1XyC0LbxyGSWdifSXHIfY7BzO6iqEIUo2i1cpIxsGkmEQmibO9ZVoCbvT5S3LqNksgRlpO8m6TmCZyJoOikLYaaNmcwRmF61YRIQCv9FAuA5qLo9XLiPH4uhDQ1imiWwY0TU6HYzJKYJ2G69WRcvn8aoV/I0aZtshNE3kZApZ0/A77X4o7kGoqkE8Pri8hB/YmA+EDLWeDk/gBqgJjdjYNLJuoMYTtO9cQ/TScRRZJ2ZkBrYZ9hIFDoKiaEcIJYueYRagKLu/I0XRiMVykaZU77sfmk0wfCxJbsQg8ENuvl7D7hw2PVdiavxFxkaf3hVm3X9s5P74Isv7jo26lmB26vP4gcPm1kUe5A6qkk5KLdD2q8TkJFawP1kcBN3uFl1zm2xm5sC7uT8uhpE2S//7j8Jz93hI+xlNkiSh62nmpn8I26lTbywAAs+DbjvEd/dm8fk+3L7j8cxTOpoGnc5egzOZGOLksa+QSU8MaDviF/m+jWlV6XQ3cd0OQegiSwqqGieZGCaVHEHTEvuO7fdK4oRhFNIPRYDnmThOE9tp0uluYKehU14i7MnEhIFPeEDK2Xj6PIaawg8dNDmG5TWx/R2/1b3Q+e6OPDDuSqiqQTI5gu9be2veyRL2egM9l0CSJdq3t3B3qHG7wsbtzVFT2mk6QZN556NdnB0zbHPceAJNihGIh/P87uHRQlpGnOJTn0HWBhcFtbdXad68+NDraEaakalnSGUnkCQZ12lTXrtIq77Uf4BetYWkq8j64boqSwrDxXMUC6dQ5PsTXCgCHLtJ1yzT6W5i2RFjX4QBsqxjGBnSqVFSyXES8eLAEMh9o+cLWFZtl6DZPXh2wMj5AnpSo71+sKtNllXGR59jauKlfY0dIQSu26Zrlel2tzDNCo7XQYQ+kqSiaQkS8SKp5Egvkyu7x/iQJAlVjTMz9VmC0GV1/e19ycxmR7C55j+Uw6OqcaYmXyGfOz5Qwj7qe4htN+h0N2l11rCsHklQigr5xWI5UslRkolh4rFC3ziVJJlMepJjsz8ykOy7E+3NBczqOr5r4VmtPXWzhAip1e8wPvrMnhCFJEnkcnMk4kVa7cF6Ko8KTU1QyJ+IDLoH4Ps2tfqdgYanmsuTOH0Ge2EerVgCRcav1VHSKSRFoXvtKmqxhN9qosTjyBOTyI06YbeLWiji1esRX06SkI0Y+sgoai5H59JFtEIxMnhUFa1YIui0iU3NIGkaQbeDmsmAotC9egXhRM9RSaWIzcwRmF1kI4Yky/jNBmouB7KCdfcOajYXLRQ0HTWVQs3lsRfuohVL+PXafY+PoqAVisRm52h/+H7PMIueQXRPLfSxcWRdI3Rd1EwWZBl7aQG/OlggTlOTpJIje7YLIfA8k+4DvLtIVM/Frpn4povfspF1A+H77CwOp+tJZHnvGAD0JqeDvU++b2No6Yd6KO/BcVu9b3Jvm5HXV+kbIbGUimsG5EZjOKa/Z/45CPnccYr5E6g7iKRChDhum665TacTjY2u10WEPrKs9jk76dQ4ycTQvl6hyHP0OWz7vuHQb4OQjl9DlbR+iOIgWHadSvUG6dT4Hv7bPWPBcVs4bgvLqkV9dju9EGZUHkbT7hkOoyQSQ2hqYt9FYSyWZ3L8RTrdrajyuhwlcOw3CsZiEpmMPHD+l2WVqYmXBho7UZjVpda4zcbmB7Q66z2Ce1TTT5IipRlZ0YgZOUaGHmN46DFisexAY9O0qqxtvItplrGdBr4f0QBEGJG1hSwhdiQXNaxO36gfBEXWqFur2H4LTYmjybvneLVUQh8fRdK0aGEkSThLK/iV+x5PIYKeAb+I51kYxm4+YObMGEYphRzT8Fo2RimNYpT7HJ6d0OUEgnAPQVkQossxFEk5UmLtIxk8kiShxlLIxn19ClnViBXHIsLe1uEmj9L4Y+ixbK92lk86P83ozPOY7a2ogjqgpOMkzk6hTwzRePUD3NWDXcmKojMy/Hj/30IIPN9kc+si25UrEdlw38EqIgmODF1gfOy5geElSZJIJkaYmniZm7f/7R6OSWO5TXYqmqS9A1WWJYr5U0xPvIyq7TV2hIhCc5XKdTa3P6LZXjnQCyHLGpn0BMOlC4wMP9GrDLx7clfVGNOTn8Wya1SqewX5VC3S4ckXFYQQrC7tP1gPFc8xMvTYLg/ag30vV66xvvkerdbqvgRPSZJJJUcZLl1gbOQpdD3dW5nJFPIn9m0/OjnKiPGd6DnHc6N0yku7PnCArrlNs7XUIzzu7m/MyFLIHafdWf9ENUri8eLAlGYhIkJr7YGYdnQ/EvrICGouj6RqhLYdKV7rGn6rhawbyEYMNZ1GzRci3k61gqTpyPE4WqmEu7GOmo2MXo/oepKiIlwX4ftIuoakqKj5AkqljKQoSJqGpCgEnW5kuCgqoiceoxWKkefGjzLm3O0t5Hgc4XoEZhNJ05ATCTRNQ/geXqWCkkwix+Ko2SxqJoukqmjDI/j1GvrYeGTIhCGhY0dtq1rvnvJRMUVdR/IDRBDgVytIA96xe0inRgdm4QGYVgXL2m0oeW0HPRd9G/Z2F8trk5g6DpLUG7d6xMmefs8gRMbA/t+2ohgk4kNIcrRaPwxcr7svX80wMsiSQoiHJMHajTYnXyygxWRWrpq4R1BzH31gbAwCl+3KFba2P6LZXj0gGzVKWR8unWdi/PmBRVujSvUlpiZeodvd2sWNC4RPKAIUScMOD8O5EGxXrjI68hSp5HDPiRDQ6W5Rb8zT6qzS7W5j2bWHGpWalqCQO8746LO90PZecrYkSeSzc+Qy05Sr1wlCyBUVSiMKm6v+gwmLjI0qXLnqsbzqU6/v3pnLzlEqnh3o9Q5Dn5W111lee2PgeH7PURKELp7XpdPdpNle4fjsj/bGr91juqLodM3t3ngyYOYPQI2nyB57DC2dR/gu1Wtv76macA8dp4obmAwnT6LIGhvtaw/cQICkKujTUzjzC6j5HNpwaZfBAxF/MR4r4PvrxGO5Hget50X0A/RCEjUTo7tQIX1qlNa19YE6PJ2gzqxxnvHwBK2gQkiAISUZ044RCB9fHC0p6NGytGyLrTf+kJ0xLUmWURNpSs994dBp6ZqepFG+Rau2CIBrN0mmR3dNSqHp0P1oAb/RJTxiHS0hBJZd5e7iq1RrNw9BEBWYVpml1ddotVc5PvelgRk+AMXCSQqFU3uUY0cfKyIrErGMjp5UcVqD20zEi8xOfS6a4Nk7KTpuk8Xl77JdvnIo7Ygw9Gg0F2l31mk0F5mb+QLJxNCej87Q08xOfR7LqtM1d69+Ax/q1YBuJ0TX9182xmNFxkefGSjIBlEYaXntDdY33nloYUghQtqddbpmmWZriWOzP7rvM98JSZJJlqYxAod4fhQRBsSLk5i19V5YdFcrbJevMFQ6jy4n91yrVDzL+ub7Dw1THAWlwmkUefBKtla/M7gtIbDu3MZeWiK0rPtFOCPLDiQZEfh0r16JirnWqpEhIkkgyfjNJoFlYi8sgCQhPJfg4gfROCME3evXIp6KCOle/ojQtgjaLSQtMq7uLVXFjni6s76OV630+S3C96NCQ5IU1e4SIaHZ7e0LIAzwZAXCgO6VS/3rBt0uoWXRvXYFU1YIbRt7PpKXF/79e/LKUZgtdJ0ojBMGA7JKIsiyylDp/D7u/pBa/faelaGa1PFaDm7TRompUTmVeiVavO1wy+tacl8NnXur6H0hQlyvTdCrMH4YeJ65r8Gta6konCTg2a+OU5iMo+oyIhTMPJ5l+XLz8ErL97ooBI7bYnH5j9kuXz5EAdfIUF9Zf4tWZ43jsz9KNjM98P5y2VmGShdY23iHe5OcKhtktWEC4SGL/Q3YnbCdBlvlyyjyU9SbS5FESHczMg6PoEvjeSZb5Ss026vMTf8QI8NPRDWYHoCiGpSKZ6hUb+LYITevOEzOaAOpG/VGyIvP6zz9lMbv/5HN2lr0/O9lBesPhnGI5FI2ty+ysv7moUPoQgRUqtdRZJ2Tx768x+Nt6BkmRp+l3V7bd57QM8Vo7PA9AtdF1mLAboNHkTQC4bHVvUUoAmy/jSwpdNzdCwa/Wot4grkc7mpUqoIBCQPxRIF84QTxRKmnDXf/22rf2kLSFOLjOTp3y8RGMnvdZD1U/FWScoYp/Uz0fUoSkgAXh3nn8p7CoQ/DI5aWEFGdpgcQ2CZOdZPE+DFady4PPFMzUsR7WjuBZ5MfPt3XS0hlJ3HtVt8wkZMxtOEsfrVN591bR+uhELhuh9vzX+t5M45C7POp1m+DJHH25J/BeCCWH8WsU4yNPEWztYy3YyXT2TLpbJlMPT9yYJNjo8+QHhjfjUTNbs9/jXLl6pG9DtGK7Squ1+XMia+SSAztWRVk0lOMjz3D3YVv7ho4jJjExLTad+WuLO5dOUmSQql4Zp/YdPTsVtffYWXtjSMNSmHoUandIgg9zpz8mUjO/6A6KULgdupo2UJUc81uo8ZSQIgWyyDLCrKi4VgNQt+l3dmg1VqhVDyz51KJeJFC/jibnxB5WVXj+3qngsChfEB5hdCywDr4Iw460WD14OsV9L7JcEeSQLCDiHvPMAEI2lFcXnge2PsvJITr9K+7b5/38Gt6qe/t+4Nq4PaKKO5wp4c72r13T1Gfe8ce2CrkMrPksrMD99l2neoAL5rf7VX5zsfprDR6Fe0F1sbyruw+VTF6+/bCD+wDv0tZVsmmJrGdZqS0fAj4/v7X1LR4z/iDi1/b5NznS7TKLuVFk/M/VNpXtO3A9gKbhaXvsLH1/pHGGCECGs1F7ix8jTMnf6Yn9bEbqmIwOvw41drNPo8pFD4Nb5O4kunXQXp4WyFrG+9Qrl7DNMsf0wMrsO06C0vfwdCzFAsn9xwhSwrJxEik76O3uPCUgePsztK6h1otZGk5YGZaIb4jwSMey5PLzA40BC27xtrGO3je4bIP+z0XIeXKVUrF04wMPbZr372wfDI5QqO5MPj8MMDrNJBVDTWR3vNey5LCSOoU6+2r5GLjVMwFOu7+kZTQsvErVZJPPk7oOJhX9mr1dLtlZPkOmpYY6Giw1uokZ0sMfe4Ubq2L1xj8TAJ85t3LbPoLJKQsiqTgCpt2UMfn6MLAj1xLS9Z0dpm+EkiKipbO9wlSg5BIDTEy/XzvFAlVTzAy9QxChKhaDLtbuz+RhiHGRInEmWn8eufQpSUiCLbKH1Gt3eJIQb4dqDfmWdt8l5nJz+3h9NxzgaaSo9Qb91P6XNNn/MkS9cU23j7CZqnkGEPFvbV/IFoFrG28Q7ly7WN84IJma4ml1e9xYu4r6Pru1YYkSQwVz1GuXKPRXNzRtqDZCAmDyPgZBF1LMlw6t2+qda1xl/Wt9x5RGVTQaC6ytv42czNfRFUHc8SiIwWe1cYyoyKUQoRUXYvAc4nnh4klCxFZOvBx/Bp+YFOuXu+lh+4lLxcLpyhXbxxaYPIg5LNzPaLpXs9do7m0S3lUVnQkWSbwPtl6VwdBkmQULY7vmXsFRv49gaYlGRt9euBKOirMeQ3H2UuMdWomm99fQNYU3IaFpOqoqSxKIoW5fKevF6aoxkD+FUTFaQ/6Nv3Apd3dJAjdh5Lu+9cM3X1/C0Ux+jpDnh1iNn3Gz6QpTMQxUuqRi4fek0TYrlx55DGm1V5jZe1NTh778T3fqSRJpJJj5LKzuxYRVtAhEP6hODz34HndXQvKjwvbabK2+R7ZzPTA8cXQ08RjefRkm3otRL4nb/XAca1WyPyCTzIhsdPejMcKxGL5PdcVIqTVXj2UltsgBKHHduVqlIjzgDGlKgaF/PF9DR6nvo3bquK2a2jJLF6n8cAREmljmKS9wXDyOF2v3uezuYFF8GDYSAiCVrunpxUOlLCQ5UiEtruPaK/XsNj8+hVkQyW0/Ydo7AnMsI35oFcKlYCAo8zvj2TwKEac0nNf2E1aliS0VBYtnWP7za/te26rtkS7sbbvfhB9BefQcum8dwtJUwktd6B44X5w3fbAbIGjIAx9NrcuUiqcJp3a69FQ1TjF/EkazcV+O8VjGSRZIj2epL7Ywm7sNv4kSWGodI54LD/QQ9LurLGx+eHH6jfcG/Svk8vOMT76NA8aV4aeYXT4CZqtlR1tSRiGhKpJKPt4nVOpUdKpsYH7PN9kY/MDHKf5sfq9Vb7MUOkCuez0Q49XY0lSw7NIskroO3jWVXzXQkophKFL0HMdCxHSaC7SNbfJpCd2XUOSohTSZGKYVnvlkfsOEZeqkD8xkIQeeQ5v7VrhZYaOoceylJffRxyS4PpxocUyjB57ifXb38N3Px0Nok8TkiQzVDxLqXBmz0paCIFpVXfrqjwAr71jAA4CArODli1EwjY9Dk+kwj7YwxOGBxs8QgR0zMMJ6+265j4Dd6Tfcr8vd9+tU1+3iKVUamvWkXR4AHzfYnPr4sfKTBQipFK7yXDpHIX8qT1jmaLoFPInqdRuoIQKOW042i5pSEg0/YN1jD49CNrtVdqddfK5uT17VTWOYaRI5xQkopqCg37qXFbmR344RqcTUq72KndLSo/UvXfwDEOfdnvtY4zrAtOq4Dgt4rHcrj2SpPRoAPLA91LSNGRFw65u9DTzHlyIBTTtDaZzT5GJjTGbe6aftbfevkbLeeBdVhXUUgFZ01FLRQCsVuuBa0bnG0YG1+0CezNShR8SHKLI+CAoqEzqp9jylj59HZ6BECF2eY3aR6/TXd0rYtQ/TIQgApKZUTKFYxixDJIk43sWneYazeoCsNPt7cFDBML2thF5Giz7cO7kg2DZNWr1O70XavfjkiSJfG4OVTX6k1h9sc3YEwZOy8Fu7/0xDT1NMXd8oIfED1w2ty/huI9uMOy6nm+zVb5MsXAKQ9+thSDLCtnMDMnEUF8NVpajCsEPZibvRCF3EmkfMmfXLFNr7P/bHxau16VcvUZ2nzpGO5EemUOEAXZzKwpJhCGKZmC2t3HMOv4OGXXLrlFvLpBKjjzw/KPsu3zuGJ0DFHQPg3gsTy47M3AituxabxUW1Y2TFRVFjeqiSZKM1PP2SJJC4EUhDkXVI2Mu8IjqRUW8FlnVCXx3l0DlvePCfbhqkqyiqDqqFkNWovNkJZrYd54rK9EAKUQ0ICk95XNFi/XbBNFPVRYi7JX0+MF4i9KpcaYmXhq4Qg9Dj63tS/uX6+i9TpIScWDu/TtwrF0eFklW9w2pRqVrDnOvETn2MF6UMAwYOLNCVMRxxyQaBoLK8qMZK0IImq1lOuaji8rdg+u2qVRvks3MDvTy5LIz6FoK127R8KL2FEnrlVH4k0OUkVYml50dYKhpyLLB7WsHT8SlksylKy75vEwmLVGvR4a4YWQHHh+GAd0BNaWOAt+3cZzmAINHQteSaGpiLzdQlokXx1HjKdort0hPn6azdhfHve95FAg2OzepmPNM///Y+88Y2dL0zhP7vceHNxnp7b15fd0yXdVVXaYN27HZ5HA4GHJnF9jBftBKgrAQpNWnXWEhAwkQIEDQp4UEfRCglXaGw9kZDoccNtmGbau6qrr8vXW9SW/D2+PP0YcTaSIjIm9m3lvNkTB/sFhdGRHHn/d93ud5/v9/5mXWGzf2A5Y9fZ7DCG2Hzs3bCAHazEwkmXH0O2GA79skEuOoapPmM2bBykIhJ49T9ja/eJaWb5vsvv/jvuEgDIJuFub4I8gWLjI6/QKdZpFOc4eQMCorTF4nnhxjc/nXA326Toog8Kg3Vo/VmzkNytUHTE2+hjZgote1yGxvrzSkpVTWfrOD1XDw7f5oPh4bIZmc6vt72K0xV2uPnilbqNnapNncRMv3r8LisRFSqZl9aXXLDKlXA+YXVVqN/mOQZT0S0Roi41+pPjhxCv84hKFPo7mG67afSEsPg24zb9DVDwECz0FP5PFdE88+GADCMKBUusP46PMYRwamKGtwhe2dT58i4BSkklP71ho9x0mU0m53iihagonzryPJKooWx2zuosUyFGZfgsBHVmPsLP8mUi2feh5JVvGcDp36Fnoih9ksMjLzAjtL75Mdu4iixQl8F1nR8VyLzQe/GEAcEBRmXiSRmcT33UidWFbJTz+PpicRkkyzvEKzssro3MuoepIw8KjtPiBdOE9x9SNmLn+L7aX3yI5dxHMt4ulxfNdC0eJsPvwVdvvJNhlPC11LMz/z9YGigCHRZL618/HQd0jPxlASGomZDOZ2k86Og1A1Asfi8Lh1rK4UwRMHWU1NYehp/MDrIwcM3+6QjYrjj+c0iN6tje6q++lRqT1i1m0NDD5VNU4yMcGuWSIkpKDNIAvtCRo8XzzC0MeyqwSh19e8vMd8kiSBqoGmC5r1/mcp6p+NDET34mTRldsYuE+Cp9b6irzMBpfcJUmNPKuOBDxaIktq9jJqKocxMkngufj2oH6ZED/w2G5FZuBB6PWXsvb2ZRgkX3sFoaigyJi3+xm/kqSg6WlsqzZU3mEYDJEgKeWp+FvEpRQJqT+IVIWOMYCA8iScOcMTus6Z13PZ0QsU1z+lWuxtRNZjOeYvfxdZ1nsDHsE+K+QkcNwW7ScooZ4GHbOMaZbRBviayIpGMjG5H/DEczoj5zNYDYetz0o9LC0hJNLpfgE8IGLRdHZpd56szHoauG57X2n46H4lSSGbnmW3eHP/RVKUKCga1AcZj43s08aPIgg86vVVntUq37IiN/UnBTxWs0R64gKyFsN3TNx2fT97I6v9K49IeXkdXU/3reAT8TEy6Vl2S2cLeCRJoTByZXBK23f3xSrjqTEUNcbqnR8xOvty1C8iSejxLFsPfoXZ3EUIiYnFNzGbO1S27jB54S1i6XEQgkR2msD3iKcnQEioepLyxg3qu4849+I/RNVTOGatZ/+yapAePc/Kzb9Gj+eYXHwrKkPrScxWifJ61GuRGllANZKs3/kJ6cJ5MqMXCMOA3MRVXLtFunAOSdaQwxDPMdl88AumLn6dWGrsCw94ZFlnZuorjOQv9WUJIkPPOqsb73RViwdDy8UYe20Ou2oSuAFmyUdSVVzb3F/Vwp7Y3lBl1ScaFyqyhqYmTpFlDo9vhD4S8Eiy6JI9ONUr5/k2zfbW6X50DCy7RrtTJB4b6ftMEgqp1BTF0i1ichJZqDS9MnF5sKDjbxOeZ3UZRkc/icQKEymZay+qhMCH75h9OrrbOwF/9A91Aj/k/Q8PjfFDst/AE+nzT0RXXHAQ9oVzj8BpVijd+BWSqmPXhpcRk1qBieRhZmlI3dqh2H7YF/gEtk3n9l3UwgherY673R/Q780Hqhob2GeHADUdQ45rkZZPsUnYZRrGpTQz2kUaVokpdZFJ9TzOEUVlCQlNGswSPg7PrqR1CnhOm3h6HLNT7qbqQyRJIZmZ6jYEHtxUKWFgLIyjz43R+vgh7s6TBxDX7WBZtWd2vL7v0Gpvk0nP9n0mS2rX5DMSNWtsdQCB03b7qKJ7gnqDsNfU9kWUBRpdfY1BgVY6NY0i6/sBj+dFwoOy0j/Yx4yRoSsY06rum34+C7huG9OqkknPH1vWshslTCOJoscxq1v4nh1pOElSnyswsK87clSYEqK+g9HCNUqVu2canOKxwtD722rv0GhGvWtCkgmCrjhYt4QE4NotXKdLTxZRGSPoNshG5SYPWdaIpUZpVleJZyZplVcwEnmsVpkw9PF9d+DAt5chiLbjdssyEPgOjtXYn2yFJEdmrEGwv+iwOzXyU9corX1KbuIKzcoqkqRgdSoEvovv2kMbfJ8VhJAYH32eqYlXBz7Hvm+zvvU+1dpjjnuHzO0mtXtFrGKLwAvwbRu7/Gz7SWRJ65ZNVVTVgRPYSzwZB+9AftrgytcKlNdMrJbH5r0mrnWyrLDv2T1N80+LPVmJ0QHsxz3bCVmoGFIKRajk1Uk6f88ZHuiayh7HFgujsbDTDoknpL6Mdzod0aO7ri77vxnWhycQp8509G1DyH1j1v7hHlHHPgzP7qDrMeLjc4RBgFXd6WFLSkJhKnWVUmcF020AIbKkMpa4QNaYomyu9GxP0jViV68AIerUFEKWcdZ7+3L3tNQajTUGkXMS50cZ/folvLYNAez85PY+U6vm79K26rhhVC1YcW6x7S73/F4TBheNV465WoPxxQU8ArSEgiRLKLpMa/dg8ilufMbkwhssXP3+/qUIwxDfs9lZ+wjvEGMl9H2EpuBslQlO4K0TEuJ6JrYzWFjpLAgCd+ggIYSErqUisbFRmcLFLL7jk04nqK+38MxDxoWSNlQkLQh9Wq3TNTqeFK3O7lANIl3PomnJ/WBFlmF8UsG2+ycNXU9HadMBMK3KMyln7cEPHCy7ThgGx06myfHzqLEUntkkM3MVu1VBVmNIkoIzsCwa0mis02xtkU33NkXvBaTJxOSZmpdH8heHsIZCSpW7+0JsZqtEbuo5Ji98DT2WwWqX9w5t7/8RBh7N0jLZicvE0hOoWpyd5d+QHb9M4LuYjSK5iasUVz4iy+Unhsmea2K1Skxf/maPY3b3APf/p9nYITO6yNSlryMrOo3SY3w3CpYds75fXlO1xP7vvvjOHUEuu8jC3O8McY8OKZZuD/VxOgw1qZNayKHEFMxiG7vioKZzSIqK12ocaP6EQVf5dsDRiMhiYdh5+4FDq1PE0DOnCJwHW9rsn+GhyWz2epr6jkWqoJGd1Nldap884AncZ7oYDMOQzhAj1T35DiEr1N0dYnIkG/HvBY5lJwoUTZDNRybKigJ3bzq4ziHLo+5pHFZaDglxhlHOhXhitvpJkGUVRRnsnh4E7tDx18iOkb30Mlo6j2+bFD/5eV+2R5Y0bL+N6UWebqpkEIT+wF5ToekgoPmLd9AW5lBGRgYEPDLp9AyalsR12zSbvZ8rcY365xtUP1juPxd87DC6jq2gSjto9DUm+3h4A/qLnoQvLOBRNJmFN8YJ3JBYTuPmXyzvj4xWp8Lq/Z+gGemubLggCNz9Fe7hITS0PdzdWmQwdhLhwTDEczuET9F42r/JrglhGAy0UVCUWPRPzEdI0NhsU7iURdZ6J2pdz/RIuh9GEHin8N45HTzXxHHbxGL9wZYkZGKxkf0mz51Nn047xLZ6BwQhZHQtNbSXwLabEbX2GcJxmgShh8TwgEdWDazaLnazhJ6ONIeEJKOosYGZDojS8JXKfdLJqb4X2tCz5HN7yssnZ1RoapJs5tzAVZxlVXuYfI5ZZ/P+L1C0WDdDYuF7NtuP38U7VF9vVlZwrAayauDaLRyzQdm7ETX5Ox3Wbv0Qq1Nh4/7PccwoYN1+9A6ONSDYDwN2Hr+PHs/id7M8rt2iuPoJwSE7DsdqsvXoHTQ9he+72J0KQsgs3fgrHLPO2u0f4TodJEneLwGVNz7r0bB51kinprlw7nsY+iCqf8S+W1n/1YkCbkmLpOiNQgKv4xIGQdQ8HuudSIJj++hEtGg9Zs4MAgdViZ+ub2NYn05ITymjsWuz8FKW7JTB1v0WvnfykNN1O2eUjBiGENtpEgT+wPdNljVULYlnNXECC0nIyEMEHZ8GQsiRN58U+U4J9kqS3X/veyRGjeS63i/4ehiuE+K6IfGEINiNGsUPY33D59/8ZQfPh2olelbC0KdjlvYtIg5DEgqpxESfUO1poGkpYrFBlPdIc26Y8KCQFTo7KziNysBALwh9dloPmE2/iNItaQUENO0damY/ozp0HIQQpL72JkLTsO4/6N9m4NJorKGqiZ5S8R5822P0d66QXBwj8Hx2f3JnoBbPjrtCMCBI9kKHR/ZnmMHpxGK/sIAnDCLTtU5tMFspCnJ8bHN3P3UuhEQyO0OnsbW/MpITBvHn5pEMneb7d59Y0tqzknjW8HwL37eRBpR0ZEVHllWaW01SEwmS43Gqy02sem/dUdOSQ2u8rtt+oj/PWRESDC83dc1F9+D7UKsM0lVQukZ2gwcJ12v3Zw6eEu6ehP8x1ZJ2aZXMzFWSY/NYjSKBFzGNWrWNoZTriLJ/l8mJV4gd0cwQkkQhf4WtnU9ORa9PJMZJJScHau80mhtH9DdCHLPW12dz9L/DMDjI/nThHgpmzFZUKjncO2N3hr8fntvBq/e+G6519LkIca1mz35CfKxWlOHcO57DoaA7KMB6RjCMHItD1LcjCnqJR8s/oT0ky3AUdqVD/WEJWVdor9chCHAaFaJujUMLrWOYWNHEfjx7UJK0PoXZ43Bsz9CR/p6dxx06DQ/VkOnUXDz75FmTL2Js9P1Ib+io3hdEzbSKYtAJihTtVWJycuAEdlrIso5hZDH0DLqWQtNSqF2mkiJr3cZjNRIglZQoIJKU6B8RiZIOU9KOjhtsM6S043HvpsNRRZR2O6TdPuLvFAa0Ozv4vo2i9PaXSJLS1f6Jnal5WQiJbHp+oLp9EHo0W1tDS1puq4bvWhhCYGTHCNyjjc8hFXOVmrWBLCIJhL3F66BetcA0ab3/IUphhKBj4tX7x0khJOKxEVQ1gaclaB1hTZprFXZ+dAslZeBW21FpawB8Bs8pISGt4PQs7C8s4AmCkJ3bVYQiYaTVnvc+kZ5k8tybqFoc12qxu/kZzcoKQpKYmPsyK/d+TNBl1wS2g1tuouZCAuskGYQQ7xmIx/Wdj+9FgdmggEdSkSWVZCFOvOuWnplO0CmbuJ2DG6aq8aFGm+4xSqtPi8hsb/BLJpB6yjDZvMT8okq9GrD88HCdVx6anQrDAM+zT6ygelJ4vvPEa+K0q1Qef4SixXHtKEDaC5zN5k5fwLCHdmeHemO1P+BBkExMkE5OUzxhwCNJCrnMOTS1P2Xt+zaV6oNnImg4DImJBFpap3p/cNOwmtSQdRmrfPKBNjmdQjEUao8GDyp6Ro+aDWtfnGCioWdZXPjOQPpwZA7aZmnlZ9QbK0O20A99JEHoBXQqDeITKZyGi6Tp2KWdHp0vP3CijO6AbUjHaPTs/9530JPpE/fLRL0Zg7fpB+4+605WBOdezlBetyitdrj6tQKduoPVOlk28lmWnfcQBH73+R4U8MgoskaXp0Tbr51pH0LIKIpBKjlFLnOOVHISXU+jqUkUxWCYo/jZECJJoGoCWRYDJTr2+nYUBVz3IHHSMcs0WhvkMuf7FO5TqWkK+UvsFG+eeqyPGSOMjV4feI6eZw2VA1FTeXy7g++YOLUSTUXtMhIPQ5A1JhlNLOL6FsX2Y1y/Q9aItOcq5qHyviwjFIUwCHB3iygjefTpKeyV1d4tdnsQbac5sMyvJA3S1yYRskwwncXabQ40Dx0GgURGHqHl1/A4eaLgCwt4ZFVi7rUxnLaHnlbZuVXdfyhGJq/Trm9Q2blLMjvDxNxr6HqKaulBNwNycFNDP8C8u4aTjvd4/AxH+FSU9mEIuuZ3gyAJGSFkAi+g8qhOp2xx+fcX2LndOwEdK2bmO0N1OJ4FPG/4hHvYjThfOBDcOgwhhjfdhWHwjNPkEZ4k8AaQnrqE22mQmriAkCR277wdNdEmJBQtDkMCnjAM2C1+zljhub6yliQpjBWeo1S5e6KBSVUS5PMXBw5Gpl17JtpEe4iPJ1ATKmpCo7lax3d8YoUEbrtrx6JKZM7lkHWZ1mYTr+My/cYM8fEEm++uDwxgEpNJlJiCltSoPa5BGBIbiWF1gxlZl8ksZJFUmeZ6ncANmP3GApImsfPhFvXl2jM7vz2oaoK5mbcYK1zvuz8hUQC/sv6rU5cIfNsjvThCbDyJWWwDEpJmIKm9k4Dn20NLmsPcwg9DkbVj2WJHEYkLDt6m79v7K+30mM6Fr+SZuuLSrroRW+sUw8ZTM4UGIAz9odnpqNT0NNOMIGbkGMlfYqxwnURiLLL9eKYBzpE9dktgW2su2RF5YPny/DkFzwt56UWNd9+z2dmNboJtd7WJUrN9Lu+qEmdu5mtYdr1H4f5J0LUMC3PfIBEf6/ssDEOq1UdDM5zp+au4nUbEAt7ojkNC6plr9qwlSp1lVElnJvMCpfbjgQtc49wC2uz0vreeksvibG73BTxB4GOaZWKxkYGLPWMijV1sUv1klfHvXEVNG3jNkwfjilCZUS+zFN7EC07+nn1xGR4voL7Rxmq4HHVwl2WNWnMH26xhmzXMVpHJhTdQ9VTPQyJUBbWQRpsaQSmk6Xy+gtM5fqUcueo++zbKMAyHNrpF6WiJxk6HVjGiu37+54/wjlhLSEeCucMIQv8LbP4Mj6Ezip4JxewEPP+KjiRH/TwHGEx7BLr02GcfrJ1km4oWR1YNPKuFYiQillEYEPjOEwPfRmuDZmuTdOqIwKGAdHqWRHxsX5TxOKRT0yRihQHHHw43Cj0jxl+exMgZ1JdrSIpE4AVkL+QggPpSjdyFPBOvTtHaapG7mGfjV6voWYNYPo4SGxywTr0+g6RINDcaXbqzIH+5gN2waa41GLlaYOTaKGbZJHs+y+Z7Gxh5A0mVUWLPfgiRZZ3ZqTeYnHhlYNNk4LtsbH/AxtYHpy4DW6U2lc820bIx3KYdCaRZncgqR4j9d9zfoy0PgKLoT8zw2E4zEnM84fEdt03Ps/ffhdqWxUd/tY1n+5gND6vlYXdOvjL+YrLI4dDFWtRTJyGQyKrj+KGLHZjYJ3BMlyQ1cmeffI10anqoe/2pjvTIGD4saDIMgREXA5vWAebnZGZnZHwfUklpP+CBgN3iTcZHr/eNK5HlxgQXz/8BaxvvUKrci4LZgddOIEkyqeQ0c9NvMpK/3B/4h5Gh6+bOx0Mzd16nSWrmIpKioeeigKl670O8dm8pOwh9auYmfujQtItMpq6iKylKnSN2FZKEs7mFX4uCDHVsdMh7EhIEPq7b6WmZ2IPfcUhfm0KoMmoqRuAcPMNRB9bxrE8FDU0Yx/stDvzdM4aQ5EiQKLCRNYnMVJx2xe6JeJq1dRKpCRrl6GJ2mjtsPPoVU+fexIjn2GeqeB5etYXfsRCruwSt357f0Kmw16Xvh4Td5rZhLul/Pzj5Y6GogpVHLp5zJPx64ga+iCDzyXonZm2b1MQFqsufkRxbIAwCFCOGosUHN+8eguM0KZbvkEpO9ahoCwS6nmYkf4l2Z/fYSUIIiUL+8j61/DA8z6Jcuf/MV9W1R1W23j9oJmws10lMReW0+FiCxkqd3Rs7LP7BRRCC2lINz/IofT54FRgGIdUHFXY/PQjuGit1tLSGkASx0QS1x1Vqj6qc//4FAs+PsjohlO88O4ozRIuh6clXmZl6faDbvB+4keP0xrunLhMqSY3EVIb4VBo1qWGXO1RuNzFGJ/E6LURpZ78s67idoYrbihI7ljmoKDEyqdmoF8J3TlTWUpT40IDHcdv7z2AYgt3ymH8pQyKrYrd9Pv7rbRzzpEHPF7OsetJWVUknrRSwgja6lKD4BOFDTUsxN/0WE+MvRUyvJ2RzQkLCwMf3HfzAJQgi6YU9uvbBP1E2StcyJBJjA0dGIWB0QmFiWmDbYV+CJ5MWVKsBQkS9PPUjlHXbabCy/jZXLv5RXzlHCEEqOcmlxT9gcuIVqrXHtNrbB/2KXeHDeGyUXGaBdHoWXUsPXGx6nsXG5vvU6ysMuwONlTt4ZhNZj9EpRmOGb/Ze+zD0KXdW0JQ4puvQdiusN24wm3mpj4hiP16KApxukONVqiAPs2Dx8D2bUOsfP9srUeZdG0lSevshTvXgmEaUaS7qr3TfxSFJBiQM8VsUHhwGvTBJfHKexr33yEwn6VQtChfSbN4o7x97Zec2mt5rdWB1yqw9+Cmp3Dz+XvklJFLACyF0vMFqeEfxDFVJezZ7mH94BMdpIBxGNPENyxJ90Tomx2VnDgbL0q5PPCHhHqWlh+Fw5oqAYf0HXzQ6lQ065Ui2vLJURVYMYukxAt974oowDAPKlQdMjr9CIt6boZEllZH8JbZ3Pzu2eTlmRGrVg+Ty683VEzfTngbBoVp3fDzB+CuTxPIx6o+qtLZbzHx1jlghjttysOsWsU6c7LksU6/PsPneYIn3w9tMzaQZf3kCJaZSX6rR3mox8eok6dkMZtnEaTm4LZeJVydx2w7bH249k/MSQmJi7CXmZ7+Oqg7yIvMple+ytPKzbkPw6eB1XKxKB8/ssrMUGa/VpL36EBA9K1XHaQ0NVDUlfqw9QhB4ke+R0+AEK4Vom+oxAY/T7HlHZ55LE/ghgQ+SIpAGaGYNwxczzoihx76X/fVDDyc00aU4Te/4AFBRYpyb+yZTQzJ8h7fteh1arS1anV0sq4rtNLuGoya+73QDnyj4CUJvf5yemXqdxXO/izSgbBMEsPrYIRZX+4hzQkA2J/HlVzRarZD4nGC36FM8ckrlyn1W137F/Nw3+rTLhBCoapx89jz57Pn9MTgIvK6A4JNLpn43y7m+9ZtjrXBC36W9sxKpQg/xogy7TcuHYXlNHpTf7v+u17uv0HUZ1EIjhEw2u0A8VsCyauRyF2g0VvflUUIvoPWoCI+KpK5MoCR03HrUY6ii4YQmu+7q0AZ3VWhMqueHnvcwPPOAR01l0Ucm8N2A0sM60y+NsHO31jPPB76L1elvsHSdNpWd2z1/06YLGIuThLZL5/PlJ1LTBQJJfvZpdkkoQ2vRYXAQ8OTOpWntdHqalfdwnMuycsQg8FnjaD35MPYeQlWF+XMqhTEZ1w15/ODgSQ4JjhHVkp5JuvkopGP8jPaQmbmGWd3CaUXPk5AimwlZNQhaT15ZR83LK8Rj+b7rn07OkEpOHhPwCLKZhYF0f993onKW8/TlLGHoxL50DevmPTZ/vYbvHpqYGzYrP3mMkAVWxSJQDHaqKezP1zG36vi2T+1Rhfste6DVCcDaL1fwD5VfrarJ0t8+AgFm2cSzXKyKibE4i+3qBE5A6fNdOrttPHNwySb2pefwdkq4myezVRBCZmLsBRZmv4E6QGskDAPK1fs8Wv7x2QUugxCCkMR0hs5WHavcRsgyxtgUBCHtdnPftdlxW0O1qzQteayInCQp5NLncL0ObbN4ogyPpqWHBlFRwHNwz1sVB6vlkXxZI55RT5XUHyZc9zQ4ThCPMCAIfAQCJ7Bp+pVjyQ1CyMxMvc7E2IsDx5QwDAkCj1Znm93iLaq1R9hOE881n8oDr/cYon+2NzzSWamnkyEMYWXF5/NbUf/USH6Y35rL+tb7hGHA7PQb6Hpm6PgeifQpJxpD98pY65vvsbn90cmynEFwxrze2bOBQgg8z2Zn9wbJ5CSdTnF/AZG8OE7oB2SuTxG4Pukrk6z/64/2Ax4fj4q3yYb7gIDBY5YmDLJyv73Mk3CqWSp98UWU+PHiSbHxWQhDJFmQGDFobD+df4i9vI2zUSJwvIE29P0QA6l7TwtJVgdbQtBldHRr9empBNm5FFbNpvSg1hP4uF57aC9NlCb/YgKeyONlsGAVh8SyXBfWV11Kuz6x+BFWTBAMZb8JIR0bUJ0VJ2HDEAZoiRyBa0X6F5KCa7dO7AJ+uHl5EJV0rPAc5cqDgQ2sqmKQz10YONjbTpNy5T4QIjQV7dwsUiKOu7mD32iizUYKpUHHxCvXkDNJ3I0d1LkpvO0iSiGPMhbRPt2tImphBK5fJjQtnPtLSAkVbWEGJEFraY3Q89EX59EyKSxbobnWJDSjCdu3fZqrDZTRPLGXzxE6DtbdR6hT4whNRSTiBI/XUOfSeMUKgWHQbkfHpi3Moasq5toWXslBv3ye2EsBXrlKY30bdXqC2Mvn8UoV3NVN1OkJlNE82sIMfv3kWZjR/BXOL3wXXUsP1Nqp1pZ4tPRDTHNwE/pJYddM7EqH6W9fovTxOuUbO1i7mxCEPf5jQeBi23VSycm+bciyHgkgDhnaPM9kt3yLIPBOPAkbembIBB9gWrV9ZWyA9VsNpq+m8JwAq+XhuSfvy5EHeF49LSRJHrpdv+v/JAmZhJxGFVFz9jC2ViY1w9T4y0MFTl2vw+ZWlNmw7UgV+FlDkmDhooYgIJWRDrd27eP+A49/8sdxZAXe+83gwNj3HdY236PV3mZ66ivksouoytnmpjAM8XyLam2Jjc33u0SI345Z71kQmYc6aFoK1233LBqdShtjPIVvunRWy2j5xP5CAyKl5YZfHhrsAPihR9nbwj2l+OCpAp6Rl76KpOkEzvCoUomn6GxHKTRJEZQe1rFbZ2TwSAKhyEhxHX1uDHe3hlc5fhAVQhqixvp0UGQdacik7vn2/mqw8qhObiGNYsiIIyU4x2kNMHWMoKrxL2T1FUH0uaXvIQyDnvJAOiNx4YpGudh7nEHodantIUfT9HsBlSQpz7RfRe3STY9DGARkpi+THJvHdyxqKzeRFT1KYZ+QrddsbdJorpPPXej5uxCCTHqeeKww0ABSN7LkBlCmAeqNVTrdyVlbnEOdGMNZ3SS0bORkgthL1zA/vU3QMVFyabQL87hbuxhXL9BptDBeuEJQb3SDhhARNwhNC3VmgsC0kPNZJF0DRUEydIKOiTo1hleuocQGTBaKTPwrL2E/WCboWBCEGFcv4DdaeFs7CAHGlUVM20EZG0HSVPxGC+38HM7KRpQOl6WIkup5xK5fJvR84l96Dmd1k9iXrhFaNrGXrmI/WEaoyslK0Ajy2UXOLXx7SLATGYI+ePyDZ+Izp+diaBmdrV88wtxpQeDjNWoDv9vuFCkMtEwQxGMjx9LhT2NcLMs6up5mUPkrUo3vndjPvZwlllYorXTwnKBPFO84RD0lT1BNPCVkWRu6yNxTAPZDl5KzjixUFDF4HJUljdHCcxhGv8AkRD0rK6u/ZGP7g6eWeRDHKFsHAdz/3AYCRieUgVyVy5cUbt9zqVaDPj2ewwhDn2p9CSEpxGOjPQHPPtlDHD2WsMt89QkCF8dtU6svU67cp941Vf57hyTt9/EIRYnGh0MXKgg8arXHqGqi73idcguvZdF6XCKwXOxSC691SPw0fPK74+Ox7t4/tRTKqQIez2xT/vXfYpc2h34ntfg88ck5giCkU7VJjBrE8zqNzdMLXglZQskmUcdzyKkYXvVkK8Zo8lWfGVVaCGmg2eQePNfc17nRkirJiTiqLlNZauAcCvYsuz50IJQkBUPPPFOfmz2oSiyyAhiAaAV5UF5sNkJWl1zcI4FzEHhRwDZARRSiNL8sac824FETQ5lh+8e784h2qVt/DkNkRcex6mixLIqeHEpLPwzX61As3yGbWehbZetaar95+egkkc+cHxhcB4FPsXQ7+r4QyKkkfq2O8yiaIJWxEfx6E2d5ndB2UGcmEZIEQkRBDGB9dgf94gLa/DR+rU7QbOOsbCAMHSkRQx0bQegafr1JYDtIiTheuYa7voU225+VEKqKMHTsh8v7mdLQ83HXt3HXNhG6tp/LF6oCsoy7tYsUj6FOjBK0O+D5uNu7OKubaLOTKLk0ykQBv90haLaRYtFg7iyvo52bGcpqPIxMeo7Fc79LIj46MNhptbd5uPTDE7HlTgJZU7BKHZpL3WdeCJREmtD3+po5h+9TDKQInxW6luqqmPe/V063J+UwFF3CtQOaZQffDU9FS1eUGLKsPUNdKHGsArvvOzhuK9JNUSNfLdsfXOZV1QT53IWB29oTC93a+fiZHPtxjFkE5EdlJqZVEkmJtSW371F2PcjlBK4jUI4ZooRQGB25wsLcN3oMVqNne4tafRkhFBQlammIMiNu5Adp1+mYRTqdEq5nHtsDehyEoka+fH36O2eDFIsRu34NZ22dwLIwLl7A2y32UdN93xlaFpZ0FSELAstFyNLQ/tjjoAoNN3ROFfScKuBpr97Dqe7i28PLVF67TuC5yIog9EM2Pysz/eLImRYVoevj7FRxdqpImjq06eowhBAoioGupXom8qeBJKnEYiMDB6QwDLCdFl73xqYmE3TKFiOLaRS198UNfJeOWSaZmBhw3DKJxPgz1WzZQzxeGFpyctx2NzUMigpjEzKFMZkggI3V3uDFdhr4vtNX+gGIGVlkRX+GSq4CfUia/zD01AjZ2euosSROq0rp4Qe4zTZWqzyQOTUIeyWTTqdEIjHec58lSSWfPc/27qc9mTBJUhjJX6J/0Iwm6T2rDsIQd3OX2AuXkXNZnMerBKZF6ByolQXNFlI6SeobryMMHcIQdXocVAU5HgMhETpOtCL0fELLwbr3GG1+mtDz8MtVfFkm/vJ1lEIuaiw8PEILQWg7eMUKqW+9id/qYH50E8Jw/50KXY+g3iT+8nMIw8Bd3UBOp5ALeYSmISXihKa9f9yh6+EVq9gPV4GQoNXB3dpFv3SOxFdfRc6ko56ZY5BMTLC48B3SqekB9ySk3dnhweMfUG+c3tdsGCRVYuTFKRIzGZpLFcyiTWJuEd+xaS/d67HIaHd28TwbZUC5JlLVlp4JzdvQMxh6tu/vYRhiWbU+PZ/alsW5V3Ikshqdhkt1yzxxlkeWNQw9OzBjeRYIIYgPCFb3jn+vgViXYkhIBKGLLAa/l7FYDuOIEOgeXLfDTvHGMxtfFDU+XGYjgErFJzcikKTBPFHXCbl2VSVmCLa2fWr1QXOTYHzsec7Pf4eYkY223c3qlKv3WVr5WXec+GJLU2o8RfrcdezqLp2dFXzHPiIjIIirOTpuBUXS8YLjA0ph6Bjn5pETCdzdXeRkAjmV7Al4DuskHSXGIAmSi6PIhkLt0zXyXzlP7eNVzI2TKyfLqMxpV9lwHmCGJ++TPFXAU739YV+X9lF0tldwaiVSE3GmXhwhNR6jVbTOdE+FpqCOZkESqKMZnPUi7u6TRYY0NYFhZJ9ZwCPLKqkBQQocMDL2TnD3ToXURJzmloJzpHE5JKDRWGOs8FzfdqR9J/Vnm24GSCenh6okt1rb+ysm34Pijk+9FqDrA0T0rCqeZw0OeGIjaGoCyzq93PcgKIpBTM/yJJZLojCL064eNFSHIWHgEcKpBCg7ZpFqY7k7eB8MhBGNdJpkfJzK4dJfcpr4EWYXQBBEg9meea3QVLydIu1ftxG6RtDuoEwUMD+6Sej5kat7q0PrZ++hX5zHuvcIv9nCXlqL2ImuS+i4tN/7lMC0sB8uEdpR0OGVKhAEBG2T0Pdp1ZvRPkyL0PMQmgoClIlRvM1dOr/5DClugB8ZY/q1GmE7mkCEqtD57A5SPIaQBH6rE13LW/cILYfAdqJbsbZJaDu0f/0xgWXTfvdjJF0j9H1Cx6X19ofRfwdBVDobdt/iYyye+10ymfm+z/YtI5Z+TK22zLN8H6xSm+ZyBd/yIraW7+NbZuQQf2QZ7zgt2p0dMkdMZiFSgY4Z+afOyAohkUiMD8wURlYFu30q6WbTQ5IgO2nQqbuny/DIOon44BLtWSCERCrRn1GEveMvAiFOYLFrr5BQMkO3FY+NDFWid9xW13n76SFLGoY2uIS4B8+FasUnlpAGjsgPHnmUKx2+9JKKLA/eTi5zjoXZb2DovedcqT3k/qO/fmZj5ZPgturUHn5KfHSWwvNfwyxv0tlexjOjQEESMpOpKzyqvMts+kWWah9w3DsXej5uqRzp5I2NEpgWUvzg+ZVljVxukXi8gOdF7R47O5/ufx6byDDy+nm0XIL09RkCx8N7gr7eUchCJinlIl+2UwwPpwp4DlvKD0NgWzi2RaUBH//pQ5y2R2LkbI1aQlWQuwrLQojIn+sE0LQk8fgo1drjM+33KAw9S+xQOvIwPN+m1T6g5aYm4hQuZumUrb4enjAMqDfX8X2nL+MihEQiPo5h5LCeUaAGoMgG6dTMQFZJGIbUm6v72SkjJjh/UUXVxMAMT6dTxHHbGEaGo4OFqsRIJiZoNDd4FhOUrqWID8mqHUbguXhWGz01EjVOCoGkRF46ISGeffLm5WLpNuOF632uxpqWIJtZoNZY7qaVBZnMwkB9EMdpUqk+ilY0qoI6O4GQZQhDlLE8XrGKOjWGn4zh7ZQRqkroeviNNn69SWjZCElCyaW6em4BcjqJV64hpeMo+QzOyhbK+AhyMo51dynKugCBaaGNjyAlY0iGjpRN4ZfrqJMFlFwad7sUHQshgWUTWnYk46BraOemCU0boatIyThsFhGqgpSI4W7sos2MI2IG1u2HkURBJ5qEQ9PCNw8Cm6P/PfDe6hnOz3+bkdylAfc3xLbrPFr+MeXq6Wv0T4Ka0kmdy2PuRIwst9nE6zRxykU40l/neh3qjbWBAnKaliSdmn3qgEeRdbKZcwPLOL5v02j2ywhMXU5y/90K2w9bvP4n06iGhOec7DrJsk4yMcnuXsn1KaFpKRKJweW9MPRptjeRkEkq+X3j0GGicup+f1E/bLv5zCyDND01NGO/B10XXHtRx7EHZ3jyOamb4ZGwrP5vqEqcmamvEI8Vevbjeh1W1n71Wwt2ACTNIDl1ASErmKV1JM0gPX+Vyt0Put8IUSSN87nXycdnu9pn0TkV20u03d62gNCycHd2EUoUPkjxOF714Hx836FafYwsa9TrK2QyCz2/NzdrbPybTxCqhLle7XsMk1KOCfXcseekCJWENDx4Hvq7U/+iCyErKMkMkjpAEj2w0Q2LkXMpZF0mNRbj4z99eOp9BG0L8/46cjqO3zLxmydjfAlJJpteYGf3xpmM2o4in7s4NEPiOE3a7QOtFcWILml6Oknpfq3v+6ZZpt5YI5c933fdYkaOfO4Cm1vHR9inQTI5QTo1M/Dltu06jebGfrrR90J2tjwCH4x4//cdt027szPQJBNgJH+Z7d3PnkHvlCAeLxAboF58FI2Ne1G2oqvd5Ls28fQERnIEs7Fz4oAHoublenON0ZGrfZ+N5C6yvvU+TtcbJpueRxxJiYdhSLO9vT9JKdk02vxUlDGptxC6hhQzujVrCTmXQcSNiDbq+RFjytCRFRltYZrQ8QhaHfxmCzkZRxgaXrmOUBX0xVlC30doShS4AMpIFm1hOuq3ESIKuJPRyksoMnIu3W10lgnaJkLXELqGkkqgnZvGr0QS9H69iZxOIiVieLsVpJiOtjhLaDsIRY4yU2eErqVYnP8OhZHLg604rBqPl39CqXwyW4/TQlIOuaW3u/L4iTRKPEV75X5P2TwIPGqNFSbGXuozxpRlnXxukVLlzlP5U8Xjo2TSswM/s5wG9cZq399bZYfZ59IU5uMEAQSncEsXktQVs0udnd5/CPnsIuoADzlgXyNHk2IoQsUPXUIkGFKmPk7baFgvyOkhSCbGSSTGh39DQCojUa8EiG57ydErLEkwNyvjugwMeOLxUfK5fruZen3lmWXXTgohybitKnatiGe2kTQdPXsQpAahz0rtY5LaCCm9gOnV97Od/gAWVOhHGR4lnQIE7vYuXrk3KIpYjg1yuQt02v1aZF7L2tfYU/Nx/JYTMbGJAp5J9Rxtvz5UeFYSMsqQ0uhxOFPAIySZ9KUXGf3yt5BjCSRFjfp2jDh+p0XlxtvUP/8l1ohObaNNfn4wQ+gkkJMx0q9fRZspUP3bD3HWnszUEAjy2fPEYyMDV0inga5lKOQvDWULVWtLPQPe1qclPNNDUiSsev/DYjtNytX7ZNJzfTR3WdaYGHuBcvnuMxmMZEljrHAdXe+PhMMwpNHapNU6yE4JSZDNy6hqJKm+MsCptlJ9yNjo88gDVqSZ1Azp1Ay1+lLfZ6c6blllNH/1RLoUvhtd+07pIN0dBj6u1URSNCRZi3zKTgDPs9gt3mIkd7Fv37FYnlRikrLTxDCypNMzfU3sQeBRKt/ZD/hC38fbKUf9MR0TUaoSmDaB4yA0FXenjJxNIWeShJ5H6LoITSW0HdytUlSashyCdqfLepJQxvL41Qb2vYgJdbhsFHoe7tYuQasT9c90e3SkTjIqrW2XUEbzSHGDMAgJHReha4SOi7uxS1BvEgYhQbMNsoTU6iBnUzirW9j3V0BAaJ994lHVOOfmv8X42AsD3yfbabK08rOuueLZg6rjYJbaVO/sEJtI0VqrRfeoVUfLFohU5nr3W2+s0rFKqGq8L8uTz10kmZg4lS/SYUTaQy8OlYyoVh/huv09K1sP25gND8WQWL/VwD2FW7pAkEl19aUqTzfGqEqcQv7K0MVgvb4a9TcGFnbQISFnUSSDtjc4u3Ec4UFWno3shaIYTIy+cCwjVkgwOa2weFWhuOUPXHsunlf42S9tZmdkclmJYqn3HqSSkwP7Jk2riv8FeD0ejxC33cAzW+jZUTyzhbl7VGiwgeU1CAkod6K+vGGQkwlSr38Fd3ubMAjwG42+Vpc9oo/v2QN7KROLo8iaSuWDJUa+cp76jY39Hh4BbLvLPLY/G+qWrosY14w3TncZOGPAI+kxspdfpn7/UzyzTXLuIpXP3kHLFkgvXqe9/hjP8VF0mYU3xrEbZ7/BgenQ/uwxXqNNcIo6n6ommBx/mWZrm/CMglRCyIyPPt/XyLoHz7OoVB8ShB5CguxcmsxMkjAIycwmaZdM3I2j+w4plm4zMfYSycRE3yCaSc0yPvYCaxu/fsoVriCXO89o4dqQYzcplm71scZsKyTwhxs61BvrmGaF5IAVkqolmJp4mXZ7G/cpMmvp1MzADNhJIas6ejwbaVfYHewBIpeDEdJortFqb5NKTvfsX5Y1ctlzVGoPSSWnBk5Sll3rCfb8Sh2/0t9z5m0flEH8cu3gf1cPJiCvOPiYvZ1oJeU0+zNXXrGKVxwwmWwcrLAO78O6dZB1PXxM+98F3M3ot07r6Zo0IPtUAADuZ0lEQVRFZVlnfuZrjI+9NDCQtZ0my6s/Z6d44wsLdgBiYwn0bAw9bZCczVJp7IIk4zvWQFaZ09VTSiene+xHICp1To6/Qqu1dYZySyRaGZX1+hcPrtuhVLnXp9slq4LFL2eprFuUV02ufG2EdtXFap18jFMUg4nxL1FvrJ25CVggkc9dGOhkD1FGplx90F0MhmhSjJSSxwraJJQcHb//vXDcNsMmWl1LoSjGU1GyhZAYK1x74tgiiMbB939ukisMXug+fOTxxus6hHDzZv/8pqmJgfvQtRTyM2QQPwlCVogVplHiKcLAJzV3heba/R7ikUCQ0sdo2Du0nQpPri4I/EYd8+49Qj8gtPuffSGk6DyFjy4PWHC7AepoDGMig5LQe4U1gyp22HmCDo+PFXaGKjEPw5mU7oSsIGSZ1vJd7NIWgWVi7W5Q/fw3dLZWiU+fByEw0hqpsRiyeqbddHcGXr1N5/OVY5sgB2G0cI2xwrUzC/pl0rNMT7060NMnDENqjRWae/07Xd2hxmab2lqT+lpzqLKtaVXY2b0xMKCRJIWZqa+Qzw6mZ54UycQE8zNfH6q/U2+sUq4+6PmbbYV02sF+lmcQbKdBqXxn8LELicLIVUYL188sYa9raWan3+zqkpwNvmN2GTQh/inLDaZVPejBOQQhZJLJSVQlPnCQj4xCH+w3K/8HHECWNWan32Bq4ssDV9aeZ7G28S6b2x9+4RNB4AYYowkaj8t4poOSzETMrGMo9MXyHSyr1vd3gaAwcoXxsRdP/bzHjBzzM1/FMHKDn6Xao4G0+PSozvlXclz7ZoGXfm8cPaEQnLC38TDyuQtMjL90ZifzRGKM2anXBxIYIsr1DrVG5PEkoZBUcqiSjioNN3w0rcrQRZ6mJsmkBpf+TgKBRDZzjtnpt1CGirDuHT9YZsjcoorrhAMfDV0XjBYkCgUJVes/n2HZqlz2PPn8xad0kD85lHiKxNR5UjOXyF97HSEr+FZv0Ci6bukgmE5d50lEkdDzkGIxUm++QeorX0ad6O/hisg8kVu6O0BtvrNaRmgyE997DqfawakcHFMzqFH1d471UfRweWzfwAxOp2R/tqseBlH/gKISODaSEUeOJfFdm8Cx0DJRg6+QRdRs/BTtKPrcGMa5CULXo3N7lcA8WUpdCIGmJjm/8B3CMKBUuXsKjRhBMjnB+flvEzP6m9siDxeT7d3P9q0DQj+k/KhOcjyOWbUJgxDXGh6hbhdvkMstks8u9m3f0HNcXPz9qHGzcv9Uk4Dosr3OL3yXTHq2L2gKwxDbabK+9f7AdPkTm4QDl2L5NqOFa8RjR+moAlWJMT/7NXzfpli6fQq5d4GhZ1iY+52nDvYkRcNsFrE7VTzndCvYMIz8mibGXsToUkkhui6GniWdmiY5gJXieh0q1YdDew2EJJOfuApColleITdxlWZ1lU59uKbVaZHITBHPTNKqrqJqSbR4lvLGzaGWIL8NCCEzOf4Kc9Nv9TGRwjDE923WN99jY+v9Z26y2ncsskBLG4R+gJ6LU7u7i6SkIoaZP1zjxDTLbO1+wrm5b/Zlp6Ln/et4vk2pdPsE7u0CQ09zbv5bXc2Z/rHFcVts73wyMJtR3bL48C+3CPyQVtXBbvmnMA49gCIbzM98Fd932SneOIW2jSAeK3Bu/tukhvQG+oHDbukWphllKUMCbL+DIaVIyFla3uDspWlVsew6iXi/ZYCqxpkYe4lGcx3HPd0kJ4lIQuLc/LdIxMeeOMYJAbG4oLTjkyvIA5WWgwAcO4yqoAMmuI5ZHqhZpqoJLpz7PXKZc5EUhrmL43QIAveJRsmRIGHYY4T6JLjNKqUbbyMpKk5jmCZZtN1LI18na0z1jL07rfs0nd42ksCyaL77PpIaLV78Rv8iT5IUdC1NtfJoYLY/DEKad7ZoPdwl9AJ6EzX9V0IgISF3GXMhPj52ePrs5JkCnsBzcBoV1ESadu0Roe8x+tq3sXY3SC0+R/PxgR9Wq2hiN89e93c2y/j1qJzlm6dLGwshiBl5Lp7/PonEGLvFW5hW5dgAQlOT5LLnmZt5q+uiPfjlqNUeUyrfoWeQDGHkfIbmdpv0VJLK43qP8OBh2Had1fW3iXUZYEdLW/FYgUuLf8B2cord0ud0OuU+59rec5UxjCwjuQtMT36lK+TWHzQEgcvm9odD6b5hGLK55g1cteyh2dpip/g58zNfHVinjhl5Lpz7HjEjz27p82NXbhBd81RqmpnJr5DLnt/vbYp+I44doNRYCt+1CDwXNZ7BNZsEvoeeyOG5Jq59ei+rZjtSXj4c8ETHmSCfu9hnbBmGIa3WNo3WkOBFSBiJAunCeYprH+O5HQLfQVFjgECLZVDUGJ7bQZJkRHdS9VwLAShaHNdp47s2ejwHhNjtSk+AIKsx8lPPYTZ38RyTIPBJ5mYRkoQQGkYiTxgGeK6JrOgIIROGPq7dQjPSEIZY7QpaLI2sGLh280zXrue0hcRY4TrzM18dqn5uOw06Zplc5twXqkbieSYWZdIXRih/tklsNEXqXJ7yjVKkHq8Pt1wIAo/d4ueM5C6SSc/3vauGnuXCue8RN0bYLd3ENKsDA31VTZBOzTA79Tq57HmGraTLlfvD9bhCcC2fS2+OUF4zsVoe67cbuNbpUvsR0yzN4sJ3SMRH2d79jI5ZPLY5WFFiZDMLzE6/STY9N1THptncYLd4g73xJSTADW1koWAHnaHUc9ftUK097mM2RccrURi5jGlX2dh8H8uuneAcZeKxAuOjzzMx/iUMPbO/3SD0EUhD9INgZ9OjXvVYvKIOXLAHQUipHGBaIeaA6n2rvU3HLPUFb9HzkmZy/GXGCtfxAzcKXI7JCoQAYYAfuLieiWXV6HSK3X2UsezascGP1zkISLR0Hs/q9IgQBqHPav1j4moWXYlTMdf39ort9wfdkmGQfO3LqJMT4Li0PvoE69793mPeE+QX+2fQAzUbJ/vSHJImY4ynWf2zD7B3BveUxUWaCfUcWXkUWaiYQYuSt0bJ28Ab5Fx6DM4W8Dg2lU9/FTX8dVpUPn2bwiu/Q+bKy7Q3l2jc/wxJFsSyOmbNJjuXZPWDs8nCh46HfmUUOZOg/emjJ1pLuJ6JaZb3ezCEEBhGlnNz32Ss8By1+jLN1hamVcF1OwSBjyTJaFqKZGKcbGaBXObcwFQtdDMkdp3VjV8PHBxqa01GLmQQksBpH3czQirVh6xuvM3iwu92vbSODqQZ5me/zuj+cW9imhUctxUZ8gkJVY1h6FmSiUmymXlSyanhglphSLF8h/XNd4cGT0LA1KyC2TlOLj1ga/sjMunZbjam32rCMLKcm/8WhZErVGuPabY2sewqnucghECWNXQtHbFUUrNkMws9gcReWj9m5HsUSo8iNXmRTmkNq1Ekt/Ai1aVPI9XiMERWzyaHEAQeu6Vb3f6ng8FZUQxGR672uR8HgUe1vjTUwVsIgaonouPZL7U57A0Eqp4gnppAVnUULY4kJHzfJTj0j6zodBrbZMev0Cgv4ZgNOBzwKBqqnsRqR6vnwHP3B0FJVtHjeYzkSHQ+YYiqJwjDgFZ1Hc1IEYYhihYnO3YJs1WkXfNw7eE9FSeBqsSZGHuhL3A8fF0S8TGuXf7jM+/jpKg31ri7/Oc4NZPMYoEQaK1UkFQVNZ1B0gyOS+V3zBJrG+8SjxVQj/Rn7L2rC3O/w2jhKtX6Mu32duS4HgaRppSRI52aIZtZ6No79CMSWyyytvHrY7Ndk5eSVDdMEjmV9JjG9sPWiQIe33dptbf3WZt79PrZ6TcYHblKtfaYRmujZ4yRJAlVTZCIj5PNzJPLnkdV4kMChRDXbbG6/g6W3Tt5eaFLxd0kIWeG+gn6vk2pco/RwrWBkg+yrDE3/SapxAS7pVvUGiuYZqVnspeEjK5nSCTGyabnyecu9PRK7ong7ZZukUnPERsgdBgEUNz2CcOQ258OHicfL/k8Xhrep2haVTa3P+Tc3LeQ5X4msyTJSFIMldiQLTwZe/ezXH3Azu4NOmb/HKtlRgl9FyMfZaUTU+eo3f8Yq9JbLnX8Do4fZUxq1vFZZ6GqBJaFeesOQasdsU6PIAw9ms1NFEXvyg30wtqssfFvPgZg4veuIymDg2BNGFw0XkYTBjV/Fy/0iEkJzukvoEkx1p17p+rjOWNJK8SuHDRCdraW2fi7/wEhqwR2h8B1kGRB+XGD/EKSzRtn15WR4noknpZNIOlPpqHV6yusrP+K+dlvMHJIplwIiWRigkR8DN93u4af3dq9EMiSiizrkUP3kIxCGIY4TpOl1Z8OZX/JmkxyLI6WUNj5vAzH6iSGbO9+hiSpkUv0gEa3SJ9nlHisEPnS+HbPcUtCRpa17ks1rAwUEgQ+5cp9llZ+OrCUtYedTZ9WI8B5QlLOsussr/wMTU32NV/vQZJkMulZUqkpfM/GDxzCoOsdIyKHdUXWe1Q54UCv6NHyj5meeG1gwCMQxAuzZOeuk568gO9YuGZz36vMc819BtdZUG+u0Whu9FCGhZAGTt6O26JUvjt0W2Hg065vYrVKtCq97AhJVomlxlC0GJqRxvMsbKuBa7dJ5eeQFA27XSUMfByrgdUqoseztKq999ox65jNXZqVFVy7hapHvVsCCT2eQ49nUdU4kqLSKC8T+A6yGiORmURWdGwzmqAa5ccksjP7gdPTQAjpzL1cXwgC8B2f0A+xKh2EJOFbbfTRSST1ySygUuU+sY13WJj9xsAFkSTJJBOTJBMTUcDatQLYM9c9+pwfRhiGmFaVpZWf9MhcDEJt2+b8K1lyUzE27jTx3ZMFpe3ODg+X/paZqdcZHbm2vzASQiIWy2MYOcaC5/H93rFx7z2NzHyPEevzTFbW3x5obOmHLi2vguk3+wQee86tvkSxdJupiVf6msQhKpXkcxfJpOdw3Q6eb+F50ZgoSfK+dYaiGChKrC+bFC1mPufR8o+jloWJVwYcxdPnGsPQZ2PrAxTZYGryywMDuKeFLKvR+JqcZHTkKuub7/eVJ4UkUOI5jMIkTq2IkI+f8g8HO7oc6SIdtQIJXRevWEJoGvriAtaD3mykJCnoeppYbARJUtC0JLUjmnixmRwjb13oHp9G5cPlgcczqswiENw0f4kdWoQEyCiMqrPMqlfYdVexwpM3sp+NpaUZpC88j7W7jlXZgSDo86FBQOgHtHYtjLSGnlZPz9YSgqBt0bm7hltu4jWeXLOrN1apN9Z4tPRDZEkll+0VMBJCQlF0FE7vGux6HVbWf8XWzidDSzT19RadssXsq2PI2pMHe9932Nj6Db7vsDD3OwNXHNFxi/3A5rQIAp/t3c9YWvnpE1PBQRD5aT0ZUdP2o6UfcvH87w8VH4No1SWpcVROZuraau/weOnHNJubtNODNStCQjqlyEjPaVdxzSi7IqsGsdRYdH+eonnMtuuUKndJJSefSI+v1ZcxrZO7eCtagkR2Ct81CXwXPZbFtdtRr00Y1dMJQ1y7hd9x8R0T26ztN2EbegHNyAztTxJCIpGZIpYaI5GdRjNSCCFHFFFF69b/I0XqdquIZqSw2hXsTpVYapzAczASedr1jaFmt/+/CNlQiE+maa/VyD8/iVVq095oR89Jd3I/DkHgsLH5GyRJZW76rYGWE9GkJrqfnXyMse06Sys/Zbd0a+h3hIBLb4xgpBR8N6RVcbBa3omblpvNTZrNDR4t/QhJyBRGrvQskoQQKLI+lGZ+HHzfYX3rfdY33zs2O+WHx88Bvu9Epf5YnpHcBQZl3fbsg4Zl4YchKk3e5NHKj7HtSONoamDA82wCE9+32dr5CE1LMjH2Up8MybOCJCmkkpNcWvx9dD3Fytov9++BXd1F1mM4tRKe2cSuFXE7/aUjRdLwAgdNju/rIeViM3i+Q7HTG/AEnQ7m/QcomQzu1g5u8UiPT+DhOG1kuY5tN4nH8n37s0stij+/B36A27IIrMHPTExK0Q4aWIf6dXw8mn4FoYovVml5D0JRSF98gdxzr+HUyzSX72Jur+B1WvtqzIEf0i7bjF7K4tk+elJh49MyZu3k/Txy0sBYnMSrtfFKdQLr+N96nkWrvUMY+rTa2zx4/IOoOTC7+MTVyXEIwwDTrLCy/jY7xc+O7UdJTyWYfGEESZZwOydrwgwCj62dT7CdJvMzXyWdmj0203Sa47asGpvbH7G589HQksvToFJ9yP3Hf835+W93e56Gr2KfhCDwqDfWWFr5u32GR6dTGtj8twerUSTwPWQ9jkDg2W3atU2M5MhTiZWFYUC58oDJ8ZeJGfmh+/d9l1L57hO1NXzPobgWpXAD36W8cRPCAMdu4jkdhJBplHzCwCcIo383a5G9hKLFCTwb37MxWyU6jR08r8bCi2nW77ZI5lTaVZdm9Q5GwiY/FadZKtGuf4KstrDaJTw3CXhorozdbuLZSmR2HDo4nQS+FyLJHlOXfdZuLRNL28hKiCRLxNMKRlKhvG5hJGU8NyTwQoIgRFElZFXsN86GAUiKOHVPyW8DnulS+nCdznYDp2EjKRJqOofXaRE49om8+jzfYm3jHXzfYW7mrS79+OwN9kEQjVUra7+gVLl37HdDoFV1GDsXx+747D5uM34hiaJJeE/Q4vF9h2Z7Cz9wMa0KD5d+iOtZjBWuIcv6U4yNUYl/fet9NrY+eCaN56ZV5dHSjyEMyWXPDVSJP+0xOm6bnd1PWV1/Z1/jrNXexvPtAQHe02V4JEklER9lfPQFspkFDCP7RBPkZwFJUpmdegPHabG5/dGBoOwhCrpnNgmOOCYIJHLGLMXOI87n3wBCCCGmptlq3unbj+j28EhGdN06n9/G3dzq+U4QeHieFXmpDWgtiE9nEZpC885W32eHYQcdcso4mjBwQpuI9SeTkDKEhEPLo8NwpoDH77TY+NGfkZhaIDF3kZEX34KXvkp7/RGd9UeYxQ1Ct0NuLsnuvRr1jTZCFvju6QbBKMARGItT+IUM5v11/GOyPKZV7XX+bm1y78FfMjX5KhNjLxIzcqccnEI8z6ZSe8T6xnvUGstP1MbRkyoIge/6J7bCgCgFWq7cp93eZnLiy4wVrkfeMmd4UfaYHpXqI7a2P6LWWPnCtE1CQirVR1hWrdsLcA1tiPPz8cfbZLd4i/XN9+iYZfab5pwGrtcZ2veQmriA06mRnryIEBKlB79BkhV81x5Kfz0pWu0tGs31btZt8LZa7e2uNMET7nUYYHdqAAS+Q6dx8KI/iUnm2geBquceDF5GIomiCsbmY5QkwcwVgWokkBVBddtG0RoEfoCqKzhWm2bZRTMkcpMyYRgiKxJ6PMbq53Uqm1EaXFDFNutMXU7juyozV1NoMYkwhGReI5aUsVoeRlLBavt0Gh4CSBVUfDcKgLS4zNIndawn2979VhG4AeZ2A0JoLpVBCGJTC6jpHE6thNvol7kfBM+zoue0s8vM1BtkMvMop8y87r2jpfJd1jff71LQn/QMwcbdJvlpA4SgXXNBPDExBUS+YIdp7h2zxMOlv6XV3mZy/EskE+OnHht936XWWGVj8z1KlfvPcIwJabY2uPfwr5idfoOx0efPWBKKSvmN5gYb2x9QLN7q6V10nBadTrHrYXgYZx83dD3D5PiXmJp4BV3LdMu6/Uy8qGzoPnHCFgiEkJEkBVlWj71HUeYrxuz0mzSa6zRbm6ipHLJ2EHAkpy/QXL2LXTvIyoQElMxlAFp2ke1WpF6fj80M7I+RNA0ENH7+K7TZGZSRfF/Ao+sZCiOXaLW30dQUnc7BmB5tRKDnE5jpGPgBnukMNBsueRuMqrNcNV6n6u/gd3t48vIUu94qdng6vbcziwH4ZovGo89pLt1BzYwQG58htXCF1Ff/gMajW1Q++QmxrI6sy8SyOg9/sXnqwDl0fdo3HiMk6YicfUjgu/uU8D0021t9ehm202B59eeUK/cp5C9TGLmMYeSQhNJ9GKWe7YZhQBD4+L5NtVtPrtaXTix4pSVVaitN2kXzCU3LA8846o1Z/TnF0m1y2fMU8pdIJMaRJS1i8AiJ3hfygKboBy6WVaNSfUil9ohmc/2Z+c886bijAfSHFEu3KYxcJZ+7gK6luhmf/uu8l8Vw3DaV6gN2S7dpNNf6sjKeZ9JqbfU5zHueRUiIrGrEMuM47RpqLBWpeoYhge88dTkmDAN2izcZHbk6sJQYBD7V2uOBGi1fNLSYRDKnksypxLMqWScgkVVpVlzaNRdJEbQqDlpc7vb/BMRSMsm8hmv51HcdZq8l8Z0Qz4leTD0uk8hpJLLRdl0rIJ5WaNdcajs2RlKmUXKQVYHZ8ggCiCVl9IRM4Id06h7TVxK4VoDnRs+l51t97+nfBzzPjHy59sagkKhs2Kgia3pUyz0FgsClVLlHs71NLhMJfGZS08iyMeA9PaATB6GH47SoVB9SKt/peuud4h0NYeWzOnPPZxhdiLPyWR2n0/uc+4GL67R63rm2WaTd6e0Nct026xvvUq09YiR3sSs1Uehml/cytYfPISAIfXzPodFcp1i+TaX68Jmowg+CaVV4tPzjqJF55Br53GI38JEj9iFHx+6QkCBS//Vtmu1tSuU7lKsPu95VvRNQ5JW22udUHxzDhj0OifgY5xe+w0j+Uo/eVBiGBIGHZVe7BI4tbKcZUdGDYCgdXUC331GO+pNkA13PkEpOkk3PdxeWvQHVHsN3rHCdVnuHzMJzICDoKiEb+QlaG/02T3vB6nbr3r5bes3a6ov91OkpYhcXUcfHSX31DeREAvN+//aCwOtqkkkDg/nQD0lfnyI2PwJ+wPaPbuFW+xd+ZtjkofUxU9oFJpXzSELBClpsuA/Y8VaOFSccBBEe00F2oohaklCTGYzCFKnF68TGZmgu3ab84Q+5+K1ptLiCa3rc+Ztn43S7B1nW+9gyvu8cqxwqSSqqGicRK5BMThIz8lEjp6RGAYNvY9l1Op0izdYmttPA86I02kmRnUuRnUsSAts3Sk+lMi2EjKIY6FqaVHKSmDGCoad7aMW+7+A4TUyrSqu9g2lV8DzrKQXcBLIe2+8nEZLoSYs+CbKsoakJEokJMtl5VMlAVWJIkkIQ+niehWVVaXV2abW2cH0L1K4glpAIe8pDAk1NICt6TwDjBy6u2yGWnyQ1fp7qyuckR+dobD2Mmiy1GGHgY7WeztzRMHK8+Nw/7Qu4AGy7wed3/oxaY/mp9oEQaIkcWiKLJCuEYYBrtbBquwyzwhYiClBcJ0DRJGIphYnFOK4dsHKjAV3FCtH1q9m7j5IkCIJITXv++RSKKlFaM6ls2gipu00rQNGjgGp0LoZj+qx83tzflpAODktI9Gzz3EtpJEmw87hDveiiqQmSYwtIskqnvEHgPStPpNMhCDxcr0MYBsRyk8hajE5lA60wTui5KIkUnbXHXT2e00EgRe+pHr2n8dgoup7eb1QOAgfXNbHsKu32Lq32Dq7XGVhylVQDI11A1qN+t8BzsOpF/COecLIa3UvPCfpa1WRJ6zIeD8bvIPCO1a8RQkZV48RjI6SSU8SMPJqa6C4gon4U22nQNks0m5vYdh3Pt06lBq/GMxiZUexmGad1OvNMWdajZykxQSIxjqFnUJU4khxlKwPfxfUtHDuSOWh3drHtxrHHKOtxspOX8VoN7FZ5f5h3PfN0QSiRFMelxT8gn7vYk5Xf0z3b2v6Q7d3PsJ1Gt/x9trKZEDKyrBIz8szNfJWxwnMDewwbrU0+u/nfoeTy2I3y/nMdn5jHruzgtp+cfjWUiPhgeQcZZjmdRhnJI8WMaFxxHNzdIn6zt11CkiLtI1kxogC/0ktbF6qMkjhYRHpNi9A/xs4CBVkoCAQBAV7oDjUWPq4p/swBj6RqxMZnScxdIj61gKzH6Wwu015/QGdzGa/dQE+pZGcS1DfaWE8x8f8H/JYhBFoyh5bKIxCEgY/vmNHA4rnImhGpGcsKhCGSouE7JpIaBSWyouE5FrJmoKXy2PUiYZdGH/pe1Izue7jtGoQhRnac+Ng8ra1HyJqBazZRjAS+YyGrGp7VIV6Ypr27im8fE9CqBgQ+RrIQ6do4HTqNfrXa0yCZmODF6/8ZxgA/snLlATdu/7OnVgdOTV1i4vlvEh+ZjpqKA5/mzmOWfvbfE3gDBt5BSmhEWR/PiQKPk0CSQdHk4cJ1AvSYjGv7R43Eh29TESiqwDEPIqIL3/3P0ZI5Hv3d/wu7fjwD6QuHkFj46n9MYnyBpZ/9f/BCG310Eq/VwNxa63NM/21CiaWYeP6bZOevo8aiyca12qy9++fU1273/2DIc/DvK0YuvMr0l3+f7Zs/Z/fWL/6+D4fkxCKXf/+/YOOjv2H7xk+HLi6eBFnSWJj/JnPTb/W1INhOk0dLP2J797Nn3lYQM/Jcu/zHZI+4ke/t99bdf0l1jx21lwkS0Xh+9LnR5f5etHxsFjewKbYPWFhSMkH8+eeQ4t2AvGPSufE5QftIQC7rFApXqddX8H27jxlsTGQQSuSWnrw4jrVTx2v0s2plFEIgOOKpJSEjo+DSPz4eF/CcqaQlxxJMfftPUBNp3FaD+p2PaW8u4bVqBO7BqsVuuuzcqZ1lF//eQgjI5iVazQD3jIvVRErge5F8+WlhxAS6IahXz/ZyKgokUhKNWv/K8DBkPcqeCVmJAqB0gc7uKonxBSRVxW03kBQt6ldyTOKjs1i1XWL5CTqlDZITC7jtOmoshWok8F0bz2xiVrYxchOEgYfXaURZKtfCbVcJfQ81nkJSFDyrgxASemYM315ByGpfiUpWjW5ZK6pRZ6avUFn+NBLoi2X3HdSfBoX8ZbQBbtBhGFAs337qYEfW44xd+ypGdpztGz+jXVxGdNkcg0xPU5MXyC++wuq7/7ovG7EfZJwQgc/xKr0h2J3TDdKBF+Kcwr377xuyEcetltAKE1g7f4+sNCFIT19i9Mqb1FZvUbr/PqHvIesxOpV+XRRZjzPz5T+gunyDxsbxzc7/AV8sEokxJkZf6At2Ir2yj9ktfv6F9FBado3d4udk0nN9wYosRVmgKo/RMgXyV19DzxTwHYvdj/6uR3VZEgqXCt/AO1LKiylpNpu9rEFj8RxBq41590G0IJqdQV+Yw7zV29wchj5B4DIychnbblAqHQTsckwldXUSJa4haQq5L89T+uX9gQFPQZkhK49xz/5Nz99TUp5Z7Qr37Q9xTtHHc6aAJwx82msPMbdXsYqb/39FXX0SFAW+/QcJ3vmZydba2RgJ+REZywqxziAJP7+ocv6Sxt/8+dn6IlRdMDap0G46eEMOX0gykqziWV3KriQRtqp4VotOeSNqCnYsZD0WBS9hQKcY6cu0d1dx2/WunYEgKG8Q+B6BY0WZIruD0yxHwVIXvm1i10tRWdGx8Mw2rtlECCnKDoUBdqNMT0FZSMRyk6jxNEZmjMBziGUnqK7cJPDdqMfnKZ9LVYkzkr88sFHQsmrUak/nCg+gxTPoqTxmdYvdO796QklFkBhdID4yfbJO1f+AJ8Iu7xDYFr799M/L00BIMvH8FEKW2b39Nu3d458t1UiRmb1GY/PBsd/7D/jiUchfQdP6F0W23WC39PmxCvlPgzAMaJslXM/sI3XslSgBlFgSq7SJ06gQuPaAsSOk1H7MVqtXSywfm+ur8gQdC212GmQZhEDJZrBXBrWriK5fWNjHglNSMRJzedRsHCWp41TaOLXBmfuknB3Y4+TjEpMSKEL94gOewLaofPZrjqtDClmQGo9FTJCkyvbtITVbAWpCw7O8yFPjKSEUCcVQcFvP9iGTJHjrWzHGJhTmzqs8uOPwO9+LU9r1eXzPYXJWYXxSYXfLI56UaDcDFEVgmgHTcyqqCuWiz6cf2Hz1O3E++8AiDOAbvxtHUaG447PyyOXLbxqMTSr84kcdbnx4kKGYPafwxjdiGHGJ4rbPH/6TJK4TUin5VMs+L3zZwLJCPDdkY8XjyvMaa0suiZTE2KSC54a889MOc+dUJmYUttc9XnpNZ3pOxXVD3v25ycuvG0xMy1QrAX/5L5YHZrCcxkFPjNuu4XWaUbnryGThmcMp8E6zV9Qu8Byc7v06+jvfMbt/PxLghQGdygaxMMCsbuPZbTLTVwgDPwqC4nna7tP5VGWz5wbK3IdhGDVCOr11cCGrKFoMSVG7qeMA37W6/U+H3hUhoRpJhKygZ0aRlIgWrCUONJg8s7kvnCgkGVmPo8bSJMbnkVQNIz16QC8NQ5yuOGHvAUkoehxJjbYfeC6e3R4YVMlaPCondqJzUoxu/wZE2Tm705fylxQdWY8hdcXMQt/Dd+3ouAekD4UQyHq0HyEkAt/Ds9pHerYOH1MMWYtFpAXfx3M60YA9BHvXSe5mHsMgIPCcgc/nHgI7usZuvYKkGqjJJIHn4HaanJmeLCRkzUBWdYQkd5voXTyr0+drJmsxZFVH0gzUeAbCEEWPoacjS4LAcyKNqe61l7U4sqqRmroQPRPxNHpmbP96e3Z7YNlX6qp4C1mOnkvH3H+3eg9dQY2n8B0L3zGP3AMPz27305olCVlPHFz3MCDwIv2owQF8iCSryEYi6lnbP57IWb3vmGQFRU9E71UYDn0e+66rZhy6/l5kQXPM83PohNDiGYQk43bqBMdITgihkEpNDRTYbLa3sO0vlqro+07UC3aUxSrY19PxbRNXkjFiSWK5MTq7vQFKEPrsHipb7aFh92ug2csrBKaJnE5BGGLdL+IW+/skhRAEoY9tN/qUlu3dBhv/9hOEJPWYhg5C1LPT/+5GzhXSqZm4Z2ZpSbpBfGoBNZHuixidWgm7uMT5tyawGi56UmHnTnV/DJQ0mfS5PE7Txm3apBdHaDwsRb4ahSR2pY2kKSgxFaduoWUMwiDEKrVJTKdxahad3dY+jS02lkTPxWit1zEKcSRVxluqkJzNghBY5Q6JyRR23Yq0N5I6VqmFpMioaYPWWg3fPL40kRuRGZ1Q+OAdk2RGIp6Q0A3B2z/pUBiTyeVlfvGjDr/7DxPkCzKP7zssXNBo1ANCP+TnP+zw1e/EEcJmd8tD0yU0PUCPCX7+tx2+/rtxPDdE0wW1SkB59+AmKwqcu6iy9MBFkgX5gszkjMJf/GmTVjPgrW/GuXPDRpYF/8l/nuZnf9NmdCI63tKOx6O7DkLA5ed07n5uM3teRVEhk5O5f9tB0wXXXtQZm4yCnZ1N78StDJ7198fACTyHdnE1mlhkhcbmPQSgJ0ZwnU402J0Rsqwzkrs40APKdTtUqg96mk61ZI6Ri6+RmlxETxeQZBXfNmmXVijee5/W9qP9SUlLZJl784/RUyMoRgK5O9ld+cP/xf721t7/t1QefgSEJEbnmXzpO+iZUbR4BhBc+v5/wd7k4DsWD374/8A+FIxKikZ2/jr58y8Ty08iZAWnWaG2cpPygw/2hRoBEIKRi19m5OKrrPzqz4gXZhm58Ap6ukAYBDS3HrD+wb/rCUaNzBiFy6+TmrqIFo80MTyzRbu0SvH223TKG0duVkBybIHU9CUSo/PIiobTrlFd+pTivfd6J2khkZw4T+HiqyTGFlC0GK7VorFxj/KDDzAHlHjUeJr8+S+RnrmKkRnbz0LajRJbN35Ca/tx328OQzESTDz/LbLzz1O8+2t277x9pgZmhETu3Ivk5p8nlp9CMRKEvofdLFPtXvvD5zp69S1yCy+gxlJRGVlInPvGf7rfaNvcesTqr/8VntVCUjSmXv4eyYnz6Mk8QpKZevn3mHzpu/vb27n5s6gf5RBi+SkKl14jNXUJ1UjiuxatnceU7r1Pa3e5Jzg1MgXm3vwTqss3aO0sM3r1TVIT55FUHa/TYP3DH9BYv8vesycpGrlzL5E//yWM7DiSouK7NnajRHXpE8oPP+4LaBU9wdj1b5BbeAEtkcV3bdq7y+zc/hWd4hqHgx41kWHk4mtkZ6+hJfOEgY9Z2aTy6CNqq58PCL4UUpOL5M9/icToPIqRIAh83E6d2vJNdu+8fXzQIyTS05eZfuX7OJ0667/5q2P7zjQ1MVQyw7LruM+grH4cIh7dgEk/DPH3xAdru9i1IlZ5KxIhbPYnH/YEIXPGNHV7myD00eVERDIJDp2DLCOnkoSuh726hmQYKLks7k7vNQoCj0ZjPVrkDNJR6nptxWfzaKMpGrc2COz+980Mmowpc2gitp/JEQjSch4I8U9sTh3hjMKDKiMvvkn60pcQRD09bruOmsji2yalD3+KufmInbs17JaLokk9Cz4tbZB/foLiRxt4bYdYIUFno056cWRfoTl3LXK1lQ2Fzk4LSZYwRuKkFnLsfnAQoQpZkL08ilAk2lsNZE3BGInT2Woy8tIUxQ/WyF0bIz6RQpIlfMejs9UkNT+Db0daOe2NJ0fhQRgiBCiq2O8VbDUCzE6I64ZRPVMXBEH0dyMm4dghqgqlSkCnHQ1gSrep04hF/27Uu5+F4LogyYIbH1qUiwcRR0i0mNnbN4S4TkijFhD4Ib4fomoCSYL1FZeFCyrLD12uvqDj2CHNRoCuCzI5gaoJNE2gGxK2FdJqBiSRCBLRDdpY8Vh+6OD/+6cbNxDJ0XlSk4sEQUDgWlSXP8NsbIOQ8JyTS44fRTw2wkju4sDsTtvcpVbvLTkoRpLk2EI0sS3fIPRcYiPT3UE9x/Lbf4Zdj7QvPLvN7q1fIWQZPV1g/Lmv47RqbN88mKjM8ib7WkStCrt33kHR44w993UULcbab/5qP1sQBn6veqoQFC59hfHr38Cs7bBz65eEnkty/Bzjz38TNZ5h48MfHGqIFghJQUtkKVx+HSMzRmt3hdrKTZRYGqAnGyDrcSa/9F2SE4tUH3+KWd1GUlSMzBh6ujAw0FTiKcae+xqd8gbbN/4OWdXJzj/P+PPfxHdtinffjR5yIUhNXWD2tT8iDAMqDz7EMesY6QLZ+ReI5SZZf//fYlYPdD8UI8HUy98nO38ds7JF+cFv8B0TJZYmlps4JnAJ938/8cK3yc4/T+n++/v9M2eBEIJEYRZZi1F59DFOp4aiJ8gtPM/ki98h8BxKd9/d/35j/Q5mZRMhKxQuvkZ6+hIbH//NPovJM1vdzEd0n2srN2ls3icze43CxVcp3v01rZ2DZ9E6MjnH8lPMfuWPUONpaiu3sJsltESO3MILxLKTrL73b2jvLh86gSg7lZ6+RHLiPIHnUrz7LkJWiGXH8ewWhwOSzNxzTH7pd7FqO+zc/Cm+56LF01GwoSe7XMFDm5dlcudewDWbVJc/w7PaJEbnyJ17CcVIsPSLfxaV0omes+mXv0965ir1tduU7kUO3ZnpK0x/+Q+Q9QTFu+/sB2xCksktPM/UK9+Pru3GfexGCaEoxDLjUXbrmPsqJJn09BWmXvk+bqfG5od/vf/ODoOiaENFYgPf+cL0z/agqvGBitNhGOB1Xcq19AiyZmAW1zHy41G2sT1YSmAseZF6N7OT1EYIAdM7mB+NxXMomQyh7yNnMwStFkJV+wIeSVJIJsep1ZZxBmTiYrN51EwMYyKNkjSwtmpYW/3zcMnbZEyZ5znjTep+EQ+PuJQiK4+y467ghKezDzpb07JukJi9SPmjn+M7FunF5ym+/yOUZJqRl76G26yBAM/2UWMK8azGYVMp33Kxyh0yF0aofO6iJjW0bIwwCDF3W3imiyRL2DUL2fYwd5poaYPQD7BrJunzI3S2mgSODyG01msUvjRNfDyFpMro+TiKoeC1HdobDZJzOUI/pFNsIsdUmksV4lNp6g9KjHxpCiMfp9XurtYF5OeTJAsGW7equN0+m1olYGPV49qLOs16QLXsI3fH9d1tn91Nj1ffMnh8z6HTCcmPSGyteyiqwDIjb6rNVY9EUlAYk0mmorLXzoaH64RsbUSfEcKFKxqxuMSvfxY9sL4Hj+67fOVrMRw7ZGvdw7EjNo7jwL1bDl9+w8C2Qv7yX7R45U2DB7cdAh+q5cgby1IFquZz/qJKLC5YWFSplKLPPC8kX5DwXBifkpk9l+Df/mkTx+5PL2em4mSn4+zcq/97wbzT0wUaWw+xGsVoVeOYUbr7KbDn8q0PYGaFoU+pfBfX6y0HmJUtln75zyPTTt+JWp+WPkUIidy5lzDSY/uDZ+DaNDaienm8MMvopddxzTr11cG2Am67Rr1dQ41nyC++ghAS9fXb+6rmRxHLTjBy8VXM6jZr7/8FTqtKGIbUVm8xDWTnr1Nfv9NdqR9A1mLEchOsvfcXWPXdiFknRbX6wxOFrGgkRhdoF1fZ+fznUb8VAiErUe/XgFKJoieoLn3K5ic/wrdNhBC0i6uc+8Y/JT11ierSp3hWG0WLM3b1q0iKxso7/5LWzhJh4CNJCmZlm5mv/ENGLr7K5sd/G1HchSA7d53M7DXqa7fZ/OSHUTkqDBCSjOhmegbcyMgw1Ugy8eK3ycxeo3j31xTv/vpkZY8hCAOfrc9+AggCz+6yE2Ws6jZzb/0J6anLPQFPp7wB5Q2ErJKavEAYhrS2HmJW+9mFYeDT3Io0T/RknjAM6ZTWhz43kqKRX3wFIzvO2nt/QX3tFoEf3VOzusXcm3/MyIVXMKtbPecshEyiMMfWpz+m8vjj6PoJ0RX07K1zJwqR11zxzjs0Nu525Q/kiG3o+33lICFFJazNj/6WdmmVMAior95GUjRSE4vE89M0NiMKc3buOunpy5QffsDOzZ/hdZ+b+tpdZl//RxQuf4XWzuP9jJ8azzD23NchhLX3/4Lm9qN9Vmgk9xAOLG2GQYCQoszO1Mvfw21X2fjwrwfegwFXmWFChZG6v/SFBT2RpcQ08gArkEhRu4qsx0hMnkdNpJH1OInJc3gPPxka8IRhQExJ4/gdNDneQ0kHEIqCs7mJs7GFfuE8sSuXcVb7e3jCMECWNUZHr2HbDarV3pJZ6AckFgpYWzUCyxtoQApghx0e2h8zo10mp4wjkPBDjy3vETssEQj/VJXns5W0hAwhWOXtfWqyb5s49TKx8XkSsxdwio+Ze3WUdslCMeQe7Y4Q6Gw38S2PwA1ortXwTBenbuGZLl7HofTZFpIq4ZseTtPCrphIqoxve7gth/BQCiJwfGr3itjVTlSiWq8TeAHV21HUWfl8m9R8DqduRY6+LYfK59vR7+4WsWsHA7SiSbz5P7rEhW9M8C/+Z++wfScK1MIA3vtF70C+x40IfHj/V0+ONH/1k2gifni3f6J6++86vPXNGK1mFIC4RwwBN1c9/s0/G9wXs7HisbFyUFraWG0N3M/yw+i/f/Gj/gkpDCBfkLGtiAQ4DF/6j87x0j+e59/9bz/m4S+ejvL9LBD4HtnZa9jNMr5rU1u7debV+R6SiUnGCs8NWLWFmFZloFFoGHhRyadL/xRSRP80q9uMXJCR1dP7E50VifEF1ESGyuOPcdq1rnhZ13ajuEJm5gqJ0fm+gEcIQW31Fp3Kxv6qedAEEfgedqNIPD9Ndv4Fass3cK0WoecM1dkJPIfq0meR1hLR5juldTyrFQlGKhrQRkvmSIzOU1+/Tae0tn8vA9+lsfkAq7pNZvYqu7d+ieM5yKpBauoCYehTvPtuT39YGPgw5HjC0EdIEhMvfIvcwgvsfP5zSvfe6yuRnAVRyUpE4nhCBsG+35tixH9rdHJZi5GZuYLVKNIurnSDEQkI6ZTXcc0mybFzyKreG+SJKFNUW721n20B8Ae8V3ajhCTJ5M69hGu2MCubhL6P7w9ZdIQBrd3lbiktGmdcs0GntE566iJqPMooSooWZW59j9ryzf3jCEOwG0Xq63eYfOm7JMfP7Qc88cI0RmaM4r13aW497HkWBx37wSF5pKeiMpbdKLP+wb/Dbhyf2dnfbjA8i2PoWRTFOLFo7WkRM/KMFq4OzC55rkmnU0TIMpKqIWk6ajKNWVrHbQ2vaJQ7K8xnXwFCbL/T19tjr65FiwXXxbr3AHyfYIDTdBj4dDpFYrGRgTpI5loFJaHTflxEScdwhzQtAzSDKnes91CFjoSCF9qEss/4pRSpkSQ7D1s0dq0TqQqcLeAJfELfRTbieO0GcjyBlhvDLm9HF1fV8ZyAtY9KhEFI4AU9B+O1HGp3DlJgVqn/gWguDXZrbh9pDYhKUg3aG43utg4unFPvNiQ2bSqf907OzcfR9tvrvTc/8EO279RQDJnOKXy/nha+Bx+8Y5FMSwQBNGq/XcbI6mOXRi1AksDsBAOzOwDFBw1WflOiuXM6Se8vCu3SCoHvIoTAtVpPPZGoaoLZ6TcxBpi47pmwDjJglRSN+MgMqamLxHIT3cZcGTWR7lL7n+qwTgwhSWiJbJQpee7rjFx4tedzWY+aZBVjSN9BbeeJ19CzO2zf+CkTL3yb8evfoHDpKzQ27lFbvYVZ3RyYIfHMVs/kCezrOglZZu8CackckqzgNMr76rB7CHwXq1kmNjKFbCSgXUNSNbREDt+xomM/ISRJpXD5DXILL9DcfEDl0SfPJNiBKOuYmrxAYnQ+uv+SgqxqGJlROuWna6Q/DRQjjmIk0ZI5Ln7vf0p4SE1aSHLUP+OYA0uQbqdxov686vIN9HSBzOw1zv3Of4pZ3qC28jmtnSWcTq3vWQp8LwpKj8xOge9F+ilStNKXNQM1lsJ3rYEihXajDGGIlsghpEhNXE+NgJAwq9unEriM5ScpXP4KshaneOcvTxzsQGRP4bqdgX5/6fQMyfgY1SPl72cBTU0yN/M14rHRgZ/XGiu4XofA8aje+whJlvuJHwNQMddouxUkIeP6Fm7Qu5D3q7WD/wiCPqf0PUiySjo9h+/b3bG09xoEro/fcTCms1ibdQL3yfOdG9rQ1d0RIbimTzyrce7LeTbvNth91HpitudsLC3XxtxdR9FjWDtreK06E1//Q9xaGX1sivJHv0CSBSMLKQI/xG67lJeaZyY9/DYReCEf/uljPvzT45scvwiYnRDzlLonzwq+T0/f0DDc+sEat37wbFWznwphiBbPRKtU7+wKphApRM9MfqWrXnpUUyOk1d5ht/h5n0GikBVGLr7KxIvfwe00aG09xOnU8F2b5Ni5HvbVFw/RnQA82rsrPY3MewgJ92UE+j47SXYsDGh2yy7p6cukpy+Tv/AKI5depfzgQ3Zu/BTviDJwEHhDBMF6/7Y3+UarwqPf3ytJiP37I5C6TJzgVLRyLZklNbGI06yQnDhPevoylcefnFl8bg+x3CQzr/8jYtkJGhv3aG09wrNNZM2gcPn1p9r2aSGkyB7CblZobj0YeG991x5Y8gsDvydAGgbParHx4V9TXb5BdvYa6ZnLzL31J3RKa2x+8sOov+jwfe8ypvqx9x2xd/CRHETIwAzB3r0WXXp09JOIBn1aeYHs7HNY9SKKFid/8VU61c0TBQcQWYw029tkM+f6mFq6lmJm+g06Zqlrs/BsEI8VODf/TUZH+scpAM+zuxph0XUWkiA1dwU1mSHwXGr3Px56fiFBXxnrWAxZHIVhQLO5jqLEBlL2EwsFsi/PISSBPdui/tk65sbJ1beFJEDA3V/uYjc94vmTedmdMeBxKH/yNoQBvm1S/M3fkb36ZdRUltIHP6P5+BaSBLImIQFqXD7CyhWkJ2N4lo9Zd4hlNPREpKhoN13MujNw3FFjMkZaQzVkhADfC7EaTl8viaLLpMcNWmUb3wmI5zXUmAJBiN326NScPhlrNSaTGosh5OjlCYOQ+mYH3zn+pdcSCrGMhqxFL6fvBtgtF7vlnnnsTE9E/Uztio2eVDHSkdO70/HoVOyBSrqKLmGkNbSYjJAFgRdit/qvpaQIMlNxzLqD0/aIZ3W0RPQYOB2PTtUmOCIcJ6sS6YkYktqtswYhjR1zv79pGNSYTCyjoejRSxl4AXbbw266J1YDfhKSY+ewGiWcVpnc/PO0iyv4weka2YSQMfQM05OvMTnxMrLczyrwfIvNnY+6xqa9UGNpxq6+hWc2Wf31v4rS+t1BV1Z0OP+ls53cQHQbNBEDQ7swCPDMFoHn0tx8QPHee4O38Qwuv2e1qDz6iPrabYzMGGPPfY2RC1/GaVUp3nn7TNt0O/V9aYGo3+PgGROSghbPEHjOfp9WRPduY2THUeOZE6/OXbPF5kd/g92qMPuVf8jEC9/Cs1pR/8hZs4RCkF98mXhuku0bf0fp/vv7wYSRHSf/BTwHx8GzTXzPwe3U2bnxsygDOmg7T5kVDQOf9u4yndI6pfvvk565wsQL32Lyxe92m5BPz+QMXAvXbqMmsiixVN82tHgmIiaYzX2X+z3moZbI7md9ToLq8g12bv6M/IVXGL38BuPXf4ftGz89VtX9MMqVe0yOvTRwYh/JX+Li4j9gdf1t2u2dM2vyyLKOrqXI5xaZHH+FZGJiYLAThj7F8i3qjYNFqZ4pRPIRikYYBMha7MQB3dNA09LEYyMDLVSELGHvNolNZZFU+UTB9WHIqoRmyMRSKrnpOFt3Tubndnbz0EPpabdZpfjB30XBeRACIaEkqK62OP+1SbZu9panjJTKH/2fvszOvTrrn5Z54Y/mGbsUaVBs3Kzy8b9cYundnZ6JunA+xYv/eIG5l0fITMeRVQmz7rL+SZkP//kjtm4d0N7HL2f4R//nV3nvv3uAEHD9H8ySm0sSeCE7d2t89GePefzObo97+/iVLL/7X79AatRAjSm4lsc//5+8TfHh4GhXkgWT13M8/4dzzL48Qmo0ClI6VZvlD4r88v92B7N6tof7u//VCwRewJ0fbXDt+7PMvJBHUgSlx00+/pdL3PnxRk/AlhqP8aU/XmD+tVHy80kUXcJueWzdqvLZny/z6J2Da5meiPMf/7dvcusHa9S3TZ7/wzlGF1NIsqD4sMkn/3qJez/ZxLUOBov0ZIw/+N+9TH4hiRaT8d2Av/ivP2Tp3cF0TSFBYTHN8384x8Jro2SnI2p3p+aw+XmVX/3f71BdfTZ17SDwUWNJCKOV/1GRqkR8DF3P4LqdqN4e+FH/hpCRZa3rfzTF6MhVkonJgSKDYRhSqTxgd/cmgyYaWdNRjCTNrYfYzfL+QCspGonRuaeix/ceSLDfSCyrxpC0fUi7vI7v2qSmLu4zYXrxtPW1Xu6N75i0iyuU7mskxhaI5cbPvGW7UcJq7JIcP4+WyPSwjozMKPGRGdrF1f2Ax3dM2qU1EmPzUS/OrV+cKEsV+C52s0ynvM7Ghz9g7o0/ZupL3+v2oWw88feDICQZNZ4m8F065Y2DzIkQGJkxtEQW8xRlt+OPPzpHWYuo7INWV77dob2zFJVZ8xO4G/f7vvP0ApYHz0IYRPT7yuNPSE6cJzW+2CMwehr4jkWnuEZqYpHUxCJ2bWc/0yOpBsnJRQLP6cofRPvvlNfx7Q6Z2WvUVj4/cfDrtGvYrSq7t99GNVIULn0Ft9OgePvtE3mFNVublCr3mBx/ua+sJQmFscI10qlpiqU71BrLdDpFHKeJ6w3RHRISimygqgl0PUXMyJNKTpPLniNm5KMxaiATPcpCr67/ep+htfd3p1mNGHi6sV82/CIRBB71+gqt1ha53GLf5+ZGlfjCCEpSp7NaxhlgHHrs9r0APSGTHjNolk5OMjhzwCMkGWN8hsTUObxOm8bDzwg8FzWdxbc6SMIjNRHn4S82cVpHauMiitAWvzrO+OUMy78p8vlfr5GdjvPc78/yzf/lc9gtl43PDgKlRMFg9EKazZtVPv3zZXwvZOq5LFd+d5p4VuMH/4dPaGx3efoSKIbMy//kHK7p8+jtbeqbS4ycS3H992f51v/qOrWN31B8cBAVFh/U+dv/46cYGY3X/uki0y/kjx0MZl8e4Xv/zUvoCYWl93b57MEKQgjyc4mIYt45e+OsrEpMXc+RmYyz9mmFBz/fIjGi89z3Z/jG//wadtvj0dvb+++KkVKZvJ6jstLi1t+s4Zo+YxfTXPu9GdLjMRrbJrvdcxUiyrxd+/4MTsdn9cMiN/9yhdRYjOf/cI5v/pfXae6arHxQ2t9+c8fkJ/+Xm+hJhZf++BwXvjYepRSHYOxihu/+Vy9QOJ9i9cMSt/92ncAPyU7H0VMqzlNcm6Nobj8kNX4eLZGjvnGvLwgYHbnKzNTreL4TuROHfrfeLiFJCpqaQFXjAwMd6A4irS1WN94Zakzr2R2cdpV4YZb01CXau8soRpLc+Ze6qsjP5lx9x8Kql0iMzjN69S1qKzcIgwBJ1eiUN/f1TtpdSnnu/JeYee2PqK1+jtuJrECMdAEtmWf39i97qeynQCw/wcjil2mX17EbJQLPQY2nGbnwKpIkn5DdMhie3aZ49z2mX/k+Uy//HqX77+N2GujpAqNX3yIMvEjLpssECwOf2vJnZKYvM3r1TWQ9HjWsuhaKkSSWn6K5eb+Hun0Urd1ltj79MdOv/gOmXv5exGxrDu4hPA6h72M3SmRmr5FdiKjXoe+RGJtn5OKrzy7wBax6kcBzyJ9/CadVxWlXkVUd12zu97z4rkXpwQfERqaZeuX3MTLjkU1FGKDGM8QLM7R2lqiv3TlTKU9SdUYvvx6RUMrreGYbSVFIjp0jUZjFrGw+lVlsdfkz0jOXGbv2FhDS2lna15dKT12ivna7577a9SLlRx8xeuUtZr/yR1SXPsVuVpAUBT1VACGoPPxoX9DzKHy7w/bNn6HEUoxd/Spup051+eYTr43nWWxs/YZkYoJUcqrPvRwEMSPH7PQbTI5/Cdup47odPM+KhAMDD4jGJFnWon8kDUUxUJU4qhYfrGVzCGEYYFoVHq/8Ha32gWQDQsKuFXGbVdx2HS2ZO5Fx6NNCCJlMehZNT+N5JrJsdA1ZQ2LTOZSUjrVRwym18E2H06acfS+ksmaSmQypbX3BSstIEqnF5yi8/DsIRcFt1mku30H4PoVXvklna5n20qcAaHFlaFkoWTB49/95n5v/bhXfDZBVieauybf+y+tc+c4Uu/fr+2WTjU/L/OX/+gNcy8fvOgTf/dEGRlpj8avjpCdi+wEPRHOMkVb5xX97m8fv7OC7IVpcxjV93vwfX2L2pZGegMdueWx+XkXRJK5+d/r4i6ZLvPqfLhLPafz0/3qLez+NMiKCKFiJKPlP1wuQGDH45H9Y5oN//gin4yHJgt37df7gf/8y1/9gls2bFcxuU3V5uclf/Tcf4jkBnu1Hmj26BELw4h/NMXohvR/wHGxf54N/fpubf7mKZwdIiqBVtvj9/82XmHulwPonlf0MmGcHbHc90RZeHzvWnE1SBS/9yQKji2ne/38/4NM/X8ZueZHnlSIhyQK7/ewCHklSaO0soSVzDHppJElF01LoZ1zJWnaN5bVf0GgObzb1zBa7t37F+PXfYeYrfwSBj+/aWLUdtm/+nJlX/8GZ9n0Uge9SefQRsewYhUuvUbj0GmHgY7eqLP38v99XSQ59l53Pf07guWRmr5KaWIw0SMIg6r+rbD1dGUNIxEfnyC68gJDlA4NZ16L86COq3Xf/LAiDgNryDWRVJ7/4CnNv/Uf7SstOu8bmpz/uKzuZ1R3WP/xrxq9/g9z8dUYWX96n0kfZp8H9Sgc7Damv30GNpxh/4VtMPP9NNj76mxOXNA5tiMrjT4nlp8jOXSc7dz0quZlNaiuf41kd1Hjq9BdlAMzKJqV775E79yILX/tPuurGDts3fkr5wW/2z6u1/YiND/+a0StvMnbta/sq4Huq20+8NseebogSS5Gdew5J0boU7EhV2qrvsn3j5329XKeB06qy8eEPmHzh24xd+xoTL3wbCPEdi9rq5+zc/HlPQBV4Dru334YwJDN7jalXfj96dsKAwHVorN954uLDaVXY+vRHzL3xj5l86XdxzeYTRSsBGs0NllZ/xuLCd0kmBmc4hRCoaqzrZE93HO1mx9g7NNH9v5OPV0Ho02xusLz6c8rVhz2fxcdmcdsNCAPM3XXM4sZT96mdBEJI6HoGSVbRtRRhGFCtPsb3bWJTWVJXJlAzBtZOE2M8jb3bxLJOvgBTdYnp5zN4doAWkznpU3ZGHZ4YmSsv03h0E7fVIHv1lYhpGfj4ZgujMEnz4Sc0Ntu4po+WHLybTsVm5cPSfnDg2QGP39nltX9qMfPSCHpK3Q94PCfAcx0kRSApUpfZGVJ63OTq96ZRjf59lJdaPHp7Zz/g2ivzBH5IarxfrOmkyC+kGL+cZfWDEg9+sYXdPMhgHS6TPQ3spsvyB0XsbnbMD0JWflOiutpm8lqWZMHYD3gCL6RT7V4bWSCU6GWpLDURkkBL9q8OGtsm93+2tX99fSdk62YVz/GjXqZjMjjHITMRZ+p6nvJyk89/sEbnUFnvJJ34p0VqYhHXbJAYXUBIMnarSjBkBXdyhBH91WmwtPIziuXbHEfVDwOfyuNP6FS2MLJjSJKMZ7WjFLtrE3g2ndL6wN86zQobH/9N137iyeiU1lj59b8inp9G1gxC38c1G30Ti9tpsPXpj6guf4aRHo2c7H0P12ph1XZwD9fww4DG+h2W7XafcN3R8hWAVd1h9d1/jZ4aObCJ8FycVoVOZatXWTcM2b31y4i5afYOaGHgR6rAQuopuwWeQ/Hur2luPcTI/n/Z+88gy5Iszw/7uV/19HuhIzIjUuss2dVVPd090zPdM8udndmF0XYXuzDsLpTBaBAfYCBAfiBopBmMIGHGDyQIgjBgiTUCWGCB2VkxWDHTo3palhZZqWVERkSGflpc6e78cF+8iMiQmZVVXT3T/7bsqIj37r1+/fp1P37O//zPBJbtoqIAv75C2K7uag+kC3tQXyE7nNZXE0KikoioU9+ZvWUMG/ffpblwi7BT23HNjfsfEHbqSMve1+N3GMLWOgtv/yNyozPYXq6/+K8TNJbJjkxje/k9jc2xcwUmL23w6Ee/TXSEHbiKfJav/SHNxTspZ0WINAxU3TnOjFY052/S21ggOzSFnSmkEgWRT9Su9fWrtsZ21G30jb0u0jac/uYxerWQpWu7uWs6iVi98X1ai3ews8VBmYgk6ODXl3d5EDtrsyy+90/o1XdvHtrLD1Jl8urOhIjexgKPf/z3yY4cx8mVMFoRdWr4teU9vUeJ32b5kz8YZI9ZtovRiiTo4jdWdxC0g+Yacz/6LXobCzv6wK8tMf/OPyI3Mr2jGPbBMGxU76BVzOmT36ZUnEYIa8+U8U1sen/g+ZzAxmjiuMfq+g2WVt6n093tWc1NnUrvwRi6Tx4AItXl+ozSHYdBCEGiQtqNR5RKM2xsbBUXrb0/iwoirLxH46N5xn/tCuyjw7MfjO7r/GWs1MlwRDyf0rJlY7kZugsPkE/pi6goxM0WyJRcKjMFVm7WyQ1n9po36dbDHVwRgDhQtNcDhk8UsLfdiFewOf7qCKfeGmPkdAEna6cE3IlsOnCeumdjoLW8m3SsEo1ONPIZO3g7ypNZ7IxFbaGL3/x8Utf9Vkoq3g6VaFqrPuMXyzjZLfe4k7GYvFLh9C+MM3a+hFdwkJagMJrByaYE76f7v73q7wq7aWVIIo20944RHwX5EY9MyWHlVpf26mc1PI4CQ3ZoCr+xQqa0u+7V80BrRav9hMeLP6JWu3ekOH4qef9kT/5HffbavsclYZfG3KfP1L6oXTtSyGVThj/22wNCr+3lUEmYLh5GpWnhUhJ2akS9Jl5phCTspRwRo8mOHCMJeyR+B7dQIWxVcYtDRO0qca814BRJ28FycwjxNJna7F/N22iaC7f2+cwQNFafKdU8CbsDYb4DemXfHbuOg31F/J4Fsd+iubD7PPtlxgEUJzNUjrWp3v/4yNfRcZiWLDlKm3qtI4UwVdgbjEc7YzF5eYjGYmdPgwdSA6N9QN287QhbG3tmDQIHPusk7NJe2oN/tA82x/1eJUh2nNdvU7337p6f+dUn+E+XRzn8ytQaD+kFVY5NfpXx0StkvKF9lZifF0pFBGGTZmuelbVrtNqL/XDRbvSWZymffRXLzSLddJPfuPcRyXOGs4/exphud4V8foxOZ3nX52G1y/jL0xROjwIC1Xu2dVQlmuZyQLbiEj4DReL5Qlp98qT0MoN6VpAaQl5ljLjbSi0vV1KZzlN/vE9K+j5/M4lBSjHg0Lg5izf/xjne+JfOUHvc5vH7G3TWA2JfceabE5SP76UpYoj3Cytt+Q+fC9JJPUwqfjaVx2eCGfzfDmilEVIMXiDLkVz9zRl+6d++TLcaMPv2Gq2V1Jg59vIQL0+c3PP0Saj3jmqYz0Y5kbZESNHXXvr8dQg6a3PkRqZprzwkCToHFvo7DForur1V1jdus7J2DT/Ye5L/WYN0XLziMJbrYbTGGI2dKYAxSNvBLQyj4rTulFccRdoe3bXHGKVxsiXsTJ7EzWJni0SdOm5hCKNVv3aSSxKkBStzYzNgFEFj/9pDP8fP8acbhiCo82juD1ldu8bI8AUq5dOUisdxncJzGz6JivD9Kp3uCq3WAvU++fmwzVhvdZ6420I6LmH9i3wvDd3uGt3u3tcMlho8+UcfYRcyxE0fHT2bx8nxLMbOFBiaziIltNeORlx+LoNHhQHd+QdpGYlmDSuTp3j2ZbIT07iVUeo33yFuhDz8/jLGQGlqdwFGgGzFxXZ3elosV5Ib8ejVw0F4qHw8zxt//TTrD1t89z/5hPp8d5DWPDSzt4Da54leLW1bcTyLk7UOTc9+HmSKTppKvw1Spl6boBURh+k1sxWXN/76acJ2zHf/k2ss36oP0sotT/LSc6R/fxYzJWhFxH5Cbij19Hze5Se0imk+uYNRCd31x7s+X12/jtYJrlsklxvBsXNIaaf/hEUYtUiSED+oUms8IgpbBGGLOOnhOgWUjlKCs7BIVIgQFrKfLr35mTFmoLYqhIVjZ1E6QvaJhlonaekFIUlUgG15gEDpCNvKYIxG6Rjb8lAq6uunSJIkwBrI0+v+9aw+8frooVOTJASN1bRQqZNmlA2yvdwshrSGleV4/QrXcVpGQMUkYQcV+umxXloB3KikXwk85YkJy0JISdxrpVooX5CS8BeBC796HK0Nq7frfPVvXeDRD5epz3e49Odn+OC/v8c3/+2rrN5pcPy1EXSi+fQfzNJY7DB5dZgLv3ocr+hQfdTm9u/N06uGZMouF//cNBOXKwgpmH9vjbt/0Pck9DdiUy8Pc/7bx7j227M0n+zNTnjrX7vA/T9ZIj+c4cKvTfPh373H8JkSXt5m/X6TK79xkuZyl8krQ1Qftfj0H82hY82FXzvO9Btj6Fgz/8E6j364jIo1QycKXPmNExQnc0SdmFv/fJ6Nh1teADtjcenPT+NkbT79h7OHynX8HIZub41ub53l1Y9x3QJZb4h8boxMZgjPLWI7WSzpDsKnxmi0TlA6JIkDorhLEDYJgjp+UCdJeinZeR9vziZK42cwxtBenwNMqqz8OQufutkypfGz1BZvoPdIQ98Lyo8PLdq9H+JIU1vs4eYsWmvhkaec5zJ4TBJTv/kuxmiKpy9juR7Dr36DqLbG+rt/QNRYoTieZeqlIVSsKU3lWL21W1SoMJph/EKJ+sLWSz1xsUx5Kse97y0PQjqZokO27FKbbdNa8QfGjpe3OfbSFynqlmL9QYvWqs+JN0aZvFxh4ePqC/f0ZCsuk5fKLN+oD+535HSR4ZMFNh626dXSQe/mbXJDHqt3mtQXuwNjx8laHHtpGMv7/FMQt6Ox2KP2uMOxl4Y49bUx7v7x8i7NoxeJ0vFLdNfn901BtS0XrWN6vTWCsDEouJkkAbadodNdIZcdxQ/qxEmPUnGaQn6SMGqRzY6gkgiDHhg4kHqClIrQOkFKmyBs9NWXBZXSCQqFqf5nDkYrtEkwRmFJl1ZniWJhim53FW0UpeIMWkXESY+MV0GpCNMXT4sTH8tySRIfbTRKhTh2jk53hSg+uo5G3GsOCM3Qz7Acmky5FrWlp8buzmeVVq9OwxGszadcIK0ImhtpNpbZ+7gXCcfJp9XnkxDb9gjD1jMZfJ8FSawZO1si7iUUxjJMXB5KPaz9fxOXK+hE88lvPUxlKWoh+bEsr/7VMzz43hLr95u8/i+d5fJfOMFHf+8B579zjBNvjvHe/+8uYTvGmJSovSmHM3llmKt/6SS3/uk8raX9qZhCCIZPFqlMFyiMegydKjJyukhjoYuTtTn3K1O8/bfv8O7fScuHqFAx/ZVRZt4Y44P/4T6Zkssb//I5uhsBtbk2X/vXL1Kba/OT/+oWtmsRtNKxboxBWIJLvz7D2PkyH/x3976Uxo4QEjdXIew1npuUK20X280T9Y4ugHc4DHHcJY67dLurbNTusMXbEfuml28//qhwc0Pkh46Rq0zRayzjZkvkh9IEnE5tAWnZZMuTCGkRtNYJOhsUhmdwMiWM0bTWHuBmy2RL40R+i25tgWx5EstOldnba49Iop1EfsvJUBw9hZMt4WQKWI5HcewUlu3ht9aI/BaF4Wmk7ZFEPdrrs2TLE2Tyw0jHo7PxGK0i8sMzGK3pVB9j2R5eYQTL9gi7NfzW7lCn5QgsV7L+qEthxEUrQ22xd2h3fQYdnh7VT35I6/6nWJlsSlbrtlBB2iHt1R62JwnaMa2lvbMdtDK8+TfOYTkW1bk2leN53vpb54i6Sd/g6afZ1kJaKz4zXxnl1NfGWL/fojCW4cpfmKEy/dk9PEKCV3CwXImTsQe8l/yIh9/IoJUh7iUDvlHQivnkH8zxq//bl/jOv/8SN393gY0HbYQlKE1mKYxm+PgfzA2MkudBEmle+V+fRCvD8s0GuWGXr/y1M9iexd0/WqLbP3fQimg86TF5uczZX5xg/sMNsmWXS792jGMvVT67YS9SwzKthybw8mk8OjfkUhjLYLQh9tUg1TzqJXz6O4+ZuFjmW//OZYZPFli+kWokFcezVKZz3Pzni9Qevxjhq8TvpNWpbRetE4LmThKm51WIog4GgwOEUYdCbhxjNEHYROkYpSMazTlct4Dj5Gi1n+C5RaKoX6pCQLO9yPjIVfygRru7jEpCJideI4o6tDspV2AzMyEK2wPhM6VjcpkRorhLGKULtVIRjdZjcrkxHDtLs7dGJjOUXk8ItFF0u6uMjVyh21uj3V3GGMPk+Gv4QY1E7eZGuSLLKecqBZEWPO2ZNveiD9HsVSxREdRXnlmRFkxKwF5feCaDoyxHOeu8euB3IhPwML6Gb3aPC4MhkxnCtj3iqIvtpF46paIBP0IIC5WEWHaGKGrh96pYlkupNINSIVqrvhKvTnVyehtHuofmQocTb45RPp5n7U6T/EiGkdNFmotpO2M/4fF7a9S3jefhk0WOvzaC7UrOfmuS4kQOaUksRzJ+scKjH62w2s963NFPx3J849+6zI3fmduXM7OJ+mKX4ZNFciMeq3caVI7nKYxlmf3xKk7WornUY/GjdTrrW2Nl6pURxi5WePNvXUDagtJUjtyQR9RLyA1nePfv3N0xV9uZVDD29DcnEULw/f/np19oSZmyHOOkcwkbF4NhVc2z4a7jeMXUExL1sL08QtqE3RqZ4hhaJakoIWmRWxUHCMtJNXuaKZckUxxFCDv1lKoYy8mAkMRBm0xxFNA4mZT4LqRAxWnNtshvEHZqCCTT9nnGrOkD21/Xq8zHd1A8Ha7ZzMx6MQKgANKyGZ6+OiDip2M93ZzlypMIK9185YeO06nNUzl2merCNcpTF/EbKxRGTtGpzjM88zK9xjKVqYskYYfS2BmUCuk1VtC75gtBYXgGrzCS9l1hJL0vrRHSZnjmFarznzB0/Cobcx9ROXaZoL1OZeoSUbdOceQkfmuN8vAFjE5wMsW0V7SmOHaK5ur9fSUELFtSHPUYO52nuRwgJNSf9A718jy3wZN2sgOCQQ0aK5vHyubRYYCOu1RmCgzNFGit9FjZw8Ozdq/J6t0mv/Cvnyc/7CEtQWcj5L2/+4DZd9YGjW8t93j3v7vPV/76GX7j//Q6OjEEnZjVO03e/jv3+PX/42uf5TbIDXv88r97hYnLFbycTWEsg5Ox+Iv/8RsErQi/GfHJP3i8o6TC7d9/gu1aXP2NaX7hXz2P7Vnp4h8olm/UP7OeV32hw8JHVV7+F07wzf/NJSxbEHYSPvmHc9z6vcWB1yRoxrz/dx/wjX/zIt/+966mIlOdhPWHLd7+O/f5lX/v6mdqh1dw+Pq/cZ7TXxvHydkURjO4OZvv/PsvDdSab//+E97777fIorNvr/G9/+wmr//V07z2V07z1t88hzGQBIrqXJvb330+Ybe9oOKATGWCwngWFYeE7dqOwrLtzhNKxWnCsEkUd1FJgFJhv5qvQxR1+kRbjW1nUSrCdfJ0e2tkM8OpVwiDSsKBYVPIT9LuLBFF3b6OxuZuWNHuLFHITxAE9TR7SSuiqDNQRY3iDjJIvW6OnSVRIY6Tp9tdxfPKhEEDbTRJEtBqLyCkTSE/Rae7MtDueLq0BYCFRUWOUbHS2jotVUUgYQ+DB3gOY2fzQLNL3PEwuCLDqH2w1IOvO1jx3lojnlvEsTMYDNKykThYlpeGDI2mUJyi0ZijVD6RhucwA4OnUJxCqYgo6uA4ecKoRasxf2SDrbncI1NKjfu1e0284ggTV4b46O+lZGGtzK7kAiR01wM++fuP6G6kE3bUSw70uQuRZliu3m1w/LVR5t9fJzggIaK52OHcL0/RWulRnW0zcblCdsijudRl9GyJOEh2ZYxKS7B8vcrH/9MW0bm7EVA6lts35GE5kriXYLTh5FvjtFcff2EeHk9kGbamcEUa9u3oBu2C7otOGvIjJ8AYIr8FxmA5Hl6+grRdvPwwfmuNbGkcy8kS+g385goIiZcfJmit42SKOMXRtP5Way0V/HOzZAqjAOQqU7TWHlEcO9UXLNV9g0dQkJVDx3SSxEjkPm/gi4WQDpbt0W0uYzmZdMM+dByvMIKTLaUZi70GfmuNXn2JXGmyPz+A5eWoPbmBkJJMcRwVB8RRL/U0G43fWKVb211OSAiB5eYIu3WCzgbZ0gRefojCyAm0inCzqeEZ9hp0avMUx04jLRejYtxcmebqfWK/lRqqSZTOzUmEtFIDtltb3HeeCrsJq/faVOe6ZMsOrdXPs3ioEGQnZhh+5Rs4hTI8JajVnb9H9aM/Ap26Qw+aHz/4Hx9y83cXKE/mMCZd6NcfttHbXtYk1Hzyjx6zdL1OZTqPsAS9Wsjq3WbqfQnUDk2d2nyH3/9PP6W5vNuztPGgze/9J9eozXdTxUljiAPDvT9ZYfGTBmCwMnkSv4PleliZHGGzzvrD/q7dGCzXI/YjPvqtRzx6e5WRUyUyJRetNGEnofa4g99MEJaNdD1U0MPK5BFSkvhdwKTaJUZjuRlUFO5yw0opuP5P5rn+v8wzdCKPkIL2qs/q3TZxkHIuEAJjBI/e7VB9/BGjp0tYrsBvxqzdaxL5ksi/QXWuDUiQ0KvH/PH/4za9RkjS5wHRjyF3NkJ+/z+9Tns1RFo5EF10AnPvbFCbSwvkWV4WvS2105i0v4W00oVQa5IwVYl+8kmNkTNFchU3TfPuxjQWe9QXXpyseXdjAb+xMuC5mKdIy35Qww8OzmjaLAYqpcQP6mkKZ2+dVntnim+9uZXd4zoFjFG7vpPG7Q8mB4ZhGl4SCPygitGadneZZnvnpBI1t/op41VIkmCnqNgLwx4plJ/5HFu/RyakqdaxhYuNixSpdo/EQh4h/VvpmG5vDa0SZP8dRAi0irEshzBsEcddVJJ6PTerUydJyPr6LeSgxtE6iQpJkqNnDyaBImzHlCZz3PujJ4ycKTF5ZQi/3vfe7tFtnbWAzrrPyJkSfj3ELTgI2Z+zbtY584uTNBY6qZyFFFQftTAYGk+6/OS/us2b/8oFXvtrZ/jo7z0g6uxN5vTrEbkhj40HTZqLXc7/yjHibkyymfW6R8WIxY82eO2vnaEwnsWvh3hFh6AVpe1d9bn456a5/70nWI5F0I4GZWwWPlhn+UaNr/0bl2iv+cz+ePULSUjYC35zLeWR9Y3+1tojHC/f/2yVJPb7C2YdFfnEfjP1/sVBauQag99MQyRaRajYwW+tIi0HrRL85ioq9hGWQ+Q3iYPOIP09DtP30WDomTYtVcMRLpawkUgEEsnBqeiQllY6sP/Etu9tpwNsZtvusbCrJCTs1Rk58SputkB7Yx7LzfRrDIao2MfoBK1iDKlWkrRspHSQlkO2OErQWqO99hBh2agkTO9dJ3tusIC+AVhl6PhVsqUxjE4QloPt5Qi7IXHY7hcI3qQCJAgpEVbKS/TyQ/jNVVqr98kUx9I0e7+Fmy2lTpQDNgiOJ5G2oL7ks/aoc+Qo5nPr8Iy8/i2k7dB88Ck63DmBRK0aCIGdtRGwr7KukIIkVCx9Wmfp04PjpirSLN9qsHyrseuzW7+3c9Hp1SJu//7eXoTORsCt31vEG56geOICKvTRSrF4SyNkQtxp4g1ZRO023lAWO2ejggJGZ8lPT6AiH6dYIdxYIayvUV/0CcJhLM9DxxE6VghZxh0qoUIfJ19ERSFeZQxhWemD1BqtElTYwxsap7v4iORp7Q2Z1sNaf9Bi9e7WZ9nRaZxCKhzmFiqE7Sp2pkCnFuF30zZIp0DUC8iPn2Lh2hrSGSE/MYKQEhUFrDwcTcmpegOEITc2nWbvaMXC9TxhO8ApjGDnhpCOy9qjkI0Fm7C1QWFyBL/WTCXt+89QRRkqZ18l8bu0n/RF4Qy0Vn1an7MLvDhxhsqJl3BzJcJOjaVrf7Bnte6joN1ZxrKqg1DUQYgTn3rz0Z51Yo6KZnsRy3IPnFQ2EUbtQXmMo0IKiUUWje7X3tJoo5EinZhNf+bMWxV83UEbhUGTs0qEqkdoeljYWMJBoxDI/jkUlrARyMHfC1aFjtp6h/NWhVZSRZPQ1lU+Cf8kLfSJwBIOGZHltPMyQ9Z+Im1y4IUJ/L0M1n4W5zZvw3ZDRgiJdJzBsUJILDeLTqL0p4r6XjcxcJunkv2ir4gs0H0DaunTKpXpPM2lHuv3Gnh5m7AdYbRh42Frl4enu+Hz7t+5y/lfPc4bf+M8vXrIvT96gtGGB99fQliCy79xAoD599aozbbwGxG1uQ5JoLj+O3O8+pdPM3yqyMrN+p5GVdiJWblZZ/1+i+ZSl/p8Z7DBC7sxGw9b6GTnKvDkkw3cvM357xzDsiXVuTb1+Q5+I+S9//Yul399hjf+xnmCVsSd7y7S3QhoPunS6fN8rv32I2beGGPp09qB3qfPE0nYIQk7WI5Hc+X+YDEHdvFL9v6bSau4k+oI+a31gfG0ef6n8XRYxaB5Et9nJZnrG+4SW7gU5RDn3a/gsrfGm7AEXtmjNFOiOdccVFg32mCMQcp0U2p7NsYYcmM5Nm6mafyWZ1GYLCBdib/ho2KFZVuoSCEdiY41MY/x16F8ukwYVvGrQVrLr++hZrBRSFif+5D80DEiv0HQqZEtTSBtj435T7AcD4xGJzG1hU8PzHztNZaI/HR90io1qILWOvR5iCoO2Xj8EQAbcx/iZIoYowja62SKozjZIs3V+3TrT0AIkrBHHLT7m/n9rRitYXg6R+VYlvVHXRpLR1tnnk+Hx3aw80XWfvJ79Jb2lmy33DR1u77Q2UoD/7IkbgiBUxzCKVawcgWC9SXsfAnldxFS4hQrg0rDdraYei+UIqguY2dy6NDfquti2TiFCna+gAoDgo1lnMIQcauKtG2c0hBWlEpnO8UKyu+CkPRWHqfnikMw+zg999goWI6LX10iO3IcO1dKZf3zFVQUELVrZCpjqf+oa6HiMLXiHRc7kydq14i7zdTA6Q9+0b+HXv0J+YmTOPkSKg5xC2V0FKZpyMVhkOmuXCcRluMibQcnVyRorJH4beTYDNL5fMWs9oJXHKa5eAs7U8SynV0Kpc5oiXhjb80J4TmYMH2ZhWvjTlZIGj2sQg7aPqq9/0tkjEKpz+asNkbtqHlz2HfVfuNkH2RknmHnOJHxCXUPR3j4qoUn80hh9fk9Alu4FKwhNAplUlXsREdgoGAPU7EnCHWXUPtkrDzNZJ2KPU6kAyxhk5iInFUmZ5XRKGIdYguXjqihDWg0odl2nwZ82hyzd9675bhkMuOo2CdbniTs1pHSSknicZBmyPVFAaXlIG2HqNdEqwjLzSOlJIkCbDdLHHbID0/TXEpJu0gLN1/B8fKo/u7RyRZTAb5eA4xBSNn3IqU6Y+m5E+beDpEyRogCy9cFc2/fH4Tx3/6vb/M0jE5L1azf3y0gGLRirv/jOa7/47kdf1+6Vh3wdjqrPj/+L/fRJ+oj7MT86P+zpfXzzn9zZ/Df9bnOnu3SieHh95d5+P3dXsLGQpe3//adXX+//jtb7XzySZUnn3w5pBrUc25qtmMvA+nIxxKTmO0Cm6BMgjZq3/BgZihD5XSF0kyJ0okSKlREnYjOUgev5JEbz9F83EQ6ks6TDra3tTwPnR3Cq3gUjxdJ/IS4GxM2Q7prXcony6hIYbShXq8T+xJjYnQSDoz2p6Fin15jBcvJpmr1G3N9Q9DsOGY/Ds3gto1ODZRtiJ9STFZ9wVkVB2iV0GssY7u5fnhtOU3Q2HaOo5gJKtY8udnEK9j4zaNnej1fSEtrdBgg7AMOF6kmi+VaODn7y2PsQOrWXHmMv7Yw8EZEzVo64SUx7bm7GJUgLIveynzKW+h7QKL+LnAztqiTmO6Th1upuCZNAxSkPInE7w5SgLtLs+m5jMYkCbGUIC3MM9Sb6a0volWcCmPVVzBKIetrfXdlQtxtDKz4xO9ijO7vWA1GKbRKaDz6NG1HX22zt76ITmJ66wv0Np6kNYEaW+cMO3VEX45eLT/s348NmFSgTqv+OfUXno4cdmqoKCA3MoO0nV38ktzF48TjZTBgZV3iahu7kiOud8meGqf1wX10L8IkGrQhf+k4caOLd3wYhET3QnQYIzNOagBpjVXKI2yL3p0FdPD5pt1/Fggkvm5jib7HwihcmcWWLr5qIZDY0u17dhSxCfv7VYnue382z7HpqlcmISeLaThOt8lZZUCQmAht0nNIUmPqoBIke0FaLtlymV59GWmlnATLzRB1G2RL49hePq3MXVtMNySWQ6Y0jtYxTqZEr7aIncmTK08QtNaR0marsKbBdnNpm4xGOl7KVfBbZIojWE6OqFtLd6lJlLr5yxN9EmyJbnWRbGUKxytgdNLfxf7pRt4dJmuXaYWrROr5jYOfow+TenniboyKFGErJOkl9DZ65CfzGG2wszZe0UOFCrfoYrnWwJgRCKJ2RNyNibsxnZVO+ncrrT4gbUluLIdbdFGhord+cNZSEnWpP7nxxd0/YHRCa/UwcdDDYTuS6ZfKFMY8lm61WLr1OVRLd4pDCNtJY6T1NYaufg1pOUTtOmbbbldHATpo01nzyY14zL/75RMiO0jKXyX7L2K7xo8xg8y0PXGANPkzbtgBBvHQ7RLp26MvaptkuGLv+3i6RtDgnNv6ZPs5t8uQb51/532pz1Az57NgU1k36tTT2PRTOz8dRJgoJn9lBtUJEJ6TGi9+hI7i1NABrLxH9uwkca2DlctgFbLYpRwmUST1DjKfIcm4CCmwyzl0lCBsC/bp4y8DeqpJS+2tbHtUNJKDC4F2VeMznX87tIqJ2hsDcqjWCUnUJQl7fb2gVBLDsr20lMZAfDND2N5I4/9yiKBTSzWEIj/lZiQhtpPtcwTaSNslbldT3RMVY0VZktBHqyTlX/Q3DDoKsByPoH9ujCF2W0S93Z6bP41wZIasU8aPWz83eF4A/KqPX/P3NEKW3tmtCt142Bj8d/VOdStK8lS0pLva3fF7/cGLTKv/8iLsKUbz9jNlIj+TwTP65nfwhtOYu3QcnEKZzOgUKvRTLYk+uvP32PjgD2n3DZ5T35jkyScbNJd6GGUIOzHf/b9ewxhDr/HFxILdkQkqr/0CTnmI3tw9Gp++h0lebAhG2A7mAGPpqPj+f34LO2PRWHwxRoSw0xo36C8muwLAqYww9PrXcYZG8J/MU//oR5j4xRoH2/t7vyKFvXtLmEQR1zqpKrgAZOq5iddbg4wuEyV0by+igwhhWdDXMBT9EiRGa0yiBmFAANXb21380+jvvfBlcqoeBSoO8Rt7T9a92u5aZE+70gGC1tbmKmB1x3f3+j5AEhyNRB92axy5SuGfAigdo3Uy4Hr9HC8An+WlNE/9fBHn/BmFijVRL6G9EX5+pSWa9z7ByuytmrwdcbsOCJy+jkN3I2DkTCre1a2G6MSwdOOLtULjRpXGJ+8w/OYv4Q6PDzKTXhSkl6V05TVaNz56btLsJraTlF8EihdfJVhZJKoevS7RZ0XSblD/5B2GXv863thkqhD8Ar0hwnYov/xVWjc/3pE19jQ2eTja321Yb/+bDmP02ovp98L5l4hq64SrLyb93hM5cqKII7x+uEkRmYCeaROZF1evTCDIigIZkccRLqJPbI6JCHQX33R+vvg9BRuXrCzgiSxWfzpVxPi6S8+0X2B/CTyRISuKuMLrk84NCTGh9vFNew+9l88GS7p04irxHrpPnwUSSVYUycg8Di6QcmIC08PXL/Y+LGxysoQnstiksgeqH771TXsnt+znIB1nWbIi359vbAyaxER0TYvQvDhPXzoO0vnGFu4gCSI2EYHpEJjuvhIYTtZi5ESeJNqnRNI+eCaDp7f4dKG6LVl5YwCtBtwWaQuK41mCZkTzSZduNfj89Rv6mRlIC7QaVImFNCwTN6oknda+Rptw3HR3bww6juEpDQDhOAjLBgRGJZh+uEo4LpmpGQpnL9Odu48ILHQcD7wPKdcp5fgIp19uIAq3PABSIh035QYp1feEbE9H3HZfGEwcp2Gm/nE6Cgf3KRwX+hwhYdnYhRLFiy+j4xDVa2P6/KvBqS0LYbtp85Lk2TxUQqTt3rO/FXGzlvZ3rrD34baT9s1+/b35OSI9f5/8LRwXb2yKwrmr9B4/RPkSnWx7HtZmeQM9uDcdRVvnF/3+lnJXu3fdF2arX4REuk/3t5OmACcxwrKw8kWKF1+hc+86SauO0Qa9PXwqrfRZis0xtH9/eyLLpH2aMes4OVHCERmkkGiTGjwd3WBNzbOWLKThvOdU/BBISnKYKfsMZTlCRhSwhYvsZ2WlBk+Plt5gKXlEW1cHHJ+fNiSSKfsMw9YkAIlJeBzfpGeOVtBy0jrFqD2NAJRRLCb3aOnDibkOLqPWNOP2DHlZ3mbwiIHB45v2vs8kMTGLyX3a+mDJhNQILTJpn2LYmiQrCrgis9PgMT06usFq8piqWnphBoM2CSVvkkRFxPqzGwYCQVEOc8w+S0WOk5E57L7Bo0gITJeWqrKUPKSpN1Ie2HO6L2xcRqwpJuyTFGSl/3yc9Dn3DZ6eaVNTK6wks/gmlQv5MsDB47T7Ep5IM2HbusHCngKGex97wrlEThYB8HWXufgGyaGbTUFW5JmyTzNsTZEVhb7BYz1l8Pjs109d3WIhvkvMwRt+iU1FjjJpn6Ykh/FErr/B2mnwNNQGK2qWtq7v2jjoxCCkYHg6R2stoLq7qtCeONTgsRyBZUsQhqi3dVHpeOSOnyY/cw6nUMGohLC6QufxXYLqCtKS5EYy+I2QyZeGuf2785/reBKWTeHcZYoXXkK4HjoMaF57n97C0aoJe+PHqLzyJnYpLYzYe/yA5o0P00VUCDIT05Rf+Sp2MRVTiqrrbPz4DxBCUH7lTYoXXsIdmWDiV/8FjEpo3/mU1u1PACi//CZ2roDye2SnTyEdl42f/CHB8gLCdiheeoXC2ctI20H5XeqfvEuwlD5BYTsUzqb3Jd1U1r99/yatWx+TGT/GyDd+jdXf/4cknRbCdhj9xq8Rt+o0PnmH3MmzlK68Tm76FFY2h7r6FeJWg7Xv/VPQGpnJUXn5q2SPnwTLIq5XqX/4I+LmEbxvUlI4fZHi5VeRXgYTRTRvfEB37v6RiMvu8BiV176GUxkBY+jNP6J544PUGBMCb3SS8qtv4ZTT0iFxo8bGj/8Qk8SUr36F4sWXyUwcZ/w7fxGjEjqP7tK8llY+Ll1+DWd4lLhZJ3/iLNL1qL73ffyFR+k4OX817U/HRfk9Gtc/wF98lBqklk3u1HlKl1/D8jIYrenO3aP56Xs4Q6OM/8pvsvqHv0PcqCIsm+E3v4VRivoHPyJ7/CSlq18hf+IMTjE1NJNuh/U/+WfoKES6GUpXXyd34izCtkmadeofv01U3c1xK4ghzrqvMmJNYbGz2rIl7MHOqGKNUZZjLCUPUObZFzobl2P2WWaci2RFWtxwe6abwMIji2dlKcohRqxjLMR3WUoeEPPTSU3ejtRYG2XKPgOkis1LyUM4osFTlMNMWacRQpCYmHW1CBxs8HgixxnnFSbtU9g4feHKTdVcgy1cSpZHieF9zxGZgHX1hDb7GzwSizFrOlXQlpWBftHWvQtcPFzhURAVhuUkq+oxj+NbeypWPw+6cY0XMXELJOPWDGecl8nL8jZtpBQSF0e45EWZIWuCx/Gt1EPWVzp/FuRFiZPOVcbtEzi4u3RxbCS2cMiYPBU5xqh1jEfxdWpq5UvhwbSEzah1nIKsAOAkSyxytGrxlrAZsY5tEyCtMR/f5jCu4bCc4Kz7KiU5MkhQMH0xJ4GFJ3N4HBzdqas1lpKHxGZ/g8clw4xzkWP2OTyR3TXfpDIYNp7JUpIjjNnTzMU3WU4e7dg8qESzer9Nc9WnsXR0D+ShBs/YiSyjM1mqTwKW76cBbGHZVC6/wchXfpmwvkbcqiOkRen8qxRPX2H5B/8LUe0JreUeQycLKRflczaeM5PTVF7/Os3rHxBVVymcvcLwL/wKYW0V1T345beyOYa/9svEzTrNn/whztAII2/9CnGzTvfRHex8kbFv/TpRY4PaO3+CTuJ0MYwjjBC0bl9L5bAvvMz6938XFfg7wix2rkDh/BWa1z+g9t73ka5HVE8n1dzJs1Re/RqNj98mqq1TOHeF0a9/h+Xf/fuoXofs9ClGvv4dmtffp7cwi+wbc2g98OAMwnNCYOVy/WsL/Cfz6CjCHR6j8dFP6C3OpR44rUFalC69QnbmDI2Pf4IKfIa/+osMvfkt1r//uwNvyX7wRqcYeuObtO5eJ1hZJH/qPMNf+xWi2vqhBpP0sgy/9SvoKKD6kz/CLpYZ+fp3SLpt2nfTUiWjv/i/QkcBtfe+j44irExf8NAY2vduoJMYYTus/+D3UH5vRxhRZrIUzl6idetjau//AOG4RLXUqMgeO8HQV75B88YHhGvL5E9fZOQXvs3qHzSIG1W8iWOMf+vXad78mO7j+2nml4oxSiEsC7tYTotmbvZ3JjcgdQcrT9BxhDc6QeOTd+nO3U+JsVEEQg4M8toHP0J121Re/zrDb/0ya3/8T3Z43TyR45z7GmPWdDrxmFSnIzR+fyEzuH2386bB4gpv1yJyGCxsTjqXOelcwRZOP4OJwXU0CRYOOVnExkUgyMkiZ91XsYTNXHzzub1KP6tw8DjjvMJx+yxSpCKIPd2iqpbp6VRA0BVZhq0JSnIk1R7qP0Ng4JHp6ibRIeGUSfsU55zXyMj84NkkRPRMm8TEg5CAKzKAwJNZZuRFbOFwN/zg0J32YdBGYRlDYj67YTtsTXLR/SoZmYoEGpP6JH3TITRBei+ygEuGrChw1n2V5WR2l8zEYciJIhfcrzJiHRscq40mMB1C4/efT3oNiYUlbCrWOJfFW9wK36WmV/iyeHq+KGzqB5Wt0cFzaagN6mqN0PhIkY6zUev4YFMEm8/QEBMS6h5NvX7gpsvB46z7Ksfss1jC7o9pQ2B8AtNFk2DjkZOFvjdOkpNFzruvI4AnycOBQep4FiMncwzP5JBS0F5/QdXSjU7Z0EYZLFugklRtt3ThVaof/5Dm/U/QUZTKTGdyTHzzL1A69zJrP1lk4YN1Vu80BjWxPk/kz1zCJHFqSBgI1pYonL9KZvwY3dmDrWNv/BjeyDjtO2m6dtJpk/Q65E6cpfvoDpnJaYTjUP/oJ0QbT/FgjEF12yi/i0li4nYT/XTWlhAknTbNGx/uEmksnLlEuLZE68410JqoXmX6r/xr5KZP0Xl0l/zJ8wRrS3seexh06JN0W5gkIel1SNqNwWeW51E4e5lwYwUVpOnW4foKxYuvYBeKxPWDd7n50+dBSKKNFQQQbqxQuvQqmcmZQw0ed2SMzNQ01Xe+l/af3yVpN8mdOEPnwU28sWNYuTzVn/whwR48GNXroHrd9L46LVRvp0ErhEAHAY1r7+96FvnTF4ibNZo3Pkz7u7ZBbuY0uRNnaLUb5E6cJWpUaV5/P9VMegboKCDptDEq6d9TY/CZdFwKZy8T1TfS9hpDuL5M+aU3cEoVwvU0G0piMW2fZ8SaGiyUgemymNxjPVnse1UMEouCrDBtX2DYmmTUOv5M7n+BYNI+zYxzsW/saLqmxZP4PhtqiYRUkVUicEWGcesEx+yzeOSwhM2MfZGebrOq5p477PCzB8GINcWUfTo1djBsqCc8iD+hp1uDkINAspBkOOlcZsa+iIWNwbCQpJ6xxMQokxzoIRuSE5xyXsITub6x22NFzbGSPCYy/kBM0sZh2JpixrlAnrT+07h1At/pMBvf+EwGqSVsHCuDrT1Cnt9j5IoMp/v3AqkB0tTrzMd3aOnqlh4ULsPWJDPOefKizHH7HBZHN+IdPE47LzNiHUMKiTKKml5hMb5LRzfR/ecjscjJIsftC4xZx1OPqSxyzn2Vm2GPrvmzkYUH6aZnxr5IUabeSEXM4/g2T5IHfQNRD763LGc5777OkJxACEFMyN3oQ5pqHY0iMTHJPmNaIJh2zg+MHW00bV3jSfKAmlpBkfTnG4knskzZp5m0T+GSxREep51X8E2Xqkqz2eJQUX/ikyk41BaPHm491ODJlizyZZt8xSYKNbUnAUiJUQp/5fFgsTGAjsNUxK9YSTsv1lsS7J8znFIZd2SC0a9/e/C3aGM15VscAiubx84XGXr961sp2DrloADYhRI68HctrEdGf1Hfy2Cxcvk0pNHn8+jQx6gEK19KPQqFIlGj9gwZZUfbEaXeihJ2oYQ3uqV26y89TrORDoFdLOMOjTDyC9v6u76RGk+HwMpksXMFKq+8tUODKK5vgDHYhSImiUm6RwtLPA3TlwrYZXgCVj+0OOjvKEDHMXY+9ZTZhRJxq5Hyeo6CoxZNExK7WMYbm8Tph0UBguXFgYgdQEFWOG6fxxLpqxnhcz/6iBU1t+uUvurQ1BtccN9g0jo1OOYoKMgKJ5xLOMLDGENbN7gVvUNL705jD0yPlq7RM20uuW9h4+DJLCedyzT0GoH5s5G6ZGEzaZ/GFikPLzQ+s/H1XTwcgyY0PebiW4MwoBSSihzjsbl1aH9tGgh5WUIgCHWPe4MxsNO4DIFu0qSta1z1vk5elLGFw7R9nppaoa6fL1Fhs85SoiPM8+hnDM4jmLLOUJajAwO+qde5Fb5N1+zUTgnp0U0atHWNy95bg0X4qJiwTzBhnxzw3FaTOe7FH+5J7PdVh5aqodw3mLLPIIWkJEeYdi5wL/rgz4wRX5CVwfgEqOs15uKbu/hCioSmXudRdJ2XvGJKNMahJIdYTg6njZTlGNP2hYFXtKHXuB2+u6dxGZgu7aiGr7ucc1/rG6R5TtqXaaoNEiKKYxmyJYfGko98hvyjQ2fIoKNwTqTkTZ2kg0BHIWFtlczYcaJWfzHue3jc4Ql6y3Mp6bMP/TQJ93NA0m0TrCyy9sf/ZJtxYI5k8OjQJ+m0Wf/h7xM3tjwbm+dJel1kv66W6u0zWW0qF++3AO7Da1G9tM7WpnCh9DJpLZNeB6M1qtfFKRQRlrVDDyc9pe4Tc9PHKG0bK5vbcQ+peInZlZVmlCbpdQdcpU0DwBh9JE+S6nYIN1ZZ+YN/vIN4e7T+Dkl6Hapv/9HAs5G2KcEoRdLrIqz0XpLOPoJSm/25T3/vJ0uu/G5q3EiZ8phcD+k4A6+L6nXwRif3lhjQqQDlZn8Ly8LK5Ulaje1X7mtlPNUuo0l6Hfwnc9Q/+NGWjIMx2zSVBKPWcTyZ7X9kWEkes672z/aKTMBcfJOSHB1USj8MEotx6wR5UUYgSIiZi2/uaexsx1qywLA1yZR1BiEEeVlm1DrOYnI0fsHPOlzhDXgVAA21TlfvL3gWm4CNZIlhOYkQkrwsU5RDBOpgg6ciJxi2JlNlc6NZTB6wrhY4aA5t6nUW4/tccN9ACIErs4zbMzSjjefy8nh2nk2xyk3j53ngiSyj9vFBuDUmZD6+vcvY2Y7U+3OXS+6bRzbiU4L/mdSb1jfgH8XXD8xijAl5HN+ibI2Sp4wQkmFrkrys0NF/FrRsRD+DbYubs54sHEiObug1uqaFZ3IIJGU5hidyB2ZvWThM2afJiBwCQWB6zEY3DvSkaTTLapYhNTEI7ZesEYatCTZYpDThAekcWZ7KHtnLc+hIllLQrkbMXWvTXNtczNKJf/Sr3+bYr/6LTPzibzD5rb/EzG/8TfLHTpOdmGH8G7+R/vv6X8DOF4/UmM+C7uw97HyR3MlzWLk8drGENzq5ZWdIC5nJIh0X4ThYmWw/4wqCtWWiRo3ixZewiyWsXAFv4lia8QT99GJD+aU38MaP4Y6Mkzl2YnA8pAaA5WXIHDuBMzSKlcsfsd13cUcnKJy7gjs6SeW1r6GTOPW0xDG9hUdkJqcpnL+KOzyWht9GJ0EIVLeNjiMK5y7jjoyTP32RzMTOCr46CtFRQPbYDM7QCE55uP/3gO6jO+ROnCEzNoWVzeEMjeCWj7ar6j6+j3AcCmcuYeUKqadobJKBh0laWF7a39K2kdv6O6qtE64tU7jwEnapjJXL441PIb20Bk24voyOQsqvvoU3cRx3uN/fzlY17aTXQToO2WMn0/4+4hjrzt3HLlUoXngZd3SC8itvpqU+FmcxKsFfnMMdGaN48WXckXG88Sm88SkQEuV3Ub0OhbNX0v4+dZ7s1Imd/R3HKfdqKh0HTmU4FbJLYroP75A5dhJvcjrt78owztDIYB2zsHdwDyIC1pKFfQUkN9HT7YGr9yhwRZYxe2awq2vpDer6YIFBSPkjG8nSIOMjbe/UM/MsflbhidxgATYYfNM+MCxlMASmM+gviSR/qFEqmLRPDgwE33RYVwcvQpvXqunlwcIjEAzLSWzhHnjcfohViGflcKT3XGT4TeREqc9lSsdIW9epqoPHmsHQUKt09dFDS0NygqKs9Mm2mg21SO8Ao2oTHdOgpdINokCQE0VKz+hZ+lmFRJAR+cE8YDB0DulzjcLXKY9QCIErPDLiYDJzVqb8HzHwIq3S1IcrlUfGp6qWBwb7ZshTK9iY66L7hVVX7x89EnCkLC1pCbQ2W5tqaSGA7sKD/u9p6YhgPa3RIhAIO12cUrLe5z8h+otz1D95m+L5q5QuvoLRinB9BX9pHiyb4qVXKZy9hDs0AtJi/Dt/CX9xlsb1D1DdNrV3v0f51bcY+6Vf7xNNQ6pv/zGq1yZuN9j48R9SfuVNxr71F9LaH/UN1tdX2Nw8BWvL9OYfMvTGN9FhSOvmR3Qe3Ezv3ezv+eg+foCVL1J++asIaaHjiNq73ydpN7c+z+UpXnyZ0uXXMErReXCLsLZO3G7SvnWN4sWXyM2cJW7W6M0/GKRvQ+rRaN74kPLLb5KZnCbcWGXjh9/FKEXr5scI26by+tcHZTU6928SrC1z0G4SUoJu/cMfUbr0KoWzl9M+adaJ1ldJQk2xnwnlVIaRrsf4t3+TYHmBxrV3UX6X6rt/wtBrX2PsF/982t9xRO299L5Vr8PGT/4o/fxbv556fdpNam9/jzhuABDV1ug8usPQ619HRQGdezdo3foYSFPE9/NS+YtzNK+/T+nya2kx1zim/sEPiWrpC+gvzVN7508oXnqF4vmrGKXoPb5PVF0n6bZpfPIOlVfeInPsBEmrTu/x/R3PVoc+jevvM/T6Nxj/9m8S1TfY+OHvY5KY9r0bSM+j8sqb6bNOYnqP76c8JUM/82pr8ujqJv4Rso00ioZa44R96dBKzQB5WSIvSmlfGUNdrREdkFmxHT3TIjJBmkYqUt0eT+T+TIS1bLGzVps2isPeE4XakfljCeeAb0NG5AahHGMMHd2gd4AXaTsiE9I1LTKkmy1XZsmJ4qHk6L3gWB6R9nGtHLZ8PqNJkHoBnW1GV12tHim92jddOqZB0QwfOqYlFiVrdGDcKRRVtbte2H5o6RqTnEL0ScwFWRmUR/nTDTHQJgL60haHPxtNMhB8FlgD/an9UJCVHWT1Tc7OUdDRdRITpRXphSQnSnjSozRuUxz1qM53KY1n6DWOxhM+sKXSFnQbMZYjcTNb5DEV9Fh757sc1ZDRz1Ar6nmxmQrem72/TdslGoSBOg9v7UpRN3E8yEYKVhaJ6htIxxto0gz4KFrTW3hEsLY0CNXpONqRyaRDn423/xjLy6Tel/6xtpfD7Uk2bvxo73bHEa0bH9B5cDMtUprEO3gwJo5o3viIzoPbA40gFQappoyQUOuw+vu/g9bxlp7M5j9Is5ru36K3MJuGxZJk8Jnyu9Q/+BFN78NUS2lTo+eAKrVbN6zo3L+NvzCbGrfGkKscozJ1mY1H79Odu4e/PL/zXpN4YBxEGyus/+D3kK6XatIkyVZpC2MIludZra4OnoftZMkWxog7jcGzq73/Q5qfvp96ULYZOK1bH9O+++ne/a0SWrev0Z29N+gPFfhb+kFJTOvup6me0uY4isJt4+g2/pPHfWMpSkOBfU2dzbZ35+4TrDzphyHVIDSmQ5/Gx+/Quv1J+qy13qHHlJPFnR4E3TmysGBgeiREOHiHfrckh7cyWFD09NEF8mIT7tjxW8LBFZk/EwaPforLIklrlB1k9FjYiG3E28O8dXlZHnCEnvYQHQZlkh3jRSIP3X3vh0RHdKIqjuzwvBtWQRrG20TqQWgcaaxtehKMpXf0316whUNBVAZjOjbhM43HlJy7hYzIYf2ZMHjYcY9p5ffDQ4ibekZAX/1r/34SCEpia75RJOlzPSLFJTLBDs0vR3i4loeUmie3mkycKxKHipV7R/PyHGzwSEG25GC7gmjbJkFYNpnx6XQB3gNJt0X4Bar6DqD1vpk1OvDRhxBqdRjsTA8uDFOaOI+QFmG3Rmv5HmhB5fgVbC9Ht7ZIZ+MxuaFj5CpTSNuj11iivTaL4+WpnHwdKW0cO4sOfZxMkfKxS1i2R3P5DlorCiMnkLaL0QkqDmk8uUVu6BiliXPEfpv6k1tIy6YycSkNCWlNbeEaWtqUxs/g5Ydprz5ExQGZ0hhOpkhn/THF8TPEQQcvV8ErDBOHXZxMgdr8TkPAJAla9yhNnMXNlpGOR+PJbcJOldzQcYrjp8EYags3UFGPyvRVLNtFSJvGk1tEvSaF0TEKoyeRlo1K0hTsbGGcwugJYr9N48lt8sPHyYyNpdWsvRzt1QdEfovi0EncXJlOdYFeuEhuZGbPviyOzRD3y0cIaVGeukhnfQ4TxRRHT+KbNfKTl3b15d4PWh1MQD9gHKH14eT1A75jVLKvTEJG5PqLaLoTSrNxjjbpKhMTmRBHHG7w5ER5Gy9DMGmfomyNHOk6Vp+wvAmJtWOX+KcZvummxp5gkKLv4O6b/i0QZGUBmy0jtqcPnphzojjoT0FK9rzkvnmk9gmsHURfgdzhXXkWJDrc8fN5IPohk008bZAdhrCfjSYPMXhSNeWtkLaNw1nnlSN7EbKiiNxm1NnCTcMvf8p5y7ovC2CMGejhFGSFht6/9qWFTVYWgJSAHpvwQP7Oppdv++/TznnGzfSR2mgLd0dY1hI2KMn6bAshBM2VAC9/9GSNA7/pZiTjJzIIKXaKDnoZRr/6bSxva+ITUmJ5OcBQv/neT8fgecHw8iPkR6ZZf/AupamLxH6bsFMl8psYoylPXSTs1CmMnsSyXdprs5QmLxC2Nxiafok47BLFTbKVKYSwGDn1FVQSYIxi+ORrtFYfkCmOAAIV+WRL43SrCwyfeIXq3Cfkho4xNH2VbnWB8tRFlm//CYXRkxTHz9J4chu/tcbQzEtI20XFAV5uiEz/HLnKMYL2OtnyJDoJKY6dIg67ePmhXXWnhJBUjl2mtTaLCTsMTb/E6v0fo1VE0N4gP3SM0sQZGkt3GDp+hbX7b+PmhyhPXaC2cJ2hmZfZmP2QyrFLALjZEsMnXqFbnSdbnkInEW6uDEJQGj+N31onN3QMrzCMlx+itfaIytQldBzs6suguUYS+UR+i8LoKRpPbiGkRXHsFH5zBaM1hZGTJHGw1ZexT7Y0QXP5HkY/H//Ay0qEBGkJ8iWbVi3GsgU6MViOwBiwHUHQ00S+RlqQyVkksaE86tBrJ5h+OS3ZnzttW4CAbiPZs8yWJZyBIbKpcHxUaDTKHM0T4OyYQCzG7KNNPntBIgYcgD/tiExAU6/3J3yoyHHKcpQNvTepPCuKjFkzA+5CYLq0DyHDbkrsQ/+9tMYGInLPA/kMmXtPIy0t8tm8HPa2EJ4y8TN5TRITH8kbJJ8y7FyZ4bg8/2wN3XG+Tc/dn3b0Q6amPQhxT1gnWUsWiNjtHBD9pIq8KKfSH0bT1nWCA8tNiB2bMEvYTNqnnrvFMp1xULFh0yJNwqPPkwe+Db1Wwvp8QHHEQSVbA08FPVZ/+E9gm9CZdBwyY8conLo04PbsBSFSFUd9xIXIcfIYo0mSvb0zluWi1NGywISwcN08UdTdlWopLMHQxVFGX5kgbkcsv7sIRhN26/Qay+SGp3GzJYSUlPreE9vLIS07VWauL9NrrlCaPI/lZLC9PO21WeKwQ3HsNNJxyZTGiHtN4rCL31gBY4j9NloptI6xvBxefiglLTdTAayRk6/Trc4T9Rr06k9wsyWcbBEwxGFnR0rz9j7YFMfTKsJvrWO7OZKws4NovR1aJ/jNVVTUozh2Bsv2KE9eSDPHbA/bSyf5JOzSrS2iVUJp4iy2l8Nohd9Yxs2VyBRGcXJlMoVhwk6N2G8SduvYmQJRt4Ht5oiDNpbtIm2PoFOlV1+iPHEe28tjVEKvXR30pbBsjE6Iw87W/W2N9XQx6c9NO/rSTZ+N0glOwWXya9PkxvM0HtRY/2QZHR8wkQo4fi5LtmDRqsVMncnSXI+RliBbtOjUY2xXMnU6w+yNLo8+7ZLNW1x8s8jKbMD0xRzVpZBM3sZ2wCBorEWcuJTDsgXvf7dGr7V74k/DH31RL8yuEMpBSOPvRwtL2cJ5wfP5n4XFIQ1HLSezDFvHcIWHJ7OcdV9FxGIHL2Fzp3zKuUpFpsaKMoql5OGhtYg2lZtfBASf7ckU3GFC1SVWwXMpEAsE1jbvn0Y/03mOWlpC9P2MLwo7tX//dKOjG2wki2Sdi0hhUbHGOO++znx8m45pDPo/Vf0+zhn3lYGHNzS9VNX8kGdkfwajezc+29M5sCWWLWjXIoQFcbBtoGpNWNvt9vJXF3CKQxROXcJfXdjznJlMBdct0uutkSQBluWl8tVCks0O0+2t4dg5LNvD92s4dpZMdoha7QG2lfI5kiRks5NLpRMEQY0wTF3FqQEUksuNEcc94rhLIT+J79fQOiGfm0DKGkHQwLYzKBWidULhWIk3/oNvMnR+GBUp7v+DWyz+XpdMYYRseRLby9GrPcHNlUkin15jiVzlWHpTfcVJSB+HVook6pEpjWKHOSw3g04iwk6NoLVGr76EVglevtI/bmvARH4baTlkSuN9L00/VfhpXo2QuNkSluPhZIqoyEclEU6mQKY0TqY4it/c9LJtv8beg0VaLrnKBCqJiMMOQkjcXIX64nUK1taOxzzlmkjCHlLaZEsTZIrp5B77LYJOjfb6LCoOUWGX/MhM2oZNrozRJEGnf5+TCMsmCXu7+lIA0nZxMsWBIaniAK0TvMIIlu1hOZn+Xe7sS0gN2VN//hwv/Ztv4BRcustt3vu//ZD1jw8mNUahJl+28duKXlulmf0WaG1YWwgpVGwKZZsk6ks1GAh6GtuV1FcjVAJCpHIAvWbC+kLI8KSL48oDKFLbDNYDntVhxx6G7RNGYmI21GK/ltCzQ5kY/5AwzZcbzzZ51tQqi/FdZpxLOMKlJEe44v4CPdNO1WKNxhNZcrJIpq9Kq0zMqppnKXl4qIfjaVJ0Xa/SOqTe1n4wRtNUh9cFO6g1lcxx2uEafvLsYnz9N2PXOV88di6Cvu6wrhafu6aYrzsknyEz7aeNZzEINIqF5C55WWHYmsQSNlP2aSrWGL7uDJSWMyI/KMJqjCEi6EtZHDy+np7HYhOyphaeu+jxZghNCBAyTaiStiDqHW1zeKDBk6/YTJ3LYzuCtjyCu9wYjFLY2b2LRQJIaVPIj+P1jZ5sdhTbzuD7VYYqZ1AqIpMdIpsZRiUhiQqRwsZ18owMX0RIi1r9AUGQTgKuU8Bzi8RxjyBoUKmcotfbIJ8fJwyatDtLDA+dpy4e0e2uprt/6VAqHqdUnMYPG2xs3CZ/rEhxuoR0LKRjMXRxlJU/8RFCpuGTxgq9xhJx0MbNlcmWJmks3yGJffzmKkmUCgZ2aguoqEd94TqV41eQlkvUfIxOQjZmP6By/DLDJ16hvTFH7LcQbUFlSBDHim4tIQk7mO4tLr7xEq1ah7B5CzQkvUWKJYEtm/gtH2k5FMdOE4cd8sPTJFEPv7VGaWyS8uQp2utzRL0GWsXEfptufQmVhMT+3ouTigO8wghGKxqLt4iDDq21+4yeu0BntU4cNrFc6Gw8To2VqEvYXUVFAfUnNykfv0TUa5IEHaJek/riDcqTF1BJyqUJWmtpG9vLCDskaMZEQRWvkKM0cY722kPC7gZuoUDU7Wz1ZRziFYbJlsZQSUhh9CTN5XvUF25QmjxHHHRor8+l92UMxuiUDKwStFZYnk3l/DBu2UuzisbylE9XaNxo4bgFksRHCgul48FPy3JYexxTeyJQKkO3CZh+iQBAJxnCjs3KbBOlFJ5XRhqP2WsBQmRQOkIKh2UdYVkuSaKQssiddxRSClSSI5Ox0SZBIDEYorDdVxvVpGoRAusZSkUI5KFch8GzRrGZZqFMwnIyy8YzpLXvhDnSLvzLimfpY0i9PGlJDc1x+xwZmccTOVyT3fG9gUq27rKczLKQ3DlSZW5FMtD0MhiqyTKPk9vP1MYtfLZnI4XEsbJY8nk5WmaH0fF0LbDDYHG0728SZ202Q4c9ZuMbz72o/iyPaYF45hIzPdPmXvQhp92X+srTDjlK5KzSznMPwlhV5pO7rCWPDzXgDTuJ0YmJWYzvH6lA735nFDZMnS9he5Js0SGJNQ/fOdr5DjR4OvWE2U9aOBmJ7W7F6YXtkD9+5inSssApViicvEDz3icHXjQImigVUirNkCQhUtooHdPzq/hBLU3Z1Qlh1MZ1i0hpkclUEFISx9tCG6ShmG5vlaHyaYSQJEmA42QJwyad3ipB2CQIG3R7a2ijkNJOPSiZYaKog1b9LK1aj7AZ4BQcdGLoLDRJ/ASfFVbv/XhwvajX2PE7QDvYIqEWnXuceElSr0WUCx/SbmpOnXTICUOz1qFsfYTnglMwuCMCIdoIAS6Gldl0cujWF5kYWeX4iKApNRNjglzhPr2KizYbPLoXc+mKw8b6J5RKktA2jJ6RNBuKk+PXqK4r7LKAMmhVIwoN87PrHCjWbAz1xZsErS3PXaf6kKHLIXidVO9nKkPszzJ8oYwKFYWZDokukB3tEHauYeUtBDGjl4eIuzUS0UahKJ92CBpVgo0OSjWY/voxWvNd7NAmSh5hQoM7bGOXChQmA1oLPUqnh4g6y1TOZol7PRJ5C78R45QcKpkClhfRrn5Id3XLMxF2tg36esqr0LGku9JFhQrLtYjaIZ0nbbK5EQrFKcKghRCp0SGAIKiTyQwRBk1sN4/rFoiiDn6vSiYzRODXKQ+dRAhJdf0ORvvki5N4mQqhX8eyPVQSIqWD39sgmxsh8Ot4mQq2kyEMmhjTIpOpEARNypUTJElIbeNun7Ow6UKWR8q42oQU8sgibZH2BwpclrD7pQ9++kUTfxqwD0kT3wsJMevJIqPWcTImT0JMZPwB9yYhxlddWnqDmlqhrWtH9jZEJkSjsZCIPv/hp/VslImJVe8zhRDibbwyG+eZQk/bOW0HQaOJTDB4lo7wEIg/k2P6ecN7PdNkI1lMvTzGISYkNlE/W00Tm4iublDXazTUWl848ihGoSHcNt/YwkEiP9OzEUYQB4qgkxB2k4Eg8lFwcEjLEUydy1MYcWhXIxorKWNfuh7Dr35zB2kZSLksy49p3d87JRhIF4Ocg5QWvd4GnlcmijrEURflFslmR4ijLhmvQjYzhO1ksSyXOPFTA0UnJMmW5Z4kPoX8VGooiVQROozaJLFPLjtCHPfw/RqF/CRBWMdxUgXRbm+VfG6cKEoNqPZ8k+t/+0Omvj5NsOHz6J/eJWllMcmzDZ7xSYtOW3PlFRetDblcqmGUzQrKZxyOTVssLSasLClOnnEpFCXLTxK0EptiywwNSwqllBjruIITp21WlxXSguFhi/UVxcQxC8eB0XELxxX4vkEpQxwZvIzg/CWHXs/QamhufhIdaOwYo/Fba6h4j4wMA9nRLEiBV/bIGoNRhrCv21KaKZEbzZKECfWHjXRn2xeEcvIOpZESvfUeQb3vEhdpdC43niNshlieheVKdGIIGgEIKJ8s45VcVKio3q9hORYqUkhH4uQcyifLtJ+00+8fAh1rHn/3PtKRFKaKrH60xMb1VRwq+L1a6m3VKV8mJThLwrCFtBwwmjjqYPpenyjqEIYtHD8lnmqdTuZR2EmLsgpBEgcoFQIhCEEUdbBsD61j4ijVbZHSIgxbRGGLwK8Txz7GKHzT6e9UHUDgiSwW9pEWSwsH9wgZWgBd08KgBxoaWVlAqM82Cf10sX3Ce7bl+XnStnOixHnvK5TkcF+t9zYryexgJ5vyrzQa9cypzb5pkxD3+VxpQc2jjoEXDUu6ZOwivb721bMiLQ665VGWWHgie8ARO+GJHPIIBk8aVu0MMrU8kcEV2Z9ZqYRd3iVx9FFtCbtfTPZZIBi3TnDOfQ0Hj7au8yi+RrOvvG4glUNB9TV4jm5gGAxd3WKTdm/jppo8+mA5h4OglaE636M8mcHNWrSOWDg0vf4BiANNuxrh5SWRv5207LP6o3/GjiIWxqDjkKTTSif/fRCEDYL1xr6fbSKs9sW2fGi1Uj6Q7+92W9Ub+9fx6PbWAUOz9XjrGsHWNTqdLR6HChXzf/CQ+T/Yfr5mSi5+Bjx+FBOFoFT6YDptg+NCFEE+L2i3NNV1RbdjeDKfYAyk0jhmYPAoBQtzCUFgcF3B+qrCcSHoGdpNSa9nuHcrwnHS8ykFUWTQCho1jRDQamjCwKAUdNoHL2RGK6pzH+36u040jdkGRhuSUJEECUmQIG1JUA9I/PT31pM2KlREnSitqCAERmmMge5ql6gbkwTJoJ+bc010olGxxvIsdKwQVv+cgUJFCsuRqEgTtkIsRw5UNVWs6a51CdsRKjraYtJd7nDjb3+4428J6/i9w9U+90KruVNfqNPev/TDYWjUHw3+u6dbaaaVyKThN1nEFdkjiQ9mReHIqrpNvTFI9xVCUJFjOLhEPG8I4KcHg0ZtI3cLju61yYgcrsg+E0nYwmbGuciwnEQKyUp8n/n49gszSNq6RmwivH678qJMVhTpmC++1IHo0573K9NyGDSGrm5upT0LQVEOs6bmDyXYp6nmhUGG20FIiGmZKsNmEiFSLZkhOX5oqZQvK7TZSda2sNIw1RHsg5woPrPXMivynHKukpVFIhMwG3/Kmtqbg/usMBiaemPHGBiSE6wx/5neGScjmbpY4vhLZR5/VKO5fLS561D3hd9JCLsKy942KWhFWPtZSDv/4uOwG2vpi9xq7n6hn15eH93f+4HPzx40ENLJvfF8PMZnglGGxuz+ZMWofXA6YDy/WyFWx5r6o8YznXN7gl7cPVrq9c8iAtOjp1uDnWpelinICr462OCxsAe1l46Crk6LTQ5ZadHYijVOyRph44CaXV9WaAwJ0WBClVjkRAk4nJM0JCeeyeMAac2mihwbpOI3VfWFel9C49NQaxT62iV5WWLEmqKbNL9wD1wrXKUTVdHPTeBN054j4w/qNQ1bE8wn3qF8pqwoUJBDRxrTm0rjkXUWT2SRSMbtGVbU7JF4U182JMQokwzGtCsyeCJ7aIafQDJqHT/wO3uhJEfI9KUWEhM/N0l+P3R0ja5pUhAVAEasKQqyMvAgPQ/iQDP/SR2/HdNrHD0t/VDzuTTqMn25gNE/mySun+Pn+FmBRrGuFge/O8Jlyj59KJen0M+wOCoiE7CaPB4oJtu4nHSu7BCJ+9mBwd9Rr8pKeQiHiCG6ItuvfP5swnwCuUN3aNyeoSxHD73es2AlmSU26SQuhcW0c2GQ3v5FQhtFosNnkkd4Gj3dprFtYcvLCuPWSQ7K1hJIRqxjA22Yo6Cu1nZ4EkpyhBn70gtNV/+i8HQoMCPyO+qR7YeyHGXEmnrm61liSw7DER5T9hlyonikcOJR4Jsua8n8YBx5IsdJ5wouzxp624K0BLYnWbnXJuwe3SA/WGnZEhSGHNYf+0hrq7OFTLNd7KyNTjT+Rg/VD1nYWZvS6SEm3zxO5dwImeEsCIiaAa2FFrVba2xcXyWo+bscMJZnkR3LI+0+277uEzUPj89JW5KdyGM5KYk6aoXp+feBlbHJjeUR1v4DKGyGhPVn2B0IyIzkcAsuRhv8jR5JL0bYkvxEgbHXJxl9eYLcRAHbs4h7Mb3VDtUba6xfW6G72sUkP30OhZ11yI7mEJYg7kb4VT/NuZaCzFCG0VcmGX99isJ0KX3+scZf79J8VGf92gqNe9U9Q03eUAavnA5wHSt66z30EUJSTtElO5LuDo0y9NY6qHCf4wRkhrO4xf0NBKMN3ZXOka69ie3jUoUJvbUuRhmcvEv57BATXz1G+ewwmUo/ZbMd0nxUZ+2jZRr3q0Sto8eYa2qFlqpRlEMIIRixjnHCucR8fGeXoq9AUpAVzjivPJOxYtCsqnlG1DFGrWMIIRmS41x2v8ZsfCOtX7NHOYNNQqQjXApyiJIc3rNdh0H0z7RzAhdYQiKM3FNe4CC0VY3Q9AYaNhVrguP2OZaShyRPiTcKBJ7Iccq58kxesU2ExqelauRFBSkkY9Y0JTlEbKJdYRqDQZmE0PRo6xo1vUpPtw7l9TR1leXkIdP2BaSwyIkiF9w3mI1vUFdrJIS7eBSbZQEc4ZATRYasKVaS2QMrUn8RiAlZTeYYsiZwcLGwOeFcJDBdamp5l3fMwmbUmmamrwtzVCRELCR3KcohsqKAJdLQI8CT5H5ftXl3v28qhbsiQ8Uax6B5kuyvI7cfUkN4p2DhZsaUMOKZs75qapUJ61SqZSRspp0LdHWThl7f5emTWJTkCOfd15/ZYwnQUlVC08MRLrZwOOVcZdI+jdqWRLEJ0ycw+6ZDo29khqZ34P1pUg2qYWuKshwdvDfa1cwnt+nq1p4lV9IRbeMIj5IcISsLPI5vo1EICaOn8qjEYIyhsfQCQlperi/qJgR+Z2tgOkWXN/6DbzD5tWn89S7v/ac/ZO2DJbKjOc7/i1c5/Rvn8Yb6sfFt88kxbTDacO3//S4P/uFt9FMLfOXcMG/9R79M4XgJHStu/p2PuPM/Xj/0JnKTBb7xH3+H8tlhdKJ5+I9v88l//u6+3x99aZy3/qNvkRnen7B49+9d58b/98NdbdwPVsbmpX/jdU7/5kXibsTH/693WPzeLCd+7QwX/vrLlE5WUkNu+/xq4PRvXqQ1W+fu/3Sdhe/N7r+Yf0EYe32Sr/7vfpHMcJbF78/x4f/9R0TtiPHXJ7nyr7zG6MsTWJ696z6MNnQWW/zwf/9d2gu7Q1nn//IVLv2tVxFC0Jqt8+7/5fs0HhziOhUw8yuneeM//CYAfrXHO//n77Fxfe9wqp2xufw3X+XcX76y7ymjdsgP/oPvUr97dHdq+dwwX+uPy8b9Kj/6P/whQgou/cuvcPLPn8XJu7vG+vFfOsmFv3aVpR/Oc/t/+JTmw6O5iXumxWJyl/PuGzi42DicdK6SlxXWkwUC08VgBkbHhH2SohgiJkTpZKACfBjCfuquJ3KUrGGksBi1jlOUw1TVEi1dI+7XsZGkGWCbWhwlOUxGFPB1h8Xk/r62ieyXOsiILBIbS1j9n5tGU2XwXUc4TNvpQqj6Ln2FQhuFIukruu5NQu2YBjW1Qs4upZlNuJx1X6Ugy2yopX56ssEWLnlRHnhlQNDW9bQO0xF5PAkRj5PbeCLLiH0MKSRZUWSvZcaYrY4xnCE0Pk+S+ywm9w5MmU5T32+REQXG+lWmS3KEl7xvUFMrNNQaofFRqMGC6Iks2X6l75wsodHU1PJP3eABWFMLjKuZdAEXghwlLrtfYzl5REOvEZuob4hmGbImGLdP4JKhq5t4IndkTkpdrfI4vsVZ91Uc4WHjcMq5wqh1fNAXm5mQUlg4eGRFnoKsUJTD2MJlOXnIE/Y3eBw8StZImnEmbGS/4KiFTVbkd7S1IIc45Vwd1J9TJCiTEtljE9HU6/uGQ2tqma5uULTSUiFFMcRl7xdYTh4NeF4SiSsylOUo4/YJsqJATESiQ3Ly6N6xrmkyG9/gnPMaGZnv1yYr7/qewex416ftC7R1jbn4Fhtq4UBeVs+0eRRf57L71sAgnbJPMWSNs6GW+veUGvISiS1cPJEjL0tpyE3kaeoN5uM7QBrSWrnXpnIsS/XxwaG+7TjQ4PHbigfv7/3CSFtiuRZO0SNTyZAdz/Pqv/Um098+3SeialScYLRBWALLtRGWIOnGtBdaexsSQiAdC8u1Uma6dTSXmoDBcUKAsA8+zmiDjjU60UhLIKRIryUYTHyHnWOvNggr7RNpZ6icGcYteVz5V14jM5xFJ5q4E6FVet+WZ2FnHCw31fx55d95C2FJZn/3PmiTtkcKTHwEA2iT7dz/b+FYmEQh7P5PS/aNEp16aw46lRRYbtqXufE8lmczeWWc1/7dt6icH0ErjQqTAYl4cxxIW9Jb69Jb33vwCUtiOVYqFuU8Zfgd1J5+nwKpB++Q43SiUxJ0/5mmP8XguVpOOkaeBUKkbbZci+KJMsOXxzj5585y/JdODrw+KlSDsW5nHaQjcQseJ/7cWdxKho//s7dpPz588TEYVpI5CrLCcfs8lrCxsZmwTjBqHRtMCraw+6EuQUTAbHSdrCxyQhytYjpAU69zL/qQc+5rlGRq9GREjuPyHFP9LKM0m0sOCM47PCKHXMYRHqedqwxZE32Pjtx9jj5s4XLcObfVD2ZTO1qTmIiH8bUDd96L8T2KcoiKHEMIiYPLcfs8E/bJwSJn9ftMINBo1tRj1pMFrnrfxDqihpEncpTl6EAu3wyEMnfuccXgZzrWNwt5nnKu4giPh9G1Xd6n7QhMlwfRxxhXM2odTz0RwmXcPsGYNTPQbEp700IKuaNfN0NiXwZoFLPxTTKiQEmO9IXsUi9bzDkSEyMQad0kHMDQ0hs8jK9xwX2Dghg68nWeJA8RSE44l9PadMKiZA1TlENsFbo0A2/l9ndFH4GcXZRDXHLfTEnlWGmpg33et7wskZfp5sv0RVd1/3+B6fJp8IN9DdLAdJmLb3FOvE5G5BBCUBBlzjqvpgYUyVN9lhrjs/F1XJHhlLh6pHlAICmIMoW+xxK23r2nV4pNEUGRpo1hYVG2RrkkvsrdSLCq5g68VlUtcS/6kDPuK+RFub9ZKDAjL6CN7ht/Zv/5ZltD3Gy6FsSBojKVwW+9gGrpALmSjbQFli3oNRPicOegsDM22bE85//qVWZ+7QxJL2bj2grV2+v0VjokQYJbdCmdrFA+M0Tci2kv/HR3Ha25Btf/6w/SEFTRxS16ZEZyHPvGDHb2s8fihRAc/9ZJnLxLZihL+3GT5XcX2Li+RlDrIaSgfHqI4790ktFXJtM+HM1x/q9cYePGGu2FJrmLx9PMpSfVLSNFCIxSSMdGRwnCSiucOyMlwoV1TKKRWZfMzChojbAtkk6AO14mafbQfkjS7CEce1DlGyBp9rYMpm3IjuQYujjK1X/9dUqnKrTnG1RvrlN/UCNs+AggM5qjcnaY8pkhVt5bfKZQ0YuGihQLf/yIzpMWbsHD6T/boUujDF8cRcjPrvJq5xyu/quvpcZfrFj5aImV95/QfFQn8RO8ksfIS+NM/8opijNlpC2ZfPM4p379PLf+208God+DkBDzKL6BMglT9hm8/oRn4+zYQRqj6Zom8/FtlpM5Ju2TKJIjF/M0GGp6hVvh28w4F1NdGZFPDTwh943ha6Pw+yGJgwitmxPyUQqa7jpW9BfyfujrsCrOHdNMxdOclxm2JrFFGt5y8HZc35AWPFxN5pmNbyARhKZHThQPOHuKihzjtPPywIALdIe2buCbDtrsTNfdDGc4IjPwIjjCwxYOx+2zVNUyG9v4WnvfU4O70Qe07QYT9gnypIvE5ljYC8YYQtPrhxq+PITdtq5xJ3qP087LjFhT/ecjccnsSKNWJqGmVpiNb9DSVbq6RUEezeCB1Du2kNylZ9pM2xeoWKlxun08PQ1jUoHEjm7QPEQQL9XHcp+D+yVAbLVAkRxYoNRgWFWPkbHkhH2JvEwNEinkrrBVOg+0WIjvsZw8ZNw+caR5QGIxZZ/mpHOFrCgiSMPDHd3cs3Cx6Ht6PZElJ0rkZQkpLDyR44RzibpeJTpgzBk0a2qeIOwxY19kxJocZEmm883uPjUmNVN906GuVlIjX0Cu7DA8kyNTdJ6JtHyowTN+KsvwsQzGwPyNNtUnO12x0pGc+LWz5KcKdJc73Pm713jyw8eEe2ikZEZyeGWP3uoh1aY/ZwQ1n/k/fLTjb9mxHMOXxyi8AIMHAaWTFYw2bFxf5fp//QHr11YG+jQAax8us/j9OV79d9/ixHfOIB2L0ukhpr42TedJC+HZ6CAmc2Ks76mQhEs1MqfHka5NXG0jbItwqYZ3fJhwMQ3R6CACAfZQgXijhTtWQro2quPjjKZuTne8QrTRInduCh0ntD94gA52W8iZ0RyX/9arDF0YYfGHj7nzP3xK4351Vx0q6UiKM2WiVvhTJbcbZajd3qB2e2e46vxfvcrQ+ZEXYvBISzJ8eSwtP/Lbt7j7P18nqO58yZ/86DHr11Z44z/8JvnJAtKWzPzKaWb/2T06i7vDfXshMj4P40+p6RVGreOU5RhZkUcKm8TE+KZNXa2yrhZp61qqyquWuRW+gyWsvoDdUbyDho5pcC/6kBU5x5AzScUaJWsKfQE3mZJXiQlMl55u0dI1OrpORzcOzFCKTchcfJPl5NG+3zkKDHuUSHhaxkNCkyp3oncZtqYYkpMU5RCuyGAJC20UgenR0lWqaomaWiEhRmJzN3ofV2T6KrJ7hx7zosx59ytU5DgANb3Co+hTWvrwLC1PZJm0znDGfalv9LiMWzOHGjyQ7vRn409ZVwsMyXEq1hh5WcYlixQWBk1iYkLj4+s2bV2jbRp0ZIvYjiGRpOq0NmiDUT+9kgktXeV29C6j1jFG3RkKooJrUmM0NiEdXaeqllhXTwjxEY7DY+6zES2BEHStNijJnpV3tyEl/y/Q1OsMyQmGrPF+aHUr5KSMIibA1106upH2m64fKgHRNg3uRB9gCQth2xil9tws7o904CqTEOiDdYI2uS8tXWPUOkZZjpG3yjikgoyJiemZFnW1NghDGzQ1tTKYB2IT7snHA5iwT3DWeQ1PZFEkLCYPWIzvHSoqKJDkRYkz7iuMWyeQQlKQZYbkxKFenjRNfZ1u1KBsjTIkJ/r8nGJ/vkk3VDFRP2u1SUvXaKs6XdNIw2YamqsBQgryI4pu7QUaPL12wpgj0Urv8u5AuhMbvjRKb63Ltf/iXZZ/srAv7yWo9giqR4+3/ayjt9rhxn/zIWufrOwZSvLXe9z7n28y9uoU+ckClmcxfGkUO2MTrzXRscIdK4GxUEFAtN7EruRASFTXxy5kMVGCavWgv5i7YyWcoQLReguZyxBX2yAFqhvgTg0h8xniRpe42iYeKaL9aF+ytOVZjFwZY/mdRT79L9/fd7HWsab56IvXCflpwSjNkx/Mce+3buwydtIvwOoHSzz+vQdc/luvImxBdjRH+czQkQ0eSCe8qlqmodb7CqWpt2OTDJuws/p0YLqsqNkjn1+4Nt7MKMHDtPBlXa8SjMG6qBIv1tMQFJtC+/2AQJ+LcBQoks8l1V3YFt6pcYIHWzpa3tQwWJJgfp2l5BFrLPQ5FnLQZxpFYpIdBElNsiMzbi9ILCbsk5TlGEIIQt3jYXSNht5dT3AvhMZnRT1iVB8bZNEU+ynXRyGzGgztvpG5nDxC7rgv+uEHPXg2slSi8vVvY5KYzvVrGJVQeuNrqMCn+ZMfYPZTIRUC6XnoKNoyKoRAehl0GDzjwr43IuOzlDwifOMEauU+4fx8/x51f0xHGAzu5BTF199EdTusfPIhdrFI+a1fonD/Lp2b13fXFtyElEjXRYdhmo2oHlNlBcfKQRgjzLbivOgBR+yoApGh6Q3esco3vkPnxicktT2M5H6/Ga0HhZyFZYGQ6ChESInwHCwrg4ljrGyOpNVAehlUGKRibNJCeB6dpIPvzLOkF3AzZXSvh5AWxiiMI4mtVJ1bygI6CIgdWPHnDnxenshx3D438BbV1CqPomvEB4RZN2HQdEyDxfg+w9YkLhlsXPKyxBG7kYSYqlqmrtawcfplR56ab/rPZq/5xvYsjl0poRJDr350qZJDDR7Hs9hY9Kk9CWht7N0ZQgqWfvSYJz98/NOQvvnSYuX9J6zvY+xsovOkRf3uBvnJtNBg4XgRO+vgP0lfonhtZ/ive3O3IFRc3dqVRKtNotW9Q4adj3cuhp1PDl4chRD49YD7v33zmRbqP+0ImwFz332Av7G/8a4jxfqnK5ypXyA7lkc4kuKJ3UTA/ZC9NI13bAQdRASzK1hDBYLZVdyJCjqMwTiULl/AaE330znAkD07hcy4xBstgrk1Cq+dwSpmCGZXiVbq5F86iZXzSNo+3RuPyb9ymsq3rtJ+7x6t9+8jsy7umVGC2VVC0SNzchzvxBjCtujdXSRea1J4+SRWOU/waIVgbveCn71wDG96FBPG+LOr2JU8wdwazmgJkyiM0uSvzICBzqdzGKXIXTiOdB3iehv/4QrF105jlfIEj9cIFzfIv3wSO58h6QRpuy/PUPnOK7Tfv5+227PJnJkkmF8HIfBOjJI9NZG2+/5Seu9XTpAZKeLPrqIePZuYqC1cRqypAcehrtfo6sYznSMyAaHusRlRSY0xe8/slP1gMOmCdAg/xx0dw6iE2h///mDR6965Qe7CFQ4iXslMhvylq/Qe3EW1+8WYC0VyZ8/TvXMLHbyoEJlBZy1CO9rboyIl3rFporUV2h++B4BqNfHnHiIcd7d3bxvsUpnMyVN079zChGn2oBipIMcm6N65CQeI4j4rrHweYe29hArbJjtzGhX0cIdG0ElMXKuCMYhSGZnJYGXzyGyWYPExMpNDuh5Iia6uYZTCymbJTp9C9To4I2MkrSaJVsQqwRsfQ4cB7ug4tlKEa8tgQA6NoLqdLaNpHxTlEPk+WV8bxYZaPJKxsx1d00xFP/vcV1u4RzbiN6FRRJu1/Z4F2pApOBTHPfxmTG3haI6UQw0eow35ikP3ACtKhQnzf/To58bONhhtDvR2bULHiu7KVojPKXgpqfdLAGMMjQc11j/9WRCZ/GJgjKG73GHjCH0SbPSIu1Fq8AiBWzoal8UqZCm+eprm23cY+pWX0UFI5tQE0Uod78QYqu0TLmwQV/thyfNTxOst8ldO0PjhTeJaB2MMSasLGEpfv0T9Dz4h//Ipqv/8Ayq/dJXg8RrxagPV8undfYKJYpTSSNfBnRomWq6TPX8MIQRxtUX+ldNYc2vkLk0TPF6n+OZ5ovUmuhtua3eGwmtnaL93n/IvXUGHMd6JMeK1Jt7MKCaI8edWiattsqcnyF2eJpxfJ3/1BI0f3CSppQVgk2YPY6D89UtU//n7FF45Te13P6D8zSuECxtEaw1UJ6B3dxETxqhEIRwL71ga2s2emcLKe4RPqhRePY2f98hfncGfXaP41XPE/eOPipRwvJX2H5hen/x6dGylLafY3MW+UAhB9tQZil/9GnapTOVb36b9wbuo7u7QSebEKfKXroBlEcw9ovfgHqWvvEX+pVfwpk/gzz7An31E+a2vkz1zDvf4NL27twkez5K7cBnv+DSohM6tGwhpUXjpVXQcIV2X1gfvovwehcsv44yMoIOA1kfvIxyH4mtvAKlRFizO72oXQlC4+gr5l15Jkzcch/YH7+72SglB7sIlsmfOgdZ0bt0gadQo/8I38aZP4B2foXv7BkmjwdA3fxmrUiEzc4L2Jx+SNBvkL7+EMzaOCQPa1z7GmzqOOzGJcBzQmuY7P0ZYFvmrr2CXSsS1Kp1rH+OMjJK/+gomCrGLB2RCGYMOfaTjoOMI1esibBvpeqheN+VjJkn6bKSFlc1hkhhhWan3hjTJREchwnHRYYAKetiFElaugA4DhO2gfB+jFcJ2kK6HUQrhZQaFjveDKzIDHpLB4Otnp5mk5U82b7dfuPmZz/J8SGLN4vUGmZJDdf4FZWnZriCJNEE7wc3sn8XQWWrTW/vZrFvyeSFsBHSW24cagUYbEn/LmLQ864VwTV4EdKJpPKweiWj7ZwYmHe9H0dZRoRoYvEKA7R1NBE1mHIzWREs1VDdIJ34pU9Jj1sNECbmrJ7CLWeyREla1TUzq6QsXq5g4wTs5RuHlUyStHnYln2Y0bLSInlRRfohwLJJmF9ULiFb64chEk7R7gzGrg4ik0SWpd3CnhnGG8jjjFeKN9DpPey6F54CBcLmGavs7251x0UD+8gz2UAF7pIjqpfXG0nZvYKIEb3qE/KunSeod7KF8Wp+sll5P9frtrnfQvYBoebPdCtXyB5mVJooJW12i1QaZE2PYlcKOdj8fz2zrnZTskz1yADIiT1ZsSQaE2ke/6PpYxuDPPkR4Lu7kMRo/+N6+YQ0dhYSrK1iFAvmrr9C9fZPOretYpTLNt39I0myAMXRv3QBp0fzJD1DdDu7kFKU33qT38D7O8AiFK68QLj/BLpXY+Ge/Q+GV18jMnMRoTfbMWYKFebKnz5Bt1LGLJeLqBr17txn5839x77IRxtC9fQOZzaCjiM61j/e/h16PaHkJZ3SMwuWrVH//n9O9dQMdRTTf/hHaTxfC7u0b2COjtN57G5Mk5C5cInfxMsHjWTInTpFtt5GZNLTT+P4fU/nl7+BOTpGZnsEqlog31smdv0i8sUHu4iV6d24Rri4z9pf+8v6PIknwF+bSd0mw+x62Z9YC4dLCrr9rv0dv7kH6e//v4Y7jYc8F5qlz793Anb/KI5TweBolOTIoWKxRfSXoL8bksV2LsbMFho5lkVLQ2TiaFtiBd6k1YCCJNHG0v6fC3+ihwp8vitsR1H2Uf8Q+eTqf9cth72CUwV/7s8O5OgqMNvhHNO6N2aZb0dezOgriegfVDhj+jTdwxivoICKutxn65ZdxJtOQlgBk1kN1g9QjkihUL9WbSS+eGiDCkkSrDUyiU+MJ0L0QEo0OY0ysGP6NryLzGbJnJ8lfOUH+6kzqkQnj9DtKo3sh/sMVgocrSM/BJGoX0T1pdEmaXYZ//Su4U8PoMCbeaFL51lXcfngOwMp66F5qTJlEpe3Z7CcD0nWQtkW02gClB94Y1QvTsFicoIKYkb/4JlYxS+b0BPmXTpC7PEPm1Dg6SjD9dqteSDC7in9/Cek5oBTafzbXvUHvkPUvypFnKtBo4zJpnxroDhljaOjP0WtqzNa/PSAsm+Irr2OikKTZHHBMBt/fdmxaR8sMNIWk66HjmGh1he7N63Suf4JRCVF1A9Xrono9hG1jZbIk7RbR6jLNd39CuPAY6XmobgcdBKhed98aXam3wKQG9T73ILNZCi+/RtJqojrtlJRNX3pj+73AloHb/ym9DLrXJVpZpvXe2/izD8EYorUVdBig/R7SdZGZHHGtSriyTOMnPyCubSAdh6TTQfs+OjjES2j6App73cN+BsnTf9/+TPY691HOsQdiwkE4VSBTOYdnWHhyosQx5ww2biq2aoIXXpLiIKhYU3/iE/YSOtUXVDxUJwZpC9ycRbt6QEgrSHZkIP0ckPjJkUULv6ww2pD0vjx6Hl8WxL3PuZ6X0tT/+BrCthj61VcxsaL5g1sIxwJjMHHS11uyB78bbVLDpq/bFC5usP7bP04/1+l3Gn+Sing2vn8DkyjQho1//DYIgQ5igsfrhL/1w3SOjpLU69JfdOKNFiZWVL/7USqHsFd2itI0/uR62u5vv4yJE5o/vr2tnf14/7bfjdb9c6ebg3Cpxvpv/yg9nzHoMKH+vU8BaP7w5qDd1d95J+U7+BHaj1j7rR+BABMmhI/TosFGm/ReY0XtDz7pt1s/M/k2MTENvUZZjiKEoCxHOG6fZz6+Q8T+vBaBJC9LTFmnOe6cH+yGA9Nl/QusW+aMjOJNn8AZGSFz4iTh8hLCcZBeBpnLDYwEE8egNdnzFwkXHhOtrqDDEGHb5C5cJJyfJ27USOo17GIJHUWoTnu3YaI14doqdqWClc8Dgmh1mXB5iezJ00jPwylX8J9BEMudOoY7MQVC4q1Po1rN9B4yWaxCMR2PgA58pOeRu3CJYOExSb2G6rbJnj2XenXm54jWVvCOT2MVCunYrm4AZstjacAoRfB4FnfqGFY2mxpE/hPC1RXyl64QV8eQ2f1VjYVlY2cLJH4HhMQku+dRIa2tQttSYmeL6DhE2mkYTMfPpmC+eU5hO+joYGOso5v4uoMjU12qCfsULV1jQz05MCnBxqFsjTFjpwV0hRAYk2ZetQ5J6X/RSCLFxmyXKDh6ePlQH7uXs9Jq1QdMEkZv7QB+jhRptfDPr0+yokhoeui++JjB4OKREJGXZdq6ARgcXCTWjkrYFg4GnabiPrV73XUfP6+hthPGoI8iBvlZLxMlmCih/eEDVKuXGjXxzonoaVFKE237XJvUc7LH59u/t91LYxKVGhT7tAdIPSdHafdHj1BdHxMrZCzJyByRDnCkRxB3d2TF7Gi3MQjfIGCQTmuiJC0KGackX0vY+EHKT9qv3a7IEJvoyO0+CIqEtWSeMWuaHCWEkJx0LlOSI9T1Cl3dTK/Vr0DvCI+MyFOwKpTkCHmR6pUYY4gJmYtvPTPp+SiwbIFKDNHqMqazLXFBSOJajaTVwmiNiWOa772DOzpKXKsSzD9O77PXpf3xBzgjo9APcSTNBp1rH2GXh9JMUL9D672f4E5MYdmSMAoJV5ZIWun1goXHKe+r2UCHAc7wSDoXJgm9+3dQfg9p2zTf/UlK4h20EWTGwyrlSKptgsezaYhB9gVhbZuotgra4IwPoZMurY/ew6kM0XtwF5n30gzUWpXOzU/xpiZwRiskrSbR+iq9e7eR2SzCtog31ug9uImVL+OMDxGuLuI/up9mp1mSuLlGXF0jrjdIOm3sUhkd9DBK0bn2Md70CTCaxo9/gGrtnczhVUbJjs/QXXqE5WZJ/A5WJo+KfCw3Q+J3yI3P0F2aRYW9VD7SzZAdmUTFEcKyUKHf5/XYCCHRfaNJOqlXxagEIfviiUKg4xAnX+5ze7qoOEBaDir0ka5H0muT9FKSuG86rKrH5GUJW7hkRYFL7ptU9TQNtY5vOoNae5awccmQk0WKcpiSHB5ogxmTylpslnz4ouDmLEZP5OlUQ9QB0aencajBE3YV7VpMt/YlrlItxZcmDDTA9nDG54CirJA1eRIiXDL0TAdPZKnr1VTMiQaGVO22KIcIjI/cTM81mhAf2ZfBevZ9xBeH5wgt/6lCtPTFuYlfJKLltN0Si1E7reBcNyvkZRltNIkJcUSGyASDkhOR8XGER0FWSEw0qKbsiizj9kk6uo6vOxStYaIk7B9nEZkAV3gYUj2XzRIFG+rJgSUcngVNXWU2vsFp52VyooglbEbsKYbMeKp6PAgxCERftNEiLcEiEBij8U2HheQeS8mDA2X4D4O0BLYriHyN4wm0AssRnH21yP0PW+TtHhNThgcrAiFBdDbwa2vYtkinpcRAa52gsYaKDU5GImS6uYnWVojWVpAWuFlJHGjUxhLJelp9/sIbJR5da2CWWkxdyvOg00opJkknfVe79XTaUwZdWyGsrZBE6TWU1gSzD/e8J3u0gntsFKtSRHd9dBCmHhcXrFJKGI+qS6hmB+E6iIyDyAi04yPy/P/be7MnOa4rzfN3fffYMyP3BDIBJHYQXESKOymRWkpVkrq6VdXW1Q/dZjNj1s/zMn/F2NjYmFWNjc3SY1YP01XdKq3URpHiIu4rSIAAASSA3PeMPcJ3v/PgkZGZyAUACUoqVnwvCUR4XHe/HnH9+Dnf+T6UvI6StombLnHUIgprqIMZ0vljRC0XKQP8tTL6gV5UJ43UIlqTn2I4/aCANpjwq/ThPEpBJ7rRgijCm53etj7KMMSZvHzLaxS6Dn69jIxCtHQWoWmErQYCgZErEm1kfjYyPEJBz/YQRwFCUdCsNAKB56ySGTqEjAJCp5UoHJspIreJlsoSNKqYhX6c1VnSoxP41TWs3kEit0Uc+HjVNeLQxyoOQxx3Ah6QLITXsESKEW0CVeiYSophcZgB9WCisr5FvX/jG520jyc320iGVOM1rvvn/6DZHUUVFMfSaKZCtt/CqYU01m+vEnHLgEfVBf0DFjKS+Et/mrdGxVBRbtOG4suCSIYE0ierFABBRIQl0hjCxmzrImyYOjpxg5SSI/EpUQlw2WrgeCuhqT8mVOufn9txF5tQUDCFRSOuEsvEG0sVGhklDwgKor8TMCiiD0jawLdmQDYUpgPpd546TWGRUXuQUqIJfUsaPlmODcVGRHdvTZDELIbX8WKHA/rxjlrwho/SXg9cGx0wa9E8i+GNxNH7cwQ7miEYP51BSsn6gsfQYZs4lEx90kAzFFRNEIYSw0r+nStqjJ3OMHelxcBBCwTMXGwweizN+mIiFDo8kaKy7DN3uYmUSabowPEURkplecph8JCNqgquvl9D1QWqrhAFMUZ7f3ZWZeKBHLOfNhkYs1AUmLnUZPCQTaMc0KpFjB5P0aqHTJ1v7Cqho2ZToCqo2RRCU9qZmApx08UcH0LoGlGtidBUUEQ7G5RGhiEibRNvyRJq+UzysNeTI6q3EoHW2WVkHKPm06iZxNA6briouTRCU9H6C20umdzkAX0ORF4Lr7yKjCPCVp3IbRG2GqAoeOVl4ijCq2zKOghVJfYdQqeJUFXCVp048AidJq2lKWQUIeMIxTDRrAxBq07QrAKC0G0Qtuqd427MXkVGIXHoE/keceDhlpZ2nJcvXa75H9GMa4xqR9uGxQrahuLxHt/pWEbU4zIr0QxL4RSO/MMKCceRZHmyTqvi4zVDzPTt3yNuuaXvxmT7DDwnpvwnGvDoaR3FuH1n3S8DEtdciRslBNqYmCYVQkJWo4VOOcCRTQSCVtRo3wo2mmG3smn/GMHObfi8CIGRu31yaBd/eggJaMUNWnGS+teFkcjeC516XCarjtGKa7iySZ96gFq0tsOuIpAuzbiGGzfb3mI6eps07EuHvNrPejSPikZGKVCJVj+TncWtIJGsxwvUvHVSSo6C2k9GFLBEClXoKCiJ9xcBvnRx4hq1uEwzruLJ1m0LNu4HK6WSK+rMX22R7zdQdQU7I0jnNcyUgmGpqLrAyqhYaZWDJzNMPJClXgqws0kHqG4q5Pv1JLMjYPiITejHSZYnAt1U6Bk0WJ52SWWTcXVDIdOjYaZUTFvBd8FMKxi2yoETaY4+kKW+7pPt0QgDiZlSSec1ckWd2nrA6LEUy1MOiiKIdimT+7MriJUK7tW5JOgII4hjZBTTunB9JxFbJArSnS4oVemUcN1r8whDw70y0xlLhhFCCFofX+uUymQQEpZrCedoegkZtUUCFUHc+nyZQRkGhGFS5nOc7QGB1+bXRO5m80Psu7SWpncdyytv17sKnQaRs7NxYrfXNuBXdzdLDvCZC6+wGs2RUQqJmrOSSxTK0RDth+lQ+riySTOuUY9LOLKOJ93PFbx/XhTHUsSRJI4k5fnb04i6ZcDj1ENKCy7BHRCDPivkFvKbIDGmvB3YfWn0zF2whPhnhI3Fc2vddONf2/gRbRO4P2R9dTdsmKYCicro7bTeC8iO3trjqIvbhKpiT0ygWDbNC+f3lehXLIvMVx5EGMnTnnvjOt707gsygGKnSN1zBndykrC8XXXbkXVCGaAILfk+ypi6rJASOVbCGVQ0DGGxGFzDVrIoKNtk9yMiWnEVSYxGks0J8SFOHNDngiuklCwRIcvhDBkljxs3CeVnL8NbRybQentovPfejvcCPKrxKtV4ddvrQtOwT5wEKWld/GTf8dVMhsyDD3U691qfXiJY2lsQUc3lsI+fwL92mdKiR7ZXZ3nKwbAUnLok8CVeK8ZMK8QxBF6MZgjqpYDJ9+vJeymV9XkPpx6xNucRBpLKiofvRKzMuB1NPt+JWJn1yBZ1FiZbpHJqwtdxYtxmhJlWiWOJ78YYlkKzGnL1/RrNasjwRIraukuzElJa8tF1weL1xHevtOwThcn6njp9GqHpND/+CGBXjtoG4vqddYpKz0d6O0scsr2fm1/b7/9/itgvsPkskEhc2cSNml+IMvoXgdCLWfy0Tn7YYm3q9ufjlgFPtlenf8xm7tIXn7aKvJBow3xSEZi9e7PgN6DoCoWJXvT0nZm5dfGHRdjcXIC0tI6evnWAauYtcodu3ziwi/0hVJX02XvRe4u0Ll3cP3UvBIptoxeLpM/eS+WVl/cNeLRiL8XvfZ/1n/yERqWyrWunGbcJtBKWw02xuSaVHeM40c51Jiai0S5xNWWVZrhTSdzd8jkn2t8P6XaQOnUK+/hxGh98cEvvpg0IXSfz4IMQxbcMeFAU1FQKraeH9NmzRI3GvgGPMTxC8bvfY+Ufakxf3OSQTH6wea7nX90MNEsLSbajvJT87tJ5DacRsjaXvH7to02NsOrq9sAwjmFhcjPIaJQ35/aT1yqdf3/8crK/0qLH1HkwUwpxVGPpRvK03aw1Ovu4/O52cm/mgQdRbJvm+Y8TorqqJdwUr/U5/L4EqpVCNZLsX+g2d3QrKZqBZqcT/kwUEDT3UpAXqKaFoiciflHgbcvIAKhWGqQk8v7A0h1CoNmZRLjQ/+zq14puoFmZhPAcBoStm+ZCUdDtbEdNOmhUNjlHNx+Spie8ozYvKXQa27ZVNCMhTjuNO+6S3AvNsk+zfGddxPsGPLqlUDxgUy8FaMYXz5HxKh5B+8a44SiupXTCfdqA7f40Q48c+BfH4fnnhuby5mJhFiyyB/OsnlvauwtMwNAjB0gNpHd/v4svFLHjUHn5JdR0GuvIkVtuH9Vq1N56C29x4a4taF9mRLUa5d8+j97Xl2SFboFwfZ3a228RrK7ectvd0KyGtGpbu+E+0zD7wmvFLE9tuQHfwT6s3kGGH/4Llt//Lc2lqc+0f6Gq5A+fIX/oHqziMKvnXmbtwus37WeIvnsexyqOEDoNrj/3f+46lp4tMPTQn2Hmi0l31uJ1Vs+93OmUAhh44BniMGDl/Rf2DAS+CKimzegTf0lreYa1C69/5n3bxRGKZx7HKg4T1Mvc+NV/3va+Zqbpu+cJUoNjWL1DXPvZ/4Fb2hmUC0Wl754nyB++BxlFBI0Kyx+8gFfZ/K5mDx6n5/iDzL783/7wAeIW7B/wmApGSiGd06mufPF6LF7ZoTFXo3hmAEVVyB/pYfTJcWZevLarzo9maxz5/gl6ThS/8GPr4vOhPl3Bq7pYPTaqrjL2zQmW35unMb/zaVwogsLRXo7+m1Po2W7m7m5DIkFVUVQNFJEQIn1/F12dKJH03y+AURQUy0ZGEdVXX9ldjK1tSol6E89Oggz8RP9lYywz8RPavp0k9rxt3kBC0xIbgLbirAyDzXG2HptpJloyitLZXoYR0t/ORxS6nrwv5d7mmreDDfVbVUUxjI6FgPR3KbGEIfGt5lfVEsE+p0X11Vd397PaZ96k73fORypqst3N+jdxnMzvlkyW0PVEzK+t2ivDcOf8qmpindDW6ulsv8v5CsNI3peyPc5NKt1CSbykPkdbpoxCKpPnaC7e4OCzf4PQdmaRnbV5Ft58jv57nyY1dGiPkQSZ4cOk+kdZfPtX+I1yoosTbT//yuQ5ZBzdFZLznUGg6Mau53cnaK3M4lV/zsBXnsXqGdzxfug2WDn3Eumhwxx89t/teW30TIHCkXupTJ6jPj8JcUzQ2J6Fba3OEbqtz6QtdDexb8Cj6grlBY/ygvcHeWqTsWThjVlGnhjDzFuYeYsz//0DCFWw9vESfj35EWm2Tno4w8FnDzP+7aNEXoTUJOqtiMsCjJyJkU38qhRNTf7qKnZfCtXc/Hx6KEP/A8NEbkgcRsRBTBzGRH6EV3H3zTp1sRPOWovld+cZ++YEQhH0nR3g7H96iKv/dJHmQp3QC1E0BSNr0nuyj4l/c4reU/0Edf+2PKgUXUmCKUvbcW1z4/nOGi80hd7T/aiW1r6mm9c2dEPctdaXXntI6DrZBx8ideIESjpNsL5O7fXX8aan7ngsY2CQnj//C9SUjZrNsfbjH+Fc/nTbNmomQ8+3v4MxOLDlRQ3FMqn9/vfU3nozGWtomMI3voGW3eRtCcNARjGl536Oe+N68tFCgdwjj2IdOoQwzIR0OjdL7c03CFY2CZ7myCi93/0u5eefxzoygXXkCIpt4U1PU/7t88St5ElT6+sj//gTmGNjSN/HuX49Ecz7jF8DxbTIP/4E9okTKHYKf2Ge2huv4y8u3vrDN8EaH6fw9WdQUimUVIrVf/j/Og7jG9B6euj51rfRe3s7rwlNB1Wh8uKLHZ6MdXCM/DPPotqbjQDCtIidFus//zn+fOIar/cPkHv0UYzRAwhDhzDCvXGd6ptvEFUqnc/ax46Te/RRKi+9RPr0acyxMYRp4ly6ROXllzoBkj44RP7JpzBHRohaLZwrl1FMi90mWNEN7P4DqIZF5Dl4lRXicIv1jmFhFvpRDIvYd/Eqq0RbylZx4BM0a3sGrRvlltB3du5fCIxMD0auSGbkKHEUougGeiqHW17u3AONbC9moR8Av17eMY5q2hjZIm55GTNfRLMzxGGAW1rq3PCFqmEW+tGsDDIK8GrrW1rGbw9CKJg9A2hWmjgM8WtrSclo431Fxcj3oaeyiVVNvUTQqNw0F3Uib4+ymJREnkPg1HcN6lQrhZnvJzU4hmpYSCnRU1lCp0HcLkuqho3VN4KiasSBv0ObTqgaVu8Qfr2EopkYueQ77FdXN8uN7euiZ3sSjadGFa+2zq7tfrfAvgGP2whJ5TSiUFLfwyn9bmPlvQWW3plj7JsTICA3XuCh/+kJypMl3LUWSImRt8iO5bH7UsR+xPXnrlA42kvfvTuj1K1QDZUj3zvBgWcOo5kqqqmhWhqapaGa2jbTzoPPHGbk8YNEXkTkhYRuSORFBC2fy/9wgflXpr7gmfhywa97XH/uCn1nB0kNZVBNjbFvTtB//zDV6yWCho9qatj9aXLjeVRLw11rcf25K5z49/egWfs/zWRGc9zzP3yFzIEcqrl5TVVLQzNVRLvkqdkaX/kfHyPyIkIvJHLD5Pp6EY35Gh/8L2/gVe6OdsufKoz+AeIjEzQ//jgxa3zwIXq/8x1W/+s/7iAc3wpBaZ3y87/GGBmh7wd/1SY5b+/8ix2H+jtvo1jtG62ikDpxgvS99xFuuYGG5RK1137feXIVuk724YdRc/mOsB3QUQhuXbxIWK+jZbNkH30Moeus/+ynneyC0DWM4RFyTzxBWC7TeO8dhG4kGa12tkixbXq+8U3MAweov/MOUaOBdfgw9omTHcfwO4IAY3SUqNWk8eEHCN0g9/Aj9Hzr26z9+Ed3PKa/sED5+V9jHZmg59t/tutTfVSvU3vzjSRDAghNJX3vfZhjY4kn1sZYqytUX3kZ0c60KaZJ7sknkXGcKCa3oaRSCMOgef4jomYTvaeX7KOPJZYYL/y2E0woho554GAyv6UStbffTjywmq3ODVLN5ej98z9HzeWpvfUmMo6wjx7DHBvDm5vddh6KptN74quopoVQVFTDpvTpO52ylGZl6L//66QHxzrBiLMyy9L7L+zg13wWCKFg9x8kN36KVP8oqpWm59gDxGFI6dLb7TZwMHK9FCbuJTN6jNrMJeZf++m2m6/VO8TQw9+heu0jMqPHUDQDoarMvfojvMoKimbQe+ph8ofPJq3mmo5fL7P8/gvbWtVvhfTQIdJD4yAUNDOFU1pk8c1fELoNhKpRmLif3hMPJZIPqkboNlh+/0WctbnPPVcARqaXwtH7sXoG0ewMuUOnidxDSeaoskIcxqimRW7sJOnhw6iGxdUf/+02XpVqpRh+9Ls0Zi9j942iGDaaZbN6/nUqk4mPWmZ4goEHnkEoajvjGLN24Q2qN87f8THvG/Ckshr1UkCuzyDbZ7A298XfCLyayyf/74comsrQw6PoaQPN1uk/uz2YkVIS1H2mf3uNC//P+5z4m7MUT/fvO7ZQFbJjefrODOy7HSRlFc3W0eztC0wcRMz2p+78xP6lQ8Lqh4uc/7/e5/R/vJ/MgRyKppAaSO/g6cRhTPV6mUt//xHlq2uMPjVG4ej+ZUs9bdBzoo/swfy+2wkhELqKoqvome3lMjP3p+NU/0VCBgGVl3+HN5vccIJSif6/+mvsEyeov/XWnY3l+/jz80k5ZI/MmAxDvNnNrIQxMooxMkrt7bdxrl/vvB47Du6NG8l/hCB1+gx6sY/yC78lXN8UNgtWlin98pdJWUrKhACczWKOH0LN5gjXN1twFdsmbrWovPjCZrlNUTrlG31ggNTp05R+9Svq777TFpubxRgaRpifpZwqkv298FuCtbWEEOo49P7FdzHHxml9cuGORotdB29uDtG2N9gN0ve3EcqtIxMYwyPUXnstuTYbYzWbuNfbwn+qSvbBhxCGSeXXvyKqbgaU3uwM/tJip8wpdB2tWMQ8cADFtrcFbWo6TVgqbQuEts6vOXoAe+IoK//1H2idT25Q/tIS5sgoN0tTKJoBMmb+9Z8R+y49J75KYeI+qjcuEDoNCsfuxyr0M//6TwhadazCACOPf5/8oTOUPn3njuZ113mMI2ozF2kuTFI8+wTpgXEW3niO0G0kWab2/DcWrtNameXg1//tnllAPV3ALAyy9M6vCT0HRdU6AVNq6BA9x77C0ru/xllfQrNSDD38HYqnH2Xp3V8TB7eXXNAzBeZf+zFueQW7b4TRx/8VqaFxalOfYBeHKZ5+hLXzv6e5NIVQdQYf/Bb99z7F/Os/vSs8Gre0yPK7z5MaHGPoq3/Gygcv4qzNI+Ook5Xz6xWW3/stPce/Qu+pR/YcKzt+mqV3foVXXe+oTCMlqpWi/76nqc9doXLtI5CS3lOPUDzzGM76An7tzgQP9w14mtUApxGyfKOFndncNPIiZl64TulysrDUpipE3l0ibUmo3ajw3v/8GgefOczwYwfJH+7B6rVRDJXYj3DWWpSvrjP/6jTzr04ROiFzr0wRB4nWwvrF3aPkOIhYfGMWt/TZme3EktKnOzUN4iDeNnZrqdEhYO87XBiz8uFi57fv173bcuL+olCfrXH5Hy+g2Vriln79zp7490Mcxkz/ZpLaVIXxb01QPDtAZjSHnjYQqiCo+zQWaqyeW2L6+WuUL6+h2Rqf/pfzZA/mCVsBrT2MO53VJpM/vtQpfwkh0IeLmIdHiBot3E9nEKqCdXIcVAX34hRR00HN2NinDxM7HrX3ru7wyTLGh1AOHeTG81OoSozW34OT6kMt5ojW9+rwSODXPK7/apJCNfntLH+QEP6ErqKP9BOslJGOB4rAGB/CGO3HvTxDuFpJjn3iAP70Iv7c6l0tKYeNOv7ypnmlNzdLHAQYA4MITft8HJZbQM1kKHz9GcJaldqbr+/g0mzAGBwi//TTNC+cp3Xx4vY3pUQxDcyJI6i5PIphoA8Oouh6Iky3BUJRaF25vJ1btCU9bwwOIYMQf2GhwxEKK+Xkpjw+9hnOUBJWK0mw0z5WbyaxW9D7+7cFA18E1HyBwjPP4E7doPHhh3teS2t8nNxjj1N/7x2cazepH0uJmkpjHDuOls0iTBO9t5hwsG7iYck4xrl8eft+Ns5PVTGGhogdh2BLOS9YWSEolzrdP52PBR7V6Yt45eS72Vy6Tm78JFoqi4wjsgdPoKgauUNnkHHczpxopIbGKX36LneDiS3DgDCKEk5YHBH5zs6Sj4yJA6+TJdwNceBRm7mUlMK2QgiyB46j6Cbp4Qns/oNJNku3SA2MoejWbQc8zcXrNJemkVGAuy7wGxWMbNLVmhk9hmalsfsPYuT7EUKgmTZGvg/VSt2VgKczP4GLlDGR7+5SHpPEod8OGPceq7UyQ3Pxxo7XUwNjmIV+/FqJnuMPAmBkChi5Ima+7+4GPKG/6cjqNbfovbghN3555Y52dCs88NeHuPH2KpXZ5IbmlV2u/eRT5l6ewuyx0WwNRVWIo5iwFeCsO/jVzUWsenWdnqLCsa8Ns/S7yq77iIOYuVemWHhtGkUThN6WhS+lMfZQH9PvrhI4dx68xWEy9tyWUle6aHLv947wyS9mceu7c35kJFl+d57ld3fXP7DyOqe+NUphNM0b//kK3h7jQMK5kkjiYPOb1XMwTabfYv6jEvFtGLzWpytc+vtznf8L5fMrHau6TRx6SBkjY0np0ir16TpmwUDPGaiGmrR+eiF+3cNZa3UC6NAJmfrl1V3HVVS93VLp01ppcvm/bE9xaoO9SUBz5gjOhSmUTArtXKvjpN368AqpB0+gX5U4n9zAn1lG2CZq0Ua6PnHTRXoBgZ7i6nMXCBbXUbIpsk/dh97Xs3vAIwRKxkboGqHnc+UfL2Cdq2FOjFJ/J5HnF1abOBrLpMW0N0f6oVME86tIP0SxTdIPnyaqNdsO43eXUyS9mwjKbdKy2CAWf0EBjzAMso8+hprLsf7znxI3dpe6ULNZ8l/7OlG1Ru2N15FbbwBCYB8/Tv7prwGCcH2t49C9pzJsc+/FXbGsbcReABlFt33T2XV/3k0eZu3xFNNEKMoXRnJVbJv8176GlFB95ZXdCc4knJ/8U1/DnZlO2u63toELQfq++8g99jix5xOW1pPz0VSE3GWKpexwoXZCICyL2PMS09aNjwQBMgh3BjxRtJ3H0p6nRLdLRbPSRL6LqpsdLkht+hLO6jx/ago6Mgy28Wk2IdBTGZAxiqZ3nOpbq7MEjcq2LrBbIWjWOqW0ZG2NkrIPoNmJVYaiatBu03crKzQWb+zN2fkjYiP7dTM0K52ckyK2yQ2UL7/b5k/dGf5kdPsLo2kMe7tvkIwlbsm5rYxMFMRMvbXK2IN96Kn9T6t4JEu6aDL11mbbnN8KufHmClFw9xYjzVTpOZD+XGUStxZw5eVFnvxPJ1G1vcX6hIADXynilDxWrm7eiCvzTaqLrdsKdm6GZqbJD5+gsTpFFLhY2T58p5aQ3QIHM1VACAWh6niNEkYqnyyAcYiqW8l2XgMrN0CzNI8M24Q9RSXTewy/Vaa6soqZ6UVGIVHoE/ouuplFz+qouonv1JOnYytD4NbRzAxSxgRuHTNVIPRaeOHuflPhcom4bmGdOoSUEjWfJlhaJ255WCfG0Pry2CfHQYJim6AI7FPjaMU8QlOp/Oy1JOjYoroaN12ifYTQtL48mcfPEnsB/swS7qUpokp9m0GmOT5E6v5jVH/9NlG1jnl4BOPgAHGjBYpAP9CPeXgYb2opyQjc5bVcGPr2Th1FQRh6QjLd56n18yJ14iTps2epvPDCngReoetkv/owel+RtZ/+ZAfnRUmlyT3+JEJRWP3hD4mqFaSUFJ79BumTp3bf8T7Zsdj3kw6jrbIWitLhuXwWKMb2UphQVISuJ4HVF9X8IQTpe+/FPnqM9Z/9hLC8+29CmBb5p7+G0NSk68vZvraquTz5J54krNVY/9nPiJsNECIpyY2M7jqm3JM8mnSJCV1P/A43jkFVt8/31u33CAZlnGQQWsvTrJx7eZtWz5+icbWEPc8l9By86jor514icltbPiPvKPu397xD5Dn4jQqrH//+pmDi7lhn3HXscUyR7xK6LUqX3tnREv9ZzuOPGvDkR1Oc/NYoMoxJF01A0HMwzcRTQ1hZnfnzJabeWmHwZIFjTw8hgel3Vpn7qMSB+3sZf6gf3wm5+tIi5dkmURBvu7EbKZXjz47QO56hVfL49IUFrKzOI//hKEZaY/TeIh//dJrADTn5jRHsvMEH/+0GXiMkM2Bx4hsjpAoGC+fLzLy3xqk/G0VRBbnhFGuTNS4+P7/zZiTgwP1FDj82QORFKLpAUQWj9/cy/lAfcSiZ/P0SlbkmRx4fZOhUAd8JufT8PE7FZ+LJQfqOZKkuOlx9aRGn6hN58bbOoeygzclvjmAXDFYna1x7bZkD9/Xy4N8cobnusXSpwrkfTVEYTXPqz0YpTTe4/LsF4kAyfKbAkccHiUPJ9TeWqS62uPcvxwmckEyfxbXXl1k4n0TOSaCRRcoYI10g3TdGvHIdI1WgWZqn58BZfKdK5DvoVgYZR1jZflTDInBq6FaW8twFDDuPo64Qh5tPvrqdxW9VUFSd3MARGqtTWNk+WpVFcoMTKJqBW18jlxugVZ4n1TOCqltEgYuqmTTWZ1DUpO3Xa+5hsKmq2GcnCFfKBEsljNGB5AK1b/bhagXn4g2kH+J8cgPFNhG6Tux42KcP3477xQ7oA73ELZfaC+/teaP1phYxxoZAgAwinIs30Ef6qL9+nrjWJCrXca/N03z7IuHK3SspbkDNZNGLxU7QYQwOougGwdraF1bOMoaHyT32GM3z52l9+unuC5wQ2CdOkDpzhuqrryZlppuPPWWjptN4szMdro4wDIzBwZ1t2beBYHUFYVnoff14bS6SmskkjuGfCQI1n0crFDqEbGN4GNF2LP+iAkrr0GGyDz5E/a03caem9jg0Qebee7EOH6H0y+cISzvLARslLH9+jqhNeFZSKfTB/RtCdkUcE6yuJPPZW+zwsLRCD2ouvyPY2g+R79BcuEbm4AmM6+c7pYyNbq6NzIhQ1CRzJEQnMySl3CQVCyV5SBNq8m+13Sp/J1o2ysYYyT4UVSOOw9sLVmRMc/4auce+i913gOZiwmFTND0J6u6SRk1z8TqFiftIDR2iPn0JKeO267rYzDxtzEWbDLxzLtrn13ZkF6rans/49kvsQmzbh6JqSEVtByu3HsNZnSUOfXKHTuM3KsgoaF9jndCp3/HD4B8t4BGK4MxfHKQ83WD5cpWRs70ouuC+74zj1gOaJZfT3znA2rU6I/f04DsRM++vUltyyRRNTjw7wrkfTZEdsLnnewd5++8n8Zs3yYZLaFV84rDO+Ff7KM82mX5nlcVPKiia4OJv5nAqPjKG2Q/XefDfHUEzVEI95uz3DlKebXLt98vc/4NxmiWPA/cXmf1gjY9/Ms2j/91xpt5do1Xanr7WLZXT3xnl459Mk+6zOtmk+/5ynMVPyqSLJme+e5CPfjTFyNke1q7VWblaxa36jNzTQ/9EjvPPzXD06SHGH+7j8u92PgnLWFJdauFUfI4/M8zch+ssXCgzfq3O7Ll15j8uEYeS6mKLtWt1esbSKIpAS6mc+YuDnP/5DJqpcurbo3zy6znGHurjjf/7MtWFFie+McLqZI3AiYgCn9BrApLQaxKHAVamD6Go2Ll+NMOmVV3Eb1boGTlNGDqJnoaqE7gNdCuLUDRUw0IzU4Reo338EYFbT9KwMsJtrJPqHSUKPKxcP7qZJQwcnMoS6UMjKMUxhFDRjBRes4QQKoqioagaqpajJZSdTzuKIP3QCaxjB2h+cAXF0IkqdYyRPmQQElUaO27uWjGPPtqHNzmXvCcE+lAvWl8efbiPsFRDzWfQ+3sQmoo/u7zDcydqOphpG+v4QcJynajSQB/pQ+vLow324s8soQ8V0Yo59OE+osof1ngPkixK7oknaZz7EIEg+8gjSbvw5GbpUEmnUSwLNZMBVUtuWgMDibprbbPtV81mUUwTrVhMynOFAnp/P3HgE9USnyIlnSb/zLMIw8SbnkLvaxPQJUStFlG7A0vvHyD/1NOE5QphuZwEMSTf96hWJXacZPtGHWN4BOvIBDIKsSeOog8MfqZgIlhZwZ26QfaRR4l9j7jZwjp8CH1ggNj5LDcfiWqnyD35FK2LFxGaRu7xJ/BXlrcRt9VMFmGZSWClKGj5PHp/Mr9hrZqcixDJ/BoGek8PKAKtpxe9r0ocBMn8SolaKJD/+jPEbS6S0Z80b0gpiRsNonbp0BgZJff4E3gzM8SOgzE01J7fmLBaRbouYb2GdF3Mg+NYhw4DYJ88iZYv7FmC3HsqJN78At78PLmnnmLDmNM+fhytUMC/g/mVUUj56gcY2V5GHvsufr2clLnsDEvv/gZndQ7NzpKfuBc9lcPI9pIdPQYIvPIK9dnLyDgiN34Ks2eQ7OhRzEwPA/c/Q+g2qU1f3NayvRcUTadw9AH0dA6rOEwcRfTf/zX8Wona9KXbClgai9eoTJ5j4P6v4R85CyTdSpXJcx1i7udFa3WW0uV3KZ56hNzB48RRhGalqM9dZf3SWwgEuUNnMAv9ZIYPo2cKyVw4DapTnxC26tjFYTIHT2Dm+1A0k+LJh/FrJRqL12mtzNz6OIUgO3oMu/8A6cEx9HSO/nufJmjVqM9d2eERthuCZo2187+n/+xTWD2DSUnTsPAbFZbe+Q0yujN5mD9awKMaibX7lRcXKE03aK676KZKYTTNwoUSoRcz+eoSgRtx480VDj3Sz5HHBpn/uIRT9YlDydq1OoETcfjRAcy0tiPgKYykOPRwP0sXKyiagm6phH6M1wxQVIXm2maw4taCTnZIMxXSvRaTry5TmWvSLHnkBm3iSDL3UZnKfIuglbi03hzwGGkN3dRY+rRKYTTEb4bYeYNMn0UUxlQXHerLDq2yz+SrSwyd7mHiySGuvLRAps+ivuJQnmlSnmlSGE2hqNvTDELA+EN9ZAdtakstzLSOogr8ZojfCnGqPk5bbjvyY9zGJlnMLhgoqmB1soaV1ZESUgUDp+yx+EmZnoMZDquJG3LgRMRxQLM0h6qZhIGLU1shcOsoioZmpijPX8RvVYhCj+rylST6bz/lBG6dwG0QhR5ufW3HE1RzfQbdzCRPvm6dwKkR+g5mupf6+jSh1yIMXKrLk8nThVBolecJvAaKahBHPrqZuEZviM/dPFFR3cG9OoeSMhMzwck5pJQIVcGbnAOZZFuIEg+3YLWM++k0SKi/mmiXCFXFv7GYuDKrKoqpEyyuQRShmBrShY6BoYRwcRXP1NEKaaTnY0o3edKdXkTRVRQt0QYKphYQxKAqSC/AOT8Jnt/R9nI/uY5stpJk1JYubwnYaQW3GW++3v7b1ojbdx2ScUzrwvmkc+jPv4uaShHWalReenGbtUH2qw+TOnESxTRRbZvU6TOYoweQvs/6L57DX5hH6Dr5p7+GOTaGatuAJPfYY2TO3kvYqFP62U8JKxW0fJ7UiRNIz6f3u9/fPJlY0rxwnsrvXgQSIq0xNEyca9H3gx9sHrPvU3nlFVqfXCBuNqm98Tr5p79O3w9+QOz7BEtL1N58g8x99237HsgNkbt9JiRqNCg//zw9zz5L8fv/ith1caemaH50DnPszknLMghofHQOIQTF738fxU4RrKxQ+d1LhKXNTGT+6acxx8dRLAuhqmQf+iqpkyeJfZ+1f/ohYamEkkrR861vYwwMoqTTgKDw9a8TOQ8Trq+z/tOfELsuxsAg1qFDxK5L8V//681jCSMa773b0TlKHT+OViwiDB1z7GBnu9hxqbz4W5zJSaJqleprr5F78kn6/uqviH0fb26e2ltvkj51avtUxm2Rxn2+b2FpnfJvfkXhmW/Q99f/lqjVxLl6ldali6ipzW5Xv15m9aNX8LaYXAaNddY+fpWgUUYICBplFt/5BanBccxsgZ4BlcXzy/jVVYSS6OJlcgKhOKyeewmg7dkXd7xGQSJDj9r0BQxLIdejUVoIEYroVHl7hw3clUmc9SWiXUj1Mo6IPIf1i29te20DXnWd1Y9e7pSSNDONZMOCQhB5DisfvkRqfhKj0A9SErbqtFaTrkk9nW9nrbYKNG7cB2RC7r5+Ab9eapfzBLHvsX7xrXbQJoiDgLULb9BcnsYqDGBme2nMT9JcutHpbEQmY1WufbR5HltLhUhk6OOuL7C4vjXbKhFCJBIMWYOgXmLt/KvotkeYSuRAZBTjN8L22hSg6itUrkwTOAEy3txH7LusX3iN0Klg5gy8ttZeZjCNU3KweixaS5eZq65i942iWSaZQZ3a9Ssgw21r4+3gjxbwRH5EaabBwa8UMTIaqV6LwIlYvlzFa4SsXq2BAK/ukx9OsTpZY+BYnpF7ejj3oymklIw/3E+qx8Cp+vhORM9YmlSPQc/BNNXFFnbBQDMUassOQoG4XRZyqj7Dp3sYOJ6nNNNAVQW94xnsgkHveIbVazVKMw1G7u3BSGtkilbC95FyG/luN3j1ALfuM/HEYBL8WCrNksf6VJ3muodT9nHqfueLujpZ49DD/RQOpCnPNTn69BAHHigycDzHypUamqnSeyg5tuLhLKvXauSGbJxagFMLkkW9fZPzmiEDR3M4ZZ/STINM0aIwkiLdZ1I4kKa27OC3Qg490o+qJQTwxprH1ozvNkiJU928CQbO3l1JzdJObQe/VUn+NneWZfxWFb+VLAhJFoldt22V9zaz8xp7lLIAohj34k7Wv/vJ9tfC5c39SdfH+Why+/ZXZ+Hqpl5I4LgMpWoYloJ1SiEKMsSxbJvdCnI9Gqvza1iUWPY9TjySYfbqHClFQWZAvc/Caa4wkq9RlyEX2uTYEbuCclwnlbMIfUkc1xA9GpphkM6rrM37mLbCypzHyQczTF1yyOTVZO1SBZ4bM3zIpLIa8slbu2u9yCCg8kIigy+DAPXttxCqRuy5nSzABhoffEDr0sVdx9nQ6pFhSO2N1xHvvbtzozgmbPNvgpUVFv7u73YtEcatzbJG88J53OnpndtJuY3L41y9ir+4mBCOpSRuNpFhiPPpJcLa5nfUn59n7n/7X7cFGjsnReLPzbL6Tz9ETaU64yW8LuuOOBWx61L65S8Srk67NCYUhdhxiZrb57f25huI93cak0JiOwGb9h5C27lMyzDqkKPdqSkW/u5vd5+35uZvq/bO2zR38/iK423zllyHKRTDTFqMm81OoBzVN7drXb3Cwv/+twS7lMa2HoN74warq/+QKHLHEVGjsamU3Y6gQqdB9fpm04GdURk5Bk5jksHTGvWyjZlSMSyF0J8jjmbpTdvIQQ9lxMQwU7itiFzmEos3HNautigMGBRHTFwtYuCsRXXNp6d/ljCYQdMFoS8ppiywPYbOKkhZIPRjekdMzr+ySLO6s7wbhwHlK+/vfb5A2KptOxc9lcPMFfGb1aR0FUVIGRMHAd7qAopmIOMY3c5hZoqY2SKh1yAKPJAQNCvoqTxCVWmtzxMHHu76ErqdIVUcQdFM4tAnajYQCNID4+3yVMJ78ssriDAmcpoY6QJGKk/QqhE2akStRjLmLmRpd30Rd31nhSF3MMvA2T4aCw2yoxn8RoBZWMHM2Ti9At3WUE0Vt+IhqOA3VmjMGjRXHXKjGUI/IqivgYDCeBrVXCb2XHIHsghVQdEVUr0W9YUG6aE0oRMRtAKEmE2alcwMQtQ48OgITtll7dLtd2r90QIeGcOF52Y5+vQQxUNZLv56jvqKw7kfTXHk8QHGv9pHaabB8qdg53UGT+TxmyEXfzNPq+Lz8U9nOPRIP34r5KMfTxGHMUOnCpRnmth5oxMk5YZS9E9kufryEquTyY917sN1UnmDsYf6ksySpdI7nmFtskbv4Qy1pRYXnptl4qlBRu7p4dMX51mfqjP5++VOt9WNt1Zwaju/JKEXc+5H0xx+bIBWyePCL2apzrf48IdTHHq4n96xDDMfrCGEoDCaIl00WblaZf5cCd+NUHWF4VMFVq7WmH5nFbvHoP9ojpUrVfqOZKktOVx6fp7Djw2Qyhuc//kMbj1Axgk36OhTQwyfKVCea1I4kEI3VRqrXuezH/5wioknB4kjycc/ncGp+Fx9JQlqnIrPjTdXCO+WxMCXFIatUihqaIZgZdZn/KRFaSlg9GjSRRBFoKiwMufjtmJMW2DYCoU+ncVpj8pqyNF7VeKo/aSExLRV0jkVVYNyM2DksEV1PWTkSNJmHwUSVRMszXh4bkwqq6JbCr2DOjOXHRqViCNnUgTefukdue2GtV8gENWqnVLTfuPdjlChDEOCleVbbhc7zu3xOtoB0M2E5puPRQYBwfKt9wuJRk3c3C55sFeX077HtUXPJvT2lpe4LYHHON6mP7Tnbn3v9uZ3l3Pca79RtcrNq0B4k12E9LxtytZ7H+DO6yX3mRsAO6tiZ1S8VkQcS2rrAccP26QLGpXlAEUleS+SjJ/K0KiEZHo0nHrUydT0DBogwEorNCoBcSjJ9xmohsCpR8hYsj7vURjQyfbqNKshcUTi6P4Z+Ht7nj4Sr17GKgwk3VmqQei3CJ06ejqPZmXwmxWc8iKZwcPIOES3c0AN3c6hmal2N5dA1c1ErVkmWTG7OJJ0ZwmVOPTxmxWMdA7VzODV1vCbVTKDh5AyRrezRF4L1UwnpqG0LT004466wzRTxe6x8Goe6cE0etqnsdikeLQHzVDxGwGNhQbFE720Vh2MTCI7IhRB7mCW5kqrTaUUaLaKVbCIgojMcIbIj2guN7GP9SS8VSFoLjcYfnCI6nSNzEgGK59USzJD6TtuMhJyH4q7uNlzpYsuusBKKximgpQS35OYdtJJpajtxbK9WvpujGEJwkCit813fTcmCCSZvEocSurV5LZipxV0QyGOJWEgMaytYwIyCY5cJ8JKqQR+3BnTc2KiSJLOqUSBpFHtBqxd/POGqgnSBY3Qj4kjCLyYdCF5Pg/9GFUTneBEt5SO16KqC5xGhO/ESRY2rRIGMYEnEQKsjIqMJXGUZEYDL0bVBaqa/E5VLXm9Xgo/U2frbhCqjhCgaNt9zGS02ZovozBpyDDshNi7ldTbdiBPXNt9ZBS0RRolimFt29e2McOAKPTbY24nCgtFJY7CjhP8nTjUa5aKZiU6bZqlEQURoRthZg1CN0TRVUInQLM1QCCjGEVTiMMYoSpEfkTQbNuOpJJsUBzK5K8fEfkxelojdCM0U8VvBhjphIIRhzGaqRJ6UZt6ERI6N3N3975u3YCniy666KKLLrr4UmC/gOfLr6PfRRdddNFFF138i8e+HJ4/RUGnLrrooosuuuiiiztFN8PTRRdddNFFF1186dENeLrooosuuuiiiy89ugFPF1100UUXXXTxpUc34Omiiy666KKLLr706AY8XXTRRRdddNHFlx7dgKeLLrrooosuuvjS4/8HYKQb07Lwpe0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# all keywords from tweets NOT associated to disaster\n",
    "all_non_disaster_keywords = \" \".join([keyword for keyword in full_df[full_df[\"target\"]==0][\"keyword\"].dropna()])\n",
    "\n",
    "# visualizing keywords\n",
    "word_cloud= WordCloud(width=800,\n",
    "                      height=500,\n",
    "                      max_font_size=112,\n",
    "                      random_state=24).generate(all_non_disaster_keywords)\n",
    "\n",
    "# plotting \n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.title(\"All keywords associated to Non-Disasters\", size=20, weight=\"bold\")\n",
    "plt.imshow(word_cloud, interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# keywords from our tweets \n",
    "all_tweets = \" \".join([word for word in full_df[\"text\"]])\n",
    "\n",
    "# visualizing tweets\n",
    "word_cloud= WordCloud(width=800,\n",
    "                      height=500,\n",
    "                      max_font_size=112,\n",
    "                      random_state=24).generate(all_tweets)\n",
    "\n",
    "# plotting \n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.title(\"All words\", size=20, weight=\"bold\")\n",
    "plt.imshow(word_cloud, interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# keywords from our tweets associated to disasters\n",
    "all_disaster_tweets = \" \".join([word for word in full_df[full_df[\"target\"]==1][\"text\"]])\n",
    "\n",
    "# visualizing tweets\n",
    "word_cloud= WordCloud(width=800,\n",
    "                      height=500,\n",
    "                      max_font_size=112,\n",
    "                      random_state=24).generate(all_disaster_tweets)\n",
    "\n",
    "# plotting \n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.title(\"All words from disaster tweets\", size=20, weight=\"bold\")\n",
    "plt.imshow(word_cloud, interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# keywords from our tweets associated to non-disasters\n",
    "all_non_disaster_tweets = \" \".join([word for word in full_df[full_df[\"target\"]==0][\"text\"]])\n",
    "\n",
    "# visualizing tweets\n",
    "word_cloud= WordCloud(width=800,\n",
    "                      height=500,\n",
    "                      max_font_size=112,\n",
    "                      random_state=24).generate(all_non_disaster_tweets)\n",
    "\n",
    "# plotting \n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.title(\"All words from non-disaster tweets\", size=20, weight=\"bold\")\n",
    "plt.imshow(word_cloud, interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>keyword</th>\n",
       "      <th>target</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">ablaze</th>\n",
       "      <th>0.0</th>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">accident</th>\n",
       "      <th>0.0</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>aftershock</th>\n",
       "      <th>0.0</th>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">airplane%20accident</th>\n",
       "      <th>0.0</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">ambulance</th>\n",
       "      <th>0.0</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">annihilated</th>\n",
       "      <th>0.0</th>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">annihilation</th>\n",
       "      <th>0.0</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">apocalypse</th>\n",
       "      <th>0.0</th>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">armageddon</th>\n",
       "      <th>0.0</th>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">army</th>\n",
       "      <th>0.0</th>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">arson</th>\n",
       "      <th>0.0</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">arsonist</th>\n",
       "      <th>0.0</th>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">attack</th>\n",
       "      <th>0.0</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">attacked</th>\n",
       "      <th>0.0</th>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">avalanche</th>\n",
       "      <th>0.0</th>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">battle</th>\n",
       "      <th>0.0</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">bioterror</th>\n",
       "      <th>0.0</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">bioterrorism</th>\n",
       "      <th>0.0</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">blaze</th>\n",
       "      <th>0.0</th>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">blazing</th>\n",
       "      <th>0.0</th>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">bleeding</th>\n",
       "      <th>0.0</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">blew%20up</th>\n",
       "      <th>0.0</th>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">blight</th>\n",
       "      <th>0.0</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">blizzard</th>\n",
       "      <th>0.0</th>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">blood</th>\n",
       "      <th>0.0</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bloody</th>\n",
       "      <th>0.0</th>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            count\n",
       "keyword             target       \n",
       "ablaze              0.0        23\n",
       "                    1.0        13\n",
       "accident            0.0        11\n",
       "                    1.0        24\n",
       "aftershock          0.0        34\n",
       "airplane%20accident 0.0         5\n",
       "                    1.0        30\n",
       "ambulance           0.0        18\n",
       "                    1.0        20\n",
       "annihilated         0.0        23\n",
       "                    1.0        11\n",
       "annihilation        0.0        19\n",
       "                    1.0        10\n",
       "apocalypse          0.0        23\n",
       "                    1.0         9\n",
       "armageddon          0.0        37\n",
       "                    1.0         5\n",
       "army                0.0        29\n",
       "                    1.0         5\n",
       "arson               0.0        10\n",
       "                    1.0        22\n",
       "arsonist            0.0        26\n",
       "                    1.0         8\n",
       "attack              0.0        11\n",
       "                    1.0        25\n",
       "attacked            0.0        14\n",
       "                    1.0        21\n",
       "avalanche           0.0        26\n",
       "                    1.0         4\n",
       "battle              0.0        21\n",
       "                    1.0         5\n",
       "bioterror           0.0        15\n",
       "                    1.0        22\n",
       "bioterrorism        0.0         9\n",
       "                    1.0        21\n",
       "blaze               0.0        33\n",
       "                    1.0         5\n",
       "blazing             0.0        33\n",
       "                    1.0         1\n",
       "bleeding            0.0        30\n",
       "                    1.0         5\n",
       "blew%20up           0.0        31\n",
       "                    1.0         2\n",
       "blight              0.0        30\n",
       "                    1.0         2\n",
       "blizzard            0.0        33\n",
       "                    1.0         4\n",
       "blood               0.0        30\n",
       "                    1.0         5\n",
       "bloody              0.0        32"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# keyword to target counts\n",
    "keyword_count_df = pd.DataFrame(full_df.groupby([\"keyword\", \"target\"])[\"text\"].count()).rename(columns={\"text\":\"count\"})\n",
    "keyword_count_df.head(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Text Stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Code From https://www.kaggle.com/gunesevitan/nlp-with-disaster-tweets-eda-cleaning-and-bert\n",
    "\n",
    "STOPWORDS = set(stopwords.words(\"english\"))\n",
    "\n",
    "# word_count\n",
    "train_df['word_count'] = train_df['text'].apply(lambda x: len(str(x).split()))\n",
    "test_df['word_count'] = test_df['text'].apply(lambda x: len(str(x).split()))\n",
    "\n",
    "# unique_word_count\n",
    "train_df['unique_word_count'] = train_df['text'].apply(lambda x: len(set(str(x).split())))\n",
    "test_df['unique_word_count'] = test_df['text'].apply(lambda x: len(set(str(x).split())))\n",
    "\n",
    "# stop_word_count\n",
    "train_df['stop_word_count'] = train_df['text'].apply(lambda x: len([w for w in str(x).lower().split() if w in STOPWORDS]))\n",
    "test_df['stop_word_count'] = test_df['text'].apply(lambda x: len([w for w in str(x).lower().split() if w in STOPWORDS]))\n",
    "\n",
    "# url_count\n",
    "train_df['url_count'] = train_df['text'].apply(lambda x: len([w for w in str(x).lower().split() if 'http' in w or 'https' in w]))\n",
    "test_df['url_count'] = test_df['text'].apply(lambda x: len([w for w in str(x).lower().split() if 'http' in w or 'https' in w]))\n",
    "\n",
    "# mean_word_length\n",
    "train_df['mean_word_length'] = train_df['text'].apply(lambda x: np.mean([len(w) for w in str(x).split()]))\n",
    "test_df['mean_word_length'] = test_df['text'].apply(lambda x: np.mean([len(w) for w in str(x).split()]))\n",
    "\n",
    "# char_count\n",
    "train_df['char_count'] = train_df['text'].apply(lambda x: len(str(x)))\n",
    "test_df['char_count'] = test_df['text'].apply(lambda x: len(str(x)))\n",
    "\n",
    "# punctuation_count\n",
    "train_df['punctuation_count'] = train_df['text'].apply(lambda x: len([c for c in str(x) if c in string.punctuation]))\n",
    "test_df['punctuation_count'] = test_df['text'].apply(lambda x: len([c for c in str(x) if c in string.punctuation]))\n",
    "\n",
    "# hashtag_count\n",
    "train_df['hashtag_count'] = train_df['text'].apply(lambda x: len([c for c in str(x) if c == '#']))\n",
    "test_df['hashtag_count'] = test_df['text'].apply(lambda x: len([c for c in str(x) if c == '#']))\n",
    "\n",
    "# mention_count\n",
    "train_df['mention_count'] = train_df['text'].apply(lambda x: len([c for c in str(x) if c == '@']))\n",
    "test_df['mention_count'] = test_df['text'].apply(lambda x: len([c for c in str(x) if c == '@']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tr5E2DoeDu+++m4yMDIYMGUKZMmX47rvvePHFF3G5XIwYMeK8ffDffvuNhIQEHn74YQ4cOED9+vXzrEtsbCxdu3YlJiaGr7/+msmTJ5OcnHzBdYPO1qpVK0aMGMGcOXPo168f1157ba7p7HY7Q4cOZdOmTcTExNC0aVP+/PNP5s2bx8aNG1m0aJFXf+lCnwGRK44hIlekX375xYiMjDS+/PJLwzAMw+12G61btzY6dOhgtGnTxnC73YZhGMaHH35oREZGGgkJCYbD4TA6duxodOrUyUhOTvaUdfr0aaNDhw5Ghw4dDLvdbhiGYXTu3Nlo2LChceTIEU86p9NpREdHG3369PGkMwzDWL58uREZGWkMHDiwwOcxduxYIyoqyoiPj/dsO3XqlHHttdcaY8aMMQzDMG6//Xbj6quvNg4fPuxJk5GRYdx6661GVFSUcfLkScMwDGPgwIFG586dcxzj3O0DBw40IiMjjTVr1niV16pVK6Nfv345zuunn37K9/nMmjUrR55jx44ZDRo0MF588UWvtLt37zYiIyONZ555xrMtMjLSaNmypZGenu7ZlpKSYlx77bXGgAEDDKfT6dn+5ptverW7y+Uyrr/+eqN///5e6VJTU42uXbsavXv3zlHPhISEAp/PuR588EEjMjLSOHbsmGEYhvHII48YkZGRnv3du3c37r33Xq88S5YsMW6++WZj3759hmEYRkJCghEZGWnMmjXLkya7/Z944gmvvD/99JMRGRlpLF++3Ot1ly5djNTUVE+6FStWGJGRkcaiRYtyzZdXeYaRdf2fez1HRkYajzzyiGEYWddo8+bNjdtuu83IzMz0pElISDCaN29u9OnTxyvf1Vdf7WkfwzCMTZs2GZGRkcb06dNzb9Q86tG5c2ejQYMGxrZt2zzbsq+vBx544LxlnS37M5DXMc/97NvtduOaa64xxo8f75U2OTnZaNq0qTF8+HCvsgvzeTv3usl+nf3+ZevevbvRvn17z+tJkyYZjRs3Nnbt2uXZduTIEePqq6/O1zV+7Ngx46677jIiIyM9Pw0aNDBuu+0247PPPvNKm31Nrlu3zmv70qVLjcjISGP16tWebWdfLyIiIlKyqW9VevpW2bLvFT///HOv7cOGDTM6d+7sdY9uGIbRt29fo0WLFjnKzr5XzH49efLkHOU1btzYSEtLy/U8sl+PHj3aK98TTzxhREZGGnv37jUM43/XzrJlyzxp7Ha7cdttt+XaR8nN8uXLjdatWxuRkZFG8+bNvfoXBZHd9zr3XvWRRx4xWrdubRw9etSzze12Gw888IDRtGlT48SJE4ZhFL5/l5eUlBRj3LhxXvfjkZGRRs+ePY133nnHcLlcnrTZfbclS5Z4lfH9998bkZGRxptvvunZllufLjedO3fO9VrP5nA4jMjISCM2Ntaz7ez2++OPP7z+fhhGVrvFxsYaEyZM8GzLrQ+e/fnZtGmT1zHz6htNmTLFs83lchmDBw82mjZtapw6dSrXfHmVl1sf+Nxre/HixUZkZKSxcOFCr7LmzZtnREZGGu+8845Xvgt9BkSuNJoeTeQKdfXVVxMaGspPP/0EZA1xT0pK4q677iIxMZHdu3cDWU/l169fnxo1avDXX39x5MgRBgwYQEhIiKesMmXKMHDgQI4ePcqWLVs822vVqkV4eLjn9datWzl58iQxMTFeT1T07t2bsmXLFvgc3G433333HZ06daJ27dqe7eXLl2fx4sU8/vjjnDhxgj/++IPevXtTpUoVTxp/f3+GDRtGRkYG//3vfwt87MDAQP71r395lVenTh1OnDhR4LIupFKlSmzcuJH77rvPs80wDM+0Z6mpqV7po6KivEaG/PTTTyQnJzN48GAsFotn+x133OH1Pv71118kJCRwww03cPr0aU6dOsWpU6fIyMjwrM1x9OjRIj+/7PMwmUy57q9SpQobNmzgrbfe8rRv//79+fjjj6lVq9YFy2/VqlW+6nHnnXcSFBTkeX3zzTdTtmxZvv3223zlL4gff/yR9PR0hg4d6jW6qEaNGtx8881s3rzZa6HVa6+9lkqVKnleN2rUCCDXKQAupE6dOl6LplaqVImKFSsW6bV77mffZrPx3//+l6efftorXWJiIiEhIaSlpZ23vIv5vHXv3t3rdcOGDT35DMNgzZo1dOjQwWs0S3h4ODfffPMFy4as9nvzzTf54IMPuPfee2nSpAmQtVDoAw88wJNPPulJu2rVKsLCwmjSpInn83Xq1Ck6deqExWLxybUmIiIivqe+VenpW52rZcuWXq9ff/11li9f7nWPnt97Vsh579moUSOcTidJSUkFzgd42uDrr7+mbNmyxMTEeNLYbDbPKK4LefHFF5k0aRLNmjXjvvvuIz09nUceeQS3283ff//Nhx9+6JlyrzDcbjdff/01LVu2xGq1eu5zExMT+fe//43dbueHH34ALr5/d67g4GBmzJjBF198wf3330+LFi2wWq38/fffPP3009x3332e2RZWrVqFyWSiU6dOXvfjjRs3plKlSj65H79Qf7dy5cqYTCZef/11vv/+e+x2OyaTifnz5zNlypQLlh8QEJDv0WfZo50AzGYzAwcOxG63F+pzeyHffPMNISEhOUbfZY/U++abb7y2X+gzIHKl0fRoIlcoq9VK27ZtPR2Ln376iYoVKxITE8O0adP45ZdfqFu3Lj/88AO33norgGc+0Tp16uQor27dukDWVEMtWrQAoEKFCl5pDh48CJDjRsxisXh1DPIrKSmJtLS0XPNmD0H+448/8qxz9pe0hw4dKvCxy5Urh9nsHff28/PzWmOjKPn5+fHJJ5+wfv164uPj2bdvnydYY5y1HgiQY+j4vn37AHK0k5+fHzVr1vS83r9/P5A1vdfUqVNzrcehQ4e8OotFISkpCYvFQpkyZXLdP2HCBEaOHMnzzz/P5MmTadKkCV26dKFv375egYy8nHsd5iX7Gs5msVioXr2657otStmfpXOPCd7XZeXKlYGc72l2J7Iw11tuUwsU9bWbW5vbbDa+/fZb1qxZw969e9m3bx+nT58Gcl7D57qYz1tubZedLykpiaSkpFzn8c7tvTmfZs2a0axZMx588EFOnjzJp59+SlxcHEuXLiUmJobmzZuzf/9+Tp06RXR0dK5lZM/jLSIiIqWL+lalq291tnPb1WKxkJCQwMyZM9m1axf79+8v0INred235zVFc7bsafXyyrdv3z5q1Kjh9RAe5O+edePGjcybN48OHTrw+uuvY7FY2LFjB2vWrOH111/nzJkzLFiwgI8//jjPacguJDExkeTkZL7++usc6xtly77Xvdj+XV7q1avH6NGjGT16NMnJyXz11VfMnDmTtWvXsnLlSnr06MH+/fsxDMMrSHi27DUri1J2wC6vtq1SpQoPP/ww06dP5+677yYoKIjo6Gh69OhB9+7dc7zn58rt85NXunPrkP19gK/6vDVr1swxZXT29xDnHvNCnwGRK42CNiJXsE6dOrFy5UqOHj3Khg0baNmyJeXLlycyMpJff/2Vpk2bkpiY6LmhOd8Xq9n7zv4P+dybi+wnS85dBBwK9+Vz9n/eeT2xcna9cpN9zHNvIvI6ztnyc1NUVDIzM7nzzjvZtm0bbdq0ITo6miFDhtC6detcbzbPbffsJ3tyWy/m7AXSs9tj7NixXH311bnWpaBfZF+IYRhs376devXq5Vo/yBoZsXLlSr7//nvWrl3L999/z6xZs1i4cCHvvffeBdf7yO97ldt1ZBjGBW+Si7ozmdtnqSivt0tx7Z7bZoZhcN9997F27VquvfZaWrRoQb9+/WjVqhV33XXXBcu7mDqfL29+Pxt5+fjjj9m9ezcPPPCA1/YKFSowZMgQKleuzPjx49m4cSPNmzfH5XIRERHhNfrmbHkFLkVERKTkU9+qdPStznVuu86fP5+pU6dSp04dWrZsyb///W+aN2/O22+/na81D8/XfudzoTZwOBy5BhTy6kOdbc2aNQCMGjXKc74vvPACt956K3FxcQQFBREREeE1Gr+gst/Xbt260b9//1zTZAcILrZ/d7Zvv/2WH374gYcfftirLUJDQ7n99tuJjIykb9++bNy4kR49euB2uwkODmb27Nm5lpefPkBB/fXXXwDnbd9hw4Zx0003sXr1ar777jt++OEH1qxZw0cffcQbb7xx3vIv1F/Ndr5r80LXX2ECJxf6e3Hu34ri/DsgUhIpaCNyBevQoQOQNVXTb7/9xpgxYwBo3bo1q1evpn79+oSGhnoWlstezHLPnj05ytq7dy+A1zD5c2XfpGWP/MhmGAYHDx4s8IL25cuXJyAgwDNC5Gzz58/n+PHjDBs2LN91NpvN2O32HOmKezjul19+yZYtW3juuee47bbbPNvz+8RXjRo1gKyFRc9+Ks4wDPbv3+9ZqDD7/Q0KCqJt27ZeZfz555+cPn3aa9q1ovDTTz+RmJhIv379ct3vcrnYvn07ISEhXH/99Z7FWL/44gvGjx/P+++/z8SJE4ukLuc+6eNwODhw4IBnyoTsm+Fzr5HCTFF29mfp3Jv37Gv1fJ+l0ubXX39l7dq13HfffYwdO9azPXuqiLNHfF1KFSpUICgoiPj4+Bz7zv07lZsNGzawfPly+vbt6/mcnS37b1r256ZGjRps2bKF6667zqtT4nA4WL169WX1nouIiFxp1LcqHX2r88nMzCQuLo42bdqwYMECr0XsZ86cWYw1y3q/N2/ejGEYXl++5+eeNfvL87O/3C9TpgwzZ86kf//+JCcnM378+IuqX1hYGIGBgTidzhx9yUOHDvHXX38RGBhY5P27rVu3smjRIrp27Urr1q1z7D/3frx69eqsX7+epk2b5nhg6quvvirU9GwX8tVXXwHQpUuXXPcnJSWxfft2rrnmGgYOHMjAgQNJS0tj4sSJrFy5kh07dtCgQYOLrsfp06dJSUnxmo4x+3Obfd7ZfRS73e4VBCvM57Z69eps2rQJh8PhFaCx2+1e/WwRyZ3CmCJXsMqVK9OoUSPeeecdkpKSPGt/tG7dmiNHjrB8+XLatWvnuVlt0qQJlSpVYsmSJaSkpHjKSUlJYfHixVSqVImmTZvmebzGjRtTvXp1lixZQnp6umf7559/TmJiYoHrb7VaadeuHd99953XtEKnT59m/vz5JCQkeOr0ySefcOTIEU8au93OwoUL8fPzo127dgBUrFiRkydPegVDtmzZkq8b4dxk3/Bc7EiM7OHU2cGVbIsWLQL+N1ogLx06dCAwMJClS5d61eXLL7/0mre4adOmVKpUibfffttrnZyUlBTGjRvHpEmTPDf62ed2oWmtziclJYUXXniBoKCgHPPcZnO5XAwePJjnn3/ea3vz5s296pFdr4tp6xUrVng9QfT++++TnJzMDTfcAGRdHwDbtm3zyvfFF1/kKMtsNp+3Lm3btsXf35+FCxd6dWaPHDnCp59+SlRUVL6ndSsN8rqGly1bRnp6+gWvYV8xm8106dKFdevWkZCQ4Nl++vRpPvvsswvm79WrFwDPPvssmZmZOfa/9957WCwWzxO1Xbp0ISkpiSVLlnilW7p0KePHj+fHH3/0qtulmBJEREREiob6VqWjb3U+GRkZpKenExER4RWw2bZtGz///DNw4b6Xr3Tt2pXExES+/PJLzza3283SpUsvmPe6664DyHEPeuzYMU//Z/ny5V7XUUFZrVY6duzId999x/bt2732vfDCC4waNYrExMQi79/17NkTs9nMlClTOHPmTI79y5YtA/AEh7IDJ6+99ppXum+++YaxY8d6jaYqivvxn376ic8++4yuXbvmOiUzwA8//MBdd93ltcZLUFCQZ1rCouqDu91uPvjgA89rp9PJW2+95ZmODfBMT3d2n/fIkSP8/vvvXmXl5/3p0qULKSkpvPvuu17bFy9eTGpqap5T1IlIFo20EbnCdezYkddff51y5cp5nkJp2bIlJpOJhIQERo0a5Ulrs9l4/PHHGT9+PH369PGM+vjggw84duwYs2bNOu+QVpPJxP/93/8xatQo+vXrR58+fTh69Cjvvvsu5cqVK1T9H3zwQW6//XZuv/12zyKey5YtIy0tjXHjxgHw+OOPc9ddd3Hbbbdxxx13EBwczCeffMLWrVt5/PHHPU/Y3HTTTXz22Wfcc8893HHHHZw8eZK3336biIgIHA5HgeuWPV/skiVLOHHihOcL3oJq27YtVquVCRMmMGDAAKxWK2vXrmX9+vXYbDavAEtuQkNDGTNmDFOmTGHIkCF069aN+Ph4li5d6vXEy9nvb0xMDLfddhv+/v68//77HDp0iBdffNHTeck+tzfeeIOOHTt6boLz8t///tfTsct+suaTTz7h2LFjvPjii561W87l5+fHoEGDeO211xg1ahQdOnQgIyOD9957j8DAQPr06QP8bx7fNWvWUK1aNf7973/nr3HPcuDAAe666y5uuukmdu3axeLFi2nRogW33HILABERETRp0oRly5Z5phBYvXq115f92cLCwti+fTuLFy+mdevWOYIV5cuX54EHHmDy5Mnccccd9OrVi9TUVJYsWYLb7ebxxx8vcP1LshYtWhASEsLkyZM5ePAgZcuWZcOGDXzxxRf4+/tf8Br2pbFjx/Ldd9/Rr18/Bg0ahJ+fH0uXLvWst3O+aQSio6MZOnQoCxcupEePHtx0003UrFmT5ORkvvnmG37++WcmTpxItWrVALj99tv58MMPeeaZZ9i6dStRUVHs3LmT9957jyZNmngtLBsWFsbPP//MsmXLaN++vacMERERKbnUtyr5favzKVu2LM2bN2fFihWEhIRQp04d/v77b95//33Pe5GamkrZsmWL/NgXcuutt7J06VImTJjA77//TkREBCtXrmTTpk3A+e9ZO3XqRJcuXVixYgWZmZm0bt2aP/74g48//pjGjRvTpk0b5s+fT2xsLPPmzfMaiVEQDz30EBs2bGDAgAEMGDCAatWq8e2337J27Vr69evn+UwUtn+XW7tHREQwadIknn/+ebp3787NN99M3bp1ycjI4IcffmDt2rUMGjSIa665xtMW119/PQsWLODgwYNER0dz8OBB3n33XapVq+YZTQYX7tOdLS0tjY8//tjzOiUlhT///JPPP/+cmjVr8tRTT+WZt3PnztSpU4fHHnuMrVu3UqtWLfbs2cO7775LdHS057gF7YOfKzAwkFmzZnH48GFq1arFF198we+//86TTz5JaGgoAN27d+f1119n/PjxDBkyhMzMTN59913Cw8O9ZifIXn/mk08+wTAMz1pdZ8vu+7zwwgvs3LmTpk2bsmXLFlasWMHVV1/N7bffXqD6i1xpFLQRucJldyyyOxOQdTNQv359du3aRceOHb3S33jjjZQtW5ZXX32VV155BavVSvPmzXnuuefyNby1c+fOvP7668TFxTF9+nTCw8N57rnncjx9kV/16tXjvffeY/r06bzxxhuYzWaioqKYMmWK56awRYsWLFmyhFmzZrFgwQLcbjcNGzbklVde8YyiyK7bE088waJFi3juueeoU6cO//nPf/jll1/49ttvC1y36Ohounfvztq1a/npp5/497//Xag5ciMjI5k1axazZ89m+vTpBAcHc9VVV7Fw4UIWL17Mzz//nGPI8bliY2Px9/dn0aJFTJ48mdq1azNjxgyeeeYZr2HP2e/va6+9xquvvorZbOaqq67itddeo3Pnzp50PXv2ZNWqVaxYsYKff/75gjeMc+bM8fzbarVSoUIFrr32WmJjY2nWrNl5844ZM4Zy5cqxfPlypkyZgsVi4ZprrmHatGme+Y4DAwMZP3488+fP59lnny3UsPYnn3ySVatW8cILLxAQEED//v154IEHvJ6ymzVrFi+88AJLly7FarXSpUsXHn30Ubp37+5V1v3338+TTz7J888/z6hRo3K9wc9e82TBggVMnz6dwMBAWrduzejRo4tk+HtJUrFiRebOncuLL77Ia6+9hp+fH3Xq1GH69On8+eefLFq0iBMnTnhGM11KtWrV4p133mHKlCm8/vrr+Pv7c8stt2CxWJg/f/4F5wmfOHEirVu3ZtmyZSxfvpykpCSCg4OJiopi/vz5tG/f3pPWz8+PN998k1deeYWVK1fyySefULlyZe644w5GjRpFYGCgJ+1DDz3ESy+9xDPPPMMzzzzjCR6KiIhIyaW+VcnvW13IzJkzmTx5MsuXL8dut1O9enXuvfde6tWrx/33389PP/1Et27divy4F2Kz2XjjjTeYNm0an3zyCZmZmbRr146nnnqKiRMnXvCe9eWXX+bVV1/lk08+YdWqVVStWpWRI0dyzz33EBAQgL+/P7t27SIoKKjQdaxVqxbLli1j1qxZnmBfzZo1mTRpEoMGDfKkK2z/rk2bNrked/DgwTRu3Jh3332XL774glOnThEQEEDDhg2ZPn06PXv29KQ1mUzMnDmTN954g48++ohvvvmGsLAw/v3vfzN27Fiv/kh++nTZEhMTmTBhgud1YGAgNWvWZNiwYQwbNuy8a1cGBQWxYMECZs2axaeffsqJEyeoVKkSd955J6NHj/akK2gf/FxlypRhypQpPP/887z77rvUrl2badOmcfPNN3vSNGzYkJdffplXXnmFqVOnUrVqVe655x4yMjKYOnWqJ129evUYNGgQK1asYPPmzbm+N2f3fb788ks++eQTqlSpwvDhwxk5cuQF178SudKZjIuZ20ZEREo8u91ORkZGrjeK11xzDTfccIPXDZjIleTkyZOEhYXleDrxmWeeYcmSJfzxxx/qUIiIiIhIscp+MOjc+9KVK1cyZswY3nzzTc8UV4V17no5IiJSfLSmjYjIZe7o0aO0atWKuXPnem3/9ttvSU1NJSoqqphqJlL8xo4dS8+ePb3mY05PT2ft2rU0bNhQARsRERERKXaLFi3i6quv9lpLCLLWMLJarTRu3Piij6GAjYhIyaGRNiJSotjtds9aEhdStmzZCw4Dlyx33HEHf/31F3feeSd169YlISGBxYsXU6FCBT766COvaZlEriTvv/8+jz/+OB06dOD6668nMzOTTz75hO3bt/P666/ToUOH4q6iiIiISKGob3X52LVrF7fccgu1atWib9++BAQE8MMPP7Bq1SpGjhzpWXNIREQuDwraiEiJsmHDBgYPHpyvtIsWLcpzXlvxdvr0aV577TVWr17NsWPHCAsL41//+hfjxo3zLCIocqX65JNPWLRoEXv27MFsNtO0aVPuu+8+WrduXdxVExERESk09a0uL3/88QezZ89my5YtpKenExERwZ133knfvn2Lu2oiIlLEFLQRkRLl9OnTbN26NV9pmzRpQtmyZX1cIxERERERkdJHfSsREZHSSUEbERERERERERERERGREsBc3BUQERERERERERERERERsBZ3BS43v//+O4ZhYLPZirsqIiIiIiKXhMPhwGQy0aJFi+KuipQS6jeJiIiIyJWkIH0mjbQpYoZhoBnn8scwDOx2u9rLB9S2vqO29Q21q++obX1Hbes7alvf8GW76h5YCkrXTP7o76HvqG19R23rO2pb31Hb+oba1XfUtr7jq7YtyP2vRtoUsewnxZo1a1bMNSn50tLS2LZtG/Xr1ycoKKi4q3NZUdv6jtrWN9SuvqO29R21re+obX3Dl+26efPmIi1PLn/qN+WP/h76jtrWd9S2vqO29R21rW+oXX1Hbes7vmrbgvSZNNJGRERERERERERERESkBFDQRkREREREREREREREpARQ0EZERERERERERERERKQEUNBGRERERERERERERESkBLAWdwVEREREpPi5XC4cDkdxVwOAzMxMz2+zWc8YFZXCtqvNZsNisfiqWiIiIiIich659dXUZ/KdktBvUtBGRERE5ApmGAZHjhzh9OnTGIZR3NUBwO12Y7VaOXTokDogRaiw7WoymShbtixVqlTBZDL5sIYiIiIiIpLtfH019Zl8pyT0mxS0EREREbmCnT59mqSkJCpVqkRwcHCJ+FLe5XKRmZmJv7+/RngUocK0q2EYpKamcvz4cQIDAylXrpxvKykiIiIiIsD5+2rqM/lOSeg3KWgjIiIicoUyDINjx45RpkwZKlasWNzV8XC5XAAEBASoA1KECtuugYGBZGZmcuzYMcqWLVsiAnsiIiIiIpezC/XV1GfynZLQb9LYKREREZErlMvlwuVyUaZMmeKuipRwZcqU8VwvIiIiIiLiW+qrlU5F1W9S0EZERETkCuV0OgGwWjX4Ws4v+xrJvmZERERERMR31FcrnYqq36SgjYiIiMgVTtNdyYXoGhERERERufR0H166FNX7paCNiIiIiIiIiIiIiIhICaDxVSIiIiKSQ2J6ImcyzxTLsUP9QvHHv0B5unTpAsAnn3xCSEiI176JEydy8OBB3n777XyVZRgGH330ER07dqRChQq5pmnQoIHXaz8/P6pUqUK3bt247777CAoKAuDAgQNcf/31LFq0iDZt2hTonAojLS2NDz/8kAEDBvj8WCIiIiIicumlpNlJSbfjdDqxZhiYTZduXEZQgJWQIL8C5Zk4cSIffvjhedPs2LGjwHUZNGgQ1atX54UXXshX+i5dunDrrbdy//33F/hYl5qCNiIiIiKSw5nMM/x44EcynZmX9Lj+Vn/aVG9DZb/KBc578OBBpk6dytNPP31Rdfjll1+YOHEia9asOW+6Rx99lB49egBZwZI///yTKVOm8Mcff7BgwQJsNhtVq1Zl/fr1lC1b9qLqlF8LFixgxYoVCtqIiIiIiFym0jKcbI8/RXqGHavVitl8aYI2NquZhrXDChy0eeyxx3jwwQc9r9u3b+/VlyqsuLg4LBZLvtN/8MEH+PsX7OHA4qKgjYiIiIjkKtOZSabr0gZtLkbNmjV57733uPHGG2nbtm2hyzEMI1/pQkNDqVSpkud17dq1qVOnDrfddhsfffQRt99+OxaLxSuNr+W37iIiIiIiUno5nG7sThcGZi5RzKbQQkNDCQ0NzbHtYvtJ5cqVK1D6sLCwizrepVTC31IREZECSkyEffsu/icxsbjPREQK6OabbyY6OprHHnuMlJSUPNMlJSXx1FNP0alTJ6Kioujfvz8bNmwAYMOGDQwePBiA66+/nhUrVhSoDk2bNuXaa6/ls88+A7KmR2vQoIGn/Pj4eIYNG8a1115LixYtGDZsmNdUADt37mT48OG0atWKpk2bcv3117NgwQLP/vT0dB577DHatWtHs2bNuOWWW1i1ahWQ9aTZ7NmzOXjwIA0aNODAgQMALF++nO7du9OiRQtiYmJ4++23cbvdXvV7/fXXadeuHddff/15205ERERKP1d6Co6kY0Xy40rXfYOIXJwVK1bQtWtXnn32Wa699lruu+8+AL7++mtuv/12rr76apo1a0ZMTAzff/+9J9+gQYOYOHGiVxnZv5s2bUpMTAwbN270pO/SpQtxcXFAVt9pyJAhzJ07l44dO9KsWTMGDhzI7t27PelPnTrF+PHjadmyJW3atOHFF19k8ODBnjJ8SSNtRETk8nLmDPz4I2RexOgAf3+Ijoby5YuuXiLicyaTieeee45evXoxZcoUnnnmmRxpXC4XsbGxOBwOpk2bRlhYGIsWLWLYsGEsXryYFi1aEBcXx/3338/7779PZGRkgesRGRnJF198keu+Bx54gIYNG7J8+XKcTidTpkxh9OjRrF69mvT0dGJjY2nXrh1Lly7FYrHw/vvvM2XKFKKjo2nUqBEzZ85kx44dzJ07lzJlyvD+++8zfvx4Vq5cSWxsLGlpaXzxxRd88MEHhIWF8d577zF9+nSeeOIJmjRp4pnC7dixY0yYMMFTrw8//JC33nqL9PT0HGsCiYiIyOXFnZlGxsEd4HReXEFWKwHVG2AJ1L2DiFyc/fv3c+zYMT766CMyMjLYsmUL999/P4888ojnwbKXXnqJCRMm8N133+Hnl3OKtsOHD7N06VKmTZtGcHAw//nPf5g4cSKrVq3CZDLlSP/rr7/i7+/P3LlzcTgcTJgwgaeeeoqFCxfidrsZOXIkbrebN954A5vNxuTJk/n1119p1aqVz9tDQRsREbn8ZGZeXNBGREqt6tWr88gjj/DEE0/QrVs32rdv77V//fr1bN26lU8//dQTkHnqqafYvHkz8+fPZ+bMmZ71Z8LCwggICChwHcqUKZPnaJX9+/fTtm1bqlevjs1m4/nnn2fPnj243W7S09MZPHgwAwYMIDg4GIAxY8bwxhtvsGPHDho1asT+/fsJDg6mZs2alClThrFjx9KqVSvKli1LcHAwQUFBXlOyvfrqq4wcOZKePXvicrmoVKkSmZmZPPPMM4wdO9ZTrzvvvJP69esX+FxFRESklHI6MVyOiyoi51egIiKFd99991GzZk0Atm3bxv/93/9x5513evYPHjyYe+65h5MnT1K1atUc+R0OB0899RSNGjUCYOjQoYwaNYrjx49TuXLONVOdTidTp0719P/69+/PtGnTANi4cSObN2/myy+/pG7dugC8/PLLdOnSpWhPOg+lKmizfv16ZsyYwa5du6hQoQIDBgwgNjY210jZuf766y9uv/12Vq5cSY0aNbz2ffnll7zxxhvs2bOHMmXK0LZtWx588EEqVqzoq1MRERERER/p168fK1eu5PHHH/dMU5Zt586dhIaGeo2gMZlMtGzZkvXr1xfJ8ZOTk3PM2Zxt/PjxPP/88yxevJjWrVvToUMHbrrpJsxmM2FhYdx555189tln/PXXX+zfv5/t27cDeKYzu+eeexgxYgTR0dFERUXRrl07evXqlevxTp06xZEjR5g+fTozZ870rHdjGAaZmZkcOHDAsxBn7dq1i+TcRURERERECiMiIsLz70aNGlG2bFnmzp3Lnj172Ldvn6dv5HK58iyjXr16nn9n95EcjtwD1BUrVvQEbLLTZ6fdvn07ZcqU8QRsstPXqVOn4CdWCKVmTZtNmzYxYsQI6tatS1xcHL169WLatGnMmzfvgnl37tzJvffeizOXYZ+ff/4548aNo0mTJsTFxTF+/Hh++ukn7rrrLjL1lLaIiIhIqfTss8+SnJzM5MmTvbZnBy7OZRgGVmvRPM+0detWGjdunOu+AQMGsG7dOh5//HFCQ0OZNWsWPXv25MSJExw/fpybb76Z999/n/DwcO68804+/PBDr/wtWrTgu+++Y9asWTRp0oSPPvqIHj168OOPP+Y4VnagZ9KkSXz00UesWLGCJUuW8OGHH7Jq1SrPU2xAoUYUiYiIiIiIFJWz+yQ///wz3bp1Y/PmzTRs2JDRo0d7RsGcT27TpuXVB8wtbTaLxZJnvkuh1Iy0iYuLo1GjRp43p2PHjjidTubMmcPgwYNz7Wja7XbeeecdZs2a5XmK8Fxz5syhU6dOPP30055tderUoW/fvqxdu5Ybb7zRNyckIiIiIj5TrVo1Jk6cyOOPP07NmjU9w+cbNGhAcnIyO3fu9Iy2MQyDjRs3eqYHy88o7rxs2bKFTZs28cILL+TYd/LkSV555RXuvfdeYmJiiImJ4ejRo3Ts2JGff/6Zo0ePkpSUxMqVK7HZbADs2LHDU0eAWbNmce2113L99ddz/fXXM2nSJHr27MnKlSuJjo72qnuFChUICwsjISGB2rVr43K5yMjIYO3ataxZs4YpU6YU+jxFRERERER8ZcGCBbRp04a4uDjPtrfffhvIOwhTlCIjI0lOTmb37t2e0TuJiYns27fP58eGUjLSxm63s2HDBrp27eq1vVu3bqSmprJx48Zc861bt47Zs2czfPhwHnrooRz73W437dq1o2/fvl7bs4c97d+/v4jOQEREREQutdtvv5327duTkJDg2da+fXsaNWrEgw8+yM8//8zu3bt5+umn2blzJ3fddRcAQUFBQNaQ+NTU1DzLT05O5vjx4xw/fpx9+/bx6aefMnr0aNq0acPNN9+cI33ZsmX59ttvefzxx9m2bRsJCQksXboUm81G06ZNqVKlCunp6Xz11VccOnSI9evX88ADDwBZ98MACQkJPPnkk/z4448cPHiQlStXcujQIVq0aOGp++nTp9m7dy9Op5N77rmHt99+m3feeYf9+/fzzTff8NRTTxEQEHDeJ8tERERERESKS9WqVdmxYwe//vorBw4cYPny5cycORP4X9/Il1q2bElUVBQTJkxg06ZNbN++nYceeoj09PSLesgvv0rFSJuEhAQcDofXvHbwv7m39+7dS7t27XLka9asGd988w3lypVjxYoVOfabzWYmTpyYY/vXX38NwFVXXVUEtRcREREpnfytuY9ULk3HfPbZZ+nVq5fntcViYcGCBUyZMoXRo0djt9tp2rQpb775JldffTWQ9VRVp06dGDduHA888ACxsbG5lv3888/z/PPPA1lD62vXrs2AAQMYPHgwFoslR3qr1cq8efOYMmUKQ4YMIT09nUaNGjF37lxq1apFzZo12bp1Ky+88AIpKSlUr16d22+/nTVr1rB582buuOMOnnzySaZMmcLDDz9MUlIS1atX56GHHqJ3794A/Pvf/2bZsmXcfPPNvPPOO8TGxuLv78/bb7/N5MmTqVixIn379mXs2LFF2s4iIiIiInLp2Kxm/KwWrFYzZvOlGZdhs1668R9jxozhxIkTjBgxAoD69evz/PPP8/DDD7N582avtWt8ZdasWTz77LMMGTIEf39/7rzzTvbs2eOZFcGXTEZxTs6WT5s2baJfv34sXLiQtm3berY7nU6aNGnC+PHjPW9gXlasWMGkSZNYs2YNNWrUyDPd/v376du3L1WqVGHFihUFvug3b96MYRie6TUkb+np6cTHxxMREUFgYGBxV+eyorb1HbWtbxRlu1oPHcL49lvIyCh8IQEBmP71L5zVql1UXUoCXbO+czm0bWZmJocOHSIiIiLHVLOnM09zOvN0sdSrjF8ZAgjA39//kjzFdKUwDIPMzMxCtWtGRgbx8fFUq1Yt12mHd+3ahclkolmzZkVVXbnMbd68GUDXzAWkpaWxbds2GjVq5BkFKEVDbes7alvfKaq2dSQdI2PfVgxX7otz55fJYiOgdhNs5SpfVDklga5b31C7Fl5GRgZ79+6lTp06OfpqKWl2UtLtOJ1OrFYrZtOlC6YEBVgJCbq8R+y7XC4OHz7Mjh076NixoydIY7fbadOmDU8++SS33HJLrnnP974V5P63VIy0yV5ENS9FFU3cvXs3w4YNw2q1MmvWrEKX63A42LZtW5HU6UoQHx9f3FW4bKltfUdt6xsX264Wi4XwjAycR4/iTksrdDnmoCCsJ05wNCUFl8t1UXUqKXTN+k5pb1ur1UpmZmaO7f74U9mveDvgudVLLl5h2jUzMxOn08mePXvyTKPp1kREREREfC8kyI9AfwsZGRkEBATkOspfLo7VauXBBx+kf//+3HHHHTgcDubPn4+fnx8dO3b0/fF9foQiEBoaCpBjTvGUlBQAQkJCLvoYGzZs4P777ycoKIi33nqLWrVqFbosm82mkTb5cDk8oVxSqW19R23rG0U+0iY8/OJH2lSsSFmNtJHzuBzaNnukjb+/f46ngIrTxYwIkbxdbLtarVZq1aqV50gbERERERGRy0FoaCivvvoqs2bN4r333sNsNnPNNdewaNEiwsLCfH78UhG0qVWrFhaLhX379nlt379/P8BFz2H32WefMXHiROrUqcMbb7xBeHj4RZVnMpk05K8AAgMD1V4+orb1HbWtbxRJu9psWT8XGKWZnzL8LqP3WNes75TmtjWbs+Y/tlgsJerprOwRbiaTqUTVq7S7mHa1WCyYzWYCAwNzDfApuCYiIiIiIpeTNm3asHTp0mI59qWb8O4i+Pv707JlS1avXs3ZS/CsXLmS0NBQoqKiCl32d999x4QJE2jRogVLliy56ICNiIiIiIiIiIiIiIhIYZSKkTYAI0eOZOjQoYwdO5Y+ffrw+++/M3/+fB588EECAwNJSUlh165d1KpVK99DlDIzM3nssccIDg5mxIgROaZ1qFKlClWqVPHF6YiIiIiIiIiIiIiIiHgpNUGb6Oho4uLimDVrFqNGjSI8PJwJEyYQGxsLwNatWxk8eDCTJ08mJiYmX2X+9ttvHD9+HMBTztlGjx7N/fffX3QnISIiIiIiIiIiIiIikodSE7QB6Nq1K127ds11X5s2bdixY0eeeWNiYnIEc6Kjo8+bR0RERERERERERERE5FIpFWvaiIiIiIiIiIiIiIiIXO4UtBERERERERERERERESkBStX0aCIiIiJyiSQmwpkzxXJoU2go+PsXy7FFSrv169czY8YMdu3aRYUKFRgwYACxsbGYTKYL5v3rr7+4/fbbWblyJTVq1PDat3nzZqZOncqWLVsIDg4mJiaG0aNH4+fn56tTEREREZFcuNJTcGakYnI6cdqtuPNxn1dUzP5BWAJDLtnxrlQK2oiIiIhITmfOwI8/QmbmpT2uvz+0aQOVKxcoW5cuXTh48KDntc1mo2LFinTq1ImxY8cSFhYGQIMGDZg8eXKOtQ59weFw8O677zJkyBCfH0sEYNOmTYwYMYLu3bszduxYNm7cyLRp03C5XNx7773nzbtz507uvfdenE5njn0JCQkMHTqUq6++mpdffpndu3czY8YMkpKSePrpp311OiIiIiKSC3dmGpkHd2LPSMNmtWG+VEEbq5WA6g0KHLSZOHEiH3744XnTXMy68xs3bsQwDFq2bFnoMkoaBW1EREREJHeZmZc+aHMRYmNjiY2NBSAjI4OdO3cybdo0Bg4cyHvvvUdoaCjr168nNDT0ktTns88+Y/LkyQrayCUTFxdHo0aNmDZtGgAdO3bE6XQyZ84cBg8eTEBAQI48drudd955h1mzZuGfxwi3efPmERwczKuvvoqfnx+dOnUiICCAZ555hhEjRlCtWjWfnpeIiIiIeDOcjqwfExiXKGhT2KM89thjPPjgg57X7du359FHH6VHjx5FUq8777yTyZMnX1ZBG61pIyIiIiKXhaCgICpVqkSlSpWoWbMm119/PQsWLODw4cO88cYbAFSqVCnXL659wTCMS3IcEcgKvmzYsIGuXbt6be/WrRupqals3Lgx13zr1q1j9uzZDB8+nIceeijXNOvXr6dTp05eU6HdeOONuN1u1q9fX3QnISIiIiKXndDQUE8/rVKlSnluk/9R0EZERERELlvVqlWja9eufP7550DW9GgrVqwA4OTJk4wZM4Y2bdoQFRVF//79+fnnnz15Dx06xPjx44mOjqZJkyZ07NiRadOm4Xa7AXC5XEybNo1OnTrRtGlTbrzxRpYsWQLAihUrmDRpkueYGzZsAGDt2rXExMQQFRVF165defnll7Hb7Z5jNmjQgFmzZtG5c2fat29PfHy8z9tILg8JCQk4HA4iIiK8tteuXRuAvXv35pqvWbNmfPPNN4wcORKLxZJjf0ZGBgcPHqROnTpe28PCwggJCcmzXBERERGR/LhQH+m7774jJiaG5s2bEx0dzcSJEzl9+jSQ1X8CmDRpEhMnTiyW+vuCpkcTERERkctaZGQkH3/8MampqV7b//Of/3imhvLz82POnDncd999rFu3jqCgIEaOHEmlSpVYuHAhwcHBrFmzhsmTJ9OiRQtuuOEGFi9ezFdffcWMGTMIDw9n7dq1/Oc//+Gqq66iR48eJCcn8/zzz7N+/XrKli3LunXrGDduHJMmTaJt27bs37+fZ555hr179zJz5kxPvRYvXsy8efNwuVw5voAXyUtycjIAISHec4wHBwcDkJKSkmu+8PDwQpWbXXZe5eaHYRikpaUVOv+VID093eu3FB21re+obX2nyNrW6cTusGM4HRdVjMlqYHE6cVwGf8t13fqG2rXwMjMzcbvduFwuXC6X1z63YQD/jOo3DNyXqE4mw8BtGDnqUxjZ5/b9998zbtw4HnnkEaKjo0lISOC5555jz549zJgxg8TEREaPHs0jjzxCx44dOXr0KBMnTmTKlCk888wzfPfdd3Tq1IlJkyZxyy23FEndsmdMMApxri6XC7fbTXp6uudhv7PLNeVzKjsFbURERETkslamTBkg55fW+/fvJzIykpo1axIQEMBjjz1Gr169sFgsZGRk0Lt3b7p3707VqlUBGDJkCPPmzWPHjh3ccMMN7N+/n6CgIGrUqEHlypUZOHAgdevWpU6dOgQEBHjWzske7j9nzhz69u1L//79AahVqxZPPfUUd911FwcOHKBGjRoA9O7dm2bNml2StpHLx7mdwnOZzYWbZOFC5ea345kbh8PBtm3bCp3/SqJRd76jtvUdta3vXEzbWiwWKgSYST52DJf94tYutPj5ExpygpMZx4rki9KSQNetb6hdC8dqtZKZyxqjJqcTh9MJ4Pl9KZgMsDmdODMyLrosh8NBRkYGr732Grfeeiu9e/cGoHLlykyaNInhw4ezZ88ekpOTsdvtVKhQwfMzY8YMXC4XGRkZnj6Xv78/NpuNjCKoW7bc2j4/eZxOJ3v27Ml1/9nTDZ+PgjYiIiIiclnLa6TA6NGjefjhh1m5ciXXXnst7du356abbvIsxj5w4EC++uor/vzzT/bt28eOHTs4ceKE50vsAQMG8PXXX9OpUycaNWpEu3bt6NmzJxUqVMi1Hn/99Rd//vknH3zwgWdb9lNcu3fv9gRtsqezEimI7A7ruSPKsoOVuY2UyY/sfOeWm1129nELw2azUb9+/ULnvxKkp6cTHx9PREQEgYGBxV2dy4ra1nfUtr5TZG2blkRQSuUiGGljI7BiRSoElbuockoCXbe+oXYtvMzMTA4dOoS/v3+ONTmddis2qxW704HNaoWLeIimIEwWGxarFWsRrBFqs9kICAhgx44dbN26lY8++ihHmgMHDtCxY0d69uzJuHHjqFSpEm3btqVTp07ccMMNWK3WHOUVBcMwyMzMxN/fv1APKFmtVmrVquXpV2bbtWtX/sso8FFFREREREqRrVu3EhER4ZkmKlvXrl35/vvv+f777/nvf//LwoULmT17NsuWLaN69eoMHDiQjIwMbrzxRm699VaioqIYMGCAJ39ERASrVq3i559/5ocffuDbb79l3rx5TJ48mVtvvTVHPdxuN3fffXeu+85efLOoOhtyZalVqxYWi4V9+/Z5bd+/fz8A9erVK1S5wcHBhIeH5yj35MmTpKamFrpcyBqlExQUVOj8V5LAwEC1lY+obX1Hbes7F9u2DnsKLpsfhvnivug1WWzYrFZsl9H7rOvWN9SuBWc2mzGbzVgslhzrDrpNJuCfz6/JhPlSBW3+OVZu6yAWVPa5XaiPZLFYmD59OqNHj2bdunX897//5ZFHHuHaa6/lrbfeylFeUcgeOWgqxLlaLBbMZjOBgYE5+nUFCQAVboy8iIiIiEgpcOTIEdasWUOvXr28ttvtdiZPnkxCQgI9evTg2Wef5euvv8ZsNvPtt9+yfv16tm7dyqJFixgzZgw9evQgJCSEkydPekbHLFq0iFWrVtGuXTsmTJjAp59+SnR0NF988QWQ86b8qquuYu/evdSuXdvzc+TIEaZOnZrrKAaRgvD396dly5asXr3ac40CrFy5ktDQUKKiogpddrt27fj222+9FoRduXIlFouF66677qLqLSIiIiJXrgv1kf744w+ef/556taty5AhQ5g7dy7PP/88P/30EydPnizu6vuMRtqIiIiISO7OGc5d0o+ZlpbG8ePHAcjIyGDHjh28/PLL1KhRg6FDh3ql9fPzY/Pmzfz666/83//9HxUrVmTdunWkpaXRokULz1zDn3zyCd26dePw4cNMnz4dh8Ph+eL61KlTvPLKKwQEBNCwYUP27NnDtm3bGDx4MIDnacItW7ZQv3597rnnHsaNG8fs2bPp2bMnR44c4bHHHqNGjRpeI21ECmvkyJEMHTqUsWPH0qdPH37//Xfmz5/Pgw8+SGBgICkpKezatYtatWoRFhaW73LvvvtuPv/8c+6++26GDh1KfHw806dPp2/fvlSrVs2HZyQiIiIiuTFZbVk/FttFrTFYINaiDyVcqI905swZFi9ejM1mo2/fvmRmZvLFF18QERFB+fLlgax+1+7du0lMTPRsK+0UtBERERGRnMqUgejo4jl2IdfIWLBgAQsWLACy5jSuWrUqPXr0IDY2NsfUaAAzZsxg8uTJjBw5kuTkZOrWrcuLL75Iy5YtAZg0aRJvvvkmL7/8MuHh4fTo0YOqVauyefNmIGtNHIfDwbPPPsvx48epVKkSd9xxB8OHDwfguuuuo3nz5vTv359p06bRvXt3ZsyYweuvv86cOXMoV64cXbp04aGHHirU+YqcKzo6mri4OGbNmsWoUaMIDw9nwoQJxMbGAllTBQ4ePJjJkycTExOT73Lr1avHggULmDp1KmPGjKF8+fIMGTKEMWPG+OpURERERCQPZv8g/KtHYnU6sVitl2x6tOxjF6Ubb7zxvH2kevXqERcXx+zZs1m8eDFms5nrrruOefPmYTZnTSIWGxvLG2+8we7du5kzZ06R1q+4KGgjIiIiIjmVL5/1UwwMlwsyMgqU55tvvslXuh07dnj+HR4ezssvv5xn2iFDhjBkyJA891utVh5++GEefvjhXPeXLVuWZcuWeW3r3r073bt3z1f9RAqja9eudO3aNdd9bdq0Oe81FhMTk2cwp2XLljmuZxERERG59CyBIeAXiDMjA2tAQJGt5XKpnHs/eqE+UufOnencuXOe+++//37uv//+IqtfSaA1bUREREREREREREREREoABW1ERERERERERERERERKAAVtRERERERERERERERESgAFbUREREREREREREREREoABW1ERERErnCGYRR3FaSE0zUiIiIiInLp6T68dCmq90tBGxEREZErlM1mAyAtLa2YayIlXfY1kn3NiIiIiIiI76ivVjoVVb/JWhSVERERKSnSHemkpydiZKQXugyTO5BARzqBRVgvkZLIYrFQrlw5jh07BkBQUBAmk6mYawUul4vMzEwgq45SNArTroZhkJaWxrFjxyhXrpzeDxERERGRS+BCfTX1mXynJPSbFLQREZHLSqbLzr7T+0hPSSp0GYEh5ajjsitoI1eEKlWqAHg6AyWB2+3G6XRitVoxmzUwvKhcTLuWK1fOc62IiIiIiIjvna+vpj6T75SEfpOCNiIictlxuJ043Y6Lyi9ypTCZTFStWpXKlSvjcBT+c1OU0tPT2bNnD7Vq1SIwUOHTolLYdrXZbHp6T0RERETkEjtfX019Jt8pCf0mBW1EREREBIvFUmK+mHe73QD4+/sTEBBQzLW5fKhdRURERERKn9z6arq3952S0LYaOyUiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSAihoIyIiIiIiIiIiIiIiUgIoaCMiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSAihoIyIiIiIiIiIiIiIiUgIoaCMiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSAihoIyIiIiIiIiIiIiIiUgIoaCMiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSAihoIyIiIiIiIiIiIiIiUgIoaCMiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSAihoIyIiIiIiIiIiIiIiUgIoaCMiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSApSqoM369evp06cPzZs3p0uXLsyfPx/DMPKV96+//qJJkyYcOHAgx77NmzczaNAgWrRoQfv27Zk+fTp2u72oqy8iIiIiIiIiIiIiIpKnUhO02bRpEyNGjKBu3brExcXRq1cvpk2bxrx58y6Yd+fOndx77704nc4c+xISEhg6dCj+/v68/PLLxMbGsnDhQp599llfnIaIiIiIiIiIiIiIiEiurMVdgfyKi4ujUaNGTJs2DYCOHTvidDqZM2cOgwcPJiAgIEceu93OO++8w6xZs/D398+13Hnz5hEcHMyrr76Kn58fnTp1IiAggGeeeYYRI0ZQrVo1n56XiIiIiIiIiIiIiIgIlJKRNna7nQ0bNtC1a1ev7d26dSM1NZWNGzfmmm/dunXMnj2b4cOH89BDD+WaZv369XTq1Ak/Pz/PthtvvBG328369euL7iRERERERERERERERETOo1QEbRISEnA4HERERHhtr127NgB79+7NNV+zZs345ptvGDlyJBaLJcf+jIwMDh48SJ06dby2h4WFERISkme5IiIiIiIiIiIiIiIiRa1UTI+WnJwMQEhIiNf24OBgAFJSUnLNFx4eXqhys8vOq9wLMQyDtLS0QuW9kqSnp3v9lqKjtvUdta1vFGW7ut0uXC4XLqer0GW4XC7cbtdl8bdc16zvqG19R23rG75sV8MwMJlMRV6uiIiIiIjIlaZUBG3cbvd595vNhRswdKFyC9vxdDgcbNu2rVB5r0Tx8fHFXYXLltrWd9S2vnGx7ern50d5ezopycmknj5d6HKcWElLS+fg7t3Y7faLqlNJoWvWd9S2vqO29Q1ftevZ0w2LiIiIiIhI4ZSKoE1oaCgAqampXtuzR8LkNlImP7LznVtudtnZxy0om81G/fr1C5X3SpKenk58fDwREREEBgYWd3UuK2pb31Hb+kZRtmvGvh2EhIZixVnoMgJCQwkKCiSsdr2LqktJoGvWd9S2vqO29Q1ftuuuXbuKtDwREREREZErVakI2tSqVQuLxcK+ffu8tu/fvx+AevUK96VacHAw4eHhOco9efIkqamphS7XZDIRFBRUqLxXosDAQLWXj6htfUdt6xtF0a52swWLxYLFmnMts/yyWCyYzZbL6j3WNes7alvfUdv6hi/aVVOjiYiIiIiIFI3CzSt2ifn7+9OyZUtWr16NYRie7StXriQ0NJSoqKhCl92uXTu+/fZbr+lvVq5cicVi4brrrruoeouIiIiIiIiIiIiIiORXqQjaAIwcOZI//viDsWPH8t133/Hyyy8zf/58hg8fTmBgICkpKWzatIlTp04VqNy7776bkydPcvfdd7N27VoWLlzI5MmT6du3L9WqVfPR2YiIiIiIiIiIiIiIiHgrNUGb6Oho4uLi2Lt3L6NGjeLTTz9lwoQJ3HPPPQBs3bqVfv368e233xao3Hr16rFgwQIyMjIYM2YMCxcuZMiQITz22GM+OAsREREREREREREREZHclYo1bbJ17dqVrl275rqvTZs27NixI8+8MTExxMTE5LqvZcuWLFu2rEjqKCIiIiIiIiIiIiIiUhilZqSNiIiIiIiIiIiIiIjI5UxBGxERERERERERERERkRJAQRsREREREREREREREZESQEEbERERERERERERERGREkBBGxERERERERERERERkRJAQRsREREREREREREREZESQEEbERERERERERERERGREkBBGxERERERERERERERkRJAQRsREREREREREREREZESQEEbERERERERERERERGREkBBGxERERERkcvE+vXr6dOnD82bN6dLly7Mnz8fwzDOm+ezzz6jZ8+eREVF0b17dz788MMcab7++mtiYmJo0aIFXbt2Zfbs2djtdl+dhoiIiIjIFUtBGxERERERkcvApk2bGDFiBHXr1iUuLo5evXoxbdo05s2bl2eelStX8tBDD9GuXTteeeUVWrduzcSJE/n88889aX744QdGjx5NREQEs2fPZsCAAcydO5cpU6ZcitMSEREREbmiWIu7AiIiIiIiInLx4uLiaNSoEdOmTQOgY8eOOJ1O5syZw+DBgwkICMiRZ/r06dx44408+uijAHTo0IHTp08zc+ZMevbsCcCKFSuoVq0a06ZNw2Kx0K5dO06ePMnChQuZOHEiNpvt0p2kiIiIiMhlTiNtRERERERESjm73c6GDRvo2rWr1/Zu3bqRmprKxo0bc+Q5cOAA8fHxuebZt28f8fHxAGRmZhIYGIjFYvGkKVeuHA6Hg9TU1KI/GRERERGRK5iCNiIiIiIiIqVcQkICDoeDiIgIr+21a9cGYO/evTny7N69G+CCeQYMGMC+ffuYP38+Z86cYdOmTbz11lt06tSJcuXKFe2JiMgVKyXNzrFTaQX+SUnT+loiInJ50fRoIiIiIiIipVxycjIAISEhXtuDg4MBSElJyZEne9uF8lx33XUMGzaMqVOnMnXqVAAaN27MSy+9dFF1NgyDtLS0iyrjcpeenu71W4qO2tZ3Ctu2p5MdbI8/hcPpyncem9VCw4gwzDgLdKzSqsiuW6cTu8OO4XRcVDEmq4HF6cRxGfwt198E31C7+o7a1nd81baGYWAymfKVVkEbERERERGRUs7tdp93v9mcc5KF/OZ58sknWbFiBSNHjiQ6OpqDBw8ye/Zs7r77bt58800CAwMLVWeHw8G2bdsKlfdKkz1VnRQ9ta3vFKRtLRYLJr9QDhw6QoY9/wGYAD8rFUPdHD+cjMuV/2BPaXcx163FYqFCgJnkY8dw2TO99plMJmz+gbhcRv7KsvkTXC6FM6fs+Pv7k5qWjmHkL282P6uJjNTTF/w/6VLR3wTfULv6jtrWd3zRtn5+fvlKp6CNiIiIiIhIKRcaGgqQY42ZvEbT5DfP0aNHWbZsGcOHD2fcuHGeNFFRUfTs2ZPly5czcODAQtXZZrNRv379QuW9UqSnpxMfH09EREShg2OSO7Wt7xS2bROTHYRXNrA78//lvZ/VTMUKFSkfWrUwVS11iuy6TUsiKKVyriNt0jJdHDmRhisfQRSrHxgZBklOC+GBARw/k4GjAO9f9kip2jWqFKj6vqC/Cb6hdvUdta3v+Kptd+3ale+0CtqIiIiIiIiUcrVq1cJisbBv3z6v7fv37wegXr16OfLUqVMHgH379tG4cWPP9uwy6tWrx6FDhzAMg2uuucYrb/369SlXrhx///13oetsMpkICgoqdP4rSWBgoNrKR9S2vlPQtk3JSMPm5wfmgnzpb8Zms11x7+HFXrcOewoumx+GOec0PZlOO5hNYORjGWyTCUxmMFswW7J+k0uZeTKXvPdPfxN8Q+3qO2pb3ynqts3v1GgA+fgLLCIiIiIiIiWZv78/LVu2ZPXq1V5T06xcuZLQ0FCioqJy5KlduzY1atRg5cqVXttXrVpFREQENWrUoHbt2lgsFjZu3OiVZs+ePSQlJVGzZk3fnJCIiIiIyBVKI21EREREREQuAyNHjmTo0KGMHTuWPn368PvvvzN//nwefPBBAgMDSUlJYdeuXdSqVYuwsDAARo0axaRJkyhXrhxdunRhzZo1fPnll8yYMQOAsLAw7rrrLubPnw9A27ZtOXToELNnz6Z69er07du32M5XRERERORypKCNiIiIiIjIZSA6Opq4uDhmzZrFqFGjCA8PZ8KECcTGxgKwdetWBg8ezOTJk4mJiQEgJiYGu93OggULWL58OTVr1mTKlCn06NHDU+6ECRMIDw9n6dKlLFiwgMqVK9OuXTvGjx9PmTJliuVcRUREREQuVwraiIiIiIiIXCa6du1K165dc93Xpk0bduzYkWN7//796d+/f55lmkwmhgwZwpAhQ4qqmiIiIiIikgetaSMiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSAihoIyIiIiIiIiIiIiIiUgIoaCMiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSAihoIyIiIiIiIiIiIiIiUgIoaCMiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSAihoIyIiIiIiIiIiIiIiUgIoaCMiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSAihoIyIiIiIiIiIiIiIiUgIoaCMiIiIiIiIiIiIiIlICKGgjIiIiIiIiIiIiIiJSAihoIyIiIiIiIiIiIiIiUgJYi7sCIiIiIiIiIiIil7OUNDtpGc4C5wsKsBIS5FdkxzOZwJbpJD3djtvpyLHf6TIKfCwRESlaCtqIiIiIiIiIiIj4UFqGk+37TuFwuvOdx2Y107B2WKGCNnkdz2Y1UzUgg+STqTjt9nP2WSgbUvBjiYhI0VLQRkRERERERERExMccTneBgja+Op7LbeByZf2czWLWKBsRkZJAQRsREREREREREbmiXOrpykRERPKrVAVt1q9fz4wZM9i1axcVKlRgwIABxMbGYjKZ8szz2Wef8dprr5GQkED16tW59957ufXWW73SfP3117z66qvs3buXihUr0rt3b+699178/PSfsIiIiIiIiIjI5eZST1cmIiKSX+birkB+bdq0iREjRlC3bl3i4uLo1asX06ZNY968eXnmWblyJQ899BDt2rXjlVdeoXXr1kycOJHPP//ck+aHH35g9OjRREREMHv2bAYMGMDcuXOZMmXKpTgtEREREREREREpBtnThxXkR0RExNdKzUibuLg4GjVqxLRp0wDo2LEjTqeTOXPmMHjwYAICAnLkmT59OjfeeCOPPvooAB06dOD06dPMnDmTnj17ArBixQqqVavGtGnTsFgstGvXjpMnT7Jw4UImTpyIzWa7dCcpIiIiIiIiIiIiIiJXrFIx0sZut7Nhwwa6du3qtb1bt26kpqaycePGHHkOHDhAfHx8rnn27dtHfHw8AJmZmQQGBmKxWDxpypUrh8PhIDU1tehPRkREREREREREREREJBelImiTkJCAw+EgIiLCa3vt2rUB2Lt3b448u3fvBrhgngEDBrBv3z7mz5/PmTNn2LRpE2+99RadOnWiXLlyRXsiIiIiIiIiIiIiIiIieSgV06MlJycDEBIS4rU9ODgYgJSUlBx5srddKM91113HsGHDmDp1KlOnTgWgcePGvPTSS4Wur2EYpKWlFTr/lSI9Pd3rtxQdta3vqG19oyjb1e124XK5cDldhS7D5XLhdrsui7/lumZ9R23rO2pb3/BluxqGgclkKvJyRURERERErjSlImjjdp9/oTezOeeAofzmefLJJ1mxYgUjR44kOjqagwcPMnv2bO6++27efPNNAgMDC1xfh8PBtm3bCpzvSpU9VZ0UPbWt76htfeNi29XPz4/y9nRSkpNJPX260OU4sZKWls7B3bux2+0XVaeSQtes76htfUdt6xu+alc/Pz+flCsiIiIiInIlKRVBm9DQUIAca8zkNZomv3mOHj3KsmXLGD58OOPGjfOkiYqKomfPnixfvpyBAwcWuL42m4369esXON+VJj09nfj4eCIiIgoVHJO8qW19R23rG0XZrhn7dhASGooVZ6HLCAgNJSgokLDa9S6qLiWBrlnfUdv6jtrWN3zZrrt27SrS8kRERERERK5UpSJoU6tWLSwWC/v27fPavn//fgDq1cv5pVqdOnUA2LdvH40bN/Zszy6jXr16HDp0CMMwuOaaa7zy1q9fn3LlyvH3338Xqr4mk4mgoKBC5b0SBQYGqr18RG3rO2pb3yiKdrWbLVgsFixWS6HLsFgsmC22y+o91jXrO2pb31Hb+oYv2lVTo4mIiPjGuf/DWiyF7+eIiEjpUCqCNv7+/rRs2ZLVq1czbNgwT6dw5cqVhIaGEhUVlSNP7dq1qVGjBitXrqR79+6e7atWrSIiIoIaNWoQFBSExWJh48aNdOrUyZNmz549JCUlUbNmTd+fnIiIlDhmmx9+hhnOeVig0MqUgfLli6YsERERERG5IljMJpxuN8dOZa216XA4MPmFkpjsICUj7/U3TSawOwq/xqeIiBSvUhG0ARg5ciRDhw5l7Nix9OnTh99//5358+fz4IMPEhgYSEpKCrt27aJWrVqEhYUBMGrUKCZNmkS5cuXo0qULa9as4csvv2TGjBkAhIWFcddddzF//nwA2rZty6FDh5g9ezbVq1enb9++xXa+IiJSfMxWG+bUVPj9T8jMvLjC/P0hOlpBGxERERERKRCz2USG3UXC0SQcTjcOu52jx44SXtnAdp615AL9rVStGHwJayoiIkWp1ARtoqOjiYuLY9asWYwaNYrw8HAmTJhAbGwsAFu3bmXw4MFMnjyZmJgYAGJiYrDb7SxYsIDly5dTs2ZNpkyZQo8ePTzlTpgwgfDwcJYuXcqCBQuoXLky7dq1Y/z48ZQpU6ZYzlVEREqIzMyLD9qIiIiIiIhcBIfTjcPpxu50k2F3Yne6wezOM73Nmvc+EREp+UpN0Aaga9eudO3aNdd9bdq0YceOHTm29+/fn/79++dZpslkYsiQIQwZMqSoqikiIiIiIiIiIiIiIlJg5uKugIiIiIiIiIiISGGYirsCIiIiRaxUjbQREREREREREREBsJhNON1ujp1KK1A+kwnsDpePaiUiInJxFLQREREREREREZFSx2w2kWF3kXA0CYcz/+u4BPpbqVox2Ic1ExERKTwFbUREREREREREpNRyON0FCtrYrPlPK1cOi8VS3FUQEQEUtBEREREREREREZErREqanbQMp9c2h8OByS+UxGQHKRm5T7cXFGAlJMjvUlRRRK5wCtqIiIiIiIiIiIjIFSEtw8n2fae8Rmc57HaOHjtKeGUDm1/OwIzNaqZh7TAFbUTkklDQRkRERERERERERArMZDZhxYzZbMJmNRcor81qxmTyUcUu4Nwp9exONxl2J3anG8yaPk9EipeCNiIiIiIiIiIiIlIgZouFMgFW/BxpBDkdVA3IxOU28p3fYjZhy0zCkZSC2T8IS2CID2srIlJ6KGgjIiIiIiIiIiIiBWK2WDC5MkhL2IPJ30Ty6XRcrgIEbSwmQioEYwkNIqB6AwVtRET+oaCNiIiIiIiIiIiIFIrL6cBtBqfdXqCgjWEx4Xb6gdPpw9qJiJQ+Pg3aHD16lPDwcF8eQkRE5NJxueDPPyE+Ho4dy/qxWKBqVahSBRo2hDp1iruWIiJSiqjPJCIiIiIiZ/Np0KZz5860bduWmJgYbrjhBvz8/Hx5OBEREd84cwa+/x7WrYOkpJz79+37378jI6FbN2jShGJbVVNEREoN9ZlERERERORsPg3aTJ48mY8//piHHnqIkJAQevbsSUxMDM2aNfPlYUVERIqG2w3ffQfLl0NmZta20FBo0SJrZE3lyllD+Q8fhgMHYNMm2Lkz6+eqq2DYsKx0IiIieVCfSUREREREzubToE3v3r3p3bs3R48e5cMPP+Tjjz9myZIl1K9fn5iYGG6++WYqVqzoyyqIiIgUiungQZg2DbZty9pQqxbccANccw3YbN6JW7TI+p2YCF9/nTUi5++/4bnn4L774F//uqR1FxGR0kN9JhERuWK5XRiZqTjcqZiOBILhxhJcFpMtAJNmLRCRK5hPgzbZwsPDGTFiBCNGjGDr1q288MILTJs2jenTp9O5c2fuvvtumjdvfimqIiIickGh2/fg9/hsSE3NCtDceit07gxm8/kzli8Pt98OnTrB669njb6ZOjWrjGeeuTSVFxGRUkl9JhERKW0MwyA108WJVHC5wemGPEMthoE18zS29OP4pZ/Eln4CizMDO2A/J6nJL5CAmo0Iqnc1gXWaY6tQPUcQJyXNTlqGs8B1NpnA7nAVOJ+IyKV0SYI2AL/++isff/wxq1ev5syZM7Rr145//etffPvtt9xxxx1MmDCBIUOGXKrqiIiI5Krarzuot3ojJsOA+vXhrruypkEriMqV4ZFHYPFi+PFHePZZqFABxo3zSZ1FROTyoD6TiIiUVIYBJzNM7D9tYd8ZM0dSzaTYDRzuXWelCsRmNggPdlOrjJvaZVxEBJwhJGU/AWf2Y3Wk5CzYZMLsF4jJLwB3egqG045hTyd992+k7/4NAP9qV1GubQxBkS0xmbIepEvLcLJ93ykcTneBziPQ30rVisGFbQYRkUvCp0Gbffv28fHHH/PJJ59w8OBBqlevzqBBg4iJiaFq1aoADBw4kIceeojXXntNHRARESk+hkG91Rup/usOAFw39cTS+5asdW0Kw88vK+ATHg4ffQTjx0NQENx7b5FVWURESj/1mUREpCQ7nWli83ELW45bOZWR+8wDfhZwuMAAHG4TB5LNBKUfo9nprVTxO+RJZ5jM2IMqYQ+siCOwIkZQOaqGl6dsmRACajfBVq4ybnsGjlOHSN/7J+l7/yB9/19kHvqbox9MwVaxBuU79SekYTQADqe7wEEbm7WQ/TsRkUvIp0Gbbt264e/vzw033MAzzzxDdHR0runq1q1LfHy8L6siIiKSN8Pgqi9/puqmXRjAoZv+RYX/PIFlyzbIzCx8uSYT9O6dFbh5/XUYMQKCg2HAgCKruoiIlG7qM4mISEljGLA3ycyGQzb2nLZ4tltMBjVC3dQq46JmGTeVywdyVeP6JO37myAbHDqRhpF4gLKJ2ynjSgLAbcBOZ1U22utglK1G+3AI/GeJUIvFlGPaM7NfAP5V6uJfpS7lom/BmZLEmV8+5/TGr3CcOMCx5S+S2iga2gy8VM0hInLJ+TRo83//93/cfPPNhIaGnjfdfffdx3333efLqoiIiOTOMLjqyw1U3bQbw2RiR69o0jq3oUJRLXxpMsHEiWC1wiuvQGwsXHUVtG5dNOWLiEipVtR9pvXr1zNjxgx27dpFhQoVGDBgALGxsedd0Pmzzz7jtddeIyEhgerVq3Pvvfdy6623eqXZvXs306ZN4+eff8ZqtdKqVSsmTpxIzZo183eiIiJS4rkN+O0QrNzhz5HU/42qqV3GRbNKThpWcOH3vxgOAUEm/KxmMAzMiQepkvAb1owkAAyThdQyEWw2NWT98XIcyLTAMdhyyqBLbTtRlfK3row1pBxhnQdQLvoWkn76hKQfPyR124+Y4rcS1OA2Toc1KcomEBEpES6wovLFWblyJceOHct13/bt2+nVq5cvDy8iInJ+hsFVX/wvYLP95miONa1T9McxmWDWLLjlFrDboU8fyOP/RxERubIUZZ9p06ZNjBgxgrp16xIXF0evXr2YNm0a8+bNO+/xH3roIdq1a8crr7xC69atmThxIp9//rknzeHDh7nzzjtJSkpi+vTpPPXUU+zatYvY2FgyMjLyf7IiIlIiGQb8nWjm9d9svPUbHEk1YzMbtKziYGSLdAY0ySSqsnfAJpvr5AECd6yE7d9gzUjCbbaSUqERx+v1JLVKC+qGBzK4aSYDm2RQKdBNutPE57v9efcvf5ILMKmBOSCYsH/dQfUhL2CrVAsj/QzhmxYQtnd11gmIiFxGinykza+//orxzx/Ln3/+mV9++YVTp07lSLd27VoSEhKK+vAiIiL5YxhEfv4TVf7c4wnYHG/ig4BNNrMZ3noLWrWCnTuhf39YtSprBI6IiFxRfNVniouLo1GjRkybNg2Ajh074nQ6mTNnDoMHDyYgICBHnunTp3PjjTfy6KOPAtChQwdOnz7NzJkz6dmzp6fckJAQFi5cSGBgIAA1atRg5MiRbNmyhZYtWxasAUREpMSIP23mu/02DqZkRWQCrNC6moNrKjsIsuWdz+xII3Dvb2Ru3IMFwGwhrXx9UspHYlj8c6SvVcZNbFQGvx6xsi7Bxv4zFuZtCuBef4NW5x9s6sW/al1qxE7lwJdv4vjzKyru/QpbximONrgNzLlElURESqEi/6bo/fff5+OPP8ZkypqX8qmnnsqRJruDctNNNxX14UVERC7M7Sbyiw1nBWzacrxJhO+PW6YMfPhh1tRoa9fC44/DCy/4/rgiIlKi+KLPZLfb2bBhA2PGjPHa3q1bN9544w02btxIu3btvPYdOHCA+Pj4XPN8+eWXxMfHU7t2bVatWkVsbKwnYAPQrFkz1q9fn6+6iYhIyXPwDKzZ40/8P2vWWM0Gbaq76NnISnqaE1ces5eZ3E6CTu0g+NROTEZWIkeFetgiWpCWbsJw5T3qxWKGNtWcXFXexYqd/hxLM/Pyejf9UjO5vVb+R8uYrDb82w3gsD2YCttXUPbwz1gzT3Oo2V25BoxEREqbIg/aPP744/Tp0wfDMLjrrrt44oknqF+/vlcas9lMmTJluOqqq4r68CIiIufndhP5+QaqbP4nYNO7LccbR1y64zduDG++CbffDlOnQvfu0KnTpTu+iIgUO1/0mRISEnA4HERERHhtr127NgB79+7NEbTZvXs3wHnzWCwWkpOTqVatGk899RSff/456enptG/fnieffJIqVark97RFRKQEOJaYxqofDvJXQtZXgmaTQYvKTtrVcBAWbCHYz0p6Wi4ZDYOAM/sIOb4FiytrakxnSDgh0X1ISUzB5gekp+erDmGBBnc1zWBVvB9/HLOy9PdMTrCH0XdUwmLJ/0oOybXak+lXlqpb3iH41A6qbX6Lg1GxYNZsBiJSuhX5X7HQ0FBa/7O48qJFi2jSpAnBwcFFfRgREZGCc7tp8PlPhG/ei2Eysa13O040rn3p63HbbXD33fDGG3DXXfDnn1mjcERE5Irgiz5TcnIyACEhIV7bs8tNSUnJkSd72/nyJCYmAvDiiy8SFRXF9OnTOXnyJNOnT2fw4MF89NFHBAUFFarOhmGQlpbbN4OSLf2fL0DT8/lFqOSf2tZ3Ctu2DocDh92O3enOdx6b2Y3b5b5k+XCbcTgchfrbVRTn53A4PGUVJB/AydMZ/LbjBPFHsv6/MGHQuIKTdjUyKeefNcrF5TQw3H64nC6c7v+NfPFLP0HZE5vxy0wCwGkN5nTFJhDegJBy1XCf+AvDbcmR73xMQM+6GTQMD2HZFvj692OcSvuRcX2j8M9t8ZxzZLdnapmryGgaS50t8wk+tYPwLe+Q0KA/mHIP/uT13l+wbS/ivb+S6W+t76htfcdXbWsYBiaTKV9pizxo89FHH9GpUyfKly/PoUOHOHTo0HnT33LLLUVdBRERkZzcbhp89hPhW/4J2NzSjhONiiFgk236dFizBvbuhfHjYf784quLiIhcUr7oM7nd5/8S0GzO+eVVfvLY7XYAKlasyOzZsz3l1K5dm379+vHpp5/Sr1+/C9YvNw6Hg23bthUq75UmPj6+uKtw2VLb+k5B2tZisWDyC+XosaNk2J35zlc2JIDK5f05dvw46Zl2n+cL8LNStbyJ44eTceU1f1guivr8Tpw8ke98xxLT2Xkog8On/heMaFozkOaBhwgxpUIGnM4aOEOgv5XQYCtnkpNxOF34OdOonLqbMvbjALhMFk4ERXAqsCaGy0xQSgoOh53U1DT8zf6efPlls5q5JhwCoiws3hLEbztO8Oir6xnQuSKBfnmPuMnZnn4kVelJi0OfUPbEZlLsLv6qdD3k8uXohd77vNq2sO+9ZNHfWt9R2/qOL9rWz88vX+mKPGgzceJEli1bRvny5Zk4ceJ505pMJgVtRETE99xuGnz6I+Fb40tGwAYgNBTeeitrarQFC+Dmm6F37+Ktk4iIXBK+6DOFhmat4pyamuq1Pa/RNPnNk52vY8eOXoGfq6++mtDQUP76668L1i0vNpstx7Rw4i09PZ34+HgiIiK81hSSi6e29Z3Ctm1isoPwykaBRqIEB1gJCgyicqVKlySfn9VMxQoVKR9aNd95shXF+TkcDk6cPEHFChWx2Wx55gvyt3DgeCa/7Eon/nCyZ3vdamVo07gSzatbObP7NE6799eC/lYzfjY/ygVYCDq5k6Az+zFhYACpZeqQXKERbos/2XMEBISEYrP5ERwchJ/NQpnQ0HyPtAGwmk2EhITQOTyAelERTP1gNwdO2nnvh2QeH3INoUF5f7mZsz2rcqBMMDW3L6b6mb+wla3Csdpdc+TL672/UNtezHt/JdPfWt9R2/qOr9p2165d+U5b5EGbNWvWUKlSJc+/RUREipPJ6aLRRz9QcWfCPwGb9pxoVKu4q5WlQwd4+OGstW1GjMgK4JQrV9y1EhERH/NFn6lWrVpYLBb27dvntX3//v0A1KtXL0eeOnXqALBv3z4aN27s2Z5dRr169Shfvjwmk8kz4uZsLpeLgICAQtfZZDIVemq1K01gYKDaykfUtr5T0LZNyUjD5ucH5gJMH+ZnxWwxX7p8VjM2m61Q10xRnp/NZsv1ae3UDAe7EpLYFn+Kk9nDZ4B61cvSqnE4FcoGYrOasVgysVrMYPGehsyKA9O+X6l4ZAcmI+t4mcFVSK7UDJd/WczA2eNfrBYzZrMJs8WKyQwWqwVc+Q/aWCwmLBYLfjY/mtYO44VRVXlszg/EH07mubd+55nhbSkb4p9r3tTMNIKCArCdFXhx1WrJCbOTSn+9R+WEb3CUq01qpaZe+S703ufVthfz3ov+1vqS2tZ3irpt8zs1GvggaFO9evVc/53N6XSSkpJCOX0pJSIiPmZ2OGm8fB1hew7jtpj569YOnIqsUdzV8vb00/Dxx7BjBzzyCLz+enHXSEREfMwXfSZ/f39atmzJ6tWrGTZsmKdTuHLlSkJDQ4mKisqRp3bt2tSoUYOVK1fSvXt3z/ZVq1YRERFBjRpZ/2e2atWKVatW8cADD3i+yPrxxx9JS0ujZcuW+a6jiFx6KWl20jLyPx1XtqAAKyHnGeUgJceZVDsJR5PZfTCJA0dTyA6Z+NnMNIoIo0ndCpQPPX+A3eRyEJS4k+DEv8HtxATYAyuSUqkpjsCKPj8HzBYwXFQLzODpgY148u2/2HvoDI+9so6nBjWmTFDOkS+2TCdVAzJwnTuyJ7IFzsxDWHd/T5W/FrO/5TgcwZV9fw4iIkWoyIM2Z3M6ncyZM4fatWvTq1cvNmzYwJgxYzhz5gytW7dm1qxZlC1b1pdVEBGRK5QtNYPGy9dR9sBxXDYLW2/rRFKdEjiU3d8f5s7NGmUzdy4MHJg1AkdERK4IRdlnGjlyJEOHDmXs2LH06dOH33//nfnz5/Pggw8SGBhISkoKu3btolatWoSFhQEwatQoJk2aRLly5ejSpQtr1qzhyy+/ZMaMGZ5yH3jgAQYNGsQ999xDbGwsJ0+e5MUXX6R58+Z06dLFJ+0iIkUjLcPJ9n2ncBRgSi6b1UzD2mEK2hSQYRieAIIJwGQi+5nqAjxcfd7yM+wuTiU7OZV+isRkB4dOpHA6xXskZHhYEE3rVeDfbWpz+ETqed97szODwMRdBCXtxuz+Z82b4AqcrtCYjIDKRVPxfDCZzLjtGdhPJFDJ6eSxG/x4bpWTfcfSeOrN33isazBBft51SU+3k3wyFdc5I3usNj8Cm9xIxsmDBCTtodrmN9nfcgyGtfAjQ0VELjWfBm1mzZrF/PnzefTRRwF49tlnKVeuHKNGjWLhwoW89NJLPP30076sgoiIXIECjiVy1VsrCUxKwelvY0vff3GmZgl+uqpjR7jnHpg3D+69FzZtygrmiIjIZa8o+0zR0dHExcUxa9YsRo0aRXh4OBMmTCA2NhaArVu3MnjwYCZPnkxMTAwAMTEx2O12FixYwPLly6lZsyZTpkyhR48ennJbtGjBokWLmDFjBmPGjCEgIIAbbriBRx55BMs5U+uISMnjcLoLFLQpjZxON2dS7aRlOHC63BhGVpDDZDJhMZswm8/+bcbhdFEm2I/0TCcul4HT7cblcuN0GZ7fTpcbu8NFpsOF3eEm0+HC6XLz89YjuNwGqRkO0tKdpGQ4SEt3kJbh4HzLudisZk99rBYTFosZyz/1yXp91r/NZlxuA7dhYDbBydMZJKdlnVuWFE+5JhNUCQumVpVQ6tcsR7kQf4ICrAT65/2Vn+nMEYIP/ox/4h7PNGhOv1AywpsRUqMejtMZBZrmrMg4nRguB9VC4LHr/XhmdSZ7T7qZtiaVR7r44W/9X+DG7XTgtNtzBG0AMFs42nwI1X56Cf+0o1TZvozDTQZdsiCUiMjF8mnQ5vPPP+eBBx5gwIAB7N69m7///psXXniBW265hXLlyjF16lQFbUREpEhZ1/+XxnPex5phJ71cCFv6/ov0iqVgVOfUqfDpp7B9O0yeDP/5T3HXSERELoGi7jN17dqVrl1zLrwM0KZNG3bs2JFje//+/enfv/95y73mmmt4++23810PERFfcbsNDp1I4fCJNI4npXEsMZ3UdEdxV+uCiipw5m8zUTksmPDyQVQKC6J6pRD8bRcOoJvcToKPb6b8oR+xJe4me8Ixe0AYaWENyAyphp+ftcQENqqVNfNIF3+e+zqTHcfdvLzOzgOd/LBZ8lc/t38oh5veRc3fZhN67A9SKjQmuaqm9BSR0sGnQZtjx47RvHlzAL799lvMZjMdO3YEoEqVKiQnJ/vy8CIiciWx2+GJJwieOhWTYXC6RiX+6tMRR3ApGQZfrhzMmgV9+8ILL8CgQZDLotEiInJ5UZ9JRCR/Tqdksi3+FNvjT5Gayzo9FrOJoAArNqsFkykr9mAYWUEe1z8/bnfWSBq3YeByGZw9RiN79IvVkjXaxWox42e14Gcz4+9nwc9mIdDfSu0qZQgPCyI4wEZwoI2gQKvn335WMwAGWceGrBE/bsPgyIlUtu45SYbdlVUflxuXO2tET9ZrA5f7n9E+bjcWs4ngABtVKgSTnGYnwM+Kn9Xg+PGjVK1S1bPG2HkZBgFJeylzZCOhxzZhcaZnbTaZsYdWJ7Vs3aw1a0pIoOZcEWFmHu7sxwtr7Px52M0rP9i5v70fFnP+6ptRtjYn63Sj4p4vqbzzQ9LL1YWAEjwDg4jIP3watKlcuTIHDhygZcuWfPPNNzRq1Mgzd/Lvv/9OlSpVfHl4ERG5UuzcCQMGwK+/YgKOtWrCjs7NMKylbMqW226Drl1h9WoYNy5r5I2IiFzW1GcSETm/1HQHP245zI59iZ5tAX4WaoaHUis8lKsbVCIt3flPoOasL/MNA2tGIv4ph/BLP45f6nGsmYlYHOlYXelYXVmL2BuGASYwzP64rQG4rf44/UJx+pfD6V8WZ0A5HP5lcfqHYgouT7OrwqkcFlTg83A43JQvE1CgETdBAVZqhoey5+BpHE43drv9wpncLvxP7MbYs52ae3/Dmpn0vzr4lyWlehuCr7qWlEP7cOanvGIWWcnCA538mPatnV8S3Mzb4ODe62wXzviPU7U6E3ziLwLP7KPKtiWcir7fh7UVESkaPg3a3HTTTUyePJlPP/2UjRs38sQTTwDw3HPPsWTJEkaMGOHLw4uIyOXu9Gl49lmYORMcDihfntSnHic+ZS9GSuKF85c0JlPWaJuoKPjss6yfm24q7lqJiIgPqc8kIpI7l8vNH7tO8Ou2o55AR83KITSuW4E6VctgsZhzBDXM9hRCTmwhKHE3gUl7sJ0VsMiN9yNeaZB5/joZmEjdUJHDFatiLVcFW1gVbP/8tpYLx+xXDKP83U78Uw4TlLSboMS/CUzag9mVFYyxAm6LH8mVojhT5VrSy9fHZrMSHHiBEy1hmla1cH97P2Z+b+f7PS4CbXBro3yuuWO2cKTxndT+ZTpBSXuw71kLVW7xaX1FRC6WT4M248aNIygoiF9++YUHH3yQO++8E4DNmzcTGxvLyJEjfXl4ERG5XJ0+DQsWZK39cvx41rbu3WHuXBypp2DFvOKt38Vo2BDGj89a42bsWLjhBggoJVO8iYhIganPJCKS05lUOyt/iudYYtZ0XuFhQXS4ujrhuYxwMRyZhBz8maDDvxGU+Dcm438jWQyTmczgKtiDKuMIqoQjMAyXLQRbUAiVq1TgwLFUnC43GGB22zE7MzA7M7DYz2DLPI01IwlrZhLWjNNYM5MwGy6M5OOkJx8H/sxRF0tIeWzlq2AtXwVb+SrYyodjLVsZS3BZDEc+pjM7H7cLW0YSYWn7CTu0l6DMk/gnH8A/+SBmw+WV1OUXgiXiGo4ER5Jcpj6GJf8jU0qqljUtDI+28dp/Haza4cKCiZaV8pfXEVSRY1f1psr2ZZT9+3OMxm2Ago+WEhG5VHwatDGZTAwfPpzhw4d7bV+6dKkvDysiIpcjlwt+/RUWLYK33oLU1KztDRrA9OnQo0fW6x2niq+OReX//g/eeQf27IFp07Jei4jIZUl9JhERb/uPJLPq531k2l34+1lo37waDWqV9576DLBknqbMvv9Cwo9Usqd6tmeE1iC1QiPSytUlo2xtDIt/jmMEBVgxlQ/FkXY6/9OVGW4C3Kk0KO8kxJmII/EojsTDOBOP4kg6gjs9BVdKIq6UREjYlmsRtc1+uPxCcPqF4LKF4Lb4YZht/wRVTIABhoHJ7cTsysDmzsQgk5rJp7DYUzCR++gSlzWQ9LIRpJW/irTyV2GtWIOaVcqSfvA0RgGmYyvp2texkuGAhb84+HKHgT3TSpuqjnzlPVO1NaHH/yT45Hb4cRE0G37hTCIixcSnQRuA5ORkfvrpJ9LS0rLmCT3HLbfc4usqiIhIfjmdsHs37NgB+/dDQgIcPAinTkFiYtYIl8zMrHQuF/j7Q3AwBAX97yc4GMqXh7CwrJ8KFXL/9/kWzjSMrGNu3QpbtsBPP8GXX8KJE/9L06QJjBkDQ4eCrfQ/OeYlJAReegnuuAOefx4GDYKIiOKulYiI+Ij6TCIiWTZuP8r3mw4BULl8IN2ui6BMsHe/wZJ5hgp7V1H28M+Y/hlh4giswOkqrUir2gJXyP8Wms/rSy+rxYzZbMJmNee63+02cLnP+XtsMuPyL4ulakVCcxnx40pPwZl4BMdZP87EIzjPnMCVehrDac8azZNxCltGwR40yz4Pt8lCmrUM7tCqOEPCyQytTkZoTRyBFbKmWs5Ob8r9vC4HN0RaSXcYLN3kZE28DZvJ4JoqzgtnNJk4GtmHiJ+nYT6yg5AKP5MY3sr3FRYRKQSfBm2+//57xowZQ3p6eq77TSaTOiAiIsXFboeNG+GXX7JGsPz2G+zcmbU2zKUQHJwVxClblgCTiUYZGQRYLJCUBCdPZtXvXGXKwI03wvDh0LmzV8fkstOvH8ydC2vXZk2X9uGHxV0jERHxAfWZRETAMAw+/HaXJ2DTuE4YHa6ujtXyv+CDyZlJ2P5vKZ/wrWfNlszy9fBv0Z0Dljq4DRPVypqxuDIueDyb1UGQ00XVgMycwRnAZQng0Gl3rvvyYgkMwRJYH/9q9XM9v2PHEtm+PR4j/cz/s3ff8VGU+QPHPzOzJbvJppBAEghJKEoHaSLSbAjYxQaiqNhFseAp6t1Zfnc2PFDRE089T09PVBQVEGkWpCNF6T0hdNKz2To78/sjggSSkMom8H2/XvNK2J3nme/zZHfZme88z4MWcGMJuFGMAEooiGocPgdTMBUFU7VgaBFYHE7iGzdij9uCz+LCa1rZd+AAyUnJ2Cq6Ce4Ud3kHK/meEN9tMflupxWbZtKxceiE5XRHIwrPGELspq9ptPkbCuPaErK5TkLEQghRNXWatPnHP/5By5YteeKJJ0hMTERVT91MvxBC1Ht+PyxbBj/9VLItXgxlXSByOkvWVWnRAlJSSraEBIiNhZiYkvVVLBbQtJI6PZ7Sm9tdMionN7ck+ZKbW/r3vDwwjJLpzX6f4kylnBmF09KgY0fo3BkGDYJzzz31RtWUR1Fg0iTo0gW++gq++64kYSWEEOKUIudMQojTnWmavPfNemYs2glA747JdGvbpNQ+kdkbaLJ5KlZ/AQDe6FSyW1+OknQmzRNdsKcAVQEt5MO7axN6sIwbwI5itWpoLjtFBV5CodKJGYvVhiO1Lapqr1LSpiKKoqBYI9CdCQRtjSpdzhlhQUl0EdhTQEg3yr6x7TR1ZXuFnKIgK/ZZmL7NhlUL0KbRiRM37vQBxB5cjZa7i8Zbv2F/hxEnIVohhKiaOk3abN++nX/+85/06NGjLg8jhBCiLKZZMrXYrFkwe3ZJksZ3zF1n8fHQuzf06AHdu5ckR1JSoC4vGBlGyTRrh5M5+fn4vF52ZWWRmp5ORHJySVyNG5ckkE5nh6eAmzix5OfatSVT0gkhhDhlyDmTEOJ0Zpomk7/8jW8XZwBwXrcUOrSMP/K8FnDTeOtXRB9YDUAgohHZrS/D3bgzKEqZN37pwQD6CZIbqqlhBBX0QOC4pI1oGBRFYVDLID4d1h6y8NUWG9e39XNGkxMUVDU49xbMGX8j+sAqCpr2wht3/OgoIYQIpzpN2jRt2hS3212XhxBCiPorLw8KC2unrujoknViTqSgAObNKxmV8d13sHt36eebNIEBA0q2886Ddu3qNkFTFlUtaUtcHLRqBYDh8VC0cSNGu3aSqDnWM8/AJ5/A1q0lyZtx48IdkRBCiFok50xCiNPZx99t4tvFGSgK3HJJe2JddoK6AYAzZxNJGz7BEnRjopCXOoCcFoMwtdN3WjBRmqLApa0CBEKwOdfC1M12RthDdDhRucYtKGzeh+ishTTZMo3Mno+clHiFEKKy6jRpc/fdd/Pmm2/SqVMnUlJS6vJQQghR/xQWwpIlJVOI1YTdXjIapqykzeHRNDNnloyoWbwY9KMWYYyIKFn7ZcgQuOiikmnPTuV1YE5F0dEwfjzcfDP83//BiBHQvHm4oxJCCFFL5JxJCHEq0jTthPtM/3kHn87bAsB913ShW5smrN2eDUaIhB2zaLTrBwD8kUnsb3cD/ujUOo1ZNEyqAleeEWDqZoUd+RqfrNW4N92HNcpR5v4WTUVVFYraXELk/lXYi/fTaP8ycpPOJsJmwWZRsVr+uLHRMMxamyZPCCEqq06TNtOnT+fAgQMMHDiQRo0aERERUep5RVGYN29epetbuHAhEydOZNu2bcTHxzNixAhGjRqFUsEFyBkzZvDWW2+RlZVFs2bNuOuuu7j66qtL7bN9+3bGjx/P8uXLsVgs9OzZk3HjxtFcLooJIWrK76950uZYpgmrV8PUqSXb1q2lnz/zzJIkzZAh0L8/OMr+sioakBEj4O23YeFCGDsWPvss3BEJIYSoJbV9ziSEEOHmCxooNhd5RUHcPk+Z+yzfsJ93vloLwFX9W9G9bRP8gRCaL5+kNf/BUZgJQH6zPhxqfTmmdpqsaymqxaLCNWf6mbLRTlaRxrvfZTL6UpVmMcePyrJagjj1EEnRGma7gfDb18Rv/5bItLbEJdqJitLRtD+SNCEtgr0FxslsjhBC1G3SJikpiaSkpFqpa82aNdxzzz0MGTKEBx98kJUrVzJ+/HhCoRB33XVXmWVmz57No48+ysiRI+nXrx/z5s1j3Lhx2Gw2Lr30UgD27dvHjTfeSIsWLZgwYQJer5dXX32VUaNGMX369ONOmoQQImxWrYIpU0oSNTt3/vG43V4yiuaSS0oWqm/ZsuJ6amvatspO2SZqTlHgjTegWzf4/HOYPx8uvDDcUQkhhKgFtXnOJIQQ9YHXF2LDzmzi8kystuMvmu/NdvPF99swgS5nJJCW7GJrVj5J5n6aLn0dS6CIkCWCA21vwN2k88lvgGiQrBpc39bPJ5ud7C0M8c8Z27i1i07cMfcwWq0amstOUYGXkOEgJiIWiy8fc/ln5EeegREdjUUrGWljsdpwpLZFVWVdUSHEyVWnSZsXXnih1uqaNGkS7dq1Y/z48QD0798fXdeZPHkyI0eOLDO5MmHCBAYPHsyTTz4JQL9+/SgoKOC11147krSZNGkSUVFRvP/++zh+vxs9JSWFe++9l3Xr1smCoEKI8PL5SqY8e+WVkmnQDnM44NJL4dprS5I1Llfl66yNadsqmrJN1I0uXWD0aJg0CR54ANasgTJOgoUQQjQstXnOJIQQ9UUgoBPQDVBLj1AoLA4w/eedhAyTlk1jOLdzU/SQiW3XMlg3BUtIxx+ZxN7Oowg64sMUvWio7BYY2VXhw9+s7M0L8N9fVW7u4Mdl/2PkjGpqGEEFPRAgFDIpbNyZRlkLcORtRSUOPcIOlZjeTwgh6tJJWX16+/btfPjhh7zyyiscOHCAX375pUqLbQYCAZYtW8bAgQNLPT5o0CCKi4tZuXLlcWV2795NRkZGmWUyMzPJyMjANE3mzJnDNddccyRhA9CpUycWLlwoCRshRPi43fDVVyWLzn/wQUnCxm6H668vGWlz6FDJiIsbbqhawuaww9O21WQTJ99zz0HjxrBxI7z+erijEUIIUYtqes4khBD1XUAP8e3inXj9OgmxEVx0dnNUIGHndzT69SMI6XibdGRfrwfB1Rjr72uLVLQdXp/k8L9VWb7ztOe0KTx8eXMaOUzy/Sr/22jHEyx//6CzCb6oZihAonvbSYtTCCEqUqcjbQzD4K9//StffPEFpmmiKApDhgzhn//8J7t27eKjjz6q1FQAWVlZBINB0tPTSz2elpYGwM6dO+nTp0+p57Zv3w5QYRlN0ygqKqJp06Y8++yzzJw5E6/XS9++fXn66adlmgIhxMnn9cK338KPP0IgUPJYUhLccQc89BDEy91mp7XYWHjpJRg1Cp59FoYPh2bNwh2VEEKIGqitcyYhhKjPTNNk3vJd5BT4cNgtXHJuC6wqJG36jOh9ywGwdbqIUOsLaWoqQOVuEju8PklyhB8UhUirSmEF6x6Hk6JQaoH7yjg6KQUQ0utn2+qb2EgLI88yeG+lQo5XZcrGCG5s7yOinKug7sadsLv3EhXMxec5SMiVfHIDFkKIY9Rp0uaf//wn06dP529/+xvnnXfekcTKn/70J0aPHs3EiRN56aWXTlhPUVERAFFRUaUej4yMBCjzDrTDj1VUJi8vD4BXXnmFzp07M2HCBHJycpgwYQIjR47kq6++wul0VqXJQMmXEY+n7MX2xB+8Xm+pn6L2SN/Wnar0rSUYxAwG/0i+VMQwUJcvx/LNNyi/f+YZzZsTGjQIo2dPlAsuQHc4oBY+W6oUV3lUFSUYRK+lzzqv14umafh8vhrXZRgGoVCIkB6qdh2hUAjDNPDXtJ+g1vuK667D/vbbaMuWoT/0EIEPPqhwd/k8qDvSt3VH+rZu1GW/Hk42iKqrrXMmIYSoz5au28/OvYWoqsIl56YTbTdpuvbfROZswkQh0KIPaqN0inauIxQyT1zh745en8Rij8SVnoZaC3PKKEclSkodz6JS1f/uQl43ht+D1a+THOEjZFShfUclpUKGScBhYf/BkzJpToMX54Dh7f18tC6C/cUqn22yM6ydH5v1+H1DtiiKY1oSVbCd6Jx15EUlUeU/tBBC1KI6Tdp88cUXjBkzhmuuuYZQ6I+LZ+3atWPMmDG88sorlarHMIwKn1fL+B+5MmUCv1+IS0hI4I033jhST1paGjfccAPTp0/nhhtuqFSMRwsGg2zcuLHK5U5XGRkZ4Q7hlCV9W3dO1LeappHo86EfOIBxgov1lrw84qdPx7p7NwDBRo3Iu+givK1agaKgHjqEJTubA253qc/S6qhKXBVRnc5ai0lVVRIsFhJ9PvxbtlTynrpy6rJasSs63mIPhQUF1a5HccaiB3Xyc3IIFhbWIKLa7avDHGPG0O7mm7FMncqOCy6g6OyzT1hGPg/qjvRt3ZG+rRt11a82WWerWmrrnEkIIeqrzZl5rNp8EIALujenabRKs9Vv4yjMxFCthM6+EX/AwB4MHFlnpLKOXp9E0cq4Gl8NqqYRHWFB5fgEi6YqWP35BPMrOX2lomAE/QQO7MRb5KEop7jaSSlFtWJrdgaW2shKnSYSHCbD2vv4eH0Eu4s0vthsZ0Qnvcx9ixq1wVGYgc1fQERRFr7o1JMcrRBC/KFOkzbZ2dm0a9euzOcSExMprOSFMNfv6zUUFxeXery80TSVLXO4XP/+/Uslfs466yxcLhcbNmyoVHzHslqttG7dulplTyder5eMjAzS09NLrSkkak76tu5UpW8te/diJiZCeaNHTBN1xQosn3+O4vNh2u2EBg/GOO88YiwWYg7vFxGBkpBATNOmtdKGE8ZVGbUcE5mZ5C1aRIzDgbUmF/2iowm1SiPaFY1iVD/9ExkVhcVqIT4+Hn4foVlttd1XAO3aod99N9a33qL1a6/hW7oUyuk3+TyoO9K3dUf6tm7UZb9u2yZzwFdXbZ0zCSFEfbQ/p5gfVmYB0K1NE9o1tZGyZjIRRbsJWZwc6HYnCUnJsGt9mCP9g6ppKCEfnqxtBHylzyk0TSEqPhLNUblzFsUegTUuGXQdQw/WMCllIrdHVF1SpMkN7fx8ssHOzgKNqRvhrl7H72dodrKdaSQW7yDq0Dp8UTINtRAifOo0aZOWlsZPP/3Eueeee9xzy5cvP7K+zImkpqaiaRqZmZmlHt+1axcArVq1Oq5MixYtAMjMzKR9+/ZHHj9cR6tWrYiLi0NRlCMjbo4WCoWIiIioVHzHUhSlWtOqna4cDof0Vx2Rvq07lepbq5Vigvj0ouOfCwaJ+nQa1pVrSv7ZIg33TddjNIoDvHDUzT+KruNAr72/pdVasp1gROIJ67DZsNVSTAGrFcPnw2q3Y69JXIaBT1HRNA3NolW7Gk3TUBUVe037CY70d2311RHPPw9ffIG6eTPOt9+Gxx+vcHf5PKg70rd1R/q2btRFv8rUaNVXW+dMQghR37i9Qb5dnEHIMElPjqbPmZE0X/0Wdvc+dGsUu7vejRmbQmXXrznZQr+P/DmaqSkYug0zVLn/9xS9dkb/iJpJcRlc28bPZ5vsbMrR+ORXGJR+/H65juYk+Pai6R6c+dsJJHU86bEKIQTUcdLmlltu4a9//SvBYJDzzz8fRVHIzMxk2bJl/Pvf/2bcuHGVqsdut9OjRw/mzp3L7bfffuSkcPbs2bhcLjp37nxcmbS0NFJSUpg9ezZDhgw58vicOXNIT08nJSUFgJ49ezJnzhweeeSRI1M6LFmyBI/HQ48ePWraBUKI05xf97MjbwdB448sjNXtpe3n32PfcwhTUcjqfxa7+3QC8xDkHDquDkdULC1CAerVveYWC+g6HJNMrxZVRQ0E5IJfVcXGwvjxcMst8NxzcOON0Lx5uKMSQghRRbV1ziSEEPVJUDf4flkWXr9OfEwEQ86Kpfnqydg9B9BtLnZ3vYdAZBKS0hAnS4tYg6vPDPDFZhsr9ihoWLggNVhqH1PRKIxvR9zB1UTmbiLYuE2YohVCnO7qNGlz3XXXkZuby1tvvcX//vc/AB555BGsVit33HEHw4cPr3Rd9957L7fddhsPPvgg11xzDatXr+a9995j7NixOBwO3G4327ZtIzU1lUaNGgEwevRonnjiCWJjY7nggguYP38+s2bNYuLEiUfqfeSRR7j55pu58847GTVqFDk5Obzyyit06dKFCy64oHY7RAhxWgoaOrpR8mXQeSifjp/9SERBMcEIGxuH9iM/PQkIgVH2eidHJ3zqDU0Dtxs2bAB/De+Mc7mgRQtJ2lTHzTfDO+/AwoXwyCPw+efhjkgIIUQV1eY5kxBC1AeGYbJscxG5hUEcdgtXdo+j5W+TsXmzCdpj2N31XoLOxuEOU5yGzmwU4qo2OtM2W1m6x0qkxaRX09Ln2x5XKq78bVgCRURkb4Izu4cpWiHE6axOkzYAd955J5dffjnLly/HYrHgcrno0qULsbGxVaqnd+/eTJo0iddff53Ro0eTmJjIY489xqhRowBYv349I0eO5IUXXmDo0KEADB06lEAgwL///W+++OILmjdvzksvvcQll1xypN6uXbvy4YcfMnHiRMaMGUNERAQXXXQRjz/+OJpW/al1hBDiWFH7cuj0yfdYfQG8cS7WXX8e3vjocIdVM35/zZM2dnvtxHI6UhR4803o1g2mToU5c+Dii8MdlRBCiCqqrXMmIYSoD6b+sJ39eUE0VWFo9xjab3oHqy+XYEQjsrreg+6ID3eI4jTWJdEgpMA3m2B+po0oq0mHxkfdQKmouOPbE7tvGRHZm9ADHkDOWYUQJ1edJW1mzJjBlClT+PXXX9H1kqx1REQE3bp1Y/jw4Vx00UVVrnPgwIEMHDiwzOd69erF5s2bj3t82LBhDBs2rMJ6u3Xrxn//+98qxyOEEJXl2pNNpynfY/EHKWiWwPrrzkN3yhc/UQs6d4YHHoBXX4X774e1ayURJoQQDURdnDMJIUQ4zVq8k+9X7gZgSEcHXXe+j9WfT8CRwO6u96BHxIU5woZNVRXsNgs2i4rVopa7n0VTUVWlzH2sFhX1NJ/k4IJWsL9QZ/leC9O324i0+UmJ+iNx43elEMzdhNVfgLZ1AbS4MozRCiFOR7WetAmFQowdO5bvvvuOxMRELr30UhISEjBNk/3797N8+XIeeOABrrzySl588cXaPrwQQtQ7rqyDtPtkPpaATkHzxqy7/nxCdpm9WdSiZ56BKVNg61Z45RV46qlwRySEEKICcs4khDgVrdp8kMnT1gLQKyXEgENTShI2zsZkdb2XkD0mzBE2bKqmEe20cmaCFbtDR9PMcve1WoI49RDJEX5CRun9NE0l0qpSeBpPT60ocHGLIEV+2Jhj4cvNdka0D/1xkVRRcCd0IG7PYtQdi9Cank/I3sBnyRBCNCi1nrT53//+x5w5c3jqqae46aabjlujIBQKMWXKFJ5//nl69OjBtddeW9shCCFEvaFl7aHdlLlYAjr5qYmsu/48DFudz0wpTjcxMSXJmptugr/9DW64AVq3DndUQgghyiHnTEKIU82u/YW89OEKDMPkvLZOBuf9D1uw8PeEzX1ywbsWqJqGovsp3rURv8WGRSt/pI3VqqG57BQVeAmFSidt7M4oXOlpqOUXPy0oClzeOkChX2GPW+OLLQ6uSCngcGoxEJlM0BGP1ZtDzM555LYdGtZ4hRCnl1r/iP7qq68YNmwYN998c5mLSmuaxogRI7j++uuZNm1abR9eCCHqj127cL3xdsmUaM0bs+4GSdiIOnTjjXDRReDzwX33gVn+nXdCCCHCS86ZhBCnkgK3n+feW4bHp9MjzcbVvmk4goX4Ixqxu+u9krCpZcFAAD3gRw8Eyt1CgQBGsJzn9EC4m1BvWFS4tq2fWLtBvl9l9p54dOP3JxUFb1IXAKKzFqP58sIXqBDitFPrSZudO3fSv3//E+7Xr18/tmzZUtuHF0KI+uHgQRg5ErWwiOImcay77jwMqyRs6pppmuQHi9hl5LFdyWOTksM65RDblTz246aIACanaDJDUeCtt0rWs5k7Fz75JNwRCSGEKIecMwkhThUeX5Bn3lnCgVwPLRvBrZZvofAAPms0GR3vRJcp0UQ9F2mF69v6sWsmB3x25mREHLn/LRiZiJHQEsUMEbt9TngDFUKcVmr9CqLX6yUm5sT/KcfFxVFcXFzbhxdCiPDzeOCyyyAjg1CjODYMH0goQtawqU3Fhp/VehbrgnvYqO9no76PnaEc9u4vwLPFX7JTOV3uNC00N6NJNaNpZcZxltmEM8xGWGr/PoaTr3Vr+Mtf4M9/hocfhsGDISIi3FEJIYQ4hpwzCSFOBYFgiL+/v5xtuwtIigzxYNyPhPL2QmQcvyUPxRkRiy3cQQpRCQlOkytbe/l8s4N12VaauUy6J+mgKITaXYz682Rce5djFFwLjVqEO1whxGmg1pM2pmmiadoJ91NVFVOmbhFCnGpME267DVasgNhYisbcQ1DfB0Yw3JE1WLoZYr2+l+XBDJYHMlgezGCdvgejghEzkdiwmSpWVDRUfOgUEyCgGHgUnc1KLpvJZS4ZADhMC13MJgwwUulnpBB1ktpWJ/70J/j4Y9i4EcaNg1dfDXdEQgghjiHnTEKIhi4UMnjl45X8ti2bRnadcUk/Q94etKg4tCGP4V9/CGe4gxSiCtJjQvRqXMDSQ7HMzbDSxGnQIgHM+HQ8Ce1wZm8k8Ms0aPFIuEMVQpwGZK4eIYSoTc89B599BhYLTJ6MkbcP9uyrUhU5eNmnuMnByyHFgy+kEfObHy2rEaZpEmmLJMoWhcvmIikqiZToFJpFNyPBmYCqNOzRIoZpsFU/wKrgriNJmpXBTLwcn/RKVmPoam1OO0sy7SxJnKE1oVlMcxq160bG919SVHjouDJ+QuzDzS6lkF1KARvVHH5VDlKkBFiq7GWpupd/mCq9itMZsy+eoWZ8w/uP0maDt9+G/v3hnXdQr78e4uLCHZUQQgghhDhFGIbJ65+tYcnafURpQf6csgglLwstMobkEc9wKOQCjv8uLkR91znOTX4okk25Vr7cYudOVwgXkNd6CM7sjehbFhM4dC22xqnhDlUIcYqrk2tRzzzzDFFRFd+n7Ha76+LQQggRPp99Bs88U/L75Mlwzjkwq+LFgw1MNiu5LFf2slHNYYuSS47iLb1TCNiw/ISHt6pWmrqa0iy6Gc2jm5MWk0ZabFqpny67q3ptqwM+M8gGfR+r8w+xau1XrAguZWPuftz4j9s3WomgpzWdntZ0zralc7Y1nWZaGYkIWzQ+rfzpwOxopBNDuhkDZnMwSv4GO5R8lih7+EHNZLuazyJ9B4t+eYwUrRF3O/pyt7M/jbX603cn1K8f3HEHvPsutjFjUP7973BHJIQQ4hhyziSEaIgMw+SNz9fw/S9ZONQgT6cvQcvbheqMJvnGZ7AlpMCBgnCHKUS1KAoMbuEjx6dxyKPy+XqN+9sYBKKb40nsgvPAr+yb+zGOwQ9WqV5nhIUop0wWKISovFpP2vTs2RPghMP4IyMj6dGjR20fXgghwuO33+DWW0t+f+QRuP12yMwsc1cTk3XKIWarO1ms7jkuSaOaCk1wkmA6iMdJnMVF41adiIpPRkGhOFiMO+CmwF/A3qK97Cncw8HigwSNIJkFmWQWlH1cgLiIONKcyaR57aQpcSRqLhqrJVuCGkVjNYoENYpYxYlWzVE7pmniNv3kmx7yDS/ZhpuMUDY7QzlkhHLYqWezM5TNXqMAs4wpziKw0snajLOtJcmZs20tOFNrUmejiFQUWptxtDbjuNnoSCYFfO/KZqa5md2BXP7i/obn3bO4y9mPR6MuJqWsZNGJKErtB34iL70EX3+NunEjiR99BC+/fPJjEEIIUSY5ZxJCVJXbE8Dj06tURlFK1p2pLYZh8s8vfmXu8l1EKEGebbEMW14GakQUyTc+ja2JjD4QDZ9Ng2vb+Hn/twj2FCl8tWQ/vbu1oPDMITgP/EZo5y9sXr2aQHTzStVntai0TWskSRshRJXUetLmv//9b21XKYQQ9Vt+PgwdCl4vDBxY7sVxD0Fmqzv5Wt3CTvWPu88cpoWzzWS6GIm0MRvRyozDcdTHc0REHGd2v5PYNp3LDSEYCrLPvY89hXvYXbibrMIsMvMzjyRxMvMzyfPlHdnWVKJZNiw4FRtOxYZDseJUbEQoVgCMXAVjvx3DU4xhGhiYeMwA+YaHAtNb4XozR2ukRNLV0YLOyV1pkeGnb1RrOjlSsCgnnue/rqQRwwMRHXi1zyvMWP4hrxbM5pdgJq95vuefnp8Y5ezDX6MupakWW7kKLRbQ9XKTeFUWHV256c4aNYKJE+Gmm0h+913899wDHTvWTgxCCCFqRM6ZhBBV5fHpbMrMJagblS7jsFtIToisleMbhsnkL39j9tJM7IrOs61WYM/dgWp3knzjX7EnptfKcYSoD+IiTK4608+UjXaWbcknKjqbbm2ToWUv2LGUmK2z2NvljnCHKYQ4hTW4qfqFEKJeMQy4+WbYvh3S0uCTT+CYhYWLCfKZuo5PtY0UKQEA7KbGhUY65xupnGUmYqNmSQqrZiU1JpXUmPLvbiv0F7KrYBeZW1aQufoHMv0HOGS4OWQUkW24OWS4yTbcFJglI38C6ARMnXzTU3aFx89iVjomNGJVJ40UJ2laPC0sCaRr8bTQ4knXEmihxdNYdaHExKC3acOBrO9IsLjCmrA5ml2zMSLqXG60dGNeYCPPu2fxY2ALb3sW8KFnCQ9HXsRjUYOIUR0VV6Rp4HbDhg3gP0GnnTAoO/TuXfk1am68kdB776H98AO2+++HH34Iz6gfIYQQQghRY0HdqFLSxmqp/L4VCYUMXvt0NT+s3I1VCfFs61+IyNmGYnOQNPwv2JNb1cpxhKhPWsYaXNDC4PudGj+s2k1ivJOUs67E3LmcqJyNRBRk4otJC3eYQohTlCRthBCiJv72N5gxo+Ri+pdfQnz8kaf8IT+vF89nojaXQqXkYn1z08VVoTMZZLTExckdHh1tj6Zjk4509Lpgu1puAiFg6hSaPrxmAM/vm9cM/v4zgIqK6oxETUtD3b4DNaijoOBUbMQoDmJVJ7GqgwisKKdAgkBRFAba2zPQ3p6fA1sZVziNxcHtPF88i8meBTwZNYTRkecdGYVULr+/5kmbqlIUAq+/jr1HD7SffoL334dRo05uDEIIIYQQosEK6iHGf7SSJWv3YVMNnjtjFY5DW1CsESQP+zMRzc4Md4hC1Jk+zU2yTRe/ZRTxzc876HBLT8zkHrj2Lid+x3fs6Xp3uEMUQpyiJGkjhBDV9e238MwzJb9PngzdugEl89PP2DKDh2c+wHZ3JiiQakYzMtSRC4w0NKqxNksdredSFptiIUGpeGFkoqIhsT3sdYJ6khMRYdTPdgYL4//EN/5feaLoKzbq+3i0aCqvFc/n/1xXcpOjV7XXAqq0KibCzJYt2XfffTSbOLFkvaXBg6Fp0zoKTgghhBBCnCp8AZ0X/rOCVZsPEmExee7MX7Hv34hisZF0w5NENG8b7hCFqFOKAtf1a0pWTgZ5RX7+++1GLuk8kKh9vxCZtwVH/g68sS3DHaYQ4hQkSRshhKgGZccOGDECTBPuuQduvRWAnXk7ue/b+/hu23cAJKrR3BHszIWh5tVL1gCq1YbNVGtnTRRVLVl7R1SboihcGXEWl9o78aF3KU8XTSfLyOPWgv/wj+K5vOwayiB7h7oZZVSN9XEswSDq0KEY8+ahrl0Lt90Gb78NMTGVn2ZNCCGEEEKcVrx+nQmfrGL9jhwcNoX/a7MW6561JQmb65/AkdYh3CEKcVJEWDUu69uCKXO2sCkzj1iXnZjkXsTuXUL8ju/Y3fVemYJaCFHrJGkjhBBVpPh82G+7DfLz4Zxz4NVXCRkh3lj+Bk9+/ySeoAebZuOR9rdzz/5U9uzbjE6w2sdTLVbU4mJY/VvNp9dyuaB165rVcRRP0IvXk1ejOlSbQaQZanBTqVkUjVHOPgx39OSN4h943v0da/U9DMmbxIW2trwcfQ3drOWvMVQt1VgfxwwG0Q8cQB86FNuGDTBnDrz2Gjz0kCRthBBCCCHEcbx+nVc+XknGvkKiIlSea7ceLXM1aBYSr30MR4vOFZZXFQW7zYLNomK1VHzjmtWiojas0wBxGoqPcTCwVyrfLs5g6br9pPQ6hz7Kcpz523HkbcXbqOJpAuUlLoSoKknaCCFEVZgmaX//e8mIhSZNYOpUtrgzufWrW1myewkAA9IG8K/L/8WZbju5s6bV3rFrY00Uu712YvmdP+RnR94OgoZe7Tqi1Ga0Nrs22LuTHIqNP0UN4nZnX553z2JS8Q/MD2yie/bfuTHibP7uuIn02j5oVV4LgQCGx4OZnFwyNdrMmfDvf5eMDkuThTOFEEIIIcQfir1Bpi/cQU6Bj5hIC8+224iyYwWoGolDH8XZquuRfUNeN4bfc1wddt3PmQlW7A4dTTMrPJ6mqURaVbwN81RAnEY6tIwn3+1n8W/7mLE6nzatz6bJ/iUk7PiOrLgzyj2f1VQF3TA4mHv8e+VEnBEWopwndy1cIUT9IEkbIYSoAsvkycTPmoWpafDpp7y7/1semv0QnqAHl83F+IHjubP7naiKCu5amM6sAQgaOrpR/ZFEeg0SPvVJIzWSV6Kv5X7nefy56Gs+9i3nf77lTN25ivvV4TwV6kUjrOENcsgQWLUK9u2Dv/0NPv88vPEIIYQQQoh6o7A4wDc/b6fAHSAuysazHbdgblkCikri1Y8QeWbPUvsbfg++PZtLpu89isftIz9jPw5nFBat4pE2dmcUrvS0BjfqXpyerjm/NVuz8jmU52XK/tbcr67AUZhJZM4mihPalVlGVRV8gRBZB/IJ6kalj2W1qLRNayRJGyFOUydvZWshhGjoFi7EOm4cAPnPPMU1B17nrhl34Ql6uKDFBay/bz1397i7JGEjTlvplgQ+irudlQlPcYGtDQFTZ8K2/9Jqz2OMd8/GZ1Y/wVVjVivcfHPJXWBTp5ZMlSaEEEIIIU57+UV+pv24jQJ3gOhIK39uvwVzywJQVJpc9RCRbc8pu6CuY4aCpTZDDxD0+9ADfvRAoMItpAdObkOFqAGrRePSc1tgs6psz1VYb+sCQPzO70rWu61AUDeqvAkhTl9yZVEIISpj3z647joUXWdr/+50iPgX0zZNw6paGT9wPHNvnkvzmObhjlLUI92sqcxr9DCzUh6nU/QZ5BseHiv6ktYH/8yk4u/Dl7xp1Qouuqjk97vuKlkjRwghhBBCnLZyC318+eM23N4gcS4bD6ZvwrJtAaDQ+PL7iWrfJ9whClFvxLrsXNizZO3ST/a1QlesRBTtJjJ7XZgjE0KcSiRpI4QQJ+L3wzXXwP797EttRNc+K9lXvJ+2CW1ZdscyHj33URldI8qkKAqDI89i9QWf8p+EO0hR49hj5DOm8FNaHnyKie55eMww3F14zTXQrBlkZsLvo8eEEEIIIcTpJ6fAx1c/bcfr10mItXNf2hYS9i0CoPFl9+HqNCDMEQpR/7RsGsNZZzam2IzgJ19bABJ2zAZTRscIIWqHXGUUQoiKmCbccw8sWUKhU6P/lbkU2+HOs+5k5V0r6Zrc9cR1iNOepmjcEtWXrU3+j39G30hzNY59RgGPFH1Oi4NPMt49G7fhO3kBRUTASy+V/P7mm/D99yfv2EIIIYQQol7IKfDy9YKShE3j2AjuSt1Gk70LALAPuA1XlwvCHKEQ9dc5HZNJjo9knqc9PtOKvXgfUQd/DXdYQohThCRthBCiIhMmwH/+Q0iBa4eGyEuJ5x89/sGrA1/FaXWGOzrRwEQoVu6NHMC2Jn/jnZibaaElcNAo4rGiL0k/+CTPFc0gxzhJ05X17VuSkAQYNQqKik7OcYUQQgghRNiVJGx2/J6wcXBH+k4Sd/8AQHbboVjbS8JGiIpoqsLF56Rh2iL5wdsegISds8EIhTkyIcSpwBLuAIQQor4KzPgay2N/QgUeGQS+C/qx9JJ/U7C74KTGoSoqJgZ5vnwMr6dmddkMokI61lqKTVSPTbFwh7Mvtzh687F3GX93z2Jb6CBPu6fzUvFs7nT05eHIi0izxNdtIC+/DN99BxkZ8Kc/weTJdXs8IYQQQggRdjkFXr76aTu+QIjGcQ5uT88kKXMuAAdbX0Fxar8wRyhEwxDlsDLw7FRm/+yhX8QmojyHiN6/gsKm54Q7NCFEAydJGyGEKEPmku9odN1QbIbJu10hauwTfH/BcwR8AQo4+UmbkGGwq2AXxUW5NaorSm3GmWZ3SdrUE1ZF41bnudzk6MVU3ypecs9mjZ7Fa57vecPzI8MdPXkschCdrM3qJgCXC/79b7jgAnj7bRg6FC6+uG6OJYQQQgghwi47v2RKNF8gRJM4B7e12E1yxncAHGp5CfmpA+RcQYgqaJ7ookv7VOZu78TVkb8Qt302RYndMTV5Jwkhqk+SNkIIcYyvFv+bTlfcgctnsjTdQvOPvuSO9pcDECAMi8b/zjANdCNY4zpqY9SOajNw6H6CoZrFI0pYFI1hjp7cENGDeYGNvOSezfzAJj7yLuMj7zKG2DvyeOQg+pvdUWr74OefDw88AJMmwe23w7p1EBNT20cRQgghhBBhdngNmyMJm1b7abpjJgDZLQaRl35hmCMUomHq0a4Js7K7k+ffQByFRO36maIWMsWgEKL6JGkjhBC/8+k+/vTtw1zx8GRa5cD+eDtp85aR3KpLuEOrNbU1aieCRFIDbTBMoxajE4qiMNDenoH29qwMZvKyezZTfauY5V/HLP86enla81jsvVxpxqFVoV5VPcESdi+8ALNmwbZt8PDDJaNvhBBCCCHEKaPA7eebn3ccSdjc2voQTbd/DUBO2kXkpg8Mc4RCNFyKonB+r5b88EN3hmo/E7tzPu6UczBlHVwhRDWd4CqOEEKcHrblbuPcd3vT7v8mM3AH+COsJMxddEolbI52eNROTTZJ2NSt7tY0Po27i82Nn+Ne5wAisLLMt41rlo+l7e7HmZj/HXuLD5DjyalwK/DnE7QEKfDnH3ks15uHN+j942CRkfD++6AoJT9nzgxfw4UQQtTIwoULueaaa+jSpQsXXHAB7733HqZpVlhmxowZXHrppXTu3JkhQ4Ywbdq0Cvd//vnnadOmTW2GLYSoQ8XeIN/8vAOPT6dRdAQjz8yj2fYvAchNPY+cloNLvgcKIarNYbeQ0OMCDoRicOBD/3VWuEMSQjRgMtJGCHHa+2z9Z9zxzR2Mnl/Efb+AqSjY//cpdO0e7tCEoLWlCf+MuZFnoi7jZd983vUsZJt+iEe80/i75zuuN9pzldmGKGxllg+FQhQVFuLyR6NpJeNzHFGxtAgFcBy9Y9++JaNsJkyAO+8smSatUaO6b6AQQohas2bNGu655x6GDBnCgw8+yMqVKxk/fjyhUIi77rqrzDKzZ8/m0UcfZeTIkfTr14958+Yxbtw4bDYbl1566XH7r1ixgg8//LCumyKEqCUeX5Avf9xGYXGA6EgbI9sVkbL1cwDyUvqR3eoySdgIUUuSEqLZ3uR8EnO+omXBclbvPxdnevNwhyWEaIAkaSOEOGXkefMo9BdWen+f7uPvP/+d//72X276FV6YX/K4d/zzOK++uo6iFKJ6mmjRPBV3Jfd2v5c3FoznY30VhxQPb2kr+cD8lSuMMxgWak8cEaXKhUIhAnoAPRTEVEpGRwUNveyD/O1vJaNsNm+Ge++FKVPkJF4IIRqQSZMm0a5dO8aPHw9A//790XWdyZMnM3LkSCIiIo4rM2HCBAYPHsyTTz4JQL9+/SgoKOC11147LmlTXFzME088QWJiIvv376/7BgkhakQPGbzz9TpyCnw4IyyM7OgjfdunKJjkNz2HQ2dcKd/1hKhl8Z36sG/BUpKN/Wi/fYM3+e5whySEaIBkejQhxCmj0F/Ikt1L+DHjxxNun677lEEfDeK/v/2Xgdvg/W9KTlY23noZh24fHuaWCFG+KIuT4dpZfBK8gif03rQwYvAoOlO0jQy3fs2H6lq8lJOUORGHA/77X9A0+Oyzkt+FEEI0CIFAgGXLljFwYOl1KQYNGkRxcTErV648rszu3bvJyMgos0xmZiYZGRmlHn/55ZdJSEhg6NChtR6/EKJ2mabJ7KWZbN9dgM2icnMnndbbPkExDQqTunOwzTWSsBGiDiiqiqdTyf+T3bWtLP35F4wTTFMqhBDHkpE2QohTil/34w/5K9znl72/8N/f/otP93HBfgfTPw9iCelsG9ST5Q8M5byTE6o4hlqPThpVRcXEIM+Xj+H11Kwum0FUSMdaS7EdZkVjsNGSi40WLFP28r72G5vVXN6z/MZX5lbuDHVhkNGy6hX37AnPPgt//jPcfz/06wctWtRy9EIIIWpbVlYWwWCQ9PT0Uo+npaUBsHPnTvr06VPque3btwNUWObwc4sWLeLrr79m2rRpzJgxo/YbIISoVcs3HGDDzlxUBUZ0MWm7838oZoiiJl3Y3/YGUOQeXiHqSii+FTmxHYjPX0939wLmLjuTM5rHhjssIUQDIkkbIcRpIxgK8vmGz/kp8ycALvU2Z+pHh7D7dbJ6t+fHZ27FqsrJy8mm/n7CGNSCFPjz0XSt2nVpdhOradRKTCHDYFfBLoqLcmtUV5TajDPN7rWetDlMRaG32YxeelN+UDN5R/uVfYqbFy1LmWFsY0yoO42rOrB23Dj47jtYuBBuugl++gks8pVBCCHqs6KiIgCioqJKPR4ZGQmA2+0+rszhx05UpqioiKeeeooxY8bQohYT+aZp4vHU7OaIU53X6y31U9Sehta3wWCQYCBAQD/xd90tu/L5ZeMBAEadbaPD9g9QDZ3CRu3Y1fo60ENAqPwKDJVgMHji96euEwgGMPVgqYdDIeP3nxUc43AVIQPDMDFCOqahEdJD6EblRyVoiolp2AjpIZTf6wrpBvoJjn10uWOPp1dUj6mUTD8cCFQqPlW1oBoGgWCAUChU4/ZBSdkT9W1121dRubLU9O93pD/1wJF+Ovb1VJ7y+rPCvx/lt/Fwn5bq25BBKBQiGAiAoWKEjEq/D3NaDSZu5Uba2/bw4/JFKOY5JCdEVqptQOXfh/VcQ/usbUikb+tOXfWtaZoolbxhWa7ACCFOC4eKD/H2yrfJKswCYFRUfya9voYIt4/9XVox9+V7MKzykRgOJQmSELsKdmHoXjSt+kmbaK056WbnWovNMA10o3InDeXRy1s/ppapKFxopNPPaM4X6mY+0NayTs3mnog5XBKdyr30JIpK9q2mlUyN1qULLF4ML7wAf/lL3TZACCFEjRhGxReQ1DJuTKlsmeeff56kpCRuvfXWasdXlmAwyMaNG2u1zlPVsVPVidrTEPpW0zQUm4sDBw/gC1T83TK7MMiyzcUADEgppuPOT1GMINmOVNbEnY+Wm43lBDeq2W0W8vI1cg+6y00OaJpGrA2KDh4kFPhjpgNVVVE0O1B2svhYQROCwQDFxR7sqp3CoiKC+omTPYc57BZckRYKi4qwhkyCwQBF7iI8xRVf6D663LHHOxxTWfVYLSoxTigq8J/wMxTAFhlNgqsJOTk56LpJYVEhwUpc8C+/fSXnJifq2+q2r6JyZanp3+9wf/r1II1cTTiUnU3Qd+KLpIdfZ2X1Z0Xtq0wbj+5bqz0C1e3mwEE/dpuFJnF2Dh46hNdfuaRdREwnUgt+5QrHSl5dlkzvdtFEOyt3ThZhs5Acp3BoX1GlEqD1XUP4rG2opG/rTl30rc1mq9R+coVSCHHK++3Ab7y/5n08QQ9RtijGJg3l0Sem48wtJPvMFL579X50hz3cYZ729JCOEQpiKtUfKWPUwiibhs6GxnCjPRca6bylreJ7LZMZkZmsNLJ5LHQO3cykylWUng5vvgk331wyXdrFF0OvXnUauxBCiOpzuVwAFBcXl3q8vNE0lS3zww8/MHPmTL744gsMwziyAei6jqqqZSaEKsNqtdK6detqlT1deL1eMjIySE9Px+FwhDucU0pD69u8oiCJTcwK7/DPK/KzalUGpglnJwW4MvAtiu7HE9uSA+1uoZnVTvM4C5pR8XTSmqrQxGUhwhZf/k6KihIK4GzS5LiREUWeIFBIVFTUCW/IiohyYbXaiIx0YrNqRLtcVRqpYbeo2Kw2ol0uLM4orFYbrigXVkvF49yPLnfs8Q7HVFY9FlUhKioKpz2mUvGpEU4inE7i4+MpLvYR7aGG7SuJ50R9W932VVSuLDX9+x3uz6gYFxFOJ40TEio90sbjD5XZnxW1D8pvYygUwu12l+pbi81OVFQUiWYsVouK0+GkSePGlRppA1AcfzmhlZtJIY8elq2s2tGBq/ql47Cf+HKszaKSEJ9AnCu5UseqrxraZ21DIn1bd+qqb7dt21bpfSVpI4Q4ZRmmwfQt0/l267cAtIhtwZ+aXc9NY94l6kAeeelJzJr0IAGXM8yRClH7muDk6VBfBgXTecWyjH2WYh5W53NF6AweMS+oXCUjRsDMmTBlSsnva9ZAGRf9hBBChF9qaiqappGZmVnq8V27dgHQqlWr48ocnuosMzOT9u3bH3n8cB2tWrXijTfewO/3c9lllx1XvkOHDlx99dW8+OKL1YpZURScTvkeVhkOh0P6qo6c7L51ewJ4fFUbia0oYKJitdlALftisccXZPay3QR0gw6N/NxgzkDTvdC4FQc73YkVK1aLik3x492zFT1Y/kgBTVPwuyOxOsq/G1ixR2CNS8ZmtWGqpad60fyh3+vRsJwgaWPRVFRVQdUsKCpoFg1CVZg+zKKhqAqaRTtSl2ZRT3jco8sde7yK6tE0BU3TKn2ntGqxoaklSQKfFqxx+0D5PY6K+7ba7augXFlq/Pc73J9H9dOxr6fy+PVAldsHJ27j0X1r0VQ0TcNqs2G1qKhaxe/D49hsFJ15CbEbvuRy52rW5Kcx75c9XNm/1e9/z/JZLSpWq/WU+eyX/8fqjvRt3antvq3s1GggSRshxCnKHXDz7qp32ZhdMuXG+ennc0v8hVx9z6u49uWQn9qEGZMfwRsfHeZIhahbPY1kXsvux5T4nXxj3cY32lZ+DR7ig9zzGcAJppJTFHjrLVi0CLZvhwcfhPfeOzmBCyGEqBK73U6PHj2YO3cut99++5GTwtmzZ+Nyuejc+fjP/LS0NFJSUpg9ezZDhgw58vicOXNIT08nJSWF+++/nxEjRpQq99lnn/HZZ58xdepU4uLi6rZhQpxiPD6dTZm5VZ4iq6K1MEIhg1mLMyjyBEiP9HKb9TsswWIC0c2xXfww5qEgHHU8PRhAr2BNFlNTMHQbZqj8i0uKXlcrNgpxanGn9iV271Ii8/dyWeRvfJ7Tkx9WZnFRz9QqXcAVQpxeJGkjhDjl7Mzbydsr3ybPl4dNs3Fz55s5z3Yml939D6L3ZFPYLIGZbz2CN6FyQ9qFaOgcpoWHgj04nzSetywmU8ln4LybeN7M4pHej6AqFdzlFRtbsr7N+efDv/8NgwfDddedtNiFEEJU3r333sttt93Ggw8+yDXXXMPq1at57733GDt2LA6HA7fbzbZt20hNTaVRo0YAjB49mieeeILY2FguuOAC5s+fz6xZs5g4cSIAKSkppKSklDrOjz/+CECnTp1OavuEOFUEdaNKSRurpeJ9F6zZw/5cD41tfu5zzcMaKMIfmUzO2ffSzOYECmoYsRCi2lQNeg2H2f/gXNsmFmqt2bIL4lwR9GiXGO7ohBD1VPUmHxZCiHrINE3m75zP+MXjyfPlkRiZyLg+4xgQ0ZZL751I7K6DFDaNZ/rbYylOlLtCxemnm5nEe8FLOU9pSdDQ+dPcP3HVlKvI9+VXXHDAABg3ruT3O+4oGXUjhBCi3unduzeTJk1i586djB49munTp/PYY49x5513ArB+/XpuuOGGI0kXgKFDh/Lss8+yePFiRo8ezYoVK3jppZe45JJLwtQKIURVrNuRw4aduTgUPw/G/4A9kEfAkcDurndj2MofnSOEOHmUph0obtIZFZNRib8BJsvW72drVn64QxNC1FMy0kYIcUooDhTzyJxHmLZpGgDdkroxsstI4tw6l947gbiM/bgT45j51iMUJzUKc7RChE8Mdl60DGFxlzieWD2e6Vum0/Odnky7YRodm3Qsv+Czz8JPP8HixXDDDSVTptntJy9wIYQQlTJw4EAGDhxY5nO9evVi8+bNxz0+bNgwhg0bVuljPPDAAzzwwAPVjlEIUTv2ZRfz8+o9WNEZ22QhLv9BdFs0u8+6m5DNFe7whBBHyW1zJY7sDTTxZXJVag5f7Upg/opduJxWkuIlwSqEKE1G2gghGrwtOVs4571zmLZpGqqicm27a7mr+13EegwuGf0qjXbspbhxLDMmP0JRs4RwhytE2CmKwm2tr2PhqIWkxqSyLXcbvd7txafrPi2/kNUKU6ZAo0awciU8/vjJC1gIIYQQQpTi9gb5bmkGmCHuT1hE4+AeQhYHu8+6C90hN6kJUd/ojkbkpl0EQD//Atok2QgZJjMX7SSvyBfm6IQQ9Y0kbYQQDdq0jdPo+U5P1h1cR2NnYx4/93EGthqIrdjHkAdeJ2HLbjzx0cx462EKmzepVJ0KFS8GqGlabYQuThOqomJikOfLJ8eTU+0t15tLwNBrNbYeTXuw8q6VXNjiQjxBD8O+GMbY2WPRyztO8+bwwQclv7/2Gnz1Va3GI4QQQgghjqeqCqqqYLWoWC0qigKzl2bg9QUZFbuUdCMTQ7VyoNudmLHNjuxn0dRS5awWFVXWPRcibPLSzsfvTMQSdDOs0W80iXPgC4SY/vMOir3BcIcnhKhHZHo0IUSDpBs6T85/kvGLxwPQL7Uf/7j4H2w4tIFQUQFDxkyiyYYMfDGRzHzzIQrSkypVr0W1EOXRoSCz7OeDQRJ9Pix795aMPCiPqoLXCydIAIlTn6qohAyDXQW7KC7KrXY9ERY7TSPb1forKsGZwHc3fcefv/8zLy16iQlLJ7By30o+vfZTEqPKWBjzsstg7Fj4xz/gttvgrLMgPb2WoxJCCCGEEACaqpAYCU69gOQIP3rI4POF+9ifU8z1Ub/QSd2GqaiEet1EQmJTwH+krNUSxKmHSI7wEzJMNE0l0qpSqMg5ihDhYKoWDra9luar3qTR/uXc0LkbH660UeAOMH3hDq4e0Bq7TW4SFUI0sKTNwoULmThxItu2bSM+Pp4RI0YwatQolAq+cMyYMYO33nqLrKwsmjVrxl133cXVV19d7v7PP/88H3zwQZlzPQsh6of97v0MmzqMnzJ/AmBs77G8cOEL7C3ay+asNVz0yD9J+m07fpeTmW8+RF7rZpWuW1M01CI3rN4Afv9xz5vBIPqBA5iJiRUnbVwuaN0aOR8ShxmmgW5U/+6pkFF3/2VbVAsvXvQiZzc7m1u+uoWfMn+i5zs9+XrY13RN7np8geefh59/huXLYdgwWLAAbLY6i08IIYQQ4nSlqgpqyId3906KcgpZugtWbNO4OOI3+tg2AuBu1ouA2w/u30qVtVo1NJedogIvoZCJ3RmFKz0NVeZcEaLSlN9Hqx09cq0qDpfTVIUg4I1tSUFyL2L2LaP5jmlc2Wc0U3/KIKfAx7eLd3J5v5ZYNHmTCnG6azCfAmvWrOGee+6hZcuWTJo0icsvv5zx48fzzjvvlFtm9uzZPProo/Tp04c333yTs88+m3HjxjFz5swy91+xYgUffvhhXTVBCFELFu5aSLe3u/FT5k9E2aL4/LrPeeXiV7BqVvD7OX/s6zT7ZTOByAi+nTSGnLap1TuQ31/25vNheDzg85W/j98PgUDtNlyIk2Bou6GsuHMFbeLbkFWYRd/3+zJ1w9Tjd7TZ4NNPITYWli2DJ5886bEKIYQQQpxODD3IjkM6s7ernG3bxqXOXwEobNIFT2Qz9EDguC0UCGAEj/q3LucoQlSFqmlER1hIjvCRaPf+PuLNRzOnv9Lb4XJJrpLEDcCh1pehW6OwFx8g/dDPXN63JTaLyt7sYuYu34VhmmFuuRAi3BrMSJtJkybRrl07xo8vmQqpf//+6LrO5MmTGTlyJBEREceVmTBhAoMHD+bJ3y8m9evXj4KCAl577TUuvfTSUvsWFxfzxBNPkJiYyP79++u+QUKIKjFNk9eWvcaf5v4J3dBp37g9X17/JW0S2pTsEAzSeNT9OBevIxhhY9ZrD3CoY4vwBi1EA9Q2oS1L71jKsKnDmL19Ntd9fh1PD3iavw74K6py1L0e6enw/vtw9dUlU6X17w9XXBG2uIUQQgghTmV5HpOpm2y01vYxLGoJAMWN2uCNOyPMkQlx6lI1DSXkw5O1DTOklxq5VllWq4Y1LgotJh1VtREyTAyrk4NthtJ03Yc0ypxPs4T2XHJuC75ZuIMdewpYsHoPF/VsXoctE0LUdw1ipE0gEGDZsmUMHDiw1OODBg2iuLiYlStXHldm9+7dZGRklFkmMzOTjIyMUo+//PLLJCQkMHTo0FqPXwhRM4X+Qq6fej0Pz34Y3dAZ3nE4y+5Y9kfCxjBg1Cic384lZLPy/asPkd+9A3bNXuXNpskUT0LERsQy48YZPHzOwwA8+9OzXP/59RQHikvveNVV8OCDJb/fcgvs2HFyAxVCCCGEOA0EdYN3l+tEG/nc7voJDROvqznuhI7hDk2I00IoePzItcpuoUAAQz9+mmx3ky4UNjkLxTRI2vAJKfF2Bp5dMlPI+h05LF0nN5QLcTprECNtsrKyCAaDpB+z0HFaWhoAO3fupE+fPqWe2759O0CFZQ4/t2jRIr7++mumTZvGjBkzar8BQohqW3tgLdd8dg1bc7diVa384+J/cP/Z95dey+rxx+GjjzAtFjJfGEfjLt1o7Kve8WwhBza7UTvBC9GAWVQLEwZNoGOTjtwz4x6+2PgF2/O28/Wwr0mNOWrawZdfhqVLS6ZJu+46WLQIyhj9KoQQQgghqs40TT5buJf8/GLGxswnQgkScCRQmNQDWUBTiIbtYJuhOPO3Y/ccJH7HLMwzrsDbVWfB6j0sW7+f9ORobhrSrsr1uj0BPD69yuWcERainHIjqxD1QYNI2hQVFQEQFRVV6vHIyEgA3G73cWUOP3aiMkVFRTz11FOMGTOGFi1qZyol0zTxeDy1UtepzOv1lvopas+p0rcfr/uYB+c+iFf3kuJK4b9X/Jezm55dql2W11/H9sorALhHDueAJ5vQ7G+rfUwlIQnOuRR/MFjmujR6MIiqqujBEywoHwyihUKEjtqqywiFME2zpB69+vXUZl2GbmKaJoZp1Er7DtNDVf9ieWxdtdK+etjnISWEYRooh/u8knUd7tOj+zYUCmEYoUr9XzWszTBSI1MZ/vVw1uxfQ49/9WDKVVM4p9k5R/ZRPviAiD59UFatInj//QRff72KrWuYTpXP2vpI+rZu1GW/mqZZ+oYKIYQQteLXrdn8uuUQY6K/J1b1oNtc5Dc7F1Qt3KEJIWrIsEZyoO0NNPvtXeKyFlCc0IFOrVrhD4RYtn4/n87bQpNGTi7ulValej0+nU2ZuQT1yt+QarWotE1rJEkbIeqJBpG0MYyKP2RU9fhZ3ipb5vnnnycpKYlbb7212vEdKxgMsnHjxlqr71R37FR1ovY01L71h/y8sv4Vpu2aBkDvxr35v67/h6vAxcaCP95bcXPm0PL3NasK77+f3OaNydu1ikANFtg0VRshI0ROwQGC7qKyd7LAgcIDFdZjMb3EBVrh8/soKiokEKx+TDZXMYZhUFxcTEFBQbXrqc26dHsUQT1IKBDEXVSEP+ivcUwAxe7iE+xdubpq2r762ec6wWAQNajjLiqiuIp1Hd23OhY8Hi97tm8nUEZy8lhxxPH+Oe8z9pexbCncwuApg3mq01Nc1vyyI/tEP/MMrceMwfree+xOTSX3mLXjTmUN9bO2IZC+rRt11a82m5zkCyFEbdpz0M3Pq3dxe9QCmltyMTQ7+c36YMqUzkKcMooT2lGQ3IuYfctI2vAxmT0foXvbJughg5WbDvLG52tw2Cz069qsSvUGdaNKSRshRP3SIJI2LpcLgOLi0hfzyhtNU9kyP/zwAzNnzuSLL77AMIwjG4Cu66iqWmZC6ESsViutW7eucrnTjdfrJSMjg/T0dBwOR7jDOaU05L7NyM/gjm/uYM2BNSgoPHnukzze+3G0Y+4kU5cvx/7sswAER48mYswYIud+gys6Gj10glEwFXBFlXx25ARzKPJnH/d8SNfxeDw4nU40S/kfoRGBEA7Di2pVcblqFlNkZCSqqhIZGYmhx1S7ntqsyxHlwmqxotqsRLlcRISqPx3W4ZgAIqMisWjV/6+pttpXL/vc6sBqtaJYLUS5XFio3KgkPaRT7C4u1bcRLhdOp4NGaa0qffx2tOPnTj9z57d38s3Wb3jm12fItebytwF/K3l/tmuHvm8f1uefJ/2ll0gaMgSzQ4dqtbWhaMiftfWd9G3dqMt+3bZtW63WJ4QQp7siT4Dvlu7kGsdyOtj2gKpRmNqXkO346x9CiIbt4BlX4ijYgc1ziKSNU9jbeRR9uzQlymHlp9V7+Mf/VhJh1+jZPincoQohTpIGkbRJTU1F0zQyMzNLPb5r1y4AWrU6/qLT4anOMjMzad++/ZHHD9fRqlUr3njjDfx+P5dddtlx5Tt06MDVV1/Niy++WOV4FUXB6XRWudzpyuFwSH/VkYbWt9M3T2fkVyPJ9+UT74jnf9f8j4tbXXz8jpmZcMMN4PfDFVdgfe012L0bTdXQNA1Tqf7dJKqmoSgKpmKWWY+pmAT0AA7FUeFxTMXABFRFrbWYNE1Ds9RsGoTaqku1KCiKUmvtO8yiWWoWV221rx72uaZpqIqK8nufV7Wuo/tW0zRUVavy54PT6WTa8Gk8++OzPLfgOV7/5XW25m/lk2s+ISYiBp57DlasQJk7F8fNN8OKFfD7TRSnsob2WduQSN/WjbroV5kaTQghao8eMpi1OINz1d/oE7EFEwW13fnoZhyEzHCHJ4SoZabFzt6OI0n95TWicjYSt+tH3K0u4qbB7QCFn1bv5sUPVvDMXb3p1Coh3OEKIU6Cqg8jCQO73U6PHj2YO3cupvnHF5TZs2fjcrno3LnzcWXS0tJISUlh9uzZpR6fM2cO6enppKSkcP/99zN16tRS2/XXXw/A1KlTuf/+++u2YUIIAHRD54l5T3DFlCvI9+VzTso5rL57ddkJm8JCuOwyOHgQzjoLPv4YNJnPWYiTRVVUnj3/WT699lMcFgezts3inPfOYWvO1pL34scfQ7NmsHkz3HEHmHJhQQghhBCiskzT5IeVu0nxbOBK56qSB7tcjpKQHta4hBB1KxDVlENnXAVAwo5Z2PN3oqoKDw3vytntkwjoBv/33lK27MoLb6BCiJOiQSRtAO69915+/fVXHnzwQX766SdeffVV3nvvPe6++24cDgdut5s1a9aQm5t7pMzo0aOZNWsWzzzzDAsWLODpp59m1qxZPPjggwCkpKTQqVOnUluTJk0A6NSpEykpKWFpqxCnk92Fu7nwwwt5cVHJqLYxZ4/hp1t/onlM8+N3Ngy45RZYtw6Sk2H6dChjekQhRN27vsP1/HzbzzRzNWNT9iZ6vduL+TvmQ+PG8NlnYLGU/HzjjXCHKoQQQgjRYPy2LRt97yZuilwEQEFqfzijb5ijEkKcDAVNz6GwyVkopkGTXz/AKM7Doqk8PrIHnVsn4PWHePpfS8jcVxjuUIUQdazBJG169+7NpEmT2LlzJ6NHj2b69Ok89thj3HnnnQCsX7+eG264gR9//PFImaFDh/Lss8+yePFiRo8ezYoVK3jppZe45JJLwtQKIcTRvtn8DV0md2FB5gKibFFMuWYKrw15DVt5C2u+9BJ89RXYbCU/JbEqRPUpNf8K0L1pd1bcuYJezXqR58tj0EeDeHP5m5i9e8P48SU7jR0LS5fW+FhCCCGEEKe63QeL2LpuI3dE/YBFMXAndCS3zZXhDksIcbIoCgfaXoffmYjFX4Dvu1cx9AA2q8afR/WiTVocbm+Qv7y9mL3Z7nBHK4SoQw1iTZvDBg4cyMCBA8t8rlevXmzevPm4x4cNG8awYcMqfYwHHniABx54oNoxCiFOzKf7eGzuY0xaPgmA7vGd+GTA65zhalGyXk1ZFiyAp54q+f255yAx8Y99VRW8XkDm0xeiMlSrDZuplv9+q4Jk4Mcrp3HXwsf572//5f5Z97P24Fom3f861kWLYOpUuP56WLUKEmT+ZSGEEEKIshQWB1i4dDP3Rc0nUg3gdTVnX4cRWBQVCIU7PCHESWJaItjbeRSpv7wGB3eQPfMtGl8xBofdwjN3nMMT/1xExr5C/jJ5MS+O7kfjOEe4QxZC1IEGlbQRQjR8m7M3M+yLYazZvwaAR+Iu4YWoodhWZQLlXEA+dAieeaZkbYwBAyApCY4aVYfLBa1bI2sgC1E5qsWKWlwMq38Dv79mldntRPTuzQdXfUDHJh0ZN28cb698mw2HNjBl4r9o+uuvsHUr3HQTfPttSZJVCCGEEEIcEdBDzFm8lZsj5pKguQlENGJvl9sxy5uBQAhxSgs6EzjY5VaSV03GvW4BtiZpxPa+iiinjefu7s24NxayN7uYv7y9mBdH9yXWZQ93yEKIWiZXToQQJ4Vpmnyw5gO6/6s7a/avIcGZwMyL3ucfMddjC4RKLhyXtXk88M9/QnExpKfDddcdv08gEO7mCdEwlfe+q+oGKIrCY30e45vh3+Cyufh51890+aQfCyc+DA4HzJ4Nf/97mBsshBBCCFG/mKbJ/GUZXBqaRwtLNrrmYE+XOwjZXOEOTQgRRr74M7D1vQmA3O//i3v9zwDEuSL4v3vOJSHWwZ5Dbp7+1xLc3mA4QxVC1AFJ2ggh6lyuN5cbpt7ArV/fSnGwmPPTz+fXe37lkpTzT1z4q69g505wOuHOO8FqrfN4hRDVd9mZl7HyrpWclXQW2Z5s+v1yH5/d//t7/emnYd688AYohBBCCFGPLN9wgM4FP9DFtgtD0djX+TaCkYnhDksIUQ9YO1xEdM+SdbkPfvMGnh1rAGgS5+Tv95xLrMvOjr0FPPvOErx+PYyRCiFqmyRthBB1au72uXR6qxOfb/gci2rhb+f/jbk3z6Wpq+mJC69fD3PmlPx+882yHoYQ9dUxcxOeEX8GS25fwuieowG4IfJbvunXpGSKw+HDYffucEQphBBCCFGvbM3Kx7HjR86P2AjAgXbD8Ma1CnNUQoj6QlEU4gfeRmT7PmDoHJg6Ht+erQA0bRzFc3f1JtJhZVNmHs+/v5xAUNa/EuJUIUkbIUSd8Aa9jJk1hos/upi9RXtpE9+GJbcv4an+T6Gp2okrKCiA998v+X3AAOjWrW4DFkJUj8UCug6ZmaW2iD0HeKPDn/j8vH8SbXVxQ/+D/JasQXY2XHUVbNt2XBkyMyEvL9wtEkIIIYSoc4fyPBxYs5Chzl9K/t3yEoqS5JxHCFGaoqg0ueIBHC26YAZ97P/07wQO7gKgRdMYnr3zHCJsGmu2HuLl//6CHjLCHLEQojZI0kYIUetW7VtF9391Z9LySQCM7jmaVXevokfTHpWrwDThww+hqAhSUkrWsRFC1E+aBm43LFkCP/543HZthpPVTf5Cx8gWXH1diHw7sHIlgdH3Hr//kiVQWBi2pgghhBBCnAzF3iC/LlnBTc4FqIpJfnIv8tIuCHdYQoh6StGsJF77J+zJrTG8Rez9+GkCBzMBaJPWiL/c3gurRWXZ+v28+slqDNOs3nFqM2ghRI1Ywh2AEOLUETJCvLzoZf7641/RDZ2kqCTev/J9BrceXLWKFiyAdetK7uC//XZZx0aIWqYqKiYGeb58DK+nZnXZDKJCOla/H/z+MvdpSQyLGj3KOOuX3HL1fL6eArY589iQ4qB9r8tqdHwhhBBCiIYkqBv8/POv3Gybg00JURR3JgfbXHPcdLNCCHE01eYgafhf2Pe/5wjs387ej54mecQz2BPT6dy6MeNu6cnz7y/np9W7AZOzzmxcpfo1VUE3DA7mVv380BlhIcppq3I5IUT5JGkjhKgVO/N2cvO0m1mUtQiAoe2G8vZlb5PgrOI6NAcOwNSpJb8PHQpNK7H2jRCiSlRFJWQY7CrYRXFRbo3qilKbcabZnROlVm2KhQnR1/P9uZ2ZvPst7lnoI+Wj6TyfkM3DLW/EociXfCGEEEKc2kzT5OPpq7g6NAOX5qPYkcz+TrdAZaaPFkKc9jRHFMkjnmb//57Dv28b+z5+huThf8We3JKz2ycx9sbujP/4F35avQe3N0ivDkkolUwIq6qCLxAi60A+Qb3yU6xZLSpt0xpJ0kaIWiZJGyFEjZimyX/W/Icx343BHXDjsrmYNGQSI7uMrNSXg+KgB58nv+QfoRDR7/4LayBA4IxWFPXqDJ6cE9ah2gwcup9gKFjD1ghxejFMA92o2ftGN/Qq7X+BvS09hv2dLXue5cydhVz6wRJ637WdfzUZxdn2tjWKRQghhBDiZHF7Anh8Vfse9PUPm+iSNYUkawE+i4sDXe/AtETUUYRCiFORFhFJ0o1/Zf8n/4d/71b2fvQXkq59HEeLzvTr2gxvQGfSZ2tYuekgFk2lR7vEKtUf1I0qJW2EEHVDkjZCiCrL8+ZR6C8k15vLE/OfYPb22QD0bNqTCRdPoHlMc3YV7KqwDlVRifYX4A24ycrbQdDQabboN+J37UaPsPHbkG4E8rZVKp4IEkkNtMEw5YuFEA1BtDWK6Huewv9/z9DlgJcx0w/S+6qX+FNwCH/Ve+EMd4BCCCGEECfg8elsysyt9MXN9duzSdrwP86wHyCo2Njf7S70iNi6DVIIcUrSIiJJvvGv7P/8JXyZ69g35e80uXIMUe37cHGvNA7leZgydwvL1u/HalHpckbVpkoTQoSfJG2EEFVW6C/krV/eYvIvkynwF6ApGle3vZpLzriE7Xnb2Z63/YR12DU7ZwXiiDZCBA0dS3YOzResAWDbwO54omxQyREAuhGUhI0QDU1sLPa77sWcOJFRa0wWppq81O1bPvtqLW9d+Q6DWg8Kd4RCCCGEEBWq7B3pWQeKsK/7mh6OnRgo5HS9jUCUTAMthKg+1e4kedifOfjNaxRvXMLBaRPRi3KIOftyBp6dRsa+Qpau28/CX/ditai0bxEf7pCFEFUgSRshRJV4gh7++sNf+fC3DwFIjkpmVNdRpMakEqziNEshI1Tyi2ly5rfLUEMGuS2SOdixRW2HLYSoj9q0QbniCvj6a96ZpbEnJZI5ZDH448EM7ziciYMmkhhVteH8QgghhBD1haYq5Bb6KFw5i6sd60oe63srenR7rJUcoWO1qFRySQohxGlGsVhpctXD5DhjKFz5HbnzPiCYvQfz7BH06pCELxBizZZD/LByN1aLyhnN48IdshCikiRpI4SotNX7VjPiyxFszN4IwAXpF3B1u6uxaTVbcK7J6q3E7jpIyKqxdcjZyFmJEA2HqqiYGOT58jG8nqpX0L8nrq2bsG3YzMzPrfx5/E2Mz/wfn6z7hFnbZvHyRS9ze7fbURW19oMXQgghhKgjmqoQZdFZsWge19uXARBqN5DYVl1ILvIRMszK1aOpRFrBV5fBCiEaLEXViB90B5a4JHLnf0jRmnmoB7LQ2tzEuZ2SCQRDbNiZy7zlu7BaNNKTo8MdshCiEiRpI4Q4oZAR4pXFr/CXH/5C0AjS2NmYkV1Gcmb8mTWuWy0oJH3+CgAyBpyFPzaqxnUKIU4eVVEJGQa7CnZRXJRbrTosQ7rRZc8e7IdyePErN9e9uZy7ZtzFqn2ruGvGXXzw6we8fdnbdGjSoZajF0IIIYSoG3rIYN68hVxv+RFVAXdsa4yIRKwZ6ygq8BIKVS5pY3dGEdOyhdzYJoQol6IoxPa6HFt8Mw58NRFj32aa5U1gb4ebGdAtlaBusDUrn++WZHBZ35akNJHrLkLUd3LbqhCiQrsKdnHhhxcybv44gkaQq9tezeybZtOpSadaqT/ms2+w+IMUNo1nT4+aJ4GEEOFhmAa6EazW5rOrbLmqP6aqwldf0X3+BpbdsYyJgyYSaY1kUdYiznr7LJ6a/xTeoDfcTRVCCCGEqFDIMFiycCVXGd9hVQyKHE0pbtKZUDCIEQygByq/hfRAuJsjhKgFiqJgtahV2qqaq3W27kazW19AiUnE4suj+ao3abT7Zy7s0Zz05GhChsm3i3eyP6e4bhophKg1krQRQpTrk7Wf0PmtzvyU+ROR1kjevfxdvrj+Cxo5GtVK/a7vF+H4bT2GqrDlkl6gykeSEKerouZN8F46qOQf992HZftOHjrnITaO3sgVba5AN3SeX/g8nd7qxNztc8MbrBBCCCFEOQzTZMnSjVzp+5pINUCxPQFPytkgU70KcdpSVA2Xw0JyhI9mTn+ltuQIH1Z/PsH8g8dtIa+73GPZElJwXvt/uBO7oJghmmz9mpQNHzKkRxNSmkQR1A1mLNxJdr7cDCdEfSbTowkhjpPvy+f+b+/n47UfA9CrWS8+GvoRrRu1rrVj2AqLSR7/FgB7zu2Ep4ksiCfE6c43+CKcB3Nh2TIYPhwWL6Z5THO+HvY1X236ivu/vZ/tedu5+KOLGdFpBBMGTaBJZJNwhy2EEEIIAYBpmixZtYPB7i+Js3jwRcTjbzEADJnaTIjTmaKqoPvwZG0l4PNXqoymKUTFR6I5jllD2GIholkbNEf5U5wpNgeHOt9CcebPNN76Da5Da2lZtIerO43g8zVO9ud4+ObnHQw9rzWxLntNmiaEqCNyq4cQopSFuxbSZXIXPl77MZqi8fSAp1k4amGtJmwAuk/8FGtOHsHExuzu26VW6xZCNFCqCq++Co0awcqV8Oc/H3nqqrZXsWH0Bh7s9SCqovLx2o9p80Yb3ln5DoZphC9mIYQQQojfrVibRd/sL2hqycevRaH2ux3TIhdEhRAlQlWcHtHQg5ih0hu6XrmDKQoFKX3J6v4AgYhG2Hy5tFrzT25psY+EWDtev87XC7ZTWCxTMApRH0nSRggBQMgI8fcFf2fAfwawq2AXLeNa8vNtP/PMec9gUWt3UF7TFZs486sFABQMH4pp0Wq1fiFEA5acDO+9V/L7+PEwZ86Rp6Lt0bw6+FWW3bGMbsndyPflc9eMu+j/fn/WH1wfpoCFEEIIIWD1pn2ctfcLzrAeIKjYyO55D0TWzrTSQghRXf7o5uzq+QhFjTuhmCGa7viaMfELaeYycHuDfPPzdop9wXCHKYQ4hiRthBAccB9g8MeD+fMPf8YwDW7ufDNr7l5D7+a9a/1Ymi9Av79/BEDutZcSaJVe68cQQjRwV10F991X8vvIkXDwYKmnezTtwbI7ljFx0EQirZEsylrEWW+fxVPzn8KvV266ASGEEEKI2rJhxyFa75xKR9tudCzs73ongehm4Q5LCHHKqnjKRUUBq0U9smmOSLLPuo2cNldjKhoxeRt52PkV3V0HKHAH+GbBDrz+So7gEUKcFJK0EeI0N3/HfLpM7sK8HfNwWp3858r/8OHVH+Kyu+rkeN3/NZ2Y3YcoTmzEgfturZNjCCFOAa+8Ah07woEDcMstYJSeAs2iWnjonIfYOHojV7a5Et3QeX7h83T/V3dW7FkRpqCFEEIIcbrZlpVH401f0N2egYHK/i634o1tGe6whBCnKlUDM0Qw/2C5m9WfT3KEj2ZO/x9bZABXu17o592P4UrEGnQz0jqbG1y/UFToZur3WyVxI0Q9UrtzHgkhGgzd0Hnup+f424K/YWLSsUlHPr32U9o3bl9nx4zftIvOH88DYOmTI0mKctbZsYQQDZzDAZ98Aj17wnffwWuvwcMPH7db85jmfDXsK77c+CX3zryX9YfWc8575/DYuY/x9HlPE2GJCEPwQgghhGgINK1m0zRvz8ojYu00+kRsxUBhf4cb8cS3q6XohBDieIqiYgR8BLKzyl3fxusNUJRTTChkll1J6gCiDq7Ffmgj51o30DJmLx/k9+VfX1kZfE563QUvhKg0GWkjxGlov3s/F314Ef+34P8wMbmz250su2NZnSZsFD3EgOc+RA0ZbB/Yg939z6qzYwkhThEdO8KECSW/P/44rFpV7q5D2w1l/X3rubHTjRimwYuLXqT7v7qzfM/ykxSsEEIIIcLJ7QlwMNdT6S2vKIhic+ELGieuvAyrNx/Ev2o6F0SUrKt3oM21uBO71maThBCifLqOGQqWuRl6ED0QKH/TDdxJXQn2vg3d5iJJy2ds9Lc0z17CzIU7CBnV+1wUQtQeGWkjxGlmSdYSrvnsGva59xFli+Jfl/2L4Z2G1/lxO380l4QtWfhiIln0pxvq/HhCiFPEPffAnDnw1VcwfDisXAlRUWXumuBM4OOhH3Nd++u4Z8Y9bDi0gd7v9ebR3o/y3PnPYbfYT27sQgghhDhpPD6dTZm5BPXKXWwMBgLk5eeQEJ8AMVU71tJ1+/htxmdc41wNwIFWl1PU7JyqhiyEEGFlJrZh77mPEb9uClHZ67na+Qubi/ewcOlg+pzTAVWteO0cIUTdkaSNEKcJ0zSZsGQCT8x/gqAR5IxGZzD5ssm0imtFZn5mpetRFRWv7q3SsaN3HaD7OzMAWPLwdfgaRSOXToUQxyvjpEBR4L334JdfYMsWeOABeP/9Cmu5qu1V9Evtx0OzH+Kj3z7i5cUvM3fHXKZcO4Uz48+so9iFEEIIEW5B3ah00iagGwQCVV+/Ycnaffww5X8Mcy4DIDttIAVp51W5HiGEqA8MWxR7O91G40PLidkwjTbWfaR4PubnpQNp0ft8FEUSN0KEgyRthDgNeINe7vv2Pv6z5j8A9Gjag9vPup2sgiyyCrKqVJfL7qJ1XOvKFzBN+v/9Iyz+ILt7tWPrpXIHmhDieJqiYpgh8n0FFBVkYZhHXXBRwT75FRKvuBHlP//hUJ+ueK69sty6FBQsqoW/nf83+qf2Z9z8cazev5qub3fl2fOe5dp211b65CPaHk2cI66mzRNCCCHEKeBwwuZ6x2IA8pv3I7floDBHJYQQNaQoFKf2Ie7MLhR++wbRvn0M9s1k86IM6HUjWGWdUCFONknaCHGKy8zPZOhnQ1m1bxWqonJd++s4P73kbgl/yF/l+ux61cbItPl6EU1XbiEYYePnJ28quWteCCGOoSoqgVCAA4W7WRvYcPznUzM46/bL6PLON8Q8PI4FSX7cKU3KrOtwcnlD9gZsmo2/9PsL/1r1LzZmb+RPc//EFxu+4JYut+CwOiqMyW6x0zultyRthBBCCFEqYaMqoHUcSF7yEChvoW8hhGhglJhkcvo+woFfptEqbzFtAuspXDye/K634ItODXd4QpxW1HAHIISoOz9m/kj3f3Vn1b5VJDgT+OjqjxjSeshJG97qPJTPOa9OBeCXe66gqFnCSTmuEKLh0o0Q/pC/zG357YPZ36UVNreXvk+8RcDvKXO/gB4AwK+X/NtpczKm1xiuansVqqKydM9S/vLjX9iUvancY/lDfvx61RPbQgghhDj1/Lx6T6mEjav7ECL63iw3pAkhTj2qBbPbNfycNIK8kJPoUD4pv7xOo51zwQiFOzohThuStBHiFPVl5pdcOfVKcrw59Gjag5V3reTc5uee1Bj6vDwFu9vLwfbprBt+4Uk9thDi1GNaNL7/2+34XU4S1+2kx+RvKl1WVVSGtB7Cn879E/GOeLI92by8+GXmbJ+DacodskIIIYQo26wlGSz4/JM/EjbdBpMw6HZZ50EIcUpL7tCN75vdyUp/OiomCTu/o/nqf2Lx5oQ7NCFOC5K0EeIUEzJCPP794zy/9nl0Q+fGTjfy820/kxpzcoeypn+/ihY/rMbQVBb85WZMTT5uhBA1506OZ8FTNwFw1gezabZsY5XKt4xryV/6/4UeTXtgmAZfbPyCd1a9I6NqhBBCCHGcz+dvYeU3U7nBueTICJuEwXdIwkYIcVro1D6Vdc2G8l93X7yGFUdBBmnL/0HUwV/DHZoQpzy5iirEKaTIX8RVn17FGyvfAOCvff/KR1d/RITl5C4aZyvy0PelTwBYc8sgcs9IOanHF0Kc2nZe1J2NV/dDMU3O/+u/icgrqlJ5h9XBHV3vYHjH4aiKysp9K3lx0YscLD5YRxELIYQQoiExTZP/zFjPlnnfMCzycMJGRtgIIU4/53RqijelJy8XXs4OvTFayE/TdR+SsG26TJcmRB2SpI0Qp4jM/Ez6/LsPM7bMIMISwUs9XuLx3o+H5aSi12tf4MwpJD8tkdW3X3rSjy+EOPUtHns9uS2TceYUct4z/wHDqFJ5RVE4L/08xvYeS7Q9mr1Fe3lh4QusPbC2bgIWQgghRIMQMkze+PxXshd/w/CokoRNdPfBJAwqPcJGUcBqUSvcVMnvCCEaOEVR6N+1GfHNUphUOIjv/R0BaLTrR1LWvI3qr9oNdEKIyrGEOwAhRMXyvHkU+gsr3Gf1/tXcOf1Osj3ZJDgTmDxkMs20Zuwt3os1YAVK1nPw6t46j7fZso20+2ohAAv+fDMhu7XOjymEOHWoqoZds594x0g7P794H5fd9Cypi9Zx1mcL2DhiEAA2zYaqVO6+lNaNWvNUv6d4e+Xb7MjbwZsr3uTyNpczpPWQmjRDCCGEEA1QUA/xyofLcG2fx9DIkul/orpcSHSvK9ALDpXa1+rXSY7wETLKXhtP01QirSqFMjJHCFFPKaqC1VJy3mTRVNSj/n2swb3TmREy+HpvN3YbCYyIXIwzfzvNlv0DI/4haNT5JEYuxKlPkjZC1HOF/kKW7F5S7noLq/at4q1f3iJoBGke3ZyHej1EnjePTQc2kehOxGotSZq47C5ax7Wu01itbi/9/+9DANZfN4D9Xc+o0+MJIU4titVKI1s07TwhQmYlpnVsHsOeMaNIfeVf9Hj1c1wdu+Nt0wp70EZclIpFteAPnXitmtiIWMb2Hsun6z9lQeYCvtn8Dbvyd3F397troVVCCCGEaAh8fp3n319G6u7vuMC5AQDnmb2ISGmLf9eG4/b3egMU5RQTCpWdtLE7o3Clp6HK/CZCiHpI1TSiIyyolCSfrZYgTj1EcoS/3GT0nRc15d05Oiv3p5JDHPfH/4zVk43nq7+RXzCCmF5XyBSSQtQSSdoI0QD4dX+ZFx5/zvyZj9d+jIlJpyaduKPbHURYIvAFfHgCHny6D0MtmTLIrlfizvUaOue1qbj251LYLIFlDwyt8+MJIU4timbBUuwjtGwhPk9BpcrsjoHIdunEb8wgfez/8et912CJT0S7qDGaolX62BbVwohOI0iLSeOTdZ+w5sAanl/4PF2SupAWm1bdJgkhxEm3cOFCJk6cyLZt24iPj2fEiBGMGjWqwosoM2bM4K233iIrK4tmzZpx1113cfXVV5faZ9asWbz77rvs2LGD6Ohozj33XMaOHUtCQkJdN0mIOuf2BHjuncV0zv6Ocx1bAYhsdy6O9E5g6JR1+dLQg+iBQLlJG4stUIcRCyFEzaiahhLy4cnaRsDnx2rV0Fx2igq85X6uAVzXCj50a2S4Xbx46CIeSVpEZFEWufM/JJi9m4Qhd6FoMuOKEDUl93wI0QCZpsmMLTP4aO1HmJj0ad6He3vcS4SlEnem15GUJetpN61kWrQfn74F3Rm+WIQQDZvu86B73JXbvMVsHtwDv8uJI6eA9K9/JOSr/lSQfVP7Mrb3WFw2F1mFWVw55UpW7FlRi60TQoi6s2bNGu655x5atmzJpEmTuPzyyxk/fjzvvPNOuWVmz57No48+Sp8+fXjzzTc5++yzGTduHDNnzjyyz8yZM3nooYfo0KEDkyZN4uGHH2bp0qXccsst+P0nHtEoRH1W4Pbz1JsLODtnOudGbMVEIarzBSUJGyGEOMWFgoGSBHQggPH77xVtmhHghrZe4h0G2X4brxzoTyi9FygKRb9+z74pfyfkKw53s4Ro8CRpI0QDY5gG/1v3P6ZvmQ7AJWdcws2db0ZTK39HeW2zFXmOTIu2dvgF7O92ZthiEUKcfnSHnU1XnoupKCT9toO4NZtqVF/LuJY80fcJUqJTOOQ5xID/DGDqhqm1FK0QQtSdSZMm0a5dO8aPH0///v15+OGHuf3225k8eTI+n6/MMhMmTGDw4ME8+eST9OvXj2effZYhQ4bw2muvHdln8uTJDBgwgOeee46+ffty1VVX8eqrr7Jt2zZ++OGHk9U8IWpdsS/Eq/9bwUXub+hmzwBVI2HQ7ThS24c7NCGEqLecVhjezk+M3SDXpzFhe1uiBt6DYovAl7GWvR88SbDg4JH9bTZbGKMVomGSpI0QDUggFODtX95mQeYCFBSGdxzOlW2uPOlzhqqKil2zH9n6TvyCqIP5FDZP5NcHbij1XEVbZRcKF0KIEylITWRXn44ANP9yPtrOzBrVF++M56m+T3F++vl4dS/XfX4dL/z8AqZZ/lQBQggRToFAgGXLljFw4MBSjw8aNIji4mJWrlx5XJndu3eTkZFRZpnMzEwyMjIwDIM+ffpw/fXXl9qnZcuWAOzatauWWyLEyZFb6GfZbwe4ITSdDrY9oFlJum4cztbdwx2aEELUe9F2k+Ht/ERaTXYXmLz0s4J94P0ozhiC2bvZ/d5jZK9dii8/hziHHV9+Dvn795bairP3Ecw/eNwW8rrD3Twhwk7WtBGigfAEPby54k225W7Dolq4vevtdEvudtLjsKgWGvlV2nkiCZkRRC9cQetvFmIqCvueepD2ShMo+0bOUjSLjVgcIIvUCSFqSWbfjsTsOkDsroPEPvQYlo//WqNvOg6rg3cuf4fXl73O68tf58nvn2Rzzmbevuxt7Ja6XydMCCGqIisri2AwSHp6eqnH09JK1uXauXMnffr0KfXc9u3bASosk56ezrhx44473rx58wA444wzaiN8IU6qA7keFi5ez92OOSRpBWB30vSGJ4lo3o5g/sETVyCEEIJGDpObOwX5YK2NLXvcvDKrmBvPvICYjB/QvPkUzJhAUUofctVoXFEuNMsfN+6qqkpinIMoxzGjcCwWIpq1QXNEneTWCFG/SNJGiAag0F/IhCUTyCrMIsISweieozkzPjxTkKmKilZUTGjxQvTsA6RO+hyAved2Iic7E+ZX7u72iLgmaF0HYCBJGyFELVFVNl7Vlx7vz8a6fSc9n32H2c+NrFFy2KJaeG3Ia7RJaMOYWWP44NcPyMjPYNoN07AjiRshRP1RVFQEQFRU6YsckZGRALjdx9+1evixqpSBktE1L730Eu3atWPAgAHVjtk0TTweT7XLnw68Xm+pn6J8wWCQYCBAQDcq3G/PoWLW/fIboyPnEqN6MRyxNL72cYz4lJLXo64TCAYw9WCF9YRCIUJ6CN0oexSuHjIwDJOQbqCHQgBoiolp2CosV1Y9pmFgGmaVypV1vLJiKpOpEAqFCAQC5e6iqhZUwyizr0Ih4/efFRzjd4djMkI6pqHVqI1KZdtHxX+LCvupEn1ztKP76USvmcq0D0rKnqhvq9u+qr5Ga/r3O9KfeqDc11N5yuvPE73Oy2vj4T49um+PrsvU9Sq/f/84nvn7e/jEr80jynmtVfTeO7otJ4rz2H6qzucTQOMIk3v7uHhjYYCt2SZTQhFc0bIvCQeWE+E5iGvXAoqjzqBYaYem/TGtv0VVCDoV/JRug2Kxouk6Qfl+cELyHaHu1FXfmqZZ6dmSJGkjRD23372fFxa+wD73Plw2Fw+e8yDNo5uHOyx0n4e0b37CVuTBEx/NznPbYXgqP4RVd0TWYXRCiNNVMMrBzhGXcMa7X5I2azEdOqay/obza1zvfT3vo1VcK677/Dp+yvyJ3u/15ouhX9RCxEIIUTsMo+IL1ap6/LS01Smzfft2br/9diwWC6+//nqZ+1RWMBhk48aN1S5/OsnIyAh3CPWapmkoNhcHDh7AF9DL3W9/XoCCjB3cF/kDDjWI2xYPA+5mZ66H0KGNaJpGfIRK0cGDhAL+cutRVRVFs1NYVEiwnCRR0IRgMECRuwhPccnFR4fdgivSQmFREUG9chduS+rR0YOBKpUr63hlxVQWq0UlxglFBf5yPydskdEkuJpwKDuboO+Pi1qH+wbKT/we374AxcUe7Kq9Rm20hsxKte/Ycscer6J+qkzfHO1wP+Xk5KDrZoWvmcq1r+QC94n6trrtq+prtKZ/v8P96deDNCrj9VSeit6DJ3qdn6iNR/ft0XWZeqDK79/Dx2ukx6LqwUq9Ng8r77VW3nvvsMp8Ph3bNk+xp1qfT4fbl9YilrsvSuSfs/exOc/K9G12+jdpT1PDQpxvL8nurRwyAhxytjxyQ1157dNsdlxR2eT4DlYq8SvkO0Jdqou+rewaT5K0EaIey8jP4Pqp17PPvY+4iDgePudhEqMSwx0WAI1+20riugxMRWHzZb0xrPJxIoSoH4rTm+EeOwbXSxM5Z+LnHGqXysHOrWpc76DWg1g0ahGX/u9SNuds5ryPz+OVrq/Qjna1ELUQQtSMy+UCoLi4uNTj5Y2mqU6ZZcuW8cADD+B0Ovnggw9ITU2tUcxWq5XWrVvXqI5TndfrJSMjg/T0dBwOR7jDqdfyioIkNjHLHWmzZVc+esYa7olaiEUxKIpKY12zS+mblE7juKP61pOP093khHf7e/whoj2Ue0d6RJQLq9WGK8qF1WIFwG5RsVltRLtclb6TvaQeC3oVy5V1vLJiKotFVYiKisJpjyl3HzXCSYTTSeOEhOP6qsgTBAqJiooqdWd9+e2zERnpxGbVatRGizOqUu07ttyxx6uonyrTN0c73E/x8fEUF/sqfM1Urn0l8Zyob6vbvqq+Rmv69zvcn1ExrnJfT+Up7z14otd5eW0MhUK43e5SfXt0XaYeqPL79/DxrBYrVou1Uq/Nw8p7rVX03jvsRJ9Px7bNarFW6/Pp6PZ1To5haLvdTN2gsakgkiiHlZiUWJS8zcTmbaSxJxOH1UJBQidQlHLbp1isOBISiHfGVjqG05V8R6g7ddW327Ztq/S+Deoq68KFC5k4cSLbtm0jPj6eESNGMGrUqAqHFc2YMYO33nqLrKwsmjVrxl133cXVV19dap9Zs2bx7rvvsmPHDqKjozn33HMZO3YsCQkJdd0kIcq1OXszF354IXuK9tDY2ZiHznmIBGf9eE2qe/aSPu0HAHad24GiZvUjLiGEOMxz0zDyVi8mdc4yLhr3L778+M/44lw1rrdTYieW3rGUy/53Gav3r+buJXdjS7Ax/KzhtRC1EEJUX2pqKpqmkZlZeqraXbt2AdCq1fHJ6xYtWgCQmZlJ+/btjzx+uI6jy8yYMYNx48bRokUL3n33XRITa34jkaIoOJ3OGtdzOnA4HNJXJ+D2ebDabKAen7T5dctBtM3zuSXqF1QFihI6sevM69Dz87FYLKX6NhhwE7LaMNWKpy/x6wE0iwahsi9uWjQVVVXQLCqW3y8AaxYNRVUqLFdWPYqqVrlcWccrK6Yyy2kKmqZVeDewarGhqSUXeY/tK83/+3RwmlbhcQ63T1UVVM2ColKjNla2fceWO/Z4FdVTmb452tH95NOCNW4fv08vfqK+rXb7qvgarfHf73B/VvB6Kk9578ETvQ5O1Maj+/boukwsNXofKpV8bf4RR9mvtYree4ed6PPp2LZZNK1an0/Htq9jkoLXH2DGdju/7LfhtMI5yW3xBkMku7cQVbAdzQxRmNQdzaKW2T5Fs2K1WLDK/3mVJt8R6k5t921lp0YDqP5Y9pNszZo13HPPPbRs2ZJJkyZx+eWXM378eN55551yy8yePZtHH32UPn368Oabb3L22Wczbtw4Zs6ceWSfmTNn8tBDD9GhQwcmTZrEww8/zNKlS7nlllvw+8sfDi1EXfrtwG/0/09/9hTtoXWj1jzZ98l6k7BR9BAxj/0Fiz9AQUoCmf06hTskIYQ4nqKw/Nm7yU9LJOpgPhc89e7v84DXXFNXUxbctoDBLQfjN/yM+HoEE5ZMwDSrMH+3EELUMrvdTo8ePZg7d26pz6PZs2fjcrno3LnzcWXS0tJISUlh9uzZpR6fM2cO6enppKSkAPDTTz/x2GOP0bVrVz755JNaSdgIUdsUSqbbOXqzaAorN+wjcdtXDI0sSdgUpPQhu+utWG127DYLag3WvhNCCFFa5yYhLkovWYdnQZaNlfut5DlSyG3SHRMFR2EGMfuWgVk752ZCnKoazEibSZMm0a5dO8aPHw9A//790XWdyZMnM3LkSCIiIo4rM2HCBAYPHsyTTz4JQL9+/SgoKOC1117j0ksvBWDy5MkMGDCA55577ki5Fi1acP311/PDDz8wePDgk9A6If6wfM9yBn80mDxfHmclncV7l7/H2oNr8YfqRxKx3T8/w/brWvQIG5uu6AM1mMdcCCHqkh7pYM74e7j6lhdJWb6JHm99zYr7rz5xwUqIskXx6dWfcvvU25maOZWxc8ayI28Hrw5+FYvaYL5eCSFOMffeey+33XYbDz74INdccw2rV6/mvffeY+zYsTgcDtxuN9u2bSM1NZVGjRoBMHr0aJ544gliY2O54IILmD9/PrNmzWLixIkA+P1+nnrqKSIjI7nnnnuOm9YhKSmJpKSkk95WcepyewJ4fOWvS1MWRQEt5CU5wkfo92l9DNPk2yVZdN79NR0i9mACoQ5DcLTuTzMlSCgUoonFil0vIJjvO1KRoVdugXkhhBBlOztZx6crLNxtZf6uCHxNIolJj0G12IjZu5SIot2oWTpm/ECgcqPWhDjdNIirCoFAgGXLljFmzJhSjw8aNIh3332XlStX0qdPn1LP7d69m4yMjDLLzJo1i4yMDFJTU+nTpw89evQotU/Lli2BP6YSEOJkWbp7KYM+GkShv5BzUs5h1ohZFPgKwh3WEc2WbqDNv0oW3s646nz8scfPjS6EEPVJfsumLPjzzVz41Lt0/c935LVqyrYhvWqlbotq4fGOj9OtRTee+vEp3lzxJpkFmXxyzSdE2eTzUQhx8vXu3ZtJkybx+uuvM3r0aBITE3nssccYNWoUAOvXr2fkyJG88MILDB06FIChQ4cSCAT497//zRdffEHz5s156aWXuOSSSwBYtWoVhw4dAjhSz9Huv/9+HnjggZPUQnE68Ph0NmXmVmmxdpfTRouYIJ6sTQR8fgwT5m/y0tf3Iym2PEJoeFLPJaDGwY61AOghA6/HjUdPwhpVchOoYo/AGpdcJ+0SQojTSb+UICEDluy1suhgHE6nj57JzchP6UPsniXY3PsJrp2LcfYQVIskboQ4VoNI2mRlZREMBklPTy/1eFpaGgA7d+48Lmmzfft2gArLpKenM27cuOOON2/ePADOOOOM2ghfiEpZtnvZkYRN/7T+zLxxJlG2qHqTtIncn8sFf34PxTTxXHMluZ2bgzsv3GEJIcQJbR/Uk/gtWZz1wWwGPPchRU0TONDl+LUdqkNRFB7s+SBnNj6Tm6bdxIwtM+j/fn9m3DiDpq6mtXIMIYSoioEDBzJw4MAyn+vVqxebN28+7vFhw4YxbNiwMsv07t27zDJC1KWgblQpaaP/PgVqKBjA7wuwaKubwcZPxFq8+JUI3M3PRXc0gkDgqDIhgn4fhh7ADJWsMaHolVsgXAghRMUUBc5LDRIyTJbvtzE3IwKL6qdrYhJ5KX2J3bMItWA/hctnEt3zElSrPdwhC1GvNIikTVFREQBRUaXvWo2MjATA7XYfV+bwY1UpAyWja1566SXatWvHgAEDqhWvaZp4PJ5qlT2deL3eUj9PZyv2ruCKz6+gMFBI35S+TL1qKqqu4tE9BINBgsEggSoM0w/8fjISOOqkJKgGCRmhKtcFoAZ1Lnz8bRz5bvLapuN74hFCs6YQ0kNVqudohm5imiaGaRAKhQiF6kldoRCmaZbUU0b79JBe6md9iCkcddV2+w47Ub9Wpq5aaV897POQEsIwDZTDfV7Jusp6zZ5K7SuzrlBJXUE9eORzcOGdl+DauY9WC35j4Nh/8vl7j1KUHF9hPapFJRgMlvt/+tH/jw1JH8KsG2Zx3bTrWL1/Nb3e6cUX13xBx8Ydq92O05l8R6gbddmvpmlWaWFNIYSoC8EQrNx8iCuURdhVnWItGk9aHwxrZLhDE0KI046iwIDmfnx+P7/luZi1w46Cn7MSG1OQdh5xWT+jFxykcMVMonteKokbIY7SIJI2hlHxHTZqGWtqVKfM9u3buf3227FYLLz++utl7lMZwWCQjRs3Vqvs6SgjIyPcIdQJVVUrdfFibe5a7ltyH27dTbf4brzc5WX2ZOwBQNM0PFYPBw4cwBOoeiIwJyfnyO+ByABel5dDhw7h9pWdtCzPpe/N4f/Zu+/wKKqvgePf7ek9hBoIoffQOxK6ICi9K4iIIGJFLD8bKgoqzYJSLKAivSuCAhp6772EEGoa6bvZ3Xn/iNmXJQkpJNkEzsdnH8yUO2fuzuzO2Ttzb+njl0hxdWL9WyNop9aQlJhI4u38PwVkNriRZk7DYkojMSEBY1r+x+wpyLL07klYrVaSkpK4fY/9S0pMKnYxFWVZhbF/kHO95ras+92/4lnnZtLS0lCnmUlMSCApj2XdWbcP4v7dSaVxxpxmJjoqmlsJt2zTFz7bmdERNyh78QZdX/ySbz9+EqNL9omBi96FKLcoEiMT79kwmfE95o4785rN44U9L3A54TKhi0KZ2mgqzfwLpju2h9GDeo3gaIVVr3q9dG0hhHCcFJOFY4dP0121H7VKIU4fgCmwOYpGnp4RQghHUamguf9tdHoD+2/o2XDBgEplpGEZb3T1u2I+shHz7VvE71mHR5PuaJzlM1sIKCGNNu7u7gAkJdn/mJfd0zT5WWf37t2MHz8eFxcXfvzxRwIDA/Mdr06no0qVKvle/2GRkpLCpUuXqFSpEs7Ozo4Op8AlmhOJN8bfc5nDNw4zdnd6g02Tsk2Y130eLjoX23y1So3GoiEgIIBUc2qut20ymYiOjsbX19f2A4qnkyfOLs74+/vjbnbPdVk1Nuym5YZ9APz17nD09WqgVWtxdXNDo6Tlupy7Obu5o9PqUOt1uLm742RxKhZlubq6olarcXV1xWr2zDTfbDGTlJiEq5srWk32H6FFGZMjyiqM/QNyrNfclnW/+1cs61znjE6nQ6XT4ubujpbcPZWU1TH7IO1fVtzc3NDqtPj6+aJ1sz+eNk4fR/9RnxEQEcXwr39n/aejUbSaLMtx0jrh5+dHWdesuznL6nusJjXZXns7A1cNZPuV7UzYO4FZnWfxZN0n870/D6MH/RrBUQqzXu8enF4IIYpSSqqJveu/p736GAA3nSujVGgAqvzdiCmEEKLgqFQQGmhEpVKx77qO9ef1qNVplKvjg2ezHtzesw5zfBS396zDq8Xjjg5XiGKhRDTaBAYGotFoCA8Pt5t++fJlAIKDM/dLHxQUBEB4eDi1atWyTc8o48511q1bx6RJkwgKCmLevHkEBATcV7wqlQoXF5ecFxQAODs7P5D1dSvuFvtu7MNozvoJhAuxF5i2Yxop5hSq+1bn6ZCnOXjzoN0y7gZ3qnhXQafTYVXnvk/nDHq93tZoo9Pq0Kg1eSor4PB52n+6GID9z3Tnamgj/LRa1IoajUaDJpsfOnNDrVWhUqnSG6Y0GhRV3vevUMrSaFCpVDnun1ajved8R8RUlGUV9P5lyKlec1NWgexfMaxzjUaDWqVGpcrf+Xdn3T6I+5dVWTqtLtOd/2nlA9j4xTh6FimR5gABAABJREFUPvMZlXaeoO03a9j5yoAsy9FpdOh1+nt+R2k0mkzfYy4uLvz15F+MXDOSX47+wtg/xhKZFMnk9pOl+6g8elCvERytMOpVjm0hhKOkJiWi2jWfEFX67wORHvXQlq6a/iuhEEKIYkGlgk6V0lAU2H9Dx9qzelxdrDxWxxfPpo9xe886LAnRxO1chaF8dXRepRwdshAOVSJuOzEYDDRu3JhNmzahKIpt+saNG3F3d6devXqZ1qlYsSLly5dn48aNdtP//PNPKlWqRPny5QHYtm0bEydOJCQkhF9//fW+G2yEuJPRbMRoyfw6FXXK1mBT1acqY5uMRaVSZVour2PPFCTX6zF0mjgHTZqZC6EN2f9MD4fFIoQQBSmqViW2vD8CgLq//k3NZduyXE6r1mK2mgmPC8/ydTXpKqmGVK4mXc0073ridT5q/xHjm44H4KN/P6L/0v7ZNuQLIYQQIu+MMTcI2DmDqqrLpCkaIku3QVummjTYCCFEMaRSQeegNBqXTu+1ZfFhhbXH09C6++DZ7DFUBhcsCdHcWjUDS9L9deMtRElXIp60AXjuuecYMWIEEyZMoE+fPhw8eJD58+fzyiuv4OzsTGJiIufOnSMwMBAfHx8Axo0bxxtvvIGXlxehoaH89ddf/P7770yfPh0Ao9HIW2+9haurK2PGjMnUrUPp0qUpXbp0ke+reLBdirvEzN0zSTGnUMWnCs83fR4nbf67lioMuqRUurz8NS7R8URVK8/W95+CfI7xJIQQxdHFjo3Y+1wvmnyzmlZTfyXF14NL7UPsltGoNCSaEjkRdSLLxpa0tDRu3LhBQGIAOl3WfS83KtOIkQ1G8uPhH1l2chk3Ft5g1cBV+Dj7FMp+CSGEEA8Ly7XTVD7xE67qVBIUZ3RtR+KaEIcxRW6QEEKI4irjiRsnHYRF6Fh8yExKGvSr74Vn08eI37OWtJirXF30DmWGvI/WzcvRIQvhECWm0aZFixbMnj2bWbNmMW7cOAICApg4cSIjR44E4Pjx4wwfPpwpU6bQu3dvAHr37o3JZGLBggUsX76cChUq8Omnn/Loo48CcODAAW7dSh+gOKOcOz3//POMHz++iPZQPAwuxV1ixq4Ztgab8U3HF7sGG5XZQsfXv8XvTATJPu78+flYzM7ZD9QthBAl1cGR3XC7Fk3NVWGEvjWPDV9O4HrDapmWy3hq8m4ms4lkUzKp5tR7djvZrHwzfJ19mbN/Dv9e/peW81uyfvB6gn0yd+8qhBBCiJypz4dR+dJqtCorV62+pLR6jgaV/Yg4vNfRoQkhhMiBSgWhlSz4uetZdUJh9XEz8akW+tV1RtfwMUyHN5IWdYWIH/+Hc883ULt62a3v4qTFzUWfdeFCPCBKTKMNQKdOnejUqVOW85o1a8bp06czTR84cCADBw7Mcp0WLVpkuY4QhaEkNNigKLSb/BMVdp0gzUnPxunPk1jG19FRCSFE4VCpCJs0GOfYBCptO0yXl79m7dxXialavsA3VbtUbZb1W8aotaM4HX2a5vObs3bQWpqXb17g2xJCCCEeWIoV12MrKXdrB6jguLUyaS2eorSfN2BxdHRCCCFySa1S0b6yQpopjfXndGw5rxCTkMbjtbV4th6N8s93aOOuErfsA643HovFyQsAnVZNjYo+0mgjHnjS35EQReDy7ct2XaIVywYboMnXq6m2fhdWjZrNn4zmVu1Kjg5JCCEKlaLV8NdHo7jWoAqGxBQefX4mnuE3CmVb1f2qs2vULhqWaUhUchTtf2zP8hPLC2VbQgghxINGbU7Bd9936Q02wD9KIyxtRuPi6urgyIQQQuRXw9JmHqtiRIXC4Ztalh5TYTR4ca3xONIM3uiTb1F671coiTGkma2kmbPv4UCIB4k02ghRyCJuRzB913SS05IJ9g4utg029X7aSMj3vwPw7xtDiGhd18ERCSFE0bA46dn4xViiqpXHJTqe7mOn43Y1qlC2Vda9LNue2kb3qt1JNafSb2k/Pt/xOYqiFMr2hBBCiAeBLjmKMrtn4JtwFpOiYZWqMz5tB+BkyHpMOSGEECVHXX8LvauZUKsUTtxSM2/jZRK1XkQ0HEuakw/6lCjKH/gabWqso0MVoshIo40QhSgi/v8bbCp7V+aFZi8UywabWku30nzWCgD2jO3F6cdbOzgiIYS4Pyq1Gr1Gj0FjyNVL5e3DX99MJC6oLG43Ynls7Aw8ohLQqDRo1QXTm6wKFQBuejdWDVzFuCbjUFB4ddOrjNswDrPVXCDbEUIIIR4kzrHnKLdnBq7GKOKszvym603VNp3Q6zSODk0IIUQBqe5rYUANI3qNwvnrySz96yyxihsRDcdicvJFnxpNhQNfo02JcXSoQhSJEjWmjRAlyZnoM0zdPpWktCQqeVXihabFs8Gm2todtP70VwAOjujGoZGPOjgiIYS4P2qdHmd0VE9ywmjJw/0pLp5EzJyM03Nv4X7lOh2efI/4BXOoVtqfo2rjfTWqaNVazFYz4XHhtmmvtngVbydvPvr3I77Z9w2nok4xq+ss3A3uOZbnYfDA29k73/EIIYQQxZVKlT5mAYD7lR34nFiOGivhZl82u/Wkbas6aDX23+9ajRqVjGkjhBAlWpCXlacaWFh80ono26ks//ssPVpXhoZjKX/wG/QpUZTZ+yXWwLfBp5KjwxWiUEmjjRCF4OStkwxePpgEUwKBnoFMaDYBZ52zo8PKpPqqMNp+tAiAo4NC2Tu2l4MjEkKI+6fS6lAlJWHZEUZqYt7uxEoFjg8MpfaCtThFXMV74JNEffcpmsp6zOS/0Uaj0pBoSuRE1AmMZqNtehWfKoxrMo5v93/Llktb6LKoCxOaTSDALSDbsgxaAy3Kt5BGGyGEECWeJSURqzHZbprOaKaMPglOrUNzIX38mv3GSpwI6MbgtoFo1GmZyjEYLOjUalQqVZHELYQQonCUdoPnewQx548IYuJTWbn1HF1bVPr/hpvkW6Ss/pi04R+g8y7t6HCFKDTSPZoQBex01GlCfwolKiWKQM9AXmz2Ii46F0eHlUmtpVtp9+FCVIrC8b7t2Ply//Tb2oQQ4gFhSU3BnJyY51eSQcWhIR1J8fVEGx1L8Jg38Lh0rUBiMpqNGC32r7oBdXm15at4Gby4mniV9/95n4PXD2Zazva6o9FHCCGEKMmsxmRSI0+TGn7c9ko+uw/rX7NsDTbrkhtwzL0V3crfJvniURLOH8n0So08BxazNNoIIcQDwNtNR/+OVSnr54rJbGVd2EWOX7cSETIWk2splMRori78H2kxVx0dqhCFRhpthChA52LOEfpTKNcTr1PDrwYTW07EVe/q6LCA9K55NCoNBo2BkF+22LpEOzGkM/vefAqD1ilX4z7oNXokFRJCPOhMHi6cerI7aWUC0N+KpuvTU/A+F1lo26vkVYk327xJkFcQyWnJzNo9i80XNqMoSqFtUwghhCgWzGYUSxqKJQ1z/C2Me1eiS7iOUdEyP6Edt71r0qWSEUuaCbMpm1da5qdvhBBClFxOei0921SmSnkvrIrC5r2X2XEumWuNxqL2LoclIYarC9/BFF14OZoQjiSNNkIUkAuxF2j/Y3uuJlyltn9tfn7iZ9z0bo4OC0hvsKms8sHvVhLtP1tGky8WA3B9WG9Sx42hrtGLuqmeuXpVSTbgbFGhUcnHhxDiwWZ2cyH6hWdIqRaEc0w8jz37Ob6nLhfa9jydPHmlxSu0KN8CBYWlJ5by4+EfSbPID1FCCCEefKaoK8TtWImSEk+sxYWZ8V1xL1WWDhXTpEMAIYR4CGk0ajo3C6RBNX8A9p28wZp9Mai7vY7OPxBLYizXFr6DKeqKgyMVouDJmDZCFIBLcZdo/2N7rsRfoaZfTf4a/hep5lRHh2WjUWkw3E7E/dU3cNmxB4Dwjk2IrOYHf2/MU1kGv/KoGnVALY02QoiHgNXNlfNffkTAK2/jf/QCPcZ8wR8znudGgyqFsj2dRseT9Z+kvEd5lp1Yxs4rO7meeJ0xjcfg5eRVKNsUQgghHC0l/DhJJ7eDonDR7Mf8hPY0rqChRTm5cUEIIR42KrUKnfb/f3N6pGF5/L2c+XtfBOeuxPHJ0lO8O+R1VBumYroZzrVF71BmyHvo/QMdGLUQBUt+dRXiPl2+fZn2P7bn8u3LVPetzt9P/n3PAaQdQZeYQuCrk3HZsQdFpeJ09+aEN62GOSUpz2M9WIzFpzFKCCGKgsXDjT+/eY1rIVUwJKbQfex0gjbvL7TtqVQqOlbuyIRmE3DRuXAx7iIf/fsRZ6LPFNo2hRBCCEdQLGYSjmwh6UQYKAp7jJX5Mr4LrYI0tChndnR4Qgghiphao8HDSUsZp1TKuRhtr8513BjTrSJuThoibiTy8pz9xIQ8ic6vPJak21xd+D+Szh8kLe6m7WVJSXT07giRb9JoI8R9uBJ/hdAfQ7kUd4mqPlX5+8m/Ke1W2tFh2XG7Fk23ER/hvmMfik7LqX6h3Kgf7OiwhBCiRDG7OvP7rBe41LY+WpOZTpO+I2TRZijEMWdq+tfkjdZvUM69HPHGeKbvms7G8xtlnBshhBAlQmKyiZsxydm+bkRe4/rK6aRePo4CrEluyC9JrRjYQEuTshZHhy+EEMIB1BoNKksqyRGnSDh/xO7lm3iOZxqaqOClIj7ZzDu/XeKIVyhaT3+sKYncXD6NhEN/kRp+nNTI01iNyY7eHSHyTbpHE+IOsSmxxBvjc7XsjcQbDFw+kItxFwn0DOSnx38izZJGeFw4apWaFHNKIUebs4BjF+k+aS4uMQmk+XoTN2IQsU7JYJVuBoQQIq/MzgY2TRtD8xlLqfvr37T6ejW6s+Hs/d9ToC+cbZZyLcXrrV7n56M/sztyNytOriA8LpxGZRsVzgaFEEKIApKcauZUeAxpZmumefr4CAIOLUCbGocRHT8ktOGUuRz9alloUl5FVFzRxyuEEKL4sKSZMJtMmaa7aVS82kbHL4fV7L5sYc4e6Bbcie4em7DE3yJu5yo8QjpiKFM43VkLUVSk0UaIO8Qb49l5ZSdGs/Gey8WlxvHJ9k+4nngdPxc/JjSdwOno05yOPg2Au8GdKt4O/IJQFJr+sZ8e329GY7YQU60Ctz6fjPula3DjtOPiEkKIEk7RqNn5ygDiy/nT4oslNN10iID4b/n702dJc3MulG0atAZGNBhBsE8wS44vYf+1/fRa3IvVA1dTN6BuoWxTCCGEKAhpZmumRhv36wcIOPUbaquZWJUnX8c+QrTiQZ/qRmr5qZCfKYQQQtyLQatifGsdFY6pWHbEzO/ntVzw6cRz3v+iio0g/sBG3OqacKpY29GhCpFv0j2aEHcxmo0YLdm/ride5+Owj7meeB0fZx9eav4SbgY3u2VM5sx3AxQVTaqJjpMX0mvuRjRmCxfbN+D3BW9iDvB3WExCCPGgOT4wlA1TnsFk0FFx90l6jpqG6/WYQtueSqWiXcV2vNriVXydfbkYd5Fm85qx8PDCQtumEEIIUaAUK37n1lHmxM+orWbOE8inMd2IxYP+NY1U9c78RI4QQgiRFZVKxRN1dbz2iB5XPZyO0fK/iHYkeVcFRSHxyN/c3rUaRZHvFlEySaONEHkQnRzNZzs/42bSTXydfXm5+cv4ufg5Oiwbj4ibPD7iU2r8sRerWsX2cb3YNHUMZtfCuftbCCEeBmq1BoPGkOl1vX0TFn4yimRfT3zPRdJn6EcE7Tmb5bJ6jR6NSoNWfX93Dwd5B/Feu/doE9iGFHMKw1cNZ8TqESSaZJBNIYQQxYtKBTqtGp1WjUExUv7oAnwubwFgu9KA2TFtUbRODKlnIchTflQTQgiRdw3Kafiom4HKvioSTGrePN+cS271AYjf/wc3V36BNe3evekIURzJc8dC5NKtpFt8sesLYlJi8Hfx56XmL+Hr4uvosGwqbj1E+3e/R5+USrK3O7+82JPUTs3Rq1SODk0IIUoslU6Hj96DmskWLIqT3TyLxUJizWac/bYeVd7+DNdT5+k47nOuPT2A6yP6gfr/740xpOnxU5KppvbnqNqI2WrOd0zuBnd+6PUDC48s5IN/PuCHQz+wI2IHi/ssJqRMSL7LFUIIIXLDkpKYq8GddUYzZZxSsdy+gW7vT6gSo1DUOlamtWbb7Qq4OWuY0KMS2ltnkN/ThBBC5Je/m5p3Ohn45UAaf56xMP1yfZ7wd+cRZSdJJ3divh1FQN/X0bp7OzpUIXJNGm2EyIXrideZvms6calxBLgG8FLzl/B2LvwPe61ai0aVfod3dtRpZkK+Wk6dH38H4Gb9Kmz+aDQ3FBMBWid0Gh0GjQG1WR6sE0KIvFJptGiTUrHsDiM1+bbdPKvZSkp8PAkeHhwZ8AhBG/SU3nuSsvMW47wtjLN9Q21POqq0zlh9KqKvF4zGoMFM/httADRqDe8+8i7tg9ozZMUQzkSfofn85nza8VMmNJuAShrshRBCFBKrMZnUyNNgvvd3WUqKiZQLp3EJ34HKmkaaxoXvEh7hTKofXk4KI5poqOSn5Wp0EQUuhBDigaXTqHiyiZ5q/mbm7k5j5a3KXHDz4Cm3bRivniVywUQC+r6GU7lqjg5ViFyRRhshcnA14SrTd00n3hhPGbcyvNT8JTydPAt9u1q1lsoqH/yikqmZ7JrpDm8Ap0sRVHpnOi5nLwJws38Prox/kqoqFWUSE3EzuaGxaNBo9XjhnN5HgRBCiDwzpyZjTrbvgsxitmBKiidNq8Kq1XCmU0PiSntR9fc9eJ+9Qr2vlnGydxsSyvph1lpQXFMLPK62Fdty6NlDPL3maVafXs1LG19i04VN/NDrB/xdZSwzIYQQhcRsRrGkZTtbURRMF/bjenE/KiBB78f0qEeINrvg72xlYC0j3gZN0cUrhBDiodCikpZAbzWzw9I4HOfHx8mdeLHUdtwSb3F14f8wtH4SXa1H8lSmi5MWNxd94QQsRDak0UaIe4iIj2DGrhkkmhIp71GeF5u9iLvBvUi2rVFpMCSlYj10BGPUeczWO5IiRaH07uNU/GMXGrOFNBcnzj/elpha5WDbZtvd3zoPD9RaNU7epdCEtMOKNNoIIURhulm3MokB3tRa8S8uMQnU/2kTF9s3IKZFg0Lbpq+LLysHrOSbfd/w8saX2XB2A/Xn1Of7Xt/TpUqXQtuuEEIIkRXFnEbCsW1Yrp1HBVx3Dmb6tWakWrWUc7PQv4YRZ52joxRCCPGgKuepZnJ3V5aedWX9HvjgekdG+e6mmuUCxm3ziTp3nOgaT6Bocm6I0WnV1KjoI402oshJf0lCZONs9Fm+2PkFiaZEAj0Debn5y0XWYHMnxZiKOTnR9lLdvEWNH9ZRed12NGYLMUFl2P90N25W8rctk5ackH73d3JC+rTUpCKPWwghHlbJpbw5+FRXblWvgNpqJfivA9T4cT2aW4XX/4tKpWJsk7HsfWYvNf1qci3xGl1/7sqYdWNINCXmXIAQQghRACzJ8cTtWo3p2nlQqTjl2phPr7Yk1aqlspeFQbWkwUYIIUTh02tUPN0liPefaYGLuxtfRbdiQ2oICuAeuYsyu2fA7eukma05voRwBGm0ESILh64fYubumSSnJRPsHcxLzV/CVe/q6LDwPR1Bo7nr8Tl/FatGzblOjTg2sD0mdxdHhyaEEOIOFic9J3u34cyjzTDrtbhH3MD/k5n4Lt8AilJo260bUJd9o/cxvul4AL7d/y3159Tn3/B/C22bQgghBIDp1mXidqzAkhCNSu/EPq8ufBNRC6uiopavmX7VjeilRzQhhBBFqGGNUsx+tT3NapdhY3Jdvo7vSBLOGBKvUXHfDNyv7y/U/EyI/JJGGyHusi18G3P2zSHNmka9gHq82PxFXHSObRTRJaZQc8W/1F7+D/oUI4mlvDgwshtXm9SQcWqEEKK4Uqm43qAK+0d1J75iGdSmNMpPm0OnsZ/hej2m0DbronNhVrdZ/DX8LwI9A7kQe4F2P7Tj1T9fJdVc8OPqCCGEeLgpikLS2X3E7/sdJc2IxtOfDU6PsfB8KQBalE2jV1UTGvn1QQghhAN4uhl4a0RThneryQWlPJ/EduecuTRqi5EyJ36hzLGfUEvvBKKYkcsmIf6jKAqz98zm+0Pfo6DQqkIrxjQagz4XfVwWYlA47z1Ig29X4X/qMopKxeWWtTn4VFeS/b0cF5cQQohcM3q5cXr4o9zu0wOrQU/ZXcfpN+B9ai3ZgspsKbTthgaFcmTMEUY2GImCwuc7P6fhtw3ZG7m30LYphBDi4WI1pRK//3dSzu0HQFu+Ft8ld+WPS86ogEeDTbSvmCb3mQkhhHAolUpFu4blGdK1Om6+/nwZ35H1yQ2woMb91hEq7fkM16gTjg5TCBtptBECsFgtjP99PJ/v/ByAblW6MazeMDRqxz2/73I9msCX38P7pyXoUowkBnhzcERXLj3SAEUr/QoIIUSJolKR9EgrTi+cyc26weiTUmk9dTFPDP+YgEPn8l4cufv1y9PJk/m95rN20FpKu5XmZNRJms9vzssbX5axboQQQtwX8+1bxO1YQdqtCFBroPojfHq5CUduqDBoYWwLNY3KFN7NCUIIIUReebs78Xi7YNqGVGCLuQFf3O7GdYsnWlMC5Y7MJ+Dkb6ildwJRDGgdHYAQjpZqTuXJVU+y5PgSVKgYXHcwbSu2dVg8KouVmsu30fSrVeiTUlG0Gi63rs/lZtVRpE8BIYQo0UyB5fjj+7eovHQTTb5ejd+ZK/QaNY2z3Zqxa0IfUvw8cyxDq9ZitpoJjwvP9XbrlqrL74N/571t77H69Gqm75rOkuNL+KLLF/Sv3f9+dkkIIcRDRlEUUsKPk3j8H7BaUDt7kBjckal73YhNUfByglcfMeDnbCbylqOjFUIIIeypVCrqBPtRsYwHW/e7Mu2GF92dD9Le6QSe1/bgEnuW6zUHkuJdxdGhioeYNNqIB0JsSizxxvg8rxeVHMXodaM5cO0AOrWOTzp+gq+zL0aLsRCizJn/sYu0/uQX/E9dBiC5bg0Se3YjUhWLYk1zSExCCCEKlqJRc6LfI1zo2IgmX6+ixqrtVP19NxX/Ocz+Z3pwvP8jWPW6bNfXqDQkmhI5EXUCozlv31dP1HiCYO9gfjz8I5EJkQxYNoBVp1Yxo+sMSrmWut9dE0II8YCzpiYR/ed8W3doOv9ATni15bvtakwWKOuhYmJ7Pf5uahKSHRysEEIIcQ/uLnp6tA7idHgsfxzWcyyhAoNdt+OXGkuFg99wu0wz4qo/Bvg5OlTxEJJGG/FAiDfGs/PKzjz9eHUl/grTd00nOiUaF50LE1tOpGNQRw5eP1iIkWbNEJdI0y9XUnNVGABGdxcOPt8H95798N53HG7EFnlMQgghCleqtzv/vjWMk0+0odXUxQQcu0iLGcuo89sWDozqzpnuze/ZHabRbMzXTQbV/arzbrt3WX92PZsubOLXY7/yx7k/+Lzz5zzZ4EnUKnmqUwghHkSWlESsxvy3pBivXyT6z/lYEqJBpca5amNWxdVmw+70LtDql1UzrpUeV70MYCOEEKI4sP8+UqlAp82c69St4kflcp78e8iDqeE+9HLZRyuns3he241b1DHMqsEoLTqjkjxJFCFptBEPjLz8eHX4xmEWHFxAqjmVUi6lGNd0HNV8qhVyhFmwWqmxejtNv1yJ0+0kAE4/1oLd43uj+PvTOE3GrhFCiAddVK1KrF4wkeprd9J4zhrcr0XTbvJP1P9xI/vGPMaFjo1AXbAJgkFrYFi9YTzX+Dne+vstjt86zsg1I/ly75e83+596gbUzXOZHgYPvJ29CzROIYQQBcdqTCY18jSYzXlaT1EUUs4fIOn0blCsaNx80NRsz6zD7hy7nt5g06u2lr71tKjV0mAjhBCiGFBrQLGQFnfTNklnNFPGKRWLVcm8vAtU61CG89c8WLnTjX3xlennspuyxJG6ZS4RJ7dgaDcStW+FXIfgbNDi5qIviL0RDyFptBEPFatiZd2Zdaw/ux6Aar7VeLbRs7jp3Qp0O1q1Fo1Kg0FjyHaZgH0nafLFYnxPpo9JEFO1PLvfGM7NkPTGI4PGgNosrfhCCPFQUKs53asV57o0odaybYR8/ztel2/Q8c15RP3wB/vG9ORym3rpt4cVEI1KQ5BXEG+0foO1Z9ay6tQqDlw7QM/FPWlbsS19avbBw+CRq7IMWgMtyreQRhshhCjuzGYUS+67XbYak0k4vIW06CsAGMpVI7Fefz5dHcGtRCsGDTzbQk+zinKzmRBCiOJDpVJjNaViioqw3ayQkmIiIToJiyWLRpv/lAJG1YU9kX7MDO9OC90pujkfhuvnSFvyNkqVVig1OoEu+9/7ANRqFTpPZ9JM9j+9qw0uaJwL9jdI8WCSRhvx0EgyJbHg4AKO3ToGQPtK7elbqy9adcGeBlq1lsoqH/yikqmZ7IpFcbKbb7gcSbmvfsLrnz0AWFycuTZqIDf7dSdAqyEgNX05jVaPF84F+gOdEEKI4s3ipOfo0E6ceqINdX79i/oL/8TvzBW6vvw10VXKcXh4Z251Dy3QbZqtZkKDQgkpHcKKUyvYE7mHbeHb2BO5h57Ve9KuYjs0avkxTgghHjbGaxdIPPEviikV1FrcarXiELX4bskVjGkK/m4qXm6rJ9BbbjQTQghRTN1xs4LVnIbZZLpno02GJgFQw0vF3xE1+Di6Er1d9lJffxnV2X+xXNxLSkA9jN6VIZsu0zQaFS6+rmic73jSRqvFqVx1abQRuSKNNuKhcD7mPPMOziMmJQadWsfQekNpXr55oWxLo9JgSErFeugIxqjzmK3pXw7apBQqbDlAwJ4TqK1WFLWK601qEhHaGLOrHrZtsivHybsUmpB2WJFGGyGEeFCo1fd+CtPGw8CJZ3tzbmBn6vywgRpL/sb3XCSh73xP8jdruT32aQwdq2LUFVxs3s7ePB3yNO0qtmPxscVExEfw2/Hf+Pfyv/Sr1Y9a/rUKbmNCCCGKLasxhcQTYZiuXwBA4+6DoU4HFp5yY+v59C6d65bR8HwrHW4GyVWEEEI8mNwNCv1qmolT+7LqeFd2xZ2jt8te/EnALXIPhlunSPSvi8m1dKYbrhWNCqtZj2L5/+nyjSnyQhptxAPNqlj549wfrD2zFqtixc/FjzGNxlDBM/d9UOaXYkzFnJyINTWZcntPU2HXCbTG9Aac6CpluRDakBQ/T8ACyYmZ1jc7uxZ6jEIIIYqOSqfDR+9BzWRLpqcws2XwJO3ZZzgxaBB+K/6g1JJ1uFyLwuV/n9L3M3eO9WvHsT5tSPb3KrA4q/hU4c02bxJ2OYxVp1ZxNeEqM3fPpLpvdZ6o8QRB3kEFti0hhBDFi/HaeRKPh6GkpYJKhXPlBtzwrMc3/yhcTbCgAno186dL+XgUSxoJydmXZc7FncxCCCFEcVfVX8ObfcuzcVsyX53rQT3VObo4H8bVFI935HaMLv4k+tfD7CRdRYuCI4024oEVlRzFT4d/4nT0aQCalm3K4LqDcdY5F8n2VSYTZXceo+yOo+hTjAAklvLmQoeGxAWVLpIYhBBCFB8qjRZtUiqW3WGkJt/O8/pJFdy4/EJfyh25SNntR9DejKLBvHXU++F3wkMbcWpgR242qJrrbjX1Gj0alQatWovRYrSbp1apaVuxLY3KNGL92fVsC9/G6ejTfLL9E0JKh/B4jccp7SbfZUII8aCwGpNJPB6G6cZFIP3pGtfa7dh03Zslf5sxW8FNp9CvvoZWjXy5duYmptTUbMvTaTV4usngy0IIIR4MapWKeqUVKrulsfd6MJ9EVuYR/THaOp3EkHwLffhfpHoEkuRbC0sBj5stHk7SaCMeOIqi8O/lf1l2YhlGixG9Rs+gOoNoUb4FqiIYH0ZtNOGzdA2l5v6CJj4BgBRvd8Lb1OVmrYqglj6fhRDiYWZOTcacxROWuXWjbmV0nbqiT0rFsGgxbodPEPTnHoL+3ENylUrc6tuN2M5tsTrf+2keQ5oePyWZamp/jqqNmK3mTMu46l3pX7s/HYI6sPbMWnZd2cXB6wc5dP0QLSu0pEe1Hvg4++R7X4QQQjiWoigYI8+QdGrXf0/XqHEObkBSQAM+2WXl9K3074Yq3ha6Bxvx9XZDURSsVus9xwTQqOUpGyGEEA8enQZaljNTvxSERdRjSlQ1HnU6RGPDRZzjL+MUH0GqRyAp/jUBabwR+SeNNuKBcivpFj8f/ZmTUScBCPYO5qkGT1HKtVSO62rV2vTxaHIz1kBW6yenUnXlNur8tBGXmzEApHq6Ed66DjfqBkljjRBCiAKj0ukxtwwhXJOI+nxNyuw6jt+Rc7icu0TFT76h3Iz5RNWrwo1GNUgq65fl0zcqrTNWn4ro6wWjMWgwk7nRJoOviy9PNXiKzsGdWXVqFYdvHGZ7xHZ2R+6mefnm9KjaozB3VwghRCEw344i8UQY5rgbAGjcfXGp047N17xYvsGM0QJOWuhbV0UlFxNWq4MDFkIIIYoJVx10qZzG7XJatl9pwbaYmnR1OkxtfSTO8eE4xV8mLSEIc/XGaN2k2zSRd9JoIx4IRrOR1adXs/bMWsxWMzq1jsdrPE5oUChqVc6NJVq1lsoqH/yikqmZ7Jr7sQYAbXQspZaux2/FH2gT0gfmtJTyJzG0NSeC3EhTSXYjhBCicJhTk0n1dCK+SyPOt61DwJELlN1/Bue4RErvOUHpPSdILOXN9frB3KxTCbPz/9+YYNZaUFyz79omK2XdyzK2yVjOx55n1clVnIk5Q9jlMLZf3s628G28/8j7NCnXpKB3UwghRAGyGpNJPruP1IhTgAIaLS5VGnHDvTaf7bBwKTa9Eb9mKTWjm+tw1piJvOXYmIUQQojiyNOg8Giwidhyrmy/0o4/YuLo7HyEuvorWG9eIPbmBQylg3EJboDOu4yjwxUliDTaiBJNURTWnlnLi3+8yMW49P6Xa/rVZFCdQQS4BeS6HI1KgyEpFeuhIxijzmO2puW4jlNUHGXDjlDq0BnUZgsAKb6e3OzcGufR47AeP4py/SRyS5oQQoiiYHY2ENmsJpFNa+B16TqlD5/H73QEbjdjqbJpH5X/PkBUtfLcql2JmMpl7+sqMNg7mFdavsK5mHP8ce4Pjt48yu/nfuf3c7/TvlJ7Xm/1Op2DOxdJt6RCCCFyx5pmJOnMHpLPHwBLesOMvkww1orN+Pm0gW07zSiAqx4Gh+hoG6xBrVKRkOzYuIUQQojizttJoUcVE9Eprmy/0pY/Ym/TxfkI9fQRmK6fx3T9PBrvMnilGfFo2AmVWuPokEUxJ402osTafWU3r216jX8v/wuAl8GLvrX70rhM43z/SKQYUzEnJ2bfaGO14ns2kjIHz+Jz4Zptcnw5PyKa1yK6ajmc/MtQySCDbgohhHAQlYq4oDLEBZVBm2Kk1LFLlD58HrebsZQ6eZlSJy+T5qQnrkYlVK0UaFgj35uq4lOF55s+z62kWxy4foA1p9ew5dIWtlzaQi3/WoxpNIbh9Yfj6eRZgDsohBAiL6xpRuIP/Enc9hVYU+IB0HqWQle1GX/f9GfVn2ZS/7sJrWUlDUMb6vB0lkZ3IYQQIq98nRV6VjWRmObKibhQ/r4cTRvdMRrowyH2GtEb5xKzfTlejbvhEdIRjYuHo0MWxZQ02ogSZ0/kHj769yPWnF4DgJPWiZENRlKnVB00hdRSbbidROlD5yh9+DyGxBTb9Ogq5YhoUYv48v5ZjhcghBBCOJLZ2cDVJtW52rgabtdjKHX8Ev4nwjEkpuB/6AwcOoPnr8sxdGrEhda1udqoGla9Ls/bKe9RnqH1hjK9y3Sm75zO3ANzOXHrBC/88QKT/ppE/9r9ebL+k7St2DZX3ZYKIYS4f1ZjMvEHN3N712osSXEAqF08MFRpQlhCRdb8YyYuNf2Jm8o+KoY11lHNX+78FUIIIe6Xp5NC37pqNCFl2XK+FDNPxVNbOU1Lw1ncE2OI3fozMf/8hlutVng06IBTYE1UkieJO0ijjSgRFEVh66WtfLL9E/48/ycAKlQ81eApPmj/ARarha2XtmK0GAtsm2qTGd9zVyh17BI+56+iUhQATC4GrtcP5nqDKqR6uxfY9oQQQohCo1KRWMaXxDK+XAgNwTPiFmVOXsHvVDi6mDhq/PYXNX77izRnA1ea1+Ry63pcblWHFL+8PSET6BnI9K7Tee+R91h0ZBHf7PuG47eO88OhH/jh0A9U9KzIkLpD6Fe7H/UD6kv3aUIIUQjMt29xe+8G4g9tRjGm922m9SyFU72ObL3izPo9ZmKS0xtr/F1V9KmnpVVQeldoQgghhCg4LnoV3Wvq6FLdhz0RLfnlYktcbx2jrdMpArXRJB3bRtKxbShufng3aI9brVbo/Ss4OmxRDEijjSjWkkxJLDqyiC/3fsmxm8eA9PFnhtYbyhut36C6X3UAwuPCC2aDaWa8T1/G9/h5fM9eQZNmsc2KqxjAtZAqRFWvgKKRO9CEEEKUUGo1tysGYAquhHnYEFKVNMxh2yj3zyFco24TtOUQQVsOAXCrRiDXGlblWsNqXA+pitHTNVeb8HTyZFzTcYxtMpYdETv48fCP/Hb8N8Jvh/Nx2Md8HPYxlb0r06dmH3pU60GL8i3QafL+hI8QQoh0itVC8rkDJBzaTPK5A6Ckj6up8y2Hqk5XNseU5/c/LpNsTO8G2tsZnqiro11lDVqNNNYIIYQQhUmrVtGqso4O7WtzNbU5f+68xO8HD1BPOUmIIRynxCjiwpYSF7YUq2cZvOu2xq16U/QBQXKj20NKGm1EsWNVrGy9tJWFRxay/MRyEkwJALjoXBhebzivtXqNyt6VC2x7+oRkKu49TNltp/H8eztlU1Jt81K83LhVqyI36lYmxVf6mRRCCPGA0WpJaFKfQ+0rYzSn4ns6gor/HCYw7CilToTjf+oy/qcuU++Xv1BUKmKqlONaw6rcqBdMVI1AblfwB3X2j/GrVCpaBbaiVWArZnadyZrTa1hyYgkbzm7gQuwFpu2YxrQd0/A0eNI5uDOPVHqE1oGtCXINKsJKEEKIkklRFEzXL5B4IozEY2FYEmNs8wyBdbga0Io1F1w5tDIKuAhAGQ813WtqaBWkQS+NNUIIIUShUKlUWK0KCckm2zS1VsGSasbFoKVXuyqYW1fm2PloVh67jPXiARpoz1Nddw3t7WvcDlvK7bClmA0eOFVuiE+NRjhXqiNj4DxESlSjTVhYGNOnT+fcuXP4+voyZMgQRo4cec8Wx3Xr1vHNN98QERFBuXLlGD16NE888YTdMkePHmXq1KkcO3YMV1dXevfuzfPPP49eL4PJF5U0Sxrbwrex6tQqVp9ezZX4K7Z5VXyqMK7JOJ5q8BReTl73vzGrFb/TEVTYcZwKO45R6thF1BarbbbR3YVbNQO5WasSiWV8ZKwaIYQQDzS1WoNBYwAgsXZVjteuyvHn+uJ8K47S+04SsP80AQdO43XxGr5nr+B79gp1ftsCQJqLEzHVA4mrWRn31jHQrB1UqwZubpm246xzZkCdAQyoM4BEUyIbzm5gzek1/HHuD6JToll6YilLTywFwEPvQR2vOnSK68QjwY/QpGwTXPW5e8pHiIed5EwPNsViJjXyNMnnDpB0ahfm2Ou2eWpnd5LKNWV7SjB/nTKTfCgFSB+Ps0E1f7o28KGO4Soqq9lB0QshhBAPB7VKRZrFSmysEYs1/TdHrV6Pu2cy11KtpJnTp2k0KprXr0ha7fKEX0tgV8QNXG8dp7bmItV01zEY4zGf3MrNk1sBSHEpja5cDfyr1ETtVwGs1uxCECVciWm0OXToEGPGjKFbt25MmDCB/fv3M23aNCwWC6NHj85ynY0bN/Lqq68yfPhw2rRpw+bNm5k0aRJ6vZ7u3bsDEBERwYgRI2jQoAEzZszg/PnzTJ8+nbi4OD744IOi3MWHiqIonIw6yW8Xf+PUqVP8E/EPt423bfM9DZ4MqD2AYfWH0apCq/t6FFCXlIr/iUsEHLlAqWMXCDhyAafbSXbLxAWVxdyiGfj7c8bNiFmRREYIIcSDT6XT4aP3oGayBYviZD/T3RPaVySpfVcuANqYONwOHsft4HFcT53H+ewldMmpBBw8Q8DBM/DLH7ZVraUDsARVwhpUKf3fwApYy5TGWraMrUGns7YGnWvXwFLzFQ7EHGfL9R3sunWQvdFHiDfFs+PmDnbc3MH7Ye8DUNm7MrX9a1OnVB3bq7pvdQxaQ1FVlxDFnuRMDx5FsaJOuEnSoSskXDtLyqUjWFPvyGU0euJ9anAorTJ/XPEgKRIgvecAX08nOjQJpFPTQEr7upIWd5PU8GsoDtkTIYQQ4uFjsVqxWNK/eVUWBYtVIc38/402/09FxTIeVCzjgUZdDRcnHQcio4g6eRjP26eporlGWW0czsnX4ex1Ys9uBcAdLWe2l0FbqjKeFavhGxiEwa8sGmcZg7ukKzGNNrNnz6ZmzZpMmzYNgLZt22I2m5kzZw7Dhw/Hyckp0zpffPEFXbt25c033wSgTZs23L59m5kzZ9oSkLlz5+Lq6srXX3+NXq+nXbt2ODk5MXnyZMaMGUPZsmWLbicfUFbFyqW4Sxy9cZQD1w6wO3I3eyL3EJsaa7dcKddSPFbtMXpV70Wn4E44aTO/p/ekKLhej8H7wlW8L1zD++I1/E+E430+ErXVPjUxuRiIbFqTiJa1udKiNmnly9I4zR/v3UfgxmkkkxFCCPEwUGm0aJNSsewOIzX5do7LJwKEBKa/LFZcouJwvRqF5/U4vKIS0d64iTruNurrN1BfvwE7d2cqw+ykx+TljsnTDaOXOyYvdyp7ulHe3ZVhntXwCejCCe8UwkqZ2GU8w4HrB7ieeJ0LsRe4EHuBtWfW2spSq9SUdi1NeY/ymV6l3UpT2bsygZ6B0g+0eGhIzlSyKVYLabE3MN0Kx3TtAsZr50m9eg5PYxIJdyxn1rpwRR/E3vgA9sQEYLr1/2OC+XgYaFmvLG0alKNGRR/U6v///DOZLSSmmLCa0/IUl9kiyZEQQghREFRqFTpt9t1LA+i0aqoHetGqfll4tB7GNAvnIuI4eu4yt88dQRV1iVLWG1TQxuCkSsMjKQIuRpB2cRsZz9+mqpxI0ftgcfFF41kKZx9/PHx98fT1Q+/hg1pn/6S02uCCxjlzbwnCcUpEo43JZGL37t288MILdtO7dOnCvHnz2L9/P61atbKbd+XKFS5dupTlOr///juXLl2iUqVKhIWF0a5dO7vH+rt27cr7779PWFgY/fv3L7wde0AoikJcahzht8MJjwvnUtyl9P+/nf7/p6NOk5SWlGk9J60T9bzq8WjNR+lWvRuNyjRCo9bca0Nw6xZERMCVK+n//vcqfeo4g0+dRpdizHLVhDK+3KwTxI16lblRtzLR1Stg1f3/4S/36AohhHiYmVOTMScn5nm9eHc98dXLElc7GGuFOqhq1ebK77+hvnwZl5h4nKPjcYmOx3A7Caf4ZHQpRrSpJrTXo3G5Hp1tuf4aNS29PUn08yTFtxTxXhW56QbX9CauaJMIVydwTonmmt5ErNNVTjhfZY9+D2TRNuOsdaa0W2nbK8A1AG9nb7ydvLP918PgIQ09osSRnKn4UxQrlsTbmONvYY6Pwnw7Kv3/b0dhjruBKfoqWDI3qKSh5bISwMkUf86ayxBu9kUh/QcfnVZN7UBvGtUoRaMaAQSVzf7zK82scCM2BVNqapbzs6LTavB0ky7whBBCiPul1mjwcNKiJhWLNfsbIrQaNZrUGOKux9mmlXOBcvUCoF4nFEUhKj6NiGtxRJw8gjopBqfUKDwtMfip4/FSp+CkpOJkvArGqxALXAITcOu/8lIVPUkqF0waF6xaZ9SuXmjdfdC7eqB380Dv7oGzuyfOHl64eXuhd3FDda/fbEWBKxGNNhEREaSlpVGpUiW76RUrVgTg4sWLmRKQ8+fPA9xzndKlSxMZGUlQkP1gtz4+Pri5uXHx4sUC3Iuicz3xOommRCxWC1bFikX57997/G22mkk1p5KSlkKKOSXb/483xhOTEoPq6lVSEmK5nRxLYsptFKsVjQJqBTTW//5VQK9AAys4qXUEeQRSxasytbyqUsulEqXxJOrSZcqkuKLf8zekrIfkZEhJgfh4iIlJf0VHp/8bGwsWS5b7nNHoYtWoiasYQFxQGWIrlyG6anlu1Asmxc+z6N4AIYQQ4iFmcXEiqbw/CeX9M81Tm8wY4tMbcAy3k/77/yQMt5PRJ6WgTzKiTTWitlgxRMViiPr/p3Jr5bBds0ZFgouWBAMk6BTidRYStAqJ+hQS9Rf/e0GSHowauKaBcA2kacB018usVaExuKBxckKrd8agd8ZJ54xB74KzzhknvQtO//2r0+jRavXoNHo0Wh26//5fq9Wj0/7/PKWUP1pXd3RqHWqVOtuXSqXKfh4q2zIAqv9aqTL+LuteFq26RFzei0IgOVPeWM0mLAkxoFhRFCX9BjGrFUWxgmIFRUFRFFJSTCSnmlCsFhSrgtWchmI2YU0zgSUNq9mEYjbBf9MVSxqkGbEak8CYBKYkVKZk1GlJaNJSUOXwSL9J0XDD4kmE2YcIix+Xzb5cs3hhIf2HktK+LrQo50mV8l7UCvKlagUv9Lrc/4hivaObltzQqOUpGyGEEKIgqDUaVJZUkiPOYUrN+qZzAJ1Og9bdQFyCEWs2Y9boXVypVb4i2usKOj9/NNrSqNVqVHonzieaSYmPx5wUjyo1Hn3abZwsybiShKc6BYPKjJPKhBMmsMSBBTACMfbbMP33yuiPwaRoSFPpMKv0WNQ6LGo9FrUBRaNH0RpQtHpUGj1qrRa1Vodaq0Ol0aLS/Pfvf3+rtVrUGj0qbfr/azQa1Go1Go0Glfq/XCfjX5UalUoNalX6PDLmpc+3LQ9otWo83QzY7uS74x4WlW2aCpXeGY1T8R8vtURkdQkJ6Q+Du901qK2ra3oFJyZmvjM0Y9q91smu3Izlsio3J2lpaSiKwpEjR/K8bkFINCVyK/lWzgtmQ//ff57c0cihJr1VxAC4gk8KeLncX5zJwAUA/wDi87KiSgUaTfpLqwWNBkWrxapRY1RbsWjV3HlWuv33yqm7M5VFhVGl4WbD1ugtzdHfR/9oKrWGqzonCGmJ3tI032XdTzmKAq6Kkv4Bpiq4mADMai0X0GFt9QQuStaNaLlRkDEV5f7dXbfFISZHlFXQ+3dRpce16zAURblnveamrILYv2JZ56i4rtWBToemTV9clNwNOJjVMfsg7Z8jY8rt50FuyirIuIq6nPyUZfzvlVU5GpUGi9UMGi0WxYLKak1/WayorEr6S8n4//R/UTJ/BtmuARxFAdL+ewGWZIjwSCKpEB/gOaE5QVn37LupUv6rp7Nnzxb4k0RpaWnydJKDlaScCRydNynpDTbW+/kOVIFaD3o95OFBFAVQUGNRVFhRY0WFBRVWRY0FNVbUqNUqKqhVVFSpUKtBhYJep0WrVaO2nWepWBIjOXUyMvfbtlpQ/Muhy+Iz815uq1VoXNKf7bGq1FyPT85VOXeul5XsysppvaykqdVcirqNxbcMOp/c7Z8OcFIUojVqYq3/1atRhepaLIrFLcvvljspBtCU9Sv0/bOq1Fy9nYhi8EFT1itP9XL39nL7/qmAW2o1Uff6Or9HXVldPPGpVSpX3wsZMVm9S3NbRZ7fe/j/fczL8Xnnendv717l5Kpu7nRHPSkG13seMznFaVWpuZmYgkdwDXKTNOVn/+61Xlbu9/2z1Wcezr0M2Z2DuTkOstpHHeBktaJS///UO8tCUfL1+QQQrdGgup2Up8/gbI+1XNRVTp9PkHU9Fcb+ZVWvGbLaXk7vX67PwSzqKTf1kpX8vH+Qef8y9s3i5Y/qHuVYgFi1CqtOyfaXFqNKzfWEZFwqVbN9HqgA1Cp8fBQgc06gAIkKJPx3YwoZL9Jz2vS/rf/dYKKgRkH13+tumv9e+WH97wVWsJoy/igQEblaSoXa1ROVNvsLuMLKm/KSM5WIRpvsWhUzqLM48XOzTk7L5OdNsd356KCk1d3gjruhkAeb8i7c4vNKRfoHxX22I6UzOOf7Q6fQyiqOMQF6QwF1Kif7l2sFFlNBllWA+2cohvtXLOsc0BicC6Qc2b/cK6iYimtZxS2mB/HBew1QycExqFQqu+6tCrpsabRxrJKUM925nmOOGxVaDz8HbNexVBoteueC+QlAo9PlvJADytJrC6YslSZ39ZSb76sC278C2jco2DrPqq7U5P3HpuJ4TBVGPRXENU5x3L+CKiu3555tu/eaVwz3r7DPPbtt5bKc4lhPBVnW3fV0P+dgcTwOCrIs8f8KK2/KS85UIhpt3N3TGyGSkuzHRcnuzrDcrpOx3t3LZCyXUUZehISE5HkdIYQQQgghhLgfJSlnAsmbhBBCCCGEyE5enwhziMDAQDQaDeHh4XbTL1++DEBwcHCmdTL6XL57nYy/g4ODcXV1JSAgINMy0dHRJCUlZVmuEEIIIYQQQhQ3kjMJIYQQQgjxYCgRjTYGg4HGjRuzadMmW59yABs3bsTd3Z169eplWqdixYqUL1+ejRs32k3/888/qVSpEuXLlwegVatWbN26FZPJZFeuRqOhefPmhbRHQgghhBBCCFFwJGcSQgghhBDiwVAiukcDeO655xgxYgQTJkygT58+HDx4kPnz5/PKK6/g7OxMYmIi586dIzAwEB8fHwDGjRvHG2+8gZeXF6Ghofz111/8/vvvTJ8+3VbuqFGjWL9+PaNGjWLEiBFcunSJL774gv79+1O2bPYDuQohhBBCCCFEcSI5kxBCCCGEECWfSrnzNqxibtOmTcyaNYuLFy8SEBDAkCFDGDlyJAC7d+9m+PDhTJkyhd69e9vWWbx4MQsWLODatWtUqFCB0aNH8/jjj9uVu2/fPqZOncrJkyfx9vamV69evPDCC+hkMCchhBBCCCFECSI5kxBCCCGEECVbiWq0EUIIIYQQQgghhBBCCCGEeFCViDFthBBCCCGEEEIIIYQQQgghHnTSaCOEEEIIIYQQQgghhBBCCFEMSKONEEIIIYQQQgghhBBCCCFEMSCNNkIIIYQQQgghhBBCCCGEEMWANNoIIYQQQgghhBBCCCGEEEIUA9JoI4QQQgghhBBCCCGEEEIIUQxIo40QQgghhBBCCCGEEEIIIUQxII02wiHCwsLo06cP9evXJzQ0lPnz56MoiqPDKvGMRiO1a9emevXqdq+QkBBHh1ZiXb9+ncaNG7N792676eHh4YwZM4bGjRvTrFkz3n33XRITEx0UZcmUXd0OGjQo0zFcvXp1jh496qBIiz+r1cqvv/7KY489RkhICB06dODjjz+2OyblmM2f3NStHLP5Y7VamT9/Pp07d6ZevXr07NmTNWvW2C1z9OhRhg0bRkhICK1bt+aLL77AZDI5KOKSIzd127Zt2yyP25iYGAdFLYS4m+RMhUNypsIheVPhkJypYEneVHgkbyo8kjcVnuKcN2kLtXQhsnDo0CHGjBlDt27dmDBhAvv372fatGlYLBZGjx7t6PBKtDNnzmA2m5k2bRqBgYG26Wq1tM/mx7Vr13j66adJSEiwmx4fH8+TTz6Jn58fn3zyCTExMUybNo0rV64wf/58B0VbsmRXt4qicPr0aUaMGEHXrl3t5gUHBxdliCXKvHnzmDFjBk8//TQtWrTg4sWLzJo1i7Nnz7JgwQISEhLkmM2nnOoWkGM2n2bOnMn8+fN54YUXqFu3Ltu2beO1115DrVbTo0cPIiIiGDFiBA0aNGDGjBmcP3+e6dOnExcXxwcffODo8Iu1nOo2JiaGGzduMHHiRBo1amS3roeHh4OiFkLcSXKmwiM5U8GTvKlwSM5U8CRvKjySNxUeyZsKT7HOmxQhitjIkSOVvn372k2bOnWqEhISoqSkpDgoqgfDkiVLlFq1ailGo9HRoZRoFotFWb58udK0aVOladOmSrVq1ZRdu3bZ5s+ZM0epX7++Eh0dbZu2detWpVq1asq+ffscEXKJkVPdXrp0SalWrZqyY8cOB0ZZslgsFqVx48bKe++9Zzd9/fr1SrVq1ZQjR47IMZtPualbOWbzJzk5WWnQoIHyySef2E0fOnSo0r9/f0VRFOV///uf0rZtW7vvtJ9//lmpUaOGEhkZWaTxliS5qdvt27cr1apVU8LDwx0RohAiFyRnKjySMxUcyZsKh+RMhUPypsIjeVPhkbyp8BT3vEluJRFFymQysXv3bjp16mQ3vUuXLiQlJbF//34HRfZgOHnyJJUrV0av1zs6lBLt9OnTvPvuuzz++ONMnTo10/ywsDAaNWqEj4+PbVrr1q1xdXXln3/+KcpQS5yc6vbkyZMA1KhRo6hDK7ESExPp1asXPXr0sJteuXJlACIiIuSYzafc1K0cs/mj1+v59ddfGTlypN10nU6H0WgE0j9r27VrZ/ed1rVrV6xWK2FhYUUab0mSm7o9efIkrq6uVKhQwREhCiFyIDlT4ZKcqeBI3lQ4JGcqHJI3FR7JmwqP5E2Fp7jnTdJoI4pUREQEaWlpVKpUyW56xYoVAbh48aIDonpwnDx5Eo1Gw8iRI2nQoAFNmzblnXfekf5X86hMmTJs2rSJN954Aycnp0zzz58/T1BQkN00jUZD+fLl5RjOQU51e/LkSVxcXJg6dSrNmjWjbt26PPPMM1y4cMEB0ZYMHh4evP3225ke1d28eTMAVapUkWM2n3JTt3LM5o9Go6FGjRr4+/ujKApRUVF899137Nixg8GDB5OamkpkZGSm49bHxwc3Nzc5bu8hp7qF9M9aLy8vXnjhBRo1akRISAgvvvgiN2/edHD0QgiQnKmwSc5UcCRvKhySMxUOyZsKj+RNhUfypsJT3PMmabQRRSqjL1Y3Nze76a6urgByoXwflP/6tQ0PD6dDhw7MnTuXMWPGsG7dOkaPHo3VanV0iCWGl5cXpUuXznZ+QkKC7Zi9k6urqxzDOcipbk+dOkVycjIeHh589dVXfPjhh4SHhzNkyBBu3LhRhJGWbIcPH+a7776jffv2VKtWTY7ZAnR33coxe//Wr19Pq1at+Pzzz2nXrh09e/bM9noB5LjNi6zqFtI/a2/cuEHt2rX59ttvmTRpEnv37mXYsGEkJyc7OGohhORMhUdypoIleVPhkJyp6EjeVHgkbyp4kjcVnuKYN2kLtXQh7pLTRbAM/ph/iqLwzTff4OPjQ9WqVQFo0qQJfn5+vPbaa/z777+0a9fOwVE+GBRFyXaeSqUqwkgePC+99BKjRo2iSZMmADRu3JiGDRvSrVs3fvrpJ1577TUHR1j87d+/nzFjxlC+fHmmTJkCyDFbULKqWzlm71+9evVYtGgRp0+fZubMmYwaNYrPP//8nuvIcZs7WdXtwoULmTx5MhqNhnr16gHpx22VKlUYPHgwq1atst1ZJoRwDMmZCo/kTEVLrkELh1x/FgzJmwqP5E2FQ/KmwlMc8yZptBFFyt3dHYCkpCS76Rktv1m1DIvcUavVNGvWLNP0Rx55BEjvF1cSkILh5uaW6RiG9OM4ICDAARE9OLLq37ZChQoEBwdz6tQpB0RUsmzYsIFJkyZRqVIl5s2bh7e3NyDHbEHIrm7lmL1/gYGBBAYG0qRJE9zc3Hj99de5fPkykPl6AdKP24zrCXFvWdXtvn37bMnynRo1aoS7u7sct0IUA5IzFR7JmYqWXIMWDrn+vH+SNxUeyZsKj+RNhac45k1yi44oUoGBgWg0GsLDw+2mZ3zIBAcHOyKsB8KNGzdYsmQJV69etZuempoKYPuiFPcvKCjIdsxmsFgsXLlyRY7h+2A2m1m5ciUHDx7MNC81NdVuMEiR2fz583n55Zdp0KABP//8M6VKlbLNk2P2/mRXt3LM5l9MTAyrVq0iOjrabnqtWrUAuHnzJgEBAZmuF6Kjo0lKSpLj9h5yqtsrV66wbNkyzpw5YzffarWSlpYmx60QxYDkTIVHcqaiJdegBU+uP++f5E2FR/Kmgid5U+Ep7nmTNNqIImUwGGjcuDGbNm2ye+x048aNuLu72x43E3lnsVj43//+x2+//WY3fcOGDWg0Gho3buygyB48rVq1Yu/evcTExNimhYWFkZycTKtWrRwYWcmm1Wr58ssvmTp1qt3048ePc/ny5SzvihTpFi9ezNSpU+nWrRvz5s3LdDeNHLP5d6+6lWM2/1JTU3n99ddZtmyZ3fTt27cDUL16dVq1asXWrVsxmUy2+Rs3bkSj0dC8efMijbckyalu69aty+TJk/n222/t5v/999+kpqbKcStEMSA5U+GRnKloyTVowZPrz/sjeVPhkbypcEjeVHiKe94k3aOJIvfcc88xYsQIJkyYQJ8+fTh48CDz58/nlVdewdnZ2dHhlVhly5ald+/ezJ8/H4PBQEhICPv372fOnDkMGTKEoKAgR4f4wBg8eDCLFi1ixIgRPP/888TFxTFt2jTatm1Lw4YNHR1eiTZ+/Hhef/11Jk6cSK9evbh69SozZ86kZs2aPPHEE44Or1i6desWU6ZMoVy5cgwZMoQTJ07YzQ8MDJRjNp9yU7dyzOZP2bJl6dOnD1999RVarZZatWqxb98+vvvuO/r27UuVKlUYNWoU69evZ9SoUYwYMYJLly7xxRdf0L9/f8qWLevoXSi2clO3zzzzDLNnz8bPz4927dpx5swZZs+eTYcOHWjRooWjd0EIgeRMhUVypqIl16CFQ64/80fypsIjeVPhkbyp8BT3vEml3GuULSEKyaZNm5g1axYXL14kICCAIUOGMHLkSEeHVeKZTCbmzZvH6tWruXr1KqVLl6Zfv36MGjVKBizNp927dzN8+HB++uknu1b0M2fO8PHHH3Pw4EFcXV3p2LEjEydOlD7G8yC7ut2wYQPz5s3jwoULODs706lTJ15++WW8vLwcF2wxtmzZMt56661s50+ZMoXevXvLMZsPua1bOWbzx2QyMX/+fFatWkVkZCRlypShf//+PP3007bvrH379jF16lROnjyJt7c3vXr14oUXXkCn0zk4+uItp7q1Wq0sXryYX375hcuXL+Pl5cVjjz3G+PHjcXJycnT4Qoj/SM5UOCRnKhySNxUOyZkKjuRNhUfypsIleVPhKc55kzTaCCGEEEIIIYQQQgghhBBCFANyG4kQQgghhBBCCCGEEEIIIUQxII02QgghhBBCCCGEEEIIIYQQxYA02gghhBBCCCGEEEIIIYQQQhQD0mgjhBBCCCGEEEIIIYQQQghRDEijjRBCCCGEEEIIIYQQQgghRDEgjTZCCCGEEEIIIYQQQgghhBDFgDTaCCGEEEIIIYQQQgghhBBCFAPSaCOEEEIIIYQQQgghhBBCCFEMSKONEEIIIYQQQgghhBBCCCFEMSCNNkIIIYQQQgghhBBCCCGEEMWANNoIIYQQQgghhBBCCCGEEEIUA9JoI4QQQgghhBBCCCGEEEIIUQxIo40QQgghhBBCCCGEEEIIIUQxII02QgghhBBCCCGEEEIIIYQQxYA02gghhBBCCCGEEEIIIYQQQhQD0mgjhBBCCCGEEEIIIYQQQghRDEijjRBCCCGEEEIIIYQQQgghRDEgjTZCCCGEEEIIIYQQQgghhBDFgDTaCCGEEEIIIYQQQgghhBBCFAPSaCOEEEIIIYQQQgghhBBCCFEMSKONEEIIIYQQQgghhBBCCCFEMSCNNkIIIYQQQgghhBBCCCGEEMWANNoIIYQQQgghhBBCCCGEEEIUA9JoI8QDZNiwYYSGhjo6jBJp0qRJVK9e3dFhFDir1cqVK1eynT979myqV6+e42vYsGFFGHXumEwmbty4cc9ldu/enWlfatWqRdOmTRkyZAirV6/OtM6KFSuoXr06u3fvznNMERERuVquevXqTJo0Kdu/C8LdsTji86Ggzqthw4bl6jidPXv2fW8r45y413mTlfs5bu7XpUuXmDRpEm3btqVOnTq0bNmSMWPGsH379vsqN7fHsxBCCPEgktwq/yS3KvzcKiPPWbFiRZ7Wu3LlSoFdN+fH5s2b6dmzJyEhIfTp04d9+/bluE5GzLl55fUaPie5vR6+efMmH3zwAR06dKBu3bo0a9aMp556ig0bNhT69jPOtztfderUoV27drz22mucPXs20zr5/XzLTQ4OmXOjwsqV7qwfRx/bQhQ0raMDEEIUnDFjxpCSkuLoMEQxkZiYyFNPPUW7du0YP358lst06tSJwMBA298XLlxgzpw5dOrUiU6dOtmm+/n5FXq8eREZGcnIkSN59tln6d27d47L37k/ZrOZ6OhoNm/ezMSJEzlw4ADvv/++bdkmTZowdepUgoOD8xTTO++8w8WLF1m4cGGOy06dOtWu3gva8uXLef/99zly5IhtmiM+HwYMGECLFi3uu5wxY8bQt29f29+bNm1i06ZNjBkzhsqVK9umF8SPAxnnhI+PT57Wy+9xc79OnjzJ4MGD8fHxoX///gQEBBAVFcWaNWsYOXIkb7/9dr5+GPj6669ZuXIlmzZtKoSohRBCiOJPcitxp+KWWwUHBzN16lQaNmyYp/V8fHyYOnWqQxrVdu3axfPPP09oaCiDBg3il19+4ZlnnmHdunWUK1cu2/UyYr7TlClTAHjjjTcyLVtQcpvfXbt2jX79+qEoCn369KFChQrExcXx559/8tJLL3HkyJF83aCXVU53L2+88Qbe3t4ApKSkcPnyZZYvX87GjRuZO3cuzZo1sy2bn8+3vOTgRZEbPf300/j7+/PJJ58Ajj22hSgM0mgjxAOkVatWjg5BFCNxcXEcPXqUdu3aZbtMjRo1qFGjhu3v3bt3M2fOHKpXr06vXr2KIsx8uXLlCpcuXcr18lntz6hRo3j99ddZvHgxzZo149FHHwWgQoUKVKhQIc8xhYWF3TPZuFNh1+3evXsxGo120xzx+RASEkJISMh9l3N37JcvX2bTpk20bNnSLvkoCHefE7mV3+Pmfk2bNg0PDw9Wr16Nm5ubbfrTTz/NgAED+Oyzz+jRo4ctgcutnTt3YrFYCjpcIYQQosSQ3ErcqbjlVn5+fvkq08XFxWF53tKlS3F1dWXWrFlotVpq1apF//792bp1K0OGDMl2vaxinjlzJlC4eVVu87uvv/6apKQkNmzYQJkyZWzTR40axZgxY/jhhx/o27cvVapUydP2s8rp7qVjx46UL1/ebtqwYcPo06cPL774Ips3b8bV1RXI3+dbXnLwosiNwsLCeOKJJ2x/O/LYFqIwSPdoQgghHkpqtZp3330XT09P5s6d6+hwhMiXgwcPUr9+fbsGGwC9Xs+gQYMwmUycPHnSQdEJIYQQQgiRLjU1ldTUVGJjY21/A+h0OkeGdd8OHjxIUFCQXYMNgEqlYvjw4SiKwsGDBx0SW5kyZXj99deJiYlh+fLlDolBCJE/0mgjhAOFhoZm2W3N3dNDQ0N55513WL16Nd27d6du3bp07tyZn3/+2W69rPol3blzJwMHDqRBgwZ07NiRZcuW8c4779gtl11/pllNP3fuHOPGjaNx48bUr1+fgQMH8u+//+Z53z/++GNq1KhBXFycbdqZM2eoXr06Y8aMsVv2o48+olGjRqSlpQHpj+W+9tprNG/enLp169KzZ0+WLFlit86kSZPo2rUrP//8M02aNKFJkyb8888/ABw7doyRI0cSEhJCmzZt+Pbbb1EUJc/7kCExMZGPP/6YRx55hPr16/PYY4+xdOlSu2ViY2N57733aNOmDXXq1KFLly589913dneyZzeWxt3TZ8+eTd26dbl06RLPPvssISEhNGnShNdff912Abx79246dOgAwJdfflkg/fv+/vvvDB06lEaNGlGnTh1CQ0OZOnUqJpPJtsywYcN4+umnmT59OiEhIbRo0YLTp08DcPjwYYYPH26r99mzZ9tiu9P169eZOHGi7f19/PHHWbNmjW3+ihUrGD58OJD+CPj9PP7s5uZG+/btOXHiBNHR0bby7+5vd+PGjfTp04eQkBAaNWrEiBEj2L9/v21+9erViYyMZM+ePba+pTP61P3hhx8YNGgQderU4amnnrItn9Uj8nPmzKFNmzbUr1+f4cOHZ3oUPrv17pw+bNgwVq5cmeX0u8/n06dPM3bsWBo3bky9evXo378/mzdvtlsm4z39559/6N27N3Xr1qVdu3bMnj0bq9V6z/q9uz/zjPPyyJEjDB06lPr169OyZUs+/PBDW9J2v+517u/cuZNRo0bRrFkzateuTZs2bXjnnXeIj4+3rZ+f8w2y77f51KlTvPLKKzRp0oSQkBDGjh2b6VxMTEzk/fffp3Xr1jRo0IAxY8awb9++XPVT7urqyu7du7l48WKmeX369OHYsWO0bNnSbvqKFSt4/PHHqVu3Ls2bN2fSpEncvHnTNj80NJQ9e/YQGRkp/UILIYQoMSS3ktyqJOVWGdeKGzduJDQ0lPr169uuucLDw3n99ddt4xU2bdqUMWPG2I1NcveYNhl/b9++nffff58WLVpQv359nnzySU6dOmVb7+5xPzL+XrVqFdOnT6dt27bUrVuXfv36sWvXLruYFUXhhx9+oHPnztSrV4/evXuza9cuOnXqlKvuv7p164bZbObNN9/k/PnzvPvuu/j4+NClS5f7qss7GY1Gpk+fTmhoKHXq1KFDhw7MnDnTLmeF/OV32XF1deXMmTMcOHAg07wWLVpw/Phx+vXrZzd9y5YtDBw4kPr169OkSRPGjx9vdz2fXU6XH127dkWv19t9ttz9eWQymfjoo4/o0KGDbTyc999/n9u3bwPZ5+AZ58+mTZto1aoVISEhLF26NNsxbG7evMm4ceNo0KABLVu2ZPLkySQmJtrmZ7fendMzjlmAlStXZpp+d+6ydOlSevXqZct9XnnlFbvzNy/ngBBFSbpHE6KE+Pfff/njjz8YOnQofn5+/Pbbb3zwwQeUL18+20e0M36gLF++PBMmTCA6OpoPPvgAf3//fMVw+vRpBg8ejJ+fH88++yw6nY5169YxevRoPv/8c1v3UrnRtm1bfvzxR/bs2UPnzp0BbF/MBw8eRFEUVCoVkP7Ya6tWrdDpdERERNC/f3+MRiNDhw7F39+fP//8k//9739cunSJiRMn2rZx7do1vvnmG55//nlu3rxJgwYNOHv2LMOGDcPDw4OxY8eSlpbGggULMl3E5ZbJZGLIkCGcPXuW/v37U6NGDbZt28bbb79NSkoKw4cP5/bt2wwcOJDIyEgGDhxIUFAQ27dv5/PPP+fEiRPMmDEjz9u1Wq0MHz6cxo0b8/rrr3P06FGWLVtGamoqM2fOJDg4mDfeeIMpU6bY+lC+n/59ly5dyttvv01oaCivvvoqaWlpbNq0ifnz5wPY1fuBAweIiIjgtdde48qVK1SpUoVjx44xfPhw/Pz8GDduHCkpKfz000+o1fb3Dty4ccPWH/CwYcPw9PTkr7/+4rXXXuPmzZuMGjWKJk2aMGbMGObMmcOAAQNo1KhRvvcLoGrVqgCcOnUqy8fE9+zZw0svvUTbtm3p168fKSkpLFq0iBEjRrB+/XoqVKjA1KlTmTJlCt7e3owZM8aub+mZM2cSGhrKY489hsFgyDaOjRs3otfrGT58ODqdjp9++onhw4ezdOlSW4y5MWbMGKxWK/v27bvn2DlHjhxh+PDhuLm5MWLECFxdXVm9ejXjxo3jnXfeseui4MyZM7z44osMGDCAAQMGsG7dOr788kt8fHzu2ZVBVmJiYnj66afp1q0bPXv25J9//mHhwoXo9Xq74+h+ZHXuh4WF8cwzz9CwYUNeeOEFVCoV27dv57fffuP27du2LhayktP5di/PPfccwcHBvPTSS0RERPDjjz9y8+ZNli1bBoDFYmHUqFEcPXqUQYMGUbFiRdavX8+4ceNyta99+vRhzpw59OjRgzZt2tC2bVuaN29O5cqV0Wg0mZb/8ssvmT17Nl26dKF///7cuHGDRYsWsWfPHpYtW4aPjw9vvvkmn3/+ObGxsffdMCqEEEIUR5JbSW51p6LOre701ltvMXToUNzc3GjQoAFRUVH0798fNzc3hg4dire3NydPnmTJkiUcP36cv//++55Pprz99tuUKlWKsWPHcvv2bebNm8czzzzDli1b0Gqz/wlw5syZODs7M3LkSNv7+Oyzz7J161ZbN7vTpk1j/vz5dOjQgSeffJIDBw7wzDPP3LPcO3Xv3p1169axZcsWwsLCKFOmDPPnz8fT0zNvlZYNi8XCs88+y4EDB+jfvz/BwcEcO3aMOXPmcPLkSb755htUKtV953d369u3L4cOHWLw4ME0a9aMRx55hBYtWlC9enXUanWmnHfFihW8+eabtGjRgtdee43bt2/z66+/0r9/f5YsWUJQUFCuc7rcMBgMBAYG2jXe3e2DDz5g3bp1DB8+nAoVKnD27Fl+/vlnwsPDWbBgwT1zcLPZzDvvvMOIESMwmUw0atSIQ4cOZbmdd955h5o1a/LKK69w5swZfv75Z86ePcuPP/5o+4zKScbYNRMnTqRx48a29zqrmwA//fRTFixYQIsWLZg4cSI3b95k0aJF7Nixg6VLl9p1J5ebc0CIoiSNNkKUENeuXWPVqlW2PnI7depEmzZtWLNmTbaJxbRp03Bzc2PJkiW2C6GGDRvy3HPP5XrsjTt9+OGH+Pj4sHLlSlxcXAAYOnQoTz75JB999BEdO3ZEr9fnqqymTZvi7OzMrl277BKLgIAAbty4Ybsz7OrVq1y4cIFnnnkGgC+++IK4uDiWLVtG7dq1ARgyZAhjx45lwYIFPPHEE7YfuFNTU5kyZYpdwvP2228DsHjxYtvjy126dOHxxx/Pc30ALFu2jFOnTvHZZ5/x2GOPAemDrw8dOpTvvvuOoUOHMnfuXC5dusRXX31Fx44dbTG///77/PLLLzzxxBP37Bs5K2azmUcffdR2x83AgQO5ceMGmzdvJiUlBT8/Pzp27MiUKVMKpA/lBQsWEBISwtdff227mBo8eDAdOnTg33//tUvokpOTmTZtGvXr17dNmzZtGgaDgaVLl9oSnA4dOtCnTx+77UyfPh2TycTatWspVaoUkF5Xr776KjNnzuSJJ56gQoUKtGzZkjlz5tCgQYP73reMc+POOxPvtGHDBpycnGwX+QAtW7bkhRde4Pjx41SoUIFevXoxc+ZMu76lM+7eKVOmDJ999lmOF6FGo5HFixfbfiDv0qULjz76KLNmzcrTkw6tWrVi7dq17Nu375518+GHH6JSqVi2bBmlS5cGYNCgQQwaNIipU6fSrVs323t18+ZNvvnmG9vdWI8//jht2rRh7dq1eW60uX37Nm+//bbtjtf+/fvz6KOPsnbt2gJrtMnq3P/hhx8oU6YM33//ve1zavDgwQwYMCDHO1pzOt+cnZ2zXbdOnTp2719ycjKLFy/m0qVLVKpUibVr13Lw4EE+/PBD2x14AwcOZPDgwdkek3caP348SUlJ/Pzzz2zZsoUtW7YAUL58efr27cvTTz9t29+IiAi++uorRo8ezSuvvGIro3v37vTu3Zs5c+bw5ptv0rFjR3788UeMRqP0Cy2EEOKBJLmV5FZ3Kurc6k7du3fnxRdftP393Xffcfv2bX755Re7QdxdXV357rvvOHPmjO29yoqvry+//PKL7eYdvV7P559/zu7du+85jomiKCxbtsx2LJYrV46XXnqJTZs20b9/f9vNR4899hifffYZkF7vH3/8MT/++GOu9vXgwYNERkYC6Q1lb731FrVq1crVurmxevVqdu7cybx582jTpo1ter169XjnnXf466+/6NixY77zu+z069ePqKgovvrqK3bt2mV7OsPf35+ePXvy3HPP4e7uDqQ/SfbRRx/x6KOP8sUXX9jK6N+/P927d+ezzz7jq6++ynVOl1seHh5cvnw52/lr166lT58+vPzyy7ZpLi4u/PvvvyQlJd0zB7darYwYMYLRo0fbpmXXaFO9enV++uknW0NfQEAAs2fPZsuWLVk+oZiVjLFrJk6caHuvgExPv507d47vv/+eTp06MXv2bNt73bFjRwYMGMC0adPsbsDL6RwQoqhJ92hClBBBQUF2gxr6+/vj5+dHVFRUlsvfunWL48eP89hjj9nduRIaGpqnu/YzxMbGsmfPHtq1a0dqaioxMTHExMQQHx9Pp06diIqK4ujRo7kuT6/X06xZM9sFjaIo7N27l2HDhqFWq9m3bx+QfhecSqWibdu2WCwWtm7dSuvWre0uVNVqNWPGjEFRFP7++2+77TRu3Nj2/1arlX///Zd27drZ9TcbHBxM69at81wnAFu3bsXHx4cePXrYpqlUKqZOncrPP/+MSqXi77//Jjg42JZUZBg7diwAf/31V7623a1bN7u/a9asidlsztUPvXm1Zs0avvvuO7uGh+joaDw8PEhOTrZb1snJibp169r+vn37Nnv27KFnz552d6TVqlXLLnGwWq1s3ryZxo0bo9VqbcdYbGwsnTt3xmQysX379gLft4yuIbJrVCldujRJSUl8+OGHnD9/HsDWlUHXrl1zLL9x48a5umuoTZs2dk80VKxYkbZt2xIWFlbgA8JHRUVx+PBhevXqZWuwgfS7sJ5++mlSU1PZsWOHbbqzszOPPPKI3XJBQUHZfv7k5O5jt0aNGvkuKzt3nvsA3377LcuXL7f78SM2NhY3N7dMx3BW8nu+ZbUeYNvfzZs34+npSe/evW3L6HQ6RowYkWNMAFqtlrfffpvNmzczceJEWrRogV6v58qVK8yYMYNBgwbZ9m/Tpk1YrVZCQ0Nt51dMTAx+fn7UrFmTrVu35mqbQgghREknuZXkVncrytzqTk2aNLH7e/To0Wzfvt2uwSY1NdX2tEZO162dO3e2e9o649rz1q1b91yvXbt2th+rAdv5kbHeli1bMJvNma5R7/yh/l7++usvhg8fjtFo5MMPP0Sn0/Huu+8SHR1t64Uhq+5+8+LPP//Ex8eH2rVr213rtmvXDo1GY7vWvd/8LivPPfcc27Zt45133uGRRx7BxcWFW7duMX/+fB5//HFbPW7fvp3ExEQ6duxoF6NGo6F58+aEhYVhNpvvqx6yYjab75mTli5dmg0bNrBixQpb19Evvvgiy5cvx9XVNcfy7z6Os/PUU0/ZPZmVcSNfYeQhW7ZsQVEURo8ebbfv9evXp1WrVmzbts2urnM6B4QoavKkjRAlRFaPX+v1+mzHlLh27RpAlo/RVq5cmWPHjuVp+xEREQAsXLiQhQsX3nObudW2bVs++OADbt26RVRUFHFxcYSGhrJu3Tr27dvHkCFDCAsLo3bt2rYkKjk5maCgoExlZVzUZty5k8HX19f2/3FxcSQnJ2dbJ3cnJbkRGRlJYGBgpgugO++2u3Llit2dPhn8/f3x8PDIFHNu3X1MZPwYXdA/8EP6j8h79+5l3bp1XLhwgcuXL9vGgLn7zkIvLy+7R8AjIiKwWq1UrFgxU7mVK1e2PeUQGxtLQkICmzdvzjSuSoa8HmO5kZGIZffI89ChQwkLC2PRokUsWrSI8uXL0759e/r27WuX7Gcnt10nVK5cOdO0wMBA/v77b2JiYvLd9UZWMo65e51LV69etU27+z2Fe3/+5CSrYze/ZWXnznMfQKPREBERwcyZMzl37hyXL1/mxo0buS4vv+fb3cfV3euFh4dTvnz5TF2ZZXU83Eu5cuV4+umnbY1uW7ZsYcaMGRw7doxFixYxevRo2911AwcOzLKMkj4IrBBCCJFbkltJbnW3osyt7nT3NSuk31Q2ffp0jh8/zuXLl7ly5YotjpyumbPbj/tdLzw8HCBTTufn54eHh8c9y05MTOTNN9+0PQXk5+dHUlISU6ZMYeLEiQwePJiPPvqIN998M8vjMbcuX75MTEwMLVq0yHJ+xjl1v/lddnx9fRkyZAhDhgwhLS2NnTt3MmvWLI4ePcqXX37J+++/b7sef+mll7ItJyYmxtbrREGJi4u7Z1763nvv8eKLL/LGG2/wv//9jwYNGtCpUyf69Olje0roXrI6jrNyd47j6emJp6dnvs/be8l48ia7z7iwsDC7MUrze+4IUVik0UaIYiirC8O7fzDNrawGgbzXuBrZxZHx/0OGDMl0V1OGKlWq5Cm2tm3bArBr1y6io6Px9fUlODiYJk2asHHjRsxmMzt37uTJJ5/Mdl8yZHyR3t2FQFZjOmTV12l+v4gtFkuOT1HkFHdOP5Rmlyjkts/XgjB58mQWLVpErVq1bI9Dh4SEMHny5EwJ5d11nnH3SlbdO9x5LGbsZ5cuXbL9UblChQr3tR9ZOXnyJCqVKttxO9zc3Fi0aBGHDh1i8+bNtjFYfv75Z6ZOnWrruiE7WR2DuZVx7NyrjPwkkrk5l+48LvP7+ZOdgi4vK3fX2fz585k6dSpBQUE0btyYzp07U79+fRYuXMjatWtzLC+/51tO+5qWlpbl3Wu56Q5l//79/Pnnn4wcOZKAgADbdCcnJ7p160bDhg0JDQ21DYqa8d5+8803ODk55WU3hBBCiBJLcivJre7eRlaKMre6093H4r59+3j66adxcXGhZcuW9OnTh1q1anH58mU++OCDPJeX3zjultE7QU45XVb2799PXFwcL7/8Mn5+fkD6Exf79u1j06ZNHDt2DI1GQ6dOnfIVewaLxUKlSpV49913s5yf0bh0v/ndnc6dO8fy5ct5/PHH7fJJnU5H27Ztady4cZbX45MnT7YbT+VOBTXGT4bExEQiIiLsek64W4sWLWxdLW/ZsoXt27czZcoUfvjhB1asWJHjjYi5Pe6yOs8URckxZy7MnNdoNAJFk6MKkRfSaCOEA6nV6kyDNJrNZmJjY+9roDlI/3FbpVJx6dKlTPMy7uy6VxyAXfcAGXc3aTQaWrZsabfcuXPnuHLlyj3HdcguxqCgIHbt2kVcXJztcfumTZuycOFC1q1bR0JCgq1PYh8fH1xcXLhw4UKmsjIepb6zq6e7eXt74+bmZrtL6E5393+aW2XLluX06dOZpm/bto0NGzbw2muvUa5cuSwf9b516xaJiYm27gQyLhLufi8KutuovIqMjGTRokX06tWLqVOn2s3LTWwZDS1ZHYt3vhc+Pj44OztjNpszHWNXr17lxIkTeT7GcpKYmEhYWBghISHZXohevHiRhIQEGjRoQIMGDXj11Vc5d+4cQ4YM4fvvv8/TRf29ZHV30aVLl3B3d7c9rZHVuZqf4yPjfM7vuVTSGI1GZs+eTbNmzViwYIHdI/l39mPsCBUqVODo0aN2AwQDWX5O3S0iIoIffviBGjVq8MQTT2SaHxAQgLu7u62BJuN9L1OmjK2rjAzbtm3Dzc3tfnZFCCGEcCjJrSS3Kgm5VU5mzZqFk5MT69evt8tP5syZ48Co7HO6atWq2aYnJibaemDITsaP53f/KD5lyhROnTpFREQEXbt2pWzZsvcVY/ny5Tl27BjNmze321ZaWhqbNm2yHc8Fmd/FxcWxYMECXF1ds7wJ0MXFhXLlytniyTj3fXx8Mp37u3fvxmq15nosq9z6448/UBSFDh06ZDnfZDJx8uRJSpcuTffu3enevTtWq5Xvv/+eqVOnsn79els3ZvcrMjLSrkvJjG4hMz6jC/K8zWgUu3Dhgt14u5B+DLi4uODp6UliYmKeyxaiKEgzohAO5Ofnx8WLF+3uTvr7779tLf33w9vbm6ZNm7JmzRq7L7gjR45w8ODBTHFER0fbdRV07NgxuwvwUqVKUadOHVauXGm3XFpaGm+++SYvvPBCvvpebdu2LTt37uTAgQM0bdoUSO8PVaVS8eWXX+Ln52cbH0Wj0dCmTRu2b9/O8ePHbWUoisLcuXNRqVT3vHtEpVLRqVMn/v33X86ePWubfuXKlXz3odq2bVuioqLYtGmT3fQff/yRrVu34u3tTfv27Tl//nymLr++++47AFvMGd1fnTp1yrZMYmIi27Zty1dsGXer3O/jvLdv3wYy3+23bds2Ll26lOP77uvrS0hICOvWrbOVBekJ7j///GP7W6vV0rZtW7Zt22ZXBwCffPIJ48aNsz2+XBD7pigKH3/8McnJyYwaNSrb5T788EPGjh1LUlKSbVrlypXx8PCwSwbUavV9xfPvv//anVtnzpwhLCyM0NBQ24/5fn5+nDp1yu6uoQ0bNmQqKyOu7OLx9/enTp06rFmzhuvXr9umm0wmvv/+e/R6/T0HKi1pUlNTSUlJoVKlSnYNNidPnmTPnj0AhdJ3dG506tSJ2NhYfv/9d9s0q9XK4sWLc1w3NDQUV1dXZs+ebfc+Zti0aROxsbG2BK19+/ZA+vg+dx5DJ0+e5LnnnrMbRPZ+j2chhBCiqEluJbkVFP/cKicZ3Vjd2WCTkJDAypUrgcLvri07HTt2RKVS8fPPP9tN/+WXX3Ksk3r16uHs7MyKFSvsfoyPi4uzna87duzIsgExL0JDQ4mLi+PXX3+1m7548WJeeukldu7cCRRsfhcSEkK5cuX46aefOHPmTKb5R44c4eTJk7br8ZYtW2IwGJg3b57t6SWAGzduMHbsWD777DNb7pdTTpcbN2/eZNasWQQEBGTbGBUbG8uAAQP49ttvbdPUarXtsyIjjoI4B5YuXWr39/z58wFs9ZNx3p48edK2jNls5s8//8xUVk7vT0buM3fuXLvc5/jx4+zYsYN27do57Ak7IXJDnrQRwoF69OjB5MmTGTVqFD179iQ8PJwlS5ZkGiMkv9566y0GDRpE//79GTx4MEajkR9++CHT48s9evRg3bp1PPPMMwwaNIjo6GgWLlxIpUqV7C4k3n77bZ588kn69OnDoEGD8PLyYv369Rw+fJhXXnkl2zFB7qVt27a2HwozBq/z9vamatWqnDlzht69e9t9kb766qvs3r2bYcOGMWzYMPz9/dm0aRO7du1ixIgROXYjMGHCBLZu3crQoUN56qmn0Gg0LFy4EFdX1yzviMvJwIEDWb58OS+99BJDhgwhKCiIrVu3sn37dj7++GM0Gg3PPvssf/75Jy+++CKDBg2iUqVK7Nq1iz///JPOnTvb7nbr2LEjH374IR988AGRkZHo9XqWLFliNxheXmSMQ/LXX39RtmxZOnfunK9HratUqULZsmWZM2cORqOR0qVLc+TIEVauXInBYLC72M3O66+/zrBhw+jbty8DBw7EZDKxcOHCTBdZGe9vRl/AZcuWZevWrWzZsoUBAwbY7srJONbWrFmDoig88cQTdj/G3+306dOsXr0aSE90oqKi2Lx5M4cPH2b48OHZ3nUEMGLECJ555hmGDBnC448/jsFgYPPmzVy+fJlPP/3UtpyPjw+nTp3il19+oWnTpnnufkqv1zN48GCGDRtGcnIyP/74Ix4eHrz44ou2ZXr06MGCBQt4/vnneeSRRzh+/Di///57pqeEMv6eNWsWzZo1y7Jf54zzuW/fvgwaNAhXV1fWrFnD8ePHefvtt3Psm7ok8fT0pH79+qxYsQI3NzeCgoI4e/YsS5cutSUhSUlJBd4VQW488cQTLF68mIkTJ3Lw4EEqVarExo0bOXToEHDvrjo8PDz45JNPePnll+nRowePPfYYNWrUwGq1sm/fPn7//Xc6duxI9+7dAahWrRrDhg1j4cKFxMXF0bFjR+Li4li0aBGurq5MmDDBVraPjw979+5lwYIFNGrUKNPdaUIIIURxI7mV5FYlIbfKSdu2bZk7dy4TJkygdevW3Lp1i2XLltkaC3OTexWGoKAghgwZwqJFi4iOjqZly5YcPXrUdgPZva5ZfXx8ePHFF5kyZQpDhw6lZ8+e3Lx5k19//RW1Ws2bb77JtGnTGD58OAsWLLB7kicv+vXrx8qVK5k8eTLHjx+nXr16nDlzht9++43atWvTu3dvIP/5XVbng0aj4fPPP2fkyJH06dOHHj16ULduXbRaLceOHWPVqlXUqVOHp556ylbmyy+/zJQpUxgwYAA9e/bEbDbzyy+/YDQaef311+22D/fO6e60efNm2+eG0WjkwoULrFq1CqPRyNy5c7PNTzMadH755RdSUlIICQmx5Qh+fn5069YNyDoHz6t9+/YxduxY2rVrx4EDB1i1ahXdunWz7VvTpk3x9/fn66+/xmg04uvry+rVq0lOTs5Ulo+PD3v27GHJkiW0bt060/yqVavacp8RI0bQsWNHbt26xcKFC/Hw8OCVV17Jc/xCFCVptBHCgQYPHkxcXBzLli1j8uTJ1KhRgy+//JIFCxZk+aWUV9WrV+eXX37h008/Zfbs2Xh5eTF+/Hg2bdpk1xVT+/bteeedd/jpp5/46KOPCAoK4r333mPv3r12d0mFhITw66+/Mnv2bL7//nvMZjNBQUF88skn+frChvQvZWdnZwwGg93FWZMmTThz5oytb+YMgYGBLFmyhBkzZrB48WJSU1MJDg7mo48+om/fvjlur0yZMvz6669MnTqVefPmodfr6devH4DdnSW55eTkxMKFC5kxYwbr168nISGB4OBgZsyYYbu48fLy4rfffmPGjBls2LCB+Ph4KlSowMSJE20Xb5B+0TF37lw+//xzZs2ahbe3N/3796dy5cr3HKgwO87Ozrz00kvMnz+fDz/8kMDAQJo1a5bncvR6Pd999x2ffPIJP/30E4qiEBgYyJtvvonZbOajjz7i2LFj1KlTJ9syQkJCmDdvHtOnT2fGjBl4eXkxbNgwzp8/z8aNG23LZby/s2bNYsmSJSQnJ1OhQgXeeOMNu0eyg4ODGTZsGCtWrODo0aM0a9bsnt1ebNq0yXbHnlqtxsPDg1q1ajF9+nQeffTRe+5/69at+eabb/j2229tF49Vq1bliy++sP0YDjB+/HjeffddPv74Y8aNG5fnbtMGDBiASqWyNY41a9aMSZMm2XUTMGHCBMxmM+vXrycsLIz69evz448/8uqrr9qVNWjQIHbt2sW8efM4evRolhf4GefzrFmzWLBgAVarlRo1avDVV19l27d6STZz5kymTJnC8uXLMZlMlCtXjtGjRxMcHMz48ePZtWsXXbp0KfK4dDod8+bNY9q0aaxZswaj0UirVq14//33mTRpUo7dI3Tu3JkVK1bw/fff888//7BixQrUajVVqlTh7bffZuDAgXZ3DL711ltUrlyZxYsX8+mnn+Lu7k7jxo2ZMGGCbdBhgFGjRnH69Gm++OILevfuLY02Qgghij3JrSS3Kgm5VU7Gjx+PxWJhw4YNbNmyhVKlStGyZUtGjhxJ9+7d2bVr132P/ZJfb775Jt7e3ixfvpytW7dSo0YN5s6dy7Bhw3IcS+ipp57Cw8ODH374wXYN2rFjRyZMmEDp0qUpX748s2fPto15kx96vZ4ffviBr776io0bN7JmzRpKlSrFoEGDGDdunK3Lwfzmd9k1Ymb0KjF//ny2b99u644sMDCQcePGMWLECLtr+qeeeoqAgAC+//57pk+fjpOTE7Vr12batGk0atTItlxucro7TZkyxfb/Op2OgIAAQkNDeeaZZwgKCrrnupMnT6ZChQqsX7+e9evX4+zsTIsWLXjppZdsjUdZ5eB5NX36dObPn89HH32El5cXzz33HOPGjbOLe968eXzyySfMmzcPFxcXevToQefOnRk6dKhdWa+++iqff/45kydPZvLkybYuIe/01ltvERQUxOLFi/nkk0/w9PSkU6dOvPDCCwXWoC9EYVEp9xqZSQjxQBo2bBiRkZH8/fffjg5FPCSioqKyvAAfM2YMp06dyncXCkKUdHFxcbi6umZKdDdu3MgLL7zADz/8kGOCJoQQQgjHkdxKPAwynvBxdXW1mx4bG0vz5s0ZO3as3VPb+XH3GI9CCPEwkzFthBBCFLp+/frx9NNP202Liopi9+7d1KtXz0FRCeF4P/30Ew0aNMg0Js369evRarXUqlXLQZEJIYQQQgiR7ujRozRs2JD169fbTc/oHq0gcjppsBFCiP8n3aMJIQqMxWIhJiYmV8u6u7vnecyPonLr1q1cLefi4pLpTiORtZ49ezJnzhxeeeUVmjVrRnx8PEuWLMFqtdo9Di3Ew+bRRx/lu+++Y+TIkfTv3x8nJye2b9/On3/+yXPPPeeQcXaEEEII4XiSW4nipGHDhlSoUIEPPviA8+fPU6ZMGU6fPs1vv/1GkyZNbGMJCSGEKBjSPZoQD6HCeoT/ypUr9xzQ/U5TpkyxDQRY3FSvXj1Xyz3//POMHz++kKN5MFitVn7++WeWLFlCREQEBoOBhg0bMmHCBGrUqOHo8IRwqMOHD/Pll19y7NgxUlJSqFSpEoMHD6Z///6ODk0IIYQQOZDc6t4kt3pwXL9+ndmzZ7N9+3aio6MpVaoU3bp1sxsvRgghRMGQRhshRIExGo3s378/V8tWqVKFUqVKFXJE+bNjx45cLVehQgUqVKhQyNEIIYQQQgghHjaSWwkhhBAPL2m0EUIIIYQQQgghhBBCCCGEKAZkTJsCdvDgQRRFQafTOToUIYQQQgghikRaWhoqlYqQkBBHhyJKCMmbhBBCCCHEwyQvOZO6COJ5qCiKgjy8dG+KomAymaSeipDUuWNIvRc9qfOiJ3Ve9KTOi57Uec7kGljklRwzOZPPHseRuncMqXfHkbp3HKl7x5B6d5yHue7zcv0rT9oUsIw7xerWrevgSIqv5ORkTp48SZUqVXBxcXF0OA8FqXPHkHovelLnRU/qvOhJnRc9qfOcHT161NEhiBJG8qacyWeP40jdO4bUu+NI3TuO1L1jSL07zsNc93nJmeRJGyGEEEIIIYQQQgghhBBCiGJAGm2EEEIIIYQQQgghhBBCCCGKAWm0EUIIIYQQQgghhBBCCCGEKAak0UYIIYQQQgghhBBCCCGEEKIYkEYbIYQQQgghhBBCCCGEEEKIYkDr6ACEEEIIIYTjWSwW0tLSHB1GsWQ0Gm3/qtUP3z1POp0OjUbj6DCEEEIIIYR4KD1IudqDnFsVZN4kjTZCCCGEEA8xRVG4fv06cXFxjg6l2LJarWi1Wq5evfrAJRa55eXlRenSpVGpVI4ORQghhBBCiIfCg5irPei5VUHlTdJoI4QQQgjxEMtIAkqVKoWLi4v8KJ8Fi8WC0WjEYDA8dE+cKIpCcnIyN2/eBKBMmTIOjkgIIYQQQoiHw4OYqz2ouVVB503SaCOEEEII8ZCyWCy2JMDX19fR4RRbFosFACcnpwcqscgtZ2dnAG7evEmpUqUeyjooScLCwpg+fTrnzp3D19eXIUOGMHLkyFwl+SdOnKBfv35s3LiR8uXL2807evQoU6dO5dixY7i6utK7d2+ef/559Hp9Ye2KEEIIIcRD60HN1R7k3Kog86YH7xkkIYQQQgiRKxn9Iru4uDg4ElHcZRwjD0pf2g+qQ4cOMWbMGCpXrszs2bN57LHHmDZtGnPnzs1x3TNnzjB69GjMZnOmeREREYwYMQKDwcCMGTMYOXIk33//PR9++GFh7IYQQgghxENPcrWSqaDyJnnSRgghhBDiIfcgPGYvCpccIyXD7NmzqVmzJtOmTQOgbdu2mM1m5syZw/Dhw3Fycsq0jslkYtGiRcyaNQuDwZBluXPnzsXV1ZWvv/4avV5Pu3btcHJyYvLkyYwZM4ayZcsW6n4JIYQQQjys5Dq8ZCmo90uetBFCCCGEEEKIEs5kMrF79246depkN71Lly4kJSWxf//+LNf7559/+PLLL3n22Wd59dVXs1wmLCyMdu3a2XWF1rVrV6xWK2FhYQW3E0IIIYQQQgh50kYIIYQQQmQWmxJLvDHeIdv2MHjg7eydp3VCQ0MBWLNmDW5ubnbzJk2aRGRkJAsXLsxVWYqisGrVKtq2bZtt/9HVq1e3+1uv11O6dGm6dOnC2LFjbY/FX7lyhQ4dOvDTTz/RrFmzPO1TfiQnJ7Ny5UqGDBlS6NsSxUtERARpaWlUqlTJbnrFihUBuHjxIq1atcq0Xt26dfn777/x8vJixYoVmeanpqYSGRlJUFCQ3XQfHx/c3Ny4ePFiwe2EEEIIIYTIUWKyieTUzF3aFgUXJy1uLnkb03DSpEmsXLnynsucPn06z7EMGzaMcuXK8cknn+Rq+dDQUJ544gnGjx+f520VNWm0EUIIIYQQmcQb49l5ZSdGs7FIt2vQGmhRvkWeG20AIiMjmTp1Kh988MF9xbB3714mTZrEX3/9dc/l3nzzTR599FEgvbHkyJEjfPrppxw+fJgFCxag0+koU6YMYWFheHp63ldMubVgwQJWrFghjTYPoYSEBIBMjZaurq4AJCYmZrleQEBAvsrNKDu7cnNDURSSk5Pzvf6DLiUlxe5fUXSk7h1D6t1xpO4dR+reMUpCvRuNRqxWKxaLBYvFYjcvMcXEqUsxpJmtRRqTTqumRiUfnA2aPK03adIkXnzxRSD9+u+RRx5h0qRJdOvWzbbM3fuYGzNmzECj0eR63d9++w2DwZCvbeWWxWLBarWSkpKC1Wr//iiKkuvu06TRRgghhBBCZMloNmK0FG2jzf2oUKECv/32G127dqVly5b5LkdRlFwt5+7ujr+/v+3vihUrEhQURN++fVm1ahX9+vVDo9HYLVPYchu7ePDcnRTeTa3OX8/YOZV7P/12p6WlcfLkyXyv/7C4dOmSo0N4aEndO8aDWu9qtTrPn5mKouT4OVyQHtS6Lwmk7h2juNe7VqvFaMycj5nNZlJSTZjMhdf4kBW9VoPZbCY1NTVP6+l0OnQ6nd00Jycn3N3dbX/ntcyMMvKybkZvCPnZVm4ZjUbMZjMXLlzIcv6d3Q3fizTaCCHEwy42FuLvswskDw/wzvtd8SIX5P0RItd69uzJgQMHeOutt1i7dm2WTwYAxMXFMXPmTP7++29iY2OpVasWL730Es2aNWP37t0MHz4cgA4dOjBlyhR69eqV6xjq1KlDo0aNWLduHf369cvUPdqlS5eYPHkyhw4dwmq10rBhQyZOnGjrbu3MmTN8/vnnHDhwgJSUFAICAhgyZAgjR44E0u8G/PDDD9m6dSvx8fEEBwf/H3v3HV9Flf9//DUzt6UXSmghoQooCIgi0mzY0HXVVbGhYl9duy66Rd11dZUVC+zK17ar6/pzdbE3sIFiQ8BC7yGhBtLL7TO/P65EIwFCSHIT8n4+HvfBzdw5Zz5zbri5Zz5zzuHXv/41J5xwAtOmTWP69OlAbPq2Dz/8kG7dujFz5kyeeuopNm3aRNeuXZkwYQIXXXQRpmnWxHfzzTfz3HPP4fP5eP3113fbdtJy7ez0VlVV1dq+cyRMQ9/TneV+Xu/Oun/a2d5Xbreb3r17N7j8gc7v95OXl0dubi4JCQnxDqdNUdvHx4He7oGwjT+wbxdYE3wWPnfTL0d9oLd9S6a2j4/W0O7BYJDNmzfj9XprkhM7uQIOLpcLp5mXq3e5TFwu1y7x7IudN5n9tJ5XX32VGTNmMHbsWF577TWOOOIIpk+fzgcffMCTTz7JmjVriEaj9O7dmxtvvJFRo0YBcPHFF9O1a1fuu+++mjquvvpqZsyYwdatW+nTpw933nknQ4cOBeD444/nl7/8Jddddx3Tp09n0aJFHHXUUfznP/+hpKSEQYMGcdddd9GrVy8AiouL+ctf/sK8efOwLItf/epXLF68mMMOO4zrrrtuD+3konv37ni93lrb16xZU+92UtJGRKStKy+HL76AOu7eqBevF0aMUFKgqej9Eak3wzD4y1/+wmmnncYDDzzAn//85132iUajTJo0iXA4zJQpU8jMzOS5557jsssu44UXXmDIkCFMmzaN3/zmN7z88sv07dt3n+Po27cv77zzTp2v3XzzzfTr14+ZM2cSiUR44IEHuO6663j//ffx+/1MmjSJkSNH8uKLL2JZFi+//DIPPPAAI0aMoH///jz66KOsXLmSJ554gtTUVF5++WVuuukmZs2axaRJk6iuruadd97hf//7H5mZmfz3v/9l6tSp/PGPf2TQoEEsW7aMP//5z2zbto3bb7+9Jq5XX32VZ599Fr/fr4RNK9W9e3csy2LDhg21tufn5wPUdD73VVJSEllZWbvUW1RURFVVVYPrhdj/2Z13PMruJSQkqJ3iRG0fHwdqu1cWV7N2c2m9pzNyu0z65WSSmNZ8bXGgtn1roLaPj5bc7qZpYpomlmVhWbWnIzMN84fX4xCTYe4Sz77YOTWZYRg19ZimSUFBAdu3b+e1114jEAiwfPlybrzxRn77299y3HHHUVlZyUMPPcTkyZOZO3cuHo8HwzBq6jFNk61bt/LSSy/xt7/9jaSkJO6++27uvPNOZs+eXbPvzjY1TZOFCxfi8/l44oknCIfD3H777dx7770899xz2LbNr3/9a6LRKE899RRut5v777+fBQsWcPjhh++2DXbWnZCQsEtya19GWzbzWysiIi1SMLh/D2laen9E6q1r16789re/5aWXXmLevHm7vD5v3jyWLl3KQw89xBFHHEHv3r2555576NOnD08//TQej6dm/ZnMzMwG3UWWmpq623U+8vPzyczMpGvXrvTu3Zv77ruPe++9t2be44kTJ/LHP/6RXr16kZuby/XXXw/8uDBnfn4+SUlJZGdnk52dzQ033MCMGTNIS0sjKSmJxMTEminZLMviH//4B9dccw3jx48nOzubE088kZtuuonnn3++1lQL559/Pr1792bgwIH7fL7SMni9XoYNG8b7779fa5q8WbNmkZKSwqBBgxpc98iRI5kzZw6hUKhWvZZlceSRR+5X3CIibUk4Yu/TQ0SkLfn1r39NdnY2ffr0wbIs/vCHP3DJJZeQnZ1N//79mThxIsXFxRQVFdVZPhwOc8899zB48GD69OnDpZdeSn5+Ptu3b69z/0gkwoMPPki/fv0YOHAgEyZMYNGiRQDMnz+f77//nr/97W8MHjyYgw8+mEceeaTe05vtL420EREREZEDyrnnnsusWbP4/e9/z1tvvVXrtVWrVpGSklJrBI1hGAwbNqzOJE9DVFRU7HbKqJtuuon77ruPF154gSOOOILRo0dz6qmnYpommZmZnH/++bz11lssW7aM/Px8VqxYAfy4rsgVV1zB1VdfzYgRIxg0aBAjR47ktNNOq/N4xcXFbN26lalTp/Loo4/WbLdtm2AwyMaNG2uG7Ofk5DTKuUt8XXPNNVx66aXccMMNnHXWWXzzzTc8/fTT3HLLLSQkJFBZWcmaNWvo3r07mZmZ9a738ssv5+233+byyy/n0ksvJS8vj6lTp3LOOefQpUuXJjwjEREREWkrcnNza57379+ftLQ0nnjiCdatW8eGDRtq+kY7R+vU5aejwHf2kcLhcJ37tm/fvuaGvZ3779x32bJlpKWl0bNnz1r79+jRY99PrAE00kZEREREDjj33nsvFRUV3H///bW2/3QEws+3u1yNcz/T0qVLGTBgQJ2vXXDBBXzyySf8/ve/JyUlhccee4zx48ezY8cOtm/fzi9+8QtefvllsrKyOP/883n11VdrlR8yZAhz587lscce4+CDD+a1117jlFNO4YsvvtjlWDsTPXfccQevvfZazeONN95g9uzZZGdn1+y7P/NSS8sxYsQIpk2bxvr167n22mt58803uf3227niiiuA2O/mueeey5w5c/ap3l69evHMM88QCAS4/vrr+ec//8kll1zC7373uyY4CxERERFpi37aJ5k/fz4nnngiixcvpl+/flx33XVMmTJlr3XUNRJmd33APY2asSyrpj8VDxppIyIiIiIHnC5dujB58mR+//vfk52dTefOnQE46KCDqKioYNWqVTWjbRzHYeHChTULou/LXMM/t2TJEr799lv++te/7vJaUVERf//737nyyis588wzOfPMM9m2bRtjxoxh/vz5bNu2jdLSUmbNmoXb7QZ+nBZtZ0fjscce47DDDuO4447juOOO44477mD8+PHMmjWLESNG1Iq9Xbt2ZGZmUlBQUGskzTvvvMP777/PAw880ODzlJZr3LhxjBs3rs7Xhg8fXvM7VZedv5d1GTZsGC+99FKjxCgiIiIisifPPPMMw4cPZ9q0aTXb/v3vfwO7T8I0pn79+lFRUcHatWtrRu+UlJTsss5jU9FIGxERERE5IJ199tmMGjWKgoKCmm2jRo2if//+3HLLLcyfP5+1a9fypz/9iVWrVnHxxRcD1CxGumLFCqqqqnZbf0VFBdu3b2f79u1s2LCBN998k+uuu47hw4fzi1/8Ypf909LSmDNnDr///e9Zvnw5BQUFvPjii7jdbg455BA6deqE3+/nvffeY/PmzcybN4+bb74ZoGYtkYKCAu666y6++OILNm3axKxZs9i8eTNDhgypib2srIz169cTiUS44oor+Pe//83zzz9Pfn4+77//PnfffTc+n6/Z5mMWERERERHZF507d2blypUsWLCAjRs3MnPmzJopn3+6zmJTGT58OIceeii333473377LStWrODWW2/F7/fv101+9aWRNiIiIiJSJ6/L2+qPee+993LaaafV/GxZFs888wwPPPAA1113HaFQiEMOOYR//etfDB48GIC+ffsyduxYbrzxRm6++eaaZM7P3Xfffdx3331AbGh9Tk4OF1xwARMnTsSyrF32d7lcPPnkkzzwwANccskl+P1++vfvzxNPPEH37t3Jzs5m6dKl/PWvf6WyspKuXbty9tln8+GHH7J48WLOO+887rrrLh544AFuu+02SktL6dq1K7feeiunn346ACeccAIvvfQSv/jFL3j++eeZNGkSXq+Xf//73/z1r3+lffv2nHPOOVx//fWN2s4iIiIiItJ83K7mH4vRnMe8/vrr2bFjB1dffTUAvXv35r777uO2225j8eLFtdauaSrTpk3jT3/6E5dccgler5fzzz+fdevW1cyK0JQMpznGE7UhixcvBmDgwIFxjqTlqq6uZvny5fTv37/mTlZpWmrz+Gg17b5hA8yZA8Fgw8p7vXD00dACFrFuNW2+L1r4+3NAtnkL15htHggEWL9+PT169NhlTZMSfwnlwfL9qr+hUr2pZCRkxOXYdYlGowQCAXw+X53JmLZgT78roO/Asu/0O7N3+hsbP2r7+DjQ272wuJrFa3cQjtRvjQS3y2Rgr/Z0zGz6tjjQ274lU9vHR2to9z19/66sDlEdiMQlrkSfi+TEho/Yby19q+LiYr777jtGjRpVk6QJhUIMHz6cu+66i1/+8pd1ltvT+7Yv33810kZEREREdpGRkNGiEiciIiIicmBoyAXnhlwobq7jiDS35ESPfk+bmMvl4qabbmLChAmcd955hMNhnn76aTweD2PGjGn64zf5EURERERERERERESA6kCEFRuK92nUUb+czH2+SN1cxxGRA09qaiozZszgkUce4b///S+maTJ06FCee+45MjMzm/z4StqIiIiIiIiIiIhIswlH7HonU1rDcUTkwHPkkUfy4osvxuXYzb9ikYiIiIiIiIiIiIiIiOxCSRsREREREREREREREZEWQEkbERERERERERERERGRFkBr2oiIiIiIiIiISKtWWR2iOhDZ53KJPpcWnhcRkRZFSRsREREREREREWnVqgMRVmwo3qdF590uk345mUraiIhIi6KkjYiIiIiIiIiItHrhiL1PSRsREZGWSGvaiIiIiIiIiIiIiIiItAAaaSMiIiIiuyopgfLy+Bw7NRUyMvapyLHHHsumTZtqfna73bRv356xY8dyww03kJmZCcBBBx3E/fffz5lnntmoIdclHA7zn//8h0suuaTJjyUiIiIiIm1D1F+JHayOy7FNbyJWQvI+lZk8eTKvvvrqHvdZuXJlg2NauHAhjuMwbNiwBtfR0ihpIyIiIiK7Ki+HL76AYLB5j+v1wogR+5y0AZg0aRKTJk0CIBAIsGrVKqZMmcKFF17If//7X1JSUpg3bx4pKSmNHXWd3nrrLe6//34lbUREREREpNHYwWoCm1ZCJNK8B3a58HU9aJ+TNr/73e+45ZZbAIhGo4wdO5Y77riD8ePHN0pY559/Pvfff7+SNiIiIrIXjTFKwTTB72+ceEQaIhhs/qTNfkhMTKRDhw41P2dnZ9O/f3/Gjx/PU089xU033VTr9abmOE6zHUtERESkuVVWh6gO7NtFY8OAUDjaRBGJtCGRCE403KyHNBpYLiUlpebGuWg09v8/OTm5WftmrY2SNiIiIk2hMUYppKRA796NF5NIG9SlSxfGjRvH22+/zU033VRrerSioiLuuecevvrqK/x+PwMGDODmm2/miCOOAGDz5s1MmTKFL7/8kvLyctq1a8dpp53GLbfcgmmaRKNRpk6dyltvvUVRURHdunXj4osv5rzzzuOVV17hjjvuAGJTsj333HMMHz6cjz/+mGnTprFmzRqysrIYP348v/71r/F4PDX7Xnvttbz66quEw2Gef/55cnNz49V8IiIiIrtVHYiwYkMx4Yhd7zIJXhed2yc1YVQi0trsrY80d+5cHn30UdauXUtiYmLNSJ20tDQOOuggAO644w7mz5/PX//613ieSqNR0kZERKSp7O8oBa+38WIRacP69u3L66+/TlVVVa3td999N6FQiOeffx6Px8OMGTP49a9/zSeffEJiYiLXXHMNHTp04KmnnsLlcvH555/z17/+lSFDhnD88cfzwgsv8N577/Hwww+TlZXFxx9/zN13302fPn045ZRTqKio4L777mPevHmkpaXxySefcOONN3LHHXdw1FFHkZ+fz5///GfWr1/Po48+WhPXCy+8wJNPPkk0GlXCRkRERFq0cMTep6SN21X/fUXkwLe3PlJxcTHXXXcdkydP5uijj2br1q3cfvvtPPjgg/zlL39h3rx5jBo1ijvvvLNZ1i1tLkraiIiIiMgBLTU1FYDKyspa2/Pz8+nbty/Z2dn4fD5+97vfcdppp2FZFoFAgNNPP52TTz6Zjh07EggEmDhxIk899RQrV67k+OOPJz8/n8TERLp160bHjh258MIL6dmzJz169MDn89VMAbBz2P+MGTM455xzmDBhAgDdu3fnnnvu4eKLL2bjxo1069YNgNNPP52BAwc2V/OIiIiIiIjExd76SBUVFYRCIbp06ULXrl3p2rUrM2bMqJlmbWdf66dTsB0IlLQRERERkQNaRUUFEJs3+aeuu+46brvtNmbNmsVhhx3GqFGjOPXUU/H+MMrtwgsv5L333uPbb78lLy+PNWvWsGPHDmw7dofoBRdcwAcffMDYsWPp378/I0eOZPz48bRr167OOJYtW8b333/P//73v5ptO9e9Wbt2bU3SJicnp3EbQEREREREpAXaWx9p7NixnHrqqVx99dV06NCBkSNHcvTRRzNu3Lh4hdwslLQRERERkQPa0qVLyc3NJSmp9vzp48aN49NPP+XTTz/l888/55///CfTp0/npZdeomvXrlx44YUEAgFOOOEETjvtNA477DAuuuiimvK5ubnMnj2b+fPn89lnnzFnzhyefPJJ7r//fs4444xd4rBtm8svv7zO1366CKfP52vEsxcREREREWmZ6tNHeuihh7j22mv55JNP+Pzzz7nttts47LDDePbZZ5s73GajpI2IiIiIHLC2bt3Khx9+yBVXXFFreygU4qGHHuL000/nlFNO4ZRTTiEQCDBy5EjmzJlDTk4OS5cu5bPPPiMjI4NAIEAgEKCoqKjmzq/nnnuOdu3aMX78eEaOHMntt9/OpZdeyjvvvMMZZ5yBYRi1jtmnTx/Wr19fayTNV199xXPPPcfdd99NYmJi0zeIiIiIiIhIC7G3PtLq1at5++23ufPOO+nZsyeXXHIJb7zxBrfddhtFRUW7neWgtVPSRkREREQOCNXV1Wzfvh2AQCDAypUreeSRR+jWrRuXXnpprX09Hg+LFy9mwYIF/OEPf6B9+/Z88sknVFdXM2TIEDweDwBvvPFGzfo1f//73wmHw4RCIQCKi4v5+9//js/no1+/fqxbt47ly5czceJEgJokzJIlS+jduzdXXHEFN954I9OnT2f8+PFs3bqV3/3ud3Tr1q3WSBsRERERAGPvu4iItGp76yOVl5fzwgsv4Ha7OeeccwgGg7zzzjvk5uaSkZEBxPpda9eupaSkpGZba6ekjYiIiIjU7Ye1XVrLMZ955hmeeeYZANxuN507d+aUU05h0qRJu0yNBvDwww9z//33c80111BRUUHPnj3529/+xrBhwwC44447+Ne//sUjjzxChw4dGD9+PF26dGHx4sVAbE2ccDjMvffey/bt2+nQoQPnnXceV111FQBHHnkkhx56KBMmTGDKlCmcfPLJPPzww/zf//0fM2bMID09nWOPPZZbb721wecsIiIiBybLNIjYNoXF1ftcNtHnIjnR0wRRiUiL4XI1f2LX1fiphJNOOmmPfaRevXoxbdo0pk+fzgsvvIBpmhx55JE8+eSTmKYJwKRJk3jqqadYu3YtM2bMaPQY40FJGxERERHZVWoqjBgRv2Pvo48++qhe+61cubLmeVZWFo888shu973kkku45JJLiEajBAIBfD4flmXVvO5yubjtttu47bbb6iyflpbGSy+9VGvbySefzMknn1yv+ERERKTtMk2DQChKwbZSwhG73uXcLpN+OZlK2ogcwExvIr6uB8Xt2Ptr0aJFtdbx3Fsf6ZhjjuGYY47Z7eu/+c1v+M1vfrPfcbUkStqIiIiIyK4yMmIPEREREYmbcMTep6SNiBz4rIRkrITkeIchTciMdwAiIiIiIiIiIiIiIiKipI2IiIiIiIiIiIiIiEiLoKSNiIiIiIiIiIiIiIhIC6CkjYiIiIiIiIiIiIiISAugpI2IiIhIG+c4TrxDkBZOvyMiIiIiIs1P38Nbl8Z6v1pV0mbevHmcddZZHHrooRx77LE8/fTTe22It956i/HjxzNo0CBOPvlkXn311V32+eCDDzjzzDMZMmQI48aNY/r06YRCoaY6DREREZEWwe12A1BdXR3nSKSl2/k7svN3RkREREREmo76aq1TY/WbXI0RTHP49ttvufrqqzn55JO54YYbWLhwIVOmTCEajXLllVfWWWbWrFnceuutTJw4kdGjR/PBBx8wefJkPB4P48ePB+Czzz7juuuu45RTTuGWW25h9erVTJ06lZKSEv7whz805ymKiIiINCvLskhPT6ewsBCAxMREDMOIc1QtTzQaJRgMArE2a0scx6G6uprCwkLS09Pb3PmLiIiIiMTDgdpXO1D7Vo3db2o1SZtp06bRv39/pkyZAsCYMWOIRCLMmDGDiRMn4vP5dikzdepUTjrpJO68804ARo8eTVlZGY8++mhN0uaVV16hS5cuTJkyBcuyGDlyJEVFRfzzn/9k8uTJuptQREREDmidOnUCqOkMyK5s2yYSieByuTDNVjVQvdGkp6fX/K6IiIiIiEjTOxD7agd636qx+k2tImkTCoX46quvuP7662ttP/HEE3nqqadYuHAhI0eOrPXaxo0bycvLq7PMu+++S15eHrm5uQSDQRISEmplv9LT0wmHw1RVVZGent5k5yUiIiISb4Zh0LlzZzp27Eg4HI53OC2S3+9n3bp1dO/enYSEhHiH0+zcbvcBdReciIiIiEhrcCD21Q7kvlVj9ptaRdKmoKCAcDhMbm5ure05OTkArF+/fpekzdq1awH2WCY3N5cLLriAK664gqeffpqzzz6bdevW8eyzzzJ27FglbERERKTNsCxLF+Z3w7ZtALxeb52ju0VERERERJrKgdRXU9+qflpF0qaiogKA5OTkWtuTkpIAqKys3KXMzm17K3PkkUdy2WWX8eCDD/Lggw8CMGDAAB566KEGx7tzDjupm9/vr/WvND21eXy0lnZ3hcM44TCEQg2rwDQxwmEiLeBzryW1+X63K0A4jBWNEm3B709LavO2Qm3e/NTme+c4zgExx7aIiIiIiEi8tYqkzc4M3O7UNf9dfcvcddddvPLKK1xzzTWMGDGCTZs2MX36dC6//HL+9a9/NWiYVjgcZvny5ftcrq3Jy8uLdwhtjto8Plpyu1uWRVYgQGTbNuwGXtQ3ExNx7djBtspKotFoI0fYMPFu88ZoVwBXKESq30/59u1E6rhBoT6a6/2Jd5u3RWrz5qc23zOPxxPvEERERERERFq9VpG0SUlJAaCqqqrW9t2NpqlvmW3btvHSSy9x1VVXceONN9bsM2jQIMaPH8/MmTO58MIL9zlet9tN796997lcW+H3+2vWFDrQ5i5sqdTm8dFa2t21eTNOVhYEAg2rwOfDaN+etC5dGjewBmhJbb7f7QqQloaVkICnQwf44e/aPmvi96cltXlboTZvfmrzvVuzZk28QxARERERETkgtIqkTffu3bEsiw0bNtTanp+fD0CvXr12KdOjRw8ANmzYwIABA2q276yjV69ebN68GcdxGDp0aK2yvXv3Jj09ndWrVzcoXsMwSExMbFDZtiQhIUHt1MzU5vHR4tvd7Y499jJCcW/lPS3oHFtEm+9vu+6sw7JwtYL3p0W0eRujNm9+avPd09RoIiIiIiIijWPXecVaIK/Xy7Bhw3j//fdxHKdm+6xZs0hJSWHQoEG7lMnJyaFbt27MmjWr1vbZs2eTm5tLt27dyMnJwbIsFi5cWGufdevWUVpaSnZ2dtOckIiIiIiIiIiIiIiIyM+0ipE2ANdccw2XXnopN9xwA2eddRbffPMNTz/9NLfccgsJCQlUVlayZs0aunfvTmZmJgDXXnstd9xxB+np6Rx77LF8+OGHvPvuuzz88MMAZGZmcvHFF/P0008DcNRRR7F582amT59O165dOeecc+J2viIiIiIiIiIiIiIi0ra0mqTNiBEjmDZtGo899hjXXnstWVlZ3H777UyaNAmApUuXMnHiRO6//37OPPNMAM4880xCoRDPPPMMM2fOJDs7mwceeIBTTjmlpt7bb7+drKwsXnzxRZ555hk6duzIyJEjuemmm0hNTY3LuYqIiIiIiIiIiIiISNvTapI2AOPGjWPcuHF1vjZ8+HBWrly5y/YJEyYwYcKE3dZpGAaXXHIJl1xySWOFKSIiIiIiIiIiIiIiss9aVdJGRETkgLF5M+Tnw6ZNsH07tGsHOTnQowd06BDv6ERERERE2gQj3gGIiIj8jJI2IiIizSkvD157DZYv3/0+AwbAhAmgaTpFRERERJqMZRpEbJvC4up9Kpfoc5Gc6GmiqEREpK1T0kZERKQ5VFTACy/AokWxny0LevaELl2gY8fYaJsNG2KPZcvgnntg/Hi48874xi0iIiIicoAyTYNAKErBtlLCEbteZdwuk345mUraiIhIk1HSRkREpKlt3gzTp0NRERgGDB8Op50G7dvvum9hIfz3v7BkCbzxBmzcCFdeGSsnIiIiIiKNLhyx6520ERERaWpK2oiIiDSlJUvgySchEIitVXPVVZCdvfv9O3aE666D776DZ5+Njcx56KHYNp+v+eIWEREREREREZFmZ8Y7ABERkQPWggWxETaBAPTpA5Mn7zlhs5NhwODBsanRUlJg9Wp49FHw+5s8ZBERERERERERiR8lbURERJrCl1/CjBngOHDkkXDjjZCcvG919OoFTzwBSUmwbh3885+x+kRERERERERE5ICkpI2IiEhjW7wYrrgCIpHYiJmLLwZXA2ckHTAAbrklVv677+Djjxs1VBERERERERERaTmUtBEREWlMmzfDSSdBRQX07QuXXQbmfv657dkTzjor9nzmTMjP3/84RURERERERESkxWngbb8iIrJfSkqgvHz/6khNhYyMxolnfxlGvCNoGSIROO+8WOKmTx+44YaGj7D5uWOOgRUrYqNtnnwSfvc78Pkap24REREREREREWkRlLQREYmH8nL44gsIBhtW3uuFESNaRtLG5YolKzZs2L96WlISqqHuvhs++SS2ds0TT8TapKHv8c8ZBkycCPfeC4WF8NprMGFC49QtIiIiIiIi6HZEEWkJlLQREYmXYLDxLujHk2VBZSUsW3ZgJKEaatYsuO++2PMnn4QePfY/kfVzycmx9XEeeQTmzoXRo6Fr18Y9hoiIiIiISBtkmQYR26awuHqfyyb6XCQnepogKhFpi5S0ERGRxnGgJKEaYutWuPBCcBy4+urYCJjGTtjs1L8/DB0KixbBiy/CzTdrejoREakxb948Hn74YdasWUO7du244IILmDRpEsYe/la89dZbPP744xQUFNC1a1euvPJKzjjjjFr7fPDBB/zjH/9g/fr1tG/fntNPP50rr7wSj0cXqERE5MBgmgaBUJSCbaWEI3a9y7ldJv1yMpW0EZFGs58rI4uIiLRxOxM1O3bAoYfCww83/TF/9Stwu2HVKliwoOmPJyIircK3337L1VdfTc+ePZk2bRqnnXYaU6ZM4cknn9xtmVmzZnHrrbcycuRI/v73v3PEEUcwefJk3n777Zp9PvvsM6677jpyc3OZPn06F1xwAU888QQPPPBAc5yWiIhIswpH7H1+iIg0Jo20ERGRhqmo+HF0zbZtYB9AX1RLSmLrDtXHq6/C66/HkigPPBBrC9MEv7/p4mvXDk46Cd58E2bOhEGDYlPMiYhImzZt2jT69+/PlClTABgzZgyRSIQZM2YwceJEfD7fLmWmTp3KSSedxJ133gnA6NGjKSsr49FHH2X8+PEAvPLKK3Tp0oUpU6ZgWRYjR46kqKiIf/7zn0yePBm32918JykiIiIicoBT0kZEROqvuBgWLow91q+v/Vq7dnD44TB8OHTpEp/4Gkt5OXzxxd6neysthd//Pvb8tNNi06Rt3QopKdC7d9PGeMIJ8PnnUFQE778Pp57atMcTEZEWLRQK8dVXX3H99dfX2n7iiSfy1FNPsXDhQkaOHFnrtY0bN5KXl1dnmXfffZe8vDxyc3MJBoMkJCRgWVbNPunp6YTDYaqqqkhPT2+y8xIRkeZhmpqMR0SkpVDSRkRE9i4UgrffhtmzfxxRYxix0SUA0WgsefDee7HH0KFwwQWQnBy/mPfX3tbocRx45hmoqoLu3eH443/cvzlGvXg8cMYZ8NRT8MEHcOyxkJjY9McVEZEWqaCggHA4TG5ubq3tOTk5AKxfv36XpM3atWsB9lgmNzeXCy64gCuuuIKnn36as88+m3Xr1vHss88yduzY/UrYOI5DdfW+L/bcVvh/GLXrb8rRu1IntX187G+7h8NhwqEQoX1Zi8S0saP2vpWzTcLh8D5/fu1rfA2KrYHx+f1+fElpbC/x46oI16uMaRiEGhCf2rw2fd7Eh9o9ftpy2zuOs8d1Jn9KSRsREdmzlSvh+eehsDD2c69esRE1Q4dCWhqkpkLPnvDcczBvHixeDIsWwZo1cMklcPDBcQ2/ySxcCN9/Dy5X7Dx/cvdxsznsMHjnHdi8OZa4+cUvmj8GERFpESoqKgBI/tkNE0lJSQBUVlbuUmbntr2VOfLII7nssst48MEHefDBBwEYMGAADz300H7FHA6HWb58+X7V0Rbk5eXFO4Q2S20fHw1pd8uyMDwpbCvcRiAUqXe5tGQfHTO8FG7fjj8YqlcZn8dF5wyD7VsqiEajTRZfQ2Lb3/i+/XYNoXrGl5zko29up32OT21eN33exIfaPX7aatt7PJ567aekjYiI1M1xYomA//0v9nN6Opx3HgwevOu+Pl8skTNoEOTnx0agbNkCjz0WmzbsQJu6y++Hl16KPT/pJOjaNT5xmGasbZ94Aj78EI47Dn640CYiIm2LvZe15eqa9qa+Ze666y5eeeUVrrnmGkaMGMGmTZuYPn06l19+Of/6179ISEhoUMxut5veTT2daCvm9/trpqhraBtLw6jt42N/272kIkxWR2efRkgk+VwkJiTSsUOHepfzuEzat2tPRkrnJo2vIbE1NL5AIEDB1hKSk9NwqN80aQ2NT21emz5v4kPtHj9tue3XrFlT732VtBERkV3ZNrz8Mnz0UeznkSPh7LOhPn9Qu3eHO++EmTNhzhx4881YAui005o05Gb1xhtQVgYdO8aSNvE0ZAh06wYbN8aSbKefHt94REQkLlJSUgCoqqqqtX13o2nqW2bbtm289NJLXHXVVdx44401+wwaNIjx48czc+ZMLrzwwgbFbBgGiZrac68SEhLUTnGito+PhrZ7ZaAat8cD5j5M1eVxYVrmPpVzu0zcbvc+x7iv8TUktv2JL1bWBWb9LhU2OD61eZ30eRMfavf4aYttX9+p0YB6ps9FRKTtiERi66TsTNj86ldw0UX1S9js5PHERuX86lexn996K5a8ORDk58PHH8een3fej+v6xItpwvjxsecffRRbY0dERNqc7t27Y1kWGzZsqLU9Pz8fgF69eu1SpkePHgC7lNn5c69evdi8eTOO4zB06NBa+/Tu3Zv09HRWr17daOcgIiIiIiJK2oiIyE/Zdmxqs4ULY2u0XHYZjBsH+3A3QC3jxtVO3Mya1XixxoNtw3/+Exs5dPjhMGBAvCOKGTw4NtomEIhNkyYiIm2O1+tl2LBhvP/++ziOU7N91qxZpKSkMGjQoF3K5OTk0K1bN2b97O/z7Nmzyc3NpVu3buTk5GBZFgsXLqy1z7p16ygtLSU7O7tpTkhERGQ/GcYPo2Dq+XBZJqZp1NpmmQ3sC4uI7AdNjyYiIjGOE0tI7EzY/PrXcMgh+1/vuHGxumfOhFdfhS5dYODA/a83Hj79FPLyYmv4nH12vKP5kWnCySfDk0/C3LmxKdvqubidiIgcOK655houvfRSbrjhBs466yy++eYbnn76aW655RYSEhKorKxkzZo1dO/enczMTACuvfZa7rjjDtLT0zn22GP58MMPeffdd3n44YcByMzM5OKLL+bpp58G4KijjmLz5s1Mnz6drl27cs4558TtfEVERHYn6q/EHSynsy9A1Hb2XgBwu8IkRqJ09gVrykQtH5vL7HrXISLSGJS0ERGRmJkzYd682O1Il13WOAmbnU44AQoLY0mPp5+GO+6ArKzGq785lJXFkk4Av/wlpKXFNZxdDBkC7dpBURF88QWMHRvviEREpJmNGDGCadOm8dhjj3HttdeSlZXF7bffzqRJkwBYunQpEydO5P777+fMM88E4MwzzyQUCvHMM88wc+ZMsrOzeeCBBzjllFNq6r399tvJysrixRdf5JlnnqFjx46MHDmSm266idTU1Licq4iIyJ7YwWoCG1dQsa2UaLSeSRu3hZXipaLMTzTq4HJ7SOjeD9P0KmkjIs1KSRsREYlNqfX++7HnF10Ehx3W+MeYMAE2b4a1a+Hxx+G3v923dXLi7X//A78fundvmQkRy4Ljj4f//hc++ABGj46NwBERkTZl3LhxjBs3rs7Xhg8fzsqVK3fZPmHCBCZMmLDbOg3D4JJLLuGSSy5prDBFRESanBMJEwmF6p20MR0LO2zsUxkRkaagqzkiIm3d55/HpkWD2AiSkSOb5jguF1x1FaSnw5Yt8PzzsWnTWoMVK2D+/NgopAsuaLnJkKOOgsTE2Kim77+PdzQiIiIiIiIiIrKPWuhVJxERaRZr18bWrrFtGD48thZKU0pLiyVuTBMWLIglQlq6cBheeCH2fOxYyM2Nazh75PPBmDGx57NnxzcWERERERERERHZZ0raiIi0VeXlcNppUFoKPXvGpkUzjKY/bs+eMH587PkLL8TWYGnJZs+GbdsgNRVOPz3e0ezdscfGpkpbuxbWrYt3NCIiIiIiIiIisg+UtBERaYuiUTjvPFi+HDp1guuvB7e7+Y5/8snQowcEAvCvf8VG+rRE27fDO+/Enp99dmzqsZYuLQ2OOCL2/OOP4xuLiIiIiIiIiIjsEyVtRETaojvuiCUjfD544onYOjPNybLgssvA64VVq+C995r3+PXhOPD//h9EItCvHxx+eLwjqr9jj439u3BhbCSViIiIiIiIiIi0CkraiIi0Nc89B1OmxJ7/618waFB84ujQAc49N/Z85kxYsiQ+cezOggWwdCm4XHD++c0zdVxj6d49Ng1dNApz58Y7GhERERERERERqSclbURE2pKvv4Yrr4w9//3vf0yaxMtRR8HgwbHkwo03gt8f33h2Ki+H//wn9vzEEyErK77xNMQxx8T+/fhjCIfjG4uIiIiIiIiIiNSLkjYiIm3F9u1w1lkQDMLpp8M998Q7otjolYsuiq3DsmYN/Pa38Y4o5q9/jU0r1rFjbP2d1mjoUEhNjZ3HrFnxjkZEREREREREROpBSRsRkbYgEoHzzoOCAujbF559FswW8icgORkuvzz2fNq0+K9vM3cuvPBC7PmFF4LbHd94GsrlgtGjY8+fey6+sYiIiIiIiIiISL20kCt2IiLSpH73O/jwQ0hKgldfjY1saUkGDoRLLok9v/RS2LEjPnH4/T8mkI4+Gg46KD5xNJYxY8CyYP58+O67eEcjIiIiIiIiIiJ7oaSNiMiBbuZMePDB2PN//hMGDIhvPLszeTL07w9bt8IVV4DjNH8Md98dm6YtKwvOOaf5j9/Y0tNj06QB/N//xTUUERERERERERHZOyVtREQOZMuX/ziC5dZb4eyz4xrOHvl8sWnJ3G547TV45pnmPf5nn8Hf/hZ7/pe/QGJi8x6/qRxzTOzf55+Hqqr4xiIiIiIirVpldYjC4up9elRWh+IdtoiISKviincAIiLSRMrL4YwzoLIyduH+/vvjHdHeDR4cS5jcfjvccENseq8+fZr+uGVlcMEFYNtw0UVw/PEwZ07TH7c59OsHubmQlwcvvgiXXRbviERERESklaoORFixoZhwxK7X/m6XSb+cTJITPU0cmUjrZVlWvEMQkRZGI21ERA5EjhMbYbNyJXTrFrtY72olefqbb46tJ1NVBb/6FVRXN+3xHAeuuQY2bICePWH69KY9XnMzTZgwIfb8iSfiG4uIiIiItHrhiL1PD2k7LNPA7TL3+HBZJuZe9rNMI96n0iwqq0OUVIQxPCmUVIQ1ck1EarSSK3giIrJPHngAXn0VPJ7YmjYdO8Y7ovqzLPjPf2DIEPj++1hC5V//AqOJvrg//zz8v//343FTU6GkpGmOFS+/+hU89BDMnw/ffhsb0SQiIiIiItJILNOgS5qJFQ3scT+3K0xiJEpnX5CoXfc6plHLx+Yye7evHyiqAxFW5BWzcfNWsjo6uD17HpGmkWsibYeSNiIiB5r334ff/S72fPp0OOKI+MbTEF26wH//C8cdB889ByNHwpVXNv5xvvsulhQCuPtuOPLIxj9GS9C+fWyqvJdeio22+cc/4h2RiIiIiIgcQEzTwIoG8OevIBLe/WgQt9vCSvFSUeYnGt01KeNye0jM7Y/X46sZqeV2mU12D1+8hSNRAqEIoYgNpkamiUiMkjYiIgeSvDw477zY2iyXXQZXXBHviBru6KNj6/D89rfwm9/AIYfAUUc1Xv1btsBpp8WmYTvuOLjjjsaruyW66qpY0ub55+HBByE5Od4RiYiIiIjIASYSDhEJ7T5pYzoWdtggEgrVmbQxLYtUnwuTQM1IG8s0cAdLCZdW1i8Iw8COaBoxEWm9lLQREWmtfn6rUTAYmwarqAiGDTsw1ma57Tb44gt47TUYPx4++QQGDtz/ev1+OP10KCiAgw6Cl1+OTY92IDvmGOjdG9asia1xdPnl8Y5IRERERESkFtOyMKIBqgvWEAoEAbAsg+R2SVgJ9ZsWzPD6cGd0bsowRUSalJI2IiKtkcsFkQhs2PDjtrvugoULISMDHn0Utm3bez2mGUtgtFSGERsZMm5cLHlzwgnw2WfQs2fD6wyF4MIL4euvITMT3nor1mYHMsOIPa68Em6/PTZFmpI2IiIiIiLSQkV/MmLHsQzsiAcnWr850oyIuylDExFpckraiIi0IFWhKgKRPS/cCGB6bBJKiwh8vxA7EMD9zfekPPssABXn/wpz2XckrV699wOmpMRGX7RkSUmxxMrYsbBkSSyB8+GHkJu773VVVcVGI733Hrjd8MorLf/899dPE3zHHRc776+/hrffjk05V1+pqQd+cktEREREREREJM6UtBERaUECkQDrStYRtiN73M9HFl0Dvdm8bSV2QQGHPvsGAJtGHMLmdg49K0tJSqzHdF9eb2OE3fQyM2H2bBg1Ctati03/9tJLcOyx9a+juDg2xdqXX0JCAsycGUsEHegsCyorYdmy2BR6Q4bA/Pnw0ENw8cX1q8PrhREjlLQREREREREREWliZrwDEBGR2sJ2hIgd3uvDxiYSCtLn1Tm4gmHKurZn3ZiBe034tFqdO8OcOXDYYbF1e8aNiyUeotE9l3MceOONWLkvv4wlHj78EE4+uVnCbjGCwdhj1KjYz198AWVlP27f20NERERERERERJqckjYiIq1Yt9lfkLq5iLDPw4pfjsSxDvCP9exs+PRTmDgRbBtuvRUGDICnn941sRCNxqYBO+00OP10yMuD7t1j5UeMiEv4LULfvtCxIwQCsGBBvKMREREREREREZGf0PRoIiKtlHfel2TO+xaAVaceSTAtOb4BNZeEBPjXv+CII+APf4BVq+Dyy+HWW/H27EnPtDS8Ph98/nlsJAnE1nG55Rb43e8gOZkSfwnlwfI6qzcNk5RAGba/BCfg32MoPpePJE9SI59gEzMMGD06Nj3cJ5/8OPJGRERERERERETiTkkbEZFWyFNSQfpjTwKw8fB+FPXNjnNEzcww4NprYyNunnwyNk3a5s1YixZRa9WV1FQ44QS491446KCazeXBcr7Y+AXByK7TfnktL/2rkwiWrCVSXbnbENymi54ZPVtf0gbgqKPg9ddhwwbIz4+NQBIREREREZFaDNPA7drzjBZul4lhNFNAItImKGkjItLa2Da9/t87mOUVVHbryPpjB8c7ovhJSYGbb4brroMlSwiuWcO2BQvo1L49nmOPhSFDwLLqLBqMBAlG616rJer4atYOOiAlJ8fa5uuvY9PFXXBBvCMSERERERFpUUzLItXnwiRA1HZ2u59lGriDpYRLd3/Tn+lNxEpoI7NjiMh+U9JGRKSV6fbVclLWb8JOTGTthBNxLDveIcWfxwNDhxLt14/tvXrRvn9/PImJ8Y6qZRs9Opa0+eorOOss8PniHZGIiIiIiEiLYVoWRjRAdcEaQoG6b/gDsCyD5HZJWAmeundwufB1PUhJGxGptwN8xWoRkQNLYmEpuZ98D0D5jVcTzEyLc0TSavXtCx07QjAICxbEOxoREREREZEWKRoOEQnt+WFHwjjRuh9EIvE+BRFpZZS0ERFpJYxolIPe/BwzalMyoCf+U06Id0jSmhlGbLQNxKZIExERERERERGRuNP0aCIirUT3z5aSsq2EcIKHvLOPp5NWOpT9NWIEvPYa5OVBfj507x7viERERERERGpzHJxAJaGqSiIVJTghP040ghMNY5gWpjcR05eEmZiGO71jvKMVEdlvStqIiLQCiYWlZH++BIA1Jx5OOFVz4UojSEmBIUNi06PNmwfnnx/viERERERERDDCfnxl+XirtuKpLiQUDRGqT0HThad9VxJ6DsbxaDpxEWmdlLQREWnpHIe+736FaTvs6NuN7QNy0ZLx0mhGj44lbb76Cs48E3z67RIRERERkTiwI7iL1hIomEta4frarxkGVlI6VkompjcRw3JjWG4cO4IdrMIOVBMt34EdrCZUuIFQ4QawXCSl5VKZ3gfbnRSfcxIRaQAlbUREWrjOi1aTumkHEY+LNSccHu9w5EBz0EHQsSMUFsaSN6NGxTsiERERERFpQ8xwFUnFq/GV52HaEWzAASK+DIJJnYikdKZjdjdSkxP2WI/jOEQrS4iUbCO4dQ3hos0kFK/BV7yW6ozeVLY/GExdChWRlk+fVCIiLZinopoec74FIO/owYRSE+MbkBx4DCOWqHnlFfj0UyVtRERERESkWbiCZSQWrcBXsREDB4CoJwVf3+HssJMJRGOXLS3LwDCtvdZnGAaulEw87bqReuQv2LHwIypXL8RTtY2kktV4K7dQ3mkY4cT2TXpeIiL7y4x3ACIisnu9Zi/AFQxT3qUdm4f2iXc4cqAaMQIsC/LyoKAg3tGIiIiIiMiBLFBB8qavyMx7n4SKAgwcgokdKek2ispDzsR98DE4nv2bzswwDKx23SjPGUNJ15FEXQm4wpVkFMwhafsScJzGORcRkSagkTYiIi1U+votdFhZgGMYrD5lOJjKs0sTSU2FwYNh4cLYaJvzz493RCIiIiIijc4yDUzTqPnZZZmYpoHbVf++lsdlYhh73+/nDINax7Fth6jdthIHRjREwvblULIWn2MDEEjuSlW7fkR8GQD4GtK4exFK7kxRwjhStn9PQlkeycUrsMJVlHcaBvUYwSMi0txaVdJm3rx5PPzww6xZs4Z27dpxwQUXMGnSJIw9fKC/9dZbPP744xQUFNC1a1euvPJKzjjjjFr7rF27lilTpjB//nxcLheHH344kydPJjs7u6lPSUSkTkbUptf7CwHYfFhfqjpmxDkiOeCNHh1L2nz1FZx1Fni98Y5IRERERKTRWKZBlzQTKxqo2eZ2hUmMROnsC9YrgWKYBqnJCXiCpYRLK/fp+O5ghM6+QM1xopaPzWV220jcOA4JZetJ3rEEMxoCIJSURUX7Q2qSNT8XjsKOaoOyoEFlxGRdpU2SL4LLhHZJBtnpJkme+id4HMtDeadhhBLak7p1IQkVBVgRP6Vdj8KxPI1ymiIijaXVJG2+/fZbrr76ak4++WRuuOEGFi5cyJQpU4hGo1x55ZV1lpk1axa33norEydOZPTo0XzwwQdMnjwZj8fD+PHjAdiyZQvnn38+PXr0YOrUqfj9fh555BEmTZrEm2++ic/na87TFBEBoPPCVSTtKCOc4GXD6IHxDme/VYWqCEQCu33dsBMwA2VUlBVg/3DHVV1SvalkJLSkBFbj3wUWNwcdBB07QmEhLFgAI0fGOyIRERERkUZjmgZWNIA/fwWRcCxx4HZbWCleKsr8RKN7T554E5Mxe+Ti37YJ071vfQG/P0RFURXRqIPL7SGhez9M03vAJ21c/mJSty3CHSwFIOpNxep1BOVk1GrziA355SYFm20KvsmjYIeJQ8JPanKAcK262yUa9OlgcmR3i0O7mHhce39PAmm52K4E0jZ/gce/g4yCuZRkj1XiRkRalFaTtJk2bRr9+/dnypQpAIwZM4ZIJMKMGTOYOHFincmVqVOnctJJJ3HnnXcCMHr0aMrKynj00UdrkjbTpk0jOTmZf/7znyQkxP4YdOvWjWuuuYYlS5YwbNiwZjpDEZEYd5Wf3E+/B2D90YcSSWj9Ix4CkQDrStYRtiN1vu5KTMZb2ovloWUEo8E69/G6vIzoNqLFJG0sw8R2ohRVF+3ymumxSYgE8QdKsf3Ve63L5/KRtJ9zNu8304RRo+CVV2JTpClpIyIiIiIHoEg4RCQUS9qYjoUdNoiEQvVK2rg8sXJOJIxj7lvSxo6E632cA4Fhh0nasZTEkjUYgG26qWx/MNEOfchIS4BSPwDbqgy+K3SxZLuLQHRnmwYBA4/lkO51SPM6JPosMEwiUdha4VBU/cNjQ5QvN0TxueCI7ha/ONhF1/Z7ji2UlEVJ9tGkb5yHO1hG+qbPKOk2BtBUaSLSMrSKpE0oFOKrr77i+uuvr7X9xBNP5KmnnmLhwoWM/NnFpY0bN5KXl1dnmXfffZe8vDxycnKYPXs2kyZNqknYAAwcOJB58+Y13QmJiOxB9pxvcAXDVGRlsPXQXvEOp9GE7QgRO1z3i3YYlxMlGA3uNmnT0piGSTASZEvlll2SUT6y6BrozebSPPyVpXusx2266JnRM/5JG4ARI+D112H9eigoAE0TKiIiIiIi+8hTtZXUrQuxIrHEjD+lOxUdB+G4fHgME8eBtSUmn+S72FjxY6Ik2W3Tp4PJ0P6dSQ9sxBMNYhhgWQZdOySTkvjjaJjqkMOGEptvNtl8uSFKUbXDJ+uifLo+yuhecM4xQfY0dibiS6e02ygyCubi8ReRvvlLqnNHNVWTiIjsk1aRtCkoKCAcDpObm1tre05ODgDr16/fJWmzdu1agD2WsSyLiooKunTpwj333MPbb7+N3+9n1KhR3HXXXXTq1KlpTkhEZDesLdvI/HY1AGtPGBYb/SAtWl3JqIgdxsbec6KqJUpNhcGDY2vbzJsH550X74hERERERKS1CAdI2vglvpJ1AETdiZRnDSWU9OP1tTXFBvO+h7zS2IwSpuHQNyPKoR0j9Ei3SUxJpnPvVDavhKB/94dK9Bj0z7Lon2UxYYiL1dtt3loWYdEmm0/WBPls3QpO6ediYPru64j40intehQZGz/FW7UFNi2AVCVuRCT+WkXSpqKiAoDk5ORa25OSYnclV1buuvjbzm17KlNSUgLA3/72NwYNGsTUqVMpKipi6tSpTJw4kddee43ExMR9jtdxHKqr9z4dTlvl9/tr/StNT20eH3tqd1c4jBMOww/D8ndKeONdDMehsG83Sjq3g0i0zrrtiINjO0SjUaI/28ewTKLRKMGf1V2ncBgrGiVaRywAwWhgj2vRAJiuCIlhP9VVRXVOBWYYBmE7HIs1Wvf5mBGbaDRKOBwmFKk7btNlEg6H9/j56vf7MU2TQGDPMUcjUUzHxLR3TYqZpgm2gx2xd2nbWnUYUWzHrvO89vT+/Nwe36+9vD/1so91GEceiWfhQpwvvyR02mng8YBpYoTDROpoe32+ND+1efNTm++d4zgYxgG0zpeIiEgjiNoO+SUOKwptVm+32VruoSJoUB0x8MxfheWycLtMMlJ8ZLVLpFNmIu3SEjD3ceq1liBhxwrcy1/E8JcBUJ3em4oOh4AZu/RY7Df4YIOHNSWxkTUu02FoVoQju4RJ3s/lZEzD4KCOFgd1tFi7w+Z/S2y+3xTmzWURvk7ycmrvIB0T656WLpzYgbIuR5K26Qu8pethawdIyNm/gERE9lOrSNrY9u4XpYYfLrA1oEzoh4tX7du3Z/r06TX15OTkcO655/Lmm29y7rnn7nO84XCY5cuX73O5tiYvLy/eIbQ5avNdmabZKBeZHMfZ7efOz9vdsiyyAgEi27Zh/+QieMKGDXRcsQrbNPhuaE+qysp2e7yIN5lQOERlRcUu+3lcHqp8VYTKwzh7+Sx0RSIk+/1UFBUR/VkC3DBNQlaINUVriER3P1oksbIzPXvmsG7jEqrLi3d93ZNIdmY2lRUVBMN1T33miTgkVFayLbyN6lDdSZlETyI7kndQualy98kf06S9y0Vw1Sp2N8maYRi4rDCJ24oprt5GcbiM4lAZZZEKAnaIkBPhdcOgOrwe0wnjdkxSbQ+ZUS/tbB+dIom0s31EvBHCvnCd57Wn92eXc3d5qPRWEiwN7vI75AqFSPX7Kd++nUgdNyjUxz7XkZpKl/R03KWlVHz0EVWHHoqZmIhrxw62Ve6+7fX50vzU5s1Pbb5nHo8W8BUREQlFHL7ZbPNFXoTFW2wCtWZS/nEqsEAkAsReLCzxszI/dmNxgtdF3+4ZDOnbgeyslOYLvIGMsJ+sFa+TtuUrAKKeZMqyDiOc2AGAcBQ+2+Tmq80uoo6BaTiMzjUY2iFAgtX46/v0am8yeVwS84uSeXJWPlurTP75vY9xPcIMzap7jdVgchcqOwwiZft3kLcAV24KUU/LWEtVRNqmVpG0SUmJ/ZGqqqqqtX13o2nqW2ZnuTFjxtRK/AwePJiUlBSWLVvWoHjdbje9e/duUNm2wO/3k5eXR25ubq21hKTpqM13rzJSSXmwfL/rSfWmkuyq/Vm0p3Z3bd6Mk5UFO0eE2Dbuf/8bgK1D+uLq3oW0PRwvITkFj9tDckoKLmp/8fS6vCQmJ2I4e09GmakeLK+FJ8WN7fLWes0wDEzbICGQQCS6+z8XvoQEXC4X3kQfTnTX3y+f24fb4yY5JQVf1FdnHe7EFLzJyWR5snY7ssfn8tG+fXu6JHXZbSyBQIDgqlWkLluGy7bxOyFWR7axKryVlZHYY1VkK6vCW6hmL9OWuX941CHV8dDbyWSYsZHeaYkcHM4g4Sc77+n9+TmX5SY5OZk0b/quL6alYSUk4OnQAVIa2GFrQB3GmDHwxhtkLl1Kykkngc+H0b49aV12bXt9vjQ/tXnzU5vv3Zo1a+IdgoiISFytLbL5cFWEr/KjtRI1iW7o28Gke7qDGQmS5LJJTXThy+7L1ioXFdVhtpf42VpUxZaiavzBCN+t3s53q7czZ9FGhh7Ukeys5N3ebGjbDlG78ZMf9eFsWkK3z5/BFSwFINrzKEoTuhGJxG5G21xp8uYaD0X+2DW3HmlRTukTpW8nDztKYTf3g+03wzAY1T+DLs42nvy8mtXFFu+t87Cj2uD43DB1DWSqzuiNN1iEp3wjKRu/IJRzHLDr9UYRkebQKpI23bt3x7IsNmzYUGt7fn4+AL167bpQd48ePQDYsGEDAwYMqNm+s45evXqRkZGBYRg1I25+KhqN4vPVfXFxbwzDaNC0am1NQkKC2qmZqc13tb10Owu2LSAY2d24jL3zuryM6DaCjokd63y9znZ3u2OPnSMr5s+HggJsr5eNY4ZguaxdK/oJ02VgmAaWZe2yr9vlJhwNs6VyC2F7zwkDn1VJ12BfNlcU4K8srf2ay0vHxI5YloVj7H7Ezp5igdjIItMw91iP6Yq97na7sc2693Fbbtxu9y5t6TgOWyq3sLpoNd9v/p7Fqz5jQ+FSVkW2sCFajEPdHRiXY5JFIplOAu2cBNLx4sNFckIaHboPoGj9UvyhSoJEKSHADsPPDqOazVRSboRYZGxlUWQruMFyGRzstGes3Z2xdney99ImtdrHtLAsC29dd6i73WBZuH76u7KvGlLH6NHw1luYeXl4CwuhVy9wu/Hs4fNDny/NT23e/NTmu6ep0UREJN4MA9yu3a8J6naZdV6s3x+RqMMXG6LMXhVhXdGP/Y52iQYjci2Gd7fIzTAwTYOK6hCbtkeJRh08CRZduqaQHYgQtV1AApBJ1HZYubGSr1eXsrygkrwt5eRtKSe7vY8ThnbkoK5Ju/zNjVo+NpfZzZq4McPVZKx6CzZ+hQsI+dpRdMh5tOvWDdZ+T9QOMW+jm883uXAwSHI7nNQjRN/MKF7PnvtHjSk9weDc/iE+zbeYW+BhwVY3RX6TM/oG8f38iqhhUNX1cDyhMqxABWlbviaQemKzxSoi8lOtImnj9XoZNmwY77//PpdddlnNH6hZs2aRkpLCoEGDdimTk5NDt27dmDVrFieffHLN9tmzZ5Obm0u3bt0AOPzww5k9ezY333xzzZQOX3zxBdXV1QwbNqwZzk5E4i0YCRKMNjxps98iEXj9dQACx40hkuSDRli8PmxHiOylnogdxsauc99Y5yG+HMchGA1SEawgEAkQtsNUhapYV7KOdaXrWFeyjvUl6/FHdr/ORIaRSH9XZ/q5OtHPlUU/Vyeywj4CpTvA3vXWLp83i+weJ1KQ/yaBaMkurweJssEoI9+qYrW7nLmRNWwxKvne2M735namsZBB1V24aKPNMCfE7ruNLVhqKgweDIsWwaefxpI2IiIiIiJxEvVXYgf3vHawOxihsy+w2+SFZZkkuU3KG+FGg0DYYe7aCO+uiFJcHTuey4Th3S2O7WPRt4OJuYfjmJaFEQ1QXbCGUKB2XzQbyM6FYI7Fgi0Wn6yNUrAjwNOz8+mdaXNSb5vMHwb+utweErr3wzS9zZa0Sdq+hKyV/8MVqgAMyrqPprDHSbi8CUCQbZXw6nIfhdWxntCAdhFO6BEicTezGDQ1w4CR3SK0T3B4Y42H9WUWzy/1cf6AwK4xWR44aCzO9+/grdqKvX0F9Okbl7hFpG2L/xW5errmmmu49NJLueGGGzjrrLP45ptvePrpp7nllltISEigsrKSNWvW0L17dzIzMwG49tprueOOO0hPT+fYY4/lww8/5N133+Xhhx+uqffmm2/moosu4oorrmDSpEkUFRXxt7/9jUMPPZRjjz02XqcrIm3J55/Djh2Qmop/zEiozGuyQzk4lBBgm1FFIdX4Q9uw8srZGPmGgFVNFAcHhygOlmHhCyVQYVaC4WBi1DysH/41MPAEk8lYW0hldDW2GdhlPw9uksIbKDJKiJgRoj/UbxsOIaIEiBCKGoS+W0KhU0kgEsAf8VMZqqQiWEG4Hgks0zDJScuhb2Zfcu1MBpW6GGhl0c/qRHtz16kEiuwiVlJMhH0fj+/Foq+TyaF0pbO3M/nBAvLtYj43NzHHzGexuZ3vo5u5bfkjJOLmeCuHX9p96eW0sjmRR4+OJW2++grOOy/W29kNy2q+u+VEREREpO2xg9UENq2M3fC2G35/iIqiKqLRupMX3sRkUnJzqGNZ5HqrDDq88uV25iwOUv1DNyU9AU7o6+Lo3i7SfPuWEIqGQ0TqmP0FIMFt8YuDvAzKCPBZgYsFW12sKTZ5/GuD4V0ijOwapjknbbVClXRY9Sqphd8CEE7qiHvs5RRHOuBEbGzb4aPvdjBrkYXtGCS4HE7qGaJ/uyaaA20fHdQuykW+AP/9IaH0n6U+zj84QNLPEzdJmVRlHUry1m/wbVqIXTkqLvGKSNvWapI2I0aMYNq0aTz22GNce+21ZGVlcfvttzNp0iQAli5dysSJE7n//vs588wzATjzzDMJhUI888wzzJw5k+zsbB544AFOOeWUmnqHDBnCc889x8MPP8z111+Pz+fj+OOP57e//a0uQolI0wuH4e23Y89PPhm8HmjYevN12kg535qFrDSKWWUUs94oJWj85EtzEFj9w/O6PvIisNehIiFgXWzRyd3+VQnvpv6dHGDryt2+7DbdpHpT6ZLShW6p3eie1p3s1Gxy0nLontadLildcFtuopEong1b8X71BWYoBJEQxRTXqsswDEKNMJLpp7qQwq/sfvzK7kch1cxN2cE71jrWVW/iDWsNb1hrGGZ3YkJ0AMOcThi0gmmE+vWD9u1jCcUFC+D44+Fn05QCuMJhsgIBXJs3x6Zi25vUVMhoZQksEREREWmwffnmu8frMJEITnT33+PtSJhIKLTbpI3LU3dypD5KAwZfbHaxeLtDxC4CoHOKwfgBLkb1sHBbTff9PtkDx+eGGZIVYfb62EiRzze5WbbDYnxfh8FNPSjecUjZ9g0dVr+GK1yFY5iUdD+a6n6nkJ2VCZvKKCkP8OGCArYVVwMGfTMinNQzRHIdM0DHU6ckhwsODvDCUi/b/SbPL/VxwYDALnEGMnrhKSvA499B6OtXofOR8QlYRNqsVpO0ARg3bhzjxo2r87Xhw4ezcuWuF/wmTJjAhAkT9ljv0KFD+fcPC4CLiDSruXOhtDR2EXv0aAiX71d1Dg7fs40nQ0t4z1pGgWvX+gwH2pNARyeJTE8anTr0wNhWiBkO14yesTDwmG7SPKmUBsqIEsX+YYSMg1Pz3MbB9CWQmNWNss3rCYcD2D9s3/kwTYskVyKBsB8cp2aUjomBB4sEXCS4E0npO5Ain41pmHhdXlI9qaR4U0j2JOO1vKR50xjQYQDLdiyrWYMo6kRZX7qe9aXrATAdkx4lJlbxWpxg3VOm7Vyrp6l0JJGLPIdzx/Df8fqcGbwUXMQnZgELzK0sMLfS287gkuhARjndWnbyxjRhzBh45RX44AO47jpYtgyCtadvcMJhItu24WRl7T1p4/XCiBFK2oiIiIi0EZZpELFtCov3PLUZQDgcxvCkUFIRxiZEcmL8r/iXBQ0+2+jm++2x0SMAPbN8nNgrylE5FmZjL5KzB+0SHCb0D7Kq2GJ2npvSoMl/FsPy6k0MG5iNey9raTaEp2obHVe9QmLJGgCCyZ3Z2u9cgqnZJFoubMdh0cpCPvtuM1HbwecxOalnmP7poT0N1I+r9gkOFx4c5D/LvBT5Tf6zzMdFB/9sqjTDoLzTMNpt+AC7cB0eTzuCSTlxi1lE2p5WlbQRETmgBALw3nux5+PHxy54N3AASBVhZpvreN1czXqzLDZCxgCXY3KI055+TjsOcjLpY2fSiSTcPwx78aVlkX3IiRQUvUkgUHv9lgQjgc7uzuT7C/a4No7Pl0V2/xMpKNy1jpp6fphGbHf1uLzJ+HJOYrGvbK/rC+1pDSLTNglH3RCNYO/mWM21Vo9hGBxmduPgaBJbopXMtFbylrmGNWYJvzc/oa+dySXRgYwht1niaZCRI+GNN2D9eliyJDYy7GdJG0Ih7Orq2O+zbccnThERERFpkUzTIBCKUrCtlHBkz98Vw6EQ2wq30a2LycA+WXFN2pQFDT7f5OK7QldNsiY3LcoxvV0cdUQOzo4NzZqw2ckwYtN85aZHmZvvZsFWF4vWlrGsoJKRh3bhoO6Nc3OUGfaTueEDMgo+wXBsbNNFcc7xFOccA2asP1VUFmDmx2tYt6kMgO6dUrhobCesrcuJNHxQU7PITHC46OAg/14aS9y8vMLLeQOCeH6SuIl6kgl0GUrCxvkkbP6Gqtz22O6k+AUtIm2KkjYiIvHywQdQUQEdOsBRRzWoikonyHPW97xkLsdvxOZ39jkuxrv6MyTUjqHRjiQRpxUfpUZnkrkuehgTo4fwkrWc/5krWWUWc6c5l37OEu4Kw7nOiF3W3om75GQYNgy+/BL++1/4YfpREREREZF9EY7Ye03ahCI2gVCEcCR+a6BUBA0+2+Ti258la0Z3C5OdauNLdmMYBnVPwNZ8vBac0CPMoM4G7+YlsaUkyIdfF7ByQwnHHZ7d4HqNaJj0gk/J3PAhViQ2c0Fl+4Mp7HM6kYR2AERth29WFrJg+TaitoPbZXLUoC4M7tOe9KQQFY1yhk0v3RcbufTvJT42VVq8tsrLeYfUXjMp1LE/SYFt2Ds2kFL4HWVdG9ZvFxHZV0raiIjEQ1kZvPNO7Pmpp8I+rqEVdCI8nvcyj4b/TbkVG/mQ46RyerQvp5v96evNjY1saejQHWkSqXi5PDqYX0X78V9rOa+YK1lhFHFe9bM8Ev6Ev6acwdHeg+IdZm1jx8aSNrNmwQkn1G/dGhERERGRViQchc83uvhik5uwHUvW5KRGGZ0dpntqyx1N3i0Vbji9J29+U8aXi7ewsbCSf7+7gi07qrj01IPrPVrJDgVwr51H7sq5uIOxkTPBpCx29DqNqvb9AXAch/xtFXz+/RaKywMA9M/NZMTAziR4XS3vBrR66JDocE7/IC8s87Km1OLN1XDJsJ/sYBh4hp2O/71p+Co346/aRigpK27xikjboaSNiEg8PP00VFdD585wxBH7VPQ7YxsPVb/DhtWxqci6O6lcHjmUMU42BgYJprcpIpZGlI6Pq6JDOCfan/+6VvCauYqvwus5pngqp3oH8mDKWfR3d453mDE9ekBODmzYAPPmwTHHxDsiEREREZFG890WmLnES1nQBKBbSpSx2WFy0lpusuanLNPg8P5Z9OicyiffbiJ/awWzv8rni8VbOef4PpwwPIdEX903XkXKiyhfNJuyBe/iC1bFtvnSKel1MpVdhoFh4gYKS6qZ9+1m8rfFxtH4PBbjjujOCUfmkL+1gnDExu0yicOMcfutW4rNGX1C/G+lh2+3WXy0Fg5t/+PrZloWwQ4H4du+gpTCbynKHQeGGb+ARaRNUNJGRKS5bd8eS9oA/OIXsQXf66GSEDOsb3jTWgM2dPRkclV0CEf7O+JCXxpbowx83OAM587kU3k4NIdnQ1/zVnAx7waXcqFnGJOtM8mN9MIfKMX2733xVp/LR5KnkedZNgwYNw6eego+/jg28qaev7MiIiIiIi1VdRheX+Ni6XYAk1SPzbE5Yfq3i7Kvg0acaBg76McOVuNEQjh2FKJRHMfBME0wLeywg+W3cQwP2AmNfj5pyV5OG9WTTdsrmb9sK5u3V/H0G0t5cfZKTjwyl/GjetAxIxE76Kdq9ddUfv8x/vWLYedkb8ntiPQchZ0zjDTLTbIdYll+BZ8tL2btllhfxDINRg7I4LhDO5CW5CYpWk5nX5Co7WBZJkluk/JWOOKmT2aUE3qEmbXew5srIKG/Sa/0H6fpC3QaiLt4Pa5QBYklq6nObGGzI4jIAUdJGxGR5vbgg1BVFRu9MGRIvYosNXbwJ9c8thqxu59Odw/kr0fdTfnnHxOgpCmjlSZmGibptoerAwM53u7M4+ZCPjULeDY0n5c2fsN1nmX8siQl9juzB27TRc+Mno2ftAEYORJefBG2bYMVK2DAgMY/hoiIiIhIM1ldYvLOWi9VYQPTgBFdwxzVJYx7b7NWOzbR4k1EC5ZQ4S8mWllKtLIEJxys13EzfvK8eomXFMNDounBdicQdSUQdSdiuxKJuhMxjGRw6je92U/ldk7llKNyWby2iFc+XkPh9lIWfvoFpV++xtDkQro6WzCdHxMSvu4D8B00gsLyIAVFUfK/WsH6EoO1JQaVoVgCxsDh4I4Ox+TaZCQUEt1YSIXbwkrxUlHmJxp18CYmk5Kb02rv7zqsU4SigMWCLRavrvIw8eAA3ZN/eNHyUNlhIGlbF5C0YzmB1O7YrsZPvImI7KSkjYhIc9q8GaZPjz0/80z2dguXjcOL5jKesr4jajh0cZL5beRIjkwZRJo7mfJmCFmaR9iO0NVO4l57DN8ZhTxuLWK5WcSUdc/xL5K4ikM53s7FIA53rvl8cNpp8P/+H8ydq6SNiEgLNm/ePB5++GHWrFlDu3btuOCCC5g0adIe1xp46623ePzxxykoKKBr165ceeWVnHHGGbX2Wbt2LVOmTGH+/Pm4XC4OP/xwJk+eTHZ2wxe8FhFpbrbt8P5ag3kbfAC0T7S5eKhJIhGi0brLmJEA3srNeCs34/EXEbB3s26oaWF6EzHcXgzTwjAtMAwc2wYnSjQcJhL0Y0aCGDgQDmIRxAII7CZg0yLDlUDElYjtSsC2PNiWF8fy4JguTLcXY6uHxIBJNBzCtCN4IpVEtoQ5NFxO/4wCQtFNseMB/DDj2/ZoCguCPfkm2pvo+nZULQvhD5nwsxkcElwOQ7IiDMmKkOaN1REJ/RCaY2GHDSKhENGog8sTqtd70JKd3CtCWchidZHByyu9XJPh1LwWSM0hoXQdnkAxyduXUN758DhGKiIHOiVtRESa0333QSAAhx0GgwZBaPdfbCsI8ifXZ8w3twBwbDSHW6PDSUILwR/oDnU68njkRD5LLeP/jIXk+7dyr+tzXrVXcX10GP2cdrsp2YQJnXPOiSVtvvsOioshM7PpjiUiIg3y7bffcvXVV3PyySdzww03sHDhQqZMmUI0GuXKK6+ss8ysWbO49dZbmThxIqNHj+aDDz5g8uTJeDwexo8fD8CWLVs4//zz6dGjB1OnTsXv9/PII48wadIk3nzzTXw+X3OepohIgwTCDtPf28TiDbHExOGdw5zQy6ZjupcdpT/b2Y7iqyggoWwDbv/22t+y3V7M1I540zvgSs7ASs7ATEjBcLn3mCCvqA6xfXsl0YiNL8FDVpcstq9eSrS6AjPixwpXY0X8mOHq2PNoAOwoVqgSK1S5+xPL/5Ssn20K//CAWA/BSkrD7NCTLd5cviztwDeboTgYwHaAsh8zRgYOnZJsctNsctKidE+1cbXSkTMNYZlw6WEw5RObkoDJ/5Y43Nbvh8SNYVDR8VDa5X+Mr3wD1Zl9iXjT4huwiBywlLQREWkuGzbAE0/Ent9yyx4TNuuNUn7nmssmoxKvY3FDdBin2L3iM8pC4sLA4Hj3QZx3+NVMmfsX/hVZwFJzB1cb73GS3ZMrooNpx49D8i3DxHaiFFUX1arH9NgkRIL1XhcHdrM2Ts+e0L8/LF8On34Kp5++3+coIiKNa9q0afTv358pU6YAMGbMGCKRCDNmzGDixIl1JlemTp3KSSedxJ133gnA6NGjKSsr49FHH61J2kybNo3k5GT++c9/kpAQ+9vTrVs3rrnmGpYsWcKwYcOa6QxFRBqmNGDw0vcOO6qqcJkOp/QMcUiHKG6z9nxoZriKxJK1JJTlYdo/9tfCvgwCyV2hQw+yBg7HKconydPAvplhgMuLmdqBaHJHglbdF/49FmT4opQWlWAEqzAjfsxoEDMawoyGwIli4mB5vIQcF7Zh4ZguHG8yGVmdSO2YhTujE56snljJ6RiGQTZwxA/1R6I2RWUByiqDmP4Sylcvwl8dxGyt85s1kiQPnN0/xDPfeVlTZPDmgiIO/+EtiiS0I5DcFV/lJpK3L6a026j4BisiBywlbUREmsuf/gThMBx3HBx1FMyZU+dunxgb+JP1KX4jQicnib9ExtLbyahzXznw+SwPl1jDOM7fmSesb5ltreddax1zzXwmRgfyK/sg3FiYhkkwEmRL5RbCduTH8mTRNdCbzaV5+CtL93q8Pa6Nc8wxsaTNvHkwfjy49DVCRKSlCIVCfPXVV1x//fW1tp944ok89dRTLFy4kJEjR9Z6bePGjeTl5dVZ5t133yUvL4+cnBxmz57NpEmTahI2AAMHDmTevHlNd0IiIo2k2G/wwjIv5SFIT3JxTv8g7d2150Izw34Sty8joXR9zVRiUVci1ek9CaRmY7tj3419ickYpomzy1GagGmBL5FIkouor32du7g8HlJ6DWJLtZdwJDb3mdtl0qlXe9IyE/dYvcsyycpMJCszkeodfqIbIOhv9LNolbKSYom9N9Z4eWthEWmDIOeH7lFlh0Ni0+VVbcVdvZ1wYof4BisiByRdbRERaQ6rVsGzz8ae//nPde7iOA6PBefyJ+tjAIbYWdwdGUU6mnJEoAOJ/C56FKfbfZhmLWSFWcQM1zfMstdxS/QIjiAHiK2NE/nJPNsRO4yNvcv2Bhk6FFJTobwcvv0WdGe1iEiLUVBQQDgcJjc3t9b2nJzY34f169fvkrRZu3YtwB7LWJZFRUUFXbp04Z577uHtt9/G7/czatQo7rrrLjp16tTgmB3Hobq6fqNA2yK/31/rX2k+avvdC4fDhEMhQj8kCPbGbdrYUbteZcLh2HfVcCRCOByu/fkQiRAKh3Aiu/8+G41GiUaiROwfUypFfpMXV/ioCpu0T4Rbz8imOn8VgUAsaeOyQzjrvydj60oMJxZfMKE9lem9CSR2+nEN0h8WvIlEbRzbwY46hEL79t36p/FFoja27RCN2ER2s5iOZTg4tmeXc6pdqU00Gq3dvra5a/vtRSQS+aG6KE49U1I/j68+51Sf86qzHscgGo0S2sNsFT9lmi5M28aOOntuvz3E1i8zwuauXhZsgpnLTC4+2CbN6xCxEqlKyyW5bD3Jhd+zvdtYcMw9xme4HKxIhPDP3pNwOEz4h7bf+fu/Rw14b6Vu+pyPn7bc9o7j7HEazZ9S0kZEpDncc0/si/748TBiRGyqtJ8IO1F+XfYCTwVid6yeEe3LddHDcNG2h6bLrg5xOvB45ERmmet43PqG9WYZ15nvc4bTjz85pzbtwV0uGD0a3n4b5s5V0kZEpAWpqKgAIDk5udb2pKTYrcGVlbuuh7Bz257KlJSUAPC3v/2NQYMGMXXqVIqKipg6dSoTJ07ktddeIzFxz3dz7044HGb58uUNKtuW5OXlxTuENkttX5tlWRieFLYVbiMQiuy9AJCW7KNjhpfC7dvxB+t3wb24uIgdRW62b6kgGo1iWRbtfCYVhYVEQ8E6y5imiWF5Ka8orxlxUhx08VZBB/xRk0xPmDP7Bkn2OGyrrKC6sorUYCFpVWsw7FidVe40tif2pNqTARFiNyr9TNiBcDiE319FaXUZtl2/5NXP49tZT0VlBdVVdV+AT/C6SElyUV5RQThSdxLE7fVhVlayrTBY8574PC46Zxg17bc3lmXRPjF2ebCqqqqm/fbm5/HV55zqc1511eN2maQlQkVZsF5t7klKpX1qFlX+qlq/E/t6Tkd1gh2h9uRtD/LqSje/6L4dy4BKV1f6kI8nWIK9fQ3lSZ32GJ/l8ZKSvIOiQGHNe7Lz/1NxcWx66x1FO/Ya376+t7J3+pyPn7ba9h6Pp177KWkjItLEjKVLYwu4Q52jbErtas4ueYIPQssxMbg+egRnRHs3c5TSmpgYnGz34ii7GzOsb3jHWsurxgo+9RdwnXEYR9Ot6dY/Gj0a3n03Nnps82ZoX/dUDSIi0rz2dhGrrjUK6lNm513D7du3Z/r06TX15OTkcO655/Lmm29y7rnnNihmt9tN7976zrM7fr+fvLw8cnNza01NJ01Pbb97JRVhsjo69R5pk+RzkZiQSMcOHeo10mZH0Q4yM9vRvl17MlI6//hidSmJlR33ONKmOhgltRoitkNFyOC99Yn4oyYdE6Occ1CQzIxk3G4PaR6TTlVL8fkLAXB8KZS2G0i1ryNuw2BPS8v7klNwuz2YCUl4k731aoO64ttZT0pyCm6Xu879vS4Tj9tDakrKbkeKuDxekpOTyXLSa9rX4zJ3bb+9iJTvoIpY0t6p542DP4+vPudUn/Oqqx6XaZCcnEyid0/vzo9MXyK+hASSEpJITUmt90ibus7pynFd+NNL6ygMeFlc0YGx2bG/i5V2H1JLVtDJn0dxVu89xme43CS0b0+7xPRa20sqwmRmhtm8dRvt27XH7d59u0HD3lupmz7n46ctt/2aNWvqvW+TJm22bdtGVlZWUx5CRKTFc997LzgO/OpXMGRIrdfyIjsYXzKdZZEtJBlenkw4l5xykwj7OY2VtAlpePlt9EhOtHvwsOtr8owy7rY+YZjRiVsiR9CFlMY/aEYGDBoUmx5t7lw466zGP4aISBvSWH2mlJTYZ35VVVWt7bsbTVPfMjvLjRkzplbiZ/DgwaSkpLBs2bIGx2wYRoNH6bQlCQkJaqc4UdvvqjJQjdvjAbOe06N5XJiWuW9lXC7cbnettg+HKom6PTjm7m9MCkZCWC6LQNDhf6t8VIRM2iXYnD8gSKLbxGWZ2AXfk77mXQw7jGOYBDoMIKHnoUTLQ7iie7+w77JMDNPAtIx63y398/iIOrgsE9M0sFwmLsuqc3/LZWGYRk2Z3cVjWVat9nW7zF3ab2+qq2OXBy3TAqN+SZufx1efc6rPedVVj2UZWJZV7zY3XR4s08S09tx+9TmnDmkeTu9n898lFl9t8dAz3aFHuk2g/UEkl6/DHa4ksWoTlpWx2/gMyx37vf7Ze1IZqMb9wzqhbrd7r+fXkPdW9kyf8/HTFtu+vlOjAU07784xxxzD5ZdfzjvvvFPveSdFRA4kicuW4XrjjdhcyPfcU+u1r4JrGV70V5ZFttDFTGdeu9s4wd0vTpFKazbYyeJ550xudR+NxzFZYG5lkvsdXjdX4ThNsEzq2LGxf7/8EoJ1T1EhIiL101h9pu7du2NZFht+NgVrfn4+AL169dqlTI8ePQB2KbPz5169epGdnY1hGHXGFo1G8fm09p6ItBxRG2au9LK92iTJ7XBuvyCJbjDsMAnrPyH05UsYdpiQL5Oi3HEEOh4M5u4TDCIAAzrCkKwwYPDGGi+VIXBMN1UZBwGQuH0ZTj2nyhMRqY8mTdrcf//92LbNrbfeyqhRo7jnnntYvHhxUx5SRKRF6TJjRuzJhRfCgAE121/Oe5ujt/6VQruCwa5s5refzGB3dpyilAOBB4sb3KN5LvpLBtsd8RsRprq+5gb/K2wKFDbuwfr1g44dIRDAXLCgcesWEWljGqvP5PV6GTZsGO+//36thP2sWbNISUlh0KBBu5TJycmhW7duzJo1q9b22bNnk5ubS7du3UhKSuLwww9n9uzZtRI3X3zxBdXV1QzT+mYi0oK8s9bNhnILj+lwbv8A6T4HK1RB5oaP8RSvA8MgkDWQku5HE/U0wah0OWAdnxOmQ4JNVdjgrTVeHAeqM3phW16scBX2tvpPeyQisjdNmrQ5/fTTeeaZZ/j444+ZNGkSX375JWeffTannnoqzzzzDDt27H2RLRGR1sr8/HPSPv8cx+WCu+4CwHZs/vjxHzlnzrUEnDDjvQP5tN2tdLUy4hytHCiySeXhyPH8JnIYHsfiq+gGjv/iGubYaxvvIKZZM9rG+uST2PR/IiLSII3ZZ7rmmmv47rvvuOGGG5g7dy6PPPIITz/9NFdddRUJCQlUVlby7bffUlxcXFPm2muv5d133+Xuu+/mk08+4a677uLdd9/lhhtuqNnn5ptvprCwkCuuuIK5c+fyyiuvcMstt3DooYdy7LHHNmp7iIg01BcbbL7d5sLA4Yy+QTolOXgqt5C54SNcoXJsdyLeY68g0HlQvacAE9nJbcEv+wZxmQ7ryiy+2uIC00VVZmy0TWTDdzh2NM5RisiBoln+SmVlZXH11Vfz7rvvMnPmTDIyMpgyZQpHH300v/nNb/juu++aIwwRkebjOLj/9CcAIhMnQq9eVIYq+dVLv+LPn/wZgFtST+L1jF+TbGpaEWlcJga/svvxdPgUBphZlEUq+W3kXR625hOkkToSI0aA2425eTPeTZsap04RkTasMfpMI0aMYNq0aaxfv55rr72WN998k9tvv50rrrgCgKVLl3LuuecyZ86cmjJnnnkm99xzD59//jnXXnstX3/9NQ888ACnnHJKzT5Dhgzhueeew7Ztrr/+eh544AGOOeYYnnrqKaw9rFsgIi1XZXWIwuLqfXpsL6kmFG6ZF6U3ltn8v+9iNxKNzg7TK8MmsXgV6Zs+w7TDhHztqOx/Klb7nDhHKq1Zh0SHcbmxUadz8t1srjCpTu+J7fJBsJLAxpVxjlBEDhSu5jrQggULeP3113n//fcpLy9n5MiRHH300cyZM4fzzjuP22+/nUsuuaS5whERaVoffoj16afYbjeR3/6WTaV5nP7i6Xy/7Xs8locnRtzHxRvbaz0QaVLdSeWJxAn8p91mHt/wMq9Zq1li7OBPkdF0ZT+ng0hKgsMPh88/J3nRothzERHZL43RZxo3bhzjxo2r87Xhw4ezcuWuF5QmTJjAhAkT9ljv0KFD+fe//13vcxGRlq06EGHFhmLCkfqvw5HgddG5fVITRtUwwYjDtE9DhKLQIz3KUV3CJBd+T1LJagCq03pQkTUEn7ttLXgtTWNwxyjryyKsKHLx2moPkwbZVLfvR/LWb/GvXYSv20EYWidJRPZTkyZtNmzYwOuvv84bb7zBpk2b6Nq1KxdddBFnnnkmnTt3BuDCCy/k1ltv5fHHH1fSRkQODLYNkycDsP2ss/jOyeOCJy9gR/UOspKyePXcVxlhd4GNc+Ibp7QJbsPiD30vp9+mAHeFZ7PGLOEq93v8MTKSI5wu+1f52LHw+eckLV9OqKIC2rVrnKBFRNoQ9ZlEJF7CEXufkjZuV8tcaP25BWE2ljmkeuGXffxkbJ2Pr2IjABUdBlKd0RcMI85RyoHCMOCUniG2VJqUBk1mrfdwZt+eJBevxA5UEdy0Cl92/3iHKSKtXJMmbU488US8Xi/HH388f/7znxkxYkSd+/Xs2ZO8vLymDEVEpPm8+CIsXIiTksLTJ2Rx10vjidgRhnYeymvnvkZ2WjZs2BDvKKWNOdLM4enwKfzB9SnLzB3c7vqYK6KDOd8egEEDO7G5udjdu2Pm52N9+SWMH9+4QYuItAHqM4mINNy89RHmrI1iGHD5YTadCz7DU7UNB4PyzocTSO0e7xDlAORzwS/7hHhuiZelO1wc1M7DsdkDia6dT/Xab/F2PQjD1LpJItJwTfoJ8oc//IF58+bx0EMP7bbzAfDrX/+a//3vf00ZiohI8wgG4c47AXhpfA9+l/8oETvCOQefw6eXfhpL2IjESXsSeTRyPKdGe+MY8ITrW+6zviC8H+vcREePBsD67LPYKDMREdkn6jOJiDTM5jKbZ+aHAThrgEPulg/wVG3DNixKu41SwkaaVNcUm5HdIgC8s9ZNRXofDLcP219OcMuaOEcnIq1dkyZtZs2aRWFhYZ2vrVixgtNOO60pDy8i0vz+/nfYsIFtaS4u7fk9JiZ3j76bF896kUTNoSwtgAeL26LDuSVyBJZjMNtaz+2uj6kg1KD67KFDifp8GEVFsHRpI0crInLgU59JRGTfhSIOj80LEYzE1hg5xv8+TtlWbNNFabfRhJKy4h2itAEju4bpnBQlEDH493cWCbkDAfCv/QbHceIcnYi0Zo0+PdqCBQtqPpjmz5/P119/TXFx8S77ffzxxxQUFDT24UVE4sYpLiZ4zx/wAXeMjZCW0Yk/DfoTFxx5AYbmUJYW5hd2Hzo5SfzR9SmLzG38xjWbByPH0IX0favI46Fq0CBS58+HuXNh4MAmiVdE5ECiPpOIyP55bmGYglKHDr4wlyZ+RKR0G1geyrNHEfZmxjs8aSMsE07rE+KZ730sKzT4vFs/hri+I1pVSmjberydejb6MXVlQaRtaPSkzcsvv8zrr7+OYRgYhsE999yzyz47OyinnnpqYx9eRKTJuUwXlmHV/Oy1vBRWFbLg8rGcVV7N9x1hy1nj+OLkJyjdVBq/QEX24ginC9Mi45jsmsN6s4zr3LN5LHoSB+1jV6DqsMNiSZslS2DHDmjfvokiFhE5MKjPJCLScJ/nRfh4TRQ3UW7rOBfKt2G4PLgGnUgk4IOoRjhI82mf4HB8bpj31nn4z3cGAw8+BGvjIqrXLMKT1aNRb+C0TIOIbVNYXL1P5RJ9LpITPY0Wh4g0vUZP2vz+97/nrLPOwnEcLr74Yv74xz/Su3fvWvuYpklqaip9+vRp7MOLiDQpl+miv6sz3qpgzbb3t37Gw89czrzZVQCsu/5C3h7zJyJlEbyBAK7Nm8Ht/rES0wS/v7lDF6lTHyeTx8Mncov7I/KNcq613uW1SDf6Vf/Y2TU9NgmRIP5AKba/dgchGo3iz0ol1KcXntVr8X80m+pTTwTA5/KR5Elq1vMREWkN1GcSkbbCNA1M08Dtqsfs/LaJz+PC7TLZ3XXuLeU2T38VxsRmcpdP8FZuxrDcpB4+noAnHQKVjRq/SH0M6xwlvxKWFcJTG/twlfU90Yoiwtvz8XTMabTjmKZBIBSlYFsp4Uj91hN1u0z65WQqaSPSyjR60iYlJYUjjjgCgOeee46DDz6YpCRdsBGRA4NlWHirgkQ++5RifxEP2fP4wF7Le2+C24aKQ/vzy27Hw9xPcMJhItu24WRl1U7apKTAzy7MiMRTR5J4NHw8t7g+Yp1ZyulVT/GofSI97DQAfGTRNdCbzaV5+CtLa5WNRqNUlJcTGNiNAavX4vriS1Yd3h2Xx0vPjJ5K2oiI1EF9JhFpCyzTICsJEiNldPYFidp7HgET9UbJMLykJYVxB0sJl/6QgDEM7EiIUHTnOjYO17WbR/tAAZgWqYedhDu9I4Hqhq3RKLK/DAMuGmpy70c2y4q95HfvT/fKxVSvWYS7Q/dGn9IsHLHrnbQRkdap0ZM2r732GmPHjiUjI4PNmzezefPmPe7/y1/+srFDEBFpcp9Vr+C+6MfsMPycvhJOXAuOy0XK2RdA8IdROKEQdnU1BAJg/+QLldcbn6BF9iCTBB6JHM9v3XNYbuzg18Y7POocT08nnYgdxsYmbEeI2OFa5aLRKKFIiMKeWfRKScBb4Sd9+TpKBurOcBGR3VGfSUTaAtM0MKMB/BvXU1FUTnQv05ZFojbl5eWY6WmkVaZgJcRGBhheH+6Mzvz76wD5JQ7npCykt5MHhknq0BNwt+vSDGcjsmcZCQaXHu5m+mdhntrYj3sylhEpKyRctAlvVo94hycirUyjJ20mT57MSy+9REZGBpMnT97jvoZhqAMiIq1KIBLgvqUvMNOeDQb0Difz3Hs2UI0xbhx06BDvEEUaLA0vf3dO4RbrQ76xN3GL60OmhcfRm6y9lnVMky2De5P76WI6L1qtpI2IyB6ozyQibYkdCRMJheqRtIkSDgaIhHzYER9ONDY+wYi4+Wx5CR+uCjPWu5yR7mUAJA86Gk+H7k0ev0h9jch1sWiTzed5CSyM9GGYtQL/2m+UtBGRfdboSZsPP/yQDj9ctPzwww8bu3oRkbhZVbSK5757ju3V2wE4M3oQD3zqJrV0CdG0VKyTTopzhCL7LxkPz3nP44zqp1ljlHCT+0OesLPIrkfZrYN7kzNvCekFhSRsL4F2TR6uiEirpD6TiEj9bS2PMmPWRga58zkj6WsAEvsega+LbhKSlueSYW6Wb4vyZsXBDE1fRbh4M+HiLfhyDo53aCLSijR60qZr1651Pt8pEolQWVlJenp6Yx9aRKRJhKIhXl/5Oh+u+xAHh06+DtwZGs6RWwx6fvY2ANW/OJkUny/OkYo0jnQjgUeiJ/Br613yjXKuq36Zd0Lj9loulJJIUZ9utF9VQKdFq6Df8GaIVkSk9VGfSUSkfkJRh0c/rqBjdBsXp32KAfiy+5PQc3C8QxOpU5LX4PLhHqbMgS8DvTjKt5rq1QtIGXJ8vEMTkVbEbMrKI5EI06dP58033wTgq6++YuTIkYwYMYKLL76YsrKypjy8iMh+yyvN475P7+ODdR/g4DCm+xj+O/IRDjO60OfdrzCjNiW9uhIaMijeoYo0qgwSmBo+js5OMhudMiZ+8wf8Tniv5bYMjd3x2OH7NRDUYrAiInujPpOIyO79Z2GYytISrkr9CBdR3B26kzRgFIbR2Eu7izSewV0tRvew+CBwCLZjENq+gVDhhniHJSKtSJMmbR577DEef/xxysvLAbj33ntJT0/njjvuID8/n4ceeqgpDy8i0mC2YzNr7Swe+OwBtlRuIdWbyrWHX8ukIZNIdiXScdFK0vMLibot1p18JKjTIAegDiQyJXwMaYaPb8tX8YfILCLYeyxT0qMT/oxkXMEw3m++b6ZIRURaL/WZRETq9kVehC/WVHF1yockGUFcaR1IHXw8htmkl7JEGsWFh7mJelJYGIqtZ1O+8L04RyQirUmT/qV7++23ufnmm7ngggtYu3Ytq1ev5pprrmHixIncdNNNfPTRR015eBGRBqkMVfKPr//BK8tfwXZshnYeyl1j72JQVmw0jau4lJz3vgQgb8yhBNNT4hmuSJPKJpW/JfwSn+nhUyePx6wFOOxhEVnDYMuQ2Ggb3+dfNVOUIiKtl/pMIiK72ljm8MyXfq5I/pgOVgVWcgZph5+K4XLHOzSRekn2Glx6hIf3/YcA4F/3LaHtBXGOSkRaiyZN2hQWFnLooYcCMGfOHEzTZMyYMQB06tSJioqKpjy8iMg+yyvN495P7mVx4WJcposLBl7AlUOvJNmTHNvBccie8n+4/UEqsjLYdPhB8Q1YpBkMsrow/ZDfYgCvW6v5n7lyj/tvG9gT2zJxFWyCvLxmiVFEpLVSn0lEpLbqMDz+ZZRf+T6nh3s7httLuxOvwPQlxTs0kX0yLNuiZ3Y7vgt1B6D4s5lxjkhEWosmTdp07NiRjRs3AvDRRx/Rv39/MjMzAfjmm2/o1KlTUx5eRGSvTMPEa3nxWl4WbVnE3z7/GyWBErKSsvjDmD8wruc4fC5fzT593/uajDlfYpsmq8YfCRqaL23EKVmjuN4aCcA/rEV8bWzZ7b7hJB9F/XNjP3zySTNEJyLSeqnPJCLyI9uB11b7GGIv4TBvHhgGaUechjsjK96hiTTIxcPcfB6NzdpRtXQe4ZKtcY5IRFqDJr3aeOqpp3L//fdz2WWXsXDhQs466ywA/vKXvzBt2jROO+20pjy8iMiuSkpgw4aaR8rWEg6qSmDu92/yfwv/j7AdZlSHw3jpyKmc6h3EwEBazWNofpgj7nsWgE3HDqOqU2acT0akeZ1nDuakaE9sw+Fu1zw2Ur7bfbcO/WEU2vz5UF3dTBGKiLQ+6jOJiMQ4DnxemE6SfwvjE74BIGnAKDzts+McmUjDpfgMTji8K8tCXTBwKPjgv/EOSURaAVdTVn7jjTeSmJjI119/zS233ML5558PwOLFi5k0aRLXXHNNUx5eRGRX5eXwxRcQDALgr97ObTv+jw/tNQBcaAzmyuKhWHM/IfDTco5Dz3+9g1VZRWhAP7aMHQb+suaPXySODMPglugRFBjlLDV3cId7LtMjx9e5b0V2RyKds3Bt2QZffgnHHtvM0YqItA7qM4mIxHy5xUNRhZ+bUj/FNMDXfQAJ3QfEOyyR/XZkrpsXNo5kQOnLRFfNI1ByPr6MDvEOS0RasCZN2hiGwVVXXcVVV11Va/uLL77YlIcVEdmzYBCCQSrsABOKZvCJvRaXY/Lb6JGcYPfAoZrIz4p0+Xol6Ws3EnW7KP39rZD3bTwiF4k7DxZ/jozhKve75BvlPOD5ilsYuOuOhkHgqCNInvlmbIq0Y45p/mBFRFoB9ZlEROC7QouFmxxuSf0InxHBSOtEUv+j4h2WSKM58/RRfP/PT+lhbuWbV55jxGW3xDskEWnBmjRpA1BRUcGXX35JdXU1juPs8vovf/nLpg5BRGQX26MVnFzyGAuj+SQ4Lu6NjGGY07nOfZO2FtPzo0UAbBw/Gk9OtpI20qa1I4E/R8byG9dsPnNtondSMhczZJf9QsOGwFuzYcsWWL0aBtaR3BEREfWZRKRNW1Vs8d5aF1enfEh7q5KoK5GEg4/BMK14hybSaNKTPSQc/ktYOIOMLV+xZeMWrMS0eIclIi1UkyZtPv30U66//nr8fn+drxuGoQ6IiDS7bdEyjil+iOWRLbQzEnkgcix9nLq/LFnBMP1fm4cZtdnRtxvbRg1GMyqLQH+nHb+JHsZU19f8O2UVg4NdGUrtxKfj88Hhh8O8ebHRNkraiIjsQn0mEWnLVhZZvLrawy8Tv6aveytRLEq7jiDR7Yt3aCKN7sgTjuPrb1+lQ3Qb81/+N0dOvDbeIYlIC9WkSZuHHnqInj17cscdd5CVlYVpmk15OBGRvdrm386xWx9geWQL3cwM/pd4KdHSYiKE69y/96yvSSyuIJCayKrxR+IyjGaOWKTl+oXdh+8jhXzg2sCfvZ/zVPgU2pFQe6exY2NJm0WLYmtKiYhILeoziUhbtXSHxRurPRzpXc1Y3woANqcOwOPV6AM5MJmmSedjzyHy/jR6Vy7imyUbwOWJd1gi0gI1adJm7dq1/OMf/2DYsGFNeRgRkXoprCrkuP/P3n3HV1Hl/x9/zcztyU0hIQUCBAhIB5GOoKAodsGGDRXXtljW1XUt3y3ub1fXdXddxbZr2bVXxAIiCtJBUHpHSkKAkN7uTW6bmd8fUTSQcglJbsrn+XjMI3jvPZ95z3XuTWbOzDkLrmV78DCd1TiWJNxHXEBlF0U1vj5l4x6St+7HVBR2XjKWkNPe9GNKCtGKKCjcGxjObrOQA1YP/8+ykn+EJqLxsxOOXbtCejpkZsLy5XDxxZGKK4QQLZIcMwkh2qONuRqf77PRw5LHFVFrASjr0JdyrSMJEc4mRFPqMnw825a/h8uXR/aSj0k+47JIRxJCtEBNehlXp06d8Hg8TbkKIYQIS3FlMWe/fjbbSnbTSavqsOlp6Vjr66MPF5Kx4FsAMscPoqxLUnNFFaJVcWLhgeKhOEwLG9Rc3lG3H/+i8eOrfi5ZAobRrPmEEKKlk2MmIUR7YpqwOMvK5/vsxKtebo1ZgoaBz51GefwpkY4nRJNTFJW0s6cBMFLdyvrtByOcSAjREjVpp81tt93Gc889x8GD8gUkhIicimAFF75zIVvytpDqTGJJyoNkWGrvhLF6ffT7aNnReWyyx/RvxrRCtD6d9SjuCgwF4FVtM9uVguovGD4cXC7Iz6+a20YIIcRRcswkhGgvAjrM3mVj9WErNoLcE/81TvwE7XGUpgwDGYpatBOxA09Hj+pItOon5tAaSr2hSEcSQrQwTTrSz2effUZubi6TJk2iQ4cOOBzVJ5JTFIWFCxc2ZQQhRDsX1INc/v7lrMpeRZwjji/PeYNem3LA76+5gWHQ5+MVOMoqqOjgZteFo+XgQYgwTNa7s07P5Wsti/9nWcn/9J8Ng2azwahR8PXX8NZbcMMNkQsqhBAtjBwzCSHag4IKhdk77eRVqFgUg98kLSc+WIKu2SnpPAZUC+h6pGMK0SwUVSP5zMspmPcCZzm28a/MvvTuYUY6lhCiBWnSTpuUlBRSUlKachVCiPaiuPiEJzE3TIMZy+9j/r75ODUH8856lQGOrkBOrW26L9lEfFYuutXC9svGoztkUkAhwqGg8Gt9BNvVAg4rHv6hfsNbDPjpBWecUdVps2gRZGdDly6RCyuEEC2IHDMJIdoy0zT5Jkvn/Y12goaCy2pyV6cNJJUfxEShtNNoDKsr0jGFaHbugWeSv/QD3J4CBuo72JmZypBT5O8BIUSVJu20efzxx5uyvBCiPSkrg9Wra79Dpgb/V/whb5bOxYLGhwl3MOaACRmBWl+fuCOLLt9Uzcex68JRVHSMO9nUQrQrbmz8X2gMd1sWskDdx/uBDdzhOrvqyZQU6NMHdu6El1+GRx+NbFghhGgh5JhJCNFW+QM6b3x9kPV7dUChW4zO1Z32kZq3DYCylKEEXYmRDSlEhCiaBcfwKfgXv8TZjq08tqMPvbomEOW0RjqaEKIFaNI5bX60d+9eXn/9df7+97+Tm5vLd999J5NtCiFOnN8f9vJy8SIeL50LwMux13O+1gcCtXfYuPJLOWXuNwBkj+pLQd9uzbJJQrQ1A80kbtAHAvBA5afsDeX/9OSECVU/X3oJQjJusxBC/JwcMwkh2pLcogreWrCT9XtLURWY0C3I9T1zSclfC4A3PgNfbPcIpxQisiy9xxJwJhCt+hlt2c7KzYcjHUkI0UI06Z02hmHw+9//ntmzZ2OaJoqicN555/H8889z4MAB3nzzTRkKQAjR6L7yb+f20rcA+H30BdzgGl3n6zVfgH6zl6IFQxR3S2b/mUOaIaUQbdf1Rn/Wm7lsUnK5puRlViQ8gFXR4LTTIDERcnJg7ly49NJIRxVCiIiTYyYhRFtimiYbduezZmsOhgnx0VZuGmoSHSgmbt8qFFPH70rC03FQpKMKEXGKqlHY7WxSd77HRMc2Hs0+hcM9E+iUGB3paEKICGvSO22ef/55PvvsM/785z+zcuVKTLNqUq3f/OY3GIbBU0891ZSrF0K0Q9uCh7m8+N/oGFzrGMEfoy+qu4FpkvHZClxF5fhiXOy89HRQm+UmRCHaLA2V3+vjiMXB2mAmfyj/tOoJiwUuv7zq3//+d+QCCiFECyLHTEKItsLrC/LZin2s3lLVYdOrSxy/uSyD9HiDmOxVaKEKQtZoSjuNAkWOuYQAKE8ajNcaT5QaYLxjJ8s3Hsb44W8BIUT71aS/JWfPns3dd9/NZZddRlxc3NHH+/bty913383KlSubcvVCiHamwPBwUfFzlJk+xtt68UrcdBRFqbON4+vlJOw6gKGp7Jg6jmCUo5nSCtG2pRDNU64pAPzVu4Cl/t1VT1x9ddXPBQsgMzMy4YQQogWRYyYhRFtw4EgZ7321m+xcDxZN4cyhaZw/Jh2XTcXctQJrZSGGaqWk8xhMzRbpuEK0HKrGvg4jAJjo3I6ntJSdmUURDiWEiLQm7bQpKCigb9++NT6XnJxMWVlZU65eCNGOBE2dK4r/zX69gO5aIrPjb8eu1DOB365duOYtAGDvpNMo7ySTYArRmC62DuRm51hMTKaX/pdSowK6dYNJk4QO2XoAAQAASURBVMA0q+a2EUKIdk6OmYQQrZlhmnyzNYfPVuyn0h8iIdbBFWf1pn+PhKoL6HYuhrw9mCiUdhqFbo+JdGQhIuT4C0oVBawWlZIOffG7knApAc607+CbrUfQDQOrRa22qGrdF6UKIdqOJu206datG0uXLq3xubVr19Ktm0z0LYRoHPeUvceSwG6iFTufxc8kUa1nDNjiYnjpJRTTJG9gT3JO7XWSCWr+40mVodZEO/dUzJX00BI5oBdxV+GbVUcmt91W9eSrr0IwGNmAQggRYXLMJIRorfxBnc9X7mfdzjwABvRM4PKJvegQUzV6gSt3E8q2LwDwppxKICo5YlmFiChVA1MnWJJXbbH6S+gcFaRPihOl70QAJjh3QMDLtl2H6OzyV1uSo6oOp4QQbZ+lKYvfcMMN/P73vycYDDJhwgQURSErK4s1a9bw6quv8uCDDzbl6oUQ7cQL3qW8ULEUBYW3426mv7VT3Q1Coaor/MvLCXVKYd/5o0Fp+JixmqJimDqFFYXVHtd1naAlSKm/BC2kHX1ctRk4Q34qfSUYlRVHH1cUhYAhJ7BF2+JWHbwRN4NxhU/yhncVF+39lCsGT4aOHeHIEXjlFTjvvBMrGhMD8fFNE1gIIZqZHDMJIVqj4nIfn6/MpMTjR1MVJgzrwildf/r7zF6WTcctb1X9R+d++GJ7gi7zdIj2SVFUjICPQEF21fmIH1RWBijPLaekpBTD7SbBHovDX8qZjh0s2G5joCuPRFfVay1WGzE9+qEo7ghthRCiOTVpp80VV1xBUVERL7zwAm+//TYAv/71r7FarfziF7/g6h/HtRdCiAZa7N/FXWXvAvCY+1Iucgyuv9F778HeveB0Un7jtRhqIZxEZ4mqqPhDfnI8OQSNn/4A03Wd8rIy3P4YNO2nThsHyXT2ZXC4JJNKT8lPj1vsJLmSGpxDiJZqjK0nD0VP5i+e+dy2+hHGHFTpPHIkzJ0Lzz4LTmf4xex2GD1aOm2EEG2GHDMJIVqbnAIvHy/biz+gE+20ct6YdJLiXUeft/hL6bz5VVQjiJncG7XnKCgoj2BiIVqIUAhT/+ncgxEKEgr4Cfp9hBx2PAl9iTv8DRMd21nq68MX31u5qo9f7q4Roh1q0k4bgFtuuYWLLrqItWvXYrFYcLvdDB48uNokm0II0RD7QvlcXvxvdAyucYzgt1Hn1t9o/nz46quqf990E0bHBCgsrLtNmIJGiNDPOn90XScQChDSg5iKcfTxkBHEwDj+9UaTfyULETF/iL6IL4I7Weffz02Hn+eLUVejzpsH27bBwYNVd94IIUQ7JcdMQojWYkdmEbMX7yGkGyTFu7hgbDoux09ziSp6gE6bX8USKCMQlYx11LUoJdkRTCxE6+GP7kzQHovNX8pEx3bmlgxlT4lKr3ij/sZCiDalyc4Qzp07l3fffZdNmzYR+uHWP4fDwdChQ7n66qs5++yzm2rVQoh2oMyo5OLi5ykyvQy3pvNy3PVVE13W5fBhePTRqn9PngyDB0NF43TYCCHqZlU03kydydDs/+Mr3zaejdnC3f36VXXaLF8OU6dGOqIQQjQ7OWYSQrRkmqpUm/j8++wSPlu+D90w6Zri5sKx3bFZfxpRAEMnactbOMoPolujKBx+K6m2E7ijWoj2TlHwJvQn7vAqznTuZKmvLwsz7XSP9TX9VfdCiBal0T/zuq5z33338cUXX5CcnMwFF1xAYmIipmly5MgR1q5dy1133cUll1zCX//618ZevRCiHdBNg+tKXmVb6DCpaixz4m/HqdjqbhQKVQ3DVFkJffvCxRc3T1ghxFF97J15csC93LnpcX5b9hFTxkyly7ZtsGpV1WfSIociQoj2QY6ZhBC18VQEqPCF6n/hz7gcFqJd9RwPnSBNVegUq6LpPgA2Z5bxybKDmCYM6RHDVeM6Y9FCwA9ZTRNt08do+VsxVQvGqOtJSnATZQVfoyYTom3zR6cSdMRj9RVzYdQm3vGM4rscC6d3j3QyIURzavSzI2+//TZffvkljzzyCNddd91xV77rus67777LY489xrBhw7j88ssbO4IQoo37v/JP+My/GTsWPo6/g85aGHNbfPop7N8PsbFw663wszlmhBDN55fdr2Lu7rl8UbmFKWkr+TY2FqW0FDZuhGHDIh1PCCGahRwzCSFqU+ELsTOriGAovOGQrBaVPt06NHqnjaoqaLqPygM72XEkyHvbVExTYVRXlXO7FVOZWVTt9c68bdhyN2ECnrTRBErKsAf2ENujOzIhhxAnQFEo7ziIDtlLGWH7noVqP1YcdDOks06HSGcTQjQbtbELfvzxx0ybNo3rr695qCJN07j22mu58sormTNnTmOvXgjRxr1duZa/er8A4JW46YywhXG5ya5d8OWXVf/+wx9kAnMhIkhRFF5NuJkEJYp15kG+Hp5Y9cSyZZENJoQQzUiOmYQQdQmGjBNamtL3eUE+2KZimAoDOupcNdDACAYIBX5aLPnf48rdBEB50hAqnMmEAgH0UKBJswnRVgVdHfFHpaBicrl7PQFDYUlmo5/CFUK0YI3+id+/fz/jx4+v93Xjxo1j9+7djb16IUQb9q1/HzeXvA7Ab6PO5VrnyPobeb3w6qtgmjBxIpx1VhOnFELUJ9USx39irwNgxoC9mIpS1bmamxvhZEII0TzkmEkI0RocKvTx7laVkKnQKz7ElFNCqMf0M9u8ucQc+Q4Ab3xvKuMzIpBUiLanvONATKCPdoBuWj4bchQOF8pgg0K0F43eaVNZWUlsbGy9r4uPj8fr9Z5Q7RUrVnDZZZcxePBgJk6cyCuvvIJpmnW2mTt3LhdccAGDBg3ivPPOq/dKtccee4xTTjnlhHIJIZreIe8RLs17Bh9BLrQP5C/uS8Nr+OGHUFICSUlw/fVNGVEIcQKmOodyo3M0B+Lg614/jNa6fHlEMwkhRHNpymMmIYRoDJ7KIP9deICgodAtRmdK7wDaMWeQLL4SYg+vRsHE5+6Cp+PAyIQVog3S7bH4YroBMC12HSbw8Tc59Z4HFUK0DY3eaWOaJloYc0WoqnpCXzQbN27k9ttvp0ePHsyaNYuLLrqIJ598kpdeeqnWNgsWLOD+++9n7NixPPfcc4wYMYIHH3yQefPm1fj6b7/9ltdffz3sTEKI5uENeLlo0c0c1kvoZ0nlrbib0ZQwvr5+nOBcUeCGG8DhaPqwQoiwPR1zFelaAv86LVj1wOrVEAxGNpQQQjSDpjpmEkKIxhAM6Xy6bC+l3hCJLpPLTvFjOebwSw16iTu4AtUIEXB1pDRlmMxdI0Qj8yT2x1RUOpHHIFs2uw952bavMNKxhBDNwBLpAOGaNWsWffv25cknnwRg/PjxhEIhXnzxRaZPn46jhpOx//znP5k8eTIPP/wwUDW8QGlpKU8//TQXXHBBtdd6vV4eeughkpOTOXLkSNNvkBAiLIZpcN2c69hQtI1E1c3c+DuJUZ14A158odpvDVZ8PmJffw0NqBw3mopO8ai+EpwhP5W+EozKChRFIWDICWIhIiVGdfJG3AwmZjxJdgx0KfPAhg0wYkSkowkhhBBCtEumabLw22zyiiuJcmhcPcCP45g+ZiXkIy57OZruI2iLoaTTaFDr74gWQpwYw+rCG9+b6KKdXOn+jm2FnZmzZC9Xnt070tGEEE2sSTpt/vjHPxIdHV3nazweT9j1AoEAa9as4e677672+LnnnsvLL7/MunXrGDt2bLXnDh48SGZmZo1t5s+fT2ZmJunp6Ucf/9vf/kZiYiKjR4/m+eefDzubEKJpPbzoYT7e+TE21cbHSXfTXamatNwX8rGveB9BI1Rjux7zV6OVlOKLi2bTqO4YhbtxkExnXwaHSzKp9JTgsNhJciU15+YIIY5xui2D+2Mm8/LQL3h0CfiXLcYunTZCiHagsY+ZhBCiMXy3I5d9h0rRVIUbzupCvGcPocDPXhD0E5u1DEvQg25xUZJ2OqZmi1heIdq6ioQ+OEszceseJkXv4ouifmzZU0D/HgmRjiaEaEKN3mkzfPhwgHpv44+KimLYsGFh1czOziYYDFbrZAHo1q1qbMf9+/cf12mzd+9egDrb/PjcypUr+eSTT5gzZw5z584NK1NdTNOkoqLipOu0VZWVldV+iqbXWt/z17e8zhMrnwDgP6MeY1hWLH5f1d01uq7jC/oJ6cffKRN7MJ+UdbsA2HHucCrRIaCjBgLoRlU7f8CHaioYpoGu6+i6HlYmI2RiGmZVm1BVG13Ra6wT0kPVftZVo6464eaIVJ26aoRbRw1VPR8MBglUOyr8SVANoht1v0Y1VMBKSA9h1pAlnDz1bU84dcKt0Rx1TqRGbXXqqlHbfq5oKrpu4A/87P9VMIim6+jBIPzs8Yfs53LFsE3oS3Owf78P/4EDkJJSc0BVRQkGCbXj37Ot9Tu9NZP3vH6maaLIsDhha4pjJiGEOFkHjpSzdnsuABOHdaF7sovyn/cd60HYsRSLvxRdc1DcZTyG1RWZsEK0E6ZqwdNxALFHvmOSYwsrvN35ZmsOPdNicdhazQBKQogT1Oif7jfeeKOxS1JeXg5w3JVoUVFRQM1XoP34WH1tysvLeeSRR7j77rvp3r17o+QNBoPs2LGjUWq1ZZmZmZGO0O60pvf8u4LvuHPNnQDc0vsWznGPJS93EUZFBaqqErQEKS8rO+7kvWIYDF2wFoCsU9LIinNAaSkAIXs0gWAAT3k53tJSQvYQQUcQT3k5/qA/rFzH1qh6rO46Xo+33hrh1AmnRiTq1FUj3Dq2kInT4yE3mEtFoOaT8YGoAJXuSvLz8/H4ar7y2GVzgTWKCm8FAW9ZLXnrzlPf9oRTJ9wazVHnRGrUViecGsfu506bE7/bxyGvB344KWkxK4nz96Ck5Aghb/X/h7+OPp/5vV7lwt0m6xe9QfLkq48+Z1PtGH4d0zRRXS4sBQXkejxhd7a2Va3pO72tkPe8bjabXGkdrqY4ZhJCiJNRXhHgq7VZAPTr3uGHq/h/9repESI6eyVUFGJoNoq7jEO31X23oBCicfhiuhFVug9LZRGXx2/jf0XD+G5HHqcP7hTpaEKIJtIqumQNw6jzeVU9fkLycNs89thjpKSkcOONNzY437GsVisZGRmNVq+tqaysPDo8ndPpjHScdqG1ved7ivfw8MKH0U2dy/tczlMXPoU1JwczORl+uNOm1F+C2x9z3J02ndftJrawnKDDRvakYcS6fprvyhntxma1Ee12YyGE0+rEarMS7Xbj0I+fF6smx9YAaq0T0kN4PV6ioqOwaJY6a9RVJ9wckapTV41w61hdbuzR0STbkmudqyjWEYvT5aRjx464Q+4aX6MaKnjAFeXCaan5iu/68tS3PeHUCbdGc9Q5kRq11amrRq37udWJqZnkeXOPDmPoCOhYdS95gTwq/SXV1wtkDsmA3d/Te9MBFozfShetA1bVQo/4HsTGd6x6ocOBkphIbKf2e4DS2r7T2wJ5z+u3Z8+eSEcQQghxAhQFrJaq8yIh3WDBN1n4AjpJ8U4mDuuC1aKi/vjntKETd2g11op80KyUdh2PbouNXHgh2htFwZs6lNh9CxnCDjppPdiyR2FAjwTi3PZIpxNCNIFW0WnjdlednPN6q1/FW9vdNOG2Wbx4MfPmzWP27NkYhnF0AQiFQqiqWmOHUH0URcHlkluE6+N0OuV9amat4T0vrizmijlXUOQrYkTnEbw+9XWcVidYrVXLD59RLaShaRqm8lMHrdVTSY8VWwDIPHMwRkwUP58OU7UoKKqCpmlolqr2qqIeV6cux9YA6q1j0SxHX1tbjXDq1JcjUnXqqhFuHdVS9bzVasVQa36N1WJFU+t+TdXwaFXvuVFDlnDy1Lc94dQJt0Zz1DmRGrXVCafGsfv5j3UMxTxax1QMUKj22M/17nEaObF7SS012LB7CUn9LkJTqj6r9h+v4P/hu8DWwr/LmkNr+E5va+Q9r50MjSaEEC2HXunB8Nc9lKzVHyLV4UM3TD5dc4TcogqcNpWbz+5MB3cQTdOJsqqUYRKbswZ7RS6moqH0PQvdcINe9/COQojGFYpKwkwbjHJwE9fFfceThZNYteUw549pnFGDhBAtS6votOnatSuappGVlVXt8QMHDgDQs2fP49r8ONRZVlYW/fr1O/r4jzV69uzJs88+i9/v58ILLzyuff/+/ZkyZQp//etfG207hBBVnTJl/pqHrfKFfEyfM53dhbvp7O7Ms+c9S543D1VRcftKMSqLMX2VKIpCwDh+Lpseizdg8QcpT+1AzhC5202I1kZVNYoHn0Lqsh1cvN7L0wM38GtzdKRjCSGEEEK0Koa/At+hXRCq/S7rysoA5YVeduXD8m1VF95c3CuINW8n5Xlgd0UT3a0L0QdXY/McxlRUPN1Oxx2TBCUyx5sQkaAMvhCO7KRz6Agj7HtZcziDI4VeuiTXPBIFVN1RJ9fWCNH6tIpOG7vdzrBhw/jqq6+4+eabj17Jt2DBAtxuN4MGDTquTbdu3UhLS2PBggWcd955Rx//8ssvSU9PJy0tjTvvvJNrr722Wrv333+f999/nw8//JD4+Pim3TAh2qEyfxmrD67GH6o+d4dhGjz37XOsy1mH0+Lk9mG3sz1/O9vzt2PX7PStiMJfvJdQhQeHxU6SK6lae/ehApK37McEvj93BDTgLjkhROSVDe6DsXwH4w7A7YW7WJLQiVPoHelYQgghhBCtSyiEqR9/oduPjFCQEk+Aj3dWDYd7WkqQnjFBfpwy1GL1E1z3KbbiTEwUSjqNguiU5kguhKiBqmlEd0ggOGQy/u8+YWr0BrYEuvDN5oOMuKg7qlpzz4ymKlj9JQRLfppTVLW70JwyJ5UQLVmr6LQBuOOOO7jpppu45557uOyyy9iwYQOvvPIK9913H06nE4/Hw549e+jatSsdOnQAYObMmTz00EPExcUxceJEFi1axPz583nqqacASEtLIy0trdp6lixZAsDAgQObdfuEaE/8IT9+/adOG9M0eXvr26zLWYdFtfDL4b8kKSqp2mt000HICBIygujGMV9dpkmPResByB3UA0+nhGbZDiFE4wu4XRT1SiNx90FuXQf/N3kF5xqnkYB8roUQQgghGothmnz6vY2KoEJHp8HErj/r4DFNHAe/I5S3DRMoTR1BILoTtoilFUKomgYhP3pMCrojFoevlItdG3i3cBQrV29lSErNQxZqmkJ0QhSa84dPsMWCo/MpYXXaeCoCVPjqnxf151wOC9Eu+bYQ4mS1mk6b0aNHM2vWLJ555hlmzpxJcnIyDzzwADNmzABg27ZtTJ8+nccff5ypU6cCMHXqVAKBAK+++iqzZ8+mS5cuPPHEE5x//vmR3BQhxDE+//5zlmUtQ0FhxpAZ9E44savqE3ZlE3swH92ikXnG4CZKKYRoLjmn9iJx90Fu3KTw4NlBflHxDt9EPYRdsUY6mhBCCCFEm7B4r8neYg2LYnJJbz/Wn01bGFW4HXvhDgAqu4zC70qrpYoQormZhoEneQixWUsZZd/NKl8GX+/rQO9YP7Yaph81NQUjZMPUq+7EOZGR0ip8IXZmFREMhTcHsNWi0qdbB+m0EaIRtJpOG4BJkyYxadKkGp8bOXIku3btOu7xadOmMW3atLDXcdddd3HXXXc1OKMQ4sQsz1rOp7s/BWDagGmc1um0E2qv6Do9Fm8E4ODIvgTcMkG0EK1dcY9UfLFRxJZ6uWGrhX+feogHyj7i6dirIh1NCCFavBUrVvDUU0+xZ88eEhISuPbaa5kxY8bRIaZrMnfuXF544QWys7Pp3Lkzt956K1OmTKn19Y899hivvfZajcdfQoiW73Cpwcfbqq7Kn5geJMn10xX6rqJdRP/QYWM99UICZixU+musI4SIjGBUEpXurjjLD3BN9Gr+VnoB3xy2Mr5L7UMiNnhdISPsThshROORSR+EEBGz8chG3tryFgDn9zqfM9PPPOEaqeu/x1lcTiDKwcFR/Ro5oRAiIhSFnCEZAPxuXRQAz1R8zUeV6yOZSgghWryNGzdy++2306NHD2bNmsVFF13Ek08+yUsvvVRrmwULFnD//fczduxYnnvuOUaMGMGDDz7IvHnzanz9t99+y+uvv95UmyCEaGK6YfLi6gBBA3rE6ZyW/NPQR87ivbjztwDg6zQUa+/RkYophKhHedIgDNVGqlbMBMd2vjlsocx/IvfRCCFaMum0EUJExJ6iPby8/mVMTMZ2GcvFvS8+4RqaL0C3FVsByBw/CN0uQycJ0VYcGdwTQ1XofLCUvxQNBWBG6evsC+ZFOJkQQrRcs2bNom/fvjz55JOMHz+ee++9l5tvvpkXX3wRn89XY5t//vOfTJ48mYcffphx48bx6KOPct555/H0008f91qv18tDDz1EcnJyU2+KEKKJzN0eYm+hidMKF/UK8ONNeI7SLGLyNgDg6dAHf+qgCKYUQtTHtDgoT6oaHv485ybiKWfJATknIkRbIZ02Qohml1mSyXPfPkfQCDIwaSDXDry2ziE7apO6djvWSj8VCTEcGdyzCZIKISIlGO2ksFfV+On3rLMy2tqDUrOSq/JfwK/LEB1CCHGsQCDAmjVrjhtO+txzz8Xr9bJu3brj2hw8eJDMzMwa22RlZZGZmVnt8b/97W8kJiYenUNUCNG6ZBUbzN5SdWfNVYMUYuxVj9vLDxJz5FsAKuIy8Cb2j1REIcQJ8MV0xe9KwqroXBW1mq0FGoc9cqpXiLagVc1pI4Ro/bblb+PJVU9SEaygZ3xPbj3tVjS1htny6qFUVNJpzTag6i4bVPnDRIi2JmdoLzruysa5biPvXf4wQ8r+xneB/fxq7Z94ocebkY4nhBAtSnZ2NsFgkPT09GqPd+vWDYD9+/czduzYas/t3bsXoM42Pz63cuVKPvnkE+bMmcPcuXMbJbNpmlRUVDRKrbaosrKy2k/RfCL53geDQYKBAIFw55AwVILBYPXPUihEIBjADP00v0XIMHlhpYFuwNBOMKyTyeF8Ha08h9icNSiA192NkoQBYBiEdAPDMNFDBiFdB0BTTEzDhh7SCRkm9QnpBqZhYBpmWG30H9ajGzq6rhMIBABQVQuqYRy3TTW1r2s9jbdNJoZuEgic2PwhP89XU5ZjhZVNN9B1vfo+U9M+Ud92hUI/lNMxqf99qClfONsUznbVWMdUqu0T9flxnzH08Pa9k92m+vLVtg/ruo5u6Ef/XZfaPk/FHYeQdGARvay5jLZ/z8L9Pbi6b+XRu+iOzaZYTLRQiGAY+0ejfB+1UPI7NnLa83tvmmbYF61Lp40Qotlszt3MdR9dhzfopUd8D+4eeTc2zdagWu6lq7H4g3iS4ino07WRkwohWoKS9BR8cW4cJeV02bCXN067iQuLn+PFXW9x2voz+cXQX0Q6ohBCtBjl5eUAREdHV3s8KqpqbjCPx3Ncmx8fq69NeXk5jzzyCHfffTfdu3dvtMzBYJAdO3Y0Wr226tg7nkTzae73XtM0FJub3LxcfIFQ/Q0Ah81CarxCfk45uq6jaRoJDpXyvDz0wE93J3+Z6SK7NAqXxeC8biV4vTaCBZl0LNqIgkmpPYlD9h5QVgZA0IRgMEC5p5wKb9UJWKfdgjvKQll5OcFQ3SeYf6oRIhQMhN0GqoZi9Hg0ykv9GIaBLSqGRHcS+QUFBH01n+RTVRVFs1NWXlbrpOmNt00BKiu9lFSUYhjhncw+Nl9NWY4VTjar3YHq8ZCb5z+6zxy7T9RH0zQSXVWnB71eb9iTzh+bL5xtCme7aqpjtajEuji6T9THFhVDYkwy3kpvnftEY21Tfflq2od/3Ce8Xi9Q8+/pn6vz8+TqTop3D5e61vHX0k5sPBSgh7uyxmyazY47uoBCX16d+0djfB+1BvI7NnLa63tvs4V3HlQ6bYQQzWJr3lbOev0sin3F9Ijrwd0j7sZhcTSolsVbSfSKtQBknjEIGjC0mhCiFVAUcof2ptvX62DZMs4f+xB/ipvC70o+YubnMxmQNIBRaaMinVIIIVqE+k5iqTXclRxum8cee4yUlBRuvPHGBueridVqJSMjo1FrtiWVlZVkZmaSnp6O0+mMdJx2JZLvfXF5kOQkM+wr220WlcSEROLdqT89WFGCy5N09Ir+vYUmS7Or6t043EJGWke8BUewFW9GxaDSlYIndSSxyk/fE45oN1arDXe0G6ulap4Mu0XFZrUR43aHdedCVQ0LoTDb6LqOx+MhKiqK6OhoXPZYAFSHC4fLRcfExDrvtKnw68RUUOt6Gm+bbKjOKOzR9npfX1u+mrIcK5xsFpud6Ohoks24o/tMjftEPUJlBXip6rQ3w5xJ4dh84WxTONtVUx2LqlTbJ+qjOlw4nE6inFHEuGPCvtOmodtUX77a9uEKv06UR6ektJzo6Gg0rfZRSOr6POkxA/AfKsLhK+KaqFW8VXgWAzvZsKjHZ1MsVpyJiSS44up9Pxrl+6iFkt+xkdOe3/s9e/aE/VrptBFCNLkd+Ts46/WzKKgoYGDSQG4fdjsWteFfP6krNqEGg5R3SqQoo3MjJhVCtDR5gzPounQjSmYmZGfzcM8LWR/jZc6BBUx9byrrbl1Hais4KBBCiKbmdrsBjl6x+6Pa7qYJt83ixYuZN28es2fPxjCMowtUDaejqmqNHULhUBQFl8vVoLbtidPplPcpQiLx3nt8FVhtNlDDO0lqtahYrdZqOYMBD7rVhqkqBEImr3znxwTGpGuM7WEjVFaIvm0RqhnC70qirPNoLMcMWW3RVFRVQbOoWH44kaxZNBRVQbNooNd/EtyiqSiqekJtADRVQ9O0o1cjqxYbmlp1Mt1Ua79gzx8K1LmextsmBVVTwr5auqZ8NWU5VjjZLJqKpmnV9pma9on6VFRUHZ9rqgZKeN/px+YLZ5vC2a4a/z9pSrV9oj4/7jOqdoL7XkO3qZ58te3D/lDg6HDxmqbVuY76Pk/lqSOwZn5Fb+sRBgS+Z2NeD0Z1Dh2XTdGsWC0WrGHsH43xfdTSye/YyGmP7/2JzOctk0AIIZrUroJdTHx9InnePE5NOZU3prxBlDWqwfVsnkqSvqsaRuPAGafKXTZCtHHBKCeBgf2q/mPZMlRF5bVx/6Bfx37keHK49L1LqQy2v7FwhRDiWF27dkXTNLKysqo9fuDAAQB69ux5XJsfhzo7ts2P/92zZ08WLFiA3+/nwgsvpH///vTv35/nn38egP79+/Pwww83+rYIIRrP+5uC5JSZxDnhhmFWQp5iSr+dC6EAQWcCJZ3HQAPmGBVCtCy6LRpPx4EAXOxaz66cSrwnNu2SEKIFkU4bIUST+b7weya8NoEjniMMSh7EV9d/RZwj7qRqpn2zHVXX8XdLo7RHp8YJKoRo0XxjRlT9Y+1a8PlwW6P5ZNondHB2YO2htdzw8Q0YZpiTYwohRBtlt9sZNmwYX331Fab509W3CxYswO12M2jQoOPadOvWjbS0NBYsWFDt8S+//JL09HTS0tK48847+fDDD6stV155JQAffvghd955Z9NumBCiwXbk6nyxs2peiVtG2nDq5ZStnYcZ8KFEJ1DWdRycxAgIQoiWpTKuJ35nR+xKiCscq1hxQDpkhWitpNNGCNEk9hbtZcJrE8jx5DAgaQALr19IgivhpGpavJWkbvgegLKzx8ldNkK0E6GMHpCUBD4ffPMNABkdMphz1RysqpUPtn/A/339fxFOKYQQkXfHHXewadMm7rnnHpYuXcq//vUvXnnlFW677TacTicej4eNGzdSVFR0tM3MmTOZP38+f/zjH1m2bBl/+MMfmD9/Pvfccw8AaWlpDBw4sNqSlJQEwMCBA0lLS4vItgoh6uYLmvznmyAmcEZPjUGJfkrXzsPwe9Gi47EOOgdTq32ODiFEK6QolKUOI6RY6W7NJ6l8B3leOW8iRGsknTZCiEa3v3g/E16bwKHyQ/Tr2I9F0xfRMarjSdfttHIzWlDH2ykRf+/jh/gQQrRRigLjxlX9++uv4YcryMd3G8/LF78MwOMrHue/G/4bqYRCCNEijB49mlmzZrF//35mzpzJZ599xgMPPMAtt9wCwLZt27jqqqtYsmTJ0TZTp07l0UcfZdWqVcycOZNvv/2WJ554gvPPPz9CWyGEaAzvrPeR5zFJcClcO9Cg9Nt5GJVlqM4YYodfgGJ1RDqiEKIJGNYovCmnAnCOYwvbMosjnEgI0RByH6wQolFllWQx8fWJZJdlc0rCKSyavoikqKSTrquVeUhZsw2Aw+NOxSl32QjRvowZA59+CgcOwPr1kJ4OwPTB0/m+8Hv+vPzP3Dr3VtLj0pnQfUJkswohRARNmjSJSZMm1fjcyJEj2bVr13GPT5s2jWnTpoW9jrvuuou77rqrwRmFEE1ry/5SvtpVNZnFLSMUglu+QC8vQrG7iB1xAaojCioCEU4phGgqvpiumKW5xFVkMVFfxY7DlzAiwxbpWEKIEyB32gghGk12aTYTX59IZkkmvTr04usbviYlOqVRanf8YB4WfxBPxzhKendtlJpCiFYkOhpG/DC3zWuvVXvqTxP+xLQB0wgZIaa+P5WdBTsjEFAIIYQQIvIqfEGe/WwvAGdnKHTN+ZpQ8REUi43YYeejuWIinFAI0RwCnYZQTjQJmpfKXasI6jIHqBCtiXTaCCEaxaGyQ0x4bQL7ivfRM74ni29YTCd3p0apbanwkfTeXAAOjB0gc9kI0V6deWbVz88/h5ycow8risJ/L/kvo9NGU+Ir4YK3L6CgoiAyGYUQQgghIujVz7aRX+qnYzRcaltJMP8AqBZihp2HJebk5hgVQrQepmbF03k4uqnQX81kw7ptkY4khDgB0mkjhDhpOeU5THhtAnuL99I9rjuLb1hM55jOjVa/18fLsJR7qEyIpaBPl0arK4RoZbp2hYwMCIXgpZeqPeWwOPhk2id0j+vOvuJ9XPrupVQGKyMUVAghhBCi+a3flceCb7IAk1+nrUc/sgcUlZhTJ2GNb5wREIQQrYcancA+1yAAuhZ8Q2FuXpOvUy6xFaJxSKeNEOKkHPEcYeLrE/m+6Hu6xXZj8Q2L6RLbeB0rSkin35sLADg8dhCo8rUlRLt29tlVP198EYLBak91jOrIvGvmEWuPZWX2Sq796Fp0Q49ASCGEEEKI5uWtDDLrvQ0A3NlzP668rQBEDzwTW5IMLy1EexXXrRd76YJFMSjf8BVGwNdk69JUhZBhkFdUcUKLR+bYEuI4lkgHEEK0XnnePM56/Sx2FuykS0wXvr7ha7rFdWvUdfRYuI7onEKC8THkn9obgk33B4YQohUYNgwSE6uGR5szB668strTfTv25ZNpn3DOm+cwZ+cc7vz8Tp6/4HkUGVZRCCGEEK2AAlgt4V+oZrWoKAq8/MlWCkp9nNvhAL2KVwAQ1XcMjs69miipEKI1UFQF94DTKdj0GYmah8NrvqJnxqlNsi5VVfAFdLJzSwiGwptDx2pR6dOtA9EuW5NkEqK1kkvWhRANUlBRwFmvn8X2/O10dnfm6xu+pkd8j8ZdiWky+I0vAci//AIMq/QzC9HuWSxwzTVV/3722Rpfckb6Gbw19S0UFF5c9yJ/XvbnZgwohBBCCNFwNvykOnx0dvnDWlIdPrZtz2Thtwfoaz3EecoyAFwZw3CmD4zw1gghWoIuCQ52JEwkaKrYS7MoWfdlk64vGDJOaBFCHE/OgAohwlJcWUyZv+zov6/56Bp2FOwgKSqJN6e8iVW1klWSVWcNVVGpDIU/x0Snb3eSuCuboMNG/mWT4btVJ7UNQojW6pi7ZK69Fp5/HpYvh02bYPDg41pc3u9ynj3/WWZ+PpPfL/k9qe5UfjH0F82UVwghhBCiYcxAJRXZOwn4/GG93m8ovPytRmetiF/ELEMxDZwZp+E6ZSQYoSZOK4RoLc45LYV3Ph/JpfbVlK/5FHevoTi7DYh0LCFELaTTRggRljJ/GasPrqaoooi/rfobWaVZxNhjuHfkvWSVZpFVWneHDYDb7iYjPiPsdf54l82eS8ahx8Y0OLsQovXSFBXD1CmsKARAMZyosQ5sF5+H66PPKH/qCYr+9XiNbS/odQE7hu/g2W+f5ba5t+GyuLhm0DXNGV8IIYQQ7ZinIkCFL/yOE1UFxTDQgwFCgfDmePh8jw014OGO2EVYzCDWxC7Ej7uSYH42ZkODCyHanCibQt9BfVmzOY+R9r3kzP4nXW/5BxZ3fKSjCSFqIJ02QoiwFVX+1GHjtrm5d9S9dHB1wK+HdxWYPWQPe10dvj9Il9XbMVSF7ddPpntDQwshWjVVUfGH/OR4cggaISyuaOwlPcm/eChnf/QZzvdms+qmsQRio2tsf1rqaYzrOo7lB5Yz49MZOCwOTut02kllirHHEO+UgxshhBBC1K3CF2JnVlHYw/+4XTa6x4bf1bKrSGNPgcE97q9xK5Vo0fHEjrgQRZNTPUKI443pbuEfmWPo4i2kU2UJeXP+Sep1f0RRtUhHE0IcQ36TCyHCUuYv4x+r/kFWaRbRtmjuHXUvndydmmx9g974CoD9Zw3F07kj+JpsVUKIViBohAgZQTCCWEydQ4PSKeidRuLug6R/vIQt102qte3VA67GG/Cy/sh6pn88nUfGPdLg7y+7xc7otNHSaSOEEEKIsJzInA0hPfy5HSqC8OU+jRnRX5NqKUG1u4gZdh6q1dHQqEKINk5RFG4Y5eZv8yZwT9RcyN5O4cLXSDxnRqSjCSGOoUY6gBCi5Sv3l3PjJzeyr2QfUdYo7h11L51jOjfZ+qKOFJGxYC0Am687p8nWI4RoxRSFbVdOAKD/B0tQ6jjJoakad4+4m0FJg/AGvTy56kmOeI7g1/0nvoTCu7NQCCGEEKKpmCZ8vs/KxbZv6G09ApqFmNPOQ3O6Ix1NCNHCJblVzhrXn7c8YwEo+3YeZRsXRjiVEOJY0mkjhKiTJ+Dh/LfPZ33OeqKsUfxq1K9Ii0lr0nUOePdrVN3g8NDe5PdPb9J1CSFarz2TR+B3u4g5VEDa6m11vtZusfPM5GdIiU6h2FfMM2ufwRvwNlNSIYQQQojGsylPo3vFdkbY92GiYO03AUtsYqRjCSFaiYtGplLecQCfVwwGoGD+S/iyd0Y4lRDi56TTRghRK2/Ay4VvX8iKAytw29z8Zsxv6BrbtUnXafVU0nfOcgA2TZe7bIQQtdMdNnZeUnWF2MC3F9X7+nhnPPePvp9YeyyHyw/z/HfPE9SDTR1TCCGEEKLRFFYq5B7K4XzXJgA8qUNROzTtRXVCiLbFoqncc9WpLAwMZmOgKxghcmf/jVBpfqSjCSF+IJ02QogaVQYrueTdS1iatZQYewxvTHmD9Lj0Jl9vv9nLsHl9FPVIJXtM/yZfnxCiddt25ZkYqkLa2h102J1d7+sTXYncPfJuHBYHe4r28MqGVzDM8MePF0IIIYSIFN2ANXs8THOtBMAbl4E/vkeEUwkhWqOeaXFcPrE3b3nGkmN0QPeWcuSDJzCCMhy0EC2BdNoIIY7jD/m5/IPLWbR/EdG2aL649guGpAxp8vWqwRAD3v0agM3XTQJVvqKEEHXzdEpk/1lDARj0VnhjMafFpPHLYb/EolrYcGQD72x9B9M0mzKmEEIIIcRJ+zY7xKXaUmyKjteRjCdpUKQjCSFasasm9SY1pQP/LjsTn+oikLuf/M+elWMjIVoAOSMqhKgmqAeZNnsan3//OU6Lk3nXzGN0l9HNsu6ML9YSlV+CNzGWPZNHNMs6hRCt3+ZrJwHQc8G3uPJLwmpzSuIpzBgyAwWFZVnL+HzP502YUAghhBDi5BwoMRnkWUG8VkGF5sabNhIUOaUjhGg4q0XjnmmnUoqbf5eMw1RUvDtWUbJydqSjCdHuyW94IcRRuqFz/Zzr+Xjnx9g1O59e/Snju41vnpWbJoPe+AqArdMmYtiszbNeIUSrlz+gOzlDMtBCOv3fWxx2u9M6ncZV/a8C4NNdn7LiwIqmiiiEEEII0WCVQRPLwQ10txTgx0pF1zGYmi3SsYQQrZZy9F+9usRz+cRe7Asl80mg6oLd4qXv4N21BkUBq0WtcdFUpbbiQohGIJ02QggADNNgxqczeG/be1hVK7OvnM3ZPc5utvV3WbmVDvsOE3DZ2XFZM3UUCSHajM3XVd1t02/2MiwVvrDbTeg+gfMyzgPgrS1vsT1/e5PkE0IIIYRoCNOEnH37ONW6D8NUKO00Ct3mjnQsIURrpWpg6gRL8o4ul42Ip0dKFIvLe7LdVjXsYt7HT6Mc3kqqw0dnl/+4pVOsdNwI0ZSk00YIgWma3DH3Dl7f9DqaovHe5e9xQe8LmjXD4De+BGDnlHEE3K5mXbcQovU7MG4QpV2SsJdXcMqnq06o7SWnXMKozqMwTIN/r/s3h8sPN1FKIYQQQogTk3M4l5HmBgAOxQ7BdCdHOJEQojVTFBUj4MN3aBe+rG34srahH9zBHSPAqsFLRwZR5uyMGfJT/sVzeHatoXzv5mpL5YGdaLoPVTpthGgy0mkjRDtnmib3LriX/6z/D6qi8ubUN5nSd0qzZkjcnkmndbsxNJUtV5/VrOsWQrQNpqay5Zqq74+B7yxC0Y2w2yqKwnWDriOjQwa+kI9n1z5Lmb+sqaIKIYQQQoSlrLScvuXfoCqw39ITW0qPSEcSQrQVoRCmHjy6dHIbXHOqFQOVJ4+cjuGIxfR5cO1bSshXSSgQ+GkJBiKdXog2TzpthGgnNE2r8fE/Lf0TT695GoBXL36VaQOmNWcs4Ke7bPaeMxxvSodmX78Qom3YddEYfLFRxBwqIH3JxhNqa9Ws3DHsDpJcSRRWFvL8t88T1INNE1QIIYQQoh6hgJ+EwytxKEGyzSQc3QeDIle1CyGazqTeGoNSVcp0O/+tmACaDWtlITG566rGahRCNBvptBGijSuuLOaw9zA+u4/D3sNklWQdXR5d8ih/XPpHAP505p84M/3Mas//uGSXZlMZqmySfO6D+XRftB6ATddPapJ1CCHaFlXVsGv24xZLlJvdV0wEYPBbi6o9Z9NsaMpP7Syq5bi60bZoZo6YicvqYn/Jft7a8hamHJwIIYQQopmZhgH719JB9VBkRKOnj0RV5fSNEKJpKYrCbaNtxDhgc0kMyx1nYKLgLDuAq2hXpOMJ0a4cf8ZCCNGmlPnLWH1wNQcOHSDZk4zVagVgVfYq/rP+PwBM6TOFrrFdWZK5pMYabrubjPiMJsk36K2vUA2T7NH9KOrdpUnWIYRoO1SrnURbHH0rQDcdx7/g0ikYr80nafMeRn2bg3dgHwDsQRuJZgV9K6LQTQf+KDs7QjmEjFC15inRKdw69FaeXvM0qw+upktMF87qIcM2CiGEEKL5eHavowu5+EwLh5PG0tFhj3QkIUQ7EedUuGOMjSe+DvBhdiopXYfSy7MOd8FWdJsbv7szAIqqYLVU70y2aCpqDY/XRZN5cYSokXTaCNEO+EN+KgIV+EI+DNVgc+5mXt7wMgATu0/k3J7n4tf9tba3h5rmIMFRXH50wvCNN0xuknUIIdoW1WJBq6hEX7MCX0Vpja/JH9iT5PW7SHz6PxRefQ4AisWJHpWMv/wQ2GzYx45Dc2iECB3Xvm/Hvlze73I+2P4BH+74kE4xneib2LdJt0sIIYQQAuDw2kV08e3GMGGTazTpCe5IRxJCtDODUjUu6mfhs+0hXjrUj4fSSogv30tszlqKrBNQnanEOCyo+NCNn0YmsFqCuEI6qQ5/tcfrZHUi3TZCHE86bYRoZ3YX7uY/6/6DYRqM6jyKK/pdgRKhsZH7v78Yiz9IXr9u5JzWOyIZhBCtU8hXQajCU+Nz2UMzSF6/iw7bM7EcysEX7yZk0TFUd1Ubw17vH0BndT+L7NJsvjn0DS+te4mHxz1Moiux8TdECCGEEOIHxuEdRG2fCwqsUYbQvUtypCMJIdqpywdb2HYkxL4ihf8UjOCeuHIclXnEHVqJN/YiFN1HRfYeAr6fLgC2WjU0t53y0kp0vf5OG4vVRnR6X6TXRojjyaCoQrQj2WXZPPftcwSNIIOSBzF98HRUJTJfA5ZKP/3fXwLApunnyqSaQohGU5EUR1GPVBTTJG3NjgbVUBSFawddS7fYbniDXv697t8E9WAjJxVCCCFES6VpWrOuz+LNp8O6V1AVk02h7nTq0VMOkYQQEWNRFX4xXMVpMTnstTI7MJ6QNRotVIlr79eYehA9GCAU+GnRAwGMYx6rcwkGIr2ZQrRY0mkjRDtR5C/ihfUv4Av56N2hN7cMvQVNbd4DkZ875ZOVOEq9lKZ1JHPCqRHLIYRom7JH9wcgZdNebJ7KBtWwaTZuH3Y7UdYoDpQe4IPtHzRmRCGEEEJEgKciQF5RRZ1LcXkQxeamuDxIXlEFnoqmPbGohipJWPcSDvwcCCXi6DUSh1V6bIQQkdXBpTDllABgsjbfxSrHeAzVisVbQGDtHDDDHAJNCHHCZHg0IdqBcn8572W+R3mgnK6xXfnl8F9i02zNtn6LakFTNGyaDU3RcJgWBr+1EIDt08/DZnPW2d6u2VHlMjMhxAko7ZpEaVpHYg/mk/bNdnImn96gOh2cHZhx6gyeXfssS7OW0iexD2emn9m4YYUQQgjRbCp8IXZmFREMGbW+JhgIkJuXS3KSicvloE+3DkS7muj4yTSIW/8/YkOFlBguyoZeR5qaj7/y+Hn3hBCiufWMNziza5AlB2x8fCCB1IwxZBQuQz+wCXsQ/DG9Ih1RiDZJ7rQRoo2rDFYy67tZFAeKSXAmcNeIu3Ba6+4kaUwW1UJfSyoDfbGc4nWQWFDBqM82EJ1TSDA+Bsek8xnoi61z6euPIVGNRlMid2eQEKKVURQOjB0AQOqG77F4G3a3DcCApAGc3+t8AP678b98X/h9o0QUQgghRGQEQ0adSyBk4AuECPzw300pescnJHr2EDA1lsZPYfSp6U26PiGEOFGjO4XoHR9CNxVez+pCaaeRADhzNmEvPxThdEK0TXKnjRBtWMgIcdf8u9hfuh+n5uSOoXcQY49p1gyaomH3+gmtXI4SMtBdSSS++BoAOUNPoXLl4nprOOKT0IacjhKh+XeEEK1TcY9UylM74M4pInnNVoyLezS41oW9L2Rv8V52Fuzkzvl3suG2Dc3aAS6EEEKItseZvYZOR1YA8LkygeFjRwAy3JAQomVRFLgoI8B/t6gU+VT+d7g392WAvucbYnPWUmQ9k5AjPtIxhWhT5AyoEG2UaZrcPf9uFu5fiFW1ckW3K0iOSo5YnpDPS6jCg3XzVqJyCtCtGgcHdSNU4al/8XkjllsI0Yr97G6b5LXbUSoafreNqqjcfOrNxNhj2FW4i9989ZvGSimEEEKIdshesp/U7z8E4OvgENLHnI2mySkaIUTLZLfAZaf4saom+4tgrn8EQXcqiqkTd2gVaqjhx1pCiOPJXwRCtFFPrHyCF757AQWFXwz5BWlRaZGOBIB7yWoAcoZkEHLaI5xGCNHWFfZKw9MxDi0QJHrltydVK8Yew61DbwXguW+f49NdnzZGRCGEEEK0M5bKIpI2vIIFg83BrtiHT8HlsEY6lhBC1Kmjy+TCjAAAX2wqYX3U6YRsbrRQJXGHVoEhc3EJ0Vik00aINuitzW/x0KKHAPj9Gb9naMrQCCeq4jpcgGPPfkxF4dCIvpGOI4RoDxSF7LH9AXCvWIPqD55UuQFJA7hl6C0AzPhkBofKZAxnIYQQQoRPDflI+O7fOM1KskMdyOl7NR07REc6lhBChKVvgs6YblX//nCXg30dTsdQrVh9xbgOrwNThngUojFIp40QbczX+7/mpk9uAuDXo37NTUNuinCin6Su2gRAfv/u+GOjIpxGCNFe5PfpSmVCLGqlj5R1O0+63m/G/IahqUMprCxk+sfTMcymnaBYCCGEEG2EaRC77n/EBgsoNZys7zyN7l2TIp1KCCFOyKQMhVM6uQjoCm/vSyAveRQmYC/JhNzvIx1PiDZBOm2EaEN2Fuxk6ntTCRpBrux/JU+e82SkIx3lzC8mfvt+AA6PHhDhNEKIdkVVyTl9CACd1mxDDZzc3TY2zcY7l72Dy+ri6/1f8+zaZxshpBBCCCHauuitH9HR+z0BU2Oh+1L69OsR6UhCCHHCNFXhtnNSiXOYFPtU3jvUlfLEH87z7F+LpaIwsgGFaAOk00aINqKwopCL3rmIUn8pY7qM4bVLX0NVWs5HvPPSDShAZf/eVCR3iHQcIUQ7UzSgJ6EOcdi8PpK/O/m7bXon9ObJSVUd479d+Ft2Few66ZpCCCGEaLuse5fTKb9qfs/52ln0G34aiqJEOJUQQjSM22lh2kADi2qyr0Tj8/IBBGI6g2ngPrgaJeSLdEQhWrWWc0ZXCNFgAT3A5R9czp6iPXSL7cacq+bgsDgiHeso28EcOm7eA0DZxHERTiOEaI9MTaV8wlgAOi3fiHKSd9sA3DHsDib1mIQv5GP6x9MJycSbQgghhKjJkR10zfwEgCXGMHqMPRtNlQ4bIUTrluqGC3oGAFidY+M7+2hwxKCFKonLWQMyjLQQDSadNkK0cqZpcufnd7IkcwnRtmg+u/ozkqJa1rjIKW98hGKYlPRMI9ilU6TjCCHaKe9pg/C7XdjLK0j4bOFJ11MUhVcveZU4RxxrD63lryv+2ggphRBCCNGWGMU5dNn2BppisknvSdzYy7BbtUjHEkKIRtE/UWdUp6oL4j763klu2pmYioatIp/ogq0RTidE6yWdNkK0cv/65l+8tP4lVEXl3cveZWDywEhHqiYqp5AOny8BIGf8qZENI4Ro3ywWDo0dBEDK/z5Aq/SfdMm0mDSePa9qTptHlz7K5tzNJ11TCCGEEG2Dr6yIDt++iFPxc8DoiHL6TcS6HVgtao2LRVOR+2+EEK3NmV2DdI/VCRoKL26JozB5OABRRbuxlx+McDohWifptBGiFZu3ex73f3U/AH+f9Hcu6H1BhBMdb8D/5qGGQpR274SnS3Kk4wgh2rncU3vhi3djKyim77snf7cNwDUDr2FKnymEjBA3f3qzDJMmhBBCtEN6pYdgSd7RxZtzgMPvPEY8ZRQZ0Whjb6RPsoXOLn+tS0d7JVbVkLluhBCtiqrApb38xDtMiirhzUM98cT3AiAm5zs0f1mEEwrR+kinjRCt1Na8rVw9+2oM0+AXp/6CX436VaQjHSfqSBG95iwDIHvC0AinEUIIMDWN7InDABjw33nYyrwnXVNRFJ47/zniHHF8d/g7nv7m6ZOuKYQQQojWxfBX4Du0C1/WNrx7N7PutX+SZOTiNWzkpZ2Jw3OI8r2b61x8h/aAHpJOGyFEq+O0wrT+QWwa7C/V+NQ7lIAzEdUMEXf4G5AL24Q4IdJpI0QrlO/N56J3LqI8UM6Z6Wfy3AXPtcg/7Ie+Mg8tGKL8tAGU9egc6ThCCAFA/uAMKnt0wV5eweA3vmyUmqnuVP5xzj8A+N3i37G3aG+j1BVCCCFEKxIKEQr6Wbd4MWl6NkFTI7PjOOLdDkKBQP1LMBjpLRBCiAZLjjK5dkjVv9ccsbPGPhZds2MJlOHOk2GkhTgR0mkjRCsT1INc+eGVZJZkktEhgw+v+BCbZot0rOPEZOdxyqerADh8yzURTiOEED+jqhy+/ToABrzzNc6C0kYpe9OQmzir+1lUhiq55bNbME2zUeoKIYQQonUwTJOVy9fT3b8Tw4TDKeNITu4Q6VhCCNFshqTC6V2qOqA/3h/D/riRALhK98n8NkKcAOm0EaKVuf/L+1mSuQS3zc2n0z4lwZUQ6Ug1GvrSPFTd4ODYQXgH9410HCGEqKb09OHkDcrA6gsw9JXPG6Wmoij856L/4LK6WJy5mFc2vNIodYUQQgjR8hmmyVdLt9KvYh0Aecmj6N2ne4RTCSFE8zuja4iMOJ2QqfBaVleK404BIObIOtTgyQ9PLUR7IJ02QrQi/9v4P55Z+wwAb0x5g74dW2ZnSNz+HDK+WAPAxjumRDiNEELUQFFYf9dlAPSZsxz3oYJGKdsjvgd/nvBnoKqT/XD54UapK4QQQoiWyzBMPpy9mEHlywEojB/AgNMGRziVEEJEhqrAxb38dHAYlAVU/ps/lICjA6oRJPbwGjCNSEcUosWTThshWom1h9Zy+9zbAfjjGX/kkj6XRDhR7Ya9+CmqYbL/zCEU9pery4QQLVPusL5kj+qHFtI57d+fNVrdu0fezYjOIyj1lzLz85kyTJoQQgjRhhmGyZtvfcGpRz7GohiUubvTe+SYSMcSQoiIcljg8lP82DSTrHIrc0NjMVQrNl8RUQXbIx1PiBZPOm2EaAWOeI4w9b2p+HU/l5xyCb8743eRjlSrpC376LFoPYaq8N3tF0c6jhBC1OnbmZcC0Gv+GuL3HGqUmpqq8crFr2BVrXy882Nm75jdKHWFEEII0bIYhsnrby9kSOYbOJQgFa5Uuo+eiKIokY4mhBARl+gyuSQjAMDSvHg2O4YDEFW0E5s3N5LRhGjxpNNGiBYuoAe47P3LOFR+iL6JfXl9yuuoSgv96JomI5+uOjm5+8IxFGd0jnAgIYSoW0Hfbuw7ayiKaTL8+U/CaqNQ/4mYAUkDeHjcwwDM/HwmRZVFJ5VTCCGEEC2LYZj8950lDN7/GtGqH5+7M13GX4SiWSIdTQghWoxeHXTGd6nquHn9UE/yXT1QgJicb1FCvsiGE6IFk78mhGihiiuLKfOX8fCih1mVvQq3zc1z5z9HcWUxxZXFYdVQFZXKUGUTJ/1Jt6WbSN24h5Ddyne3X9Rs6xVCiJPx7R2XkL54A+nLNpG8aS+5g3vW+lqLaiFkhMgqyaq37jUDruHtLW/zfdH33D73dp6c9GS152PsMcQ74086vxBCCCGal64bvPjWMoZn/o9YrZJAdCo9rvwVwdwsTD0Y6XhCCNGijO0c4ohXZXeRhefzRvBQfAG2YBnR2auhz4hIxxOiRWpVnTYrVqzgqaeeYs+ePSQkJHDttdcyY8aMOm89njt3Li+88ALZ2dl07tyZW2+9lSlTqk+MPn/+fF5++WX27dtHTEwMY8aM4b777iMxMbGpN0mIWpX5y/jzsj/z9ta3UVD4xdBfcKD0AAdKD4Rdw213kxGf0YQpf6KEdEY+8xEAm689m4okOREphGgdStNT2HXxWPp+vIJR//qAT179LdTyt4WmaHgCHrYXbMcf8tdb+6r+V/GX5X/hg+0f0CO+B30T+wJgt9gZnTZaOm2EEEKIViYY0nn6f8sYc/gNEjUPIVciGTP+H6YeRLprhBDieIoCF2UE+O9mlSKfjfd947jWMh+bJwdj32qU1MsjHVGIFqeFjrF0vI0bN3L77bfTo0cPZs2axUUXXcSTTz7JSy+9VGubBQsWcP/99zN27Fiee+45RowYwYMPPsi8efOOvmbevHn86le/on///syaNYt7772Xb775hhtuuAG/v/6TMUI0lU1HNvG/Tf8D4OJTLqZPYh/8uv+ElkAo0Gx5+3y8grgDuVTGu9k0/dxmW68QQjSG726/mKDTTvKW/fT88rt6X+8Phfc93CW2C+O7jQfgfxv/hyfgqXoujA4fIYQQQrQsPn+Ix19axvBDb5OilaI74+h+0//D4paLMIQQoi52Dab29mNRTb4tTWCTdQgAypZ5BAoPkldUcUKLp6L5zncJEQmt5k6bWbNm0bdvX558smpokfHjxxMKhXjxxReZPn06DofjuDb//Oc/mTx5Mg8/XDWm/Lhx4ygtLeXpp5/mggsuAODFF1/kjDPO4E9/+tPRdt27d+fKK69k8eLFTJ48uRm2TojqCioK+OXnvyRkhBiSPITzMs6LdKQ62Uu9DH+hai6IdbdcQDDaGeFEQghxYioTY9l4w7kMf/FTRsz6iMwzBqM7bI1S+9I+l7LhyAZyvbl8secLLjpFho8UQgghWhtPZZDHXlrOhKIP6GItwrC76Tb9UaxxSZGOJoQQrUJSlMnk7gHm7rXz2pF+dE/NIdafg2/Rvzk47G6CRv1zhwJYLSp9unUg2tU4x2tCtESt4k6bQCDAmjVrmDRpUrXHzz33XLxeL+vWrTuuzcGDB8nMzKyxTVZWFpmZmRiGwdixY7nyyiurvaZHjx4AHDgQ/jBUQjQW3dC59qNrOVR+iOSoZG4ccmOdQwC2BMNe/ARHqZeinp3YMXV8pOMIIUSDbL5uEp7keNxHihj4zqJGq+uyupjWfxoAX+z9giOeI41WWwghhBBNr9wb4A/PLeGMog/pac3DtDrpct0fsCWmRTqaEEK0KoOSdAZ1DGGg8kLhGAyrEwoyidr9BcGQEfYiRFvXKu60yc7OJhgMkp6eXu3xbt26AbB//37Gjh1b7bm9e/cC1NkmPT2dBx988Lj1LVy4EIBevXo1KK9pmlRUVDSobXtQWVlZ7aeo7i8r/8KXe7/EYXFw+6m3o5kagUDDbvsMqkF0QycYrBpduTHqHDvkWuLug/SdvQyApfdejt/QIaAffV61qOi6jhEyqn6aVT91XSdcRsjENMyqdiEdXYlcnWNrALXWCemhaj/rqlFXnXBzRKpOXTXCraP+sH/UtI/9qK798GgdQwWshPQQZg1ZwslT3/aEUyfcGs1R50Rq1Fanrhq17ecnWifcPA2pcWwdpbb9TYVVt1/EOY++zpD/zmfr5OFUJMRUqxPOfliTAQkD6J/Yn20F23hj0xs8MOoBgsFgg/5ekN+jzU/e8/qZptniLzIRQoiGKK8I8NTrq7g4+BkZ1jywOuh8ze+wp3SPdDQhhGiVzu0eIMejklMZxRfm6ZzPV8Tt+4ry+D74YrtFOp4QLUKr6LQpLy8HIDo6utrjUVFRAHg8nuPa/PjYibSBqrtrnnjiCfr27csZZ5zRoLzBYJAdO3Y0qG17kpmZGekILc7KvJU8vvZxAB4Y+gDWSis5pTkNrheIClDprqSkpASAwsLCk6qTn5+Px/ezz45pcuETb6EaJpvH9OW71GjIqZ7XZXPhsVqpLCvDGtIJOoJ4ysvxB8OfzyFkjyYQDOApL8dbWkrIHopYnWNrVD1Wdx2vx1tvjXDqhFMjEnXqqhFuHVvIxOnxkBvMpSJQ80nsWvfDn3HZXGCNosJbQcBbVkveuvPUtz3h1Am3RnPUOZEatdUJp8bx+3nD6tSXpyE1jq1j+gNEV/oo85RRGax+Ev7boRkM6NWZTt8f4rR/fcjcX11W7XnVpRKMDeIp8eD1ewnpIQJ6eJ03ZyScwe7C3ewp3sP87fMZ6B6I55DnhDqff05+jzY/ec/rZrPJEBVCiOblqQhQ4QvV/8IfKAoEgtV/72qqgqoe0+lsqDhsFir9Ib5c8T1Xq/PpYc0Hq5NO1/4eR+fejRFfCCHaJasGU0/x898tDhbkpTK420A6l28hZftbZA2/D9Nij3REISKuVXTaGEbdt72p6vGjvDWkzd69e7n55puxWCw888wzNb4mHFarlYyMjAa1bQ8qKyvJzMwkPT0dp1PmPvlRVmkWf1z4R0xMfjH4F1w/7HqWZC7BF/I1uGasIxany0lcXByeIx4SEhIadELlxzodO3bEHXIffbz3gm9J33GQoMPG+t9cTWry8RNwOiwOogPRWGNisARDWG1Wot1uHPrx81DVxhntxma1Ee12YyGE0+qMWJ1jawC11gnpIbweL1HRUVg0S5016qoTbo5I1amrRrh1rC439uhokm3Jte7zte2HP6caKnjAFeXCaan5iu/68tS3PeHUCbdGc9Q5kRq11amrRq37+QnWCTdPQ2ocW0eLjiUtIQ23L5qQcXyNkvtn0um2hxm8aAPWK67AO+CnEzN2i52OFSZnRHcn5Arhd9nZFjhE0AjWmyGVVC4wL+Dj3R/z5eEv+W3Ub+nd7cRP+sjv0eYn73n99uzZE+kI4gcrVqzgqaeeYs+ePSQkJHDttdcyY8aMOu+Emjt3Li+88ALZ2dl07tyZW2+9lSlTplR7zfz583n55ZfZt28fMTExjBkzhvvuu4/ExMSm3iQhalXhC7EzqyjsoXKcdgupiVFH/1tTFTrFqmh69b8/dbuOXq4ye9kurrUsoLs1H2xOki6+Gy0qjmBJXvXCioJxAnfgCiFEe5fgNLmwt8FHOzRmHejPH5OycFQW0nHPp+T1uSLS8YSIuFbRaeN2V52c83qrX8Vb2900DWmzZs0a7rrrLlwuF6+99hpdu3ZtcF5FUXC5XA1u3144nU55n37gC/m4/rPrKfYVM7zTcJ698FmOeI5gtVox1IaP1Wm1WNFUDavVClRdAduQTpuf1/kxj73Ew7hn5gCw8abzCHRJpqbKVs2KpmuoFhXN0FAVFU3TMJXwt0u1KCiqgqZpaBYNTYtcnWNrAPXWsWiWo6+trUY4derLEak6ddUIt45qqXq+rn2+pv3wuDpGVWe7RbNg1JAlnDz1bU84dcKt0Rx1TqRGbXXCqXHsft7QOvXlaUiNY+tYHDaslX7MNasIVhx/t04JkHdqb5I27Kbr/3uKzbdNgR+uwLVYnJhRyQTLD4HNhmvsOBwOB4oe3rBQ52Scw7oj68guy+aJ1U/w0VUfhb0Nx5Lfo81P3vPaydBoLcPGjRu5/fbbOe+887jnnntYt24dTz75JLquc+utt9bYZsGCBdx///1Mnz6dcePGsXDhQh588EFsNhsXXHABAPPmzePXv/41V111Fffeey8FBQU8/fTT3HDDDXz00UfY7XJFrIicE5nfwGo55m8tVUHTfVQe2Eko+FOny6FSk9lbdG6K+pp0SwGmxU78iIswfV58WduOq6vYHVjjU09uQ4QQop0ZkGSSq3Rg5fYiXisbw63OBcQd/gZvYn+8if0iHU+IiGoVnTZdu3ZF0zSysrKqPX7gwAEAevbseVyb7t2rxpfNysqiX7+fPug/1vh5m7lz5/Lggw/SvXt3Xn75ZZKTkxt9G4Soy93z72ZdzjoSnAl8eOWH2FvBraCj/vUhzuJyinp0YtP0cyIdRwghTljIV0Goouah9vaOG0CH7fuJPpRP4jebODKk6g7akEXHUN1V7Qz7Cf8hpaka1w26jr+u+Ctzds5h4b6FnN3j7JPcEiGEqDJr1iz69u3Lk08+CcD48eMJhUK8+OKLTJ8+HYfj+DtM//nPfzJ58mQefvhhAMaNG0dpaSlPP/300U6bF198kTPOOIM//elPR9t1796dK6+8ksWLFzN58uRm2Dohmk4oGCD0w/yfh8pVPt6hcHPUIrpZCtFVG45B52Jxx2PqNd9Zq4SszRlXCCHajEtHpXCgMMD2XFjrHMRINpG84z2yRt6Pbqt5hA0h2oOGjf/VzOx2O8OGDeOrr77CNM2jjy9YsAC3282gQYOOa9OtWzfS0tJYsGBBtce//PJL0tPTSUtLA2Dp0qU88MADnHrqqbzzzjvSYSOa3X83/JeX1r+EgsLbl71N19iG3+XVXDqv2cEpc1djKgrL/u86DGur6P8VQoiwBaOdZI0bCED64o1YKsOfP6s+6XHpRztqbp97+3Hz6gghREMEAgHWrFnDpEmTqj1+7rnn4vV6Wbdu3XFtDh48SGZmZo1tsrKyyMzMxDAMxo4dy5VXXlntNT169AB+upBOiLYgs1Tl0x0Gt0Z9ebTDpiz9DFR3QqSjCSFEm2S1qNx0UX+sFpX3iwZQbEnEEvSQtGs2/OwcsBDtTas503rHHXdw0003cc8993DZZZexYcMGXnnlFe677z6cTicej4c9e/bQtWtXOnToAMDMmTN56KGHiIuLY+LEiSxatIj58+fz1FNPAeD3+3nkkUeIiori9ttvP24s7pSUFFJSUpp9W0X7sfHIRn75+S8BePTMRzmnZ8u/Y0XzBRj32JsAbLvyTPIGHX+nmxBCtAWHTzuFlI17iSooJX3JJvacN6LRak/tM5UteVvYW7yXvyz/C3+e+OdGqy2EaJ+ys7MJBoOkp6dXe7xbt24A7N+/n7Fjx1Z7bu/evQB1tklPT+fBBx88bn0LFy4EoFevXg3ObJomFRUVDW7f1lVWVlb7KY4XDAYJBgIEwh0eTTUwdOOnNoaKbtcJ6Qa7CmHp3iAzoxfSUSsnqFgpSB2DanGj6zqBQO1z1qiqBdUwCAQDmKGf7sbRdR09pBMywjvxaOg6JiZGSCek62G1wVSq5asty7HqyxbSDQzDRA8ZR7Noiolp2MLeppBuYBoGpmGG1Ub/YT26obfwbTIxdJNAoP45DWvLV1OWY4WVTTfQdb3658BQCQaDJ/T9GgqFfihXtQ+G49h84WxTONtVY51j9vP6/LjPGHp4+97JblN9+er8jjD0o/+uy4l+nmrLFu7n6Wi+GtZV2/tyop8ndAND10mMdXDmqZ346tuD/KdwFL+J/Rx3/hZKD35DSfJpx7drwD5+LPkdGznt+b03TTPsYaVbTafN6NGjmTVrFs888wwzZ84kOTmZBx54gBkzZgCwbds2pk+fzuOPP87UqVMBmDp1KoFAgFdffZXZs2fTpUsXnnjiCc4//3wA1q9fT35+PsDROj935513ctdddzXTFor2priymMvevwxfyMf5vc7nkfGPRDpSWIY//zExhwrwJMfz7S8vjXQcIYRoMqamsufc4Qx+ayGpG74nd1APQt26NEptp9XJo2c+ym1zb+OJlU9w9YCr6Z/Uv1FqCyHap/LycuD4uTujoqomXf9xbs+fq22+z7raQNXdNU888QR9+/bljDPOaHDmYDDIjh07Gty+vcjMzIx0hBZJ0zQUm5vcvFx8gVBYbWKjHSTF28nLz6fSH8BhsxCv2Fl/wMemgzp3xSwiTq0goDrIihtCMKBiNcqIdUF5qR/DqLlzyBYVQ6I7ifyCAoK+qpNQqqqiaHbKysvCnnNHs1owdQNvhZfS0vKw2lgtarV8NWU5VjjZgiYEgwHKPeVUeKtOjDrtFtxRFsrKywmG6u9UqqoRIhQMhN0GquYm9ni0FrxNASorvZRUlNa6T9SXr6Ysxwonm9XuQPV4yM3zH/0cOGwWUuMV8nPK6+0IgKrPUqKr6vSg1+sNe389Nl842xTOdtVU59j9vD62qBgSY5LxVnpP6DPY0G2qL19d3xE/zsVd2+/cHzX089SQ74if56vp/avtfTnRz5PV7sBVUYHVVkmcI0CXjjay8zvwhX8I59vXk7z3U/YHovFZY6q1O9F9vC7yOzZy2ut7H+5c462m0wZg0qRJx926/6ORI0eya9eu4x6fNm0a06ZNq7HN6NGja2wjRFMzTIMbPr6BfcX7SI9L540pb6AqLX+0wpS12xn09iIAlj98HcGo48dFF0KItqS0WzJHBvYgZcs+es1fw45bOzda7XN7nsslp1zCJ7s+4da5t7L8puWt4neBEKJlqu8klqoe//3SkDZ79+7l5ptvxmKx8Mwzz9T4mnBZrVYyMjIa3L6tq6ysJDMzk/T0dJxOZ6TjtEjF5UGSk8yw77SJclhwOV0kdexIIGRgs6jsPFLIjkN+7opZRJQaIGB1k58yiqBPJzo6GrvVQnR0NC57bK11VYcLh8tFx8TEaleuV/h1YioI+4r4qKgoFE0lyhVFuKPZW1SlWr7ashyrvmyOaDdWqw13tBurpWrOHrtFxWa1EeN2h7VNVTUshMJso+s6Ho+HqKioFr5NNlRnFPboE5uL9uf5aspyrHCyWWx2oqOjSTbjjn4ObBaVxIRE4t2pYWcLlRXgpWofNMPc947NF842hbNdNdU5dj+vj+pw4XA6iXJGEeOOCfsz2NBtqi9fXd8RUR6dktJyoqOj0TSt1nWc6Oeptmzhfp5+zFfTZ6q29+VEP08Wmx2Xy4XF6SSpY0fOdsczZ/l+vizvx2D7YTobRzi1ZBmZA26Gnx0nNWQfP5b8jo2c9vzeHzvKV11aVaeNEG3FX1f8lc92f4Zds/PhFR/Swdkh0pHqpZaWMfYPLwOwfep4sscOiHAiIYRoHvsnnkrC9weJzishec02mNR4HTezzpvFov2LWJW9ipfXv8ytp93aaLWFEO2L2101We+PV+z+qLa7aRrSZs2aNdx11124XC5ee+01unY9ubkYFUXB5XKdVI32wOl0yvtUC4+vAqvNBmqYw6PZLKiaerTN9v2FHNq0npkxS7ArIQKODpSknQ5o4CtF0zQ0i4amaXVeGatabGhq1clKU/1p2BN/KIBm0UAP7+SqqmkoKKgWDUsdJ29/TtOUavlqy3Ks+rJZNBVVVdAs6tEsmkVDUZWwt8miqSiqekJtADRVa+HbpKBqSthXS9eUr6Ysxwonm0VT0TSt2ufAalGxWq0n9L1RUVF1elBTtWonx+tybL5wtimc7arx/9Mx+3l9ftxnVO0E972GblM9+er8jlB/3Ma6P/cN/jw18DviaL4a1lXb+9KQz5OqaUe/l12qhcmj0vlg0fe8WjKKh+LnEV26j6S8tZR0GX+0XUP28drI79jIaY/vfbhDo0G4l24IIRrNwn0L+d3i3wHw7PnPclqnGsbnbIE6P/JXoo8UUdoliW9+dVmk4wghRLMJRjnYP/FUADovWYdWXNpotbvEduEvE/8CwANfPcARz5FGqy2EaF+6du2KpmlkZWVVe/zAgQMA9Ox5/DyE3bt3BziuzY///fM2c+fO5eabbyY5OZn33nuvxnpCtCbrd+ZRtHklt7m/xq6E8LuSKOkyHlM7sRPxQgghGk9CrJNxQzpTYMQwxzMUgMS987B5cyOcTIjmJZ02QjSjg2UHuXr21RimwYwhM/jF0F9EOlK9LKqFHgvWEj97HoaqsOLPt6K5Y7Fr9rAX9QR6koUQoiU6MrgnpWkd0YIh4j76HMwwJ/4Mw8zhMxnWaRil/lLuXXBvo9UVQrQvdrudYcOG8dVXX2H+7DtqwYIFuN1uBg0adFybbt26kZaWxoIFC6o9/uWXX5Kenk5aWhoAS5cu5YEHHuDUU0/lnXfeITk5uWk3RogmZJomqzYfxvL9Ym6MXopFMfDHdKGk81hMVQYjEUKISOvXvQMZaXGs8Pdmt56GaoRI2f42GCc3f40QrYn8RSJEMwnoAa744AoKKgoYkjKEZ89/NtKR6mVRLZx6UGfQH18EIO/GK0ntfRqpvvBraBYbCaqdQ4oGyC9YIUQrpSjsPn8kp73yOc5de0jcmkrB8H6NUlpTNf5z4X8Y9tIw3t36LjcMvoHJGZMbpbYQon254447uOmmm7jnnnu47LLL2LBhA6+88gr33XcfTqcTj8fDnj176Nq1Kx06VA3PO3PmTB566CHi4uKYOHEiixYtYv78+Tz11FMA+P1+HnnkEaKiorj99tuPG4s7JSWFlJSUZt9WIRrCNE0+Wvw9KfvncVbUdgD09JF4ortDMBThdEIIIaBqCKkJp6WRV1zBG2WjeCT+MxzlB0nIXEhhj3MjHU+IZiGdNkI0k/sW3Mc3B78hzhHH7Ctn47S2/Mm2bH6dU379GJq3En9Gdw50TyC06IsTquGIT0IbcjqKTK4thGjlKhNjOTz+VNIWr6P7l2sp7du90Wqfmnoqvxr5K/75zT+5Y94dbL1jK1G2qEarL4RoH0aPHs2sWbN45plnmDlzJsnJyTzwwAPMmDEDgG3btjF9+nQef/xxpk6dCsDUqVMJBAK8+uqrzJ49my5duvDEE09w/vnnA7B+/Xry8/MBjtb5uTvvvJO77rqrmbZQiIYzTJOFq/cyOPczhjozASjKuIDo/qfDvi2RDSeEEKIam1Xj3JHdmL04yLueEdwYvZwOWQvxJvZF75Ae6XhCNDnptBGiGby95W2e/bbqzpo3prxBj/geEU4UnhF/exPXnkyC0S4Kr7qEkL+EkBE8oRohp5x0FEK0HUfGDCZpZza2nDy6z1vJgUumNFrtRyc8yoc7PiSzJJM/Lf0TT0x6otFqCyHaj0mTJjFp0qQanxs5ciS7du067vFp06Yxbdq0GtuMHj26xjZCtCa6YbJi7W4mlH5Chj0XA5XcftPwpQ0nWvFHOp4QQogaJHVwMXpgKis3mwwKZDPUlknK9rc5PPr+SEcTosnJpe9CNLGteVu55bNbAHhk3CNc2PvCCCcKT+/PVtF7zjJMRSFz2mSMWHekIwkhRMSZmkrxFRdjKgqJW/YSt2R1o9WOtkXz3PnPAfCP1f9g45GNjVZbCCGEaK9CusHKVZu5qPw9Mqy56Jqd3NNupzzltEhHE0IIUY/BvRJJT43hA+9IykwXtop84r+fG+lYQjQ56bQRogmV+cu47P3LqAhWcHaPs3n0zEcjHSksSVv2Me6xtwDIufkqPBldI5xICCFajmBaKodGDwCgyxMv4igsbbTaF/a+kMv7XY5u6sz4ZAZB/cTubhRCCCHET4Ihne9WrOEK3wekaKX4rTFoFz6CL6FXpKMJIYSgav4aVVGwWtQaF5tV49xR3VAd0bzlGQ1A7IHl6Ae3Rji5EE1LOm2EaCKmaTLjkxnsLtxNWkwab099G03VIh2rXlG5xZxz/wtowRAHJgzlyE1XRDqSEEK0ONnjh+BN6YC1pIzRf/4fmGaj1X72vGfp4OzAhiMbeGKlDJEmhBBCNIQ/qLN72UKmheYQq1ZS7kim6PT7UDqkRTqaEEIIQNU0oh0azlApqQ4fnV3+GpeMeJ3rJ3RiV6gzK3y9AfB//W/8uZkES/IIluShV3oivDVCNC7ptBGiifxj9T+YvWM2VtXKB1d8QMeojpGOVC/NF+Cc+5/HVVhGYUZnlv/5VlDla0IIIY5lWjS+v3wihsVC1yUb6D238YZJS45OZtZ5swD409I/sTVPriITQgghTkSlL0j+sg+ZwpfYFJ0idy9yR9yN7oyLdDQhhBA/UDUNQn4qD+6ifN9myvfWvnT07uWMbjqfVJxGvu7G8JZQMP/f+LK24Tu0C8NfEenNEaJRydlYIZrA4v2L+e3C3wLw9OSnGZU2KsKJ6qfoBhN/9yoddxzAFxvFl//4JSGXI9KxhBCixapISSDnF1UTd4/5+3u4DxU0Wu2rB1zNxadcTNAIcuPHNxIyQo1WWwghhGgrFDhuKJ2g3w8rXmGishaAI0mjKR15G5rDhUVTUdXqw/CoSmS3QQgh2jsjFCQUCNS7jErxkxqj8qb3dAxTwX9oN5UHtkFIjpVE22OJdAAh2pqteVu54oMrMEyDqX2ncl7GeWSVZJ1QDVVRqQxVNlHCGpgmo//5Pt0Xb0C3Wvjyydsp75yIvfkSCCFEq5R77aVYV39D0qY9TPjdK3z2n/sxLSc/FKaiKLx4wYssy1rGupx1/G3l33h43MONkFgIIYRoO2z4SXX40I2qYUpLiorRlv+PrmouuqlQ1vt8OvQfB4SAEFZLEFdIJ9XhRzdMNE0lyqpSpkjPjRBCtHSqApf08vPy5kS+qBzE+a5NeLetwNqhc6SjCdHopNNGiEYU0ANMnzOdwspCusR04dwe57I0a+kJ13Hb3WTEZzRBwpoNeuNLBry3GIDFf7qJI0N7N9u6hRCiVbNoLHvsNi6+8nekbN7HaS/N5bs7LmmU0qnuVJ6e/DQ3fHwDf1zyR87vdT5DUoY0Sm0hhBCiLTADlVRk7yTg81NeUkpM1lK6qh4qTStFnU/H4YilfO/mo6+3WjU0t53y0kp03cTuisad3k1GhBZCiFYi2gaX9g7wzraB9LYeIYNcyjcsIKrPyEhHE6JRyZ8mQjSiXy/4NRuObMBldXHbabeBAn7df8JLIBRotsy95q5m1DMfAbD63ivYN2lYs61bCCHaAm+njix75DoATn11Pqnf7Wq02tcPup4pfaYQNIJc99F1+EK+RqsthBBCtAV6MEBZTjYpB76kg+qhyIgmr/NELO6E44bW0QMBjODP/rsZj7uEEEI0jp7xBuf00njdczpe00aoNJ/Sbz6JdCwhGpV02gjRSN7Y9AbPffscALcOvZWOUR0jnKh+3Ret54w/vQbA5mvPZsu1Z0c4kRBCtE77zhnOzkvGopgmE3/3Ko7i8kapqygK/77w3yRHJbMtfxv/9/X/NUpdIYQQoq2oyN5N1/wVOJQgB4wkyrpPwOF2RzqWEEKIJnRxP4WkBDdve8YAUL5xIRV7N0Q4lRCNRzpthGgEm45s4ra5twFw94i7W8XwNV1WbGHiIy+jGiY7Lx7LN/dcFulIQgjRqq26/yqK01OIyi9h4iOvoOhGo9TtGNWRly9+GYB/rv4nyw4sa5S6QgghRGtmGjoHv3qbToXfoikmW/QeGBljcTpkZk4hhGjrNFVh5lgr+5SuLPOdAkD+Z7MIeYojnEyIxiGdNkKcpOLKYqa+P5XKUCWTMyZzz8h7Ih2pXp3W7mDSb/+NFtLZO2kYyx+5DhnIWQghTk7IaWfhE7cRdNhIW7uD0/7zWaPVvrD3hdwy9BZMTG75/BZKA6WNVlsIIYRobfTKcna/8jtcB1YDsEwfQmzvU3FatQgnE0II0Vw6RqvcNsrGJxXDOBSKR/eWkv/pM5hm41w8J0QkyVlaIU6CYRpM/3g6+4r3kR6XzltT30JTW/aBQudvtjP53uew+INkjRvI1/9vBqYmXwVCCNEYint2Ytn/XQ/A0Fc+p8uKLY1W+5/n/pNeHXpxsPwgf978Z0zTbLTaQgghRGsRyM9m74v3Y83bhd+0MI8z6HFKBnaLEuloQgghmtmwLhrn9HPymmccAVOjcv9mSr/5NNKxhDhpcqZWiJPw2PLHmLt7LnbNzuwrZ9PB2SHSkY6yqBZsmg1N0bBb7LhsLnp+u4fJv67qsMkeP5hlf78bm92FXbPXuqiKHPwIIcSJ2Dt5BNuuOBOAib97lZgDuY1SN9oWzbuXv4tVtbL4yGJe2vhSo9QVQgghGpOnIkBeUcUJL56KQL21vbu/5cArv8VSUUChHs1X8VcxclAacoONEEK0X1cPtZPYpSuzK0YAULTkbXwHd0Y4lRAnxxLpAEK0Vgv2LOD3i38PwAsXvMDQ1KERTvQTi2qhryWVGK9JolnBAF8Mg7/LZ8Djz6MGQpSMG07B//sN/Q0r+Gqvo1lsJKh2CqTjRgghTsjqey8ncWcWyVv2c+6vn+fj/z1IMNp50nWHpg7lz2f8md8u/i0PLn6QCT0nMDhlcCMkFkIIIRpHhS/EzqwigqHwh6exWlT6dOtAtMtW4/OmaVK6eg6Fi99GxeT7YDJ7Mq7h2ondydqwBr2xwgshhGh1NFXhvqm9+M2rftb5czjNnknu7H/Q+eYnsUTHRTqeEA0inTZCNEBmSSbXfHQNJia3nXYbN516U6QjVaMpGnavH33NWnQtBvfXX9Lj4yWopklhv3R2nzUYc/mieus44pPQhpyOgnTaCCHEiTBsVr588g6mTH+M+MwjnPXwyyx4amajDEc587SZfLbtM1bkrWDa7Gms/cVa3HZ3I6QWQgghGkcwZJxQp01djKCf/HnP4922AgVY7jsF35AruGPKEMrychplHUIIIVq3uGgbD94wgj8856WzpZgUTxF5c/5J6rV/QGnh0xgIURMZHk2IE+QJeLjk3UsoqixieKfhPD356UhHqpXuq8Q1fyEZcxajmiY5A7qz7eLRBAOVhCo89S8+b6Q3QQghWq3KxFi+/PsdhOxWuq7ayohZHzVKXUVR+MPgP5AancrOgp3c/OnNMr+NEEKINilUVsjh1/8P77YV6KbC+96RmCOv5dapQ1BVubBMCCHET/p068DNlw3jlfIz8ZkWfAe2UbT4zUjHEqJBpNNGiBNgmAY3fnwjm3M3kxyVzOwrZ2O32CMdq2amSafPlxP3edUdNd8P6s7O80aAKh97IYRoLgX90lnyhxsAGPzmV/T9cGmj1I23x/PmxW9iUS18sP0DnvrmqUapK4QQQrQUvoO7OPTqAwSO7MNj2HmufBLdJ17CDRf0Q5Hhm4UQQtTgnJHdGDX2VN72jAWg9JtP8WxfGeFUQpw4OXsrxAn487I/M3vHbGyajY+u+ogusV0iHalGSkin61+eJXnZOgD2TRjKttF9QA5uhBCi2e07Zzjf3XYRAGP/9g7dlmxslLqjOo/iqXOrOmse+OoBlmY2ToeQEEIIEWnlmxdz+M3fo3tLOByK4x9l5zPhgrO56uxTpMNGCCFEnWZc1B+1+zAWVvYHIO+zZ/Hn7D3udZomw6aJlks6bYQI05wdc/jDkj8A8MIFLzCmy5gIJ6qZ5gtw5m+eJXHe15iKQtEVF3FoVP9IxxJCiHZt/S8uYOclY1ENk7MeeZnEzXsape7M4TO5btB16KbOlR9eycGyg41SVwghhIgE09ApXPg/8j97FvQQmwJd+Vf5eVxz2TguGd8z0vGEEEK0Apqm8sD04WyIOp1tgc4QCpDz/uOEyovwVATIK6qguDyIYnNTXB4kr6iizsVTEYj0Jol2yBLpAEK0Bltyt3D9nOsBuHvE3cw4dUaEE9XMWVDKub9+nqTtmRg2K5lXTcY2cAgUZ0Y6mhBCtG+KwvKHrsWVX0rXVVs5655/UdRrPIzudpJlFf594b/ZnLuZzbmbufidi1l+03KibFGNFFwIIYRofJqqVJuTxmpRwe/lyHv/oHLfRgDmVw7iK/8Q7r3mNM4YmlZjHbnnRgghRE2inVZ+d8sY/u+ZSjqEPiHVU8yRD/6K9cKH2XXIQ0WFj9y8XJKTTKw2W611rBaVPt06EO2q/TVCNAW500aIehRUFHDxuxfjDXo5q/tZ/OPcf0Q6Uo3i9xzi0hv/StL2THyxUXz/9B8p7S9XowkhRFNSVQ27Zg9rsdldLH/yTgr6d8dR4iF56nWw9/jb9MPx81v5XVYXn0z7hI6ujmw4soHr5lyHYRqNtYlCCCFEo9JUhU6xKp1d/qNLajCbitm/p3LfRoJYeLX8DBYFTuU3l5/CmB42giV5xy+l+WiEZLg0IYQQNeqUGM0DM8bxWuVZeA0bgZy9+Bb9m2AwRCBk4AtU/QzWswgRCXKnjRB1COpBrvjgCjJLMukR34P3Ln8Pi9ryPjZdVm7lrIdfwub1UdI1ma9n/Zr0pN4oS2V+AyGEaCqq1U6iLY6+FaCbjjAbxXLoH38keubvcezNwhg/nrKP36OsV1dMzLBKBINBfHYfh72HsQasxNhjSI9LZ85Vc5j4+kQ+3vkxjyx6hMfPfvwktk4IIYRoGqqqoOk+Kg/sJBQMYC0/jPvASgwjSBlRvFg6gUKlAw+c5aS/IwdfVk6NdRS7A9OdLJ02QgghatUnvQM3XDOB/77t4fbohbBvLR1CDrxdz4t0NCHq1PLOPgvRQpimya+++BVLMpcQbYvm02mfkuBKiHSs4/R7fzFj/v4eqmFy+LTefPW326FDB/BFOpkQQrRtqsWCVlGJvmYFvorSE2r7/bRz6Pufj7AcPozzsqtY+srDlHSMDqttMBgkNzeXZE8y0c5oRqeNJt4Zz9iuY3nl4le4fs71/HXlX+mV0KvFDucphBBChAJ+bLlbic7fggJkG0m8WHoG2Jw8PMFOzwQTUw/W2l4JWZsvrBBCiFZr7KBOFJSczVvzK7khejmxB5ZRoUWTo2VEOpoQtZLh0YSoxVPfPMXz3z0PwFtT36J/Uv8IJ6pOCemM/vt7nP63d1ENk10XjeHzZ+/BHyvzGAghRHMK+SoIVXhOaPFpJvm3XIs/zo09+zATZzyK5VAOft1f7+IL+agIVOAL+fCH/NWyXDfoOh4Z9wgAt352K5/t+iwSb4kQQghRNz1I9MHVuH/osFkXzOCpkklYHU5+N8lOzwQ5VSGEEKLxXDK+Jxnjz+WTiqEApO7/nOTy3RFOJUTt5C8hIWowe/ts7v/yfgD+PunvXHzKxRFOVJ29xMN5dz/DwHe/BmDNnVNY+vvpGFa5eU4IIVoLPS6WHbdMwd85GffBfC669e9EHy446br/b8L/44bBN6CbOld+eCWrslc1QlohhBCicWi+Uiwr/oO9JBMThU99w3m9fDQdojT+cI6dtFg5TSGEEKLxXTe5D2a/c1nq6wPAgNwvcRfuiHAqIWomfw0JcYzV2au5bs51mJjMHD6TX4/+daQjVdNhdzZTpj9G2tqdBJ12vvzbbWy6cTLIWM5CCNHqBOJj2P38nyntmkzM4UIuvuXvxO07fFI1FUXhpYte4oJeF+AL+bjw7QvZlretkRILIYQQDecozaLTmqdQi7MJqTZe8pzFooq+JLlM7h+v0jFaTlEIIYRoGoqicM3kvmxPnMR3/u6oGKTtfAtXkdxxI1oe+YtIiJ/ZU7SHi9+9GF/Ix0W9L+LpyU+3qIkte3z5LZfe9AQxhwsp65zIx//9LZkTh0Y6lhBCiJMQTEpkwUsPUtw9lejcYi6+5e8kbdl3UjWtmpX3r3ifUWmjKPYVc/YbZ7O7UA5GhBBCRE7M4TWkrX8Oi78UnyORJ0vOZ1ugE2lunRsG+Yl1tJzjLiGEEG2TqihMGtWdle7JbAp0RTN1Uje9irPk5I6/hGhs0mkjxA8KKgo4763zKKgoYFinYbxz2TtoqhbpWAAousGIZ2Zz9sMvY/EHyR7VjzmvP0xxRudIRxNCCNEIKpPi+fSl+8kd0B1HqZcL7niKLiu3nlRNl9XF3KvnMjBpIEc8R5j42kT2Fu1tpMRCCCFEmIwQSbtmk7LzfVRTJze6D48emcSRUAw94nSm9fXjkFGehRBCNBNNVZgwrAsLrBPZHuiEZgZJ3fgSzmI5VhIth3TaCAFUBiu55N1L2FO0h26x3fjs6s+IskVFOhZQNX/N5F/NYsjrXwKw8YZz+eLpu/DHtox8QgghGoc/Lpp5L9xL9uh+WH0Bzv31c/T9cOlJ1UxwJbBw+kL6dezHofJDTHhtAvuL9zdSYiGEEKJuWqCctA3/Ju7QKkwUtsaM4/EDw6kwrPTraHDFKX5sLeM6OSGEEO2IqioM7ulmUfRF7AqmYjECdNr4H1yFuyIdTQhAOm2EwDANbvj4BlZlryLOEcf8a+eTEp0S0UwW1YKmaHTaeoDLrvsLXVZvJ+SwsfTx29n0q6ux2ZzYNXudi9qChnUTQggRnpDTzoJ/zmT3BaNQdYNxf32bkf/6EAyjwTWTopJYNH0RpyScQnZZNme+dibfF37feKGFEEKIGtjLDtD126dwle5D1xwsdF/CS5ndMVEY3SeeqX0NNDkjIYQQolGEdw5MUcBqUbFZVFwOK2eP6s6SuKlsC3RGM0OkbnqFqAKZD1REntyELNo10zS5e/7dfLD9A6yqlY+v+pi+HftGNJNFtdCDeLo89Sp9//EMaiiEr0sq+x97AHdGOgN99dfQLDYSVDsF0nEjhBCtjmG1sOSPN1LaJYnhL37K4De/IvZAHov/dBPBaGeDaqZEp/D1DV8z4bUJ7C7czbj/juOr679iYPLARk4vhBBCQPShtSTs+ADVCOF3JfG+cQ7fZVX10IwdlMolp8Xh2ZdPwy9JEEIIIX6gamDqBEvy6n2p1R8i1eEjoIWIV+xER+t0PzuNT1dNIXToUwbbDpC6+b/k9rmC8k4jmyG8EDWTThvRrv1+8e957tvnUFB4fcrrnJF+RqQj4fAG6Hn/H4j5eiUABf17sHfKGehZOyFrZ3g14pPQhpyOEuaVBkIIISJHVTXsmv24x7ffNpXKrp0Y+8eXSV+2ianTH2fJP+4iv1syLpsLh8Xxw52V4V2m3MndiWU3LuPcN89lU+4mzvjfGcy/dj4j0+RgRAghROMw9RD+FW/QcVvV0M6lHfrxavFoMguDqIrCxGFd/j979xkfRdX2cfy3u+mFEnoLPYAQIBB6E5CqoIICEkSagA1ERLEXEBSkSBGUoqLSREBEFFBADFWaFClSQ++B9LbzvMiTvVmSQBKSbBL+Xz8x7NmZM9fMnt3MtWfOGWpULITJFOPgSEVEJK8wmcxYY6OJvXIa4uPvuGxUVCxhVyOIiU3g5s2bWPPlw8lipm1pZ/5y7ULMsRXUdz1OiUOLcYoOJbxy+2zaCxF76rSR+9bELRMZ/ddoAKZ3nE67iu04FXrqnuo0m8xExUdleH2f/87Q5vUvyR9yEcNs5sRDgZypWwmssRAZm+Z64t11vxsRkdzA7OxCYZcCVIuEBMMt+QIt2/Ff8YqUf3Mc+UMu8sjTozg58jlCGtbGK9YLF6sL3heug9ULCha86/aKeRVj/TPr6Ti/I1vPbKX1vNYsfnIxHSt3zIK9ExGR+0lCxA0uLptA3KnEaWXOlWrNrJPluRYWi4uTmfaNylGmmLeDoxQRkTwrPh4jIe6Oi1jj44iPjSU+Np64mGjiY13BknhztXaBxVnl1J3fD/7MQ+77KXJyDc7RoRjln8uO6EXsqNNG7kuzd81m+JrhAHzU6iOeq/ccp0JPseXMFmLiM37Vl7erN5UKVkr/iobBA0v+pOHkJTjFxBFbrAg3gp7ggkcUWO/8B0dERHIvs5MzlsgoErYFEx15I8VlooGbfTvgt3gdBY6doeL7kzHX8ePcw80w3N0xileHVh3S1GkDUNC9IGufXsvjix7n9+O/03lBZ6Z3nM6gwEGZuGciInI/iT5ziItLJ5AQdg2c3Tjs25Wv97kSGR2Lp7szjzQpT+ECGZviU0REJLvU8ivKf+5dWbrLi8fctlHgwnZuLrtO4aA3sHjmd3R4ch/Rbf/kvvPV7q8Y+PNAAF5t9CpvNH3D9lxMfAwxCRn/iY1P+2iYJK6h4bQdPoOmnyzAKSaOM01qcvzbz4gr75tp+ywiIjlbfHQk8ZHhqf5EmxLY+2QzQhpXB6D8riNU/+onTBcvYcSk/2IDLxcvfun5C8/UeoYEI4HBvwxm5O8jsRq6u4CIiKSdYRjc2L6Sc9++S0LYNZwLleJorRf5YpcTkdHx+ORzo2vLSuqwERGRXKNciXwUb/II38c+RLThhOXyfxz/YjgxF044OjS5j2ikjdxXvtnzDf1X9MfA4KX6LzGuzThMJsfd96Xk34do+e5XeF4OJcHZiW0vPc5/QR0ITFDvvYiI3MZs5uSDtblRrCBVf9lKgTNXqD1rBVG9PQlt2ZKwG6fT3enyfov3KehWkMnbJvPJpk84eOUg3z7+Lflc82XRToiISF5hjYnk8i+fE3FwCwAe1RqzzrU1C9YkTjldtrg3bRqUxdXZ4sgwRURE0q1wAXc8Wrbm+60+dI5bRZGo64TMfYOiDw8if62Wjg5P7gPqtJH7xrf/fEvfn/piYPB84PN81v4zh3XYmOITCJy5gtrfrMZkGISWLcYfHw3galVfXM1mSHBIWCIikgtcqVyaDY83ptG6vXhdDsV55ldcu3iera93J9I1/X/XahevzXOBzzFn9xxWHF5Bw9kNWd5jOX6F/LIgehERyQtiL4Vw8cfxxF07B2Yn8j/4NF8cKsKW/YkdNnWqFKVBjeKYHXiBnIiIyL3wcHOm1UMN2XG4FOX+W0g1l3NcXTmNy//uwrtVX0zOKdyT1LauE14eLtkYreQ16rSR+8IXO77guV+ew8BgUN1BTO041WEdNgWOn+PB97+m6L+JCc3Bx5uy5ZVuxLu7OiQeERHJfSIKeLLj6TZU2XKI4lv347PsN9ru3M26D/tyuUb5dNfXoFQD2lVsxwurXuDglYPUn1WfeY/Po3OVzlkQvYiI5BbhkbFERsfbHhuGQfyRTcRs/AriYzF5+hDTZCDvrA/j9MULWMwmerarQqH87sTFa8pNERHJ3ZydzHRsVYPV7v04tecX2rruwXx8M5fOHCG0bh9ivUuluE7Vsj7qtJF7onvaSJ736eZPGfzLYAwMXqj3Ap8//DlmU/Y3fVOClZrzVtOl10cU/fcUMd4erP14IH+99bQ6bEREJN0MJwtn2jTg6ov9iS1amPwhF3m0/zjqzFqJKT79QzZrF6/NjoE7aFymMTdibvDowkd5ZfUrxCak/35tIiKSN0RGx3Po1DX2HbvC/kOnufTTZ8Ss+wLiY4kuXIW/Kw3mveWXOH0xDA9XJ57uUI0GNUrg7GS+449ZA3BERCQXqexbCJ9mT/Kd8QihVnc8Y69QfMtEPA7/RlxsHHHxVrsfkXulThvJswzD4N317zJi7QgARjYZydQOUx3SYZP/5AU6DxhHwylLcYqNJ6RxDX5Y9C4nHqqb7bGIiEjeEutXkSPfTeFEuwaYE6wEfvEzj/X9mEKHQtJdV3Gv4qx/Zj3DGg4DYNLWSTSd25Tj149ndtgiIpJLxMVbsVw9Tqktn+J5fieGyUxc1Tb86f0w3284Q2R0PCUKuvLyo+WoXcqMR/wNSrhFU8ojJsWfEu4xeLmaHXpvURERkfQq4O1KvZbNWVXoGfbGlsGClWKnVlNs22e4RFx0dHiSx2h6NMmT4hLiGLRyEF/t+QqAMa3G8EazN7I9DlOClRoL11Hv8+U4xcQR6+nGlle6cbhzY1CSIiIimSQhnxcbP36O481q0PSTBRQ5GMLjvcew/6nW7BjUiXiP1Odbvp2LxYWJ7SbyYLkH6bO8D3+f+5taM2vxWfvP6Fu7r75kExG5jxhWKwWOraHA8dWYDCuGhw9Xizdk4SEf/rt2BYAaRa084heB08VDhF2zYPF2JexGFAkJRop1unp44V2uLGZdQioiIrmMxWImMKAyZy72Z8nu9XR02kz+qLN4bZvAlTItuVnhIXDSbDpy79RpI3nOzZibPPnDk6w5tgazycznHT9nUOCgbI+j4NGzNBvzPcX3HgPgTINq/PlObyKK+2R7LCIicn841r4+5wKr0GjiD1Ra8zc1v/+d8n/sYtPrTxHSrGa66upcpTN7Bu8haGkQwSHB9F/Rn+WHljOr0yyKeRXLoj0QEZGcIv7GZaJWTKLg+cMAhJeoy8UyD/HN+nPciDFhMRm0LR9L7aIJmBIgPgHMhgVrnIn42NhUO22cXDTtpoiI5DwmswlnJ/srCpwsZswplJcvlZ9SRTuxfLcftS6torrLWYqd/h2vC7sJr9UdKhbOztAlD1KnjeQpp0JP8ejCR/nn4j94OHuw+InFPOz3cLbGYI6IpO6khTzw/RrMCVZiPVzZ+vITHHq8mUbXiIhIlosqnJ91YwZw5JGGNP14PvnOXaX9sOkcb12HLa90I6JYwTTX5Zvflw3PbGDilom8vf5tfj7yMw98/gAT206kd63eGnUjIpIHGYZB2J4/uPbHN1hjIrFaXLno14XNkeUIXn0Wq2GioJuVLn4xFPNMuWNGREQkNzFbLORzc8JMNAnW//1tc3aKwyM+gRJuMXblSco/WJFj5/ry45bNPGTaQv64q3ju+Jzr5zdT8NFncS5YPDt3Q/IQddpInrH+xHq6LenGlcgrFPMsxsqeKwksGZitMZRavwO/ccNwOXsBgFOt6rJ9RE8iixcirYMjXS2umOM1V4CIiNybM41rsGTRe9SZtZKa3/9OhT924Ru8j309H2LPM+2I83JPUz0Ws4URTUbQvlJ7ei/vzZ4Le+jzUx++2/cdMx+eSUWfilm8JyIikl3irl/g8qqZRJ/cB4C5aEWOlH2CX/ZGcPL8WQAeKGKlQ7loXPVtgoiI5BFmiwVTQjSRp48SGx1jK3d2vvu0n0UBn5rF+fPUIxS8spfGrkdwPruHUzOG4Fn3YYo274LF3Tub9kTyCp1mSa5nGAZTt0/lldWvkGAkUKdEHZZ1X4Zvft9si8Hr3BUaf7qYchv/ASCmRFFOD3+Wm00CqQgQnfa6LE4uFMBdo3JEROSexbu7sn1IV462r0+T8QspsfsoAV/9StXlwex89mEOdmmO4WRJU13+xfzZPmA7E7dM5P0/3+f3479TY0YNXm/yOq83eR1357R1AomISM5jWBO48fcvXN+wACM+FpOTCwUffIqtCTWYu/IgUTHxWMwmOtUvhr/LGRLiHB2xiIhI5kuIiyU+9n/TeKZl2s8kDUrBzeJ1WXYuAP8bf1LF+TxRO1ZwbPdqCjToROFGnTG7eWb1LkgeoU4bydWuR11n4MqBLPl3CQBP13yaLx75Itu+OHIJiyRg7q9UX7QOp9h4rE4Wovo8zZFKBYmKvgJ//JbuOt0KFsUS0AIr6rQREZHMcc2vDD9/+Spl//yHBlOXUuDURZqOW0iNhevZ/tLjnG/dIE31OFuceb3p63R9oCuDVw7mjxN/8MGfH/D1nq+Z0HYCXap10ZRpIiK5TOylEC7/8jkx5/4DwK1sDTxaDeCrPy+zbkfiiJtC+d1o37AstUtZCDt2xpHhioiI5Fg+7vB4+wDORTbgp99/p170JkoSSvjmJYRu/wWfxo/j06AjZhdd8CZ3pk4bybWCQ4Lp+WNPTt88jZPZiU/bfMqQBkOy5csic1w8D/ywgTpzVuF2IwKAs4FV+PedwdSs2IS4FfOIjwzPUN3x7up1FxGRLGAycerB2oQ09afq8mACv/iZAiEXaTtiJlerrML6Wjg88xxY7j7yppJPJdY+vZYfD/7I8DXDOXXjFE/88ARNyjThk4c+oYlvk2zYIRERuRfWmCiub1rCjW0rwRqP2dUDn9bPsMeowqwvDhAaHoMJqFutKIFVi+Hm6gTE3K1aERGR+94DFQrTdERf/tr9EMtXr6Jh/HaKc4ObG+dzbctPFG7alQKB7TC7uDk6VMmh1GkjuU50fDSj/hzFx5s+xmpYqViwIgu6LqBeqXpZv3HDoPwfu2gwdSn5zl4B4FqFEmwb0pXTTWpQ2KMI6F6cIiKSgxlOFg4+0YKj7etT69s1+M//g0KHQ6D/SzBmMrz2GvTuDW53TiBMJhNPPPAEHSt35JPgTxi/eTybTm+i6VdN6eTXidGtRlOzWM3s2SkREUkzw7ASvu9Prq37joSIUAA8/Ophrd+LSWvPsOPgLgDKFPOmV/uqRMXEExdvdWDEIiIiuY/FbOLBur40qz2QdX+346fff6GxdQdFCCN0/Tyu/vUD+QIeolDDR3DKV9jR4UoOo04byVWCQ4IZsGIAh68eBhKnQ5vecTrerll8Qy+rlfLrdhPw1a8UPnwagMhC+dgxuDOHOzVO8/0AREREsoLZbMHV4pq+lfK7su/Fbhzp1ZHqP2zggYV/YDl2DAYNgvfeg2HDoH9/KFTojtV4OHvwQcsPGBQ4iA82fMCc3XP4+cjP/HzkZx6r+hjvNH+HOiXq3MPeiYhIZjAMg6gT/3Bt/ffEXjgOgFPB4ng/2JufT3ixbPpu4hOsOFnMdHvIjydaVeL6zRj2Hbvi4MhFRERyL4vFTJuG5Xkw8DnWbDnBlvUracQeihBGxN8/E/b3LzhXqk+xpo/iVsrP0eFKDqFOG8kVLkdc5p317/Dlzi8xMCjuVZzpHafTpVqXLN2uKT6BSr9tp/bXv1Hw5AUA4txd+efpNuzt1YZ4Dw1jFBERxzI5O+Pjko9qkQkkGBn4u+SWH2vv3twc9j4Ff/kdPv0UzpyB11+Hd96BLl1gwABo2RLM5lSrKeldki86fcErjV7hvQ3vsfjAYpYfWs7yQ8tpV7EdwxsN56EKD+meNyIiDhB99gjXNswn+mTiPWpMLu7kb9yVHaaafP/DUa7dTMx1avsVYeBj/pQplsUXxYmIiNxnnJ0sPNysEjENX2Ld36f46891+MfsorLzRRKObuXc0a3EFiyPd512OFWoh8nJJU31erg54eWRtmUl91CnjeRoMfExTN0+lVEbR3Ez5iYA/QP6M77NeAq6F8yy7VqiY/FbuYVa81aT79zVxFi8PdjfvSX7e7QipoBXlm1bREQkPUwWJ5wioknYFkx05I0M1eHhWRDal+F0ny5Yn+qI55KfyDfzK1z2/QsLF8LChcSVLUN4r+5E9HyChJLFU62rqGdRFj6xkPdavMeY4DHM3zef1cdWs/rYamoUrcHQBkN5qsZTeLroHm4iIlnJMAyiQ/4ldNMSok7sTSy0OJGvTjuOFGjMJ+vOcPbyfgCK+Xgw4NEaNKheXJ3rIiIi98BkMnGnP6WuzhY6NK5Au4bl2XW4Ez+t20Lxi5up63ICl+sniPljJuHrviK8eG2iyjQkJn9ZUqvQ2clM1bI+6rTJg9RpIzlSbEIs3/7zLR/99REnQk8AEFA8gMntJ9O8bPMs227+4+eouOR3Kv+yFbebkQBEFfRmb9BD/PtEC+K83LNs2yIiIvciPjqS+MjwDK1rOLkTmxDH3+f+JiwmDBoXgcav4XPwJJWXbaTCr1twOXWagh99Sv6xE7hU249TrQMJaVWHyOL/mz7N1cmVRqUbUdC9INWKVOPbx7/l/RbvM2XbFObumcv+S/t59udneWX1K/Sq2Ytn6zxL7eK19QWhiEgmMqwJRBzexo3tK4k5kzitNGYLntWbc9inGYu2XCXkQmK5t4cL3R6qTMfG5XFx1pTPIiIi98JsseDt7oRzdChxoXfPzWqVMFErqDGnLtXm17+O4HRyK4HORylkiaDg+W0UPL+NcJdCRJZqQFjJQBJc82fDXkhOoE4byVEi4yL59p9vGRs8llM3TgFQ3Ks4Y1qNoXet3ljMWZBIxMTAjz9SbPpnPLZ5u604rEQh9gY9xKHHmpLgph5rERHJ+2LjY4lJiLE9Pu9XgvOvd2fT0Mep8PtOqi4PpsSeoxTfdZjiuw7TYPz3XKpejhMtAzjZMoDo8mWS1VnRpyKfdfiMD1p+wOxds/li5xccvXaUGTtmMGPHDKoXqU5P/5709O9JuQLlsnFvRUTylviw64TvW8+NnatJuPn/96GxOOFe/UF2uwby49+hXLp2EgB3Vyceb1GRR1tUxMPN2XFBi4iI5CFmiwXio4m6fAyzc9ovTCsGPFHd4FihGuw4X53Qy5cpH3+M2i6n8Iq9iteJVRQ5sYob7mWIKVGTyKI1ifMonHU7Ig6nThvJEY5fP86Mv2cwZ/ccrkdfBxI7a15r/BqDAgfh4eyR6rrXo67bpk5Ls7g43DZtw2PFr3is+BXL1Wu4AVaziZBmNTnYpTlnGj6AYUl97n4REZG8xGQ242JywdXimvxJT1dCHn2QkEcfxPPcFXzX76TsHzspuuc/ih44SdEDJ2kwbRnhJYtA61bQ8TFo1QqKFrVVUcCtAK82fpVXGr3ChpMb+HLnlyw/tJwDlw/w1rq3eGvdW9QtUZfHqz7OY1Uf44EiD2gEjojIXVjjY4k6upuwveuIPLoLDCsAZo98xFdszh9hFVmz6SaxcecAyO/lwqPNK9KhcXm83NVZIyIikhWM+DgMc/pyGWt8HC5GLLWLGDiVKkJUoaYsPXAV5zO7CDAfpoLzZQpEnYbjp+H4L9xwKUpMiVokFHgQo2AV5U55jDptxGFCo0NZcGgB3+/7ng0nN2BgAFCuQDlebvAyA+sOxN357tOR3Yy5yZYzW4iJj7njcubYOEpsO0DZP3ZSZsMu3G5E2J6LLF6IsKe7s7VtdUILJ86xn5GxNS4WF0zxGVhRRETEgczOLrjjTJUIN2IS7nLBgk9+6FqRs127cfHqdQr8uY0CG7bitfsAXucuw7eLEn8AatWCli2hUSNo2BDKlMFsMtOqfCtalW9FaHQoSw8u5ft937P+xHp2nt/JzvM7eXv925TNX5Y2FdrQtmJbWpZvSWFdSSYiAoA1Loao4/8QcWgLEUf+xoiNsj1nKlaJo+61WHbKh9N/xgCJF8SVK5GPjo3L0aqeL67pmAbNZEqcLx8Sf6fz+ycRERHJoKIFXGkQUJ6YGr4cvxjOljNn8L6yn6qmk1R0ukj+2Etwai1Rp9Zy2MkLU4lqFK4WQL5KtXAqUEydOLlcruq0CQ4OZtKkSRw9epRChQoRFBREv3797tgIV65cyYwZMzh9+jSlSpVi4MCBPP7443bL7Nu3j3HjxrF//348PT3p0qULL774Ii4umhIrs4XcCGHZ/mUs2buEv3/9224KlrYV2/JivRfpWLljuqdBi4mPsasLwBSfQKEjpym58wgldh2hxK7/cImItj0fVdCbkw/W4kSrOkQ1a0yjgv6UO3+MhOiEDO+fh+GKu8WExaQROiIiknuYnJwxRUSQsDmY6PBr6Vo3PD+cebQh5g51KXz+JqXjPXDb9Q/8c8vP5MmJCxcvnth507Ah1KtHAX9/+gX0o19APy6GX+TnIz+z/NByfj/+O6dunGL27tnM3j0bgIoFK9KwdEPbT81iNXGx6FxN5HbKmfIew7ASe+kUUSf3EXlsF9Gn/sVIiLM9b3UvyBmv6qy5WoZ9B5NGz8Tg4myhsX8J2jcqxwPlfYgKu0nU1YtEpbyZZEyA2WqlhFs0CVYDi8WMp7OZm/oSSEREJNuYTSZ8i3vjW7wahlGVS9ej2H32Iq4X91Mx/ihVnM/jEh8Op//mxum/ubEGop0LQImqFKzkT8HyfrgW8cVkyVXdAPe9XPNq7dmzh8GDB9OhQweGDh3Kzp07GT9+PAkJCQwcODDFdVavXs2rr75K7969adasGb///jsjR47ExcWFhx9+GIDTp0/Tt29fateuzeTJkzl27BiTJk0iNDSUDz/8MDt3Mc8xDIOToSfZdHoTf536i40hGzl05ZDdMg8UeYAg/6BMmcfe/epNfP47Q+FDIZTY/R/F9xy166QBiChSgBMta3OiVR0uBFS2TX9W2NkZS9j/f1kVeSPDMbgWLo2pbmvM6rQREZFcKCE6ivjIu98wMzXXyhencJdncatSEy5dgnXrIDgYtm5N7Ly5cAGWL0/8SVK8OPj7U8zfnwH+/gx44F0iWs1gY9h+1h5fy5pjazhw+QDHrh/j2PVjfL/vewDcnNwIKB5A9SLVqVq4KlULV6VakWqUzV82a+6BJ5ILKGfKGxKiwog5f5zwkEN4/rebS+vPYcRE2C0T41KA/8wV2XCtOEev+WCQ2JFiMZuoVbkID9YtTcMaJXB3/V/KHxsZwZn9e4iNsc+RUuPkZCGfpwthN6JISDBw9fDCu1xZzEp1REREHMJkMlHUx4OiPuXBvzxRMfHsj40l/PQhOH+QUvFnKOd0Gbe4UAjZSlTIVqKAeCxEuBfHVKgc3r6VKVqpKp5FS2N2vfsMR+IYuabTZurUqVSrVo3x48cD0Lx5c+Lj45k5cya9e/fGzc0t2ToTJ06kffv2vPnmmwA0a9aMGzdu8Nlnn9kSkFmzZuHp6cnnn3+Oi4sLLVq0wM3NjVGjRjF48GBKliyZfTuZS8XEx3Ay9CTHrx/n2PVjHL12lH8u/sOeC3sIjQ61W9ZsMtOgZAPqeNehd8Pe1POtl77herGxcOYMnDoFJ0/C/v0U3bWdbnv34n4t+X1tYrzcuRBQmXN1/Thf148rVcpwpywjPjrynr6sSkhjAiQiIpLnFS0KPXok/gBERsKuXbBtG2zZArt3w/HjiR05Fy7A2rW2VT2BDgUK0KFiRahUgyjfdhzPn8BeyxU2WU+yOmo/x6w32HJmC1vObLHbrKvFFb9CflQoWIHS+UpTOl9pyuQrY/t3Se+SaZp+VSQ3Us6Ue1hjo4m/eYX4G5eJv3GZuGvniL18hrgrp4m/ecW2nAtgAHEmZ84YxdgTWZyDsSW5aM0P/99Rk9/LhQC/otSvXpw6VYrieYd71cTGRBMTdedppZMYzhasLhAfG0tCgoGTS+w97LGIiIhktnyeLtSsWZIibR8A4NK1SP797xwXDv6Dcf4gPjHnKWW5ioc5jvxRZ+HMWTizicub4TIQYfIgyqUQCV5FcSpYAo+ipfAsXJR8hYuSv3ARLM66/52j5IpOm9jYWLZt28aQIUPsytu1a8fs2bPZuXMnTZo0sXvuzJkznDx5MsV1fv31V06ePEm5cuUIDg6mRYsWdsP627dvzwcffEBwcDDdunXLuh3LYRKsCUTFRxEZF0lEbETi77gIrkdd52rUVa5EXuFq5FXbv8+Hn+f49eOcvXnWdj+a2zmbnaldvDbNyzanednmNPVtipvVlUP//ENVS0lM584lfokTFZX4OzQUrlyBq1f/93Plyv86as6dA8N+W0lfuxgmEzfKFOVapVJcrFWRc3X9uFa5tG00jYiIiGQti8mMAZy9eRbr/98M245/2cSfAYnnV6bwCJwPHcH530M4H0j8cTp2HKfzFxPPCXbuhJ07cQeq///PU/9fleHsTESR/IR6u3DZ3cpZ52hOWcK45BbDVfd9hLnu44IzHHOBCGcId4GI//+34emOW75C5PcuTCHPwhRyL0Qh90Lkc82Hl4sXni6eib+dE387GU5cun4JrkChfIVwsbjgbHbG2eJs+7eT2UnzRotDKWfKXoZhYMTHJv7ExWIkxGHExWKNj8WIjSIhKhxrVBjxkWHERST+jo+8ScLNKxjhVzHFRtyx/ssJ3pyOL0RIQiGOxRXjTIIPVhLzmqI+HjQpU4Dq5QtRs1JhfIt76/NHREQkjzGZTbb7yqXGzdlCgmHl8vXIxHVMUN2vJNX9SgIdiIlN4Nylm5wICSH63DHM10+RL/o8RU3X8TZH42lE4hkTCTGn4SpwFKxAKHDNgEjciTR7EePkRYKzJ4aLB4aLB2ZXT8xunji5e+Ls7oWLuxuubu64ebjj5OKCs6sbzm6uOLm44eLihLOTGSeLWecr6WAyDCPlb9tzkGPHjtGxY0emTp1K27ZtbeU3btygfv36vPPOO/Tq1ctunT///JOBAweydOlSqlevbiv/999/efzxx5k5cyaNGjWiVq1ajBw5kr59+9qtX7duXbp168brr7+erlh37dqFYRg4O6gnMjYhlmtR17BiBQNbZ4qR+MD+ceI/MJL+S0dTyBcD3v9/oZXp//9v+v//m+z+fQvDsP/JKLMZLBZwcgJnZxKcnYixGCQ4WRI/nTLAYrbgalhIiIrASOlLpjSH5oSTqztx0ZEYRsbujWMyW7C4ukFsLPEJ8ZBKh9hd63BxwxobjRkT8dYErFYrJpMpXYcopXrSG09SHQkxUWAYWMyWdNdzax2GYcWEyWH13F4HkGo9iU3dSHbcU6rjTvWkNQ5H1XOnOtJcj8mMyc2NOJORaiew2WTGyexEXEJcqssAOCcAMTGpbutu8dxtf9JST1rryI560lNHavXcqY5U23k660lrPBmp4/Z6TGZzhurIinoSAIuLa7rquPWYm00mLE7OiX8Po9MfR5LM+PuVWI8Fi7snCdaEO75P78pkwmw1MMXHY4qLh/h4TAkJEJ+Q+Dsh4zEm39b/3jHGrf++5bmkf9/qDp+KyZZNMJu47mnBak46Y0ptTbs3UfKyu/Bw9iC/a/40L5+Z4uLiMJlM1KlTxyHbl9yVM4Hj8yZrdDhGfNwtJYbdr6QHVuttf5uT/qbdy2ecrXYTCYYJK2YSkn6MxN8GiX9XzSaT7YsOJ4sJJ4sZszljOY9hTSA+NjbNeZ8JMJtNWK2Jn+gmkxmLkxMJ8XGp1nH7Oikuk0I9JsBiNqcvnTOZwOKUZftkWK2YzOa0xWYyYbI4YSTE2+W6hgEJVmuaW4vZnBhPfFzqxzilfbKLL5VYbne32FJ7ne72+iarwzkxFmtC2o5D0nF3ysn75OQE1vh0/IVOHl+mvZ8wYXJ2JsEw2Q6NyQTO6f2ssCYQHxeb7DPvTjLyGZHSesmez4zPiP9vM9b4OBLS2PbudZ/uGN8dPiPirVZbu7/zLqX//ZRibGl8PyXFl9J7KrXjkh2fEZm5T7ce90zdp0z5jDBhcXbBahh3/FrHZEpc1jBSi89EQgoposVixjCsWOPjE4+bNQEMKyYj6SzEmu74U5M0hav9UeW2Mvvy5M+lvMztEkwWYkzJR5bfymwy4eXhjCWD51P3Ij05U64YaRMWFgaAl5eXXbmnpycA4eHJp7NKKrvTOqnVm7RcSvXeTVKPoaN6Dl2dXCnhXcIh23YUC+CRWXW5uGZKPS6umVCPqzv3OiO/xS1xHFJOqCepjnup59Y6HF3P7XVkpJ6U6khvPanV4Yh67lRHWutJy62M03Tjcffkn+u3u1s8d9uftNST1jqyo5701JFaPemtIyvryUgdt9eT0Tqyop57qcNWVybMR5wpf7+A3DbG1XTb76yQWecqOVVix62unHOk3JQzgePzJou7t0O2e7vs7LIyWZxwcb/3rwAya6qUzKonJ+1TSjd5zkiu4eJ07/Gk5YbTaYktU45NJuwP5LB9yuC7N9k5bSa1vXuuxeKEcybdpDwnfUZYLE73/H1IZsUCmfQZkY3vJ7hLnppZF17kxX3KrM+Iew/kDpGYwTlXdA2ki6ejA7iD9ORMueKVsVrvfNWoOYXe6LSsc7dlMpJABAQEpHsdERERERGRe5GbciZQ3iQiIiIikppccSGkt3fiVVAREfbz/qZ2ZVha10la7/ZlkpZLqkNERERERCQnU84kIiIiIpI35IpOG19fXywWC6dOnbIrDwkJAaBixYrJ1ilfvjxAsnWSHlesWBFPT0+KFSuWbJmrV68SERGRYr0iIiIiIiI5jXImEREREZG8IVd02ri6uhIYGMjatWvtbga1evVqvL29qVmzZrJ1ypYtS+nSpVm9erVd+Zo1ayhXrhylS5cGoEmTJmzYsIHY2Fi7ei0WCw0bNsyiPRIREREREck8yplERERERPKGXHFPG4DnnnuOvn37MnToULp27cru3buZM2cOw4cPx93dnfDwcI4ePYqvry8+Pj4AvPDCC7zxxhsUKFCAVq1a8ccff/Drr78yadIkW70DBgzgl19+YcCAAfTt25eTJ08yceJEunXrRsmSJR21uyIiIiIiIuminElEREREJPczGbdehpXDrV27lilTpnDixAmKFStGUFAQ/fr1A2Dbtm307t2bsWPH0qVLF9s6CxcuZO7cuZw/f54yZcowcOBAHnvsMbt6d+zYwbhx4zh48CAFCxbk0UcfZciQITg7O2fn7omIiIiIiNwT5UwiIiIiIrlbruq0ERERERERERERERERyatyxT1tRERERERERERERERE8jp12oiIiIiIiIiIiIiIiOQA6rQRERERERERERERERHJAdRpIyIiIiIiIiIiIiIikgOo00ZERERERERERERERCQHUKeNiIiIiIiIiIiIiIhIDqBOG8lWwcHBdO3alVq1atGqVSvmzJmDYRiODivPiomJoXr16lSpUsXuJyAgwNGh5UkXLlwgMDCQbdu22ZWfOnWKwYMHExgYSIMGDXjvvfcIDw93UJR5S2rH/KmnnkrW7qtUqcK+ffscFGnuZrVaWbBgAZ06dSIgIIDWrVszZswYu3asdp650nLM1c4zn9VqZc6cObRt25aaNWvSuXNnVqxYYbfMvn37ePrppwkICKBp06ZMnDiR2NhYB0UsInmV8ibHUP6U/ZRDOY5yqeyjfMpxlFc5jnKre+Pk6ADk/rFnzx4GDx5Mhw4dGDp0KDt37mT8+PEkJCQwcOBAR4eXJx05coT4+HjGjx+Pr6+vrdxsVn9tZjt//jz9+/cnLCzMrvzmzZs888wzFC5cmI8//phr164xfvx4zpw5w5w5cxwUbd6Q2jE3DIPDhw/Tt29f2rdvb/dcxYoVszPEPGP27NlMnjyZ/v3706hRI06cOMGUKVP477//mDt3LmFhYWrnmexuxxxQO88Cn332GXPmzGHIkCH4+/vz559/MmLECMxmM4888ginT5+mb9++1K5dm8mTJ3Ps2DEmTZpEaGgoH374oaPDF5E8QnmT4yh/yl7KoRxHuVT2Uj7lOMqrHEe51b1Rp41km6lTp1KtWjXGjx8PQPPmzYmPj2fmzJn07t0bNzc3B0eY9xw6dAgnJyfat2+Pi4uLo8PJk6xWK8uXL+eTTz5J8fkFCxYQGhrK0qVL8fHxAaBYsWIMHDiQnTt3Urdu3ewMN0+42zEPCQkhIiKCFi1aULt27ewNLg+yWq3MmjWL7t27M3z4cAAaN25MwYIFGTZsGPv372fz5s1q55koLcc8X758aueZLCoqinnz5vH000/bvhRt1KgRBw4c4Ntvv+WRRx5h1qxZeHp68vnnn+Pi4kKLFi1wc3Nj1KhRDB48mJIlSzp4L0QkL1De5DjKn7KHcijHUS6V/ZRPOY7yKsdRbnXvdLmIZIvY2Fi2bdtGmzZt7MrbtWtHREQEO3fudFBkedvBgwepUKGCEo4sdPjwYd577z0ee+wxxo0bl+z54OBg6tatazvxAmjatCmenp5s3LgxO0PNM+52zA8ePAhA1apVszu0PCk8PJxHH32URx55xK68QoUKAJw+fVrtPJOl5ZirnWc+FxcXFixYQL9+/ezKnZ2diYmJARI/01u0aGH3d7V9+/ZYrVaCg4OzNV4RyZuUNzmW8qfsoRzKcZRLZT/lU46jvMpxlFvdO3XaSLY4ffo0cXFxlCtXzq68bNmyAJw4ccIBUeV9Bw8exGKx0K9fP2rXrk39+vV59913NS9qJipRogRr167ljTfeSPGqx2PHjlG+fHm7MovFQunSpdXuM+hux/zgwYN4eHgwbtw4GjRogL+/P88++yzHjx93QLS5X758+Xj77beTXd31+++/A1CpUiW180yWlmOudp75LBYLVatWpUiRIhiGwZUrV/jyyy/ZvHkzPXv2JDo6mrNnzyZr6z4+Pnh5eamti0imUN7kWMqfsodyKMdRLpX9lE85jvIqx1Fude/UaSPZImmeVC8vL7tyT09PAJ0EZ4GkuWhPnTpF69atmTVrFoMHD2blypUMHDgQq9Xq6BDzhAIFClC8ePFUnw8LC7O181t5enqq3WfQ3Y75oUOHiIyMJF++fEyfPp3Ro0dz6tQpgoKCuHjxYjZGmnf9888/fPnll7Rs2RI/Pz+182xw+zFXO89av/zyC02aNGHChAm0aNGCzp07p3ouA2rrIpJ5lDc5jvKn7KMcynGUS+UMyqccR3lV9lNulTG6p41ki7ud4OrGjpnPMAxmzJiBj48PlStXBqBevXoULlyYESNG8Ndff9GiRQsHR5n3GYaR6nMmkykbI7l/DBs2jAEDBlCvXj0AAgMDqVOnDh06dGDevHmMGDHCwRHmbjt37mTw4MGULl2asWPHAmrnWS2lY652nrVq1qzJd999x+HDh/nss88YMGAAEyZMuOM6ausikhmUNzmO8qecQ+eWjqNzzKynfMpxlFc5hnKrjFGnjWQLb29vACIiIuzKk3pOU+pZlXtjNptp0KBBsvIHH3wQSJzLVklH1vPy8krW7iGx7RcrVswBEeV9Kc1FW6ZMGSpWrMihQ4ccEFHesWrVKkaOHEm5cuWYPXs2BQsWBNTOs1Jqx1ztPGv5+vri6+tLvXr18PLy4vXXXyckJARIfi4DiW096VxHROReKG9yHOVPOYfOLR1H55hZS/mU4yivchzlVhmjy3QkW/j6+mKxWDh16pRdedKbtGLFio4IK0+7ePEiixcv5ty5c3bl0dHRALY/UJK1ypcvb2vnSRISEjhz5ozafRaIj49n2bJl7N69O9lz0dHRdjd2lPSZM2cOr7zyCrVr1+b777+naNGitufUzrNGasdc7TxrXLt2jeXLl3P16lW78gceeACAS5cuUaxYsWTnMlevXiUiIkJtXUQyhfImx1H+lHPo3NIxdI6ZtZRPOY7yquyn3OreqdNGsoWrqyuBgYGsXbvWbtjn6tWr8fb2pmbNmg6MLm9KSEjgnXfeYdGiRXblq1atwmKxEBgY6KDI7i9NmjTh77//5tq1a7ay4OBgIiMjadKkiQMjy5ucnJyYNm0a48aNsys/cOAAISEhKV49KXe3cOFCxo0bR4cOHZg9e3ayq17UzjPfnY652nnWiI6O5vXXX2fJkiV25Zs2bQKgSpUqNGnShA0bNhAbG2t7fvXq1VgsFho2bJit8YpI3qS8yXGUP+UcOrd0DJ1jZh3lU46jvMoxlFvdO02PJtnmueeeo2/fvgwdOpSuXbuye/du5syZw/Dhw3F3d3d0eHlOyZIl6dKlC3PmzMHV1ZWAgAB27tzJzJkzCQoKonz58o4O8b7Qs2dPvvvuO/r27cuLL75IaGgo48ePp3nz5tSpU8fR4eVJL730Eq+//jqvvfYajz76KOfOneOzzz6jWrVqPP74444OL9e5fPkyY8eOpVSpUgQFBfHvv//aPe/r66t2nsnScszVzjNfyZIl6dq1K9OnT8fJyYkHHniAHTt28OWXX/LEE09QqVIlBgwYwC+//MKAAQPo27cvJ0+eZOLEiXTr1o2SJUs6ehdEJI9Q3uQYyp9yDp1bOo7OMTOf8inHUV7lOMqt7p3JuNPdrkQy2dq1a5kyZQonTpygWLFiBAUF0a9fP0eHlWfFxsYye/ZsfvrpJ86dO0fx4sV58sknGTBggG5imgW2bdtG7969mTdvnt0VGUeOHGHMmDHs3r0bT09PHnroIV577TXNSZ4JUjvmq1atYvbs2Rw/fhx3d3fatGnDK6+8QoECBRwXbC61ZMkS3nrrrVSfHzt2LF26dFE7z0RpPeZq55kvNjaWOXPmsHz5cs6ePUuJEiXo1q0b/fv3t/3d3LFjB+PGjePgwYMULFiQRx99lCFDhuDs7Ozg6EUkL1He5BjKn7KfcijHUS6VPZRPOY7yKsdSbnVv1GkjIiIiIiIiIiIiIiKSA+hSERERERERERERERERkRxAnTYiIiIiIiIiIiIiIiI5gDptREREREREREREREREcgB12oiIiIiIiIiIiIiIiOQA6rQRERERERERERERERHJAdRpIyIiIiIiIiIiIiIikgOo00ZERERERERERERERCQHUKeNiIiIiIiIiIiIiIhIDqBOGxERERERERERERERkRxAnTYiIiIiIiIiIiIiIiI5gDptREREREREREREREREcgB12oiIiIiIiIiIiIiIiOQA6rQRERERERERERERERHJAdRpIyIiIiIiIiIiIiIikgOo00ZERERERERERERERCQHUKeNiIiIiIiIiIiIiIhIDqBOGxERERERERERERERkRxAnTYiIiIiIiIiIiIiIiI5gDptREREREREREREREREcgB12oiIiIiIiIiIiIiIiOQA6rQRERERERERERERERHJAdRpIyIiIiIiIiIiIiIikgOo00ZERERERERERERERCQHUKeNSB4SHh7OtWvXHB1GjjJ16lSqVKnCmTNnHB1Kpjt9+nSqzy1dupQqVarc9adVq1bZGHHaWK3Wu75eZ86cSbYv1apVo27dujzxxBN8++23JCQk2K2zbds2qlSpwtKlS9Md052O9a1atWrF008/nerjzHD16lUiIyNtj0eOHEmVKlUydRt3k1nvq6TY7/YzcuTIe4456T2xbdu2dK13L+3mXl26dIkPP/yQ1q1b4+/vT4MGDejTpw+rVq26p3rT2p5FRETuZ8qtklNulfW5VVKeM3Xq1HSvm1nnzRmxY8cOunfvTkBAAI888ghr165N03ppOa4ZOYe/m7SeD4eFhTFhwgTat29PzZo1CQwMpEePHixcuDBZvpket+d0KUl6v936U6NGDZo2bcqLL77Irl27kq2T0dwwLTk4JM+NsipXuv31cWTbFnEUJ0cHICKZY//+/Tz33HN8+umnNGjQwNHhSBbr378/RYoU4eOPP07x+Xr16jFu3Djb4+vXrzN27FgCAwPp1q2brdzT0zPLY02P8PBw+vTpQ4sWLXjppZfuuvyt+2O1WgkNDeWvv/5i9OjRBAcH8/nnn2OxWACoWLEi48aNo06dOumK6fPPP2fZsmVpSjzefPNN3N3d01V/evz555+8+uqrLFu2DA8PDwC6d+9Oo0aNsmybKWnTpg2+vr74+PjcUz23x75z504WLVpE9+7dqVu3rq3c19f3nrYD/3tPVKxYMV3rZbTd3Kvz58/z5JNPYhgGXbt2pUyZMoSGhrJmzRqGDRvG3r17M5S4/Pjjj3zwwQfs3bs3C6IWERHJG5Rb3V9yUm7l4+PDuHHjMvTF+7hx4zLlvDm9jh07Rr9+/fD39+e1117jl19+YciQISxatIiaNWvecd1bjyvAzJkzOX78eLLy9J7D30la87vw8HB69OjBhQsX6Nq1KxUqVCAqKorg4GDee+89Nm/ezGeffYbJZErX9lPK6e5k8ODBVKhQAYCYmBjOnTvH8uXLCQoKYty4cXTq1Mm2bEZyw/Tk4NmRG7377rucOHGCb7/91lbmqLYt4kjqtBHJI44cOcKlS5ccHYZkk+DgYB5//PFUny9TpgxlypSxPT5z5gxjx46lTJkyPProo9kRYoaEhoayb98+WrRokablU9qfvn37MnHiRL744gvmzp3Ls88+C0DhwoUztO9btmxJ81VUDz30ULrrT4+9e/dy8+ZNu7KAgAACAgKydLu3q1q1KlWrVr3nem6PPSEhgUWLFlG7du1Mb6e3vyfSKqPt5l59/vnnREREsGrVKkqUKGErHzBgAIMHD+brr7/miSeeoFKlSumq9++//yYmJiazwxUREclTlFvdX3JSbuXh4ZHhOh2V561YsYKYmBimTp2Kj48Pbdq0oUmTJvz666937bS5PeYlS5Zw/PjxLN2XtOZ33333HUePHmXp0qVUr17dVt63b18++OAD5s+fz8aNG9OcuyZJKae7k8aNGyfrPO7Xrx89evTgrbfeom7dupQsWRLIWG6Ynhw8O3Kj4OBgSpUqZVeWk7/DEMkqmh5NRETynCFDhlC+fHm++uor4uPjHR2OSLrt3r2b8uXL23XYAJhMJnr37o1hGOzevdtB0YmIiIiIJIqKigLg7NmzAERHRwPg4uLisJgyw+7duylQoIBdh02SZ555BoA9e/Zkc1SJ8uXLx4cffkhMTAzffPONQ2IQkaylThuRXODGjRuMHDmSBx98kBo1avDQQw8xYcIE29XSU6dO5Y033gCgd+/ednPpnj17lhEjRtCwYUP8/f3p3Lkzixcvtqt/5MiRtGnTht27d9OlSxdq1qxJ+/btWbBgQbpj/eabb6hSpQoHDx60lYWFhfHAAw/YDdsF+Prrr6latSqXL18GEoeZv//++zRr1owaNWrQrl07vvzyS7urYKZOnYq/vz9r166lSZMmBAQE8MMPPwAQEhLCSy+9RL169WjQoAGffPIJcXFx6d6HJLGxsUydOpW2bdtSs2bNFOOJiopiwoQJtGrViho1atCqVSs+/fRT24krpH4vjdvLkx4fOnSI4cOHU69ePQICAnj++edt88smzXEMsGzZskyZ33fLli0MGDCABg0aUL16dZo1a8a7775rd/XPyJEjad++Pd9//z316tWjXr16bNy4EYDjx4/z3HPPERgYSIMGDRg9ejSLFy9ONt/1jRs3GDVqlO317dChA9988w2GYQCJ8+G2bt0agGnTpt3TfNlOTk507NiRq1ev8u+//9rqv32+3e3btxMUFERgYCABAQH06NGDdevW2Z5v1aoV27dv5+zZs3ZzS1epUoXJkyczePBgatSowcMPP0x8fHyq97D54YcfbPclefLJJ/nrr7/snk9tvVvLR44cybRp0wBo3bq1Xfnt0yek9X3fvn179u7dS69evahVqxaNGzdm9OjRtkQrNbfPZ570vjx58iSDBg0iICCAevXq8frrr3P9+vU71pVWd3rvHzhwgJdeeonGjRtTvXp1GjVqxPDhw7lw4YJt/Yy83yD1eZs3bdrEBx98QKNGjahVqxbPPPMMhw4dsos5Li6OyZMn8+CDD1KrVi169erFoUOHeOCBB+46T7mnpydHjhxJca7qRo0aceDAAZ588km78vXr19OjRw9q1apFvXr1eOmllzhx4oTt+aeffpply5YBmhdaRETuX8qtlFtlZW6VdK64bNkyOnXqhL+/v609Xb58mQ8++IDWrVtTo0YN6tatS+/evdm5c6dt/dvvaZP0ePny5UyaNInmzZvbcoqtW7fabfv287sqVarw5Zdf8tVXX/HQQw9Ro0YNOnXqxK+//pos7p9++olOnTpRs2ZNOnbsyK+//kqfPn3SdH/ODh06APDOO+9w+vRpXn31VVxdXe84eim9rFYrc+fOpX379tSoUYNmzZoxevRowsPD7ZbLaH6XEk9PT0JDQ/ntt9+SPVeuXDn27dvH0KFD7cp3795N3759bSNe+vXrZzctcWo5XUYEBgZSsmRJu9zy9tzQMAymTZtGu3bt8Pf3p3HjxowYMYLz588DqefgSe+f1atX06pVK2rVqsXUqVNTvYdNeHg4b7zxBnXq1KF+/fq89tprts+ipO2ktN7t5VWqVOHs2bNs3749Wfntucvvv/9Ojx49bPcaGjx4cLJ8LD3vAZGcRtOjieQCL7/8Mv/++y+9e/emaNGi7N69my+//JLQ0FBGjRpFmzZtuHz5MosWLWLw4MH4+/sDiTdv69atGzExMfTq1YsiRYqwZs0a3nnnHU6ePMlrr71m20ZoaCgDBgygRYsWdOnShTVr1vD+++9z8+ZNBg0alOZYmzdvzpgxY9i6dSvVqlUDEqfjSUhI4L///uPGjRvkz58fSBz2Wr16dYoUKcKNGzfo0aMHZ8+epUePHpQvX55NmzYxYcIE/v33XyZPnmzbRnx8PO+++y59+/YlNjaWunXrcuXKFXr06EFcXBzPPPMMbm5uzJ8//56+MH7hhRfYuHEjnTp1om/fvuzdu5cJEyZw9epV3njjDWJjY+nbty979uyhS5cu1KhRg7179zJr1ix27tzJvHnzcHZ2Tvd2n3vuOSpWrMiwYcM4ffo033zzDZcuXWLJkiW2OY5fe+012xzK9zK/b3BwMM8++yx16tRhyJAhmEwmNm3axKJFi7hx4wafffaZbdnz588zY8YMXnzxRS5dukTt2rU5d+4cPXv2BBKHaDs5OfH999/z888/220nMjKSXr16cf78eXr27Enx4sXZunUrY8aM4eTJk7z33ntUrFiRN954g7Fjx9KmTRvatGlzT/dMqVy5MgCHDh1KcVj+8ePHGTRoENWqVWPYsGEALF68mOeff57vvvuOwMBA3nzzTSZMmMD169d544037E6Av/nmG+rUqcPbb79NdHQ0Tk4p/0ndv38/e/fupXfv3vj4+LBw4UIGDRrE7Nmzady4cZr3p3v37oSHh7N27VreeOMN2/7dLj3v+2vXrtG/f386dOhA586d2bhxI99++y0uLi52y6WF1Wqld+/eBAYG8vrrr7Nv3z6WLFlCdHS0XTu6Fym99w8fPkzPnj0pW7YsAwcOxN3dnV27dvHTTz9x6tQplixZcsc67/R+u5O3336bokWL8vzzz3Pjxg1mz57Ns88+y/r1621t4dVXX+W3337j8ccfx9/fn/Xr19O7d2+sVutd9/WJJ55gz5499OzZkwYNGvDggw/SqFEjqlSpgtlsxmy2v+5m6dKlvPnmmzRq1IgRI0Zw48YNFixYQLdu3Vi8eDHly5dn8ODBWK1WduzYoXmhRUTkvqXcSrlVVuVWt/rwww/p0qULTz75JCVLliQ6OpqgoCDCwsIICgqiWLFinDx5kgULFjBgwAB+//13ChUqlGp9n332Ge7u7vTr14+4uDjmzp3LoEGD2LBhAwULFkx1vQULFmC1WgkKCsLNzY1vvvmGYcOGUbFiRfz8/AD4/vvv+fDDD6lfvz7du3fnv//+Y/jw4Xh5eaXp3joBAQH06tWL7777jrZt25I/f35mzJhBuXLl0n3cUvPWW2/x008/8dhjj9GnTx+OHTvGggUL2LVrFwsWLMDV1fWe87vbde3alVWrVjF06FBq1qxJ69atbR22Fosl2UiiTZs2MWjQIKpWrcrQoUOJjY1l6dKlBAUF8dVXXxEYGJjmnC6tKleuzJ9//klsbGyKI5tmzpzJ9OnTCQoKsnXIzJs3j/3797Ny5cq75uBvvfUWvXr1wsvLi9q1a6c6rdykSZMoXbo0Q4YM4eLFi3z77bfs27ePZcuW4ebmlub9GTduHGPHjqVgwYIMHjw41XvnJLXZGjVq8MorrxAeHs78+fN56qmn+Oabb+zy/7S8B0RyJENEcrQrV64Yfn5+xuzZs+3KR44caTzzzDO2xz/++KPh5+dnbN261Vb28ssvG1WrVjX2799vK0tISDAGDRpkVKlSxThy5IhhGIbx+uuvG35+fsbo0aNty8XHxxtBQUFGzZo1jdDQ0HTF3Lp1a2PgwIG2x2PGjDGaNWtm+Pn5GX/88YdhGIYRHR1t1KxZ05gyZYphGIYxfvx4w8/Pz1i7dq1dXe+//77h5+dnbNiwwTAMw5gyZYrh5+dnfPHFF3bLffzxx0aVKlXs9vXKlStGw4YNDT8/P+P06dPp2ocNGzYYfn5+xowZM+zKhw8fblSvXt24ceOGMX/+fMPPz8/46quv7JaZNWuW4efnZ3z33XeGYaT82qRUnvT4xRdftFvu3XffNfz8/IwTJ07Yyvz8/IzXX389zftz+vTpFNfp37+/0bJlSyMmJsauvFu3bkZAQIDtcVIb+eWXX+yWe+ONN4wHHnjAOHr0qK3swoULRu3ate2O+5QpU4zq1asbhw4dslt/woQJhp+fn3Hw4EG7OJPaRXr351abNm2yaytbt241/Pz8jB9//NEwDMP48ssvDT8/P+Pq1au2da5du2a0bdvWmDdvnq2sV69eRsuWLe3q9vPzMwIDA42oqCi78pYtWxq9evWye3xr+zUMw7h+/bpRv3594/HHH091vdTKk9r/re056bVJkt73/a37ahiG0aFDB6Np06bJYrnV7XEkPR47dqzdcv379zceeOABIzIy8o71JUl6DyS9Rilt8/b3/rvvvmvUqlXLuH79ul35sGHDDD8/P1t5Rt9vt7ebpMddu3Y14uPjbet98cUXhp+fnxEcHGwYhmH8/fffhp+fnzFx4kTbMlar1XjhhRfS1MYNwzA+//xzo3r16oafn5/tp0mTJsYnn3xi3Lx507ZcWFiYUadOHWPYsGF261+6dMmoV6+e8fzzz9vKbm8vIiIi9xPlVsqtsjK3Moz/nSv279/frvyXX34x/Pz8jI0bN9qVL1iwwPDz8zNWr15tV3fSa5n0uEWLFkZERESy+hYtWpTqfvj5+Rm1a9c2Ll26ZCvbs2eP3TlqeHi4UbduXSMoKMju3Pbrr782/Pz8UsxRbvfff/8ZTz31lO189ZtvvrnrOqnp1atXsnPVpGO6YMECu/K//vrL8PPzM77++mvDMO4tv0vNDz/8YAQEBNidj9erV8945513jIsXL9qWS0hIMFq3bm306NHD7jhGREQYbdq0MR599FFbWUo5XUqSlru9rd9q+PDhhp+fn+01vv1cv0OHDnafH4aR2OY6d+5snDp1yjCMlHPwpPfPu+++a7duarlRq1at7Nrn0qVL7XLN29dLrT7DSDk3vrVtX7t2zahVq5bxxBNP2H2Pcfr0aaNWrVpG165d7da723tAJKfS9GgiOZy3tzceHh7Mnz+f1atXExkZCcDYsWP5+uuvU10vISGBDRs20LRpU7s5WM1mM4MHD8YwDLthwoDdVV8Wi4XevXsTHR3N5s2b0xVz8+bN2bFjh+0qjG3bttG5c2cKFizIjh07gMQrxKKjo203u1u3bh0VK1ZMdiP3559/HoA//vjDrrxevXp2jzdu3Ii/v7/dvhYqVIiHH344XbEn2bBhA2azmV69etmVv/766/z00094enqybt06vLy8CAoKslumd+/eeHl5JTu+aZU0vDxJ0lV1V65cyVB9d/LFF1/w448/2l2Vc/36dby8vGxt7VaBgYG2fxuGwR9//EGzZs3srkgrVqwYnTt3tltvzZo1+Pn5UaRIEa5du2b7SXq9169fn9m7dtfpG4oXLw7AqFGj2L9/PwAFCxZk9erVaRqmXrNmzTRdNeTn52d3U8cCBQrQqVMnDhw4YDdkPDNk5H1/e3urWrVqhttaSm03Pj6e0NDQDNWXktvf+++//z7r1q2jQIECtrLw8HBcXV0BUmzHt8ro+61t27ZYLJZk6yW9pmvXrgUSb1SaxGQy8eyzz96x3ls999xz/Pnnn7z77rs8+OCDeHh4cPnyZebMmcNjjz1m29amTZsIDw/noYcesnt/WSwWGjZsSHBwsO7tJCIignIr5VZZm1vd6vZj2rFjR7Zs2ULTpk1tZbGxsbZ/3+2ctUWLFnh4eNgeV61aFeCu+UTdunUpUqSI7fHt56xbt24lLCyM3r17253bPvXUU3h5ed2xboB//vmH7t27c+rUKcaMGYO3tzeTJk3i2LFjAHz77be26aozas2aNZhMJlq0aGF3rvvAAw9QpEgRNmzYANx7fpeSJ554gj///JOxY8fSrl07ChQowI0bN1i0aBGdOnWy7ee///7L6dOneeihh7hx44YtxujoaFq2bMnBgwe5ePHiPR2HlCSd45tMphSfL168ONu2beObb76xtfkePXrw008/pWnU/e3tODU9e/a0a5+dO3cmf/78ttcmM23ZsoWoqCj69u1r9z1G6dKl6dy5M/v27ePSpUu28ru9B0RyKk2PJpLDubi48OGHH/LOO+8wZMgQXFxcqF+/Pm3btuWxxx6zfTF5u+vXrxMZGUn58uWTPZf0BXvSjQIh8YvkwoUL2y1XtmzZZMulRfPmzfn+++/Zt28f5cqV49ChQwwbNozjx4/bEovg4GAKFSpkm27gzJkzNGvWLFldRYoUIV++fMliuH3o+NmzZ21zsd6qQoUK6Yr91voKFSqU7ES1SJEitj/4Z86coUyZMsmG6bu4uFCmTJl0H7cktw9vTzoRSW0o8r2wWCycPn2azz77jKNHjxISEnLHk8lbj3toaCihoaEpDnu//biHhIQQHR1No0aNUqw3aU7dzJTUUZDaFGvt27dn7dq1rFq1ilWrVlGkSBFatGjB448/btc5lZq0Tt2W0nsw6QT57NmzdieQ9yq973tIvh8uLi5pmr4rJSnVBZnbdm9/75tMJq5fv84XX3zB4cOHCQkJ4dy5c7Z7Jd1tXzL6fkttX5O2d+rUKQoUKGDXmQTp/0wqVKgQQUFBBAUFERcXx5YtW5gyZQr79u1j2rRpfPDBB4SEhADYpoFIybVr1yhatGi6ti0iIpLXKLdSbpWVudWtUsoVTCYTX375Jbt37yYkJISQkBDbhWZ3O2e927lnRtc7deoU8L/2eetyZcqUuWPdCQkJjBw5EsMwmDdvHhUrViRfvny8+OKLvPzyy3z00UeMHj2aZ555hgceeOCOdd1JSEgIhmHw4IMPpvi8p6cncO/5XWq8vb3p0qULXbp0wWq1smvXLmbMmEFwcDBjx45l9uzZtvPxcePGMW7cuBTrOXfuHMWKFctwHCkJDQ3FYrGQL1++FJ9/7bXXeO655xgzZgxjx46levXqtGrVim7duqUpD73TlH23uv2zwWKxUKpUqQy/b+8k6Z5UKX0eJX0enzt3zpb7ZPS9I+Jo6rQRyQU6depEs2bN+P333/nzzz/ZvHkzwcHBzJ8/nx9++CHFuUuTvrBMSdIfp1vXS2l+4KTlbr3iJi0aNmyIq6srW7du5fLly5jNZurWrcuJEydsN5IMDg6mefPmtitC7hbv7fHdfj8Hk8mU4s3T71TvnaTlJD69Mad1G7fvW1aaM2cO48aNo3z58gQGBtK2bVtq1arFt99+m+y+NGDfFpKu6kmp/d2e8CYkJFC3bl1efPHFFOPIii+Tk27YmnQV2u2cnZ2ZMmUKhw8fZu3atWzcuJGlS5eyZMkShg8fzsCBA+9Yf3rfF7dKajt3e63Tm0ym932flhjSI7UrvDLT7fGuWrWKV199laJFi9KwYUOaN29OjRo1CA4O5osvvkh3fRmN43ZxcXEpfgak9mXQrY4ePcqPP/7IY489ZjfPtrOzM82bNycwMJBWrVqxa9cu4H+v7ahRoyhdunSKdSbNdy8iInK/U26l3Co73P46Hz9+nKeeeoq4uDiaNm1Kx44dqVatGoZh8MILL9y1vqw6Z01PTne7EydOcPz4cbp37277srxNmzb06dOHr7/+2jbCvF27dhkJ3cZqteLp6cm0adNSfD4pznvN726VdF+W5s2bU79+fVu52WwmMDCQL7/8kscee4ydO3faYgQYOnQotWvXTrHOjHZ6psYwDA4dOkTFihVTfP0gMRdevXo1f/31F+vXr+evv/5iypQpfPXVVyxatOiu93BKa7tLKQ80DOOun3eZ3XGS9Dly6+eFoz4DRO6VOm1EcriIiAgOHjxI5cqVeeKJJ3jiiSeIjY1l/PjxzJs3j+DgYFq1apVsPR8fHzw8PDh+/Hiy506cOAH8b/gwJA4Pj4iIsF2lAnDy5Ekg+VU3d+Pm5ka9evXYunUr165do1q1anh5eVGvXj3i4uJYvXo1//33n93JaalSpWxx3ery5cuEh4dTokSJO26zdOnStquEbnX69Ol0xZ6kZMmSbN68OdkxOXDgAHPnzuW5556jVKlS7NmzJ9mXs7GxsZw5c8Z2NU/SScKtw98h64fk301MTAxTp06lQYMGzJ0713bzdCBNN44vVKgQHh4etnZyq9tfi1KlShEREUHjxo3tym/cuMGWLVvS3cbuxmq1smbNGooXL243rcOtzp07x7lz5wgMDKRKlSq8+OKLXLhwgWeeeYY5c+ak66T+TlK6uijpmCVdvWY2m5O1j/j4eK5fv56um8Wn932fF0yYMIGyZcvy448/2g3JT6nTMTuVKVOGzZs3Ex4ebndVaUrvl9uFhoYyd+5cPD09U7w5qoeHB6VKlbJ9tpQqVQpIfP1vf49t27YNq9WaaiInIiJyP1FupdzKUWbNmsXNmzf59ddf7WYqcPQ5a9IFPydPnrQbSWYYBiEhIVSqVCnVdVO7EO3VV19lz5497Nmzhxo1alC3bt17irFUqVIEBwdTo0aNZCNKfvvtN1u+lJn5ndVqZdasWVy9etWu0yaJxWKhfPnyXL161RYjJJ6n334+vnfvXm7cuJGmqbXTY+vWrVy/fp3u3bun+HxCQgKHDh3Cy8uL1q1b20bPrVq1imHDhvHDDz8wcuTITInl9pw3Li7O7n2b1Hlz+/s2I1OUJR3r48ePJ7tAM+kzOq/lvHJ/UnejSA7333//ERQUxJIlS2xlLi4utuHFSX/8kk6Ubr2Cq1mzZmzatIkDBw7Y1jUMg1mzZmEymeyGFxuGwffff297HB8fzzfffIO3t3eqU1rdSfPmzdm1axdbtmyxneRUq1YNb29vpk2bhpOTk918vi1btuTYsWP8/vvvdvV8+eWXAKkOhU7Stm1b/vvvPzZu3GgrCwsL46effkp37JA4Z7DVauWHH36wK1+wYAG//vorhQsXplWrVoSHh9sdN4D58+cTERFhizlp2HHSyA9IPL5r1qzJUGyQ+Hrf61Up0dHRREVFUa5cObsOm4MHD7J9+3ZbnHeKoVWrVmzcuNEugbtx4wYrV660W7ZVq1YcOnSIP//80658xowZDB06lP/++w/4X3u+1337/PPPOXv2LP3790919MfMmTPp06eP3XRwxYsXp2jRonaJx70e6wMHDtjN43zlyhVWrFhBYGCgbbqGwoULc+LECbsrGtetW0dMTIxdXUlxpXYlYnrf93lBaGgoJUuWtOuwOX/+vO39ldVTX6SmTZs2WK1W5s+fb1d+++dFSgICAihVqhTz5s3jyJEjyZ7fu3cvBw8etCVejRs3xtXVldmzZ9vdy+nixYs8//zzfPrpp7b3we1/K0RERO4nyq2UW6UkM3KruwkNDcXd3Z2SJUvaymJjY1m4cCHguHPWZs2a4e7uzsKFC+2Owa+//sq1a9fuuG758uUpWrQov/76q909LMPCwggPDwfg8OHDtmn8MiqpI3XGjBl25evWrWPo0KG2jq/MzO9KlChBYGAgP//8M1u2bEn2/JkzZ9i8ebPtfLxGjRoUKVKEb7/9loiICNty4eHhvPzyy7zxxhvJPl8yOnItqd6PP/4YDw+PZPeBSpKQkEDv3r0ZM2aMXXmtWrXs4siMHHzp0qV2bfiHH34gLCzMdl+tpOkib33fQmIH0u3u9vok5T5fffWVXSfQhQsX+Pnnn6lZs2aap3UTyck00kYkh6tVqxaBgYFMmjSJ8+fPU6VKFc6fP893331HhQoVbCf9SfN0LliwgCtXrtCpUydeffVVtm3bxtNPP83TTz9NkSJFWLt2LVu3bqVv377JrppJ+qK7cuXK/Prrr+zevZuPPvoId3f3dMfdvHlzxowZw5EjR2z3WUgaSrx+/Xrq16+Pt7e3bflBgwaxZs0aXn75ZZ566inKlSvH1q1bWbNmDW3btrW7kXtK+vbty88//8xLL73EM888g4+PD4sWLcrwiVCrVq1o2rQpH3/8Mf/99x/+/v7s3r2b5cuX88ILL1CgQAGefPJJli1bxscff8yRI0eoUaMG+/fvZ+nSpdSuXZsnn3wSgPr161OkSBE+//xzYmJiKFSoED/99NNdbzZ5Jz4+Pmzfvp3FixfTtGlTu5P/tMqfPz+1atVi6dKleHl5Ub58ef777z9++OEH2wlcRETEHadVGjp0KH/++Sfdu3fn6aefxsXFhYULF3Ljxg3gf8Okk17fF154gR49elC5cmV27tzJTz/9RPPmzWnevDmQOP+32Wzmjz/+oGTJkrRt2/aO2z99+rQteTQMg2vXrhEcHMymTZto06ZNspud3iooKIiffvqJoKAgunfvTv78+dm6dSvbt29nyJAhtuV8fHz4+++/mTt3LnXr1rWd5KZV/vz56d+/P3379sVisfD9998THx/PG2+8YVvmkUceYdSoUQwYMIDOnTtz6tQpFi9ebLuK6NZYAGbPnk3z5s1TnGs8ve/73K558+asWrWKd999F39/f86cOcPixYuJiooCsEuaslOTJk1o2bIlEyZM4MSJE/j7+7N582bblx93mkrOYrEwYcIE+vXrR9euXXnkkUfw9/fHycmJ/fv3s3z5cmrUqEGfPn2AxHbxyiuvMHbsWLp3707nzp2Jj49n/vz5xMTE8Prrr9vqTmpDU6ZMoUGDBhn64khERCS3Um6l3ColmZFb3U3z5s1Zt24dgwYNon379oSFhbF8+XLbvVAcdc7q7e3NkCFD+OSTT+jTpw/t2rXj5MmTLFy48K5T0jk5OfH2228zdOhQnnrqKbp3705ERAQLFiwgLCyMt956iylTpjBw4EBmzJhBgwYNMhRjixYtaN26NXPnzuXs2bM0atSIs2fP8v3331OyZEn69+8PZH5+N2bMGHr27Em/fv1o06YN9erVw83Njf/++49ly5ZRsGBB2/vR2dmZt99+m2HDhtGlSxeeeOIJXF1d+eGHHzh37hyffvqp7ULJtOR0t9q8eTMXLlwA/jfybMWKFVy6dIlPP/001anGXVxcePrpp5kxYwYvvPACzZo1Izo6mkWLFuHu7k7Xrl2BlHPw9Dpz5gzPPPMMjzzyCEePHmX+/PkEBATw2GOPAVCuXDmqV6/O4sWL8fDwoFy5cqxduzbF0Xs+Pj4cOnSI+fPnU79+/WSfrQULFrTlPk899RSdOnWytTur1crbb7+d7vhFciJ12ojkcCaTienTpzNt2jTWr1/PokWLyJ8/P23btmXo0KG2KW8aNWpEhw4dWL9+PVu3bqVt27b4+vqyePFiJk+ezMKFC4mOjqZixYp89NFHPPHEE8m2NWfOHN5//32WLVtGpUqVmDZtGm3atMlQ3OXLl8fX15czZ87YDYeuV68e69evT5YoFChQgEWLFjF58mRWrVrFzZs3KVOmDK+99prti8k78fLy4vvvv2f8+PEsWrSIhIQEOnbsSOXKlRk9enS64zebzXz++edMnz6dn3/+mRUrVuDr68u7777LU089BSSeBH399ddMnz6dX3/9lRUrVlC8eHEGDRrEc889ZzvJdXZ2Zvbs2Xz88cfMnj0bDw8PHnnkEdq2bXvHToU7efXVV5kwYQKjRo1i1KhRtpOh9Prss88YO3YsP/74I7GxsZQqVYqBAwdSsWJFXnrpJbZu3XrHOYh9fX357rvv+OSTT/jiiy9wdXXlsccew2KxMGfOHFv7THp9p0yZwm+//caiRYsoWbIkzz//PAMHDrR1Erm7uzNs2DDmzJnD6NGj8fX1vePJ/Y4dO2xXbplMJry8vKhcuTIffPABTz755B3nr61SpQpfffUV06dPZ+7cuYSHh1OuXDneeecdu6uVBgwYwOHDh5k4cSJdunRJd6dNs2bN8Pf3Z86cOYSGhlKrVi0mT55MjRo1bMv07NmT0NBQlixZwqhRo6hatSrTpk1j7ty5dgnoww8/zJo1a1i6dCnbt29P8QQ/ve/73O7999/Hw8ODdevW8dNPP1G8eHEee+wx2rRpw1NPPcXWrVvv6can92LSpElMmjSJX375hZUrVxIQEMCkSZN4/vnn7zpdWUBAACtXrmTOnDls2rSJ3377DcMw8PX15YUXXqBv3752dfTp04dixYrx1VdfMWnSJNzc3KhevTrjx4+3+wxOOiazZ89m37596rQREZH7inIr5VYpyazc6k569OjBzZs3+eGHHxg9ejSFCxemdu3aTJs2jR49erB169Y0vTZZoV+/fri6ujJv3jzGjh1L2bJlmTRpEqNGjbrrOWu7du2YMWMGM2bMYOLEibi5udGwYUOGDh1KxYoVqVmzJm+99dY9TVdlMpn47LPPmD17NsuXL2fdunX4+PjY3rdJozgyO78rW7YsK1euZPbs2WzcuJHg4GDi4+MpWbIkPXr0YODAgXadpe3btyd//vzMmDGDzz//HLPZTOXKlZkxYwYtW7a0LZeWnO5WM2fOtP3bycmJQoUKUbduXfr164e/v/8d1x0yZAgFChTgxx9/5JNPPsFisVCnTh3Gjx9vu59NSjl4er333nusWbOGjz/+GDc3N3r06MErr7xiN6PHlClT+Pjjj1m4cCFOTk60atWKN998kw4dOtjV9dJLL/Hee+8xZswYXnjhhRQvOuzTpw9FixZl7ty5TJw4EXd3d+rXr8+LL76Y4vTSIrmRybiX8XgikieMHDmSZcuWcfjwYUeHIrnM1atX8fHxSTZqYNSoUSxYsIB//vnnrldoieRFYWFhuLi4JLuB6/79++natWue7UQTERG53ym3ktwkNjaW6OjoZPeKAahTpw4PPfQQ48aNu6dtGIZxx1HmIiKSnO5pIyIiGTZ06FAefvhhuzlno6KiWL9+PVWrVlWHjdy31qxZQ+3atdm1a5dd+S+//AJAzZo1HRGWiIiIiIjNxYsXqVevnu1+R0k2bNhAREREppyzqsNGRCT9ND2aiKTJ5cuX07Sch4cHnp6eWRxNxly7di1NN3h0c3OzG+YsqXv00Ud5++23GThwIK1btyYmJoYVK1Zw4cIFPvjgA0eHJ+IwLVu2xNvbm2HDhhEUFESBAgXYs2cPS5cupXPnzvj5+Tk6RBEREXEQ5VaSU5QpU4Y6deowffp0rl+/ToUKFTh9+jTz58+nXLlytvueiIhI9lKnjYikSdOmTdO03IsvvshLL72UxdFkzBNPPMHZs2fvutzjjz/Oxx9/nA0R5X5PPvmkbf7j8ePHYzabqVGjBl9//TX169d3dHgiDuPj48OCBQuYOnUq8+bN4+bNm5QqVYpXXnnFdrNUERERuT8pt5KcZObMmcyYMYM1a9Zw6dIlfHx8ePjhh3n55Zdxd3d3dHgiIvcl3dNGRNJk8+bNaVquTJkylClTJoujyZidO3cSExNz1+WKFi2a4s3uRERERERE7pVyKxEREbkTddqIiIiIiIiIiIiIiIjkAGZHByAiIiIiIiIiIiIiIiK6p02m2717N4Zh4Ozs7OhQRERERESyRVxcHCaTiYCAAEeHIrmE8iYRERERuZ+kJ2fSSJtMZhgGmnEuaxmGQWxsrI6z3JXaiqSV2oqkhdqJpNX92FZ0DizppTaTte7HzyG5N2ozkl5qM5JeajOSXnmtzaTn/FcjbTJZ0pVi/v7+Do4k74qMjOTgwYNUqlQJDw8PR4cjOZjaiqSV2oqkhdqJpNX92Fb27dvn6BAkl1HelLXux88huTdqM5JeajOSXmozkl55rc2kJ2fSSBsREREREREREREREZEcQJ02IiIiIiIiIiIiIiIiOUCu6rQJDg6ma9eu1KpVi1atWjFnzpw7zgMXExPDxIkTadmyJbVq1aJ79+789ddf91yviIiIiIiIiIiIiIhIZss1nTZ79uxh8ODBVKhQgalTp9KpUyfGjx/PrFmzUl3nrbfe4vvvv2fAgAHMmDEDX19fBg0axI4dO+6pXhERERERERERERERkczm5OgA0mrq1KlUq1aN8ePHA9C8eXPi4+OZOXMmvXv3xs3NzW75M2fO8PPPP/Puu+8SFBQEQMOGDdm1axfz588nMDAwQ/WKiIiI5EUJCQnExcU5Oow8ISYmxvbbbM4110ilytnZGYvF4ugwRERERETuS/drrpbb8qrMzJtyRadNbGws27ZtY8iQIXbl7dq1Y/bs2ezcuZMmTZrYPVe0aFGWLFlCuXLlbGVmsxknJyfbC56RekVERETyEsMwuHDhAqGhoY4OJc+wWq04OTlx7ty5XJFcpEWBAgUoXrw4JpPJ0aGIiIiIiNwX7vdcLTfmVZmVN+WKTpvTp08TFxdn1wEDULZsWQBOnDiRrHPFxcUFf39/IPEFvnjxInPnziUkJIS33347w/WKiIiI5CVJSUDRokXx8PDQl/KZICEhgZiYGFxdXXP9CBXDMIiMjOTSpUsAlChRwsERiYiIiIjcH+73XC035VWZnTflik6bsLAwALy8vOzKPT09AQgPD7/j+rNmzWLixIkAdOvWjcaNG2dKvalJepEka0RFRdn9FkmN2oqkldqKpEVebCcJCQlcu3aNokWLUqBAAUeHk2c4OSWeYru6uuaJxMrFxQWr1cqlS5fw8vJKMWEyDCNP7KuIiIiISE6QkJBg67ApVKiQo8NxiISEBADc3NxyfKcNgLu7OwCXLl2iaNGi9xRzrui0sVqtd3z+bsOjWrZsSZ06ddi5cyfTp08nOjqa8ePH33O9qYmLi+PgwYMZWlfS7uTJk44OQXIJtRVJK7UVSYu81k4sFgtms5no6GhHh5LnJE3JmxeYzWbi4uI4cuRIqsu4uLhkY0QiIiIiInlX0j1sPDw8HByJpEfS6xUXF5f3O228vb0BiIiIsCtPGglz+0iZ2/n5+QFQr1494uPjmTp1KsOGDbvnelPj7OxMpUqVMrSu3F1UVBQnT56kXLlyth5MkZSorUhaqa1IWuTFdhITE8O5c+dwc3PDzc3N0eHkGYZh2Ibx56XRJ87OzpQtWxZXV9dkzx09etQBEYmIiIiI5G15KZ+4H2TW65UrOm18fX2xWCycOnXKrjwkJASAihUrJlvn7NmzbN68mc6dO9slltWrVwcShylVq1Yt3fWmhclkUi9oNnB3d9dxljRRW5G0UluRtMhL7cRsNmM2m7FYLLliuHlukTSM32Qy5ZnjmjQiy93dPcUOPiWTIiIiIiIimSNj839lM1dXVwIDA1m7di2GYdjKV69ejbe3NzVr1ky2zrlz53j77bdZu3atXfmmTZtwdnamfPnyGapXREREREREREREREQkK+SKkTYAzz33HH379mXo0KF07dqV3bt3M2fOHIYPH467uzvh4eEcPXoUX19ffHx8qFu3Lo0bN2bUqFGEh4fj6+vL+vXr+f7773nppZfInz9/muoVERERuR9dj7rOzZibDtl2Ptd8FHQvmK51WrVqBcCKFSuSTXE7cuRIzp49y7fffpumugzDYPny5TRv3jzVm35WqVLF7rGLiwvFixenXbt2DBo0yHZvxDNnztC6dWvmzZtHgwYN0rVPGREZGcmyZcsICgrK8m2JiIiIiEj2C4+MJTI63iHb9nBzwssjffeyHDlyJMuWLbvjMocPH053LE8//TSlSpXi448/TtPyrVq14vHHH+ell15K97ayW67ptGnUqBFTp05lypQpvPDCCxQrVozXXnuNfv36AXDgwAF69+7N2LFj6dKlC2azmalTpzJ9+nS+/PJLLl26RLly5fjwww958skn01yviIiIyP3oZsxNtpzZQkx8TLZu19XJlUalG6W70wYSp8cdN24cH3744T3F8PfffzNy5Ej++OOPOy735ptv0rFjRyCxs2Tv3r188skn7Nmzh2nTpuHm5kaJEiUIDg62XTCU1ebOncvSpUvVaSMiIiIikkdFRsdz6NQ14uKt2bpdZyczVcv6pLvT5q233mL48OG2x02bNrXLpTJq6tSp6ZqOesmSJSnenzMnyjWdNgBt2rShTZs2KT7XoEGDZD1yXl5evP7667z++usZrlckU1y/DjczeLVyvnxQMP1fXImIiNyrmPgYYhKyt9PmXpQpU4ZFixbRvn17GjdunOF6bp029068vb0pUqSI7XHZsmUpX748TzzxBCtXruSpp57CYrHYLZPV0hq7iEhekNErjTNylbCIiEhOEhdvzfZOm4zy9vbG29s7Wdm95kkFChRI1/I+Pj73tL3slCvuaSOS6928CVu2wIYN6fvZsiXjnT0iIiL3mc6dO9OoUSPeeustwsPDU10uNDSUDz74gBYtWlCzZk169OjBtm3bANi2bRu9e/cGoHXr1ixdujRdMdSoUYM6derw22+/AYnTo1WpUsVW/8mTJ+nfvz9169YlICCA/v372114dOTIEQYNGkS9evWoUaMGrVu3Zu7cubbno6KieOutt2jSpAn+/v489thjrFmzBki80mzatGmcPXuWKlWqcObMGQB+/PFHOnToQM2aNenQoQPffPMNVqvVLr4vvviCJk2a0Lp16zseOxGRnCTpSuN9x66k+efQqWsOm1JGREREklu6dClt2rRh9OjR1K1bl+effx6A33//nd69e1O3bl38/f3p0qULf/31l229p59+mpEjR9rVkfS7Ro0adOnShZ07d9qWb9WqFVOnTgUSc6c+ffrw5Zdf0rx5c/z9/enVqxfHjh2zLX/t2jWGDRtGYGAgDRo04NNPP6V37962OrKSOm1EsktMTMZ+REREJE1MJhMfffQRN27c4JNPPklxmYSEBPr168eOHTsYP348S5cuxc/Pj/79+7N3714CAgJsJ+E//PBDhobs+/n58d9//6X43CuvvEKxYsX48ccf+eGHHzCbzbz44otAYodMv379KFCgAAsXLmTlypW0b9+eTz75hIMHDwLw2WefcfjwYb788ktWrVpF8+bNGTZsGGfOnKFfv37069eP4sWLExwcTIkSJVi0aBHjxo3jxRdf5JdffuHll19m1qxZfPrpp3ZxLVu2jG+++YbJkycnuyeQiEhOlnSlcXp+REREJGcJCQnh0qVLLF++nGHDhrF//35efvll2rVrx08//cTixYvx8fHhtddeIzY2NsU6zp8/z8KFCxk/fjzLli3D3d2dkSNHpjobwY4dO9i5cydffvkl8+fP5+rVq3zwwQcAWK1WBg0axKlTp5g9ezZz585lz549bN++PcuOwa3UaSMiIiIieUapUqV4/fXXWbx4McHBwcmeDw4O5sCBA0yYMIH69etTqVIlPvjgAypXrsycOXNwcXGx3X/Gx8cHNze3dMfg7e2d6miVkJAQfHx8KFWqFJUqVWLMmDGMHj0aq9VKVFQUvXv35t1336VixYqUK1eOIUOGAP+7MWdISAienp6UKVOGMmXKMHToUGbOnEn+/Pnx9PTEw8PDNiWbxWLh888/57nnnuPhhx+mTJkytGvXjmHDhvHdd98Rc8vFIT179qRSpUr4+/une39FRERERETu1fPPP0+ZMmWoXLkyFouFt99+m6CgIEqXLk21atXo3bs3165d4+rVqymuHxcXxwcffEDt2rWpXLkyffv2JSQkhMuXL6e4fHx8POPGjaNq1ar4+/vTo0cPdu3aBcD27dvZu3cvn376KbVr16Z69epMnjwZF5fsmV41V93TRkRERETkbrp3787q1at5++23Wblypd1zR44cwdvbGz8/P1uZyWQiMDAwxU6ejAgPD091tMqwYcMYM2YM8+fPp379+jRr1oxHHnkEs9mMj48PPXv2ZOXKlfz777+EhIRw6NAhANt0Zs8++yyDBw+mUaNG1KxZkyZNmtCpU6dkc0RD4nD+CxcuMHHiRD777DNbudVqJSYmhjNnzthuxFm2bNlM2XcREREREZGMKFeunO3f1apVw8vLi6+//pqQkBC73CghISHVOipWrGj7d1KOFBcXl+KyhQsXtl2wl7R80rL//vsv+fPnp0KFCnbLly9fPv07lgHqtBERERGRPGf06NF06tSJsWPH2pWnNjTeMAycnDLn1PjAgQNUrVo1xeeCgoJo3749f/75J1u2bGHKlCnMmDGD5cuXYxgG3bt3x8fHh1atWtG0aVP8/f1p0aKFbf2AgAD+/PNPNm3axJYtW1i+fDkzZsxg9uzZNGrUyG5bSR09b7zxBo0bN04WS4kSJbh06RJAhkYUiYiIiIiIZJZbc5Lt27fTv39/mjZtSr169ejcuTNRUVG88MILd6wjpZEwqeWAdxo1Y7FYbPmUI2h6NBERERHJc0qWLMnIkSNZsmQJO3bssJVXqVKFsLAwjhw5YiszDIOdO3dSqVIlIHHkTUbt37+ff/75hw4dOiR77urVq3z44YfExcXRpUsXxo8fz4oVK7h8+TLbt29n5cqVhIaGsmDBAp5//nnatGnDjRs3bDECTJkyhZ07d9K6dWvefvttVq9eTZkyZVi9enWy2AsVKoSPjw+nT5+mbNmytp8DBw4wefLkDO+jiIiIiIhIVpo7dy7169fn008/5ZlnnqFJkyacP38eSL0TJjNVrVqVsLAwjh07Ziu7fv06p06dyvJtg0baiIiIiEgqXJ1cc/U2n3zySX777TeCg4MpUaIEAE2bNqVatWoMHz6cd955h0KFCvHdd99x5MgR3nvvPQA8PDwAOHToEAULFsTT0zPF+sPCwmzzI0dGRrJ3714mTJhAgwYN6NixY7Ll8+fPz4YNGwgJCWH48OF4eXmxdOlSnJ2dqVGjBiaTiaioKH777Tfq1q3L8ePHbSOFkm62efr0aVasWMGoUaPw9fXln3/+4dy5cwQEBNhiv3HjBidOnKB06dI8++yzTJo0iZIlS9K8eXMOHz7M+++/T+vWrbNtPmYREREREclczk7ZPxYjO7dZokQJfv/9d3bv3o2vry9///23bcrnpNwoKzVo0IBatWrx2muv8c477+Dm5sb48eOJioq6p4v80kqdNiIiIiKSTD7XfDQq3ejuC2bRtjNL0jRpSSwWC3PnzuWTTz7hxRdfJDY2lho1avD1119Tu3ZtAPz8/GjRogUvv/wyr7zyCv369Uux7jFjxjBmzBggcWh92bJlCQoKIigoKMWrv5ycnJg1axaffPIJffr0ISoqimrVqvHll1/i6+tLmTJlOHDgAB9//DHh4eGUKlWKJ598kj/++IN9+/bx1FNP8d577/HJJ58wYsQIQkNDKVWqFK+++iqPPvooAG3btmXx4sV07tyZ7777jn79+uHq6sq3337Lxx9/TOHChenWrRtDhgzJtGMsIiIiIiLZx8PNiaplfRy27ewwZMgQLl++zNChQzGZTFSqVIkxY8YwYsQI9u3bZ3fvmqwydepUPvzwQ/r06YOrqys9e/bk+PHjODs7Z/m2TUZ2jCe6j+zbtw8Af39/B0eSd0VGRnLw4EGqVatmuxI2xzt1CjZsgJiY9K3n6goPPgi6OXCG5Mq2Ig6htiJpkRfbSXR0NCdOnKB8+fK6p0kmSkhIIDo6Gjc3NywWi6PDyRR3ays6B5b0UpvJWnnxb1ZKLl2LZN+xK8TFp33OeWcnM/4VC1PUJ+8el4y4X9qMZB61GUkvtZn0Ua7m2Lzq2rVr/PPPPzRt2tTWSRMbG0uDBg147733eOyxx1Jc706vW3rOfzXSRkREREREREREREREhMRZEoYNG0aPHj146qmniIuLY86cObi4uNC8efMs3372T34nIiIiIiIiIiIiIiKSA+XLl4+ZM2eyZ88eHnvsMbp3786VK1eYN28ePj5ZPzWdRtqIiIiIiIiIiIiIiIj8v4YNG7Jw4UKHbFsjbURERERERERERERERHIAddqIiIiIiIiIiIiIiIjkAOq0ERERERERERERERERyQHUaSMiIiIiIiIiIiIiIpIDqNNGREREREREREREREQkB1CnjYiIiIiIiIiIiIiISA7g5OgARERERCQHun4dbt50zLbz5YOCBdO1SqtWrTh79qztsbOzM4ULF6ZFixYMHToUHx8fAKpUqcLYsWPp0qVLpoackri4OL799lv69OmT5dsSEREREZH7Q0JUONaYSIds2+zqgcXdK13rjBw5kmXLlt1xmcOHD2c4pp07d2IYBoGBgRmuI6dRp42IiIiIJHfzJmzZAjEx2btdV1do1CjdnTYA/fr1o1+/fgBER0dz5MgRxo8fT69evVi0aBHe3t4EBwfj7e2d2VGn6JdffmHs2LHqtBERERERkUxjjYkk+uxhiI/P3g07OeFWqkq6O23eeusthg8fbnvctGlT3nzzTTp27JgpYfXs2ZOxY8eq00ZERERE7gMxMdnfaXMPPDw8KFKkiO1xmTJlqFatGg8//DCzZ89m2LBhds9nNcMwsm1bIiIiIiJyH4mPx0iIy9ZNmjK4nre3d7IL57y9vbM1N8ttdE8bEREREcmzSpYsSZs2bfjll1+AxOnRli5dCsDVq1cZMmQIDRo0oGbNmvTo0YPt27fb1j137hzDhg2jUaNGVK9enebNmzN+/HisVisACQkJjB8/nhYtWlCjRg3at2/PggULAFixYgVvvfWWbZvbtm0DYP369XTp0oWaNWvSpk0bJk+eTGxsrG2bVapUYcqUKbRs2ZKmTZty8uTJLD9GIiIiIiIijnK3HGnjxo106dKFWrVq0ahRI0aOHMmNGzeAxPwJ4I033mDkyJEOiT8rqNNGRERERPI0Pz8/Tp8+TUREhF35+++/T0xMDN999x0///wz5cuX5/nnnycyMnF+6Oeee46wsDC++uorfvvtN/r168fs2bNZt24dAPPnz+e3335j0qRJrF69ml69evH++++zc+dO2rZtyxtvvAFAcHAwAQEBbNy4kZdffplu3bqxcuVK3nvvPX799VdGjBhhF9f8+fOZMmUK06ZNo1y5cll/gERERERERBzgbjnS9evXGTJkCF27dmXVqlVMmzaNv//+m3HjxgGJuRbAm2++abtoLi/Q9GgiIiIikqfly5cPgPDwcLvykJAQ/Pz8KFOmDG5ubrz11lt06tQJi8VCdHQ0jz76KB06dKBEiRIA9OnTh1mzZnH48GEeeughQkJC8PDwoHTp0hQtWpRevXpRoUIFypUrh5ubG15eiXM9Jw37nzlzJt26daNHjx4A+Pr68sEHH/DMM89w5swZSpcuDcCjjz6Kv79/thwbERERERERR7lTjjR8+HCuXLlCbGwsJUuWpFSpUpQqVYqZM2eSkJAA/C/XSmkKttxMnTYiIiIikqeFhYUB2DpRkrz44ouMGDGC1atXU7duXZo2bcojjzyCq6srAL169eK3335j7969nDp1isOHD3PlyhXb9GhBQUH8/vvvtGjRgmrVqtGkSRMefvhhChUqRHR0dLI4/v33X/bu3cuSJUtsZUn3vTl27Jit06Zs2bKZfxBERERERERymLvlSPXr1+fhhx9m8ODBFClShCZNmvDggw/Spk0bR4WcLdRpIyIiIiJ52oEDByhXrhyenp525W3atOGvv/7ir7/+YvPmzXz11VdMmzaNxYsXU6pUKXr16kV0dDTt27fn8ccfp2bNmgQFBdnWL1euHGvWrGH79u1s2rSJDRs2MGvWLD766CPat2+fLA6r1cqAAQN4/PHHkz1360043dzcMnHvRUREREREcqY75Ug+Pj4AjB8/nhdffJGNGzeyefNmRowYQd26dfnmm2+yO9xso04bEREREcmzLly4wB9//MGzzz5rVx4bG8uECRN49NFH6dixIx07diQ6OpomTZqwYcMGypYty4EDB9i0aROFCxcGIDQ0lKtXr9qu/Jo3bx6FChXi4YcfpkmTJrz22mv07duXX3/9lfbt22Mymey2WblyZU6cOGE3kmbbtm3MmzeP999/Hw8Pjyw+GiIiIiIiIjnHnXKkd955h5MnT/LHH3/w1ltvUaFCBfr06cOKFSsYMWIEV69epVChQg6MPuuo00ZERERE8oTIyEguX74MQHR0NIcPH2by5MmULl2avn372i3r4uLCvn372LFjB++88w6FCxdm48aNREZGEhAQgIuLCwArVqygXbt2nD9/nokTJxIXF0dsbCwA165dY/r06bi5uVG1alWOHz/OwYMHefrppwFsnTD79++nUqVKPPvss7z88stMmzaNhx9+mAsXLvDWW29RunRpu5E2IiIiIiIi94O75UiXL19m/vz5uLi40K1bN2JiYli1ahXlypWjYMGCQGLedezYMa5fv24ry+3UaSMiIiIiKfv/e7vklm3OnTuXuXPnAuDs7EyJEiXo2LEj/fr1SzY1GsCkSZMYO3Yszz33HGFhYVSoUIFPP/2UwMBAAN544w2+/vprJk+eTLFixejYsSMlSpRg3759QOI9ceLi4hg9ejSXL1+mSJEiPPXUUzz77LPExcXRoEEDatWqRY8ePRg/fjwdOnRg0qRJfPHFF8ycOZMCBQrQqlUrXn311Qzvs4iIZJ/wyFgio+PTvZ6HmxNeHi5ZEJGIiNy3nJww3X2pTN9mZmvfvv0dc6QKFSowZcoUPv/8c+bPn4/ZbKZhw4bMmjULs9kMQL9+/Zg9ezbHjh1j5syZmR6jI6jTRkRERESSy5cPGjVy3LbTad26dWla7vDhw7Z/FytWjMmTJ6e6bJ8+fejTp0+qzzs5OTFixAhGjBhhV56QkEBcXBz58+dn8eLFds916NCBDh06pCk+ERHJWSKj4zl06hpx8dY0r+PsZKZqWR912oiISKYxu3rgVqqKw7Z9r27PeVLLkRISEgB48MEHad26dar1vfTSS7z00kv3HFdOok4bEREREUmuYMHEHxEREbGJi7emq9NGREQks1ncvbC4ezk6DMlC6rQRycuuX4ebNzO2br58+rJOREREREREREREJBup00buP/dTR8bNm7BlC8TEpG89V9fEKXFy076KiIiIiIiIiIiI5HLqtJH7z/3WkRETk/59FREREREREREREZFsp04buT+pI0NEREREREREREREchh12oiIiIjc5wzDcHQIksOpjeQewcHBTJo0iaNHj1KoUCGCgoLo168fJpMpxeVjY2OZO3cuy5cv58KFCxQrVoxOnToxcOBAXFxcbMs1b96cixcvJlt/y5Yt+Pj4ZNn+iIiIiNzPdB6eu2TW66VOGxEREZH7lLOzMwCRkZG4u7s7OBrJySIjI4H/tRnJmfbs2cPgwYPp0KEDQ4cOZefOnYwfP56EhAQGDhyY4jqjR49mxYoVPP/88/j7+7Nv3z6mT5/OuXPnGDNmDADXrl3j4sWLvPbaa9StW9du/Xz58mX5fomIiIjcb5Sr5U6ZlTep00ZERETkPmWxWChQoACXLl0CwMPDI9Wr8SXtEhISiPn/aVgtFouDo7k3hmEQGRnJpUuXKFCgQK7fn7xu6tSpVKtWjfHjxwOJo2Pi4+OZOXMmvXv3xs3NzW7569evs3jxYl599VUGDBgAQKNGjQCYMGECr776Kj4+Phw6dAiANm3a4Ovrm417JCIiInJ/Uq6Wu/KqzM6b1GkjIiIich8rXrw4gC0ZkHtntVqJj4/HyckJs9ns6HAyRYECBWxtRXKm2NhYtm3bxpAhQ+zK27Vrx+zZs9m5cydNmjSxey48PJwePXrQqlUru/IKFSoAcPr0aXx8fDh48CCenp6UKVMma3dCRERERGzu91wtN+ZVmZU3qdNGRERE5D5mMpkoUaIERYsWJS4uztHh5AlRUVEcP34cX1/fPDGVgbOzc46/sk0SO1ji4uIoV66cXXnZsmUBOHHiRLJOmzJlyvD+++8nq+uPP/7A2dnZVtfBgwcpUKAAQ4YMYfPmzVitVlq0aMGbb75J0aJFMxxz0hWJkvmioqLsfudVcXFxxMXGEhtvTftKVjNxcXEZanvZvb3sdL+0Gck8ajOSXmozGZM/f368vLyIj493dCjZLjo6mnPnzlG0aNFkI8ZzIicnJywWS6pt3DCMNI+WUqeNiIiIiGCxWPTFfCaxWhO/zHN1dc0VyYXkDWFhYQB4eXnZlXt6egKJo2rSYu3atSxbtoxevXqRP39+AA4dOsTFixfp1q0bzzzzDMeOHWPKlCk8/fTTLFu2DA8PjwzFHBcXx8GDBzO0rqTNyZMnHR1ClrFYLJhcvLl46SLRsWn/IsvNxYkSBU1cPh9GQkJCjt2eo+TlNiNZQ21G0kttRtLr3Llzjg4h07i4uKRpOXXaiIiIiIiI5HJJnYWpScuUEmvWrGH48OHUrVuXESNG2MpHjRqFxWKhZs2aAAQGBlKpUiV69uzJ8uXL6dmzZ4ZidnZ2plKlShlaV+4sKiqKkydPUq5cuTwx4i8118PiKFbUSNfIFxcnM4ULFaagd4kcv73sdL+0Gck8ajOSXmozkl55rc0cPXo0zcuq00ZERERERCSX8/b2BiAiIsKuPGmEze0jcG739ddf88knn1C/fn2mT5+Oq6ur7bmAgIBky9etWxdvb28OHTqU4ZhNJlOGR+lI2ri7u+fpYxweHYmziwuY096J4uxkxtnZOUPHJbu35wh5vc1I5lObkfRSm5H0yittJq1TowHkjjv4iIiIiIiISKp8fX2xWCycOnXKrjwkJASAihUrprieYRiMHj2asWPH0rFjR2bNmmXXwRMWFsaSJUs4cuSI3XpWq5W4uDh8fHwyeU9ERERERO5v6rQRERERERHJ5VxdXQkMDGTt2rUYhmErX716Nd7e3rapzW43ceJEvv32W/r27cunn36abJ5tFxcXRo0axRdffGFXvm7dOqKjo2nQoEHm74yIiIiIyH0sV02PFhwczKRJkzh69CiFChUiKCiIfv36pTq0KDY2lrlz57J8+XIuXLhAsWLF6NSpEwMHDrRLRpo3b87FixeTrb9lyxZdOSYiIiIiIrnCc889R9++fRk6dChdu3Zl9+7dzJkzh+HDh+Pu7k54eDhHjx7F19cXHx8fDh48yKxZs/D396d9+/b8888/dvVVqlQJLy8vnn32WaZOnUrhwoVp0aIFR44cYerUqbRu3ZpGjRo5aG9FRERERPKmXNNps2fPHgYPHkyHDh0YOnQoO3fuZPz48SQkJDBw4MAU1xk9ejQrVqzg+eefx9/fn3379jF9+nTOnTvHmDFjALh27RoXL17ktddeo27dunbr58uXL8v3S0REREREJDM0atSIqVOnMmXKFF544QWKFSvGa6+9Rr9+/QA4cOAAvXv3ZuzYsXTp0oU1a9ZgGAb79u2je/fuyeqbN28eDRo04Pnnn8fHx4f58+ezYMECChQoQI8ePXjppZeyexdFRERERPK8XNNpM3XqVKpVq8b48eOBxNEx8fHxzJw5k969e+Pm5ma3/PXr11m8eDGvvvoqAwYMALBdBTZhwgReffVVfHx8bDfObNOmDb6+vtm4RyIiIiIiIpmrTZs2tGnTJsXnGjRowOHDh22Phw4dytChQ+9ap9lspmfPnvTs2TPT4hQRERERkZTlinvaxMbGsm3btmTJR7t27YiIiGDnzp3J1gkPD6dHjx60atXKrrxChQoAnD59GoCDBw/i6elJmTJlsih6ERERERERERERERGRu8sVI21Onz5NXFwc5cqVsysvW7YsACdOnKBJkyZ2z5UpU4b3338/WV1//PEHzs7OtroOHjxIgQIFGDJkCJs3b8ZqtdKiRQvefPNNihYtmqF4DcMgMjIyQ+vK3UVFRdn9Ti+nuDiMuDiIjU3fimYzprg44jPw2jpim47cbk5xr21F7h9qK5IWaieSVvdjWzEMI9X7TIqIiIiIiEja5YpOm7CwMAC8vLzsyj09PYHEUTVpsXbtWpYtW0avXr3Inz8/AIcOHeLixYt069aNZ555hmPHjjFlyhSefvppli1bhoeHR7rjjYuL4+DBg+leT9Ln5MmT6V7HYrFQLDqa+IsXsaazQ8Ls4YHTlStcDA8nISEhR2/TkdvNiTLSVuT+pLYiaaF2Iml1v7UVFxcXR4cgIiIiIiKS6+WKThur1XrH583mu8/ytmbNGoYPH07dunUZMWKErXzUqFFYLBZq1qwJQGBgIJUqVaJnz54sX748Q/M2Ozs7U6lSpXSvJ2kTFRXFyZMnKVeuHO7u7ule3+ncOYxixSA6On0rurlhKlyY/CVL5optOnK7OcW9thW5f6itSFqonUha3Y9t5ejRo44OQUREREREJE/IFZ023t7eAERERNiVJ42wuX0Ezu2+/vprPvnkE+rXr8/06dNxdXW1PRcQEJBs+bp16+Lt7c2hQ4cyFK/JZMrQCB1JH3d394wdZ2fnxJ+7dAamtp5LbtmmI7ebw2S4rch9R21F0kLtRNLqfmormhpNREREREQkc9x9iEoO4Ovri8Vi4dSpU3blIf/H3p3HV1Hd/x9/zczdsi8Ewr5GAZVNUIwoKIqIu1D3FVTcKrR1qda2P+tS2+LSglr7VaxV61p3bUUUNxQREJAdAgQCgbBkz81dZ35/RNBIgCQkuVnez8fjPixz55zzOTcHmrmfOZ/ZvBmAPn361NjOcRzuv/9+HnzwQc444wyeeuqpagmesrIy/vOf/7B27dpq7WzbJhwOk56e3sAzERERERERERERERERqVmLSNp4vV6GDRvG7NmzcRxn7/FZs2aRlJS0t7TZTz3yyCM8//zzTJw4kYceemifOtsej4f77ruPf/zjH9WOz5kzh0AgwPDhwxt+MiIiIiIiIiIiIiIiIjVoEeXRAG688UYmTpzI1KlTmTBhAosXL2bmzJnceuutxMXFUV5eTk5ODt27dyc9PZ1Vq1bx1FNPMWDAAE4//XSWLl1arb+srCwSExO57rrrmDFjBhkZGYwaNYq1a9cyY8YMTjnlFLKzs2M0WxERERERERERERERaWtaTNImOzubGTNmMH36dG6++WYyMzO54447mDRpEgArVqzgyiuv5MEHH2T8+PF8+OGHOI7DsmXLuOiii/bp77nnnmP48OHcdNNNpKen8+KLL/LSSy+RmprKxRdfzC233NLUUxQRERERERERERERkTasxSRtAMaMGcOYMWNqfG/48OGsWbNm75+nTp3K1KlTD9qnaZpceumlXHrppQ0Wp4iIiIiIiIiIiIiISF21iGfaiIiIiIiIiIiIiIiItHYtaqeNiIiIiIiIiDRP5f4Q/kCkzu3ifS4S4z2NEJGIiIhIy6OkjYiIiIiIiIgcMn8gwupNhYQjdq3buF0m/XqkK2kjIiIi8j0lbURERERERESkQYQjdp2SNiIiIiJSnZ5pIyIiIiIiIiIiIiIi0gwoaSMiIiIiIiIiIiIiItIMKGkjIiIiIiIiIiIiIiLSDChpIyIiIiIiIiIiIiIi0gwoaSMiIiIiIiIiIiIiItIMKGkjIiIiIiIiIiIiIiLSDChpIyIiIiIiIiIiIiIi0gwoaSMiIiIiIiIiIiIiItIMKGkjIiIiIiIiIiIiIiLSDChpIyIiIiIiIiIiIiIi0gwoaSMiIiIiIiIiIiIiItIMKGkjIiIiIiIiIiIiIiLSDChpIyIiIiIiIiIiIiIi0gwoaSMiIiIiIiIiIiIiItIMKGkjIiIiIiIiIiIiIiLSDChpIyIiIiIiIiIiIiIi0gwoaSMiIiIiIiIiIiIiItIMKGkjIiIiIiIiIiIiIiLSDChpIyIiIiIiIiIiIiIi0gwoaSMiIiIiIiIiIiIiItIMKGkjIiIiIiIiIiIiIiLSDChpIyIiIiIiIiIiIiIi0gy4Yh2AiIiIiIiIiIhUV+4P4Q9E6twu3uciMd7TCBGJiIhIU1DSRkRERERERESkmfEHIqzeVEg4Yte6jdtl0q9HupI2IiIiLZiSNiIiIiIiIiIizVA4YtcpaSMiIiItn55pIyIiIiIiIiIiIiIi0gwoaSMiIiIiIiIiIiIiItIMqDyaiIiIiIiIiLQ4BlXPcKkLt8vEMBonHhEREZGGoKSNiDSsoiIoLa1f2+RkSEtr2HhERERERKRV8hCkky9A1HZq3cYyDdzBYsLF5XuPmd54rLjExghRREREpM6UtBGJsYpQBYFIoMb3DDsOM1BCWUketrP/h08me5NJi2smyY7SUpg3D4LBurXzeiE7W0kbERERERGpFSdUiT9vNaFA7a89LMsgsV0CVpyn6oDLha9LXyVtREREpNlQ0kYkxgKRABuKNhC2I/u854pPxFvch1WhlQSjNV+IeF1esrtmN5+kDVQlbOqatBEREREREamjaDhEJBSq9fmOZWBHPDjRqhppqpQmIiIizY2SNiLNQNiOELHD+75hh3E5UYLR4H6TNiIiIiIiIiIiIiLSOtTtiX0iIiIiIiIiIiIiIiLSKJS0ERERERERaSXmzp3LhAkTGDRoEKNHj2bmzJk4zv4f0h4KhXjyySc5/fTTGTx4MGPHjuWxxx4j9JNyU8uWLeOKK65gyJAhnHDCCTzyyCP7nCMiIiIiIodO5dFERERERERagSVLlnDDDTcwbtw4pk6dyqJFi5g2bRrRaJTJkyfX2Ob+++/nnXfe4aabbmLAgAEsW7aMxx9/nPz8fP74xz8CkJeXx8SJExk8eDB//etfWb9+PY8++ijFxcXce++9TTlFEREREZFWT0kbERERERGRVmDGjBn079+fadOmATBy5EgikQhPPvkkV155JT6fr9r5RUVFvPrqq9x2221ce+21AGRnZwPw8MMPc9ttt5Gens5TTz1FQkICTzzxBB6Ph1GjRuHz+bjvvvu44YYb6Ny5c9NOVERERESkFVN5NBERERERkRYuFAoxf/58xowZU+342LFjqaioYNGiRfu0KS8v5+KLL2b06NHVjvfu3Ruo2mEDVSXXRo0ahcfj2XvO6aefjm3bzJ07t6GnIiIiIiLSpmmnjYiIiIiISAuXl5dHOBymZ8+e1Y736NEDgI0bNzJixIhq73Xr1o177rlnn74+/vhj3G43PXv2JBAIsHXrVnr16lXtnPT0dBITE9m4cWO9Y3YcB7/fX+/2sn+VlZXV/ttUwuEw4VCIUMSufSPbJBwO12st2HaUaMQmEo3WvpFjEI1G9z6TyXA5WJEI4VqM39Tza8rxYrVmpOXSmpG60pqRumpta8ZxHAzDqNW5StqIiIiIiIi0cGVlZQAkJiZWO56QkABU7aqpjdmzZ/Pmm29y+eWXk5KSws6dO2vsd0/fte23JuFwmFWrVtW7vRxcbm5uk41lWRaGJ4mCHQUEQpFat/N5XHRKM9i5rYxoHZIvHo+HtDgvZeVl+Ctqn6Bwu0xS4qGsJIht21geL0mJu9gd2HHA8Zt6fk093h5NuWakddCakbrSmpG6ak1r5sc71w9ESRsREREREZEWzrYPfCe+aR68MvaHH37IrbfeytChQ7n99ttr1W9t7xasidvtJisrq97tZf8qKyvJzc2lZ8+exMXFNdm4RWVhMjs4ddoZ4nGZZLTLIC2pU53HCxTvJikxCbfLXes2LtMgMTGReG8KAIbLTVxGBu3iUw/atqnn15TjxWrNSMulNSN1pTUjddXa1kxOTk6tz1XSRkREREQI9yEuAAEAAElEQVREpIVLSkoCoKKiotrxPTthatop82PPPvssf/7znzn22GN5/PHH8Xq91dr9tN89fe8Ztz4MwyA+Pr7e7eXg4uLimvQzLg/4cXs8YNY+yeB2mbjd7nrFGSotxnKZuCyr1m0sy8CyrL13uhqWG7fLjbsW41cE/cTH+3AfIIli2w5R29n750OZX1N/ntD0a0ZaPq0ZqSutGamr1rJm6nKzU4tK2sydO5dHH32UnJwc2rVrx2WXXcakSZP2O+FQKMQzzzzDW2+9xfbt28nMzOTss89m8uTJ1bYiLVu2jL/85S8sX76chIQExo8fz89//vNab1cSERERERGJpe7du2NZFps2bap2fPPmzQD06dOnxnaO4/DAAw/w/PPPc9ZZZ/Hggw9Wuw5KSEggMzNzn353795NRUXFfvsVaTFMC5wo4eIdBz3VHYzQyReolpT5qajlI7/EPuA5IiIiIgfSYpI2S5Ys4YYbbmDcuHFMnTqVRYsWMW3aNKLRKJMnT66xzf33388777zDTTfdxIABA1i2bBmPP/44+fn5/PGPfwSqHtg5ceJEBg8ezF//+lfWr1/Po48+SnFxMffee29TTlFERERERKRevF4vw4YNY/bs2VxzzTV7b2ybNWsWSUlJDBw4sMZ2jzzyCM8//zwTJ07k17/+dY03xI0YMYJPP/2Uu+66a29CZ9asWViWxXHHHdd4kxJpAoZhYocChHblQeTAz46prAxRtruCaLTmhIzL7SGuez9M06ukjYiIiNRbi0nazJgxg/79+zNt2jQARo4cSSQS4cknn+TKK6/E5/NVO7+oqIhXX32V2267jWuvvRaA7OxsAB5++GFuu+020tPTeeqpp0hISOCJJ57A4/EwatQofD4f9913HzfccAOdO3du2omKiIiIiIjUw4033sjEiROZOnUqEyZMYPHixcycOZNbb72VuLg4ysvLycnJoXv37qSnp7Nq1SqeeuopBgwYwOmnn87SpUur9ZeVlUViYiLXXnst77//Ptdeey0TJ04kNzeXRx55hAsvvFDXS9J6RCI40fABT7EjYSKh0H6TNiIiIiIN4eBPo2wGQqEQ8+fPZ8yYMdWOjx07loqKChYtWrRPm/Lyci6++GJGjx5d7Xjv3r2Bqh02UFVybdSoUdVKAJx++unYts3cuXMbeioiIiIiIiKNIjs7mxkzZrBx40Zuvvlm3n33Xe644w6uu+46AFasWMFFF13Ep59+CsCHH36I4zgsW7aMiy66aJ/XihUrgKrSas888wyBQIApU6bwz3/+k6uvvpq77747VlMVEREREWm1WsROm7y8PMLhMD179qx2vEePHgBs3LiRESNGVHuvW7du3HPPPfv09fHHH+N2u+nZsyeBQICtW7fSq1evauekp6eTmJjIxo0b6xWv4zj4/f56tZWDq6ysrPbfunKFwzjhMIRCdWtomhjhMJF6/GwPNGY0Gt372mfIiE00GiUcDhOK1Byv6TIJh8M1rrnmNtfGGnN/DnWtSNuhtSK1oXUitdUW14rjOHV6sKY0njFjxuxzs9sew4cPZ82aNXv/PHXqVKZOnVqrfocNG8arr77aIDGKiIiIiMj+tYikTVlZGQCJiYnVjickJABVu2pqY/bs2bz55ptcfvnlpKSksHPnzhr73dN3bfv9qXA4zKpVq+rVVmovNze3zm0syyIzECBSUIBdx+SAGR+Pa9cuCsrLa0yw1GdM0zQJu8KUlZbWmJTxRBziysspCBfgD9Ucb7wnnl2JuyjfWj2u5jbXxhqzNuqzVqRt0lqR2tA6kdpqa2vlxzvXRUREREREpH5aRNLGtu0Dvm+aB6/y9uGHH3LrrbcydOhQbr/99lr1W9+7Bd1uN1lZWfVqKwdXWVlJbm4uPXv2JC4urs7tXfn5OJmZEAjUraHPh5GRQUo96nYfaMySYDFJwWQiNdRPdscn4U1MJNOTSSBSc7w+l4+MjAw6J+wbV3Oba2ONuT+Hulak7dBakdrQOpHaaotrJScnJ9YhiIiIiIiItAotImmTlJQEQEVFRbXje3bC1LRT5seeffZZ/vznP3Psscfy+OOP4/V6q7X7ab97+t4zbl0ZhkF8fHy92krtxcXF1e9zdrurXgdJ2u2vnaeBx7QiFpZl4Rj7vme6TCzLwu12Y5s1x+u23Hjcnpo/i2Y210Yb8yDqvVakzdFakdrQOpHaaktrRaXRREREREREGkaLSNp0794dy7LYtGlTteObN28Gqh6MWRPHcXjggQd4/vnnOeuss3jwwQerlW1ISEggMzNzn353795NRUXFfvsVaU5cpouIHWFTcfV1bBomSYES7MoinMDBa+r7XD4SPAmNFaaIiIiIiIiIiIiIHESLSNp4vV6GDRvG7Nmzueaaa/beyTdr1iySkpIYOHBgje0eeeQRnn/+eSZOnMivf/3rGu8AHDFiBJ9++il33XXX3oTOrFmzsCyL4447rvEmJdJALMOiPFTOyl0rCUaCe497LS/9/QkEi9YT8R/4+Uxu00XvtN5K2oiIiIiISL0ZBrhdBy5fbtsOUdtpoohEREREWp4WkbQBuPHGG5k4cSJTp05lwoQJLF68mJkzZ3LrrbcSFxdHeXk5OTk5dO/enfT0dFatWsVTTz3FgAEDOP3001m6dGm1/rKyskhMTOTaa6/l/fff59prr2XixInk5ubyyCOPcOGFF9K5AZ+tIdLYgpEgwWiw2rGo4yNih4nY+z4vR0REREREpDaileXYQf9Bz3MHI3TyBQ6YlIlaPvJLbCVuRERERPajxSRtsrOzmTFjBtOnT+fmm28mMzOTO+64g0mTJgGwYsUKrrzySh588EHGjx/Phx9+iOM4LFu2jIsuumif/p577jmGDx9Onz59eOaZZ/jLX/7ClClTSEtL4+qrr2bKlClNPUURERERERGRZscO+glsXQORyAHPq6wMUba7gmi05oSMy+0hrns/TNOrpI2IiIjIfrSYpA3AmDFjGDNmTI3vDR8+nDVr1uz989SpU5k6dWqt+h02bBivvvpqg8QoIiIiIiIi0upEIjjRA+/gtyNhIqHQfpM2IiIiInJwBy42KyIiIiIiIiIiIiIiIk1CSRsREREREREREREREZFmQEkbERERERERERERERGRZkBJGxERERERERERERERkWZASRsRERERERERkTbONPUVkYiISHPginUAIiIiIiIiIiISW76EFIrKwpQH/HVqF+9zkRjvaaSoRERE2h4lbURERERERERE2rhQxGF1biGYVq3buF0m/XqkK2kjIiLSgJS0ERERERERERERwpEomEaswxAREWnTVLBURERERERERERERESkGVDSRkREREREREREREREpBlQ0kZERERERERERERERKQZUNJGRERERERERERERESkGVDSRkREREREREREREREpBlQ0kZERERERERERERERKQZUNJGRERERERERERERESkGXDFOgAREREREREREanOANyuut1r63aZGEbjxCMiIiJNQ0kbEREREREREZFmxkOQTr4AUdupdRvLNHAHiwkXl1c7bnrjseISGzpEERERaQRK2oiIiIiIiIiINDNOqBJ/3mpCgWCt21iWQWK7BKw4zw8HXS58XfoqaSMiItJCKGkjIiIiIiIiItIMRcMhIqFQrc93LAM74sGJ/lAjTdXSREREWpa6FUcVERERERERERERERGRRtGoSZuCgoLG7F5ERERERKRF0zWTiIiIiIj8WKMmbU4++WSuvfZa/vvf/xKqw3ZeERERERGRtkDXTCIiIiIi8mONmrR58MEHsW2b2267jRNOOIE//OEPLFu2rDGHFBERERERaTF0zSQiIiIiIj/maszOzz33XM4991wKCgp48803efvtt3nppZfIyspi/PjxnHPOOWRkZDRmCCIiIiIiIs2WrplEREREROTHGnWnzR6ZmZnccMMN/O9//+P1118nLS2NadOmcdJJJ3HLLbewdOnSpghDRERERESkWdI1k4iIiIiIQBMlbQAWLlzI7373O6655hoWLVrEiBEjuPPOO6msrOSSSy7h2WefbapQREREREREmh1dM4mIiIiISKOWR9u0aRNvv/0277zzDlu3bqVLly5cccUVjB8/nk6dOgFw+eWXc9ttt/H3v/+dq6++ujHDERERERERaVZ0zSQiIiIiIj/WqEmbsWPH4vV6OfXUU7nvvvvIzs6u8bzevXuTm5vbmKGISBtlWVasQxARERHZL10ziYiIiIjIjzVq0uZ3v/sd55xzDklJSQc876abbuKmm25qzFBEpLUrKoLS0mqHXOEwmYEArvx8cLv33zY5GdLSGjlAERERkX3pmklERERERH6sUZM2s2bN4rjjjqvxAmT16tXcfvvtvPvuu40Zgoi0FaWlMG8eBIN7DznhMJGCApzMzP0nbbxeyM5W0kZERERiQtdM0lhMs8keYSsiIiIiDajBkzYLFy7EcRwAvvnmGxYsWEBhYeE+533yySfk5eU19PAi0pYFg9WSNoRC2H4/BAJg27GLS0RERORHdM0kTcGXkEJRWZjygL9O7eJ9LhLjPY0UlYiIiIgcTIMnbV577TXefvttDMPAMAz+8Ic/7HPOnguUs846q6GHFxERERERadZ0zSRNIRRxWJ1bCGbtn/Hodpn065GupI2IiIhIDDV40ua3v/0tEyZMwHEcrrrqKn7/+9+TlZVV7RzTNElOTuawww5r6OFFJIaKK4shUIJdWYQTqKxTW8OOwwyUQGUxqXGpjRKfiIiISHOgayZpKuFIFEwj1mGIiIiISB00eNImKSmJY489FoDnnnuOI488koSEhIYeRkSaobJQGaWlW6goWk/EX16ntq74RBJKDyc5lKakjYiIiLRqumYSEREREZH9afCkzVtvvcWoUaNIS0sjPz+f/Pz8A55/3nnnNXQIIhJDETtKxA4TscN1a2iHidjRxglKREREpBnRNZOIiIiIiOxPgydt7rzzTl599VXS0tK48847D3iuYRi6ABERERERkTZF10wiIiIiIrI/DZ60+fjjj2nfvv3e/y3SXFWEKghEArU+f88zV8pK8rAdG4BkbzJpcWmNFaKIiIiItEK6ZhIRERERkf1p8KRNly5davzfe0QiEcrLy0lNTW3ooUXqJBAJsKFoA2E7UqvzXfGJeIv7sCq0kmA0iNflJbtrtpI2IiIiIlInumYSEREREZH9MRuz80gkwmOPPca7774LwPz58xkxYgTZ2dlcddVVlJSUNObwIgcVtiN7n79Sm1fUiRKMBqtekWCswxcRERGRFq6hr5nmzp3LhAkTGDRoEKNHj2bmzJk4jlOrtitXruTII49ky5Yt+7w3cuRI+vbtu8+rsLCwTvGJiIiIiMiBNWrSZvr06fz973+ntLQUgPvvv5/U1FTuuusuNm/ezMMPP9yYw4uIiIiIiDRrDXnNtGTJEm644QZ69+7NjBkzOPvss5k2bRpPPfXUQduuXbuWyZMnE4nsuwu9sLCQgoIC7rjjDl555ZVqr+Tk5NpPVkREREREDqrBy6P92Pvvv8+vfvUrLrvsMtavX8+6dev405/+xHnnnUdqaip/+ctfuPfeexszBBERERERkWarIa+ZZsyYQf/+/Zk2bRpQtTsmEonw5JNPcuWVV+Lz+fZpEwqFeOGFF5g+fTper7fGflevXg3AmDFj6N69ez1nKiIiIiIitdGoO2127NjBoEGDAPj0008xTZORI0cC0LFjR8rKyhpzeBERERERkWatoa6ZQqEQ8+fPZ8yYMdWOjx07loqKChYtWlRju88//5zHHnuM66+/nttuu63Gc1atWkVCQgLdunWr7bRERERERKSeGjVp06FDh731kOfMmUP//v1JT08HYPHixXTs2LExhxcREREREWnWGuqaKS8vj3A4TM+ePasd79GjBwAbN26ssd2AAQOYM2cON954I5Zl1XjOqlWrSE1NZcqUKQwdOpQhQ4bwi1/8gh07dtQqNhERERERqb1GLY921lln8eCDD/Luu++yaNEifv/73wPwwAMP8NJLL3HDDTc05vAiIiIiIiLNWkNdM+3ZkZOYmFjteEJCAgDl5eU1tsvMzDxo36tXr6agoIALL7yQq666ivXr1zN9+nSuuOIK3nzzTeLj42sV4085joPf769XWzmwQCAAQDgSwcGufUPbJBwO7/tziUQIhUM4kfABm0ejUaKRKBHb2c8JNtFolHAoRChiH3jM2oRrR4lGbCLRaO0bOQbRaJRQKASAabowbbvVzg/AcDlYkQjhA8TQ4GtGWr3Kyspq/xU5GK0ZqavWtmYcx8EwjFqd26hJm1/84hfEx8ezYMECbr31Vi699FIAli1bxqRJk7jxxhvr1N/cuXN59NFHycnJoV27dlx22WVMmjSpVpNduXIlF1xwAbNmzaJr167V3hs5ciQFBQX7tJk3b97eu9xEREREREQaWkNdM9n2gb9kNc36F1m47777sCyLgQMHAjBs2DCysrK49NJLeeutt/bGXFfhcJhVq1bVOy7ZP8uyMDxJFBbuJhCK1Lqdz+OiU5rBzm1lRL9PFFiWRTufSdmOHURDwf22NU0Tw/JSWlZKOFLzenR7fZjl5RTsCO6Nq6Yxa8Pj8ZAW56WsvAx/Re0TBm6XSUo8lJUEsW0bT0IyGUkd2LlrF+HA/r8UaqnzA7A8XpISd7E7sGO/MTTkmpG2JTc3N9YhSAujNSN11ZrWjMfjqdV5jZq0MQyD66+/nuuvv77a8ZdffrnOfS1ZsoQbbriBcePGMXXqVBYtWsS0adOIRqNMnjz5gG3Xrl3L5MmTiUT2/cWjsLCQgoIC7rjjDoYOHVrtveTk5DrHKSIiIiIiUlsNdc2UlJQEQEVFRbXje3bY/HQHTl0MGTJkn2NDhw4lKSmJ1atX17tft9tNVlZWvdvL/gUCAfK2F5Ge3g6nDlXRPS6TjHYZpCV1qv6Gv5j48g4H3YniD0ZJ9rPfnSguj5fExEQyndS9O1H2O2YtBIp3k5SYhNvlrnUbl2mQmJhIvDcFANMXjy8+nvYZGa1yfgCGy01cRgbt4lP3P1ZDrxlp9SorK8nNzaVnz57ExcXFOhxpAbRmpK5a25rJycmp9bmNmrSBqm36X3/9NX6/H8fZ9xeb8847r1b9zJgxg/79+zNt2jSgandMJBLhySef5Morr8Tn8+3TJhQK8cILLzB9+nS8Xm+N/e65yBgzZgzdu3ev5axEREREREQaRkNcM3Xv3h3Lsti0aVO145s3bwagT58+9Y5t1qxZDBw4kMMPP3zvcdu2CYfDh1SZwDCMepdWk9pxu1xg1v6y3+0ycbvd+/xcwqFyom4PjnngKhfBSAjLZUF0P0kNy8SyLNweD5j2AcesjVBpMZbLxLWf5zHVxLIMLMvae6er6fJgmSaeVjo/AMNy43a5cNcihoZaM9J2xMXF6ecvdaI1I3XVWtZMbUujQSMnbb744gumTJmy37pzhmHU6gIkFAoxf/58pkyZUu342LFjefrpp1m0aBEjRozYp93nn3/OY489xvXXX09GRga//e1v9zln1apVJCQk0K1bt9pNSqShOQ7xO4rwbd+Jp8yPt9SP4ThEfB7s5CSinnS8QzsRTKk58SgiIiIiLVdDXTN5vV6GDRvG7Nmzueaaa/ZeFM6aNYukpKS9pc3qyuPxcN9993Hqqafy8MMP7z0+Z84cAoEAw4cPr1e/IiIiIiJSs0ZN2jz88MP07t2bu+66i8zMzHrXUc7LyyMcDtOzZ89qx3v06AHAxo0ba0zaDBgwgDlz5pCamsobb7xRY9+rVq0iNTWVKVOm8NVXX2HbNqNGjeI3v/kNHTp0qFe8IgflOLB6NSxYQOryZbQrKd3/uR98TR+gpGt78kYcRc7px7LjqF5Qh+ysiIiIiDRPDXXNBHDjjTcyceJEpk6dyoQJE1i8eDEzZ87k1ltvJS4ujvLycnJycujevXutd8h4vV6uu+46ZsyYQUZGBqNGjWLt2rXMmDGDU045hezs7HrHKyIiIiIi+2rUpM369et54oknGDZs2CH1U1ZWBuxbhzkhIQH4oU7zT2VmZh6079WrV1NQUMCFF17IVVddxfr165k+fTpXXHEFb775Zr22XjmOg99f+wcFSt3suQtxf3cjHowrHMYJh4lGo3tftWFGbKLRKOFwmFAkhOkyCYfDtfpZ7xmTykrMRYuw5szB3LoVAAuIuixKO6UTSE4glBSHbZq4AyE8YZvE8hDxG/NI2bKTlFc+4ahXPqGkcwYrzslmxXknEO4QR9T+Ia698bpMotEodsQmGjnwHA2r6txg6Pv2pokRDhOp4zoOh8PYtl2rMX/KjNh7y2zU5+/P3s849MNnEAmHMU2TSPgAtanrOVdpXQ713xVpG7ROpLba4lpxHKdO2/3lBw11zQSQnZ3NjBkzmD59OjfffDOZmZnccccdTJo0CYAVK1Zw5ZVX8uCDDzJ+/Pha93vTTTeRnp7Oiy++yEsvvURqaioXX3wxt9xyyyHHLCIiIiIi1TVq0qZz5877TajUhW3bB3z/UO5Gu++++7Asa2+5gGHDhpGVlcWll17KW2+9xaWXXlrnPsPhMKtWrap3TFI7ubm5dW5jWRaZgQD2zp0EQ+WUlZZWS3QciCfiEFdeTkG4AH/IT7wnnl2JuyjfWn7AxM+eMa0vvyTtnXdwFxYCYLvd+AcOpKx/H5Ym+Amwbx+ehGTiThvHoqJ1ZC5dy4CvVtL/m7Wk5O/i+CffZdg/P2DlaccSvfVX7KzYSXngh79v8Z54yt1uKktLCVUcYCcP4HF5KPeWEywOYts2Znw8rl27KCg/8Nx+Os9IfIRARTmltRhznxgiDlSUEy0spHRLaa3H3TN2ZiBApKAAp7IS02sRsoNVb7qgoLRgv23NuHhcJTvYbhcTiUb2Hk9wJRApjxz03x9pXerz74q0PVonUlttba38+PkJUnsNdc20x5gxYxgzZkyN7w0fPpw1a9bst+348eNrTOaYpsmll15ar2sjEZH9KfeH8AciBz+xBvE+F4nx+v8dERFpnRo1aXP99dfz+OOPM2DAALp27VrvfpKSkgCoqKiodnzPxc1Pd+DUxZAhQ/Y5NnToUJKSkli9enW9+nS73WRlZdU7JjmwyspKcnNz6dmzJ3FxcXVu78rPx2nfnpKSKEnBZCLRA+zC+BF3fBLexEQyPZkEIgF8Lh8ZGRl0Tuh8wHZGfj7eO+/EnDULACcxkejJJxMdMQJ3QgJWsJiE3Wvx1hDHnjFT03tS0qMjc88ZydeVQbLmLGbwK5+QkZPP4He/xP5gPnHnnMD8K0ZT0SENAJ/LR2IoEXdyMmHXge98dVluEhMTSfGmVh3w+TAyMkjpfOC5/dR2/3ZKdidCLcasaa4JCYmkpKfTsWvHOrWF73+umZkQCFASLGZLUR6BUAC/3098fDyWq+Z/7lxWIr7QTlZVlBKMVCV6vC4v2V2z6dylbvOXlutQ/12RtkHrRGqrLa6VnJycWIfQYjXUNZOISEvjD0RYvamQcKRuN8q5XSb9eqQraSMiIq1WoyZt3n33XQoKChgzZgzp6en4fL5q7xuGwUcffXTQfrp3745lWWzatKna8c2bNwPQp0+fesVXVlbGrFmzGDhwIIcffvje43tKNNW2zvNPGYZRr7JqUnumaRIXF1e/z9ntBrcby7KwLAvHqN0viKbLxLIs3G43tmnjtty43e4Dx/DOOzBxIhQWgmnCSSdhnHMOrri4vX/5rMj+4/jpmAB4PGw4fyQbzjuRzgvXMOzZ2XScv5wjXv+Uvu/MZfnFJ7N44jiMtCSsqFXVh8s64NwssyoG7547ZL//jDx1/HzdYTemadZqzJrmaprmwT/T/Q5eFTO2jRWxsA0Hx3AIRULEGXH7/Tk7ho1jONiGvfcztg27/nFIi1bvf1ekTdE6kdpqS2tFpdHqr6GumUREWqJwxK5z0kZERKS1a9SkTceOHenYse53zP+U1+tl2LBhzJ49m2uuuWbvReGsWbNISkraW9qsrjweD/fddx+nnnoqDz/88N7jc+bMIRAIMHz48EOOXRqHK9FFfkU+7pC7Tu1MwyQpUIITKCZk126HTb0Eg3D77TBjRtWfjzoKLroIOnRouDEMg/xj+vHpiGM5JqeShAf+TMdFaxj0/Gz6vvMV300+F845v+HGExEREZEG11DXTCIiIiIi0jo0atLmwQcfbLC+brzxRiZOnMjUqVOZMGECixcvZubMmdx6663ExcVRXl5OTk4O3bt3r/UOGa/Xy3XXXceMGTPIyMhg1KhRrF27lhkzZnDKKaeQnZ3dYPFLw6qIVLBkyxLsWu6S2cNreenvT4CSzbQzEhonuMJCOO88+OKLqj//8pdwww0wb15VMqcRVGQPZe5Td9Lhi28Z/rf/kL5hG8dOe5HK1+ey/uRBFGYmN8q4IiIiInJoGvKaSUREREREWr5GTdrssX79er788kt27NjBFVdcQV5eHv369avTs2iys7OZMWMG06dP5+abbyYzM5M77riDSZMmAbBixQquvPJKHnzwwRofnrk/N910E+np6bz44ou89NJLpKamcvHFF3PLLbfUeZ7StIKR4A8lw+og6vgwHBsao4rHhg1wxhmwZg0kJ8O//w1nnQU/Ke3XKAyDvBFHsWV4f/q9/SXH/P1t4jZs5qgNmyk4qhfrTz2aSLzv4P2IiIiISJNriGsmERERERFp+Ro1aWPbNr///e95/fXXcRwHwzAYN24cTzzxBJs3b+aFF16oUymAMWPGMGbMmBrfGz58OGvWrNlv2/Hjx9eYzDFNk0svvZRLL7201nGI1GjJEjjtNNi5E7p1g/ffhwEDmjwMx2WxasJItp6WzSl/e4eMtz8kc/lG0jZsY93px7C7X/cmj0lEREREatbQ10wiIiIiItKymY3Z+RNPPMG7777L/fffz5dffonjOADcfvvt2LbNo48+2pjDizSd5cvh1FOrEjZDhsDXX8ckYfNjwdRE8n59I8smn0dFRgoef4Aj3/iCfm/NxQqEYhqbiIiIiFTRNZPIoXOcqpeIiIhIa9CoO21ef/11pkyZwoQJE4hGo3uP9+/fnylTpvDQQw815vAiTWPVKjjlFNi9G4YNg48+gpSUWEe1V3m3TL6dNI4ec5fRbd5KOqzcRFL+bladdwLlndvFOjwRERGRNk3XTCJ14zgOq3OL+OTbPHLzdrN9p0lJMA4DSPY6JHscMuJseqfa9EyJ4rZiHbGIiIhI3TRq0mbXrl3079+/xvcyMzMpLS1tzOFFGp21eQucfgHs2AGDB8OHHzarhM0ejssi96TB7D6sK/3fmktccTmDn/uQDacMIX9Y31iHJyIiItJm6ZpJpHaC4SgfzMtl1tebyCso+9E7PzystChgUBSATaUWiwrAMhx6ptgM7BDh8LQoVqPWGhERERFpGI2atOnRowefffYZxx9//D7vffPNN/To0aMxhxdpVC5/gA6Tr4Vt2+Coo2D2bEhLi3VYB1TWJYNF15zB4e9/Tfs1eWTNXkTCjmJyz9j376g0Y0VFUJ8vcJKTm/0aFRERaWt0zSRycN/l7OSxV5eybXcFAB63xYmDO3NYBzeh/LUkOH5wHMpCUBo02FTuJafETUnQZH2xxfpiiwS3w8D2EYZ2jtIlxvMREREROZBGTdpcddVV/P73vyccDnPyySdjGAabNm1i/vz5PPPMM9x5552NObxI47FtTvjd03hWrIYOHeD99yEjI9ZR1UrU52HV+BMpXbCa3h8vptPS9cQXlhOd3A3iVS6tRSgthXnzIBisfRuvF7KzlbQRERFpZnTNJLJ/FZVhZr6znNnfbAYcDksJMuEok97uXTjF8wktLyBaXoTh2NXaOYCT5CGc4mW3ncT6QCpbwilsLkhnfn4afTdHOa1vlKO7mnhiMjMRERGR/WvUpM0FF1xAYWEhf//733nxxRcB+NWvfoXb7ebaa6/lkksuaczhRRrN0Kfep8ecRThuN8abb0L37rEOqW4Mg63H9sffLpn+b31JSl4B0b/9A375qxaTfGrzgsG6JW1ERESkWdI1k0jN8neWc+/TX+Mp3sj4+FyGJ27FFymDVVD5o/OMGtoagGGH8NohOlNGZ08+e7IzQcdic2UGaxdm8sm3XTiybzfGnhBR8kZERESajUZN2gBcd911nH322XzzzTe4XC6SkpIYNGgQqampjT20SKPo9PUKhj71HgC7H32AjBpKWbQURX26sOTKsRz16if4du2GadNg6lTo1SvWoYmIiIi0GbpmEqlu6YrNfPHaS1xjrqBdclVJNCJgWG48nfrg63I43o69qYzAlo0bCYRNMAyq0jUORjSEGQ1hRSqxwuVYoTJcwVLcgSK8dpjD3AUc5i4AvsO/wcNn67oQadebwUd0p2Oa0jciIiISW42WtHnvvfd4+eWXWbp0KZFIBACfz8fRRx/NJZdcwqmnntpYQ4s0GqusghH3zARgzYST8F12IS19X4q/fQrLrzqDwa9+hmv7jqrEza23wkknxTo0ERERkVZN10wi1UX9pSx5/VniNn3FGe5w1UFPHIl9jyWh//HE9xqE4XLvPT+yPR9n606I/ngHuoHj8hF1+Yh6k4HMH95yHDzRctpbZRgl26ncuYV4Qgw2N0LpRoLzXMx3dSejTz969+6KYdS0j0dasnJ/CH8gUud28T4XifFK6ImISNNo8KRNNBrl1ltv5YMPPiAzM5MzzzyTjIwMHMdh+/btfPPNN9xyyy2ce+65/OlPf2ro4UUaVbeH/4+EgkKKu3dg4a2XcEKsA2ogoeQESn8+mfSZ/4aNG+Ghh+CYY0APvhURERFpcLpmEqnOiYYp/vptdn76KmnRABhQ6s6gxyk/I2XQKExXA31ZbhhEvclY7TuT1GcAyY5NtLyEbZvziOZ9RyIV9IlugLUb2LguCV/XfnQ8/AhMj69hxpeY8wcirN5USDhiH/zk77ldJv16pCtpIyIiTabBkzYvvvgiH374IXfffTeXX375PnemRKNRXn75Zf74xz8ybNgwfvaznzV0CCKNot2y9aTP+hzbMvnk3klE4ryxDqlBOQnx8MtfwowZsG4dXHEFfPopDB4c69BEREREWhVdM4n8wLd7Df55r1NRthML2BJJo/jwszjronMwTbNRxzYME0+7LmT1G05w29Fs27yFLWtX0zGwgWTKIG8BO/K+xdO5LylZA8CIb9R4pGmEI3adkjYiIiJNrcF/A3rrrbe4+OKLueKKK2rcSmxZFpdddhkXXnghb775ZkMPL9IoXP4gvd+dC8CySWex86hW+swXrxd+/nPIyoKSEhgzBpYvj3VUIiIiIq2KrplEwIgG6bDmdTotehKnbCfFdhz/Lj+e/OxbOfvicxs9YbNPPIZBp64dOWb0SbiPv5yvfSewJZKGiyh2/koKP3+F8KrPMINlTRqXiIiItD0N/lvQxo0bGTly5EHPO/HEE1m7dm1DDy/SKHp+vhS3P0Blnx4sve6cWIfTuHw++NWvYOBA2LULTj0VVq+OdVQiIiIirYaumaSt85Tm0eObh0nd+hUAXwT68kDxeRx52rlcfFr/mD9LpmOqh7NOPpLk7Am85oxlRagLBmDv2EDa+g9I3rYAM+yPaYwiIiLSejV40qayspKUlJSDnpeWlkZFRUVDDy/S4BIKiui0OAeAvF9di+Nu8KqCzU98PDz/fFVptIICGD0acnJiHZWIiIhIq6BrJmnLzM2L6PTNdDyVuyk3kni89FT+4x/OpPOPZvzJWbEOr5reGRbXnd6D4j5jeaTsTJaFumIAcaWbyNj4AQk7l2PY4ViHKSIiIq1MgydtHMfBsqyDD2yaOI7T0MOLNCzHoc/shRiOw66jelN+9FGxjqjppKTA7Nlw1FGwbVtV4iY3N9ZRiYiIiLR4umaSNsmxic9fhOvb1zDtCLlWL+4vPJO1kc5cfeYRnHlC71hHWCOXaXDuUW5uOq0z7zGah0vOICecieHYJBaupt2GWfhKNoH+roqIiEgDaQNbBkTqL2PVZlI37yDqssg9/biGz3I2dxkZ8NFHcNJJVSXSTj0VvvgCOnWKdWTNQ1ERlJbWr21yMqSlNWw8IiIiIiLNkR0lNf9rvBXbAFjoGc4L2w8Hw+D07B6cOLhLjAM8uK6pJneeZPLkvDRm7D6NAe48LkxaSHK0nJTtC/CVbsLf9dhYh3kABy85Z1kmbpcDB3mekG07RG0lqURERBpLoyRt7rnnHhITEw94Tnl5eWMMLdJgjGiU3p8sBiAv+0hCqUn4YhxTTGRmwscfwwknwPr1MGYMfPYZtGsX68hir7QU5s2DYLBu7bxeyM5W0kZERKQN0zWTtBWGHSZ161d4/DtxDIvPE07jjc3tMQw4bXgP+vVIj3WIteZzG/ysX4gvNlt8ltedlYVduCh9Occay/D6d+BZ91+iVhi6jKE2SZImY1rgRAkX79j/OZEIqVYYV4IDRvSA3UUtH/klthI3IiIijaTBkzbHHHMMwEG38SckJDBs2LCGHl6kwXRcugFfSQXBxDi2HNe/7e2y+bHOnat23Jx4IqxYAePGVSVykpJiHVnsBYN1T9qIiIhIm6ZrJmkrjGiI1C1z8QQKsU0Xs8yT+eBHCZusrqmxDrHODANGdI2Q6nN4N8fDi4WDWJHSg0uS5hPnL8C1ahadt65kW/+LCSV0jHW4ABiGiR0KENqVB5FIjeeEwiEqCssoq6RqkvvhcnuI694P0/QqaSMiItJIGjxp8/zzzzd0lyL7MA0Tr8uLbdh1aue1vJiGwcF+tTQiUbp/uRyo2mVju11tO2kD0Lt31TNuRo6EBQvg7LPhf/+DuLhYRyYiIiLSouiaSdoCww6TtuUL3IEibNPDe8bJfLwjE8OA07N70rtzSqxDPCRHZkSJdwX5zxovS0tS2RE5hck9N5K2azHe0jy6f/MIu/uMo7zXybEO9QeRCE40XONbTiRMNBwkEgKMNn/1KyIiElN6po20SB0MD+5AMo5Rtzt7LJeHdqaXXQe4cwig49L1eMv8BJPi2DYk61BCbV2OOAJmzYKTT64qkXbBBfDGG+DxxDoyERERERFpLhyblK3zqhI2loe3OYVPd7bHwOGSkV3p0CmNcKRuN+A1R71SbS4/MsjLq7xsq3Dxj01Z3HjaiXiWv0f8rpW0z3mPxMI12J1ugfT4WIcrIiIiLYSSNtIiucr9RL78gnCwbnW+fWkdsAafgHGA+sJGJEr3r6p22WzOPhLHZR1SrK3O0KHw3nswdiy8/z5ceSX8+99g6XMSEREREWnzHIeUbQvw+ndgGxbvc9LehM15/WyG9Elhqz/WQTacTok2lx0Z4MWVPraXG/z9kyLOHnkV7XcspP26t4krXIf/1d9QcfbPSTj8mFiHKyIiIi2A9rxKixUJ+In4y+v2ClQctN9OS3LwllUSTIpn+2DtsqnRyJFVO2zcbnjlFbjhBjhITXYREREREWn9EgqW4ivLw8HgE9eJfLSzI+BwdlaIAZmt85qhQ7zD5UcGSPQ4bC8K8p9PcshPH8qmY35JMKkLBMopeO1P7P74XzjRmp8pIyIiIrKHkjYiP2bbdP16JQCbj28+u2zC0TD5ZfksLVjKovxFLMhfwDdbv2HFjhVsLdtKZbiy6YMaN65qh41pwtNPw+23K3EjIiIiItKGRbfnEFe4DoAF3uN4p6A7AGf1CXFU+2gsQ2t0GXEOVw2KkpLgoqg0yJuf5VBopJI//Be4B44FoOTrd8h/4f8RKd0d42hFRESkOVN5NJEfab96M75SP6F4L9sH9YlZHEEiLDS281W0gCWfv83WygIcDpwQSY9Lp3dab7LSsjis3WH0Tu3d+IFecAGUlcE118DDD5PshcJzRjX+uCIiIiIi0qxESnYSWfcVAOu8R/LvbYcBcGrPEAM7tO6EzR7t4uGmM3ry+H83U1Ie4q3P1jPh5Cy8Iy4n/bCB7HjvcYJbVrNl5m1kTriduO5HxDpkERERaYaUtBHZw3HoMn81APlDD4/JLpt1RiGvmKv43MwjaETBAb7fRONz+eiQ0AGP5cE0TAwMykJlFFUWURmppLCykMLKQhbmLwSgQ0IHxnUYwYmOQRa+Az7H55BMmgSlpfDLX5Lyx4fJqCyhol3z2KEkIiIiIiKNzw5VUvrth2BH2e3pzOPbhgBwfJcwx3ZqW+XA0pM8XDD6MP7zyTpKykP8Z846srqmMrDfcXTN7EnBf6YR2pHLtn/fQ8Zpk0g6eiyG0UjXaiIiItIiKWkj8r3kLTtJ3rYb2zLZdvThTTr2YrbzL9dSFpjb9h7LdOI50ezNqKPHE81Ix+fy1fjLfJI7iW4p3Xh37bus3rWanKIc1u1ex46KHfxr45v8C8hypXGufRin2j2Jx93wE/jFL6CkBO65hy6PPk3l+aPI79+14ccREREREZFmxXEcypbMwQ6UE/Ek88jOE3EwGdwhzKhu4ViHFxNJCR7OH5XF25+vp6gsyIPPLeC+yceT1a0jna/+Izvfe5yKlV+y64OnCG7fSMbp12FY+npGREREqui3ApHvdfmmapdNwYDehBN8TTLmlmgRP/e/yNuu5QBYjsFJdncusPvTz0nHHZ+EL2MIy3wlBKPBGvswDINkbzJHtD+CPulVJd0CkQBrdq1h3ZalfLb9a3LMIh42v+FJZzFn21lcFO1POnENO5nf/56yHVtIeuJp+rz1OSFGsKt/j4Ydowk12s4kEREREZFWJJC7jPDuLWC6+HvJSZRHvfRJjXJ67zBteQNJQpyb80/K4r25G9hRVMlv/v4lv510LAOz2tPhvF9S0rE3hXNeoGzJR0SKC+gw4XYsX0KswxYREZFmQEkbEcBXVEbGmjwAth7Tr9HHizhR/lrxMfeUv0eFE8RyDM6ys7gkegSdSDzk/n0uH8d2OZZr2o1hx863eS/4HW9Z69hqlPGytYo3zbWcYx/GJdEjaNdQyRvDoPiB3xHK20S7d2fT7+2vWOl2UZjVpWH6b0Iu00XEjrCpeNN+zzENk6RACXZlEU6gssZzfC4fCR5deImIiIhI6xQp203FmvkAfGwfQ05lKhlxNuceFsRswwmbPeK8Ln42+jDmLMxj9aYi7nnqa3558dGcOKQLqdnn4cnoRsFbj1CZu4z8f/2Gjhf9BndqZqzDFhERkRhT0kYE6LxwDQZQ2Kcz/vYpjTpWXrSQy4pn8kUoB4Bjre7cFBxMLzupUcZLNrxcaPfnZ3Y/vja28ry1nJXmbl6zVvOuuY6L7SO4zBnYMIMZBlvuvAkndwMZy9ZzxOufs/zCkynu1bFh+m8ilmFRHipn5a6VBCM173DyWl76+xMIFq0n4i/f53236aJ3Wm8lbURERESkVXKiUcqWzgHHZqvVjXd2ZpHghouOCOHTNw17edwWv7h4CP/67yrmLdvGX15YSP6uci489XDiDxtK5yvuZ/urfyS8awv5z95Fx4t+i7dT71iHLSIiIjFkxjoAkVgzwxE6frcBgK3H9G3Usd4MLGbQzvv4IpRDkuHj6ZQreC9hMoeR3qjjApgYHO905YnIWB4Kj+ZIO4OAEeVZaxkXW2/wQmghtmMf+kCWxbqfncyuw7tiRm2O/M+nJOftOPR+YyAYCRKM7v8VdaJE7HCNr7Ddth64KiIiIiLNi2kYuF1mnV+1LWnmX/cN0bJCIpaPv+86DsswmDzcJD3OadyJtUBul8WvrzyG80ZVlbN+4YPV/PXlxYQjUbwde9Hl6j/hyexFtKKE/Bd+T2XushhHLCIiIrGkpI20ee1XbsIVDFOZmkhRr06NMkbEjnBr4UuML3qSIsfPMe6eLM74LdfEn4BpNO1fQwODY5xOPB45jXvDJ9LFSWS3UckvKt9g5O6HWBHOP+QxHMti1XknUNirE1Y4ylGvfELitt0NEL2IiIiIiNRGapxFl4QwXeKDtX518gVwB4sJF+/44VWyEzsSqtZ3uLiAyo3fAfB86XGUOXFcONhF3/aqibY/lmlwzTlHcdOEgZimwZyFefzmiS8pLA3gSm5H5yvuxdfjKJxQJdtevp/yVfNiHbKIiIjEiDYtS5vXafE6ALYNyaIxnpRZHCjm4o8mMav0cwBuTziN+5POxWPE9q+fgcEopzvHh7vwtrWeZ6ylfBlez5Bd9/Pr8BncHTkO3yH077gsVv5sJEe9/AmpeTsY8NIcvrv8VCo6pDXYHEREREREpGZGJEjl5tVEIrXfAW5ZBontErDiPD/04/XhTvvh5jbHtilf/gUAy+3eLAl2Z1BnkzP6u6ioDDfcBFqpccf3IrNdAn95fiGrNxXxy0c/5a6rjqVfz3Q6Xnw3O9/+GxWrv2bHGw+TMPKyWIcrIiIiMaCdNtKmJWzfTXL+bmzTpGBgnwbvf+3utQx/ejiz8j8nzvDwaupk/pI8IeYJmx9zY3GxcyRfJv2Cs70DCRPl/pJ3GfjOOD7Z+Mkh9W27Xay48CRKO7fDHQgx4MU5xO0qaaDIRURERETkQCLhMJFQqE4vOxLGif7wIhKt1mflpmVEy3YTNLy8WDKMtDi4IduD2Qg3wLVWR/ftwCO/GEn3jkkUlga564m5zPo6F9PlocP5vyJp8KmAQ8Xn/8aze32sw200BtSrhF9dyviJiIi0REraSJuW+e0aAHb160Y44VD2lexr/pb5ZM/MZu3utXRL6MyXHe/mgrihDTpGQ+pqpvJ22k38J/V6OlmprCvdyOjnRjPx7Yns9te/tFnU62bZxaMpz0zD4w8w8KWP8RWVNWDkIiIiIiLSFKKVZfjXLQTg9bKj8ePjphEekn36Br2uOmckMu2WE8ke0IlI1OGx15by+H+WErENMs64geShpwMOcXlf4yveGOtwG4WHqpJ8dSnht78yftHK8lhPR0REpME0n9v9RZqYEQjSfvkGALYNOaxB+56VM4vxr47HH/ZzTOdjePfEJ8icvwKCwQYdp6EZhsGEuKM5NXkQv4mfx99Xv8CzS57lf+v+xz/O+gfn9ju3Xv1GfR6WXTyagf/+iIRdJQx88WOWXjGGYHJCA89AREREREQag+M4lK+YC9EIudFM5oeyOOsIF0dkWrEOrcWK97m566pjeO3jdbzwwSo+mJfLpm2l3HnVMbQbey3BykqCKz8jpWARBg6Vqb1jHXKDckKV+PNWEwrU7Tp5nzJ+Lhe+Ln2x4hIbIUoREZGmp5020mbFL1mOFYrgb5dMSfcODdbvi8te5KyXzsIf9nNan9OYc9UcMuPaN1j/TSHFjOfx4+7jy0lf0j+jPwUVBZz3ynlc9sZl9d51E07wsezSU6hMS8JXUsGAFz/GXV7ZwJGLiIiIiEhjCO3IJbxzM1FMXiwbTpcUkwkDdR/ooTIMgwtPPZzfX3McCT4Xq3IL+eWjn7FmcxHxx00gmNEXgOSCb4kr3hDjaBteNFy38n01lfGjDs9tEhERaQmUtJE2K2HBEgC2Dc6ioQriTp8/ncveuIyIHeGSoy7h3UveJdHTcu/2ye6WzbfXf8udI+7ENExeXPYiRz5xJG+vfrte/YUS4/ju0lMIJMcTX1jGgJfm4Kps3ruPRERERETaOseOUrHySwA+qezPDieV64/z4LFUFq2hDOufySO/GEW3zCQKSwPc9fiXfLZsF5VdhlKRlgV8n7gpar3PuGmNyv0hdhT66/wq94diHbqIiMSQkjbSJnm378KTl49tGuw4qtch9+c4Dnd/fDdTP5gKwC3H3sIL41/AY3kOue9Y87l8PHjqg8y7Zl6D7LoJpiTw3WWnEkzwkbizmKNe+QQzFG6EyEVEREREpCFUrPyKaEUx5Y6PDysHcFZ/F30y9HVCQ+vcPpGHpux5zo3NzFm5vLfWpKTdICrSqkp6J+9YTFyxEjcthT8QYfWmQpat31Xr1+pNhfgD2j0kItKW6bcsaZPSF64AoOiwboQTfIfUV8SOMPndyfxx7h8BuP/k+/nb6X/DNFrXX69juxzbYLtuAmlJLLvkFMJxHpLzd3Pka59hhPVLqYiIiIhIc2OHApQungXAe/7BtEv2qixaI4r3ubnzymO4fFw/DGDBVpN/r/KxPWUgFWmHA5BcsBhfyabYBiq1Fo7YdX6JiEjb1rq+VRapjUiEtMWrANgxKOuQugpEAlzw2gU8vfhpTMPk/876P+4eeTdGA5Vba24acteNv0Mqyy4aTcTjIm1TAX1f+Ui1iEVEREREmpmKNV/jBCvJj6TydTCLa4e7cassWqMyTYOLTu3Lr8Yfhtdy2FJm8c/lcaz1DcKf+n2ptO0L8JZtiXGkIiIi0hiUtJE2xztvAe5yP9HEBIr7dK13P/6wn6veuoq3Vr+F1/Ly2gWvcd3Q6xow0uZrf7tuPlz/YZ36Ke/cjhUXnIRtmaSv3kT3+/4Gtu4qEhERERFpDqIVJVRuXArAm/5hjOrjpm8HK8ZRtR2D+6Qy+RibdnE2ZSGT51f6mMvRVKb0xABS8ufjKd8W6zBFRESkgSlpI21O/H+rEgv+owfgWPX7K1ASKOHBuQ8yf+t8kjxJfHD5B4zvP74hw2z2atp1c+2713LX0ocpcQK17qekRyYrx5+IbZqkzfqMtNt/B47TiJGLiIiIiEhtVKxbAI7NilAX8q0uXDzEHeuQ2pyMeLj6qACHp0WIOgbvb/Dxn4rh+BO7YeCQmj8Pd8WOWIcpIiIiDUhJG2lTXGV+vF/OB6Bi2KB69bGjYgd/+eov5JXmkRGfwWdXf8ZJPU9qwChblp/uuvnfts+4PPoqc428WvdReFhX1v3sZBzDIHHm8/Cb3zRixCIiIiKt19y5c5kwYQKDBg1i9OjRzJw5E6eWN8SsXLmSI488ki1b9i25tGzZMq644gqGDBnCCSecwCOPPEIoFGro8KUZiZTuJrSt6oH371UezWVDvSR5VRYtFrwumNA3xMhuIcBh4Q4vTxadQEV8ZwzHJnXrl7grd8U6TBEREWkgStpIm9Ju8WqMaBR/10wiHTvUuf3q0g3c/8X97PLvon18e16/4HWGdBrSCJG2LHt23bx10Vv0TuhGIZXc7f6c+6wvKSFYqz52D8xiy69vrPrDn/5U9RIRERGRWluyZAk33HADvXv3ZsaMGZx99tlMmzaNp5566qBt165dy+TJk4nU8IzBvLw8Jk6ciNfr5a9//SuTJk3in//8J/fff39jTEOaiYq13wCwKNiT1E5dGdlHu2xiyTDghK4RLugXxGs5bCpz85cdoyj1ZmI6UVK3zMUVKIp1mCIiItIAlLSRNqXdt6sAKBx6RJ3bfmvnM/mb31IaLKVrclfuPvFueqT2aOgQW7TBHQfz0vGPcrkxGNMx+MjK5Wr3e3xibMLh4Hd4Fp53OsX3fr/L5q674IknGjliERERkdZjxowZ9O/fn2nTpjFy5Eh++ctfcs011/Dkk08SCNRcvjYUCvHMM89w4YUXEg6HazznqaeeIiEhgSeeeIJRo0YxadIk7rrrLl577TXy8/Mbc0oSI+Gi7YR3bibqGMwKDOaaMV0wDO2yaQ4OS7O5ekCAdnE2xSE3D2wfTZGrPaYdIW3LF1iBkliHKCIiIodISRtpM+J2l5KYV4BjmZQM7Funtp8bm/mV/T4V0Ur6tuvLbdm3kepLbZxAWziv5eFGazhPRE6jh5NMoRHgHvdcbnd9Qh6lB21fNuUGuPvuqj/cfDO88EIjRywiIiLS8oVCIebPn8+YMWOqHR87diwVFRUsWrSoxnaff/45jz32GNdffz233XZbjefMnTuXUaNG4fF49h47/fTTsW2buXPnNtwkpFlwHIfyNVW7bOYH+zD48A70aB8X46jkx9rFOXufcxNw3Dy44xR2GemY0RApmz/H9itxIyIi0pK5Yh1AXcydO5dHH32UnJwc2rVrx2WXXcakSZNqdcfPypUrueCCC5g1axZdu3at9t6yZcv4y1/+wvLly0lISGD8+PH8/Oc/r3ZRIi1fh+UbAQgeO4xIYnyt271jruNRawE2Did1GM6lx15Tq10jbV1/J4OnwmfworWCF80VLDC3MdH9Phfb/bk8ehS+A/3zc999UFICjz0GV18NSUlw7rlNFruIiIhIS5OXl0c4HKZnz57VjvfoUbUzfOPGjYwYMWKfdgMGDGDOnDmkpqbyxhtv7PN+IBBg69at9OrVq9rx9PR0EhMT2bhxY71jdhwHv99f7/ayf8FgVYniqB0lEo3WvqFjECncgl20jYhjMjc6iLsHuIjaNqFwCCdS826sPaLRKNFIlIi9n+ulqE00GiUcChGK2FXHbJNwOFyvtWDbUaIRu85zjEaje5/JZJouzBY4P8uAc7Mq+Srfw5dbvTxcOIZfpsyiQ6SY8HcfEBh6JmZcYq3nGP6+NGLUjh74evenc2zqnx/s8zM0XA5WJEK4FjGEw+HqP59aBVr/OTb1eE2psrKy2n9FDkZrRuqqta0Zx3FqvXO5xSRt9tRnHjduHFOnTmXRokVMmzaNaDTK5MmTD9i2NvWZBw8ezF//+lfWr1/Po48+SnFxMffee29jTUeamuPQYUUuAJWnnQwc+JdxAAeH583lzHR9B8DZRj9+O+h2VlnlBKO1e05LW+fFYmJ0IGOivZjuWsh8M5/nrRXMNnOZEhnGCKdrzQ0NA/72NygtheeegwsvhP/+F045pWknICIiItJClJWVAZCYmFjteEJCAgDl5eU1tsvMzKxXv3v63l+/tREOh1m1alW928v+eTwe0uK8+P1+/BW1/+LXbRmklyzBDXwZPJxju9n4S3cT789k565dhAP7/9LENE0My0tpWSnh/XxB7fb6MMvLKdgRJBCquj73eVx0SjPYua2MaB2+vN8zx7LysrrN0WWSEg9lJUFs28aTkExGUocWO7+jEiGpi48529KZXjKGqcmzaB8spXTh+wR6Dsdx+2o1xz3zq6io2O/8appjU//8YN+foeXxkpS4i92BHQeMwbIsDE8SBTsK9v58aqO+c2zq8WIlNzc31iFIC6M1I3XVmtZMbTeJtJikzY/rMwOMHDmSSCTCk08+yZVXXonP59unTSgU4oUXXmD69Ol4vd4a+/1xfWaPx8OoUaPw+Xzcd9993HDDDXTu3LlR5yVNI2nrLuKKy4l63ARPPB4WfXbA820cplsLedNaC8AV0SO53jMCl2k1RbitTleS+HPkJL4wtjDDtZDtRgW/cX9Gtt2ZmyJD6U7yvo1ME2bOhLIyePNNOOecqsTNqFFNPwERERGRZs62D3wXt2nWrzL2wfo9lOecuN1usrKy6t1e9i8YDFKxeyfx8fG4Xe5at4sL7MJduZuIY7LGcxS/GpyIKy4BX3w87TMyDroTxR+MkuxnvztRXB4viYmJZDqpe3ceeFwmGe0ySEvqVPsJfi9QvJukxKQ6zdFlGiQmJhLvTQHA9MW3+PkNTIEu6X7eXBfHjNKqxE27UDmJWxcTf/Q4XMnpB51jOBKhqKSChIQEnANU0v/pHJv65wf7/gwNl5u4jPa0i085aNuS8ghdy4wDJqaitkP0Rz/jQ5ljUVmYzA5OnXbaHMp4TamyspLc3Fx69uxJXJxKKMrBac1IXbW2NZOTk1Prc1tE0mZPfeYpU6ZUOz527FiefvppFi1aVONW/x/XZ87IyOC3v/3tPufsrz7zH/7wB+bOncuFF17Y8BOSJpf5fWm0ogFZOHH7Jvh+LEyUP1rzmGNtAuCWyFB+ZvfTgzcPkYHBSKcbx4Q78Zy1jFfMVcwz8/nGvY1z7MO41jmOhJ82crngpZeqEjYffgjjxsF778Ho0bGYgoiIiEizlZSUBEBFRUW143t2wtS0U6Y29rT7ab97+t4zbn0YhkF8fO3LFkvdVACWaeFYdfiyeNcaAL4OZjFhRCo+r4Xp8mCZJh63B8c88DVRMBLCclkQ3U9SwzKxLAu3xwNmVVxul4nb7a7XWgiVFmO5TFxW7W+usywDy7L2fgfQWuaXmQgTBwT5YKOXxwqrEjepFcWUffsh7UddWOs5WqYFxgGSNj+ZY1P//GDfn6Hh9uG2DAgdfOdfnB2he7JdLSnzU1HLR37JD+ccyhzLA/5q66E2DmW8WIiLi2sxsUrzoDUjddVa1kxdvltuEUmbllafWbWZG9ee+sx2pKqe8MEYUZuMVVUJmJ2D+pFiOzi2g21W1eL98XbjSiL8P+9cFlrbsRyDO0PDOSXakyhRzMj3tXvDYUKREKar9nVmXeEwTjgM39fc/bE9MdS07fmnY9YkbIaJ2vueY7pMotEodsQ+6OdkWFXnBvfEZ5oY4TCROq7jcDiMbdsHHNODwbWRgZxm9OQf7iXMc+XzprWW2dFcrllvcH3PLPzun4z70kt4L74Ya/ZsnDPPJPjqq9g/KZX24894z+cZiVZtQd/z35rU9Bnv7zOt1u4gn+8+n2m1xvX7fPc40Hrar0Mcs7VrbXVSpXFonUhttcW1Upf6zNI4unfvjmVZbNq0qdrxzZs3A9CnT5969ZuQkEBmZuY+/e7evZuKiop69yvNj8u/i8TADqKOwa70gfTtoCoDLY3XBef3DbMlkMzTy8Zwffwskip2s2nOG/S+cMrBO2ihDMPEDgUI7cqDGsri/1hlZYiy3RVE95d4c3uI694P0/QeMLEjIiLSmFpE0qal1WdWbebG5fF4SAP8lX4qSkoOen7mph14KkME4jxs7ZRGXDhERUUFSV435WVlBMNVSaAKI8z96YtYbRXhtS3uKB7C0cE0SqgawxNxiCsvpyBcgD/kJ94Tz67EXZRvLT9o3dzMQIBIQQH2T74wN02TsCtMWWlpjcmBn45Zk1BCiMqkSnbu3El54Ic1G++Jp9ztprK0lFBF6QE/I4/LQ7m3nGBxVU1gMz4e165dFJQfeG4/nWckPkKgopzSWoyZAtzBIL7zdOXZ5FVsdJfxt3X/4rX82UztP5XRmaOrfflj/OEP9K6sJHXuXDw/+xnrH3qI0uOP3zv2ns+YQGCfz7SifN87Q/fOvYbPeH+f6Y8d7PP96Wf6Y/X5fPc40Ho6kEMZsy1pTXVSpfFonUhttbW1Utv6zNI4vF4vw4YNY/bs2VxzzTV7f4+aNWsWSUlJDBw4sN59jxgxgk8//ZS77rpr78951qxZWJbFcccd1yDxS+yZBasBWBjqw9knpsU4Gqkvw4DjupsM6tKBV748jXOiH5AQKODbFx6n0/Fn0SGpFSfYIxGc6IFL3NmRMJFQaL9JGxERkeagRSRtWlp9ZtVmblzBYJCKDauIj4vHxcEf5tc7dwUAO4/oSWJyCh63h4SEBNymm8SkJHxRHyUEudf7NWutIhIcN38KjeJIXwb8qJKaOz4Jb2IimZ5MApEAPpePjIwMOicc/LlHrvx8nMxMCAT2ea8kWExSMJlIDb9c/nTMmqT4UoiLj6N9+/YkRX4oT+Fz+UgMJeJOTibsOvBadlluEhMTSfGmft/Yh5GRQUodn+m03b+dkt2JUIsx9ziRFI4P92SOu4CnvcvIr8jn1wt/zdCOQ7l35L2c1OOkH05+5x0iV16J6733yLrtNoIvvYR9+ulVc/jRZ7znMw2EKqkoryAhMQGXVfM/dzV9xvv7TH/sYJ/vPp9ptcb1+3z39n2A9bRfhzhma9fa6qRK49A6kdpqi2ulLvWZpfHceOONTJw4kalTpzJhwgQWL17MzJkzufXWW4mLi6O8vJycnBy6d+9Oenp6rfu99tpref/997n22muZOHEiubm5PPLII1x44YV6BmgrYVUWkhbaTtQxKO8wgMyk+l1jS/PRIcnk5tM68uWy0+m19X90sfNZ9cn7fJs1htP6eTAPUiZNREREYqdFJG1aWn1m1WZufBWA6bKq6gkfgBUMk5GzFYCdA3pjugwMs+plGlW1eHcZFfzKNYdcs4QUx8tDkdEcbqbz02cvmq7va/e63dimjdty177OrNtd9aohUWhFLCzLwjH2fe+nY9bYtcuNZe57jttyY0Wtqj4O9jmZVTF499wh+328njquY3fYjWmatRqz2vhYnOXqxzkn3sxr5V/zj0X/YNH2RZz56pmM6T2GP57yR4Z1Hgbx8fD663DJJRhvvIHv4ovhtdfg3HOrfcZ7PtM9iRqX5dpvPDV9xvv7TKvN9SCf7z6fabXGtf98iyqLKA3+sJPHNEySon7sSDlOpHZld3wuHwnupHr9TNua1lInVRqX1onUVltaKyqN1jxkZ2czY8YMpk+fzs0330xmZiZ33HEHkyZNAmDFihVceeWVPPjgg4wfP77W/fbp04dnnnmGv/zlL0yZMoW0tDSuvvrqfZ45Ki1XJH8tAEvDvTjpiIM/zF1aBtM0OHFQJ3ZmnkNk8dv0d29l6bo53Ld5FNdm++iSouSciIhIc9Qikjaqzyz11W5tHlYkij89ifJO6T/eOAPAdsqZ4v6QrUY5GU4cD4dPoSe6SImVOJePXxz3C+4YcQcPfPEATy58ktkbZjN7w2wuOOIC7jv5Pvpm9IWXX4bLL4dXX4UJE+CZZ2DUqFiH3yhKg6XM2zKPYKSqjJ/X8tLfn0CwaD0R/8FLOLpNF73TepPQ2IGKiIhIszBmzBjGjBlT43vDhw9nzZo1+207fvz4/SZzhg0bxquvvtogMUrzEvWX0TG8BQwob9eXeI+SsK1NZvfuRDpMZNeHMxnk2YwZ/ITf/3cU5wzwcuYRLlzadSMiItKstIjbKn5cn9lxfqg72pD1mUM/eqC36jO3HpnLNwKw48heVcV9f2SDvZsbrf+y1Sino5PAjPAYJWyaiczETKaPm86an6/hioFXYGDw2srXOPKJI7nunevYUlkA//43XHklRKNw1VXw9NOxDrvRBCNBgtEfXlEnSsQO1+oVtg9eQrA2iiqL2FS86ZBeRZVFDRKLiIiIiDQcf/56TAPWRLvQt0v9qlhI8xfXrR+px5wJpsUAzxYmJXzMW0sr+f0HQXILD1w6XkRERJpWi9hpA6rPLHXnKa8kNbcAgB1H9az2Xo69ixuDr7PT8NPdSebh8Cl0oG2UL2lJeqX14rnzn+P242/nt5/8lnfWvMPTi5/m+e+e55Zjb+HOxx+iXfv28PDDcP/9cOaZcPbZsQ67Vfrpjp+68rq8ZHfNJi1OD7UVERERaS7K/UF6RDaAAYH0vlgt4rZOqS9vhx4kDzuD0kUf0Jft/DzlI/5ePJrff+Awrp9BdmasIxQRERFoITtt4If6zBs3buTmm2/m3Xff5Y477uC6664DquozX3TRRXz66ad16ndPfeZAIMCUKVP45z//ydVXX83dd9/dCLOQptR+ZS6G41DaJYNA2g/PJ1pfsYXrg/9hJxVkOWlMD49RwqaZG5A5gLcvfpsvJ33Jid1PJBgN8tC8h+j9WBYPnJ1K8IE/VJ34/vvw/PNVu2+kwf10x0+dXvVM9oiIiIhI4ynJ24DbsMl3MsjsoJtr2gJPu86kHHsmhstDD2snd7abRbJRznurHP62II6tZS3mayIREZFWq8XstAHVZ5a66bA8F4CCI3vuPZZvl3DTol+zGz9HGJk8HBlNfMvJXbZ5x3c7ns+u/owPcj7gro/vYmnBUn776e+YkZDJi784l5P/9g7Gl1+SVFqEcebRsQ5XRERERKTZ2l4SpZ+9DkwItjuceD3XpM1wp2aSctw5lC74H6nBYn6b8QFPlp7Cuoo0/rUijuO7RBjZLYyWhIiISGzo22ppleJ2lZC0vRDHMNjVvwcAu/Bzi/8/bAvuopeRzr99l5GMN8aRSl0ZhsG4w8bx7fXf8uL4F+md1puCigJOSX2bGy9JIuqy8CxbyRH/no2rUrs7RERERER+ynFg99bNxJshSkgiPqNTrEOSJuZKakdK9nlYiWm4In5+nvQBZ3XYDBh8tdXNv1d4KQspayMiIhILStpIq9RhRS4AhX06EU7wUUGY212fsMUpoXtcR570TiDDSIhtkHJITMPkkgGXsOrmVTxxxhN0jGvPPw4v5ZTLopR5DVLyCjj6xY+JK6uMdaitgoGB1/LW6+UyW9SmThEREZFWb30RDGI1AIF2h4GhL+fbIisukZTjzsWV1gmiYU6NfMrPu36Hx7LJK7OYudTHxmJ9bSQiItLU9P++0vo4zt6kzY4jexHB5h7XF2wwi2lnJPDq0D+TaSQduA9pMTyWhxuPuZGc8Z/xx9SfsaR3HCMmOmxJgoTdpRz/1pckFhTFOswWL9Efob8/gQGBlDq/+rs6KXEjIiIi0kw4DmzfuoN2VgVBPJDeI9YhSQyZbi8px5yJu9NhGMBh/iXc3flLOseH8UcMXl7lZd5WF44T60hFRETaDn2LJq1O8tZdxBWXE/G42HV4F2ZYC/nG3IbXsXg4/ly6x3VkB0tjHaY0sAR3PHelnsX13uP5g+ctRl47l7f/bTNgR5gjX/qQb8YPx+zdJ9ZhtlhmWTnRr+YS8JfUqZ3Ll4B3xIlYCVYjRSYiIiIidbFqt8Ugo2qXTWVqbzD1e1pbZ1gWvv4j8Bs+XPnLSK3YyC9Tinkr4US+3JnKJ5s9bCs3OSsrpC+RREREmoB22kir02H5RgB2H96NV73rectah+HAbyMj6G91jHF00tjSzQR+7zudRxMm8McrejKnJ8SHHEa8+jVrl39GkEisQ2yxIgE/EX953V6BiliHLSIiIiLfsx1Yt6WULPcObAzC7XRTk1QxDINoh8Mo7nI8tunGEyziZ87/uKLbRkzDYXWhi2eX+djtj3WkIiIirZ+SNtKqGFGb9qs2AzBvQCpPWN8CcGP0aEY63WIZmjSx9iQw2TqOVaeP4H9H+XDbcO07W/h23hvMZTMO2t8vIiIiIm3Lsp0WQ8w1AFQmdsN2xcU4ImluQgkd2d3zVMK+NEw7zLCKL7iz69ekusPsqjR5+luLlZvLYh2miIhIq6akjbQqaRvycVcGCSR4uT5rFbbhMDbaiwvtfrEOTWKki5OMd9w5zD2+KwC//iRMu1lf8BvzE7ZQGuPoRERERESaRsSGJVvCDPHkAhBolxXbgKTZst0JFHY/GX9q1RrJrFjH3envc3TSToJRg39+lMfXy7fh6EE3IiIijUJJG2lVOizPBeCNoyx2WAF62in8MnosBkZsA5OYMgwT+6RRrBx7NLYB1y+Cu17Zxs/t9/invYiwHY51iCIiIiIijWrZTotB5jpchk3Q146ILz3WIUlzZpiUZQ6mqMvxRC0vnnApV7o/YGKHJVhE+Xr5dv77VS7BUDTWkYqIiLQ6StpIq2EFw7RbtwWARwb68TkWf4icSJwelSjf2zW0P6smjCTiMjlrHXz6jMPs3Qu5bN6t5BTmxDo8EREREZFGYTvwzVaT473rAKhMPyzGEUlLEUrszO6epxFI7IyBw+DId9zfaRZ93DvJ3VbKy7PXkL+zPNZhioiItCpK2kirkbEmDysSZXU7WNQZfhk9lp6kxDosaWZ2H96NZZePIZjgY+AOWPgUdF6exwNfPMBLy18iEAnEOkQRERERkQa1YpdFD2cLSWaAqOUjmNg51iFJC+K4vJR0zqak07HYlpf44C5uSfqAy5PnEyov4f5nv2HOwjyVSxMREWkgStpIq5GxYgMA/x4Ip9m9ON3uHeOIpLkq65zB4onjKOuYToYf5jxncM0ih09zP+WeT+/h223fxjpEEREREZEGYTvw1VY3I7xrAKhM7QWGvgqQOjIMAsndKT78LKLdh2LgcIxrDb9Pe4tsYxnTX1rAQy8sorxSpadFREQOlX5Tk1bBU15JWm4BAO8P8HBLdGiMI5LmLpQcz9IrxrBrQB9ctsNT78L/zfZRWlHEtHnTuH327RQHimMdpoiIiIjIIVlTaOEJlZDl3oGDQWWKbm6T+nNcXqJHX0D+MT8nkNgFHyHOT1jIXSnvUL5yLlMensOStTtiHaaIiEiLpqSNtArOypWYDnzVFX6WdBzJeGMdkrQAttvF2gtPIX/ypQBc92WABa+n07HC4MMNH/KbOb/hy81fapu/iIiIiLRIjgNfbnEzwrsWgGBiZ2x3XIyjktYgmNaHzcf8gp1HXIQRl0x7q4yrEr/g6uhrvPzMqzz64iJKK0KxDlNERKRFUtJGWrwwUZJWVD1Qc8GAdE5wusU4ImlRDIPtEy/gk4dvIRznZcjKQtbNTGTi7u74w36e++45Hv36UXZU6G4xEREREWlZcooMiv1RjvFWlZKuTNUuG2lAhkl51+OIv/Qh0kZejOGJo6uriMlJn3DMuif4+7R/8NHXG7HttnsTnAG4XWadX4YR68hFRCSWlLSRFu/zwiUctS1K2IS+fY+PdTjSQm0ePZQ3/3Unhb07k1hYxszH8nhzaX8SbBdrdq/h3s/u5YOcD4ja0ViHKiIiIiJSK/O3mAzzbsRnhIm4EwnFd4h1SNIKGZ440k68gO43/52U7PNwXF46u4q5wP0pyR/ewz8feowV67bHOsyY8BCkky9Al/hgrV+dfAHcwWLCxTuqvaKV5bGejoiINBFXrAMQORS7qSR+RdUDNXP6pBEfnxLjiKQlK+7dmTefu4uTHn2TPq/P4bw3V7FhSQdu/lk8/0nI5c3Vb7IgfwFXDLyCvu36xjpcEREREZH9yi8MsqHY4GfJVddLlam90e370pis+CTajb6C1OzzKVrwPwrnvUsG5Zwc/pTSl7/mjZRjGXLOBfTq2TnWoTYZJ1SJP281oUCw1m0syyCxXQJWnOeHgy4Xvi59seISGyFKERFpbrTTRlq0p80lXLCsaqu1c0T/GEcjrUHU52HB/7uO3KcepjI9mQ4bd/DKw5v437dH0ikaz5bSLfxp7p94efnLVEYCsQ5XRERERKRGn3xXSE/XTrq4inAMk8qUnrEOSdoIKy6RjJEXkPWrp4gfdRWVrhSSzQCDyz4n+MIv+Oiv97F51cpYh9lkouEQkVDdXnYkjBP94UUkEutpiIhIE1LSRlqsNc5OSrZuoHcxhDwWhYfrWTbScErPOpW3//MAOWOPwbQdTn9nBTkzDP6Y0xPDdvhg/Qdc9NUvmG/nxTpUEREREZFqSitCzF9bwgnetQAEkrrjWJ6DtBJpWKbbS8cTzuGI2/4Pc+S1FLk74DGi9K5YQuSN37H6+T8TKNgMjh3rUEVERJoVlUeTFslxHP5qz+X6ZVV/LuzbA9ut5SwNK5iWxJwHrmXdGceR/cirpG4q4K4XKpjUNZU/HB/h//oW8Cvrv4y1enFzdCgpeGMdsoiIiIgIHy/ciseuZIgnFwB/au/YBiRtmmG56HniOHqccDoblyxk05w36Vq5lg6hLbBtC+Xb4qlI7YOR0RPH0jXVoSj3h/AH6r4rJ97nIjFeiV0RkeZC33JLi/T+tk9YGdnOhSuq/rzjqJ4xjUdat7wRR7FleH+OfO1Tjn7qPTK3FPPEq/D/2sfz56P9PDtoI1/H5XNz9GhOs3thoFrhIiIiIhIb4YjNrPl5DPfm4DJswt40InHpsQ5LBMMw6D3kGHoPOYac1RtY+t4r9KlcRqLpJ7F4GZHilZTEd4f2fYj4UmMdbovkD0RYvamQcKT2u5fcLpN+PdKVtBERaUaUtJEWJ2JHmLbm/zg9B9pVQjAxjuIembEOS1o5x2Wx/JJTWHP28Rzxn88Y+O+PyNxZxiOz4MGP4LUjgrw0YB6ze67n5xxLFhmxDllERERE2qCvvsunuCzAianrAPCnaZeNND9Z/XqTkXoVn3/0Jdtzc+kbXUs3VyHt/Bth00ZK3RnYGX0IJnUBQ5X96yIcseuUtBERkeZHSRtpcV5d9SobKvJ46DsTsNlxZE8w9UucNI1wYhxLrz6ddZeezsi3FpP+/H9I3LaLy5fB5cugxLuD/x32Hit7daHngGTong6Gdt6IiIiISNP44Otc+rrzSTfLsE03gSQ9+1Oar65pFu19XdlR0ZXFW0voGljLIM9mksO7YNsuAtvjCKX1IpjWG9vli3W4IiIiTUJJG2lRInaEB796kOQAnLXWAahK2og0sWicl13nj2VLko1v/WYyl20gbc1mUsoDXLwcWL4V3p1OICUBX/fe0K0bdO4MGRnQsSM4TqynICIiIiKtzNad5Sxfv5vrEtcAEEzrBaYu+6X565AAHQ5PoThwLG/mDya5bCPHedaSbFbiK1xJtHA15QldibTrg5PQLtbhioiINCr99iYtyvNLn2dD8QZuWRuHO1JJRUYKFZlpsQ5L2jLDoLxzO8o7t4PThpGYv4uK9atxb97C0VtsfCUVsGxZ1evHfv1r6NEDevaErl2hS5fqr65dqxI8IiIiIiK19OHXm0gx/Bzh2QpAIP2wGEckUjepPocTe7upCB/OR9v6EinK5xjXGnq5dpFSsRkqNlNipVMROoLEPn0xLH2tJSIirY/+301ajHA0zH2f3wfAL9akA1vZcVRPlZ6S5sMwKO/SHrq0p9yEu1wbWbRpHgO2OwzdZjCqOIUeJWAWl0AwCGvXVr32Jz2dzH5ZDO+WxJbBvckf1hcnw9t082lgBvq7KiIiItJYwhGbjxdu5lhvDiYORvte2N5kCIdjHZpInSW4YUR3B7tbJ9YVdmVeQQlZkbUc7cklJVoI6+eyZf0Cdif3pX2/o+mV0SXWIYuIiDQYJW2kxfjX0n+xsXgjg0Lt6LUyH1BpNGm+4nHzm5Sz2D50DL8qfY3HQiuBYtqbSTyQdBkTh0zCZQO5ubBlC2zdWv21YwcUFuL76hv6Af1e+RiA3f16UHnqSWxLtIm0oEc5uUwXETvCpuJNh9RPsjeZtDjtrhMRERH5qW9WbKe0PMjxaesBMHsNBX+MgxI5RKYBfdtF6dsukbLQUD7aMRBvSS6DjbWkWX66ln5HdP4yPv66B8VpR9Cteyf6d7TwunTDmIiItFxK2kiLELEj/PGLPwLwaOGxGM7/KO3ZiWBKYowjEzmwI92d+SB9Cv8LLudXpa+xJlrA5JIXmLF0IY+cNYNTT55Yc8PKSli9ml3ffMaOz/9L5jcraZezlXarN8Hqf9HFNNid1YXNI46ivFPzr+lsGibloXJW7lpJMBKsVx9el5fsrtlK2oiIiIjUYNbXufRxFZBulGF4fJjdBsCa1bEOS6TBJHkchnR1YfU4DE/8QDbmbcW3cwWd7O30N3KhJJf8xak8E+qHP7UPR3TxMbSLSYekFnS3m4iICEraSAvx+srX2Vi8kYz4DE78YjMAOwcdHuOoRGrHMAzO8A1gjPcI/u7/jHvK32NZ0WrGPD+G0/qcxgOjH2BY52HVG8XFwZAhVPRKZ8HwNILRIHG7S8n6fDkD3p5H4vK1ZKzdQsbaLew6rCubRg6gIjM9NhOsg2AkSDBav6SNiIiIiNSsoNDPknU7uSw+BwBf32yiLk+MoxJpPOkJFj2OzgKyCJRXUJCzCu+2pXR2FXOB62v8gUXMX3kY9y7uR3JKEsO6WRzfwyJB34KJiEgLoNsNpNlzHIdpX00D4N70n+FasQLH7Wb3kX1iHJlI3bgNiykJo8np8mdu6X81LtPFh+s/5JinjmH8K+NZVrDsgO0r2yWz9mcns/apP7N4yoVsH9AbxzDIWLeFo5/5gN6zF2KGVLNcREREpK2Z/c0mvIQY4q26wS3uyJExjkik6cSnt+fwMy8l87Srie93HLYvmXgzzMlxK/ldypucEPqCr1bs5NZ3gzz0eZQlBRahaKyjFhER2T8lbaTZ+2zTZyzatgify8dVK6puiwmckE00ruU+kF3atnQrkenD72HNz9dwxcArMDB4c/WbDHxyIOe9fB4Lti44aB+VHdJYe3Y2CyefxY7+3TEch64L1jDs/94jbX1+E8xCRERERJoDx3H47NstDPVsxEUEd/tuuDvqBjdpe0yPj/heg2h/0sUkDz0dd3pnLMPhWO8G7kx5l+sS52CXFPDuOg+PLYpjziY3pUE9+0ZERJofJW2k2duzy2bSwKuJf/VNACrGjY1lSCINondab547/zmW3biMC464AAODt9e8zbFPH8upz53K+2vfx3bsA/ZR2S6Z1eefyLKLTyaQkoCv1M+AVz6h18ffYkQP3FZEREREWr6cLcVs3+0n27cegKRBp2AY+iJa2i7DMPB06EHK8LNJyT4fT2YvAI7ybGFq8ixuTfkfvcx8vs538cRiH++s81BYqb8zIiLSfChpI83aih0r+O+6/2Jg8Bt7BGzdipOaSmBEdqxDE2kwR3Y4klcveJWVN6/kykFXYhkWH2/8mLNeOotTnjuFjzZ8hD/sP2AfRb07s/C6s9g6tOpZT93mr2LgC7PxlJQ3xRREREREJEY+X7yVzlYR3axdYLpIOkql0UT2cKd2IPno00gbeRHebv3AMOlu7eSGpI/5ddr/ONyVz/JdFv9Y4uO9HA9FlbGOWEREREkbaeYenvcwAOf3P58u734KQPT888Gr0mjS+vTL6Me/zvsX66es59bsW0n2JrOxeCMvLHuBO2bfwbNLnmXt7rU4jlNje9vjYv3YY1gxYSQRr5uUrbsYNPM9XBs2NfFMRERERKQp2LbD3KX5DPfmAJBw+DCshJQYRyXS/FgJqSQdNQrP8Avwpx+OY1h0NnZx497kzTa+22nx+AKL/8zNp7QiFOuQWwTT1NeKIiKNwRXrAET2p6C8gBe+ewGAO46eAtedA0Dk4otjGZZIo+uR2oOHTnuI/zfq//HIvEd46tun2Fq2lXlb5jFvyzz+FZfJqdHOjKYLPdn3onx33258m5lG/9c/J6mgiOQnnoZJNpx0UtNPRkREREQazepNhRQVl3Ns2gagqjSaiOyf4Y3H33EQFWmHE1+4hvji9XRmFzclf8RWpz1vlA1h/lqDBTklHNErnaH9MklL0k2j++NLSKGoLEx54MCVIX4q3uciMd7TSFGJiLR8StpIs/XPJf8kbIcZ3mU4w5fshNJS6N4d+/jjYc13sQ5PpNEleZO4evDV9Ejpwardq5i7eS6L8hextbKAf1HAvzyL6e4kc7zdhWy7C0c57XF9v4EykJrI0itOo/97X9Nu9SZ46qmqHWrTp4NqnIuIiIi0Cl8s3soAdx7xRhArKZ243oNiHZJIi2C7fJR3GIQ/fU/yZgNd2MktyR+Sa3bjlaJBLF/vsGpjIQOyMuiemUSH9PhYh93shCIOq3MLwbRq3cbtMunXI11JGxGRA1DSRpol27H5x6J/AHDjsBvhnqodN1x2GWj7rbQxhmHQJ60PfdL6cNXAq9idt4b3l73OfDuPzUYpm61SXrZWkeh4GG534ninK8fanUj2eFkz4SQGf7OJ+NmfwmOPQWUlPPkkuPTPv4iIiEhLFrUd5n6Xz8Xfl0ZLGngyRh2+OBURsF1xlHcYjD+9Lwm7VxNXvIGedh53pGxhBYfxevFRLFnrsHLDbs4Y0YsJJx9GqnbeVBOORMHUjYEiIg1J39pJs/Th+g/JLc4l1ZfKhR1Pgf9eV/XGZZfFNjCRGPO6vIztdCKjVlZQHCxkgbGNr8ytzDfzKTGCfGxt4mM2YTjQ20nlaDpx5pghjO90MUkvvAozZ8KuXfDSSxAXF+vpiIiIiEg9LV+/C6NiN31T8gFIGjQ6xhGJtFy2K46yzCEEOxxBcsVmrK1LOYq1HJG2nkXOEbxZ1J+3PlvP/+blctaIXpx/UhYpiUreiIhI41DSRpqlvy/8OwBXD7qauLfeg3AYBg+GI48Ef91qpYq0Vol4ONnpwcnRHkSjNiuNXcwzt/KVsZWNZgnrjWLWU8xr/lVc3RumXN2Zh54vwP3224ROORnP+/+DtLRYT0NERERE6uGLJVs5xrMB0wBfjyNxp3WMdUgiLZ7tTSJ6xCVs73YKqWveJaFoHcewjKEZa/nGHMLrBb14/ZMc/vvVRs45sQ/njeqjMl8iItLglLSRZievJI/31r4HwPXDrocHvt9lc/nlMYxKpHmzMBngdGBAtAOTGUIhlSw1dvCdtYuVrkJW2zuY3j2fxZfBOy9B6rz5rD2qE//60yUMG3YOJ/U8ibQ4JXBEREREWoJI1Gbed1v5xZ7SaINOiXFEIq1LKLkbW4fcQHzhGtqv/y/esi0cF/2aYzut4FN7KO8WdOWVj9by7twNnDcqi3NH9ibe527kqA5egswwqp4ZcyC27RC1nYYKSkREGoGSNtLsPP3t09iOzUk9T6JfmRfmzq36zeOSS2IdmkiLkU4cJzs9GGNn0TfpcOzkRD7v4+Yz/0qu6fw/Hpuew+H5Qa675VnGXvEsOe1NhnYayim9TuGU3qcwotsI4txtq3yaZakGvIiIiLQMS9bupGMoj3a+cgxvPAn9jot1SCKtkj+9L/nt+9LPWU904etEigsYzaeM7J7Je4FhfLIjnRdnreb9Lzdw4amHMy67J25XI1xXmBY4UcLFOw54mjsYoZMvcMCkTNTykV9iK3EjItKMKWkjzUo4Guapb58C4IahN8CLL1a9ccop0LlzDCMTadnaW8lM6HkSE3rcAOOg6LJvKTvjLHpu2sZXz1qcdmmUBc4CFuQv4E9f/ok4Vxyn9TmNc/qew1mHn0Vr2vBfVFlEabC02rFwOEzAGyC/Ih936OB3yCV7k7UzSURERGLmiyVbGf79LpvEI0/AdOvZGiKNxjBxZ2XTedhISr+dTdHc13CVF3Ae7zPusMN4sXAQS3bDU28t5+3P1nPp2H6cNLQblnnwnTG1DsEwsUMBQrvyIBLZ73mVlSHKdlcQjdackHG5PcR174dpepW0ERFpxpS0kWblvbXvsa18G+3j23N+v/PggsFVb6g0mkiDSjviaPhmCYwbR7tvv2XBS4nMfuTnvJiRz8cbPmZr2VbeXvM2b695G9MwGdnhWEZE48mmHUktPIVTGixl3pZ5BCPBvcfC4TAFBQVklmfidh84aeN1ecnumq2kjYiIiMREKBxlyfJczojbBECySqOJNAnDcpNyzBkkDRhF0VdvUPrN+3h3r2MiOZQeMZSZWw4nt6iSv768mDc+zeGKcf3p266BEyORCE40vN+37UiYSCi036SNiIi0DEraSLPy5KInAbhmyDV4li6H1avB54Pzz49xZCKtUIcO8MkncN55mJ98wtibH2Hsyy/j/PJZviv4bm/S5ttt3/Jpwdd8CrjdJifYXTnTzmKo0xGzFnWVm6NgJEgw+kPSJhQJ4Q/5CUQC2KYdw8hEREREDuzbNTs4wlmH27Bxd+iBp1OfWIck0qaYvgTajb6C5KPHUvTpi5Sv+ILk7Qv5pW8p23uewD/WdWXz9jIe+Oc3DOiZzEkdIallXjaJiEiMHPjpZCJNaH3hej5c/yEGBtcNvQ5eeKHqjXPPheTk2AYn0lolJ8N//1uVGA2F4Gc/w3jmGQZ1HMTvR/2eRZMXkXNLDncP+Dm9jXTChs0n1mZuc8/hEvfbvGiuoIzgwcdpZYwWmqwSEZHWb+7cuUyYMIFBgwYxevRoZs6cieMc+I7r9957jzPPPJOBAwcybtw43nzzzX3OGTlyJH379t3nVVhY2FhTkf34YvFWjvu+NFryoNEYhn4vEYkFd2oHOpz3CzpP/DO+bv0hEqbjlk+4p9073DKoGI8Fy3JLeWK+yaeb3YSjsY5YRERaCu20kWbj/xb9HwBjs8bSO6k7vPxy1RsqjSbSuHw+ePVVuOEGmDkTrr0Wdu+GO+4AoE96H2478jrOWQPfVaznfTOHj8xcthsV/MO1hOec5Zxh9+GCaD86kbhP96Zp4bFcWIaF16pbvfWoEyVi779mcyy4TBcRO8Km4k2H1I+eiyMiIg1tyZIl3HDDDYwbN46pU6eyaNEipk2bRjQaZfLkyTW2mTVrFrfddhtXXnklJ554Ih999BF33nknHo+HM888E4DCwkIKCgq44447GDp0aLX2ybq5qkkFghE2r17BhPhCHNNF4lGjYh2SSJvn65xFpyvuw7/2GwrnPE+4cBtZ/nd4qGdnPggO5b9bUvlqq/v/s3ff8VFU6+PHP7OzLdn0QhoJCaGX0EFEQCkqViwURVCwYb928frTr+WKglcE9IpXwXZVQEXBiogoggiKKL0nEEghvW22z++PJSshCUkgsAGe9+u1bHZ2ynNmZ5c585w5hx2FKle0cRAXJHf2CyGEOLbTKmmzatUqZsyYwe7du4mMjGTcuHFMmjTpmC2LvvzyS15//XUyMzNJSEjgtttu46qjutoaNGgQubm5NZZds2YNERERTV4OUZPdZWfen/MAmNxrMvzwA+TkQGQkXHSRn6MT4iyg18Obb0J0NLzwAjz6KOTlwbRpcMRvbDstgnbuvtzh7skPun18rNvOXl0xn6o7+Ey3k4FaS0a7O9JFiwZAZzARZQzDXGYl3GWlo9WCWzM3OCy7xcQ2V3azStyoikq5o5yt+VurjYvTGDIujhBCiJNh9uzZdOzYkenTpwPeeo7L5WLOnDlMmDABs7nm/8Evv/wyF198MY8//jgAAwcOpKSkhJkzZ/qSNtu3bwdg+PDhJCUlnaLSiNr8ti2XXrodAAS174saGOzniIQQAIqiYGnfj8A2PSn9YxlFPy/EU5TFRWTRLzaW94t6sbsyknc2mRjQ0sWABCeq9H0jhBCiDqdN0kZajZ3ZFm1bRL41n4TgBC5tdyk8P8n7xtixUM+g4EKIJqIoMHUqREXBQw/BSy9577j5739rzGpGzyWeVEZ4WvO7ksNCdRvrdNn8pGTyky6TLp4obnB34Xy1Baq1Evfvq3DrLNjLDuLy1D1w5pH0ZgumAQNRzSoumk/SpsrR4+IIIYQQ/uRwOFi7di333ntvtekXXXQRb731FuvXr2fAgAHV3jtw4AAZGRm1LvPNN9+QkZFBcnIy27Ztw2KxkJiYeNLLIY5t9YZ9XGpMByC42xA/RyOEOJqiGgjtcwlBXQdTvPpTStZ9RZgjh7stX7HD0poPi3qy6kAgu4pULm9jp0XgsbuvFEIIcXY6bZI20mrszDZn/RwAbu15K/pKOyxa5H1DukYT4tR78EHvXW633AJvvw2FhfD047XOqqDQR4ujjyuOvUoxH+u2s0yXzmZdPo/pfqS9dSsP5VroVVmBR6fgspY3OGkDp9F/UkIIIYSfZWZm4nQ6SU5Orja9VatWAKSnp9dI2uzZswfgmMtUJW3CwsK49957+eWXX/B4PAwePJjHH3+cFi1aHHfMmqZhtVqPe/mzjdXmwrH7NyyBDrTAcLSYtnXuP7vd27DE7XHjcjdiIA1Nwe1243A4fJN0Oj06jweH04HmOvZ5nNvtxu1y4/LUcSHa7cHtduN0OHC4DncR5dHhdDqP61jweNy4XZ4TKuOZXj5oWBmdLtfhIrjROEYi4egynurywWnyGSoE9L8WT8s08pe9i6lkPx3Yy1Ph+1hh68TSii68vdHMeS0d9Il1oDuyA5kT+B6eymPUZrMB3mNHoxFdvp3AMWNzeqi0Hd/gQAFmFbNBbm/yp8rKymrPQtTnTDtmNE1r8FiEp8X1MGk1dmbbmreVlftWoioqt/S8BRYvhooKSE2Ffv38HZ4QZ6ebboKICBg9GhYvJijrIOqIHsdcpLUWxqPuc7jF3Y2P1e18rtvJDs8hbt34HK2VCO4zDKQ7oacmfiGEEOIsU1ZWBkBQUPXx5SwWCwDl5eU1lqmaVt8y27dvJzc3l9GjR3PjjTeyZ88eZs2axfjx4/nss88IDAw8rpidTifbtm07rmXPRn+lV9DXsBMAW1wntu/YUee8RqOR8AATVqsVa0XDL4wa9DpCA6GsxI7H470Ia7SEEBXcgrz8fJy2ui+a6HQ6FNVEaVkpTlftF3ANJjO68nJyD9mxObxJArNRT1y4Ql52Ge5GXLyvKmNZedkJlfFMLx807DOsKl9FRUWd5autjKe6fLWVsXl/hoFkh6ehKdHElO8m0FXCMPMm+pt28oW1Bysz27AjHy6ILSTE6K61fNC4z/BUlU9VVRRjMIWFBb51NcSJbm9rej6ORmwPwGjU0yklCs3RuG2KkyMjI8PfIYjTzJl0zBiNxgbNd1okbU63VmPSYqxxXv31VQAubXMp4fpw3PPmoQLOMWNw1pJJrWo15nF5W5A0hseloXm8D4/O28Kkof9h61yHW6Q4nThcDnT6hrcO0TudaE4nHNFSpkpVDLXFcfQ2a+PUOXF7as6j0+twu914XJ5695Oieue1V8Wn06E4nbgaeRw7nU48Hk+Dtnk0ncuDx+M57hY3R+7jqv3pcntP5Kqe69ru0fu4rn1abbl69m+NfVpt4YbvX6fTWS2Oxnyu1eJwOhv/mQ4bhm7xYkyjR6P/7Xc6ZGaw4ZrzcFqOPSZNGEZudaUxmvZ8EZLFJ2xmr6uQ+xyLiVeDuM7dkQvdyRhQj7meE/nOHcvR+xTwtWJz1PZ5Hb18A46P+jRVWcSpdaa18hEnz9l4rDSm1Zg4Oaou7NVFp6vZurihyzz77LOoqkpaWhoAvXv3pk2bNlx//fV8/vnnXH/99ccVs8FgoE2bNse17Nnoh7UrON+QgwYknX8takhUnfPa7XYqCvIIDAzEoG94d9N6nUJQUBCBpr8b2ujMgZgDA4mOiqr3Lgar3U2IlTpb+euNJoKCgojRwnyt/I16HVGRUYQHxzU4ziq24gKCg4JPqIxnevmgYWV0ulwUlVRgsVjQqPtuhKPLeKrLB6fnZ2jTGyiKTKSyIovQgi1YnBWMtfzK+eZtLLb24pN98QxrZadLlAuDevzfw1NZPpvNRmZOERERkcc8Zo52IvuzqMxJeJH2911Cp2CboulUVlb6GtEHBAT4OxxxGjjTjpndu3c3eN7TImlzurUakxZjDWdz23h/4/sAXBhxIbt//JGuP/wAwPa+fXHUsh+NRiPhgLXSSkVJSaO25zIF4XA6qKioINhkoLysDLuzYWNSGF0aAeXl5DpzsTqsBBoDyQ/Kp/xg+TETP6qqEmOz4crNxXPUBVqdTodT76SstLTWi79Hb7M2DouDyuBK8vLyKLf9/V0INAZSbjBQWVqKo6L02GXTGyk3lWMv9rbk0QUGos/PJ7f82GU7upyuQBe2inJKG7DNGjG4NKgox11YSOmB0ka3uKnax9hsNfZpRXnFMbd79D6ua58eqb79e/Q+PVJD96+qqthMNnJz/46tMZ/rkXE4HXnoGvmZAhAVRcibb9L6jslYcvLp/v53/HJJb6yhlgYtPtbUlfsG/oP//PwyC9XNZCnl/Nv0G++4N3F1eWuGWltiqiN5c7zfuWOpbZ8eqaCgoN51NOT4qE9TlEX4z5nUykecXGfbsdLQVmPi5AgO9g5IX1FR/bynrnpRY5bp0aPm3ba9evUiODjY19308VAU5bjv0jnblFkdhGT/BmbQtexCcGz9XXtXAKpORVMbfnFTVRVUVa32fdbpjag6HUaDEU137OSs3eVA1avgruOCsapDVVUMRiPovHEZ9DoMBsNxHQuO0mJUvQ69euzGQEc6uoxnevmgcWVUdSoox0jaHFXGU10+OL0/Q1doEgUhLQko3kNQ/jZiKeH24B/Y6Yxlyf6e7C0J47K2zuP+DE91+XSKQqDZCLqGX1406HUYjce3vXKbtVrsjdnm8ZZRNL2AgAD5LESjnCnHTGMauZ0WSZvTrdWYtBhruPc2vUe5q5yU0BRuHHgjxpf+jaJpuAcOJHX48FqXsdvtVOzdRmBAIPpGDk4eEBSM0WDEYrFg0BkICg7G7D72XQNVDIHBmIKCiDHGYHPZMOvNREVFEW+Jr3dZfVYWWkwMHO7z9Ugl9mKC7SG43DVbyxy9zdqEmkMJCAwgOjqaYFewb7pZbybIEYQhJASn/tg/CnrVQFBQEKGmsMMLm1GiogiNr79sR8qx5lBSEAQN2ObRDIHBWCxBhEZEENsytlHLQvV9XLVPbY5KKsorsARZ0Ku1/9zVto/r2qdHqm//1tin1RZu+P7Nqsgipvzv2BrzuVaLIzT6uD5TADp2pCzkbczXjyeoqIzzl6xl4zWDKIuLrHfRgKBgogLCmRx4Hv9Qzue18h/4SLeFAtXGm6Fb+SRkL6Oc7bnC1YZAqrewO5Hv3LHkWHNIsiVhd/2dsHU4HBQVFREeHo6qV3EeY9ydhhwf9WmqsohT60xr5SNOnrPxWGlMqzFxciQlJaGqKvv27as2ff/+/QCkpqbWWCYlJQWAffv20alTJ9/0qnWkpqZSVlbG0qVLSUtLo127dr55qu6QjoiIaPKyiJp++fMAfY3e71l0v4v9HI0Q4oQoOirD22ILaYWlcDuBRbtpZ8jhodCvWW9PZuGf3blK1eiX4u9A6xcWoGJw20BpRKNLnYLBXoyzuHoDOJ0pEDWgZgMDIYQ4G50WSZvTrdWYtBhruLc3vQ3A5D6TCQq0wIcfAqBOmnTMfVgB6PSqtwVJI+j0CorO+9Ap3hYmmtKwFho6/eEWKQYDHp0Hg2poeEsNg8H7qCWZqLrUOuM4epu1rlpvQNXVnMegGlDdqncd9ewnVeeNwVTVkudwvMZGHscGpwGdTtegbR5Np9eh051A65cj9nHVPq1K1OhVfZ3x1LaP69qn1TZXz/6tsU9ribUh+9fgMFSPrRGfa7U4jvMzreJISWHb5Gtp8/ZignMK6TH/B7ZdNZDCNgnHXO7I71yQYuY6unKFqy3f6PbwkbqVHKWC/xr/Yr5hG9e6O3C1pz3BVLWYO4HvXFERlNZ+J1KErZw0Rxhu7e+KhRs35QYLQQThCgxkmysbl6f2pHBDjo/6NKosotk5U1r5iJPvbDpWpGs0/zOZTPTu3Ztly5Zx8803+z6TpUuXEhwc7GukdqRWrVrRsmVLli5dyogRI3zTv/vuO5KTk2nZsiV2u51nn32WYcOG8e9//9s3zw8//IDNZqOfjEF5Suz7fRVtdZU49RYsbXv7OxwhRBPQVCPl0WlYw9oQlL8Fc+k+epky6Gbcz6o/27M3rxtX9QzB3MgGkaeS4rJTuX87LlfDG9SqqkJQpAU14Ii6sl6POaG9JG2EEOKw0yJpI63Gzkx/ZP/BuoPrMOgMTOw+EX79FXbuBIsFrr3W3+EJIY7iDLawcdwwOn72MxF7s+n88U/sGtGXnO6Nu7PQhMpITzsu87RhmS6d/6lbOKCUMU+/kfnaVq7ytGe0uwNRnMAJe2kprFkD9prdH3oqi7AX7cF1xN00HpeHytJSAmJiMQ06H9Ws4mrknXxCCCGEv91xxx1MnDiR++67j2uuuYYNGzYwd+5cHnzwQQICAigvL2f37t0kJSX56jp33XUXU6ZMISwsjCFDhrB8+XK++eYbZsyYAXiTQbfeeiuzZ88mKiqKwYMHs3PnTmbPns3QoUPp37+/P4t8VigqsxFbsB6MENB5EIrauPE/hBDNm8cQSGlcH6zhbbEc2oi58hDnm7dhz9/F0m870KZbd7qmNt9GIC6nE5fz2GMJHUlTFTwuI5r772RU801LCSGEfzR8pDA/OrLVmKb93S9nQ1uNHenIVmNGo5Fnn32WN954o9o80mrs1Jjz+xwAru10LdGWaHjnHe8b114Ltdw9JYTwP7fJwJZR55OT1hpF02j39VpardwIWu19Jh+LHh0jPKm857yMJ10DSPGEYlVcfKBuYbThc2a5fyHPVnj8wdrttT40WyUua3m1h9NahqOiFFdl7WNHCSGEEKeD/v37M3v2bNLT07nrrrv44osveOSRR7j11lsB2LJlC2PGjOHHH3/0LXP11Vfz9NNP88svv3DXXXfx22+/8eKLL3LJJZf45rnzzjt56qmnWL16NZMnT2bevHmMHTuWl19++VQX8ay0bt02OhkOAhB7jnSNJsSZymUOoyRpECVJA7GZozApLgaomwndtICfvvuJkuIyf4cohBDiFDkt7rQBaTV2pimxlfDhJm9XaJN7T4bKSpg/3/vmTTf5LzAhRL00VcfOS8/BHhxIq9WbabVqE6aSCnaN6IvWyG7xAFR0DPUkc4GnFb8oB3hP3cwOXSELtE0sWnk757UayPnJ59MqtNVJKI0QQghxZhk+fDjD6xgbsl+/fuzYsaPG9LFjxzJ27Ng616nT6bj++uuPa7xPceKK//wBnaJRHpKCMaqlv8MRQpxkzqBYopNTUUqyObT5N0LdhXSs/INDH2+mOLIbnbp3Rm8y+TtMIYQQJ9Fpk7SpajU2a9Ys7rrrLmJiYnjkkUeYNGkS4G01NmHCBKZOncrVV18NeFuNORwO5s2bx6effkpiYmKtrcYiIiL48MMP+eijjwgLC2Ps2LHcc889finn2eKDTR9Q4aygY1RHBiYN9CZsSkshORkGDfJ3eEKI+igK+wZ3wx4SSNtvfyN2014CisvYcs0gXIHm41qlDoXztEQGuFrym5LN+4ZtbNRyWJGxghUZK+gc3RmH28GkHpNQdY1PDgkhhBBCnG7yiipIqdgIKkT1udDf4QghThFFUQiOTyYorhUZO/dg37OeKKWYwMLfyF3+J66YjiR2TkNntvg71CZUfydpigIGff2dBnk8Gm5P43uDEEKI5uK0SdqAtBo7U2ia5usabXLvyd5BUqu6RrvxRtCdFr32CSGAnB5tsYdY6Pj5KkIz8+jxzlK2jDofa3Toca9TQaGvFk9/tS1beyby2v5P2Ji7kS15W7jty9t47ufnuKP3Hdzc42Zv14pnsaLKIkrtpSe0jhBTCOEB4U0UkRBCCCGa0l8rf6a1Wo4dE8m9Bvs7HCHEKaYoCint2+Dp1Jk/N6dj2vMzMWoxpkMbyTu0GU90O1p07I5qOf76V7OgU0Fz4yw+dMzZDHYXcWZbvQkZt2omq8TTJImbcqsDq63x450GmvUEBRpPePtCiLPTaZW0EWeGNQfWsOnQJgL0AYxPGw8HDsCyZd43J0zwb3BCiEYrSo3nzwkX0fnjHwkoLqf7e0vZNvI8ilLjT2i9iqLQK6IL98cncrDsIKv2r2LNgTXsL9nPlOVTeOrHp7im4zWMTxvP8NTh6HVn339ppfZS1hxYg91lP67lTXoT/Vv2l6SNEEII0Uy5t/8IQEV8T3QG6Q5JiLOVXlXpP+x88lJbsvq3nUQWbqS1Pg81bzuFedtxh6cQ2a4rminC36EeF0XR4XHYcORngqvuBEllpYOyggrc7rqTMXqDkYCkDuh0piZJ2lhtLrbvK8Tp8jR4GYNeR4dWEZK0EUIct7PvCpfwu6q7bMZ2Geu9UPj+HO8g5oMHQ+vWfo5OCHE8rNGhbLjpIjp/upLQzDy6LPyRPcN6UXhRiyZZf1RgFGM6j2HGRTNYc2ANr/32Gr9n/c5Hmz/io80fEWOJ4bou13FD2g30jOvZgBvrzxx2lx27+/iSNkIIIYRovrIP5JDi3AMKtBp0mb/DEUI0A6EBKiMGtCG3rDXfrz9IbMlGuhgPoC9Kp2RtOg5zOObwFKxBSWinY6M2lwvN7azzbY/LicvhOGbS5mRwujyNStoIIcSJkn6oxClVYC1g4ZaFgLdrNDTt767RbrrJb3EJIU6cK9DMxuuHkpPWGkXTaLPsd5IXLgO7o8m2Ydabuan7Tfx262+su2Udd/e5m6jAKHIrcnll7Sv0frM3nf/TmX/99SpbHAfRNOnHWAghhBCnp50/fo1e8ZCvtiA6tYO/wxFCNCMxwTrGnp9I60Ej+NYykjX2Njg0FaOtiKDsP4jY/SVBuRtQT7ArZSGEEP5xGqbdxens3b/exe620yO2B33i+8Cvv8LOnWCxwLXX+js8IcQJ0lSVnZeegzUqlJQVf9Ji3Wacd9xP8cjBENm0g2T2SehDn4Q+vHzRyyzds5T/bfwfi3csZlv+Np7I38YTQGs1istNaVxuTmOgsS1GRf7bE0IIIUTzp2kagfvXAOBpM8jP0QghmqukcB03DIohpyyapZv74szaybmmHbRQy9AX78FSvAe7ORJ7aCtswS0B6a5LCCFOB3L1Spwymqb5uka7o/cdKIry9102114LQUH+C04I0XQUhQPndKI8JpyOS9Zg2LGbtrMyKR51BSQ1beIGwKAauKzdZVzW7jJK7aV8uvVTPl7/Hj8cXMVedz4zrT8w0/oDIYqZi02dGaC0IhaIwYxyVnWkJoQQQojTxf5NfxKpFeLQVDoOHeHvcIQQzVxssI4b+wezv6ALn//VlrKCQ/Q37qSL4QAmWwEmWwFBuX/iDElACVQhOA3pfEcIIZovSdqIU2ZFxgp2Fe4i2BjMdV2vg8pKmD/f+6Z0jSbEGac4JY4t999Ap0UrMW7dQdR7H+Pq2Z7dQ7vjMZyc/35CTCFM7DGRiRFDKP/hW74v+4sltr/4yr6JQ54yFtrWs5D1oIdoLYBunhi6aS3oqkQRgnSlJoQQQojmIeeXr4gGMgM60CE8zN/hCCFOE+EBChemuihLCGdj3gC+y3XQlgz6GPcSry/GVJoJa98nyRBIWYtulEd1xRnd1t9hCyGEOIokbcQpU3WXzfi08QQZg+D996G0FJKTYZDc8i/EmcgRHkzBf/6N+tT/0eKn34n9YwfB+7LZccW5lMdFntRtB+nMjDR3Z6S5Ox7NwzpnBl/aN/J95VbWuzLJUyr5Xs3gezJAD6FGI52IoevuUgKj4ogPjifUHHpSYxRCCCGEOJqrooTwgo0ABHYb7udohBCno0ADnBPvol+cjvSSNizK6YC1pITexnR6mdIJdVoJO7iGsINrcOvN2Pb1oLzrAAJTu6MzBvg7fCGEOOtJ0kacEgdLD/LZ9s8AuL337d6Jb7zhfb7lFtDJbblCnLEMBrIvGYTSrj2hHy3CUlBKj3eWknlOR/af1/Wk3XVzJJ2i4xxja84xtuZ+dSB/FWxlo5bNBl0ufymH2KrkU6I6WEMma/YsgD3e5cLN4bQKbUVCSAIJwQnEB8djCW/6Lt6EEEIIIars//kr9LjJdEfSe0A/f4cjhDiNKQq0DvPQOsxBiT2Qv/J78nJeX2KcB+hm3EdXYyYhLhuuXWs4tGsNqAYCkrsSmNqdgJRuGCITvF3bCyGEOKUkaSNOiTm/z8HlcTEwaSBpMWmwZQusXg16PUya5O/whBCngL1ta/687UqSv11Di637SFqzlagdmey5sA9FreNOaSxm9PTUYunpjgWg0uVggzWTnCiF3fEmNpTtJLssmyJbEUW2Iv7M/dO3rF6np3VYayICI4gNiiU+OJ6E4AQiAiLQKZKAFkIIIcTx0zxubBu/xwwcjOzH4AAZNFwI0TRCTRpDUjxcPqQ9azNaszGjgMUHiokjlzRDJmnG/URTRuWeP6jc8wcAanAkASndCGydRkByGqpFeiIQQohTQZI24qSzu+z894//AnBvv3u9E6vusrniCog7tRdrhRD+4wo0s33keeR1akWbb38jsLCMrvN/IL9dInuG9cQeFuSXuIyodHCGcx4tCex6CZvMJZTYS8gsyWRfyT6yyrI4WHaQ7LJs7G47Owt3QmH1dZhUE3HBcb47cqruzgkxhfilTEIIIYQ4/ZTv/B2zs4Ryj4nkc4f5OxwhxBlIp1NIig0mLsqCu2dLcgpaU1zWk//sPoSpJJeOhoN0MGTTWp8LZQWUb/yB8o0/AGCIaok5sSPmxA5oUclomowLKoQQJ4MkbcRJt3DLQg5VHKJlSEtGdhgJViu89573zdtv92tsQgj/KGiXSHFSDK1+3kTC7zuI2plJxJ6DZPVqR2b/zjgtZn+HiFlvpm1kW9pG/j0wp0fz4HQ5QYGV+1ayv3Q/WWVZ5JTnYHfbySjOIKM4o9p6go3BvrtxEkISaBnSktTw1FNcGiGEEEKcDrJ/XoweWO9uzw1dW/o7HCHEGU7V6UiOC6HreVFEh/ckM7eMv3bls35XHh/sySHWlUV7QxbtDdm01BfhzD+AM/8AZRuWeVdgDiHIGIbdHIEzIBKXKczbJ5sQQogTIkkbcVJpmsasdbMAuKP3Heh1elj4PygpgZQUGCatx4Q4W7nNRvYO70VOt1RSl/1O+L5cWq7bTuyfu8nq3Z6cwb38HWINOkVHtCWaTtGdCDGFYHfbAXB73ByqOOS7I+dg6UGyyrLIs+ZR5ihjR8EOdhTs8K1Hr9OTFpPGwKSB9EvoR7+W/UgJS5H+ooUQQoizmCP/APpDO/BoClr78zHoVX+HJIQ4iyiKQlJsCEmxIVw+sDVut4c9B0v4a1ce3+/OZ19GFvFaDq31h2htyCVRLURvK8VkK8VUuh8Aj06P83ACxxkQidMcgaZKN49CCNFYkrQRJ9Xag2v5Pet3TKqJW3ve6p1Y1TXarbeCTsZ/EOJsZ20RxqbrhxKenkPyj38SnFNI0i9bSPhtBwU780i/6QLscc2772RVpxIXHEdccBy9+DvZZHfZyS7PrpbI2VeyD6vTyh/Zf/BH9h++eaMDozk/+XyGpgxlSMoQ2kS0kSSOEEIIcRYpXPsVAJudLel/Tlc/RyOEONupqo52SeG0Swpn1NB2uNwe9hwoZvOeAlbtLWDn3lyi3YeTOPpDpOjzCMCJyXoIk/UQABrgNobgCIjEGRCB0xwJAdJ9tBBC1EeSNuKkmrXWe5fNdV2vI9oSDX/8Ab/+Cno9TJzo5+iEEM2GolDUOo6ilFgid2SStGYLwdmFtPj0G65e9C2Z/Tuza8wwSBzo70gbxaQ3kRyWTHJYsm+apmkU24ox6U3sKdzDuqx1bMjeQJ41j4+3fszHWz8GIDEkkaGthzI0ZSjDWw8nJijGT6UQQgghxMnmtpZSvnEFOmCLsTtXJof7OyQhhKhGr+po3yqC9q0iuGZIW8rLK/hr027++GMPK4o68V6pQjglpOjzSNbnkaLPI1otQ+8oRe8ohZJ0ADw6A87cGKyRcejDYzCEtgC5GUcIIaqRpI04abLKsnwXH+/pe4934syZ3udRoyA21k+RCSGaLUWhoEMSBe0TicgpJXHrQULXbiDpl80k/bIZ1wsfwbjxMH48pKX5O9rjoigKsUGxnJ98Pq3CWgHeO3J+z/qd5enLWZ6+nDWZa8gszeSdP9/hnT/fQUHh3MRzGdlhJCM7jKRNRBs/l0IIIYQQTal0/bfoPE4yXRGk9Osnd9sKIZo9nU6hVXQAxpYeesc48WiQWxFAekkKq0vaML9URwA2kvX5pOgPkazPp5U+H4PHiafwANbCA94VKQr6sBjMSZ1RzRb0oVEoqsG/hRNCCD+TpI04aWasmYHL4+K8pPPoGdcTcnNh/nzvm//4h19jE0I0c4pCaWoCe267mYxDO0n95HvaL/kFc3YuvPSS99GuHVxxhffRv7/3Dr7TlElvYkDSAAYkDeDJwU9S4ahgdeZqlu9dzrK9y9iQs4HVmatZnbmah5c9TOfozozsMJJzEs5B0zR/hy+EEEKIE+Bx2ile9zUAy22dmdw70c8RCSFE4+kUiAvSiAtycW6CC6cbDpTpyCiJ5beSeL4o06FDI0EtJFmfR2tDHm2MeYRoFbiKcigvyvGuSNGhD2uBITIBY3QS+tBoSWQLIc46p+8VLtGsFduKeWO9d+yaxwY85p04Zw44HHDOOdC3rx+jE0KcTsqSYlh737VsvGcMF+1002LRUvjyS9i58+8ETkQEXHopXH45DB3q75BPmMVo4cLUC7kw9UJe5EUySzJZsmMJn+/4nB8zfmRL3ha25G0BIC4ojn4t+9EvoR8RARF+jlwIIYQQjVW+cQWarYwCdxC22O7ERwX5OyQhhDhhBhVSwjykhHm4ALA6YV+pyr7SMLaVRfFzeUcAwnXltNHn0s6QTXtjLqF4kziuohwqd69HMQVijE7C2KIVWmAL/xZKCCFOEUnaiJPi9d9ep8xRRpcWXbik7SVgt8Prr3vfvO8+/wYnhDgteQx6Ki8dBuNug9JSWLoUliyBr76CwkJ4/33vQ1GgSxdITIS2baFNGzCemk6S9To9qqLWO59JNaFTdA1eb2JoInf1vYu7+t5FUWURX+/6ms+2f8ZXu74iuzybz7d/zuLti2kf1Z5zWp5Dj9gemPXmEymKEEIIIU4BzeOmeO0XAKywdWTI8GT/BiSEECdJoAE6Rrrp0sJDQrSJSreebYc87MoPZXd+KL8Xp6JVaETpymhryKG9PpuOxizMdiv2A9uxH9iOpqgEW1pgC0rAHpSAJt2oCSHOUJK0EU2u0lnJK2tfAeCRcx/x3sa6cKG3e7SEBLjmGv8GKIQ4/YWEeMfGGjUKXC5YvdqbwPnmG9i2DTZt8j7A221a69bQoQN07AjRJ6f1ql6np6M+DlOFvd55VUUlOKcIij3VyxRe/6DD4QHhjEsbx7i0cWzO3cyMX2ewav8qdhbuZHv+drbnb+cj9SP6xPfh/JTzSQyRLlaEEEKI5qpixzpcRTlUeIz8RQfu7pHg75CEEOKUaBGso0WwjsGpoDMG4giJY/uWvew8ZGBXXhgfF7TDVuGmjT6XzsYDdDFkEqlWYCrPxlSejZsNFJni0SIS8QTHQiMaxQkhRHMnSRvR5N79610OVRwiKTSJsV3GgqbBK69437zzTjBISwghRBPS62HwYO/j3/+GrCxYsAA+/RS2boWiIm9Xajt3wpIlhJtNdEhsQWFyC4qTY7FGhTZJGKqiYqqw41r9My5bxbFD1hnwhKdCwOEkjcnkHZenAUmbIwWbghnUahD9WvYj35rP2gNr+fXArxyyHmJV5ipWZa6iTUQbhiQPoXtsd1Rd/XcBCSGEEOLU0DSN4l8+A+BnewcG9Eoh0Cx1JSHE2cliUukar6dLjHfMTk3TyC3T2F3Qij35ifwvvy+OkiI6GTLpZUonVi0hyp4J2ZlUZhnJVJOoCE4iIiaGYD+XRQghTpQkbUSTcnlcTP9lOgAP9n8Qg2qA776DP/6AgAC47TY/RyiEOOPFx8PVV3vHubHZ4NAh790327fDjh3orFYidmUSsSsTALvFTFFSDJnxYbjCT7yPZJetApe1/Ngz6QxoAZWgCzzh7el13v/KE4ITuLrj1VzV4Sp2Fu5k+d7l/J79O7sLd7O7cDfh5nAuSL6Awa0GE2oOrbasEEIIIU49687fcOTswa7pWWnrwNT+yf4OSQghmg1FUYgNUYgN0XFeindaYZmODfsC+L24PfbyEmId++iiZhCqq6SdZzeU7Ca7IJQft6WTHdaNsOgo4qMsRIYef9fRCmDQN+4uHoNeh6Ic9yaFEEKSNqJpLdyykL1Fe4kMiOTmHjd7J/7rX97n22+HqCj/BSeEOPsoCsTEeB/nnw8eD8U7N1Hy11pC0g8SkpmHqcJG7LZ9xG7bh+fHTZSu2krFhd3Zc15HHCEWf5fgmBQU2umiUa3WatPTLH25tmtfDrUt4NPMpSw68B2FtiIWbV/EFzuWcGn8+dyQfCVJse1QkNqEEEIIcappmoeilR8BsNLWgaRW8aTEN83dv0IIcaYyqAoJwRqxgR4gCOjMIVtn9hblE1y2jyTPfuL0JcTxK87SdfyV34pf7G3J0SfQKSWKnh1a0CklklZxIai6htWDjNiJM9twe7QGx6nqFAz2YpzFfzfm05kCUQNOTlfdQogzjyRtRJNxup08ueJJAP5xzj+wGC3w88+wcqV3EPCHHvJzhEKIs55OhzupJQctVvad0wHF5SbkQB5he7KI2L6f4JIKwlb9xsBVv3GuXuVg3w7subAPGRf0wGk5/tZZJ4uiKBgr7Njr6JItBJhIBOO0UazQ7eUTz2a2aof4/OD3fH7wewZH9+Xu8x8mMTTRO/6YEEIIIU6Jim1rcBzaj00z8oOtM5PPTfZ3SEIIcVoKMUNIXBTERVHsTsNQloWpdD+Blbn0NqXT25ROrjuENelt+d/2VCo0Mxazng7JEXRJjaJ7u2hax4eiqyOJozkqsWZux2Grf+zSKqqqEBRpQQ0weifo9ZgT2kvSRgjRYJK0EU1m7oa57CnaQwtLC/5xzj+8E6vusrnpJkiQQTWFEM2LplcpSY6lsGU0G7q1Ikm1EOfQY/5xFeF7DpL0yxaSftmCa+oHZAzuzu4RfSkZdI6/w66hvi7ZdMBQ4hhKHJuUQ8xXt7Fad4Cf8tbx08ej6JfQj4fOfYirOlwl494IIYQQJ5nmcVO0cgEAKyo7ogYEMyAt3s9RCSHE6U9TDXhatEXf/xoO5hzCsv8XgnM3EEMpIwPXc3ngBra4klhlbcMf252s336Id7+C0CAj3dpG06NdC3q0jyYyNKDaet1OBy6HoxFxKHhcRjS3NxEkzeOEEI0lSRvRJKxOK8/89AwA/xz4T4KMQfDbb7B0KagqPPqonyMUQoh6KArWmAiyL7qETXePwLxnH6nLfqfNN+sI259Lm+9+o813v2ELf4/yKy/hwOA2HOiSyOnWWXFXrQVdXS04GODi07hivsz+kbUH1zLq41GkhqfyQP8HuKn7TQQaTny8HSGEEELUVL7lZ5wFB7ErZn60d2TE4CSMBmk0IYQQTckRkkhFh1HktbmCsPy/iMn/DQ7tJU2fQVpIBg5TONsNnfjqUDw55bByw0FWbjgIQFJsMOd0ieO8bvGEKQ3vFk0IIZqKJG1Ek3h13atkl2fTKrQVt/e63Tvxuee8z9dfD61b+y84IYQ4DiXJsfxx62X8cculRG/dR5tv15L63e8EFpRifmcBl7wDpQlR7L64L7tG9MOW2srfITdKKyWM/9dlHI+PeJ7Pd3zOa7+9xp6iPdz19V08ueJJ7upzF3f3vZtoS7S/QxVCCCHOGB6Xg6KVCwH4rqIjDsXEJdI1mhBCnDSa3kR5y3NIGXwZoY5cyv5aTvnmlRhtRaTZV5MWqOBu3YndAV354VAkOw6UsT/H+1j4/U5iw010CFPoHK4QapIEjhDi1JCkjThhxbZiXlj1AgBPn/80Jr0JVq2CJUtAp4MpU/wcoRBCnABFIa9zMnmdk/n1vmtpu2E/3ZZvJuirZYQczKfn3K/pOfdr8jsmYxt+AdkBTlynUWPZaEs0z1zwDI8OeJS3/3ybl9e8THpxOs+sfIZpv0zjpm438UD/B2gb2dbfoQohhBCnvZK1X+AqzsWqs7DS1oHze7ckNtLi77CEEOKsYIpNwRR7CxFDxmPdsY7SP7/Htm8zas4W2rOFjoEhmIaex57Abvy018367YfIKbKTU6Tjx3QzyaEeesS4aB/hpo4hcIQQoklI0kacsKk/T6XIVkSn6E7ckHYDaBo8/LD3zZtvho4d/RugEEI0EU2vkjOgGxEjr2PTA5cT+8M62ny7jsQ1W4jalgHb3iZBUShOjiG3SwoF7RJxmwz+DrtBLEYLd/e9mzt638GibYuY/st0fsv6jTnr5/DG+jcY2WEkD5/7MP0T+/s7VCGEEOK05CrNp3j1pwB8WtoDp2Jg1FBpFCGEEKeazmAiqMtAgroMxFmUQ9mfyynbuAJ3eRGVf3xNPF9zU1wqt11xLn+URvPV+jzSixQySlQySlRCjB56x7no3sKFWa6sCiFOAvlpESdky6EtvPzrywBMHTrVO4D1xx/Dr7+CxQJPP+3nCIUQ4uRwBZjYc3Ff9lzcF3NRGe2W/0mXL38jaPMOwtNzCE/Pwa1fR0HbluR3SKQ4ORZXgMnfYddL1amM6jyKaztdy8/7f2b6L9P5cueXfLb9Mz7b/hkDEgfw0LkPcUX7K9ApOgCKKosotZee0HZDTCGEB4Q3RRGEEEKIZqlg+XtoTjv5ppb8XpjCgG7xtGwR7O+whBDirGYIjyXignGEDx6Ldc8Gyv78Huuu9diz92DP3kNbFO4KbkFBZEvWWJNZdyiQUoeOH/YZ+TnTQFoLF31iXUQESNdpQoimI0kbcdw8mofJX03G5XFxRfsruKL9FWC3w2OPeWd46CGIi/NvkEIIcQrYwoPZMWYYxiuvQVu4gMj1W2mxOZ3AwjJabNtHi2370BSFsrgIilLiKE1NhLBUf4d9TIqiMKjVIAa1GsTWvK38+5d/879N/2N15mpWL1hNu8h2PNj/QcZ1HUepvZQ1B9Zgd9mPa1sWo4WesT0l8SOEEOKMVblvMxVbV4Oi8HZed0BhzLB2/g5LCCHEYYpOxdK2N5a2vXFXlFC+7RfKt6zCfmA7hvJcYsllJH8wIjaG3VoiSwtbsb8ykPU5Btbn6Gkb7uaceBctgz11baFBcZRbHVTaXceeSYOjU0SBZj1BgcYGbUMI0fxJ0kYct3f+fIdV+1cRaAhk1sWzvBP/8x/YuxdiY71JGyGEOMvYI0PZf15X9g/oQlBOIdFb9xGxJwtLfgkhWQWEZBXA6s14TD9A69aQnAzt2kGXLtCqlb/Dr1Wn6E7MvXIuzw15jtnrZvP676+zs2Ant395Ow9+9yCXtLmE1IhUWoW2QlEa37mzyW2i3FHO1vytx534MelN9G/ZX5I2Qgghmh3N7aTgu7kAZAT35EBBBH06xZASH+rnyIQQQtRGtYQS2nsEob1HULBrEzk/f46+MB2DvQSzNYcu5NA54DfKQqL4y57EitJW7CoKZleRnoQgN/1buoiLOiKtolNBc+MsPlTvtl02F6UllXg8dd+541bN5JRpuA/PY9Dr6NAq4riSNuVWB1ZbPUmiWkiSSIiTS5I24rjkW/N5eJl33Jqnz3+aVmGtYP9+ePJJ7wzPPANBQX6MUAgh/ExRKI+LpDwukvShPTGWWQlPzyZ8bzbhGTkYrHbYts37+OYbmDkTUlKgb19IS/Mmcbp08SZ1dDp/lwaAuOA4nh/6PFPOm8K8DfN49bdX2V24m4VbFwIQGRBJr7he9IrvdVwJHLvLjt19fEkbIYQQorkqWrkQx6H9YArizf3eO21Hy102QghxWlCDI7HHdKY0pA2qvRRz+UFMZVkY7EWEOPMZqMtnYNgfFBHKBlsCW20JfLa9BSszPVzW2cXAFBWzUYfHYcORnwmuYydIKisdlBRU4HbXnrTRG4wEJHXA7THhdNV1V0/DWW0utu8rbNS6TiRJJIRoGEnaiOPywNIHKKwspGuLrtzX7z7QNJg8GcrL4dxz4eab/R2iEEI0K47gQHLTUslNS0Wv6OlkDyEsuxDS0yEjA7KyvH+np8OCBX8vaLFA587eR8eO3keHDt4Ej58Em4K575z7uLffvazOXM3stbNZsmMJBZUFfLf3O77b+x0RARF0bdGVri260j6qPUZVTuiFEEKcfWyZ2yhe8zkAS3XnU+4xM7B7Ah1aRfg3MCGEEI3mNoVQYQqhIrIjOqcVU3kWpvKDGK35hFPCEHMJQ8xbsWt6djpj2f5XPMs3JtCzHVw8wEGwy4Xmdh5zGx6XE5fDUWfS5mRwujxNkgASQjQdSdqIRnv/r/d5f+P76BQdcy6bg0E1wPvve1uKm0wwd26zaRUuhBDNkqLgToiDtl1g0CDvb2ePHpCbC+vXw+bN3se2bVBRAevWeR9HMpmISU0hOC6KMo+V8pAArFGhVEYE4zGcmv/eFUXhvKTzSAxJZFjrYazPXs/vWb+z6dAmCisL+WnfT/y07yf0Oj2tQluRGpFK24i2pIanYjFaTkmMQgghhL947FYOLZ4Fmoey+L58vTkCs1Fl0uWd/R2aEEKIE+QxBFIZ3obK8DYobjvGikOYKnIwVuRgctvpajxAV+MBAAr3WVi5JxZXSDypqfF0TAxFp2t8t9JCiLOHJG1Eo2zL28bkryYD8NTgpzg38VzvRcZ//MM7w1NPeVuACyGEaJzQUG+3aMOH/z3N5YLdu2HTJti6FbZv9yZyduwAmw3j1u0Yt0LYEavRAFtYEOUx4ZTFe7tnK4uNwG0+uXe6GFUjPeN60jOuJw63gx35O9h4aCObcjdRZCtiT9Ee9hTt4bs93wEQHxxPm/A2JIYm0iGyA8lhySc1PiGEEOJUy/9uLq6SQ6gh0cze1xHQGDO8PVFhAf4OTQghRBPSVBP2kETsIYmgaRhdpURphSjFWTiLcohQK+ir7gH7HtgKezYHUWmJIyohgRYJ8egDg/1dBCFEMyNJG9FgVqeV0Z+Mxuq0MjRlKP8c+E9wu2HiRCgshO7d4aGH/B2mEEKcOfR6byL86GS42w379pH3+0qcq1ai/rIGc24+gfmlGGwOAorLCSguJ3pHpm8Ra0QIZfGRFLeKobhVDO7AkzfumFE10jWmK11juqJ10ci35rO7cDe7Cnexu3A3uRW5ZJVlkVWW5VvmyR+fpIWlBfHB8SSEJJAQnEBcUBwtLC1QdepJi1UIIYQ4GUrXL6V844+AwrrIy8nNcJEQbeHKQa39HZoQQoiTSVFwm8PQR7ckuENvNJcTV3kxRfn5lKRvI8SZT7iunPDKXbB7F8W7waoGowuLJTw2Dk9gJGhS/xHibCdJG9EgmqZxz9f3sPnQZmIsMXxw9Qfei2j/7/95u0Uzm+Gdd8Bg8HeoQghx5lNVaN0aW6SBwlaRVMQYcVnLQdMwWO1Y8ooJyikkOKuA4OwCzCUVBBaWElhYSszmdABsYcFUrN0Dl10Gl42C+PiTEqqiKERboom2RNM/sT8AZfYy7503hXs4UHaArLIsim3F5FbkkluRy4acDb7ldYqOGEsMsUGxxAbFEh8c7/tbxskRQgjRHFn3bCB/6VsAOLpezv9+dgNw28g0DHq5ECeEEGcTRW/A1KIViZ0HENM+Dbu1nJ27s8nPOkiILZuWaiGB7jIoKKOyYBcAwYqJSlMkWCLxWKJwmsJAGrIJcVaRpI1okKd/epp5f85DQeHDaz4kJigGPv8cnnvOO8Obb0K3bn6NUQghznqKgtNiptgSS3FyrG+yocJGUE4BIQfyCduXS3BWPubiMsxffA9ffA/8A7p2hYsv9j4GDPCOs3OSBJuC6R7bne6x3QEIMYYQGxTLN7u/Ib04nQOlB8guzya7LBu72+79uzy7elFRiAyMJC4ojtigWBJDEgkxhRBmDiPUHHrSYhdCCCGOxXFoP7mL/g2aB0OHgfzfHy3weBxc0KslPTu08Hd4Qggh/MxoMtGlczJ0TqbSqbEp00bm/iy0khxaKnkk6fMxYcdkywJbFhSACx0luggqzVE4Q2IwxbYG5eTV14QQ/idJG1GvGWtm8PRPTwMwe8RshqQM8Y6tMGGCd4Z774UbbvBjhEIIIY7FaTFTlJpAUWoC+wCdw0nEoTKiPAGEbd6F8a/N3nFzNm2C6dPBYoELLvg7iZOaetJjjAiIoFN0J1Ij/t6WpmkU24p9CZyq5E12WTYVzgryrfnkW/PZdGgTAPP+nAd4x8vpHN2ZHrE96BnXkx5xPWgT0Qadojvp5RBCCHH2cpXkkbPgX2iOSkyJHXktuztFZSW0ig3mzmukgZsQQojqAgwKfVsH0Ld1Kh6tNfuLNH7dV0ludh4Wex4tdXm01h8iSGcn0pMP1nywboecn6hwh5GltKDAGE9ZYCL7s1KIaxFKaJCJ0CAjYUEmQoNMBJr1KIri76IKIRpJkjbimOb+MZcHvnsAgH8N+Rd39b3LOxD2kCFQVgYDB8JLL/k5SiGEEI3hMRoobpeEc9il2Dt0J9EZAN9/D99+633k5sKXX3of4E3aVCVwzj8fgqqPh6NTdJjUhrf0cmtuXB5XvfMpikJ4QDjhAeF0iu6EXqdHVbzdApTaS33j4mSVZZFTkUNeRV618XKW7V3mW1eQMYjusd3pGetN4vSI7UGn6E4YVOnWUwghxIlz5B8g+8NncJcVYIiI44fgK9n0VxYBJj1TbuqL2SRVbyGEEHXTKQrJEQqRZgMHI0JwuYIpsafye7mCraIck62AcFc+8UoeLdRSYtRiYigG104oBfsmPZmuSDa7otjniiLDFU2JFoheVbyJHIs3mRN6OJlT9beiQUFpJQEmPZYAQ4MSPAa9DskDCXFyyZmjqJWmaby85mUeXvYwAI+c+whTzpviTdicf773gl63brBokYxjI4QQp7uoKBg71vvweGDjRli61JvAWbUK9uyB117zPgwG6NMHevWCLl2gd2+CLXo6Wi24NXODNme3mNjmym5Q4qaKXqenoz4OU4X98JRQCEqEICAOVEWlVVgrFJ3CtuLdbCzazobCLfxRsJmNRdspd5Szav8qVu1f5VunSTXRpUUX7904sT3oEdeDtJg0Ag2BdcahqtKXtBBCiOrsWbvJXvAvPNZSDJEJbE69kYXfHgDgvrE9SIgOqmcNQgghRHWKAmFmjTCzBlGBQCCQiGo0UtqiFbn7D6AWphNUcYAwexYmHLQx5NLGkOtbR7EnkExXBAcdERy0RrAvJ5xCTxBQe8bFoCpEhhiJDDYSFWIkMsRIdIiR6DAjIQF/37Gj6hQM9mKcxeXVlteZAlEDjv1/nk4nvR8I0RCStBE12Fw2bv/ydt776z0A7u5zNy8MewHljz+8A1bn5kJamrdVdlSUn6MVQgjRpHQ66N7d+3j0Ue9dlStW/H0XTno6/PKL93FYcIto4ltGUtEiDGuLcKwtInCEWqit+ZXebME0YCCqWcVFw5M2qqJiqrDjWv0zLltFzfXqDHjCU4kICOcc4BzigXgIGo4rQs/2jtFsUHLZkLOBP7L/YEPOBkrtpazPXs/67PV/F1/RkRKWQqfoTn8/ojoRbYnG6XRiM9nIqsjC4Ki7wUKIKYTwgPAGl00IIcTpq2L7Wg59MdvbJVpcKmvjruPtb/cDMGZYOwakxfs5QiGEEGcac3Ao+pQWOBO7UwxUqNA5womlIhPbwV3Ys3bhOLSPMJ2VMKOVrhzwLetWzZSZYynQtyBHiyTDGszuUgNFNh1ON+QU2ckpstfYpknViAqEaItGtAXax5pIbWEi2qKg0ymg12NOaF9v0sZsCaWozEm5zdqoMgea9QQFGhu1jBCnM0naiGoyijMY+8lY1h5ci6qozLhoBnf3uQvlrbfg7rvB4fAmbJYvl4SNEEKcDYKD4YorvA9Ng717vXffLF0KK1fCwYOoh/KIPpRH9BGLuUwGrFGhVEYEYw8O9D3c0ZEoHbuixGjHFY7LVoHLWl7zDZ0BLaASdDXvktEDXcLb06XVhYzvNh4Aj+YhvSi9WhJnQ/YGcity2VO0hz1Fe/hi5xe+dYSaQkkMSSRCjaBtTFuSwpKIDYrFpK/eLZxJb6J/y/6StBFCiDOcx2GjYNnblP35PQDmVl1YETqS+d97EzbXX9iesRe292eIQgghzhaKDl1EAsFt2hLcbQjg/X/KkZuOPSf97+e8TFS3jbCKDMLIIBUYAGiBCq7QIGz6YEqUEPK1ULJdoexzhJFbaaTIpmB3Kxwsg4Nl3oZ5y/Y4AScGFeJCFBJCVVq1OkByKxctY4KIjwrCoK95V43DpbE9oxB0De/BwKDX0aFVhCRtxFlFkjYCAIfbwUu/vMRzK5+j0lVJuDmchaMWMiysJ0yaBO++653xiiu8f4eF+TVeIYQQfqAo3vFtUlO9XWX++CMUFlK67S9Ktv+JOa+IwLxiAorK0NudhBzMJ+Rgfs31vL6INMBhMeMICsAVEoQ+IppwkwdboBFXgAlnYNXDjDPABEFBhOojMO0+gENz4TbocZv0uA0G3EY9GBp3SqNTdKRGpJIakcq1na71Tf/t4G/M3zyf9OJ0MkszySzJ5FDFIUrsJZTklQCwMmeld3egEBkYSVxQHHHBccQGxZIQnEBqeCpJoUky4KcQQpyhKtM3kv/tmzgLswAFc6/LeOdgO9b86E3YTLysM1df0Ma/QQohhDir6YxmzIkdMSd29E3T3E4c+Qdx5OzFnpuOIzcDe/ZecNowOMswOMsIJouWQHcABdwhATijginXhVDkCSLPFUSWM5gDzlAOlBtxumF/kcb+IhdrMjKBTO/2dQpxkRYSY4JIjAmmZYtgokL0VNhcOJw6FFXqSkIcy2mVtFm1ahUzZsxg9+7dREZGMm7cOCZNmnTMiyJffvklr7/+OpmZmSQkJHDbbbdx1VVXVZtn06ZNTJs2jc2bN2OxWLj66qu5++67MRrP/Ayu2+NmyY4lPP7D42zP3w7ABckX8OaI10n9+Ht4cgwUFnq7y3n+eXj4Ye/fQgghBIDFgrNTezJjFFweJwCK201AQRmW/GLMReWYyqwYyysxlVkxldswlFeiaBrGChvGChvkFgGZnEiP/x6dAiYTmAMOP5u9zwEBEBICa9ZASgpERnofERHVn03eO2ZaWFqQFpNG+6i/W0e7PW6yyrJIL0xnR+4OStwlZJVnUeGsIN+aT741n02HNvnmn7pqKoGGQFLDU2kT0caXxEkKTSIxNJGk0CQiAyIlqSOEOCmkznTy2LP3ULjiAyrT/wJADY4gp9P1zPypkjJrHnpV4bar0hjRP9m/gQohhBC1UFQDpphkTDHJBB+eVpR9kIxfV+ApzUd1lKK3l6F3lKI6ylDddlRXJaqrEjOHiALaVq1MD0qUEY8pmEo1iGJCyNdFcdAWQHqRQr7dyKE8Jwfzyvl1c061OPSqjmCLgZBAI8EWI8GB3keIxUhwoIEAk17qSuKsd9okbf78808mT57MiBEjuO+++1i/fj3Tp0/H7XZz22231brM0qVLeeihh5gwYQIDBw7k+++/57HHHsNoNHLppZcCkJmZycSJE+nevTuvvPIKe/bsYcaMGRQXF/PMM8+cyiKeUqX2Ut7e8Daz1s1ib9FewHuhata5zzF6vQ1l0JWwY4d35s6d4T//gUGD/BixEEKI04WmqlhbhGFtEVbjPX1gEObBw9npzIaSYoxlVsJtCq2VCA7u3wIV5RisdgxWG4ZK++G/7RhtTkLLnCh5eejsDlSHE9XhQnW5AdB5NKi0eR+1Wbny2EEHBkJkJHFhwVwYoGENCcQeYsEZFkxoeBwEBOAISqTckIwhtgWe1GDyzR722LPZW55Jenkm+63ZHLDmkGU7hNVpZdOhTdWSOUcK0AeQGJpIfHA8LSwtaBHYgpigGO/fhx8xFu/rIGOQVFqEEA0idaam53E5sO5YR9lfy6lM3+idqNNjbTWAhfkd2fBNKQCtE0K5/7qeJMeF+DFaIYQQonEURUEzBuKwxIAlpvp7boc3gWMvQ+8sQ3VaUZ0VqE4rOrcdzeVAcRUQSAGBQDyQBhBw+AG4VRM2nYUSTwAFDiOFThPlHjOVdiOVNiPWAiM5mpG9HiOVmvfh1ukJNBsINBmwBHjHsknPKiExJpjwEDMRwWbCQ0wEBxoxGhrezZoQp5PTJmkze/ZsOnbsyPTp0wEYNGgQLpeLOXPmMGHCBMxmc41lXn75ZS6++GIef/xxAAYOHEhJSQkzZ870VUDefPNNLBYL//nPfzAajQwePBiz2cyzzz7L5MmTiY8/MwaO1DSN/SX7+XrX1yzesZgVGStwuB0AtCKMf3ku4NqNAZj+736oODzAc2QkPPMM3HYb6E+bQ0UIIURzp1exBwVjD/G2znYYQ4iM7sSunCjs7pqDXgKYVBNdbaHYln9bfUwbjwfV6cbk1Ei1tCRcCQC73fuw2cBq9T6Hh4PLBQUF3jtICwr+/tvj8c5ntWLMhLhGFGWwyYgr0ITrcDdunsBgzOGtsQUHcCgIMhNDSQ92k66UkOHKY68jlwxnPuXGSnY6d7KzYGe92zCpJkJMIQSbggk2BhNiCvG+Ngb7pgWbggkyBhGgDyBAH4BZbyYyMJKYoBgCDYEE6AMINAQSaAjErDdLEkiIM5TUmZqGq7yYyoyNVKb/hXXn73hsVf/vKBREdeeTwk5sXa8CVvSqwuih7Rg1rB16VXokEEIIcebQVCPOgCicAdXHtFZVhfgIE4HY8VSW4a4sw2OzAhpuayluawmeilI0txPVbcfitmMB4lWgATkWl6ajUjPi8OhxlOtxlKs4cvU4ND2Z6NmrqTg072u3zohiMKIaTahGEwajEaPJhMlsxmQ2oej1oNNjMBrRm7zvm0xmDGYjJpMJ4+H51FquewaY9DKOjvCb0+JKvMPhYO3atdx7773Vpl900UW89dZbrF+/ngEDBlR778CBA2RkZNS6zDfffENGRgbJycmsWrWKwYMHV7ut/+KLL+bpp59m1apVjB49+uQV7CQpsBaws2Ane4v2sqtwF+uz1/Pbwd/IK8slvgxSimBCAQwtCueColBa7DiA4vrs7xV07Ah33gkTJni7lBFCCCGaK50Ot0mHI8CAJzIaAiNrzmMyecfgadWq5nseD5SW+hI5ufu3sWPnL6iFxZhKK7CU2ogpcqDsTUctr0BXYcNkd2Kwe7uC09sd6O0OKCo7YqW7sACRQMeaW/TRFAWX2YjTbMBm0mM1KZQboMzgpkRxUKY4sOo82FU7DjUPuz4Puwp2PdWey/VQqP49zakDlw6c6uHnWl7rjFUVGzOK3oBiNKIYDCiGv5+NehMB+gAsRgsmvQmjasSoM3qfG/AwqAYMOgN6nR69To9B9f5dNa2xr/U66SZBiGOROlPjaJqGp7IMV0kezpJDOPMP4sjNwHEoA2dhdrV5rWoIv7vasKIkmcJCb2eeFrOeEeemcNl5KUSGBvijCEIIIYTfKKoBfaAFgiMA0BkDMUS3xJGfCS4XmqahuZx47BV47FY8ditOaykVxcU47Q4UtwPF40TnPvy32+l9RkOveAhW6uhBoS6uww9r4xZzH17Eoym40OFGxYWKBx1uRcWDikdR0RQdKHo0nQpVD+Xws6qCTu977UGHR9H55lN0Koqq9/6t6r2vdXoU1ftap3r/NpmMBASY0en1qHo9ql5FVQ8/6w2oBj16VUU1GNDrVRTVgKLT+baBTnf4WZV60xngtEjaZGZm4nQ6SU5Orja91eGLL+np6TUqIHv27AE45jKxsbEcPHiQlJSUavNEREQQFBREenp6E5bi1Phk6yeM/WQsbs1dbfq1W+Cdz8HiPHJq0eEH0L49XHIJjBwJAwd6B5sWQgghznQ6HYSFeR+tW2Nr24L0VM13x8+Rd/jYS0soKSkhNDQUVaegtzkwVDrQV9ox2LzPJpuLGIIIdHigshKMRu9dPIWF3jtZKyq8rwFF07xdwFXaCQQiTmnBHYcfZXXO4VLqT/4c672q104dVDZiPW4daICm1HxWFAWdTkXR6dDpVFRF9b1WFBX18N/2ACOru0fgCjTXmgDSKTpUnYpO0Xn/VtS/p3GM9xo4zeV0kXcoj5jyGIxGIwre86qqytPJen1u4rl0btH5BI8NcbqSOlPDaZqHrLenYM/eXec8WVokW22xbHfGs9sVg4YOo15H7/bR9O0Uw+CeLQk0G05h1EIIIcRpwOVCcx8e61SnoAYEoQZ4GzwoDgfF5hJKrIBSy92pmoaiuTDoICg+hbwKcDvtGHDSKspMiEnD47SjOe24HTacNhuOSitOmw2nvRK304HH6cTtdKK5nWguJ7id4Hag09x4UzB/P+uOuPSpUzSMuPGmcY6O6/CD2t8+GeqIpME8KHhQ0NDhQed9VnRoKGjK4WlHPGtVz76/VTRFgcMJq6oHis43DUWHpvPO601YHX5f531fOWLZakkk39/KEX/qjnhb8c3ncrvJtSrsLQr0NR5SDv+jHLG8cnj+Gq+P3NzhOlNQoIG+nWIx6Jv3HdKnRdKmrMx7QSEoqPoQxRaLBYDy8vIay1RNO9Yyda23ar7a1lsfp9OJpmls3Lix0cs2hZbOlnx2wWfoFJ3vwoRRNRJ4gZO940q9R6pe730YjWgmk7cF8pG3AW6qvf/95kLTNDSMGM8fg0HzNGpZRaeSazDjGXAl+SgYPW6Mvl/eehdG05tp745FQ0NxKxTuK6Rkf0n9y7pc0K4daDW35dE8GD39a4/jqG3WRufU4cxx0t7dvto8iltB0ysYB1+Hsd79pJCp03Ow6kdSUbwXGEsaULYjuDU3HrVFA7d5dAg6XKqZ/Ix8ipSixi0L1fZx1T41aBoWTUM54oe7tu0evY/r2qfVFqt3/x61T6u91fD969bc1eJo3Od6RBw69bg+0yqay4k68FoCz9DvnKaBRdPQ6XRo+gD5zjVELd+5Bn22p/F3zuDx1PqbcuQJdTkKJYeTAigKmM3elldH83i8B56m/f33kc9uFx6HHU3TUDQA7e+KwuHjWqk6vo94VlC82/V4UMBbjqOXB5Ra1ne89DTPE8oRAVBUsyeok0vDezDogNjD05x1z97UMnZm4M45RTXJozidTmnR52enU50J/F1v0nC3vxjaun0XFxSdCqr+cEtYPe4KJ209Gh1VHXpVQa/XYdSrh3//y9i9c5sf4m44TdPQ3G50sYkYGnruhfdyRp5OR/6R/9XaFZTsIjR3UL3/Z2gmUOOjqOsyiIKC1V5GiK4c7XDOS1Ega38ROQca/xuiedxo0QkYGvF/WY0ynunlgwaVUdNreKKjMNSzqaPLeKrL541BPsM6t3cKy6dpGprn1P7O1Fc+7/qb4Wcox6h3Ww38nQGFCoMBk0lB04JQFMhTdRQoChjxPix1L33kvtM8blwOBy5Nw1VrUH/XmbS/J3ijUDhcp+LvCR7P36+PKKdWrb5Vve515Aul1td/Tzv6/fqWOdGz7+adtvCKAIo8xXi0I6I9gSpspR02/JmL2Xjqx0NqTJ2pOdaxa/B4jn0hSqereYg1ZJn65jmeiqevxaOfKq0WowWLsZZfLjMQHlVj8ulYtVYUBQ73VXm8VLO3C4Pj+XoeV2+WBoP3UVssDYijIds0qnXMZQpswNJNQ6/owaQ/pdv0OWIfN7Cb1Gpq23t17tMjneSy6hU9emMtP9WneB8rBiPG0OO/D0C+cyeHfOea3in7ztWWyDl6libYzOn4/3xTCT/8EKeGN5l5Nh9x/nc61ZmOXM4/x42CPqRm3ehIESGn98DGiqKATodax/nQca1Tbdjlg4bsuaaKSlH1GAOa5rLGmV6+qvUdS2OO+qYo46kuX5Uz+TOEU1c+3++M/tT+zjT0OG2On6Eco6f/74zwj2h/B9BEGlNnOi2O2uDgYAAqKiqqTa+rZVhDl6la7uh5quarWkdj9OjRo9HLCCGEEEIIIcSJOJ3qTCD1JiGEEEIIIepyOtwFRVJSEqqqsm/fvmrT9+/fD0BqamqNZar6XD56marXqampWCwWYmJiasxTUFBARUVFresVQgghhBBCiOZG6kxCCCGEEEKcGU6LpI3JZKJ3794sW7YM7Yj+ApcuXUpwcDBpaWk1lmnVqhUtW7Zk6dKl1aZ/9913JCcn07JlSwAGDBjAjz/+iMPhqLZeVVU555xzTlKJhBBCCCGEEKLpSJ1JCCGEEEKIM8Np0T0awB133MHEiRO57777uOaaa9iwYQNz587lwQcfJCAggPLycnbv3k1SUhIREd5xF+666y6mTJlCWFgYQ4YMYfny5XzzzTfMmDHDt95bbrmFr776iltuuYWJEyeSkZHByy+/zOjRo4mPj/dXcYUQQgghhBCiUaTOJIQQQgghxOlP0Y5shtXMLVu2jFmzZpGenk5MTAzjxo1j0qRJAKxdu5YJEyYwdepUrr76at8y8+fPZ968eWRnZ5OYmMhtt93GyJEjq633999/Z9q0aWzbto3w8HCuvPJK7r33XgxNOGijEEIIIYQQQpxsUmcSQgghhBDi9HZaJW2EEEIIIYQQQgghhBBCCCHOVKfFmDZCCCGEEEIIIYQQQgghhBBnOknaCCGEEEIIIYQQQgghhBBCNAOStBFCCCGEEEIIIYQQQgghhGgGJGkjhBBCCCGEEEIIIYQQQgjRDEjSRgghhBBCCCGEEEIIIYQQohmQpI0QQgghhBBCCCGEEEIIIUQzIEkbcVpZtWoV11xzDd26dWPIkCHMnTsXTdP8HZZoZux2O507d6Z9+/bVHj169PB3aKKZyMnJoXfv3qxdu7ba9H379jF58mR69+5Nv379eOqppygvL/dTlKI5qOtYue6662r8xrRv355Nmzb5KVJxqnk8Hj766CMuv/xyevTowdChQ3n++eer/WbIb4oQwh+kziQaQ+pOojGkHiUaS+pToj5Sr6qd3t8BCNFQf/75J5MnT2bEiBHcd999rF+/nunTp+N2u7ntttv8HZ5oRnbu3InL5WL69OkkJSX5put0kqcWkJ2dzc0330xZWVm16aWlpdx4441ERUXxwgsvUFhYyPTp0zlw4ABz5871U7TCn+o6VjRNY8eOHUycOJGLL7642nupqamnMkThR2+99RavvPIKN998M/379yc9PZ1Zs2axa9cu5s2bR1lZmfymCCFOOakzicaSupNoKKlHicaS+pRoCKlX1U6SNuK0MXv2bDp27Mj06dMBGDRoEC6Xizlz5jBhwgTMZrOfIxTNxfbt29Hr9Vx88cUYjUZ/hyOaCY/Hw+eff86LL75Y6/sfffQRxcXFLFq0iIiICABiYmK47bbbWL9+Pb169TqV4Qo/qu9Y2b9/PxUVFQwePJju3buf2uBEs+DxeHjzzTcZM2YMDz74IADnnnsu4eHh3H///WzevJlffvlFflOEEKec1JlEY0ndSdRH6lGisaQ+JRpK6lV1k6YT4rTgcDhYu3Ytw4cPrzb9oosuoqKigvXr1/spMtEcbdu2jdatW0ulQ1SzY8cOnnrqKUaOHMm0adNqvL9q1Sp69erlOwkAOO+887BYLKxcufJUhir8rL5jZdu2bQB06NDhVIcmmony8nKuvPJKLrvssmrTW7duDUBmZqb8pgghTjmpM4njIXUnUR+pR4nGkvqUaCipV9VNkjbitJCZmYnT6SQ5Obna9FatWgGQnp7uh6hEc7Vt2zZUVWXSpEl0796dvn378uSTT57x/V2KY4uLi2PZsmVMmTKl1lame/bsISUlpdo0VVVp2bKl/MacZeo7VrZt20ZgYCDTpk2jX79+dO3alVtvvZW9e/f6IVrhDyEhITzxxBM1WnV9//33ALRp00Z+U4QQp5zUmcTxkLqTqI/Uo0RjSX1KNJTUq+omSRtxWqjq/zIoKKjadIvFAiAnlMKnqm/Uffv2MXToUN58800mT57Ml19+yW233YbH4/F3iMJPwsLCiI2NrfP9srIy32/KkSwWi/zGnGXqO1a2b9+O1WolJCSE1157jeeee459+/Yxbtw4cnNzT2Gkojn566+/+O9//8sFF1xAu3bt5DdFCHHKSZ1JNJbUnURDSD1KNJbUp8SJkHqVl4xpI04L9Z0syiCJooqmabz++utERETQtm1bAPr06UNUVBQPP/wwP//8M4MHD/ZzlKI50jStzvcURTmFkYjm7v777+eWW26hT58+APTu3ZuePXsyYsQI3nvvPR5++GE/RyhOtfXr1zN58mRatmzJ1KlTAflNEUKcelJnEo0ldSfRFOScRzSW1KdEXaRe9Tc5axOnheDgYAAqKiqqTa/KqB7dmkycvXQ6Hf369fNVOqqcf/75gLdvVSFqExQUVOM3Bry/M1W/QUKAt+/lqgpGlcTERFJTU9m+fbufohL+8vXXXzNx4kTi4uJ45513CA8PB+Q3RQhx6kmdSTSW1J1EU5BzHtFYUp8StZF6VXWStBGnhaSkJFRVZd++fdWm79+/H4DU1FR/hCWaodzcXBYuXEhWVla16TabDcD3oy/E0VJSUny/KVXcbjcHDhyQ3xjh43K5+Oyzz9iwYUON92w2W7XBEcWZb+7cuTzwwAN0796dDz74gBYtWvjek98UIcSpJnUm0VhSdxJNQc55RGNIfUrURupVNUnSRpwWTCYTvXv3ZtmyZdVui1u6dCnBwcGkpaX5MTrRnLjdbv7f//t/LFiwoNr0r7/+GlVV6d27t58iE83dgAED+O233ygsLPRNW7VqFVarlQEDBvgxMtGc6PV6Xn31VaZNm1Zt+pYtW9i/fz/9+vXzU2TiVJs/fz7Tpk1jxIgRvPXWWzVaeclvihDiVJM6k2gsqTuJpiDnPKIxpD4ljib1qtrJmDbitHHHHXcwceJE7rvvPq655ho2bNjA3LlzefDBBwkICPB3eKKZiI+P5+qrr2bu3LmYTCZ69OjB+vXrmTNnDuPGjSMlJcXfIYpm6vrrr+d///sfEydO5O6776a4uJjp06czaNAgevbs6e/wRDNyzz338Oijj/LII49w5ZVXkpWVxcyZM+nYsSNXXXWVv8MTp0BeXh5Tp04lISGBcePGsXXr1mrvJyUlyW+KEMIvpM4kGkPqTqIpyDmPaCypT4kqUq+qm6IdazQfIZqZZcuWMWvWLNLT04mJiWHcuHFMmjTJ32GJZsbhcPDWW2+xePFisrKyiI2NZdSoUdxyyy0yAKsAYO3atUyYMIH33nuvWkuenTt38vzzz7NhwwYsFgvDhg3jkUcekT7gz2J1HStff/01b731Fnv37iUgIIDhw4fzwAMPEBYW5r9gxSnzySef8M9//rPO96dOncrVV18tvylCCL+QOpNoDKk7icaQepRoLKlPiWORelXdJGkjhBBCCCGEEEIIIYQQQgjRDEizCSGEEEIIIYQQQgghhBBCiGZAkjZCCCGEEEIIIYQQQgghhBDNgCRthBBCCCGEEEIIIYQQQgghmgFJ2gghhBBCCCGEEEIIIYQQQjQDkrQRQgghhBBCCCGEEEIIIYRoBiRpI4QQQgghhBBCCCGEEEII0QxI0kYIIYQQQgghhBBCCCGEEKIZkKSNEEIIIYQQQgghhBBCCCFEMyBJGyGEEEIIIYQQQgghhBBCiGZAkjZCCCGEEEIIIYQQQgghhBDNgCRthBBCCCGEEEIIIYQQQgghmgFJ2gghhBBCCCGEEEIIIYQQQjQDkrQRQgghhBBCCCGEEEIIIYRoBiRpI4QQQgghhBBCCCGEEEII0QxI0kYIIYQQQgghhBBCCCGEEKIZkKSNEEIIIYQQQgghhBBCCCFEMyBJGyGEEEIIIYQQQgghhBBCiGZAkjZCCCGEEEIIIYQQQgghhBDNgCRthBBCCCGEEEIIIYQQQgghmgFJ2gghhBBCCCGEEEIIIYQQQjQDkrQRQgghhBBCCCGEEEIIIYRoBiRpI4QQQgghhBBCCCGEEEII0QxI0kYIIYQQQgghhBBCCCGEEKIZkKSNEOKkGzJkCOPHj/d3GE2uvLycwsLCOt8fP3487du3r/cxe/bsUxh1wxQUFGC1Wo85z+zZs2uUpUuXLpx33nncfffd/PHHHzWWeeyxx2jfvn2j4/F4PBw4cKDe+dauXUv79u1ZtGhRra+bSmZmZrXX7du357HHHmvSbdSnqb5XDTlG27dvz9q1a094W+PHj2fIkCGNXu54j5umsHr1am699Vb69etHly5duOCCC5gyZQoZGRkntN6jjyEhhBBCiIaQutXJr1tV1XMaUv840qJFi5rsvLmx3G43c+bMYciQIfTu3ZvJkyeTlZVV73JVMdf3OJ5z+GNpaP0OYNOmTdx7770MGDDAV9+8//772bRp0wnF0JDz8SFDhlTbDx06dKBbt25cfPHFvPjii5SUlNRY5njrhg2pg0PNutHJqCs5HA5yc3N9r/15bAtxttL7OwAhhDgdbd68mTvuuIOXXnqJfv361TrP5MmTufbaa32vly1bxrJly5g8eTKtW7f2TffXxei6/PTTTzz00EN89tlnBAYG1jv/keWx2+1kZWXx+eefM27cOKZNm8bll1/um3fMmDH079+/UfGUl5dz0003MXjwYO65555jzpuamsq0adPo2bNno7bRGE8++STp6em8//77vmnTpk0jKSnppG2zNo8//jgBAQEnvJ5p06ZVez1nzhz27t1bY3pqauoJb2vy5MlUVlY2ernjOW6awscff8wTTzxBr169uPXWWwkJCWHfvn188sknfP3117z33nt069at0eu9+eabiY6O5oUXXjgJUQshhBBCnF6aW91q+PDhJCUlERER0ajl+vTpw7Rp05rkvLmx/vOf//Daa68xceJEoqOjmTNnDnfccQeLFi1CVdU6l6uKuUpRURFTp06ld+/ejB492jfdYrE0WayNqd+tXLmSyZMn06ZNGyZMmEBERATZ2dl8+umnfPvtt8yePZthw4Y1Ooba6nR1CQ8PZ8qUKQBomkZFRQWbN2/m3XffZenSpSxcuJCoqCjf/MdTN2xMHfxk140OHjzIpEmTuP3227n66qsB/x7bQpytJGkjhBDHYefOnRw6dOiY8wwYMKDa6/3797Ns2TLOPffcOisjzcHGjRspLS1t8Py1lWfSpEmMHTuWf/7zn/Tq1Yv4+HgAevToQY8ePRoVT3FxMZs2bWLw4MH1zhsVFcWVV17ZqPU31qpVq0hISKg27WRvszbHUzmpzdGxf/LJJ+zdu/eklOno70RDHc9xc6IqKyuZNm0aQ4YM4fXXX6/23tixY7nyyit57rnn+Pjjjxu97lWrVnHVVVc1VahCCCGEEKe15la36tChAx06dGj0comJiSQmJjZpLA21cOFCBg0axKOPPgqAy+Xi3//+N3v37qVt27Z1Lnd0zAcOHGDq1KkkJiaetDpOY+p3//rXv+jQoQMLFizAYDD4pk+YMIErr7ySZ555hvPPPx+9vnGXN2ur09UlMDCw1n0xYsQIbrvtNqZMmcKbb77pm348+60xdfCTXTc6cOBAjV4F/HlsC3G2ku7RhBBCNLmQkBCeeeYZ7HY77777rr/DEaLRdu/eTWlpaa2JpsTERC644AK2bduG3W73Q3RCCCGEEEL8zWazkZ2djaZpAL5z1CMTHaebwsJCMjIy6NevX41yhIWFMXLkSPLz8xvdjV1TGTRoENdccw0rV65k+/btfolBCHHmkqSNEKJedfWbfPT0IUOG8MQTT/D444+TlpbGoEGDjtkvcUPs2bOH++67j379+tGrVy/Gjx/P77//Xm2eHTt2cOedd9K7d2/S0tIYPXo033//fbV56hpL4+jp48eP5+abb2blypVcffXVdO3alcGDBzN79mw8Hg/g7eO46vboCRMmnHD/vk6nkzfeeIMrrriCbt26kZaWxhVXXMEnn3xSbb727dvzyiuvMHnyZLp06cKll16Ky+UCYPHixVx++eWkpaVxySWX8M0333DTTTfV+Nw2bNjAxIkTfa1zJk2axMaNG33vP/bYY7z66qsADB069IT6y+7duzfx8fH8/PPP1dZ/ZJcFmqbx6quvctFFF9G1a1fOPfdcHn74YbKzswHvmDRDhw4F4NVXX/X1LV3Vp+7SpUsZMmQI3bp1Y/bs2XWOYVNeXs6UKVPo2bMnffv25ZFHHiEvL8/3fl3LHT29ffv2HDx4kHXr1tWYfnS/xd9//z1jx44lLS3N16/00Sfz7du357///S9vv/02w4YNo0uXLlx++eV888039e7f2r5/Tz75JIsXL+bSSy+la9euXHjhhXzwwQf1rquh6vqOa5rGRx99xLXXXkuPHj3o2rUrF198Mf/97399FUc4vu8b1N5v88UXX8zGjRu54YYb6NatG+eeey7PPfccNputWsx79+7ljjvuoHfv3vTr14/nnnuOhQsX1ttPeVUXEF9++SXl5eU13n/hhRfYvHkzJpPJN81utzNjxgyGDBlCly5dGDp0KDNnzsThcADeVmtV5fjss8+kX2ghhBDiLCR1q5Nbt4K/zxU/+OAD+vTpQ58+fVi5ciUAa9as4ZZbbqFfv3507tyZgQMH8uSTT1a7y+HoMW1mz55N165dycjI4Pbbb6dHjx706dOHRx99lKKiIt9yR4/7UfV6+/btPPjgg/Tp04cePXpw55131jgPLS8v5+mnn+a8886je/fuTJ48md9//73B43OOGDGCnTt38t///peffvqJefPm0b9/f5KTk090d/rk5OTwyCOPcM4559C1a1dGjhzJkiVLqs1zvPW72gQEBKCqKsuXL69Wd6tyzz33sGXLlmpl9Hg8zJs3j4svvpguXbowcOBAnnvuuWrn83XV6Y5HVVfgR9Z5j64bZmVlcc8993DeeefRtWtXLrnkEt58803fd6CuOnjV92fGjBn06NGD/v37s2PHjjrHsNmwYQPXXHONrx74zjvvVHu/ruWOnL5o0SImTJgAwJQpU6pNP7ruUllZyb///W9f3WfIkCG89NJL1brDbsx3QAhRnXSPJoRoUl999RWtW7fm8ccfJz8/v9H9AB8pIyOD0aNHo9frueGGG4iIiGD+/PlMnDiRDz74gLS0NDZu3MiECRMICgpi4sSJWCwWFi9ezF133cWTTz7JuHHjGr3dnTt38o9//IMxY8YwZswYvvzyS1599VUiIiIYN24cw4cPJy8vjwULFjB58mS6du163GUE78nQN998w3XXXcf48eMpKipi4cKF/POf/yQ6OrrabePvvvsuPXv25IknnsBms6HX6/nggw945pln6Nu3L2PGjGHXrl08+OCDBAUFVTspW716NbfffjsdOnTgvvvuw+FwsGjRIsaNG8fbb79N7969GTNmDOXl5SxbtowpU6Yc81b6hmjbti0//fQTDocDo9FY4/05c+bw2muvMW7cON8J+3vvvcfmzZv58ssvSU1NZcqUKUydOpXhw4czfPjwasfUP//5T2644QaCgoLo3r07bre71jhmzJhBy5Ytuffee8nNzeX9999n06ZNfPbZZ5jN5gaXZ9q0aUydOpXw8HAmT55c59g5VZ9Jly5deOCBBygvL+fDDz/kuuuu49133yUtLc0370cffYTH42HcuHGYzWbeffdd7r//flJTU2nXrl2DYwNvZeHbb7/lhhtuICoqigULFvDMM8/QsmXLBnU/0BC1fcdnzJjBnDlzuOqqqxg9ejQVFRV8/vnn/Pvf/8ZisRzze1jf960uhYWF3HzzzYwYMYIrrriClStX8v7772M0GnnkkUcAbwXp+uuvB7xd9lV9X7744ot6y9m6dWt69uzJH3/8wQUXXMCwYcM477zz6NevH1FRUTVa+7ndbm6//Xb++OMPRo8eTWpqKps3b2bOnDls27aN119/nYiICKZNm8Yjjzzi6ydc+oUWQgghRF2kbnX8srOzef3117n77rs5dOgQ3bt3Z9WqVdx666307NmTe++9F0VRWL16NQsWLKCkpISZM2fWuT6Px8OECRPo3bs3jz76KJs2beKTTz7BZrMdczmAO+64g9TUVO6//34yMzN59913OXTokK+Rntvt5pZbbmHTpk1cd911tGrViq+++oq77rqrweV94IEH+Pnnn5kxYwaaptG3b99642qM3NxcRo0ahaZpjB8/ntDQUJYvX87DDz/MoUOHuOWWW4ATr98dKSAggEsuuYQvvviCYcOGMWTIEM477zzOOeccEhISau0S7Z///CeLFy9m5MiR3HTTTezZs4ePPvqIP/74g48++giTydTgOl1DVNXX6rrTxul0csstt2Cz2bjpppsICQnhp59+4qWXXsLtdjN58uRj1sH/+OMPMjMzefjhhzlw4ABt2rSpM5ZJkyYxfPhwrr76ar7//numTp1KWVlZveMGHalPnz5MnjyZOXPmMGbMGHr16lXrfA6Hg4kTJ/Lnn39y9dVX06VLFzZu3Mibb77J+vXree+996rVl+r7DgghapKkjRCiSdlsNv7zn/8QExNzwut65ZVXcLlcLFq0iFatWgFwySWXMHz4cObOncvMmTN57rnnUBSFTz75hNjYWACuu+46rrvuOqZNm8aIESMaXbk5dOgQr7/+uq+V18iRIxk4cCBffPEF48aNo0OHDnTv3p0FCxaccB/KeXl5fPnll9x66608+OCDvunDhg1jxIgR/Pzzz9Uutuv1el577TVfoqGiooIZM2bQp08f3nnnHd8gk61bt+b555/3LefxeHjqqafo2rUr//vf/3zz3XDDDYwcOZLnnnuOzz//nB49etC+fXuWLVvGsGHDaNmy5XGXDbzdpAGUlJQQHR1d4/0vvviCQYMG8cQTT/imxcXF8dFHH3Hw4EGSkpIYNmwYU6dOpX379jX6B7700kv5xz/+4Xtd110LERERLFiwwDeoY7t27Xjsscf4+OOPG3U30ZVXXsnMmTOPOXZOUVER06dPJy0tjQ8++MCXrBo5ciSXXXYZzzzzTLWT0+LiYr777jvf/unWrRujR4/mq6++anTSJjs7m88//9zXB/fw4cMZOHAgS5YsabKkzdHfcafTyf/+9z8uvfRSXnjhBd98o0aNon///vz888/HrODX932rS0lJCU888YTv8xs9erSvUleVtHn11VcpKytjyZIlvuTIlVdeycUXX9ygss6aNYuHH36YNWvWsGjRIhYtWoSiKHTt2pWbbrqJSy+91Dfv4sWLWbNmDW+99RYDBw70TU9LS+PJJ59k+fLlDBs2jCuvvJJHHnnkpPYTLoQQQogzg9Stjp/NZmPq1KlccsklvmnvvPMOcXFxvP32275z9Ouvv54xY8ZUu1OiNi6Xi0suucR3B8XYsWPJzc3l+++/p7KykoCAgDqX7dKlC7Nnz/a9tlqtzJ8/n4yMDJKTk/niiy/YsGEDzz33HKNGjfKt//rrr6e4uLhB5f3hhx+wWq1omkZAQAAvv/wyoaGhDVq2IWbMmIHD4eCLL76gRYsWAIwbN46HHnqImTNnctVVVxEZGXnC9bujPf3007jdbr7++mvfA7yNA6uOTZ3O24nQ2rVrWbRoEU8//TRjx471rWPw4MHcfPPNzJ8/nxtvvLFBdbqGqqrv1vU5bdu2jT179jBz5kxfHWTUqFHccsstpKenAxyzDm61Wpk+fTrdunWrN5brrrvOVw+67rrrmDhxIv/973+54YYbCA8Pb1B5EhMTOffcc5kzZw7du3evc/98+umnbNiwgSlTpnDTTTcB3u9SmzZtmD59OgsXLqxWl6vvOyCEqEm6RxNCNKmkpKQmqVR4PB5++uknBg8e7KtUAISHh/Phhx/yxBNPkJ+fz19//cWVV17pq1QAmEwmbr75Zmw2G7/88kujtx0QEMD5559fbX0pKSnk5+efUJlqEx0dzfr167nzzjt90zRN83V7VlFRUW3+tLS0aneG/Prrr5SVlTFhwgRfIga8J2lBQUG+11u3biUzM5Nhw4ZRUlJCYWEhhYWF2Gw239gcubm5TV6+qnIoilLr+7Gxsaxdu5Z3333Xt3/Hjh3L4sWLSUpKqnf9ffr0aVAc119/vS9hA3DFFVcQGhrKjz/+2KDlG2PNmjVUVlYyceLEancXtWzZkiuuuIJNmzZVG2i1V69e1RJaHTt2BKi1C4D6pKSkVBs0NTo6mqioqCY9do/+jhsMBn755ReeeeaZavMVFRURFBSE1Wo95vpO5Ps2YsSIaq87dOjgW07TNJYvX87AgQOr3c0SExPDFVdcUe+6wbv/3nnnHT755BNuu+02OnfuDHgHCn3ggQd46qmnfPN+9913RERE0LlzZ9/3q7CwkMGDB6Oq6kk51oQQQghxZpO61Ynp3bt3tddvvPEGn376abVz9Iaes0LNc8+OHTvicrnqTazUthzg2wfff/89oaGhXH311b55DAYDEydOrDcmgJdeeokpU6bQtWtX7rzzTiorK3n00UfxeDzs2rWLzz777IS61vN4PHz//ff07t0bvV7vO88tKiriwgsvxOFwsHr1auDE63dHs1gszJgxg6+//pp77rmHHj16oNfr2bVrF8888wx33nmnr7eF7777DkVRGDx4cLXz8U6dOhEdHX1Szsfrq++2aNECRVF44403+Pnnn3E4HCiKwty5c3nxxRfrXb/ZbG7w3WdVdzsB6HQ6brjhBhwOx3F9b+vzww8/EBQUVKORXdWdej/88EO16fV9B4QQNcmdNkKIJhUZGdkk6ykuLsZqtVarVFSpuvvgr7/+ArwXqo9WdZE2Kyur0dsOCwvztdapYjQaq42x0ZSMRiNLlixh1apVZGRksG/fPl+y5sjxQIAaLdv27dsHUGM/GY1GEhMTfa/3798PeLv3mjZtWq1xZGVlNUml8EjFxcWoquprgXS0Rx55hDvuuIPnn3+eqVOn0rlzZ4YMGcLo0aNrvTPnaA093lq3bl3ttaqqJCQkcPDgwQYt3xhVffMevU2oflxWtVA7+jOtqkQez/FWW8vHpj52a9vnBoOBH3/8keXLl5Oens6+ffsoKSkBah7DRzuR71tt+65queLiYoqLi2ttuVXbZ3MsXbt2pWvXrjz44IMUFBTwxRdfMHv2bObPn8/VV19Nt27d2L9/P4WFhfTv37/WdVT14y2EEEII0VBStzoxR+8/VVXJzMxk5syZ7N69m/379zeq4Vpd5+11ddFc5ei7HI5ebt++fbRs2bJaIzxo2Dnr+vXrefPNNxk4cCBvvPEGqqqyY8cOli9fzhtvvEFpaSnz5s1j8eLFx929XlFREWVlZXz//fc1xjeqUnWue6L1u7qkpqZy9913c/fdd1NWVsa3337LzJkzWbFiBUuXLuWSSy5h//79aJpWLUl4pKoxK5tSVcKurn0bGxvLww8/zMsvv8wtt9xCYGAg/fv355JLLmHEiBE1PvOj1fb9qWu+o2Oouh5wsuq8iYmJNbqMrroOcfQ26/sOCCFqkqSNEOK41fYfbH0nHY1dd10tVuDYF4OrKgFHn0TUtZ0jNeSkqKnY7Xauv/56tm3bRr9+/ejfvz833XQTffv2rfVk8+j9W9Wyp7bxYo4cIL1qf9x3331079691lgaeyG7PpqmsX37dlJTU2uND7x3RixdupSff/6ZFStW8PPPPzNr1izefvttFixYUO94Hw39rGo7jjRNq/d4berKZNUxe+Rx2ZTH26k4do/eZ5qmceedd7JixQp69epFjx49GDNmDH369OHGG2+sd30nEvOxlm3od6MuixcvZs+ePTzwwAPVpkdGRnLTTTfRokUL7r//ftavX0+3bt1wu90kJydXu/vmSHUlLoUQQgghQOpWJ8PR+2/u3LlMmzaNlJQUevfuzYUXXki3bt14//33GzTm4bH237HUtw+cTmetCYW66lBHWr58OQB33XWXr7wvvPACV111FbNnzyYwMJDk5ORqd+M3VtXnetFFF1XrduxIVQmCE63fHenHH39k9erVPPzww9X2RXBwMKNGjaJdu3aMHj2a9evXc8kll+DxeLBYLLz66qu1rq8hdYDG2rp1K8Ax9+/NN9/MZZddxrJly/jpp59YvXo1y5cv5/PPP+ett9465vob+htwrGOzvuPveBIn9f1eHP1b4c/fASFOV5K0EULUS6fT4XA4qk1zuVwUFRUd1y3ODREeHo7ZbPbdIXKkuXPnkpeXx8033wzA3r17a8xT1T9s1a39tZUB/H877jfffMPmzZv517/+xbXXXuub3tAWX1X93WZkZFRrFadpGvv37/cNVJiQkABAYGAg5557brV1bNy4kZKSkmrdrjWFX3/9laKiIsaMGVPr+263m+3btxMUFMTQoUMZOnQoAF9//TX3338/H3/8sa/P6BN1dEsfp9PJgQMHfF0mVJ0MH32MHE8XZVX7eu/evTVO3quO1SO7nDjd/f7776xYsYI777yT++67zze9qquII+/4OpUiIyMJDAwkIyOjxntVd6gdy9q1a/n0008ZPXp0rWM7VQ0QWvW9admyJZs3b+acc86pVilxOp0sW7bsjPrMhRBCCHH8pG7lH3a7ndmzZ9OvXz/mzZtXbRD7mTNn+jEyb8Jj06ZNaJpW7eJ7Q85Zqy6eH3lxPyQkhJkzZzJ27FjKysq4//77Tyi+iIgIAgICcLlcNeqSWVlZbN26lYCAgCav323ZsoX33nuP4cOH07dv3xrvH30+npCQwKpVq+jSpUuNBlPffvvtSfl+ffvttwC+MZuOVlxczPbt2+nZsyc33HADN9xwA1arlccee4ylS5eyY8cO2rdvf8JxlJSUUF5eXq2L9KrvbVW5q+ooDoejWhLseL63CQkJ/PnnnzidzmoJGofDUa2eLYQ4fpLqFELUKyoqivT0dGw2m2/aDz/8gN1uP2nb1Ov1DBgwgJ9++qlat0IlJSXMnTuXzMxMoqOj6dKlC0uWLCEnJ8c3j8Ph8A0uOWDAAF8ZCgoKqiVDNm/e3KAT4dpUnfCc6J0YVbdTVyVXqrz33nvA33cL1GXgwIEEBAQwf/78arF888031fot7tKlC9HR0bz//vvVxskpLy/nH//4B1OmTPGd6FeVrb5urY6lvLycF154gcDAwDoHk3e73UyYMIHnn3++2vSqQRar4qiK60T29aJFi6q1IPr4448pKytj2LBhgPf4AO9AkUeqGujySDqd7pixnHvuuZhMJt5+++1qldmcnBy++OIL0tLSmqyri+agrmN44cKFVFZW1nsMnyw6nY4hQ4awcuVKMjMzfdNLSkr48ssv613+8ssvB+C5556r9bduwYIFqKrquyNuyJAhFBcX89FHH1Wbb/78+dx///2sWbOmWmynoksQIYQQQjQ/UreqqanqVsdis9morKwkOTm5WsJm27ZtrFu3Dqi/7nWyDB8+nKKiIr755hvfNI/Hw/z58+td9pxzzgGocQ566NAhX/3n008/pbKy8rjj0+v1DBo0iJ9++ont27dXe++FF17grrvuoqioqMnrd5deeik6nY4XX3yR0tLSGu8vXLgQwJccqkqcvP7669Xm++GHH7jvvvuq3U3VFOfjv/76K19++SXDhw+vtUtmgNWrV3PjjTdWG+MlMDDQ1y1hU9XBPR4Pn3zyie+1y+Xi3Xff9XXHBvi6pzuyzpuTk8OGDRuqrashn8+QIUMoLy/ngw8+qDb9ww8/pKKios4u6oQQDSd32ggh6nXZZZfx7LPPcsstt3DFFVewb98+Fi5c6Luj4GR58MEHGTVqFKNGjWLcuHEEBQWxcOFCrFYr//jHPwB44oknuPHGG7n22mu57rrrsFgsLFmyhC1btvDEE0/4WthcdtllfPnll9x6661cd911FBQU8P7775OcnIzT6Wx0bFX9xX700Ufk5+f7LvA21rnnnoter+eRRx5h3Lhx6PV6VqxYwapVqzAYDNUSLLUJDg7m3nvv5cUXX+Smm27ioosuIiMjg/nz51dr8WIwGHjiiSe4//77ufrqq7n22msxmUx8/PHHZGVl8dJLL/kqL1Vle+uttxg0aJDvJLguv/zyi69iV9WyZsmSJRw6dIiXXnrJN3bL0YxGI+PHj+f111/nrrvuYuDAgdhsNhYsWEBAQADXXHMN8Hc/vsuXLyc+Pp4LL7ywYTv3CAcOHODGG2/ksssuY/fu3Xz44Yf06NGDkSNHApCcnEznzp1ZuHChrwuBZcuWVbvYXyUiIoLt27fz4Ycf0rdv3xrJivDwcB544AGmTp3Kddddx+WXX05FRQUfffQRHo+HJ554otHxN2c9evQgKCiIqVOncvDgQUJDQ1m7di1ff/01JpOp3mP4ZLrvvvv46aefGDNmDOPHj8doNDJ//nzfeDvH6kagf//+TJw4kbfffptLLrmEyy67jMTERMrKyvjhhx9Yt24djz32GPHx8QCMGjWKzz77jGeffZYtW7aQlpbGzp07WbBgAZ07d642sGxERATr1q1j4cKFnHfeeb51CCGEEOLMJ3WrmpqqbnUsoaGhdOvWjUWLFhEUFERKSgq7du3i448/9l0wr6ioIDQ0tMm3XZ+rrrqK+fPn88gjj7BhwwaSk5NZunQpf/75J3Dsc9bBgwczZMgQFi1ahN1up2/fvvz1118sXryYTp060a9fP+bOncukSZN48803q92J0RgPPfQQa9euZdy4cYwbN474+Hh+/PFHVqxYwZgxY3x3vRxv/a62/Z6cnMyUKVN4/vnnGTFiBFdccQWtW7fGZrOxevVqVqxYwfjx4+nZs6dvXwwdOpR58+Zx8OBB+vfvz8GDB/nggw+Ij4/33U0G9dfpjmS1Wlm8eLHvdXl5ORs3buSrr74iMTGRp59+us5lL7jgAlJSUvjnP//Jli1bSEpKYu/evXzwwQf079/ft93G1sGPFhAQwKxZs8jOziYpKYmvv/6aDRs28NRTTxEcHAzAiBEjeOONN7j//vu56aabsNvtfPDBB8TExFTrnaBq/JklS5agaRpXXXVVje1V1X1eeOEFdu7cSZcuXdi8eTOLFi2ie/fujBo1qlHxCyFqkqSNEKJe119/PcXFxXzyySc8++yzdOjQgVdffZV58+ZhtVpP2nZTU1NZsGABL7/8Mm+99RY6nY60tDRefPFF30lhjx49+Oijj5g1axbz5s3D4/HQoUMHXnvtNd9dFOA9WXryySd57733+Ne//kVKSgr/93//x2+//caPP/7Y6Nj69+/PiBEjWLFiBb/++isXXnjhcfWR265dO2bNmsWrr77Kyy+/jMVioW3btrz99tt8+OGHrFu3rsYtx0ebNGkSJpOJ9957j6lTp9KqVStmzJjBs88+W+2254svvpjQ0FBef/11/vOf/6DT6Wjbti2vv/46F1xwgW++Sy+9lO+++45Fixaxbt26ek8Y58yZ4/tbr9cTGRlJr169mDRpEl27dj3msvfeey9hYWF8+umnvPjii6iqSs+ePZk+fbqvv+OAgADuv/9+5s6dy3PPPXdct7U/9dRTfPfdd7zwwguYzWbGjh3LAw88UK2V3axZs3jhhReYP38+er2eIUOG8PjjjzNixIhq67rnnnt46qmneP7557nrrrtqPcGvGvNk3rx5vPzyywQEBNC3b1/uvvvuJrn9vTmJioriv//9Ly+99BKvv/46RqORlJQUXn75ZTZu3Mh7771Hfn6+726mUykpKYn//e9/vPjii7zxxhuYTCZGjhyJqqrMnTu33n7CH3vsMfr27cvChQv59NNPKS4uxmKxkJaWxty5cznvvPN88xqNRt555x1ee+01li5dypIlS2jRogXXXXcdd911FwEBAb55H3roIf7973/z7LPP8uyzz/qSh0IIIYQ480ndqqamqlvVZ+bMmUydOpVPP/0Uh8NBQkICt912G6mpqdxzzz38+uuvXHTRRU2+3foYDAbeeustpk+fzpIlS7Db7QwYMICnn36axx57rN5z1ldeeYX//Oc/LFmyhO+++464uDjuuOMObr31VsxmMyaTid27dxMYGHjcMSYlJbFw4UJmzZrlS/YlJiYyZcoUxo8f75vveOt3/fr1q3W7EyZMoFOnTnzwwQd8/fXXFBYWYjab6dChAy+//DKXXnqpb15FUZg5cyZvvfUWn3/+OT/88AMRERFceOGF3HfffdXqIw2p01UpKirikUce8b0OCAggMTGRm2++mZtvvvmYY1cGBgYyb948Zs2axRdffEF+fj7R0dFcf/313H333b75GlsHP1pISAgvvvgizz//PB988AGtWrVi+vTpXHHFFb55OnTowCuvvMJrr73GtGnTiIuL49Zbb8VmszFt2jTffKmpqYwfP55FixaxadOmWj+bI+s+33zzDUuWLCE2Npbbb7+dO+644/+zd9/xbVX3/8ffV9N7x3HixHH2IIMsQkggEKDsUQqUDQ3wYxRogUJpoYOulNL22xYolF1omWWPQtkjhEyy93CcxEkcj3jJ1ry/PxQ7GNuJnUi6kv16Ph55yOge3ftxdAAdve8554D7XwE4MMM8lPVvAACW8vl8ampqaveD4oQJE3TCCSe0+gAG9CSVlZXKyclpc3fir3/9az377LNaunQpAwoAAABYqvnGoG9+Ln333Xd100036cknn2xZ4upgfXO/HABAfGNPGwBIYLt27dLkyZP18MMPt3r+448/VkNDg8aOHWtRZYD1fvCDH+i0005rtR5zY2OjPvroI40YMYLABgAAAJZ76qmndPjhh7faS0iS3nrrLTkcDo0aNeqQr0FgAwCJhZk2AGLG5/O17CVxIJmZmQecBo6wCy+8UKtWrdJFF12kQYMGaevWrXrmmWeUm5urV199tdWyTEBP8uKLL+quu+7S0UcfreOPP15er1evv/661qxZo3/84x86+uijrS4RAADgoDC26j42bNigs88+W0VFRTr//POVlJSkOXPm6H//+5+uu+66lj2HAAA9B6ENgJiZN2+eLrvssk61feqppzpc1xat1dTU6MEHH9R7772n8vJy5eTk6Nhjj9UPf/jDlk0EgZ7q9ddf11NPPaVNmzbJZrNp9OjRuv7663XEEUdYXRoAAMBBY2zVvSxdulT333+/VqxYocbGRhUXF+uiiy7S+eefb3VpAAALENoAiJmamhqtXLmyU20PO+wwZWZmRrkiAAAAdIbX69WECRMUCARaPZ+SkqKvvvrKoqqAnouxFQAA3RehDQAAAABgv5YvX65zzz1X9957r4qKilqet9ls7KEHAAAARJDD6gIAAAAAAPFtzZo1cjgcOvnkk9kbAwAAAIgiQpsI++qrr2SappxOp9WlAAAAADHh9/tlGIbGjx9vdSmIktWrV2vQoEERC2wYNwEAAKAn6cqYidBGkV2f2TRNseJcZJimKb/fL6fTKcMwrC4HcYS+gY7QN9AR+gbaQ7+IHD7/dn+rV6+W3W7XrFmztHjxYrlcLp188sm6/fbblZaW1uXzMW6KPP6bhvbQL/BN9Am0h36B9tAvIqsrn30JbSStW7dOgUCg3fWZu6r5TrExY8ZErL6eyuPxaPXq1RoyZIhSUlKsLgdxhL6BjtA30BH6BtpDv4ic5cuXW10Cosg0Ta1du1amaeq8887Tddddp+XLl+v+++/Xhg0b9K9//avLYyen0ynTNDV48OAoVd3zNDY2qqSkRIWFhUpOTra6HMQJ+gW+iT6B9tAv0B76RWRt2LCh0+EXoY1YnxkAAAAAOmKaph588EHl5ORo6NChkqTJkycrLy9Pt912mz777DPNmDGjy+f1+/1avXp1pMvt8UpKSqwuAXGIfoFvok+gPfQLtId+ETmdzR4IbRT59ZkBAAAAoLuw2WyaMmVKm+ePPfZYSdLatWsPKrRxOp0aMmTIoZaHvZrvhi0uLuZuWLSgX+Cb6BNoD/0C7aFfRNaGDRs63ZbQRtFZn9nj8USh0p6lsbGx1SPQjL6BjtA30BH6BtpDv4gc0zRZ57ob27Vrlz755BNNnz5dffv2bXm+qalJkpSdnX1Q5zUMg6UJoyA5OZm/V7RBv8A30SfQHvoF2kO/iIyujJd6fGgTjfWZmeYfWUzBQ0foG+gIfQMdoW+gPfSLyGDWevcVDAb1s5/9TNd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C//73v6uuu/HGG5WTk1PtHpXfTz/9dI0YMULr16+vGn/hhRfq6aeflhSYO40dO1bPP/+8Bg4cqJ49e+qGG27Qtm3bqsYXFRVpypQp6tu3r/r376/HH39cY8aMqbpHKFG0QUhULqdS51eY18cHAADNn8Fg0P/93//pyJEjmjlzZq1jvF6vxo0bp3Xr1mnWrFlavny5unXrpvHjx+vbb79V7969q96Ev/76641q2e/WrZs2b95c67m77rpLbdq00RtvvKHXX39dRqNRv//97yUFCjLjxo1TcnKyli1bppUrV+qSSy7RzJkzlZubK0l66qmntGXLFj3//PNatWqVBg4cqClTpmjXrl0aN26cxo0bp7Zt2+qzzz5Tu3bt9Oqrr+qxxx7T73//e7377ru68847tWDBAj3++OPV4nrzzTf1t7/9TXPmzKmxJxCA4PJ73cf9kqfuzYUBAACamx07dujAgQNasWKFpkyZoo0bN+qOO+7QsGHD9M477+i1115Tamqq/vCHP6iioqLWe+zdu1fLli3TrFmz9OabbyouLk45OTl1rkawbt06rV+/Xs8//7xefvllFRYW6uGHH5YUWGLu1ltvVX5+vhYuXKjFixfrm2++0ddffx2yHPwSy6MBAACg2ejQoYP++Mc/6k9/+pMGDx6sc845p9r5zz77TJs2bdI777yjbt26SZIefvhhfffdd1q0aJGeeuqpqv1nUlNTFRsb2+AYEhMT6+xW2bFjh84++2x16NBBFotFjz76qH766Sf5fD45nU6NGTNGo0ePVnx8vCRp0qRJWrhwobZs2aIePXpox44dio+PV6dOnZSYmKjJkyfrrLPOUlJSkuLj42Wz2aotyfbMM8/o9ttv17BhwyQFlpArLS3Vww8/XFUskqTrr79eXbt2bfBrBQAAAIBgmDBhgjp16iRJys3N1YMPPqjrr7++6vyYMWP0u9/9ToWFhWrXrl2N691utx5++GH16NFDknTTTTdp4sSJKigoUOvWrWuM93g8euyxx6rmf6NGjdKsWbMkSV9//bW+/fZbvffeezrppJMkSXPmzNGFF14Y3BddB4o2AAAAaFauvfZarV69Wg888EDVMmWVfvjhByUkJFQVbKRAh07fvn312WefBeX5JSUlNdZsrjRlyhQ9+uijevnll9WvXz+de+65Gj58uIxGo1JTU3X99ddr5cqV+v7777Vjx46qjp3K5cx+97vf6bbbblN2drZ69eqlAQMG6NJLL631eUVFRdq3b5+efPJJPfXUU1XHfT6fXC6Xdu3aJYPBICmwHw8AAAAAREpWVlbVn3v06KGkpCQ9//zz+umnn5Sfn181N/J6vXXeo0uXLlV/rpwjud3uWsemp6dXFWwqx1eO/f7775WUlFRVsKkc37lz54a/sEagaAMAAIBm5y9/+YsuvfRSTZ8+vdrxulrj/X6/zObgvDXetGmTTj311FrPjR49Wpdccok++eQTffnll5o7d66effZZrVixQn6/X9dee61SU1N14YUX6pxzzlHPnj113nnnVV3fu3dvffLJJ/r888/15ZdfasWKFXr22We1cOFCZWdnV3tWZaHn3nvv1dlnn10jltatW1fte9OYjiIAAAAACJZfzkm+/vprjR8/Xueff7769OmjSy+9VE6nUxMnTjzmPaxWa41jdc0BaxtbyWQyVc2nIqFZ7Wnj8/m0aNEiXXzxxerVq5cuu+wyvf3228e85osvvlD37t1rfN16661hihoAAADB1r59e+Xk5Ogf//iH1q1bV3W8e/fuKikp0Q8//FB1zO/3a/369VXLg1V2nzTGxo0b9c033+jSSy+tca6wsFB//vOf5Xa7NWLECM2aNUtvv/22CgoK9PXXX2vlypU6fPiwXnnlFU2YMEGDBg3SkSNHqmKUpLlz52r9+vW66KKL9MADD2j16tXq1KmTVq9eXSP2tLQ0paamaufOncrMzKz62rRpk+bMmdPo1wgAAAAAobR48WL1799fTz/9tMaOHasBAwZo7969kuouwgTTKaecopKSEm3btq3q2KFDh5Sfnx/yZ0vNrNPmqaee0qJFizRp0iT17NlTn3zyiaZOnSqj0ajhw4fXek1ubq7sdrsWLVpU7XhiYmI4QgYAAIhaMeaYJv3Mq6++Wu+//74+++yzqjWPzznnHPXo0UN33323HnzwQaWlpemll17SDz/8oGnTpkmSbDabJGnz5s1KSUmp2l/mf5WUlKigoECS5HA49O233+qJJ55Q//79ddlll9UYn5SUpDVr1mjHjh26++67ZbfbtXz5clksFp1++ukyGAxyOp16//331adPH/30009VnUKVm23u3LlTb7/9th555BFlZGRow4YN2rNnj3r37l0V+5EjR7R9+3Z17NhRv/vd7zR79my1b99eAwcO1JYtW/TQQw/poosuOuYnywAAAABEL4u57l4Mn08yyCSz2SijMXg9G8d6ZrC1a9dOH330kdatW6e2bdtq7dq1VUs+V86NQql///4644wz9Ic//EEPPvigYmNjNWvWLDmdzhP6kF99NZuijdPp1NKlS3XjjTfqlltukSRlZ2dr06ZNevHFF49ZtOnevbvOPPPMMEYLAAAQ3RJjEpXdMfv4A0P07GCpXCatkslk0uLFizVz5kz9/ve/V0VFhU4//XQtWbKk6v1gt27ddN555+nOO+/UXXfdpXHjxtV670cffVSPPvqopEBrfWZmpkaPHq0xY8bIZDLVGG82m7VgwQLNnDlTY8eOldPpVI8ePfT8888rIyNDnTp10qZNmzRjxgyVlpaqQ4cOuvrqq/Xxxx/ru+++03XXXadp06Zp5syZmjp1qg4fPqwOHTronnvu0eWXXy5Juvjii/Xaa6/psssu00svvaRx48YpJiZGL774ombMmKH09HRdc801mjRpUtByDAAAACB8bLFmnZKZWud5n98nj8cjs9ksoyG4hRZbbHjKCZMmTdLBgwd12223SZK6du2qRx99VFOnTtV3331Xbe+aUHn66af15z//WWPHjlVMTIyuv/56/fTTT7JYLCF/tsEfjn6iMPB6vfrxxx+VlpamVq1aVR0fN26cioqKtGLFilqvGz58uPr3768HH3wwKHF89913kqSePXsG5X5NjcPh0Lf532pj6Ub5jHWv+xdjitH5WecrM5lNbxvK4XAoNzdXPXr0qPokMIKLHIceOQ4t8ht6zSXH5eXl2r59uzp37hx1e5p4vV6Vl5crNja21gIITlxDcny835WW/h64KfH5fHrhhRf06quvat++fcrKytLNN99ca3fYL/3tb3/TSy+9pP3796tLly668847q+231FAt8XfG4XCocMdW2Ur3ymI89ic0DSaLYjNPkyW5dZiiaz6ay/9HNwXkOjzIc3iQ5/Agz/V3InM15lInrqioSBs2bNA555xTVaSpqKhQ//79NW3aNF1xxRWSaub6WH9vDXn/22w6bUwmk0455RRJgXXtCgsLtXz5cn3xxRf685//XOs1LperaumIyy+/XNu2bVOrVq10ww03aNy4cY1udfL7/XI4HI1+LU1ZeXm5pMAv8bGKNkazUW63u8Xm6UQ4nc5q3xF85Dj0yHFokd/Qay45drlc8vl88nq98nq9kQ6nmsrPFfn9/qiLrbloSI69Xq98Pp+cTmetG3L6/f6wLBOAE9eYJaVfeOEFzZo1SxMnTtTpp5+uN954Q7fffruWLl2qvn37hvkVAAAAAKFlNps1ZcoUjRo1Stddd53cbrcWLVokq9WqgQMHhv75IX9CBLz77ru6++67JUnnn39+nZ8a++GHH+TxeLR9+3ZNmTJFSUlJ+vjjjzVr1iwVFxdrypQpjXq+2+1Wbm5uo+NvykwmkxQT2JjJUVF3QcZmtemg/aBKd5fyDzGNlJeXF+kQmj1yHHrkOLTIb+g1hxybzWa5XK5Ih1GnaI6tuahPjl0ulzwej3766ac6x7BHTvRrzJLS5eXleuaZZ3TTTTdp4sSJkqSBAwdq1KhRmj9/vl544YWwvgYAAAAg1BITE/Xcc89pzpw5evXVV2U0GvWrX/1KS5cuVWpq3UvTBUuzLNr06tVLL730krZs2aKnnnpKN998s1588cUan/7LysrS888/r549e1YlOzs7W+Xl5Vq0aJFuvvlmJSQkNPj5FotFXbt2DcpraWrKy8v1w/4flJKSoiRjUp3jYs2xSk9PV/v49mGMrnlwOp3Ky8tTVlaW4uLiIh1Os0SOQ48chxb5Db3mkmOXy6U9e/YoJiYm6pZH8/v9crlciomJoYMjRBqaY7PZrIyMDMXExNQ4t3Xr1lCEiCCzWq165ZVXlJaWVu24xWJRSUlJrdds2LBBxcXFGjRoUNUxg8GgQYMG6cknn6xaDgIAAABoTn79619r2bJlEXl2syzaZGRkKCMjQ2eddZbsdrv++Mc/at26dTrrrLOqjUtISKh1Hebzzz9fr7/+urZt21a1IW1DGAyGFr8uo9VqPebyaBaTRRaLpcXn6UTExcWRvxAjx6FHjkOL/IZeU8+x0WiU0WiUyWSKurWOKztxDQZD1MXWXDQkxyaTSUajUXFxcbX+Az2FtaahMUtKb9u2TVLgA2+/lJmZKa/Xqx07dqhbt24hjRsAAABoSZpN0aaoqEiffvqpzj333GqfHDv11FMlSQcOHKhxzffff69vvvlGo0aNktForDpeuS9LOFqdAAAAACDc6rukdGlpqSTJbrdXOx4fH1/tfGO0tL1AK+eZbrdHfoP/mGMNZr9MHo/cLSg/wdJc9p1rCsh1eJDn8CDP4UGe6+9E9h9lf9Dw+d9cH2sv0IbsA9psijbl5eX64x//qLvuuku33npr1fHPP/9cktS9e/ca1/zwww96+OGHlZmZqQEDBlQdX7VqlTp06KCOHTuGPnAAAAAACLP6Lin9v5PN//XLD781VEvbC9RkMikt1qiiQ0XyVhx7LymTNUYJ9oMqLD/AP7Y0UnPYd66pINfhQZ7DgzyHB3m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\n",
      "text/plain": [
       "<Figure size 2000x5000 with 18 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Code From https://www.kaggle.com/gunesevitan/nlp-with-disaster-tweets-eda-cleaning-and-bert\n",
    "METAFEATURES = ['word_count', 'unique_word_count', 'stop_word_count', 'url_count', 'mean_word_length',\n",
    "                'char_count', 'punctuation_count', 'hashtag_count', 'mention_count']\n",
    "\n",
    "DISASTER_TWEETS = train_df['target'] == 1\n",
    "\n",
    "fig, axes = plt.subplots(ncols=2, nrows=len(METAFEATURES), figsize=(20, 50), dpi=100)\n",
    "\n",
    "for i, feature in enumerate(METAFEATURES):\n",
    "    sns.distplot(train_df.loc[~DISASTER_TWEETS][feature], label='Not Disaster', ax=axes[i][0], color='green')\n",
    "    sns.distplot(train_df.loc[DISASTER_TWEETS][feature], label='Disaster', ax=axes[i][0], color='red')\n",
    "\n",
    "    sns.distplot(train_df[feature], label='Training', ax=axes[i][1])\n",
    "    sns.distplot(test_df[feature], label='Test', ax=axes[i][1])\n",
    "    \n",
    "    for j in range(2):\n",
    "        axes[i][j].set_xlabel('')\n",
    "        axes[i][j].tick_params(axis='x', labelsize=12)\n",
    "        axes[i][j].tick_params(axis='y', labelsize=12)\n",
    "        axes[i][j].legend()\n",
    "    \n",
    "    axes[i][0].set_title(f'{feature} Target Distribution in Training Set', fontsize=13)\n",
    "    axes[i][1].set_title(f'{feature} Training & Test Set Distribution', fontsize=13)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preprocessing & Transformations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to clean tweets\n",
    "def clean_tweet(tweet:str) -> str:\n",
    "    \"\"\"\n",
    "    Convert all text to lowercase, remove stock market tickers, RT symbol, hyperlinks and the hastag symbol\n",
    "    :param tweet: tweet by a unique user\n",
    "    :return: cleaned string without hashtags, emojis, and punctuation\n",
    "    \"\"\"\n",
    "    # make text lower case\n",
    "    tweet = tweet.lower()\n",
    "    # remove stock market tickers like $GE\n",
    "    tweet = re.sub(r'\\$\\w*', '', str(tweet))\n",
    "    # remove old style retweet text \"RT\"\n",
    "    tweet = re.sub(r'^RT[\\s]+', '', str(tweet))\n",
    "    # remove hyperlinks\n",
    "    tweet = re.sub(r'https?:\\/\\/.*[\\r\\n]*', '', str(tweet))\n",
    "    # remove hashtags\n",
    "    # only removing the hash # sign from the word\n",
    "    tweet = re.sub(r'#', '', str(tweet))\n",
    "    \n",
    "    # remove punctuation\n",
    "    punct = set(string.punctuation)\n",
    "    tweet = \"\".join(ch for ch in tweet if ch not in punct)\n",
    "    \n",
    "    # remove stopwords\n",
    "    stop_words = set(stopwords.words(\"english\"))\n",
    "    tweet = \" \".join(word for word in tweet.split() if word not in stop_words)\n",
    "    \n",
    "    return tweet\n",
    "\n",
    "def target_relabel(df:pd.DataFrame) -> pd.DataFrame:\n",
    "    \"\"\"\n",
    "    Relabel duplicate tweets that are mislabelled in the training dataset\n",
    "    :param df: A pandas dataframe with a \"target\" column\n",
    "    :return: df\n",
    "    \"\"\"\n",
    "    # manually relabel all mislabelled targets\n",
    "    df.loc[df[\"text\"]==\n",
    "           \"#Allah describes piling up #wealth thinking it would last #forever as the description of the people of #Hellfire in Surah Humaza. #Reflect\",\n",
    "           \"target\"]= 0\n",
    "    df.loc[df[\"text\"]==\n",
    "          \"#foodscare #offers2go #NestleIndia slips into loss after #Magginoodle #ban unsafe and hazardous for #humanconsumption\",\n",
    "          \"target\"] = 0\n",
    "    df.loc[df[\"text\"]==\n",
    "          \".POTUS #StrategicPatience is a strategy for #Genocide; refugees; IDP Internally displaced people; horror; etc. https://t.co/rqWuoy1fm4\",\n",
    "          \"target\"] = 0\n",
    "    df.loc[df[\"text\"]==\n",
    "          \"CLEARED:incident with injury:I-495  inner loop Exit 31 - MD 97/Georgia Ave Silver Spring\",\n",
    "          \"target\"] = 1\n",
    "    df.loc[df[\"text\"]==\n",
    "          \"He came to a land which was engulfed in tribal war and turned it into a land of peace i.e. Madinah. #ProphetMuhammad #islam\",\n",
    "          \"target\"] = 0\n",
    "    df.loc[df[\"text\"]==\n",
    "          \"Hellfire is surrounded by desires so be careful and don‰Ûªt let your desires control you! #Afterlife\",\n",
    "          \"target\"] = 0\n",
    "    df.loc[df[\"text\"]==\n",
    "          \"The Prophet (peace be upon him) said 'Save yourself from Hellfire even if it is by giving half a date in charity.'\",\n",
    "          \"target\"] = 0\n",
    "    df.loc[df[\"text\"]==\"To fight bioterrorism sir.\", \"target\"] = 0\n",
    "    df.loc[df[\"text\"]==\n",
    "          \"that horrible sinking feeling when you‰Ûªve been at home on your phone for a while and you realise its been on 3G this whole time\",\n",
    "          \"target\"] = 0\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# seperate off train and test\n",
    "train = full_df.iloc[:len(train_df), :]\n",
    "test = full_df.iloc[len(train_df):, :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>keyword</th>\n",
       "      <th>location</th>\n",
       "      <th>text</th>\n",
       "      <th>target</th>\n",
       "      <th>text_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Our Deeds are the Reason of this #earthquake M...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>deeds reason earthquake may allah forgive us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Forest fire near La Ronge Sask. Canada</td>\n",
       "      <td>1.0</td>\n",
       "      <td>forest fire near la ronge sask canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All residents asked to 'shelter in place' are ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>residents asked shelter place notified officer...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13,000 people receive #wildfires evacuation or...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13000 people receive wildfires evacuation orde...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Just got sent this photo from Ruby #Alaska as ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>got sent photo ruby alaska smoke wildfires pou...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id keyword location                                               text  \\\n",
       "0   1     NaN      NaN  Our Deeds are the Reason of this #earthquake M...   \n",
       "1   4     NaN      NaN             Forest fire near La Ronge Sask. Canada   \n",
       "2   5     NaN      NaN  All residents asked to 'shelter in place' are ...   \n",
       "3   6     NaN      NaN  13,000 people receive #wildfires evacuation or...   \n",
       "4   7     NaN      NaN  Just got sent this photo from Ruby #Alaska as ...   \n",
       "\n",
       "   target                                         text_clean  \n",
       "0     1.0       deeds reason earthquake may allah forgive us  \n",
       "1     1.0              forest fire near la ronge sask canada  \n",
       "2     1.0  residents asked shelter place notified officer...  \n",
       "3     1.0  13000 people receive wildfires evacuation orde...  \n",
       "4     1.0  got sent photo ruby alaska smoke wildfires pou...  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# clean tweets\n",
    "train[\"text_clean\"] = train[\"text\"].apply(clean_tweet)\n",
    "test[\"text_clean\"] = test[\"text\"].apply(clean_tweet)\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2830</th>\n",
       "      <td>.POTUS #StrategicPatience is a strategy for #G...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2831</th>\n",
       "      <td>.POTUS #StrategicPatience is a strategy for #G...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2832</th>\n",
       "      <td>.POTUS #StrategicPatience is a strategy for #G...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2833</th>\n",
       "      <td>.POTUS #StrategicPatience is a strategy for #G...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   text  target\n",
       "2830  .POTUS #StrategicPatience is a strategy for #G...       0\n",
       "2831  .POTUS #StrategicPatience is a strategy for #G...       0\n",
       "2832  .POTUS #StrategicPatience is a strategy for #G...       0\n",
       "2833  .POTUS #StrategicPatience is a strategy for #G...       0"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# relabel targets in train\n",
    "train_df = target_relabel(train_df)\n",
    "\n",
    "# checking if old different labels are now all the same\n",
    "train_diff_label = train_duplicates.iloc[diff_label_idx].index\n",
    "# will generate new example after each run\n",
    "train_df.loc[train_df[\"text\"] == train_diff_label[np.random.randint(0, len(train_diff_label))], [\"text\", \"target\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# target variable \n",
    "y = train[\"target\"].values\n",
    "\n",
    "# initializing Kfold\n",
    "skf = StratifiedKFold(n_splits=5, shuffle=True, random_state=24)\n",
    "\n",
    "# count vectorizer transformation\n",
    "count_vect = CountVectorizer()\n",
    "count_vect.fit(train[\"text_clean\"].values.tolist() + test[\"text_clean\"].values.tolist())\n",
    "train_count_vect = count_vect.transform(train[\"text_clean\"])\n",
    "\n",
    "# tfidf vectorizer transformation \n",
    "tfidf_vect = TfidfVectorizer()\n",
    "tfidf_vect.fit(train[\"text_clean\"].values.tolist() + test[\"text_clean\"].values.tolist())\n",
    "train_tfidf_vect = tfidf_vect.transform(train[\"text_clean\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# models\n",
    "models= {\n",
    "    \"svm\": SVC(),\n",
    "    \"logistic_regression\": LogisticRegression(),\n",
    "    \"naive_bayes\": MultinomialNB(),\n",
    "    \"SGD\": SGDClassifier(),\n",
    "    \"random_forest\": RandomForestClassifier()\n",
    "}\n",
    "\n",
    "# current vectors\n",
    "vectors = {\n",
    "    \"count_vect\": train_count_vect,\n",
    "    \"tfidf_vect\": train_tfidf_vect\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def stratified_kfold(clf:str, vect_type:str, y, kfold):\n",
    "    \"\"\"\n",
    "    Perform Kfold Cross-Validation\n",
    "    :param model: the model used to make predictions\n",
    "    :param X: the train features being used \n",
    "    :param y: the target feature,\n",
    "    :param kfold: the cross validation strategy\n",
    "    :return: dictionary with model name key and results as the values\n",
    "    \"\"\"\n",
    "    results = {}\n",
    "    # store the name of the model in dictionary\n",
    "    results[\"model_name\"] = clf + \"_\" + vect_type\n",
    "    \n",
    "    # call the model and training data\n",
    "    model = models[clf]\n",
    "    X = vectors[vect_type]\n",
    "    \n",
    "    # perfrom kfold cv\n",
    "    for fold, (train_idx, valid_idx) in enumerate(kfold.split(X, y)):\n",
    "        X_train, X_valid = X[train_idx], X[valid_idx]\n",
    "        y_train, y_valid = y[train_idx], y[valid_idx]\n",
    "        \n",
    "        # train on seen data, predict on unseen\n",
    "        model.fit(X_train, y_train)\n",
    "        y_preds = model.predict(X_valid)\n",
    "        \n",
    "        results[\"fold_{}\".format(fold+1)] = f1_score(y_valid, y_preds)\n",
    "    return results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current Model: svm_count_vect...\n",
      "\n",
      "Current Model: svm_tfidf_vect...\n",
      "\n",
      "Current Model: logistic_regression_count_vect...\n",
      "\n",
      "Current Model: logistic_regression_tfidf_vect...\n",
      "\n",
      "Current Model: naive_bayes_count_vect...\n",
      "\n",
      "Current Model: naive_bayes_tfidf_vect...\n",
      "\n",
      "Current Model: SGD_count_vect...\n",
      "\n",
      "Current Model: SGD_tfidf_vect...\n",
      "\n",
      "Current Model: random_forest_count_vect...\n",
      "\n",
      "Current Model: random_forest_tfidf_vect...\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# store all models\n",
    "all_models = []\n",
    "\n",
    "for clf in models:\n",
    "    for vect in vectors:\n",
    "        all_models.append(stratified_kfold(clf, vect, y, skf))\n",
    "        print(f\"Current Model: {clf}_{vect}...\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>model_name</th>\n",
       "      <th>fold_1</th>\n",
       "      <th>fold_2</th>\n",
       "      <th>fold_3</th>\n",
       "      <th>fold_4</th>\n",
       "      <th>fold_5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>svm_count_vect</td>\n",
       "      <td>0.726481</td>\n",
       "      <td>0.727915</td>\n",
       "      <td>0.747116</td>\n",
       "      <td>0.748252</td>\n",
       "      <td>0.725835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>svm_tfidf_vect</td>\n",
       "      <td>0.711312</td>\n",
       "      <td>0.702304</td>\n",
       "      <td>0.718750</td>\n",
       "      <td>0.724138</td>\n",
       "      <td>0.698994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>logistic_regression_count_vect</td>\n",
       "      <td>0.737531</td>\n",
       "      <td>0.735802</td>\n",
       "      <td>0.750422</td>\n",
       "      <td>0.742998</td>\n",
       "      <td>0.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>logistic_regression_tfidf_vect</td>\n",
       "      <td>0.735371</td>\n",
       "      <td>0.713781</td>\n",
       "      <td>0.736748</td>\n",
       "      <td>0.738707</td>\n",
       "      <td>0.723063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>naive_bayes_count_vect</td>\n",
       "      <td>0.753165</td>\n",
       "      <td>0.736508</td>\n",
       "      <td>0.753036</td>\n",
       "      <td>0.755842</td>\n",
       "      <td>0.741281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>naive_bayes_tfidf_vect</td>\n",
       "      <td>0.737747</td>\n",
       "      <td>0.703030</td>\n",
       "      <td>0.739629</td>\n",
       "      <td>0.739774</td>\n",
       "      <td>0.720070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>SGD_count_vect</td>\n",
       "      <td>0.725567</td>\n",
       "      <td>0.713154</td>\n",
       "      <td>0.735818</td>\n",
       "      <td>0.724638</td>\n",
       "      <td>0.711726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>SGD_tfidf_vect</td>\n",
       "      <td>0.734930</td>\n",
       "      <td>0.727569</td>\n",
       "      <td>0.754371</td>\n",
       "      <td>0.744186</td>\n",
       "      <td>0.738513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>random_forest_count_vect</td>\n",
       "      <td>0.727578</td>\n",
       "      <td>0.726968</td>\n",
       "      <td>0.748528</td>\n",
       "      <td>0.731747</td>\n",
       "      <td>0.715736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>random_forest_tfidf_vect</td>\n",
       "      <td>0.712702</td>\n",
       "      <td>0.710169</td>\n",
       "      <td>0.739655</td>\n",
       "      <td>0.733837</td>\n",
       "      <td>0.711835</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       model_name    fold_1    fold_2    fold_3    fold_4  \\\n",
       "0                  svm_count_vect  0.726481  0.727915  0.747116  0.748252   \n",
       "1                  svm_tfidf_vect  0.711312  0.702304  0.718750  0.724138   \n",
       "2  logistic_regression_count_vect  0.737531  0.735802  0.750422  0.742998   \n",
       "3  logistic_regression_tfidf_vect  0.735371  0.713781  0.736748  0.738707   \n",
       "4          naive_bayes_count_vect  0.753165  0.736508  0.753036  0.755842   \n",
       "5          naive_bayes_tfidf_vect  0.737747  0.703030  0.739629  0.739774   \n",
       "6                  SGD_count_vect  0.725567  0.713154  0.735818  0.724638   \n",
       "7                  SGD_tfidf_vect  0.734930  0.727569  0.754371  0.744186   \n",
       "8        random_forest_count_vect  0.727578  0.726968  0.748528  0.731747   \n",
       "9        random_forest_tfidf_vect  0.712702  0.710169  0.739655  0.733837   \n",
       "\n",
       "     fold_5  \n",
       "0  0.725835  \n",
       "1  0.698994  \n",
       "2  0.750000  \n",
       "3  0.723063  \n",
       "4  0.741281  \n",
       "5  0.720070  \n",
       "6  0.711726  \n",
       "7  0.738513  \n",
       "8  0.715736  \n",
       "9  0.711835  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert to df\n",
    "models_df = pd.DataFrame(all_models)\n",
    "models_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### LightGBM "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# light gbm parameters\n",
    "lgbm_params = {\n",
    "    \"learning_rate\": 0.02, \n",
    "    \"random_state\": 24, \n",
    "    \"metric\": \"auc\",\n",
    "    \"n_estimators\": 2000\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Currently Training: lgbm_count_vect... Fold: 1\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.805416\n",
      "[200]\tvalid_0's auc: 0.825222\n",
      "[300]\tvalid_0's auc: 0.83141\n",
      "[400]\tvalid_0's auc: 0.833187\n",
      "[500]\tvalid_0's auc: 0.833978\n",
      "[600]\tvalid_0's auc: 0.834552\n",
      "[700]\tvalid_0's auc: 0.835404\n",
      "Early stopping, best iteration is:\n",
      "[622]\tvalid_0's auc: 0.835658\n",
      "\n",
      "Currently Training: lgbm_count_vect... Fold: 2\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.815301\n",
      "[200]\tvalid_0's auc: 0.830552\n",
      "[300]\tvalid_0's auc: 0.830014\n",
      "Early stopping, best iteration is:\n",
      "[213]\tvalid_0's auc: 0.831145\n",
      "\n",
      "Currently Training: lgbm_count_vect... Fold: 3\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.823354\n",
      "[200]\tvalid_0's auc: 0.843054\n",
      "[300]\tvalid_0's auc: 0.850541\n",
      "[400]\tvalid_0's auc: 0.850172\n",
      "Early stopping, best iteration is:\n",
      "[313]\tvalid_0's auc: 0.850938\n",
      "\n",
      "Currently Training: lgbm_count_vect... Fold: 4\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.811595\n",
      "[200]\tvalid_0's auc: 0.830556\n",
      "[300]\tvalid_0's auc: 0.837055\n",
      "[400]\tvalid_0's auc: 0.839659\n",
      "[500]\tvalid_0's auc: 0.84043\n",
      "[600]\tvalid_0's auc: 0.840794\n",
      "Early stopping, best iteration is:\n",
      "[548]\tvalid_0's auc: 0.84101\n",
      "\n",
      "Currently Training: lgbm_count_vect... Fold: 5\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.795911\n",
      "[200]\tvalid_0's auc: 0.812582\n",
      "[300]\tvalid_0's auc: 0.818561\n",
      "[400]\tvalid_0's auc: 0.823062\n",
      "[500]\tvalid_0's auc: 0.824283\n",
      "[600]\tvalid_0's auc: 0.824673\n",
      "[700]\tvalid_0's auc: 0.825134\n",
      "[800]\tvalid_0's auc: 0.825663\n",
      "[900]\tvalid_0's auc: 0.826086\n",
      "[1000]\tvalid_0's auc: 0.826048\n",
      "Early stopping, best iteration is:\n",
      "[974]\tvalid_0's auc: 0.826408\n"
     ]
    }
   ],
   "source": [
    "# train then validate lightgbm with count vectors\n",
    "model_dict = {}\n",
    "model_dict[\"model_name\"] = \"lgbm_count_vect\"\n",
    "\n",
    "for fold, (train_idx, valid_idx) in enumerate(skf.split(train_count_vect, y)):\n",
    "    print(f\"\\nCurrently Training: {model_dict['model_name']}... Fold: {fold+1}\")\n",
    "    X_train, X_valid= train_count_vect[train_idx].astype(np.float32), train_count_vect[valid_idx].astype(np.float32)\n",
    "    y_train, y_valid= y[train_idx].astype(np.float32), y[valid_idx].astype(np.float32)\n",
    "\n",
    "    # training\n",
    "    lgbm = lgb.LGBMClassifier(**lgbm_params)\n",
    "    lgbm.fit(X_train,\n",
    "             y_train,\n",
    "             eval_set=[(X_valid, y_valid)],\n",
    "             verbose=100,\n",
    "             early_stopping_rounds=100)\n",
    "\n",
    "    # predictions\n",
    "    y_preds = lgbm.predict(X_valid)\n",
    "    model_dict[\"fold_{}\".format(fold+1)] = f1_score(y_valid, y_preds)\n",
    "\n",
    "\n",
    "# adding results to models df\n",
    "new_model = pd.DataFrame(model_dict, columns=models_df.columns, index=[0])\n",
    "models_df = pd.concat([models_df, new_model], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Currently Training: lgbm_tfidf_vect... Fold: 1\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.802061\n",
      "[200]\tvalid_0's auc: 0.824537\n",
      "[300]\tvalid_0's auc: 0.829379\n",
      "[400]\tvalid_0's auc: 0.829765\n",
      "Early stopping, best iteration is:\n",
      "[316]\tvalid_0's auc: 0.830546\n",
      "\n",
      "Currently Training: lgbm_tfidf_vect... Fold: 2\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.806633\n",
      "[200]\tvalid_0's auc: 0.82151\n",
      "[300]\tvalid_0's auc: 0.825436\n",
      "[400]\tvalid_0's auc: 0.824272\n",
      "Early stopping, best iteration is:\n",
      "[314]\tvalid_0's auc: 0.826033\n",
      "\n",
      "Currently Training: lgbm_tfidf_vect... Fold: 3\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.818616\n",
      "[200]\tvalid_0's auc: 0.834182\n",
      "[300]\tvalid_0's auc: 0.840385\n",
      "[400]\tvalid_0's auc: 0.841885\n",
      "Early stopping, best iteration is:\n",
      "[392]\tvalid_0's auc: 0.842282\n",
      "\n",
      "Currently Training: lgbm_tfidf_vect... Fold: 4\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.814958\n",
      "[200]\tvalid_0's auc: 0.827705\n",
      "[300]\tvalid_0's auc: 0.832143\n",
      "[400]\tvalid_0's auc: 0.832305\n",
      "Early stopping, best iteration is:\n",
      "[371]\tvalid_0's auc: 0.832617\n",
      "\n",
      "Currently Training: lgbm_tfidf_vect... Fold: 5\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.793585\n",
      "[200]\tvalid_0's auc: 0.810687\n",
      "[300]\tvalid_0's auc: 0.81554\n",
      "[400]\tvalid_0's auc: 0.818717\n",
      "[500]\tvalid_0's auc: 0.82001\n",
      "[600]\tvalid_0's auc: 0.81983\n",
      "Early stopping, best iteration is:\n",
      "[530]\tvalid_0's auc: 0.820544\n"
     ]
    }
   ],
   "source": [
    "# train then validate lightgbm with tfidf vectors\n",
    "model_dict = {}\n",
    "model_dict[\"model_name\"] = \"lgbm_tfidf_vect\"\n",
    "\n",
    "for fold, (train_idx, valid_idx) in enumerate(skf.split(train_tfidf_vect, y)):\n",
    "    print(f\"\\nCurrently Training: {model_dict['model_name']}... Fold: {fold+1}\")\n",
    "    X_train, X_valid= train_tfidf_vect[train_idx].astype(np.float32), train_tfidf_vect[valid_idx].astype(np.float32)\n",
    "    y_train, y_valid= y[train_idx].astype(np.float32), y[valid_idx].astype(np.float32)\n",
    "\n",
    "    # training\n",
    "    lgbm = lgb.LGBMClassifier(**lgbm_params)\n",
    "    lgbm.fit(X_train,\n",
    "             y_train,\n",
    "             eval_set=[(X_valid, y_valid)],\n",
    "             verbose=100,\n",
    "             early_stopping_rounds=100)\n",
    "\n",
    "    # predictions\n",
    "    y_preds = lgbm.predict(X_valid)\n",
    "    model_dict[\"fold_{}\".format(fold+1)] = f1_score(y_valid, y_preds)\n",
    "\n",
    "# adding results to models df\n",
    "new_model = pd.DataFrame(model_dict, columns=models_df.columns, index=[0])\n",
    "models_df = pd.concat([models_df, new_model], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>model_name</th>\n",
       "      <th>fold_1</th>\n",
       "      <th>fold_2</th>\n",
       "      <th>fold_3</th>\n",
       "      <th>fold_4</th>\n",
       "      <th>fold_5</th>\n",
       "      <th>avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>svm_count_vect</td>\n",
       "      <td>0.726481</td>\n",
       "      <td>0.727915</td>\n",
       "      <td>0.747116</td>\n",
       "      <td>0.748252</td>\n",
       "      <td>0.725835</td>\n",
       "      <td>73.511976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>svm_tfidf_vect</td>\n",
       "      <td>0.711312</td>\n",
       "      <td>0.702304</td>\n",
       "      <td>0.718750</td>\n",
       "      <td>0.724138</td>\n",
       "      <td>0.698994</td>\n",
       "      <td>71.109958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>logistic_regression_count_vect</td>\n",
       "      <td>0.737531</td>\n",
       "      <td>0.735802</td>\n",
       "      <td>0.750422</td>\n",
       "      <td>0.742998</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>74.335061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>logistic_regression_tfidf_vect</td>\n",
       "      <td>0.735371</td>\n",
       "      <td>0.713781</td>\n",
       "      <td>0.736748</td>\n",
       "      <td>0.738707</td>\n",
       "      <td>0.723063</td>\n",
       "      <td>72.953393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>naive_bayes_count_vect</td>\n",
       "      <td>0.753165</td>\n",
       "      <td>0.736508</td>\n",
       "      <td>0.753036</td>\n",
       "      <td>0.755842</td>\n",
       "      <td>0.741281</td>\n",
       "      <td>74.796648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>naive_bayes_tfidf_vect</td>\n",
       "      <td>0.737747</td>\n",
       "      <td>0.703030</td>\n",
       "      <td>0.739629</td>\n",
       "      <td>0.739774</td>\n",
       "      <td>0.720070</td>\n",
       "      <td>72.805019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>SGD_count_vect</td>\n",
       "      <td>0.725567</td>\n",
       "      <td>0.713154</td>\n",
       "      <td>0.735818</td>\n",
       "      <td>0.724638</td>\n",
       "      <td>0.711726</td>\n",
       "      <td>72.218062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>SGD_tfidf_vect</td>\n",
       "      <td>0.734930</td>\n",
       "      <td>0.727569</td>\n",
       "      <td>0.754371</td>\n",
       "      <td>0.744186</td>\n",
       "      <td>0.738513</td>\n",
       "      <td>73.991390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>random_forest_count_vect</td>\n",
       "      <td>0.727578</td>\n",
       "      <td>0.726968</td>\n",
       "      <td>0.748528</td>\n",
       "      <td>0.731747</td>\n",
       "      <td>0.715736</td>\n",
       "      <td>73.011145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>random_forest_tfidf_vect</td>\n",
       "      <td>0.712702</td>\n",
       "      <td>0.710169</td>\n",
       "      <td>0.739655</td>\n",
       "      <td>0.733837</td>\n",
       "      <td>0.711835</td>\n",
       "      <td>72.163992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>lgbm_count_vect</td>\n",
       "      <td>0.720528</td>\n",
       "      <td>0.682310</td>\n",
       "      <td>0.719586</td>\n",
       "      <td>0.717735</td>\n",
       "      <td>0.711617</td>\n",
       "      <td>71.035515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>lgbm_tfidf_vect</td>\n",
       "      <td>0.695427</td>\n",
       "      <td>0.687225</td>\n",
       "      <td>0.721368</td>\n",
       "      <td>0.711489</td>\n",
       "      <td>0.695580</td>\n",
       "      <td>70.221766</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        model_name    fold_1    fold_2    fold_3    fold_4  \\\n",
       "0                   svm_count_vect  0.726481  0.727915  0.747116  0.748252   \n",
       "1                   svm_tfidf_vect  0.711312  0.702304  0.718750  0.724138   \n",
       "2   logistic_regression_count_vect  0.737531  0.735802  0.750422  0.742998   \n",
       "3   logistic_regression_tfidf_vect  0.735371  0.713781  0.736748  0.738707   \n",
       "4           naive_bayes_count_vect  0.753165  0.736508  0.753036  0.755842   \n",
       "5           naive_bayes_tfidf_vect  0.737747  0.703030  0.739629  0.739774   \n",
       "6                   SGD_count_vect  0.725567  0.713154  0.735818  0.724638   \n",
       "7                   SGD_tfidf_vect  0.734930  0.727569  0.754371  0.744186   \n",
       "8         random_forest_count_vect  0.727578  0.726968  0.748528  0.731747   \n",
       "9         random_forest_tfidf_vect  0.712702  0.710169  0.739655  0.733837   \n",
       "10                 lgbm_count_vect  0.720528  0.682310  0.719586  0.717735   \n",
       "11                 lgbm_tfidf_vect  0.695427  0.687225  0.721368  0.711489   \n",
       "\n",
       "      fold_5        avg  \n",
       "0   0.725835  73.511976  \n",
       "1   0.698994  71.109958  \n",
       "2   0.750000  74.335061  \n",
       "3   0.723063  72.953393  \n",
       "4   0.741281  74.796648  \n",
       "5   0.720070  72.805019  \n",
       "6   0.711726  72.218062  \n",
       "7   0.738513  73.991390  \n",
       "8   0.715736  73.011145  \n",
       "9   0.711835  72.163992  \n",
       "10  0.711617  71.035515  \n",
       "11  0.695580  70.221766  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "models_df[\"avg\"] = 100*(models_df.loc[:, \"fold_1\":\"fold_5\"].sum(axis=1)/5)\n",
    "models_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Word2Vec Embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_word2vec_enc(corpus:list, vocab_size:int, embedding_size:int, gensim_pretrained_emb:str) -> list:\n",
    "    \"\"\"\n",
    "    Get the embeddings value for each word withing\n",
    "    :param corpus: The text we want to get embeddings for\n",
    "    :param vocab_list: The size of the vocabulary\n",
    "    :param embedding_size: The dimensions of the embedding\n",
    "    :param gensim_pretrained_emb: The pretrained embedding from gensim\n",
    "    :return: words encoded as vectors\n",
    "    \"\"\"\n",
    "    word_vecs = api.load(gensim_pretrained_emb)\n",
    "    embedding_weights = np.zeros((vocab_size, embedding_size))\n",
    "    for word, i in corpus:\n",
    "        if word in word_vecs:\n",
    "            embedding_weights[i] = word_vecs[word]\n",
    "    return embedding_weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# lstm configurations\n",
    "n_epochs = 8\n",
    "embedding_size = 300\n",
    "max_length = 202\n",
    "pretrained_embedding_file = \"word2vec-google-news-300\"\n",
    "\n",
    "# tokenizer\n",
    "tokenizer = Tokenizer(oov_token=\"<unk>\")\n",
    "tokenizer.fit_on_texts(train[\"text_clean\"].values)\n",
    "train_tokenized_list = tokenizer.texts_to_sequences(train[\"text_clean\"].values)\n",
    "\n",
    "# store vocab size \n",
    "vocab_size = len(tokenizer.word_index) + 1\n",
    "\n",
    "# padding sequences\n",
    "X_padded = pad_sequences(train_tokenized_list, maxlen=max_length)\n",
    "\n",
    "# get the pretrained word embeddings and prepare embedding layer\n",
    "embedding_matrix = get_word2vec_enc(corpus=tokenizer.word_index.items(),\n",
    "                                    vocab_size=vocab_size,\n",
    "                                    embedding_size=embedding_size,\n",
    "                                    gensim_pretrained_emb=pretrained_embedding_file)\n",
    "\n",
    "embedding_layer = Embedding(input_dim=vocab_size,\n",
    "                            output_dim=embedding_size,\n",
    "                            weights=[embedding_matrix],\n",
    "                            input_length=max_length,\n",
    "                            trainable=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### LSTM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "def my_LSTM(embedding_layer):\n",
    "    print('Creating model...')\n",
    "    model = Sequential()\n",
    "    model.add(embedding_layer)\n",
    "    model.add(Bidirectional(LSTM(units=64, dropout=0.1,  recurrent_dropout=0.1)))\n",
    "    model.add(Dense(50, activation=\"relu\"))\n",
    "    model.add(Dropout(0.1))\n",
    "    model.add(Dense(1, activation = \"sigmoid\"))\n",
    "\n",
    "    print('Compiling...')\n",
    "    model.compile(loss='binary_crossentropy',\n",
    "                  optimizer='adam',\n",
    "                  metrics=[\"accuracy\"])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Currently Training: lstm_word_2_vec... Fold: 1\n",
      "Creating model...\n",
      "Compiling...\n",
      "Epoch 1/8\n",
      "191/191 [==============================] - 78s 385ms/step - loss: 0.5551 - accuracy: 0.7294\n",
      "Epoch 2/8\n",
      "191/191 [==============================] - 76s 397ms/step - loss: 0.4382 - accuracy: 0.8062\n",
      "Epoch 3/8\n",
      "191/191 [==============================] - 76s 397ms/step - loss: 0.4022 - accuracy: 0.8288\n",
      "Epoch 4/8\n",
      "191/191 [==============================] - 76s 395ms/step - loss: 0.3937 - accuracy: 0.8351\n",
      "Epoch 5/8\n",
      "191/191 [==============================] - 76s 396ms/step - loss: 0.3717 - accuracy: 0.8451\n",
      "Epoch 6/8\n",
      "191/191 [==============================] - 76s 396ms/step - loss: 0.3506 - accuracy: 0.8575\n",
      "Epoch 7/8\n",
      "191/191 [==============================] - 77s 402ms/step - loss: 0.3267 - accuracy: 0.8648\n",
      "Epoch 8/8\n",
      "191/191 [==============================] - 77s 402ms/step - loss: 0.3089 - accuracy: 0.8734\n",
      "\n",
      "Currently Training: lstm_word_2_vec... Fold: 2\n",
      "Creating model...\n",
      "Compiling...\n",
      "Epoch 1/8\n",
      "191/191 [==============================] - 86s 431ms/step - loss: 0.5624 - accuracy: 0.7113\n",
      "Epoch 2/8\n",
      "191/191 [==============================] - 86s 449ms/step - loss: 0.4332 - accuracy: 0.8124\n",
      "Epoch 3/8\n",
      "191/191 [==============================] - 89s 464ms/step - loss: 0.4012 - accuracy: 0.8287\n",
      "Epoch 4/8\n",
      "191/191 [==============================] - 94s 491ms/step - loss: 0.3781 - accuracy: 0.8364\n",
      "Epoch 5/8\n",
      "191/191 [==============================] - 89s 466ms/step - loss: 0.3603 - accuracy: 0.8505\n",
      "Epoch 6/8\n",
      "191/191 [==============================] - 89s 466ms/step - loss: 0.3443 - accuracy: 0.8555\n",
      "Epoch 7/8\n",
      "191/191 [==============================] - 90s 469ms/step - loss: 0.3120 - accuracy: 0.8660\n",
      "Epoch 8/8\n",
      "191/191 [==============================] - 91s 478ms/step - loss: 0.2909 - accuracy: 0.8815\n",
      "\n",
      "Currently Training: lstm_word_2_vec... Fold: 3\n",
      "Creating model...\n",
      "Compiling...\n",
      "Epoch 1/8\n",
      "191/191 [==============================] - 99s 493ms/step - loss: 0.5624 - accuracy: 0.7062\n",
      "Epoch 2/8\n",
      "191/191 [==============================] - 94s 492ms/step - loss: 0.4375 - accuracy: 0.8124\n",
      "Epoch 3/8\n",
      "191/191 [==============================] - 94s 493ms/step - loss: 0.4273 - accuracy: 0.8154\n",
      "Epoch 4/8\n",
      "191/191 [==============================] - 95s 498ms/step - loss: 0.4016 - accuracy: 0.8282\n",
      "Epoch 5/8\n",
      "191/191 [==============================] - 96s 504ms/step - loss: 0.3679 - accuracy: 0.8444\n",
      "Epoch 6/8\n",
      "191/191 [==============================] - 96s 502ms/step - loss: 0.3552 - accuracy: 0.8530\n",
      "Epoch 7/8\n",
      "191/191 [==============================] - 97s 506ms/step - loss: 0.3327 - accuracy: 0.8595\n",
      "Epoch 8/8\n",
      "191/191 [==============================] - 97s 506ms/step - loss: 0.3088 - accuracy: 0.8673\n",
      "\n",
      "Currently Training: lstm_word_2_vec... Fold: 4\n",
      "Creating model...\n",
      "Compiling...\n",
      "Epoch 1/8\n",
      "191/191 [==============================] - 95s 475ms/step - loss: 0.5577 - accuracy: 0.7030\n",
      "Epoch 2/8\n",
      "191/191 [==============================] - 90s 472ms/step - loss: 0.4391 - accuracy: 0.8071\n",
      "Epoch 3/8\n",
      "191/191 [==============================] - 92s 479ms/step - loss: 0.4168 - accuracy: 0.8146\n",
      "Epoch 4/8\n",
      "191/191 [==============================] - 91s 478ms/step - loss: 0.3839 - accuracy: 0.8394\n",
      "Epoch 5/8\n",
      "191/191 [==============================] - 92s 480ms/step - loss: 0.3657 - accuracy: 0.8438\n",
      "Epoch 6/8\n",
      "191/191 [==============================] - 93s 485ms/step - loss: 0.3496 - accuracy: 0.8514\n",
      "Epoch 7/8\n",
      "191/191 [==============================] - 99s 517ms/step - loss: 0.3147 - accuracy: 0.8696\n",
      "Epoch 8/8\n",
      "191/191 [==============================] - 94s 493ms/step - loss: 0.2950 - accuracy: 0.8817\n",
      "\n",
      "Currently Training: lstm_word_2_vec... Fold: 5\n",
      "Creating model...\n",
      "Compiling...\n",
      "Epoch 1/8\n",
      "191/191 [==============================] - 98s 490ms/step - loss: 0.5546 - accuracy: 0.7414\n",
      "Epoch 2/8\n",
      "191/191 [==============================] - 95s 499ms/step - loss: 0.4338 - accuracy: 0.8143\n",
      "Epoch 3/8\n",
      "191/191 [==============================] - 96s 504ms/step - loss: 0.4010 - accuracy: 0.8240\n",
      "Epoch 4/8\n",
      "191/191 [==============================] - 97s 507ms/step - loss: 0.3919 - accuracy: 0.8311\n",
      "Epoch 5/8\n",
      "191/191 [==============================] - 97s 507ms/step - loss: 0.3745 - accuracy: 0.8431\n",
      "Epoch 6/8\n",
      "191/191 [==============================] - 220s 1s/step - loss: 0.3620 - accuracy: 0.8447\n",
      "Epoch 7/8\n",
      "191/191 [==============================] - 99s 519ms/step - loss: 0.3366 - accuracy: 0.8571\n",
      "Epoch 8/8\n",
      "191/191 [==============================] - 100s 523ms/step - loss: 0.3122 - accuracy: 0.8722\n"
     ]
    }
   ],
   "source": [
    "# stratified kfold with LSTM \n",
    "model_dict = {}\n",
    "model_dict[\"model_name\"] = \"lstm_word_2_vec\"\n",
    "\n",
    "for fold, (train_idx, val_idx) in enumerate(skf.split(X=X_padded, y=y)):\n",
    "    print(f\"\\nCurrently Training: {model_dict['model_name']}... Fold: {fold+1}\")\n",
    "    X_train, X_val = X_padded[train_idx], X_padded[val_idx]\n",
    "    y_train, y_val = y[train_idx], y[val_idx]\n",
    "     \n",
    "    # train the model\n",
    "    clf = my_LSTM(embedding_layer)\n",
    "    clf.fit(X_train,\n",
    "            y_train,\n",
    "            epochs=n_epochs,\n",
    "            verbose=1)\n",
    "    # make predictions\n",
    "    y_preds = clf.predict_classes(X_val, verbose=-1)\n",
    "    model_dict[\"fold_{}\".format(fold+1)] = f1_score(y_val, y_preds)\n",
    "        \n",
    "# adding results to models df\n",
    "new_model = pd.DataFrame(model_dict, columns=models_df.columns, index=[0])\n",
    "models_df = pd.concat([models_df, new_model], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Currently Training: lgbm_word_2_vec... Fold: 1\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.682487\n",
      "[200]\tvalid_0's auc: 0.691179\n",
      "[300]\tvalid_0's auc: 0.69598\n",
      "[400]\tvalid_0's auc: 0.698711\n",
      "[500]\tvalid_0's auc: 0.698148\n",
      "Early stopping, best iteration is:\n",
      "[446]\tvalid_0's auc: 0.699143\n",
      "\n",
      "Currently Training: lgbm_word_2_vec... Fold: 2\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.652833\n",
      "[200]\tvalid_0's auc: 0.662344\n",
      "[300]\tvalid_0's auc: 0.669086\n",
      "[400]\tvalid_0's auc: 0.673721\n",
      "[500]\tvalid_0's auc: 0.673499\n",
      "Early stopping, best iteration is:\n",
      "[400]\tvalid_0's auc: 0.673721\n",
      "\n",
      "Currently Training: lgbm_word_2_vec... Fold: 3\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.695932\n",
      "[200]\tvalid_0's auc: 0.708832\n",
      "[300]\tvalid_0's auc: 0.715208\n",
      "[400]\tvalid_0's auc: 0.716586\n",
      "Early stopping, best iteration is:\n",
      "[376]\tvalid_0's auc: 0.717966\n",
      "\n",
      "Currently Training: lgbm_word_2_vec... Fold: 4\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.687578\n",
      "[200]\tvalid_0's auc: 0.69591\n",
      "[300]\tvalid_0's auc: 0.699045\n",
      "[400]\tvalid_0's auc: 0.700947\n",
      "[500]\tvalid_0's auc: 0.702226\n",
      "[600]\tvalid_0's auc: 0.702575\n",
      "Early stopping, best iteration is:\n",
      "[549]\tvalid_0's auc: 0.703316\n",
      "\n",
      "Currently Training: lgbm_word_2_vec... Fold: 5\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's auc: 0.674138\n",
      "[200]\tvalid_0's auc: 0.68321\n",
      "[300]\tvalid_0's auc: 0.689375\n",
      "[400]\tvalid_0's auc: 0.691183\n",
      "[500]\tvalid_0's auc: 0.691927\n",
      "[600]\tvalid_0's auc: 0.696046\n",
      "[700]\tvalid_0's auc: 0.696008\n",
      "Early stopping, best iteration is:\n",
      "[605]\tvalid_0's auc: 0.696381\n"
     ]
    }
   ],
   "source": [
    "# train then validate lightgbm with word2vec vectors\n",
    "model_dict = {}\n",
    "model_dict[\"model_name\"] = \"lgbm_word_2_vec\"\n",
    "\n",
    "for fold, (train_idx, valid_idx) in enumerate(skf.split(X_padded, y)):\n",
    "    print(f\"\\nCurrently Training: {model_dict['model_name']}... Fold: {fold+1}\")\n",
    "    X_train, X_valid= X_padded[train_idx].astype(np.float32), X_padded[valid_idx].astype(np.float32)\n",
    "    y_train, y_valid= y[train_idx].astype(np.float32), y[valid_idx].astype(np.float32)\n",
    "\n",
    "    # training\n",
    "    lgbm = lgb.LGBMClassifier(**lgbm_params)\n",
    "    lgbm.fit(X_train,\n",
    "             y_train,\n",
    "             eval_set=[(X_valid, y_valid)],\n",
    "             verbose=100,\n",
    "             early_stopping_rounds=100)\n",
    "\n",
    "    # predictions\n",
    "    y_preds = lgbm.predict(X_valid)\n",
    "    model_dict[\"fold_{}\".format(fold+1)] = f1_score(y_valid, y_preds)\n",
    "\n",
    "# adding results to models df\n",
    "new_model = pd.DataFrame(model_dict, columns=models_df.columns, index=[0])\n",
    "models_df = pd.concat([models_df, new_model], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>model_name</th>\n",
       "      <th>fold_1</th>\n",
       "      <th>fold_2</th>\n",
       "      <th>fold_3</th>\n",
       "      <th>fold_4</th>\n",
       "      <th>fold_5</th>\n",
       "      <th>avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>svm_count_vect</td>\n",
       "      <td>0.726481</td>\n",
       "      <td>0.727915</td>\n",
       "      <td>0.747116</td>\n",
       "      <td>0.748252</td>\n",
       "      <td>0.725835</td>\n",
       "      <td>73.511976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>svm_tfidf_vect</td>\n",
       "      <td>0.711312</td>\n",
       "      <td>0.702304</td>\n",
       "      <td>0.718750</td>\n",
       "      <td>0.724138</td>\n",
       "      <td>0.698994</td>\n",
       "      <td>71.109958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>logistic_regression_count_vect</td>\n",
       "      <td>0.737531</td>\n",
       "      <td>0.735802</td>\n",
       "      <td>0.750422</td>\n",
       "      <td>0.742998</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>74.335061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>logistic_regression_tfidf_vect</td>\n",
       "      <td>0.735371</td>\n",
       "      <td>0.713781</td>\n",
       "      <td>0.736748</td>\n",
       "      <td>0.738707</td>\n",
       "      <td>0.723063</td>\n",
       "      <td>72.953393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>naive_bayes_count_vect</td>\n",
       "      <td>0.753165</td>\n",
       "      <td>0.736508</td>\n",
       "      <td>0.753036</td>\n",
       "      <td>0.755842</td>\n",
       "      <td>0.741281</td>\n",
       "      <td>74.796648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>naive_bayes_tfidf_vect</td>\n",
       "      <td>0.737747</td>\n",
       "      <td>0.703030</td>\n",
       "      <td>0.739629</td>\n",
       "      <td>0.739774</td>\n",
       "      <td>0.720070</td>\n",
       "      <td>72.805019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>SGD_count_vect</td>\n",
       "      <td>0.725567</td>\n",
       "      <td>0.713154</td>\n",
       "      <td>0.735818</td>\n",
       "      <td>0.724638</td>\n",
       "      <td>0.711726</td>\n",
       "      <td>72.218062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>SGD_tfidf_vect</td>\n",
       "      <td>0.734930</td>\n",
       "      <td>0.727569</td>\n",
       "      <td>0.754371</td>\n",
       "      <td>0.744186</td>\n",
       "      <td>0.738513</td>\n",
       "      <td>73.991390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>random_forest_count_vect</td>\n",
       "      <td>0.727578</td>\n",
       "      <td>0.726968</td>\n",
       "      <td>0.748528</td>\n",
       "      <td>0.731747</td>\n",
       "      <td>0.715736</td>\n",
       "      <td>73.011145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>random_forest_tfidf_vect</td>\n",
       "      <td>0.712702</td>\n",
       "      <td>0.710169</td>\n",
       "      <td>0.739655</td>\n",
       "      <td>0.733837</td>\n",
       "      <td>0.711835</td>\n",
       "      <td>72.163992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>lgbm_count_vect</td>\n",
       "      <td>0.720528</td>\n",
       "      <td>0.682310</td>\n",
       "      <td>0.719586</td>\n",
       "      <td>0.717735</td>\n",
       "      <td>0.711617</td>\n",
       "      <td>71.035515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>lgbm_tfidf_vect</td>\n",
       "      <td>0.695427</td>\n",
       "      <td>0.687225</td>\n",
       "      <td>0.721368</td>\n",
       "      <td>0.711489</td>\n",
       "      <td>0.695580</td>\n",
       "      <td>70.221766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>lstm_word_2_vec</td>\n",
       "      <td>0.752506</td>\n",
       "      <td>0.735000</td>\n",
       "      <td>0.749565</td>\n",
       "      <td>0.759839</td>\n",
       "      <td>0.755880</td>\n",
       "      <td>75.055806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>lgbm_word_2_vec</td>\n",
       "      <td>0.564236</td>\n",
       "      <td>0.520354</td>\n",
       "      <td>0.551978</td>\n",
       "      <td>0.534283</td>\n",
       "      <td>0.547515</td>\n",
       "      <td>54.367329</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        model_name    fold_1    fold_2    fold_3    fold_4  \\\n",
       "0                   svm_count_vect  0.726481  0.727915  0.747116  0.748252   \n",
       "1                   svm_tfidf_vect  0.711312  0.702304  0.718750  0.724138   \n",
       "2   logistic_regression_count_vect  0.737531  0.735802  0.750422  0.742998   \n",
       "3   logistic_regression_tfidf_vect  0.735371  0.713781  0.736748  0.738707   \n",
       "4           naive_bayes_count_vect  0.753165  0.736508  0.753036  0.755842   \n",
       "5           naive_bayes_tfidf_vect  0.737747  0.703030  0.739629  0.739774   \n",
       "6                   SGD_count_vect  0.725567  0.713154  0.735818  0.724638   \n",
       "7                   SGD_tfidf_vect  0.734930  0.727569  0.754371  0.744186   \n",
       "8         random_forest_count_vect  0.727578  0.726968  0.748528  0.731747   \n",
       "9         random_forest_tfidf_vect  0.712702  0.710169  0.739655  0.733837   \n",
       "10                 lgbm_count_vect  0.720528  0.682310  0.719586  0.717735   \n",
       "11                 lgbm_tfidf_vect  0.695427  0.687225  0.721368  0.711489   \n",
       "12                 lstm_word_2_vec  0.752506  0.735000  0.749565  0.759839   \n",
       "13                 lgbm_word_2_vec  0.564236  0.520354  0.551978  0.534283   \n",
       "\n",
       "      fold_5        avg  \n",
       "0   0.725835  73.511976  \n",
       "1   0.698994  71.109958  \n",
       "2   0.750000  74.335061  \n",
       "3   0.723063  72.953393  \n",
       "4   0.741281  74.796648  \n",
       "5   0.720070  72.805019  \n",
       "6   0.711726  72.218062  \n",
       "7   0.738513  73.991390  \n",
       "8   0.715736  73.011145  \n",
       "9   0.711835  72.163992  \n",
       "10  0.711617  71.035515  \n",
       "11  0.695580  70.221766  \n",
       "12  0.755880  75.055806  \n",
       "13  0.547515  54.367329  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "models_df[\"avg\"] = 100*(models_df.loc[:, \"fold_1\":\"fold_5\"].sum(axis=1)/5)\n",
    "models_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Sws9+9jNmzpzJG2+8kTbrAD63+Jg1axaVlZXs2LGDN998kxtvvJFTTjmFrVu3pgV2RUUFBQUFnHHGGTidTrxeL48++ih+v5/jjjuOV199NS3sLr30UhYuXIjf7+evf/0rANdeey1XXHEFWVlZbN68mV27dgHJCNbQlEGBQCAQCEYLIZoEgmOEOXPmpEWTwWBI21KPhMvl4te//jXXXnstfr+fFStWsGLFivT7er2e++67L90RqyzL3HvvvXznO98hGo3y8ssvpyNMs2bNYvv27Rm1LQB33XUX3/jGN+jt7eW1117jtddeS79nsVi4++67R7RDHw1KS0u5+eabuffeewkGg2n3vwHmzJnDZZdd9oW3U1FRwd13383tt99OLBbjySefzHjfZrPx0EMPDatDGm0uvvhiHnnkEQD+9re/8be//Q1IXucBq/GOjg7Gjh17wOuWJIlf/vKXXHHFFfj9fl566SVeeuml9Ps2m4177703Pf7zn/+c66+/nlgslu6EeICxY8dy7bXXAnDmmWdywQUXsGLFCpqbmzMcHiH5mbztttsOeH8FAoFAIPg8iPQ8geAYYWg63rRp0/b5BH7BggWsWLGCpUuXUlpaisFgIDs7m3POOYdnn312WB3SvHnz+Nvf/sb8+fMxmUzk5ubyX//1X/z5z38esa5mzJgxvPDCC3z961+nsLAQvV5Pfn4+55xzDk8//fQhdz/79re/zWOPPcaCBQtwOp0Yjcb0Tfpjjz2GyWQ6KNu58MILWb58OYsXL8447osvvpgXXnhhrxHA0eLqq6/mxhtvZMyYMRiNRsrKyli8eDFPPfVUWri+9dZbn3v906ZN47nnnuPCCy8kNzcXg8FAaWkpX/3qV1m+fHmGNfhZZ53FU089xaJFi3C73RgMBsrLy7niiiv429/+lk4dHBBj9913H7NnzyYnJwedTkdOTg5nnHEGf/3rX/nKV77yxU6MQCAQCAT7iaSNZJkkEAgEAoFAIBAIBAJARJoEAoFAIBAIBAKBYK8I0SQQCAQCgUAgEAgEe0GIJoFAIBAIBAKBQCDYC8e0e56qqgQCAfR6/SFz6RIIBAKBQCD4PGiaRiwWw2q1jmrfbQKB4MA5pkVTIBBg27Zth3s3BAKBQCAQCPabCRMmYLfbD/duCASCIRzTokmv1wPJH5/R7gBxy5YtTJkyZVS3ITjyENf9y4u49l9exLX/8jLa1z4ajbJt27b0/YtAIDhyOKZF00BKnsFgwGg0jvr2DsU2BEce4rp/eRHX/suLuPZfXg7FtRclBQLBkYdImBUIBAKBQCAQCASCvSBEk0AgEAgEAoFAIBDsBSGaBAKBQCAQCAQCgWAvHNM1TQKBQCAQCASCAycWi9Hc3Ew4HD7cuyIQHBJMJhMlJSV7NGIRokkgEAgEAoFAkEFzczN2u50xY8YIYwrBMY+mafT09NDc3ExFRcWIbUR6nkAgEAgEAoEgg3A4THZ2thBMgi8FkiSRnZ2918iqEE0CgUAgEAgEgmEIwST4MrGvz7sQTQKBQCAQCAQCgUCwF4RoEggEAoFAIBAIvgDNzc1MnDiRb37zm8Peu/XWW5k4cSK9vb37vb7/+Z//Yfny5Xtts2bNGs4777wD3lfB50OIJoFAIBAIBAKB4AtiNBqpr6+npaUlPS8YDLJ+/frDuFeCg4UQTQKBQCAQCAQCwRdEURTOOeccVq5cmZ73+uuvs2jRovT0008/zXnnnccFF1zAf/3Xf7Fr1y4AOjo6uOKKKzj33HP57//+b7q6utLL7Nixg//6r/9i8eLFXHjhhTz77LPDtr1u3Tr+8z//k8WLF7N48WJee+21UTzSLydCNAkEAoFAIBAIBAeBr371q6xYsSI9/cILL3DRRRcBsHr1apYtW8YTTzzBihUrOO+887j66qvRNI2f/exnTJ8+nX/961/ccccdaTEVj8e57rrruPHGG1m+fDlPPvkkjz/+OJs2bcrY7sMPP8wVV1zB8uXLuffee1m9evUhO+YvC6KfJoFAIBAIBAKB4CAwZcoUZFlmy5YtZGdnEwgEmDBhAgDvvfce//Ef/0FWVhYAixcv5p577qG5uZkPP/yQH/7whwCUl5czf/58AOrr62lsbOS2225LbyMcDvPZZ59RWVmZnnfOOefws5/9jLfeeosFCxZwww03HKpD/tIgRJNAIBAIBAKBQHCQuOCCC1ixYgVZWVlceOGF6fmyPDzBS9M04vE4kiShaVp6vk6XvEVPJBI4HA5efPHF9Hvd3d3Y7faMaNOSJUtYuHAhH3zwAe+99x6///3vWbFiBXa7fRSO8MuJSM8TCAQCgUAgEAgOEhdeeCGvvvoqL7/8coa73UknncTLL7+cdtF77rnncLlclJeXc/LJJ/P0008D0Nraypo1awCoqKjAaDSmRVNbWxvnnXceW7ZsydjmkiVLqK6uZvHixdx99934fD68Xu+hONwvDSLSJBAIBAKBQCAQHCTy8/OprKzEbrfjcrnS8+fPn8/ll1/Ot7/9bVRVJSsriz/96U/IssxPf/pTbr31Vs455xwKCgqoqqoCwGAw8Mgjj3DPPfewbNky4vE4119/PbNnz04LK4CbbrqJe++9l9/+9rfIssw111xDSUnJoT70YxpJGxoLPMaIRCJs2bKFKVOmYDQaR3Vb69evZ/bs2aO6DcGRh7juX17Etf9yoGkafWEvnf5uOvzddAS6aWxpZExJOSadCYvehElnwqw3YtYNGdebMeuM6BX94T4EwUFktL/3h/K+ZV9UV1czadKkw7oPAsGhZm+fexFpEggEAsGXmmg8Smegh45ANx3+rrQ46vR30xnoJpqIpdtKSCiSzFrP5v1atyIrmHUmzLpBIWXSm5ICS2/EojOlp816425CzJRub9GZMOqMSJI0WqdBIBAIBHtBiCaBQCAQHNNomoY37EuJopQwSomiDn83feHMvH+Tzki+NYdCex4zCo8j35pDvi2HPFsOuZYsPt30KdNnziAcDxOORQjGQoTjEULxMKFYmHB8yLxYmNBAu3iYcCyMPxqgO9CbbJ96T2PfSR8SEiadEVMqqmVOCStTSlyZUwIsKbqMg+/rhsxLCzYTOlkZrVMuEAgExxxCNAkEAoHgqCeaiNE5RAgNiqKkQNo9WpRldpFvy2F64eS0KMq35ZJvzcFutO0zoqOTFWwGKzaD9Qvvu6qpRONRQinhFY6FCcbChONhQrHUvHhqXiyc0S4UC+OL+Aen4xHiany/tqtX9Blia6Ro2B6jXwPzUu0Mil5EwQQCwTGNEE0CgUAgOOLRNA1vpD9DFHX4u+hMRY96Q56M9kbFkBRB9jymFUxOiaIc8q055FizMRxBtUayJGNKCRA3zi+8vlgiRigeSYmopPBKi65UNCwUj+wmxJIRMm/YR/vAcvEIkXhk/49hSCQrU3gNpiMOnTYPi34ZsejMmHTGEa2ZBQKB4HAiRJNAIBAIjghiiRhd6dqi3SJGge5hN/AD0aKp+VXpKNFAGp3TaP/SRj70ih69osdhtH3hdamqSjiRmWY4kIYYGiK2MtMQQ+l2npA3GRmLhQjFI6iaul/bNSqGIdEvU2Y0bEB4DUS/BtoMtBtizGHWm4QZh0AgOCgI0SQQCASCQ4KmafRH/CMaLgxEi4bW9hgUfUoI5TIlf2KGKMqz5hxR0aJjFVmWschmLHrzF16XpmmpKFgqxTA2UAM2GBEbFF+DaYgDbXqDfRkRtKEpl3tjqBnHnqNfRsw6czod0TxCuqJFZ/rC50AgEBy9CNEkEAgEgoNGPBGnM9izx9qi8G7RIrfJSb4th+PyJ6QF0kAandPk2O9okaZpxOMqsWiCeCxBLJYgFlOT49HkdHzovNT8eEwd8l5qOqP9YJuBebKisW3TWgqKnRQUOSgoduLKMn9pI1v7iyRJGHQGDDrDQUhChISaGB79GmLGMXR6aLtw/PObcZyddzKzEV0NCARfRoRoEggEAsF+o2ka/dFAKmWuK51GN1Bb1BPsy7j51Mt6ci3Z5JiyqMgfQ5YhC5fOhUNxYpccSAl5UJR0JYi3JWiORqmPNWcIlVhsUBCNJIri8f1L+xqGBHq9gk4nozcoyXH9wFDGZNajN2TOa2psw9MTpK66k4GeDo0mHQXFjgwhlZNvQ1FEbc5ooRxEMw5N04gkosMjXUPSEKOJKNY+Ed0UCL6sCNEkEAgEB0AsFmPHjh3U19djNBpxuVw4nU5stn07rh1uNE0jkVAzoikjiZJINEpPqI/ucC+90V76oh48CQ++hJd+fMSIZqzXkDBhilkxRm0URfLQh8woQTO6kBldzIiEhAp0A92oQG/qNTKyLA0RKnJayOj0CkaTHpvdmHzPkHx/UNDsYZ5ezhA+A+JHr1dQdPIBX7f168PMnj2bWCxBZ5uP9pbUq9XLhtWNxKIJABRFJq/QTn6RIymoipzkFzkwmsRf75GGJKXs3HXGvZpxrF+//hDuleBYY+nSpfz1r38d9e08/fTTWK1WzjvvvFHf1pcJ8cstEAgE+yCRSFBfX09NTQ07duwgFkvWUtTX16fbKIqCw+FIi6iB18C0wWAYcd2aqo2YApYWMfHEkBSzIallQ9LLhs6Lx3ZPUctcNxpoaCSUGDFTkKhxt5cpSMwQgiE6QlJlDFELpqiV7EQploQNq+bAITmwSQ7MemNSlFgV9K5BUTJUpCRFizwskrN7dEevl5GPkuiMXq9QXOamuMydnqeqGr1dAdpbvLS3+mhv8bJtaweb1jal22TlWCgodqbElJOCYgd2h6iXERy5vLWukX+vbRyVdZ85r4zT55SNyrqPNNauXXtItrNx40bmzZt3SLb1ZUKIpi+IpmqseX8XHZ1BxpT5ycqxHvFPmwUCwb7RNI3m5mZqamrYtm0b4XAYk8nExIlV5OWU0rizi5zcHPx+H4Ggn2DITzgcoK2lm4b6JlQts68cCR2SZgTVgJrQo8Z0xKPJl5bQkaFS9gNJYsToyUC0xWTVEdUHCRvChBQ/YbmfIP30a158qpeIlllbZNPZyDVlkWMuI8+aTb4thwJ7HkXOPHJsLhRFdIS6P8iyRE6+jZx8G1NmFQOplEZfOB2R6mj10tbs5bNP2tLLWe3GVFpfMiJVUOIgK9uKJIv/E4Ggvb2dm266iWAwiCzLnHbaaWzevJk//elPADz55JPU19czefJk3nnnHTo7O2lvb+fb3/42ra2trF69GpfLxbJlyzAajXvczsqVK3n00UeRJImpU6dy9913E4/HueOOO6itrUWSJL7zne/w1a9+leXLl7N27Vp++ctfAsko0jXXXAPAn/70J0wmEzt27GDixIn86le/4v777wfga1/7Gv/85z9H3P6bb77JM888M+y4br31Vu6//37Wrl1LIpFg8eLFXH755Wiaxq9+9SveeOMNFEXh61//OuPHj+ett95i9erV5ObmcvLJJx+06/BlR4imL0g4HGPluneI9ctsWNODzWSmuMxFcbk7OSxzYbaM/IRZIBAcWWiaRkdHBzU1NdTW1uL3+9HpdORmF6N3Z+Pr0rHurX4S8R2pJXxDltahKG50+mx0Bhm9HmR9HFmJIikxNCmKSpiEGkJNeJANGgYrGEimBhkNFsxmG1aLHZvVht3uwOFw4nS5sFrNGSlner2CrEgEYsG0HfdAbVFLqs6oO9g3aO+sgg4dedZsSmy55FknZRgu5FmzMelFpGO0kCQJh9OMw2lmwuT89PxwKEZHqy8dkepo8fHRqp2oiWShlN6gJKNRQyJSeQV2dHohYAWHltPnHN5o0LPPPstpp53Gd7/7XdasWcPmzZvZunUrXq8Xp9PJSy+9xG233UZdXR2bN29m5cqVeL1eTj/9dJYtW8btt9/O0qVLee+99zjjjDNG3EZHRwe/+MUvWL58OQUFBdx8882sWrWKDRs24Ha7eemll+jt7eVrX/saVVVVe93fjRs38sorr5CXl8cll1zC+++/zx133MFf//rXPQomgFNOOYWf/vSnw47rmWeeAeD5558nGo3yne98hylTptDV1cWGDRtYuXIlsViMSy+9lGXLlnH66aczb948IZgOMkI0fUFUXZyWMVsIxkJISLjIorXfzbp1Nixvu9FHzeTk2igpd1Nc7qK4zE1+of2oST8RCL4M9PT0UFNTQ3V1DV6vJyliFDcES/F6TXgbZXS6EIUlTuaeOIbiMhddvY3MmDEtI71M3s+ogKqq9Pf34/F48Hq9eL3e9Hh3bzPNrWEgmUYXUeJoFgmsCgmTRkQXJ0AIT6yfUCKcsV6H0Ua+NYcJ2WM5qTwnbdGdb8vFbXYiS+J350jCZNZTXplNeWV2el48nqC7w5+ukWpv8fHp+hbWfdgAgCRL5ObZ0qYT+cVJUSUezgmOZU444QSuvfZaqqurOfXUU1m6dCmtra28/vrrLFiwAI/Hw7Rp06irq2PWrFnYbDZsNlt6WYDi4mJ8Pt8et7Fx40ZmzZpFQUEBAA888AAAjzzyCPfeey8AWVlZLFq0iLVr16bXPxLjx49Pr6eyshKv17tfx6nX6znrrLOGHdeyZcuorq5m9erVAASDQWpra9mxYwfnnHMOBoMBg8HAiy++uF/bEXw+DqloGgh7xmIxLr/8cr75zW+m36uuruZHP/pRerq3tzetsl944QV+9atfkZ2d/GM57bTT+MEPfnAod32PWA0WHjnvHl5e8zqqW6G2ewfbdbsI25OpL1bJiieWy65OO7pqO6agE4NOR1FpMgpVkopIOVxfvA8MgUCw/3g9Xtat+5S67dvwBz2gQSJqIR7KJx6yY8p1Mm6cK/2wI6/QnuGEtn59G64sy+fatizL6ZqnYDRER6Abvb8L1W8kGJDp8XXQ3t9Fb9iDOsSJTopJGMM6jHE99riR3LgVU8JAtslFvi2XHEs2Toczo67KZDKJlOGjCJ1OSUWVnEApkEwD7+sNDqmT8rFrezefrm9JL+d0mwdT+1KCyuES115wbDB79mz+9a9/8c477/Dyyy/z/PPPc/311/O73/0Or9ebYXig12c6HOp0+3eru3u73t6kWY2mZVrRJw11EkiSlPHeQK0rkJECuHu7fXHBBRcMO65EIsHNN9/MWWedld43i8XCr3/964xlm5ubycrK2u9tCQ6MQyaaOjo6+M1vfsPy5csxGAwsWbKE+fPnM27cOAAmTZqUVsihUIivfe1r3HnnnQBs3ryZH/3oR0esC4jFYKbCUsLsKcm+G1RVpdHbSm33Dmp7drKtewctunooAJ2kI5s8vH4Xn31qxfS+C13cgN1pyhBRhSVODEYRCBQIDgaapuHzhNlZ10ZNdS2d3U3EtX4AElETslpIQV4pZWMK0mm1JvPerYX3909QVVW6Q310jtCZa0egG380kNHePhAtyqsc1m9RltkFgN/vz4hODbzq6uoIhUIZ6zMajSMaUzidThwOh6hVOgqQZImsHCtZOVYmTy9Kzw/0R9Kpfcl6KS+1WzsY0Nlmiz7DbKKg2ElOrlVkOgiOOu6//37y8vK4/PLLmT9/PhdddBEzZsygs7OTF198kUceeeQLb2Pq1KncdddddHV1kZuby7333sv8+fM5/vjjefbZZ7njjjvo7e3lzTff5OGHH6arq4sdO3ak619ra2v3uQ1FUYjH43sVciMd1/HHH88zzzzDwoULiUajXHrppdx1113MnTuXJ554gm984xvE43G++93v8uijj6IoColE4gufE0Emh+yu/MMPP+T444/H5XIB8JWvfIVXX301XTQ3lD/96U/MnTuXOXPmAEnR1NDQwGOPPcaECRP48Y9/jNN5MLrGGx1kWWaMu4Qx7hK+Mv5UAHpDHrZ172Rb905qu3ewU6olYU1+oN2KG1csl+5uO5vesGIM25BlmfwCe7o2qqTcTXauKAoWCPaHSDhOa7OHlgYPTQ1dtLY2EZd6UYwBJAlkTORljWfC+AlMmFSKK8uyxyfyqqbS6e9ml6eJ+r5m6j1N7Oprwhvux9XyLC6zA4fBhkFnQJbkdH8vgWgQb7if3lAfCW2wDyFFkslNGS1UZs0mz5YzpLYoB4th31Fnh8OBw+GgtLR02HvRaHREQdXT08POnTsz/kglScJut2cIqqEOgGaz6LD1SMZqN1I5MZfKibnpedFInI62fjpaB4XUug/q0/1Y6XRJG/QBIZVf5CS/0C4e0u2BeCKOJ+LDG+6nP+Inokb3vZDgoLN06VJuvPFGnn/+eRRF4ac//SkA55xzDu+///6Iv4UHSn5+Prfffjvf+c53UFWVGTNmsHjxYkKhEHfeeSfnn38+iUSCq666iuOOO45oNMpzzz3H2WefTUVFBbNn77vT40WLFnHhhReyfPnyvRpS7H5cS5YsoaGhgYsuuoh4PM7ixYuZP38+AFu2bGHx4sWoqsq3vvUtKioqWLBgAb/+9a+x2+2cffbZX/jcCJJI2oHEDL8Af/rTnwgGg+m0un/+8598+umn3H333RntfD4fZ599NitXrkyn41199dVceeWVTJs2jV//+te0trby4IMP7nObkUiELVu2HPyDOQjE1DgdkW6awx20hDtoCXUSUpP1CQYMuOPZWPxu5C4HRq8TWdWh00u4svW4cgy4U0ODUTwxFHy50VSNfm8cT08MT08UT3eMfm8UxRRAZ/ahMwVA0lAUA9lZuZSUFGB3jNynUkJL0B310BHpoTPSTUekl85ID1FtMO3CobNilI2omkowESaiRlHZe8eqOkmHRTFiV6w4dDbseitWxYJNZ04NLVgVM0bZMKoiRdM0otEooVCIcDg8bBiNZt4QKoqCyWTCbDYPGxqNRhGlOkpQVY2AL463L4avL46vL4avL0YsOvj3b3UoON16HOmXDqPp2Ly+CS1BIBEmEA8STIQIJEIE4qlhIkQgHiSQCBFMhAmrmS6TC7PnM889ddT3ccqUKXu9qT4UVFdXM2nSpMO6DwLBoWZvn/tD9mhpJG020s3BypUrOeOMM9KCCeAPf/hDevy73/3uHp1P9sSh+PFZv379fj1l2BOaptHm70xFopLRqF26z8AFMjJ5hjzcqWhU23YT+i3Jp9FZOZZkPyGpuouCIgeKTgipQ8UXve6CA6ffG6alsY/mBg8tjX20NnlTnYlqmB1RrO4g2HtR1Thmk5mJVdOpqqqiqKgo4zcnGAvR4Gmmvq85FUVqosnXRkJNRmL0sp5si5siUz5xNU5fyEsgFsIXDwABnDo743MrkpGilOFCjiULs95EJB7FE/bhCXvpC3npC3uT0yEf3WEvdb5GYmp82LHpFT1ukwO3yYnTnBy6zU5cJicukwO32Ynb5MBhtCPLB/97HovFMqJTQ6NV7e3txOOZ+2yz2TLS/YZGqiyWPUfvjnaOhe/9QMrq0NS+9lYfrQ396TZ2hzFtNlGY6lfKnWU5IjMe4ok43kg/3rAPT7gfT9iHN/XyhH14I/2p76SPQDQ44jrMehMuowOX3UGxsQinyY7L5MBpcuAy2XGZnPTt6hrVa38kP+w9FgiHw3z9618f8b3rrruORYsWHZL9WLp06YimFEuWLOEb3/jGIdkHwYFzyERTfn4+69atS093dnaSl5c3rN0bb7zB//zP/6Sn+/v7ee6557j88suB5A/9/hb1HU1IkkSRPZ8iez6nVSSdXvzRANt7diVro7p3UtdTSyQ7CtngMjjJkwrw9rvpberm040mJE1G0ckUFjspLndRkhJTTrdIsREcnUQjcdqavbQ0JgVSS4MHnzcZkZUVifxCOxOm2knIPXT1tBAOh0hIBiZNmkhVVRVlZWXIsown5GVT+1Z29TVR72mmvq+Jdn9XejtWvRm32UmJo5BIPEJPsI+YGqPd34lO1lHqLGReyUyKLU5ytSi2cBdRXw/ZOXlYneVYnWWYbQVI8v49mdc0jWAslBRToaSg6gv5MqZbfO1s7aglEAsNW16SJJxGO26TE1dKSLnMDlxpkeVIv2dQ9l6bNRS9Xk9OTg45OTkj73MwOCztz+Px0NDQgN/vz2iv0+lGrKMaEFa7F2t/HjRNQ1U1VE0jkdBIqAMvFTU1PjBMJFRUDRIJNWO+mmqf2K29mhicn15Hqq23J8Sk42JYTF/8GA4XkiThdJtxus1MnFKQnh8KRtNmEx0pQVVX24WmJh98Gk26VJ3UoOlEbr59VB7WxdUEvvCg2PEOiJ+QF09aICVT53avDRzArDOlhI+dEkchU/ImDhFBSUHkNDlwGe0YdPt2IFxf33OwD1NwCDGZTEeEw9xf//rXw70Lgs/BIVMfCxYs4OGHH6a3txez2czrr78+LDVP0zS2bt3KzJkz0/MsFgvLli1j5syZTJ8+nSeffJIzzzzzUO32YcVmsDKzcAozC6cAkFATNHiak5GonmQ0qsdQCxVgqDRQZCrEFc2lqydA85ou1rybvLxWu5GSgb6jyl0Ulbgwmo494Sk4utFUja5OPy0NfSmR5KGzvT99s+bOtlA2NoviMhdWl0ZPbzPbttdS3+ZDURTGjh3LxIkTseTZafa38WHfJv7+3kp2eZrxhgef6LlMduxGO2XOYgKxIL1BD4FYiEAshEVvpsJdyqyiqVS4Sim15+KI+Qj01uHtriXmSdrGytZ8kC14u2vpaV2fnCfrsThLsTrLsbnKsDrL0BsdIx6rJElYDRasBgsljsK9npdoPIondaPYF/bSG0xFr9LTHnb2NuKL9KMxPKJvUkzYDXZsejs2vQ2rzo5VsWLR2bHorJhlKybZig4jmkZKJAwXEYmUiFA1DTUhk1BdJFQnCWspilnDGo8Rj4ZIxIKo0RDxeJBuf4huTwfsrEfaLYUxgZ6EZCSOkTgGYpqRiKonqhmIJhQSKunt71HYqIcku3xEnvvgFY4bm82cSfnMmZRPSd7IKZ9HG2aLgYpxOVSMGxTO8ViCzvb+jIjUxjVNxKL1QPIBRl6+PWl/XuykoMhBfpFjRDOVuJrAF+nHE/LhTdUKDRVFAyLIG/bRvxch5DTZcZoclDgKOS5vAi6TY1AEGe24zM79FkICgUCwPxzSSNMPfvADvvWtbxGLxfjP//xPpk2bxn//939z3XXXMXXqVHp7e9Hr9RmpdIqi8Nvf/pY777yTcDjMmDFj0r0qf9lQZIWxWeWMzSrnHBYC0B3sZVt3Mhq1rXsnn4Y2oDpVmA4F5jzy5ALod9PYEqJmazsSEpIEuQX2tFNfcbmbnDzbfvcxIxAcDPz9kQyB1NLoIRpJpn8ZTTqKy1ycdPq4VOqpi1g8lOxLqeZdenp6kCSJ3KJ8XOPz8FmCrOvfxnNb3iYUT0WikMi2uHEa7dgNVnwRf/JmLZx8ZZvdjHGXsLDiBMa4ShnjLiXH7CLkb8PXXYuvawN9dQ30aSqyzoQjaxyO7DMIUEJ1U4z123eSnZ2NngAWqROb0o090o2ttx5ZSgqEYNxCX8RNbziLnpCbnrCDWFxK3vAPiY6oqoqqkiEMEolkG1VVM6IogzhTrwE00EeR9JGMV9wQIaCPgL4XSd+WnK8Mr8HSVBktZoSYAS1qQosZUy8DWtSYniZmAGRkKWl6oygSiiwhS9LguGxEkU3IcnJakUEvqxikCHophl6KoiOCokUwaf1IWhQpedGS+6LISIoJSWdG0ptR9GYUvQXFaEFvtKLT6YesW0qPy7KcnLfbPqXnD2mrpObJA/OUwfm7r3voMrIs8ca76+hXXayr7uDxlVt5fOVW8rMszJ2Uz5zJ+UytzMFwDHVAq9MrFJW6KCp1peepqkZfT4D2Zh9tLR6am3up/aydTz5uHlzOpoIzStwWIGDuo0/fiYc+GOGvxqQzpiJADooc+UzOHY/L7MBpdKTT5AZEkVEIIYFAcBg4ZEYQh4OB3OCjoabpYBGOR9jR25AWUbU9O9P52za9lRJzCa5oDroeB8FdOqLB5M2TwahLWy0Xl7spKXNhtR/eItSjgSPluh/pxGKJwTS7lFDy9iXTzmRZIr/IMfj5Kxt0ivT7/Wzbto2tn31GZ0dHsr1DR581xC65lYiUNGjQK3qyzS6MioGYGqc35CEcTxZwS5JEsb2AMa4SxrhL00OHMdkxYSzix9dTm3x1byMeSz7dtjhKcGRPICyXsa3dyOadHjbv6MbTn1yvQSdhMup3uxmX0SsqubZ+8q1e8qwecswebIbksaqahCfiwhPNwhvLxhfLJqrZkjfjGTf6w2/yB9avKKk28oAgGH6jP7T9UEEgSxKyDHEtRjDhJxD3E4j344/58ceSw/5oP76oD1/UR3Ck1EAkHCZ7svbK7MRpGlp7NZAimJy3v0/54/E4/f39w+qoBsZ3N6iwWCwjpv45nU5sNtuo1HsNZej3vrMvyPqaTtZ91sEndV1EogkMeoXp43OYOymf2ZPyyXN/vv68DicJNYEv4k9HfwYiQINpcskaPU+kH38kkI5y6qJGTEEH5qADS8iNOehEFzKl16uYwJajkFVgpqDYSWlpNmXFeVgMpj3tyhHFaP/mH8r7ln0hjCAEX0aOCCMIwaHBpDNyXN4EjsubACTtklv7O6jtGugzaic14VqwgjJNodRWTJ5UgKXfjbfVR8PbPemUF1eWJWV3nhRSBcUOdLpj5+mpYHTQVI2e7kBGFKmj1Zf+XDndZorLXMw7uSLdJ5l+yFP59r5O/vXB+zTsqCfckxQwAX2EHmc/3eZ+DGYDLpOTfDmPcDxCb6iPWCJGu78Lg6Kn3FnMcXkTGOMqpcJdSqmzKOPJtKYm8HsbaGl8H19PLUFf8sm4Tm/Fnj2BhKGcHd0uPt0eYvOr3Xj66wDIcZqYOSGXqZU5TB2XQ/Ou6nS3CPsiFvER8Dbi9zTi8DaQ421EVXckt2uwYXWWpdP6LI4SFN2RcQMZS8RS9VbeIcYWviHGFl7qPc14w/2o2vDolVlvGlFQ7V57ZTVYcLvduN3uYevQNI1wODyijXpbWxu1tbUZRkOKouBwOPYoqg72jWie28I5J4zhnBPGEI0l2LKjh4+r21lX3cHHnyWFfnmBPZ3GN2lMVkYnyYeSTCHUjyfsTafCeQaEUEoYDRVCQzHqjLiMydS4Qns+Vbnj0hGigdqhgYiQSZc815FwjI7W/iGd83pp2NjPrnV+PqIFvUEhr9CeNpsoKHaSV2jP+F0QCASCw40QTcc4siRT4iikxFHIosqTAPBF/Mk+o3qSTn0bezcSU2NQALljsykxleCO5aB0G2is72HrplYAFEUmv9iRFFFlbkrKXXvt30bw5SDoj9LcmBJIDR5amzyEQ8kIkMGoo6jUyQkLK5N1dWUubI6kIFA1lXZ/Fx+3bWJXTwON9Y1EOoJYAwZkJPr1IXy5EXDrkPQy4ahGPKQSS9Uf2Q1WxrhLOb50Zjp6VGTLHzHKEA314e3Zhq+7Bl9vHWo8DJKcFCsFC2n0ZrNxl8SWVb14+ruB7mEiKX+3z3pL/f5/7vVGB668KbjykvWJmpog5G8n4G0k4G3A72nE2/VZqrWE2ZafNJhwJcWUyZqLJB36G229oifXmk2uNXuv7VRVpT/qpy806BjoCQ8YWyTn1fU24Al5iSSG93Ojk3UpAeVIGVs4M4wt3CYHLoeT8XnjUXYz20gkEuko1UiOf+FwOKO9yWQaJqQGpu32L+ZKaNArzKrKY1ZVHld+VaO508/6mqR4emHVDp57uw6rWc+siXnMmZTP7Ko8nLYvJuJUVR2Sdjo8CuQdUi/UvychpBhSYsdJgS2XiTmVKRFkTwuiAbMEk/7ABb3RpKdsbBZlY7PS8xJxla5Of9psor3Vy+YNLaz7sAFIduibk2ejIGU6kZ8ynbBYRWqeYPS49dZbueaaayguLmbVqlXceeedzJo1C5PJxJIlS5g6NdNu/kc/+hHz5s1j8eLFPPTQQ7z44otcdtllXHHFFaO2j08//TRWq5Xzzjtv1LYhGBkhmr6EOIw25hRPY07xNCBp1VrvaaZmIKWvewcbw5+AEUyTjYx1lpMnFWDud5Noi7NxTRNr36sHwGI1pO3OS8qTOe8jFf8Kjg3i8QTtLb6MKFJfTzL9U5Igr9DB5OmFw2rlYokYTd421navp3570uK7oa8Zk18hK2TDEjUS1kcJmmJ0ZvUTVCIE46nUsCDkWbMZn12Rjh6NcZWQZXbtuUPaRAx/386UUKolHEg+8dcbnRgck2gP5rGpwcym9/vx+CNA+z5F0sFEkhUsjmIsjmJyS5NumfFYMCmiPI0EvI30dXxKd8saAGSdCauzFFvKqc/qLENnsI7Kvn0eZFlOu5BByR7baZpGKB5OR6n6UpGrodPt/Z3UdNWNaAIgIeEw2pJF/mmHwCHDQicTxhbiGhLlGIhS7S6oOjo62L59O6o6GCGTZTkjSrV7pMpk2n/BIEkSpfl2SvPtfPXUcQTDMTZt62JddQfrqjt4b1MLkgQTSt3MmZzPnKp8xhY7kWUpKYSi/t3MErx4wv3DzBJ8Ef+IQsig6NNiJz8thOw4jY50rdCAg9znEUJfFEUnJwVRkYPpc5PzNE3D0xvKjEjt6GHzhpb0cg6XKW02MdBBr3CIHX36P32H/k/eGpV126efjn3aaaOy7gNlzZo1XH311QC8+uqrXHXVVXu0KN+dF198kWXLllFRUTGau8jGjRuZN2/eqG5DMDJCNAnQKTrGZY9hXPYYmLgITdPoCvayLWV1vq17J6u876FpGlKWRGlFIaXmUlyxXHTdJnobA2z/rDO5Mgly82yDfUeVu8nLtyEfpnQUwedH0zT6eoJpgdTc6KG9xYuaSN6g2Z0mistczDq+jOJyN0UlTgxGHcFoiHpPM+s8H7OrIdn/UbOvjYSmggbOhBWHasEZMxPQhWlwdZOQkzeuSioyepy7ijGuEircpZS7SrAa9l4TomkakWA3vu5avD219PfuQFNjSJKCzlpOv2EBW1rtrKmN4fFHgQA5zgQzJx4akbQ/6PQWnDlVOHOqUsekEgl2E/A04vc2EPA20rbzTUjdIBstOem0PqurDIutcL8tzw8XkiRh0Zux6M0U2fP32jaWiKVraPrS0atk5GoggtXkbcUb9iU/W7th1pkGBdVABMvuxJ3nZIKpJCkojHaIaiP2TbV9+3ZCocyaLqPRiNPpJJFI0NXVNWKnv0OHQ7vHMBkUJk+wUVymcsopRra3tlPd0k5Ddz3/3Objn7si6IwxdKYYccJ7FEIDEZ88Ww4TsiuGRIIyzRJMOuNRJyQkScKdbcGdbWHStEFXyYA/QkfKBn1AUG3/rIOBrEyTWT9og54SUjl5tsOWBik4+LS3t3PTTTcRDAaRZZnTTjuNzZs386c//QmAJ598kvr6eiZPnsw777xDZ2cn7e3tfPvb36a1tZXVq1fjcrlYtmzZHlN0H3vsMTo7O7nyyiv56le/yptvvslHH32ELMusWLGCa665hnnz5vHLX/6Sd955h7y8PBKJBPPmzeMnP/kJHR0dXH311Tz44IMj1sS8+eabPPPMM8P2+dZbb+X+++9n7dq1JBIJFi9ezOWXX46mafzqV7/ijTfeQFEUvv71rzN+/HjeeustVq9eTW5uLieffPLonXTBMIRoEgxDkiTyrNnkWbM5qTz5NCMUC1PXW5/uM2pDzyeEYmGQwDnRwbj5Y8iTC7D0ZxFrNVC7tZ1NHzcBoDcoFJU609Go4nI3dseRUbMhGCQUjKZT7FpS6XahYMpoIXUNjz9lbCqK5MLuMNEX9lLf18QGz3aeW5cUSB2B7vQ6rXozTqODAlMu/WE//VoAry6AlwA6g0KJrYAJ+ZWMzSpnjKuEUmch+v3sVygRD9PfW4evexvenlqioV4AFGM2AaWK2m4XH9QqdPuSjnxJkZR3xIikfSFJMiZrHiZrHtnFydqpRDxC0NecTuvz9Wynt21Dsr2sw+ooTQqpVFqfweTc2yaOaPSKnhxrFjnWrL22UzUVfyQwJGrlTddh9YW9eMM+dvY10tfmI5IyBxmKIisZ/Vq5Chy4xziZYC7DpljRx2SkiEY8FMPn9eH1eunq6qKhoYFwODysw9+haDKoikpMThAhRlxOEJfV1DA5btBDqc0Ekolw1EpvN8QieuSEkWJ3DlPKC5kzroyJxQVY9F/OiIrVZmTshFzGTshNz4tFE3S0+VJiKpnit/6jBuKx1AMYnUxegT0dkcovTka1DEZx2/N5sE877bBGg5599llOO+00vvvd77JmzRo2b97M1q1b8Xq9OJ1OXnrpJW677Tbq6urYvHkzK1euxOv1cvrpp7Ns2TJuv/12li5dynvvvccZZ5wx4jauvPJKnnrqKR577DFKSkrYuXNnOvVuxYoVALz22mt89tlnvPTSS/T393PBBRcA8LOf/Yz3338/vexInHLKKfz0pz8dts/PPPMMAM8//zzRaJTvfOc7TJkyha6uLjZs2MDKlSuJxWJceumlLFu2jNNPP5158+YJwXQYEL8egv3CrDcxNb+KqfnJp+CqqtLsa0v1GZUUUuv9nwKgc+oYe2oZ5dZSXNFcdD12ehojrH53ZzpK4XCZMizPdzcDEIwuibhKR5uP5obBWqTe7lQ6lAR5+XaqphSkUy+z8yx0hnqSAqmvhuWbmqjva8Yb6U+v02VyYDNYKXEU0B8J4I30p/s/0icUrDEjkywVTCmpYn7VbIpdhcgHUKejaVraDtzbXUvAU4+mJZBkPSGpmF3eMXy03URjT3KdOU4jU8fnHDUiaX9QdEbsWZXYsyqB5DmJhj1pERXwNNLZ+D5aQwJIpiNaXeXYUil9FkcJ8gF0dns0IEsyDpMdh8lOuWvvbcOxMH1pY4tMceUJ+ej0d1PbvYP+iH/YshISdqMVl9VJWA4RlePJz78K+oSMTlVSLxkjBmySGbNkwqjpsWpmHAkJ4hpqTCUeizFCICm5HUlCpzeQ0CkEPV52dXjYvnobBoORglwXY4qzqCzNxWazZES1DkZnwUcTeoNCSbmbkvJB8xA1odLTHRiMSLX4qNnSzsa1yQd4SJCVbc2ISBUUO7EJp9gjnhNOOIFrr72W6upqTj31VJYuXUprayuvv/46CxYswOPxMG3aNOrq6pg1axY2mw2bzZZeFqC4uBifz7e3zeyTtWvXctZZZ6HX68nKyuKUU07Z72X1ej1nnXXWsH1etmwZ1dXVrF69GoBgMEhtbS07duzgnHPOwWAwYDAYjohOeb/sCNEk+FzIskyZq5gyVzFnjks+7fCEfemaqG3dO3m7+QPiavIpbP74XCbMryBfLsTidxNu1dHa6OGzT9pS6xu0nS5JdcKblWM96m9yjwQG6gRahpg1tLV4ScSTT2RtdiPFZS5mzCuluMxFbpGVzkgn9Z5mNvZV8/xnTdR/1JJ+Si8jkWVx4zDasBjMeMM+grFwus7CpbdjDRtw+LOxRA2Mz61gxpTpjB8/HrPZfED7Ho8G8PVsx9dTg7d7G/FoUqTF5Gxa+sexrt5CdauZhCaT4zQxdVwOX1107IikfSFJEkazG6PZTVbBdABUNU6ovzUjrc/T8WlqARmLvShdF2V1lWM0Zx/z52kAk95Eod5EoT1vr+3iiaQgGhBXaYOLVO2VJ+ahrKB0RMc4l9GBWW/a6zkdcAQMh8OEQqGM4cD4wHS/P0i/P0AsGiDa1822Pti2Zfg6dTpdWkTtKV1w93lGo3HU7dkPJbIik5tvJzffztRZxUDyXPd7w+kaqfYWH61N3vR/DyR/AwuKHeQXOyksTnbMm5Wd7PZAcGQwe/Zs/vWvf/HOO+/w8ssv8/zzz3P99dfzu9/9Dq/Xm2GKsPsDhKFpsl8USZIy6iAPdN0XXHDBsH1OJBLcfPPNnHXWWQD09vZisVj49a9/nbFsc3MzWVl7j7wLRhchmgQHDZfJwbySGcwrmQEkaxJ29jWm66I+7ajGG1kLgMVqZvxJFYyzl+OK5iD12OhqDPDp+ua0e5LZoqeozEXJQH1UmQuzRTgn7YtwKDakw9ikUAr6k45lOr1MYYmLuSeOoaTcRVahmR4tKZA2ebby4o5mmje2pWtEDIoet8lJniWLSCJKX8hLTI3THexFJ+socxYxvnAMprCeSEeAQKsPRZMpKCiganYVEydOTD/t2x80TSXgbUp2LttTS8DbBGioGOkM5fFpcwmbW2z0R4xpkXT6iV8ekbQ/yLIuLYrySDpmxiL9qWhUIwFPAz2t6+lq+hAARW9JGky4UkLKUYqiPzBxe6yhU3RkW9xkW4ZboMMX76tHkqS0uBnJZn1PBEIRPqltZVNNKzW7Oun3B9HLCfKcegrtBpx2HUadSjgcpqurKy3C9tYd4/6Iq92HR1NUS5IkHC4zDpeZCZMH6+jCoVhaSHWkIlM7t3Wnu0YwGBXyCzMjUrkF+/9bJji43H///eTl5XH55Zczf/58LrroImbMmEFnZycvvvgijzzyyEHZjqIoJBKJPb5/wgkn8Oc//5lvfOMbhEIh3nvvPWbMmLHf6x9pn48//nieeeYZFi5cSDQa5dJLL+Wuu+5i7ty5PPHEE3zjG98gHo/z3e9+l0cffXSf+ygYPYRoEowaekXPxJxKJuYMphJ1BLqTfUWlolGftr+KhoYkSZSPLWbC3EoK9YVY+rPob0nQ2uhlVe22dCpLdq412fluKm0sr9D+pS72VRMqHW39GZ3GdncOphbl5NkYX5VHUZkLR76OfmMvDb5mPvVsZkVTE501Pem2Vr0Fp8lGoT2fYCxEX8hLNBGjI9CNVW9mjLuUucUzGOMqocRWQLCzn+2122nY2kBEVcnKymL2gpOZOHHiAd0IRsNefCmXO1/PNhLxEBrgjWZT3T6GLa0OWr02sp1mpo7L4Yo5QiQdKHqjHVfecbjyjgOS4jTs78A/JK3P212dai1hsuYNSesrx2TLOyyW54JMrGYjC2ZUsGBGBZqWtDQfcOP7d3UPCVXDajYya2Ipc6YlLc0dVgORSGTEqNbQiFYoFMLv99Pd3U0oFCIWi+1xPwaiWvsSV7sLsSMpqmUy6xlTmc2YykE7/Xg8QVe7Px2Ram/18cm6Jj7+IHmDKssS0493IvozP/QsXbqUG2+8keeffx5FUfjpT38KwDnnnMP7779PaWnpQdnOaaedxpVXXsmyZctGfP+MM85g8+bNnHfeeeTk5FBZWXnA29h9n5csWUJDQwMXXXQR8XicxYsXM3/+fAC2bNnC4sWLUVWVb33rW1RUVLBgwQJ+/etfY7fbOfvssz//wQoOGEnb2yOoo5xD2bP2aPcSfqwSjIbY1rOLbam6qO09uwin0sDcZicTsyupdJXjjuWhdZtpa0zaXQd2i5yUpCJRJeVuHK5D95T8UF53TdPwecK0NPbR3JCMJLU1e9KFzxabgeIyF0VlLsw5GkGbh+ZgKw2eJnb1NeEbUqfhMjmwGizJ1JVIgP7o4HvZFjcVrlLGuEsY4ypljLuUXEsWiUSCXbt2UVNTw86dO4nH49jtdqqqqqiqqiI3N3e/RIyqxgl46vF21+LrriXkT6bJRBIm6rrdfNbuYGePC6vFztRxR25N0rH2nY/HQgR9TQQ8DSkx1UgilrSTlxUjVmfpoFufswy98cv71P1IvPaBUIxN27tY91kH62o68PRHkpbmZe50x7qVxc79/g7F4/ERUwh3TyPcfbi3Wwqj0bhf4mpoiqFerz+s33tN1ejrDdLe4qWzvR/0fZx2+vGjtr1Ded+yL6qrq0d0gRMIjmX29rkXkSbBYcViMDOjcDIzCicDyR7rm7ytSYOJ7h3U9uxkdXPSHUyv6Bk3ppwJs8dSYirB0u+mtyVCS4OHte/Xp2t07A4jxSmTiZKUycTR6JgUCcdpbfJkRJH8/UlBqehkCoudzJhfiilHJWTz0JpoZavnE172thDpTdUfSTJZZid2ow2L3own7CMcjyTrjyL9FNsLmF44OcPe2zHkZlhVVRobG3mt5mPq6uqIRCKYzWamTJlCVVUVRUVF+3VDEwn2pERSsnNZTY2hajItXic1HWOo63aTULKYOi6XRafk8L9HoEgaii8YYldPH8a6OqwKmBQJObWvu980Dk5ruw32MJ1caOhb6emBOYOb2G06vVzmugfbDb+hHTZPy0FnysFunIEa9xOPdpOI9hDs76a/d0d6XbJiRTFko+gHXk4kSRl+vAe0f3vf332ey5Hm7Wkde2i373MO3d29BCeMw2I/ctwJrWY9J04r4sRpRaiqxo4WD+uqO1lX3c7fX6vhb6/WkOUwMrsqKaBmTMjFYtpzmp1Op8sopt8fNE0jGo2OKKZ2HwaDQXp6egiHw0Sjwzs8HkBRlANKIRwYP1hRLUmWyMqxkpVjZfL0pGAWHL2Ew+E99rt03XXXsWjRoi+8jaVLl45oOLFkyRK+8Y1vfOH1Cw4fItJ0kDgSnzweK/SGPCmDiZ1s697BTk8TCTWZLlFkz2dCzlgmuMeSlcgj1qmjtclLc0PfYKerskR+gT3tBFdc7iIn13ZQinwP1nVXVY2u9v5kDVIqitTZ0Z++g8vKsZJfYsOQoxK2+ehUWmjwNdPiG1p/ZMBtdqCX9YTjEfpCXhJaIvWennJXSVocjXGVUuYswqAbXiOmaRptbW3U1NRQW1tLMBjEYDAwfvx4qqqqKCsr2+cNSSIexd+3A293Lb0d1SSiSTtwb9jEtk4Xdd1ufPF8qsYWHLGRpN1RNY0tbd28srmWHTEDmjxEiGsaSjyMLhZODUMosTC6eDg9zJwXQhePII3Qv9CRjCyD1a7D5tBjd+iwO3UYjEnXSzWh4ffH8Xvj+H0x+n1xopGj6/gOlKz8YkrGTqKkchJFYydiMh85HQ4PxdMfYUNtBx9/1sHG2k4C4Tg6RWJyRTZzJydFVHGu7bB9/xKJxIgmGPsaDi3I3x2j0XhAImugVmtf52C0/+tFpEkgOLzs7XMvRNNBQoimQ0c0HmVHX0M6GrWteyf90aRdttVgYUL2WCbmjKXcWoqx30lX82AHrZFw0s3PaNKl7c6LU2YTFtuBm0x83uvu84bS4qilsY/WJi+xaFLgmC16cottGHNUInYfXfoWGoKNdAYG649segt2kw0ZmUAsiCc8+FTLbrTtll5XQpEtf59Cp6uri5qaGmpqavD5fCiKwtixY6mqqqKiomKvxd+aphEOdODtqqGz7TOi/gYkVGIJmV29Tuq63fRECigrKWVqZe5RIZIG6AlFWLWzjfcaOvCjR4mFKY31UKSHnKISggkIqalXAkIJjZBKen58L7+wRhksCphlCYsiYVbAokuNy9LguCJhVcCsSOhTNXwSqXOXHmROD4yMdI6HzZNGbjs4LQ1tNnSjxKP9RIMdRILtRILtREMdaCmxruisGK2FGC0FmKxFGM35yDr9XteZ3uaw49rTvg2ixROo8RgkEqixOFoigRaPpebHIR5HjSfQ4vEh04PDzHbxYe20WHLYGe5HKc6lN+Kjs7OZeCwKkkRuYRkllZMoHltFUcUEDMYjz1AjnlCpru9lfXUHH1d30NiedKQszLYye1IecycVMKUyG8MR3gWEpmnEYrE91meN5EgYDoeJRIb31TWALMv7rM8KBoPpepPRQIgmgeDwIkTTKP/4aKrKho0bhWg6TGiaRpu/k9quZDrftu6dNPuSdTKKJDPGVcqEnLFMzB5LDvkEO0jXBXW2+dJpN+5sS0bfUQVFDhTd3oXG/oimaCROW7OXlkZPul+kfm8YAFmRyMo3Y8rViNj76Ta0Uh/dlVFj5DI6sBgsaJqKL+InkKozAci35lDuLkmJpFIqXKW4zftft+DxeKitraW6upqenp6kIUd5OVVVVYwbN26v35t4LISvZxttzVsJ9G1D0ZLCtbPfQl23m65wHu7ccUypzD+qRBJALKGyscPDql3tbPOEQJKw9TUy2RDhP46fR3FpxX4L5khCxR+NE4jG8Ufj+GNxAtEE/bHUvFg89X4iPR5J7OUJuiJj1euwGRRsBl1qXIdNr2A1DIynhgYFq16HUZEPyrnXVBU1FkuKiVhKVKSnk8NENEw43E043E441k0k3kM89dlAk9BpVvRxK7qoBV3YCBEFYomUKIntYRhHjcdG3N7Afmh76WT2cyHLyDodkl6HrNMj6XTI+uQw1N0N4eR3WNPrUSuKCOXY8EhRerzdqGoCSZbJL6mgOBWJKiwfh05/5Ll/dvYGWVeTjEJ9WtdNNJbAaFCYPi6XOZPzmVOVT677yBN/nxdVVfcosvYW1RpwK6usrOSrX/3qqO2fEE0CweFFiKZR/PHp7/fwl1/eQMRmggklSPnZ6BQdOlmHIivoZAWdrEu9hk4nh4o0ZJ6ipKZ1u7UbHFd2Xz69noNzU3Ss4I8EMgwm6nrqiSSSefPZFnfS1S97LGOd5ej6bbQ3+tKixu/LrBsqLh+0PXe6zRnnefcbZ03V6Or0pyNbLY0eOtv70VI2tjaXAVOuRtTeT7ehjUZtJ2EtJaAkmSyTE6POSEyN4Qn7iCaSDlaKJFPiLBqSXldCuasEq8FywOcmEAhQW1tLTU0NbW1JcVlUVERVVdIi3GIZeZ1JO/Bmmhs309dZgy7RgSxphGMKO3tctAfysLjHMaGi/KgTSQM0eoO839zD6uZuQgkNQ9hHVmcNc3KtnHLKGbhzC9NtRyu6rCUSRKJR/MEI/eEo/nCE/kiMQDSGP5ogEEvgjycIxFUCCY2gCgEVwuz5XCuailmNY07EMcejmOJRzLEoxmgEUzSMMRzCFAlhDAUxhgMYAgH04WBSrAwRKewlHWqvmGTkfCNyvgmpIDU0JB9IaGEVrTsGvQmkPg3JJyGTKVIGh7o9zB8y1OtSYkefHOr0yeUGpgdE0O7t9PrM+cqeIy3r1q3juOIS/HU78NfVpYY7UMNhVAmCThORoix8RhlvtB9N05AVHQVllZRUJkVUfslYlIPYf8zBIBJLsLmum3WpKFRnb/IBzZhCR9pMoqrc/aVzLB2IakUiEWpra5kzZ86obUuIJoHg8CJE0yj++ETiUR556hewvQl9NEHUoqevyE5fjpEYKnE1TlxLEFcTxBPxzILlg8yehJVO2h/htef39yj2lEFBqEi7t9n3NuRDaGEcVxM0eprTVue1PTvpCfYBYFQMjMsew8ScsUzIrqRAV4inLTLoUNfkIZ4ymbCmOoIdiEg1t+4gL7uc5pRZQ2uTl2gk+cRbb5Qx5ULM7qfH2EazXE9MlxRIBkWPy+RELyuEUsYMaqq+xaQzMsZVwphU7VGFu5QSRwF65fP3jRIOh9m+fTs1NTU0NTWhaRq5ublp5zuHwzHictGwj/pdm+ls24oSbcQgJwVli9dGa38OOlsl5WUTmDo+/6gUSQCBaJw1rb2839xDky+ErKk4uurI6a7l+AnjmHXK2dhdg7bEaiyGb+tn1L7/AUX5+ZlRkT1EX/YVnVHjsXTq1+cVJqokETGaiZjMREwWwiZzctpqI2q2EjFbiJgsRExmwkYTYYOJiN6AtofvoaypmNQEFjWOWVOxkHpJYJHBKoNFkbHpZKx6BZtewaLXoTPsRdCkhA+KTDTSR7C/mYA36dYX9ncwUMRnsuZldMBrtuYjyUdOuthIgllTVUKtrWkB5a/bQWDHTmLxKH6LjoDTRMBpxE/yQYhOp6ewYkJSRI2dRG5ROfJehNqhRtM0mjr6U2YSHXy2K2lpbjPrmTUxjzmT85k1MQ+n7fDe2B9qRE2TQHBsI0TTIfjx+fjjtTh0CTa+9yrdbY2YbQ6mnbCIKfNPx2zNdCNLiqh4UkipcRJqIj0eVxOp6XhGm/ge26TWMUSYxdXEAWxjpPfjxDU1PX+0kCV5j6IqQ+wpKaElDYq0/RF/exd6CoFoiFZfBy2+Nhq9rbT5O1BTX4dCWx7js8cwPruC8Vlj0futtDf5aGny0tLQR09XIONYJBmMbog5/PQa2+nQNxM1BUBK1lnZDTYkCQLRYIb1t9vkzKg9qnCVkmfLOSiCMhaLsXPnTqqrq6mvryeRSOByudJCKTs7e9gyaiLOzvoaWho3owZ34dAnhWUgoqfJl41mGkNB0WSmTCg7akUSJE0dqrv7+aC5h40dHuKqhjPWj61hPXneRmbOO4npC85Mu6PFvF761m+gd+06PJs+IREKZazvc0dFBtplRDt2j4rs7f0h7UZav6Ig7aWWTdU0QrHBtMBkJGswjXD3tMGB9xJ7+NeQAIteSacIWg3KkFRB3bC0QrtBlxRaskQiHibgbcrohDceS37PZMWAxZG0PLelOuHVG0cW+oeC/b1x1hIJgk3NGULK27CLfiP4LQp+u4GQIfkd0usMFJaNo7RqGqXjJpGdX7LXa3eoCYRibNrWxcfV7ayv7sTjH7Q0n5uKQo09AEvzoxUhmg4fa9as4fe//z1//etfD2i5f/zjHwB7dK576623aGho4Iorrthn26OJ22+/nSVLljB16tTDvSv7za233so111xDcXHxqG5n6DXfHWE5PsrE/X4kJCbOPIEJM46nZWc1G999lTX/fp717/yLSbNPYvqJZ+HKSRbjG5AxfIGowaFE07SkoNqHCBt53t6F2YEIvWgiTkKN7H172sGL5rX5O2nzd/Juw9qM+bIioxunYKwwYwm60fwKfnMfQasHZA2XyYFFb8atWfCFE4TiYQLRIMFoiAJ7LlPyJqYjSGPcJbhMB/fGL5FI0NDQQE1NDXV1dcRiMaxWK9OnT6eqqoqCgoKMmxpN06hvamLXzk8J++pw6dox6hJYVGgLueiJTiUrfxKTZlVxcvbhc9c6WHQFI3zY3MOHzb30hqOYZSj2NmDc/iFuwsw48StMPf4qDCYzwYZGml59g76P19O/bRtoGqaCMWSfcCE6azHRkIo1z4E+y4LBbUbvNieHTiPSUZK+JEsSVoMOq0FH/n4av2maRjiu7iakEhmiaqBuqzcUo8kXwh+NE1P3/L006+Qhoqocm74Sa56CWYqii3uRo93IoTbo+wSTthoTESxmJ1bXYL9RFkcxsnxk/aVJioJ1TDnWMeXkn3E6kIxUBpuakiJqex29ddvp7G2j3xSlI7CZxp2fAclodH5+KWWTZ1I+dRbu3MLD+v2zmvWcOL2IE6cPsTT/LJnG9+SrNTw5xNJ87uR8po/fu6W5QHCo2JcA2rp16363PZq45557DvcuHDBr1qzh6quvHvXtDL3mB8KR9Q9zFBLr9/PyDTeiGQxE3nmXnElVFM6ezXmX/4DezlY2vf8aWz9+l81r3mbs5FnMPPkrFJaPP9y7vd9IkpSM9KADjo40DFVVM4XU3oTbXoReLBGjN+Shvb+LzkA3XcFe/NEA0YRKjDiSW0NxSlj0OqJhhbgaxxP2EYgGKXUWcVzehMH+j5zFmPSmUTleTdNobm6mpqaGbdu2EQ6HMZlM6YhSSUlJ2jlP0zQaWnvYtn0L/b3bsEnNZFuCOAFZMtITL8fumMiECdOZk5t11IskgGhCZWO7h/ebe6jp6UcCxpg0itvXQ91aHA4HMxeeQ9X0Ewhu207zE3+jb916Ip1dIMk4Js2l8OzvguYkEUhADGTFRMIZQY2p+Gu6UCNDIrIS6J0m9C4zhqzkcEBQ6RzGg2J1fziRJAmzXsGsV8i17P9vQiShZphh7B7FShtkROK0+cO7GWLkpF6DT0z1ARVTIIKxOYRJ2oKJjdgMehxmCy6biyxHNk6LE7tRf9ANMb4Isl6PbexYbGPHwllnAqBGowTqG/DX7aC7tprWpjp6Ql7aQ3U0te7kgzeewyAp5LnyKR5bxdi5C8gqG3vYjkWWJcaXuhlf6uYbX6mirz/MhppOPq7u4INPW/n32kZ0isRxY7OZM6mAuZPzKcqxHvZzL/j8rNq1mrd3fTgq615YsYBTK/a/w+Bdu3bxk5/8BI/Hg8Vi4fbbb2fatGm0t7dz00034fV6mTBhAh9//DHvvvsuDz/8MABXXXUVt912G9u3bwfg0ksvZdasWTz11FNAsra3tbUVgGuvvZaVK1fy6KOPIkkSU6dO5e67796ji+zy5ct5/vnn8Xg8LFy4kG9961v85Cc/ob29HUmSuPHGG1mwYAH9/f3ccsstNDY2UlpaSnt7O7///e9Zu3btfi3/0Ucf8cADDwDgdDp58MEHMRgM3HDDDXR3dwNw9dVXs2jRIpYuXco111zD/Pnz+eMf/8iKFStQFIUTTzyRm2++mba2Nq655hrGjx9PdXU12dnZ/O53v8Plcu3x3H/44Yf88pe/RNM0ioqKePDBB7FYLNx777189NFHSJLEBRdcwJVXXjksMvijH/2IefPmMW/evBG3+8wzz9DZ2cmVV17J3/72N9xu97Dt19TUcNNNN/HSSy8B8Pbbb/P000/zxz/+kccee4xXXnmFRCLBSSedxM0334wkSfzlL3/hH//4B4qisHDhQi666KKMa37xxRfv92dPiKYvSEKvo+G4ScQSCXYA1NZAbQ2SpmFWFKx2O3nTzyTs97CzqZHt/9+juLNzmDzreMZPmY3NZkM5gvLYjwVkWcYgGxgNnypfxJ/qM2oH23p20tjbwhhbAfNLZqYNGoocBehGuf5C0zQ6Ozuprq6mtrYWv9+PTqejsrKSSZMmMWbMGBQl2dFoY7uP6rod9HRUY0o0UezoI0tRcZhlfPE8AqZZVIydzsyiffe/dLSgaRoN3iAfNPewprWPUDxBjtnAAmsU9ZN/E2rbiTM7n+lnf43csIRn1QY2PPQX1HAYxeLENe0ksudVkgjq0WIqakjCXObAOtaNdWwWeqeJ9evXM3n2DDRNQw3FiXpCxPpCRPvCxPqS494WL1pssEZJUiR0TtOQyJQJvduM3mVGZzcc0zeVRkXGaDaQZd7/b2YsoSaNL3aLYg2NbPWHw/jCIXqjMZqiEInowKMB3anXIDpJSka0DENSCIc4DQ6mFQ44ECqYdcqoXxfZYMA+YTz2CeMp/I+zmQokwmH8O3fRufUTmrZ/RmdvG+1dzTT3tbJm/VsYEpBtclJYXEH5tDnkT52O7gA6oj2YuO0mFs0tY9HcsrSl+UAU6s8rtvDnFVsozLYm3fgm5TNl7JFvaS44crn55pu58sorOeuss9i0aRPXX389r732Gvfccw/nnHMO3/zmN/n3v/+dvrEeYOPGjXi9Xl544QX6+vq47777uOSSS1iyZAkAF198cVpgdXR08Itf/ILly5dTUFDAzTffzKpVqzjjjDP2uF8dHR28/PLL6HQ6fvCDH3DxxRezaNEiOjs7ufTSS3nhhRf4wx/+QEVFBY8++iibN2/mkksuOaDlH3nkEe68806mTZvGE088wWeffUZXVxfFxcU89thj7Nixg2effTajk95Vq1bx1ltvsXz5cnQ6Hddeey1PPfUUp556KjU1Ndx7771Mnjw5LRSXLl064vFFo1Fuuukm/vznPzNp0iR+/etf8/zzzyPLMm1tbaxYsYJoNMrSpUuZMGECZvOeXTdH2u6VV17JU089xWOPPTaiYAKoqqpClmW2bdvGhAkTeOmll7jgggt499132bJlC88++yySJHHzzTezYsUKKioq+Pvf/85zzz2H2Wzmu9/9Luecc07GNT8QhGj6gphMJr539dWsXr2a8vJy+uob6K7bgae1lUC/j2hPLwGjkbjZRNTgBoObriisWr2RVas3ptdhs9mwWCwjDq1WK1arFYPh2L6pOhpwGG3MKZ7GnOJpwKHvn6u3tzfdl1JfXx+yLDNmzBhOOeUUKisr0ev1NHX089pHdbS1VCOF6ylzdpNriZDrgGDcTsI8hYKyqZSWTULRHR3Rw/2lPxpnTUsvHzT30NwfQi9LzMxzUOxvpvOjlfg9Pbiz8jluzExM21vof/Ax+gFz8XhyT7wY2ZhPoj+VRpYwYJ+UhbXSjaXUhWwY+SZPkiQUix6zRY+5KDPdUtM0EoFYUkx5QsR6Q0Q9SVEVbPCgxYcIKp2M3mUaTPNzD4orxbLvTjePRfSKjEuRcR1Amlc8HqfX20ZXbzM93g76+vvoj4QJYySsGYlrLmJxB+GEBU9QTyCuEYgl9pjUq0hg0esy6rToB1tPP5VuG7pRihwqJhPOyZNwTp7EQG5CLBCgbdN6GjZvoK11F10RL231m9hQvwnjPxO4MJKXXUjphKlkT5qMdexYdJZDaxeuU+Rkh9WVOVxx/nF09AZZV93BuuoOXvuonpXv7cRoUJgxPjftyJfjOnYszY9VTq04/oCiQaNFIBCgubmZs846C4AZM2bgdDrZuXMnH3zwAb/4xS8AOPPMM4cZHI0fP55du3bxne98h1NOOYWbbrppj9vZuHEjs2bNoqCgACAd3dkbkydPRpdyxPzwww/ZuXMnDz30EJD8XWpqauKDDz7gV7/6FQBTp05l4sSJB7T8okWLuOaaazjjjDNYtGgRJ554IvX19fz617+mo6OD0047bVh62+rVqzn33HMxmZLZLhdffDEvvPACp556KtnZ2UyePDl9frxe7x6Pr7a2lvz8/HS9zw033ADAddddx0UXXYSiKJjNZs4//3w++ugjTj/99D2u60C2uzsXXngh//rXvygtLWXt2rXce++9/Pa3v+XTTz9l8eLFQNL8qqioiO7ubhYuXIjdbgfgL3/5C5CMUH0ehGg6COj1eiwWC2VlZZSVlcEpJwMQD4bwbt6CZ+NG+tZvJNTVRUyvRyopJFBWQHs8iD8UJBEzoxpkwrKEx+MhEAik+4QYik6nSwuovb0sFssxEzEQgM/nS1uEd3Z2AlBaWsqcOXMYN24c3b44m+u6eXPjOyT8OyhxdFPq6iffrRFXdaiGUlxFkykum4rJMtz84WhH1TQ+6/bxflMPmzq8JDSNMU4LX5+Yj6XxE6pf/v/YGejHbbQzsU/B/Nl2VKUB3eR5FJ69CC1hQw2raFHQZ9twTc/COtaNIfeLpxNJkoTOZkBnM2AudWa8p2ka8f4Isb4w0VRkKtYXItoTJLCjF4bUAMkGBb07lfKXElIDokoxi7qRoeh0OvKyS8nLLk3Pi0cDKZOJhpTRxGoSsaSTpaIzYXGXodjL0SwlqKY8Qqp+WH3WwHhnIEJ7EDat2Y5ZJzMp28GUPAdTch24TaPbD5PeaqXsxFMoO/EUIOnY176zlvr1q2neVUu3t4sOfxObNzRh+nAl9mCCLJODorLxuCdMxDauEuvYCpRDaDCQn2Xh3BMrOPfECsLROFt29PDxZ+2sq+5gzdZ2IGlpPjcVhZpY9uWzNBfsP5qmsbt/maZpJBKJdHbFnnC73fzrX//igw8+YNWqVVx00UX861//GrGtbrfuAHp7ewHIysra4/oHRAkkywT+7//+L53q1tHRQU5Ozl73cX+WnzRpEgsXLuTtt9/mgQce4NNPP+V73/ser7zyCu+99x5vv/02jz/+OK+88krGunYnnurXbqjZiCRJez1/u6cm9vf3EwgEhq1/4Hrsvr5YLJYeP5Dt7s55553Ht7/9baqqqjjppJMwGo0kEgm+/e1vp40dfD4fiqLw7LPPZizb0dGx1wjYvhCiaRTRWcxkz59L9vy5yeLp1jb6NmzEs3Ej3g834opGCTmM9JS56fY2IssKE2ctYMb5/4nVlUMgEMh4+f1+gsEggUCA3t5empqaCKc6WNwdi8WyXwLLYDjyOlsUQDAYTFuENzc3A1BQUMCpp56KPauYurYw//6khRdWPUOxrYvKnD5OyIlBDsTlHJy5CygsmYLNPeaIK44/WHQGInzQ3MOHLT14wjFseoWF5bnMyTbSvvp1try6ilg8hiOoUtIZwqU34jzuFAwzx5AIKKBqaDEFS4Ub61g3loosdJZDJ0AkSULvMKF3mLCUuzLe01SNuC+SFlPJYZhIux//tm6GhkVkky4dmdpdVCnGY/PaHyg6gxVnbhXO3Cog2edYJNiN3zMgohrob3iDgRNrtORQ6EyaTNhyyjDbijMszz/6eD3G0rFs6fKyucvHhg4PACV2M1NzkyJqrGv0olADSLJM4bhJFI5LPvlVEwm6Whto2LqRxupP6OpqoUsLU9u1GXPTJuwr4thCKrlZBbjGjcc2rjIppCrGIO+hVuNgYjLo0tGlQUvzZBrfc2/X8c83tyctzavymDspn5lfQktzwd6x2WyUlpby+uuvp9Pzuru7GT9+PAsWLGDlypVceumlrFq1Cp/Pl7Hsm2++yYsvvsjvfvc7Tj75ZD766CPa2tpQFIVIJJLRdurUqdx11110dXWRm5vLvffey/z58/na1762X/t5/PHH8/e//53vf//71NXV8c1vfpM333wzvY9VVVXU1tayffv2ER/O7Wn5K664grvuuovLL78cl8vFm2++yZNPPklTUxO33norp5xyCgsXLqS/vz9jXY8++ihf//rX0el0PPfccxx//IFHDSsqKujt7aWuro5x48axbNmy9PpfeOEFFi5cSDQaZeXKlVx11VW43W6ampqIRCKEQiHWr1/PiSeeuNdtKIoyYtBgKPn5+RQWFvLYY49xyy23pPfhoYce4pJLLsFoNHL11Vdz0UUXMWfOHG666Sauu+46jEYjN954I9///vdHvOb7g/hHPURIkoS5uAhzcRFF559LIhLB91k1ng0byd6widxOP11ZBmo+fo/qde9RlFfG7K9cRNmk6Xt92h2PxwkGg/j9/mEia+DV3d1NMBgc8WmDXq/f7+jVlzE96FASjUapq6ujpqaGhoYGVFUlKyuL46bNJiRls601yKZ36iiwfMi4nD5OzfMj5YMqGbG6JpJXNBlnzsTDasU82kQSKhva+/igqYfaXj8ScFyug69PKqGws55PXlnGa10NqGi4+1Uq9GXkjp2LMjGHRDB5QyzrzdhnJaNJ5mLHEel0J8lSMlXPZYKKzNxuLaES84YzaqeifSFCTT76P+vKaKtY9MNqpwwpcbWndMMvA5IkY7LmYbLmkVM8F4BEPELQl+o3ytOIr2cbvW0bku1lPVZHSdqtz6AFmVXgYlaBC03TaOkPpwXU67s6eGVnRzIKleNIiqhcB65RjkIByIpCfulY8kvHMu/si0nEY3Q07aJ5x2c01W6ho3UXnarKLrxY69dh/fQD7IE4tpiErawsLaJs4yqxlJUhj2Lnu5IkUVbgoKzAweKF4/GHYmza1snHn3WwoaaTdze2IKcszedMzmfupAIqihzif0jAAw88wJ133snDDz+MXq/n4YcfxmAwcNttt/HDH/6QZ555ZsT+B0855RRee+01zj33XIxGI2eddRYTJ07E5/Pxwx/+kJycnHTb/Px8br/9dr7zne+gqiozZsxIp37tD3fccQc/+clPOP/88wG4//77sdlsfP/73+fWW2/l/PPPp6ysjJycnIwI076Wv+GGG/jRj36ETqfDaDRy1113UVRUxA033MD555+PTqfjmmuuyTj2hQsXUl1dzcUXX0w8Hufkk0/msssuo729/YDOu9Fo5IEHHuCWW24hFotRVlbG/fffj8FgoL6+ngsvvJBYLMYFF1zAmWcmTW5OPfVUzj33XIqLi/erlOG0007jyiuvZNmyZZSWlu6x3YUXXshvfvMb5s+fD8Dpp59OTU0Nl1xyCYlEgpNPPpmLLroISZK47LLLWLJkCaqqcuaZZ7JgwQL0en36mu+phmskRD9NB4kvWtsS7uzEs3ETHevWsaOphk67RFwnY0PPxIopHHf6OdjHVn7ufjs0TSMUCu1RWA19RaPRYctLkrTf0as9ucsci3zR6x6Px9m1axc1NTXs3LmTeDyO2WLF7CymI2xjV5uHfHMn43I8VOZ4MOniaEgYrcVk50/CmVOFxVmCdAg7Cj7UaJpGvTfI+009fNzWSyiukmsxsqDQyeTeNvrXfkDNzk/pNqvoJCOV+kpK86aiJBxoMQ1kCUupE0vKxMHgPjj1E4e6nm1/UGMJYp4wMU9oN1EVJhHI/F7rbIZURCpTVOldJmTdsft52l80TSMa7iPgaUxHo4K+FjQt+RRUb3RgcZQkO+B1lGBxlqLTWwjGEtT0+Njc6WNLlw9PJJmSUmI3MzXPwZRcJ5UuK8phcFGMRSO0N9bRvKOG5h3VdDbvQtNUZEnGgQFrXxBLXwhLKIGi12MdMwbb+AEhNQ5LSTHSITAuUlWNumZPOgpV1+QBIMthSkeqpo/POSyW5qKfpiOXJ554ggULFjBu3Di2bt3Kj3/8Y5YvX364dyuDF198kZKSEmbPnk1rayuXXXYZb7zxhiipOIIQndseBaJpKGo8juezrWx55zW2t2wjJCfQx1QKggrjx00jd85sXDOmo3eMTkQhFovtl7gKBoMj5qEajcY9mloMHZrN5qP+qeHnue6qqtLU1ERNTQ3bt28nEomg6AxEddns6tWjlwOMy/EwMd9LjiXZEa6st+HOrcKRU4Ujezw6vWU0DueIwheJsTpl6tDqD2OQJWa4LUzpbcGxbjXtNVtoc8ok3HnkGssotU3ApCa/E4pVj7UiZeJQ7kI2HPwn5keiaNobajQ+KKQ8YaK9IWIpx79EKD7YUAKd3TisdkrvNqN3HD19UI0Gqhon6GuhdsuHZDkh4G0iEhyM7hktOSkhVYrVUYrZXkRrMMGWrqSAquvzo2pg1ilMzrEzNdfJcbmOAzK6OJhEwyFa67fRvLOalh3VdLU1gaahKDqyjHZsIRVTcw9GbxAJkI1GrGMrhkSkxmEuKhz1Tnj7fGHW13SyrrqDjds6CYbj6BSJKWNz0o58xbmHxjlQiKYjl1WrVvHggw8iyzJGo5Gf/OQnHHfccQdt/S+//DJ/+tOfRnzvxRdf3K91bN68mZ/+9Keoqoosy9xwww2cdNJJB20fDwZLly4dltoIsGTJkkPWj9WNN95IXV3dsPmnn346119//ahuW4imo0w0DUVTVeo2fMSGt1bS1deBompk90bJ7YuRNaYS96wZuGbNxD5+3CF5AjgUVVX3K3rl9/vTRYdDkWV5n+JqIDVw96LMI4X9ve6aptHW1kZ1dTXVNbVEwiE0SaE3YsMfU8h1hJlU6KPM5UGR4iDJ2N1jcWRPxJEzAbPt8HZseahIqBpbu3180NTDJ50eEhqUmRSm9LRQvOZdYtu3E7AaiY4Zj8VSQq6hDJOc7JXVmG/DWplMuzPmj35HvEebaNobiXB8SO1UpqjK6INKltA7jUNqpwbd/nT2o78Pqv1l6LWPx0KptL4mgr4mAt4mYpGUE5QkY7bmY3WWYnGWIlmKqQ9b2NLtZ0uXD28qClXmMDMlNxmFGnuYolAA4aCfll21NO+opmVnDb0dLQAYDCZynLk4VT2WHj/ajia0VD2AYjZjrRybFlG2cZWYCvJH7fsXT6hU7+rl4+oO1lW309SRfLBUmGNl7qR8Zk/KZ2plNnrd6PwfCtEkEBzbCNF0FIumoXQ072LTu69St+Vj0CBXM+Ku78USiqOz2XBOn4Z71kxcM2dgzN6zw8vhIBqN7lVUDdRlhUKhEZc3mUz7lRpoNBoPqbjY13Xv6upi7fpP2VG3jVgkiKpJeKImDEYoy40xLteDRUn+6RvMWThzJuLIrsKeVXnM2YHvjY5AmA+aeviwpRdvJIZV0pjc10bZ6lXYG3YimZ3oq2aDOR+7nIMi6dBkDcsYN/bxOVgrstDZDq2pybEkmvaEpmkkQvGM2qmhbn8ZlumKlOrI15QhqgxuM4rt2OouYV/XPhbxJd36fE0EvUkhlYgnf9skWYfFXozFUYrXUMquqJMaT5wdngCqBhadwuRcO1NynUzJdeA0Hr5050C/l5adNbTsrKZ5RzXenqR7p8lio6CgDLfehq0/itbYSnBXA1rKHUtns6WFlH18UkgZcnJG5TPQ3hNgfSqNb3NdN9G4ismgMH2ULM2FaBIIjm329rk/Mh/fC0Ykv6SCr1z6PU7o+xqffPBvPvv4XTorLOTnFFGsWvF9Vk3PB8keuy3lZUkBNWsmjklVh8QZaW8YDAYMBsMeOywbIJFIEAwG92pu0dLSskdbdkVR9tvYYjQ6FdY0jZodLazdsJmu1nqkRDKFMSHrcLt0jM2P4jI0IKEiy3rsWeNw5EzEkTMRkyVn3xs4hgjHE6xv9/BBUw/b+/xIaIzxdDJ7/YcU76zFkl2GfcJctMqzUWLJm4eQ5kct1Cg6fgK2MTmi9maUkSQJnUWPzqLHXDxSH1TRYYYUsb4wwV19aInB53GSTs5M83MN1lEdi31Q6Y0OXHnH4cpLpgZpmkY01JMWUgFvE90ta9DU9ykGynRm5Oxy2nUV1MeyqO3pZ12bBxiIQjmZmudgrMuKfAjPldXuZML0+UyYniy27vf00LIzWQ/VvKOaem/ShtnidlE861Rynfk4YxJaSwf+uh20vrACLfU7rXc6kk59lYMRqYPxcK8g28q5J43l3JPGEo4mu1/4ONUv1ICleUWRIy2gJpZnHbZInkAgOLoRkaaDxOF46hwJBdm69h0++fANAr4+svKKmTxpDm5/gv5PNuP7rBotHkc2mXBOnYJ71kzcs2ZgSnXWdjSjaRqRSGS/aq/2ZMtuNpv325Z9Tzd169atI69kAhurW6itrSXsbcWqC6GTVcwWKMqRyLP3oxAEwGTNT0aTciZic1UgK18e0wxIXredngDvN3XzcUsvEQ1cAR+Vm9cxblctufnjsZZNAc2BFgMVlb5YO359H0VzJzFhwfHo9EeGTf6XIdL0edG0pGV6zBMeZpse84ZH6IMq05DC4E4aUhypfVAdjGuvqQlCgY5kJMrXRMDbTMjfBpqKpoFXX0Krfhz18RyaQno0wKJXOC7HkUrlc+A4jFEoTdPw9XalBVTLzmqC/mQdhN2VTUnlJIrKx+PW29DaOvHX7cC/vY5gUzOknFwNWVkZjn22cZXonc69bfaA9q+xfdDSvLq+F1XVsFv0zJqYz5xJecyqysdhPbDfExFpEgiObUR63ij/+AQ8jdRUb2LcuPGABJKUusmWU8PU9NDxIUMkCQl5yHID8zKHg8vIGetTEwl2bN3AJx/8m56OZiw2J1PnL6Jq+vFE6nbh2fQJng0bCbd3AGAqKsQ9cyauWTNwTp1ySDs63BOqqpFQVeIJjYSqkUioxBMqidR0PKEODlPjicTg/ERCJZ5eThvSRiUWjxONhIhEwsSiYeLRMPFoiEQsghqPkIhH0BIRSETJ6AAnhYaMKulJoCeu6YmjI67qiKkKgXAUl74ftyGIwxIny6mSn6ViUXyAhqIzYc+egDNVm2QwuQ71qT0i8EVivL+rg/frO+hSJXSxKGN2VDOxoZ7x2WWYssaiRvSggabT6Io20RrYjuaWmHn6V6icMveIcxcSounzoakaMe8QQ4ohoirui2T2QWXWYXDtZkaRElejYe6xv4zWtVcTMYL9LQS9zQR8jQS8zUSCXUQ0PU1aAS1KBY2JfAJq8tjLHCam5rmYmuug4hBHoXZH0zT6OluTImpnDS07a4iEAgC4cgooqZxE8dgqCoor0Dp7kiIq9Qq1tEDqVsSYm5NRH2UbV4nO9sVNHvzBKBu3dbGuuoP1NR14/VFkCSaWZzF7Ut5+W5oL0SQQHNsI0TSKPz7xWJBP3r6TkW62jxQ0QEJO7qGqJf+cEurgLksymqygKbrkOBIaUvIGNjWuDYxroGkSGgybp2qk56ualBoObDL5vqoOzhs6rmm7b4Ph293TML0/uw9HbjNwzJIkIWUMQZZAJ6kosoYsqcioyCSQUZFIIGkJJC2efhqsV1SynSrZjigyUUDC4ijBkZMUSlZnWUanmF8m4qrGxu2NvFvXQi0GNEkmr72ZSe3tzDDlYNblokaT10OfY8av91Dd8D4d/Q0UlI1lzsLzKZ847YhN3RKi6eCjxlXi3iFCyhMmljKkiPdnWqYr1lQfVK7dbdNNyPrR/c4dymufNJpIRqKCvib8nibaIjKNWiGNWjGdWjYaEmZFY5LbxPTCPKbkuQ5rFAqSJkbd7U1pe/PW+lpikWTUP7ughOKxVUkhVVGFokkEdu3Ev30H/ro6/HU7CLcN9iFjKijIiEZZK8eis3x+B9EBS/OPP0uaSdQ1J407sp1JS/PZVfnMmJCLeYTOoYVoOnysWbOG3//+9/z1r389oOX+8Y9/AOzR+e2tt96ioaGBK664Yp9tjyZuv/12lixZwtSpUw/aOh966CEWLFjAnDlz2Lp1K9deey3FxcXMmTOHKVOmsGjRooz2Dz/8MADXXnstzzzzDI8++ihnn302P/zhDw/aPu3O0Ov5eRA1TaOIJJvotlzGrl07cGdloaoqCTWBqmpoqkpCVVFVDVVT0TQVdWBaVZPzVBVV0zKGmjbQPjWNllyfpoKmkQwyaUgMDAfmkR43SiHcUi922YcEBLHh1dxEJVPSOhYVRyKAMx7AmQhgViMgSURlHf16K36dhYDeDLKMJIOSEhSyvNsw9ZIkLTUkPVRkbcj0wP4OaZtSbZKkDe57aprU+IBsI91eG5yX1vuD85PzBl6HBp3BhiN7Cs6cKuzZ49EbDo317ZGIlkhQt6WW97Y384lsIWiyYA4lmNXdzEzVRlYkCwxZSLKMudSFvsTCrs5P+GTd60TCQUrHH8dFS26hqGLiESuWBKOHrJMxZFswZA+/IR7ogyrt8NcXJuoJEdjZSyIYy2irsxsHnf1cJvRZKXHlMh11luk6vRlH9gQc2RPS8yYPGE14m+jxfEKtJ0Z9PJvq7iI2dEeARoqMMSa5DUwvzGNCfhHKIY7USrJMblE5uUXlzDz5K6iJBJ0t9Wl7888+fpdPP3wDSZLIKSqnpHISJZMmUXHOWRiMJuJ+P/4dO9PRqP5t2+h+/4PUypOdxQ+1PrdWjEEZoZPQkZBliQllbiaUufnm2VX0+sJsqEmm8b27sYXXVjegU2SmVGYzZ1I+cyflU3SILM0FB599CaCtW7fud9ujiXvuueegr/Pjjz9Odyj79ttvc95553HDDTfs17IvvfQSd99996hbrA+9ngcbIZq+IOFogif/3Yo3IKNTfOgUCUWW0SkysiyhUxQURU7PVxQJ3cAw3WZwOvn+wLiMTpaQd1tGSW9jcCgPTO+2LTXsp732Q3w1q0lEO8kuqKBy1kKKKqei1+vS21c9vQS3bCbw6SfoN2/GGQyBLOOomohr1kzcM2dgHVsx6v1xHEw0bVBIaQNDTQPUzHlDxJY2dJhqu/s8LbU8aFRXb2PavNOO6c5l90U8GKRjwyZWb2tig2KlM7cIyZTFWJ+f6X1BKvokFHLQOYxYJyQtwVWnyqaP/s3Wle8Qj0UZe9xsZp92LvklFYf7cARHKLJewZhrxZhrHfZeIhJPduo71Da9L4y/ths1vFsfVI7BPqgGaqf0WWb0DtNRY5k+1GiiGJiqaURCPfg9jezo6qC6L0JdyMpb7W7ebO/ERBMVJj9VTh3TCnLIyy7DYDo4tUP7i6woFJRVUlBWyZzTziMRj9HetDNtb/7JB6+z8d1XkGWFvNIKSsZOoqSyioILzk3XMca83iFCqg7v5i10vfNuagMyltISbJUpITV+HNYx5ciGfdcsZTlMnDGvnDPmlROLq1TX96SiUB0se3ELy17cQlGOlTmT8hmfM9yASHBo2bVrFz/5yU/weDxYLBZuv/12pk2bRnt7OzfddBNer5cJEybw8ccf8+6776ajHVdddRW33XYb27dvB+DSSy9l1qxZPPXUUwAUFRXR2toKJCMjK1eu5NFHH0WSJKZOncrdd9+Nfg+mWsuXL+f555/H4/GwcOFCvvWtb/GTn/yE9vZ2JEnixhtvZMGCBfT393PLLbfQ2NhIaWkp7e3t/P73v2ft2rX7tfxHH33EAw88AIDT6eTBBx/EYDBwww030N3dDcDVV1/NokWLWLp0Kddccw3z58/nj3/8IytWrEBRFE488URuvvlm2trauOaaaxg/fjzV1dVkZ2fzu9/9DpfLNeIxvvDCC2zZsoU77riDyy67LB2VMxgMNDc3M2/ePBYvXsyyZct45plncLvdOBwOpk2bxu9//3s2b97MXXfdxR133MGpp546bP01NTXcdNNNvPTSS0BSlD399NP88Y9/5LHHHuOVV14hkUhw0kkncfPNNyNJEn/5y1/4xz/+gaIoLFy4kIsuuijjel588cUH/PnaG0I0fUFMssTPirKIxGM4it3Jp6RZFgzZZgxZFmTDEZCaNWsc0cglVK97j00fvM76lx+nLjufGSedRdWsE9EbjOAqhjHFcN7ZqPE4/m3b6duwkb4Nm2h88u80Pvl39E4HrpkzcM2ciXvm9INWsDtaDNaHwajdCuk6vpSCKdTWTu+6dWyp3sknBge7KqqIF4wnKxLjtK4ok3vj2FQdpmIH1inJTmYN2Ra8PZ2sefdFajZ8gKZpTJh+PLNP/Q+y8osP9yEJjmIUow4l34Ypf3g0IBGKDUaoekNEPUlBFW7tRI3u3geVaTDNzz1om66zH9quDA4USZIwWXIwWXLIKYL5JI0muj1tfNraytaeKHVBO9UdBp7viJLHGsboe5nokKjMycHuKsXiKDmknWYrOj3FFRMprpgIQCwaob2xLm0ssX7Vv1j39koUnY6CsnEpETWJvGlTcc+amV5PtLcP/46kyYS/bgd969fT+dbbyfOiKFjKyzIiUpay0r26yep1MtPG5TJtXC7fuWAK7T2BtJnEqx/VE5vu4LRRPTNHJp1vvUPHm2+NyrrzF51O3umn7Xf7m2++mSuvvJKzzjqLTZs2cf311/Paa69xzz33cM455/DNb36Tf//73+mb7wE2btyI1+vlhRdeoK+vj/vuu49LLrmEJUuWAHDxxRenBVZHRwe/+MUvWL58OQUFBdx8882sWrWKM844Y4/71dHRwcsvv4xOp+MHP/gBF198MYsWLaKzs5NLL72UF154gT/84Q9UVFTw6KOPsnnzZi655JIDWv6RRx7hzjvvZNq0/5+98w6Pqkz/932mT2bSG6kQICQBAiS00EsAQZqAICKou1hWRd1VEVxZhNVlLdi7X/dn20VAmgKCFEE6oYROQgoloaT3Nu38/phkkkACoQQCvPd1cWWYU973zJlyPud5ns/Tge+//55jx46RlZVFQEAAX331FSkpKSxZsqRWmtwff/zB77//zrJly1CpVDz77LMsXLiQfv36kZCQwLx582jbtq1DKE6ZMqXO47vvvvtYunSpQ4hVNcCdNm0aM2fOBOzNe5cuXcry5cuRJIkHHniADh06MG3aNHbv3u3Yti7Cw8NRKBScOHGCNm3asGrVKkaNGsWWLVs4cuQIS5YsQZIkpk+fzi+//EJISAgLFixg6dKl6PV6HnvsMYYNG1brfN5ohGi6ThRqJW7R/pw/dgZzbhklqXm1nKFUztrKdBO9I+1E46G/6a5QGq2Ojr0GExkzkJSj+4jfupY/fv6B3euXExkzkMgesTgZ7ZbCCpUKl7YRuLSNoPnkSZjyC8g/cID8/QfI23/AfmdPkjC2ammPQkVH4dwm9KY31xXcPGSrlcKERPL27CXt0DGOGr1IjoiioH1vNDaZtgVWIvPLCZQVGEPcMXTzwKmFm+N9nn0+jX0LfyD5cBwKpZJ2XfsR1XcYLu53l8264Oaj1KtR6tXo/JxrPS/LMtZSc2V0qhxzfrWoKj1TULsHlUqB2lVXbUhRZKH8fBEaT/0tNaS4HJJCibdHILEegcQCNlnmVF4h8WfPcTTbRlyZJ3E5ErqccoKkIwRJ62jtZMLLrRlOrkH2hrzOATfN4VOt0RLUuh1Bre027abyMs6dOuFw5tu9cQW7NyxHrdHi1zzUXg/VKgJv/+Z4dO2CR9cuQKW9e3aOIxpVnJxCzs5dZKzbYH9dVCoMIS1qGU04BQXW+/vVzNPAiN4tGdG7JTabTHz8/pvyegjqpqSkhPT0dIYMGQJAp06dcHV1JTU1le3bt/Pvf/8bgMGDB+PiUrtNQmhoKCdPnmTq1Kn07duXl156qd5x4uPjiY6Oplml23BVdOdytG3bFpXK/n2wY8cOUlNT+eijjwCwWCykpaWxfft25s+fD0BkZCRhYWFXtX1sbCzTpk1j0KBBxMbG0qtXL06dOsV7771HRkYG/fv355lnnqk1r127djF8+HB0lemr48aNY8WKFfTr1w9PT0/atm3reH0KCgqueJyXIy4ujn79+mEw2DMChg4dis1mu8JW1YwePZrVq1cTFBREXFwc8+bN44MPPuDQoUOMHTsWgPLycvz9/cnOzmbAgAE4O9u/27/99lvAHqFqLJrmt/1thKSQcO8aSKoig7adOyNbbfa7mjmlmHLL7H9zSilIr/0jrHRSOwSUQ0x56lEaGrcJpEKpJLRDN1pHduX8qSTit65hz++/sH/Lr4RF9SKq9z24+/jV2kbj5opP/3749O+HbLNRnJJKfvwB8uMPkL5kGemLl6A0OOHWsSPu0fZIlNbLs9GOQXBzsBSX2KONe/eRE3+Akx5+pET2IC12PLIkEVhipefZCiI1WtxDfDD0c0fn71Irxen86WT2bV7FqYSDqLU6ovoOo2OvIRicm3aUUnDnI0kSKoMGlUGDPrD6/WgzV2AtLcKcV0hFdqHdiKKgAktROeXpUJKiQi8rSEs4CFTeGPOyf4drvZwc3+dNIsugBgpJoqWHKy09XBkHFJksHMsq5FBmLkezdCRZWvB7sYxvaT5B51IJkrbhI+Xj5NwMg0uQQ0jpDb43xdxGo9PTIrwjLcI7AlBWUsy5kwl2Z76U4+xY+5NjvYCQsEp3vgg8fQPQenuh9fbCs4f9jrYsy1RkZNRy7Mv6YwsX1qy1vzYaDYaWIdURqdDW6P39L0lHV9wm6ZuNgc/A/lcVDWosZEeafe3nrFYrSqXykmU1cXd3Z/Xq1Wzfvp0//viDMWPGsHr16jrXrRIvVeTm2nuSeXjU31tMV6Omzmaz8d133zlS3TIyMvDy8rrsHBuyfUREBAMGDGDTpk288847HDp0iKeeeoo1a9awdetWNm3axP/7f/+PNWvW1NrXxVgs9rTlmmYjkiRd9vVrCJIk1RpPpVJhMpkus0VtRowYwSOPPEJ4eDi9e/dGq9VitVp55JFHHMYOhYWFKJVKlixZUmvbjIwM9Pob18i6LoRousFIyroLmWVZxlJQgSm3tFJIlWHKLaUoIQtbRXWKiEKrrE7vc6T6OaFyvbHpIZIk4R/SBv+QNuRlnefAtnUk7N/OsT1/0CK8I1F9htZZjC8pFDiHtsY5tDVBE+7HUlxC/qFDlVGoeHJ27ATszXXdojrhHh2FS9uIW95cV9Awys6dI3fPXvL27KPw2HHyPfxIjepL0vielKqUGMw2uuda6GJwonlrPwwt3VG71i6+lmWZtORj7Nu8irOpCeicjHQfPIbIHrHo9JfWowgENxpZlpFN5VjLi7CVFWMrK8ZaXvm3rBhb5fP2x5V/Kx/Llsv8wCuUqLRGrOUSksIDyakFCnUrzPlWys7k12roq3Kxiymtp1OlqDLYI1ON7OzXUJw1KroHeNA9wAObLHO6oJTDWYUcyTKwL9+dvUTipLTRoiyPgOKTBKTHo5NMSAo1Ti7+GFyC7dEol0C0Tl6Nnr6oNxhp1b4LrdrbI0olRQWORrtnU45z8vgBAHQGI4EtIxzufG5ezezpi82aoWvWDK/evQC7u1/5+Qt2k4mkZEpSUshYv5Hzq34FQKHTVYuoVq0whra6I3oc3u4YjUaCgoJYt26dIz0vOzub0NBQevbsycqVK5k0aRJ//PGHI32sio0bN/Lzzz/z4Ycf0qdPH3bu3Mn58+dRKpVUVFTUWjcyMpK5c+eSlZWFt7c38+bNo3v37owfP75B84yJiWHBggU8/fTTJCcn89BDD7Fx40bHHMPDw0lMTCQpKanOz0592//pT39i7ty5PProo7i5ubFx40b++9//kpaWxiuvvELfvn0ZMGAARUVFtfb1+eef88ADD6BSqVi6dCkxMTHX8OqDUqnEaq2/rq9Hjx48//zzPPvss2g0GtavX19n/VJ9+Pr64ufnx1dffcXLL7/smP9HH33EhAkT0Gq1PPPMM4wZM4YuXbrw0ksv8dxzz6HVannxxRd5+umn6zyfNwohmm4SkiTZC47ddBhaVt+pkGUZa4nZLqayq6NTJal5FB7JrN5epaiOSnnoUXvaf4xvhBuUu7cfA8Y8QvfBYzi863cO79rI8v97C5+AFkT1HUqrdl1Q1JO6oDIa8OrZA6+ePZBlmbK0NPIqBdT5Vb9ybsUvKLTayua6nXCLjkLv51fnvgQ3H5vFQtHxBHL37iM3bi/l585hcwvgbOf+HI8azjm9CoUsE1om002rp2Mbb5yD3eu8iy7bbKQej2ffplVknj2FwcWd3sMfpF23fva6OYHgKpFtVmwVpbUEjv1xUbXYKS/BVlbkEEVVz2Or/4ddUmlQ6I0odEaUeiNq92Yo/Y2Vzzmj1NsfK3WVz+mNKHXOSBodkiSxf8cWWuvKKUnYRdmpzSDbULv4og/tjcorEll2sd8Yyy6l7HRtMaV21TkiU46/HrdWTCkkiRA3AyFuBkaF+lFUYeZodhFHsgo4mqXmmNkTiS4EOUGItoBA82mc03bBma0AKFV6nFwDMbhUpvW5BDW60YTB2ZU2HbvTpqM9mlSUn1Or0W7y4T329VzcHAIqsFVbR0qwpFCgD/BHH+CPd78+gD0Nuezs2VoRqfOr1yCb7e6MSoMBxYhhIFoN3FLeeecd5syZw8cff4xarebjjz9Go9Hw97//nRkzZrB48WLCw8MvSc/r27cvv/32G8OHD0er1TJkyBDCwsIoLCxkxowZeHlVp4v7+vry6quvMnXqVGw2G506dXKkhzWEWbNmMXv2bEaOHAnA22+/jdFo5Omnn+aVV15h5MiRBAcH4+XlVSvCdKXtX3jhBWbOnIlKpUKr1TJ37lz8/f154YUXGDlyJCqVimnTptU69gEDBnD8+HHGjRuHxWKhT58+TJ48mQsXLlwy7pXo06cPr732Gm+99VadyyMiInjkkUe4//77cXFxwd/f/6rHGD16NO+//76j9mngwIEkJCQwYcIErFYrffr0YcyYMUiSxOTJk5k4cSI2m43BgwfTs2dP1Gq143zWV591rYg+TTeIxujdYC0z10rxq4pOWQprKGiFXYzVrJe63h9hi9lEwv7txG/9jYKcDJzdPOnYawhtu/ZBo2146NNaXk7BkaPk748nb3+8o++Grlkz3KLtUSjXyPYNtoltityOvXrMRUXk7z9A7p495O0/gK3chNozhIL2PTjq40uiswqzQsLbCt2MBnq38cXT37XeO8lWq4Wkg3Hs+2M1eZnncPXwIbr/vYRH9USpunMjjLfjub9VyFYLtvKS2mLHIXCKakWCaj0uL+Fy7QMkjd4ucCrFz8Wip+bzSp1z5XMGFOrr+z2oee6tpUWUJu2h+PhOyk4eApsFpbMnhvAYDOExaP3bYCkwUZFTeWOs6m9eWXX9q0T197iXwRGdUrvrUahurdGMTZY5VVDKkcwCjmQVcqqgFBl7pCrcTUUrXTEBtnRsJacpK74Asj01R611cQioqojUzTKakGWZgpzMSnvzBNJTj1NWbI86OLt72QVUywgCWoVjdHG/7L5sFgulZ9IoTk6h9NRpcvx86TpyRKPNXfRpuna+//57evbsSevWrTl69Cj/+Mc/WLZs2a2eVi1+/vlnAgMD6dy5M+fOnWPy5Mls2LChyTVvv5sRzW1vU9FUHzaT1S6mHKl+9giVOa+s1vWFylXrSO+rme6n1DUswCjbbJxKOEj81rWcO3UCjU5P+2796dBzMEbXy//Q1EXZ+fP2NL74eAoOHcFWUYFUaTrhHh2FW3QUTsFBTdql6mJuhwtnWZYpO3uW3Li95O3dR+HxBJQaZ/T+bbG2iOSIqyuHXVXkaxVoZYhydqJvGz9a+7pc9lxYzGaO79vK/i1rKMrLxrNZIJ37j6B1+/ojk3cKsiyzf+8eOnftdqunclOxmStqRXPsAqeojueqBJA9AiSbyi+zVwmF3lApcJwvEkAXi56a6xmQlLcmWaK+z721vITSpD32CFTKAWSrGaXBzSGgdMFtHfVAstWGKa+y/jW7pLaYcjQex+7i51kzzc9+U+xW9ZuyR6EKOZxVyNGsQkrMViSgpZuBdl4GWjuV42Y5T3lhGiWFaVSUZju21Tp51RZSN8loQpZlcjPPcTbluF1IpSZSUVYCgJt3M4czX0BIGHqjy2X3JZrbNl3++OMP3n33XRQKBVqtltmzZ9OuXbsbtv9ff/2VL7/8ss5lP//8c4P2cfjwYV577TVsNhsKhYIXXnih0fsWXS1Tpky5JLURYOLEiTekj9WLL75IcnLyJc8PHDiQ559//rr3f70I0XSHiab6sP8Il9kjUjmllaKqDHNuaa30EKVBc1HNlP2x0kld70VyRloq8VvXknJkL5KkILRjd6L6DMXLL+ia5mozmyk8nuCIQpWePgOAxtPDbmkeHYVbxw6ojE27BqYpnPe6sFksFB47XimU9lJ+IRO1iz+GFh1RuoeQ7KTjsJuKk0YFsiTR2klHn1Y+dPb3QHuFizFTRRlHdm/mwNa1lBYX4hvUii4DRtAivONtJXivBdlipvjYNgp2r8SUeRql0QOVmw9qNx9Urj7Vj918Ubl43pSC+avFXu9TdqnoqRI7tWp/rq7eR6l3rhY7OgOKyv9XpblVRYUUeufqxzqn2862vyGfe1tFGaXJ+yhJ2EVp8j5kiwmFkwuGNt0wRPRA37x9naJPttqqMwyyS+0RqpzS2jfFFBIat5ppfgb7X/eb27zXJsuczC/lSFYBh7MKOV1QCoCLRkU7bxcivV1o46ZGKjtPSUEapYX2hrzmisoLMkmB3tisOq3vJhlN2Gw2ci6kOdL5zp08gblS2Hs2CyKwMp3PPyQMrb52dEyIJoHgzkaIpkb88rFabXz363H0ch4TR/ZqkheNsk3GXFheneJX9SOcW1arT4lCp6rt5lf5WOVSbUJRmJvFge3rOL53K2ZTBUGt2xHVZyhBoe2u69grsnPIP2Cvhco/cAhrSQkoFDiHtbELqKhOGFu1bHLNdZuSaDIXFpG3bx+5e/aRH38Am1lG69UKY4uOKDTeZKkVHHZXc8xdRakEbhoVPYO86BXogY/hyimSZSVFHNqxgUM7NlBRXkpQ63Z0HjCCgDoMQ+40rKWFFO5fR+HeNVhL8lF7B1HoHIS3UYslPxNLfgaWolxHahJgNw1w8UTl5ovaIah8UbnZHysNbtf1ujWs3qe2+UGVAKo1z4uoqvdRVqa6XUn0VEWCJLXujn8fVHG1n3ubqZzS1HhKju+0CyhTOQqdEac23TCGx6AP6YB0hVRWm8WGObf0kjQ/c36NKJ5CQuOur1UzpfW0p/ndjMa9hVVRqMxCjmVXR6FauRto7+1Ce29Xglz0WCoKHQKqpDCN0oJ0rJYygEqjiYBaQkqr92zU95bVaiHr7GlHPdS5U0lYLWYkScLbv7nD3ty/RRsOHT4iRJNAcAcjRFMjfvmUVVj42/t/cDarmNZBbjw4JIyuEb63xcWDLMtYi+259uaLaqesZWbHepJKUZ3iV5nuJxvgROIuDu7cQGlRPp7NAunU+x7adIxBqbq+lBnZaqWosrlufvwBipNTQJZRubjgHtUJt+hOuHXqhMbt1ttW30rRVGW8kbtnH7l79lKUeAKV3hN9QAT6ZuEgG6hQQKK3lsOeas5iQylJdPJ1pVegJ+28XVA04H1aXJBH/Na1HI3bjMVsomW7aDr3G45vUMubcJS3FlN2OgVxqyk+vBnZYkLfMgrX7iPRNI9k6469RHXqiFqlQKVSoMSKXJyLOT+jUkhlYi7IdDy2luTX2rek0qBy9Ubl6o3S6I7SyQWF1glJrUVSqux1QDXrfmoJoJIr1/toneoQO1UCyLn2c46oz/XX+9wNXM/n3mYxUZZ6kJKEnZSc2INcUYqkdcIQ2gVDeA/0LTte1Tmwma21IlMOMVVQLaYkpWRP87vIzU/tpms0MWWPQpVwJMsuok4XVkeh2nu70N7HlbZezhjUKrsleGk2pYXplULqDKWFZ5FtdlvkaqOJYAyugRhcg1FrL59Gdz1YLWYunElx2JtfSEvBZrWiUChp1XUQ99w3sdHGFqJJILi1CNHUyF8+FquNb5ZuY3dSBRm5pbQOdOXBIeF0bXt7iKe6sJaaHel9NVP9LEUXmVC466hQlHE+O5nswjRsOiutunelXY/+N8xe2lxQQP6BQw4RZa5svmZo1bJSREXhHNYGxXWKtWvhZosmm9lM4dFj5MbtJXfvXiqyctG4BWNo0QG1cxDYVMjAhUADRzw1HLGYMMsyAc46egd60T3AA+cGNuPMz85g/5Y1JOzfjizbaNMxhs797sXDN6BxD/IWI8sy5acOk797JWUp+5GUaoyR/XDtNhyFRyCb96Wz5PcTnM0quWRbhQQqpYRSIaFWyCgVoJJsqLChlUy4U4iHVIgbxbhShItUgotUhrOiDI1U2+3NLCsplTWUo8Wk0GNSOmHRGLFpXLDp3VDpDWh0OtR6HRqdExq9ExonJ7ROBjR6A2qNGpXSLujUKoX9sVKBSindtt9LTYUb9bmXLWbKTh2i+PguSk/EYSsvRtLocGrdGUN4D5xaRaHQXJtRjs1srfz+LqlO88uubSQkKSXUHjX6S1X+VbveeDFVWGHmSFYhR7IKOZpdSKnZikKy10K193Yl0tuFIBe9470p26yUFV+gpDCd0kohVVacUcNowhWDayBOlULKySUIlbpxerSYTRWcP53MhdNJVCic6DNwSKOMA0I0CQS3GiGablJNU8dOUWzel8aiDSe4kFNKq0BXJg4Oo3u7ZnfMRYrNZKkhpGqk+hWUO256y7KNMrkEhbMKj5YBOAd42n+IPfQotdcZhbLZKDl5ivx4eypf4fEEsNlQOjnh1jESt+go3KM6ofX2vgFHe2VuhmgyFxSQt28/uXF7yT9wENmmQucdilNwJAqVO8gSklqJuYULxzw17DWVk11uRq9S0t3fnV6BnjR3dWrwezD7Qhr7Nq8m+VAcCqWSiM59iO47DBePm/Oa3iouqVcyuOLSeSgu0fdg0xrZsPs0SzYmkllgIthoJkp7Ep0SzCYzZrMZq03GIiuxosAiK7Bgf2yVFVhQYVNqsCjUWCU1NkmFRVJhRYkVJRZZgUo24SyX4EIRrhThJhXjRhGeymI8FMWXiKoim44cm5Ecq5Fcm9HxOMfmTJ7NgI36U1lVSgmVsoaYqiGq1CoFasdzUq3nVVXLamxTLcikWuKs5r6rt5FQK5WoVLX3W0vUVT5WNuFGoo3xuZetFspOH7VHoBJ3YystRFJpcGodbRdQrTujuAr30vqwmayO7+2KGpGpmjfEHC0uqvpLVUaoblS/QKtN5mRBCYczCzmSVcCZQntqnqtWXZnG50JbL2ec1LV/L2xWE6VF5+z1UQV1GU14OwRUYxlNiJomgeDORoimm2wEYbHa2LwvncUbTnA+p4SWAXbxFNP+zhFPF2Oz2DDn2UVU/unz5KSkYyuyYlC4oJCqi3pVRk1ljym9/Q6npxNqTydUTtf2w2YpKaHg0BHy4uPJ2xePKdv+A6oPCsQ9Oqq6ua5Gc0OO82Ia5eJJlik9fcbRZLboRBJq52bo/dui8wkF2X7nWe2mQxviTqq3lriyMo7nFCED4Z7O9Ar0JLqZG5qrKAq/cCaFvZtXcer4AdQaHe1jBtCp1xAMLm439PiaGnXVK7l2G4k+uB1F507x2+7T/JqkIN+sobkyi3v0h2jvXIDJyR1XH3+H+UHtnj61U+Ak9bVdbMqyjNUmYzZbMRXlYcrLwJyXiaUgA2tBJnJRNnJRNpTkINWoU5KRsOrcMOs9MGndKde6U652p0ztRqnajVKFAbMVLBYbZqsNi9WGxSJjsdowWyr/X99jiw2LVXZsZ7bYsNlu/M+IQgKVSolaKdUSdXUKuMp16hJttQWZ5NimwYKxxnNVf48dOUT3bl1u+DFXIduslJ85RknCLkoSdmEtyUdSqtG37IQhIgan0K4odTfWJKfqhlhFdkl1ml9OKZaiavMPR6q2V203v5p1r9dCgSMKVcCxrCJKLfYoVCs3I+29XYj0cSHQWV/nGBZzaXVaX6XZxCVGE65BGFxujNGEEE0CwZ2NEE23yD3ParWxeX86izac4Hx2CSH+Ljw4JIzu7fxQNOG7qDeK4oJcDm3fQMqefWisOvy9Q/Hzao3GosWUW4Zsrr7IU+hVl7j5aTycUDlrGvxjLMsyZeln7Wl8++MpOHoM2WxGodHgGtneHoWK7oTOz++Gidcb9QNqM5koOHLULpT27sOUW4jGvQWG5h1QOfmDrACFhD7ABUMrD/J89ewuLGH3uVxKzFY8dGp6BnrSM9ATb6eGv9dlWSY95Rh7N63ibGoCWr2BTr2GENkz9oalVzZVLq5X0vq3RuPTHEtpEYVnT7Il24ffy9tSLOsJdSrgvgiZTu2D0QWEofbwY//+/U3GBES2WbEU5VTXUlXWVZmr6qmKc2tvoFShdvW2m1K4+lY6/tld/9RuPij0zlf1GbHaZKwXiatqwSVXCi27QKstvqrWlbFYrJitsuM5S439mGutX0Pc1RR9leuYL95vjXndSJx0KlwMGlwNWpwNGvtjoxaXqscGDS4GLa5G+/+ddOpr+t6XZRsV6YkUH99pF1BFOaBQoQ+JxBDeA0ObbiidnG/osdXEWmG5pF6qIqcUa3ENMaVWovHU10jzs7v5Xc33t2M8m0xqfglHsux9oaqiUG5atcORL8LLBafL9CE0lRdc2WiihpC6GqMJIZpuH0aPHt1gK/CGMGXKFKZNm+Zounonk5aWxueff868efMafaxXXnmFadOmERDQNFL/hWi6xZbjVquNP+LTWbT+BOeyS2jh58LEIWH0aH93iCdTeRnH9m7h4Pb1FOXn4ObVjE6976F1685YCy01+k3ZI1W2cotjW4VGidpDf0m/qYbk3FsrKig8cpS8/fHk7T9A+blzAOia+eIWZXfkc+vQHqX+2lNerucH1JSfT97effa0u4OHkBQGdN6tcQpsh6RwASSUejVOLd0xtPRADjCyL6eI7Wk5nC4sRaWQiPJ1o1egJxFezg0ydahCttk4efwAezevIjP9JAYXN6L6DKVt135otLdvs+ErIcsyZScPkr9tCeVpx0FSoNDqsZWXAjKlNg3bpC5sKgqh1KKkY3MDDwxrT2Ros0v21ZScE6+EzWLCUpB1kUFFtbCylRXVWl/S6FC5+jjElNrNt4aluu8NSRO72VRF7WoKOItFxmy1OqJndYu+GgLOKmO2WElJPYPR1YvCEhMFxRUUlpoqH5swma11jq9QSDUEVbW4cqkUVS4GbaXQqhZfmouEgSzbqDiXbE/hO74LS0GmPZrSItLeCyqsO0rDzTHIsZZXiamSWml+1tJqEyGFRlmrVqoqQqU0NlxM5ZebOZpVyOGsAo5lF1FmsaKUoJV7ZRTK24WAeqJQVVQZTdgFVKWQqmk0oXbC4FKd1mdwDarXaEKIpruXu0k07d69m08++YQffvih0ccaOHAg33//PYGBgY0+VkMQoqmJ9GmyWm1sOXCWResTOZtVKZ4Gh9Ej8u4QTzarleQje4nfupass6fQG5yJjBlIZMxAR0NBWZYrTShquPlVPq51Z7PKDeoie3S1ux6Fqu6UtPILF8iLP0D+/gPkHzqMrbzc3lw3ItwRhXJq3vyq7oxezQ+oLMuUnDzlEErFyalo3ILQ+0eg9WwJsj2FUOtjwNDSA0MrD9Q+Bk7kFbMtLYf9GflYbDKBznp6B3kS4++BoYGmDlXYrFaSDu1m3+bV5Gaew8XDm879hhMe3RPlFSyPb1cshTmUpx2n6PAflJ85imyuUbuhdUIXEEaFZ2t+z/Lht6OllFZY6d6uGRMGtaFNcP1NnG8n0XQlbBWljqiUpeDSSJVsrt2cVqF3rh2dcvVxWKmrXL1RqBonHbapcLlzX26yUFhsF1GFJSYKSiqqHxdXPy6sfL6oxER92Y06jRKXSgFVJaiqolfOThoM5jzUWQko0vajLzqLXmHGqXmEPQIV1h2Vs0cjvgp1Yy0z1zKecIipGo6sCm1tMaWtjEwpDfX3CgR7FCqlRhQqrSoKpVMTWVkLFeHpgv4yUagqahtNnKGkMK0Oo4mqRrzVRhN3q2g6uDedA3FnGmWcTt2C6djlyhfMu3fv5ssvv0Sn05GSkkJYWBjz58/n008/ZefOnRQUFODu7s7HH3+Mt7c3YWFhHD16lP79+7NixQq8vLzIz89nxIgRbNq0iZ07d/LRRx9hsVgIDAzk9ddfx929/u/8KVOm4OPjQ2pqKrIs88orr9C9e3cyMjL4+9//TlFREVlZWQwfPpyXXnqJSZMm8fTTT9O7d29kWeaee+7hhx9+ICMjg3//+9+Ul5fj7u7O3LlzCQoK4ptvvmH58uUoFAo6dOjAP//5z3rnIssy8+fPZ8OGDSiVSh544AEeeeQRTp48yezZs8nPz8fJyYlXX32VDh06MHPmTLp168bYsWMBCAsLIzExkY8//piMjAxOnz7N2bNnGT9+PE899RQjR44kPT2d++67j9dee63OOfz73//Gx8eHqVOnAvDcc88xYsQIoqOjmT17NhcuXECSJF588UV69uxJfn4+r776KqmpqWg0GmbOnMnhw4f56KOPCA4O5n//+99lX/+bxeVE061pp36XolQqGNA5iL5RgWyNT2fh+hO8+f0emjdzZuKQMHpG+t/R4kmhVNKmY3dCO3Tj3MlE4reuJW7jz+z741fCo3vRqfc9uHs3Q2XQoDJocAqqfcfUkSZS2bC3IqeUigvFFCdWFwIj2Wt96kr10zVrht+wofgNG1rdXLfSUOL0dz9w+rsf0Hh44BbVCffoTrh27IDa+frSXqwVFRQcPkLenr3k7tmHpagCjUcITsFd8Okz3G7ioFLg1NwNQ0sPnFq6o3bWklNWwbr0XHYknCanzISTWkmfIC96B3oS7Op05YEvwmI2k7B/G/v/WENhXhYevgEMeeBJWkd2RaFseg1YrxWbqYyK8ylUnE2i/FwS5emJ2GpYfUsqDboW7TG264s+OIJCpTsr/khhzaZTmMxF9Orgz4RBbQjxv/V29jcThdYJrW8LtL4tLlkmyzK2sqJKAVVDTBVkYMo4RcmJPWC11NqmVtPfi/pTqZybZtPfG4VOo0LnocLHo2GfU6tNpqTMXKegKiiu8bjERFpmMYXFFZSbakaznIDeAEjIGArMGA5mYlQswcWgxs3TEw//ANw93eqMcumu8sbLlVDq1eiDXNFf9P1tKTVjyi6plepXnJSD7VCGYx2FTlVnzVRV43WlQqKNh5E2HkbGhgWQX25yOPLtPZ/H1rQcRxQqsrIvVIBz3f3DJIUSJ5cAnFwCINAeObBZTZQWnq3h2JdGfuYRxzZaJ29Qtbuhr5fg6oiPj2fNmjX4+PgwYcIEFi1aRGpqKgsXLkShUPDyyy+zcuVK/vznPwOgUqkYOnQoa9euZfLkyaxbt45BgwZRVFTEu+++y/fff4+rqysLFy5k/vz5/Otf/7rs+E5OTixfvpyEhASefPJJ1q9fz6pVqxgxYgRjxoyhqKiIfv368ec//5lx48bxyy+/0Lt3b/bu3UtwcDDu7u48/vjjfPHFF/j7+7N161b+8Y9/8PXXX/Pll1+ydetWlEolc+fOJSMjA19f3zrnsXbtWvbv38/KlSsxm81MmjSJe++9l+nTp/PEE08wZMgQDhw4wPPPP89vv/122WNKTEzkf//7H0VFRQwaNIiHHnqIWbNm8cknn9QrmMCe/jhr1iymTp1KcXEx+/fvZ/78+cyYMYNx48YRGxtLZmYmkyZNYsWKFXz44YcEBwfz6aefkpiYyOzZs1m0aBELFy7kq6++ahKC6UoI0XQLUCok+ncOok9UIFsrI09vfb+X4GbOTBwcRq8Od7Z4kiSJgJbhBLQMJzfzHAe2/cbxfds4uucPQiI6EdV7KH4tQi/5oVNqVej9XdD7106bsJmtlSYUtaNTJal51LyFq3LWVosoTye0HsEETQinxSNTqMjJJf+APQqVuzuOzI2/25vrhobiFt0J9+goe3PdBggMU24euXvtJg75Bw+j0Lih82mDa8RYJMlon4uL1hFN0ge5olApMFttxGfks/34GY5n29OlIrycGRvmT5SvG+qrMHVwzKWijCO7N3Ng22+UFhXgG9SSPiMn0SKsQ5NrFHy1yDYrpqw0Ks4lOUSSOTvdcadY0ugdUSVtQBvce92PvnU0kiSRmVfKgk3JrNu9D6tNpn90IPcPDCXIt/FqQ25XJElC6eSC0skF/FtfslyWbViL8ursT1V+5hiWo9vqaPrrZRdUjdD093ZDWSNtr6FUmK0U1YhcFdQQWoXFJvJz88nPyeVCYRnJJ0spST2DjfQ696VRKx11Vy5Oteuy6opyORs01+RsqHJSowp2wynYzfGcI7OgRq2UKbuU4sRsCmumaetVdhFVK9XPgJuTht5BXvQO8sJik0nNL+ZIZiGHswpZmniOpYnncNepHY11IzydLxuFUig1GN1DMLqHOJ6raTRRVnSOirLb+3vzWunYJbBB0aDGJjQ0lGbN7OnSrVq1wmg0MmPGDH766SdOnjzJgQMHCA4OrrXN6NGjmTdvHpMnT2bVqlX89a9/5eDBg5w/f56HH34YAJvNhqvrlW+W3X///QCEh4fj4eFBamoqU6dOZdeuXfznP/8hKSkJs9lMWVkZw4YN4/3336esrIzly5czduxYTp06RVpaGk899ZRjn8XFxahUKqKiorj//vuJjY3loYceqlcwAezZs4dhw4ah0WjQaDT8/PPPlJSUcObMGYYMsVvid+rUCVdXV1JTUy97TN27d0ej0eDp6YmbmxtFRUWXXb+Ktm3bYjKZOH36NPHx8QwYMACNRsOOHTtITU3lo48+AsBisZCWlsaePXuYP38+YI90LVq0qEHjNCWEaLqFKBUS/aMD6dMpgO0Hz7JwfSJv/7CXIF9nJg5uQ6+OAU3advdG4OHjz8CxfyJm8FgO7/qdQzs3cvJYPL6BLYnqO5SWbaOvGAlRqJVofYxofYy1npetNsz55Zf0myo4eAG5RlG40kldmd4XjG9sOIHjHsFcmEnBsUPkx8eTtnAxaT8uQuXsjFtUR9yjonCL6oim8q6ILMuUpKSSW5l2V3oqDY17C/T+4Xh1jwFZBRLoAlzsQqmlOxrPagvwMwWlbEvPYffZXEotVjz1GkaE+tEr0ANP/bWlZ5SVFHNo5wYO7dhARVkJQa3bMuSBJwloGX7bXpBaCnMoP3eCirNJdqF0PtWRNqbQG9E0a43GNwRLTjoV51PAasG540Bcuw1H423/ET2XXcySjUn8vjcNSYLYrsGMGxCKn9edbXrRmEiSApWLJyoXTwhue8ly2WrGUphTW1RVPi5N3ou1pKD2/lSayjS/qkhVbaOKG+0adzuiVSvRuunxcrtybZkp5xxFx3eRfWwXeRfOU2LTUe7WHLN3OBWuwZTIuhpRrgrO55RQWGKitNxS5/4kCYx6NS41IlZVQsu1Rn1WzWU6jbLuaI8kVWcWXCymSsyVtujV0amihCxsFdVRNqWTupaQCvJyolVzH8aGB5BXFYXKLGRPjShUaw8jkd6utPd2wd9YdxSqJiq1Ey6ebXDxbAPYUzMFt46aKYuSJJGXl8fUqVN59NFHueeee1AoFFxcdRIZGUlBQQGHDh0iIyOD6OhoNmzYQHR0NF988QVgT4ssKbm0997FKGtcj8iyjEql4s033yQtLY0RI0YwaNAgduzYgSzLODk50bdvX9auXcuuXbuYM2cOqampBAYGOgwqrFYr2ZWuv5999hkHDhxgy5YtPPbYY8yfP59u3brVOQ/VRX0p09PTcXV1veTYZVnGarUiSZJjmdlsrrXOxa/p1VTtjBo1il9//ZX4+Hgef/xxwC5Av/vuO9zc3ADIyMjAy8vrkjmnpKQQEhJy8S6bNEI0NQGUCom+UYH06hjAjoPn+HF9Iu/8dx8L1yfywKAwene688WTk7Mr3QePIbrfvSTs386Bbb+xdsFnOLt70anXECK69LlqgwJJqXBElQitfl6WZSyFFZfUTF38g6zQBOPRKRyfPiosZXmUn0uh4Oh+srdsB2QMLUMwGZzY+8kXWMtkNJ4tcQrohcHfA5BQ6FQYQuwmDk4t3FDqq2uGik0Wdp/LZXt6DmmFZagUEtHN3Ogd6EmY59WZOtSkuDCPA9t+4+juzZhNFbRsG03n/sPxDWp5Tfu7Vdgqyqg4n0zFuSTKzyZRcS652gFOqULrG4Jzx4FoA0LR+rag/FwKhXErKT95AKXBFfe+D+ASfY+jKP7MhUJ+2pjElvh0VEoFw3q2YGz/ULzdbz9Dg9sNSalG7d4MtfulZhoANlM5loJMLPlZdjFVUF1LVZGegK2itNb6Cp2hRoSqSlxVR6oU6ltbB9LU0Hj649l7LJ69x2LOz7DbmB/fScWp/9qX+zS3m0iE90DjHeTYzmyxVqcLFteuz6qZSpiRW0pSWh6FJSYs1rovttQqRT0GGNoaQqt6ubNBg8po/+fU3M2xH1mWsRabLqmXKjqaia1GyqLSYBdT4V5OdPA0oGzrSZpS5lhBCYezCliScJYlCWfx0KlpXymgIryc0anu3LTROxVJkujWrRsPPvggRUVFzJkzhwEDBlyy3siRI3nttde49957AejYsSOzZs3i5MmThISE8Nlnn5GRkcGbb7552fFWrlxJ+/btOXz4MMXFxTRv3pzt27czd+5coqOj2bVrFxkZGdhs9huz48aN429/+5sjCtOyZUsKCgrYu3cvXbp0YenSpaxcuZIPP/yQSZMmsXTpUqKiorhw4QKJiYn1iqauXbvy/fff8+CDD2KxWHjsscf4/PPPCQoKYt26dY70vOzsbEJDQ3FzcyM5ORmADRs2XPF1VSqVWCx13zi5+HV94oknMJlMdOlib8MQExPDggULePrpp0lOTuahhx5i48aNdOnShV9//ZXw8HBSUlJ4/PHH2bhxI0qlEqu1bgOdpoYQTU0IpUKiT1QAvTr6s/3QORauT2T+/yrF0+Aw+twF4kmt0RIZM5B23fpz8ng88VvXsnXVAuI2rKB9zAA69Bh03X2DJElC7apD7arD0LK6ULpWqkgNN7+ys8VYSwBa4RreCtqCpDRjKclGKshF37YvkmQXdBovJ0fanc7PuZbDn02WOZ5dxPb0HOIrTR2auzgxqV0Q3fzdMaiv/eNYkJPJ/i2/cnzfdmTZRpsO3YnuPxxP36Zh4Xk5HGl2Z0/YRdK5JMxZ6VR1S1a5N0Pfoj1a/1D7P98WSCq1o79S7obvHP2VvIY/jbF9H4cRQerZAhZvOMGOw+fQqpWM7teaMf1a4e5y5zoE3m4oNDo03sGOaODFWMuKK1P+akeqzDlnKUuJR7aYaq2vNLg5BJTdoMIXlZu3XVi5eCEp796fPbWbL24xo3GLGY2lMNvRBypvy2LytixC7RVYLaB8muPpqsfTtWE3FmRZprTcUtv8orimCUa18MrIK6WwxERJmbne/Rn06lrW7ZdEsowaXLw9cTX44+6kRmO2Yc4tc9RNVWSXUnA4w9HaQgVEGTXEeDpR5ulCql4i0WYh7lwuW9KyUUoSoR7Vjnx+DYhCCW495eXlJCQkMHLkSNRqNWFhYaSnX5qKOmrUKD788EPee+89ALy9vZk3bx5//etfsdls+Pr68s4771xxvNLSUu677z4UCgXvvvsuarWaJ598kpdffhkXFxc8PT1p37496enpBAcH07lzZyRJYty4cQBoNBo+/PBD/vWvf1FRUYHRaOStt97Cw8ODiRMncv/996PX6/Hz82PMmDH1zmPw4MEcOXKEsWPHYrPZePjhhwkJCeGdd95hzpw5fPzxx6jVaj7++GM0Gg2TJk3ir3/9KyNHjiQmJgZv78s3q2/VqhVFRUVMnz79sq+Ln58f7u7udOrUyfF5mTVrFrNnz2bkyJEAvP322xiNRp577jlmzZrFqFGjUKlUvP3220iSRP/+/XniiSf4+uuvCQoKqnespoBwz7tOTFYb3x46zfmcXDzd7M1EVQoJjVKBWqFArZRQKxSO5+2PpcplCtQKqfKv/XmVovqxEok9Ry+wcH0ipy8UEeBt5IHBbejbKQDlNdS33K6cP53MgW2/kXJ0HwqFgjadehDV+x48m928/GqHvW5u5R3OyuiUubgCQ3N3R9qd2vXSi/Gs0gp2pOewIz2H3HIzBrWSmAAPegV6EuRy9aYONcm5kM6+zatJOrQbSaGkbZc+RPUdiquHz3Xtt7GQZRlrUU5l9OgEFeeSqTif4qg9UuiNaP1D0fm3sUeR/Fpf0oPm4v5K+pZRuHYfiT6kg+NLO/F0Los2nGDPsQycdCpG9m7JyD4tcTXeuO+BO8k973bFnsaVf2l/qipL9YLs2vVUkgKVs0elkLrUUl3p7I4kXfm79U4795aiXEoSd1OSsIvyM8dAtqFyb4YxooddQDVr2SgCwmK1UVRycRSrhhnGJREuExZr3f22VErpktRAF4MGo0qJkwxOFhu6ciu6UjOaogqcbKCSJKzABS8tJ93VpGggo/L9UhWFivRxIdyzOgp1t7rnCa4eWZY5ceIEM2bMYMWKFbd6OoIGItzzGhEZewTBJENOmQmzrbKXh81W+dhGPRkLDUbV3g2fZjqyUgp4b8F+Pv35MAHhnvg1d0WjUjqEWZUIsws0BZoaguySdRQKVMqa69Rc1/7/a00Ru9H4NW+NX/PWFORkcmD7Oo7v3UrCvm0Eh7Ynqu9QAlu1bfQ7gkqdCn2AC/qA2iYU+/bto03nS92UTFYb+y/ksz09h4ScIiSgnbcL4yMC6ejjek2mDjW5cCaFfZtXcfL4AdQaHZ1630On3vdcdxTuRlOVZldeVYd0LglrcZ59YVWaXafYSqEUisq9WZ3nUpZlyk8dJn/3SspS9iMp1Rgj+9WqVwI4kpLNog0nOHAiC2cnNZOHhjO8d0uM+jvTTv1uR5IkVEZ3VEZ3CAy7ZLlss2IpzKkUUFm1rNTLUg9SfFHTX0mpRuVo+utz3U1/bxdUzh64dhmGa5dhWEsKHAIqf+fP5O9YjsrVB0OEPQKl9W/dIGHZoHGVCtxddA2O/MqyTFmFpYbLoF1cOaJYNSJbJ88V2C3dS+uPZuk1SoxqJcaSEgynQG+VaalUUK5TUGRQ8btzARs0StQaBSFGPR19XfG83h90QZPmxRdfdKSx1WTgwIE8//zzV7Wv7777jq+//poPP/zwmuayd+9eXn/99TqXffXVV5c1irhRnDlzhmeffbbOZW+88QaRkZGNPoemhIg0XSeyzUrxse2cPHmKNp26onLxQunsUctS12qTsdhsmGwyZqvtEmFlstqXm62XX8dstXLmVD7HD2ZQlF+O3qghMMITN38jFuwX6pbK7Uw2G5b6mn80EHtkrO6omCOCplCgUtpFWO11qrervc5F+3OsU73vK6UglpUUczRuE4d2bKC0uBAvvyCi+gyldYduKG9y6k3Nu46yLHO6oJTt6TnsPpdHmcWKl15DryBPegZ44qG/vt41siyTnnKcfZtXkZ5yHK3eQMdeg+nQIxadk/HKO2hkZJsVU+YZhzi6OM1O7eFXnWJXI83usvu0mCk+to2C3SsxZZ5GaXDFpfPQWvVKsiwTfyKLxRtOcDQ1BzdnLWP6tWZYzxbotY33frjTog13I7Wb/mY4aqmqLNVtZcW11pc0OtRuPhQrnGjWtita/9Zom7W6LZv9NgRraRGlSXsoPr6TspOHwGZB6eyJITwGY0QPtIFhN0xANRZWq42iUrNdXDlqtC5OG6y9zGSpO5qFBN3C3fjHY/0abb4i0iQQ3FpEpKkRsZnKyVn7fxgrSjl3yO6GgqRA6eyBysULlauX/a+LNypXLwwuXvbmj05O13bHsgPYRsjsPnqehetOkLTnPH5eBh4Y1Ib+0YG10vZssozFJjsiXmabXCms5EqBdnFUTK4UaPZ1LVdYp9xiqVyn9hhmq43rkWsKiTqEVU1hpkDt0hbV0LaYC7I5fiGNg3uOoz2QjH9QCwKCQtBrtdXr1oi+qesUb/Z1VArpms5JkcnC7rO5bEvP5mxROWqFROdm7vQO8iTUw3jdETvZZuNkwgH2bVpNRnoqTs5u9Lp3Iu269btqc4wbhSzLWAuzKa8USBVnk6i4kFojzc4ZrX8oxvCe9jQ7/9Yo9Q23866qVyrcu6beeiVZltlzLINFGxI5cSYfL1cdT46JZHD35mgb0NxSIFCoNGg8A9B41l37V1/TX2V6Erm//1C5loTaKwCtX2u0fq3Q+rdG49vijmjwq3RyxrnjQJw7DsRaXkJp0h5Kju+iaP86CvesRml0xxDWHUN4DLrgtk2y/5ZSqcDNWYubc8MFSHmNaFZBSQUFRRXkZZeSnVtCc2/TlXcgEAjuSESk6QZgM5VzcOcfhAX6YCnMxlKQbf9bmFX5OAdstV1IJI3+EkFVLbK8UTl7XLFgWZZldh+9wI+/JZJ6rgA/TwMTBoXSv3MQqltY8yTLMlZZro6gVUXKLhJWNZ+3VEbHLl1HrhRxdrFnujgKV7lOhdmC2WZDvo67nhLYxVNldMwhrOqqTatcJy0zizMmBVZZpoWrE72DPOnq54HTDbhot1mtJB2KY98fq8nNOIuLhzfR/e4lPKoXKvXNTTezVZRScS6Z8nPJ9lqks0lYq5rGVqbZaQOqa5FUbr7XJEAbUq9ktcnsPHyOxRtOcPJcIb4eToyPDWVglyDUN9H9SkSa7l727dtHp/DW9kbK55MdtXmOz4RChcYn2C6k/Fuh9WuNxjuoSYqKa8FWUUZp8j5KEnZSmrwf2WJC4eTiEFD65u3vWMMNUdMkENzZiEhTI6PQ6LAZvXBqFVXnclm2YS0usIsoh6jKcoirivMp2EoLL9pKQunsXltQVUapqsSVQmckpr0f3ds1I+7oBRasS+TDRQdYtOEEE2LbMKDLrRFPkiShkiRUCoCbe5FwPv0k8ds2kHT8ADaFiqCITrSJ7oOzl191BK1GNK2meKv5/KXr2AVbidlSax2rGQY096ZXoCeBLjcmRcdiNpOwfxv7/1hDYV4WHr4BDH7gCUIju12xZ9WNwJ5md9oukioNG8zZZ6mZZqcP6WBPsQtog9a3OZLy2kVcQ+uVrFYbWw6cZfGGE6RnFhPgbeRvD0bTL+ruMkYRNA2UBlecWkfj1DoaqDY5sQsou5AqObaNovh1AEhqLRrfELT+rdFViimVu99tWSOl0OoxtuuNsV1vbKZySlPjKTm+k+KjWymKX49CZ8SpTTeMETHoW3S4YhquQCAQ3A4I0XQTkCQFKmd3VM7uENCmznVs5oo6BJX9b8X5FEoSd4P14miVzhGpaunqxWtdvTgU7sryw1Y+WnyARRsSmTAojIG3SDzdCvwCQ/Cb+DhF+Tkc3LGeo3F/sCV+CwEtw4nqM5Q2bSKRFDfutdi3bx+d294YFz9TRTlH4zYTv/U3Sovy8Q1sSZ8RD9IivOMNnXNN7D2rsuwXeo6msSkOG2dHml3bXpW1SFeXZnfZseuoV7q4vxKA2WLj971pLPn9BBdySmnh58LLU7rQs4P/HW/BL7h9kCTJcXPLEB4D2G+YmXMv1IhGJdtT2yyrAHvPKa1fq8rUvtZo/VvbmwTfRig0OozhPTCG98BmrqAs9SAlCTspSdxF8aHfUWidcArtgiG8B/qWHUUfLYFAcNsiRFMTQaHWXja3XpZtWEsK6kj9swutigv2aFUw8JwMx4wBrCnoyMeLy1iwfBfDgwvpG6pB5+ZdKw1QoTfelnc6r4Szmye9751I14GjOLZnCwe3r2PVdx/g7u1Hpz73ENap501PcauP8tJiDu3YwMEdG6goKyGwVVuGPPA4AS0jbvi5sZWXUHE+xV6LVCmSqlKKJKUaTbMQnKMGowuwmzVca5rd5WhIvRJAhdnK+t2nWbopmez8MloHuTFrVHu6tm2GQoglwW2AJCnQePqj8fTHuX1foEZfshoRqfydKxzW6Eqju0NAVQmqi233myoKtRZDWDcMYd2QLWbKTh2i+PguSk/EUXxkC5JGh1PrzhgieuDUMgqFRvRLEzQeo0eP5ueff75h+5syZQrTpk2je/fuN2yf10pRUREzZszgs88+A+Cjjz7i559/ZvLkyaxYsaLO4x44cCDff/89fn5+PPHEE1y4cIHZs2c36vG88sorTJs2jYCApt8zsiEI0XSbIEmKamvdgNA617FHq3KwFGbhXZBNz4Js4k9m83OKnu9TfFh1spjBui1006agkuw/0JJaW7uWqqZ5has3KmfP2zq1QqtzIqrPUDr0HETyoT3Eb13LpmXfsmvdMjrExNI+ZgB6w625ICkpzOfAtt84snsTZlMFIW2j6NxvOM2CW92Q/ctWC6asM1ScTXIYNtROs/NH37Kjw+5bc51pdleiIfVKAGUVFtbuPMXyzcnkFVUQ0cKDZ8d3IirM+44U+IK7C0mhROvbAq1vC4gaBNi/u00Zp2pFpEqT9ji2Ubn5VoqoyhqpZi1RaJq2Y5+kUuPUujNOrTsjW5+k7PQRezPdxN2UHNuOpNLg1DoaQ3gPnFp3vmMdCAW3jhspmJoaBQUFJCQkOP7/888/8/XXXxMSEsKf/vSny26bkZFBYmIi27Zta+xpsnv3bp555plGH+dmIUTTHYQ9WmW/q1nFoH4QK8vsS8jkx3WJLDpjZKOyL/d11NG7WQkUV0erSjNOVxcy10BpcKtVS3WxeYXCyaXJX8wqlSrConrQplMMZ1OPE79lLbs3LGffH6uJ6Nybjr2G4ObV+D0PAApyM4nfspZje7ci26yEduxO537Dr6tZryPNrjJ6VH42CdOF1Oo0OycXdP6hGNv2tl98+Yei1De+TXlD65UASsrMrNqeys9/pFJUaqJTqDfTp7ShfUvPJv/+EgiuB4Vaiy4wDF2NXlO28hIqLqRWR6TSEyk5tt2+UFLUcOyrjEr5NG+yN7gkpQqnlp1watkJr6GPU37mmF1AVf6TlGr0LTthiIjBKbQrSp3hVk9Z0ATZvXs3X375JTqdjpSUFMLCwpg/fz6ffvopO3fupKCgAHd3dz7++GO8vb0JCwvj6NGj9O/fnxUrVuDl5UV+fj4jRoxg06ZN7Ny5k48++giLxUJgYCCvv/467u7ul53D4sWLefPNN5FlmVdeeYXu3buTkZHB3//+d4qKisjKymL48OG89NJLTJo0iaeffprevXsjyzL33HMPP/zwAxkZGfz73/+mvLwcd3d35s6dS1BQEN988w3Lly9HoVDQoUMH/vnPf9Y7jzfeeIPMzEyeeeYZPD09ycjI4JlnnuHdd9/lvvvuIzExkfz8fKZPn86FCxdo1aoVFRV2d9snn3yS/Px8xo4dy7Jly+rc/7///W98fHyYOnUqAM899xwjRowgOjqa2bNnc+HCBSRJ4sUXX6Rnz57k5+fz6quvkpqaikajYebMmRw+fJjMzEyeeOIJ/ve//13xtb0dEKLpLkCSJLpE+NI53If9iXbx9PW2PFa46Rkf25/BA4IdrmM2iwlrYU6lkMqq5QZoyjpNafI+x4W4Y/8qTb2CSuXqhdLFq8nY70qSRGCrtgS2aktOxlkObPuNo3u2cHj3Jlq2jSKqz1D8mtcdybteci6ks++P1SQdikOSFER07k10v2G4evhc9b5s5SWUn69Rh3Qu+aI0u5Y4Rw9BVymQGiPN7nI0tF4JoLDExC9bU1i1NZWScgtdInx5YFAbwlt43LT5CgRNDYXOgL5FJPoW1c0jrSUFdoOWyohUafI+ig9tqtxAhda3eY3UvtaovQKanGOfpFA6jstzyJ+pOHuC4uM7KUnYZY+uKVToQzpgjOhhF1C3SWrinU7C/u0c27u1UfbdtksfwqN7NWjd+Ph41qxZg4+PDxMmTGDRokWkpqaycOFCFAoFL7/8MitXruTPf/4zACqViqFDh7J27VomT57MunXrGDRoEEVFRbz77rt8//33uLq6snDhQubPn8+//vWvy47v5OTE8uXLSUhI4Mknn2T9+vWsWrWKESNGMGbMGIqKiujXrx9//vOfGTduHL/88gu9e/dm7969BAcH4+7uzuOPP84XX3yBv78/W7du5R//+Adff/01X375JVu3bkWpVDJ37lwyMjLqbWA7a9YsHn74YT799FMAtm3bxldffUVgYPXN148++oi2bdvyf//3f+zZs4c1a9YA8Pnnn/Pwww/XK5jAnto4a9Yspk6dSnFxMfv372f+/PnMmDGDcePGERsbS2ZmJpMmTWLFihV8+OGHBAcH8+mnn5KYmMjs2bNZtGgRCxcu5KuvvrojBBMI0XRXIUkSncN9iQ7zIf5EFj/+lsDnSw/x04YT3B/bhiHdg1GrNCg8/FB7+NW5D1mWsZUVVRtVXGReUZoSj7U475LtlAZXe+PfixwAq1IClQbXmx5N8PQNIHbcn4kZMo7DOzdweNcmUo/up1lwKzr1GUrLttEoboABQ0ZaKvs2ryb12H7UGi0dew2mU+97MLo07EtEtloqm8aecNQimXPOOparPf3Rt+xkd+W6CWl2l6Oh9UoAeYXlrPgjhV93nKTcZKVnBz8mxLahVaDbLZm7QNDUURpccQrtjFNodUNtu5FLtfV50ZEtFO7/DQBJrUPbLKRGal/rm34D5XJICiW6oAh0QRF4Dn7U7jiYsJOS47vIWvUpSAr0LSIxhMdgCOt+yQ0Xwd1HaGgozZo1A6BVq1YYjUZmzJjBTz/9xMmTJzlw4ADBwbWzGEaPHs28efOYPHkyq1at4q9//SsHDx7k/PnzPPzwwwDYbDZcXa/8/rr//vsBCA8Px8PDg9TUVKZOncquXbv4z3/+Q1JSEmazmbKyMoYNG8b7779PWVkZy5cvZ+zYsZw6dYq0tDSeeuopxz6Li4tRqVRERUVx//33Exsby0MPPVSvYGoocXFxvPvuuwB07dqVoKCgBm/btm1bTCYTp0+fJj4+ngEDBqDRaNixYwepqal89NFHAFgsFtLS0tizZw/z588HICwsjEWLFl3X3JsqQjTdhUiSRHSYD1FtvDlwIosf1yXyxbJD/LTxBOMHhjK4e3M09fQZkiQJpZMLSicXtH4t61xHtpixFOXU7llVGbUy55ylLPWAowmqY79KNUoXz2pBVVNUVaUBNpLrksHZlZgh4+jcfwTH927lwPZ1rP3fp7h4eNOp9z1EdO6NWnN1Y8uyzNnU4+zdtJr0lGNo9Qa6xo6mQ49B6A31p8XJsoylIKuyYaxdJJkunLw0za5dH3vTWL/WNyXN7ko0tF4JIDu/jKWbkli36zQWq42+UYHcHxtK82Yut2byAsFtiiRJqF19ULv6YIzoAVQ69uWcqxRRdjFVuHctstUMgEJvvNSxz/nWR3UlSYEuoA26gDZ4DHwY04VUShJ2Unx8J9lrviR77f+hC25bKaBi7G60gptGeHSvBkeDGpOavaskSSIvL4+pU6fy6KOPcs8996BQKLi4/WhkZCQFBQUcOnSIjIwMoqOj2bBhA9HR0XzxxReAvT9WSUnJFcdX1mj7IcsyKpWKN998k7S0NEaMGMGgQYPYsWMHsizj5ORE3759Wbt2Lbt27WLOnDmkpqYSGBjoqLeyWq1kZ2cD8Nlnn3HgwAG2bNnCY489xvz58+nWrds1v1aSJNV6LZRX2bJk1KhR/Prrr8THx/P4448DdnH53Xff4ebmBtjro7y8vFCpasuJlJQUQkJCrnnuTRUhmu5iJEkiKsyHTm28OZhUKZ6WH2bxxiTGx4Yy5DLi6bL7ValRuzdD7d6szuWyLGMrL75EUFWJrLKTB7EW5VFlWFCFwsml7kbAVWmABlek62huq9Zo6dBzEO1jBpJ6bD/xW9ay5Zf/snv9ciJjBhDZYxAG58vfiZJtNk4lHGTv5lVkpKXi5OxKr3sfoF23fmjqKHS2lpfYaxYqRVLF+WSsJQWAPe1R0yykMs0u1N401tWnydwlvpp6JYALOSUs+T2JjXvOIMswsEsQ9w8Mxd/71os+geBOQZIUaLwC0XgF4hzZH6hhClPZhLfiXDL5O5bXcOzzcDThrXLtu1GtBa7tGKRKYdcK9/4PYco8XRmB2knOb1+T89t/0AWF2wVUeAwqF69bNlfBrUWSJLp168aDDz5IUVERc+bMYcCAAZesN3LkSF577TXuvfdeADp27MisWbM4efIkISEhfPbZZ2RkZPDmm29edryVK1fSvn17Dh8+THFxMc2bN2f79u3MnTuX6Ohodu3aRUZGBjab/bM1btw4/va3vzkiNS1btqSgoIC9e/fSpUsXli5dysqVK/nwww+ZNGkSS5cuJSoqigsXLpCYmFivaFKpVFgsljqXVdGjRw9+/vlnwsPDOXToEGfOnGnIS1rrNXviiScwmUx06dIFgJiYGBYsWMDTTz9NcnIyDz30EBs3bqRLly78+uuvhIeHk5KSwuOPP87GjRtRKpVYrdarGrcpI0STAEmS6NTGh46h3hxKzubHdYl8ufwwP21MYtzA1twT0wLtNYiny42n1Duj1DujbVb3nQjZasZSlHeJtbqlMAtz7jnKTh5ENpXX3kipuihKdVF9lYtXgyxuFQoFrdt3oXX7Lpw/nUT81rXs3bya/VvWEhbVg6je9+DhW9s+02a1knQ4jn2bV5ObcRYXd2/63/cw4dG9Hdbm9jS705UNYyvd7C5Js4uyu9kFhKLxaY6kbHof0aupVwJIzyzip41JbN6fjkKSGNK9OeMGhOLj4XQLZi8Q3H1IShXaZi3RNqvODrA79p2sJaRKT9Rw7HNvZhcuVal9zVreEotwSZIcboMe/R7ElJVmF1AJu8hZ/w05679B6x+KIaIHhvAY1G43x9BH0DQoLy8nISGBkSNHolarCQsLIz09/ZL1Ro0axYcffsh7770HgLe3N/PmzeOvf/0rNpsNX19f3nnnnSuOV1payn333YdCoeDdd99FrVbz5JNP8vLLL+Pi4oKnpyft27cnPT2d4OBgOnfujCRJjBs3DgCNRsOHH37Iv/71LyoqKjAajbz11lt4eHgwceJE7r//fvR6PX5+fowZM6beeXh6euLv78+UKVP44Ycf6lznueeeY+bMmQwfPpyWLVteVXoegJ+fH+7u7nTq1Mlxs3bWrFnMnj2bkSNHAvD2229jNBp57rnnmDVrFqNGjUKlUvH2228jSRL9+/fniSee4Ouvv77q8ZsiknxxHPMOoqKigiNHjtC+fftaId3GYN++fXTu3LlRx7hZyLLM4ZRsFvyWyNHUHDxctIwbEMo9PW6seLoeZFnGVlF6kVlFbeMKa1Gu405qFQq9c52pf1VpgUqjW53RqvzsCxzYto7j+7ZhtZhpHtaBqD73cD6nCD1l7P/jVwpzs/DwDaBzv+G0juyKrTinlt13XWl22oA21U1jm7hjVF31Sq7dRtZZrwRw8lwBP21MYtvBs6hVSob1aMGY/q3wdL0zrIXvpM+84Oq4U8+9tbwE03l7Sl95pZiyFtpTh+yOfYFo/Vqjq4xK3cr6SQBTzrlKB76dmC6kAqBp1gpDeAzGiBjUHv5X2MPV09jn/mZet1yJ48ePExERcUvncDsjyzInTpxgxowZrFix4lZPR9BALve+F6LpBnGn/ogeTs5mwboEjqTk4O6sZdzAUIY2IfF0OWSbFWtRrr2WqiCrlmFFVVqgbCqrvZFChcrF45IIVZWoMqt0HNu/k0M7N1BWUoRCqcJmteDj35zIdpH4qqyYzidTfi4JW2khUJ1mV1MkqVxvn55DV1OvBJCUlsei9SfYffQCeq2KEb1DGNWnFW7Ot/YC4EZzp37mBVfmbjr3luL8Wv2jKs6nOL7bUKrQ+rSobsTr3xq1561x7DPnXbD3gDq+k4pzSQBofJpjCLdHoDTeN+YutxBNdzYvvvgiycnJlzw/cOBAnn/++ava17fffsvXX3/Nhx9+eE3vmb179/L666/Xueyrr766bqOIM2fO8Oyzz9a57I033iAyMrLOZXc6QjQJ0XTdHE7JZuG6RA4lZ+PmrGXcgNYM7dECnabppY9dDbbyknojVZaCLCx1Rat0RiSjJ+esGs7lFxGit+FakkmVflB7BqANsDeM1fq3QeMT3CTT7C7H1dYrARw7mcOiDSfYn5CJQa9mdJ+WjOjTEmenpmE3f6O50z/zgvq5m8+9w6ymlpBKddyAkjQ6eypgjfqom+3YZynIsguohF2UpyUAMmqvwMoaqB721OdrnI8QTQLBnc3l3ve315Wc4JYR2cqLyKe8OJJir3n6zy9HWfp7MmMHtGZYjxbotLfnW0mhM6DRGdD4NK9zuWyzYi3OqzNKFVSYjZe2FOeANmj9Y2+bNLvLcbX1SrIscygpm0UbTnA4JRtXo4ZHhrfl3p4tcNI1zUabAoHg2pEkCbWbD2o3H4wRPYEajn1VIupcMgV7fwWrvVBdoXeuduyrrJFqTPc7las3rt1G4NptBJai3EoBtZP87cvI37YEtYdfdQSqWcvbJuovEAhuLTf1SnflypV8/vnnmM1mHn30UR566CHHsuPHjzNz5kzH/3Nzc3F1dWXVqlWcO3eO6dOnk5OTQ0hICPPnz8dguH0vTG9n2rfy4l9PeXE0NYcf1yXw/1YeZdmmZMb0b829PW9f8VQfkkLpSNGD8EuW79u3j9A74I7z1fRXArtY2peQyaL1iSSczsPDRcdjo9tzT0zz2z76KBAIro5ajn0d+gN2Mx97f7mqaFQy+TuWVTv2OXvUElF2x74b76SpcvbAtcswXLsMw1pS4IhA5e9cQf6OZahcfTBE2CNQWv9QIaAEAkG93LSrm4yMDN5//32WLVuGRqNh4sSJdO/endatWwMQERHh8K0vKytj/PjxzJkzB4C5c+cyadIkhg8fzqeffspnn33G9OnTb9bUBXXQrqUnb/ylF8dO5vDjukS+WXWUZZuTGNOvNff2CkF/h4mnO5WrrVey2WR2HTnPog0nSD1bgI+7nqfHdSC2a/A12dMLBII7E0mpdtiGwz0A2EzlmDJOVppMJFc69sU5tlF7+NUSUppmITe0P5/S4IpL9BBcoodgLS2i5EQcJQk7KYj7lYJdv6B08cIQ1h1jRA+0gWHX1cJCIBDcedy0K9sdO3YQExPjaIh1zz33sHbtWqZNm3bJul9++SVdu3alS5cumM1m9uzZw6effgrA2LFjmTx5shBNTYS2IZ68/mRPjp/M5cd1CXy7+hjLNtsjT8OFeGqSXEu9ktUms/XAWRZvOEFaRhF+Xgaef6AT/TsHoVKKCwuBQHBlFBoduqAIdEHV9QLWsmK75XmliCo7c5Tio1vtCyUFGu+g2kLqBtWIKp2ccekUi0unWKzlJZQm7aHk+C6K9q+jcM9qlEZ3DGHdMUT0QBcUcUvMLQQCQdPipl3RZmZm4u3t7fi/j48Phw4dumS9wsJCFi9ezMqVKwHIy8vDaDQ6ug17e3uTkZFxVWMfOXLkOmbecPbt23dTxmmqjO6iJbq5N5uPFPLd6mMs3pBAz3Aj3doY0arv3Avr2+a82yxozh9DeyoOVVEmNo0TFa37UBEUTa7WAGey7P9qYLXJHDpZytZjReQWWfB2VTGupwftgvUoFNkcPJB9iw6maXDbnHvBDUec+xuMrgW0bAEtByGVF6MqPIey4DzmgvOUH9uB4uBGAGSFEquzLxZXP6yu/lhc/bAZPOG60+qcodVgaN4XdWYymowELPEbKNy3FpvGCbNPG0zNIsCzuTj3AsFdyk0TTXWZ9NWV/rNy5UoGDRqEp6fnVW13OYR73s2jM3DfUEg4ncvCdYlsPJhJXFKZI/J0p5kD3A7nvc7+Sn3rr1cCMJmtbNhzhqW/J5GZV0bLAFeeHNuGmPZ+KBQi5x9uj3MvaBzEub+5yLKMJT/D0YTXXiN1FPmMXbxIGj1av5a1jSauq62D3eDCZiqnNCWekoSdlCbtQ5t+gNKIwbQf+5cbdGSXUuWeJxAImh43TTT5+vqyd+9ex/8zMzPx8fG5ZL0NGzbw5JNPOv7v4eFBcXExVqsVpVJJVlZWndsJmhbhzT2Y83gPTpzJ48d1iXz/63GWb05mdL9WjOzd8o4TT02Rq61XAig3Wfht12mWbUomt7CcsObuPDWuI53DfUSBtEAguCVIkoTavRlq92YY2/YC7M6m5pyzlSLKLqYK9qyuduxzcrnUsc/odlXjKjQ6jBE9MEb0wGauoDwtgYSMght9eIIGsnbtWr766issFguyLDN69Ggee+wxAHbu3Mmnn35KVlYWNpuNiIgI/v73v9OsWTPS09MZOnQorVq1AqC8vJywsDBmz56Nl5fXLTueoqIiZsyYwWeffdboY3300Uf07NmTLl26NPpYdzI3TTT17NmTjz/+mNzcXPR6PevWrbukaZcsyxw9epSoqCjHc2q1mi5duvDrr78ycuRIVqxYQd++fW/WtAXXSZtgd157LMYhnv67JoEVm1O4r18rRvYR4ulGcy31SgCl5WZWbz/Jz1tSKCg2EdnKixcmRdOhtZcQSwKBoMkhKZRovIPReAfj3HEgYG+ZYMo8TcX5ZMrP2eukylIPVjv2uXih9WuFroZjn6KBLSIUai1OLTsi592dqXmFRzMoPHx1pRENxSXSF5d2l2/UmpGRwVtvvcWyZctwd3enpKSEKVOmEBISgqurK9OnT+eTTz6hU6dOAPzvf//jmWeeYenSpYC9JKTKbEyWZd577z2ee+45FixY0CjH1BAKCgpISEi4KWPt2bOH7t2735Sx7mRuaqTpb3/7Gw8//DBms5n777+fDh068Pjjj/Pcc88RGRlJbm4uarX6klS61157jZkzZ/L555/j5+fHe++9d7OmLbhBVImnpLRK8bQ2gRV/pDgiTwa9EE/Xw9X2V6qiuNTEyq2p/LI1leIyM9HhPkyIbUO7lp43cfYCgUBw/UgqtT2q5N8al8rsSZupjIoLJ2s0402hNHG3Yxu1h7+jCa/WvzUa3xvr2Ce4MeTl5WE2mykvLwfAYDDw5ptvotVqmTt3Lk899ZRDMAE89NBDlJeXYzKZLtmXJEk8++yz9OrVi4SEBMLDL20nUsW3337Ljz/+iFKpZMCAAUyfPp3s7GxeffVVzp07h0ql4m9/+xt9+/bl448/BuDZZ58FYODAgXz//ffExcWxdetWCgoKSEtLo1evXsyZM4c33niDzMxMnnnmGYfZ2cV8//33nDp1itmzZwPw1ltv4ePjw4QJE/jnP/9JUlISVquVxx9/nBEjRlBRUcHcuXPZt28farWap59+GpPJxJEjR5g1axaffPIJYWFh13QOBDe5T9PIkSMZOXJkref+7//+z/HY09OT7du3X7JdQEAAP/zwQ6PPT9D4hAa5M3tqDMlp+Sxcn8j/qsRTn5aM7NsKoxBPV8XV9leqIr+ogp+3pLB6+0nKKix0b9eMBwa3ITSo8RpOCgQCwc1GodGjD26LPrit4zlrWVGt+qiyU0coPrLFvlBSoPEOri2kvG+MY9/tjEu7K0eDGpPw8HBiY2MZNGgQERERdO/enZEjR9K8eXMOHDhQq89nFVOnTq13fxqNhubNm5OamlqvaDp06BALFixg6dKl6PV6HnvsMY4cOcL//d//ERMTw5/+9CfS0tJ48MEHWbFixWXnHx8fz6pVq1AqlQwdOpQHH3yQWbNm8fDDD9crmACGDx/OmDFjePXVV1EoFPz2228sXLiQzz//nHbt2vHWW29RXFzMxIkT6dixI7/99hulpaWsWbOGnJwcHn30UZYvX87SpUuZNm2aEEzXyd39LXCDMOddQFGah81cIe5QNZDWQW7M+nN3ktPzWbgukQXrEvl5Swqj+rZilBBPV+Ra6pUAcgrKWLY5mbU7T2O2WOndMYDxsaGE+NcfjRIIBII7CaXeGaeWnXBq2cnxnKUot1Yj3pKEXRQd2ACApNKg8W2B1q81kiHkFs1aMHfuXJ5++mm2bdvGtm3bmDBhAvPnzweqDcJMJhPjx48H7Olv7733Xr118JIkodPp6h1vz549DBgwAGdnZ8AedQLYtWsXb7zxBgBBQUF07NiRgwcPXnbuUVFRGI1GxzYFBQUYDFdODfX09CQiIoLdu3ejVqtp0aIFPj4+7Nixg/Lyckf6YWlpKUlJSezZs4cJEyagUCjw9vZm9erVVxxD0HCEaLpOrGVFpH02DVdkTm35HIXeiMrZE6WzBypnzxqPPVC52B8rdEZRJ1JJ60C7eEpJt0eeflyXyC9bUhjZpxWj+7bE6FR/tORu41rrlQAyc0tZsimJ9bvPYJNl+kcHMj42lEAf55s0e4FAIGi6qJw9UIV1wxDWDajh2FejEW/x4c2oW9/aed6tbN68mdLSUu69917GjRvHuHHjWLx4MUuWLCEyMpL9+/cTGhqKRqNx1C5NmTIFs9lc5/5MJhMnT56kdev6T2hVq5sqMjIy0Ov1l7g6y7KM1WpFkiRsNpvj+Zpj1yw7kSSpTmfo+hg1ahS//vorarWaUaNGAWCz2XjnnXdo164dANnZ2bi6ujpEVBWnT5/Gz8+vwWMJLo8QTdeJUu9MwJ/e5MSerQR6OmMtysVSlIOlKBfThZNYS/Iv2UZSaWqIKg+ULpV/awoto9td1UyvVaAbr/6pO6lnC1i4PpGF6xP5ZWsKI/u0ZHTfVjjfxeLpWuuVAM5lFfPTxiQ27UtDkiC2azD3DwylmWfDip8FAoHgbqSWY1+73oD94nj//v23eGZ3Jzqdjtdff50OHToQGBiILMskJycTERFBnz59eOGFFwgPD6djx44AJCQkkJaWhlJ56XWUzWbj448/pmPHjgQH13/DsUuXLrz00ks899xzaLVaXnzxRZ5++mliYmJYsmSJIz1v//79zJkzh6ysLHbvttfLHTp0iKysrHr3DXZRZrFYrnjssbGxfPTRR9hsNl566SUAYmJi+PHHHx11Uffddx8LFy6ka9eurFmzhoEDB5Kbm8vkyZNZs2YNSqUSq9V6xbEEl0eIphuA1r81psAC3Ovo2yFbzViK8+xiqtAupqqElbUol/KziVgSch02qQ4kBUqDW7WYukhYKSsFl0JTf2j5dqRlgCt/f7QbJ8/ZxdOi9Sf4ZUsqI/u05L5+d5d4utZ6JYDTFwr5aUMSWw+ko1IquLdXCGP7t8bLTX+TZi8QCAR3FiJD5NYRExPDtGnT+Mtf/uKI4PTp04dnnnkGjUbD+++/zwcffEB2djayLOPm5saMGTPo0qUL6enpZGZmMnr0aACHJfm777572THbtWvH5MmTmThxIjabjcGDB9OzZ09atWrF7NmzWbZsGQBvvPEGPj4+3Hvvvfz222/ce++9tGvXjrZt2152/56envj7+zNlypTL1u3rdDqio6MxmUyOlL5p06YxZ84cRowYgdVqZfr06QQHBzNp0iTeeOMNR0TqH//4B0ajkT59+vDaa6/x1ltvER0d3bAXXXAJknw1McLbjKomcU29ua0sy9hKC7HUEFOWohwshblYiyuFVmEOtorSS7ZV6AzV6X/1pAUqnFxu2y/7k+cKWLT+BNsPnUOvVTGidwj39WuNi6FpiKfGaHJ5rfVKAMnp+SzecIKdh8+j0yi5t2cI9/VrhbvLnSWumwKiwendizj3dy+Nfe5v5nXLlTh+/DgRERG3dA4Cwc3mcu97EWlqAkiShNLgitLgirZZ/UWmNlN5ZaQqp1pc1YhelWaewVqcD9TWwZJSjdLZvZaouiR6ZXRHUjY984UQf1dmPtKVU+cLWbg+kSW/J7FqWyojetvT9lyNd4bxxvXUKwEknM5l0foT7D2egUGn4oHBbRjVp1WTEZcCgUAgEDQ1zpw547AIv5g33niDyMjIRp9DeXk5DzzwQJ3LnnvuOWJjYxt9DoKGIUTTbYRCo0Pj6Q+e/vWuI9usWIvzK+uqqoWVPXqVa+9RcWIPsuXi3gWVwq1mrVUN84qq6JVCe2vSu1r4uTDz4a6cvlDIovUnWPJ7Eiu3pjK8Vwhj+re+bcXT9dQrybLMkZQcFm1I5GBSNs5OGiYPC2dEL9H3SiAQCASCKxEcHOwwjrhV6HS6Wz4HQcMQoukOQ1Io7REkl/qbk8qyjK28uJaYqpUWWJBBefpxbGXFl+5fo6/lBKgyVj2uElqeKA0uSJKiUY6veTMXXp7ShYmD27Bo/QmWbU5m9faTt514up56JVmWiU/MYtGGRI6dzMXNWcufR7ZjaI8W6LXiIy0QCAQCgUBwoxFXWHchkiSh1Duj1DuDb4t617OZK7AW59UQVzWiV0W5mE4exlqcB7Kt9oYKFSqjWw1XQM9LolcqoweS6tqjIcHNXJg+pQsTh4SxcH0iyzYns2r7SYb3tIsnN+emKZ6up17JZpOJO3aBRRtOkJyWj5erjifHRDK4e3O06rvHaVEgEAgEAoHgZiNEk6BeFGotikrL1fqQbVasJYWVYiqnRs1VpbDKOI0lOR7ZXH7p/p1caoupS3paeaLQOl1WTAT5OjN9chcmDg5j8YYTrPgjmdU7TjKsRwvGDmiNu/OtN0C43nolq01mx6FzLN5wglPnC2nm6cS08Z0Y2CUItapxInoCgUAgEAgEgmqEaBJcF5JCicrZHZWzO1B3kzhZlpErSh39q2obWNj/lp9LwlZaeOn+1dpLxZSxUmBVRbIMrgT5OvPiQ515YHAbFm04wS9bUvh1xynu7dmCsf1b3xL3uOupVwKwWG1siU9n8YYkzmYVE+hj5IVJ0fTtFIBSKcSSQCAQCAQCwc1CiCZBoyNJEpLOgEZnuGxkRbaYsRTnVtdZFebUiFrlUJ52HEtRHtjq6GlldK+0XffgES9P7r/HyO6T5ezacZbdOw8R0y2CMbERN0U8XU+9EoDZYmXjnjSW/J5ERm4pLfxcmPFwF3pE+qNU3J7W8QKBQCAQXA9r167lq6++wmKxIMsyo0eP5rHHHgNg586dfPrpp2RlZTn6MP3973+nWbNmpKenM3ToUFq1agXY3erCwsKYPXs2Xl5elx2zZg+lxYsX8/nnnzN06FCSk5N544038PX1vWT9adOm0b17d1555RX279/Ps88+y4gRIxrhFbHz0Ucf0bNnT7p06dJoYwjsCNEkaDJIKjVqN1/Ubr71riPLNqwlhTUaBFenAlqLcjDnnKXs1GHkilK6AF2cKzc8BulHtJzRu+Lu2wy9h0+d/a0UeuM197S6nnolgAqzlXW7TrNsUxLZBeWEBrnxxH2RdG3re9v22RIIBAKB4HrJyMjgrbfeYtmyZbi7u1NSUsKUKVMICQnB1dWV6dOn88knn9CpUycA/ve///HMM8+wdOlSAHx8fBwOdbIs89577/Hcc8+xYMGCy44bFxfneLxq1Spef/11evfu3aA5L1++nEOHDqHRNG7rjz179tC9e/dGHUNgR4gmwW2FJClQGd1QGd3Q+rWsdz1bRVktR8C8CxfITDxJcU4m+aVn8TmXitZSwiU9rVSaOsSUR2UqYGU6oNEdSVFpvCDLlJ08dM31SgBlFRbW7DjJ8j9SyC+qoG2IB88+EEVUG28hlgQCgUBwyzl69ChHjhxplH23b9+edu3aXXadvLw8zGYz5eX2+miDwcCbb76JVqtl7ty5PPXUUw7BBPDQQw9RXl6OyXRxexV79suzzz5Lr169SEhIIDw8vM4x33jjDQDGjx9Pv379OHz4MHPnzmXWrFnMnTuX77//Hh8fH1599VWOHDlCQEAAeXl5APzlL39BlmXGjx/P//t//w9Pz0sdjb///ntOnTrF7NmzAXjrrbfw8fFhwoQJ/POf/yQpKQmr1crjjz/OiBEjqKioYO7cuezbtw+1Ws3TTz+NyWTiyJEjzJo1i08++YSwsLArv+CCa0aIJsEdiUKrR6MNBK9AAJw7QPAQOJ9dwuINJ/h9XxpqhczIzh4M7eCKQS6udgisdAssP3sCS1EOWOtIBzS4onL2wKWogPPF2VddrwRQXGZm9bZUft6SQlGpmU5tvHlgShvat7p8uoBAIBAIBHcT4eHhxMbGMmjQICIiIujevTsjR46kefPmHDhwgJkzZ16yzdSpU+vdn0ajoXnz5qSmptYrmmbNmsUPP/zATz/9BMDu3bsdqXdVVKXurVmzhlOnTjFq1CgAvvjiC8LCwi7bf2n48OGMGTOGV199FYVCwW+//cbChQv5/PPPadeuHW+99RbFxcVMnDiRjh078ttvv1FaWsqaNWvIycnh0UcfZfny5SxdupRp06YJwXQTEKJJcFfh52Xg+YlRPDC4DYs3nGDZnjR+3pfPPd2bc39sFJ6utZv3yrKMrazInv5XmFPDzML+11Zuxvcq6pUACoor+GVrKqu2pVJabqFrW18mDGpDeHOPxjhkgUAgEAiui3bt2l0xGtTYzJ07l6effppt27axbds2JkyYwPz58wEcWRkmk4nx48cDUFBQwHvvvYePj0+d+5MkCZ3u+uqc4+LieOCBBwBo0aIFUVFRDd7W09OTiIgIdu/ejVqtpkWLFvj4+LBjxw7Ky8sdqYWlpaUkJSWxZ88eJkyYgEKhwNvbm9WrV1/X3AVXjxBNgruSZp4GnnsgigmD2vDTxiTW7DzF2l2nGdI9mPsHtsHb3S6eJElC6eSC0smlzp5W5/btw6VT5waNmVdYzrLNyazZeQqT2UrPSH/Gx4bSKtDtBh6ZQCAQCAR3Fps3b6a0tJR7772XcePGMW7cOBYvXsySJUuIjIxk//79hIaGotFoHNGdKVOmYDab69yfyWTi5MmTtG5dt+tvQ5EkCZutulelSnV1l9WjRo3i119/Ra1WO6JUNpuNd955xyFSs7OzcXV1dYioKk6fPo2fn991zV9wdQjfYsFdTTNPA89O6MSXrwwitmsQv+06zRP/3sBnSw+SlVd2Q8bIyivjy2WHmPqv9fyyJYUe7f345KUBzHykqxBMAoFAIBBcAZ1Ox7vvvkt6ejpgzwJJTk4mIiKCZ599lk8//ZSDBw861k9ISCAtLQ2l8tLG7zabjY8//piOHTsSHHz52mOlUonFYql3eY8ePVi1ahU2m42zZ8+yf//+qzqu2NhY9uzZw7Zt2xg8eDAAMTEx/PjjjwBkZmYyatQozp8/T9euXVmzZg2yLJOTk8PkyZMxmUwolUqsVutVjSu4NkSkSSAAfD3sDWPHx7bhp40nWL/7NOt3n2Zwt+bcHxuKj7vTVe/zQk4JP21M4ve9Z5BlGNgliPtjQ/H3MjbCEQgEAoFAcGcSExPDtGnT+Mtf/uKIHvXp04dnnnkGjUbD+++/zwcffEB2djayLOPm5saMGTPo0qUL6enpZGZmMnr0aACHJfm77757xXFjY2MZPXo0y5Ytq3P5pEmTSEpKYtiwYQQEBNCmTZurOi6dTkd0dDQmkwmDwQDAtGnTmDNnDiNGjMBqtTJ9+nSCg4OZNGkSb7zxhiMi9Y9//AOj0UifPn147bXXeOutt4iOjr6q8QVXhyTLsnzl1W5PKioqOHLkCO3bt0er1TbqWPv27aNz54alaQmaPpm5pSz5PYn1cacBGNStOeMHhuLjUVs81XXe0zKK+GnjCf6IP4tSITGke3PG9m99ybaC2xvxmb97Eef+7qWxz/3NvG65EsePHyciIuKWzkEguNlc7n0vIk0CQR34eDjx9P0duT821C6edp9mQ9xpYrsGMz62Db51CKCT5wpYtOEEOw6dQ6NWMqpPS+7r1+oScwmBQCAQCAS3njNnzvDss8/WueyNN94gMjLyuvZfXl7uMIq4mOeee47Y2Njr2r/g5iJEk0BwGXzcnXh6XEfGD2zDkt9PsG73GTbEnakUT6EAnDiTx+INJ9h99AJ6rYr7B4Yyum8rXI239i6hQCAQCASC+gkODr6sLfj1otPpGnX/gpuLEE0CQQPwdtfz1LiOjI9tw5Lfk/ht12k27jmDj5uK87npGPVqJt0TzsjeIRidGrf7t0AgEAgEAoHg5iJEk0BwFXi56fnL2A6Mr0zb2304jUeGt+Xeni1w0qlv9fQEAoFAIBAIBI2AEE0CwTXg6arnyTEd6BJspnPn0Fs9HYFAIBAIBAJBIyL6NAkEAoFAIBAIBALBZRCiSSAQCAQCgUAgEAgugxBNAoFAIBAIBIK7hpkzZ9bbsPZGcO7cOYYOHcrYsWMpLi5ulDGmTJnSKPu9Gl555RXOnj3b6OP8/vvvfPPNN40+zpUQNU0CgUAgEAgEgnrJObeX7LN7GmXfXgFd8fTv0ij7vlXExcXRrl073n333UYd41aze/dunnnmmUYf5+jRo40+RkMQokkgEAgEAoFA0KTZvXs377zzDjabDVdXVxQKBUVFRWRlZTF8+HBeeuklli1bxtatWykoKCAtLY1evXoxZ84cZFnmzTffZPPmzfj4+GC1WunWrRsAS5cu5ZtvvkGSJNq1a8c//vEPDAYDvXr1YsCAAezduxdvb28mTZrEDz/8wIULF3jzzTcd21/M8ePH+eCDDygtLWX27Nm88sorzJo1i8TERCRJYurUqdx3330sW7aM5cuXk5+fz4ABA3j44YeZPXs2Fy5cQJIkXnzxRXr27MnOnTt55513AHB1deXdd9/ls88+A2D8+PH89NNP9b5mO3bs4M0330SWZfz9/Xn33XdxcnJi3rx57Ny5E0mSGDVqFE888QS7d+/mk08+4YcffgDs0bhu3brRrVs3pk2bRmhoKMePH8fT05MPP/yQxYsXk5mZyRNPPMH//vc/3N3dLxk/ISGBl156iVWrVgGwadMmFi1axBdffMFXX33FmjVrsFqt9O7dm+nTpyNJEt9++y0//vgjSqWSAQMGMGbMGBYuXAiAv78/48aNu8Z30PUjRJNAIBAIBAKBoF48/bs0iWjQqVOn2LRpE4sXL8bDw4MxY8ZQVFREv379+POf/wxAfHw8q1atQqlUMnToUB588EFOnjzJsWPHWLVqFUVFRYwaNQqAxMREvvjiCxYvXoy7uztz587lk08+YcaMGWRnZ9O/f3/eeOMNpkyZwoYNG1iwYAHLly/nu+++q1c0RURE8NxzzxEXF8c///lP3n77bdzd3Vm1ahW5ubmMHz+e8PBwADIyMvj1119RqVT87W9/Y9y4ccTGxpKZmcmkSZNYsWIFn332GXPmzKFDhw58//33HDt2jFmzZvHDDz9cVjCZTCZeeukl/vOf/xAREcF7773H8uXLUSgUnD9/nl9++QWTycSUKVNo06YNer2+3n0lJCQwb9482rZty7PPPsvKlSt54oknWLhwIV999VWdggkgPDwchULBiRMnaNOmDatWrWLUqFFs2bKFI0eOsGTJEiRJYvr06fzyyy+EhISwYMECli5dil6v57HHHmPYsGFMnDgR4JYKJhCiSSAQCAQCgUBwGxASEoKzszNTp05l165d/Oc//yEpKQmz2UxZWRkAUVFRGI1GAIKCgigoKCAuLo4hQ4agVqvx8PCgb9++AOzZs4cBAwY4LvofeOABXnnlFcd4VesFBATQuXNnwB7tKCwsbPCcd+3axbx58wDw8PAgNjaWuLg4jEYjbdu2RaWyX4rv2LGD1NRUPvroIwAsFgtpaWnExsYybdo0Bg0aRGxsLL169WrQuImJifj6+hIREQHACy+8AMBzzz3HmDFjUCqV6PV6Ro4cyc6dOxk4cGC9+/L09KRt27YAhIaGUlBQ0ODjHz16NKtXryYoKIi4uDjmzZvHBx98wKFDhxg7diwA5eXl+Pv7k52dzYABA3B2dgbg22+/BewRqqaAEE0CgUAgEAgEgiaPTqcD4M033yQtLY0RI0YwaNAgduzYgSzLAGi1Wsf6kiQhyzKSJGGz2RzPVwmVms8ByLKMxWJx/F+j0TgeK5XKa5pz1bxq/t9qtdY6nqq5fPfdd7i5uQH2KJSXlxcREREMGDCATZs28c4773Do0CGeeuqpK46rVqtr/b+oqIiSkpI6j9lqtTpeqyrMZrPjcV2vaUMZMWIEjzzyCOHh4fTu3RutVovVauWRRx7hT3/6EwCFhYUolUqWLFlSa9uMjIzLRsBuNsI9TyAQCAQCgUBw27B9+3amTp3KsGHDOH/+PBkZGZeIgZr06NGDtWvXYjKZKCgoYOvWrQB069aN33//nfz8fAAWL15M9+7db+hcY2JiHGIgNzeXjRs31pnaFxMTw4IFCwBITk5m1KhRlJWVMX78eEpKSnj00Ud59NFHOXbsGGAXcTUF3sWEhISQm5tLcnIyAF9//TU//vgjMTExrFixAqvVSllZGStXrqR79+64u7uTlpZGRUUF+fn57Nu374rHplQqHQKwPnx9ffHz8+Orr75ypEXGxMTw888/U1JSgsVi4ZlnnuG3336jS5cubNmyxfH8iy++yJEjR654rDcLEWkSCAQCgUAgENw2PPnkk7z88su4uLjg6elJ+/btSU9Pr3f9QYMGcfjwYUaMGIGXlxetWrUC7DU3Tz75JFOmTMFsNtOuXTvmzp17Q+f6zDPPMGfOHEaOHInVauUvf/kL7dq1IzExsdZ6s2bNYvbs2YwcORKAt99+G6PRyAsvvMDMmTNRqVRotVrH/GJjYxk9ejTLli2rFQmqQqvV8s477/Dyyy9jNpsJDg7m7bffRqPRcOrUKUaPHo3ZbGbUqFEMHjwYgH79+jF8+PBa6YiXo3///jzxxBN8/fXXBAUF1bve6NGjef/99x2CdODAgSQkJDBhwgSsVit9+vRhzJgxSJLE5MmTmThxIjabjcGDB9OzZ0/UajUzZszAy8vrllqtS/LVxNhuMyoqKjhy5Ajt27ev8w11I9m3b1+D3mCCOwtx3u9exLm/exHn/u6lsc/9zbxuuRLHjx931MMIBHcLl3vfi0iTQCAQCAQCgUBwFbz11lvs2LHjkufbt2/Pv/71r5s2jylTptRpTDFx4kQefPDBmzKHF1980ZEGWJOBAwfy/PPP35Q53AyEaBIIBAKBQCAQCK6CGTNm3OopADj6Kt1KGrOJb1NCGEEIBAKBQCAQCAQCwWUQokkgEAgEAoFAIBAILoMQTQKBQCAQCAQCgUBwGYRoEggEAoFAIBAIBILLIESTQCAQCAQCgeCuYebMmSxbtqzR9n/u3DmGDh3K2LFjKS4ubpQxGtKv6KOPPmLv3r0AHD16lIEDBzJlyhQ+/PBDNm7ceMn6H3/8MR9//DFgb/Q7YMAA3nrrrRs78Yv4/fff+eabbxp1jBuFcM8TCAQCgUAgEAhuEHFxcbRr165RXeXi4uKuuM6ePXscDWU3bdrEiBEjeOGFFxq0/1WrVvH666/Tu3fv65rnlTh69Gij7v9GIkSTQCAQCAQCgaBedqTnsD09p1H23SvQk56Bnldcb/fu3bzzzjvYbDZcXV1RKBQUFRWRlZXF8OHDeemll1i2bBlbt26loKCAtLQ0evXqxZw5c5BlmTfffJPNmzfj4+OD1WqlW7duACxdupRvvvkGSZJo164d//jHPzAYDPTq1YsBAwawd+9evL29mTRpEj/88AMXLlzgzTffdGx/McePH+eDDz6gtLSU2bNn88orrzBr1iwSExORJImpU6dy3333sWzZMpYvX05+fj4DBgzg4YcfZvbs2Vy4cAFJknjxxRfp2bMnO3fu5J133gHA1dWVd999l88++wyA8ePH89NPP9U5jxUrVnDkyBFmzZrF5MmT+fHHHwHQaDSkp6fTrVs3xo4dy9dff83ixYtxd3fHxcWFDh068Mknn3D48GHmzp3LrFmz6Nev3yX7T0hI4KWXXmLVqlWAXZQtWrSIL774gq+++oo1a9ZgtVrp3bs306dPR5Ikvv32W3788UeUSiUDBgxgzJgxLFy4EAB/f3/GjRt3xffBrUSIJoFAIBAIBAJBk+fUqVNs2rSJxYsX4+HhwZgxYygqKqJfv378+c9/BiA+Pp5Vq1ahVCoZOnQoDz74ICdPnuTYsWOsWrWKoqIiRo0aBUBiYiJffPGFQzTMnTuXTz75hBkzZpCdnU3//v154403mDJlChs2bGDBggUsX76c7777rl7RFBERwXPPPUdcXBz//Oc/efvtt3F3d2fVqlXk5uYyfvx4wsPDAcjIyODXX39FpVLxt7/9jXHjxhEbG0tmZiaTJk1ixYoVfPbZZ8yZM4cOHTrw/fffc+zYMWbNmsUPP/xQr2ACuO+++1i6dCnTpk2je/fujga406ZNY+bMmQAcPnyYpUuXsnz5ciRJ4oEHHqBDhw5MmzaN3bt3O7ati/DwcBQKBSdOnKBNmzasWrWKUaNGsWXLFo4cOcKSJUuQJInp06fzyy+/EBISwoIFC1i6dCl6vZ7HHnuMYcOGMXHiRIAmL5hAiCaBQCAQCAQCwWXo2cBoUGMTEhKCs7MzU6dOZdeuXfznP/8hKSkJs9lMWVkZAFFRURiNRgCCgoIoKCggLi6OIUOGoFar8fDwoG/fvoA9fW3AgAG4u7sD8MADD/DKK684xqtaLyAggM6dOwP2iEiVAGkIu3btYt68eQB4eHgQGxtLXFwcRqORtm3bolLZL8V37NhBamoqH330EQAWi4W0tDRiY2OZNm0agwYNIjY2ll69el3z63cxcXFx9OvXD4PBAMDQoUOx2WwN3n706NGsXr2aoKAg4uLimDdvHh988AGHDh1i7NixAJSXl+Pv7092djYDBgzA2dkZgG+//RawR6huF4RoEggEAoFAIBA0eXQ6HQBvvvkmaWlpjBgxgkGDBrFjxw5kWQZAq9U61pckCVmWkSSplhioEioXCwRZlrFYLI7/azQax2OlUnlNc66aV83/W63WWsdTNZfvvvsONzc3wB6F8vLyIiIiggEDBrBp0ybeeecdDh06xFNPPXVNc7mYul4Xk8nU4O1HjBjBI488Qnh4OL1790ar1WK1WnnkkUf405/+BEBhYSFKpZIlS5bU2jYjIwO9Xn9DjuNmIdzzBAKBQCAQCAS3Ddu3b2fq1KkMGzaM8+fPk5GRcdkISY8ePVi7di0mk4mCggK2bt0KQLdu3fj999/Jz88H7I5x9aWjXSsxMTEOwZCbm8vGjRvrTO2LiYlhwYIFACQnJzNq1CjKysoYP348JSUlPProozz66KMcO3YMsIu4mgKvLpRKpUOg1UWPHj3YvHkzRUVFVFRUsH79+qs6Nl9fX/z8/Pjqq68cKY8xMTH8/PPPlJSUYLFYeOaZZ/jtt9/o0qULW7ZscTz/4osvcuTIkQYdR1NBRJoEAoFAIBAIBLcNTz75JC+//DIuLi54enrSvn170tPT611/0KBBHD58mBEjRuDl5UWrVq0Ae13Ok08+yZQpUzCbzbRr1465c+fe0Lk+88wzzJkzh5EjR2K1WvnLX/5Cu3btSExMrLXerFmzmD17NiNHjgTg7bffxmg08sILLzBz5kxUKhVardYxv9jYWEaPHs2yZctqRddq0qdPH1577bV6bcMjIiJ45JFHuP/++3FxccHf3/+qj2/06NG8//77DrE5cOBAEhISmDBhAlarlT59+jBmzBgkSWLy5MlMnDgRm83G4MGD6dmzJ2q1mhkzZuDl5dUgG/VbiSRfHDe8g6ioqODIkSO0b9++3jfUjWLfvn2OfFfB3YM473cv4tzfvYhzf/fS2Of+Zl63XInjx48TERFxS+cgENxsLve+F5EmgUAgEAgEAoHgKnjrrbfYsWPHJc+3b9+ef/3rXzdtHlOmTKnTmGLixIk8+OCD173/F198keTk5EueHzhwIM8///x17/92QogmgUAgEAgEAoHgKpgxY8atngIAP/zwQ6PuvzEb9N5uCCMIgUAgEAgEAoFAILgMQjQJBAKBQCAQCAQCwWUQokkgEAgEAoFAIBAILoMQTQKBQCAQCAQCgUBwGYRoEggEAoFAIBA0aXbv3n3ZPj4zZ85k2bJlN3FGN4ab1Zto0aJFrFq16qaMdaciRJNAIBAIBAKBQHALiIuLuynjxMfHYzKZbspYdyrCclwgEAgEAoFAUC+/7z3D+rgzjbLvwd2CGdgluMHrnzhxgpkzZ2K1WunSpQtbtmxh/fr1AGzevJn//ve/mM1mnnrqKe69916WLVvG5s2byczM5MKFCzzyyCOcO3eOXbt24ebmxtdff33ZRsIrV67k888/R5IkIiMjef3117FYLMyaNYvExEQkSWLq1Kncd999LFu2jLi4ON58803AHkWaNm0aAF9++SU6nY6UlBTCwsKYP38+b7/9NgDjx4/np59+qnP8jRs3snjxYr788ksA/vvf/3Lq1CleeeUV3n77beLi4rBarYwdO5ZHH30UWZaZP38+GzZsQKlU8sADDxAaGsrvv//Orl278Pb2pk+fPg1+vQXVCNEkEAgEAoFAILgtmDlzJs8//zz9+vXj22+/xWq1OpaVlZWxePFicnJyGDduHF27dgXg8OHDrFy5koKCAgYOHMjXX3/Nq6++ypQpU9i6dSuDBg2qc6yMjAz+/e9/s2zZMpo1a8b06dP5448/2L9/P+7u7qxatYrc3FzGjx9PeHj4ZecdHx/PmjVr8PHxYcKECWzbto1Zs2bxww8/1CuYAPr27ctrr71GQUEBrq6urFq1ir///e8sXrwYgOXLl2MymZg6dSrt27cnKyuL/fv3s3LlSsxmM5MmTeLrr79m4MCBdOvWTQim60CIJoFAIBAIBAJBvQzscnXRoMYiPz+fzMxM+vXrB8C4ceP4/vvvHcvHjBmDSqXC19eXTp06cfDg7ISBnAAAQrZJREFUQQCio6MxGo0YjUYAevToAUBAQACFhYX1jhcfH090dDTNmjUD4J133gHgs88+Y968eQB4eHgQGxtLXFycY/91ERoa6thPq1atKCgoaNAxq9VqhgwZwrp16+jZsyf5+fl06NCBr7/+muPHj7Nr1y4ASktLSUxMJCUlhWHDhqHRaNBoNPz8888NGkdwZYRoEggEAoFAIBA0eZRKJbIsX3Z5FbIso1arARx/q1CpGnb5e/F6ubm5jn3XRJZlrFYrkiTVWmY2mx2Pa6YAXrzelRg1ahQffvghBQUFjBgxAgCr1cr06dMZMmSIY25OTk689957tbZNT0/Hw8OjwWMJ6kcYQQgEAoFAIBAImjzOzs4EBwfzxx9/APZ6o5qsXr0aWZY5e/Yshw8fJjIy8rrGi4yM5ODBg2RlZQEwb948Nm7cSExMDEuWLAHsYmXjxo1069YNd3d3UlJSkGWZtLQ0EhMTrziGUqnEYrFcdp1OnTqRmZnJzz//zOjRowGIiYlh8eLFmM1mSkpKmDRpEgcPHqRr166sX78es9lMWVkZjz32GBkZGSiVylqpjIKrR0SaBAKBQCAQCAS3BW+99RZ///vf+eCDDwgLC0On0zmWOTk5MXbsWCwWC//85z+vO8Li6+vLq6++ytSpU7HZbHTq1ImxY8dSVlbGnDlzGDlyJFarlb/85S+0a9cOk8nE0qVLGTp0KCEhIXTu3PmKY8T+//buPKyqcn3j+L2ZQWaZRMRZoZxwHk7iPKBIojlmeRosT2ZZx6NZ6UnTX5mppWmZnTpapzRnHHA2NWczlRJLzQEVUEjFiXH//kC3krBFZQPC93NdXcpea6/1Ll+xffOu51lt2yoiIkKLFi0y25Cic+fO2rp1qypUqCBJ6tOnj06cOKHu3bsrIyNDkZGRatKkiSQpJiZGkZGRysrK0lNPPaXKlSurefPmmjx5slxcXNSpU6cH+nMprQzGfK4PXrp0ScuWLVNMTIwqV66sli1bymAw3LXwrSilpqYqJiZGtWrVMvsXsSDs3bs3X98cKFmY99KLuS+9mPvSy9JzX5ifW+7m0KFDCg4OLtIx5Gb69Onq1auXfHx8tGbNGkVFRWnatGlFPSyUEOb+3udrpem3337T3//+dyUlJclgMKht27a6evWq/vOf/2jGjBl04gAAAIDF+fv765lnnpGNjY1cXV01fvz4Bzre9evX1bt371y3DR06VG3btn2g4+fXgAEDcm1K0adPH/Xt27dQxgDz8hWa3n33XV26dEljx47V6NGjJUmPPvqoJGnKlCmEJgAAAFhcZGSkIiMjC+x4Dg4OxaLD3Ny5c4t6CLiLfDWCuFlY1qtXL9NrHTp0UEhIiI4ePWqxwQEAAABAUctXaHJzc9OxY8eUkpJiei0xMVG///47bQwBAAAAlGj5Ck39+vVTfHy8QkNDZTAY9OOPP6p9+/b6888/1aNHD0uPEQAAAACKTL5qml588UW5uLjo888/19WrV3Xt2jV5eXnpH//4hwYNGmTpMQIAAABAkcnXStOGDRvUuXNnbdq0SXv37tXOnTu1detWvfDCCzIYDJYeIwAAAEqxnTt3asCAAXluHzlypBYtWlTg533jjTd0+vRpSdIPP/yg1q1b6/XXX9ebb76pgwcPmh3Hxx9/rLZt2+rLL78s8HHdbt68eVq+fLlFz4F8rjT961//Uvny5bV06VKVKVPmvk8WFRWlmTNnKj09XQMHDlT//v1zbD927JjGjBmjixcvytvbW5MnT5abm5uWLFmiSZMmqWzZspKkVq1aadiwYfc9DgAAAOBudu7cqZdeekmSFB0drRdffDHPFuV/tXTpUs2ePVuVK1e25BC1b98+NW7c2KLnQD5DU82aNZWcnKyrV6/Kycnpvk6UkJCgKVOmaNGiRbKzs1OfPn3UpEkTVatWTZJkNBo1ePBgvfnmm2rZsqUmTZqkWbNmafjw4Tp48KBGjhyprl273te5AQAA8PD77bffNHLkSGVmZqphw4bavHmz1q5dK0natGmTvv76a6Wnp2vw4MEKCwvTokWLtGnTJiUmJio+Pl5PP/20zpw5ox07dsjd3V2zZ8/O80HCs2bNUmJiogYNGqTHH39c69ev1/bt22VlZaVly5ZpyJAhaty4sd577z1t2rRJPj4+yszMVOPGjTV69GglJCTopZde0ocffpjrA1PXr1+v+fPn67PPPpMkff311zp+/LjeeOMNTZw4Ubt27VJmZqYiIyM1cOBAGY1GTZo0SevWrZO1tbV69+6t6tWra8OGDdqxY4e8vb15DJAF5Ss0+fn5ad++ffrb3/6m6tWry9nZWVZW2Xf2GQwGzZo1667H2LZtm5o2bSp3d3dJUseOHRUdHa0hQ4ZIkn755Rc5OTmpZcuWkrLrqG4+5OvgwYM6ceKEZs2apRo1aujtt9+Wm5vbPV8sAAAA7k3KgU1K2b/BIsd2qdtGLnVa5Xv/kSNH6pVXXlFoaKi++uorZWZmmrZdu3ZN8+fPV1JSknr06KFGjRpJyv4cGRUVpYsXL6pNmzaaPXu23nzzTQ0YMEBbtmxRu3btcj3XoEGD9N1332nWrFkKCAjQsWPH1LhxY0VGRmrZsmWSpNWrV+vXX3/V8uXLlZKSom7dukmSxo4dq61bt5rem5uWLVua7rByc3PT8uXLNWrUKM2fP1+StHjxYqWlpenZZ59VrVq1dO7cOf3000+KiopSenq6+vXrp9mzZ6tNmzZq3LgxgcnC8hWaVqxYIUm6evWq9u/fn2NbfmuaEhMT5e3tbfrax8dHBw4cMH198uRJeXl5acSIEfr1119N4UiSvL29NWjQINWpU0eTJ0/W2LFj9eGHH+brvAAAAHj4XbhwQYmJiQoNDZUk9ejRQ3PmzDFt7969u2xsbOTr66t69eqZPrPWr19fzs7OcnZ2liQ1a9ZMklS+fHnTD+jv165du9ShQwfZ2trK09PT9MP//LC1tVWHDh20Zs0aNW/eXBcuXFCdOnU0e/ZsHTp0SDt27JCU/fn78OHDOnr0qDp37iw7OzvZ2dkVi4fylib5Ck23/4W8X0aj8Y7Xbg9cGRkZ2rVrl77++mvVrl1bU6dO1Xvvvaf33ntPn3zyiWm/5557Ls+fCOQlJibm/gd+D/bu3Vso50HxwryXXsx96cXcl16lce5d6rS6p9UgS7G2ts718+Tt228yGo2ytbWVJNOvN9nY5Ovjb74YDAZlZWXd97G7deumjz76SBcvXjSVoWRmZmr48OHq0KGDJCk5OVlOTk6aPHlyjvfGxcXxvNRClK+ZvVlcdvbsWR04cEAGg0F169aVr69vvk/k6+urPXv2mL5OTEyUj4+P6Wtvb29VrFhRtWvXliR17dpVQ4cOVUpKihYuXKiBAwdKyv4muNe/kLVq1crzftWCsnfvXjVo0MCi50Dxw7yXXsx96cXcl16WnvvU1NRC+0Hvw8jFxUWBgYH64YcfFBoaqqioqBzbV6xYoQ4dOujMmTM6ePCgxo0bp02bNj3QOa2trXPcAvhXzZo10xdffKG+ffvq2rVr2rJli+rVq5fv49erV0+JiYlaunSpZsyYIUlq2rSp5s+fr9atWystLU39+vXTO++8o0aNGmnOnDnq27evMjIy9Nxzz2nmzJl3HSMKRr7SR1ZWlt59913NmzfPlKatrKzUr18/vfnmm/k6UfPmzTVt2jQlJyfL0dFRa9as0bhx40zbQ0JClJycrNjYWAUFBWnDhg169NFH5eTkpNmzZyskJER169bV119/rfbt29/HpQIAAOBh9v7772vUqFGaOnWqatasKQcHB9M2JycnRUZGKiMjQ2PHji2QVZhWrVpp0KBBmj17dq7b27Vrp4MHD6pr167y8vJS1apV7/kcnTt31tatW1WhQgVJUp8+fXTixAl1795dGRkZioyMVJMmTSRl3z0VGRmprKwsPfXUU6pcubKaN2+uyZMny8XFRZ06dbr/i4VZBqO5dc4bPvnkE02bNk1ubm5q0aKFJOnHH3/UpUuX9Oqrr+qFF17I18mioqL02WefKT09XT179tTzzz+v559/XkOHDlXt2rW1f/9+jRs3TteuXZOfn58mTpyosmXLas+ePRo/fryuX7+uSpUqaeLEiXJxcbnr+W7+xIaVJlgK8156MfelF3NfehXWSlNhfG65m0OHDuXa8a2oTZ8+Xb169ZKPj4/WrFmjqKgoTZs2raiHhRLC3N/7fK00LViwQJ6enoqKijI9K+n8+fMKDw/XvHnz8h2awsPDFR4enuO1zz//3PT7unXrasGCBXe8r2HDhlq8eHG+zgEAAICSyd/fX88884xsbGzk6uqq8ePHP9Dxrl+/nudzl4YOHaq2bds+0PElacCAAbk2nOjTp4/69u37wMdH4chXaEpKSlL9+vVNgUmSvLy8VKNGDf3888+WGhsAAABgEhkZqcjIyAI7noODg8W70M2dO9eix0fhsMrPTlWqVNG+ffu0fft202vbt2/Xvn377uveTQAAAAB4WORrpemFF17QsGHD9Mwzz5hWm5KSkiRltwAHAAAAgJIqX6Gpc+fOMhqNmjp1qk6ePCkp+4FggwcPVlhYmEUHCAAAAABFKd8PPAoLC1NYWJguXLggKysrubq6WnJcAAAAAFAs5KumSZK++eYbffXVV3J3d5erq6ueffZZ/fe//7Xk2AAAAACgyOUrNH366ad69913tX79eknZzxHYtm2b3nvvPX322WcWHSAAAAAAFKV8hab58+erbNmyGjt2rCTJ3t5e0dHRKlu2rObPn2/RAQIAAKB027lzpwYMGJDrtlOnTmnUqFGFPKL8W7RokUaOHGl2n6NHj6pfv36KiIhQ7969dejQoUIaHfIrXzVN58+fV4MGDVS5cmXTaxUrVlTVqlW1b98+iw0OAAAAReuHP3Zo4x/bLHLs1pWbK7Ry0wc6xpkzZ3Tq1KkCGlHReOuttzRo0CC1bt1a27dv14gRI7Rs2bKiHhZuk6/QVKlSJe3evVsLFixQ06ZNlZmZqa1bt2rPnj08pwkAAACF4ssvv9TixYtlZWWlOnXqaOzYsXr33XcVFxend955R506ddKnn34qo9GokydPqmPHjnJxcdG6deskSbNmzZKXl1eux/7Pf/6jpKQkDR8+XD/++KOGDBmi3bt3y8bGRmFhYZozZ47i4uI0fvx4paamysPDQ2PHjlXFihU1YMAAubm56ffff9fUqVN1+PBhzZw5U87OzipfvrycnJzMXtcTTzyhli1bSpJq1qyps2fP5rlvRkaGWrVqpSVLlsjLy0sXLlxQ165dtXHjRm3fvl0ff/yxMjIyFBAQoHHjxsnDw8NUVmM0GuXv768PP/xQzs7O9zkLpVO+QtOwYcM0ZMgQvf3223dsGzp0aIEPCgAAAMVDaOWmD7waVBAyMjL02WefacuWLbK2ttY777yjhIQEvfXWW5o+fbrGjBmjnTt3av/+/VqxYoXc3d3VvHlzjRgxQosWLdIbb7yhFStW6Omnn871+KGhoRo+fLgkafv27XJ0dNSvv/4qDw8PlSlTRq6urnrttdc0depU1alTR6tWrdJrr72mhQsXSsoOO9OnT1dCQoImTZqkJUuWyN3dXS+88MJdQ1NkZKTp9x9//LHatWuX5742Njbq1KmToqOj9eSTT2rNmjVq166dUlJS9OGHH2rOnDlyc3PTd999p0mTJmnMmDH65z//qS+++ELBwcGaPHmyFi9enOftjshdvkJT69attWjRIn3++ec6duyYJKlKlSp65pln9Mgjj1h0gAAAAICNjY1CQkLUs2dPtW3bVv3795evr6+OHz+eY78aNWqoXLlykiQPDw81a9ZMkuTv769Lly7lefyqVavq8uXLunjxovbs2aP+/ftr165dcnR0VGhoqI4fPy5XV1fVqVNHUvZzTEePHq2UlBRJMr2+b98+hYSEmFa0wsPDtWPHjrten9Fo1MSJE7V//37NmTPH7L4RERGaMGGCnnzySS1fvlyvvvqq9u/fr7Nnz+qpp56SJGVlZcnNzU2HDx+Wr6+vgoODJUmvvfbaXceCO+X7OU01a9bUpEmTLDkWAAAAIE8zZszQzz//rM2bN+u5557L9bOpra1tjq+tra3zffzHHntMa9eulcFgUOvWrfXRRx/JYDDo5ZdfVlZW1h37G41GZWZmSpIcHBwkSQaDIce+NjZ3/7idkZGhESNGKCEhQXPmzJGLi4vZ/WvXrq2LFy/qwIEDSkhIUP369bVu3TrVr19fn376qaTsbtdXrlxRYmJijvempKToypUr8vPzu+u4cIvZ7nnnzp3TN998ozNnzkiSjh07pldffVVdunTRs88+q82bNxfKIAEAAFC6JScnq3PnzqpRo4ZeeeUVtWjRQocPH5a1tbUyMjIK5ByhoaH67LPP1KBBAwUHB+vIkSP6448/9Oijj6pKlSq6cOGCDhw4IElauXKl/P395e7unuMYDRo00P79+5WQkKCsrCytXLnyrud9//33dfnyZf3nP/+5a2C6KTw8XGPGjFFYWJgkqW7duvr555/1xx9/SMoOmBMnTlTlypWVnJysI0eOSJJmz56tb7/9Nr9/JLghz+j7+++/68knn9SlS5cUHBwsBwcH9e/fXxcuXJDRaNTRo0dNxWbm7rsEAAAAHpSnp6fatm2rnj17ytHRUeXKlVP37t2Vnp6ulJQUDR8+XD179nygczRp0kTnzp1T48aNZTAY9Mgjj5hCkZ2dnaZMmaJx48bp2rVrcnNz05QpU+44hpeXl9566y0NHDhQjo6OqlatmtlzJicn65tvvlFAQICeeOIJ0+tLly41+75u3brpo48+0uTJkyVJ3t7emjBhgl599VVlZWXJ19dXH3zwgezt7fXBBx/oX//6l9LT0xUYGKiJEyfe458MDEaj0ZjbhsGDB2vjxo0KCwvTqFGjtHDhQk2ZMkUeHh6aMWOG4uLiNGLECNWtW7fYptXU1FTFxMSoVq1asre3t+i59u7dqwYNGlj0HCh+mPfSi7kvvZj70svSc1+Yn1vu5tChQ6YaGKC0MPf3Ps+VppiYGAUFBZnS67p162QwGBQREaGQkBCFhITo22+/VWxsrGVGDQAAABSwAQMG5NoQok+fPurbt6/Fzvv666+bbpG7XZs2bfTKK6/c8fpXX32lxYsX3/G6j4+PPv/8c4uMEXnLMzRdvHhRNWrUkJRd2xQTEyNJph7yUnZh3b0U1wEAAABFae7cuUVy3g8//PCe9h84cKAGDhxomcHgnuUZmgIDA7Vv3z7FxMRowYIFMhqN8vDwUNOm2X36t2zZop9++omlWwAAAAAlWp6hqW/fvho3blyOgrTnnntOVlZWev31102dQHgwFgAAAICSLM/Q1L9/f1lZWWnBggWytbVVeHi4+vfvb9ru5uamIUOGKCIiolAGCgAAAABFwezTtvr27ZtrQdzbb799R096AAAAwBJ27typ6dOn51mPNHLkSDVu3FiRkZGFPLJ7N23aNEnSyy+/nOc+e/fu1YQJE5SRkSF3d3dNmDBB5cuXL6whIhdmH26bFwITAAAAYBnDhw/X+PHjtXTpUoWHh+vdd98t6iGVevcVmgAAAIDC9ttvvykyMlIREREaN26c2rdvb9q2adMmRUZGKjw83FR7v2jRIg0dOlR9+vRRq1at9OWXX2r8+PEKDw/XgAEDlJqamue5xo0bp//973+SpPnz56tz586SpPT0dIWGhio9PV0bN25URESEwsPD9Y9//EPnz5+XlN1G/NVXX1XHjh2VlJSk2bNnq0OHDurdu7cOHDhg9hrT0tL0yiuvKCgoSJJUs2ZNnT17Ns/9//zzT7Vo0ULp6emmP6Pw8HBJ0pIlS9S9e3dFRERo1KhRpuuNiopSWFiYunTpopEjR5rei7yZvT0PAAAApVvihk1KWL/BIsf2bdtGPm1a5Xv/kSNH6pVXXlFoaKi++uorZWZmmrZdu3ZN8+fPV1JSknr06KFGjRpJkg4ePKioqChdvHhRbdq00ezZs/Xmm29qwIAB2rJli9q1a5fruUJDQ7VgwQL169dP27dv18WLF3X+/HkdOXJE9erV06VLlzR69Gh9++23CggI0OzZszV27Fh9/PHHkrIf0zN16lQdPHhQCxcu1OLFi2UwGNS7d2/VqVMnz2u0s7Mz9QzIysrS9OnT8xyjJHl4eKhOnTraunWrWrdurRUrVqhbt276/fffNX/+fH333Xeyt7fXhx9+qC+++EI9evTQ//3f/2nRokXy8/PT8OHD9cMPP5g9B1hpAgAAwEPgwoULOn36tEJDQyVJPXr0yLG9e/fusrGxka+vr+rVq6f9+/dLkurXry9nZ2dTTVCzZs0kSeXLl8/1Ibc3NWnSRAcOHFBmZqaOHTumsLAw7d69W5s3b1br1q114MAB1alTRwEBAZKk3r17a8eOHab3161bV5K0a9cuhYaGqkyZMnJyclKnTp3ydb1paWn65z//qYyMDL3wwgtm942IiNCKFSskSatWrVJ4eLh27typEydOqFevXoqIiND69et17Ngx7du3T/Xr15efn58k6YMPPiAw5QMrTQAAAMiTT5tW97QaZCnW1tYyGo1mt99kNBpla2srSaZfb7Kxyd/HX3t7ewUFBSkqKkpVqlRRkyZNtH37du3du1fPPfec9u3bl2N/o9GojIyMHO+XJIPBoKysrBznT0tLM3vuK1euaPDgwXJ3d9fMmTPvuIa/atOmjf7v//5Pu3fvlp+fn/z8/JSZmanOnTvrrbfeMh0zMzNTu3btyvHe5ORkSZKnp+dd/kRKtzxXmpKSkvL9HwAAAGBJLi4uCgwM1A8//CApuy7nditWrJDRaNTp06d18OBB1a5d+4HPGRoaqk8++USNGzdW48aNtX79ejk6OsrT01N169bV/v37FRcXJ0maN2+emjRpcscxmjVrpk2bNiklJUWpqalau3btXc87fPhwVaxYUR999JHs7Ozuur+dnZ0ee+wxTZgwQd26dZOUvVK2du1aJSUlyWg06t///rf++9//qnbt2tq/f7/OnTsnSZowYYLWr19/L38spVKeUbtFixYyGAx3PYDBYNCvv/5aoIMCAAAA/ur999/XqFGjNHXqVNWsWVMODg6mbU5OToqMjFRGRobGjh1bICsnrVq10r///W81btxYbm5uKlu2rFq1aiVJ8vLy0tixYzVkyBClp6fL399f48ePv+MYwcHBevrpp9WzZ0+5urrK39/f7Dl//fVXrV+/XtWqVdPjjz8uSfLx8dHnn39u9n0RERFatmyZ6fa/oKAgDRkyRE8//bSysrIUHBysQYMGyd7eXm+++aaeffZZZWVlqV69eg9Fq/aiZjDmsc45YMAA7d69W5Lk6+ubY8nzrzZssExx4INKTU1VTEyMatWqZVoitZS9e/eqQYMGFj0Hih/mvfRi7ksv5r70svTcF+bnlrs5dOiQgoODi3QMuZk+fbp69eolHx8frVmzRlFRUabnHgEPytzf+zxXmubOnatp06bpk08+UatWrfTOO+9YbIAAAADA3fj7++uZZ56RjY2NXF1dc13ZuRfXr19X7969c902dOhQtW3b9oGOb86AAQNybUTRp08f9e3b947X33//fW3btu2O12vVqvXAfw64O7OVcC+//LJ++eUXzZ8/X127djW1bgQAAAAKW2RkZIHeSubg4KClS5cW2PHuxdy5c+9p/xEjRlhoJMiPu7YPGT16tHbu3Fnky8QAAAAAUBTuGpr8/f3VvXv3whgLAAAAigmj0ZivpmBASWCunb1kpuV427ZtNWbMmByvxcbG6vTp0wUzMgAAABRLDg4OplbVQElnNBqVlJSUoxvjX+W50nT69Ok7nsH0+OOPq3379nQpAQAAKMECAgIUFxdnepYPUNI5ODgoICAgz+35eyTybfiJAwAAQMlma2urypUrF/UwgGIjz9vzAAAAAACEJgAAAAAwy+zteRs3blTdunVNXxsMhlxf+/nnny02QAAAAAAoSmZDU2ZmpjIzM+/6GgAAAACUVHmGptjY2MIcBwAAAAAUS9Q0AQAAAIAZhCYAAAAAMIPQBAAAAABmEJoAAAAAwAxCEwAAAACYQWgCAAAAADMITQAAAABgBqEJAAAAAMwgNAEAAACAGYQmAAAAADCD0AQAAAAAZhCaAAAAAMAMQhMAAAAAmEFoAgAAAAAzCE0AAAAAYAahCQAAAADMIDQBAAAAgBmEJgAAAAAwg9AEAAAAAGYQmgAAAADADEITAAAAAJhBaAIAAAAAMwhNAAAAAGAGoQkAAAAAzCA0AQAAAIAZhCYAAAAAMIPQBAAAAABmEJoAAAAAwAxCEwAAAACYQWgCAAAAADMITQAAAABgBqEJAAAAAMwo1NAUFRWlsLAwtW/fXt98880d248dO6YBAwaoW7duevbZZ3Xx4kVJ0pkzZ9S/f3916tRJgwcP1pUrVwpz2AAAAABKsUILTQkJCZoyZYr+97//aenSpZo3b56OHDli2m40GjV48GA9//zzWrZsmYKDgzVr1ixJ0jvvvKN+/fopOjpatWrV0owZMwpr2AAAAABKuUILTdu2bVPTpk3l7u4uJycndezYUdHR0abtv/zyi5ycnNSyZUtJ0osvvqj+/fsrPT1du3fvVseOHSVJkZGROd4HAAAAAJZkU1gnSkxMlLe3t+lrHx8fHThwwPT1yZMn5eXlpREjRujXX39VjRo19Pbbb+vPP/+Us7OzbGyyh+rt7a2EhIR7OndMTEzBXMRd7N27t1DOg+KFeS+9mPvSi7kvvZh7oHQqtNBkNBrveM1gMJh+n5GRoV27dunrr79W7dq1NXXqVL333nsaNmyY2fflR61atWRvb3/vg74He/fuVYMGDSx6DhQ/zHvpxdyXXsx96WXpuU9NTS20H/QCuDeFdnuer6+vzp8/b/o6MTFRPj4+pq+9vb1VsWJF1a5dW5LUtWtXHThwQJ6enrp8+bIyMzMlSefOncvxPgAAAACwpEILTc2bN9f27duVnJysa9euac2aNab6JUkKCQlRcnKyYmNjJUkbNmzQo48+KltbWzVs2FArV66UJC1ZsiTH+wAAAADAkgrt9jxfX18NGzZMTz31lNLT09WzZ0/VqVNHzz//vIYOHaratWvrk08+0VtvvaVr167Jz89PEydOlCSNGTNGI0eO1MyZM1WuXDlNnjy5sIYNAAAAoJQrtNAkSeHh4QoPD8/x2ueff276fd26dbVgwYI73le+fHnNnTvX4uMDAAAAgL8q1IfbAgAAAMDDhtAEAAAAAGYQmgAAAADADEITAAAAAJhBaAIAAAAAMwhNAAAAAGAGoQkAAAAAzCA0AQAAAIAZhCYAAAAAMIPQBAAAAABmEJoAAAAAwAxCEwAAAACYQWgCAAAAADMITQAAAABgBqEJAAAAAMwgNAEAAACAGYQmAAAAADCD0AQAAAAAZhCaAAAAAMAMQhMAAAAAmEFoAgAAAAAzCE0AAAAAYAahCQAAAADMIDQBAAAAgBmEJgAAAAAwg9AEAAAAAGYQmgAAAADADEITAAAAAJhBaAIAAAAAMwhNAAAAAGAGoQkAAAAAzCA0AQAAAIAZhCYAAAAAMIPQBAAAAABmEJoAAAAAwAxCEwAAAACYQWgCAAAAADMITQAAAABgBqEJAAAAAMwgNAEAAACAGYQmAAAAADCD0AQAAAAAZhCaAAAAAMAMQhMAAAAAmEFoAgAAAAAzCE0AAAAAYAahCQAAAADMIDQBAAAAgBmEJgAAAAAwg9AEAAAAAGYQmgAAAADADEITAAAAAJhBaHpAWRkZOj7na2WdOFnUQwEAAABgATZFPYCHnTE9XUk/blNafIJifz+qSgMHyMHXt6iHBQAAAKCAsNL0gKwdHVXv4ymyadVSf+79ST+99IpOzP1GGVevFfXQAAAAABQAQlMBsLa3l03Lv6n+jGnyatFccQsW6afBQ5Swbr2MWVlFPTwAAAAAD4DQVIDsvcqqxrChqvPBe3Lw9dWRaTO0//V/6eIvvxT10AAAAADcJ0KTBbjUqK7a749XjdeHKf1SimJGjVbs+5N0PSGhqIcGAAAA4B7RCMJCDAaDvFv+TZ5NGunMkmWKW7hYybt2yz8iXAE9e8jGybGohwgAAAAgH1hpsjBre3tV6P2E6s+cJq/H/qbTCxffqnfKzCzq4QEAAAC4C0JTIbEvW1Y1Xn05Z73TP0dQ7wQAAAAUc4SmQka9EwAAAPBwoaapCOSod1oapbgFi6h3AgAAAIopVpqKkLW9vSr06nlnvdPaddQ7AQAAAMUEoakYMNU7TXpfDn6+OjJ9Zna9Uwz1TgAAAEBRIzQVIy7Vq6n2e7fVO705WrHvfaDr8fFFPTQAAACg1KKmqZjJtd5p954b9U6RsnFyKuohAgAAAKUKK03FVO71Ti9T7wQAAAAUMkJTMUe9EwAAAFC0CE0PCVO90z9fU0YK9U4AAABAYaGm6SFiMBjk/VgLeTZumLPeqVtXBTzRg3onAAAAwAJYaXoI3ap3mi7vln/T6UVLqHcCAAAALITQ9BCzL+up6q/8pd7pdeqdAEu7fOSoMg/G6NqZMzIajUU9HAAAYGGFenteVFSUZs6cqfT0dA0cOFD9+/fPsX369OlauHChXF1dJUm9evVS//7983wd2W7WO53fuk0n/jtHMW+OVtlmTVRp4FNy8PMr6uEBJUJmaqrOb/lR8dGrdfn3I5KknxYvk62bm1yCaso1OEguwUFyrlpFVra2RTxaAABQkAotNCUkJGjKlClatGiR7Ozs1KdPHzVp0kTVqlUz7RMTE6PJkycrJCQkx3vzeh233FHvtHCxkne/Qr0T8ICunT6j+OjVStywSRmXL8sxoLwqP/+sTsuoCra2unTosFIOxSp55y5JksHWVi7Vq90KUkFBsnV1KeKrAAAAD6LQQtO2bdvUtGlTubu7S5I6duyo6OhoDRkyxLRPTEyMPv/8c506dUqNGjXSiBEjZG9vn+fruNPNeieftm108utvdHrREiVu2KSKT/aVT5vWMlhbF/UQgWLPmJmp5F27dXbVal3cf0AGa2t5Nm2icp07yrXWozIYDDq7d6/8GjSQX8cOkqS0P/9USuxhXToUq0uHYnVm2XKdXrREkuRY3l8uwUGmEOVY3l8Gg6EIrxAAANyLQgtNiYmJ8vb2Nn3t4+OjAwcOmL6+cuWKgoODNWLECJUvX14jR47UjBkzNGjQoFxfHzZsWGEN/aF0s97JL6yz/vjiSx2ZPlNnV0Sr8rMD5Va7VlEPDyiWUpOSlbB2nRLWrFVaUrLsvLwU2L+vfNu1lZ2nh9n32nl4qGyzpirbrKmk7Nv5Lh85opRDh3UpNnslKnHdBkmSjaurXINqmoKUc7Wq3NIHAEAxZjAWUhXzp59+qmvXrpnCzvfff6+DBw9q7Nixue7/66+/atSoUVqyZEm+Xs9NamqqYmJiHnToDz2j0aisXw8pfd0G6eIlWQXVlE37NrLyMP8hECgNjEajsv44rsy9Pykr9jfJaJRV1SqyblhfVtWryWBVMP1yjEajjOeTlHUqTsZTcdm/Jidnb7S2lqFcOVlVCJBVYICsAsrLUKZMgZwXwMOnVq1a3FEDFDOFttLk6+urPXv2mL5OTEyUj4+P6eszZ85o27Zt6tmzp6TsDxg2NjZ5vn4vCuMfn71796pBgwYWPccDadhQmb17meqd0md+Tr1TASj28448ZVy+rMQNmxQfvVqpp8/IxsVZfhHh8uvUQY7lyt31/QUx92kXLiolNvt2vpRDh3V59x5lbt8hSXLw95drcJBcg7NXpBzLl+eWvmKC7/vSy9Jzzw97geKr0EJT8+bNNW3aNCUnJ8vR0VFr1qzRuHHjTNsdHBz0wQcfqEmTJgoICNA333yj9u3b5/k67l2u9U7rNyrwyX7ybUu9E0qHlN+PKD56tc5v3qqstDS51Kyh6q+8rLItmsm6kH+ya+fuprJNm6hs0yaSpKy0NF0+ctRUF5W8a7cS19+4pc/FxdRcwnRLn51doY4XKM14DiJQuhXqStOwYcP01FNPKT09XT179lSdOnX0/PPPa+jQoapdu7bGjh2rwYMHKz09XfXr19ff//532dnZ5fo67t9f652OfjJT8Supd0LJ9dd24Vb29vJu1VJ+nTvKuUqVoh6eiZWdnVwfCZbrI8GSslfWr50+rZRDsbp0KLvJxJ+7s1fsDTY2cq5aVS7Bt7r02bm7FeXwgRLBmJmp6/EJunrypK6cOKmrJ0/q6olTun72rKw7tpNYZQRKpUKraSoKN5e5uT0vb0ajUUk/btPx/85VauI5nu90jx7WeS8tbrYLT1i/UZlXrsgxIEB+nTvKp3WobB6wZqio5j794kVdij18I0jF6vKRozJmZEiSHPzLyTUoyNRgwrG8f4HVZOEWvu9LBqPRqLTzSbfC0Y2AdC3utLLS0rJ3Mhjk4Ocrp8BAOQVW0LmA8mrYKtRiYyrMzy0A7k2hPtwWxY/BYJDX31rIoxHPd0LJYGoXvjJaFw8czLVd+MPM1s1NZZs0VtkmjSXduKXv6LEbdVGxSt6zV4kbNkqSbFyc5VLz5oN3a8q5WrVCvwURKA7SL168sWp06sbKUfbvM69eNe1jV9ZTToGBcqtTW2UqBsopMFCOFQJyfM+c37u3KIYPoBggNEHSX+ud/ndbvVNf+bZtQ70Tir3UpCQlrFmnhDXrlJZ8W7vw9m1lV4I7RVrZ2ZnqnKTsn55fP3PWVBeVEhurP/dkf9Az2NioTJXKpv1dgoNkd+PZeUBJkHH1qq6diruxcnQiOySdOKn0ixdN+9i4OMupYkV5t2opp8DAGwGpgmycnYtw5ACKO0ITcsiudxoiv7BON+qdPr1R7/R36p1Q7BiNRl08cFDxq6KVtHO3lJUl95B6qvLiIHk2rF8qw77BYJBjeX85lveXb7s2kqT0S5dMD95NiT2ssyujdWZplCTJwc/vxu182StSjgEB3NKHYi8rLU1X407nWDW6evKkUhPPmfaxcnCQU4UK8mjU4FY4qhgoW3f3h37FGUDhIzQhVy7Vq6n2/71rqneKeWuMPJtm1zs5lqPeCUXrZrvws6tW6/qZ7Hbh/t265rtdeGlj6+oqz8aN5Nm4kSQpKz1dl48eM9VFXfjpJ53buEmSZOPsLJeaNW49eLc6t/Sh6BgzM3XtbHx2OLqxanT1xAldOxsvZWVJyl5BdQwoL5egIPl17CCnwApyqhgoe29vfgAAoMAQmpCnHPVOy5YrbsEi7RtCvROKTsrvRxS/arXOb7nVLrzCqy/Lq0Vz2m/fAytbW7kG1ZRrUE2V7x6RfUvf2bOm50VdOhSrP/f+JEkyWFurTJUqpudFuQYHlejbHVE0jEajUs+duxWMbnSsuxoXJ2N6evZOBoMcyvnJKTBQZVs0N9UdOfiXk9U9Pr8RAO4V/8rgrqzt7VXhiR7ybdtGJ+Z+Q70TClV2u/Ctil+1WpePHM1uF946VH6dOsq5SuWiHl6JYDAY5OjvL0d/f/m2vXlLX4pSDh82NZiIj16jM8uWS5Ic/HzlEnSrLsqpArf0If/SLly87ba625oyXLtm2sfOy0tlKlaQe7062Z3rKgbKMaA8q54AigyhCflm5+mh6q8MUbkunXPUO1V6ZqDc69Qu6uGhhLkad1rx0WuUuOFWu/Aqg56Vd6sHbxeOu7N1dZFno4bybNRQUvYtfVeO/WFqMHFh3886t+kHSZJ1GadbXfqCasqlRnVZOzgU5fBRDGRcuXJbt7obv548qfSLl0z72Li4yKlioHzatDKFI6cKFWTjzPc4gOKF0IR75lytqmpNGKekbdt1/Ks5+uXtf1PvhAKRlZGh5F27Fb9qdc524WGd5ProIxRvFyErW9vsWqeaNVT+8W7Zt/TFx5vqolJiD+vkN99KunFLX+VKptv5XIKCZF/Ws4ivAJaSmZqqa6dP32rIcCL7uUdp58+b9rFycFCZioHybNxYThUrmAKSrZsb39cAHgqEJtwXg8EgrxbN5dGwQc56p/AuCujVk3on3JPS2i78YWYwGORYrpwcy5WTT5vWkrIbdJgevBt7WAmr1+ps1ApJkr2Pj+l5Ua7BQXKqUIFbex8yxsxMXTtzNsetdVdOnNL1+JxNGZwqBMjt0UdMDRmcAgNl7+3FLZwAHmqEJjyQO+qdFi9V4oZN1DvhroxZWdntwqNX32oXXj+kVLcLf9jZODvLs2EDeTZsIOnGLX1/HDfVRV04cEDnftgsSbJ2cpJLzRqmuihu6Ss+jFlZSj13/o523ldPxcmYkZG9k5WVHPz8VKZiBXm3/NuNlaMKcixXju9dACUSoQkFIrd6p7MrVqnys3+n3gk5ZFy+rIT1GxUfveZGu3AXlY8Il2/HDtzeWcJY2drKpUZ1udSoLkWEZ3dIS0i4URd1WCmxsTr57TzJaJSsrFSmcmXT86JcgoNkX7ZsUV9CiWY0GpV+4YIpGF252Zjh5CllXb9u2s/e20tOgYFyD6lnWj1yLE9TBgClC6EJBYp6J+TlznbhNWkXXsoYDAY5+PnJwc9PPq1bSZIyLl8xdem7dChWCWvW6ezylZIkex9vU5c+1+AgOQVyS9/9yrh8RVdPnbrttrrsVaSMlBTTPjauripTMVC+bdvIqVL2bXVOFQJovAIAIjTBAm7WO3neeL7Tqe8X3qp3eqIH/wMuRe5oF+7gQLtw5GDjXEYeDerLo0F9SdnNQK78cdzUYOLiwRid37xFkmTt6HjrwbtBNeVSs4asHR2LcvjFTmZqqq6dirsVjG40ZkhLSjLtY+3omP2so2ZNbnWsCwyUnbtbEY4cAIo3QhMsxsrOTgE9I+XTprVOfP0/nV6yTIkbNmYX+Ldry0+MS7A72oVXoF048sfKxkYu1avJpXo1+Xfrmn1LX2KiqS7qUuxhnfpu/q1b+ipVNHXocw0Okr23V1FfQqHIysjQ9RtNGa7cVnd0/Wx89p+NJIOtrZwCAuRW+1FTOCpTMVB2Xl50rAOAe0RogsXZeXqo+tCXVC6sU3a904zPdHZlNPVOJcwd7cJtbFS2aRP5hXWU6yO0C8f9MRgMcvD1lYOvr3xahUrKfv5PyuHfTK3OE9Zt0NkVqyRlPxT19rqoMhUrPtQ/oMluynBOV46fND3n6OqJk7p2+kyOpgyO/uVUplIleYe2zK47CgyUYzm/h/raAaA4ITSh0ORa79SksSr9/Sk5litX1MPDfbrZLjx+9Vql//mn7L29FPhkv+x24e7uRT08lEA2ZcrIo36IPOqHSMpuhX2zS9+lQ7G69Oshnd/yo6Ts5wPd7NLnGhwk5xo1ZONU/G7pMxqNSv/zwm0rRzceCHvqL00ZfLzlFBgojwb1b6wcVZRjeX/qAgHAwghNKFS51zu9Sr3TQ+Zmu/Czq1YredduyWiUe0g9lfvHC/JoQLtwFC6DtbWcq1WVc7Wq8g/vkn1L37lzSjl0+MZqVKxOzfv+1i19FSuanheVfUufd6GON+Py5ZzB6MYKUkbKZdM+tu7ucgqsIN/2beUUmH1bnWOFAJ6BBwBFhNCEIpGj3ukb6p0eFukpKUrccLNd+FnahaNYMhgMcvDxkYOPj7xDH5MkZVy9qpTDv5kaTCRu2KT4ldGSJLuyZU2387kGB6lMpYK5pS8zNfXWM45O3upcl5aUbNrH2slJToEVVLZ5s+y6o8AKKlMxULZuNGUAgOKE0IQiZefpoeovv6Rynal3Ks5Sfj+i+JXROr/1x1vtwoc9Ia/mzbgtCA8FGycneYTUk0dIPUk3buk7fuJWg4lDsTq/9bZb+mpUv/Xg3Zo1zK7wZDdlOKMrJ07p6okTphWk6wkJpqYMVnZ2cqwQILc6dUzByCkwUHZeZan3A4CHAKEJxcKteqcd1DsVEzfbhZ9duVpXjtIuHCWLwdpazlWryLlqFalrmCQp9dw5U11UyqHDOvX9QikrSzIY5FQx0NSlL/PMaZ06+odpBenOpgz+KlO1srxbh5rCkYOfLyvoAPAQIzSh2Miud2omz0YNctQ7lesapgq9elLvVEiy24WvVuKGTbe1C39O3q1aMgco0ey9veXt7S3vljdv6bumy7/d6tKXuPEHxa9aLUk6Kcnex0dOFSvIs1HDGy29K8ixfHlZ2doW4VUAACyB0IRi56/1TmeWRuncxk3UO1lQVkaGknfuVnz0be3CmzWRX2fahaP0snFylHu9unKvV1fSjVv6TpzUoYMHFdK+fbHswgcAsAxCE4otU71TWGf9Mfs/1DtZQOr5JCWsWav4NetoFw7chcHaWs5VKsvqz2QCEwCUMoQmFHvOVatQ71SAcmsX7lG/nvw60S4cAAAgN4QmPBSod3pwd7QLd3VV+ce7ya9jezn40S4cAAAgL4QmPFTyrHfq11e+7al3+iuj0ajLvx9R/KrVt9qFB9VUhd60CwcAAMgvQhMeSnfUO838TGdXrlLl556h3kk32oVv3qKzq9bc1i68lcp17qgylSsV9fAAAAAeKoQmPNRM9U7bd+j4lzfrnRqp0sCn5OjvX9TDK3RX4+IUH73G1C7cKbBCdrvw1qFmH84JAACAvBGa8NAzGAzyat5Mng1vq3d6eVipqXeiXTgAAIBlEZpQYpjqndq21omvvy3x9U60CwcAACgchCaUOHYeHqr+8j9ULqyT/vjiyxJV72RqF74yWsm799xqF975RXnUDylxwRAAAKA4IDShxHKuWkW1xo8tEfVOpnbhq1br+tl42oUDAAAUIkITSjSz9U5P9JSNc/Gtd7rVLjxa57duu9UuvE9vebVoJitb26IeIgAAQKlAaEKpkFu9U+KGTarYv/jVO2Vev65zm7cqPnq1rhw9JisHB/m0aSW/zh1VplKloh4eAABAqUNoQqliqnfq0kl/zL6t3unZv8u9bp0iHdvVuDjFr1qtxI2blHnlqpwqBqrKC8/Lu1VL2oUDAAAUIUITSiXnKrfVO301R7+MfkeejRup0t8Lt97J1C58VbQuHozJbhfevKn8OnWU6yPBtAsHAAAoBghNKLVy1DtFrdCp+QsKrd4p9XyS4levUcLa9aZ24RUH9JdPuza0CwcAAChmCE0o9azs7BTQo7t82rTKUe8U2K+P/Dq0K7B6J2NWli7sP6D4VatvaxceQrtwAACAYo7QBNzw13qnY5/OUvyq6Aeud0q/dKNdePRf2oV36iAHX98CvAIAAABYAqEJ+Iub9U7JO3bqjy//e1/1TkajUZd/+13x0atvtQsPDqJdOAAAwEOI0ATkwmAwqGyzpvJoUF9nolYo7ubznbp0VoVeT+RZ70S7cAAAgJKH0ASYcXu908lvvtOZZcuVuPEHU73TTVdPxSk+mnbhAAAAJRGhCcgHOw8PVRsyWH5hnfTHF7fqnTKCgxSzeFmOduHlOneSS3AQ7cIBAABKCEITcA+cq1RWrXffMdU7ZUSv0XUf7xvtwtvKzt2tqIcIAACAAkZoAu7R7fVOe9esVYPOnWgXDgAAUIJZFfUAgIeVlZ2drMr5EZgAAABKOEITAAAAAJhBaAIAAAAAMwhNAAAAAGAGoQkAAAAAzCA0AQAAAIAZhCYAAAAAMIPQBAAAAABmEJoAAAAAwAxCEwAAAACYQWgCAAAAADMITQAAAABgBqEJAAAAAMwgNAEAAACAGYQmAAAAADCD0AQAAAAAZhCaAAAAAMAMm6IegCUZjUZJUlpaWqGcLzU1tVDOg+KFeS+9mPvSi7kvvSw59zc/r9z8/AKg+DAYS/B3ZkpKin777beiHgYAAEC+1ahRQy4uLkU9DAC3KdGhKSsrS1euXJGtra0MBkNRDwcAACBPRqNR6enpKlOmjKysqKAAipMSHZoAAAAA4EHxYwwAAAAAMIPQBAAAAABmEJoAAAAAwAxCEwAAAACYQWgCAAAAADMITQAAAABgBqEJAAAAAMwgNAEAAACAGYSmv3jjjTfUsWNHLV++PNftNWvWzPX1Nm3aKC4u7q7Hv3z5srp27ZqvfVF4LDnv06dPV5cuXdSlSxdNnDjxgceKgmXJuf/oo48UFhamLl266Msvv3zgsaJgWfrfe0l6//33NXLkyPseIyzDknP/1FNPqUuXLoqIiFBERIT279//wOMFUPRsinoAxc3ixYt14MAB2dnZFfix9+/fr7feekvHjx8v8GPjwVhq3rdt26atW7dq8eLFMhgMeu6557R27Vq1b9++QM+D+2epud+1a5d27NihZcuWKSMjQ2FhYQoNDVWVKlUK9Dy4f5b8916Stm/frsWLF6tVq1YWOT7un6Xm3mg06tixY9q0aZNsbPiIBZQkfEff5sUXX5TRaNQTTzyhLl26aNmyZTIYDHr00Uf19ttvq0yZMqZ9L1y4oOHDhys+Pl5Vq1ZVamrqXY8/f/58jRkzRv/6178seRm4R5acd29vb40cOdL0P+aqVavqzJkzFr0e5J8l575x48aaM2eObGxslJCQoMzMTDk5OVn6kpBPlv73/sKFC5oyZYpefPFFxcbGWvJScI8sOffHjh2TwWDQ888/r6SkJPXq1UtPPvmkpS8JQCHg9rzbfPrpp5KkiRMn6vvvv9fcuXMVFRUlR0dHTZ8+Pce+H3/8sR555BFFRUWpf//+On/+/F2PP378eDVs2NAiY8f9s+S8V69eXfXq1ZMkHT9+XCtXrlRoaKhFrgP3ztLf87a2tvr444/VpUsXNWvWTL6+vha5Dtw7S8/96NGjNWzYMLm6ulpk/Lh/lpz7S5cuqVmzZvrkk0/01Vdf6bvvvtOPP/5osWsBUHgITbnYvXu3WrduLQ8PD0lS7969tWPHjhz77Nq1S2FhYZKkRo0aqUKFCoU+ThQsS87777//rmeeeUYjRoxQpUqVCnTceHCWnPuhQ4dq+/btOnv2rObPn1+wA8cDs8Tcf//99ypXrpyaNWtmmUGjQFhi7kNCQjRx4kQ5OTnJ09NTPXv21A8//GCZCwBQqLg9LxdZWVk5vjYajcrIyMjxmsFgkNFoNH1tbW1dKGOD5Vhq3vfu3auhQ4dq1KhR6tKlS8EMFgXKEnN/9OhRpaWlKTg4WI6OjurQoYMOHz5ccINGgbDE3K9cuVLnzp1TRESELl68qKtXr2rChAkaNWpUwQ0cD8wSc79nzx6lp6ebArPRaKS2CSghWGnKRePGjbVhwwZduHBBUnYtUpMmTXLs06xZMy1dulSSdODAAZ08ebKwh4kCZol5P3v2rF566SVNmjSJwFSMWWLu4+Li9NZbbyktLU1paWlav369GjRoYJHx4/5ZYu6//PJLLV++XEuXLtXQoUPVpk0bAlMxZIm5T0lJ0cSJE5WamqrLly9r8eLFNP4BSgh+/JGLoKAgvfDCCxowYIDS09P16KOP6p133smxz9ChQzVy5Eh16dJFVapU4fa8EsAS8/7FF18oNTVV7733num1Pn36qG/fvha5BtwfS8x9aGio9u/fr8cff1zW1tbq0KEDwbkY4t/70ssSc9+6dWvT931WVpb69eunkJAQS14GgEJiMN6+7gwAAAAAyIGVpgK0Z88ejRs3Ltdts2bNonNWCcW8l17MfenF3JdezD1QOrHSBAAAAABm0AgCAAAAAMwgNAEAAACAGYQmAAAAADCDRhAASp2aNWvm+nr58uW1YcOGfB/Dzs5OBw8ezHX7ihUr9Nprr6l79+45Ws4DAICHD6EJQKlkZWWl1q1b53itbNmyRTQaAABQnBGaAJRKNjY2mjFjRlEPAwAAPASoaQKAXOzYsUN9+vRR3bp11aJFC40fP17Xr1/Pc//Y2Fj16dNHtWvXVt++fXXq1Kkc2xMTE/XKK6+oWbNmqlevniIjI7VlyxZLXwYAACgAhCYA+IuffvpJzzzzjPbv36/atWvLxsZGc+bM0csvv5zr/unp6XrppZe0b98++fv769q1a/roo49y7PPuu+8qOjpa5cqVU0hIiA4fPqyXXnpJCQkJhXFJAADgAXB7HoBSKS0t7Y6GEEuWLFFwcLCmTZumzMxMjRs3Tr169dLVq1fVvXt3bd68WXv27FHDhg1zvG/Lli2Ki4tTrVq1NG/ePFlbW2vw4MHauHGjaZ9Tp07JxsZGEyZMUFBQkNatW6fLly/L1ta2UK4XAADcP1aaAJRKVlZWatu2bY7/nJ2dJUk///yzJKlbt26SJCcnJ7Vv3z7HttudPHlSkvTYY4/JxsZGBoNBrVq1yrFP//79lZmZqYiICLVp00abN29W5cqV5enpaZkLBAAABYaVJgClkrlGEFZWef88yWAw5Pma0WjM8xg9e/ZUnTp1tHLlSu3YsUMLFy7UvHnz9Mknn6hdu3b3cwkAAKCQsNIEAH/xyCOPSJKWLVsmSbp69arWrl0rSapXr94d+1epUkVS9m166enpMhqNWr9+vWl7Wlqa3n33XU2fPl2DBw/Wd999p3//+9+SpO3bt1vwSgAAQEFgpQkA/uLFF1/Unj17NGbMGC1btkynTp1SfHy8WrdurQYNGtyxf4sWLVS9enX98ssv6tq1qxwdHXXixAnTdjs7O8XFxWnjxo06dOiQKlasaLrN76/1UQAAoPhhpQkA/qJFixaaPXu26tWrp4MHDyo9PV0DBw68oyPeTVZWVpo+fboaNmyoM2fOqEyZMho3blyOfT744AP17t1b169f165du+Tt7a3Ro0erc+fOhXFJAADgARiMt9+EDwAAAADIgZUmAAAAADCD0AQAAAAAZhCaAAAAAMAMQhMAAAAAmEFoAgAAAAAzCE0AAAAAYAahCQAAAADMIDQBAAAAgBn/D/mQWjPNVLkSAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# transposing the dataframe\n",
    "model_names = models_df[\"model_name\"].values\n",
    "model_names_mappings = dict(zip(range(0, len(model_names)), model_names))\n",
    "transpose_models_df = models_df.loc[:, \"fold_1\":\"fold_5\"].T.rename(columns=model_names_mappings)\n",
    "\n",
    "x = transpose_models_df.index\n",
    "fig, ax = plt.subplots(figsize=(10,8))\n",
    "\n",
    "for model in transpose_models_df.columns:\n",
    "    plt.plot(x, transpose_models_df[model], label=model)\n",
    "plt.title(\"Model Performances\", size=20, weight=\"bold\")\n",
    "plt.xlabel(\"Folds\", size=14, weight=\"bold\")\n",
    "plt.ylabel(\"F1 Score\", size=14, weight=\"bold\")\n",
    "plt.legend(title=\"Models\", bbox_to_anchor=(1.05, 1), loc=\"upper left\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating model...\n",
      "Compiling...\n",
      "Epoch 1/8\n",
      "167/167 [==============================] - 82s 463ms/step - loss: 0.5679 - accuracy: 0.7120\n",
      "Epoch 2/8\n",
      "167/167 [==============================] - 78s 470ms/step - loss: 0.4423 - accuracy: 0.8095\n",
      "Epoch 3/8\n",
      "167/167 [==============================] - 82s 489ms/step - loss: 0.4185 - accuracy: 0.8195\n",
      "Epoch 4/8\n",
      "167/167 [==============================] - 83s 497ms/step - loss: 0.3843 - accuracy: 0.8404\n",
      "Epoch 5/8\n",
      "167/167 [==============================] - 83s 497ms/step - loss: 0.3576 - accuracy: 0.8475\n",
      "Epoch 6/8\n",
      "167/167 [==============================] - 83s 496ms/step - loss: 0.3375 - accuracy: 0.8602\n",
      "Epoch 7/8\n",
      "167/167 [==============================] - 87s 523ms/step - loss: 0.3247 - accuracy: 0.8629\n",
      "Epoch 8/8\n",
      "167/167 [==============================] - 88s 526ms/step - loss: 0.2990 - accuracy: 0.8753\n",
      "\n",
      "\n",
      "Train F1 Score: 0.8829623098964073\n",
      "Valid F1 Score: 0.76232308443143\n"
     ]
    }
   ],
   "source": [
    "# training a single LSTM model\n",
    "X_train, X_valid, y_train, y_valid = train_test_split(X_padded, y, test_size=.3, shuffle=True, random_state=24)\n",
    "\n",
    "clf = my_LSTM(embedding_layer)\n",
    "clf.fit(X_train,\n",
    "        y_train,\n",
    "        epochs=n_epochs,\n",
    "        verbose=1)\n",
    "\n",
    "# make predictions\n",
    "y_preds = clf.predict_classes(X_valid, verbose=-1)\n",
    "y_train_preds = clf.predict_classes(X_train, verbose=-1)\n",
    "\n",
    "print(f\"\\n\\nTrain F1 Score: {f1_score(y_train ,y_train_preds)}\\nValid F1 Score: {f1_score(y_valid ,y_preds)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         0.0       0.81      0.80      0.81      1272\n",
      "         1.0       0.75      0.77      0.76      1012\n",
      "\n",
      "    accuracy                           0.79      2284\n",
      "   macro avg       0.78      0.79      0.78      2284\n",
      "weighted avg       0.79      0.79      0.79      2284\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# printing the report\n",
    "print(classification_report(y_valid, y_preds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting confusion matrix\n",
    "labels= [\"Negative\", \"Positive\"]\n",
    "cm = confusion_matrix(y_valid, y_preds)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 8))\n",
    "sns.heatmap(cm, annot=True, fmt=\"g\", ax=ax)\n",
    "plt.xlabel(\"Predicted Labels\")\n",
    "plt.ylabel(\"Actual Labels\")\n",
    "plt.title(\"Confusion Matrix\", size=20, weight=\"bold\")\n",
    "plt.yticks(ticks=[0.5, 1.5], labels=labels)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Overcoming Overfitting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Removing a Layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating model...\n",
      "Compiling...\n",
      "Model: \"sequential_4\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "embedding (Embedding)        (None, 202, 300)          5187000   \n",
      "_________________________________________________________________\n",
      "bidirectional_4 (Bidirection (None, 128)               186880    \n",
      "_________________________________________________________________\n",
      "dropout_4 (Dropout)          (None, 128)               0         \n",
      "_________________________________________________________________\n",
      "dense_6 (Dense)              (None, 1)                 129       \n",
      "=================================================================\n",
      "Total params: 5,374,009\n",
      "Trainable params: 187,009\n",
      "Non-trainable params: 5,187,000\n",
      "_________________________________________________________________\n",
      "None\n",
      "Epoch 1/8\n",
      "167/167 [==============================] - 82s 466ms/step - loss: 0.5715 - accuracy: 0.7045\n",
      "Epoch 2/8\n",
      "167/167 [==============================] - 77s 458ms/step - loss: 0.4393 - accuracy: 0.8113\n",
      "Epoch 3/8\n",
      "167/167 [==============================] - 76s 458ms/step - loss: 0.4231 - accuracy: 0.8188\n",
      "Epoch 4/8\n",
      "167/167 [==============================] - 78s 467ms/step - loss: 0.3999 - accuracy: 0.8280\n",
      "Epoch 5/8\n",
      "167/167 [==============================] - 79s 471ms/step - loss: 0.3837 - accuracy: 0.8337\n",
      "Epoch 6/8\n",
      "167/167 [==============================] - 77s 462ms/step - loss: 0.3669 - accuracy: 0.8503\n",
      "Epoch 7/8\n",
      "167/167 [==============================] - 78s 466ms/step - loss: 0.3452 - accuracy: 0.8561\n",
      "Epoch 8/8\n",
      "167/167 [==============================] - 78s 465ms/step - loss: 0.3309 - accuracy: 0.8621\n",
      "\n",
      "\n",
      "Train F1 Score: 0.8097186700767264\n",
      "Valid F1 Score: 0.728110599078341\n"
     ]
    }
   ],
   "source": [
    "def my_LSTM(embedding_layer):\n",
    "    print('Creating model...')\n",
    "    model = Sequential()\n",
    "    model.add(embedding_layer)\n",
    "    model.add(Bidirectional(LSTM(units=64, dropout=0.1,  recurrent_dropout=0.1)))\n",
    "    model.add(Dropout(0.1))\n",
    "    model.add(Dense(1, activation = \"sigmoid\"))\n",
    "\n",
    "    print('Compiling...')\n",
    "    model.compile(loss='binary_crossentropy',\n",
    "                  optimizer='adam',\n",
    "                  metrics=[\"accuracy\"])\n",
    "    return model\n",
    "\n",
    "# training a single LSTM model\n",
    "X_train, X_valid, y_train, y_valid = train_test_split(X_padded, y, test_size=.3, shuffle=True, random_state=24)\n",
    "\n",
    "# initializing model\n",
    "clf = my_LSTM(embedding_layer)\n",
    "print(clf.summary())\n",
    "\n",
    "# training the model\n",
    "clf.fit(X_train,\n",
    "        y_train,\n",
    "        epochs=n_epochs,\n",
    "        verbose=1)\n",
    "\n",
    "# make predictions\n",
    "y_preds = clf.predict_classes(X_valid, verbose=-1)\n",
    "y_train_preds = clf.predict_classes(X_train, verbose=-1)\n",
    "\n",
    "print(f\"\\n\\nTrain F1 Score: {f1_score(y_train ,y_train_preds)}\\nValid F1 Score: {f1_score(y_valid ,y_preds)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adding L2 Normalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating model...\n",
      "Compiling...\n",
      "Model: \"sequential_5\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "embedding (Embedding)        (None, 202, 300)          5187000   \n",
      "_________________________________________________________________\n",
      "bidirectional_5 (Bidirection (None, 128)               186880    \n",
      "_________________________________________________________________\n",
      "dense_7 (Dense)              (None, 50)                6450      \n",
      "_________________________________________________________________\n",
      "dropout_5 (Dropout)          (None, 50)                0         \n",
      "_________________________________________________________________\n",
      "dense_8 (Dense)              (None, 1)                 51        \n",
      "=================================================================\n",
      "Total params: 5,380,381\n",
      "Trainable params: 193,381\n",
      "Non-trainable params: 5,187,000\n",
      "_________________________________________________________________\n",
      "None\n",
      "Epoch 1/8\n",
      "167/167 [==============================] - 90s 510ms/step - loss: 0.6336 - accuracy: 0.6936\n",
      "Epoch 2/8\n",
      "167/167 [==============================] - 81s 488ms/step - loss: 0.4739 - accuracy: 0.8026\n",
      "Epoch 3/8\n",
      "167/167 [==============================] - 81s 484ms/step - loss: 0.4174 - accuracy: 0.8353\n",
      "Epoch 4/8\n",
      "167/167 [==============================] - 81s 485ms/step - loss: 0.3988 - accuracy: 0.8388\n",
      "Epoch 5/8\n",
      "167/167 [==============================] - 81s 487ms/step - loss: 0.3894 - accuracy: 0.8422\n",
      "Epoch 6/8\n",
      "167/167 [==============================] - 82s 488ms/step - loss: 0.3728 - accuracy: 0.8560\n",
      "Epoch 7/8\n",
      "167/167 [==============================] - 82s 491ms/step - loss: 0.3421 - accuracy: 0.8665\n",
      "Epoch 8/8\n",
      "167/167 [==============================] - 83s 498ms/step - loss: 0.3111 - accuracy: 0.8754\n",
      "\n",
      "\n",
      "Train F1 Score: 0.889921040408732\n",
      "Valid F1 Score: 0.7503812913065582\n"
     ]
    }
   ],
   "source": [
    "def my_LSTM(embedding_layer):\n",
    "    print('Creating model...')\n",
    "    model = Sequential()\n",
    "    model.add(embedding_layer)\n",
    "    model.add(Bidirectional(LSTM(units=64, dropout=0.1,  recurrent_dropout=0.1)))\n",
    "    model.add(Dense(50, kernel_regularizer=regularizers.l2(0.001), activation=\"relu\"))\n",
    "    model.add(Dropout(0.1))\n",
    "    model.add(Dense(1, activation = \"sigmoid\"))\n",
    "\n",
    "    print('Compiling...')\n",
    "    model.compile(loss='binary_crossentropy',\n",
    "                  optimizer='adam',\n",
    "                  metrics=[\"accuracy\"])\n",
    "    return model\n",
    "\n",
    "# training a single LSTM model\n",
    "X_train, X_valid, y_train, y_valid = train_test_split(X_padded, y, test_size=.3, shuffle=True, random_state=24)\n",
    "\n",
    "# initializing model\n",
    "clf = my_LSTM(embedding_layer)\n",
    "print(clf.summary())\n",
    "\n",
    "# training model\n",
    "clf.fit(X_train,\n",
    "        y_train,\n",
    "        epochs=n_epochs,\n",
    "        verbose=1)\n",
    "\n",
    "# make predictions\n",
    "y_preds = clf.predict_classes(X_valid, verbose=-1)\n",
    "y_train_preds = clf.predict_classes(X_train, verbose=-1)\n",
    "\n",
    "print(f\"\\n\\nTrain F1 Score: {f1_score(y_train ,y_train_preds)}\\nValid F1 Score: {f1_score(y_valid ,y_preds)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adding Dropout Layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating model...\n",
      "Compiling...\n",
      "Model: \"sequential_6\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "embedding (Embedding)        (None, 202, 300)          5187000   \n",
      "_________________________________________________________________\n",
      "dropout_6 (Dropout)          (None, 202, 300)          0         \n",
      "_________________________________________________________________\n",
      "bidirectional_6 (Bidirection (None, 128)               186880    \n",
      "_________________________________________________________________\n",
      "dense_9 (Dense)              (None, 50)                6450      \n",
      "_________________________________________________________________\n",
      "dropout_7 (Dropout)          (None, 50)                0         \n",
      "_________________________________________________________________\n",
      "dense_10 (Dense)             (None, 1)                 51        \n",
      "=================================================================\n",
      "Total params: 5,380,381\n",
      "Trainable params: 193,381\n",
      "Non-trainable params: 5,187,000\n",
      "_________________________________________________________________\n",
      "None\n",
      "Epoch 1/8\n",
      "167/167 [==============================] - 92s 522ms/step - loss: 0.6460 - accuracy: 0.6808\n",
      "Epoch 2/8\n",
      "167/167 [==============================] - 86s 518ms/step - loss: 0.4942 - accuracy: 0.7935\n",
      "Epoch 3/8\n",
      "167/167 [==============================] - 88s 526ms/step - loss: 0.4700 - accuracy: 0.7962\n",
      "Epoch 4/8\n",
      "167/167 [==============================] - 86s 514ms/step - loss: 0.4644 - accuracy: 0.8044\n",
      "Epoch 5/8\n",
      "167/167 [==============================] - 85s 510ms/step - loss: 0.4493 - accuracy: 0.8150\n",
      "Epoch 6/8\n",
      "167/167 [==============================] - 85s 509ms/step - loss: 0.4220 - accuracy: 0.8238\n",
      "Epoch 7/8\n",
      "167/167 [==============================] - 85s 511ms/step - loss: 0.4256 - accuracy: 0.8151\n",
      "Epoch 8/8\n",
      "167/167 [==============================] - 87s 523ms/step - loss: 0.3985 - accuracy: 0.8292\n",
      "\n",
      "\n",
      "Train F1 Score: 0.8205128205128204\n",
      "Valid F1 Score: 0.7699680511182109\n"
     ]
    }
   ],
   "source": [
    "def my_LSTM(embedding_layer):\n",
    "    print('Creating model...')\n",
    "    model = Sequential()\n",
    "    model.add(embedding_layer)\n",
    "    model.add(Dropout(0.4))\n",
    "    model.add(Bidirectional(LSTM(units=64, dropout=0.1,  recurrent_dropout=0.1)))\n",
    "    model.add(Dense(50, kernel_regularizer=regularizers.l2(0.001), activation=\"relu\"))\n",
    "    model.add(Dropout(0.1))\n",
    "    model.add(Dense(1, activation = \"sigmoid\"))\n",
    "\n",
    "    print('Compiling...')\n",
    "    model.compile(loss='binary_crossentropy',\n",
    "                  optimizer='adam',\n",
    "                  metrics=[\"accuracy\"])\n",
    "    return model\n",
    "\n",
    "# training a single LSTM model\n",
    "X_train, X_valid, y_train, y_valid = train_test_split(X_padded, y, test_size=.3, shuffle=True, random_state=24)\n",
    "\n",
    "# initializing model\n",
    "clf = my_LSTM(embedding_layer)\n",
    "print(clf.summary())\n",
    "\n",
    "# training model\n",
    "clf.fit(X_train,\n",
    "        y_train,\n",
    "        epochs=n_epochs,\n",
    "        verbose=1)\n",
    "\n",
    "# make predictions\n",
    "y_preds = clf.predict_classes(X_valid, verbose=-1)\n",
    "y_train_preds = clf.predict_classes(X_train, verbose=-1)\n",
    "\n",
    "print(f\"\\n\\nTrain F1 Score: {f1_score(y_train ,y_train_preds)}\\nValid F1 Score: {f1_score(y_valid ,y_preds)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Early Stopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating model...\n",
      "Compiling...\n",
      "Model: \"sequential_2\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "embedding (Embedding)        (None, 202, 300)          5187000   \n",
      "_________________________________________________________________\n",
      "bidirectional_2 (Bidirection (None, 128)               186880    \n",
      "_________________________________________________________________\n",
      "dense_4 (Dense)              (None, 50)                6450      \n",
      "_________________________________________________________________\n",
      "dropout_2 (Dropout)          (None, 50)                0         \n",
      "_________________________________________________________________\n",
      "dense_5 (Dense)              (None, 1)                 51        \n",
      "=================================================================\n",
      "Total params: 5,380,381\n",
      "Trainable params: 193,381\n",
      "Non-trainable params: 5,187,000\n",
      "_________________________________________________________________\n",
      "None\n",
      "Epoch 1/8\n",
      "167/167 [==============================] - 85s 482ms/step - loss: 0.6298 - accuracy: 0.7067\n",
      "Epoch 2/8\n",
      "167/167 [==============================] - 79s 471ms/step - loss: 0.4824 - accuracy: 0.7943\n",
      "Epoch 3/8\n",
      "167/167 [==============================] - 78s 464ms/step - loss: 0.4376 - accuracy: 0.8167\n",
      "Epoch 4/8\n",
      "167/167 [==============================] - 77s 463ms/step - loss: 0.4115 - accuracy: 0.8343\n",
      "Epoch 5/8\n",
      "167/167 [==============================] - 78s 468ms/step - loss: 0.3935 - accuracy: 0.8430\n",
      "Epoch 6/8\n",
      "167/167 [==============================] - 78s 466ms/step - loss: 0.3700 - accuracy: 0.8466\n",
      "Epoch 7/8\n",
      "167/167 [==============================] - 78s 464ms/step - loss: 0.3582 - accuracy: 0.8584\n",
      "Epoch 8/8\n",
      "167/167 [==============================] - 78s 466ms/step - loss: 0.3354 - accuracy: 0.8643\n",
      "\n",
      "\n",
      "Train F1 Score: 0.8649963512527366\n",
      "Valid F1 Score: 0.7525496511003757\n"
     ]
    }
   ],
   "source": [
    "def my_LSTM(embedding_layer):\n",
    "    print('Creating model...')\n",
    "    model = Sequential()\n",
    "    model.add(embedding_layer)\n",
    "    model.add(Bidirectional(LSTM(units=64, dropout=0.1,  recurrent_dropout=0.1)))\n",
    "    model.add(Dense(50, kernel_regularizer=regularizers.l2(0.001), activation=\"relu\"))\n",
    "    model.add(Dropout(0.1))\n",
    "    model.add(Dense(1, activation = \"sigmoid\"))\n",
    "\n",
    "    print('Compiling...')\n",
    "    model.compile(loss='binary_crossentropy',\n",
    "                  optimizer='adam',\n",
    "                  metrics=[\"accuracy\"])\n",
    "    return model\n",
    "\n",
    "# training a single LSTM model\n",
    "X_train, X_valid, y_train, y_valid = train_test_split(X_padded, y, test_size=.3, shuffle=True, random_state=24)\n",
    "\n",
    "# initializing model\n",
    "clf = my_LSTM(embedding_layer)\n",
    "print(clf.summary())\n",
    "\n",
    "# initializing early stopping \n",
    "early_stopping = EarlyStopping(monitor='loss', patience=3)\n",
    "\n",
    "# training model\n",
    "clf.fit(X_train,\n",
    "        y_train,\n",
    "        epochs=n_epochs,\n",
    "        callbacks=[early_stopping],\n",
    "        verbose=1)\n",
    "\n",
    "# make predictions\n",
    "y_preds = clf.predict_classes(X_valid, verbose=-1)\n",
    "y_train_preds = clf.predict_classes(X_train, verbose=-1)\n",
    "\n",
    "print(f\"\\n\\nTrain F1 Score: {f1_score(y_train ,y_train_preds)}\\nValid F1 Score: {f1_score(y_valid ,y_preds)}\")"
   ]
  }
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